Difference between revisions of "Team:British Columbia/Description"

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<h1>Description</h1>
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<p>Tell us about your project, describe what moves you and why this is something important for your team.</p>
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<h3>What should this page contain?</h3>
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<li> A clear and concise description of your project.</li>
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<li>A detailed explanation of why your team chose to work on this particular project.</li>
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<p>See how other teams have described and presented their projects: </p>
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<li><a href="https://2016.igem.org/Team:Imperial_College/Description">2016 Imperial College</a></li>
 
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<li><a href="https://2016.igem.org/Team:Wageningen_UR/Description">2016 Wageningen UR</a></li>
 
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<li><a href="https://2014.igem.org/Team:UC_Davis/Project_Overview"> 2014 UC Davis</a></li>
 
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<li><a href="https://2014.igem.org/Team:SYSU-Software/Overview">2014 SYSU Software</a></li>
 
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<h3>Advice on writing your Project Description</h3>
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We encourage you to put up a lot of information and content on your wiki, but we also encourage you to include summaries as much as possible. If you think of the sections in your project description as the sections in a publication, you should try to be concise, accurate, and unambiguous in your achievements.  
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<img src="https://static.igem.org/mediawiki/2018/f/fa/T--British_Columbia--glucose-kaempferol-graphic.png" style = "height: 400px; display: block; margin-left: 210px;>
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<br>Distributing metabolic pathways between microbial community members has shown significant potential for the large-scale production of complex, biologically-derived chemical products. <b>Our goal is to address the challenge of regulating population dynamics in a synthetic microbial consortium, by improving the rate of production of naringenin and its pharmaceutically significant derivative, kaempferol, which has anti-cancer properties. </b>This is done by distributing the synthesis of kaempferol between two <i>E. coli</i> strains and optimizing their relative proportions in co-culture. To optimize population dynamics for the production of kaempferol, we regulated the ratio of the two strains using GP2, a transcriptional inhibitor, under the control of a biosensor responsive to the pathway intermediate naringenin. This couples cell growth with the concentration of naringenin, allowing the co-culture to self-optimize based on pathway intermediate abundance. Using our system, we have demonstrated a novel way to optimize microbial polycultures for the synthesis of metabolically complex compounds.
 
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<h3>References</h3>
 
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<p>iGEM teams are encouraged to record references you use during the course of your research. They should be posted somewhere on your wiki so that judges and other visitors can see how you thought about your project and what works inspired you.</p>
 
  
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<ol>
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<p style = "color: grey; font-size: 13pt; margin-left: 80px;">References</p>
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<li> Zhang, H. and X. Wang, Modular co-culture engineering, a new approach for metabolic engineering. Metabolic Engineering, 2016. 37: p. 114-121.</li>
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<li> Ganesan, V., et al., Heterologous biosynthesis of natural product naringenin by co-culture engineering. Synthetic and Systems Biotechnology, 2017. 2(3): p. 236-242.</li>
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<li>Jones, J.A., et al., Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids. Metabolic Engineering, 2016. 35: p. 55-63.</li>
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<li>Cámara, B., et al., T7 phage protein Gp2 inhibits the Escherichia coli RNA polymerase by antagonizing stable DNA strand separation near the transcription start site. Proceedings of the National Academy of Sciences of the United States of America, 2010. 107(5): p. 2247-2252.</li>
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<li>Siedler, S., et al., Novel biosensors based on flavonoid-responsive transcriptional regulators introduced into Escherichia coli. Metabolic Engineering, 2014. 21: p. 2-8.</li>
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<li>Raman, S., et al., Evolution-guided optimization of biosynthetic pathways. Proceedings of the National Academy of Sciences of the United States of America, 2014. 111(50): p. 17803-17808.</li>
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Latest revision as of 01:00, 11 November 2018


Distributing metabolic pathways between microbial community members has shown significant potential for the large-scale production of complex, biologically-derived chemical products. Our goal is to address the challenge of regulating population dynamics in a synthetic microbial consortium, by improving the rate of production of naringenin and its pharmaceutically significant derivative, kaempferol, which has anti-cancer properties. This is done by distributing the synthesis of kaempferol between two E. coli strains and optimizing their relative proportions in co-culture. To optimize population dynamics for the production of kaempferol, we regulated the ratio of the two strains using GP2, a transcriptional inhibitor, under the control of a biosensor responsive to the pathway intermediate naringenin. This couples cell growth with the concentration of naringenin, allowing the co-culture to self-optimize based on pathway intermediate abundance. Using our system, we have demonstrated a novel way to optimize microbial polycultures for the synthesis of metabolically complex compounds.


    References

  1. Zhang, H. and X. Wang, Modular co-culture engineering, a new approach for metabolic engineering. Metabolic Engineering, 2016. 37: p. 114-121.
  2. Ganesan, V., et al., Heterologous biosynthesis of natural product naringenin by co-culture engineering. Synthetic and Systems Biotechnology, 2017. 2(3): p. 236-242.
  3. Jones, J.A., et al., Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids. Metabolic Engineering, 2016. 35: p. 55-63.
  4. Cámara, B., et al., T7 phage protein Gp2 inhibits the Escherichia coli RNA polymerase by antagonizing stable DNA strand separation near the transcription start site. Proceedings of the National Academy of Sciences of the United States of America, 2010. 107(5): p. 2247-2252.
  5. Siedler, S., et al., Novel biosensors based on flavonoid-responsive transcriptional regulators introduced into Escherichia coli. Metabolic Engineering, 2014. 21: p. 2-8.
  6. Raman, S., et al., Evolution-guided optimization of biosynthetic pathways. Proceedings of the National Academy of Sciences of the United States of America, 2014. 111(50): p. 17803-17808.