Literature DB >> 32123323

Dissimilation of synonymous codon usage bias in virus-host coevolution due to translational selection.

Feng Chen1,2,3, Peng Wu2, Shuyun Deng4, Heng Zhang5, Yutong Hou2, Zheng Hu6, Jianzhi Zhang7, Xiaoshu Chen8,9, Jian-Rong Yang10,11,12,13,14,15.   

Abstract

Eighteen of the 20 amino acids are each encoded by more than one synonymous codon. Due to differential transfer RNA supply within the cell, synonymous codons are not used with equal frequency, a phenomenon termed codon usage bias (CUB). Previous studies have demonstrated that CUB of endogenous genes trans-regulates the translational efficiency of other genes. We hypothesized similar effects for CUB of exogenous genes on host translation, and tested it in the case of viral infection, a common form of naturally occurring exogenous gene translation. We analysed public Ribo-Seq datasets from virus-infected yeast and human cells and showed that virus CUB trans-regulated tRNA availability, and therefore the relative decoding time of codons. Manipulative experiments in yeast using 37 synonymous fluorescent proteins confirmed that an exogenous gene with CUB more similar to that of the host would apply decreased translational load on the host per unit of expression, whereas expression of the exogenous gene was elevated. The combination of these two effects was that exogenous genes with CUB overly similar to that of the host severely impeded host translation. Finally, using a manually curated list of viruses and natural and symptomatic hosts, we found that virus CUB tended to be more similar to that of symptomatic hosts than that of natural hosts, supporting a general deleterious effect of excessive CUB similarity between virus and host. Our work revealed repulsion between virus and host CUBs when they are overly similar, a previously unrecognized complexity in the coevolution of virus and host.

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Year:  2020        PMID: 32123323      PMCID: PMC7249751          DOI: 10.1038/s41559-020-1124-7

Source DB:  PubMed          Journal:  Nat Ecol Evol        ISSN: 2397-334X            Impact factor:   15.460


  62 in total

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Journal:  Genetics       Date:  1991-11       Impact factor: 4.562

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Journal:  Annu Rev Genet       Date:  2008       Impact factor: 16.830

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Authors:  X Xia
Journal:  Genetics       Date:  1996-11       Impact factor: 4.562

4.  How optimized is the translational machinery in Escherichia coli, Salmonella typhimurium and Saccharomyces cerevisiae?

Authors:  X Xia
Journal:  Genetics       Date:  1998-05       Impact factor: 4.562

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Authors:  M A Sørensen; C G Kurland; S Pedersen
Journal:  J Mol Biol       Date:  1989-05-20       Impact factor: 5.469

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Journal:  Proc Natl Acad Sci U S A       Date:  1987-01       Impact factor: 11.205

7.  Codon usage in bacteria: correlation with gene expressivity.

Authors:  M Gouy; C Gautier
Journal:  Nucleic Acids Res       Date:  1982-11-25       Impact factor: 16.971

8.  Translation efficiency is determined by both codon bias and folding energy.

Authors:  Tamir Tuller; Yedael Y Waldman; Martin Kupiec; Eytan Ruppin
Journal:  Proc Natl Acad Sci U S A       Date:  2010-02-02       Impact factor: 11.205

9.  Codon usage can affect efficiency of translation of genes in Escherichia coli.

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Journal:  Nucleic Acids Res       Date:  1984-09-11       Impact factor: 16.971

10.  A major controversy in codon-anticodon adaptation resolved by a new codon usage index.

Authors:  Xuhua Xia
Journal:  Genetics       Date:  2014-12-05       Impact factor: 4.562

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  24 in total

1.  Expression level is a major modifier of the fitness landscape of a protein coding gene.

Authors:  Zhuoxing Wu; Xiujuan Cai; Xin Zhang; Yao Liu; Guo-Bao Tian; Jian-Rong Yang; Xiaoshu Chen
Journal:  Nat Ecol Evol       Date:  2021-11-18       Impact factor: 15.460

2.  Deep learning based on biologically interpretable genome representation predicts two types of human adaptation of SARS-CoV-2 variants.

Authors:  Jing Li; Ya-Nan Wu; Sen Zhang; Xiao-Ping Kang; Tao Jiang
Journal:  Brief Bioinform       Date:  2022-05-13       Impact factor: 13.994

3.  Biased Mutation and Selection in RNA Viruses.

Authors:  Talia Kustin; Adi Stern
Journal:  Mol Biol Evol       Date:  2021-01-23       Impact factor: 16.240

4.  Molecular features similarities between SARS-CoV-2, SARS, MERS and key human genes could favour the viral infections and trigger collateral effects.

Authors:  Lucas L Maldonado; Andrea Mendoza Bertelli; Laura Kamenetzky
Journal:  Sci Rep       Date:  2021-02-18       Impact factor: 4.379

Review 5.  Chimeric antigen receptor natural killer (CAR-NK) cell design and engineering for cancer therapy.

Authors:  Ying Gong; Roel G J Klein Wolterink; Jianxiang Wang; Gerard M J Bos; Wilfred T V Germeraad
Journal:  J Hematol Oncol       Date:  2021-05-01       Impact factor: 17.388

6.  From Mutation Signature to Molecular Mechanism in the RNA World: A Case of SARS-CoV-2.

Authors:  Jun Yu
Journal:  Genomics Proteomics Bioinformatics       Date:  2020-07-30       Impact factor: 7.691

Review 7.  Emerging translation strategies during virus-host interaction.

Authors:  Huy-Dung Hoang; Serge Neault; Adrian Pelin; Tommy Alain
Journal:  Wiley Interdiscip Rev RNA       Date:  2020-08-05       Impact factor: 9.957

8.  Analysis of the Codon Usage Pattern of HA and NA Genes of H7N9 Influenza A Virus.

Authors:  Jiumeng Sun; Wen Zhao; Ruyi Wang; Wenyan Zhang; Gairu Li; Meng Lu; Yuekun Shao; Yichen Yang; Ningning Wang; Qi Gao; Shuo Su
Journal:  Int J Mol Sci       Date:  2020-09-27       Impact factor: 5.923

Review 9.  The Paradoxes of Viral mRNA Translation during Mammalian Orthoreovirus Infection.

Authors:  Yingying Guo; John S L Parker
Journal:  Viruses       Date:  2021-02-11       Impact factor: 5.048

10.  Sequence analysis of SARS-CoV-2 genome reveals features important for vaccine design.

Authors:  Jacob Kames; David D Holcomb; Ofer Kimchi; Michael DiCuccio; Nobuko Hamasaki-Katagiri; Tony Wang; Anton A Komar; Aikaterini Alexaki; Chava Kimchi-Sarfaty
Journal:  Sci Rep       Date:  2020-09-24       Impact factor: 4.996

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