Development and optimization of a simian immunodeficiency virus (SIV) droplet digital PCR (ddPCR) assay

Identifying SARS-CoV-2 Variants of Concern through Saliva-Based RT-qPCR by Targeting Recurrent Mutation Sites

SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to complement whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60 and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20, 96.40, 99.60, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from 7 to 22 December 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs.

IMPORTANCE SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between variants of concern and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future.

In pursuit of sensitivity: Lessons learned from viral nucleic acid detection and quantification on the Raindance ddPCR platform

Sensitive PCR detection of viral nucleic acids plays a critical role in infectious disease research, diagnosis and monitoring. In the context of SARS-CoV-2 detection, recent reports indicate that digital PCR-based tests are significantly more sensitive than traditional qPCR tests. Numerous factors can influence digital PCR reaction sensitivity. In this review, using a model for human HIV infection and the Raindance ddPCR platform as an example, we describe technical aspects that contribute to sensitive viral signal detection in DNA and RNA from tissue samples, which often harbor viral reservoirs and serve as better predictors of disease outcome and indicators of treatment efficacy.

Ultrasensitive detection and quantification of viral nucleic acids with Raindance droplet digital PCR (ddPCR)

Sensitive detection of viral nucleic acids is critically important for diagnosis and monitoring of the progression of infectious diseases such as those caused by SARS-CoV2, HIV-1, and other viruses. In HIV-1 infection cases, assessing the efficacy of treatment interventions that are superimposed on combination antiretroviral therapy (cART) has benefited tremendously from the development of sensitive HIV-1 DNA and RNA quantitation assays. Simian immunodeficiency virus (SIV) infection of Rhesus macaques is similar in many key aspects to human HIV-1 infection and consequently this non-human primate (NHP) model has and continues to prove instrumental in evaluating HIV prevention, treatment and eradication approaches. Cell and tissue associated HIV-1 viral nucleic acids have been found to serve as useful predictors of disease outcome and indicators of treatment efficacy, highlighting the value of and the need for sensitive detection of viruses in cells/tissues from infected individuals or animal models. However, viral nucleic acid detection and quantitation in such sample sources can often be complicated by high nucleic acid input (that is required to detect ultralow level viruses in, for example, cure research) or inhibitors, leading to reduced detection sensitivity and under-quantification, and confounded result interpretation. Here, we present a step-by-step procedure to quantitatively recover cell/tissue associated viral DNA and RNA, using SIV-infected Rhesus macaque cells and tissues as model systems, and subsequently quantify the viral DNA and RNA with an ultrasensitive SIV droplet digital PCR (ddPCR) assay and reverse transcription ddPCR (RT-ddPCR) assay, respectively, on the Raindance ddPCR platform. The procedure can be readily adapted for a broad range of applications where highly sensitive nucleic acid detection and quantitation are required.

Clinical Application of Droplet Digital PCR for Hepatitis Delta Virus Quantification

Droplet digital PCR (ddPCR) is a novel developed PCR technology providing the absolute quantification of target nucleic acid molecules without the need for a standard curve and regardless PCR amplification efficiency. Our aim was to develop a ddPCR assay for Hepatitis Delta virus (HDV)-RNA viremia quantification and then evaluate its performance in relation to real-time PCR methods. Primers and probe were designed from conserved regions of HDV genome to detect all the 8 HDV genotypes; the World Health Organization (WHO)-HDV international standard was used to calculate the conversion factor transforming results from copies/mL to IU/mL. To evaluate the clinical performance of ddPCR assay, plasma specimens of HDV-infected patients were tested and results were compared with data obtained with two real-time quantitative PCR (RT-qPCR) assays (i.e., in-house assay and commercial RoboGene assay). Analyzing by linear regression a series of 10-fold dilutions of the WHO-HDV International Standard, ddPCR assay showed good linearity with a slope coefficient of 0.966 and R² value of 0.980. The conversion factor from copies to international units was 0.97 and the quantitative linear dynamic range was from 10 to 1 × 10⁶ IU/mL. Probit analysis estimated at 95% an LOD of 9.2 IU/mL. Data from the evaluation of HDV-RNA in routine clinical specimen of HDV patients exhibited strong agreement with results obtained by RT-qPCR showing a concordance correlation coefficient of 0.95. Overall ddPCR and RT-qPCR showed highly comparable technical performance. Moreover, ddPCR providing an absolute quantification method may allow the standardization of HDV-RNA measurement thus improving the clinical and diagnostic management of delta hepatitis.

Identifying SARS-CoV-2 Variants of Concern through saliva-based RT-qPCR by targeting recurrent mutation sites.. [PMID: 35262087 PMCID: PMC8902870 DOI: 10.1101/2022.03.02.22271785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0]

SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to compliment whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60% and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20%, 96.40%, 99.60%, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from December 7-22, 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs.

Importance

SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our real-time RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between VOCs and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future.

SARS-CoV-2 Subgenomic RNAs: Characterization, Utility, and Perspectives

SARS-CoV-2, the etiologic agent at the root of the ongoing COVID-19 pandemic, harbors a large RNA genome from which a tiered ensemble of subgenomic RNAs (sgRNAs) is generated. Comprehensive definition and investigation of these RNA products are important for understanding SARS-CoV-2 pathogenesis. This review summarizes the recent progress on SARS-CoV-2 sgRNA identification, characterization, and application as a viral replication marker. The significance of these findings and potential future research areas of interest are discussed.

Development of a reverse transcription droplet digital PCR (RT-ddPCR) assay for sensitive detection of simian immunodeficiency virus (SIV)

BACKGROUND

Simian immunodeficiency virus (SIV)-infected rhesus macaques constitute an excellent model of human HIV infection. Sensitive detection of SIV RNA in cell and tissue samples from infected animals subjected to treatment regimens becomes especially critical in determining which therapeutic attempts are successful, and consequently, which interventions should be prioritized in HIV cure research.

RESULTS

In this report, we describe the design and testing of a Raindance ddPCR platform-based, sensitive SIV reverse transcription droplet digital PCR (RT-ddPCR) assay by exploring the combinations of various priming conditions and reverse transcriptases, and testing one-step vs. two-step procedures, to eliminate background signal(s) and enable detection and quantification of low level target signals.

CONCLUSIONS

Similar reaction conditions and assay validation procedures can be explored for potential development of additional assays for other applications that require sensitive detection of low-level targets in RNA samples.