Objectives

To evaluate a testing algorithm for the rapid identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants that includes the use of PCR-based targeted single nucleotide polymorphism (SNP) detection assays preceded by a multiplex PCR sensitive to S-Gene Target Failure (SGTF).

Methods

PCR SNP assays targeting SARS-CoV-2 S-gene mutations ΔH69–V70, L452R, E484K, N501Y, H655Y and P681R using melting curve analysis were performed on 567 samples in which SARS-CoV-2 viral RNA was detected by a multiplex PCR. Viral whole-genome sequencing (WGS) was performed to confirm the presence of SNPs and to identify the Pangolin lineage. Additionally, 1133 SARS-CoV-2 positive samples with SGTF were further assessed by WGS to determine the presence of ΔH69–V70.

Results

The N501Y-specific assay (n = 567) had an overall percentage agreement (OPA) of 98.5%. The ΔH69-V70-specific (n = 178) and E484K-specific (n = 401) assays had OPA of 96.6% and 99.7%, respectively. Assessment of H655Y (n = 139) yielded a 100.0% concordance when applied in the proposed algorithm. The L452R-specific (n = 67) and P681R-specific (n = 62) assays had an OPA of 98.2% and 98.1%, respectively. The proposed algorithm identified six variants of concern/interest (VOC/VOI)—Alpha (n = 149), Beta (n = 65), Gamma (n = 86), Delta (n = 49), Eta (n = 6), Kappa (n = 6)—and 205 non-VOC/VOI strains—including the variants under monitoring B.1.214.2 (n = 43) and B.1.1.318 (n = 18) and Epsilon (n = 1). An excellent concordance was observed for the identification of all SARS-CoV-2 lineages evaluated.

Conclusions

We present a flexible testing algorithm for the rapid detection of current and emerging SARS-CoV-2 VOC/VOIs, which can be easily adapted based on the local endemicity of specific variants.

中文翻译：

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监测 SARS-CoV-2 大流行：采用单核苷酸多态性检测的筛选算法，用于快速识别已建立的和新出现的变异

目标

评估快速识别严重急性呼吸综合征冠状病毒 2 (SARS-CoV-2) 变体的测试算法，包括使用基于 PCR 的靶向单核苷酸多态性 (SNP) 检测分析，然后进行对 S 敏感的多重PCR -基因靶标失败（SGTF）。

方法

使用熔解曲线分析对 567 个样本进行针对 SARS-CoV-2 S基因突变 ΔH69–V70、L452R、E484K、N501Y、H655Y 和 P681R的 PCR SNP测定，其中通过多重 PCR 检测到 SARS-CoV-2 病毒 RNA 。进行病毒全基因组测序 (WGS) 以确认 SNP 的存在并鉴定穿山甲谱系。此外，还通过 WGS 进一步评估了 1133 个带有 SGTF 的 SARS-CoV-2 阳性样本，以确定是否存在 ΔH69-V70。

结果

N501Y 特异性检测 ( n =  567) 的总体一致性百分比 (OPA) 为 98.5%。ΔH69-V70 特异性 ( n =  178) 和 E484K 特异性 ( n =  401) 检测的 OPA 分别为 96.6% 和 99.7%。 当应用于所提出的算法时，H655Y ( n = 139) 的评估得出了 100.0% 的一致性。L452R 特异性 ( n =  67) 和 P681R 特异性 ( n =  62) 检测的 OPA 分别为 98.2% 和 98.1%。所提出的算法确定了关注/兴趣的六种变体（VOC/VOI）——Alpha（n =  149）、Beta（n =  65）、Gamma（n =  86）、Delta（n =  49）、Eta（n =  6） 、Kappa ( n =  6) 和 205 个非 VOC/VOI 菌株 - 包括监测下的变体 B.1.214.2 ( n =  43) 和 B.1.1.318 ( n =  18) 以及 Epsilon ( n =  1) 。所有评估的 SARS-CoV-2 谱系的鉴定都观察到了极好的一致性。

结论

我们提出了一种灵活的测试算法，用于快速检测当前和新兴的 SARS-CoV-2 VOC/VOI，该算法可以根据特定变体的当地流行情况轻松进行调整。