# Proteomics analysis of Gargling samples from CoviD-19 infected patients
# Live Resources
Ihling et al present a protein MS-based ‘proof-of-principle’ method to detect SARS-CoV-2 virus proteins from gargle samples from COVID-19 patients. Their protocol consists of an acetone precipitation step, followed by tryptic digestion of gargle solution proteins, followed by MS analysis. In the original manuscript, the authors detect peptides from SARS-CoV-2 virus proteins and present evidence for their spectral annotation. This study is an initiative in developing a routine MS-based diagnostic method for COVID-19 patients.
The Galaxy workflow includes RAW data conversion to MGF and mzML format. The MGF files are searched against the combined database of Human Uniprot proteome, contaminant proteins and SARS-Cov-2 proteins database using X!tandem, MSGF+, OMSSA search algorithms with SearchGUI and FDR and protein grouping using PeptideShaker. This resulted in detection of nine peptides from SARS-CoV-2 proteins.
The detected peptides were searched against NCBInr to ascertain that these peptides were specific to SARS-CoV-2 proteins. Also, the detected peptides were subjected to analysis by PepQuery and Lorikeet to ascertain the quality of peptide identification.
The database search workflow yielded us 8 COV-2 peptides from the second and third raw files.
When we performed the validation search using PepQuery it gave us 21 COV-2 peptides. We also checked the Lorikeet spectra of these peptides. Here are some examples of the Lorikeet spectra using the Multiomics visualization tool in the Galaxy platform.