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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.
Global and even national genome surveillance approaches do not provide the resolution necessary for rapid and accurate direct response by local public health authorities. Hence, a regional network of microbiological laboratories in collaboration with the health departments of all districts of the German federal state of Mecklenburg-Western Pomerania (M-V) was formed to investigate the regional molecular epidemiology of circulating SARS-CoV-2 lineages between 11/2020 and 03/2022. More than 4750 samples from all M-V counties were sequenced using Illumina and Nanopore technologies. Overall, 3493 (73.5%) sequences fulfilled quality criteria for time-resolved and/or spatially-resolved maximum likelihood phylogenic analyses and k-mean/ median clustering (KMC). We identified 116 different Pangolin virus lineages that can be assigned to 16 Nextstrain clades. The ten most frequently detected virus lineages belonged to B.1.1.7, AY.122, AY.43, BA.1, B.1.617.2, BA.1.1, AY.9.2, AY.4, P.1 and AY.126. Time-resolved phylogenetic analyses showed the occurrence of virus clades as determined worldwide, but with a substantial delay of one to two months. Further spatio-temporal phylogenetic analyses revealed a regional outbreak of a Gamma variant limited to western M-V counties. Finally, KMC elucidated a successive introduction of the various virus lineages into M-V, possibly triggered by vacation periods with increased (inter-) national travel activities. The COVID-19 pandemic in M-V was shaped by a combination of several SARS-CoV-2 introductions, lockdown measures, restrictive quarantine of patients and the lineage specific replication rate. Complementing global and national surveillance, regional surveillance adds value by providing a higher level of surveillance resolution tailored to local health authorities.