The mutational landscape of SARS-CoV-2 variants diversifies T cell targets in an HLA-supertype-dependent manner

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Abstract

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  1. SciScore for 10.1101/2021.06.03.446959: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Antibodies
    SentencesResources
    Briefly, HLA molecules were purified from lysates of EBV transformed homozygous cell lines by affinity chromatography by repeated passage over Protein A Sepharose beads conjugated with the W6/32 (anti-HLA-A, -B, -C) antibody, following separation from HLA-B and -C molecules by pre-passage over a B1.23.2 (antiHLA B, C) column.
    anti-HLA-A, -B, -C
    suggested: None
    antiHLA B
    suggested: None
    Software and Algorithms
    SentencesResources
    Following Huddelston et.al. (Huddleston et al., 2020) who used SANTA-SIM to simulate influenza A/H3N2 that has a yearly substitution rate approximately twice as high as SARS-CoV-2 [∼48,824 substitutions/year (https://nextstrain.org/flu/seasonal/h3n2/ha/2y?l=clock) vs. ∼24.5 substitution/year (https://nextstrain.org/ncov/global?l=clock)], we chose 400 generations/year, with the mutation rate per position per generation set to 2.04E-6 (yearly substitution rate/(generations in one year * genome size)).
    SARS-CoV-2
    suggested: (BioLegend Cat# 944703, RRID:AB_2890874)

    Results from OddPub: Thank you for sharing your code.


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    LIMITATIONS AND FUTURE DIRECTIONS: Our analyses focused on class I molecules for which predictors are established to be more accurate in comparison with class II. HLA-C and non-classical HLA were not included in this study. Predictions were performed on the most common HLA class I alleles and rare HLA alleles were not included. Study has been performed using the GISAID dataset available in December 31st 2020, i.e. first year of the pandemic, before mass vaccination. Our epitope binding results rely on in silico predictions using a method that has been widely benchmarked, but is designed to predict peptide presentation rather than immunogenicity. Follow up experiments would need to be performed to further validate the proposed model. Priority follow up studies are 1) to investigate T cell response to SARS-CoV-2 mutants in large cohorts of B7 supertype-positive versus negative patients, and 2) to determine the direct role of APOBEC family proteins in modulation of SARS-CoV-2-specific T cell immunity. Moreover, this study lays the foundation to understand the evolutionary dynamics of pandemic viruses with a time 0 / no vaccine-induced immune pressure start point. Employing SARS-CoV-2 as model provides an opportunity in future studies to look at the dynamic of the relationship between mutational patterns and HLA-restricted T cell immunity in real-time. Kinetic analyses using the latest GISAID datasets, which now include 1.7M SARS-CoV-2 genomes as of May 2021, may lead to addition...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


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