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Paradis NJ, Wu C. Enhanced detection and molecular modeling of adaptive mutations in SARS-CoV-2 coding and non-coding regions using the c/µ test. Virus Evol 2024; 10:veae089. [PMID: 39584063 PMCID: PMC11584280 DOI: 10.1093/ve/veae089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2024] [Revised: 10/09/2024] [Accepted: 10/24/2024] [Indexed: 11/26/2024] Open
Abstract
Accurately identifying mutations under beneficial selection in viral genomes is crucial for understanding their molecular evolution and pathogenicity. Traditional methods like the Ka/Ks test, which assesses non-synonymous (Ka) versus synonymous (Ks) substitution rates, assume that synonymous substitutions at synonymous sites are neutral and thus is equal to the mutation rate (µ). Yet, evidence suggests that synonymous sites in translated regions (TRs) and untranslated regions (UTRs) can be under strong beneficial selection (Ks > µ) and strongly conserved (Ks ≈ 0), leading to false predictions of adaptive mutations from codon-by-codon Ka/Ks analysis. Our previous work used a relative substitution rate test (c/µ, c: substitution rate in UTR/TR, and µ: mutation rate) to identify adaptive mutations in SARS-CoV-2 genome without the neutrality assumption of the synonymous sites. This study refines the c/µ test by optimizing µ value, leading to a smaller set of nucleotide and amino acid sites under beneficial selection in both UTR (11 sites with c/µ > 3) and TR (69 nonsynonymous sites: c/µ > 3 and Ka/Ks > 2.5; 107 synonymous sites: Ks/µ > 3). Encouragingly, the top two mutations in UTR and 70% of the top nonsynonymous mutations in TR had reported or predicted effects in the literature. Molecular modeling of top adaptive mutations for some critical proteins (S, NSP11, and NSP5) was carried out to elucidate the possible molecular mechanism of their adaptivity.
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Affiliation(s)
- Nicholas J Paradis
- Department of Chemistry and Biochemistry, Rowan University, 201 Mullica Hill Rd., Glassboro, NJ 08028, United States
| | - Chun Wu
- Department of Chemistry and Biochemistry, Rowan University, 201 Mullica Hill Rd., Glassboro, NJ 08028, United States
- Department of Biological & Biomedical Sciences, Rowan University, 201 Mullica Hill Rd., Glassboro, NJ 08028, United States
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Majchrzak M, Madej Ł, Łysek-Gładysińska M, Zarębska-Michaluk D, Zegadło K, Dziuba A, Nogal-Nowak K, Kondziołka W, Sufin I, Myszona-Tarnowska M, Jaśkowski M, Kędzierski M, Maciukajć J, Matykiewicz J, Głuszek S, Adamus-Białek W. The RdRp genotyping of SARS-CoV-2 isolated from patients with different clinical spectrum of COVID-19. BMC Infect Dis 2024; 24:281. [PMID: 38439047 PMCID: PMC10913261 DOI: 10.1186/s12879-024-09146-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Accepted: 02/16/2024] [Indexed: 03/06/2024] Open
Abstract
BACKGROUND The evolution of SARS-CoV-2 has been observed from the very beginning of the fight against COVID-19, some mutations are indicators of potentially dangerous variants of the virus. However, there is no clear association between the genetic variants of SARS-CoV-2 and the severity of COVID-19. We aimed to analyze the genetic variability of RdRp in correlation with different courses of COVID-19. RESULTS The prospective study included 77 samples of SARS-CoV-2 isolated from outpatients (1st degree of severity) and hospitalized patients (2nd, 3rd and 4th degree of severity). The retrospective analyses included 15,898,266 cases of SARS-CoV-2 genome sequences deposited in the GISAID repository. Single-nucleotide variants were identified based on the four sequenced amplified fragments of SARS-CoV-2. The analysis of the results was performed using appropriate statistical methods, with p < 0.05, considered statistically significant. Additionally, logistic regression analysis was performed to predict the strongest determinants of the observed relationships. The number of mutations was positively correlated with the severity of the COVID-19, and older male patients. We detected four mutations that significantly increased the risk of hospitalization of COVID-19 patients (14676C > T, 14697C > T, 15096 T > C, and 15279C > T), while the 15240C > T mutation was common among strains isolated from outpatients. The selected mutations were searched worldwide in the GISAID database, their presence was correlated with the severity of COVID-19. CONCLUSION Identified mutations have the potential to be used to assess the increased risk of hospitalization in COVID-19 positive patients. Experimental studies and extensive epidemiological data are needed to investigate the association between individual mutations and the severity of COVID-19.
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Affiliation(s)
- Michał Majchrzak
- Institute of Medical Sciences, Jan Kochanowski University, Kielce, Poland
| | - Łukasz Madej
- Institute of Medical Sciences, Jan Kochanowski University, Kielce, Poland
| | | | | | - Katarzyna Zegadło
- Institute of Medical Sciences, Jan Kochanowski University, Kielce, Poland
| | - Anna Dziuba
- Institute of Medical Sciences, Jan Kochanowski University, Kielce, Poland
| | | | | | | | | | | | | | | | | | - Stanisław Głuszek
- Institute of Medical Sciences, Jan Kochanowski University, Kielce, Poland
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3
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Lu Y, Wang W, Liu H, Li Y, Yan G, Franzo G, Dai J, He WT. Mutation and codon bias analysis of the spike protein of Omicron, the recent variant of SARS-CoV-2. Int J Biol Macromol 2023; 250:126080. [PMID: 37536405 DOI: 10.1016/j.ijbiomac.2023.126080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 07/29/2023] [Indexed: 08/05/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant is a heavily mutated virus and designated as a variant of concern. To investigate the codon usage pattern of this new variant, we performed mutation and codon bias analysis for Omicron as well as for its sub-lineages BA.1 and BA.2 and compared them with the original SARS-CoV-2 and the Delta variant sequences obtained in this study. Our results indicate that the sub-lineage BA.1 and BA.2 have up to 23 sites of difference on the spike protein, which have minimal impact on function. The Omicron variant and its sub-lineages have similar codon usage patterns and A/U ending codons appear to be preferred over G/C ending codons. The Omicron has a lower degree of codon usage bias in spite of evidence that natural selection, mutation pressure and dinucleotide abundance shape the codon usage bias of Omicron, with natural selection being more significant on BA.2 than the other sub-lineages of Omicron. The codon usage pattern of Omicron variant that we explored provides valid information for a clearer understanding of Omicron and its sub-lineages, which could find application in vaccine development and optimization.
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Affiliation(s)
- Yunbiao Lu
- School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing 211198, People's Republic of China
| | - Weixiu Wang
- School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing 211198, People's Republic of China
| | - Hao Liu
- School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing 211198, People's Republic of China
| | - Yue Li
- School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing 211198, People's Republic of China
| | - Ge Yan
- School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing 211198, People's Republic of China
| | - Giovanni Franzo
- Department of Animal Medicine, Production and Health (MAPS), University of Padua, Viale dell'Università 16, Legnaro 35020, PD, Italy
| | - Jianjun Dai
- School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing 211198, People's Republic of China.
| | - Wan-Ting He
- School of Pharmacy, China Pharmaceutical University, 639 Longmian Avenue, Nanjing 211198, People's Republic of China.
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Zou J, Kurhade C, Chang HC, Hu Y, Meza JA, Beaver D, Trinh K, Omlid J, Elghetany B, Desai R, McCaffrey P, Garcia JD, Shi PY, Ren P, Xie X. An Integrated Research-Clinical BSL-2 Platform for a Live SARS-CoV-2 Neutralization Assay. Viruses 2023; 15:1855. [PMID: 37766263 PMCID: PMC10536566 DOI: 10.3390/v15091855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Revised: 08/28/2023] [Accepted: 08/30/2023] [Indexed: 09/29/2023] Open
Abstract
A reliable and efficient serological test is crucial for monitoring neutralizing antibodies against SARS-CoV-2 and its variants of concern (VOCs). Here, we present an integrated research-clinical platform for a live SARS-CoV-2 neutralization assay, utilizing highly attenuated SARS-CoV-2 (Δ3678_WA1-spike). This strain contains mutations in viral transcription regulation sequences and deletion in the open-reading-frames 3, 6, 7, and 8, allowing for safe handling in biosafety level 2 (BSL-2) laboratories. Building on this backbone, we constructed a genetically stable reporter virus (mGFP Δ3678_WA1-spike) by incorporating a modified green fluorescent protein sequence (mGFP). We also constructed mGFP Δ3678_BA.5-spike and mGFP Δ3678_XBB.1.5-spike by substituting the WA1 spike with variants BA.5 and XBB.1.5 spike, respectively. All three viruses exhibit robust fluorescent signals in infected cells and neutralization titers in an optimized fluorescence reduction neutralization assay that highly correlates with a conventional plaque reduction assay. Furthermore, we established that a streamlined robot-aided Bench-to-Clinics COVID-19 Neutralization Test workflow demonstrated remarkably sensitive, specific, reproducible, and accurate characteristics, allowing the assessment of neutralization titers against SARS-CoV-2 variants within 24 h after sample receiving. Overall, our innovative approach provides a valuable avenue for large-scale testing of clinical samples against SARS-CoV-2 and VOCs at BSL-2, supporting pandemic preparedness and response strategies.
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Affiliation(s)
- Jing Zou
- Department of Biochemistry & Molecular Biology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Chaitanya Kurhade
- Department of Pathology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Hope C Chang
- Department of Pathology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Yanping Hu
- Department of Biochemistry & Molecular Biology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Jose A Meza
- Department of Pathology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - David Beaver
- Department of Biochemistry & Molecular Biology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Ky Trinh
- Department of Biochemistry & Molecular Biology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Joseph Omlid
- Department of Pathology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Bassem Elghetany
- Department of Pathology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Ragini Desai
- Department of Pathology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Peter McCaffrey
- Department of Pathology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Juan D Garcia
- Department of Pathology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Pei-Yong Shi
- Department of Biochemistry & Molecular Biology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Ping Ren
- Department of Pathology, University of Texas Medical Branch, Galveston, TX 77555, USA
| | - Xuping Xie
- Department of Biochemistry & Molecular Biology, University of Texas Medical Branch, Galveston, TX 77555, USA
- Sealy Institute for Drug Discovery, University of Texas Medical Branch, Galveston, TX 77555, USA
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Wu X, Shan K, Zan F, Tang X, Qian Z, Lu J. Optimization and Deoptimization of Codons in SARS-CoV-2 and Related Implications for Vaccine Development. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2205445. [PMID: 37267926 PMCID: PMC10427376 DOI: 10.1002/advs.202205445] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 04/08/2023] [Indexed: 06/04/2023]
Abstract
The spread of coronavirus disease 2019 (COVID-19), caused by severe respiratory syndrome coronavirus 2 (SARS-CoV-2), has progressed into a global pandemic. To date, thousands of genetic variants have been identified among SARS-CoV-2 isolates collected from patients. Sequence analysis reveals that the codon adaptation index (CAI) values of viral sequences have decreased over time but with occasional fluctuations. Through evolution modeling, it is found that this phenomenon may result from the virus's mutation preference during transmission. Using dual-luciferase assays, it is further discovered that the deoptimization of codons in the viral sequence may weaken protein expression during virus evolution, indicating that codon usage may play an important role in virus fitness. Finally, given the importance of codon usage in protein expression and particularly for mRNA vaccines, it is designed several codon-optimized Omicron BA.2.12.1, BA.4/5, and XBB.1.5 spike mRNA vaccine candidates and experimentally validated their high levels of expression. This study highlights the importance of codon usage in virus evolution and provides guidelines for codon optimization in mRNA and DNA vaccine development.
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Affiliation(s)
- Xinkai Wu
- State Key Laboratory of Protein and Plant Gene ResearchCenter for BioinformaticsSchool of Life SciencesPeking UniversityBeijing100871China
| | - Ke‐jia Shan
- State Key Laboratory of Protein and Plant Gene ResearchCenter for BioinformaticsSchool of Life SciencesPeking UniversityBeijing100871China
| | - Fuwen Zan
- NHC Key Laboratory of Systems Biology of PathogensInstitute of Pathogen BiologyChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing100176China
| | - Xiaolu Tang
- State Key Laboratory of Protein and Plant Gene ResearchCenter for BioinformaticsSchool of Life SciencesPeking UniversityBeijing100871China
| | - Zhaohui Qian
- NHC Key Laboratory of Systems Biology of PathogensInstitute of Pathogen BiologyChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing100176China
| | - Jian Lu
- State Key Laboratory of Protein and Plant Gene ResearchCenter for BioinformaticsSchool of Life SciencesPeking UniversityBeijing100871China
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Fumagalli SE, Padhiar NH, Meyer D, Katneni U, Bar H, DiCuccio M, Komar AA, Kimchi-Sarfaty C. Analysis of 3.5 million SARS-CoV-2 sequences reveals unique mutational trends with consistent nucleotide and codon frequencies. Virol J 2023; 20:31. [PMID: 36812119 PMCID: PMC9936480 DOI: 10.1186/s12985-023-01982-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 02/02/2023] [Indexed: 02/19/2023] Open
Abstract
BACKGROUND Since the onset of the SARS-CoV-2 pandemic, bioinformatic analyses have been performed to understand the nucleotide and synonymous codon usage features and mutational patterns of the virus. However, comparatively few have attempted to perform such analyses on a considerably large cohort of viral genomes while organizing the plethora of available sequence data for a month-by-month analysis to observe changes over time. Here, we aimed to perform sequence composition and mutation analysis of SARS-CoV-2, separating sequences by gene, clade, and timepoints, and contrast the mutational profile of SARS-CoV-2 to other comparable RNA viruses. METHODS Using a cleaned, filtered, and pre-aligned dataset of over 3.5 million sequences downloaded from the GISAID database, we computed nucleotide and codon usage statistics, including calculation of relative synonymous codon usage values. We then calculated codon adaptation index (CAI) changes and a nonsynonymous/synonymous mutation ratio (dN/dS) over time for our dataset. Finally, we compiled information on the types of mutations occurring for SARS-CoV-2 and other comparable RNA viruses, and generated heatmaps showing codon and nucleotide composition at high entropy positions along the Spike sequence. RESULTS We show that nucleotide and codon usage metrics remain relatively consistent over the 32-month span, though there are significant differences between clades within each gene at various timepoints. CAI and dN/dS values vary substantially between different timepoints and different genes, with Spike gene on average showing both the highest CAI and dN/dS values. Mutational analysis showed that SARS-CoV-2 Spike has a higher proportion of nonsynonymous mutations than analogous genes in other RNA viruses, with nonsynonymous mutations outnumbering synonymous ones by up to 20:1. However, at several specific positions, synonymous mutations were overwhelmingly predominant. CONCLUSIONS Our multifaceted analysis covering both the composition and mutation signature of SARS-CoV-2 gives valuable insight into the nucleotide frequency and codon usage heterogeneity of SARS-CoV-2 over time, and its unique mutational profile compared to other RNA viruses.
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Affiliation(s)
- Sarah E Fumagalli
- Hemostasis Branch, Division of Plasma Protein Therapeutics, Office of Tissues and Advanced Therapies, Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Nigam H Padhiar
- Hemostasis Branch, Division of Plasma Protein Therapeutics, Office of Tissues and Advanced Therapies, Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Douglas Meyer
- Hemostasis Branch, Division of Plasma Protein Therapeutics, Office of Tissues and Advanced Therapies, Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Upendra Katneni
- Hemostasis Branch, Division of Plasma Protein Therapeutics, Office of Tissues and Advanced Therapies, Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA
| | - Haim Bar
- Department of Statistics, University of Connecticut, Storrs, CT, USA
| | | | - Anton A Komar
- Department of Biological, Geological and Environmental Sciences, Center for Gene Regulation in Health and Disease, Cleveland State University, Cleveland, OH, USA
| | - Chava Kimchi-Sarfaty
- Hemostasis Branch, Division of Plasma Protein Therapeutics, Office of Tissues and Advanced Therapies, Center for Biologics Evaluation and Research, US Food and Drug Administration, Silver Spring, MD, USA.
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7
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Zhou H, Ren R, Yau SST. Utilizing the codon adaptation index to evaluate the susceptibility to HIV-1 and SARS-CoV-2 related coronaviruses in possible target cells in humans. Front Cell Infect Microbiol 2023; 12:1085397. [PMID: 36760235 PMCID: PMC9905242 DOI: 10.3389/fcimb.2022.1085397] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 12/30/2022] [Indexed: 01/27/2023] Open
Abstract
Comprehensive identification of possible target cells for viruses is crucial for understanding the pathological mechanism of virosis. The susceptibility of cells to viruses depends on many factors. Besides the existence of receptors at the cell surface, effective expression of viral genes is also pivotal for viral infection. The regulation of viral gene expression is a multilevel process including transcription, translational initiation and translational elongation. At the translational elongation level, the translational efficiency of viral mRNAs mainly depends on the match between their codon composition and cellular translational machinery (usually referred to as codon adaptation). Thus, codon adaptation for viral ORFs in different cell types may be related to their susceptibility to viruses. In this study, we selected the codon adaptation index (CAI) which is a common codon adaptation-based indicator for assessing the translational efficiency at the translational elongation level to evaluate the susceptibility to two-pandemic viruses (HIV-1 and SARS-CoV-2) of different human cell types. Compared with previous studies that evaluated the infectivity of viruses based on codon adaptation, the main advantage of our study is that our analysis is refined to the cell-type level. At first, we verified the positive correlation between CAI and translational efficiency and strengthened the rationality of our research method. Then we calculated CAI for ORFs of two viruses in various human cell types. We found that compared to high-expression endogenous genes, the CAIs of viral ORFs are relatively low. This phenomenon implied that two kinds of viruses have not been well adapted to translational regulatory machinery in human cells. Also, we indicated that presumptive susceptibility to viruses according to CAI is usually consistent with the results of experimental research. However, there are still some exceptions. Finally, we found that two viruses have different effects on cellular translational mechanisms. HIV-1 decouples CAI and translational efficiency of endogenous genes in host cells and SARS-CoV-2 exhibits increased CAI for its ORFs in infected cells. Our results implied that at least in cases of HIV-1 and SARS-CoV-2, CAI can be regarded as an auxiliary index to assess cells' susceptibility to viruses but cannot be used as the only evidence to identify viral target cells.
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Affiliation(s)
- Haoyu Zhou
- Yanqi Lake Beijing Institute of Mathematical Sciences and Applications (BIMSA), Beijing, China,School of Life Sciences, Tsinghua University, Beijing, China
| | - Ruohan Ren
- Yanqi Lake Beijing Institute of Mathematical Sciences and Applications (BIMSA), Beijing, China,Zhili College, Tsinghua University, Beijing, China
| | - Stephen Shing-Toung Yau
- Yanqi Lake Beijing Institute of Mathematical Sciences and Applications (BIMSA), Beijing, China,Department of Mathematical Sciences, Tsinghua University, Beijing, China,*Correspondence: Stephen Shing-Toung Yau,
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Liu Y. Attenuation and Degeneration of SARS-CoV-2 Despite Adaptive Evolution. Cureus 2023; 15:e33316. [PMID: 36741655 PMCID: PMC9894646 DOI: 10.7759/cureus.33316] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Accepted: 01/02/2023] [Indexed: 01/04/2023] Open
Abstract
The evolution of severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) has followed similar trends as other RNA viruses, such as human immunodeficiency virus type 1 and the influenza A virus. Rapid initial diversification was followed by strong competition and a rapid succession of dominant variants. Host-initiated RNA editing has been the primary mechanism for introducing mutations. A significant number of mutations detrimental to viral replication have been quickly purged. Fixed mutations are mostly diversifying mutations selected for host adaptation and immune evasion, with the latter accounting for the majority of the mutations. However, immune evasion often comes at the cost of functionality, and thus, optimal functionality is still far from being accomplished. Instead, selection for antibody-escaping variants and accumulation of near-neutral mutations have led to suboptimal codon usage and reduced replicative capacity, as demonstrated in non-respiratory cell lines. Beneficial adaptation of the virus includes reduced infectivity in lung tissues and increased tropism for the upper airway, resulting in shorter incubation periods, milder diseases, and more efficient transmission between people.
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Affiliation(s)
- Yingguang Liu
- Molecular and Cellular Sciences, Liberty University College of Osteopathic Medicine, Lynchburg, USA
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Jiang L, Zhang Q, Xiao S, Si F. Deep decoding of codon usage strategies and host adaption preferences of soybean mosaic virus. Int J Biol Macromol 2022; 222:803-817. [PMID: 36167098 DOI: 10.1016/j.ijbiomac.2022.09.179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 09/13/2022] [Accepted: 09/17/2022] [Indexed: 11/05/2022]
Abstract
Soybean mosaic virus (SMV) has threatened the global yield of Leguminosae crops, but the mechanism of its infection, spread, and evolution remains unknown. A systemic analysis of 107 SMV strains was performed to explore the genome-wide codon usage profile and the various factors influencing the codon usage patterns of SMV, which provides insight into its molecular evolution and elucidates its unknown host adaptation pattern. The overall nucleotide composition and correlation analysis revealed that the preferred synonymous codons mostly end with A/U. Clustering by RSCU value of each strain and phylogenetic tree analysis showed that the SMV isolates studied were divided into four clades, with a low overall extent of codon usage bias (CUB) in SMV. According to the ENC, PR2, neutrality plot, and correspondence analysis, natural selection of geographical diversity may play a critical role in the CUB. Higher adaptability was shown in Glycine with SMV and more pressure was received by clade III. These findings could not only provide valuable information about the overall codon usage pattern of the SMV genome, but could also aid in the clarification of the involved mechanisms that dominate the codon usage patterns and genetic evolution of the SMV genome.
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Affiliation(s)
- Li Jiang
- Guangdong Provincial Key Laboratory of Plant Adaptation and Molecular Design, Guangzhou Key Laboratory of Crop Gene Editing, Innovative Center of Molecular Genetics and Evolution, School of Life Sciences, Guangzhou University, Guangzhou 510006, China
| | - Qiang Zhang
- Zhengzhou Fruit Research Institute, Chinese Academy of Agricultural Sciences, Zhengzhou 450009, China
| | - Shimin Xiao
- Shanwei Marine Industry Institute, Shanwei Institute of Technology, Shanwei 516600, China.
| | - Fusheng Si
- Institute of Animal Science and Veterinary Medicine, Shanghai Academy of Agricultural Sciences, Shanghai Key Laboratory of Agricultural Genetics and Breeding, Shanghai Engineering Research Center of Breeding Pig, Shanghai 201106, China.
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