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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.
In temperate regions, climate warming alters temperature and precipitation regimes. During winter, a decline in insulating snow cover changes the soil environment, where especially frost exposure can have severe implications for soil microorganisms and subsequently for soil nutrient dynamics. Here, we investigated winter climate change responses in European beech forests soil microbiome. Nine study sites with each three treatments (snow exclusion, insolation, and ambient) were investigated. Long-term adaptation to average climate was explored by comparing across sites. Triplicated treatment plots were used to evaluate short-term (one single winter) responses. Community profiles of bacteria, archaea and fungi were created using amplicon sequencing. Correlations between the microbiome, vegetation and soil physicochemical properties were found. We identify core members of the forest-microbiome and link them to key processes, for example, mycorrhizal symbiont and specialized beech wood degraders (fungi) and nitrogen cycling (bacteria, archaea). For bacteria, the shift of the microbiome composition due to short-term soil temperature manipulations in winter was similar to the community differences observed between long-term relatively cold to warm conditions. The results suggest a strong link between the changes in the microbiomes and changes in environmental processes, for example, nitrogen dynamics, driven by variations in winter climate.
The impact of summer drought on peat soil microbiome structure and function-A multi-proxy-comparison
(2022)
Different proxies for changes in structure and/or function of microbiomes have been developed, allowing assessing microbiome dynamics at multiple levels. However, the lack and differences in understanding the microbiome dynamics are due to the differences in the choice of proxies in different studies and the limitations of proxies themselves. Here, using both amplicon and metatranscriptomic sequencings, we compared four different proxies (16/18S rRNA genes, 16/18S rRNA transcripts, mRNA taxonomy and mRNA function) to reveal the impact of a severe summer drought in 2018 on prokaryotic and eukaryotic microbiome structures and functions in two rewetted fen peatlands in northern Germany. We found that both prokaryotic and eukaryotic microbiome compositions were significantly different between dry and wet months. Interestingly, mRNA proxies showed stronger and more significant impacts of drought for prokaryotes, while 18S rRNA transcript and mRNA taxonomy showed stronger drought impacts for eukaryotes. Accordingly, by comparing the accuracy of microbiome changes in predicting dry and wet months under different proxies, we found that mRNA proxies performed better for prokaryotes, while 18S rRNA transcript and mRNA taxonomy performed better for eukaryotes. In both cases, rRNA gene proxies showed much lower to the lowest accuracy, suggesting the drawback of DNA based approaches. To our knowledge, this is the first study comparing all these proxies to reveal the dynamics of both prokaryotic and eukaryotic microbiomes in soils. This study shows that microbiomes are sensitive to (extreme) weather changes in rewetted fens, and the associated microbial changes might contribute to ecological consequences.
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.