Postdoctoral Fellow
Despite their small size, microorganisms exhibit vast diversity in where they live, what kinds of resources they use, and how they interact with one another. The existence of much of this diversity coincides nicely with how different the challenges are for living in such vastly different environments that change drastically over both space and time. However, the existence of these complex conditions alone is not enough to drive the evolution of microbial diversity; a so-called ``Darwinian demon'' that could grow at the highest possible rate in every environment would proliferate without limit. Thus, trade-offs between growth rates in different environments are crucial for generating biological novelty and maintaining diversity. In general, trade-offs are due to metabolic, physiological, or physical constraints, and how organisms evolve in response to these constraints is determined by their mechanistic details. The primary focus of this proposed work is to develop computational models of the evolution of important microbial traits, such as social behavior and phenotypic variability, that integrate the metabolic and physiological basis of core growth-rate trade-offs with complex demographic and ecological conditions. Many of these core trade-offs are mechanistically related to host-pathogen interactions, such as pathogen virulence, and the second focus of this proposed work is to incorporate the mechanistic details of core trade-offs into models of host-pathogen evolution. These models will be built with the powerful tools of modern evolutionary theory that allow both the prediction of long-term qualitative outcomes as well as the prediction of short-term quantitative outcomes.
Mechanistic trade-offs in evolution of microbial sociality, plasticity, virulence
| PI(s): | Jeremy Van Cleve |
| Start Date: | 7-Jan-2013 |
| End Date: | 1-Dec-2014 |
| Keywords: | evolutionary theory, mathematical modeling, sociality, life histories, disease |
Despite their small size, microorganisms exhibit vast diversity in where they live, what kinds of resources they use, and how they interact with one another. The existence of much of this diversity coincides nicely with how different the challenges are for living in such vastly different environments that change drastically over both space and time. However, the existence of these complex conditions alone is not enough to drive the evolution of microbial diversity; a so-called ``Darwinian demon'' that could grow at the highest possible rate in every environment would proliferate without limit. Thus, trade-offs between growth rates in different environments are crucial for generating biological novelty and maintaining diversity. In general, trade-offs are due to metabolic, physiological, or physical constraints, and how organisms evolve in response to these constraints is determined by their mechanistic details. The primary focus of this proposed work is to develop computational models of the evolution of important microbial traits, such as social behavior and phenotypic variability, that integrate the metabolic and physiological basis of core growth-rate trade-offs with complex demographic and ecological conditions. Many of these core trade-offs are mechanistically related to host-pathogen interactions, such as pathogen virulence, and the second focus of this proposed work is to incorporate the mechanistic details of core trade-offs into models of host-pathogen evolution. These models will be built with the powerful tools of modern evolutionary theory that allow both the prediction of long-term qualitative outcomes as well as the prediction of short-term quantitative outcomes.Related products
Publications- Pathways to Social Evolution: Reciprocity, Relatedness, and Synergy Van Cleve, Jeremy and Akçay, Erol. 2014. Pathways to Social Evolution: Reciprocity, Relatedness, and Synergy. Evolution 68(8):2245--2258.
- Stochastic stability and the evolution of coordination in spatially structured populations Van Cleve, J. and Lehmann, L. 2013. Stochastic stability and the evolution of coordination in spatially structured populations. Theoretical Population Biology.
