1
|
Ahmad A, Majaz S, Saeed A, Noreen S, Abbas M, Khan B, Rahman HU, Nouroz F, Xie Y, Rashid A, Rehman AU. Microevolution and phylogenomic study of Respiratory Syncytial Virus type A. PLoS One 2025; 20:e0319437. [PMID: 39999081 PMCID: PMC11856557 DOI: 10.1371/journal.pone.0319437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2024] [Accepted: 02/02/2025] [Indexed: 02/27/2025] Open
Abstract
Communal respiratory syncytial virus (RSV) causes mild to severe illnesses, predominantly in older adults, or people with certain chronic medical conditions, and in children. Symptoms may include rhinorrhea, cough, fever, and dyspnea. In most cases, the infection is mild and resolves on its own, but in some cases, it can lead to more serious illness such as bronchiolitis or pneumonia. The RSV genome codes for ten proteins, NS1, NS2, N, P, M, SH, G, F, M2 and L. We aimed to identify the RSV geographical transmission pattern based on parsimony and investigate hotspot regions across the complete RSV genomes. We employed Viral Evolutionary Network Analysis System on full-length available RSV genomes and with HyPhy for elucidating type of selection pressure. These results indicated that RSV strains circulating in South and North America are not mixed to the European samples, however, genomes reported from Australia are the direct decedents of European samples. Samples reported from the United Kingdom exhibited significant diversity, spanning almost every cluster. This report provides a complete mutational analysis of all the individual RSV genes, and particularly the 31 hotspot substituting regions circulating across the globe in RSV type A samples. Further, protein G and L displayed higher level of codons experienced positive selection. This analysis of RSV type A highlights mutational frequencies across the whole genome, offering valuable insights for epidemiological control and drug development.
Collapse
Affiliation(s)
- Ashfaq Ahmad
- Department of Bioinformatics, Faculty of Natural and Computational Sciences, Hazara University, Mansehra, Khyber Pakhtunkhwa, Pakistan
| | - Sidra Majaz
- Department of Bioinformatics, Faculty of Natural and Computational Sciences, Hazara University, Mansehra, Khyber Pakhtunkhwa, Pakistan
| | - Aamir Saeed
- Department of Bioinformatics, Faculty of Natural and Computational Sciences, Hazara University, Mansehra, Khyber Pakhtunkhwa, Pakistan
| | - Shumaila Noreen
- Department of Zoology, Faculty of Biological and Health Sciences, Hazara University, Mansehra, Khyber Pakhtunkhwa, Pakistan
| | - Muhammad Abbas
- Department of Urology, Pakistan Institute of Medical Sciences, Islamabad, Pakistan
| | - Bilal Khan
- Department of Pediatrics, Tehsil Headquarter Hospital (THQ), Dargai, Malakand, Khyber Pakhtunkhwa, Pakistan
| | - Hamid Ur Rahman
- Department of Zoology, Faculty of Biological and Health Sciences, Hazara University, Mansehra, Khyber Pakhtunkhwa, Pakistan
| | - Faisal Nouroz
- Department of Bioinformatics, Faculty of Natural and Computational Sciences, Hazara University, Mansehra, Khyber Pakhtunkhwa, Pakistan
| | - Yingqiu Xie
- Department of Biology, School of Sciences and Humanities, Nazarbayev University, Astana, Kazakhstan
| | - Abdur Rashid
- Government Degree College Ara Khel, F.R Kohat, Higher Education Department, Government of Khyber Pakhtunkhwa, Kohat, Khyber Pakhtunkhwa, Pakistan
| | - Atta Ur Rehman
- Department of Zoology, Faculty of Biological and Health Sciences, Hazara University, Mansehra, Khyber Pakhtunkhwa, Pakistan
| |
Collapse
|
2
|
Gupta S, Gupta D, Bhatnagar S. Analysis of SARS-CoV-2 genome evolutionary patterns. Microbiol Spectr 2024; 12:e0265423. [PMID: 38197644 PMCID: PMC10846092 DOI: 10.1128/spectrum.02654-23] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 11/20/2023] [Indexed: 01/11/2024] Open
Abstract
The spread of SARS-CoV-2 virus accompanied by public availability of abundant sequence data provides a window for the determination of viral evolutionary patterns. In this study, SARS-CoV-2 genome sequences were collected from seven countries in the period January 2020-December 2022. The sequences were classified into three phases, namely, pre-vaccination, post-vaccination, and recent period. Comparison was performed between these phases based on parameters like mutation rates, selection pressure (dN/dS ratio), and transition to transversion ratios (Ti/Tv). Similar comparisons were performed among SARS-CoV-2 variants. Statistical significance was tested using Graphpad unpaired t-test. The analysis showed an increase in the percent genomic mutation rates post-vaccination and in recent periods across all countries from the pre-vaccination sequences. Mutation rates were highest in NSP3, S, N, and NSP12b before and increased further after vaccination. NSP4 showed the largest change in mutation rates after vaccination. The dN/dS ratios showed purifying selection that shifted toward neutral selection after vaccination. N, ORF8, ORF3a, and ORF10 were under highest positive selection before vaccination. Shift toward neutral selection was driven by E, NSP3, and ORF7a in the after vaccination set. In recent sequences, the largest dN/dS change was observed in E, NSP1, and NSP13. The Ti/Tv ratios decreased with time. C→U and G→U were the most frequent transitions and transversions. However, U→G was the most frequent transversion in recent period. The Omicron variant had the highest genomic mutation rates, while Delta showed the highest dN/dS ratio. Protein-wise dN/dS ratio was also seen to vary across the different variants.IMPORTANCETo the best of our knowledge, there exists no other large-scale study of the genomic and protein-wise mutation patterns during the time course of evolution in different countries. Analyzing the SARS-CoV-2 evolutionary patterns in view of the varying spatial, temporal, and biological signals is important for diagnostics, therapeutics, and pharmacovigilance of SARS-CoV-2.
Collapse
Affiliation(s)
- Shubhangi Gupta
- Department of Biological Sciences and Engineering, Computational and Structural Biology Laboratory, Netaji Subhas University of Technology, Dwarka, New Delhi, India
| | - Deepanshu Gupta
- Division of Biotechnology, Computational and Structural Biology Laboratory, Netaji Subhas Institute of Technology, Dwarka, New Delhi, India
| | - Sonika Bhatnagar
- Department of Biological Sciences and Engineering, Computational and Structural Biology Laboratory, Netaji Subhas University of Technology, Dwarka, New Delhi, India
- Division of Biotechnology, Computational and Structural Biology Laboratory, Netaji Subhas Institute of Technology, Dwarka, New Delhi, India
| |
Collapse
|
3
|
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.
Collapse
Affiliation(s)
- Yingguang Liu
- Molecular and Cellular Sciences, Liberty University College of Osteopathic Medicine, Lynchburg, USA
| |
Collapse
|
4
|
Chakraborty C, Bhattacharya M, Sharma AR, Dhama K, Lee SS. Continent-wide evolutionary trends of emerging SARS-CoV-2 variants: dynamic profiles from Alpha to Omicron. GeroScience 2022; 44:2371-2392. [PMID: 35831773 PMCID: PMC9281186 DOI: 10.1007/s11357-022-00619-y] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 06/27/2022] [Indexed: 01/06/2023] Open
Abstract
The ongoing SARS-CoV-2 evolution process has generated several variants due to its continuous mutations, making pandemics more critical. The present study illustrates SARS-CoV-2 evolution and its emerging mutations in five directions. First, the significant mutations in the genome and S-glycoprotein were analyzed in different variants. Three linear models were developed with the regression line to depict the mutational load for S-glycoprotein, total genome excluding S-glycoprotein, and whole genome. Second, the continent-wide evolution of SARS-CoV-2 and its variants with their clades and divergence were evaluated. It showed the region-wise evolution of the SARS-CoV-2 variants and their clustering event. The major clades for each variant were identified. One example is clade 21K, a major clade of the Omicron variant. Third, lineage dynamics and comparison between SARS-CoV-2 lineages across different countries are also illustrated, demonstrating dominant variants in various countries over time. Fourth, gene-wise mutation patterns and genetic variability of SARS-CoV-2 variants across various countries are illustrated. High mutation patterns were found in the ORF10, ORF6, S, and low mutation pattern E genes. Finally, emerging AA point mutations (T478K, L452R, N501Y, S477N, E484A, Q498R, and Y505H), their frequencies, and country-wise occurrence were identified, and the highest event of two mutations (T478K and L452R) was observed.
Collapse
Affiliation(s)
- Chiranjib Chakraborty
- Department of Biotechnology, School of Life Science and Biotechnology, Adamas University, Kolkata, West Bengal 700126 India
| | - Manojit Bhattacharya
- Department of Zoology, Fakir Mohan University, Vyasa Vihar, Balasore, 756020 Odisha India
| | - Ashish Ranjan Sharma
- Institute for Skeletal Aging & Orthopedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Chuncheon-si, 24252 Gangwon-do Republic of Korea
| | - Kuldeep Dhama
- Division of Pathology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly, 243122 Uttar Pradesh India
| | - Sang-Soo Lee
- Institute for Skeletal Aging & Orthopedic Surgery, Hallym University-Chuncheon Sacred Heart Hospital, Chuncheon-si, 24252 Gangwon-do Republic of Korea
| |
Collapse
|
5
|
Yépez Y, Marcano-Ruiz M, Bezerra RS, Fam B, Ximenez JPB, Silva WA, Bortolini MC. Evolutionary history of the SARS-CoV-2 Gamma variant of concern (P.1): a perfect storm. Genet Mol Biol 2022; 45:e20210309. [PMID: 35266951 PMCID: PMC8908351 DOI: 10.1590/1678-4685-gmb-2021-0309] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 12/29/2021] [Indexed: 12/11/2022] Open
Abstract
Our goal was to describe in more detail the evolutionary history of Gamma and two derived lineages (P.1.1 and P.1.2), which are part of the arms race that SARS-CoV-2 wages with its host. A total of 4,977 sequences of the Gamma strain of SARS-CoV-2 from Brazil were analyzed. We detected 194 sites under positive selection in 12 genes/ORFs: Spike, N, M, E, ORF1a, ORF1b, ORF3, ORF6, ORF7a, ORF7b, ORF8, and ORF10. Some diagnostic sites for Gamma lacked a signature of positive selection in our study, but these were not fixed, apparently escaping the action of purifying selection. Our network analyses revealed branches leading to expanding haplotypes with sites under selection only detected when P.1.1 and P.1.2 were considered. The P.1.2 exclusive haplotype H_5 originated from a non-synonymous mutational step (H3509Y) in H_1 of ORF1a. The selected allele, 3509Y, represents an adaptive novelty involving ORF1a of P.1. Finally, we discuss how phenomena such as epistasis and antagonistic pleiotropy could limit the emergence of new alleles (and combinations thereof) in SARS-COV-2 lineages, maintaining infectivity in humans, while providing rapid response capabilities to face the arms race triggered by host immuneresponses.
Collapse
Affiliation(s)
- Yuri Yépez
- Universidade Federal do Rio Grande do Sul, Departamento de Genética,
Laboratório de Evolução Humana e Molecular, Porto Alegre, RS, Brazil
| | - Mariana Marcano-Ruiz
- Universidade Federal do Rio Grande do Sul, Departamento de Genética,
Laboratório de Evolução Humana e Molecular, Porto Alegre, RS, Brazil
| | - Rafael S Bezerra
- Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto,
Departamento de Genética, Ribeirão Preto, SP, Brazil
| | - Bibiana Fam
- Universidade Federal do Rio Grande do Sul, Departamento de Genética,
Laboratório de Evolução Humana e Molecular, Porto Alegre, RS, Brazil
| | - João PB Ximenez
- Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto,
Departamento de Genética, Ribeirão Preto, SP, Brazil
| | - Wilson A Silva
- Universidade de São Paulo, Faculdade de Medicina de Ribeirão Preto,
Departamento de Genética, Ribeirão Preto, SP, Brazil
- Instituto de Pesquisa do Câncer de Guarapuava, Guarapuava, PR,
Brazil
| | - Maria Cátira Bortolini
- Universidade Federal do Rio Grande do Sul, Departamento de Genética,
Laboratório de Evolução Humana e Molecular, Porto Alegre, RS, Brazil
| |
Collapse
|