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. 2021 Sep;21(17-18):e2100036.
doi: 10.1002/pmic.202100036. Epub 2021 Apr 14.

Resourcing, annotating, and analysing synthetic peptides of SARS-CoV-2 for immunopeptidomics and other immunological studies

Chen Li  1 , Jerico Revote  2 , Sri H Ramarathinam  1 , Shan Zou Chung  1 , Nathan P Croft  1 , Katherine E Scull  1 , Ziyi Huang  1 , Rochelle Ayala  1 , Asolina Braun  1 , Nicole A Mifsud  1 , Patricia T Illing  1 , Pouya Faridi  1 , Anthony W Purcell  1
Affiliations

Resourcing, annotating, and analysing synthetic peptides of SARS-CoV-2 for immunopeptidomics and other immunological studies

Chen Li et al. Proteomics. 2021 Sep.

Abstract

SARS-CoV-2 has caused a significant ongoing pandemic worldwide. A number of studies have examined the T cell mediated immune responses against SARS-CoV-2, identifying potential T cell epitopes derived from the SARS-CoV-2 proteome. Such studies will aid in identifying targets for vaccination and immune monitoring. In this study, we applied tandem mass spectrometry and proteomic techniques to a library of ∼40,000 synthetic peptides, in order to generate a large dataset of SARS-CoV-2 derived peptide MS/MS spectra. On this basis, we built an online knowledgebase, termed virusMS (https://virusms.erc.monash.edu/), to document, annotate and analyse these synthetic peptides and their spectral information. VirusMS incorporates a user-friendly interface to facilitate searching, browsing and downloading the database content. Detailed annotations of the peptides, including experimental information, peptide modifications, predicted peptide-HLA (human leukocyte antigen) binding affinities, and peptide MS/MS spectral data, are provided in virusMS.

Keywords: COVID19; LC-MS; SARS-CoV-2; database; synthetic peptides; tandem mass spectrometry.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

FIGURE 1
FIGURE 1
A graphical illustration demonstrating (A) the process SARS‐CoV‐2 synthetic peptide dataset generation and (B) the construction of virusMS database
FIGURE 2
FIGURE 2
A schematic illustration of the functionalities in virusMS, including (A) database keyword search, (B) peptide‐HLA binding prediction summary, (C) database browsing, (D) detailed presentation of peptide information, and (E) bulk and customisable download from virusMS
FIGURE 3
FIGURE 3
Extracting all peptides of an experiment documented in virusMS. (A) Browsing all experiments documented in virusMS. (B) Extracting all peptides by clicking the experiment ID
FIGURE 4
FIGURE 4
Searching virusMS using a variety of keywords, including (A) peptide sequence, (B) peptide source protein, (C) peptide modification, and (D) peptide‐HLA binding prediction
FIGURE 5
FIGURE 5
A graphical illustration for the detailed information of a peptide presented in virusMS, including (A) peptide basic information (experimental information and cross‐references), (B) prediction affinities of the peptide binding to 12 HLA class I supertype representatives, and (C) the spectral data of the peptide using the Lorikeet plug‐in
FIGURE 6
FIGURE 6
Bulk and customisable download from virusMS. Users can either (A) download the search results by selecting peptides of interests, or (B) download the information of a specific peptide on the detailed information page. The downloaded file is in TSV format and can be opened by any text editor or Microsoft Excel (C). The “Instruction” webpage provides fouroptions for downloading the entire database (D), including the database SQL file, data tables, peptide spectral data and peptide‐HLA‐I binding predictions
See this image and copyright information in PMC

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