Antibiotic resistance surveillance through regional and up-to-date testing of clinical isolates is a foundation for implementing effective empirical treatment. Surveillance data also provides an overview of geographical and temporal changes that are invaluable for guiding interventions. Still, due to limited infrastructure and resources, clinical surveillance data is lacking in many parts of the world. Given that sewage is largely made up of human fecal bacteria from many people, sewage epidemiology could provide a cost-efficient strategy to partly fill the current gap in clinical surveillance of antibiotic resistance. Here we explored the potential of sewage metagenomic data to assess clinical antibiotic resistance prevalence using environmental and clinical surveillance data from across the world. The sewage resistome correlated to clinical surveillance data of invasive Escherichia coli isolates, but none of several tested approaches provided a sufficient resolution for clear discrimination between resistance towards different classes of antibiotics. However, in combination with socioeconomic data, the overall clinical resistance situation could be predicted with good precision. We conclude that analyses of bacterial genes in sewage could contribute to informing management of antibiotic resistance.

通过对临床分离株进行区域和最新检测进行抗生素耐药性监测是实施有效的经验性治疗的基础。监测数据还提供了地理和时间变化的概述，这对于指导干预措施非常有价值。尽管如此，由于基础设施和资源有限，世界许多地区仍缺乏临床监测数据。鉴于污水主要由许多人的粪便细菌组成，污水流行病学可以提供一种具有成本效益的策略，以部分填补当前抗生素耐药性临床监测的空白。在这里，我们探索了污水宏基因组数据利用世界各地的环境和临床监测数据评估临床抗生素耐药性流行率的潜力。污水耐药组与侵入性大肠杆菌分离株的临床监测数据相关，但几种测试方法都没有提供足够的分辨率来明确区分对不同类别抗生素的耐药性。然而，结合社会经济数据，可以很好地预测总体临床耐药情况。我们的结论是，对污水中细菌基因的分析可能有助于为抗生素耐药性管理提供信息。