Biophysical constraints determine the selection of phenotypic fluctuations during directed evolution

TL;DR

This study investigates how biophysical constraints influence phenotypic fluctuations during directed evolution, showing that selection for fast migration reduces cell-to-cell variation and that these effects can be modeled and generalized.

Contribution

The paper combines experimental, genetic, and modeling approaches to reveal how biophysical constraints shape phenotypic fluctuations in evolution.

Findings

Selection for fast migration reduces phenotypic variability.

Genetic basis for fluctuation reduction identified through sequencing.

Model predicts fluctuation trends under different selection pressures.

Abstract

Phenotypes of individuals in a population of organisms are not fixed. Phenotypic fluctuations, which describe temporal variation of the phenotype of an individual or individual-to-individual variation across a population, are present in populations from microbes to higher animals. Phenotypic fluctuations can provide a basis for adaptation and be the target of selection. Here we present a theoretical and experimental investigation of the fate of phenotypic fluctuations in directed evolution experiments where phenotypes are subject to constraints. We show that selecting bacterial populations for fast migration through a porous environment drives a reduction in cell-to-cell variation across the population. Using sequencing and genetic engineering we study the genetic basis for this reduction in phenotypic fluctuations. We study the generality of this reduction by developing a simple, abstracted, numerical simulation model of the evolution of phenotypic fluctuations subject to constraints. Using this model we find that strong and weak selection generally lead respectively to increasing or decreasing cell-to-cell variation as a result of a bound on the selected phenotype under a wide range of parameters. However, other behaviors are also possible, and we describe the outcome of selection simulations for different model parameters and suggest future experiments. We analyze the mechanism of the observed reduction of phenotypic fluctuations in our experimental system, discuss the relevance of our abstract model to the experiment and explore its broader implications for evolution.