Objective In this proposal we aim to expose and characterize members of the human-associated microbial dark matter and exploit the novel information to dramatically enhance the resolution of metagenomic profiling and develop accurate predictive/diagnostic tools.As a first step we will discover currently uncharacterized human microbiome members from metagenomic data through novel application of assembly-based approaches on a large compendium of newly generated and available shotgun metagenomes (Aim 1). The new identified genomes will be phylogenetically and taxonomically characterized and investigated to track strain-level individual and temporal genetic variability (Aim 2). The new genomes will be then used to develop a next generation host condition prediction approach through a genome-level machine learning tool (Aim 3).The three main objectives of the proposal are functional to the characterization of microbial dark matter from human microbiome and its use for strain-level microbiology tasks and metagenomic prediction/association tools. DiMeTrack focuses specifically on shotgun metagenomics and tracking across time and individual on many samples from publicly available databases and generated at the host laboratory. By discovering previously uncharacterized microorganisms and unravelling their roles in specific biological phenomena (e.g. mother-to-neonate transmission) and association with disease states, we fulfil the Horizon 2020 policies in supporting research and innovation that improve our understanding of the causes and mechanisms underlying healthy and diseased people and improve our ability to monitor and detect diseases.The profile and the future research plan of the applicant fits well with these research areas. In addition, after working in United States for a few years, he wants to be reintegrated in a research position in EU. Fields of science natural sciencesphysical sciencesastronomyastrophysicsdark matternatural sciencesbiological sciencesecologyecosystemsnatural sciencescomputer and information sciencesartificial intelligencemachine learningnatural sciencesbiological sciencesmicrobiologynatural sciencesbiological sciencesgeneticsgenomeseukaryotic genomes Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2015-EF - Marie Skłodowska-Curie Individual Fellowships (IF-EF) Call for proposal H2020-MSCA-IF-2015 See other projects for this call Funding Scheme MSCA-IF-EF-RI - RI – Reintegration panel Coordinator UNIVERSITA DEGLI STUDI DI TRENTO Net EU contribution € 180 277,20 Address VIA CALEPINA 14 38122 Trento Italy See on map Region Nord-Est Provincia Autonoma di Trento Trento Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 180 277,20