A recent study posted to the medRxiv* preprint server reported the development and validation of a two-reaction multiplex reverse transcription-quantitative polymerase chain reaction (RT-qPCR) genotyping strategy that distinguishes severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs).
Background
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Following the emergence of SARS-CoV-2 in 2019, several VOCs such as Alpha, Gamma, Beta, Omicron, and Delta, have evolved in the last two years. As variations have been reported in response to vaccination, transmissibility, therapy, and clinical prognosis in the SARS-CoV-2 VOCs, the ability to differentiate between SARS-CoV-2 VOCs is of active interest within the scientific community.
The detailed genetic characterization of SARS-CoV-2 using whole-genome sequencing (WGS) is tedious and laborious and, thus, not suitable for routine use. By contrast, a targeted nucleic acid amplification test (NAAT) is more accessible and rapid than sequencing and can serve a complementary role to WGS in clinical settings.
About the study
In the present study, the researchers designed a multiplex RT-qPCR assay that identifies the SARS-CoV-2 S protein mutations in the T478K, K417N, and del69-70 sites using the SARS-CoV-2 WT 69-70 sequence as an internal control, and the assay is termed as reaction two. The team further assessed the performance of this assay combined with their previously developed RT-qPCR assay, which detects the N501Y, L452R, and E484K SARS-CoV-2 mutation sites, termed as reaction one. The researchers also demonstrated the feasibility of this targeted mutational analysis in precise differentiation of various SARS-CoV-2 VOCs.
Upper respiratory swab specimens collected from patients in connection with their routine clinical visit from April 26 to August 1, 2021, were used as samples in the initial phase of the study. These samples were analyzed in the Stanford Clinical Virology Laboratory. The assessment of the two-reaction multiplex RT-qPCR assay in detecting the Omicron variant was conducted using 230 Omicron variant samples with available WGS data collected between December 2021 and January 2022.
Findings
The study results indicated that of the 1,093 samples genotyped, the two-reaction multiplex RT-qPCR assay designed in the current study had 95% to 100% agreement with WGS in 502 upper respiratory swabs.
Nearly 14% of the samples were indicated as unable to genotype in the novel RT-qPCR genotyping technique as the target amplification was absent in one or both of the reactions. The assay failed to genotype about 35% of the positive samples, which were initially tested at or near the point of care and triaged for genotyping without any filter. By contrast, assay failure was less frequent in 4% of samples initially evaluated at moderate-to-high complexity virology labs, where samples containing less virus load were not sent for genotyping from these labs.
In the combinations of reactions one and two, the E484K, del69-70, N501Y, T478K, and L452R had 100% positive percent agreement (PPA), and K417N had a PPA of 96% with WGS. Further, the negative percent agreement (NPAs) for K417N, T478K, N501Y, and del69-70 were 100%, NPA of E484K was 99%, and NPA of L452R was 95% between WGS and the two-reaction RT-qPCR genotyping method.
The validation of the current RT-qPCR in another lot of 230 Omicron-infected samples confirmed by WGS demonstrated 100% agreement. A unique mutation pattern of del69-70 and K417N was observed in reaction two. Further, all the 230 Omicron samples tested failed to amplify any target in reaction one, including internal control. These patterns were not observed in the previous 1,093 samples evaluated.
The correlation between the results of WGS and two-reaction multiplexed RT-qPCR was observed in 732 samples with two, 20, 43, 59, 230, and 378 infections by SARS-CoV-2 Beta, Gamma, Alpha, non-VOC, Omicron, and Delta strains, respectively. Error reporting by RT-qPCR was observed in five samples, where one was assigned as Beta and the others as Gamma, whereas these samples were actually found to be variants of interest (VOIs) Mu (BB.2 or B.1.621) using WGS. SARS-CoV-2 VOC-associated mutation patterns were not observed in the remaining 54 samples.
Conclusions
According to the authors, the two-reaction multiplex RT-qPCR genotyping approach designed and validated in the current study evaluating six different SARS-CoV-2 mutation sites - namely N501Y, L452R, E484K, T478K, K417N, and del69-70 - is the most comprehensive SARS-CoV-2 variant genotyping test that can identify Omicron, Delta, Gamma, Beta, and Alpha variants to date.
The results of this RT-qPCR approach demonstrated an excellent concordance to WGS with 95% NPA and PPA for all targeted mutations.
Taken together, the findings show that the two-reaction multiplex RT-qPCR genotyping strategy developed in the present study can complement WGS and is suitable for the triage of samples for sequencing, near real-time variant surveillance, and clinical decision-making in association with SARS-CoV-2 VOCs.
This news article was a review of a preliminary scientific report that had not undergone peer-review at the time of publication. Since its initial publication, the scientific report has now been peer reviewed and accepted for publication in a Scientific Journal. Links to the preliminary and peer-reviewed reports are available in the Sources section at the bottom of this article. View Sources
Article Revisions
- May 11 2023 - The preprint preliminary research paper that this article was based upon was accepted for publication in a peer-reviewed Scientific Journal. This article was edited accordingly to include a link to the final peer-reviewed paper, now shown in the sources section.