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author:

Sun, Haoyu (Sun, Haoyu.) [1] | Xu, Fangyu (Xu, Fangyu.) [2] | Luo, Ruijia (Luo, Ruijia.) [3] | Liu, Ying (Liu, Ying.) [4] | Wang, Jiajun (Wang, Jiajun.) [5] | Lei, Bo (Lei, Bo.) [6] | Tang, Liang (Tang, Liang.) [7] | Pu, Xianjuan (Pu, Xianjuan.) [8] | Wu, Minghong (Wu, Minghong.) [9]

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EI

Abstract:

The increasing demand and use of antibiotics due to epidemic outbreaks under climate change leads to more antibacterial substances entering the environment. The residual drugs, commonly found as mixtures, can specially target bacteria, posing a threat to the ecosystem and human health. Therefore, it is necessary to assess the risk of antibiotic mixtures using bacteria as the model organisms. In this study, selecting sulfonamides, sulfonamides potentiators, and tetracyclines as the representative antibiotics, the individual and combined toxicity of these agents were tested against Gram-positive (Bacillus subtilis) and Gram-negative bacteria (Aliivibrio fischeri and Escherichia coli). The quantitative structure–activity relationship models were constructed by setting Ebind (lowest interaction energy between antibiotic and target protein) and Kow (octanol–water partition coefficient) as the structural descriptors, which provide reliable and robust tools for predicting the toxicity of single agents and binary mixtures. Furthermore, the hormetic effects, characterized by low-dose stimulation and high-dose inhibition, were observed in Gram-negative bacteria, and the dose-responses in Gram-positive bacteria all exhibited S-shaped. Within the hormetic phenomena of antibiotic mixtures, the pattern of joint toxic action and component contribution generally changed with the transition from stimulatory to inhibitory actions. These results not only demonstrate the influence of bacterial species and test endpoints on the toxicity of antibiotics, but also clarify the pivotal role of hormesis in the joint effects of antibiotics. This study provides a data-driven methodology for evaluating the combined toxicity of mixtures, which will promote the development of the risk assessment of antibiotics and other environmental pollutants. © 2025 The Author(s)

Keyword:

Antibiotics Bacteriology Binary mixtures Climate change Ecosystems Escherichia coli Health risks Toxicity

Community:

  • [ 1 ] [Sun, Haoyu]Key Laboratory of Organic Compound Pollution Control Engineering (MOE), School of Environmental and Chemical Engineering, Shanghai University, Shanghai; 200444, China
  • [ 2 ] [Xu, Fangyu]Key Laboratory of Organic Compound Pollution Control Engineering (MOE), School of Environmental and Chemical Engineering, Shanghai University, Shanghai; 200444, China
  • [ 3 ] [Luo, Ruijia]Key Laboratory of Organic Compound Pollution Control Engineering (MOE), School of Environmental and Chemical Engineering, Shanghai University, Shanghai; 200444, China
  • [ 4 ] [Liu, Ying]State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai; 200092, China
  • [ 5 ] [Wang, Jiajun]Key Laboratory of Organic Compound Pollution Control Engineering (MOE), School of Environmental and Chemical Engineering, Shanghai University, Shanghai; 200444, China
  • [ 6 ] [Lei, Bo]Key Laboratory of Organic Compound Pollution Control Engineering (MOE), School of Environmental and Chemical Engineering, Shanghai University, Shanghai; 200444, China
  • [ 7 ] [Tang, Liang]Key Laboratory of Organic Compound Pollution Control Engineering (MOE), School of Environmental and Chemical Engineering, Shanghai University, Shanghai; 200444, China
  • [ 8 ] [Pu, Xianjuan]School of Future Membrane Technology, Fuzhou University, Fujian, Fuzhou; 350108, China
  • [ 9 ] [Wu, Minghong]Key Laboratory of Organic Compound Pollution Control Engineering (MOE), School of Environmental and Chemical Engineering, Shanghai University, Shanghai; 200444, China
  • [ 10 ] [Wu, Minghong]School of Future Membrane Technology, Fuzhou University, Fujian, Fuzhou; 350108, China

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Source :

Environment International

ISSN: 0160-4120

Year: 2025

Volume: 202

1 0 . 3 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 1

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