Urban Resistom

拟议的项目是德累斯顿理工大学城市水管理主席和水生生物学主席之间的研究合作。该项目旨在检测和量化城市下水道系统对城市化水体中抗生素和抗生素耐药性基因的传播、动态和季节性的贡献。抗生素耐药性对人类健康和公共卫生系统具有很高的风险，因为它们存在于环境中的致病细菌和/或机会性细菌中，或被这些细菌感染。向环境排放耐药菌株的其他来源之一是下水道网络，这应该在我们的研究地点德累斯顿市内的洛克维茨巴赫集水区进行示范调查。那里已经有六个监测站在运行，配备了在线水量传感器。六分之四的人正在记录水质，包括自动取样器。其中两个站点专门用于河流监测，另外四个站点安装在排水系统中的雨水出口和一个联合下水道溢流(CSO)结构处，将污水排入洛克维茨巴赫。将使用和加强这一监测网络，以检测和抽样城市排水网络对抗生素耐药性的存在和传播的具体贡献。应对水和生物膜样本进行基于事件和季节性的抽样活动，并对化学和微生物参数进行分析，以检测下水道排污口的贡献模式以及细菌群落中抗生素耐药性的构成和存在的季节性趋势。此外，还将检查排放路径和下水道网络中重金属的残留，这些也是抗生素共同耐药性的选择。下水道流域的颗粒传输模型将与河流和下水道网络的水力模型相结合，并进行校准，以预测所获得的水质参数以及抗生素耐药基因排放模式。不同的处理方法将在模型中实施并进行评估。这些结果将提供关于可能的排放情景和途径的有价值的信息，以及它们对水环境中抗生素耐药性传播的重要性。

The proposed project is a research cooperation between the TU Dresden’s chair of Urban Water Management and the chair of Hydrobiology. The project aims to detect and quantify the contribution of a city’s sewer system on the spread, dynamics and seasonality of antibiotics and antibiotic resistance genes within an urbanized water body. Antibiotic resistance represents a high risk to human health as well as the public health system, due to their presence in, or acquisition by, pathogenic and/or opportunistic bacteria occurring in the environment. One among other emission sources of resistant strains into the environment is the sewer network, which should be exemplary investigated at our study site, the Lockwitzbach catchment within the city of Dresden. Six monitoring stations are already in operation there, equipped with online sensors for water quantity. Four out of six are recording water quality, including auto samplers. Two of the stations are dedicated to river monitoring, four further stations were mounted within the sewer system at rain water outlets and at a combined sewer overflow (CSO) structures, draining into Lockwitzbach. This monitoring network will be used and enhanced for the detection and sampling of specific contributions from the urban drainage network on the presence and dispersion of antibiotic resistances. Event-based and seasonal sampling campaigns coupled with analysis on chemical and microbiological parameters should be performed on water and biofilm samples to detect contribution patterns from the sewer outlets together with seasonal trends in composition and presence of antibiotic resistance in the bacterial community. Furthermore, emission pathways and the remaining of heavy metals from the sewer network, that also select for antibiotic co-resistancence, will be under examination. A particle transport model for the sewer catchment will be coupled with a hydraulic model for stream and sewer network and calibrated to predict gained water quality parameters as well as antibiotic resistant gene discharge patterns. Different treatment methods will be implemented in the model and evaluated. These results will yield valuable information on possible emission scenarios and pathways, as well as their importance on the spread of antibiotic resistance in the aquatic environment.