Designing microbial metabolic interactions to secure microbial fuel cell performance across organic load variability in pineapple wastewater

Microbial fuel cells (MFCs) offer a promising solution for energy recovery from industrial wastewater, yet their performance is highly sensitive to microbial community dynamics disrupted by fluctuating organic loads. This study presents a model-based approach to understanding and stabilizing MFC performance in sulfide-rich wastewater from a canned-pineapple factory. We developed a microbe-microbe interaction genome-scale metabolic model (mmGEM) incorporating three key microbial guilds: sulfate-reducing bacteria (SRB), methanogens (MET), and sulfide-oxidizing bacteria (SOB). The model revealed a community shift from SOB-dominance at low organic loading rates (L-OLRs) to MET-dominance at high OLRs (H-OLRs), correlating with reduced MFC efficiency. Simulations showed that SOB growth is inhibited at H-OLRs due to diminished sulfate-sulfide cycling and restricted acetate cross-feeding with SRB, resulting in increased metabolite flow to MET and their competitive advantage. Scenario-based simulations further demonstrated how elevated acidity exacerbates SOB suppression, compounding performance loss. These findings highlight the pivotal role of metabolic interactions in microbial adaptation and provide a framework for engineering resilient MFC systems under variable industrial conditions.