SARS-CoV-2 transcriptome analysis and molecular cataloguing of immunodominant epitopes for multi-epitope based vaccine design

  1. Sandeep Kumar Kushwaha
  2. Veerbhan Kesarwani
  3. Samraggi Choudhury
  4. Sonu Gandhi
  5. Shailesh Sharma

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Abstract

SARS-CoV-2 is a single-stranded RNA virus that has caused more than 0.29 million deaths worldwide as of May 2020, and influence of COVID-19 pandemic is increasing continuously in the absence of approved vaccine and drug. Moreover, very limited information is available about SARS-CoV-2 expressed regions and immune responses. In this paper an effort has been made, to facilitate vaccine development by proposing multiple epitopes as potential vaccine candidates by utilising SARS-CoV-2 transcriptome data. Here, publicly available RNA-seq data of SARS-CoV-2 infection in NHBE and A549 human cell lines were used to construct SARS-CoV-2 transcriptome to understand disease pathogenesis and immune responses. In the first step, epitope prediction, MHC class I and II gene identification for epitopes, population coverage, antigenicity, immunogenicity, conservation and crossreactivity analysis with host antigens were performed by using SARS-CoV-2 transcriptome, and in the second step, structural compatibility of identified T-and B-cell epitopes were evaluated with MHC molecules and B-cell receptors through molecular docking studies. Quantification of MHC gene expression was also performed that indicated high variation in allele types and expression level of MHC genes with respect to cell lines. In A549 cell line, HLA-A*30:01:01:01 and HLA-B*44:03:01:01 were highly expressed, whereas 92 variants of HLA-A*24 genes such as HLA-A*24:02:01:01, HLA-A*24:286, HLA-A*24:479Q, HLA-A*24:02:134 and HLA-A*24:02:116 were highly expressed in NHBE cell lines. Prevalence of HLA-A*24 alleles was suggested as risk factors for H1N1 infection, and associated with type-1 diabetes. HLA-C*03:03, linked with male infertility factors was also highly expressed in SARS-CoV-2 infected NHBE cell lines. Finally, three potential T-cell and five B-cell epitopes were selected for molecular docking studies with twenty-two MHC molecules and two B-cell receptors respectively. The results of in silico analysis indicated that proposed epitopes have high potential to recognize immune response of SARS-CoV-2 infection. This study will facilitate in vitro and in vivo vaccine related research studies.

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    SciScore for 10.1101/2020.05.14.097170: (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

    Experimental Models: Cell Lines
    SentencesResources
    We used publicly available transcriptome data (PRJNA615032) of SARS-CoV-2 infection in A549 and NHBE cell lines [13].
    A549
    suggested: NCI-DTP Cat# A549, RRID:CVCL_0023)
    Software and Algorithms
    SentencesResources
    All the available data were download from the sequence read archive of NCBI database and fastq-dump program of SRAtoolkit [14] was used to extract fastq reads.
    NCBI
    suggested: (NCBI, RRID:SCR_006472)
    Quality assessment and control of RNA-seq data was performed through the FastQC version 0.11.5 [15], MultiQC version 1.8 [16] and trimmomatic version 0.39 software [17].
    FastQC
    suggested: (FastQC, RRID:SCR_014583)
    MultiQC
    suggested: (MultiQC, RRID:SCR_014982)
    trimmomatic
    suggested: (Trimmomatic, RRID:SCR_011848)
    All high-quality reads were mapped over SARS-CoV-2 isolate Wuhan-Hu-1(MN908947.3) by using HISAT2 version 2.1.0 on default parameters [18].
    HISAT2
    suggested: (HISAT2, RRID:SCR_015530)
    Samtools version 1.1.0 [19] and Bedtools version 2.26.0 [20] were used to extract all the mapped read from each sample and extracted reads were used to construct de novo assemblies by using the Trinity assembler version 2.5.1 [21].
    Samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    Bedtools
    suggested: (BEDTools, RRID:SCR_006646)
    Trinity
    suggested: (Trinity, RRID:SCR_013048)
    TransDecoder program [22] was used to generate protein sequence from assembled transcriptome.
    TransDecoder
    suggested: (TransDecoder, RRID:SCR_017647)
    Therefore, selected epitopes were checked for similarities with the human proteome sequences (Homo sapiens: GRCh38) through standalone NCBI BLAST similarity search tool. 2.3.
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)
    In the sequence based approach, VaxiJen server was used to identify most antigenic proteins from translated transcriptome, and BepiPred-2.0 program [29] was used to identify B-cell epitopes from the identified antigenic proteins.
    VaxiJen
    suggested: (VaxiJen, RRID:SCR_018514)
    To identify the interactions between predicted T- and B-cell epitopes and protein receptors, the molecular docking studies were performed using AutoDockTools, AutoDock Vina and CABS-dock server [31–33].
    AutoDockTools
    suggested: None
    Therefore, initial screening of peptides for receptors were performed through Autodock, whereas CABSdocks, considered full flexibility of peptide and small fluctuation in receptor backbone, was used for final binding and compatibility analysis.
    Autodock
    suggested: (AutoDock, RRID:SCR_012746)

    Results from OddPub: Thank you for sharing your data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Genetic diversity of MHC molecules across the various ethnic groups worldwide is another the major limitation such as different MHC class alleles form different geographical region might be presented by a particular set of epitopes only. To understand demographic coverage of epitopes, population coverage analysis was performed through selected T-cell epitopes, and analysis revealed that approximately 89.44% and 93% average coverage can be achieved for world population and population of ethnic groups respectively (Figure-2, Supplementary file1: Table – S3). In various B-cell research studies, particular antigen induces distinct class or subclass of antibodies such as schistosomiasis and filariasis induced a mixed response of IgE and IgG [57, 58]. In order to select distinct class of epitopes, sequence and structure-based dual approaches were used to identify B-cell epitope by using BepiPred-2.0 and ElliPro programs. 14 non-toxic, non cross-reactive, antigenic, and immunogenic B-cell epitopes were identified of different length (Table – 4). Predicted epitopes may or may not be a key feature of proteins because prediction methods, ignored epitope and receptor interaction, may be predicted only putative epitopes, which might lead to produce an antibody of no use. The real epitopes cannot be identified without considering the structural compatibility of complex formation [41]. Therefore, it became important to determine the structural coordinates of peptide-binding pockets to iden...

    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.
    • No funding statement was detected.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.05.14.097170 on bioRxiv