Dataset Information

Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community.

ABSTRACT: 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.

SUBMITTER: D'hoe K

PROVIDER: S-EPMC6237439 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community.

D'hoe Kevin K Vet Stefan S Faust Karoline K Moens Frédéric F Falony Gwen G Gonze Didier D Lloréns-Rico Verónica V Gelens Lendert L Danckaert Jan J De Vuyst Luc L Raes Jeroen J

eLife 20181016

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. System ...[more]

PMID: 30322445

Similar Datasets

Project description:Gene essentiality is altered during polymicrobial infections. Nevertheless, most studies rely on single-species infections to assess pathogen gene essentiality. Here, we use genome-scale metabolic models (GEMs) to explore the effect of coinfection of the diarrheagenic pathogen Vibrio cholerae with another enteric pathogen, enterotoxigenic Escherichia coli (ETEC). Model predictions showed that V. cholerae metabolic capabilities were increased due to ample cross-feeding opportunities enabled by ETEC. This is in line with increased severity of cholera symptoms known to occur in patients with dual infections by the two pathogens. In vitro coculture systems confirmed that V. cholerae growth is enhanced in cocultures relative to single cultures. Further, expression levels of several V. cholerae metabolic genes were significantly perturbed as shown by dual RNA sequencing (RNAseq) analysis of its cocultures with different ETEC strains. A decrease in ETEC growth was also observed, probably mediated by nonmetabolic factors. Single gene essentiality analysis predicted conditionally independent genes that are essential for the pathogen's growth in both single-infection and coinfection scenarios. Our results reveal growth differences that are of relevance to drug targeting and efficiency in polymicrobial infections.IMPORTANCE Most studies proposing new strategies to manage and treat infections have been largely focused on identifying druggable targets that can inhibit a pathogen's growth when it is the single cause of infection. In vivo, however, infections can be caused by multiple species. This is important to take into account when attempting to develop or use current antibacterials since their efficacy can change significantly between single infections and coinfections. In this study, we used genome-scale metabolic models (GEMs) to interrogate the growth capabilities of Vibrio cholerae in single infections and coinfections with enterotoxigenic E. coli (ETEC), which cooccur in a large fraction of diarrheagenic patients. Coinfection model predictions showed that V. cholerae growth capabilities are enhanced in the presence of ETEC relative to V. cholerae single infection, through cross-fed metabolites made available to V. cholerae by ETEC. In vitro, cocultures of the two enteric pathogens further confirmed model predictions showing an increased growth of V. cholerae in coculture relative to V. cholerae single cultures while ETEC growth was suppressed. Dual RNAseq analysis of the cocultures also confirmed that the transcriptome of V. cholerae was distinct during coinfection compared to single-infection scenarios where processes related to metabolism were significantly perturbed. Further, in silico gene-knockout simulations uncovered discrepancies in gene essentiality for V. cholerae growth between single infections and coinfections. Integrative model-guided analysis thus identified druggable targets that would be critical for V. cholerae growth in both single infections and coinfections; thus, designing inhibitors against those targets would provide a broader spectrum of coverage against cholera infections.

Dataset Information

Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community.

Publications

Integrated culturing, modeling and transcriptomics uncovers complex interactions and emergent behavior in a three-species synthetic gut community.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure