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:Pesticides are widely used to protect growth of crops and prevent the spread of diseases. However, more and more pest insects have developed resistance to chemical pesticides along with the long-term application of the pesticides. It is very important to explore the molecular mechanisms of insecticide resistance not only for reversing the resistance in insects, but also for finding out new function targets of the insecticides. Recently, the next-generation sequence technique has become an effective tool to screen resistance genes and has developed transcriptome profiles of various species. However, a comprehensive database to collect these transcriptome data remains poorly developed. In this study, we constructed a database for insect resistance called IRdb, which contains gene count data from various insect species analyzed by a unified process. In addition to the gene data, IRdb also contains 430 unique resistance proteins (experimentally verified proteins manually extracted from literature). Users can discriminate the resistance proteins by submitting fasta sequence of proteins of interest, which can provide clues to detect resistance proteins. The application of resistance protein part in IRdb indicates the accuracy of prediction of IRdb by extracting CTD features and employing random forest. The database IRdb online web server (http://120.27.24.199:20609/) was provided for users to download the transcriptome and protein data for resistance of insects to insecticides and to predict potential resistance proteins.