Bacterial fitness landscapes stratify based on proteome allocation associated with discrete aero-types

Ke Chen, Amitesh Anand, Connor Olson, Troy E. Sandberg, Ye Gao, Nathan Mih, Bernhard O. Palsson*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

The fitness landscape is a concept commonly used to describe evolution towards optimal phenotypes. It can be reduced to mechanistic detail using genome-scale models (GEMs) from systems biology. We use recently developed GEMs of Metabolism and protein Expression (ME-models) to study the distribution of Escherichia coli phenotypes on the rate-yield plane. We found that the measured phenotypes distribute non-uniformly to form a highly stratified fitness landscape. Systems analysis of ME-model simulations suggest that this stratification results from discrete ATP generation strategies. Accordingly, we define “aero-types”, a phenotypic trait that characterizes how a balanced proteome can achieve a given growth rate by modulating 1) the relative utilization of oxidative phosphorylation, glycolysis, and fermentation pathways; and 2) the differential employment of electron-transport-chain enzymes. This global, quantitative, and mechanistic systems biology interpretation of fitness landscape formed upon proteome allocation offers a fundamental understanding of bacterial physiology and evolution dynamics.

Original languageEnglish
Article numbere1008596
JournalPLOS Computational Biology
Volume17
Issue number1
Number of pages25
ISSN1553-734X
DOIs
Publication statusPublished - 19 Jan 2021

Bibliographical note

Publisher Copyright:
Copyright: © 2021 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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