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BIOREM

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Systems Biology Artificial Intelligence and Advanced BiOtechnology Approaches t...

Systems Biology Artificial Intelligence and Advanced BiOtechnology Approaches to Improve Soil BioREMediation The growing presence of hazardous compounds in the environment such as persistent organic pollutants compromises the health of ecosystems and humans worldwide. The spontaneous ecological recovery of contaminated sites is possible... ver más

31/12/2028

Líder desconocido

478K€

Presupuesto del proyecto: 478K€

Líder del proyecto Líder desconocido

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-10-14

HORIZON-MSCA-2023-SE-01-01: MSCA Staff Exchanges 2023 Expected Outcome:Project results are expected to contribute to the following outcomes:

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6 Participantes

WAGENINGEN UNIVERSITY

UNIVERSITY OF SURREY

INSTITUT JOZEF STEFAN

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Duración del proyecto: 50 meses Fecha Inicio: 2024-10-14
Fecha Fin: 2028-12-31

Líder del proyecto Líder desconocido

Presupuesto del proyecto 478K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto The growing presence of hazardous compounds in the environment such as persistent organic pollutants compromises the health of ecosystems and humans worldwide. The spontaneous ecological recovery of contaminated sites is possible due to the action of biological agents, including plants and microorganisms. The exploitation of the capability of the latter to transform toxic contaminants into harmless end-products can lead to cheap and sustainable bioremediation alternatives. However, the significant knowledge gap on the molecular mechanisms and microbial species responsible for an efficient detoxification of specific pollutants in determined environmental conditions is a burden slowing down the development of efficient microbial assisted bioremediation technologies. BIOREM is an integrated action conformed by experts in microbial systems biology, artificial intelligence tools and environmental sciences that will work together to gain knowledge in the identification of responsible microbial metabolic routes within natural and synthetic consortia for the degradation of target contaminants. The project through inter-sectorial and multidisciplinary training and collaboration will investigate the synergetic effect of different and combined bioremediation strategies, such as bioaugmentation, bioestimulation and microbial-assisted phytoremediation, stablishing links between effective pollutants removal and the responsible microbial pathways. Predictive models for TPHs and PAH remediation will be developed using High-Perfomance Computing (HPC) and Artificial Intelligence to enhance the efficiency of bioremediation strategies by enabling the analysis of vast amounts of environmental data. The integration of the project information (key microbial players and environmental conditions) into mathematical models will allow the establishment of tailored and efficient removal strategies based on the chemical composition and natural microbiome presence in polluted sites.

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