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Inferring metabolic mechanisms of interaction within a defined gut microbiota

Inferring metabolic mechanisms of interaction within a defined gut microbiota
Inferring metabolic mechanisms of interaction within a defined gut microbiota

The diversity and number of species present within microbial communities create the potential for a multitude of interspecies metabolic interactions. Here, we develop, apply, and experimentally test a framework for inferring metabolic mechanisms associated with interspecies interactions. We perform pairwise growth and metabolome profiling of co-cultures of strains from a model mouse microbiota. We then apply our framework to dissect emergent metabolic behaviors that occur in co-culture. Based on one of the inferences from this framework, we identify and interrogate an amino acid cross-feeding interaction and validate that the proposed interaction leads to a growth benefit in vitro. Our results reveal the type and extent of emergent metabolic behavior in microbial communities composed of gut microbes. We focus on growth-modulating interactions, but the framework can be applied to interspecies interactions that modulate any phenotype of interest within microbial communities.

Animals, Clostridium/physiology, Coculture Techniques, Computer Simulation, Eubacterium/physiology, Gastrointestinal Microbiome/physiology, Humans, Lactobacillus/physiology, Metabolic Networks and Pathways, Metabolome, Mice, Microbial Interactions, Models, Biological, Models, Theoretical, Principal Component Analysis
2405-4712
245-257.e7
Medlock, Gregory L.
41c918e5-fee8-4a6e-a422-e5f09ccc8888
Carey, Maureen A.
6ee03fd8-d9fc-45bd-998e-9b3bdf9ac0b7
McDuffie, Dennis G.
e76585f6-0cef-4a6b-918f-1fa8febba262
Mundy, Michael B.
96927550-a674-4b5f-81f5-08a88530c4c9
Giallourou, Natasa
b5891ea7-98d4-49d7-b883-2c57ca2d962a
Swann, Jonathan R.
7c11a66b-f4b8-4dbf-aa17-ad8b0561b85c
Kolling, Glynis L.
502c0b3d-ac97-4850-8c38-890da2124e13
Papin, Jason A.
beec0af9-791c-4f7a-9aeb-9926049bd9d0
Medlock, Gregory L.
41c918e5-fee8-4a6e-a422-e5f09ccc8888
Carey, Maureen A.
6ee03fd8-d9fc-45bd-998e-9b3bdf9ac0b7
McDuffie, Dennis G.
e76585f6-0cef-4a6b-918f-1fa8febba262
Mundy, Michael B.
96927550-a674-4b5f-81f5-08a88530c4c9
Giallourou, Natasa
b5891ea7-98d4-49d7-b883-2c57ca2d962a
Swann, Jonathan R.
7c11a66b-f4b8-4dbf-aa17-ad8b0561b85c
Kolling, Glynis L.
502c0b3d-ac97-4850-8c38-890da2124e13
Papin, Jason A.
beec0af9-791c-4f7a-9aeb-9926049bd9d0

Medlock, Gregory L., Carey, Maureen A., McDuffie, Dennis G., Mundy, Michael B., Giallourou, Natasa, Swann, Jonathan R., Kolling, Glynis L. and Papin, Jason A. (2018) Inferring metabolic mechanisms of interaction within a defined gut microbiota. Cell Systems, 7 (3), 245-257.e7. (doi:10.1016/j.cels.2018.08.003).

Record type: Article

Abstract

The diversity and number of species present within microbial communities create the potential for a multitude of interspecies metabolic interactions. Here, we develop, apply, and experimentally test a framework for inferring metabolic mechanisms associated with interspecies interactions. We perform pairwise growth and metabolome profiling of co-cultures of strains from a model mouse microbiota. We then apply our framework to dissect emergent metabolic behaviors that occur in co-culture. Based on one of the inferences from this framework, we identify and interrogate an amino acid cross-feeding interaction and validate that the proposed interaction leads to a growth benefit in vitro. Our results reveal the type and extent of emergent metabolic behavior in microbial communities composed of gut microbes. We focus on growth-modulating interactions, but the framework can be applied to interspecies interactions that modulate any phenotype of interest within microbial communities.

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Accepted/In Press date: 3 August 2018
e-pub ahead of print date: 5 September 2018
Published date: 26 September 2018
Keywords: Animals, Clostridium/physiology, Coculture Techniques, Computer Simulation, Eubacterium/physiology, Gastrointestinal Microbiome/physiology, Humans, Lactobacillus/physiology, Metabolic Networks and Pathways, Metabolome, Mice, Microbial Interactions, Models, Biological, Models, Theoretical, Principal Component Analysis

Identifiers

Local EPrints ID: 440788
URI: http://eprints.soton.ac.uk/id/eprint/440788
ISSN: 2405-4712
PURE UUID: f9b1c0f2-7055-4111-9433-9008403abeb8
ORCID for Jonathan R. Swann: ORCID iD orcid.org/0000-0002-6485-4529

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Date deposited: 18 May 2020 16:38
Last modified: 17 Mar 2024 04:00

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Contributors

Author: Gregory L. Medlock
Author: Maureen A. Carey
Author: Dennis G. McDuffie
Author: Michael B. Mundy
Author: Natasa Giallourou
Author: Glynis L. Kolling
Author: Jason A. Papin

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