Download PDF
CC BY-NC-ND 4.0 · J Lab Physicians 2020; 12(02): 154-160
DOI: 10.1055/s-0040-1715790
Original Article

Mutations in SARS-CoV-2 Leading to Antigenic Variations in Spike Protein: A Challenge in Vaccine Development

Praveen Kumar Singh
2   Department of Microbiology, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
,
Umay Kulsum
2   Department of Microbiology, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
,
Syed Beenish Rufai
3   Infectious Diseases and Immunity in Global Health Program, Research Institute of the McGill University Health Center, and McGill International TB Center, Montreal, Quebec, Canada
,
S. Rashmi Mudliar
2   Department of Microbiology, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh, India
,
Sarman Singh 
1   Molecular Medicine Laboratory, Department of Microbiology, All India Institute of Medical Sciences, Bhopal, Madhya Pradesh India
› Author Affiliations Funding None.
› Further Information
Also available at
   Permissions and Reprints

Abstract

Objectives The spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) virus has been unprecedentedly fast, spreading to more than 180 countries within 3 months with variable severity. One of the major reasons attributed to this variation is genetic mutation. Therefore, we aimed to predict the mutations in the spike protein (S) of the SARS-CoV-2 genomes available worldwide and analyze its impact on the antigenicity.

Materials and Methods Several research groups have generated whole genome sequencing data which are available in the public repositories. A total of 1,604 spike proteins were extracted from 1,325 complete genome and 279 partial spike coding sequences of SARS-CoV-2 available in NCBI till May 1, 2020 and subjected to multiple sequence alignment to find the mutations corresponding to the reported single nucleotide polymorphisms (SNPs) in the genomic study. Further, the antigenicity of the predicted mutations inferred, and the epitopes were superimposed on the structure of the spike protein.

Results The sequence analysis resulted in high SNPs frequency. The significant variations in the predicted epitopes showing high antigenicity were A348V, V367F and A419S in receptor binding domain (RBD). Other mutations observed within RBD exhibiting low antigenicity were T323I, A344S, R408I, G476S, V483A, H519Q, A520S, A522S and K529E. The RBD T323I, A344S, V367F, A419S, A522S and K529E are novel mutations reported first time in this study. Moreover, A930V and D936Y mutations were observed in the heptad repeat domain and one mutation D1168H was noted in heptad repeat domain 2.

Conclusion S protein is the major target for vaccine development, but several mutations were predicted in the antigenic epitopes of S protein across all genomes available globally. The emergence of various mutations within a short period might result in the conformational changes of the protein structure, which suggests that developing a universal vaccine may be a challenging task.

Keywords

SARS-CoV-2 - spike protein - mutations - epitopes - antigenicity


Publication History

Article published online:
01 September 2020

© .

Thieme Medical and Scientific Publishers Private Ltd.
A-12, Second Floor, Sector -2, NOIDA -201301, India

 

  • References

  • 1 Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis 2020; 20 (05) 533-534
    CrossrefPubMedGoogle Scholar
  • 2 Tu YF, Chien CS, Yarmishyn AA. et al. A review of SARS-CoV-2 and the ongoing clinical trials. Int J Mol Sci 2020; 21 (07) 2657
    CrossrefPubMedGoogle Scholar
  • 3 Khailany RA, Safdar M, Ozaslan M. Genomic characterization of a novel SARS-CoV-2. Gene Rep 2020; 19: 100682
    CrossrefPubMedGoogle Scholar
  • 4 Schoeman D, Fielding BC. Coronavirus envelope protein: current knowledge. Virol J 2019; 16 (01) 69
    CrossrefPubMedGoogle Scholar
  • 5 Wrapp D, Wang N, Corbett KS. et al. Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation. Science 2020; 367 (6483) 1260-1263
    CrossrefPubMedGoogle Scholar
  • 6 Shang J, Wan Y, Liu C. et al. Structure of mouse coronavirus spike protein complexed with receptor reveals mechanism for viral entry. PLoS Pathog 2020; 16 (03) e1008392
    CrossrefPubMedGoogle Scholar
  • 7 Pachetti M, Marini B, Benedetti F. et al. Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant. J Transl Med 2020; 18 (01) 179
    CrossrefPubMedGoogle Scholar
  • 8 Ahmed SF, Quadeer AA, McKay MR. Preliminary identification of potential vaccine targets for the COVID-19 coronavirus (SARS-CoV-2) based on SARS-CoV immunological studies. Viruses 2020; 12 (03) 254
    CrossrefPubMedGoogle Scholar
  • 9 Baud D, Qi X, Nielsen-Saines K, Musso D, Pomar L, Favre G. Real estimates of mortality following COVID-19 infection. Lancet Infect Dis 2020; 20 (07) 773
    CrossrefPubMedGoogle Scholar
  • 10 Yi CE, Ba L, Zhang L, Ho DD, Chen Z. Single amino acid substitutions in the severe acute respiratory syndrome coronavirus spike glycoprotein determine viral entry and immunogenicity of a major neutralizing domain. J Virol 2005; 79 (18) 11638-11646
    CrossrefPubMedGoogle Scholar
  • 11 Li KB. ClustalW-MPI: ClustalW analysis using distributed and parallel computing. Bioinformatics 2003; 19 (12) 1585-1586
    CrossrefPubMedGoogle Scholar
  • 12 Waterhouse AM, Procter JB, Martin DMA, Clamp M, Barton GJ. Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics 2009; 25 (09) 1189-1191
    CrossrefPubMedGoogle Scholar
  • 13 Stamatakis A. RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models. Bioinformatics 2006; 22 (21) 2688-2690
    CrossrefPubMedGoogle Scholar
  • 14 Letunic I, Bork P. Interactive Tree of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res 2019; 47 (W1) W256-W259
    CrossrefPubMedGoogle Scholar
  • 15 Rice P, Longden I, Bleasby A. EMBOSS: the European Molecular Biology Open Software Suite. Trends Genet 2000; 16 (06) 276-277
    CrossrefPubMedGoogle Scholar
  • 16 Kolaskar AS, Tongaonkar PC. A semi-empirical method for prediction of antigenic determinants on protein antigens. FEBS Lett 1990; 276 (1-2) 172-174
    CrossrefPubMedGoogle Scholar
  • 17 Parker JM, Guo D, Hodges RS. New hydrophilicity scale derived from high-performance liquid chromatography peptide retention data: correlation of predicted surface residues with antigenicity and X-ray-derived accessible sites. Biochemistry 1986; 25 (19) 5425-5432
    CrossrefPubMedGoogle Scholar
  • 18 Barile E, Baggio C, Gambini L, Shiryaev SA, Strongin AY, Pellecchia M. Potential therapeutic targeting of coronavirus spike glycoprotein priming. Molecules 2020; 25 (10) e2424
    CrossrefPubMedGoogle Scholar
  • 19 Becerra-Flores M, Cardozo T. SARS-CoV-2 viral spike G614 mutation exhibits higher case fatality rate. Int J Clin Pract 2020; DOI: 10.1111/ijcp.13525. [epub ahead of print]
    CrossrefPubMedGoogle Scholar
  • 20 Andersen KG, Rambaut A, Lipkin WI, Holmes EC, Garry RF. The proximal origin of SARS-CoV-2. Nat Med 2020; 26 (04) 450-452
    CrossrefPubMedGoogle Scholar
  • 21 Duffy S. Why are RNA virus mutation rates so damn high?. PLoS Biol 2018; 16 (08) e3000003
    CrossrefPubMedGoogle Scholar
  • 22 Zhou HX, Pang X. Electrostatic interactions in protein structure, folding, binding, and condensation. Chem Rev 2018; 118 (04) 1691-1741
    CrossrefPubMedGoogle Scholar
  • 23 Lokman SM, Rasheduzzaman M, Salauddin A. et al. Exploring the genomic and proteomic variations of SARS-CoV-2 spike glycoprotein: a computational biology approach. Infect Genet Evol 2020; 84: 104389
    CrossrefPubMedGoogle Scholar
  • 24 Huzurbazar S, Kolesov G, Massey SE, Harris KC, Churbanov A, Liberles DA. Lineage-specific differences in the amino acid substitution process. J Mol Biol 2010; 396 (05) 1410-1421
    CrossrefPubMedGoogle Scholar
  • 25 Liu S, Xiao G, Chen Y. et al. Interaction between heptad repeat 1 and 2 regions in spike protein of SARS-associated coronavirus: implications for virus fusogenic mechanism and identification of fusion inhibitors. Lancet 2004; 363 (9413) 938-947
    CrossrefPubMedGoogle Scholar
  • 26 Walls AC, Tortorici MA, Snijder J. et al. Tectonic conformational changes of a coronavirus spike glycoprotein promote membrane fusion. Proc Natl Acad Sci U S A 2017; 114 (42) 11157-11162
    CrossrefPubMedGoogle Scholar
  • 27 Eckert DM, Kim PS. Mechanisms of viral membrane fusion and its inhibition. Annu Rev Biochem 2001; 70: 777-810
    CrossrefPubMedGoogle Scholar
  • 28 Bosch BJ, Rossen JWA, Bartelink W. et al. Coronavirus escape from heptad repeat 2 (HR2)-derived peptide entry inhibition as a result of mutations in the HR1 domain of the spike fusion protein. J Virol 2008; 82 (05) 2580-2585
    CrossrefPubMedGoogle Scholar
  • 29 Yuan M, Wu NC, Zhu X. et al. A highly conserved cryptic epitope in the receptor binding domains of SARS-CoV-2 and SARS-CoV. Science 2020; 368 (6491) 630-633
    CrossrefPubMedGoogle Scholar