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Jena D, Ghosh A, Jha A, Prasad P, Raghav SK. Impact of vaccination on SARS-CoV-2 evolution and immune escape variants. Vaccine 2024; 42:126153. [PMID: 39060204 DOI: 10.1016/j.vaccine.2024.07.054] [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: 12/26/2023] [Revised: 06/18/2024] [Accepted: 07/15/2024] [Indexed: 07/28/2024]
Abstract
Vaccines and host genetic factors can influence the SARS-CoV-2 evolution and emergence of new variants. Even vaccinated cases get affected as virus continues to evolve, raising concerns about vaccine efficacy and the emergence of immune escape variants. Here, we have analyzed 2295 whole-genome sequences of SARS-CoV-2 collected from vaccinated and unvaccinated cases to evaluate the impact of vaccines on virus diversity within hosts. Our comparative analysis revealed a significant higher incidence of intra-host single nucleotides variants (iSNVs) in vaccinated cases compared to unvaccinated ones (p value<0.0001). Furthermore, we have found that specific mutational processes, including APOBEC (C > T) mediated and ADAR1 (A > G) mediated mutations, were found more prevalent in vaccinated cases. Vaccinated cases exhibited higher accumulation of nonsynonymous mutation than unvaccinated cases. Fixed iSNVs were predominantly located in the ORF1ab and spike genes, several key omicron defining immune escape variants S477N, Q493R, Q498R, Y505H, L452R, and N501Y were identified in the RBD domain of spike gene in vaccinated cases. Our findings suggest that vaccine plays an important role in the evolution of the virus genome. The virus genome acquires random mutations due to error-prone replication of the virus, host modification through APOBEC and ADAR1 mediated editing mechanism, and oxidative stress. These mutations become fixed in the viral population due to the selective pressure imposed by vaccination.
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Affiliation(s)
- Deepak Jena
- DBT - Institute of Life Sciences, Bhubaneswar, India.
| | - Arup Ghosh
- DBT - Institute of Life Sciences, Bhubaneswar, India
| | - Atimukta Jha
- DBT - Institute of Life Sciences, Bhubaneswar, India
| | - Punit Prasad
- DBT - Institute of Life Sciences, Bhubaneswar, India
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2
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Xiong D, Zhang X, Xu B, Shi M, Chen M, Dong Z, Zhong J, Gong R, Wu C, Li J, Wei H, Yu J. PHDtools: A platform for pathogen detection and multi-dimensional genetic signatures decoding to realize pathogen genomics data analyses online. Gene 2024; 909:148306. [PMID: 38408616 DOI: 10.1016/j.gene.2024.148306] [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: 12/15/2023] [Revised: 02/06/2024] [Accepted: 02/20/2024] [Indexed: 02/28/2024]
Abstract
OBJECTIVES Facing the emerging diseases, rapid identification of the pathogen and multi-dimensional characterization of the genomic features at both isolate-level and population-level through high-throughput sequencing data can provide invaluable information to guide the development of antiviral agents and strategies. However, a user-friendly program is in urgent need for clinical laboratories without bioinformatics background to decode the complex big genomics data. METHODS In this study, we developed an interactive online platform named PHDtools with a total of 15 functions to analyze metagenomics data to identify the potential pathogen and decode multi-dimensional genetic signatures including intra-/inter-host variations and lineage-level variations. The platform was applied to analyze the meta-genomic data of the samples collected from the 172 imported COVID-19 cases. RESULTS According to the analytical results of mNGS, 27 patients were found to have the co-infections of SARS-CoV-2 with either influenza virus (n = 9) or human picobirnavirus (n = 19). Enough coverages of all the assembled SARS-CoV-2 genomes provided the sub-lineages of Omicron variant, and the number of mutations in the non-structural genes and M gene was increased, as well as the intra-host variations occurred in E and M gene were under positive selection (Ka/Ks > 1). These findings of increased or changed mutations in the SARS-CoV-2 genome characterized the current adaptive evolution patterns of Omicron sub-lineages, and revealed the evolution speed of these sub-lineages might increase. CONCLUSIONS Consequently, the application of PHDtools has proved that this platform is accurate, user-friendly and convenient for clinical users who are deficient in bioinformatics, and the clinical monitor of SARS-CoV-2 genomes by PHDtools also highlighted the potential evolution features of current SARS-CoV-2 and indicated that the development of anti-SARS-CoV-2 agents and new-designed vaccines should incorporate the gene variations other than S gene.
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Affiliation(s)
- Dongyan Xiong
- CAS Key Laboratory of Special Pathogens and Biosafety, Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China; University of Chinese Academy of Sciences, Beijing 100049, China; Centre for Novostics, Hong Kong Science Park, Pak Shek Kok, New Territories, Hong Kong SAR, China; Department of Chemical Pathology, Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China
| | - Xiaoxu Zhang
- CAS Key Laboratory of Special Pathogens and Biosafety, Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China
| | - Bohan Xu
- CAS Key Laboratory of Special Pathogens and Biosafety, Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Mengjuan Shi
- CAS Key Laboratory of Special Pathogens and Biosafety, Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Min Chen
- CAS Key Laboratory of Special Pathogens and Biosafety, Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhuo Dong
- Hubei International Travel Healthcare Center (Wuhan Customs Port Outpatient Department), Wuhan 430070, China
| | - Jie Zhong
- Hubei International Travel Healthcare Center (Wuhan Customs Port Outpatient Department), Wuhan 430070, China
| | - Rui Gong
- Hubei International Travel Healthcare Center (Wuhan Customs Port Outpatient Department), Wuhan 430070, China
| | - Chang Wu
- Hubei International Travel Healthcare Center (Wuhan Customs Port Outpatient Department), Wuhan 430070, China
| | - Ji Li
- Hubei International Travel Healthcare Center (Wuhan Customs Port Outpatient Department), Wuhan 430070, China
| | - Hongping Wei
- CAS Key Laboratory of Special Pathogens and Biosafety, Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Junping Yu
- CAS Key Laboratory of Special Pathogens and Biosafety, Center for Biosafety Mega-Science, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan 430071, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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3
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Wu C, A R, Ye S, Ye F, Huo W, Lu R, Tang Y, Yang J, Meng X, Tang Y, Chen S, Zhao L, Huang B, Zhang Z, Chen Y, Li D, Wang W, Shan KJ, Lu J, Tan W. Rapid identification of full-length genome and tracing variations of monkeypox virus in clinical specimens based on mNGS and amplicon sequencing. Virol Sin 2024; 39:134-143. [PMID: 38070873 PMCID: PMC10877412 DOI: 10.1016/j.virs.2023.12.002] [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: 09/23/2023] [Accepted: 12/04/2023] [Indexed: 01/05/2024] Open
Abstract
The monkeypox virus (MPXV) has triggered a current outbreak globally. Genome sequencing of MPXV and rapid tracing of genetic variants will benefit disease diagnosis and control. It is a significant challenge but necessary to optimize the strategy and application of rapid full-length genome identification and to track variations of MPXV in clinical specimens with low viral loads, as it is one of the DNA viruses with the largest genome and the most AT-biased, and has a significant number of tandem repeats. Here we evaluated the performance of metagenomic and amplicon sequencing techniques, and three sequencing platforms in MPXV genome sequencing based on multiple clinical specimens of five mpox cases in Chinese mainland. We rapidly identified the full-length genome of MPXV with the assembly of accurate tandem repeats in multiple clinical specimens. Amplicon sequencing enables cost-effective and rapid sequencing of clinical specimens to obtain high-quality MPXV genomes. Third-generation sequencing facilitates the assembly of the terminal tandem repeat regions in the monkeypox virus genome and corrects a common misassembly in published sequences. Besides, several intra-host single nucleotide variations were identified in the first imported mpox case. This study offers an evaluation of various strategies aimed at identifying the complete genome of MPXV in clinical specimens. The findings of this study will significantly enhance the surveillance of MPXV.
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Affiliation(s)
- Changcheng Wu
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Ruhan A
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Sheng Ye
- Chongqing Municipal Key Laboratory for High Pathogenic Microbes, Chongqing Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Fei Ye
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Weibang Huo
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Roujian Lu
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Yue Tang
- MGI, BGI-Shenzhen, Shenzhen, 518083, China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | | | - Xuehong Meng
- Thermo Fisher Scientific, Beijing, 100013, China
| | - Yun Tang
- Chongqing Municipal Key Laboratory for High Pathogenic Microbes, Chongqing Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Shuang Chen
- Chongqing Municipal Key Laboratory for High Pathogenic Microbes, Chongqing Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Li Zhao
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Baoying Huang
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Zhongxian Zhang
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China; School of Public Health, Baotou Medical College, Baotou, 014030, China
| | - Yuda Chen
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China; School of Public Health, Baotou Medical College, Baotou, 014030, China
| | - Dongfang Li
- BGI PathoGenesis Pharmaceutical Technology, Shenzhen, 518000, China
| | - Wenling Wang
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China
| | - Ke-Jia Shan
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing, 100871, China
| | - Jian Lu
- State Key Laboratory of Protein and Plant Gene Research, Center for Bioinformatics, School of Life Sciences, Peking University, Beijing, 100871, China.
| | - Wenjie Tan
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, 100052, China; School of Public Health, Baotou Medical College, Baotou, 014030, China.
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4
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Mattiuz G, Di Giorgio S, Conticello SG. An elusive debate on the evidence for RNA editing in SARS-CoV-2. RNA Biol 2024; 21:1-2. [PMID: 38426405 PMCID: PMC10913694 DOI: 10.1080/15476286.2024.2321032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/14/2024] [Indexed: 03/02/2024] Open
Affiliation(s)
- Giorgio Mattiuz
- Department of Experimental and Clinical Medicine, University of Florence, Firenze, Italy
| | - Salvatore Di Giorgio
- German Cancer Research Center (DKFZ) - Division of Immune Diversity, Foundation under Public Law, Heidelberg, Germany
| | - Silvestro G. Conticello
- Core Research Laboratory, ISPRO, Firenze, Italy
- Institute of Clinical Physiology, National Research Council, Pisa, Italy
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5
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Domingo E, Martínez-González B, García-Crespo C, Somovilla P, de Ávila AI, Soria ME, Durán-Pastor A, Perales C. Puzzles, challenges, and information reservoir of SARS-CoV-2 quasispecies. J Virol 2023; 97:e0151123. [PMID: 38092661 PMCID: PMC10734546 DOI: 10.1128/jvi.01511-23] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2023] Open
Abstract
Upon the emergence of SARS-CoV-2 in the human population, it was conjectured that for this coronavirus the dynamic intra-host heterogeneity typical of RNA viruses would be toned down. Nothing of this sort is observed. Here we review the main observations on the complexity and diverse composition of SARS-CoV-2 mutant spectra sampled from infected patients, within the framework of quasispecies dynamics. The analyses suggest that the information provided by myriads of genomic sequences within infected individuals may have a predictive value of the genomic sequences that acquire epidemiological relevance. Possibilities to reconcile the presence of broad mutant spectra in the large RNA coronavirus genome with its encoding a 3' to 5' exonuclease proofreading-repair activity are considered. Indeterminations in the behavior of individual viral genomes provide a benefit for the survival of the ensemble. We propose that this concept falls in the domain of "stochastic thinking," a notion that applies also to cellular processes, as a means for biological systems to face unexpected needs.
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Affiliation(s)
- Esteban Domingo
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
| | - Brenda Martínez-González
- Centro Nacional de Biotecnología (CNB-CSIC), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
- Department of Clinical Microbiology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain
| | - Carlos García-Crespo
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
| | - Pilar Somovilla
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
- Departamento de Biología Molecular, Universidad Autónoma de Madrid, Campus de Cantoblanco, Madrid, Spain
| | - Ana Isabel de Ávila
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
| | - María Eugenia Soria
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
- Department of Clinical Microbiology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain
| | - Antoni Durán-Pastor
- Centro Nacional de Biotecnología (CNB-CSIC), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
| | - Celia Perales
- Centro Nacional de Biotecnología (CNB-CSIC), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
- Department of Clinical Microbiology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain
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6
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Xi B, Zeng X, Chen Z, Zeng J, Huang L, Du H. SARS-CoV-2 within-host diversity of human hosts and its implications for viral immune evasion. mBio 2023; 14:e0067923. [PMID: 37273216 PMCID: PMC10470530 DOI: 10.1128/mbio.00679-23] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 04/17/2023] [Indexed: 06/06/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving, bringing great challenges to the control of the virus. In the present study, we investigated the characteristics of SARS-CoV-2 within-host diversity of human hosts and its implications for immune evasion using about 2,00,000 high-depth next-generation genome sequencing data of SARS-CoV-2. A total of 44% of the samples showed within-host variations (iSNVs), and the average number of iSNVs in the samples with iSNV was 1.90. C-to-U is the dominant substitution pattern for iSNVs. C-to-U/G-to-A and A-to-G/U-to-C preferentially occur in 5'-CG-3' and 5'-AU-3' motifs, respectively. In addition, we found that SARS-CoV-2 within-host variations are under negative selection. About 15.6% iSNVs had an impact on the content of the CpG dinucleotide (CpG) in SARS-CoV-2 genomes. We detected signatures of faster loss of CpG-gaining iSNVs, possibly resulting from zinc-finger antiviral protein-mediated antiviral activities targeting CpG, which could be the major reason for CpG depletion in SARS-CoV-2 consensus genomes. The non-synonymous iSNVs in the S gene can largely alter the S protein's antigenic features, and many of these iSNVs are distributed in the amino-terminal domain (NTD) and receptor-binding domain (RBD). These results suggest that SARS-CoV-2 interacts actively with human hosts and attempts to take different evolutionary strategies to escape human innate and adaptive immunity. These new findings further deepen and widen our understanding of the within-host evolutionary features of SARS-CoV-2. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of the coronavirus disease 2019, has evolved rapidly since it was discovered. Recent studies have pointed out that some mutations in the SARS-CoV-2 S protein could confer SARS-CoV-2 the ability to evade the human adaptive immune system. In addition, it is observed that the content of the CpG dinucleotide in SARS-CoV-2 genome sequences has decreased over time, reflecting the adaptation to the human host. The significance of our research is revealing the characteristics of SARS-CoV-2 within-host diversity of human hosts, identifying the causes of CpG depletion in SARS-CoV-2 consensus genomes, and exploring the potential impacts of non-synonymous within-host variations in the S gene on immune escape, which could further deepen and widen our understanding of the evolutionary features of SARS-CoV-2.
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Affiliation(s)
- Binbin Xi
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Xi Zeng
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Zixi Chen
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Jiong Zeng
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Lizhen Huang
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Hongli Du
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
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7
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Zheng P, Zhou C, Ding Y, Liu B, Lu L, Zhu F, Duan S. Nanopore sequencing technology and its applications. MedComm (Beijing) 2023; 4:e316. [PMID: 37441463 PMCID: PMC10333861 DOI: 10.1002/mco2.316] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Revised: 05/29/2023] [Accepted: 05/31/2023] [Indexed: 07/15/2023] Open
Abstract
Since the development of Sanger sequencing in 1977, sequencing technology has played a pivotal role in molecular biology research by enabling the interpretation of biological genetic codes. Today, nanopore sequencing is one of the leading third-generation sequencing technologies. With its long reads, portability, and low cost, nanopore sequencing is widely used in various scientific fields including epidemic prevention and control, disease diagnosis, and animal and plant breeding. Despite initial concerns about high error rates, continuous innovation in sequencing platforms and algorithm analysis technology has effectively addressed its accuracy. During the coronavirus disease (COVID-19) pandemic, nanopore sequencing played a critical role in detecting the severe acute respiratory syndrome coronavirus-2 virus genome and containing the pandemic. However, a lack of understanding of this technology may limit its popularization and application. Nanopore sequencing is poised to become the mainstream choice for preventing and controlling COVID-19 and future epidemics while creating value in other fields such as oncology and botany. This work introduces the contributions of nanopore sequencing during the COVID-19 pandemic to promote public understanding and its use in emerging outbreaks worldwide. We discuss its application in microbial detection, cancer genomes, and plant genomes and summarize strategies to improve its accuracy.
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Affiliation(s)
- Peijie Zheng
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
| | - Chuntao Zhou
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
| | - Yuemin Ding
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
- Institute of Translational Medicine, School of MedicineZhejiang University City CollegeHangzhouChina
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineZhejiang University City CollegeHangzhouChina
| | - Bin Liu
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
| | - Liuyi Lu
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
| | - Feng Zhu
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
| | - Shiwei Duan
- Department of Clinical MedicineSchool of MedicineZhejiang University City CollegeHangzhouChina
- Institute of Translational Medicine, School of MedicineZhejiang University City CollegeHangzhouChina
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, School of MedicineZhejiang University City CollegeHangzhouChina
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8
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Gu H, Quadeer AA, Krishnan P, Ng DYM, Chang LDJ, Liu GYZ, Cheng SMS, Lam TTY, Peiris M, McKay MR, Poon LLM. Within-host genetic diversity of SARS-CoV-2 lineages in unvaccinated and vaccinated individuals. Nat Commun 2023; 14:1793. [PMID: 37002233 PMCID: PMC10063955 DOI: 10.1038/s41467-023-37468-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 03/13/2023] [Indexed: 04/03/2023] Open
Abstract
Viral and host factors can shape SARS-CoV-2 evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here, we analysed deep sequencing data from 2,820 SARS-CoV-2 respiratory samples with different viral lineages to describe the patterns of within-host diversity under different conditions, including vaccine-breakthrough infections. In unvaccinated individuals, variant of Concern (VOC) Alpha, Delta, and Omicron respiratory samples were found to have higher within-host diversity and were under neutral to purifying selection at the full genome level compared to non-VOC SARS-CoV-2. Breakthrough infections in 2-dose or 3-dose Comirnaty and CoronaVac vaccinated individuals did not increase levels of non-synonymous mutations and did not change the direction of selection pressure. Vaccine-induced antibody or T cell responses did not appear to have significant impact on within-host SARS-CoV-2 sequence diversification. Our findings suggest that vaccination does not increase exploration of SARS-CoV-2 protein sequence space and may not facilitate emergence of viral variants.
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Affiliation(s)
- Haogao Gu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Ahmed Abdul Quadeer
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Pavithra Krishnan
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Daisy Y M Ng
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Lydia D J Chang
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Gigi Y Z Liu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Samuel M S Cheng
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Tommy T Y Lam
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong SAR, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong SAR, China
| | - Malik Peiris
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong SAR, China
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Matthew R McKay
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, VIC, 3010, Australia
- Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, 3000, Australia
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Leo L M Poon
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong SAR, China.
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
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9
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Gazeau S, Deng X, Ooi HK, Mostefai F, Hussin J, Heffernan J, Jenner AL, Craig M. The race to understand immunopathology in COVID-19: Perspectives on the impact of quantitative approaches to understand within-host interactions. IMMUNOINFORMATICS (AMSTERDAM, NETHERLANDS) 2023; 9:100021. [PMID: 36643886 PMCID: PMC9826539 DOI: 10.1016/j.immuno.2023.100021] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 11/16/2022] [Accepted: 01/03/2023] [Indexed: 01/09/2023]
Abstract
The COVID-19 pandemic has revealed the need for the increased integration of modelling and data analysis to public health, experimental, and clinical studies. Throughout the first two years of the pandemic, there has been a concerted effort to improve our understanding of the within-host immune response to the SARS-CoV-2 virus to provide better predictions of COVID-19 severity, treatment and vaccine development questions, and insights into viral evolution and the impacts of variants on immunopathology. Here we provide perspectives on what has been accomplished using quantitative methods, including predictive modelling, population genetics, machine learning, and dimensionality reduction techniques, in the first 26 months of the COVID-19 pandemic approaches, and where we go from here to improve our responses to this and future pandemics.
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Affiliation(s)
- Sonia Gazeau
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Canada
- Sainte-Justine University Hospital Research Centre, Montréal, Canada
| | - Xiaoyan Deng
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Canada
- Sainte-Justine University Hospital Research Centre, Montréal, Canada
| | - Hsu Kiang Ooi
- Digital Technologies Research Centre, National Research Council Canada, Toronto, Canada
| | - Fatima Mostefai
- Montréal Heart Institute Research Centre, Montréal, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, Canada
| | - Julie Hussin
- Montréal Heart Institute Research Centre, Montréal, Canada
- Department of Medicine, Faculty of Medicine, Université de Montréal, Montréal, Canada
| | - Jane Heffernan
- Modelling Infection and Immunity Lab, Mathematics Statistics, York University, Toronto, Canada
- Centre for Disease Modelling (CDM), Mathematics Statistics, York University, Toronto, Canada
| | - Adrianne L Jenner
- School of Mathematical Sciences, Queensland University of Technology, Brisbane Australia
| | - Morgan Craig
- Department of Mathematics and Statistics, Université de Montréal, Montréal, Canada
- Sainte-Justine University Hospital Research Centre, Montréal, Canada
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10
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Snead AA, Alda F. Time-Series Sequences for Evolutionary Inferences. Integr Comp Biol 2022; 62:1771-1783. [PMID: 36104153 DOI: 10.1093/icb/icac146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 07/28/2022] [Accepted: 07/29/2022] [Indexed: 01/05/2023] Open
Affiliation(s)
- Anthony A Snead
- Department of Biological Sciences, University of Alabama, 300 Hackberry Lane, Tuscaloosa, AL 35487, USA
| | - Fernando Alda
- Department of Biology, Geology and Environmental Science, University of Tennessee at Chattanooga, 615 McCallie Ave, Chattanooga, TN 37403, USA
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11
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Xiong D, Zhang X, Yu J, Wei H. Distribution of intra-host variations and mutations in the genomes of SARS-CoV-2 and their implications on detection and therapeutics. MedComm (Beijing) 2022; 3:e186. [PMID: 36474856 PMCID: PMC9717708 DOI: 10.1002/mco2.186] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/25/2022] [Accepted: 10/27/2022] [Indexed: 12/03/2022] Open
Abstract
The ongoing circulation of SARS-CoV-2 variants of concern (VOCs) has caused global concerns, because VOCs could escape current vaccines, antiviral drugs, and diagnosis. Analyzing mutations and intra-host diversities in different and widespread VOCs can provide important insights to virus adaptive evolution and validity of vaccines, antiviral drugs, and diagnosis. In this study, by analyzing 1744 high-throughput sequencing data for intra-host single-nucleotide variations (iSNVs) and 3,668,205 genome sequences for mutations in different VOCs, it was found that Omicron variant is still evolving at high speed, especially having high iSNVs frequency in its S and N genes. The efficacies of antibodies or detection primers targeting these two genes are at high risks to be invalid. Instead, highly conserved regions such as NSP8 gene could be better therapeutic and detection targets. Furthermore, mutations in later VOCs could be traced to the minor alleles in the previous variant samples such as Alpha and Delta in different countries. Finally, it was found that mutations C14408T in RdRp and A18163G in NSP14 gene might be associated with the higher genetic diversity in Omicron. Our findings not only contribute to understanding the adaptive evolution of SARS-CoV-2 VOCs, but also provide useful information for both drugs and diagnostic kits development.
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Affiliation(s)
- Dongyan Xiong
- CAS Key Laboratory of Special Pathogens and BiosafetyCenter for Biosafety Mega‐ScienceWuhan Institute of VirologyChinese Academy of SciencesWuhanChina
- CAS Key Laboratory of Special Pathogens and BiosafetyUniversity of Chinese Academy of SciencesBeijingChina
| | - Xiaoxu Zhang
- CAS Key Laboratory of Special Pathogens and BiosafetyCenter for Biosafety Mega‐ScienceWuhan Institute of VirologyChinese Academy of SciencesWuhanChina
| | - Junping Yu
- CAS Key Laboratory of Special Pathogens and BiosafetyCenter for Biosafety Mega‐ScienceWuhan Institute of VirologyChinese Academy of SciencesWuhanChina
- CAS Key Laboratory of Special Pathogens and BiosafetyUniversity of Chinese Academy of SciencesBeijingChina
| | - Hongping Wei
- CAS Key Laboratory of Special Pathogens and BiosafetyCenter for Biosafety Mega‐ScienceWuhan Institute of VirologyChinese Academy of SciencesWuhanChina
- CAS Key Laboratory of Special Pathogens and BiosafetyUniversity of Chinese Academy of SciencesBeijingChina
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12
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Mushegian AA, Long SW, Olsen RJ, Christensen PA, Subedi S, Chung M, Davis J, Musser J, Ghedin E. Within-host genetic diversity of SARS-CoV-2 in the context of large-scale hospital-associated genomic surveillance. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.08.17.22278898. [PMID: 36032964 PMCID: PMC9413716 DOI: 10.1101/2022.08.17.22278898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The COVID-19 pandemic has resulted in extensive surveillance of the genomic diversity of SARS-CoV-2. Sequencing data generated as part of these efforts can also capture the diversity of the SARS-CoV-2 virus populations replicating within infected individuals. To assess this within-host diversity of SARS-CoV-2 we quantified low frequency (minor) variants from deep sequence data of thousands of clinical samples collected by a large urban hospital system over the course of a year. Using a robust analytical pipeline to control for technical artefacts, we observe that at comparable viral loads, specimens from patients hospitalized due to COVID-19 had a greater number of minor variants than samples from outpatients. Since individuals with highly diverse viral populations could be disproportionate drivers of new viral lineages in the patient population, these results suggest that transmission control should pay special attention to patients with severe or protracted disease to prevent the spread of novel variants.
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Affiliation(s)
- Alexandra A. Mushegian
- Systems Genomics Section, Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - Scott W. Long
- Laboratory of Molecular and Translational Human Infectious Diseases Research, Center for Infectious Diseases, Department of Pathology and Genomic Medicine, Houston Methodist Research Institute and Houston Methodist Hospital Houston, Texas, 77030
| | - Randall J. Olsen
- Laboratory of Molecular and Translational Human Infectious Diseases Research, Center for Infectious Diseases, Department of Pathology and Genomic Medicine, Houston Methodist Research Institute and Houston Methodist Hospital Houston, Texas, 77030
| | - Paul A. Christensen
- Laboratory of Molecular and Translational Human Infectious Diseases Research, Center for Infectious Diseases, Department of Pathology and Genomic Medicine, Houston Methodist Research Institute and Houston Methodist Hospital Houston, Texas, 77030
| | - Sishir Subedi
- Laboratory of Molecular and Translational Human Infectious Diseases Research, Center for Infectious Diseases, Department of Pathology and Genomic Medicine, Houston Methodist Research Institute and Houston Methodist Hospital Houston, Texas, 77030
| | - Matthew Chung
- Systems Genomics Section, Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
| | - James Davis
- Division of Data Science and Learning, Argonne National Laboratory, 9700 S. Cass Ave., Lemont, Illinois, 60439
- University of Chicago Consortium for Advanced Science and Engineering, 5801 South Ellis Avenue, Chicago, Illinois, 60637
| | - James Musser
- Laboratory of Molecular and Translational Human Infectious Diseases Research, Center for Infectious Diseases, Department of Pathology and Genomic Medicine, Houston Methodist Research Institute and Houston Methodist Hospital Houston, Texas, 77030
| | - Elodie Ghedin
- Systems Genomics Section, Laboratory of Parasitic Diseases, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD USA
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13
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Patel RS, Agrawal B. Heterologous immunity induced by 1 st generation COVID-19 vaccines and its role in developing a pan-coronavirus vaccine. Front Immunol 2022; 13:952229. [PMID: 36045689 PMCID: PMC9420909 DOI: 10.3389/fimmu.2022.952229] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 07/19/2022] [Indexed: 12/23/2022] Open
Abstract
Severe acute respiratory syndrome virus-2 (SARS-CoV-2), the causative infectious agent of the COVID-19 pandemic, has led to multiple (4-6) waves of infections worldwide during the past two years. The development of vaccines against SARS-CoV-2 has led to successful mass immunizations worldwide, mitigating the worldwide mortality due the pandemic to a great extent. Yet the evolution of new variants highlights a need to develop a universal vaccine which can prevent infections from all virulent SARS-CoV-2. Most of the current first generation COVID-19 vaccines are based on the Spike protein from the original Wuhan-hu-1 virus strain. It is encouraging that they still protect from serious illnesses, hospitalizations and mortality against a number of mutated viral strains, to varying degrees. Understanding the mechanisms by which these vaccines provide heterologous protection against multiple highly mutated variants can reveal strategies to develop a universal vaccine. In addition, many unexposed individuals have been found to harbor T cells that are cross-reactive against SARS-CoV-2 antigens, with a possible protective role. In this review, we will discuss various aspects of natural or vaccine-induced heterologous (cross-reactive) adaptive immunity against SARS-CoV-2 and other coronaviruses, and their role in achieving the concept of a pan-coronavirus vaccine.
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Affiliation(s)
| | - Babita Agrawal
- Department of Surgery, Faculty of Medicine and Dentistry, College of Health Sciences, University of Alberta, Edmonton, AB, Canada
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14
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Gu H, Quadeer AA, Krishnan P, Ng DY, Chang LD, Liu GY, Cheng SS, Lam TT, Peiris M, McKay MR, Poon LL. Within-host diversity of SARS-CoV-2 lineages and effect of vaccination. RESEARCH SQUARE 2022:rs.3.rs-1927944. [PMID: 35982671 PMCID: PMC9387541 DOI: 10.21203/rs.3.rs-1927944/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Viral and host factors can shape SARS-CoV-2 within-host viral diversity and virus evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here we analysed deep sequencing data from 2,146 SARS-CoV-2 samples with different viral lineages to describe the patterns of within-host diversity in different conditions, including vaccine-breakthrough infections. Variant of Concern (VOC) Alpha, Delta, and Omicron samples were found to have higher within-host nucleotide diversity while being under weaker purifying selection at full genome level compared to non-VOC SARS-CoV-2 viruses. Breakthrough Delta and Omicron infections in Comirnaty and CoronaVac vaccinated individuals appeared to have higher within-host purifying selection at the full-genome and/or Spike gene levels. Vaccine-induced antibody or T cell responses did not appear to have significant impact on within-host SARS-CoV-2 evolution. Our findings suggest that vaccination does not increase SARS-CoV-2 protein sequence space and may not facilitate emergence of more viral variants.
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Affiliation(s)
- Haogao Gu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Ahmed Abdul Quadeer
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Pavithra Krishnan
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Daisy Y.M. Ng
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Lydia D.J Chang
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Gigi Y.Z. Liu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Samuel S.M. Cheng
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Tommy T.Y. Lam
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
| | - Malik Peiris
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong, China
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Matthew R. McKay
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, VIC 3010, Australia
- Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC 3000, Australia
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Leo L.M. Poon
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong, China
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
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15
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Wang Q, Wu X, Mao Q, Gao F, Liu M, Song Z, Bian L, Liang Z. How SARS-CoV-2 dodges immune surveillance and facilitates infection: an analytical review. Expert Rev Anti Infect Ther 2022; 20:1119-1127. [PMID: 35574688 DOI: 10.1080/14787210.2022.2078307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Effective treatments for the ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic are limited. The virus has evolved strategies to evade the immune system or hijack immune responses to facilitate infection and escape immune surveillance. Mechanistically, SARS-CoV-2 takes advantage of TLR4 and cytokine-induced integrins to promote its entrance into the cell. Furthermore, the activation of pattern recognition receptors (PRR)-mediated signaling pathways is compromised by SARS-CoV-2 non-structural proteins (NSPs), accessory protein open reading frames (ORFs), and structural proteins upon infection, contributing to viral infection and replication. Host factors necessary for cellular protein synthesis, metabolism, and viral replication can also be inhibited by the SARS-CoV-2 proteins. Exploring specific mechanisms would optimize the therapy methods and benefit drug research and development. AREAS COVERED : We describe pathways and mechanisms by which SARS-CoV-2 evades immune system; these include the mechanisms that operate during virus entry, signaling pathways involved, and processes at RNA and protein levels. EXPERT OPINION : Increased understanding of how viruses interfere with immune responses would provide more evidence for drug development. Drugs targeting conserved viral proteins to inhibit their replication or host factors to enhance immune responses would minimize the impact of virus mutations and prepare for future coronavirus outbreaks.
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Affiliation(s)
- Qian Wang
- National Institutes for Food and Drug Control, Beijing, People's Republic of China.,NHC Key Laboratory of Research on Quality and Standardization of Biotech Products, Beijing, People's Republic of China.,NMPA Key Laboratory for Quality Research and Evaluation of Biological Products, Beijing, People's Republic of China
| | - Xing Wu
- National Institutes for Food and Drug Control, Beijing, People's Republic of China.,NHC Key Laboratory of Research on Quality and Standardization of Biotech Products, Beijing, People's Republic of China.,NMPA Key Laboratory for Quality Research and Evaluation of Biological Products, Beijing, People's Republic of China
| | - Qunying Mao
- National Institutes for Food and Drug Control, Beijing, People's Republic of China.,NHC Key Laboratory of Research on Quality and Standardization of Biotech Products, Beijing, People's Republic of China.,NMPA Key Laboratory for Quality Research and Evaluation of Biological Products, Beijing, People's Republic of China
| | - Fan Gao
- National Institutes for Food and Drug Control, Beijing, People's Republic of China.,NHC Key Laboratory of Research on Quality and Standardization of Biotech Products, Beijing, People's Republic of China.,NMPA Key Laboratory for Quality Research and Evaluation of Biological Products, Beijing, People's Republic of China
| | - Mingchen Liu
- National Institutes for Food and Drug Control, Beijing, People's Republic of China.,NHC Key Laboratory of Research on Quality and Standardization of Biotech Products, Beijing, People's Republic of China.,NMPA Key Laboratory for Quality Research and Evaluation of Biological Products, Beijing, People's Republic of China
| | - Ziyang Song
- National Institutes for Food and Drug Control, Beijing, People's Republic of China.,NHC Key Laboratory of Research on Quality and Standardization of Biotech Products, Beijing, People's Republic of China.,NMPA Key Laboratory for Quality Research and Evaluation of Biological Products, Beijing, People's Republic of China
| | - Lianlian Bian
- National Institutes for Food and Drug Control, Beijing, People's Republic of China.,NHC Key Laboratory of Research on Quality and Standardization of Biotech Products, Beijing, People's Republic of China.,NMPA Key Laboratory for Quality Research and Evaluation of Biological Products, Beijing, People's Republic of China
| | - Zhenglun Liang
- National Institutes for Food and Drug Control, Beijing, People's Republic of China.,NHC Key Laboratory of Research on Quality and Standardization of Biotech Products, Beijing, People's Republic of China.,NMPA Key Laboratory for Quality Research and Evaluation of Biological Products, Beijing, People's Republic of China
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16
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Liu Y, Kearney J, Mahmoud M, Kille B, Sedlazeck FJ, Treangen TJ. Rescuing low frequency variants within intra-host viral populations directly from Oxford Nanopore sequencing data. Nat Commun 2022; 13:1321. [PMID: 35288552 PMCID: PMC8921239 DOI: 10.1038/s41467-022-28852-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 02/10/2022] [Indexed: 12/28/2022] Open
Abstract
Infectious disease monitoring on Oxford Nanopore Technologies (ONT) platforms offers rapid turnaround times and low cost. Tracking low frequency intra-host variants provides important insights with respect to elucidating within-host viral population dynamics and transmission. However, given the higher error rate of ONT, accurate identification of intra-host variants with low allele frequencies remains an open challenge with no viable computational solutions available. In response to this need, we present Variabel, a novel approach and first method designed for rescuing low frequency intra-host variants from ONT data alone. We evaluate Variabel on both synthetic data (SARS-CoV-2) and patient derived datasets (Ebola virus, norovirus, SARS-CoV-2); our results show that Variabel can accurately identify low frequency variants below 0.5 allele frequency, outperforming existing state-of-the-art ONT variant callers for this task. Variabel is open-source and available for download at: www.gitlab.com/treangenlab/variabel. Tracking low frequency intra-host variants has helped understanding within-host viral population dynamics and transmission. Precise tracking, however, depends partially on the error rate of the sequencing platforms used. Here, Liu et al. present Variabel, a method to rescue low frequency intra-host variants from Oxford Nanopore Technologies (ONT) platforms and validate their approach on Ebola virus, norovirus, and SARS-CoV-2 datasets.
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