PRODIGIO comprised two lines of research, each focused on analyzing the bio-based production systems explored in the project: microalgae photobioreactors (PBRs) for biomass production (Work Packages 1 and 3) and anaerobic reactors (ARs) for biogas conversion (Work Packages 2 and 4). Each line involved experimental (Work Packages 1 and 2) and analytical (Work Packages 3, 4, and 5) stages. The experimental stage consisted in sampling and data collection, while the analytical stage employed big data analysis using (meta)genomics and chemical fingerprinting, alongside empirical dynamic modeling for time series analysis (Work Packages 3 and 4). A Life Cycle Sustainability Assessment of PRODIGIO's microalgae-to-biogas chain (Work Package 5) has been carried out to evaluate the actual potential of the technology proposed.
All samples and data, from both microalgal PBRs and bench-scale ARs, were analyzed using standard methods, including routine variables, metabarcoding, metagenomics, metaproteomics, and high-resolution mass spectrometry. This created a comprehensive database, invaluable for investigating bioreactor community responses to perturbations. Applying bioinformatics (Work Packages 1, 2, 3, 4) and empirical dynamic modeling (Work Packages 3, 4) revealed ecological complexities under normal, stressed, and failure conditions. This included reconstructing potential chemical-microbial interactions within bioreactor interactomes and analyzing network properties to uncover key architectural and dynamic features.
Key project results include: i) comprehensive descriptions of algal microbiome structure, diversity, and dynamics; ii) detailed descriptions of biochemical and ecological responses of microbial communities to common AR shocks; iii) reconstruction of PBR and AR interactomes; iv) the discovery of stabilizing positive and negative microalgae-microbiome interactions; v) identification of cascading transitions in key species and metabolites preceding methanogenic ecosystem collapse; and vi) a comprehensive assessment of environmental, social, and techno-economic aspects of PRODIGIO's biogas production chain, pinpointing areas for improvement and implementing sustainable practices to maximize the efficiency of processes and minimize the environmental footprint.
Ultimately, PRODIGIO's findings provide an empirical basis for developing effective early warning signals (EWS) for system failure in microalgae production and biomass to biogas conversion systems. Specifically, key population dynamics and chemical compounds were identified as potential EWS, enabling proactive interventions to prevent bioreactor collapse and enhance operational stability beyond current capabilities.
Overall, this research not only advances scientific knowledge but also has practical implications for enhancing the reliability and sustainability of microalgae biomass and biogas production systems. The potential for publication in high-impact scientific journals underscores the significance and relevance of these findings to the scientific community and stakeholders in the microalgae and renewable energy sectors.
