Difference between revisions of "Team:KUAS Korea/Project/Description"
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| − | < | + | <h3>What is the evolutionary game theory?</h3> |
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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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| − | + | <h3>Our Goal</h3> | |
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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> | |
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| − | 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. | + | |
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| + | <h3>References</h3> | ||
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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 08:38, 3 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
- Sigmund, Karl, and Martin A. Nowak. "Evolutionary game theory." Current Biology 9.14 (1999): R503-R505.
Sponsors
