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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.
Four aerobic bacteria with bacteriolytic capabilities were isolated from the brackish water site Strait Uzynaral of Lake Balkhash in Kazakhstan. The morphology and physiology of the bacterial isolates have subsequently been analyzed. Using matrix assisted laser desorption ionization-time of flight mass spectrum and partial 16S rRNA gene sequence analyses, three of the isolates have been identified as Pseudomonas veronii and one as Paenibacillus apiarius. We determined the capability of both species to lyse pre-grown cells of the Gram-negative strains Pseudomonas putida SBUG 24 and Escherichia coli SBUG 13 as well as the Gram-positive strains Micrococcus luteus SBUG 16 and Arthrobacter citreus SBUG 321 on solid media. The bacteriolysis process was analyzed by creating growth curves and electron micrographs of co-cultures with the bacteriolytic isolates and the lysis sensitive strain Arthrobacter citreus SBUG 321 in nutrient-poor liquid media. One metabolite of Paenibacillus apiarius was isolated and structurally characterized by various chemical structure determination methods. It is a novel antibiotic substance.
Influenza A Virus (IAV) infection followed by bacterial pneumonia often leads to hospitalization and death in individuals from high risk groups. Following infection, IAV triggers the process of viral RNA replication which in turn disrupts healthy gut microbial community, while the gut microbiota plays an instrumental role in protecting the host by evolving colonization resistance. Although the underlying mechanisms of IAV infection have been unraveled, the underlying complex mechanisms evolved by gut microbiota in order to induce host immune response following IAV infection remain evasive. In this work, we developed a novel Maximal-Clique based Community Detection algorithm for Weighted undirected Networks (MCCD-WN) and compared its performance with other existing algorithms using three sets of benchmark networks. Moreover, we applied our algorithm to gut microbiome data derived from fecal samples of both healthy and IAV-infected pigs over a sequence of time-points. The results we obtained from the real-life IAV dataset unveil the role of the microbial families Ruminococcaceae, Lachnospiraceae, Spirochaetaceae and Prevotellaceae in the gut microbiome of the IAV-infected cohort. Furthermore, the additional integration of metaproteomic data enabled not only the identification of microbial biomarkers, but also the elucidation of their functional roles in protecting the host following IAV infection. Our network analysis reveals a fast recovery of the infected cohort after the second IAV infection and provides insights into crucial roles of Desulfovibrionaceae and Lactobacillaceae families in combating Influenza A Virus infection. Source code of the community detection algorithm can be downloaded from https://github.com/AniBhar84/MCCD-WN.
Background: Methanogenic archaea represent a less investigated and likely underestimated part of the intestinal tract microbiome in swine.
Aims/Methods: This study aims to elucidate the archaeome structure and function in the porcine intestinal tract of healthy and H1N1 infected swine. We performed multi-omics analysis consisting of 16S rRNA gene profiling, metatranscriptomics and metaproteomics.
Results and discussion: We observed a significant increase from 0.48 to 4.50% of archaea in the intestinal tract microbiome along the ileum and colon, dominated by genera Methanobrevibacter and Methanosphaera. Furthermore, in feces of naïve and H1N1 infected swine, we observed significant but minor differences in the occurrence of archaeal phylotypes over the course of an infection experiment. Metatranscriptomic analysis of archaeal mRNAs revealed the major methanogenesis pathways of Methanobrevibacter and Methanosphaera to be hydrogenotrophic and methyl-reducing, respectively. Metaproteomics of archaeal peptides indicated some effects of the H1N1 infection on central metabolism of the gut archaea.
Conclusions/Take home message: Finally, this study provides the first multi-omics analysis and high-resolution insights into the structure and function of the porcine intestinal tract archaeome during a non-lethal Influenza A virus infection of the respiratory tract, demonstrating significant alterations in archaeal community composition and central metabolic functions.