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Cui L, Li T, Lan M, Zhou M, Xue W, Zhang S, Wang H, Hong M, Zhang Y, Yuan L, Sun H, Ye J, Zheng Q, Guan Y, Gu Y, Xia N, Li S. A cryptic site in class 5 epitope of SARS-CoV-2 RBD maintains highly conservation across natural isolates. iScience 2024; 27:110208. [PMID: 39015149 PMCID: PMC11251093 DOI: 10.1016/j.isci.2024.110208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 03/12/2024] [Accepted: 05/28/2024] [Indexed: 07/18/2024] Open
Abstract
The emergence of SARS-CoV-2 variants raises concerns about the efficacy of existing COVID-19 vaccines and therapeutics. Previously, we identified a conserved cryptic class 5 epitope of SARS-CoV-2 receptor binding domain (RBD) by two cross-neutralizing antibodies 7D6 and 6D6. Intriguingly, this site remains resistant to substantial mutations occurred in ever-changing SARS-CoV-2 subvariants. As compared to class 3 antibody S309, 6D6 maintains broad and consistent neutralizing activities against SARS-CoV-2 variants. Furthermore, 6D6 effectively protected hamster from the virulent Beta strain. Sequence alignment of approximately 6 million documented SARS-CoV-2 isolates revealed that 6D6 epitope maintains an exceptionally high conservation rate (99.92%). Structural analysis demonstrated that all 33 mutations accumulated in XBB.1.5 since the original strain do not perturb the binding 6D6 to RBD, in line with the sequence analysis throughout the antigenicity evolution of SARS-CoV-2. These findings suggest the potential of this epitope serving as a critical determinant for vaccines and therapeutic design.
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Affiliation(s)
- Lingyan Cui
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Tingting Li
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Miaolin Lan
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Ming Zhou
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Wenhui Xue
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Sibo Zhang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Hong Wang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Minqing Hong
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Yali Zhang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Lunzhi Yuan
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Hui Sun
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Jianghui Ye
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Qingbing Zheng
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Yi Guan
- State Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Hong Kong 999077, China
- Joint Institute of Virology (Shantou University and University of Hong Kong), Guangdong-Hongkong Joint Laboratory of Emerging Infectious Diseases, Shantou University, Shantou 515063, China
| | - Ying Gu
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Ningshao Xia
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
| | - Shaowei Li
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Public Health, School of Life Sciences, Xiamen University, Xiamen 361102, China
- National Institute of Diagnostics and Vaccine Development in Infectious Diseases, State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, Collaborative Innovation Center of Biologic Products, National Innovation Platform for Industry-Education Integration in Vaccine Research, the Research Unit of Frontier Technology of Structural Vaccinology of Chinese Academy of Medical Sciences, Xiamen University, Xiamen 361102, China
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2
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Ling-Hu T, Simons LM, Dean TJ, Rios-Guzman E, Caputo MT, Alisoltani A, Qi C, Malczynski M, Blanke T, Jennings LJ, Ison MG, Achenbach CJ, Larkin PM, Kaul KL, Lorenzo-Redondo R, Ozer EA, Hultquist JF. Integration of individualized and population-level molecular epidemiology data to model COVID-19 outcomes. Cell Rep Med 2024; 5:101361. [PMID: 38232695 PMCID: PMC10829796 DOI: 10.1016/j.xcrm.2023.101361] [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: 12/02/2022] [Revised: 08/07/2023] [Accepted: 12/11/2023] [Indexed: 01/19/2024]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with enhanced transmissibility and immune escape have emerged periodically throughout the coronavirus disease 2019 (COVID-19) pandemic, but the impact of these variants on disease severity has remained unclear. In this single-center, retrospective cohort study, we examined the association between SARS-CoV-2 clade and patient outcome over a two-year period in Chicago, Illinois. Between March 2020 and March 2022, 14,252 residual diagnostic specimens were collected from SARS-CoV-2-positive inpatients and outpatients alongside linked clinical and demographic metadata, of which 2,114 were processed for viral whole-genome sequencing. When controlling for patient demographics and vaccination status, several viral clades were associated with risk for hospitalization, but this association was negated by the inclusion of population-level confounders, including case count, sampling bias, and shifting standards of care. These data highlight the importance of integrating non-virological factors into disease severity and outcome models for the accurate assessment of patient risk.
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Affiliation(s)
- Ted Ling-Hu
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Lacy M Simons
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Taylor J Dean
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Estefany Rios-Guzman
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Matthew T Caputo
- Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Arghavan Alisoltani
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Chao Qi
- Clinical Microbiology Laboratory, Department of Pathology, Northwestern Memorial Hospital, Chicago, IL 60611, USA
| | - Michael Malczynski
- Clinical Microbiology Laboratory, Department of Pathology, Northwestern Memorial Hospital, Chicago, IL 60611, USA
| | - Timothy Blanke
- Diagnostic Molecular Biology Laboratory, Northwestern Memorial Hospital, Chicago, IL 60611, USA
| | - Lawrence J Jennings
- Clinical Microbiology Laboratory, Department of Pathology, Northwestern Memorial Hospital, Chicago, IL 60611, USA
| | - Michael G Ison
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Chad J Achenbach
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Paige M Larkin
- Department of Molecular Microbiology, Northshore University HealthSystem, Evanston, IL 60201, USA
| | - Karen L Kaul
- Department of Pathology, Northshore University HealthSystem, Evanston, IL 60201, USA
| | - Ramon Lorenzo-Redondo
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Egon A Ozer
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Judd F Hultquist
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA.
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3
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Qin J, Tian X, Liu S, Yang Z, Shi D, Xu S, Zhang Y. Rapid classification of SARS-CoV-2 variant strains using machine learning-based label-free SERS strategy. Talanta 2024; 267:125080. [PMID: 37678002 DOI: 10.1016/j.talanta.2023.125080] [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: 03/03/2023] [Revised: 08/05/2023] [Accepted: 08/13/2023] [Indexed: 09/09/2023]
Abstract
The spread of COVID-19 over the past three years is largely due to the continuous mutation of the virus, which has significantly impeded global efforts to prevent and control this epidemic. Specifically, mutations in the amino acid sequence of the surface spike (S) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have directly impacted its biological functions, leading to enhanced transmission and triggering an immune escape effect. Therefore, prompt identification of these mutations is crucial for formulating targeted treatment plans and implementing precise prevention and control measures. In this study, the label-free surface-enhanced Raman scattering (SERS) technology combined with machine learning (ML) algorithms provide a potential solution for accurate identification of SARS-CoV-2 variants. We establish a SERS spectral database of SARS-CoV-2 variants and demonstrate that a diagnostic classifier using a logistic regression (LR) algorithm can provide accurate results within 10 min. Our classifier achieves 100% accuracy for Beta (B.1.351/501Y.V2), Delta (B.1.617), Wuhan (COVID-19) and Omicron (BA.1) variants. In addition, our method achieves 100% accuracy in blind tests of positive and negative human nasal swabs based on the LR model. This method enables detection and classification of variants in complex biological samples. Therefore, ML-based SERS technology is expected to accurately discriminate various SARS-CoV-2 variants and may be used for rapid diagnosis and therapeutic decision-making.
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Affiliation(s)
- Jingwang Qin
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, PR China; Department of Translational Medicine, Xiamen Institute of Rare Earth Materials, Haixi Institute, Chinese Academy of Sciences, Xiamen, 361021, PR China
| | - Xiangdong Tian
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, PR China; Department of Translational Medicine, Xiamen Institute of Rare Earth Materials, Haixi Institute, Chinese Academy of Sciences, Xiamen, 361021, PR China
| | - Siying Liu
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, PR China; Department of Translational Medicine, Xiamen Institute of Rare Earth Materials, Haixi Institute, Chinese Academy of Sciences, Xiamen, 361021, PR China; University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhengxia Yang
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, PR China; Department of Translational Medicine, Xiamen Institute of Rare Earth Materials, Haixi Institute, Chinese Academy of Sciences, Xiamen, 361021, PR China; University of the Chinese Academy of Sciences, Beijing, 100049, China
| | - Dawei Shi
- National Institutes for Food and Drug Control, Beijing, 100050, China.
| | - Sihong Xu
- National Institutes for Food and Drug Control, Beijing, 100050, China.
| | - Yun Zhang
- State Key Laboratory of Structural Chemistry, Fujian Institute of Research on the Structure of Matter, Chinese Academy of Sciences, Fuzhou, Fujian, 350002, PR China; Department of Translational Medicine, Xiamen Institute of Rare Earth Materials, Haixi Institute, Chinese Academy of Sciences, Xiamen, 361021, PR China; University of the Chinese Academy of Sciences, Beijing, 100049, China.
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4
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Sinnathamby MA, Zaidi A, Twohig KA, Aliabadi S, Aziz NA, Groves N, Gallagher E, Thelwall S, Dabrera G. Descriptive epidemiology of SARS-CoV-2 Beta (B.1.351) variant cases in England, December 2020 to June 2022. Influenza Other Respir Viruses 2023; 17:e13204. [PMID: 38019701 PMCID: PMC10651643 DOI: 10.1111/irv.13204] [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: 05/19/2023] [Revised: 09/06/2023] [Accepted: 09/10/2023] [Indexed: 12/01/2023] Open
Abstract
The emergence of the SARS-CoV-2 Beta (B.1.351) variant in November 2020 raised concerns of increased transmissibility and severity. We describe the epidemiology of 949 confirmed SARS-CoV-2 Beta variant cases in England, identified between December 2020 and June 2022. Most cases were detected in the first 3 months. A total of 10 deaths (1.1%; 10/949) were identified among all cases and of those with travel information, 38 (4.9%; 38/781) cases with hospital admissions within 14 days of a positive test being detected. 52.9% (413/781) cases were imported. This study reinforces the importance of monitoring of travel-associated cases to inform public health response and reduce transmissibility of new variants.
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Affiliation(s)
- Mary A. Sinnathamby
- COVID‐19 Vaccines and Epidemiology Division, Public Health Programmes DirectorateUK Health Security AgencyLondonUK
| | - Asad Zaidi
- COVID‐19 Vaccines and Epidemiology Division, Public Health Programmes DirectorateUK Health Security AgencyLondonUK
| | - Katherine A. Twohig
- COVID‐19 Vaccines and Epidemiology Division, Public Health Programmes DirectorateUK Health Security AgencyLondonUK
| | - Shirin Aliabadi
- COVID‐19 Vaccines and Epidemiology Division, Public Health Programmes DirectorateUK Health Security AgencyLondonUK
| | - Nurin Abdul Aziz
- COVID‐19 Vaccines and Epidemiology Division, Public Health Programmes DirectorateUK Health Security AgencyLondonUK
| | - Natalie Groves
- Genomics Public Health Analysis, TARZET Division, Clinical and Emerging Infections DirectorateUK Health Security AgencyLondonUK
| | - Eileen Gallagher
- Genomics Public Health Analysis, TARZET Division, Clinical and Emerging Infections DirectorateUK Health Security AgencyLondonUK
| | - Simon Thelwall
- COVID‐19 Vaccines and Epidemiology Division, Public Health Programmes DirectorateUK Health Security AgencyLondonUK
| | - Gavin Dabrera
- COVID‐19 Vaccines and Epidemiology Division, Public Health Programmes DirectorateUK Health Security AgencyLondonUK
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5
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Ghoula M, Deyawe Kongmeneck A, Eid R, Camproux AC, Moroy G. Comparative Study of the Mutations Observed in the SARS-CoV-2 RBD Variants of Concern and Their Impact on the Interaction with the ACE2 Protein. J Phys Chem B 2023; 127:8586-8602. [PMID: 37775095 PMCID: PMC10578311 DOI: 10.1021/acs.jpcb.3c01467] [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: 03/02/2023] [Revised: 04/20/2023] [Indexed: 10/01/2023]
Abstract
SARS-CoV-2 strains have made an appearance across the globe, causing over 757 million cases and over 6.85 million deaths at the time of writing. The emergence of these variants shows the amplitude of genetic variation to which the wild-type strains have been subjected. The rise of the different SARS-CoV-2 variants resulting from such genetic modification has significantly affected COVD-19's major impact on proliferation, virulence, and clinics. With the emergence of the variants of concern, the spike protein has been identified as a possible therapeutic target due to its critical role in binding to human cells and pathogenesis. These mutations could be linked to functional heterogeneity and use a different infection strategy. For example, the Omicron variant's multiple mutations should be carefully examined, as they represent one of the most widely spread strains and hint to us that there may be more genetic changes in the virus. As a result, we applied a common protocol where we reconstructed SARS-CoV-2 variants of concern and performed molecular dynamics simulations to study the stability of the ACE2-RBD complex in each variant. We also carried out free energy calculations to compare the binding and biophysical properties of the different SARS-CoV-2 variants when they interact with ACE2. Therefore, we were able to obtain consistent results and uncover new crucial residues that were essential for preserving a balance between maintaining a high affinity for ACE2 and the capacity to evade RBD-targeted antibodies. Our detailed structural analysis showed that SARS-CoV-2 variants of concern show a higher affinity for ACE2 compared to the Wuhan strain. Additionally, residues K417N and E484K/A might play a crucial role in antibody evasion, whereas Q498R and N501Y are specifically mutated to strengthen RBD affinity to ACE2 and, thereby, increase the viral effect of the COVID-19 virus.
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Affiliation(s)
- Mariem Ghoula
- Université de Paris, CNRS,
INSERM, Unité de Biologie Fonctionnelle et Adaptative, F-75013 Paris, France
| | - Audrey Deyawe Kongmeneck
- Université de Paris, CNRS,
INSERM, Unité de Biologie Fonctionnelle et Adaptative, F-75013 Paris, France
| | - Rita Eid
- Université de Paris, CNRS,
INSERM, Unité de Biologie Fonctionnelle et Adaptative, F-75013 Paris, France
| | - Anne-Claude Camproux
- Université de Paris, CNRS,
INSERM, Unité de Biologie Fonctionnelle et Adaptative, F-75013 Paris, France
| | - Gautier Moroy
- Université de Paris, CNRS,
INSERM, Unité de Biologie Fonctionnelle et Adaptative, F-75013 Paris, France
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6
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Naik R, Avula S, Palleti SK, Gummadi J, Ramachandran R, Chandramohan D, Dhillon G, Gill AS, Paiwal K, Shaik B, Balachandran M, Patel B, Gurugubelli S, Mariswamy Arun Kumar AK, Nanjundappa A, Bellamkonda M, Rathi K, Sakhamuri PL, Nassar M, Bali A. From Emergence to Endemicity: A Comprehensive Review of COVID-19. Cureus 2023; 15:e48046. [PMID: 37916248 PMCID: PMC10617653 DOI: 10.7759/cureus.48046] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/31/2023] [Indexed: 11/03/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), later renamed coronavirus disease 2019 (COVID-19), was first identified in Wuhan, China, in early December 2019. Initially, the China office of the World Health Organization was informed of numerous cases of pneumonia of unidentified etiology in Wuhan, Hubei Province at the end of 2019. This would subsequently result in a global pandemic with millions of confirmed cases of COVID-19 and millions of deaths reported to the WHO. We have analyzed most of the data published since the beginning of the pandemic to compile this comprehensive review of SARS-CoV-2. We looked at the core ideas, such as the etiology, epidemiology, pathogenesis, clinical symptoms, diagnostics, histopathologic findings, consequences, therapies, and vaccines. We have also included the long-term effects and myths associated with some therapeutics of COVID-19. This study presents a comprehensive assessment of the SARS-CoV-2 virology, vaccines, medicines, and significant variants identified during the course of the pandemic. Our review article is intended to provide medical practitioners with a better understanding of the fundamental sciences, clinical treatment, and prevention of COVID-19. As of May 2023, this paper contains the most recent data made accessible.
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Affiliation(s)
- Roopa Naik
- Medicine, Geisinger Commonwealth School of Medicine, Scranton, USA
- Internal Medicine/Hospital Medicine, Geisinger Health System, Wilkes Barre, USA
| | - Sreekant Avula
- Diabetes, Endocrinology, and Metabolism, University of Minnesota, Minneapolis, USA
| | - Sujith K Palleti
- Nephrology, Louisiana State University Health Sciences Center, Shreveport, USA
| | - Jyotsna Gummadi
- Internal Medicine, MedStar Franklin Square Medical Center, Baltimore, USA
| | | | | | - Gagandeep Dhillon
- Physician Executive MBA, University of Tennessee, Knoxville, USA
- Internal Medicine, University of Maryland Baltimore Washington Medical Center, Glen Burnie, USA
| | | | - Kapil Paiwal
- Oral & Maxillofacial Pathology, Daswani Dental College & Research Center, Kota, IND
| | - Bushra Shaik
- Internal Medicine, Onslow Memorial Hospital, Jacksonville, USA
| | | | - Bhumika Patel
- Oral Medicine and Radiology, Howard University, Washington, D.C., USA
| | | | | | | | - Mahita Bellamkonda
- Hospital Medicine, University of Oklahoma Health Sciences Center, Oklahoma City, USA
| | - Kanika Rathi
- Internal Medicine, University of Florida, Gainesville, USA
| | | | - Mahmoud Nassar
- Endocrinology, Diabetes, and Metabolism, Jacobs School of Medicine and Biomedical Sciences, Buffalo, USA
| | - Atul Bali
- Internal Medicine/Nephrology, Geisinger Medical Center, Danville, USA
- Internal Medicine/Nephrology, Geisinger Health System, Wilkes-Barre, USA
- Medicine, Geisinger Commonwealth School of Medicine, Scranton, USA
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7
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Rabarison JH, Rakotondramanga JM, Ratovoson R, Masquelier B, Rasoanomenjanahary AM, Dreyfus A, Garchitorena A, Rasambainarivo F, Razanajatovo NH, Andriamandimby SF, Metcalf CJ, Lacoste V, Heraud JM, Dussart P. Excess mortality associated with the COVID-19 pandemic during the 2020 and 2021 waves in Antananarivo, Madagascar. BMJ Glob Health 2023; 8:e011801. [PMID: 37495370 PMCID: PMC10373673 DOI: 10.1136/bmjgh-2023-011801] [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: 01/18/2023] [Accepted: 06/17/2023] [Indexed: 07/28/2023] Open
Abstract
INTRODUCTION COVID-19-associated mortality remains difficult to estimate in sub-Saharan Africa because of the lack of comprehensive systems of death registration. Based on death registers referring to the capital city of Madagascar, we sought to estimate the excess mortality during the COVID-19 pandemic and calculate the loss of life expectancy. METHODS Death records between 2016 and 2021 were used to estimate weekly excess mortality during the pandemic period. To infer its synchrony with circulation of SARS-CoV-2, a cross-wavelet analysis was performed. Life expectancy loss due to the COVID-19 pandemic was calculated by projecting mortality rates using the Lee and Carter model and extrapolating the prepandemic trends (1990-2019). Differences in life expectancy at birth were disaggregated by cause of death. RESULTS Peaks of excess mortality in 2020-21 were associated with waves of COVID-19. Estimates of all-cause excess mortality were 38.5 and 64.9 per 100 000 inhabitants in 2020 and 2021, respectively, with excess mortality reaching ≥50% over 6 weeks. In 2021, we quantified a drop of 0.8 and 1.0 years in the life expectancy for men and women, respectively attributable to increased risks of death beyond the age of 60 years. CONCLUSION We observed high excess mortality during the pandemic period, in particular around the peaks of SARS-CoV-2 circulation in Antananarivo. Our study highlights the need to implement death registration systems in low-income countries to document true toll of a pandemic.
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Affiliation(s)
| | | | - Rila Ratovoson
- Institut Pasteur de Madagascar, Antananarivo, Madagascar
| | - Bruno Masquelier
- Universite Catholique de Louvain Centre de recherche en demographie et societes, Louvain la neuve, Belgium
| | | | - Anou Dreyfus
- Institut Pasteur de Madagascar, Antananarivo, Madagascar
| | - Andres Garchitorena
- Institut Pasteur de Madagascar, Antananarivo, Madagascar
- UMR 224 MIVEGEC, IRD, Montpellier, France
| | - Fidisoa Rasambainarivo
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, USA
- Mahaliana Labs SARL, Antananarivo, Madagascar
| | | | | | - C Jessica Metcalf
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey, USA
| | | | - Jean-Michel Heraud
- Institut Pasteur de Madagascar, Antananarivo, Madagascar
- Institut Pasteur de Dakar, Dakar, Senegal
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8
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Lyu S, Qian C, McIntyre A, Lee CH. One Pandemic, Two Solutions: Comparing the U.S.-China Response and Health Priorities to COVID-19 from the Perspective of "Two Types of Control". Healthcare (Basel) 2023; 11:1848. [PMID: 37444682 DOI: 10.3390/healthcare11131848] [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: 05/11/2023] [Revised: 06/20/2023] [Accepted: 06/21/2023] [Indexed: 07/15/2023] Open
Abstract
After three years of global rampage, the COVID-19 epidemic, the most serious infectious disease to occur worldwide since the 1918 influenza pandemic, is nearing its end. From the global experience, medical control and social control are the two main dimensions in the prevention and control of COVID-19. From the perspective of "two types of control", namely medical control and social control, this paper finds that the political system, economic structure, and cultural values of the United States greatly limit the government's ability to impose social control, forcing it to adopt medical control to fight the virus in a single dimension. In contrast, China's political system, economic structure, and cultural values allow its government to adopt stringent, extensive, and frequent social control, as well as medical control to fight the virus. This approach departs from the traditional pathway of fighting the epidemic, i.e., "infection-treatment-immunization", thereby outpacing the evolution of the virus and controlling its spread more rapidly. This finding helps explain why the Chinese government adopted a strict "zeroing" and "dynamic zeroing" policy during the first three years, at the cost of enormous economic, social, and even political legitimacy. It was not until late 2022, when the Omicron variant with the waning virulence became prevalent, that China chose to "coexist" with the virus, thus avoiding a massive epidemic-related death. While the United States adopted a pulsed-style strategy at the beginning of the epidemic, i.e., "relaxation-suppression-relaxation-suppression", and began to "coexist" with the virus in just one year, resulting in a large number of excess deaths associated with the epidemic. The study contributes to explaining the difference in the interplay between public health priorities and COVID-19 response strategies in China and the United States, based on the specific public health context and the perspective of "medical control" and "social control".
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Affiliation(s)
- Shupeng Lyu
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an 710049, China
| | - Chen Qian
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an 710049, China
| | - Aaron McIntyre
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an 710049, China
| | - Ching-Hung Lee
- School of Public Policy and Administration, Xi'an Jiaotong University, Xi'an 710049, China
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9
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Nasrallah GK, Ali F, Younes S, Al Khatib HA, Al-Thani AA, Yassine HM. Enhancing the sensitivity of rapid antigen detection test (RADT) of different SARS-CoV-2 variants and lineages using fluorescence-labeled antibodies and a fluorescent meter. Heliyon 2023; 9:e17179. [PMID: 37325455 PMCID: PMC10257515 DOI: 10.1016/j.heliyon.2023.e17179] [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: 12/12/2022] [Revised: 05/21/2023] [Accepted: 06/08/2023] [Indexed: 06/17/2023] Open
Abstract
RT-qPCR is considered the gold standard for diagnosis of COVID-19; however, it is laborious, time-consuming, and expensive. RADTs have evolved recently as relatively inexpensive methods to address these shortcomings, but their performance for detecting different SARS-COV-2 variants remains limited. RADT test performance could be enhanced using different antibody labeling and signal detection techniques. Here, we aimed to evaluate the performance of two antigen RADTs for detecting different SARS-CoV-2 variants: (i) the conventional colorimetric RADT (Ab-conjugated with gold beads); and (ii) the new Finecare™ RADT (Ab-coated fluorescent beads). Finecare™ is a meter used for the detection of a fluorescent signal. 187 frozen nasopharyngeal swabs collected in Universal transport (UTM) that are RT-qPCR positive for different SARS-CoV-2 variants were selected, including Alpha (n = 60), Delta (n = 59), and Omicron variants (n = 108). Sixty flu and 60 RSV-positive samples were included as negative controls (total sample number = 347). The conventional RADT showed sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 62.4% (95%CI: 54-70), 100% (95%CI: 97-100), 100% (95%CI: 100-100), and 58% (95%CI: 49-67), respectively. These measurements were enhanced using the Finecare™ RADT: sensitivity, specificity, PPV, and NPV were 92.6% (95%CI: 89.08-92.3), 96% (95%CI: 96-99.61), 98% (95%CI: 89-92.3), and 85% (95%CI: 96-99.6) respectively. The sensitivity of both RADTs could be greatly underestimated because nasopharyngeal swab samples collected UTM and stored at -80 °C were used. Despite that, our results indicate that the Finecare™ RADT is appropriate for clinical laboratory and community-based surveillance due to its high sensitivity and specificity.
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Affiliation(s)
- Gheyath K Nasrallah
- Biomedical Research Center, Qatar University, Doha, 2713, Qatar
- Biomedical Sciences Department, College of Health Sciences, Qatar University, Doha, 2713, Qatar
| | - Fatma Ali
- Biomedical Research Center, Qatar University, Doha, 2713, Qatar
- Biomedical Sciences Department, College of Health Sciences, Qatar University, Doha, 2713, Qatar
| | - Salma Younes
- Biomedical Research Center, Qatar University, Doha, 2713, Qatar
- Biomedical Sciences Department, College of Health Sciences, Qatar University, Doha, 2713, Qatar
| | | | | | - Hadi M Yassine
- Biomedical Research Center, Qatar University, Doha, 2713, Qatar
- Biomedical Sciences Department, College of Health Sciences, Qatar University, Doha, 2713, Qatar
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10
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Salzberger B, Mellmann A, Bludau A, Ciesek S, Corman V, Dilthey A, Donker T, Eckmanns T, Egelkamp R, Gatermann SG, Grundmann H, Häcker G, Kaase M, Lange B, Mielke M, Pletz MW, Semmler T, Thürmer A, Wieler LH, Wolff T, Widmer AF, Scheithauer S. An appeal for strengthening genomic pathogen surveillance to improve pandemic preparedness and infection prevention: the German perspective. Infection 2023:10.1007/s15010-023-02040-9. [PMID: 37129842 PMCID: PMC10152431 DOI: 10.1007/s15010-023-02040-9] [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: 01/20/2023] [Accepted: 04/13/2023] [Indexed: 05/03/2023]
Abstract
The SARS-CoV-2 pandemic has highlighted the importance of viable infection surveillance and the relevant infrastructure. From a German perspective, an integral part of this infrastructure, genomic pathogen sequencing, was at best fragmentary and stretched to its limits due to the lack or inefficient use of equipment, human resources, data management and coordination. The experience in other countries has shown that the rate of sequenced positive samples and linkage of genomic and epidemiological data (person, place, time) represent important factors for a successful application of genomic pathogen surveillance. Planning, establishing and consistently supporting adequate structures for genomic pathogen surveillance will be crucial to identify and combat future pandemics as well as other challenges in infectious diseases such as multi-drug resistant bacteria and healthcare-associated infections. Therefore, the authors propose a multifaceted and coordinated process for the definition of procedural, legal and technical standards for comprehensive genomic pathogen surveillance in Germany, covering the areas of genomic sequencing, data collection and data linkage, as well as target pathogens. A comparative analysis of the structures established in Germany and in other countries is applied. This proposal aims to better tackle epi- and pandemics to come and take action from the "lessons learned" from the SARS-CoV-2 pandemic.
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Affiliation(s)
- Bernd Salzberger
- Department for Infection Control and Infectious Diseases, University Hospital Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Germany.
| | - Alexander Mellmann
- Institute for Hygiene, University Hospital Münster, Robert-Koch-Straße 41, 48149, Münster, Germany.
| | - Anna Bludau
- Department for Infection Control and Infectious Diseases, University Medical Center (UMG), Georg-August University Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Sandra Ciesek
- Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Frankfurt Am Main, Germany
| | - Victor Corman
- Institute of Virology, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Alexander Dilthey
- Institute of Medical Microbiology and Hospital Hygiene, University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Tjibbe Donker
- Institute for Infection Prevention and Hospital Epidemiology, University Medical Center Freiburg, Freiburg, Germany
| | | | - Richard Egelkamp
- Next Generation Sequencing, Public Health Agency of Lower Saxony, Hanover, Germany
| | - Sören G Gatermann
- Department of Medical Microbiology, Ruhr University Bochum, Bochum, Germany
| | - Hajo Grundmann
- Institute for Infection Prevention and Hospital Epidemiology, University Medical Center Freiburg, Freiburg, Germany
| | - Georg Häcker
- Faculty of Medicine, Institute of Medical Microbiology and Hygiene, Medical Centre University of Freiburg, Freiburg, Germany
| | - Martin Kaase
- Department for Infection Control and Infectious Diseases, University Medical Center (UMG), Georg-August University Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany
| | - Berit Lange
- Department of Epidemiology, Helmholtz Centre for Infection Research, Brunswick, Germany
| | | | - Mathias W Pletz
- Institute of Infectious Diseases and Infection Control, University Hospital, Jena, Germany
| | | | | | | | | | - Andreas F Widmer
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, Basel, Switzerland
| | - Simone Scheithauer
- Department for Infection Control and Infectious Diseases, University Medical Center (UMG), Georg-August University Göttingen, Robert-Koch-Straße 40, 37075, Göttingen, Germany.
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11
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Polatoğlu I, Oncu‐Oner T, Dalman I, Ozdogan S. COVID-19 in early 2023: Structure, replication mechanism, variants of SARS-CoV-2, diagnostic tests, and vaccine & drug development studies. MedComm (Beijing) 2023; 4:e228. [PMID: 37041762 PMCID: PMC10082934 DOI: 10.1002/mco2.228] [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: 09/07/2022] [Revised: 01/21/2023] [Accepted: 01/30/2023] [Indexed: 04/13/2023] Open
Abstract
Coronavirus Disease-19 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome-coronaviruses-2 (SARS-CoV-2), a highly pathogenic and transmissible coronavirus. Most cases of COVID-19 have mild to moderate symptoms, including cough, fever, myalgias, and headache. On the other hand, this coronavirus can lead to severe complications and death in some cases. Therefore, vaccination is the most effective tool to prevent and eradicate COVID-19 disease. Also, rapid and effective diagnostic tests are critical in identifying cases of COVID-19. The COVID-19 pandemic has a dynamic structure on the agenda and contains up-to-date developments. This article has comprehensively discussed the most up-to-date pandemic situation since it first appeared. For the first time, not only the structure, replication mechanism, and variants of SARS-CoV-2 (Alpha, Beta, Gamma, Omicron, Delta, Epsilon, Kappa, Mu, Eta, Zeta, Theta, lota, Lambda) but also all the details of the pandemic, such as how it came out, how it spread, current cases, what precautions should be taken, prevention strategies, the vaccines produced, the tests developed, and the drugs used are reviewed in every aspect. Herein, the comparison of diagnostic tests for SARS-CoV-2 in terms of procedure, accuracy, cost, and time has been presented. The mechanism, safety, efficacy, and effectiveness of COVID-19 vaccines against SARS-CoV-2 variants have been evaluated. Drug studies, therapeutic targets, various immunomodulators, and antiviral molecules applied to patients with COVID-19 have been reviewed.
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Affiliation(s)
- Ilker Polatoğlu
- Department of BioengineeringManisa Celal Bayar UniversityYunusemreManisaTurkey
| | - Tulay Oncu‐Oner
- Department of BioengineeringManisa Celal Bayar UniversityYunusemreManisaTurkey
| | - Irem Dalman
- Department of BioengineeringEge UniversityBornovaIzmirTurkey
| | - Senanur Ozdogan
- Department of BioengineeringManisa Celal Bayar UniversityYunusemreManisaTurkey
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12
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Shan J, Wu T, Wei W, Huang J, Li Y, Zou B, Ma Y, Cui L, Wu H, Zhou G. Visualized RNA detection of SARS-CoV-2 in a closed tube by coupling RT-PCR with nested invasive reaction. Analyst 2023; 148:995-1004. [PMID: 36723063 DOI: 10.1039/d2an01679f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
A simple, cost-effective and reliable diagnosis of pathogen nucleic acids assay is much required for controlling a pandemic of a virus disease, such as COVID-19. Our previously developed visualized detection of pathogen DNA in a single closed tube is very suitable for POCT. However, virus RNA could not be detected directly and should be reverse-transcribed into cDNA in advance. To enable this visualized assay to detect virus RNA directly, various types of reverse transcriptase were investigated, and finally we found that HiScript II reverse transcriptase could keep active and be well adapted to the one-pot visualized assay in optimized conditions. Reverse transcription, template amplification and amplicon identification by PCR coupled with invasive reaction, as well as visualization by self-assembling of AuNP probes could be automatically and sequentially performed in a closed tube under different temperature conditions, achieving "sample (RNA)-in-result (red color)-out" only by a simple PCR engine plus the naked eye. The visualized RT-PCR is sensitive to unambiguous detection of 5 copies of the N and ORFlab genes of SARS-CoV-2 RNA comparing favourably with qPCR methods (commercialized kit), is specific to genotype 3 variants (Alpha, Beta and Omicron) of SARS-CoV-2, and is very accurate for picking up 0.01% Omicron variant from a large amount of sequence-similar backgrounds. The method is employed in detecting 50 clinical samples, and 10 of them were detected as SARS-CoV-2 positive samples, identical to those by conventional RT-PCR, indicating that the method is cost-effective and labor-saving for pathogen RNA screening in resource-limited regions.
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Affiliation(s)
- Jingwen Shan
- Department of Clinical Pharmacy, Jinling Hospital, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, China.
| | - Tao Wu
- NHC Key laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.
| | - Wei Wei
- Department of Clinical Pharmacy, Jinling Hospital, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, China.
| | - Jinling Huang
- Department of Clinical Pharmacy, Jinling Hospital, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, China.
| | - Yijun Li
- Department of Clinical Pharmacy, Jinling Hospital, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, China.
| | - Bingjie Zou
- Department of Clinical Pharmacy, Jinling Hospital, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, China. .,School of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, China
| | - Yi Ma
- State Key Laboratory of Analytical Chemistry for Life Science & Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, 210023, China
| | - Lunbiao Cui
- NHC Key laboratory of Enteric Pathogenic Microbiology, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, 210009, China.
| | - Haiping Wu
- Department of Clinical Pharmacy, Jinling Hospital, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, China. .,School of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, China
| | - Guohua Zhou
- Department of Clinical Pharmacy, Jinling Hospital, School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, 510515, China. .,School of Life Science and Technology, China Pharmaceutical University, Nanjing, 210009, China.,State Key Laboratory of Analytical Chemistry for Life Science & Jiangsu Key Laboratory of Molecular Medicine, Medical School of Nanjing University, Nanjing, 210023, China.,School of Pharmacy, Nanjing Medical University, Nanjing, 211166, China
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13
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Scheithauer S, Dilthey A, Bludau A, Ciesek S, Corman V, Donker T, Eckmanns T, Egelkamp R, Grundmann H, Häcker G, Kaase M, Lange B, Mellmann A, Mielke M, Pletz M, Salzberger B, Thürmer A, Widmer A, Wieler LH, Wolff T, Gatermann S, Semmler T. [Establishment of genomic pathogen surveillance to strengthen pandemic preparedness and infection prevention in Germany]. Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz 2023; 66:443-449. [PMID: 36811648 PMCID: PMC9945818 DOI: 10.1007/s00103-023-03680-w] [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] [Indexed: 02/24/2023]
Abstract
The SARS-CoV‑2 pandemic has shown a deficit of essential epidemiological infrastructure, especially with regard to genomic pathogen surveillance in Germany. In order to prepare for future pandemics, the authors consider it urgently necessary to remedy this existing deficit by establishing an efficient infrastructure for genomic pathogen surveillance. Such a network can build on structures, processes, and interactions that have already been initiated regionally and further optimize them. It will be able to respond to current and future challenges with a high degree of adaptability.The aim of this paper is to address the urgency and to outline proposed measures for establishing an efficient, adaptable, and responsive genomic pathogen surveillance network, taking into account external framework conditions and internal standards. The proposed measures are based on global and country-specific best practices and strategy papers. Specific next steps to achieve an integrated genomic pathogen surveillance include linking epidemiological data with pathogen genomic data; sharing and coordinating existing resources; making surveillance data available to relevant decision-makers, the public health service, and the scientific community; and engaging all stakeholders. The establishment of a genomic pathogen surveillance network is essential for the continuous, stable, active surveillance of the infection situation in Germany, both during pandemic phases and beyond.
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Affiliation(s)
- Simone Scheithauer
- Institut für Krankenhaushygiene und Infektiologie, Universitätsmedizin Göttingen (UMG), Georg-August Universität Göttingen, Robert-Koch-Str. 40, 37075, Göttingen, Deutschland.
| | - Alexander Dilthey
- Medizinische Mikrobiologie und Krankenhaushygiene, Universitätsklinikum Düsseldorf, Düsseldorf, Deutschland
| | - Anna Bludau
- Institut für Krankenhaushygiene und Infektiologie, Universitätsmedizin Göttingen (UMG), Georg-August Universität Göttingen, Robert-Koch-Str. 40, 37075, Göttingen, Deutschland
| | - Sandra Ciesek
- Institut für Medizinische Virologie, Universitätsklinikum Frankfurt, Frankfurt am Main, Deutschland
| | - Victor Corman
- Institut für Virologie, Charité Universitätsmedizin Berlin, Berlin, Deutschland
| | - Tjibbe Donker
- Institut für Infektionsprävention und Krankenhaushygiene, Universitätsklinikum Freiburg, Freiburg, Deutschland
| | | | - Richard Egelkamp
- Next Generation Sequencing, Niedersächsisches Landesgesundheitsamt, Hannover, Deutschland
| | - Hajo Grundmann
- Institut für Infektionsprävention und Krankenhaushygiene, Universitätsklinikum Freiburg, Freiburg, Deutschland
| | - Georg Häcker
- Institut für Medizinische Mikrobiologie und Hygiene, Universitätsklinikum Freiburg, Freiburg, Deutschland
| | - Martin Kaase
- Institut für Krankenhaushygiene und Infektiologie, Universitätsmedizin Göttingen (UMG), Georg-August Universität Göttingen, Robert-Koch-Str. 40, 37075, Göttingen, Deutschland
| | - Berit Lange
- Abteilung Epidemiologie, Helmholtz-Zentrum für Infektionsforschung, Braunschweig, Deutschland
| | - Alexander Mellmann
- Institut für Hygiene, Universitätsklinikum Münster, Münster, Deutschland
| | | | - Mathias Pletz
- Institut für Infektionsmedizin und Krankenhaushygiene, Universitätsklinikum Jena, Jena, Deutschland
| | - Bernd Salzberger
- Infektiologie, Abteilung für Krankenhaushygiene und Infektiologie, Universitätsklinikum Regensburg, Regensburg, Deutschland
| | | | - Andreas Widmer
- Abteilung für Infektiologie und Spitalhygiene, Universitätsspital Basel, Basel, Schweiz
| | | | | | - Sören Gatermann
- Institut für Hygiene und Mikrobiologie, Ruhr-Universität Bochum, Bochum, Deutschland
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14
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Abstract
The COVID-19 pandemic has been accompanied by SARS-CoV-2 evolution and emergence of viral variants that have far exceeded initial expectations. Five major variants of concern (Alpha, Beta, Gamma, Delta, and Omicron) have emerged, each having both unique and overlapping amino acid substitutions that have affected transmissibility, disease severity, and susceptibility to natural or vaccine-induced immune responses and monoclonal antibodies. Several of the more recent variants appear to have evolved properties of immune evasion, particularly in cases of prolonged infection. Tracking of existing variants and surveillance for new variants are critical for an effective pandemic response.
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Affiliation(s)
- Jana L Jacobs
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA; , ,
| | - Ghady Haidar
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA; , ,
| | - John W Mellors
- Division of Infectious Diseases, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA; , ,
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15
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Gao W, Li Z, Guan Q, Cui W, Zheng B, Ding Q, Lv G, Xu J, Zhang W. Characterization and analysis of linear epitopes corresponding to SARS-CoV-2 outbreak in Jilin Province, China. J Med Virol 2023; 95:e28323. [PMID: 36401153 DOI: 10.1002/jmv.28323] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 11/15/2022] [Accepted: 11/16/2022] [Indexed: 11/21/2022]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants have caused hundreds of thousands of deaths and shown serious social influence worldwide. Jilin Province, China, experienced the first wave of the outbreak from December 2020 to February 2021. Here, we analyzed the genomic characteristics of the SARS-CoV-2 outbreak in Jilin province using a phylogeographic tree and found that clinical isolates belonged to the B.1 lineage, which was considered to be the ancestral lineage. Several dominant SARS-CoV-2 specific linear B cell epitopes that reacted with the convalescent sera were also analysed and identified using a peptide microarray composed of S, M, and E proteins. Moreover, the serum of convalescent patients infected with SARS-CoV-2 showed neutralizing activity against four widely spreading SARS-CoV-2 variants; however, significant differences were observed in neutralizing activities against different SARS-CoV-2 variants. These data provide important information on genomic characteristics, linear epitopes, and neutralizing activity of SARS-CoV-2 outbreak in Jilin Province, China, which may aid in understanding disease patterns and regional aspects of the pandemic.
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Affiliation(s)
- Wenying Gao
- Department of Infectious Diseases, Center of Infectious Diseases and Pathogen Biology, Key Laboratory of Organ Regeneration and Transplantation of The Ministry of Education, First Hospital of Jilin University, Changchun, Jilin, China.,Institute of Virology and AIDS Research, First Hospital of Jilin University, Changchun, Jilin, China
| | - Zhaolong Li
- Institute of Virology and AIDS Research, First Hospital of Jilin University, Changchun, Jilin, China
| | - Qingtian Guan
- Department of Infectious Diseases, Center of Infectious Diseases and Pathogen Biology, Key Laboratory of Organ Regeneration and Transplantation of The Ministry of Education, First Hospital of Jilin University, Changchun, Jilin, China
| | - Wenzhe Cui
- Jilin Provincial Key Laboratory on Molecular and Chemical Genetics, Second Hospital of Jilin University, Changchun, China
| | - Baishong Zheng
- Institute of Virology and AIDS Research, First Hospital of Jilin University, Changchun, Jilin, China
| | - Qiang Ding
- School of Medicine, Tsinghua University, Beijing, China
| | - Guoyue Lv
- Department of Hepatobiliary and Pancreatic Surgery, First Hospital of Jilin University, Changchun, Jilin, China
| | - Jiancheng Xu
- Department of Laboratory Medicine, First Hospital of Jilin University, Changchun, Jilin, China
| | - Wenyan Zhang
- Department of Infectious Diseases, Center of Infectious Diseases and Pathogen Biology, Key Laboratory of Organ Regeneration and Transplantation of The Ministry of Education, First Hospital of Jilin University, Changchun, Jilin, China.,Institute of Virology and AIDS Research, First Hospital of Jilin University, Changchun, Jilin, China
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16
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Butt AA, Dargham SR, Coyle P, Yassine HM, Al-Khal A, Abou-Samra AB, Abu-Raddad LJ. COVID-19 Disease Severity in Persons Infected With Omicron BA.1 and BA.2 Sublineages and Association With Vaccination Status. JAMA Intern Med 2022; 182:1097-1099. [PMID: 35994264 PMCID: PMC9396464 DOI: 10.1001/jamainternmed.2022.3351] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
This retrospective study compares the severity of SARS-CoV-2 infection among persons infected with BA.1 and BA.2 sublineages by vaccination status.
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Affiliation(s)
- Adeel A Butt
- Hamad Medical Corporation, Doha, Qatar.,Department of Medicine, Weill Cornell Medicine, New York, New York.,Department of Population Health Sciences, Weill Cornell Medicine, New York, New York
| | - Soha R Dargham
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York.,Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Doha, Qatar.,World Health Organization Collaborating Center for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Doha, Qatar
| | | | - Hadi M Yassine
- Hamad Medical Corporation, Doha, Qatar.,Biomedical Research Center, Qatar University, Doha, Qatar
| | | | | | - Laith J Abu-Raddad
- Department of Population Health Sciences, Weill Cornell Medicine, New York, New York.,Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Doha, Qatar.,World Health Organization Collaborating Center for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine-Qatar, Doha, Qatar
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17
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Qassim SH, Hasan MR, Tang P, Chemaitelly H, Ayoub HH, Yassine HM, Al-Khatib HA, Smatti MK, Abdul-Rahim HF, Nasrallah GK, Al-Kuwari MG, Al-Khal A, Coyle P, Gillani I, Kaleeckal AH, Shaik RM, Latif AN, Al-Kuwari E, Jeremijenko A, Butt AA, Bertollini R, Al-Romaihi HE, Al-Thani MH, Abu-Raddad LJ. Effects of SARS-CoV-2 Alpha, Beta, and Delta variants, age, vaccination, and prior infection on infectiousness of SARS-CoV-2 infections. Front Immunol 2022; 13:984784. [PMID: 36177014 PMCID: PMC9513583 DOI: 10.3389/fimmu.2022.984784] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 08/22/2022] [Indexed: 11/17/2022] Open
Abstract
In 2021, Qatar experienced considerable incidence of SARS-CoV-2 infection that was dominated sequentially by the Alpha, Beta, and Delta variants. Using the cycle threshold (Ct) value of an RT-qPCR-positive test to proxy the inverse of infectiousness, we investigated infectiousness of SARS-CoV-2 infections by variant, age, sex, vaccination status, prior infection status, and reason for testing in a random sample of 18,355 RT-qPCR-genotyped infections. Regression analyses were conducted to estimate associations with the Ct value of RT-qPCR-positive tests. Compared to Beta infections, Alpha and Delta infections demonstrated 2.56 higher Ct cycles (95% CI: 2.35-2.78), and 4.92 fewer cycles (95% CI: 4.67- 5.16), respectively. The Ct value declined gradually with age and was especially high for children <10 years of age, signifying lower infectiousness in small children. Children <10 years of age had 2.18 higher Ct cycles (95% CI: 1.88-2.48) than those 10-19 years of age. Compared to unvaccinated individuals, the Ct value was higher among individuals who had received one or two vaccine doses, but the Ct value decreased gradually with time since the second-dose vaccination. Ct value was 2.07 cycles higher (95% CI: 1.42-2.72) for those with a prior infection than those without prior infection. The Ct value was lowest among individuals tested because of symptoms and was highest among individuals tested as a travel requirement. Delta was substantially more infectious than Beta. Prior immunity, whether due to vaccination or prior infection, is associated with lower infectiousness of breakthrough infections, but infectiousness increases gradually with time since the second-dose vaccination.
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Affiliation(s)
- Suelen H. Qassim
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States
| | | | - Patrick Tang
- Department of Pathology, Sidra Medicine, Doha, Qatar
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States
| | - Houssein H. Ayoub
- Mathematics Program, Department of Mathematics, Statistics, and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Hadi M. Yassine
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Hebah A. Al-Khatib
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Maria K. Smatti
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Hanan F. Abdul-Rahim
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | - Gheyath K. Nasrallah
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Department of Biomedical Science, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
| | | | | | - Peter Coyle
- Biomedical Research Center, QU Health, Qatar University, Doha, Qatar
- Hamad Medical Corporation, Doha, Qatar
- Wellcome-Wolfson Institute for Experimental Medicine, Queens University, Belfast, United Kingdom
| | | | | | | | | | | | | | - Adeel A. Butt
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States
- Hamad Medical Corporation, Doha, Qatar
- Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, United States
| | | | | | | | - Laith J. Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, New York, NY, United States
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
- *Correspondence: Laith J. Abu-Raddad,
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18
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Association between Mutations in Papain-like Protease (PLpro) of SARS-CoV-2 with COVID-19 Clinical Outcomes. Pathogens 2022; 11:pathogens11091008. [PMID: 36145442 PMCID: PMC9501953 DOI: 10.3390/pathogens11091008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/26/2022] [Accepted: 08/30/2022] [Indexed: 12/01/2022] Open
Abstract
Papain-like protease (PLpro) is important for the replication and transcription of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aimed to reveal the PLpro mutations associated with the clinical outcomes of patients. Due to the importance of the S protein in the pathogenicity of SARS-CoV-2, the mutation of the S protein was also analyzed in this study. After downloading the data from the Global Initiative on Sharing Avian Influenza Data (GISAID) database, samples were divided into two groups on the basis of patient status, namely, recovered and dead groups. This study performed a univariate analysis and further explored the association of mutations with patient outcomes through multivariate logistic regression analysis. A total of 138,492 samples were used for analysis. The patients had a mean age of 43.66 ± 21.56 years, and 51.3% of them were female. Multivariate logistic regression results showed that, compared with men, women had a lower risk of dying from coronavirus disease 2019 (COVID-19) (OR = 0.687, 95%CI: 0.638–0.740). Compared with patients aged 17 years and younger, patients aged 18–64 years (OR = 2.864, 95%CI: 1.982–4.139) and patients over 65 years old (OR = 19.135, 95%CI: 13.280–27.572) had a higher risk of death after infection. Compared with the wild type, P78L (OR = 5.185, 95%CI: 2.763–9.730) and K233Q (OR = 5.154, 95%CI: 1.442–18.416) in PLpro were associated with an increased risk of death. A synergistic interaction existed between age and mutations A146D and P78L. The results of the multivariate logistic regression analysis of the data on vaccinated patients demonstrated that, compared with the wild type, the P78L (OR = 3.376, 95%CI: 2.040–5.585) mutation was associated with an increased risk of death. In conclusion, compared with the wild-type PLpro protein, the P78L and K233Q mutations may increase the risk of death in infected individuals. In addition, a synergistic effect existed between age and P78L and K233Q that increased the risk of death in older patients.
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19
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Candido KL, Eich CR, de Fariña LO, Kadowaki MK, da Conceição Silva JL, Maller A, Simão RDCG. Spike protein of SARS-CoV-2 variants: a brief review and practical implications. Braz J Microbiol 2022; 53:1133-1157. [PMID: 35397075 PMCID: PMC8994061 DOI: 10.1007/s42770-022-00743-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2022] [Accepted: 03/21/2022] [Indexed: 12/24/2022] Open
Abstract
The scientific community has been alarmed by the possible immunological evasion, higher infectivity, and severity of disease caused by the newest variants of SARS-CoV-2. The spike protein has an important role in the cellular invasion of viruses and is the target of several vaccines and therapeutic resources, such as monoclonal antibodies. In addition, some of the most relevant mutations in the different variants are on the spike (S) protein gene sequence that leads to structural alterations in the predicted protein, thus causing concern about the protection mediated by vaccines against these new strains. The present review highlights the most recent knowledge about COVID-19 and vaccines, emphasizing the different spike protein structures of SARS-CoV-2 and updating the reader about the emerging viral variants and their classifications, the more common viral mutations described and their distribution in Brazil. It also compiles a table with the most recent knowledge about all of the Omicron spike mutations.
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Affiliation(s)
- Kattlyn Laryssa Candido
- Present Address: Laboratório de Bioquímica Molecular (LaBioqMol), Centro de Ciências Médicas e Farmacêuticas, Unioeste, Cascavel, PR Brazil
| | - Caio Ricardo Eich
- Present Address: Laboratório de Bioquímica Molecular (LaBioqMol), Centro de Ciências Médicas e Farmacêuticas, Unioeste, Cascavel, PR Brazil
| | - Luciana Oliveira de Fariña
- Present Address: Laboratório de Bioquímica Molecular (LaBioqMol), Centro de Ciências Médicas e Farmacêuticas, Unioeste, Cascavel, PR Brazil
| | - Marina Kimiko Kadowaki
- Present Address: Laboratório de Bioquímica Molecular (LaBioqMol), Centro de Ciências Médicas e Farmacêuticas, Unioeste, Cascavel, PR Brazil
| | - José Luis da Conceição Silva
- Present Address: Laboratório de Bioquímica Molecular (LaBioqMol), Centro de Ciências Médicas e Farmacêuticas, Unioeste, Cascavel, PR Brazil
| | - Alexandre Maller
- Present Address: Laboratório de Bioquímica Molecular (LaBioqMol), Centro de Ciências Médicas e Farmacêuticas, Unioeste, Cascavel, PR Brazil
| | - Rita de Cássia Garcia Simão
- Present Address: Laboratório de Bioquímica Molecular (LaBioqMol), Centro de Ciências Médicas e Farmacêuticas, Unioeste, Cascavel, PR Brazil
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20
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RBD-VLP Vaccines Adjuvanted with Alum or SWE Protect K18-hACE2 Mice against SARS-CoV-2 VOC Challenge. mSphere 2022; 7:e0024322. [PMID: 35968964 PMCID: PMC9429941 DOI: 10.1128/msphere.00243-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The ongoing COVID-19 pandemic has contributed largely to the global vaccine disparity. Development of protein subunit vaccines can help alleviate shortages of COVID-19 vaccines delivered to low-income countries. Here, we evaluated the efficacy of a three-dose virus-like particle (VLP) vaccine composed of hepatitis B surface antigen (HBsAg) decorated with the receptor binding domain (RBD) from the Wuhan or Beta SARS-CoV-2 strain adjuvanted with either aluminum hydroxide (alum) or squalene in water emulsion (SWE). RBD HBsAg vaccines were compared to the standard two doses of Pfizer mRNA vaccine. Alum-adjuvanted vaccines were composed of either HBsAg conjugated with Beta RBD alone (β RBD HBsAg+Al) or a combination of both Beta RBD HBsAg and Wuhan RBD HBsAg (β/Wu RBD HBsAg+Al). RBD vaccines adjuvanted with SWE were formulated with Beta RBD HBsAg (β RBD HBsAg+SWE) or without HBsAg (β RBD+SWE). Both alum-adjuvanted RBD HBsAg vaccines generated functional RBD IgG against multiple SARS-CoV-2 variants of concern (VOC), decreased viral RNA burden, and lowered inflammation in the lung against Alpha or Beta challenge in K18-hACE2 mice. However, only β/Wu RBD HBsAg+Al was able to afford 100% survival to mice challenged with Alpha or Beta VOC. Furthermore, mice immunized with β RBD HBsAg+SWE induced cross-reactive neutralizing antibodies against major VOC of SARS-CoV-2, lowered viral RNA burden in the lung and brain, and protected mice from Alpha or Beta challenge similarly to mice immunized with Pfizer mRNA. However, RBD+SWE immunization failed to protect mice from VOC challenge. Our findings demonstrate that RBD HBsAg VLP vaccines provided similar protection profiles to the approved Pfizer mRNA vaccines used worldwide and may offer protection against SARS-CoV-2 VOC. IMPORTANCE Global COVID-19 vaccine distribution to low-income countries has been a major challenge of the pandemic. To address supply chain issues, RBD virus-like particle (VLP) vaccines that are cost-effective and capable of large-scale production were developed and evaluated for efficacy in preclinical mouse studies. We demonstrated that RBD-VLP vaccines protected K18-hACE2 mice against Alpha or Beta challenge similarly to Pfizer mRNA vaccination. Our findings showed that the VLP platform can be utilized to formulate immunogenic and efficacious COVID-19 vaccines.
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21
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Yang W, Shaman JL. COVID-19 pandemic dynamics in South Africa and epidemiological characteristics of three variants of concern (Beta, Delta, and Omicron). eLife 2022; 11:e78933. [PMID: 35943138 PMCID: PMC9363123 DOI: 10.7554/elife.78933] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2022] [Accepted: 07/21/2022] [Indexed: 12/13/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) have been key drivers of new coronavirus disease 2019 (COVID-19) pandemic waves. To better understand variant epidemiologic characteristics, here we apply a model-inference system to reconstruct SARS-CoV-2 transmission dynamics in South Africa, a country that has experienced three VOC pandemic waves (i.e. Beta, Delta, and Omicron BA.1) by February 2022. We estimate key epidemiologic quantities in each of the nine South African provinces during March 2020 to February 2022, while accounting for changing detection rates, infection seasonality, nonpharmaceutical interventions, and vaccination. Model validation shows that estimated underlying infection rates and key parameters (e.g. infection-detection rate and infection-fatality risk) are in line with independent epidemiological data and investigations. In addition, retrospective predictions capture pandemic trajectories beyond the model training period. These detailed, validated model-inference estimates thus enable quantification of both the immune erosion potential and transmissibility of three major SARS-CoV-2 VOCs, that is, Beta, Delta, and Omicron BA.1. These findings help elucidate changing COVID-19 dynamics and inform future public health planning.
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Affiliation(s)
- Wan Yang
- Department of Epidemiology, Mailman School of Public Health, Columbia UniversityNew YorkUnited States
| | - Jeffrey L Shaman
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia UniversityNew YorkUnited States
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22
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Hoteit R, Yassine HM. Biological Properties of SARS-CoV-2 Variants: Epidemiological Impact and Clinical Consequences. Vaccines (Basel) 2022; 10:919. [PMID: 35746526 PMCID: PMC9230982 DOI: 10.3390/vaccines10060919] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 05/18/2022] [Accepted: 05/21/2022] [Indexed: 02/06/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a virus that belongs to the coronavirus family and is the cause of coronavirus disease 2019 (COVID-19). As of May 2022, it had caused more than 500 million infections and more than 6 million deaths worldwide. Several vaccines have been produced and tested over the last two years. The SARS-CoV-2 virus, on the other hand, has mutated over time, resulting in genetic variation in the population of circulating variants during the COVID-19 pandemic. It has also shown immune-evading characteristics, suggesting that vaccinations against these variants could be potentially ineffective. The purpose of this review article is to investigate the key variants of concern (VOCs) and mutations of the virus driving the current pandemic, as well as to explore the transmission rates of SARS-CoV-2 VOCs in relation to epidemiological factors and to compare the virus's transmission rate to that of prior coronaviruses. We examined and provided key information on SARS-CoV-2 VOCs in this study, including their transmissibility, infectivity rate, disease severity, affinity for angiotensin-converting enzyme 2 (ACE2) receptors, viral load, reproduction number, vaccination effectiveness, and vaccine breakthrough.
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Affiliation(s)
- Reem Hoteit
- Clinical Research Institute, Faculty of Medicine, American University of Beirut, Beirut 110236, Lebanon;
| | - Hadi M. Yassine
- Biomedical Research Center and College of Health Sciences-QU Health, Qatar University, Doha 2713, Qatar
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23
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Ribeiro Xavier C, Sachetto Oliveira R, da Fonseca Vieira V, Lobosco M, Weber dos Santos R. Characterisation of Omicron Variant during COVID-19 Pandemic and the Impact of Vaccination, Transmission Rate, Mortality, and Reinfection in South Africa, Germany, and Brazil. BIOTECH 2022; 11:biotech11020012. [PMID: 35822785 PMCID: PMC9264399 DOI: 10.3390/biotech11020012] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Revised: 04/21/2022] [Accepted: 04/21/2022] [Indexed: 02/05/2023] Open
Abstract
Several variants of SARS-CoV-2 have been identified in different parts of the world, including Gamma, detected in Brazil, Delta, detected in India, and the recent Omicron variant, detected in South Africa. The emergence of a new variant is a cause of great concern. This work considers an extended version of an SIRD model capable of incorporating the effects of vaccination, time-dependent transmissibility rates, mortality, and even potential reinfections during the pandemic. We use this model to characterise the Omicron wave in Brazil, South Africa, and Germany. During Omicron, the transmissibility increased by five for Brazil and Germany and eight for South Africa, whereas the estimated mortality was reduced by three-fold. We estimated that the reported cases accounted for less than 25% of the actual cases during Omicron. The mortality among the nonvaccinated population in these countries is, on average, three to four times higher than the mortality among the fully vaccinated. Finally, we could only reproduce the observed dynamics after introducing a new parameter that accounts for the percentage of the population that can be reinfected. Reinfection was as high as 40% in South Africa, which has only 29% of its population fully vaccinated and as low as 13% in Brazil, which has over 70% and 80% of its population fully vaccinated and with at least one dose, respectively. The calibrated models were able to estimate essential features of the complex virus and vaccination dynamics and stand as valuable tools for quantifying the impact of protocols and decisions in different populations.
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Affiliation(s)
- Carolina Ribeiro Xavier
- Department of Computer Science, Federal University of São João del-Rei, São João del-Rei 36301-360, MG, Brazil; (C.R.X.); (R.S.O.); (V.d.F.V.)
| | - Rafael Sachetto Oliveira
- Department of Computer Science, Federal University of São João del-Rei, São João del-Rei 36301-360, MG, Brazil; (C.R.X.); (R.S.O.); (V.d.F.V.)
| | - Vinícius da Fonseca Vieira
- Department of Computer Science, Federal University of São João del-Rei, São João del-Rei 36301-360, MG, Brazil; (C.R.X.); (R.S.O.); (V.d.F.V.)
| | - Marcelo Lobosco
- Department of Computer Science, Federal University of Juiz de Fora, Juiz de Fora 36036-330, MG, Brazil;
| | - Rodrigo Weber dos Santos
- Department of Computer Science, Federal University of Juiz de Fora, Juiz de Fora 36036-330, MG, Brazil;
- Correspondence:
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24
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Jeong GU, Yoon GY, Moon HW, Lee W, Hwang I, Kim H, Kim KD, Kim C, Ahn DG, Kim BT, Kim SJ, Kwon YC. Comparison of Plaque Size, Thermal Stability, and Replication Rate among SARS-CoV-2 Variants of Concern. Viruses 2021; 14:v14010055. [PMID: 35062259 PMCID: PMC8781966 DOI: 10.3390/v14010055] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 11/23/2021] [Accepted: 12/28/2021] [Indexed: 12/22/2022] Open
Abstract
SARS-CoV-2, like other RNA viruses, has a propensity for genetic evolution owing to the low fidelity of its viral polymerase. Several recent reports have described a series of novel SARS-CoV-2 variants. Some of these have been identified as variants of concern (VOCs), including alpha (B.1.1.7, Clade GRY), beta (B.1.351, Clade GH), gamma (P.1, Clade GR), and delta (B.1.617.2, Clade G). VOCs are likely to have some effect on transmissibility, antibody evasion, and changes in therapeutic or vaccine effectiveness. However, the physiological and virological understanding of these variants remains poor. We demonstrated that these four VOCs exhibited differences in plaque size, thermal stability at physiological temperature, and replication rates. The mean plaque size of beta was the largest, followed by those of gamma, delta, and alpha. Thermal stability, evaluated by measuring infectivity and half-life after prolonged incubation at physiological temperature, was correlated with plaque size in all variants except alpha. However, despite its relatively high thermal stability, alpha’s small plaque size resulted in lower replication rates and fewer progeny viruses. Our findings may inform further virological studies of SARS-CoV-2 variant characteristics, VOCs, and variants of interest. These studies are important for the effective management of the COVID-19 pandemic.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Seong-Jun Kim
- Correspondence: (S.-J.K.); (Y.-C.K.); Tel.: +82-42-860-7477 (S.-J.K.); +82-42-860-7028 (Y.-C.K.)
| | - Young-Chan Kwon
- Correspondence: (S.-J.K.); (Y.-C.K.); Tel.: +82-42-860-7477 (S.-J.K.); +82-42-860-7028 (Y.-C.K.)
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25
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Laverdure F, Frossard B, Monnet C, Amour J. Extracorporeal membrane oxygenation for COVID-19: Some answers and a remaining question. Anaesth Crit Care Pain Med 2021; 41:100986. [PMID: 34838733 PMCID: PMC8612749 DOI: 10.1016/j.accpm.2021.100986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Florent Laverdure
- Institut de Perfusion, de Réanimation et d'Anesthésie en Chirurgie Cardiaque Paris Sud, IPRA, Hôpital Privé Jacques Cartier, Massy, France.
| | - Benjamin Frossard
- Institut de Perfusion, de Réanimation et d'Anesthésie en Chirurgie Cardiaque Paris Sud, IPRA, Hôpital Privé Jacques Cartier, Massy, France
| | | | - Julien Amour
- Institut de Perfusion, de Réanimation et d'Anesthésie en Chirurgie Cardiaque Paris Sud, IPRA, Hôpital Privé Jacques Cartier, Massy, France
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26
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Ayoub HH, Mumtaz GR, Seedat S, Makhoul M, Chemaitelly H, Abu-Raddad LJ. Estimates of global SARS-CoV-2 infection exposure, infection morbidity, and infection mortality rates in 2020. GLOBAL EPIDEMIOLOGY 2021; 3:100068. [PMID: 34841244 PMCID: PMC8609676 DOI: 10.1016/j.gloepi.2021.100068] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 10/31/2021] [Accepted: 11/19/2021] [Indexed: 12/16/2022] Open
Abstract
We aimed to estimate, albeit crudely and provisionally, national, regional, and global proportions of respective populations that have been infected with SARS-CoV-2 in the first year after the introduction of this virus into human circulation, and to assess infection morbidity and mortality rates, factoring both documented and undocumented infections. The estimates were generated by applying mathematical models to 159 countries and territories. The percentage of the world's population that has been infected as of 31 December 2020 was estimated at 12.56% (95% CI: 11.17-14.05%). It was lowest in the Western Pacific Region at 0.66% (95% CI: 0.59-0.75%) and highest in the Americas at 41.92% (95% CI: 37.95-46.09%). The global infection fatality rate was 10.73 (95% CI: 10.21-11.29) per 10,000 infections. Globally per 1000 infections, the infection acute-care bed hospitalization rate was 19.22 (95% CI: 18.73-19.51), the infection ICU bed hospitalization rate was 4.14 (95% CI: 4.10-4.18). If left unchecked with no vaccination and no other public health interventions, and assuming circulation of only wild-type variants and no variants of concern, the pandemic would eventually cause 8.18 million deaths (95% CI: 7.30-9.18), 163.67 million acute-care hospitalizations (95% CI: 148.12-179.51), and 33.01 million ICU hospitalizations (95% CI: 30.52-35.70), by the time the herd immunity threshold is reached at 60-70% infection exposure. The global population remained far below the herd immunity threshold by end of 2020. Global epidemiology reveals immense regional variation in infection exposure and morbidity and mortality rates.
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Affiliation(s)
- Houssein H. Ayoub
- Mathematics Program, Department of Mathematics, Statistics, and Physics, College of Arts and Sciences, Qatar University, Doha, Qatar
| | - Ghina R. Mumtaz
- Department of Epidemiology and Population Health, American University of Beirut, Beirut, Lebanon
| | - Shaheen Seedat
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, NY, New York, USA
| | - Monia Makhoul
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, NY, New York, USA
| | - Hiam Chemaitelly
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
| | - Laith J. Abu-Raddad
- Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar
- World Health Organization Collaborating Centre for Disease Epidemiology Analytics on HIV/AIDS, Sexually Transmitted Infections, and Viral Hepatitis, Weill Cornell Medicine–Qatar, Cornell University, Qatar Foundation – Education City, Doha, Qatar
- Department of Population Health Sciences, Weill Cornell Medicine, Cornell University, NY, New York, USA
- Department of Public Health, College of Health Sciences, QU Health, Qatar University, Doha, Qatar
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