1
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Lopes R, Pham K, Klaassen F, Chitwood MH, Hahn AM, Redmond S, Swartwood NA, Salomon JA, Menzies NA, Cohen T, Grubaugh ND. Combining genomic data and infection estimates to characterize the complex dynamics of SARS-CoV-2 Omicron variants in the US. Cell Rep 2024; 43:114451. [PMID: 38970788 DOI: 10.1016/j.celrep.2024.114451] [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: 01/18/2024] [Revised: 05/03/2024] [Accepted: 06/20/2024] [Indexed: 07/08/2024] Open
Abstract
Omicron surged as a variant of concern in late 2021. Several distinct Omicron variants appeared and overtook each other. We combined variant frequencies and infection estimates from a nowcasting model for each US state to estimate variant-specific infections, attack rates, and effective reproduction numbers (Rt). BA.1 rapidly emerged, and we estimate that it infected 47.7% of the US population before it was replaced by BA.2. We estimate that BA.5 infected 35.7% of the US population, persisting in circulation for nearly 6 months. Other variants-BA.2, BA.4, and XBB-together infected 30.7% of the US population. We found a positive correlation between the state-level BA.1 attack rate and social vulnerability and a negative correlation between the BA.1 and BA.2 attack rates. Our findings illustrate the complex interplay between viral evolution, population susceptibility, and social factors during the Omicron emergence in the US.
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Affiliation(s)
- Rafael Lopes
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
| | - Kien Pham
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA
| | - Fayette Klaassen
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Melanie H Chitwood
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA
| | - Anne M Hahn
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA
| | - Seth Redmond
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA
| | - Nicole A Swartwood
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Joshua A Salomon
- Department of Health Policy, Stanford University School of Medicine, Stanford, CA, USA
| | - Nicolas A Menzies
- Department of Global Health and Population, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Ted Cohen
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA.
| | - Nathan D Grubaugh
- Department of Epidemiology of Microbial Diseases and Public Health Modeling Unit, Yale School of Public Health, New Haven, CT, USA; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA.
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2
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Xiao B, Wu L, Sun Q, Shu C, Hu S. Dynamic analysis of SARS-CoV-2 evolution based on different countries. Gene 2024; 916:148426. [PMID: 38575101 DOI: 10.1016/j.gene.2024.148426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 03/18/2024] [Accepted: 04/01/2024] [Indexed: 04/06/2024]
Abstract
Since late 2019, COVID-19 has significantly impacted the world. Understanding the evolution of SARS-CoV-2 is crucial for protecting against future infectious pathogens. In this study, we conducted a comprehensive chronological analysis of SARS-CoV-2 evolution by examining mutation prevalence from the source countries of VOCs: United Kingdom, India, Brazil, South Africa, plus two countries: United States, Russia, utilizing genomic sequences from GISAID. Our methodological approach involved large-scale genomic sequence alignment using MAFFT, Python-based data processing on a high-performance computing platform, and advanced statistical methods the Maximal Information Coefficient (MIC), and also Long Short-Term Memory (LSTM) models for correlation analysis. Our findings elucidate the dynamics of SARS-CoV-2 evolution, highlighting the virus's changing behaviour over various pandemic stages. Key results include the discovery of three temporal mutation patterns-lineage distinct, long-span, and competitive mutations-with varying levels of impact on the virus. Notably, we observed a convergence of advantageous mutations in the spike protein, especially in the later stages of the pandemic, indicating a substantial evolutionary pressure on the virus. One of the most significant revelations is the predominant role of natural immunity over vaccination-induced immunity in driving these evolutionary changes. This emphasizes the critical need for regular vaccine updates to maintain efficacy against evolving strains. In conclusion, our study not only sheds light on the evolutionary trajectory of SARS-CoV-2 but also underscores the urgency for robust, continuous global data collection and sharing. It highlights the necessity for rapid adaptations in medical countermeasures, including vaccine development, to stay ahead of pathogen evolution. This research provides valuable insights for future pandemic preparedness and response strategies.
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Affiliation(s)
- Binghan Xiao
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing, China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing, China
| | - Linhuan Wu
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; Chinese National Microbiology Data Center (NMDC), Beijing 100101, China
| | - Qinglan Sun
- Microbial Resource and Big Data Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; Chinese National Microbiology Data Center (NMDC), Beijing 100101, China
| | - Chang Shu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.
| | - Songnian Hu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing, China.
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3
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Lucaci AG, Pond SLK. AOC: Analysis of Orthologous Collections - an application for the characterization of natural selection in protein-coding sequences. ARXIV 2024:arXiv:2406.09522v1. [PMID: 38947939 PMCID: PMC11213150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Motivation Modern molecular sequence analysis increasingly relies on automated and robust software tools for interpretation, annotation, and biological insight. The Analysis of Orthologous Collections (AOC) application automates the identification of genomic sites and species/lineages influenced by natural selection in coding sequence analysis. AOC quantifies different types of selection: negative, diversifying or directional positive, or differential selection between groups of branches. We include all steps necessary to go from unaligned homologous sequences to complete results and interactive visualizations that are designed to aid in the useful interpretation and contextualization. Results We are motivated by a desire to make evolutionary analyses as simple as possible, and to close the disparity in the literature between genes which draw a significant amount of interest and those that are largely overlooked and underexplored. We believe that such underappreciated and understudied genetic datasets can hold rich biological information and offer substantial insights into the diverse patterns and processes of evolution, especially if domain experts are able to perform the analyses themselves. Availability and implementation A Snakemake [Mölder et al., 2021] application implementation is publicly available on GitHub at https://github.com/aglucaci/AnalysisOfOrthologousCollections and is accompanied by software documentation and a tutorial.
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Affiliation(s)
- Alexander G Lucaci
- Department of Physiology and Biophysics, Weill Cornell Medicine, Cornell University, New York, NY 10021, USA
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA
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4
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Rojas Chávez RA, Fili M, Han C, Rahman SA, Bicar IGL, Gregory S, Helverson A, Hu G, Darbro BW, Das J, Brown GD, Haim H. Mapping the Evolutionary Space of SARS-CoV-2 Variants to Anticipate Emergence of Subvariants Resistant to COVID-19 Therapeutics. PLoS Comput Biol 2024; 20:e1012215. [PMID: 38857308 PMCID: PMC11192331 DOI: 10.1371/journal.pcbi.1012215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 06/21/2024] [Accepted: 05/30/2024] [Indexed: 06/12/2024] Open
Abstract
New sublineages of SARS-CoV-2 variants-of-concern (VOCs) continuously emerge with mutations in the spike glycoprotein. In most cases, the sublineage-defining mutations vary between the VOCs. It is unclear whether these differences reflect lineage-specific likelihoods for mutations at each spike position or the stochastic nature of their appearance. Here we show that SARS-CoV-2 lineages have distinct evolutionary spaces (a probabilistic definition of the sequence states that can be occupied by expanding virus subpopulations). This space can be accurately inferred from the patterns of amino acid variability at the whole-protein level. Robust networks of co-variable sites identify the highest-likelihood mutations in new VOC sublineages and predict remarkably well the emergence of subvariants with resistance mutations to COVID-19 therapeutics. Our studies reveal the contribution of low frequency variant patterns at heterologous sites across the protein to accurate prediction of the changes at each position of interest.
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Affiliation(s)
| | - Mohammad Fili
- Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, Iowa, United States of America
| | - Changze Han
- Department of Microbiology and Immunology, The University of Iowa, Iowa City, Iowa, United States of America
| | - Syed A. Rahman
- Center for Systems Immunology, Departments of Immunology and Computational & Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Isaiah G. L. Bicar
- Department of Microbiology and Immunology, The University of Iowa, Iowa City, Iowa, United States of America
| | - Sullivan Gregory
- Department of Microbiology and Immunology, The University of Iowa, Iowa City, Iowa, United States of America
| | - Annika Helverson
- Department of Biostatistics, College of Public Health, The University of Iowa, Iowa City, Iowa, United States of America
| | - Guiping Hu
- Department of Industrial and Manufacturing Systems Engineering, Iowa State University, Ames, Iowa, United States of America
| | - Benjamin W. Darbro
- Department of Pediatrics, University of Iowa Hospitals and Clinics, Iowa City, Iowa, United States of America
| | - Jishnu Das
- Center for Systems Immunology, Departments of Immunology and Computational & Systems Biology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, United States of America
| | - Grant D. Brown
- Department of Biostatistics, College of Public Health, The University of Iowa, Iowa City, Iowa, United States of America
| | - Hillel Haim
- Department of Microbiology and Immunology, The University of Iowa, Iowa City, Iowa, United States of America
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5
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Chen Z, Li Q, Xu Y, Tian D, Zhang M, Guo Y, Min X, Xiao D. Study on the detection rate, genetic polymorphism, viral load, persistent infection capacity, and pathogenicity of human papillomavirus type 81. J Med Virol 2024; 96:e29753. [PMID: 38895800 DOI: 10.1002/jmv.29753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2024] [Revised: 05/27/2024] [Accepted: 06/09/2024] [Indexed: 06/21/2024]
Abstract
Human papillomavirus (HPV) type 81 has recently become one of the most common low-risk HPV types; however, literature focusing on it is limited. This study aimed to analyze the reasons for the increased detection rate of HPV81 and investigate its evolving pathogenicity. We analyzed the detection rates and trends of HPV81 in 229 061 exfoliated cervical cell samples collected from 2014 to 2023; collected samples of HPV81 single infections from two different time periods; and analyzed the allele frequencies, positive selection, viral load, persistent infection capacity, and pathogenicity of E6 and E7 genotypes. We found that the detection rate of HPV81 ranked first among the low-risk types in exfoliated cervical cells and exhibited a significantly increasing trend (p < 0.001). The frequency of the E6 prototype allele of HPV81 (n = 317) was significantly increased (p = 0.018) and demonstrated the strongest adaptive capacity. The viral load and persistent infection capacity of the E6 prototype were significantly higher than those of the mutants, thus serving as key drivers for increasing the detection rate of HPV81 and enhancing its pathogenicity. The viral load was positively correlated with persistent infection capacity and pathogenicity. Persistent infection was a crucial factor in the pathogenicity of HPV81. Successful adaptive evolution of HPV81 is accompanied by enhanced pathogenicity.
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Affiliation(s)
- Zuyi Chen
- Department of Laboratory Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- School of Laboratory Medicine, Zunyi Medical University, Zunyi, China
| | - Qiongyao Li
- Department of Information, Affiliated Hospital of Zunyi Medical University, Zunyi, China
| | - Yajing Xu
- Department of Laboratory Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- School of Laboratory Medicine, Zunyi Medical University, Zunyi, China
| | - Di Tian
- Department of Laboratory Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- School of Laboratory Medicine, Zunyi Medical University, Zunyi, China
| | - Mingjing Zhang
- Department of Laboratory Medicine, Chongqing Tongnan Women and Children Health Care Hospital, Chongqing, China
| | - Yongmei Guo
- Department of Laboratory Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- School of Laboratory Medicine, Zunyi Medical University, Zunyi, China
| | - Xun Min
- Department of Laboratory Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- School of Laboratory Medicine, Zunyi Medical University, Zunyi, China
| | - Daimin Xiao
- Department of Laboratory Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, China
- School of Laboratory Medicine, Zunyi Medical University, Zunyi, China
- Department of Laboratory Medicine, Kweichow Moutai Hospital, Renhuai, Guizhou, China
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6
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Xue S, Han Y, Wu F, Wang Q. Mutations in the SARS-CoV-2 spike receptor binding domain and their delicate balance between ACE2 affinity and antibody evasion. Protein Cell 2024; 15:403-418. [PMID: 38442025 PMCID: PMC11131022 DOI: 10.1093/procel/pwae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Accepted: 02/05/2024] [Indexed: 03/07/2024] Open
Abstract
Intensive selection pressure constrains the evolutionary trajectory of SARS-CoV-2 genomes and results in various novel variants with distinct mutation profiles. Point mutations, particularly those within the receptor binding domain (RBD) of SARS-CoV-2 spike (S) protein, lead to the functional alteration in both receptor engagement and monoclonal antibody (mAb) recognition. Here, we review the data of the RBD point mutations possessed by major SARS-CoV-2 variants and discuss their individual effects on ACE2 affinity and immune evasion. Many single amino acid substitutions within RBD epitopes crucial for the antibody evasion capacity may conversely weaken ACE2 binding affinity. However, this weakened effect could be largely compensated by specific epistatic mutations, such as N501Y, thus maintaining the overall ACE2 affinity for the spike protein of all major variants. The predominant direction of SARS-CoV-2 evolution lies neither in promoting ACE2 affinity nor evading mAb neutralization but in maintaining a delicate balance between these two dimensions. Together, this review interprets how RBD mutations efficiently resist antibody neutralization and meanwhile how the affinity between ACE2 and spike protein is maintained, emphasizing the significance of comprehensive assessment of spike mutations.
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Affiliation(s)
- Song Xue
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Frontiers Science Center of Pathogenic Microorganisms and Infection, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Yuru Han
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Frontiers Science Center of Pathogenic Microorganisms and Infection, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Fan Wu
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Frontiers Science Center of Pathogenic Microorganisms and Infection, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Qiao Wang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Frontiers Science Center of Pathogenic Microorganisms and Infection, School of Basic Medical Sciences, Shanghai Medical College, Fudan University, Shanghai 200032, China
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7
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Silva T, Oliveira E, Oliveira A, Menezes A, Jeremias WDJ, Grenfell RF, Monte-Neto RLD, Pascoal-Xavier MA, Campos MA, Fernandes G, Alves P. Enhancing the epidemiological surveillance of SARS-CoV-2 using Sanger sequencing to identify circulating variants and recombinants. Braz J Microbiol 2024:10.1007/s42770-024-01387-x. [PMID: 38802687 DOI: 10.1007/s42770-024-01387-x] [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: 12/12/2023] [Accepted: 05/13/2024] [Indexed: 05/29/2024] Open
Abstract
Since the emergence of SARS-CoV-2 in December 2019, more than 12,000 mutations in the virus have been identified. These could cause changes in viral characteristics and directly impact global public health. The emergence of variants is a great concern due to the chance of increased transmissibility and infectivity. Sequencing for surveillance and monitoring circulating strains is extremely necessary as the early identification of new variants allows public health agencies to make faster and more effective decisions to contain the spread of the virus. In the present study, we identified circulating variants in samples collected in Belo Horizonte, Brazil, and detected a recombinant lineage using the Sanger method. The identification of lineages was done through gene amplification of SARS-CoV-2 by Reverse Transcription-Polymerase Chain Reaction (RT-PCR). By using these specific fragments, we were able to differentiate one variant of interest and five circulating variants of concern. We were also able to detect recombinants. Randomly selected samples were sequenced by either Sanger or Next Generation Sequencing (NGS). Our findings validate the effectiveness of Sanger sequencing as a powerful tool for monitoring variants. It is easy to perform and allows the analysis of a larger number of samples in countries that cannot afford NGS.
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Affiliation(s)
- Thaís Silva
- Instituto René Rachou, Fundação Oswaldo Cruz, 1715, Augusto de Lima Avenue, Belo Horizonte, Minas Gerais, 30190-002, Brazil
| | - Eneida Oliveira
- Secretaria Municipal de Saúde, 2336, Afonso Pena Avenue, Belo Horizonte, Minas Gerais, 30130-007, Brazil
| | - Alana Oliveira
- Instituto René Rachou, Fundação Oswaldo Cruz, 1715, Augusto de Lima Avenue, Belo Horizonte, Minas Gerais, 30190-002, Brazil
| | - André Menezes
- Secretaria Municipal de Saúde, 2336, Afonso Pena Avenue, Belo Horizonte, Minas Gerais, 30130-007, Brazil
| | - Wander de Jesus Jeremias
- Department of Pharmacy, Federal University of Ouro Preto (UFOP), 27, Nine Street, Ouro Preto, Minas Gerais, 35400-000, Brazil
| | - Rafaella Fq Grenfell
- Instituto René Rachou, Fundação Oswaldo Cruz, 1715, Augusto de Lima Avenue, Belo Horizonte, Minas Gerais, 30190-002, Brazil
- Department of Infectious Diseases, College of Veterinary Medicine, University of Georgia, 501 D.W. Brooks Drive, Athens, GA, 30602, USA
| | - Rubens Lima do Monte-Neto
- Instituto René Rachou, Fundação Oswaldo Cruz, 1715, Augusto de Lima Avenue, Belo Horizonte, Minas Gerais, 30190-002, Brazil
| | - Marcelo A Pascoal-Xavier
- Instituto René Rachou, Fundação Oswaldo Cruz, 1715, Augusto de Lima Avenue, Belo Horizonte, Minas Gerais, 30190-002, Brazil
- Department of Anatomic Pathology, College of Medicine, Federal University of Minas Gerais, 6627, Presidente Antônio Carlos Avenue, Belo Horizonte, Minas Gerais, 31270-901, Brazil
| | - Marco A Campos
- Instituto René Rachou, Fundação Oswaldo Cruz, 1715, Augusto de Lima Avenue, Belo Horizonte, Minas Gerais, 30190-002, Brazil
| | - Gabriel Fernandes
- Instituto René Rachou, Fundação Oswaldo Cruz, 1715, Augusto de Lima Avenue, Belo Horizonte, Minas Gerais, 30190-002, Brazil
| | - Pedro Alves
- Instituto René Rachou, Fundação Oswaldo Cruz, 1715, Augusto de Lima Avenue, Belo Horizonte, Minas Gerais, 30190-002, Brazil.
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8
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Sarkar A, Ghosh TA, Bandyopadhyay B, Maiti S, Panja AS. Prediction of Prospective Mutational Landscape of SARS-CoV-2 Spike ssRNA and Evolutionary Basis of Its Host Interaction. Mol Biotechnol 2024:10.1007/s12033-024-01146-1. [PMID: 38619800 DOI: 10.1007/s12033-024-01146-1] [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: 01/23/2024] [Accepted: 03/14/2024] [Indexed: 04/16/2024]
Abstract
Booster doses are crucial against severe COVID-19, as rapid virus mutations and variant emergence prolong the pandemic crisis. The virus's quick evolution, short generation-time, and adaptive changes impact virulence and evolvability, helping predictions about variant of concerns' (VOCs') landscapes. Here, in this study, we used a new computational algorithm, to predict the mutational pattern in SARS-CoV-2 ssRNA, proteomics, structural identification, mutation stability, and functional correlation, as well as immune escape mechanisms. Interestingly, the sequence diversity of SARS Coronavirus-2 has demonstrated a predominance of G- > A and C- > U substitutions. The best validation statistics are explored here in seven homologous models of the expected mutant SARS-CoV-2 spike ssRNA and employed for hACE2 and IgG interactions. The interactome profile of SARS-CoV-2 spike with hACE2 and IgG revealed a strong correlation between phylogeny and divergence time. The systematic adaptation of SARS-CoV-2 spike ssRNA influences infectivity and immune escape. Data suggest higher propensity of Adenine rich sequence promotes MHC system avoidance, preferred by A-rich codons. Phylogenetic data revealed the evolution of SARS-CoV-2 lineages' epidemiology. Our findings may unveil processes governing the genesis of immune-resistant variants, prompting a critical reassessment of the coronavirus mutation rate and exploration of hypotheses beyond mechanical aspects.
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Affiliation(s)
- Aniket Sarkar
- Post Graduate Department of Biotechnology, Oriental Institute of Science and Technology, Vidyasagar University, Midnapore, West Bengal, 721102, India
| | - Trijit Arka Ghosh
- Department of Computer Application, Burdwan Institute of Management and Computer Science, The University of Burdwan, Dewandighi, Burdwan, West Bengal, 713102, India
| | - Bidyut Bandyopadhyay
- Post Graduate Department of Biotechnology, Oriental Institute of Science and Technology, Vidyasagar University, Midnapore, West Bengal, 721102, India
| | - Smarajit Maiti
- Department of Medical Laboratory Technology, Haldia Institute of Health Sciences, ICARE Complex, Haldia, West Bengal, 721657, India
| | - Anindya Sundar Panja
- Post Graduate Department of Biotechnology, Molecular Informatics Laboratory, Oriental Institute of Science and Technology, Vidyasagar University, Midnapore, West Bengal, 721102, India.
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9
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Langedijk AC, Vrancken B, Lebbink RJ, Wilkins D, Kelly EJ, Baraldi E, Mascareñas de Los Santos AH, Danilenko DM, Choi EH, Palomino MA, Chi H, Keller C, Cohen R, Papenburg J, Pernica J, Greenough A, Richmond P, Martinón-Torres F, Heikkinen T, Stein RT, Hosoya M, Nunes MC, Verwey C, Evers A, Kragten-Tabatabaie L, Suchard MA, Kosakovsky Pond SL, Poletto C, Colizza V, Lemey P, Bont LJ. The genomic evolutionary dynamics and global circulation patterns of respiratory syncytial virus. Nat Commun 2024; 15:3083. [PMID: 38600104 PMCID: PMC11006891 DOI: 10.1038/s41467-024-47118-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 03/14/2024] [Indexed: 04/12/2024] Open
Abstract
Respiratory syncytial virus (RSV) is a leading cause of acute lower respiratory tract infection in young children and the second leading cause of infant death worldwide. While global circulation has been extensively studied for respiratory viruses such as seasonal influenza, and more recently also in great detail for SARS-CoV-2, a lack of global multi-annual sampling of complete RSV genomes limits our understanding of RSV molecular epidemiology. Here, we capitalise on the genomic surveillance by the INFORM-RSV study and apply phylodynamic approaches to uncover how selection and neutral epidemiological processes shape RSV diversity. Using complete viral genome sequences, we show similar patterns of site-specific diversifying selection among RSVA and RSVB and recover the imprint of non-neutral epidemic processes on their genealogies. Using a phylogeographic approach, we provide evidence for air travel governing the global patterns of RSVA and RSVB spread, which results in a considerable degree of phylogenetic mixing across countries. Our findings highlight the potential of systematic global RSV genomic surveillance for transforming our understanding of global RSV spread.
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Affiliation(s)
- Annefleur C Langedijk
- Department of Paediatric Immunology and Infectious Diseases, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Lundlaan 6, 3584 EA, Utrecht, the Netherlands
| | - Bram Vrancken
- Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical and Epidemiological Virology, Herestraat 49, 3000, Leuven, Belgium
- Spatial Epidemiology Lab (SpELL), Université Libre de Bruxelles, Bruxelles, Belgium
| | - Robert Jan Lebbink
- Department of Medical Microbiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands
| | - Deidre Wilkins
- Translational Medicine, Vaccines & Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, 1 MedImmune Way, Gaithersburg, MD, USA
| | - Elizabeth J Kelly
- Translational Medicine, Vaccines & Immune Therapies, BioPharmaceuticals R&D, AstraZeneca, 1 MedImmune Way, Gaithersburg, MD, USA
| | - Eugenio Baraldi
- Department of Woman's and Child's Health, University Hospital of Padova, Padova, Italy
- ReSViNET Foundation, Zeist, the Netherlands
- Institute of Pediatric Research "Città della Speranza", Padova, Italy
| | | | - Daria M Danilenko
- Smorodintsev Research Institute of Influenza, St. Petersburg, Russia
| | - Eun Hwa Choi
- Seoul National University Children's Hospital, Seoul, South Korea
| | | | - Hsin Chi
- MacKay Children's Hospital, New Taipei, Taiwan, ROC
| | - Christian Keller
- Institute of Virology, University Hospital Giessen and Marburg, Marburg, Germany
| | | | | | | | - Anne Greenough
- ReSViNET Foundation, Zeist, the Netherlands
- King's College London, London, UK
| | | | - Federico Martinón-Torres
- ReSViNET Foundation, Zeist, the Netherlands
- Hospital Clínico Universitario de Santiago, Galicia, Spain
| | - Terho Heikkinen
- ReSViNET Foundation, Zeist, the Netherlands
- University of Turku and Turku University Hospital, Turku, Finland
| | - Renato T Stein
- ReSViNET Foundation, Zeist, the Netherlands
- Pontificia Universidade Catolica de Rio Grande do Sul, Porto Alegre, Brazil
| | - Mitsuaki Hosoya
- Fukushima Medical University School of Medicine, Fukushima, Japan
| | - Marta C Nunes
- ReSViNET Foundation, Zeist, the Netherlands
- Department of Paediatrics and Child Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- South African Medical Research Council, Vaccines & Infectious Diseases Analytics Research Unit, and Department of Science and Technology/National Research Foundation, South African Research Chair Initiative in Vaccine Preventable Diseases, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Charl Verwey
- Department of Paediatrics and Child Health, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Hospices Civils de Lyon and the Centre International de Recherche en Infectiologie (CIRI) Inserm U1111, CNRS UMR5308, ENS de Lyon, UCBL1, Lyon, France
| | - Anouk Evers
- Department of Medical Microbiology, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX, Utrecht, the Netherlands
| | | | - Marc A Suchard
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Department of Biostatistics, Jonathan and Karin Fielding School of Public Health, University of California, Los Angeles, CA, 90095, USA
- Department of Biomathematics, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Sergei L Kosakovsky Pond
- Institute for Genomics and Evolutionary Medicine, Department of Biology, Temple University, 801 N Broad St, Philadelphia, PA, 19122, USA
| | - Chiara Poletto
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, F75012, Paris, France
| | - Vittoria Colizza
- INSERM, Sorbonne Université, Institut Pierre Louis d'Epidémiologie et de Santé Publique IPLESP, F75012, Paris, France
| | - Philippe Lemey
- Department of Microbiology, Immunology and Transplantation, Laboratory of Clinical and Epidemiological Virology, Herestraat 49, 3000, Leuven, Belgium
| | - Louis J Bont
- Department of Paediatric Immunology and Infectious Diseases, Wilhelmina Children's Hospital, University Medical Centre Utrecht, Lundlaan 6, 3584 EA, Utrecht, the Netherlands.
- ReSViNET Foundation, Zeist, the Netherlands.
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10
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Morel M, Zhukova A, Lemoine F, Gascuel O. Accurate Detection of Convergent Mutations in Large Protein Alignments With ConDor. Genome Biol Evol 2024; 16:evae040. [PMID: 38451738 PMCID: PMC10986858 DOI: 10.1093/gbe/evae040] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 01/30/2024] [Accepted: 02/22/2024] [Indexed: 03/09/2024] Open
Abstract
Evolutionary convergences are observed at all levels, from phenotype to DNA and protein sequences, and changes at these different levels tend to be correlated. Notably, convergent mutations can lead to convergent changes in phenotype, such as changes in metabolism, drug resistance, and other adaptations to changing environments. We propose a two-component approach to detect mutations subject to convergent evolution in protein alignments. The "Emergence" component selects mutations that emerge more often than expected, while the "Correlation" component selects mutations that correlate with the convergent phenotype under study. With regard to Emergence, a phylogeny deduced from the alignment is provided by the user and is used to simulate the evolution of each alignment position. These simulations allow us to estimate the expected number of mutations in a neutral model, which is compared to the observed number of mutations in the data studied. In Correlation, a comparative phylogenetic approach, is used to measure whether the presence of each of the observed mutations is correlated with the convergent phenotype. Each component can be used on its own, for example Emergence when no phenotype is available. Our method is implemented in a standalone workflow and a webserver, called ConDor. We evaluate the properties of ConDor using simulated data, and we apply it to three real datasets: sedge PEPC proteins, HIV reverse transcriptase, and fish rhodopsin. The results show that the two components of ConDor complement each other, with an overall accuracy that compares favorably to other available tools, especially on large datasets.
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Affiliation(s)
- Marie Morel
- Institut Pasteur, Université Paris Cité, Unité Bioinformatique Evolutive, Paris, France
- Université Claude Bernard Lyon 1, LBBE, UMR 5558, CNRS, VAS, Villeurbanne, 69100, France
| | - Anna Zhukova
- Institut Pasteur, Université Paris Cité, Unité Bioinformatique Evolutive, Paris, France
- Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, Paris, France
| | - Frédéric Lemoine
- Institut Pasteur, Université Paris Cité, Unité Bioinformatique Evolutive, Paris, France
- Institut Pasteur, Université Paris Cité, Bioinformatics and Biostatistics Hub, Paris, France
- Institut Pasteur, Université Paris Cité, CNR Virus Des Infections Respiratoires, Paris, France
| | - Olivier Gascuel
- Institut Pasteur, Université Paris Cité, Unité Bioinformatique Evolutive, Paris, France
- Institut de Systématique, Evolution, Biodiversité (UMR 7205—CNRS, Muséum National d’Histoire Naturelle, SU, EPHE, UA), Paris, France
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11
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Zech F, Jung C, Jacob T, Kirchhoff F. Causes and Consequences of Coronavirus Spike Protein Variability. Viruses 2024; 16:177. [PMID: 38399953 PMCID: PMC10892391 DOI: 10.3390/v16020177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 01/20/2024] [Accepted: 01/23/2024] [Indexed: 02/25/2024] Open
Abstract
Coronaviruses are a large family of enveloped RNA viruses found in numerous animal species. They are well known for their ability to cross species barriers and have been transmitted from bats or intermediate hosts to humans on several occasions. Four of the seven human coronaviruses (hCoVs) are responsible for approximately 20% of common colds (hCoV-229E, -NL63, -OC43, -HKU1). Two others (SARS-CoV-1 and MERS-CoV) cause severe and frequently lethal respiratory syndromes but have only spread to very limited extents in the human population. In contrast the most recent human hCoV, SARS-CoV-2, while exhibiting intermediate pathogenicity, has a profound impact on public health due to its enormous spread. In this review, we discuss which initial features of the SARS-CoV-2 Spike protein and subsequent adaptations to the new human host may have helped this pathogen to cause the COVID-19 pandemic. Our focus is on host forces driving changes in the Spike protein and their consequences for virus infectivity, pathogenicity, immune evasion and resistance to preventive or therapeutic agents. In addition, we briefly address the significance and perspectives of broad-spectrum therapeutics and vaccines.
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Affiliation(s)
- Fabian Zech
- Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany
| | - Christoph Jung
- Institute of Electrochemistry, Ulm University, 89081 Ulm, Germany; (C.J.); (T.J.)
- Helmholtz-Institute Ulm (HIU) Electrochemical Energy Storage, 89081 Ulm, Germany
- Karlsruhe Institute of Technology (KIT), 76021 Karlsruhe, Germany
| | - Timo Jacob
- Institute of Electrochemistry, Ulm University, 89081 Ulm, Germany; (C.J.); (T.J.)
- Helmholtz-Institute Ulm (HIU) Electrochemical Energy Storage, 89081 Ulm, Germany
- Karlsruhe Institute of Technology (KIT), 76021 Karlsruhe, Germany
| | - Frank Kirchhoff
- Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany
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12
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Pérez-Massón B, Quintana-Pérez Y, Tundidor Y, Pérez-Martínez D, Castro-Martínez C, Pupo-Meriño M, Orosa I, Relova-Hernández E, Villegas R, Guirola O, Rojas G. Studying SARS-CoV-2 interactions using phage-displayed receptor binding domain as a model protein. Sci Rep 2024; 14:712. [PMID: 38184672 PMCID: PMC10771503 DOI: 10.1038/s41598-023-50450-4] [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: 09/06/2023] [Accepted: 12/20/2023] [Indexed: 01/08/2024] Open
Abstract
SARS-CoV-2 receptor binding domain (RBD) mediates viral entry into human cells through its interaction with angiotensin converting enzyme 2 (ACE2). Most neutralizing antibodies elicited by infection or vaccination target this domain. Such a functional relevance, together with large RBD sequence variability arising during viral spreading, point to the need of exploring the complex landscape of interactions between RBD-derived variants, ACE2 and antibodies. The current work was aimed at developing a simple platform to do so. Biologically active and antigenic Wuhan-Hu-1 RBD, as well as mutated RBD variants found in nature, were successfully displayed on filamentous phages. Mutational scanning confirmed the global plasticity of the receptor binding motif within RBD, highlighted residues playing a critical role in receptor binding, and identified mutations strengthening the interaction. The ability of vaccine-induced antibodies to inhibit ACE2 binding of many mutated RBD variants, albeit at different extents, was shown. Amino acid replacements which could compromise such inhibitory potential were underscored. The expansion of our approach could be the starting point for a large-scale phage-based exploration of diversity within RBD of SARS-CoV-2 and related coronaviruses, useful to understand structure-function relationships, to engineer RBD proteins, and to anticipate changes to watch during viral evolution.
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Affiliation(s)
- Beatriz Pérez-Massón
- Center of Molecular Immunology, Calle 216 esq 15, apartado 16040, Atabey, Playa, CP 11300, Havana, Cuba
| | - Yazmina Quintana-Pérez
- Center of Molecular Immunology, Calle 216 esq 15, apartado 16040, Atabey, Playa, CP 11300, Havana, Cuba
| | - Yaima Tundidor
- Center of Molecular Immunology, Calle 216 esq 15, apartado 16040, Atabey, Playa, CP 11300, Havana, Cuba
| | - Dayana Pérez-Martínez
- Center of Molecular Immunology, Calle 216 esq 15, apartado 16040, Atabey, Playa, CP 11300, Havana, Cuba
| | - Camila Castro-Martínez
- Center of Molecular Immunology, Calle 216 esq 15, apartado 16040, Atabey, Playa, CP 11300, Havana, Cuba
| | - Mario Pupo-Meriño
- Universidad de Ciencias Informáticas, Carretera a San Antonio de los Baños, km 2 1/2, Torrens, Boyeros, CP 19370, Havana, Cuba
| | - Ivette Orosa
- Center of Molecular Immunology, Calle 216 esq 15, apartado 16040, Atabey, Playa, CP 11300, Havana, Cuba
| | - Ernesto Relova-Hernández
- Center of Molecular Immunology, Calle 216 esq 15, apartado 16040, Atabey, Playa, CP 11300, Havana, Cuba
| | - Rosmery Villegas
- Universidad de Ciencias Informáticas, Carretera a San Antonio de los Baños, km 2 1/2, Torrens, Boyeros, CP 19370, Havana, Cuba
| | - Osmany Guirola
- Center for Genetic Engineering and Biotechnology, Ave 31 E/158 y 190, Cubanacán, Playa, CP 11300, Havana, Cuba
| | - Gertrudis Rojas
- Center of Molecular Immunology, Calle 216 esq 15, apartado 16040, Atabey, Playa, CP 11300, Havana, Cuba.
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13
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Feng Y, Yi J, Yang L, Wang Y, Wen J, Zhao W, Kim P, Zhou X. COV2Var, a function annotation database of SARS-CoV-2 genetic variation. Nucleic Acids Res 2024; 52:D701-D713. [PMID: 37897356 PMCID: PMC10767816 DOI: 10.1093/nar/gkad958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/29/2023] [Accepted: 10/16/2023] [Indexed: 10/30/2023] Open
Abstract
The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has resulted in the loss of millions of lives and severe global economic consequences. Every time SARS-CoV-2 replicates, the viruses acquire new mutations in their genomes. Mutations in SARS-CoV-2 genomes led to increased transmissibility, severe disease outcomes, evasion of the immune response, changes in clinical manifestations and reducing the efficacy of vaccines or treatments. To date, the multiple resources provide lists of detected mutations without key functional annotations. There is a lack of research examining the relationship between mutations and various factors such as disease severity, pathogenicity, patient age, patient gender, cross-species transmission, viral immune escape, immune response level, viral transmission capability, viral evolution, host adaptability, viral protein structure, viral protein function, viral protein stability and concurrent mutations. Deep understanding the relationship between mutation sites and these factors is crucial for advancing our knowledge of SARS-CoV-2 and for developing effective responses. To fill this gap, we built COV2Var, a function annotation database of SARS-CoV-2 genetic variation, available at http://biomedbdc.wchscu.cn/COV2Var/. COV2Var aims to identify common mutations in SARS-CoV-2 variants and assess their effects, providing a valuable resource for intensive functional annotations of common mutations among SARS-CoV-2 variants.
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Affiliation(s)
- Yuzhou Feng
- Department of Laboratory Medicine and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu 610041, China
- Med-X Center for Informatics, Sichuan University, Chengdu 610041, China
| | - Jiahao Yi
- School of Big Health, Guizhou Medical University, Guiyang 550025, China
| | - Lin Yang
- Department of Cardiology and Laboratory of Gene Therapy for Heart Diseases, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University and Collaborative Innovation Center for Biotherapy, Chengdu 610041, China
| | - Yanfei Wang
- Center for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Jianguo Wen
- Center for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Weiling Zhao
- Center for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Pora Kim
- Center for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Xiaobo Zhou
- Center for Computational Systems Medicine, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- School of Dentistry, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
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14
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Baboo S, Diedrich JK, Torres JL, Copps J, Singh B, Garrett PT, Ward AB, Paulson JC, Yates JR. Evolving spike-protein N-glycosylation in SARS-CoV-2 variants. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.08.539897. [PMID: 37214937 PMCID: PMC10197516 DOI: 10.1101/2023.05.08.539897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Since >3 years, SARS-CoV-2 has plunged humans into a colossal pandemic. Henceforth, multiple waves of infection have swept through the human population, led by variants that were able to partially evade acquired immunity. The co-evolution of SARS-CoV-2 variants with human immunity provides an excellent opportunity to study the interaction between viral pathogens and their human hosts. The heavily N-glycosylated spike-protein of SARS-CoV-2 plays a pivotal role in initiating infection and is the target for host immune-response, both of which are impacted by host-installed N-glycans. Using highly-sensitive DeGlyPHER approach, we compared the N-glycan landscape on spikes of the SARS-CoV-2 Wuhan-Hu-1 strain to seven WHO-defined variants of concern/interest, using recombinantly expressed, soluble spike-protein trimers, sharing same stabilizing-mutations. We found that N-glycan processing is conserved at most sites. However, in multiple variants, processing of N-glycans from high mannose- to complex-type is reduced at sites N165, N343 and N616, implicated in spike-protein function.
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Affiliation(s)
- Sabyasachi Baboo
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Jolene K. Diedrich
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Jonathan L. Torres
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Jeffrey Copps
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Bhavya Singh
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Patrick T. Garrett
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, California 92037, United States
| | - Andrew B. Ward
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, California 92037, United States
| | - James C. Paulson
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, California 92037, United States
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, California 92037, United States
| | - John R. Yates
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, California 92037, United States
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15
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Duchene S. Tracing the origin of virulence. Science 2023; 382:1245-1246. [PMID: 38096277 DOI: 10.1126/science.adl6094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Microbial genomes from ancient chickens uncover the drivers of pathogenicity.
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Affiliation(s)
- Sebastian Duchene
- Department of Computational Biology, Institut Pasteur, Paris, France
- Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, Australia
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16
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Weber A, Översti S, Kühnert D. Reconstructing relative transmission rates in Bayesian phylodynamics: Two-fold transmission advantage of Omicron in Berlin, Germany during December 2021. Virus Evol 2023; 9:vead070. [PMID: 38107332 PMCID: PMC10725310 DOI: 10.1093/ve/vead070] [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: 08/17/2023] [Revised: 11/08/2023] [Accepted: 11/27/2023] [Indexed: 12/19/2023] Open
Abstract
Phylodynamic methods have lately played a key role in understanding the spread of infectious diseases. During the coronavirus disease (COVID-19) pandemic, large scale genomic surveillance has further increased the potential of dynamic inference from viral genomes. With the continual emergence of novel severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) variants, explicitly allowing transmission rate differences between simultaneously circulating variants in phylodynamic inference is crucial. In this study, we present and empirically validate an extension to the BEAST2 package birth-death skyline model (BDSKY), BDSKY[Formula: see text], which introduces a scaling factor for the transmission rate between independent, jointly inferred trees. In an extensive simulation study, we show that BDSKY[Formula: see text] robustly infers the relative transmission rates under different epidemic scenarios. Using publicly available genome data of SARS-CoV-2, we apply BDSKY[Formula: see text] to quantify the transmission advantage of the Omicron over the Delta variant in Berlin, Germany. We find the overall transmission rate of Omicron to be scaled by a factor of two with pronounced variation between the individual clusters of each variant. These results quantify the transmission advantage of Omicron over the previously circulating Delta variant, in a crucial period of pre-established non-pharmaceutical interventions. By inferring variant- as well as cluster-specific transmission rate scaling factors, we show the differences in transmission dynamics for each variant. This highlights the importance of incorporating lineage-specific transmission differences in phylodynamic inference.
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Affiliation(s)
- Ariane Weber
- Transmission, Infection, Diversification & Evolution Group (tide), Max Planck Institute of Geoanthropology, Kahlaische Strasse 10, Jena, Thuringia 07745, Germany
- Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, Leipzig, Saxony 04103, Germany
| | | | - Denise Kühnert
- Transmission, Infection, Diversification & Evolution Group (tide), Max Planck Institute of Geoanthropology, Kahlaische Strasse 10, Jena, Thuringia 07745, Germany
- Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, Leipzig, Saxony 04103, Germany
- Centre for Artificial Intelligence in Public Health Research, Robert Koch Institute, Ludwig-Witthöft-Straße 14, Wildau, Brandenburg 15745, Germany
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17
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Niedre-Otomere B, Kampenusa I, Trofimova J, Bodrenko J, Vangravs R, Skenders G, Nikisins S, Savicka O. Multiplexed RT-qPCR Coupled with Whole-Genome Sequencing to Monitor a SARS-CoV-2 Omicron Variant of Concern in a Hospital Laboratory Setting in Latvia. Diagnostics (Basel) 2023; 13:3467. [PMID: 37998603 PMCID: PMC10670528 DOI: 10.3390/diagnostics13223467] [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: 10/13/2023] [Revised: 11/10/2023] [Accepted: 11/12/2023] [Indexed: 11/25/2023] Open
Abstract
At the end of 2021, the SARS-CoV-2 Omicron variant of concern (VOC) displaced the previously dominant Delta VOC and enhanced diagnostic and therapeutic challenges worldwide. Respiratory specimens submitted to the Riga East University Hospital Laboratory Service by the central and regional hospitals of Latvia from January to March 2022 that were positive for SARS-CoV-2 RNA were tested by commercial multiplexed RT-qPCR targeting three of the Omicron VOC signature mutations: ΔH69/V70, E484A, and N501Y. Of the specimens tested and analyzed in parallel by whole-genome sequencing (WGS), 964 passed the internal quality criteria (genome coverage ≥90%, read depth ≥400×) and the Nextstrain's quality threshold for "good". We validated the detection accuracy of RT-qPCR for each target individually by using WGS as a control. The results were concordant with both approaches for 938 specimens, with the correct classification rate exceeding 96% for each target (CI 95%); however, the presumptive WHO label was misassigned for 21 specimens. The RT-qPCR genotyping provided an acceptable means to pre-monitor the prevalence of the two presumptive Omicron VOC sublineages, BA.1 and BA.2.
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18
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Gomez-Romero N, Basurto-Alcantara FJ, Velazquez-Salinas L. Assessing the Potential Role of Cats ( Felis catus) as Generators of Relevant SARS-CoV-2 Lineages during the Pandemic. Pathogens 2023; 12:1361. [PMID: 38003825 PMCID: PMC10675002 DOI: 10.3390/pathogens12111361] [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: 10/07/2023] [Revised: 11/09/2023] [Accepted: 11/14/2023] [Indexed: 11/26/2023] Open
Abstract
Several questions regarding the evolution of SARS-CoV-2 remain poorly elucidated. One of these questions is the possible evolutionary impact of SARS-CoV-2 after the infection in domestic animals. In this study, we aimed to evaluate the potential role of cats as generators of relevant SARS-CoV-2 lineages during the pandemic. A total of 105 full-length genome viral sequences obtained from naturally infected cats during the pandemic were evaluated by distinct evolutionary algorithms. Analyses were enhanced, including a set of highly related SARS-CoV-2 sequences recovered from human populations. Our results showed the apparent high susceptibility of cats to the infection SARS-CoV-2 compared with other animal species. Evolutionary analyses indicated that the phylogenomic characteristics displayed by cat populations were influenced by the dominance of specific SARS-CoV-2 genetic groups affecting human populations. However, disparate dN/dS rates at some genes between populations recovered from cats and humans suggested that infection in these two species may suggest a different evolutionary constraint for SARS-CoV-2. Interestingly, the branch selection analysis showed evidence of the potential role of natural selection in the emergence of five distinct cat lineages during the pandemic. Although these lineages were apparently irrelevant to public health during the pandemic, our results suggested that additional studies are needed to understand the role of other animal species in the evolution of SARS-CoV-2 during the pandemic.
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Affiliation(s)
- Ninnet Gomez-Romero
- Comisión México-Estados Unidos para la Prevención de Fiebre Aftosa y Otras Enfermedades Exóticas de los Animales, Carretera Mexico-Toluca Km 15.5 Piso 4 Col. Palo Alto, Cuajimalpa de Morelos, Mexico City 05110, Mexico;
- Departamento de Microbiología e Inmunología, Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autónoma de México, Av. Universidad No. 3000 Col Copilco Universidad, Mexico City 14510, Mexico;
| | - Francisco Javier Basurto-Alcantara
- Departamento de Microbiología e Inmunología, Facultad de Medicina Veterinaria y Zootecnia, Universidad Nacional Autónoma de México, Av. Universidad No. 3000 Col Copilco Universidad, Mexico City 14510, Mexico;
| | - Lauro Velazquez-Salinas
- Plum Island Animal Disease Center, Agricultural Research Service, United States Department of Agriculture, Greenport, NY 11944, USA
- National Bio and Agro-Defense Facility (NBAF), Agricultural Research Service, United States Department of Agriculture, Manhattan, KS 66502, USA
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19
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Roemer C, Sheward DJ, Hisner R, Gueli F, Sakaguchi H, Frohberg N, Schoenmakers J, Sato K, O'Toole Á, Rambaut A, Pybus OG, Ruis C, Murrell B, Peacock TP. SARS-CoV-2 evolution in the Omicron era. Nat Microbiol 2023; 8:1952-1959. [PMID: 37845314 DOI: 10.1038/s41564-023-01504-w] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 09/13/2023] [Indexed: 10/18/2023]
Abstract
Since SARS-CoV-2 BA.5 (Omicron) emerged and spread in 2022, Omicron lineages have markedly diversified. Here we review the evolutionary trajectories and processes that underpin the emergence of these lineages, and identify the most prevalent sublineages. We discuss the potential origins of second-generation BA.2 lineages. Simple and complex recombination, antigenic drift and convergent evolution have enabled SARS-CoV-2 to accumulate mutations that alter its antigenicity. We also discuss the potential evolutionary trajectories of SARS-CoV-2 in the future.
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Affiliation(s)
- Cornelius Roemer
- Biozentrum, University of Basel, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Daniel J Sheward
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Ryan Hisner
- University of Cape Town, Rondebosch, South Africa
| | | | | | | | | | - Kenta Sato
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Áine O'Toole
- Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, UK
| | - Andrew Rambaut
- Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, UK
| | - Oliver G Pybus
- Department of Biology, University of Oxford, Oxford, UK
- Department of Pathobiology and Population Science, Royal Veterinary College, London, UK
| | - Christopher Ruis
- Molecular Immunity Unit, Department of Medicine, University of Cambridge, MRC Laboratory of Molecular Biology, Cambridge, UK
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
- Cambridge Centre for AI in Medicine, University of Cambridge, Cambridge, UK
| | - Ben Murrell
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
| | - Thomas P Peacock
- Department of Infectious Disease, Imperial College London, London, UK.
- The Pirbright Institute, Woking, UK.
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20
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Zhakparov D, Quirin Y, Xiao Y, Battaglia N, Holzer M, Bühler M, Kistler W, Engel D, Zumthor JP, Caduff A, Baerenfaller K. Sequencing of SARS-CoV-2 RNA Fragments in Wastewater Detects the Spread of New Variants during Major Events. Microorganisms 2023; 11:2660. [PMID: 38004672 PMCID: PMC10672834 DOI: 10.3390/microorganisms11112660] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 11/26/2023] Open
Abstract
The sequencing of SARS-CoV-2 RNA in wastewater is an unbiased method to detect the spread of emerging variants and to track regional infection dynamics, which is especially useful in case of limited testing and clinical sequencing. To test how major international events influence the spread of new variants we have sequenced SARS-CoV-2 RNA in the wastewater samples of Davos, Landquart, Lostallo, and St. Moritz in the Swiss canton of Grisons in the time around the international sports competitions in Davos and St. Moritz in December 2021, and additionally in May 2022 and January 2023 in Davos and St. Moritz during the World Economic Forum (WEF) in Davos. The prevalence of the variants identified from the wastewater sequencing data showed that the Omicron variant BA.1 had spread in Davos and St. Moritz during the international sporting events hosted there in December 2021. This spread was associated with an increase in case numbers, while it was not observed in Landquart and Lostallo. Another instance of new variant spread occurred during the WEF in January 2023, when the Omicron variant BA.2.75 arrived in Davos but not in St. Moritz. We can therefore conclude that major international events promote the spread of new variants in the respective host region, which has important implications for the protective measures that should be taken.
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Affiliation(s)
- Damir Zhakparov
- Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, 7265 Davos, Switzerland; (D.Z.)
- Swiss Institute of Bioinformatics (SIB), 1005 Lausanne, Switzerland
| | - Yves Quirin
- Cantonal Office for Nature and Environment, 7000 Chur, Switzerland
| | - Yi Xiao
- Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, 7265 Davos, Switzerland; (D.Z.)
- Swiss Institute of Bioinformatics (SIB), 1005 Lausanne, Switzerland
| | - Nicole Battaglia
- Cantonal Office for Food Security and Animal Health, 7000 Chur, Switzerland
| | - Michael Holzer
- Cantonal Office for Nature and Environment, 7000 Chur, Switzerland
| | - Martin Bühler
- Cantonal Office for Military and Civil Protection, 7000 Chur, Switzerland (A.C.)
| | | | | | - Jon Paulin Zumthor
- Cantonal Office for Food Security and Animal Health, 7000 Chur, Switzerland
| | - Alexa Caduff
- Cantonal Office for Military and Civil Protection, 7000 Chur, Switzerland (A.C.)
| | - Katja Baerenfaller
- Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, 7265 Davos, Switzerland; (D.Z.)
- Swiss Institute of Bioinformatics (SIB), 1005 Lausanne, Switzerland
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21
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Islam MA, Marzan AA, Arman MS, Shahi S, Sakif TI, Hossain M, Islam T, Hoque MN. Some common deleterious mutations are shared in SARS-CoV-2 genomes from deceased COVID-19 patients across continents. Sci Rep 2023; 13:18644. [PMID: 37903828 PMCID: PMC10616235 DOI: 10.1038/s41598-023-45517-1] [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: 06/19/2023] [Accepted: 10/20/2023] [Indexed: 11/01/2023] Open
Abstract
The identification of deleterious mutations in different variants of SARS-CoV-2 and their roles in the morbidity of COVID-19 patients has yet to be thoroughly investigated. To unravel the spectrum of mutations and their effects within SARS-CoV-2 genomes, we analyzed 5,724 complete genomes from deceased COVID-19 patients sourced from the GISAID database. This analysis was conducted using the Nextstrain platform, applying a generalized time-reversible model for evolutionary phylogeny. These genomes were compared to the reference strain (hCoV-19/Wuhan/WIV04/2019) using MAFFT v7.470. Our findings revealed that SARS-CoV-2 genomes from deceased individuals belonged to 21 Nextstrain clades, with clade 20I (Alpha variant) being the most predominant, followed by clade 20H (Beta variant) and clade 20J (Gamma variant). The majority of SARS-CoV-2 genomes from deceased patients (33.4%) were sequenced in North America, while the lowest percentage (0.98%) came from Africa. The 'G' clade was dominant in the SARS-CoV-2 genomes of Asian, African, and North American regions, while the 'GRY' clade prevailed in Europe. In our analysis, we identified 35,799 nucleotide (NT) mutations throughout the genome, with the highest frequency (11,402 occurrences) found in the spike protein. Notably, we observed 4150 point-specific amino acid (AA) mutations in SARS-CoV-2 genomes, with D614G (20%) and N501Y (14%) identified as the top two deleterious mutations in the spike protein on a global scale. Furthermore, we detected five common deleterious AA mutations, including G18V, W45S, I33T, P30L, and Q418H, which play a key role in defining each clade of SARS-CoV-2. Our novel findings hold potential value for genomic surveillance, enabling the monitoring of the evolving pattern of SARS-CoV-2 infection, its emerging variants, and their impact on the development of effective vaccination and control strategies.
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Affiliation(s)
- Md Aminul Islam
- Advanced Molecular Lab, Department of Microbiology, President Abdul Hamid Medical College, Karimganj, Kishoreganj, 2310, Bangladesh.
- COVID-19 Diagnostic Lab, Department of Microbiology, Noakhali Science and Technology University, Noakhali, 3814, Bangladesh.
| | - Abdullah Al Marzan
- Advanced Molecular Lab, Department of Microbiology, President Abdul Hamid Medical College, Karimganj, Kishoreganj, 2310, Bangladesh
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh
| | - Md Sakil Arman
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh
| | - Shatila Shahi
- Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet, 3114, Bangladesh
| | - Tahsin Islam Sakif
- Lane Department of Computer Science and Electrical Engineering, West Virginia University, Morgantown, WV, 26506-6109, USA
| | - Maqsud Hossain
- University of Nottingham, Sutton Bonington Campus, LE12 5RD, Loughborough, NG7 2RD, Leicestershire, UK
| | - Tofazzal Islam
- Institute of Biotechnology and Genetic Engineering (IBGE), Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, 1706, Bangladesh.
| | - M Nazmul Hoque
- Molecular Biology and Bioinformatics Laboratory, Department of Gynecology, Obstetrics and Reproductive Health, Bangabandhu Sheikh Mujibur Rahman Agricultural University, Gazipur, 1706, Bangladesh.
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22
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Padhi AK, Kalita P, Maurya S, Poluri KM, Tripathi T. From De Novo Design to Redesign: Harnessing Computational Protein Design for Understanding SARS-CoV-2 Molecular Mechanisms and Developing Therapeutics. J Phys Chem B 2023; 127:8717-8735. [PMID: 37815479 DOI: 10.1021/acs.jpcb.3c04542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/11/2023]
Abstract
The continuous emergence of novel SARS-CoV-2 variants and subvariants serves as compelling evidence that COVID-19 is an ongoing concern. The swift, well-coordinated response to the pandemic highlights how technological advancements can accelerate the detection, monitoring, and treatment of the disease. Robust surveillance systems have been established to understand the clinical characteristics of new variants, although the unpredictable nature of these variants presents significant challenges. Some variants have shown resistance to current treatments, but innovative technologies like computational protein design (CPD) offer promising solutions and versatile therapeutics against SARS-CoV-2. Advances in computing power, coupled with open-source platforms like AlphaFold and RFdiffusion (employing deep neural network and diffusion generative models), among many others, have accelerated the design of protein therapeutics with precise structures and intended functions. CPD has played a pivotal role in developing peptide inhibitors, mini proteins, protein mimics, decoy receptors, nanobodies, monoclonal antibodies, identifying drug-resistance mutations, and even redesigning native SARS-CoV-2 proteins. Pending regulatory approval, these designed therapies hold the potential for a lasting impact on human health and sustainability. As SARS-CoV-2 continues to evolve, use of such technologies enables the ongoing development of alternative strategies, thus equipping us for the "New Normal".
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Affiliation(s)
- Aditya K Padhi
- Laboratory for Computational Biology & Biomolecular Design, School of Biochemical Engineering, Indian Institute of Technology (BHU), Varanasi 221005, Uttar Pradesh, India
| | - Parismita Kalita
- Molecular and Structural Biophysics Laboratory, Department of Biochemistry, North-Eastern Hill University, Shillong 793022, India
| | - Shweata Maurya
- Laboratory for Computational Biology & Biomolecular Design, School of Biochemical Engineering, Indian Institute of Technology (BHU), Varanasi 221005, Uttar Pradesh, India
| | - Krishna Mohan Poluri
- Department of Biosciences and Bioengineering, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
- Centre for Nanotechnology, Indian Institute of Technology Roorkee, Roorkee 247667, Uttarakhand, India
| | - Timir Tripathi
- Molecular and Structural Biophysics Laboratory, Department of Biochemistry, North-Eastern Hill University, Shillong 793022, India
- Department of Zoology, School of Life Sciences, North-Eastern Hill University, Shillong 793022, India
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23
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Devaux CA, Fantini J. Possible contribution of rare alleles of human ACE2 in the emergence of SARS-CoV-2 variants escaping the immune response. Front Immunol 2023; 14:1252367. [PMID: 37885880 PMCID: PMC10598458 DOI: 10.3389/fimmu.2023.1252367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 09/28/2023] [Indexed: 10/28/2023] Open
Abstract
Since the start of the SARS-CoV-2 pandemic, the rapid replacement of one lineage by another has been observed. Indeed, SARS-CoV-2 is evolving through a quasispecies mechanism leading to post-infection mutation selection under positive evolutionary pressure (host-driven viral evolution). These mutations may reduce the effectiveness of the specific neutralizing immune response against the virus. We provide here evidence that apart from the selection of SARS-CoV-2 variants by the immune system, selection by the cellular receptor can just as well select variants which escape neutralization.
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Affiliation(s)
- Christian A. Devaux
- Institut National des Sciences Biologiques (INSB), Centre National de la Recherche Scientifique (CNRS), Marseille, France
- Microbes, Evolution, Phylogénie et Infections, Faculté de Pharmacie, Aix Marseille Université, Marseille, France
| | - Jacques Fantini
- Institut National de la Santé et de la Recherche Médicale (INSERM) U_1072, Faculté des Sciences, Aix-Marseille Université, Marseille, France
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24
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Tay JH, Baele G, Duchene S. Detecting Episodic Evolution through Bayesian Inference of Molecular Clock Models. Mol Biol Evol 2023; 40:msad212. [PMID: 37738550 PMCID: PMC10560005 DOI: 10.1093/molbev/msad212] [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: 06/17/2023] [Revised: 09/13/2023] [Accepted: 09/20/2023] [Indexed: 09/24/2023] Open
Abstract
Molecular evolutionary rate variation is a key aspect of the evolution of many organisms that can be modeled using molecular clock models. For example, fixed local clocks revealed the role of episodic evolution in the emergence of SARS-CoV-2 variants of concern. Like all statistical models, however, the reliability of such inferences is contingent on an assessment of statistical evidence. We present a novel Bayesian phylogenetic approach for detecting episodic evolution. It consists of computing Bayes factors, as the ratio of posterior and prior odds of evolutionary rate increases, effectively quantifying support for the effect size. We conducted an extensive simulation study to illustrate the power of this method and benchmarked it to formal model comparison of a range of molecular clock models using (log) marginal likelihood estimation, and to inference under a random local clock model. Quantifying support for the effect size has higher sensitivity than formal model testing and is straight-forward to compute, because it only needs samples from the posterior and prior distribution. However, formal model testing has the advantage of accommodating a wide range molecular clock models. We also assessed the ability of an automated approach, known as the random local clock, where branches under episodic evolution may be detected without their a priori definition. In an empirical analysis of a data set of SARS-CoV-2 genomes, we find "very strong" evidence for episodic evolution. Our results provide guidelines and practical methods for Bayesian detection of episodic evolution, as well as avenues for further research into this phenomenon.
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Affiliation(s)
- John H Tay
- Peter Doherty Institute for Infection and Immunity, Department of Microbiology and Immunology, University of Melbourne, Melbourne, Victoria, Australia
| | - Guy Baele
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU Leuven, Leuven, Belgium
| | - Sebastian Duchene
- Peter Doherty Institute for Infection and Immunity, Department of Microbiology and Immunology, University of Melbourne, Melbourne, Victoria, Australia
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25
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Colquhoun R, Jackson B, O’Toole Á, Rambaut A. SCORPIO: a utility for defining and classifying mutation constellations of virus genomes. Bioinformatics 2023; 39:btad575. [PMID: 37713452 PMCID: PMC10563142 DOI: 10.1093/bioinformatics/btad575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 09/04/2023] [Accepted: 09/14/2023] [Indexed: 09/17/2023] Open
Abstract
SUMMARY Scorpio provides a set of command line utilities for classifying, haplotyping, and defining constellations of mutations for an aligned set of genome sequences. It was developed to enable exploration and classification of variants of concern within the SARS-CoV-2 pandemic, but can be applied more generally to other species. AVAILABILITY AND IMPLEMENTATION Scorpio is an open-source project distributed under the GNU GPL version 3 license. Source code and binaries are available at https://github.com/cov-lineages/scorpio, and binaries are also available from Bioconda. SARS-CoV-2 specific definitions can be installed as a separate dependency from https://github.com/cov-lineages/constellations.
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Affiliation(s)
- Rachel Colquhoun
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Charlotte Auerbach Road, Edinburgh EH9 3FL, United Kingdom
| | - Ben Jackson
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Charlotte Auerbach Road, Edinburgh EH9 3FL, United Kingdom
| | - Áine O’Toole
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Charlotte Auerbach Road, Edinburgh EH9 3FL, United Kingdom
| | - Andrew Rambaut
- Institute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Charlotte Auerbach Road, Edinburgh EH9 3FL, United Kingdom
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26
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Volz E. Fitness, growth and transmissibility of SARS-CoV-2 genetic variants. Nat Rev Genet 2023; 24:724-734. [PMID: 37328556 DOI: 10.1038/s41576-023-00610-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/25/2023] [Indexed: 06/18/2023]
Abstract
The massive scale of the global SARS-CoV-2 sequencing effort created new opportunities and challenges for understanding SARS-CoV-2 evolution. Rapid detection and assessment of new variants has become one of the principal objectives of genomic surveillance of SARS-CoV-2. Because of the pace and scale of sequencing, new strategies have been developed for characterizing fitness and transmissibility of emerging variants. In this Review, I discuss a wide range of approaches that have been rapidly developed in response to the public health threat posed by emerging variants, ranging from new applications of classic population genetics models to contemporary synthesis of epidemiological models and phylodynamic analysis. Many of these approaches can be adapted to other pathogens and will have increasing relevance as large-scale pathogen sequencing becomes a regular feature of many public health systems.
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Affiliation(s)
- Erik Volz
- Department of Infectious Disease Epidemiology, MRC Centre for Global Infectious Disease Analysis, Imperial College London, London, UK.
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27
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Xu X, Deng Y, Ding J, Zheng X, Wang C, Wang D, Liu L, Gu H, Peiris M, Poon LLM, Zhang T. Wastewater genomic sequencing for SARS-CoV-2 variants surveillance in wastewater-based epidemiology applications. WATER RESEARCH 2023; 244:120444. [PMID: 37579567 DOI: 10.1016/j.watres.2023.120444] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 08/01/2023] [Accepted: 08/02/2023] [Indexed: 08/16/2023]
Abstract
Wastewater-based epidemiology (WBE) has been widely used as a complementary approach to SARS-CoV-2 clinical surveillance. Wastewater genomic sequencing could provide valuable information on the genomic diversity of SARS-CoV-2 in the surveyed population. However, reliable detection and quantification of variants or mutations remain challenging. In this study, we used mock wastewater samples created by spiking SARS-CoV-2 variant standard RNA into wastewater RNA to evaluate the impacts of sequencing throughput on various aspects such as genome coverage, mutation detection, and SARS-CoV-2 variant deconvolution. We found that wastewater datasets with sequencing throughput greater than 0.5 Gb yielded reliable results in genomic analysis. In addition, using in silico mock datasets, we evaluated the performance of the adopted pipeline for variant deconvolution. By sequencing 86 wastewater samples covering more than 6 million people over 7 months, we presented two use cases of wastewater genomic sequencing for surveying COVID-19 in Hong Kong in WBE applications, including the replacement of Delta variants by Omicron variants, and the prevalence and development trends of three Omicron sublineages. Importantly, the wastewater genomic sequencing data were able to reveal the variant trends 16 days before the clinical data did. By investigating mutations of the spike (S) gene of the SARS-CoV-2 virus, we also showed the potential of wastewater genomic sequencing in identifying novel mutations and unique alleles. Overall, our study demonstrated the crucial role of wastewater genomic surveillance in providing valuable insights into the emergence and monitoring of new SARS-CoV-2 variants and laid a solid foundation for the development of genomic analysis methodologies for WBE of other novel emerging viruses in the future.
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Affiliation(s)
- Xiaoqing Xu
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Yu Deng
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Jiahui Ding
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Xiawan Zheng
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Chunxiao Wang
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Dou Wang
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Lei Liu
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China
| | - Haogao Gu
- Li Ka Shing Faculty of Medicine, School of Public Health, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China
| | - Malik Peiris
- Li Ka Shing Faculty of Medicine, School of Public Health, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China; HKU-Pasteur Research Pole, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China
| | - Leo L M Poon
- Li Ka Shing Faculty of Medicine, School of Public Health, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China; HKU-Pasteur Research Pole, The University of Hong Kong, Sassoon Road, Hong Kong SAR, China
| | - Tong Zhang
- Department of Civil Engineering, Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, The University of Hong Kong, Pokfulam Road, Hong Kong SAR, China.
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28
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Hu D, Irving AT. Massively-multiplexed epitope mapping techniques for viral antigen discovery. Front Immunol 2023; 14:1192385. [PMID: 37818363 PMCID: PMC10561112 DOI: 10.3389/fimmu.2023.1192385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Accepted: 09/04/2023] [Indexed: 10/12/2023] Open
Abstract
Following viral infection, viral antigens bind specifically to receptors on the surface of lymphocytes thereby activating adaptive immunity in the host. An epitope, the smallest structural and functional unit of an antigen, binds specifically to an antibody or antigen receptor, to serve as key sites for the activation of adaptive immunity. The complexity and diverse range of epitopes are essential to study and map for the diagnosis of disease, the design of vaccines and for immunotherapy. Mapping the location of these specific epitopes has become a hot topic in immunology and immune therapy. Recently, epitope mapping techniques have evolved to become multiplexed, with the advent of high-throughput sequencing and techniques such as bacteriophage-display libraries and deep mutational scanning. Here, we briefly introduce the principles, advantages, and disadvantages of the latest epitope mapping techniques with examples for viral antigen discovery.
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Affiliation(s)
- Diya Hu
- Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Zhejiang University, Haining, China
| | - Aaron T. Irving
- Department of Clinical Laboratory Studies, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Centre for Infection, Immunity & Cancer, Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Zhejiang University, Haining, China
- Biomedical and Health Translational Research Centre of Zhejiang Province (BIMET), Haining, China
- College of Medicine & Veterinary Medicine, The University of Edinburgh, Edinburgh, United Kingdom
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29
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Urakawa R, Isomura ET, Matsunaga K, Kubota K. Multivariate Analysis of Adverse Reactions and Recipient Profiles in COVID-19 Booster Vaccinations: A Prospective Cohort Study. Vaccines (Basel) 2023; 11:1513. [PMID: 37896917 PMCID: PMC10611183 DOI: 10.3390/vaccines11101513] [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: 08/17/2023] [Revised: 09/21/2023] [Accepted: 09/21/2023] [Indexed: 10/29/2023] Open
Abstract
BACKGROUND This study investigated the impact of vaccinated population profiles, vaccine type/interval, and the number of vaccine doses on adverse reactions to receiving a coronavirus disease 2019 (COVID-19) booster vaccination. METHODS A survey of adverse reactions was conducted from January 2022 to December 2022 among Osaka University Dental Hospital employees who received their third or fourth doses. The study included 194 third-dose recipients and 131 fourth-dose recipients. Comparisons of the occurrence of adverse reactions between the third- and fourth-dose groups were analyzed via a chi-squared test. The relationships between each adverse reaction occurrence and recipient profiles, vaccine type/interval, and the number of vaccine doses were analyzed via a logistic regression analysis. RESULTS No significant differences were found in the occurrence of adverse reactions between the third and fourth doses. Younger recipients often developed injection site reaction, fatigue, chills, fever, arthralgia, headache, diarrhea, and any adverse reactions more often. Females had higher frequencies of fatigue, chills, headache, and nausea compared to males. Recipients without underlying diseases had higher frequencies of fever and nausea than those with underlying diseases. CONCLUSIONS Younger recipients and females were at higher risk for adverse reactions to a COVID-19 booster vaccination, while the number of vaccinations, vaccination interval, vaccine type, and cross-vaccination showed no significant associations.
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Affiliation(s)
- Ryuta Urakawa
- Department of Pharmacy, Osaka University Dental Hospital, 1-8 Yamada-oka, Suita, Osaka 565-0871, Japan
- Department of Clinical Pharmacy Research and Education, Graduate School of Pharmaceutical Sciences, Osaka University, 1-6 Yamada-oka, Suita, Osaka 565-0871, Japan
| | - Emiko Tanaka Isomura
- Department of Oral and Maxillofacial Surgery, Graduate School of Dentistry, Osaka University, 1-8 Yamada-oka, Suita, Osaka 565-0871, Japan
| | - Kazuhide Matsunaga
- Department of Oral & Maxillofacial Oncology and Surgery, Graduate School of Dentistry, Osaka University, 1-8 Yamada-oka, Suita, Osaka 565-0871, Japan
| | - Kazumi Kubota
- Department of Healthcare Information Management, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan
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30
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Bloom JD, Neher RA. Fitness effects of mutations to SARS-CoV-2 proteins. Virus Evol 2023; 9:vead055. [PMID: 37727875 PMCID: PMC10506532 DOI: 10.1093/ve/vead055] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 08/08/2023] [Accepted: 08/22/2023] [Indexed: 09/21/2023] Open
Abstract
Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here, we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.
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Affiliation(s)
- Jesse D Bloom
- Basic Sciences and Computational Biology, Fred Hutchinson Cancer Center, 1100 Fairview Ave N, Seattle, WA 98109, USA
- Department of Genome Sciences, University of Washington, 3720 15th Ave NE, Seattle, WA 98195, USA
- Howard Hughes Medical Institute, 1100 Fairview Ave N, Seattle, WA 98109, USA
| | - Richard A Neher
- Biozentrum, University of Basel, Spitalstrasse 41, Basel 4056, Switzerland
- Swiss Institute of Bioinformatics, Lausanne 1015, Switzerl
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31
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Ma W, Fu H, Jian F, Cao Y, Li M. Immune evasion and ACE2 binding affinity contribute to SARS-CoV-2 evolution. Nat Ecol Evol 2023; 7:1457-1466. [PMID: 37443189 DOI: 10.1038/s41559-023-02123-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 06/13/2023] [Indexed: 07/15/2023]
Abstract
Mutations in the SARS-CoV-2 genome could confer resistance to pre-existing antibodies and/or increased transmissibility. The recently emerged Omicron subvariants exhibit a strong tendency for immune evasion, suggesting adaptive evolution. However, because previous studies have been limited to specific lineages or subsets of mutations, the overall evolutionary trajectory of SARS-CoV-2 and the underlying driving forces are still not fully understood. Here we analysed all open-access SARS-CoV-2 genomes (up to November 2022) and correlated the mutation incidence and fitness changes with the impacts of mutations on immune evasion and ACE2 binding affinity. Our results show that the Omicron lineage had an accelerated mutation rate in the RBD region, while the mutation incidence in other genomic regions did not change dramatically over time. Mutations in the RBD region exhibited a lineage-specific pattern and tended to become more aggregated over time, and the mutation incidence was positively correlated with the strength of antibody pressure. Additionally, mutation incidence was positively correlated with changes in ACE2 binding affinity, but with a lower correlation coefficient than with immune evasion. In contrast, the effect of mutations on fitness was more closely correlated with changes in ACE2 binding affinity than with immune evasion. Our findings suggest that immune evasion and ACE2 binding affinity play significant and diverse roles in the evolution of SARS-CoV-2.
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Affiliation(s)
- Wentai Ma
- Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Haoyi Fu
- Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Fanchong Jian
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China
| | - Yunlong Cao
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.
- Changping Laboratory, Beijing, China.
| | - Mingkun Li
- Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing, China.
- University of Chinese Academy of Sciences, Beijing, China.
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32
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N’Guessan A, Kailasam S, Mostefai F, Poujol R, Grenier JC, Ismailova N, Contini P, De Palma R, Haber C, Stadler V, Bourque G, Hussin JG, Shapiro BJ, Fritz JH, Piccirillo CA. Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping and sequence analysis. iScience 2023; 26:107394. [PMID: 37599818 PMCID: PMC10433132 DOI: 10.1016/j.isci.2023.107394] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 02/10/2023] [Accepted: 07/10/2023] [Indexed: 08/22/2023] Open
Abstract
Here, we exploit a deep serological profiling strategy coupled with an integrated, computational framework for the analysis of SARS-CoV-2 humoral immune responses. Applying a high-density peptide array (HDPA) spanning the entire proteomes of SARS-CoV-2 and endemic human coronaviruses allowed identification of B cell epitopes and relate them to their evolutionary and structural properties. We identify hotspots of pre-existing immunity and identify cross-reactive epitopes that contribute to increasing the overall humoral immune response to SARS-CoV-2. Using a public dataset of over 38,000 viral genomes from the early phase of the pandemic, capturing both inter- and within-host genetic viral diversity, we determined the evolutionary profile of epitopes and the differences across proteins, waves, and SARS-CoV-2 variants. Lastly, we show that mutations in spike and nucleocapsid epitopes are under stronger selection between than within patients, suggesting that most of the selective pressure for immune evasion occurs upon transmission between hosts.
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Affiliation(s)
- Arnaud N’Guessan
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
- McGill Genome Centre, McGill University, Montréal, QC, Canada
| | - Senthilkumar Kailasam
- Canadian Center for Computational Genomics, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
| | - Fatima Mostefai
- Research Centre, Montreal Heart Institute, Montreal, QC, Canada
- Département de Biochimie et Médecine Moléculaire, Université de Montréal, Montréal, QC, Canada
| | - Raphaël Poujol
- Research Centre, Montreal Heart Institute, Montreal, QC, Canada
| | | | - Nailya Ismailova
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
- McGill University Research Center on Complex Traits (MRCCT), McGill University, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
| | - Paola Contini
- Department of Internal Medicine, University of Genoa and IRCCS IST-Ospedale San Martino, Genoa, Italy
| | - Raffaele De Palma
- Department of Internal Medicine, University of Genoa and IRCCS IST-Ospedale San Martino, Genoa, Italy
| | | | | | - Guillaume Bourque
- Canadian Center for Computational Genomics, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
| | - Julie G. Hussin
- Research Centre, Montreal Heart Institute, Montreal, QC, Canada
- Département de Médecine, Université de Montréal, Montréal, QC, Canada
| | - B. Jesse Shapiro
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
- McGill Genome Centre, McGill University, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
| | - Jörg H. Fritz
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
- McGill University Research Center on Complex Traits (MRCCT), McGill University, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
| | - Ciriaco A. Piccirillo
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
- McGill University Research Center on Complex Traits (MRCCT), McGill University, Montréal, QC, Canada
- Infectious Diseases and Immunity in Global Health Program of the Research Institute of McGill Health Center, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
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Li K, Melnychuk S, Sandstrom P, Ji H. Tracking the evolution of the SARS-CoV-2 Delta variant of concern: analysis of genetic diversity and selection across the whole viral genome. Front Microbiol 2023; 14:1222301. [PMID: 37614597 PMCID: PMC10443222 DOI: 10.3389/fmicb.2023.1222301] [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: 05/17/2023] [Accepted: 07/17/2023] [Indexed: 08/25/2023] Open
Abstract
Background Since 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has diversified extensively, producing five highly virulent lineages designated as variants of concern (VOCs). The Delta VOC emerged in India with increased transmission, immune evasion, and mortality, causing a massive global case surge in 2021. This study aims to understand how the Delta VOC evolved by characterizing mutation patterns in the viral population before and after its emergence. Furthermore, we aim to identify the influence of positive and negative selection on VOC evolution and understand the prevalence of different mutation types in the viral genome. Methods Three groups of whole viral genomes were retrieved from GISAID, sourced from India, with collection periods as follows: Group A-during the initial appearance of SARS-CoV-2; Group B-just before the emergence of the Delta variant; Group C-after the establishment of the Delta variant in India. Mutations in >1% of each group were identified with BioEdit to reveal differences in mutation quantity and type. Sites under positive or negative selection were identified with FUBAR. The results were compared to determine how mutations correspond with selective pressures and how viral mutation profiles changed to reflect genetic diversity before and after VOC emergence. Results The number of mutations increased progressively in Groups A-C, with Group C reporting a 2.2- and 1.9-fold increase from Groups A and B, respectively. Among all the observed mutations, Group C had the highest percentage of deletions (22.7%; vs. 4.2% and 2.6% in Groups A and B, respectively), and most mutations altered the final amino acid code, such as non-synonymous substitutions and deletions. Conversely, Group B had the most synonymous substitutions that are effectively silent. The number of sites experiencing positive selection increased in Groups A-C, but Group B had 2.4- and 2.6 times more sites under negative selection compared to Groups A and C, respectively. Conclusion Our findings demonstrated that viral genetic diversity continuously increased during and after the emergence of the Delta VOC. Despite this, Group B reports heightened negative selection, which potentially preserves important gene regions during evolution. Group C contains an unprecedented quantity of mutations and positively selected sites, providing strong evidence of active viral adaptation in the population.
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Affiliation(s)
- Katherine Li
- National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, MB, Canada
- Department of Medical Microbiology and Infectious Diseases, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, Canada
| | - Stephanie Melnychuk
- National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Paul Sandstrom
- National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, MB, Canada
- Department of Medical Microbiology and Infectious Diseases, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, Canada
| | - Hezhao Ji
- National Microbiology Laboratory at JC Wilt Infectious Diseases Research Centre, Public Health Agency of Canada, Winnipeg, MB, Canada
- Department of Medical Microbiology and Infectious Diseases, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB, Canada
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Velazquez-Salinas L. Deciphering the evolutionary mechanisms of SARS-CoV-2: Absence of ORF8 protein and its potential advantage in the emergence of viral lineages. J Med Virol 2023; 95:e29002. [PMID: 37534900 DOI: 10.1002/jmv.29002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 05/28/2023] [Accepted: 07/18/2023] [Indexed: 08/04/2023]
Affiliation(s)
- Lauro Velazquez-Salinas
- Plum Island Animal Disease Center, Agricultural Research Service, USDA, Greenport, New York, USA
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Rouzine IM. Long-range linkage effects in adapting sexual populations. Sci Rep 2023; 13:12492. [PMID: 37528175 PMCID: PMC10393966 DOI: 10.1038/s41598-023-39392-z] [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: 11/16/2022] [Accepted: 07/25/2023] [Indexed: 08/03/2023] Open
Abstract
In sexual populations, closely-situated genes have linked evolutionary fates, while genes spaced far in genome are commonly thought to evolve independently due to recombination. In the case where evolution depends essentially on supply of new mutations, this assumption has been confirmed by mathematical modeling. Here I examine it in the case of pre-existing genetic variation, where mutation is not important. A haploid population with [Formula: see text] genomes, [Formula: see text] loci, a fixed selection coefficient, and a small initial frequency of beneficial alleles [Formula: see text] is simulated by a Monte-Carlo algorithm. When the number of loci, L, is larger than a critical value of [Formula: see text] simulation demonstrates a host of linkage effects that decrease neither with the distance between loci nor the number of recombination crossovers. Due to clonal interference, the beneficial alleles become extinct at a fraction of loci [Formula: see text]. Due to a genetic background effect, the substitution rate varies broadly between loci, with the fastest value exceeding the one-locus limit by the factor of [Formula: see text] Thus, the far-situated parts of a long genome in a sexual population do not evolve as independent blocks. A potential link between these findings and the emergence of new Variants of Concern of SARS-CoV-2 is discussed.
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Affiliation(s)
- Igor M Rouzine
- Sechenov Institute of Evolutionary Physiology and Biochemistry, Russian Academy of Sciences, Saint-Petersburg, Russia, 194223.
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Castelán-Sánchez HG, Delaye L, Inward RPD, Dellicour S, Gutierrez B, Martinez de la Vina N, Boukadida C, Pybus OG, de Anda Jáuregui G, Guzmán P, Flores-Garrido M, Fontanelli Ó, Hernández Rosales M, Meneses A, Olmedo-Alvarez G, Herrera-Estrella AH, Sánchez-Flores A, Muñoz-Medina JE, Comas-García A, Gómez-Gil B, Zárate S, Taboada B, López S, Arias CF, Kraemer MUG, Lazcano A, Escalera Zamudio M. Comparing the evolutionary dynamics of predominant SARS-CoV-2 virus lineages co-circulating in Mexico. eLife 2023; 12:e82069. [PMID: 37498057 PMCID: PMC10431917 DOI: 10.7554/elife.82069] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 07/23/2023] [Indexed: 07/28/2023] Open
Abstract
Over 200 different SARS-CoV-2 lineages have been observed in Mexico by November 2021. To investigate lineage replacement dynamics, we applied a phylodynamic approach and explored the evolutionary trajectories of five dominant lineages that circulated during the first year of local transmission. For most lineages, peaks in sampling frequencies coincided with different epidemiological waves of infection in Mexico. Lineages B.1.1.222 and B.1.1.519 exhibited similar dynamics, constituting clades that likely originated in Mexico and persisted for >12 months. Lineages B.1.1.7, P.1 and B.1.617.2 also displayed similar dynamics, characterized by multiple introduction events leading to a few successful extended local transmission chains that persisted for several months. For the largest B.1.617.2 clades, we further explored viral lineage movements across Mexico. Many clades were located within the south region of the country, suggesting that this area played a key role in the spread of SARS-CoV-2 in Mexico.
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Affiliation(s)
- Hugo G Castelán-Sánchez
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Programa de Investigadoras e Investigadores por México, Consejo Nacional de Ciencia y TecnologíaMexico CityMexico
| | - Luis Delaye
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Departamento de Ingeniería Genética, CINVESTAV-Unidad IrapuatoGuanajuatoMexico
| | - Rhys PD Inward
- Department of Biology, University of OxfordOxfordUnited Kingdom
| | - Simon Dellicour
- Spatial Epidemiology Lab (SpELL), Université Libre de BruxellesBruxellesBelgium
- Department of Microbiology, Immunology and Transplantation, Rega Institute, KU LeuvenLeuvenBelgium
| | - Bernardo Gutierrez
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Department of Biology, University of OxfordOxfordUnited Kingdom
| | | | - Celia Boukadida
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades RespiratoriasMexico CityMexico
| | - Oliver G Pybus
- Department of Biology, University of OxfordOxfordUnited Kingdom
- Department of Pathobiology, Royal Veterinary CollegeLondonUnited Kingdom
| | - Guillermo de Anda Jáuregui
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Programa de Investigadoras e Investigadores por México, Consejo Nacional de Ciencia y TecnologíaMexico CityMexico
- Instituto Nacional de Medicina GenómicaMexico CityMexico
| | | | - Marisol Flores-Garrido
- Escuela Nacional de Estudios Superiores, Universidad Nacional Autónoma de MéxicoMexico CityMexico
- Departamento de Ciencias de la Computación, CINVESTAV-IPNMexico CityMexico
| | - Óscar Fontanelli
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Departamento de Ingeniería Genética, CINVESTAV-Unidad IrapuatoGuanajuatoMexico
| | - Maribel Hernández Rosales
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Departamento de Ingeniería Genética, CINVESTAV-Unidad IrapuatoGuanajuatoMexico
| | - Amilcar Meneses
- Escuela Nacional de Estudios Superiores, Universidad Nacional Autónoma de MéxicoMexico CityMexico
- Departamento de Ciencias de la Computación, CINVESTAV-IPNMexico CityMexico
| | - Gabriela Olmedo-Alvarez
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Departamento de Ingeniería Genética, CINVESTAV-Unidad IrapuatoGuanajuatoMexico
| | - Alfredo Heriberto Herrera-Estrella
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Laboratorio de expresión génica y desarrollo en hongos, CINVESTAV-Unidad IrapuatoIrapuatoMexico
| | - Alejandro Sánchez-Flores
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Unidad Universitaria de Secuenciación Masiva y Bioinformática, Instituto de Biotecnología, Universidad Nacional Autónoma de MéxicoChamilpaMexico
| | - José Esteban Muñoz-Medina
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro SocialMexico CityMexico
| | - Andreu Comas-García
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Facultad de Medicina y Centro de Investigación en Ciencias de la Salud y Biomedicina, Universidad Autónoma de San Luis PotosíSan Luis PotosíMexico
| | - Bruno Gómez-Gil
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Centro de Investigación en Alimentación y Desarrollo-CIAD, Unidad Regional Mazatlán en Acuicultura y Manejo AmbientalSinaloaMexico
| | - Selene Zárate
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Posgrado en Ciencias Genómicas, Universidad Autónoma de la Ciudad de MéxicoMexico CityMexico
| | - Blanca Taboada
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Departamento de Genética del Desarrollo y Fisiología Molecular, Universidad Nacional Autónoma de MéxicoCuernavacaMexico
| | - Susana López
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Departamento de Genética del Desarrollo y Fisiología Molecular, Universidad Nacional Autónoma de MéxicoCuernavacaMexico
| | - Carlos F Arias
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Departamento de Genética del Desarrollo y Fisiología Molecular, Universidad Nacional Autónoma de MéxicoCuernavacaMexico
| | - Moritz UG Kraemer
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Department of Biology, University of OxfordOxfordUnited Kingdom
| | - Antonio Lazcano
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Facultad de Ciencias, Universidad Nacional Autónoma de MéxicMexico CityMexico
| | - Marina Escalera Zamudio
- Consorcio Mexicano de Vigilancia Genómica (CoViGen-Mex)Mexico CityMexico
- Department of Biology, University of OxfordOxfordUnited Kingdom
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Lucaci AG, Zehr JD, Enard D, Thornton JW, Kosakovsky Pond SL. Evolutionary Shortcuts via Multinucleotide Substitutions and Their Impact on Natural Selection Analyses. Mol Biol Evol 2023; 40:msad150. [PMID: 37395787 PMCID: PMC10336034 DOI: 10.1093/molbev/msad150] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 06/15/2023] [Accepted: 06/26/2023] [Indexed: 07/04/2023] Open
Abstract
Inference and interpretation of evolutionary processes, in particular of the types and targets of natural selection affecting coding sequences, are critically influenced by the assumptions built into statistical models and tests. If certain aspects of the substitution process (even when they are not of direct interest) are presumed absent or are modeled with too crude of a simplification, estimates of key model parameters can become biased, often systematically, and lead to poor statistical performance. Previous work established that failing to accommodate multinucleotide (or multihit, MH) substitutions strongly biases dN/dS-based inference towards false-positive inferences of diversifying episodic selection, as does failing to model variation in the rate of synonymous substitution (SRV) among sites. Here, we develop an integrated analytical framework and software tools to simultaneously incorporate these sources of evolutionary complexity into selection analyses. We found that both MH and SRV are ubiquitous in empirical alignments, and incorporating them has a strong effect on whether or not positive selection is detected (1.4-fold reduction) and on the distributions of inferred evolutionary rates. With simulation studies, we show that this effect is not attributable to reduced statistical power caused by using a more complex model. After a detailed examination of 21 benchmark alignments and a new high-resolution analysis showing which parts of the alignment provide support for positive selection, we show that MH substitutions occurring along shorter branches in the tree explain a significant fraction of discrepant results in selection detection. Our results add to the growing body of literature which examines decades-old modeling assumptions (including MH) and finds them to be problematic for comparative genomic data analysis. Because multinucleotide substitutions have a significant impact on natural selection detection even at the level of an entire gene, we recommend that selection analyses of this type consider their inclusion as a matter of routine. To facilitate this procedure, we developed, implemented, and benchmarked a simple and well-performing model testing selection detection framework able to screen an alignment for positive selection with two biologically important confounding processes: site-to-site synonymous rate variation, and multinucleotide instantaneous substitutions.
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Affiliation(s)
- Alexander G Lucaci
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
| | - Jordan D Zehr
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
| | - David Enard
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona
| | - Joseph W Thornton
- Department of Human Genetics, University of Chicago, Chicago, Illinois
- Department of Ecology & Evolution, University of Chicago, Chicago, Illinois
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Ferdous N, Reza MN, Hossain MU, Mahmud S, Napis S, Chowdhury K, Mohiuddin AKM. Mpropred: A machine learning (ML) driven Web-App for bioactivity prediction of SARS-CoV-2 main protease (Mpro) antagonists. PLoS One 2023; 18:e0287179. [PMID: 37352252 PMCID: PMC10289339 DOI: 10.1371/journal.pone.0287179] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Accepted: 05/31/2023] [Indexed: 06/25/2023] Open
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic emerged in 2019 and still requiring treatments with fast clinical translatability. Frequent occurrence of mutations in spike glycoprotein of SARS-CoV-2 led the consideration of an alternative therapeutic target to combat the ongoing pandemic. The main protease (Mpro) is such an attractive drug target due to its importance in maturating several polyproteins during the replication process. In the present study, we used a classification structure-activity relationship (CSAR) model to find substructures that leads to to anti-Mpro activities among 758 non-redundant compounds. A set of 12 fingerprints were used to describe Mpro inhibitors, and the random forest approach was used to build prediction models from 100 distinct data splits. The data set's modelability (MODI index) was found to be robust, with a value of 0.79 above the 0.65 threshold. The accuracy (89%), sensitivity (89%), specificity (73%), and Matthews correlation coefficient (79%) used to calculate the prediction performance, was also found to be statistically robust. An extensive analysis of the top significant descriptors unveiled the significance of methyl side chains, aromatic ring and halogen groups for Mpro inhibition. Finally, the predictive model is made publicly accessible as a web-app named Mpropred in order to allow users to predict the bioactivity of compounds against SARS-CoV-2 Mpro. Later, CMNPD, a marine compound database was screened by our app to predict bioactivity of all the compounds and results revealed significant correlation with their binding affinity to Mpro. Molecular dynamics (MD) simulation and molecular mechanics/Poisson Boltzmann surface area (MM/PBSA) analysis showed improved properties of the complexes. Thus, the knowledge and web-app shown herein can be used to develop more effective and specific inhibitors against the SARS-CoV-2 Mpro. The web-app can be accessed from https://share.streamlit.io/nadimfrds/mpropred/Mpropred_app.py.
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Affiliation(s)
- Nadim Ferdous
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Santosh, Tangail, Bangladesh
| | - Mahjerin Nasrin Reza
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Santosh, Tangail, Bangladesh
| | - Mohammad Uzzal Hossain
- Department of Pharmacology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
- Bioinformatics Division, National Institute of Biotechnology, Ashulia, Ganakbari, Savar, Dhaka, Bangladesh
| | - Shahin Mahmud
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Santosh, Tangail, Bangladesh
| | - Suhami Napis
- Department of Molecular Biology, Universiti Putra Malaysia, Serdang, Selangor D.E., Malaysia
| | - Kamal Chowdhury
- Biology Department, Claflin University, Orangeburg, SC, United States of America
| | - A. K. M. Mohiuddin
- Department of Biotechnology and Genetic Engineering, Mawlana Bhashani Science and Technology University, Santosh, Tangail, Bangladesh
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Rouzine IM, Rozhnova G. Evolutionary implications of SARS-CoV-2 vaccination for the future design of vaccination strategies. COMMUNICATIONS MEDICINE 2023; 3:86. [PMID: 37336956 DOI: 10.1038/s43856-023-00320-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 06/07/2023] [Indexed: 06/21/2023] Open
Abstract
Once the first SARS-CoV-2 vaccine became available, mass vaccination was the main pillar of the public health response to the COVID-19 pandemic. It was very effective in reducing hospitalizations and deaths. Here, we discuss the possibility that mass vaccination might accelerate SARS-CoV-2 evolution in antibody-binding regions compared to natural infection at the population level. Using the evidence of strong genetic variation in antibody-binding regions and taking advantage of the similarity between the envelope proteins of SARS-CoV-2 and influenza, we assume that immune selection pressure acting on these regions of the two viruses is similar. We discuss the consequences of this assumption for SARS-CoV-2 evolution in light of mathematical models developed previously for influenza. We further outline the implications of this phenomenon, if our assumptions are confirmed, for the future design of SARS-CoV-2 vaccination strategies.
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Affiliation(s)
- Igor M Rouzine
- Immunogenetics, Sechenov Institute of Evolutionary Physiology and Biochemistry of Russian Academy of Sciences, Saint-Petersburg, Russia.
| | - Ganna Rozhnova
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
- BioISI - Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.
- Center for Complex Systems Studies (CCSS), Utrecht University, Utrecht, The Netherlands.
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40
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Niveditha D, Khan S, Khilari A, Nadkarni S, Bhalerao U, Kadam P, Yadav R, Kanekar JB, Shah N, Likhitkar B, Sawant R, Thakur S, Tupekar M, Nagar D, Rao AG, Jagtap R, Jogi S, Belekar M, Pathak M, Shah P, Ranade S, Phadke N, Das R, Joshi S, Karyakarte R, Ghose A, Kadoo N, Shashidhara LS, Monteiro JM, Shanmugam D, Raghunathan A, Karmodiya K. A tale of two waves: Delineating diverse genomic and transmission landscapes driving the COVID-19 pandemic in Pune, India. J Infect Public Health 2023; 16:1290-1300. [PMID: 37331277 DOI: 10.1016/j.jiph.2023.06.004] [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: 02/07/2023] [Revised: 05/30/2023] [Accepted: 06/06/2023] [Indexed: 06/20/2023] Open
Abstract
BACKGROUND Modern response to pandemics, critical for effective public health measures, is shaped by the availability and integration of diverse epidemiological outbreak data. Tracking variants of concern (VOC) is integral to understanding the evolution of SARS-CoV-2 in space and time, both at the local level and global context. This potentially generates actionable information when integrated with epidemiological outbreak data. METHODS A city-wide network of researchers, clinicians, and pathology diagnostic laboratories was formed for genome surveillance of COVID-19 in Pune, India. The genomic landscapes of 10,496 sequenced samples of SARS-CoV-2 driving peaks of infection in Pune between December-2020 to March-2022, were determined. As a modern response to the pandemic, a "band of five" outbreak data analytics approach was used. This integrated the genomic data (Band 1) of the virus through molecular phylogenetics with key outbreak data including sample collection dates and case numbers (Band 2), demographics like age and gender (Band 3-4), and geospatial mapping (Band 5). RESULTS The transmission dynamics of VOCs in 10,496 sequenced samples identified B.1.617.2 (Delta) and BA(x) (Omicron formerly known as B.1.1.529) variants as drivers of the second and third peaks of infection in Pune. Spike Protein mutational profiling during pre and post-Omicron VOCs indicated differential rank ordering of high-frequency mutations in specific domains that increased the charge and binding properties of the protein. Time-resolved phylogenetic analysis of Omicron sub-lineages identified a highly divergent BA.1 from Pune in addition to recombinant X lineages, XZ, XQ, and XM. CONCLUSIONS The band of five outbreak data analytics approach, which integrates five different types of data, highlights the importance of a strong surveillance system with high-quality meta-data for understanding the spatiotemporal evolution of the SARS-CoV-2 genome in Pune. These findings have important implications for pandemic preparedness and could be critical tools for understanding and responding to future outbreaks.
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Affiliation(s)
- Divya Niveditha
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Soumen Khan
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Ajinkya Khilari
- Biochemical Sciences Division, CSIR - National Chemical Laboratory, Dr. Homi Bhabha Road, 411008, Pune, India.; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Sanica Nadkarni
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Unnati Bhalerao
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Pradnya Kadam
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Ritu Yadav
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Jugal B Kanekar
- Biochemical Sciences Division, CSIR - National Chemical Laboratory, Dr. Homi Bhabha Road, 411008, Pune, India.; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Nikita Shah
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Bhagyashree Likhitkar
- Biochemical Sciences Division, CSIR - National Chemical Laboratory, Dr. Homi Bhabha Road, 411008, Pune, India.; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Rutuja Sawant
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Shikha Thakur
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Manisha Tupekar
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Dhriti Nagar
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Anjani G Rao
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Rutuja Jagtap
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India
| | - Shraddha Jogi
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Madhuri Belekar
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Maitreyee Pathak
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Priyanki Shah
- The Pune Knowledge Cluster (PKC), Savitribai Phule Pune University, Ganeshkhind Road, 411007 Pune, India
| | | | - Nikhil Phadke
- GenePath Diagnostics India Private Limited, Pune 411004, India
| | - Rashmita Das
- Byramjee Jeejeebhoy Government Medical College (BJGMC), Jai Prakash Narayan Road, Pune 411001, India
| | - Suvarna Joshi
- Byramjee Jeejeebhoy Government Medical College (BJGMC), Jai Prakash Narayan Road, Pune 411001, India
| | - Rajesh Karyakarte
- Byramjee Jeejeebhoy Government Medical College (BJGMC), Jai Prakash Narayan Road, Pune 411001, India
| | - Aurnab Ghose
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Narendra Kadoo
- Biochemical Sciences Division, CSIR - National Chemical Laboratory, Dr. Homi Bhabha Road, 411008, Pune, India.; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - L S Shashidhara
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India; The Pune Knowledge Cluster (PKC), Savitribai Phule Pune University, Ganeshkhind Road, 411007 Pune, India
| | - Joy Merwin Monteiro
- Department of Earth and Climate Science, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India; Department of Data Science, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India
| | - Dhanasekaran Shanmugam
- Biochemical Sciences Division, CSIR - National Chemical Laboratory, Dr. Homi Bhabha Road, 411008, Pune, India.; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India
| | - Anu Raghunathan
- Chemical Engineering & Process Development Division, CSIR-National Chemical Laboratory, Dr. Homi Bhabha Road, Pune 411008, India; Academy of Scientific and Innovative Research (AcSIR), CSIR-HRDC, Ghaziabad 201002, India.
| | - Krishanpal Karmodiya
- Department of Biology, Indian Institute of Science Education and Research, Dr. Homi Bhabha Road, Pashan, Pune 411008, India.
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Moustafa RI, Faraag AHI, El-Shenawy R, Agwa MM, Elsayed H. Harnessing immunoinformatics for developing a multiple-epitope peptide-based vaccination approach against SARS-CoV-2 spike protein. Saudi J Biol Sci 2023; 30:103661. [PMID: 37163156 PMCID: PMC10141799 DOI: 10.1016/j.sjbs.2023.103661] [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: 02/27/2023] [Revised: 03/30/2023] [Accepted: 04/21/2023] [Indexed: 05/11/2023] Open
Abstract
COVID-19 has spread to over 200 countries with variable severity and mortality rates. Computational analysis is a valuable tool for developing B-cell and T-cell epitope-based vaccines. In this study, by harnessing immunoinformatics tools, we designed a multiple-epitope vaccine to protect against COVID-19. The candidate epitopes were designed from highly conserved regions of the SARS-CoV-2 spike (S) glycoprotein. The consensus amino acids sequence of ten SARS-CoV-2 variants including Gamma, Beta, Epsilon, Delta, Alpha, Kappa, Iota, Lambda, Mu, and Omicron was involved. Applying the multiple sequence alignment plugin and the antigenic prediction tools of Geneious prime 2021, ten predicted variants were identified and consensus S-protein sequences were used to predict the antigenic part. According to ElliPro analysis of S-protein B-cell prediction, we explored 22 continuous linear epitopes with high scores ranging from 0.879 to 0.522. First, we reported five promising epitopes: BE1 1115-1192, BE2 481-563, BE3 287-313, BE4 62-75, and BE5 112-131 with antigenicity scores of 0.879, 0.86, 0.813, 0.779, and 0.765, respectively, while only nine discontinuous epitopes scored between 0.971 and 0.511. Next, we identified 194 Major Histocompatibility Complex (MHC) - I and 156 MHC - II epitopes with antigenic characteristics. These spike-specific peptide-epitopes with characteristically high immunogenic and antigenic scores have the potential as a SARS-CoV-2 multiple-epitope peptide-based vaccination strategy. Nevertheless, further experimental investigations are needed to test for the vaccine efficacy and efficiency.
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Affiliation(s)
- Rehab I Moustafa
- Department of Microbial Biotechnology, Biotechnology Research Institute, National Research Centre, Egypt
| | - Ahmed H I Faraag
- Botany and Microbiology Department, Faculty of Science, Helwan University, Egypt
- School of Biotechnology, Badr University in Cairo, Egypt
| | | | - Mona M Agwa
- Department of Chemistry of Natural and Microbial Products, Pharmaceutical and Drug Industries Research Institute, National Research Centre, Egypt
| | - Hassan Elsayed
- Department of Microbial Biotechnology, Biotechnology Research Institute, National Research Centre, Egypt
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42
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Cheng Y, Ji C, Zhou HY, Zheng H, Wu A. Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking. Viruses 2023; 15:v15051158. [PMID: 37243244 DOI: 10.3390/v15051158] [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: 04/04/2023] [Revised: 05/10/2023] [Accepted: 05/10/2023] [Indexed: 05/28/2023] Open
Abstract
The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus.
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Affiliation(s)
- Yexiao Cheng
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 211100, China
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
| | - Chengyang Ji
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
| | - Hang-Yu Zhou
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
| | - Heng Zheng
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 211100, China
| | - Aiping Wu
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
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43
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Ito J, Suzuki R, Uriu K, Itakura Y, Zahradnik J, Kimura KT, Deguchi S, Wang L, Lytras S, Tamura T, Kida I, Nasser H, Shofa M, Begum MM, Tsuda M, Oda Y, Suzuki T, Sasaki J, Sasaki-Tabata K, Fujita S, Yoshimatsu K, Ito H, Nao N, Asakura H, Nagashima M, Sadamasu K, Yoshimura K, Yamamoto Y, Nagamoto T, Kuramochi J, Schreiber G, Saito A, Matsuno K, Takayama K, Hashiguchi T, Tanaka S, Fukuhara T, Ikeda T, Sato K. Convergent evolution of SARS-CoV-2 Omicron subvariants leading to the emergence of BQ.1.1 variant. Nat Commun 2023; 14:2671. [PMID: 37169744 PMCID: PMC10175283 DOI: 10.1038/s41467-023-38188-z] [Citation(s) in RCA: 46] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 04/18/2023] [Indexed: 05/13/2023] Open
Abstract
In late 2022, various Omicron subvariants emerged and cocirculated worldwide. These variants convergently acquired amino acid substitutions at critical residues in the spike protein, including residues R346, K444, L452, N460, and F486. Here, we characterize the convergent evolution of Omicron subvariants and the properties of one recent lineage of concern, BQ.1.1. Our phylogenetic analysis suggests that these five substitutions are recurrently acquired, particularly in younger Omicron lineages. Epidemic dynamics modelling suggests that the five substitutions increase viral fitness, and a large proportion of the fitness variation within Omicron lineages can be explained by these substitutions. Compared to BA.5, BQ.1.1 evades breakthrough BA.2 and BA.5 infection sera more efficiently, as demonstrated by neutralization assays. The pathogenicity of BQ.1.1 in hamsters is lower than that of BA.5. Our multiscale investigations illuminate the evolutionary rules governing the convergent evolution for known Omicron lineages as of 2022.
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Affiliation(s)
- Jumpei Ito
- Division of Systems Virology, Department of Microbiology and Immunology, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Rigel Suzuki
- Department of Microbiology and Immunology, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Keiya Uriu
- Division of Systems Virology, Department of Microbiology and Immunology, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yukari Itakura
- Division of Molecular Pathobiology, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Jiri Zahradnik
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
- First Medical Faculty at Biocev, Charles University, Vestec-Prague, Czechia
| | - Kanako Terakado Kimura
- Laboratory of Medical Virology, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
| | - Sayaka Deguchi
- Center for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto, Japan
| | - Lei Wang
- Department of Cancer Pathology, Faculty of Medicine, Hokkaido University, Sapporo, Japan
- Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Sapporo, Japan
| | - Spyros Lytras
- Medical Research Council-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Tomokazu Tamura
- Department of Microbiology and Immunology, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Izumi Kida
- Division of Risk Analysis and Management, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Hesham Nasser
- Division of Molecular Virology and Genetics, Joint Research Center for Human Retrovirus infection, Kumamoto University, Kumamoto, Japan
- Department of Clinical Pathology, Faculty of Medicine, Suez Canal University, Ismailia, Egypt
| | - Maya Shofa
- Department of Veterinary Science, Faculty of Agriculture, University of Miyazaki, Miyazaki, Japan
- Graduate School of Medicine and Veterinary Medicine, University of Miyazaki, Miyazaki, Japan
| | - Mst Monira Begum
- Division of Molecular Virology and Genetics, Joint Research Center for Human Retrovirus infection, Kumamoto University, Kumamoto, Japan
| | - Masumi Tsuda
- Department of Cancer Pathology, Faculty of Medicine, Hokkaido University, Sapporo, Japan
- Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Sapporo, Japan
| | - Yoshitaka Oda
- Department of Cancer Pathology, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Tateki Suzuki
- Laboratory of Medical Virology, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
| | - Jiei Sasaki
- Laboratory of Medical Virology, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
| | - Kaori Sasaki-Tabata
- Department of Medicinal Sciences, Graduate School of Pharmaceutical Sciences, Kyushu University, Fukuoka, Japan
| | - Shigeru Fujita
- Division of Systems Virology, Department of Microbiology and Immunology, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
- Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | | | - Hayato Ito
- Department of Microbiology and Immunology, Faculty of Medicine, Hokkaido University, Sapporo, Japan
| | - Naganori Nao
- Division of International Research Promotion, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- One Health Research Center, Hokkaido University, Sapporo, Japan
- Institute for Vaccine Research and Development: HU-IVReD, Hokkaido University, Sapporo, Japan
| | | | - Mami Nagashima
- Tokyo Metropolitan Institute of Public Health, Tokyo, Japan
| | - Kenji Sadamasu
- Tokyo Metropolitan Institute of Public Health, Tokyo, Japan
| | | | | | | | - Jin Kuramochi
- Interpark Kuramochi Clinic, Utsunomiya, Japan
- Department of Global Health Promotion, Tokyo Medical and Dental University, Tokyo, Japan
| | - Gideon Schreiber
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Akatsuki Saito
- Department of Veterinary Science, Faculty of Agriculture, University of Miyazaki, Miyazaki, Japan
- Graduate School of Medicine and Veterinary Medicine, University of Miyazaki, Miyazaki, Japan
- Center for Animal Disease Control, University of Miyazaki, Miyazaki, Japan
| | - Keita Matsuno
- Division of Risk Analysis and Management, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
- Institute for Vaccine Research and Development: HU-IVReD, Hokkaido University, Sapporo, Japan
- International Collaboration Unit, International Institute for Zoonosis Control, Hokkaido University, Sapporo, Japan
| | - Kazuo Takayama
- Center for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto, Japan
- AMED-CREST, Japan Agency for Medical Research and Development (AMED), Tokyo, Japan
| | - Takao Hashiguchi
- Laboratory of Medical Virology, Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan.
| | - Shinya Tanaka
- Department of Cancer Pathology, Faculty of Medicine, Hokkaido University, Sapporo, Japan.
- Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Sapporo, Japan.
| | - Takasuke Fukuhara
- Department of Microbiology and Immunology, Faculty of Medicine, Hokkaido University, Sapporo, Japan.
- AMED-CREST, Japan Agency for Medical Research and Development (AMED), Tokyo, Japan.
- Laboratory of Virus Control, Research Institute for Microbial Diseases, Osaka University, Suita, Japan.
| | - Terumasa Ikeda
- Division of Molecular Virology and Genetics, Joint Research Center for Human Retrovirus infection, Kumamoto University, Kumamoto, Japan.
| | - Kei Sato
- Division of Systems Virology, Department of Microbiology and Immunology, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
- Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
- International Research Center for Infectious Diseases, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
- International Vaccine Design Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
- Graduate School of Frontier Sciences, The University of Tokyo, Kashiwa, Japan.
- Collaboration Unit for Infection, Joint Research Center for Human Retrovirus infection, Kumamoto University, Kumamoto, Japan.
- CREST, Japan Science and Technology Agency, Kawaguchi, Japan.
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Gonçalves-Brito AS, Magaldi M, Farias BO, Nascimento APA, Flores C, Montenegro KS, Lopes-Carvalho M, Gimenez A, Costa VSC, Assunção VC, Quidorne CS, Bianco K, Clementino MM. Environmental genomic surveillance of SARS-CoV-2 in wastewater in Rio de Janeiro, Brazil. JOURNAL OF WATER AND HEALTH 2023; 21:653-662. [PMID: 37254912 PMCID: wh_2023_034 DOI: 10.2166/wh.2023.034] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
Wastewater-based epidemiology can be a complementary approach for monitoring SARS-CoV-2 prevalence, diversity, and geographic distribution. It is a complementary approach regarding its prevalence and diversity, and geographic distribution. The study aimed to evaluate the genetic diversity of SARS-CoV-2 in two wastewater treatment plants (WWTPs) in Rio de Janeiro, Brazil. Samples were collected over a period of January to December 2021 and were concentrated with PEG8000 and the presence of SARS-CoV-2 was detected using E and N1 genes. Partial sequencing of the SARS-CoV-2 genomes resulted in the identification of variants of concern and variants of interest throughout the collection period. It was possible to identify the Mu, Delta, Gamma and Omicron variants in WWTP1; on the contrary, no variants were observed in WWTP2. To the best of our knowledge, we detected the variant Mu (B.1.621) containing characteristic mutations (S:E484K, S:N501Y) from WWTP, for the first time, in Brazil. Another Mu variant detected from clinical surveillance was announced one month after our finding. The detection of SARS-CoV-2 in wastewater can serve as a tool to monitor the prevalence and epidemiology in each community, helping to understand the spread of the virus among the population.
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Affiliation(s)
- Andressa S Gonçalves-Brito
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail: ; Fiocruz Genomic Network, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil
| | - Mariana Magaldi
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail: ; Fiocruz Genomic Network, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil
| | - Beatriz Oliveira Farias
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail: ; Fiocruz Genomic Network, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil
| | - Ana Paula Alves Nascimento
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail:
| | - Claudia Flores
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail:
| | - Kaylanne S Montenegro
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail:
| | - Maiara Lopes-Carvalho
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail:
| | - Aline Gimenez
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail:
| | - Vinícius Souza Carvalho Costa
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail:
| | - Vinícius Carneiro Assunção
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail:
| | - Camila Silva Quidorne
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail:
| | - Kayo Bianco
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail: ; Fiocruz Genomic Network, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil; COVID-19 Monitoring Network in Wastewater, São Paulo, Brazil
| | - Maysa M Clementino
- National Institute of Quality Control in Health - INCQS, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil E-mail: ; Fiocruz Genomic Network, Oswaldo Cruz Foundation - FIOCRUZ, Rio de Janeiro, RJ 4365, Brazil; COVID-19 Monitoring Network in Wastewater, São Paulo, Brazil
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45
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de Souza Andrade A, Freitas EF, de Castro Barbosa E, Guimarães N, de Melo Iani FC, da Costa AVB, Bernardes AFL, Adelino TER, Ataide ACZ, Gregianini TS, Nunes JD, Stringari LL, Riediger IN, Fernandes SB, de Jesus R, Fonseca V, Caldas S. Potential use of high-resolution melting analyses for SARS-CoV-2 genomic surveillance. J Virol Methods 2023; 317:114742. [PMID: 37116586 PMCID: PMC10132831 DOI: 10.1016/j.jviromet.2023.114742] [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: 02/22/2023] [Revised: 04/23/2023] [Accepted: 04/25/2023] [Indexed: 04/30/2023]
Abstract
The pandemic caused by COVID-19 and the emergence of new variants of SARS-CoV-2 have generated clinical and epidemiological impacts on a global scale. The use of strategies for monitoring viral circulation and identifying mutations in genomic regions involved in host interaction are important measures to mitigate viral dissemination and reduce its likely complications on population health. In this context, the objective of this work was to explore the potential of high-resolution melting (HRM) analysis combined with one-step real-time reverse transcription PCR in a closed-tube system, as a fast and convenient method of screening for SARS-CoV-2 mutations with possible implications on host-pathogen interactions. The HRM analyses allowed the distinction of the Gamma, Zeta, Alpha, Delta, and Omicron variants against the predecessors (B.1.1.28, B.1.1.33) of occurrence in Brazil. It is concluded that the molecular tool standardized here has the potential to optimize the genomic surveillance of SARS-CoV-2, and could be adapted for genomic surveillance of other pathogens, due to its ability to detect, prior to sequencing, samples suggestive of new variants, selecting them more assertively and earlier for whole genome sequencing when compared to random screening.
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Affiliation(s)
- Adriana de Souza Andrade
- Serviço de Pesquisa em Doenças Infecciosas, Divisão de Ciência e Inovação, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil
| | - Eduarda Fernandes Freitas
- Serviço de Pesquisa em Doenças Infecciosas, Divisão de Ciência e Inovação, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil; Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Emerson de Castro Barbosa
- Serviço de Pesquisa em Doenças Infecciosas, Divisão de Ciência e Inovação, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil; Serviço de Virologia e Riquetsioses, Divisão de Epidemiologia e Controle de Doenças, Laboratório Central do Estado de Minas Gerais, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil
| | - Natália Guimarães
- Serviço de Virologia e Riquetsioses, Divisão de Epidemiologia e Controle de Doenças, Laboratório Central do Estado de Minas Gerais, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil
| | - Felipe Campos de Melo Iani
- Serviço de Virologia e Riquetsioses, Divisão de Epidemiologia e Controle de Doenças, Laboratório Central do Estado de Minas Gerais, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil; Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Alana Vitor Barbosa da Costa
- Serviço de Virologia e Riquetsioses, Divisão de Epidemiologia e Controle de Doenças, Laboratório Central do Estado de Minas Gerais, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil
| | - André Felipe Leal Bernardes
- Serviço de Virologia e Riquetsioses, Divisão de Epidemiologia e Controle de Doenças, Laboratório Central do Estado de Minas Gerais, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil
| | - Talita Emile Ribeiro Adelino
- Serviço de Virologia e Riquetsioses, Divisão de Epidemiologia e Controle de Doenças, Laboratório Central do Estado de Minas Gerais, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil
| | - Ana Caroline Zampiroli Ataide
- Serviço de Pesquisa em Doenças Infecciosas, Divisão de Ciência e Inovação, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil
| | - Tatiana Schäffer Gregianini
- Laboratório de Influenza e outros Vírus Respiratórios, Laboratório de Biologia Molecular de Dengue, Febre Amarela, Zika e Chikungunya, Seção de Virologia. Laboratório Central do Estado do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Jônathas Dias Nunes
- Laboratório Central Noel Nutels. Laboratório Central do Estado do Rio de Janeiro, Rio de Janeiro, RJ, Brazil
| | - Lorenzzo L Stringari
- Laboratório Central de Saúde Pública do Estado do Espírito Santo, Secretaria de Estado de Saúde do Espírito Santo, Vitória, ES, Brazil; Núcleo de Doenças Infecciosas, Universidade Federal do Espírito Santo, Vitória, ES, Brazil
| | - Irina Nastassja Riediger
- Divisão dos Laboratórios de Epidemiologia e Controle de Doenças, Laboratório Central do Estado do Paraná, São José dos Pinhais, PR, Brazil
| | | | - Ronaldo de Jesus
- Coordenação-Geral de Laboratórios de Saúde Pública, Ministério da Saúde, Brasília, Distrito Federal, Brazil; Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil
| | - Vagner Fonseca
- Organização Pan-Americana da Saúde/Organização Mundial da Saúde, Brasília, Distrito Federal, Brazil
| | - Sérgio Caldas
- Serviço de Pesquisa em Doenças Infecciosas, Divisão de Ciência e Inovação, Fundação Ezequiel Dias, Belo Horizonte, MG, Brazil.
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46
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Bloom JD, Beichman AC, Neher RA, Harris K. Evolution of the SARS-CoV-2 Mutational Spectrum. Mol Biol Evol 2023; 40:msad085. [PMID: 37039557 PMCID: PMC10124870 DOI: 10.1093/molbev/msad085] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Revised: 02/07/2023] [Accepted: 04/06/2023] [Indexed: 04/12/2023] Open
Abstract
SARS-CoV-2 evolves rapidly in part because of its high mutation rate. Here, we examine whether this mutational process itself has changed during viral evolution. To do this, we quantify the relative rates of different types of single-nucleotide mutations at 4-fold degenerate sites in the viral genome across millions of human SARS-CoV-2 sequences. We find clear shifts in the relative rates of several types of mutations during SARS-CoV-2 evolution. The most striking trend is a roughly 2-fold decrease in the relative rate of G→T mutations in Omicron versus early clades, as was recently noted by Ruis et al. (2022. Mutational spectra distinguish SARS-CoV-2 replication niches. bioRxiv, doi:10.1101/2022.09.27.509649). There is also a decrease in the relative rate of C→T mutations in Delta, and other subtle changes in the mutation spectrum along the phylogeny. We speculate that these changes in the mutation spectrum could arise from viral mutations that affect genome replication, packaging, and antagonization of host innate-immune factors, although environmental factors could also play a role. Interestingly, the mutation spectrum of Omicron is more similar than that of earlier SARS-CoV-2 clades to the spectrum that shaped the long-term evolution of sarbecoviruses. Overall, our work shows that the mutation process is itself a dynamic variable during SARS-CoV-2 evolution and suggests that human SARS-CoV-2 may be trending toward a mutation spectrum more similar to that of other animal sarbecoviruses.
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Affiliation(s)
- Jesse D Bloom
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer Center, Seattle, WA
- Department of Genome Sciences, University of Washington, Seattle, WA
- Howard Hughes Medical Institute, Seattle, WA
| | | | - Richard A Neher
- Biozentrum, University of Basel, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Kelley Harris
- Department of Genome Sciences, University of Washington, Seattle, WA
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47
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Kun Á, Hubai AG, Král A, Mokos J, Mikulecz BÁ, Radványi Á. Do pathogens always evolve to be less virulent? The virulence–transmission trade-off in light of the COVID-19 pandemic. Biol Futur 2023:10.1007/s42977-023-00159-2. [PMID: 37002448 PMCID: PMC10066022 DOI: 10.1007/s42977-023-00159-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 03/09/2023] [Indexed: 04/03/2023]
Abstract
AbstractThe direction the evolution of virulence takes in connection with any pathogen is a long-standing question. Formerly, it was theorized that pathogens should always evolve to be less virulent. As observations were not in line with this theoretical outcome, new theories emerged, chief among them the transmission–virulence trade-off hypotheses, which predicts an intermediate level of virulence as the endpoint of evolution. At the moment, we are very much interested in the future evolution of COVID-19’s virulence. Here, we show that the disease does not fulfill all the assumptions of the hypothesis. In the case of COVID-19, a higher viral load does not mean a higher risk of death; immunity is not long-lasting; other hosts can act as reservoirs for the virus; and death as a consequence of viral infection does not shorten the infectious period. Consequently, we cannot predict the short- or long-term evolution of the virulence of COVID-19.
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48
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Akhter N, Sana S, Adnan Ahsan M, Siddique Z, Huraira A, Sana S. Advances in Diagnosis and Treatment for SARS-CoV-2 Variants. Infect Dis (Lond) 2023. [DOI: 10.5772/intechopen.107846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/31/2023] Open
Abstract
The COVID-19 pandemic’s epidemiological and clinical characteristics have been affected in recent months by the introduction of SARS-CoV-2 variants with unique spikes of protein alterations. These variations can lessen the protection provided by suppressing monoclonal antibodies and vaccines, as well as enhance the frequencies of transmission of the virus and/or the risk of contracting the disease. Due to these mutations, SARS-CoV-2 may be able to proliferate despite increasing levels of vaccination coverage while preserving and enhancing its reproduction efficiency. This is one of the main strategies in tackling the COVID-19 epidemics, the accessibility of precise and trustworthy biomarkers for the SARS-CoV-2 genetic material and also its nucleic acids is important to investigate the disease in suspect communities, start making diagnoses and management in symptomatic or asymptomatic persons, and evaluate authorization of the pathogen after infection. Quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) for virus nucleic acid identification is still the most effective method for such uses due to its sensitivity, quickness, high-throughput sequencing capacity, and trustworthiness. It is essential to update the primer and probe sequences to maintain the recognition of recently emerging variations. Concerning viral variations could develop that are dangerously resistant to the immunization induced by the present vaccinations in coronavirus disease 2019. Additionally, the significance of effective public health interventions and vaccination programs will grow if some variations of concern exhibit an increased risk of transmission or toxicity. The international reaction must’ve been immediate and established in science. These results supported ongoing efforts to prevent and identify infection, as well as to describe mutations in vaccine recipients, and they suggest a potential risk of illness following effective immunization and transmission of pathogens with a mutant viral.
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49
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Zehr JD, Kosakovsky Pond SL, Millet JK, Olarte-Castillo XA, Lucaci AG, Shank SD, Ceres KM, Choi A, Whittaker GR, Goodman LB, Stanhope MJ. Natural selection differences detected in key protein domains between non-pathogenic and pathogenic feline coronavirus phenotypes. Virus Evol 2023; 9:vead019. [PMID: 37038392 PMCID: PMC10082545 DOI: 10.1093/ve/vead019] [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: 01/09/2023] [Revised: 02/14/2023] [Accepted: 03/13/2023] [Indexed: 03/17/2023] Open
Abstract
Feline coronaviruses (FCoVs) commonly cause mild enteric infections in felines worldwide (termed feline enteric coronavirus [FECV]), with around 12 per cent developing into deadly feline infectious peritonitis (FIP; feline infectious peritonitis virus [FIPV]). Genomic differences between FECV and FIPV have been reported, yet the putative genotypic basis of the highly pathogenic phenotype remains unclear. Here, we used state-of-the-art molecular evolutionary genetic statistical techniques to identify and compare differences in natural selection pressure between FECV and FIPV sequences, as well as to identify FIPV- and FECV-specific signals of positive selection. We analyzed full-length FCoV protein coding genes thought to contain mutations associated with FIPV (Spike, ORF3abc, and ORF7ab). We identified two sites exhibiting differences in natural selection pressure between FECV and FIPV: one within the S1/S2 furin cleavage site (FCS) and the other within the fusion domain of Spike. We also found fifteen sites subject to positive selection associated with FIPV within Spike, eleven of which have not previously been suggested as possibly relevant to FIP development. These sites fall within Spike protein subdomains that participate in host cell receptor interaction, immune evasion, tropism shifts, host cellular entry, and viral escape. There were fourteen sites (twelve novel sites) within Spike under positive selection associated with the FECV phenotype, almost exclusively within the S1/S2 FCS and adjacent to C domain, along with a signal of relaxed selection in FIPV relative to FECV, suggesting that furin cleavage functionality may not be needed for FIPV. Positive selection inferred in ORF7b was associated with the FECV phenotype and included twenty-four positively selected sites, while ORF7b had signals of relaxed selection in FIPV. We found evidence of positive selection in ORF3c in FCoV-wide analyses, but no specific association with the FIPV or FECV phenotype. We hypothesize that some combination of mutations in FECV may contribute to FIP development, and that it is unlikely to be one singular 'switch' mutational event. This work expands our understanding of the complexities of FIP development and provides insights into how evolutionary forces may alter pathogenesis in coronavirus genomes.
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Affiliation(s)
- Jordan D Zehr
- Department of Biology, Temple University, Institute for Genomics and Evolutionary Medicine, Philadelphia, PA 19122, USA
| | - Sergei L Kosakovsky Pond
- Department of Biology, Temple University, Institute for Genomics and Evolutionary Medicine, Philadelphia, PA 19122, USA
| | - Jean K Millet
- Université Paris-Saclay, INRAE, UVSQ, Virologie et Immunologie Moléculaires, Jouy-en-Josas 78352, France
| | - Ximena A Olarte-Castillo
- Department of Microbiology & Immunology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
- James A. Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
| | - Alexander G Lucaci
- Department of Biology, Temple University, Institute for Genomics and Evolutionary Medicine, Philadelphia, PA 19122, USA
| | - Stephen D Shank
- Department of Biology, Temple University, Institute for Genomics and Evolutionary Medicine, Philadelphia, PA 19122, USA
| | - Kristina M Ceres
- Department of Public and Ecosystem Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
| | - Annette Choi
- Department of Microbiology & Immunology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
- Department of Public and Ecosystem Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
| | - Gary R Whittaker
- Department of Microbiology & Immunology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
- Department of Public and Ecosystem Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
| | - Laura B Goodman
- James A. Baker Institute for Animal Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
- Department of Public and Ecosystem Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
| | - Michael J Stanhope
- Department of Public and Ecosystem Health, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA
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50
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Oudit GY, Wang K, Viveiros A, Kellner MJ, Penninger JM. Angiotensin-converting enzyme 2-at the heart of the COVID-19 pandemic. Cell 2023; 186:906-922. [PMID: 36787743 PMCID: PMC9892333 DOI: 10.1016/j.cell.2023.01.039] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Revised: 12/06/2022] [Accepted: 01/26/2023] [Indexed: 02/05/2023]
Abstract
ACE2 is the indispensable entry receptor for SARS-CoV and SARS-CoV-2. Because of the COVID-19 pandemic, it has become one of the most therapeutically targeted human molecules in biomedicine. ACE2 serves two fundamental physiological roles: as an enzyme, it alters peptide cascade balance; as a chaperone, it controls intestinal amino acid uptake. ACE2's tissue distribution, affected by co-morbidities and sex, explains the broad tropism of coronaviruses and the clinical manifestations of SARS and COVID-19. ACE2-based therapeutics provide a universal strategy to prevent and treat SARS-CoV-2 infections, applicable to all SARS-CoV-2 variants and other emerging zoonotic coronaviruses exploiting ACE2 as their cellular receptor.
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Affiliation(s)
- Gavin Y Oudit
- Division of Cardiology, Department of Medicine, University of Alberta, Edmonton, AB, Canada; Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, AB, Canada.
| | - Kaiming Wang
- Division of Cardiology, Department of Medicine, University of Alberta, Edmonton, AB, Canada; Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, AB, Canada
| | - Anissa Viveiros
- Division of Cardiology, Department of Medicine, University of Alberta, Edmonton, AB, Canada; Mazankowski Alberta Heart Institute, University of Alberta, Edmonton, AB, Canada
| | - Max J Kellner
- Institute of Molecular Biotechnology of the Austrian Academy of Science, Vienna, Austria
| | - Josef M Penninger
- Institute of Molecular Biotechnology of the Austrian Academy of Science, Vienna, Austria; Department of Medical Genetics, Life Sciences Institute, University of British Columbia, Vancouver, BC, Canada.
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