Mauriello, Italia Elisa (2023) Identification of species and sub-species in food and human microbiomes. [Tesi di dottorato]

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Abstract

The study of food and human microbiomes has assumed a central role in the scientific community, especially in the last few years thanks to the advancement of sequencing technologies and the dramatic decrease of sequencing cost for exploring complex microbial communities. This is generating a large amount of data that needs proper computational tools and methodologies to be analysed. For that purpose, this thesis aims to develop and apply tools and analyses for the identification of species and sub-species in food and human microbiomes. This is accomplished by considering large-scale approaches built on shotgun metagenomics data. It has been developed and validated a methodology based on a clustering approach for sub-species identification from genomes. The main idea is to view clustering as a supervised classification problem, in which we must estimate the true number of clusters (i.e., sub-species in our case). Such methodology has been validated on synthetic data in which we tried to estimate the right number of clusters/sub-species by changing different variables. The methodology has been also applied in real scenarios by considering two microbial families of great relevance in the food science field as lactic acid bacteria (LAB) and Bifidobacteriaceae.

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