Shortlisting SARS‐CoV‐2 peptides for targeted studies from experimental data‐dependent acquisition tandem mass spectrometry data

Duarte Gouveia (1, 2, 3) , Lucia Grenga (1, 2, 3) , Jean‐charles Gaillard (1, 2, 3) , Fabrice Gallais (1, 2, 3) , Laurent Bellanger (1, 2, 3) , Olivier Pible (1, 2, 3) , J. Armengaud (1, 2, 3)

1 MTS - Médicaments et Technologies pour la Santé
2 SPI - Service de Pharmacologie et Immunoanalyse
3 LI2D - Laboratoire Innovations technologiques pour la Détection et le Diagnostic

Detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a crucial tool for fighting the COVID-19 pandemic. This dataset brief presents the exploration of a shotgun proteomics dataset acquired on SARS-CoV-2 infected Vero cells. Proteins from inactivated virus samples were extracted, digested with trypsin, and the resulting peptides were identified by data-dependent acquisition tandem mass spectrometry. The 101 peptides reporting for six viral proteins were specifically analyzed in terms of their analytical characteristics, species specificity and conservation, and their proneness to structural modifications. Based on these results, a shortlist of 14 peptides from the N, S, and M main structural proteins that could be used for targeted mass-spectrometry method development and diagnostic of the new SARS-CoV-2 is proposed and the best candidates are commented.

Mots clés: COVID-19; mass spectrometry; peptides; proteomics; SARS-CoV-2; viral protein detection

Domaines: Biochimie, Biologie Moléculaire

Duarte Gouveia, Lucia Grenga, Jean‐charles Gaillard, Fabrice Gallais, Laurent Bellanger, et al.. Shortlisting SARS‐CoV‐2 peptides for targeted studies from experimental data‐dependent acquisition tandem mass spectrometry data. Proteomics, 2020, 20 (14), pp.2000107. ⟨10.1002/pmic.202000107⟩. ⟨hal-03349684⟩