Analisi genomiche, bioinformatiche ed epidemiologiche per lo studio di microrganismi di interesse sanitario

For many years, the characterization and epidemiological surveillance of pathogenic bacteria has been based on the use of conventional techniques and methodologies which, although essential for a first form of investigation, do not allow to obtain a detailed and complete picture of the phenotypic and genetic variability of the pathogen itself. The limits of these ‘classical’ methods are clear in terms of turnaround times and detail of characterization, and thus represent bottlenecks in the timing of the implementation of surveillance measures and in the effectiveness of health treatments. In this context, the implementation of modern bioinformatics and evolutionary approaches based on genomics and transcriptomics is currently making it possible to considerably expand the knowledge of the various bacterial strains, to fully characterize them and to reconstruct their epidemiological evolutionary history, with significant advantages both at a diagnostic and therapeutic level. On these basis, in the following pages, I will show practical examples of the application of the latest generation sequencing techniques for the genomic and transcriptomic analysis of the following pathogens of interest: Mycobacterium tuberculosis, Bacillus anthracis, Streptococcus agalactiae and Staphylococcus aureus. For Mycobacterium tuberculosis and Streptococcus agalactiae, I performed differential gene expression studies (RNA-Seq) to identify the altered molecular processes following the administration of the molecule 11726172 in Mycobacterium tuberculosis and the deletion of the codY gene in Streptococcus agalactiae. The analysis of RNA-Seq data resulted to be very fruitful, as it made it possible to delineate in detail the mechanisms of action of these two therapeutic approaches and to infer the genes involved in these processes. In Bacillus anthracis, genome sequencing with Illumina and Oxford Nanopore technology was fundamental to study the compensatory mechanisms in response to the deletion of the sap and eag genes, encoding for two proteins of the S-layer. The chromosome-level assembly of these genomes made it possible to carry out comparative analyzes between wild-type and mutant strains, allowing the identification of variations at the level of gene content and single nucleotide mutations (SNPs) involved in the adaptation process. Finally, for my main Ph.D. project, I carried out a retrospective study on a nine-year collection of Staphylococcus aureus within the San Matteo Hospital in Pavia (Italy). Thanks to the combination of metadata and genomic data, I was able to describe in detail the phenotypic and genetic variability of the various strains of Staphylococcus aureus circulating within this hospital, highlighting the existence of a complex network of sequence types and clonal complexes (CC), of environmental and hospital origin. My analyses allowed to detect the presence not only of highly abundant strains, such as CC8 or CC22, but also of rarer variants, some of which with relevant resistance and virulence profiles (e.g ST30). Lastly, phylogenetic analyses based on coreSNPs, allowed to identify clusters of highly-related samples belonging to ST22 and ST8, responsible for persistent episodes of infection throughout the course of the nine analysed years. In conclusion, this study represents a clear example of how a well-constructed research project can provide a complete depiction of the epidemiological and genetic status of a pathogen in clinical setting and therefore, direct the attention of medical personnel not only towards common variants, but also rarer ones than could escape normal surveillance controls.