Ecological assembly of activated sludge microbiomes under contrasting process configurations and influent regimes

Activated sludge microbial communities are central to pollutant removal and operational stability in petrochemical wastewater treatment plants (PWWTPs). However, in full-scale systems, the relative associations of process configuration and influent composition with microbial community organization and treatment performance remain difficult to disentangle. This study investigated four full-scale PWWTPs in Northeast China, including three oxic systems and one anoxic/oxic system receiving different proportions of petrochemical, mixed industrial, and domestic wastewater inputs. We combined 16S rRNA gene sequencing, phylogenetic bin-based null model analysis (iCAMP), and partial least squares path modeling (PLS-PM) to evaluate microbial community structure, inferred assembly patterns, and their associations with influent characteristics, effluent quality, and chemical oxygen demand (COD) removal. The oxic systems showed higher alpha diversity than the anoxic/oxic system, although this comparison was potentially influenced by differences in influent composition and site-specific operational conditions. Community composition differed among influent types, with Proteobacteria, Bacteroidota, Acidobacteriota, and Planctomycetota showing contrasting enrichment patterns. iCAMP indicated a predominance of stochastic assembly patterns in the oxic systems and deterministic assembly in the anoxic/oxic system. Core zOTUs, including members of Rhodocyclaceae, Pseudomonadaceae, and Candidatus Berkiella, were associated with COD and nitrogen removal, supporting their potential as ecological indicators of treatment performance. Within the PLS-PM, influent characteristics showed stronger direct statistical associations with COD removal than process configuration, whereas process-related associations were represented mainly by indirect paths through microbial community composition. These findings highlight the joint influence of influent composition and process configuration on activated sludge microbial communities and treatment performance while providing an ecological basis for future microbiome-informed monitoring and process diagnosis in PWWTPs.