Team:Berkeley

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     <title>Berkeley iGEM 2011 </title>
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     <title>Berkeley iGEM 2012 </title>
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     <li><a href="https://2012.igem.org/Team:Berkeley/Team">Team</a></li>
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     <li><a href="https://2012.igem.org/Team:Berkeley/Judging">Judging</a></li>
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<p>
Many applications in synthetic biology demand precise control over subcellular localization, cell morphology, motility, and other such phenotypes that are only observable via microscopy. At present, engineering these properties is challenging due in large part to the inherent throughput limitation imposed by microscopy. We have developed a strategy that enables high-throughput library screening with microscopy by coupling a unique fluorescence signature with each genotype present in a library. These MiCodes (microscopy barcodes) are generated by targeting combinations of fluorophores to several organelles within yeast, and they eliminate the need to isolate and observe clonal populations separately. MiCodes can potentially scale to library sizes of 10^6 or more, and their analysis can be largely automated using existing image processing software. As a proof of principle, we applied MiCodes to the problem of finding unique pairs of protein-protein interaction parts.  
Many applications in synthetic biology demand precise control over subcellular localization, cell morphology, motility, and other such phenotypes that are only observable via microscopy. At present, engineering these properties is challenging due in large part to the inherent throughput limitation imposed by microscopy. We have developed a strategy that enables high-throughput library screening with microscopy by coupling a unique fluorescence signature with each genotype present in a library. These MiCodes (microscopy barcodes) are generated by targeting combinations of fluorophores to several organelles within yeast, and they eliminate the need to isolate and observe clonal populations separately. MiCodes can potentially scale to library sizes of 10^6 or more, and their analysis can be largely automated using existing image processing software. As a proof of principle, we applied MiCodes to the problem of finding unique pairs of protein-protein interaction parts.  
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<div class="col3-2"style="background-color:#101a4d;"><a href="https://2011.igem.org/Team:Berkeley/Project#ToxR"> <img src="https://static.igem.org/mediawiki/igem.org/1/10/Subtitlepic1.jpg"  
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<div class="col3-2"style="background-color:#101a4d;"><a href="https://2012.igem.org/Team:Berkeley/Project#ToxR"> <img src="https://static.igem.org/mediawiki/igem.org/1/10/Subtitlepic1.jpg"  
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  <p style="text-align:center; color:#CECECE;"> A protein with great potential as a general biosensor system.</p> </div>
  <p style="text-align:center; color:#CECECE;"> A protein with great potential as a general biosensor system.</p> </div>
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<div class="col3-2"style="background-color:#185f73;"><a href="https://2011.igem.org/Team:Berkeley/Project#ToxRChimera"><img src="https://static.igem.org/mediawiki/2011/b/bb/Subtitlepic3header.jpg"  
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<div class="col3-2"style="background-color:#185f73;"><a href="https://2012.igem.org/Team:Berkeley/Project#ToxRChimera"><img src="https://static.igem.org/mediawiki/2011/b/bb/Subtitlepic3header.jpg"  
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<p>We are Team Berkeley, a cohesive unit of 7 undergraduates and 3 advisers. Earlier this year we planned a complex and risky project, given the short amount of time iGEM made available. We quickly learned each others strengths and weaknesses and developed standard systems of organizational management in order to synchronize our efforts for the many parallel tasks at hand. We created protocols, shared them with one another, and worked together on troubleshooting. Using google docs to keep up with the status of cloning projects, the results of assays, material logistics, or the final steps required to complete a project ensured that through the months of hard work, we fine-tuned our ability to work together. As a team, we have learned firsthand how the synthetic biology community relies on the goal-oriented cooperation of skilled individuals from very different backgrounds and with very different skill sets. Some of us have strong engineering backgrounds while others of us have strong biology backgrounds, but we all share a desire to build synthetic biological systems that solve human problems. We are proud of the project that we have created which we will present at the Jamboree together in October.</p>
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<p style="text-align:left; color:#CECECE; font-size:13px; font-weight:bold; padding:3px"> The UC Berkeley iGEM team would like to thank Autodesk and Agilent for their financial support and Synberc, for their administrative support. </p>
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<p style="text-align:left; color:#CECECE; font-size:13px; font-weight:bold; padding:3px"> The UC Berkeley iGEM team would like to thank Agilent for their financial support and Synberc for their administrative support. </p>
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Revision as of 04:06, 26 September 2012

Berkeley iGEM 2012

header
Mercury

Many applications in synthetic biology demand precise control over subcellular localization, cell morphology, motility, and other such phenotypes that are only observable via microscopy. At present, engineering these properties is challenging due in large part to the inherent throughput limitation imposed by microscopy. We have developed a strategy that enables high-throughput library screening with microscopy by coupling a unique fluorescence signature with each genotype present in a library. These MiCodes (microscopy barcodes) are generated by targeting combinations of fluorophores to several organelles within yeast, and they eliminate the need to isolate and observe clonal populations separately. MiCodes can potentially scale to library sizes of 10^6 or more, and their analysis can be largely automated using existing image processing software. As a proof of principle, we applied MiCodes to the problem of finding unique pairs of protein-protein interaction parts.

A protein with great potential as a general biosensor system.

Chimeric proteins that drive translation off of the Pctx promoter.

Our method for expressing interesting (but toxic) proteins.

Bacteria engineered to detect the presence of estrogen.


INSERT IGEM 2012 BLURB HERE


The UC Berkeley iGEM team would like to thank Agilent for their financial support and Synberc for their administrative support.


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iGEM Berkeley iGEMBerkeley iGEMBerkeley

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