Dataset Information

Comparison of RT-qPCR and RT-dPCR Platforms for the Trace Detection of SARS-CoV-2 RNA in Wastewater.

ABSTRACT: We compared reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and RT digital PCR (RT-dPCR) platforms for the trace detection of SARS-CoV-2 RNA in low-prevalence COVID-19 locations in Queensland, Australia, using CDC N1 and CDC N2 assays. The assay limit of detection (ALOD), PCR inhibition rates, and performance characteristics of each assay, along with the positivity rates with the RT-qPCR and RT-dPCR platforms, were evaluated by seeding known concentrations of exogenous SARS-CoV-2 in wastewater. The ALODs using RT-dPCR were approximately 2-5 times lower than those using RT-qPCR. During sample processing, the endogenous (n = 96) and exogenous (n = 24) SARS-CoV-2 wastewater samples were separated, and RNA was extracted from both wastewater eluates and pellets (solids). The RT-dPCR platform demonstrated a detection rate significantly greater than that of RT-qPCR for the CDC N1 and CDC N2 assays in the eluate (N1, p = 0.0029; N2, p = 0.0003) and pellet (N1, p = 0.0015; N2, p = 0.0067) samples. The positivity results also indicated that for the analysis of SARS-CoV-2 RNA in wastewater, including the eluate and pellet samples may further increase the detection sensitivity using RT-dPCR.

SUBMITTER: Ahmed W

PROVIDER: S-EPMC8848507 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Comparison of RT-qPCR and RT-dPCR Platforms for the Trace Detection of SARS-CoV-2 RNA in Wastewater.

Ahmed Warish W Smith Wendy J M WJM Metcalfe Suzanne S Jackson Greg G Choi Phil M PM Morrison Mary M Field Daniel D Gyawali Pradip P Bivins Aaron A Bibby Kyle K Simpson Stuart L SL

ACS ES&T water 20220128 11

We compared reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and RT digital PCR (RT-dPCR) platforms for the trace detection of SARS-CoV-2 RNA in low-prevalence COVID-19 locations in Queensland, Australia, using CDC N1 and CDC N2 assays. The assay limit of detection (ALOD), PCR inhibition rates, and performance characteristics of each assay, along with the positivity rates with the RT-qPCR and RT-dPCR platforms, were evaluated by seeding known concentrations of exogenous SAR ...[more]

PMID: 36380768

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Project description:Effective wastewater surveillance of SARS-CoV-2 RNA requires the rigorous characterization of the limit of detection resulting from the entire sampling process - the process limit of detection (PLOD). Yet to date, no studies have gone beyond quantifying the assay limit of detection (ALOD) for RT-qPCR or RT-dPCR assays. While the ALOD is the lowest number of gene copies (GC) associated with a 95% probability of detection in a single PCR reaction, the PLOD represents the sensitivity of the method after considering the efficiency of all processing steps (e.g., sample handling, concentration, nucleic acid extraction, and PCR assays) to determine the number of GC in the wastewater sample matrix with a specific probability of detection. The primary objective of this study was to estimate the PLOD resulting from the combination of primary concentration and extraction with six SARS-CoV-2 assays: five RT-qPCR assays (US CDC N1 and N2, China CDC N and ORF1ab (CCDC N and CCDC ORF1ab), and E_Sarbeco RT-qPCR, and one RT-dPCR assay (US CDC N1 RT-dPCR) using two models (exponential survival and cumulative Gaussian). An adsorption extraction (AE) concentration method (i.e., virus adsorption on membrane and the RNA extraction from the membrane) was used to concentrate gamma-irradiated SARS-CoV-2 seeded into 36 wastewater samples. Overall, the US CDC N1 RT-dPCR and RT-qPCR assays had the lowest ALODs (< 10 GC/reaction) and PLODs (<3,954 GC/50 mL; 95% probability of detection) regardless of the seeding level and model used. Nevertheless, consistent amplification and detection rates decreased when seeding levels were < 2.32 × 103 GC/50 mL even for US CDC N1 RT-qPCR and RT-dPCR assays. Consequently, when SARS-CoV-2 RNA concentrations are expected to be low, it may be necessary to improve the positive detection rates of wastewater surveillance by analyzing additional field and RT-PCR replicates. To the best of our knowledge, this is the first study to assess the SARS-CoV-2 PLOD for wastewater and provides important insights on the analytical limitations for trace detection of SARS-CoV-2 RNA in wastewater.

Project description:BackgroundSensitive, rapid, and accessible diagnostics continue to be critical to track the COVID-19 pandemic caused by the SARS-CoV-2 virus. RT-qPCR is the gold standard test, and comparison of methodologies and reagents, utilizing patient samples, is important to establish reliable diagnostic pipelines.MethodsHere, we assessed indirect methods that require RNA extraction with direct RT-qPCR on patient samples. Four different RNA extraction kits (Qiagen, Invitrogen, BGI and Norgen Biotek) were compared. For detection, we assessed two recently developed Taqman-based modules (BGI and Norgen Biotek), a SYBR green-based approach (NEB Luna Universal One-Step Kit) with published and newly-developed primers, and clinical results (Seegene STARMag RNA extraction system and Allplex 2019-nCoV RT-qPCR assay). We also tested and optimized direct, extraction-free detection using these RT-qPCR systems and performed a cost analysis of the different methods evaluated here.ResultsMost RNA isolation procedures performed similarly, and while all RT-qPCR modules effectively detected purified viral RNA, the BGI system provided overall superior performance (lower detection limit, lower Ct values and higher sensitivity), generating comparable results to original clinical diagnostic data, and identifying samples ranging from 65 copies to 2.1 × 105 copies of viral genome/μl. However, the BGI detection system is more expensive than other options tested here. With direct RT-qPCR, simply adding an RNase inhibitor greatly improved detection, without the need for any other treatments (e.g. lysis buffers or boiling). The best direct methods detected ~ 10 fold less virus than indirect methods, but this simplified approach reduced sample handling, as well as assay time and cost.ConclusionsWith extracted RNA, the BGI RT-qPCR detection system exhibited superior performance over the Norgen system, matching initial clinical diagnosis with the Seegene Allplex assay. The BGI system was also suitable for direct, extraction-free analysis, providing 78.4% sensitivity. The Norgen system, however, still accurately detected samples with a clinical Ct < 33 from extracted RNA, provided significant cost savings, and was superior to SYBR green assays that exhibited reduced specificity.

Project description:During the coronavirus disease 2019 (COVID-19) pandemic, wastewater surveillance has become an important tool for monitoring the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within communities. In particular, reverse transcription-quantitative PCR (RT-qPCR) has been used to detect and quantify SARS-CoV-2 RNA in wastewater, while monitoring viral genome mutations requires separate approaches such as deep sequencing. A high throughput sequencing platform (ATOPlex) that uses a multiplex tiled PCR-based enrichment technique has shown promise in detecting variants of concern (VOC) while also providing virus quantitation data. However, detection sensitivities of both RT-qPCR and sequencing can be impacted through losses occurring during sample handling, virus concentration, nucleic acid extraction, and RT-qPCR. Therefore, process limit of detection (PLOD) assessments are required to estimate the gene copies of target molecule to attain specific probability of detection. In this study, we compare the PLOD of four RT-qPCR assays (US CDC N1 and N2, China CDC N and ORF1ab) for detection of SARS-CoV-2 to that of ATOPlex sequencing by seeding known concentrations of gamma-irradiated SARS-CoV-2 into wastewater. Results suggest that among the RT-qPCR assays, US CDC N1 was the most sensitive, especially at lower SARS-CoV-2 seed levels. However, when results from all RT-qPCR assays were combined, it resulted in greater detection rates than individual assays, suggesting that application of multiple assays is better suited for the trace detection of SARS-CoV-2 from wastewater samples. Furthermore, while ATOPlex offers a promising approach to SARS-CoV-2 wastewater surveillance, this approach appears to be less sensitive compared to RT-qPCR under the experimental conditions of this study, and may require further refinements. Nonetheless, the combination of RT-qPCR and ATOPlex may be a powerful tool to simultaneously detect/quantify SARS-CoV-2 RNA and monitor emerging VOC in wastewater samples.

Project description:Multiple mutations in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) increase transmission, disease severity, and immune evasion and facilitate zoonotic or anthropozoonotic infections. Four such mutations, ΔH69/V70, L452R, E484K, and N501Y, occurred in the SARS-CoV-2 spike glycoprotein in combinations that allow the simultaneous detection of VOCs. Here, we present two flexible reverse transcription-quantitative PCR (RT-qPCR) platforms for small- and large-scale screening (also known as variant PCR) to detect these mutations and schemes for adapting the platforms to future mutations. The large-scale RT-qPCR platform was validated by pairwise matching of RT-qPCR results with whole-genome sequencing (WGS) consensus genomes, showing high specificity and sensitivity. Both platforms are valuable examples of complementing WGS to support the rapid detection of VOCs. Our mutational signature approach served as an important intervention measure for the Danish public health system to detect and delay the emergence of new VOCs. IMPORTANCE Denmark weathered the SARS-CoV-2 crisis with relatively low rates of infection and death. Intensive testing strategies with the aim of detecting SARS-CoV-2 in symptomatic and nonsymptomatic individuals were available by establishing a national test system called TestCenter Denmark. This testing regime included the detection of SARS-CoV-2 signature mutations, with referral to the national health system, thereby delaying outbreaks of variants of concern. Our study describes the design of the large-scale RT-qPCR platform established at TestCenter Denmark in conjunction with whole-genome sequencing to report mutations of concern to the national health system. Validation of the large-scale RT-qPCR platform using paired WGS consensus genomes showed high sensitivity and specificity. For smaller laboratories with limited infrastructure, we developed a flexible small-scale RT-qPCR platform to detect three signature mutations in a single run. The RT-qPCR platforms are important tools to support the control of the SARS-CoV-2 endemic in Denmark.

Dataset Information

Comparison of RT-qPCR and RT-dPCR Platforms for the Trace Detection of SARS-CoV-2 RNA in Wastewater.

Publications

Comparison of RT-qPCR and RT-dPCR Platforms for the Trace Detection of SARS-CoV-2 RNA in Wastewater.

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