Development of new technologies to study gut microbiomes

Metaproteomics allows the qualitative and quantitative evaluation of the protein complement of an environment at a given time. Given the youth of this research field, significant efforts are needed to optimize sample preparation and data analysis workflows for metaproteome analysis.A major task is aimed at developing novel, rapid and efficient workflows for shotgun metaproteomic analysis.In the present PhD Thesis the investigation of a number of experimental methods have been developed to optimize sample preparation and its MS analysis. Methods were assessed on mock and real gut microbiome samples, combining bead-beating/freeze-thawing for protein extraction, FASP for clean-up and digestion, and single-run LC-MS/MS for peptide separation and identification. The impact of different sequence databases on data analysis was evaluated using mock microbial mixtures. Upon comparison of experimental metagenomic-derived and publicly deposited databases, complementary results suggested the use of iterative searches and suitable taxonomy filters to improve metaproteomic analysis. According to data obtained, the workflow enables protein identification also from fungi, showing high reproducibility (>99%), sensitivity (<104bacterial CFUs) and dynamic range (>104).Finally, this workflow was successfully applied to investigate the sheep fecal metaproteome, obtaining the identification of more than 35,000 proteins belonging to more than 700 microbial species (10 % of which fungi).