key: cord-1020071-a8po47xl
authors: Subramoney, Kathleen; Mtileni, Nkhensani; Bharuthram, Avani; Davis, Ashlyn; Kalenga, Beauty; Rikhotso, Mikateko; Maphahlele, Mpho; Giandhari, Jennifer; Naidoo, Yeshnee; Pillay, Sureshnee; Ramphal, Upasana; Ramphal, Yajna; Tegally, Houriiyah; Wilkinson, Eduan; Mohale, Thabo; Ismail, Arshad; Mashishi, Bonolo; Mbenenge, Nonhlanhla; de Oliveira, Tulio; Makatini, Zinhle; Fielding, Burtram C.; Treurnicht, Florette K.
title: Identification of SARS‐CoV‐2 Omicron variant using spike gene target failure and genotyping assays, Gauteng, South Africa, 2021
date: 2022-05-08
journal: J Med Virol
DOI: 10.1002/jmv.27797
sha: f7ad6e301130c3bef3c2af734c333c3ec3de5a50
doc_id: 1020071
cord_uid: a8po47xl

The circulation of Omicron BA.1 led to the rapid increase in severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) cases in South Africa in November 2021, which warranted the use of more rapid detection methods. We, therefore, assessed the ability to detect Omicron BA.1 using genotyping assays to identify specific mutations in SARS‐CoV‐2 positive samples, Gauteng province, South Africa. The TaqPath™ COVID‐19 real‐time polymerase chain reaction assay was performed on all samples selected to identify spike gene target failure (SGTF). SARS‐CoV‐2 genotyping assays were used for the detection of del69/70 and K417N mutation. Whole‐genome sequencing was performed on a subset of genotyped samples to confirm these findings. Of the positive samples received, 11.0% (175/1589) were randomly selected to assess if SGTF and genotyping assays, that detect del69/70 and K417N mutations, could identify Omicron BA.1. We identified SGTF in 98.9% (173/175) of samples, of which 88.0% (154/175) had both the del69/70 and K417N mutation. The genotyped samples (45.7%; 80/175) that were sequenced confirmed Omicron BA.1 (97.5%; 78/80). Our data show that genotyping for the detection of the del69/70 and K417N coupled with SGTF is efficient to exclude Alpha and Beta variants and rapidly detect Omicron BA.1. However, we still require assays for the detection of unique mutations that will allow for the differentiation between other Omicron sublineages. Therefore, the use of genotyping assays to detect new dominant or emerging lineages of SARS‐CoV‐2 will be beneficial in limited‐resource settings.

Alpha and Beta variants and rapidly detect Omicron BA.1. However, we still require assays for the detection of unique mutations that will allow for the differentiation between other Omicron sublineages. Therefore, the use of genotyping assays to detect new dominant or emerging lineages of SARS-CoV-2 will be beneficial in limited-resource settings.

genotyping, Omicron BA.1, SARS-CoV-2, variants of concern 1 | INTRODUCTION The rapid evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to the emergence of several variants of concern (VOC), which have been classified as variants with key characteristic features bearing significant epidemiological and clinical consequences. 1 Omicron has dominated the fourth wave. 7 Since the initial detection of Omicron, the number of cases increased more rapidly compared to previous waves. 7, 8 Omicron has over 30 mutations in the spike (S) protein, some of which overlap with the Alpha (del69/70, P681H), Beta (K417N, N501Y), and Delta (G142D and T478K) VOCs. 7, [9] [10] [11] A number of these mutations, including the del69/70, are predicted or known to have an impact on immune escape or transmissibility. 11 Since the discovery of 13, 14 The latter was found to be significant for the detection and reporting of Omicron. 13, 14 Although next-generation sequencing (NGS) remains the ideal tool for surveillance and detection of novel SARS-CoV-2 VOCs, many low-to middle-income countries are unable to effectively implement this tool due to lack of resources, facilities, or expertise. Inconsistencies in testing and time delays in generating and releasing sequencing data were reported to hinder surveillance initiatives in African countries. 5 Although still posing many challenges, the implementation of molecular diagnostic testing is far more achievable when coordinated efforts are made in comparison to the implementation of NGS.

In this study, we investigated the use of the Thermo Fisher Scientific TaqPath™ COVID-19 assay and the SARS-CoV-2 genotyping assays to rapidly identify infections that occurred due to Omicron BA.1 sublineage, at the start of the fourth wave in South Africa, to highlight the usefulness and importance of molecular assays, especially in settings where NGS may not be readily available.

The study cohort includes persons of all ages for whom upper respiratory tract samples were received for SARS-CoV-2 diagnosis, at the National Health Laboratory Service, Virology Laboratory, Charlotte Maxeke Johannesburg Academic Hospital the primary SARS-CoV-2 diagnostic testing facility in the City of Johannesburg Metropolitan district of Gauteng Province, from November 1 to 30, 2021. This includes samples collected from in-patients, out-patients, and community surveillance.

The majority of respiratory samples received included nasal/ nasopharyngeal and/or oropharyngeal swabs in viral or inactivation transport medium (Wuxi NEST Biotechnology), or dry swabs reconstituted in the laboratory in 1 ml phosphate-buffered saline or viral transport medium. Samples that were initially tested on the CFX and BioFire platforms were retested using the TaqPath™ COVID-19 assay to detect SGTF. The SGFT was defined as any sample for which the S gene did not amplify, but the N and/or ORF1ab genes amplified with C t < 38.

The TaqMan SARS-CoV-2 singleplex single-nucleotide polymorphism (SNP) genotyping assays (Thermo Fisher Scientific) were performed using the QuantStudio 5 real-time platform (Thermo Fisher Scientific), to detect the del69/70 and K417N mutations associated with Omicron BA.1. These assays differentiate between wild type (H69V70 and K417) and mutant (del69/70 and 417N) in each sample.

SARS-CoV-2 PCR assay analysis was performed on the Quant-Studio 5 design and analysis V2.5.1 software. SNPs were confirmed using both the allelic discrimination plots and amplification plots.

Alleles that clustered along the x-axis (allele 1, VIC-labeled) represented the homozygous wild-type genotype, while alleles that clustered along the y-axis (allele 2, FAM-labeled) represented homozygous mutant genotype, and alleles that clustered between the x-axis and y-axis represented heterozygous genotypes where both the mutant and wild-type were present. Amplification curves were also analyzed to confirm the presence of the mutant and/or wild-type.

Samples with C t < 31 were randomly selected across collection dates and sites on a weekly basis for SARS-CoV-2 whole-genome sequencing. As part of the Network for Genomics Surveillance in South Africa, samples were submitted to the KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), the National Institute for Communicable Diseases (NICD), or sequencing was performed in-house.

Samples were amplified using the ARCTIC V4 primers 15 (Table S1 ). Sequences were then downloaded from GISAID for further analysis using the Nextstrain (https://clades. nextstrain.org) online tool for the construction of the phylogenetic trees and the Pangolin lineage assigner (https://pangolin.cog-uk.io) was used to confirm the lineages. samples tested positive. The number of samples received and tested declined from November 6th to 7th, 13th to 14th, 20th to 21st, and 27th to 28th, which was indicative of weekends ( Figure 1 ). The detection rate of SARS-CoV-2 was below 6.7% from November 1st to 21st, 2021, and by the last week of November (22nd to 30th), the detection rate increased steadily up to 47.5% (Figure 1) Figure 3B ). Surveillance in South Africa contributed to generating wholegenome sequences, curation of metadata, and analysis. Florette K.

Treurnicht, Burtram C. Fielding and Kathleen Subramoney were involved with the initial drafting of the manuscript, which was reviewed by all authors.

Centres for Disease Control and Prevention (CDC)

The spike D614G mutation increases SARS-CoV-2 infection of multiple human cell types

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Increased risk of SARS-CoV-2 reinfection associated with emergence of the Omicron variant in South Africa

Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa

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S-gene target failure as a marker of variant B.1.1.7 among SARS-CoV-2 Isolates in the Greater Toronto Area

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Development of new SNP genotyping assays to discriminate the Omicron variant of SARS-CoV-2

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Identification of SARS-CoV-2 Omicron variant using spike gene target failure and genotyping assays, gauteng, South Africa, 2021

The authors declare no conflicts of interest.

Sequence data can be accessed on GISAID (https://www.gisaid. org/) using the accession numbers provided in Table S1 . Additional data (genotyping by polymerase chain reaction) has not been made available apart from the figures and tables included in this paper.

This study has received ethical clearance from the University of the Witwatersrand (Clearance Certificate Number M210119).

http://orcid.org/0000-0001-6037-9890Upasana Ramphal http://orcid.org/0000-0002-2441-3868Burtram C. Fielding http://orcid.org/0000-0002-1873-3363