A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19)

Abstract

Background The Coronavirus Disease 2019 (COVID-19) global pandemic has had a profound, lasting impact on the world's population. A key aspect to providing care for those with COVID-19 and checking its further spread is early and accurate diagnosis of infection, which has been generally done via methods for amplifying and detecting viral RNA molecules. Detection and quantitation of peptides using targeted mass spectrometry-based strategies has been proposed as an alternative diagnostic tool due to direct detection of molecular indicators from non-invasively collected samples as well as the potential for high-throughput analysis in a clinical setting; many studies have revealed the presence of viral peptides within easily accessed patient samples. However, evidence suggests that some viral peptides could serve as better indicators of COVID-19 infection status than others, due to potential misidentification of peptides derived from human host proteins, poor spectral quality, high limits of detection etc. Methods In this study we have compiled a list of 636 peptides identified from Sudden Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) samples, including from in vitro and clinical sources. These datasets were rigorously analyzed using automated, Galaxy-based workflows containing tools such as PepQuery, BLAST-P, and the Multi-omic Visualization Platform as well as the open-source tools MetaTryp and Proteomics Data Viewer (PDV). Results Using PepQuery for confirming peptide spectrum matches, we were able to narrow down the 639-peptide possibilities to 87 peptides that were most robustly detected and specific to the SARS-CoV-2 virus. The specificity of these sequences to coronavirus taxa was confirmed using Unipept and BLAST-P. Through stringent p-value cutoff combined with manual verification of peptide spectrum match quality, 4 peptides derived from the nucleocapsid phosphoprotein and membrane protein were found to be most robustly detected across all cell culture and clinical samples, including those collected non-invasively. Conclusion We propose that these peptides would be of the most value for clinical proteomics applications seeking to detect COVID-19 from patient samples. We also contend that samples harvested from the upper respiratory tract and oral cavity have the highest potential for diagnosis of SARS-CoV-2 infection from easily collected patient samples using mass spectrometry-based proteomics assays.

Use of MALDI-TOF mass spectrometry for virus identification: a review

“…42 Nevertheless, identification based on viral proteins/peptides is promising due to the better chemical stability of proteins than RNA and the lack of a need for PCR amplification. 43 Recently, Rajczewski et al 43 evaluated optimal SARS-CoV-2 peptide targets from a compilation of 636 peptides identified from SARS-CoV-2 samples by MS-based proteomics and selected the 87 most specific peptides that were most robustly detected. Among these 87 peptides, 4 highly confident peptides, MAGNGGDAALALLLLDR, DGIIWVATEGALNTPK, RGPEQTQGNFGDQELIR, and IGMEVTPSGTWLTYTGAIK, which exhibited excellent quality spectra across most of the upper respiratory tract clinical datasets analysed, were selected.…”

Review of Liquid Chromatography-Mass Spectrometry-Based Proteomic Analyses of Body Fluids to Diagnose Infectious Diseases

“…Rajczewski and colleagues thoroughly evaluated 636 viral peptides identified in datasets using Galaxy-based workflows [110]. Galaxy is a web-based platform that provides reproducible computational research and numerous bioinformatics tools.…”

“…Deposited data should be processed in a standard format that can be reused for further analysis. Accumulated datasets should be easily accessible and should be capable of being reanalyzed; this could be achieved by using an improved pipeline or other processes in a high-performance cloud computing environment [110]. These databases should also support other independent research results or benchmarking for new algorithms [110,132,133].…”

“…Accumulated datasets should be easily accessible and should be capable of being reanalyzed; this could be achieved by using an improved pipeline or other processes in a high-performance cloud computing environment [110]. These databases should also support other independent research results or benchmarking for new algorithms [110,132,133]. The integration of proteomic datasets with other omics datasets would expand the scope of our understanding of infectious diseases.…”

Unleashing immuno-mass spectrometry superpowers to detect SARS-CoV-2

“…The most relevant peptides from the SARS-CoV-2 capsid for use as tandem mass spectrometry markers were rapidly reported [4] . The list was further improved by taking into account the numerous SARS-CoV-2 genome sequences produced [5] . Several targeted proteomic approaches were then proposed to identify the main viral components present on nasopharyngeal swabs [6] and in gargle samples [7] .…”