RR:C19 Evidence Scale rating by reviewer:
Reliable. The main study claims are generally justified by its methods and data. The results and conclusions are likely to be similar to the hypothetical ideal study. There are some minor caveats or limitations, but they would/do not change the major claims of the study. The study provides sufficient strength of evidence on its own that its main claims should be considered actionable, with some room for future revision.
***************************************
Review:
The manuscript by Mirshra et al reports a large peptide microarray to map the antibody response (IgM and IgG) at two different time points (10-13 and 24-35 days days post infection) across three SARS CoV-2 patient groups: sever disease, mild disease, asymptomatic in comparison to healthy patient or patient exposed to other coronaviruses.
The results corroborate earlier findings in terms of immune reactive peptides (1-5).
Claims are very generally supported by the data and the method is robust however, the extrapolation of the microarray data to another analytical format (ELISA, RIA, lateral flow,…) for diagnostics and other public health applications remains to be demonstration. The list of linear epitopes is actionable without reservation for further assay development.
1. C. M. Poh, G. Carissimo, B. Wang. et al. Two linear epitopes on the SARS-CoV-2 spike protein that elicit neutralising antibodies in COVID-19 patients. Nat Commun 11, 2806 (2020).
2. L Farrera, J.-P. Daguer, S. Barluenga, et al. Identification of immunodominant linear epitopes from SARS-CoV-2 patient plasma. medRxiv 2020.06.15.20131391
3. Y. Li, M. Ma, Q. Lei et al. Linear epitope landscape of SARS-CoV-2 Spike protein constructed from 1,051 COVID-19 patients medRxiv 2020.07.13.20152587.
4. H. Wang, X. Hou, X. Wu, et al. SARS-CoV-2 proteome microarray for mapping COVID-19 antibody interactions at amino acid resolution bioRxiv 2020.03.26.994756
5. B.-Z. Zhang, Y.-F. Hu, L.-L. Chen et al. Mapping the Immunodominance Landscape of SARS-CoV-2 Spike Protein for the Design of Vaccines against COVID-19. bioRxiv 2020.04.23.056853