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dc.contributor.authorThommes, Meghanen_US
dc.contributor.authorWang, Taiyaoen_US
dc.contributor.authorZhao, Qien_US
dc.contributor.authorPaschalidis, Ioannis Ch.en_US
dc.contributor.authorSegre, Danielen_US
dc.date2018-10-29
dc.date.accessioned2020-01-28T15:15:44Z
dc.date.available2020-01-28T15:15:44Z
dc.date.issued2019
dc.identifier.citationMeghan Thommes, Taiyao Wang, Qi Zhao, Ioannis Ch Paschalidis, Daniel Segre. 2019. "Designing metabolic division of labor in microbial communities." mSystems, https://doi.org/10.1128/mSystems.00263-18
dc.identifier.urihttps://hdl.handle.net/2144/39181
dc.description.abstractMicrobes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A “gedanken” (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor.en_US
dc.language.isoen_US
dc.relation.ispartofmSystems
dc.rightsAttribution 4.0 Internationalen_US
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectDivision of laboren_US
dc.subjectFlux balance analysisen_US
dc.subjectGenome-scale stoichiometric modelsen_US
dc.subjectMetabolic networksen_US
dc.subjectMicrobial communitiesen_US
dc.subjectMicrobiomeen_US
dc.subjectMixed-integer linear programmingen_US
dc.subjectResource allocationen_US
dc.subjectSynthetic ecologyen_US
dc.titleDesigning metabolic division of labor in microbial communitiesen_US
dc.typeArticleen_US
dc.description.versionPublished versionen_US
dc.identifier.doi10.1128/mSystems.00263-18
pubs.elements-sourcemanual-entryen_US
pubs.notesin press optvolume: optnumber: optpages: optmonth:en_US
pubs.notesEmbargo: Not knownen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Biologyen_US
pubs.organisational-groupBoston University, College of Engineeringen_US
pubs.organisational-groupBoston University, College of Engineering, Department of Electrical & Computer Engineeringen_US
pubs.publication-statusAccepteden_US
dc.identifier.orcid0000-0002-3343-2913 (Paschalidis, Ioannis Ch)
dc.identifier.orcid0000-0003-4859-1914 (Segre, Daniel)
dc.identifier.mycv454801


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International