Difference between revisions of "Team:KUAS Korea/Description"

 
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        <td class="align-middle text-center section-header"><h3>Description</h3></td>
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<p>Medical and unit staffs are considered as the main route for secondary infection in the hospital since contacts between staffs and immunocompromised patients frequently occur in the confined space. Our plan is to develop a toolkit for detecting pathogens and further prevent the spread via staffs.
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We are trying to develop a toolkit that senses the presence and the quantity of pathogen such as MRSA. It is done by attaching fluorescent tags to the protein that specifically binds to the pathogen-specific surface protein.
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The proof of concept will be done by the detection of E.coli DH5-alpha, which is transformed to express the surface protein of the pathogen(e.g. MRSA).
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The development of such toolkit will resolve the problems regarding hospital-acquired infections (HAIs). HAIs may lead to complications and this can be potentially fatal to patients with compromised immune systems.
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For antibiotics are widely used and prescribed in hospitals, early detecting and eliminating antibiotic-resistance bacteria are crucial tasks for medical institutions.
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This method is cost-effective, multi-plexible, highly sensitive and specific to pathogens which enables easy and intuitive analysis.</p>
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                <center><h4><strong>What is the evolutionary game theory?</strong></h4>
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                <ol>How does microbial community perpetuate or perish? Like human society, in nature, microorganisms not only compete but also interact and cooperate with each other for a successful establishment of a microbial community. Even though microbes cannot be seen with bare eyes, the population dynamics in the microbial community can be explained by evolutionary game theory. The evolutionary game theory is simply an application of game theory to evolving populations in biology illustrating how cooperative systems could have evolved over time from various strategies the biological creatures might have adopted. The evolutionary game theory differs from classical game theory in that it focuses more on the dynamics of strategy change. While EGT provides theoretical basis for evolution of cooperation, the empirical validation is not a trivial task and requires sophisticated design and construction of experimental model system.</ol>
 
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                <center><h4><strong>Our Goal</strong></h4>
  
  
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                <ol>The major goal of our project is to construct an accessible evolutionary game model using a synthetic microbial population controlled by genetic circuits. Here, we use E. coli to form a microbial population composed of the "cooperator" and the "cheater". "Cooperator" which displays β-glucosidase on the cell surface breaks down cellobiose into glucose. This enzymatic activity allows both "cooperator" and "cheater" to share glucose as energy source (public goods). "Cheater" which expresses GFP is now able to proliferate within microbe population depending on breaking cellobiose by cooperator. We use GFP expression from "cheater" as an indicator to estimate an increased number of "cheater". Based on the combination of mathematical modeling and experiments, we are going to find critical parameters for evolutionary games such as harmony, snow-drift and prisoner’s dilemma and relevant conditions for controlling population dynamics of microbial community.</ol><br><br><br><br><br>
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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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<h3>Inspiration</h3>
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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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<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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                <h4><strong>References</strong></h4>
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                <li>Sigmund, Karl, and Martin A. Nowak. "Evolutionary game theory." Current Biology 9.14 (1999): R503-R505.</li></ol>
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Latest revision as of 17:57, 17 October 2018

Description



What is the evolutionary game theory?

    How does microbial community perpetuate or perish? Like human society, in nature, microorganisms not only compete but also interact and cooperate with each other for a successful establishment of a microbial community. Even though microbes cannot be seen with bare eyes, the population dynamics in the microbial community can be explained by evolutionary game theory. The evolutionary game theory is simply an application of game theory to evolving populations in biology illustrating how cooperative systems could have evolved over time from various strategies the biological creatures might have adopted. The evolutionary game theory differs from classical game theory in that it focuses more on the dynamics of strategy change. While EGT provides theoretical basis for evolution of cooperation, the empirical validation is not a trivial task and requires sophisticated design and construction of experimental model system.



Our Goal

    The major goal of our project is to construct an accessible evolutionary game model using a synthetic microbial population controlled by genetic circuits. Here, we use E. coli to form a microbial population composed of the "cooperator" and the "cheater". "Cooperator" which displays β-glucosidase on the cell surface breaks down cellobiose into glucose. This enzymatic activity allows both "cooperator" and "cheater" to share glucose as energy source (public goods). "Cheater" which expresses GFP is now able to proliferate within microbe population depending on breaking cellobiose by cooperator. We use GFP expression from "cheater" as an indicator to estimate an increased number of "cheater". Based on the combination of mathematical modeling and experiments, we are going to find critical parameters for evolutionary games such as harmony, snow-drift and prisoner’s dilemma and relevant conditions for controlling population dynamics of microbial community.





References

  1. Sigmund, Karl, and Martin A. Nowak. "Evolutionary game theory." Current Biology 9.14 (1999): R503-R505.

Sponsors

KUAS

Korea University


iGEM

Links

About Us

Student Leader: Taehoon Lee
Wet Lab Leader: Bosun Ryu
Dry Lab Leader: Uijin Han
Human Practices Leader: Eunmin Kim

Contact Us

Seoul Seongbuk-gu Anam-ro 145
Tel: 02)1234-5678
Email: kuaskorea@gmail.com

© Copyright KUAS 2018. All Rights Reserved