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Agüero B, Berrios F, Pardo-Roa C, Ariyama N, Bennett B, Medina RA, Neira V. First detection of Omicron variant BA.4.1 lineage in dogs, Chile. Vet Q 2024; 44:1-10. [PMID: 38174799 PMCID: PMC10769545 DOI: 10.1080/01652176.2023.2298089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 12/16/2023] [Indexed: 01/05/2024] Open
Abstract
SARS-CoV-2's rapid global spread caused the declaration of COVID-19 as a pandemic in March 2020. Alongside humans, domestic dogs and cats are also susceptible to infection. However, limited reports on pet infections in Chile prompted a comprehensive study to address this knowledge gap. Between March 2021 and March 2023, the study assessed 65 pets (26 dogs and 39 cats) from 33 COVID-19+ households alongside 700 nasal swabs from animals in households with unknown COVID-19 status. Using RT-PCR, nasal, fecal, and environmental samples were analyzed for the virus. In COVID-19+ households, 6.06% tested positive for SARS-CoV-2, belonging to 3 dogs, indicating human-to-pet transmission. Pets from households with unknown COVID-19 status tested negative for the virus. We obtained 2 SARS-CoV-2 genomes from animals, that belonged to Omicron BA.4.1 variant, marking the first report of pets infected with this lineage globally. Phylogenetic analysis showed these sequences clustered with human sequences collected in Chile during the same period when the BA.4.1 variant was prevalent in the country. The prevalence of SARS-CoV-2 in Chilean pets was relatively low, likely due to the country's high human vaccination rate. Our study highlights the importance of upholding and strengthening human vaccination strategies to mitigate the risk of interspecies transmission. It underscores the critical role of the One Health approach in addressing emerging zoonotic diseases, calling for further research on infection dynamics and risk factors for a comprehensive understanding.
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Affiliation(s)
- B. Agüero
- Programa de Doctorado en Ciencias Silvoagropecuarias y Veterinarias, Universidad de Chile, Santiago, Chile
- Departamento de Medicina Preventiva Animal, Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
| | - F. Berrios
- Departamento de Medicina Preventiva Animal, Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
| | - C. Pardo-Roa
- Department of Pediatric Infectious Diseases and Immunology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Child and Adolescent Health, School of Nursing, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - N. Ariyama
- Programa de Doctorado en Ciencias Silvoagropecuarias y Veterinarias, Universidad de Chile, Santiago, Chile
- Departamento de Medicina Preventiva Animal, Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
| | - B. Bennett
- Departamento de Medicina Preventiva Animal, Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
| | - RA. Medina
- Department of Pediatric Infectious Diseases and Immunology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Pathology and Laboratory Medicine, School of Medicine, Emory Vaccine Center, Emory University, Atlanta, GA, USA
- Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - V. Neira
- Departamento de Medicina Preventiva Animal, Facultad de Ciencias Veterinarias y Pecuarias, Universidad de Chile, Santiago, Chile
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Khairnar K, Tomar SS. COVID-19 genome surveillance: A geographical landscape and mutational mapping of SARS-CoV-2 variants in central India over two years. Virus Res 2024; 344:199365. [PMID: 38527669 PMCID: PMC10998191 DOI: 10.1016/j.virusres.2024.199365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 03/21/2024] [Accepted: 03/22/2024] [Indexed: 03/27/2024]
Abstract
Reading the viral genome through whole genome sequencing (WGS) enables the detection of changes in the viral genome. The rapid changes in the SARS-CoV-2 viral genome may cause immune escape leading to an increase in the pathogenicity or infectivity. Monitoring mutations through genomic surveillance helps understand the amino acid changes resulting from the mutation. These amino acid changes, especially in the spike glycoprotein, may have implications on the pathogenicity of the virus by rendering it immune-escape. The region of Vidarbha in Maharashtra represents 31.6 % of the state's total area. It holds 21.3 % of the total population. In total, 7457 SARS-CoV-2 positive samples belonging to 16 Indian States were included in the study, out of which 3002 samples passed the sequencing quality control criteria. The metadata of 7457 SARS-CoV-2 positive samples included in the study was sourced from the Integrated Health Information Platform (IHIP). The metadata of 3002 sequenced samples, including the FASTA sequence, was submitted to the Global Initiative on Sharing Avian Influenza Data (GISAID) and the Indian biological data centre (IBDC). This study identified 104 different SARS-CoV-2 pango-lineages classified into 19 clades. We have also analysed the mutation profiles of the variants found in the study, which showed eight mutations of interest, including L18F, K417N, K417T, L452R, S477N, N501Y, P681H, P681R, and mutation of concern E484K in the spike glycoprotein region. The study was from November 2020 to December 2022, making this study the most comprehensive genomic surveillance of SARS-CoV-2 conducted for the region.
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Affiliation(s)
- Krishna Khairnar
- Environmental Epidemiology & Pandemic Management (EE&PM), Council of Scientific and Industrial Research-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, UP, India.
| | - Siddharth Singh Tomar
- Environmental Epidemiology & Pandemic Management (EE&PM), Council of Scientific and Industrial Research-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, UP, India
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3
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Post LA, Wu SA, Soetikno AG, Ozer EA, Liu Y, Welch SB, Hawkins C, Moss CB, Murphy RL, Mason M, Havey RJ, Lundberg AL. Updated Surveillance Metrics and History of the COVID-19 Pandemic (2020-2023) in Latin America and the Caribbean: Longitudinal Trend Analysis. JMIR Public Health Surveill 2024; 10:e44398. [PMID: 38568194 DOI: 10.2196/44398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 03/12/2024] [Accepted: 03/20/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND In May 2020, the World Health Organization (WHO) declared Latin America and the Caribbean (LAC) the epicenter of the COVID-19 pandemic, with over 40% of worldwide COVID-19-related deaths at the time. This high disease burden was a result of the unique circumstances in LAC. OBJECTIVE This study aimed to (1) measure whether the pandemic was expanding or contracting in LAC when the WHO declared the end of COVID-19 as a public health emergency of international concern on May 5, 2023; (2) use dynamic and genomic surveillance methods to describe the history of the pandemic in the region and situate the window of the WHO declaration within the broader history; and (3) provide, with a focus on prevention policies, a historical context for the course of the pandemic in the region. METHODS In addition to updates of traditional surveillance data and dynamic panel estimates from the original study, we used data on sequenced SARS-CoV-2 variants from the Global Initiative on Sharing All Influenza Data (GISAID) to identify the appearance and duration of variants of concern (VOCs). We used Nextclade nomenclature to collect clade designations from sequences and Pangolin nomenclature for lineage designations of SARS-CoV-2. Additionally, we conducted a 1-sided t test for whether the regional weekly speed (rate of novel COVID-19 transmission) was greater than an outbreak threshold of 10. We ran the test iteratively with 6 months of data across the period from August 2020 to May 2023. RESULTS The speed of pandemic spread for the region had remained below the outbreak threshold for 6 months by the time of the WHO declaration. Acceleration and jerk were also low and stable. Although the 1- and 7-day persistence coefficients remained statistically significant for the 120-day period ending on the week of May 5, 2023, the coefficients were relatively modest in magnitude (0.457 and 0.491, respectively). Furthermore, the shift parameters for either of the 2 most recent weeks around May 5, 2023, did not indicate any change in this clustering effect of cases on future cases. From December 2021 onward, Omicron was the predominant VOC in sequenced viral samples. The rolling t test of speed=10 became entirely insignificant from January 2023 onward. CONCLUSIONS Although COVID-19 continues to circulate in LAC, surveillance data suggest COVID-19 is endemic in the region and no longer reaches the threshold of the pandemic definition. However, the region experienced a high COVID-19 burden in the early stages of the pandemic, and prevention policies should be an immediate focus in future pandemics. Ahead of vaccination development, these policies can include widespread testing of individuals and an epidemiological task force with a contact-tracing system.
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Affiliation(s)
- Lori Ann Post
- Buehler Center for Health Policy and Economics, Robert J Havey, MD Institute for Global Health, Northwestern University, Chicago, IL, United States
- Department of Emergency Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Scott A Wu
- Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Alan G Soetikno
- Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Egon A Ozer
- Department of Medicine, Division of Infectious Diseases, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Center for Pathogen Genomics and Microbial Evolution, Robert J Havey, MD Institute for Global Health, Northwestern University, Chicago, IL, United States
| | - Yingxuan Liu
- Buehler Center for Health Policy and Economics, Robert J Havey, MD Institute for Global Health, Northwestern University, Chicago, IL, United States
- Department of Emergency Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Sarah B Welch
- Buehler Center for Health Policy and Economics, Robert J Havey, MD Institute for Global Health, Northwestern University, Chicago, IL, United States
- Department of Emergency Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Claudia Hawkins
- Department of Medicine, Division of Infectious Diseases, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Center for Global Communicable and Emerging Infectious Diseases, Robert J Havey, MD Institute for Global Health, Northwestern University, Chicago, IL, United States
| | - Charles B Moss
- Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL, United States
| | - Robert L Murphy
- Department of Medicine, Division of Infectious Diseases, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
- Robert J Havey, MD Institute for Global Health, Northwestern University, Chicago, IL, United States
| | - Maryann Mason
- Buehler Center for Health Policy and Economics, Robert J Havey, MD Institute for Global Health, Northwestern University, Chicago, IL, United States
- Department of Emergency Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Robert J Havey
- Robert J Havey, MD Institute for Global Health, Northwestern University, Chicago, IL, United States
- Department of Medicine, General Internal Medicine and Geriatrics, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
| | - Alexander L Lundberg
- Buehler Center for Health Policy and Economics, Robert J Havey, MD Institute for Global Health, Northwestern University, Chicago, IL, United States
- Department of Emergency Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, United States
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Exner HM, Gregorchuk BSJ, Castor AG, Crisostomo L, Kolsun K, Giesbrecht S, Dust K, Alexander DC, Bolaji A, Quill Z, Head BM, Meyers AFA, Sandstrom P, Becker MG. Post-market surveillance of six COVID-19 point-of-care tests using pre-Omicron and Omicron SARS-CoV-2 variants. Microbiol Spectr 2024:e0016324. [PMID: 38757955 DOI: 10.1128/spectrum.00163-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2024] [Accepted: 04/18/2024] [Indexed: 05/18/2024] Open
Abstract
Post-market surveillance of test performance is a critical function of public health agencies and clinical researchers that ensures tests maintaining diagnostic characteristics following their regulatory approval. Changes in product quality, manufacturing processes over time, or the evolution of new variants may impact product performance. During the COVID-19 pandemic, a plethora of point-of-care tests (POCTs) was released onto the Canadian market. This study evaluated the performance characteristics of several of the most widely distributed POCTs in Canada, including four rapid antigen tests (Abbott Panbio, BTNX Rapid Response, SD Biosensor, and Quidel QuickVue) and two molecular tests (Abbott ID NOW and Lucira Check IT). All tests were challenged with 149 SARS-CoV-2 clinical positives, including multiple variants up to and including Omicron XBB.1.5, as well as 29 clinical negatives. Results were stratified based on whether the isolate was Omicron or pre-Omicron as well as by reverse transcriptase quantitative PCR Ct value. The test performance of each POCT was consistent with the manufacturers' claims and showed no significant decline in clinical performance against any of the variants tested. These findings provide continued confidence in the results of these POCTs as they continue to be used to support decentralized COVID-19 testing. This work demonstrates the essential role of post-market surveillance in ensuring reliability in diagnostic tools.IMPORTANCEPost-market surveillance of diagnostic test performance is critical to ensure their reliability after regulatory approval. This is especially critical in the context of the COVID-19 pandemic as the use of point-of-care tests (POCTs) became widespread. Our study focused on four rapid antigen tests (Abbott Panbio, BTNX Rapid Response, SD Biosensor, and Quidel QuickVue) and two molecular tests (Abbott ID NOW and Lucira Check IT) that were widely distributed across Canada, assessing their performance using many SARS-CoV-2 variants, including up to Omicron subvariant XBB.1.5. Overall, we found no significant difference in performance against any variant, reinforcing confidence in their use. As concerns in test efficacy have been raised by news outlets, particularly regarding the BTNX Rapid Response, this work is even more timely and crucial. Our research offers insights into the performance of widely used COVID-19 POCTs but also highlights the necessity for post-market surveillance.
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Affiliation(s)
- Hannah M Exner
- JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Branden S J Gregorchuk
- JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Ac-Green Castor
- JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Leandro Crisostomo
- JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Kurt Kolsun
- Department of Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Shayna Giesbrecht
- Department of Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Kerry Dust
- Cadham Provincial Laboratory, Winnipeg, Manitoba, Canada
| | | | | | - Zoe Quill
- JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Breanne M Head
- JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
| | - Adrienne F A Meyers
- Office of Population and Public Health, Indigenous Services Canada, Ottawa, Ontario, Canada
| | - Paul Sandstrom
- JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Michael G Becker
- JC Wilt Infectious Diseases Research Centre, National Microbiology Laboratory Branch, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
- Department of Microbiology, University of Manitoba, Winnipeg, Manitoba, Canada
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5
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Päll T, Abroi A, Avi R, Niglas H, Shablinskaja A, Pauskar M, Jõgeda EL, Soeorg H, Kallas E, Lahesaare A, Truusalu K, Hoidmets D, Sadikova O, Ratnik K, Sepp H, Dotsenko L, Epštein J, Suija H, Kaarna K, Smit S, Milani L, Metspalu M, Oopkaup OE, Koppel I, Jaaniso E, Kuzmin I, Inno H, Raudvere U, Härma MA, Naaber P, Reisberg T, Peterson H, Talas UG, Lutsar I, Huik K. SARS-CoV-2 clade dynamics and their associations with hospitalisations during the first two years of the COVID-19 pandemic. PLoS One 2024; 19:e0303176. [PMID: 38728305 PMCID: PMC11086870 DOI: 10.1371/journal.pone.0303176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Accepted: 04/20/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND The COVID-19 pandemic was characterised by rapid waves of disease, carried by the emergence of new and more infectious SARS-CoV-2 virus variants. How the pandemic unfolded in various locations during its first two years has yet to be sufficiently covered. To this end, here we are looking at the circulating SARS-CoV-2 variants, their diversity, and hospitalisation rates in Estonia in the period from March 2000 to March 2022. METHODS We sequenced a total of 27,550 SARS-CoV-2 samples in Estonia between March 2020 and March 2022. High-quality sequences were genotyped and assigned to Nextstrain clades and Pango lineages. We used regression analysis to determine the dynamics of lineage diversity and the probability of clade-specific hospitalisation stratified by age and sex. RESULTS We successfully sequenced a total of 25,375 SARS-CoV-2 genomes (or 92%), identifying 19 Nextstrain clades and 199 Pango lineages. In 2020 the most prevalent clades were 20B and 20A. The various subsequent waves of infection were driven by 20I (Alpha), 21J (Delta) and Omicron clades 21K and 21L. Lineage diversity via the Shannon index was at its highest during the Delta wave. About 3% of sequenced SARS-CoV-2 samples came from hospitalised individuals. Hospitalisation increased markedly with age in the over-forties, and was negligible in the under-forties. Vaccination decreased the odds of hospitalisation in over-forties. The effect of vaccination on hospitalisation rates was strongly dependent upon age but was clade-independent. People who were infected with Omicron clades had a lower hospitalisation likelihood in age groups of forty and over than was the case with pre-Omicron clades regardless of vaccination status. CONCLUSIONS COVID-19 disease waves in Estonia were driven by the Alpha, Delta, and Omicron clades. Omicron clades were associated with a substantially lower hospitalisation probability than pre-Omicron clades. The protective effect of vaccination in reducing hospitalisation likelihood was independent of the involved clade.
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Affiliation(s)
- Taavi Päll
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Aare Abroi
- Faculty of Science and Technology, Institute of Technology, University of Tartu, Tartu, Estonia
| | - Radko Avi
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Heiki Niglas
- Department of Communicable Diseases, Health Board, Tallinn, Estonia
| | - Arina Shablinskaja
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Merit Pauskar
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Ene-Ly Jõgeda
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Hiie Soeorg
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Eveli Kallas
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | | | - Kai Truusalu
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Dagmar Hoidmets
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Olga Sadikova
- Department of Communicable Diseases, Health Board, Tallinn, Estonia
| | | | - Hanna Sepp
- Department of Communicable Diseases, Health Board, Tallinn, Estonia
| | - Liidia Dotsenko
- Department of Communicable Diseases, Health Board, Tallinn, Estonia
| | - Jevgenia Epštein
- Department of Communicable Diseases, Health Board, Tallinn, Estonia
| | - Heleene Suija
- Department of Communicable Diseases, Health Board, Tallinn, Estonia
| | - Katrin Kaarna
- Clinical Research Centre, Faculty of Medicine, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Tartu University Hospital, Tartu, Estonia
| | - Steven Smit
- Institute of Genomics, Faculty of Science and Technology, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Institute of Genomics, Faculty of Science and Technology, University of Tartu, Tartu, Estonia
| | - Mait Metspalu
- Institute of Genomics, Faculty of Science and Technology, University of Tartu, Tartu, Estonia
| | - Ott Eric Oopkaup
- High Performance Computing Centre, Faculty of Science and Technology, Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Ivar Koppel
- High Performance Computing Centre, Faculty of Science and Technology, Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Erik Jaaniso
- Institute of Computer Science, Faculty of Science and Technology, University of Tartu, Tartu, Estonia
| | - Ivan Kuzmin
- High Performance Computing Centre, Faculty of Science and Technology, Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Heleri Inno
- High Performance Computing Centre, Faculty of Science and Technology, Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Uku Raudvere
- High Performance Computing Centre, Faculty of Science and Technology, Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Mari-Anne Härma
- Department of Communicable Diseases, Health Board, Tallinn, Estonia
| | - Paul Naaber
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
- SYNLAB Eesti OÜ, Tallinn, Estonia
| | - Tuuli Reisberg
- Institute of Genomics, Faculty of Science and Technology, University of Tartu, Tartu, Estonia
| | - Hedi Peterson
- Institute of Computer Science, Faculty of Science and Technology, University of Tartu, Tartu, Estonia
| | - Ulvi Gerst Talas
- High Performance Computing Centre, Faculty of Science and Technology, Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Irja Lutsar
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
| | - Kristi Huik
- Department of Microbiology, Faculty of Medicine, Institute of Biomedicine and Translational Medicine, University of Tartu, Tartu, Estonia
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Paull JS, Petros BA, Brock-Fisher TM, Jalbert SA, Selser VM, Messer KS, Dobbins ST, DeRuff KC, Deng D, Springer M, Sabeti PC. Optimisation and evaluation of viral genomic sequencing of SARS-CoV-2 rapid diagnostic tests: a laboratory and cohort-based study. Lancet Microbe 2024; 5:e468-e477. [PMID: 38621394 DOI: 10.1016/s2666-5247(23)00399-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 12/04/2023] [Accepted: 12/05/2023] [Indexed: 04/17/2024]
Abstract
BACKGROUND Sequencing of SARS-CoV-2 from rapid diagnostic tests (RDTs) can bolster viral genomic surveillance efforts; however, approaches to maximise and standardise pathogen genome recovery from RDTs remain underdeveloped. We aimed to systematically optimise the elution of genetic material from RDT components and to evaluate the efficacy of RDT sequencing for outbreak investigation. METHODS In this laboratory and cohort-based study we seeded RDTs with inactivated SARS-CoV-2 to optimise the elution of genomic material from RDT lateral flow strips. We measured the effect of changes in buffer type, time in buffer, and rotation on PCR cycle threshold (Ct) value. We recruited individuals older than 18 years residing in the greater Boston area, MA, USA, from July 18 to Nov 5, 2022, via email advertising to students and staff at Harvard University, MA, USA, and via broad social media advertising. All individuals recruited were within 5 days of a positive diagnostic test for SARS-CoV-2; no other relevant exclusion criteria were applied. Each individual completed two RDTs and one PCR swab. On Dec 29, 2022, we also collected RDTs from a convenience sample of individuals who were positive for SARS-CoV-2 and associated with an outbreak at a senior housing facility in MA, USA. We extracted all returned PCR swabs and RDT components (ie, swab, strip, or buffer); samples with a Ct of less than 40 were subject to amplicon sequencing. We compared the efficacy of elution and sequencing across RDT brands and components and used RDT-derived sequences to infer transmission links within the outbreak at the senior housing facility. We conducted metagenomic sequencing of negative RDTs from symptomatic individuals living in the senior housing facility. FINDINGS Neither elution duration of greater than 10 min nor rotation during elution impacted viral titres. Elution in Buffer AVL (Ct=31·4) and Tris-EDTA Buffer (Ct=30·8) were equivalent (p=0·34); AVL outperformed elution in lysis buffer and 50% lysis buffer (Ct=40·0, p=0·0029 for both) as well as Universal Viral Transport Medium (Ct=36·7, p=0·079). Performance of RDT strips was poorer than that of matched PCR swabs (mean Ct difference 10·2 [SD 4·3], p<0·0001); however, RDT swabs performed similarly to PCR swabs (mean Ct difference 4·1 [5·2], p=0·055). No RDT brand significantly outperformed another. Across sample types, viral load predicted the viral genome assembly length. We assembled greater than 80% complete genomes from 12 of 17 RDT-derived swabs, three of 18 strips, and four of 11 residual buffers. We generated outbreak-associated SARS-CoV-2 genomes using both amplicon and metagenomic sequencing and identified multiple introductions of the virus that resulted in downstream transmission. INTERPRETATION RDT-derived swabs are a reasonable alternative to PCR swabs for viral genomic surveillance and outbreak investigation. RDT-derived lateral flow strips yield accurate, but significantly fewer, viral reads than matched PCR swabs. Metagenomic sequencing of negative RDTs can identify viruses that might underlie patient symptoms. FUNDING The National Science Foundation, the Hertz Foundation, the National Institute of General Medical Sciences, Harvard Medical School, the Howard Hughes Medical Institute, the US Centers for Disease Control and Prevention, the Broad Institute and the National Institute of Allergy and Infectious Diseases.
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Affiliation(s)
- Jillian S Paull
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Brittany A Petros
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Health Sciences and Technology, Harvard Medical School and MIT, Cambridge, MA, USA; Harvard/MIT MD-PhD Program, Harvard Medical School, Boston, MA, USA.
| | - Taylor M Brock-Fisher
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | | | | | | | | | | | - Davy Deng
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michael Springer
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA
| | - Pardis C Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA; Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA.
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7
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Igari H, Sakao S, Ishige T, Saito K, Murata S, Yahaba M, Taniguchi T, Suganami A, Matsushita K, Tamura Y, Suzuki T, Ido E. Dynamic diversity of SARS-CoV-2 genetic mutations in a lung transplantation patient with persistent COVID-19. Nat Commun 2024; 15:3604. [PMID: 38684722 PMCID: PMC11058237 DOI: 10.1038/s41467-024-47941-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 04/15/2024] [Indexed: 05/02/2024] Open
Abstract
Numerous SARS-CoV-2 variant strains with altered characteristics have emerged since the onset of the COVID-19 pandemic. Remdesivir (RDV), a ribonucleotide analogue inhibitor of viral RNA polymerase, has become a valuable therapeutic agent. However, immunosuppressed hosts may respond inadequately to RDV and develop chronic persistent infections. A patient with respiratory failure caused by interstitial pneumonia, who had undergone transplantation of the left lung, developed COVID-19 caused by Omicron BA.5 strain with persistent chronic viral shedding, showing viral fusogenicity. Genome-wide sequencing analyses revealed the occurrence of several viral mutations after RDV treatment, followed by dynamic changes in the viral populations. The C799F mutation in nsp12 was found to play a pivotal role in conferring RDV resistance, preventing RDV-triphosphate from entering the active site of RNA-dependent RNA polymerase. The occurrence of diverse mutations is a characteristic of SARS-CoV-2, which mutates frequently. Herein, we describe the clinical case of an immunosuppressed host in whom inadequate treatment resulted in highly diverse SARS-CoV-2 mutations that threatened the patient's health due to the development of drug-resistant variants.
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Affiliation(s)
- Hidetoshi Igari
- Department of Infectious Diseases, Chiba University Hospital, Chiba, Chiba, Japan.
- Future Mucosal Vaccine Research and Development Center, Chiba University Hospital, Chiba, Chiba, Japan.
- COVID-19 Vaccine Center, Chiba University Hospital, Chiba, Chiba, Japan.
- Research Institute of Disaster Medicine, Chiba University, Chiba, Chiba, Japan.
| | - Seiichiro Sakao
- Department of Respiratory Medicine, Chiba University Hospital, Chiba, Chiba, Japan
- Department of Pulmonary Medicine, School of Medicine, International University of Health and Welfare, Narita, Chiba, Japan
| | - Takayuki Ishige
- Division of Laboratory Medicine, Chiba University Hospital, Chiba, Chiba, Japan.
| | - Kengo Saito
- Department of Molecular Virology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Shota Murata
- Division of Laboratory Medicine, Chiba University Hospital, Chiba, Chiba, Japan
| | - Misuzu Yahaba
- Department of Infectious Diseases, Chiba University Hospital, Chiba, Chiba, Japan
| | - Toshibumi Taniguchi
- Department of Infectious Diseases, Chiba University Hospital, Chiba, Chiba, Japan
- Research Institute of Disaster Medicine, Chiba University, Chiba, Chiba, Japan
| | - Akiko Suganami
- Department of Bioinformatics, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Kazuyuki Matsushita
- Division of Laboratory Medicine, Chiba University Hospital, Chiba, Chiba, Japan
| | - Yutaka Tamura
- Department of Bioinformatics, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan
| | - Takuji Suzuki
- Future Mucosal Vaccine Research and Development Center, Chiba University Hospital, Chiba, Chiba, Japan
- Department of Respiratory Medicine, Chiba University Hospital, Chiba, Chiba, Japan
- Synergy Institute for Futuristic Mucosal Vaccine Research and Development, Chiba University, Chiba, Chiba, Japan
| | - Eiji Ido
- Department of Infectious Diseases, Chiba University Hospital, Chiba, Chiba, Japan.
- Department of Molecular Virology, Graduate School of Medicine, Chiba University, Chiba, Chiba, Japan.
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8
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Santos JD, Sobral D, Pinheiro M, Isidro J, Bogaardt C, Pinto M, Eusébio R, Santos A, Mamede R, Horton DL, Gomes JP, Borges V. INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance. Genome Med 2024; 16:61. [PMID: 38659008 PMCID: PMC11044337 DOI: 10.1186/s13073-024-01334-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 04/15/2024] [Indexed: 04/26/2024] Open
Abstract
BACKGROUND Implementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification. RESULTS The routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a "generic" build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis. CONCLUSIONS The accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).
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Affiliation(s)
- João Dourado Santos
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Daniel Sobral
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Miguel Pinheiro
- Institute of Biomedicine-iBiMED, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Joana Isidro
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Carlijn Bogaardt
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, University of Surrey, Surrey, UK
| | - Miguel Pinto
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Rodrigo Eusébio
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - André Santos
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
| | - Rafael Mamede
- Faculdade de Medicina, Instituto de Microbiologia, Instituto de Medicina Molecular, Universidade de Lisboa, Lisbon, Portugal
| | - Daniel L Horton
- Department of Comparative Biomedical Sciences, School of Veterinary Medicine, University of Surrey, Surrey, UK
| | - João Paulo Gomes
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal
- Veterinary and Animal Research Centre (CECAV), Faculty of Veterinary Medicine, Lusófona University, Lisbon, Portugal
| | - Vítor Borges
- Genomics and Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal.
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9
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Chandy S, Kumar H, Pearl S, Basu S, M G, Sankar J, Manoharan A, Ramaiah S, Anbarasu A. Whole genome analysis reveals unique traits of SARS-CoV-2 in pediatric patients. Gene 2024; 919:148508. [PMID: 38670399 DOI: 10.1016/j.gene.2024.148508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 04/10/2024] [Accepted: 04/23/2024] [Indexed: 04/28/2024]
Abstract
Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) continues to challenge the global healthcare with emerging variants and higher infectivity as well as morbidities. This study investigated potential age-related variations through genomic characterization of the virus under common clinical settings. A cohort comprising 71 SARS-CoV-2 strains from both infected infants and accompanying adults, diagnosed via RT-PCR at a tertiary pediatric hospital and research center, underwent Illumina paired-end sequencing. The subsequent analysis involved standard genomic screening, phylogeny construction, and mutational analyses. The analyzed SARSCoV- 2 strains were compared with globally circulating variants. The overall distribution revealed 67.61 % Delta, 25.7 % Omicron, and 1 % either Kappa or Alpha variants. In 2021, Delta predominated at ∼ 94 %, with Alpha/Kappa accounting for around 5 %. However, in 2022, over 94 % of the samples were Omicron variants, signifying a substantial shift from Delta dominance. Delta variants constituted 69.5 % of infections in adults and 78.5 % in infants, while Omicron variants were responsible for 31 % of cases in infants and 18 % in adults. The Spike region harbored the majority of mutations, with T19R being the most prevalent mutation in the Delta lineage. Notably, the frequencies of this mutation varied between infants and adults. In Omicron samples, G142D emerged as the most prevalent mutation. Our dataset predominantly featured clade 21A and lineage B.1.617.2. This study underscores the differential clinical presentations and genomic characteristics of SARS-CoV-2 in pediatric patients and accompanying adults. Understanding the dynamic evolution of the SARS- CoV-2 in both pediatric and adults can help in strengthening prophylactic measures.
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Affiliation(s)
- Sara Chandy
- The CHILDS Trust Medical Research Foundation (CTMRF), 12-A, Nageswara Road, Nungambakkam, Chennai 600034, Tamil Nadu, India
| | - Hithesh Kumar
- Department of Bio-Sciences, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), Vellore 632014, India; Medical and Biological Computing Laboratory, SBST, VIT, Vellore 632014, India
| | - Sara Pearl
- Medical and Biological Computing Laboratory, SBST, VIT, Vellore 632014, India; Department of Integrative Biology, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), Vellore 632014, India
| | - Soumya Basu
- Medical and Biological Computing Laboratory, SBST, VIT, Vellore 632014, India; Department of Biotechnology, NIST University, Berhampore 761008, India
| | - Gurumoorthy M
- The CHILDS Trust Medical Research Foundation (CTMRF), 12-A, Nageswara Road, Nungambakkam, Chennai 600034, Tamil Nadu, India
| | - Janani Sankar
- The CHILDS Trust Medical Research Foundation (CTMRF), 12-A, Nageswara Road, Nungambakkam, Chennai 600034, Tamil Nadu, India
| | - Anand Manoharan
- Kanchi Kamakoti CHILDS Trust Hospital (KKCTH), 12-A, Nageswara Road, Nungambakkam, Chennai 600034, Tamil Nadu, India
| | - Sudha Ramaiah
- Department of Bio-Sciences, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), Vellore 632014, India; Medical and Biological Computing Laboratory, SBST, VIT, Vellore 632014, India
| | - Anand Anbarasu
- Medical and Biological Computing Laboratory, SBST, VIT, Vellore 632014, India; Department of Biotechnology, School of Biosciences and Technology (SBST), Vellore Institute of Technology (VIT), Vellore 632014, India.
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10
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Merkt S, Ali S, Gudina EK, Adissu W, Gize A, Muenchhoff M, Graf A, Krebs S, Elsbernd K, Kisch R, Betizazu SS, Fantahun B, Bekele D, Rubio-Acero R, Gashaw M, Girma E, Yilma D, Zeynudin A, Paunovic I, Hoelscher M, Blum H, Hasenauer J, Kroidl A, Wieser A. Long-term monitoring of SARS-CoV-2 seroprevalence and variants in Ethiopia provides prediction for immunity and cross-immunity. Nat Commun 2024; 15:3463. [PMID: 38658564 PMCID: PMC11043357 DOI: 10.1038/s41467-024-47556-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 04/03/2024] [Indexed: 04/26/2024] Open
Abstract
Under-reporting of COVID-19 and the limited information about circulating SARS-CoV-2 variants remain major challenges for many African countries. We analyzed SARS-CoV-2 infection dynamics in Addis Ababa and Jimma, Ethiopia, focusing on reinfection, immunity, and vaccination effects. We conducted an antibody serology study spanning August 2020 to July 2022 with five rounds of data collection across a population of 4723, sequenced PCR-test positive samples, used available test positivity rates, and constructed two mathematical models integrating this data. A multivariant model explores variant dynamics identifying wildtype, alpha, delta, and omicron BA.4/5 as key variants in the study population, and cross-immunity between variants, revealing risk reductions between 24% and 69%. An antibody-level model predicts slow decay leading to sustained high antibody levels. Retrospectively, increased early vaccination might have substantially reduced infections during the delta and omicron waves in the considered group of individuals, though further vaccination now seems less impactful.
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Affiliation(s)
- Simon Merkt
- Life and Medical Sciences (LIMES), University of Bonn, Bonn, Germany
| | - Solomon Ali
- Saint Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia
| | - Esayas Kebede Gudina
- Jimma University Clinical Trial Unit, Jimma University Institute of Health, Jimma, Ethiopia
| | - Wondimagegn Adissu
- Jimma University Clinical Trial Unit, Jimma University Institute of Health, Jimma, Ethiopia
| | - Addisu Gize
- Saint Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia
- CIH LMU Center for International Health, LMU Munich, Munich, Germany
| | - Maximilian Muenchhoff
- Max von Pettenkofer Institute and Gene Center, Virology, National Reference Center for Retroviruses, LMU Munich, Munich, Germany
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
| | - Alexander Graf
- Laboratory for Functional Genome Analysis, Gene Center, LMU Munich, Munich, Germany
| | - Stefan Krebs
- Laboratory for Functional Genome Analysis, Gene Center, LMU Munich, Munich, Germany
| | - Kira Elsbernd
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Faculty of Medicine, LMU Munich, Munich, Germany
| | - Rebecca Kisch
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | | | - Bereket Fantahun
- Saint Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia
| | - Delayehu Bekele
- Saint Paul's Hospital Millennium Medical College, Addis Ababa, Ethiopia
| | - Raquel Rubio-Acero
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
| | - Mulatu Gashaw
- Jimma University Clinical Trial Unit, Jimma University Institute of Health, Jimma, Ethiopia
| | - Eyob Girma
- Jimma University Clinical Trial Unit, Jimma University Institute of Health, Jimma, Ethiopia
| | - Daniel Yilma
- Jimma University Clinical Trial Unit, Jimma University Institute of Health, Jimma, Ethiopia
| | - Ahmed Zeynudin
- Jimma University Clinical Trial Unit, Jimma University Institute of Health, Jimma, Ethiopia
| | - Ivana Paunovic
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Immunology, Infection and Pandemic Research IIP, Fraunhofer ITMP, Munich, Germany
| | - Michael Hoelscher
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany
- Immunology, Infection and Pandemic Research IIP, Fraunhofer ITMP, Munich, Germany
- Unit Global Health, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Helmut Blum
- Laboratory for Functional Genome Analysis, Gene Center, LMU Munich, Munich, Germany
| | - Jan Hasenauer
- Life and Medical Sciences (LIMES), University of Bonn, Bonn, Germany.
- Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.
- Center for Mathematics, Technische Universität München, Garching, Germany.
| | - Arne Kroidl
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany.
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany.
| | - Andreas Wieser
- German Center for Infection Research (DZIF), partner site Munich, Munich, Germany.
- Division of Infectious Diseases and Tropical Medicine, LMU University Hospital, LMU Munich, Munich, Germany.
- Immunology, Infection and Pandemic Research IIP, Fraunhofer ITMP, Munich, Germany.
- Faculty of Medicine, Max Von Pettenkofer Institute, LMU Munich, Munich, Germany.
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11
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Alfonsi T, Bernasconi A, Chiara M, Ceri S. Data-driven recombination detection in viral genomes. Nat Commun 2024; 15:3313. [PMID: 38632281 PMCID: PMC11024102 DOI: 10.1038/s41467-024-47464-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 03/25/2024] [Indexed: 04/19/2024] Open
Abstract
Recombination is a key molecular mechanism for the evolution and adaptation of viruses. The first recombinant SARS-CoV-2 genomes were recognized in 2021; as of today, more than ninety SARS-CoV-2 lineages are designated as recombinant. In the wake of the COVID-19 pandemic, several methods for detecting recombination in SARS-CoV-2 have been proposed; however, none could faithfully confirm manual analyses by experts in the field. We hereby present RecombinHunt, an original data-driven method for the identification of recombinant genomes, capable of recognizing recombinant SARS-CoV-2 genomes (or lineages) with one or two breakpoints with high accuracy and within reduced turn-around times. ReconbinHunt shows high specificity and sensitivity, compares favorably with other state-of-the-art methods, and faithfully confirms manual analyses by experts. RecombinHunt identifies recombinant viral genomes from the recent monkeypox epidemic in high concordance with manually curated analyses by experts, suggesting that our approach is robust and can be applied to any epidemic/pandemic virus.
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Affiliation(s)
- Tommaso Alfonsi
- Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, 20133, Milan, Italy
| | - Anna Bernasconi
- Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, 20133, Milan, Italy.
| | - Matteo Chiara
- Department of Biosciences, Università degli Studi di Milano, Via Celoria 26, 20133, Milan, Italy
| | - Stefano Ceri
- Department of Electronics, Information, and Bioengineering, Politecnico di Milano, Via Ponzio 34/5, 20133, Milan, Italy
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12
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Lataretu M, Drechsel O, Kmiecinski R, Trappe K, Hölzer M, Fuchs S. Lessons learned: overcoming common challenges in reconstructing the SARS-CoV-2 genome from short-read sequencing data via CoVpipe2. F1000Res 2024; 12:1091. [PMID: 38716230 PMCID: PMC11074694 DOI: 10.12688/f1000research.136683.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/11/2024] [Indexed: 05/12/2024] Open
Abstract
Background Accurate genome sequences form the basis for genomic surveillance programs, the added value of which was impressively demonstrated during the COVID-19 pandemic by tracing transmission chains, discovering new viral lineages and mutations, and assessing them for infectiousness and resistance to available treatments. Amplicon strategies employing Illumina sequencing have become widely established for variant detection and reference-based reconstruction of SARS-CoV-2 genomes, and are routine bioinformatics tasks. Yet, specific challenges arise when analyzing amplicon data, for example, when crucial and even lineage-determining mutations occur near primer sites. Methods We present CoVpipe2, a bioinformatics workflow developed at the Public Health Institute of Germany to reconstruct SARS-CoV-2 genomes based on short-read sequencing data accurately. The decisive factor here is the reliable, accurate, and rapid reconstruction of genomes, considering the specifics of the used sequencing protocol. Besides fundamental tasks like quality control, mapping, variant calling, and consensus generation, we also implemented additional features to ease the detection of mixed samples and recombinants. Results We highlight common pitfalls in primer clipping, detecting heterozygote variants, and dealing with low-coverage regions and deletions. We introduce CoVpipe2 to address the above challenges and have compared and successfully validated the pipeline against selected publicly available benchmark datasets. CoVpipe2 features high usability, reproducibility, and a modular design that specifically addresses the characteristics of short-read amplicon protocols but can also be used for whole-genome short-read sequencing data. Conclusions CoVpipe2 has seen multiple improvement cycles and is continuously maintained alongside frequently updated primer schemes and new developments in the scientific community. Our pipeline is easy to set up and use and can serve as a blueprint for other pathogens in the future due to its flexibility and modularity, providing a long-term perspective for continuous support. CoVpipe2 is written in Nextflow and is freely accessible from \href{https://github.com/rki-mf1/CoVpipe2}{github.com/rki-mf1/CoVpipe2} under the GPL3 license.
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Affiliation(s)
- Marie Lataretu
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
| | - Oliver Drechsel
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
| | - René Kmiecinski
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
| | - Kathrin Trappe
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
| | - Martin Hölzer
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
| | - Stephan Fuchs
- Genome Competence Center (MF1), Robert Koch Institute, Berlin, 13353, Germany
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13
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Seekings AH, Shipley R, Byrne AMP, Shukla S, Golding M, Amaya-Cuesta J, Goharriz H, Vitores AG, Lean FZX, James J, Núñez A, Breed A, Frost A, Balzer J, Brown IH, Brookes SM, McElhinney LM. Detection of SARS-CoV-2 Delta Variant (B.1.617.2) in Domestic Dogs and Zoo Tigers in England and Jersey during 2021. Viruses 2024; 16:617. [PMID: 38675958 PMCID: PMC11053977 DOI: 10.3390/v16040617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2024] [Revised: 04/02/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024] Open
Abstract
Reverse zoonotic transmission events of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been described since the start of the pandemic, and the World Organisation for Animal Health (WOAH) designated the detection of SARS-CoV-2 in animals a reportable disease. Eighteen domestic and zoo animals in Great Britain and Jersey were tested by APHA for SARS-CoV-2 during 2020-2023. One domestic cat (Felis catus), three domestic dogs (Canis lupus familiaris), and three Amur tigers (Panthera tigris altaica) from a zoo were confirmed positive during 2020-2021 and reported to the WOAH. All seven positive animals were linked with known SARS-CoV-2 positive human contacts. Characterisation of the SARS-CoV-2 variants by genome sequencing indicated that the cat was infected with an early SARS-CoV-2 lineage. The three dogs and three tigers were infected with the SARS-CoV-2 Delta variant of concern (B.1.617.2). The role of non-human species in the onward transmission and emergence of new variants of SARS-CoV-2 remain poorly defined. Continued surveillance of SARS-CoV-2 in relevant domestic and captive animal species with high levels of human contact is important to monitor transmission at the human-animal interface and to assess their role as potential animal reservoirs.
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Affiliation(s)
- Amanda H. Seekings
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
- National Reference Laboratory for SARS-CoV-2 in Animals, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Rebecca Shipley
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
- National Reference Laboratory for SARS-CoV-2 in Animals, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Alexander M. P. Byrne
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
- Worldwide Influenza Centre, The Francis Crick Institute, Midland Road, London NW1 1AT, UK
| | - Shweta Shukla
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
- National Reference Laboratory for SARS-CoV-2 in Animals, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Megan Golding
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Joan Amaya-Cuesta
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Hooman Goharriz
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
- National Reference Laboratory for SARS-CoV-2 in Animals, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Ana Gómez Vitores
- Department of Pathology and Animal Sciences, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Fabian Z. X. Lean
- Department of Pathology and Animal Sciences, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Joe James
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Alejandro Núñez
- Department of Pathology and Animal Sciences, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Alistair Breed
- Government of Jersey, Infrastructure Housing and Environment, Howard Davis Farm, La Route de la Trinité, Trinity, Jersey JE3 5JP, UK
| | - Andrew Frost
- One Health, Animal Health and Welfare Advice Team, Animal and Plant Health Agency, Nobel House, 17 Smith Square, London SW1P 3JR, UK
| | - Jörg Balzer
- Vet Med Labor GmbH, Division of IDEXX Laboratories, Humboldtstraße 2, 70806 Kornwestheim, Germany
| | - Ian H. Brown
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Sharon M. Brookes
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
| | - Lorraine M. McElhinney
- Department of Virology, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
- National Reference Laboratory for SARS-CoV-2 in Animals, Animal and Plant Health Agency-Weybridge, Woodham Lane, New Haw, Addlestone, Surrey KT15 3NB, UK
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14
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Sultana A, Bienzle D, Weese S, Pickering B, Kruczkiewicz P, Smith G, Pinette M, Lung O. Whole-genome sequencing of SARS-CoV-2 from the initial cases of domestic cat infections in Canada. Microbiol Resour Announc 2024; 13:e0129523. [PMID: 38411070 PMCID: PMC11008122 DOI: 10.1128/mra.01295-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 02/16/2024] [Indexed: 02/28/2024] Open
Abstract
Two cat nasal swabs from Canada's earliest confirmed SARS-CoV-2 positive domestic cats were sequenced to over 99% SARS-CoV-2 genome coverage. One cat had lineage A.23.1 SARS-CoV-2 not reported before in animals. Both sequences have multiple spike gene mutations and clustered closely with human-derived sequences in the global SARS-CoV-2 phylogenetic tree.
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Affiliation(s)
- Asma Sultana
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Dorothee Bienzle
- Ontario Veterinary College, Centre for Public Health and Zoonoses, University of Guelph, Ontario, Guelph, Canada
| | - Scott Weese
- Ontario Veterinary College, Centre for Public Health and Zoonoses, University of Guelph, Ontario, Guelph, Canada
| | - Brad Pickering
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
- Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Peter Kruczkiewicz
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Greg Smith
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Mathieu Pinette
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
| | - Oliver Lung
- Department of Biological Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
- National Centre for Foreign Animal Disease, Canadian Food Inspection Agency, Winnipeg, Manitoba, Canada
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15
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Tanneti NS, Patel AK, Tan LH, Marques AD, Perera RAPM, Sherrill-Mix S, Kelly BJ, Renner DM, Collman RG, Rodino K, Lee C, Bushman FD, Cohen NA, Weiss SR. Comparison of SARS-CoV-2 variants of concern in primary human nasal cultures demonstrates Delta as most cytopathic and Omicron as fastest replicating. mBio 2024; 15:e0312923. [PMID: 38477472 PMCID: PMC11005367 DOI: 10.1128/mbio.03129-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Accepted: 02/20/2024] [Indexed: 03/14/2024] Open
Abstract
The SARS-CoV-2 pandemic was marked with emerging viral variants, some of which were designated as variants of concern (VOCs) due to selection and rapid circulation in the human population. Here, we elucidate functional features of each VOC linked to variations in replication rate. Patient-derived primary nasal cultures grown at air-liquid interface were used to model upper respiratory infection and compared to cell lines derived from human lung epithelia. All VOCs replicated to higher titers than the ancestral virus, suggesting a selection for replication efficiency. In primary nasal cultures, Omicron replicated to the highest titers at early time points, followed by Delta, paralleling comparative studies of population sampling. All SARS-CoV-2 viruses entered the cell primarily via a transmembrane serine protease 2 (TMPRSS2)-dependent pathway, and Omicron was more likely to use an endosomal route of entry. All VOCs activated and overcame dsRNA-induced cellular responses, including interferon (IFN) signaling, oligoadenylate ribonuclease L degradation, and protein kinase R activation. Among the VOCs, Omicron infection induced expression of the most IFN and IFN-stimulated genes. Infections in nasal cultures resulted in cellular damage, including a compromise of cell barrier integrity and loss of nasal cilia and ciliary beating function, especially during Delta infection. Overall, Omicron was optimized for replication in the upper respiratory tract and least favorable in the lower respiratory cell line, and Delta was the most cytopathic for both upper and lower respiratory cells. Our findings highlight the functional differences among VOCs at the cellular level and imply distinct mechanisms of pathogenesis in infected individuals. IMPORTANCE Comparative analysis of infections by SARS-CoV-2 ancestral virus and variants of concern, including Alpha, Beta, Delta, and Omicron, indicated that variants were selected for efficiency in replication. In infections of patient-derived primary nasal cultures grown at air-liquid interface to model upper respiratory infection, Omicron reached the highest titers at early time points, a finding that was confirmed by parallel population sampling studies. While all infections overcame dsRNA-mediated host responses, infections with Omicron induced the strongest interferon and interferon-stimulated gene response. In both primary nasal cultures and lower respiratory cell line, infections by Delta were most damaging to the cells as indicated by syncytia formation, loss of cell barrier integrity, and nasal ciliary function.
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Affiliation(s)
- Nikhila S. Tanneti
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Anant K. Patel
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Li Hui Tan
- Department of Otorhinolaryngology- Head and Neck Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Andrew D. Marques
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ranawaka A. P. M. Perera
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Scott Sherrill-Mix
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Brendan J. Kelly
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David M. Renner
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Ronald G. Collman
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kyle Rodino
- Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Carole Lee
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Frederic D. Bushman
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Noam A. Cohen
- Department of Otorhinolaryngology- Head and Neck Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
- Corporal Michael J. Crescenz VA Medical Center, Surgical Services, Philadelphia, Pennsylvania, USA
- Monell Chemical Senses Center, Philadelphia, Pennsylvania, USA
| | - Susan R. Weiss
- Department of Microbiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
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16
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Sila T, Surasombatpattana S, Rajborirug S, Laochareonsuk W, Choochuen P, Kongkamol C, Ingviya T, Prompat N, Mahasirimongkol S, Sangkhathat S, Aiewsakun P. SARS-CoV-2 variant with the spike protein mutation F306L in the southern border provinces of Thailand. Sci Rep 2024; 14:7729. [PMID: 38565881 PMCID: PMC10987673 DOI: 10.1038/s41598-024-56646-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 03/08/2024] [Indexed: 04/04/2024] Open
Abstract
The southernmost part of Thailand is a unique and culturally diverse region that has been greatly affected by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak during the coronavirus disease-2019 pandemic. To gain insights into this situation, we analyzed 1942 whole-genome sequences of SARS-CoV-2 obtained from the five southernmost provinces of Thailand between April 2021 and March 2022, together with those publicly available in the Global Initiative on Sharing All Influenza Data database. Our analysis revealed evidence for transboundary transmissions of the virus in and out of the five southernmost provinces during the study period, from both domestic and international sources. The most prevalent viral variant in our sequence dataset was the Delta B.1.617.2.85 variant, also known as the Delta AY.85 variant, with many samples carrying a non-synonymous mutation F306L in their spike protein. Protein-protein docking and binding interface analyses suggested that the mutation may enhance the binding between the spike protein and host cell receptor protein angiotensin-converting enzyme 2, and we found that the mutation was significantly associated with an increased fatality rate. This mutation has also been observed in other SARS-CoV-2 variants, suggesting that it is of particular interest and should be monitored.
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Affiliation(s)
- Thanit Sila
- Department of Pathology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand
| | - Smonrapat Surasombatpattana
- Department of Pathology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand
| | - Songyos Rajborirug
- Department of Epidemiology, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand
| | - Wison Laochareonsuk
- Division of Surgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand
- Translational Medicine Research Center, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand
| | - Pongsakorn Choochuen
- Translational Medicine Research Center, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand
- Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand
| | - Chanon Kongkamol
- Department of Family Medicine and Preventive Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand
| | - Thammasin Ingviya
- Department of Family Medicine and Preventive Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand
| | - Napat Prompat
- Faculty of Medical Technology, Medical of Technology Service Center, Prince of Songkla University, Songkhla, 90110, Thailand
| | - Surakameth Mahasirimongkol
- Department of Medical Sciences, Genetics Center, Medical Life Sciences Institute, Ministry of Public Health, Nonthaburi, 11000, Thailand
| | - Surasak Sangkhathat
- Division of Surgery, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand.
- Translational Medicine Research Center, Faculty of Medicine, Prince of Songkla University, Hat Yai, Songkhla, 90110, Thailand.
| | - Pakorn Aiewsakun
- Pornchai Matangkasombut Center for Microbial Genomics, Department of Microbiology, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand.
- Department of Microbiology, Faculty of Science, Mahidol University, Bangkok, 10400, Thailand.
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17
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Alrezaihi A, Penrice-Randal R, Dong X, Prince T, Randle N, Semple MG, Openshaw PJM, MacGill T, Myers T, Orr R, Zakotnik S, Suljič A, Avšič-Županc T, Petrovec M, Korva M, AlJabr W, Hiscox JA. Enrichment of SARS-CoV-2 sequence from nasopharyngeal swabs whilst identifying the nasal microbiome. J Clin Virol 2024; 171:105620. [PMID: 38237303 DOI: 10.1016/j.jcv.2023.105620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 11/06/2023] [Accepted: 11/18/2023] [Indexed: 03/17/2024]
Abstract
Simultaneously characterising the genomic information of coronaviruses and the underlying nasal microbiome from a single clinical sample would help characterise infection and disease. Metatranscriptomic approaches can be used to sequence SARS-CoV-2 (and other coronaviruses) and identify mRNAs associated with active transcription in the nasal microbiome. However, given the large sequence background, unenriched metatranscriptomic approaches often do not sequence SARS-CoV-2 to sufficient read and coverage depth to obtain a consensus genome, especially with moderate and low viral loads from clinical samples. In this study, various enrichment methods were assessed to detect SARS-CoV-2, identify lineages and define the nasal microbiome. The methods were underpinned by Oxford Nanopore long-read sequencing and variations of sequence independent single primer amplification (SISPA). The utility of the method(s) was also validated on samples from patients infected seasonal coronaviruses. The feasibility of profiling the nasal microbiome using these enrichment methods was explored. The findings shed light on the performance of different enrichment strategies and their applicability in characterising the composition of the nasal microbiome.
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Affiliation(s)
| | | | | | | | | | - Malcolm G Semple
- University of Liverpool, Liverpool, UK; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, UK; Alder Hey Children's Hospital, Liverpool, UK
| | | | - Tracy MacGill
- Office of Counterterrorism and Emerging Threats, U.S. Food and Drug Administration, Silver Spring, USA
| | - Todd Myers
- Office of Counterterrorism and Emerging Threats, U.S. Food and Drug Administration, Silver Spring, USA
| | - Robert Orr
- Office of Counterterrorism and Emerging Threats, U.S. Food and Drug Administration, Silver Spring, USA
| | | | - Alen Suljič
- University of Ljubljana, Ljubljana, Slovenia
| | | | | | - Miša Korva
- University of Ljubljana, Ljubljana, Slovenia
| | - Waleed AlJabr
- University of Liverpool, Liverpool, UK; King Fahad Medical City, Riyadh, Saudi Arabia
| | - Julian A Hiscox
- University of Liverpool, Liverpool, UK; NIHR Health Protection Research Unit in Emerging and Zoonotic Infections, Liverpool, UK; Agency for Science, Technology and Research (A*STAR), Singapore.
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18
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Yu Q, Ascensao JA, Okada T, Boyd O, Volz E, Hallatschek O. Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England. PLoS Pathog 2024; 20:e1012090. [PMID: 38620033 PMCID: PMC11045146 DOI: 10.1371/journal.ppat.1012090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 04/25/2024] [Accepted: 03/03/2024] [Indexed: 04/17/2024] Open
Abstract
Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don't yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.
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Affiliation(s)
- QinQin Yu
- Department of Physics, University of California, Berkeley, California, United States of America
| | - Joao A. Ascensao
- Department of Bioengineering, University of California, Berkeley, California, United States of America
| | - Takashi Okada
- Department of Physics, University of California, Berkeley, California, United States of America
- Department of Integrative Biology, University of California, Berkeley, California, United States of America
- Institute for Life and Medical Sciences, Kyoto University, Kyoto, Japan
- RIKEN iTHEMS, Wako, Saitama, Japan
| | | | - Olivia Boyd
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Erik Volz
- MRC Centre for Global Infectious Disease Analysis, Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Oskar Hallatschek
- Department of Physics, University of California, Berkeley, California, United States of America
- Department of Integrative Biology, University of California, Berkeley, California, United States of America
- Peter Debye Institute for Soft Matter Physics, Leipzig University, Leipzig, Germany
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19
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Liu P, Cai J, Tian H, Li J, Lu L, Xu M, Zhu X, Fu X, Wang X, Zhong H, Jia R, Ge Y, Zhu Y, Zeng M, Xu J. Characteristics of SARS-CoV-2 Omicron BA.5 variants in Shanghai after ending the zero-COVID policy in December 2022: a clinical and genomic analysis. Front Microbiol 2024; 15:1372078. [PMID: 38605705 PMCID: PMC11007228 DOI: 10.3389/fmicb.2024.1372078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 03/15/2024] [Indexed: 04/13/2024] Open
Abstract
Introduction An unprecedented surge of Omicron infections appeared nationwide in China in December 2022 after the adjustment of the COVID-19 response policy. Here, we report the clinical and genomic characteristics of SARS-CoV-2 infections among children in Shanghai during this outbreak. Methods A total of 64 children with symptomatic COVID-19 were enrolled. SARS-CoV-2 whole genome sequences were obtained using next-generation sequencing (NGS) technology. Patient demographics and clinical characteristics were compared between variants. Phylogenetic tree, mutation spectrum, and the impact of unique mutations on SARS-CoV-2 proteins were analysed in silico. Results The genomic monitoring revealed that the emerging BA.5.2.48 and BF.7.14 were the dominant variants. The BA.5.2.48 infections were more frequently observed to experience vomiting/diarrhea and less frequently present cough compared to the BF.7.14 infections among patients without comorbidities in the study. The high-frequency unique non-synonymous mutations were present in BA.5.2.48 (N:Q241K) and BF.7.14 (nsp2:V94L, nsp12:L247F, S:C1243F, ORF7a:H47Y) with respect to their parental lineages. Of these mutations, S:C1243F, nsp12:L247F, and ORF7a:H47Y protein were predicted to have a deleterious effect on the protein function. Besides, nsp2:V94L and nsp12:L247F were predicted to destabilize the proteins. Discussion Further in vitro to in vivo studies are needed to verify the role of these specific mutations in viral fitness. In addition, continuous genomic monitoring and clinical manifestation assessments of the emerging variants will still be crucial for the effective responses to the ongoing COVID-19 pandemic.
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Affiliation(s)
- Pengcheng Liu
- Department of Clinical Laboratory, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Jiehao Cai
- Department of Infectious Diseases, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - He Tian
- Department of Infectious Diseases, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Jingjing Li
- Department of Infectious Diseases, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Lijuan Lu
- Department of Clinical Laboratory, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Menghua Xu
- Department of Clinical Laboratory, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Xunhua Zhu
- Department of Clinical Laboratory, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Xiaomin Fu
- Department of Infectious Diseases, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Xiangshi Wang
- Department of Infectious Diseases, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Huaqing Zhong
- Department of Clinical Laboratory, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Ran Jia
- Department of Clinical Laboratory, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Yanling Ge
- Department of Infectious Diseases, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Yanfeng Zhu
- Department of Infectious Diseases, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Mei Zeng
- Department of Infectious Diseases, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
| | - Jin Xu
- Department of Clinical Laboratory, National Children’s Medical Center, Children’s Hospital of Fudan University, Shanghai, China
- Shanghai Institute of Infectious Disease and Biosecurity, Fudan University, Shanghai, China
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20
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Saha G, Sawmya S, Saha A, Akil MA, Tasnim S, Rahman MS, Rahman MS. PRIEST: predicting viral mutations with immune escape capability of SARS-CoV-2 using temporal evolutionary information. Brief Bioinform 2024; 25:bbae218. [PMID: 38742520 PMCID: PMC11091746 DOI: 10.1093/bib/bbae218] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 04/04/2024] [Accepted: 04/06/2024] [Indexed: 05/16/2024] Open
Abstract
The dynamic evolution of the severe acute respiratory syndrome coronavirus 2 virus is primarily driven by mutations in its genetic sequence, culminating in the emergence of variants with increased capability to evade host immune responses. Accurate prediction of such mutations is fundamental in mitigating pandemic spread and developing effective control measures. This study introduces a robust and interpretable deep-learning approach called PRIEST. This innovative model leverages time-series viral sequences to foresee potential viral mutations. Our comprehensive experimental evaluations underscore PRIEST's proficiency in accurately predicting immune-evading mutations. Our work represents a substantial step in utilizing deep-learning methodologies for anticipatory viral mutation analysis and pandemic response.
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Affiliation(s)
- Gourab Saha
- Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - Shashata Sawmya
- Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - Arpita Saha
- Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - Md Ajwad Akil
- Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - Sadia Tasnim
- Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - Md Saifur Rahman
- Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
| | - M Sohel Rahman
- Department of Computer Science and Engineering, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
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21
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St Clair LA, Eldesouki RE, Sachithanandham J, Yin A, Fall A, Morris CP, Norton JM, Abdullah O, Dhakal S, Barranta C, Golding H, Bersoff-Matcha SJ, Pilgrim-Grayson C, Berhane L, Cox AL, Burd I, Pekosz A, Mostafa HH, Klein EY, Klein SL. Reduced control of SARS-CoV-2 infection associates with lower mucosal antibody responses in pregnancy. mSphere 2024; 9:e0081223. [PMID: 38426787 PMCID: PMC10964408 DOI: 10.1128/msphere.00812-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 01/10/2024] [Indexed: 03/02/2024] Open
Abstract
Pregnant patients are at greater risk of hospitalization with severe COVID-19 than non-pregnant people. This was a retrospective observational cohort study of remnant clinical specimens from patients who visited acute care hospitals within the Johns Hopkins Health System in the Baltimore, MD-Washington DC, area between October 2020 and May 2022. Participants included confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-infected pregnant people and matched non-pregnant people (the matching criteria included age, race/ethnicity, area deprivation index, insurance status, and vaccination status to ensure matched demographics). The primary dependent measures were clinical COVID-19 outcomes, infectious virus recovery, viral RNA levels, and mucosal anti-spike (S) IgG titers from upper respiratory tract samples. A total of 452 individuals (117 pregnant and 335 non-pregnant) were included in the study, with both vaccinated and unvaccinated individuals represented. Pregnant patients were at increased risk of hospitalization (odds ratio [OR] = 4.2; confidence interval [CI] = 2.0-8.6), intensive care unit admittance (OR = 4.5; CI = 1.2-14.2), and being placed on supplemental oxygen therapy (OR = 3.1; CI = 1.3-6.9). Individuals infected during their third trimester had higher mucosal anti-S IgG titers and lower viral RNA levels (P < 0.05) than those infected during their first or second trimesters. Pregnant individuals experiencing breakthrough infections due to the Omicron variant had reduced anti-S IgG compared to non-pregnant patients (P < 0.05). The observed increased severity of COVID-19 and reduced mucosal antibody responses particularly among pregnant participants infected with the Omicron variant suggest that maintaining high levels of SARS-CoV-2 immunity through booster vaccines may be important for the protection of this at-risk population.IMPORTANCEIn this retrospective observational cohort study, we analyzed remnant clinical samples from non-pregnant and pregnant individuals with confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections who visited the Johns Hopkins Hospital System between October 2020 and May 2022. Disease severity, including intensive care unit admission, was greater among pregnant than non-pregnant patients. Vaccination reduced recovery of infectious virus and viral RNA levels in non-pregnant patients, but not in pregnant patients. In pregnant patients, increased nasopharyngeal viral RNA levels and recovery of infectious virus were associated with reduced mucosal IgG antibody responses, especially among women in their first trimester of pregnancy or experiencing breakthrough infections from Omicron variants. Taken together, this study provides insights into how pregnant patients are at greater risk of severe COVID-19. The novelty of this study is that it focuses on the relationship between the mucosal antibody response and its association with virus load and disease outcomes in pregnant people, whereas previous studies have focused on serological immunity. Vaccination status, gestational age, and SARS-CoV-2 omicron variant impact mucosal antibody responses and recovery of infectious virus from pregnant patients.
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Affiliation(s)
- Laura A. St Clair
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Raghda E. Eldesouki
- Department of Pathology, Division of Medical Microbiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Medical Genetics Unit, School of Medicine, Suez Canal University, Ismailia, Egypt
| | - Jaiprasath Sachithanandham
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Anna Yin
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Amary Fall
- Department of Pathology, Division of Medical Microbiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - C. Paul Morris
- Department of Pathology, Division of Medical Microbiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- National Institute of Allergy and Infectious Disease, National Institutes of Health, Bethesda, Maryland, USA
| | - Julie M. Norton
- Department of Pathology, Division of Medical Microbiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Omar Abdullah
- Department of Pathology, Division of Medical Microbiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Santosh Dhakal
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Caelan Barranta
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Hana Golding
- Division of Viral Products, Center of Biologics Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | | | - Catherine Pilgrim-Grayson
- Division of Urology, Obstetrics, and Gynecology, Office of Rare Diseases, Pediatrics, Urologic and Reproductive Medicine and Office of New Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Leah Berhane
- Division of Urology, Obstetrics, and Gynecology, Office of Rare Diseases, Pediatrics, Urologic and Reproductive Medicine and Office of New Drugs, Center for Drug Evaluation and Research, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
| | - Andrea L. Cox
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Bloomberg Kimmel Institute for Cancer Immunotherapy, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Irina Burd
- Department of Obstetrics, Gynecology and Reproductive Sciences, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Andrew Pekosz
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Heba H. Mostafa
- Department of Pathology, Division of Medical Microbiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Eili Y. Klein
- Department of Emergency Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- Center for Disease Dynamics, Economics, and Policy, United Nations Office for Disease Risk Reduction, Washington DC, USA
| | - Sabra L. Klein
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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22
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Dzieciolowska S, Charest H, Roy T, Fafard J, Carazo S, Levade I, Longtin J, Parkes L, Beaulac SN, Villeneuve J, Savard P, Corbeil J, De Serres G, Longtin Y. Timing and Predictors of Loss of Infectivity Among Healthcare Workers With Mild Primary and Recurrent COVID-19: A Prospective Observational Cohort Study. Clin Infect Dis 2024; 78:613-624. [PMID: 37675577 PMCID: PMC10954326 DOI: 10.1093/cid/ciad535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 08/21/2023] [Accepted: 08/30/2023] [Indexed: 09/08/2023] Open
Abstract
BACKGROUND There is a need to understand the duration of infectivity of primary and recurrent coronavirus disease 2019 (COVID-19) and identify predictors of loss of infectivity. METHODS Prospective observational cohort study with serial viral culture, rapid antigen detection test (RADT) and reverse transcription polymerase chain reaction (RT-PCR) on nasopharyngeal specimens of healthcare workers with COVID-19. The primary outcome was viral culture positivity as indicative of infectivity. Predictors of loss of infectivity were determined using multivariate regression model. The performance of the US Centers for Disease Control and Prevention (CDC) criteria (fever resolution, symptom improvement, and negative RADT) to predict loss of infectivity was also investigated. RESULTS In total, 121 participants (91 female [79.3%]; average age, 40 years) were enrolled. Most (n = 107, 88.4%) had received ≥3 severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccine doses, and 20 (16.5%) had COVID-19 previously. Viral culture positivity decreased from 71.9% (87/121) on day 5 of infection to 18.2% (22/121) on day 10. Participants with recurrent COVID-19 had a lower likelihood of infectivity than those with primary COVID-19 at each follow-up (day 5 odds ratio [OR], 0.14; P < .001]; day 7 OR, 0.04; P = .003]) and were all non-infective by day 10 (P = .02). Independent predictors of infectivity included prior COVID-19 (adjusted OR [aOR] on day 5, 0.005; P = .003), an RT-PCR cycle threshold [Ct] value <23 (aOR on day 5, 22.75; P < .001) but not symptom improvement or RADT result.The CDC criteria would identify 36% (24/67) of all non-infectious individuals on day 7. However, 17% (5/29) of those meeting all the criteria had a positive viral culture. CONCLUSIONS Infectivity of recurrent COVID-19 is shorter than primary infections. Loss of infectivity algorithms could be optimized.
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Affiliation(s)
| | - Hugues Charest
- Faculté de médecine, Université de Montréal, Montréal, Canada
- Laboratoire de Santé Publique du Québec, Sainte-Anne-de-Bellevue, Canada
- Institut National de Santé Publique du Québec, Québec City, Canada
| | - Tonya Roy
- Laboratoire de Santé Publique du Québec, Sainte-Anne-de-Bellevue, Canada
- Institut National de Santé Publique du Québec, Québec City, Canada
| | - Judith Fafard
- Laboratoire de Santé Publique du Québec, Sainte-Anne-de-Bellevue, Canada
- Institut National de Santé Publique du Québec, Québec City, Canada
| | - Sara Carazo
- Institut National de Santé Publique du Québec, Québec City, Canada
- Université Laval, Québec City, Canada
| | - Ines Levade
- Laboratoire de Santé Publique du Québec, Sainte-Anne-de-Bellevue, Canada
- Institut National de Santé Publique du Québec, Québec City, Canada
| | - Jean Longtin
- CHU de Québec—Université Laval, Québec City, Canada
| | - Leighanne Parkes
- McGill University Faculty of Medicine, Montréal, Canada
- Jewish General Hospital Sir Mortimer B. Davis, Montréal, Canada
| | - Sylvie Nancy Beaulac
- Laboratoire de Santé Publique du Québec, Sainte-Anne-de-Bellevue, Canada
- Institut National de Santé Publique du Québec, Québec City, Canada
| | | | - Patrice Savard
- Faculté de médecine, Université de Montréal, Montréal, Canada
- Centre Hospitalier de l’Université de Montréal (CHUM) and CHUM Research Center, Montréal, Canada
| | | | - Gaston De Serres
- Institut National de Santé Publique du Québec, Québec City, Canada
- Université Laval, Québec City, Canada
| | - Yves Longtin
- McGill University Faculty of Medicine, Montréal, Canada
- Jewish General Hospital Sir Mortimer B. Davis, Montréal, Canada
- Lady Davis Research Institute, Montréal, Canada
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23
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Cahuantzi R, Lythgoe KA, Hall I, Pellis L, House T. Unsupervised identification of significant lineages of SARS-CoV-2 through scalable machine learning methods. Proc Natl Acad Sci U S A 2024; 121:e2317284121. [PMID: 38478692 PMCID: PMC10962941 DOI: 10.1073/pnas.2317284121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 02/05/2024] [Indexed: 03/21/2024] Open
Abstract
Since its emergence in late 2019, SARS-CoV-2 has diversified into a large number of lineages and caused multiple waves of infection globally. Novel lineages have the potential to spread rapidly and internationally if they have higher intrinsic transmissibility and/or can evade host immune responses, as has been seen with the Alpha, Delta, and Omicron variants of concern. They can also cause increased mortality and morbidity if they have increased virulence, as was seen for Alpha and Delta. Phylogenetic methods provide the "gold standard" for representing the global diversity of SARS-CoV-2 and to identify newly emerging lineages. However, these methods are computationally expensive, struggle when datasets get too large, and require manual curation to designate new lineages. These challenges provide a motivation to develop complementary methods that can incorporate all of the genetic data available without down-sampling to extract meaningful information rapidly and with minimal curation. In this paper, we demonstrate the utility of using algorithmic approaches based on word-statistics to represent whole sequences, bringing speed, scalability, and interpretability to the construction of genetic topologies. While not serving as a substitute for current phylogenetic analyses, the proposed methods can be used as a complementary, and fully automatable, approach to identify and confirm new emerging variants.
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Affiliation(s)
- Roberto Cahuantzi
- Department of Mathematics, The University of Manchester, ManchesterM13 9PL, United Kingdom
- United Kingdom Health Security Agency, University of Oxford, OxfordOX3 7LF, United Kingdom
| | - Katrina A. Lythgoe
- Department of Biology, University of Oxford, OxfordOX1 3SZ, United Kingdom
- Big Data Institute, University of Oxford, OxfordOX3 7LF, United Kingdom
- Pandemic Sciences Institute, University of Oxford, OxfordOX3 7LF, United Kingdom
| | - Ian Hall
- Department of Mathematics, The University of Manchester, ManchesterM13 9PL, United Kingdom
| | - Lorenzo Pellis
- Department of Mathematics, The University of Manchester, ManchesterM13 9PL, United Kingdom
| | - Thomas House
- Department of Mathematics, The University of Manchester, ManchesterM13 9PL, United Kingdom
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24
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Magaret CA, Li L, deCamp AC, Rolland M, Juraska M, Williamson BD, Ludwig J, Molitor C, Benkeser D, Luedtke A, Simpkins B, Heng F, Sun Y, Carpp LN, Bai H, Dearlove BL, Giorgi EE, Jongeneelen M, Brandenburg B, McCallum M, Bowen JE, Veesler D, Sadoff J, Gray GE, Roels S, Vandebosch A, Stieh DJ, Le Gars M, Vingerhoets J, Grinsztejn B, Goepfert PA, de Sousa LP, Silva MST, Casapia M, Losso MH, Little SJ, Gaur A, Bekker LG, Garrett N, Truyers C, Van Dromme I, Swann E, Marovich MA, Follmann D, Neuzil KM, Corey L, Greninger AL, Roychoudhury P, Hyrien O, Gilbert PB. Quantifying how single dose Ad26.COV2.S vaccine efficacy depends on Spike sequence features. Nat Commun 2024; 15:2175. [PMID: 38467646 PMCID: PMC10928100 DOI: 10.1038/s41467-024-46536-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 02/29/2024] [Indexed: 03/13/2024] Open
Abstract
In the ENSEMBLE randomized, placebo-controlled phase 3 trial (NCT04505722), estimated single-dose Ad26.COV2.S vaccine efficacy (VE) was 56% against moderate to severe-critical COVID-19. SARS-CoV-2 Spike sequences were determined from 484 vaccine and 1,067 placebo recipients who acquired COVID-19. In this set of prespecified analyses, we show that in Latin America, VE was significantly lower against Lambda vs. Reference and against Lambda vs. non-Lambda [family-wise error rate (FWER) p < 0.05]. VE differed by residue match vs. mismatch to the vaccine-insert at 16 amino acid positions (4 FWER p < 0.05; 12 q-value ≤ 0.20); significantly decreased with physicochemical-weighted Hamming distance to the vaccine-strain sequence for Spike, receptor-binding domain, N-terminal domain, and S1 (FWER p < 0.001); differed (FWER ≤ 0.05) by distance to the vaccine strain measured by 9 antibody-epitope escape scores and 4 NTD neutralization-impacting features; and decreased (p = 0.011) with neutralization resistance level to vaccinee sera. VE against severe-critical COVID-19 was stable across most sequence features but lower against the most distant viruses.
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Affiliation(s)
- Craig A Magaret
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Li Li
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Allan C deCamp
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Morgane Rolland
- US Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
| | - Michal Juraska
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Brian D Williamson
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Biostatistics Division, Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - James Ludwig
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Cindy Molitor
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - David Benkeser
- Departments of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Alex Luedtke
- Department of Statistics, University of Washington, Seattle, WA, USA
| | - Brian Simpkins
- Department of Computer Science, Pitzer College, Claremont, CA, USA
| | - Fei Heng
- University of North Florida, Jacksonville, FL, USA
| | - Yanqing Sun
- University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Lindsay N Carpp
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Hongjun Bai
- US Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
| | - Bethany L Dearlove
- US Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, MD, USA
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
| | - Elena E Giorgi
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Mandy Jongeneelen
- Johnson & Johnson Innovative Medicine, Janssen Vaccines & Prevention B.V, Leiden, The Netherlands
| | - Boerries Brandenburg
- Johnson & Johnson Innovative Medicine, Janssen Vaccines & Prevention B.V, Leiden, The Netherlands
| | - Matthew McCallum
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - John E Bowen
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - David Veesler
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- Howard Hughes Medical Institute, University of Washington, Seattle, WA, USA
| | - Jerald Sadoff
- Johnson & Johnson Innovative Medicine, Janssen Vaccines & Prevention B.V, Leiden, The Netherlands
| | - Glenda E Gray
- Perinatal HIV Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- South African Medical Research Council, Cape Town, South Africa
| | - Sanne Roels
- Janssen R&D, a division of Janssen Pharmaceutica NV, Beerse, Belgium
| | - An Vandebosch
- Janssen R&D, a division of Janssen Pharmaceutica NV, Beerse, Belgium
| | - Daniel J Stieh
- Johnson & Johnson Innovative Medicine, Janssen Vaccines & Prevention B.V, Leiden, The Netherlands
| | - Mathieu Le Gars
- Johnson & Johnson Innovative Medicine, Janssen Vaccines & Prevention B.V, Leiden, The Netherlands
| | - Johan Vingerhoets
- Janssen R&D, a division of Janssen Pharmaceutica NV, Beerse, Belgium
| | - Beatriz Grinsztejn
- Evandro Chagas National Institute of Infectious Diseases-Fundação Oswaldo Cruz, Rio de Janeiro, RJ, Brazil
| | - Paul A Goepfert
- Division of Infectious Diseases, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Leonardo Paiva de Sousa
- Evandro Chagas National Institute of Infectious Diseases-Fundação Oswaldo Cruz, Rio de Janeiro, RJ, Brazil
| | - Mayara Secco Torres Silva
- Evandro Chagas National Institute of Infectious Diseases-Fundação Oswaldo Cruz, Rio de Janeiro, RJ, Brazil
| | - Martin Casapia
- Facultad de Medicina Humana, Universidad Nacional de la Amazonia Peru, Iquitos, Peru
| | - Marcelo H Losso
- Hospital General de Agudos José María Ramos Mejia, Buenos Aires, Argentina
| | - Susan J Little
- Division of Infectious Diseases, University of California San Diego, La Jolla, CA, USA
| | - Aditya Gaur
- Department of Infectious Diseases, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Linda-Gail Bekker
- The Desmond Tutu HIV Centre, University of Cape Town, Observatory, Cape Town, South Africa
| | - Nigel Garrett
- Centre for the AIDS Programme of Research in South Africa, University of KwaZulu-Natal, Durban, South Africa
- Discipline of Public Health Medicine, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa
| | - Carla Truyers
- Janssen R&D, a division of Janssen Pharmaceutica NV, Beerse, Belgium
| | - Ilse Van Dromme
- Janssen R&D, a division of Janssen Pharmaceutica NV, Beerse, Belgium
| | - Edith Swann
- Vaccine Research Program, Division of AIDS, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Mary A Marovich
- Vaccine Research Program, Division of AIDS, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Dean Follmann
- Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Kathleen M Neuzil
- Center for Vaccine Development and Global Health, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Lawrence Corey
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Alexander L Greninger
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Pavitra Roychoudhury
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Ollivier Hyrien
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Peter B Gilbert
- Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
- Department of Biostatistics, University of Washington School of Public Health, Seattle, WA, USA.
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25
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Álvarez-Herrera M, Sevilla J, Ruiz-Rodriguez P, Vergara A, Vila J, Cano-Jiménez P, González-Candelas F, Comas I, Coscollá M. VIPERA: Viral Intra-Patient Evolution Reporting and Analysis. Virus Evol 2024; 10:veae018. [PMID: 38510921 PMCID: PMC10953798 DOI: 10.1093/ve/veae018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 02/02/2024] [Accepted: 03/05/2024] [Indexed: 03/22/2024] Open
Abstract
Viral mutations within patients nurture the adaptive potential of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) during chronic infections, which are a potential source of variants of concern. However, there is no integrated framework for the evolutionary analysis of intra-patient SARS-CoV-2 serial samples. Herein, we describe Viral Intra-Patient Evolution Reporting and Analysis (VIPERA), a new software that integrates the evaluation of the intra-patient ancestry of SARS-CoV-2 sequences with the analysis of evolutionary trajectories of serial sequences from the same viral infection. We have validated it using positive and negative control datasets and have successfully applied it to a new case, which revealed population dynamics and evidence of adaptive evolution. VIPERA is available under a free software license at https://github.com/PathoGenOmics-Lab/VIPERA.
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Affiliation(s)
- Miguel Álvarez-Herrera
- Institute for Integrative Systems Biology (I2SysBio, University of Valencia—CSIC), FISABIO Joint Research Unit ‘Infection and Public Health’, C/Agustín Escardino, 9, Paterna 46980, Spain
| | - Jordi Sevilla
- Institute for Integrative Systems Biology (I2SysBio, University of Valencia—CSIC), FISABIO Joint Research Unit ‘Infection and Public Health’, C/Agustín Escardino, 9, Paterna 46980, Spain
| | - Paula Ruiz-Rodriguez
- Institute for Integrative Systems Biology (I2SysBio, University of Valencia—CSIC), FISABIO Joint Research Unit ‘Infection and Public Health’, C/Agustín Escardino, 9, Paterna 46980, Spain
| | - Andrea Vergara
- Department of Clinical Microbiology, CDB, Hospital Clínic of Barcelona; University of Barcelona; ISGlobal, C. de Villarroel, 170, Barcelona 08007, Spain
- CIBER of Infectious Diseases (CIBERINFEC), Av. Monforte de Lemos, 3-5, Madrid 28029, Spain
| | - Jordi Vila
- Department of Clinical Microbiology, CDB, Hospital Clínic of Barcelona; University of Barcelona; ISGlobal, C. de Villarroel, 170, Barcelona 08007, Spain
- CIBER of Infectious Diseases (CIBERINFEC), Av. Monforte de Lemos, 3-5, Madrid 28029, Spain
| | - Pablo Cano-Jiménez
- Institute of Biomedicine of Valencia (IBV-CSIC), C/ Jaime Roig, 11, Valencia 46010, Spain
| | - Fernando González-Candelas
- Institute for Integrative Systems Biology (I2SysBio, University of Valencia—CSIC), FISABIO Joint Research Unit ‘Infection and Public Health’, C/Agustín Escardino, 9, Paterna 46980, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5, Madrid 28029, Spain
| | - Iñaki Comas
- Institute of Biomedicine of Valencia (IBV-CSIC), C/ Jaime Roig, 11, Valencia 46010, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Av. Monforte de Lemos, 3-5, Madrid 28029, Spain
| | - Mireia Coscollá
- Institute for Integrative Systems Biology (I2SysBio, University of Valencia—CSIC), FISABIO Joint Research Unit ‘Infection and Public Health’, C/Agustín Escardino, 9, Paterna 46980, Spain
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26
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Arantes I, Gomes M, Ito K, Sarafim S, Gräf T, Miyajima F, Khouri R, de Carvalho FC, de Almeida WAF, Siqueira MM, Resende PC, Naveca FG, Bello G. Spatiotemporal dynamics and epidemiological impact of SARS-CoV-2 XBB lineage dissemination in Brazil in 2023. Microbiol Spectr 2024; 12:e0383123. [PMID: 38315011 PMCID: PMC10913747 DOI: 10.1128/spectrum.03831-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Accepted: 12/27/2023] [Indexed: 02/07/2024] Open
Abstract
The SARS-CoV-2 XBB is a group of highly immune-evasive lineages of the Omicron variant of concern that emerged by recombining BA.2-descendent lineages and spread worldwide during 2023. In this study, we combine SARS-CoV-2 genomic data (n = 11,065 sequences) with epidemiological data of severe acute respiratory infection (SARI) cases collected in Brazil between October 2022 and July 2023 to reconstruct the space-time dynamics and epidemiologic impact of XBB dissemination in the country. Our analyses revealed that the introduction and local emergence of lineages carrying convergent mutations within the Spike protein, especially F486P, F456L, and L455F, propelled the spread of XBB* lineages in Brazil. The average relative instantaneous reproduction numbers of XBB* + F486P, XBB* + F486P + F456L, and XBB* + F486P + F456L + L455F lineages in Brazil were estimated to be 1.24, 1.33, and 1.48 higher than that of other co-circulating lineages (mainly BQ.1*/BE*), respectively. Despite such a growth advantage, the dissemination of these XBB* lineages had a reduced impact on Brazil's epidemiological scenario concerning previous Omicron subvariants. The peak number of SARI cases from SARS-CoV-2 during the XBB wave was approximately 90%, 80%, and 70% lower than that observed during the previous BA.1*, BA.5*, and BQ.1* waves, respectively. These findings revealed the emergence of multiple XBB lineages with progressively increasing growth advantage, yet with relatively limited epidemiological impact in Brazil throughout 2023. The XBB* + F486P + F456L + L455F lineages stand out for their heightened transmissibility, warranting close monitoring in the months ahead. IMPORTANCE Brazil was one the most affected countries by the SARS-CoV-2 pandemic, with more than 700,000 deaths by mid-2023. This study reconstructs the dissemination of the virus in the country in the first half of 2023, a period characterized by the dissemination of descendants of XBB.1, a recombinant of Omicron BA.2 lineages evolved in late 2022. The analysis supports that XBB dissemination was marked by the continuous emergence of indigenous lineages bearing similar mutations in key sites of their Spike protein, a process followed by continuous increments in transmissibility, and without repercussions in the incidence of severe cases. Thus, the results suggest that the epidemiological impact of the spread of a SARS-CoV-2 variant is influenced by an intricate interplay of factors that extend beyond the virus's transmissibility alone. The study also underlines the need for SARS-CoV-2 genomic surveillance that allows the monitoring of its ever-shifting composition.
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Affiliation(s)
- Ighor Arantes
- Laboratório de Arbovírus e Vírus Hemorrágicos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Marcelo Gomes
- Grupo de Métodos Analíticos em Vigilância Epidemiológica, Fiocruz, Rio de Janeiro, Brazil
| | - Kimihito Ito
- International Institute for Zoonosis Control, Hokkaido University, Hokkaido, Japan
| | - Sharbilla Sarafim
- Laboratório de Arbovírus e Vírus Hemorrágicos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Tiago Gräf
- Laboratório de Virologia Molecular, Instituto Carlos Chagas, Fiocruz, Curitiba, Brazil
| | | | | | - Felipe Cotrim de Carvalho
- Departamento do Programa Nacional de Imunizações, Coordenação-Geral de Vigilância das doenças imunopreveníveis, Secretaria de Vigilância em saúde e ambiente, Brasília, Brazil
| | - Walquiria Aparecida Ferreira de Almeida
- Departamento do Programa Nacional de Imunizações, Coordenação-Geral de Vigilância das doenças imunopreveníveis, Secretaria de Vigilância em saúde e ambiente, Brasília, Brazil
| | - Marilda Mendonça Siqueira
- Laboratório de Vírus Respiratórios, Exantemáticos, Enterovírus e Emergências Virais, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Paola Cristina Resende
- Laboratório de Vírus Respiratórios, Exantemáticos, Enterovírus e Emergências Virais, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - Felipe Gomes Naveca
- Laboratório de Arbovírus e Vírus Hemorrágicos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
- Núcleo de Vigilância de Vírus Emergentes, Reemergentes ou Negligenciados, Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Gonzalo Bello
- Laboratório de Arbovírus e Vírus Hemorrágicos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
| | - COVID-19 Fiocruz Genomic Surveillance Network
- Laboratório de Arbovírus e Vírus Hemorrágicos, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
- Grupo de Métodos Analíticos em Vigilância Epidemiológica, Fiocruz, Rio de Janeiro, Brazil
- International Institute for Zoonosis Control, Hokkaido University, Hokkaido, Japan
- Laboratório de Virologia Molecular, Instituto Carlos Chagas, Fiocruz, Curitiba, Brazil
- Fiocruz, Fortaleza, Brazil
- Instituto Gonçalo Moniz, Fiocruz, Salvador, Brazil
- Departamento do Programa Nacional de Imunizações, Coordenação-Geral de Vigilância das doenças imunopreveníveis, Secretaria de Vigilância em saúde e ambiente, Brasília, Brazil
- Laboratório de Vírus Respiratórios, Exantemáticos, Enterovírus e Emergências Virais, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Brazil
- Núcleo de Vigilância de Vírus Emergentes, Reemergentes ou Negligenciados, Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
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Martiny HM, Pyrounakis N, Petersen TN, Lukjančenko O, Aarestrup FM, Clausen PTLC, Munk P. ARGprofiler-a pipeline for large-scale analysis of antimicrobial resistance genes and their flanking regions in metagenomic datasets. Bioinformatics 2024; 40:btae086. [PMID: 38377397 PMCID: PMC10918635 DOI: 10.1093/bioinformatics/btae086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 12/11/2023] [Accepted: 02/19/2024] [Indexed: 02/22/2024] Open
Abstract
MOTIVATION Analyzing metagenomic data can be highly valuable for understanding the function and distribution of antimicrobial resistance genes (ARGs). However, there is a need for standardized and reproducible workflows to ensure the comparability of studies, as the current options involve various tools and reference databases, each designed with a specific purpose in mind. RESULTS In this work, we have created the workflow ARGprofiler to process large amounts of raw sequencing reads for studying the composition, distribution, and function of ARGs. ARGprofiler tackles the challenge of deciding which reference database to use by providing the PanRes database of 14 078 unique ARGs that combines several existing collections into one. Our pipeline is designed to not only produce abundance tables of genes and microbes but also to reconstruct the flanking regions of ARGs with ARGextender. ARGextender is a bioinformatic approach combining KMA and SPAdes to recruit reads for a targeted de novo assembly. While our aim is on ARGs, the pipeline also creates Mash sketches for fast searching and comparisons of sequencing runs. AVAILABILITY AND IMPLEMENTATION The ARGprofiler pipeline is a Snakemake workflow that supports the reuse of metagenomic sequencing data and is easily installable and maintained at https://github.com/genomicepidemiology/ARGprofiler.
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Affiliation(s)
- Hannah-Marie Martiny
- Research Group for Genomic Epidemiology, Technical University of Denmark, Henrik Danms Allé, Bygning 204, Kongens Lyngby 2800, Denmark
| | - Nikiforos Pyrounakis
- Research Group for Genomic Epidemiology, Technical University of Denmark, Henrik Danms Allé, Bygning 204, Kongens Lyngby 2800, Denmark
| | - Thomas N Petersen
- Research Group for Genomic Epidemiology, Technical University of Denmark, Henrik Danms Allé, Bygning 204, Kongens Lyngby 2800, Denmark
| | - Oksana Lukjančenko
- Research Group for Genomic Epidemiology, Technical University of Denmark, Henrik Danms Allé, Bygning 204, Kongens Lyngby 2800, Denmark
| | - Frank M Aarestrup
- Research Group for Genomic Epidemiology, Technical University of Denmark, Henrik Danms Allé, Bygning 204, Kongens Lyngby 2800, Denmark
| | - Philip T L C Clausen
- Research Group for Genomic Epidemiology, Technical University of Denmark, Henrik Danms Allé, Bygning 204, Kongens Lyngby 2800, Denmark
| | - Patrick Munk
- Research Group for Genomic Epidemiology, Technical University of Denmark, Henrik Danms Allé, Bygning 204, Kongens Lyngby 2800, Denmark
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Nikiforuk AM, Kuchinski KS, Short K, Roman S, Irvine MA, Prystajecky N, Jassem AN, Patrick DM, Sekirov I. Nasopharyngeal angiotensin converting enzyme 2 (ACE2) expression as a risk-factor for SARS-CoV-2 transmission in concurrent hospital associated outbreaks. BMC Infect Dis 2024; 24:262. [PMID: 38408924 PMCID: PMC10898082 DOI: 10.1186/s12879-024-09067-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 01/28/2024] [Indexed: 02/28/2024] Open
Abstract
BACKGROUND Widespread human-to-human transmission of the severe acute respiratory syndrome coronavirus two (SARS-CoV-2) stems from a strong affinity for the cellular receptor angiotensin converting enzyme two (ACE2). We investigate the relationship between a patient's nasopharyngeal ACE2 transcription and secondary transmission within a series of concurrent hospital associated SARS-CoV-2 outbreaks in British Columbia, Canada. METHODS Epidemiological case data from the outbreak investigations was merged with public health laboratory records and viral lineage calls, from whole genome sequencing, to reconstruct the concurrent outbreaks using infection tracing transmission network analysis. ACE2 transcription and RNA viral load were measured by quantitative real-time polymerase chain reaction. The transmission network was resolved to calculate the number of potential secondary cases. Bivariate and multivariable analyses using Poisson and Negative Binomial regression models was performed to estimate the association between ACE2 transcription the number of SARS-CoV-2 secondary cases. RESULTS The infection tracing transmission network provided n = 76 potential transmission events across n = 103 cases. Bivariate comparisons found that on average ACE2 transcription did not differ between patients and healthcare workers (P = 0.86). High ACE2 transcription was observed in 98.6% of transmission events, either the primary or secondary case had above average ACE2. Multivariable analysis found that the association between ACE2 transcription (log2 fold-change) and the number of secondary transmission events differs between patients and healthcare workers. In health care workers Negative Binomial regression estimated that a one-unit change in ACE2 transcription decreases the number of secondary cases (β = -0.132 (95%CI: -0.255 to -0.0181) adjusting for RNA viral load. Conversely, in patients a one-unit change in ACE2 transcription increases the number of secondary cases (β = 0.187 (95% CI: 0.0101 to 0.370) adjusting for RNA viral load. Sensitivity analysis found no significant relationship between ACE2 and secondary transmission in health care workers and confirmed the positive association among patients. CONCLUSION Our study suggests that ACE2 transcription has a positive association with SARS-CoV-2 secondary transmission in admitted inpatients, but not health care workers in concurrent hospital associated outbreaks, and it should be further investigated as a risk-factor for viral transmission.
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Affiliation(s)
- Aidan M Nikiforuk
- British Columbia Centre for Disease Control, V5Z 4R4, Vancouver, BC, Canada
- School of Population and Public Health, University of British Columbia, V6T 1Z4, Vancouver, BC, Canada
| | - Kevin S Kuchinski
- British Columbia Centre for Disease Control, V5Z 4R4, Vancouver, BC, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, V6T 1Z4, Vancouver, BC, Canada
| | - Katy Short
- Fraser Health Authority, V3L 3C2, New Westminster, BC, Canada
| | - Susan Roman
- Fraser Health Authority, V3L 3C2, New Westminster, BC, Canada
| | - Mike A Irvine
- British Columbia Centre for Disease Control, V5Z 4R4, Vancouver, BC, Canada
- Faculty of Health Sciences, Simon Fraser University, V5A 1S6, Burnaby, BC, Canada
| | - Natalie Prystajecky
- British Columbia Centre for Disease Control, V5Z 4R4, Vancouver, BC, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, V6T 1Z4, Vancouver, BC, Canada
| | - Agatha N Jassem
- British Columbia Centre for Disease Control, V5Z 4R4, Vancouver, BC, Canada
- Department of Pathology and Laboratory Medicine, University of British Columbia, V6T 1Z4, Vancouver, BC, Canada
| | - David M Patrick
- British Columbia Centre for Disease Control, V5Z 4R4, Vancouver, BC, Canada
- School of Population and Public Health, University of British Columbia, V6T 1Z4, Vancouver, BC, Canada
| | - Inna Sekirov
- British Columbia Centre for Disease Control, V5Z 4R4, Vancouver, BC, Canada.
- Department of Pathology and Laboratory Medicine, University of British Columbia, V6T 1Z4, Vancouver, BC, Canada.
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Szabó D, Crowe A, Mamotte C, Strappe P. Natural products as a source of Coronavirus entry inhibitors. Front Cell Infect Microbiol 2024; 14:1353971. [PMID: 38449827 PMCID: PMC10915212 DOI: 10.3389/fcimb.2024.1353971] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 02/01/2024] [Indexed: 03/08/2024] Open
Abstract
The COVID-19 pandemic has had a significant and lasting impact on the world. Four years on, despite the existence of effective vaccines, the continuous emergence of new SARS-CoV-2 variants remains a challenge for long-term immunity. Additionally, there remain few purpose-built antivirals to protect individuals at risk of severe disease in the event of future coronavirus outbreaks. A promising mechanism of action for novel coronavirus antivirals is the inhibition of viral entry. To facilitate entry, the coronavirus spike glycoprotein interacts with angiotensin converting enzyme 2 (ACE2) on respiratory epithelial cells. Blocking this interaction and consequently viral replication may be an effective strategy for treating infection, however further research is needed to better characterize candidate molecules with antiviral activity before progressing to animal studies and clinical trials. In general, antiviral drugs are developed from purely synthetic compounds or synthetic derivatives of natural products such as plant secondary metabolites. While the former is often favored due to the higher specificity afforded by rational drug design, natural products offer several unique advantages that make them worthy of further study including diverse bioactivity and the ability to work synergistically with other drugs. Accordingly, there has recently been a renewed interest in natural product-derived antivirals in the wake of the COVID-19 pandemic. This review provides a summary of recent research into coronavirus entry inhibitors, with a focus on natural compounds derived from plants, honey, and marine sponges.
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Affiliation(s)
- Dávid Szabó
- Curtin Health Innovation Research Institute, Curtin University, Bentley, WA, Australia
- Curtin Medical School, Curtin University, Bentley, WA, Australia
| | - Andrew Crowe
- Curtin Health Innovation Research Institute, Curtin University, Bentley, WA, Australia
- Curtin Medical School, Curtin University, Bentley, WA, Australia
| | - Cyril Mamotte
- Curtin Health Innovation Research Institute, Curtin University, Bentley, WA, Australia
- Curtin Medical School, Curtin University, Bentley, WA, Australia
| | - Padraig Strappe
- Curtin Health Innovation Research Institute, Curtin University, Bentley, WA, Australia
- Curtin Medical School, Curtin University, Bentley, WA, Australia
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Kandel S, Hartzell SL, Ingold AK, Turner GA, Kennedy JL, Ussery DW. Genomic surveillance of SARS-CoV-2 using long-range PCR primers. Front Microbiol 2024; 15:1272972. [PMID: 38440140 PMCID: PMC10910555 DOI: 10.3389/fmicb.2024.1272972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 01/03/2024] [Indexed: 03/06/2024] Open
Abstract
Introduction Whole Genome Sequencing (WGS) of the SARS-CoV-2 virus is crucial in the surveillance of the COVID-19 pandemic. Several primer schemes have been developed to sequence nearly all of the ~30,000 nucleotide SARS-CoV-2 genome, using a multiplex PCR approach to amplify cDNA copies of the viral genomic RNA. Midnight primers and ARTIC V4.1 primers are the most popular primer schemes that can amplify segments of SARS-CoV-2 (400 bp and 1200 bp, respectively) tiled across the viral RNA genome. Mutations within primer binding sites and primer-primer interactions can result in amplicon dropouts and coverage bias, yielding low-quality genomes with 'Ns' inserted in the missing amplicon regions, causing inaccurate lineage assignments, and making it challenging to monitor lineage-specific mutations in Variants of Concern (VoCs). Methods In this study we used a set of seven long-range PCR primer pairs to sequence clinical isolates of SARS-CoV-2 on Oxford Nanopore sequencer. These long-range primers generate seven amplicons approximately 4500 bp that covered whole genome of SARS-CoV-2. One of these regions includes the full-length S-gene by using a set of flanking primers. We also evaluated the performance of these long-range primers with Midnight primers by sequencing 94 clinical isolates in a Nanopore flow cell. Results and discussion Using a small set of long-range primers to sequence SARS-CoV-2 genomes reduces the possibility of amplicon dropout and coverage bias. The key finding of this study is that long range primers can be used in single-molecule sequencing of RNA viruses in surveillance of emerging variants. We also show that by designing primers flanking the S-gene, we can obtain reliable identification of SARS-CoV-2 variants.
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Affiliation(s)
- Sangam Kandel
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | | | - Ashton K. Ingold
- Arkansas Children's Research Institute, Little Rock, AR, United States
| | - Grace A. Turner
- Arkansas Children's Research Institute, Little Rock, AR, United States
| | - Joshua L. Kennedy
- Arkansas Children's Research Institute, Little Rock, AR, United States
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR, United States
- Department of Internal Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, United States
| | - David W. Ussery
- Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, United States
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31
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Turcinovic J, Kuhfeldt K, Sullivan M, Landaverde L, Platt JT, Alekseyev YO, Doucette-Stamm L, Hamer DH, Klapperich C, Landsberg HE, Connor JH. Transmission Dynamics and Rare Clustered Transmission Within an Urban University Population Before Widespread Vaccination. J Infect Dis 2024; 229:485-492. [PMID: 37856283 DOI: 10.1093/infdis/jiad397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 09/18/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Universities returned to in-person learning in 2021 while SARS-CoV-2 spread remained high. At the time, it was not clear whether in-person learning would be a source of disease spread. METHODS We combined surveillance testing, universal contact tracing, and viral genome sequencing to quantify introductions and identify likely on-campus spread. RESULTS Ninety-one percent of viral genotypes occurred once, indicating no follow-on transmission. Less than 5% of introductions resulted in >3 cases, with 2 notable exceptions of 40 and 47 cases. Both partially overlapped with outbreaks defined by contact tracing. In both cases, viral genomics eliminated over half the epidemiologically linked cases but added an equivalent or greater number of individuals to the transmission cluster. CONCLUSIONS Public health interventions prevented within-university transmission for most SARS-CoV-2 introductions, with only 2 major outbreaks being identified January to May 2021. The genetically linked cases overlap with outbreaks identified by contact tracing; however, they persisted in the university population for fewer days and rounds of transmission than estimated via contact tracing. This underscores the effectiveness of test-trace-isolate strategies in controlling undetected spread of emerging respiratory infectious diseases. These approaches limit follow-on transmission in both outside-in and internal transmission conditions.
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Affiliation(s)
- Jacquelyn Turcinovic
- Department of Virology, Immunology, and Microbiology, Chobanian & Avedisian School of Medicine
- National Emerging Infectious Diseases Laboratories
- Program in Bioinformatics
| | | | | | - Lena Landaverde
- Department of Biomedical Engineering
- Precision Diagnostics Center
- BU Clinical Testing Laboratory, Research Department
| | | | | | | | - Davidson H Hamer
- National Emerging Infectious Diseases Laboratories
- Precision Diagnostics Center
- Department of Global Health, School of Public Health
- Section of Infectious Disease, Department of Medicine, Chobanian & Avedisian School of Medicine
- Center for Emerging Infectious Disease Policy and Research, Boston University, Massachusetts
| | - Catherine Klapperich
- Department of Biomedical Engineering
- Precision Diagnostics Center
- BU Clinical Testing Laboratory, Research Department
| | | | - John H Connor
- Department of Virology, Immunology, and Microbiology, Chobanian & Avedisian School of Medicine
- National Emerging Infectious Diseases Laboratories
- Program in Bioinformatics
- Center for Emerging Infectious Disease Policy and Research, Boston University, Massachusetts
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Janssen R, Cuypers L, Laenen L, Keyaerts E, Beuselinck K, Janssenswillen S, Slechten B, Bode J, Wollants E, Van Laethem K, Rector A, Bloemen M, Sijmons A, de Schaetzen N, Capron A, Van Baelen K, Pascal T, Vermeiren C, Bureau F, Vandesompele J, De Smet P, Uten W, Malonne H, Kerkhofs P, De Cock J, Matheeussen V, Verhasselt B, Gillet L, Detry G, Bearzatto B, Degosserie J, Henin C, Pairoux G, Maes P, Van Ranst M, Lagrou K, Dequeker E, André E. Nationwide quality assurance of high-throughput diagnostic molecular testing during the SARS-CoV-2 pandemic: role of the Belgian National Reference Centre. Virol J 2024; 21:40. [PMID: 38341597 PMCID: PMC10858549 DOI: 10.1186/s12985-024-02308-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 01/29/2024] [Indexed: 02/12/2024] Open
Abstract
Since the onset of the coronavirus disease (COVID-19) pandemic in Belgium, UZ/KU Leuven has played a crucial role as the National Reference Centre (NRC) for respiratory pathogens, to be the first Belgian laboratory to develop and implement laboratory developed diagnostic assays for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and later to assess the quality of commercial kits. To meet the growing demand for decentralised testing, both clinical laboratories and government-supported high-throughput platforms were gradually deployed across Belgium. Consequently, the role of the NRC transitioned from a specialised testing laboratory to strengthening capacity and coordinating quality assurance. Here, we outline the measures taken by the NRC, the national public health institute Sciensano and the executing clinical laboratories to ensure effective quality management of molecular testing throughout the initial two years of the pandemic (March 2020 to March 2022).
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Affiliation(s)
- Reile Janssen
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium.
| | - Lize Cuypers
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
- Laboratory of Clinical Microbiology, Department of Microbiology, Immunology and Transplantation, KU Leuven, 3000, Leuven, Belgium
| | - Lies Laenen
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
- Laboratory of Clinical Microbiology, Department of Microbiology, Immunology and Transplantation, KU Leuven, 3000, Leuven, Belgium
| | - Els Keyaerts
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
- Laboratory of Clinical Microbiology, Department of Microbiology, Immunology and Transplantation, KU Leuven, 3000, Leuven, Belgium
| | - Kurt Beuselinck
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
| | - Sunita Janssenswillen
- Federal Testing Platform COVID-19, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
| | - Bram Slechten
- Federal Testing Platform COVID-19, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
| | - Jannes Bode
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
| | - Elke Wollants
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000, Leuven, Belgium
| | - Kristel Van Laethem
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000, Leuven, Belgium
| | - Annabel Rector
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000, Leuven, Belgium
| | - Mandy Bloemen
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000, Leuven, Belgium
| | - Anke Sijmons
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
| | - Nathalie de Schaetzen
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
| | - Arnaud Capron
- Quality of Laboratories Unit, Scientific Directorate of Biological Health Risks, Sciensano, 1000, Brussels, Belgium
| | - Kurt Van Baelen
- Janssen Pharmaceutica N.V, Johnson & Johnson, 2340, Beerse, Belgium
| | | | | | - Fabrice Bureau
- Laboratory of Cellular and Molecular Immunology, GIGA Institute, University of Liège, 4000, Liège, Belgium
| | - Jo Vandesompele
- Biogazelle, a CellCarta Company, Technologiepark Zwijnaarde, 9052, Zwijnaarde, Belgium
| | | | | | - Hugues Malonne
- Federal Agency for Medicines and Health Products (FAGG-AFMPS), 1210, Brussels, Belgium
- Department of Pharmacology, Pharmacotherapy and Pharmaceutical Care, Faculty of Pharmacy, Université Libre de Bruxelles, 1070, Brussels, Belgium
- Department of Biomedical Sciences, Namur Research Institute for Life Sciences, University of Namur, 5000, Namur, Belgium
| | - Pierre Kerkhofs
- Federal Public Service Public Health, Safety of the Food Chain and the Environment, 1210, Brussels, Belgium
| | - Jo De Cock
- National Institute for Health and Disability Insurance (RIZIV/INAMI), 1150, Brussels, Belgium
| | - Veerle Matheeussen
- Federal Testing Platform COVID-19, University Hospitals Antwerp, 2650, Edegem, Belgium
| | - Bruno Verhasselt
- Federal Testing Platform COVID-19, Department of Laboratory Medicine, Ghent University and Ghent University Hospital, 9000, Ghent, Belgium
| | - Laurent Gillet
- Federal Testing Platform COVID-19, University of Liège, 4000, Liège, Belgium
| | - Gautier Detry
- Federal Testing Platform COVID-19, Laboratory of Clinical Biology, Pole Hospitalier Jolimont, 7100, La Louvière, Belgium
| | - Bertrand Bearzatto
- Federal Testing Platform COVID-19, Centre Des Technologies Moléculaires Appliquées (CTMA), Institute of Experimental and Clinical Research (IREC), Cliniques Universitaires Saint-Luc and Université Catholique de Louvain (UCLouvain), 1200, Brussels, Belgium
| | - Jonathan Degosserie
- Federal Testing Platform COVID-19, Department of Laboratory Medicine, CHU UCL Namur, 5530, Yvoir, Belgium
| | - Coralie Henin
- Federal Testing Platform COVID-19, Université Libre de Bruxelles, 1070, Brussels, Belgium
| | - Gregor Pairoux
- Quality of Laboratories Unit, Scientific Directorate of Biological Health Risks, Sciensano, 1000, Brussels, Belgium
| | - Piet Maes
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000, Leuven, Belgium
| | - Marc Van Ranst
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
- Laboratory of Clinical and Epidemiological Virology, Department of Microbiology, Immunology and Transplantation, Rega Institute for Medical Research, KU Leuven, 3000, Leuven, Belgium
| | - Katrien Lagrou
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
- Laboratory of Clinical Microbiology, Department of Microbiology, Immunology and Transplantation, KU Leuven, 3000, Leuven, Belgium
| | - Elisabeth Dequeker
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
- Biomedical Quality Assurance Research Unit, Department of Public Health and Primary Care, University of Leuven, 3000, Leuven, Belgium
| | - Emmanuel André
- National Reference Centre for Respiratory Pathogens, Department of Laboratory Medicine, University Hospitals Leuven, 3000, Leuven, Belgium
- Laboratory of Clinical Microbiology, Department of Microbiology, Immunology and Transplantation, KU Leuven, 3000, Leuven, Belgium
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Rancati S, Nicora G, Prosperi M, Bellazzi R, Salemi M, Marini S. Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders. bioRxiv 2024:2023.10.24.563721. [PMID: 37961168 PMCID: PMC10634784 DOI: 10.1101/2023.10.24.563721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The coronavirus disease of 2019 (COVID-19) pandemic is characterized by sequential emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and lineages outcompeting previously circulating ones because of, among other factors, increased transmissibility and immune escape1-3. We devised an unsupervised deep learning AutoEncoder for viral genomes anomaly detection to predict future dominant lineages (FDLs), i.e., lineages or sublineages comprising ≥10% of viral sequences added to the GISAID database on a given week4. The algorithm was trained and validated by assembling global and country-specific data sets from 16,187,950 Spike protein sequences sampled between December 24th, 2019, and November 8th, 2023. The AutoEncoder flags low frequency FDLs (0.01% - 3%), with median lead times of 4-16 weeks. Over time, positive predictive values oscillate, decreasing linearly with the number of unique sequences per data set, showing average performance up to 30 times better than baseline approaches. The B.1.617.2 vaccine reference strain was flagged as FDL when its frequency was only 0.01%, more than one year earlier of being considered for an updated COVID-19 vaccine. Our AutoEncoder, applicable in principle to any pathogen, also pinpoints specific mutations potentially linked to increased fitness, and may provide significant insights for the optimization of public health pre-emptive intervention strategies.
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Affiliation(s)
- Simone Rancati
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Giovanna Nicora
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Mattia Prosperi
- Department of Epidemiology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
| | - Riccardo Bellazzi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Marco Salemi
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
- Department of Pathology, Immunology and Laboratory Medicine, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Simone Marini
- Department of Epidemiology, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA
- Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA
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Banga J, Brock-Fisher T, Petros BA, Dai EY, Leonelli AT, Dobbins ST, Messer KS, Nathanson AB, Capone A, Littlehale N, Appiah-Danquah V, Dim S, Moreno GK, Crowther M, Lee KA, DeRuff KC, MacInnis BL, Springer M, Sabeti PC, Stephenson KE. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Household Transmission during the Omicron Era in Massachusetts: A Prospective, Case-Ascertained Study using Genomic Epidemiology. medRxiv 2024:2024.02.05.24302348. [PMID: 38370621 PMCID: PMC10871383 DOI: 10.1101/2024.02.05.24302348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Background Households are a major setting for SARS-CoV-2 infections, but there remains a lack of knowledge regarding the dynamics of viral transmission, particularly in the setting of widespread pre-existing SARS-CoV-2 immunity and evolving variants. Methods We conducted a prospective, case-ascertained household transmission study in the greater Boston area in March-July 2022. Anterior nasal swabs, along with clinical and demographic data, were collected for 14 days. Nasal swabs were tested for SARS-CoV-2 by PCR. Whole genome sequencing was performed on high-titer samples. Results We enrolled 33 households in a primary analysis set, with a median age of participants of 25 years old (range 2-66); 98% of whom had received at least 2 doses of a COVID-19 vaccine. 58% of households had a secondary case during follow up and the secondary attack rate (SAR) for contacts infected was 39%. We further examined a strict analysis set of 21 households that had only 1 PCR+ case at baseline, finding an SAR of 22.5%. Genomic epidemiology further determined that there were multiple sources of infection for household contacts, including the index case and outside introductions. When limiting estimates to only highly probable transmissions given epidemiologic and genomic data, the SAR was 18.4%. Conclusions Household contacts of a person newly diagnosed with COVID-19 are at high risk for SARS-CoV-2 infection in the following 2 weeks. This is, however, not only due to infection from the household index case, but also because the presence of an infected household member implies increased SARS-CoV-2 community transmission. Further studies to understand and mitigate household transmission are needed.
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Affiliation(s)
- Jaspreet Banga
- Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Taylor Brock-Fisher
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Faculty of Arts and Sciences, Harvard University, Cambridge, MA, USA
| | - Brittany A Petros
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard/MIT MD-PhD Program, Boston, MA, USA
| | - Eric Y Dai
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Ariana T Leonelli
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | | | - Audrey B Nathanson
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Amelia Capone
- Beth Israel Lahey Health Primary Care, Chelsea, MA, USA
| | | | - Viola Appiah-Danquah
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Siang Dim
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Gage K Moreno
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Maura Crowther
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Kannon A Lee
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | | | - Michael Springer
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Pardis C Sabeti
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Faculty of Arts and Sciences, Harvard University, Cambridge, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Kathryn E Stephenson
- Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Ragon Institute of Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
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35
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Camp JV, Puchhammer-Stöckl E, Aberle SW, Buchta C. Virus sequencing performance during the SARS-CoV-2 pandemic: a retrospective analysis of data from multiple rounds of external quality assessment in Austria. Front Mol Biosci 2024; 11:1327699. [PMID: 38375507 PMCID: PMC10875003 DOI: 10.3389/fmolb.2024.1327699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 01/03/2024] [Indexed: 02/21/2024] Open
Abstract
Introduction: A notable feature of the 2019 coronavirus disease (COVID-19) pandemic was the widespread use of whole genome sequencing (WGS) to monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. Countries around the world relied on sequencing and other forms of variant detection to perform contact tracing and monitor changes in the virus genome, in the hopes that epidemic waves caused by variants would be detected and managed earlier. As sequencing was encouraged and rewarded by the government in Austria, but represented a new technicque for many laboratories, we designed an external quality assessment (EQA) scheme to monitor the accuracy of WGS and assist laboratories in validating their methods. Methods: We implemented SARS-CoV-2 WGS EQAs in Austria and report the results from 7 participants over 5 rounds from February 2021 until June 2023. The participants received sample material, sequenced genomes with routine methods, and provided the sequences as well as information about mutations and lineages. Participants were evaluated on the completeness and accuracy of the submitted sequence and the ability to analyze and interpret sequencing data. Results: The results indicate that performance was excellent with few exceptions, and these exceptions showed improvement over time. We extend our findings to infer that most publicly available sequences are accurate within ≤1 nucleotide, somewhat randomly distributed through the genome. Conclusion: WGS continues to be used for SARS-CoV-2 surveillance, and will likely be instrumental in future outbreak scenarios. We identified hurdles in building next-generation sequencing capacity in diagnostic laboratories. EQAs will help individual laboratories maintain high quality next-generation sequencing output, and strengthen variant monitoring and molecular epidemiology efforts.
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Affiliation(s)
- Jeremy V Camp
- Center for Virology, Medical University of Vienna, Vienna, Austria
| | | | - Stephan W Aberle
- Center for Virology, Medical University of Vienna, Vienna, Austria
| | - Christoph Buchta
- Austrian Association for Quality Assurance and Standardization of Medical and Diagnostic Tests (ÖQUASTA), Vienna, Austria
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Hilti D, Wehrli F, Berchtold S, Bigler S, Bodmer T, Seth-Smith HMB, Roloff T, Kohler P, Kahlert CR, Kaiser L, Egli A, Risch L, Risch M, Wohlwend N. S-Gene Target Failure as an Effective Tool for Tracking the Emergence of Dominant SARS-CoV-2 Variants in Switzerland and Liechtenstein, Including Alpha, Delta, and Omicron BA.1, BA.2, and BA.4/BA.5. Microorganisms 2024; 12:321. [PMID: 38399725 PMCID: PMC10892681 DOI: 10.3390/microorganisms12020321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Revised: 01/24/2024] [Accepted: 02/01/2024] [Indexed: 02/25/2024] Open
Abstract
During the SARS-CoV-2 pandemic, the Dr. Risch medical group employed the multiplex TaqPathTM COVID-19 CE-IVD RT-PCR Kit for large-scale routine diagnostic testing in Switzerland and the principality of Liechtenstein. The TaqPath Kit is a widely used multiplex assay targeting three genes (i.e., ORF1AB, N, S). With emergence of the B.1.1.7 (Alpha) variant, a diagnostic flaw became apparent as the amplification of the S-gene target was absent in these samples due to a deletion (ΔH69/V70) in the Alpha variant genome. This S-gene target failure (SGTF) was the earliest indication of a new variant emerging and was also observed in subsequent variants such as Omicron BA.1 and BA4/BA.5. The Delta variant and Omicron BA.2 did not present with SGTF. From September 2020 to November 2022, we investigated the applicability of the SGTF as a surrogate marker for emerging variants such as B.1.1.7, B.1.617.2 (Delta), and Omicron BA.1, BA.2, and BA.4/BA.5 in samples with cycle threshold (Ct) values < 30. Next to true SGTF-positive and SGTF-negative samples, there were also samples presenting with delayed-type S-gene amplification (higher Ct value for S-gene than ORF1ab gene). Among these, a difference of 3.8 Ct values between the S- and ORF1ab genes was found to best distinguish between "true" SGTF and the cycle threshold variability of the assay. Samples above the cutoff were subsequently termed partial SGTF (pSGTF). Variant confirmation was performed by whole-genome sequencing (Oxford Nanopore Technology, Oxford, UK) or mutation-specific PCR (TIB MOLBIOL). In total, 17,724 (7.4%) samples among 240,896 positives were variant-confirmed, resulting in an overall sensitivity and specificity of 93.2% [92.7%, 93.7%] and 99.3% [99.2%, 99.5%], respectively. Sensitivity was increased to 98.2% [97.9% to 98.4%] and specificity lowered to 98.9% [98.6% to 99.1%] when samples with pSGTF were included. Furthermore, weekly logistic growth rates (α) and sigmoid's midpoint (t0) were calculated based on SGTF data and did not significantly differ from calculations based on comprehensive data from GISAID. The SGTF therefore allowed for a valid real-time estimate for the introduction of all dominant variants in Switzerland and Liechtenstein.
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Affiliation(s)
- Dominique Hilti
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
- Institute of Laboratory Medicine, Private University in the Principality of Liechtenstein (UFL), 9495 Triesen, Liechtenstein
| | - Faina Wehrli
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
| | | | - Susanna Bigler
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
| | - Thomas Bodmer
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
| | | | - Tim Roloff
- Institute of Medical Microbiology, University of Zurich, 8006 Zurich, Switzerland
| | - Philipp Kohler
- Zentrallabor, Kantonsspital Graubünden, 7000 Chur, Switzerland
| | - Christian R. Kahlert
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, 9007 St. Gallen, Switzerland
| | - Laurent Kaiser
- Division of Infectious Diseases, Geneva University Hospitals, 1205 Geneva, Switzerland
- Geneva Centre for Emerging Viral Diseases, Geneva University Hospitals, 1205 Geneva, Switzerland
| | - Adrian Egli
- Institute of Medical Microbiology, University of Zurich, 8006 Zurich, Switzerland
| | - Lorenz Risch
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
- Institute of Laboratory Medicine, Private University in the Principality of Liechtenstein (UFL), 9495 Triesen, Liechtenstein
| | - Martin Risch
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, 9007 St. Gallen, Switzerland
| | - Nadia Wohlwend
- Laboratory Dr. Risch, 9470 Buchs, Switzerland (L.R.); (N.W.)
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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El Soufi G, Di Jorio L, Gerber Z, Cluzel N, Van Assche J, Delafoy D, Olaso R, Daviaud C, Loustau T, Schwartz C, Trebouet D, Hernalsteens O, Marechal V, Raffestin S, Rousset D, Van Lint C, Deleuze JF, Boni M, Rohr O, Villain-Gambier M, Wallet C. Highly efficient and sensitive membrane-based concentration process allows quantification, surveillance, and sequencing of viruses in large volumes of wastewater. Water Res 2024; 249:120959. [PMID: 38070350 DOI: 10.1016/j.watres.2023.120959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 11/29/2023] [Accepted: 11/30/2023] [Indexed: 01/03/2024]
Abstract
Wastewater-based epidemiology is experiencing exponential development. Despite undeniable advantages compared to patient-centered approaches (cost, anonymity, survey of large populations without bias, detection of asymptomatic infected peoples…), major technical limitations persist. Among them is the low sensitivity of the current methods used for quantifying and sequencing viral genomes from wastewater. In situations of low viral circulation, during initial stages of viral emergences, or in areas experiencing heavy rains, the extremely low concentrations of viruses in wastewater may fall below the limit of detection of the current methods. The availability during crisis and the cost of the commercial kits, as well as the requirement of expensive materials such as high-speed centrifuge, can also present major blocks to the development of wastewater-based epidemiological survey, specifically in low-income countries. Thereby, highly sensitive, low cost and standardized methods are still needed, to increase the predictability of the viral emergences, to survey low-circulating viruses and to make the results from different labs comparable. Here, we outline and characterize new protocols for concentrating and quantifying SARS-CoV-2 from large volumes (500 mL-1 L) of untreated wastewater. In addition, we report that the methods are applicable for monitoring and sequencing. Our nucleic acid extraction technique (the routine C: 5 mL method) does not require sophisticated equipment such as automatons and is not reliant on commercial kits, making it readily available to a broader range of laboratories for routine epidemiological survey. Furthermore, we demonstrate the efficiency, the repeatability, and the high sensitivity of a new membrane-based concentration method (MBC: 500 mL method) for enveloped (SARS-CoV-2) and non-enveloped (F-specific RNA phages of genogroup II / FRNAPH GGII) viruses. We show that the MBC method allows the quantification and the monitoring of viruses in wastewater with a significantly improved sensitivity compared to the routine C method. In contexts of low viral circulation, we report quantifications of SARS-CoV-2 in wastewater at concentrations as low as 40 genome copies per liter. In highly diluted samples collected in wastewater treatment plants of French Guiana, we confirmed the accuracy of the MBC method compared to the estimations done with the routine C method. Finally, we demonstrate that both the routine C method processing 5 mL and the MBC method processing 500 mL of untreated wastewater are both compatible with SARS-CoV-2 sequencing. We show that the quality of the sequence is correlated with the concentration of the extracted viral genome. Of note, the quality of the sequences obtained with some MBC processed wastewater was improved by dilutions or enzyme substitutions suggesting the presence of specific enzyme inhibitors in some wastewater. To the best of our knowledge, our MBC method is one of the first efficient, sensitive, and repeatable method characterized for SARS-CoV-2 quantification and sequencing from large volumes of wastewater.
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Affiliation(s)
- G El Soufi
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France; CNRS, IPHC, UMR 7178, Université de Strasbourg, Strasbourg F-67000, France
| | - L Di Jorio
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - Z Gerber
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - N Cluzel
- Maison des Modélisations Ingénieries et Technologies (SUMMIT), Sorbonne Université, Paris 75005, France
| | - J Van Assche
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - D Delafoy
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - R Olaso
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - C Daviaud
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - T Loustau
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - C Schwartz
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France
| | - D Trebouet
- CNRS, IPHC, UMR 7178, Université de Strasbourg, Strasbourg F-67000, France
| | - O Hernalsteens
- Department of Molecular Biology (DBM), Service of Molecular Virology, Université Libre de Bruxelles (ULB), Gosselies 6041, Belgium
| | - V Marechal
- INSERM, Centre de Recherche Saint-Antoine, Sorbonne Université, Paris 75012, France; OBEPINE Consortium, Paris, France
| | - S Raffestin
- Institut Pasteur de la Guyane, French Guiana, Cayenne 97300, France; OBEPINE Consortium, Paris, France
| | - D Rousset
- Institut Pasteur de la Guyane, French Guiana, Cayenne 97300, France; OBEPINE Consortium, Paris, France
| | - C Van Lint
- Department of Molecular Biology (DBM), Service of Molecular Virology, Université Libre de Bruxelles (ULB), Gosselies 6041, Belgium
| | - J F Deleuze
- CEA, Centre National de Recherche en Génomique Humaine, Université Paris-Saclay, Evry 91057, France
| | - M Boni
- French Armed Forces Biomedical Research Institute, 91220 Brétigny-sur-Orge, France; OBEPINE Consortium, Paris, France
| | - O Rohr
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France; OBEPINE Consortium, Paris, France.
| | - M Villain-Gambier
- CNRS, IPHC, UMR 7178, Université de Strasbourg, Strasbourg F-67000, France
| | - C Wallet
- DHPI UR 7292, IUT Louis Pasteur, Université de Strasbourg, Schiltigheim, France; OBEPINE Consortium, Paris, France
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Rahman N, O'Cathail C, Zyoud A, Sokolov A, Oude Munnink B, Grüning B, Cummins C, Amid C, Nieuwenhuijse DF, Visontai D, Yuan DY, Gupta D, Prasad DK, Gulyás GM, Rinck G, McKinnon J, Rajan J, Knaggs J, Skiby JE, Stéger J, Szarvas J, Gueye K, Papp K, Hoek M, Kumar M, Ventouratou MA, Bouquieaux MC, Koliba M, Mansurova M, Haseeb M, Worp N, Harrison PW, Leinonen R, Thorne R, Selvakumar S, Hunt S, Venkataraman S, Jayathilaka S, Cezard T, Maier W, Waheed Z, Iqbal Z, Aarestrup FM, Csabai I, Koopmans M, Burdett T, Cochrane G. Mobilisation and analyses of publicly available SARS-CoV-2 data for pandemic responses. Microb Genom 2024; 10:001188. [PMID: 38358325 PMCID: PMC10926692 DOI: 10.1099/mgen.0.001188] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 01/14/2024] [Indexed: 02/16/2024] Open
Abstract
The COVID-19 pandemic has seen large-scale pathogen genomic sequencing efforts, becoming part of the toolbox for surveillance and epidemic research. This resulted in an unprecedented level of data sharing to open repositories, which has actively supported the identification of SARS-CoV-2 structure, molecular interactions, mutations and variants, and facilitated vaccine development and drug reuse studies and design. The European COVID-19 Data Platform was launched to support this data sharing, and has resulted in the deposition of several million SARS-CoV-2 raw reads. In this paper we describe (1) open data sharing, (2) tools for submission, analysis, visualisation and data claiming (e.g. ORCiD), (3) the systematic analysis of these datasets, at scale via the SARS-CoV-2 Data Hubs as well as (4) lessons learnt. This paper describes a component of the Platform, the SARS-CoV-2 Data Hubs, which enable the extension and set up of infrastructure that we intend to use more widely in the future for pathogen surveillance and pandemic preparedness.
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Affiliation(s)
- Nadim Rahman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Colman O'Cathail
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Ahmad Zyoud
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Alexey Sokolov
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Bas Oude Munnink
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | - Björn Grüning
- University of Freiburg, Friedrichstr. 39, 79098 Freiburg, Germany
| | - Carla Cummins
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Clara Amid
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | | | - Dávid Visontai
- Eötvös Loránd University, H-1053 Budapest, Egyetem tér 1-3, Hungary
| | - David Yu Yuan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Dipayan Gupta
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Divyae K. Prasad
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | - Gábor Máté Gulyás
- Technical University of Denmark, Anker Engelunds Vej 101, 2800 Kongens Lyngby, Denmark
| | - Gabriele Rinck
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Jasmine McKinnon
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Jeena Rajan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Jeff Knaggs
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Jeffrey Edward Skiby
- Technical University of Denmark, Anker Engelunds Vej 101, 2800 Kongens Lyngby, Denmark
| | - József Stéger
- Eötvös Loránd University, H-1053 Budapest, Egyetem tér 1-3, Hungary
| | - Judit Szarvas
- Technical University of Denmark, Anker Engelunds Vej 101, 2800 Kongens Lyngby, Denmark
| | - Khadim Gueye
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Krisztián Papp
- Eötvös Loránd University, H-1053 Budapest, Egyetem tér 1-3, Hungary
| | - Maarten Hoek
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | - Manish Kumar
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Marianna A. Ventouratou
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | | | - Martin Koliba
- Technical University of Denmark, Anker Engelunds Vej 101, 2800 Kongens Lyngby, Denmark
| | - Milena Mansurova
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Muhammad Haseeb
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Nathalie Worp
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | - Peter W. Harrison
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Rasko Leinonen
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Ross Thorne
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Sandeep Selvakumar
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Sarah Hunt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Sundar Venkataraman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Suran Jayathilaka
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Timothée Cezard
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Wolfgang Maier
- University of Freiburg, Friedrichstr. 39, 79098 Freiburg, Germany
| | - Zahra Waheed
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Zamin Iqbal
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | | | - Istvan Csabai
- Eötvös Loránd University, H-1053 Budapest, Egyetem tér 1-3, Hungary
| | - Marion Koopmans
- Erasmus Medical Center, Wytemaweg 80, 3015 CN Rotterdam, Netherlands
| | - Tony Burdett
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
| | - Guy Cochrane
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK
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McBroome J, de Bernardi Schneider A, Roemer C, Wolfinger MT, Hinrichs AS, O'Toole AN, Ruis C, Turakhia Y, Rambaut A, Corbett-Detig R. A framework for automated scalable designation of viral pathogen lineages from genomic data. Nat Microbiol 2024; 9:550-560. [PMID: 38316930 PMCID: PMC10847047 DOI: 10.1038/s41564-023-01587-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 12/13/2023] [Indexed: 02/07/2024]
Abstract
Pathogen lineage nomenclature systems are a key component of effective communication and collaboration for researchers and public health workers. Since February 2021, the Pango dynamic lineage nomenclature for SARS-CoV-2 has been sustained by crowdsourced lineage proposals as new isolates were sequenced. This approach is vulnerable to time-critical delays as well as regional and personal bias. Here we developed a simple heuristic approach for dividing phylogenetic trees into lineages, including the prioritization of key mutations or genes. Our implementation is efficient on extremely large phylogenetic trees consisting of millions of sequences and produces similar results to existing manually curated lineage designations when applied to SARS-CoV-2 and other viruses including chikungunya virus, Venezuelan equine encephalitis virus complex and Zika virus. This method offers a simple, automated and consistent approach to pathogen nomenclature that can assist researchers in developing and maintaining phylogeny-based classifications in the face of ever-increasing genomic datasets.
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Affiliation(s)
- Jakob McBroome
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA.
| | - Adriano de Bernardi Schneider
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Cornelius Roemer
- Biozentrum, University of Basel, Basel, Switzerland
- Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Michael T Wolfinger
- Department of Theoretical Chemistry, University of Vienna, Vienna, Austria
- Research Group Bioinformatics and Computational Biology, Faculty of Computer Science, University of Vienna, Vienna, Austria
- RNA Forecast e.U., Vienna, Austria
- Bioinformatics Group, Department of Computer Science, University of Freiburg, Freiburg, Germany
| | - Angie S Hinrichs
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA
| | - Aine Niamh O'Toole
- Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, UK
| | - Christopher Ruis
- Molecular Immunity Unit, MRC Laboratory of Molecular Biology, Department of Medicine, University of Cambridge, Cambridge, UK
- Department of Veterinary Medicine, University of Cambridge, Cambridge, UK
- Cambridge Centre for AI in Medicine, University of Cambridge, Cambridge, UK
| | - Yatish Turakhia
- Department of Electrical and Computer Engineering, University of California San Diego, San Diego, CA, USA
| | - Andrew Rambaut
- Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, UK
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, USA.
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, USA.
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Al Qurashi YMA, Abdulhakim JA, Alkhalil SS, Alansari M, Almutiri R, Alabbasi R, Fawzy MS. Molecular Epidemiology of Omicron CH.1.1 Lineage: Genomic and Phenotypic Data Perspective. Cureus 2024; 16:e53496. [PMID: 38440013 PMCID: PMC10910519 DOI: 10.7759/cureus.53496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/31/2024] [Indexed: 03/06/2024] Open
Abstract
BACKGROUND The Omicron variant (B.1.1.529 lineage) of SARS-CoV-2 represents a substantial global health challenge due to its high transmissibility and potential resistance to immunity from vaccines or previous infections. Among the rapidly evolving Omicron lineages, the BA.2.75 and the emerging CH.1.1 have garnered attention. While BA.2.75 is marked by mutations that may enhance immune evasion, CH.1.1 is distinguished by the S: L452R mutation, linked to increased pathogenicity and transmission. Initially identified in India by the end of 2021, these variants have exhibited global dissemination, signaling an urgent need to track and analyze their progression. METHODS In this study, the genomic and geographical distribution data of CH.1.1 were collected from the Global Initiative on Sharing Avian Influenza Data (GISAID), PANGOLIN, CoV-Spectrum, and NextStrain databases. Due to the unavailability of epidemiological and genomic data of the CH.1.1 lineage, PubMed and ScienceDirect were used as sources of the phenotypic data of the lineage variations. Amino acid variations utilized in the data mining included S: R346T, S: K444T, S: L452R, and S: F486S. RESULTS The current epidemiological data indicate that CH.1.1 is more likely to become one of the dominant spreading lineages in the United Kingdom, New Zealand, Australia, and the United States based on a 32% growth advantage, present CH.1.1 lineage cases number, and the amino acid variation's impact. CONCLUSION A significant increase in the newly detected lineage CH.1.1 is highly anticipated. The rise in the detected sequences number from 13,231 on January 21, 2023, to 23,181 on February 6, 2023, supports the prediction and growth advantage of the lineage detected cases. Increases in viral transmissibility caused by higher affinity to ACE2 receptors and immune evasion are deduced from amino acid variations analyzed in the study.
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Affiliation(s)
| | - Jawaher A Abdulhakim
- Department of Medical Laboratory, College of Applied Medical Sciences, Taibah University, Yanbu, SAU
| | - Samia S Alkhalil
- Department of Clinical Laboratory Sciences, College of Applied Medical Sciences, Shaqra University, Alquwayiyah, SAU
| | - Maymuna Alansari
- Department of Medical Laboratory, College of Applied Medical Sciences, Taibah University, Yanbu, SAU
| | - Renad Almutiri
- Department of Medical Laboratory, College of Applied Medical Sciences, Taibah University, Yanbu, SAU
| | - Rageed Alabbasi
- Department of Medical Laboratory, College of Applied Medical Sciences, Taibah University, Yanbu, SAU
| | - Manal S Fawzy
- Department of Biochemistry, Unit of Medical Research and Postgraduate Studies, Faculty of Medicine, Northern Border University, Arar, SAU
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Ciubotariu II, Wilkes RP, Kattoor JJ, Christian EN, Carpi G, Kitchen A. Investigating the rise of Omicron variant through genomic surveillance of SARS-CoV-2 infections in a highly vaccinated university population. Microb Genom 2024; 10:001194. [PMID: 38334271 PMCID: PMC10926704 DOI: 10.1099/mgen.0.001194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 01/23/2024] [Indexed: 02/10/2024] Open
Abstract
Novel variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continue to emerge as the coronavirus disease 2019 (COVID-19) pandemic extends into its fourth year. Understanding SARS-CoV-2 circulation in university populations is vital for effective interventions in higher education settings and will inform public health policy during pandemics. In this study, we generated 793 whole-genome sequences collected over an entire academic year in a university population in Indiana, USA. We clearly captured the rapidity with which Delta variant was wholly replaced by Omicron variant across the West Lafayette campus over the length of two academic semesters in a community with high vaccination rates. This mirrored the emergence of Omicron throughout the state of Indiana and the USA. Further, phylogenetic analyses demonstrated that there was a more diverse set of potential geographic origins for Omicron viruses introduction into campus when compared to Delta. Lastly, statistics indicated that there was a more significant role for international and out-of-state migration in the establishment of Omicron variants at Purdue. This surveillance workflow, coupled with viral genomic sequencing and phylogeographic analyses, provided critical insights into SARS-CoV-2 transmission dynamics and variant arrival.
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Affiliation(s)
- Ilinca I. Ciubotariu
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana 47907, USA
| | - Rebecca P. Wilkes
- Department of Comparative Pathobiology, Animal Disease Diagnostic Laboratory, Purdue University College of Veterinary Medicine, West Lafayette, Indiana 47907, USA
| | - Jobin J. Kattoor
- Department of Comparative Pathobiology, Animal Disease Diagnostic Laboratory, Purdue University College of Veterinary Medicine, West Lafayette, Indiana 47907, USA
| | - Erin N. Christian
- Department of Comparative Pathobiology, Animal Disease Diagnostic Laboratory, Purdue University College of Veterinary Medicine, West Lafayette, Indiana 47907, USA
| | - Giovanna Carpi
- Department of Biological Sciences, Purdue University, West Lafayette, Indiana 47907, USA
- Purdue Institute of Inflammation, Immunology and Infectious Disease, West Lafayette, Indiana 47907, USA
| | - Andrew Kitchen
- Department of Anthropology, University of Iowa, Iowa City, Iowa, USA
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Adzdzakiy MM, Sutarno S, Asyifa IZ, Sativa AR, Fiqri AR, Fibriani A, Ristandi RB, Ningrum RA, Iryanto SB, Prasetyoputri A, Dharmayanthi AB, Saputra S. SARS-CoV-2 genetic variation and bacterial communities of naso-oropharyngeal samples in middle-aged and elderly COVID-19 patients in West Java, Indonesia. J Taibah Univ Med Sci 2024; 19:70-81. [PMID: 37868100 PMCID: PMC10589881 DOI: 10.1016/j.jtumed.2023.09.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 07/21/2023] [Accepted: 09/01/2023] [Indexed: 10/24/2023] Open
Abstract
Objective The number of COVID-19 cases in Indonesia reflects the disease severity and rapid dissemination. In response to the mounting threat, SARS-CoV-2 genomic surveillance and the investigation of naso-oropharyngeal bacterial communities in West Java were conducted, as dysbiosis of the upper respiratory tract microbiota might adversely affect the clinical condition of patients. Methods We utilized the Oxford Nanopore sequencing platform to analyze genetic variation of 43 samples of SARS-CoV-2 and 11 selected samples for 16S rRNA gene sequencing, using samples collected from May to August 2021. Results The prevalence of AY.23 (>82%) predominated among five virus lineages in the populations (AY.23, AY.24, AY.26, AY.42, B.1.1.7). The region in the SARS-CoV-2 genome found to have the highest number of mutations was the spike (S) protein (>20%). There was no association between SARS-CoV-2 lineages, mutation frequency, patient profile, and COVID-19 rapid spread-categorized cases. There was no association of bacterial relative abundance, alpha-beta diversity, and linear discriminant analysis effect size analysis with patient profile and rapid spread cases. MetagenomeSeq analysis showed eight differential abundance species in individual patient profiles, including Pseudomonas aeruginosa and Haemophilus parainfluenzae. Conclusions The data demonstrated relevant AY.23 dominance (the Delta variant) in West Java during that period supporting the importance of surveillance program in monitoring disease progression. The inconsistent results of the bacterial communities suggest that a complex multifactor process may contribute to the progression of bacterial-induced disease in each patient.
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Affiliation(s)
- Muhammad M. Adzdzakiy
- Graduate School of Bioscience, Faculty of Mathematics and Natural Sciences, Universitas Sebelas Maret, Jl. Ir. Sutami 36A Surakarta, Central Java, Indonesia
| | - Sutarno Sutarno
- Graduate School of Bioscience, Faculty of Mathematics and Natural Sciences, Universitas Sebelas Maret, Jl. Ir. Sutami 36A Surakarta, Central Java, Indonesia
| | - Isnaini Z. Asyifa
- Master Program in Biomedical Science, Faculty of Medicine, Universitas Indonesia, Jl. Salemba Raya No.6, Jakarta, Indonesia
| | - Alvira R. Sativa
- School of Life Science and Technology, Institut Teknologi Bandung, Jl. Ganesa 10, Bandung, West Java, Indonesia
| | - Ahmad R.A. Fiqri
- Master Program in Biomedical Science, Faculty of Medicine, Universitas Indonesia, Jl. Salemba Raya No.6, Jakarta, Indonesia
| | - Azzania Fibriani
- School of Life Science and Technology, Institut Teknologi Bandung, Jl. Ganesa 10, Bandung, West Java, Indonesia
| | - Ryan B. Ristandi
- West Java Health Laboratory, Jl. Sederhana No. 3-5, Pasteur, Sukajadi, Bandung, West Java, Indonesia
| | - Ratih A. Ningrum
- Research Center for Genetic Engineering, National Research and Innovation Agency (BRIN), Jl. Raya Jakarta Bogor Km 46, Bogor, West Java, Indonesia
| | - Syam B. Iryanto
- Research Center for Computation, National Research and Innovation Agency (BRIN), Jl. Raya Jakarta Bogor Km 46, Bogor, West Java, Indonesia
| | - Anggia Prasetyoputri
- Research Center for Applied Microbiology, National Research and Innovation Agency (BRIN), Jl. Raya Jakarta Bogor Km 46, Bogor, West Java, Indonesia
| | - Anik B. Dharmayanthi
- Research Center for Biosystematics and Evolution, National Research and Innovation Agency (BRIN), Jl. Raya Jakarta Bogor Km 46, Bogor, West Java, Indonesia
| | - Sugiyono Saputra
- Research Center for Applied Microbiology, National Research and Innovation Agency (BRIN), Jl. Raya Jakarta Bogor Km 46, Bogor, West Java, Indonesia
- Research Center for Applied Zoology, National Research and Innovation Agency (BRIN), Jl. Raya Jakarta Bogor Km 46, Bogor, West Java, Indonesia
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Allen A, Magee R, Devaney R, Ardis T, McNally C, McCormick C, Presho E, Doyle M, Ranasinghe P, Johnston P, Kirke R, Harwood R, Farrell D, Kenny K, Smith J, Gordon S, Ford T, Thompson S, Wright L, Jones K, Prodohl P, Skuce R. Whole-Genome sequencing in routine Mycobacterium bovis epidemiology - scoping the potential. Microb Genom 2024; 10:001185. [PMID: 38354031 PMCID: PMC10926703 DOI: 10.1099/mgen.0.001185] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 01/09/2024] [Indexed: 02/16/2024] Open
Abstract
Mycobacterium bovis the main agent of bovine tuberculosis (bTB), presents as a series of spatially-localised micro-epidemics across landscapes. Classical molecular typing methods applied to these micro-epidemics, based on genotyping a few variable loci, have significantly improved our understanding of potential epidemiological links between outbreaks. However, they have limited utility owing to low resolution. Conversely, whole-genome sequencing (WGS) provides the highest resolution data available for molecular epidemiology, producing richer outbreak tracing, insights into phylogeography and epidemic evolutionary history. We illustrate these advantages by focusing on a common single lineage of M. bovis (1.140) from Northern Ireland. Specifically, we investigate the spatial sub-structure of 20 years of herd-level multi locus VNTR analysis (MLVA) surveillance data and WGS data from a down sampled subset of isolates of this MLVA type over the same time frame. We mapped 2108 isolate locations of MLVA type 1.140 over the years 2000-2022. We also mapped the locations of 148 contemporary WGS isolates from this lineage, over a similar geographic range, stratifying by single nucleotide polymorphism (SNP) relatedness cut-offs of 15 SNPs. We determined a putative core range for the 1.140 MLVA type and SNP-defined sequence clusters using a 50 % kernel density estimate, using cattle movement data to inform on likely sources of WGS isolates found outside of core ranges. Finally, we applied Bayesian phylogenetic methods to investigate past population history and reproductive number of the 1.140 M. bovis lineage. We demonstrate that WGS SNP-defined clusters exhibit smaller core ranges than the established MLVA type - facilitating superior disease tracing. We also demonstrate the superior functionality of WGS data in determining how this lineage was disseminated across the landscape, likely via cattle movement and to infer how its effective population size and reproductive number has been in flux since its emergence. These initial findings highlight the potential of WGS data for routine monitoring of bTB outbreaks.
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Affiliation(s)
- Adrian Allen
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Ryan Magee
- Queen’s University Belfast, school of Biological Sciences, UK
| | - Ryan Devaney
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Tara Ardis
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Caitlín McNally
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Carl McCormick
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Eleanor Presho
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Michael Doyle
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Purnika Ranasinghe
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Philip Johnston
- Department of Agriculture, Environment and Rural Affairs for Northern Ireland, Belfast, UK
| | - Raymond Kirke
- Department of Agriculture, Environment and Rural Affairs for Northern Ireland, Belfast, UK
| | - Roland Harwood
- Department of Agriculture, Environment and Rural Affairs for Northern Ireland, Belfast, UK
| | - Damien Farrell
- Central Veterinary Research Laboratory, Kildare, Ireland
- University College Dublin, Dublin, Ireland
| | - Kevin Kenny
- Central Veterinary Research Laboratory, Kildare, Ireland
| | | | | | - Tom Ford
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Suzan Thompson
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Lorraine Wright
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Kerri Jones
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
| | - Paulo Prodohl
- Queen’s University Belfast, school of Biological Sciences, UK
| | - Robin Skuce
- Agrifood and Biosciences Institute, Veterinary Sciences Division, Belfast, UK
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Abd-Elshafy DN, Nadeem R, Nasraa MH, Bahgat MM. Analysis of the SARS-CoV-2 nsp12 P323L/A529V mutations: coeffect in the transiently peaking lineage C.36.3 on protein structure and response to treatment in Egyptian records. Z NATURFORSCH C 2024; 79:13-24. [PMID: 38265042 DOI: 10.1515/znc-2023-0132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 01/09/2024] [Indexed: 01/25/2024]
Abstract
SARS-CoV-2 nsp12, the RNA-dependent RNA-polymerase plays a crucial role in virus replication. Monitoring the effect of its emerging mutants on viral replication and response to antiviral drugs is important. Nsp12 of two Egyptian isolates circulating in 2020 and 2021 were sequenced. Both isolates included P323L, one included the A529V. Tracking A529V mutant frequency, it relates to the transience peaked C.36.3 variant and its parent C.36, both peaked worldwide on February-August 2021, enlisted as high transmissible variants under investigation (VUI) on May 2021. Both Mutants were reported to originate from Egypt and showed an abrupt low frequency upon screening, we analyzed all 1104 nsp12 Egyptian sequences. A529V mutation was in 36 records with an abrupt low frequency on June 2021. As its possible reappearance might obligate actions for a candidate VUI, we analyzed the predicted co-effect of P323L and A529V mutations on protein stability and dynamics through protein structure simulations. Three available structures for drug-nsp12 interaction were used representing remdesivir, suramin and favipiravir drugs. Remdesivir and suramin showed an increase in structure stability and considerable change in flexibility while favipiravir showed an extreme interaction. Results predict a favored efficiency of the drugs except for favipiravir in case of the reported mutations.
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Affiliation(s)
- Dina N Abd-Elshafy
- Department of Water Pollution Research, Environmental and Climate Change Research Institute, The National Research Centre, Dokki, Cairo, Egypt
- Immune- and Bio-markers for Infection Research Group, The Center of Excellence for Advanced Sciences, The National Research Centre, Dokki, Cairo, Egypt
| | - Rola Nadeem
- Department of Therapeutic Chemistry, Pharmaceutical and Drug Industries Research Institute, The National Research Centre, Dokki, Cairo, Egypt
- Immune- and Bio-markers for Infection Research Group, The Center of Excellence for Advanced Sciences, The National Research Centre, Dokki, Cairo, Egypt
| | - Mohamed H Nasraa
- Department of Therapeutic Chemistry, Pharmaceutical and Drug Industries Research Institute, The National Research Centre, Dokki, Cairo, Egypt
- Immune- and Bio-markers for Infection Research Group, The Center of Excellence for Advanced Sciences, The National Research Centre, Dokki, Cairo, Egypt
| | - Mahmoud M Bahgat
- Department of Therapeutic Chemistry, Pharmaceutical and Drug Industries Research Institute, The National Research Centre, Dokki, Cairo, Egypt
- Immune- and Bio-markers for Infection Research Group, The Center of Excellence for Advanced Sciences, The National Research Centre, Dokki, Cairo, Egypt
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46
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Rubio A, de Toro M, Pérez-Pulido AJ. The most exposed regions of SARS-CoV-2 structural proteins are subject to strong positive selection and gene overlap may locally modify this behavior. mSystems 2024; 9:e0071323. [PMID: 38095866 PMCID: PMC10804949 DOI: 10.1128/msystems.00713-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 11/10/2023] [Indexed: 12/22/2023] Open
Abstract
The SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic that emerged in 2019 has been an unprecedented event in international science, as it has been possible to sequence millions of genomes, tracking their evolution very closely. This has enabled various types of secondary analyses of these genomes, including the measurement of their sequence selection pressure. In this work, we have been able to measure the selective pressure of all the described SARS-CoV-2 genes, even analyzed by sequence regions, and we show how this type of analysis allows us to separate the genes between those subject to positive selection (usually those that code for surface proteins or those exposed to the host immune system) and those subject to negative selection because they require greater conservation of their structure and function. We have also seen that when another gene with an overlapping reading frame appears within a gene sequence, the overlapping sequence between the two genes evolves under a stronger purifying selection than the average of the non-overlapping regions of the main gene. We propose this type of analysis as a useful tool for locating and analyzing all the genes of a viral genome when an adequate number of sequences are available.IMPORTANCEWe have analyzed the selection pressure of all severe acute respiratory syndrome coronavirus 2 genes by means of the nonsynonymous (Ka) to synonymous (Ks) substitution rate. We found that protein-coding genes are exposed to strong positive selection, especially in the regions of interaction with other molecules (host receptor and genome of the virus itself). However, overlapping coding regions are more protected and show negative selection. This suggests that this measure could be used to study viral gene function as well as overlapping genes.
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Affiliation(s)
- Alejandro Rubio
- Faculty of Experimental Sciences, Genetics Area, Andalusian Centre for Developmental Biology (CABD, UPO-CSIC-JA), University Pablo de Olavide, Sevilla, Spain
| | - Maria de Toro
- Genomics and Bioinformatics Core Facility, Center for Biomedical Research of La Rioja, Logroño, Spain
| | - Antonio J. Pérez-Pulido
- Faculty of Experimental Sciences, Genetics Area, Andalusian Centre for Developmental Biology (CABD, UPO-CSIC-JA), University Pablo de Olavide, Sevilla, Spain
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Farjo M, Koelle K, Martin MA, Gibson LL, Walden KKO, Rendon G, Fields CJ, Alnaji FG, Gallagher N, Luo CH, Mostafa HH, Manabe YC, Pekosz A, Smith RL, McManus DD, Brooke CB. Within-host evolutionary dynamics and tissue compartmentalization during acute SARS-CoV-2 infection. J Virol 2024; 98:e0161823. [PMID: 38174928 PMCID: PMC10805032 DOI: 10.1128/jvi.01618-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 12/01/2023] [Indexed: 01/05/2024] Open
Abstract
The global evolution of SARS-CoV-2 depends in part upon the evolutionary dynamics within individual hosts with varying immune histories. To characterize the within-host evolution of acute SARS-CoV-2 infection, we sequenced saliva and nasal samples collected daily from vaccinated and unvaccinated individuals early during infection. We show that longitudinal sampling facilitates high-confidence genetic variant detection and reveals evolutionary dynamics missed by less-frequent sampling strategies. Within-host dynamics in both unvaccinated and vaccinated individuals appeared largely stochastic; however, in rare cases, minor genetic variants emerged to frequencies sufficient for forward transmission. Finally, we detected significant genetic compartmentalization of viral variants between saliva and nasal swab sample sites in many individuals. Altogether, these data provide a high-resolution profile of within-host SARS-CoV-2 evolutionary dynamics.IMPORTANCEWe detail the within-host evolutionary dynamics of SARS-CoV-2 during acute infection in 31 individuals using daily longitudinal sampling. We characterized patterns of mutational accumulation for unvaccinated and vaccinated individuals, and observed that temporal variant dynamics in both groups were largely stochastic. Comparison of paired nasal and saliva samples also revealed significant genetic compartmentalization between tissue environments in multiple individuals. Our results demonstrate how selection, genetic drift, and spatial compartmentalization all play important roles in shaping the within-host evolution of SARS-CoV-2 populations during acute infection.
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Affiliation(s)
- Mireille Farjo
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, Georgia, USA
| | - Michael A. Martin
- Department of Biology, Emory University, Atlanta, Georgia, USA
- Population Biology, Ecology, and Evolution Graduate Program, Emory University, Atlanta, Georgia, USA
| | - Laura L. Gibson
- Division of Infectious Diseases and Immunology, Department of Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USA
- Department of Pediatrics, University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - Kimberly K. O. Walden
- High-Performance Biological Computing at the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Gloria Rendon
- High-Performance Biological Computing at the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Christopher J. Fields
- High-Performance Biological Computing at the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Fadi G. Alnaji
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Nicholas Gallagher
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Chun Huai Luo
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Heba H. Mostafa
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Yukari C. Manabe
- Division of Infectious Disease, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Andrew Pekosz
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Rebecca L. Smith
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Department of Pathobiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - David D. McManus
- Division of Cardiology, University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - Christopher B. Brooke
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
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Banho CA, de Carvalho Marques B, Sacchetto L, Sepedro Lima AK, Pereira Parra MC, Jeronimo Lima AR, Ribeiro G, Jorge Martins A, dos Santos Barros CR, Carolina Elias M, Coccuzzo Sampaio S, Nanev Slavov S, Strazza Rodrigues E, Vieira Santos E, Tadeu Covas D, Kashima S, Augusto Brassaloti R, Petry B, Gaspar Clemente L, Lehmann Coutinho L, Akemi Assato P, da Silva da Costa FA, Souza-Neto JA, Maria Tommasini Grotto R, Daiana Poleti M, Cristina Chagas Lesbon J, Chicaroni Mattos E, Fukumasu H, Giovanetti M, Carlos Junior Alcantara L, Rahal P, Pessoa Araújo JF, Althouse BM, Vasilakis N, Lacerda Nogueira M. Dynamic clade transitions and the influence of vaccine rollout on the spatiotemporal circulation of SARS-CoV-2 variants in São Paulo, Brazil. Res Sq 2024:rs.3.rs-3788142. [PMID: 38343798 PMCID: PMC10854302 DOI: 10.21203/rs.3.rs-3788142/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Since 2021, the emergence of variants of concern (VOC) has led Brazil to experience record numbers of in COVID-19 cases and deaths. The expanded spread of the SARS-CoV-2 combined with a low vaccination rate has contributed to the emergence of new mutations that may enhance viral fitness, leading to the persistence of the disease. Due to limitations in the real-time genomic monitoring of new variants in some Brazilian states, we aimed to investigate whether genomic surveillance, coupled with epidemiological data and SARS-CoV-2 variants spatiotemporal spread in a smaller region, can reflect the pandemic progression at a national level. Our findings revealed three SARS-CoV-2 variant replacements from 2021 to early 2022, corresponding to the introduction and increase in the frequency of Gamma, Delta, and Omicron variants, as indicated by peaks of the Effective Reproductive Number (Reff). These distinct clade replacements triggered two waves of COVID-19 cases, influenced by the increasing vaccine uptake over time. Our results indicated that the effectiveness of vaccination in preventing new cases during the Delta and Omicron circulations was six and eleven times higher, respectively, than during the period when Gamma was predominant, and it was highly efficient in reducing the number of deaths. Furthermore, we demonstrated that genomic monitoring at a local level can reflect the national trends in the spread and evolution of SARS-CoV-2.
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Affiliation(s)
- Cecília Artico Banho
- Laboratório de Pesquisas em Virologia, Faculdade de Medicina de São José do Rio Preto; São José do Rio Preto, São Paulo, Brazil
| | - Beatriz de Carvalho Marques
- Laboratório de Pesquisas em Virologia, Faculdade de Medicina de São José do Rio Preto; São José do Rio Preto, São Paulo, Brazil
| | - Lívia Sacchetto
- Laboratório de Pesquisas em Virologia, Faculdade de Medicina de São José do Rio Preto; São José do Rio Preto, São Paulo, Brazil
| | - Ana Karoline Sepedro Lima
- Laboratório de Pesquisas em Virologia, Faculdade de Medicina de São José do Rio Preto; São José do Rio Preto, São Paulo, Brazil
| | - Maisa Carla Pereira Parra
- Laboratório de Pesquisas em Virologia, Faculdade de Medicina de São José do Rio Preto; São José do Rio Preto, São Paulo, Brazil
| | - Alex Ranieri Jeronimo Lima
- Center for Viral Surveillance and Serological Assessment (CeVIVAS), Butantan Institute, São Paulo, Brazil
| | - Gabriela Ribeiro
- Center for Viral Surveillance and Serological Assessment (CeVIVAS), Butantan Institute, São Paulo, Brazil
| | - Antonio Jorge Martins
- Center for Viral Surveillance and Serological Assessment (CeVIVAS), Butantan Institute, São Paulo, Brazil
| | | | - Maria Carolina Elias
- Center for Viral Surveillance and Serological Assessment (CeVIVAS), Butantan Institute, São Paulo, Brazil
| | - Sandra Coccuzzo Sampaio
- Center for Viral Surveillance and Serological Assessment (CeVIVAS), Butantan Institute, São Paulo, Brazil
| | - Svetoslav Nanev Slavov
- Center for Viral Surveillance and Serological Assessment (CeVIVAS), Butantan Institute, São Paulo, Brazil
- University of São Paulo, Ribeirão Preto Medical School, Blood Center of Ribeirão Preto, Ribeirão Preto, SP, Brazil
| | - Evandra Strazza Rodrigues
- University of São Paulo, Ribeirão Preto Medical School, Blood Center of Ribeirão Preto, Ribeirão Preto, SP, Brazil
| | - Elaine Vieira Santos
- University of São Paulo, Ribeirão Preto Medical School, Blood Center of Ribeirão Preto, Ribeirão Preto, SP, Brazil
| | - Dimas Tadeu Covas
- Center for Viral Surveillance and Serological Assessment (CeVIVAS), Butantan Institute, São Paulo, Brazil
- University of São Paulo, Ribeirão Preto Medical School, Blood Center of Ribeirão Preto, Ribeirão Preto, SP, Brazil
| | - Simone Kashima
- University of São Paulo, Ribeirão Preto Medical School, Blood Center of Ribeirão Preto, Ribeirão Preto, SP, Brazil
| | | | - Bruna Petry
- University of São Paulo, Centro de Genômica Funcional da ESALQ, Piracicaba, SP, Brazil
| | - Luan Gaspar Clemente
- University of São Paulo, Centro de Genômica Funcional da ESALQ, Piracicaba, SP, Brazil
| | - Luiz Lehmann Coutinho
- University of São Paulo, Centro de Genômica Funcional da ESALQ, Piracicaba, SP, Brazil
| | - Patricia Akemi Assato
- São Paulo State University (UNESP), School of Agricultural Sciences, Department of Bioprocesses and Biotechnology, Botucatu, Brazil
| | - Felipe Allan da Silva da Costa
- São Paulo State University (UNESP), School of Agricultural Sciences, Department of Bioprocesses and Biotechnology, Botucatu, Brazil
| | - Jayme A. Souza-Neto
- São Paulo State University (UNESP), School of Agricultural Sciences, Botucatu, Brazil
| | - Rejane Maria Tommasini Grotto
- São Paulo State University (UNESP), School of Agricultural Sciences, Botucatu, Brazil
- Molecular Biology Laboratory, Applied Biotechnology Laboratory, Clinical Hospital of the Botucatu Medical School, Brazil
| | - Mirele Daiana Poleti
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, São Paulo, Brazil
| | - Jessika Cristina Chagas Lesbon
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, São Paulo, Brazil
| | - Elisangela Chicaroni Mattos
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, São Paulo, Brazil
| | - Heidge Fukumasu
- Department of Veterinary Medicine, School of Animal Science and Food Engineering, University of São Paulo, Pirassununga, São Paulo, Brazil
| | - Marta Giovanetti
- Oswaldo Cruz Foundation, FIOCRUZ, Rio de Janeiro, Brazil
- Climate Amplified Diseases And Epidemics (CLIMADE), Brazil, Americas
- Sciences and Technologies for Sustainable Development and One Health, Universita Campus Bio-Medico di Roma, Italy
| | - Luiz Carlos Junior Alcantara
- Oswaldo Cruz Foundation, FIOCRUZ, Rio de Janeiro, Brazil
- Climate Amplified Diseases And Epidemics (CLIMADE), Brazil, Americas
| | - Paula Rahal
- Laboratório de Estudos Genômicos, Departamento de Biologia, Instituto de Biociências Letras e Ciências Exatas (IBILCE), Universidade Estadual Paulista (Unesp), São José do Rio Preto, Brazil
| | - João Fernando Pessoa Araújo
- Instituto de Biotecnologia, Universidade Estadual Paulista (Unesp), Botucatu, Brazil
- Laboratório de Microbiologia Molecular, Instituto de Ciências da Saúde, Universidade Feevale, Novo Hamburgo, Brazil
| | - Benjamin M. Althouse
- Department of Biology, New Mexico State University, Las Cruces, NM
- Information School, University of Washington, Seattle, WA
| | - Nikos Vasilakis
- Department of Pathology, University of Texas Medical Branch; Galveston, Texas, United States of America
- Center for Vector-Borne and Zoonotic Diseases, University of Texas Medical Branch, Galveston, Texas, United States of America
- Institute for Human Infection and Immunity, University of Texas Medical Branch, Galveston, Texas, United States of America
| | - Maurício Lacerda Nogueira
- Laboratório de Pesquisas em Virologia, Faculdade de Medicina de São José do Rio Preto; São José do Rio Preto, São Paulo, Brazil
- Department of Pathology, University of Texas Medical Branch; Galveston, Texas, United States of America
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49
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Harari S, Miller D, Fleishon S, Burstein D, Stern A. Using big sequencing data to identify chronic SARS-Coronavirus-2 infections. Nat Commun 2024; 15:648. [PMID: 38245511 PMCID: PMC10799923 DOI: 10.1038/s41467-024-44803-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 01/04/2024] [Indexed: 01/22/2024] Open
Abstract
The evolution of SARS-Coronavirus-2 (SARS-CoV-2) has been characterized by the periodic emergence of highly divergent variants. One leading hypothesis suggests these variants may have emerged during chronic infections of immunocompromised individuals, but limited data from these cases hinders comprehensive analyses. Here, we harnessed millions of SARS-CoV-2 genomes to identify potential chronic infections and used language models (LM) to infer chronic-associated mutations. First, we mined the SARS-CoV-2 phylogeny and identified chronic-like clades with identical metadata (location, age, and sex) spanning over 21 days, suggesting a prolonged infection. We inferred 271 chronic-like clades, which exhibited characteristics similar to confirmed chronic infections. Chronic-associated mutations were often high-fitness immune-evasive mutations located in the spike receptor-binding domain (RBD), yet a minority were unique to chronic infections and absent in global settings. The probability of observing high-fitness RBD mutations was 10-20 times higher in chronic infections than in global transmission chains. The majority of RBD mutations in BA.1/BA.2 chronic-like clades bore predictive value, i.e., went on to display global success. Finally, we used our LM to infer hundreds of additional chronic-like clades in the absence of metadata. Our approach allows mining extensive sequencing data and providing insights into future evolutionary patterns of SARS-CoV-2.
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Affiliation(s)
- Sheri Harari
- The Shmunis School of Biomedicine and Cancer Research, Tel Aviv University, Tel Aviv, Israel
- Edmond J. Safra Center for Bioinformatics, Tel Aviv University, Tel Aviv, Israel
| | - Danielle Miller
- The Shmunis School of Biomedicine and Cancer Research, Tel Aviv University, Tel Aviv, Israel
- Edmond J. Safra Center for Bioinformatics, Tel Aviv University, Tel Aviv, Israel
| | - Shay Fleishon
- Israeli Health Intelligence Agency, Public Health Division, Ministry of Health, Jerusalem, Israel
| | - David Burstein
- The Shmunis School of Biomedicine and Cancer Research, Tel Aviv University, Tel Aviv, Israel
- Edmond J. Safra Center for Bioinformatics, Tel Aviv University, Tel Aviv, Israel
| | - Adi Stern
- The Shmunis School of Biomedicine and Cancer Research, Tel Aviv University, Tel Aviv, Israel.
- Edmond J. Safra Center for Bioinformatics, Tel Aviv University, Tel Aviv, Israel.
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50
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Ling-Hu T, Simons LM, Dean TJ, Rios-Guzman E, Caputo MT, Alisoltani A, Qi C, Malczynski M, Blanke T, Jennings LJ, Ison MG, Achenbach CJ, Larkin PM, Kaul KL, Lorenzo-Redondo R, Ozer EA, Hultquist JF. Integration of individualized and population-level molecular epidemiology data to model COVID-19 outcomes. Cell Rep Med 2024; 5:101361. [PMID: 38232695 PMCID: PMC10829796 DOI: 10.1016/j.xcrm.2023.101361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 08/07/2023] [Accepted: 12/11/2023] [Indexed: 01/19/2024]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with enhanced transmissibility and immune escape have emerged periodically throughout the coronavirus disease 2019 (COVID-19) pandemic, but the impact of these variants on disease severity has remained unclear. In this single-center, retrospective cohort study, we examined the association between SARS-CoV-2 clade and patient outcome over a two-year period in Chicago, Illinois. Between March 2020 and March 2022, 14,252 residual diagnostic specimens were collected from SARS-CoV-2-positive inpatients and outpatients alongside linked clinical and demographic metadata, of which 2,114 were processed for viral whole-genome sequencing. When controlling for patient demographics and vaccination status, several viral clades were associated with risk for hospitalization, but this association was negated by the inclusion of population-level confounders, including case count, sampling bias, and shifting standards of care. These data highlight the importance of integrating non-virological factors into disease severity and outcome models for the accurate assessment of patient risk.
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Affiliation(s)
- Ted Ling-Hu
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Lacy M Simons
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Taylor J Dean
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Estefany Rios-Guzman
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Matthew T Caputo
- Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Arghavan Alisoltani
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Chao Qi
- Clinical Microbiology Laboratory, Department of Pathology, Northwestern Memorial Hospital, Chicago, IL 60611, USA
| | - Michael Malczynski
- Clinical Microbiology Laboratory, Department of Pathology, Northwestern Memorial Hospital, Chicago, IL 60611, USA
| | - Timothy Blanke
- Diagnostic Molecular Biology Laboratory, Northwestern Memorial Hospital, Chicago, IL 60611, USA
| | - Lawrence J Jennings
- Clinical Microbiology Laboratory, Department of Pathology, Northwestern Memorial Hospital, Chicago, IL 60611, USA
| | - Michael G Ison
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Chad J Achenbach
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Havey Institute for Global Health, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA
| | - Paige M Larkin
- Department of Molecular Microbiology, Northshore University HealthSystem, Evanston, IL 60201, USA
| | - Karen L Kaul
- Department of Pathology, Northshore University HealthSystem, Evanston, IL 60201, USA
| | - Ramon Lorenzo-Redondo
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Egon A Ozer
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA
| | - Judd F Hultquist
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA; Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL 60611, USA.
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