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| − | <h3><b><font size="4">Every Gene Harbors a Vulnerability</font></b></h3>
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| − | <p> <font size="3"> At the foundation of the field of synthetic biology lies a seemingly irreconcilable paradox. By applying our mastery over life’s genetic code, we aim to turn biological systems into devices that we can control and program in predictable ways. Yet the same genetic elements that we incorporate into our designs owe their existence to the unpredictability of evolution operating to mutate and change DNA.</p><br>
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| − | <p> Evolution and mutation work hand in hand to select against the maintenance of synthetic DNA sequences, taking the biological engineer’s best-formulated designs and eroding them to nothing. No matter if it is a complex gene circuit or single-gene expression, a single mutation is enough to render an entire system nonfunctional. As soon as a mutant cell emerges, its mutation frees it from the metabolic burden of sustaining transgenes, allowing it to outcompete all the remaining cells that are functioning as intended [1]. Within days the population ceases to be what it was engineered to be [2]. Nature defeats the engineer’s attempts at harnessing the vast potential for biological machines to be re-purposed as agents for good.</font></p>
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| − | <h3><b><font size="4">How to Tame Evolution</font> </b> </h3>
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| − | <p> <font size="3"> How is it even possible to combat processes as fundamental as mutation and natural selection? The dogma in biology has been that random mutation will strike any gene sequence and initiate a process of selection as a logical consequence of the variations that mutation introduces. But that basic dogma is wrong. As soon as we realize that subtle mistake, the way is opened to bring mutation itself under the synthetic biologist’s control.</font> </p><br>
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| − | <p> <font size="3"> Decades of genomics and biochemistry research has established that mutation is not truly random. Certain DNA sequences are “hotspots” more prone to mutation than others, while others are resistant against mutagenic damage [3]. Our idea is to rationally modulate the sequence composition of synthetic genes to reduce or eliminate motifs with high mutation risk, substituting them out for mutation-resistant sequences. When combined with gene synthetic technologies, our process becomes a simple and reliable optimization that is universally applicable to genes expressed in any organism </font> </p>
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| − | <h3><b><font size="4">An Algorithmic Approach to Control Mutation</font></b> </h3>
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| − | <p><font size="3"> We have developed a computational algorithm that returns control back into the hands of synthetic biologists. By making synonymous substitutions that preserve gene function, substantial proportions of mutagenic sites can be eliminated from any sequence. Our robust algorithmic strategy for generating mutation-resistant genes has potential for improving the safety and stability of transgenes, which we are demonstrating by performing multiple independent techniques to measure stability at the level of sequences in vitro up to the function of cell populations.</p><br>
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| − | <p> To complement our applied research, we are also taking advantage of our new software tools to begin to answer a lingering question in the field: why would a site’s risk of mutation depend so greatly on the base-composition of the nucleotides surrounding it? By synthesizing sequences with tailored patterns of mutation “hotspots”, we may be able to further improve the performance of our own algorithm, and may provide insight into the nature of mutagenesis to advance the field of cancer research. </font> </p>
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| − | <p><font size="3"> While any single engineered change to reduce mutation may still fail, when our innovative approaches to modulating evolutionary stability are taken in combination, they offer an unprecedented hope for overcoming evolutionary entropy. More than a victory for synthetic biology, we prove that through rational design principles- exactly what mutation most virulently tries to uproot- and with enough clever innovations, it is possible to defend against what seemed like an inevitability of nature.</font> </p><br><br>
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| − | <i><font size="2.5">References</i></font><font size="2">
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| − | <br>1. Ceroni, F., Algar, R., Stan, G.-B., and Ellis, T. (2015). Quantifying cellular capacity identifies gene expression designs with reduced burden. Nature Methods 12, 415–418.
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| − | <br> 2. Sleight, S.C., Bartley, B.A., Lieviant, J.A., and Sauro, H.M. (2010). Designing and engineering evolutionary robust genetic circuits. Journal of Biological Engineering 4, 12.
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| − | <br> 3. Das, S., Duggal, P., Roy, R., Myneedu, V.P., Behera, D., Prasad, H.K., and Bhattacharya, A. (2012). Identification of Hot and Cold spots in genome of Mycobacterium tuberculosis using Shewhart Control Charts. Scientific Reports 2.</font>
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| − | <br><br><br><br>
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| − | <h2> Welcome to iGEM 2016! </h2>
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| − | <p>Your team has been approved and you are ready to start the iGEM season! </p>
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| − | <h5>Before you start: </h5>
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| − | <p> Please read the following pages:</p>
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| − | <ul>
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| − | <li> <a href="https://2016.igem.org/Requirements">Requirements page </a> </li>
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| − | <li> <a href="https://2016.igem.org/Wiki_How-To">Wiki Requirements page</a></li>
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| − | <li> <a href="https://2016.igem.org/Resources/Template_Documentation"> Template Documentation </a></li>
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| − | </ul>
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| − | </div>
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| − | <div class="highlight">
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| − | <h5> Styling your wiki </h5>
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| − | <p>You may style this page as you like or you can simply leave the style as it is. You can easily keep the styling and edit the content of these default wiki pages with your project information and completely fulfill the requirement to document your project.</p>
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| − | <p>While you may not win Best Wiki with this styling, your team is still eligible for all other awards. This default wiki meets the requirements, it improves navigability and ease of use for visitors, and you should not feel it is necessary to style beyond what has been provided.</p>
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| − | </div>
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| − | <h5> Wiki template information </h5>
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| − | <p>We have created these wiki template pages to help you get started and to help you think about how your team will be evaluated. You can find a list of all the pages tied to awards here at the <a href="https://2016.igem.org/Judging/Pages_for_Awards/Instructions">Pages for awards</a> link. You must edit these pages to be evaluated for medals and awards, but ultimately the design, layout, style and all other elements of your team wiki is up to you!</p>
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| − | <h5> Editing your wiki </h5>
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| − | <p>On this page you can document your project, introduce your team members, document your progress and share your iGEM experience with the rest of the world! </p>
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| − | <p> <a href="https://2016.igem.org/wiki/index.php?title=Team:Example&action=edit"> Click here to edit this page! </a></p>
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| − | </div>
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| − | <h5>Tips</h5>
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| − | <p>This wiki will be your team’s first interaction with the rest of the world, so here are a few tips to help you get started: </p>
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| − | <ul>
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| − | <li>State your accomplishments! Tell people what you have achieved from the start. </li>
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| − | <li>Be clear about what you are doing and how you plan to do this.</li>
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| − | <li>You have a global audience! Consider the different backgrounds that your users come from.</li>
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| − | <li>Make sure information is easy to find; nothing should be more than 3 clicks away. </li>
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| − | <li>Avoid using very small fonts and low contrast colors; information should be easy to read. </li>
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| − | <li>Start documenting your project as early as possible; don’t leave anything to the last minute before the Wiki Freeze. For a complete list of deadlines visit the <a href="https://2016.igem.org/Calendar">iGEM 2016 calendar</a> </li>
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| − | <li>Have lots of fun! </li>
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| − | </ul>
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| − | </div>
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| − | <h5>Inspiration</h5>
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| − | <p> You can also view other team wikis for inspiration! Here are some examples:</p>
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| − | <ul>
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| − | <li> <a href="https://2014.igem.org/Team:SDU-Denmark/"> 2014 SDU Denmark </a> </li>
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| − | <li> <a href="https://2014.igem.org/Team:Aalto-Helsinki">2014 Aalto-Helsinki</a> </li>
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| − | <li> <a href="https://2014.igem.org/Team:LMU-Munich">2014 LMU-Munich</a> </li>
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| − | <li> <a href="https://2014.igem.org/Team:Michigan"> 2014 Michigan</a></li>
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| − | <li> <a href="https://2014.igem.org/Team:ITESM-Guadalajara">2014 ITESM-Guadalajara </a></li>
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| − | <li> <a href="https://2014.igem.org/Team:SCU-China"> 2014 SCU-China </a></li>
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| − | </ul>
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| − | </div>
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| − | <h5> Uploading pictures and files </h5>
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| − | <p> You can upload your pictures and files to the iGEM 2016 server. Remember to keep all your pictures and files within your team's namespace or at least include your team's name in the file name. <br />
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| − | When you upload, set the "Destination Filename" to <code>Team:YourOfficialTeamName/NameOfFile.jpg</code>. (If you don't do this, someone else might upload a different file with the same "Destination Filename", and your file would be erased!)</p>
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| − | <div class="button_click" onClick=" parent.location= 'https://2016.igem.org/Special:Upload '">
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| − | UPLOAD FILES
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| − | </div>
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| − | </div>
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| | + | <h2 align="center">Every Gene Harbors a Vulnerability</h2> |
| | + | <p> At the foundation of the field of synthetic biology lies a seemingly irreconcilable paradox. By applying our mastery over life’s genetic code, we aim to turn biological systems into devices that we can control and program in predictable ways. Yet the same genetic elements that we incorporate into our designs owe their existence to the unpredictability of evolution operating to mutate and change DNA.</p> |
| | + | <p> Evolution and mutation work hand in hand to select against the maintenance of synthetic DNA sequences, taking the biological engineer’s best-formulated designs and eroding them to nothing. No matter if it is a complex gene circuit or single-gene expression, a single mutation is enough to render an entire system nonfunctional. As soon as a mutant cell emerges, its mutation frees it from the metabolic burden of sustaining transgenes, allowing it to outcompete all the remaining cells that are functioning as intended [1]. Within days the population ceases to be what it was engineered to be [2]. Nature defeats the engineer’s attempts at harnessing the vast potential for biological machines to be re-purposed as agents for good. </p> |
| | + | <br> |
| | + | <h2> How to Tame Evolution </h2> |
| | + | <p> How is it even possible to combat processes as fundamental as mutation and natural selection? The dogma in biology has been that random mutation will strike any gene sequence and initiate a process of selection as a logical consequence of the variations that mutation introduces. But that basic dogma is wrong. As soon as we realize that subtle mistake, the way is opened to bring mutation itself under the synthetic biologist’s control. </p> |
| | + | <p> Decades of genomics and biochemistry research has established that mutation is not truly random. Certain DNA sequences are “hotspots” more prone to mutation than others, while others are resistant against mutagenic damage [3]. Our idea is to rationally modulate the sequence composition of synthetic genes to reduce or eliminate motifs with high mutation risk, substituting them out for mutation-resistant sequences. When combined with gene synthetic technologies, our process becomes a simple and reliable optimization that is universally applicable to genes expressed in any organism. </p> |
| | + | <br> |
| | + | <br> |
| | + | <p><i> References</i></p> |
| | + | <p>1. Ceroni, F., Algar, R., Stan, G.-B., and Ellis, T. (2015). Quantifying cellular capacity identifies gene expression designs with reduced burden. Nature Methods 12, 415–418.</p> |
| | + | <p> 2. Sleight, S.C., Bartley, B.A., Lieviant, J.A., and Sauro, H.M. (2010). Designing and engineering evolutionary robust genetic circuits. Journal of Biological Engineering 4, 12. </p> |
| | + | <p> 3. Das, S., Duggal, P., Roy, R., Myneedu, V.P., Behera, D., Prasad, H.K., and Bhattacharya, A. (2012). Identification of Hot and Cold spots in genome of Mycobacterium tuberculosis using Shewhart Control Charts. Scientific Reports 2.</font></p> |
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| | </html> | | </html> |
Every Gene Harbors a Vulnerability
At the foundation of the field of synthetic biology lies a seemingly irreconcilable paradox. By applying our mastery over life’s genetic code, we aim to turn biological systems into devices that we can control and program in predictable ways. Yet the same genetic elements that we incorporate into our designs owe their existence to the unpredictability of evolution operating to mutate and change DNA.
Evolution and mutation work hand in hand to select against the maintenance of synthetic DNA sequences, taking the biological engineer’s best-formulated designs and eroding them to nothing. No matter if it is a complex gene circuit or single-gene expression, a single mutation is enough to render an entire system nonfunctional. As soon as a mutant cell emerges, its mutation frees it from the metabolic burden of sustaining transgenes, allowing it to outcompete all the remaining cells that are functioning as intended [1]. Within days the population ceases to be what it was engineered to be [2]. Nature defeats the engineer’s attempts at harnessing the vast potential for biological machines to be re-purposed as agents for good.
How to Tame Evolution
How is it even possible to combat processes as fundamental as mutation and natural selection? The dogma in biology has been that random mutation will strike any gene sequence and initiate a process of selection as a logical consequence of the variations that mutation introduces. But that basic dogma is wrong. As soon as we realize that subtle mistake, the way is opened to bring mutation itself under the synthetic biologist’s control.
Decades of genomics and biochemistry research has established that mutation is not truly random. Certain DNA sequences are “hotspots” more prone to mutation than others, while others are resistant against mutagenic damage [3]. Our idea is to rationally modulate the sequence composition of synthetic genes to reduce or eliminate motifs with high mutation risk, substituting them out for mutation-resistant sequences. When combined with gene synthetic technologies, our process becomes a simple and reliable optimization that is universally applicable to genes expressed in any organism.
References
1. Ceroni, F., Algar, R., Stan, G.-B., and Ellis, T. (2015). Quantifying cellular capacity identifies gene expression designs with reduced burden. Nature Methods 12, 415–418.
2. Sleight, S.C., Bartley, B.A., Lieviant, J.A., and Sauro, H.M. (2010). Designing and engineering evolutionary robust genetic circuits. Journal of Biological Engineering 4, 12.
3. Das, S., Duggal, P., Roy, R., Myneedu, V.P., Behera, D., Prasad, H.K., and Bhattacharya, A. (2012). Identification of Hot and Cold spots in genome of Mycobacterium tuberculosis using Shewhart Control Charts. Scientific Reports 2.
