How we do it step by step
1. Integrated cross-referenced database
BIOSYSMO will capitalize a vast amount of public data and information to identify candidate organisms or genes attributed with desired bioremediation functionalities and be added to the studied communities. Machine learning algorithms will be employed to automatically mine databases and scientific publications to identify pathways with biosequestration and biodegradation activity of specific pollutants as well as traits linked with plant colonization. The integrated cross-referenced database will be also fed with the experimental microbial and plant characterization data obtained in BIOSYSMO. The data mining algorithms will focus on (1) strains with specific biodegradation pathways, (2) candidate bacteria or fungi with traits favoring plant colonization, (3) bacteria with exoelectrogenic activity, (4) bacteria and plant genes that can improve pollutant uptake or degradation pathways, and (5) plant genes associated with plant susceptibility to microbe colonization.
2. Model-driven metabolic pathways reconstruction and analysis
Genome-Scale Models (GEM) will be employed to design suitable microbial communities for the degradation of specific and mixtures of pollutants. GEM incorporate the metabolic pathways of microbial communities, and essentially the degradation (consumption) of substrates, which constitute pollutants to remove for bioremediation purposes. The analysis enables modelling and simulation of the metabolic and transport network of organisms with high remediation potential. In addition, model-driven metabolic pathways analysis will reveal means of reconstructing strains to enhance their abilities and capacities of growth, metabolites (pollutants) consumption and by-product production.
3. Experimental testing and design of biosystems
BIOSYSMO will exploit synergetic interactions within microbial communities as well as the interaction between microbes and plants. Different strategies (C1-C6) will be used for the design and enhancement of these biosystems, which will target the degradation of pollutants in different matrices.
3.1. Endophyte-poplar biosystems for soil phytoremediation
Endophytes colonize the plant host promoting plant growth and health by a symbiotic relationship. Poplar genes will be edited to facilitate colonization by selected microbes and enhanced Cd, Hg sequestration. Moreover, microbial communities will be managed to withstand stressful conditions, increase pollutants degradation, increase metal availability for the plant and promote plant growth. These traits will be achieved by editing targets genes of selected microbes with the use of computational databases and tools.
3.2. Microbial-assisted phytoremediation of salt marsh sediments
Microbial diversity will be examined to find candidates for symbiotic association with salt marsh plants towards degradation of micropollutants (e.g., nonylphenol, octylphenol, pentachlorophenol, paroxetine, bezafibrate) in estuarine sediments, enhancement of plant growth and promotion of metal (Cu, Cd) uptake.
3.3. PGPR-assisted phytoremediation of wastewater
Plant Growth Promoting Rhizobacteria (PGPR) will be employed to increase availability of contaminants to plants in aquatic systems and to cope with induced stresses. Phytoremediation will be achieved by the use of aquatic plants, BES and carrier-assisted PGPR inocula to be use for removal of toxic metal ions and pesticides from aqueous solutions.
3.4. Bioelectrochemical Systems (BES)
Microbial conversion includes both oxidation and reduction pathways that involve donation and acceptance of electron in solutions, thus driving biological processes. Electroactive bacteria can exchange electrons also with electrodes. BES reactors are hosting microbial biofilms on electrodes driving oxidation/reduction (removal) of several types of pollutants, including hydrocarbons (aromatic, chlorinated, aliphatic, BTEX), metals, nitrates, sulfates, antibiotics.
3.5. Artificially assembled consortia
Consortia are exposed and enriched in specific polluted samples, where their micro-position ensure efficient metabolites exchange and multi-step degradation of complex pollutants. The consortia will be isolated, selected and micro-structured to prepare spatially oriented artificial bacterial consortia to be applied in bioremediation processes (water, soil and sediment), in electroactive biofilms (BES) and in immobilized in carriers (plant-based systems).
3.6. Strategies based on genetic modification of bacteria
Bottleneck reactions in the desired degradation pathway will also be addressed from a synthetic biology approach by targeting the appropriate genes or regulatory mechanisms. Robust microorganisms will be generated for the bioremediation of the pollutants. Engineered bacteria will provide the functionalities lacking in the autochthonous community through cell bioaugmentation or through genetic bioaugmentation Any concern from the use of Genetically-Modified microorganisms is minimized by implementing safe-by-design strategies.
4. Evaluation of pollutants removal and detoxification
For the characterization of pollutants and multiresidue analysis of traces, there are employed several analytical instruments and methods including: Liquid or gas chromatography coupled to tandem mass spectrometry (LC-MS/MS, GC-MS/MS), micro-liquid chromatography (μLC-MS/MS), high resolution mass spectrometry (HRMS) and the use of time-of-flight or orbitrap analyzers. (Eco)toxicity analysis will be based on the guidelines of Environmental Risk Assessment (ERA) for toxicity testing. QSAR models, namely theoretical modelling and simulation of physicochemical properties, will be implemented for in silico analysis and minimization of in vitro/vivo experimentation.