Genome Sequencing of SARS-CoV-2 Allows Monitoring of Variants of Concern through Wastewater

Definition of a concentration and RNA extraction protocol for optimal whole genome sequencing of SARS-CoV-2 in wastewater (ANRS0160)

Monitoring the presence of RNA from emerging pathogenic viruses, such as SARS-CoV-2, in wastewater (WW) samples requires suitable methods to ensure an effective response. Genome sequencing of WW is one of the crucial methods, but it requires high-quality RNA in sufficient quantities, especially for monitoring emerging variants. Consequently, methods for viral concentration and RNA extraction from WW samples have to be optimized before sequencing. The purpose of this study was to achieve high coverage (≥ 90 %) and sequencing depth (at least ≥200×) even for low initial RNA concentrations (< 105 genome copies (GC)/L) in WW. A further objective was to determine the range of SARS-CoV-2 RNA concentrations that allow high-quality sequencing, and the optimal sample volume for analysis. Ultrafiltration (UF) methods were used to concentrate viral particles from large influent samples (up to 500 mL). An RNA extraction protocol using silica beads, neutral phenol-chloroform treatment, and a PCR inhibitor removal kit was chosen for its effectiveness in extracting RNA and eliminating PCR inhibitors, as well as its adaptability for use with large influent samples. Recovery rates ranged from 24 % to 63 % (N = 17) for SARS-CoV-2 naturally present in WW samples. 200 mL WW samples can be enough for UF concentration, as they showed high quality sequencing analyses with between 5 × 104 GC/L and 6 × 103 GC/L. Below 6 × 103 GC/L, high-quality sequencing was also achieved for ∼40 % of the samples using 500 mL of WW. Sequencing analysis for variant detection was performed on 200 mL WW samples with coverage of >95 % and sequencing depth of >1000×. Analyses revealed the predominance of variant EG.5, known as Eris (66 %-100 %). The use of UF methods in combination with a suitable RNA extraction protocol appear promising for sequencing enveloped viruses in WW in a context of viral emergence.

Crykey: Rapid identification of SARS-CoV-2 cryptic mutations in wastewater

Wastewater surveillance for SARS-CoV-2 provides early warnings of emerging variants of concerns and can be used to screen for novel cryptic linked-read mutations, which are co-occurring single nucleotide mutations that are rare, or entirely missing, in existing SARS-CoV-2 databases. While previous approaches have focused on specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and investigating their potential origin. We present Crykey, a tool for rapidly identifying rare linked-read mutations across the genome of SARS-CoV-2. We evaluated the utility of Crykey on over 3,000 wastewater and over 22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations in wastewater that represent potential circulating cryptic lineages, serving as a new computational tool for wastewater surveillance of SARS-CoV-2.

Emergence and spread of SARS-CoV-2 variants of concern in Canada: a retrospective analysis from clinical and wastewater data

BACKGROUND

The spread of SARS-CoV-2 has been studied at unprecedented levels worldwide. In jurisdictions where molecular analysis was performed on large scales, the emergence and competition of numerous SARS-CoV-2lineages have been observed in near real-time. Lineage identification, traditionally performed from clinical samples, can also be determined by sampling wastewater from sewersheds serving populations of interest. Variants of concern (VOCs) and SARS-CoV-2 lineages associated with increased transmissibility and/or severity are of particular interest.

METHOD

Here, we consider clinical and wastewater data sources to assess the emergence and spread of VOCs in Canada retrospectively.

RESULTS

We show that, overall, wastewater-based VOC identification provides similar insights to the surveillance based on clinical samples. Based on clinical data, we observed synchrony in VOC introduction as well as similar emergence speeds across most Canadian provinces despite the large geographical size of the country and differences in provincial public health measures.

CONCLUSION

In particular, it took approximately four months for VOC Alpha and Delta to contribute to half of the incidence. In contrast, VOC Omicron achieved the same contribution in less than one month. This study provides significant benchmarks to enhance planning for future VOCs, and to some extent for future pandemics caused by other pathogens, by quantifying the rate of SARS-CoV-2 VOCs invasion in Canada.

Effectiveness of environmental surveillance of SARS-CoV-2 as an early-warning system: Update of a systematic review during the second year of the pandemic

The aim of this updated systematic review was to offer an overview of the effectiveness of environmental surveillance (ES) of SARS-CoV-2 as a potential early-warning system (EWS) for COVID-19 and new variants of concerns (VOCs) during the second year of the pandemic. An updated literature search was conducted to evaluate the added value of ES of SARS-CoV-2 for public health decisions. The search for studies published between June 2021 and July 2022 resulted in 1,588 publications, identifying 331 articles for full-text screening. A total of 151 publications met our inclusion criteria for the assessment of the effectiveness of ES as an EWS and early detection of SARS-CoV-2 variants. We identified a further 30 publications among the grey literature. ES confirms its usefulness as an EWS for detecting new waves of SARS-CoV-2 infection with an average lead time of 1-2 weeks for most of the publication. ES could function as an EWS for new VOCs in areas with no registered cases or limited clinical capacity. Challenges in data harmonization and variant detection require standardized approaches and innovations for improved public health decision-making. ES confirms its potential to support public health decision-making and resource allocation in future outbreaks.

Spatiotemporal genome diversity of SARS-CoV-2 in wastewater: a two-year global epidemiological study

Wastewater surveillance locally and globally is important for the investigation of the molecular epidemiological features of SARS-CoV-2 in the environment. The current study investigated the genomic diversity and mutation profile of SARS-CoV-2 variants in wastewater for the period spanning COVID-19 pandemic up to December, 2022. A total of 3618 complete SARS-CoV-2 genome sequences from waste water samples submitted to the GISAID database were retrieved. The SARS-CoV-2 sequences were subjected to pairwise alignment against reference, followed by clade and lineage assignment (based on Nextstrain, GISAID and Pango), distance metric phylogenetic analysis, and detection of substitution mutations. Following GISAID, Nextstrain, and Pango nomenclatures, an overall agreement in clade and lineage determination in wastewater samples was observed. There was successive appearance, dissemination, and disappearance of SARS-CoV-2 lineages along time in wastewater. The SARS-CoV-2 genomes from wastewater were clustered into the variants of concern (VOC) as Alpha GRY (B.1.1.7 + Q.7), Delta GK (B.1.617.2 + AY.*), and Omicron GRA (BA.1*, BA.2* + B.1.1.529, BA.5*). The evolutionary rate was 9.63e-04 substitutions/site/year for SARS-CoV-2 in wastewater. B.1.1.7 was less prevalent than B.1.617.2 in 2021, appeared in succession, and BA.1, BA.2, BA.5 were serially detected in 2022, the latter strain continued to persist in wastewater. The N501Y, E484K/Q, K417N/T, L452R, T478K spike substitutions remained dominant attribute of SARS-CoV-2 VOCs. The study underlines the importance of wastewater surveillance for enumerating spatiotemporal diversity of SARS-CoV-2 variants and mutations, which might pave the way for novel antiviral and vaccine designing towards management and prevention of SARS-CoV-2 infection.

Crykey: Rapid Identification of SARS-CoV-2 Cryptic Mutations in Wastewater

We present Crykey, a computational tool for rapidly identifying cryptic mutations of SARS-CoV-2. Specifically, we identify co-occurring single nucleotide mutations on the same sequencing read, called linked-read mutations, that are rare or entirely missing in existing databases, and have the potential to represent novel cryptic lineages found in wastewater. While previous approaches exist for identifying cryptic linked-read mutations from specific regions of the SARS-CoV-2 genome, there is a need for computational tools capable of efficiently tracking cryptic mutations across the entire genome and for tens of thousands of samples and with increased scrutiny, given their potential to represent either artifacts or hidden SARS-CoV-2 lineages. Crykey fills this gap by identifying rare linked-read mutations that pass stringent computational filters to limit the potential for artifacts. We evaluate the utility of Crykey on >3,000 wastewater and >22,000 clinical samples; our findings are three-fold: i) we identify hundreds of cryptic mutations that cover the entire SARS-CoV-2 genome, ii) we track the presence of these cryptic mutations across multiple wastewater treatment plants and over a three years of sampling in Houston, and iii) we find a handful of cryptic mutations in wastewater mirror cryptic mutations in clinical samples and investigate their potential to represent real cryptic lineages. In summary, Crykey enables large-scale detection of cryptic mutations representing potential cryptic lineages in wastewater.

Enabling accurate and early detection of recently emerged SARS-CoV-2 variants of concern in wastewater

As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variant of concerns (VoCs) in communities. In this paper we present QuaID, a novel bioinformatics tool for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3-week earlier VoC detection, (ii) accurate VoC detection (>95% precision on simulated benchmarks), and (iii) leverages all mutational signatures (including insertions & deletions).

Rise and fall of SARS-CoV-2 variants in Rotterdam: Comparison of wastewater and clinical surveillance

Monitoring of SARS-CoV-2 in wastewater (WW) is a promising tool for epidemiological surveillance, correlating not only viral RNA levels with the infection dynamics within the population, but also to viral diversity. However, the complex mixture of viral lineages in WW samples makes tracking of specific variants or lineages circulating in the population a challenging task. We sequenced sewage samples of 9 WW-catchment areas within the city of Rotterdam, used specific signature mutations from individual SARS-CoV-2 lineages to estimate their relative abundances in WW and compared them against those observed in clinical genomic surveillance of infected individuals between September 2020 and December 2021. We showed that especially for dominant lineages, the median of the frequencies of signature mutations coincides with the occurrence of those lineages in Rotterdam's clinical genomic surveillance. This, along with digital droplet RT-PCR targeting signature mutations of specific variants of concern (VOCs), showed that several VOCs emerged, became dominant and were replaced by the next VOC in Rotterdam at different time points during the study. In addition, single nucleotide variant (SNV) analysis provided evidence that spatio-temporal clusters can also be discerned from WW samples. We were able to detect specific SNVs in sewage, including one resulting in the Q183H amino acid change in the Spike gene, that was not captured by clinical genomic surveillance. Our results highlight the potential use of WW samples for genomic surveillance, increasing the set of epidemiological tools to monitor SARS-CoV-2 diversity.

High-throughput sequencing approaches applied to SARS-CoV-2

High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.

Comprehensive mutation profiling from wastewater in southern Germany extends evidence of circulating SARS-CoV-2 diversity beyond mutations characteristic for Omicron

Tracking SARS-CoV-2 variants in wastewater is primarily performed by detecting characteristic mutations of the variants. Unlike the Delta variant, the emergence of the Omicron variant and its sublineages as variants of concern has posed a challenge in using characteristic mutations for wastewater surveillance. In this study, we monitored the temporal and spatial variation of SARS-CoV-2 variants by including all the detected mutations and compared whether limiting the analyses to characteristic mutations for variants like Omicron impact the outcomes. We collected 24-hour composite samples from 15 wastewater treatment plants (WWTP) in Hesse and sequenced 164 wastewater samples with a targeted sequencing approach from September 2021 to March 2022. Our results show that comparing the number of all the mutations against the number of the characteristic mutations reveals a different outcome. A different temporal variation was observed for the ORF1a and S gene. As Omicron became dominant, we observed an increase in the overall number of mutations. Based on the characteristic mutations of the SARS-CoV-2 variants, a decreasing trend for the number of ORF1a and S gene mutations was noticed, though the number of known characteristic mutations in both genes is higher in Omicron than Delta.

A Molecular and Epidemiological Investigation of a Large SARS-CoV-2 Outbreak in a Long-Term Care Facility in Luxembourg, 2021

In spring 2021, a long-term care facility (LTCF) of 154 residents in Luxembourg experienced a large severe, acute respiratory-syndrome coronavirus 2 (SARS-CoV-2) outbreak a few days after a vaccination campaign. We conducted an outbreak investigation and a serosurvey two months after the outbreak, compared attack rates (AR) among residents and staff, and calculated hospitalization and case-fatality rates (CFR). Whole genome sequencing (WGS) was performed to detect variants in available samples and results were compared to genomes published on GISAID. Eighty-four (55%) residents and forty-five (26%) staff members tested positive for SARS-CoV-2; eighteen (21%) residents and one (2.2%) staff member were hospitalized, and twenty-three (CFR: 27%) residents died. Twenty-seven (21% of cases) experienced a reinfection. Sequencing identified seventy-seven cases (97% of sequenced cases) with B.1.1.420 and two cases among staff with B.1.351. The outbreak strain B.1.1.420 formed a separate cluster from cases from other European countries. Convalescent and vaccinated residents had higher anti-SARS-CoV-2 IgG antibody concentrations than vaccinated residents without infection (98% vs. 52%, respectively, with >120 RU/mL, p < 0.001). We documented an extensive outbreak of SARS-CoV-2 in an LTCF due to the presence of a specific variant leading to high CFR. Infection in vaccinated residents increased antibody responses. A single vaccine dose was insufficient to mitigate the outbreak.

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.

Monitoring the evolution of SARS-CoV-2 on a Spanish university campus through wastewater analysis: A pilot project for the reopening strategy

Wastewater surveillance is a fast and cost-effective tool that enables tracing of both symptomatic and asymptomatic transmission of SARS-CoV-2. In this paper, a pilot program carried out at the University Jaume I for monitoring the trends of the presence of SARS-CoV-2 in wastewater. To the best of our knowledge, this is the first such project conducted on a university campus in Spain. Wastewater samples (n = 838) were collected when students returned to campus, from October 2020 until August 2021, at a confluence sewer point and at the building level including different academic departments and services, the library, administration offices and the university student residence. It has been observed that the probability of SARS-CoV-2 RNA detection in wastewater depended on COVID-19 incidence on campus and visitors/occupants of the buildings i.e., high-, or low-traffic buildings with high or low frequency of potential contacts. Moreover, the third wave in Spain (after Christmas 2020) and an outbreak that occurred at the university student's residence could be carefully followed, allowing confirmation of the end of the outbreak. In addition, viral variants (i.e., mutations and linages) from selected time points were detected by sequencing and gave an indication of the evolution of the virus over time. The results illustrate the potential of wastewater-based epidemiology to provide an early warning for SARS-CoV-2 within the university, especially in buildings with low traffic and more defined populations, like the student residence. The strategy and experience gathered in this study will allow for implementation of improvements for reliable monitoring in the future.

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.

Mobilome-driven segregation of the resistome in biological wastewater treatment

Biological wastewater treatment plants (BWWTP) are considered to be hotspots for the evolution and subsequent spread of antimicrobial resistance (AMR). Mobile genetic elements (MGEs) promote the mobilization and dissemination of antimicrobial resistance genes (ARGs) and are thereby critical mediators of AMR within the BWWTP microbial community. At present, it is unclear whether specific AMR categories are differentially disseminated via bacteriophages (phages) or plasmids. To understand the segregation of AMR in relation to MGEs, we analyzed meta-omic (metagenomic, metatranscriptomic and metaproteomic) data systematically collected over 1.5 years from a BWWTP. Our results showed a core group of 15 AMR categories which were found across all timepoints. Some of these AMR categories were disseminated exclusively (bacitracin) or primarily (aminoglycoside, MLS and sulfonamide) via plasmids or phages (fosfomycin and peptide), whereas others were disseminated equally by both. Combined and timepoint-specific analyses of gene, transcript and protein abundances further demonstrated that aminoglycoside, bacitracin and sulfonamide resistance genes were expressed more by plasmids, in contrast to fosfomycin and peptide AMR expression by phages, thereby validating our genomic findings. In the analyzed communities, the dominant taxon Candidatus Microthrix parvicella was a major contributor to several AMR categories whereby its plasmids primarily mediated aminoglycoside resistance. Importantly, we also found AMR associated with ESKAPEE pathogens within the BWWTP, and here MGEs also contributed differentially to the dissemination of the corresponding ARGs. Collectively our findings pave the way toward understanding the segmentation of AMR within MGEs, thereby shedding new light on resistome populations and their mediators, essential elements that are of immediate relevance to human health.

Research needs for optimising wastewater-based epidemiology monitoring for public health protection

Wastewater-based epidemiology (WBE) is an unobtrusive method used to observe patterns in illicit drug use, poliovirus, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The pandemic and need for surveillance measures have led to the rapid acceleration of WBE research and development globally. With the infrastructure available to monitor SARS-CoV-2 from wastewater in 58 countries globally, there is potential to expand targets and applications for public health protection, such as other viral pathogens, antimicrobial resistance (AMR), pharmaceutical consumption, or exposure to chemical pollutants. Some applications have been explored in academic research but are not used to inform public health decision-making. We reflect on the current knowledge of WBE for these applications and identify barriers and opportunities for expanding beyond SARS-CoV-2. This paper critically reviews the applications of WBE for public health and identifies the important research gaps for WBE to be a useful tool in public health. It considers possible uses for pathogenic viruses, AMR, and chemicals. It summarises the current evidence on the following: (1) the presence of markers in stool and urine; (2) environmental factors influencing persistence of markers in wastewater; (3) methods for sample collection and storage; (4) prospective methods for detection and quantification; (5) reducing uncertainties; and (6) further considerations for public health use.

QuaID: Enabling Earlier Detection of Recently Emerged SARS-CoV-2 Variants of Concern in Wastewater

As clinical testing declines, wastewater monitoring can provide crucial surveillance on the emergence of SARS-CoV-2 variants of concern (VoC) in communities. Multiple recent studies support that wastewater-based SARS-CoV-2 detection of circulating VoC can precede clinical cases by up to two weeks. Furthermore, wastewater based epidemiology enables wide population-based screening and study of viral evolutionary dynamics. However, highly sensitive detection of emerging variants remains a complex task due to the pooled nature of environmental samples and genetic material degradation. In this paper we propose quasi-unique mutations for VoC identification, implemented in a novel bioinformatics tool (QuaID) for VoC detection based on quasi-unique mutations. The benefits of QuaID are three-fold: (i) provides up to 3 week earlier VoC detection compared to existing approaches, (ii) enables more sensitive VoC detection, which is shown to be tolerant of >50% mutation drop-out, and (iii) leverages all mutational signatures, including insertions & deletions.

Metagenomics of Wastewater Influent from Wastewater Treatment Facilities across Ontario in the Era of Emerging SARS-CoV-2 Variants of Concern

We report metagenomic sequencing analyses of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA in composite wastewater influent from 10 regions in Ontario, Canada, during the transition between Delta and Omicron variants of concern. The Delta and Omicron BA.1/BA.1.1 and BA.2-defining mutations occurring in various frequencies were reported in the consensus and subconsensus sequences of the composite samples.

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.

Spatial and temporal distribution of SARS-CoV-2 diversity circulating in wastewater

Wastewater-based epidemiology (WBE) has proven to be an effective tool for epidemiological surveillance of SARS-CoV-2 during the current COVID-19 pandemic. Furthermore, combining WBE together with high-throughput sequencing techniques can be useful for the analysis of SARS-CoV-2 viral diversity present in a given sample. The present study focuses on the genomic analysis of SARS-CoV-2 in 76 sewage samples collected during the three epidemiological waves that occurred in Spain from 14 wastewater treatment plants distributed throughout the country. The results obtained demonstrate that the metagenomic analysis of SARS-CoV-2 in wastewater allows the detection of mutations that define the B.1.1.7 lineage and the ability of the technique to anticipate the detection of certain mutations before they are detected in clinical samples. The study proves the usefulness of sewage sequencing to track Variants of Concern that can complement clinical testing to help in decision-making and in the analysis of the evolution of the pandemic.