An improved method for determining frequency of multiple variants of SARS-CoV-2 in wastewater using qPCR assays

Real-time evaluation of signal accuracy in wastewater surveillance of pathogens with high rates of mutation

Wastewater surveillance of coronavirus disease 2019 (COVID-19) commonly applies reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater over time. In most applications worldwide, maximal sensitivity and specificity of RT-qPCR has been achieved, in part, by monitoring two or more genomic loci of SARS-CoV-2. In Ontario, Canada, the provincial Wastewater Surveillance Initiative reports the average copies of the CDC N1 and N2 loci normalized to the fecal biomarker pepper mild mottle virus. In November 2021, the emergence of the Omicron variant of concern, harboring a C28311T mutation within the CDC N1 probe region, challenged the accuracy of the consensus between the RT-qPCR measurements of the N1 and N2 loci of SARS-CoV-2. In this study, we developed and applied a novel real-time dual loci quality assurance and control framework based on the relative difference between the loci measurements to the City of Ottawa dataset to identify a loss of sensitivity of the N1 assay in the period from July 10, 2022 to January 31, 2023. Further analysis via sequencing and allele-specific RT-qPCR revealed a high proportion of mutations C28312T and A28330G during the study period, both in the City of Ottawa and across the province. It is hypothesized that nucleotide mutations in the probe region, especially A28330G, led to inefficient annealing, resulting in reduction in sensitivity and accuracy of the N1 assay. This study highlights the importance of implementing quality assurance and control criteria to continually evaluate, in near real-time, the accuracy of the signal produced in wastewater surveillance applications that rely on detection of pathogens whose genomes undergo high rates of mutation.

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.

Underestimation of SARS-CoV-2 in wastewater due to single or double mutations in the N1 qPCR probe binding region

Wastewater surveillance using RT-qPCR has now been widely adopted to track circulating levels of SARS-CoV-2 virus in many sewersheds. The CDC qPCR assays targeting two regions (N1 and N2) within the N gene are commonly used, but a discrepancy between the two biomarkers has been noticed by independent studies using these methods since late 2021. The reason is presumed to be due to mutations in regions targeted by the N1 qPCR probe. In this study, we systematically investigated and unequivocally confirmed that the underlying reason for this discrepancy was mutations in the N1 probe target, and that a single mutation could cause a significant drop in signal. We first confirmed the proportion of related mutations in wastewater samples (Jan 2021-Dec 2022) using nested PCR and LC-MS. Based on relative proportions of N1 alleles, we separated the wastewater data into four time periods corresponding to different variant waves: Period I (Alpha and Delta waves with 0 mutation), Period II (BA.1/BA.2 waves with a single mutation found in all Omicron strains), Period III (BA.5.2* wave with two mutations), and Period IV (BQ.1* wave with two mutations). Significantly lower N1 copies relative to N2 copies in samples from Periods II-IV compared to those from Period I was observed in wastewater. To further pinpoint the extent to which each mutation impacted N1 quantification, we compared the qPCR response among different synthetic oligomers with corresponding mutations. This study highlighted the impact of even just one or two mutations on qPCR-based wastewater surveillance of SARS-CoV-2.

Digital microfluidics with distance-based detection - a new approach for nucleic acid diagnostics

There is great enthusiasm for using loop-mediated isothermal amplification (LAMP) in point-of-care nucleic acid amplification tests (POC NAATs), as an alternative to PCR. While isothermal amplification techniques like LAMP eliminate the need for rapid temperature cycling in a portable format, these systems are still plagued by requirements for dedicated optical detection apparatus for analysis and manual off-chip sample processing. Here, we developed a new microfluidic system for LAMP-based POC NAATs to address these limitations. The new system combines digital microfluidics (DMF) with distance-based detection (DBD) for direct signal readout. This is the first report of the use of (i) LAMP or (ii) DMF with DBD - thus, we describe a number of characterization steps taken to determine optimal combinations of reagents, materials, and processes for reliable operation. For example, DBD was found to be quite sensitive to background signals from low molecular weight LAMP products; thus, a Capto™ adhere bead-based clean-up procedure was developed to isolate the desirable high-molecular-weight products for analysis. The new method was validated by application to detection of SARS-CoV-2 in saliva. The method was able to distinguish between saliva containing no virus, saliva containing a low viral load (104 genome copies per mL), and saliva containing a high viral load (108 copies per mL), all in an automated system that does not require detection apparatus for analysis. We propose that the combination of DMF with distance-based detection may be a powerful one for implementing a variety of POC NAATs or for other applications in the future.

Wastewater surveillance monitoring of SARS-CoV-2 variants of concern and dynamics of transmission and community burden of COVID-19

Wastewater-based surveillance is a valuable approach for monitoring COVID-19 at community level. Monitoring SARS-CoV-2 variants of concern (VOC) in wastewater has become increasingly relevant when clinical testing capacity and case-based surveillance are limited. In this study, we ascertained the turnover of six VOC in Alberta wastewater from May 2020 to May 2022. Wastewater samples from nine wastewater treatment plants across Alberta were analysed using VOC-specific RT-qPCR assays. The performance of the RT-qPCR assays in identifying VOC in wastewater was evaluated against next generation sequencing. The relative abundance of each VOC in wastewater was compared to positivity rate in COVID-19 testing. VOC-specific RT-qPCR assays performed comparatively well against next generation sequencing; concordance rates ranged from 89% to 98% for detection of Alpha, Beta, Gamma, Omicron BA.1 and Omicron BA.2, with a slightly lower rate of 85% for Delta (p < 0.01). Elevated relative abundance of Alpha, Delta, Omicron BA.1 and BA.2 were each associated with increased COVID-19 positivity rate. Alpha, Delta and Omicron BA.2 reached 90% relative abundance in wastewater within 80, 111 and 62 days after their initial detection, respectively. Omicron BA.1 increased more rapidly, reaching a 90% relative abundance in wastewater after 35 days. Our results from VOC surveillance in wastewater correspond with clinical observations that Omicron is the VOC with highest disease burden over the shortest period in Alberta to date. The findings suggest that changes in relative abundance of a VOC in wastewater can be used as a supplementary indicator to track and perhaps predict COVID-19 burden in a population.

Quantification and Differentiation of SARS-CoV-2 Variants in Wastewater for Surveillance

Wastewater surveillance plays an important role in the monitoring of infections of SARS-CoV-2 at the community level. We report here the determination of SARS-CoV-2 and differentiation of its variants of concern in 294 wastewater samples collected from two major Canadian cities from May 2021 to March 2023. The overall method of analysis involved extraction of the virus and viral components using electronegative membranes, in situ stabilization and concentration of the viral RNA onto magnetic beads, and direct analysis of the viral RNA on the magnetic beads. Multiplex reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays, targeting specific and naturally selected mutations in SARS-CoV-2, enabled detection and differentiation of the Alpha, Beta, Gamma, Delta, and Omicron variants. An Omicron triplex RT-qPCR assay targeting three mutations, HV 69-70 deletion, K417N, and L452R, was able to detect and differentiate the Omicron BA.1/BA.3, BA.2/XBB, and BA.4/5. This assay had efficiencies of 90-104% for all three mutation targets and a limit of detection of 28 RNA copies per reaction. Analyses of 294 wastewater samples collected over a two-year span showed the concentrations and trends of Alpha, Beta, Gamma, Delta, and Omicron variants as they emerge in two major Canadian cities participating in the wastewater surveillance program. The trends of specific variants were consistent with clinical reports for the same period. At the beginning of each wave, the corresponding variants were detectable in wastewater. For example, RNA concentrations of the BA.2 variant were as high as 104 copies per 100 mL of wastewater collected in January 2022, when approximately only 50-60 clinical cases of BA.2 infection were reported in Canada. These results show that the strategy and highly sensitive assays for the variants of concern in wastewater are potentially useful for the detection of newly emerging SARS-CoV-2 variants and other viruses for future community biomonitoring.