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Prognostic accuracy of MALDI-TOF mass spectrometric analysis of plasma in COVID-19.

ABSTRACT: SARS-CoV-2 infection poses a global health crisis. In parallel with the ongoing world effort to identify therapeutic solutions, there is a critical need for improvement in the prognosis of COVID-19. Here, we report plasma proteome fingerprinting that predict high (hospitalized) and low-risk (outpatients) cases of COVID-19 identified by a platform that combines machine learning with matrix-assisted laser desorption ionization mass spectrometry analysis. Sample preparation, MS, and data analysis parameters were optimized to achieve an overall accuracy of 92%, sensitivity of 93%, and specificity of 92% in dataset without feature selection. We identified two distinct regions in the MALDI-TOF profile belonging to the same proteoforms. A combination of SDS-PAGE and quantitative bottom-up proteomic analysis allowed the identification of intact and truncated forms of serum amyloid A-1 and A-2 proteins, both already described as biomarkers for viral infections in the acute phase. Unbiased discrimination of high- and low-risk COVID-19 patients using a technology that is currently in clinical use may have a prompt application in the noninvasive prognosis of COVID-19. Further validation will consolidate its clinical utility.

SUBMITTER: Lazari LC

PROVIDER: S-EPMC8321665 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:A method of analysis is presented that utilizes matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) to monitor the kinetics and products of RNA cleavage, by use of a program designed to mass-match observed MS peaks with predicted RNA cleavage products. The method is illustrated through application to the study of targeted oxidation of RNA stem loops from HIV-1 Rev Response Element mRNA (RRE RNA) and ribosomal 16S A-site RNA (16S RNA) by metallonucleases. Following incubation of each RNA with catalysts and/or redox co-reactants, reaction mixtures were desalted, and MALDI-TOF MS was used to monitor both time-resolved formation of cleavage products and disappearance of full-length RNA. For each RNA, a unique list was generated that contained the predicted masses of both the full-length, and all of the possible RNA cleavage fragments that resulted from the combination of all possible cleavage sites and each of the six expected overhangs formed at nascent termini adjacent to the cleavage sites. The overhangs corresponded to 2',3'-cyclic phosphate, 3'-phosphate, 3'-phosphoglycolate, 5'- hydroxyl and 5'- phosphate, which corresponded to differing oxidative, hydrolytic, and/or 2'-OH-mediated-endonucleolytic modes of scission. Each mass spectrum was compared with a corresponding list of predicted masses, and peaks were rapidly assigned by use of a Perl script, with a mass-matching tolerance of 200 ppm. Both time-dependent cleavage mediated by metallonucleases and MALDI-TOF-induced fragmentation were observed, and these were distinguished by time-dependent experiments. The resulting data allowed a semi-quantitative assessment of the rate of formation of each overhang at each nucleotide position. Limitations included artifactual skewing of quantification by mass bias, a limited mass range for quantification, and a lack of detection of secondary cleavage products. Nevertheless, the method presented herein provides a rapid, accurate, highly-detailed and semi-quantitative analysis of RNA cleavage that should be widely applicable.

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Prognostic accuracy of MALDI-TOF mass spectrometric analysis of plasma in COVID-19.

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