Large scale study on the mechanism of sialic acid incorporation by microorganisms of intestinal human microbiota

• Grant number: 23/14358-6
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: September 01, 2024
• End date: March 31, 2027
• Field of knowledge: Biological Sciences - Microbiology - Biology and Physiology of Microorganisms
• Principal Investigator: Lívia Soares Zaramela
• Grantee: Edson Alexandre do Nascimento Silva
• 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

The sialic acids are monosaccharides composed of nine carbons and are mostly presented in the cell surface of vertebrates. Among them, N-acetylneuraminic acid and the N-glycolylneuraminic acid are the major groups of sialic acid in mammals. However, in humans, the Neu5Gc is not synthesized due to one mutation in the Cmah gene, responsible for the hydroxylation of Neu5Ac into Neu5Gc. The glycoconjugates that own sialic acid have an important role in cell signalization and also interaction among different cells. Beyond that, the pathogenic microorganisms presented in microbiota can remove the host's sialic acid and incorporate it in their cell surface. With this mechanism, the microorganisms are capable of hiding their presence in front of the host's immune system. Previous studies showed the capacity of some species such as Escherichia coli and Campylobacter jejuni to have such mechanisms of immune system's evasion. Although, a mapping of bacterias and fungi species carriers of sialic acid incorporation mechanisms and their importance to the host's health is not available yet. Therefore, this project aims to identify the microorganisms of human microbiota, pathogenics or not, that have the capacity to incorporate the host's sialic acid in their cell wall. Besides a robust computational analysis of genomics data already available in the public dataset, we will use a murine model to identify the bacterias involved in nonspecific inflammatory processes in the gastrointestinal tract.