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Risk Assesment of Bacterial Sepsis using multiomic and bioinformatics tools: an approach towards the Precision Medicine in Infectious Diseases

Sepsis: Early Warning, Prevention and Treatment

Senior Researcher : Teresa Coque González

Research Centre or Institution : Fundación para la Investigación Biomédica. Hospital Universitario Ramón y Cajal. Madrid.

Abstract

The BioMetaSEP consortium aims to develop an integrated ecological model focused on the structure of bacterial intestinal communities and the factors that determine their dynamics in the hospital environment (considering patients, use of antibiotics and other interventions, local ecology), to diagnose hyper-colonization by potential pathogen populations to establish defined risks for bacterial sepsis. This approach is based on the convergence model by the IOM (Institute of Medicine-USA) in 2003 for the study of the acquisition and transmission of infectious diseases in the s. XXI, which is complementary to the perspective of Precision Public Health (National Research Council, 2011). Until now, the experimental approaches using such models have been impaired by the limitation of tools to study bacterial communities ("omics") and to analyse complex data.

BioMetaSEP, is structured in 5 work packages (WP) linked to three blocks: 1) Ecology and microbial dynamics (WP1-3); 2) Patient’ characterization (profiling) (WP4), and 3) Mathematical (computational) modeling (WP5). Samples will be collected in a prospective longitudinal study at a ICU-HryC, and we will specifically focused to model main opportunistic pathogens (e.g. Escherichia coli, Enterococcus spp., staphylococci), which are the predominant species causing epidemic outbreaks and severe infections in the hospital setting. This multidisciplinary approach will apply “omics” tools to accurately detect the abundance (hiper-colonization), diversity of the main pathogens (16SRNA metagenomics; "kin-metagenomics", that allows the description of bacterial population structure of the main etiological agents of sepsis at subspecies level by amplification of single marker genes associated with phylogeny), resistome (targeted metagenomics of all genes conferring resistance to antimicrobials in metagenomes) and alteration of the expression profiles of bacterial communities (metatranscriptomic and metaproteomics). The datasets from microorganisms (omics), patients (clinical records) and environment/setting (ecology, hospital interventions,..) will be integrated into mathematical models that enable us to analyse complex multi-hierarchical systems and thus, to suggest compound risk indexes that allow the stratification of the patients according to the risk of develop sepsis and the susceptibility to terapeuthic treatments.

This project intends to open a research investigation line towards the future implementation of precision medicine in infectious diseases, which could lead to new approches to prevent episodes of sepsis of different etiologies and/or novel ways of testing drugs for personalized therapy.

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