饮用水深度处理生物活性炭工艺中抗性基因的行为特征及传播机制

Antibiotic resistance has been identified as one of the biggest threats to human health in recent Global Risks Report. Because of high correlation between drinking water and human health, Antiobiotic resistance genes (ARGs) in drinking water need to be focused on. However, there is still a lack of knowledge about the distribution and migration as well as transformation of ARGs in biological activated carbon (BAC) that serves as an advanced treatment in drinking water. The objective of this project is to definite the distribution of ARGs, bacterial community structure, signaling molecules (quorom sensing) from the drinking water treatment process of BAC in different areas, using modern analytical technology means, such as high-throughput real-time PCR, 16S rDNA sequencing, UPLC/MS/MS. Meanwhile, to analysis the relationship of ARGs and signaling molecules. Simulation systems in lab conditions will be set up to investigate the effect of technological and water quality parameters on ARGs and signaling molecules, explore the transfer and propagation of ARGs among the biofilm of BAC. Combined with the results of signaling molecules on conjugative transfer frequency of ARGs, we will build a model to evaluate the transfer and propagation of ARGs among the interface biofilm of BAC. This research project can help to evaluate the pollution of ARGs in drinking water scientifically and provide theoretical proofs to reveal the occurrence, transfer and proliferation of ARGs in drinking water as well as the effective control methods.

近年来全球风险报告已将抗生素抗性列为人类健康的最大威胁之一。饮用水与人类生活息息相关，但关于饮用水深度处理生物活性炭工艺中抗性基因的行为特征及迁移转化规律尚不明确。本项目采用高通量荧光定量PCR、16S rDNA高通量测序、超高效液相色谱/串联质谱等现代分析手段, 在表征不同区域饮用水深度处理生物活性炭工艺段抗性基因、细菌群落结构、信号分子分布特征的基础上，揭示抗性基因行为特征及影响规律；通过实验室模拟，明确工艺参数和水质参数对抗性基因、群感效应 (信号分子) 的影响；结合细菌信号分子影响抗性基因接合转移能力实验，阐述生物膜抗性基因转移与传播的主控因子及机制，建立抗性基因的转移与传播模型。本项目的研究有助于科学地评估饮用水厂生物活性炭工艺对抗性基因行为特征的影响，为揭示生物活性炭生物膜中抗性基因转移和传播规律，以及有效的控制方法提供理论依据。

本研究对杭州不同饮用水厂进行四季采样，采用高通量荧光定量PCR进行抗性基因的时空表征，解析了抗性基因的行为特征并判别了目标风险基因；结合实验室小试装置，建立了抗性基因在活性炭生物膜中传播模型，并揭示了生物活性炭工艺参数、微生物群落、微囊藻毒素、群体感应等因素对抗性基因传播的影响及其机理；针对市场上不同类型的六种家用活性炭净水器，进行长期模拟实验，利用宏基因组深入探究抗性基因的动态变化及影响因素。结果显示，饮用水厂中生物活性炭工艺会导致抗生素抗性污染加剧，出水中抗性基因检出数量由84个上升至159个，有29个抗性基因被识别为来自于活性炭生物膜且在氯消毒过程中富集，这些基因被认为是目标风险基因。对于不同类型的生物活性炭，煤质炭抗性基因污染程度小于木质炭，而载银活性炭由于银离子的抑菌效果，抗性基因污染水平最低。对于不同的空床接触时间，出水中生物膜污染程度不同，为保障处理前期的出水水质，综合考虑选择20 min的空床接触时间最为合适。反冲洗能有效减少抗性基因污染，而气洗的效果好于水洗和气水混洗。饮用水厂生物活性炭表面6种信号分子的浓度范围为0.01-0.76ng/mL，这些信号分子能诱导细菌间的群感效应，进而促进同菌种间抗性基因的水平转移，其中效果最显著的是C8-HSL。外源信号分子分泌菌也能不同程度提高抗性基因的水平转移，效果最显著的是Paenibacillus chibensis。吸附在活性炭上的微囊藻毒素与活性炭生物膜上的抗性基因呈现显著相关性,其对抗性基因接合转移促进作用的排序为：MC-LR>MC-YR>e-MCs>MC-RR。MCs的最佳接合浓度为10^-3 mg/L，与饮用水环境中MCs检出限值相同，需要引起重视。此外， SourceTracker溯源发现活性炭净水器生物膜对出水细菌群落结构的平均贡献达49%，对抗性基因的平均贡献也达到了34%，可移动遗传元件在生物膜抗性基因增殖与传播中发挥了重要作用。该研究聚焦饮用水生物活性炭工艺中抗性基因行为特征，揭示生物活性炭生物膜中抗性基因转移和传播规律，为有效控制饮用水生物活性炭工艺中抗性基因的传播提供理论依据和技术支撑。