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Van Dusen J, LeBlanc H, Nastasi N, Panescu J, Shamblin A, Smith JW, Sovic MG, Williams A, Quam MBM, Faith S, Dannemiller KC. Identification of SARS-CoV-2 variants in indoor dust. PLoS One 2024; 19:e0297172. [PMID: 38335205 PMCID: PMC10857703 DOI: 10.1371/journal.pone.0297172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 12/30/2023] [Indexed: 02/12/2024] Open
Abstract
Environmental surveillance of pathogens underlying infectious disease is critical to ensure public health. Recent efforts to track SARS-CoV-2 have utilized wastewater sampling to infer community trends in viral abundance and variant composition. Indoor dust has also been used for building-level inferences, though to date no sequencing data providing variant-scale resolution have been reported from dust samples, and strategies to monitor circulating variants in dust are needed to help inform public health decisions. In this study, we demonstrate that SARS-CoV-2 lineages can be detected and sequenced from indoor bulk dust samples. We collected 93 vacuum bags from April 2021 to March 2022 from buildings on The Ohio State University's (OSU) Columbus campus, and the dust was used to develop and apply an amplicon-based whole-genome sequencing protocol to identify the variants present and estimate their relative abundances. Three variants of concern were detected in the dust: Alpha, Delta, and Omicron. Alpha was found in our earliest sample in April 2021 with an estimated frequency of 100%. Delta was the primary variant present from October of 2021 to January 2022, with an average estimated frequency of 91% (±1.3%). Omicron became the primary variant in January 2022 and was the dominant strain in circulation through March with an estimated frequency of 87% (±3.2%). The detection of these variants on OSU's campus correlates with the circulation of these variants in the surrounding population (Delta p<0.0001 and Omicron p = 0.02). Overall, these results support the hypothesis that dust can be used to track COVID-19 variants in buildings.
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Affiliation(s)
- John Van Dusen
- Department of Microbiology, College of Arts and Sciences, The Ohio State University, Columbus, Ohio, United States of America
| | - Haley LeBlanc
- Genetic Counseling Program, College of Biological Sciences, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Nicholas Nastasi
- Environmental Sciences Graduate Program, The Ohio State University, Columbus, Ohio, United States of America
- Department of Civil, Environmental & Geodetic Engineering, College of Engineering, The Ohio State University, Columbus, Ohio, United States of America
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America
| | - Jenny Panescu
- Department of Civil, Environmental & Geodetic Engineering, College of Engineering, The Ohio State University, Columbus, Ohio, United States of America
| | - Austin Shamblin
- Applied Microbiology Services Lab, The Ohio State University, Columbus, Ohio, United States of America
| | - Jacob W. Smith
- Department of Chemistry and Biochemistry, College of Arts and Sciences, The Ohio State University, Columbus, Ohio, United States of America
| | - Michael G. Sovic
- Applied Microbiology Services Lab, The Ohio State University, Columbus, Ohio, United States of America
- Infectious Diseases Institute, The Ohio State University, Columbus, Ohio, United States of America
| | - Amanda Williams
- Institute for Genomic Medicine, Nationwide Children’s Hospital, Columbus, Ohio, United States of America
| | - Mikkel B. M. Quam
- Infectious Diseases Institute, The Ohio State University, Columbus, Ohio, United States of America
- Division of Epidemiology, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America
- Section of Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Seth Faith
- Applied Microbiology Services Lab, The Ohio State University, Columbus, Ohio, United States of America
- Infectious Diseases Institute, The Ohio State University, Columbus, Ohio, United States of America
| | - Karen C. Dannemiller
- Department of Civil, Environmental & Geodetic Engineering, College of Engineering, The Ohio State University, Columbus, Ohio, United States of America
- Division of Environmental Health Sciences, College of Public Health, The Ohio State University, Columbus, Ohio, United States of America
- Sustainability Institute, The Ohio State University, Columbus, Ohio, United States of America
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2
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Adediran T, Zawitz C, Piriani A, Bendict E, Thiede S, Barbian H, Aroutcheva A, Green SJ, Welbel S, Weinstein RA, Snitkin E, Popovich KJ. Genomic Epidemiology of Severe Acute Respiratory Syndrome Coronavirus 2 in a County Jail. Open Forum Infect Dis 2024; 11:ofad675. [PMID: 38379564 PMCID: PMC10878058 DOI: 10.1093/ofid/ofad675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 12/21/2023] [Indexed: 02/22/2024] Open
Abstract
Background In the coronavirus disease 2019 (COVID-19) pandemic, correctional facilities are potential hotspots for transmission. We examined the genomic epidemiology of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) early in the pandemic in one of the country's largest urban jails. Methods Existing SARS-CoV-2 isolates from 131 detainees at the Cook County Jail in Chicago, Illinois, from March 2020 through May 2020 were analyzed by whole-genome sequencing. Contemporaneous isolates from Rush University Medical Center (Chicago, Illinois) and the Global Initiative on Sharing All Influenza Data (GISAID) were used to identify genetic clusters containing only jail isolates. Transmission windows were identified for each pair of detainees using the date of the SARS-CoV-2-positive test and location data to determine if detainees overlapped in the jail, within a specific building, or within particular living units during transmission windows. Results We identified 29 jail-only clusters that contained 75 of the 132 SARS-CoV-2 isolates from detainees; of these clusters, 17 (58.6%) had individuals who overlapped in the jail during putative transmission windows. Focusing on specific buildings revealed that 2 buildings, a single- and double-cell style of housing. were associated with having detainees infected with similar SARS-CoV-2 genomes during their infectious time period (P < .001). Conclusions Our findings suggest that there was transmission of SARS-CoV-2 in the jail, in the setting of extensive importation of COVID-19 from the community. Numerous infection control practices at intake and during incarceration were implemented in the jail to limit viral spread. Our study shows the importance of genomic analysis in this type of settings and how it can be utilized within infection control protocols.
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Affiliation(s)
- Timileyin Adediran
- Department of Microbiology and Immunology, University of Michigan School of Medicine, Ann Arbor, Michigan, USA
| | - Chad Zawitz
- Cermak Health Services of Cook County, Chicago, Illinois, USA
- Cook County Health, Chicago, Illinois, USA
| | - Ali Piriani
- Department of Microbiology and Immunology, University of Michigan School of Medicine, Ann Arbor, Michigan, USA
| | - Emily Bendict
- Department of Microbiology and Immunology, University of Michigan School of Medicine, Ann Arbor, Michigan, USA
| | - Stephanie Thiede
- Department of Microbiology and Immunology, University of Michigan School of Medicine, Ann Arbor, Michigan, USA
| | - Hannah Barbian
- Division of Infectious Diseases, Department of Internal Medicine, Rush Medical College, Chicago, Illinois, USA
| | | | - Stefan J Green
- Division of Infectious Diseases, Department of Internal Medicine, Rush Medical College, Chicago, Illinois, USA
| | | | - Robert A Weinstein
- Cook County Health, Chicago, Illinois, USA
- Division of Infectious Diseases, Department of Internal Medicine, Rush Medical College, Chicago, Illinois, USA
| | - Evan Snitkin
- Department of Microbiology and Immunology, University of Michigan School of Medicine, Ann Arbor, Michigan, USA
| | - Kyle J Popovich
- Cook County Health, Chicago, Illinois, USA
- Division of Infectious Diseases, Department of Internal Medicine, Rush Medical College, Chicago, Illinois, USA
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3
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Ma W, Shi L, Li M. A fast and accurate method for SARS-CoV-2 genomic tracing. Brief Bioinform 2023; 24:bbad339. [PMID: 37779249 DOI: 10.1093/bib/bbad339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Revised: 09/04/2023] [Accepted: 09/07/2023] [Indexed: 10/03/2023] Open
Abstract
To contain infectious diseases, it is crucial to determine the origin and transmission routes of the pathogen, as well as how the virus evolves. With the development of genome sequencing technology, genome epidemiology has emerged as a powerful approach for investigating the source and transmission of pathogens. In this study, we first presented the rationale for genomic tracing of SARS-CoV-2 and the challenges we currently face. Identifying the most genetically similar reference sequence to the query sequence is a critical step in genome tracing, typically achieved using either a phylogenetic tree or a sequence similarity search. However, these methods become inefficient or computationally prohibitive when dealing with tens of millions of sequences in the reference database, as we encountered during the COVID-19 pandemic. To address this challenge, we developed a novel genomic tracing algorithm capable of processing 6 million SARS-CoV-2 sequences in less than a minute. Instead of constructing a giant phylogenetic tree, we devised a weighted scoring system based on mutation characteristics to quantify sequences similarity. The developed method demonstrated superior performance compared to previous methods. Additionally, an online platform was developed to facilitate genomic tracing and visualization of the spatiotemporal distribution of sequences. The method will be a valuable addition to standard epidemiological investigations, enabling more efficient genomic tracing. Furthermore, the computational framework can be easily adapted to other pathogens, paving the way for routine genomic tracing of infectious diseases.
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Affiliation(s)
- Wentai Ma
- Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Leisheng Shi
- Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Mingkun Li
- Beijing Institute of Genomics, Chinese Academy of Sciences, and China National Center for Bioinformation, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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4
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Tiezzi C, Vecchi A, Rossi M, Cavazzini D, Bolchi A, Laccabue D, Doselli S, Penna A, Sacchelli L, Brillo F, Meschi T, Ticinesi A, Nouvenne A, Donofrio G, Zanelli P, Benecchi M, Giuliodori S, Fisicaro P, Montali I, Ceccatelli Berti C, Reverberi V, Montali A, Urbani S, Pedrazzi G, Missale G, Telenti A, Corti D, Ottonello S, Ferrari C, Boni C. Natural heteroclitic-like peptides are generated by SARS-CoV-2 mutations. iScience 2023; 26:106940. [PMID: 37275517 PMCID: PMC10200277 DOI: 10.1016/j.isci.2023.106940] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 04/13/2023] [Accepted: 05/18/2023] [Indexed: 06/07/2023] Open
Abstract
Humoral immunity is sensitive to evasion by SARS-CoV-2 mutants, but CD8 T cells seem to be more resistant to mutational inactivation. By a systematic analysis of 30 spike variant peptides containing the most relevant VOC and VOI mutations that have accumulated overtime, we show that in vaccinated and convalescent subjects, mutated epitopes can have not only a neutral or inhibitory effect on CD8 T cell recognition but can also enhance or generate de novo CD8 T cell responses. The emergence of these mutated T cell function enhancing epitopes likely reflects an epiphenomenon of SARS-CoV-2 evolution driven by antibody evasion and increased virus transmissibility. In a subset of individuals with weak and narrowly focused CD8 T cell responses selection of these heteroclitic-like epitopes may bear clinical relevance by improving antiviral protection. The functional enhancing effect of these peptides is also worth of consideration for the future development of new generation, more potent COVID-19 vaccines.
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Affiliation(s)
- Camilla Tiezzi
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Andrea Vecchi
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Marzia Rossi
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Davide Cavazzini
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy
| | - Angelo Bolchi
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy
- Interdepartmental Center Biopharmanet-Tec, University of Parma, Parma, Italy
| | - Diletta Laccabue
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Sara Doselli
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Amalia Penna
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Luca Sacchelli
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Federica Brillo
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Tiziana Meschi
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Geriatric-Rehabilitation Department, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Andrea Ticinesi
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Geriatric-Rehabilitation Department, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Antonio Nouvenne
- Geriatric-Rehabilitation Department, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Gaetano Donofrio
- Department of Veterinary Science, University of Parma, Parma, Italy
| | - Paola Zanelli
- Unità di Immunogenetica dei Trapianti, Azienda Ospedaliero Universitaria di Parma, Parma, Italy
| | - Magda Benecchi
- Unità di Immunogenetica dei Trapianti, Azienda Ospedaliero Universitaria di Parma, Parma, Italy
| | - Silvia Giuliodori
- Unità di Immunogenetica dei Trapianti, Azienda Ospedaliero Universitaria di Parma, Parma, Italy
| | - Paola Fisicaro
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Ilaria Montali
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | | | - Valentina Reverberi
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Anna Montali
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Simona Urbani
- UO Immunoematologia e Medicina Trasfusionale, Dipartimento Diagnostico, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Giuseppe Pedrazzi
- Department of Neuroscience - Biophysics and Medical Physics Unit, University of Parma, Parma, Italy
| | - Gabriele Missale
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | | | - Davide Corti
- Humabs Biomed SA, a subsidiary of Vir Biotechnology, Bellinzona, Switzerland
| | - Simone Ottonello
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy
- Interdepartmental Center Biopharmanet-Tec, University of Parma, Parma, Italy
| | - Carlo Ferrari
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Carolina Boni
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda Ospedaliero-Universitaria di Parma, Parma, Italy
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5
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Gill IS, Griffiths EJ, Dooley D, Cameron R, Savić Kallesøe S, John NS, Sehar A, Gosal G, Alexander D, Chapel M, Croxen MA, Delisle B, Di Tullio R, Gaston D, Duggan A, Guthrie JL, Horsman M, Joshi E, Kearny L, Knox N, Lau L, LeBlanc JJ, Li V, Lyons P, MacKenzie K, McArthur AG, Panousis EM, Palmer J, Prystajecky N, Smith KN, Tanner J, Townend C, Tyler A, Van Domselaar G, Hsiao WWL. The DataHarmonizer: a tool for faster data harmonization, validation, aggregation and analysis of pathogen genomics contextual information. Microb Genom 2023; 9:mgen000908. [PMID: 36748616 PMCID: PMC9973856 DOI: 10.1099/mgen.0.000908] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 10/11/2022] [Indexed: 01/25/2023] Open
Abstract
Pathogen genomics is a critical tool for public health surveillance, infection control, outbreak investigations as well as research. In order to make use of pathogen genomics data, they must be interpreted using contextual data (metadata). Contextual data include sample metadata, laboratory methods, patient demographics, clinical outcomes and epidemiological information. However, the variability in how contextual information is captured by different authorities and how it is encoded in different databases poses challenges for data interpretation, integration and their use/re-use. The DataHarmonizer is a template-driven spreadsheet application for harmonizing, validating and transforming genomics contextual data into submission-ready formats for public or private repositories. The tool's web browser-based JavaScript environment enables validation and its offline functionality and local installation increases data security. The DataHarmonizer was developed to address the data sharing needs that arose during the COVID-19 pandemic, and was used by members of the Canadian COVID Genomics Network (CanCOGeN) to harmonize SARS-CoV-2 contextual data for national surveillance and for public repository submission. In order to support coordination of international surveillance efforts, we have partnered with the Public Health Alliance for Genomic Epidemiology to also provide a template conforming to its SARS-CoV-2 contextual data specification for use worldwide. Templates are also being developed for One Health and foodborne pathogens. Overall, the DataHarmonizer tool improves the effectiveness and fidelity of contextual data capture as well as its subsequent usability. Harmonization of contextual information across authorities, platforms and systems globally improves interoperability and reusability of data for concerted public health and research initiatives to fight the current pandemic and future public health emergencies. While initially developed for the COVID-19 pandemic, its expansion to other data management applications and pathogens is already underway.
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Affiliation(s)
- Ivan S. Gill
- University of British Columbia, Vancouver, BC, Canada
| | - Emma J. Griffiths
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | - Damion Dooley
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | - Rhiannon Cameron
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | | | - Nithu Sara John
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | - Anoosha Sehar
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | - Gurinder Gosal
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
| | | | - Madison Chapel
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Matthew A. Croxen
- Alberta Precision Labs, Edmonton, AB, Canada
- Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada
| | | | | | - Daniel Gaston
- Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, NS, Canada
| | - Ana Duggan
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | | | - Mark Horsman
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
- Public Health Ontario Laboratory, Toronto, ON, Canada
| | - Esha Joshi
- Public Health Ontario Laboratory, Toronto, ON, Canada
| | - Levon Kearny
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Natalie Knox
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Lynette Lau
- The Hospital for Sick Children, Toronto, ON, Canada
| | - Jason J. LeBlanc
- Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, NS, Canada
| | - Vincent Li
- Alberta Precision Labs, Edmonton, AB, Canada
| | - Pierre Lyons
- Public Health Agency of Canada, Moncton, NB, Canada
| | | | - Andrew G. McArthur
- Michael G. DeGroote Institute for Infectious Disease Research & Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - Emily M. Panousis
- Michael G. DeGroote Institute for Infectious Disease Research & Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada
| | - John Palmer
- Public Health Ontario Laboratory, Toronto, ON, Canada
| | - Natalie Prystajecky
- University of British Columbia, Vancouver, BC, Canada
- BCCDC Public Health Laboratory, Vancouver, BC, Canada
| | | | - Jennifer Tanner
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Christopher Townend
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Andrea Tyler
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - Gary Van Domselaar
- National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, MB, Canada
| | - William W. L. Hsiao
- University of British Columbia, Vancouver, BC, Canada
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
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6
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Viral Dynamic Surveillance in COVID-19 Patients: A Cohort Study. BIOMED RESEARCH INTERNATIONAL 2022; 2022:1399268. [PMID: 36033569 PMCID: PMC9417765 DOI: 10.1155/2022/1399268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Accepted: 08/03/2022] [Indexed: 11/18/2022]
Abstract
Background. Coronavirus disease 2019 (COVID-19) is a potentially fatal pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), especially those of novel SARS-CoV-2 variants and infection has affected over 700 million people globally. Methods. This retrospective, descriptive study included 118 patients admitted with SARS-CoV-2 infection as confirmed by real-time reverse transcription polymerase chain reaction. Results. The median duration of detectable SARS-CoV-2 infection in patients with high ALT, AST, and PLT/LYMPH, or low CD4+, CD8+, and PLT/MONO was considerably longer. In the risk factor model, multivariate analysis was performed for the estimation of ALT (HR, 0.54; 95% CI, 0.36-0.81), AST (HR, 0.56; 95% CI, 0.34-0.93), CD4+ (HR,0.77; 95% CI, 0.48-1.24), CD8+ (HR,0.64; 95% CI, 0.37-1.11), PLT/LYMPH (HR, 1.16; 95% CI, 0.76-1.77), and PLT/MONO (HR, 0.64; 95% CI, 0.43-0.94). Conclusions. The longer viral RNA duration was associated with a higher International Prognostic Index score (
), demonstrating for the first time that multivariate features of the bioindicators closely associated with SARS-CoV-2-infected patients clear the virus.
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7
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Li J, Jia H, Tian M, Wu N, Yang X, Qi J, Ren W, Li F, Bian H. SARS-CoV-2 and Emerging Variants: Unmasking Structure, Function, Infection, and Immune Escape Mechanisms. Front Cell Infect Microbiol 2022; 12:869832. [PMID: 35646741 PMCID: PMC9134119 DOI: 10.3389/fcimb.2022.869832] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Accepted: 04/06/2022] [Indexed: 12/24/2022] Open
Abstract
As of April 1, 2022, over 468 million COVID-19 cases and over 6 million deaths have been confirmed globally. Unlike the common coronavirus, SARS-CoV-2 has highly contagious and attracted a high level of concern worldwide. Through the analysis of SARS-CoV-2 structural, non-structural, and accessory proteins, we can gain a deeper understanding of structure-function relationships, viral infection mechanisms, and viable strategies for antiviral therapy. Angiotensin-converting enzyme 2 (ACE2) is the first widely acknowledged SARS-CoV-2 receptor, but researches have shown that there are additional co-receptors that can facilitate the entry of SARS-CoV-2 to infect humans. We have performed an in-depth review of published papers, searching for co-receptors or other auxiliary membrane proteins that enhance viral infection, and analyzing pertinent pathogenic mechanisms. The genome, and especially the spike gene, undergoes mutations at an abnormally high frequency during virus replication and/or when it is transmitted from one individual to another. We summarized the main mutant strains currently circulating global, and elaborated the structural feature for increased infectivity and immune evasion of variants. Meanwhile, the principal purpose of the review is to update information on the COVID-19 outbreak. Many countries have novel findings on the early stage of the epidemic, and accruing evidence has rewritten the timeline of the outbreak, triggering new thinking about the origin and spread of COVID-19. It is anticipated that this can provide further insights for future research and global epidemic prevention and control.
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Affiliation(s)
| | | | | | | | | | | | | | - Feifei Li
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Hongjun Bian
- Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China
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8
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Guo L, Boocock J, Hilt EE, Chandrasekaran S, Zhang Y, Munugala C, Sathe L, Alexander N, Arboleda VA, Flint J, Eskin E, Luo C, Yang S, Garner OB, Yin Y, Bloom JS, Kruglyak L. Genomic epidemiology of the Los Angeles COVID-19 outbreak and the early history of the B.1.43 strain in the USA. BMC Genomics 2022; 23:260. [PMID: 35379194 PMCID: PMC8978495 DOI: 10.1186/s12864-022-08488-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 03/15/2022] [Indexed: 11/10/2022] Open
Abstract
Background The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused global disruption of human health and activity. Being able to trace the early outbreak of SARS-CoV-2 within a locality can inform public health measures and provide insights to contain or prevent viral transmission. Investigation of the transmission history requires efficient sequencing methods and analytic strategies, which can be generally useful in the study of viral outbreaks. Methods The County of Los Angeles (hereafter, LA County) sustained a large outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To learn about the transmission history, we carried out surveillance viral genome sequencing to determine 142 viral genomes from unique patients seeking care at the University of California, Los Angeles (UCLA) Health System. 86 of these genomes were from samples collected before April 19, 2020. Results We found that the early outbreak in LA County, as in other international air travel hubs, was seeded by multiple introductions of strains from Asia and Europe. We identified a USA-specific strain, B.1.43, which was found predominantly in California and Washington State. While samples from LA County carried the ancestral B.1.43 genome, viral genomes from neighboring counties in California and from counties in Washington State carried additional mutations, suggesting a potential origin of B.1.43 in Southern California. We quantified the transmission rate of SARS-CoV-2 over time, and found evidence that the public health measures put in place in LA County to control the virus were effective at preventing transmission, but might have been undermined by the many introductions of SARS-CoV-2 into the region. Conclusion Our work demonstrates that genome sequencing can be a powerful tool for investigating outbreaks and informing the public health response. Our results reinforce the critical need for the USA to have coordinated inter-state responses to the pandemic. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-022-08488-7.
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Affiliation(s)
- Longhua Guo
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA.,Howard Hughes Medical Institute, HHMI, Chevy Chase, USA.,Department of Biological Chemistry, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - James Boocock
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA.,Howard Hughes Medical Institute, HHMI, Chevy Chase, USA.,Department of Biological Chemistry, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Evann E Hilt
- Department of Pathology & Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Sukantha Chandrasekaran
- Department of Pathology & Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Yi Zhang
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Chetan Munugala
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Laila Sathe
- Department of Pathology & Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Noah Alexander
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Valerie A Arboleda
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA.,Department of Pathology & Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Jonathan Flint
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA.,Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Eleazar Eskin
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA.,Department of Computer Science, Samueli School of Engineering, UCLA, Los Angeles, USA.,Department of Computational Medicine, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Chongyuan Luo
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Shangxin Yang
- Department of Pathology & Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Omai B Garner
- Department of Pathology & Laboratory Medicine, David Geffen School of Medicine, UCLA, Los Angeles, USA
| | - Yi Yin
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA.
| | - Joshua S Bloom
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA. .,Howard Hughes Medical Institute, HHMI, Chevy Chase, USA. .,Octant, Inc, Los Angeles, USA.
| | - Leonid Kruglyak
- Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, USA. .,Howard Hughes Medical Institute, HHMI, Chevy Chase, USA. .,Department of Biological Chemistry, David Geffen School of Medicine, UCLA, Los Angeles, USA.
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9
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Griffiths EJ, Timme RE, Mendes CI, Page AJ, Alikhan NF, Fornika D, Maguire F, Campos J, Park D, Olawoye IB, Oluniyi PE, Anderson D, Christoffels A, da Silva AG, Cameron R, Dooley D, Katz LS, Black A, Karsch-Mizrachi I, Barrett T, Johnston A, Connor TR, Nicholls SM, Witney AA, Tyson GH, Tausch SH, Raphenya AR, Alcock B, Aanensen DM, Hodcroft E, Hsiao WWL, Vasconcelos ATR, MacCannell DR. Future-proofing and maximizing the utility of metadata: The PHA4GE SARS-CoV-2 contextual data specification package. Gigascience 2022; 11:giac003. [PMID: 35169842 PMCID: PMC8847733 DOI: 10.1093/gigascience/giac003] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/15/2021] [Accepted: 01/07/2022] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The Public Health Alliance for Genomic Epidemiology (PHA4GE) (https://pha4ge.org) is a global coalition that is actively working to establish consensus standards, document and share best practices, improve the availability of critical bioinformatics tools and resources, and advocate for greater openness, interoperability, accessibility, and reproducibility in public health microbial bioinformatics. In the face of the current pandemic, PHA4GE has identified a need for a fit-for-purpose, open-source SARS-CoV-2 contextual data standard. RESULTS As such, we have developed a SARS-CoV-2 contextual data specification package based on harmonizable, publicly available community standards. The specification can be implemented via a collection template, as well as an array of protocols and tools to support both the harmonization and submission of sequence data and contextual information to public biorepositories. CONCLUSIONS Well-structured, rich contextual data add value, promote reuse, and enable aggregation and integration of disparate datasets. Adoption of the proposed standard and practices will better enable interoperability between datasets and systems, improve the consistency and utility of generated data, and ultimately facilitate novel insights and discoveries in SARS-CoV-2 and COVID-19. The package is now supported by the NCBI's BioSample database.
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Affiliation(s)
- Emma J Griffiths
- Faculty of Health Sciences, Simon Fraser University, Burnaby V5A 1S6, BC, Canada
| | - Ruth E Timme
- Center for Food Safety and Applied Nutrition, U.S. Food and Drug Administration, College Park, MD 20740, USA
| | - Catarina Inês Mendes
- Instituto de Microbiologia, Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Lisboa 1649-028, Portugal
| | - Andrew J Page
- Microbes in the Food Chain, Quadram Institute Bioscience, Norwich, Norfolk NR4 7UQ, UK
| | - Nabil-Fareed Alikhan
- Microbes in the Food Chain, Quadram Institute Bioscience, Norwich, Norfolk NR4 7UQ, UK
| | - Dan Fornika
- BC Centre for Disease Control Public Health Laboratory, Vancouver, BC V5Z 4R4, Canada
| | - Finlay Maguire
- Faculty of Computer Science, Dalhousie University, Halifax, NS B3H 1W5, Canada
| | - Josefina Campos
- INEI-ANLIS “Dr Carlos G. Malbrán,” Buenos Aires C1282AFF, Argentina
| | - Daniel Park
- Infectious Disease and Microbiome Program, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Idowu B Olawoye
- African Center of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State 232103, Nigeria
- Department of Biological Sciences, College of Natural Sciences, Redeemer's University, Ede, Osun State 232103, Nigeria
| | - Paul E Oluniyi
- African Center of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University, Ede, Osun State 232103, Nigeria
- Department of Biological Sciences, College of Natural Sciences, Redeemer's University, Ede, Osun State 232103, Nigeria
| | - Dominique Anderson
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville 7530, South Africa
| | - Alan Christoffels
- South African Medical Research Council Bioinformatics Unit, South African National Bioinformatics Institute, University of the Western Cape, Bellville 7530, South Africa
| | - Anders Gonçalves da Silva
- Microbiological Diagnostic Unit Public Health Laboratory, The Peter Doherty Institute for Infection and Immunity, The University of Melbourne, Melbourne, VIC 3000, Australia
| | - Rhiannon Cameron
- Faculty of Health Sciences, Simon Fraser University, Burnaby V5A 1S6, BC, Canada
| | - Damion Dooley
- Faculty of Health Sciences, Simon Fraser University, Burnaby V5A 1S6, BC, Canada
| | - Lee S Katz
- Center for Food Safety, University of Georgia, Atlanta, GA 30333, USA
- Office of Advanced Molecular Detection, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, GA 30333, USA
| | - Allison Black
- Department of Epidemiology, University of Washington, WA 98109, USA
| | - Ilene Karsch-Mizrachi
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Tanya Barrett
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Anjanette Johnston
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Thomas R Connor
- Organisms and Environment Division, School of Biosciences, Cardiff University, Cardiff CF10 3AX, UK
- Public Health Wales, University Hospital of Wales, Cardiff CF14 4XW, UK
| | | | - Adam A Witney
- Institute for Infection and Immunity, St George's, University of London, London SW17 0RE, UK
| | - Gregory H Tyson
- Center for Veterinary Medicine, U.S. Food and Drug Administration, Laurel, MD 20708, USA
| | - Simon H Tausch
- Department of Biological Safety, German Federal Institute for Risk Assessment, Berlin 12277, Germany
| | - Amogelang R Raphenya
- Department of Biochemistry and Biomedical Sciences and the Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - Brian Alcock
- Department of Biochemistry and Biomedical Sciences and the Michael G. DeGroote Institute for Infectious Disease Research, McMaster University, Hamilton, ON L8S 4L8, Canada
| | - David M Aanensen
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Cambridge CB10 1SA, UK
- The Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, UK
| | - Emma Hodcroft
- Biozentrum, University of Basel, Basel 3012, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - William W L Hsiao
- Faculty of Health Sciences, Simon Fraser University, Burnaby V5A 1S6, BC, Canada
- BC Centre for Disease Control Public Health Laboratory, Vancouver, BC V5Z 4R4, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC V6T 1Z7 V6T 1Z7, Canada
| | - Ana Tereza R Vasconcelos
- Bioinformatics Laboratory National Laboratory of Scientific Computation LNCC/MCTI, Petrópolis 25651-075, Brazil
| | - Duncan R MacCannell
- Office of Advanced Molecular Detection, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, GA 30333, USA
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10
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Aggarwal D, Myers R, Hamilton WL, Bharucha T, Tumelty NM, Brown CS, Meader EJ, Connor T, Smith DL, Bradley DT, Robson S, Bashton M, Shallcross L, Zambon M, Goodfellow I, Chand M, O'Grady J, Török ME, Peacock SJ, Page AJ. The role of viral genomics in understanding COVID-19 outbreaks in long-term care facilities. THE LANCET. MICROBE 2022; 3:e151-e158. [PMID: 34608459 PMCID: PMC8480962 DOI: 10.1016/s2666-5247(21)00208-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
We reviewed all genomic epidemiology studies on COVID-19 in long-term care facilities (LTCFs) that had been published to date. We found that staff and residents were usually infected with identical, or near identical, SARS-CoV-2 genomes. Outbreaks usually involved one predominant cluster, and the same lineages persisted in LTCFs despite infection control measures. Outbreaks were most commonly due to single or few introductions followed by a spread rather than a series of seeding events from the community into LTCFs. The sequencing of samples taken consecutively from the same individuals at the same facilities showed the persistence of the same genome sequence, indicating that the sequencing technique was robust over time. When combined with local epidemiology, genomics allowed probable transmission sources to be better characterised. The transmission between LTCFs was detected in multiple studies. The mortality rate among residents was high in all facilities, regardless of the lineage. Bioinformatics methods were inadequate in a third of the studies reviewed, and reproducing the analyses was difficult because sequencing data were not available in many facilities.
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Affiliation(s)
- Dinesh Aggarwal
- Department of Medicine, University of Cambridge, Cambridge, UK
- Public Health England, London, UK
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | | | - William L Hamilton
- Department of Medicine, University of Cambridge, Cambridge, UK
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
| | - Tehmina Bharucha
- Public Health England, London, UK
- Oxford Glycobiology Institute, Department of Biochemistry, University of Oxford, Oxford, UK
- Lao-Oxford-Mahosot Hospital, Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Laos
| | - Niamh M Tumelty
- Cambridge University Libraries, University of Cambridge, Cambridge, UK
| | - Colin S Brown
- Public Health England, London, UK
- Oxford Glycobiology Institute, Department of Biochemistry, University of Oxford, Oxford, UK
- Lao-Oxford-Mahosot Hospital, Wellcome Trust Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Laos
| | - Emma J Meader
- Norfolk and Norwich University Hospital, Norwich, UK
| | - Tom Connor
- Organisms and Environment Division, School of Biosciences, Cardiff University, Cardiff, Wales, UK
- Public Health Wales, University Hospital of Wales, Cardiff, UK
- Quadram Institute Bioscience, Norwich Research Park, Norwich, UK
| | - Darren L Smith
- Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Declan T Bradley
- Public Health Agency, Belfast, UK
- Centre for Public Health, Queen's University Belfast, Belfast, UK
| | - Samuel Robson
- University of Portsmouth, Centre for Enzyme Innovation, Portsmouth, UK
| | - Matthew Bashton
- Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Laura Shallcross
- Institute of Health Informatics, University College London, London, UK
| | | | - Ian Goodfellow
- Department of Pathology, University of Cambridge, Cambridge, UK
| | - Meera Chand
- Public Health England, London, UK
- Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Justin O'Grady
- Quadram Institute Bioscience, Norwich Research Park, Norwich, UK
| | - M Estée Török
- Department of Medicine, University of Cambridge, Cambridge, UK
- Cambridge University Hospital NHS Foundation Trust, Cambridge, UK
| | - Sharon J Peacock
- Department of Medicine, University of Cambridge, Cambridge, UK
- Wellcome Sanger Institute, Hinxton, Cambridge, UK
| | - Andrew J Page
- Quadram Institute Bioscience, Norwich Research Park, Norwich, UK
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11
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The Genomic Physics of COVID-19 Pathogenesis and Spread. Cells 2021; 11:cells11010080. [PMID: 35011641 PMCID: PMC8750765 DOI: 10.3390/cells11010080] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 12/19/2021] [Accepted: 12/23/2021] [Indexed: 12/11/2022] Open
Abstract
Coronavirus disease (COVID-19) spreads mainly through close contact of infected persons, but the molecular mechanisms underlying its pathogenesis and transmission remain unknown. Here, we propose a statistical physics model to coalesce all molecular entities into a cohesive network in which the roadmap of how each entity mediates the disease can be characterized. We argue that the process of how a transmitter transforms the virus into a recipient constitutes a triad unit that propagates COVID-19 along reticulate paths. Intrinsically, person-to-person transmissibility may be mediated by how genes interact transversely across transmitter, recipient, and viral genomes. We integrate quantitative genetic theory into hypergraph theory to code the main effects of the three genomes as nodes, pairwise cross-genome epistasis as edges, and high-order cross-genome epistasis as hyperedges in a series of mobile hypergraphs. Charting a genome-wide atlas of horizontally epistatic hypergraphs can facilitate the systematic characterization of the community genetic mechanisms underlying COVID-19 spread. This atlas can typically help design effective containment and mitigation strategies and screen and triage those more susceptible persons and those asymptomatic carriers who are incubation virus transmitters.
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12
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Stampfer SD, Goldwater MS, Bujarski S, Regidor B, Zhang W, Feinstein AJ, Swift R, Eshaghian S, Vail E, Berenson JR. Severe breakthrough COVID-19 with a heavily mutated variant in a multiple myeloma patient 10 weeks after vaccination. CLINICAL INFECTION IN PRACTICE 2021; 13:100130. [PMID: 34909634 PMCID: PMC8654462 DOI: 10.1016/j.clinpr.2021.100130] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 12/01/2021] [Accepted: 12/02/2021] [Indexed: 11/21/2022] Open
Abstract
Background Patients with multiple myeloma have unpredictable responses to vaccination for COVID-19. Anti-spike antibody levels can determine which patients develop antibodies at levels similar to healthy controls, and are a known correlate of protection. Case report A multiple myeloma patient developed protective anti-spike antibodies after vaccination (608 IU/mL), but nonetheless developed severe breakthrough COVID-19 just 10 weeks following his second vaccination with mRNA-1273. Results Sequencing of the viral isolate revealed an extensively mutated variant with 10 spike protein mutations, including E484Q and N440K. Serology testing showed a dramatic decline in anti-spike antibodies immediately prior to virus exposure. Conclusions Multiple myeloma patients who do develop detectable antibody responses to vaccination may be at increased risk for breakthrough infections due to rapid decline in antibody levels. Viral variants with immune escape mutations such as N440K, also seen independently in the SARS-CoV-2 Omicron variant (B.1.1.529) and in viral passaging experiments, likely require a higher level of anti-spike antibodies to prevent severe COVID-19.
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Affiliation(s)
- Samuel D Stampfer
- Division of Infectious Diseases, Department of Medicine, Emory University School of Medicine, 954 Gatewood Rd NE, Atlanta, GA 30329, USA
| | - Marissa-Skye Goldwater
- Institute for Myeloma and Bone Cancer Research, 9201 Sunset Blvd #300, West Hollywood, CA 90069, USA
| | - Sean Bujarski
- Institute for Myeloma and Bone Cancer Research, 9201 Sunset Blvd #300, West Hollywood, CA 90069, USA
| | - Bernard Regidor
- Berenson Cancer Center, 9201 Sunset Blvd #300, West Hollywood, CA 90069, USA
| | - Wenjuan Zhang
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, 8700 Beverly BLVD #2900A, Los Angeles, CA 90048, USA
| | - Aaron J Feinstein
- Providence Cedars-Sinai Tarzana Medical Center, 1831 Clark St, Tarzana, CA 91356, USA.,ENT Group of Los Angeles, 5525 Etiwanda Ave #211, Tarzana, CA 91356, USA
| | - Regina Swift
- Berenson Cancer Center, 9201 Sunset Blvd #300, West Hollywood, CA 90069, USA
| | - Shahrooz Eshaghian
- Division of Hematology and Oncology, Cedars Sinai Medical Center, 8700 Beverly BLVD #2900A, Los Angeles, CA 90048, USA
| | - Eric Vail
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, 8700 Beverly BLVD #2900A, Los Angeles, CA 90048, USA
| | - James R Berenson
- Institute for Myeloma and Bone Cancer Research, 9201 Sunset Blvd #300, West Hollywood, CA 90069, USA.,Berenson Cancer Center, 9201 Sunset Blvd #300, West Hollywood, CA 90069, USA.,ONCOtherapeutics, 9201 Sunset Blvd #317, West Hollywood, CA 90069, USA
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13
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Graf EH. Finding the Middle Ground with the Clinical Laboratory's Role in SARS-CoV-2 Genomic Surveillance. J Clin Microbiol 2021; 59:e0181621. [PMID: 34550811 PMCID: PMC8601223 DOI: 10.1128/jcm.01816-21] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Continued replacement of the dominant severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineages, and associated surges, highlights the importance of genomic surveillance to identify the next possible threats. Despite concerted efforts between clinical laboratories and public health to generate sequence data, the United States has lagged in percentage of SARS-CoV-2 cases sequenced. A more simple and cost-effective option is needed to allow front-line clinical laboratories to perform high-throughput surveillance and refer important samples for slow and expensive next-generation sequencing (NGS). In this issue of the Journal of Clinical Microbiology, A. Babiker, K. Immergluck, S. D. Stampfer, A. Rao, et al. (J Clin Microbiol 59:e01446-21, 2021, https://doi.org/10.1128/JCM.01446-21) describe a rapid and flexible multiplex single-nucleotide polymorphism (SNP) assay targeting mutations associated with Alpha, Beta/Gamma, and, added later, Delta variants. They show 100% accuracy in characterized variant pools and clinical samples confirmed by NGS. Such an approach could be a happy medium in the role of front-line laboratories to assist with critically needed high-throughput genomic surveillance.
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Affiliation(s)
- Erin H. Graf
- Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Phoenix, Arizona, USA
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14
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Oulas A, Richter J, Zanti M, Tomazou M, Michailidou K, Christodoulou K, Christodoulou C, Spyrou GM. In depth analysis of Cyprus-specific mutations of SARS-CoV-2 strains using computational approaches. BMC Genom Data 2021; 22:48. [PMID: 34773976 PMCID: PMC8590444 DOI: 10.1186/s12863-021-01007-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 10/26/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND This study aims to characterize SARS-CoV-2 mutations which are primarily prevalent in the Cypriot population. Moreover, using computational approaches, we assess whether these mutations are associated with changes in viral virulence. METHODS We utilize genetic data from 144 sequences of SARS-CoV-2 strains from the Cypriot population obtained between March 2020 and January 2021, as well as all data available from GISAID. We combine this with countries' regional information, such as deaths and cases per million, as well as COVID-19-related public health austerity measure response times. Initial indications of selective advantage of Cyprus-specific mutations are obtained by mutation tracking analysis. This entails calculating specific mutation frequencies within the Cypriot population and comparing these with their prevalence world-wide throughout the course of the pandemic. We further make use of linear regression models to extrapolate additional information that may be missed through standard statistical analysis. RESULTS We report a single mutation found in the ORF1ab gene (nucleotide position 18,440) that appears to be significantly enriched within the Cypriot population. The amino acid change is denoted as S6059F, which maps to the SARS-CoV-2 NSP14 protein. We further analyse this mutation using regression models to investigate possible associations with increased deaths and cases per million. Moreover, protein structure prediction tools show that the mutation infers a conformational change to the protein that significantly alters its structure when compared to the reference protein. CONCLUSIONS Investigating Cyprus-specific mutations for SARS-CoV-2 can lead to a better understanding of viral pathogenicity. Researching these mutations can generate potential links between viral-specific mutations and the unique genomics of the Cypriot population. This can not only lead to important findings from which to battle the pandemic on a national level, but also provide insights into viral virulence worldwide.
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Affiliation(s)
- Anastasis Oulas
- Bioinformatics Department, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.
- The Cyprus School of Molecular Medicine, Nicosia, Cyprus.
| | - Jan Richter
- Molecular Virology Department, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Maria Zanti
- Bioinformatics Department, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
- The Cyprus School of Molecular Medicine, Nicosia, Cyprus
- Biostatistics Unit, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Marios Tomazou
- Bioinformatics Department, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
- The Cyprus School of Molecular Medicine, Nicosia, Cyprus
- Neurogenetics Department, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Kyriaki Michailidou
- The Cyprus School of Molecular Medicine, Nicosia, Cyprus
- Biostatistics Unit, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Kyproula Christodoulou
- The Cyprus School of Molecular Medicine, Nicosia, Cyprus
- Neurogenetics Department, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Christina Christodoulou
- The Cyprus School of Molecular Medicine, Nicosia, Cyprus
- Molecular Virology Department, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - George M Spyrou
- Bioinformatics Department, Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
- The Cyprus School of Molecular Medicine, Nicosia, Cyprus
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15
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Clinical and Infection Prevention Applications of SARS-CoV-2 Genotyping: an IDSA/ASM Consensus Review Document. J Clin Microbiol 2021; 60:e0165921. [PMID: 34731022 PMCID: PMC8769737 DOI: 10.1128/jcm.01659-21] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged into a world of maturing pathogen genomics, with more than 2 million genomes sequenced at the time of writing. The rise of more transmissible variants of concern that impact vaccine and therapeutic effectiveness has led to widespread interest in SARS-CoV-2 evolution. Clinicians are also eager to take advantage of the information provided by SARS-CoV-2 genotyping beyond surveillance purposes. Here, we review the potential role of SARS-CoV-2 genotyping in clinical care. The review covers clinical use cases for SARS-CoV-2 genotyping, methods of SARS-CoV-2 genotyping, assay validation and regulatory requirements, and clinical reporting for laboratories, as well as emerging issues in clinical SARS-CoV-2 sequencing. While clinical uses of SARS-CoV-2 genotyping are currently limited, rapid technological change along with a growing ability to interpret variants in real time foretells a growing role for SARS-CoV-2 genotyping in clinical care as continuing data emerge on vaccine and therapeutic efficacy.
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16
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Greninger AL, Dien Bard J, Colgrove RC, Graf EH, Hanson KE, Hayden MK, Humphries RM, Lowe CF, Miller MB, Pillai DR, Rhoads DD, Yao JD, Lee FM. Clinical and Infection Prevention Applications of SARS-CoV-2 Genotyping: An IDSA/ASM Consensus Review Document. Clin Infect Dis 2021; 74:1496-1502. [PMID: 34731234 PMCID: PMC8689887 DOI: 10.1093/cid/ciab761] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Indexed: 11/12/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged into a world of maturing pathogen genomics, with >2 million genomes sequenced at this writing. The rise of more transmissible variants of concern that affect vaccine and therapeutic effectiveness has led to widespread interest in SARS-CoV-2 evolution. Clinicians are also eager to take advantage of the information provided by SARS-CoV-2 genotyping beyond surveillance purposes. Here, we review the potential role of SARS-CoV-2 genotyping in clinical care. The review covers clinical use cases for SARS-CoV-2 genotyping, methods of SARS-CoV-2 genotyping, assay validation and regulatory requirements, clinical reporting for laboratories, and emerging issues in clinical SARS-CoV-2 sequencing. While clinical uses of SARS-CoV-2 genotyping are currently limited, rapid technological change along with a growing ability to interpret variants in real time foretell a growing role for SARS-CoV-2 genotyping in clinical care as continuing data emerge on vaccine and therapeutic efficacy.
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Affiliation(s)
- Alexander L Greninger
- Department of Laboratory Medicine and Pathology, University of Washington School of Medicine, Seattle, WA, USA
| | - Jennifer Dien Bard
- Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA, USA; Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Robert C Colgrove
- Division of Infectious Diseases, Mount Auburn Hospital, Harvard School of Medicine
| | - Erin H Graf
- Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, USA
| | - Kimberly E Hanson
- Department of Internal Medicine and Pathology, University of Utah, Salt Lake City, UT, USA
| | - Mary K Hayden
- Division of Infectious Diseases, Department of Medicine and Division of Laboratory Medicine, Department of Pathology, Rush University Medical Center, Chicago, Illinois, USA
| | - Romney M Humphries
- Division of Pathology, Microbiology, and Immunology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Christopher F Lowe
- Division of Medical Microbiology and Virology, Providence Health Care, Vancouver, BC, Canada; Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Melissa B Miller
- Clinical Microbiology Laboratory, University of North Carolina Hospitals and Department of Pathology and Laboratory Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Dylan R Pillai
- Department of Pathology and Laboratory Medicine and Microbiology & Infectious Diseases, University of Calgary, Alberta, Canada
| | - Daniel D Rhoads
- Department of Laboratory Medicine, Cleveland Clinic, Cleveland, OH, USA
| | - Joseph D Yao
- Division of Clinical Microbiology, Department of Laboratory Medicine and Pathology, College of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Francesca M Lee
- Division of Infectious Diseases and Geographic Medicine, Department of Pathology and Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
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17
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COVID-19: Integrating genomic and epidemiological data to inform public health interventions and policy in Tasmania, Australia. Western Pac Surveill Response J 2021; 12:1-9. [PMID: 35251740 PMCID: PMC8873912 DOI: 10.5365/wpsar.2021.12.4.878] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Objective We undertook an integrated analysis of genomic and epidemiological data to investigate a large health-care-associated outbreak of coronavirus disease 2019 (COVID-19) and to better understand the epidemiology of COVID-19 cases in Tasmania, Australia. Methods Epidemiological data collected on COVID-19 cases notified in Tasmania between 2 March and 15 May 2020, and positive samples of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or RNA extracted from the samples were included. Sequencing was conducted by tiled amplicon polymerase chain reaction with ARTIC v1 or v3 primers and Illumina sequencing. Consensus sequences were generated, sequences were aligned to a reference sequence and phylogenetic analysis was performed. Genomic clusters were determined and integrated with epidemiological data to provide additional information. Results All 231 COVID-19 cases notified in Tasmania during the study period and 266 SARS-CoV-2-positive samples, representing 217/231 (94%) notified cases, were included; 184/217 (84%) were clustered, 21/217 (10%) were unique and 12/217 (6%) could not be sequenced. Genomics confirmed the presence of seven clusters already identified through epidemiological links, clarified transmission networks in which the epidemiology had been unclear and identified one cluster that had not previously been recognized. Discussion Genomic analysis provided useful additional information on COVID-19 in Tasmania, including evidence of a large health-care-associated outbreak linked to an overseas cruise, the probable source of infection in cases with no previously identified epidemiological link and confirmation that there was no identified community transmission from other imported cases. Genomic insights are an important component of the response to COVID-19, and continuing genomic surveillance is warranted.
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Boni C, Cavazzini D, Bolchi A, Rossi M, Vecchi A, Tiezzi C, Barili V, Fisicaro P, Ferrari C, Ottonello S. Degenerate CD8 Epitopes Mapping to Structurally Constrained Regions of the Spike Protein: A T Cell-Based Way-Out From the SARS-CoV-2 Variants Storm. Front Immunol 2021; 12:730051. [PMID: 34566990 PMCID: PMC8455995 DOI: 10.3389/fimmu.2021.730051] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 08/11/2021] [Indexed: 01/01/2023] Open
Abstract
There is an urgent need for new generation anti-SARS-Cov-2 vaccines in order to increase the efficacy of immunization and its broadness of protection against viral variants that are continuously arising and spreading. The effect of variants on protective immunity afforded by vaccination has been mostly analyzed with regard to B cell responses. This analysis revealed variable levels of cross-neutralization capacity for presently available SARS-Cov-2 vaccines. Despite the dampened immune responses documented for some SARS-Cov-2 mutations, available vaccines appear to maintain an overall satisfactory protective activity against most variants of concern (VoC). This may be attributed, at least in part, to cell-mediated immunity. Indeed, the widely multi-specific nature of CD8 T cell responses should allow to avoid VoC-mediated viral escape, because mutational inactivation of a given CD8 T cell epitope is expected to be compensated by the persistent responses directed against unchanged co-existing CD8 epitopes. This is particularly relevant because some immunodominant CD8 T cell epitopes are located within highly conserved SARS-Cov-2 regions that cannot mutate without impairing SARS-Cov-2 functionality. Importantly, some of these conserved epitopes are degenerate, meaning that they are able to associate with different HLA class I molecules and to be simultaneously presented to CD8 T cell populations of different HLA restriction. Based on these concepts, vaccination strategies aimed at potentiating the stimulatory effect on SARS-Cov-2-specific CD8 T cells should greatly enhance the efficacy of immunization against SARS-Cov-2 variants. Our review recollects, discusses and puts into a translational perspective all available experimental data supporting these "hot" concepts, with special emphasis on the structural constraints that limit SARS-CoV-2 S-protein evolution and on potentially invariant and degenerate CD8 epitopes that lend themselves as excellent candidates for the rational development of next-generation, CD8 T-cell response-reinforced, COVID-19 vaccines.
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Affiliation(s)
- Carolina Boni
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda-Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Davide Cavazzini
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy
| | - Angelo Bolchi
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy
- Interdepartmental Center Biopharmanet-Tec, University of Parma, Parma, Italy
| | - Marzia Rossi
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda-Ospedaliero-Universitaria di Parma, Parma, Italy
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Andrea Vecchi
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda-Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Camilla Tiezzi
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda-Ospedaliero-Universitaria di Parma, Parma, Italy
| | - Valeria Barili
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda-Ospedaliero-Universitaria di Parma, Parma, Italy
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Paola Fisicaro
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda-Ospedaliero-Universitaria di Parma, Parma, Italy
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Carlo Ferrari
- Laboratory of Viral Immunopathology, Unit of Infectious Diseases and Hepatology, Azienda-Ospedaliero-Universitaria di Parma, Parma, Italy
- Department of Medicine and Surgery, University of Parma, Parma, Italy
| | - Simone Ottonello
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy
- Interdepartmental Center Biopharmanet-Tec, University of Parma, Parma, Italy
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19
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The first SARS-CoV-2 genetic variants of concern (VOC) in Poland: The concept of a comprehensive approach to monitoring and surveillance of emerging variants. Adv Med Sci 2021; 66:237-245. [PMID: 33827042 DOI: 10.1016/j.advms.2021.03.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 03/26/2021] [Indexed: 01/17/2023]
Abstract
PURPOSE We analyzed the SARS-CoV-2 genome using our integrated genome analysis system and present the concept of a comprehensive approach to monitoring and surveillance of emerging variants. MATERIAL/METHODS A total of 69 SARS-CoV-2 positive samples (with Ct value ≤ 28) were tested. Samples included in this study were selected from 7 areas of eastern Poland. All samples were sequenced on an Illumina MiSeq platform using a 300-cycle MiSeq Reagent Kit v2. BWA was used for reads mapping on the reference SARS-CoV-2 sequence. SAMTools were used for post-processing of reads to genome assembly. Pango lineage and Nexstrain were used to identify variants and amino acid mutations. Statistical analysis was performed with R 4.0.2. RESULTS This study shows the first confirmed case of SARS-CoV-2 in Poland with the lineage B.1.351 (known as 501Y.V2 South African variant), as well as another 18 cases with epidemiologically relevant lineage B.1.1.7, known as British variant. Supplementary analysis of SARS-CoV-2 sequences deposited in GISAID shows that the share of a new variant can change rapidly within one month. In addition, we show a complete, integrated concept of a networked system for analyzing the variability of the SARS-CoV-2 genome, which, used in the present study, generated data and a variant report within 6 days. CONCLUSION The analyzed viral genomes showed considerable variability with simultaneous clear distinction of local clusters of genomes showing high similarity. Implementing real-time monitoring of new SARS-CoV-2 variants in Poland is urgently needed, and our developed system is available to be implemented on a large scale.
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Safiabadi Tali SH, LeBlanc JJ, Sadiq Z, Oyewunmi OD, Camargo C, Nikpour B, Armanfard N, Sagan SM, Jahanshahi-Anbuhi S. Tools and Techniques for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)/COVID-19 Detection. Clin Microbiol Rev 2021; 34:e00228-20. [PMID: 33980687 PMCID: PMC8142517 DOI: 10.1128/cmr.00228-20] [Citation(s) in RCA: 170] [Impact Index Per Article: 56.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory disease coronavirus 2 (SARS-CoV-2), has led to millions of confirmed cases and deaths worldwide. Efficient diagnostic tools are in high demand, as rapid and large-scale testing plays a pivotal role in patient management and decelerating disease spread. This paper reviews current technologies used to detect SARS-CoV-2 in clinical laboratories as well as advances made for molecular, antigen-based, and immunological point-of-care testing, including recent developments in sensor and biosensor devices. The importance of the timing and type of specimen collection is discussed, along with factors such as disease prevalence, setting, and methods. Details of the mechanisms of action of the various methodologies are presented, along with their application span and known performance characteristics. Diagnostic imaging techniques and biomarkers are also covered, with an emphasis on their use for assessing COVID-19 or monitoring disease severity or complications. While the SARS-CoV-2 literature is rapidly evolving, this review highlights topics of interest that have occurred during the pandemic and the lessons learned throughout. Exploring a broad armamentarium of techniques for detecting SARS-CoV-2 will ensure continued diagnostic support for clinicians, public health, and infection prevention and control for this pandemic and provide advice for future pandemic preparedness.
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Affiliation(s)
- Seyed Hamid Safiabadi Tali
- Department of Chemical and Materials Engineering, Gina Cody School of Engineering, Concordia University, Montréal, Québec, Canada
- Department of Mechanical, Industrial, and Aerospace Engineering, Gina Cody School of Engineering, Concordia University, Montréal, Québec, Canada
| | - Jason J LeBlanc
- Department of Pathology, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Microbiology and Immunology, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Medicine (Infectious Diseases), Dalhousie University, Halifax, Nova Scotia, Canada
- Division of Microbiology, Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, Nova Scotia, Canada
| | - Zubi Sadiq
- Department of Chemical and Materials Engineering, Gina Cody School of Engineering, Concordia University, Montréal, Québec, Canada
| | - Oyejide Damilola Oyewunmi
- Department of Chemical and Materials Engineering, Gina Cody School of Engineering, Concordia University, Montréal, Québec, Canada
| | - Carolina Camargo
- Department of Microbiology and Immunology, McGill University, Montréal, Québec, Canada
| | - Bahareh Nikpour
- Department of Electrical and Computer Engineering, McGill University, Montréal, Québec, Canada
| | - Narges Armanfard
- Department of Electrical and Computer Engineering, McGill University, Montréal, Québec, Canada
- Mila-Quebec AI Institute, Montréal, Québec, Canada
| | - Selena M Sagan
- Department of Microbiology and Immunology, McGill University, Montréal, Québec, Canada
- Department of Biochemistry, McGill University, Montréal, Québec, Canada
| | - Sana Jahanshahi-Anbuhi
- Department of Chemical and Materials Engineering, Gina Cody School of Engineering, Concordia University, Montréal, Québec, Canada
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Xu F, Beard K. A comparison of prospective space-time scan statistics and spatiotemporal event sequence based clustering for COVID-19 surveillance. PLoS One 2021; 16:e0252990. [PMID: 34111199 PMCID: PMC8191960 DOI: 10.1371/journal.pone.0252990] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 05/26/2021] [Indexed: 12/03/2022] Open
Abstract
The outbreak of the COVID-19 disease was first reported in Wuhan, China, in December 2019. Cases in the United States began appearing in late January. On March 11, the World Health Organization (WHO) declared a pandemic. By mid-March COVID-19 cases were spreading across the US with several hotspots appearing by April. Health officials point to the importance of surveillance of COVID-19 to better inform decision makers at various levels and efficiently manage distribution of human and technical resources to areas of need. The prospective space-time scan statistic has been used to help identify emerging COVID-19 disease clusters, but results from this approach can encounter strategic limitations imposed by constraints of the scanning window. This paper presents a different approach to COVID-19 surveillance based on a spatiotemporal event sequence (STES) similarity. In this STES based approach, adapted for this pandemic context we compute the similarity of evolving daily COVID-19 incidence rates by county and then cluster these sequences to identify counties with similarly trending COVID-19 case loads. We analyze four study periods and compare the sequence similarity-based clusters to prospective space-time scan statistic-based clusters. The sequence similarity-based clusters provide an alternate surveillance perspective by identifying locations that may not be spatially proximate but share a similar disease progression pattern. Results of the two approaches taken together can aid in tracking the progression of the pandemic to aid local or regional public health responses and policy actions taken to control or moderate the disease spread.
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Affiliation(s)
- Fuyu Xu
- School of Computing and Information Science, University of Maine, Orono, ME, United States of America
| | - Kate Beard
- School of Computing and Information Science, University of Maine, Orono, ME, United States of America
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Zhang W, Davis BD, Chen SS, Sincuir Martinez JM, Plummer JT, Vail E. Emergence of a Novel SARS-CoV-2 Variant in Southern California. JAMA 2021; 325:1324-1326. [PMID: 33571356 PMCID: PMC7879386 DOI: 10.1001/jama.2021.1612] [Citation(s) in RCA: 240] [Impact Index Per Article: 80.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
This research describes findings of sequencing and phylogenetic analyses of SARS-CoV-2 isolates from symptomatic patients cared for at Cedar-Sinai Medical Center in November-December 2020 during a regional surge in cases and hospitalizations.
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Affiliation(s)
- Wenjuan Zhang
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, California
| | - Brian D. Davis
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Stephanie S. Chen
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Jorge M. Sincuir Martinez
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, California
| | - Jasmine T. Plummer
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, California
| | - Eric Vail
- Department of Pathology and Laboratory Medicine, Cedars-Sinai Medical Center, Los Angeles, California
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23
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Harris JE. Los Angeles County SARS-CoV-2 Epidemic: Critical Role of Multi-generational Intra-household Transmission. JOURNAL OF BIOECONOMICS 2021. [PMCID: PMC7934992 DOI: 10.1007/s10818-021-09310-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
We observed wide variation in the incidence of confirmed COVID-19 cases in 300 communities making up Los Angeles County, the largest county by population in the United States. The surge in incidence from October 19, 2020 to January 10, 2021, accounting for two-thirds of all confirmed cases since the start of the epidemic, was concentrated in communities with a high prevalence of multi-generational households. This indicator of household structure was a more important predictor of the surge in incidence than the prevalence of households with low income or with at least one high-risk worker. Based upon a spatial adaptation of the standard SIR model, the cumulative incidence of COVID-19, adjusted for underascertainment of both asymptomatic and symptomatic cases, ranged from under 10% in low multi-generational communities to over 30% in high multi-generational communities.
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