MALDI-TOF mass spectrometry of saliva samples as a prognostic tool for COVID-19

The SARS-CoV-2 infections are still imposing a great public health challenge despite the recent developments in vaccines and therapy. Searching for diagnostic and prognostic methods that are fast, low-cost and accurate is essential for disease control and patient recovery. The MALDI-TOF mass spectrometry technique is rapid, low cost and accurate when compared to other MS methods, thus its use is already reported in the literature for various applications, including microorganism identification, diagnosis and prognosis of diseases. Here we developed a prognostic method for COVID-19 using the proteomic profile of saliva samples submitted to MALDI-TOF and machine learning algorithms to train models for COVID-19 severity assessment. We achieved an accuracy of 88.5%, specificity of 85% and sensitivity of 91.5% for classification between mild/moderate and severe conditions. Then, we tested the model performance in an independent dataset, we achieved an accuracy, sensitivity and specificity of 67.18, 52.17 and 75.60% respectively. Saliva is already reported to have high inter-sample variation; however, our results demonstrates that this approach has the potential to be a prognostic method for COVID-19. Additionally, the technology used is already available in several clinics, facilitating the implementation of the method. Further investigation using a bigger dataset is necessary to consolidate the technique.

Protein arginylation is regulated during SARS-CoV-2 infection

In 2019, the world witnessed the onset of an unprecedented pandemic. In September 2021, the infection by SARS-CoV-2 had already been responsible for the death of more than 4 million people worldwide. Recently, we and other groups discovered that SARS-CoV-2 infection induces ER-stress and activation of unfolded protein response (UPR) pathway. The degradation of misfolded/unfolded proteins is an essential element of proteostasis and occurs mainly in lysosomes or proteasomes. The N-terminal arginylation of proteins is characterized as an inducer of ubiquitination and proteasomal degradation by the N-end rule pathway. Here we present, for the first time, data on the role of arginylation during SARS-CoV-2 infection. We studied the modulation of protein arginylation in Vero CCL-81 and Calu-3 cells infected after 2h, 6h, 12h, 24h, and 48h. A reanalysis of in vivo and in vitro public omics data combined with immunoblotting was performed to measure the levels of ATE1 and arginylated proteins. This regulation is seen specifically during infections by coronaviruses. We demonstrate that during SARS-CoV-2 infection there is an increase in the expression of the ATE1 enzyme associated with regulated levels of specific arginylated proteins. On the other hand, infected macrophages showed no ATE1 regulation. An important finding revealed that modulation of the N-end rule pathway differs between different types of infected cells. We also confirmed the potential of tannic acid to reduce viral load, and furthermore, to modulate ATE1 levels during infection. In addition, the arginylation inhibitor merbromin (MER) is also capable of both reducing viral load and reducing ATE1 levels. Taken together, these data show the importance of arginylation during the progression of SARS-CoV-2 infection and open the door for future studies that may unravel the role of ATE1 and its inhibitors in pathogen infection.

SARS-CoV-2 activates ER stress and Unfolded protein response

Coronavirus disease-2019 (COVID-19) pandemic caused by the SARS-CoV-2 coronavirus infection is a major global public health concern affecting millions of people worldwide. The scientific community has joint efforts to provide effective and rapid solutions to this disease. Knowing the molecular, transmission and clinical features of this disease is of paramount importance to develop effective therapeutic and diagnostic tools. Here, we provide evidence that SARS-CoV-2 hijacks the glycosylation biosynthetic, ER-stress and UPR machineries for viral replication using a time-resolved (0-48 hours post infection, hpi) total, membrane as well as glycoproteome mapping and orthogonal validation. We found that SARS-CoV-2 induces ER stress and UPR is observed in Vero and Calu-3 cell lines with activation of the PERK-eIF2-ATF4-CHOP signaling pathway. ER-associated protein upregulation was detected in lung biopsies of COVID-19 patients and associated with survival. At later time points, cell death mechanisms are triggered. The data show that ER stress and UPR pathways are required for SARS-CoV-2 infection, therefore representing a potential target to develop/implement anti-CoVID-19 drugs.

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

PurposeSARS-CoV-2 infection poses a global public health problem. There is a critical need for improvements in the noninvasive prognosis of COVID-19. We hypothesized that matrix-assisted laser desorption ionization mass spectrometry (MALDI-TOF MS) analysis combined with bottom-up proteomic analysis of plasma proteins might identify features to predict high and low risk cases of COVID-19. Patients and MethodsWe used MALDI-TOF MS to analyze plasma small proteins and peptides isolated using C18 micro-columns from a cohort containing a total of 117 cases of high (hospitalized) and low risk (outpatients) cases split into training (n = 88) and validation sets (n= 29). The plasma protein/peptide fingerprint obtained was used to train the algorithm before validation using a blinded test cohort. ResultsSeveral sample preparation, MS and data analysis parameters were optimized to achieve an overall accuracy of 85%, sensitivity of 90%, and specificity of 81% in the training set. In the blinded test set, this signature reached an overall accuracy of 93.1%, sensitivity of 87.5%, and specificity of 100%. From this signature, we identified two distinct regions in the MALDI-TOF profile belonging to the same proteoforms. A combination of 1D 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. Conclusions: We found a plasma proteomic profile that discriminates against patients with high and low risk COVID-19. Proteomic analysis of C18-fractionated plasma may have a role in the noninvasive prognosis of COVID-19. Further validation will consolidate its clinical utility. Key messageO_ST_ABSWhat is the key question?C_ST_ABSDo individuals infected with SARS-CoV-2 harboring different degree of disease severity have a plasma protein profile that differentiate them and predict the COVID-19 outcome? What is the bottom line?In a series of 117 patients with COVID-19 divided in hospitalized (60) and outpatients (57), differential expression of serum amyloid A-1 (SAA1) and A-2 (SAA2) predict their outcome. Why read on?The high mortality rate in SARS-CoV-2 infected individuals requires accurate markers for predicting COVID-19 severity. Plasma levels of SAA1 and SAA2 indicate higher risk of hospitalization and can be used to improve COVID-19 monitoring and therapy.