In the current COVID-19 pandemic, a significant proportion of cases shed SARS-Coronavirus-2 (SARS-CoV-2) with their faeces. To determine if SARS-CoV-2 RNA was present in sewage during the emergence of COVID-19 in The Netherlands, sewage samples of six cities and the airport were tested using four qRT-PCR assays, three targeting the nucleocapsid gene (N1−N3) and one the envelope gene (E). No SARS-CoV-2 RNA was detected on February 6, 3 weeks before the first Dutch case was reported. On March 4/5, one or more gene fragments were detected in sewage of three sites, in concentrations of 2.6−30 gene copies per mL. In Amersfoort, N3 was detected in sewage 6 days before the first cases were reported. As the prevalence of COVID-19 in these cities increased in March, the RNA signal detected by each qRT-PCR assay increased, for N1−N3 up to 790−2200 gene copies per mL. This increase correlated significantly with the increase in reported COVID-19 prevalence. The detection of the virus RNA in sewage, even when the COVID-19 prevalence is low, and the correlation between concentration in sewage and reported prevalence of COVID-19, indicate that sewage surveillance could be a sensitive tool to monitor the circulation of the virus in the population.

In the current COVID-19 pandemic, a significant proportion of cases shed SARS-Coronavirus-2 (SARS-CoV-2) with their faeces. To determine if SARS-CoV-2 is present in sewage during the emergence of COVID-19 in the Netherlands, sewage samples of 7 cities and the airport were tested using RT-PCR against three fragments of the nucleocapsid protein gene (N1-3) and one fragment of the envelope protein gene (E). No SARS-CoV-2 was detected in samples of February 6, three weeks before the first case was reported in the Netherlands on February 27. On March 5, the N1 fragment was detected in sewage of five sites. On March 15/16, the N1 fragment was detected in sewage of six sites, and the N3 and E fragment were detected at 5 and 4 sites respectively. This is the first report of detection of SARS-CoV-2 in sewage. The detection of the virus in sewage, even when the COVID-19 prevalence is low, indicates that sewage surveillance could be a sensitive tool to monitor the circulation of the virus in the population.

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Wastewater surveillance has shown to be a valuable and efficient tool to obtain information about the trends of COVID-19 in the community. Since the recent emergence of new variants, associated with increased transmissibility and/or antibody escape (variants of concern), there is an urgent need for methods that enable specific and timely detection and quantification of the occurrence of these variants in the community. In this study, we demonstrate the use of RT-ddPCR on wastewater samples for specific detection of mutation N501Y. This assay enabled simultaneous enumeration of lineage B.1.351 (containing the 501Y mutation) and Wild Type (WT, containing 501N) SARS-CoV-2 RNA. Detection of N501Y was possible in samples with mixtures of WT with low proportions of B.1.351 (0.5%) and could accurately determine the proportion of N501Y and WT in mixtures of SARS-CoV-2 RNA. The application to raw sewage samples from the cities of Amsterdam and Utrecht demonstrated that this method can be applied to wastewater samples. The emergence of N501Y in Amsterdam and Utrecht wastewater aligned with the emergence of B.1.1.7 as causative agent of COVID-19 in the Netherlands, indicating that RT-ddPCR of wastewater samples can be used to monitor the emergence of the N501Y mutation in the community. It also indicates that RT-ddPCR could be used for sensitive and accurate monitoring of current (like K417N, K417T, E484K, L452R) or future mutations present in SARS-CoV-2 variants of concern. Monitoring these mutations can be used to obtain insight in the introduction and spread of VOC and support public health decision-making regarding measures to limit viral spread or allocation of testing or vaccination.

The current SARS-CoV-2 pandemic has rapidly become a major global health problem for which public health surveillance is crucial to monitor virus spread. Given the presence of viral RNA in feces in around 40% of infected persons, wastewater-based epidemiology has been proposed as an addition to disease-based surveillance to assess the spread of the virus at the community level. Here we have explored the possibility of using next-generation sequencing (NGS) of sewage samples to evaluate the diversity of SARS-CoV-2 at the community level from routine wastewater testing, and compared these results with the virus diversity in patients from the Netherlands and Belgium. Phylogenetic analysis revealed the presence of viruses belonging to the most prevalent clades (19A, 20A and 20B) in both countries. Clades 19B and 20C were not identified, while they were present in clinical samples during the same period. Low frequency variant (LFV) analysis showed that some known LFVs can be associated with particular clusters within a clade, different to those of their consensus sequences, suggesting the presence of at least 2 clades within a single sewage sample. Additionally, combining genome consensus and LFV analyses we found a total of 57 unique mutations in the SARS-CoV-2 genome which have not been described before. In conclusion, this work illustrates how NGS analysis of wastewater can be used to approximate the diversity of SARS-CoV-2 viruses circulating in a community.

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Wastewater surveillance has shown to be a valuable and efficient tool to obtain information about the trends of COVID-19 in the community. Since the recent emergence of new variants, associated with increased transmissibility and/or antibody escape (variants of concern), there is an urgent need for methods that enable specific and timely detection and quantification of the occurrence of these variants in the community. In this study we demonstrate the use of RT-ddPCR on wastewater samples for specific detection of mutation N501Y. This assay enabled simultaneous enumeration of the concentration of variants with the 501Y mutation and Wild Type (WT, containing 501N) SARS-CoV-2 RNA. Detection of N501Y was possible in samples with mixtures of WT with low proportions of lineage B.1.351 (0.5%). The method could accurately determine the proportion of N501Y and WT in mixtures of SARS-CoV-2 RNA. The application to raw sewage samples from the cities of Amsterdam and Utrecht demonstrated that this method can be applied to determine the concentrations and the proportions of WT and N501Y containing SARS-CoV-2 RNA in wastewater samples. The emergence of N501Y in Amsterdam and Utrecht wastewater aligned with the emergence of B.1.1.7 as causative agent of COVID-19 in the Netherlands, indicating that RT-ddPCR of wastewater samples can be used to monitor the emergence of the N501Y mutation in the community. It also indicates that RT-ddPCR could be used for sensitive and accurate monitoring of current (like K417N, E484K) or future mutations present in SARS-CoV-2 variants of concern. Monitoring emergence of these mutations in the community via wastewater is rapid, efficient and valuable in supporting public health decision-making.

Social concern has raised during the last years due to the development of antibiotic resistance hotspots in different environmental compartments, including the edible parts of crops. To assess the influence of the water quality used for watering, we collected samples from soil, roots, leaves and beans from the legume plant Vicia faba (broad beans) in three agricultural peri-urban plots (Barcelona, NE Spain), irrigated with either groundwater, river water, or reclaimed water. Antibiotic resistance genes (ARGs) sul1, tetM, qnrS1, mecA, and blaTEM were quantified by real-time PCR, along with 16S rDNA and intl1 sequences, as proxies for bacterial abundance and integron prevalence, respectively. Microbiome composition of all samples were analyzed by high-throughput DNA sequencing. Results show a gradient of bacterial species diversity and of ARG prevalence from highly diverse soil samples to microbially-poor beans and leaves, in which Rhizobiales essentially displaced all other groups, and that presented very small loads of ARGs and integron sequences. The data suggest that the microbiome and the associated resistome were likely influenced by agricultural practices and water quality, and that future irrigation water legal standards should consider the specific Physiology of the different crop plants. 2