eLifeBioinformaticsPeer-reviewed journal article
Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a synthetic gut community
Kevin D’hoe, Stefan VetiD, Karoline FaustiD, Frédéric Moens, Gwen FalonyiD, Didier GonzeiD, Verónica Lloréns‐RicoiD, Lendert GelensiD, Jan DanckaertiD, Luc De VuystiD, Jeroen RaesiD
Abstract
Whereas the composition of the human gut microbiome is relatively well resolved, predictive understanding of its response to perturbations such as diet shifts 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 in well-controlled conditions in vitro. We then explored species interactions by performing all mono- and pair-wise fermentation experiments and quantified with a mechanistic community model how well tri-culture dynamics was predicted from mono-culture data. With the model as a reference, we demonstrated that species 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 in simulations that dominance in tri-culture sensitively depends on initial conditions. Our work has important implications for gut microbial community modeling as well as ecological interaction detection from batch cultures.
- organism: human
- assay: bulk RNA-seq
- research focus: cell-cell communication
- research focus: benchmarking
- approach: statistical model
- Citations
- 95
- FWCI
- 4.27
- Field percentile
- top 4%
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