Comparative genomics and metagenomics analysis to assess the genetic basis of the synthesis, metabolism and incorporation of sialic acids by bacteria.

• Grant number: 24/10047-9
• Support Opportunities: Scholarships in Brazil - Doctorate (Direct)
• Start date: September 01, 2024
• End date: May 31, 2028
• Field of knowledge: Biological Sciences - Microbiology - Biology and Physiology of Microorganisms
• Principal Investigator: Lívia Soares Zaramela
• Grantee: Thais Alana Ferreira Moura
• Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated research grant: 20/08554-9 - Establishment of an experimental and computational platform to study host-microbes interactions promoted by sialic acids, AP.JP

Abstract

Several commensal and pathogenic bacteria have the ability to metabolize, synthesize and incorporate sialic acids through catabolism, anabolism and assimilation pathways. The project in question aims to evaluate genomics and metagenomics data available to date, characterizing them in order to obtain a global view of how these organisms are distributed, their origins and their interactions with their hosts.For an in silico genetic characterization of the sialic acid metabolism pathways of bacterial isolates, the analysis will be carried out using all the complete bacterial genomes deposited in NCBI's GenBank (30,362 genomes), with the data downloaded using the automated flow proposed by RepoPhlAn. The quality of the genomes will be assessed in terms of integrity, contamination and heterogeneity by the CheckM tool, using the standard lineage_wf protocol, so that genomes that do not meet the proposed quality threshold metrics will be excluded from the analysis. Genomes with satisfactory quality will be re-annotated to ensure uniformity and consistency. The Prodigal (single-genome mode) and Prokka tools will be used to annotate the coding regions (CDSs), and the functional genes directly involved in sialic acid metabolism will be annotated using a repository of marker genes taken from specialized databases (Kegg, UNIPROT and Cazzy). Local alignment algorithms (BlastN and BlastP) and alignment algorithms that use a hidden Markov model (HMMER) will be used to identify the genomes with the genes of interest.The project also aims to evaluate metagenomics data from microbial communities associated with inflammatory diseases. To this end, whole genome sequencing data (shotgun metagenomics) generated primarily from the Illumina platform and whose samples were collected from humans and murine models with inflammatory and related diseases will be processed as described in the referenced article and using the Trimmomatic, Megahit and MetaBat2 tools. The quality of this data will be assessed in the same way as data taken from GenBank.At the end of the project, we will present a global view of the distribution of commensal and pathogenic bacteria capable of catabolizing, synthesizing and incorporating sialic acids. In this way, we will be able to identify aspects of niche-dependent bacterial colonization and the association between bacteria capable of metabolizing sialic acids and inflammatory processes. This work will also provide information to explore the evolutionary processes of genes involved in sialic acid metabolism in bacteria and their hosts.