Stochastic models of evolution driven by spatial heterogeneity

Samenvatting

In the course of evolution, organisms have adapted to a wide variety of physical conditions and now populate virtually every corner of the earth. It seems evident, therefore, that spatial heterogeneity must play an important role in evolution. And yet, most mathematical models of evolution ignore space altogether.

We propose a theoretical study of modes of evolution in which spatial variation is the essential driving force.

We will explore the novel idea that some beneficial mutations do not so much improve the fitness of the organism in its current habitat, but instead allow it to expand its habitat. Consequently, spatial heterogeneity can drive a mode of adaptation that differs qualitatively from the conventional evolution theories. This process is likely to play a role in the evolution of antibiotic resistance, virulence and insecticide resistance, because these processes each involve adaptation to a different habitat.

To analyze these ideas, we here propose three theoretical models, exploring adaptation
1. in environments consisting of two discrete ?patches?,
2. in environments consisting of many patches, and
3. in continuous space.

Evolution is an intrinsically stochastic process, in which rare events can have large consequences. Therefore, to analyze the models we will employ a wide array of concepts and tools from statistical physics, ranging from the theory of first-passage processes to the theory of stochastically propagating fronts. Thus, we ask: Can spatial heterogeneity indeed drive evolution or speed it up? How does the rate of adaptation depend on geometry, population size, and rates of dispersion, mutation, reproduction and death? How do populations adapt to an environmental gradient?

In the host institute, experiments are conducted in which bacteria evolve in nano-fabricated micro-ecologies. Collaboration with these experimentalists will inspire more specific models and will allow me to test insights obtained from conceptual models in real, tangible systems.

Output

Wetenschappelijk artikel

  • R Hermsen, D J Barrett, T Hwa(2012): On the rapidity of antibiotic resistance evolution facilitated by a concentration gradient. Proceedings of the National Academy of Scineces pp. 10775 - 10780
  • JB Deris, M Kim, Z Zhang, H Okano, R Hermsen, A Groisman, T Hwa(2013): The Innate Growth Bistability and Fitness Landscapes of Antibiotic-Resistant Bacteria Science pp. 1237435 - 1237435
  • R Hermsen, H Okano, C You, N Werner, T Hwa(2015): A growth-rate composition formula for the growth of E. coli on co-utilized carbon substrates Molecular Systems Biology pp. 801 - 801 ISSN: 1744-4292.

Publieksinformatie

  • R Hermsen, C. You, T. Hwa(2012): Predicting the growth rate of bacteria provided with multiple carbon sources
  • J.B. Deris, M. Kim, Z. Zhang, H. Okano, R. Hermsen, A. Groisman, T. Hwa(2012): The innate growth bistability of antibiotic resistant bacteria
  • R Hermsen, J.B. Deris, T. Hwa(2012): Stochastic models of evolution in heterogeneous environments
  • R Hermsen(2012): Stochastic models of evolution in heterogeneous environments

Kenmerken

Projectnummer

680-47-419

Hoofdaanvrager

Dr. R. Hermsen

Verbonden aan

Universiteit Utrecht, Faculteit Bètawetenschappen, Departement Biologie

Uitvoerders

Dr. R. Hermsen

Looptijd

15/03/2012 tot 10/11/2015