Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community
- KU Leuven, Belgium
- Vrije Universiteit Brussel, Belgium
- Université Libre de Bruxelles, Belgium
Abstract
Whereas the composition of the human gut microbiome is well resolved, predictive understanding 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 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 depended on initial conditions. Our work has important implications for gut microbial community modeling as well as ecological interaction detection from batch cultures.
Data availability
RNA-seq results have been deposited to the Short Read Archive under the study identifier SRP136465 (https://www.ncbi.nlm.nih.gov/sra/SRP136465). Fermentation data have been submitted to Dryad (doi:10.5061/dryad.g83f29f). Source data has been provided for Figures 3 to 6.
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Data from: Integrated culturing, modeling and transcriptomics uncovers emergent behavior in a synthetic gut communityAvailable at Dryad Digital Repository under a CC0 Public Domain Dedication.
Article and author information
Author details
Funding
Vrije Universiteit Brussel
- Kevin D'hoe
Fonds Wetenschappelijk Onderzoek
- Kevin D'hoe
- Karoline Faust
- Frédéric Moens
- Verónica Lloréns-Rico
Interuniversity Institute of Bioinformatics in Brussels
- Stefan Vet
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Xochitl Morgan, University of Otago, New Zealand
Version history
- Received: March 29, 2018
- Accepted: October 4, 2018
- Accepted Manuscript published: October 16, 2018 (version 1)
- Version of Record published: November 15, 2018 (version 2)
- Version of Record updated: November 4, 2019 (version 3)
Copyright
© 2018, D'hoe et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community
eLife 7:e37090.
https://doi.org/10.7554/eLife.37090
Further reading
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- Computational and Systems Biology
Transcriptomic profiling became a standard approach to quantify a cell state, which led to accumulation of huge amount of public gene expression datasets. However, both reuse of these datasets or analysis of newly generated ones requires significant technical expertise. Here we present Phantasus - a user-friendly web-application for interactive gene expression analysis which provides a streamlined access to more than 96000 public gene expression datasets, as well as allows analysis of user-uploaded datasets. Phantasus integrates an intuitive and highly interactive JavaScript-based heatmap interface with an ability to run sophisticated R-based analysis methods. Overall Phantasus allows users to go all the way from loading, normalizing and filtering data to doing differential gene expression and downstream analysis. Phantasus can be accessed on-line at https://alserglab.wustl.edu/phantasus or can be installed locally from Bioconductor (https://bioconductor.org/packages/phantasus). Phantasus source code is available at https://github.com/ctlab/phantasus under MIT license.
