Strain-level (meta)genomic profiling of bacteria from hospital pathogens to non-human primate commensals
Creators: name: Manara, Serena
Publisher: name: Universit� degli studi di Trento
Year: 2019

description: Studying microbial organisms at the level of single genetic variants (strains) is key not only for human pathogens but also for commensal members of the human microbiome. However, several limitations make isolation-based methods only partially effective in surveying the complexity of host-associated microbial communities. Novel biotechnological advances are revolutionizing the study of host-associated microbes, enabling the transition from low-resolution cultivation-based typing to cultivation-free metagenomic characterizations. In my doctoral work, I tested the hypothesis that appropriate analytical tools applied to genomic and metagenomic data can provide information about microbes at a resolution comparable to that of cultivation-based methods. To this end, I employed a set of integrated methods to reconstruct the genome and analyse the functional and transmission patterns of pathogenic and commensal microbes across human and non-human hosts in different contexts. We initially focused on the whole-genome sequencing of a cohort of 184 Staphylococcus aureus infections from patients with a set of diverse diseases at multiple departments of Meyer?s Children Hospital in Florence, Italy. By applying a combination of isolation-based techniques and computational analysis, we surveyed the epidemiology, transmission patterns, and genomic features associated with both highly-studied and under-investigated S. aureus clones. We identified new infective clones and two novel variants of the beta-lactam resistance cassette. We moreover profiled the virulence and resistance factors typically associated with this opportunistic pathogen, observed the dispensability of genes previously considered as putative targets for vaccine development, and tracked the transmission of a newly-emerging epidemic clone. We then focused on the challenging task of extracting strain-level genomic information from cultivation-free metagenomic sequencing of stool samples obtained from mothers and their infants during the first year of life. By applying genetic and pangenomic profiling tools, we showed that the spread of microbiome members can be inferred from metagenomes directly, and we tracked the vertical transmission of microbial strains from mother to her infant and their corresponding transcriptional profiles. This pilot study laid the foundations for larger cohort studies investigating microbiome transmission via metagenomic sequencing. The next step was the application of cultivation-free approaches to identify and survey currently neglected host-associated microbes. In order to explore those species lacking relatively close already sequenced genomes, we performed a large-scale assembly-based analysis to reconstruct high-quality microbial genomes for species and strains in the under-investigated microbiome of non-human primates (NHPs). Overall, less than one-quarter of the recovered genomes were assigned to known species or species previously observed in the human microbiome. The remaining genomes were assigned to over 1,000 new species, which improved the mappable fraction of NHP metagenomes by over 600%. The analysis of this newly-established catalog of NHP-associated species in the context of available human-associated microbial genomes further exposed the loss of biodiversity from wild and captive NHPs to non-Westernized and Westernized human populations, showing that microbiome members shared between NHPs and humans mostly belong to uncharacterized species that are heavily lifestyle-dependent. Through characterization of a cohort of Staphylococcus aureus isolates, tracking of transmission of commensals from mother to infant, and recovering of microbial dark matter associated with non-human primates, we showed that cultivation-free profiling of known and unknown host-associated species can achieve a resolution for comparative genomics that is close to that available for isolate sequencing.