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Authors: Lucia Grenga, Fabrice Gallais, Olivier Pible, Jean-Charles Gaillard, Duarte Gouveia, Helene Batina, Niza Bazaline, Sylvie Ruat, Karen Culotta, Guylaine Miotello, Stephanie Debroas, Marie-Anne Roncato, Gerard Steinmetz, Charlotte Foissard, Anne Desplan, Beatrice Alpha-Bazin, Christine Almunia, Fabienne Gas, Laurent Bellanger, Jean Armengaud

Link to paper:

Journal/ Pre-Print: Preprint (Biorxiv)

Key Words: Proteomics; mass spectrometry; vaccine production

Research Highlights 

1. Infection of vero cells with SARS-CoV-2 at two multiplicities (MOI 0.01 and 0.001) of infection and harvesting at day 1,2,3,4 and 7. Label-free LC-MS of viral and host proteins, as well as RNA detection using standard WHO IP2/IP4 primers. The overall objective was to establish an LC-MS workflow to guide optimisation of conditions for whole viral particle antigen production for vaccine development.

2. 3 structural and 3 non-structural proteins were identified; covered with 40 (N), 29 (S), 7 (M), 13 (ORF1ab), 4 (ORF3a), and 1 (ORF7a) distinct peptides. At all time points N, S and M were the most abundant, peaking at 3-4 days post infection, and their relative abundances remained constant. Protein detection closely mirrored viral count detected by qPCR.

3. The authors found that the host proteome underwent substnail remodelling, and identified a number of clusters of co-expressed proteins with different putative functions, including RNA-modifiers (particular spliceosome components), protein processing in the endoplasmatic reticulum and vacuole formation.


The authors demonstrate detection of both SARS-CoV-2 and host proteins by LC-MS in an in vitro model of infection involving Vero cells (a primate kidney epithelial-derived cell line). They detect six viral proteins (three structural, three non-structural), with peak detection 3-4 days post-infection. Protein abundance correlated with RNA-based viral count, with no obvious change in the ratios of viral proteins over time. The paper also describe clusters of host proteins with differential abundance after infection. The authors suggest their workflow may be used for optimization of high-quality antigen production for virus research and manufacture, though they do not demonstrate this.

Impact for SARS-CoV2/COVID19 research efforts

Understand the immune response to SARS-CoV2/COVID19

Understand the virology and/or cell biology of SARS-CoV2/COVID19

Develop a vaccine for SARS-CoV2/COVID19

Study Type

· In vitro study

Strengths and limitations of the paper

Novelty: Demonstrates the detection of SARS-CoV-2 proteins by LC-MS in an in vitro model of infection involving Vero cells. Demonstrates that the viral proteins increase up to day 3, that their ratios remain the same, and that they correlate with RNA levels.

Standing in the field: Reasonable. There is limited discussion of why haven’t they detected E, and one would have expected N to be higher earlier.

Appropriate statistics: Unclear whether replicates were tested. Labelling may have provided more accurate quantitation, and even without labelling they should have included a standard/control for quantitation.

Viral model used: The SARS-CoV-2 strains 2019-nCoV/Italy-INMI1 (Genbank MT066156) was provided by the Lazzaro Spallanzani National Institute of Infectious Diseases (Rome, Italy) via the EVAg network (European Virus Archive goes global).

Translatability: Contributes towards vaccine development; however this is a long way off from translatability to bedside.

Main limitations: Vero cells rather than lung epithelial cells; replicates; quantitative