Dataset Information

Deciphering microbial interactions in synthetic human gut microbiome communities.

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.

SUBMITTER: Venturelli OS

PROVIDER: S-EPMC6011841 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Deciphering microbial interactions in synthetic human gut microbiome communities.

Venturelli Ophelia S OS Carr Alex C AC Fisher Garth G Hsu Ryan H RH Lau Rebecca R Bowen Benjamin P BP Hromada Susan S Northen Trent T Arkin Adam P AP

Molecular systems biology 20180621 6

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 interact ...[more]

PMID: 29930200

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Project description:We investigated the requirement of 15 human butyrate-producing gut bacterial strains for eight B vitamins and the proteinogenic amino acids by a combination of genome sequence analysis and in vitro growth experiments. The Ruminococcaceae species Faecalibacterium prausnitzii and Subdoligranulum variabile were auxotrophic for most of the vitamins and the amino acid tryptophan. Within the Lachnospiraceae, most species were prototrophic for all amino acids and several vitamins, but biotin auxotrophy was widespread. In addition, most of the strains belonging to Eubacterium rectale and Roseburia spp., but few of the other Lachnospiraceae strains, were auxotrophic for thiamine and folate. Synthetic coculture experiments of five thiamine or folate auxotrophic strains with different prototrophic bacteria in the absence and presence of different vitamin concentrations were carried out. This demonstrated that cross-feeding between bacteria does take place and revealed differences in cross-feeding efficiency between prototrophic strains. Vitamin-independent growth stimulation in coculture compared to monococulture was also observed, in particular for F. prausnitzii A2-165, suggesting that it benefits from the provision of other growth factors from community members. The presence of multiple vitamin auxotrophies in the most abundant butyrate-producing Firmicutes species found in the healthy human colon indicates that these bacteria depend upon vitamins supplied from the diet or via cross-feeding from other members of the microbial community.IMPORTANCE Microbes in the intestinal tract have a strong influence on human health. Their fermentation of dietary nondigestible carbohydrates leads to the formation of health-promoting short-chain fatty acids, including butyrate, which is the main fuel for the colonic wall and has anticarcinogenic and anti-inflammatory properties. A good understanding of the growth requirements of butyrate-producing bacteria is important for the development of efficient strategies to promote these microbes in the gut, especially in cases where their abundance is altered. The demonstration of the inability of several dominant butyrate producers to grow in the absence of certain vitamins confirms the results of previous in silico analyses. Furthermore, establishing that strains prototrophic for thiamine or folate (butyrate producers and non-butyrate producers) were able to stimulate growth and affect the composition of auxotrophic synthetic communities suggests that the provision of prototrophic bacteria that are efficient cross feeders may stimulate butyrate-producing bacteria under certain in vivo conditions.

Project description:BackgroundMicrobiome studies commonly use 16S rRNA gene amplicon sequencing to characterize microbial communities. Errors introduced at multiple steps in this process can affect the interpretation of the data. Here we evaluate the accuracy of operational taxonomic unit (OTU) generation, taxonomic classification, alpha- and beta-diversity measures for different settings in QIIME, MOTHUR and a pplacer-based classification pipeline, using a novel software package: DECARD.ResultsIn-silico we generated 100 synthetic bacterial communities approximating human stool microbiomes to be used as a gold-standard for evaluating the colligative performance of microbiome analysis software. Our synthetic data closely matched the composition and complexity of actual healthy human stool microbiomes. Genus-level taxonomic classification was correctly done for only 50.4-74.8% of the source organisms. Miscall rates varied from 11.9 to 23.5%. Species-level classification was less successful, (6.9-18.9% correct); miscall rates were comparable to those of genus-level targets (12.5-26.2%). The degree of miscall varied by clade of organism, pipeline and specific settings used. OTU generation accuracy varied by strategy (closed, de novo or subsampling), reference database, algorithm and software implementation. Shannon diversity estimation accuracy correlated generally with OTU-generation accuracy. Beta-diversity estimates with Double Principle Coordinate Analysis (DPCoA) were more robust against errors introduced in processing than Weighted UniFrac. The settings suggested in the tutorials were among the worst performing in all outcomes tested.ConclusionsEven when using the same classification pipeline, the specific OTU-generation strategy, reference database and downstream analysis methods selection can have a dramatic effect on the accuracy of taxonomic classification, and alpha- and beta-diversity estimation. Even minor changes in settings adversely affected the accuracy of the results, bringing them far from the best-observed result. Thus, specific details of how a pipeline is used (including OTU generation strategy, reference sets, clustering algorithm and specific software implementation) should be specified in the methods section of all microbiome studies. Researchers should evaluate their chosen pipeline and settings to confirm it can adequately answer the research question rather than assuming the tutorial or standard-operating-procedure settings will be adequate or optimal.

Dataset Information

Deciphering microbial interactions in synthetic human gut microbiome communities.

Publications

Deciphering microbial interactions in synthetic human gut microbiome communities.

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