Deciphering microbial interactions in synthetic human gut microbiome communities. Issue 6 (21st June 2018)

• Record Type: Journal Article
• Authors: Venturelli, Ophelia S; Carr, Alex V; Fisher, Garth; Hsu, Ryan H; Lau, Rebecca; Bowen, Benjamin P; Hromada, Susan; Northen, Trent; Arkin, Adam P
• Is Part Of: Molecular systems biology. Volume 14:Issue 6(2018)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2018-06-21
• Subjects: ecology -- human gut microbiome -- mathematical modeling -- microbial community -- microbial interaction; Molecular biology -- Periodicals; Systems biology -- Periodicals; 572.8
• DOI: 10.15252/msb.20178157
• Languages: English
• ISSNs: 1744-4292

Abstract

Abstract: The ecological forces that govern the assembly and stability of the human gut microbiota remain unresolved. We developed a generalizable model‐guided framework to predict higher‐dimensional consortia from time‐resolved measurements of lower‐order assemblages. This method was employed to decipher microbial interactions in a diverse human gut microbiome synthetic community. We show that pairwise interactions are major drivers of multi‐species community dynamics, as opposed to higher‐order interactions. The inferred ecological network exhibits a high proportion of negative and frequent positive interactions. Ecological drivers and responsive recipient species were discovered in the network. Our model demonstrated that a prevalent positive and negative interaction topology enables robust coexistence by implementing a negative feedback loop that balances disparities in monospecies fitness levels. We show that negative interactions could generate history‐dependent responses of initial species proportions that frequently do not originate from bistability. Measurements of extracellular metabolites illuminated the metabolic capabilities of monospecies and potential molecular basis of microbial interactions. In sum, these methods defined the ecological roles of major human‐associated intestinal species and illuminated design principles of microbial communities. Synopsis: Analysis of microbial interactions in a synthetic human gut microbiome community shows that pairwise microbial interactions are major drivers of multi‐species community dynamics. The study reveals ecological drivers, metabolite hub species and ecologically sensitive organisms in the network. A data‐driven pipeline is used to construct a predictive dynamic model of a diverse anaerobic human gut microbiome community. Design principles of stable coexistence and history‐dependence are elucidated. Ecological roles and metabolite profiles are analyzed for each organism. The study highlights challenges in using phylogenetic and exo‐metabolomic "signals" to predict microbial interactions and community functions. Abstract : Analysis of microbial interactions in a synthetic human gut microbiome community shows that pairwise microbial interactions are major drivers of multi‐species community dynamics. The study reveals ecological drivers, metabolite hub species and ecologically sensitive organisms in the network.