Abstract
BackgroundThe extent to which deterministic rather than stochastic processes guide gut bacteria co-existence and ultimately their assembling into a community remains largely unknown. Co-occurrence networks of bacterial associations offer a powerful approach to begin exploring gut microbial community structure, maintenance and dynamics, beyond compositional aspects alone. Here we used an iconic model system, the cichlid fishes, with their multiple lake assemblages and extraordinary ecological diversity, to investigate a) patterns of microbial associations that were robust to major phylogeographical variables, and b) changes in microbial network structure along dietary shifts. We tackled these objectives using the large gut microbiota sequencing dataset available (nine lakes from Africa and America), building geographical and diet-specific networks and performing comparative network analyses.ResultsMajor findings indicated that lake and continental microbial networks were highly resembling in global topology and node taxonomic composition, despite the heterogeneity of the samples. A small fraction of the observed co-occurrences among operational taxonomic units (OTUs) was conserved across all lake assemblages. These were all positive associations and involved OTUs within the genera Cetobacterium and Turicibacter and several OTUs belonging to the families of Peptostreptococcaceae and Clostridiaceae (order Clostridiales). Mapping of diet contribution on the African Lake Tanganyika network (therefore excluding the geographic variable) revealed a clear community change from carnivores (C) to omnivores (O) to herbivores (H). Node abundances and effect size for pairwise comparisons between diets supported a strong contrasting pattern between C and H. Moreover, diet-associated nodes in H formed complex modules of positive interactions among taxonomically diverse bacteria (mostly Verrucomicrobia and Proteobacteria).ConclusionsConservation of microbial network topologies and specific bacterial associations across distinct lake assemblages point to a major host-associated effect and potential deterministic processes shaping the cichlid gut microbiota. While the origin and biological relevance of these common associations remain unclear, their persistence suggests an important functional role in the cichlid gut. Among the very diverse cichlids of L. Tanganyika, diet nonetheless represents a major driver of microbial community changes. By intersecting results from predictive network inferences and experimental trials, future studies will be directed to explore the strength of these associations, predict the outcome of community alterations driven by diet and ultimately help understanding the role of gut microbiota in cichlid trophic diversification.
Highlights
The extent to which deterministic rather than stochastic processes guide gut bacteria co-existence and their assembling into a community remains largely unknown
By intersecting results from predictive network inferences and experimental trials, future studies will be directed to explore the strength of these associations, predict the outcome of community alterations driven by diet and help understanding the role of gut microbiota in cichlid trophic diversification
Comparative analyses of lake and continental networks We used the CoNet ensemble approach based on four correlation measures (Spearman, Pearson, Bray-Curtis and Kullback-Leibler) to infer robust bacterial association patterns in the cichlid gut
Summary
The extent to which deterministic rather than stochastic processes guide gut bacteria co-existence and their assembling into a community remains largely unknown. We used an iconic model system, the cichlid fishes, with their multiple lake assemblages and extraordinary ecological diversity, to investigate a) patterns of microbial associations that were robust to major phylogeographical variables, and b) changes in microbial network structure along dietary shifts. We tackled these objectives using the large gut microbiota sequencing dataset available (nine lakes from Africa and America), building geographical and diet-specific networks and performing comparative network analyses. The assumption is that a non-random pattern is shaped by ecological processes driving coexistence (e.g. cross-feeding or partial niche overlap) or exclusion (e.g. competition or predation) [9, 10]
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