Dataset Information

In vitro co-cultures of human gut bacterial species as predicted from co-occurrence network analysis.

ABSTRACT: Network analysis of large metagenomic datasets generated by current sequencing technologies can reveal significant co-occurrence patterns between microbial species of a biological community. These patterns can be analyzed in terms of pairwise combinations between all species comprising a community. Here, we construct a co-occurrence network for abundant microbial species encompassing the three dominant phyla found in human gut. This was followed by an in vitro evaluation of the predicted microbe-microbe co-occurrences, where we chose species pairs Bifidobacterium adolescentis and Bacteroides thetaiotaomicron, as well as Faecalibacterium prausnitzii and Roseburia inulinivorans as model organisms for our study. We then delineate the outcome of the co-cultures when equal distributions of resources were provided. The growth behavior of the co-culture was found to be dependent on the types of microbial species present, their specific metabolic activities, and resulting changes in the culture environment. Through this reductionist approach and using novel in vitro combinations of microbial species under anaerobic conditions, the results of this work will aid in the understanding and design of synthetic community formulations.

SUBMITTER: Das P

PROVIDER: S-EPMC5877883 | biostudies-other | 2018

REPOSITORIES: biostudies-other

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In vitro co-cultures of human gut bacterial species as predicted from co-occurrence network analysis.

Das Promi P Das Promi P Ji Boyang B Kovatcheva-Datchary Petia P Bäckhed Fredrik F Nielsen Jens J

PloS one 20180330 3

Network analysis of large metagenomic datasets generated by current sequencing technologies can reveal significant co-occurrence patterns between microbial species of a biological community. These patterns can be analyzed in terms of pairwise combinations between all species comprising a community. Here, we construct a co-occurrence network for abundant microbial species encompassing the three dominant phyla found in human gut. This was followed by an in vitro evaluation of the predicted microbe ...[more]

PMID: 29601608

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Project description:mRNA sequencing in bacteria is challenging due to the abundance of ribosomal rRNA that cannot be easily removed prior to sequencing. While commercially available kits target specific rRNA sequences found in defined lists of common bacterial species, they are frequently inefficient when applied to other divergent species, including those from environmental isolates. Similar to the commercial kits, other common techniques for rRNA depletion typically employ large probe sets that tile full-length rRNA sequences; however, such approaches are both time consuming and expensive when applied to multiple species or complex consortia of non-model microbes. To overcome these limitations, we present EMBR-seq+, which employs less than twenty target oligonucleotides per rRNA molecule, and builds upon our previous rRNA depletion approach, EMBR-seq, through the addition of an RNase H depletion step, to achieve rRNA removal efficiencies of up to 99%. First, we applied EMBR-seq+ to monocultures of Escherichia coli, Geobacter metallireducens, and Fibrobacter succinogenes strain UWB7 to deplete rRNA to approximately 1-7% of the sequencing reads, demonstrating that the new method can be easily extended to diverse bacterial species. Further, in more complex co-cultures between F. succinogenes strain UWB7 and anerobic fungal species, we applied EMBR-seq+ to deplete both bacterial and fungal rRNA, with an approximately 4-fold improved bacterial rRNA depletion efficiency compared to a previous report using a commercial kit, thereby showing that the method can be effectively translated to non-model microbial mixtures. Notably, we also demonstrate that for microbial species with poorly annotated genomes and unknown rRNA sequences, the RNase H depletion component of EMBR-seq+ enables rapid iterations in probe design without requiring to start experiments from total RNA each time, and was key for depleting fungal rRNA to enrich the bacterial mRNA readout in co-cultures. Finally, efficient depletion of rRNA enabled systematic quantification of the reprogramming of the bacterial transcriptome when cultured in the presence of the anerobic fungi, Anaeromyces robustus and Caecomyces churrovis. We observed that F. succinogenes strain UWB7 transcribes nearly 200 carbohydrate-active enzyme (CAZyme) genes in both monoculture and co-culture conditions, with several lignocellulose-degrading CAZymes downregulated in the presence of an anerobic gut fungus. This finding is consistent with the premise that bacteria and fungi specialize in different aspects of biomass breakdown, such that the presence of one regulates the CAZyme production of the other. This also supports previous findings that the fungi release excess reducing sugars in the supernatant, which benefits other members of the microbial community. Thus EMBR-seq+ provides a new and detailed perspective of a rumen microbiome model system by dramatically improving the efficiency of mRNA sequencing, and more generally also enables high-throughput, cost-effective and rapid quantification of the transcriptome to gain functional insights into less-studied and non-model microbial systems.

Dataset Information

In vitro co-cultures of human gut bacterial species as predicted from co-occurrence network analysis.

Publications

In vitro co-cultures of human gut bacterial species as predicted from co-occurrence network analysis.

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