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.

Integrated metabolic modeling, culturing and transcriptomics explains enhanced virulence ofV. choleraeduring co-infection with ETEC

“…RNAseq thus confirmed that there is an emergent behavior in the co-cultures and that the observed changes were not just due to variations in inoculum composition or the lag phase 67 . Taken together, our integrated modeling, co-culturing and transcriptomics approach provided mechanistic insights into the observed increase in cholera infection severity in dual infections with ETEC where ETEC co-infection results in an increased growth of V. cholerae due to expanded metabolic capabilities enabled by ETEC.…”

“…To assess the level of genetic perturbations due to addition of ETEC as an interaction partner to V. cholerae cultures, we conducted a dual RNAseq analysis 64-67 of V. cholerae co-cultures (Figure 1, Step 4) with each of the two ETEC strains (E36 or E616). We then compared the gene expression levels for each pathogen to its single-culture (see methods section and Tables S7-S10 at https://github.com/alyamahmoud/coinfection_modeling/blob/master/supplementary_material/supplementary_tables.xlsx).…”

Bifidobacterium breveUCC2003 exopolysaccharide modulates the early life microbiota by acting as a dietary substrate

“…Another possible interaction is via predicted production of formate by Tyzzerella , that may be metabolised by Faecalibacterium , as has been described in an in silico biofilm model [42] ( Fig S8) . Delineating intricate and complex cross-feeding relationships is difficult and cannot be predicted from non-community cultures, as strains grow, and behave differently when grown in co-culture, compared to those grown individually [43]. Further studies, possible utilising isotope labelling, would be required for targeted identification of metabolites impacting these important EPS-associated cross-feeding networks [44].…”

Stochasticity in microbiology: managing unpredictability to reach the Sustainable Development Goals

“…These communities can range from very few species to complex aggregates of trillions of cells and go through stages of community succession (Lyautey et al , 2005; Datta et al , 2016; Wright et al , 2019). The complexity of community dynamics, even in low diverse communities, can be illustrated through the interactions of three common gut bacteria cultivated under well‐controlled in vitro conditions (D'Hoe et al , 2018). The results showed the difficulty in predicting the winner without a predictive model, which should include both the internal metabolism of community members, as well as their response to interaction partners.…”