Abstract：
Antimicrobial resistance (AMR) undermines the United Nations Sustainable Development Goals of good health and well-being. Antibiotics are known to exacerbate AMR, but nonantibiotic antimicrobials, such as quaternary ammonium compounds (QACs), are now emerging as another significant driver of AMR. However, assessing the AMR risks of QACs in complex environmental matrices remains challenging due to the ambiguity in their chemical structures and antibacterial activity. By machine learning prediction and high-resolution mass spectrometric analysis, a list of antibacterial QACs (n = 856) from industrial chemical inventories is compiled, and it leads to the identification of 50 structurally diverse antibacterial QACs in sediments, including traditional hydrocarbon-based compounds and new subclasses that bear additional functional groups, such as choline, ester, betaine, aryl ether, and pyridine. Urban wastewater, aquaculture, and hospital discharges are the main factors influencing QAC distribution patterns in estuarine sediments. Toxic unit calculations and metagenomic analysis revealed that these QACs can influence antibiotic resistance genes (particularly sulfonamide resistance genes) through cross- and coresistances. The potential to influence the AMR is related to their environmental persistence. These results suggest that controlling the source, preventing the co-use of QACs and sulfonamides, and prioritizing control of highly persistent molecules will lead to global stewardship and sustainable use of QACs.
摘要：
抗菌素耐药性（AMR）破坏了联合国可持续发展目标的良好健康和福祉。已知抗生素会加剧AMR，但是非抗生素抗生素，例如季铵化合物(QAC)，现在正在成为AMR的另一个重要驱动力。然而,由于化学结构和抗菌活性的模糊性，评估QAC在复杂环境基质中的AMR风险仍然具有挑战性。通过机器学习预测和高分辨率质谱分析,编制了工业化学品清单中的抗菌QAC(n=856)清单，它导致了沉积物中50种结构多样的抗菌QAC的鉴定，包括传统的烃基化合物和带有额外官能团的新亚类，比如胆碱，酯,甜菜碱,芳基醚,还有吡啶.城市废水,水产养殖,和医院出院是影响河口沉积物QAC分布规律的主要因素。毒性单位计算和宏基因组分析显示，这些QAC可以通过交叉和共抗性影响抗生素抗性基因（特别是磺酰胺抗性基因）。影响AMR的潜力与其环境持久性有关。这些结果表明，控制源头，防止共同使用QAC和磺胺类药物，优先控制高持久性分子将导致全球管理和可持续使用QAC。
