Year: 2020
Type: article
Abstract: 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.
Source: Genetics
Authors: Jie Lin, Michael Manhart, Ariel Amir
Institutions: Harvard University, ETH Zurich, Institute of Integrative Biology
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: bronze
Awards: G1020486556, G3366412161, CAREER: Stochastic Effects in the Microbial Cell Cycle: From Single-cell Level Variability to Population Growth, G6671297155, Molecular mechanisms and evolutionary consequences of pleiotropy and single-cell variation in microbial growth, Characterizing the Co-evolution of Protein-protein and Regulatory Interactions, Materials Research Science and Engineering Center, G8954024240
OpenAlex ID: W3022103416