http://2012.igem.org/wiki/index.php?title=Special:Contributions&feed=atom&limit=50&target=Ychoo2012.igem.org - User contributions [en]2024-03-29T06:49:42ZFrom 2012.igem.orgMediaWiki 1.16.0http://2012.igem.org/JamboreesJamborees2012-11-11T21:51:58Z<p>Ychoo: </p>
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<p>For iGEM 2012, teams will participate in a two-tiered competition. Regional Jamborees will be held in October and the World Championship Jamboree will be held on the first weekend of November. There will be five Regions for iGEM 2012.</p><br />
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<p>All teams must attend and present their projects at their Regional Jamboree and a percentage of teams from each Regional Jamboree will advance to the World Championship.</p><br />
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<br />
<div style="border: 2px solid #00925f; width: 600px; padding: 5px; margin-left: 25px;"><br />
<ul><br />
<lh style="font-weight:bold;">iGEM 2012 Jamboree Schedule:</lh><br />
<li><a href="https://2012.igem.org/Regions/Asia/Jamboree">Asia Regional Jamboree</a>: October 5-7, HKUST, Hong Kong</li><br />
<li><a href="https://2012.igem.org/Regions/Europe/Jamboree">Europe Regional Jamboree</a>: October 5-7, Vrije University, Amsterdam, Netherlands</li><br />
<li><a href="https://2012.igem.org/Regions/Latin_America/Jamboree">Latin America Regional Jamboree</a>: October 5-7, Universidad de los Andes, Bogota, Colombia</li><br />
<li><a href="https://2012.igem.org/Regions/Americas_East/Jamboree">Americas East Regional Jamboree</a>: October 12-14, IBE, Pittsburgh</li><br />
<li><a href="https://2012.igem.org/Regions/Americas_West/Jamboree">Americas West Regional Jamboree</a>: October 12-14, Stanford University, Palo Alto</li><br />
<hr><br />
<li><a href="https://2012.igem.org/World_Championship_Jamboree">World Championship Jamboree</a>: November 2-5, Stata Center, Cambridge, MA</li><br />
</ul><br />
</div><br />
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<br />
<div class="region"><br />
<div class="title"><br />
<a name="World Championship"></a>World Championship Results<br />
</div><br />
<br />
<div id="sidebar"><br />
<br />
<div id="highlight_box"><br />
<h3 style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;"> <a class="quick_link" href="https://2012.igem.org/World_Championship_Jamboree">iGEM 2012 World Championship Jamboree</a></h3><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center; font-weight:bold;">November 2-5, 2012</p><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;">Cambridge, USA</p><br />
<ul style="list-style:none;" ><br />
<lh style="font-size:110%; font-weight:bold; color:#576f91;">Quick links:</lh><br />
<li><a class="quick_link" href="https://igem.org/Team_Wikis?year=2012">Team websites</a></li><br />
<li><a class="quick_link" href="https://igem.org/Results?year=2012&region=Championship&division=igem">iGEM 2012 Jamboree results</a></li><br />
</ul><br />
</div><br />
<br />
<div class="photo"><a href="http://www.flickr.com/photos/igemhq/8094104418/in/photostream"><img style="width: 400px;" src="https://static.igem.org/mediawiki/igem.org/7/7e/2012-iGEM-from-Above.png"></a></div><br />
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</div> <!-- End SIDEBAR div --><br />
<br />
<div id="results"><br />
<div id="regional_winner"><br />
<div class="award_name">Grand Prize Winner:</div><br />
<div class="team_name"><a href="https://2012.igem.org/Team:Groningen">Groningen</a></div><br />
<div class="award_name">1st Runner Up:</div><br />
<div class="team_name"><a href="https://2012.igem.org/Team:Slovenia">Slovenia</a></div><br />
<div class="award_name">2nd Runner Up:</div><br />
<div class="team_name"><a href="https://2012.igem.org/Team:Paris_Bettencourt">Paris Bettencourt</a></div><br />
</div><br />
<br />
<div id="finalists"><br />
<div class="award_name">Finalists:</div><br />
<div class="team_name">Groningen</div><br />
<div class="team_name">LMU-Munich</div><br />
<div class="team_name">Paris Bettencourt</div><br />
<div class="team_name">Slovenia</div><br />
</div><br />
<br />
<div id="igemers"><br />
<div class="award_name">iGEMer's Prize:</div><br />
<div class="team_name">Groningen</div><br />
</div><br />
<br />
<div id="advancing_teams_names">Sweet Sixteen:</div><br />
<div id="advancing_teams"><br />
<div class="team_name">Bielefeld-Germany</div><br />
<div class="team_name">Calgary</div><br />
<div class="team_name">Carnegie Mellon</div><br />
<div class="team_name">Cornell</div><br />
<div class="team_name">Freiburg</div><br />
<div class="team_name">Groningen</div><br />
<div class="team_name">LMU-Munich</div><br />
<div class="team_name">Paris Bettencourt</div><br />
</div><br />
<div id="advancing_teams"><br />
<div class="team_name">Penn</div><br />
<div class="team_name">SJTU-BioX-Shanghai</div><br />
<div class="team_name">Slovenia</div><br />
<div class="team_name">Stanford-Brown</div><br />
<div class="team_name">TU Munich</div><br />
<div class="team_name">UNITN-Trento</div><br />
<div class="team_name">University College London</div><br />
<div class="team_name">Wageningen</div><br />
</div><br />
<br />
<div style="clear: both;"></div><br />
<br><br />
<br />
<div id="advancing_teams"><br />
<div class="award_name">Best Foundational Advance Project:</div><br />
<div class="team_name">Carnegie Mellon</div><br />
<div class="award_name">Best Health & Medicine Project:</div><br />
<div class="team_name">Slovenia</div><br />
<div class="award_name">Best New Application Project:</div><br />
<div class="team_name">LMU-Munich</div><br />
<div class="award_name">Best Food & Energy Project:</div><br />
<div class="team_name">Groningen</div><br />
<div class="award_name">Best Environment Project:</div><br />
<div class="team_name">Paris Bettencourt</div><br />
<div class="award_name">Best Information Processing Project:</div><br />
<div class="team_name">Tokyo Tech</div><br />
<div class="award_name">Best Manufacturing Project:</div><br />
<div class="team_name">Utah State</div><br />
<div class="award_name">Best Poster:</div><br />
<div class="team_name">Groningen</div><br />
<div class="award_name">Best Human Practices Advance:</div><br />
<div class="team_name">Calgary</div><br />
<div class="award_name">Best Model:</div><br />
<div class="team_name">Slovenia</div><br />
<div class="award_name">Best Presentation</div><br />
<div class="team_name"><small>(Tie)</small> Groningen & University College London</div><br />
<div class="award_name">Best Wiki</div><br />
<div class="team_name"><small>(Tie)</small> LMU-Munich & Slovenia</div><br />
</div><br />
<br />
<div id="finalists"><br />
<div class="award_name"></div><br />
<div class="award_name">Best Software Tools Project:</div><br />
<div class="team_name"><small>(Tie)</small> Johns Hopkins-Software & USTC-Software</div><br />
<div class="award_name">Best SBOL-Based Tool:</div><br />
<div class="team_name"><small>(Tie)</small> Wellesley HCI & Johns Hopkins-Software</div><br />
<div class="award_name">Best Interaction with the Parts Registry:</div><br />
<div class="team_name">UT-Tokyo-Software</div><br />
<div class="award_name">Best Clotho App:</div><br />
<div class="team_name">SYSU-Software</div><br />
<div class="award_name">Best Genome Compiler-Based Design:</div><br />
<div class="team_name">SYSU-Software</div><br />
<div class="award_name">Best Eugene-Based Design:</div><br />
<div class="team_name">Wellesley HCI</div><br />
<div class="award_name">Best Requirements Engineering:</div><br />
<div class="team_name">Wellesley HCI</div><br />
</div><br><br><br />
<br />
<div id="finalists"><br />
<div class="award_name">Best Entrepreneurship Project:</div><br />
<div class="team_name">Alberta-North-RBI E</div><br />
<div class="award_name">Best Business Model Process Analysis:</div><br />
<div class="team_name">UTPreneur</div><br />
</div><br />
<br />
</div> <!-- End Region Div (World Championship Jamboree) --><br />
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<br />
<div class="region"><br />
<div class="title"><br />
<a name="Americas_West"></a>Americas West Results<br />
</div><br />
<br />
<div id="sidebar"><br />
<br />
<div id="highlight_box"><br />
<h3 style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;"> <a class="quick_link" href="https://2012.igem.org/Regions/Americas_West/Jamboree">iGEM 2012 Regional Jamboree: Americas West</a></h3><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center; font-weight:bold;">October 12 - 14, 2012</p><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;">Palo Alto, USA</p><br />
<ul style="list-style:none;" ><br />
<lh style="font-size:110%; font-weight:bold; color:#576f91;">Quick links:</lh><br />
<li><a class="quick_link" href="https://igem.org/Team_Wikis?year=2012">Team websites</a></li><br />
<li><a class="quick_link" href="https://igem.org/Results?year=2012&division=igem&region=Americas_West">iGEM 2012 Jamboree results</a></li><br />
</ul><br />
</div><br />
<br />
<div class="photo"><a href="http://www.flickr.com/photos/igemhq/8094104418/in/photostream"><img style="width: 400px;" src="https://static.igem.org/mediawiki/2012/3/33/2012RJ-Americas-West-from-Above.png"></a></div><br />
<br />
</div> <!-- End SIDEBAR div --><br />
<br />
<div id="results"><br />
<div id="regional_winner"><br />
<div class="award_name">Regional Winner:</div><br />
<div class="team_name">Berkeley</div><br />
</div><br />
<br />
<div id="finalists"><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Berkeley</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Calgary</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Utah State</div><br />
</div><br />
<br />
<div id="advancing_teams_names">Advance to World Championship:</div><br />
<div id="advancing_teams"><br />
<div class="team_name">Arizona State</div> <br />
<div class="team_name">Austin Texas</div><br />
<div class="team_name">Berkeley</div><br />
<div class="team_name">Calgary</div><br />
<div class="team_name">Nevada</div><br />
<div class="team_name">Stanford-Brown</div><br />
<div class="team_name">UC Davis</div><br />
<div class="team_name">Utah State</div><br />
</div><br />
</div><br />
</div> <!-- End Region Div (Americas West) --><br />
<br />
<br />
<div class="region"><br />
<div class="title"><br />
<a name="Americas_East"></a>Americas East Results<br />
</div><br />
<br />
<div id="sidebar"><br />
<br />
<div id="highlight_box"><br />
<h3 style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;"> <a class="quick_link" href="https://2012.igem.org/Regions/Americas_East/Jamboree">iGEM 2012 Regional Jamboree: Americas East</a></h3><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center; font-weight:bold;">October 12 - 14, 2012</p><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;">Pittsburgh, USA</p><br />
<ul style="list-style:none;" ><br />
<lh style="font-size:110%; font-weight:bold; color:#576f91;">Quick links:</lh><br />
<li><a class="quick_link" href="https://igem.org/Team_Wikis?year=2012">Team websites</a></li><br />
<li><a class="quick_link" href="https://igem.org/Results?year=2012&division=igem&region=Americas_East">iGEM 2012 Jamboree results</a></li><br />
</ul><br />
</div><br />
<br />
<div class="photo"><a href="http://www.flickr.com/photos/igemhq/8094100483/in/photostream"><img style="width: 400px;" src="https://static.igem.org/mediawiki/igem.org/3/35/2012_Americas_East_iGEM_From_Above-500px.jpg"></a></div><br />
<br />
</div> <!-- End SIDEBAR div --><br />
<br />
<div id="results"><br />
<div id="regional_winner"><br />
<div class="award_name">Regional Winner:</div><br />
<div class="team_name">Penn</div><br />
</div><br />
<br />
<div id="finalists"><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Carnegie Mellon</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Cornell</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Penn</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Virginia</div><br />
</div><br />
<br />
<div id="advancing_teams_names">Advance to World Championship:</div><br />
<div id="advancing_teams"><br />
<div class="team_name">BostonU</div> <br />
<div class="team_name">Carnegie Mellon</div><br />
<div class="team_name">Cornell</div><br />
<div class="team_name">Michigan</div><br />
<div class="team_name">MIT</div><br />
<div class="team_name">Northwestern</div><br />
<div class="team_name">Penn</div><br />
</div><br />
<br />
<div id="advancing_teams"><br />
<div class="team_name">Penn State</div><br />
<div class="team_name">Purdue</div><br />
<div class="team_name">Queens Canada</div><br />
<div class="team_name">UIUC-Illinois</div><br />
<div class="team_name">Virginia</div><br />
<div class="team_name">Wisconsin-Madison</div><br />
<div class="team_name">Yale</div><br />
</div><br />
<div id="advancing_teams_names" style="clear: left;">Software Teams advancing to Software Jamboree:</div><br />
<div id="advancing_teams"><br />
<div class="team_name">Johns Hopkins-Software</div> <br />
<div class="team_name">Wellesley HCI</div> <br />
</div><br />
</div><br />
<br />
</div> <!-- End Region Div (Americas East) --><br />
<br />
<br />
<br />
<div class="region"><br />
<div class="title"><br />
<a name="Latin_America"></a>Latin America Results<br />
</div><br />
<br />
<div id="sidebar"><br />
<br />
<div id="highlight_box"><br />
<h3 style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;"> <a class="quick_link" href="https://2012.igem.org/Latin_America">iGEM 2012 Regional Jamboree: Latin America</a></h3><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center; font-weight:bold;">October 5 - 7, 2012</p><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;">Bogota, Colombia</p><br />
<ul style="list-style:none;" ><br />
<lh style="font-size:110%; font-weight:bold; color:#576f91;">Quick links:</lh><br />
<li><a class="quick_link" href="https://igem.org/Team_Wikis?year=2012">Team websites</a></li><br />
<li><a class="quick_link" href="https://igem.org/Results?year=2012&division=igem&region=Latin_America">iGEM 2012 Jamboree results</a></li><br />
</ul><br />
</div><br />
<br />
<div class="photo"><a href="http://www.flickr.com/photos/igemhq/8074960538/in/photostream/"><img style="width: 400px;" src="https://static.igem.org/mediawiki/2012/b/bb/2012_Latin_America_iGEM_From_Above.jpg"></a></div><br />
<br />
</div> <!-- End SIDEBAR div --><br />
<br />
<div id="results"><br />
<div id="regional_winner"><br />
<div class="award_name">Regional Winner:</div><br />
<div class="team_name">Colombia</div><br />
</div><br />
<br />
<div id="finalists"><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">CINVESTAV-IPN-UNAM MX</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Colombia</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">UC Chile</div><br />
</div><br />
<br />
<div id="advancing_teams_names">Advance to World Championship:</div><br />
<div id="advancing_teams"><br />
<div class="team_name">Buenos Aires</div><br />
<div class="team_name">CINVESTAV-IPN-UNAM MX</div><br />
<div class="team_name">Colombia</div><br />
<div class="team_name">UC Chile</div><br />
<div class="team_name">UNAM Genomics Mexico</div><br />
</div><br />
<br />
<div id="advancing_teams_names" style="clear: left;">Software Teams advancing to Software Jamboree:</div><br />
<div id="advancing_teams"><br />
<div class="team_name">UTP-Software</div> <br />
</div><br />
</div><br />
<br />
</div> <!-- End Region Div (Latin America) --><br />
<br />
<div class="region"><br />
<div class="title"><br />
<a name="Europe"></a>Europe Results<br />
</div><br />
<br />
<div id="sidebar"><br />
<br />
<div id="highlight_box"><br />
<h3 style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;"> <a class="quick_link" href="https://2012.igem.org/Europe">iGEM 2012 Regional Jamboree: Europe</a></h3><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center; font-weight:bold;">October 5 - 7, 2012</p><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;">Amsterdam, Netherlands</p><br />
<ul style="list-style:none;" ><br />
<lh style="font-size:110%; font-weight:bold; color:#576f91;">Quick links:</lh><br />
<li><a class="quick_link" href="https://igem.org/Team_Wikis?year=2012">Team websites</a></li><br />
<li><a class="quick_link" href="https://igem.org/Results?year=2012&division=igem&region=Europe">iGEM 2012 Jamboree results</a></li><br />
</ul><br />
</div><br />
<br />
<div class="photo"><a href="http://www.flickr.com/photos/igemhq/8074959354/in/photostream/"><img style="width: 400px;" src="https://static.igem.org/mediawiki/2012/4/41/2012_Europe_iGEM_From_Above.jpg"></a></div><br />
<br />
</div> <!-- End SIDEBAR div --><br />
<br />
<div id="results"><br />
<div id="regional_winner"><br />
<div class="award_name">Regional Winner:</div><br />
<div class="team_name">Groningen</div><br />
</div><br />
<br />
<div id="finalists"><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Cambridge</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Groningen</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Slovenia</div><br />
</div><br />
<br />
<div id="advancing_teams_names">Advance to World Championship:</div><br />
<div id="advancing_teams"><br />
<div class="team_name">Bielefeld-Germany</div><br />
<div class="team_name">Cambridge</div><br />
<div class="team_name">Edinburgh </div><br />
<div class="team_name">ETH Zurich</div><br />
<div class="team_name">Evry</div><br />
<div class="team_name">Freiburg</div><br />
<div class="team_name">Groningen</div><br />
<div class="team_name">LMU-Munich</div><br />
<div class="team_name">Lyon-INSA</div><br />
</div><br />
<br />
<div id="advancing_teams"><br />
<div class="team_name">Paris Bettencourt</div><br />
<div class="team_name">Potsdam Bioware</div><br />
<div class="team_name">Slovenia</div><br />
<div class="team_name">Trieste</div><br />
<div class="team_name">TU-Delft</div><br />
<div class="team_name">TU Munich</div><br />
<div class="team_name">UNITN-Trento </div><br />
<div class="team_name">University College London</div><br />
<div class="team_name">Wageningen UR </div><br />
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<a name="Asia"></a>Asia Results<br />
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<h3 style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;"> <a class="quick_link" href="https://2012.igem.org/Asia">iGEM 2012 Regional Jamboree: Asia</a></h3><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center; font-weight:bold;">October 5 - 7, 2012</p><br />
<p style="font-family: Lucida Grande, Verdana, Arial, sans-serif; color:#666; text-align:center;">Hong Kong, Hong Kong</p><br />
<ul style="list-style:none;" ><br />
<lh style="font-size:110%; font-weight:bold; color:#576f91;">Quick links:</lh><br />
<li><a class="quick_link" href="https://igem.org/Team_Wikis?year=2012">Team websites</a></li><br />
<li><a class="quick_link" href="https://igem.org/Results?year=2012&division=igem&region=Asia">iGEM 2012 Jamboree results</a></li><br />
</ul><br />
</div><br />
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<div class="photo"><a href="http://www.flickr.com/photos/igemhq/8074965799/in/photostream"><img style="width: 400px;" src="https://static.igem.org/mediawiki/2012/e/e7/2012_Asia_iGEM_From_Above.jpg"></a></div><br />
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<div id="results"><br />
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<div class="award_name">Regional Winner:</div><br />
<div class="team_name">SJTU-BioX-Shanghai</div><br />
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<div id="finalists"><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Peking</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">SJTU-BioX-Shanghai</div><br />
<div class="award_name">Finalist:</div><br />
<div class="team_name">Tianjin</div><br />
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<div id="advancing_teams_names">Advance to World Championship:</div><br />
<div id="advancing_teams"><br />
<div class="team_name">HKUST-Hong Kong </div> <br />
<div class="team_name">Hong Kong-CUHK</div><br />
<div class="team_name">KAIST Korea</div><br />
<div class="team_name">Kyoto </div><br />
<div class="team_name">Macquarie_Australia</div><br />
<div class="team_name">NCTU Formosa</div><br />
<div class="team_name">NTU-Taida</div><br />
<div class="team_name">NYMU-Taipei </div><br />
<div class="team_name">OUC-China</div><br />
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<div id="advancing_teams"><br />
<div class="team_name">Peking</div><br />
<div class="team_name">SJTU-BioX-Shanghai</div><br />
<div class="team_name">Tianjin</div><br />
<div class="team_name">Tokyo Tech </div><br />
<div class="team_name">Tsinghua-A</div><br />
<div class="team_name">WHU-China</div><br />
<div class="team_name">XMU-China</div><br />
<div class="team_name">ZJU-China</div> <br />
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<div id="advancing_teams_names" style="clear: left;">Software Teams advancing to Software Jamboree:</div><br />
<div id="advancing_teams"><br />
<div class="team_name">CBNU-Korea</div> <br />
<div class="team_name">SUST Shenzhen-A</div> <br />
<div class="team_name">SUST Shenzhen-B</div> <br />
<div class="team_name">SYSU-Software</div> <br />
<div class="team_name">USTC-Software</div> <br />
<div class="team_name">UT-Tokyo-Software</div> <br />
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</html></div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-CircuitTeam:Carnegie Mellon/Hum-Circuit2012-10-27T04:01:17Z<p>Ychoo: </p>
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit">Circuit Kit</a><br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team">Team Presentation</a><br />
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
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<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
<li><a href="#section1-4">1.2 Question 3</a></li><br />
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<h1 id="section1-1">Circuit Kit: Overview </h1><br />
<p><br />
In order to raise awareness, and motivate continued innovation in the field of synthetic biology, our iGEM team took the initiative to design a simple hardware demonstration platform, with which mentors can allow students to interact with a physical model of our project! The platform uses a microcontroller and a collection of simple circuits and components which communicate with a Matlab GUI to demonstrate how the various portions of our BioBricks interact to accomplish our goal. <br><br />
Most importantly, we hope all iGEM teams can take inspiration from our experiences and build similar electric analogs of their BioBricks designs! We've found them to be an amazing tool for engaging high school students and piquing their interest and understanding in Synthetic Biology.<br />
</p><br />
<br />
<br />
<h1 id="section1-2">Microcontrollers 101 </h1><br />
<p><br />
Typically, microcontrollers are general purpose microprocessors which have additional parts that allow them to read, and control external devices. We often use the terms microcontroller and microprocessor interchangeably. <br />
</p><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/6/6f/CMU_Arduino.jpg" height="287" width="287" align="right" alt="Matlab BioBrick GUI"/><br />
<b> Microcontrollers are typically used to: </b> <br />
<li> Gather sensor and component <i>inputs</i>. </li><br />
<li> Process these inputs, in digital format, to determine some <i>output</i> or action. </li><br />
<li> Utilize output devices and/or communication channels to do something useful. </li><br />
<br><br />
<br />
<br />
<p><br />
Why use <i>microcontrollers</i> to help spread synthetic biology awareness? Microcontrollers are a good starting point for teaching students about general input/output systems, which are the primary design focus of synthetic biology: <b>creating biological systems that transform environmental inputs into useful outputs</b>. A basic microcontroller typically includes a microprocessor, digital inputs/outputs, analog inputs/outputs, and some type of communication interface (e.g., serial, wi-fi, bluetooth, etc.). <br />
</p><br />
<br />
<p><br />
Although our kit utilizes an off-the-shelf microcontroller (AtMega328P-PU based Arduino), we additionally designed a simplified version. This allows other collaborators and students to potentially replicate, or modify the project and eventually fabricate their own simplified microcontrollers for use in DIY synthetic biology education. In many senses, the BioBricks being developed through the iGEM foundation essentially function like minute microcontroller systems. It is thus important to identify this similarity, and provide students and future researchers with an opportunity to explore it. <br />
</p><br />
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<br />
<h1 id="section1-3">Simplified Microcontroller </h1><br />
<p>Below is a list of components used in our simplified microcontroller, and an image of the schematic designating the physical connections between the components and the AtMega328P-PU. These connections can initially be wired using a breadboard, which allows students to gain a simplified understanding of what connections are being made in off-the-shelf microcontrollers. If they choose, students can use the provided schematic files to order a PCB of their own from any of a variety of PCB manufacturers. <br />
</p><br />
<br />
<b> Parts List: </b> <br />
<li> AtMega328P-PU: <i>ATMega328P-PU (AVR microcontroller) </i></li><br />
<li> IC2: <i>78L05 (5v Voltage Regulator, 100ma) </i></li><br />
<li> Q1: <i>16MHz Resonator (with internal capacitors) </i> </li><br />
<li> C1: <i>0.1μF Capacitor </i> </li><br />
<li> C2: <i>0.33μF Capacitor </i> </li><br />
<li> C3: <i>0.1μF Capacitor </i> </li><br />
<li> R1: <i>10KΩ Resistor </i> </li><br />
<br><br />
<br />
<b>Simplified Microcontroller Schematic</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a7/Schematic_PCB_MCU.png" height="450" width="650"/><br />
<br><br><br />
<br />
<b>Simplified Microcontroller PCB Layout</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/c/c5/Schematic_PCB_Layout.png" /><br />
<br><br><br />
<p><br />
Follow this <a href="https://www.dropbox.com/sh/nb9cs0gpbvlrpxa/PMXNzM1p7G"> link</a> to download the eagle schematic files. The link also contains a.) tutorial on how to wire up and program the simplified microcontroller on a breadboard from scratch (this should be accomplished prior to pcb manufacture) and b.) parts list for the project enclosure and supporting components.<br />
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<h1 id = "section1-4"> Using the Hardware/Software Platform </h1><br />
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<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
<br />
<br />
<b> General Notes </b><br />
<ol><br />
<li> Use the provided usb cable to connect the platform to a computer. Please do not detach the cable from the kit. </li><br />
<li> The GUI is implemented in Matlab currently, but will also be implemented via an open-source language.</li><br />
<li> Source-code for both implementations will be available via this <a href="https://www.dropbox.com/sh/zeeugv3pt4pgo0l/JkQ47msyeM"> link</a>. </li><br />
</ol><br />
<br><br><br />
<br />
<br />
<b> Overview </b><br><br />
<br />
<p><br />
The kit is comprised of one main BioBrick Unit (containing the programmed microcontroller) with interactive components, and an accompanying Fluorescence Unit which uses LEDs and a photo-resistor to emulate the process of collecting fluorescence microscope data. The LEDs illuminate with variable brightness in response to the user's choice of physical BioBrick configuration. This is roughly analogous to the fluorescence produced by cells illuminating in response to different BioBrick configurations in-vivo. The photo-resistor then emulates the fluorescence microscope by quantifying the light which is emitted by the LEDs. This "microscopy" process is paralleled by a Matlab GUI, which subsequently feeds the fluorescence data to the physical model, described <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> here</a>.<br />
</p><br />
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<br />
<br />
<b> Build a BioBrick </b><br />
<ol><br />
<li> Insert the start-sequence, represented by the first set of 2-pin jumpers on the far left of the main unit. </li><br />
<li>Select a promoter from the 4 provided, and insert each promoter region. </li><br />
<ul><br />
<li> A single promoter is composed of 3 promoter regions, represented by identically-colored resistors. </li><br />
<li> Note the orientation of the components when inserting each region. </li><br />
<li> The top resistor should connect slots 1 & 2. The middle resistor should connect slots 2 & 3. The bottom resistor should connect slots 3 & 4. </li><br />
</ul><br />
<br><br />
<li> Insert the tRNA stabilizer headers (2). </li> <br />
<li> Insert the Spinach sequence (6-pin header). </li><br />
<li> Insert both RBS & FAP sequences. </li><br />
<li> Insert the end-sequence, represented by the final set of 2-pin jumpers. </li><br />
</ol><br />
<br><br><br />
<br />
<br />
<br />
<b> Characterize the Chosen Promoter </b><br />
<ol><br />
<li> Open Matlab, and add the folder with the provided software to the Matlab path.</li><br />
<ul><li> Right click the provided folder, and select "Add to Path -> Selected Folders and Sub-Folders" </li></ul><br />
<li> Type "BioBrick_GUI" at the command prompt, and hit enter. </li><br />
<li> First, populate the time-step input table from top to bottom with the values 10, 20, 30, 40 ,50 </li><br />
<li> Next, hit "Begin Time Lapse" at the top of the GUI: </li><br />
<ul><br />
<li> Note that the software will first sweep through the entire range of all possible fluorescence input levels, and plot the measured fluorescence values. </li><br />
<li> Allow the program to run to completion, populating the output tables. </li><br />
</ul><br />
<br><br />
<li> When the program is finished populating the outputs, hit "Calculate" to display the output values for translational efficiency and transcriptional strength. </li><br />
<li> To export the output tables to the Matlab workspace, select "File" from the menu bar, and choose "Export".</li><br />
<ul><li> This will move the output tables, and calculated values to the workspace. </li></ul><br />
<br><br />
<li> To plot an example comparison of the different promoters over time, enter "plot_data" at the Matlab command prompt. </li><br />
<ul><li> Observe the plot_data.m function if you wish to plot your own data </li></ul><br />
</ol><br />
<br><br><br />
<br />
<br />
<br />
<b> Make a Change and Observe the Effect! </b><br />
<li> Any of the following changes can be made to the BioBrick to help demonstrate the component relationships: </li><br />
<ul><br />
<li> Remove the Spinach sequence, </li><br />
<li> Remove the tRNA stabilizer (one or both components), </li><br />
<li> Remove the RBS sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the FAP sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the START/END sequence, </li><br />
<li> Remove either DFHBI or MG by toggling the switches off (illuminated when 'ON'), </li><br />
<li> …or any combination of the previous. </li><br />
</ul><br />
<br />
<br><br><br />
<br />
<h1 id="section1-1">Pictures and Schematics of the Kit </h1><br />
<br />
<b>BioBrick Circuit Kit</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/9/9a/CMU_BioBrick_Both_Units.jpg" height="300" width="433"/><br />
<br><br><br />
<br />
<b>BioBrick Components</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/1/16/CMU_BioBrick_Components.JPG" height="300" width="433"/><br />
<br><br><br />
<br />
<b>BioBrick Main Unit Circuit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/f/f3/CMU_Circ_Biobrick.png" height="300" width="700"/><br />
<br><br><br />
<br />
<b>BioBrick Fluorescence Unit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_Fluor.png" height="300" width="433"/><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_PhotoR.png" height="300" width="433"/><br />
<br><br><br />
<br />
<br />
<p><br />
To download the more detailed schematic files for your own design, please follow this <a href="https://www.dropbox.com/sh/nb9cs0gpbvlrpxa/PMXNzM1p7G"> link</a>.<br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Mod-ExpandedTeam:Carnegie Mellon/Mod-Expanded2012-10-27T03:58:39Z<p>Ychoo: </p>
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<br />
<h1 id = "section 1-1">Overview</h1><br />
<id = "section1-1"><br />
<p><br />
Our original model was based on the assumption that the T7 RNA polymerase is constitutively expressed and thus that IPTG addition instantaneously “turns on” the expression of the mRNA and FAP (reactions 3-12 in Figure 1). <br />
In this model, reactions 3 - 7 involve mRNA. The T7 RNAP polymerase is not consumed in producing mRNA and mRNA is not consumed in producing the FAP. </p><p><br />
We assumed that the fluorescence signal is proportional to the concentration of the [mRNA-DFHBI]. The proportionality constant K includes factors specific to the fluorimeter settings and K was one of the variable parameters in our fitting algorithm.</p><p><br />
The dosage curve indicated that the dye binding reactions (6, 7 and 10, 11) are not rate-limiting and allowed us to measure the equilibrium constant K<sub>D</sub> for these reactions. K<sub>D</sub> is equal to the ratio of the “off” rate (k<sub>d</sub>) to “on” rate (k<sub>a</sub>). </p><p><br />
The degradation of [dye-mRNA] and [dye-FAP] complexes affects only the biological component of the complex and not the dye. We assumed that the two complexes degrade with the same rate constant, α and β, as their mRNA and FAP unbound counterparts, respectively.</p><br />
<p><br />
The model described above could not lead to good simulations of the time dependence of the fluorescence of the [mRNA-DFHBI] complex. The apparent exponential dependence of the [mRNA-DFHBI] on time could be rationalized if one includes in the model two additional reaction that account for the fact that in the regulatory mechanism the T7 RNA polymerase in the BL21(DE3) cell strain, there is a LacO site upstream of the promoter for the polymerase. We accounted for this process by including reactions 1 and 2 in the Figure 1. Reaction 1 represents the induction of the T7 RNAP by adding a fixed amount of IPTG and reaction 2 represents the degradation of T7 RNAP.<br />
</p><br />
<br />
<p align='center'><br />
<img src='https://static.igem.org/mediawiki/2012/a/af/CMU_modelexpanded.jpg' width='799' height='599'><br />
</p><br />
<p><br />
<strong>Figure 1</strong> The quantities circled in red are measurable or approximated in our model. The only two physical quantities not known are the RNA and protein concentrations. These two can be solved by using a fitting function of the simulation.<br />
<br><br />
<br />
</p><br />
<p><br />
The following system of differential equations represent the chemical reactions in Figure 1.<br> <br />
<img src="https://static.igem.org/mediawiki/2012/8/89/CMUDifferentials.jpg"><br><br />
<strong>Figure 2</strong><br />
<br />
K<sub>D</sub>'s were taken from the original papers Szent-Gyorgi et al. and Paige et al.<br />
</p><br />
<p><br />
The initial concentrations of dyes and IPTG are known. The [IPTG] value is constant. k<sub>1</sub> should be determined so that the steady state for T7RNAP is accurate. We implemented these equations in MATLAB using an ODE function and a stochastic simulation approach. <br />
</p><br />
<br />
<br />
<p><br />
For low dye concentration, the fluorescence increases until all the dye is bound. One can take advantage of this property in a titration experiment to determine the maximum concentration of RNA or protein produced by the cell. <br />
</p><br />
<p align='center'><br />
<strong>All dye bound condition (Figure 3):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/5/54/ABDCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/4/44/ADBFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Total.jpg'><br><br />
</p><br />
<p><br />
It can be seen that the MG and DFHBI have been added in an amount to minimize the amount of free protein and RNA. This value can be determined experimentally.<br />
<br/><br />
</p><br />
<br><br />
<p align='center'><br />
<strong>Excess dye condition (Figure 4):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/b/bd/ExcessCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/6/60/ExcessFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/f/fc/ExcessTotal.jpg'><br><br />
</p><p><br />
In this case, the dyes are in excess. This will cause the data to be too high and should be avoided experimentally. <br />
</p><br />
<p align='center'><br />
<strong>Limited Dye Added (Figure 5):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Cell.jpg'><br><br />
</p><p><br />
In this case, MG isn't added in enough quantities. As it can be seen, the bound quantity levels off too soon with a characteristic curve that shows a sharp change in signal to a flat, consistent curve. By running a titration experiment, one can determine the moment when this condition no longer applies (when the protein or RNA binds to the dyes).<br />
</p><br />
<hr \><br />
<font size="2"><br />
<sup>[1]</sup> Szent-Gyorgyi, Christopher, Brigitte A. Schmidt, Yehuda Creeger, Gregory W. Fisher, Kelly L. Zakel, Sally Adler, James A J. Fitzpatrick, Carol A. Woolford, Qi Yan, Kalin V. Vasilev, Peter B. Berget, Marcel P. Bruchez, Jonathan W. Jarvik, and Alan Waggoner. "Fluorogen-activating Single-chain Antibodies for Imaging Cell Surface Proteins." Nature Biotechnology 26.2 (2007): 235-40. Print.<br />
<br \><br />
<sup>[2]</sup> Paige, J. S., K. Y. Wu, and S. R. Jaffrey. "RNA Mimics of Green Fluorescent Protein." Science 333.6042 (2011): 642-46. Print.<br />
</font><br />
</html><br />
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<ul class="toc-sub closed"><br />
<li><a href="#section1-1">Overview</a></li><br />
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<li><a href="#section1-3">Cloning Protocol</a></li><br />
<li><a href="#section1-4">Gel Protocol</a></li><br />
<li><a href="#section1-5">Dosage Curve</a></li><br />
<li><a href="#section1-6">Time Lapse Protocol</a></li><br />
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<br />
<h1 id = "section 1-1">Overview</h1><br />
<id = "section1-1"><br />
<p><br />
Our original model was based on the assumption that the T7 RNA polymerase is constitutively expressed and thus that IPTG addition instantaneously “turns on” the expression of the mRNA and FAP (reactions 3-12 in Figure 1). <br />
In this model, reactions 3 - 7 involve mRNA. The T7 RNAP polymerase is not consumed in producing mRNA and mRNA is not consumed in producing the FAP. </p><p><br />
We assumed that the fluorescence signal is proportional to the concentration of the [mRNA-DFHBI]. The proportionality constant K includes factors specific to the fluorimeter settings and K was one of the variable parameters in our fitting algorithm.</p><p><br />
The dosage curve indicated that the dye binding reactions (6, 7 and 10, 11) are not rate-limiting and allowed us to measure the equilibrium constant K<sub>D</sub> for these reactions. K<sub>D</sub> is equal to the ratio of the “off” rate (k<sub>d</sub>) to “on” rate (k<sub>a</sub>). </p><p><br />
The degradation of [dye-mRNA] and [dye-FAP] complexes affects only the biological component of the complex and not the dye. We assumed that the two complexes degrade with the same rate constant, α and β, as their mRNA and FAP unbound counterparts, respectively.</p><br />
<p><br />
The model described above could not lead to good simulations of the time dependence of the fluorescence of the [mRNA-DFHBI] complex. The apparent exponential dependence of the [mRNA-DFHBI] on time could be rationalized if one includes in the model two additional reaction that account for the fact that in the regulatory mechanism the T7 RNA polymerase in the BL21(DE3) cell strain, there is a LacO site upstream of the promoter for the polymerase. We accounted for this process by including reactions 1 and 2 in the Figure 1. Reaction 1 represents the induction of the T7 RNAP by adding a fixed amount of IPTG and reaction 2 represents the degradation of T7 RNAP.<br />
</p><br />
<p align='center'><br />
<img src='https://static.igem.org/mediawiki/2012/a/af/CMU_modelexpanded.jpg' width='799' height='599'><br><br />
</p><br />
<p><br />
<strong>Figure 1</strong> The quantities circled in red are measurable or approximated in our model. The only two physical quantities not known are the RNA and protein concentrations. These two can be solved by using a fitting function of the simulation.<br />
<br><br />
<br />
</p><br />
<p><br />
The following system of differential equations represent the chemical reactions in Figure 1.<br> <br />
<img src="https://static.igem.org/mediawiki/2012/8/89/CMUDifferentials.jpg"><br><br />
<strong>Figure 2</strong><br />
<br />
K<sub>D</sub>'s were taken from the original papers Szent-Gyorgi et al. and Paige et al.<br />
</p><br />
<p><br />
The initial concentrations of dyes and IPTG are known. The [IPTG] value is constant. k<sub>1</sub> should be determined so that the steady state for T7RNAP is accurate. We implemented these equations in MATLAB using an ODE function and a stochastic simulation approach. <br />
</p><br />
<br />
<br />
<p><br />
For low dye concentration, the fluorescence increases until all the dye is bound. One can take advantage of this property in a titration experiment to determine the maximum concentration of RNA or protein produced by the cell. <br />
</p><br />
<p align='center'><br />
<strong>All dye bound condition (Figure 3):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/5/54/ABDCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/4/44/ADBFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Total.jpg'><br><br />
</p><br />
<p><br />
It can be seen that the MG and DFHBI have been added in an amount to minimize the amount of free protein and RNA. This value can be determined experimentally.<br />
<br/><br />
</p><br />
<br><br />
<p align='center'><br />
<strong>Excess dye condition (Figure 4):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/b/bd/ExcessCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/6/60/ExcessFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/f/fc/ExcessTotal.jpg'><br><br />
</p><p><br />
In this case, the dyes are in excess. This will cause the data to be too high and should be avoided experimentally. <br />
</p><br />
<p align='center'><br />
<strong>Limited Dye Added (Figure 5):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Cell.jpg'><br><br />
</p><p><br />
In this case, MG isn't added in enough quantities. As it can be seen, the bound quantity levels off too soon with a characteristic curve that shows a sharp change in signal to a flat, consistent curve. By running a titration experiment, one can determine the moment when this condition no longer applies (when the protein or RNA binds to the dyes).<br />
</p><br />
<hr \><br />
<font size="2"><br />
<sup>[1]</sup> Szent-Gyorgyi, Christopher, Brigitte A. Schmidt, Yehuda Creeger, Gregory W. Fisher, Kelly L. Zakel, Sally Adler, James A J. Fitzpatrick, Carol A. Woolford, Qi Yan, Kalin V. Vasilev, Peter B. Berget, Marcel P. Bruchez, Jonathan W. Jarvik, and Alan Waggoner. "Fluorogen-activating Single-chain Antibodies for Imaging Cell Surface Proteins." Nature Biotechnology 26.2 (2007): 235-40. Print.<br />
<br \><br />
<sup>[2]</sup> Paige, J. S., K. Y. Wu, and S. R. Jaffrey. "RNA Mimics of Green Fluorescent Protein." Science 333.6042 (2011): 642-46. Print.<br />
</font><br />
</html><br />
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<br />
<h1 id = "section 1-1">Overview</h1><br />
<id = "section1-1"><br />
<p><br />
Our original model was based on the assumption that the T7 RNA polymerase is constitutively expressed and thus that IPTG addition instantaneously “turns on” the expression of the mRNA and FAP (reactions 3-12 in Figure 1). <br />
In this model, reactions 3 - 7 involve mRNA. The T7 RNAP polymerase is not consumed in producing mRNA and mRNA is not consumed in producing the FAP. </p><p><br />
We assumed that the fluorescence signal is proportional to the concentration of the [mRNA-DFHBI]. The proportionality constant K includes factors specific to the fluorimeter settings and K was one of the variable parameters in our fitting algorithm.</p><p><br />
The dosage curve indicated that the dye binding reactions (6, 7 and 10, 11) are not rate-limiting and allowed us to measure the equilibrium constant K<sub>D</sub> for these reactions. K<sub>D</sub> is equal to the ratio of the “off” rate (k<sub>d</sub>) to “on” rate (k<sub>a</sub>). </p><p><br />
The degradation of [dye-mRNA] and [dye-FAP] complexes affects only the biological component of the complex and not the dye. We assumed that the two complexes degrade with the same rate constant, α and β, as their mRNA and FAP unbound counterparts, respectively.</p><br />
<p><br />
The model described above could not lead to good simulations of the time dependence of the fluorescence of the [mRNA-DFHBI] complex. The apparent exponential dependence of the [mRNA-DFHBI] on time could be rationalized if one includes in the model two additional reaction that account for the fact that in the regulatory mechanism the T7 RNA polymerase in the BL21(DE3) cell strain, there is a LacO site upstream of the promoter for the polymerase. We accounted for this process by including reactions 1 and 2 in the Figure 1. Reaction 1 represents the induction of the T7 RNAP by adding a fixed amount of IPTG and reaction 2 represents the degradation of T7 RNAP.<br />
</p><br />
<p align='center'><br />
<img src='https://static.igem.org/mediawiki/2012/a/af/CMU_modelexpanded.jpg' width='799' height='599'><br><br />
</p><br />
<p><br />
<strong>Figure 1</strong> The quantities circled in red are measurable or approximated in our model. The only two physical quantities not known are the RNA and protein concentrations. These two can be solved by using a fitting function of the simulation.<br />
<br><br />
<br />
</p><br />
<p><br />
The following system of differential equations represent the chemical reactions in Figure 1.<br> <br />
<img src="https://static.igem.org/mediawiki/2012/8/89/CMUDifferentials.jpg"><br><br />
<strong>Figure 2</strong><br />
<br />
K<sub>D</sub>'s were taken from the original papers Szent-Gyorgi et al. and Paige et al.<br />
</p><br />
<p><br />
The initial concentrations of dyes and IPTG are known. The [IPTG] value is constant. k<sub>1</sub> should be determined so that the steady state for T7RNAP is accurate. We implemented these equations in MATLAB using an ODE function and a stochastic simulation approach. <br />
</p><br />
<br />
<br />
<p><br />
For low dye concentration, the fluorescence increases until all the dye is bound. One can take advantage of this property in a titration experiment to determine the maximum concentration of RNA or protein produced by the cell. <br />
</p><br />
<p align='center'><br />
<strong>All dye bound condition (Figure 3):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/5/54/ABDCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/4/44/ADBFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Total.jpg'><br><br />
It can be seen that the MG and DFHBI have been added in an amount to minimize the amount of free protein and RNA. This value can be determined experimentally.<br />
<br/><br />
</p><br><br />
<p align='center'><br />
<strong>Excess dye condition (Figure 4):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/b/bd/ExcessCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/6/60/ExcessFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/f/fc/ExcessTotal.jpg'><br><br />
In this case, the dyes are in excess. This will cause the data to be too high and should be avoided experimentally. <br />
</p><br />
<p align='center'><br />
<strong>Limited Dye Added (Figure 5):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Cell.jpg'><br><br />
In this case, MG isn't added in enough quantities. As it can be seen, the bound quantity levels off too soon with a characteristic curve that shows a sharp change in signal to a flat, consistent curve. By running a titration experiment, one can determine the moment when this condition no longer applies (when the protein or RNA binds to the dyes).<br />
</p><br />
<hr \><br />
<font size="2"><br />
<sup>[1]</sup> Szent-Gyorgyi, Christopher, Brigitte A. Schmidt, Yehuda Creeger, Gregory W. Fisher, Kelly L. Zakel, Sally Adler, James A J. Fitzpatrick, Carol A. Woolford, Qi Yan, Kalin V. Vasilev, Peter B. Berget, Marcel P. Bruchez, Jonathan W. Jarvik, and Alan Waggoner. "Fluorogen-activating Single-chain Antibodies for Imaging Cell Surface Proteins." Nature Biotechnology 26.2 (2007): 235-40. Print.<br />
<br \><br />
<sup>[2]</sup> Paige, J. S., K. Y. Wu, and S. R. Jaffrey. "RNA Mimics of Green Fluorescent Protein." Science 333.6042 (2011): 642-46. Print.<br />
</font><br />
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<ul class="toc-sub closed"><br />
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<li><a href="#section1-3">Cloning Protocol</a></li><br />
<li><a href="#section1-4">Gel Protocol</a></li><br />
<li><a href="#section1-5">Dosage Curve</a></li><br />
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<br />
<h1 id = "section 1-1">Overview</h1><br />
<id = "section1-1"><br />
<p><br />
Our original model was based on the assumption that the T7 RNA polymerase is constitutively expressed and thus that IPTG addition instantaneously “turns on” the expression of the mRNA and FAP (reactions 3-12 in Figure 1). <br />
In this model, reactions 3 - 7 involve mRNA. The T7 RNAP polymerase is not consumed in producing mRNA and mRNA is not consumed in producing the FAP. </p><p><br />
We assumed that the fluorescence signal is proportional to the concentration of the [mRNA-DFHBI]. The proportionality constant K includes factors specific to the fluorimeter settings and K was one of the variable parameters in our fitting algorithm.</p><p><br />
The dosage curve indicated that the dye binding reactions (6, 7 and 10, 11) are not rate-limiting and allowed us to measure the equilibrium constant K<sub>D</sub> for these reactions. K<sub>D</sub> is equal to the ratio of the “off” rate (k<sub>d</sub>) to “on” rate (k<sub>a</sub>). </p><p><br />
The degradation of [dye-mRNA] and [dye-FAP] complexes affects only the biological component of the complex and not the dye. We assumed that the two complexes degrade with the same rate constant, α and β, as their mRNA and FAP unbound counterparts, respectively.</p><br />
<p><br />
The model described above could not lead to good simulations of the time dependence of the fluorescence of the [mRNA-DFHBI] complex. The apparent exponential dependence of the [mRNA-DFHBI] on time could be rationalized if one includes in the model two additional reaction that account for the fact that in the regulatory mechanism the T7 RNA polymerase in the BL21(DE3) cell strain, there is a LacO site upstream of the promoter for the polymerase. We accounted for this process by including reactions 1 and 2 in the Figure 1. Reaction 1 represents the induction of the T7 RNAP by adding a fixed amount of IPTG and reaction 2 represents the degradation of T7 RNAP.<br />
</p><br />
<p align='center'><br />
<img src='https://static.igem.org/mediawiki/2012/a/af/CMU_modelexpanded.jpg' width='799' height='599'><br><br />
</p><br />
<p><br />
<strong>Figure 1</strong><br><br />
<br />
The quantities circled in red are measurable or approximated in our model. The only two physical quantities not known are the RNA and protein concentrations. These two can be solved by using a fitting function of the simulation.<br />
<br><br />
<br />
</p><br />
<p><br />
The following system of differential equations represent the chemical reactions in Figure 1.<br> <br />
<img src="https://static.igem.org/mediawiki/2012/8/89/CMUDifferentials.jpg"><br><br />
<strong>Figure 2</strong><br />
<br />
K<sub>D</sub>'s were taken from the original papers Szent-Gyorgi et al. and Paige et al.<br />
</p><br />
<p><br />
The initial concentrations of dyes and IPTG are known. The [IPTG] value is constant. k<sub>1</sub> should be determined so that the steady state for T7RNAP is accurate. We implemented these equations in MATLAB using an ODE function and a stochastic simulation approach. <br />
</p><br />
<br />
<br />
<p><br />
For low dye concentration, the fluorescence increases until all the dye is bound. One can take advantage of this property in a titration experiment to determine the maximum concentration of RNA or protein produced by the cell. <br />
</p><br />
<p align='center'><br />
<strong>All dye bound condition (Figure 3):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/5/54/ABDCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/4/44/ADBFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Total.jpg'><br><br />
It can be seen that the MG and DFHBI have been added in an amount to minimize the amount of free protein and RNA. This value can be determined experimentally.<br />
<br/><br />
</p><br><br />
<p align='center'><br />
<strong>Excess dye condition (Figure 4):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/b/bd/ExcessCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/6/60/ExcessFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/f/fc/ExcessTotal.jpg'><br><br />
In this case, the dyes are in excess. This will cause the data to be too high and should be avoided experimentally. <br />
</p><br />
<p align='center'><br />
<strong>Limited Dye Added (Figure 5):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Cell.jpg'><br><br />
In this case, MG isn't added in enough quantities. As it can be seen, the bound quantity levels off too soon with a characteristic curve that shows a sharp change in signal to a flat, consistent curve. By running a titration experiment, one can determine the moment when this condition no longer applies (when the protein or RNA binds to the dyes).<br />
</p><br />
<hr \><br />
<font size="2"><br />
<sup>[1]</sup> Szent-Gyorgyi, Christopher, Brigitte A. Schmidt, Yehuda Creeger, Gregory W. Fisher, Kelly L. Zakel, Sally Adler, James A J. Fitzpatrick, Carol A. Woolford, Qi Yan, Kalin V. Vasilev, Peter B. Berget, Marcel P. Bruchez, Jonathan W. Jarvik, and Alan Waggoner. "Fluorogen-activating Single-chain Antibodies for Imaging Cell Surface Proteins." Nature Biotechnology 26.2 (2007): 235-40. Print.<br />
<br \><br />
<sup>[2]</sup> Paige, J. S., K. Y. Wu, and S. R. Jaffrey. "RNA Mimics of Green Fluorescent Protein." Science 333.6042 (2011): 642-46. Print.<br />
</font><br />
</html><br />
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<h1 id = "section 1-1">Overview</h1><br />
<id = "section1-1"><br />
<p><br />
Our original model was based on the assumption that the T7 RNA polymerase is constitutively expressed and thus that IPTG addition instantaneously “turns on” the expression of the mRNA and FAP (reactions 3-12 in Figure 1). <br />
In this model, reactions 3 - 7 involve mRNA. The T7 RNAP polymerase is not consumed in producing mRNA and mRNA is not consumed in producing the FAP. </p><p><br />
We assumed that the fluorescence signal is proportional to the concentration of the [mRNA-DFHBI]. The proportionality constant K includes factors specific to the fluorimeter settings and K was one of the variable parameters in our fitting algorithm.</p><p><br />
The dosage curve indicated that the dye binding reactions (6, 7 and 10, 11) are not rate-limiting and allowed us to measure the equilibrium constant K<sub>D</sub> for these reactions. K<sub>D</sub> is equal to the ratio of the “off” rate (k<sub>d</sub>) to “on” rate (k<sub>a</sub>). </p><p><br />
The degradation of [dye-mRNA] and [dye-FAP] complexes affects only the biological component of the complex and not the dye. We assumed that the two complexes degrade with the same rate constant, α and β, as their mRNA and FAP unbound counterparts, respectively.</p><br />
<p><br />
The model described above could not lead to good simulations of the time dependence of the fluorescence of the [mRNA-DFHBI] complex. The apparent exponential dependence of the [mRNA-DFHBI] on time could be rationalized if one includes in the model two additional reaction that account for the fact that in the regulatory mechanism the T7 RNA polymerase in the BL21(DE3) cell strain, there is a LacO site upstream of the promoter for the polymerase. We accounted for this process by including reactions 1 and 2 in the Figure 1. Reaction 1 represents the induction of the T7 RNAP by adding a fixed amount of IPTG and reaction 2 represents the degradation of T7 RNAP.<br />
</p><br />
<p align='center'><br />
<img src='https://static.igem.org/mediawiki/2012/a/af/CMU_modelexpanded.jpg' width='799' height='599'><br><br />
<strong>Figure 3</strong><br><br />
The quantities circled in red are measurable or approximated in our model. The only two physical quantities not known are the RNA and protein concentrations. These two can be solved by using a fitting function of the simulation.<br />
<br><br />
<br />
</p><br />
<p><br />
The following system of differential equations represent the chemical reactions in Figure 1.<br> <br />
<img src="https://static.igem.org/mediawiki/2012/8/89/CMUDifferentials.jpg"><br><br />
<strong>Figure 2</strong><br />
<br />
K<sub>D</sub>'s were taken from the original papers Szent-Gyorgi et al. and Paige et al.<br />
</p><br />
<p><br />
The initial concentrations of dyes and IPTG are known. The [IPTG] value is constant. k<sub>1</sub> should be determined so that the steady state for T7RNAP is accurate. We implemented these equations in MATLAB using an ODE function and a stochastic simulation approach. <br />
</p><br />
<br />
<br />
<p><br />
For low dye concentration, the fluorescence increases until all the dye is bound. One can take advantage of this property in a titration experiment to determine the maximum concentration of RNA or protein produced by the cell. <br />
</p><br />
<p align='center'><br />
<strong>All dye bound condition (Figure 4):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/5/54/ABDCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/4/44/ADBFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Total.jpg'><br><br />
It can be seen that the MG and DFHBI have been added in an amount to minimize the amount of free protein and RNA. This value can be determined experimentally.<br />
<br/><br />
</p><br><br />
<p align='center'><br />
<strong>Excess dye condition (Figure 5):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/b/bd/ExcessCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/6/60/ExcessFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/f/fc/ExcessTotal.jpg'><br><br />
In this case, the dyes are in excess. This will cause the data to be too high and should be avoided experimentally. <br />
</p><br />
<p align='center'><br />
<strong>Limited Dye Added (Figure 6):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Cell.jpg'><br><br />
In this case, MG isn't added in enough quantities. As it can be seen, the bound quantity levels off too soon with a characteristic curve that shows a sharp change in signal to a flat, consistent curve. By running a titration experiment, one can determine the moment when this condition no longer applies (when the protein or RNA binds to the dyes).<br />
</p><br />
<hr \><br />
<font size="2"><br />
<sup>[1]</sup> Szent-Gyorgyi, Christopher, Brigitte A. Schmidt, Yehuda Creeger, Gregory W. Fisher, Kelly L. Zakel, Sally Adler, James A J. Fitzpatrick, Carol A. Woolford, Qi Yan, Kalin V. Vasilev, Peter B. Berget, Marcel P. Bruchez, Jonathan W. Jarvik, and Alan Waggoner. "Fluorogen-activating Single-chain Antibodies for Imaging Cell Surface Proteins." Nature Biotechnology 26.2 (2007): 235-40. Print.<br />
<br \><br />
<sup>[2]</sup> Paige, J. S., K. Y. Wu, and S. R. Jaffrey. "RNA Mimics of Green Fluorescent Protein." Science 333.6042 (2011): 642-46. Print.<br />
</font><br />
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The software consists of two parts: model implementation and GUI, both written in Matlab. <br />
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<h1 id="section1-1"> Physical Model</h1><br />
<p><br />
We implemented the model described <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Matlab"> here</a>.<br />
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BioBrick Circuit GUI<br />
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The interface allows users to enter time-step data (e.g., at what time points should images be captured), which populates two tables, displayed in the Matlab GUI. When the user starts the simulated microscopy time lapse, a full sweep of measured vs. actual fluorescence values are plotted for both mRNA and protein. This is essentially plotting the <br />
<br />
<img src="https://static.igem.org/mediawiki/2012/4/4d/CMU_BioBrick_GUI_Screen_Shot.png" height="400" width="405" align="right"/><br />
<br />
quantity of light produced by the LEDs (representing cells) versus the quantity of light detected by the photo-resistor (representing the microscopy). The GUI then iterates through each time-step, plotting a horizontal line with each sweep plot corresponding to the measured fluorescence at that particular time step. The GUI also populates both tables with the actual values as it moves to each next time step.<br />
</p><br />
<br />
<br />
<p><br />
Furthermore, the GUI successfully displays a relevant image of the cells at every timestep. Illuminated fields above the plots indicate which type of fluorescence (mRNA or protein) is currently being populated. When the time lapse is finished, a push-button becomes available which, when clicked, opens a dialog-box displaying and transcriptional strength (<i>Ts</i>) and translational efficiency (<i>Tl</i>). This component calls the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Matlab"> computational function</a> that implements the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Derivations"> model</a>, which computes <i>Ts</i> and <i>Tl</i>.<br />
</p><br />
<p><br />
Finally, a File-Menu dropdown option ('Export') serves to export the table data for both mRNA and protein, as well as the computed values for transcriptional strength and translational efficiency to the local Matlab workspace.<br />
</p><br />
To download the software accompanying the kit, please visit the circuit kit <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> documentation</a>, and scroll down to "General Notes" under the "Using the Hardware/Software Platform" section. <br />
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</ul><br />
</li><br />
<br />
<li style ='width: 193px'><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview">Methods and Results</a><br />
<ul><br />
<li class = 'offset' style ='width: 386px'> <a href="#"></a></li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview">Overview</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Results">Results</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Protocols">Protocols</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Challenges">Challenges</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Notebook">Notebook</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Safety">Safety</a><br />
</li><br />
</ul><br />
</li><br />
<br />
<li style ='width: 193px'><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview">Modeling</a> <br />
<ul><br />
<li class = 'offset' style ='width: 579px'> <a href="#"></a></li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview">Overview</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Derivations">Derivations</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Matlab">Matlab</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Expanded">Expanded</a><br />
</li><br />
</ul> <br />
</li><br />
<br />
<li class="current" style ='width: 193px'><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Human Practices</a><br />
<ul><br />
<li class = 'offset' style ='width: 293px'> <a href="#"></a></li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Overview</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Outreach">Outreach</a><br />
</li><br />
<li class="current"><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit">Circuit Kit</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software">Software</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team">Team Presentation</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Teaching">Teaching Presentation</a><br />
</li><br />
</ul> <br />
</li> <br />
</ul><br />
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
<li><a href="#section1-4">1.2 Question 3</a></li><br />
</ul><br />
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<br />
<h1 id="section1-1">Circuit Kit: Overview </h1><br />
<p><br />
In order to raise awareness, and motivate continued innovation in the field of synthetic biology, our iGEM team took the initiative to design a simple hardware demonstration platform, with which mentors can allow students to interact with a physical model of our project! The platform uses a microcontroller and a collection of simple circuits and components which communicate with a Matlab GUI to demonstrate how the various portions of our BioBricks interact to accomplish our goal. <br><br />
Most importantly, we hope all iGEM teams can take inspiration from our experiences and build similar electric analogs of their BioBricks designs! We've found them to be an amazing tool for engaging high school students and piquing their interest and understanding in Synthetic Biology.<br />
</p><br />
<br />
<br />
<h1 id="section1-2">Microcontrollers 101 </h1><br />
<p><br />
Typically, microcontrollers are general purpose microprocessors which have additional parts that allow them to read, and control external devices. We often use the terms microcontroller and microprocessor interchangeably. <br />
</p><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/6/6f/CMU_Arduino.jpg" height="287" width="287" align="right" alt="Matlab BioBrick GUI"/><br />
<b> Microcontrollers are typically used to: </b> <br />
<li> Gather sensor and component <i>inputs</i>. </li><br />
<li> Process these inputs, in digital format, to determine some <i>output</i> or action. </li><br />
<li> Utilize output devices and/or communication channels to do something useful. </li><br />
<br><br />
<br />
<br />
<p><br />
Why use <i>microcontrollers</i> to help spread synthetic biology awareness? Microcontrollers are a good starting point for teaching students about general input/output systems, which are the primary design focus of synthetic biology: <b>creating biological systems that transform environmental inputs into useful outputs</b>. A basic microcontroller typically includes a microprocessor, digital inputs/outputs, analog inputs/outputs, and some type of communication interface (e.g., serial, wi-fi, bluetooth, etc.). <br />
</p><br />
<br />
<p><br />
Although our kit utilizes an off-the-shelf microcontroller (AtMega328P-PU based Arduino), we additionally designed a simplified version. This allows other collaborators and students to potentially replicate, or modify the project and eventually fabricate their own simplified microcontrollers for use in DIY synthetic biology education. In many senses, the BioBricks being developed through the iGEM foundation essentially function like minute microcontroller systems. It is thus important to identify this similarity, and provide students and future researchers with an opportunity to explore it. <br />
</p><br />
<br />
<br />
<br />
<br />
<br />
<br />
<h1 id="section1-3">Simplified Microcontroller </h1><br />
<p>Below is a list of components used in our simplified microcontroller, and an image of the schematic designating the physical connections between the components and the AtMega328P-PU. These connections can initially be wired using a breadboard, which allows students to gain a simplified understanding of what connections are being made in off-the-shelf microcontrollers. If they choose, students can use the provided schematic files to order a PCB of their own from any of a variety of PCB manufacturers. <br />
</p><br />
<br />
<b> Parts List: </b> <br />
<li> AtMega328P-PU: <i>ATMega328P-PU (AVR microcontroller) </i></li><br />
<li> IC2: <i>78L05 (5v Voltage Regulator, 100ma) </i></li><br />
<li> Q1: <i>16MHz Resonator (with internal capacitors) </i> </li><br />
<li> C1: <i>0.1μF Capacitor </i> </li><br />
<li> C2: <i>0.33μF Capacitor </i> </li><br />
<li> C3: <i>0.1μF Capacitor </i> </li><br />
<li> R1: <i>10KΩ Resistor </i> </li><br />
<br><br />
<br />
<b>Simplified Microcontroller Schematic</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a7/Schematic_PCB_MCU.png" height="450" width="650"/><br />
<br><br><br />
<br />
<b>Simplified Microcontroller PCB Layout</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/c/c5/Schematic_PCB_Layout.png" /><br />
<br><br><br />
<p><br />
Follow this <a href="https://www.dropbox.com/sh/nb9cs0gpbvlrpxa/PMXNzM1p7G"> link</a> to download the eagle schematic files. The link also contains a.) tutorial on how to wire up and program the simplified microcontroller on a breadboard from scratch (this should be accomplished prior to pcb manufacture) and b.) parts list for the project enclosure and supporting components.<br />
<br><br><br />
</p><br />
</section><br />
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<h1 id = "section1-4"> Using the Hardware/Software Platform </h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
<br />
<br />
<b> General Notes </b><br />
<ol><br />
<li> Use the provided usb cable to connect the platform to a computer. Please do not detach the cable from the kit. </li><br />
<li> The GUI is implemented in Matlab currently, but will also be implemented via an open-source language.</li><br />
<li> Source-code for both implementations will be available via this <a href="https://www.dropbox.com/sh/zeeugv3pt4pgo0l/JkQ47msyeM"> link</a>. </li><br />
</ol><br />
<br><br><br />
<br />
<br />
<b> Overview </b><br><br />
<br />
<p><br />
The kit is comprised of one main BioBrick Unit (containing the programmed microcontroller) with interactive components, and an accompanying Fluorescence Unit which uses LEDs and a photo-resistor to emulate the process of collecting fluorescence microscope data. The LEDs illuminate with variable brightness in response to the user's choice of physical BioBrick configuration. This is roughly analogous to the fluorescence produced by cells illuminating in response to different BioBrick configurations in-vivo. The photo-resistor then emulates the fluorescence microscope by quantifying the light which is emitted by the LEDs. This "microscopy" process is paralleled by a Matlab GUI, which subsequently feeds the fluorescence data to the physical model, described <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> here</a>.<br />
</p><br />
<br><br><br />
<br />
<br />
<br />
<b> Build a BioBrick </b><br />
<ol><br />
<li> Insert the start-sequence, represented by the first set of 2-pin jumpers on the far left of the main unit. </li><br />
<li>Select a promoter from the 4 provided, and insert each promoter region. </li><br />
<ul><br />
<li> A single promoter is composed of 3 promoter regions, represented by identically-colored resistors. </li><br />
<li> Note the orientation of the components when inserting each region. </li><br />
<li> The top resistor should connect slots 1 & 2. The middle resistor should connect slots 2 & 3. The bottom resistor should connect slots 3 & 4. </li><br />
</ul><br />
<br><br />
<li> Insert the tRNA stabilizer headers (2). </li> <br />
<li> Insert the Spinach sequence (6-pin header). </li><br />
<li> Insert both RBS & FAP sequences. </li><br />
<li> Insert the end-sequence, represented by the final set of 2-pin jumpers. </li><br />
</ol><br />
<br><br><br />
<br />
<br />
<br />
<b> Characterize the Chosen Promoter </b><br />
<ol><br />
<li> Open Matlab, and add the folder with the provided software to the Matlab path.</li><br />
<ul><li> Right click the provided folder, and select "Add to Path -> Selected Folders and Sub-Folders" </li></ul><br />
<li> Type "BioBrick_GUI" at the command prompt, and hit enter. </li><br />
<li> First, populate the time-step input table from top to bottom with the values 10, 20, 30, 40 ,50 </li><br />
<li> Next, hit "Begin Time Lapse" at the top of the GUI: </li><br />
<ul><br />
<li> Note that the software will first sweep through the entire range of all possible fluorescence input levels, and plot the measured fluorescence values. </li><br />
<li> Allow the program to run to completion, populating the output tables. </li><br />
</ul><br />
<br><br />
<li> When the program is finished populating the outputs, hit "Calculate" to display the output values for translational efficiency and transcriptional strength. </li><br />
<li> To export the output tables to the Matlab workspace, select "File" from the menu bar, and choose "Export".</li><br />
<ul><li> This will move the output tables, and calculated values to the workspace. </li></ul><br />
<br><br />
<li> To plot an example comparison of the different promoters over time, enter "plot_data" at the Matlab command prompt. </li><br />
<ul><li> Observe the plot_data.m function if you wish to plot your own data </li></ul><br />
</ol><br />
<br><br><br />
<br />
<br />
<br />
<b> Make a Change and Observe the Effect! </b><br />
<li> Any of the following changes can be made to the BioBrick to help demonstrate the component relationships: </li><br />
<ul><br />
<li> Remove the Spinach sequence, </li><br />
<li> Remove the tRNA stabilizer (one or both components), </li><br />
<li> Remove the RBS sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the FAP sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the START/END sequence, </li><br />
<li> Remove either DFHBI or MG by toggling the switches off (illuminated when 'ON'), </li><br />
<li> …or any combination of the previous. </li><br />
</ul><br />
<br />
<br><br><br />
<br />
<h1 id="section1-1">Pictures and Schematics of the Kit </h1><br />
<br />
<b>BioBrick Circuit Kit</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/9/9a/CMU_BioBrick_Both_Units.jpg" height="300" width="433"/><br />
<br><br><br />
<br />
<b>BioBrick Components</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/1/16/CMU_BioBrick_Components.JPG" height="300" width="433"/><br />
<br><br><br />
<br />
<b>BioBrick Main Unit Circuit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/f/f3/CMU_Circ_Biobrick.png" height="300" width="700"/><br />
<br><br><br />
<br />
<b>BioBrick Fluorescence Unit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_Fluor.png" height="300" width="433"/><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_PhotoR.png" height="300" width="433"/><br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-CircuitTeam:Carnegie Mellon/Hum-Circuit2012-10-27T03:38:46Z<p>Ychoo: </p>
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
<li><a href="#section1-4">1.2 Question 3</a></li><br />
</ul><br />
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<section id="left"><br />
<header id = "header2"><br />
</p><br />
<br />
<br />
<br />
<h1 id="section1-1">Circuit Kit: Overview </h1><br />
<p><br />
In order to raise awareness, and motivate continued innovation in the field of synthetic biology, our iGEM team took the initiative to design a simple hardware demonstration platform, with which mentors can allow students to interact with a physical model of our project! The platform uses a microcontroller and a collection of simple circuits and components which communicate with a Matlab GUI to demonstrate how the various portions of our BioBricks interact to accomplish our goal. <br><br />
Most importantly, we hope all iGEM teams can take inspiration from our experiences and build similar electric analogs of their BioBricks designs! We've found them to be an amazing tool for engaging high school students and piquing their interest and understanding in Synthetic Biology.<br />
</p><br />
<br />
<br />
<h1 id="section1-2">Microcontrollers 101 </h1><br />
<p><br />
Typically, microcontrollers are general purpose microprocessors which have additional parts that allow them to read, and control external devices. We often use the terms microcontroller and microprocessor interchangeably. <br />
</p><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/6/6f/CMU_Arduino.jpg" height="287" width="287" align="right" alt="Matlab BioBrick GUI"/><br />
<b> Microcontrollers are typically used to: </b> <br />
<li> Gather sensor and component <i>inputs</i>. </li><br />
<li> Process these inputs, in digital format, to determine some <i>output</i> or action. </li><br />
<li> Utilize output devices and/or communication channels to do something useful. </li><br />
<br><br />
<br />
<br />
<p><br />
Why use <i>microcontrollers</i> to help spread synthetic biology awareness? Microcontrollers are a good starting point for teaching students about general input/output systems, which are the primary design focus of synthetic biology: <b>creating biological systems that transform environmental inputs into useful outputs</b>. A basic microcontroller typically includes a microprocessor, digital inputs/outputs, analog inputs/outputs, and some type of communication interface (e.g., serial, wi-fi, bluetooth, etc.). <br />
</p><br />
<br />
<p><br />
Although our kit utilizes an off-the-shelf microcontroller (AtMega328P-PU based Arduino), we additionally designed a simplified version. This allows other collaborators and students to potentially replicate, or modify the project and eventually fabricate their own simplified microcontrollers for use in DIY synthetic biology education. In many senses, the BioBricks being developed through the iGEM foundation essentially function like minute microcontroller systems. It is thus important to identify this similarity, and provide students and future researchers with an opportunity to explore it. <br />
</p><br />
<br />
<br />
<br />
<br />
<br />
<br />
<h1 id="section1-3">Simplified Microcontroller </h1><br />
<p>Below is a list of components used in our simplified microcontroller, and an image of the schematic designating the physical connections between the components and the AtMega328P-PU. These connections can initially be wired using a breadboard, which allows students to gain a simplified understanding of what connections are being made in off-the-shelf microcontrollers. If they choose, students can use the provided schematic files to order a PCB of their own from any of a variety of PCB manufacturers. <br />
</p><br />
<br />
<b> Parts List: </b> <br />
<li> AtMega328P-PU: <i>ATMega328P-PU (AVR microcontroller) </i></li><br />
<li> IC2: <i>78L05 (5v Voltage Regulator, 100ma) </i></li><br />
<li> Q1: <i>16MHz Resonator (with internal capacitors) </i> </li><br />
<li> C1: <i>0.1μF Capacitor </i> </li><br />
<li> C2: <i>0.33μF Capacitor </i> </li><br />
<li> C3: <i>0.1μF Capacitor </i> </li><br />
<li> R1: <i>10KΩ Resistor </i> </li><br />
<br><br />
<br />
<b>Simplified Microcontroller Schematic</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a7/Schematic_PCB_MCU.png" height="450" width="650"/><br />
<br><br><br />
<br />
<b>Simplified Microcontroller PCB Layout</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/c/c5/Schematic_PCB_Layout.png" /><br />
<br><br><br />
<p><br />
Follow this <a href="https://www.dropbox.com/sh/nb9cs0gpbvlrpxa/PMXNzM1p7G"> link</a> to download the eagle schematic files. The link also contains a.) tutorial on how to wire up and program the simplified microcontroller on a breadboard from scratch (this should be accomplished prior to pcb manufacture) and b.) parts list for the project enclosure and supporting components.<br />
<br><br><br />
</p><br />
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<h1 id = "section1-4"> Using the Hardware/Software Platform </h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
<br />
<br />
<b> General Notes </b><br />
<ol><br />
<li> Use the provided usb cable to connect the platform to a computer. Please do not detach the cable from the kit. </li><br />
<li> The GUI is implemented in Matlab currently, but will also be implemented via an open-source language.</li><br />
<li> Source-code for both implementations will be available via this <a href="https://www.dropbox.com/sh/zeeugv3pt4pgo0l/JkQ47msyeM"> link</a>. </li><br />
</ol><br />
<br><br><br />
<br />
<br />
<b> Overview </b><br><br />
<br />
<p><br />
The kit is comprised of one main BioBrick Unit (containing the programmed microcontroller) with interactive components, and an accompanying Fluorescence Unit which uses LEDs and a photo-resistor to emulate the process of collecting fluorescence microscope data. The LEDs illuminate with variable brightness in response to the user's choice of physical BioBrick configuration. This is roughly analogous to the fluorescence produced by cells illuminating in response to different BioBrick configurations in-vivo. The photo-resistor then emulates the fluorescence microscope by quantifying the light which is emitted by the LEDs. This "microscopy" process is paralleled by a Matlab GUI, which subsequently feeds the fluorescence data to the physical model, described <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> here</a>.<br />
</p><br />
<br><br><br />
<br />
<br />
<br />
<b> Build a BioBrick </b><br />
<ol><br />
<li> Insert the start-sequence, represented by the first set of 2-pin jumpers on the far left of the main unit. </li><br />
<li>Select a promoter from the 4 provided, and insert each promoter region. </li><br />
<ul><br />
<li> A single promoter is composed of 3 promoter regions, represented by identically-colored resistors. </li><br />
<li> Note the orientation of the components when inserting each region. </li><br />
<li> The top resistor should connect slots 1 & 2. The middle resistor should connect slots 2 & 3. The bottom resistor should connect slots 3 & 4. </li><br />
</ul><br />
<br><br />
<li> Insert the tRNA stabilizer headers (2). </li> <br />
<li> Insert the Spinach sequence (6-pin header). </li><br />
<li> Insert both RBS & FAP sequences. </li><br />
<li> Insert the end-sequence, represented by the final set of 2-pin jumpers. </li><br />
</ol><br />
<br><br><br />
<br />
<br />
<br />
<b> Characterize the Chosen Promoter </b><br />
<ol><br />
<li> Open Matlab, and add the folder with the provided software to the Matlab path.</li><br />
<ul><li> Right click the provided folder, and select "Add to Path -> Selected Folders and Sub-Folders" </li></ul><br />
<li> Type "BioBrick_GUI" at the command prompt, and hit enter. </li><br />
<li> First, populate the time-step input table from top to bottom with the values 10, 20, 30, 40 ,50 </li><br />
<li> Next, hit "Begin Time Lapse" at the top of the GUI: </li><br />
<ul><br />
<li> Note that the software will first sweep through the entire range of all possible fluorescence input levels, and plot the measured fluorescence values. </li><br />
<li> Allow the program to run to completion, populating the output tables. </li><br />
</ul><br />
<br><br />
<li> When the program is finished populating the outputs, hit "Calculate" to display the output values for translational efficiency and transcriptional strength. </li><br />
<li> To export the output tables to the Matlab workspace, select "File" from the menu bar, and choose "Export".</li><br />
<ul><li> This will move the output tables, and calculated values to the workspace. </li></ul><br />
<br><br />
<li> To plot an example comparison of the different promoters over time, enter "plot_data" at the Matlab command prompt. </li><br />
<ul><li> Observe the plot_data.m function if you wish to plot your own data </li></ul><br />
</ol><br />
<br><br><br />
<br />
<br />
<br />
<b> Make a Change and Observe the Effect! </b><br />
<li> Any of the following changes can be made to the BioBrick to help demonstrate the component relationships: </li><br />
<ul><br />
<li> Remove the Spinach sequence, </li><br />
<li> Remove the tRNA stabilizer (one or both components), </li><br />
<li> Remove the RBS sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the FAP sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the START/END sequence, </li><br />
<li> Remove either DFHBI or MG by toggling the switches off (illuminated when 'ON'), </li><br />
<li> …or any combination of the previous. </li><br />
</ul><br />
<br />
<br><br><br />
<br />
<h1 id="section1-1">Pictures and Schematics of the Kit </h1><br />
<br />
<b>BioBrick Circuit Kit</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/9/9a/CMU_BioBrick_Both_Units.jpg" height="300" width="433"/><br />
<br><br><br />
<br />
<b>BioBrick Components</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/1/16/CMU_BioBrick_Components.JPG" height="300" width="433"/><br />
<br><br><br />
<br />
<b>BioBrick Main Unit Circuit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/f/f3/CMU_Circ_Biobrick.png" height="300" width="700"/><br />
<br><br><br />
<br />
<b>BioBrick Fluorescence Unit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_Fluor.png" height="300" width="433"/><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_PhotoR.png" height="300" width="433"/><br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-CircuitTeam:Carnegie Mellon/Hum-Circuit2012-10-27T03:38:39Z<p>Ychoo: </p>
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
<li><a href="#section1-4">1.2 Question 3</a></li><br />
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<h1 id="section1-1">Circuit Kit: Overview </h1><br />
<p><br />
In order to raise awareness, and motivate continued innovation in the field of synthetic biology, our iGEM team took the initiative to design a simple hardware demonstration platform, with which mentors can allow students to interact with a physical model of our project! The platform uses a microcontroller and a collection of simple circuits and components which communicate with a Matlab GUI to demonstrate how the various portions of our BioBricks interact to accomplish our goal. <br><br />
Most importantly, we hope all iGEM teams can take inspiration from our experiences and build similar electric analogs of their BioBricks designs! We've found them to be an amazing tool for engaging high school students and piquing their interest and understanding in Synthetic Biology.<br />
</p><br />
<br />
<br />
<h1 id="section1-2">Microcontrollers 101 </h1><br />
<p><br />
Typically, microcontrollers are general purpose microprocessors which have additional parts that allow them to read, and control external devices. We often use the terms microcontroller and microprocessor interchangeably. <br />
</p><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/6/6f/CMU_Arduino.jpg" height="287" width="287" align="right" alt="Matlab BioBrick GUI"/><br />
<b> Microcontrollers are typically used to: </b> <br />
<li> Gather sensor and component <i>inputs</i>. </li><br />
<li> Process these inputs, in digital format, to determine some <i>output</i> or action. </li><br />
<li> Utilize output devices and/or communication channels to do something useful. </li><br />
<br><br />
<br />
<br />
<p><br />
Why use <i>microcontrollers</i> to help spread synthetic biology awareness? Microcontrollers are a good starting point for teaching students about general input/output systems, which are the primary design focus of synthetic biology: <b>creating biological systems that transform environmental inputs into useful outputs</b>. A basic microcontroller typically includes a microprocessor, digital inputs/outputs, analog inputs/outputs, and some type of communication interface (e.g., serial, wi-fi, bluetooth, etc.). <br />
</p><br />
<br />
<p><br />
Although our kit utilizes an off-the-shelf microcontroller (AtMega328P-PU based Arduino), we additionally designed a simplified version. This allows other collaborators and students to potentially replicate, or modify the project and eventually fabricate their own simplified microcontrollers for use in DIY synthetic biology education. In many senses, the BioBricks being developed through the iGEM foundation essentially function like minute microcontroller systems. It is thus important to identify this similarity, and provide students and future researchers with an opportunity to explore it. <br />
</p><br />
<br />
<br />
<br />
<br />
<br />
<br />
<h1 id="section1-3">Simplified Microcontroller </h1><br />
<p>Below is a list of components used in our simplified microcontroller, and an image of the schematic designating the physical connections between the components and the AtMega328P-PU. These connections can initially be wired using a breadboard, which allows students to gain a simplified understanding of what connections are being made in off-the-shelf microcontrollers. If they choose, students can use the provided schematic files to order a PCB of their own from any of a variety of PCB manufacturers. <br />
</p><br />
<br />
<b> Parts List: </b> <br />
<li> AtMega328P-PU: <i>ATMega328P-PU (AVR microcontroller) </i></li><br />
<li> IC2: <i>78L05 (5v Voltage Regulator, 100ma) </i></li><br />
<li> Q1: <i>16MHz Resonator (with internal capacitors) </i> </li><br />
<li> C1: <i>0.1μF Capacitor </i> </li><br />
<li> C2: <i>0.33μF Capacitor </i> </li><br />
<li> C3: <i>0.1μF Capacitor </i> </li><br />
<li> R1: <i>10KΩ Resistor </i> </li><br />
<br><br />
<br />
<b>Simplified Microcontroller Schematic</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a7/Schematic_PCB_MCU.png" height="450" width="650"/><br />
<br><br><br />
<br />
<b>Simplified Microcontroller PCB Layout</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/c/c5/Schematic_PCB_Layout.png" /><br />
<br><br><br />
<p><br />
Follow this <a href="https://www.dropbox.com/sh/nb9cs0gpbvlrpxa/PMXNzM1p7G"> link</a> to download the eagle schematic files. The link also contains a.) tutorial on how to wire up and program the simplified microcontroller on a breadboard from scratch (this should be accomplished prior to pcb manufacture) and b.) parts list for the project enclosure and supporting components.<br />
<br><br><br />
</p><br />
</section><br />
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<h1 id = "section1-4"> Using the Hardware/Software Platform </h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
<br />
<br />
<b> General Notes </b><br />
<ol><br />
<li> Use the provided usb cable to connect the platform to a computer. Please do not detach the cable from the kit. </li><br />
<li> The GUI is implemented in Matlab currently, but will also be implemented via an open-source language.</li><br />
<li> Source-code for both implementations will be available via this <a href="https://www.dropbox.com/sh/zeeugv3pt4pgo0l/JkQ47msyeM"> link</a>. </li><br />
</ol><br />
<br><br><br />
<br />
<br />
<b> Overview </b><br><br />
<br />
<p><br />
The kit is comprised of one main BioBrick Unit (containing the programmed microcontroller) with interactive components, and an accompanying Fluorescence Unit which uses LEDs and a photo-resistor to emulate the process of collecting fluorescence microscope data. The LEDs illuminate with variable brightness in response to the user's choice of physical BioBrick configuration. This is roughly analogous to the fluorescence produced by cells illuminating in response to different BioBrick configurations in-vivo. The photo-resistor then emulates the fluorescence microscope by quantifying the light which is emitted by the LEDs. This "microscopy" process is paralleled by a Matlab GUI, which subsequently feeds the fluorescence data to the physical model, described <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> here</a>.<br />
</p><br />
<br><br><br />
<br />
<br />
<br />
<b> Build a BioBrick </b><br />
<ol><br />
<li> Insert the start-sequence, represented by the first set of 2-pin jumpers on the far left of the main unit. </li><br />
<li>Select a promoter from the 4 provided, and insert each promoter region. </li><br />
<ul><br />
<li> A single promoter is composed of 3 promoter regions, represented by identically-colored resistors. </li><br />
<li> Note the orientation of the components when inserting each region. </li><br />
<li> The top resistor should connect slots 1 & 2. The middle resistor should connect slots 2 & 3. The bottom resistor should connect slots 3 & 4. </li><br />
</ul><br />
<br><br />
<li> Insert the tRNA stabilizer headers (2). </li> <br />
<li> Insert the Spinach sequence (6-pin header). </li><br />
<li> Insert both RBS & FAP sequences. </li><br />
<li> Insert the end-sequence, represented by the final set of 2-pin jumpers. </li><br />
</ol><br />
<br><br><br />
<br />
<br />
<br />
<b> Characterize the Chosen Promoter </b><br />
<ol><br />
<li> Open Matlab, and add the folder with the provided software to the Matlab path.</li><br />
<ul><li> Right click the provided folder, and select "Add to Path -> Selected Folders and Sub-Folders" </li></ul><br />
<li> Type "BioBrick_GUI" at the command prompt, and hit enter. </li><br />
<li> First, populate the time-step input table from top to bottom with the values 10, 20, 30, 40 ,50 </li><br />
<li> Next, hit "Begin Time Lapse" at the top of the GUI: </li><br />
<ul><br />
<li> Note that the software will first sweep through the entire range of all possible fluorescence input levels, and plot the measured fluorescence values. </li><br />
<li> Allow the program to run to completion, populating the output tables. </li><br />
</ul><br />
<br><br />
<li> When the program is finished populating the outputs, hit "Calculate" to display the output values for translational efficiency and transcriptional strength. </li><br />
<li> To export the output tables to the Matlab workspace, select "File" from the menu bar, and choose "Export".</li><br />
<ul><li> This will move the output tables, and calculated values to the workspace. </li></ul><br />
<br><br />
<li> To plot an example comparison of the different promoters over time, enter "plot_data" at the Matlab command prompt. </li><br />
<ul><li> Observe the plot_data.m function if you wish to plot your own data </li></ul><br />
</ol><br />
<br><br><br />
<br />
<br />
<br />
<b> Make a Change and Observe the Effect! </b><br />
<li> Any of the following changes can be made to the BioBrick to help demonstrate the component relationships: </li><br />
<ul><br />
<li> Remove the Spinach sequence, </li><br />
<li> Remove the tRNA stabilizer (one or both components), </li><br />
<li> Remove the RBS sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the FAP sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the START/END sequence, </li><br />
<li> Remove either DFHBI or MG by toggling the switches off (illuminated when 'ON'), </li><br />
<li> …or any combination of the previous. </li><br />
</ul><br />
<br />
<br><br><br />
<br />
<h1 id="section1-1">Pictures and Schematics of the Kit </h1><br />
<br />
<b>BioBrick Circuit Kit</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/9/9a/CMU_BioBrick_Both_Units.jpg" height="300" width="433"/><br />
<br><br><br />
<br />
<b>BioBrick Components</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/1/16/CMU_BioBrick_Components.JPG" height="300" width="433"/><br />
<br><br><br />
<br />
<b>BioBrick Main Unit Circuit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/f/f3/CMU_Circ_Biobrick.png" height="300" width="700"/><br />
<br><br><br />
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<b>BioBrick Fluorescence Unit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_Fluor.png" height="300" width="433"/><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_PhotoR.png" height="300" width="433"/><br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-OutreachTeam:Carnegie Mellon/Hum-Outreach2012-10-27T03:38:22Z<p>Ychoo: </p>
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<br />
<h1 id="section1-1"> Summer Presentations to High School Students </h1><br />
<br />
<p><br />
The <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Human Practices/Overview</a> page provides information about the teaching materials, including a circuit kit, that our team created for the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 grade outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The Synthetic Biology kit will be used by high school Science teachers in classrooms in the Pittsburgh Public School System. We have already tested the kit in several presentations given by the team to High School students studying on the Carnegie Mellon campus this summer.<br />
</p><br />
<p><br />
This was the schedule and audience of our presentations:<br />
</p><br />
<p><br />
<ol><li> July 18 and August 1: Presentations to rising junior and senior high school students who participated in the Summer Academy of Math and Science at Carnegie Mellon. <br />
"The Summer Academy for Mathematics and Science (SAMS) is a rigorous residential summer experience for good students who have a strong interest in math and science and want to become excellent students." An objective of SAMS is to contribute to the expansion of the pipeline of outstanding college-bound high school graduates with diverse backgrounds.<br />
</li><li> July 20: Presentation to high school students taking AP Biology at Carnegie Mellon and their teacher. <br />
</ol> <br />
</p><br />
<br />
<p><br />
In these presentations (<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team"> download here!</a>), we introduced Synthetic Biology and iGEM to the students. <br><br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905934" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe><br />
<br><br><br />
<br />
In conjunction with the presentation, we used the circuit kit to explain the main aspects of our research project and to demonstrate how the biosensor can be used to characterize a promoter. For a given set of electronic components, we measured and displayed graphical representations of the current/voltage. <br />
<br><br />
<br><br />
<b> Interactive Mini-game </b><br />
<br><br><br />
<img src ="https://static.igem.org/mediawiki/2012/f/f1/Minigame.png" width="385px" height="345px" align="right"> <br />
To encourage the students to interact and play with the circuit kit, we devised a mini-game which placed the students in our shoes: <b> as Synthetic Biologists using our BioBrick system to characterize new promoters. </b> <br><br><br />
We did this by giving the students a set of different resistors, and gave them the challenge to find the best promoter by mixing and matching these parts and characterizing them using our circuit kit. <br><br />
Students could then change the electronic components and observe the corresponding changes in current/voltage. In the process, we explained to the students the formal equivalence of the electronic components and Biobricks and of the current/voltage and measured fluorescence signals. We also explained to them the biological significance of the graphs obtained.<br />
</p><br />
<br />
<br><br />
<p><br />
The students who attended our presentations learned about:<br />
<ol><li> Synthetic biology and its relationship to Biology and Science and Engineering in general<br />
</li><li> Gene expression and the central dogma of molecular biology<br />
</li><li> How synthetic biologists tackle real-world problems<br />
</li><li> The iGEM competition and how our iGEM team's project enables one to measures the properties of promoters<br />
</li><li> The interdisciplinary nature of synthetic biology<br />
</li><li> The advantages and challenges of interdisciplinary work<br />
</li></ol><br />
</p><br />
<br />
<p> Photos from our summer presentations can be found <a href="https://www.dropbox.com/sh/7kqncwq63vay4za/5zUMzdUbNs"> here</a>. </p><br />
<br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />
<h1 id = "section1-2"><br />
Future Outreach Plans<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<br />
<p><br />
The circuit is the basis for a kit to be used by high school Science teachers in classrooms in public schools in Pittsburgh. This is a means to incorporate Synthetic Biology in the HS curriculum. The kit is made available through the Lending Library of Science Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a>.<br />
<br><br />
We also came up with a teaching presentation to assist teachers in using our kits for teaching about Synthetic Biology. To download the presentation, please go to the Teaching Presentation portion of our Wiki.<br />
<br />
<br><br />
<br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905902" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe> <br />
<br><br />
</p><br />
<p><br />
The educational objectives of the classes in which the students use our Synthetic Biology kit are:<br />
<ol><li>Students will be able to give a definition of synthetic biology<br />
</li><li> Students will be able to identify one real-world application of synthetic biology <br />
</li><li> Students will be able to explain how technology is used to extend human abilities<br />
</li><li> Students will be able to recognize the correlation between the input and output of a biological or electronic circuit<br />
</li><li> Students will be able to recognize the advantages and limitations of using models to simulate processes that relate an input and its output<br />
</li><li> Students will be able to discuss the value of collaboration in interdisciplinary fields <br />
</li><li> Students will be able to discuss ethics aspects related to synthetic biology<br />
</ol> <br />
</p><br />
<br />
<br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-OutreachTeam:Carnegie Mellon/Hum-Outreach2012-10-27T03:38:12Z<p>Ychoo: </p>
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
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<section id="left"><br />
<header id = "header2"><br />
<br />
<h1 id="section1-1"> Summer Presentations to High School Students </h1><br />
<br />
<p><br />
The <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Human Practices/Overview</a> page provides information about the teaching materials, including a circuit kit, that our team created for the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 grade outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The Synthetic Biology kit will be used by high school Science teachers in classrooms in the Pittsburgh Public School System. We have already tested the kit in several presentations given by the team to High School students studying on the Carnegie Mellon campus this summer.<br />
</p><br />
<p><br />
This was the schedule and audience of our presentations:<br />
</p><br />
<p><br />
<ol><li> July 18 and August 1: Presentations to rising junior and senior high school students who participated in the Summer Academy of Math and Science at Carnegie Mellon. <br />
"The Summer Academy for Mathematics and Science (SAMS) is a rigorous residential summer experience for good students who have a strong interest in math and science and want to become excellent students." An objective of SAMS is to contribute to the expansion of the pipeline of outstanding college-bound high school graduates with diverse backgrounds.<br />
</li><li> July 20: Presentation to high school students taking AP Biology at Carnegie Mellon and their teacher. <br />
</ol> <br />
</p><br />
<br />
<p><br />
In these presentations (<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team"> download here!</a>), we introduced Synthetic Biology and iGEM to the students. <br><br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905934" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe><br />
<br><br><br />
<br />
In conjunction with the presentation, we used the circuit kit to explain the main aspects of our research project and to demonstrate how the biosensor can be used to characterize a promoter. For a given set of electronic components, we measured and displayed graphical representations of the current/voltage. <br />
<br><br />
<br><br />
<b> Interactive Mini-game </b><br />
<br><br><br />
<img src ="https://static.igem.org/mediawiki/2012/f/f1/Minigame.png" width="385px" height="345px" align="right"> <br />
To encourage the students to interact and play with the circuit kit, we devised a mini-game which placed the students in our shoes: <b> as Synthetic Biologists using our BioBrick system to characterize new promoters. </b> <br><br><br />
We did this by giving the students a set of different resistors, and gave them the challenge to find the best promoter by mixing and matching these parts and characterizing them using our circuit kit. <br><br />
Students could then change the electronic components and observe the corresponding changes in current/voltage. In the process, we explained to the students the formal equivalence of the electronic components and Biobricks and of the current/voltage and measured fluorescence signals. We also explained to them the biological significance of the graphs obtained.<br />
</p><br />
<br />
<br><br />
<p><br />
The students who attended our presentations learned about:<br />
<ol><li> Synthetic biology and its relationship to Biology and Science and Engineering in general<br />
</li><li> Gene expression and the central dogma of molecular biology<br />
</li><li> How synthetic biologists tackle real-world problems<br />
</li><li> The iGEM competition and how our iGEM team's project enables one to measures the properties of promoters<br />
</li><li> The interdisciplinary nature of synthetic biology<br />
</li><li> The advantages and challenges of interdisciplinary work<br />
</li></ol><br />
</p><br />
<br />
<p> Photos from our summer presentations can be found <a href="https://www.dropbox.com/sh/7kqncwq63vay4za/5zUMzdUbNs"> here</a>. </p><br />
<br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />
<h1 id = "section1-2"><br />
Future Outreach Plans<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<br />
<p><br />
The circuit is the basis for a kit to be used by high school Science teachers in classrooms in public schools in Pittsburgh. This is a means to incorporate Synthetic Biology in the HS curriculum. The kit is made available through the Lending Library of Science Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a>.<br />
<br><br />
We also came up with a teaching presentation to assist teachers in using our kits for teaching about Synthetic Biology. To download the presentation, please go to the Teaching Presentation portion of our Wiki.<br />
<br />
<br><br />
<br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905902" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe> <br />
<br><br />
</p><br />
<p><br />
The educational objectives of the classes in which the students use our Synthetic Biology kit are:<br />
<ol><li>Students will be able to give a definition of synthetic biology<br />
</li><li> Students will be able to identify one real-world application of synthetic biology <br />
</li><li> Students will be able to explain how technology is used to extend human abilities<br />
</li><li> Students will be able to recognize the correlation between the input and output of a biological or electronic circuit<br />
</li><li> Students will be able to recognize the advantages and limitations of using models to simulate processes that relate an input and its output<br />
</li><li> Students will be able to discuss the value of collaboration in interdisciplinary fields <br />
</li><li> Students will be able to discuss ethics aspects related to synthetic biology<br />
</ol> <br />
</p><br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-OverviewTeam:Carnegie Mellon/Hum-Overview2012-10-27T03:37:59Z<p>Ychoo: </p>
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<p><br />
The impact of synthetic biology depends on the number and quality of scientists making significant contributions to the field. Future scientists will rise from current high school students who are excited about science and gain a solid background in math and science in their formative years. To this end, we decided to raise the awareness of high school students about the interdisciplinary field of synthetic biology and to also teach them about the process of scientific research.<br><br />
As an additional outcome, the proposed methodology of using an electronic circuit equivalent for modeling biological phenomena can be replicated and used beyond the context of our current project.<br />
</p><br />
<br />
<img src = "https://static.igem.org/mediawiki/2012/2/20/Outreachphoto1.JPG" align = "right" padding ="5px"><br />
<p><br />
We decided to create teaching materials for high school students inspired by our team’s research project. Our goal was that these materials can be easily used by a science teacher in a lecture in a Biology or Chemistry course to:<br />
<div class = "ol"><br />
<ol type = "1" compact> <br />
<li>Explain what Synthetic Biology is; </li><br />
<li>Illustrate the opportunities created by Synthetic Biology in improving human well being; </li><br />
<li>Discuss ethical concerns related to Synthetic Biology; </li><br />
<li>Enable the students to understand how our <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a> works.</li><br />
</ol><br />
</div><br />
</p><br />
<br />
<p><br />
To bridge the gap between the background of a high school student and the complexity of our project, we built an affordable, microcontroller-based, hardware platform and associated, open-source, digital simulation software. In designing the demonstration platform, we exploited the relationship between biological networks in synthetic biology and electronic circuits in electrical engineering. Specifically, we created a circuit kit that emulates in hardware our biological construct and in software both the response of the biological construct to specific cell conditions and the fluorescence measurement. It is important to note that the kit is <b>INTERACTIVE</b> (students can easily change electronic components to simulate different biological or external changes and the outcome of these changes), <b> RELATABLE</b> (the students can directly use the kit) and <b>EASILY SHARED AND IMPROVED</b> (the list of electronic components, circuit diagrams etc. are in the public domain and the software is open source).<br />
</p><br />
<br />
<p><br />
The teaching materials we have created, specifically a <a href="https://www.dropbox.com/s/n1bpb77einu26ko/iGEM_Summer_Presentation.pdf"> power point presentation</a> and an <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> electronic circuit kit</a>, have become part of the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The kits in the Library are loaned to high school teachers in the Pittsburgh area to be used in teaching Math and Science. We identified for the teachers how the use of our kit can help the High School students meet specific objectives from the <a href ="http://static.pdesas.org/content/documents/Academic_Standards_for_Science_and_Technology_and_Engineering_Education_%28Secondary%29.pdf">Pennsylvania Academic Standards for Science, Technology, and Engineering Education</a> and the <a href ="http://www.portal.state.pa.us/portal/server.pt/community/assessment_anchors/7440 ">Pennsylvania Assessment Anchors</a>. We have also tested the kit in several demonstrations in the Summer of 2012 to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> Summer Academy of Math and Science (SAMS)</a> at Carnegie Mellon.<br />
</p><br />
<br />
<p><br />
A very important original property of our approach to Human Practices stems from the fact that the teaching materials we created are available to teachers in any Pittsburgh Public School District who can borrow them from the Lending Library of Kits and use them even after the work of the current CMU iGEM team ends. Another original factor is the fact that we identified for the teachers which objectives from the Pennsylvania Academic Standards for Science, Technology and Engineering they can teach using the kit. This identification should eliminate the barrier to adoption of the kit by teachers faced with tight time schedules to cover these objectives.<br />
</p><br />
<p><br />
</p><br />
<h1 id="section1-1"> System Implemented with the Kit </h1><br />
<img src="https://static.igem.org/mediawiki/2012/f/f4/System_model.jpg" height="300" width="433" align="right"/><br />
<p><br />
As described <a href="https://2012.igem.org/Team:Carnegie_Mellon"> here</a>, our team engineered a fluorescence-based sensor that provides information on both transcription strength and translation efficiency of a promoter. The sensor is noninvasive, easily applied to a variety of promoters, and capable of providing results in a time frame that is short when compared to current technologies for the characterization of promoters. <br />
</p><br />
<p><br />
The sensor is based on the use of an RNA aptamer (termed Spinach) and a fluorogen activating protein (FAP). The complexes of Spinach (mRNA-DMHBI in the Figure) and FAP (FAP-MG in the Figure) with specific dyes, DFHBI and MG, respectively, are fluorescent. Measurements of the fluorescence intensity of these complexes enables one to determine the concentration of mRNA and expressed protein for a given promoter. Analysis of the fluorescence data with an appropriate model leads to the transcription strength and translation efficiency for each promoter.<br />
</p><br />
</section><br />
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<header id = "header"><br />
<h1 id = "section1-2"><br />
The Hardware/Software Platform<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
<p><br />
</p><br />
</p><br />
<p><br />
The goal was to create a model of our <b><a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a></b> that clearly represents its main components and makes clear how the biosensor works. We also planned to enable the students to simulate changes in the “environment” and to observe the outcome of these changes. To achieve this goal, we built an affordable, microcontroller-based, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> hardware</a> platform and also developed an associated, open-source, simulation <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software"> software</a>. <br />
<br />
</p><br />
<p><br />
The combined hardware/software platform allows the students to directly manipulate electronic components, which are formal equivalents of the BioBricks used in our sensor, and to observe the effect of changing these components on the current or voltage output, which is the equivalent of the fluorescence intensity in our lab experiments. In using the kit, the students get a feel for how different promoters are compared using the biosensor; they can rank "virtual promoters" in the order of their strength. Students who use the kit gain hands-on experience and understand how all the parts of the biosensor work together to measure the mRNA and protein levels, without working in the wet lab.<br />
The figure on the right is a photograph of the hardware platform on which the correspondence between the biological components of the biosensor and the electronic components of the kit are identified.<br />
</p><br />
<p><br />
The software used in the platform is based on the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> model</a> derived for the analysis of the fluorescence data obtained with the biosensor. We have also created a GUI that allows the students to modify the parameters used in the model and to visualize on a computer display the current/voltage output (which is the equivalent of the fluorescence output in our experiments).<br />
</p><br />
</section><br />
<br />
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<header id = "header"><br />
<h1 id = "section1-3"><br />
Team Presentations to Groups of High School Students<br />
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<header id = "header2"><br />
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</p><br />
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<p><br />
To obtain feedback for how high school students use the circuit kit, the team has given several presentations about synthetic biology and our project to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> SAMS</a> and in <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/apea.html"> AP Biology</a> at Carnegie Mellon University. <br />
We have also sought and obtained feedback on the kit from Dr. Janet Waldeck, Physics teacher at the Pittsburgh Allderdice High School in Pittsburgh. <br />
The feedback and input gained from these presentations was used to refine the kit. <br />
</p><br />
<br />
<br />
<br />
<h1> Broader Impact in Biological Modeling Methodology </h1><br />
<p><br />
The methodology used to build the electrical equivalent of the biological processes is not unique to the problem we are solving in this project. Starting from first principles modeling, one can use the methodology followed in our circuit kit implementation and emulate the behavior of the processes governing other biological phenomena by using simple controllers and circuit components. This shows that interdisciplinary training is not only desirable, but can also be beneficial for solving synthetic biology problems, thereby underscoring the importance of such training starting from high school through college.<br />
<br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-OverviewTeam:Carnegie Mellon/Hum-Overview2012-10-27T03:37:47Z<p>Ychoo: </p>
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
</ul><br />
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<section id="left"><br />
<header id = "header2"><br />
</p><br />
<p><br />
The impact of synthetic biology depends on the number and quality of scientists making significant contributions to the field. Future scientists will rise from current high school students who are excited about science and gain a solid background in math and science in their formative years. To this end, we decided to raise the awareness of high school students about the interdisciplinary field of synthetic biology and to also teach them about the process of scientific research.<br><br />
As an additional outcome, the proposed methodology of using an electronic circuit equivalent for modeling biological phenomena can be replicated and used beyond the context of our current project.<br />
</p><br />
<br />
<img src = "https://static.igem.org/mediawiki/2012/2/20/Outreachphoto1.JPG" align = "right" padding ="5px"><br />
<p><br />
We decided to create teaching materials for high school students inspired by our team’s research project. Our goal was that these materials can be easily used by a science teacher in a lecture in a Biology or Chemistry course to:<br />
<div class = "ol"><br />
<ol type = "1" compact> <br />
<li>Explain what Synthetic Biology is; </li><br />
<li>Illustrate the opportunities created by Synthetic Biology in improving human well being; </li><br />
<li>Discuss ethical concerns related to Synthetic Biology; </li><br />
<li>Enable the students to understand how our <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a> works.</li><br />
</ol><br />
</div><br />
</p><br />
<br />
<p><br />
To bridge the gap between the background of a high school student and the complexity of our project, we built an affordable, microcontroller-based, hardware platform and associated, open-source, digital simulation software. In designing the demonstration platform, we exploited the relationship between biological networks in synthetic biology and electronic circuits in electrical engineering. Specifically, we created a circuit kit that emulates in hardware our biological construct and in software both the response of the biological construct to specific cell conditions and the fluorescence measurement. It is important to note that the kit is <b>INTERACTIVE</b> (students can easily change electronic components to simulate different biological or external changes and the outcome of these changes), <b> RELATABLE</b> (the students can directly use the kit) and <b>EASILY SHARED AND IMPROVED</b> (the list of electronic components, circuit diagrams etc. are in the public domain and the software is open source).<br />
</p><br />
<br />
<p><br />
The teaching materials we have created, specifically a <a href="https://www.dropbox.com/s/n1bpb77einu26ko/iGEM_Summer_Presentation.pdf"> power point presentation</a> and an <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> electronic circuit kit</a>, have become part of the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The kits in the Library are loaned to high school teachers in the Pittsburgh area to be used in teaching Math and Science. We identified for the teachers how the use of our kit can help the High School students meet specific objectives from the <a href ="http://static.pdesas.org/content/documents/Academic_Standards_for_Science_and_Technology_and_Engineering_Education_%28Secondary%29.pdf">Pennsylvania Academic Standards for Science, Technology, and Engineering Education</a> and the <a href ="http://www.portal.state.pa.us/portal/server.pt/community/assessment_anchors/7440 ">Pennsylvania Assessment Anchors</a>. We have also tested the kit in several demonstrations in the Summer of 2012 to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> Summer Academy of Math and Science (SAMS)</a> at Carnegie Mellon.<br />
</p><br />
<br />
<p><br />
A very important original property of our approach to Human Practices stems from the fact that the teaching materials we created are available to teachers in any Pittsburgh Public School District who can borrow them from the Lending Library of Kits and use them even after the work of the current CMU iGEM team ends. Another original factor is the fact that we identified for the teachers which objectives from the Pennsylvania Academic Standards for Science, Technology and Engineering they can teach using the kit. This identification should eliminate the barrier to adoption of the kit by teachers faced with tight time schedules to cover these objectives.<br />
</p><br />
<p><br />
</p><br />
<h1 id="section1-1"> System Implemented with the Kit </h1><br />
<img src="https://static.igem.org/mediawiki/2012/f/f4/System_model.jpg" height="300" width="433" align="right"/><br />
<p><br />
As described <a href="https://2012.igem.org/Team:Carnegie_Mellon"> here</a>, our team engineered a fluorescence-based sensor that provides information on both transcription strength and translation efficiency of a promoter. The sensor is noninvasive, easily applied to a variety of promoters, and capable of providing results in a time frame that is short when compared to current technologies for the characterization of promoters. <br />
</p><br />
<p><br />
The sensor is based on the use of an RNA aptamer (termed Spinach) and a fluorogen activating protein (FAP). The complexes of Spinach (mRNA-DMHBI in the Figure) and FAP (FAP-MG in the Figure) with specific dyes, DFHBI and MG, respectively, are fluorescent. Measurements of the fluorescence intensity of these complexes enables one to determine the concentration of mRNA and expressed protein for a given promoter. Analysis of the fluorescence data with an appropriate model leads to the transcription strength and translation efficiency for each promoter.<br />
</p><br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<h1 id = "section1-2"><br />
The Hardware/Software Platform<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
<p><br />
</p><br />
</p><br />
<p><br />
The goal was to create a model of our <b><a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a></b> that clearly represents its main components and makes clear how the biosensor works. We also planned to enable the students to simulate changes in the “environment” and to observe the outcome of these changes. To achieve this goal, we built an affordable, microcontroller-based, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> hardware</a> platform and also developed an associated, open-source, simulation <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software"> software</a>. <br />
<br />
</p><br />
<p><br />
The combined hardware/software platform allows the students to directly manipulate electronic components, which are formal equivalents of the BioBricks used in our sensor, and to observe the effect of changing these components on the current or voltage output, which is the equivalent of the fluorescence intensity in our lab experiments. In using the kit, the students get a feel for how different promoters are compared using the biosensor; they can rank "virtual promoters" in the order of their strength. Students who use the kit gain hands-on experience and understand how all the parts of the biosensor work together to measure the mRNA and protein levels, without working in the wet lab.<br />
The figure on the right is a photograph of the hardware platform on which the correspondence between the biological components of the biosensor and the electronic components of the kit are identified.<br />
</p><br />
<p><br />
The software used in the platform is based on the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> model</a> derived for the analysis of the fluorescence data obtained with the biosensor. We have also created a GUI that allows the students to modify the parameters used in the model and to visualize on a computer display the current/voltage output (which is the equivalent of the fluorescence output in our experiments).<br />
</p><br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<h1 id = "section1-3"><br />
Team Presentations to Groups of High School Students<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<br />
<p><br />
</p><br />
</p><br />
<p><br />
To obtain feedback for how high school students use the circuit kit, the team has given several presentations about synthetic biology and our project to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> SAMS</a> and in <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/apea.html"> AP Biology</a> at Carnegie Mellon University. <br />
We have also sought and obtained feedback on the kit from Dr. Janet Waldeck, Physics teacher at the Pittsburgh Allderdice High School in Pittsburgh. <br />
The feedback and input gained from these presentations was used to refine the kit. <br />
</p><br />
<br />
<br />
<br />
<h1> Broader Impact in Biological Modeling Methodology </h1><br />
<p><br />
The methodology used to build the electrical equivalent of the biological processes is not unique to the problem we are solving in this project. Starting from first principles modeling, one can use the methodology followed in our circuit kit implementation and emulate the behavior of the processes governing other biological phenomena by using simple controllers and circuit components. This shows that interdisciplinary training is not only desirable, but can also be beneficial for solving synthetic biology problems, thereby underscoring the importance of such training starting from high school through college.<br />
<br />
</div><br />
</div><br />
</p><br />
<br />
</html><br />
{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-OverviewTeam:Carnegie Mellon/Hum-Overview2012-10-27T03:37:26Z<p>Ychoo: </p>
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
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<p><br />
The impact of synthetic biology depends on the number and quality of scientists making significant contributions to the field. Future scientists will rise from current high school students who are excited about science and gain a solid background in math and science in their formative years. To this end, we decided to raise the awareness of high school students about the interdisciplinary field of synthetic biology and to also teach them about the process of scientific research.<br><br />
As an additional outcome, the proposed methodology of using an electronic circuit equivalent for modeling biological phenomena can be replicated and used beyond the context of our current project.<br />
</p><br />
<br />
<img src = "https://static.igem.org/mediawiki/2012/2/20/Outreachphoto1.JPG" align = "right" padding ="5px"><br />
<p><br />
We decided to create teaching materials for high school students inspired by our team’s research project. Our goal was that these materials can be easily used by a science teacher in a lecture in a Biology or Chemistry course to:<br />
<div class = "ol"><br />
<ol type = "1" compact> <br />
<li>Explain what Synthetic Biology is; </li><br />
<li>Illustrate the opportunities created by Synthetic Biology in improving human well being; </li><br />
<li>Discuss ethical concerns related to Synthetic Biology; </li><br />
<li>Enable the students to understand how our <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a> works.</li><br />
</ol><br />
</div><br />
</p><br />
<br />
<p><br />
To bridge the gap between the background of a high school student and the complexity of our project, we built an affordable, microcontroller-based, hardware platform and associated, open-source, digital simulation software. In designing the demonstration platform, we exploited the relationship between biological networks in synthetic biology and electronic circuits in electrical engineering. Specifically, we created a circuit kit that emulates in hardware our biological construct and in software both the response of the biological construct to specific cell conditions and the fluorescence measurement. It is important to note that the kit is <b>INTERACTIVE</b> (students can easily change electronic components to simulate different biological or external changes and the outcome of these changes), <b> RELATABLE</b> (the students can directly use the kit) and <b>EASILY SHARED AND IMPROVED</b> (the list of electronic components, circuit diagrams etc. are in the public domain and the software is open source).<br />
</p><br />
<br />
<p><br />
The teaching materials we have created, specifically a <a href="https://www.dropbox.com/s/n1bpb77einu26ko/iGEM_Summer_Presentation.pdf"> power point presentation</a> and an <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> electronic circuit kit</a>, have become part of the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The kits in the Library are loaned to high school teachers in the Pittsburgh area to be used in teaching Math and Science. We identified for the teachers how the use of our kit can help the High School students meet specific objectives from the <a href ="http://static.pdesas.org/content/documents/Academic_Standards_for_Science_and_Technology_and_Engineering_Education_%28Secondary%29.pdf">Pennsylvania Academic Standards for Science, Technology, and Engineering Education</a> and the <a href ="http://www.portal.state.pa.us/portal/server.pt/community/assessment_anchors/7440 ">Pennsylvania Assessment Anchors</a>. We have also tested the kit in several demonstrations in the Summer of 2012 to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> Summer Academy of Math and Science (SAMS)</a> at Carnegie Mellon.<br />
</p><br />
<br />
<p><br />
A very important original property of our approach to Human Practices stems from the fact that the teaching materials we created are available to teachers in any Pittsburgh Public School District who can borrow them from the Lending Library of Kits and use them even after the work of the current CMU iGEM team ends. Another original factor is the fact that we identified for the teachers which objectives from the Pennsylvania Academic Standards for Science, Technology and Engineering they can teach using the kit. This identification should eliminate the barrier to adoption of the kit by teachers faced with tight time schedules to cover these objectives.<br />
</p><br />
<p><br />
</p><br />
<h1 id="section1-1"> System Implemented with the Kit </h1><br />
<img src="https://static.igem.org/mediawiki/2012/f/f4/System_model.jpg" height="300" width="433" align="right"/><br />
<p><br />
As described <a href="https://2012.igem.org/Team:Carnegie_Mellon"> here</a>, our team engineered a fluorescence-based sensor that provides information on both transcription strength and translation efficiency of a promoter. The sensor is noninvasive, easily applied to a variety of promoters, and capable of providing results in a time frame that is short when compared to current technologies for the characterization of promoters. <br />
</p><br />
<p><br />
The sensor is based on the use of an RNA aptamer (termed Spinach) and a fluorogen activating protein (FAP). The complexes of Spinach (mRNA-DMHBI in the Figure) and FAP (FAP-MG in the Figure) with specific dyes, DFHBI and MG, respectively, are fluorescent. Measurements of the fluorescence intensity of these complexes enables one to determine the concentration of mRNA and expressed protein for a given promoter. Analysis of the fluorescence data with an appropriate model leads to the transcription strength and translation efficiency for each promoter.<br />
</p><br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<h1 id = "section1-2"><br />
The Hardware/Software Platform<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
<p><br />
</p><br />
</p><br />
<p><br />
The goal was to create a model of our <b><a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a></b> that clearly represents its main components and makes clear how the biosensor works. We also planned to enable the students to simulate changes in the “environment” and to observe the outcome of these changes. To achieve this goal, we built an affordable, microcontroller-based, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> hardware</a> platform and also developed an associated, open-source, simulation <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software"> software</a>. <br />
<br />
</p><br />
<p><br />
The combined hardware/software platform allows the students to directly manipulate electronic components, which are formal equivalents of the BioBricks used in our sensor, and to observe the effect of changing these components on the current or voltage output, which is the equivalent of the fluorescence intensity in our lab experiments. In using the kit, the students get a feel for how different promoters are compared using the biosensor; they can rank "virtual promoters" in the order of their strength. Students who use the kit gain hands-on experience and understand how all the parts of the biosensor work together to measure the mRNA and protein levels, without working in the wet lab.<br />
The figure on the right is a photograph of the hardware platform on which the correspondence between the biological components of the biosensor and the electronic components of the kit are identified.<br />
</p><br />
<p><br />
The software used in the platform is based on the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> model</a> derived for the analysis of the fluorescence data obtained with the biosensor. We have also created a GUI that allows the students to modify the parameters used in the model and to visualize on a computer display the current/voltage output (which is the equivalent of the fluorescence output in our experiments).<br />
</p><br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<h1 id = "section1-3"><br />
Team Presentations to Groups of High School Students<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<br />
<p><br />
</p><br />
</p><br />
<p><br />
To obtain feedback for how high school students use the circuit kit, the team has given several presentations about synthetic biology and our project to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> SAMS</a> and in <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/apea.html"> AP Biology</a> at Carnegie Mellon University. <br />
We have also sought and obtained feedback on the kit from Dr. Janet Waldeck, Physics teacher at the Pittsburgh Allderdice High School in Pittsburgh. <br />
The feedback and input gained from these presentations was used to refine the kit. <br />
</p><br />
<br />
<br />
<br />
<h1> Broader Impact in Biological Modeling Methodology </h1><br />
<p><br />
The methodology used to build the electrical equivalent of the biological processes is not unique to the problem we are solving in this project. Starting from first principles modeling, one can use the methodology followed in our circuit kit implementation and emulate the behavior of the processes governing other biological phenomena by using simple controllers and circuit components. This shows that interdisciplinary training is not only desirable, but can also be beneficial for solving synthetic biology problems, thereby underscoring the importance of such training starting from high school through college.<br />
<br />
</div><br />
</div><br />
</p><br />
<br />
</html><br />
{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-TeamTeam:Carnegie Mellon/Hum-Team2012-10-27T03:36:55Z<p>Ychoo: </p>
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The software consists of two parts: model implementation and GUI, both written in Matlab. <br />
</p><br />
<h1 id="section1-1"> Physical Model</h1><br />
<p><br />
We implemented the model described <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Matlab"> here</a>.<br />
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BioBrick Circuit GUI<br />
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The interface allows users to enter time-step data (e.g., at what time points should images be captured), which populates two tables, displayed in the Matlab GUI. When the user starts the simulated microscopy time lapse, a full sweep of measured vs. actual fluorescence values are plotted for both mRNA and protein. This is essentially plotting the <br />
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<img src="https://static.igem.org/mediawiki/2012/4/4d/CMU_BioBrick_GUI_Screen_Shot.png" height="400" width="405" align="right"/><br />
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quantity of light produced by the LEDs (representing cells) versus the quantity of light detected by the photo-resistor (representing the microscopy). The GUI then iterates through each time-step, plotting a horizontal line with each sweep plot corresponding to the measured fluorescence at that particular time step. The GUI also populates both tables with the actual values as it moves to each next time step.<br />
</p><br />
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<p><br />
Furthermore, the GUI successfully displays a relevant image of the cells at every timestep. Illuminated fields above the plots indicate which type of fluorescence (mRNA or protein) is currently being populated. When the time lapse is finished, a push-button becomes available which, when clicked, opens a dialog-box displaying and transcriptional strength (<i>Ts</i>) and translational efficiency (<i>Tl</i>). This component calls the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Matlab"> computational function</a> that implements the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Derivations"> model</a>, which computes <i>Ts</i> and <i>Tl</i>.<br />
</p><br />
<p><br />
Finally, a File-Menu dropdown option ('Export') serves to export the table data for both mRNA and protein, as well as the computed values for transcriptional strength and translational efficiency to the local Matlab workspace.<br />
</p><br />
To download the software accompanying the kit, please visit the circuit kit <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> documentation</a>, and scroll down to "General Notes" under the "Using the Hardware/Software Platform" section. <br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-CircuitTeam:Carnegie Mellon/Hum-Circuit2012-10-27T03:35:55Z<p>Ychoo: </p>
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<h1 id="section1-1">Circuit Kit: Overview </h1><br />
<p><br />
In order to raise awareness, and motivate continued innovation in the field of synthetic biology, our iGEM team took the initiative to design a simple hardware demonstration platform, with which mentors can allow students to interact with a physical model of our project! The platform uses a microcontroller and a collection of simple circuits and components which communicate with a Matlab GUI to demonstrate how the various portions of our BioBricks interact to accomplish our goal. <br><br />
Most importantly, we hope all iGEM teams can take inspiration from our experiences and build similar electric analogs of their BioBricks designs! We've found them to be an amazing tool for engaging high school students and piquing their interest and understanding in Synthetic Biology.<br />
</p><br />
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<br />
<h1 id="section1-2">Microcontrollers 101 </h1><br />
<p><br />
Typically, microcontrollers are general purpose microprocessors which have additional parts that allow them to read, and control external devices. We often use the terms microcontroller and microprocessor interchangeably. <br />
</p><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/6/6f/CMU_Arduino.jpg" height="287" width="287" align="right" alt="Matlab BioBrick GUI"/><br />
<b> Microcontrollers are typically used to: </b> <br />
<li> Gather sensor and component <i>inputs</i>. </li><br />
<li> Process these inputs, in digital format, to determine some <i>output</i> or action. </li><br />
<li> Utilize output devices and/or communication channels to do something useful. </li><br />
<br><br />
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<br />
<p><br />
Why use <i>microcontrollers</i> to help spread synthetic biology awareness? Microcontrollers are a good starting point for teaching students about general input/output systems, which are the primary design focus of synthetic biology: <b>creating biological systems that transform environmental inputs into useful outputs</b>. A basic microcontroller typically includes a microprocessor, digital inputs/outputs, analog inputs/outputs, and some type of communication interface (e.g., serial, wi-fi, bluetooth, etc.). <br />
</p><br />
<br />
<p><br />
Although our kit utilizes an off-the-shelf microcontroller (AtMega328P-PU based Arduino), we additionally designed a simplified version. This allows other collaborators and students to potentially replicate, or modify the project and eventually fabricate their own simplified microcontrollers for use in DIY synthetic biology education. In many senses, the BioBricks being developed through the iGEM foundation essentially function like minute microcontroller systems. It is thus important to identify this similarity, and provide students and future researchers with an opportunity to explore it. <br />
</p><br />
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<h1 id="section1-3">Simplified Microcontroller </h1><br />
<p>Below is a list of components used in our simplified microcontroller, and an image of the schematic designating the physical connections between the components and the AtMega328P-PU. These connections can initially be wired using a breadboard, which allows students to gain a simplified understanding of what connections are being made in off-the-shelf microcontrollers. If they choose, students can use the provided schematic files to order a PCB of their own from any of a variety of PCB manufacturers. <br />
</p><br />
<br />
<b> Parts List: </b> <br />
<li> AtMega328P-PU: <i>ATMega328P-PU (AVR microcontroller) </i></li><br />
<li> IC2: <i>78L05 (5v Voltage Regulator, 100ma) </i></li><br />
<li> Q1: <i>16MHz Resonator (with internal capacitors) </i> </li><br />
<li> C1: <i>0.1μF Capacitor </i> </li><br />
<li> C2: <i>0.33μF Capacitor </i> </li><br />
<li> C3: <i>0.1μF Capacitor </i> </li><br />
<li> R1: <i>10KΩ Resistor </i> </li><br />
<br><br />
<br />
<b>Simplified Microcontroller Schematic</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a7/Schematic_PCB_MCU.png" height="450" width="650"/><br />
<br><br><br />
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<b>Simplified Microcontroller PCB Layout</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/c/c5/Schematic_PCB_Layout.png" /><br />
<br><br><br />
<p><br />
Follow this <a href="https://www.dropbox.com/sh/nb9cs0gpbvlrpxa/PMXNzM1p7G"> link</a> to download the eagle schematic files. The link also contains a.) tutorial on how to wire up and program the simplified microcontroller on a breadboard from scratch (this should be accomplished prior to pcb manufacture) and b.) parts list for the project enclosure and supporting components.<br />
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<b> General Notes </b><br />
<ol><br />
<li> Use the provided usb cable to connect the platform to a computer. Please do not detach the cable from the kit. </li><br />
<li> The GUI is implemented in Matlab currently, but will also be implemented via an open-source language.</li><br />
<li> Source-code for both implementations will be available via this <a href="https://www.dropbox.com/sh/zeeugv3pt4pgo0l/JkQ47msyeM"> link</a>. </li><br />
</ol><br />
<br><br><br />
<br />
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<b> Overview </b><br><br />
<br />
<p><br />
The kit is comprised of one main BioBrick Unit (containing the programmed microcontroller) with interactive components, and an accompanying Fluorescence Unit which uses LEDs and a photo-resistor to emulate the process of collecting fluorescence microscope data. The LEDs illuminate with variable brightness in response to the user's choice of physical BioBrick configuration. This is roughly analogous to the fluorescence produced by cells illuminating in response to different BioBrick configurations in-vivo. The photo-resistor then emulates the fluorescence microscope by quantifying the light which is emitted by the LEDs. This "microscopy" process is paralleled by a Matlab GUI, which subsequently feeds the fluorescence data to the physical model, described <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> here</a>.<br />
</p><br />
<br><br><br />
<br />
<br />
<br />
<b> Build a BioBrick </b><br />
<ol><br />
<li> Insert the start-sequence, represented by the first set of 2-pin jumpers on the far left of the main unit. </li><br />
<li>Select a promoter from the 4 provided, and insert each promoter region. </li><br />
<ul><br />
<li> A single promoter is composed of 3 promoter regions, represented by identically-colored resistors. </li><br />
<li> Note the orientation of the components when inserting each region. </li><br />
<li> The top resistor should connect slots 1 & 2. The middle resistor should connect slots 2 & 3. The bottom resistor should connect slots 3 & 4. </li><br />
</ul><br />
<br><br />
<li> Insert the tRNA stabilizer headers (2). </li> <br />
<li> Insert the Spinach sequence (6-pin header). </li><br />
<li> Insert both RBS & FAP sequences. </li><br />
<li> Insert the end-sequence, represented by the final set of 2-pin jumpers. </li><br />
</ol><br />
<br><br><br />
<br />
<br />
<br />
<b> Characterize the Chosen Promoter </b><br />
<ol><br />
<li> Open Matlab, and add the folder with the provided software to the Matlab path.</li><br />
<ul><li> Right click the provided folder, and select "Add to Path -> Selected Folders and Sub-Folders" </li></ul><br />
<li> Type "BioBrick_GUI" at the command prompt, and hit enter. </li><br />
<li> First, populate the time-step input table from top to bottom with the values 10, 20, 30, 40 ,50 </li><br />
<li> Next, hit "Begin Time Lapse" at the top of the GUI: </li><br />
<ul><br />
<li> Note that the software will first sweep through the entire range of all possible fluorescence input levels, and plot the measured fluorescence values. </li><br />
<li> Allow the program to run to completion, populating the output tables. </li><br />
</ul><br />
<br><br />
<li> When the program is finished populating the outputs, hit "Calculate" to display the output values for translational efficiency and transcriptional strength. </li><br />
<li> To export the output tables to the Matlab workspace, select "File" from the menu bar, and choose "Export".</li><br />
<ul><li> This will move the output tables, and calculated values to the workspace. </li></ul><br />
<br><br />
<li> To plot an example comparison of the different promoters over time, enter "plot_data" at the Matlab command prompt. </li><br />
<ul><li> Observe the plot_data.m function if you wish to plot your own data </li></ul><br />
</ol><br />
<br><br><br />
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<b> Make a Change and Observe the Effect! </b><br />
<li> Any of the following changes can be made to the BioBrick to help demonstrate the component relationships: </li><br />
<ul><br />
<li> Remove the Spinach sequence, </li><br />
<li> Remove the tRNA stabilizer (one or both components), </li><br />
<li> Remove the RBS sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the FAP sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the START/END sequence, </li><br />
<li> Remove either DFHBI or MG by toggling the switches off (illuminated when 'ON'), </li><br />
<li> …or any combination of the previous. </li><br />
</ul><br />
<br />
<br><br><br />
<br />
<h1 id="section1-1">Pictures and Schematics of the Kit </h1><br />
<br />
<b>BioBrick Circuit Kit</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/9/9a/CMU_BioBrick_Both_Units.jpg" height="300" width="433"/><br />
<br><br><br />
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<b>BioBrick Components</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/1/16/CMU_BioBrick_Components.JPG" height="300" width="433"/><br />
<br><br><br />
<br />
<b>BioBrick Main Unit Circuit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/f/f3/CMU_Circ_Biobrick.png" height="300" width="700"/><br />
<br><br><br />
<br />
<b>BioBrick Fluorescence Unit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_Fluor.png" height="300" width="433"/><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_PhotoR.png" height="300" width="433"/><br />
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<h1 id="section1-1"> Summer Presentations to High School Students </h1><br />
<br />
<p><br />
The <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Human Practices/Overview</a> page provides information about the teaching materials, including a circuit kit, that our team created for the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 grade outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The Synthetic Biology kit will be used by high school Science teachers in classrooms in the Pittsburgh Public School System. We have already tested the kit in several presentations given by the team to High School students studying on the Carnegie Mellon campus this summer.<br />
</p><br />
<p><br />
This was the schedule and audience of our presentations:<br />
</p><br />
<p><br />
<ol><li> July 18 and August 1: Presentations to rising junior and senior high school students who participated in the Summer Academy of Math and Science at Carnegie Mellon. <br />
"The Summer Academy for Mathematics and Science (SAMS) is a rigorous residential summer experience for good students who have a strong interest in math and science and want to become excellent students." An objective of SAMS is to contribute to the expansion of the pipeline of outstanding college-bound high school graduates with diverse backgrounds.<br />
</li><li> July 20: Presentation to high school students taking AP Biology at Carnegie Mellon and their teacher. <br />
</ol> <br />
</p><br />
<br />
<p><br />
In these presentations (<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team"> download here!</a>), we introduced Synthetic Biology and iGEM to the students. <br><br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905934" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe><br />
<br><br><br />
<br />
In conjunction with the presentation, we used the circuit kit to explain the main aspects of our research project and to demonstrate how the biosensor can be used to characterize a promoter. For a given set of electronic components, we measured and displayed graphical representations of the current/voltage. <br />
<br><br />
<br><br />
<b> Interactive Mini-game </b><br />
<br><br><br />
<img src ="https://static.igem.org/mediawiki/2012/f/f1/Minigame.png" width="385px" height="345px" align="right"> <br />
To encourage the students to interact and play with the circuit kit, we devised a mini-game which placed the students in our shoes: <b> as Synthetic Biologists using our BioBrick system to characterize new promoters. </b> <br><br><br />
We did this by giving the students a set of different resistors, and gave them the challenge to find the best promoter by mixing and matching these parts and characterizing them using our circuit kit. <br><br />
Students could then change the electronic components and observe the corresponding changes in current/voltage. In the process, we explained to the students the formal equivalence of the electronic components and Biobricks and of the current/voltage and measured fluorescence signals. We also explained to them the biological significance of the graphs obtained.<br />
</p><br />
<br />
<br><br />
<p><br />
The students who attended our presentations learned about:<br />
<ol><li> Synthetic biology and its relationship to Biology and Science and Engineering in general<br />
</li><li> Gene expression and the central dogma of molecular biology<br />
</li><li> How synthetic biologists tackle real-world problems<br />
</li><li> The iGEM competition and how our iGEM team's project enables one to measures the properties of promoters<br />
</li><li> The interdisciplinary nature of synthetic biology<br />
</li><li> The advantages and challenges of interdisciplinary work<br />
</li></ol><br />
</p><br />
<br />
<p> Photos from our summer presentations can be found <a href="https://www.dropbox.com/sh/7kqncwq63vay4za/5zUMzdUbNs"> here</a>. </p><br />
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Future Outreach Plans<br />
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<p><br />
The circuit is the basis for a kit to be used by high school Science teachers in classrooms in public schools in Pittsburgh. This is a means to incorporate Synthetic Biology in the HS curriculum. The kit is made available through the Lending Library of Science Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a>.<br />
<br><br />
We also came up with a teaching presentation to assist teachers in using our kits for teaching about Synthetic Biology. To download the presentation, please go to the Teaching Presentation portion of our Wiki.<br />
<br />
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<iframe src="http://www.slideshare.net/slideshow/embed_code/14905902" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe> <br />
<br><br />
</p><br />
<p><br />
The educational objectives of the classes in which the students use our Synthetic Biology kit are:<br />
<ol><li>Students will be able to give a definition of synthetic biology<br />
</li><li> Students will be able to identify one real-world application of synthetic biology <br />
</li><li> Students will be able to explain how technology is used to extend human abilities<br />
</li><li> Students will be able to recognize the correlation between the input and output of a biological or electronic circuit<br />
</li><li> Students will be able to recognize the advantages and limitations of using models to simulate processes that relate an input and its output<br />
</li><li> Students will be able to discuss the value of collaboration in interdisciplinary fields <br />
</li><li> Students will be able to discuss ethics aspects related to synthetic biology<br />
</ol> <br />
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The impact of synthetic biology depends on the number and quality of scientists making significant contributions to the field. Future scientists will rise from current high school students who are excited about science and gain a solid background in math and science in their formative years. To this end, we decided to raise the awareness of high school students about the interdisciplinary field of synthetic biology and to also teach them about the process of scientific research.<br><br />
As an additional outcome, the proposed methodology of using an electronic circuit equivalent for modeling biological phenomena can be replicated and used beyond the context of our current project.<br />
</p><br />
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<img src = "https://static.igem.org/mediawiki/2012/2/20/Outreachphoto1.JPG" align = "right" padding ="5px"><br />
<p><br />
We decided to create teaching materials for high school students inspired by our team’s research project. Our goal was that these materials can be easily used by a science teacher in a lecture in a Biology or Chemistry course to:<br />
<div class = "ol"><br />
<ol type = "1" compact> <br />
<li>Explain what Synthetic Biology is; </li><br />
<li>Illustrate the opportunities created by Synthetic Biology in improving human well being; </li><br />
<li>Discuss ethical concerns related to Synthetic Biology; </li><br />
<li>Enable the students to understand how our <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a> works.</li><br />
</ol><br />
</div><br />
</p><br />
<br />
<p><br />
To bridge the gap between the background of a high school student and the complexity of our project, we built an affordable, microcontroller-based, hardware platform and associated, open-source, digital simulation software. In designing the demonstration platform, we exploited the relationship between biological networks in synthetic biology and electronic circuits in electrical engineering. Specifically, we created a circuit kit that emulates in hardware our biological construct and in software both the response of the biological construct to specific cell conditions and the fluorescence measurement. It is important to note that the kit is <b>INTERACTIVE</b> (students can easily change electronic components to simulate different biological or external changes and the outcome of these changes), <b> RELATABLE</b> (the students can directly use the kit) and <b>EASILY SHARED AND IMPROVED</b> (the list of electronic components, circuit diagrams etc. are in the public domain and the software is open source).<br />
</p><br />
<br />
<p><br />
The teaching materials we have created, specifically a <a href="https://www.dropbox.com/s/n1bpb77einu26ko/iGEM_Summer_Presentation.pdf"> power point presentation</a> and an <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> electronic circuit kit</a>, have become part of the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The kits in the Library are loaned to high school teachers in the Pittsburgh area to be used in teaching Math and Science. We identified for the teachers how the use of our kit can help the High School students meet specific objectives from the <a href ="http://static.pdesas.org/content/documents/Academic_Standards_for_Science_and_Technology_and_Engineering_Education_%28Secondary%29.pdf">Pennsylvania Academic Standards for Science, Technology, and Engineering Education</a> and the <a href ="http://www.portal.state.pa.us/portal/server.pt/community/assessment_anchors/7440 ">Pennsylvania Assessment Anchors</a>. We have also tested the kit in several demonstrations in the Summer of 2012 to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> Summer Academy of Math and Science (SAMS)</a> at Carnegie Mellon.<br />
</p><br />
<br />
<p><br />
A very important original property of our approach to Human Practices stems from the fact that the teaching materials we created are available to teachers in any Pittsburgh Public School District who can borrow them from the Lending Library of Kits and use them even after the work of the current CMU iGEM team ends. Another original factor is the fact that we identified for the teachers which objectives from the Pennsylvania Academic Standards for Science, Technology and Engineering they can teach using the kit. This identification should eliminate the barrier to adoption of the kit by teachers faced with tight time schedules to cover these objectives.<br />
</p><br />
<p><br />
</p><br />
<h1 id="section1-1"> System Implemented with the Kit </h1><br />
<img src="https://static.igem.org/mediawiki/2012/f/f4/System_model.jpg" height="300" width="433" align="right"/><br />
<p><br />
As described <a href="https://2012.igem.org/Team:Carnegie_Mellon"> here</a>, our team engineered a fluorescence-based sensor that provides information on both transcription strength and translation efficiency of a promoter. The sensor is noninvasive, easily applied to a variety of promoters, and capable of providing results in a time frame that is short when compared to current technologies for the characterization of promoters. <br />
</p><br />
<p><br />
The sensor is based on the use of an RNA aptamer (termed Spinach) and a fluorogen activating protein (FAP). The complexes of Spinach (mRNA-DMHBI in the Figure) and FAP (FAP-MG in the Figure) with specific dyes, DFHBI and MG, respectively, are fluorescent. Measurements of the fluorescence intensity of these complexes enables one to determine the concentration of mRNA and expressed protein for a given promoter. Analysis of the fluorescence data with an appropriate model leads to the transcription strength and translation efficiency for each promoter.<br />
</p><br />
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<h1 id = "section1-2"><br />
The Hardware/Software Platform<br />
</h1><br />
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<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
<p><br />
</p><br />
</p><br />
<p><br />
The goal was to create a model of our <b><a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a></b> that clearly represents its main components and makes clear how the biosensor works. We also planned to enable the students to simulate changes in the “environment” and to observe the outcome of these changes. To achieve this goal, we built an affordable, microcontroller-based, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> hardware</a> platform and also developed an associated, open-source, simulation <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software"> software</a>. <br />
<br />
</p><br />
<p><br />
The combined hardware/software platform allows the students to directly manipulate electronic components, which are formal equivalents of the BioBricks used in our sensor, and to observe the effect of changing these components on the current or voltage output, which is the equivalent of the fluorescence intensity in our lab experiments. In using the kit, the students get a feel for how different promoters are compared using the biosensor; they can rank "virtual promoters" in the order of their strength. Students who use the kit gain hands-on experience and understand how all the parts of the biosensor work together to measure the mRNA and protein levels, without working in the wet lab.<br />
The figure on the right is a photograph of the hardware platform on which the correspondence between the biological components of the biosensor and the electronic components of the kit are identified.<br />
</p><br />
<p><br />
The software used in the platform is based on the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> model</a> derived for the analysis of the fluorescence data obtained with the biosensor. We have also created a GUI that allows the students to modify the parameters used in the model and to visualize on a computer display the current/voltage output (which is the equivalent of the fluorescence output in our experiments).<br />
</p><br />
</section><br />
<br />
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<header id = "header"><br />
<h1 id = "section1-3"><br />
Team Presentations to Groups of High School Students<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<br />
<p><br />
</p><br />
</p><br />
<p><br />
To obtain feedback for how high school students use the circuit kit, the team has given several presentations about synthetic biology and our project to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> SAMS</a> and in <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/apea.html"> AP Biology</a> at Carnegie Mellon University. <br />
We have also sought and obtained feedback on the kit from Dr. Janet Waldeck, Physics teacher at the Pittsburgh Allderdice High School in Pittsburgh. <br />
The feedback and input gained from these presentations was used to refine the kit. <br />
</p><br />
<br />
<br />
<br />
<h1> Broader Impact in Biological Modeling Methodology </h1><br />
<p><br />
The methodology used to build the electrical equivalent of the biological processes is not unique to the problem we are solving in this project. Starting from first principles modeling, one can use the methodology followed in our circuit kit implementation and emulate the behavior of the processes governing other biological phenomena by using simple controllers and circuit components. This shows that interdisciplinary training is not only desirable, but can also be beneficial for solving synthetic biology problems, thereby underscoring the importance of such training starting from high school through college.<br />
<br />
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<li class="toc-h1"><a href="#section1">Introduction</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">Overview</a></li><br />
<li><a href="#section1-2">Kit Protocols</a></li><br />
<li><a href="#section1-3">Cloning Protocol</a></li><br />
<li><a href="#section1-4">Gel Protocol</a></li><br />
<li><a href="#section1-5">Dosage Curve</a></li><br />
<li><a href="#section1-6">Time Lapse Protocol</a></li><br />
<li><a href="#section1-7">Materials used</a></li><br />
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<br />
<h1 id = "section 1-1">Overview</h1><br />
<id = "section1-1"><br />
<p><br />
Our original model was based on the assumption that the T7 RNA polymerase is constitutively expressed and thus that IPTG addition instantaneously “turns on” the expression of the mRNA and FAP (reactions 3-12 in Figure 1). <br />
In this model, reactions 3 - 7 involve mRNA. The T7 RNAP polymerase is not consumed in producing mRNA and mRNA is not consumed in producing the FAP. </p><p><br />
We assumed that the fluorescence signal is proportional to the concentration of the [mRNA-DFHBI]. The proportionality constant K includes factors specific to the fluorimeter settings and K was one of the variable parameters in our fitting algorithm.</p><p><br />
The dosage curve indicated that the dye binding reactions (6, 7 and 10, 11) are not rate-limiting and allowed us to measure the equilibrium constant K<sub>D</sub> for these reactions. K<sub>D</sub> is equal to the ratio of the “off” rate (k<sub>d</sub>) to “on” rate (k<sub>a</sub>). </p><p><br />
The degradation of [dye-mRNA] and [dye-FAP] complexes affects only the biological component of the complex and not the dye. We assumed that the two complexes degrade with the same rate constant, α and β, as their mRNA and FAP unbound counterparts, respectively.</p><br />
<p><br />
The model described above could not lead to good simulations of the time dependence of the fluorescence of the [mRNA-DFHBI] complex. The apparent exponential dependence of the [mRNA-DFHBI] on time could be rationalized if one includes in the model two additional reaction that account for the fact that in the regulatory mechanism the T7 RNA polymerase in the BL21(DE3) cell strain, there is a LacO site upstream of the promoter for the polymerase. We accounted for this process by including reactions 1 and 2 in the Figure 1. Reaction 1 represents the induction of the T7 RNAP by adding a fixed amount of IPTG and reaction 2 represents the degradation of T7 RNAP.<br />
</p><br />
<p><strong>Figure 1</strong><br><br />
<i><br />
Reaction 1: IPTG->T7RNAP+IPTG<br><br />
Reaction 2: T7RNAP->0<br><br />
Reaction 3: T7RNAP->mRNA+T7RNAP<br><br />
Reaction 4: mRNA->0<br><br />
Reaction 5: mRNA->FAP+mRNA<br><br />
Reaction 6: mRNA+DFHBI->[mRNA-DFHBI]<br><br />
Reaction 7: [mRNA-DFHBI]->mRNA+DFHBI<br><br />
Reaction 8: [mRNA-DFHBI]->0+DFHBI<br><br />
Reaction 9: [mRNA-DFHBI]->FAP+[mRNA-DFHBI]<br><br />
Reaction 10: FAP+MG->[FAP-MG]<br><br />
Reaction 11: [FAP-MG]->FAP+MG<br><br />
Reaction 12: FAP->0<br><br />
Reaction 13: [FAP-MG]->0+MG<br></i><br />
</i><br />
</p><br />
<p><br />
The following system of differential equations represent the chemical reactions in Figure 1.<br> <br />
<img src="https://static.igem.org/mediawiki/2012/8/89/CMUDifferentials.jpg"><br><br />
<strong>Figure 2</strong><br />
<br />
K<sub>D</sub>'s were taken from the original papers Szent-Gyorgi et al and Paige et al.<br />
</p><br />
<p><br />
The initial concentrations of dyes and IPTG are known. The [IPTG] value is constant. k<sub>1</sub> should be determined so that the steady state for T7RNAP is accurate. We implemented these equations in MATLAB using an ODE function and a stochastic simulation approach. <br />
</p><br />
<p align='center'><br />
<img src='https://static.igem.org/mediawiki/2012/a/af/CMU_modelexpanded.jpg' width='799' height='599'><br><br />
<strong>Figure 3</strong><br><br />
The quantities circled in red are measurable or approximated in our model. The only two physical quantities not known are the RNA and protein concentrations. These two can be solved by using a fitting function of the simulation.<br />
<br><br />
<br />
</p><br />
<br />
<p><br />
For low dye concentration, the fluorescence increases until all the dye is bound. One can take advantage of this property in a titration experiment to determine the maximum concentration of RNA or protein produced by the cell. <br />
</p><br />
<p align='center'><br />
<strong>All dye bound condition (Figure 4):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/5/54/ABDCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/4/44/ADBFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Total.jpg'><br><br />
It can be seen that the MG and DFHBI have been added in an amount to minimize the amount of free protein and RNA. This value can be determined experimentally.<br />
<br/><br />
</p><br><br />
<p align='center'><br />
<strong>Excess dye condition (Figure 5):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/b/bd/ExcessCell.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/6/60/ExcessFluorescence.jpg'><br><br />
<img src='https://static.igem.org/mediawiki/2012/f/fc/ExcessTotal.jpg'><br><br />
In this case, the dyes are in excess. This will cause the data to be too high and should be avoided experimentally.<br />
</p><br />
<p align='center'><br />
<strong>Limited Dye Added (Figure 6):</strong><br><br />
<img src='https://static.igem.org/mediawiki/2012/e/e8/Cell.jpg'><br><br />
In this case, MG isn't added in enough quantities. As it can be seen, the bound quantity levels off too soon with a characteristic curve that shows a sharp change in signal to a flat, consistent curve. By running a titration experiment, one can determine the moment when this condition no longer applies (when the protein or RNA binds to the dyes).<br />
</p><br />
<hr \><br />
<font size="2"><br />
<sup>[1]</sup> Szent-Gyorgyi, Christopher, Brigitte A. Schmidt, Yehuda Creeger, Gregory W. Fisher, Kelly L. Zakel, Sally Adler, James A J. Fitzpatrick, Carol A. Woolford, Qi Yan, Kalin V. Vasilev, Peter B. Berget, Marcel P. Bruchez, Jonathan W. Jarvik, and Alan Waggoner. "Fluorogen-activating Single-chain Antibodies for Imaging Cell Surface Proteins." Nature Biotechnology 26.2 (2007): 235-40. Print.<br />
<br \><br />
<sup>[2]</sup> Paige, J. S., K. Y. Wu, and S. R. Jaffrey. "RNA Mimics of Green Fluorescent Protein." Science 333.6042 (2011): 642-46. Print.<br />
</font><br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Outreach">Outreach</a><br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit">Circuit Kit</a><br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software">Software</a><br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team">Team Presentation</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Teaching">Teaching Presentation</a><br />
</li><br />
</ul> <br />
</li> <br />
</ul><br />
<br /><br /><br /><br />
<br />
<br />
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<a href="#" class="toc-link" id="toc-link"><span>&#9660;</span> Table of Contents</a><br />
<ul id="toc" class="toc" style="background: #ac9d74;"><br />
<li class="toc-h1"><a href="#section1">Model Documentation</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Inputs</a></li><br />
<li><a href="#section1-2">1.2 Walkthrough</a></li><br />
<li><a href="#section1-3">1.3 Outputs</a></li><br />
</ul><br />
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<p><br />
<h1 id = "section1-1">Inputs</h1><br />
</p><br />
<p><br />
The inputs to the model are the measurement tables of concentration of dye vs. time. Optional inputs to the model include an <i>in vitro</i> measurement of<br />
saturation of the dye, and measurements of the fluorescence of the dye with mRNA and protein synthesis turned off. The first optional measurement can be<br />
used to compare the <i>in vitro</i> fluorescence saturation levels with the <i>in vivo</i> fluorescence saturation levels in order to give a scaling factor for the all<br />
the measurements in the input. Estimations can be used in place of these to simplify the number of inputs. The second optional measurement can be used to<br />
determine the degradation rates of mRNA and protein.<br />
</p><br />
<p><br />
The equations for the model can be found <a rel="external" href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Derivations">here</a>.<br />
</p><br />
<p><br />
<br />
<h1 id = "section1-2" >Walkthrough</h1><br />
</p><br />
<p><br />
<strong>Fluoro2.m</strong><br />
</p><br />
<p><br />
This function is the function that is called to run the entire program. In addition, it takes the mRNA titration tables (modeldata) and converts it into<br />
fluorescent mRNA concentrations. It then passes the degradation data to the degradation functions, Degradation.m and DegradationP.m to return alpha2 and<br />
beta2, the degradation coefficients.<br />
</p><br />
<br />
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<pre><br />
<span class="lnr"> 1 </span><span class="Identifier">function</span> <span class="Identifier">[</span> PoPSans <span class="Identifier">]</span> = Fluoro2( matrix, matrix2, DNA, modeldata )<br />
<span class="lnr"> 2 </span><span class="Comment">%Fluoro 2: This function takes in a matrix of titrations and determines</span><br />
<span class="lnr"> 3 </span><span class="Comment">%both the possible percentage for bound mRNA as well as the actual</span><br />
<span class="lnr"> 4 </span><span class="Comment">%fluorescent mRNA concentration from fluorescent input values.</span><br />
<span class="lnr"> 5 </span><br />
<span class="lnr"> 6 </span><br />
<span class="lnr"> 7 </span>controlc = matrix(<span class="Statement">end</span>,:)<span class="Special">;</span> <span class="Comment">%concentration and fluorescence of the control</span><br />
<span class="lnr"> 8 </span>controlconc = controlc(<span class="Constant">1</span>)<span class="Special">;</span> <span class="Comment">%concentration of dye for the control</span><br />
<span class="lnr"> 9 </span>controldat = controlc(<span class="Constant">1</span>:<span class="Statement">end</span>)<span class="Special">;</span> <span class="Comment">%fluorescence of the control</span><br />
<span class="lnr">10 </span>maxc = <span class="Statement">max</span>(controldat)<span class="Special">;</span><br />
<span class="lnr">11 </span>concs = matrix(:,<span class="Constant">1</span>)<span class="Special">;</span> <span class="Comment">%concentrations of the dye in the wells</span><br />
<span class="lnr">12 </span>concs1 = concs(<span class="Constant">1</span>:(<span class="Statement">end</span> <span class="Statement">-</span> <span class="Constant">2</span>))<span class="Special">;</span><br />
<span class="lnr">13 </span>controlmax = maxc<span class="Special">;</span><br />
<span class="lnr">14 </span><br />
<span class="lnr">15 </span>Rf = <span class="Identifier">[]</span><span class="Special">;</span><br />
<span class="lnr">16 </span><br />
<span class="lnr">17 </span><span class="Statement">for</span> i = <span class="Constant">2</span>:<span class="Statement">size</span>(matrix, <span class="Constant">2</span>)<span class="Special">;</span><br />
<span class="lnr">18 </span> fluordat = matrix(:,i)<span class="Special">;</span> <span class="Comment">%fluoroscence data at some time point</span><br />
<span class="lnr">19 </span> fluordat1 = fluordat(<span class="Constant">1</span>:(<span class="Statement">end</span> <span class="Statement">-</span> <span class="Constant">2</span>))<span class="Special">;</span><br />
<span class="lnr">20 </span> s = fitoptions(<span class="String">'Method'</span>, <span class="String">'NonlinearLeastSquares'</span>, <span class="String">'Startpoint'</span>,<span class="Comment">...</span><br />
<span class="lnr">21 </span> <span class="Identifier">[</span>fluordat1(<span class="Statement">end</span>), <span class="Constant">1</span><span class="Statement">/</span>(controlconc)<span class="Identifier">]</span>)<span class="Special">;</span><br />
<span class="lnr">22 </span> g = fittype(<span class="String">'a * (1 - exp(b * (-x)))'</span>, <span class="String">'coefficients'</span>, {<span class="String">'a'</span>, <span class="String">'b'</span>},<span class="Comment">...</span><br />
<span class="lnr">23 </span> <span class="String">'options'</span>, s)<span class="Special">;</span><br />
<span class="lnr">24 </span> h = fit(concs1, fluordat1, g)<span class="Special">;</span><br />
<span class="lnr">25 </span> coeffvals = coeffvalues(h)<span class="Special">;</span><br />
<span class="lnr">26 </span> <span class="Comment">%figure(i);</span><br />
<span class="lnr">27 </span> <span class="Comment">%plot(h, concs1, fluordat1)</span><br />
<span class="lnr">28 </span> factorScale = coeffvals(<span class="Constant">1</span>) <span class="Statement">/</span> controlmax<span class="Special">;</span><br />
<span class="lnr">29 </span> <span class="Comment">%scaling factor from in vitro to in vivo</span><br />
<span class="lnr">30 </span> <span class="Statement">for</span> j = <span class="Constant">1</span>:<span class="Statement">size</span>(concs1)<span class="Special">;</span><br />
<span class="lnr">31 </span> <span class="Statement">if</span> <span class="Statement">abs</span>(h(concs1(j)) <span class="Statement">-</span> h(<span class="Constant">1</span>)) <span class="Statement">&lt;=</span> (<span class="Constant">.2</span> <span class="Statement">*</span> h(<span class="Constant">1</span>))<span class="Special">;</span><br />
<span class="lnr">32 </span> Rf(i <span class="Statement">-</span> <span class="Constant">1</span>) = concs1(j) <span class="Statement">*</span> factorScale<span class="Special">;</span><br />
<span class="lnr">33 </span> <span class="Statement">break</span><br />
<span class="lnr">34 </span> <span class="Statement">end</span><br />
<span class="lnr">35 </span> <span class="Statement">end</span><br />
<span class="lnr">36 </span><br />
<span class="lnr">37 </span><span class="Statement">end</span><br />
<span class="lnr">38 </span>time = matrix(<span class="Constant">1</span>,:)<span class="Special">;</span><br />
<span class="lnr">39 </span>fluortime = time(<span class="Constant">2</span>:<span class="Statement">size</span>(matrix, <span class="Constant">2</span>))<span class="Special">;</span><br />
<span class="lnr">40 </span><br />
<span class="lnr">41 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">42 </span><span class="Comment">%Section for Transcriptional Efficiency %</span><br />
<span class="lnr">43 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">44 </span><br />
<span class="lnr">45 </span>Rt = FluoroLR(Rf, fluortime)<span class="Special">;</span><br />
<span class="lnr">46 </span><br />
<span class="lnr">47 </span><br />
<span class="lnr">48 </span>alpha2 = Degradation(modeldata)<span class="Special">;</span><br />
<span class="lnr">49 </span><br />
<span class="lnr">50 </span>ETF = mRNAexpress(fluortime, DNA, Rt, alpha2)<span class="Special">;</span><br />
<span class="lnr">51 </span><span class="Comment">%ETF = mean(ETF);</span><br />
<span class="lnr">52 </span><br />
<span class="lnr">53 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">54 </span><span class="Comment">%Section for Translational Efficiency %</span><br />
<span class="lnr">55 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">56 </span><br />
<span class="lnr">57 </span>Pt = ProteinFunctions(matrix2)<span class="Special">;</span><br />
<span class="lnr">58 </span><br />
<span class="lnr">59 </span>beta2 = DegradationP(modeldata)<span class="Special">;</span><br />
<span class="lnr">60 </span><br />
<span class="lnr">61 </span>Tl = proteinexpress(DNA, Pt, ETF, alpha2, beta2)<span class="Special">;</span><br />
<span class="lnr">62 </span><br />
<span class="lnr">63 </span><span class="Comment">%Tl = proteinexpress(DNA, 1.6, ETF, alpha2, beta2)</span><br />
<span class="lnr">64 </span><br />
<span class="lnr">65 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">66 </span><span class="Comment">%Section for Polymerase per Second %</span><br />
<span class="lnr">67 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">68 </span><br />
<span class="lnr">69 </span>PoPSans = PoPS(alpha2, beta2, Pt, Tl)<span class="Special">;</span><br />
<span class="lnr">70 </span><br />
<span class="lnr">71 </span><span class="Statement">end</span><br />
</pre><br />
<br />
<br />
</div><br />
<br />
<br />
<p><br />
<strong>Degradation.m</strong><br />
</p><br />
<p><br />
This function takes in mRNA fluorescence data with mRNA synthesis turned off. This makes determining degradation rates easier, as all the change (as we<br />
will define degradation) in the mRNA concentration will be due to degradation. The function takes the data and fits a curve to the data, in the process<br />
calculating the degradation rate.<br />
</p><br />
<br />
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<span class="lnr"> 1 </span><span class="Identifier">function</span> <span class="Identifier">[</span> alpha2 <span class="Identifier">]</span> = Degradation ( modeldata )<br />
<span class="lnr"> 2 </span>dRi = modeldata(:,<span class="Constant">3</span>)<span class="Special">;</span><br />
<span class="lnr"> 3 </span>time = modeldata(:,<span class="Constant">1</span>)<span class="Special">;</span><br />
<span class="lnr"> 4 </span><span class="Comment">%dRi(length(dRi),:) = [];</span><br />
<span class="lnr"> 5 </span>C = <span class="Statement">max</span>(dRi)<span class="Special">;</span><br />
<span class="lnr"> 6 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr"> 7 </span><span class="Comment">%Differential Equation: dRi./dt = alpha * Rt%</span><br />
<span class="lnr"> 8 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr"> 9 </span><br />
<span class="lnr">10 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">11 </span><span class="Comment">%dRi is the fluorescence measurements of RNA during degradation only%</span><br />
<span class="lnr">12 </span><span class="Comment">%alpha is the desired result, so we solve the diff eq %</span><br />
<span class="lnr">13 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">14 </span><br />
<span class="lnr">15 </span><span class="Statement">for</span> i = <span class="Constant">1</span>:(length(dRi))<span class="Special">;</span><br />
<span class="lnr">16 </span> <span class="Statement">if</span> dRi(i) <span class="Statement">~</span>= <span class="Constant">0</span> <span class="Statement">&amp;&amp;</span> time(i) <span class="Statement">~</span>= <span class="Constant">0</span><br />
<span class="lnr">17 </span> alpha(i) = <span class="Statement">log</span>(dRi(i) <span class="Statement">./</span> C) <span class="Statement">./</span> time(i)<span class="Special">;</span><br />
<span class="lnr">18 </span> <span class="Statement">else</span><br />
<span class="lnr">19 </span> alpha(i) = <span class="Statement">log</span>(dRi(<span class="Constant">2</span>) <span class="Statement">./</span> C) <span class="Statement">./</span> time(<span class="Constant">2</span>)<span class="Special">;</span><br />
<span class="lnr">20 </span> <span class="Statement">end</span><br />
<span class="lnr">21 </span><span class="Statement">end</span><br />
<span class="lnr">22 </span>alpha<span class="Special">;</span><br />
<span class="lnr">23 </span>alpha2 = <span class="Statement">-</span><span class="Statement">mean</span>(alpha)<span class="Special">;</span><br />
<span class="lnr">24 </span><span class="Comment">%Rdegra = Rt * alpha2;</span><br />
<span class="lnr">25 </span><br />
<span class="lnr">26 </span><span class="Statement">end</span><br />
</pre><br />
<br />
</div><br />
<br />
<p><br />
<strong>DegradationP.m</strong><br />
</p><br />
<p><br />
This function has a similar role to Degradation.m. This function takes in protein fluorescence data with protein synthesis turned off. This function,<br />
similarly to Degradation.m, takes the data and fits a curve to the data.<br />
</p><br />
<p><br />
The degradation functions return alpha2 and beta2 to Fluoro2.m. Fluoro2.m then calls ProteinFunctions.m to convert the protein titration data to<br />
fluorescent protein concentrations.<br />
</p><br />
<br />
<br />
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<span class="lnr"> 1 </span><span class="Identifier">function</span> <span class="Identifier">[</span> beta2 <span class="Identifier">]</span> = DegradationP ( modeldata )<br />
<span class="lnr"> 2 </span><span class="Comment">%DegradationP</span><br />
<span class="lnr"> 3 </span><br />
<span class="lnr"> 4 </span>dPi = modeldata(:,<span class="Constant">6</span>)<span class="Special">;</span><br />
<span class="lnr"> 5 </span>timeP = modeldata(:,<span class="Constant">1</span>)<span class="Special">;</span><br />
<span class="lnr"> 6 </span><span class="Comment">%dRi ./ dt = alpha * Ri, solution: R = Ce^(alpha t) ./ alpha</span><br />
<span class="lnr"> 7 </span>C1 = <span class="Statement">max</span>(dPi)<span class="Special">;</span><br />
<span class="lnr"> 8 </span><span class="Comment">%ln(Ri ./ C) ./ t = alpha</span><br />
<span class="lnr"> 9 </span><span class="Statement">for</span> i = <span class="Constant">1</span>:length(dPi)<br />
<span class="lnr">10 </span> <span class="Statement">if</span> dPi(i) <span class="Statement">~</span>= <span class="Constant">0</span> <span class="Statement">&amp;&amp;</span> timeP(i) <span class="Statement">~</span>= <span class="Constant">0</span><br />
<span class="lnr">11 </span> beta(i) = <span class="Statement">log</span>(dPi(i) <span class="Statement">./</span> C1) <span class="Statement">./</span> timeP(i)<span class="Special">;</span><br />
<span class="lnr">12 </span> <span class="Statement">else</span><br />
<span class="lnr">13 </span> beta(i) = <span class="Statement">log</span>(dPi(<span class="Constant">2</span>) <span class="Statement">./</span> C1) <span class="Statement">./</span> timeP(<span class="Constant">2</span>)<span class="Special">;</span><br />
<span class="lnr">14 </span> <span class="Statement">end</span><br />
<span class="lnr">15 </span><span class="Statement">end</span><br />
<span class="lnr">16 </span><br />
<span class="lnr">17 </span>beta2 = <span class="Statement">-</span><span class="Statement">mean</span>(beta)<span class="Special">;</span><br />
<span class="lnr">18 </span><span class="Comment">%Pdegra = beta2 * Pt;</span><br />
<span class="lnr">19 </span><span class="Statement">end</span><br />
</pre><br />
<br />
</div><br />
<br />
<p><br />
<strong>ProteinFunctions.m</strong><br />
</p><br />
<p><br />
This function does the same thing as Fluoro2.m with the mRNA titration data. It returns fluorescent protein concentrations over time.<br />
</p><br />
<p><br />
Fluoro2.m takes the fluorescent protein and fluorescent mRNA concentrations and passes them to FluoroLR.m and FluoroLP.m to convert to total protein and<br />
total mRNA concentrations.<br />
</p><br />
<br />
<br />
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<span class="lnr"> 1 </span><span class="Identifier">function</span> <span class="Identifier">[</span> Pt <span class="Identifier">]</span> = ProteinFunctions( matrix)<br />
<span class="lnr"> 2 </span><span class="Comment">%UNTITLED Summary of this function goes here</span><br />
<span class="lnr"> 3 </span><span class="Comment">% Detailed explanation goes here</span><br />
<span class="lnr"> 4 </span><br />
<span class="lnr"> 5 </span>controlc = matrix(<span class="Statement">end</span>,:)<span class="Special">;</span> <span class="Comment">%concentration and fluorescence of the control</span><br />
<span class="lnr"> 6 </span>controlconc = controlc(<span class="Constant">1</span>)<span class="Special">;</span> <span class="Comment">%concentration of dye for the control</span><br />
<span class="lnr"> 7 </span>controldat = controlc(<span class="Constant">1</span>:<span class="Statement">end</span>)<span class="Special">;</span> <span class="Comment">%fluorescence of the control</span><br />
<span class="lnr"> 8 </span>maxc = <span class="Statement">max</span>(controldat)<span class="Special">;</span><br />
<span class="lnr"> 9 </span>concs = matrix(:,<span class="Constant">1</span>)<span class="Special">;</span> <span class="Comment">%concentrations of the dye in the wells</span><br />
<span class="lnr">10 </span>concs1 = concs(<span class="Constant">1</span>:(<span class="Statement">end</span> <span class="Statement">-</span> <span class="Constant">2</span>))<span class="Special">;</span><br />
<span class="lnr">11 </span>controlmax = maxc<span class="Special">;</span><br />
<span class="lnr">12 </span><br />
<span class="lnr">13 </span>Pf = <span class="Identifier">[]</span><span class="Special">;</span><br />
<span class="lnr">14 </span><br />
<span class="lnr">15 </span><span class="Statement">for</span> i = <span class="Constant">2</span>:<span class="Statement">size</span>(matrix, <span class="Constant">2</span>)<span class="Special">;</span><br />
<span class="lnr">16 </span> fluordat = matrix(:,i)<span class="Special">;</span> <span class="Comment">%fluoroscence data at some time point</span><br />
<span class="lnr">17 </span> fluordat1 = fluordat(<span class="Constant">1</span>:(<span class="Statement">end</span> <span class="Statement">-</span> <span class="Constant">2</span>))<span class="Special">;</span><br />
<span class="lnr">18 </span><br />
<span class="lnr">19 </span> s = fitoptions(<span class="String">'Method'</span>, <span class="String">'NonlinearLeastSquares'</span>, <span class="String">'Startpoint'</span>,<span class="Comment">...</span><br />
<span class="lnr">20 </span> <span class="Identifier">[</span>fluordat1(<span class="Statement">end</span>), <span class="Constant">1</span><span class="Statement">/</span>(controlconc)<span class="Identifier">]</span>)<span class="Special">;</span><br />
<span class="lnr">21 </span><br />
<span class="lnr">22 </span> g = fittype(<span class="String">'a * (1 - exp(b * (-x)))'</span>, <span class="String">'coefficients'</span>, {<span class="String">'a'</span>, <span class="String">'b'</span>},<span class="Comment">...</span><br />
<span class="lnr">23 </span> <span class="String">'options'</span>, s)<span class="Special">;</span><br />
<span class="lnr">24 </span><br />
<span class="lnr">25 </span> h = fit(concs1, fluordat1, g)<span class="Special">;</span><br />
<span class="lnr">26 </span> coeffvals = coeffvalues(h)<span class="Special">;</span><br />
<span class="lnr">27 </span> <span class="Comment">%figure(i);</span><br />
<span class="lnr">28 </span> <span class="Comment">%plot(h, concs1, fluordat1)</span><br />
<span class="lnr">29 </span> factorScale = coeffvals(<span class="Constant">1</span>) <span class="Statement">/</span> controlmax<span class="Special">;</span><span class="Comment">...</span><br />
<span class="lnr">30 </span> <span class="Comment">%scaling factor from in vitro to in vivo</span><br />
<span class="lnr">31 </span> <span class="Statement">for</span> j = <span class="Constant">1</span>:<span class="Statement">size</span>(concs1)<span class="Special">;</span><br />
<span class="lnr">32 </span> <span class="Statement">if</span> <span class="Statement">abs</span>(h(concs1(j)) <span class="Statement">-</span> h(<span class="Constant">1</span>)) <span class="Statement">&lt;=</span> (<span class="Constant">.2</span> <span class="Statement">*</span> h(<span class="Constant">1</span>))<span class="Special">;</span><br />
<span class="lnr">33 </span> Pf(i <span class="Statement">-</span> <span class="Constant">1</span>) = concs1(j) <span class="Statement">*</span> factorScale<span class="Special">;</span><br />
<span class="lnr">34 </span> <span class="Statement">break</span><br />
<span class="lnr">35 </span> <span class="Statement">end</span><br />
<span class="lnr">36 </span> <span class="Statement">end</span><br />
<span class="lnr">37 </span><br />
<span class="lnr">38 </span><span class="Statement">end</span><br />
<span class="lnr">39 </span>time = matrix(<span class="Constant">1</span>,:)<span class="Special">;</span><br />
<span class="lnr">40 </span>fluortime = time(<span class="Constant">2</span>:<span class="Statement">size</span>(matrix, <span class="Constant">2</span>))<span class="Special">;</span><br />
<span class="lnr">41 </span><br />
<span class="lnr">42 </span>Pt = FluoroLP (Pf, fluortime)<span class="Special">;</span><br />
<span class="lnr">43 </span><br />
<span class="lnr">44 </span><span class="Statement">end</span><br />
<span class="lnr">45 </span><br />
</pre><br />
</div><br />
<br />
<p><br />
<strong>FluoroLR.m</strong><br />
</p><br />
<p><br />
This function takes in fluorescent mRNA concentrations and converts it to mRNA concentrations using first-order chemical reactions. One dye molecule will<br />
bond to one mRNA molecule, creating an mRNA-dye complex. This leads to a rather simple conversion using the known dye concentration.<br />
</p><br />
\begin{equation}K_{D_R} = \frac{[R_f]}{([R]_0 - [R_f])([D_R]_0 - [R_f])}\end{equation}<br />
<p><br />
where KDR is the dissociation constant, $[Rf]$ is the fluorescent mRNA concentration, $[R]$ is the mRNA concentration, and $[D_R]$ is the dye concentration.<br />
</p><br />
<br />
<br />
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<pre><br />
<span class="lnr"> 1 </span><span class="Identifier">function</span> <span class="Identifier">[</span>Rt<span class="Identifier">]</span> = FluoroLR (Rf, concentrations)<br />
<span class="lnr"> 2 </span><span class="Comment">%DFHBI = 1*10^(-9); %concentration of dye</span><br />
<span class="lnr"> 3 </span><span class="Comment">%Rfmax = 1*10^(-10);%max concentration of the mRNA</span><br />
<span class="lnr"> 4 </span>KD = <span class="Constant">464</span><span class="Statement">*</span><span class="Constant">10</span><span class="Statement">^</span>(<span class="Statement">-</span><span class="Constant">9</span>)<span class="Special">;</span><br />
<span class="lnr"> 5 </span><br />
<span class="lnr"> 6 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr"> 7 </span><span class="Comment">%Relates the mRNA fluorescence levels with the total mRNA levels%</span><br />
<span class="lnr"> 8 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr"> 9 </span><br />
<span class="lnr">10 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">11 </span><span class="Comment">%fluorescence is measured, Rf is the fluorescent mRNA concentration%</span><br />
<span class="lnr">12 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">13 </span><br />
<span class="lnr">14 </span><span class="Comment">%a = max(fluorescence) ./ Rfmax;</span><br />
<span class="lnr">15 </span><span class="Comment">%Rf = zeros(length(fluorescence) - 1, 1);</span><br />
<span class="lnr">16 </span><span class="Comment">%for i = 1:(length(fluorescence) - 1)</span><br />
<span class="lnr">17 </span><span class="Comment">% Rf(i) = fluorescence(i) ./ a; </span><br />
<span class="lnr">18 </span><span class="Comment">%end</span><br />
<span class="lnr">19 </span><br />
<span class="lnr">20 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">21 </span><span class="Comment">%Rt is the total mRNA%</span><br />
<span class="lnr">22 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">23 </span><br />
<span class="lnr">24 </span>Rt = <span class="Identifier">[]</span><span class="Special">;</span><br />
<span class="lnr">25 </span><span class="Statement">for</span> j = <span class="Constant">1</span>:(length(Rf))<br />
<span class="lnr">26 </span> Rt(j) = Rf(j) <span class="Statement">*</span> (<span class="Constant">1</span> <span class="Statement">+</span> KD <span class="Statement">./</span> (concentrations(j) <span class="Statement">-</span> Rf(j)))<span class="Special">;</span><br />
<span class="lnr">27 </span><span class="Statement">end</span><br />
<span class="lnr">28 </span><br />
<span class="lnr">29 </span><span class="Statement">end</span><br />
</pre><br />
</div><br />
<br />
<p><br />
<strong>FluoroLP.m</strong><br />
</p><br />
<p><br />
This function has a similar role to FluoroLR.m, except using fluorescent protein concentrations and converting it to protein concentration.<br />
</p><br />
<br />
<br />
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<pre><br />
<span class="lnr"> 1 </span><span class="Identifier">function</span> <span class="Identifier">[</span>Pt<span class="Identifier">]</span> = FluoroLP (Pf, concentrationsP)<br />
<span class="lnr"> 2 </span>MAG = <span class="Constant">1</span><span class="Statement">*</span><span class="Constant">10</span><span class="Statement">^</span>(<span class="Statement">-</span><span class="Constant">9</span>)<span class="Special">;</span> <span class="Comment">%concentration of dye</span><br />
<span class="lnr"> 3 </span>Pfmax = <span class="Constant">1</span><span class="Statement">*</span><span class="Constant">10</span><span class="Statement">^</span>(<span class="Statement">-</span><span class="Constant">10</span>)<span class="Special">;</span> <span class="Comment">%max concentration of the protein</span><br />
<span class="lnr"> 4 </span>KD2 = <span class="Constant">464</span><span class="Statement">*</span><span class="Constant">10</span><span class="Statement">^</span>(<span class="Statement">-</span><span class="Constant">9</span>)<span class="Special">;</span><br />
<span class="lnr"> 5 </span><br />
<span class="lnr"> 6 </span><br />
<span class="lnr"> 7 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr"> 8 </span><span class="Comment">%Relates the protein fluorescence levels with the total protein levels%</span><br />
<span class="lnr"> 9 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">10 </span><br />
<span class="lnr">11 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">12 </span><span class="Comment">%fluorescence is measured, Pf is the fluorescent protein concentration%</span><br />
<span class="lnr">13 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">14 </span><br />
<span class="lnr">15 </span><span class="Comment">%b = max(fluorescenceP) ./ Pfmax;</span><br />
<span class="lnr">16 </span><span class="Comment">%Pf = zeros(length(fluorescenceP), 1);</span><br />
<span class="lnr">17 </span><span class="Comment">%for i = 1:(length(fluorescenceP))</span><br />
<span class="lnr">18 </span><span class="Comment">% Pf(i) = fluorescenceP(i) ./ b;</span><br />
<span class="lnr">19 </span><span class="Comment">%end</span><br />
<span class="lnr">20 </span><br />
<span class="lnr">21 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">22 </span><span class="Comment">%Pt is the total protein concentration%</span><br />
<span class="lnr">23 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">24 </span><br />
<span class="lnr">25 </span>Pt = <span class="Identifier">[]</span><span class="Special">;</span><br />
<span class="lnr">26 </span><span class="Statement">for</span> j = <span class="Constant">1</span>:(length(concentrationsP))<br />
<span class="lnr">27 </span> Pt(j) = Pf(j) <span class="Statement">*</span> (<span class="Constant">1</span> <span class="Statement">+</span> KD2 <span class="Statement">./</span> (concentrationsP(j) <span class="Statement">-</span> Pf(j)))<span class="Special">;</span><br />
<span class="lnr">28 </span><span class="Statement">end</span><br />
<span class="lnr">29 </span><span class="Statement">end</span><br />
</pre><br />
</div><br />
<br />
<br />
<p><br />
<strong>mRNAexpress.m</strong><br />
</p><br />
<p><br />
Fluoro2.m then takes the total mRNA concentrations passed by FluoroLR.m and passes it to mRNAexpress.m, which calculates the transcriptional efficiency.<br />
This is done via the differential equation<br />
</p><br />
<br />
\begin{equation}\frac{d[R]}{dt} = Ts \cdot [D] - \alpha \cdot [R]\end{equation}<br />
<br />
<p><br />
to which the solution is<br />
</p><br />
<p><br />
\begin{equation} Ts = \frac{[R] \cdot \alpha}{[D] \cdot (1 - e^{-\alpha \cdot t})}\end{equation}<br />
</p><br />
<p><br />
where $[R]$ is mRNA concentration, $Ts$ is transcriptional efficiency, $[D]$ is DNA concentration, and $\alpha$ is the mRNA degradation coefficient.<br />
</p><br />
<br />
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<span class="lnr"> 1 </span><span class="Identifier">function</span> <span class="Identifier">[</span> ETF <span class="Identifier">]</span> = mRNAexpress ( fluortime, DNA, Rt, alpha2 )<br />
<span class="lnr"> 2 </span><span class="Comment">%mRNA expression model</span><br />
<span class="lnr"> 3 </span><br />
<span class="lnr"> 4 </span><span class="Comment">%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr"> 5 </span><span class="Comment">%DNA is measured%</span><br />
<span class="lnr"> 6 </span><span class="Comment">%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr"> 7 </span><br />
<span class="lnr"> 8 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr"> 9 </span><span class="Comment">%ET is the transcriptional efficiency, ETF is the average%</span><br />
<span class="lnr">10 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr">11 </span><br />
<span class="lnr">12 </span><span class="Statement">for</span> k = <span class="Constant">1</span>:(length(Rt))<br />
<span class="lnr">13 </span> <span class="Statement">if</span> fluortime(k) <span class="Statement">~</span>= <span class="Constant">0</span><br />
<span class="lnr">14 </span> ET(k) = Rt(k) <span class="Statement">*</span> alpha2 <span class="Statement">./</span> DNA <span class="Statement">./</span>(<span class="Constant">1</span> <span class="Statement">-</span> <span class="Statement">exp</span>(<span class="Statement">-</span>alpha2 <span class="Statement">*</span> (fluortime(k))))<span class="Special">;</span><br />
<span class="lnr">15 </span> <span class="Statement">else</span><br />
<span class="lnr">16 </span> ET(k) = Rt(k) <span class="Statement">*</span> alpha2 <span class="Statement">./</span> DNA <span class="Statement">./</span>(<span class="Constant">1</span> <span class="Statement">-</span> <span class="Statement">exp</span>(<span class="Statement">-</span>alpha2 <span class="Statement">*</span> (<span class="Constant">.2</span>)))<span class="Special">;</span><br />
<span class="lnr">17 </span> <span class="Statement">end</span><br />
<span class="lnr">18 </span><span class="Statement">end</span><br />
<span class="lnr">19 </span>ET<span class="Special">;</span><br />
<span class="lnr">20 </span>ET = ET(<span class="Constant">2</span>:<span class="Statement">end</span>)<span class="Special">;</span><br />
<span class="lnr">21 </span>ETF = <span class="Statement">mean</span>(ET)<span class="Special">;</span><br />
<span class="lnr">22 </span><span class="Comment">%ETF = ET;</span><br />
<span class="lnr">23 </span><span class="Statement">end</span><br />
</pre><br />
</div><br />
<br />
<br />
<p><br />
<strong>proteinexpress.m</strong><br />
</p><br />
<p><br />
Fluoro2.m takes the transcriptional efficiency from mRNAexpress.m, total protein concentrations from FluoroLP.m, and alpha2 and beta2 from Degradation.m<br />
and DegradationP.m, and passes them to proteinexpress.m. proteinexpress.m computes the translational efficiency using the differential equation<br />
</p><br />
<p><br />
\begin{equation}\frac{d[P]}{dt} = [R] \cdot Tl - \beta \cdot [P]\end{equation}<br />
</p><br />
<p><br />
to which the solution is<br />
</p><br />
<p><br />
\begin{equation}Tl = \frac{[P]}{\frac{Ts \cdot [D]}{(\alpha \cdot \beta)} \cdot (1 - e^{-\beta \cdot t}) - \frac{Ts \cdot [D]}{\alpha \cdot (-\alpha + \beta)} \cdot (e^{-\alpha \cdot t} - e^{-\beta \cdot t})} \label{eq:Tl}\end{equation}<br />
</p><br />
<p><br />
where Tl is translational efficiency, beta is the protein degradation coefficient, and [P] is the protein concentration.<br />
</p><br />
<br />
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<span class="lnr"> 1 </span><span class="Identifier">function</span> <span class="Identifier">[</span> Tl <span class="Identifier">]</span> = proteinexpress (DNA, Pt, ETF, alpha2, beta2)<br />
<span class="lnr"> 2 </span><span class="Comment">%proteinexpress</span><br />
<span class="lnr"> 3 </span><br />
<span class="lnr"> 4 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr"> 5 </span><span class="Comment">%differential equation comes from: dP./dt = Trans * RNA - beta * P%</span><br />
<span class="lnr"> 6 </span><span class="Comment">%want to solve for Trans, the translational efficiency %</span><br />
<span class="lnr"> 7 </span><span class="Comment">%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%</span><br />
<span class="lnr"> 8 </span><br />
<span class="lnr"> 9 </span><span class="Statement">for</span> k = <span class="Constant">1</span>:length(Pt)<br />
<span class="lnr">10 </span> Trans(k) = Pt(k) <span class="Statement">./</span> (ETF <span class="Statement">*</span> DNA <span class="Statement">./</span> (alpha2 <span class="Statement">*</span> beta2) <span class="Statement">*</span><span class="Comment">...</span><br />
<span class="lnr">11 </span> (<span class="Constant">1</span> <span class="Statement">-</span> <span class="Statement">exp</span>(<span class="Statement">-</span>beta2 <span class="Statement">*</span> (k <span class="Statement">-</span> <span class="Constant">1</span>))) <span class="Statement">-</span> ETF <span class="Statement">*</span> DNA <span class="Statement">./</span> (alpha2 <span class="Statement">*</span><span class="Comment">...</span><br />
<span class="lnr">12 </span> (<span class="Statement">-</span>alpha2 <span class="Statement">+</span> beta2)) <span class="Statement">*</span> (<span class="Statement">exp</span>(<span class="Statement">-</span>alpha2 <span class="Statement">*</span> (k <span class="Statement">-</span> <span class="Constant">1</span>)) <span class="Statement">-</span> <span class="Statement">exp</span>(<span class="Statement">-</span>beta2 <span class="Statement">*</span> (k <span class="Statement">-</span> <span class="Constant">1</span>))))<span class="Special">;</span><br />
<span class="lnr">13 </span><span class="Statement">end</span><br />
<span class="lnr">14 </span><br />
<span class="lnr">15 </span><span class="Comment">%for k = 1:length(ETF)</span><br />
<span class="lnr">16 </span><span class="Comment">% Pt(k) = Trans * (ETF(k) * DNA ./ (alpha2 * beta2) * (1 -...</span><br />
<span class="lnr">17 </span><span class="Comment">% exp(-beta2 * (k - 1))) - ETF(k) * DNA ./ (alpha2 *...</span><br />
<span class="lnr">18 </span><span class="Comment">% (-alpha2 + beta2)) * (exp(-alpha2 * (k - 1)) - ...</span><br />
<span class="lnr">19 </span><span class="Comment">% exp(-beta2 * (k - 1))));</span><br />
<span class="lnr">20 </span><span class="Comment">% </span><br />
<span class="lnr">21 </span><span class="Comment">%end</span><br />
<span class="lnr">22 </span><br />
<span class="lnr">23 </span>Tl = <span class="Statement">mean</span>(Trans)<span class="Special">;</span><br />
<span class="lnr">24 </span><span class="Statement">end</span><br />
</pre><br />
</div><br />
<br />
<p><br />
<strong>PoPS.m</strong><br />
</p><br />
<p><br />
Fluoro2.m passes to the final function alpha2 and beta2 from Degradation.m and DegradationP.m, total protein concentration from FluoroLP.m, and<br />
translational efficiency from proteinexpress.m. PoPS.m calculates the approximate polymerase per second using the equation<br />
</p><br />
<p><br />
\begin{equation}PoPS = \frac{\alpha \cdot \beta \cdot [P]}{n \cdot Tl} \label{eq:PoPS}\end{equation}<br />
</p><br />
<p><br />
where n is the approximate number of the promoters of interest in a cell (i.e., plasmid copy).<br />
</p><br />
<br />
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<span class="lnr">1 </span><span class="Identifier">function</span> <span class="Identifier">[</span> PoPS <span class="Identifier">]</span> = PoPS( alpha2, beta2, Pt, Tl )<br />
<span class="lnr">2 </span><span class="Comment">%This function calculates Polymerase per second given a few parameters</span><br />
<span class="lnr">3 </span><span class="Comment">%This equation is valid at steady state.</span><br />
<span class="lnr">4 </span><br />
<span class="lnr">5 </span>n = <span class="Constant">1</span><span class="Special">;</span><br />
<span class="lnr">6 </span>PoPS = alpha2 <span class="Statement">*</span> beta2 <span class="Statement">*</span> Pt <span class="Statement">./</span> (n <span class="Statement">*</span> Tl)<span class="Special">;</span><br />
<span class="lnr">7 </span><br />
<span class="lnr">8 </span><span class="Statement">end</span><br />
</pre><br />
</div><br />
<p><br />
<strong> </strong><br />
</p><br />
<br />
<p><br />
<h1 id = "section1-3">Outputs</h1><br />
</p><br />
<br /><br />
<br />
<p><br />
The model outputs polymerase per second, although transcriptional efficiency and translational efficiency are also important factors in the model.<br />
Derivations of these equations can be found on the <a href = "https://2012.igem.org/Team:Carnegie_Mellon/Mod-Derivations">derivations page</a>.<br />
</p><br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Mod-DerivationsTeam:Carnegie Mellon/Mod-Derivations2012-10-27T03:33:45Z<p>Ychoo: </p>
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<a href="#" class="toc-link" id="toc-link"><span>&#9660;</span> Table of Contents</a><br />
<ul id="toc" class="toc" style="background: #ac9d74;"><br />
<li class="toc-h1"><a href="#section1">1. Documentation</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Preface</a></li><br />
<li><a href="#section1-2">1.2 Experimental Data Analysis</a></li><br />
<li><a href="#section1-3">1.3 Equilibrium Constants</a></li><br />
<li><a href="#section1-4">1.4 Degradation</a></li><br />
<li><a href="#section1-5">1.5 mRNA Expression</a></li><br />
<li><a href="#section1-6">1.6 Protein Expression</a></li><br />
<li><a href="#section1-7">1.7 Polymerase Per Second</a></li><br />
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<body><br />
<h1 id = "section1-1">Documentation Preface</h1><br />
<p>The documentation of the model consists of the derivations of all the equations used to create the model. Each equation contributes a piece of the picture which ultimately results in the calculations of important cell characteristics. These equations live in the Matlab model that can be found <a rel="external" href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Matlab">here</a>. <br />
The characteristics we are measuring include transcriptional strength, <i>Ts </i> \eqref{eq:eR}, translational efficiency, <i>Tl </i> \eqref{eq:Tl}, and Polymerase Per Second, <i> PoPS</i> \eqref{eq:PoPS}.<br />
</p><br />
<br />
Note: We derived equations for the model to fit the data that we obtained experimentally, while the Matlab code has even broader application and can be applied to several different experimental setups (e.g., measurement of fluorescence of both RNA and protein in the presence of degradation only, or both synthesis and degradation). These equations formed the foundation that helped extract some important cellular characteristics from the raw data that we took.<br />
<br /><br />
<br /><br />
<br />
<h1 id = "section1-2">Experimental Data Analysis</h1><br />
<br /><br />
<p><br />
Let fluorescent mRNA and protein concentration (concentration of the mRNA/dye and protein/dye complexes) be represented by $[R_f]$ and $[P_f]$, respectively. They are related directly to the fluorescence level, which we will label $F_r$ and $F_p$. Thus, we can write<br />
</p><br />
<br />
\begin{equation}{F_r = k_r \cdot [R_f]\cdot (S_r)}\end{equation}<br />
<br />
\begin{equation}{F_p = k_p \cdot [P_f] \cdot (S_p)}\end{equation}<br />
<br />
<p><br />
where $S_r$ and $S_p$ are scaling factors for mRNA and protein, respectively, and $k_r$ and $k_p$ are constants that transform fluorescence to mRNA and protein concentrations.<br />
</p><br />
<br />
<p><br />
In the experiment, one uses a plate reader with varying concentration of the dyes in rows and varying time measurements in columns. The following image represents this.<br />
</p><br />
<img src = "https://static.igem.org/mediawiki/2012/0/0f/DyePicture.png" height = "400" width = "350" ><br />
<p><br />
We will also have another row for <i> in vitro</i> measurements. From this row we will graph the fluorescence versus the dye concentration, and the fluorescence will level off at some saturation point. Because the saturation point <i> in vitro</i> will be greater than the saturation point <i> in vivo</i>, we must scale all the fluorescence measurements we find <i> in vivo </i>, which is the importance of $S_r$ and $S_p$. <br />
</p><br />
<p><br />
At this point we will find out the scaling factors $S_r$ and $S_p$. Step 1 is to put samples into the plate reader and take more samples of the same concentration and measure them <i> in vitro</i>. Then, we will measure all the wells at the same time point, and find the saturation fluorescence of the <i> in vitro</i> and the <i> in vivo </i> wells. Dividing the two gives us the $S_r$ and $S_p$.<br />
</p><br />
<p><br />
At each time point we will graph the <i> in vivo </i> fluorescence vs. dye concentrations and find the first dye concentration where saturation occurs. This dye concentration is thus the mRNA/protein total concentration, as we will assume that there will be a 1-1 correspondence of dye and mRNA/protein. We then multiply each by the scaling factor $S_r$ or $S_p$ to get the actual mRNA.<br />
</p><br />
<br\><br />
<br />
<h1 id = "section1-3">Equilibrium Constants</h1><br />
<br /><br /><br />
<p><br />
To check, we can find the fluorescent mRNA concentrations from the mRNA values we obtained in vivo. General first order chemical reactions begin (theoretically):<br />
</p><br />
<br />
\begin{equation}\alpha [A] + \beta [B] \leftrightarrow \gamma [AB]\end{equation}<br />
<p><br />
where $\alpha$, $\beta$, $\gamma$ are coefficients describing the ratio of molecules of $[A]$ and $[B]$ needed to synthesize $[AB]$. $[A]$, $[B]$, and $[AB]$ are different molecule concentrations. After some time, there will be some equilibrium where some amount of $[A]$ and $[B]$ become $[AB]$. So then, the equation at equilibrium becomes:<br />
</p><br />
<br />
<p><br />
\begin{equation}(\alpha[A] - \gamma [AB]) + (\beta[B] - \gamma [AB]) \leftrightarrow \gamma [AB]\label{eq:equi}\end{equation} <br />
</p><br />
<p><br />
We will assume that $\alpha$, $\beta$, and $\gamma$ are all equal to 1. Our $[A]$ will be mRNA/protein and $[B]$ will be the dye concentrations. mRNA dye, which is DFHBI, will be $[D_R]$ and protein dye, which is malachite green (MG), will be $[D_P]$. $[R]_0$ and $[P]_0$ are the initial concentrations of RNA and protein, respectively. Our equations are thus:<br />
</p><br />
<p><br />
\begin{equation}([R]_0 - [R_f]) + ([D_R] - [R_f]) \leftrightarrow ([R_f])\end{equation}<br />
\begin{equation}([P]_0 - [P_f]) + ([D_P] - [P_f]) \leftrightarrow ([P_f])\end{equation} <br />
</p><br />
<p><br />
The equilibrium constant for RNA, $K_{D_R}$ is then defined as the product of the reaction product concentrations over the reactant concentrations. We will take the equilibrium constant at equilibrium, so from equation \eqref{eq:equi}, we can determine the equilibrium constant. We will have $[A]_0$ and $[B]_0$ instead of $[A]$ and $[B]$ to signify the initial concentrations of $[A]$ and $[B]$.<br />
</p><br />
\begin{equation}K_{D_R} = \frac{[AB]}{([A]_0 - [AB]) ([B]_0 - [AB])}\end{equation} <br />
<p><br />
Now inputting our variables for mRNA expression, once again using $[R]_0$ and $[D_R]_0$ to signify initial concentration of $[R]$ and $[D_R]$:<br />
</p><br />
<p><br />
\begin{equation}K_{D_R} = \frac{[R_f]}{([R]_0 - [R_f])([D_R]_0 - [R_f])} \label{eq:8}\end{equation}<br />
</p><br />
<p><br />
we can solve for $[Rf]$ using a quadratic equation based off of \eqref{eq:8}.<br />
</p><br />
<p><br />
\begin{equation}[R_f]^2 \cdot K_{D_R} - [R_f]\cdot [K_{D_R}([R] + D_R) + 1] + K_{D_R} \cdot [R] \cdot {D_R} = 0\end{equation}<br />
</p><br />
\begin{equation}[R_f] = \frac{[K_{D_R}([R][D_R]) + 1] \pm \sqrt{[K_{D_R}([R][D_R]) + 1]^2 - 4 \cdot (K_{D_R}) \cdot (K_{D_R}[R][D_R])}}{2 \cdot K_{D_R}}\end{equation} <br />
<p><br />
We can apply the similar procedure for determining the protein concentration.<br />
</p><br />
<p><br />
<br />
</p><br />
<br /><br />
<br />
<h1 id = "section1-4">Degradation</h1><br />
<br /><br />
<p><br />
Degradation occurs for both mRNA and protein. After shutting off production of mRNA/protein, one can measure the degradation coefficient. Some intuition<br />
reveals that the amount that is degraded is proportional to the amount of mRNA/protein that is present. We will let $\frac{d[R]_D}{dt}$ be the change in the concentration of RNA, and $\alpha$ be the degradation coefficient determining the fraction of RNA that will be degraded in time.<br />
</p><br />
<p><br />
\begin{equation}\frac{d[R]_D}{dt} = -\alpha \cdot [R]\end{equation} <br />
</p><br />
<p><br />
Protein often has another constant attached to degradation, labeled maturation. Maturation $(a)$ takes into account the time it takes for a protein to<br />
mature before fluorescence can actually occur. Maturation is also dependent on the amount of protein available. We will let $\frac{d[P]_D}{dt}$ be the change in the concentration of protein, and $\beta$ be the degradation coefficient determining the fraction of protein that will be degraded in time. In this case, the equation would be<br />
</p><br />
<p><br />
\begin{equation}\frac{d[P]_D}{dt} = -(a + \beta) \cdot [P]\label{eq:12}\end{equation} <br />
</p><br />
<p><br />
However, since the fluorogen activated protein (FAP) takes a small amount of time to fold and to bind to the dye, one can make a reasonable assumption that<br />
maturation is 0. So the simplified equation is:<br />
</p><br />
<p><br />
\begin{equation}\frac{d[P]}{dt} = -\beta \cdot [P] \label{eq:13}\end{equation} <br />
</p><br />
<p><br />
Equations \eqref{eq:12} and \eqref{eq:13} can be solved by first order linear differential equation techniques. We will let $[R]_{max}$ and $[P]_{max}$ be the theoretical maximum concentration of RNA and protein (can also be thought of as at equilibrium):<br />
</p><br />
<p><br />
\begin{equation}[R] = [R]_{max}\cdot e^{-\alpha \cdot t}\end{equation}<br />
\begin{equation}[P] = [P]_{max}\cdot e^{-\beta \cdot t}\end{equation} <br />
</p><br />
<p><br />
From these equations $\alpha$ and $\beta$ can be determined easily.<br />
</p><br />
<br />
<br /><br />
<h1 id = "section1-5" >mRNA Expression</h1><br />
<br /><br />
<br />
<p><br />
From the mRNA expression equations, we know that<br />
</p><br />
<p><br />
\begin{equation}\frac{d[R]}{dt} = Ts \cdot [D] - \alpha \cdot [R]\end{equation}<br />
</p><br />
<p><br />
where $Ts$ is the transcriptional efficiency and $\alpha$ is the degradation constant associated with mRNA degradation, $\frac{d[R]}{dt}$ is the change in RNA over time, and $[R]$ is the mRNA concentration or amount.<br />
</p><br />
<p><br />
We see next that this is a first order linear equation, as $Ts$, $[D]$ and $\alpha$ are constants. Rearranging, we get<br />
</p><br />
<p><br />
\begin{equation}\frac{d[R]}{dt} + \alpha \cdot [R] = Ts \cdot [D] \label{eq:e1}\end{equation} <br />
</p><br />
<p><br />
The small integrating factor is thus $e^{\alpha \cdot t}$.<br />
</p><br />
<p><br />
Multiplying the small integrating factor through equation \eqref{eq:e1}<br />
(Warning: Math ahead!)<br />
</p><br />
<br />
\begin{equation}\frac{d[R]}{dt} \cdot e^{\alpha \cdot t} + \alpha \cdot [R] \cdot e^{\alpha \cdot t} = Ts \cdot [D] \cdot e^{\alpha \cdot t}\end{equation}<br />
<br />
\begin{equation}\frac{d([R]\cdot e^{\alpha \cdot t})}{dt} = Ts \cdot [D] \cdot e^{\alpha \cdot t}\end{equation}<br />
<br />
\begin{equation}[R]\cdot e^{\alpha \cdot t} = \int \! Ts \cdot [D] \cdot e^{\alpha \cdot t} \ dt\end{equation}<br />
<br />
\begin{equation}[R]\cdot e^{\alpha \cdot t} = \frac{Ts \cdot [D]}{\alpha} \cdot e^{\alpha \cdot t} + C \label{eq:e2}\end{equation}<br />
<br />
<br />
<br />
<p><br />
At $t = 0$, $[R] = 0$. Plugging into \eqref{eq:e2}, we obtain:<br />
</p><br />
<br />
\begin{equation}C = \frac{-Ts \cdot [D]}{\alpha}\end{equation}<br />
<br />
\begin{equation}[R] \cdot e^{\alpha \cdot t} = \frac{Ts \cdot [D]}{\alpha} \cdot e^{\alpha \cdot t} - \frac{Ts \cdot [D]}{\alpha}\end{equation}<br />
<br />
\begin{equation}[R] = \frac{Ts \cdot [D]}{\alpha} - \frac{Ts \cdot [D]}{\alpha} \cdot e^{-\alpha \cdot t}\end{equation}<br />
<br />
\begin{equation}[R] = \frac{Ts \cdot [D]}{\alpha} \cdot (1 - e^{-\alpha \cdot t})\label{eq:eR}\end{equation} <br />
<br />
<p><br />
$Ts$ is then calculated by <br />
</p><br />
<br />
\begin{equation} Ts = \frac{[R] \cdot \alpha}{[D] \cdot (1 - e^{-\alpha \cdot t})}\end{equation} <br />
</p><br />
<br /><br />
<br />
<h1 id = "section1-6">Protein Expression</h1><br />
<br /><br />
<p><br />
The protein model is a bit different from the mRNA model due to the fact that the amount of protein depends on the amount of mRNA, which is variable. mRNA<br />
is only dependent on $[D]$, which is invariable.<br />
</p><br />
<p><br />
The basic equation looks like:<br />
</p><br />
<br />
\begin{equation}\frac{d[P]}{dt} = [R] \cdot Tl - \beta \cdot [P]\end{equation}<br />
<br />
<p><br />
where $[P]$ is the protein concentration or amount, $[R]$ is still mRNA, $Tl$ is the translational efficiency, and $\beta$ is the degradation constant associated<br />
with the protein.<br />
</p><br />
<p><br />
Conveniently, we have already solved for our only hurdle to a first order linear equation, the mRNA amount (from equation \eqref{eq:eR}). We will substitute in for mRNA now:<br />
</p><br />
<p><br />
\begin{equation}\frac{d[P]}{dt} = (1 - e^{-\alpha \cdot t}) \cdot \frac{Ts \cdot [D]}{\alpha} \cdot Tl - \beta \cdot [P]\end{equation} <br />
</p><br />
<p><br />
Now we can solve the first order linear equation:<br />
</p><br />
<p><br />
\begin{equation}\frac{d[P]}{dt} + \beta \cdot [P] = (1 - e^{-\alpha \cdot t}) \cdot \frac{Ts \cdot [D]}{\alpha} \cdot Tl\end{equation} <br />
</p><br />
<p><br />
It can be seen that the integrating factor is $e^{\beta \cdot t}$ :<br />
</p><br />
\begin{equation}\frac{d[P]}{dt} \cdot e^{\beta \cdot t} + \beta \cdot [P] \cdot e^{\beta \cdot t} = e^{\beta \cdot t} \cdot (1 - e^{-\alpha \cdot t}) \cdot \frac{Ts \cdot [D]}{\alpha} \cdot Tl\end{equation}<br />
<br />
\begin{equation}\frac{d([P] \cdot e^{\beta \cdot t})}{dt} = e^{\beta \cdot t} \cdot (1 - e^{-\alpha \cdot t}) \cdot \frac{Ts \cdot [D]}{\alpha} \cdot Tl\end{equation}<br />
<br />
\begin{equation}[P]\cdot e^{\beta \cdot t} = \int \! (1 - e^{-\alpha \cdot t}) \cdot \frac{Ts \cdot [D]}{\alpha} \cdot e^{\beta \cdot t} \cdot Tl\ dt\end{equation}<br />
<br />
\begin{equation}[P]\cdot e^{\beta \cdot t} = Tl \cdot \int \! \frac{Ts \cdot [D]}{\alpha} \cdot e^{\beta \cdot t} \ dt - Tl \cdot \int \!\frac{Ts \cdot [D]}{\alpha} \cdot e^{(-\alpha + \beta) \cdot t} \ dt\end{equation}<br />
<br />
\begin{equation}[P] \cdot e^{\beta \cdot t} = Tl \cdot \frac{Ts \cdot [D]}{\alpha \cdot \beta} \cdot e^{\beta \cdot t} - Tl \cdot \frac{Ts \cdot [D]}{\alpha \cdot (-\alpha + \beta)} \cdot e^{(-\alpha + \beta) \cdot t} + C \label{eq:34}\end{equation} <br />
<p><br />
Now we solve for C. When $t = 0$, $P = 0$ :<br />
</p><br />
<br />
\begin{equation}C = -Tl \cdot \frac{Ts \cdot [D]}{\alpha} \cdot (\frac{1}{\beta} - \frac{1}{-\alpha + \beta})\end{equation} <br />
<p><br />
Substituting into \eqref{eq:34}, we obtain:<br />
\begin{equation}[P] \cdot e^{\beta \cdot t} = Tl \cdot \frac{Ts \cdot [D]}{\alpha \cdot \beta} \cdot e^{\beta \cdot t} - Tl \cdot \frac{Ts \cdot [D]}{\alpha \cdot (-\alpha + \beta)} \cdot e^{(-\alpha + \beta) \cdot t} - Tl \cdot \frac{Ts \cdot [D]}{\alpha} \cdot (\frac{1}{\beta} - \frac{1}{-\alpha + \beta}) \end{equation} <br />
</p><br />
<p><br />
<br />
</p><br />
<p><br />
FInally, we solve for Tl. Tl is the translational efficiency, which is the second characteristic we were trying to solve for:<br />
</p><br />
<br />
\begin{equation}Tl = \frac{[P]}{\frac{Ts \cdot [D]}{(\alpha \cdot \beta)} \cdot (1 - e^{-\beta \cdot t}) - \frac{Ts \cdot [D]}{\alpha \cdot (-\alpha + \beta)} \cdot (e^{-\alpha \cdot t} - e^{-\beta \cdot t})} \label{eq:Tl}\end{equation}<br />
<br /><br />
<br />
<p> The following figures show that our model described above, and the parameters that we obtained fit well the measured fluorescence for the wild type (WT) promoter and three new promoters (Mutants 1,2, and 3). </p><br />
<br />
<p><br />
<img src="https://static.igem.org/mediawiki/2012/e/e1/WT.jpg" height="180" width="210" align="center"/><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/1/10/Mutant1.jpg" height="180" width="210" align="center"/><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/d/db/Mutant2.jpg" height="180" width="210" align="center"/><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/8/86/Mutant3.jpg" height="180" width="210" align="center"/><br />
</p><br />
<br />
<br />
<h1 id = "section1-7">Polymerase Per Second</h1><br />
<br /><br />
<br />
<p><br />
Taking inspiration from ”Measuring the activity of BioBrick promoters using an <i>in vivo</i> reference standard” by Kelly et al.<sup><a href = "#cite1">[1]</a></sup>, we can derive our own equation<br />
for polymerase per second (PoPS), as follows.<br />
</p><br />
<p><br />
mRNA is produced by the number of promoters times the rate of initiations of polymerase onto the promoters, or $n \cdot PoPS$. mRNA is degraded by the degradation equation we derived earlier, which is $-\alpha \cdot [R]$ :<br />
</p><br />
<p><br />
\begin{equation}\frac{d[R]}{dt} = n \cdot PoPS - \alpha \cdot [R] \label{eq:Po1}\end{equation} <br />
</p><br />
<p><br />
where $n$ is the number of promoters in a cell, PoPS is the rate of initiations of RNA polymerase onto the promoters.<br />
</p><br />
<p><br />
Protein is produced by the translational efficiency times the mRNA, which is $[R] \cdot Tl$. Protein is degraded by the degradation equation we derived above, which is $-\beta \cdot [P]$ :<br />
</p><br />
<p><br />
\begin{equation}\frac{d[P]}{dt} = [R] \cdot Tl - \beta \cdot [P] \label{eq:Po2}\end{equation} <br />
</p><br />
<p><br />
At steady state, it can be assumed that $d[R] = 0$ and $d[P] = 0$.<br />
</p><br />
<p><br />
So simplifying \eqref{eq:Po1} and \eqref{eq:Po2}, we obtain:<br />
</p><br />
\begin{equation}PoPS = \frac{\alpha \cdot [R]}{n}\end{equation} <br />
<p><br />
Substituting leaves:<br />
</p><br />
<br />
<p><br />
\begin{equation}PoPS = \frac{\alpha \cdot \beta \cdot [P]}{n \cdot Tl} \label{eq:PoPS}\end{equation} <br />
</p><br />
<p><br />
The output of the model is polymerase per second, which is what we have found here. It is important to realize that the purpose of finding polymerase per<br />
second is that for the current environment of a promoter and the specific type of promoter, it can be characterized using polymerase per second.<br />
Experiments can thus easily be conceived by running two experiments on the same promoter under different conditions to see how a promoter is affected, or<br />
by running two experiments on different promoters under the same conditions to see which is a stronger promoter.<br />
</p><br />
<br><br />
<br><br />
<h1>Fitting</h1><br />
<br /><br />
With the data we were given, we decided to fit the equations we derived to the data. We used a method of gradient descent to minimize the error from our fits. We began by trying to fit the transcriptional strength equation, equation \eqref{eq:eR}. We defined our fitting function, $R_i$, in terms of our equation for transcriptional strength, \eqref{eq:eR}, as well as some error $\epsilon$. Since the experimental data was taken in discrete time, we took each point for RNA to be $R_i$ and each point for time to be $t_i$.<br />
<br />
<p><br />
\begin{equation}R_i = f(t_i) + \epsilon\end{equation}<br />
</p><br />
<p><br />
\begin{equation}R_i = \frac{T_s}{\alpha} \cdot D \cdot (1 - e^{-\alpha \cdot t_i}) + \epsilon\end{equation}<br />
</p><br />
<p><br />
\begin{equation}R_i = \frac{T_s}{\alpha} \cdot D - \frac{T_s}{\alpha} \cdot D \cdot e^{-\alpha \cdot t_i} + \epsilon\end{equation}<br />
</p><br />
$D$ represents the concentration of DNA, and we are looking for $T_s$ and $\alpha$ as the outputs from our fitting model.<br />
<br />
<p><br />
We want to minimize our error. To do this, we will use a common method called the method of least squares.<br />
We define our error function to be $L(T_s, \alpha)$.<br />
</p><br />
<p><br />
\begin{equation}L(T_s, \alpha) = \sum^n_{i = 1}(R_i - f(t_i))^2\end{equation}<br />
</p><br />
<p><br />
\begin{equation}L(T_s, \alpha) = \sum^n_{i = 1}(R_i - (\frac{T_s}{\alpha} \cdot D - \frac{T_s}{\alpha} \cdot D \cdot e^{-\alpha \cdot t_i}))^2\end{equation}<br />
</p><br />
<p><br />
Now we use a method called gradient descent. This function, over the course of many trials, increments the variables, in our case $T_s$ and $\alpha$, such that the variables gradually approach acceptable values for a fitted function. To do this, we take the derivative of our error function with respect to both our variables, $T_s$ and $\alpha$.<br />
</p><br />
<br />
<p><br />
\begin{equation}\frac{\delta L}{\delta T_s} = \sum^n_{i = 1}(2\cdot(R_i - \frac{T_s}{\alpha} \cdot D - \frac{T_s}{\alpha} \cdot D \cdot e^{-\alpha \cdot t_i} \cdot ( -\frac{D}{\alpha} + \frac{D}{\alpha} \cdot e^{\alpha \cdot t_i})))\end{equation}<br />
</p><br />
<p><br />
\begin{equation}<br />
\begin{split}\frac{\delta L}{\delta \alpha} &= \sum^n_{i = 1}(2 \cdot (R_i - \frac{T_s}{\alpha} \cdot D + \frac{T_s}{\alpha}\cdot D \cdot e^{-\alpha \cdot t_i})\cdot \\&(\frac{T_s \cdot D}{\alpha^2} - \frac{T_s \cdot D}{\alpha^2} \cdot e^{-\alpha \cdot t_i} + \frac{T_s}{\alpha} \cdot D \cdot e^{-\alpha \cdot t_i}\cdot (-t_i)))\end{split}\end{equation}<br />
</p><br />
<p><br />
From here, we begin incrementing $T_s$ and $\alpha$ for a number of trials $K$.<br />
</p><br />
<br />
<p><br />
\begin{equation}T^{k + 1}_s = T^k_s + \eta \cdot \frac{\delta L}{\delta T^k_s}\end{equation}<br />
for k = 1... K.<br />
</p><br />
<p><br />
$\eta$ is a term often called "learning rate" in machine learning, but which we will call step size. It is called thusly due to the fact that $T_s$ and $\alpha$ are incrementing a different amount every time based on the closeness of the fit for each trial. In this sense, the variables could be seen as "learning" where the optimal fitting values are and changing their increments accordingly. $\eta$ is equivalent to the inverse of the number of trials, K. $\eta = \frac{1}{K}$.<br />
</p><br />
<p><br />
We can do a similar equation for $\alpha^{k + 1}$.<br />
</p><br />
<p><br />
\begin{equation}\alpha^{k + 1} = \alpha^k + \eta \cdot \frac{\delta L}{\delta \alpha ^k}\end{equation}<br />
for k = 1...K.<br />
</p><br />
<br />
<p><br />
The final values, $T^K_s$ and $\alpha^K$ are the parameters we are looking for in our fitting function.<br />
</p><br />
<br />
<p><br />
For our translational efficiency model, we performed the same set of methods to get our fit. We will use our fitted variables from the transcriptional strength fitting in our translational efficiency fitting so that we still are only fitting 2 variables. We first defined our fitting function, $M(Tl, \beta)$.<br />
</p><br />
<br />
<p><br />
\begin{equation}\begin{split}[P] &= Tl \cdot \frac{T_s \cdot D}{\alpha \cdot \beta} - Tl \cdot \frac{T_s \cdot D}{\alpha \cdot (-\alpha + \beta)} \cdot e^{-\alpha \cdot t} - Tl \cdot \frac{T_s \cdot D}{\alpha \cdot \beta} \cdot e^{-\beta \cdot t} \\&+ Tl \cdot \frac{T_s \cdot D}{\alpha \cdot (-\alpha + \beta)} \cdot e^{-\beta \cdot t} + \epsilon \end{split}\end{equation}<br />
</p><br />
<br />
<p><br />
\begin{equation}[P] = Tl \cdot (\frac{T_s \cdot D}{\alpha}\cdot (\frac{1}{\beta}\cdot (1 - e^{-\beta \cdot t}) - \frac{1}{-\alpha + \beta}(e^{-\alpha \cdot t} - e^{-\beta \cdot t}))) + \epsilon\end{equation}<br />
</p><br />
<p><br />
\begin{equation} M(Tl, \beta) =\sum^n_{i = 1}([P] - Tl \cdot (\frac{T_s \cdot D}{\alpha}\cdot (\frac{1}{\beta}\cdot (1 - e^{-\beta \cdot t}) - \frac{1}{-\alpha + \beta}(e^{-\alpha \cdot t} - e^{-\beta \cdot t}))))^2\end{equation}<br />
</p><br />
<p><br />
Again, we take the partial derivatives with respect to each variable, in our case $Tl$ and $\beta$.<br />
</p><br />
<p><br />
\begin{equation} \begin{split} \frac{\delta M}{\delta Tl} &= \sum^n_{i = 1}(2([P] - Tl \cdot (\frac{T_s \cdot D}{\alpha}\cdot (\frac{1}{\beta}\cdot (1 - e^{-\beta \cdot t}) - \frac{1}{-\alpha + \beta}(e^{-\alpha \cdot t} - e^{-\beta \cdot t})))) \cdot (\frac{T_s \cdot D}{\alpha})\\ &\cdot (\frac{1}{\beta}\cdot (1 - e^{-\beta \cdot t}) - \frac{1}{-\alpha + \beta} \cdot e^{-\beta \cdot t}))\end{split} \end{equation}<br />
</p><br />
<p><br />
\begin{equation} \begin{split} \frac{\delta M}{\delta \beta} &= \sum^n_{i = 1}(2([P] - Tl \cdot (\frac{T_s \cdot D}{\alpha}\cdot (\frac{1}{\beta}\cdot (1 - e^{-\beta \cdot t}) - \frac{1}{-\alpha + \beta}(e^{-\alpha \cdot t} - e^{-\beta \cdot t})))) \cdot \\&(Tl \cdot \frac{T_s \cdot D}{\alpha} \cdot (\frac{-1}{\beta^2}\cdot (1 - e^{-\beta \cdot t}) + \frac{t \cdot e^{-\beta \cdot t}}{\beta} + \frac{1}{(-\alpha + \beta)^2} \cdot (e^{-\alpha \cdot t} - e^{-\beta \cdot t}) - \frac{1}{-\alpha + \beta}\cdot(t \cdot e^{-\beta \cdot t}))))\end{split}\end{equation}<br />
</p><br />
<p><br />
We will increment $Tl$ and $\beta$ similar to the $T_s$ and $\alpha$ incrementing, with $K$ being the number of trials and $\eta$ being the step size.<br />
</p><br />
<p><br />
\begin{equation}Tl^{k + 1} = Tl^k + \eta \cdot \frac{\delta M}{\delta Tl^k}\end{equation}<br />
for k = 1...K.<br />
</p><br />
<p><br />
\begin{equation}\beta^{k + 1} = \beta^k + \eta \cdot \frac{\delta L}{\delta \beta^k} \end{equation}<br />
for k = 1...K.<br />
</p><br />
<p><br />
As a summary, we can minimize the error of the fitting using the above techniques. This algorithm for minimizing error can be best utilized in code, due to the fact that an accurate fit requires a large $K$.<br />
<br><br />
<hr \><br />
<p><font size="2"><br />
<sup><a name="cite1">[1]</a></sup><br />
Kelly, Jason R., Adam J. Rubin, Joseph H. Davis, Caroline M. Ajo-Franklin, John Cumbers, Michael J. Czar, Kim De Mora, Aaron L. Glieberman, Dileep D. Monie, and Drew Endy. "Measuring the Activity of BioBrick Promoters Using an in Vivo Reference Standard." Journal of Biological Engineering 3.1 (2009): 4. Print.<br />
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<h1 id="section1-1"> Modeling Goals </h1><br />
<p><br />
The purpose of the model in the scope of the project is to provide an acceptable estimate of desired parameters within the biological system. These parameters often cannot be measured or calculated directly, which highlights the importance of modeling. The advancements in measurement capabilities have allowed us to develop a suitable model of these processes.<br />
</p><br />
<p><br />
The focus of our model is to help characterize promoters, by computing translational efficiency and Polymerases Per Second (<i>PoPS</i>). These parameters are notoriously difficult to measure consistently <i>in vivo</i>. In addition to these main output values, the model also calculates other characteristics of the cell, such as degradation constants for mRNA and protein, and transcriptional strength. By identifying these parameters, the model will help better characterization of promoters that are to be used in experiments. <br />
</p><br />
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<h1 id = "section1-2"><br />
The Model<br />
</h1><br />
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<img src="https://static.igem.org/mediawiki/2012/a/a2/Black-box-figure2.jpg" height="300" width="400" align="right"/><br />
<p><br />
The black-box representation of our model, with its inputs and outputs is shown on the right, and the details of the model are described <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Derivations">here</a>. <br />
</p><br />
<p><br />
Inputs to the model constitute measurements taken from the actual biological system. Dyes mixed with solutions of the cells bind to mRNA and protein complexes to cause the cells to fluoresce over time. These fluorescent measurements form the basis of the inputs to the model. Using a gradient of concentrations of dye vs. time applied to cells, one can obtain estimates about the amount of bound mRNA and protein. More formally, inputs to our model include: time steps and RNA fluorescence measured at those time steps, (<i>t</i>, <i>R</i>(<i>t</i>)); time steps and protein fluorescence measured at those time steps, (<i>t</i>, <i>P</i>(<i>t</i>)).<br />
</p><br />
<br />
<p><br />
The outputs of the model represent estimated system parameters that fit experimental measurements: transcriptional strength (<i>Ts</i>), RNA degradation rate (<i>α</i>), translational efficiency (<i>Tl</i>), protein degradation rate (<i>β</i>), and <i>PoPS</i>.<br />
</p><br />
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Implementation of the Model<br />
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<p><br />
The model is composed in Matlab. It incorporates file input/output to retrieve experimental measurement data. The inputs to the model are time dependent and dye-dependent fluorescence measurements of mRNA and protein. Several time dependent measurements can be included in input files: mRNA fluorescence during synthesis, mRNA fluorescence during degradation (with or without mRNA production), protein fluorescence during synthesis, and protein fluorescence during degradation (with or without protein production). Other constants are approximated as needed.<br />
</p><br />
<br />
<p><br />
Using the total mRNA and protein measurements, along with either estimates or measurements of the degradation of mRNA and protein, one can determine the transcriptional and translational efficiency using general differential equations. Finally, <i> PoPS</i> can be determined using translational efficiency, as we describe in detail <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Derivations"> here</a>.<br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Met-SafetyTeam:Carnegie Mellon/Met-Safety2012-10-27T03:32:38Z<p>Ychoo: </p>
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</p> <h1>Safety Information</h1><p id="section1-1"><br />
1. <b>Would any of your project ideas raise safety issues in terms of researcher safety, public safety or environmental safety:</b></p><br />
<br />
<p><br />
Our project ideas do not raise any researcher safety issues. One of the dyes that we used is malachite green, which has the ability to cause low concentrations of free radicals as described by J.C. Liao et al<sup>[1]</sup> . Even though there is a risk of a few free radicals being formed during measurements, all assay-ed micro-plates were properly disposed of and malachite green is relatively safe by itself.<br />
We only used non-pathogenic Escherichia. coli, which is a biosafety level 1 organism. To facilitate the selection of E. coli, we transformed E. coli strains (DH5-alpha and BL21(DE3)) with ampicillin resistant genes. We also used BL21 (DE3) pLysS strain for gene expression, which contains a chloramphenicol resistance gene. While these antibiotic resistant strains may pose a threat to public safety if released from the lab environment, all safety protocols were followed and cells were disposed according to institutional requirements.</p><br />
<p><br />
Other than the use of antibiotic resistant strains as mentioned above, our project did not incorporate any biological components, which pose a threat to environmental safety. Regarding possible toxic chemicals used such as ethidium bromide for running gels, these chemicals were all disposed of according to institutional requirement. The researchers using ethidium bromide were required to read all of the MSDS forms and participate in chemical lab safety before handling the equipment.<br />
</p><br />
<hr \><br />
<p> [1] J.C Liao, J Roider, D.G Jay. “Chromophore-assisted laser inactivation of proteins is mediated by the photogeneration of free radicals”. Proc. Natl. Acad. Sci. USA, 91 (1994), pp. 2659–2663</p><br />
<br />
<p id="section1-2"><br />
2. <b>Do any of the new BioBrick parts (or devices) that you made this year raise any safety issues? If yes, did you document these issues in the Registry? How did you manage to handle the safety issue? How could other teams learn from your experience? </b></p><p><br />
No, our parts themselves do not pose any risks. </p><br />
<p id="section1-3"><br />
3. <b>Is there a local biosafety group, committee, or review board at your institution? </b></p><p><br />
There is a biological safety group, which is part of the Environmental, Health and Safety department. We have been exempted by this group to perform rDNA work. We obeyed all of the federal, state and local laws pertaining to the disposal of hazardous waste and biohazard waste (including liquids, solids and sharps). Our project used only biosafety level 1 organisms. All of the chemicals we use in the lab have been cleared for laboratory use. </p><br />
<br />
<p id="section1-4"><br />
4. <b>Do you have any other ideas how to deal with safety issues that could be useful for future iGEM competitions? How could parts, devices and systems be made even safer through biosafety engineering?</b></p><p><br />
One possible idea is to create an inducible (light-based) “kill-switch” in E. coli and yeast similar to the apoptotic pathways in mammalian cells using LovTAP. This would allow for easy disposal of cells, by simply placing the cells in a dark environment when we do not need them. <br />
A similar idea is to create a strain of E. coli with a knocked out metabolic pathway, causing it to depend on a laboratory supplied environment to survive (such as a chemical or light). This would be a more passive safeguard against an accidental release of the bacteria.</p><br />
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<h1 id = "section 1-1"> Overview</h1><br />
<id = "section1-1"><br />
<p><br />
Lab notebooks were kept using Google docs, and they mostly contain information from the experimental side, including details such as the protocol followed, timestamp of the experiments and the observed results. <br />
<br \><br />
Feel free to click on the links below to view the actual lab notebooks and email us if you have any questions!<br />
</p><br />
<br />
<h1 id = "section1-2"> Notebooks</h1><br />
<br />
<p><br />
<br />
During the first 2 weeks after final exams, we were mainly focused on settling the logistics of getting the project off the ground. Hence there were no lab experiments and hence no notebook kept. <br />
<br \><br \><br />
<br />
1. <a href="https://docs.google.com/document/d/1rLIBV3wwV6zzKGaTIbFQf2UdksK0lluRZFd-njcyLqk/edit">Week 3</a> was focused transforming two different FAP plasmids we obtained into DH5a and working out the exact construct design <br />
<br \><br \><br />
2. <a href="https://docs.google.com/document/d/1Hf4BhpGf1OCukNzULbElX0ZgVzSmGa7Fu4kH8AxSxE8/edit">Week 4</a> was focused on testing and comparing the functionality of the two FAP plasmids expressed in BL21DE3 cells using two variants of Malachite Green (5% EtOH and PBS)<br />
<br \><br \><br />
3. <a href="https://docs.google.com/document/d/1r4RECG92rop1xuOs-0jIC303CcVzAKN3bNZLa1iaxvw/edit">Week 5</a> was focused on cloning our synthesized Spinach cassette into our vector, and conducting dosage and temporal curves using the FAP and MG(5% EtOH) used.<br />
<br \><br \><br />
4. <a href="https://docs.google.com/document/d/1wH9gUvaaxaLmb3aetGs9DwUoSB7h6yoLNuoviSy1w2A/edit">Week 6</a> was focused on Spinach. We ran a gel and sequenced our Spinach transformant and also PCR amplified the original cassette to obtain more copies.<br />
<br \><br \><br />
5. <a href="https://docs.google.com/document/d/1AoaOuvT6I6cKguLkRqwm-l32u_pYSiKQAg8qbecLgf8/edit">Week 7</a> was focused on Spinach cloning. We tried another round of cloning of Spinach into the FAP vector and a pET vector. Also provides the basis for the first T7 promoter designs. <br />
<br \><br \><br />
6. <a href="https://docs.google.com/document/d/1Xi6JxTts2XbQGFtpnM92sDUSm4DftFqjyUGsjhRcQ2o/edit">Week 8</a> was focused again on cloning Spinach into the FAP vector and the pET vector after another negative result of cloning. Finalized the T7 promoter designs<br />
<br \><br \><br />
7. <a href="https://docs.google.com/document/d/1nYWf_uWMG4JdDJ7qKhkv9az2DsZQ-70-uqPGlUS5Jt4/edit">Week 9</a> was focused on characterizing the Spinach cassette in a pET vector. Efforts continued to create a clone with both the FAP and the Spinach Cassettes.<br />
<br \><br \><br />
8. <a href="https://docs.google.com/document/d/1zschOOFerRaZeCdbADdh4lld2_oindBloPdJZD3DPXs/edit">Week 10</a> focused on cloning Spinach and the FAP into a different vector with entirely new restriction sites. Began preparation for a cloning round in URA- yeast as a backup plan. Cloned cassettes into pIVEX vector.<br />
<br \><br \><br />
9. <a href="https://docs.google.com/document/d/1Oe9OEPeRk6LF2vfuey5QqRgAWYewko9sDssDii5KTds/edit">Week 11</a> included cloning round in URA- yeast using homologous recombination. Characterized Spinach using a functional assay in pIVEX vector.<br />
<br \><br \><br />
10. <a href="https://docs.google.com/document/d/1f8m0_xXKlDkqEjsDUJNTVHA0Cohd76ylFR3BXms4Td4/edit">Week 12</a> is a brief document detailing the PCR reaction, which is in preparation for the Fall laboratory rounds or cloning.<br />
<br \><br \><br />
11. <a href="https://docs.google.com/document/d/1q4LFNBFHz5GOIxMp1fbecpJ3SVy9t7eWDwCCFCMD7HU/edit">Fall notebook </a> is a consolidated log of all our experiments carried through Fall, including the final characterization and cloning experiments.<br />
<br />
<br />
</p><br />
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<h1>Challenges with Molecular Cloning</h1><br />
<br />
<p> Cloning was a major challenge for us. It often took us multiple rounds of digestion/ligation/cloning to get our construct into the cells. Our cloning procedures did not work initially due to confounding factors of contamination in media and competent cells, inappropriate design of digestion sites, and non-optimal PCR reactions. However, these issues were eventually ironed out and we managed to get the FAP and Spinach into a single construct. <br \><br />
A major help in diagnosing our failures was using the gel consistently to check the length of our inserts, and to sequence periodically to ensure the insert and vector are as expected. <br \><br />
Please refer to our protocols for our final cloning protocol, and remember to reserve some amount of time to allow for experimental failures!<br />
<br \> <br><br><br />
We attempted to clone our constructs into pSB1C3 and another plasmid vector that has both EcoR1 and Pst1 digestion sites. Using our previous cloning protocols, the cloning using the plasmid vector worked in the first trial. Unfortunately, the cloning using pSB1C3 was more difficult than we expected and only worked after four trials and extensive optimization of our protocols. <br \><br />
The key difference between our plasmid vector and the pSB1C3 vector from the registry was the fact that the submission vector was linearized. We have not been able to pinpoint the exact cause for this, so again, budget sufficient time for cloning! </p><br />
<p><br />
We attempted to utilize flow cytometry to analyze expression data of our fluorogen-activating biosensors. In order to save time and prevent a queue from forming, we had to fix our cells with 5% formaldehyde before running it in the cytometer. This had negative effects on our results and were unable to see significant signal.<br />
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<id = "section1-1"><br />
<p><br />
Our protocols are based on standard protocols used in the lab of our advisers unless otherwise stated. These protocols were subsequently modified if necessary based on our experiments. A knowledge of basic lab techniques such as pippeting, plating, etc. are assumed and not covered as there are existing & comprehensive tutorials on the web for those.<br />
<br/><br />
</p><br />
<br />
<br />
<h1 id = "section1-7"> Materials </h1><br />
<br />
<p><br />
<ol><br />
<li> Cloning strains: DH5-alpha, Top10F', & BL21Pro. </li><br />
<li> Expression cell strains: BL21(DE3) & BL21(DE3)-pLys </li><br />
<li> Media: Luria Broth media, <a href = "http://products.invitrogen.com/ivgn/product/A1374401"> M9 media </a>, Ampicillin, & Chloramphenicol. </li><br />
<li> Dyes: <a href= " http://www.mbic.cmu.edu/images/datasheet/MG-ester-info_rev21.pdf"> Malachite Green ester </a> [from MBIC], <a href =" http://www.lucernatechnologies.com/3-5-difluoro-4-hydroxybenzylidene-imidazolinone-DFHBI-5-mg-p25.html"> 3,5-difluoro-4-hydroxybenzylidene imidazolinone (DFHBI) </a> </li><br />
</ol> <br />
</p><br />
<br \><br />
<br />
<h1 id = "section1-2"> Kit Protocols </h1><br />
<p><br />
<ol><br />
<li> <a href="http://www.zymoresearch.com/downloads/dl/file/id/166/t3001i.pdf">Z-Competent E. Coli Transformation Kit</a> for making competent cells for easy transformation. Modified to incubate cells on ice for 1 hour during transformation</li><br />
<li><a href ="http://www.neb.com/nebecomm/ManualFiles/manualE0553.pdf"> Phusion High Fidelity PCR Kit </a> for amplifying our inserts and DNA cassettes.</li><br />
<li> <a href ="http://www.neb.com/nebecomm/products_intl/protocol568.asp"> TAQ DNA Polymerase </a> for verifying our cloned constructs</li><br />
<li> <a href = "http://www.qiagen.com/literature/render.aspx?id=201794">Qiagen Mini-prep Kit </a> for extracting our plasmids from the cells. </li><br />
<li> <a href = "http://www.zymoresearch.com/dna-purification/dna-clean-up/pcr-dna-clean-up-concentration/dna-clean-concentrator-5">Zymo Clean and Concentrator kit </a> for cleaning up DNA before digestion and ligation.</li><br />
</ol> <br />
</p><br />
<br/><br />
<br />
<p><h1 id = "section1-3">Cloning Protocol</h1><br />
<p><br />
<ol><br />
<li>If necessary, first prepare the insert using PCR amplification. This was done to add the necessary restriction sites for cloning. The PCR protocol follows the kit protocol outlined above, except with our specific range of melting and annealing temperatures calculated using <a href = "http://www.neb.com/nebecomm/tech_reference/tmcalc/"> NEB's Tm calculator </a> </li><br />
<li> Start digestion of vector and insert DNA using desired restriction enzyme manufacturer protocol. [NEB] </li><br />
<li> After 2 hours, add Phosphatase [CIP] according to manufacturer protocol to insert to prevent self-ligation </li><br />
<li> Purify and clean DNA using kit protocol. [Zymo Research] </li><br />
<li>Measure vector/insert concentration. [Nanodrop] </li><br />
<li> Divide the concentration by the length of the sequence and calculate ligation ratios of 1 vector to 3 insert. Mix the ratios according to the calculations, including T4 buffer and ligase. </li><br />
<li>Leave ligation products at room temperature for 1 hour. </li><br />
<li>Transform ligation products into competent cells using appropriate protocol. Incubate on ice for 1 hour if using Zymo competent cells </li><br />
<li>Plate cells and incubate at 37 degrees overnight. Check for colonies the next morning. If there are colonies present, inoculate 1-3 colonies into (selective) L.B. in the evening and culture overnight. </li><br />
</ol> <br />
</p><br />
<br/><br />
<br />
<h1 id = "section1-4"> Gel Protocol </h1><br />
<p><br />
<ol><br />
<li> For 7x7 cm, 0.5cm thick gel, with 1.75% agarose Concentration. </li><br />
<li> Add 0.35 grams of agarose to 20ml of 1x buffer (TBE)<br />
Note: Place mark on container to keep track of liquid level using marker, so water can be added to bring the liquid back to original level </li><br />
<li> Place gel solution in microwave. Use low/medium, set timer for 5 minutes. Stop the oven every 30 seconds and swirl gently to suspend undissolved agarose. </li><br />
<li> Once dissolved, set aside to cool (~60 degrees). Once solution is warm to touch, add 0.5ug/ml ethidium bromide. [1&#181;l of 10mg/ml]</li><br />
<li> Pour into casting tray, remember to add in comb at the cathode side (black). Gel will solidify in ~10 mins</li><br />
<li> Divide the concentration by the length of the sequence and calculate ligation ratios of 1 vector to 3 insert. Mix the ratios according to the calculations, including T4 buffer and ligase. </li><br />
<li> Remove comb for solidified gel, remove casting gates and submerge gel beneath 2 to 6mm of 1x buffer. </li><br />
<li> Mix loading dye with PCR/digested products, load mixture into wells, together with 10&#181;l of ladder </li><br />
<li> Run gel at 75V for ~1 hour. Adjust voltage accordingly if require faster or more distinct gels. </li><br />
</ol> <br />
</p><br />
<br/><br />
<br />
<p><h1 id = "section1-5"> Dosage Curve </h1><br />
<br />
<p><br />
<ol><br />
<li> The night before the experiment, start an overnight culture by seeding 1:100 of expression cell stock to fresh selection media [Typically 30&#181;l stock to 3ml LB+Amp]. Place tube in a shaking water bath at 37 degrees celsius overnight. </li><br />
<li> Culture a fresh batch of cells using 1:100 of overnight culture prepared to selection media. Culture in a shaking 37 degrees celsius water bath for around 2 hours or until the solution is lightly turbid. </li><br />
<li> Induce cells by adding 1&#181;l of 1M IPTG. Incubate cells in a shaking water bath at 37 degrees celsius for 2 hours. </li><br />
<li> Aliquot 1ml of induced cells into an 1.5ml Eppendorf tube and spin down the cells at 10,000rpm for 1min and discard the supernatant. Wash the cells with 1ml of PBS, repeat spinning down the cells at 10,000rpm and discard the supernatant. Resuspend the washed cells in 1mL M9 media. </li><br />
<li> To increase DFHBI fluorescence, add 1µL of 50nM Mg2+ to the tubes (from MgCl2 from PCR kit) </li><br />
<li> Aliquot (100&#181;l/200&#181;l) of cells into desired wells of a 96-well plate.</li><br />
<li>To each of the 96-wells, add 1&#181;l of 1mM IPTG to maintain the production of FAP and Spinach. Add various doses of DFHBI to the wells intended for testing DFHBI dosage. To a separate set of wells, add the desired doses of MG. </li><br />
<li> Incubate for 45mins in 37 degrees celsius, as recommended by Paige et al. Plate read with plate reader (Tecan Safire II). First find cell density using OD600. Then use Excitation/Emission of 469/501 for Spinach and 635/660 for Malachite-green. </li><br />
</ol> <br />
</p><br />
<br/><br />
<br />
<h1 id = "section1-6"> Time Lapse Protocol </h1><br />
<br />
<p><br />
<ol><br />
<li> For the temporal analysis, we will be characterizing different promoters. Culture fresh batches of cells using 1:100 of overnight culture of the different promoter constructs. Do include the wild type promoter to act a a form of comparison. Culture for around 2 hours or until the solution is lightly turbid. </li><br />
<li> Culture a fresh batch of cells using 1:100 of overnight culture prepared to selection media. Culture in a shaking 37 degrees celsius water bath for around 2 hours or until the solution is lightly turbid. </li><br />
<li> For each ml of cells required for the assay: Aliquot 1ml of cells into 1.5ml Eppendorf tubes and spin down the cells at 10,000rpm for 1min and discard the supernatant. Wash the cells with 1ml of PBS, repeat spinning down the cells at 10,000rpm and discard the supernatant. Resuspend the washed cells in 1mL M9+3&#181;l 50nM Mg media.</li><br />
<li> Reserve part of the cells for testing the un-induced construct for leaky expression. Add 1&#181;l of 1M IPTG per ml of remaining cells </li><br />
<li> Aliquot 100&#181;l of induced and uninduced cells per well into a 96-well plate </li><br />
<li> Add the maximum dosage of DFHBI and MG as determined by the dosage curve into separate wells for each of the clones. </li><br />
<li>To each of the 96-wells, add 1&#181;l of 1mM IPTG to maintain the production of FAP and Spinach. Add various doses of DFHBI to the wells intended for testing DFHBI dosage. To a separate set of wells, add the desired doses of MG. </li><br />
<li> As soon as the dyes are added, measure samples using the plate reader (Tecan Safire II). Measure cell density using absorbance @600nm, followed by Excitation/Emission of 469nm/501nm for Spinach and 635nm/660nm for Malachite-green. Set the plate reader temperature to 37 degrees and to shake the plate for 10 seconds every 10mins. Repeat the OD and fluorescence measurements every 30minutes until the fluorescence output begins to plateau (~3 hours). </li><br />
</ol> <br />
</p><br />
<br/><br />
<br />
</html><br />
{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Met-ProtocolsTeam:Carnegie Mellon/Met-Protocols2012-10-27T03:31:12Z<p>Ychoo: </p>
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<!--Main Contents --><br />
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<br />
<!--Table of Contents --><br />
<!-- Remove for testing<br />
<div id="toc-holder" class="toc-holder"><br />
<a href="#" class="toc-link" id="toc-link"><span>&#9660;</span> Table of Contents</a><br />
<ul id="toc" class="toc-new" style="background: #c1a562;"><br />
<li class="toc-h1"><a href="#section1">Introduction</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">Overview</a></li><br />
<li><a href="#section1-2">Kit Protocols</a></li><br />
<li><a href="#section1-3">Cloning Protocol</a></li><br />
<li><a href="#section1-4">Gel Protocol</a></li><br />
<li><a href="#section1-5">Dosage Curve</a></li><br />
<li><a href="#section1-6">Time Lapse Protocol</a></li><br />
<li><a href="#section1-7">Materials used</a></li><br />
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<div class = "main_content"><br />
<br />
<h1 id = "section 1-1">Overview</h1><br />
<id = "section1-1"><br />
<p><br />
Our protocols are based on standard protocols used in the lab of our advisers unless otherwise stated. These protocols were subsequently modified if necessary based on our experiments. A knowledge of basic lab techniques such as pippeting, plating, etc. are assumed and not covered as there are existing & comprehensive tutorials on the web for those.<br />
<br/><br />
</p><br />
<br />
<br />
<h1 id = "section1-7"> Materials </h1><br />
<br />
<p><br />
<ol><br />
<li> Cloning strains: DH5-alpha, Top10F', & BL21Pro. </li><br />
<li> Expression cell strains: BL21(DE3) & BL21(DE3)-pLys </li><br />
<li> Media: Luria Broth media, <a href = "http://products.invitrogen.com/ivgn/product/A1374401"> M9 media </a>, Ampicillin, & Chloramphenicol. </li><br />
<li> Dyes: <a href= " http://www.mbic.cmu.edu/images/datasheet/MG-ester-info_rev21.pdf"> Malachite Green ester </a> [from MBIC], <a href =" http://www.lucernatechnologies.com/3-5-difluoro-4-hydroxybenzylidene-imidazolinone-DFHBI-5-mg-p25.html"> 3,5-difluoro-4-hydroxybenzylidene imidazolinone (DFHBI) </a> </li><br />
</ol> <br />
</p><br />
<br \><br />
<br />
<h1 id = "section1-2"> Kit Protocols </h1><br />
<p><br />
<ol><br />
<li> <a href="http://www.zymoresearch.com/downloads/dl/file/id/166/t3001i.pdf">Z-Competent E. Coli Transformation Kit</a> for making competent cells for easy transformation. Modified to incubate cells on ice for 1 hour during transformation</li><br />
<li><a href ="http://www.neb.com/nebecomm/ManualFiles/manualE0553.pdf"> Phusion High Fidelity PCR Kit </a> for amplifying our inserts and DNA cassettes.</li><br />
<li> <a href ="http://www.neb.com/nebecomm/products_intl/protocol568.asp"> TAQ DNA Polymerase </a> for verifying our cloned constructs</li><br />
<li> <a href = "http://www.qiagen.com/literature/render.aspx?id=201794">Qiagen Mini-prep Kit </a> for extracting our plasmids from the cells. </li><br />
<li> <a href = "http://www.zymoresearch.com/dna-purification/dna-clean-up/pcr-dna-clean-up-concentration/dna-clean-concentrator-5">Zymo Clean and Concentrator kit </a> for cleaning up DNA before digestion and ligation.</li><br />
</ol> <br />
</p><br />
<br/><br />
<br />
<p><h1 id = "section1-3">Cloning Protocol</h1><br />
<p><br />
<ol><br />
<li>If necessary, first prepare the insert using PCR amplification. This was done to add the necessary restriction sites for cloning. The PCR protocol follows the kit protocol outlined above, except with our specific range of melting and annealing temperatures calculated using <a href = "http://www.neb.com/nebecomm/tech_reference/tmcalc/"> NEB's Tm calculator </a> </li><br />
<li> Start digestion of vector and insert DNA using desired restriction enzyme manufacturer protocol. [NEB] </li><br />
<li> After 2 hours, add Phosphatase [CIP] according to manufacturer protocol to insert to prevent self-ligation </li><br />
<li> Purify and clean DNA using kit protocol. [Zymo Research] </li><br />
<li>Measure vector/insert concentration. [Nanodrop] </li><br />
<li> Divide the concentration by the length of the sequence and calculate ligation ratios of 1 vector to 3 insert. Mix the ratios according to the calculations, including T4 buffer and ligase. </li><br />
<li>Leave ligation products at room temperature for 1 hour. </li><br />
<li>Transform ligation products into competent cells using appropriate protocol. Incubate on ice for 1 hour if using Zymo competent cells </li><br />
<li>Plate cells and incubate at 37 degrees overnight. Check for colonies the next morning. If there are colonies present, inoculate 1-3 colonies into (selective) L.B. in the evening and culture overnight. </li><br />
</ol> <br />
</p><br />
<br/><br />
<br />
<h1 id = "section1-4"> Gel Protocol </h1><br />
<p><br />
<ol><br />
<li> For 7x7 cm, 0.5cm thick gel, with 1.75% agarose Concentration. </li><br />
<li> Add 0.35 grams of agarose to 20ml of 1x buffer (TBE)<br />
Note: Place mark on container to keep track of liquid level using marker, so water can be added to bring the liquid back to original level </li><br />
<li> Place gel solution in microwave. Use low/medium, set timer for 5 minutes. Stop the oven every 30 seconds and swirl gently to suspend undissolved agarose. </li><br />
<li> Once dissolved, set aside to cool (~60 degrees). Once solution is warm to touch, add 0.5ug/ml ethidium bromide. [1&#181;l of 10mg/ml]</li><br />
<li> Pour into casting tray, remember to add in comb at the cathode side (black). Gel will solidify in ~10 mins</li><br />
<li> Divide the concentration by the length of the sequence and calculate ligation ratios of 1 vector to 3 insert. Mix the ratios according to the calculations, including T4 buffer and ligase. </li><br />
<li> Remove comb for solidified gel, remove casting gates and submerge gel beneath 2 to 6mm of 1x buffer. </li><br />
<li> Mix loading dye with PCR/digested products, load mixture into wells, together with 10&#181;l of ladder </li><br />
<li> Run gel at 75V for ~1 hour. Adjust voltage accordingly if require faster or more distinct gels. </li><br />
</ol> <br />
</p><br />
<br/><br />
<br />
<p><h1 id = "section1-5"> Dosage Curve </h1><br />
<br />
<p><br />
<ol><br />
<li> The night before the experiment, start an overnight culture by seeding 1:100 of expression cell stock to fresh selection media [Typically 30&#181;l stock to 3ml LB+Amp]. Place tube in a shaking water bath at 37 degrees celsius overnight. </li><br />
<li> Culture a fresh batch of cells using 1:100 of overnight culture prepared to selection media. Culture in a shaking 37 degrees celsius water bath for around 2 hours or until the solution is lightly turbid. </li><br />
<li> Induce cells by adding 1&#181;l of 1M IPTG. Incubate cells in a shaking water bath at 37 degrees celsius for 2 hours. </li><br />
<li> Aliquot 1ml of induced cells into an 1.5ml Eppendorf tube and spin down the cells at 10,000rpm for 1min and discard the supernatant. Wash the cells with 1ml of PBS, repeat spinning down the cells at 10,000rpm and discard the supernatant. Resuspend the washed cells in 1mL M9 media. </li><br />
<li> To increase DFHBI fluorescence, add 1µL of 50nM Mg2+ to the tubes (from MgCl2 from PCR kit) </li><br />
<li> Aliquot (100&#181;l/200&#181;l) of cells into desired wells of a 96-well plate.</li><br />
<li>To each of the 96-wells, add 1&#181;l of 1mM IPTG to maintain the production of FAP and Spinach. Add various doses of DFHBI to the wells intended for testing DFHBI dosage. To a separate set of wells, add the desired doses of MG. </li><br />
<li> Incubate for 45mins in 37 degrees celsius, as recommended by Paige et al. Plate read with plate reader (Tecan Safire II). First find cell density using OD600. Then use Excitation/Emission of 469/501 for Spinach and 635/660 for Malachite-green. </li><br />
</ol> <br />
</p><br />
<br/><br />
<br />
<h1 id = "section1-6"> Time Lapse Protocol </h1><br />
<br />
<p><br />
<ol><br />
<li> For the temporal analysis, we will be characterizing different promoters. Culture fresh batches of cells using 1:100 of overnight culture of the different promoter constructs. Do include the wild type promoter to act a a form of comparison. Culture for around 2 hours or until the solution is lightly turbid. </li><br />
<li> Culture a fresh batch of cells using 1:100 of overnight culture prepared to selection media. Culture in a shaking 37 degrees celsius water bath for around 2 hours or until the solution is lightly turbid. </li><br />
<li> For each ml of cells required for the assay: Aliquot 1ml of cells into 1.5ml Eppendorf tubes and spin down the cells at 10,000rpm for 1min and discard the supernatant. Wash the cells with 1ml of PBS, repeat spinning down the cells at 10,000rpm and discard the supernatant. Resuspend the washed cells in 1mL M9+3&#181;l 50nM Mg media.</li><br />
<li> Reserve part of the cells for testing the un-induced construct for leaky expression. Add 1&#181;l of 1M IPTG per ml of remaining cells </li><br />
<li> Aliquot 100&#181;l of induced and uninduced cells per well into a 96-well plate </li><br />
<li> Add the maximum dosage of DFHBI and MG as determined by the dosage curve into separate wells for each of the clones. </li><br />
<li>To each of the 96-wells, add 1&#181;l of 1mM IPTG to maintain the production of FAP and Spinach. Add various doses of DFHBI to the wells intended for testing DFHBI dosage. To a separate set of wells, add the desired doses of MG. </li><br />
<li> As soon as the dyes are added, measure samples using the plate reader (Tecan Safire II). Measure cell density using absorbance @600nm, followed by Excitation/Emission of 469nm/501nm for Spinach and 635nm/660nm for Malachite-green. Set the plate reader temperature to 37 degrees and to shake the plate for 10 seconds every 10mins. Repeat the OD and fluorescence measurements every 30minutes until the fluorescence output begins to plateau (~3 hours). </li><br />
</ol> <br />
</p><br />
<br/><br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Met-ResultsTeam:Carnegie Mellon/Met-Results2012-10-27T03:30:47Z<p>Ychoo: </p>
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<br />
<h1>Dosage Curves of Spinach and FAP with Their Respective Dyes</h1><br />
<p><br />
To understand binding kinetics and equilibria of both Spinach and FAP with their respective fluorogens, we collected dosage curves of the biosensors by adding different concentrations of fluorogens to bacteria that express both Spinach and FAP. Based on the dosage curves, we calculated dissociation constants (K<sub>D</sub>) of each biosensor-fluorogen complex and saturating dose of each fluorogen. <br />
</p><br />
<br><br />
<br />
<p><br />
<img src="http://partsregistry.org/wiki/images/f/f8/CMU_Spin-DFHBI1.jpg", width="729", height="430"> <br \><br />
<strong>Figure 1: Fluorescence intensities of Spinach-DFHBI at a fixed concentration of Spinach and different concentrations of added DFHBI </strong>. <br />
<br><br />
<br />
The measured K<sub>D</sub> of the Spinach-DFHBI complex is 537nM <sup>[2]</sup>. Our measured K<sub>D</sub> also has a nanomolar affinity. We also measured the dosage curves at both 10th and 60th minute timepoint. We did not observe significant differences in the fluorescence levels, suggesting that DFHBI diffusion across bacterial membrane and its binding to Spinach occurs rapidly. Lines are drawn as guide of eyes. Please refer to the Protocols page for details of experiments. <br />
<br><br><br />
<br />
<img src="http://partsregistry.org/wiki/images/1/14/CMU_FAP-MG1.jpg", width="729", height="436"> <br \><br />
<strong>Figure 2: Fluorescence intensities of FAP-MG at a fixed concentration of FAP and different concentrations of added MG </strong>.<br />
<br><br />
The measured K<sub>D</sub> of the FAP-MG complex is close to the published value of 320nM <sup>[1]</sup>. A line is drawn as guide of eyes. Please refer to the Protocols page for details of experiments. <br />
</p><br />
<br />
<br><br><br />
<br />
<h1>RNA and Protein Expression Levels of T7Lac Promoters</h1><br />
<p><br />
We aim to compare expression levels of three new T7Lac promoters with the wild-type T7Lac promoter, when either 3,5-difluoro-4-hydroxybenzylidene imidazolinone (DFHBI) or Malachite Green (MG) is added. DFHBI is a specific fluorogen that binds to Spinach and MG is a specific fluorogen that binds to FAP. Therefore, we assume that there is a positive correlation between fluorescence values and the amount of either RNA and proteins in bacteria. <br />
</p><br />
<br />
<p><br />
<img src="https://static.igem.org/mediawiki/igem.org/5/5c/CMU_Spin-DFHBI2.jpg", width="689", height="384"><br><br />
<strong>Figure 3: Spinach fluorescence (reporter for RNA levels) over time</strong>. <br />
<br><br />
Fluorescence values increase over time with all promoters. Mutant I (BBa_K921000) closely parallels the wild-type promoter in terms of magnitudes and expression rates of Spinach. Mutant II (BBa_K921001) exhibits significantly lower fluorescence levels than the wild-type promoter, indicating slower mRNA transcription rates. Fluorescence levels of mutant III (BBa_K921002) seems to be increasing at an accelerating rate as compared to the wild-type promoter and reach a significantly higher fluorescence level at the end of the experiment. All fluorescence values are normalized by the corresponding OD600 readings. Each error bar indicates one standard deviation of two replicates. Please refer to the Time-Lapse protocol in the Protocols page for the full experimental details.<br />
<br><br><br />
<br />
<img src="https://static.igem.org/mediawiki/igem.org/d/d0/CMU_FAP-MG2.jpg", width="689", height="384"><br><br />
<strong>Figure 4: FAP fluorescence (reporter for protein levels) over time </strong>.<br />
<br><br />
Fluorescence values increase over time with all promoters. The fluorescence level of Mutant I (BBa_K921000) increases more rapidly than the other constructs, indicating that this promoter indirectly increases the translation rate of mRNA. Fluorescence levels of mutant II (BBa_K921001) closely parallels the wild type fluorescence levels, being only slightly lower in magnitude. Mutant III's fluorescence levels (BBa_K921002) increase very rapidly at first, but seems to be leveling off after one hour. This may indicate that bacteria have adapted host machinery to compensate for the metabolic burden. The metabolic burden could also result in larger OD600 and fluorescence fluctuations across replicates, which could give rise to large error bars. All fluorescence values are normalized by the corresponding OD600 readings. Each error bar indicates one standard error of two replicates. Please refer to the Time-Lapse protocol in the Protocols page for the full experimental details.<br />
<br />
<br><br><br />
<img src="http://partsregistry.org/wiki/images/0/09/CMU_leakyp.jpg", width="464", height="295"><br><br />
<img src="http://partsregistry.org/wiki/images/b/b4/CMU_leakyr.jpg", width="465", height="295"><br><br />
<br />
<br><strong>Figure 5: Leaky RNA (top panel) and protein (bottom panel) expression levels of our T7Lac promoters in BL21(DE3) cells.</strong> <br />
<br><br />
The leaky expression level of BBa_K921000 promoter is noticeably lower than the wild type promoter, which is consistent with the low RNA expression rates after induction of the promoter. However, the leaky expression levels of both BBa_K921001 and BBa_K921002 promoters are noticeably higher than the wild type promoter. Uninduced cells (without IPTG) were added to wells in a 96 well plate supplemented with either 200µM of DFHBI or 10µM of malachite green. Fluorescence intensities at the 3rd hour time point are shown for comparison between promoters.</p><br />
<br><br />
<p><br />
<img src="https://static.igem.org/mediawiki/2012/d/de/Ts.png" height="300" width="380" align="center"/><br />
<img src="https://static.igem.org/mediawiki/2012/9/9b/Tl.png" height="300" width="380" ><br><br />
<strong>Figure 6: Calculated values of transcription strength (left panel) and translation efficiency (right panel).</strong><br />
<br><br />
Raw fluorescence values were normalized by OD600. Next, the normalized fluorescence values were fitted using differential equations that we developed to model our system. <br />
<br><br />
<br><br />
<h1>Conclusion and Future Work</h1><br />
<p><br />
Based on our coupled RNA and protein biosensors, we have successfully characterized both translation and transcription rates of four T7Lac promoters. The coupled and non-invasive measurements of RNA and protein levels open doors to tremendous opportunities in studies of metabolic burden, gene regulation, and synthetic gene circuits.<br />
<br><br><br />
In the near future, we plan to establish the kinetics of our biosensors more thoroughly using different bacterial strains and growth conditions. Furthermore, we plan to extend our study to different promoters and RBS, which could potentially generate new insight into the tight interplay between transcription and translation reactions.<br />
</p><br />
<br />
<hr \><br />
<font size="2"><br />
<sup>[1]</sup> Szent-Gyorgyi, Christopher, Brigitte A. Schmidt, Yehuda Creeger, Gregory W. Fisher, Kelly L. Zakel, Sally Adler, James A J. Fitzpatrick, Carol A. Woolford, Qi Yan, Kalin V. Vasilev, Peter B. Berget, Marcel P. Bruchez, Jonathan W. Jarvik, and Alan Waggoner. "Fluorogen-activating Single-chain Antibodies for Imaging Cell Surface Proteins." Nature Biotechnology 26.2 (2007): 235-40. Print.<br />
<br \><br />
<sup>[2]</sup> Paige, J. S., K. Y. Wu, and S. R. Jaffrey. "RNA Mimics of Green Fluorescent Protein." Science 333.6042 (2011): 642-46. Print.<br />
</font><br />
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<h1>The Design of Fluorogen-Activated Biosensors</h1><br />
<p><br />
Our synthetic reporters consist of a Spinach RNA reporter and a FAP protein reporter. By placing a promoter of interest immediately upstream of Spinach, we can measure a fluorescence signal from mRNA that is transcribed from the promoter. To measure protein expression levels, we placed a ribosomal binding site (RBS) and a FAP at 14 base-pairs downstream of the Spinach sequence to avoid a steric clash between the Spinach RNA secondary structure and the ribosome. This way, we can measure the expression levels of both RNA and proteins in each cell over time. Our modular construct allows the plug-and-play of promoters, hence allowing tremendous flexibility in the characterization of any promoters. This coupled system has several advantages over traditional systems that only measure protein levels through fluorescent molecules such as green fluorescent proteins (GFP), CFP, and YFP. Our reporters differ significantly from the classical fluorescent proteins in that they only fluoresce upon the binding of specific fluorogens (malachite green for the FAP reporter and DFHBI for the Spinach reporter). This construct allows us to address differences in RNA and protein expression dynamics. The plasmid map is shown here.</p><br />
<p> <img src="https://static.igem.org/mediawiki/igem.org/1/1b/CMU_plasmid_map.jpg" height="400", width="511"></img></p><br />
<br><br />
<p>A simplified version of our construct is shown here.<br><img src="https://static.igem.org/mediawiki/igem.org/a/a4/CMU_Linear_pmap.jpg" width="800", height"41"></p><br />
<br />
<h1>The Design of Fluorescence Spectra and Measurements</h1><br />
<p><br />
To measure both RNA and protein levels simultaneously in a single cell, we need to design the fluorescence spectra such that the emission spectra do not overlap significantly. Therefore, we have chosen to use a FAP with Ex/Em=635/660. This FAP has a far-red emmision spectra that would be well-separated from any green fluorescent probes. For RNA measurements, we used a Spinach with Ex/Em=469/501. As shown by the following fluorescence spectra, the emission spectra of both FAP and Spinach do not overlap. Note, however that the excitation spectra have a small overlap, which may prove to be useful in FRET experiments. For our experiments, we did not mix dyes in wells with induced cells.<br />
<br />
<br> <br />
<h3>L5 FAP (MG) Excitation and Emission Spectra</h3><br />
<img src="https://static.igem.org/mediawiki/2012/c/c9/L5_Excitation-Emission.jpg"><br><br />
<h3>Spinach (DFHBI) Excitation and Emission Spectra</h3><br />
<img src="https://static.igem.org/mediawiki/2012/7/7a/Spinach_Excitation-Emission.jpg", width="329"><br></p><br />
<br />
<br><br />
In our experiments, fluorescence intensities were measured using a Tecan SafireII at their maximum excitation and emission peaks with a 10nm bandwidth and optimal gain (100 for Spinach and 255 for the FAP). <br />
<br> <br><br />
<br />
<br />
<h1>Sequences of Spinach and FAP</h1><br />
The coding sequence of the Spinach RNA reporter is as follows<sup>[1]</sup>:<br />
<br><b>GCCCGGATAGCTCAGTCGGTAGAGCAGCGGCCGAGTAATTTACGTCGACGACGCAACCGAATGAAATGGT<br>GAAGGACGGGTCCAGGTGTGGCTGCTTCGGCAGTGCAGCTTGTTGAGTAGAGTGTGAGCTCCGTAACTGG<br>TCGCGTCGACGTCGATGGTTGCGGCCGCGGGTCCAGGGTTCAAGTCCCTGTTCGGGCGCCA</b><br />
<br><br />
The coding sequence of the FAP protein reporter is as follows<sup>[2]</sup>:<br />
<br><b>CAGGCGGTGGTGACCCAGGAACCGAGCGTGACCGTGAGCCCGGGCGGCACCGTGATTCTGACCTGCGGCA<br>GCAGCACCGGCGCGTGCACCAGCGGCCATTATGCGAACTGGTTTCAGCAGAAACCGGGCCAGGCGCCGCG<br>CGCGCTGATTTTTGAAACCGATAAAAAATATAGCTGGACCCCGGGCCGCTTTAGCGGCAGCCTGCTGGGC<br>GCGAAAGCGGCGCTGACCATTAGCGATGCGCAGCCGGAAGATGAAGCGGAATAT<br>TATTGCAGCCTGAGCGATGTGGATGGCTATCTGTTTGGCGGCGGCACCCAGCTGACCGTGCTGAGC</b><br />
<br> <br><br />
<br />
<p><br />
Ribosome binding site used in construct:<br><br />
<b>AAGAAGGAGA</b> TATACC ATG(start) (Used in part BBa_K112227 and used in pRSET shuttle vectors)<br />
<br> <br />
Note:<br />
In our experiments, we used an improved version of the original L5 FAP that was published in Nature Biotechnology in 2008. The engineered version binds malachite green faster than L5 FAP. Due to unresolved issues of intellectual property, we could not deposit these reporters in the parts registry. However, we may be able to share the parts upon formal requests by other labs.</p><br />
<br><br />
<br><br />
<br />
<hr \><br />
<p><font size="2"><br />
<sup>[1]</sup>Jeremy S. Paige, Karen Y. Wu, and Samie R. Jaffrey, et al. RNA Mimics of Green Fluorescent Protein. <br />
Science 29 July 2011: 333 (6042), 642-646. [DOI:10.1126/science.1207339]<br />
<br> <br />
<sup>[2]</sup>Shruti S, Urban-Ciecko J, Fitzpatrick JA, Brenner R, Bruchez MP, et al. (2012) The Brain-Specific Beta4 Subunit Downregulates BK Channel Cell Surface Expression. PLoS ONE 7(3): e33429. doi:10.1371/journal.pone.0033429 </p><br />
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<p><br />
We have submitted three T7Lac promoter parts to the registry. The followings show the sequences of these constructs.</br><br />
<br />
(<a href="http://partsregistry.org/Part:BBa_K921000"> BBa_K921000 </a> ) Mutant I: TAATGCGACTCACTATAGGACAATTGTGGGCGGACAACAATTCCAA <br><br />
(<a href="http://partsregistry.org/Part:BBa_K921001"> BBa_K921001 </a> ) Mutant II: TAATACGACTCACTACAGGGCGGAATTGTGAGCGGATAACAATTCCAA <br><br />
(<a href="http://partsregistry.org/Part:BBa_K921002"> BBa_K921002 </a> ) Mutant III: CAATCCGACTCACTAAAGAGAGAATTGTGAGCGGATAACAATTCCAA <br><br />
</p><p class="promoter"><br />
<br />
<br />
<h1> Characteristics of our hybrid T7Lac promoters </h1><br />
<h3 class="pre-experiment">Predicted Strength</h3><br />
<br />
Expected promoter strength of the mutants (relative to BBa_K613007):<br><br />
Mutant I: <100% <br><br />
Mutant II: ~100% <br><br />
Mutant III: ~50%<br><br />
<br />
</p><p class="leaky"><br />
Expected LacI leaky expression of different mutants: <br><br />
Mutant I: More than average <br><br />
Mutant II: Average <br><br />
Mutant III: Average <br><br />
<br><p><br />
Promoters were rationally designed to have the previously described characteristics according to the reported findings by<br />
Ikeda et al.<sup><a href ="#cite1">[1]</a></sup>, Sadler et al.<sup><a href ="#cite2">[2]</a></sup>, Gilbert et al.<sup><a href ="#cite3">[3]</a></sup>. Mutant 1 has mutations in the recognition site and the initiation site that have been previously shown to decrease initiation frequency. Mutant II was designed to have a melting box mutation, which prevents the DNA from melting, to start transcription. The overall effect of this mutation was not known but the hypothesis was that transcription strength would be exceed the wild type. Mutant III contains mutations described by Ikeda et al, which are associated with class II promoters. The mutations that are associated with this class of T7 promoters affect how well the polymerase clears the promoter sequence. This mutant is expected to produce much less protein than the wild type.</p><br />
<p> The lac operators in these promoters were rationally designed as well, according to the finding of Sadler et al and Gilbert et al. The promoters were designed to have a nearly palindromic sequence as described by Sadler et al to increase lacI repressor affinity. Mutant I includes mutations that have been shown to favor lacI repressor binding. Mutants II and III contain mutations in the lac operator but are not expected to have increased performance <i>in vivo</i>.<br />
</p><br />
</p><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview">Click here</a> to see our results discussion.<br />
<br />
<h3 class="pre-experiment">Measured Strength</h3><br />
<p><br />
We have measured both RNA and protein expression levels of the designed T7Lac promoters using fluorogen-activated biosensors (see details in <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> Methods & Results </a>). These experimental results were analyzed using a mathematical model that we developed in MATLAB (see details in <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> Model </a>). Based on the analysis, we obtained the following properties of the new T7Lac promoters with respect to the wild-type T7Lac promoter.<br />
</p><br />
<br />
<strong>Table 1: Relative transcription and translation rate constants of three T7Lac promoters as compared to the wildtype T7 promoter</strong><br><br />
<table border="1" cellpadding="5"><br />
<br />
<tr><br />
<th>Promoter</th><br />
<td> Mutant I </td><br />
<td> Mutant II </td><br />
<td> Mutant III </td><br />
</tr><br />
<br />
<tr><br />
<th>Transcription Strength</th><br />
<td> 97% </td><br />
<td> 72% </td><br />
<td> 127% </td><br />
<br />
</tr><br />
<br />
<tr><br />
<th>Translational Efficiency</th><br />
<td> 169%</td><br />
<td> 90%</td><br />
<td> 160%</td><br />
<br />
</tr><br />
</table><br />
<br />
<br \><br />
<h1>Discussion</h1><br />
<br><br />
<b>BBa_K921000</b><br><br />
<p>The design of Mutant I (BBa_K921000) was based on random mutations throughout the promoter region including the recognition site, initiation site, and the lac operator. This promoter was expected to have a lower affinity to the T7 RNAP and therefore have a lower RNA and protein expression rates. The mutant I (BBa_K921000) promoter produces less RNA, but more protein than the wild type promoter. We hypothesize that the difference between prediction and experimental results is due to cellular adaptation to metabolic burden.<br />
<br><br><br />
<br><br />
<b>BBa_K921001</b><br><br />
The design of this mutant T7Lac promoter (BBa_K921001) was based on random mutations throughout the promoter including the recognition site, melting box, initiation site, and the lac operator. This promoter was expected to exhibit a significantly lower initiation frequency due to the T->C mutation in the melting box. RNA polymerase denatures DNA at the melting box to initiate transcription. The melting box TATA can be found in all T7 promoters. Thymine and adenine have lower melting temperatures and are easily melted. Guanine and cytosine form an extra hydrogen bond and cause base stacking, which increases their melting temperature, making it more difficult for RNAP to initiate transcription. This mutation was rationally made to decrease an initiation frequency, resulting in a weaker T7Lac promoter. Indeed, mutant II (BBa_K921001) of this set of T7Lac promoters produces less protein than the wildtype T7 promoter. <br><br><br />
<br><br />
<b>BBa_K921002</b><br><br />
The design of this mutant T7Lac promoter (BBa_K921002) was based on a different class of T7 promoters, which are weaker than the wildtype T7 promoter. Therefore, this promoter was expected to produce less protein than the wildtype promoter. However, this mutant promoter produces more RNA and protein than the wildtype promoter in our experiments. <br><br><br />
<br />
<hr><br />
<b>Citations:</b><br />
<p><br />
<a name = "cite1"></a><sup>[1]</sup>Ikeda RA. The efficiency of promoter clearance distinguishes T7 class II and class III promoters. J Biol Chem. 1992 Jun 5;267(16):11322-8.<br />
<br><br />
<a name = "cite2"></a><sup>[2]</sup>Gilbert, Walter, and Allan Maxam. "Result Filters." <i>National Center for Biotechnology Information.</i> U.S. National Library of Medicine, n.d. Web. 03 Oct. 2012. <http://www.ncbi.nlm.nih.gov/pubmed/4587255>.<br />
<br><br />
<a name = "cite3"></a><sup>[3]</sup>Sadler, J. R. "A Perfectly Symmetric Lac Operator Binds the Lac Repressor Very Tightly." <i>Proceedings of the National Academy of Sciences</i> 80.22 (1983): 6785-789. Print.<br />
</p><br />
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<h1> Promoter Variants</h1><br />
<p><br />
We have created three new T7Lac hybrid promoters that are mutated based on both the T7 promoter and the lac operator. The hybrid promoters enable high gene expression levels by T7 RNA polymerase, while allowing control of the expression levels by IPTG. All three biobricks have been submitted to the Registry of Standard Biological Parts, together with detailed characterization of both RNA and protein expression levels of the promoters (<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview">See our method of analysis</a>).<br />
</p><br />
<br /><br />
<br />
<br />
<h3> T7 Promoter </h3><br />
<p><br />
The T7 promoter comes from the phage T7 and is a strong promoter. T7 promoters can only be expressed in strains of bacteria that express T7 RNA polymerase (the unique polymerase that activates gene expression from the T7 promoter). T7 promoters can be classified into different classes, and each class corresponds to a different level of gene expression level. The commonly used T7 promoter is the class I variant because of its ability to produce a high amount of protein. The T7 promoter has three distinct regions: a recognition site, a melting box, and an initiation site. The recognition site is the specific region that the T7 promoter binds to. The melting box is a highly conserved sequence, which is also known as the TATA box. The melting box allows the T7 RNAP to melt the two strands of DNA and start adding NTPs to build mRNA. The initiation site is where the first nucleotide of the mRNA is added. T7 RNAP favors the addition of guanine. As a result, most T7 promoters have a poly-G region of 3-5 nucleotides to increase the chance of initiation.<br />
</p><br />
<br />
<p><br />
TAATACGACTCACTATAGGG<br /><br />
T7 region:<br><br />
<b>TAATACGACTCAC</b> - Recognition site<br><br />
<b>TATA</b> - Melting box<br><br />
<b>GGGAGA </b> - Initiation site<br><br />
</p><br />
<br />
<h3> LacO Operator and LacI Repressor</h3><br />
<p><br />
The LacO operator is a DNA sequence that is recognized by the LacI repressor. The LacI repressor is found in the lac operon of <i>E. coli</i>. When a LacO operator is located in a promoter region, LacI repressor prevents transcription from the promoter by forming a "hairpin" like structure that prevents RNAPs from traveling along the DNA. The LacI repressor cannot bind to the LacO operator when lactose is bound to LacI. This property can be exploited to prevent the expression of a certain gene by modulating the level of lactose or a lactose analog. Since lactose is consumed by <i>E. coli</i>, researchers found an analog (called Isopropyl β-D-1-thiogalactopyranoside IPTG) that binds to the lacI repressor, but is not consumed by <i>E. coli</i>. The wild type lac operator is nearly-symmetrical and has its own binding properties. In our constructs, we characterized a symmetrical lac operator and measured its leaky expression levels (the amount of expression without the inducer present). <br />
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</li><br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software">Software</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team">Team Presentation</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Teaching">Teaching Presentation</a><br />
</li><br />
</ul> <br />
</li> <br />
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<br /><br /><br /><br />
<br />
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<!--Main Contents --><br />
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<br />
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
<li><a href="#section1-4">1.2 Question 4</a></li><br />
<br />
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<br />
<h1> Our Supporters </h1><br />
<img src= "https://static.igem.org/mediawiki/2012/c/c9/Logos-cons.png" width="100%"> </img><br />
<br \><br />
<br \><br />
<h1> A Big "Thank you!" Goes to: </h1><br />
<br \><br />
Prof. Marcel Bruchez<br />
<br \> Prof. Michael Domach<br />
<br \>Prof. Carrie Doonan<br />
<br \>Prof. Emily Drill<br />
<br \> Prof. Eric Grotzinger<br />
<br \>Prof. Veronica Hinman<br />
<br \>Prof. Jon Jarvik<br />
<br \>Prof. Philip LeDuc<br />
<br \>Prof. Nathan Urban<br />
<br \><br />
Dr. Sebastian Stoian<br />
<br \>Dr. Christopher Szent-Gyorgyi<br />
<br \>Dr. Kalin Vasilev<br />
<br \>Dr. Janet Waldeck<br />
<br \>Dr. Carol Woolford <br />
<br \> <br />
Charlotte Bartosh<br />
<br \>Stephanie Blotner<br />
<br \>Ronni Rossman<br />
<br \>Saumya Saurabh<br />
<br \>Sombeet Sahu<br />
<br \><br />
<br><br />
For the wiki, thanks to the following references:<br />
<br> <a href = "http://users.tpg.com.au/j_birch/plugins/superfish/">Superfish</a><br />
<br> <a href = "http://www.mathjax.org">MathJax</a><br />
<br> <a href = "https://2011.igem.org/Team:DTU-Denmark/How_to_customize_an_iGEM_wiki"> DTU-Denmark's Wiki Walkthrough </a><br />
</html><br />
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Each team member (Yang, Eric, Jesse and Peter) contributed to multiple parts of the overall project. <br />
<br><br />
<p><br />
All four students brainstormed possible project ideas during the Spring and finally agreed on promoter characterization using fluorogen-activating biosensors.</p><br />
<p><br />
Yang and Eric kept the notebooks, designed experiments and followed through with the biological experiments (including cloning, culturing the cells, fluorescence spectroscopy and fluorescence microscopy). Yang designed the wiki layout and made modifications as necessary. Eric was a consultant with Peter to incorporate a biologically accurate model. Eric also designed the expanded model with Peter to include more information. Peter designed the model and derived the equations to fit our system and performed the nonlinear regression to attain the data we put onto the Parts Registry. Jesse designed the interactive circuit kit and GUI and provided the open source documentation on the wiki so that other groups may use it as a basis for their own projects. </p><br />
<p><br />
All four students presented our project and circuit kit throughout the summer. Eric and Peter gave a presentation at Taylor Allderdice High School in Pittsburgh during the academic school year. <br />
</p><br />
<p><br />
The summer experiments were conducted in the Mellon College of Science's Interdisciplinary Laboratory, courtesy of Dr. Karen Stump, Dr. Eric Grotzinger and Dr. Maggie Braun. The experiments during the year were conducted in Dr. Robert Murphy's lab with our team instructor Cheemeng Tan. The fluorescence spectroscopy was performed in the Molecular Biosensors and Imaging Center at Carnegie Mellon and the fluorescence microscopy was performed in Dr. Aaron Mitchell' laboratory.<br />
</p><br />
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<ul class="toc-sub closed"><br />
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<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
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<br />
<h1> The Team </h1><br />
<br \><br />
<table width = "80%" cellspacing = "5" cellpadding ="0"><br />
<tr> <td width = "50%" align = "middle"> <img src = "https://static.igem.org/mediawiki/2012/3/3a/Cmu_yang_photo.jpg" height = "250" width = "250"> </td><br />
<td width = "50%"> <div class ="name"> Yang Choo </div> <br \> Junior <br \> Department of Chemical Engineering and Biomedical Engineering <br> Primary responsibility: Wetlab </td><br />
</tr><br />
<br />
<table width = "80%" cellspacing = "5" cellpadding ="0"><br />
<tr> <td width = "50%" align = "middle"> <img src = "https://static.igem.org/mediawiki/2012/d/dc/Cmu_eric_photo.jpg" height = "250" width = "250"> </td><br />
<td width = "50%"> <div class ="name"> Eric Pederson</div> <br \> Sophomore <br \> Department of Biological Sciences <br> Primary responsibility: Wetlab </td><br />
</tr><br />
<br />
<table width = "80%" cellspacing = "5" cellpadding ="0"><br />
<tr> <td width = "50%" align = "middle"> <img src = "https://static.igem.org/mediawiki/2012/5/55/Cmu_peter_photo.jpg" height = "250" width = "250"> </td><br />
<td width = "50%"><div class ="name"> Peter Wei </div><br \> Sophomore <br \> Department of Electrical and Computer Engineering, and Biomedical Engineering <br> Primary responsibility: Modeling </td><br />
<br />
<table width = "80%" cellspacing = "5" cellpadding ="0"><br />
<tr> <td width = "50%" align = "middle"> <img src = "https://static.igem.org/mediawiki/2012/5/56/Cmu_jesse_photo.jpg" height = "250" width = "250"> </td><br />
<td width = "50%"><div class ="name"> Jesse Salazar </div><br \> Senior <br \> Department of Electrical and Computer Engineering, and Biomedical Engineering <br> Primary responsibility: Circuit Kit </td><br />
</tr><br />
</tr><br />
<br />
</table><br />
<br \><br />
<br />
<br />
<br />
<h1> The Instructors </h1><br />
<br \><br />
<table width = "80%" cellspacing = "5" cellpadding ="0"><br />
<tr> <td width = "50%" align = "middle"> <img src = "https://static.igem.org/mediawiki/2012/e/e5/Cmu_cheemeng_photo.jpg" height = "250" width = "250"> </td><br />
<td width = "50%"><div class ="name"> Cheemeng Tan </div> <br \> Lane Post-doctoral Fellow <br \> Lane Center of Computational Biology </td><br />
</tr><br />
<br />
<table width = "80%" cellspacing = "5" cellpadding ="0"><br />
<tr> <td width = "50%" align = "middle"> <img src = "https://static.igem.org/mediawiki/2012/b/bc/Cmu_natasa_photo.jpg" height = "250" width = "250"> </td><br />
<td width = "50%"><div class ="name"> Natasa Miskov-Zivanov </div><br \> Adjunct Faculty <br \> Department of Electrical and Computer Engineering </td><br />
</tr><br />
<br />
</table><br />
<br \><br />
<br />
<h1> The Advisors </h1> <br />
<br \><br />
<table width = "80%" cellspacing = "5" cellpadding ="0"><br />
<tr> <td width = "50%" align = "middle"> <img src = "https://static.igem.org/mediawiki/2012/0/0f/Cmu_catalina_photo.jpg" height = "250" width = "250"> </td><br />
<td width = "50%"><div class ="name"> Catalina Achim </div><br \> Professor <br \> Department of Chemistry <br \> <br \> Associate Director <br \> The Center for Nucleic Acids Science and Technology </td><br />
</tr><br />
<br />
<tr> <td width = "50%" align = "middle"> <img src = "https://static.igem.org/mediawiki/2012/b/b4/Cmu_diana_photo.jpg" height = "250" width = "250"> </td><br />
<td width = "50%"><div class ="name"> Diana Marculescu </div> <br \> Professor <br \> Department of Electrical and Computer Engineering </td><br />
</tr><br />
<br />
<tr> <td width = "50%" align = "middle"> <img src = "https://static.igem.org/mediawiki/2012/c/cc/Cmu_aaron_photo.jpg" height = "250" width = "250"> </td><br />
<td width = "50%"><div class ="name"> Aaron Mitchell </div> <br \> Professor <br \> Department of Biological Sciences </td><br />
</tr><br />
<br />
<tr> <td width = "50%" align = "middle"> <img src = "https://static.igem.org/mediawiki/2012/1/12/Cmu_ge_photo.jpg" height = "250" width = "250"> </td><br />
<td width = "50%"><div class ="name"> Ge Yang</div> <br \> Assistant Professor <br \> Department of Biomedical Engineering, Computational Biology, & Biological Sciences (by courtesy) </td><br />
</tr><br />
<br />
</table><br />
<br \><br />
<br />
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<h1> An Introduction to Promoters</h1><br />
<p><br />
Promoters are upstream sequences that regulate transcription. Promoters are usually short sequences and act as binding sites for RNA polymerases. Promoters have different binding affinities based on their sequence and can be characterized in different ways. Our project aims to measure some of these properties using fluorescence measurements. In our case, we are characterizing promoters that bind to RNA polymerase from the T7 phage. The T7 RNA polymerase binds to its promoter very tightly and produces a high amount of RNA. The lac operator is a short sequence that binds to the LacI repressor, which prevents transcription. The LacI protein is inhibited by lactose. Lactose analogs have been made, which are not consumed by E. coli and can be used to "turn on" the gene of interest. Our promoters have different affinities to the T7 RNA polymerase and the LacI repressor and therefore have different measurable properties.<br />
</p><br />
<br />
<h1> What Is Fluorescence?</h1><br />
<p><br />
Fluorescence is a property of certain molecules, particularly aromatic organic dyes. These molecules can absorb photons at a certain wavelength and emit them at a longer wavelength. Fluorescence is described using quantum mechanics principles and organic chemistry. Five and six-member rings tend to fluoresce brightly because of electron delocalization and the quantum properties that are associated with it. Fluorescent molecules are known as fluorophores and can take the form of organic dyes or proteins. So far, many different types of fluorophores have been discovered, developed and studied in great detail. Typically, a fluorescent protein has a fluorophore that consists of a few side chains that react and form a complex similar to that of an organic dye. For example, GFP (the most common fluorescent protein) has an HBI fluorophore. Our Spinach construct binds to a dye that is derived from this fluorophore. The fluorescence of a molecule can depend on conformation, in the case of our fluorogens, malachite green and DFHBI, which are conditional fluorophores, the molecule must be in a certain conformation to fluoresce. Otherwise, it will absorb photons, but it will emit them very inefficiently (extremely low quantum yield). Fluorescence is a widely studied phenomena and a lot of research is involved with improving current fluorescence technologies and its applications.</p><br />
</p><br />
<br />
<h1>What Is Spinach?</h1><br />
<img src="https://static.igem.org/mediawiki/2012/archive/e/e4/20120620211241!Spinach_Graphic_6-20-12.jpg" height="300" width="433" align="right"/><br />
<p><br />
Spinach is an RNA sequence that can be expressed in cells (in this case, E. coli ) and fluoresces green when DFHBI (an organic dye) is bound to it. Spinach can be fused to RNAs of interest to quantify RNA concentrations in a cell. Spinach binds to an organic dye called DFHBI that doesn't fluoresce by itself but fluoresces very brightly when it is bound to Spinach. DFHBI is chemically derived from the chromophore in GFP but is altered to increase brightness when bound to RNA. Other fluorescent RNAs have been described, but many are non-specific and have many unwanted functions like cytotoxicity. Spinach utilizes a scaffold that derives from a tRNA sequence, which disguises the RNA so that they are less prone to RNases degradation. RNase A has been shown to degrade Spinach, however. Manipulations to the sequence that Spinach is attached to allows for a variety of analyses functions. RNA can be arranged to bind to just about any small molecule in the same way that Spinach was developed (using a SELEX method) to track cellular metabolites. This allows for quantification of another important system in cells. In our system, Spinach is incorporated in the mRNA (between the promoter and the RBS).<a href="http://www.sciencemag.org/content/333/6042/642.full"> Click for more information on Spinach</a>. Spinach is the first published RNA sequence of its kind and more sequence/dye combinations are in development; as a result, in years to come, multiple genes (both RNA and protein) can be analyzed in great details simultaneously.<br />
</p><br />
<br /><br />
<br />
<h1> What Is a FAP?</h1><br />
<p><img src="https://static.igem.org/mediawiki/2012/4/4b/FAP_graphic_6-26-12.jpg" alt="FAP" align="right" height="300" width="433" /></p><br />
<p><br />
A fluorogen activating protein is a small (26-35kD) protein that is derived from a variable region of an human antibody. FAPs do not fluoresce unless a fluorogen (also not normally fluorescent) is added, in which case the FAP changes the conformation of the fluorogen and the complex fluoresces brightly. FAPs are currently used to tag certain proteins like actin or tubulin in mammalian cells. FAPs are primarily expressed in<i> S. cerevisiae</i> or mammalian cells although some variants have been expressed in <i>E. coli</i>. The two main dyes that the current series of FAPs bind to are malachite green and thiazole orange; our construct uses a variant that binds to malachite green. These dyes are normally cell impermeable but can be designed to penetrate cell membranes. As a result, they were originally used to tag surface proteins. FAPs are excellent reporters because they are small proteins that are soluble and have virtually no maturation time and are highly photostable unlike traditional variants of GFP. FAP technology has great potential for advancing fluorescent technology. FAPs have been used to track individual molecules to <a href="http://www.photonics.com/Article.aspx?AID=45024">5nm definition as opposed to the typical 200nm</a>. Engineered dyes, called dyedrons, have been developed that increase fluorescence intensity and can allow researchers to improve on live cell imaging techniques. Different FAPs are genetically unique and respond to different excitation wavelengths, hence could be used to image multiple proteins at the same time. Sequences of a few FAPs have been published and they are under patent protection. For this reason, we did not submit our FAPs to the parts registry.<br />
</p><br />
<br />
<h1>Why Is This Project Important?</h1><br />
<ul><br />
<p><li><br />
The ability to monitor protein production with fluorescence is a growing field that promises advances in drug development and improving quality control in drug manufacturing.</p></li><br />
<p><li><br />
Promoter strength directly affects a cell's ability to perform cellular functions like divide or move. Designing genetic circuits that do not overload cells is critical for successful implementation of synthetic biological systems.<br />
</p></li><br />
<p><li><br />
Inducible promoters are widely used in synthetic biology and iGEM, but they often lack quantitative measurements of both RNA and protein synthesis rates.<br />
</p></li><br />
<br /><br />
</html><br />
{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_MellonTeam:Carnegie Mellon2012-10-27T03:26:47Z<p>Ychoo: </p>
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<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
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<p><br />
<h3 align="center"><br />
<i><div class="glow-title">Real-time quantitative measurement of RNA and protein levels using fluorogen-activated biosensors </div></i><br />
</h3><br />
</p><br />
<br /><br /><br />
</p><br />
<br />
<h1> Introduction: Motivation and Background </h1><br />
<br />
<p><br />
<b> Our primary goal is to develop new promoters that can be measured with fluorescent technology.</b> <br />
</p><br />
<br />
<li><p> We seek to develop a system that will allow researchers in the field of synthetic biology to accurately measure a variety of metrics in gene expression networks including translational efficiency and transcriptional strength.<br />
</p></li><br />
<li><p> We hypothesize that we can use Spinach (a fluorogen-activating RNA sequence) and a FAP (fluorogen activating protein) as biosensors to measure these gene expression metrics <i>in vivo</i> (in living cells), rather than <i>in vitro</i> (in a test tube), which can be very costly and labor intensive.<br />
</p></li><br />
<li><p> We aim to characterize the relationship between synthesis rates of Spinach and transcription rates and the relationship between synthesis rates of FAP and translation rates. <br />
</p></li><br />
<br />
<br /><br /><br />
<br />
<p><h1><br />
<a name="Project_description"></a>Project Description</h1><br />
<h3><b>Experimental</b></h3><br />
<p><br />
The design and implementation of synthetic biological systems often require information on transcription and translation rates and on the impact of both RNA and protein levels on metabolic activities of host cells. Such information is needed when both strong and low levels of expression are desired, depending on the biologists’ goal, e.g., high production or single-molecule localization of a protein, respectively. To date, however, quantitative information about the expression strength of a promoter is difficult to obtain due to the lack of noninvasive and quick approaches to measure levels of RNA and protein in cells. <br />
</p><br />
<p><br />
Here, we engineer a fluorescence-based biosensor that can provide information on both transcription strength and translation efficiency that is noninvasive, easily applied to a variety of promoters, and capable of providing results in a time frame that is short when compared to current technologies. The sensor is based on the use of an RNA aptamer (termed Spinach) and a fluorogen activating protein (FAP). Both the Spinach and FAP become fluorescent in response to binding with dye molecules. The combination of FAP and Spinach will allow us to quantitatively determine relationships involving mRNA and protein, such as translational efficiency.<br />
</p><br />
<p><br />
To demonstrate the utility of the sensor, we have constructed and characterized four T7Lac promoters. For each of the promoters, we have measured both mRNA and protein fluorescence over time. The time-lapse fluorescence levels of mRNA and protein were used in a mathematical model for the estimation of transcription and translation rate constants.<br />
We have submitted these promoters to the parts registry, whose strength is measured by the newly developed biosensor.<br />
</p><br />
<br />
<p><br />
<i><a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> Learn more here</a></i><br />
</p><br />
<br />
<h3><b><br />
Human Practices<br />
</b></h3><br />
<p><br />
The impact of synthetic biology depends on the number and quality of scientists making significant contributions to the field. To this end, we contributed to raising the awareness of high school students, who may become future scientists, about the interdisciplinary field of synthetic biology, and about the preparation one needs to become a synthetic biologist.<br />
</p><br />
<p><br />
We decided to create teaching materials for high school students inspired by our team’s research project. Our goal was that these materials can be easily used by a science teacher in a lecture in a Biology or Chemistry course to (1) explain what Synthetic Biology is, and (2) enable the students to understand how our <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a> works. The teaching materials we have created, specifically a power point presentation and an <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> electronic circuit kit</a>, have become part of the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The kits in the Library are loaned to high school teachers in the Pittsburgh area to be used in teaching Math and Science. We have also tested the kit in several demonstrations in the Summer of 2012 to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> Summer Academy of Math and Science (SAMS)</a> at Carnegie Mellon.<br />
</p><br />
<p><br />
To bridge the gap between the background of a high school student and the complexity of our project, we built an affordable, microcontroller-based, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> hardware platform</a> and associated, open-source, digital simulation <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software"> software</a>. The combined hardware/software platform allows the students to directly manipulate electronic components, which are formal equivalents of the BioBricks used in our sensor, and to observe the effect of changing these components on the current or voltage output, which is the equivalent of the fluorescence intensity in our lab experiments. The software part of the platform includes the same model we created for the analysis of the sensor, and the GUI that facilitates the manipulation of the circuit kit.<br />
</p><br />
</p><br />
<p><br />
<i><a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview"> Learn more here</a></i><br />
</p><br />
<br \><br \><br />
<br />
<a name="Objective_1:_A_New_Set_of_Well-Characterized_Promoters"></a><h1> <span class="mw-headline"> Objective 1: Novel Well-Characterized Promoters </span></h1><br />
<br />
<br />
<!-- Picture of fluorescence microscopy<br />
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<p><b>Our first objective is to develop a series of BioBricks that are well characterized based on our methods of measurement.</b></p></font><br />
<br />
<p>We assert that our new method of analyzing promoters can quantify certain properties such as: </p><br />
<br />
<p><br />
<ol><li> Translational efficiency <i>in vivo </i><br />
</li><li> <i>In vivo</i> transcription rates<br />
</li><li> Promoter strength<br />
</li><li> <i>In vivo</i> mRNA and protein half-lives in real time<br />
</ol> <br />
</p><br />
<br />
<br><br />
<p>The promoters we submit were characterized with these properties. </p><br />
<br />
<p><br />
<img src="https://static.igem.org/mediawiki/2012/d/de/Ts.png" height="300" width="380" align="center"/><br />
<img src="https://static.igem.org/mediawiki/2012/9/9b/Tl.png" height="300" width="380" ><br />
<br><br />
<strong>Figure 1: Measured transcription (left panel) and translation (right panel) rate constants of three new promoters using a new fluorogen-activated biosensor. </strong><br />
<br> Based on established parts, we have developed a new biosensor that can report levels of both RNA and protein in a single cell. This biosensor enables non-invasive and real-time measurements of RNA and protein expression rates. We have applied the biosensor in the characterization of three new T7Lac promoters, which yielded high quality time-lapse data of both RNA and protein levels (see details in <a href = "https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> Methods & Results </a>). The data was used to estimate transcription and translation rate constants (see details in <a href =" https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> Modeling </a>). <br />
</p><br />
<br />
<br \><br \><br />
<br />
<a name="Objective_2:_Human_Practices"></a><h1> <span class="mw-headline"> Objective 2: Human Practices</span></h1><br />
<br />
<p> As part of our project, we seek to intrigue high school students about synthetic biology and engineering. In this pursuit, we developed an electrical analog of our BioBricks (with a simulated microscope using LEDs and a photoresistor) to teach high school students about:<br />
<ol><li> Synthetic biology and its relationship to biology, science, and engineering in general<br />
</li><li> Gene expression and the central dogma of molecular biology<br />
</li><li> How synthetic biologists tackle real-world problems<br />
</li><li> The iGEM competition and how our iGEM team's project enables one to measures the properties of promoters<br />
</li><li> The interdisciplinary nature of synthetic biology<br />
</li><li> The advantages and challenges of interdisciplinary work<br />
</li></ol><br />
</p><br />
<br \><br \><br />
<br />
<!--<br />
<a name="The_Team"></a><h1><span class="mw-headline"> The Team</span></h1><br />
<p>The 2012 Carnegie Mellon University iGEM team consists of students from Biological Sciences, Electrical and Computer Engineering, Biomedical Engineering and Chemical Engineering.<br />
<ul><li>Peter Wei (ECE, BME)<br />
</li><li>Yang Choo (ChemE, BME)<br />
</li><li>Jesse Salazar (ECE, BME)<br />
</li><li>Eric Pederson (Bio)<br />
</li></ul><br />
Advisors for the team are from the Chemistry, Biomedical Engineering, Electrical and Computer Engineering, Computational Biology, and Biological Science Departments. <br />
</p><br />
<br \><br />
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<br />
<br />
<a name="Further_Considerations"></a><h1> <span class="mw-headline"> Further Considerations </span></h1><br />
<p>In the pursuit of our project we:<br />
<ul><li> Considered the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview" rel="nofollow">ethical, legal and social implications</a> of our BioBrick<br />
</li><li> Wrote <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Matlab" rel="nofollow"> new software</a> for modeling the performance of our BioBrick<br />
</li><li> Developed and tested <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Protocols" rel="nofollow">techniques for measuring translational efficiency and transcriptional strength </a><br />
</li><li> Created materials for teaching high school students about synthetic biology and scientific research. These materials included a programmable and interactive, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit" rel="nofollow">electrical analog of our biosensor.</a><br />
</li></ul><br />
</p><br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hom-AcknowledgementsTeam:Carnegie Mellon/Hom-Acknowledgements2012-10-27T03:23:25Z<p>Ychoo: </p>
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team">Team Presentation</a><br />
</li><br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Teaching">Teaching Presentation</a><br />
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<li><a href="#section1-2">1.2 Question 2</a></li><br />
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<li><a href="#section1-4">1.2 Question 4</a></li><br />
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<h1> Our Supporters </h1><br />
<img src= "https://static.igem.org/mediawiki/2012/c/c9/Logos-cons.png" width="100%"> </img><br />
<br \><br />
<br \><br />
<h1> A Big "Thank you!" Goes to: </h1><br />
<br \><br />
Prof. Marcel Bruchez<br />
<br \> Prof. Michael Domach<br />
<br \>Prof. Carrie Doonan<br />
<br \>Prof. Emily Drill<br />
<br \> Prof. Eric Grotzinger<br />
<br \>Prof. Veronica Hinman<br />
<br \>Prof. Jon Jarvik<br />
<br \>Prof. Philip LeDuc<br />
<br \>Prof. Nathan Urban<br />
<br \><br />
Dr. Sebastian Stoian<br />
<br \>Dr. Christopher Szent-Gyorgyi<br />
<br \>Dr. Kalin Vasilev<br />
<br \>Dr. Janet Waldeck<br />
<br \>Dr. Carol Woolford <br />
<br \> <br />
Charlotte Bartosh<br />
<br \>Stephanie Blotner<br />
<br \>Ronni Rossman<br />
<br \>Saumya Saurabh<br />
<br \>Sombeet Sahu<br />
<br \><br />
<br><br />
For the wiki, thanks to the following references:<br />
<br> <a href = "http://users.tpg.com.au/j_birch/plugins/superfish/">Superfish</a><br />
<br> <a href = "http://www.mathjax.org">MathJax</a><br />
<br> <a href = "https://2011.igem.org/Team:DTU-Denmark/How_to_customize_an_iGEM_wiki"> DTU-Denmark's Wiki Walkthrough </a><br />
</html><br />
{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-OutreachTeam:Carnegie Mellon/Hum-Outreach2012-10-27T03:20:57Z<p>Ychoo: </p>
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<h1 id="section1-1"> Summer Presentations to High School Students </h1><br />
<br />
<p><br />
The <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Human Practices/Overview</a> page provides information about the teaching materials, including a circuit kit, that our team created for the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 grade outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The Synthetic Biology kit will be used by high school Science teachers in classrooms in the Pittsburgh Public School System. We have already tested the kit in several presentations given by the team to High School students studying on the Carnegie Mellon campus this summer.<br />
</p><br />
<p><br />
This was the schedule and audience of our presentations:<br />
</p><br />
<p><br />
<ol><li> July 18 and August 1: Presentations to rising junior and senior high school students who participated in the Summer Academy of Math and Science at Carnegie Mellon. <br />
"The Summer Academy for Mathematics and Science (SAMS) is a rigorous residential summer experience for good students who have a strong interest in math and science and want to become excellent students." An objective of SAMS is to contribute to the expansion of the pipeline of outstanding college-bound high school graduates with diverse backgrounds.<br />
</li><li> July 20: Presentation to high school students taking AP Biology at Carnegie Mellon and their teacher. <br />
</ol> <br />
</p><br />
<br />
<p><br />
In these presentations (<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team"> download here!</a>), we introduced Synthetic Biology and iGEM to the students. <br><br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905934" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe><br />
<br><br><br />
<br />
In conjunction with the presentation, we used the circuit kit to explain the main aspects of our research project and to demonstrate how the biosensor can be used to characterize a promoter. For a given set of electronic components, we measured and displayed graphical representations of the current/voltage. <br />
<br><br />
<br><br />
<b> Interactive Mini-game </b><br />
<br><br><br />
<img src ="https://static.igem.org/mediawiki/2012/f/f1/Minigame.png" width="385px" height="345px" align="right"> <br />
To encourage the students to interact and play with the circuit kit, we devised a mini-game which placed the students in our shoes: <b> as Synthetic Biologists using our BioBrick system to characterize new promoters. </b> <br><br><br />
We did this by giving the students a set of different resistors, and gave them the challenge to find the best promoter by mixing and matching these parts and characterizing them using our circuit kit. <br><br />
Students could then change the electronic components and observe the corresponding changes in current/voltage. In the process, we explained to the students the formal equivalence of the electronic components and Biobricks and of the current/voltage and measured fluorescence signals. We also explained to them the biological significance of the graphs obtained.<br />
</p><br />
<br />
<br><br />
<p><br />
The students who attended our presentations learned about:<br />
<ol><li> Synthetic biology and its relationship to Biology and Science and Engineering in general<br />
</li><li> Gene expression and the central dogma of molecular biology<br />
</li><li> How synthetic biologists tackle real-world problems<br />
</li><li> The iGEM competition and how our iGEM team's project enables one to measures the properties of promoters<br />
</li><li> The interdisciplinary nature of synthetic biology<br />
</li><li> The advantages and challenges of interdisciplinary work<br />
</li></ol><br />
</p><br />
<br />
<p> Photos from our summer presentations can be found <a href="https://www.dropbox.com/sh/7kqncwq63vay4za/5zUMzdUbNs"> here</a>. </p><br />
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Future Outreach Plans<br />
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<p><br />
The circuit is the basis for a kit to be used by high school Science teachers in classrooms in public schools in Pittsburgh. This is a means to incorporate Synthetic Biology in the HS curriculum. The kit is made available through the Lending Library of Science Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a>.<br />
<br><br />
We also came up with a teaching presentation to assist teachers in using our kits for teaching about Synthetic Biology. To download the presentation, please go to the Teaching Presentation portion of our Wiki.<br />
<br />
<br><br />
<br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905902" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe> <br />
<br><br />
</p><br />
<p><br />
The educational objectives of the classes in which the students use our Synthetic Biology kit are:<br />
<ol><li>Students will be able to give a definition of synthetic biology<br />
</li><li> Students will be able to identify one real-world application of synthetic biology <br />
</li><li> Students will be able to explain how technology is used to extend human abilities<br />
</li><li> Students will be able to recognize the correlation between the input and output of a biological or electronic circuit<br />
</li><li> Students will be able to recognize the advantages and limitations of using models to simulate processes that relate an input and its output<br />
</li><li> Students will be able to discuss the value of collaboration in interdisciplinary fields <br />
</li><li> Students will be able to discuss ethics aspects related to synthetic biology<br />
</ol> <br />
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
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<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
<li><a href="#section1-4">1.2 Question 3</a></li><br />
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<h1 id="section1-1">Circuit Kit: Overview </h1><br />
<p><br />
In order to raise awareness, and motivate continued innovation in the field of synthetic biology, our iGEM team took the initiative to design a simple hardware demonstration platform, with which mentors can allow students to interact with a physical model of our project! The platform uses a microcontroller and a collection of simple circuits and components which communicate with a Matlab GUI to demonstrate how the various portions of our BioBricks interact to accomplish our goal. <br><br />
Most importantly, we hope all iGEM teams can take inspiration from our experiences and build similar electric analogs of their BioBricks designs! We've found them to be an amazing tool for engaging high school students and piquing their interest and understanding in Synthetic Biology.<br />
</p><br />
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<h1 id="section1-2">Microcontrollers 101 </h1><br />
<p><br />
Typically, microcontrollers are general purpose microprocessors which have additional parts that allow them to read, and control external devices. We often use the terms microcontroller and microprocessor interchangeably. <br />
</p><br />
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<img src="https://static.igem.org/mediawiki/2012/6/6f/CMU_Arduino.jpg" height="287" width="287" align="right" alt="Matlab BioBrick GUI"/><br />
<b> Microcontrollers are typically used to: </b> <br />
<li> Gather sensor and component <i>inputs</i>. </li><br />
<li> Process these inputs, in digital format, to determine some <i>output</i> or action. </li><br />
<li> Utilize output devices and/or communication channels to do something useful. </li><br />
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<p><br />
Why use <i>microcontrollers</i> to help spread synthetic biology awareness? Microcontrollers are a good starting point for teaching students about general input/output systems, which are the primary design focus of synthetic biology: <b>creating biological systems that transform environmental inputs into useful outputs</b>. A basic microcontroller typically includes a microprocessor, digital inputs/outputs, analog inputs/outputs, and some type of communication interface (e.g., serial, wi-fi, bluetooth, etc.). <br />
</p><br />
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<p><br />
Although our kit utilizes an off-the-shelf microcontroller (AtMega328P-PU based Arduino), we additionally designed a simplified version. This allows other collaborators and students to potentially replicate, or modify the project and eventually fabricate their own simplified microcontrollers for use in DIY synthetic biology education. In many senses, the BioBricks being developed through the iGEM foundation essentially function like minute microcontroller systems. It is thus important to identify this similarity, and provide students and future researchers with an opportunity to explore it. <br />
</p><br />
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<h1 id="section1-3">Simplified Microcontroller </h1><br />
<p>Below is a list of components used in our simplified microcontroller, and an image of the schematic designating the physical connections between the components and the AtMega328P-PU. These connections can initially be wired using a breadboard, which allows students to gain a simplified understanding of what connections are being made in off-the-shelf microcontrollers. If they choose, students can use the provided schematic files to order a PCB of their own from any of a variety of PCB manufacturers. <br />
</p><br />
<br />
<b> Parts List: </b> <br />
<li> AtMega328P-PU: <i>ATMega328P-PU (AVR microcontroller) </i></li><br />
<li> IC2: <i>78L05 (5v Voltage Regulator, 100ma) </i></li><br />
<li> Q1: <i>16MHz Resonator (with internal capacitors) </i> </li><br />
<li> C1: <i>0.1μF Capacitor </i> </li><br />
<li> C2: <i>0.33μF Capacitor </i> </li><br />
<li> C3: <i>0.1μF Capacitor </i> </li><br />
<li> R1: <i>10KΩ Resistor </i> </li><br />
<br><br />
<br />
<b>Simplified Microcontroller Schematic</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a7/Schematic_PCB_MCU.png" height="450" width="650"/><br />
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<b>Simplified Microcontroller PCB Layout</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/c/c5/Schematic_PCB_Layout.png" /><br />
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<p><br />
Follow this <a href="https://www.dropbox.com/sh/nb9cs0gpbvlrpxa/PMXNzM1p7G"> link</a> to download the eagle schematic files. The link also contains a.) tutorial on how to wire up and program the simplified microcontroller on a breadboard from scratch (this should be accomplished prior to pcb manufacture) and b.) parts list for the project enclosure and supporting components.<br />
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<h1 id = "section1-4"> Using the Hardware/Software Platform </h1><br />
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<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
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<b> General Notes </b><br />
<ol><br />
<li> Use the provided usb cable to connect the platform to a computer. Please do not detach the cable from the kit. </li><br />
<li> The GUI is implemented in Matlab currently, but will also be implemented via an open-source language.</li><br />
<li> Source-code for both implementations will be available via this <a href="https://www.dropbox.com/sh/zeeugv3pt4pgo0l/JkQ47msyeM"> link</a>. </li><br />
</ol><br />
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<b> Overview </b><br><br />
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<p><br />
The kit is comprised of one main BioBrick Unit (containing the programmed microcontroller) with interactive components, and an accompanying Fluorescence Unit which uses LEDs and a photo-resistor to emulate the process of collecting fluorescence microscope data. The LEDs illuminate with variable brightness in response to the user's choice of physical BioBrick configuration. This is roughly analogous to the fluorescence produced by cells illuminating in response to different BioBrick configurations in-vivo. The photo-resistor then emulates the fluorescence microscope by quantifying the light which is emitted by the LEDs. This "microscopy" process is paralleled by a Matlab GUI, which subsequently feeds the fluorescence data to the physical model, described <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> here</a>.<br />
</p><br />
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<b> Build a BioBrick </b><br />
<ol><br />
<li> Insert the start-sequence, represented by the first set of 2-pin jumpers on the far left of the main unit. </li><br />
<li>Select a promoter from the 4 provided, and insert each promoter region. </li><br />
<ul><br />
<li> A single promoter is composed of 3 promoter regions, represented by identically-colored resistors. </li><br />
<li> Note the orientation of the components when inserting each region. </li><br />
<li> The top resistor should connect slots 1 & 2. The middle resistor should connect slots 2 & 3. The bottom resistor should connect slots 3 & 4. </li><br />
</ul><br />
<br><br />
<li> Insert the tRNA stabilizer headers (2). </li> <br />
<li> Insert the Spinach sequence (6-pin header). </li><br />
<li> Insert both RBS & FAP sequences. </li><br />
<li> Insert the end-sequence, represented by the final set of 2-pin jumpers. </li><br />
</ol><br />
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<b> Characterize the Chosen Promoter </b><br />
<ol><br />
<li> Open Matlab, and add the folder with the provided software to the Matlab path.</li><br />
<ul><li> Right click the provided folder, and select "Add to Path -> Selected Folders and Sub-Folders" </li></ul><br />
<li> Type "BioBrick_GUI" at the command prompt, and hit enter. </li><br />
<li> First, populate the time-step input table from top to bottom with the values 10, 20, 30, 40 ,50 </li><br />
<li> Next, hit "Begin Time Lapse" at the top of the GUI: </li><br />
<ul><br />
<li> Note that the software will first sweep through the entire range of all possible fluorescence input levels, and plot the measured fluorescence values. </li><br />
<li> Allow the program to run to completion, populating the output tables. </li><br />
</ul><br />
<br><br />
<li> When the program is finished populating the outputs, hit "Calculate" to display the output values for translational efficiency and transcriptional strength. </li><br />
<li> To export the output tables to the Matlab workspace, select "File" from the menu bar, and choose "Export".</li><br />
<ul><li> This will move the output tables, and calculated values to the workspace. </li></ul><br />
<br><br />
<li> To plot an example comparison of the different promoters over time, enter "plot_data" at the Matlab command prompt. </li><br />
<ul><li> Observe the plot_data.m function if you wish to plot your own data </li></ul><br />
</ol><br />
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<b> Make a Change and Observe the Effect! </b><br />
<li> Any of the following changes can be made to the BioBrick to help demonstrate the component relationships: </li><br />
<ul><br />
<li> Remove the Spinach sequence, </li><br />
<li> Remove the tRNA stabilizer (one or both components), </li><br />
<li> Remove the RBS sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the FAP sequence, and replace with one of the 3-pin headers with blue wire (short), </li><br />
<li> Remove the START/END sequence, </li><br />
<li> Remove either DFHBI or MG by toggling the switches off (illuminated when 'ON'), </li><br />
<li> …or any combination of the previous. </li><br />
</ul><br />
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<h1 id="section1-1">Pictures and Schematics of the Kit </h1><br />
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<b>BioBrick Circuit Kit</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/9/9a/CMU_BioBrick_Both_Units.jpg" height="300" width="433"/><br />
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<b>BioBrick Components</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/1/16/CMU_BioBrick_Components.JPG" height="300" width="433"/><br />
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<b>BioBrick Main Unit Circuit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/f/f3/CMU_Circ_Biobrick.png" height="300" width="700"/><br />
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<b>BioBrick Fluorescence Unit Diagram</b><br><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_Fluor.png" height="300" width="433"/><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/CMU_Circ_PhotoR.png" height="300" width="433"/><br />
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<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
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<h1 id="section1-1"> Summer Presentations to High School Students </h1><br />
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<p><br />
The <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Human Practices/Overview</a> page provides information about the teaching materials, including a circuit kit, that our team created for the Lending Library of Kits of DNAZone, the K-12 grade outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The Synthetic Biology kit will be used by high school Science teachers in classrooms in the Pittsburgh Public School System. We have already tested the kit in several presentations given by the team to High School students studying on the Carnegie Mellon campus this summer.<br />
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This was the schedule and audience of our presentations:<br />
</p><br />
<p><br />
<ol><li> July 18 and August 1: Presentations to rising junior and senior high school students who participated in the Summer Academy of Math and Science at Carnegie Mellon. <br />
"The Summer Academy for Mathematics and Science (SAMS) is a rigorous residential summer experience for good students who have a strong interest in math and science and want to become excellent students." An objective of SAMS is to contribute to the expansion of the pipeline of outstanding college-bound high school graduates with diverse backgrounds.<br />
</li><li> July 20: Presentation to high school students taking AP Biology at Carnegie Mellon and their teacher. <br />
</ol> <br />
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<p><br />
In these presentations (<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team"> download here!</a>), we introduced Synthetic Biology and iGEM to the students. <br><br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905934" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe><br />
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<br />
In conjunction with the presentation, we used the circuit kit to explain the main aspects of our research project and to demonstrate how the biosensor can be used to characterize a promoter. For a given set of electronic components, we measured and displayed graphical representations of the current/voltage. <br />
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<b> Interactive Mini-game </b><br />
<br><br><br />
<img src ="https://static.igem.org/mediawiki/2012/f/f1/Minigame.png" width="385px" height="345px" align="right"> <br />
To encourage the students to interact and play with the circuit kit, we devised a mini-game which placed the students in our shoes: <b> as Synthetic Biologists using our BioBrick system to characterize new promoters. </b> <br><br><br />
We did this by giving the students a set of different resistors, and gave them the challenge to find the best promoter by mixing and matching these parts and characterizing them using our circuit kit. <br><br />
Students could then change the electronic components and observe the corresponding changes in current/voltage. In the process, we explained to the students the formal equivalence of the electronic components and Biobricks and of the current/voltage and measured fluorescence signals. We also explained to them the biological significance of the graphs obtained.<br />
</p><br />
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<p><br />
The students who attended our presentations learned about:<br />
<ol><li> Synthetic biology and its relationship to Biology and Science and Engineering in general<br />
</li><li> Gene expression and the central dogma of molecular biology<br />
</li><li> How synthetic biologists tackle real-world problems<br />
</li><li> The iGEM competition and how our iGEM team's project enables one to measures the properties of promoters<br />
</li><li> The interdisciplinary nature of synthetic biology<br />
</li><li> The advantages and challenges of interdisciplinary work<br />
</li></ol><br />
</p><br />
<br />
<p> Photos from our summer presentations can be found <a href="https://www.dropbox.com/sh/7kqncwq63vay4za/5zUMzdUbNs"> here</a>. </p><br />
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Future Outreach Plans<br />
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<p><br />
The circuit is the basis for a kit to be used by high school Science teachers in classrooms in public schools in Pittsburgh. This is a means to incorporate Synthetic Biology in the HS curriculum. The kit is made available through the Lending Library of Science Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a>.<br />
<br><br />
We also came up with a teaching presentation to assist teachers in using our kits for teaching about Synthetic Biology. To download the presentation, please go to the Teaching Presentation portion of our Wiki.<br />
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<iframe src="http://www.slideshare.net/slideshow/embed_code/14905902" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe> <br />
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The educational objectives of the classes in which the students use our Synthetic Biology kit are:<br />
<ol><li>Students will be able to give a definition of synthetic biology<br />
</li><li> Students will be able to identify one real-world application of synthetic biology <br />
</li><li> Students will be able to explain how technology is used to extend human abilities<br />
</li><li> Students will be able to recognize the correlation between the input and output of a biological or electronic circuit<br />
</li><li> Students will be able to recognize the advantages and limitations of using models to simulate processes that relate an input and its output<br />
</li><li> Students will be able to discuss the value of collaboration in interdisciplinary fields <br />
</li><li> Students will be able to discuss ethics aspects related to synthetic biology<br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Bio-Overview">BioBricks</a><br />
<ul><br />
<li class = 'offset' style ='width: 193px'> <a href="#"></a></li><br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Bio-Overview">Overview</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Bio-Submitted">Submitted Parts</a><br />
</li><br />
</ul><br />
</li><br />
<br />
<li style ='width: 193px'><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview">Methods and Results</a><br />
<ul><br />
<li class = 'offset' style ='width: 386px'> <a href="#"></a></li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview">Overview</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Results">Results</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Protocols">Protocols</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Challenges">Challenges</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Notebook">Notebook</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Safety">Safety</a><br />
</li><br />
</ul><br />
</li><br />
<br />
<li style ='width: 193px'><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview">Modeling</a> <br />
<ul><br />
<li class = 'offset' style ='width: 579px'> <a href="#"></a></li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview">Overview</a><br />
</li><br />
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</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Matlab">Matlab</a><br />
</li><br />
</ul> <br />
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<li class="current" style ='width: 193px'><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Human Practices</a><br />
<ul><br />
<li class = 'offset' style ='width: 296px'> <a href="#"></a></li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Overview</a><br />
</li><br />
<li class = "current"><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Outreach">Outreach</a><br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit">Circuit Kit</a><br />
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
</ul><br />
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<header id = "header2"><br />
<br />
<h1 id="section1-1"> Summer Presentations to High School Students </h1><br />
<br />
<p><br />
The Human Practices/Overview <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview"</a> page provides information about the teaching materials, including a circuit kit, that our team created for the Lending Library of Kits of DNAZone, the K-12 grade outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The Synthetic Biology kit will be used by high school Science teachers in classrooms in the Pittsburgh Public School System. We have already tested the kit in several presentations given by the team to High School students studying on the Carnegie Mellon campus this summer.<br />
</p><br />
<p><br />
This was the schedule and audience of our presentations:<br />
</p><br />
<p><br />
<ol><li> July 18 and August 1: Presentations to rising junior and senior high school students who participated in the Summer Academy of Math and Science at Carnegie Mellon. <br />
"The Summer Academy for Mathematics and Science (SAMS) is a rigorous residential summer experience for good students who have a strong interest in math and science and want to become excellent students." An objective of SAMS is to contribute to the expansion of the pipeline of outstanding college-bound high school graduates with diverse backgrounds.<br />
</li><li> July 20: Presentation to high school students taking AP Biology at Carnegie Mellon and their teacher. <br />
</ol> <br />
</p><br />
<br />
<p><br />
In these presentations (<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team"> download here!</a>), we introduced Synthetic Biology and iGEM to the students. <br><br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905934" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe><br />
<br><br><br />
<br />
In conjunction with the presentation, we used the circuit kit to explain the main aspects of our research project and to demonstrate how the biosensor can be used to characterize a promoter. For a given set of electronic components, we measured and displayed graphical representations of the current/voltage. <br />
<br><br />
<br><br />
<b> Interactive Mini-game </b><br />
<br><br><br />
<img src ="https://static.igem.org/mediawiki/2012/f/f1/Minigame.png" width="385px" height="345px" align="right"> <br />
To encourage the students to interact and play with the circuit kit, we devised a mini-game which placed the students in our shoes: <b> as Synthetic Biologists using our BioBrick system to characterize new promoters. </b> <br><br><br />
We did this by giving the students a set of different resistors, and gave them the challenge to find the best promoter by mixing and matching these parts and characterizing them using our circuit kit. <br><br />
Students could then change the electronic components and observe the corresponding changes in current/voltage. In the process, we explained to the students the formal equivalence of the electronic components and Biobricks and of the current/voltage and measured fluorescence signals. We also explained to them the biological significance of the graphs obtained.<br />
</p><br />
<br />
<br><br />
<p><br />
The students who attended our presentations learned about:<br />
<ol><li> Synthetic biology and its relationship to Biology and Science and Engineering in general<br />
</li><li> Gene expression and the central dogma of molecular biology<br />
</li><li> How synthetic biologists tackle real-world problems<br />
</li><li> The iGEM competition and how our iGEM team's project enables one to measures the properties of promoters<br />
</li><li> The interdisciplinary nature of synthetic biology<br />
</li><li> The advantages and challenges of interdisciplinary work<br />
</li></ol><br />
</p><br />
<br />
<p> Photos from our summer presentations can be found <a href="https://www.dropbox.com/sh/7kqncwq63vay4za/5zUMzdUbNs"> here</a>. </p><br />
<br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />
<h1 id = "section1-2"><br />
Future Outreach Plans<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<br />
<p><br />
The circuit is the basis for a kit to be used by high school Science teachers in classrooms in public schools in Pittsburgh. This is a means to incorporate Synthetic Biology in the HS curriculum. The kit is made available through the Lending Library of Science Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a>.<br />
<br><br />
We also came up with a teaching presentation to assist teachers in using our kits for teaching about Synthetic Biology. To download the presentation, please go to the Teaching Presentation portion of our Wiki.<br />
<br />
<br><br />
<br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905902" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe> <br />
<br><br />
</p><br />
<p><br />
The educational objectives of the classes in which the students use our Synthetic Biology kit are:<br />
<ol><li>Students will be able to give a definition of synthetic biology<br />
</li><li> Students will be able to identify one real-world application of synthetic biology <br />
</li><li> Students will be able to explain how technology is used to extend human abilities<br />
</li><li> Students will be able to recognize the correlation between the input and output of a biological or electronic circuit<br />
</li><li> Students will be able to recognize the advantages and limitations of using models to simulate processes that relate an input and its output<br />
</li><li> Students will be able to discuss the value of collaboration in interdisciplinary fields <br />
</li><li> Students will be able to discuss ethics aspects related to synthetic biology<br />
</ol> <br />
</p><br />
<br />
<br />
</div><br />
</div><br />
<br />
<br />
</html><br />
{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-OutreachTeam:Carnegie Mellon/Hum-Outreach2012-10-27T03:16:43Z<p>Ychoo: </p>
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
</ul><br />
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<br />
<section id="left"><br />
<header id = "header2"><br />
<br />
<h1 id="section1-1"> Summer Presentations to High School Students </h1><br />
<br />
<p><br />
The Human Practices/Overview <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview"> page provides information about the teaching materials, including a circuit kit, that our team created for the Lending Library of Kits of DNAZone, the K-12 grade outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The Synthetic Biology kit will be used by high school Science teachers in classrooms in the Pittsburgh Public School System. We have already tested the kit in several presentations given by the team to High School students studying on the Carnegie Mellon campus this summer.<br />
</p><br />
<p><br />
This was the schedule and audience of our presentations:<br />
</p><br />
<p><br />
<ol><li> July 18 and August 1: Presentations to rising junior and senior high school students who participated in the Summer Academy of Math and Science at Carnegie Mellon. <br />
"The Summer Academy for Mathematics and Science (SAMS) is a rigorous residential summer experience for good students who have a strong interest in math and science and want to become excellent students." An objective of SAMS is to contribute to the expansion of the pipeline of outstanding college-bound high school graduates with diverse backgrounds.<br />
</li><li> July 20: Presentation to high school students taking AP Biology at Carnegie Mellon and their teacher. <br />
</ol> <br />
</p><br />
<br />
<p><br />
In these presentations (<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team"> download here!</a>), we introduced Synthetic Biology and iGEM to the students. <br><br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905934" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe><br />
<br><br><br />
<br />
In conjunction with the presentation, we used the circuit kit to explain the main aspects of our research project and to demonstrate how the biosensor can be used to characterize a promoter. For a given set of electronic components, we measured and displayed graphical representations of the current/voltage. <br />
<br><br />
<br><br />
<b> Interactive Mini-game </b><br />
<br><br><br />
<img src ="https://static.igem.org/mediawiki/2012/f/f1/Minigame.png" width="385px" height="345px" align="right"> <br />
To encourage the students to interact and play with the circuit kit, we devised a mini-game which placed the students in our shoes: <b> as Synthetic Biologists using our BioBrick system to characterize new promoters. </b> <br><br><br />
We did this by giving the students a set of different resistors, and gave them the challenge to find the best promoter by mixing and matching these parts and characterizing them using our circuit kit. <br><br />
Students could then change the electronic components and observe the corresponding changes in current/voltage. In the process, we explained to the students the formal equivalence of the electronic components and Biobricks and of the current/voltage and measured fluorescence signals. We also explained to them the biological significance of the graphs obtained.<br />
</p><br />
<br />
<br><br />
<p><br />
The students who attended our presentations learned about:<br />
<ol><li> Synthetic biology and its relationship to Biology and Science and Engineering in general<br />
</li><li> Gene expression and the central dogma of molecular biology<br />
</li><li> How synthetic biologists tackle real-world problems<br />
</li><li> The iGEM competition and how our iGEM team's project enables one to measures the properties of promoters<br />
</li><li> The interdisciplinary nature of synthetic biology<br />
</li><li> The advantages and challenges of interdisciplinary work<br />
</li></ol><br />
</p><br />
<br />
<p> Photos from our summer presentations can be found <a href="https://www.dropbox.com/sh/7kqncwq63vay4za/5zUMzdUbNs"> here</a>. </p><br />
<br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />
<br />
<h1 id = "section1-2"><br />
Future Outreach Plans<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<br />
<p><br />
The circuit is the basis for a kit to be used by high school Science teachers in classrooms in public schools in Pittsburgh. This is a means to incorporate Synthetic Biology in the HS curriculum. The kit is made available through the Lending Library of Science Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a>.<br />
<br><br />
We also came up with a teaching presentation to assist teachers in using our kits for teaching about Synthetic Biology. To download the presentation, please go to the Teaching Presentation portion of our Wiki.<br />
<br />
<br><br />
<br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905902" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe> <br />
<br><br />
</p><br />
<p><br />
The educational objectives of the classes in which the students use our Synthetic Biology kit are:<br />
<ol><li>Students will be able to give a definition of synthetic biology<br />
</li><li> Students will be able to identify one real-world application of synthetic biology <br />
</li><li> Students will be able to explain how technology is used to extend human abilities<br />
</li><li> Students will be able to recognize the correlation between the input and output of a biological or electronic circuit<br />
</li><li> Students will be able to recognize the advantages and limitations of using models to simulate processes that relate an input and its output<br />
</li><li> Students will be able to discuss the value of collaboration in interdisciplinary fields <br />
</li><li> Students will be able to discuss ethics aspects related to synthetic biology<br />
</ol> <br />
</p><br />
<br />
<br />
</div><br />
</div><br />
<br />
<br />
</html><br />
{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-OverviewTeam:Carnegie Mellon/Hum-Overview2012-10-27T03:16:36Z<p>Ychoo: </p>
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</li><br />
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<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Results">Results</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Protocols">Protocols</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Challenges">Challenges</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Notebook">Notebook</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Safety">Safety</a><br />
</li><br />
</ul><br />
</li><br />
<br />
<li style ='width: 193px'><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview">Modeling</a> <br />
<ul><br />
<li class = 'offset' style ='width: 579px'> <a href="#"></a></li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview">Overview</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Derivations">Derivations</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Matlab">Matlab</a><br />
</li><br />
</ul> <br />
</li><br />
<br />
<li class="current" style ='width: 193px'><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Human Practices</a><br />
<ul><br />
<li class = 'offset' style ='width: 292px'> <a href="#"></a></li><br />
<li class = "current"><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview">Overview</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Outreach">Outreach</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit">Circuit Kit</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software">Software</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team">Team Presentation</a><br />
</li><br />
<li><br />
<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Teaching">Teaching Presentation</a><br />
</li><br />
</ul> <br />
</li> <br />
</ul><br />
<br /><br /><br /><br />
<br />
<!--Main Contents --><br />
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<br />
<!--Table of Contents --><br />
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<ul id="toc" class="toc-new" style="background: #c1a562;"><br />
<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
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<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
</p><br />
<p><br />
The impact of synthetic biology depends on the number and quality of scientists making significant contributions to the field. Future scientists will rise from current high school students who are excited about science and gain a solid background in math and science in their formative years. To this end, we decided to raise the awareness of high school students about the interdisciplinary field of synthetic biology and to also teach them about the process of scientific research.<br><br />
As an additional outcome, the proposed methodology of using an electronic circuit equivalent for modeling biological phenomena can be replicated and used beyond the context of our current project.<br />
</p><br />
<br />
<img src = "https://static.igem.org/mediawiki/2012/2/20/Outreachphoto1.JPG" align = "right" padding ="5px"><br />
<p><br />
We decided to create teaching materials for high school students inspired by our team’s research project. Our goal was that these materials can be easily used by a science teacher in a lecture in a Biology or Chemistry course to:<br />
<div class = "ol"><br />
<ol type = "1" compact> <br />
<li>Explain what Synthetic Biology is; </li><br />
<li>Illustrate the opportunities created by Synthetic Biology in improving human well being; </li><br />
<li>Discuss ethical concerns related to Synthetic Biology; </li><br />
<li>Enable the students to understand how our <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a> works.</li><br />
</ol><br />
</div><br />
</p><br />
<br />
<p><br />
To bridge the gap between the background of a high school student and the complexity of our project, we built an affordable, microcontroller-based, hardware platform and associated, open-source, digital simulation software. In designing the demonstration platform, we exploited the relationship between biological networks in synthetic biology and electronic circuits in electrical engineering. Specifically, we created a circuit kit that emulates in hardware our biological construct and in software both the response of the biological construct to specific cell conditions and the fluorescence measurement. It is important to note that the kit is <b>INTERACTIVE</b> (students can easily change electronic components to simulate different biological or external changes and the outcome of these changes), <b> RELATABLE</b> (the students can directly use the kit) and <b>EASILY SHARED AND IMPROVED</b> (the list of electronic components, circuit diagrams etc. are in the public domain and the software is open source).<br />
</p><br />
<br />
<p><br />
The teaching materials we have created, specifically a <a href="https://www.dropbox.com/s/n1bpb77einu26ko/iGEM_Summer_Presentation.pdf"> power point presentation</a> and an <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> electronic circuit kit</a>, have become part of the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The kits in the Library are loaned to high school teachers in the Pittsburgh area to be used in teaching Math and Science. We identified for the teachers how the use of our kit can help the High School students meet specific objectives from the <a href ="http://static.pdesas.org/content/documents/Academic_Standards_for_Science_and_Technology_and_Engineering_Education_%28Secondary%29.pdf">Pennsylvania Academic Standards for Science, Technology, and Engineering Education</a> and the <a href ="http://www.portal.state.pa.us/portal/server.pt/community/assessment_anchors/7440 ">Pennsylvania Assessment Anchors</a>. We have also tested the kit in several demonstrations in the Summer of 2012 to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> Summer Academy of Math and Science (SAMS)</a> at Carnegie Mellon.<br />
</p><br />
<br />
<p><br />
A very important original property of our approach to Human Practices stems from the fact that the teaching materials we created are available to teachers in any Pittsburgh Public School District who can borrow them from the Lending Library of Kits and use them even after the work of the current CMU iGEM team ends. Another original factor is the fact that we identified for the teachers which objectives from the Pennsylvania Academic Standards for Science, Technology and Engineering they can teach using the kit. This identification should eliminate the barrier to adoption of the kit by teachers faced with tight time schedules to cover these objectives.<br />
</p><br />
<p><br />
</p><br />
<h1 id="section1-1"> System Implemented with the Kit </h1><br />
<img src="https://static.igem.org/mediawiki/2012/f/f4/System_model.jpg" height="300" width="433" align="right"/><br />
<p><br />
As described <a href="https://2012.igem.org/Team:Carnegie_Mellon"> here</a>, our team engineered a fluorescence-based sensor that provides information on both transcription strength and translation efficiency of a promoter. The sensor is noninvasive, easily applied to a variety of promoters, and capable of providing results in a time frame that is short when compared to current technologies for the characterization of promoters. <br />
</p><br />
<p><br />
The sensor is based on the use of an RNA aptamer (termed Spinach) and a fluorogen activating protein (FAP). The complexes of Spinach (mRNA-DMHBI in the Figure) and FAP (FAP-MG in the Figure) with specific dyes, DFHBI and MG, respectively, are fluorescent. Measurements of the fluorescence intensity of these complexes enables one to determine the concentration of mRNA and expressed protein for a given promoter. Analysis of the fluorescence data with an appropriate model leads to the transcription strength and translation efficiency for each promoter.<br />
</p><br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<h1 id = "section1-2"><br />
The Hardware/Software Platform<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
<p><br />
</p><br />
</p><br />
<p><br />
The goal was to create a model of our <b><a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a></b> that clearly represents its main components and makes clear how the biosensor works. We also planned to enable the students to simulate changes in the “environment” and to observe the outcome of these changes. To achieve this goal, we built an affordable, microcontroller-based, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> hardware</a> platform and also developed an associated, open-source, simulation <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software"> software</a>. <br />
<br />
</p><br />
<p><br />
The combined hardware/software platform allows the students to directly manipulate electronic components, which are formal equivalents of the BioBricks used in our sensor, and to observe the effect of changing these components on the current or voltage output, which is the equivalent of the fluorescence intensity in our lab experiments. In using the kit, the students get a feel for how different promoters are compared using the biosensor; they can rank "virtual promoters" in the order of their strength. Students who use the kit gain hands-on experience and understand how all the parts of the biosensor work together to measure the mRNA and protein levels, without working in the wet lab.<br />
The figure on the right is a photograph of the hardware platform on which the correspondence between the biological components of the biosensor and the electronic components of the kit are identified.<br />
</p><br />
<p><br />
The software used in the platform is based on the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> model</a> derived for the analysis of the fluorescence data obtained with the biosensor. We have also created a GUI that allows the students to modify the parameters used in the model and to visualize on a computer display the current/voltage output (which is the equivalent of the fluorescence output in our experiments).<br />
</p><br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<h1 id = "section1-3"><br />
Team Presentations to Groups of High School Students<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<br />
<p><br />
</p><br />
</p><br />
<p><br />
To obtain feedback for how high school students use the circuit kit, the team has given several presentations about synthetic biology and our project to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> SAMS</a> and in <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/apea.html"> AP Biology</a> at Carnegie Mellon University. <br />
We have also sought and obtained feedback on the kit from Dr. Janet Waldeck, Physics teacher at the Pittsburgh Allderdice High School in Pittsburgh. <br />
The feedback and input gained from these presentations was used to refine the kit. <br />
</p><br />
<br />
<br />
<br />
<h1> Broader Impact in Biological Modeling Methodology </h1><br />
<p><br />
The methodology used to build the electrical equivalent of the biological processes is not unique to the problem we are solving in this project. Starting from first principles modeling, one can use the methodology followed in our circuit kit implementation and emulate the behavior of the processes governing other biological phenomena by using simple controllers and circuit components. This shows that interdisciplinary training is not only desirable, but can also be beneficial for solving synthetic biology problems, thereby underscoring the importance of such training starting from high school through college.<br />
<br />
</div><br />
</div><br />
</p><br />
<br />
</html><br />
{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_Mellon/Hum-OverviewTeam:Carnegie Mellon/Hum-Overview2012-10-27T03:15:20Z<p>Ychoo: </p>
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</li><br />
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<!--Main Contents --><br />
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<!--Table of Contents --><br />
<!-- Remove for testing<br />
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<a href="#" class="toc-link" id="toc-link"><span>&#9660;</span> Table of Contents</a><br />
<ul id="toc" class="toc-new" style="background: #c1a562;"><br />
<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
<ul class="toc-sub closed"><br />
<li><a href="#section1-1">1.1 Question 1</a></li><br />
<li><a href="#section1-2">1.2 Question 2</a></li><br />
<li><a href="#section1-3">1.2 Question 3</a></li><br />
</ul><br />
</li><br />
<br />
</ul><br />
</div><br />
--><br />
<!-- .toc-holder --><br />
<br />
<div class = "main_content"><br />
<br />
<body><br />
<div id="wrapper"><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
</p><br />
<p><br />
The impact of synthetic biology depends on the number and quality of scientists making significant contributions to the field. Future scientists will rise from current high school students who are excited about science and gain a solid background in math and science in their formative years. To this end, we decided to raise the awareness of high school students about the interdisciplinary field of synthetic biology and to also teach them about the process of scientific research.<br><br />
As an additional outcome, the proposed methodology of using an electronic circuit equivalent for modeling biological phenomena can be replicated and used beyond the context of our current project.<br />
</p><br />
<br />
<img src = "https://static.igem.org/mediawiki/2012/2/20/Outreachphoto1.JPG" align = "right" padding ="5px"><br />
<p><br />
We decided to create teaching materials for high school students inspired by our team’s research project. Our goal was that these materials can be easily used by a science teacher in a lecture in a Biology or Chemistry course to:<br />
<div class = "ol"><br />
<ol type = "1" compact> <br />
<li>Explain what Synthetic Biology is; </li><br />
<li>Illustrate the opportunities created by Synthetic Biology in improving human well being; </li><br />
<li>Discuss ethical concerns related to Synthetic Biology; </li><br />
<li>Enable the students to understand how our <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a> works.</li><br />
</ol><br />
</div><br />
</p><br />
<br />
<p><br />
To bridge the gap between the background of a high school student and the complexity of our project, we built an affordable, microcontroller-based, hardware platform and associated, open-source, digital simulation software. In designing the demonstration platform, we exploited the relationship between biological networks in synthetic biology and electronic circuits in electrical engineering. Specifically, we created a circuit kit that emulates in hardware our biological construct and in software both the response of the biological construct to specific cell conditions and the fluorescence measurement. It is important to note that the kit is <b>INTERACTIVE</b> (students can easily change electronic components to simulate different biological or external changes and the outcome of these changes), <b> RELATABLE</b> (the students can directly use the kit) and <b>EASILY SHARED AND IMPROVED</b> (the list of electronic components, circuit diagrams etc. are in the public domain and the software is open source).<br />
</p><br />
<br />
<p><br />
The teaching materials we have created, specifically a <a href="https://www.dropbox.com/s/n1bpb77einu26ko/iGEM_Summer_Presentation.pdf"> power point presentation</a> and an <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> electronic circuit kit</a>, have become part of the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The kits in the Library are loaned to high school teachers in the Pittsburgh area to be used in teaching Math and Science. We identified for the teachers how the use of our kit can help the High School students meet specific objectives from the <a href ="http://static.pdesas.org/content/documents/Academic_Standards_for_Science_and_Technology_and_Engineering_Education_%28Secondary%29.pdf">Pennsylvania Academic Standards for Science, Technology, and Engineering Education</a> and the <a href ="http://www.portal.state.pa.us/portal/server.pt/community/assessment_anchors/7440 ">Pennsylvania Assessment Anchors</a>. We have also tested the kit in several demonstrations in the Summer of 2012 to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> Summer Academy of Math and Science (SAMS)</a> at Carnegie Mellon.<br />
</p><br />
<br />
<p><br />
A very important original property of our approach to Human Practices stems from the fact that the teaching materials we created are available to teachers in any Pittsburgh Public School District who can borrow them from the Lending Library of Kits and use them even after the work of the current CMU iGEM team ends. Another original factor is the fact that we identified for the teachers which objectives from the Pennsylvania Academic Standards for Science, Technology and Engineering they can teach using the kit. This identification should eliminate the barrier to adoption of the kit by teachers faced with tight time schedules to cover these objectives.<br />
</p><br />
<p><br />
</p><br />
<h1 id="section1-1"> System Implemented with the Kit </h1><br />
<img src="https://static.igem.org/mediawiki/2012/f/f4/System_model.jpg" height="300" width="433" align="right"/><br />
<p><br />
As described <a href="https://2012.igem.org/Team:Carnegie_Mellon"> here</a>, our team engineered a fluorescence-based sensor that provides information on both transcription strength and translation efficiency of a promoter. The sensor is noninvasive, easily applied to a variety of promoters, and capable of providing results in a time frame that is short when compared to current technologies for the characterization of promoters. <br />
</p><br />
<p><br />
The sensor is based on the use of an RNA aptamer (termed Spinach) and a fluorogen activating protein (FAP). The complexes of Spinach (mRNA-DMHBI in the Figure) and FAP (FAP-MG in the Figure) with specific dyes, DFHBI and MG, respectively, are fluorescent. Measurements of the fluorescence intensity of these complexes enables one to determine the concentration of mRNA and expressed protein for a given promoter. Analysis of the fluorescence data with an appropriate model leads to the transcription strength and translation efficiency for each promoter.<br />
</p><br />
</section><br />
<br />
</div><br />
</div><br />
<div id="wrapper"><br />
<header id = "header"><br />
<h1 id = "section1-2"><br />
The Hardware/Software Platform<br />
</h1><br />
</header><br />
<br />
<div id="core" class="clearfix"><br />
<section id="left"><br />
<header id = "header2"><br />
<img src="https://static.igem.org/mediawiki/2012/a/a9/Circuit_kit.jpg" height="300" width="500" align="right"/><br />
<p><br />
</p><br />
</p><br />
<p><br />
The goal was to create a model of our <b><a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a></b> that clearly represents its main components and makes clear how the biosensor works. We also planned to enable the students to simulate changes in the “environment” and to observe the outcome of these changes. To achieve this goal, we built an affordable, microcontroller-based, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> hardware</a> platform and also developed an associated, open-source, simulation <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software"> software</a>. <br />
<br />
</p><br />
<p><br />
The combined hardware/software platform allows the students to directly manipulate electronic components, which are formal equivalents of the BioBricks used in our sensor, and to observe the effect of changing these components on the current or voltage output, which is the equivalent of the fluorescence intensity in our lab experiments. In using the kit, the students get a feel for how different promoters are compared using the biosensor; they can rank "virtual promoters" in the order of their strength. Students who use the kit gain hands-on experience and understand how all the parts of the biosensor work together to measure the mRNA and protein levels, without working in the wet lab.<br />
The figure on the right is a photograph of the hardware platform on which the correspondence between the biological components of the biosensor and the electronic components of the kit are identified.<br />
</p><br />
<p><br />
The software used in the platform is based on the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> model</a> derived for the analysis of the fluorescence data obtained with the biosensor. We have also created a GUI that allows the students to modify the parameters used in the model and to visualize on a computer display the current/voltage output (which is the equivalent of the fluorescence output in our experiments).<br />
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Team Presentations to Groups of High School Students<br />
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To obtain feedback for how high school students use the circuit kit, the team has given several presentations about synthetic biology and our project to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> SAMS</a> and in <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/apea.html"> AP Biology</a> at Carnegie Mellon University. <br />
We have also sought and obtained feedback on the kit from Dr. Janet Waldeck, Physics teacher at the Pittsburgh Allderdice High School in Pittsburgh. <br />
The feedback and input gained from these presentations was used to refine the kit. <br />
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<h1 id="section1-1"> Summer Presentations to High School Students </h1><br />
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<p><br />
The Human Practices/Overview page provides information about the teaching materials, including a circuit kit, that our team created for the Lending Library of Kits of DNAZone, the K-12 grade outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The Synthetic Biology kit will be used by high school Science teachers in classrooms in the Pittsburgh Public School System. We have already tested the kit in several presentations given by the team to High School students studying on the Carnegie Mellon campus this summer.<br />
</p><br />
<p><br />
This was the schedule and audience of our presentations:<br />
</p><br />
<p><br />
<ol><li> July 18 and August 1: Presentations to rising junior and senior high school students who participated in the Summer Academy of Math and Science at Carnegie Mellon. <br />
"The Summer Academy for Mathematics and Science (SAMS) is a rigorous residential summer experience for good students who have a strong interest in math and science and want to become excellent students." An objective of SAMS is to contribute to the expansion of the pipeline of outstanding college-bound high school graduates with diverse backgrounds.<br />
</li><li> July 20: Presentation to high school students taking AP Biology at Carnegie Mellon and their teacher. <br />
</ol> <br />
</p><br />
<br />
<p><br />
In these presentations (<a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Team"> download here!</a>), we introduced Synthetic Biology and iGEM to the students. <br><br />
<iframe src="http://www.slideshare.net/slideshow/embed_code/14905934" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe><br />
<br><br><br />
<br />
In conjunction with the presentation, we used the circuit kit to explain the main aspects of our research project and to demonstrate how the biosensor can be used to characterize a promoter. For a given set of electronic components, we measured and displayed graphical representations of the current/voltage. <br />
<br><br />
<br><br />
<b> Interactive Mini-game </b><br />
<br><br><br />
<img src ="https://static.igem.org/mediawiki/2012/f/f1/Minigame.png" width="385px" height="345px" align="right"> <br />
To encourage the students to interact and play with the circuit kit, we devised a mini-game which placed the students in our shoes: <b> as Synthetic Biologists using our BioBrick system to characterize new promoters. </b> <br><br><br />
We did this by giving the students a set of different resistors, and gave them the challenge to find the best promoter by mixing and matching these parts and characterizing them using our circuit kit. <br><br />
Students could then change the electronic components and observe the corresponding changes in current/voltage. In the process, we explained to the students the formal equivalence of the electronic components and Biobricks and of the current/voltage and measured fluorescence signals. We also explained to them the biological significance of the graphs obtained.<br />
</p><br />
<br />
<br><br />
<p><br />
The students who attended our presentations learned about:<br />
<ol><li> Synthetic biology and its relationship to Biology and Science and Engineering in general<br />
</li><li> Gene expression and the central dogma of molecular biology<br />
</li><li> How synthetic biologists tackle real-world problems<br />
</li><li> The iGEM competition and how our iGEM team's project enables one to measures the properties of promoters<br />
</li><li> The interdisciplinary nature of synthetic biology<br />
</li><li> The advantages and challenges of interdisciplinary work<br />
</li></ol><br />
</p><br />
<br />
<p> Photos from our summer presentations can be found <a href="https://www.dropbox.com/sh/7kqncwq63vay4za/5zUMzdUbNs"> here</a>. </p><br />
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Future Outreach Plans<br />
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The circuit is the basis for a kit to be used by high school Science teachers in classrooms in public schools in Pittsburgh. This is a means to incorporate Synthetic Biology in the HS curriculum. The kit is made available through the Lending Library of Science Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the K-12 outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a>.<br />
<br><br />
We also came up with a teaching presentation to assist teachers in using our kits for teaching about Synthetic Biology. To download the presentation, please go to the Teaching Presentation portion of our Wiki.<br />
<br />
<br><br />
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<iframe src="http://www.slideshare.net/slideshow/embed_code/14905902" width="476" height="400" align="middle" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" ></iframe> <br />
<br><br />
</p><br />
<p><br />
The educational objectives of the classes in which the students use our Synthetic Biology kit are:<br />
<ol><li>Students will be able to give a definition of synthetic biology<br />
</li><li> Students will be able to identify one real-world application of synthetic biology <br />
</li><li> Students will be able to explain how technology is used to extend human abilities<br />
</li><li> Students will be able to recognize the correlation between the input and output of a biological or electronic circuit<br />
</li><li> Students will be able to recognize the advantages and limitations of using models to simulate processes that relate an input and its output<br />
</li><li> Students will be able to discuss the value of collaboration in interdisciplinary fields <br />
</li><li> Students will be able to discuss ethics aspects related to synthetic biology<br />
</ol> <br />
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<p><br />
The impact of synthetic biology depends on the number and quality of scientists making significant contributions to the field. Future scientists will rise from current high school students who are excited about science and gain a solid background in math and science in their formative years. To this end, we decided to raise the awareness of high school students about the interdisciplinary field of synthetic biology and to also teach them about the process of scientific research.<br />
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<img src = "https://static.igem.org/mediawiki/2012/2/20/Outreachphoto1.JPG" align = "right" padding ="5px"><br />
<p><br />
We decided to create teaching materials for high school students inspired by our team’s research project. Our goal was that these materials can be easily used by a science teacher in a lecture in a Biology or Chemistry course to:<br />
<div class = "ol"><br />
<ol type = "1" compact> <br />
<li>Explain what Synthetic Biology is; </li><br />
<li>Illustrate the opportunities created by Synthetic Biology in improving human well being; </li><br />
<li>Discuss ethical concerns related to Synthetic Biology; </li><br />
<li>Enable the students to understand how our <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a> works.</li><br />
</ol><br />
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</p><br />
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<p><br />
To bridge the gap between the background of a high school student and the complexity of our project, we built an affordable, microcontroller-based, hardware platform and associated, open-source, digital simulation software. In designing the demonstration platform, we exploited the relationship between biological networks in synthetic biology and electronic circuits in electrical engineering. Specifically, we created a circuit kit that emulates in hardware our biological construct and in software both the response of the biological construct to specific cell conditions and the fluorescence measurement. It is important to note that the kit is <b>INTERACTIVE</b> (students can easily change electronic components to simulate different biological or external changes and the outcome of these changes), <b> RELATABLE</b> (the students can directly use the kit) and <b>EASILY SHARED AND IMPROVED</b> (the list of electronic components, circuit diagrams etc. are in the public domain and the software is open source).<br />
</p><br />
<br />
<p><br />
The teaching materials we have created, specifically a <a href="https://www.dropbox.com/s/n1bpb77einu26ko/iGEM_Summer_Presentation.pdf"> power point presentation</a> and an <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> electronic circuit kit</a>, have become part of the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The kits in the Library are loaned to high school teachers in the Pittsburgh area to be used in teaching Math and Science. We identified for the teachers how the use of our kit can help the High School students meet specific objectives from the <a href ="http://static.pdesas.org/content/documents/Academic_Standards_for_Science_and_Technology_and_Engineering_Education_%28Secondary%29.pdf">Pennsylvania Academic Standards for Science, Technology, and Engineering Education</a> and the <a href ="http://www.portal.state.pa.us/portal/server.pt/community/assessment_anchors/7440 ">Pennsylvania Assessment Anchors</a>. We have also tested the kit in several demonstrations in the Summer of 2012 to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> Summer Academy of Math and Science (SAMS)</a> at Carnegie Mellon.<br />
</p><br />
<br />
<p><br />
A very important original property of our approach to Human Practices stems from the fact that the teaching materials we created are available to teachers in any Pittsburgh Public School District who can borrow them from the Lending Library of Kits and use them even after the work of the current CMU iGEM team ends. Another original factor is the fact that we identified for the teachers which objectives from the Pennsylvania Academic Standards for Science, Technology and Engineering they can teach using the kit. This identification should eliminate the barrier to adoption of the kit by teachers faced with tight time schedules to cover these objectives.<br />
</p><br />
<p><br />
</p><br />
<h1 id="section1-1"> System Implemented with the Kit </h1><br />
<img src="https://static.igem.org/mediawiki/2012/f/f4/System_model.jpg" height="300" width="433" align="right"/><br />
<p><br />
As described <a href="https://2012.igem.org/Team:Carnegie_Mellon"> here</a>, our team engineered a fluorescence-based sensor that provides information on both transcription strength and translation efficiency of a promoter. The sensor is noninvasive, easily applied to a variety of promoters, and capable of providing results in a time frame that is short when compared to current technologies for the characterization of promoters. <br />
</p><br />
<p><br />
The sensor is based on the use of an RNA aptamer (termed Spinach) and a fluorogen activating protein (FAP). The complexes of Spinach (mRNA-DMHBI in the Figure) and FAP (FAP-MG in the Figure) with specific dyes, DFHBI and MG, respectively, are fluorescent. Measurements of the fluorescence intensity of these complexes enables one to determine the concentration of mRNA and expressed protein for a given promoter. Analysis of the fluorescence data with an appropriate model leads to the transcription strength and translation efficiency for each promoter.<br />
</p><br />
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The Hardware/Software Platform<br />
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The goal was to create a model of our <b><a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a></b> that clearly represents its main components and makes clear how the biosensor works. We also planned to enable the students to simulate changes in the “environment” and to observe the outcome of these changes. To achieve this goal, we built an affordable, microcontroller-based, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> hardware</a> platform and also developed an associated, open-source, simulation <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software"> software</a>. <br />
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The combined hardware/software platform allows the students to directly manipulate electronic components, which are formal equivalents of the BioBricks used in our sensor, and to observe the effect of changing these components on the current or voltage output, which is the equivalent of the fluorescence intensity in our lab experiments. In using the kit, the students get a feel for how different promoters are compared using the biosensor; they can rank "virtual promoters" in the order of their strength. Students who use the kit gain hands-on experience and understand how all the parts of the biosensor work together to measure the mRNA and protein levels, without working in the wet lab.<br />
The figure on the right is a photograph of the hardware platform on which the correspondence between the biological components of the biosensor and the electronic components of the kit are identified.<br />
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The software used in the platform is based on the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> model</a> derived for the analysis of the fluorescence data obtained with the biosensor. We have also created a GUI that allows the students to modify the parameters used in the model and to visualize on a computer display the current/voltage output (which is the equivalent of the fluorescence output in our experiments).<br />
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Team Presentations to Groups of High School Students<br />
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To obtain feedback for how high school students use the circuit kit, the team has given several presentations about synthetic biology and our project to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> SAMS</a> and in <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/apea.html"> AP Biology</a> at Carnegie Mellon University. <br />
We have also sought and obtained feedback on the kit from Dr. Janet Waldeck, Physics teacher at the Pittsburgh Allderdice High School in Pittsburgh. <br />
The feedback and input gained from these presentations was used to refine the kit. <br />
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{{:Team:Carnegie_Mellon/Templates/Footer}}</div>Ychoohttp://2012.igem.org/Team:Carnegie_MellonTeam:Carnegie Mellon2012-10-27T03:13:10Z<p>Ychoo: </p>
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<li class="toc-h1"><a href="#section1">1. FAQ</a><br />
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<i><div class="glow-title">Real-time quantitative measurement of RNA and protein levels using fluorogen-activated biosensors </div></i><br />
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<h1> Introduction: Motivation and Background </h1><br />
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<p><br />
<b> Our primary goal is to develop new promoters that can be measured with fluorescent technology.</b> <br />
</p><br />
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<li><p> We seek to develop a system that will allow researchers in the field of synthetic biology to accurately measure a variety of metrics in gene expression networks including translational efficiency and transcriptional strength.<br />
</p></li><br />
<li><p> We hypothesize that we can use Spinach (a fluorogen-activating RNA sequence) and a FAP (fluorogen activating protein) as biosensors to measure these gene expression metrics <i>in vivo</i> (in living cells), rather than <i>in vitro</i> (in a test tube), which can be very costly and labor intensive.<br />
</p></li><br />
<li><p> We aim to characterize the relationship between synthesis rates of Spinach and transcription rates and the relationship between synthesis rates of FAP and translation rates. <br />
</p></li><br />
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<p><h1><br />
<a name="Project_description"></a>Project Description</h1><br />
<h3><b>Experimental</b></h3><br />
<p><br />
The design and implementation of synthetic biological systems often require information on transcription and translation rates and on the impact of both RNA and protein levels on metabolic activities of host cells. Such information is needed when both strong and low levels of expression are desired, depending on the biologists’ goal, e.g., high production or single-molecule localization of a protein, respectively. To date, however, quantitative information about the expression strength of a promoter is difficult to obtain due to the lack of noninvasive and quick approaches to measure levels of RNA and protein in cells. <br />
</p><br />
<p><br />
Here, we engineer a fluorescence-based biosensor that can provide information on both transcription strength and translation efficiency that is noninvasive, easily applied to a variety of promoters, and capable of providing results in a time frame that is short when compared to current technologies. The sensor is based on the use of an RNA aptamer (termed Spinach) and a fluorogen activating protein (FAP). Both the Spinach and FAP become fluorescent in response to binding with dye molecules. The combination of FAP and Spinach will allow us to quantitatively determine relationships involving mRNA and protein, such as translational efficiency.<br />
</p><br />
<p><br />
To demonstrate the utility of the sensor, we have constructed and characterized four T7Lac promoters. For each of the promoters, we have measured both mRNA and protein fluorescence over time. The time-lapse fluorescence levels of mRNA and protein were used in a mathematical model for the estimation of transcription and translation rate constants.<br />
We have submitted these promoters to the parts registry, whose strength is measured by the newly developed biosensor.<br />
</p><br />
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<p><br />
<i><a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> Learn more here</a></i><br />
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<h3><b><br />
Human Practices<br />
</b></h3><br />
<p><br />
The impact of synthetic biology depends on the number and quality of scientists making significant contributions to the field. To this end, we contributed to raising the awareness of high school students, who may become future scientists, about the interdisciplinary field of synthetic biology, and about the preparation one needs to become a synthetic biologist.<br />
</p><br />
<p><br />
We decided to create teaching materials for high school students inspired by our team’s research project. Our goal was that these materials can be easily used by a science teacher in a lecture in a Biology or Chemistry course to (1) explain what Synthetic Biology is, and (2) enable the students to understand how our <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> biosensor</a> works. The teaching materials we have created, specifically a power point presentation and an <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> electronic circuit kit</a>, have become part of the Lending Library of Kits of <a href="http://www.cmu.edu/cnast/DNAZone/index"> DNAZone</a>, the outreach program of the <a href="http://www.cmu.edu/cnast/"> Center of Nucleic Acids Science and Technology (CNAST)</a> at Carnegie Mellon. The kits in the Library are loaned to high school teachers in the Pittsburgh area to be used in teaching Math and Science. We have also tested the kit in several demonstrations in the Summer of 2012 to high school students enrolled in the <a href="http://www.cmu.edu/enrollment/summerprogramsfordiversity/sams.html"> Summer Academy of Math and Science (SAMS)</a> at Carnegie Mellon.<br />
</p><br />
<p><br />
To bridge the gap between the background of a high school student and the complexity of our project, we built an affordable, microcontroller-based, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit"> hardware platform</a> and associated, open-source, digital simulation <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Software"> software</a>. The combined hardware/software platform allows the students to directly manipulate electronic components, which are formal equivalents of the BioBricks used in our sensor, and to observe the effect of changing these components on the current or voltage output, which is the equivalent of the fluorescence intensity in our lab experiments. The software part of the platform includes the same model we created for the analysis of the sensor, and the GUI that facilitates the manipulation of the circuit kit.<br />
</p><br />
</p><br />
<p><br />
<i><a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview"> Learn more here</a></i><br />
</p><br />
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<a name="Objective_1:_A_New_Set_of_Well-Characterized_Promoters"></a><h1> <span class="mw-headline"> Objective 1: Novel Well-Characterized Promoters </span></h1><br />
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<p><b>Our first objective is to develop a series of BioBricks that are well characterized based on our methods of measurement.</b></p></font><br />
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<p>We assert that our new method of analyzing promoters can quantify certain properties such as: </p><br />
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<p><br />
<ol><li> Translational efficiency <i>in vivo </i><br />
</li><li> <i>In vivo</i> transcription rates<br />
</li><li> Promoter strength<br />
</li><li> <i>In vivo</i> mRNA and protein half-lives in real time<br />
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<p>The promoters we submit were characterized with these properties. </p><br />
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<p><br />
<img src="https://static.igem.org/mediawiki/2012/d/de/Ts.png" height="300" width="380" align="center"/><br />
<img src="https://static.igem.org/mediawiki/2012/9/9b/Tl.png" height="300" width="380" ><br />
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<strong>Figure 1: Measured transcription (left panel) and translation (right panel) rate constants of three new promoters using a new fluorogen-activated biosensor. </strong><br />
<br> Based on established parts, we have developed a new biosensor that can report levels of both RNA and protein in a single cell. This biosensor enables non-invasive and real-time measurements of RNA and protein expression rates. We have applied the biosensor in the characterization of three new T7Lac promoters, which yielded high quality time-lapse data of both RNA and protein levels (see details in <a href = "https://2012.igem.org/Team:Carnegie_Mellon/Met-Overview"> Methods & Results </a>). The data was used to estimate transcription and translation rate constants (see details in <a href =" https://2012.igem.org/Team:Carnegie_Mellon/Mod-Overview"> Modeling </a>). <br />
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<a name="Objective_2:_Human_Practices"></a><h1> <span class="mw-headline"> Objective 2: Human Practices</span></h1><br />
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<p> As part of our project, we seek to intrigue high school students about synthetic biology and engineering. In this pursuit, we developed an electrical analog of our BioBricks (with a simulated microscope using LEDs and a photoresistor) to teach high school students about:<br />
<ol><li> Synthetic biology and its relationship to biology, science, and engineering in general<br />
</li><li> Gene expression and the central dogma of molecular biology<br />
</li><li> How synthetic biologists tackle real-world problems<br />
</li><li> The iGEM competition and how our iGEM team's project enables one to measures the properties of promoters<br />
</li><li> The interdisciplinary nature of synthetic biology<br />
</li><li> The advantages and challenges of interdisciplinary work<br />
</li></ol><br />
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<p>The 2012 Carnegie Mellon University iGEM team consists of students from Biological Sciences, Electrical and Computer Engineering, Biomedical Engineering and Chemical Engineering.<br />
<ul><li>Peter Wei (ECE, BME)<br />
</li><li>Yang Choo (ChemE, BME)<br />
</li><li>Jesse Salazar (ECE, BME)<br />
</li><li>Eric Pederson (Bio)<br />
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<a name="Further_Considerations"></a><h1> <span class="mw-headline"> Further Considerations </span></h1><br />
<p>In the pursuit of our project we:<br />
<ul><li> Considered the <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Overview" rel="nofollow">ethical, legal and social implications</a> of our BioBrick<br />
</li><li> Wrote <a href="https://2012.igem.org/Team:Carnegie_Mellon/Mod-Matlab" rel="nofollow"> new software</a> for modeling the performance of our BioBrick<br />
</li><li> Developed and tested <a href="https://2012.igem.org/Team:Carnegie_Mellon/Met-Protocols" rel="nofollow">techniques for measuring translational efficiency and transcriptional strength </a><br />
</li><li> Created materials for teaching high school students about synthetic biology and scientific research. These materials included a programmable and interactive, <a href="https://2012.igem.org/Team:Carnegie_Mellon/Hum-Circuit" rel="nofollow">electrical analog of our biosensor.</a><br />
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