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Establishment of an experimental and computational platform to study host-microbes interactions promoted by sialic acids

Abstract

Microorganisms engage in complex interactions with other members of the microbial community, higher organisms as well as their environment. However, determining the exact nature of these interactions can be challenging due to the large number of members in these communities and the manifold of interactions they can engage in. Various omic data, such as 16S rRNA gene sequencing, shotgun metagenomics, metatranscriptomics, metaproteomics, and metabolomics, have been deployed to unravel the community structure, interactions, and resulting community dynamics in situ. Interpretation of these multi-omic data often requires advanced computational methods and robust databases. Interactions between microorganisms and host are very dynamic: they can be facultative or obligatory, they can involve intense molecular responses or not, and in most cases they result in benefits to the host health or diseases. Interactions between microorganisms and hosts mediated by sialic acids have shown an dual nature, being associated with health or with pathologies. Sialic acids are nine-carbon keto-sugars found primarily in animals as terminal subunits of glycoconjugates. These glycans not only function as barriers for microorganisms that inhabit or invade the host, but also represent potential sources of carbon, nitrogen and cell all components. Additionally, sialic acids are involved in the colonization, resistance and growth of bacteria, both commensal and pathogenic. In this project we propose to build an experimental and computational platform to study the different mechanisms of interaction between microorganisms and hosts mediated by sialic acids. The combination of experiments of microbial cooperation using microbial synthetic communities, immunoprecipitation assays using antibodies anti-sialic acid followed by high-hroughput sequencing and classical molecular biology assays will allow the identification of microorganisms able to metabolize and incorporate sialic acids. Computational analyzes of genomics and metagenomics data will reveal a genetic basis for the sialic acids metabolism, which will allow to map the distribution of interaction mechanisms mediated by sialic acid in different contexts (health and disease). As a final goal, the combination of computational and experimental approaches will result on the identification of potential targets for medical interventions which will contribute for the biotechnological development in Brazil. (AU)

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