Microbial phenotypic heterogeneity in response to a metabolic toxin: Continuous, dynamically shifting distribution of formaldehyde tolerance in Methylobacterium extorquens populations.

Jessica A Lee,Shahla Nemati,Jannell V Bazurto,Benjamin J Ridenhour,Christopher J Marx,Siavash Riazi,Andreas E Vasdekis,Christopher H Remien,Mark L Siegal

doi:10.1371/journal.pgen.1008458

Jessica A Lee, Shahla Nemati + Show 7 more

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https://doi.org/10.1371/journal.pgen.1008458

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Abstract

While microbiologists often make the simplifying assumption that genotype determines phenotype in a given environment, it is becoming increasingly apparent that phenotypic heterogeneity (in which one genotype generates multiple phenotypes simultaneously even in a uniform environment) is common in many microbial populations. The importance of phenotypic heterogeneity has been demonstrated in a number of model systems involving binary phenotypic states (e.g., growth/non-growth); however, less is known about systems involving phenotype distributions that are continuous across an environmental gradient, and how those distributions change when the environment changes. Here, we describe a novel instance of phenotypic diversity in tolerance to a metabolic toxin within wild-type populations of Methylobacterium extorquens, a ubiquitous phyllosphere methylotroph capable of growing on the methanol periodically released from plant leaves. The first intermediate in methanol metabolism is formaldehyde, a potent cellular toxin that is lethal in high concentrations. We have found that at moderate concentrations, formaldehyde tolerance in M. extorquens is heterogeneous, with a cell's minimum tolerance level ranging between 0 mM and 8 mM. Tolerant cells have a distinct gene expression profile from non-tolerant cells. This form of heterogeneity is continuous in terms of threshold (the formaldehyde concentration where growth ceases), yet binary in outcome (at a given formaldehyde concentration, cells either grow normally or die, with no intermediate phenotype), and it is not associated with any detectable genetic mutations. Moreover, tolerance distributions within the population are dynamic, changing over time in response to growth conditions. We characterized this phenomenon using bulk liquid culture experiments, colony growth tracking, flow cytometry, single-cell time-lapse microscopy, transcriptomics, and genome resequencing. Finally, we used mathematical modeling to better understand the processes by which cells change phenotype, and found evidence for both stochastic, bidirectional phenotypic diversification and responsive, directed phenotypic shifts, depending on the growth substrate and the presence of toxin.

Highlights

IntroductionEven in seemingly simple unicellular organisms, phenotype is not always the straightforward product of genotype and environment; cells with identical genotypes in identical environments may demonstrate cell-to-cell diversity in the expression of any of a number of traits
We demonstrate that the distribution of phenotypes changes in different growth conditions, and we use mathematical modeling to show that cells may change their phenotype either randomly or in a particular direction in response to the environment
Our work expands our understanding of how a bacterial cell’s genome, family history, and environment all contribute to its behavior, with implications for the diverse situations in which we care to understand the growth of any single-celled populations

Summary

Introduction

Even in seemingly simple unicellular organisms, phenotype is not always the straightforward product of genotype and environment; cells with identical genotypes in identical environments may demonstrate cell-to-cell diversity in the expression of any of a number of traits. Overlooked in everyday microbiology experiments, the phenomenon of cell-to-cell phenotypic heterogeneity has drawn increasing attention in recent decades both from a systems biology perspective and from an evolutionary perspective, as well as for its consequences to applied fields such as medicine (e.g., antibiotic persistence [1]; cancer cell drug tolerance [2,3]) and biological engineering [4]. All genes might be expected to be expressed at slightly different levels among different cells [5,6,7], and historical contingency (e.g., pole age, asymmetrical division of macromolecules) can create inherent diversity within microbial populations, independent of signals from the environment [8,9,10]. Genes involved in stress response and in metabolism have been found to show higher heterogeneity in expression than those in other pathways [12], and many of the well-understood examples of binary phenotypes involve stress response (antibiotic persistence [13]; sporulation [14]), or carbon transport and use

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