Project description:Aging is associated with declining immunity and inflammation as well as alterations in the gut microbiome with a decrease of beneficial microbes and increase in pathogenic ones. The aim of this study was to investigate aging associated gut microbiome in relation to immunologic and metabolic profile in a non-human primate (NHP) model. 12 old (age>18 years) and 4 young (age 3-6 years) Rhesus macaques were included in this study. Immune cell subsets were characterized in PBMC by flow cytometry and plasma cytokines levels were determined by bead based multiplex cytokine analysis. Stool samples were collected by ileal loop and investigated for microbiome analysis by shotgun metagenomics. Serum, gut microbial lysate and microbe-free fecal extract were subjected to metabolomic analysis by mass-spectrometry. Our results showed that the old animals exhibited higher inflammatory biomarkers in plasma and lower CD4 T cells with altered distribution of naïve and memory T cell maturation subsets. The gut microbiome in old animals had higher abundance of Archaeal and Proteobacterial species and lower Firmicutes than the young. Significant enrichment of metabolites that contribute to inflammatory and cytotoxic pathways was observed in serum and feces of old animals compared to the young. We conclude that aging NHP undergo immunosenescence and age associated alterations in the gut microbiome that has a distinct metabolic profile.
Project description:We compared the microbiota of paired mouse caecal contents and faeces by applying a multi-omic approach, including 16S rDNA sequencing, shotgun metagenomics, and shotgun metaproteomics. The aim of the study was to verify whether faecal samples are a reliable proxy for the mouse colonic luminal microbiota, as well as to identify changes in taxonomy and functional activity between caecal and faecal microbial communities, which have to be carefully considered when using stool as sample for mouse gut microbiota investigations.
Project description:We applied metagenomic shotgun sequencing to investigate the effects of ZEA exposure on the change of mouse gut microbiota composition and function.
Project description:Gut microbiome research is rapidly moving towards the functional characterization of the microbiota by means of shotgun meta-omics. Here, we selected a cohort of healthy subjects from an indigenous and monitored Sardinian population to analyze their gut microbiota using both shotgun metagenomics and shotgun metaproteomics. We found a considerable divergence between genetic potential and functional activity of the human healthy gut microbiota, in spite of a quite comparable taxonomic structure revealed by the two approaches. Investigation of inter-individual variability of taxonomic features revealed Bacteroides and Akkermansia as remarkably conserved and variable in abundance within the population, respectively. Firmicutes-driven butyrogenesis (mainly due to Faecalibacterium spp.) was shown to be the functional activity with the higher expression rate and the lower inter-individual variability in the study cohort, highlighting the key importance of the biosynthesis of this microbial by-product for the gut homeostasis. The taxon-specific contribution to functional activities and metabolic tasks was also examined, giving insights into the peculiar role of several gut microbiota members in carbohydrate metabolism (including polysaccharide degradation, glycan transport, glycolysis and short-chain fatty acid production). In conclusion, our results provide useful indications regarding the main functions actively exerted by the gut microbiota members of a healthy human cohort, and support metaproteomics as a valuable approach to investigate the functional role of the gut microbiota in health and disease.
Project description:Rationale: Recent studies suggest a potential link between gut bacterial microbiota dysbiosis and PAH, but the exact role of gut microbial communities, including bacteria, archaea, and fungi, in PAH remains unclear. Objectives: To investigate the role of gut microbiota dysbiosis in idiopathic pulmonary arterial hypertension (IPAH) and to assess the therapeutic potential of fecal microbiota transplantation (FMT) in modulating PAH progression. Methods: Using shotgun metagenomics, we analyzed gut microbial communities in IPAH patients and healthy controls. FMT was performed to transfer gut microbiota from IPAH patients or MCT-PAH rats to normal rats and from healthy rats to MCT-PAH rats. Hemodynamic measurements, echocardiography, histological examination, metabolomic and RNA-seq analysis were conducted to evaluate the effects of FMT on PAH phenotypes. Measurements and Main Results: Gut microbiota analysis revealed significant alterations in the bacterial, archaeal, and fungal communities in IPAH patients compared to healthy controls. FMT from IPAH patients induced PAH phenotypes in recipient rats. Conversely, FMT from healthy rats to IPAH rats significantly ameliorated PAH symptoms, restored gut microbiota composition, and normalized serum metabolite profiles. Specific microbial species were identified with high diagnostic potential for IPAH, improving predictive performance beyond individual or combined microbial communities. Conclusions: This study establishes a causal link between gut microbiota dysbiosis and IPAH and demonstrates the therapeutic potential of FMT in reversing PAH phenotypes. The findings highlight the critical role of bacterial, archaeal, and fungal communities in PAH pathogenesis and suggest that modulation of the gut microbiome could be a promising treatment strategy for PAH.
Project description:Monitoring microbial communities can aid in understanding the state of these habitats. Environmental DNA (eDNA) techniques provide efficient and comprehensive monitoring by capturing broader diversity. Besides structural profiling, eDNA methods allow the study of functional profiles, encompassing the genes within the microbial community. In this study, three methodologies were compared for functional profiling of microbial communities in estuarine and coastal sites in the Bay of Biscay. The methodologies included inference from 16S metabarcoding data using Tax4Fun, GeoChip microarrays, and shotgun metagenomics.