Sustainable Food Waste Management in Anaerobic Digesters: Prediction of the Organic Load Impact by Metagenome-Scale Metabolic Modeling

Abstract

The increasing urbanization has led to rising waste and energy demands, necessitating innovative solutions. A sustainable food waste management approach involves anaerobic codigestion with sewage sludge, enhancing biogas production while managing waste. Although this technology has been successfully tested, the biological mechanisms determining its efficiency are still poorly understood. This study leverages genome-scale metabolic modeling of 138 metagenome-assembled genomes to explore species interactions in lab-scale anaerobic reactors fed with sewage sludge to increasing proportions of food waste. The models showed positive correlations with experimental biogas production (CH4: r = 0.54, CO2: r = 0.66), validating their reliability. The dominant methanogen, Methanothrix sp., adapted its metabolism based on feedstock, affecting methane yields, which ranged from 2.5 to 3 mmol/g of volatile solids·h with sewage sludge to 10–14 mmol/g of VS·h with high food waste. The integration of extracellular enzymes into the models highlighted the role in methane production of pectin degradation, protein hydrolysis, and lipid metabolism, mediated by Proteiniphilum sp., Kiritimatiellae sp., and Olb16 sp. The study identified 475 mutualistic interactions involving amino acid, hydrogen, acetate, and phosphate exchange and 44 competitive interactions in hydrolytic and fermentative processes. These insights can help optimize anaerobic digestion and sustainable waste management in urban settings.