Non-optimal codon usage preferences of coronaviruses determine their promiscuity for infecting multiple hosts

Gon Carmi, Alessandro Gorohovski, Sumit Mukherjee, Milana Frenkel-Morgenstern

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Circulating animal coronaviruses occasionally infect humans. The SARS-CoV-2 is responsible for the current worldwide outbreak of COVID-19 that has resulted in 2 112 844 deaths as of late January 2021. We compared genetic code preferences in 496 viruses, including 34 coronaviruses and 242 corresponding hosts, to uncover patterns that distinguish single- and ‘promiscuous’ multiple-host-infecting viruses. Based on a codon usage preference score, promiscuous viruses were shown to significantly employ nonoptimal codons, namely codons that involve ‘wobble’ binding to anticodons, as compared to single-host viruses. The codon adaptation index (CAI) and the effective number of codons (ENC) were calculated for all viruses and hosts. Promiscuous viruses were less adapted hosts vs single-host viruses (P-value = 4.392e-11). All coronaviruses exploit nonoptimal codons to infect multiple hosts. We found that nonoptimal codon preferences at the beginning of viral coding sequences enhance the translational efficiency of viral proteins within the host. Finally, coronaviruses lack endogenous RNA degradation motifs to a significant degree, thereby increasing viral mRNA burden and infection load. To conclude, we found that promiscuously infecting coronaviruses prefer nonoptimal codon usage to remove degradation motifs from their RNAs and to dramatically increase their viral RNA production rates.

Original languageEnglish
Pages (from-to)5201-5223
Number of pages23
JournalFEBS Journal
Volume288
Issue number17
Early online date7 Apr 2021
DOIs
StatePublished - Sep 2021

Bibliographical note

Publisher Copyright:
© 2021 Federation of European Biochemical Societies

Funding

The authors thank the members of the Laboratory of Cancer Genomics and Biocomputing of Complex Diseases for their input at different stages of this project. We thank Dr. Dorith Raviv‐Shay, Dr. Somnath Tagore, and Prof. Chaim Putterman for valuable suggestions and comments. We thank Prof. Karl Skorecki, the Dean of the Azrieli Faculty of Medicine, for the significant comments and valuable discussions on the manuscript. Fundings came from a KAMIN Grant of the Israel Innovation Authority (MF‐M; Grant Number 66824) and the COVID‐19 Data Science Institute (DSI), Bar‐Ilan University (MF‐M; Grant Number 247017). The authors thank the members of the Laboratory of Cancer Genomics and Biocomputing of Complex Diseases for their input at different stages of this project. We thank Dr. Dorith Raviv-Shay, Dr. Somnath Tagore, and Prof. Chaim Putterman for valuable suggestions and comments. We thank Prof. Karl Skorecki, the Dean of the Azrieli Faculty of Medicine, for the significant comments and valuable discussions on the manuscript. Fundings came from a KAMIN Grant of the Israel Innovation Authority (MF-M; Grant Number 66824) and the COVID-19 Data Science Institute (DSI), Bar-Ilan University (MF-M; Grant Number 247017).

FundersFunder number
COVID-19 Data Science Institute
COVID‐19 Data Science Institute
Israel Innovation Authority66824
Bar-Ilan University247017
Defence Science Institute

    Keywords

    • COVID-19
    • SARS-CoV-2
    • coronavirus
    • host
    • nonoptimal codon usage
    • virus interaction

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