Humans and wildlife are exposed to an intractably large number of different combinations of chemicals via food, water, air, consumer products, and other media and sources. This raises concerns about their impact on public and environmental health. The risk assessment of chemicals for regulatory purposes mainly relies on the assessment of individual chemicals. If exposure to multiple chemicals is considered in a legislative framework, it is usually limited to chemicals falling within this framework and co-exposure to chemicals that are covered by a different regulatory framework is often neglected. Methodologies and guidance for assessing risks from combined exposure to multiple chemicals have been developed for different regulatory sectors, however, a harmonised, consistent approach for performing mixture risk assessments and management across different regulatory sectors is lacking. At the time of this publication, several EU research projects are running, funded by the current European Research and Innovation Programme Horizon 2020 or the Seventh Framework Programme. They aim at addressing knowledge gaps and developing methodologies to better assess chemical mixtures, by generating and making available internal and external exposure data, developing models for exposure assessment, developing tools for in silico and in vitro effect assessment to be applied in a tiered framework and for grouping of chemicals, as well as developing joint epidemiological-toxicological approaches for mixture risk assessment and for prioritising mixtures of concern. The projects EDC-MixRisk, EuroMix, EUToxRisk, HBM4EU and SOLUTIONS have started an exchange between the consortia, European Commission Services and EU Agencies, in order to identify where new methodologies have become available and where remaining gaps need to be further addressed. This paper maps how the different projects contribute to the data needs and assessment methodologies and identifies remaining challenges to be further addressed for the assessment of chemical mixtures.

The spread of antibiotic resistance in the water environment has been widely described. However, still many knowledge gaps exist regarding the selection pressure from antibiotics, heavy metals and other substances present in surface waters as a result of anthropogenic activities, as well as the extent and impact of this phenomenon on aquatic organisms and humans. In particular, the relationship between environmental concentrations of antibiotics and the acquisition of ARGs by antibiotic-sensitive bacteria as well as the impact of heavy metals and other selective agents on antimicrobial resistance (AMR) need to be defined. Currently, established safety values are based on the effects of antibiotic toxicity neglecting the question of AMR spread. In turn, risk assessment of antibiotics in waterbodies remains a complex question implicating multiple variables and unknowns reinforced by the lack of harmonized protocols and official guidelines. In the present review, we discussed current state-of-the-art and the knowledge gaps related to pressure exerted by antibiotics and heavy metals on aquatic environments and their relationship to the spread of AMR. Along with this latter, we reflected on (i) the risk assessment in surface waters, (ii) selective pressures contributing to its transfer and propagation and (iii) the advantages of metagenomics in investigating AMR. Furthermore, the role of microplastics in co-selection for metal and antibiotic resistance, together with the need for more studies in freshwater are highlighted.

A multiplex reverse transcription quantitative PCR (RT-qPCR)-based method was designed for the simultaneous detection of different SARS-CoV-2 genes. In this study, we used three target genes encoding for the nucleocapsid 1 and 3 (N1, N3), and the spike (S) proteins, all commonly used in the detection of SARS-CoV-2 in human and environmental samples. The performance of the multiplex assay, compared to the single assay was assessed for the standard calibration curve, required for absolute quantification, and then, for the real environmental samples to detect SARS-CoV-2. For this latter, four environmental samples were collected at a local wastewater treatment plant (WWTP). The results showed that the cycle threshold (Ct) values of the multiplex were comparable to the values obtained by the singleplex PCR. The amplification of the three target genes indicated the presence of SARS-CoV-2 in the four water samples with an increasing trend in February and these results were confirmed in the multiplex approach, showing the robustness of this method and its applicability for the relative abundance analysis among the samples. Overall, both the laboratory and field work results demonstrated that the multiplex PCR assay developed in this study could provide a method for SARS-CoV-2 detection as robust as the single qPCR, but faster and cost-effective, reducing by three times the number of reactions, and consequently the handling time and reagents.

Estrogenic compounds are widely released to surface waters and may cause adverse effects to sensitive aquatic species. Three hormones, estrone, 17β-estradiol and 17α-ethinylestradiol, are of particular concern as they are bioactive at very low concentrations. Current analytical methods are not all sensitive enough for monitoring these substances in water and do not cover mixture effects. Bioassays could complement chemical analysis since they detect the overall effect of complex mixtures. Here, four chemical mixtures and two hormone mixtures were prepared and tested as reference materials together with two environmental water samples by eight laboratories employing nine in vitro and in vivo bioassays covering different steps involved in the estrogenic response. The reference materials included priority substances under the European Water Framework Directive, hormones and other emerging pollutants. Each substance in the mixture was present at its proposed safety limit concentration (EQS) in the European legislation. The in vitro bioassays detected the estrogenic effect of chemical mixtures even when 17β-estradiol was not present but differences in responsiveness were observed. LiBERA was the most responsive, followed by LYES. The additive effect of the hormones was captured by ERα-CALUX, MELN, LYES and LiBERA. Particularly, all in vitro bioassays detected the estrogenic effects in environmental water samples (EEQ values in the range of 0.75-304 × EQS), although the concentrations of hormones were below the limit of quantification in analytical measurements. The present study confirms the applicability of reference materials for estrogenic effects' detection through bioassays and indicates possible methodological drawbacks of some of them that may lead to false negative/positive outcomes. The observed difference in responsiveness among bioassays - based on mixture composition - is probably due to biological differences between them, suggesting that panels of bioassays with different characteristics should be applied according to specific environmental pollution conditions.

This study aimed to investigate the bacterial diversity and the background level of antibiotic resistance in two freshwater ecosystems with low anthropogenic impact in order to evaluate the presence of natural antimicrobial resistance in these areas and its potential to spread downstream. Water samples from a pre-Alpine and an Apennine river (Variola and Tiber, respectively) were collected in three different sampling campaigns and bacterial diversity was assessed by 16S sequencing, while the presence of bacteria resistant to five antibiotics was screened using a culturable approach. Overall bacterial load was higher in the Tiber River compared with the Variola River. Furthermore, the study revealed the presence of resistant bacteria, especially the Tiber River showed, for each sampling, the presence of resistance to all antibiotics tested, while for the Variola River, the detected resistance was variable, comprising two or more antibiotics. Screening of two resistance genes on a total of one hundred eighteen bacterial isolates from the two rivers showed that bla_TEM, conferring resistance to β-lactam antibiotics, was dominant and present in ~58 % of isolates compared to only ~9 % for mefA/E conferring resistance to macrolides. Moreover, β-lactam resistance was detected in various isolates showing also resistance to additional antibiotics such as macrolides, aminoglycosides and tetracyclines. These observations would suggest the presence of co-resistant bacteria even in non-anthropogenic environments and this resistance may spread from the environment to humans and/or animals.