Identification of key degraders for controlling toxicity risks of disguised toxic pollutants with division of labor mechanisms in activated sludge microbiomes: Using nonylphenol ethoxylate as an example

Efficient management of disguised toxic pollutants (DTPs), which can undergo microbial degradation and convert into more toxic substances, necessitates the collaboration of diverse microbial populations in wastewater treatment plants. However, the identification of key bacterial degraders capable of controlling the toxicity risks of DTPs through division of labor mechanisms in activated sludge microbiomes has received limited attention. In this study, we investigated the key degraders capable of controlling the risk of estrogenicity associated with nonylphenol ethoxylate (NPEO), a representative DTP, in textile activated sludge microbiomes. The results of our batch experiments revealed that the transformation of NPEO into NP and subsequent NP degradation were the rate-limiting processes for controlling the risk of estrogenicity, resulting in an inverted V-shaped curve of estrogenicity in water samples during the biodegradation of NPEO by textile activated sludge. By utilizing enrichment sludge microbiomes treated with NPEO or NP as the sole carbon and energy source, a total of 15 bacterial degraders, including Sphingbium, Pseudomonas, Dokdonella, Comamonas, and Hyphomicrobium, were identified as capable of participating in these processes, Among them, Sphingobium and Pseudomonas were the two key degraders that could cooperatively interact in the degradation of NPEO with division of labor mechanisms. Co-culturing Sphingobium and Pseudomonas isolates exhibited a synergistic effect in degrading NPEO and reducing estrogenicity. Our study underscores the potential of the identified functional bacteria for controlling estrogenicity associated with NPEO and provides a methodological framework for identifying key cooperators engaged in labor division, contributing to the management of risks associated with DTPs by leveraging intrinsic microbial metabolic interactions.