Power to gas: metagenomics and metabolic modeling for the optimization of anaerobic CO2 capture and green biomethane production

Microorganism-driven processes capable of sequestering carbon dioxide are attracting increasing attention for their potential to mitigate greenhouse gas emissions and produce added value compounds within a circular economy framework. Biomethanation, in particular, which has the potential to treat a diverse range of carbon-rich gas streams, is appealing for its ability to generate methane –an energy-dense molecule supported by an extensive existing infrastructure for storage and transportation. This bio-based conversion takes place in anaerobic environments, where complex metabolic and ecological dynamics regulate microbial activity and interaction. Understanding the microbial dynamics driving the carbon conversion aided with hydrogen– is fundamental to regulate process stability. Microbiology has long sought to investigate the features of microbes, both as individuals and communities. However, the difficulties in culturing and the specificity of microbial dynamics have rendered the microscopic universe elusive to classical methods. In the last decade, system biology has emerged as an alternative to uncover the hidden intricacies of this universe. Specifically, genome-scale metabolic modelling, by enabling the integration of genomic data and environmental factors to simulate microbial metabolism and community-level behavior, offers a powerful tool to tackle complex challenges. Metabolic modelling has the potential to provide valuable insights into the role of different species in biomethanation processes and strategies for the processes optimization. This thesis focused on applying metabolic modelling to investigate the microbial dynamics behind biomethanation across two case studies and on developing a computational tool to improve genome-scale metabolic model reconstruction of microbial species that have not yet been isolated. The first case study explored the microbial consortia of biofilms formed in four ex-situ biogas upgrading reactors. Through metagenomic analyses, this research identified key anaerobic digestion species, such as Methanothermobacter wolfeii and Limnochordia sp., and elucidated their roles in the trophic network, particularly in formate transfer and amino acid exchanges. These findings provided insights into which species act as keystones in anaerobic systems and how their metabolic potential enables consortia to adapt to the selective conditions of carbon fixation. The second case study investigated the impact of trace metals on the post-starvation recovery of methanogenic communities. Specifically, it assessed how supplementation with nickel and cobalt, essential cofactors for methanogenic enzymes, affected microbiome structure and methane production rates. Using a combination of metabolic modelling and metatranscriptomics, the study demonstrated that nickel supplementation accelerated the recovery of methanogenic activity following starvation. This underscored the role of trace metals in overcoming metabolic bottlenecks caused by hydrogen and carbon deprivation and provided practical insights for improving reactor efficiency through micronutrient management. Additionally, this thesis introduced a novel framework, pan-Draft, to obtain high quality species-level metabolic models by integrating shared genetic evidence across multiple metagenome assemble genomes. This approach significantly improved model accuracy and facilitated the reconstruction of reliable genome-scale metabolic models. This work highlighted the importance of syntrophic interactions in carbon dioxide conversion and contributed to advancing our understanding of microbial dynamics. The findings align with the European goals of fostering a circular economy and renewable energy systems, offering sustainable solutions to global energy challenges.