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一种稳健、高通量的质谱分析方法,用于鉴定 SARS-CoV-2 变体。

A Robust, Highly Multiplexed Mass Spectrometry Assay to Identify SARS-CoV-2 Variants.

机构信息

Department of Pathology, Molecular, and Cell-Based Medicine, Icahn School of Medicine at Mount Sinaigrid.59734.3c, New York, New York, USA.

Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinaigrid.59734.3c, New York, New York, USA.

出版信息

Microbiol Spectr. 2022 Oct 26;10(5):e0173622. doi: 10.1128/spectrum.01736-22. Epub 2022 Sep 7.

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants are characterized by differences in transmissibility and response to therapeutics. Therefore, discriminating among them is vital for surveillance, infection prevention, and patient care. While whole-genome sequencing (WGS) is the "gold standard" for variant identification, molecular variant panels have become increasingly available. Most, however, are based on limited targets and have not undergone comprehensive evaluation. We assessed the diagnostic performance of the highly multiplexed Agena MassARRAY SARS-CoV-2 Variant Panel v3 to identify variants in a diverse set of 391 SARS-CoV-2 clinical RNA specimens collected across our health systems in New York City, USA and Bogotá, Colombia (September 2, 2020 to March 2, 2022). We demonstrated almost perfect levels of interrater agreement between this assay and WGS for 9 of 11 variant calls (κ ≥ 0.856) and 25 of 30 targets (κ ≥ 0.820) tested on the panel. The assay had a high diagnostic sensitivity (≥93.67%) for contemporary variants (e.g., Iota, Alpha, Delta, and Omicron [BA.1 sublineage]) and a high diagnostic specificity for all 11 variants (≥96.15%) and all 30 targets (≥94.34%) tested. Moreover, we highlighted distinct target patterns that could be utilized to identify variants not yet defined on the panel, including the Omicron BA.2 and other sublineages. These findings exemplified the power of highly multiplexed diagnostic panels to accurately call variants and the potential for target result signatures to elucidate new ones. The continued circulation of SARS-CoV-2 amid limited surveillance efforts and inconsistent vaccination of populations has resulted in the emergence of variants that uniquely impact public health systems. Thus, in conjunction with functional and clinical studies, continuous detection and identification are quintessential to informing diagnostic and public health measures. Furthermore, until WGS becomes more accessible in the clinical microbiology laboratory, the ideal assay for identifying variants must be robust, provide high resolution, and be adaptable to the evolving nature of viruses like SARS-CoV-2. Here, we highlighted the diagnostic capabilities of a highly multiplexed commercial assay to identify diverse SARS-CoV-2 lineages that circulated from September 2, 2020 to March 2, 2022 among patients seeking care in our health systems. This assay demonstrated variant-specific signatures of nucleotide/amino acid polymorphisms and underscored its utility for the detection of contemporary and emerging SARS-CoV-2 variants of concern.

摘要

严重急性呼吸系统综合症冠状病毒 2 型(SARS-CoV-2)变体的特征在于其传播能力和对治疗药物的反应有所不同。因此,对它们进行区分对于监测、感染预防和患者护理至关重要。虽然全基因组测序(WGS)是变体识别的“金标准”,但分子变体面板已经越来越普及。然而,大多数基于有限的目标,并且尚未经过全面评估。我们评估了高度多重化的 Agena MassARRAY SARS-CoV-2 变体面板 v3 的诊断性能,以鉴定来自我们在美国纽约市和哥伦比亚波哥大的医疗系统收集的 391 个 SARS-CoV-2 临床 RNA 标本中的变体。我们证明了该检测方法与 WGS 在 11 个变体呼叫中的 9 个(κ≥0.856)和 30 个目标中的 25 个(κ≥0.820)的检测结果具有近乎完美的一致性。该检测方法对当前变体(例如 Iota、Alpha、Delta 和 Omicron [BA.1 亚谱系])的诊断敏感性较高(≥93.67%),对所有 11 个变体(≥96.15%)和所有 30 个目标(≥94.34%)的诊断特异性较高。此外,我们强调了可以用于识别面板上尚未定义的变体的独特目标模式,包括 Omicron BA.2 和其他亚谱系。这些发现说明了高度多重化诊断面板准确呼叫变体的能力,以及目标结果特征可以阐明新变体的潜力。在有限的监测工作和人群接种疫苗不一致的情况下,SARS-CoV-2 的持续传播导致了对公共卫生系统产生独特影响的变体的出现。因此,结合功能和临床研究,连续检测和识别对于告知诊断和公共卫生措施至关重要。此外,在临床微生物学实验室中 WGS 变得更加普及之前,用于识别变体的理想检测方法必须具有稳健性、提供高分辨率,并且能够适应 SARS-CoV-2 等病毒的不断变化的性质。在这里,我们强调了一种高度多重化商业检测方法的诊断能力,该方法可识别 2020 年 9 月 2 日至 2022 年 3 月 2 日期间在我们的医疗系统中寻求护理的患者中传播的多种 SARS-CoV-2 谱系。该检测方法展示了核苷酸/氨基酸多态性的变体特异性特征,并强调了其用于检测当代和新兴 SARS-CoV-2 变体的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b224/9604185/f4b6971c2c24/spectrum.01736-22-f001.jpg

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