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Gonzalez-Orozco M, Tseng HC, Hage A, Xia H, Behera P, Afreen K, Peñaflor-Tellez Y, Giraldo MI, Huante M, Puebla-Clark L, van Tol S, Odle A, Crown M, Teruel N, Shelite TR, Menachery V, Endsley M, Endsley JJ, Najmanovich RJ, Bashton M, Stephens R, Shi PY, Xie X, Freiberg AN, Rajsbaum R. TRIM7 ubiquitinates SARS-CoV-2 membrane protein to limit apoptosis and viral replication. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.17.599107. [PMID: 38948778 PMCID: PMC11212893 DOI: 10.1101/2024.06.17.599107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
SARS-CoV-2 is a highly transmissible virus that causes COVID-19 disease. Mechanisms of viral pathogenesis include excessive inflammation and viral-induced cell death, resulting in tissue damage. We identified the host E3-ubiquitin ligase TRIM7 as an inhibitor of apoptosis and SARS-CoV-2 replication via ubiquitination of the viral membrane (M) protein. Trim7 -/- mice exhibited increased pathology and virus titers associated with epithelial apoptosis and dysregulated immune responses. Mechanistically, TRIM7 ubiquitinates M on K14, which protects cells from cell death. Longitudinal SARS-CoV-2 sequence analysis from infected patients revealed that mutations on M-K14 appeared in circulating variants during the pandemic. The relevance of these mutations was tested in a mouse model. A recombinant M-K14/K15R virus showed reduced viral replication, consistent with the role of K15 in virus assembly, and increased levels of apoptosis associated with the loss of ubiquitination on K14. TRIM7 antiviral activity requires caspase-6 inhibition, linking apoptosis with viral replication and pathology.
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Affiliation(s)
- Maria Gonzalez-Orozco
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX
| | - Hsiang-chi Tseng
- Center for Virus-Host-Innate-Immunity, RBHS Institute for Infectious and Inflammatory Diseases, and Department of Medicine, New Jersey Medical School, Rutgers University, Newark, NJ
| | - Adam Hage
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX
| | - Hongjie Xia
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX
| | - Padmanava Behera
- Center for Virus-Host-Innate-Immunity, RBHS Institute for Infectious and Inflammatory Diseases, and Department of Medicine, New Jersey Medical School, Rutgers University, Newark, NJ
| | - Kazi Afreen
- Center for Virus-Host-Innate-Immunity, RBHS Institute for Infectious and Inflammatory Diseases, and Department of Medicine, New Jersey Medical School, Rutgers University, Newark, NJ
| | - Yoatzin Peñaflor-Tellez
- Center for Virus-Host-Innate-Immunity, RBHS Institute for Infectious and Inflammatory Diseases, and Department of Medicine, New Jersey Medical School, Rutgers University, Newark, NJ
| | - Maria I. Giraldo
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX
| | - Matthew Huante
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX
| | - Lucinda Puebla-Clark
- Department of Internal Medicine, Division of Infectious Diseases, University of Texas Medical Branch, Galveston, TX
| | - Sarah van Tol
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX
| | - Abby Odle
- Center for Virus-Host-Innate-Immunity, RBHS Institute for Infectious and Inflammatory Diseases, and Department of Medicine, New Jersey Medical School, Rutgers University, Newark, NJ
| | - Matthew Crown
- Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle, UK
| | - Natalia Teruel
- Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal, Montreal, Canada
| | - Thomas R Shelite
- Department of Internal Medicine, Division of Infectious Diseases, University of Texas Medical Branch, Galveston, TX
| | - Vineet Menachery
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX
| | - Mark Endsley
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX
| | - Janice J. Endsley
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX
| | - Rafael J. Najmanovich
- Department of Pharmacology and Physiology, Faculty of Medicine, Université de Montréal, Montreal, Canada
| | - Matthew Bashton
- Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle, UK
| | - Robin Stephens
- Department of Internal Medicine, Division of Infectious Diseases, University of Texas Medical Branch, Galveston, TX
- Center for Immunity and Inflammation and Department of Pharmacology, Physiology and Neuroscience, New Jersey Medical School, Rutgers University, Newark, NJ
| | - Pei-Yong Shi
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX
| | - Xuping Xie
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, TX
| | | | - Ricardo Rajsbaum
- Department of Microbiology and Immunology, University of Texas Medical Branch, Galveston, TX
- Center for Virus-Host-Innate-Immunity, RBHS Institute for Infectious and Inflammatory Diseases, and Department of Medicine, New Jersey Medical School, Rutgers University, Newark, NJ
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Wang Y, Hao A, Ji P, Ma Y, Zhang Z, Chen J, Mao Q, Xiong X, Rehati P, Wang Y, Wang Y, Wen Y, Lu L, Chen Z, Zhao J, Wu F, Huang J, Sun L. A bispecific antibody exhibits broad neutralization against SARS-CoV-2 Omicron variants XBB.1.16, BQ.1.1 and sarbecoviruses. Nat Commun 2024; 15:5127. [PMID: 38879565 PMCID: PMC11180174 DOI: 10.1038/s41467-024-49096-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 05/22/2024] [Indexed: 06/19/2024] Open
Abstract
The Omicron subvariants BQ.1.1, XBB.1.5, and XBB.1.16 of SARS-CoV-2 are known for their adeptness at evading immune responses. Here, we isolate a neutralizing antibody, 7F3, with the capacity to neutralize all tested SARS-CoV-2 variants, including BQ.1.1, XBB.1.5, and XBB.1.16. 7F3 targets the receptor-binding motif (RBM) region and exhibits broad binding to a panel of 37 RBD mutant proteins. We develop the IgG-like bispecific antibody G7-Fc using 7F3 and the cross-neutralizing antibody GW01. G7-Fc demonstrates robust neutralizing activity against all 28 tested SARS-CoV-2 variants and sarbecoviruses, providing potent prophylaxis and therapeutic efficacy against XBB.1 infection in both K18-ACE and BALB/c female mice. Cryo-EM structure analysis of the G7-Fc in complex with the Omicron XBB spike (S) trimer reveals a trimer-dimer conformation, with G7-Fc synergistically targeting two distinct RBD epitopes and blocking ACE2 binding. Comparative analysis of 7F3 and LY-CoV1404 epitopes highlights a distinct and highly conserved epitope in the RBM region bound by 7F3, facilitating neutralization of the immune-evasive Omicron variant XBB.1.16. G7-Fc holds promise as a potential prophylactic countermeasure against SARS-CoV-2, particularly against circulating and emerging variants.
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Affiliation(s)
- Yingdan Wang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
- Shanghai Frontiers Science Center of Pathogenic Microorganisms and Infection, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Aihua Hao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Ping Ji
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Yunping Ma
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
- Shanghai Immune Therapy Institute, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai, China
| | - Zhaoyong Zhang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Jiali Chen
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Qiyu Mao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Xinyi Xiong
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Palizhati Rehati
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Yajie Wang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Yanqun Wang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Yumei Wen
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Lu Lu
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Zhenguo Chen
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Jincun Zhao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
- Shanghai Institute for Advanced Immunochemical Studies, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
| | - Fan Wu
- Shanghai Immune Therapy Institute, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai, China.
| | - Jinghe Huang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China.
- Shanghai Frontiers Science Center of Pathogenic Microorganisms and Infection, School of Basic Medical Sciences, Fudan University, Shanghai, China.
| | - Lei Sun
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China.
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53
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Kim JM, Kim D, Rhee JE, Yoo CK, Kim EJ. Replication kinetics and infectivity of SARS-CoV-2 Omicron variant sublineages recovered in the Republic of Korea. Osong Public Health Res Perspect 2024; 15:260-264. [PMID: 38988029 PMCID: PMC11237318 DOI: 10.24171/j.phrp.2023.0216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 02/14/2024] [Accepted: 04/02/2024] [Indexed: 07/12/2024] Open
Abstract
BACKGROUND We analyzed the correlation between the infectivity and transmissibility of the severe acute respiratory syndrome coronavirus 2 Omicron sublineages BA.1, BA. 2, BA.4, and BA.5. METHODS We assessed viral replication kinetics and infectivity at the cellular level. Nasopharyngeal and oropharyngeal specimens were obtained from patients with coronavirus disease 2019, confirmed using whole-genome sequencing to be caused by the Omicron sublineages BA.1, BA.2, BA.4, or BA.5. These specimens were used to infect Vero E6 cells, derived from monkey kidneys, for the purpose of viral isolation. Viral stocks were then passaged in Vero E6 cells at a multiplicity of infection of 0.01, and culture supernatants were harvested at 12-hour intervals for 72 hours. To evaluate viral replication kinetics, we determined the cycle threshold values of the supernatants using real-time reverse transcription polymerase chain reaction and converted these values to genome copy numbers. RESULTS The viral load was comparable between BA.2, BA.4, and BA.5, whereas BA.1 exhibited a lower value. The peak infectious load of BA.4 was approximately 3 times lower than that of BA.2 and BA.5, while the peak load of BA.2 and BA.5 was about 7 times higher than that of BA.1. Notably, BA.1 demonstrated the lowest infectivity over the entire study period. CONCLUSION Our results suggest that the global BA.5 wave may have been amplified by the higher viral replication and infectivity of BA.5 compared to other Omicron sublineages. These analyses could support the rapid assessment of the impact of novel variants on case incidence.
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Affiliation(s)
- Jeong-Min Kim
- Division of Emerging Infectious Diseases, Department of Disease Diagnosis and Analysis, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea
| | - Dongju Kim
- Division of Emerging Infectious Diseases, Department of Disease Diagnosis and Analysis, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea
| | - Jee Eun Rhee
- Division of Emerging Infectious Diseases, Department of Disease Diagnosis and Analysis, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea
| | - Cheon Kwon Yoo
- Department of Disease Diagnosis and Analysis, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea
| | - Eun-Jin Kim
- Division of Emerging Infectious Diseases, Department of Disease Diagnosis and Analysis, Korea Disease Control and Prevention Agency, Cheongju, Republic of Korea
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Reichmuth ML, Heron L, Beutels P, Hens N, Low N, Althaus CL. Social contacts in Switzerland during the COVID-19 pandemic: Insights from the CoMix study. Epidemics 2024; 47:100771. [PMID: 38821037 DOI: 10.1016/j.epidem.2024.100771] [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: 02/14/2024] [Revised: 04/29/2024] [Accepted: 05/07/2024] [Indexed: 06/02/2024] Open
Abstract
To mitigate the spread of SARS-CoV-2, the Swiss government enacted restrictions on social contacts from 2020 to 2022. In addition, individuals changed their social contact behavior to limit the risk of COVID-19. In this study, we aimed to investigate the changes in social contact patterns of the Swiss population. As part of the CoMix study, we conducted a survey consisting of 24 survey waves from January 2021 to May 2022. We collected data on social contacts and constructed contact matrices for the age groups 0-4, 5-14, 15-29, 30-64, and 65 years and older. We estimated the change in contact numbers during the COVID-19 pandemic to a synthetic pre-pandemic contact matrix. We also investigated the association of the largest eigenvalue of the social contact and transmission matrices with the stringency of pandemic measures, the effective reproduction number (Re), and vaccination uptake. During the pandemic period, 7084 responders reported an average number of 4.5 contacts (95% confidence interval, CI: 4.5-4.6) per day overall, which varied by age and survey wave. Children aged 5-14 years had the highest number of contacts with 8.5 (95% CI: 8.1-8.9) contacts on average per day and participants that were 65 years and older reported the fewest (3.4, 95% CI: 3.2-3.5) per day. Compared with the pre-pandemic baseline, we found that the 15-29 and 30-64 year olds had the largest reduction in contacts. We did not find statistically significant associations between the largest eigenvalue of the social contact and transmission matrices and the stringency of measures, Re, or vaccination uptake. The number of social contacts in Switzerland fell during the COVID-19 pandemic and remained below pre-pandemic levels after contact restrictions were lifted. The collected social contact data will be critical in informing modeling studies on the transmission of respiratory infections in Switzerland and to guide pandemic preparedness efforts.
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Affiliation(s)
- Martina L Reichmuth
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Leonie Heron
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Philippe Beutels
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, Antwerp, Belgium
| | - Niel Hens
- Centre for Health Economic Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, Antwerp, Belgium; Data Science Institute, I-BioStat, Hasselt University, Hasselt, Belgium
| | - Nicola Low
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Multidisciplinary Center for Infectious Diseases, University of Bern, Bern, Switzerland
| | - Christian L Althaus
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland; Multidisciplinary Center for Infectious Diseases, University of Bern, Bern, Switzerland.
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55
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Hoenigsperger H, Sivarajan R, Sparrer KM. Differences and similarities between innate immune evasion strategies of human coronaviruses. Curr Opin Microbiol 2024; 79:102466. [PMID: 38555743 DOI: 10.1016/j.mib.2024.102466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Revised: 02/20/2024] [Accepted: 03/12/2024] [Indexed: 04/02/2024]
Abstract
So far, seven coronaviruses have emerged in humans. Four recurring endemic coronaviruses cause mild respiratory symptoms. Infections with epidemic Middle East respiratory syndrome-related coronavirus or severe acute respiratory syndrome coronavirus (SARS-CoV)-1 are associated with high mortality rates. SARS-CoV-2 is the causative agent of the coronavirus disease 2019 pandemic. To establish an infection, coronaviruses evade restriction by human innate immune defenses, such as the interferon system, autophagy and the inflammasome. Here, we review similar and distinct innate immune manipulation strategies employed by the seven human coronaviruses. We further discuss the impact on pathogenesis, zoonotic emergence and adaptation. Understanding the nature of the interplay between endemic/epidemic/pandemic coronaviruses and host defenses may help to better assess the pandemic potential of emerging coronaviruses.
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Affiliation(s)
- Helene Hoenigsperger
- Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany
| | - Rinu Sivarajan
- Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany
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Endo N, Nihei Y, Fujita T, Yasojima M, Daigo F, Takemori H, Nakamura M, Matsuda R, Sovannrlaksmy S, Ihara M. Explaining the impact of mutations on quantification of SARS-CoV-2 in wastewater. Sci Rep 2024; 14:12482. [PMID: 38816525 PMCID: PMC11139995 DOI: 10.1038/s41598-024-62659-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Accepted: 05/20/2024] [Indexed: 06/01/2024] Open
Abstract
Wastewater surveillance is an effective tool for monitoring community spread of COVID-19 and other diseases. Quantitative PCR (qPCR) analysis for wastewater surveillance is more susceptible to mutations in target genome regions than binary PCR analysis for clinical surveillance. The SARS-CoV-2 concentrations in wastewater estimated by N1 and N2 qPCR assays started to diverge around July 2022 in data from different sampling sites, analytical methods, and analytical laboratories in Japan. On the basis of clinical genomic surveillance data and experimental data, we demonstrate that the divergence is due to two mutations in the N1 probe region, which can cause underestimation of viral concentrations. We further show that this inaccuracy can be alleviated if the qPCR data are analyzed with the second derivative method or the Cy0 method instead of the crossing point method.
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Affiliation(s)
- Noriko Endo
- Research Center for Environmental Quality Management, Graduate School of Engineering, Kyoto University, 1-2 Yumihama, Otsu, Shiga, 520-0811, Japan.
| | - Yoshiaki Nihei
- Research Center for Environmental Quality Management, Graduate School of Engineering, Kyoto University, 1-2 Yumihama, Otsu, Shiga, 520-0811, Japan
- Water Agency, Inc., 3-25 Higashi-Goken-cho, Shinjuku-ku, Tokyo, 162-0813, Japan
| | - Tomonori Fujita
- Research Center for Environmental Quality Management, Graduate School of Engineering, Kyoto University, 1-2 Yumihama, Otsu, Shiga, 520-0811, Japan
| | - Makoto Yasojima
- Shimadzu Techno-Research, Inc., 1 Nishinokyo Shimoai-cho, Nakagyo-ku, Kyoto, 604-8436, Japan
| | - Fumi Daigo
- Shimadzu Techno-Research, Inc., 1 Nishinokyo Shimoai-cho, Nakagyo-ku, Kyoto, 604-8436, Japan
| | - Hiroaki Takemori
- Shimadzu Techno-Research, Inc., 1 Nishinokyo Shimoai-cho, Nakagyo-ku, Kyoto, 604-8436, Japan
| | - Masafumi Nakamura
- Hiyoshi Corporation, 908 Kitanosho, Omihachiman, Shiga, 523-0806, Japan
| | - Ryo Matsuda
- Hiyoshi Corporation, 908 Kitanosho, Omihachiman, Shiga, 523-0806, Japan
| | - Sorn Sovannrlaksmy
- Faculty of Agriculture and Marine Science, Kochi University, 200 Monobe-Otsu, Nankoku City, Kochi, 783-8502, Japan
| | - Masaru Ihara
- Faculty of Agriculture and Marine Science, Kochi University, 200 Monobe-Otsu, Nankoku City, Kochi, 783-8502, Japan
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Yi B, Patrasová E, Šimůnková L, Rost F, Winkler S, Laubner A, Reinhardt S, Dahl A, Dalpke AH. Investigating the cause of a 2021 winter wave of COVID-19 in a border region in eastern Germany: a mixed-methods study, August to November 2021. Epidemiol Infect 2024; 152:e87. [PMID: 38751220 PMCID: PMC11149030 DOI: 10.1017/s0950268824000761] [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: 01/28/2023] [Revised: 04/15/2024] [Accepted: 04/24/2024] [Indexed: 05/31/2024] Open
Abstract
It is so far unclear how the COVID-19 winter waves started and what should be done to prevent possible future waves. In this study, we deciphered the dynamic course of a winter wave in 2021 in Saxony, a state in Eastern Germany neighbouring the Czech Republic and Poland. The study was carried out through the integration of multiple virus genomic epidemiology approaches to track transmission chains, identify emerging variants and investigate dynamic changes in transmission clusters. For identified local variants of interest, functional evaluations were performed. Multiple long-lasting community transmission clusters have been identified acting as driving force for the winter wave 2021. Analysis of the dynamic courses of two representative clusters indicated a similar transmission pattern. However, the transmission cluster caused by a locally occurring new Delta variant AY.36.1 showed a distinct transmission pattern, and functional analyses revealed a replication advantage of it. This study indicated that long-lasting community transmission clusters starting since early autumn caused by imported or locally occurring variants all contributed to the development of the 2021 winter wave. The information we achieved might help future pandemic prevention.
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Affiliation(s)
- Buqing Yi
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Eva Patrasová
- Department of Epidemiology, Regional Public Health Authority for Ustecky Kraj, Ústí nad Labem, Czech Republic
- Third Faculty of Medicine, Charles University in Prague, Prague, Czech Republic
| | - Lenka Šimůnková
- Department of Epidemiology, Regional Public Health Authority for Ustecky Kraj, Ústí nad Labem, Czech Republic
| | - Fabian Rost
- DRESDEN-Concept Genome Center, Center for Molecular and Cellular Bioengineering, Technische Universität Dresden, Dresden, Germany
- Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany
| | - Sylke Winkler
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
- DRESDEN-Concept Genome Center, Technische Universität Dresden, Dresden, Germany
| | - Alexa Laubner
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - Susanne Reinhardt
- DRESDEN-Concept Genome Center, Center for Molecular and Cellular Bioengineering, Technische Universität Dresden, Dresden, Germany
| | - Andreas Dahl
- DRESDEN-Concept Genome Center, Center for Molecular and Cellular Bioengineering, Technische Universität Dresden, Dresden, Germany
| | - Alexander H. Dalpke
- Institute of Medical Microbiology and Virology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
- Department of Infectious Diseases, Medical Microbiology and Hygiene, University of Heidelberg, Heidelberg, Germany
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Gill EE, Jia B, Murall CL, Poujol R, Anwar MZ, John NS, Richardsson J, Hobb A, Olabode AS, Lepsa A, Duggan AT, Tyler AD, N’Guessan A, Kachru A, Chan B, Yoshida C, Yung CK, Bujold D, Andric D, Su E, Griffiths EJ, Van Domselaar G, Jolly GW, Ward HK, Feher H, Baker J, Simpson JT, Uddin J, Ragoussis J, Eubank J, Fritz JH, Gálvez JH, Fang K, Cullion K, Rivera L, Xiang L, Croxen MA, Shiell M, Prystajecky N, Quirion PO, Bajari R, Rich S, Mubareka S, Moreira S, Cain S, Sutcliffe SG, Kraemer SA, Joly Y, Alturmessov Y, consortium CPHLN, consortium C, VirusSeq Data Portal Academic and Health network, Fiume M, Snutch TP, Bell C, Lopez-Correa C, Hussin JG, Joy JB, Colijn C, Gordon PM, Hsiao WW, Poon AF, Knox NC, Courtot M, Stein L, Otto SP, Bourque G, Shapiro BJ, Brinkman FS. The Canadian VirusSeq Data Portal & Duotang: open resources for SARS-CoV-2 viral sequences and genomic epidemiology. ARXIV 2024:arXiv:2405.04734v1. [PMID: 38764594 PMCID: PMC11100916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 05/21/2024]
Abstract
The COVID-19 pandemic led to a large global effort to sequence SARS-CoV-2 genomes from patient samples to track viral evolution and inform public health response. Millions of SARS-CoV-2 genome sequences have been deposited in global public repositories. The Canadian COVID-19 Genomics Network (CanCOGeN - VirusSeq), a consortium tasked with coordinating expanded sequencing of SARS-CoV-2 genomes across Canada early in the pandemic, created the Canadian VirusSeq Data Portal, with associated data pipelines and procedures, to support these efforts. The goal of VirusSeq was to allow open access to Canadian SARS-CoV-2 genomic sequences and enhanced, standardized contextual data that were unavailable in other repositories and that meet FAIR standards (Findable, Accessible, Interoperable and Reusable). In addition, the Portal data submission pipeline contains data quality checking procedures and appropriate acknowledgement of data generators that encourages collaboration. From inception to execution, the portal was developed with a conscientious focus on strong data governance principles and practices. Extensive efforts ensured a commitment to Canadian privacy laws, data security standards, and organizational processes. This Portal has been coupled with other resources like Viral AI and was further leveraged by the Coronavirus Variants Rapid Response Network (CoVaRR-Net) to produce a suite of continually updated analytical tools and notebooks. Here we highlight this Portal, including its contextual data not available elsewhere, and the 'Duotang', a web platform that presents key genomic epidemiology and modeling analyses on circulating and emerging SARS-CoV-2 variants in Canada. Duotang presents dynamic changes in variant composition of SARS-CoV-2 in Canada and by province, estimates variant growth, and displays complementary interactive visualizations, with a text overview of the current situation. The VirusSeq Data Portal and Duotang resources, alongside additional analyses and resources computed from the Portal (COVID-MVP, CoVizu), are all open-source and freely available. Together, they provide an updated picture of SARS-CoV-2 evolution to spur scientific discussions, inform public discourse, and support communication with and within public health authorities. They also serve as a framework for other jurisdictions interested in open, collaborative sequence data sharing and analyses.
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Affiliation(s)
- Erin E. Gill
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada
| | - Baofeng Jia
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada
| | - Carmen Lia Murall
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Raphaël Poujol
- Research Centre, Montréal Heart Institute, Montréal, QC, Canada
| | - Muhammad Zohaib Anwar
- Centre for Infectious Disease Genomics and One Health, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | - Nithu Sara John
- Centre for Infectious Disease Genomics and One Health, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | | | | | - Abayomi S. Olabode
- Department of Pathology and Laboratory Medicine, Western University, ON Canada
| | | | - Ana T. Duggan
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Andrea D. Tyler
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Arnaud N’Guessan
- Département de Biochimie et Médecine Moléculaire, Université de Montréal, Montreal, QC, Canada
- McGill Genome Centre, McGill University, Montréal, QC, Canada
| | - Atul Kachru
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Brandon Chan
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Catherine Yoshida
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Christina K. Yung
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- Indoc Systems, Toronto, ON, Canada
| | - David Bujold
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Canadian Centre for Computational Genomics, Montréal, QC, Canada
| | - Dusan Andric
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Edmund Su
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Emma J. Griffiths
- Centre for Infectious Disease Genomics and One Health, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | - Gary Van Domselaar
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Gordon W. Jolly
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | | | - Henrich Feher
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Jared Baker
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | | | - Jaser Uddin
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | | | - Jon Eubank
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Jörg H. Fritz
- Department of Microbiology and Immunology, McGill Research Center on Complex Traits (MRCCT), Dahdaleh Institute of Genomic Medicine (DIGM), McGill University, Montréal, QC, Canada
| | | | | | - Kim Cullion
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | | | - Linda Xiang
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Matthew A. Croxen
- Alberta Precision Laboratories, Public Health Laboratory, Edmonton, AB, Canada
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada
- Li Ka Shing Institute of Virology, University of Alberta, Edmonton, AB, Canada
- Women and Children’s Health Research Institute, University of Alberta, Edmonton, AB, Canada
| | | | - Natalie Prystajecky
- British Columbia Centre for Disease Control Public Health Laboratory, Vancouver, BC Canada
- Department of Pathology and Laboratory Medicine, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | | | - Rosita Bajari
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Samantha Rich
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Samira Mubareka
- Sunnybrook Research Institute; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | | | - Scott Cain
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Steven G. Sutcliffe
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
| | - Susanne A. Kraemer
- McGill Genome Centre, McGill University, Montréal, QC, Canada
- Aquatic Contaminants Research Division, ECCC, Montréal, QC, Canada
| | - Yann Joly
- Centre of Genomics and Policy, McGill University, Montréal, QC, Canada
| | | | | | | | | | | | - Terrance P. Snutch
- Michael Smith Laboratories and Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Cindy Bell
- Genome Canada, 150 Metcalfe Street, Suite 2100, Ottawa, ON, Canada
| | | | - Julie G. Hussin
- Département de Biochimie et Médecine Moléculaire, Université de Montréal, Montreal, QC, Canada
- Research Centre, Montréal Heart Institute, Montréal, QC, Canada
- Mila-Québec AI institute, Montréal, QC, Canada
| | - Jeffrey B. Joy
- Molecular Epidemiology and Evolutionary Genetics, BC Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada
- Infectious Diseases, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
- Bioinformatics Programme, University of British Columbia, Vancouver, BC, Canada
| | - Caroline Colijn
- Department of Mathematics, Simon Fraser University, Burnaby, BC, Canada
| | - Paul M.K. Gordon
- Centre for Health Genomics and Informatics, University of Calgary, Calgary, AB, Canada
| | - William W.L. Hsiao
- Centre for Infectious Disease Genomics and One Health, Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | - Art F.Y. Poon
- Department of Pathology and Laboratory Medicine, Western University, ON Canada
| | - Natalie C. Knox
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Mélanie Courtot
- Ontario Institute for Cancer Research, Toronto, ON, Canada
- Department of Medical BioPhysics, University of Toronto, ON, Canada
| | - Lincoln Stein
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Sarah P. Otto
- Department of Zoology & Biodiversity Research Centre, University of British Columbia, Vancouver BC Canada
| | - Guillaume Bourque
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Canadian Centre for Computational Genomics, Montréal, QC, Canada
| | - B. Jesse Shapiro
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
| | - Fiona S.L. Brinkman
- Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada
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Sutcliffe SG, Kraemer SA, Ellmen I, Knapp JJ, Overton AK, Nash D, Nissimov JI, Charles TC, Dreifuss D, Topolsky I, Baykal PI, Fuhrmann L, Jablonski KP, Beerenwinkel N, Levy JI, Olabode AS, Becker DG, Gugan G, Brintnell E, Poon AF, Valieris R, Drummond RD, Defelicibus A, Dias-Neto E, Rosales RA, Tojal da Silva I, Orfanou A, Psomopoulos F, Pechlivanis N, Pipes L, Chen Z, Baaijens JA, Baym M, Shapiro BJ. Tracking SARS-CoV-2 variants of concern in wastewater: an assessment of nine computational tools using simulated genomic data. Microb Genom 2024; 10:001249. [PMID: 38785221 PMCID: PMC11165662 DOI: 10.1099/mgen.0.001249] [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: 02/21/2024] [Accepted: 04/18/2024] [Indexed: 05/25/2024] Open
Abstract
Wastewater-based surveillance (WBS) is an important epidemiological and public health tool for tracking pathogens across the scale of a building, neighbourhood, city, or region. WBS gained widespread adoption globally during the SARS-CoV-2 pandemic for estimating community infection levels by qPCR. Sequencing pathogen genes or genomes from wastewater adds information about pathogen genetic diversity, which can be used to identify viral lineages (including variants of concern) that are circulating in a local population. Capturing the genetic diversity by WBS sequencing is not trivial, as wastewater samples often contain a diverse mixture of viral lineages with real mutations and sequencing errors, which must be deconvoluted computationally from short sequencing reads. In this study we assess nine different computational tools that have recently been developed to address this challenge. We simulated 100 wastewater sequence samples consisting of SARS-CoV-2 BA.1, BA.2, and Delta lineages, in various mixtures, as well as a Delta-Omicron recombinant and a synthetic 'novel' lineage. Most tools performed well in identifying the true lineages present and estimating their relative abundances and were generally robust to variation in sequencing depth and read length. While many tools identified lineages present down to 1 % frequency, results were more reliable above a 5 % threshold. The presence of an unknown synthetic lineage, which represents an unclassified SARS-CoV-2 lineage, increases the error in relative abundance estimates of other lineages, but the magnitude of this effect was small for most tools. The tools also varied in how they labelled novel synthetic lineages and recombinants. While our simulated dataset represents just one of many possible use cases for these methods, we hope it helps users understand potential sources of error or bias in wastewater sequencing analysis and to appreciate the commonalities and differences across methods.
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Affiliation(s)
- Steven G. Sutcliffe
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
| | - Susanne A. Kraemer
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
- Environment and Climate Change Canada, Montreal, QC, Canada
| | - Isaac Ellmen
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
| | | | | | - Delaney Nash
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
| | | | | | - David Dreifuss
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Ivan Topolsky
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Pelin I. Baykal
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Lara Fuhrmann
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Kim P. Jablonski
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, BS, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, VD, Switzerland
| | - Joshua I. Levy
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, USA
| | - Abayomi S. Olabode
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Devan G. Becker
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Gopi Gugan
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Erin Brintnell
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Art F.Y. Poon
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - Renan Valieris
- Computational Biology, A.C. Camargo Cancer Center, São Paulo, SP, Brazil
| | | | | | | | | | | | - Aspasia Orfanou
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thermi, 57001, Thessaloníki, Greece
| | - Fotis Psomopoulos
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thermi, 57001, Thessaloníki, Greece
| | - Nikolaos Pechlivanis
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thermi, 57001, Thessaloníki, Greece
| | - Lenore Pipes
- Department of Integrative Biology, University of California, Berkeley, CA, USA
| | - Zihao Chen
- School of Mathematical Sciences, Peking University, Beijing, BJ, PR China
| | - Jasmijn A. Baaijens
- Delft University of Technology, Delft, ZH, Netherlands
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Michael Baym
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - B. Jesse Shapiro
- Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
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Daviña-Núñez C, Pérez S, Cabrera-Alvargonzález JJ, Rincón-Quintero A, Treinta-Álvarez A, Godoy-Diz M, Suárez-Luque S, Regueiro-García B. Performance of amplicon and capture based next-generation sequencing approaches for the epidemiological surveillance of Omicron SARS-CoV-2 and other variants of concern. PLoS One 2024; 19:e0289188. [PMID: 38683803 PMCID: PMC11057745 DOI: 10.1371/journal.pone.0289188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 03/14/2024] [Indexed: 05/02/2024] Open
Abstract
To control the SARS-CoV-2 pandemic, healthcare systems have focused on ramping up their capacity for epidemiological surveillance through viral whole genome sequencing. In this paper, we tested the performance of two protocols of SARS-CoV-2 nucleic acid enrichment, an amplicon enrichment using different versions of the ARTIC primer panel and a hybrid-capture method using KAPA RNA Hypercap. We focused on the challenge of the Omicron variant sequencing, the advantages of automated library preparation and the influence of the bioinformatic analysis in the final consensus sequence. All 94 samples were sequenced using Illumina iSeq 100 and analysed with two bioinformatic pipelines: a custom-made pipeline and an Illumina-owned pipeline. We were unsuccessful in sequencing six samples using the capture enrichment due to low reads. On the other hand, amplicon dropout and mispriming caused the loss of mutation G21987A and the erroneous addition of mutation T15521A respectively using amplicon enrichment. Overall, we found high sequence agreement regardless of method of enrichment, bioinformatic pipeline or the use of automation for library preparation in eight different SARS-CoV-2 variants. Automation and the use of a simple app for bioinformatic analysis can simplify the genotyping process, making it available for more diagnostic facilities and increasing global vigilance.
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Affiliation(s)
- Carlos Daviña-Núñez
- Microbiology and Infectology Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), Vigo, Spain
- Universidade de Vigo, Vigo, Spain
| | - Sonia Pérez
- Microbiology and Infectology Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), Vigo, Spain
- Microbiology Department, Complexo Hospitalario Universitario de Vigo (CHUVI), SERGAS, Vigo, Spain
| | - Jorge Julio Cabrera-Alvargonzález
- Microbiology and Infectology Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), Vigo, Spain
- Microbiology Department, Complexo Hospitalario Universitario de Vigo (CHUVI), SERGAS, Vigo, Spain
| | - Anniris Rincón-Quintero
- Microbiology and Infectology Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), Vigo, Spain
- Microbiology Department, Complexo Hospitalario Universitario de Vigo (CHUVI), SERGAS, Vigo, Spain
| | - Ana Treinta-Álvarez
- Microbiology Department, Complexo Hospitalario Universitario de Vigo (CHUVI), SERGAS, Vigo, Spain
| | - Montse Godoy-Diz
- Microbiology Department, Complexo Hospitalario Universitario de Vigo (CHUVI), SERGAS, Vigo, Spain
| | - Silvia Suárez-Luque
- Dirección Xeral de Saúde Pública, Xunta de Galicia, Consellería de Sanidade, Santiago de Compostela, A Coruña, Spain
| | - Benito Regueiro-García
- Microbiology and Infectology Research Group, Galicia Sur Health Research Institute (IIS Galicia Sur), Vigo, Spain
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Santos JD, Sobral D, Pinheiro M, Isidro J, Bogaardt C, Pinto M, Eusébio R, Santos A, Mamede R, Horton DL, Gomes JP, Borges V. INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance. Genome Med 2024; 16:61. [PMID: 38659008 PMCID: PMC11044337 DOI: 10.1186/s13073-024-01334-3] [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: 11/06/2023] [Accepted: 04/15/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND Implementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification. RESULTS The routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a "generic" build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis. CONCLUSIONS The accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).
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Affiliation(s)
- João Dourado Santos
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Daniel Sobral
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Miguel Pinheiro
- Institute of Biomedicine-iBiMED, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Joana Isidro
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Carlijn Bogaardt
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, University of Surrey, Surrey, UK
| | - Miguel Pinto
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Rodrigo Eusébio
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - André Santos
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Rafael Mamede
- Faculdade de Medicina, Instituto de Microbiologia, Instituto de Medicina Molecular, Universidade de Lisboa, Lisbon, Portugal
| | - Daniel L Horton
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, University of Surrey, Surrey, UK
| | - João Paulo Gomes
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
- Veterinary and Animal Research Centre (CECAV), Faculty of Veterinary Medicine, Lusófona University, Lisbon, Portugal
| | - Vítor Borges
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal.
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Tonon E, Cecchetto R, Diani E, Medaina N, Turri G, Lagni A, Lotti V, Gibellini D. Surfing the Waves of SARS-CoV-2: Analysis of Viral Genome Variants Using an NGS Survey in Verona, Italy. Microorganisms 2024; 12:846. [PMID: 38792676 PMCID: PMC11124265 DOI: 10.3390/microorganisms12050846] [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: 03/06/2024] [Revised: 04/16/2024] [Accepted: 04/22/2024] [Indexed: 05/26/2024] Open
Abstract
The availability of new technologies for deep sequencing, including next-generation sequencing (NGS), allows for the detection of viral genome variations. The epidemiological determination of SARS-CoV-2 viral genome changes during the pandemic waves displayed the genome evolution and subsequent onset of variants over time. These variants were often associated with a different impact on viral transmission and disease severity. We investigated, in a retrospective study, the trend of SARS-CoV-2-positive samples collected from the start of the Italian pandemic (January 2020) to June 2023. In addition, viral RNAs extracted from 938 nasopharyngeal swab samples were analyzed using NGS between February 2022 and June 2023. Sequences were analyzed with bioinformatic tools to identify lineages and mutations and for phylogenetic studies. Six pandemic waves were detected. In our samples, we predominantly detected BA.2, BQ.1, BA.5.1, BA.5.2, and, more recently, XBB.1 and its subvariants. The data describe the SARS-CoV-2 genome evolution involved in viral interactions with the host and the dynamics of specific genome mutations and deletions.
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Affiliation(s)
- Emil Tonon
- Department of Diagnostic and Public Health, Microbiology Section, University of Verona, 37134 Verona, Italy; (E.T.); (R.C.); (A.L.); (V.L.); (D.G.)
- UOC Microbiology Unit, AOUI Verona, 37134 Verona, Italy; (N.M.); (G.T.)
| | - Riccardo Cecchetto
- Department of Diagnostic and Public Health, Microbiology Section, University of Verona, 37134 Verona, Italy; (E.T.); (R.C.); (A.L.); (V.L.); (D.G.)
- UOC Microbiology Unit, AOUI Verona, 37134 Verona, Italy; (N.M.); (G.T.)
| | - Erica Diani
- Department of Diagnostic and Public Health, Microbiology Section, University of Verona, 37134 Verona, Italy; (E.T.); (R.C.); (A.L.); (V.L.); (D.G.)
- UOC Microbiology Unit, AOUI Verona, 37134 Verona, Italy; (N.M.); (G.T.)
| | - Nicoletta Medaina
- UOC Microbiology Unit, AOUI Verona, 37134 Verona, Italy; (N.M.); (G.T.)
| | - Giona Turri
- UOC Microbiology Unit, AOUI Verona, 37134 Verona, Italy; (N.M.); (G.T.)
| | - Anna Lagni
- Department of Diagnostic and Public Health, Microbiology Section, University of Verona, 37134 Verona, Italy; (E.T.); (R.C.); (A.L.); (V.L.); (D.G.)
| | - Virginia Lotti
- Department of Diagnostic and Public Health, Microbiology Section, University of Verona, 37134 Verona, Italy; (E.T.); (R.C.); (A.L.); (V.L.); (D.G.)
| | - Davide Gibellini
- Department of Diagnostic and Public Health, Microbiology Section, University of Verona, 37134 Verona, Italy; (E.T.); (R.C.); (A.L.); (V.L.); (D.G.)
- UOC Microbiology Unit, AOUI Verona, 37134 Verona, Italy; (N.M.); (G.T.)
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Feng Y, Su Q, Li L, He X, Niu P, Guo X, Zhao X, Tang J, Jia Z, Wang J, Wu C, Xia B, Chen Z, Wu Y, Yang J, Chen S, Chen C, Wang S, Dong X. Genomic Surveillance for SARS-CoV-2 Variants: Dominance of XBB Replacement - China, January-June 2023. China CDC Wkly 2024; 6:324-331. [PMID: 38736991 PMCID: PMC11082056 DOI: 10.46234/ccdcw2024.061] [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: 12/13/2023] [Accepted: 03/26/2024] [Indexed: 05/14/2024] Open
Abstract
Introduction In the first half of 2023, a global shift was observed towards the predominance of XBB variants. China faced a significant epidemic between late 2022 and early 2023 due to Omicron subvariants BA.5.2 and BF.7. This study aims to depict the evolving variant distribution among provincial-level administrative divisions (PLADs) in China and explore the factors driving the predominance of XBB replacement. Methods Sequences from local and imported coronavirus disease 2019 (COVID-19) cases recorded between January 1 and June 30, 2023, were included. The study analyzed the changing distribution of viral variants and assessed how the prior dominance of specific variants, XBB subvariants, and imported cases influenced the prevalence of the XBB replacement variant. Results A total of 56,486 sequences were obtained from local cases, and 8,669 sequences were from imported cases. Starting in April, there was a shift in the prevalence of XBB from imported to local cases, with varying dominance among PLADs. In PLADs previously high in BF.7, the rise of XBB was delayed. A positive correlation was found between XBB proportions in imported cases from January to March and local cases in April. The distribution pattern of XBB subvariants differed between local and imported cases within the same PLAD. No significant differences were noted in the replacement rates of XBB subvariants. Conclusions The timing of XBB dominance differed among various PLADs in China in the first half of 2023, correlating closely with the prevalence of XBB variants among imported cases.
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Affiliation(s)
- Yenan Feng
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Qiudong Su
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Lili Li
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaozhou He
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Peihua Niu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaojuan Guo
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiang Zhao
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jing Tang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhiyuan Jia
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ji Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Changcheng Wu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Baicheng Xia
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhixiao Chen
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuchao Wu
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jing Yang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Songqi Chen
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Cao Chen
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shiwen Wang
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaoping Dong
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
- NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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Lipponen A, Kolehmainen A, Oikarinen S, Hokajärvi AM, Lehto KM, Heikinheimo A, Halkilahti J, Juutinen A, Luomala O, Smura T, Liitsola K, Blomqvist S, Savolainen-Kopra C, Pitkänen T. Detection of SARS-COV-2 variants and their proportions in wastewater samples using next-generation sequencing in Finland. Sci Rep 2024; 14:7751. [PMID: 38565591 PMCID: PMC10987589 DOI: 10.1038/s41598-024-58113-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Accepted: 03/25/2024] [Indexed: 04/04/2024] Open
Abstract
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants may have different characteristics, e.g., in transmission, mortality, and the effectiveness of vaccines, indicating the importance of variant detection at the population level. Wastewater-based surveillance of SARS-CoV-2 RNA fragments has been shown to be an effective way to monitor the COVID-19 pandemic at the population level. Wastewater is a complex sample matrix affected by environmental factors and PCR inhibitors, causing insufficient coverage in sequencing, for example. Subsequently, results where part of the genome does not have sufficient coverage are not uncommon. To identify variants and their proportions in wastewater over time, we utilized next-generation sequencing with the ARTIC Network's primer set and bioinformatics pipeline to evaluate the presence of variants in partial genome data. Based on the wastewater data from November 2021 to February 2022, the Delta variant was dominant until mid-December in Helsinki, Finland's capital, and thereafter in late December 2022 Omicron became the most common variant. At the same time, the Omicron variant of SARS-CoV-2 outcompeted the previous Delta variant in Finland in new COVID-19 cases. The SARS-CoV-2 variant findings from wastewater are in agreement with the variant information obtained from the patient samples when visually comparing trends in the sewerage network area. This indicates that the sequencing of wastewater is an effective way to monitor temporal and spatial trends of SARS-CoV-2 variants at the population level.
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Affiliation(s)
- Anssi Lipponen
- Expert Microbiology Unit, Department of Health Security, Finnish Institute for Health and Welfare, Kuopio, Finland.
- Institute of Biomedicine, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.
| | - Aleksi Kolehmainen
- Expert Microbiology Unit, Department of Health Security, Finnish Institute for Health and Welfare, Kuopio, Finland
| | - Sami Oikarinen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Anna-Maria Hokajärvi
- Expert Microbiology Unit, Department of Health Security, Finnish Institute for Health and Welfare, Kuopio, Finland
| | - Kirsi-Maarit Lehto
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Annamari Heikinheimo
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
- Microbiology Unit, Laboratory and Research Division, Finnish Food Authority, Helsinki, Finland
| | - Jani Halkilahti
- Expert Microbiology Unit, Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Aapo Juutinen
- Infectious Disease Control and Vaccinations Unit, Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Oskari Luomala
- Infectious Disease Control and Vaccinations Unit, Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Teemu Smura
- Department of Virology, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Kirsi Liitsola
- Expert Microbiology Unit, Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Soile Blomqvist
- Expert Microbiology Unit, Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Carita Savolainen-Kopra
- Expert Microbiology Unit, Department of Health Security, Finnish Institute for Health and Welfare, Helsinki, Finland
| | - Tarja Pitkänen
- Expert Microbiology Unit, Department of Health Security, Finnish Institute for Health and Welfare, Kuopio, Finland
- Department of Food Hygiene and Environmental Health, Faculty of Veterinary Medicine, University of Helsinki, Helsinki, Finland
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65
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Shafer MM, Bobholz MJ, Vuyk WC, Gregory DA, Roguet A, Haddock Soto LA, Rushford C, Janssen KH, Emmen IE, Ries HJ, Pilch HE, Mullen PA, Fahney RB, Wei W, Lambert M, Wenzel J, Halfmann P, Kawaoka Y, Wilson NA, Friedrich TC, Pray IW, Westergaard R, O'Connor DH, Johnson MC. Tracing the origin of SARS-CoV-2 omicron-like spike sequences detected in an urban sewershed: a targeted, longitudinal surveillance study of a cryptic wastewater lineage. THE LANCET. MICROBE 2024; 5:e335-e344. [PMID: 38484748 PMCID: PMC11049544 DOI: 10.1016/s2666-5247(23)00372-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 11/03/2023] [Accepted: 11/15/2023] [Indexed: 04/08/2024]
Abstract
BACKGROUND The origin of novel SARS-CoV-2 spike sequences found in wastewater, without corresponding detection in clinical specimens, remains unclear. We sought to determine the origin of one such cryptic wastewater lineage by tracking and characterising its persistence and genomic evolution over time. METHODS We first detected a cryptic lineage, WI-CL-001, in municipal wastewater in Wisconsin, USA, in January, 2022. To determine the source of WI-CL-001, we systematically sampled wastewater from targeted sub-sewershed lines and maintenance holes using compositing autosamplers. Viral concentrations in wastewater samples over time were measured by RT digital PCR. In addition to using metagenomic 12s rRNA sequencing to determine the virus's host species, we also sequenced SARS-CoV-2 spike receptor binding domains, and, where possible, whole viral genomes to identify and characterise the evolution of this lineage. FINDINGS We traced WI-CL-001 to its source at a single commercial building. There we detected the cryptic lineage at concentrations as high as 2·7 × 109 genome copies per L. The majority of 12s rRNA sequences detected in wastewater leaving the identified source building were human. Additionally, we generated over 100 viral receptor binding domain and whole-genome sequences from wastewater samples containing the cryptic lineage collected over the 13 consecutive months this virus was detectable (January, 2022, to January, 2023). These sequences contained a combination of fixed nucleotide substitutions characteristic of Pango lineage B.1.234, which circulated in humans in Wisconsin at low levels from October, 2020, to February, 2021. Despite this, mutations in the spike gene and elsewhere resembled those subsequently found in omicron variants. INTERPRETATION We propose that prolonged detection of WI-CL-001 in wastewater indicates persistent shedding of SARS-CoV-2 from a single human initially infected by an ancestral B.1.234 virus. The accumulation of convergent omicron-like mutations in WI-CL-001's ancestral B.1.234 genome probably reflects persistent infection and extensive within-host evolution. People who shed cryptic lineages could be an important source of highly divergent viruses that sporadically emerge and spread. FUNDING The Rockefeller Foundation, Wisconsin Department of Health Services, Centers for Disease Control and Prevention, National Institute on Drug Abuse, and the Center for Research on Influenza Pathogenesis and Transmission.
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Affiliation(s)
- Martin M Shafer
- Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, USA
| | - Max J Bobholz
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - William C Vuyk
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Devon A Gregory
- School of Medicine, University of Missouri, Columbia, MO, USA
| | - Adelaide Roguet
- Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, USA
| | - Luis A Haddock Soto
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Kayley H Janssen
- Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, USA
| | - Isla E Emmen
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Hunter J Ries
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Hannah E Pilch
- Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, USA
| | - Paige A Mullen
- Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, USA
| | - Rebecca B Fahney
- Wisconsin State Laboratory of Hygiene, University of Wisconsin-Madison, Madison, WI, USA
| | - Wanting Wei
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Matthew Lambert
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA; Wisconsin Department of Health Services, Madison, WI, USA
| | - Jeff Wenzel
- Missouri Department of Health and Senior Services, Jefferson City, MO, USA
| | - Peter Halfmann
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Yoshihiro Kawaoka
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Nancy A Wilson
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Thomas C Friedrich
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Ian W Pray
- Wisconsin Department of Health Services, Madison, WI, USA
| | - Ryan Westergaard
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA; Wisconsin Department of Health Services, Madison, WI, USA
| | - David H O'Connor
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Marc C Johnson
- School of Medicine, University of Missouri, Columbia, MO, USA.
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Ou G, Yang Y, Zhang S, Niu S, Cai Q, Liu Y, Lu H. Evolving immune evasion and transmissibility of SARS-CoV-2: The emergence of JN.1 variant and its global impact. Drug Discov Ther 2024; 18:67-70. [PMID: 38382991 DOI: 10.5582/ddt.2024.01008] [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] [Indexed: 02/23/2024]
Abstract
The continuous evolution of SARS-CoV-2 variants constitutes a significant impediment to the public health. The World Health Organization (WHO) has designated the SARS-CoV-2 variant JN.1, which has evolved from its progenitor BA.2.86, as a Variant of Interest (VOI) in light of its enhanced immune evasion and transmissibility. The proliferating dissemination of JN.1 globally accentuates its competitive superiority and the potential to instigate fresh surges of infection, notably among cohorts previously infected by antecedent variants. Notably, prevailing evidence does not corroborate an increase in pathogenicity associated with JN.1, and antiviral agents retain their antiviral activity against both BA.2.86 and JN.1. The sustained effectiveness of antiviral agents offers a beacon of hope. Nonetheless, the variant's adeptness at eluding the immunoprotective effects conferred by extant vaccines highlights the imperative for the development of more effective vaccines and therapeutic approaches. Overall, the distinct evolutionary trajectories of BA.2.86 and JN.1 underscore the necessity for ongoing surveillance and scholarly inquiry to elucidate their implications for the pandemic's evolution, which requires the international communities to foster collaboration through the sharing of data, exchange of insights, and collective scientific endeavors.
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Affiliation(s)
- Guanyong Ou
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Clinical Research Center for infectious disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, Guangdong, China
- National Clinical Research Center for infectious disease, Shenzhen, Guangdong, China
| | - Yang Yang
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Clinical Research Center for infectious disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, Guangdong, China
- National Clinical Research Center for infectious disease, Shenzhen, Guangdong, China
| | - Shengjie Zhang
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Clinical Research Center for infectious disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, Guangdong, China
- National Clinical Research Center for infectious disease, Shenzhen, Guangdong, China
| | - Shiyu Niu
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Clinical Research Center for infectious disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, Guangdong, China
- National Clinical Research Center for infectious disease, Shenzhen, Guangdong, China
| | - Qingxian Cai
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Clinical Research Center for infectious disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, Guangdong, China
- National Clinical Research Center for infectious disease, Shenzhen, Guangdong, China
| | - Yingxia Liu
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Clinical Research Center for infectious disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, Guangdong, China
- National Clinical Research Center for infectious disease, Shenzhen, Guangdong, China
| | - Hongzhou Lu
- Shenzhen Key Laboratory of Pathogen and Immunity, Shenzhen Clinical Research Center for infectious disease, State Key Discipline of Infectious Disease, Shenzhen Third People's Hospital, Second Hospital Affiliated to Southern University of Science and Technology, Shenzhen, Guangdong, China
- National Clinical Research Center for infectious disease, Shenzhen, Guangdong, China
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Krogsgaard LW, Benedetti G, Gudde A, Richter SR, Rasmussen LD, Midgley SE, Qvesel AG, Nauta M, Bahrenscheer NS, von Kappelgaard L, McManus O, Hansen NC, Pedersen JB, Haimes D, Gamst J, Nørgaard LS, Jørgensen ACU, Ejegod DM, Møller SS, Clauson-Kaas J, Knudsen IM, Franck KT, Ethelberg S. Results from the SARS-CoV-2 wastewater-based surveillance system in Denmark, July 2021 to June 2022. WATER RESEARCH 2024; 252:121223. [PMID: 38310802 DOI: 10.1016/j.watres.2024.121223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 11/01/2023] [Accepted: 01/28/2024] [Indexed: 02/06/2024]
Abstract
The microbiological analysis of wastewater samples is increasingly used for the surveillance of SARS-CoV-2 globally. We described the setup process of the national SARS-CoV-2 wastewater-based surveillance system in Denmark, presented its main results during the first year of activities, from July 2021 to June 2022, and discussed their operational significance. The Danish SARS-CoV-2 wastewater-based surveillance system was designed to cover 85 % of the population in Denmark and it entailed taking three weekly samples from 230 sites. Samples were RT-qPCR tested for SARS-CoV-2 RNA, targeting the genetic markers N1, N2 and RdRp, and for two faecal indicators, Pepper Mild Mottle Virus and crAssphage. We calculated the weekly SARS-CoV-2 RNA concentration in the wastewater from each sampling site and monitored it in view of the results from individual testing, at the national and regional levels. We attempted to use wastewater results to identify potential local outbreaks, and we sequenced positive wastewater samples using Nanopore sequencing to monitor the circulation of viral variants in Denmark. The system reached its full implementation by October 2021 and covered up to 86.4 % of the Danish population. The system allowed for monitoring of the national and regional trends of SARS-CoV-2 infections in Denmark. However, the system contribution to the identification of potential local outbreaks was limited by the extensive information available from clinical testing. The sequencing of wastewater samples identified relevant variants of concern, in line with results from sequencing of human samples. Amidst the COVID-19 pandemic, Denmark implemented a nationwide SARS-CoV-2 wastewater-based surveillance system that integrated routine surveillance from individual testing. Today, while testing for COVID-19 at the community level has been discontinued, the system is on the frontline to monitor the occurrence and spread of SARS-CoV-2 in Denmark.
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Affiliation(s)
- Lene Wulff Krogsgaard
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Guido Benedetti
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark.
| | - Aina Gudde
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Stine Raith Richter
- Department of Virus and Microbiological Special Diagnostics, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Lasse Dam Rasmussen
- Department of Virus and Microbiological Special Diagnostics, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Sofie Elisabeth Midgley
- Department of Virus and Microbiological Special Diagnostics, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Amanda Gammelby Qvesel
- Department of Virus and Microbiological Special Diagnostics, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Maarten Nauta
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Naja Stolberg Bahrenscheer
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Lene von Kappelgaard
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Oliver McManus
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark; European Programme for Intervention Epidemiology Training (EPIET), European Centre for Disease Prevention and Control, Gustav III: s Boulevard 40, 16973 Solna, Sweden
| | - Nicco Claudio Hansen
- Test Centre Denmark, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Jan Bryla Pedersen
- Department of Finance, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Danny Haimes
- Danish Patient Safety Authority, Islands Brygge 67, 2300 Copenhagen, Denmark
| | - Jesper Gamst
- Eurofins Environment, Ladelundvej 85, 6600 Vejen, Denmark
| | | | | | | | | | - Jes Clauson-Kaas
- HOFOR - Greater Copenhagen Utility, Ørestads Boulevard 35, 2300 Copenhagen, Denmark
| | - Ida Marie Knudsen
- HOFOR - Greater Copenhagen Utility, Ørestads Boulevard 35, 2300 Copenhagen, Denmark
| | - Kristina Træholt Franck
- Department of Virus and Microbiological Special Diagnostics, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark
| | - Steen Ethelberg
- Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Artillerivej 5, 2300 Copenhagen, Denmark; Department of Public Health, Global Health Section, University of Copenhagen, Øster Farimagsgade 5, 1014 Copenhagen, Denmark
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68
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Arantes I, Gomes M, Ito K, Sarafim S, Gräf T, Miyajima F, Khouri R, de Carvalho FC, de Almeida WAF, Siqueira MM, Resende PC, Naveca FG, Bello G, COVID-19 Fiocruz Genomic Surveillance Network. Spatiotemporal dynamics and epidemiological impact of SARS-CoV-2 XBB lineage dissemination in Brazil in 2023. Microbiol Spectr 2024; 12:e0383123. [PMID: 38315011 PMCID: PMC10913747 DOI: 10.1128/spectrum.03831-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 12/27/2023] [Indexed: 02/07/2024] Open
Abstract
The SARS-CoV-2 XBB is a group of highly immune-evasive lineages of the Omicron variant of concern that emerged by recombining BA.2-descendent lineages and spread worldwide during 2023. In this study, we combine SARS-CoV-2 genomic data (n = 11,065 sequences) with epidemiological data of severe acute respiratory infection (SARI) cases collected in Brazil between October 2022 and July 2023 to reconstruct the space-time dynamics and epidemiologic impact of XBB dissemination in the country. Our analyses revealed that the introduction and local emergence of lineages carrying convergent mutations within the Spike protein, especially F486P, F456L, and L455F, propelled the spread of XBB* lineages in Brazil. The average relative instantaneous reproduction numbers of XBB* + F486P, XBB* + F486P + F456L, and XBB* + F486P + F456L + L455F lineages in Brazil were estimated to be 1.24, 1.33, and 1.48 higher than that of other co-circulating lineages (mainly BQ.1*/BE*), respectively. Despite such a growth advantage, the dissemination of these XBB* lineages had a reduced impact on Brazil's epidemiological scenario concerning previous Omicron subvariants. The peak number of SARI cases from SARS-CoV-2 during the XBB wave was approximately 90%, 80%, and 70% lower than that observed during the previous BA.1*, BA.5*, and BQ.1* waves, respectively. These findings revealed the emergence of multiple XBB lineages with progressively increasing growth advantage, yet with relatively limited epidemiological impact in Brazil throughout 2023. The XBB* + F486P + F456L + L455F lineages stand out for their heightened transmissibility, warranting close monitoring in the months ahead. IMPORTANCE Brazil was one the most affected countries by the SARS-CoV-2 pandemic, with more than 700,000 deaths by mid-2023. This study reconstructs the dissemination of the virus in the country in the first half of 2023, a period characterized by the dissemination of descendants of XBB.1, a recombinant of Omicron BA.2 lineages evolved in late 2022. The analysis supports that XBB dissemination was marked by the continuous emergence of indigenous lineages bearing similar mutations in key sites of their Spike protein, a process followed by continuous increments in transmissibility, and without repercussions in the incidence of severe cases. Thus, the results suggest that the epidemiological impact of the spread of a SARS-CoV-2 variant is influenced by an intricate interplay of factors that extend beyond the virus's transmissibility alone. The study also underlines the need for SARS-CoV-2 genomic surveillance that allows the monitoring of its ever-shifting composition.
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Affiliation(s)
- Ighor Arantes
- Laboratório de Arbovírus e Vírus Hemorrágicos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Marcelo Gomes
- Grupo de Métodos Analíticos em Vigilância Epidemiológica, Fiocruz, Rio de Janeiro, Brazil
| | - Kimihito Ito
- International Institute for Zoonosis Control, Hokkaido University, Hokkaido, Japan
| | - Sharbilla Sarafim
- Laboratório de Arbovírus e Vírus Hemorrágicos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Tiago Gräf
- Laboratório de Virologia Molecular, Instituto Carlos Chagas, Fiocruz, Curitiba, Brazil
| | | | | | - Felipe Cotrim de Carvalho
- Departamento do Programa Nacional de Imunizações, Coordenação-Geral de Vigilância das doenças imunopreveníveis, Secretaria de Vigilância em saúde e ambiente, Brasília, Brazil
| | - Walquiria Aparecida Ferreira de Almeida
- Departamento do Programa Nacional de Imunizações, Coordenação-Geral de Vigilância das doenças imunopreveníveis, Secretaria de Vigilância em saúde e ambiente, Brasília, Brazil
| | - Marilda Mendonça Siqueira
- Laboratório de Vírus Respiratórios, Exantemáticos, Enterovírus e Emergências Virais, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Paola Cristina Resende
- Laboratório de Vírus Respiratórios, Exantemáticos, Enterovírus e Emergências Virais, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Felipe Gomes Naveca
- Laboratório de Arbovírus e Vírus Hemorrágicos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
- Núcleo de Vigilância de Vírus Emergentes, Reemergentes ou Negligenciados, Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Gonzalo Bello
- Laboratório de Arbovírus e Vírus Hemorrágicos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - COVID-19 Fiocruz Genomic Surveillance Network
- Laboratório de Arbovírus e Vírus Hemorrágicos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
- Grupo de Métodos Analíticos em Vigilância Epidemiológica, Fiocruz, Rio de Janeiro, Brazil
- International Institute for Zoonosis Control, Hokkaido University, Hokkaido, Japan
- Laboratório de Virologia Molecular, Instituto Carlos Chagas, Fiocruz, Curitiba, Brazil
- Fiocruz, Fortaleza, Brazil
- Instituto Gonçalo Moniz, Fiocruz, Salvador, Brazil
- Departamento do Programa Nacional de Imunizações, Coordenação-Geral de Vigilância das doenças imunopreveníveis, Secretaria de Vigilância em saúde e ambiente, Brasília, Brazil
- Laboratório de Vírus Respiratórios, Exantemáticos, Enterovírus e Emergências Virais, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
- Núcleo de Vigilância de Vírus Emergentes, Reemergentes ou Negligenciados, Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
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García-López R, Taboada B, Zárate S, Muñoz-Medina JE, Salas-Lais AG, Herrera-Estrella A, Boukadida C, Vazquez-Perez JA, Gómez-Gil B, Sanchez-Flores A, Arias CF. Exploration of low-frequency allelic variants of SARS-CoV-2 genomes reveals coinfections in Mexico occurred during periods of VOCs turnover. Microb Genom 2024; 10:001220. [PMID: 38512312 PMCID: PMC11004493 DOI: 10.1099/mgen.0.001220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 03/04/2024] [Indexed: 03/22/2024] Open
Abstract
A total of 14 973 alleles in 29 661 sequenced samples collected between March 2021 and January 2023 by the Mexican Consortium for Genomic Surveillance (CoViGen-Mex) and collaborators were used to construct a thorough map of mutations of the Mexican SARS-CoV-2 genomic landscape containing Intra-Patient Minor Allelic Variants (IPMAVs), which are low-frequency alleles not ordinarily present in a genomic consensus sequence. This additional information proved critical in identifying putative coinfecting variants included alongside the most common variants, B.1.1.222, B.1.1.519, and variants of concern (VOCs) Alpha, Gamma, Delta, and Omicron. A total of 379 coinfection events were recorded in the dataset (a rate of 1.28 %), resulting in the first such catalogue in Mexico. The most common putative coinfections occurred during the spread of Delta or after the introduction of Omicron BA.2 and its descendants. Coinfections occurred constantly during periods of variant turnover when more than one variant shared the same niche and high infection rate was observed, which was dependent on the local variants and time. Coinfections might occur at a higher frequency than customarily reported, but they are often ignored as only the consensus sequence is reported for lineage identification.
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Affiliation(s)
- Rodrigo García-López
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, Mexico
| | - Blanca Taboada
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, Mexico
| | - Selene Zárate
- Posgrado en Ciencias Genómicas, Universidad Autónoma de la Ciudad de México, Mexico City, Mexico
| | - José Esteban Muñoz-Medina
- Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Angel Gustavo Salas-Lais
- Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Alfredo Herrera-Estrella
- Laboratorio Nacional de Genómica para la Biodiversidad-Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados del IPN, Irapuato, Guanajuato, Mexico
| | - Celia Boukadida
- Centro de Investigación en Enfermedades Infecciosas, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
| | - Joel Armando Vazquez-Perez
- Laboratorio de Biología Molecular de Enfermedades Emergentes y EPOC, Instituto Nacional de Enfermedades Respiratorias Ismael Cosío Villegas, Mexico City, Mexico
| | - Bruno Gómez-Gil
- Centro de Investigación en Alimentación y Desarrollo AC, Unidad Mazatlán, Mazatlán, Sinaloa, Mexico
| | - Alejandro Sanchez-Flores
- Unidad Universitaria de Secuenciación Masiva y Bioinformática, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, Mexico
| | - Carlos F. Arias
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, Mexico
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70
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Novkovic M, Banovic Djeri B, Ristivojevic B, Knezevic A, Jankovic M, Tanasic V, Radojicic V, Keckarevic D, Vidanovic D, Tesovic B, Skakic A, Tolinacki M, Moric I, Djordjevic V. Genome sequence diversity of SARS-CoV-2 in Serbia: insights gained from a 3-year pandemic study. Front Microbiol 2024; 15:1332276. [PMID: 38476954 PMCID: PMC10929721 DOI: 10.3389/fmicb.2024.1332276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/15/2024] [Indexed: 03/14/2024] Open
Abstract
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for the COVID-19 pandemic, has been evolving rapidly causing emergence of new variants and health uncertainties. Monitoring the evolution of the virus was of the utmost importance for public health interventions and the development of national and global mitigation strategies. Here, we report national data on the emergence of new variants, their distribution, and dynamics in a 3-year study conducted from March 2020 to the end of January 2023 in the Republic of Serbia. Nasopharyngeal and oropharyngeal swabs from 2,398 COVID-19-positive patients were collected and sequenced using three different next generation technologies: Oxford Nanopore, Ion Torrent, and DNBSeq. In the subset of 2,107 SARS-CoV-2 sequences which met the quality requirements, detection of mutations, assignment to SARS-CoV-2 lineages, and phylogenetic analysis were performed. During the 3-year period, we detected three variants of concern, namely, Alpha (5.6%), Delta (7.4%), and Omicron (70.3%) and one variant of interest-Omicron recombinant "Kraken" (XBB1.5) (<1%), whereas 16.8% of the samples belonged to other SARS-CoV-2 (sub)lineages. The detected SARS-CoV-2 (sub)lineages resulted in eight COVID-19 pandemic waves in Serbia, which correspond to the pandemic waves reported in Europe and the United States. Wave dynamics in Serbia showed the most resemblance with the profile of pandemic waves in southern Europe, consistent with the southeastern European location of Serbia. The samples were assigned to sixteen SARS-CoV-2 Nextstrain clades: 20A, 20B, 20C, 20D, 20E, 20G, 20I, 21J, 21K, 21L, 22A, 22B, 22C, 22D, 22E, and 22F and six different Omicron recombinants (XZ, XAZ, XAS, XBB, XBF, and XBK). The 10 most common mutations detected in the coding and untranslated regions of the SARS-CoV-2 genomes included four mutations affecting the spike protein (S:D614G, S:T478K, S:P681H, and S:S477N) and one mutation at each of the following positions: 5'-untranslated region (5'UTR:241); N protein (N:RG203KR); NSP3 protein (NSP3:F106F); NSP4 protein (NSP4:T492I); NSP6 protein (NSP6: S106/G107/F108 - triple deletion), and NSP12b protein (NSP12b:P314L). This national-level study is the most comprehensive in terms of sequencing and genomic surveillance of SARS-CoV-2 during the pandemic in Serbia, highlighting the importance of establishing and maintaining good national practice for monitoring SARS-CoV-2 and other viruses circulating worldwide.
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Affiliation(s)
- Mirjana Novkovic
- Center for Genome Sequencing and Bioinformatics, Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Bojana Banovic Djeri
- Center for Genome Sequencing and Bioinformatics, Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Bojan Ristivojevic
- Center for Genome Sequencing and Bioinformatics, Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Aleksandra Knezevic
- Institute of Microbiology and Immunology, Department of Virology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Marko Jankovic
- Institute of Microbiology and Immunology, Department of Virology, Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Vanja Tanasic
- Center for Forensic and Applied Molecular Genetics, Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | - Verica Radojicic
- Center for Forensic and Applied Molecular Genetics, Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | - Dusan Keckarevic
- Center for Forensic and Applied Molecular Genetics, Faculty of Biology, University of Belgrade, Belgrade, Serbia
| | - Dejan Vidanovic
- Veterinary Specialized Institute “Kraljevo”, Kraljevo, Serbia
| | - Bojana Tesovic
- Veterinary Specialized Institute “Kraljevo”, Kraljevo, Serbia
| | - Anita Skakic
- Center for Genome Sequencing and Bioinformatics, Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Maja Tolinacki
- Center for Genome Sequencing and Bioinformatics, Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Ivana Moric
- Center for Genome Sequencing and Bioinformatics, Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
| | - Valentina Djordjevic
- Center for Genome Sequencing and Bioinformatics, Institute of Molecular Genetics and Genetic Engineering, University of Belgrade, Belgrade, Serbia
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71
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Thakali O, Mercier É, Eid W, Wellman M, Brasset-Gorny J, Overton AK, Knapp JJ, Manuel D, Charles TC, Goodridge L, Arts EJ, Poon AFY, Brown RS, Graber TE, Delatolla R, DeGroot CT. Real-time evaluation of signal accuracy in wastewater surveillance of pathogens with high rates of mutation. Sci Rep 2024; 14:3728. [PMID: 38355869 PMCID: PMC10866965 DOI: 10.1038/s41598-024-54319-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 02/11/2024] [Indexed: 02/16/2024] Open
Abstract
Wastewater surveillance of coronavirus disease 2019 (COVID-19) commonly applies reverse transcription-quantitative polymerase chain reaction (RT-qPCR) to quantify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in wastewater over time. In most applications worldwide, maximal sensitivity and specificity of RT-qPCR has been achieved, in part, by monitoring two or more genomic loci of SARS-CoV-2. In Ontario, Canada, the provincial Wastewater Surveillance Initiative reports the average copies of the CDC N1 and N2 loci normalized to the fecal biomarker pepper mild mottle virus. In November 2021, the emergence of the Omicron variant of concern, harboring a C28311T mutation within the CDC N1 probe region, challenged the accuracy of the consensus between the RT-qPCR measurements of the N1 and N2 loci of SARS-CoV-2. In this study, we developed and applied a novel real-time dual loci quality assurance and control framework based on the relative difference between the loci measurements to the City of Ottawa dataset to identify a loss of sensitivity of the N1 assay in the period from July 10, 2022 to January 31, 2023. Further analysis via sequencing and allele-specific RT-qPCR revealed a high proportion of mutations C28312T and A28330G during the study period, both in the City of Ottawa and across the province. It is hypothesized that nucleotide mutations in the probe region, especially A28330G, led to inefficient annealing, resulting in reduction in sensitivity and accuracy of the N1 assay. This study highlights the importance of implementing quality assurance and control criteria to continually evaluate, in near real-time, the accuracy of the signal produced in wastewater surveillance applications that rely on detection of pathogens whose genomes undergo high rates of mutation.
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Affiliation(s)
- Ocean Thakali
- Department of Civil Engineering, University of Ottawa, Ottawa, ON, K1N 6N5, Canada
| | - Élisabeth Mercier
- Department of Civil Engineering, University of Ottawa, Ottawa, ON, K1N 6N5, Canada
| | - Walaa Eid
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, K1H 8L1, Canada
| | - Martin Wellman
- The Ottawa Hospital Research Institute, 1053 Carling Ave, Ottawa, ON, K1Y 4E9, Canada
| | - Julia Brasset-Gorny
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, K1H 8L1, Canada
| | - Alyssa K Overton
- Department of Biology, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| | - Jennifer J Knapp
- Department of Biology, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| | - Douglas Manuel
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, K1H 8L1, Canada
- Department of Family Medicine, University of Ottawa, 75 Laurier Ave. E, Ottawa, ON, K1N 6N5, Canada
- School of Epidemiology and Public Health, University of Ottawa, 75 Laurier Ave. E, Ottawa, ON, K1N 6N5, Canada
| | - Trevor C Charles
- Department of Biology, University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada
| | - Lawrence Goodridge
- Department of Food Science, Canadian Research Institute for Food Safety, University of Guelph, Guelph, ON, N1G 2W1, Canada
| | - Eric J Arts
- Department of Microbiology and Immunology, Western University, London, ON, N6A 3K7, Canada
| | - Art F Y Poon
- Department of Microbiology and Immunology, Western University, London, ON, N6A 3K7, Canada
| | - R Stephen Brown
- School of Environmental Studies and Department of Chemistry, Queen's University, Kingston, ON, Canada
| | - Tyson E Graber
- Children's Hospital of Eastern Ontario Research Institute, Ottawa, ON, K1H 8L1, Canada
| | - Robert Delatolla
- Department of Civil Engineering, University of Ottawa, Ottawa, ON, K1N 6N5, Canada
| | - Christopher T DeGroot
- Department of Mechanical and Materials Engineering, Western University, London, ON, N6A 5B9, Canada.
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72
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Hilti D, Wehrli F, Berchtold S, Bigler S, Bodmer T, Seth-Smith HMB, Roloff T, Kohler P, Kahlert CR, Kaiser L, Egli A, Risch L, Risch M, Wohlwend N. S-Gene Target Failure as an Effective Tool for Tracking the Emergence of Dominant SARS-CoV-2 Variants in Switzerland and Liechtenstein, Including Alpha, Delta, and Omicron BA.1, BA.2, and BA.4/BA.5. Microorganisms 2024; 12:321. [PMID: 38399725 PMCID: PMC10892681 DOI: 10.3390/microorganisms12020321] [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: 12/31/2023] [Revised: 01/24/2024] [Accepted: 02/01/2024] [Indexed: 02/25/2024] Open
Abstract
During the SARS-CoV-2 pandemic, the Dr. Risch medical group employed the multiplex TaqPathTM COVID-19 CE-IVD RT-PCR Kit for large-scale routine diagnostic testing in Switzerland and the principality of Liechtenstein. The TaqPath Kit is a widely used multiplex assay targeting three genes (i.e., ORF1AB, N, S). With emergence of the B.1.1.7 (Alpha) variant, a diagnostic flaw became apparent as the amplification of the S-gene target was absent in these samples due to a deletion (ΔH69/V70) in the Alpha variant genome. This S-gene target failure (SGTF) was the earliest indication of a new variant emerging and was also observed in subsequent variants such as Omicron BA.1 and BA4/BA.5. The Delta variant and Omicron BA.2 did not present with SGTF. From September 2020 to November 2022, we investigated the applicability of the SGTF as a surrogate marker for emerging variants such as B.1.1.7, B.1.617.2 (Delta), and Omicron BA.1, BA.2, and BA.4/BA.5 in samples with cycle threshold (Ct) values < 30. Next to true SGTF-positive and SGTF-negative samples, there were also samples presenting with delayed-type S-gene amplification (higher Ct value for S-gene than ORF1ab gene). Among these, a difference of 3.8 Ct values between the S- and ORF1ab genes was found to best distinguish between "true" SGTF and the cycle threshold variability of the assay. Samples above the cutoff were subsequently termed partial SGTF (pSGTF). Variant confirmation was performed by whole-genome sequencing (Oxford Nanopore Technology, Oxford, UK) or mutation-specific PCR (TIB MOLBIOL). In total, 17,724 (7.4%) samples among 240,896 positives were variant-confirmed, resulting in an overall sensitivity and specificity of 93.2% [92.7%, 93.7%] and 99.3% [99.2%, 99.5%], respectively. Sensitivity was increased to 98.2% [97.9% to 98.4%] and specificity lowered to 98.9% [98.6% to 99.1%] when samples with pSGTF were included. Furthermore, weekly logistic growth rates (α) and sigmoid's midpoint (t0) were calculated based on SGTF data and did not significantly differ from calculations based on comprehensive data from GISAID. The SGTF therefore allowed for a valid real-time estimate for the introduction of all dominant variants in Switzerland and Liechtenstein.
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Affiliation(s)
- Dominique Hilti
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
- Institute of Laboratory Medicine, Private University in the Principality of Liechtenstein (UFL), 9495 Triesen, Liechtenstein
| | - Faina Wehrli
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
| | | | - Susanna Bigler
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
| | - Thomas Bodmer
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
| | | | - Tim Roloff
- Institute of Medical Microbiology, University of Zurich, 8006 Zurich, Switzerland
| | - Philipp Kohler
- Zentrallabor, Kantonsspital Graubünden, 7000 Chur, Switzerland
| | - Christian R. Kahlert
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, 9007 St. Gallen, Switzerland
| | - Laurent Kaiser
- Division of Infectious Diseases, Geneva University Hospitals, 1205 Geneva, Switzerland
- Geneva Centre for Emerging Viral Diseases, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Adrian Egli
- Institute of Medical Microbiology, University of Zurich, 8006 Zurich, Switzerland
| | - Lorenz Risch
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
- Institute of Laboratory Medicine, Private University in the Principality of Liechtenstein (UFL), 9495 Triesen, Liechtenstein
| | - Martin Risch
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, 9007 St. Gallen, Switzerland
| | - Nadia Wohlwend
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
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73
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Rahman N, O'Cathail C, Zyoud A, Sokolov A, Oude Munnink B, Grüning B, Cummins C, Amid C, Nieuwenhuijse DF, Visontai D, Yuan DY, Gupta D, Prasad DK, Gulyás GM, Rinck G, McKinnon J, Rajan J, Knaggs J, Skiby JE, Stéger J, Szarvas J, Gueye K, Papp K, Hoek M, Kumar M, Ventouratou MA, Bouquieaux MC, Koliba M, Mansurova M, Haseeb M, Worp N, Harrison PW, Leinonen R, Thorne R, Selvakumar S, Hunt S, Venkataraman S, Jayathilaka S, Cezard T, Maier W, Waheed Z, Iqbal Z, Aarestrup FM, Csabai I, Koopmans M, Burdett T, Cochrane G. Mobilisation and analyses of publicly available SARS-CoV-2 data for pandemic responses. Microb Genom 2024; 10:001188. [PMID: 38358325 PMCID: PMC10926692 DOI: 10.1099/mgen.0.001188] [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: 05/04/2023] [Accepted: 01/14/2024] [Indexed: 02/16/2024] Open
Abstract
The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and variants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learnt. This paper describes a component of the Platform, the SARS-CoV-2 Data Hubs, which enable the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.
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Affiliation(s)
- Nadim Rahman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Colman O'Cathail
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Ahmad Zyoud
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Alexey Sokolov
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Bas Oude Munnink
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | - Björn Grüning
- University of Freiburg, Friedrichstr. 39, 79098 Freiburg, Germany
| | - Carla Cummins
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Clara Amid
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | | | - Dávid Visontai
- Eötvös Loránd University, H-1053 Budapest, Egyetem tér 1-3, Hungary
| | - David Yu Yuan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Dipayan Gupta
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Divyae K. Prasad
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | - Gábor Máté Gulyás
- Technical University of Denmark, Anker Engelunds Vej 101, 2800 Kongens Lyngby, Denmark
| | - Gabriele Rinck
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Jasmine McKinnon
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Jeena Rajan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Jeff Knaggs
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Jeffrey Edward Skiby
- Technical University of Denmark, Anker Engelunds Vej 101, 2800 Kongens Lyngby, Denmark
| | - József Stéger
- Eötvös Loránd University, H-1053 Budapest, Egyetem tér 1-3, Hungary
| | - Judit Szarvas
- Technical University of Denmark, Anker Engelunds Vej 101, 2800 Kongens Lyngby, Denmark
| | - Khadim Gueye
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Krisztián Papp
- Eötvös Loránd University, H-1053 Budapest, Egyetem tér 1-3, Hungary
| | - Maarten Hoek
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | - Manish Kumar
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Marianna A. Ventouratou
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | | | - Martin Koliba
- Technical University of Denmark, Anker Engelunds Vej 101, 2800 Kongens Lyngby, Denmark
| | - Milena Mansurova
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Muhammad Haseeb
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Nathalie Worp
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | - Peter W. Harrison
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Rasko Leinonen
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Ross Thorne
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Sandeep Selvakumar
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Sarah Hunt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Sundar Venkataraman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Suran Jayathilaka
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Timothée Cezard
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Wolfgang Maier
- University of Freiburg, Friedrichstr. 39, 79098 Freiburg, Germany
| | - Zahra Waheed
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Zamin Iqbal
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | | | - Istvan Csabai
- Eötvös Loránd University, H-1053 Budapest, Egyetem tér 1-3, Hungary
| | - Marion Koopmans
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | - Tony Burdett
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Guy Cochrane
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
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McBroome J, de Bernardi Schneider A, Roemer C, Wolfinger MT, Hinrichs AS, O'Toole AN, Ruis C, Turakhia Y, Rambaut A, Corbett-Detig R. A framework for automated scalable designation of viral pathogen lineages from genomic data. Nat Microbiol 2024; 9:550-560. [PMID: 38316930 PMCID: PMC10847047 DOI: 10.1038/s41564-023-01587-5] [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: 02/06/2023] [Accepted: 12/13/2023] [Indexed: 02/07/2024]
Abstract
Pathogen lineage nomenclature systems are a key component of effective communication and collaboration for researchers and public health workers. Since February 2021, the Pango dynamic lineage nomenclature for SARS-CoV-2 has been sustained by crowdsourced lineage proposals as new isolates were sequenced. This approach is vulnerable to time-critical delays as well as regional and personal bias. Here we developed a simple heuristic approach for dividing phylogenetic trees into lineages, including the prioritization of key mutations or genes. Our implementation is efficient on extremely large phylogenetic trees consisting of millions of sequences and produces similar results to existing manually curated lineage designations when applied to SARS-CoV-2 and other viruses including chikungunya virus, Venezuelan equine encephalitis virus complex and Zika virus. This method offers a simple, automated and consistent approach to pathogen nomenclature that can assist researchers in developing and maintaining phylogeny-based classifications in the face of ever-increasing genomic datasets.
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Affiliation(s)
- Jakob McBroome
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA.
| | - Adriano de Bernardi Schneider
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Cornelius Roemer
- Biozentrum, University of Basel, Basel, Switzerland
- Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Michael T Wolfinger
- Department of Theoretical Chemistry, University of Vienna, Vienna, Austria
- Research Group Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Vienna, Austria
- RNA Forecast e.U., Vienna, Austria
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany
| | - Angie S Hinrichs
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Aine Niamh O'Toole
- Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, UK
| | - Christopher Ruis
- Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Department of Medicine, University of Cambridge, Cambridge, UK
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
- Cambridge Centre for AI in Medicine, University of Cambridge, Cambridge, UK
| | - Yatish Turakhia
- Department of Electrical and Computer Engineering, University of California San Diego, San Diego, CA, USA
| | - Andrew Rambaut
- Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, UK
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA.
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75
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Focosi D, Spezia PG, Maggi F. Fixation and reversion of mutations in the receptor-binding domain of SARS-CoV-2 spike protein. Diagn Microbiol Infect Dis 2024; 108:116104. [PMID: 38048665 DOI: 10.1016/j.diagmicrobio.2023.116104] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 10/06/2023] [Accepted: 10/09/2023] [Indexed: 12/06/2023]
Affiliation(s)
- Daniele Focosi
- North-Western Tuscany Blood Bank Pisa University Hospital, Pisa, Italy.
| | - Pietro Giorgio Spezia
- Laboratory of Virology, National Institute for Infectious Diseases, Lazzaro Spallanzani IRCCS, Rome, Italy
| | - Fabrizio Maggi
- Laboratory of Virology, National Institute for Infectious Diseases, Lazzaro Spallanzani IRCCS, Rome, Italy
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76
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Al Qurashi YMA, Abdulhakim JA, Alkhalil SS, Alansari M, Almutiri R, Alabbasi R, Fawzy MS. Molecular Epidemiology of Omicron CH.1.1 Lineage: Genomic and Phenotypic Data Perspective. Cureus 2024; 16:e53496. [PMID: 38440013 PMCID: PMC10910519 DOI: 10.7759/cureus.53496] [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] [Accepted: 01/31/2024] [Indexed: 03/06/2024] Open
Abstract
BACKGROUND The Omicron variant (B.1.1.529 lineage) of SARS-CoV-2 represents a substantial global health challenge due to its high transmissibility and potential resistance to immunity from vaccines or previous infections. Among the rapidly evolving Omicron lineages, the BA.2.75 and the emerging CH.1.1 have garnered attention. While BA.2.75 is marked by mutations that may enhance immune evasion, CH.1.1 is distinguished by the S: L452R mutation, linked to increased pathogenicity and transmission. Initially identified in India by the end of 2021, these variants have exhibited global dissemination, signaling an urgent need to track and analyze their progression. METHODS In this study, the genomic and geographical distribution data of CH.1.1 were collected from the Global Initiative on Sharing Avian Influenza Data (GISAID), PANGOLIN, CoV-Spectrum, and NextStrain databases. Due to the unavailability of epidemiological and genomic data of the CH.1.1 lineage, PubMed and ScienceDirect were used as sources of the phenotypic data of the lineage variations. Amino acid variations utilized in the data mining included S: R346T, S: K444T, S: L452R, and S: F486S. RESULTS The current epidemiological data indicate that CH.1.1 is more likely to become one of the dominant spreading lineages in the United Kingdom, New Zealand, Australia, and the United States based on a 32% growth advantage, present CH.1.1 lineage cases number, and the amino acid variation's impact. CONCLUSION A significant increase in the newly detected lineage CH.1.1 is highly anticipated. The rise in the detected sequences number from 13,231 on January 21, 2023, to 23,181 on February 6, 2023, supports the prediction and growth advantage of the lineage detected cases. Increases in viral transmissibility caused by higher affinity to ACE2 receptors and immune evasion are deduced from amino acid variations analyzed in the study.
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Affiliation(s)
| | - Jawaher A Abdulhakim
- Department of Medical Laboratory, College of Applied Medical Sciences, Taibah University, Yanbu, SAU
| | - Samia S Alkhalil
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Shaqra University, Alquwayiyah, SAU
| | - Maymuna Alansari
- Department of Medical Laboratory, College of Applied Medical Sciences, Taibah University, Yanbu, SAU
| | - Renad Almutiri
- Department of Medical Laboratory, College of Applied Medical Sciences, Taibah University, Yanbu, SAU
| | - Rageed Alabbasi
- Department of Medical Laboratory, College of Applied Medical Sciences, Taibah University, Yanbu, SAU
| | - Manal S Fawzy
- Department of Biochemistry, Unit of Medical Research and Postgraduate Studies, Faculty of Medicine, Northern Border University, Arar, SAU
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77
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Reuschl AK, Thorne LG, Whelan MVX, Ragazzini R, Furnon W, Cowton VM, De Lorenzo G, Mesner D, Turner JLE, Dowgier G, Bogoda N, Bonfanti P, Palmarini M, Patel AH, Jolly C, Towers GJ. Evolution of enhanced innate immune suppression by SARS-CoV-2 Omicron subvariants. Nat Microbiol 2024; 9:451-463. [PMID: 38228858 PMCID: PMC10847042 DOI: 10.1038/s41564-023-01588-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 12/13/2023] [Indexed: 01/18/2024]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) human adaptation resulted in distinct lineages with enhanced transmissibility called variants of concern (VOCs). Omicron is the first VOC to evolve distinct globally dominant subvariants. Here we compared their replication in human cell lines and primary airway cultures and measured host responses to infection. We discovered that subvariants BA.4 and BA.5 have improved their suppression of innate immunity when compared with earlier subvariants BA.1 and BA.2. Similarly, more recent subvariants (BA.2.75 and XBB lineages) also triggered reduced innate immune activation. This correlated with increased expression of viral innate antagonists Orf6 and nucleocapsid, reminiscent of VOCs Alpha to Delta. Increased Orf6 levels suppressed host innate responses to infection by decreasing IRF3 and STAT1 signalling measured by transcription factor phosphorylation and nuclear translocation. Our data suggest that convergent evolution of enhanced innate immune antagonist expression is a common pathway of human adaptation and link Omicron subvariant dominance to improved innate immune evasion.
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Affiliation(s)
| | - Lucy G Thorne
- Division of Infection and Immunity, University College London, London, UK
- Department of Infectious Diseases, St Mary's Medical School, Imperial College London, London, UK
| | - Matthew V X Whelan
- Division of Infection and Immunity, University College London, London, UK
| | - Roberta Ragazzini
- Division of Infection and Immunity, University College London, London, UK
- Epithelial Stem Cell Biology and Regenerative Medicine Laboratory, The Francis Crick Institute, London, UK
| | - Wilhelm Furnon
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Vanessa M Cowton
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | | | - Dejan Mesner
- Division of Infection and Immunity, University College London, London, UK
| | - Jane L E Turner
- Division of Infection and Immunity, University College London, London, UK
| | - Giulia Dowgier
- Division of Infection and Immunity, University College London, London, UK
- COVID Surveillance Unit, The Francis Crick Institute, London, UK
| | - Nathasha Bogoda
- Division of Infection and Immunity, University College London, London, UK
| | - Paola Bonfanti
- Division of Infection and Immunity, University College London, London, UK
- Epithelial Stem Cell Biology and Regenerative Medicine Laboratory, The Francis Crick Institute, London, UK
| | | | - Arvind H Patel
- MRC-University of Glasgow Centre for Virus Research, Glasgow, UK
| | - Clare Jolly
- Division of Infection and Immunity, University College London, London, UK.
| | - Greg J Towers
- Division of Infection and Immunity, University College London, London, UK.
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78
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Focosi D, Casadevall A, Franchini M, Maggi F. Sotrovimab: A Review of Its Efficacy against SARS-CoV-2 Variants. Viruses 2024; 16:217. [PMID: 38399991 PMCID: PMC10891757 DOI: 10.3390/v16020217] [Citation(s) in RCA: 17] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 01/24/2024] [Accepted: 01/28/2024] [Indexed: 02/25/2024] Open
Abstract
Among the anti-Spike monoclonal antibodies (mAbs), the S-309 derivative sotrovimab was the most successful in having the longest temporal window of clinical use, showing a high degree of resiliency to SARS-CoV-2 evolution interrupted only by the appearance of the BA.2.86* variant of interest (VOI). This success undoubtedly reflects rational selection to target a highly conserved epitope in coronavirus Spike proteins. We review here the efficacy of sotrovimab against different SARS-CoV-2 variants in outpatients and inpatients, discussing both randomized controlled trials and real-world evidence. Although it could not be anticipated at the time of its development and introduction, sotrovimab's use in immunocompromised individuals who harbor large populations of variant viruses created the conditions for its eventual demise, as antibody selection and viral evolution led to its eventual withdrawal due to inefficacy against later variant lineages. Despite this, based on observational and real-world data, some authorities have continued to promote the use of sotrovimab, but the lack of binding to newer variants strongly argues for the futility of continued use. The story of sotrovimab highlights the power of modern biomedical science to generate novel therapeutics while also providing a cautionary tale for the need to devise strategies to minimize the emergence of resistance to antibody-based therapeutics.
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Affiliation(s)
- Daniele Focosi
- North-Western Tuscany Blood Bank, Pisa University Hospital, via Paradisa 2, 56124 Pisa, Italy
| | - Arturo Casadevall
- Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA;
| | - Massimo Franchini
- Department of Transfusion Medicine and Hematology, Carlo Poma Hospital, 46100 Mantua, Italy;
| | - Fabrizio Maggi
- National Institute for Infectious Diseases “Lazzaro Spallanzani” IRCCS, 00149 Rome, Italy;
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79
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Wang Y, Yan A, Song D, Duan M, Dong C, Chen J, Jiang Z, Gao Y, Rao M, Feng J, Zhang Z, Qi R, Ma X, Liu H, Yu B, Wang Q, Zong M, Jiao J, Xing P, Pan R, Li D, Xiao J, Sun J, Li Y, Zhang L, Shen Z, Sun B, Zhao Y, Zhang L, Dai J, Zhao J, Wang L, Dou C, Liu Z, Zhao J. Identification of a highly conserved neutralizing epitope within the RBD region of diverse SARS-CoV-2 variants. Nat Commun 2024; 15:842. [PMID: 38287016 PMCID: PMC10825162 DOI: 10.1038/s41467-024-45050-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 01/11/2024] [Indexed: 01/31/2024] Open
Abstract
The constant emergence of SARS-CoV-2 variants continues to impair the efficacy of existing neutralizing antibodies, especially XBB.1.5 and EG.5, which showed exceptional immune evasion properties. Here, we identify a highly conserved neutralizing epitope targeted by a broad-spectrum neutralizing antibody BA7535, which demonstrates high neutralization potency against not only previous variants, such as Alpha, Beta, Gamma, Delta and Omicron BA.1-BA.5, but also more recently emerged Omicron subvariants, including BF.7, CH.1.1, XBB.1, XBB.1.5, XBB.1.9.1, EG.5. Structural analysis of the Omicron Spike trimer with BA7535-Fab using cryo-EM indicates that BA7535 recognizes a highly conserved cryptic receptor-binding domain (RBD) epitope, avoiding most of the mutational hot spots in RBD. Furthermore, structural simulation based on the interaction of BA7535-Fab/RBD complexes dissects the broadly neutralizing effect of BA7535 against latest variants. Therapeutic and prophylactic treatment with BA7535 alone or in combination with BA7208 protected female mice from the circulating Omicron BA.5 and XBB.1 variant infection, suggesting the highly conserved neutralizing epitope serves as a potential target for developing highly potent therapeutic antibodies and vaccines.
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Affiliation(s)
- Yanqun Wang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Clinical Laboratory Medicine Department, The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- GMU-GIBH Joint School of Life Sciences, Guangzhou Medical University, Guangzhou, China
| | - An Yan
- Cryo-electron Microscopy Center, Southern University of Science and Technology, Shenzhen, China
| | - Deyong Song
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Maoqin Duan
- Division of Monoclonal Antibodies, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), Beijing, China
| | - Chuangchuang Dong
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Jiantao Chen
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Zihe Jiang
- Cryo-electron Microscopy Center, Southern University of Science and Technology, Shenzhen, China
| | - Yuanzhu Gao
- Cryo-electron Microscopy Center, Southern University of Science and Technology, Shenzhen, China
| | - Muding Rao
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Jianxia Feng
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Zhaoyong Zhang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ruxi Qi
- Cryo-electron Microscopy Center, Southern University of Science and Technology, Shenzhen, China
| | - Xiaomin Ma
- Cryo-electron Microscopy Center, Southern University of Science and Technology, Shenzhen, China
| | - Hong Liu
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Beibei Yu
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Qiaoping Wang
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Mengqi Zong
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Jie Jiao
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Pingping Xing
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Rongrong Pan
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Dan Li
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Juxue Xiao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Junbo Sun
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Ying Li
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Linfeng Zhang
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Zhenduo Shen
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Baiping Sun
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Yanyan Zhao
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China
| | - Lu Zhang
- Health and Quarantine Laboratory, Guangzhou Customs District Technology Centre, Guangzhou, China
| | - Jun Dai
- Health and Quarantine Laboratory, Guangzhou Customs District Technology Centre, Guangzhou, China
| | - Jingxian Zhao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Lan Wang
- Division of Monoclonal Antibodies, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), Beijing, China.
| | - Changlin Dou
- Antibody Research and Development Center, Shandong Boan Biotechnology Co., Ltd., Yantai, China.
| | - Zheng Liu
- Cryo-electron Microscopy Center, Southern University of Science and Technology, Shenzhen, China.
| | - Jincun Zhao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
- Guangzhou National Laboratory, Bio-Island, Guangzhou, China.
- Shanghai Institute for Advanced Immunochemical Studies, School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
- Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third People's Hospital; The Second Affiliated Hospital, School of Medicine, Southern University of Science and Technology, Shenzhen, China.
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80
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Kar M, Johnson KEE, Vanderheiden A, Elrod EJ, Floyd K, Geerling E, Stone ET, Salinas E, Banakis S, Wang W, Sathish S, Shrihari S, Davis-Gardner ME, Kohlmeier J, Pinto A, Klein R, Grakoui A, Ghedin E, Suthar MS. CD4+ and CD8+ T cells are required to prevent SARS-CoV-2 persistence in the nasal compartment. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.23.576505. [PMID: 38410446 PMCID: PMC10896337 DOI: 10.1101/2024.01.23.576505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
SARS-CoV-2 is the causative agent of COVID-19 and continues to pose a significant public health threat throughout the world. Following SARS-CoV-2 infection, virus-specific CD4+ and CD8+ T cells are rapidly generated to form effector and memory cells and persist in the blood for several months. However, the contribution of T cells in controlling SARS-CoV-2 infection within the respiratory tract are not well understood. Using C57BL/6 mice infected with a naturally occurring SARS-CoV-2 variant (B.1.351), we evaluated the role of T cells in the upper and lower respiratory tract. Following infection, SARS-CoV-2-specific CD4+ and CD8+ T cells are recruited to the respiratory tract and a vast proportion secrete the cytotoxic molecule Granzyme B. Using antibodies to deplete T cells prior to infection, we found that CD4+ and CD8+ T cells play distinct roles in the upper and lower respiratory tract. In the lungs, T cells play a minimal role in viral control with viral clearance occurring in the absence of both CD4+ and CD8+ T cells through 28 days post-infection. In the nasal compartment, depletion of both CD4+ and CD8+ T cells, but not individually, results in persistent and culturable virus replicating in the nasal compartment through 28 days post-infection. Using in situ hybridization, we found that SARS-CoV-2 infection persisted in the nasal epithelial layer of tandem CD4+ and CD8+ T cell-depleted mice. Sequence analysis of virus isolates from persistently infected mice revealed mutations spanning across the genome, including a deletion in ORF6. Overall, our findings highlight the importance of T cells in controlling virus replication within the respiratory tract during SARS-CoV-2 infection.
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81
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You R, Wu R, Wang X, Fu R, Xia N, Chen Y, Yang K, Chen J. Systematic Genomic Surveillance of SARS-CoV-2 at Xiamen International Airport and the Port of Xiamen Reveals the Importance of Incoming Travelers in Lineage Diversity. Viruses 2024; 16:132. [PMID: 38257832 PMCID: PMC10821529 DOI: 10.3390/v16010132] [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: 12/15/2023] [Revised: 01/13/2024] [Accepted: 01/15/2024] [Indexed: 01/24/2024] Open
Abstract
Sever Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is still a threat to human health globally despite the World Health Organization (WHO) announcing the end of the COVID-19 pandemic. Continued surveillance of SARS-CoV-2 at national borders would be helpful in understanding the epidemics of novel imported variants and updating local strategies for disease prevention and treatment. This study focuses on the surveillance of imported SARS-CoV-2 variants among travelers entering Xiamen International Airport and the Port of Xiamen from February to August 2023. A total of 97 imported SARS-CoV-2 sequences among travelers from 223 cases collected from 12 different countries and regions were identified by real-time RT-PCR. Next-generation sequencing was used to generate high-quality complete sequences for phylogenetic and population dynamic analysis. The study revealed a dominant shift in variant distribution, in which the XBB subvariant (XBB.1.5, XBB.1.16, XBB.1.9, XBB.2.3, and EG.5.1) accounted for approximately 88.8% of the sequenced samples. In detail, clades 23D and 23E accounted for 26.2% and 21.4% of the sequenced samples, respectively, while clades 23B (13.6%) and 23F (10.7%) took the third and fourth spots in the order of imported sequences, respectively. Additionally, the XBB.2.3 variants were first identified in imported cases from the mainland of Xiamen, China on 27 February 2023. The spatiotemporal analyses of recent viral genome sequences from a limited number of travelers into Xiamen provide valuable insights into the situation surrounding SARS-CoV-2 and highlight the importance of sentinel surveillance of SARS-CoV-2 variants in the national border screening of incoming travelers, which serves as an early warning system for the presence of highly transmissible circulating SARS-CoV-2 lineages.
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Affiliation(s)
- Ruiluan You
- Xiamen International Travel Healthcare Center, Xiamen Entry-Exit Inspection and Quarantine Bureau, Xiamen 361001, China;
| | - Ruotong Wu
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Department of Laboratory Medicine, School of Public Health & School of Life Sciences, Xiamen University, Xiamen 361102, China; (R.W.); (N.X.); (Y.C.)
| | - Xijing Wang
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Department of Laboratory Medicine, School of Public Health & School of Life Sciences, Xiamen University, Xiamen 361102, China; (R.W.); (N.X.); (Y.C.)
| | - Rao Fu
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Department of Laboratory Medicine, School of Public Health & School of Life Sciences, Xiamen University, Xiamen 361102, China; (R.W.); (N.X.); (Y.C.)
- 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, Xiamen University, Xiamen 361102, China
| | - Ningshao Xia
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Department of Laboratory Medicine, School of Public Health & School of Life Sciences, Xiamen University, Xiamen 361102, China; (R.W.); (N.X.); (Y.C.)
- 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, Xiamen University, Xiamen 361102, China
| | - Yixin Chen
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Department of Laboratory Medicine, School of Public Health & School of Life Sciences, Xiamen University, Xiamen 361102, China; (R.W.); (N.X.); (Y.C.)
- 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, Xiamen University, Xiamen 361102, China
| | - Kunyu Yang
- Xiamen International Travel Healthcare Center, Xiamen Entry-Exit Inspection and Quarantine Bureau, Xiamen 361001, China;
| | - Junyu Chen
- State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, Department of Laboratory Medicine, School of Public Health & School of Life Sciences, Xiamen University, Xiamen 361102, China; (R.W.); (N.X.); (Y.C.)
- 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, Xiamen University, Xiamen 361102, China
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82
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Di Chiara C, Cantarutti A, Raffaella Petrara M, Bonfante F, Benetti E, Boracchini R, Bosa L, Carmona F, Cosma C, Cotugno N, Le Prevost M, Martini G, Meneghel A, Pagliari M, Palma P, Ruffoni E, Zin A, De Rossi A, Giaquinto C, Donà D, Padoan A. Stronger and durable SARS-CoV-2 immune response to mRNA vaccines in 5-11 years old children with prior COVID-19. Vaccine 2024; 42:263-270. [PMID: 38071105 DOI: 10.1016/j.vaccine.2023.12.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Revised: 11/08/2023] [Accepted: 12/01/2023] [Indexed: 01/01/2024]
Abstract
BACKGROUND AND OBJECTIVES mRNA vaccines elicit a durable humoral response to SARS-CoV-2 in adults, whereas evidence in children is scarce. This study aimed to assess the early and long-term immune response to the mRNA vaccine in children with or without previous SARS-CoV-2 infection. METHODS In a multicentre prospective observational study, we profiled the immune response to the Pfizer BioNTech (BNT162b2) vaccine in 5-11-year-old children attending the University Pediatric Hospital of Padua and Bambino-Gesù Hospital in Rome (Italy) from December-2021 to February-2023. Blood samples were collected pre-, 1-, and 6-months after vaccination. Neutralizing antibodies (NAbs) and anti-spike-receptor-binding-domain (anti-S-RBD) IgG titers were analyzed through Plaque Reduction Neutralization Test (PRNT) and chemiluminescent immune-enzymatic assay (CLIA), respectively. Immune cell phenotypes were analyzed by flow cytometry. RESULTS Sixty children (26 [43 %] female, median age = 8 years [IQR = 7-10.7]) were enrolled in the study, including 46 children with a laboratory-confirmed previous COVID-19 (SARS-CoV-2-recovered) and 14 SARS-CoV-2-naïve participants defined as the absence of antigen-specific antibodies before vaccination. SARS-CoV-2-recovered participants recorded higher anti-S-RBD IgG and Wild-type and Omicron BA.2 NAbs titers than SARS-CoV-2-naïve participants at both 1- and 6-months after vaccination. Antibody titers correlated with T (Tregs) and B (Bregs) regulatory cell frequencies in SARS-CoV-2-recovered children. Both SARS-CoV-2-recovered and SARS-CoV-2-naïve participants decreased antibody titers by approximately 100 to 250 % from 1 to 6 months. While children with immunocompromising underlying conditions developed immune responses comparable to those of healthy children, solid organ transplant recipients exhibited lower levels of NAbs and anti-S-RBD IgG titers, as well as reduced frequencies of Tregs and Bregs. CONCLUSIONS mRNA vaccination triggered a higher production of specific anti-SARS-CoV-2 antibodies along with increased levels of regulatory cells in children with previous SARS-CoV-2 infection up to the following 6 months. These findings provide insights into boosting pre-existing immunity.
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Affiliation(s)
- Costanza Di Chiara
- Department for Women's and Children's Health, University of Padova, Via Giustiniani, 3 - 35128 Padua, Italy; Penta - Child Health Research, Corso Stati Uniti, 4 - 35127 Padua, Italy.
| | - Anna Cantarutti
- Department of Statistics and Quantitative Methods, Division of Biostatistics, Epidemiology and Public Health, Laboratory of Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Piazza dell'Ateneo Nuovo, 1 - 20126 Milan, Italy.
| | - Maria Raffaella Petrara
- Oncology and Immunology Section, Department of Surgery, Oncology and Gastroenterology, University of Padova, Via Giustiniani, 2 - 35124 Padua, Italy.
| | - Francesco Bonfante
- Division of Comparative Biomedical Sciences, Istituto Zooprofilattico Sperimentale delle Venezie, Viale dell'Università, 10 - 35020 Legnaro (Padua), Italy.
| | - Elisa Benetti
- Department of Medicine-DIMED, University of Padova, Via Giustiniani 2, 35128 Padua, Italy.
| | - Riccardo Boracchini
- Department of Statistics and Quantitative Methods, Division of Biostatistics, Epidemiology and Public Health, Laboratory of Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Piazza dell'Ateneo Nuovo, 1 - 20126 Milan, Italy.
| | - Luca Bosa
- Department for Women's and Children's Health, University of Padova, Via Giustiniani, 3 - 35128 Padua, Italy.
| | - Francesco Carmona
- Immunology and Diagnostic Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Via Gattamelata, 64 - 35128 Padua, Italy.
| | - Chiara Cosma
- Department of Laboratory Medicine, University-Hospital of Padova, Via Giambattista Belzoni, 160 - 35121 Padua, Italy.
| | - Nicola Cotugno
- Unit of Clinical Immunology and Vaccinology, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy; Department of Systems Medicine, University of Rome "Tor Vergata", Piazza Sant'Onofrio, 4 - 00165 Rome, Italy.
| | - Marthe Le Prevost
- Medical Research Council Clinical Trials Unit at University College London, 90 High Holborn, WC1V 6LJ London, United Kingdom.
| | - Giorgia Martini
- Department for Women's and Children's Health, University of Padova, Via Giustiniani, 3 - 35128 Padua, Italy.
| | - Alessandra Meneghel
- Department for Women's and Children's Health, University of Padova, Via Giustiniani, 3 - 35128 Padua, Italy.
| | - Matteo Pagliari
- Division of Comparative Biomedical Sciences, Istituto Zooprofilattico Sperimentale delle Venezie, Viale dell'Università, 10 - 35020 Legnaro (Padua), Italy.
| | - Paolo Palma
- Unit of Clinical Immunology and Vaccinology, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy; Department of Systems Medicine, University of Rome "Tor Vergata", Piazza Sant'Onofrio, 4 - 00165 Rome, Italy.
| | - Elena Ruffoni
- Immunology and Diagnostic Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Via Gattamelata, 64 - 35128 Padua, Italy.
| | - Annachiara Zin
- Department for Women's and Children's Health, University of Padova, Via Giustiniani, 3 - 35128 Padua, Italy.
| | - Anita De Rossi
- Oncology and Immunology Section, Department of Surgery, Oncology and Gastroenterology, University of Padova, Via Giustiniani, 2 - 35124 Padua, Italy; Immunology and Diagnostic Molecular Oncology Unit, Veneto Institute of Oncology IOV-IRCCS, Via Gattamelata, 64 - 35128 Padua, Italy.
| | - Carlo Giaquinto
- Department for Women's and Children's Health, University of Padova, Via Giustiniani, 3 - 35128 Padua, Italy; Penta - Child Health Research, Corso Stati Uniti, 4 - 35127 Padua, Italy.
| | - Daniele Donà
- Department for Women's and Children's Health, University of Padova, Via Giustiniani, 3 - 35128 Padua, Italy; Penta - Child Health Research, Corso Stati Uniti, 4 - 35127 Padua, Italy.
| | - Andrea Padoan
- Department of Medicine-DIMED, University of Padova, Via Giustiniani 2, 35128 Padua, Italy.
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Fuhrmann L, Jablonski KP, Topolsky I, Batavia AA, Borgsmüller N, Baykal PI, Carrara M, Chen C, Dondi A, Dragan M, Dreifuss D, John A, Langer B, Okoniewski M, du Plessis L, Schmitt U, Singer F, Stadler T, Beerenwinkel N. V-pipe 3.0: a sustainable pipeline for within-sample viral genetic diversity estimation. Gigascience 2024; 13:giae065. [PMID: 39347649 PMCID: PMC11440432 DOI: 10.1093/gigascience/giae065] [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: 10/31/2023] [Revised: 06/11/2024] [Accepted: 08/13/2024] [Indexed: 10/01/2024] Open
Abstract
The large amount and diversity of viral genomic datasets generated by next-generation sequencing technologies poses a set of challenges for computational data analysis workflows, including rigorous quality control, scaling to large sample sizes, and tailored steps for specific applications. Here, we present V-pipe 3.0, a computational pipeline designed for analyzing next-generation sequencing data of short viral genomes. It is developed to enable reproducible, scalable, adaptable, and transparent inference of genetic diversity of viral samples. By presenting 2 large-scale data analysis projects, we demonstrate the effectiveness of V-pipe 3.0 in supporting sustainable viral genomic data science.
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Affiliation(s)
- Lara Fuhrmann
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Kim Philipp Jablonski
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Ivan Topolsky
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Aashil A Batavia
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Nico Borgsmüller
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Pelin Icer Baykal
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Matteo Carrara
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
- NEXUS Personalized Health Technologies, ETH Zurich, Basel 4058, Switzerland
| | - Chaoran Chen
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Arthur Dondi
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Monica Dragan
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - David Dreifuss
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Anika John
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Benjamin Langer
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
| | | | - Louis du Plessis
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Uwe Schmitt
- Scientific IT Services, ETH Zurich, Zurich 8092, Switzerland
| | - Franziska Singer
- NEXUS Personalized Health Technologies, ETH Zurich, Basel 4058, Switzerland
| | - Tanja Stadler
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel 4056, Switzerland
- SIB Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
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84
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Hu B, Chan JFW, Liu Y, Liu H, Chen YX, Shuai H, Hu YF, Hartnoll M, Chen L, Xia Y, Hu JC, Yuen TTT, Yoon C, Hou Y, Huang X, Chai Y, Zhu T, Shi J, Wang Y, He Y, Cai JP, Zhou J, Yuan S, Zhang J, Huang JD, Yuen KY, To KKW, Zhang BZ, Chu H. Divergent trajectory of replication and intrinsic pathogenicity of SARS-CoV-2 Omicron post-BA.2/5 subvariants in the upper and lower respiratory tract. EBioMedicine 2024; 99:104916. [PMID: 38101297 PMCID: PMC10733096 DOI: 10.1016/j.ebiom.2023.104916] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 11/23/2023] [Accepted: 11/30/2023] [Indexed: 12/17/2023] Open
Abstract
BACKGROUND Earlier Omicron subvariants including BA.1, BA.2, and BA.5 emerged in waves, with a subvariant replacing the previous one every few months. More recently, the post-BA.2/5 subvariants have acquired convergent substitutions in spike that facilitated their escape from humoral immunity and gained ACE2 binding capacity. However, the intrinsic pathogenicity and replication fitness of the evaluated post-BA.2/5 subvariants are not fully understood. METHODS We systemically investigated the replication fitness and intrinsic pathogenicity of representative post-BA.2/5 subvariants (BL.1, BQ.1, BQ.1.1, XBB.1, CH.1.1, and XBB.1.5) in weanling (3-4 weeks), adult (8-10 weeks), and aged (10-12 months) mice. In addition, to better model Omicron replication in the human nasal epithelium, we further investigated the replication capacity of the post-BA.2/5 subvariants in human primary nasal epithelial cells. FINDINGS We found that the evaluated post-BA.2/5 subvariants are consistently attenuated in mouse lungs but not in nasal turbinates when compared with their ancestral subvariants BA.2/5. Further investigations in primary human nasal epithelial cells revealed a gained replication fitness of XBB.1 and XBB.1.5 when compared to BA.2 and BA.5.2. INTERPRETATION Our study revealed that the post-BA.2/5 subvariants are attenuated in lungs while increased in replication fitness in the nasal epithelium, indicating rapid adaptation of the circulating Omicron subvariants in the human populations. FUNDING The full list of funding can be found at the Acknowledgements section.
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Affiliation(s)
- Bingjie Hu
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Jasper Fuk-Woo Chan
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Department of Infectious Disease and Microbiology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong Province, China; Centre for Virology, Vaccinology and Therapeutics, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China; Academician Workstation of Hainan Province, Hainan Medical University-The University of Hong Kong Joint Laboratory of Tropical Infectious Diseases, Hainan Medical University, Haikou, Hainan, China; and The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Department of Microbiology, Queen Mary Hospital, Pokfulam, Hong Kong Special Administrative Region, China; Guangzhou Laboratory, Guangdong Province, China
| | - Yuanchen Liu
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Huan Liu
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Yan-Xia Chen
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Huiping Shuai
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Ye-Fan Hu
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Madeline Hartnoll
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Li Chen
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Yao Xia
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Jing-Chu Hu
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Terrence Tsz-Tai Yuen
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Centre for Virology, Vaccinology and Therapeutics, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
| | - Chaemin Yoon
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Yuxin Hou
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Centre for Virology, Vaccinology and Therapeutics, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
| | - Xiner Huang
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Yue Chai
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Tianrenzheng Zhu
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Jialu Shi
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Yang Wang
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Yixin He
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Jian-Piao Cai
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Jie Zhou
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Shuofeng Yuan
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Department of Infectious Disease and Microbiology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong Province, China; Centre for Virology, Vaccinology and Therapeutics, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
| | - Jinxia Zhang
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Centre for Virology, Vaccinology and Therapeutics, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China
| | - Jian-Dong Huang
- School of Biomedical Sciences, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong Province, China
| | - Kwok-Yung Yuen
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Department of Infectious Disease and Microbiology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong Province, China; Centre for Virology, Vaccinology and Therapeutics, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China; Academician Workstation of Hainan Province, Hainan Medical University-The University of Hong Kong Joint Laboratory of Tropical Infectious Diseases, Hainan Medical University, Haikou, Hainan, China; and The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Department of Microbiology, Queen Mary Hospital, Pokfulam, Hong Kong Special Administrative Region, China; Guangzhou Laboratory, Guangdong Province, China
| | - Kelvin Kai-Wang To
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Department of Infectious Disease and Microbiology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong Province, China; Centre for Virology, Vaccinology and Therapeutics, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China; Department of Microbiology, Queen Mary Hospital, Pokfulam, Hong Kong Special Administrative Region, China; Guangzhou Laboratory, Guangdong Province, China
| | - Bao-Zhong Zhang
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong Province, China
| | - Hin Chu
- State Key Laboratory of Emerging Infectious Diseases, Department of Microbiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China; Department of Infectious Disease and Microbiology, The University of Hong Kong-Shenzhen Hospital, Shenzhen, Guangdong Province, China; Centre for Virology, Vaccinology and Therapeutics, Hong Kong Science and Technology Park, Hong Kong Special Administrative Region, China.
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85
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Focosi D, Spezia PG, Gueli F, Maggi F. The Era of the FLips: How Spike Mutations L455F and F456L (and A475V) Are Shaping SARS-CoV-2 Evolution. Viruses 2023; 16:3. [PMID: 38275938 PMCID: PMC10818967 DOI: 10.3390/v16010003] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/12/2023] [Accepted: 12/15/2023] [Indexed: 01/27/2024] Open
Abstract
Convergent evolution of the SARS-CoV-2 Spike protein has been mostly driven by immune escape, in particular by escape to the viral infection-neutralizing antibodies (nAbs) elicited by previous infections and/or vaccinations [...].
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Affiliation(s)
- Daniele Focosi
- North-Western Tuscany Blood Bank, Pisa University Hospital, 56124 Pisa, Italy
| | - Pietro Giorgio Spezia
- National Institute for Infectious Diseases “Lazzaro Spallanzani” IRCCS, 00149 Rome, Italy; (P.G.S.); (F.M.)
| | | | - Fabrizio Maggi
- National Institute for Infectious Diseases “Lazzaro Spallanzani” IRCCS, 00149 Rome, Italy; (P.G.S.); (F.M.)
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86
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Ishige T. Molecular biology of SARS-CoV-2 and techniques of diagnosis and surveillance. Adv Clin Chem 2023; 118:35-85. [PMID: 38280807 DOI: 10.1016/bs.acc.2023.11.003] [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] [Indexed: 01/29/2024]
Abstract
The World Health Organization (WHO) declared coronavirus disease 2019 (COVID-19), a disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a global pandemic in March 2020. Reverse transcription-polymerase chain reaction (RT-PCR) is the reference technique for molecular diagnosis of SARS-CoV-2 infection. The SARS-CoV-2 virus is constantly mutating, and more transmissible variants have emerged, making genomic surveillance a crucial tool for investigating virus transmission dynamics, detecting novel genetic variants, and assessing mutation impact. The S gene, which encodes the spike protein, is frequently mutated, and it plays an important role in transmissibility. Spike protein mutations affect infectivity and vaccine effectiveness. SARS-CoV-2 variants are tracked using whole genome sequencing (WGS) and S-gene analysis. WGS, Sanger sequencing, and many S-gene-targeted RT-PCR methods have been developed. WGS and Sanger sequencing are standard methods for detecting mutations and can be used to identify known and unknown mutations. Melting curve analysis, endpoint genotyping assay, and S-gene target failure are used in the RT-PCR-based method for the rapid detection of specific mutations in SARS-CoV-2 variants. Therefore, these assays are suitable for high-throughput screening. The combinatorial use of RT-PCR-based assays, Sanger sequencing, and WGS enables rapid and accurate tracking of SARS-CoV-2 variants. In this review, we described RT-PCR-based detection and surveillance techniques for SARS-CoV-2.
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Affiliation(s)
- Takayuki Ishige
- Division of Laboratory Medicine, Chiba University Hospital, Chiba, Japan.
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87
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Freitas MTDS, Sena LOC, Fukutani KF, dos Santos CA, Neto FDCB, Ribeiro JS, dos Reis ES, Balbino VDQ, de Sá Paiva Leitão S, de Aragão Batista MV, Lipscomb MW, de Moura TR. The increase in SARS-CoV-2 lineages during 2020-2022 in a state in the Brazilian Northeast is associated with a number of cases. Front Public Health 2023; 11:1222152. [PMID: 38186707 PMCID: PMC10771345 DOI: 10.3389/fpubh.2023.1222152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 11/15/2023] [Indexed: 01/09/2024] Open
Abstract
SARS-CoV-2 has caused a high number of deaths in several countries. In Brazil, there were 37 million confirmed cases of COVID-19 and 700,000 deaths caused by the disease. The population size and heterogeneity of the Brazilian population should be considered in epidemiological surveillance due to the varied tropism of the virus. As such, municipalities and states must be factored in for their unique specificities, such as socioeconomic conditions and population distribution. Here, we investigate the spatiotemporal dispersion of emerging SARS-CoV-2 lineages and their dynamics in each microregion from Sergipe state, northeastern Brazil, in the first 3 years of the pandemic. We analyzed 586 genomes sequenced between March 2020 and November 2022 extracted from the GISAID database. Phylogenetic analyses were carried out for each data set to reconstruct evolutionary history. Finally, the existence of a correlation between the number of lineages and infection cases by SARS-CoV-2 was evaluated. Aracaju, the largest city in northeastern Brazil, had the highest number of samples sequenced. This represented 54.6% (320) of the genomes, and consequently, the largest number of lineages identified. Studies also analyzed the relationship between mean lineage distributions and mean monthly infections, daily cases, daily deaths, and hospitalizations of vaccinated and unvaccinated patients. For this, a correlation matrix was created. Results revealed that the increase in the average number of SARS-CoV-2 variants was related to the average number of SARS-CoV-2 cases in both unvaccinated and vaccinated individuals. Thus, our data indicate that it is necessary to maintain epidemiological surveillance, especially in capital cities, since they have a high rate of circulation of resident and non-resident inhabitants, which contributes to the dynamics of the virus.
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Affiliation(s)
- Moises Thiago de Souza Freitas
- Health Sciences Graduate Program, Federal University of Sergipe, Aracaju, Brazil
- Parasitic Biology Graduate Program, Federal University of Sergipe, São Cristóvão, Brazil
| | - Ludmila Oliveira Carvalho Sena
- Health Foundation Parreiras Horta, Central Laboratory of Public Health (LACEN/SE), Sergipe State Health Secretariat, Aracaju, Brazil
| | - Kiyoshi Ferreira Fukutani
- Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, NH, United States
| | - Cliomar Alves dos Santos
- Health Foundation Parreiras Horta, Central Laboratory of Public Health (LACEN/SE), Sergipe State Health Secretariat, Aracaju, Brazil
| | | | - Julienne Sousa Ribeiro
- Center for Biological and Health Sciences, Federal University of Sergipe, São Cristóvão, Brazil
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88
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Cheng CW, Wu CY, Wang SW, Chen JY, Kung CC, Liao KS, Wong CH. Low-sugar universal mRNA vaccine against coronavirus variants with deletion of glycosites in the S2 or stem of SARS-CoV-2 spike messenger RNA (mRNA). Proc Natl Acad Sci U S A 2023; 120:e2314392120. [PMID: 38011546 DOI: 10.1073/pnas.2314392120] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Accepted: 10/25/2023] [Indexed: 11/29/2023] Open
Abstract
Since the outbreak of Severe Acute Respiratory Syndrome Virus-2 (SARS-CoV-2) in 2019, more than 15 million spike protein sequences have been identified, raising a new challenge for the development of a broadly protective vaccine against the various emerging variants. We found that the virus, like most other human viruses, depends on host-made glycans to shield the conserved epitopes on spike protein from immune response and demonstrated that deletion of the glycan shields exposed highly conserved epitopes and elicited broadly protective immune responses. In this study, we identified 17 conserved epitopes from 14 million spike protein sequences and 11 of the conserved epitopes are in the S2 domain, including the six most conserved epitopes in the stem region. We also demonstrated that deletion of the glycosites in the spike messenger RNA (mRNA) S2 domain or the stem region exposed the highly conserved epitopes and elicited broadly protective immune responses, particularly CD-8+ T cell response against various SARS-CoV-2 variants, and other human coronaviruses including MERS, SARS viruses, and those causing common cold.
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Affiliation(s)
- Cheng-Wei Cheng
- Genomics Research Center, Academia Sinica, Taipei City 11529, Taiwan
- The Master Program of AI Application in Health Industry, Kaohsiung Medical University, Kaohsiung City 80708, Taiwan
- Center for Big Data Research, Kaohsiung Medical University, Kaohsiung City 80708, Taiwan
- Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung City 80708, Taiwan
| | - Chung-Yi Wu
- Genomics Research Center, Academia Sinica, Taipei City 11529, Taiwan
- Rock BioMedical, Inc., Taipei City 115202, Taiwan
| | - Szu-Wen Wang
- Genomics Research Center, Academia Sinica, Taipei City 11529, Taiwan
- Rock BioMedical, Inc., Taipei City 115202, Taiwan
| | - Jia-Yan Chen
- Genomics Research Center, Academia Sinica, Taipei City 11529, Taiwan
| | - Chih-Chuan Kung
- Genomics Research Center, Academia Sinica, Taipei City 11529, Taiwan
| | - Kuo-Shiang Liao
- Genomics Research Center, Academia Sinica, Taipei City 11529, Taiwan
| | - Chi-Huey Wong
- Genomics Research Center, Academia Sinica, Taipei City 11529, Taiwan
- Department of Chemistry, Scripps Research, La Jolla, CA 92037
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89
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Faraone JN, Qu P, Goodarzi N, Zheng YM, Carlin C, Saif LJ, Oltz EM, Xu K, Jones D, Gumina RJ, Liu SL. Immune evasion and membrane fusion of SARS-CoV-2 XBB subvariants EG.5.1 and XBB.2.3. Emerg Microbes Infect 2023; 12:2270069. [PMID: 37819267 PMCID: PMC10606793 DOI: 10.1080/22221751.2023.2270069] [Citation(s) in RCA: 56] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 10/05/2023] [Indexed: 10/13/2023]
Abstract
Immune evasion by SARS-CoV-2 paired with immune imprinting from monovalent mRNA vaccines has resulted in attenuated neutralizing antibody responses against Omicron subvariants. In this study, we characterized two new XBB variants rising in circulation - EG.5.1 and XBB.2.3, for their neutralization and syncytia formation. We determined the neutralizing antibody titers in sera of individuals that received a bivalent mRNA vaccine booster, BA.4/5-wave infection, or XBB.1.5-wave infection. Bivalent vaccination-induced antibodies neutralized ancestral D614G efficiently, but to a much less extent, two new EG.5.1 and XBB.2.3 variants. In fact, the enhanced neutralization escape of EG.5.1 appeared to be driven by its key defining mutation XBB.1.5-F456L. Notably, infection by BA.4/5 or XBB.1.5 afforded little, if any, neutralization against EG.5.1, XBB.2.3 and previous XBB variants - especially in unvaccinated individuals, with average neutralizing antibody titers near the limit of detection. Additionally, we investigated the infectivity, fusion activity, and processing of variant spikes for EG.5.1 and XBB.2.3 in HEK293T-ACE2 and CaLu-3 cells but found no significant differences compared to earlier XBB variants. Overall, our findings highlight the continued immune evasion of new Omicron subvariants and, more importantly, the need to reformulate mRNA vaccines to include XBB spikes for better protection.
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Affiliation(s)
- Julia N. Faraone
- Center for Retrovirus Research, The Ohio State University, Columbus, OH, USA
- Department of Veterinary Biosciences, The Ohio State University, Columbus, OH, USA
- Molecular, Cellular, and Developmental Biology Program, The Ohio State University, Columbus, OH, USA
| | - Panke Qu
- Center for Retrovirus Research, The Ohio State University, Columbus, OH, USA
- Department of Veterinary Biosciences, The Ohio State University, Columbus, OH, USA
| | - Negin Goodarzi
- Center for Retrovirus Research, The Ohio State University, Columbus, OH, USA
- Department of Veterinary Biosciences, The Ohio State University, Columbus, OH, USA
| | - Yi-Min Zheng
- Center for Retrovirus Research, The Ohio State University, Columbus, OH, USA
- Department of Veterinary Biosciences, The Ohio State University, Columbus, OH, USA
| | - Claire Carlin
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, Columbus, OH, USA
| | - Linda J. Saif
- Center for Food Animal Health, Animal Sciences Department, OARDC, College of Food, Agricultural and Environmental Sciences, The Ohio State University, Wooster, OH, USA
- Veterinary Preventive Medicine Department, College of Veterinary Medicine, The Ohio State University, Wooster, OH, USA
- Viruses and Emerging Pathogens Program, Infectious Diseases Institute, The Ohio State University, Columbus, OH, USA
| | - Eugene M. Oltz
- Department of Microbial Infection and Immunity, The Ohio State University, Columbus, OH, USA
| | - Kai Xu
- Center for Retrovirus Research, The Ohio State University, Columbus, OH, USA
- Department of Veterinary Biosciences, The Ohio State University, Columbus, OH, USA
| | - Daniel Jones
- Department of Pathology, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Richard J. Gumina
- Department of Internal Medicine, Division of Cardiovascular Medicine, The Ohio State University, Columbus, OH, USA
- Dorothy M. Davis Heart and Lung Research Institute, The Ohio State University Wexner Medical Center, Columbus, OH, USA
- Department of Physiology and Cell Biology, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA
| | - Shan-Lu Liu
- Center for Retrovirus Research, The Ohio State University, Columbus, OH, USA
- Department of Veterinary Biosciences, The Ohio State University, Columbus, OH, USA
- Viruses and Emerging Pathogens Program, Infectious Diseases Institute, The Ohio State University, Columbus, OH, USA
- Department of Microbial Infection and Immunity, The Ohio State University, Columbus, OH, USA
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90
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Taboada BI, Zárate S, García-López R, Muñoz-Medina JE, Gómez-Gil B, Herrera-Estrella A, Sanchez-Flores A, Salas-Lais AG, Roche B, Martínez-Morales G, Domínguez Zárate H, Duque Molina C, Avilés Hernández R, López S, Arias CF. SARS-CoV-2 Omicron variants BA.4 and BA.5 dominated the fifth COVID-19 epidemiological wave in Mexico. Microb Genom 2023; 9:001120. [PMID: 38112714 PMCID: PMC10763511 DOI: 10.1099/mgen.0.001120] [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: 07/04/2023] [Accepted: 10/09/2023] [Indexed: 12/21/2023] Open
Abstract
In Mexico, the BA.4 and BA.5 Omicron variants dominated the fifth epidemic wave (summer 2022), superseding BA.2, which had circulated during the inter-wave period. The present study uses genome sequencing and statistical and phylogenetic analyses to examine these variants' abundance, distribution, and genetic diversity in Mexico from April to August 2022. Over 35 % of the sequenced genomes in this period corresponded to the BA.2 variant, 8 % to the BA.4 and 56 % to the BA.5 variant. Multiple subvariants were identified, but the most abundant, BA.2.9, BA.2.12.1, BA.5.1, BA.5.2, BA.5.2.1 and BA.4.1, circulated across the entire country, not forming geographical clusters. Contrastingly, other subvariants exhibited a geographically restricted distribution, most notably in the Southeast region, which showed a distinct subvariant dynamic. This study supports previous results showing that this region may be a significant entry point and contributed to introducing and evolving novel variants in Mexico. Furthermore, a differential distribution was observed for certain subvariants among specific States through time, which may have contributed to the overall increased diversity observed during this wave compared to the previous ones. This study highlights the importance of sustaining genomic surveillance to identify novel variants that may impact public health.
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Affiliation(s)
- Blanca Itzelt Taboada
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico
| | - Selene Zárate
- Posgrado en Ciencias Genómicas, Universidad Autónoma de la Ciudad de México, Mexico City 03100, Mexico
| | - Rodrigo García-López
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico
| | - José Esteban Muñoz-Medina
- Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro Social, Mexico City 07760, Mexico
| | - Bruno Gómez-Gil
- Centro de Investigación en Alimentación y Desarrollo AC, Coordinación Regional Mazatlán, Acuicultura y Manejo Ambiental, Mazatlan 82100, Mexico
| | - Alfredo Herrera-Estrella
- Laboratorio Nacional de Genómica Para la Biodiversidad-Unidad de Genómica Avanzada, Centro de Investigación y de Estudios Avanzados del IPN, Irapuato 36824, Mexico
| | - Alejandro Sanchez-Flores
- Unidad Universitaria de Secuenciación Masiva y Bioinformática, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico
| | - Angel Gustavo Salas-Lais
- Laboratorio Central de Epidemiología, Instituto Mexicano del Seguro Social, Mexico City 02990, Mexico
| | - Benjamin Roche
- Infectious Diseases: Vector, Control, Genetic, Ecology and Evolution (MIVEGEC) Université de Montpellier, IRD, CNRS, 34090 Montpellier, France
| | - Gabriela Martínez-Morales
- Laboratorio Central de Epidemiología, Instituto Mexicano del Seguro Social, Mexico City 02990, Mexico
| | - Hermilo Domínguez Zárate
- Coordinación de Calidad de Insumos y Laboratorios Especializados, Instituto Mexicano del Seguro Social, Mexico City 07760, Mexico
| | - Célida Duque Molina
- Dirección de Prestaciones Médicas, Instituto Mexicano del Seguro Social, Ciudad de México 06700, Mexico
| | - Ricardo Avilés Hernández
- Unidad de Planeación e Innovación en Salud, Instituto Mexicano del Seguro Social, Ciudad de México, Mexico
| | - Susana López
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico
| | - Carlos F. Arias
- Departamento de Genética del Desarrollo y Fisiología Molecular, Instituto de Biotecnología, Universidad Nacional Autónoma de México, Cuernavaca 62210, Mexico
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91
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Ma Y, Mao Q, Wang Y, Zhang Z, Chen J, Hao A, Rehati P, Wang Y, Wen Y, Lu L, Chen Z, Zhao J, Wu F, Sun L, Huang J. A broadly neutralizing antibody inhibits SARS-CoV-2 variants through a novel mechanism of disrupting spike trimer integrity. Cell Res 2023; 33:975-978. [PMID: 37758899 PMCID: PMC10709632 DOI: 10.1038/s41422-023-00880-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2023] [Accepted: 09/12/2023] [Indexed: 09/29/2023] Open
Affiliation(s)
- Yunping Ma
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
- Shanghai Immune Therapy Institute, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai, China
| | - Qiyu Mao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Yingdan Wang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Zhaoyong Zhang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Jiali Chen
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Aihua Hao
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Palizhati Rehati
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Yanqun Wang
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China
| | - Yumei Wen
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Lu Lu
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Zhenguo Chen
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China
| | - Jincun Zhao
- State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, China.
- Shanghai Institute for Advanced Immunochemical Studies, School of Life Science and Technology, Shanghai Tech University, Shanghai, China.
| | - Fan Wu
- Shanghai Immune Therapy Institute, Shanghai Jiao Tong University School of Medicine Affiliated Renji Hospital, Shanghai, China.
| | - Lei Sun
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China.
| | - Jinghe Huang
- Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS) and Shanghai Institute of Infectious Disease and Biosecurity, Shanghai Public Health Clinical Center, Shanghai Fifth People's Hospital, Institutes of Biomedical Sciences, School of Basic Medical Sciences, Fudan University, Shanghai, China.
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92
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Jian F, Feng L, Yang S, Yu Y, Wang L, Song W, Yisimayi A, Chen X, Xu Y, Wang P, Yu L, Wang J, Liu L, Niu X, Wang J, Xiao T, An R, Wang Y, Gu Q, Shao F, Jin R, Shen Z, Wang Y, Wang X, Cao Y. Convergent evolution of SARS-CoV-2 XBB lineages on receptor-binding domain 455-456 synergistically enhances antibody evasion and ACE2 binding. PLoS Pathog 2023; 19:e1011868. [PMID: 38117863 PMCID: PMC10766189 DOI: 10.1371/journal.ppat.1011868] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2023] [Revised: 01/04/2024] [Accepted: 11/28/2023] [Indexed: 12/22/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) XBB lineages have achieved dominance worldwide and keep on evolving. Convergent evolution of XBB lineages on the receptor-binding domain (RBD) L455F and F456L is observed, resulting in variants with substantial growth advantages, such as EG.5, FL.1.5.1, XBB.1.5.70, and HK.3. Here, we show that neutralizing antibody (NAb) evasion drives the convergent evolution of F456L, while the epistatic shift caused by F456L enables the subsequent convergence of L455F through ACE2 binding enhancement and further immune evasion. L455F and F456L evade RBD-targeting Class 1 public NAbs, reducing the neutralization efficacy of XBB breakthrough infection (BTI) and reinfection convalescent plasma. Importantly, L455F single substitution significantly dampens receptor binding; however, the combination of L455F and F456L forms an adjacent residue flipping, which leads to enhanced NAbs resistance and ACE2 binding affinity. The perturbed receptor-binding mode leads to the exceptional ACE2 binding and NAb evasion, as revealed by structural analyses. Our results indicate the evolution flexibility contributed by epistasis cannot be underestimated, and the evolution potential of SARS-CoV-2 RBD remains high.
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Affiliation(s)
- Fanchong Jian
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
- College of Chemistry and Molecular Engineering, Peking University, Beijing, People’s Republic of China
| | - Leilei Feng
- CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, People’s Republic of China
- University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Sijie Yang
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, People’s Republic of China
- Peking-Tsinghua Center for Life Sciences, Tsinghua University, Beijing, People’s Republic of China
| | - Yuanling Yu
- Changping Laboratory, Beijing, People’s Republic of China
| | - Lei Wang
- CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, People’s Republic of China
- University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Weiliang Song
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
- School of Life Sciences, Peking University, Beijing, People’s Republic of China
| | - Ayijiang Yisimayi
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
- School of Life Sciences, Peking University, Beijing, People’s Republic of China
| | - Xiaosu Chen
- Institute for Immunology, College of Life Sciences, Nankai University, Tianjin, People’s Republic of China
| | - Yanli Xu
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Peng Wang
- Changping Laboratory, Beijing, People’s Republic of China
| | - Lingling Yu
- Changping Laboratory, Beijing, People’s Republic of China
| | - Jing Wang
- Changping Laboratory, Beijing, People’s Republic of China
| | - Lu Liu
- Changping Laboratory, Beijing, People’s Republic of China
| | - Xiao Niu
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, People’s Republic of China
- College of Chemistry and Molecular Engineering, Peking University, Beijing, People’s Republic of China
| | - Jing Wang
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
- School of Life Sciences, Peking University, Beijing, People’s Republic of China
| | - Tianhe Xiao
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, People’s Republic of China
- Joint Graduate Program of Peking-Tsinghua-NIBS, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, People’s Republic of China
| | - Ran An
- Changping Laboratory, Beijing, People’s Republic of China
| | - Yao Wang
- Changping Laboratory, Beijing, People’s Republic of China
| | - Qingqing Gu
- Changping Laboratory, Beijing, People’s Republic of China
| | - Fei Shao
- Changping Laboratory, Beijing, People’s Republic of China
| | - Ronghua Jin
- Beijing Ditan Hospital, Capital Medical University, Beijing, People’s Republic of China
| | - Zhongyang Shen
- Organ Transplant Center, NHC Key Laboratory for Critical Care Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, People’s Republic of China
| | - Youchun Wang
- Changping Laboratory, Beijing, People’s Republic of China
- Institute of Medical Biology, Chinese Academy of Medical Science & Peking Union Medical College, Kunming, People’s Republic of China
| | - Xiangxi Wang
- CAS Key Laboratory of Infection and Immunity, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, People’s Republic of China
- University of Chinese Academy of Sciences, Beijing, People’s Republic of China
| | - Yunlong Cao
- Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, People’s Republic of China
- Changping Laboratory, Beijing, People’s Republic of China
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93
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Di Chiara C, Barbieri E, Chen YX, Visonà E, Cavagnis S, Sturniolo G, Parca A, Liberati C, Cantarutti L, Lupattelli A, Le Prevost M, Corrao G, Giaquinto C, Donà D, Cantarutti A. Comparative study showed that children faced a 78% higher risk of new-onset conditions after they had COVID-19. Acta Paediatr 2023; 112:2563-2571. [PMID: 37688774 DOI: 10.1111/apa.16966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 08/11/2023] [Accepted: 08/29/2023] [Indexed: 09/11/2023]
Abstract
AIM Children have largely been unaffected by severe COVID-19 compared to adults, but data suggest that they may have experienced new conditions after developing the disease. We compared outcomes in children who had experienced COVID-19 and healthy controls. METHODS A retrospective nested cohort study assessed the incidence rate of new-onset conditions after COVID-19 in children aged 0-14 years. Data were retrieved from an Italian paediatric primary care database linked to Veneto Region registries. Exposed children with a positive nasopharyngeal swab were matched 1:1 with unexposed children who had tested negative. Conditional Cox regression was fitted to estimate the adjusted hazard ratios (aHR) and 95% confidence intervals (CI) for the exposure and outcome associations after adjusting for covariates. RESULTS We compared 1656 exposed and 1656 unexposed children from 1 February 2020 to 30 November 2021. The overall excess risk for new-onset conditions after COVID-19 was 78% higher in the exposed than unexposed children. We found significantly higher risks for some new conditions in exposed children, including mental health issues (aHR 1.8, 95% CI 1.1-3.0) and neurological problems (aHR 2.4, 95% CI 1.4-4.1). CONCLUSION Exposed children had a 78% higher risk of developing new conditions of interest after COVID-19 than unexposed children.
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Affiliation(s)
- Costanza Di Chiara
- Division of Paediatric Infectious Diseases, Department for Women's and Children's Health, University of Padua, Padua, Italy
- Penta-Child Health Research, Padua, Italy
| | - Elisa Barbieri
- Division of Paediatric Infectious Diseases, Department for Women's and Children's Health, University of Padua, Padua, Italy
- Penta-Child Health Research, Padua, Italy
| | - Yu Xi Chen
- Department of Statistics and Quantitative Methods, Division of Biostatistics, Epidemiology and Public Health, Laboratory of Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy
| | - Elisa Visonà
- Division of Paediatric Infectious Diseases, Department for Women's and Children's Health, University of Padua, Padua, Italy
| | - Sara Cavagnis
- Division of Paediatric Infectious Diseases, Department for Women's and Children's Health, University of Padua, Padua, Italy
| | - Giulia Sturniolo
- Division of Paediatric Infectious Diseases, Department for Women's and Children's Health, University of Padua, Padua, Italy
| | - Agnese Parca
- Department of Statistics and Quantitative Methods, Division of Biostatistics, Epidemiology and Public Health, Laboratory of Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy
| | - Cecilia Liberati
- Division of Paediatric Infectious Diseases, Department for Women's and Children's Health, University of Padua, Padua, Italy
| | | | - Angela Lupattelli
- PharmacoEpidemiology and Drug Safety Research Group, Department of Pharmacy, and PharmaTox Strategic Research Initiative, University of Oslo, Oslo, Norway
| | | | - Giovanni Corrao
- Department of Statistics and Quantitative Methods, Division of Biostatistics, Epidemiology and Public Health, Laboratory of Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy
| | - Carlo Giaquinto
- Division of Paediatric Infectious Diseases, Department for Women's and Children's Health, University of Padua, Padua, Italy
- Penta-Child Health Research, Padua, Italy
- Società Servizi Telematici-Pedianet, Padua, Italy
| | - Daniele Donà
- Division of Paediatric Infectious Diseases, Department for Women's and Children's Health, University of Padua, Padua, Italy
- Penta-Child Health Research, Padua, Italy
| | - Anna Cantarutti
- Department of Statistics and Quantitative Methods, Division of Biostatistics, Epidemiology and Public Health, Laboratory of Healthcare Research and Pharmacoepidemiology, University of Milano-Bicocca, Milan, Italy
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94
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Zimmermann L, Zhao X, Makroczyova J, Wachsmuth-Melm M, Prasad V, Hensel Z, Bartenschlager R, Chlanda P. SARS-CoV-2 nsp3 and nsp4 are minimal constituents of a pore spanning replication organelle. Nat Commun 2023; 14:7894. [PMID: 38036567 PMCID: PMC10689437 DOI: 10.1038/s41467-023-43666-5] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 11/16/2023] [Indexed: 12/02/2023] Open
Abstract
Coronavirus replication is associated with the remodeling of cellular membranes, resulting in the formation of double-membrane vesicles (DMVs). A DMV-spanning pore was identified as a putative portal for viral RNA. However, the exact components and the structure of the SARS-CoV-2 DMV pore remain to be determined. Here, we investigate the structure of the DMV pore by in situ cryo-electron tomography combined with subtomogram averaging. We identify non-structural protein (nsp) 3 and 4 as minimal components required for the formation of a DMV-spanning pore, which is dependent on nsp3-4 proteolytic cleavage. In addition, we show that Mac2-Mac3-DPUP-Ubl2 domains are critical for nsp3 oligomerization and crown integrity which influences membrane curvature required for biogenesis of DMVs. Altogether, SARS-CoV-2 nsp3-4 have a dual role by driving the biogenesis of replication organelles and assembly of DMV-spanning pores which we propose here to term replicopores.
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Affiliation(s)
- Liv Zimmermann
- Schaller Research Group, Department of Infectious Diseases, Virology, Heidelberg University, 69120, Heidelberg, Germany
| | - Xiaohan Zhao
- Schaller Research Group, Department of Infectious Diseases, Virology, Heidelberg University, 69120, Heidelberg, Germany
| | - Jana Makroczyova
- Schaller Research Group, Department of Infectious Diseases, Virology, Heidelberg University, 69120, Heidelberg, Germany
| | - Moritz Wachsmuth-Melm
- Schaller Research Group, Department of Infectious Diseases, Virology, Heidelberg University, 69120, Heidelberg, Germany
| | - Vibhu Prasad
- Department of Infectious Diseases, Molecular Virology, Heidelberg University, 69120, Heidelberg, Germany
| | - Zach Hensel
- ITQB NOVA, Universidade NOVA de Lisboa, 2780-157, Oeiras, Portugal
| | - Ralf Bartenschlager
- Department of Infectious Diseases, Molecular Virology, Heidelberg University, 69120, Heidelberg, Germany
- Division Virus-Associated Carcinogenesis, German Cancer Research Center (DKFZ), 69120, Heidelberg, Germany
- German Center for Infection Research (DZIF), Heidelberg partner site, 69120, Heidelberg, Germany
| | - Petr Chlanda
- Schaller Research Group, Department of Infectious Diseases, Virology, Heidelberg University, 69120, Heidelberg, Germany.
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95
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Focosi D, McConnell S, Sullivan DJ, Casadevall A. Analysis of SARS-CoV-2 mutations associated with resistance to therapeutic monoclonal antibodies that emerge after treatment. Drug Resist Updat 2023; 71:100991. [PMID: 37572569 DOI: 10.1016/j.drup.2023.100991] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 07/18/2023] [Accepted: 07/30/2023] [Indexed: 08/14/2023]
Abstract
The mutation rate of the Omicron sublineage has led to baseline resistance against all previously authorized anti-Spike monoclonal antibodies (mAbs). Nevertheless, in case more antiviral mAbs will be authorized in the future, it is relevant to understand how frequently treatment-emergent resistance has emerged so far, under different combinations and in different patient subgroups. We report the results of a systematic review of the medical literature for case reports and case series for treatment-emergent immune escape, which is defined as emergence of a resistance-driving mutation in at least 20% of sequences in a given host at a given timepoint. We identified 32 publications detailing 216 cases that included different variants of concern (VOC) and found that the incidence of treatment emergent-resistance ranged from 10% to 50%. Most of the treatment-emergent resistance events occurred in immunocompromised patients. Interestingly, resistance also emerged against cocktails of two mAbs, albeit at lower frequencies. The heterogenous therapeutic management of those cases doesn't allow inferences about the clinical outcome in patients with treatment-emergent resistance. Furthermore, we noted a temporal correlation between the introduction of mAb therapies and a subsequent increase in SARS-CoV-2 sequences across the globe carrying mutations conferring resistance to that mAb, raising concern as to whether these had originated in mAb-treated individuals. Our findings confirm that treatment-emergent immune escape to anti-Spike mAbs represents a frequent and concerning phenomenon and suggests that these are associated with mAb use in immunosuppressed hosts.
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Affiliation(s)
- Daniele Focosi
- North-Western Tuscany Blood Bank, Pisa University Hospital, Italy.
| | - Scott McConnell
- Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - David J Sullivan
- Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Arturo Casadevall
- Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
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96
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Calderón-Osorno M, Cordero-Laurent E, Duarte-Martínez F. CoVEx: SARS-CoV-2 Mutation Explorer for genomic surveillance. INFECTION, GENETICS AND EVOLUTION : JOURNAL OF MOLECULAR EPIDEMIOLOGY AND EVOLUTIONARY GENETICS IN INFECTIOUS DISEASES 2023; 116:105521. [PMID: 39492419 DOI: 10.1016/j.meegid.2023.105521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 10/21/2023] [Accepted: 10/26/2023] [Indexed: 11/05/2024]
Abstract
Effective management of emerging diseases relies on timely pathogen identification and monitoring. The emergence of COVID-19 in December 2019, rapidly evolved into a global pandemic, with millions of cases and deaths reported worldwide. The accumulation of SARS-CoV-2 genomes provided unprecedented opportunities for studying the virus's evolutionary dynamics, understanding the impact of mutations, and identifying emerging Variants of Interest (VOIs) and Variants of Concern (VOCs). During the COVID-19 pandemic, health systems faced challenges in promptly detecting such variants and timely notifying. To facilitate the continuous monitoring of mutations, various initiatives and open-source pipelines have been established. However, these platforms often lack integration for conducting user sequence analysis and comparing it with publicly reported data on platforms like GISAID. Here, we present CoVEx, an easy-to-use tool for analyzing and visualizing SARS-CoV-2 variant sequences obtained using Illumina sequencing technology. CoVEx integrates quality control, alignment, genome annotation, lineage designation, and mutation analysis tools. Implemented in Python, CoVEx also has a mutation explorer feature that generates interactive graphs summarising identified mutations in an intuitive manner. Similarly, it leverages the Outbreak.info package to create heatmaps highlighting the mutations associated with designated Pangolin lineages. Furthermore, by comparing mutation profiles against GISAID data, CoVEx offers valuable insights into the prevalence and distribution of mutations worldwide. We validated CoVEx using raw sequence data (n = 108) and demonstrated its accuracy in assembling sequences and predicting Pangolin and Nextclade Pango lineages. Notably, the tool revealed the emergence of a previously unreported mutation, ORF1a:I2501T, within the Costa Rica GN.1 lineage. This finding highlights CoVEx's capability to identify novel mutations in the different lineages, providing valuable information to researchers and public health decision makers. CoVEx and documentation are freely available on GitLab: https://gitlab.com/CNCA_CeNAT/covex.
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Affiliation(s)
| | - Estela Cordero-Laurent
- Costa Rican Institute for Research and Education in Nutrition and Health (INCIENSA), Tres Rios, 30301 Cartago, Costa Rica
| | - Francisco Duarte-Martínez
- Costa Rican Institute for Research and Education in Nutrition and Health (INCIENSA), Tres Rios, 30301 Cartago, Costa Rica
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97
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Singh J, Vashishtha S, Kundu B. Spike Protein Mutation-Induced Changes in the Kinetic and Thermodynamic Behavior of Its Receptor Binding Domains Explain Their Higher Propensity to Attain Open States in SARS-CoV-2 Variants of Concern. ACS CENTRAL SCIENCE 2023; 9:1894-1904. [PMID: 37901170 PMCID: PMC10604015 DOI: 10.1021/acscentsci.3c00810] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Indexed: 10/31/2023]
Abstract
Spike (S) protein opening in SARS-CoV-2 controls the accessibility of its receptor binding domains (RBDs) to host receptors and immune recognition. Along the evolution of SARS-CoV-2 to its variants of concern (VOC)-alpha, beta, gamma, delta, and omicron-their S proteins showed a higher propensity to attain open states. Deciphering how mutations in S protein can shape its conformational dynamics will contribute to the understanding of viral host tropism. Here using microsecond-scale multiple molecular dynamics simulations (MDS), we provide insights into the kinetic and thermodynamic contributions of these mutations to RBD opening pathways in S proteins of SARS-CoV-2 VOCs. Mutational effects were analyzed using atomistic (i) equilibrium MDS of closed and open states of S proteins and (ii) nonequilibrium MDS for closed-to-open transitions. In MDS of closed or open states, RBDs in S proteins of VOCs showed lower thermodynamic stability with higher kinetic fluctuations, compared to S proteins of ancestral SARS-CoV-2. For closed-to-open transitions in S proteins of VOCs, we observed apparently faster RBD opening with a 1.5-2-fold decrease in the thermodynamic free-energy barrier (ΔGclosed→open). Saturation mutagenesis studies highlighted S protein mutations that may control its conformational dynamics and presentation to host receptors.
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Affiliation(s)
- Jasdeep Singh
- Department
of Chemistry and Biochemistry, University
of Denver, Denver, Colorado 80208, United States
| | - Shubham Vashishtha
- Kusuma
School of Biological Sciences, Indian Institute
of Technology-Delhi, New Delhi 110016, India
| | - Bishwajit Kundu
- Kusuma
School of Biological Sciences, Indian Institute
of Technology-Delhi, New Delhi 110016, India
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98
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Colson P, Delerce J, Fantini J, Pontarotti P, La Scola B, Raoult D. The return of the "Mistigri" (virus adaptative gain by gene loss) through the SARS-CoV-2 XBB.1.5 chimera that predominated in 2023. J Med Virol 2023; 95:e29146. [PMID: 37800455 DOI: 10.1002/jmv.29146] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/03/2023] [Accepted: 09/19/2023] [Indexed: 10/07/2023]
Abstract
Severe acute respiratory syndrome coronavirus 2 XBB.1.5 is the first recombinant lineage to predominate at the country and global scales. Very interestingly, like the Marseille-4B subvariant (or B.1.160) and the pandemic variant B.1.1.7 (or Alpha) previously, it has its ORF8 gene inactivated by a stop codon. We aimed here to study the distribution of stop codons in ORF8 of XBB.1.5 and non-XBB.1.5 genomes. We identified that a stop codon was present at 89 (74%) ORF8 codons in ≥1 of 15 222 404 genomes available in GISAID. The mean proportion of genomes with a stop codon per codon was 0.11% (range, 0%-7.8%). In addition, a stop codon was detected at 15 (12%) codons in at least 1000 genomes. These 15 codons are notably located on seven stem-loop hairpin regions and in the signal peptide region for the case of the XBB.1.5 lineage (codon 8). Thus, it is very likely that stop codons in ORF8 gene contributed on at least three occasions and independently during the pandemic to the evolutionary success of a lineage that became transiently predominant. Such association of gene loss with evolutionary success, which suits the recently described Mistigri rule, is an important biological phenomenon very unknown in virology while largely described in cellular organisms.
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Affiliation(s)
- Philippe Colson
- IHU Méditerranée Infection, Marseille, France
- Aix-Marseille Université, Institut de Recherche pour le Développement (IRD), Microbes Evolution Phylogeny and Infections (MEPHI), Marseille, France
- Assistance Publique-Hôpitaux de Marseille (AP-HM), Marseille, France
| | | | - Jacques Fantini
- INSERM UMR_S 1072, Aix-Marseille Université, Marseille, France
| | - Pierre Pontarotti
- IHU Méditerranée Infection, Marseille, France
- Aix-Marseille Université, Institut de Recherche pour le Développement (IRD), Microbes Evolution Phylogeny and Infections (MEPHI), Marseille, France
- Department of Biological Sciences, Centre National de la Recherche Scientifique (CNRS)-SNC5039, Marseille, France
| | - Bernard La Scola
- IHU Méditerranée Infection, Marseille, France
- Aix-Marseille Université, Institut de Recherche pour le Développement (IRD), Microbes Evolution Phylogeny and Infections (MEPHI), Marseille, France
- Assistance Publique-Hôpitaux de Marseille (AP-HM), Marseille, France
| | - Didier Raoult
- IHU Méditerranée Infection, Marseille, France
- Aix-Marseille Université, Institut de Recherche pour le Développement (IRD), Microbes Evolution Phylogeny and Infections (MEPHI), Marseille, France
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99
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Zhang L, Kempf A, Nehlmeier I, Cossmann A, Dopfer-Jablonka A, Stankov MV, Schulz SR, Jäck HM, Behrens GMN, Pöhlmann S, Hoffmann M. Neutralisation sensitivity of SARS-CoV-2 lineages EG.5.1 and XBB.2.3. THE LANCET. INFECTIOUS DISEASES 2023; 23:e391-e392. [PMID: 37716358 DOI: 10.1016/s1473-3099(23)00547-9] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Revised: 08/19/2023] [Accepted: 08/21/2023] [Indexed: 09/18/2023]
Affiliation(s)
- Lu Zhang
- Infection Biology Unit, German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, Georg-August-University Göttingen, Göttingen, Germany
| | - Amy Kempf
- Infection Biology Unit, German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, Georg-August-University Göttingen, Göttingen, Germany
| | - Inga Nehlmeier
- Infection Biology Unit, German Primate Center, 37077 Göttingen, Germany
| | - Anne Cossmann
- Department of Rheumatology and Immunology, Hannover Medical School, Hannover, Germany
| | - Alexandra Dopfer-Jablonka
- Department of Rheumatology and Immunology, Hannover Medical School, Hannover, Germany; German Centre for Infection Research, partner site Hannover-Braunschweig, Hannover, Germany
| | - Metodi V Stankov
- Department of Rheumatology and Immunology, Hannover Medical School, Hannover, Germany
| | - Sebastian R Schulz
- Division of Molecular Immunology, Department of Internal Medicine 3, Friedrich-Alexander University of Erlangen-Nürnberg, Erlangen, Germany
| | - Hans-Martin Jäck
- Division of Molecular Immunology, Department of Internal Medicine 3, Friedrich-Alexander University of Erlangen-Nürnberg, Erlangen, Germany
| | - Georg M N Behrens
- Department of Rheumatology and Immunology, Hannover Medical School, Hannover, Germany; German Centre for Infection Research, partner site Hannover-Braunschweig, Hannover, Germany
| | - Stefan Pöhlmann
- Infection Biology Unit, German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, Georg-August-University Göttingen, Göttingen, Germany
| | - Markus Hoffmann
- Infection Biology Unit, German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, Georg-August-University Göttingen, Göttingen, Germany.
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100
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Li C, Ma L, Zou D, Zhang R, Bai X, Li L, Wu G, Huang T, Zhao W, Jin E, Bao Y, Song S. RCoV19: A One-stop Hub for SARS-CoV-2 Genome Data Integration, Variant Monitoring, and Risk Pre-warning. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:1066-1079. [PMID: 37898309 PMCID: PMC10928372 DOI: 10.1016/j.gpb.2023.10.004] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 10/17/2023] [Accepted: 10/19/2023] [Indexed: 10/30/2023]
Abstract
The Resource for Coronavirus 2019 (RCoV19) is an open-access information resource dedicated to providing valuable data on the genomes, mutations, and variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this updated implementation of RCoV19, we have made significant improvements and advancements over the previous version. Firstly, we have implemented a highly refined genome data curation model. This model now features an automated integration pipeline and optimized curation rules, enabling efficient daily updates of data in RCoV19. Secondly, we have developed a global and regional lineage evolution monitoring platform, alongside an outbreak risk pre-warning system. These additions provide a comprehensive understanding of SARS-CoV-2 evolution and transmission patterns, enabling better preparedness and response strategies. Thirdly, we have developed a powerful interactive mutation spectrum comparison module. This module allows users to compare and analyze mutation patterns, assisting in the detection of potential new lineages. Furthermore, we have incorporated a comprehensive knowledgebase on mutation effects. This knowledgebase serves as a valuable resource for retrieving information on the functional implications of specific mutations. In summary, RCoV19 serves as a vital scientific resource, providing access to valuable data, relevant information, and technical support in the global fight against COVID-19. The complete contents of RCoV19 are available to the public at https://ngdc.cncb.ac.cn/ncov/.
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Affiliation(s)
- Cuiping Li
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Lina Ma
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Dong Zou
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Rongqin Zhang
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xue Bai
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Lun Li
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Gangao Wu
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Tianhao Huang
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Zhao
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Enhui Jin
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yiming Bao
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Shuhui Song
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of Chinese Academy of Sciences, Beijing 100049, China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, China.
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