Evolution of Microbial Growth Traits Under Serial Dilution

Abstract

<jats:p>Selection of mutants in a microbial population depends on multiple cellular traits. In serial-dilution evolution experiments, three key traits are the lag time when transitioning from starvation to growth, the exponential growth rate, and the yield (number of cells per unit resource). Here, we investigate how these traits evolve in laboratory evolution experiments using a minimal model of population dynamics, where the only interaction between cells is competition for a single limiting resource. We find that the fixation probability of a beneficial mutation depends on a linear combination of its growth rate and lag time relative to its immediate ancestor, even under clonal interference. The relative selective pressure on growth rate and lag time is set by the dilution factor; a larger dilution factor favors the adaptation of growth rate over the adaptation of lag time. The model shows that yield, however, is under no direct selection. We also show how the adaptation speeds of growth and lag depend on experimental parameters and the underlying supply of mutations. Finally, we investigate the evolution of covariation between these traits across populations, which reveals that the population growth rate and lag time can evolve a nonzero correlation even if mutations have uncorrelated effects on the two traits. Altogether these results provide useful guidance to future experiments on microbial evolution.</jats:p>

Microbial population dynamics decouple growth response from environmental nutrient concentration

“…Testing this would require a distribution of K and g max measurements over a large mutant library in a single environment, which to our knowledge has not been done. However, even in the absence of an underlying correlation in mutation effects, such a tradeoff could still emerge across clones within a rapidly evolving population, at least transiently [75, 76]. Experiments with soil bacteria, designed by Velicer et al [77] to evolve a tradeoff in acid degradation, found that lineages adapting for 500 generations in a low concentration environment also become superior competitors in high concentrations and vice versa.…”

“…The factor D is known as the dilution factor and is the ratio of the total biomass at the end of the previous growth cycle (, where is the effective population yield; see Table S2 and Supplementary Information Sec. S3) and the total biomass at the beginning of the next growth cycle ( N 0 ) [76]: This constraint establishes the two possible protocols of serial transfers: either fixing the biomass bottleneck size N 0 (Fig. 3B, top panel) or fixing the dilution factor D (Fig.…”

Mutant fate in spatially structured populations on graphs: connecting models to experiments

“…of preexisting mutants. It would be interesting both theoretically and experimentally to consider longer evolutionary trajectories [58], and to include de novo mutants, which may appear at any time during the growth phase [59][60][61][62][63][64]. Further extensions include addressing environmental gradients [65][66][67][68], changing environments [69][70][71][72][73][74][75], possible deme extinctions [11], cooperative interactions [76][77][78], and connecting to models of expanding populations [79,80].…”

Evolution in microbial microcosms is highly parallel regardless of the presence of interacting species

“…Populations in our experiments were propagated using growth-dilution cycles, as commonly done in many evolution experiments 46 . In such a scenario, mutations that arise early in the cycle have a higher fixation probability 47 , and mutations that give benefit at the end of the cycle by increasing yield are not directly under selection 48 . At the beginning of each cycle, cell-densities are low and selection forces that depend on biotic interaction are likely only significant after cultures reach high densities toward the end of the cycle.…”