Project description:On going efforts are directed at understanding the mutualism between the gut microbiota and the host in breast-fed versus formula-fed infants. Due to the lack of tissue biopsies, no investigators have performed a global transcriptional (gene expression) analysis of the developing human intestine in healthy infants. As a result, the crosstalk between the microbiome and the host transcriptome in the developing mucosal-commensal environment has not been determined. In this study, we examined the host intestinal mRNA gene expression and microbial DNA profiles in full term 3 month-old infants exclusively formula fed (FF) (n=6) or breast fed (BF) (n=6) from birth to 3 months. Host mRNA microarray measurements were performed using isolated intact sloughed epithelial cells in stool samples collected at 3 months. Microbial composition from the same stool samples was assessed by metagenomic pyrosequencing. Both the host mRNA expression and bacterial microbiome phylogenetic profiles provided strong feature sets that clearly classified the two groups of babies (FF and BF). To determine the relationship between host epithelial cell gene expression and the bacterial colony profiles, the host transcriptome and functionally profiled microbiome data were analyzed in a multivariate manner. From a functional perspective, analysis of the gut microbiota's metagenome revealed that characteristics associated with virulence differed between the FF and BF babies. Using canonical correlation analysis, evidence of multivariate structure relating eleven host immunity / mucosal defense-related genes and microbiome virulence characteristics was observed. These results, for the first time, provide insight into the integrated responses of the host and microbiome to dietary substrates in the early neonatal period. Our data suggest that systems biology and computational modeling approaches that integrate “-omic” information from the host and the microbiome can identify important mechanistic pathways of intestinal development affecting the gut microbiome in the first few months of life. KEYWORDS: infant, breast-feeding, infant formula, exfoliated cells, transcriptome, metagenome, multivariate analysis, canonical correlation analysis 12 samples, 2 groups
Project description:Hundreds of microbial species were found to be transcriptionally active in the human gut microbiome based on the expression profiling of ca. 680.000 microbial genes As a part of the MetaHIT cohort 233 human stool samples were transcriptionally profiled using a custom made microarray that included probes for most prevalent microbial genes in the cohort as established by whole-genome sequencing of the same samples
Project description:On going efforts are directed at understanding the mutualism between the gut microbiota and the host in breast-fed versus formula-fed infants. Due to the lack of tissue biopsies, no investigators have performed a global transcriptional (gene expression) analysis of the developing human intestine in healthy infants. As a result, the crosstalk between the microbiome and the host transcriptome in the developing mucosal-commensal environment has not been determined. In this study, we examined the host intestinal mRNA gene expression and microbial DNA profiles in full term 3 month-old infants exclusively formula fed (FF) (n=6) or breast fed (BF) (n=6) from birth to 3 months. Host mRNA microarray measurements were performed using isolated intact sloughed epithelial cells in stool samples collected at 3 months. Microbial composition from the same stool samples was assessed by metagenomic pyrosequencing. Both the host mRNA expression and bacterial microbiome phylogenetic profiles provided strong feature sets that clearly classified the two groups of babies (FF and BF). To determine the relationship between host epithelial cell gene expression and the bacterial colony profiles, the host transcriptome and functionally profiled microbiome data were analyzed in a multivariate manner. From a functional perspective, analysis of the gut microbiota's metagenome revealed that characteristics associated with virulence differed between the FF and BF babies. Using canonical correlation analysis, evidence of multivariate structure relating eleven host immunity / mucosal defense-related genes and microbiome virulence characteristics was observed. These results, for the first time, provide insight into the integrated responses of the host and microbiome to dietary substrates in the early neonatal period. Our data suggest that systems biology and computational modeling approaches that integrate “-omic” information from the host and the microbiome can identify important mechanistic pathways of intestinal development affecting the gut microbiome in the first few months of life. KEYWORDS: infant, breast-feeding, infant formula, exfoliated cells, transcriptome, metagenome, multivariate analysis, canonical correlation analysis
Project description:The human stool samples were collected and processed for in vitro culturing under anaerobic condition using rapidAIM assay with or without SAHA, an lysine deacetylase inhibitor, for evaluating the effects of SAHA on human gut microbiome. Metaproteomics were used to analyze the microbiome composition and functions.
Project description:We processed a human stool sample and cultured the processed microbiome in vitro under anaerobic condition for 48 hours using the rapidAIM assay. The microbiome was treated with either azathioprine, ciprofolxacin, diclofenac, nicatidine, paracetamol or control DMSO. Each drug was used at three different concentrations. We compared these results to those acquired using MS1-only data.
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:Dysbiotic configurations of the human gut microbiota have been linked with colorectal cancer (CRC). Human small non-coding RNAs are also implicated in CRC and recent findings suggest that their release in the gut lumen contributes to shape the gut microbiota. Bacterial small RNAs (bsRNAs) may also play a role in carcinogenesis but their role is less explored. Here, we performed small RNA and shotgun sequencing on 80 stool specimens of patients with CRC, or adenomas, and healthy subjects collected in a cross-sectional study to evaluate their combined use as a predictive tool for disease detection. We reported a considerable overlap and correlation between metagenomic and bsRNA quantitative taxonomic profiles obtained from the two approaches. Furthermore, we identified a combined predictive signature composed by 32 features from human and microbial small RNAs and DNA-based microbiome able to accurately classify CRC from healthy and adenoma samples (AUC= 0.87). In summary we reported evidence that host-microbiome dysbiosis in CRC can be observed also by altered small RNA stool profiles. Integrated analyses of the microbiome and small RNAs in the human stool may provide insights for designing more accurate tools for diagnostic purposes.