Microbial community dynamics and biogas optimization in full-scale anaerobic digesters across South Korea
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Optimizing microbial communities in anaerobic digesters is essential to improving biogas production for sustainable energy. This study utilized high-throughput 16S rRNA gene sequencing to profile microbial communities from 18 full-scale biogasplants across South Korea, revealing key microbial patterns linked to performance. The bacterial consortia were dominated byFirmicutes, Bacteroidetes, Cloacimonetes, and Proteobacteria, with feedstock type exerting a marked influence on communitycomposition. Firmicutes predominated in FW-fed digesters that exhibited high methane yields (≥ 1 m³ CH₄ m⁻³ day⁻¹), whereasProteobacteria prevailed in activated sludge-fed systems characterized by lower methane production. Among archaeal families,Methanosarcinaceae, Methanomassiliicoccaceae, and Methanobacteriaceae were especially abundant in high-performingplants. Co-occurrence network analysis revealed a strong positive association between Firmicutes and Methanosarcinaceaein these reactors, indicative of synergistic metabolic interactions that enhance methane generation. Conversely, low-yieldplants showed prominent co-occurrence patterns between Proteobacteria and Methanosaetaceae, suggesting alternative orless efficient pathways of methanogenesis. Overall, our findings underscore the critical role of feedstock-dependent microbialnetworks in determining biogas plant performance, highlighting specific bacterial and archaeal groups as potential biomarkersfor monitoring and optimizing anaerobic digestion. These insights also lay a foundation for computational modeling aimed atpredicting metabolic outcomes based on microbiome data, ultimately contributing to more effective and sustainable biogasproduction.
Abstract
Optimizing microbial communities in anaerobic digesters is essential to improving biogas production for sustainable energy. This study utilized high-throughput 16S rRNA gene sequencing to profile microbial communities from 18 full-scale biogasplants across South Korea, revealing key microbial patterns linked to performance. The bacterial consortia were dominated byFirmicutes, Bacteroidetes, Cloacimonetes, and Proteobacteria, with feedstock type exerting a marked influence on communitycomposition. Firmicutes predominated in FW-fed digesters that exhibited high methane yields (≥ 1 m³ CH₄ m⁻³ day⁻¹), whereasProteobacteria prevailed in activated sludge-fed systems characterized by lower methane production. Among archaeal families,Methanosarcinaceae, Methanomassiliicoccaceae, and Methanobacteriaceae were especially abundant in high-performingplants. Co-occurrence network analysis revealed a strong positive association between Firmicutes and Methanosarcinaceaein these reactors, indicative of synergistic metabolic interactions that enhance methane generation. Conversely, low-yieldplants showed prominent co-occurrence patterns between Proteobacteria and Methanosaetaceae, suggesting alternative orless efficient pathways of methanogenesis. Overall, our findings underscore the critical role of feedstock-dependent microbialnetworks in determining biogas plant performance, highlighting specific bacterial and archaeal groups as potential biomarkersfor monitoring and optimizing anaerobic digestion. These insights also lay a foundation for computational modeling aimed atpredicting metabolic outcomes based on microbiome data, ultimately contributing to more effective and sustainable biogasproduction.