The evolution of microbial growth across environments

Many microbial organisms are able to grow with extremely low concentration of nutrients, many orders of magnitude below the concentrations used in laboratory experiments. In my Ph.D., I asked how the traits for maximum growth rate and the half-saturation concentration (Monod K) are distributed across microbial taxa and resources, and how microbial populations improve their growth response over evolutionary time. By simulating evolution experiments in different environments, I found that microbial taxa evolve half-saturation concentrations much below the environmental levels of the nutrient and the evolved trait also depends on the size of the population.

More broadly, I am interested in nutrient limitation and the selection pressure that microbial populations experience in natural environments. In particular, I am interested in ways to estimate taxon-specific death and growth rates for microbial populations in situ.

  • Fink JW, Held NA, Manhart M. “Microbial population dynamics decouple growth response from environmental nutrient concentration”. PNAS, 2023. doi:10.1073/pnas.2207295120
  • Fink JW, Manhart M. “How do microbes grow in nature? The role of population dynamics in microbial ecology and evolution”. Curr Opin Syst Biol, 2023. doi:/10.1016/j.coisb.2023.100470

Quantification challenges in microbial ecology and evolution

Few concepts are as central to microbial ecology as ‘fitness’ and ‘interaction’, but the actual quantification of these concepts is ambiguous. During my PhD, I developed a unified framework that rederives all common statistics of relative fitness from first principles and helps to better distinguish relative fitness from related but distinct concepts, like absolute fitness or fitness proxies like the area-under-the-curve (AUC). Using empirical trait data, I was able to show that the choice of time-scale for quantifying relative fitness (per-generation vs. per-cycle) can give rise to different fitness rankings and that a low initial abundance of the mutant library is key parameter to avoid higher-order interactions in transposon-seq fitness measurements.

I am broadly interested in issues of quantification in the microbial sciences. As a collaborator the projects of others, I have contributed a measure of interaction strength that links interaction to nutrient limitation and developed custom software to quantify growth traits from high-throughput growth curve datasets.

Pre-PhD: Mathematical modeling for spatially structured populations

During an undergraduate research internship at the University of Ottawa with Frithjof Lutscher, I helped to derive a set of partial differential equations for the spread of ecosystem engineers (think of beavers!). The fact that these organisms modify their environment means the speed of expansion is modeled by an unusual traveling wave that also appears in models of melting ice (Stefan problem).

  • Lutscher F, Fink JW, Zhu, Y. “Pushing the Boundaries: Models for the Spatial Spread of Ecosystem Engineers”. Bull. Math. Biol., 2020. doi:10.1007/s11538-020-00818-8

For my master’s thesis at the University of Bonn with Anton Bovier, I studied the invasion of mutant cells into a population with phenotypic heterogeneity, using a spatially-structured version of the Lotka-Volterra. Building on previous results, I was able to propose sufficient conditions for the successful invasion of a mutant based on an eigenvalue theorem for linear operators in the space of population densities.

  • Fink JW, “Spatially structured stochastic models of adaptive dynamics”. Master’s thesis at the Department of Mathematics, University of Bonn, 2019.