The COVID-19 pandemic has underscored the significance of monitoring genetic variations in pathogenic viruses to manage its transmission and identify emerging variants. Nonetheless, sequencing every positive patient case is impractical for large-scale testing of the population. Here, we introduce a cost-effective tool for identifying SARS-CoV-2 mutations associated with variants in wastewater. This approach relies on a wastewater surveillance system and reverse transcription-quantitative polymerase chain reaction (RT-qPCR), utilizing mutation-specific probes. Wastewater samples were analyzed for SARS-CoV-2 mutations corresponding to variants under monitoring (VUM) (P.2, alpha, beta, gamma, delta, and omicron) as part of a wastewater-based SARS-CoV-2 monitoring program. Our findings validate the efficacy of this method in detecting SARS-CoV-2 mutations linked to variants in wastewater, facilitating early detection of emerging variants and informing decision-making on control measures.

  • We presented a cost-effective tool for mutations detection of circulating SARS-Cov-2 in a population using wastewater.

  • Wastewater-based epidemiology with variant-related mutations detection approach could give more information about the virus circulating in large communities.

  • This approach can be applied to other genotyping panels to surveil pathogens circulating using residual water.

Firstly reported in December 2019 in the Chinese city of Wuhan, the severe acute respiratory syndrome virus (SARS-CoV-2) spreads worldwide rapidly (Mercatelli & Giorgi 2020). As the virus spreads and replicates, mutations arise, giving rise to variants of interest (VOIs) and variants of concern (VOCs). VOIs are emerging variants that exhibit mutations conferring a selective advantage to the virus, such as evasion of immune responses or heightened transmissibility between hosts. VOCs share these characteristics with VOIs, but also have significant implications for public health, such as a notable decrease in the efficacy of available vaccines. Presently, the majority of these variants are categorized as variants under monitoring (VUM) and are continually monitored for mutations that may pose potential health risks to the population (Mercatelli & Giorgi 2020; Choi & Smith 2021; Oude Munnink et al. 2021; Chavda et al. 2022). Therefore, tracking genetic variations became crucial during the COVID-19 pandemic. However, sequencing or genotyping every positive clinical sample is technically and financially unfeasible for population-scale testing (Choi & Smith 2021). Because infected individuals contribute to the viral load in sewage, it becomes feasible to assess the variants circulating within the population served by the wastewater treatment plant (Hillary et al. 2020). Consequently, wastewater-based detection of SARS-CoV-2 can serve as a population surveillance system for tracking and anticipating the spread of the virus. Here, we introduce a cost-effective method for detecting SARS-CoV-2 variants in wastewater by leveraging an established wastewater surveillance system (Prandi et al. 2022), augmented with variant-specific probes.

Although applying a genotyping approach allows the detection of several mutations in the wastewater samples, it is impossible to discriminate a unique viral variant, since the test does not detect the whole genome information, only the mutation present in many viral particles in the sample. Nevertheless, despite the challenges associated with wastewater samples, this method can identify the presence of specific mutations associated with VUMs on a population-wide scale with reduced cost and effort compared with sequencing wastewater samples or mass clinical samples sequencing, as it necessitates a smaller number of sample to achieve coverage at that scale. In this study, we examined wastewater samples for VUMs (P.2, alpha, beta, gamma, delta, and omicron) as part of a program that focused on monitoring the circulation of SARS-CoV-2 through wastewater. The TaqMan™/SARS-CoV-2 Mutation Panel used in this work is widely applied in variant detection in clinical samples (Hirotsu & Omata 2021; Neopane et al. 2021; Ashford et al. 2022). To our knowledge, this is the first time this protocol was adapted to wastewater samples showing effective results.

Samples

The samples in this study were gathered from the Serraria Wastewater Treatment Plant (Serraria WWTP) in Porto Alegre, Brazil, which is the largest WWTP in the capital city of Rio Grande do Sul state. Serraria WWTP receives wastewater from approximately 760,000 individuals, constituting around 50% of the city's population, and maintains a median flow rate of 140,000 m3/day. Composite samples, each with a volume of 400 ml, were collected over 24-h periods using an automated sampler and stored at 4 °C until processing. The samples underwent concentration through ultracentrifugation (Pina et al. 1998) with adaptations (Girardi et al. 2018). Briefly, 36 ml of each sample was subjected to ultracentrifugation at 100,000 × g for 1 h at 4 °C. The sediment obtained was then eluted by combining it with 4 ml of 0.25 N glycine (pH 9.5) on ice for 30 min. Subsequently, suspended solids were separated by centrifugation at 10,000 × g for 30 min following the addition of 4 ml of 2× phosphate-buffered saline (PBS). The viruses were pelleted via ultracentrifugation at 100,000 × g for 1 h at 4 °C, then resuspended in 0.5 ml of 1× PBS and stored at −80 °C. Sampling was conducted twice a week, every Tuesday and Wednesday, from November 2020 to January 2022, resulting in a total of 120 processed samples.

RNA extraction and RT-qPCR

The RNA was extracted from concentrated samples using the Maxwell® 16 Viral Total Nucleic Acid Purification Kit (Promega) and automatic extractor Maxwell® RSC (Promega), according to the manufacturer's instructions. The RT-qPCR targeted the N1 genomic region of SARS-CoV-2 using an Applied Biosystems™ 7500 Fast Real-Time instrument, as detailed in Prandi et al. (2022). The amplification protocol, probes, and primers adhered to the CDC-2019-N1N2-SARS-CoV-2 protocol (Lu et al. 2020 and Supplementary Table S14). Samples were deemed positive if the cycle threshold (Ct) fell below 40 cycles; otherwise, they were considered negative. It is common for the number of cycles to reach 40 in wastewater samples due to the low viral concentrations present (Ahmed et al. 2020; La Rosa et al. 2020; Wu et al. 2020). Each qPCR run included SARS-CoV-2 RNA positive controls. For the samples selected for genotyping, a positive control curve with known concentrations was used to estimate SARS-COV-2 viral loads (Supplementary Table S1; Prandi et al. 2022), along with a negative control.

Mutation panel

Samples with a Ct value below 36 underwent genotyping utilizing the TaqMan™ SARS-CoV-2 Mutation Panel from ThermoFisher Scientific, following the specified protocol (Fisher 2021). The point mutations used for the inference of the variants were T20N for gamma; N501Y for alpha, beta, and gamma; V1176F for P2; P681R for delta; and K417N (Supplementary Figures S1–S13) for omicron and beta variants. The results obtained from genotyping of wastewater samples were compared with the results of VUMs detection performed by the State Health Surveillance Center (SHSC).

Fifty-six samples presented a Ct below 36 and were genotyped, of which 26 contained the T20N mutation, 16 contained P681R, and 5 contained K417N. V1176F mutation was not detected. Five samples presented positive results for more than one variant. Figure 1 shows the test results for the T20N, P681R, and K417N (amplification table and graphs can be found in Supplementary Figures S1–S13).
Figure 1

Detection of point mutations in wastewater samples. This graph shows the Ct values on the Y-axis and collection time points on the X-axis. Until July 2021, only the T20N mutation (cyan) was detected in the samples. At the end of July, both T20N and P681R (dark red bars) were detected in the samples. We last detected T20N in September. K417N (dark green bars) was first detected in November and became the only circulating mutation in January of 2022. N1 amplification (dark blue line) represents the Ct of the first RT-qPCR used to select the samples based on the genomic region N1. The first month of Gamma detection in clinical samples (light cyan). The first month of Delta detection in clinical samples (light red). The first month of Omicron detection in clinical samples (light green).

Figure 1

Detection of point mutations in wastewater samples. This graph shows the Ct values on the Y-axis and collection time points on the X-axis. Until July 2021, only the T20N mutation (cyan) was detected in the samples. At the end of July, both T20N and P681R (dark red bars) were detected in the samples. We last detected T20N in September. K417N (dark green bars) was first detected in November and became the only circulating mutation in January of 2022. N1 amplification (dark blue line) represents the Ct of the first RT-qPCR used to select the samples based on the genomic region N1. The first month of Gamma detection in clinical samples (light cyan). The first month of Delta detection in clinical samples (light red). The first month of Omicron detection in clinical samples (light green).

Close modal

Here, we performed sample concentration followed by an RT-qPCR assay for SARS-CoV-2 genome detection, as described in detail in Prandi et al. (2022). These are well-accepted methods for detecting SARS-CoV-2 genomes in wastewater samples (Mercatelli & Giorgi 2020; La Rosa et al. 2020; Wu et al. 2020; Yolshin et al. 2022). For variant-related mutation detection, variant-specific probes were used for their cost–effectiveness, also a common technique used for SARS-Cov-2 wastewater samples detection (Yolshin et al. 2022; Xu et al. 2022). Other studies used different methods for variant detection, including whole genome sequencing (Bar-Or et al. 2021; Pérez-Cataluña et al. 2022) and metagenomics (Crits-Christoph et al. 2021). Those types of approaches cannot only detect VUMs but they can also detect other viral variants. All these methods have given rise to consistent results with clinical samples; nonetheless, they have several difficulties, such as the heterogeneous nature of wastewater samples and the fragmentation of viral RNA that interferes with the genome coverage and assembly (Pérez-Cataluña et al. 2022; Sutton et al. 2022). Genotyping specifically amplifies a small fragment of viral RNA, rendering it a simpler tool for handling fragmented and heterogeneous RNA samples.

Whereas the wastewater sample has several viral particles, and we use a genotyping test, we cannot affirm that the detected mutation is a specific variant purely by the PCR result. Hence, we compared our results with the detection made in clinical samples by the SHSC, aligning them based on confirmed clinical sample dates and our wastewater collections. The first detection of the P2 lineage in clinical samples occurred in October 2020; the first case where the Gamma variant was present in the metropolitan region of Porto Alegre was in February 2021. The Delta variant was detected in August 2021, and the first Omicron case in Porto Alegre was detected in December 2022 (State Health Surveillance Center). In our samples, the point mutation T20N, which is typical of the Gamma VBM, was detected for the first time in January 2021 and remained consistently prevalent until September 2021 (Figure 1). We detected P681R mutation, characteristic of the Delta VBM, from July 2021 to December 2021. We detected the first K417N mutation, a characteristic feature of Omicron and Beta, on 23 November 2021. Since P2 shares this point mutation with Omicron, we carried out a V1176F assay to verify the presence of this lineage; all samples presented wild-type characteristics. Taken together, these findings indicate the presence of the Omicron variant from November to January. The absence of K417N positivity in December 2021 may be linked to demographic shifts and sample conditions. In December, there is significant urban migration to coastal areas due to the holiday season and elevated summer temperatures, as evidenced by the decline in average flows recorded at WWTP Serraria (data not shown). Moreover, high temperatures can adversely affect the quality of samples collected during this period. Nevertheless, it is noteworthy that the observed mutation replacement over time aligns with the detection of variants in clinical samples or indicates the detection preceding clinical samples reported by the SHSC.

Wastewater sampling holds significant potential for enabling a more extensive sampling of populations, thereby providing valuable insights into viral spread and variant circulation. The identification of variant mutations, coupled with the genomic load in wastewater, furnishes essential information for informing the decision-making processes of public health authorities (Karthikeyan et al. 2022). Furthermore, this kind of approach, using the TaqMan™ SARS-CoV-2 Mutation Panel was never reported before and presented itself as a cost-effective method alternative for rapid and effective variant surveillance. Similar approaches can be adapted for surveilling other pathogens of interest. In this work, we were able to genotype samples with Ct values up to 36. Ashford et al. (2022) had already detected mutations with relatively high Ct samples using the same panel in clinical samples. This report demonstrates the potential use of TaqMan™ SARS-CoV-2 Mutation Panel for variant detection in challenging samples, such as wastewater.

Wastewater sampling provides a more representative depiction of viral circulation in a population as large as the coverage of the sewage collection system. A wastewater collection system with limited coverage means that only a fraction of the population served by this system contributes to the wastewater sample. In this study, we selected WWTP Serraria due to its coverage of the largest population, while the remainder of the population is served by smaller WWTPs. However, it is important to note that the lack of information about other WWTPs is a limitation of this study. Additionally, this study was conducted in a specific geographic location, and therefore, the findings may not be directly applicable to other cities or populations, as they depend on the sewage collection network of the local area. Finally, while wastewater surveillance can provide valuable epidemiological information about the circulation of SARS-CoV-2 in a population, it cannot replace clinical testing for diagnosing COVID-19 cases and new variants identification.

With this approach, it is possible to gather valuable epidemiological information on the circulating variants, which health authorities can use as an additional instrument to contribute to disease monitoring and decision-making regarding vaccinations and other measures that might be implemented to control virus circulation. In addition, it is known that several cases of asymptomatic or subclinical infections are not detected clinically and untraced contacts may account for an estimated 80% of virus dissemination events (Hillary et al. 2020). As such, a wastewater surveillance system with this described variant-related mutation detection approach could give more information about the virus circulating in large communities.

We presented a cost-effective tool using wastewater surveillance systems for mutation detection of circulating SARS-Cov-2. This approach, with the support of health agencies, enabled them to monitor the virus dynamics within the population. This study marks the inaugural utilization of the TaqMan™ SARS-CoV-2 Mutation Panel (Ashford et al. 2022) for detecting variants in wastewater. Originally, this kit was not tailored for wastewater samples. Despite being influenced by sample conditions and low viral loads, it demonstrates proficiency in variant detection in environmental samples. This approach can be applied to other genotyping panels to surveil pathogens circulating in a population using residual water.

This work was financially supported by Capes (No 88887.509240/2020-00) and FAPERGS (21/2551-0000069-4). A.C.F., F.S.C., and P.M.R. are CNPq researchers fellows. The authors would thank DMAE and SES for help in the water collection and also UFRGS for the laboratory support and human resources.

All relevant data are included in the paper or its Supplementary Information.

The authors declare there is no conflict.

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