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

19th national competition for scientific and technical research

Sepsis: Early Warning, Prevention and Treatment

Senior Researcher : María Teresa Coque González


Sepsis represents the third cause of death in Western countries and the clinical portrait with the highest economic cost in the hospital setting. It occurs due to an invasion of the bloodstream either from an acute focus or by an overgrowth (hyper-colonization) of the etiologic agent in the mucous membranes, favoring translocation processes. To date, there are no diagnostic techniques that allow diagnosing the hyper-colonization and therefore of risk of secondary or systemic infection, which may explain the frequency of "inadvertent sepsis" with a high frequency of therapeutic failures. BioMetaSEP proposes the development of metagenomic biomarkers (abundance and diversity) of opportunistic pathogens in faecal samples to determine the risk of sepsis (based on hyper-colonization pressure) and treatment sensitivity (based on resistome characterization) in hospital areas.

BioMetaSEP, is organized into 5 work packages (WP) divided into three section: i)) Ecology and microbial dynamics (WPs1-3); ii) Patient characterization (WP4), and iii) Mathematical modeling (WP5). The project uses samples (feces, blood) and data from hospitalized patients in a medical intensive care unit (ICU) and different environmental factors (prospective longitudinal study).

In the first year of the project, the activities programmed for the different WPss have been fulfilled. They include the collection of samples, the optimization of some technical protocols (DNA extraction automation and omic techniques), and the creation of metadata datasets. More specifically, an articulated workflow has been implemented in REDCap (Research Electronic Data Capture), an electronic data capture software aimed at translational research, which operates in web browsers and allows analysising metadata from the same or different institutions. Such implementation integrates the design of the database and its different modules (clinical, microbiological, omic data), and the training of the tool. In addition, the designs of different next generation omic tools for the determination of the diversity of the main pathogens causing sepsis (metagenomics directed at the sub-species level), the resistome (set of genes that confer resistance to antimicrobial agents) and the expression of some biomarkers of pathogenic importance (metaproteomics) have been designed.

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