Reverse Transcription Droplet Digital PCR Research Articles

Surveillance of SARS-CoV-2 in wastewater by quantitative PCR and digital PCR: a case study in Shijiazhuang city, Hebei province, China

ABSTRACT In this study, we reported the first long-term monitoring of SARS-CoV-2 in wastewater in Mainland China from November 2021 to October 2023. The city of Shijiazhuang was employed for this case study. We developed a triple reverse transcription droplet digital PCR (RT-ddPCR) method using triple primer-probes for simultaneous detection of the N1 gene, E gene, and Pepper mild mottle virus (PMMoV) to achieve accurate quantification of SARS-CoV-2 RNA in wastewater. Both the RT-ddPCR method and the commercial multiplex reverse transcription quantitative polymerase chain reaction (RT-qPCR) method were implemented for the detection of SARS-CoV-2 in wastewater in Shijiazhuang City over a 24-month period. Results showed that SARS-CoV-2 was detected for the first time in the wastewater of Shijiazhuang City on 10 November 2022. The peak of COVID-19 cases occurred in the middle of December 2022, when the concentration of SARS-CoV-2 in the wastewater was highest. The trend of virus concentration increases and decreases forming a “long-tailed” shape in the COVID-19 outbreak and recession cycle. The results indicated that both multiplex RT-ddPCR and RT-qPCR are effective in detecting SARS-CoV-2 in wastewater, but RT-ddPCR is capable of detecting low concentrations of SARS-CoV-2 in wastewater which is more efficient. The SARS-CoV-2 abundance in wastewater is correlated to clinical data, outlining the public health utility of this work. Highlights First long-term monitoring of SARS-CoV-2 in wastewater in Mainland China COVID-19 outbreak was tracked in Shijiazhuang City from outbreak to containment Wastewater was monitored simultaneously using RT-ddPCR and RT-qPCR methods Triple primer-probe RT-ddPCR detects N1 and E genes of SARS-CoV-2 and PMMoV

Utilizing droplet digital polymerase chain reaction for siRNA quantitation in rodent plasma and tissue via stem-loop reverse transcription.

Background: siRNA is a promising therapeutic modality highlighted by several US FDA approvals since 2018, with many more oligonucleotide assetsin clinical development. To support siRNA discovery and development, robust and sensitive quantitative platforms for bioanalysis must be established to assess pharmacokinetic/pharmacodynamic relationships and toxicology. Droplet digital PCR offers improved sensitivity and throughput, as well as reduced susceptibility to matrix effects, compared with other analytical platforms. Methodology: The authors developed a stem-loop reverse transcription droplet digital PCR method to measure siRNA in mouse plasma and liver extract using bioanalytical method qualification guidelines. Conclusion: This newly developed assay has been demonstrated to be a superior alternative to other platforms, with the added benefit of greater sensitivity, with dynamic range from 390 to 400,000 copies/reaction and readiness for FDA investigational new drug-enabling applications.

Persistence of Infectious Human Norovirus in Estuarine Water

Norovirus is the predominant cause of viral acute gastroenteritis globally. While person-to-person is the most reported transmission route, norovirus is also associated with waterborne and foodborne illness, including from the consumption of contaminated bivalve molluscan shellfish. The main cause of shellfish contamination is via the bioaccumulation of norovirus from growing waters impacted by human wastewater. However, data on the persistence of infectious norovirus in the environment are limited due to a lack of a human norovirus culture method in the past. In this study, we applied the recently established method of norovirus replication in human intestinal enteroids to determine the persistence of norovirus in artificial estuarine water at 25 ppt for up to 21 days at 4 °C and 16 °C in the dark. Infectious norovirus was detected for up to 21 days. The relative infectivity declined from 100 to 3% at day 21, with decay rate constants of 0.07 day−1 at 4 °C and 0.17 day−1 at 16 °C. There was no decrease in norovirus titres as measured by reverse transcription-droplet digital PCR (RT-ddPCR), confirming the lack of the relationship between norovirus infectivity and direct detection by PCR. The results confirm that norovirus can remain infectious for at least 3 weeks in an estuarine water environment, presenting associated health risks.

Evaluating the sensitivity of droplet digital PCR for the quantification of SARS-CoV-2 in wastewater.

Wastewater surveillance for SARS-CoV-2 has been demonstrated to be a valuable tool in monitoring community-level virus circulation and assessing new outbreaks. It may become a useful tool in the early detection and response to future pandemics, enabling public health authorities to implement timely interventions and mitigate the spread of infectious diseases with the fecal excretion of their agents. It also offers a chance for cost-effective surveillance. Reverse transcription-quantitative polymerase chain reaction (RTqPCR) is the most commonly used method for viral RNA detection in wastewater due to its sensitivity, reliability, and widespread availability. However, recent studies have indicated that reverse transcription droplet digital PCR (RTddPCR) has the potential to offer improved sensitivity and accuracy for quantifying SARS-CoV-2 RNA in wastewater samples. In this study, we compared the performance of RTqPCR and RTddPCR approaches for SARS-CoV-2 detection and quantification on wastewater samples collected during the third epidemic wave in Saxony, Germany, characterized by low-incidence infection periods. The determined limits of detection (LOD) and quantification (LOQ) were within the same order of magnitude, and no significant differences were observed between the PCR approaches with respect to the number of positive or quantifiable samples. Our results indicate that both RTqPCR and RTddPCR are highly sensitive methods for detecting SARS-CoV-2. Consequently, the actual gain in sensitivity associated with ddPCR lags behind theoretical expectations. Hence, the choice between the two PCR methods in further environmental surveillance programs is rather a matter of available resources and throughput requirements.

Quantitation and integrity evaluation of RNA genome in lentiviral vectors by direct reverse transcription-droplet digital PCR (direct RT-ddPCR)

Lentiviral vectors (LV) have proven to be powerful tools for stable gene delivery in both dividing and non-dividing cells. Approval of these LVs for use in clinical applications has been achieved by improvements in LV design. Critically important characteristics concerning quality control are LV titer quantification and the detection of impurities. However, increasing evidence concerning high variability in titration assays indicates poor harmonization of the methods undertaken to date. In this study, we developed a direct reverse transcription droplet digital PCR (Direct RT-ddPCR) approach without RNA extraction and purification for estimation of LV titer and RNA genome integrity. The RNA genome integrity was assessed by RT-ddPCR assays targeted to four distant regions of the LV genome. Results of the analyses showed that direct RT-ddPCR without RNA extraction and purification performs similarly to RT-ddPCR on purified RNA from 3 different LV samples, in terms of robustness and assay variance. Interestingly, these RNA titer results were comparable to physical titers by p24 antigen ELISA (enzyme-linked immunosorbent assay). Moreover, we confirmed the partial degradation or the incomplete RNA genomes in the prepared 3 LV samples. These results may partially explain the discrepancy of the LV particle titers to functional titers. This work not only demonstrates the feasibility of direct RT-ddPCR in determining LV titers, but also provides a method that can be easily adapted for RNA integrity assessment.

Development and preliminary application of a reverse-transcription droplet digital PCR assay for detection and quantification of apple stem pitting virus in vitro propagated apple plantlets

Apple stem pitting virus (ASPV) is a viral pathogen that affects pomefruit trees and causes significant economic losses. Considering its global distribution and economic impact, developing accurate and sensitive diagnostic technologies is imperative for producing ASPV-free plantlets through in vitro micropropagation. In the current study, the complete genome sequence of ASPV was obtained through high-throughput sequencing of micro-propagated apple plantlets. Further, the genome sequence was used to design primer sets for detecting ASPV using reverse-transcription droplet digital PCR (RT-ddPCR). The optimized RT-ddPCR assay did not show cross-reactivity to other major apple viruses, and it was at least 10 times more sensitive than RT-real-time quantitative PCR (RT-qPCR). Both RT-ddPCR and RT-qPCR data exhibited high degrees of linearity, with an R2 value of 0.9982. In addition, a field test was performed to validate the RT-ddPCR data in 44 apple plantlets. The results revealed that ddRT-PCR detected 41 positive samples, whereas only 39 positive samples were detected by RT-qPCR. The developed RT-ddPCR assay can serve as a precise, sensitive, and quantifiable method for the reliable diagnosis of ASPV infection in micropropagated apple plantlets, particularly in ASPV-free certification programs. Its utilization contributes to improved disease management, ensuring the maintenance of apple production.

Zika virus RNA persistence and recovery in water and wastewater: An approach for Zika virus surveillance in resource-constrained settings

During the 2015–2016 Zika virus (ZIKV) epidemic in the Americas, serological cross-reactivity with other flaviviruses and relatively high costs of nucleic acid testing in the region hindered the capacity for widespread diagnostic testing. In such cases where individual testing is not feasible, wastewater monitoring approaches may offer a means of community-level public health surveillance. To inform such approaches, we characterized the persistence and recovery of ZIKV RNA in experiments where we spiked cultured ZIKV into surface water, wastewater, and a combination of both to examine the potential for detection in open sewers serving communities most affected by the ZIKV outbreak, such as those in Salvador, Bahia, Brazil. We used reverse transcription droplet digital PCR to quantify ZIKV RNA. In our persistence experiments, we found that the persistence of ZIKV RNA decreased with increasing temperature, significantly decreased in surface water versus wastewater, and significantly decreased when the initial concentration of virus was lowered by one order of magnitude. In our recovery experiments, we found higher percent recovery of ZIKV RNA in pellets versus supernatants from the same sample, higher recoveries in pellets using skimmed milk flocculation, lower recoveries of ZIKV RNA in surface water versus wastewater, and lower recoveries from a freeze thaw. We also analyzed samples collected from Salvador, Brazil during the ZIKV outbreak (2015–2016) that consisted of archived samples obtained from open sewers or environmental waters thought to be contaminated by sewage. Although we did not detect any ZIKV RNA in the archived Brazil samples, results from these persistence and recovery experiments serve to inform future wastewater monitoring efforts in open sewers, an understudied and important application of wastewater monitoring.

Application of wastewater-based surveillance and copula time-series model for COVID-19 forecasts

The objective of this study was to develop a novel copula-based time series (CTS) model to forecast COVID-19 cases and trends based on wastewater SARS-CoV-2 viral load and clinical variables. Wastewater samples were collected from wastewater pumping stations in five sewersheds in the City of Chesapeake VA. Wastewater SARS-CoV-2 viral load was measured using reverse transcription droplet digital PCR (RT-ddPCR). The clinical dataset included daily COVID-19 reported cases, hospitalization cases, and death cases. The CTS model development included two steps: an autoregressive moving average (ARMA) model for time series analysis (step I), and an integration of ARMA and a copula function for marginal regression analysis (step II). Poisson and negative binomial marginal probability densities for copula functions were used to determine the forecasting capacity of the CTS model for COVID-19 forecasts in the same geographical area. The dynamic trends predicted by the CTS model were well suited to the trend of the reported cases as the forecasted cases from the CTS model fell within the 99 % confidence interval of the reported cases. Wastewater SARS CoV-2 viral load served as a reliable predictor for forecasting COVID-19 cases. The CTS model provided robust modeling to predict COVID-19 cases.

Development and application of a reverse transcription droplet digital PCR assay for detection and quantification of Plantago asiatica mosaic virus

Plantago asiatica mosaic virus (PlAMV), which infects lilies worldwide, constitutes a potential risk factor for lily production. Development of effective and sensitive methods for the detection and specific quantification of PlAMV is required to prevent the spread of PlAMV in lilies. In this study, we established a sensitive and accurate quantification method for PlAMV infection in lily samples using a reverse transcription droplet digital polymerase chain reaction (RT-ddPCR) assay. The specificity and sensitivity of the proposed RT-ddPCR assay was evaluated for precise detection and quantification of PlAMV. The assay exhibited high specificity for PlAMV and showed no cross-reactivity with other lily viruses. It was about 10-fold more sensitive than reverse-transcription followed by quantitative polymerase chain reaction (RT-qPCR). RT-ddPCR (R2 = 0.9985) and RT-qPCR (R2 = 0.9869) showed high degrees of linearity. In addition, field validation tests on 92 lily samples confirmed that RT-ddPCR (45/92) has higher sensitivity than RT-qPCR (8/92). In summary, RT-ddPCR outperforms RT-qPCR in the analysis of low-viral-load samples and can be utilized for PlAMV infection diagnosis, especially in plant quarantine inspection and PlAMV-free certification programs.

Comparison of the methods for isolation and detection of SARS-CoV-2 RNA in municipal wastewater.

Coronavirus SARS-CoV-2 is a causative agent responsible for the current global pandemic situation known as COVID-19. Clinical manifestations of COVID-19 include a wide range of symptoms from mild (i.e., cough, fever, dyspnea) to severe pneumonia-like respiratory symptoms. SARS-CoV-2 has been demonstrated to be detectable in the stool of COVID-19 patients. Waste-based epidemiology (WBE) has been shown as a promising approach for early detection and monitoring of SARS-CoV-2 in the local population performed via collection, isolation, and detection of viral pathogens from environmental sources. In order to select the optimal protocol for monitoring the COVID-19 epidemiological situation in region Turiec, Slovakia, we (1) compared methods for SARS-CoV-2 separation and isolation, including virus precipitation by polyethylene glycol (PEG), virus purification via ultrafiltration (Vivaspin®) and subsequent isolation by NucleoSpin RNA Virus kit (Macherey-Nagel), and direct isolation from wastewater (Zymo Environ Water RNA Kit); (2) evaluated the impact of water freezing on SARS- CoV-2 separation, isolation, and detection; (3) evaluated the role of wastewater filtration on virus stability; and (4) determined appropriate methods including reverse transcription-droplet digital PCR (RT-ddPCR) and real-time quantitative polymerase chain reaction (RT-qPCR) (targeting the same genes, i.e., RdRp and gene E) for quantitative detection of SARS-CoV-2 in wastewater samples. (1) Usage of Zymo Environ Water RNA Kit provided superior quality of isolated RNA in comparison with both ultracentrifugation and PEG precipitation. (2) Freezing of wastewater samples significantly reduces the RNA yield. (3) Filtering is counterproductive when Zymo Environ Water RNA Kit is used. (4) According to the specificity and sensitivity, the RT-ddPCR outperforms RT-qPCR. The results of our study suggest that WBE is a valuable early warning alert and represents a non-invasive approach to monitor viral pathogens, thus protects public health on a regional and national level. In addition, we have shown that the sensitivity of testing the samples with a nearer detection limit can be improved by selecting the appropriate combination of enrichment, isolation, and detection methods.

Comparison of RT-qPCR and RT-ddPCR with Rift valley fever virus (RVFV) RNA

Rift valley fever (RVF) is an important zoonotic disease caused by the Rift valley fever virus (RVFV) which can affect ruminants and humans. In this study, a comparison was done of the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and reverse transcription-droplet digital PCR (RT-ddPCR) assays with synthesized RVFV RNA, cultured viral RNA, and mock clinical RVFV RNA samples. The genomic segments (L, M, and S) of three RVFV strains (BIME01, Kenya56, and ZH548) were synthesized and used as templates for in vitro transcription (IVT). Both the RT-qPCR and RT-ddPCR assays for RVFV did not react with any of the negative reference viral genomes. Thus, both the RT-qPCR and RT-ddPCR assays are specific to RVFV. The comparison of both the RT-qPCR and RT-ddPCR assays with serially diluted templates showed that the LoD of both assays are similar, and a concordant of the results was observed. The LoD of both assays reached the practical measurable minimum concentration. Taken altogether, the sensitivity of the RT-qPCR and RT-ddPCR assays is similar, and the material measured by RT-ddPCR can be used as a reference material for RT-qPCR.

A multiplexed, paired-pooled droplet digital PCR assay for detection of SARS-CoV-2 in saliva

In response to the SARS-CoV-2 pandemic, we developed a multiplexed, paired-pool droplet digital PCR (MP4) screening assay. Key features of our assay are the use of minimally processed saliva, 8-sample paired pools, and reverse-transcription droplet digital PCR (RT-ddPCR) targeting the SARS-CoV-2 nucleocapsid gene. The limit of detection was determined to be 2 and 12 copies per µl for individual and pooled samples, respectively. Using the MP4 assay, we routinely processed over 1,000 samples a day with a 24-h turnaround time and over the course of 17 months, screened over 250,000 saliva samples. Modeling studies showed that the efficiency of 8-sample pools was reduced with increased viral prevalence and that this could be mitigated by using 4-sample pools. We also present a strategy for, and modeling data supporting, the creation of a third paired pool as an additional strategy to employ under high viral prevalence.

Prostate cancer extracellular vesicle digital scoring assay – a rapid noninvasive approach for quantification of disease-relevant mRNAs

Optimizing outcomes in prostate cancer (PCa) requires precision in characterization of disease status. This effort was directed at developing a PCa extracellular vesicle (EV) Digital Scoring Assay (DSA) for detecting metastasis and monitoring progression of PCa. PCa EV DSA is comprised of an EV purification device (i.e., EV Click Chip) and reverse-transcription droplet digital PCR that quantifies 11 PCa-relevant mRNA in purified PCa-derived EVs. A Met score was computed for each plasma sample based on the expression of the 11-gene panel using the weighted Z score method. Under optimized conditions, the EV Click Chips outperformed the ultracentrifugation or precipitation method of purifying PCa-derived EVs from artificial plasma samples. Using PCa EV DSA, the Met score distinguished metastatic (n = 20) from localized PCa (n = 20) with an area under the receiver operating characteristic curve of 0.88 (95% CI:0.78–0.98). Furthermore, longitudinal analysis of three PCa patients showed the dynamics of the Met scores reflected clinical behavior even when disease was undetectable by imaging. Overall, a sensitive PCa EV DSA was developed to identify metastatic PCa and reveal dynamic disease states noninvasively. This assay may complement current imaging tools and blood-based tests for timely detection of metastatic progression that can improve care for PCa patients.

Transcriptomic Signatures of Human Immunodeficiency Virus Post-Treatment Control.

Posttreatment controllers (PTCs) are rare HIV-infected individuals who can limit viral rebound after antiretroviral therapy interruption (ATI), but the mechanisms of this remain unclear. To investigate these mechanisms, we quantified various HIV RNA transcripts (via reverse transcription droplet digital PCR [RT-ddPCR]) and cellular transcriptomes (via RNA-seq) in blood cells from PTCs and noncontrollers (NCs) before and two time points after ATI. HIV transcription initiation did not significantly increase after ATI in PTCs or in NCs, whereas completed HIV transcripts increased at early ATI in both groups and multiply-spliced HIV transcripts increased only in NCs. Compared to NCs, PTCs showed lower levels of HIV DNA, more cell-associated HIV transcripts per total RNA at all times, no increase in multiply-spliced HIV RNA at early or late ATI, and a reduction in the ratio of completed/elongated HIV RNA after early ATI. NCs expressed higher levels of the IL-7 pathway before ATI and expressed higher levels of multiple cytokine, inflammation, HIV transcription, and cell death pathways after ATI. Compared to the baseline, the NCs upregulated interferon and cytokine (especially TNF) pathways during early and late ATI, whereas PTCs upregulated interferon and p53 pathways only at early ATI and downregulated gene translation during early and late ATI. In NCs, viral rebound after ATI is associated with increases in HIV transcriptional completion and splicing, rather than initiation. Differences in HIV and cellular transcription may contribute to posttreatment control, including an early limitation of spliced HIV RNA, a delayed reduction in completed HIV transcripts, and the differential expression of the IL-7, p53, and TNF pathways. IMPORTANCE The findings presented here provide new insights into how HIV and cellular gene expression change after stopping ART in both noncontrollers and posttreatment controllers. Posttreatment control is associated with an early ability to limit increases in multiply-spliced HIV RNA, a delayed (and presumably immune-mediated) ability to reverse an initial rise in processive/completed HIV transcripts, and multiple differences in cellular gene expression pathways. These differences may represent correlates or mechanisms of posttreatment control and may provide insight into the development and/or monitoring of therapeutic strategies that are aimed at a functional HIV cure.

Development of multiplex RT-ddPCR assays for detection of SARS-CoV-2 and other common respiratory virus infections.

Measures for mitigation of Coronavirus Disease 2019 (COVID-19) were set to reduce the spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). SARS-CoV-2 and other respiratory viruses share similar transmission routes and some common clinical manifestations. Co-circulation of SARS-CoV-2 and other common respiratory viruses is imminent. Therefore, development of multiplex assays for detecting these respiratory viruses is essential for being prepared for future outbreaks of respiratory viruses. A panel of three reverse transcription droplet digital PCR (RT-ddPCR) assays were developed to detect 15 different human respiratory viruses. Evaluations of its performance were demonstrated. A total of 100 local and 98 imported COVID-19 cases in Hong Kong were screened for co-infection with other common respiratory viruses. All detected viral targets showed distinct signal clusters using the multiplex RT-ddPCR assays. These assays have a broad range of linearity and good intra-/inter-assay reproducibility for each target. The lower limits of quantification for all targets were ≤46 copies per reaction. Six imported cases of COVID-19 were found to be co-infected with other respiratory viruses, whereas no local case of co-infection was observed. The multiplex RT-ddPCR assays were demonstrated to be useful for screening of respiratory virus co-infections. The strict preventive measures applied in Hong Kong may be effective in limiting the circulation of other human respiratory viruses. The multiplex assays developed in this study can achieve a robust detection method for clinical and research purposes.

Development and Analytical Validation of a 6-Plex Reverse Transcription Droplet Digital PCR Assay for the Absolute Quantification of Prostate Cancer Biomarkers in Circulating Tumor Cells of Patients with Metastatic Castration-Resistant Prostate Cancer.

Gene expression in circulating tumor cells (CTCs) can be used as a predictive liquid biopsy test in metastatic castration-resistant prostate cancer (mCRPC). We developed a novel 6-plex reverse transcription droplet digital PCR (RT-ddPCR) assay for the absolute quantification of 4 prostate cancer biomarkers, a reference gene, and a synthetic DNA external control (DNA-EC) in CTCs isolated from mCRPC patients. A novel 6-plex RT-ddPCR assay was developed for the simultaneous absolute quantification of AR-FL, AR-V7, PSA, and PSMA, HPRT (used as a reference gene), and a synthetic DNA-EC that was included for quality control. The assay was optimized and analytically validated using DNA synthetic standards for each transcript as positive controls. Epithelial cellular adhesion molecule (EpCAM)-positive CTC fractions isolated from 90 mCRPC patients and 11 healthy male donors were analyzed, and results were directly compared with reverse transcription quantitative PCR (RT-qPCR) for all markers in all samples. Linear dynamic range, limit of detection, limit of quantification, intra- and interassay precision, and analytical specificity were determined for each marker. Application of the assay in EpCAM-positive CTC showed positivity for AR-FL (71/90; 78.9%), AR-V7 (28/90; 31.1%), PSA (41/90; 45.6%), PSMA (38/90; 42.2%), and HPRT (90/90; 100%); DNA-EC concentration was constant across all samples. Direct comparison with RT-qPCR for the same markers in the same samples revealed RT-ddPCR to have superior diagnostic sensitivity. Our 6-plex RT-ddPCR assay was highly sensitive, specific, and reproducible, and enabled simultaneous and absolute quantification of 5 gene transcripts in minute amounts of CTC-derived cDNA. Application of this assay in clinical samples gave diagnostic sensitivity and specificity comparable to, or better than, RT-qPCR.

Quantification of hepatitis E virus in raw pork livers using droplet digital RT-PCR

Hepatitis E virus (HEV) is the causative agent of hepatitis E. Some of the rise in hepatitis E infection in China may be linked to undercooked pork. In this study, we established a reverse transcription droplet digital PCR (RT-ddPCR) method to detect HEV in raw pork livers. The detection limit of the assay for HEV RNA was as low as 1.81 copies/μL. The suggested approach was validated on 14 samples, demonstrating greater sensitivity, specificity, and anti-interference performance features than RT-qPCR. Furthermore, we amplified the partial ORF2 gene by nested RT-PCR and sequenced for the HEV RNA positive samples. The prevalence of HEV in all collected samples was 2.24% (14/626), and the viral load was between 8.0 copies/μL and 8975 copies/μL. Specifically, the virus was detected in 10.62% (12/113) of the samples collected from the bio-safety disposal centers for dead livestock and poultry, in 0.67% (2/300) of the samples collected from the slaughterhouses, and none of the samples collected from the retail markets was HEV RNA positive. The subsequent phylogenetic analysis revealed that all HEV isolates belonged to the subtype 4d, which is one of the most common subtypes in northern China.

Quantitative differential analysis of norovirus outbreak samples using RT-ddPCR.

Noroviruses cause acute gastroenteritis with symptoms of diarrhoea and vomiting, and their high infectivity allows outbreaks to readily occur. Quickly identifying and isolating potential contaminants is an effective method to prevent the spread of outbreaks. A total of 376 samples collected from nine outbreaks were categorized as either patient, asymptomatic individual, cook or environmental samples, according to the source of contamination. Using real-time PCR and sequencing analysis, norovirus GII genotypes were detected in 34·9% of samples from patients, 19·2% from asymptomatic individuals, 2·4% from the environment and 1·4% from cooks. Our findings showed contrasting results in samples categories quantified based on the limit of blank and detection limit by reverse transcription droplet digital PCR, which is a more sensitive testing method than real-time-PCR.

A reverse-transcription droplet digital PCR assay to detect and quantify SARS-CoV-2 RNA in upper respiratory tract specimens.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a positive-sense, single-stranded RNA virus that causes coronavirus disease 2019 (COVID-19). Symptoms are variable and range from asymptomatic or mild to severe (i.e., pneumonia) in both healthy and immunocompromised patients. We developed a reverse-transcription droplet digital PCR (RT-ddPCR) assay for quantification of SARS-CoV-2 RNA in clinical nasopharyngeal and oropharyngeal swab specimens and evaluated the assay, including reproducibility, agreement of results, analytical measurement range, linearity, analytical sensitivity, and analytical specificity. This quantitative assay had a LoD of 218 copies/mL of viral transport media, with a linear quantification range from 500 to 5,000,000 copies/mL (R2 of 0.9817 and 0.9853 for N1 and N2 targets, respectively). Qualitative agreement of categorical results was 90.5% (57/63) between the reference and RT-ddPCR assays. Quantitative agreement between the two assays showed correlation, with R2 of 0.9726 and 0.9713 for N1 and N2 targets, respectively. No cross-reactivity with common coronavirus strains was detected. This SARS-CoV-2 quantitative RT-ddPCR assay may be a useful tool for a variety of applications including identification of patients with low viral load and serial monitoring of viral load in respiratory tracts specimens of patients for evaluation of the efficacy of therapy for COVID-19.

Wastewater surveillance of SARS-CoV-2 in dormitories as a part of comprehensive university campus COVID-19 monitoring

Wastewater-based epidemiology is an effective tool for monitoring infectious disease spread or illicit drug use within communities. At the Ohio State University, we conducted a SARS-CoV-2 wastewater surveillance program in the 2020–2021 academic year and compared results with the university-required weekly COVID-19 saliva testing to monitor COVID-19 infection prevalence in the on-campus residential communities. The objectives of the study were to rapidly track trends in the wastewater SARS-CoV-2 gene concentrations, analyze the relationship between case numbers and wastewater signals when adjusted using human fecal viral indicator concentrations (PMMoV, crAssphage) in wastewater, and investigate the relationship of the SARS-CoV-2 gene concentrations with wastewater parameters. SARS-CoV-2 nucleocapsid and envelope (N1, N2, and E) gene concentrations, determined with reverse transcription droplet digital PCR, were used to track SARS-CoV-2 viral loads in dormitory wastewater once a week at 6 sampling sites across the campus during the fall semester in 2020. During the following spring semester, research was focused on SARS-CoV2 N2 gene concentrations at 5 sites sampled twice a week. Spearman correlations both with and without adjusting using human fecal viral indicators showed a significant correlation (p < 0.05) between human COVID-19 positive case counts and wastewater SARS-CoV-2 gene concentrations. Spearman correlations showed significant relationships between N1 gene concentrations and both TSS and turbidity, and between E gene concentrations and both pH and turbidity. These results suggest that wastewater signal increases with the census of infected individuals, in which the majority are asymptomatic, with a statistically significant (p-value <0.05) temporal correlation. The study design can be utilized as a platform for rapid trend tracking of SARS-CoV-2 variants and other diseases circulating in various communities.