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通过结合新型 PCR 检测和基因组测序快速检测和监测 SARS-CoV-2 B.1.1.7 变异株,精准应对变异株的兴起。

Precision Response to the Rise of the SARS-CoV-2 B.1.1.7 Variant of Concern by Combining Novel PCR Assays and Genome Sequencing for Rapid Variant Detection and Surveillance.

机构信息

Alberta Precision Laboratories, Public Health Laboratory, Edmonton, Alberta, Canada.

Department of Laboratory Medicine and Pathology, University of Albertagrid.17089.37, Edmonton, Alberta, Canada.

出版信息

Microbiol Spectr. 2021 Sep 3;9(1):e0031521. doi: 10.1128/Spectrum.00315-21. Epub 2021 Aug 11.

Abstract

SARS-CoV-2 variants of concern (VOCs) have emerged as a global threat to the COVID-19 pandemic response. We implemented a combined approach to quickly detect known VOCs while continuously monitoring for evolving mutations of the virus. To rapidly detect VOCs, two real-time reverse transcriptase PCR assays were designed and implemented, targeting the spike gene H69/V70 deletion and the N501Y mutation. The H69/V70 deletion and N501Y mutation assays demonstrated accuracies of 98.3% (95% CI 93.8 to 99.8) and 100% (95% CI 96.8 to 100), limits of detection of 1,089 and 294 copies/ml, and percent coefficients of variation of 0.08 to 1.16% and 0 to 2.72% for the two gene targets, respectively. No cross-reactivity with common respiratory pathogens was observed with either assay. Implementation of these tests allowed the swift escalation in testing for VOCs from 2.2% to ∼100% of all SARS-CoV-2-positive samples over 12 January to 9 February 2021, and resulted in the detection of a rapid rise of B.1.1.7 cases within the province of Alberta, Canada. A prospective comparison of the VOC assays to genome sequencing for the detection of B.1.1.7, combined detection of P.1 and B.1.351, and wild-type (i.e., non-VOC) lineages showed sensitivities of 98.2 to 100%, specificities of 98.9 to 100%, positive predictive values of 76.9% to 100%, and negative predictive values of 96 to 100%. Variant screening results inform sampling strategies for regular surveillance by genome sequencing, thus allowing rapid identification of known VOCs while continuously monitoring the evolution of SARS-CoV-2 in the province. Different strains, or variants, of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, the virus that causes COVID-19) have emerged that have higher levels of transmission, less susceptibility to our immune response, and possibly cause more severe disease than previous strains of the virus. Rapid detection of these variants of concern is important to help contain them and prevent them from spreading widely within the population. This study describes two newly developed tests that are able to identify and differentiate the variants of concern from regular strains of SARS-CoV-2. These tests are faster and simpler than the main, gold standard method of identifying variants of concern (genome sequencing). These tests also demonstrated a high correlation with genome sequencing and allowed for the rapid and accurate detection of the rise of B.1.1.7 (one of the variants of concern) in the province of Alberta, Canada.

摘要

SARS-CoV-2 变体(VOC)已成为 COVID-19 大流行应对的全球威胁。我们采取了综合方法,快速检测已知的 VOC,同时持续监测病毒的进化突变。为了快速检测 VOC,我们设计并实施了两种实时逆转录酶 PCR 检测方法,针对刺突基因 H69/V70 缺失和 N501Y 突变。H69/V70 缺失和 N501Y 突变检测的准确率分别为 98.3%(95%置信区间 93.8 至 99.8)和 100%(95%置信区间 96.8 至 100),检测限为 1089 和 294 拷贝/ml,两个基因靶标分别为 0.08%至 1.16%和 0 至 2.72%。两种检测方法均未观察到与常见呼吸道病原体的交叉反应。从 2021 年 1 月 12 日至 2 月 9 日,对这两种检测方法的实施使对 VOC 的检测迅速从 2.2%增加到所有 SARS-CoV-2 阳性样本的约 100%,并导致在加拿大阿尔伯塔省快速检测到 B.1.1.7 病例。对 VOC 检测与基因组测序检测 B.1.1.7、P.1 和 B.1.351 的联合检测以及野生型(即非 VOC)谱系的前瞻性比较显示,敏感性为 98.2%至 100%,特异性为 98.9%至 100%,阳性预测值为 76.9%至 100%,阴性预测值为 96%至 100%。变体筛查结果为通过基因组测序进行常规监测提供了采样策略,从而能够快速识别已知的 VOC,同时持续监测该省 SARS-CoV-2 的演变。不同的严重急性呼吸综合征冠状病毒 2(SARS-CoV-2,引起 COVID-19 的病毒)株或变体已经出现,其传播性更高,对我们的免疫反应的敏感性更低,并且可能比以前的病毒株导致更严重的疾病。快速检测这些关注的变体对于帮助控制它们并防止它们在人群中广泛传播很重要。本研究描述了两种新开发的能够识别和区分关注变体与常规 SARS-CoV-2 株的检测方法。这些检测方法比识别关注变体的主要、黄金标准方法(基因组测序)更快、更简单。这些检测方法还与基因组测序具有高度相关性,并允许在加拿大阿尔伯塔省快速准确地检测到 B.1.1.7(一种关注变体)的上升。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a54c/8552604/eb12a864aee4/spectrum.00315-21-f001.jpg

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