A Quantitative Test of Population Genetics Using Spatio-Genetic Patterns in Bacterial Colonies

TL;DR

This study empirically tests and validates spatial population genetics models using bacterial colonies, demonstrating that these models can accurately predict genetic diversity and migration patterns in microbial biofilms.

Contribution

It provides the first quantitative validation of spatial population genetics models with bacterial experiments, linking theory with empirical data.

Findings

Spatio-genetic patterns are well described by an extended stepping-stone model.

Genetic diversity at the colony edge predicts cell migration.

The model estimates effective population size at the expansion front.

Abstract

It is widely accepted that population genetics theory is the cornerstone of evolutionary analyses. Empirical tests of the theory, however, are challenging because of the complex relationships between space, dispersal, and evolution. Critically, we lack quantitative validation of the spatial models of population genetics. Here we combine analytics, on and off-lattice simulations, and experiments with bacteria to perform quantitative tests of the theory. We study two bacterial species, the gut microbe Escherichia coli and the opportunistic pathogen Pseudomonas aeruginosa, and show that spatio-genetic patterns in colony biofilms of both species are accurately described by an extension of the one-dimensional stepping-stone model. We use one empirical measure, genetic diversity at the colony periphery, to parameterize our models and show that we can then accurately predict another key variable: the degree of short-range cell migration along an edge. Moreover, the model allows us to estimate other key parameters including effective population size (density) at the expansion frontier. While our experimental system is a simplification of natural microbial community, we argue it is a proof of principle that the spatial models of population genetics can quantitatively capture organismal evolution.