"Systems biology of microbial evolution: a multiscale approach"

Abstract:

Microbial populations can adapt rapidly due to their vast supply of mutations.  To understand what makes these mutations adaptive, we need a systems-level approach that accounts for the wide range of biological traits that mutations can affect.  Using a combination of high-throughput experimental methods and computational modeling, I will discuss two systems-level approaches to microbial evolution.  First, I will show that both genetic and non-genetic mechanisms lead to substantial covariation in microbial life-history traits, such as the maximum growth rate in an environment and the lag time when transitioning between environments.  In particular, I will demonstrate the potential for tradeoffs in these traits and how such tradeoffs produce rich evolutionary and ecological phenomena, including stable coexistence of multiple strains and higher-order ecological effects.  Second, I will describe our development of a high-diversity DNA barcode library to track adaptation at high-resolution in bacterial populations with large numbers of simultaneously segregating mutations.  We apply this method to study adaptation to ultra-low concentrations of antibiotics, which are believed to be common in both clinical and natural environments.  We show that these ultra-low concentrations have distinct effects on evolution even without detectable resistance, and that adaptation to these conditions is highly predictable at the population level.  Furthermore, the fate of individual lineages can also be highly predictable in some conditions, depending on the relative contributions of standing genetic variation and de novo mutations to adaptation.  Altogether these examples demonstrate the power of systems-level approaches to elucidating the evolution of microbes.