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Swine are regarded as promising biomedical models, but the dynamics of theirgastrointestinal microbiome have been much less investigated than that of humans or mice. The aimof this study was to establish an integrated multi-omics protocol to investigate the fecal microbiomeof healthy swine. To this end, a preparation and analysis protocol including integrated samplepreparation for meta-omics analyses of deep-frozen feces was developed. Subsequent data integrationlinked microbiome composition with function, and metabolic activity with protein inventories, i.e.,16S rRNA data and expressed proteins, and identified proteins with corresponding metabolites.16S rRNA gene amplicon and metaproteomics analyses revealed a fecal microbiome dominated byPrevotellaceae,Lactobacillaceae,Lachnospiraceae,RuminococcaceaeandClostridiaceae.Similar microbiomecompositions in feces and colon, but not ileum samples, were observed, showing that feces can serveas minimal-invasive proxy for porcine colon microbiomes. Longitudinal dynamics in composition,e.g., temporal decreased abundance ofLactobacillaceaeandStreptococcaceaeduring the experiment,were not reflected in microbiome function. Instead, metaproteomics and metabolomics showed arather stable functional state, as evident from short-chain fatty acids (SCFA) profiles and associatedmetaproteome functions, pointing towards functional redundancy among microbiome constituents.In conclusion, our pipeline generates congruent data from different omics approaches on the taxonomyand functionality of the intestinal microbiome of swine.
Summary
This study aimed to establish a robust and reliable metaproteomics protocol for an in‐depth characterization of marine particle‐associated (PA) bacteria. To this end, we compared six well‐established protein extraction protocols together with different MS‐sample preparation techniques using particles sampled during a North Sea spring algae bloom in 2009. In the final optimized workflow, proteins are extracted using a combination of SDS‐containing lysis buffer and cell disruption by bead‐beating, separated by SDS‐PAGE, in‐gel digested and analysed by LC–MS/MS, before MASCOT search against a metagenome‐based database and data processing/visualization with the in‐house‐developed bioinformatics tools Prophane and Paver. As an application example, free‐living (FL) and particulate communities sampled in April 2009 were analysed, resulting in an as yet unprecedented number of 9354 and 5034 identified protein groups for FL and PA bacteria, respectively. Our data suggest that FL and PA communities appeared similar in their taxonomic distribution, with notable exceptions: eukaryotic proteins and proteins assigned to Flavobacteriia, Cyanobacteria, and some proteobacterial genera were found more abundant on particles, whilst overall proteins belonging to Proteobacteria were more dominant in the FL fraction. Furthermore, our data points to functional differences including proteins involved in polysaccharide degradation, sugar‐ and phosphorus uptake, adhesion, motility, and stress response.