The target of this project is to develop bioremediation / revitalization strategies based on assemblies of multiple biologics, developed and applied on matrices from different EU contaminated sites: groundwater, sediments (hyporheic zone), wastewater as well as industrial, and agricultural soils. The assembly of systems is guided using predictive microbial interaction models in the microbiome of the actual site matrix to be decontaminated. Our ambition is to remove at least 90% of the main contaminants of polluted sites (e.g. plastics and pesticides in the agricultural soil, and chlorinated solvents/total petroleum hydrocarbon in groundwater and sediments of the industrial site) and improve their biodiversity status. The approach includes the implementation of a Biological Toolbox for designing efficacious degrading catalytic agents. Bioremediation/revitalization strategies undergo a full assessment: ecological and environmental risk analyses, technology risk analysis, life cycle assessment, life cycle cost, cost-efficiency analysis, biosafety & regulatory constraints analysis, and societal analysis to be finally benchmarked with current solutions.


The major environmental and economical challenges we are facing require constant innovation. In Biomachine we want to develop, and also train a new generation of experts capable of implementing, “Nature-inspired” and “Artificial intelligent-edited” biologics with which to develop (micro)plastic-degradation strategies, namely, for polyethylene-terephthalate (PET), and also polyurethane (PU) and polyamide (PA). Biomachine outperforms the use of single degraders of (micro)plastics, e.g. bacteria and enzymes, by designing new biologics that can help to reach a healthy zero-pollution environment. Biomachine aims to assess the design of biologics consisting on genomically edited bacteria with their own proteins “artificially-evolved” to synergetically support (micro)plastic degradation. Both the biologics and the strategies (including experimental and deep learning) will allow, in a circular economy context, controlling pollution, promoting environmental restoration, and mitigating climate change. Biomachine stems from our own experience and the expertise of Nostrum Biodiscover (NBD) in massive supercomputing capabilities and transfer possibilities.


MetaMorph will strive to develop a high-tech platform to perform the MetaMorphosis of enzymes [with original properties fitting industrial needs] into a new generation of artificial enzyme designs [PluriZymes] and BioHybrid catalysts with innovative structures and functionalities. They will enhance performances for processes and products with markedly reduced environmental impacts. The high-tech enzyme development platform will take advantage of our high capacity for enzyme bioprospecting, big biodata mining and analysis, disruptive machine learning, protein engineering, nano-biotechnology, upscale fermentation, and downstream processing. 


Enzymes undoubtedly have a central role as green catalysts operating efficiently at low energy needs and enabling novel functionalities. However, one of the current main bottlenecks in the implementation of enzymes in greener industry processes and products, hindering economic competitiveness and greater sustainability, is that, although, bio-prospecting and engineering technology is enjoying a high level of sophistication, we are unable to accurately predict enzyme parameters from a protein sequence. This limits the exploitation of the existing large sequence databases for searching enzymes with industrial and manufacturing requirements. Succeeding in this undertaking would revolutionize the possibilities of industry to better recover the needed enzymes from the ever-increasing amount of sequencing data, which can be generated at an ever-lower price compared to any other method.


FuturEnzyme is conceived to develop enzymes to be used for the eco-friendly making and economically viable textiles, detergents and cosmetics, but also of any other sectors that can find an interest on them. With this purpose, a high-tech enzyme development platform will use big biodata mining of public and internal databases and bioresources, disruptive machine-learning, activity-based bioprospecting, protein engineering, nano-biotechnology, upscale fermentation and downstream processing systems.

Manuel Ferrer
Research Professor
Systems Biotechnology Group
Office 202

Department of Applied Biocatalysis
Institute of Catalysis, Spanish National Research Council
Marie Curie, 2
+34 91 585 48 72