Instituto Nacional de Enfermedades Infecciosas (INEI) - Administración Nacional de Laboratorios e Institutos de Salud (ANLIS) "Dr. Carlos G. Malbrán", Ciudad Autónoma de Buenos Aires, Argentina; Red Nacional de Espectrometría de Masas aplicada a la Microbiología Clínica (ReNaEM Argentina), Argentina.
Instituto Nacional de Enfermedades Infecciosas (INEI) - Administración Nacional de Laboratorios e Institutos de Salud (ANLIS) "Dr. Carlos G. Malbrán", Ciudad Autónoma de Buenos Aires, Argentina; Red Nacional de Espectrometría de Masas aplicada a la Microbiología Clínica (ReNaEM Argentina), Argentina.
J Virol Methods. 2020 Dec;286:113991. doi: 10.1016/j.jviromet.2020.113991. Epub 2020 Oct 9.
Coronavirus disease 2019, known as COVID-19, is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The early, sensitive and specific detection of SARS-CoV-2 virus is widely recognized as the critical point in responding to the ongoing outbreak. Currently, the diagnosis is based on molecular real time RT-PCR techniques, although their implementation is being threatened due to the extraordinary demand for supplies worldwide. That is why the development of alternative and / or complementary tests becomes so relevant. Here, we exploit the potential of mass spectrometry technology combined with machine learning algorithms, for the detection of COVID-19 positive and negative protein profiles directly from nasopharyngeal swabs samples. According to the preliminary results obtained, accuracy = 67.66 %, sensitivity = 61.76 %, specificity = 71.72 %, and although these parameters still need to be improved to be used as a screening technique, mass spectrometry-based methods coupled with multivariate analysis showed that it is an interesting tool that deserves to be explored as a complementary diagnostic approach due to the low cost and fast performance. However, further steps, such as the analysis of a large number of samples, should be taken in consideration to determine the applicability of the method developed.
新型冠状病毒病(COVID-19),又称 2019 冠状病毒病,是由严重急性呼吸系统综合征冠状病毒 2(SARS-CoV-2)引起的。早期、敏感且特异性地检测 SARS-CoV-2 病毒被广泛认为是应对当前疫情的关键。目前,诊断主要基于分子实时 RT-PCR 技术,尽管由于全球对供应品的巨大需求,其实施受到了威胁。这就是为什么开发替代和/或补充测试变得如此相关的原因。在这里,我们利用质谱技术与机器学习算法相结合的潜力,直接从鼻咽拭子样本中检测 COVID-19 阳性和阴性的蛋白质谱。根据初步获得的结果,准确性为 67.66%,灵敏度为 61.76%,特异性为 71.72%,尽管这些参数仍需要进一步改进,以用作筛选技术,但基于质谱的方法与多元分析相结合表明,这是一种很有前途的工具,值得作为一种补充诊断方法进行探索,因为它具有成本低、速度快的特点。然而,为了确定所开发方法的适用性,应该考虑采取进一步的步骤,例如分析大量样本。