http://2012.igem.org/wiki/index.php?title=Special:Contributions&feed=atom&limit=50&target=LoboLofi&year=&month=2012.igem.org - User contributions [en]2024-03-29T05:15:31ZFrom 2012.igem.orgMediaWiki 1.16.0http://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/Cellular.htmTeam/CINVESTAV-IPN-UNAM MX/Cellular.htm2012-10-27T00:18:21Z<p>LoboLofi: </p>
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<h1><em>Strange variant of cellular automata for the simulation of a bio-reactor!<em></h1><br />
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<p id="text2">Introduction</p><br />
<p><br />
First of all: why use cellular automata if any linear models are easier to analyze? Well, for starters look great.<br />
</p><br />
<img src="https://static.igem.org/mediawiki/2012/5/50/CA1.gif" alt="This look great, no?"><br />
<p>Second, depending on the configuration of the cellular automaton "how you look", the CA is more realistic and we can provide sufficient data to feed other models. In fact, is just what took place in this model.<br />
</p><p>Imagine that we are scientists with more material resources in the world and that we can generate hundreds of experiments in the conditions we want to feed our prediction models. Well, the CA allows us to do this with the only drawback that we hate our CPU.<br />
</p><h2>Brief History</h2><br />
<p>Cellular automata are a mathematical model developed by Konrad Zuse and Stanislaw Ulam, but was better known and developed by a guy named John Vonn Neumann who loved parallel computing, but, as usual, history remembers him as the father of sequential computing.<br />
</p><p>Later, during the disruptive and flowery decade of 60's, a crazy mathematical said "oh, it would be great to do a math game where no players" (you know, the time before tetris and farmville), and created the world famous "Game of Life". The name of this cool mathematician was John Horton Conway. The really curious thing about this game was that, unlike tetris and Farmville, is a universal machine,is that you can solve almost any problem with it.<br />
</p><p>For this reason lot of scientists began to study seriously about the CA. Primarily a physicist a bit eccentric named Steven Wolfram, he study until the 90's, He used cellular automata to deal a coup against traditional scientific methodology, emphasizing the importance of simulations and modeling computer as unquestionable substitutes of the traditional experimentation.<br />
</p><h2>How To?</h2><br />
<img src="https://static.igem.org/mediawiki/2012/b/b8/Resistentbacter.gif" alt="A very Resistent bacterium"><br />
<p>How does a cellular automaton? Well, imagine a group of guys in a dance floor. One of these says, "Well, If I'm the only one who is dancing or there is only one person dancing, I think that i'm don't i will not be a laughing stock" and "If more than 4 people are dancing, the better is stop of dance, it's uncomfortable dancing among many people ". And of course "else, i dancing all the night". Now, imagine that all people think the same track, that's basically a CA: a set of individuals (cells) that act similarly and simultaneously within a (lattice).<br />
</p><p>But, think more applied: if instead of teenage dancers, bacteria were willing to eat? Instead of a dance floor, outside a bioreactor? There are a more couple of questions to answer: If you want to feed the bacteria, the amount of food that is around you is also important, and we should consider adding it, and if they are fed well, they can not go to the bathroom to leave their waste , so we must take into account their waste.<br />
</p><p>Well, this is a brief description of our model, we have a bioreactor cells, bacteria, food and debris. That is, a lattice and three types of cells that fill it.<br />
</p><p>What else do we need to know? In the past example we said, "I need two or three people so that I can dance", but as we speak now of bacteria and food, we say "I need amount n of food and amout m of other bacteria that can feed with me", because , you know, no one likes to eat alone.<br />
</p><p>But we can go further in this model. Suppose the bioreactor gives us ideal conditions every so often and eliminates food waste produced and they distributed throughout the lattice.<br />
</p><p>In our model, we decided to have two lattices: one for our friend Rhodobacter, where there may be a bacterium or may be not that. And another lattice with the same number of squares, but with x percent of food, "y" percent of wastes and z percent for other resources. In this way we can generate simple rules:<br />
</p><ul><br />
<li>If, for example, among all the cells I have around, sum at least 2 complete squares, the bacter will survive.</li><br />
<li>However, If there more than 5 boxes of waste, the bacterium die.</li><br />
<li>If at least two bacteria and exist enough food, namely more than 2 squares of food, grow a new bacteria.</li><br />
</ul><br />
<p>Thus, the CA showed a more realistic simulation, but mostly we will get data from simulation models can feed others.<br />
</p><p>The two main disadvantages of the CA is the CPU time needed to calculate the simulation and randomness that can have its outcome, in other words, depending on how initialize living cells and the percentage that we decide to add for each compound in the second lattice.<br />
</p><p>The first problem is easy to solve: the current CPU is fast enough to avoid problems in these calculations.<br />
</p><p>The second problem is harder to solve. There are several methods, our personal favorite, another mathematical model: perform multiple simulations with different distributions of bacteria and its results are added to a probability function that characterizes certain experiment.<br />
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<br />
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</html></div>LoboLofihttp://2012.igem.org/File:GUI_prototype_for_cellular_automata.pngFile:GUI prototype for cellular automata.png2012-10-27T00:14:14Z<p>LoboLofi: GUI prototype for cellular automata. V1.0</p>
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<div>GUI prototype for cellular automata. V1.0</div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/Cellular.htmTeam/CINVESTAV-IPN-UNAM MX/Cellular.htm2012-10-26T22:07:00Z<p>LoboLofi: </p>
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<h1>Strange variant of cellular automata for the simulation of a bio-reactor</h1><br />
<br />
<h2>Introduction</h2><br />
<p><br />
First of all: why use cellular automata if any linear models are easier to analyze? Well, for starters look great.<br />
</p><br />
<img src="https://static.igem.org/mediawiki/2012/5/50/CA1.gif" alt="This look great, no?"><br />
<p>Second, depending on the configuration of the cellular automaton "how you look", the CA is more realistic and we can provide sufficient data to feed other models. In fact, is just what took place in this model.<br />
</p><p>Imagine that we are scientists with more material resources in the world and that we can generate hundreds of experiments in the conditions we want to feed our prediction models. Well, the CA allows us to do this with the only drawback that we hate our CPU.<br />
</p><h2>Brief History</h2><br />
<p>Cellular automata are a mathematical model developed by Konrad Zuse and Stanislaw Ulam, but was better known and developed by a guy named John Vonn Neumann who loved parallel computing, but, as usual, history remembers him as the father of sequential computing.<br />
</p><p>Later, during the disruptive and flowery decade of 60's, a crazy mathematical said "oh, it would be great to do a math game where no players" (you know, the time before tetris and farmville), and created the world famous "Game of Life". The name of this cool mathematician was John Horton Conway. The really curious thing about this game was that, unlike tetris and Farmville, is a universal machine,is that you can solve almost any problem with it.<br />
</p><p>For this reason lot of scientists began to study seriously about the CA. Primarily a physicist a bit eccentric named Steven Wolfram, he study until the 90's, He used cellular automata to deal a coup against traditional scientific methodology, emphasizing the importance of simulations and modeling computer as unquestionable substitutes of the traditional experimentation.<br />
</p><h2>How To?</h2><br />
<img src="https://static.igem.org/mediawiki/2012/b/b8/Resistentbacter.gif" alt="A very Resistent bacterium"><br />
<p>How does a cellular automaton? Well, imagine a group of guys in a dance floor. One of these says, "Well, If I'm the only one who is dancing or there is only one person dancing, I think that i'm don't i will not be a laughing stock" and "If more than 4 people are dancing, the better is stop of dance, it's uncomfortable dancing among many people ". And of course "else, i dancing all the night". Now, imagine that all people think the same track, that's basically a CA: a set of individuals (cells) that act similarly and simultaneously within a (lattice).<br />
</p><p>But, think more applied: if instead of teenage dancers, bacteria were willing to eat? Instead of a dance floor, outside a bioreactor? There are a more couple of questions to answer: If you want to feed the bacteria, the amount of food that is around you is also important, and we should consider adding it, and if they are fed well, they can not go to the bathroom to leave their waste , so we must take into account their waste.<br />
</p><p>Well, this is a brief description of our model, we have a bioreactor cells, bacteria, food and debris. That is, a lattice and three types of cells that fill it.<br />
</p><p>What else do we need to know? In the past example we said, "I need two or three people so that I can dance", but as we speak now of bacteria and food, we say "I need amount n of food and amout m of other bacteria that can feed with me", because , you know, no one likes to eat alone.<br />
</p><p>But we can go further in this model. Suppose the bioreactor gives us ideal conditions every so often and eliminates food waste produced and they distributed throughout the lattice.<br />
</p><p>In our model, we decided to have two lattices: one for our friend Rhodobacter, where there may be a bacterium or may be not that. And another lattice with the same number of squares, but with x percent of food, "y" percent of wastes and z percent for other resources. In this way we can generate simple rules:<br />
</p><ul><br />
<li>If, for example, among all the cells I have around, sum at least 2 complete squares, the bacter will survive.</li><br />
<li>However, If there more than 5 boxes of waste, the bacterium die.</li><br />
<li>If at least two bacteria and exist enough food, namely more than 2 squares of food, grow a new bacteria.</li><br />
</ul><br />
<p>Thus, the CA showed a more realistic simulation, but mostly we will get data from simulation models can feed others.<br />
</p><p>The two main disadvantages of the CA is the CPU time needed to calculate the simulation and randomness that can have its outcome, in other words, depending on how initialize living cells and the percentage that we decide to add for each compound in the second lattice.<br />
</p><p>The first problem is easy to solve: the current CPU is fast enough to avoid problems in these calculations.<br />
</p><p>The second problem is harder to solve. There are several methods, our personal favorite, another mathematical model: perform multiple simulations with different distributions of bacteria and its results are added to a probability function that characterizes certain experiment.<br />
</p><br />
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</html></div>LoboLofihttp://2012.igem.org/File:Resistentbacter.gifFile:Resistentbacter.gif2012-10-26T22:04:35Z<p>LoboLofi: A example of a bacterium very resistent to other bacteriums and the lonely</p>
<hr />
<div>A example of a bacterium very resistent to other bacteriums and the lonely</div>LoboLofihttp://2012.igem.org/File:CA1.gifFile:CA1.gif2012-10-26T22:00:37Z<p>LoboLofi: Cellular Automata</p>
<hr />
<div>Cellular Automata</div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/Cellular.htmTeam/CINVESTAV-IPN-UNAM MX/Cellular.htm2012-10-26T21:59:23Z<p>LoboLofi: </p>
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<h1>Strange variant of cellular automata for the simulation of a bio-reactor</h1><br />
<br />
<h2>Introduction</h2><br />
<p><br />
First of all: why use cellular automata if any linear models are easier to analyze? Well, for starters look great.<br />
</p><p>Second, depending on the configuration of the cellular automaton "how you look", the CA is more realistic and we can provide sufficient data to feed other models. In fact, is just what took place in this model.<br />
</p><p>Imagine that we are scientists with more material resources in the world and that we can generate hundreds of experiments in the conditions we want to feed our prediction models. Well, the CA allows us to do this with the only drawback that we hate our CPU.<br />
</p><h2>Brief History</h2><br />
<p>Cellular automata are a mathematical model developed by Konrad Zuse and Stanislaw Ulam, but was better known and developed by a guy named John Vonn Neumann who loved parallel computing, but, as usual, history remembers him as the father of sequential computing.<br />
</p><p>Later, during the disruptive and flowery decade of 60's, a crazy mathematical said "oh, it would be great to do a math game where no players" (you know, the time before tetris and farmville), and created the world famous "Game of Life". The name of this cool mathematician was John Horton Conway. The really curious thing about this game was that, unlike tetris and Farmville, is a universal machine,is that you can solve almost any problem with it.<br />
</p><p>For this reason lot of scientists began to study seriously about the CA. Primarily a physicist a bit eccentric named Steven Wolfram, he study until the 90's, He used cellular automata to deal a coup against traditional scientific methodology, emphasizing the importance of simulations and modeling computer as unquestionable substitutes of the traditional experimentation.<br />
</p><h2>How To?</h2><br />
<p>How does a cellular automaton? Well, imagine a group of guys in a dance floor. One of these says, "Well, If I'm the only one who is dancing or there is only one person dancing, I think that i'm don't i will not be a laughing stock" and "If more than 4 people are dancing, the better is stop of dance, it's uncomfortable dancing among many people ". And of course "else, i dancing all the night". Now, imagine that all people think the same track, that's basically a CA: a set of individuals (cells) that act similarly and simultaneously within a (lattice).<br />
</p><p>But, think more applied: if instead of teenage dancers, bacteria were willing to eat? Instead of a dance floor, outside a bioreactor? There are a more couple of questions to answer: If you want to feed the bacteria, the amount of food that is around you is also important, and we should consider adding it, and if they are fed well, they can not go to the bathroom to leave their waste , so we must take into account their waste.<br />
</p><p>Well, this is a brief description of our model, we have a bioreactor cells, bacteria, food and debris. That is, a lattice and three types of cells that fill it.<br />
</p><p>What else do we need to know? In the past example we said, "I need two or three people so that I can dance", but as we speak now of bacteria and food, we say "I need amount n of food and amout m of other bacteria that can feed with me", because , you know, no one likes to eat alone.<br />
</p><p>But we can go further in this model. Suppose the bioreactor gives us ideal conditions every so often and eliminates food waste produced and they distributed throughout the lattice.<br />
</p><p>In our model, we decided to have two lattices: one for our friend Rhodobacter, where there may be a bacterium or may be not that. And another lattice with the same number of squares, but with x percent of food, "y" percent of wastes and z percent for other resources. In this way we can generate simple rules:<br />
</p><ul><br />
<li>If, for example, among all the cells I have around, sum at least 2 complete squares, the bacter will survive.</li><br />
<li>However, If there more than 5 boxes of waste, the bacterium die.</li><br />
<li>If at least two bacteria and exist enough food, namely more than 2 squares of food, grow a new bacteria.</li><br />
</ul><br />
<p>Thus, the CA showed a more realistic simulation, but mostly we will get data from simulation models can feed others.<br />
</p><p>The two main disadvantages of the CA is the CPU time needed to calculate the simulation and randomness that can have its outcome, in other words, depending on how initialize living cells and the percentage that we decide to add for each compound in the second lattice.<br />
</p><p>The first problem is easy to solve: the current CPU is fast enough to avoid problems in these calculations.<br />
</p><p>The second problem is harder to solve. There are several methods, our personal favorite, another mathematical model: perform multiple simulations with different distributions of bacteria and its results are added to a probability function that characterizes certain experiment.<br />
</p><br />
</div><br />
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<div id="updates" class="orangebox"><br />
<br />
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</html></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/automata.htmTeam/CINVESTAV-IPN-UNAM MX/automata.htm2012-09-27T04:07:59Z<p>LoboLofi: </p>
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<p><strong>Cellular automata approaches to biological modeling.</strong></p><br />
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In the near future, our project can be used to produce biofuels, so we decided to create a software that allows us to generate Pilot-Plant simulations. </p><br />
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To perform this software, we are taking the two-dimensional Cellular Automata developed by John Conway called &quot;GAME OF LIFE&quot;, and extending it over a living cell type, in where there are several stages of the cell and different scope ranges. Our goal is to generate enough simulations at different concentrations of reactants or products under distinct environmental conditions; until the program shows what inputs (concentrations) are optimal to maximize the production.</p><br />
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At this point, the program runs simulations based on precompiled transition rules, but due to the inherent complexity of cellular automata, a single simulation isn´t enough. So the next step is to vary the concentrations and apply an evolutionary algorithm to modify the starting conditions of the &quot;game&quot; in each iteration cycle.</p><br />
<p><img src="https://static.igem.org/mediawiki/2012/3/3a/Pic1q.png" width="625" height="305" /></p><br />
<p><strong>Figure 1. TWO-DIMENSIONAL CELLULAR AUTOMATA.</strong></p><br />
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<img src="https://static.igem.org/mediawiki/2012/9/99/Interaction_between_AppA_and_PpsR.png" alt="Interaccion between AppA and PpsR with light and oxigen" ><br />
<strong style="font-size: 0.875em;">FIGURE 1. Interaction between AppA and PpsR as a function of the oxygen concentration [O2] and blue-light irradiance LI . The tetramers with intramolecular disul?de bonds (S-S) and thiol groups (SH) denote the oxidized and the reduced form of the PpsR repressor, respectively. The AppA protein has an FAD and a heme cofactor attached where h+ and hפenote the oxidized and reduced form of the heme cofactor, respectively. Both the oxidized and the reduced form of PpsR act as a repressor of photosynthesis genes, but with different strengths as indicated by the line thickness. Pandey, 2011.</strong><br />
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<div id="TexBox1" style=" background-color:DarkSeaGreen;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px"><br />
<p> The proteins in our regulatory system constitute a network of intermingling elements whose behavior can be narrow into basic interaction rules. Primarily in this part of the modeling we focused on the PpsR and AppA anti-repressor/repressor system and chose to model it using a system of ordinary differential equations. The systemӳ repressive activity varies with the redox (O2) state of the cell and Light intensity and thus we wondered how exactly these two variables affect the overall repressive level of PpsR over the expression of PS genes.</p><br />
</div><br />
<p>This is the code written for the regulatory system Appa-PpsR in Mathematica.</p><br />
<img src="https://static.igem.org/mediawiki/2012/2/26/MathemathcaCodeICIPNUNAMMX.png" alt="Code of Differential Equations in mathematica"><br />
<div id="TexBox2" style=" background-color:Crimson;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px; color:#FFF"><br />
<p>To do this we based ourselves on a previous work that had attempted to study this same regulatory system. <strong style="color:#000">[Pandey, Rakesh Flockerzi, Dietrich Hauser, Marcus JB Straube, Ronny. 2011. Modeling the light- and redox-dependent interaction of PpsR/AppA in Rhodobacter sphaeroides.]</strong> In addition to contacting the responsible authors and discussing this model, we chose to improve it based on recent publications and preliminary experimental results i.e. we introduced a more subtle way light and oxygen affects the protein concentration dynamic, which is exactly what we were interested in understanding better.</p><br />
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<strong>Results generated with the model:</strong><br />
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<table cellspacing="10"><br />
<tr><br />
<td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/e/ed/Graph_Oxigen_and_Light_1.jpg" alt="Graph number 1" /></td> <td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/a/a8/Graph_Oxigen_and_Light_2.jpg" alt="Graph number 2"/></td><br />
<tr><br />
<tr><br />
<td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/6/63/Graph_Oxigen_and_Light_3.jpg" alt="Graph number 3"/></td> <td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/2/20/Graph_Oxigen_and_Light_4.jpg" alt="Graph number 2"/></td><br />
<tr><br />
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<br/><br />
<strong style="font-size: 0.875em;">Figure1. Steady state behavior of reduced PpsR (P4+), oxidized PpsR (P4-) and the AppA-PpsR complex as a function of oxygen concentration and light irradiance.</strong><br />
<br/><br />
<p style="color:green;"><br />
With our differential equations system we calculated protein concentrations at stable steady states and assumed this to be a natural "resting", or homeostatic, state given a set of parameters, oxygen and light intensities. As such, this gave us a steady state total repressive force, in essence, as a function of oxygen tension and light intensity. This is because PpsR-AppAӳ total repressive strength is a function of the concentrations of both its oxidative and reduced state.<br />
</p><br />
<div id="TexBox3" style=" background-color:RoyalBlue;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px; color:#FFF"><br />
<p>Because all this was done in Mathematica, we were able to generate an interactive graphical representation of the repressive strength over a range of conditions. This is really the strength of our work because with this model, we can make predictions in sillico as to how the organism will react to a given environmental surrounding and then go back to the lab and validate that prediction.</p><br />
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<p><br />
<strong>Also, since we have the power to manipulate the values of the parameters in an easy and intuitive way, we can explore the parameter space and visually observe the change in the concentration curves, which can be of interest to, not only us, but other people that might not be interested in all the math behind interphase. This parameter tweaking allows us to compare experimental data against sillico predictions; the only difference is that if we focus on the parameters, this can actually give us hints respect to the still-blurred nature of Protein-Protein and Protein-Environment mechanisms that exist in this extremely versatile cell.</strong><br />
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<p><strong>Construction of Model</strong></p><br />
<p>The mathematical model is based on the ODEs and kinetic parameters outlined in <strong>Pandey et al 2011. </strong>The following are its assumptions and basis:</p><br />
<p>In vitro experiments showed that AppA inhibits the DNA-binding activity of oxidized PpsR by two mechanisms (1,2):</p><br />
<p>1. By reducing a disulfide bond in PpsR.<br /><br />
2. By a blue-light-dependent sequestration of PpsR proteins into transcriptionally inactive complexes.</p><br />
<p>At the first stage, the reduced form of AppA (A-) reduces a disulfide bond in oxidized PpsR (P4+), which occurs independently of the light conditions. The molecular mechanism of this two-electron transfer is not yet clear.</p><br />
<p>Redox titration experiments have shown that both PpsR and AppA have two redox-active thiol groups that can form intramolecular disulfide bonds with a similar midpoint potential, according to this equation:</p><br />
<table width="400" border="0"><br />
<tr><br />
<td width="215"><img src="https://static.igem.org/mediawiki/2012/e/e2/Formula.JPG" width="197" height="57" /></td><br />
<td width="169">...1</td><br />
</tr><br />
</table><br />
<p>&nbsp;</p><br />
<p>&nbsp;</p><br />
<p>At the second level of regulation, the reduced form of AppA can form a complex with reduced PpsR. Experiments based on size exclusion chromatography have revealed that, in the complex, one AppA molecule is associated with two PpsR monomers corresponding to half of a PpsR molecule, which exists as a stable tetramer in solution (1).</p><br />
<p>The same study showed that complex formation is inhibited by high intensities of blue-light irradiation (LI ¼ 900mmol/m2s). However, a subsequent study found that AppA responds to blue light over several orders of magnitude down to 0.2 mmol/m2s (3).</p><br />
<p>Other experiments indicate that light absorption induces a structural change in the BLUF domain of AppA (5), which results in interactions with its C-terminal part, thereby causing the dissociation of PpsR (4).</p><br />
<table width="400" border="0"><br />
<tr><br />
<td width="215"><img src="https://static.igem.org/mediawiki/2012/7/72/Formula1.JPG" width="210" height="50" /></td><br />
<td width="169">...2</td><br />
</tr><br />
</table><br />
<p></p><br />
<p> To implement the redox-sensing capabilities of AppA, we use the model proposed by Han et al. (4), according to which AppA utilizes heme as a cofactor, bound to its C-terminal domain, to sense the cytosolic redox conditions, according to this equation:</p> <br />
<table width="400" border="0"><br />
<tr><br />
<td width="215"><img src="https://static.igem.org/mediawiki/2012/f/fc/Formula_2.JPG" width="141" height="55" /></td><br />
<td width="169">...3</td><br />
</tr><br />
</table><br />
<p>&nbsp;</p><br />
<p>If the electron transfer from AppA to PpsR in Eq. 1 was indeed effectively irreversible (kPr -&lt;&lt; kPr+), as suggested by the experiments of Masuda and Bauer (1), PpsR would have to be reoxidized through an AppA-independent mechanism. To account for this possibility, the assumption is that PpsR is reoxidized proportional to the oxygen concentration as:</p><br />
<table width="400" border="0"><br />
<tr><br />
<td width="215"><img src="https://static.igem.org/mediawiki/2012/8/81/Formula3.JPG" width="125" height="47" /></td><br />
<td width="169">...4</td><br />
</tr><br />
</table><br />
<p></p><br />
<p>Finally assuming mass-action kinetics for the reactions in Eq. 1 and Eqs. 3–5 the following are the set of ordinary differential equations established:</p><br />
<table width="400" border="0"><br />
<tr><br />
<td width="215"><img src="https://static.igem.org/mediawiki/2012/8/89/Formula4.JPG" width="422" height="221" /></td><br />
<td width="169">...5</td><br />
</tr><br />
</table><br />
<p></p><br />
<p>Were the total amounts of PpsR and AppA molecules are conserved according to:</p><br />
<br />
<table width="400" border="0"><br />
<tr><br />
<td width="215"><img src="https://static.igem.org/mediawiki/2012/9/9c/Formula5.JPG" width="262" height="70" /></td><br />
<td width="169">...6</td><br />
</tr><br />
</table><br />
<br />
<p></p><br />
<p>1. Masuda, S., and C. E. Bauer. 2002. <strong>AppA is a blue light photoreceptor that antirepresses photosynthesis gene expression in Rhodobacter sphaeroides.</strong> Cell. 110:613–623.<br /><br />
2. Bauer, C. E., S. Elsen, . , S. Masuda. 2003.<strong> Redox and light regulation of gene expression in photosynthetic prokaryotes. </strong>Philos. Trans.R. Soc. Lond. B Biol. Sci. 358:147–153, discussion 153–154.<br /><br />
3. Metz, S., A. Jager, and G. Klug. 2009.<strong> In vivo sensitivity of blue-light- dependent signaling mediated by AppA/PpsR or PrrB/PrrA in Rhodobacter sphaeroides.</strong> J. Bacteriol. 191:4473–4477.<br /><br />
4. Han, Y., M. H. F. Meyer, . , G. Klug. 2007. <strong>A heme cofactor is required for redox and light signaling by the AppA protein of Rhodobacter sphaeroides.</strong> Mol. Microbiol. 64:1090–1104.<br /><br />
5. Masuda, S., K. Hasegawa, and T. A. Ono. 2005.<strong> Light-induced structural changes of apoprotein and chromophore in the sensor of blue light using FAD (BLUF) domain of AppA for a signaling state.</strong>Biochemistry. 44:1215–1224.</p><br />
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<p><strong>Wolfram Research Mathematica</strong></p><br />
<p><br /><br />
Mathematica is a general computer software system and language intended for mathematical and other applications. You can use Mathematica as: A numerical and symbolic calculator where you type in questions, and Mathematica prints out answers, a visualization system for functions and data, a high-level programming language in which you can create programs, large and small ones. and a modeling and data analysis environment.</p><br />
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<strong>Rule-Based Modeling of Biochemical Systems with BioNetGen</strong><br /><br />
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<p>Rule-based modeling involves the representation of molecules as structured objects and molecular interactions as rules for transforming the attributes of these objects. The approach is notable in that it allows one to systematically incorporate site-specific details about protein-protein interactions into a model. BioNetGen allows a user to create a computational model that characterizes the dynamics of a signal transduction system, and that accounts comprehensively and precisely for specified enzymatic activities, potential post-translational modifications and interactions of the domains of signaling molecules. The output defines and parameterizes the network of molecular species that can arise during signaling and provides functions that relate model variables to experimental readouts of interest. Models that can be generated are relevant for rational drug discovery, analysis of proteomic data and mechanistic studies of signal transduction.</p><br />
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<strong>For further details go to:</strong></p><br />
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<p>Characterization of biological systems has reached an unparalleled level of detail. To organize this detail and arrive at a better fundamental understanding of life processes, it is essential that powerful conceptual tools from mathematics and computer science be applied to the frontier problems in biology. </p><br />
<p><br /><br />
Modeling of biological systems is evolving into an important partner of experimental work. They attempt to predict and understand the behavior of complex biological systems before they are actually created. Also models can help to simplify the complexity of data and interactions involved into a more concise form with some measure of predictive ability. This can provide valuable insights into the working and general principles of organization of biological systems. Also it may suggest novel experiments for testing hypotheses, based on the modeling experiences.</p><br />
<p><a href="Tools.htm"><strong>Some of the tools that we used during the modeling process.</strong></a></p><br />
<p><strong><a href="Model.htm">Construction of Model</a></strong></p><br />
<p><strong><a href="intercellular.htm">Modeling the intercellular signaling process during regulation of PS genes expression in BioNetGEn.</a></strong></p><br />
<p><strong><a href="equations.htm">Differential equations modeling the interactions between AppA and PpsR. </a></strong><a href="equations.htm"><br /><br />
<strong>Modeling Steady State</strong></a><strong></strong></p><br />
<p><a href="automata.htm"><strong>Cellular automata approaches to biological modeling.</strong></a></p><br />
<p><strong>References used through this section.</strong></p><br />
<ol><br />
<li>Oh JI, Kaplan S. (2001) <strong>Generalized approach to the regulation and integration of gene expression. </strong>Mol Microbiol. </li><br />
</ol><br />
<ol><br />
<li>Zeilstra-Ryalls JH, Kaplan S. (1995) <strong>Aerobic and anaerobic regulation in Rhodobacter sphaeroides</strong> 2.4.1: the role of the fnrL gene. J Bacteriol. </li><br />
</ol><br />
<p>&nbsp;</p><br />
<ol><br />
<li>Rakesh Pandey, Dietrich Flockerz. (2011) <strong>Modeling the Light- and Redox-Dependent Interaction of PpsR/AppA in Rhodobacter sphaeroides. </strong>Cell Press.</li><br />
</ol><br />
<ol><br />
<li>Shinji Masuda&nbsp;and&nbsp;Carl E. Bauer. (2002) <strong>AppA Is a Blue Light Photoreceptor that Antirepresses Photosynthesis Gene Expression in Rhodobacter sphaeroides.</strong> Cell Press.</li><br />
</ol><br />
<ol><br />
<li>Blinov ML, Faeder JR, Goldstein B, Hlavacek WS. (2004) <strong>BioNetGen: software for rule-based modeling of signal transduction based on the interactions of molecular domains. </strong>Bioinformatics. </li><br />
</ol><br />
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</html></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/Acknowledgments.htmTeam/CINVESTAV-IPN-UNAM MX/Acknowledgments.htm2012-09-27T04:04:14Z<p>LoboLofi: </p>
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<p><strong>We thank all the people who help us in all and every panic </strong></p><br />
<p><strong>moment that we have</strong>, lol : )</p><br />
<p><br /><br />
<strong>Juan Carlos Martinez-Garcia PhD</strong><br /><br />
For his support in mathematical modeling<br /><br />
<strong>Ing. Susana Ruiz</strong><br /><br />
For his support in Molecular Biology Techniques<br /><br />
<strong>Ana Lilia Hernández</strong><br /><br />
For his support in Molecular Biology Techniques<br /><br />
<strong>QFB. Norma Silvia Sánchez-Sánchez</strong><br /><br />
For her advices and support to the team.<br /><br />
<strong>Dr. Heliodoro Celis Sandoval</strong><br /><br />
For allow us to work in his lab at iFC, UNAM<strong>.</strong><br /><br />
<strong>Dra. Karen Nava Castro</strong><br /><br />
For her advices and help in Flow Citometry.<br /><br />
<strong>Dr. Jorge Morales Montor</strong><br /><br />
For his support in the project and allow us to work in his lab<strong>.</strong><br /><br />
<br />
<p><strong>Msc Libertad Pantoja Hernández</strong></p><br />
<p><strong>Javier</strong><br /><br />
<strong>Vero</strong><br /><br />
<strong>Angi</strong><br /><br />
<strong>Hector Silva-Gutierrez</strong><br /><br />
<strong>Cesar Villavicencio-Cordova</strong><br /><br />
<strong>Eduardo Moreno Rodríguez</strong><br /><br />
<strong>Manuel Camacho Zaragoza</strong> </p><br />
<p><strong>Wiki Design </strong></p><br />
<p><strong>Alejandro Peréz Cruz</strong><br /><br />
<strong>María Luisa Sáenz Jaramillo</strong></p><br />
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<p><strong>Headquarters</strong><strong> </strong></p><br />
<p><strong>Systems and Synthetic Biology Lab </strong></p><br />
<p><br /><br />
During the summer we worked with our lead instructor, Agustino Martínez-Antonio PhD in the Systems and Synthetic Biology Lab in the installations of the Center for Research and Advanced Studies at Irapuato (Cinvestav) located in Guanajuato Mexico (4 hours distance to Mexico City). </p><br />
<p><img src="https://static.igem.org/mediawiki/2012/c/cf/Headquarters.jpg" width="349" height="141" /><br /><br />
<a href="http://bioingenios.ira.cinvestav.mx:81/" target="_blank">BioINGENios</a>&nbsp;is a group of work at&nbsp;Cinvestav Irapuato&nbsp;whose primary mission is to contribute to the advance of basic research and their applications, we also&nbsp;continuously&nbsp;are training future researchers with these aims in their minds.<br /><br />
This vocation is powered by a team who study operative principles and mechanisms that drive the function of single-cell organisms and uses this knowledge and their ingenious creativity to bioengineer new genetic circuits and cellular prototypes with improved/desired properties and the construction of new biological modules and biosystems.</p><br />
<p><br /><br />
<strong>After and before the summer we worked in 3 different labs: </strong></p><br />
<p><br /><br />
Conservation Medicine Lab at Superior School for Medicine (IPN) with our instructor Paola Zárate-Segura PhD<br /><br />
Photosynthetic bacteria lab at Cell Phisiology Institute (UNAM) with our instructor Fernando Suaste-Olmos<br /><br />
Protein Engineering Lab at Chemistry Institute (UNAM). with our instructor Nuria Sánchez-Puig</p><br />
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<p><strong>We thank all the people who help us in all and every panic </strong></p><br />
<p><strong>moment that we have</strong>, lol : )</p><br />
<p><br /><br />
<strong>Juan Carlos Martinez-Garcia PhD</strong><br /><br />
For his support in mathematical modeling<br /><br />
<strong>Ing. Susana Ruiz</strong><br /><br />
For his support in Molecular Biology Techniques<br /><br />
<strong>Ana Lilia Hernández</strong><br /><br />
For his support in Molecular Biology Techniques<br /><br />
<strong>QFB. Norma Silvia Sánchez-Sánchez</strong><br /><br />
For her advices and support to the team.<br /><br />
<strong>Dr. Heliodoro Celis Sandoval</strong><br /><br />
For allow us to work in his lab at iFC, UNAM<strong>.</strong><br /><br />
<strong>Dra. Karen Nava Castro</strong><br /><br />
For her advices and help in Flow Citometry.<br /><br />
<strong>Dr. Jorge Morales Montor</strong><br /><br />
For his support in the project and allow us to work in his lab<strong>.</strong><br /><br />
<br />
<p><strong>Msc Libertad Pantoja Hernández</strong></p><br />
<p><strong>Javier</strong><br /><br />
<strong>Vero</strong><br /><br />
<strong>Angi</strong><br /><br />
<strong>Hector Silva-Gutierrez</strong><br /><br />
<strong>Cesar Villavicencio-Cordova</strong><br /><br />
<strong>Eduardo Moreno Rodríguez</strong><br /><br />
<strong>Manuel Camacho Zaragoza</strong> </p><br />
<p><strong>Wiki Design </strong></p><br />
<p><strong>Alejandro Peréz Cruz</strong><br /><br />
<strong>María Luisa Sáenz Jaramillo</strong></p><br />
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<br />
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<div id="bodys_r1_c2"><br />
</div><br />
<div id="bodys_r1_c3"><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/0/01/Modelling.fw.png" width="640" height="109" /> </div><br />
<div class="clearFloat"></div><br />
<div id="bodys_r2_c2"></div><br />
<div id="bodys_r2_c3"><br />
<div class="Text"><br />
<p>To get an overview of the regulatory system that governs the PS (Photosynthetic) gene expression, we developed a rule-based model; with this our goal was to comprehend how these proteins work in our system as a whole.</p><br />
<br />
<p>We focused on three main proteins AppA, PpsR, and TspO but we also include Qpool,cbb3 cytochrome c oxidase , PrrC a membrane-localized polypeptide and the two-component signal transduction system that induces PS gene expression in response to a decrease in oxygen tension; PrrBA.</p><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/0/06/ProteinsInteraction.jpg" /><br />
<h2>Our simulation results</h2> <br />
<br />
<p><strong> Total protein concentration. Low oxygen and high blue light</strong></p><br />
<img src="https://static.igem.org/mediawiki/2012/7/73/BioNetGenALLProducts.PNG" width="500" height="168" /><br/><br />
<p><strong> Total protein concentration. High oxygen levels and low blue light</strong></p><br />
<img src="https://static.igem.org/mediawiki/2012/2/24/4proteinsMuchoOxigenoPocaLuz.PNG" width="500" height="168" /><br/><br />
<br />
<p> <strong>Total concentration PpsR, AppA, TspO and PrrA, Low oxygen and high blue light</strong></p><br />
<img src="https://static.igem.org/mediawiki/2012/5/54/4proteinsPocoOxigenoMuchaLuz.PNG" width="500" height="168" /><br/><br />
<p> <strong>Total concentration PpsR, AppA, TspO and PrrA, High oxygen levels and low blue light</strong></p><br />
<img src="https://static.igem.org/mediawiki/2012/3/30/PocaLuzMuchoOxigeno.PNG" width="500" height="168" /><br/><br />
</div><br />
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</html></div>LoboLofihttp://2012.igem.org/File:PocaLuzMuchoOxigeno.PNGFile:PocaLuzMuchoOxigeno.PNG2012-09-27T03:47:52Z<p>LoboLofi: </p>
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<div></div>LoboLofihttp://2012.igem.org/File:4proteinsPocoOxigenoMuchaLuz.PNGFile:4proteinsPocoOxigenoMuchaLuz.PNG2012-09-27T03:47:24Z<p>LoboLofi: </p>
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<div></div>LoboLofihttp://2012.igem.org/File:4proteinsMuchoOxigenoPocaLuz.PNGFile:4proteinsMuchoOxigenoPocaLuz.PNG2012-09-27T03:46:38Z<p>LoboLofi: </p>
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<div></div>LoboLofihttp://2012.igem.org/File:BioNetGenALLProducts.PNGFile:BioNetGenALLProducts.PNG2012-09-27T03:38:30Z<p>LoboLofi: uploaded a new version of &quot;File:BioNetGenALLProducts.PNG&quot;</p>
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<div></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/intercellular.htmTeam/CINVESTAV-IPN-UNAM MX/intercellular.htm2012-09-27T03:37:59Z<p>LoboLofi: Created page with "<html xmlns="http://www.w3.org/1999/xhtml"><head> <title>Home</title> <link rel="stylesheet" href="https://dl.dropbox.com/u/199422/Cinvestav/style.css" /> <meta http-equiv="Co..."</p>
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<p>To get an overview of the regulatory system that governs the PS (Photosynthetic) gene expression, we developed a rule-based model; with this our goal was to comprehend how these proteins work in our system as a whole.</p><br />
<br />
<p>We focused on three main proteins AppA, PpsR, and TspO but we also include Qpool,cbb3 cytochrome c oxidase , PrrC a membrane-localized polypeptide and the two-component signal transduction system that induces PS gene expression in response to a decrease in oxygen tension; PrrBA.</p><br />
<br />
<img src="https://static.igem.org/mediawiki/2012/0/06/ProteinsInteraction.jpg" /><br />
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</html></div>LoboLofihttp://2012.igem.org/File:ProteinsInteraction.jpgFile:ProteinsInteraction.jpg2012-09-27T03:37:14Z<p>LoboLofi: </p>
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<div></div>LoboLofihttp://2012.igem.org/File:BioNetGenALLProducts.PNGFile:BioNetGenALLProducts.PNG2012-09-27T03:28:18Z<p>LoboLofi: </p>
<hr />
<div></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/Human_Practice.htmTeam/CINVESTAV-IPN-UNAM MX/Human Practice.htm2012-09-27T02:28:31Z<p>LoboLofi: </p>
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<p>Sometimes is hard for scientist to get involved in Human Practices, we think is important to solve all those economical, ethical, legal and social issues in order to change the public perception of synthetic biology, We have worked in many activities for human practices<br /><br />
</p><br />
<p><strong><a href="https://2012.igem.org/wiki/index.php?title=Team/CINVESTAV-IPN-UNAM_MX/Meet.htm">Collaboration: iGEMMX Meet up!</a></strong><br /><br />
Twelve Mexican teams have participated in iGEM since 2007, they have had very successful participations, but they have never had an efficient communication. If we are connected, we can make things better. If we want to be competitive as a country in synthetic biology development, we have to collaborate. So, with the objective of improve our connections, improve our projects and establish collaboration agreements, we decided to organize the First iGEM MeetUP in our headquarters in Irapuato.<br /><br />
</p><br />
<p><strong>Education: SynBio Summer Workshop</strong></p><br />
<p><br /><br />
Every year, the leader of Systems and Synthetic Biology Group, and our main instructor, Agustino Martinez-Antonio organizes a Synthetic Biology Summer Workshop at the Center for Research and Advanced Studies (CINVESTAV), where undergrad students from all the country take part in the creation, design and development of new synbio projects during the summer. Some members of our team guided the new students in this workshop.<br /><br />
</p><br />
<p><a href="https://static.igem.org/mediawiki/2012/1/1a/Education_SynBio_Summer_Workshop.pdf" target="_blank"><strong>Read more…</strong></a><br /><br />
</p><br />
<p>&nbsp;</p><br />
<p><strong>Ownership: Intellectual Property vs. Open Source</strong><br /><br />
We know that Open source is the strategy to reach a global development in Synthetic Biology, but there´re many questions to answer in this topic. First, we have to decide a strategy to establish a strong Intellectual Property Platform. We asked many experts in IP in Mexico some of these questions<br /><br />
</p><br />
<p><strong><a href="https://static.igem.org/mediawiki/2012/3/36/Intellectual_Property_report.pdf" target="_blank">Read more…</a></strong></p><br />
<p>&nbsp;</p><br />
<p><strong>Sharing: iGEM Experience</strong><br /><br />
Maybe the most difficult part in making a new iGEM team is getting started, how do you get the right idea? How do you design the project? How do you work in teams? How do you get money? etc, . Since this is our first iGEM participation, we have had some little troubles that every team can face. We asked for opinions to answer all these questions in a document that can tell future iGEM teams what they should do in order to have success in the iGEM experience.<br /><br />
</p><br />
<p><strong><a href="https://static.igem.org/mediawiki/2012/e/e4/IGEM_Experience.pdf">Read more…</a></strong></p><br />
<p>&nbsp;</p><br />
<p><br /><br />
<strong>Biosafety…</strong><br /><br />
<a href="https://static.igem.org/mediawiki/2012/6/63/Cartel_BN.pdf" target="_blank"><strong>Poster</strong></a></p><br />
<p><strong>&nbsp;</strong></p><br />
<p><strong>Gaceta UNAM!</strong></p><br />
<p><strong><a href="http://www.quimica.unam.mx/IMG/pdf/flogisto81.pdf" target="_blank">Link1</a></strong></p><br />
<p><strong> <a href="http://www.quimica.unam.mx/IMG/pdf/gacetaseptiembre.pdf" target="_blank">Link 2</a></strong></p><br />
<p align="center">&nbsp;</p><br />
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</html></div>LoboLofihttp://2012.igem.org/File:Cartel_BN.pdfFile:Cartel BN.pdf2012-09-27T02:27:29Z<p>LoboLofi: </p>
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<div></div>LoboLofihttp://2012.igem.org/File:IGEM_Experience.pdfFile:IGEM Experience.pdf2012-09-27T02:25:55Z<p>LoboLofi: </p>
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<div></div>LoboLofihttp://2012.igem.org/File:Intellectual_Property_report.pdfFile:Intellectual Property report.pdf2012-09-27T02:24:18Z<p>LoboLofi: </p>
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<img src="https://static.igem.org/mediawiki/2012/9/99/Interaction_between_AppA_and_PpsR.png" alt="Interaccion between AppA and PpsR with light and oxigen" ><br />
<strong style="font-size: 0.875em;">FIGURE 1. Interaction between AppA and PpsR as a function of the oxygen concentration [O2] and blue-light irradiance LI . The tetramers with intramolecular disul?de bonds (S-S) and thiol groups (SH) denote the oxidized and the reduced form of the PpsR repressor, respectively. The AppA protein has an FAD and a heme cofactor attached where h+ and hפenote the oxidized and reduced form of the heme cofactor, respectively. Both the oxidized and the reduced form of PpsR act as a repressor of photosynthesis genes, but with different strengths as indicated by the line thickness. Pandey, 2011.</strong><br />
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<p> The proteins in our regulatory system constitute a network of intermingling elements whose behavior can be narrow into basic interaction rules. Primarily in this part of the modeling we focused on the PpsR and AppA anti-repressor/repressor system and chose to model it using a system of ordinary differential equations. The systemӳ repressive activity varies with the redox (O2) state of the cell and Light intensity and thus we wondered how exactly these two variables affect the overall repressive level of PpsR over the expression of PS genes.</p><br />
</div><br />
<p>This is the code written for the regulatory system Appa-PpsR in Mathematica.</p><br />
<img src="https://static.igem.org/mediawiki/2012/2/26/MathemathcaCodeICIPNUNAMMX.png" alt="Code of Differential Equations in mathematica"><br />
<div id="TexBox2" style=" background-color:Crimson;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px; color:#FFF"><br />
<p>To do this we based ourselves on a previous work that had attempted to study this same regulatory system. <strong style="color:#000">[Pandey, Rakesh Flockerzi, Dietrich Hauser, Marcus JB Straube, Ronny. 2011. Modeling the light- and redox-dependent interaction of PpsR/AppA in Rhodobacter sphaeroides.]</strong> In addition to contacting the responsible authors and discussing this model, we chose to improve it based on recent publications and preliminary experimental results i.e. we introduced a more subtle way light and oxygen affects the protein concentration dynamic, which is exactly what we were interested in understanding better.</p><br />
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<strong>Results generated with the model:</strong><br />
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<td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/e/ed/Graph_Oxigen_and_Light_1.jpg" alt="Graph number 1" /></td> <td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/a/a8/Graph_Oxigen_and_Light_2.jpg" alt="Graph number 2"/></td><br />
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<td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/6/63/Graph_Oxigen_and_Light_3.jpg" alt="Graph number 3"/></td> <td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/2/20/Graph_Oxigen_and_Light_4.jpg" alt="Graph number 2"/></td><br />
<tr><br />
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<br/><br />
<strong style="font-size: 0.875em;">Figure1. Steady state behavior of reduced PpsR (P4+), oxidized PpsR (P4-) and the AppA-PpsR complex as a function of oxygen concentration and light irradiance.</strong><br />
<br/><br />
<p style="color:green;"><br />
With our differential equations system we calculated protein concentrations at stable steady states and assumed this to be a natural "resting", or homeostatic, state given a set of parameters, oxygen and light intensities. As such, this gave us a steady state total repressive force, in essence, as a function of oxygen tension and light intensity. This is because PpsR-AppAӳ total repressive strength is a function of the concentrations of both its oxidative and reduced state.<br />
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<div id="TexBox3" style=" background-color:RoyalBlue;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px; color:#FFF"><br />
<p>Because all this was done in Mathematica, we were able to generate an interactive graphical representation of the repressive strength over a range of conditions. This is really the strength of our work because with this model, we can make predictions in sillico as to how the organism will react to a given environmental surrounding and then go back to the lab and validate that prediction.</p><br />
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<p><br />
<strong>Also, since we have the power to manipulate the values of the parameters in an easy and intuitive way, we can explore the parameter space and visually observe the change in the concentration curves, which can be of interest to, not only us, but other people that might not be interested in all the math behind interphase. This parameter tweaking allows us to compare experimental data against sillico predictions; the only difference is that if we focus on the parameters, this can actually give us hints respect to the still-blurred nature of Protein-Protein and Protein-Environment mechanisms that exist in this extremely versatile cell.</strong><br />
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Importance of Modeling and Simulation<br />
</strong><br />
<p>&nbsp;</p><br />
<p>Characterization of biological systems has reached an unparalleled level of detail. To organize this detail and arrive at a better fundamental understanding of life processes, it is essential that powerful conceptual tools from mathematics and computer science be applied to the frontier problems in biology. </p><br />
<p><br /><br />
Modeling of biological systems is evolving into an important partner of experimental work. They attempt to predict and understand the behavior of complex biological systems before they are actually created. Also models can help to simplify the complexity of data and interactions involved into a more concise form with some measure of predictive ability. This can provide valuable insights into the working and general principles of organization of biological systems. Also it may suggest novel experiments for testing hypotheses, based on the modeling experiences.</p><br />
<p><a href="Tools.htm"><strong>Some of the tools that we used during the modeling process.</strong></a></p><br />
<p><strong><a href="Model.htm">Construction of Model</a></strong></p><br />
<p><strong><a href="intercellular.htm">Modeling the intercellular signaling process during regulation of PS genes expression in BioNetGEn.</a></strong></p><br />
<p><strong><a href="equations.htm">Differential equations modeling the interactions between AppA and PpsR. </a></strong><a href="equations.htm"><br /><br />
<strong>Modeling Steady State</strong></a><strong></strong></p><br />
<p><a href="automata.htm"><strong>Cellular automata approaches to biological modeling.</strong></a></p><br />
<p><strong>References used through this section.</strong></p><br />
<ol><br />
<li>Oh JI, Kaplan S. (2001) <strong>Generalized approach to the regulation and integration of gene expression. </strong>Mol Microbiol. </li><br />
</ol><br />
<ol><br />
<li>Zeilstra-Ryalls JH, Kaplan S. (1995) <strong>Aerobic and anaerobic regulation in Rhodobacter sphaeroides</strong> 2.4.1: the role of the fnrL gene. J Bacteriol. </li><br />
</ol><br />
<p>&nbsp;</p><br />
<ol><br />
<li>Rakesh Pandey, Dietrich Flockerz. (2011) <strong>Modeling the Light- and Redox-Dependent Interaction of PpsR/AppA in Rhodobacter sphaeroides. </strong>Cell Press.</li><br />
</ol><br />
<ol><br />
<li>Shinji Masuda&nbsp;and&nbsp;Carl E. Bauer. (2002) <strong>AppA Is a Blue Light Photoreceptor that Antirepresses Photosynthesis Gene Expression in Rhodobacter sphaeroides.</strong> Cell Press.</li><br />
</ol><br />
<ol><br />
<li>Blinov ML, Faeder JR, Goldstein B, Hlavacek WS. (2004) <strong>BioNetGen: software for rule-based modeling of signal transduction based on the interactions of molecular domains. </strong>Bioinformatics. </li><br />
</ol><br />
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<p><img src="https://dl.dropbox.com/u/199422/Cinvestav/images/meet.jpg" width="640" height="441" /></p><br />
<p align="center">We thank to the members who attended to this event and represented their teams:</p><br />
<p>&nbsp;</p><br />
<p>We organized the First iGEM Meet up between Mexican teams, and it took place on August 10th, 2012, in CINVESTAV Irapuato, Mexico.</p><br />
<p>&nbsp;</p><br />
<p>The purpose of this event was to start a collaboration network between Mexican iGEM teams, with the goals of increase the potential of Synthetic Biology in our country, share knowledge and obtain help from experts and other students. </p><br />
<p>&nbsp;</p><br />
<p>In this meetup, we invited participants from Collegiate, High School and Entrepreneurship Divisions. Each team was represented by some of its members, and they were encouraged to make an oral presentation about their iGEM projects. During this event, all the teams received comments and suggestions from other iGEM students and researches from CINVESTAV Irapuato.</p><br />
<p>&nbsp;</p><br />
<p>Furthermore, this was a successful day because we created agreements between Mexican iGEM teams, some of them are the start of a Collaboration Network in Mexican iGEM teams; the ideas to solve problems, such as the importation of iGEM distributions; to share the experience of using some Biobricks and the creation of tutorial videos to homogenize the protocols and techniques in Synthetic Biology.</p><br />
<p align="center"><img src="https://dl.dropbox.com/u/199422/Cinvestav/images/poster.png" width="441" height="625" /></p><br />
<p align="center"><iframe width="560" height="315" src="http://www.youtube.com/embed/D3Xb4vuy8Ko" frameborder="0" allowfullscreen></iframe></p><br />
<p align="center">We thank to the members who attended to this event and represented their teams:</p><br />
<p align="center"><img src="https://dl.dropbox.com/u/199422/Cinvestav/images/tn.jpg" width="548" height="211" /></p><br />
<p>&nbsp;</p><br />
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</html></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/Human_Practice.htmTeam/CINVESTAV-IPN-UNAM MX/Human Practice.htm2012-09-27T02:18:02Z<p>LoboLofi: </p>
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<p>Sometimes is hard for scientist to get involved in Human Practices, we think is important to solve all those economical, ethical, legal and social issues in order to change the public perception of synthetic biology, We have worked in many activities for human practices<br /><br />
</p><br />
<p><strong><a href="https://2012.igem.org/wiki/index.php?title=Team/CINVESTAV-IPN-UNAM_MX/Meet.htm">Collaboration: iGEMMX Meet up!</a></strong><br /><br />
Twelve Mexican teams have participated in iGEM since 2007, they have had very successful participations, but they have never had an efficient communication. If we are connected, we can make things better. If we want to be competitive as a country in synthetic biology development, we have to collaborate. So, with the objective of improve our connections, improve our projects and establish collaboration agreements, we decided to organize the First iGEM MeetUP in our headquarters in Irapuato.<br /><br />
</p><br />
<p><strong>Education: SynBio Summer Workshop</strong></p><br />
<p><br /><br />
Every year, the leader of Systems and Synthetic Biology Group, and our main instructor, Agustino Martinez-Antonio organizes a Synthetic Biology Summer Workshop at the Center for Research and Advanced Studies (CINVESTAV), where undergrad students from all the country take part in the creation, design and development of new synbio projects during the summer. Some members of our team guided the new students in this workshop.<br /><br />
</p><br />
<p><a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/Education%20SynBio%20Summer%20Workshop.pdf" target="_blank"><strong>Read more…</strong></a><br /><br />
</p><br />
<p>&nbsp;</p><br />
<p><strong>Ownership: Intellectual Property vs. Open Source</strong><br /><br />
We know that Open source is the strategy to reach a global development in Synthetic Biology, but there´re many questions to answer in this topic. First, we have to decide a strategy to establish a strong Intellectual Property Platform. We asked many experts in IP in Mexico some of these questions<br /><br />
</p><br />
<p><strong><a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/Intellectual%20Property%20report.pdf" target="_blank">Read more…</a></strong></p><br />
<p>&nbsp;</p><br />
<p><strong>Sharing: iGEM Experience</strong><br /><br />
Maybe the most difficult part in making a new iGEM team is getting started, how do you get the right idea? How do you design the project? How do you work in teams? How do you get money? etc, . Since this is our first iGEM participation, we have had some little troubles that every team can face. We asked for opinions to answer all these questions in a document that can tell future iGEM teams what they should do in order to have success in the iGEM experience.<br /><br />
</p><br />
<p><strong><a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/iGEM%20Experience.pdf">Read more…</a></strong></p><br />
<p>&nbsp;</p><br />
<p><br /><br />
<strong>Biosafety…</strong><br /><br />
<a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/Cartel%20BN.pdf" target="_blank"><strong>Poster</strong></a></p><br />
<p><strong>&nbsp;</strong></p><br />
<p><strong>Gaceta UNAM!</strong></p><br />
<p><strong><a href="http://www.quimica.unam.mx/IMG/pdf/flogisto81.pdf" target="_blank">Link1</a></strong></p><br />
<p><strong> <a href="http://www.quimica.unam.mx/IMG/pdf/gacetaseptiembre.pdf" target="_blank">Link 2</a></strong></p><br />
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</html></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/Safety.htmTeam/CINVESTAV-IPN-UNAM MX/Safety.htm2012-09-27T02:16:58Z<p>LoboLofi: </p>
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<p>&nbsp;</p><br />
<p><strong>Question 1</strong>:<strong>'''Would any of your project ideas raise safety issues in terms of researcher, public or enviromental safety?'''</strong> </p><br />
<p><br /><br />
Purple Non sulfur Bacteria are one of the most metabolically diverse groups known in nature, they are able to grow under different conditions such as, aerobic respiration, anoxigenic photosynthesis, and anaerobic fermentation. Due to its diverse metabolism and their ability to eat aromatic compounds, these bacteria can live in hostile media such as polluted water. Despite all these features, work with these microorganisms in lab conditions is very laborious; especially since its growth medium is a complex mix of metals and vitamins.<br /><br />
The risk in PNSB management in the lab is very low since they are non-pathogenic bacteria. R. sphaeroides and R. palustris´ grow rates are quite slow, thus, our genetic systems do not represent a public safety menace since they are highly specific. Besides, we have designed these systems for its specific functioning in purple photosynthetic bacteria. Nevertheless, it is very important to take special care during our wetlab work, taking into account the basic precautions and methods commonly used in microbiology.<br /><br />
Our project aims to build two regulation systems, and introduce them into Rhodopseudomonas palustris. Since PCR isolation of the five genes that form the system is extremely difficult, gene synthesis technology provided by Genescript was used instead for the obtainment of these BioBricks. All our biobricks </p><br />
<p><br /><br />
<strong>Question 2</strong>: <strong>'''Do any of the new BioBrick parts (or devices) that you made this year raise any safety issues?'''</strong></p><br />
<p><br /><br />
No, our BioBricks parts came from Rhodobacter sphaeroides, this bacteria is non-pathogenic and it can be worked in a Biosafety level 1 laboratory, based on the CDC Biosafety in Microbiological and Biomedical Laboratories (CDC, 2007). The functionality of our parts do not produce any dangerous compound, we are working in gene expression control. Furthermore, we used BioBricks from iGEM distribution for all our assemblies, for example GFP as reporter, these parts do not represent a biological risk.</p><br />
<p><br /><br />
<strong>Question 3</strong>: <strong>'''Is there a local biosafety group, committee, or review board at your institution? If no, which specific biosafety rules or guidelines do you have to consider in your country?'''</strong></p><br />
<p><br /><br />
No, a Biosafety committee must be integrated, by a multidisciplinary group of members among Research Centers, Industries and Universities. This committee should provide expert advice on laboratory, biosafety and biosecurity issues related to research and other academic activities. <br /><br />
The objectives of this group should be:</p><br />
<ul><br />
<li>Plan, design and implement the necessary instruments for biosafety risk assessment. </li><br />
<li>Establish, disseminate and analyze safety approaches in handling chemicals, genetically modified organisms and potentially infectious pathogens that allow us to make decisions for users in order to minimize potential health risks.</li><br />
<li>Conduct briefings and feedback sessions with the actors involved in biosafety.</li><br />
<li>Propound consistent Biosecurity regulations, which allow the development and promotion of basic and applied research. </li><br />
</ul><br />
<p>Particular problems should be evaluated case by case for the analysis of their solutions , this analysis should also include assessment of the risks of alternative technological options for coping with the specific problem to which the GMO was designed. And finally, it is important to review other laws; this will help to strengthen biosecurity aspects of other organisms that are not GMOs.</p><br />
<p>In Mexico CIBIOGEM, which is a governmental organism, was created to regulate biosafety issues mainly related with transgenic organisms and GMOs. The mentioned committee should work along this institution in order to establish a synthetic biology approach to biosafety.</p><br />
<p><strong>Question 4</strong>: <strong>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?</strong></p><br />
<p><br /><br />
As a part of our human practices work, we are trying to implement the Quality Function Deployment tool in order to answer the most important questions in terms of safety and biosecurity. The relevance of this work is that through a thorough analysis of the proposed goals and needs of our work, we are going to be able to make different proposals that support the development of synthetic biology-based projects in Mexico</p><br />
<p align="center">&nbsp;</p><br />
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</html></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/Meet.htmTeam/CINVESTAV-IPN-UNAM MX/Meet.htm2012-09-27T02:14:11Z<p>LoboLofi: Created page with "<html xmlns="http://www.w3.org/1999/xhtml"><head> <title>Home</title> <link rel="stylesheet" href="https://dl.dropbox.com/u/199422/Cinvestav/style.css" /> <meta http-equiv="C..."</p>
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<p align="center">We thank to the members who attended to this event and represented their teams:</p><br />
<p>&nbsp;</p><br />
<p>We organized the First iGEM Meet up between Mexican teams, and it took place on August 10th, 2012, in CINVESTAV Irapuato, Mexico.</p><br />
<p>&nbsp;</p><br />
<p>The purpose of this event was to start a collaboration network between Mexican iGEM teams, with the goals of increase the potential of Synthetic Biology in our country, share knowledge and obtain help from experts and other students. </p><br />
<p>&nbsp;</p><br />
<p>In this meetup, we invited participants from Collegiate, High School and Entrepreneurship Divisions. Each team was represented by some of its members, and they were encouraged to make an oral presentation about their iGEM projects. During this event, all the teams received comments and suggestions from other iGEM students and researches from CINVESTAV Irapuato.</p><br />
<p>&nbsp;</p><br />
<p>Furthermore, this was a successful day because we created agreements between Mexican iGEM teams, some of them are the start of a Collaboration Network in Mexican iGEM teams; the ideas to solve problems, such as the importation of iGEM distributions; to share the experience of using some Biobricks and the creation of tutorial videos to homogenize the protocols and techniques in Synthetic Biology.</p><br />
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<p align="center"><iframe width="560" height="315" src="http://www.youtube.com/embed/D3Xb4vuy8Ko" frameborder="0" allowfullscreen></iframe></p><br />
<p align="center">We thank to the members who attended to this event and represented their teams:</p><br />
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</html></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/Safety.htmTeam/CINVESTAV-IPN-UNAM MX/Safety.htm2012-09-27T02:10:07Z<p>LoboLofi: Created page with "<html xmlns="http://www.w3.org/1999/xhtml"><head> <title>Home</title> <link rel="stylesheet" href="https://dl.dropbox.com/u/199422/Cinvestav/style.css" /> <meta http-equiv="C..."</p>
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<br />
<p>&nbsp;</p><br />
<p><strong>Question 1</strong>:<strong>'''Would any of your project ideas raise safety issues in terms of researcher, public or enviromental safety?'''</strong> </p><br />
<p><br /><br />
Purple Non sulfur Bacteria are one of the most metabolically diverse groups known in nature, they are able to grow under different conditions such as, aerobic respiration, anoxigenic photosynthesis, and anaerobic fermentation. Due to its diverse metabolism and their ability to eat aromatic compounds, these bacteria can live in hostile media such as polluted water. Despite all these features, work with these microorganisms in lab conditions is very laborious; especially since its growth medium is a complex mix of metals and vitamins.<br /><br />
The risk in PNSB management in the lab is very low since they are non-pathogenic bacteria. R. sphaeroides and R. palustris´ grow rates are quite slow, thus, our genetic systems do not represent a public safety menace since they are highly specific. Besides, we have designed these systems for its specific functioning in purple photosynthetic bacteria. Nevertheless, it is very important to take special care during our wetlab work, taking into account the basic precautions and methods commonly used in microbiology.<br /><br />
Our project aims to build two regulation systems, and introduce them into Rhodopseudomonas palustris. Since PCR isolation of the five genes that form the system is extremely difficult, gene synthesis technology provided by Genescript was used instead for the obtainment of these BioBricks. All our biobricks </p><br />
<p><br /><br />
<strong>Question 2</strong>: <strong>'''Do any of the new BioBrick parts (or devices) that you made this year raise any safety issues?'''</strong></p><br />
<p><br /><br />
No, our BioBricks parts came from Rhodobacter sphaeroides, this bacteria is non-pathogenic and it can be worked in a Biosafety level 1 laboratory, based on the CDC Biosafety in Microbiological and Biomedical Laboratories (CDC, 2007). The functionality of our parts do not produce any dangerous compound, we are working in gene expression control. Furthermore, we used BioBricks from iGEM distribution for all our assemblies, for example GFP as reporter, these parts do not represent a biological risk.</p><br />
<p><br /><br />
<strong>Question 3</strong>: <strong>'''Is there a local biosafety group, committee, or review board at your institution? If no, which specific biosafety rules or guidelines do you have to consider in your country?'''</strong></p><br />
<p><br /><br />
No, a Biosafety committee must be integrated, by a multidisciplinary group of members among Research Centers, Industries and Universities. This committee should provide expert advice on laboratory, biosafety and biosecurity issues related to research and other academic activities. <br /><br />
The objectives of this group should be:</p><br />
<ul><br />
<li>Plan, design and implement the necessary instruments for biosafety risk assessment. </li><br />
<li>Establish, disseminate and analyze safety approaches in handling chemicals, genetically modified organisms and potentially infectious pathogens that allow us to make decisions for users in order to minimize potential health risks.</li><br />
<li>Conduct briefings and feedback sessions with the actors involved in biosafety.</li><br />
<li>Propound consistent Biosecurity regulations, which allow the development and promotion of basic and applied research. </li><br />
</ul><br />
<p>Particular problems should be evaluated case by case for the analysis of their solutions , this analysis should also include assessment of the risks of alternative technological options for coping with the specific problem to which the GMO was designed. And finally, it is important to review other laws; this will help to strengthen biosecurity aspects of other organisms that are not GMOs.</p><br />
<p>In Mexico CIBIOGEM, which is a governmental organism, was created to regulate biosafety issues mainly related with transgenic organisms and GMOs. The mentioned committee should work along this institution in order to establish a synthetic biology approach to biosafety.</p><br />
<p><strong>Question 4</strong>: <strong>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?</strong></p><br />
<p><br /><br />
As a part of our human practices work, we are trying to implement the Quality Function Deployment tool in order to answer the most important questions in terms of safety and biosecurity. The relevance of this work is that through a thorough analysis of the proposed goals and needs of our work, we are going to be able to make different proposals that support the development of synthetic biology-based projects in Mexico</p><br />
<p align="center">&nbsp;</p><br />
</div><br />
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</html></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/Human_Practice.htmTeam/CINVESTAV-IPN-UNAM MX/Human Practice.htm2012-09-27T02:05:28Z<p>LoboLofi: Created page with "<html xmlns="http://www.w3.org/1999/xhtml"><head> <title>Home</title> <link rel="stylesheet" href="https://dl.dropbox.com/u/199422/Cinvestav/style.css" /> <meta http-equiv="C..."</p>
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<p>Sometimes is hard for scientist to get involved in Human Practices, we think is important to solve all those economical, ethical, legal and social issues in order to change the public perception of synthetic biology, We have worked in many activities for human practices<br /><br />
</p><br />
<p><strong><a href="https://2012.igem.org/wiki/index.php?title=Team/CINVESTAV-IPN-UNAM_MX/Meet.htm">Collaboration: iGEMMX Meet up!</a></strong><br /><br />
Twelve Mexican teams have participated in iGEM since 2007, they have had very successful participations, but they have never had an efficient communication. If we are connected, we can make things better. If we want to be competitive as a country in synthetic biology development, we have to collaborate. So, with the objective of improve our connections, improve our projects and establish collaboration agreements, we decided to organize the First iGEM MeetUP in our headquarters in Irapuato.<br /><br />
</p><br />
<p><strong>Education: SynBio Summer Workshop</strong></p><br />
<p><br /><br />
Every year, the leader of Systems and Synthetic Biology Group, and our main instructor, Agustino Martinez-Antonio organizes a Synthetic Biology Summer Workshop at the Center for Research and Advanced Studies (CINVESTAV), where undergrad students from all the country take part in the creation, design and development of new synbio projects during the summer. Some members of our team guided the new students in this workshop.<br /><br />
</p><br />
<p><a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/Education%20SynBio%20Summer%20Workshop.pdf" target="_blank"><strong>Read more…</strong></a><br /><br />
</p><br />
<p>&nbsp;</p><br />
<p><strong>Ownership: Intellectual Property vs. Open Source</strong><br /><br />
We know that Open source is the strategy to reach a global development in Synthetic Biology, but there´re many questions to answer in this topic. First, we have to decide a strategy to establish a strong Intellectual Property Platform. We asked many experts in IP in Mexico some of these questions<br /><br />
</p><br />
<p><strong><a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/Intellectual%20Property%20report.pdf" target="_blank">Read more…</a></strong></p><br />
<p>&nbsp;</p><br />
<p><strong>Sharing: iGEM Experience</strong><br /><br />
Maybe the most difficult part in making a new iGEM team is getting started, how do you get the right idea? How do you design the project? How do you work in teams? How do you get money? etc, . Since this is our first iGEM participation, we have had some little troubles that every team can face. We asked for opinions to answer all these questions in a document that can tell future iGEM teams what they should do in order to have success in the iGEM experience.<br /><br />
</p><br />
<p><strong><a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/iGEM%20Experience.pdf">Read more…</a></strong></p><br />
<p>&nbsp;</p><br />
<p><br /><br />
<strong>Biosafety…</strong><br /><br />
<a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/Cartel%20BN.pdf" target="_blank"><strong>Poster</strong></a></p><br />
<p><strong>&nbsp;</strong></p><br />
<p><strong>Gaceta UNAM!</strong></p><br />
<p><strong><a href="http://www.quimica.unam.mx/IMG/pdf/flogisto81.pdf" target="_blank">Link1</a></strong></p><br />
<p><strong> <a href="http://www.quimica.unam.mx/IMG/pdf/gacetaseptiembre.pdf" target="_blank">Link 2</a></strong></p><br />
<p align="center">&nbsp;</p><br />
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</html></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/outreach.htmTeam/CINVESTAV-IPN-UNAM MX/outreach.htm2012-09-27T02:00:38Z<p>LoboLofi: Created page with "<html xmlns="http://www.w3.org/1999/xhtml"><head> <title>Home</title> <link rel="stylesheet" href="https://dl.dropbox.com/u/199422/Cinvestav/style.css" /> <meta http-equiv="C..."</p>
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<p>Sometimes is hard for scientist to get involved in Human Practices, we think is important to solve all those economical, ethical, legal and social issues in order to change the public perception of synthetic biology, We have worked in many activities for human practices<br /><br />
</p><br />
<p><strong><a href="https://2012.igem.org/wiki/index.php?title=Team/CINVESTAV-IPN-UNAM_MX/Meet.htm">Collaboration: iGEMMX Meet up!</a></strong><br /><br />
Twelve Mexican teams have participated in iGEM since 2007, they have had very successful participations, but they have never had an efficient communication. If we are connected, we can make things better. If we want to be competitive as a country in synthetic biology development, we have to collaborate. So, with the objective of improve our connections, improve our projects and establish collaboration agreements, we decided to organize the First iGEM MeetUP in our headquarters in Irapuato.<br /><br />
</p><br />
<p><strong>Education: SynBio Summer Workshop</strong></p><br />
<p><br /><br />
Every year, the leader of Systems and Synthetic Biology Group, and our main instructor, Agustino Martinez-Antonio organizes a Synthetic Biology Summer Workshop at the Center for Research and Advanced Studies (CINVESTAV), where undergrad students from all the country take part in the creation, design and development of new synbio projects during the summer. Some members of our team guided the new students in this workshop.<br /><br />
</p><br />
<p><a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/Education%20SynBio%20Summer%20Workshop.pdf" target="_blank"><strong>Read more…</strong></a><br /><br />
</p><br />
<p>&nbsp;</p><br />
<p><strong>Ownership: Intellectual Property vs. Open Source</strong><br /><br />
We know that Open source is the strategy to reach a global development in Synthetic Biology, but there´re many questions to answer in this topic. First, we have to decide a strategy to establish a strong Intellectual Property Platform. We asked many experts in IP in Mexico some of these questions<br /><br />
</p><br />
<p><strong><a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/Intellectual%20Property%20report.pdf" target="_blank">Read more…</a></strong></p><br />
<p>&nbsp;</p><br />
<p><strong>Sharing: iGEM Experience</strong><br /><br />
Maybe the most difficult part in making a new iGEM team is getting started, how do you get the right idea? How do you design the project? How do you work in teams? How do you get money? etc, . Since this is our first iGEM participation, we have had some little troubles that every team can face. We asked for opinions to answer all these questions in a document that can tell future iGEM teams what they should do in order to have success in the iGEM experience.<br /><br />
</p><br />
<p><strong><a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/iGEM%20Experience.pdf">Read more…</a></strong></p><br />
<p>&nbsp;</p><br />
<p><br /><br />
<strong>Biosafety…</strong><br /><br />
<a href="https://dl.dropbox.com/u/199422/Cinvestav/Down/Cartel%20BN.pdf" target="_blank"><strong>Poster</strong></a></p><br />
<p><strong>&nbsp;</strong></p><br />
<p><strong>Gaceta UNAM!</strong></p><br />
<p><strong><a href="http://www.quimica.unam.mx/IMG/pdf/flogisto81.pdf" target="_blank">Link1</a></strong></p><br />
<p><strong> <a href="http://www.quimica.unam.mx/IMG/pdf/gacetaseptiembre.pdf" target="_blank">Link 2</a></strong></p><br />
<p align="center">&nbsp;</p><br />
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</html></div>LoboLofihttp://2012.igem.org/Team/CINVESTAV-IPN-UNAM_MX/equations.htmTeam/CINVESTAV-IPN-UNAM MX/equations.htm2012-09-27T01:40:10Z<p>LoboLofi: </p>
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<img src="https://static.igem.org/mediawiki/2012/9/99/Interaction_between_AppA_and_PpsR.png" alt="Interaccion between AppA and PpsR with light and oxigen" ><br />
<strong style="font-size: 0.875em;">FIGURE 1. Interaction between AppA and PpsR as a function of the oxygen concentration [O2] and blue-light irradiance LI . The tetramers with intramolecular disul?de bonds (S-S) and thiol groups (SH) denote the oxidized and the reduced form of the PpsR repressor, respectively. The AppA protein has an FAD and a heme cofactor attached where h+ and hפenote the oxidized and reduced form of the heme cofactor, respectively. Both the oxidized and the reduced form of PpsR act as a repressor of photosynthesis genes, but with different strengths as indicated by the line thickness. Pandey, 2011.</strong><br />
<br/><br />
<br/><br />
<div id="TexBox1" style=" background-color:DarkSeaGreen;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px"><br />
<p> The proteins in our regulatory system constitute a network of intermingling elements whose behavior can be narrow into basic interaction rules. Primarily in this part of the modeling we focused on the PpsR and AppA anti-repressor/repressor system and chose to model it using a system of ordinary differential equations. The systemӳ repressive activity varies with the redox (O2) state of the cell and Light intensity and thus we wondered how exactly these two variables affect the overall repressive level of PpsR over the expression of PS genes.</p><br />
</div><br />
<p>This is the code written for the regulatory system Appa-PpsR in Mathematica.</p><br />
<img src="https://static.igem.org/mediawiki/2012/2/26/MathemathcaCodeICIPNUNAMMX.png" alt="Code of Differential Equations in mathematica"><br />
<div id="TexBox2" style=" background-color:Crimson;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px; color:#FFF"><br />
<p>To do this we based ourselves on a previous work that had attempted to study this same regulatory system. <strong style="color:#000">[Pandey, Rakesh Flockerzi, Dietrich Hauser, Marcus JB Straube, Ronny. 2011. Modeling the light- and redox-dependent interaction of PpsR/AppA in Rhodobacter sphaeroides.]</strong> In addition to contacting the responsible authors and discussing this model, we chose to improve it based on recent publications and preliminary experimental results i.e. we introduced a more subtle way light and oxygen affects the protein concentration dynamic, which is exactly what we were interested in understanding better.</p><br />
</div><br />
<br/><br />
<br/><br />
<strong>Results generated with the model:</strong><br />
<br/><br />
<br/><br />
<br/><br />
<table cellspacing="10"><br />
<tr><br />
<td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/e/ed/Graph_Oxigen_and_Light_1.jpg" alt="Graph number 1" /></td> <td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/a/a8/Graph_Oxigen_and_Light_2.jpg" alt="Graph number 2"/></td><br />
<tr><br />
<tr><br />
<td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/6/63/Graph_Oxigen_and_Light_3.jpg" alt="Graph number 3"/></td> <td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/2/20/Graph_Oxigen_and_Light_4.jpg" alt="Graph number 2"/></td><br />
<tr><br />
</table><br />
<br/><br />
<strong style="font-size: 0.875em;">Figure1. Steady state behavior of reduced PpsR (P4+), oxidized PpsR (P4-) and the AppA-PpsR complex as a function of oxygen concentration and light irradiance.</strong><br />
<br/><br />
<p style="color:green;"><br />
With our differential equations system we calculated protein concentrations at stable steady states and assumed this to be a natural "resting", or homeostatic, state given a set of parameters, oxygen and light intensities. As such, this gave us a steady state total repressive force, in essence, as a function of oxygen tension and light intensity. This is because PpsR-AppAӳ total repressive strength is a function of the concentrations of both its oxidative and reduced state.<br />
</p><br />
<div id="TexBox3" style=" background-color:RoyalBlue;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px; color:#FFF"><br />
<p>Because all this was done in Mathematica, we were able to generate an interactive graphical representation of the repressive strength over a range of conditions. This is really the strength of our work because with this model, we can make predictions in sillico as to how the organism will react to a given environmental surrounding and then go back to the lab and validate that prediction.</p><br />
</div><br />
<p><br />
<strong>Also, since we have the power to manipulate the values of the parameters in an easy and intuitive way, we can explore the parameter space and visually observe the change in the concentration curves, which can be of interest to, not only us, but other people that might not be interested in all the math behind interphase. This parameter tweaking allows us to compare experimental data against sillico predictions; the only difference is that if we focus on the parameters, this can actually give us hints respect to the still-blurred nature of Protein-Protein and Protein-Environment mechanisms that exist in this extremely versatile cell.</strong><br />
</p><br />
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<img src="https://static.igem.org/mediawiki/2012/9/99/Interaction_between_AppA_and_PpsR.png" alt="Interaccion between AppA and PpsR with light and oxigen" ><br />
<strong style="font-size: 0.875em;">FIGURE 1. Interaction between AppA and PpsR as a function of the oxygen concentration [O2] and blue-light irradiance LI . The tetramers with intramolecular disul?de bonds (S-S) and thiol groups (SH) denote the oxidized and the reduced form of the PpsR repressor, respectively. The AppA protein has an FAD and a heme cofactor attached where h+ and h–denote the oxidized and reduced form of the heme cofactor, respectively. Both the oxidized and the reduced form of PpsR act as a repressor of photosynthesis genes, but with different strengths as indicated by the line thickness. Pandey, 2011.</strong><br />
<br/><br />
<br/><br />
<div id="TexBox1" style=" background-color:DarkSeaGreen;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px"><br />
<p> The proteins in our regulatory system constitute a network of intermingling elements whose behavior can be narrow into basic interaction rules. Primarily in this part of the modeling we focused on the PpsR and AppA anti-repressor/repressor system and chose to model it using a system of ordinary differential equations. The system’s repressive activity varies with the redox (O2) state of the cell and Light intensity and thus we wondered how exactly these two variables affect the overall repressive level of PpsR over the expression of PS genes.</p><br />
</div><br />
<p>This is the code written for the regulatory system Appa-PpsR in Mathematica.</p><br />
<img src="https://static.igem.org/mediawiki/2012/2/26/MathemathcaCodeICIPNUNAMMX.png" alt="Code of Differential Equations in mathematica"><br />
<div id="TexBox2" style=" background-color:Crimson;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px; color:#FFF"><br />
<p>To do this we based ourselves on a previous work that had attempted to study this same regulatory system. <strong style="color:#000">[Pandey, Rakesh Flockerzi, Dietrich Hauser, Marcus JB Straube, Ronny. 2011. Modeling the light- and redox-dependent interaction of PpsR/AppA in Rhodobacter sphaeroides.]</strong> In addition to contacting the responsible authors and discussing this model, we chose to improve it based on recent publications and preliminary experimental results i.e. we introduced a more subtle way light and oxygen affects the protein concentration dynamic, which is exactly what we were interested in understanding better.</p><br />
</div><br />
<br/><br />
<br/><br />
<strong>Results generated with the model:</strong><br />
<br/><br />
<br/><br />
<br/><br />
<table cellspacing="10"><br />
<tr><br />
<td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/e/ed/Graph_Oxigen_and_Light_1.jpg" alt="Graph number 1" /></td> <td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/a/a8/Graph_Oxigen_and_Light_2.jpg" alt="Graph number 2"/></td><br />
<tr><br />
<tr><br />
<td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/6/63/Graph_Oxigen_and_Light_3.jpg" alt="Graph number 3"/></td> <td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/2/20/Graph_Oxigen_and_Light_4.jpg" alt="Graph number 2"/></td><br />
<tr><br />
</table><br />
<p style="color:green;"><br />
With our differential equations system we calculated protein concentrations at stable steady states and assumed this to be a natural “resting”, or homeostatic, state given a set of parameters, oxygen and light intensities. As such, this gave us a steady state total repressive force, in essence, as a function of oxygen tension and light intensity. This is because PpsR-AppA’s total repressive strength is a function of the concentrations of both its oxidative and reduced state.<br />
</p><br />
<div id="TexBox3" style=" background-color:RoyalBlue;border: Orange; border-style:solid; border-top-width: 4px; border-right-width: 4px; border-bottom-width: 4px; border-left-width: 4px; color:#FFF"><br />
<p>Because all this was done in Mathematica, we were able to generate an interactive graphical representation of the repressive strength over a range of conditions. This is really the strength of our work because with this model, we can make predictions in sillico as to how the organism will react to a given environmental surrounding and then go back to the lab and validate that prediction.</p><br />
</div><br />
<p><br />
<strong>Also, since we have the power to manipulate the values of the parameters in an easy and intuitive way, we can explore the parameter space and visually observe the change in the concentration curves, which can be of interest to, not only us, but other people that might not be interested in all the math behind interphase. This parameter tweaking allows us to compare experimental data against sillico predictions; the only difference is that if we focus on the parameters, this can actually give us hints respect to the still-blurred nature of Protein-Protein and Protein-Environment mechanisms that exist in this extremely versatile cell.</strong><br />
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<p> The proteins in our regulatory system constitute a network of intermingling elements whose behavior can be narrow into basic interaction rules. Primarily in this part of the modeling we focused on the PpsR and AppA anti-repressor/repressor system and chose to model it using a system of ordinary differential equations. The system’s repressive activity varies with the redox (O2) state of the cell and Light intensity and thus we wondered how exactly these two variables affect the overall repressive level of PpsR over the expression of PS genes.</p><br />
</div><br />
<p>This is the code written for the regulatory system Appa-PpsR in Mathematica.</p><br />
<img src="https://static.igem.org/mediawiki/2012/2/26/MathemathcaCodeICIPNUNAMMX.png" alt="Code of Differential Equations in mathematica"><br />
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<p>To do this we based ourselves on a previous work that had attempted to study this same regulatory system. <strong style="color:#000">[Pandey, Rakesh Flockerzi, Dietrich Hauser, Marcus JB Straube, Ronny. 2011. Modeling the light- and redox-dependent interaction of PpsR/AppA in Rhodobacter sphaeroides.]</strong> In addition to contacting the responsible authors and discussing this model, we chose to improve it based on recent publications and preliminary experimental results i.e. we introduced a more subtle way light and oxygen affects the protein concentration dynamic, which is exactly what we were interested in understanding better.</p><br />
</div><br />
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<br/><br />
<strong>Results generated with the model:</strong><br />
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<table cellspacing="10"><br />
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<td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/e/ed/Graph_Oxigen_and_Light_1.jpg" alt="Graph number 1" /></td> <td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/a/a8/Graph_Oxigen_and_Light_2.jpg" alt="Graph number 2"/></td><br />
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<td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/6/63/Graph_Oxigen_and_Light_3.jpg" alt="Graph number 3"/></td> <td><img width="280" height="215" src="https://static.igem.org/mediawiki/2012/2/20/Graph_Oxigen_and_Light_4.jpg" alt="Graph number 2"/></td><br />
<tr><br />
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<p style="color:green;"><br />
With our differential equations system we calculated protein concentrations at stable steady states and assumed this to be a natural “resting”, or homeostatic, state given a set of parameters, oxygen and light intensities. As such, this gave us a steady state total repressive force, in essence, as a function of oxygen tension and light intensity. This is because PpsR-AppA’s total repressive strength is a function of the concentrations of both its oxidative and reduced state.<br />
</p><br />
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<p>Because all this was done in Mathematica, we were able to generate an interactive graphical representation of the repressive strength over a range of conditions. This is really the strength of our work because with this model, we can make predictions in sillico as to how the organism will react to a given environmental surrounding and then go back to the lab and validate that prediction.</p><br />
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<p><br />
<strong>Also, since we have the power to manipulate the values of the parameters in an easy and intuitive way, we can explore the parameter space and visually observe the change in the concentration curves, which can be of interest to, not only us, but other people that might not be interested in all the math behind interphase. This parameter tweaking allows us to compare experimental data against sillico predictions; the only difference is that if we focus on the parameters, this can actually give us hints respect to the still-blurred nature of Protein-Protein and Protein-Environment mechanisms that exist in this extremely versatile cell.</strong><br />
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<div></div>LoboLofihttp://2012.igem.org/File:Interaction_between_AppA_and_PpsR.pngFile:Interaction between AppA and PpsR.png2012-09-27T00:18:06Z<p>LoboLofi: Interaction between AppA and PpsR as a function of the oxygen concentration [O2] and blue-light irradiance LI . The tetramers with intramolecular disulfide bonds (S-S) and thiol groups (SH) denote the oxidized and the reduced form of the PpsR repressor, </p>
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<div>Interaction between AppA and PpsR as a function of the oxygen concentration [O2] and blue-light irradiance LI . The tetramers with intramolecular disulfide bonds (S-S) and thiol groups (SH) denote the oxidized and the reduced form of the PpsR repressor, respectively. The AppA protein has an FAD and a heme cofactor attached where h+ and h–denote the oxidized and reduced form of the heme cofactor, respectively. Both the oxidized and the reduced form of PpsR act as a repressor of photosynthesis genes, but with different strengths as indicated by the line thickness. Pandey, 2011</div>LoboLofihttp://2012.igem.org/Team:CINVESTAV-IPN-UNAM_MX/TeamTeam:CINVESTAV-IPN-UNAM MX/Team2012-09-09T15:33:19Z<p>LoboLofi: </p>
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<td>After a day of work, we always smile and have some fun!!!!</td><br />
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<h3>Arias Orozco Patricia</h3><br />
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<li>undergrad</li><br />
<li>Biotechnological Engineer at<a href="http://www.ipn.mx/">National Polytechnic Institute</a></li><br />
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<h3>Domínguez Gómez Daniel</h3><br />
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<li>undergrad</li><br />
<li>Biotechnological Engineer at National Polytechnic Institute</li><br />
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<h3>Guerra Calderas Lissania</h3><br />
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<li>undergrad</li><br />
<li>Pharmaceutical and Biological Chemist at <a href="http://www.unam.mx/">National University of Mexico</a></li><br />
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<h3>Hernández Gardiol Daniel Federico</h3><br />
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<li>undergrad</li><br />
<li>Biologist at <a href="http://www.universidad.edu.uy/">University of the Republic of Uruguay</a></li><br />
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<h3>Hernández Gallardo Karen</h3><br />
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<li>undergrad</li><br />
<li>Biotechnological Engineer at National Polytechnic Institute</a></li><br />
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<h3>Hernández Valdéz Jhonatan</h3><br />
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<li>Pharmaceutical and Biological Chemist at National University of Mexico</li><br />
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<h3>Iván López Flores</h3><br />
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<li>Computer System Engineer at National Polytechnic Institute</li><br />
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<h3>Uriostegui Arcos Maritere</h3><br />
<ul><br />
<li>undergrad</li><br />
<li>Pharmaceutical and Biological Chemist at National University of Mexico</li><br />
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<article><h1>Project Description</h1><br />
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<h2>Construction of a light and oxygen sensor to control protein expression regulation</h2><br />
<p><br />
Rhodobacter sphaeroides (Rhb. sphaeroides) is a purple non-sulphur bacterium that belongs to the alpha-proteobacteria, the most metabolically diverse group of organisms on the planet. Part of this versatility is attributed to regulatory proteins which coordinate different metabolic states such as anaerobic photosynthesis and chemi-heterotrophy.<br />
</p><p><br />
Specifically, our project is concerned with two regulatory protein systems. The first one, is the two-component global activator under anaerobiosis, PrrB/PrrA. The second system is the light and oxygen mediated repressor/anti-repressor PpsR/AppA. These act in conjunction, along with a slew of other proteins in Rhb. sphaeroides, to tightly control and balance the metabolic demands of the cell. Our team will take these two regulatory systems to express them into a Rhodopseudomonas palustris chassis. The goal is to achieve a better comprehension of the R. palustris regulatory networks through the study of their properties of genetic switches in expressed in a relative isolation within another organism, considering the interference caused by other proteins could be minimal. This will allow us to study in a more precise way how the regulatory systems sense external conditions and transduce them into alternative expression levels via signaling pathways.<br />
</p><p><br />
For us to achieve this goal a cassette in which GFP expression is light-dependent by the antirepression of PpsR and oxygen dependent by the activation of PrrA/B system has been designed. All this lab work is accompanied by a computational model which, based on our experimental data, will provide a way of testing our knowledge of these systems. This in turn allows us to enhance the functionality of the device as it expresses heterologous genes in R. palustris.<br />
</p><p><br />
Once we have characterized the functionality of these regulatory networks we aim to take advantage of R. palustri’s metabolic versatility, and use this functional bacteria as a microbial factory that will allow the production of products of economic value from byproducts otherwise considered pollutants such as CO2 and other industrial derivatives.<br />
</p><br />
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<h2>Safety</h2><br />
<p><br />
<b>Question 1</b>:'''Would any of your project ideas raise safety issues in terms of researcher, public or enviromental safety?'''<br />
</p><p><br />
Our intention is to re-design two regulation systems from Rhodobacter sphaeroides, and introduce them into Rhodopseudomonas palustris. Since the PCR obtention of the 5 proteins that form the system is extremely difficult, we use the gene synthesis technology provided by Genescript in order to get this genes. <br />
Purple Non sulfur Bacteria are one of the most metabolically diverse groups known in nature, they are able to grow under different conditions such as, aerobic respiration, anoxigenic photosynthesis, anaerobic fermentation. Due to this ability, plus their ability to eat aromatic compounds, these bacteria can be found in hostile media such as polluted water.<br />
Despite all these features, work with these microorganisms in lab conditions is very hard, its growth medium is composed by a complex mix of metals and vitamins. We can consider that the risk in PNSB management in the lab is very low since they are non-pathogenic bacteria.<br />
R. sphaeroides and R. palustris´s grow rate is quite slow, thus, our genetic systems do not represent a public safety menace since they are highly specific, we have designed this systems for its specific functioning in purple photosynthetic bacteria.<br />
Nevertheless is very important to take special care when working in the wetlab, we have to take into consideration the basic precautions in microbiology.<br />
</p><p><br />
<b>Question 2</b>: '''Do any of the new BioBrick parts (or devices) that you made this year raise any safety issues?'''<br />
</p><p><br />
No, our BioBricks parts come from Rhodobacter sphaeroides, this bacteria is non-pathogenic and it can be worked in a Biosafety level 1 laboratory, based on the CDC Biosafety in Microbiological and Biomedical Laboratories (CDC, 2007). The functionality of our parts do not produce any dangerous compound, we are working in control of gene expression. Furthermore, we used BioBricks from iGEM distribution for all our assemblies, for example GFP as reporter, these parts do not represent a biological risk.<br />
</p><p><br />
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<b>Question 3</b>: '''Is there a local biosafety group, committee, or review board at your institution? If no, which specific biosafety rules or guidelines do you have to consider in your country?'''<br />
</p><p><br />
A Biosafety committee would have to be integrated by a multidisciplinary group of members among Institutions and Universities and it should provide expert advice on laboratory, biosafety and biosecurity issues related to research and other academic activities.<br />
Plan, design and implement the necessary instruments for biosafety risk assessment.<br />
Establish, disseminate and analyze safety measures in handling chemicals, genetically modified organisms and potentially infectious pathogens that will allow to make timely decisions for users in order to minimize potential health risks.<br />
Conduct briefings and feedback sessions with the areas involved in biosafety.<br />
Biosecurity measures established in the regulations must be consistent with the development and promotion of basic and applied research.<br />
For the analysis of solutions to particular problems should be evaluated case by case, the benefits and potential risks of the use of GMOs, this analysis should also include assessment of the risks of alternative technological options for coping with the specific problem to which the GMO was designed.<br />
Encourage and ensure the mechanisms that establish responsibilities who violates the regulations under existing legislation.<br />
And finally,it is important that other laws are reviewed; this will help to strengthen biosecurity aspects of other organisms that are not GMOs.<br />
</p><p><br />
<b>Question 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?'''<br />
</p><p><br />
As a part of our human practices work, we are trying to implement an administrative tool in order to answer the most important questions in terms of safety and biosecurity, this tool is the Quality Function Deployment. The relevance of this work is that we can be able to use the results to make different proposals that could support the development of synthetic biology based projects in Mexico. <br />
</p><br />
<h2>References</h2><br />
<p><br />
Biosafety in Microbiological and Biomedical Laboratories, (BMBL) 5th Edition (HHS Publication No. (CDC) 93-8395. U.S. Department of Health and Human Services, Centers for Disease Control and Prevention and National Institutes of Health; U.S. Government Printing Office: Washington DC; 2007). <br />
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<h1>Human Practices</h1><br />
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<p>Sometimes Human Practices work is hard for scientist, most scientist are not worried in solving ethical, legal or social issues. Nonetheless, in a country like Mexico, the human practices work is very important to create the ideal conditions that could guide us to a real development of synthetic biology in short term.<br />
</p><br />
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<p>We need education programs, research opportunities, colaboration agreements, biosafety agreements and information resources that provide a foundation for the development of new projects.<br />
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<p>Our Human Practices Work we prepare a network including many advances in ethical, legal and social implications, some of the activities are:</p><br />
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<li>Using of administrative tools for project design</li><br />
<li>Feedback sessions for project redesign</li><br />
<li>iGEM experience</li><br />
<li>Synthetic Biology Summer Workshop</li><br />
<li>Synthetic Biology Science Club</li><br />
<li>iGEMMX National Meeting for Mexican teams</li><br />
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