Shotgun proteomics analysis of SARS-CoV-2-infected cells and how it can optimize whole viral particle antigen production for vaccines

Emerg Microbes Infect. 2020 Dec;9(1):1712-1721. doi: 10.1080/22221751.2020.1791737.

Abstract

Severe acute respiratory syndrome-related coronavirus 2 (SARS-CoV-2) has resulted in a pandemic and is continuing to spread rapidly around the globe. No effective vaccine is currently available to prevent COVID-19, and intense efforts are being invested worldwide into vaccine development. In this context, all technology platforms must overcome several challenges resulting from the use of an incompletely characterized new virus. These include finding the right conditions for virus amplification for the development of vaccines based on inactivated or attenuated whole viral particles. Here, we describe a shotgun tandem mass spectrometry workflow, the data produced can be used to guide optimization of the conditions for viral amplification. In parallel, we analysed the changes occurring in the host cell proteome following SARS-CoV-2 infection to glean information on the biological processes modulated by the virus that could be further explored as potential drug targets to deal with the pandemic.

Keywords: COVID-19; SARS-CoV-2; host response; infection kinetics; mass spectrometry; proteomics; vaccine; viral protein detection.

MeSH terms

  • Animals
  • Antigens, Viral / biosynthesis*
  • Antigens, Viral / immunology
  • Betacoronavirus / immunology*
  • Chlorocebus aethiops
  • Proteomics / methods*
  • SARS-CoV-2
  • Tandem Mass Spectrometry
  • Vero Cells
  • Viral Vaccines / immunology*
  • Virion / immunology*

Substances

  • Antigens, Viral
  • Viral Vaccines

Grants and funding

This work was funded in part by the French Alternative Energies and Atomic Energy Commission, and the Agence Nationale de la Recherche (project “Phylopeptidomics”, ANR-17-CE18-0023-01). This publication was supported by the European Virus Archive goes Global (EVAg) project that has received funding from the European Union’s Horizon 2020 research and innovation programme under [grant agreement number 653316]; Agence Nationale de la Recherche; European Commission.