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通过针对反复出现的突变位点的基于唾液的 RT-qPCR 识别 SARS-CoV-2 关注变体。

Identifying SARS-CoV-2 Variants of Concern through Saliva-Based RT-qPCR by Targeting Recurrent Mutation Sites.

机构信息

Center for Innovative Medical Devices and Sensors (REDDI Lab), Clemson Universitygrid.26090.3d, Clemson, South Carolina, USA.

Department of Bioengineering, Clemson Universitygrid.26090.3d, Clemson, South Carolina, USA.

出版信息

Microbiol Spectr. 2022 Jun 29;10(3):e0079722. doi: 10.1128/spectrum.00797-22. Epub 2022 May 12.

Abstract

SARS-CoV-2 variants of concern (VOCs) continue to pose a public health threat which necessitates a real-time monitoring strategy to complement whole genome sequencing. Thus, we investigated the efficacy of competitive probe RT-qPCR assays for six mutation sites identified in SARS-CoV-2 VOCs and, after validating the assays with synthetic RNA, performed these assays on positive saliva samples. When compared with whole genome sequence results, the SΔ69-70 and ORF1aΔ3675-3677 assays demonstrated 93.60 and 68.00% accuracy, respectively. The SNP assays (K417T, E484K, E484Q, L452R) demonstrated 99.20, 96.40, 99.60, and 96.80% accuracies, respectively. Lastly, we screened 345 positive saliva samples from 7 to 22 December 2021 using Omicron-specific mutation assays and were able to quickly identify rapid spread of Omicron in Upstate South Carolina. Our workflow demonstrates a novel approach for low-cost, real-time population screening of VOCs. SARS-CoV-2 variants of concern and their many sublineages can be characterized by mutations present within their genetic sequences. These mutations can provide selective advantages such as increased transmissibility and antibody evasion, which influences public health recommendations such as mask mandates, quarantine requirements, and treatment regimens. Our RT-qPCR workflow allows for strain identification of SARS-CoV-2 positive saliva samples by targeting common mutation sites shared between variants of concern and detecting single nucleotides present at the targeted location. This differential diagnostic system can quickly and effectively identify a wide array of SARS-CoV-2 strains, which can provide more informed public health surveillance strategies in the future.

摘要

SARS-CoV-2 关注变种(VOC)继续构成公共卫生威胁,这需要实时监测策略来补充全基因组测序。因此,我们研究了针对 SARS-CoV-2 VOC 中六个突变位点鉴定的竞争探针 RT-qPCR 检测的功效,并在合成 RNA 上验证了这些检测后,对阳性唾液样本进行了这些检测。与全基因组序列结果相比,SΔ69-70 和 ORF1aΔ3675-3677 检测的准确性分别为 93.60%和 68.00%。SNP 检测(K417T、E484K、E484Q、L452R)的准确性分别为 99.20%、96.40%、99.60%和 96.80%。最后,我们使用针对奥密克戎突变的检测在 2021 年 12 月 7 日至 22 日筛查了 345 份阳性唾液样本,能够快速确定奥密克戎在南卡罗来纳州北部的快速传播。我们的工作流程展示了一种低成本、实时的 VOC 人群筛选的新方法。SARS-CoV-2 关注变种及其许多亚谱系可以通过其遗传序列中的突变来表征。这些突变可以提供选择性优势,例如增加传染性和抗体逃避,这影响了公共卫生建议,如口罩要求、检疫要求和治疗方案。我们的 RT-qPCR 工作流程允许通过针对关注变种之间共享的常见突变位点并检测靶向位置的存在的单个核苷酸来鉴定 SARS-CoV-2 阳性唾液样本的株系。这种差异诊断系统可以快速有效地识别广泛的 SARS-CoV-2 株系,这可以为未来提供更明智的公共卫生监测策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2e33/9241879/6223427683b3/spectrum.00797-22-f001.jpg

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