Multi-agent simulation predicts interspecies interaction in microbial electrolysis cell using waste sludge

Abstract:

[Background] Microbial electrochemical system (MES) is coupled with electrochemical reaction and anaerobic digestion process. It is one of the technologies for implementing simultaneously energy recovery and waste sludge treatment. Understanding the syntrophic interaction in electroactive biofilm and activated sludge will be helpful to enhance the ability and regulation of bioreactors. High-throughput nucleic acid sequencing technology has the disadvantages of high cost, long time consumption and unpredictability. Therefore, dynamic simulation of microbial community will effectively predict structure and function. [Objective] The evolution of thermodynamics and kinetics between microbial species in anaerobic digestion and bioelectrochemical system was studied. Under the different ecological conditions including electron donor, electron acceptor, temperature and pH value, the electron flow direction of substrate and the dynamic change of microbial community structure were analyzed. [Methods] A multi-agent-based simulation (MAS) model was established for the microbial electrolysis cell (MEC) fed with waste sludge to evaluate the energy efficiency, mass transfer efficiency, and electron transfer from substrate oxidation of MEC, and to simulate the real-time change of microbial community structure coupled with dynamic and thermodynamic analysis. It revealed the decisive factors affecting the electronic flow direction of MEC and the corresponding microbial community, and provided the basis research on interspecies interaction and dynamics in the biological treatment system in complex pollutants. [Results] The optimal energy transfer efficiency (0.2) and mass transfer efficiency (0.5) of the MEC using waste sludge were determined through MAS simulation. The predicted microbial community dynamics under MAS with thermodynamic and kinetic parameters agreed with the high-throughput sequencing of 16S rRNA gene. Propionic acid was not accumulated in MEC during long-term operation. [Conclusion] It confirms that MAS combined thermodynamic and kinetic parameters can real-time predict the microbial community dynamics. The research shows that multi-agent simulation provides a new method to monitor the change of microbial community structure, which is flexible to combine with high-throughput nucleic acid sequencing technology, and will become a new approach for the prediction and estimation of microbial community in the engineered and natural ecosystems.