Urban Resistom

拟议的项目是德累斯顿工业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以及公共卫生系统构成高风险，因为它们存在于环境中发生的致病性和/或机会性细菌中，或被其获得。耐药菌株进入环境的其他排放源之一是下水道网络，这应该是在我们的研究地点，德累斯顿市内的Lockwitzbach集水区进行示范性调查。六个监测站已经在那里运行，配备了在线水量传感器。六分之四的人正在记录水质，包括自动采样器。其中两个监测站专门用于河流监测，另外四个监测站安装在雨水出口和联合下水道溢流（CSO）结构的下水道系统内，排入Lockwitzbach。这一监测网络将用于检测和采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。基于事件和季节性的抽样活动 此外，还应分析水质和生物膜样本的化学和微生物参数，以检测污水出口的排放模式，以及细菌群落的组成和耐药性的季节性趋势。此外，还将检查排放途径和下水道网络中剩余的重金属，这些重金属也选择抗生素共耐药性。污水集水区的颗粒传输模型将与河流和污水管网的水力模型相结合，并进行校准，以预测获得的水质参数以及抗生素耐药基因排放模式。将在模型中实施不同的处理方法并进行评价。这些结果将产生关于可能的排放情景和途径的有价值的信息，以及它们对水生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.