Dataset Information

Use of Whole Genome Sequencing Data for a First in Silico Specificity Evaluation of the RT-qPCR Assays Used for SARS-CoV-2 Detection.

ABSTRACT: The current COronaVIrus Disease 2019 (COVID-19) pandemic started in December 2019. COVID-19 cases are confirmed by the detection of SARS-CoV-2 RNA in biological samples by RT-qPCR. However, limited numbers of SARS-CoV-2 genomes were available when the first RT-qPCR methods were developed in January 2020 for initial in silico specificity evaluation and to verify whether the targeted loci are highly conserved. Now that more whole genome data have become available, we used the bioinformatics tool SCREENED and a total of 4755 publicly available SARS-CoV-2 genomes, downloaded at two different time points, to evaluate the specificity of 12 RT-qPCR tests (consisting of a total of 30 primers and probe sets) used for SARS-CoV-2 detection and the impact of the virus' genetic evolution on four of them. The exclusivity of these methods was also assessed using the human reference genome and 2624 closely related other respiratory viral genomes. The specificity of the assays was generally good and stable over time. An exception is the first method developed by the China Center for Disease Control and prevention (CDC), which exhibits three primer mismatches present in 358 SARS-CoV-2 genomes sequenced mainly in Europe from February 2020 onwards. The best results were obtained for the assay of Chan et al. (2020) targeting the gene coding for the spiking protein (S). This demonstrates that our user-friendly strategy can be used for a first in silico specificity evaluation of future RT-qPCR tests, as well as verifying that the former methods are still capable of detecting circulating SARS-CoV-2 variants.

SUBMITTER: Gand M

PROVIDER: S-EPMC7432934 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Use of Whole Genome Sequencing Data for a First in Silico Specificity Evaluation of the RT-qPCR Assays Used for SARS-CoV-2 Detection.

Gand Mathieu M Vanneste Kevin K Thomas Isabelle I Van Gucht Steven S Capron Arnaud A Herman Philippe P Roosens Nancy H C NHC De Keersmaecker Sigrid C J SCJ

International journal of molecular sciences 20200804 15

The current COronaVIrus Disease 2019 (COVID-19) pandemic started in December 2019. COVID-19 cases are confirmed by the detection of SARS-CoV-2 RNA in biological samples by RT-qPCR. However, limited numbers of SARS-CoV-2 genomes were available when the first RT-qPCR methods were developed in January 2020 for initial in silico specificity evaluation and to verify whether the targeted loci are highly conserved. Now that more whole genome data have become available, we used the bioinformatics tool S ...[more]

PMID: 32759818

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Project description:BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant of concern (VoC) Omicron (B.1.1.529) has rapidly spread around the world, presenting a new threat to global public human health. Due to the large number of mutations accumulated by SARS-CoV-2 Omicron, concerns have emerged over potentially reduced diagnostic accuracy of reverse-transcription polymerase chain reaction (RT-qPCR), the gold standard diagnostic test for diagnosing coronavirus disease 2019 (COVID-19). Thus, we aimed to assess the impact of the currently endemic Omicron sublineages BA.4 and BA.5 on the integrity and sensitivity of RT-qPCR assays used for coronavirus disease 2019 (COVID-19) diagnosis via in silico analysis. We employed whole genome sequencing data and evaluated the potential for false negatives or test failure due to mismatches between primers/probes and the Omicron VoC viral genome.MethodsIn silico sensitivity of 12 RT-qPCR tests (containing 30 primers and probe sets) developed for detection of SARS-CoV-2 reported by the World Health Organization (WHO) or available in the literature, was assessed for specifically detecting SARS-CoV-2 Omicron BA.4 and BA.5 sublineages, obtained after removing redundancy from publicly available genomes from National Center for Biotechnology Information (NCBI) and Global Initiative on Sharing Avian Influenza Data (GISAID) databases. Mismatches between amplicon regions of SARS-CoV-2 Omicron VoC and primers and probe sets were evaluated, and clustering analysis of corresponding amplicon sequences was carried out.ResultsFrom the 1164 representative SARS-CoV-2 Omicron VoC BA.4 sublineage genomes analyzed, a substitution in the first five nucleotides (C to T) of the amplicon's 3'-end was observed in all samples resulting in 0% sensitivity for assays HKUnivRdRp/Hel (mismatch in reverse primer) and CoremCharite N (mismatch in both forward and reverse primers). Due to a mismatch in the forward primer's 5'-end (3-nucleotide substitution, GGG to AAC), the sensitivity of the ChinaCDC N assay was at 0.69%. The 10 nucleotide mismatches in the reverse primer resulted in 0.09% sensitivity for Omicron sublineage BA.4 for Thai N assay. Of the 1926 BA.5 sublineage genomes, HKUnivRdRp/Hel assay also had 0% sensitivity. A sensitivity of 3.06% was observed for the ChinaCDC N assay because of a mismatch in the forward primer's 5'-end (3-nucleotide substitution, GGG to AAC). Similarly, due to the 10 nucleotide mismatches in the reverse primer, the Thai N assay's sensitivity was low at 0.21% for sublineage BA.5. Further, eight assays for BA.4 sublineage retained high sensitivity (more than 97%) and 9 assays for BA.5 sublineage retained more than 99% sensitivity.ConclusionWe observed four assays (HKUnivRdRp/Hel, ChinaCDC N, Thai N, CoremCharite N) that could potentially result in false negative results for SARS-CoV-2 Omicron VoCs BA.4 and BA.5 sublineages. Interestingly, CoremCharite N had 0% sensitivity for Omicron Voc BA.4 but 99.53% sensitivity for BA.5. In addition, 66.67% of the assays for BA.4 sublineage and 75% of the assays for BA.5 sublineage retained high sensitivity. Further, amplicon clustering and additional substitution analysis along with sensitivity analysis could be used for the modification and development of RT-qPCR assays for detecting SARS-CoV-2 Omicron VoC sublineages.

Project description:SARS-CoV-2 variants of concern, demonstrating higher infection rate and lower vaccine effectiveness as compared with the original virus, are important factors propelling the ongoing COVID-19 global outbreak. Therefore, prompt identification of these variants in the environment is essential for pandemic assessment and containment efforts. One well established tool for such viral monitoring is the use of wastewater systems. Here, we describe continuous monitoring of traces of SARS-CoV-2 viruses in the municipal wastewater of a large city in Israel. By observing morbidity fluctuations (during three main COVID-19 surges) occurring in parallel with Pfizer-BioNTech COVID-19 vaccine vaccination rate, compromised immunity was revealed in the current morbidity peak. RT-qPCR assays for the Original (D614G), Alpha and Beta variants had been previously developed and are being employed for wastewater surveillance. In the present study we developed a sensitive RT-qPCR assay designed for the rapid, direct detection of Gamma and Delta variants of concern. Sensitive quantification and detection of the various variants showed the prevalence of the original variant during the first morbidity peak. The dominance of the Alpha variant over the original variant correlated with the second morbidity peak. These variants decreased concurrently with an increase in vaccinations (Feb-March 2021) and the observed decrease in morbidity. The appearance and subsequent rise of the Delta variant became evident and corresponded to the third morbidity peak (June-August 2021). These results suggest a high vaccine neutralization efficiency towards the Alpha variant compared to its neutralization efficiency towards the Delta variant. Moreover, the third vaccination dose (booster) seems to regain neutralization efficiency towards the Delta variant. The developed assays and wastewater-based epidemiology are important tools aiding in morbidity surveillance and disclosing vaccination efforts and immunity dynamics in the community.

Dataset Information

Use of Whole Genome Sequencing Data for a First in Silico Specificity Evaluation of the RT-qPCR Assays Used for SARS-CoV-2 Detection.

Publications

Use of Whole Genome Sequencing Data for a First in Silico Specificity Evaluation of the RT-qPCR Assays Used for SARS-CoV-2 Detection.

Similar Datasets

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