With the global concerns on antibiotic resistance (AR) as a public health issue, it is pivotal to have data exchange platforms for studies on antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) in the environment. For this purpose, the NORMAN Association is hosting the NORMAN ARB&ARG database, which was developed within the European project ANSWER. The present article provides an overview on the database functionalities, the extraction and the contribution of data to the database. In this study, AR data from three studies from China and Nepal were extracted and imported into the NORMAN ARB&ARG in addition to the existing AR data from 11 studies (mainly European studies) on the database. This feasibility study demonstrates how the scientific community can share their data on AR to generate an international evidence base to inform AR mitigation strategies. The open and FAIR data are of high potential relevance for regulatory applications, including the development of emission limit values / environmental quality standards in relation to AR. The growth in sharing of data and analytical methods will foster collaboration on risk management of AR worldwide, and facilitate the harmonization in the effort for identification and surveillance of critical hotspots of AR. The NORMAN ARB&ARG database is publicly available at: https://www.norman-network.com/nds/bacteria/.

The aim of this study was to capture and explain changes in antibiotic resistance gene (ARG) presence and concentration internationally across the Rhine river. Intl1 concentrations and national antibiotic usage were investigated as proxies to predict anthropogenic ARG pollution. Newly-developed multiplex qPCR assays were employed to investigate ARG profiles across 8 locations (L1-L8) in three countries (Switzerland, Germany, the Netherlands) and to detect potential regional causes for variation. Two of these locations were further monitored, over the duration of one month. A total of 13 ARGs, Intl1 and 16S rRNA were quantified. ARG presence and concentrations initially increased from L1(Diepoldsau) to L3(Darmstadt). A continuous increase could not be observed at subsequent locations, with the large river volume likely being a major contributing factor for stability. ARG presence and concentrations fluctuated widely across different locations. L2(Basel) and L3 were the two most polluted locations, coinciding with these locations being well-developed pharmaceutical production locations. We draw attention to the characteristic, clearly distinct ARG profiles, with gene presence being consistent and gene concentrations varying significantly less over time than across different locations. Five genes were Rhine-typical (ermB, ermF, Intl1, sul1 and tetM). Intl1 and sul1 were the genes with highest and second-highest concentration, respectively. Aph(III)a and bla_OXA were permanently introduced downstream of L1, indicating no source of these genes prior to L1. We highlight that correlations between Intl1 and ARG concentrations (R² = 0.72) were driven by correlations to sul1 and disappeared when excluding sul1 from the analysis (R² = 0.05). Intl1 therefore seems to be a good proxy for sul1 concentrations but not necessarily for overall (anthropogenic) ARG pollution. Aminoglycoside usage per country correlated with concentrations of aph(III)a and several unrelated antibiotic resistance genes (bla_OXA ermB, ermF and tetM). This correlation can be explained by co-resistance caused by mobile genetic elements (MGEs), such as Tn1545.