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Bukur T, Riesgo-Ferreiro P, Sorn P, Gudimella R, Hausmann J, Rösler T, Löwer M, Schrörs B, Sahin U. CoVigator-A Knowledge Base for Navigating SARS-CoV-2 Genomic Variants. Viruses 2023; 15:1391. [PMID: 37376690 DOI: 10.3390/v15061391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 06/15/2023] [Accepted: 06/16/2023] [Indexed: 06/29/2023] Open
Abstract
BACKGROUND The outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) resulted in the global COVID-19 pandemic. The urgency for an effective SARS-CoV-2 vaccine has led to the development of the first series of vaccines at unprecedented speed. The discovery of SARS-CoV-2 spike-glycoprotein mutants, however, and consequentially the potential to escape vaccine-induced protection and increased infectivity, demonstrates the persisting importance of monitoring SARS-CoV-2 mutations to enable early detection and tracking of genomic variants of concern. RESULTS We developed the CoVigator tool with three components: (1) a knowledge base that collects new SARS-CoV-2 genomic data, processes it and stores its results; (2) a comprehensive variant calling pipeline; (3) an interactive dashboard highlighting the most relevant findings. The knowledge base routinely downloads and processes virus genome assemblies or raw sequencing data from the COVID-19 Data Portal (C19DP) and the European Nucleotide Archive (ENA), respectively. The results of variant calling are visualized through the dashboard in the form of tables and customizable graphs, making it a versatile tool for tracking SARS-CoV-2 variants. We put a special emphasis on the identification of intrahost mutations and make available to the community what is, to the best of our knowledge, the largest dataset on SARS-CoV-2 intrahost mutations. In the spirit of open data, all CoVigator results are available for download. The CoVigator dashboard is accessible via covigator.tron-mainz.de. CONCLUSIONS With increasing demand worldwide in genome surveillance for tracking the spread of SARS-CoV-2, CoVigator will be a valuable resource of an up-to-date list of mutations, which can be incorporated into global efforts.
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Affiliation(s)
- Thomas Bukur
- TRON-Translational Oncology at the Medical Center of the Johannes Gutenberg-University Mainz Gemeinnützige GmbH, 55131 Mainz, Germany
| | - Pablo Riesgo-Ferreiro
- TRON-Translational Oncology at the Medical Center of the Johannes Gutenberg-University Mainz Gemeinnützige GmbH, 55131 Mainz, Germany
| | - Patrick Sorn
- TRON-Translational Oncology at the Medical Center of the Johannes Gutenberg-University Mainz Gemeinnützige GmbH, 55131 Mainz, Germany
| | - Ranganath Gudimella
- TRON-Translational Oncology at the Medical Center of the Johannes Gutenberg-University Mainz Gemeinnützige GmbH, 55131 Mainz, Germany
| | - Johannes Hausmann
- TRON-Translational Oncology at the Medical Center of the Johannes Gutenberg-University Mainz Gemeinnützige GmbH, 55131 Mainz, Germany
| | - Thomas Rösler
- TRON-Translational Oncology at the Medical Center of the Johannes Gutenberg-University Mainz Gemeinnützige GmbH, 55131 Mainz, Germany
| | - Martin Löwer
- TRON-Translational Oncology at the Medical Center of the Johannes Gutenberg-University Mainz Gemeinnützige GmbH, 55131 Mainz, Germany
| | - Barbara Schrörs
- TRON-Translational Oncology at the Medical Center of the Johannes Gutenberg-University Mainz Gemeinnützige GmbH, 55131 Mainz, Germany
| | - Ugur Sahin
- BioNTech SE, 55131 Mainz, Germany
- Research Center for Immunotherapy (FZI), University Medical Center of the Johannes Gutenberg University Mainz, 55099 Mainz, Germany
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2
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Cheng Y, Ji C, Zhou HY, Zheng H, Wu A. Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking. Viruses 2023; 15:v15051158. [PMID: 37243244 DOI: 10.3390/v15051158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/10/2023] [Accepted: 05/10/2023] [Indexed: 05/28/2023] Open
Abstract
The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus.
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Affiliation(s)
- Yexiao Cheng
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 211100, China
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
| | - Chengyang Ji
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
| | - Hang-Yu Zhou
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
| | - Heng Zheng
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 211100, China
| | - Aiping Wu
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
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3
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Naveca FG, Nascimento VA, Nascimento F, Ogrzewalska M, Pauvolid-Corrêa A, Araújo MF, Arantes I, Batista ÉR, Magalhães AÁ, Vinhal F, Mattos TP, Riediger I, Debur MDC, Grinsztejn B, Veloso VG, Brasil P, Rodrigues RR, Rovaris DB, Fernandes SB, Fernandes C, Santos JHA, Abdalla LF, Costa-Filho R, Silva M, Souza V, Costa ÁA, Mejía M, Brandão MJ, Gonçalves LF, Silva GA, de Jesus MS, Pessoa K, Corado ADLG, Duarte DCG, Machado AB, Zukeram KDA, Valente N, Lopes RS, Pereira EC, Appolinario LR, Rocha AS, Tort LFL, Sekizuka T, Itokawa K, Hashino M, Kuroda M, Dezordi FZ, Wallau GL, Delatorre E, Gräf T, Siqueira MM, Bello G, Resende PC. SARS-CoV-2 intra-host diversity, antibody response, and disease severity after reinfection by the variant of concern Gamma in Brazil. Sci Rep 2023; 13:7306. [PMID: 37147348 PMCID: PMC10160723 DOI: 10.1038/s41598-023-33443-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 04/12/2023] [Indexed: 05/07/2023] Open
Abstract
The rapid spread of the SARS-CoV-2 Variant of Concern (VOC) Gamma in Amazonas during early 2021 fueled a second large COVID-19 epidemic wave and raised concern about the potential role of reinfections. Very few cases of reinfection associated with the VOC Gamma have been reported to date, and their potential impact on clinical, immunological, and virological parameters remains largely unexplored. Here we describe 25 cases of SARS-CoV-2 reinfection in Brazil. SARS-CoV-2 genomic analysis confirmed that individuals were primo-infected with distinct viral lineages between March and December 2020 (B.1.1, B.1.1.28, B.1.1.33, B.1.195, and P.2) and reinfected with the VOC Gamma between 3 to 12 months after primo-infection. We found a similar mean cycle threshold (Ct) value and limited intra-host viral diversity in both primo-infection and reinfection samples. Sera of 14 patients tested 10-75 days after reinfection displayed detectable neutralizing antibodies (NAb) titers against SARS-CoV-2 variants that circulated before (B.1.*), during (Gamma), and after (Delta and Omicron) the second epidemic wave in Brazil. All individuals had milder or no symptoms after reinfection, and none required hospitalization. These findings demonstrate that individuals reinfected with the VOC Gamma may display relatively high RNA viral loads at the upper respiratory tract after reinfection, thus contributing to onward viral transmissions. Despite this, our study points to a low overall risk of severe Gamma reinfections, supporting that the abrupt increase in hospital admissions and deaths observed in Amazonas and other Brazilian states during the Gamma wave was mostly driven by primary infections. Our findings also indicate that most individuals analyzed developed a high anti-SARS-CoV-2 NAb response after reinfection that may provide some protection against reinfection or disease by different SARS-CoV-2 variants.
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Affiliation(s)
- Felipe Gomes Naveca
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil.
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Rio de Janeiro, Brazil.
| | - Valdinete Alves Nascimento
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Fernanda Nascimento
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Maria Ogrzewalska
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Alex Pauvolid-Corrêa
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
| | - Mia Ferreira Araújo
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Ighor Arantes
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
- Laboratório de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | | | | | | | - Tirza Peixoto Mattos
- Laboratório Central de Saúde Pública do Amazonas (LACEN-AM, Manaus, Amazonas, Brazil
| | - Irina Riediger
- Laboratório Central de Saúde Pública do Paraná (LACEN-PR) Curitiba, Paraná, Brazil
| | - Maria do Carmo Debur
- Laboratório Central de Saúde Pública do Paraná (LACEN-PR) Curitiba, Paraná, Brazil
| | - Beatriz Grinsztejn
- Instituto Nacional de Infectologia Evandro Chagas (INI), Fiocruz, Rio de Janeiro, Brazil
| | - Valdiléa G Veloso
- Instituto Nacional de Infectologia Evandro Chagas (INI), Fiocruz, Rio de Janeiro, Brazil
| | - Patrícia Brasil
- Instituto Nacional de Infectologia Evandro Chagas (INI), Fiocruz, Rio de Janeiro, Brazil
| | | | - Darcita Buerger Rovaris
- Laboratório Central de Saúde Pública do Estado de Santa Catarina (LACEN-SC), Florianópolis, Santa Catarina, Brazil
| | - Sandra Bianchini Fernandes
- Laboratório Central de Saúde Pública do Estado de Santa Catarina (LACEN-SC), Florianópolis, Santa Catarina, Brazil
| | - Cristiano Fernandes
- Fundação de Vigilância em Saúde do Amazonas-Dra Rosemary Costa Pinto, Manaus, Amazonas, Brazil
| | | | | | | | - Marineide Silva
- Laboratório Central de Saúde Pública do Amazonas (LACEN-AM, Manaus, Amazonas, Brazil
| | - Victor Souza
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Ágatha Araújo Costa
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Matilde Mejía
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Maria Júlia Brandão
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Luciana Fé Gonçalves
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
- Fundação de Vigilância em Saúde do Amazonas-Dra Rosemary Costa Pinto, Manaus, Amazonas, Brazil
| | - George Allan Silva
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Michele Silva de Jesus
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Karina Pessoa
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - André de Lima Guerra Corado
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Debora Camila Gomes Duarte
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Ana Beatriz Machado
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Ketiuce de Azevedo Zukeram
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Natalia Valente
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Renata Serrano Lopes
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Elisa Cavalcante Pereira
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Luciana Reis Appolinario
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Alice Sampaio Rocha
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Luis Fernando Lopez Tort
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
- CENUR Litoral Norte, Universidad de la República, Salto, Uruguay
| | - Tsuyoshi Sekizuka
- Pathogen Genomics Center, National Institute of Infectious Diseases, 1-23-1 Toyama, Shinjuku-Ku, Tokyo, 162-8640, Japan
| | - Kentaro Itokawa
- Pathogen Genomics Center, National Institute of Infectious Diseases, 1-23-1 Toyama, Shinjuku-Ku, Tokyo, 162-8640, Japan
| | - Masanori Hashino
- Pathogen Genomics Center, National Institute of Infectious Diseases, 1-23-1 Toyama, Shinjuku-Ku, Tokyo, 162-8640, Japan
| | - Makoto Kuroda
- Pathogen Genomics Center, National Institute of Infectious Diseases, 1-23-1 Toyama, Shinjuku-Ku, Tokyo, 162-8640, Japan
| | | | - Gabriel Luz Wallau
- Instituto Aggeu Magalhães, Fundação Oswaldo Cruz, Recife, Pernambuco, Brazil
| | - Edson Delatorre
- Departamento de Biologia, Centro de Ciências Exatas, Naturais e da Saúde, Universidade Federal do Espírito Santo, Alegre, Brazil
| | - Tiago Gräf
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Marilda Mendonça Siqueira
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Gonzalo Bello
- Laboratório de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - Paola Cristina Resende
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
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High-depth sequencing characterization of viral dynamics across tissues in fatal COVID-19 reveals compartmentalized infection. Nat Commun 2023; 14:574. [PMID: 36732505 PMCID: PMC9894515 DOI: 10.1038/s41467-022-34256-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 10/17/2022] [Indexed: 02/04/2023] Open
Abstract
SARS-CoV-2 distribution and circulation dynamics are not well understood due to challenges in assessing genomic data from tissue samples. We develop experimental and computational workflows for high-depth viral sequencing and high-resolution genomic analyses from formalin-fixed, paraffin-embedded tissues and apply them to 120 specimens from six subjects with fatal COVID-19. To varying degrees, viral RNA is present in extrapulmonary tissues from all subjects. The majority of the 180 viral variants identified within subjects are unique to individual tissue samples. We find more high-frequency (>10%) minor variants in subjects with a longer disease course, with one subject harboring ten such variants, exclusively in extrapulmonary tissues. One tissue-specific high-frequency variant was a nonsynonymous mutation in the furin-cleavage site of the spike protein. Our findings suggest adaptation and/or compartmentalized infection, illuminating the basis of extrapulmonary COVID-19 symptoms and potential for viral reservoirs, and have broad utility for investigating human pathogens.
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Kimbrel J, Moon J, Avila-Herrera A, Martí JM, Thissen J, Mulakken N, Sandholtz SH, Ferrell T, Daum C, Hall S, Segelke B, Arrildt KT, Messenger S, Wadford DA, Jaing C, Allen JE, Borucki MK. Multiple Mutations Associated with Emergent Variants Can Be Detected as Low-Frequency Mutations in Early SARS-CoV-2 Pandemic Clinical Samples. Viruses 2022; 14:v14122775. [PMID: 36560780 PMCID: PMC9788161 DOI: 10.3390/v14122775] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 08/23/2022] [Accepted: 12/06/2022] [Indexed: 12/15/2022] Open
Abstract
Genetic analysis of intra-host viral populations provides unique insight into pre-emergent mutations that may contribute to the genotype of future variants. Clinical samples positive for SARS-CoV-2 collected in California during the first months of the pandemic were sequenced to define the dynamics of mutation emergence as the virus became established in the state. Deep sequencing of 90 nasopharyngeal samples showed that many mutations associated with the establishment of SARS-CoV-2 globally were present at varying frequencies in a majority of the samples, even those collected as the virus was first detected in the US. A subset of mutations that emerged months later in consensus sequences were detected as subconsensus members of intra-host populations. Spike mutations P681H, H655Y, and V1104L were detected prior to emergence in variant genotypes, mutations were detected at multiple positions within the furin cleavage site, and pre-emergent mutations were identified in the nucleocapsid and the envelope genes. Because many of the samples had a very high depth of coverage, a bioinformatics pipeline, "Mappgene", was established that uses both iVar and LoFreq variant calling to enable identification of very low-frequency variants. This enabled detection of a spike protein deletion present in many samples at low frequency and associated with a variant of concern.
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Affiliation(s)
- Jeffrey Kimbrel
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Joseph Moon
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | | | | | - James Thissen
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Nisha Mulakken
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | | | - Tyshawn Ferrell
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Chris Daum
- Lawrence Berkeley National Laboratory, US Department of Energy Joint Genome Institute, Berkeley, CA 94720, USA
| | - Sara Hall
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Brent Segelke
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | | | - Sharon Messenger
- Viral and Rickettsial Disease Laboratory, California Department of Public Health, Richmond, CA 94804, USA
| | - Debra A. Wadford
- Viral and Rickettsial Disease Laboratory, California Department of Public Health, Richmond, CA 94804, USA
| | - Crystal Jaing
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | | | - Monica K. Borucki
- Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
- Correspondence:
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Roder AE, Johnson KEE, Knoll M, Khalfan M, Wang B, Schultz-Cherry S, Banakis S, Kreitman A, Mederos C, Youn JH, Mercado R, Wang W, Ruchnewitz D, Samanovic MI, Mulligan MJ, Lassig M, Łuksza M, Das S, Gresham D, Ghedin E. Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2021.05.05.442873. [PMID: 36656775 PMCID: PMC9836620 DOI: 10.1101/2021.05.05.442873] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller, and use of replicate sequencing have the most significant impact on single nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false negative rates. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intrahost viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intrahost variation, viral diversity, and viral evolution. IMPORTANCE When viruses replicate inside a host, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus, nor strongly beneficial, can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in inclusion of false positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant calling tools. We used simulated and synthetic data to test their performance against a true set of variants, and then used these studies to inform variant identification in data from clinical SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.
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Focosi D, Franchini M. Potential use of convalescent plasma for SARS-CoV-2 prophylaxis and treatment in immunocompromised and vulnerable populations. Expert Rev Vaccines 2022; 21:877-884. [PMID: 34015243 PMCID: PMC8171015 DOI: 10.1080/14760584.2021.1932475] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Accepted: 05/17/2021] [Indexed: 12/21/2022]
Abstract
INTRODUCTION : The ongoing SARS-CoV-2 pandemic is a serious threat for the health of immunocompromised patients. Among neutralizing antibody-based therapeutics, convalescent plasma containing polyclonal anti-SARS-CoV-2 immunoglobulins has promising results in both congenital and iatrogenic immunodeficiencies in oncohematological and transplant patients. AREAS COVERED : This article discusses case reports, case series and controlled studies detailing the efficacy of convalescent plasma in immunocompromised patients. EXPERT OPINION : Convalescent plasma, when administered at high neutralizing antibody titers, is a safe and effective treatment for frail immunocompromised patients. Genetic monitoring of refractory patients is recommended to intercept intra-host emergence of SARS-CoV-2 variants.
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Affiliation(s)
- Daniele Focosi
- North-Western Tuscany Blood Bank, Pisa University Hospital, Pisa, Italy
| | - Massimo Franchini
- Department of Hematology and Transfusion Medicine, Carlo Poma Hospital, Mantua, Italy
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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: 10] [Impact Index Per Article: 3.3] [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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9
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Cobey S, Larremore DB, Grad YH, Lipsitch M. Concerns about SARS-CoV-2 evolution should not hold back efforts to expand vaccination. Nat Rev Immunol 2021; 21:330-335. [PMID: 33795856 PMCID: PMC8014893 DOI: 10.1038/s41577-021-00544-9] [Citation(s) in RCA: 70] [Impact Index Per Article: 23.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/22/2021] [Indexed: 12/18/2022]
Abstract
When vaccines are in limited supply, expanding the number of people who receive some vaccine, such as by halving doses or increasing the interval between doses, can reduce disease and mortality compared with concentrating available vaccine doses in a subset of the population. A corollary of such dose-sparing strategies is that the vaccinated individuals may have less protective immunity. Concerns have been raised that expanding the fraction of the population with partial immunity to SARS-CoV-2 could increase selection for vaccine-escape variants, ultimately undermining vaccine effectiveness. We argue that, although this is possible, preliminary evidence instead suggests such strategies should slow the rate of viral escape from vaccine or naturally induced immunity. As long as vaccination provides some protection against escape variants, the corresponding reduction in prevalence and incidence should reduce the rate at which new variants are generated and the speed of adaptation. Because there is little evidence of efficient immune selection of SARS-CoV-2 during typical infections, these population-level effects are likely to dominate vaccine-induced evolution.
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Affiliation(s)
- Sarah Cobey
- Department of Ecology and Evolution, University of Chicago, Chicago, IL, USA.
| | - Daniel B Larremore
- Department of Computer Science, University of Colorado Boulder, Boulder, CO, USA
- BioFrontiers Institute, University of Colorado Boulder, Boulder, CO, USA
| | - Yonatan H Grad
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Marc Lipsitch
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
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10
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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: 210] [Impact Index Per Article: 70.0] [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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11
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Martin MA, Koelle K. Reanalysis of deep-sequencing data from Austria points towards a small SARS-COV-2 transmission bottleneck on the order of one to three virions.. [PMID: 0 DOI: 10.1101/2021.02.22.432096] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/26/2023]
Abstract
An early analysis of SARS-CoV-2 deep-sequencing data that combined epidemiological and genetic data to characterize the transmission dynamics of the virus in and beyond Austria concluded that the size of the virus’s transmission bottleneck was large – on the order of 1000 virions. We performed new computational analyses using these deep-sequenced samples from Austria. Our analyses included characterization of transmission bottleneck sizes across a range of variant calling thresholds and examination of patterns of shared low-frequency variants between transmission pairs in cases where de novo genetic variation was present in the recipient. From these analyses, among others, we found that SARS-CoV-2 transmission bottlenecks are instead likely to be very tight, on the order of 1-3 virions. These findings have important consequences for understanding how SARS-CoV-2 evolves between hosts and the processes shaping genetic variation observed at the population level.
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