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Minami S, Kotaki T, Sakai Y, Okamura S, Torii S, Ono C, Motooka D, Hamajima R, Nouda R, Nurdin JA, Yamasaki M, Kanai Y, Ebina H, Maeda Y, Okamoto T, Tachibana T, Matsuura Y, Kobayashi T. Vero cell-adapted SARS-CoV-2 strain shows increased viral growth through furin-mediated efficient spike cleavage. Microbiol Spectr 2024; 12:e0285923. [PMID: 38415690 PMCID: PMC10986611 DOI: 10.1128/spectrum.02859-23] [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: 07/13/2023] [Accepted: 02/01/2024] [Indexed: 02/29/2024] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) utilizes several host proteases to cleave the spike (S) protein to enter host cells. SARS-CoV-2 S protein is cleaved into S1 and S2 subunits by furin, which is closely involved in the pathogenicity of SARS-CoV-2. However, the effects of the modulated protease cleavage activity due to S protein mutations on viral replication and pathogenesis remain unclear. Herein, we serially passaged two SARS-CoV-2 strains in Vero cells and characterized the cell-adapted SARS-CoV-2 strains in vitro and in vivo. The adapted strains showed high viral growth, effective S1/S2 cleavage of the S protein, and low pathogenicity compared with the wild-type strain. Furthermore, the viral growth and S1/S2 cleavage were enhanced by the combination of the Δ68-76 and H655Y mutations using recombinant SARS-CoV-2 strains generated by the circular polymerase extension reaction. The recombinant SARS-CoV-2 strain, which contained the mutation of the adapted strain, showed increased susceptibility to the furin inhibitor, suggesting that the adapted SARS-CoV-2 strain utilized furin more effectively than the wild-type strain. Pathogenicity was attenuated by infection with effectively cleaved recombinant SARS-CoV-2 strains, suggesting that the excessive cleavage of the S proteins decreases virulence. Finally, the high-growth-adapted SARS-CoV-2 strain could be used as the seed for a low-cost inactivated vaccine; immunization with this vaccine can effectively protect the host from SARS-CoV-2 variants. Our findings provide novel insights into the growth and pathogenicity of SARS-CoV-2 in the evolution of cell-cell transmission. IMPORTANCE The efficacy of the S protein cleavage generally differs among the SARS-CoV-2 variants, resulting in distinct viral characteristics. The relationship between a mutation and the entry of SARS-CoV-2 into host cells remains unclear. In this study, we analyzed the sequence of high-growth Vero cell-adapted SARS-CoV-2 and factors determining the enhancement of the growth of the adapted virus and confirmed the characteristics of the adapted strain by analyzing the recombinant SARS-CoV-2 strain. We successfully identified mutations Δ68-76 and H655Y, which enhance viral growth and the S protein cleavage by furin. Using recombinant viruses enabled us to conduct a virus challenge experiment in vivo. The pathogenicity of SARS-CoV-2 introduced with the mutations Δ68-76, H655Y, P812L, and Q853L was attenuated in hamsters, indicating the possibility of the attenuation of excessive cleaved SARS-CoV-2. These findings provide novel insights into the infectivity and pathogenesis of SARS-CoV-2 strains, thereby significantly contributing to the field of virology.
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Affiliation(s)
- Shohei Minami
- Department of Virology, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Tomohiro Kotaki
- Department of Virology, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Yusuke Sakai
- Department of Pathology, National Institute of Infectious Diseases, Tokyo, Japan
| | - Shinya Okamura
- Virus Vaccine Group, BIKEN Innovative Vaccine Research Alliance Laboratories, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Osaka, Japan
- The Research Foundation for Microbial Diseases of Osaka University, Suita, Osaka, Japan
| | - Shiho Torii
- Laboratory of Virus Control, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Chikako Ono
- Laboratory of Virus Control, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
- Center for Infectious Disease Education and Research, Osaka University, Osaka, Japan
| | - Daisuke Motooka
- Department of Infection Metagenomics, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Rina Hamajima
- Department of Virology, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Ryotaro Nouda
- Department of Virology, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Jeffery A. Nurdin
- Department of Virology, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Moeko Yamasaki
- Department of Virology, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Yuta Kanai
- Department of Virology, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
| | - Hirotaka Ebina
- Virus Vaccine Group, BIKEN Innovative Vaccine Research Alliance Laboratories, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Osaka, Japan
- The Research Foundation for Microbial Diseases of Osaka University, Suita, Osaka, Japan
- Center for Infectious Disease Education and Research, Osaka University, Osaka, Japan
- Center for Advanced Modalities and DDS, Osaka University, Osaka, Japan
| | - Yusuke Maeda
- Laboratory of Viral Dynamism Research, Research Institute for Microbial Diseases Osaka University, Osaka, Japan
| | - Toru Okamoto
- Institute for Advanced Co-creation Studies, Research Institute for Microbial Diseases Osaka University, Osaka, Japan
| | - Taro Tachibana
- Cell Engineering Corporation, Osaka, Japan
- Department of Bioengineering, Graduate School of Engineering, Osaka Metropolitan University, Osaka, Japan
| | - Yoshiharu Matsuura
- Laboratory of Virus Control, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
- Center for Infectious Disease Education and Research, Osaka University, Osaka, Japan
- Center for Advanced Modalities and DDS, Osaka University, Osaka, Japan
| | - Takeshi Kobayashi
- Department of Virology, Research Institute for Microbial Diseases, Osaka University, Osaka, Japan
- Center for Infectious Disease Education and Research, Osaka University, Osaka, Japan
- Center for Advanced Modalities and DDS, Osaka University, Osaka, Japan
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2
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Barroso-Arévalo S, Díaz-Frutos M, Domínguez L, Sánchez-Vizcaíno JM. Importance of genomic surveillance of SARS-CoV-2 in cats during reverse zoonosis events: potential viral evolution may occur. Microbiol Spectr 2023; 11:e0068023. [PMID: 37565759 PMCID: PMC10581217 DOI: 10.1128/spectrum.00680-23] [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: 02/16/2023] [Accepted: 06/29/2023] [Indexed: 08/12/2023] Open
Abstract
The apparition of new variants of severe acute respiratory syndrome coronavirus 2 and lineages is constantly happening because of the high viral mutation rate. Since numerous reverse zoonosis events have been reported so far, genomic surveillance should be conducted in susceptible species to evaluate potential adaptations that may trigger the apparition of new variants. Here, we evaluate the evolution of the infection in a cat naturally infected in parallel with its owner, performing a comparative phylogenetic analysis. Sequencing analysis showed that both were infected with the Omicron BA.5/BF.1 lineage and revealed the presence of nucleotide substitution in the viral genome recovered from the cat with respect to the viral genome from the human sample. This nucleotide substitution (C11897A) produced the amino acid change Orf1a: Q3878K. Therefore, genomic surveillance in the case of reverse zoonosis events is still necessary in order to control possible adaptations of the virus to other susceptible species. IMPORTANCE Genomic surveillance of pets for severe acute respiratory syndrome coronavirus 2 is important to monitor the emergence of new variants of the virus associated with these animals. Pets can serve as a potential reservoir for the virus, and their close contact with humans increases the risk of transmission. By conducting genomic surveillance in pets, it is possible to detect and track new variants early on, allowing for more effective control measures to be put in place. This can help prevent the spread of these variants to human populations and potentially mitigate the impact of the pandemic. Furthermore, it may also provide insight into the evolution and spread of the virus within the animal population.
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Affiliation(s)
- Sandra Barroso-Arévalo
- VISAVET Health Surveillance Center, Complutense University of Madrid, Madrid, Spain
- Department of Animal Health, Faculty of Veterinary, Complutense University of Madrid, Madrid, Spain
| | - Marta Díaz-Frutos
- VISAVET Health Surveillance Center, Complutense University of Madrid, Madrid, Spain
- Department of Animal Health, Faculty of Veterinary, Complutense University of Madrid, Madrid, Spain
| | - Lucas Domínguez
- VISAVET Health Surveillance Center, Complutense University of Madrid, Madrid, Spain
- Department of Animal Health, Faculty of Veterinary, Complutense University of Madrid, Madrid, Spain
| | - José M. Sánchez-Vizcaíno
- VISAVET Health Surveillance Center, Complutense University of Madrid, Madrid, Spain
- Department of Animal Health, Faculty of Veterinary, Complutense University of Madrid, Madrid, Spain
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3
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Nagy A, Stará M, Vodička R, Černíková L, Jiřincová H, Křivda V, Sedlák K. Reverse-zoonotic transmission of SARS-CoV-2 lineage alpha (B.1.1.7) to great apes and exotic felids in a zoo in the Czech Republic. Arch Virol 2022; 167:1681-1685. [PMID: 35616738 PMCID: PMC9133317 DOI: 10.1007/s00705-022-05469-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 02/28/2022] [Indexed: 11/26/2022]
Abstract
We report an outbreak of SARS-CoV-2 lineage alpha in gorillas and felid species in a zoo in Prague, Czech Republic. The course of illness and clinical signs are described, as are the results of characterization of these particular SARS-CoV-2 variants by next-generation sequencing and phylogenetic analysis. The putative transmission routes are also discussed.
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Affiliation(s)
- Alexander Nagy
- State Veterinary Institute Prague, Prague, Czech Republic
- National Institute of Public Health, Prague, Czech Republic
| | - Martina Stará
- State Veterinary Institute Prague, Prague, Czech Republic
| | | | - Lenka Černíková
- State Veterinary Institute Prague, Prague, Czech Republic.
- State Veterinary Institute Prague, Sídlištní 136/24, 165 03, Prague 6, Czech Republic.
| | | | | | - Kamil Sedlák
- State Veterinary Institute Prague, Prague, Czech Republic
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4
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Lythgoe KA, Hall M, Ferretti L, de Cesare M, MacIntyre-Cockett G, Trebes A, Andersson M, Otecko N, Wise EL, Moore N, Lynch J, Kidd S, Cortes N, Mori M, Williams R, Vernet G, Justice A, Green A, Nicholls SM, Ansari MA, Abeler-Dörner L, Moore CE, Peto TEA, Eyre DW, Shaw R, Simmonds P, Buck D, Todd JA, Connor TR, Ashraf S, da Silva Filipe A, Shepherd J, Thomson EC, Bonsall D, Fraser C, Golubchik T. SARS-CoV-2 within-host diversity and transmission. Science 2021; 372:eabg0821. [PMID: 33688063 PMCID: PMC8128293 DOI: 10.1126/science.abg0821] [Citation(s) in RCA: 243] [Impact Index Per Article: 60.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 03/03/2021] [Indexed: 12/14/2022]
Abstract
Extensive global sampling and sequencing of the pandemic virus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have enabled researchers to monitor its spread and to identify concerning new variants. Two important determinants of variant spread are how frequently they arise within individuals and how likely they are to be transmitted. To characterize within-host diversity and transmission, we deep-sequenced 1313 clinical samples from the United Kingdom. SARS-CoV-2 infections are characterized by low levels of within-host diversity when viral loads are high and by a narrow bottleneck at transmission. Most variants are either lost or occasionally fixed at the point of transmission, with minimal persistence of shared diversity, patterns that are readily observable on the phylogenetic tree. Our results suggest that transmission-enhancing and/or immune-escape SARS-CoV-2 variants are likely to arise infrequently but could spread rapidly if successfully transmitted.
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Affiliation(s)
- Katrina A Lythgoe
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
- Department of Zoology, University of Oxford, Oxford OX1 3SZ, UK
| | - Matthew Hall
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
| | - Luca Ferretti
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK
| | - Mariateresa de Cesare
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
| | - George MacIntyre-Cockett
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
| | - Amy Trebes
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
| | - Monique Andersson
- Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
- Division of Medical Virology, Stellenbosch University, Stellenbosch, South Africa
| | - Newton Otecko
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK
| | - Emma L Wise
- Hampshire Hospitals NHS Foundation Trust, Basingstoke and North Hampshire Hospital, Basingstoke RG24 9NA, UK
- School of Biosciences and Medicine, University of Surrey, Guildford GU2 7XH, UK
| | - Nathan Moore
- Hampshire Hospitals NHS Foundation Trust, Basingstoke and North Hampshire Hospital, Basingstoke RG24 9NA, UK
| | - Jessica Lynch
- Hampshire Hospitals NHS Foundation Trust, Basingstoke and North Hampshire Hospital, Basingstoke RG24 9NA, UK
| | - Stephen Kidd
- Hampshire Hospitals NHS Foundation Trust, Basingstoke and North Hampshire Hospital, Basingstoke RG24 9NA, UK
| | - Nicholas Cortes
- Hampshire Hospitals NHS Foundation Trust, Basingstoke and North Hampshire Hospital, Basingstoke RG24 9NA, UK
- Gibraltar Health Authority, Gibraltar, UK
| | - Matilde Mori
- School of Medicine, University of Southampton, Southampton SO17 1BJ, UK
| | - Rebecca Williams
- Hampshire Hospitals NHS Foundation Trust, Basingstoke and North Hampshire Hospital, Basingstoke RG24 9NA, UK
| | - Gabrielle Vernet
- Hampshire Hospitals NHS Foundation Trust, Basingstoke and North Hampshire Hospital, Basingstoke RG24 9NA, UK
| | - Anita Justice
- Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
| | - Angie Green
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
| | - Samuel M Nicholls
- Institute of Microbiology and Infection, University of Birmingham, Birmingham B15 2TT, UK
| | - M Azim Ansari
- Peter Medawar Building for Pathogen Research, University of Oxford, Oxford OX1 3SY, UK
| | - Lucie Abeler-Dörner
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK
| | - Catrin E Moore
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK
| | - Timothy E A Peto
- Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
- Nuffield Department of Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
| | - David W Eyre
- Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
- Big Data Institute, Nuffield Department of Public Health, University of Oxford, Old Road Campus, Oxford OX3 7FL, UK
| | - Robert Shaw
- Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
| | - Peter Simmonds
- Peter Medawar Building for Pathogen Research, University of Oxford, Oxford OX1 3SY, UK
| | - David Buck
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
| | - John A Todd
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
| | - Thomas R Connor
- Pathogen Genomics Unit, Public Health Wales Microbiology, Cardiff CF10 4BZ, UK
- Cardiff University School of Biosciences, Cardiff University, Cardiff CF10 3AX, UK
| | - Shirin Ashraf
- MRC-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, UK
| | | | - James Shepherd
- MRC-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, UK
| | - Emma C Thomson
- MRC-University of Glasgow Centre for Virus Research, Glasgow G61 1QH, UK
| | - David Bonsall
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
- Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford OX3 9DU, UK
| | - Christophe Fraser
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Old Road Campus, Oxford OX3 7BN, UK
- Wellcome Sanger Institute, Cambridge CB10 1SA, UK
| | - Tanya Golubchik
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford OX3 7LF, UK.
- Department of Zoology, University of Oxford, Oxford OX1 3SZ, UK
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5
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Bashor L, Gagne RB, Bosco-Lauth A, Bowen R, Stenglein M, VandeWoude S. SARS-CoV-2 evolution in animals suggests mechanisms for rapid variant selection. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.03.05.434135. [PMID: 33758844 PMCID: PMC7987003 DOI: 10.1101/2021.03.05.434135] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
SARS-CoV-2 spillback from humans into domestic and wild animals has been well-documented. We compared variants of cell culture-expanded SARS-CoV-2 inoculum and virus recovered from four species following experimental exposure. Five nonsynonymous changes in nsp12, S, N and M genes were near fixation in the inoculum, but reverted to wild-type sequences in RNA recovered from dogs, cats and hamsters within 1-3 days post-exposure. Fourteen emergent variants were detected in viruses recovered from animals, including substitutions at spike positions H69, N501, and D614, which also vary in human lineages of concern. The rapidity of in vitro and in vivo SARS-CoV-2 selection reveals residues with functional significance during host-switching, illustrating the potential for spillback reservoir hosts to accelerate evolution, and demonstrating plasticity of viral adaptation in animal models. ONE-SENTENCE SUMMARY SARS-CoV-2 variants rapidly arise in non-human hosts, revealing viral evolution and potential risk for human reinfection.
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Affiliation(s)
- Laura Bashor
- Department of Microbiology, Immunology, and Pathology, Colorado State University; Fort Collins, CO, 80523, USA
| | - Roderick B. Gagne
- Department of Pathobiology, Wildlife Futures Program, University of Pennsylvania School of Veterinary Medicine; Kennett Square, PA, 19348, USA
| | - Angela Bosco-Lauth
- Department of Biomedical Sciences, Colorado State University; Fort Collins, CO, 80523, USA
| | - Richard Bowen
- Department of Biomedical Sciences, Colorado State University; Fort Collins, CO, 80523, USA
| | - Mark Stenglein
- Department of Microbiology, Immunology, and Pathology, Colorado State University; Fort Collins, CO, 80523, USA
| | - Sue VandeWoude
- Department of Microbiology, Immunology, and Pathology, Colorado State University; Fort Collins, CO, 80523, USA
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6
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Moreno GK, Braun KM, Pray IW, Segaloff HE, Lim A, Poulson K, Meiman J, Borcher J, Westergaard RP, Moll MK, Friedrich TC, O'Connor DH. SARS-CoV-2 transmission in intercollegiate athletics not fully mitigated with daily antigen testing. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021. [PMID: 33688665 PMCID: PMC7941640 DOI: 10.1101/2021.03.03.21252838] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Background High frequency, rapid turnaround SARS-CoV-2 testing continues to be proposed as a way of efficiently identifying and mitigating transmission in congregate settings. However, two SARS-CoV-2 outbreaks occurred among intercollegiate university athletic programs during the fall 2020 semester despite mandatory directly observed daily antigen testing. Methods During the fall 2020 semester, athletes and staff in both programs were tested daily using Quidel's Sofia SARS Antigen Fluorescent Immunoassay (FIA), with positive antigen results requiring confirmatory testing with real-time reverse transcription polymerase chain reaction (RT-PCR). We used genomic sequencing to investigate transmission dynamics in these two outbreaks. Results In Outbreak 1, 32 confirmed cases occurred within a university athletics program after the index patient attended a meeting while infectious despite a negative antigen test on the day of the meeting. Among isolates sequenced from Outbreak 1, 24 (92%) of 26 were closely related, suggesting sustained transmission following an initial introduction event. In Outbreak 2, 12 confirmed cases occurred among athletes from two university programs that faced each other in an athletic competition despite receiving negative antigen test results on the day of the competition. Sequences from both teams were closely related and unique from strains circulating in the community, suggesting transmission during intercollegiate competition. Conclusions These findings suggest that antigen testing alone, even when mandated and directly observed, may not be sufficient as an intervention to prevent SARS-CoV-2 outbreaks in congregate settings, and highlights the importance of supplementing serial antigen testing with appropriate mitigation strategies to prevent SARS-CoV-2 outbreak in congregate settings. Summary High frequency, rapid turnaround SARS-CoV-2 testing continues to be proposed as a way of efficiently identifying and mitigating transmission in congregate settings. However, here we describe two SARS-CoV-2 outbreaks occurred among intercollegiate university athletic programs during the fall 2020 semester.
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Affiliation(s)
- Gage K Moreno
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison USA 53711
| | - Katarina M Braun
- Department of Pathobiological Sciences, University of Wisconsin-Madison USA 53711
| | - Ian W Pray
- Wisconsin Department of Health Services, USA 53703.,Epidemic Intelligence Service, Centers for Disease Control and Prevention USA 30333
| | - Hannah E Segaloff
- Wisconsin Department of Health Services, USA 53703.,Epidemic Intelligence Service, Centers for Disease Control and Prevention USA 30333
| | - Ailam Lim
- Wisconsin Veterinary Diagnostic Laboratory, University of Wisconsin-Madison USA 53711
| | - Keith Poulson
- Wisconsin Veterinary Diagnostic Laboratory, University of Wisconsin-Madison USA 53711
| | | | - James Borcher
- Department of Family Medicine, Division of Sports Medicine, Ohio State University USA 43210
| | - Ryan P Westergaard
- Wisconsin Department of Health Services, USA 53703.,Department of Medicine, University of Wisconsin-Madison, USA 53711
| | - Michael K Moll
- Athletic Department, University of Wisconsin-Madison USA 53711
| | - Thomas C Friedrich
- Department of Pathobiological Sciences, University of Wisconsin-Madison USA 53711
| | - David H O'Connor
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison USA 53711
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7
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Martin MA, Koelle K. Reanalysis of deep-sequencing data from Austria points towards a small SARS-COV-2 transmission bottleneck on the order of one to three virions.. [PMID: 0 DOI: 10.1101/2021.02.22.432096] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
An early analysis of SARS-CoV-2 deep-sequencing data that combined epidemiological and genetic data to characterize the transmission dynamics of the virus in and beyond Austria concluded that the size of the virus’s transmission bottleneck was large – on the order of 1000 virions. We performed new computational analyses using these deep-sequenced samples from Austria. Our analyses included characterization of transmission bottleneck sizes across a range of variant calling thresholds and examination of patterns of shared low-frequency variants between transmission pairs in cases where de novo genetic variation was present in the recipient. From these analyses, among others, we found that SARS-CoV-2 transmission bottlenecks are instead likely to be very tight, on the order of 1-3 virions. These findings have important consequences for understanding how SARS-CoV-2 evolves between hosts and the processes shaping genetic variation observed at the population level.
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8
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Wang D, Wang Y, Sun W, Zhang L, Ji J, Zhang Z, Cheng X, Li Y, Xiao F, Zhu A, Zhong B, Ruan S, Li J, Ren P, Ou Z, Xiao M, Li M, Deng Z, Zhong H, Li F, Wang WJ, Zhang Y, Chen W, Zhu S, Xu X, Jin X, Zhao J, Zhong N, Zhang W, Zhao J, Li J, Xu Y. Population Bottlenecks and Intra-host Evolution During Human-to-Human Transmission of SARS-CoV-2. Front Med (Lausanne) 2021; 8:585358. [PMID: 33659260 PMCID: PMC7917136 DOI: 10.3389/fmed.2021.585358] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 01/11/2021] [Indexed: 01/19/2023] Open
Abstract
The emergence of the novel human coronavirus, SARS-CoV-2, causes a global COVID-19 (coronavirus disease 2019) pandemic. Here, we have characterized and compared viral populations of SARS-CoV-2 among COVID-19 patients within and across households. Our work showed an active viral replication activity in the human respiratory tract and the co-existence of genetically distinct viruses within the same host. The inter-host comparison among viral populations further revealed a narrow transmission bottleneck between patients from the same households, suggesting a dominated role of stochastic dynamics in both inter-host and intra-host evolutions.
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Affiliation(s)
- Daxi Wang
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 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, China
| | - Wanying Sun
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China
| | - Lu 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
- Institute of Infectious Disease, Guangzhou Eighth People's Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jingkai Ji
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, 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
| | - Xinyi Cheng
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Yimin Li
- 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
| | - Fei Xiao
- Guangdong Provincial Key Laboratory of Biomedical Imaging, Department of Infectious Diseases, Guangdong Provincial Engineering Research Center of Molecular Imaging, The Fifth Affiliated Hospital, Sun Yat-sen University, Zhuhai, China
| | - Airu Zhu
- 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
| | - Bei Zhong
- The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, China
| | | | - Jiandong Li
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China
| | - Peidi Ren
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
| | - Zhihua Ou
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
| | - Minfeng Xiao
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
| | - Min Li
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China
| | - Ziqing Deng
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
| | - Huanzi Zhong
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
- Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Fuqiang Li
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
- Guangdong Provincial Key Laboratory of Human Disease Genomics, Shenzhen Key Laboratory of Genomics, BGI-Shenzhen, Shenzhen, China
| | - Wen-jing Wang
- BGI-Shenzhen, Shenzhen, China
- Guangdong Provincial Key Laboratory of Human Disease Genomics, Shenzhen Key Laboratory of Genomics, BGI-Shenzhen, Shenzhen, China
| | | | - Weijun Chen
- BGI Education Center, University of Chinese Academy of Sciences, Shenzhen, China
- BGI PathoGenesis Pharmaceutical Technology, BGI-Shenzhen, Shenzhen, China
| | - Shida Zhu
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Engineering Laboratory for Innovative Molecular Diagnostics, BGI-Shenzhen, Shenzhen, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI-Shenzhen, Shenzhen, China
| | - Xin Jin
- BGI-Shenzhen, Shenzhen, 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
| | - Nanshan Zhong
- 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
| | | | - 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
- Institute of Infectious Disease, Guangzhou Eighth People's Hospital of Guangzhou Medical University, Guangzhou, China
| | - Junhua Li
- BGI-Shenzhen, Shenzhen, China
- Shenzhen Key Laboratory of Unknown Pathogen Identification, BGI-Shenzhen, Shenzhen, China
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Yonghao Xu
- 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
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9
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Valesano AL, Rumfelt KE, Dimcheff DE, Blair CN, Fitzsimmons WJ, Petrie JG, Martin ET, Lauring AS. Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.01.19.427330. [PMID: 33501443 PMCID: PMC7836113 DOI: 10.1101/2021.01.19.427330] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified a viral load threshold that minimizes false positives. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.
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Affiliation(s)
- Andrew L. Valesano
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA
| | - Kalee E. Rumfelt
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA
| | - Derek E. Dimcheff
- Division of Hospital Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Christopher N. Blair
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA
| | - William J. Fitzsimmons
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA
| | - Joshua G. Petrie
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Emily T. Martin
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Adam S. Lauring
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA
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