BIOREM

Project: Systems Biology, Artificial Intelligence and Advanced BiOtechnology Approaches to Improve Soil BioREMediation (BIOREM)

Harnessing microbes to clean up pollution

Hazardous compounds, including persistent organic pollutants, increasingly endanger ecosystems and human health. While natural recovery processes do exist, leveraging biological agents such as plants and microorganisms could provide cost-effective and sustainable clean-up solutions. Supported by the Marie Skłodowska-Curie Actions programme, the BIOREM project will close critical knowledge gaps about microbial species and the biochemical pathways they use to detoxify specific pollutants under various conditions. BIOREM brings together experts in microbial biology, AI and environmental science to advance microbial-assisted bioremediation. By combining bioaugmentation, biostimulation and phytoremediation, the project aims to link pollutant removal with the responsible microbial pathways. Using high-performance computing and AI, BIOREM will develop predictive models to customise efficient bioremediation strategies for polluted sites.

BIOREM Objectives

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.

Fields of science (EuroSciVoc):

• engineering and technology
  • environmental biotechnology
    • bioremediation
      • phytoremediation
• natural sciences
  • biological sciences
    • microbiology

Keywords:

• bioaugmentation
• bioestimulation
• genome scale modelling
• persistent organic pollutants
• heavy metals
• microbial communities
• systems biology
• transcriptomics
• artificial intelligence