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Authors:Stervbo et al. 

Journal/ Pre-Print:BioRxiv  

Tags: Bioinformatics, Immunology/Immunity 

Research Highlights 

1. Extensive epitope comparison between predicted SARS-CoV-2 and most common pathogens in Europe aiming to explain pre-immunity in T cells.  

2. Hundreds of HLA-I and HLA-II bound epitopes from 2 common CoV (HKU1 and OC43) were found to be similar or identical to SARS-CoV-2.  

3. When allowing some dissimilarity, the highest number of shared epitopes was found for HLA-1 bound epitopes from VZV that related to HLA-B and HLA-C, but not for HLA-II.  

Summary  

Stervbo et al. compared the epitopes for the most common pathogens in Europe to those predicted for SARS-CoV-2. Short epitopes were analysed by Levenshtein distance that accounts for addition, deletion and exchange of amino acidsIdentical HLA-I and HLA-II bound epitopes were found for common CoV HKU1 and OC43. When allowing some dissimilarity, VZV appeared to have the most similar epitope profile for HLA-I, followed by OC43 and HKU1, with more than thousand similar epitopes. This in silico study provides valuable information to further evaluate in vitro or in vivo the existence of a pre-existing immunity for SARS-CoV-2. 

Impact for SARS-CoV2/COVID19 research efforts  

Understand the immune response to SARS-CoV2/COVID19:  Important identification of possible epitopes that may cause pre-existing immunity to SARS-CoV-2. 

Study Type  

  • In silico study / bioinformatics study 

Strengths and limitations of the paper 

Novelty: Extensive epitope comparison for common pathogens and SARS-CoV-2 predicted epitopes 

Standing in the field: In line with other studies published (p.e. Kiyotani K, Toyoshima Y, Nemoto K, Nakamura Y. Bioinformatic prediction of potential T cell epitopes for SARS-Cov-2. J Hum Genet. 2020;65(7):569-575. doi:10.1038/s10038-020-0771-5) but to our knowledge the only comprehensive epitope comparison with many other pathogenic agents. The current discussion in the literature is about whether or not the T cell cross-reactivity from other CoV may influence the SARS-CoV-2 immune response.  

Appropriate statistics: Not familiar with, but protocol for analysis was extensively described. 

Viral model used: none; Protein sequences only. 

The SARS-CoV2 protein sequences were downloaded from ViralZone (33; https://viralzone.expasy.org/89966), accessed May 29, 2020.  

The protein reference sequences for the coronaviruses OC43, HKU1, 229E, and NL63, and Influenza B, Human Gammaherpesvirus 4, Rotavirus A, and Human alphaherpesvirus 3, were downloaded from https://ftp.ncbi.nlm.nih.gov/refseq/release/viral on 26 Jun 2020.  

Translatability: This paper dose not focus on therapeutics 

Main limitations:  

  • The title is overinterpreting the results 

  • The study does not prove that any of the peptides found can cross-react in vitro or in vivo  

  • The study is Eurocentric, focuses on more common European HLA and pathogens found in Europe.  

  • HLA-II prediction is poorer than HLA-I 

  • Results need to be examined with further experiments and clinical data.  

Despite these limitations, the study is an important first approach to understand where a pre-existing immunity to SARS-CoV-2 may come from.