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Species matter for predicting the functioning of evolving microbial communities – an eco-evolutionary model

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Title: Species matter for predicting the functioning of evolving microbial communities – an eco-evolutionary model
Authors: Barraclough, T
Item Type: Journal Article
Abstract: Humans depend on microbial communities for numerous ecosystem services such as global nutrient cycles, plant growth and their digestive health. Yet predicting dynamics and functioning of these complex systems is hard, making interventions to enhance functioning harder still. One simplifying approach is to assume that functioning can be predicted from the set of enzymes present in a community. Alternatively, ecological and evolutionary dynamics of species, which depend on how enzymes are packaged among species, might be vital for predicting community functioning. I investigate these alternatives by extending classical chemostat models of bacterial growth to multiple species that evolve in their use of chemical resources. Ecological interactions emerge from patterns of resource use, which change as species evolve in their allocation of metabolic enzymes. Measures of community functioning derive in turn from metabolite concentrations and bacterial density. Although the model shows considerable functional redundancy, species packaging does matter by introducing constraints on whether enzyme levels can reach optimum levels for the whole system. Evolution can either promote or reduce functioning compared to purely ecological models, depending on the shape of trade-offs in resource use. The model provides baseline theory for interpreting emerging data on evolution and functioning in real bacterial communities.
Issue Date: 19-Aug-2019
Date of Acceptance: 2-Aug-2019
URI: http://hdl.handle.net/10044/1/72743
DOI: https://dx.doi.org/10.1371/journal.pone.0218692
ISSN: 1932-6203
Publisher: Public Library of Science (PLoS)
Journal / Book Title: PLoS ONE
Volume: 14
Issue: 8
Copyright Statement: © 2019 Timothy G. Barraclough. 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.
Sponsor/Funder: The Leverhulme Trust
Natural Environment Research Council (NERC)
Funder's Grant Number: RF-2012-532
NE/K006215/1
Keywords: MD Multidisciplinary
General Science & Technology
Publication Status: Published
Article Number: e0218692
Appears in Collections:Faculty of Natural Sciences



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