摘要

     人们越来越需要减少城市污水处理系统中细胞外抗生素耐药基因（ARGs）的排放。在这里，合成了分子印迹石墨碳氮化物（MIP-C3N4）纳米片，用于选择性光催化降解二级出水中编码ARG（blaNDM-1，编码耐多药的新德里金属-β-内酰胺酶-1）的质粒。鸟嘌呤分子印迹增强了ARG的吸附，提高了光生氧化产物降解blaNDM-1的利用率，而不被背景非目标组分清除。结果表明，在UVA（365nm，3.64×10-6einstein/L·s）照射下，MIP-C3N4（k=0.111±0.028min-1）对二级出水中blaNDM-1的光催化去除比裸石墨碳氮化物（k=0.003±0.001min-1）快37倍。MIP-C3N4能有效催化blaNDM-1的裂解，降低转化菌修复ARG的潜力。分子印迹也改变了主要的降解途径；电子空穴（h+）是主要的氧化物种，负责用MIP-C3N4去除blaNDM-1，而对涂层但未印迹的C3N4则是自由基（即，·OH和O2-）。总的来说，MIP-C3N4有效地去除了二级出水中的blaNDM-1，显示了分子印迹技术在提高光催化过程的选择性和效率以减轻污水处理系统中抗生素耐药性传播方面的潜力。

     There is a growing need to mitigate the discharge of extracellular antibiotic resistance genes (ARGs) from municipal wastewater treatment systems. Here, molecularly-imprinted graphitic carbon nitride (MIP-C₃N₄) nanosheets were synthesized for selective photocatalytic degradation of a plasmid-encoded ARG (bla_NDM-1, coding for multidrug resistance New Delhi metallo-β-lactamase-1) in secondary effluent. Molecular imprinting with guanine enhanced ARG adsorption, which improved the utilization of photogenerated oxidizing species to degrade bla_NDM-1 rather than being scavenged by background nontarget constituents. Consequently, photocatalytic removal of bla_NDM-1 in secondary effluent with MIP-C₃N₄ (k = 0.111 ± 0.028 min^-1) was 37 times faster than with bare graphitic carbon nitride (k = 0.003 ± 0.001 min^-1) under UVA irradiation (365 nm, 3.64 × 10^-6 Einstein/L·s). MIP-C₃N₄ can efficiently catalyze the fragmentation of bla_NDM-1, which decreased the potential for ARG repair by transformed bacteria. Molecular imprinting also changed the primary degradation pathway; electron holes (h⁺) were the predominant oxidizing species responsible for bla_NDM-1 removal with MIP-C₃N₄ versus free radicals (i.e., ·OH and O₂^-) for coated but nonimprinted C₃N₄. Overall, MIP-C₃N₄ efficiently removed bla_NDM-1 from secondary effluent, demonstrating the potential for molecular imprinting to enhance the selectivity and efficacy of photocatalytic processes to mitigate dissemination of antibiotic resistance from sewage treatment systems.

      https://pubs.acs.org/doi/10.1021/acs.est.9b06926