Prof. Nicola Segata
University of Trento
Full Professor Nicola Segata is a computational biologist at the CIBIO Department at University of Trento (Italy). His lab (http://segatalab.cibio.unitn.it) comprises seven postdoctoral fellows, seven PhD students, and two research assistants and focuses on the study of the host-associated microbial diversity with biomedical relevance.
Upon starting his independent research lab, Prof. Segata focused on experimental and computational projects aimed at characterising with strain-level resolution the characteristics of microbial communities associated with the host in healthy and dysbiotic conditions. On the experimental side, the laboratory is producing and analysing shotgun metagenomics and metatranscriptomics data for studying the link between the gut microbiome and colorectal cancer, the skin microbiome and psoriasis, the food microbiome and human microbiome, the vertical and horizontal transmission of microbial organisms and the cultivation and characterization of unknown human gut microbes. The main computational projects focus instead on the profiling of microbiomes with strain-level resolution and the meta-analysis of very large sets of metagenomes with multiple analytic tools.
Focus in CoDiet
Increasing the NCD associated microbiome biomarkers knowledge and exploiting the newly generated microbiome data for large comparative analysis with publicly available datasets. The newly generated data will implement and update the curatedMetagenomic database developed by Segata group. Establishing new research collaborations.
Blanco-Míguez, A., Beghini, F., Cumbo, F. et al. Extending and improving metagenomic taxonomic profiling with uncharacterized species using MetaPhlAn 4. Nat Biotechnol (2023). https://doi.org/10.1038/s41587-023-01688-w
Valles-Colomer, … Segata. The person-to-person transmission landscape of the gut and oral microbiomes. Nature 2023. https://doi.org/10.1038/s41586-022-05620-1
Asnicar … Segata. Microbiome connections with host metabolism and habitual diet from 1098 deeply phenotyped individuals. Nature Medicine, [I.F. 53.44], 27:321–332, 2021.https://doi.org/10.1038/s41591-020-01183-8
Thomas … Segata N. Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nat Med. 2019 Apr;25(4):667-678. PubMed PMID: 30936548.