Monitoring SARS-CoV-2 Populations in Wastewater by Amplicon Sequencing and Using the Novel Program SAM Refiner

SWAMPy: simulating SARS-CoV-2 wastewater amplicon metagenomes

MOTIVATION

Tracking SARS-CoV-2 variants through genomic sequencing has been an important part of the global response to the pandemic and remains a useful tool for surveillance of the virus. As well as whole-genome sequencing of clinical samples, this surveillance effort has been aided by amplicon sequencing of wastewater samples, which proved effective in real case studies. Because of its relevance to public healthcare decisions, testing and benchmarking wastewater sequencing analysis methods is also crucial, which necessitates a simulator. Although metagenomic simulators exist, none is fit for the purpose of simulating the metagenomes produced through amplicon sequencing of wastewater.

RESULTS

Our new simulation tool, SWAMPy (Simulating SARS-CoV-2 Wastewater Amplicon Metagenomes with Python), is intended to provide realistic simulated SARS-CoV-2 wastewater sequencing datasets with which other programs that rely on this type of data can be evaluated and improved. Our tool is suitable for simulating Illumina short-read RT-PCR amplified metagenomes.

AVAILABILITY AND IMPLEMENTATION

The code for this project is available at https://github.com/goldman-gp-ebi/SWAMPy. It can be installed on any Unix-based operating system and is available under the GPL-v3 license.

Highly sensitive wastewater surveillance of SARS-CoV-2 variants by targeted next-generation amplicon sequencing provides early warning of incursion in Victoria, Australia

The future of the COVID pandemic and its public health and societal impact will be determined by the profile and spread of emerging variants and the timely identification and response to them. Wastewater surveillance of SARS-CoV-2 has been widely adopted in many countries across the globe and has played an important role in tracking infection levels and providing useful epidemiological information that cannot be adequately captured by clinical testing alone. However, novel variants can emerge rapidly, spread globally, and markedly alter the trajectory of the pandemic, as exemplified by the Delta and Omicron variants. Most mutations linked to the emergence of new SARS-CoV-2 variants are found within variable regions of the SARS-CoV-2 Spike protein. We have developed a duplex hemi-nested PCR method that, coupled with short amplicon sequencing, allows simultaneous typing of two of the most highly variable and informative regions of the Spike gene: the N-terminal domain and the receptor binding motif. Using this method in an operationalized public health program, we identified the first known incursion of Omicron BA.1 into Victoria, Australia and demonstrated how sensitive amplicon sequencing methods can be combined with wastewater surveillance as a relatively low-cost solution for early warning of variant incursion and spread.IMPORTANCEThis study offers a rapid, cost-effective, and sensitive approach for monitoring SARS-CoV-2 variants in wastewater. The method's flexibility permits timely modifications, enabling the integration of emerging variants and adaptations to evolving SARS-CoV-2 genetics. Of particular significance for low- and middle-income regions with limited surveillance capabilities, this technique can potentially be utilized to study a range of pathogens or viruses that possess diverse genetic sequences, similar to influenza.

Wastewater surveillance together with metaviromic data revealed the unusual resurgence of infectious diseases after the first wave of the COVID-19 outbreak

How to address public health priorities after COVID-19 is becoming a critical task. To this end, we conducted wastewater surveillance for six leading pathogens, namely, SARS-CoV-2, norovirus, rotavirus, influenza A virus (IAV), enteroviruses and respiratory syncytial virus (RSV), in Nanchang city from January to April 2023. Metaviromic sequencing was conducted at the 1st, 4th, 7th, 9th, 12th and 14th weeks to reveal the dynamics of viral pathogens that were not covered by qPCR. Amplicon sequencing of the conserved region of norovirus GI and GII and the rotavirus and region encoding nonstructural protein of RSV was also conducted weekly. The results showed that after a rapid decrease in SARS-CoV-2 sewage concentrations occurred in January 2023, surges of norovirus, rotavirus, IAV and RSV started at the 6th, 7th, 8th and 11th weeks, respectively. The dynamics of the sewage concentrations of norovirus, rotavirus, IAV and RSV were consistent with the off-season resurgence of the above infectious diseases. Notably, peak sewage concentrations of norovirus GI, GII, rotavirus, IAV and RSV were found at the 6th, 3rd, 7th, 7th and 8th weeks, respectively. Astroviruses also resurge after the 7th week, as revealed by metaviromic data, suggesting that wastewater surveillance together with metaviromic data provides an essential early warning tool for revealing patterns of infectious disease resurgence.

RBD amplicon sequencing of wastewater reveals patterns of variant emergence and evolution

Rapid evolution of SARS-CoV-2 has resulted in the emergence of numerous variants, posing significant challenges to public health surveillance. Clinical genome sequencing, while valuable, has limitations in capturing the full epidemiological dynamics of circulating variants in the general population. This study utilized receptor-binding domain (RBD) amplicon sequencing of wastewater samples to monitor the SARS-CoV-2 community dynamics and evolution in El Paso, TX. Over 17 months, we identified 91 variants and observed waves of dominant variants transitioning from BA.2 to BA.2.12.1, BA.4&5, BQ.1, and XBB.1.5. Our findings demonstrated early detection of variants and identification of unreported outbreaks, while showing strong consistency with clinical genome sequencing data at the local, state, and national levels. Alpha diversity analyses revealed significant periodical variations, with the highest diversity observed in winter and the outbreak lag phases, likely due to lower competition among variants before the outbreak growth phase. The data underscores the importance of low transmission periods for rapid mutation and variant evolution. This study highlights the effectiveness of integrating RBD amplicon sequencing with wastewater surveillance in tracking viral evolution, understanding variant emergence, and enhancing public health preparedness.

Environmental Surveillance of Flood Control Infrastructure Impacted by Unsheltered Individuals Leads to the Detection of SARS-CoV-2 and Novel Mutations in the Spike Gene

In the United States, the growing number of people experiencing homelessness has become a socioeconomic crisis with public health ramifications, recently exacerbated by the COVID-19 pandemic. We hypothesized that the environmental surveillance of flood control infrastructure may be an effective approach to understand the prevalence of infectious disease. From December 2021 through July 2022, we tested for SARS-CoV-2 RNA from two flood control channels known to be impacted by unsheltered individuals residing in upstream tunnels. Using qPCR, we detected SARS-CoV-2 RNA in these environmental water samples when significant COVID-19 outbreaks were occurring in the surrounding community. We also performed whole genome sequencing to identify SARS-CoV-2 lineages. Variant compositions were consistent with those of geographically and temporally matched municipal wastewater samples and clinical specimens. However, we also detected 10 of 22 mutations specific to the Alpha variant in the environmental water samples collected during January 2022-one year after the Alpha infection peak. We also identified mutations in the spike gene that have never been identified in published reports. Our findings demonstrate that environmental surveillance of flood control infrastructure may be an effective tool to understand public health conditions among unsheltered individuals-a vulnerable population that is underrepresented in clinical surveillance data.

Tracing the origin of SARS-CoV-2 omicron-like spike sequences detected in an urban sewershed: a targeted, longitudinal surveillance study of a cryptic wastewater lineage

BACKGROUND

The origin of novel SARS-CoV-2 spike sequences found in wastewater, without corresponding detection in clinical specimens, remains unclear. We sought to determine the origin of one such cryptic wastewater lineage by tracking and characterising its persistence and genomic evolution over time.

METHODS

We first detected a cryptic lineage, WI-CL-001, in municipal wastewater in Wisconsin, USA, in January, 2022. To determine the source of WI-CL-001, we systematically sampled wastewater from targeted sub-sewershed lines and maintenance holes using compositing autosamplers. Viral concentrations in wastewater samples over time were measured by RT digital PCR. In addition to using metagenomic 12s rRNA sequencing to determine the virus's host species, we also sequenced SARS-CoV-2 spike receptor binding domains, and, where possible, whole viral genomes to identify and characterise the evolution of this lineage.

FINDINGS

We traced WI-CL-001 to its source at a single commercial building. There we detected the cryptic lineage at concentrations as high as 2·7 × 109 genome copies per L. The majority of 12s rRNA sequences detected in wastewater leaving the identified source building were human. Additionally, we generated over 100 viral receptor binding domain and whole-genome sequences from wastewater samples containing the cryptic lineage collected over the 13 consecutive months this virus was detectable (January, 2022, to January, 2023). These sequences contained a combination of fixed nucleotide substitutions characteristic of Pango lineage B.1.234, which circulated in humans in Wisconsin at low levels from October, 2020, to February, 2021. Despite this, mutations in the spike gene and elsewhere resembled those subsequently found in omicron variants.

INTERPRETATION

We propose that prolonged detection of WI-CL-001 in wastewater indicates persistent shedding of SARS-CoV-2 from a single human initially infected by an ancestral B.1.234 virus. The accumulation of convergent omicron-like mutations in WI-CL-001's ancestral B.1.234 genome probably reflects persistent infection and extensive within-host evolution. People who shed cryptic lineages could be an important source of highly divergent viruses that sporadically emerge and spread.

FUNDING

The Rockefeller Foundation, Wisconsin Department of Health Services, Centers for Disease Control and Prevention, National Institute on Drug Abuse, and the Center for Research on Influenza Pathogenesis and Transmission.

Omicron and Delta variant prevalence detection and identification during the fourth COVID-19 wave in Mexico using wastewater-based epidemiology

Objectives

To identify the SARS-CoV-2 variants Delta and Omicron during the fourth wave of the COVID-19 pandemic in Mexico using samples taken from 19 locations in 18 out of the 32 states.

Methods

The genetic material concentration was done with PEG/NaCl precipitation, SARS-CoV-2 presence was confirmed by reverse transcriptase-quantitative polymerase chain reaction assay, the variant detection was carried out using a commercial mutation detection panel kit, and variant/mutation confirmation was done by amplicon sequencing of receptor-binding domain target region. The study used 41 samples.

Results

The Delta variant was confirmed in two samples during August 2021 (Querétaro and CDMX) and in three samples during November 2021 (Aguascalientes, Ciudad Juárez campuses, and Nuevo Leon). In December 2021, another sample with the Delta variant was confirmed in Nuevo Leon. Between January to March 2022 only the presence of Omicron was confirmed, (variant BA.1). Additionally, in this period six samples were identified with the status "Variant Not Determined".

Conclusion

To our knowledge, this study is one of the first to identify Omicron and Delta variants with polymerase chain reaction in Mexico and Latin America and its distribution across the country with 56% Mexican states making it a viable alternative for variant detection without conducting a large quantity of sequencing of clinical tests.

An interpretative review of the wastewater-based surveillance of the SARS-CoV-2: where do we stand on its presence and concern?

Wastewater-based epidemiology (WBE) has been used for monitoring infectious diseases like polio, hepatitis, etc. since the 1940s. It is also being used for tracking the SARS-CoV-2 at the population level. This article aims to compile and assess the information for the qualitative and quantitative detection of the SARS-CoV-2 in wastewater. Based on the globally published studies, we highlight the importance of monitoring SARS-CoV-2 presence/detection in the wastewater and concurrently emphasize the development of early surveillance techniques. SARS-CoV-2 RNA sheds in the human feces, saliva, sputum and mucus that ultimately reaches to the wastewater and brings viral RNA into it. For the detection of the virus in the wastewater, different detection techniques have been optimized and are in use. These are based on serological, biosensor, targeted PCR, and next generation sequencing for whole genome sequencing or targeted amplicon sequencing. The presence of the SARS-CoV-2 RNA in wastewater could be used as a potential tool for early detection and devising the strategies for eradication of the virus before it is spread in the community. Additionally, with the right and timely understanding of viral behavior in the environment, an accurate and instructive model that leverages WBE-derived data may be created. This might help with the creation of technological tools and doable plans of action to lessen the negative effects of current viral epidemics or future potential outbreaks on public health and the economy. Further work toward whether presence of viral load correlates with its ability to induce infection, still needs evidence. The current increasing incidences of JN.1 variant is a case in point for continued early detection and surveillance, including wastewater.

Impact of reference design on estimating SARS-CoV-2 lineage abundances from wastewater sequencing data

BACKGROUND

Sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA from wastewater samples has emerged as a valuable tool for detecting the presence and relative abundances of SARS-CoV-2 variants in a community. By analyzing the viral genetic material present in wastewater, researchers and public health authorities can gain early insights into the spread of virus lineages and emerging mutations. Constructing reference datasets from known SARS-CoV-2 lineages and their mutation profiles has become state-of-the-art for assigning viral lineages and their relative abundances from wastewater sequencing data. However, selecting reference sequences or mutations directly affects the predictive power.

RESULTS

Here, we show the impact of a mutation- and sequence-based reference reconstruction for SARS-CoV-2 abundance estimation. We benchmark 3 datasets: (i) synthetic "spike-in"' mixtures; (ii) German wastewater samples from early 2021, mainly comprising Alpha; and (iii) samples obtained from wastewater at an international airport in Germany from the end of 2021, including first signals of Omicron. The 2 approaches differ in sublineage detection, with the marker mutation-based method, in particular, being challenged by the increasing number of mutations and lineages. However, the estimations of both approaches depend on selecting representative references and optimized parameter settings. By performing parameter escalation experiments, we demonstrate the effects of reference size and alternative allele frequency cutoffs for abundance estimation. We show how different parameter settings can lead to different results for our test datasets and illustrate the effects of virus lineage composition of wastewater samples and references.

CONCLUSIONS

Our study highlights current computational challenges, focusing on the general reference design, which directly impacts abundance allocations. We illustrate advantages and disadvantages that may be relevant for further developments in the wastewater community and in the context of defining robust quality metrics.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Air travel monitoring does not accelerate outbreak detection in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

Comparison of metagenomic and targeted methods for sequencing human pathogenic viruses from wastewater

IMPORTANCE

Most public health initiatives that monitor viruses in wastewater have utilized quantitative polymerase chain reaction (PCR) and whole genome PCR sequencing, mirroring techniques used for viral epidemiology in individuals. These techniques require prior knowledge of the target viral genome and are limited to monitoring individual or small groups of viruses. Metagenomic sequencing may offer an alternative strategy for monitoring a broad spectrum of viruses in wastewater, including novel and emerging pathogens. In this study, while amplicon sequencing gave high viral genome coverage, untargeted shotgun sequencing of total nucleic acid samples was unable to detect human pathogenic viruses with enough sensitivity for use in genomic epidemiology. Enrichment of shotgun libraries for respiratory viruses using hybrid-capture technology provided genotypic information on a range of viruses simultaneously, indicating strong potential for wastewater surveillance. This type of targeted metagenomics could be used for monitoring diverse targets, such as pathogens or antimicrobial resistance genes, in environmental samples.

Continued selection on cryptic SARS-CoV-2 observed in Missouri wastewater

Deep sequencing of wastewater to detect SARS-CoV-2 has been used during the COVID-19 pandemic to monitor viral variants as they appear and circulate in communities. SARS-CoV-2 lineages of an unknown source that have not been detected in clinical samples, referred to as cryptic lineages, are sometimes repeatedly detected from specific locations. We have continued to detect one such lineage previously seen in a Missouri site. This cryptic lineage has continued to evolve, indicating continued selective pressure similar to that observed in Omicron lineages.

Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics

Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Monitoring of air travel provides little benefit in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.

Wastewater genomic sequencing for SARS-CoV-2 variants surveillance in wastewater-based epidemiology applications

Wastewater-based epidemiology (WBE) has been widely used as a complementary approach to SARS-CoV-2 clinical surveillance. Wastewater genomic sequencing could provide valuable information on the genomic diversity of SARS-CoV-2 in the surveyed population. However, reliable detection and quantification of variants or mutations remain challenging. In this study, we used mock wastewater samples created by spiking SARS-CoV-2 variant standard RNA into wastewater RNA to evaluate the impacts of sequencing throughput on various aspects such as genome coverage, mutation detection, and SARS-CoV-2 variant deconvolution. We found that wastewater datasets with sequencing throughput greater than 0.5 Gb yielded reliable results in genomic analysis. In addition, using in silico mock datasets, we evaluated the performance of the adopted pipeline for variant deconvolution. By sequencing 86 wastewater samples covering more than 6 million people over 7 months, we presented two use cases of wastewater genomic sequencing for surveying COVID-19 in Hong Kong in WBE applications, including the replacement of Delta variants by Omicron variants, and the prevalence and development trends of three Omicron sublineages. Importantly, the wastewater genomic sequencing data were able to reveal the variant trends 16 days before the clinical data did. By investigating mutations of the spike (S) gene of the SARS-CoV-2 virus, we also showed the potential of wastewater genomic sequencing in identifying novel mutations and unique alleles. Overall, our study demonstrated the crucial role of wastewater genomic surveillance in providing valuable insights into the emergence and monitoring of new SARS-CoV-2 variants and laid a solid foundation for the development of genomic analysis methodologies for WBE of other novel emerging viruses in the future.

Wastewater surveillance uncovers regional diversity and dynamics of SARS-CoV-2 variants across nine states in the USA

Wastewater-based epidemiology (WBE) is a non-invasive and cost-effective approach for monitoring the spread of a pathogen within a community. WBE has been adopted as one of the methods to monitor the spread and population dynamics of the SARS-CoV-2 virus, but significant challenges remain in the bioinformatic analysis of WBE-derived data. Here, we have developed a new distance metric, CoVdist, and an associated analysis tool that facilitates the application of ordination analysis to WBE data and the identification of viral population changes based on nucleotide variants. We applied these new approaches to a large-scale dataset from 18 cities in nine states of the USA using wastewater collected from July 2021 to June 2022. We found that the trends in the shift between the Delta and Omicron SARS-CoV-2 lineages were largely consistent with what was seen in clinical data, but that wastewater analysis offered the added benefit of revealing significant differences in viral population dynamics at the state, city, and even neighborhood scales. We also were able to observe the early spread of variants of concern and the presence of recombinant lineages during the transitions between variants, both of which are challenging to analyze based on clinically-derived viral genomes. The methods outlined here will be beneficial for future applications of WBE to monitor SARS-CoV-2, particularly as clinical monitoring becomes less prevalent. Additionally, these approaches are generalizable, allowing them to be applied for the monitoring and analysis of future viral outbreaks.

Environmental genomic surveillance of SARS-CoV-2 in wastewater in Rio de Janeiro, Brazil

Wastewater-based epidemiology can be a complementary approach for monitoring SARS-CoV-2 prevalence, diversity, and geographic distribution. It is a complementary approach regarding its prevalence and diversity, and geographic distribution. The study aimed to evaluate the genetic diversity of SARS-CoV-2 in two wastewater treatment plants (WWTPs) in Rio de Janeiro, Brazil. Samples were collected over a period of January to December 2021 and were concentrated with PEG8000 and the presence of SARS-CoV-2 was detected using E and N1 genes. Partial sequencing of the SARS-CoV-2 genomes resulted in the identification of variants of concern and variants of interest throughout the collection period. It was possible to identify the Mu, Delta, Gamma and Omicron variants in WWTP1; on the contrary, no variants were observed in WWTP2. To the best of our knowledge, we detected the variant Mu (B.1.621) containing characteristic mutations (S:E484K, S:N501Y) from WWTP, for the first time, in Brazil. Another Mu variant detected from clinical surveillance was announced one month after our finding. The detection of SARS-CoV-2 in wastewater can serve as a tool to monitor the prevalence and epidemiology in each community, helping to understand the spread of the virus among the population.

Wastewater surveillance of SARS-CoV-2 genomic populations on a country-wide scale through targeted sequencing

SARS-CoV-2 surveillance of viral populations in wastewater samples is recognized as a useful tool for monitoring epidemic waves and boosting health preparedness. Next generation sequencing of viral RNA isolated from wastewater is a convenient and cost-effective strategy to understand the molecular epidemiology of SARS-CoV-2 and provide insights on the population dynamics of viral variants at the community level. However, in low- and middle-income countries, isolated groups have performed wastewater monitoring and data has not been extensively shared in the scientific community. Here we report the results of monitoring the co-circulation and abundance of variants of concern (VOCs) of SARS-CoV-2 in Uruguay, a small country in Latin America, between November 2020-July 2021 using wastewater surveillance. RNA isolated from wastewater was characterized by targeted sequencing of the Receptor Binding Domain region within the spike gene. Two computational approaches were used to track the viral variants. The results of the wastewater analysis showed the transition in the overall predominance of viral variants in wastewater from No-VOCs to successive VOCs, in agreement with clinical surveillance from sequencing of nasal swabs. The mutations K417T, E484K and N501Y, that characterize the Gamma VOC, were detected as early as December 2020, several weeks before the first clinical case was reported. Interestingly, a non-synonymous mutation described in the Delta VOC, L452R, was detected at a very low frequency since April 2021 when using a recently described sequence analysis tool (SAM Refiner). Wastewater NGS-based surveillance of SARS-CoV-2 is a reliable and complementary tool for monitoring the introduction and prevalence of VOCs at a community level allowing early public health decisions. This approach allows the tracking of symptomatic and asymptomatic individuals, who are generally under-reported in countries with limited clinical testing capacity. Our results suggests that wastewater-based epidemiology can contribute to improving public health responses in low- and middle-income countries.

MixviR: an R Package for Exploring Variation Associated with Genomic Sequence Data from Environmental SARS-CoV-2 and Other Mixed Microbial Samples

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)/coronavirus disease 2019 (COVID-19) pandemic has highlighted an important role for efficient surveillance of microbial pathogens. High-throughput sequencing technologies provide valuable surveillance tools, offering opportunities to conduct high-resolution monitoring from diverse sample types, including from environmental sources. However, given their large size and potential to contain mixtures of lineages within samples, such genomic data sets can present challenges for analyzing the data and communicating results with diverse stakeholders. Here, we report MixviR, an R package for exploring, analyzing, and visualizing genomic data from potentially mixed samples of a target microbial group. MixviR characterizes variation at both the nucleotide and amino acid levels and offers the RShiny interactive dashboard for exploring data. We demonstrate MixviR's utility with validation studies using mixtures of known lineages from both SARS-CoV-2 and Mycobacterium tuberculosis and with a case study analyzing lineages of SARS-CoV-2 in wastewater samples over time at a sampling location in Ohio, USA. IMPORTANCE High-throughput sequencing technologies hold great potential for contributing to genomic-based surveillance of microbial diversity from environmental samples. However, the size of the data sets, along with the potential for environmental samples to contain multiple evolutionary lineages of interest, present challenges around analyzing and effectively communicating inferences from these data sets. The software described here provides a novel and valuable tool for exploring such data. Though originally designed and used for monitoring SARS-CoV-2 lineages in wastewater, it can also be applied to analyses of genomic diversity in other microbial groups.

One health genomic surveillance and response to a university-based outbreak of the SARS-CoV-2 Delta AY.25 lineage, Arizona, 2021

Genomic surveillance and wastewater tracking strategies were used to strengthen the public health response to an outbreak of the SARS-CoV-2 Delta AY.25 lineage associated with a university campus in Arizona. Epidemiologic and clinical data routinely gathered through contact tracing were matched to SARS-CoV-2 genomes belonging to an outbreak of AY.25 identified through ongoing phylogenomic analyses. Continued phylogenetic analyses were conducted to further describe the AY.25 outbreak. Wastewater collected twice weekly from sites across campus was tested for SARS-CoV-2 by RT-qPCR, and subsequently sequenced to identify variants. The AY.25 outbreak was defined by a single mutation (C18804T) and comprised 379 genomes from SARS-CoV-2 positive cases associated with the university and community. Several undergraduate student gatherings and congregate living settings on campus likely contributed to the rapid spread of COVID-19 across the university with secondary transmission into the community. The clade defining mutation was also found in wastewater samples collected from around student dormitories a week before the semester began, and 9 days before cases were identified. Genomic, epidemiologic, and wastewater surveillance provided evidence that an AY.25 clone was likely imported into the university setting just prior to the onset of the Fall 2021 semester, rapidly spread through a subset of the student population, and then subsequent spillover occurred in the surrounding community. The university and local public health department worked closely together to facilitate timely reporting of cases, identification of close contacts, and other necessary response and mitigation strategies. The emergence of new SARS-CoV-2 variants and potential threat of other infectious disease outbreaks on university campuses presents an opportunity for future comprehensive One Health genomic data driven, targeted interventions.

Genetic diversity and evolutionary convergence of cryptic SARS- CoV-2 lineages detected via wastewater sequencing

Wastewater-based epidemiology (WBE) is an effective way of tracking the appearance and spread of SARS-COV-2 lineages through communities. Beginning in early 2021, we implemented a targeted approach to amplify and sequence the receptor binding domain (RBD) of SARS-COV-2 to characterize viral lineages present in sewersheds. Over the course of 2021, we reproducibly detected multiple SARS-COV-2 RBD lineages that have never been observed in patient samples in 9 sewersheds located in 3 states in the USA. These cryptic lineages contained between 4 to 24 amino acid substitutions in the RBD and were observed intermittently in the sewersheds in which they were found for as long as 14 months. Many of the amino acid substitutions in these lineages occurred at residues also mutated in the Omicron variant of concern (VOC), often with the same substitutions. One of the sewersheds contained a lineage that appeared to be derived from the Alpha VOC, but the majority of the lineages appeared to be derived from pre-VOC SARS-COV-2 lineages. Specifically, several of the cryptic lineages from New York City appeared to be derived from a common ancestor that most likely diverged in early 2020. While the source of these cryptic lineages has not been resolved, it seems increasingly likely that they were derived from long-term patient infections or animal reservoirs. Our findings demonstrate that SARS-COV-2 genetic diversity is greater than what is commonly observed through routine SARS-CoV-2 surveillance. Wastewater sampling may more fully capture SARS-CoV-2 genetic diversity than patient sampling and could reveal new VOCs before they emerge in the wider human population.

SARS-CoV-2 and other respiratory pathogens are detected in continuous air samples from congregate settings

Two years after the emergence of SARS-CoV-2, there is still a need for better ways to assess the risk of transmission in congregate spaces. We deployed active air samplers to monitor the presence of SARS-CoV-2 in real-world settings across communities in the Upper Midwestern states of Wisconsin and Minnesota. Over 29 weeks, we collected 527 air samples from 15 congregate settings. We detected 106 samples that were positive for SARS-CoV-2 viral RNA, demonstrating that SARS-CoV-2 can be detected in continuous air samples collected from a variety of real-world settings. We expanded the utility of air surveillance to test for 40 other respiratory pathogens. Surveillance data revealed differences in timing and location of SARS-CoV-2 and influenza A virus detection. In addition, we obtained SARS-CoV-2 genome sequences from air samples to identify variant lineages. Collectively, this shows air sampling is a scalable, high throughput surveillance tool that could be used in conjunction with other methods for detecting respiratory pathogens in congregate settings.

Direct comparison of RT-ddPCR and targeted amplicon sequencing for SARS-CoV-2 mutation monitoring in wastewater

Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for identification and analysis of variants. However, when applied to environmental samples such as wastewater, it remains unclear how sensitive this method is for detecting variant-associated mutations in environmental samples. Here we directly compare a targeted amplicon sequencing approach (using ARTIC v3; hereafter referred to as sequencing) with RT-ddPCR quantification for the detection of five mutations that are characteristic of variants of concern (VoCs) in wastewater samples. In total, 547 wastewater samples were analyzed using both methods in parallel. When we observed positive mutation detections by RT-ddPCR, 42.6% of the detection events were missed by sequencing, due to negative detection or the limited read coverage at the mutation position. Further, when sequencing reported negative or depth-limited mutation detections, 26.7% of those events were instead positive detections by RT-ddPCR, highlighting the relatively poor sensitivity of sequencing. No or weak associations were observed between quantitative measurements of target mutations determined by RT-ddPCR and sequencing. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on sequencing.

Direct comparison of RT-ddPCR and targeted amplicon sequencing for SARS-CoV-2 mutation monitoring in wastewater

Over the course of the COVID-19 pandemic, variants of SARS-CoV-2 have emerged that are more contagious and more likely to cause breakthrough infections. Targeted amplicon sequencing approach is a gold standard for identification and analysis of variants. However, when applied to environmental samples such as wastewater, it remains unclear how sensitive this method is for detecting variant-associated mutations in environmental samples. Here we directly compare a targeted amplicon sequencing approach (using ARTIC v3; hereafter referred to as sequencing) with RT-ddPCR quantification for the detection of five mutations that are characteristic of variants of concern (VoCs) in wastewater samples. In total, 547 wastewater samples were analyzed using both methods in parallel. When we observed positive mutation detections by RT-ddPCR, 42.6% of the detection events were missed by sequencing, due to negative detection or the limited read coverage at the mutation position. Further, when sequencing reported negative or depth-limited mutation detections, 26.7% of those events were instead positive detections by RT-ddPCR, highlighting the relatively poor sensitivity of sequencing. No or weak associations were observed between quantitative measurements of target mutations determined by RT-ddPCR and sequencing. These findings caution the use of quantitative measurements of SARS-CoV-2 variants in wastewater samples determined solely based on sequencing.

Wastewater Sequencing-An Innovative Method for Variant Monitoring of SARS-CoV-2 in Populations

The SARS-CoV-2 outbreak has already affected more than 555 million people, and 6.3 million people have died. Due to its high infectivity, it is crucial to track SARS-CoV-2 outbreaks early to prevent the spread of infection. Wastewater monitoring appears to be a powerful and effective tool for managing epidemiological situations. Due to emerging mutations of SARS-CoV-2, there is a need to monitor mutations in order to control the pandemic. Since the sequencing of randomly chosen individuals is time-consuming and expensive, sequencing of wastewater plays an important role in revealing the dynamics of infection in a population. The sampling method used is a crucial factor and significantly impacts the results. Wastewater can be collected as a grab sample or as a 24 h composite sample. Another essential factor is the sample volume, as is the method of transport used. This review discusses different pretreatment procedures and RNA extraction, which may be performed using various methods, such as column-based extraction, TRIzol, or magnetic extraction. Each of the methods has its advantages and disadvantages, which are described accordingly. RT-qPCR is a procedure that confirms the presence of SARS-CoV-2 genes before sequencing. This review provides an overview of currently used methods for preparing wastewater samples, from sampling to sequencing.

Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC

The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.

Early detection and surveillance of SARS-CoV-2 genomic variants in wastewater using COJAC

The continuing emergence of SARS-CoV-2 variants of concern and variants of interest emphasizes the need for early detection and epidemiological surveillance of novel variants. We used genomic sequencing of 122 wastewater samples from three locations in Switzerland to monitor the local spread of B.1.1.7 (Alpha), B.1.351 (Beta) and P.1 (Gamma) variants of SARS-CoV-2 at a population level. We devised a bioinformatics method named COJAC (Co-Occurrence adJusted Analysis and Calling) that uses read pairs carrying multiple variant-specific signature mutations as a robust indicator of low-frequency variants. Application of COJAC revealed that a local outbreak of the Alpha variant in two Swiss cities was observable in wastewater up to 13 d before being first reported in clinical samples. We further confirmed the ability of COJAC to detect emerging variants early for the Delta variant by analysing an additional 1,339 wastewater samples. While sequencing data of single wastewater samples provide limited precision for the quantification of relative prevalence of a variant, we show that replicate and close-meshed longitudinal sequencing allow for robust estimation not only of the local prevalence but also of the transmission fitness advantage of any variant. We conclude that genomic sequencing and our computational analysis can provide population-level estimates of prevalence and fitness of emerging variants from wastewater samples earlier and on the basis of substantially fewer samples than from clinical samples. Our framework is being routinely used in large national projects in Switzerland and the UK.

Genetic Diversity and Evolutionary Convergence of Cryptic SARS-CoV-2 Lineages Detected Via Wastewater Sequencing

Wastewater-based epidemiology (WBE) is an effective way of tracking the appearance and spread of SARS-COV-2 lineages through communities. Beginning in early 2021, we implemented a targeted approach to amplify and sequence the receptor binding domain (RBD) of SARS-COV-2 to characterize viral lineages present in sewersheds. Over the course of 2021, we reproducibly detected multiple SARS-COV-2 RBD lineages that have never been observed in patient samples in 9 sewersheds located in 3 states in the USA. These cryptic lineages contained between 4 to 24 amino acid substitutions in the RBD and were observed intermittently in the sewersheds in which they were found for as long as 14 months. Many of the amino acid substitutions in these lineages occurred at residues also mutated in the Omicron variant of concern (VOC), often with the same substitution. One of the sewersheds contained a lineage that appeared to be derived from the Alpha VOC, but the majority of the lineages appeared to be derived from pre-VOC SARS-COV-2 lineages. Specifically, several of the cryptic lineages from New York City appeared to be derived from a common ancestor that most likely diverged in early 2020. While the source of these cryptic lineages has not been resolved, it seems increasingly likely that they were derived from immunocompromised patients or animal reservoirs. Our findings demonstrate that SARS-COV-2 genetic diversity is greater than what is commonly observed through routine SARS-CoV-2 surveillance. Wastewater sampling may more fully capture SARS-CoV-2 genetic diversity than patient sampling and could reveal new VOCs before they emerge in the wider human population.

Author Summary

During the COVID-19 pandemic, wastewater-based epidemiology has become an effective public health tool. Because many infected individuals shed SARS-CoV-2 in feces, wastewater has been monitored to reveal infection trends in the sewersheds from which the samples were derived. Here we report novel SARS-CoV-2 lineages in wastewater samples obtained from 3 different states in the USA. These lineages appeared in specific sewersheds intermittently over periods of up to 14 months, but generally have not been detected beyond the sewersheds in which they were initially found. Many of these lineages may have diverged in early 2020. Although these lineages share considerable overlap with each other, they have never been observed in patients anywhere in the world. While the wastewater lineages have similarities with lineages observed in long-term infections of immunocompromised patients, animal reservoirs cannot be ruled out as a potential source.

Molecular Diagnostic Tools Applied for Assessing Microbial Water Quality

Microbial water quality is of vital importance for human, animal, and environmental health. Notably, pathogenically contaminated water can result in serious health problems, such as waterborne outbreaks, which have caused huge economic and social losses. In this context, the prompt detection of microbial contamination becomes essential to enable early warning and timely reaction with proper interventions. Recently, molecular diagnostics have been increasingly employed for the rapid and robust assessment of microbial water quality implicated by various microbial pollutants, e.g., waterborne pathogens and antibiotic-resistance genes (ARGs), imposing the most critical health threats to humans and the environment. Continuous technological advances have led to constant improvements and expansions of molecular methods, such as conventional end-point PCR, DNA microarray, real-time quantitative PCR (qPCR), multiplex qPCR (mqPCR), loop-mediated isothermal amplification (LAMP), digital droplet PCR (ddPCR), and high-throughput next-generation DNA sequencing (HT-NGS). These state-of-the-art molecular approaches largely facilitate the surveillance of microbial water quality in diverse aquatic systems and wastewater. This review provides an up-to-date overview of the advancement of the key molecular tools frequently employed for microbial water quality assessment, with future perspectives on their applications.

An immunoPET probe to SARS-CoV-2 reveals early infection of the male genital tract in rhesus macaques

The systemic nature of SARS-CoV-2 infection is highly recognized, but poorly characterized. A non-invasive and unbiased method is needed to clarify whole body spatiotemporal dynamics of SARS-CoV-2 infection after transmission. We recently developed a probe based on the anti-SARS-CoV-2 spike antibody CR3022 to study SARS-CoV-2 pathogenesis in vivo. Herein, we describe its use in immunoPET to investigate SARS-CoV-2 infection of three rhesus macaques. Using PET/CT imaging of macaques at different times post-SARS-CoV-2 inoculation, we track the 64Cu-labelled CR3022-F(ab')2 probe targeting the spike protein of SARS-CoV-2 to study the dynamics of infection within the respiratory tract and uncover novel sites of infection. Using this method, we uncovered differences in lung pathology between infection with the WA1 isolate and the delta variant, which were readily corroborated through computed tomography scans. The 64Cu-CR3022-probe also demonstrated dynamic changes occurring between 1- and 2-weeks post-infection. Remarkably, a robust signal was seen in the male genital tract (MGT) of all three animals studied. Infection of the MGT was validated by immunofluorescence imaging of infected cells in the testicular and penile tissue and severe pathology was observed in the testes of one animal at 2-weeks post-infection. The results presented here underscore the utility of using immunoPET to study the dynamics of SARS-CoV-2 infection to understand its pathogenicity and discover new anatomical sites of viral replication. We provide direct evidence for SARS-CoV-2 infection of the MGT in rhesus macaques revealing the possible pathologic outcomes of viral replication at these sites.

SARS-CoV-2 and other respiratory pathogens are detected in continuous air samples from congregate settings

Two years after the emergence of SARS-CoV-2, there is still a need for better ways to assess the risk of transmission in congregate spaces. We deployed active air samplers to monitor the presence of SARS-CoV-2 in real-world settings across communities in the Upper Midwestern states of Wisconsin and Minnesota. Over 29 weeks, we collected 527 air samples from 15 congregate settings and detected 106 SARS-CoV-2 positive samples, demonstrating SARS-CoV-2 can be detected in air collected from daily and weekly sampling intervals. We expanded the utility of air surveillance to test for 40 other respiratory pathogens. Surveillance data revealed differences in timing and location of SARS-CoV-2 and influenza A virus detection in the community. In addition, we obtained SARS-CoV-2 genome sequences from air samples to identify variant lineages. Collectively, this shows air surveillance is a scalable, cost-effective, and high throughput alternative to individual testing for detecting respiratory pathogens in congregate settings.

An immunoPET probe to SARS-CoV-2 reveals early infection of the male genital tract in rhesus macaques

The systemic nature of SARS-CoV-2 infection is highly recognized, but poorly characterized. A non-invasive and unbiased method is needed to clarify whole body spatiotemporal dynamics of SARS-CoV-2 infection after transmission. We recently developed a probe based on the anti-SARS-CoV-2 spike antibody CR3022 to study SARS-CoV-2 pathogenesis in vivo. Herein, we describe its use in immunoPET to investigate SARS-CoV-2 infection of three rhesus macaques. Using PET/CT imaging of macaques at different times post-SARS-CoV-2 inoculation, we track the 64Cu-labelled CR3022-F(ab')2 probe targeting the spike protein of SARS-CoV-2 to study the dynamics of infection within the respiratory tract and uncover novel sites of infection. Using this method, we uncovered differences in lung pathology between infection with the WA1 isolate and the delta variant, which were readily corroborated through computed tomography scans. The 64Cu-CR3022-probe also demonstrated dynamic changes occurring between 1- and 2-weeks post-infection. Remarkably, a robust signal was seen in the male genital tract (MGT) of all three animals studied. Infection of the MGT was validated by immunofluorescence imaging of infected cells in the testicular and penile tissue and severe pathology was observed in the testes of one animal at 2-weeks post-infection. The results presented here underscore the utility of using immunoPET to study the dynamics of SARS-CoV-2 infection to understand its pathogenicity and discover new anatomical sites of viral replication. We provide direct evidence for SARS-CoV-2 infection of the MGT in rhesus macaques revealing the possible pathologic outcomes of viral replication at these sites.

Tracking cryptic SARS-CoV-2 lineages detected in NYC wastewater

Tracking SARS-CoV-2 genetic diversity is strongly indicated because diversifying selection may lead to the emergence of novel variants resistant to naturally acquired or vaccine-induced immunity. To monitor New York City (NYC) for the presence of novel variants, we deep sequence most of the receptor binding domain coding sequence of the S protein of SARS-CoV-2 isolated from the New York City wastewater. Here we report detecting increasing frequencies of novel cryptic SARS-CoV-2 lineages not recognized in GISAID's EpiCoV database. These lineages contain mutations that had been rarely observed in clinical samples, including Q493K, Q498Y, E484A, and T572N and share many mutations with the Omicron variant of concern. Some of these mutations expand the tropism of SARS-CoV-2 pseudoviruses by allowing infection of cells expressing the human, mouse, or rat ACE2 receptor. Finally, pseudoviruses containing the spike amino acid sequence of these lineages were resistant to different classes of receptor binding domain neutralizing monoclonal antibodies. We offer several hypotheses for the anomalous presence of these lineages, including the possibility that these lineages are derived from unsampled human COVID-19 infections or that they indicate the presence of a non-human animal reservoir.