Does immune recognition of SARS-CoV2 epitopes vary between different ethnic groups?

  1. Tungadri Bose
  2. Namrata Pant
  3. Nishal Kumar Pinna
  4. Subhrajit Bhar
  5. Anirban Dutta
  6. Sharmila S. Mande

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Abstract

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  1. Version published to 10.1016/j.virusres.2021.198579
  2. ScreenIT

    SciScore for 10.1101/2021.05.24.21257707: (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

    Software and Algorithms
    SentencesResources
    While the phyloseq package (from R version 3.6) was used to calculate diversity, the ggplot2 package in R version 3.6 was used for the visualization.
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    The hclust package in R version 3.6 was used for this purpose.
    hclust
    suggested: (HCLUST, RRID:SCR_009154)
    The DescTools package in R version 3.6 was used for this purpose.
    DescTools
    suggested: None
    Epitope Variations Among SARS-CoV2 Genomes: Nextstrain/augur pipeline (accessed on 21st April, 2020 from https://github.com/nextstrain/ncov) was used to align 40342 SARS-CoV2 genome sequences downloaded from GISAID using Wuhan-Hu-1/2019, as a reference sequence using MAFFT (Katoh and Standley, 2013).
    Nextstrain/augur
    suggested: None
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Consequently, some of the earlier studies associate with in silico identification of SARS-CoV2 epitopes (Abdelmageed et al., 2020; Dong et al., 2020; Lin et al., 2020; Naz et al., 2020; TOPUZOĞULLARI et al., 2020) are likely to have suffered from the mentioned limitations associated with these tools (Jespersen et al., 2017; Paul et al., 2016; Saha and Raghava, 2004; Zhang et al., 2009). In other words, these studies might not have arrived at a list of epitopes as comprehensive as the one mentioned in the current study. Further, studies following a combinatorial approach (H.-Z. Chen et al., 2020; Zaheer et al., 2020) are also expected to miss some of the epitopes reported in this study. It may however be noted that like most previous studies, the current study refrained from predicting potential B-cell epitopes, due to the computational complexities involved in the process and may be considered a limitation of this exercise. Most B-cell epitopes are conformational in nature and comprise of discontinuous amino acid stretches which are difficult to be identified (with adequate confidence) from genomic information alone (Wang et al., 2011). A total of 276 CD8 (involving 108 MHC class-I alleles) and 50 CD4 (involving 22 MHC class-II alleles) SARS-CoV2 epitopes were predicted in the current study. The highest number of SARS-CoV2 epitopes were presented by the MHC class-I associated HLA alleles HLA-A*02:11, HLA.A*26:02, HLA.B*15:17, HLA.A*24:03, HLA.B*35.41, and MHC class-II associa...

    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.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2021.05.24.21257707v1 on medRxiv