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Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community
The composition of the human gut microbiome is well resolved, but predictive understanding of its dynamics is still lacking. Here, we followed a bottom-up strategy to explore human gut community dynamics: we established a synthetic community composed of three representative human gut isolates (Roseb...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237439/ https://www.ncbi.nlm.nih.gov/pubmed/30322445 http://dx.doi.org/10.7554/eLife.37090 |
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author | D'hoe, Kevin Vet, Stefan Faust, Karoline Moens, Frédéric Falony, Gwen Gonze, Didier Lloréns-Rico, Verónica Gelens, Lendert Danckaert, Jan De Vuyst, Luc Raes, Jeroen |
author_facet | D'hoe, Kevin Vet, Stefan Faust, Karoline Moens, Frédéric Falony, Gwen Gonze, Didier Lloréns-Rico, Verónica Gelens, Lendert Danckaert, Jan De Vuyst, Luc Raes, Jeroen |
author_sort | D'hoe, Kevin |
collection | PubMed |
description | The composition of the human gut microbiome is well resolved, but predictive understanding of its dynamics is still lacking. Here, we followed a bottom-up strategy to explore human gut community dynamics: we established a synthetic community composed of three representative human gut isolates (Roseburia intestinalis L1-82, Faecalibacterium prausnitzii A2-165 and Blautia hydrogenotrophica S5a33) and explored their interactions under well-controlled conditions in vitro. Systematic mono- and pair-wise fermentation experiments confirmed competition for fructose and cross-feeding of formate. We quantified with a mechanistic model how well tri-culture dynamics was predicted from mono-culture data. With the model as reference, we demonstrated that strains grown in co-culture behaved differently than those in mono-culture and confirmed their altered behavior at the transcriptional level. In addition, we showed with replicate tri-cultures and simulations that dominance in tri-culture sensitively depends on the initial conditions. Our work has important implications for gut microbial community modeling as well as for ecological interaction detection from batch cultures. |
format | Online Article Text |
id | pubmed-6237439 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-62374392018-11-19 Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community D'hoe, Kevin Vet, Stefan Faust, Karoline Moens, Frédéric Falony, Gwen Gonze, Didier Lloréns-Rico, Verónica Gelens, Lendert Danckaert, Jan De Vuyst, Luc Raes, Jeroen eLife Computational and Systems Biology The composition of the human gut microbiome is well resolved, but predictive understanding of its dynamics is still lacking. Here, we followed a bottom-up strategy to explore human gut community dynamics: we established a synthetic community composed of three representative human gut isolates (Roseburia intestinalis L1-82, Faecalibacterium prausnitzii A2-165 and Blautia hydrogenotrophica S5a33) and explored their interactions under well-controlled conditions in vitro. Systematic mono- and pair-wise fermentation experiments confirmed competition for fructose and cross-feeding of formate. We quantified with a mechanistic model how well tri-culture dynamics was predicted from mono-culture data. With the model as reference, we demonstrated that strains grown in co-culture behaved differently than those in mono-culture and confirmed their altered behavior at the transcriptional level. In addition, we showed with replicate tri-cultures and simulations that dominance in tri-culture sensitively depends on the initial conditions. Our work has important implications for gut microbial community modeling as well as for ecological interaction detection from batch cultures. eLife Sciences Publications, Ltd 2018-10-16 /pmc/articles/PMC6237439/ /pubmed/30322445 http://dx.doi.org/10.7554/eLife.37090 Text en © 2018, D'hoe et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Computational and Systems Biology D'hoe, Kevin Vet, Stefan Faust, Karoline Moens, Frédéric Falony, Gwen Gonze, Didier Lloréns-Rico, Verónica Gelens, Lendert Danckaert, Jan De Vuyst, Luc Raes, Jeroen Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community |
title | Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community |
title_full | Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community |
title_fullStr | Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community |
title_full_unstemmed | Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community |
title_short | Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community |
title_sort | integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community |
topic | Computational and Systems Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6237439/ https://www.ncbi.nlm.nih.gov/pubmed/30322445 http://dx.doi.org/10.7554/eLife.37090 |
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