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Caccuri F, Messali S, Bortolotti D, Di Silvestre D, De Palma A, Cattaneo C, Bertelli A, Zani A, Milanesi M, Giovanetti M, Campisi G, Gentili V, Bugatti A, Filippini F, Scaltriti E, Pongolini S, Tucci A, Fiorentini S, d’Ursi P, Ciccozzi M, Mauri P, Rizzo R, Caruso A. Competition for dominance within replicating quasispecies during prolonged SARS-CoV-2 infection in an immunocompromised host. Virus Evol 2022; 8:veac042. [PMID: 35706980 PMCID: PMC9129230 DOI: 10.1093/ve/veac042] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 05/10/2022] [Accepted: 05/20/2022] [Indexed: 11/30/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) emerge for their capability to better adapt to the human host aimed and enhance human-to-human transmission. Mutations in spike largely contributed to adaptation. Viral persistence is a prerequisite for intra-host virus evolution, and this likely occurred in immunocompromised patients who allow intra-host long-term viral replication. The underlying mechanism leading to the emergence of variants during viral persistence in the immunocompromised host is still unknown. Here, we show the existence of an ensemble of minor mutants in the early biological samples obtained from an immunocompromised patient and their dynamic interplay with the master mutant during a persistent and productive long-term infection. In particular, after 222 days of active viral replication, the original master mutant, named MB610, was replaced by a minor quasispecies (MB61222) expressing two critical mutations in spike, namely Q493K and N501T. Isolation of the two viruses allowed us to show that MB61222 entry into target cells occurred mainly by the fusion at the plasma membrane (PM), whereas endocytosis characterized the entry mechanism used by MB610. Interestingly, coinfection of two human cell lines of different origin with the SARS-CoV-2 isolates highlighted the early and dramatic predominance of MB61222 over MB610 replication. This finding may be explained by a faster replicative activity of MB61222 as compared to MB610 as well as by the capability of MB61222 to induce peculiar viral RNA-sensing mechanisms leading to an increased production of interferons (IFNs) and, in particular, of IFN-induced transmembrane protein 1 (IFITM1) and IFITM2. Indeed, it has been recently shown that IFITM2 is able to restrict SARS-CoV-2 entry occurring by endocytosis. In this regard, MB61222 may escape the antiviral activity of IFITMs by using the PM fusion pathway for entry into the target cell, whereas MB610 cannot escape this host antiviral response during MB61222 coinfection, since it has endocytosis as the main pathway of entry. Altogether, our data support the evidence of quasispecies fighting for host dominance by taking benefit from the cell machinery to restrict the productive infection of competitors in the viral ensemble. This finding may explain, at least in part, the extraordinary rapid worldwide turnover of VOCs that use the PM fusion pathway to enter into target cells over the original pandemic strain.
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Affiliation(s)
- Francesca Caccuri
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
| | - Serena Messali
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
| | - Daria Bortolotti
- Department of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, Via Luigi Borsari, 46, Ferrara 44121, Italy
| | - Dario Di Silvestre
- Proteomic and Metabolomic Laboratory, Institute of Biomedical Technologies, National Research Council (ITB-CNR), Via Fratelli Cervi, 201, Segrate 20054, Italy
| | - Antonella De Palma
- Proteomic and Metabolomic Laboratory, Institute of Biomedical Technologies, National Research Council (ITB-CNR), Via Fratelli Cervi, 201, Segrate 20054, Italy
| | - Chiara Cattaneo
- Department of Hematology, ASST Spedali Civili di Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
| | - Anna Bertelli
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
| | - Alberto Zani
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
| | - Maria Milanesi
- Section of Experimental Oncology and Immunology, Department of Molecular and Translational Medicine, University of Brescia, V.le Europa, 11, Brescia 25123, Italy
| | - Marta Giovanetti
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Av. Brasil, 4365, Manguinhos, Rio de Janeiro 21040-360, Brazil
- Laboratório de Genética Celular e Molecular, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Av. Pres. Antônio Carlos, 6627, Pampulha, Belo Horizonte, Minas Gerais 31270-901, Brazil
| | - Giovanni Campisi
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
| | - Valentina Gentili
- Department of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, Via Luigi Borsari, 46, Ferrara 44121, Italy
| | - Antonella Bugatti
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
| | - Federica Filippini
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
| | - Erika Scaltriti
- Risk Analysis and Genomic Epidemiology Unit, Istituto Zooprofilattico Sperimentale della Lombardia e dell’Emilia-Romagna, Str. dei Mercati, 13a, Parma 43126, Italy
| | - Stefano Pongolini
- Risk Analysis and Genomic Epidemiology Unit, Istituto Zooprofilattico Sperimentale della Lombardia e dell’Emilia-Romagna, Str. dei Mercati, 13a, Parma 43126, Italy
| | - Alessandra Tucci
- Department of Hematology, ASST Spedali Civili di Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
| | - Simona Fiorentini
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
| | - Pasqualina d’Ursi
- Institute of Technologies in Biomedicine, National Research Council, Via Fratelli Cervi, 201, Segrate 20054, Italy
| | - Massimo Ciccozzi
- Unit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Via Álvaro del Portillo, 21, Rome 00128, Italy
| | - Pierluigi Mauri
- Proteomic and Metabolomic Laboratory, Institute of Biomedical Technologies, National Research Council (ITB-CNR), Via Fratelli Cervi, 201, Segrate 20054, Italy
| | - Roberta Rizzo
- Department of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, Via Luigi Borsari, 46, Ferrara 44121, Italy
| | - Arnaldo Caruso
- Section of Microbiology, Department of Molecular and Translational Medicine, University of Brescia, P.le Spedali Civili, 1, Brescia 25123, Italy
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52
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Agius JE, Johnson-Mackinnon JC, Fong W, Gall M, Lam C, Basile K, Kok J, Arnott A, Sintchenko V, Rockett RJ. SARS-CoV-2 Within-Host and in vitro Genomic Variability and Sub-Genomic RNA Levels Indicate Differences in Viral Expression Between Clinical Cohorts and in vitro Culture. Front Microbiol 2022; 13:824217. [PMID: 35663867 PMCID: PMC9161297 DOI: 10.3389/fmicb.2022.824217] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 04/18/2022] [Indexed: 12/23/2022] Open
Abstract
Background Low frequency intrahost single nucleotide variants (iSNVs) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) have been increasingly recognised as predictive indicators of positive selection. Particularly as growing numbers of SARS-CoV-2 variants of interest (VOI) and concern (VOC) emerge. However, the dynamics of subgenomic RNA (sgRNA) expression and its impact on genomic diversity and infection outcome remain poorly understood. This study aims to investigate and quantify iSNVs and sgRNA expression in single and longitudinally sampled cohorts over the course of mild and severe SARS-CoV-2 infection, benchmarked against an in vitro infection model. Methods Two clinical cohorts of SARS-CoV-2 positive cases in New South Wales, Australia collected between March 2020 and August 2021 were sequenced. Longitudinal samples from cases hospitalised due to SARS-CoV-2 infection (severe) (n = 16) were analysed and compared with cases that presented with SARS-CoV-2 symptoms but were not hospitalised (mild) (n = 23). SARS-CoV-2 genomic diversity profiles were also examined from daily sampling of culture experiments for three SARS-CoV-2 variants (Lineage A, B.1.351, and B.1.617.2) cultured in VeroE6 C1008 cells (n = 33). Results Intrahost single nucleotide variants were detected in 83% (19/23) of the mild cohort cases and 100% (16/16) of the severe cohort cases. SNP profiles remained relatively fixed over time, with an average of 1.66 SNPs gained or lost, and an average of 4.2 and 5.9 low frequency variants per patient were detected in severe and mild infection, respectively. sgRNA was detected in 100% (25/25) of the mild genomes and 92% (24/26) of the severe genomes. Total sgRNA expressed across all genes in the mild cohort was significantly higher than that of the severe cohort. Significantly higher expression levels were detected in the spike and the nucleocapsid genes. There was significantly less sgRNA detected in the culture dilutions than the clinical cohorts. Discussion and Conclusion The positions and frequencies of iSNVs in the severe and mild infection cohorts were dynamic overtime, highlighting the importance of continual monitoring, particularly during community outbreaks where multiple SARS-CoV-2 variants may co-circulate. sgRNA levels can vary across patients and the overall level of sgRNA reads compared to genomic RNA can be less than 1%. The relative contribution of sgRNA to the severity of illness warrants further investigation given the level of variation between genomes. Further monitoring of sgRNAs will improve the understanding of SARS-CoV-2 evolution and the effectiveness of therapeutic and public health containment measures during the pandemic.
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Affiliation(s)
- Jessica E. Agius
- Centre for Infectious Diseases and Microbiology Public Health, Westmead Hospital, Institute for Clinical Pathology and Medical Research, Westmead, NSW, Australia
- Faculty of Medicine and Health, Sydney Medical School, University of Sydney, Sydney, NSW, Australia
- Sydney Institute for Infectious Diseases, Westmead Institute for Medical Research, Westmead, NSW, Australia
| | - Jessica C. Johnson-Mackinnon
- Centre for Infectious Diseases and Microbiology Public Health, Westmead Hospital, Institute for Clinical Pathology and Medical Research, Westmead, NSW, Australia
- Faculty of Medicine and Health, Sydney Medical School, University of Sydney, Sydney, NSW, Australia
- Sydney Institute for Infectious Diseases, Westmead Institute for Medical Research, Westmead, NSW, Australia
| | - Winkie Fong
- Centre for Infectious Diseases and Microbiology Public Health, Westmead Hospital, Institute for Clinical Pathology and Medical Research, Westmead, NSW, Australia
- Faculty of Medicine and Health, Sydney Medical School, University of Sydney, Sydney, NSW, Australia
| | - Mailie Gall
- Sydney Institute for Infectious Diseases, Westmead Institute for Medical Research, Westmead, NSW, Australia
- Centre for Infectious Diseases and Microbiology Laboratory Services, NSW Health Pathology – Institute of Clinical Pathology and Medical Research, Westmead, NSW, Australia
| | - Connie Lam
- Centre for Infectious Diseases and Microbiology Public Health, Westmead Hospital, Institute for Clinical Pathology and Medical Research, Westmead, NSW, Australia
| | - Kerri Basile
- Centre for Infectious Diseases and Microbiology Laboratory Services, NSW Health Pathology – Institute of Clinical Pathology and Medical Research, Westmead, NSW, Australia
| | - Jen Kok
- Centre for Infectious Diseases and Microbiology Public Health, Westmead Hospital, Institute for Clinical Pathology and Medical Research, Westmead, NSW, Australia
- Centre for Infectious Diseases and Microbiology Laboratory Services, NSW Health Pathology – Institute of Clinical Pathology and Medical Research, Westmead, NSW, Australia
| | - Alicia Arnott
- Centre for Infectious Diseases and Microbiology Public Health, Westmead Hospital, Institute for Clinical Pathology and Medical Research, Westmead, NSW, Australia
- Sydney Institute for Infectious Diseases, Westmead Institute for Medical Research, Westmead, NSW, Australia
- Centre for Infectious Diseases and Microbiology Laboratory Services, NSW Health Pathology – Institute of Clinical Pathology and Medical Research, Westmead, NSW, Australia
| | - Vitali Sintchenko
- Centre for Infectious Diseases and Microbiology Public Health, Westmead Hospital, Institute for Clinical Pathology and Medical Research, Westmead, NSW, Australia
- Faculty of Medicine and Health, Sydney Medical School, University of Sydney, Sydney, NSW, Australia
- Sydney Institute for Infectious Diseases, Westmead Institute for Medical Research, Westmead, NSW, Australia
- Centre for Infectious Diseases and Microbiology Laboratory Services, NSW Health Pathology – Institute of Clinical Pathology and Medical Research, Westmead, NSW, Australia
| | - Rebecca J. Rockett
- Centre for Infectious Diseases and Microbiology Public Health, Westmead Hospital, Institute for Clinical Pathology and Medical Research, Westmead, NSW, Australia
- Faculty of Medicine and Health, Sydney Medical School, University of Sydney, Sydney, NSW, Australia
- Sydney Institute for Infectious Diseases, Westmead Institute for Medical Research, Westmead, NSW, Australia
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53
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Ke R, Martinez PP, Smith RL, Gibson LL, Mirza A, Conte M, Gallagher N, Luo CH, Jarrett J, Zhou R, Conte A, Liu T, Farjo M, Walden KKO, Rendon G, Fields CJ, Wang L, Fredrickson R, Edmonson DC, Baughman ME, Chiu KK, Choi H, Scardina KR, Bradley S, Gloss SL, Reinhart C, Yedetore J, Quicksall J, Owens AN, Broach J, Barton B, Lazar P, Heetderks WJ, Robinson ML, Mostafa HH, Manabe YC, Pekosz A, McManus DD, Brooke CB. Daily longitudinal sampling of SARS-CoV-2 infection reveals substantial heterogeneity in infectiousness. Nat Microbiol 2022; 7:640-652. [PMID: 35484231 PMCID: PMC9084242 DOI: 10.1038/s41564-022-01105-z] [Citation(s) in RCA: 103] [Impact Index Per Article: 34.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 03/15/2022] [Indexed: 02/07/2023]
Abstract
The dynamics of SARS-CoV-2 replication and shedding in humans remain poorly understood. We captured the dynamics of infectious virus and viral RNA shedding during acute infection through daily longitudinal sampling of 60 individuals for up to 14 days. By fitting mechanistic models, we directly estimated viral expansion and clearance rates and overall infectiousness for each individual. Significant person-to-person variation in infectious virus shedding suggests that individual-level heterogeneity in viral dynamics contributes to 'superspreading'. Viral genome loads often peaked days earlier in saliva than in nasal swabs, indicating strong tissue compartmentalization and suggesting that saliva may serve as a superior sampling site for early detection of infection. Viral loads and clearance kinetics of Alpha (B.1.1.7) and previously circulating non-variant-of-concern viruses were mostly indistinguishable, indicating that the enhanced transmissibility of this variant cannot be explained simply by higher viral loads or delayed clearance. These results provide a high-resolution portrait of SARS-CoV-2 infection dynamics and implicate individual-level heterogeneity in infectiousness in superspreading.
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Affiliation(s)
- Ruian Ke
- T-6, Theoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Pamela P Martinez
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Statistics, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Rebecca L Smith
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Department of Pathobiology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Laura L Gibson
- Division of Infectious Diseases and Immunology, Departments of Medicine and Pediatrics, University of Massachusetts Medical School, Worcester, MA, USA
| | - Agha Mirza
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Madison Conte
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Nicholas Gallagher
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Chun Huai Luo
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Junko Jarrett
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ruifeng Zhou
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Abigail Conte
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Tongyu Liu
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Mireille Farjo
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Kimberly K O Walden
- High-Performance Biological Computing at the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Gloria Rendon
- High-Performance Biological Computing at the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Christopher J Fields
- High-Performance Biological Computing at the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Leyi Wang
- Veterinary Diagnostic Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Richard Fredrickson
- Veterinary Diagnostic Laboratory, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Darci C Edmonson
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Melinda E Baughman
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Karen K Chiu
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Hannah Choi
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Kevin R Scardina
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Shannon Bradley
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Stacy L Gloss
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Crystal Reinhart
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Jagadeesh Yedetore
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Jessica Quicksall
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Alyssa N Owens
- Center for Clinical and Translational Research, University of Massachusetts Medical School, Worcester, MA, USA
| | - John Broach
- UMass Memorial Medical Center, Worcester, MA, USA
- Department of Emergency Medicine, University of Massachusetts Medical School, Worcester, MA, USA
| | - Bruce Barton
- Division of Biostatistics and Health Services Research, University of Massachusetts Medical School, Worcester, MA, USA
- Department of Population and Quantitative Health Sciences, University of Massachusetts Medical School, Worcester, MA, USA
| | - Peter Lazar
- Division of Biostatistics and Health Services Research, University of Massachusetts Medical School, Worcester, MA, USA
| | - William J Heetderks
- National Institute for Biomedical Imaging and Bioengineering, Bethesda, MD, USA
| | - Matthew L Robinson
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Heba H Mostafa
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yukari C Manabe
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Andrew Pekosz
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - David D McManus
- Division of Cardiology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Christopher B Brooke
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA.
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Goyal A, Reeves DB, Schiffer JT. Multi-scale modelling reveals that early super-spreader events are a likely contributor to novel variant predominance. J R Soc Interface 2022; 19:20210811. [PMID: 35382576 PMCID: PMC8984334 DOI: 10.1098/rsif.2021.0811] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 03/07/2022] [Indexed: 12/12/2022] Open
Abstract
The emergence of new SARS-CoV-2 variants of concern (VOC) has hampered international efforts to contain the COVID-19 pandemic. VOCs have been characterized to varying degrees by higher transmissibility, worse infection outcomes and evasion of vaccine and infection-induced immunologic memory. VOCs are hypothesized to have originated from animal reservoirs, communities in regions with low surveillance and/or single individuals with poor immunologic control of the virus. Yet, the factors dictating which variants ultimately predominate remain incompletely characterized. Here we present a multi-scale model of SARS-CoV-2 dynamics that describes population spread through individuals whose viral loads and numbers of contacts (drawn from an over-dispersed distribution) are both time-varying. This framework allows us to explore how super-spreader events (SSE) (defined as greater than five secondary infections per day) contribute to variant emergence. We find stochasticity remains a powerful determinant of predominance. Variants that predominate are more likely to be associated with higher infectiousness, an SSE early after variant emergence and ongoing decline of the current dominant variant. Additionally, our simulations reveal that most new highly infectious variants that infect one or a few individuals do not achieve permanence in the population. Consequently, interventions that reduce super-spreading may delay or mitigate emergence of VOCs.
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Affiliation(s)
- Ashish Goyal
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Daniel B. Reeves
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Joshua T. Schiffer
- Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
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55
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Maher MC, Bartha I, Weaver S, di Iulio J, Ferri E, Soriaga L, Lempp FA, Hie BL, Bryson B, Berger B, Robertson DL, Snell G, Corti D, Virgin HW, Kosakovsky Pond SL, Telenti A. Predicting the mutational drivers of future SARS-CoV-2 variants of concern. Sci Transl Med 2022; 14:eabk3445. [PMID: 35014856 PMCID: PMC8939770 DOI: 10.1126/scitranslmed.abk3445] [Citation(s) in RCA: 97] [Impact Index Per Article: 32.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 01/06/2022] [Indexed: 12/17/2022]
Abstract
SARS-CoV-2 evolution threatens vaccine- and natural infection-derived immunity as well as the efficacy of therapeutic antibodies. To improve public health preparedness, we sought to predict which existing amino acid mutations in SARS-CoV-2 might contribute to future variants of concern. We tested the predictive value of features comprising epidemiology, evolution, immunology, and neural network-based protein sequence modeling, and identified primary biological drivers of SARS-CoV-2 intra-pandemic evolution. We found evidence that ACE2-mediated transmissibility and resistance to population-level host immunity has waxed and waned as a primary driver of SARS-CoV-2 evolution over time. We retroactively identified with high accuracy (area under the receiver operator characteristic curve, AUROC=0.92-0.97) mutations that will spread, at up to four months in advance, across different phases of the pandemic. The behavior of the model was consistent with a plausible causal structure wherein epidemiological covariates combine the effects of diverse and shifting drivers of viral fitness. We applied our model to forecast mutations that will spread in the future and characterize how these mutations affect the binding of therapeutic antibodies. These findings demonstrate that it is possible to forecast the driver mutations that could appear in emerging SARS-CoV-2 variants of concern. We validate this result against Omicron, showing elevated predictive scores for its component mutations prior to emergence, and rapid score increase across daily forecasts during emergence. This modeling approach may be applied to any rapidly evolving pathogens with sufficiently dense genomic surveillance data, such as influenza, and unknown future pandemic viruses.
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Affiliation(s)
| | - Istvan Bartha
- Vir Biotechnology, San Francisco, California 94158, USA
| | - Steven Weaver
- Department of Biology Institute for Genomics and Evolutionary Medicine Temple University, Philadelphia, PA 19122
| | | | - Elena Ferri
- Vir Biotechnology, San Francisco, California 94158, USA
| | - Leah Soriaga
- Vir Biotechnology, San Francisco, California 94158, USA
| | | | - Brian L. Hie
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
| | - Bryan Bryson
- Ragon Institute of MGH, MIT, and Harvard, Cambridge, MA 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Bonnie Berger
- Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Computer Science and Artificial Intelligence Laboratory. Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - David L. Robertson
- MRC-University of Glasgow Centre for Virus Research, University of Glasgow, Glasgow GS1 1QH, UK
| | - Gyorgy Snell
- Vir Biotechnology, San Francisco, California 94158, USA
| | - Davide Corti
- Vir Biotechnology, San Francisco, California 94158, USA
| | - Herbert W. Virgin
- Vir Biotechnology, San Francisco, California 94158, USA
- Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Sergei L. Kosakovsky Pond
- Department of Biology Institute for Genomics and Evolutionary Medicine Temple University, Philadelphia, PA 19122
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56
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Hannon WW, Roychoudhury P, Xie H, Shrestha L, Addetia A, Jerome KR, Greninger AL, Bloom JD. Narrow transmission bottlenecks and limited within-host viral diversity during a SARS-CoV-2 outbreak on a fishing boat.. [PMID: 35169803 PMCID: PMC8845427 DOI: 10.1101/2022.02.09.479546] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
The long-term evolution of viruses is ultimately due to viral mutants that arise within infected individuals and transmit to other individuals. Here we use deep sequencing to investigate the transmission of viral genetic variation among individuals during a SARS-CoV-2 outbreak that infected the vast majority of crew members on a fishing boat. We deep-sequenced nasal swabs to characterize the within-host viral population of infected crew members, using experimental duplicates and strict computational filters to ensure accurate variant calling. We find that within-host viral diversity is low in infected crew members. The mutations that did fix in some crew members during the outbreak are not observed at detectable frequencies in any of the sampled crew members in which they are not fixed, suggesting viral evolution involves occasional fixation of low-frequency mutations during transmission rather than persistent maintenance of within-host viral diversity. Overall, our results show that strong transmission bottlenecks dominate viral evolution even during a superspreading event with a very high attack rate.
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57
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Benevides Lima L, Mesquita FP, Brasil de Oliveira LL, Andréa da Silva Oliveira F, Elisabete Amaral de Moraes M, Souza PFN, Montenegro RC. True or False: What are the factors that influence COVID-19 diagnosis by RT-qPCR? Expert Rev Mol Diagn 2022; 22:157-167. [PMID: 35130461 PMCID: PMC8862161 DOI: 10.1080/14737159.2022.2037425] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Introduction The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease has had a catastrophic impact on the world resulting in several deaths. Since World Health Organization declared the pandemic status of the disease, several molecular diagnostic kits have been developed to help the tracking of viruses spread. Areas Covered This review aims to describe and evaluate the currently reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) diagnosis kit. Several processes used in COVID-19 diagnostic procedures are detailed in further depth to demonstrate optimal practices. Therefore, we debate the main factors that influence the viral detection of SARS-COV-2 and how they can affect the diagnosis of patients. Expert Opinion Here is highlighted and discussed several factors that can interfere in the RT-PCR analysis, such as the viral load of the sample, collection site, collection methodology, sample storage, transport, primer, and probe mismatch/dimerization in different brand kits. This is a pioneer study to discuss the factor that could lead to the wrong interpretation of RT-qPCR diagnosis of SARS-CoV-2. This study aimed to help the readers to understand what very likely is behind a bad result of SARS-CoV-2 detection by RT-PCR and what could be done to reach a reliable diagnosis.
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Affiliation(s)
- Luina Benevides Lima
- Laboratory of Pharmacogenetics, Drug Research and Development Center (NPDM), Federal University of Ceará, Fortaleza, CE 60430-275, Brazil
| | - Felipe Pantoja Mesquita
- Laboratory of Pharmacogenetics, Drug Research and Development Center (NPDM), Federal University of Ceará, Fortaleza, CE 60430-275, Brazil
| | - Lais Lacerda Brasil de Oliveira
- Laboratory of Pharmacogenetics, Drug Research and Development Center (NPDM), Federal University of Ceará, Fortaleza, CE 60430-275, Brazil
| | - Francisca Andréa da Silva Oliveira
- Laboratory of Pharmacogenetics, Drug Research and Development Center (NPDM), Federal University of Ceará, Fortaleza, CE 60430-275, Brazil
| | - Maria Elisabete Amaral de Moraes
- Laboratory of Pharmacogenetics, Drug Research and Development Center (NPDM), Federal University of Ceará, Fortaleza, CE 60430-275, Brazil
| | - Pedro F N Souza
- Department of Biochemistry and Molecular Biology (DBBM), Federal University of Ceará, Fortaleza, CE 60430-275, Brazil
| | - Raquel Carvalho Montenegro
- Laboratory of Pharmacogenetics, Drug Research and Development Center (NPDM), Federal University of Ceará, Fortaleza, CE 60430-275, Brazil
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58
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Li B, Deng A, Li K, Hu Y, Li Z, Shi Y, Xiong Q, Liu Z, Guo Q, Zou L, Zhang H, Zhang M, Ouyang F, Su J, Su W, Xu J, Lin H, Sun J, Peng J, Jiang H, Zhou P, Hu T, Luo M, Zhang Y, Zheng H, Xiao J, Liu T, Tan M, Che R, Zeng H, Zheng Z, Huang Y, Yu J, Yi L, Wu J, Chen J, Zhong H, Deng X, Kang M, Pybus OG, Hall M, Lythgoe KA, Li Y, Yuan J, He J, Lu J. Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant. Nat Commun 2022; 13:460. [PMID: 35075154 PMCID: PMC8786931 DOI: 10.1038/s41467-022-28089-y] [Citation(s) in RCA: 217] [Impact Index Per Article: 72.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 01/04/2022] [Indexed: 12/30/2022] Open
Abstract
The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.
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Affiliation(s)
- Baisheng Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Aiping Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Kuibiao Li
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Yao Hu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Zhencui Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yaling Shi
- Guangzhou 8th People's Hospital, Guangzhou, Guangdong, China
| | - Qianling Xiong
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Zhe Liu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Qianfang Guo
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Lirong Zou
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huan Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Meng Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Fangzhu Ouyang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Juan Su
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Wenzhe Su
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Jing Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huifang Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jing Sun
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jinju Peng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Huiming Jiang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Pingping Zhou
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Ting Hu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Min Luo
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yingtao Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huanying Zheng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jianpeng Xiao
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Tao Liu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Mingkai Tan
- Guangzhou 8th People's Hospital, Guangzhou, Guangdong, China
| | - Rongfei Che
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Hanri Zeng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Zhonghua Zheng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yushi Huang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jianxiang Yu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Lina Yi
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jie Wu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jingdiao Chen
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Haojie Zhong
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Xiaoling Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Min Kang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Oliver G Pybus
- 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
| | - Katrina A Lythgoe
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Yan Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China. .,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
| | - Jun Yuan
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
| | - Jianfeng He
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China. .,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
| | - Jing Lu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China. .,Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China. .,Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China.
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59
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Li B, Deng A, Li K, Hu Y, Li Z, Shi Y, Xiong Q, Liu Z, Guo Q, Zou L, Zhang H, Zhang M, Ouyang F, Su J, Su W, Xu J, Lin H, Sun J, Peng J, Jiang H, Zhou P, Hu T, Luo M, Zhang Y, Zheng H, Xiao J, Liu T, Tan M, Che R, Zeng H, Zheng Z, Huang Y, Yu J, Yi L, Wu J, Chen J, Zhong H, Deng X, Kang M, Pybus OG, Hall M, Lythgoe KA, Li Y, Yuan J, He J, Lu J. Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant. Nat Commun 2022. [PMID: 35075154 DOI: 10.1101/2021.07.07.21260122] [Citation(s) in RCA: 100] [Impact Index Per Article: 33.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/13/2023] Open
Abstract
The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.
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Affiliation(s)
- Baisheng Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Aiping Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Kuibiao Li
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Yao Hu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Zhencui Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yaling Shi
- Guangzhou 8th People's Hospital, Guangzhou, Guangdong, China
| | - Qianling Xiong
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Zhe Liu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Qianfang Guo
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Lirong Zou
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huan Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Meng Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Fangzhu Ouyang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Juan Su
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Wenzhe Su
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Jing Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huifang Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jing Sun
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jinju Peng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Huiming Jiang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Pingping Zhou
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Ting Hu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Min Luo
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yingtao Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huanying Zheng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jianpeng Xiao
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Tao Liu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Mingkai Tan
- Guangzhou 8th People's Hospital, Guangzhou, Guangdong, China
| | - Rongfei Che
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Hanri Zeng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Zhonghua Zheng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yushi Huang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jianxiang Yu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Lina Yi
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jie Wu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jingdiao Chen
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Haojie Zhong
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Xiaoling Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Min Kang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Oliver G Pybus
- 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
| | - Katrina A Lythgoe
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Yan Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
| | - Jun Yuan
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
| | - Jianfeng He
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
| | - Jing Lu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China.
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60
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Li B, Deng A, Li K, Hu Y, Li Z, Shi Y, Xiong Q, Liu Z, Guo Q, Zou L, Zhang H, Zhang M, Ouyang F, Su J, Su W, Xu J, Lin H, Sun J, Peng J, Jiang H, Zhou P, Hu T, Luo M, Zhang Y, Zheng H, Xiao J, Liu T, Tan M, Che R, Zeng H, Zheng Z, Huang Y, Yu J, Yi L, Wu J, Chen J, Zhong H, Deng X, Kang M, Pybus OG, Hall M, Lythgoe KA, Li Y, Yuan J, He J, Lu J. Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant. Nat Commun 2022; 13:460. [PMID: 35075154 DOI: 10.21203/rs.3.rs-738164/v1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 01/04/2022] [Indexed: 05/18/2023] Open
Abstract
The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.
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Affiliation(s)
- Baisheng Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Aiping Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Kuibiao Li
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Yao Hu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Zhencui Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yaling Shi
- Guangzhou 8th People's Hospital, Guangzhou, Guangdong, China
| | - Qianling Xiong
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Zhe Liu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Qianfang Guo
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Lirong Zou
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huan Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Meng Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Fangzhu Ouyang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Juan Su
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Wenzhe Su
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Jing Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huifang Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jing Sun
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jinju Peng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Huiming Jiang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Pingping Zhou
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Ting Hu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Min Luo
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yingtao Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huanying Zheng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jianpeng Xiao
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Tao Liu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Mingkai Tan
- Guangzhou 8th People's Hospital, Guangzhou, Guangdong, China
| | - Rongfei Che
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Hanri Zeng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Zhonghua Zheng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yushi Huang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jianxiang Yu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Lina Yi
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jie Wu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jingdiao Chen
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Haojie Zhong
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Xiaoling Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Min Kang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Oliver G Pybus
- 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
| | - Katrina A Lythgoe
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Yan Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
| | - Jun Yuan
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
| | - Jianfeng He
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
| | - Jing Lu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China.
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61
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Li B, Deng A, Li K, Hu Y, Li Z, Shi Y, Xiong Q, Liu Z, Guo Q, Zou L, Zhang H, Zhang M, Ouyang F, Su J, Su W, Xu J, Lin H, Sun J, Peng J, Jiang H, Zhou P, Hu T, Luo M, Zhang Y, Zheng H, Xiao J, Liu T, Tan M, Che R, Zeng H, Zheng Z, Huang Y, Yu J, Yi L, Wu J, Chen J, Zhong H, Deng X, Kang M, Pybus OG, Hall M, Lythgoe KA, Li Y, Yuan J, He J, Lu J. Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant. Nat Commun 2022; 13:460. [PMID: 35075154 DOI: 10.1101/2021.1107.1107.21260122v21260122] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 01/04/2022] [Indexed: 05/23/2023] Open
Abstract
The SARS-CoV-2 Delta variant has spread rapidly worldwide. To provide data on its virological profile, we here report the first local transmission of Delta in mainland China. All 167 infections could be traced back to the first index case. Daily sequential PCR testing of quarantined individuals indicated that the viral loads of Delta infections, when they first become PCR-positive, were on average ~1000 times greater compared to lineage A/B infections during the first epidemic wave in China in early 2020, suggesting potentially faster viral replication and greater infectiousness of Delta during early infection. The estimated transmission bottleneck size of the Delta variant was generally narrow, with 1-3 virions in 29 donor-recipient transmission pairs. However, the transmission of minor iSNVs resulted in at least 3 of the 34 substitutions that were identified in the outbreak, highlighting the contribution of intra-host variants to population-level viral diversity during rapid spread.
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Affiliation(s)
- Baisheng Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Aiping Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Kuibiao Li
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Yao Hu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Zhencui Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yaling Shi
- Guangzhou 8th People's Hospital, Guangzhou, Guangdong, China
| | - Qianling Xiong
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Zhe Liu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Qianfang Guo
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Lirong Zou
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huan Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Meng Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Fangzhu Ouyang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Juan Su
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Wenzhe Su
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China
| | - Jing Xu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huifang Lin
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jing Sun
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jinju Peng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Huiming Jiang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Pingping Zhou
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Ting Hu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Min Luo
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yingtao Zhang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Huanying Zheng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jianpeng Xiao
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Tao Liu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Mingkai Tan
- Guangzhou 8th People's Hospital, Guangzhou, Guangdong, China
| | - Rongfei Che
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Hanri Zeng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Zhonghua Zheng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Yushi Huang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jianxiang Yu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Lina Yi
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China
| | - Jie Wu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Jingdiao Chen
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Haojie Zhong
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Xiaoling Deng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Min Kang
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China
| | - Oliver G Pybus
- 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
| | - Katrina A Lythgoe
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Oxford, OX3 7LF, UK
| | - Yan Li
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
| | - Jun Yuan
- Guangzhou Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
| | - Jianfeng He
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
| | - Jing Lu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, Guangdong, China.
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Chinese Academy of Medical Sciences, Guangzhou, Guangdong, China.
- Guangdong Provincial Institution of Public Health, Guangzhou, Guangdong, China.
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62
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Pathak AK, Mishra GP, Uppili B, Walia S, Fatihi S, Abbas T, Banu S, Ghosh A, Kanampalliwar A, Jha A, Fatma S, Aggarwal S, Dhar MS, Marwal R, Radhakrishnan VS, Ponnusamy K, Kabra S, Rakshit P, Bhoyar RC, Jain A, Divakar MK, Imran M, Faruq M, Sowpati DT, Thukral L, Raghav SK, Mukerji M. Spatio-temporal dynamics of intra-host variability in SARS-CoV-2 genomes. Nucleic Acids Res 2022; 50:1551-1561. [PMID: 35048970 PMCID: PMC8860616 DOI: 10.1093/nar/gkab1297] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 12/09/2021] [Accepted: 01/13/2022] [Indexed: 12/13/2022] Open
Abstract
During the course of the COVID-19 pandemic, large-scale genome sequencing of SARS-CoV-2 has been useful in tracking its spread and in identifying variants of concern (VOC). Viral and host factors could contribute to variability within a host that can be captured in next-generation sequencing reads as intra-host single nucleotide variations (iSNVs). Analysing 1347 samples collected till June 2020, we recorded 16 410 iSNV sites throughout the SARS-CoV-2 genome. We found ∼42% of the iSNV sites to be reported as SNVs by 30 September 2020 in consensus sequences submitted to GISAID, which increased to ∼80% by 30th June 2021. Following this, analysis of another set of 1774 samples sequenced in India between November 2020 and May 2021 revealed that majority of the Delta (B.1.617.2) and Kappa (B.1.617.1) lineage-defining variations appeared as iSNVs before getting fixed in the population. Besides, mutations in RdRp as well as RNA-editing by APOBEC and ADAR deaminases seem to contribute to the differential prevalence of iSNVs in hosts. We also observe hyper-variability at functionally critical residues in Spike protein that could alter the antigenicity and may contribute to immune escape. Thus, tracking and functional annotation of iSNVs in ongoing genome surveillance programs could be important for early identification of potential variants of concern and actionable interventions.
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Affiliation(s)
- Ankit K Pathak
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
| | | | - Bharathram Uppili
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Safal Walia
- Institute of Life Sciences (ILS), Bhubaneswar, Odisha, India
| | - Saman Fatihi
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Tahseen Abbas
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Sofia Banu
- CSIR - Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, Telangana, India
| | - Arup Ghosh
- Institute of Life Sciences (ILS), Bhubaneswar, Odisha, India
| | | | - Atimukta Jha
- Institute of Life Sciences (ILS), Bhubaneswar, Odisha, India
| | - Sana Fatma
- Institute of Life Sciences (ILS), Bhubaneswar, Odisha, India
| | - Shifu Aggarwal
- Institute of Life Sciences (ILS), Bhubaneswar, Odisha, India
| | - Mahesh Shanker Dhar
- Biotechnology Division, National Centre for Disease Control (NCDC), New Delhi, India
| | - Robin Marwal
- Biotechnology Division, National Centre for Disease Control (NCDC), New Delhi, India
| | | | - Kalaiarasan Ponnusamy
- Biotechnology Division, National Centre for Disease Control (NCDC), New Delhi, India
| | - Sandhya Kabra
- Biotechnology Division, National Centre for Disease Control (NCDC), New Delhi, India
| | - Partha Rakshit
- Biotechnology Division, National Centre for Disease Control (NCDC), New Delhi, India
| | - Rahul C Bhoyar
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
| | - Abhinav Jain
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Mohit Kumar Divakar
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Mohamed Imran
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.,Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Mohammed Faruq
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
| | - Divya Tej Sowpati
- CSIR - Centre for Cellular and Molecular Biology (CSIR-CCMB), Hyderabad, Telangana, India
| | - Lipi Thukral
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India
| | - Sunil K Raghav
- Institute of Life Sciences (ILS), Bhubaneswar, Odisha, India
| | - Mitali Mukerji
- CSIR - Institute of Genomics and Integrative Biology (CSIR-IGIB), Delhi, India.,Indian Institute of Technology (IIT), Jodhpur, India
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63
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Lina B. [The different phases of molecular and antigenic evolution of SARS-CoV-2 viruses during the 20 months following its emergence]. BULLETIN DE L'ACADEMIE NATIONALE DE MEDECINE 2022; 206:87-99. [PMID: 34866635 PMCID: PMC8629187 DOI: 10.1016/j.banm.2021.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Accepted: 11/04/2021] [Indexed: 01/04/2023]
Abstract
From its emergence in December 2019 and until the end of the fourth pandemic wave in October 2021, SARS-CoV-2 circulation has been associated with significant molecular evolutions of the virus. These were linked to mutations that have led to new virus linages with replication advantages as a result of increased transmission, or partial immune escape in the context of progressively increasing global immunisation. The pandemic context with large scale epidemics massive outbreaks observed in highly populated areas has favoured this emergence of "variants". During the 20 months period, at least three evolutionary phases have been observed, leading to the situation observed in October 2021. For the first time, an unprecedented worldwide surveillance effort has been conducted to monitor the circulation of the emerging virus, with rapid data sharing. This molecular surveillance system has provided an accurate description of the circulating viruses, and their evolution. The implementation of these tools and skills able to provide SARS-CoV-2 molecular epidemiological data has upgraded the global capacity for surveillance worldwide, and may allow us to be better prepared for a future pandemic episode.
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Affiliation(s)
- B. Lina
- Laboratoire de virologie des HCL, institut des agents infectieux (IAI), CNR des virus à transmission respiratoire (dont la grippe), groupement hospitalier Nord, hôpital de la Croix Rousse, 103, grande rue de la Croix Rousse, 69317 Lyon cedex 04, France,Inserm U1111, laboratoire Virpath, CNRS UMR 5308, ENS de Lyon, UCBL, centre international de recherche en infectiologie (CIRI), université de Lyon, 7–11, rue Guillaume-Paradin, 69372 Lyon cedex 08, France
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64
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Roggero PF, Calistri A, Palù G. On the intrinsic nature of viral pathogenesis: The assumption of a Darwinian paradigm to describe COVID-19 pandemic. Comput Struct Biotechnol J 2022; 20:5870-5872. [PMID: 36320938 PMCID: PMC9613777 DOI: 10.1016/j.csbj.2022.10.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 10/17/2022] [Accepted: 10/23/2022] [Indexed: 11/30/2022] Open
Abstract
Our hypothesis about evolution of the COVID-19 pandemic foresees an inverse relation between infectivity (R0) and lethality (L) of SARS-CoV-2. The above parameters are driven by a continuing mutation process granting the virus a clear survival advantage over virulence. For interpreting this relation we adopted a simple equation, R0 × L ≈ k, by which R0 and L depend upon a constant k, that corresponds to an intrinsic property of the viral species involved. The hypothesis was verified by following changes of the R0 and L terms of the formula in the different variants of SARS-CoV-2 that progressively appeared. A further validation came when the equation was applied to pandemic and epidemic influenza type A viruses, Ebola virus and measles virus. We believe this equation that considers virus biology in Darwinian terms could be extremely useful to better face infectious viral threats and validate virus-host molecular interactions relevant to viral pathogenesis.
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Affiliation(s)
- Pier Francesco Roggero
- Department of Molecular Medicine, University of Padua, via A. Gabelli 63, 35121 Padua, Italy
| | - Arianna Calistri
- Department of Molecular Medicine, University of Padua, via A. Gabelli 63, 35121 Padua, Italy
| | - Giorgio Palù
- Department of Molecular Medicine, University of Padua, via A. Gabelli 63, 35121 Padua, Italy,Italian Medicines Agency, Via del Tritone 181, 00187 Rome, Italy,Corresponding author at: Department of Department of Molecular Medicine, University of Padua, via A. Gabelli 63, 35121 Padua, Italy; Italian Medicines Agency, Via del Tritone 181, 00187, Rome, Italy
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65
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Gallego-García P, Varela N, Estévez-Gómez N, De Chiara L, Fernández-Silva I, Valverde D, Sapoval N, Treangen TJ, Regueiro B, Cabrera-Alvargonzález JJ, del Campo V, Pérez S, Posada D. OUP accepted manuscript. Virus Evol 2022; 8:veac008. [PMID: 35242361 PMCID: PMC8889950 DOI: 10.1093/ve/veac008] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 12/21/2021] [Accepted: 02/04/2022] [Indexed: 11/23/2022] Open
Abstract
A detailed understanding of how and when severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission occurs is crucial for designing effective prevention measures. Other than contact tracing, genome sequencing provides information to help infer who infected whom. However, the effectiveness of the genomic approach in this context depends on both (high enough) mutation and (low enough) transmission rates. Today, the level of resolution that we can obtain when describing SARS-CoV-2 outbreaks using just genomic information alone remains unclear. In order to answer this question, we sequenced forty-nine SARS-CoV-2 patient samples from ten local clusters in NW Spain for which partial epidemiological information was available and inferred transmission history using genomic variants. Importantly, we obtained high-quality genomic data, sequencing each sample twice and using unique barcodes to exclude cross-sample contamination. Phylogenetic and cluster analyses showed that consensus genomes were generally sufficient to discriminate among independent transmission clusters. However, levels of intrahost variation were low, which prevented in most cases the unambiguous identification of direct transmission events. After filtering out recurrent variants across clusters, the genomic data were generally compatible with the epidemiological information but did not support specific transmission events over possible alternatives. We estimated the effective transmission bottleneck size to be one to two viral particles for sample pairs whose donor–recipient relationship was likely. Our analyses suggest that intrahost genomic variation in SARS-CoV-2 might be generally limited and that homoplasy and recurrent errors complicate identifying shared intrahost variants. Reliable reconstruction of direct SARS-CoV-2 transmission based solely on genomic data seems hindered by a slow mutation rate, potential convergent events, and technical artifacts. Detailed contact tracing seems essential in most cases to study SARS-CoV-2 transmission at high resolution.
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Affiliation(s)
| | - Nair Varela
- CINBIO, Universidade de Vigo, Vigo 36310, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
| | - Nuria Estévez-Gómez
- CINBIO, Universidade de Vigo, Vigo 36310, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
| | - Loretta De Chiara
- CINBIO, Universidade de Vigo, Vigo 36310, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
| | - Iria Fernández-Silva
- Department of Biochemistry, Genetics, and Immunology, Universidade de Vigo, Vigo 36310, Spain
| | - Diana Valverde
- CINBIO, Universidade de Vigo, Vigo 36310, Spain
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
- Department of Biochemistry, Genetics, and Immunology, Universidade de Vigo, Vigo 36310, Spain
| | | | | | - Benito Regueiro
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
- Department of Microbiology, Complexo Hospitalario Universitario de Vigo (CHUVI), Sergas, Vigo 36213, Spain
- Microbiology and Parasitology Department, Medicine and Odontology, Universidade de Santiago, Santiago de Compostela 15782, Spain
| | - Jorge Julio Cabrera-Alvargonzález
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
- Department of Microbiology, Complexo Hospitalario Universitario de Vigo (CHUVI), Sergas, Vigo 36213, Spain
| | - Víctor del Campo
- Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO
- Department of Preventive Medicine, Complexo Hospitalario Universitario de Vigo (CHUVI), Sergas, Vigo 36213, Spain
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66
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Dejnirattisai W, Huo J, Zhou D, Zahradník J, Supasa P, Liu C, Duyvesteyn HM, Ginn HM, Mentzer AJ, Tuekprakhon A, Nutalai R, Wang B, Dijokaite A, Khan S, Avinoam O, Bahar M, Skelly D, Adele S, Johnson SA, Amini A, Ritter T, Mason C, Dold C, Pan D, Assadi S, Bellass A, Omo-Dare N, Koeckerling D, Flaxman A, Jenkin D, Aley PK, Voysey M, Clemens SAC, Naveca FG, Nascimento V, Nascimento F, Fernandes da Costa C, Resende PC, Pauvolid-Correa A, Siqueira MM, Baillie V, Serafin N, Ditse Z, Da Silva K, Madhi S, Nunes MC, Malik T, Openshaw PJM, Baillie JK, Semple MG, Townsend AR, Huang KYA, Tan TK, Carroll MW, Klenerman P, Barnes E, Dunachie SJ, Constantinides B, Webster H, Crook D, Pollard AJ, Lambe T, OPTIC consortium, ISARIC4C consortium, Paterson NG, Williams MA, Hall DR, Fry EE, Mongkolsapaya J, Ren J, Schreiber G, Stuart DI, Screaton GR. Omicron-B.1.1.529 leads to widespread escape from neutralizing antibody responses. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.12.03.471045. [PMID: 34981049 PMCID: PMC8722586 DOI: 10.1101/2021.12.03.471045] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
On the 24 th November 2021 the sequence of a new SARS CoV-2 viral isolate spreading rapidly in Southern Africa was announced, containing far more mutations in Spike (S) than previously reported variants. Neutralization titres of Omicron by sera from vaccinees and convalescent subjects infected with early pandemic as well as Alpha, Beta, Gamma, Delta are substantially reduced or fail to neutralize. Titres against Omicron are boosted by third vaccine doses and are high in cases both vaccinated and infected by Delta. Mutations in Omicron knock out or substantially reduce neutralization by most of a large panel of potent monoclonal antibodies and antibodies under commercial development. Omicron S has structural changes from earlier viruses, combining mutations conferring tight binding to ACE2 to unleash evolution driven by immune escape, leading to a large number of mutations in the ACE2 binding site which rebalance receptor affinity to that of early pandemic viruses.
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Affiliation(s)
- Wanwisa Dejnirattisai
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jiandong Huo
- Division of Structural Biology, Nuffield Department of Medicine, University of Oxford, The Wellcome Centre for Human Genetics, Oxford, UK
| | - Daming Zhou
- Division of Structural Biology, Nuffield Department of Medicine, University of Oxford, The Wellcome Centre for Human Genetics, Oxford, UK
- Chinese Academy of Medical Science (CAMS) Oxford Institute (COI), University of Oxford, Oxford, UK
| | - Jiří Zahradník
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Piyada Supasa
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Chang Liu
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Chinese Academy of Medical Science (CAMS) Oxford Institute (COI), University of Oxford, Oxford, UK
| | - Helen M.E. Duyvesteyn
- Division of Structural Biology, Nuffield Department of Medicine, University of Oxford, The Wellcome Centre for Human Genetics, Oxford, UK
| | - Helen M. Ginn
- Diamond Light Source Ltd, Harwell Science & Innovation Campus, Didcot, UK
| | - Alexander J. Mentzer
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Aekkachai Tuekprakhon
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Rungtiwa Nutalai
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Beibei Wang
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Aiste Dijokaite
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Suman Khan
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Ori Avinoam
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Mohammad Bahar
- Division of Structural Biology, Nuffield Department of Medicine, University of Oxford, The Wellcome Centre for Human Genetics, Oxford, UK
| | - Donal Skelly
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Peter Medawar Building for Pathogen Research, Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Sandra Adele
- Peter Medawar Building for Pathogen Research, Oxford, UK
| | | | - Ali Amini
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Peter Medawar Building for Pathogen Research, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
| | - Thomas Ritter
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Chris Mason
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Christina Dold
- NIHR Oxford Biomedical Research Centre, Oxford, UK
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, UK
| | - Daniel Pan
- Department of Infectious Diseases and HIV Medicine, University Hospitals of Leicester NHS Trust,
- Department of Respiratory Sciences, University of Leicester
| | - Sara Assadi
- Department of Infectious Diseases and HIV Medicine, University Hospitals of Leicester NHS Trust,
| | - Adam Bellass
- Department of Infectious Diseases and HIV Medicine, University Hospitals of Leicester NHS Trust,
| | - Nikki Omo-Dare
- Department of Infectious Diseases and HIV Medicine, University Hospitals of Leicester NHS Trust,
| | | | - Amy Flaxman
- Jenner Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Daniel Jenkin
- Jenner Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Parvinder K Aley
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, UK
| | - Merryn Voysey
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, UK
| | - Sue Ann Costa Clemens
- Institute of Global Health, University of Siena, Siena, Brazil; Department of Paediatrics, University of Oxford, Oxford, UK
| | - Felipe Gomes Naveca
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Amazonas, Brazil
| | - Valdinete Nascimento
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Amazonas, Brazil
| | - Fernanda Nascimento
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Amazonas, Brazil
| | | | | | - Alex Pauvolid-Correa
- Laboratorio de vírus respiratórios- IOC/FIOCRUZ, Rio de Janeiro, Brazil
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, United States
| | | | - Vicky Baillie
- South African Medical Research Council, Vaccines and Infectious Diseases Analytics Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Science and Technology/National Research Foundation, South African Research Chair Initiative in Vaccine Preventable Diseases, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Natali Serafin
- South African Medical Research Council, Vaccines and Infectious Diseases Analytics Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Science and Technology/National Research Foundation, South African Research Chair Initiative in Vaccine Preventable Diseases, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Zanele Ditse
- South African Medical Research Council, Vaccines and Infectious Diseases Analytics Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Science and Technology/National Research Foundation, South African Research Chair Initiative in Vaccine Preventable Diseases, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Kelly Da Silva
- South African Medical Research Council, Vaccines and Infectious Diseases Analytics Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Science and Technology/National Research Foundation, South African Research Chair Initiative in Vaccine Preventable Diseases, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Shabir Madhi
- South African Medical Research Council, Vaccines and Infectious Diseases Analytics Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Science and Technology/National Research Foundation, South African Research Chair Initiative in Vaccine Preventable Diseases, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Marta C Nunes
- South African Medical Research Council, Vaccines and Infectious Diseases Analytics Research Unit, School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Science and Technology/National Research Foundation, South African Research Chair Initiative in Vaccine Preventable Diseases, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Tariq Malik
- National Infection Service, Public Health England (PHE), Porton Down, Salisbury, UK
| | | | - J Kenneth Baillie
- Genetics and Genomics, Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Malcolm G Semple
- NIHR Health Protection Research Unit, Institute of Infection, Veterinary and Ecological Sciences, Faculty of Health and Life Sciences, University of Liverpool, Liverpool, UK
| | - Alain R Townsend
- Chinese Academy of Medical Science (CAMS) Oxford Institute (COI), University of Oxford, Oxford, UK
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Kuan-Ying A. Huang
- Research Center for Emerging Viral Infections, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Tiong Kit Tan
- MRC Human Immunology Unit, Weatherall Institute of Molecular Medicine, University of Oxford, John Radcliffe Hospital, Oxford, OX3 9DS, UK
| | - Miles W. Carroll
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- National Infection Service, Public Health England (PHE), Porton Down, Salisbury, UK
| | - Paul Klenerman
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Peter Medawar Building for Pathogen Research, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Eleanor Barnes
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Peter Medawar Building for Pathogen Research, Oxford, UK
- Translational Gastroenterology Unit, University of Oxford, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford, UK
| | - Susanna J. Dunachie
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Peter Medawar Building for Pathogen Research, Oxford, UK
- Centre For Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Mahidol-Oxford Tropical Medicine Research Unit, Bangkok, Thailand, Department of Medicine, University of Oxford, Oxford, UK
| | | | - Hermione Webster
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Derrick Crook
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Andrew J Pollard
- NIHR Oxford Biomedical Research Centre, Oxford, UK
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, UK
| | - Teresa Lambe
- Chinese Academy of Medical Science (CAMS) Oxford Institute (COI), University of Oxford, Oxford, UK
- Oxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, UK
| | | | | | - Neil G. Paterson
- Diamond Light Source Ltd, Harwell Science & Innovation Campus, Didcot, UK
| | - Mark A. Williams
- Diamond Light Source Ltd, Harwell Science & Innovation Campus, Didcot, UK
| | - David R. Hall
- Diamond Light Source Ltd, Harwell Science & Innovation Campus, Didcot, UK
| | - Elizabeth E. Fry
- Division of Structural Biology, Nuffield Department of Medicine, University of Oxford, The Wellcome Centre for Human Genetics, Oxford, UK
| | - Juthathip Mongkolsapaya
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Chinese Academy of Medical Science (CAMS) Oxford Institute (COI), University of Oxford, Oxford, UK
- Siriraj Center of Research Excellence in Dengue & Emerging Pathogens, Dean Office for Research, Faculty of Medicine Siriraj Hospital, Mahidol University, Thailand
- corresponding authors: , , , ,
| | - Jingshan Ren
- Division of Structural Biology, Nuffield Department of Medicine, University of Oxford, The Wellcome Centre for Human Genetics, Oxford, UK
- corresponding authors: , , , ,
| | - Gideon Schreiber
- Department of Biomolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
- corresponding authors: , , , ,
| | - David I. Stuart
- Division of Structural Biology, Nuffield Department of Medicine, University of Oxford, The Wellcome Centre for Human Genetics, Oxford, UK
- Chinese Academy of Medical Science (CAMS) Oxford Institute (COI), University of Oxford, Oxford, UK
- Diamond Light Source Ltd, Harwell Science & Innovation Campus, Didcot, UK
- Instruct-ERIC, Oxford House, Parkway Court, John Smith Drive, Oxford, UK
- corresponding authors: , , , ,
| | - Gavin R Screaton
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Chinese Academy of Medical Science (CAMS) Oxford Institute (COI), University of Oxford, Oxford, UK
- corresponding authors: , , , ,
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67
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Focosi D, Maggi F, Franchini M, McConnell S, Casadevall A. Analysis of Immune Escape Variants from Antibody-Based Therapeutics against COVID-19: A Systematic Review. Int J Mol Sci 2021; 23:29. [PMID: 35008446 PMCID: PMC8744556 DOI: 10.3390/ijms23010029] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 12/14/2021] [Accepted: 12/17/2021] [Indexed: 12/31/2022] Open
Abstract
The accelerated SARS-CoV-2 evolution under selective pressure by massive deployment of neutralizing antibody-based therapeutics is a concern with potentially severe implications for public health. We review here reports of documented immune escape after treatment with monoclonal antibodies and COVID-19-convalescent plasma (CCP). While the former is mainly associated with specific single amino acid mutations at residues within the receptor-binding domain (e.g., E484K/Q, Q493R, and S494P), a few cases of immune evasion after CCP were associated with recurrent deletions within the N-terminal domain of the spike protein (e.g., ΔHV69-70, ΔLGVY141-144 and ΔAL243-244). The continuous genomic monitoring of non-responders is needed to better understand immune escape frequencies and the fitness of emerging variants.
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Affiliation(s)
- Daniele Focosi
- North-Western Tuscany Blood Bank, Pisa University Hospital, 56124 Pisa, Italy
| | - Fabrizio Maggi
- Department of Medicine and Surgery, University of Insubria, 21100 Varese, Italy;
- Laboratory of Microbiology, Azienda Socio Sanitaria Territoriale Sette Laghi, 21100 Varese, Italy
| | - Massimo Franchini
- Division of Transfusion Medicine, Carlo Poma Hospital, 46100 Mantua, Italy;
| | - Scott McConnell
- Department of Medicine, Johns Hopkins School of Public Health, Baltimore, MD 21218, USA; (S.M.); (A.C.)
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21218, USA
| | - Arturo Casadevall
- Department of Medicine, Johns Hopkins School of Public Health, Baltimore, MD 21218, USA; (S.M.); (A.C.)
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21218, USA
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68
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Abstract
The success of many viruses depends upon cooperative interactions between viral genomes. However, whenever cooperation occurs, there is the potential for 'cheats' to exploit that cooperation. We suggest that: (1) the biology of viruses makes viral cooperation particularly susceptible to cheating; (2) cheats are common across a wide range of viruses, including viral entities that are already well studied, such as defective interfering genomes, and satellite viruses. Consequently, the evolutionary theory of cheating could help us understand and manipulate viral dynamics, while viruses also offer new opportunities to study the evolution of cheating.
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Affiliation(s)
- Asher Leeks
- Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK.
| | - Stuart A West
- Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK
| | - Melanie Ghoul
- Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK
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69
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Van Egeren D, Novokhodko A, Stoddard M, Tran U, Zetter B, Rogers MS, Joseph-McCarthy D, Chakravarty A. Controlling long-term SARS-CoV-2 infections can slow viral evolution and reduce the risk of treatment failure. Sci Rep 2021; 11:22630. [PMID: 34799659 PMCID: PMC8604936 DOI: 10.1038/s41598-021-02148-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 10/27/2021] [Indexed: 12/23/2022] Open
Abstract
The rapid emergence and expansion of novel SARS-CoV-2 variants threatens our ability to achieve herd immunity for COVID-19. These novel SARS-CoV-2 variants often harbor multiple point mutations, conferring one or more evolutionarily advantageous traits, such as increased transmissibility, immune evasion and longer infection duration. In a number of cases, variant emergence has been linked to long-term infections in individuals who were either immunocompromised or treated with convalescent plasma. In this paper, we used a stochastic evolutionary modeling framework to explore the emergence of fitter variants of SARS-CoV-2 during long-term infections. We found that increased viral load and infection duration favor emergence of such variants. While the overall probability of emergence and subsequent transmission from any given infection is low, on a population level these events occur fairly frequently. Targeting these low-probability stochastic events that lead to the establishment of novel advantageous viral variants might allow us to slow the rate at which they emerge in the patient population, and prevent them from spreading deterministically due to natural selection. Our work thus suggests practical ways to achieve control of long-term SARS-CoV-2 infections, which will be critical for slowing the rate of viral evolution.
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Affiliation(s)
- Debra Van Egeren
- Harvard Medical School, Boston, MA, USA
- Dana-Farber Cancer Institute, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | | | | | - Uyen Tran
- Fractal Therapeutics, Cambridge, MA, USA
| | - Bruce Zetter
- Harvard Medical School, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
| | - Michael S Rogers
- Harvard Medical School, Boston, MA, USA
- Boston Children's Hospital, Boston, MA, USA
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70
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Chappleboim A, Joseph-Strauss D, Rahat A, Sharkia I, Adam M, Kitsberg D, Fialkoff G, Lotem M, Gershon O, Schmidtner AK, Oiknine-Djian E, Klochendler A, Sadeh R, Dor Y, Wolf D, Habib N, Friedman N. Early sample tagging and pooling enables simultaneous SARS-CoV-2 detection and variant sequencing. Sci Transl Med 2021; 13:eabj2266. [PMID: 34591660 PMCID: PMC9928115 DOI: 10.1126/scitranslmed.abj2266] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Most severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnostic tests have relied on RNA extraction followed by reverse transcription quantitative polymerase chain reaction (RT-qPCR) assays. Whereas automation improved logistics and different pooling strategies increased testing capacity, highly multiplexed next-generation sequencing (NGS) diagnostics remain a largely untapped resource. NGS tests have the potential to markedly increase throughput while providing crucial SARS-CoV-2 variant information. Current NGS-based detection and genotyping assays for SARS-CoV-2 are costly, mostly due to parallel sample processing through multiple steps. Here, we have established ApharSeq, in which samples are barcoded in the lysis buffer and pooled before reverse transcription. We validated this assay by applying ApharSeq to more than 500 clinical samples from the Clinical Virology Laboratory at Hadassah hospital in a robotic workflow. The assay was linear across five orders of magnitude, and the limit of detection was Ct 33 (~1000 copies/ml, 95% sensitivity) with >99.5% specificity. ApharSeq provided targeted high-confidence genotype information due to unique molecular identifiers incorporated into this method. Because of early pooling, we were able to estimate a 10- to 100-fold reduction in labor, automated liquid handling, and reagent requirements in high-throughput settings compared to current testing methods. The protocol can be tailored to assay other host or pathogen RNA targets simultaneously. These results suggest that ApharSeq can be a promising tool for current and future mass diagnostic challenges.
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Affiliation(s)
- Alon Chappleboim
- Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Daphna Joseph-Strauss
- Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Ayelet Rahat
- Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Israa Sharkia
- Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Miriam Adam
- Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Daniel Kitsberg
- Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Gavriel Fialkoff
- Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Matan Lotem
- Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Omer Gershon
- Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Anna-Kristina Schmidtner
- Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Esther Oiknine-Djian
- Hadassah Hebrew University Medical Center, Jerusalem 9112001, Israel.,Lautenberg Centre for Immunology and Cancer Research, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 9112001, Israel
| | - Agnes Klochendler
- Department of Developmental Biology and Cancer Research, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 9112001, Israel
| | - Ronen Sadeh
- Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Yuval Dor
- Department of Developmental Biology and Cancer Research, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 9112001, Israel
| | - Dana Wolf
- Hadassah Hebrew University Medical Center, Jerusalem 9112001, Israel.,Lautenberg Centre for Immunology and Cancer Research, IMRIC, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 9112001, Israel
| | - Naomi Habib
- Edmond and Lily Safra Center for Brain Sciences, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Nir Friedman
- Alexander Silberman Institute of Life Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel.,Rachel and Selim Benin School of Computer Science, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
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Valesano AL, Fitzsimmons WJ, Blair CN, Woods RJ, Gilbert J, Rudnik D, Mortenson L, Friedrich TC, O’Connor DH, MacCannell DR, Petrie JG, Martin ET, Lauring AS. SARS-CoV-2 Genomic Surveillance Reveals Little Spread From a Large University Campus to the Surrounding Community. Open Forum Infect Dis 2021; 8:ofab518. [PMID: 34805437 PMCID: PMC8600169 DOI: 10.1093/ofid/ofab518] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 10/07/2021] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Coronavirus disease 2019 (COVID-19) has had high incidence rates at institutions of higher education (IHE) in the United States, but the transmission dynamics in these settings are poorly understood. It remains unclear to what extent IHE-associated outbreaks have contributed to transmission in nearby communities. METHODS We implemented high-density prospective genomic surveillance to investigate these dynamics at the University of Michigan and the surrounding community during the Fall 2020 semester (August 16-November 24). We sequenced complete severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes from 1659 individuals, including 468 students, representing 20% of cases in students and 25% of total cases in Washtenaw County over the study interval. RESULTS Phylogenetic analysis identified >200 introductions into the student population, most of which were not related to other student cases. There were 2 prolonged student transmission clusters, of 115 and 73 individuals, that spanned multiple on-campus residences. Remarkably, <5% of nonstudent genomes were descended from student clusters, and viral descendants of student cases were rare during a subsequent wave of infections in the community. CONCLUSIONS The largest outbreaks among students at the University of Michigan did not significantly contribute to the rise in community cases in Fall 2020. These results provide valuable insights into SARS-CoV-2 transmission dynamics at the regional level.
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Affiliation(s)
- Andrew L Valesano
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
| | - William J Fitzsimmons
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Christopher N Blair
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Robert J Woods
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Julie Gilbert
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Dawn Rudnik
- University Health Service, University of Michigan, Ann Arbor, Michigan, USA
| | - Lindsey Mortenson
- University Health Service, University of Michigan, Ann Arbor, Michigan, USA
| | - Thomas C Friedrich
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - David H O’Connor
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | | | - Joshua G Petrie
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Emily T Martin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Adam S Lauring
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
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72
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Focosi D, Maggi F. Neutralising antibody escape of SARS-CoV-2 spike protein: Risk assessment for antibody-based Covid-19 therapeutics and vaccines. Rev Med Virol 2021; 31:e2231. [PMID: 33724631 PMCID: PMC8250244 DOI: 10.1002/rmv.2231] [Citation(s) in RCA: 115] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 01/29/2021] [Accepted: 02/15/2021] [Indexed: 12/15/2022]
Abstract
The Spike protein is the target of both antibody-based therapeutics (convalescent plasma, polyclonal serum, monoclonal antibodies) and vaccines. Mutations in Spike could affect efficacy of those treatments. Hence, monitoring of mutations is necessary to forecast and readapt the inventory of therapeutics. Different phylogenetic nomenclatures have been used for the currently circulating SARS-CoV-2 clades. The Spike protein has different hotspots of mutation and deletion, the most dangerous for immune escape being the ones within the receptor binding domain (RBD), such as K417N/T, N439K, L452R, Y453F, S477N, E484K, and N501Y. Convergent evolution has led to different combinations of mutations among different clades. In this review we focus on the main variants of concern, that is, the so-called UK (B.1.1.7), South African (B.1.351) and Brazilian (P.1) strains.
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MESH Headings
- Antibodies, Monoclonal/chemistry
- Antibodies, Monoclonal/metabolism
- Antibodies, Monoclonal/therapeutic use
- Antibodies, Neutralizing/chemistry
- Antibodies, Neutralizing/metabolism
- Antibodies, Neutralizing/therapeutic use
- Antibodies, Viral/chemistry
- Antibodies, Viral/metabolism
- Antibodies, Viral/therapeutic use
- Brazil/epidemiology
- COVID-19/epidemiology
- COVID-19/immunology
- COVID-19/therapy
- COVID-19/virology
- COVID-19 Vaccines/administration & dosage
- Gene Expression
- Humans
- Immune Evasion
- Immunization, Passive/methods
- Mutation
- Phylogeny
- Protein Binding
- Risk Assessment
- SARS-CoV-2/classification
- SARS-CoV-2/drug effects
- SARS-CoV-2/genetics
- SARS-CoV-2/immunology
- South Africa/epidemiology
- Spike Glycoprotein, Coronavirus/genetics
- Spike Glycoprotein, Coronavirus/immunology
- United Kingdom/epidemiology
- COVID-19 Serotherapy
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Affiliation(s)
- Daniele Focosi
- North‐Western Tuscany Blood BankPisa University HospitalPisaItaly
| | - Fabrizio Maggi
- Department of Medicine and SurgeryUniversity of InsubriaVareseItaly
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73
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Martin MA, Koelle K. Comment on "Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2". Sci Transl Med 2021; 13:eabh1803. [PMID: 34705523 DOI: 10.1126/scitranslmed.abh1803] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
[Figure: see text].
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Affiliation(s)
- Michael A Martin
- Graduate Program in Population Biology, Ecology, and Evolution, Emory University, Atlanta, GA 30322, USA
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, GA 30322, USA.,Emory-UGA Center of Excellence for Influenza Research and Surveillance (CEIRS), Atlanta GA 30322, USA
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74
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Nicholson MD, Endler L, Popa A, Genger JW, Bock C, Michor F, Bergthaler A. Response to comment on "Genomic epidemiology of superspreading events in Austria reveals mutational dynamics and transmission properties of SARS-CoV-2". Sci Transl Med 2021; 13:eabj3222. [PMID: 34705522 DOI: 10.1126/scitranslmed.abj3222] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Further analysis of SARS-CoV-2 genome sequencing data identifies several highly recurrent genetic variants with low allele frequencies, which, if filtered out, provide estimates consistent with tighter transmission bottlenecks.
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Affiliation(s)
- Michael D Nicholson
- Cancer Research UK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road, Edinburgh EH4 2XU, UK
| | - Lukas Endler
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria
| | - Alexandra Popa
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria
| | - Jakob-Wendelin Genger
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria
| | - Christoph Bock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria
- Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, 1090 Vienna, Austria
| | - Franziska Michor
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02215, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- The Ludwig Center at Harvard, Boston, MA 02115, USA
- Center for Cancer Evolution, Dana-Farber Cancer Institute, Boston, MA 02115, USA
| | - Andreas Bergthaler
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria
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75
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Voloch CM, da Silva Francisco R, de Almeida LGP, Brustolini OJ, Cardoso CC, Gerber AL, Guimarães APDC, Leitão IDC, Mariani D, Ota VA, Lima CX, Teixeira MM, Dias ACF, Galliez RM, Faffe DS, Pôrto LC, Aguiar RS, Castiñeira TMPP, Ferreira OC, Tanuri A, de Vasconcelos ATR. Intra-host evolution during SARS-CoV-2 prolonged infection. Virus Evol 2021; 7:veab078. [PMID: 34642605 PMCID: PMC8500031 DOI: 10.1093/ve/veab078] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 09/05/2021] [Accepted: 09/09/2021] [Indexed: 12/23/2022] Open
Abstract
Long-term infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a challenge to virus dispersion and the control of coronavirus disease 2019 (COVID-19) pandemic. The reason why some people have prolonged infection and how the virus persists for so long are still not fully understood. Recent studies suggested that the accumulation of intra-host single nucleotide variants (iSNVs) over the course of the infection might play an important role in persistence as well as emergence of mutations of concern. For this reason, we aimed to investigate the intra-host evolution of SARS-CoV-2 during prolonged infection. Thirty-three patients who remained reverse transcription polymerase chain reaction (RT-PCR) positive in the nasopharynx for on average 18 days from the symptoms onset were included in this study. Whole-genome sequences were obtained for each patient at two different time points. Phylogenetic, populational, and computational analyses of viral sequences were consistent with prolonged infection without evidence of coinfection in our cohort. We observed an elevated within-host genomic diversity at the second time point samples positively correlated with cycle threshold (Ct) values (lower viral load). Direct transmission was also confirmed in a small cluster of healthcare professionals that shared the same workplace by the presence of common iSNVs. A differential accumulation of missense variants between the time points was detected targeting crucial structural and non-structural proteins such as Spike and helicase. Interestingly, longitudinal acquisition of iSNVs in Spike protein coincided in many cases with SARS-CoV-2 reactive and predicted T cell epitopes. We observed a distinguishing pattern of mutations over the course of the infection mainly driven by increasing A→U and decreasing G→A signatures. G→A mutations may be associated with RNA-editing enzyme activities; therefore, the mutational profiles observed in our analysis were suggestive of innate immune mechanisms of the host cell defense. Therefore, we unveiled a dynamic and complex landscape of host and pathogen interaction during prolonged infection of SARS-CoV-2, suggesting that the host’s innate immunity shapes the increase of intra-host diversity. Our findings may also shed light on possible mechanisms underlying the emergence and spread of new variants resistant to the host immune response as recently observed in COVID-19 pandemic.
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Affiliation(s)
- Carolina M Voloch
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373 - Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-902, Brazil
| | - Ronaldo da Silva Francisco
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Av. Getúlio Vargas, 333 - Quitandinha, Petrópolis 25651-076, Brazil
| | - Luiz G P de Almeida
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Av. Getúlio Vargas, 333 - Quitandinha, Petrópolis 25651-076, Brazil
| | - Otavio J Brustolini
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Av. Getúlio Vargas, 333 - Quitandinha, Petrópolis 25651-076, Brazil
| | - Cynthia C Cardoso
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373 - Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-902, Brazil
| | - Alexandra L Gerber
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Av. Getúlio Vargas, 333 - Quitandinha, Petrópolis 25651-076, Brazil
| | - Ana Paula de C Guimarães
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Av. Getúlio Vargas, 333 - Quitandinha, Petrópolis 25651-076, Brazil
| | - Isabela de Carvalho Leitão
- Instituto de Biofísica, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373 - Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-170, Brazil
| | - Diana Mariani
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373 - Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-902, Brazil
| | - Victor Akira Ota
- Departamento de Doenças Infecciosas e Parasitárias, Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373, Edifício do Centro de Ciências da Saúde, Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-902, Brazil
| | - Cristiano X Lima
- Departamento de Cirurgia, Faculdade de Medicina, Universidade Federal de Minas Gerais, Av. Prof. Alfredo Balena, 190 - Santa Efigênia, Belo Horizonte, MG 30130-100, Brazil
| | - Mauro M Teixeira
- Departamento de Bioquimica e Imunologia, Universidade Federal de Minas Gerais, Av. Antônio Carlos, 6627 - Pampulha, Belo Horizonte 31270-901, Brazil
| | - Ana Carolina F Dias
- Simile Instituto de Imunologia Aplicada Ltda. R. São Paulo, 1932, Belo Horizonte, 30170-132, Brazil
| | - Rafael Mello Galliez
- Departamento de Doenças Infecciosas e Parasitárias, Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373, Edifício do Centro de Ciências da Saúde, Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-902, Brazil
| | - Débora Souza Faffe
- Instituto de Biofísica, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373 - Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-170, Brazil
| | - Luís Cristóvão Pôrto
- Instituto de Biologia Roberto Alcântara Gomes, Universidade do Estado do Rio de Janeiro, Boulevard 28 de Setembro, 87, Rio de Janeiro 20511-010, Brazil
| | - Renato S Aguiar
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373 - Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-902, Brazil
| | - Terezinha M P P Castiñeira
- Departamento de Doenças Infecciosas e Parasitárias, Faculdade de Medicina, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373, Edifício do Centro de Ciências da Saúde, Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-902, Brazil
| | - Orlando C Ferreira
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373 - Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-902, Brazil
| | - Amilcar Tanuri
- Departamento de Genética, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Av. Carlos Chagas Filho, 373 - Cidade Universitária da Universidade Federal do Rio de Janeiro - Ilha do Fundão, Rio de Janeiro 21941-902, Brazil
| | - Ana Tereza R de Vasconcelos
- Laboratório de Bioinformática, Laboratório Nacional de Computação Científica, Av. Getúlio Vargas, 333 - Quitandinha, Petrópolis 25651-076, Brazil
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76
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Goldhill DH, Barclay WS. 2020 Hindsight: Should evolutionary virologists have expected the unexpected during a pandemic? Evolution 2021; 75:2311-2316. [PMID: 34342897 PMCID: PMC8444725 DOI: 10.1111/evo.14317] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Revised: 06/21/2021] [Accepted: 07/12/2021] [Indexed: 12/11/2022]
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77
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Braun KM, Moreno GK, Wagner C, Accola MA, Rehrauer WM, Baker DA, Koelle K, O’Connor DH, Bedford T, Friedrich TC, Moncla LH. Acute SARS-CoV-2 infections harbor limited within-host diversity and transmit via tight transmission bottlenecks. PLoS Pathog 2021; 17:e1009849. [PMID: 34424945 PMCID: PMC8412271 DOI: 10.1371/journal.ppat.1009849] [Citation(s) in RCA: 85] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 09/02/2021] [Accepted: 07/29/2021] [Indexed: 02/08/2023] Open
Abstract
The emergence of divergent SARS-CoV-2 lineages has raised concern that novel variants eliciting immune escape or the ability to displace circulating lineages could emerge within individual hosts. Though growing evidence suggests that novel variants arise during prolonged infections, most infections are acute. Understanding how efficiently variants emerge and transmit among acutely-infected hosts is therefore critical for predicting the pace of long-term SARS-CoV-2 evolution. To characterize how within-host diversity is generated and propagated, we combine extensive laboratory and bioinformatic controls with metrics of within- and between-host diversity to 133 SARS-CoV-2 genomes from acutely-infected individuals. We find that within-host diversity is low and transmission bottlenecks are narrow, with very few viruses founding most infections. Within-host variants are rarely transmitted, even among individuals within the same household, and are rarely detected along phylogenetically linked infections in the broader community. These findings suggest that most variation generated within-host is lost during transmission.
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Affiliation(s)
- Katarina M. Braun
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Gage K. Moreno
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Cassia Wagner
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Molly A. Accola
- University of Wisconsin School of Medicine and Public Health and the William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin, United States of America
| | - William M. Rehrauer
- University of Wisconsin School of Medicine and Public Health and the William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin, United States of America
| | - David A. Baker
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, Georgia, United States of America
| | - David H. O’Connor
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Trevor Bedford
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Thomas C. Friedrich
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Louise H. Moncla
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
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78
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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: 264] [Impact Index Per Article: 66.0] [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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