Deciphering microbial interactions in synthetic human gut microbiome communities

Abstract

1The human gut microbiota comprises a dynamic ecological system that contributes significantly 2 to human health and disease. The ecological forces that govern community assembly and 3 stability in the gut microbiota remain unresolved. We developed a generalizable model-guided 4 framework to predict higher-order consortia from time-resolved measurements of lower-order 5 assemblages. This method was employed to decipher microbial interactions in a diverse 12-6 member human gut microbiome synthetic community. We show that microbial growth 7 parameters and pairwise interactions are the major drivers of multi-species community 8 dynamics, as opposed to context-dependent (conditional) interactions. The inferred microbial 9 interaction network as well as a top-down approach to community assembly pinpointed both 10 ecological driver and responsive species that were significantly modulated by microbial inter-

Contrasting Strategies: Human Eukaryotic Versus Bacterial Microbiome Research

“…Venturelli et al. ). Even if these interactions occur naturally in much more complex communities, such simplifications nonetheless allow the identification of relevant causal variables, and the direction of causality.…”

Pairing off: a bottom‐up approach to the human gut microbiome

“…Metagenomic analyses have facilitated a “top‐down” look at gut community composition (Human Microbiome Project Consortium, ), but “bottom‐up” approaches can be instrumental for understanding how these complex bacterial communities form, interact, and affect the health of their host. In their recent study, Venturelli et al () use a bottom‐up approach to community assembly by performing experiments with a synthetic gut microbial community and analyze the data using a predictive dynamic computational model. They find that pairwise interactions are sufficient to model multispecies community assembly and that certain pairwise motifs may be key to making a healthy microbiome resilient over time.…”

“…Although the authors’ model community is less complex and diverse than real gut microbiome communities, its 12 species span the major phyla of human‐associated intestinal bacteria. Venturelli et al () performed all possible two‐species combination experiments and tracked the relative abundances across time with multiplexed 16S sequencing and the total biomass with OD600 measurements. By fitting the pairwise dynamics to a generalized Lotka–Volterra model, they estimated the network of interactions (Fig ) and were able to accurately predict the majority of temporal changes in 11‐species (single‐species dropout communities) and 12‐species (full communities) communities.…”

“…The temporal dynamics of two‐species bacterial communities were used by Venturelli et al () to estimate the parameters of a Lotka–Volterra model. The parameters of this model represent growth rates, intra‐ and interspecies interactions, and the interspecies interaction coefficients can be used to visualize the microbial ecological network.…”

“… Analyses of how the gut microbiome develops and evolves through interspecies competition and cooperation have been lacking. In their recent work, Venturelli et al () build a synthetic gut bacterial community and predict its dynamics with a simple network of pairwise interactions.

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