Rapid and sensitive detection of SARS-CoV-2 infection using quantitative peptide enrichment LC-MS analysis.
Rapid and sensitive detection of SARS-CoV-2 infection using quantitative peptide enrichment LC-MS analysis.
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DOI：
10.7554/elife.70843
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发表时间：
2021-11-08
期刊：
影响因子：
7.7
通讯作者：
Edfors F
中科院分区：
文献类型：
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作者：
Hober A;Tran-Minh KH;Foley D;McDonald T;Vissers JP;Pattison R;Ferries S;Hermansson S;Betner I;Uhlén M;Razavi M;Yip R;Pope ME;Pearson TW;Andersson LN;Bartlett A;Calton L;Alm JJ;Engstrand L;Edfors F
对严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)进行可靠、可靠和大规模的分子检测对于监测正在进行的2019年冠状病毒病(新冠肺炎)大流行至关重要。我们开发了一种基于多肽免疫亲和富集法和液相色谱-质谱法(LC-MS)相结合的可扩展的分析方法来检测病毒蛋白。这是一种基于靶向蛋白质组学分析和LC-MS读出的多重策略，能够准确地定量和确认咽喉/鼻咽/唾液联合样本的磷酸盐缓冲盐水(PBS)拭子中SARS-CoV-2的存在。结果表明，LC-MS检测的SARS-CoV-2水平与其相应的实时聚合酶链式反应(RT-PCR)读数具有良好的相关性(r=0.79)。分析工作流程显示的周转时间与常规RT-PCR仪器相似，定量读出的病毒蛋白对应于21至34个周期阈值(Ct)当量。以反转录-聚合酶链式反应为参照，我们证明了基于LC-MS的方法在质谱仪(CT≤30)的检测范围内分析无症状个体的临床样品时，具有100%的阴性符合率(估计的特异度)和95%的阳性符合率(估计的灵敏度)。这些结果表明，基于LC-MS的可扩展分析方法在未来的大流行预防中心有一席之地，以补充当前的病毒检测技术。
Reliable, robust, large-scale molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for monitoring the ongoing coronavirus disease 2019 (COVID-19) pandemic. We have developed a scalable analytical approach to detect viral proteins based on peptide immuno-affinity enrichment combined with liquid chromatography-mass spectrometry (LC-MS). This is a multiplexed strategy, based on targeted proteomics analysis and read-out by LC-MS, capable of precisely quantifying and confirming the presence of SARS-CoV-2 in phosphate-buffered saline (PBS) swab media from combined throat/nasopharynx/saliva samples. The results reveal that the levels of SARS-CoV-2 measured by LC-MS correlate well with their correspondingreal-time polymerase chain reaction (RT-PCR) read-out (r = 0.79). The analytical workflow shows similar turnaround times as regular RT-PCR instrumentation with a quantitative read-out of viral proteins corresponding to cycle thresholds (Ct) equivalents ranging from 21 to 34. Using RT-PCR as a reference, we demonstrate that the LC-MS-based method has 100% negative percent agreement (estimated specificity) and 95% positive percent agreement (estimated sensitivity) when analyzing clinical samples collected from asymptomatic individuals with a Ct within the limit of detection of the mass spectrometer (Ct ≤ 30). These results suggest that a scalable analytical method based on LC-MS has a place in future pandemic preparedness centers to complement current virus detection technologies.