Enhancing Biotransformation of Organic Micropollutants by Complex Microbial Communities Using Metabolic Modeling

Organic micropollutants (OMPs) from human activities present serious threats to ecosystems and human health. This project aims to identify the conditions and microorganisms that enhance OMP degradation by simulating nitrifying microbial communities. As a demonstration, we applied a proof-of-concept on Nitrosomonas europaea, the main nitrifier of the community. Its metabolic network was decomposed into so-called 91 modules of 3 to 10 reactions to reduce spurious identifications, representing 36% of network reactions. Transcript counts averaged at the module level were correlated with removal rates of OMPs and substrates. After running flux balance analysis for various values of substrate consumption, we monitored metabolic fluxes going through correlated modules. It showed that fluxes might be diverted toward modules correlating with atenolol degradation, while this effect was not observed for mycophenolic acid. It highlights the potential of this method to inform experimental design in complex bioprocesses.