Integrating Fungal-Bacterial Synergy to Enhance Circular MFC-Hydroponic Performance

Microbial fuel cells (MFCs) represent a promising technology for the simultaneous treatment of wastewater and bioelectricity generation. In this study, the MFCs are conceived as functional modules to be integrated into hydroponic cultivation systems, acting as a prosthetic rhizosphere capable of coupling wastewater treatment and bioelectrochemical activity with plant nutrition improvement. We compared the electrochemical performance of different microbial consortia comprising the electroactive bacterium Shewanella oneidensis, the plant growth promoting rhizobacterium (PGPR) Pseudomonas putida, and the plant biomass-degrading fungus Ophiostoma piceae, along with the supplementation with the quorum sensing (QS) analogue molecule 1{square} dodecanol. These microbial consortia are tested in MFCs fed with wastewater and root exudates to analyze enhanced feedstock assimilation, electricity production, and the generation of plant growth-promoting substances (PGPS). From an electrochemical perspective, we evaluated planktonic growth, anode adhesion, substrate consumption, and the production of redox-active molecules and PGPS such as flavins and siderophores respectively alongside key electrical production parameters, including current output and power. Among the different microbial configurations tested, the consortium combining S. oneidensis, P. putida, and O. piceae exhibited the highest electrical production potential. Moreover, within this framework, we detected the extracellular production of siderophores in MFCs containing P. putida, suggesting a potential role supporting hydroponic crop growth. Furthermore, the addition of 1-dodecanol led to an improvement of the bioelectrochemical parameters. These results highlight the potential of synthetic microbial consortia in MFC-based systems not only to enhance electricity generation from wastewater but also to provide added value in integrated hydroponic applications through rhizosphere-like functions.