Short Communication
The worldwide search for the new mutations in the RNA-directed RNA Polymerase domain of SARS-CoV-2
Siarhei A. Dabravolski * ,
Yury K. Kavalionak

Mac Vet Rev 2021; 44 (1): 87 - 94

10.2478/macvetrev-2020-0036

Received: 24 June 2020

Received in revised form: 01 October 2020

Accepted: 12 November 2020

Available Online First: 31 December 2020

Published on: 15 March 2021

Correspondence: Siarhei A. Dabravolski, sergedobrowolski@gmail.com
PDF HTML

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is an RNA virus, responsible for the current pandemic outbreak. In total, 200 genomes of the SARS‐CoV‐2 strains from four host organisms have been analyzed. To investigate the presence of the new mutations in the RNA-directed RNA Polymerase (RdRp) of SARS-CoV-2, we analyzed sequences isolated from different hosts, with particular emphasis on human isolates. We performed a search for the new mutations of the RdRp proteins and study how those newly identified mutations could influence RdRp protein stability. Our results revealed 25 mutations in Rhinolophus sinicus, 1 in Mustela lutreola, 6 in Homo sapiens, and none in Mus musculus RdRp proteins of the SARS-CoV-2 isolates. We found that P323L is the most common stabilising radical mutation in human isolates. Also, we described several unique mutations, specific for studied hosts. Therefore, our data suggest that new and emerging variants of the SARS-CoV-2 RdRp have to be considered for the development of effective therapeutic agents and treatments.

Keywords: SARS-CoV-2, mutation, RNA-dependent, RNA polymerases, RdRp, Nsp12

References

  1. Wu, Z., Yang, L., Ren, X., He, G., Zhang, J., Yang, J., Qian, Z., et al. (2016). Deciphering the bat virome catalog to better understand the ecological diversity of bat viruses and the bat origin of emerging infectious diseases. ISME J. 10(3): 609-620. https://doi.org/10.1038/ismej.2015.138 PMid:26262818 PMCid:PMC4817686
  2. Huang, J., Song, W., Huang, H., Sun, Q. (2020). Pharmacological therapeutics targeting RNA-dependent RNA polymerase, proteinase and spike protein: from mechanistic studies to clinical trials for COVID-19. J Clin Med. 9(4): 1131. https://doi.org/10.3390/jcm9041131 PMid:32326602 PMCid:PMC7231166
  3. Ge, X.Y., Li, J.L., Yang, X.L., Chmura, A.A., Zhu, G., Epstein, J.H., Mazet, J.K., et al. (2013). Isolation and characterization of a bat SARS-like coronavirus that uses the ACE2 receptor. Nature 503(7477): 535-538. https://doi.org/10.1038/nature12711 PMid:24172901 PMCid:PMC5389864
  4. Oreshkova, N., Molenaar, R.J., Vreman, S., Harders, F., Munnink, B.B.O., Hakze, R., Gerhards, N., et al. (2020). SARS-CoV2 infection in farmed mink, Netherlands, April 2020 [Internet]. Microbiology; 2020 May [cited 2020 May 23]. Available from: http://biorxiv.org/lookup/doi/10.1101/2020.05.18.101493 https://doi.org/10.1101/2020.05.18.101493
  5. Gretebeck, L.M., Subbarao, K. (2015). Animal models for SARS and MERS coronaviruses. Curr Opin Virol. 13, 123-129. https://doi.org/10.1016/j.coviro.2015.06.009 PMid:26184451 PMCid:PMC4550498
  6. Dabravolski, S. (2020). The worldwide search for the new mutations in the RNA-directed RNA polymerase domain of SARS-CoV-2 [Supplementary data and figures]. Available at: https://osf.io/xtz6a/. https://doi.org/10.17605/OSF.IO/XTZ6A
  7. Edgar, R.C. (2004). Muscle: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5, 113. https://doi.org/10.1186/1471-2105-5-113 PMid:15318951 PMCid:PMC517706
  8. Okonechnikov, K., Golosova, O., Fursov, M. (2012). Unipro UGENE: a unified bioinformatics toolkit. Bioinformatics 28(8): 1166-1167. https://doi.org/10.1093/bioinformatics/bts091 PMid:22368248
  9. Buchan, D.W.A., Jones, D.T. (2019). The PSIPRED protein analysis workbench: 20 years on. Nucleic Acids Res. 47(W1): W402-W407. https://doi.org/10.1093/nar/gkz297 PMid:31251384 PMCid:PMC6602445
  10. Laimer, J., Hiebl-Flach, J., Lengauer, D., Lackner, P. (2016). MAESTRO web: a web server for structure-based protein stability prediction. Bioinformatics 32(9): 1414-1416. https://doi.org/10.1093/bioinformatics/btv769 PMid:26743508
  11. Rodrigues, C.H.M., Pires, D.E.V., Ascher, D.B. (2018). DynaMut: predicting the impact of mutations on protein conformation, flexibility and stability. Nucleic Acids Res. 46(W1): W350-W355. https://doi.org/10.1093/nar/gky300 PMid:29718330 PMCid:PMC6031064
  12. Pires, D.E.V., Ascher, D.B., Blundell, T.L. (2014). DUET: a server for predicting effects of mutations on protein stability using an integrated computational approach. Nucleic Acids Res. 42(W1):W314-W319. https://doi.org/10.1093/nar/gku411 PMid:24829462 PMCid:PMC4086143
  13. Duffy, S. (2018). Why are RNA virus mutation rates so damn high? PLOS Biol. 16(8): e3000003. https://doi.org/10.1371/journal.pbio.3000003 PMid:30102691 PMCid:PMC6107253
  14. Smith, E.C., Denison, M.R. (2013). Coronaviruses as DNA wannabes: a new model for the regulation of RNA virus replication fidelity. PLoS Pathog. 9(12): e1003760. https://doi.org/10.1371/journal.ppat.1003760 PMid:24348241 PMCid:PMC3857799
  15. Irwin, K.K., Renzette, N., Kowalik, T.F., Jensen, J.D. (2015). Antiviral drug resistance as an adaptive process. Virus Evol. 2(1): vew014. https://doi.org/10.1093/ve/vew014 PMid:28694997 PMCid:PMC5499642
  16. Frappier, V., Chartier, M., Najmanovich, R.J. (2015). ENCoM server: exploring protein conformational space and the effect of mutations on protein function and stability. Nucleic Acids Res. 43(W1): W395-400. https://doi.org/10.1093/nar/gkv343 PMid:25883149 PMCid:PMC4489264
  17. Bao, L., Deng, W., Huang, B., Gao, H., Liu, J., Ren, L., Wei, Q., et al. (2020). The pathogenicity of SARS-CoV-2 in hACE2 transgenic mice. Nature 583(7818): 830-833. https://doi.org/10.1038/s41586-020-2312-y PMid:32380511
  18. Zhou, P., Yang, X.L., Wang, X.G., Hu, B., Zhang, L., Zhang, W., Si, H.R., et al. (2020). A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature 579(7798): 270-273.
  19. Sexton, N.R., Smith, E.C., Blanc, H., Vignuzzi, M., Peersen, O.B., Denison, M.R. (2016). Homology-based identification of a mutation in the coronavirus RNA-dependent RNA polymerase that confers resistance to multiple mutagens. J Virol. 90(16): 7415-7428. https://doi.org/10.1128/JVI.00080-16 PMid:27279608 PMCid:PMC4984655
  20. Ruan, Z., Liu, C., Guo, Y., He, Z., Huang, X., Jia, X. (2020). Potential inhibitors targeting RNA-dependent RNA polymerase activity (NSP12) of SARS-CoV-2 [Internet]. Preprints  2020030024 [cited 2020 May 23]. Available from: https://www.preprints.org/manuscript/202003.0024/v1 https://doi.org/10.20944/preprints202003.0024.v1
  21. Pfeiffer, J.K., Kirkegaard, K. (2003). A single mutation in poliovirus RNA-dependent RNA polymerase confers resistance to mutagenic nucleotide analogs via increased fidelity. Proc Natl Acad Sci U S A. 100(12): 7289-7294. https://doi.org/10.1073/pnas.1232294100 PMid:12754380 PMCid:PMC165868
  22. Neogi, U., Hill, K.J., Ambikan, A.T., Heng, X., Quinn, T.P., Byrareddy, S.N., Sönnerborg, A., et al. (2020). Feasibility of known RNA polymerase inhibitors as Anti-SARS-CoV-2 drugs. Pathogens 9(5): 320. https://doi.org/10.3390/pathogens9050320 PMid:32357471 PMCid:PMC7281371
  23. Shannon, A., Le, N.T.T., Selisko, B., Eydoux, C., Alvarez, K., Guillemot, J.C., Decroly, E., et al. (2020). Remdesivir and SARS-CoV-2: Structural requirements at both nsp12 RdRp and nsp14 Exonuclease active-sites. Antiviral Res. 178, 104793. https://doi.org/10.1016/j.antiviral.2020.104793 PMid:32283108 PMCid:PMC7151495
  24. Gao, Y., Yan, L., Huang, Y., Liu, F., Zhao, Y., Cao, L., Wang, T., et al. (2020). Structure of the RNA-dependent RNA polymerase from COVID-19 virus. Science 368(6492): 779-782. https://doi.org/10.1126/science.abb7498 PMid:32277040 PMCid:PMC7164392
  25. Wang, M., Cao, R., Zhang, L., Yang, X., Liu, J., Xu, M., Shi, Z., et al. (2020). Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Res. 30(3): 269-271. https://doi.org/10.1038/s41422-020-0282-0 PMid:32020029 PMCid:PMC7054408
  26. Pachetti, M., Marini, B., Benedetti, F., Giudici, F., Mauro, E., Storici, P., Masciovecchio, C., et al. (2020). Emerging SARS-CoV-2 mutation hot spots include a novel RNA-dependent-RNA polymerase variant. J Transl Med. 18(1): 179. https://doi.org/10.1186/s12967-020-02344-6 PMid:32321524 PMCid:PMC7174922
  27. Coppée, F., Lechien, J.R., Declèves, A.E., Tafforeau, L., Saussez, S. (2020). Severe acute respiratory syndrome coronavirus 2: virus mutations in specific European populations. New Microbes New Infect. 36, 100696. https://doi.org/10.1016/j.nmni.2020.100696 PMid:32509310 PMCid:PMC7238997
  28. Chand, G.B., Banerjee, A., Azad, G.K. (2020). Identification of novel mutations in RNA-dependent RNA polymerases of SARS-CoV-2 and their implications on its protein structure. PeerJ. 8, e9492. https://doi.org/10.7717/peerj.9492 PMid:32685291 PMCid:PMC7337032

Copyright

© 2020 Dabravolski S.A. This is an open-access article published under the terms of the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Conflict of Interest Statement

The authors have declared that no competing interests exist.

Citation Information

Macedonian Veterinary Review. Volume 44, Issue 1, Pages 87-94, e-ISSN 1857-7415, p-ISSN 1409-7621, DOI: 10.2478/macvetrev-2020-0036, 2021

The all content of the Macedonian Veterinary Review, except where otherwise noted, is licensed under a Creative Commons Attribution License.