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In Journal of virological methods

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.

Rocca María Florencia, Zintgraff Jonathan Cristian, Dattero María Elena, Santos Leonardo Silva, Ledesma Martín, Vay Carlos, Prieto Mónica, Benedetti Estefanía, Avaro Martín, Russo Mara, Nachtigall Fabiane Manke, Baumeister Elsa


COVID-19, MALDI-TOF, Mass spectrometry, SARS-CoV-2, machine learning