Mass spectrometry applied to diagnosis, prognosis, and therapeutic targets identification for the novel coronavirus SARS-CoV-2: A review

Abstract

Mass spectrometry (MS) has found numerous applications in medicine and has been widely used in the detection and characterization of biomolecules associated with viral infections such as COVID-19. COVID-19 is a multisystem disease and, therefore, the need arises to carry out a careful and conclusive assessment of the pathophysiological parameters involved in the infection, to develop an effective therapeutic approach, assess the prognosis of the disease, and especially the early diagnosis of the infected population. Thus, the urgent need for highly accurate methods of diagnosis and prognosis of this infection presents new challenges for the development of laboratory medicine, whose methods require sensitivity, speed, and accuracy of the techniques for analyzing the biological markers involved in the infection. In this context, MS stands out as a robust analytical tool, with high sensitivity and selectivity, accuracy, low turnaround time, and versatility for the analysis of biological samples. However, it has not yet been adopted as a frontline clinical laboratory technique. Therefore, this review explores the potential and trends of current MS methods and their contribution to the development of new strategies to COVID-19 diagnosis and prognosis and how this tool can assist in the discovery of new therapeutic targets, in addition, to comment what could be the future of MS in medicine.

Keywords: COVID-19; Diagnosis; Mass spectrometry; Prognosis; SARS-CoV-2; Therapeutic targets.

Graphical abstract

Fig. 1

Mind map on MS-based “omics” workflow, applications and possibilities.

Fig. 2

Graphical flowchart of MS potentialities to elucidate key clinical challenges on diagnosis, prognosis and therapeutic targets.

Fig. 3

A statistical overview of the main courses of action and scientific targets of COVID-19 related studies using MS (dark-red shades representing mostly diagnosis and prognosis approaches; light-red shades representing exclusively therapeutic target assignments). Statistics was calculated based on the total of publications. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4

MS-based multi-omics universal workflow to study new alternatives for COVID-19 diagnosis. Source: Mahmud & Garrett 2020 [30].

Fig. 5

Identification and relative quantification of urine samples from COVID-19 patients and healthy controls. The graphics present the accumulation curve of the quantified proteins from (A) 32 healthy volunteers, (B) 6 COVID-19 patients and (C) 2 recovered patients. The Venn diagram (D) shows the identified urine proteins from the healthy volunteers, COVID-19 patients and recovered patients. The graphic (E) presents the dynamic range of the absolute quantitative information (iBAQ) of identified proteins from healthy volunteers, COVID-19 patients and recovered patients [31].

Fig. 6

Schematic representation of sample pre-treatment based on paper spray mass spectrometry (PS-MS) on a Teslin® substrate. Source: adapted from Silva et al. (2020) [58].

Fig. 7

Lipid profile changes in exosomes for different degree of severities of COVID-19 patients. Blue (≥2 fold) and red (<2 fold) dots indicate dramatic change in lipids. Source: adapted from Song et al. (2020) [59]. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 8

Total ion chromatograms of Qingfei Paidu decoction: (A) ESI negative mode, (B) ESI positive mode and, on the right, the number of chemical constituents of each herb and representative constituent structures identified from Qingfei Paidu decoction. Source: Adapted from Yang et al. (2020) [85].