The antibiotic resistome in European UWTPs mirrors the gradient of north-to-south clinical antibiotic resistance prevalence.

There is increasing public concern regarding the fate of antibiotic resistance genes (ARGs) during wastewater treatment, their persistence during the treatment process and their potential impacts on the receiving water bodies. In this study, we used quantitative PCR (qPCR) to determine the abundance of nine ARGs and a class 1 integron associated integrase gene in 16 wastewater treatment plant (WWTP) effluents from ten different European countries. In order to assess the impact on the receiving water bodies, gene abundances in the latter were also analysed. Six out of the nine ARGs analysed were detected in all effluent and river water samples. Among the quantified genes, intI1 and sul1 were the most abundant. Our results demonstrate that European WWTP contribute to the enrichment of the resistome in the receiving water bodies with the particular impact being dependent on the effluent load and local hydrological conditions. The ARGs concentrations in WWTP effluents were found to be inversely correlated to the number of implemented biological treatment steps, indicating a possible option for WWTP management. Furthermore, this study has identified blaOXA-58 as a possible resistance gene for future studies investigating the impact of WWTPs on their receiving water.

Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5–10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary.

When antimicrobial resistant bacteria (ARB) and genes (ARGs) reach novel habitats, they can become part of the habitat’s microbiome in the long term if they are able to overcome the habitat’s biotic resilience towards immigration. This process should become more difficult with increasing biodiversity, as exploitable niches in a given habitat are reduced for immigrants when more diverse competitors are present. Consequently, microbial diversity could provide a natural barrier towards antimicrobial resistance by reducing the persistence time of immigrating ARB and ARG. To test this hypothesis, a pan-European sampling campaign was performed for structured forest soil and dynamic riverbed environments of low anthropogenic impact. In soils, higher diversity, evenness and richness were significantly negatively correlated with relative abundance of >85% of ARGs. Furthermore, the number of detected ARGs per sample were inversely correlated with diversity. However, no such effects were present in the more dynamic riverbeds. Hence, microbiome diversity can serve as a barrier towards antimicrobial resistance dissemination in stationary, structured environments, where long-term, diversity-based resilience against immigration can evolve.

River sediments are regarded as hot spots of bacterial density and activity. Moreover, high bacterial densities and biofilm formation are known to promote horizontal gene transfer, the latter playing a vital role in the spread of antimicrobial resistance. It can thus be hypothesized that sediments act as a reservoir of antibiotic resistant bacteria (ARB) and resistance genes (ARGs), particularly in rivers receiving microbes and drug residues from treated sewage. We analyzed the phenotypic susceptibility of 782 Escherichia coli isolates against 24 antimicrobials and we measured the relative abundances of five ARGs in water and sediment extracts of a small stream. We did not find evidence for a general increase in the proportion of resistant E. coli isolated from sediments as compared to those found in stream water. For most antimicrobials, the likelihood of detecting a resistant isolate was similar in water and sediment or it was even lower in the latter compartment. The mean relative abundance of ARGs was moderately increased in sediment-borne samples. Generally, absolute abundances of resistant cells and resistance genes in the sediment exceeded the pelagic level owing to higher bacterial densities. The river bottom thus represents a reservoir of ARB and ARGs that can be mobilized by resuspension.