Simultaneous detection and characterization of common respiratory pathogens in wastewater through genomic sequencing.

Genomic surveillance of SARS-CoV-2 has given insight into the evolution and epidemiology of the virus and its variant lineages during the COVID-19 pandemic. Expanding this approach to include a range of respiratory pathogens can better inform public health preparedness for potential outbreaks and epidemics. Here, we simultaneously sequenced 38 pathogens including influenza viruses, coronaviruses and bocaviruses, to examine the abundance and seasonality of respiratory pathogens in urban wastewater. We deployed a targeted bait capture method and short-read sequencing (Illumina Respiratory Virus Oligos Panel; RVOP) on composite wastewater samples from 8 wastewater treatment plants (WWTPs) and one associated hospital site. By combining seasonal sampling with whole genome sequencing, we were able to concurrently detect and characterise a range of common respiratory pathogens, including SARS-CoV-2, adenovirus and parainfluenza virus. We demonstrated that 38 respiratory pathogens can be detected at low abundances year-round, that hospital pathogen diversity is higher in winter vs. summer sampling events, and that significantly more viruses are detected in raw influent compared to treated effluent samples. Finally, we compared detection sensitivity of RT-qPCR vs. next generation sequencing for SARS-CoV-2, enteroviruses, influenza A/B, and respiratory syncytial viruses. We conclude that both should be used in combination; RT-qPCR allowed accurate quantification, whilst genomic sequencing detected pathogens at lower abundance. We demonstrate the valuable role of wastewater genomic surveillance and its contribution to the field of wastewater-based epidemiology, gaining rapid understanding of the seasonal presence and persistence for common respiratory pathogens. By simultaneously monitoring seasonal trends and early warning signs of many viruses circulating in communities, public health agencies can implement targeted prevention and rapid response plans.

Comparative assessment of Nanotrap and polyethylene glycol-based virus concentration in wastewater samples.

Wastewater-based epidemiology is now widely used in many countries for the routine monitoring of SARS-CoV-2 and other viruses at a community level. However, efficient sample processing technologies are still under investigation. In this study, we compared the performance of the novel Nanotrap® Microbiome Particles (NMP) concentration method to the commonly used polyethylene glycol (PEG) precipitation method for concentrating viruses from wastewater and their subsequent quantification and sequencing. For this, we first spiked wastewater with SARS-CoV-2, influenza and measles viruses and norovirus and found that the NMP method recovered 0.4%-21% of them depending on virus type, providing consistent and reproducible results. Using the NMP and PEG methods, we monitored SARS-CoV-2, influenza A and B viruses, RSV, enteroviruses and norovirus GI and GII and crAssphage in wastewater using quantitative PCR (qPCR)-based methods and next-generation sequencing. Good viral recoveries were observed for highly abundant viruses using both methods; however, PEG precipitation was more successful in the recovery of low-abundance viruses present in wastewater. Furthermore, samples processed with PEG precipitation were more successfully sequenced for SARS-CoV-2 than those processed with the NMP method. Virus recoveries were enhanced by high sample volumes when PEG precipitation was applied. Overall, our results suggest that the NMP concentration method is a rapid and easy virus concentration method for viral targets that are abundant in wastewater, whereas PEG precipitation may be more suited to the recovery and analysis of low-abundance viruses and for next generation sequencing.

National-scale antimicrobial resistance surveillance in wastewater: A comparative analysis of HT qPCR and metagenomic approaches.

Wastewater serves as an important reservoir of antimicrobial resistance (AMR), and its surveillance can provide insights into population-level trends in AMR to inform public health policy. This study compared two common high-throughput screening approaches, namely (i) high-throughput quantitative PCR (HT qPCR), targeting 73 antimicrobial resistance genes, and (ii) metagenomic sequencing. Weekly composite samples of wastewater influent were taken from 47 wastewater treatment plants (WWTPs) across Wales, as part of a national AMR surveillance programme, alongside 4 weeks of daily wastewater effluent samples from a large municipal hospital. Metagenomic analysis provided more comprehensive resistome coverage, detecting 545 genes compared to the targeted 73 genes by HT qPCR. It further provided contextual information critical to risk assessment (i.e. potential bacterial hosts). In contrast, HT qPCR exhibited higher sensitivity, quantifying all targeted genes including those of clinical relevance present at low abundance. When limited to the HT qPCR target genes, both methods were able to reflect the spatiotemporal dynamics of the complete metagenomic resistome, distinguishing that of the hospital and the WWTPs. Both approaches revealed correlations between resistome compositional shifts and environmental variables like ammonium wastewater concentration, though differed in their interpretation of some potential influencing factors. Overall, metagenomics provides more comprehensive resistome profiling, while qPCR permits sensitive quantification of genes significant to clinical resistance. We highlight the importance of selecting appropriate methodologies aligned to surveillance aims to guide the development of effective wastewater-based AMR monitoring programmes.