INTEGRATING ANALYSIS OF MICROBIAL COMMUNITY COMPOSITION AND FUNCTIONAL CAPACITY IN MEMBRANE BIOREACTOR TECHNOLOGY APPLIED TO RURAL WASTEWATER TREATMENT

Abstract

Rural wastewater treatment remains critically underserved, with 80% of wastewater in developing regions discharged untreated, threatening public health and ecosystems. This study integrates 16S rRNA sequencing, metagenomics, and metatranscriptomics to resolve the taxonomy-function relationship governing membrane bioreactor (MBR) performance under rural conditions. Deploying aerobic and anaerobic MBRs across three climatically distinct rural communities over 18 months revealed that Proteobacteria (38.7%), Bacteroidetes (22.3%), and Chloroflexi (14.8%) dominated the core microbiome, with 36,420 functional genes driving nutrient removal. Membrane fouling correlated strongly (R²=0.87) with EPS-producing taxa (Thauera, Zoogloea) and quorum-sensing genes, not biomass concentration, enabling 72-hour fouling prediction. Functional redundancy buffered treatment efficiency (>89% N removal) despite 40% seasonal taxonomic turnover, while transcript-informed aeration control reduced energy use by 27.4%. This microbiome-informed framework enables predictive MBR management, achieving >95% pollutant removal with 30% lower energy consumption for sustainable rural water reuse.