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The single and combined inhibitory effects of different nitrophenols on the anaerobic toxicity assay (ATA) of anaerobic sludge and the variations in the content of extracellular polymeric substances (EPS) were investigated. The results indicated that 2,4-dinitrophenol (2,4-DNP) demonstrated the highest inhibitory effect, followed by 4-nitrophenol (4-NP) and 2-nitrophenol (2-NP), and the combined effects of binary and ternary nitrophenols induced additive toxicity. Furthermore, 2,4-DNP, the dominant toxic nitrophenol, at various concentrations and toxicant ratios, was the major contributor to the combined inhibitory effects of the nitrophenol mixtures. Abundant EPS could be secreted by the anaerobic sludge under the inhibitory effects of toxic 2-NP, 4-NP, and 2,4-DNP at concentrations from 0 to 200 mg/L to resist the adverse effects of the external environment. The protein contents of both loosely bound EPS (LB-EPS) and tightly bound EPS (TB-EPS) exhibited a better linear positive correlation relationship (R2 > 0.92) with the inhibitory rates of 2-NP, 4-NP, and 2,4-DNP, indicating that the proteins generated in the EPS of anaerobic sludge could be a stress response. Therefore, increasing the concentration of the toxic nitrophenols could enhance the stress response and increase protein production. Parallel factor (PARAFAC) analysis for TB-EPS and LB-EPS further confirmed that the major proteins were tyrosine, tryptophan, and aromatic proteins. Moreover, with an increase in the concentrations of 2-NP, 4-NP, and 2,4-DNP from 0 to 200 mg/L, microbial cell lysis and death in anaerobic sludge could be increasingly severe. Thus, this study provides new insights into the inhibitory effects of nitrophenol mixtures, which are frequently found in pharmaceutical and petrochemical effluents, on anaerobic sludge. Copyright © 2021 Elsevier Ltd. All rights reserved.

Citation

Zhuowei Zhang, Yin Yu, Hongbo Xi, Yuexi Zhou. Inhibitory effect of individual and mixtures of nitrophenols on anaerobic toxicity assay of anaerobic systems: Metabolism and evaluation modeling. Journal of environmental management. 2022 Feb 15;304:114237

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PMID: 34896800

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