Coupled Microbiome Analyses Highlights Relative Functional Roles of Bacteria in a Bivalve Hatchery

Abstract

Background: Microbial communities are ubiquitous throughout ecosystems and are commensal with hosts across taxonomic boundaries. Environmental and species-specific microbiomes are instrumental in maintaining ecosystem and host health, respectively. The introduction of pathogenic microbes that shift microbiome community structure can lead to illness and death. Understanding the dynamics of microbiomes across a diversity of environments and hosts will help us to better understand which taxa forecast survival and which forecast mortality events. Results: We characterized the microbiome in the water of a commercial shellfish hatchery in Washington state, USA, where the hatchery has been plagued by recurring and unexplained larval mortality events. By applying the complementary methods of metagenomics and metaproteomics we were able to more fully characterize the bacterial taxa in the hatchery at high (pH 8.2) and low (pH 7.1) pH that were metabolically active versus present but not contributing metabolically. There were shifts in the taxonomy and functional profile of the microbiome between pH and over time. Based on detected metagenomic reads and metaproteomic peptide spectral matches, some taxa were more metabolically active than expected based on presence alone (Deltaproteobacteria, Alphaproteobacteria) and some were less metabolically active than expected (e.g., Betaproteobacteria, Cytophagia). There was little correlation between potential and realized metabolic function based on Gene Ontology analysis of detected genes and peptides. Conclusion: Analyzed together, the metagenomics and metaproteomics datasets reveal that a complete understanding of water quality and interactions with a microbiome require multiple data types to fully reveal the relationship between potential and realized microbiome function.

Metaproteomic Profiling of Fungal Gut Colonization in Gnotobiotic Mice

“…Here, we strengthened these results using a metaproteomic approach that provided an independent functional measure of the microbiome-host crosstalk. Similarly to other multi-omics studies (43, 44), we found discrepancies between the quantitative proteome profiles and the DNA-based relative abundance of individual species. These differences likely stem from complex regulatory networks along the gene to protein expression path, which differ between microbial kingdoms.…”