Identification of conserved epitopes in SARS-CoV-2 spike and nucleocapsid protein

  1. Sergio Forcelloni
  2. Anna Benedetti
  3. Maddalena Dilucca
  4. Andrea Giansanti

Reviewed by

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which first occurred in Wuhan (China) in December 2019, is a novel virus that causes a severe acute respiratory disease. The virus spike glycoproteins and nucleocapsid proteins are the main targets for the development of vaccines and antiviral drugs, to control the disease spread. We herein study the structural order-disorder propensity and the rates of evolution of these two proteins to characterize their B cell and T cell epitopes, previously suggested to contribute to immune response caused by SARS-CoV-2 infections. We first analyzed the rates of evolution along the sequences of spike and nucleocapsid proteins in relation to the spatial locations of their epitopes. For this purpose, we compared orthologs from seven human coronaviruses: SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-229E, HCoV-OC43, HCoV-NL63, and HCoV-HKU1. We then focus on the local, structural order-disorder propensities of the protein regions where the SARS-CoV-2 epitopes are located. We show that the vast majority of nucleocapsid protein epitopes overlap the RNA-binding and dimerization domains and some of them are characterized by low rates of evolutions. Similarly, spike protein epitopes are preferentially located in regions that are predicted to be ordered and well-conserved, in correspondence of the heptad repeats 1 and 2. Interestingly, both the receptor-binding motif to ACE2 and the fusion peptide of spike protein are characterized by high rates of evolution, probably to overcome host immunity. In conclusion, our results provide evidence for conserved epitopes that may help to develop long-lasting, broad-spectrum SARS-CoV-2 vaccines.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.14.095133: (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
    We downloaded the coding sequences of these coronaviruses from the National Center for Biotechnological Information (NCBI) (available at https://www.ncbi.nlm.nih.gov/).
    https://www.ncbi.nlm.nih.gov/
    suggested: (GENSAT at NCBI - Gene Expression Nervous System Atlas, RRID:SCR_003923)
    2.2 Sequence alignment: To explore the evolutionary relationships among the proteins N and S in the seven human coronaviruses here considered, the selected protein sequences were aligned by using Clustal Omega (https://www.ebi.ac.uk/Tools/msa/clustalo/
    Clustal Omega
    suggested: (Clustal Omega, RRID:SCR_001591)

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    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.

    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.

  2. Version published to 10.1101/2020.05.14.095133 on bioRxiv