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Zhao L, Guo X, Li L, Jing Q, Ma J, Xie T, Lin D, Li L, Yin Q, Wang Y, Zhang X, Li Z, Liu X, Hu T, Hu M, Ren W, Li J, Peng J, Yu L, Peng Z, Hong W, Leng X, Luo L, Ngobeh JJK, Tang X, Wu R, Zhao W, Shi B, Liu J, Yang Z, Chen XG, Zhou X, Zhang F. Phylodynamics unveils invading and diffusing patterns of dengue virus serotype-1 in Guangdong, China from 1990 to 2019 under a global genotyping framework. Infect Dis Poverty 2024; 13:43. [PMID: 38863070 PMCID: PMC11165891 DOI: 10.1186/s40249-024-01211-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Accepted: 05/29/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND The strong invasiveness and rapid expansion of dengue virus (DENV) pose a great challenge to global public health. However, dengue epidemic patterns and mechanisms at a genetic scale, particularly in term of cross-border transmissions, remain poorly understood. Importation is considered as the primary driver of dengue outbreaks in China, and since 1990 a frequent occurrence of large outbreaks has been triggered by the imported cases and subsequently spread to the western and northern parts of China. Therefore, this study aims to systematically reveal the invasion and diffusion patterns of DENV-1 in Guangdong, China from 1990 to 2019. METHODS These analyses were performed on 179 newly assembled genomes from indigenous dengue cases in Guangdong, China and 5152 E gene complete sequences recorded in Chinese mainland. The genetic population structure and epidemic patterns of DENV-1 circulating in Chinese mainland were characterized by phylogenetics, phylogeography, phylodynamics based on DENV-1 E-gene-based globally unified genotyping framework. RESULTS Multiple serotypes of DENV were co-circulating in Chinese mainland, particularly in Guangdong and Yunnan provinces. A total of 189 transmission clusters in 38 clades belonging to 22 subgenotypes of genotype I, IV and V of DENV-1 were identified, with 7 Clades of Concern (COCs) responsible for the large outbreaks since 1990. The epidemic periodicity was inferred from the data to be approximately 3 years. Dengue transmission events mainly occurred from Great Mekong Subregion-China (GMS-China), Southeast Asia (SEA), South Asia Subcontinent (SASC), and Oceania (OCE) to coastal and land border cities respectively in southeastern and southwestern China. Specially, Guangzhou was found to be the most dominant receipting hub, where DENV-1 diffused to other cities within the province and even other parts of the country. Genome phylogeny combined with epidemiological investigation demonstrated a clear local consecutive transmission process of a 5C1 transmission cluster (5C1-CN4) of DENV-1 in Guangzhou from 2013 to 2015, while the two provinces of Guangdong and Yunnan played key roles in ongoing transition of dengue epidemic patterns. In contextualizing within Invasion Biology theories, we have proposed a derived three-stage model encompassing the stages of invasion, colonization, and dissemination, which is supposed to enhance our understanding of dengue spreading patterns. CONCLUSIONS This study demonstrates the invasion and diffusion process of DENV-1 in Chinese mainland within a global genotyping framework, characterizing the genetic diversities of viral populations, multiple sources of importation, and periodic dynamics of the epidemic. These findings highlight the potential ongoing transition trends from epidemic to endemic status offering a valuable insight into early warning, prevention and control of rapid spreading of dengue both in China and worldwide.
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Affiliation(s)
- Lingzhai Zhao
- Institute of Infectious Diseases, Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, 510440, Guangdong, China
| | - Xiang Guo
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | - Liqiang Li
- Department of Clinical Laboratory, The Third People's Hospital of Shenzhen, Southern University of Science and Technology, National Clinical Research Center for Infectious Diseases, Guangdong Provincial Clinical Research Center for Infectious Diseases (Tuberculosis), Shenzhen Clinical Research Center for Tuberculosis, Shenzhen, China
| | - Qinlong Jing
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, China
| | - Jinmin Ma
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Tian Xie
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | | | - Li Li
- Department of Biostatistics, School of Public Health, State Key Laboratory of Organ Failure Research, Guangdong Provincial Key Laboratory of Tropical Disease Research, Southern Medical University, Guangzhou, 510515, China
| | - Qingqing Yin
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | - Yuji Wang
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | - Xiaoqing Zhang
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | - Ziyao Li
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | - Xiaohua Liu
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | - Tian Hu
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | - Minling Hu
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | - Wenwen Ren
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | - Jun Li
- Guangdong Provincial Key Laboratory of Research On Emergency in TCM, Guangdong Provincial Hospital of Traditional Chinese Medicine, Guangzhou, 510120, China
| | - Jie Peng
- Department of Infectious Diseases, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, China
| | - Lei Yu
- Institute of Infectious Diseases, Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, 510440, Guangdong, China
| | - Zhiqiang Peng
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, 511430, China
| | - Wenxin Hong
- Institute of Infectious Diseases, Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, 510440, Guangdong, China
| | - Xingyu Leng
- Institute of Infectious Diseases, Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, 510440, Guangdong, China
| | - Lei Luo
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, China
| | - Jone Jama Kpanda Ngobeh
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China
| | - Xiaoping Tang
- Institute of Infectious Diseases, Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, 510440, Guangdong, China
| | - Rangke Wu
- The School of Foreign Studies, Southern Medical University, Guangzhou, 510515, China
| | - Wei Zhao
- BSL-3 Laboratory(Guangdong), School of Public Health, Southern Medical University, Guangzhou, 510515, China
| | - Benyun Shi
- College of Computer and Information Engineering, Nanjing Tech University, Nanjing, 211816, China
| | - Jiming Liu
- Department of Computer Science, Hong Kong Baptist University, Hong Kong, 999077, China
| | - Zhicong Yang
- Guangzhou Center for Disease Control and Prevention, Guangzhou, 510440, China.
| | - Xiao-Guang Chen
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China.
| | - Xiaohong Zhou
- Department of Pathogen Biology, School of Public Health, Institute of Tropical Medicine, Southern Medical University; Guangdong Provincial Key Laboratory of Tropical Disease Research; Key Laboratory of Prevention and Control for Emerging Infectious Diseases of Guangdong Higher Institutes; Key Laboratory of Infectious Diseases Research in South China of Ministry of Education, Guangzhou, 510515, China.
| | - Fuchun Zhang
- Institute of Infectious Diseases, Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, 510440, Guangdong, China.
- Guangzhou Medical Research Institute of Infectious Diseases, Infectious Disease Center, Guangzhou Eighth People's Hospital, Guangzhou Medical University, Guangzhou, 510440, China.
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2
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Astakhova EA, Morozov AA, Vavilova JD, Filatov AV. Antigenic Cartography of SARS-CoV-2. BIOCHEMISTRY. BIOKHIMIIA 2024; 89:862-871. [PMID: 38880647 DOI: 10.1134/s0006297924050079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 01/14/2024] [Accepted: 01/17/2024] [Indexed: 06/18/2024]
Abstract
Antigenic cartography is a tool for interpreting and visualizing antigenic differences between virus variants based on virus neutralization data. This approach has been successfully used in the selection of influenza vaccine seed strains. With the emergence of SARS-CoV-2 variants escaping vaccine-induced antibody response, adjusting COVID-19 vaccines has become essential. This review provides information on the antigenic differences between SARS-CoV-2 variants revealed by antigenic cartography and explores a potential of antigenic cartography-based methods (e.g., building antibody landscapes and neutralization breadth gain plots) for the quantitative assessment of the breadth of the antibody response. Understanding the antigenic differences of SARS-CoV-2 and the possibilities of the formed humoral immunity aids in the prompt modification of preventative vaccines against COVID-19.
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Affiliation(s)
- Ekaterina A Astakhova
- National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, Moscow, 115522, Russia.
- Department of Immunology, Faculty of Biology, Lomonosov Moscow State University, Moscow, 119234, Russia
| | - Alexey A Morozov
- National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, Moscow, 115522, Russia
- Department of Immunology, Faculty of Biology, Lomonosov Moscow State University, Moscow, 119234, Russia
| | - Julia D Vavilova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, Moscow, 117997, Russia
| | - Alexander V Filatov
- National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, Moscow, 115522, Russia
- Department of Immunology, Faculty of Biology, Lomonosov Moscow State University, Moscow, 119234, Russia
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3
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Isabel S, Eshaghi A, Duvvuri VR, Gubbay JB, Cronin K, Li A, Hasso M, Clark ST, Hopkins JP, Patel SN, Braukmann TWA. Targeted amplification-based whole genome sequencing of Monkeypox virus in clinical specimens. Microbiol Spectr 2024; 12:e0297923. [PMID: 38047694 PMCID: PMC10783113 DOI: 10.1128/spectrum.02979-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 10/29/2023] [Indexed: 12/05/2023] Open
Abstract
IMPORTANCE We present a protocol to efficiently sequence genomes of the MPXV-causing mpox. This enables researchers and public health agencies to acquire high-quality genomic data using a rapid and cost-effective approach. Genomic data can be used to conduct surveillance and investigate mpox outbreaks. We present 91 mpox genomes that show the diversity of the 2022 mpox outbreak in Ontario, Canada.
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Affiliation(s)
- S. Isabel
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
| | - A. Eshaghi
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
| | - V. R. Duvvuri
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - J. B. Gubbay
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - K. Cronin
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
| | - Aimin Li
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
| | - M. Hasso
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
| | - S. T. Clark
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
| | - J. P. Hopkins
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario, Canada
| | - S. N. Patel
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - T. W. A. Braukmann
- Public Health Ontario Laboratory, Public Health Ontario, Toronto, Ontario, Canada
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Kulemzin SV, Guselnikov SV, Nekrasov BG, Molodykh SV, Kuvshinova IN, Murasheva SV, Belovezhets TN, Gorchakov AA, Chikaev AN, Chikaev NA, Volkova OY, Yurina AA, Najakshin AM, Taranin AV. Hybrid Immunity from Gam-COVID-Vac Vaccination and Natural SARS-CoV-2 Infection Confers Broader Neutralizing Activity against Omicron Lineage VOCs Than Revaccination or Reinfection. Vaccines (Basel) 2024; 12:55. [PMID: 38250868 PMCID: PMC10818410 DOI: 10.3390/vaccines12010055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 12/13/2023] [Accepted: 01/04/2024] [Indexed: 01/23/2024] Open
Abstract
SARS-CoV-2 has a relatively high mutation rate, with the frequent emergence of new variants of concern (VOCs). Each subsequent variant is more difficult to neutralize by the sera of vaccinated individuals and convalescents. Some decrease in neutralizing activity against new SARS-CoV-2 variants has also been observed in patients vaccinated with Gam-COVID-Vac. In the present study, we analyzed the interplay between the history of a patient's repeated exposure to SARS-CoV-2 antigens and the breadth of neutralization activity. Our study includes four cohorts of patients: Gam-COVID-Vac booster vaccinated individuals (revaccinated, RV), twice-infected unvaccinated individuals (reinfected, RI), breakthrough infected (BI), and vaccinated convalescents (VC). We assessed S-protein-specific antibody levels and the ability of sera to neutralize lentiviral particles pseudotyped with Spike protein from the original Wuhan variant, as well as the Omicron variants BA.1 and BA.4/5. Individuals with hybrid immunity (BI and VC cohorts) exhibited significantly higher levels of virus-binding IgG and enhanced breadth of virus-neutralizing activity compared to individuals from either the revaccination or reinfection (RV and RI) cohorts. These findings suggest that a combination of infection and vaccination, regardless of the sequence, results in significantly higher levels of S-protein-specific IgG antibodies and the enhanced neutralization of SARS-CoV-2 variants, thereby underscoring the importance of hybrid immunity in the context of emerging viral variants.
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Affiliation(s)
- Sergey V. Kulemzin
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
| | - Sergey V. Guselnikov
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
| | | | | | | | - Svetlana V. Murasheva
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
| | - Tatyana N. Belovezhets
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
| | - Andrey A. Gorchakov
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
| | - Anton N. Chikaev
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
| | - Nikolai A. Chikaev
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
| | - Olga Y. Volkova
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
| | - Anna A. Yurina
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
| | - Alexander M. Najakshin
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
| | - Alexander V. Taranin
- Institute of Molecular and Cellular Biology SB RAS, Novosibirsk 630090, Russia; (S.V.K.); (S.V.G.)
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5
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Hare D, Dembicka KM, Brennan C, Campbell C, Sutton-Fitzpatrick U, Stapleton PJ, De Gascun CF, Dunne CP. Whole-genome sequencing to investigate transmission of SARS-CoV-2 in the acute healthcare setting: a systematic review. J Hosp Infect 2023; 140:139-155. [PMID: 37562592 DOI: 10.1016/j.jhin.2023.08.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 07/03/2023] [Accepted: 08/04/2023] [Indexed: 08/12/2023]
Abstract
BACKGROUND Whole-genome sequencing (WGS) has been used widely to elucidate transmission of SARS-CoV-2 in acute healthcare settings, and to guide infection, prevention, and control (IPC) responses. AIM To systematically appraise available literature, published between January 1st, 2020 and June 30th, 2022, describing the implementation of WGS in acute healthcare settings to characterize nosocomial SARS-CoV-2 transmission. METHODS Searches of the PubMed, Embase, Ovid MEDLINE, EBSCO MEDLINE, and Cochrane Library databases identified studies in English reporting the use of WGS to investigate SARS-CoV-2 transmission in acute healthcare environments. Publications involved data collected up to December 31st, 2021, and findings were reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. FINDINGS In all, 3088 non-duplicate records were retrieved; 97 met inclusion criteria, involving 62 outbreak analyses and 35 genomic surveillance studies. No publications from low-income countries were identified. In 87/97 (90%), WGS supported hypotheses for nosocomial transmission, while in 46 out of 97 (47%) suspected transmission events were excluded. An IPC intervention was attributed to the use of WGS in 18 out of 97 (18%); however, only three (3%) studies reported turnaround times ≤7 days facilitating near real-time IPC action, and none reported an impact on the incidence of nosocomial COVID-19 attributable to WGS. CONCLUSION WGS can elucidate transmission of SARS-CoV-2 in acute healthcare settings to enhance epidemiological investigations. However, evidence was not identified to support sequencing as an intervention to reduce the incidence of SARS-CoV-2 in hospital or to alter the trajectory of active outbreaks.
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Affiliation(s)
- D Hare
- UCD National Virus Reference Laboratory, University College Dublin, Ireland; School of Medicine, University of Limerick, Limerick, Ireland.
| | - K M Dembicka
- School of Medicine, University of Limerick, Limerick, Ireland
| | - C Brennan
- UCD National Virus Reference Laboratory, University College Dublin, Ireland
| | - C Campbell
- UCD National Virus Reference Laboratory, University College Dublin, Ireland
| | | | | | - C F De Gascun
- UCD National Virus Reference Laboratory, University College Dublin, Ireland
| | - C P Dunne
- School of Medicine, University of Limerick, Limerick, Ireland; Centre for Interventions in Infection, Inflammation & Immunity (4i), University of Limerick, Limerick, Ireland
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6
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Palyanova NV, Sobolev IA, Palyanov AY, Kurskaya OG, Komissarov AB, Danilenko DM, Fadeev AV, Shestopalov AM. The Development of the SARS-CoV-2 Epidemic in Different Regions of Siberia in the 2020-2022 Period. Viruses 2023; 15:2014. [PMID: 37896792 PMCID: PMC10612024 DOI: 10.3390/v15102014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/08/2023] [Accepted: 09/15/2023] [Indexed: 10/29/2023] Open
Abstract
The comparison of the development of the SARS-CoV-2 epidemic in several neighboring regions can help researchers to assess the risks and develop more effective strategies and approaches in the field of preventive medicine. We analyzed the infection and mortality statistics for the 2020-2022 period in ten individual regions of the Siberian Federal District of Russia. We also sequenced complete genomes, which allowed us to analyze the genetic diversity of SARS-CoV-2 circulated in each of the ten regions and to build a phylogenetic dendrogram for the virus variants. The ParSeq v.1.0 software was developed to automate and speed up the processing and analysis of viral genomes. At the beginning of the pandemic, in the first two waves, the B.1.1 variant (20B) dominated in all regions of the Siberian Federal District. The third and fourth waves were caused by the Delta variant. Mortality during this period was at a maximum; the incidence was quite high, but the number of deposited genomes with GISAID during this period was extremely low. The maximum incidence was at the beginning of 2022, which corresponds to the arrival of the Omicron variant in the region. The BA.5.2 variant became the dominant one. In addition, by using NextClade, we identified three recombinants in the most densely populated areas.
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Affiliation(s)
- Natalia V. Palyanova
- Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia; (I.A.S.); (A.Y.P.); (O.G.K.); (A.M.S.)
| | - Ivan A. Sobolev
- Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia; (I.A.S.); (A.Y.P.); (O.G.K.); (A.M.S.)
| | - Andrey Yu. Palyanov
- Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia; (I.A.S.); (A.Y.P.); (O.G.K.); (A.M.S.)
- A.P. Ershov Institute of Informatics Systems, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia
- Department of Mathematics and Mechanics, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Olga G. Kurskaya
- Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia; (I.A.S.); (A.Y.P.); (O.G.K.); (A.M.S.)
| | - Andrey B. Komissarov
- Federal Budgetary Institution «Smorodintsev Research Institute of Influenza», 197376 St. Petersburg, Russia; (A.B.K.); (D.M.D.); (A.V.F.)
| | - Daria M. Danilenko
- Federal Budgetary Institution «Smorodintsev Research Institute of Influenza», 197376 St. Petersburg, Russia; (A.B.K.); (D.M.D.); (A.V.F.)
| | - Artem V. Fadeev
- Federal Budgetary Institution «Smorodintsev Research Institute of Influenza», 197376 St. Petersburg, Russia; (A.B.K.); (D.M.D.); (A.V.F.)
| | - Alexander M. Shestopalov
- Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia; (I.A.S.); (A.Y.P.); (O.G.K.); (A.M.S.)
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7
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Sukhova M, Byazrova M, Mikhailov A, Yusubalieva G, Maslova I, Belovezhets T, Chikaev N, Vorobiev I, Baklaushev V, Filatov A. Humoral Immune Responses in Patients with Severe COVID-19: A Comparative Pilot Study between Individuals Infected by SARS-CoV-2 during the Wild-Type and the Delta Periods. Microorganisms 2023; 11:2347. [PMID: 37764191 PMCID: PMC10536989 DOI: 10.3390/microorganisms11092347] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 09/08/2023] [Accepted: 09/09/2023] [Indexed: 09/29/2023] Open
Abstract
Since the onset of the COVID-19 pandemic, humanity has experienced the spread and circulation of several SARS-CoV-2 variants that differed in transmissibility, contagiousness, and the ability to escape from vaccine-induced neutralizing antibodies. However, issues related to the differences in the variant-specific immune responses remain insufficiently studied. The aim of this study was to compare the parameters of the humoral immune responses in two groups of patients with acute COVID-19 who were infected during the circulation period of the D614G and the Delta variants of SARS-CoV-2. Sera from 48 patients with acute COVID-19 were tested for SARS-CoV-2 binding and neutralizing antibodies using six assays. We found that serum samples from the D614G period demonstrated 3.9- and 1.6-fold increases in RBD- and spike-specific IgG binding with wild-type antigens compared with Delta variant antigens (p < 0.01). Cluster analysis showed the existence of two well-separated clusters. The first cluster mainly consisted of D614G-period patients and the second cluster predominantly included patients from the Delta period. The results thus obtained indicate that humoral immune responses in D614G- and Delta-specific infections can be characterized by variant-specific signatures. This can be taken into account when developing new variant-specific vaccines.
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Affiliation(s)
- Maria Sukhova
- Laboratory of Immunochemistry, National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, 115522 Moscow, Russia; (M.S.); (M.B.); (A.M.)
- Department of Immunology, Faculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia
| | - Maria Byazrova
- Laboratory of Immunochemistry, National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, 115522 Moscow, Russia; (M.S.); (M.B.); (A.M.)
- Department of Immunology, Faculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia
- Department of Immunology, Peoples’ Friendship University of Russia (RUDN University) of Ministry of Science and Higher Education of the Russian Federation, 117198 Moscow, Russia
| | - Artem Mikhailov
- Laboratory of Immunochemistry, National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, 115522 Moscow, Russia; (M.S.); (M.B.); (A.M.)
- Department of Immunology, Faculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia
| | - Gaukhar Yusubalieva
- Laboratory of Cell Technology, Federal Research and Clinical Center for Specialized Types of Medical Care and Medical Technologies of the FMBA of Russia, 115682 Moscow, Russia; (G.Y.); (V.B.)
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Irina Maslova
- Clinical Hospital #85, Federal Medical Biological Agency of Russia, 115409 Moscow, Russia;
| | - Tatyana Belovezhets
- Laboratory of Immunogenetics, Institute of Molecular and Cellular Biology, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia; (T.B.); (N.C.)
| | - Nikolay Chikaev
- Laboratory of Immunogenetics, Institute of Molecular and Cellular Biology, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia; (T.B.); (N.C.)
| | - Ivan Vorobiev
- Laboratory of Mammalian Cell Bioengineering, Skryabin Institute of Bioengineering, Research Center of Biotechnology of the Russian Academy of Sciences, 117312 Moscow, Russia;
| | - Vladimir Baklaushev
- Laboratory of Cell Technology, Federal Research and Clinical Center for Specialized Types of Medical Care and Medical Technologies of the FMBA of Russia, 115682 Moscow, Russia; (G.Y.); (V.B.)
- Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia
| | - Alexander Filatov
- Laboratory of Immunochemistry, National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, 115522 Moscow, Russia; (M.S.); (M.B.); (A.M.)
- Department of Immunology, Faculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia
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8
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Klink GV, Danilenko D, Komissarov AB, Yolshin N, Shneider O, Shcherbak S, Nabieva E, Shvyrev N, Konovalova N, Zheltukhina A, Fadeev A, Komissarova K, Ksenafontov A, Musaeva T, Eder V, Pisareva M, Nekrasov P, Shchur V, Bazykin GA, Lioznov D. An Early SARS-CoV-2 Omicron Outbreak in a Dormitory in Saint Petersburg, Russia. Viruses 2023; 15:1415. [PMID: 37515103 PMCID: PMC10385080 DOI: 10.3390/v15071415] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 06/12/2023] [Accepted: 06/14/2023] [Indexed: 07/30/2023] Open
Abstract
The Omicron variant of SARS-CoV-2 rapidly spread worldwide in late 2021-early 2022, displacing the previously prevalent Delta variant. Before 16 December 2021, community transmission had already been observed in tens of countries globally. However, in Russia, the majority of reported cases at that time had been sporadic and associated with travel. Here, we report an Omicron outbreak at a student dormitory in Saint Petersburg between 16-29 December 2021, which was the earliest known instance of a large-scale community transmission in Russia. Out of the 465 sampled residents of the dormitory, 180 (38.7%) tested PCR-positive. Among the 118 residents for whom the variant had been tested by whole-genome sequencing, 111 (94.1%) were found to carry the Omicron variant. Among these 111 residents, 60 (54.1%) were vaccinated or had reported a previous infection of COVID-19. Phylogenetic analysis confirmed that the outbreak was caused by a single introduction of the BA.1.1 sub-lineage of the Omicron variant. The dormitory-derived clade constituted a significant proportion of BA.1.1 samples in Saint Petersburg and has spread to other regions of Russia and even to other countries. The rapid spread of the Omicron variant in a population with preexisting immunity to previous variants underlines its propensity for immune evasion.
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Affiliation(s)
- Galya V Klink
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, 127051 Moscow, Russia
| | - Daria Danilenko
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Andrey B Komissarov
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Nikita Yolshin
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Olga Shneider
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
- City Hospital #40, 197706 Saint-Petersburg, Russia
| | | | - Elena Nabieva
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, 127051 Moscow, Russia
| | - Nikita Shvyrev
- International Laboratory of Statistical and Computational Genomics, HSE University, 101000 Moscow, Russia
| | - Nadezhda Konovalova
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Alyona Zheltukhina
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Artem Fadeev
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Kseniya Komissarova
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Andrey Ksenafontov
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Tamila Musaeva
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Veronika Eder
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Maria Pisareva
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Petr Nekrasov
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
| | - Vladimir Shchur
- International Laboratory of Statistical and Computational Genomics, HSE University, 101000 Moscow, Russia
| | - Georgii A Bazykin
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, 127051 Moscow, Russia
- Skolkovo Institute of Science and Technology (Skoltech), 121205 Moscow, Russia
| | - Dmitry Lioznov
- Smorodintsev Research Institute of Influenza, 197376 Saint-Petersburg, Russia
- First Pavlov State Medical University, 197022 Saint-Petersburg, Russia
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9
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Hamza S, Martynova E, Garanina E, Shakirova V, Bilalova A, Moiseeva S, Khaertynova I, Ohlopkova O, Blatt N, Markelova M, Khaiboullina S. Neutralizing Antibodies in COVID-19 Serum from Tatarstan, Russia. Int J Mol Sci 2023; 24:10181. [PMID: 37373331 DOI: 10.3390/ijms241210181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/05/2023] [Accepted: 06/10/2023] [Indexed: 06/29/2023] Open
Abstract
The severity of COVID-19 is a result of the complex interplay between various branches of the immune system. However, our understanding of the role of neutralizing antibodies and the activation of cellular immune response in COVID-19 pathogenesis remains limited. In this study, we investigated neutralizing antibodies in patients with mild, moderate, and severe COVID-19, analyzing their cross-reactivity with the Wuhan and Omicron variants. We also assessed the activation of the immune response by measuring serum cytokines in patients with mild, moderate, and severe COVID-19. Our findings suggest the early activation of neutralizing antibodies in moderate COVID-19 compared to mild cases. We also observed a strong correlation between the cross-reactivity of neutralizing antibodies to the Omicron and Wuhan variants and the severity of the disease. In addition, we found that Th1 lymphocyte activation was present in mild and moderate cases, while inflammasomes and Th17 lymphocytes were activated in severe COVID-19. In conclusion, our data indicate that the early activation of neutralizing antibodies is evident in moderate COVID-19, and there is a strong correlation between the cross-reactivity of neutralizing antibodies and the severity of the disease. Our findings suggest that the Th1 immune response may play a protective role, while inflammasome and Th17 activation may be involved in severe COVID-19.
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Affiliation(s)
- Shaimaa Hamza
- OpenLab "Gene and Cell Technologies", Kazan Federal University, 420021 Kazan, Russia
| | - Ekaterina Martynova
- OpenLab "Gene and Cell Technologies", Kazan Federal University, 420021 Kazan, Russia
| | - Ekaterina Garanina
- OpenLab "Gene and Cell Technologies", Kazan Federal University, 420021 Kazan, Russia
| | - Venera Shakirova
- Department of Infectious Diseases, Kazan State Medical Academy, 420012 Kazan, Russia
| | - Alisa Bilalova
- Department of Infectious Diseases, Kazan State Medical Academy, 420012 Kazan, Russia
| | - Svetlana Moiseeva
- Department of Infectious Diseases, Kazan State Medical Academy, 420012 Kazan, Russia
| | - Ilsiyar Khaertynova
- Department of Infectious Diseases, Kazan State Medical Academy, 420012 Kazan, Russia
| | - Olesia Ohlopkova
- State Research Center of Virology and Biotechnology «Vector» of Rospotrebnadzor, 630559 Koltsovo, Russia
| | - Nataliya Blatt
- OpenLab "Gene and Cell Technologies", Kazan Federal University, 420021 Kazan, Russia
| | - Maria Markelova
- OpenLab "Gene and Cell Technologies", Kazan Federal University, 420021 Kazan, Russia
| | - Svetlana Khaiboullina
- OpenLab "Gene and Cell Technologies", Kazan Federal University, 420021 Kazan, Russia
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10
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Matsvay A, Klink GV, Safina KR, Nabieva E, Garushyants SK, Biba D, Bazykin GA, Mikhaylov IM, Say AV, Zakamornaya AI, Khakhina AO, Lisitsa TS, Ayginin AA, Abramov IS, Bogdan SA, Kolbutova KB, Oleynikova DU, Avdeenko TF, Shipulin GA, Yudin SM, Skvortsova VI. Genomic epidemiology of SARS-CoV-2 in Russia reveals recurring cross-border transmission throughout 2020. PLoS One 2023; 18:e0285664. [PMID: 37192187 PMCID: PMC10187899 DOI: 10.1371/journal.pone.0285664] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 04/22/2023] [Indexed: 05/18/2023] Open
Abstract
In 2020, SARS-CoV-2 has spread rapidly across the globe, with most nations failing to prevent or substantially delay its introduction. While many countries have imposed some limitations on trans-border passenger traffic, the effect of these measures on the global spread of COVID-19 strains remains unclear. Here, we report an analysis of 3206 whole-genome sequences of SARS-CoV-2 samples from 78 regions of Russia covering the period before the spread of variants of concern (between March and November 2020). We describe recurring imports of multiple COVID-19 strains into Russia throughout this period, giving rise to 457 uniquely Russian transmission lineages, as well as repeated cross-border transmissions of local circulating variants out of Russia. While the phylogenetically inferred rate of cross-border transmissions was somewhat reduced during the period of the most stringent border closure, it still remained high, with multiple inferred imports that each led to detectable spread within the country. These results indicate that partial border closure has had little effect on trans-border transmission of variants, which helps explain the rapid global spread of newly arising SARS-CoV-2 variants throughout the pandemic.
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Affiliation(s)
- Alina Matsvay
- Federal State Budgetary Institution “Centre for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical Biological Agency, Moscow, Russia
| | - Galya V. Klink
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia
| | - Ksenia R. Safina
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
| | - Elena Nabieva
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
| | - Sofya K. Garushyants
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia
| | - Dmitry Biba
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
| | - Georgii A. Bazykin
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
| | - Ivan M. Mikhaylov
- Federal State Budgetary Institution “Centre for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical Biological Agency, Moscow, Russia
| | - Anna V. Say
- Federal State Budgetary Institution “Centre for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical Biological Agency, Moscow, Russia
| | - Anastasiya I. Zakamornaya
- Federal State Budgetary Institution “Centre for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical Biological Agency, Moscow, Russia
| | - Anastasiya O. Khakhina
- Federal State Budgetary Institution “Centre for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical Biological Agency, Moscow, Russia
| | - Tatiana S. Lisitsa
- Federal State Budgetary Institution “Centre for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical Biological Agency, Moscow, Russia
| | - Andrey A. Ayginin
- Federal State Budgetary Institution “Centre for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical Biological Agency, Moscow, Russia
| | - Ivan S. Abramov
- Federal State Budgetary Institution “Centre for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical Biological Agency, Moscow, Russia
| | - Sergey A. Bogdan
- Chief Federal State Budgetary Healthcare Institution “Centre of Hygiene and Epidemiology” of the Federal Medical Biological Agency, Moscow, Russia
| | - Kseniya B. Kolbutova
- Chief Federal State Budgetary Healthcare Institution “Centre of Hygiene and Epidemiology” of the Federal Medical Biological Agency, Moscow, Russia
| | - Daria U. Oleynikova
- Chief Federal State Budgetary Healthcare Institution “Centre of Hygiene and Epidemiology” of the Federal Medical Biological Agency, Moscow, Russia
| | - Tatiana F. Avdeenko
- Chief Federal State Budgetary Healthcare Institution “Centre of Hygiene and Epidemiology” of the Federal Medical Biological Agency, Moscow, Russia
| | - German A. Shipulin
- Federal State Budgetary Institution “Centre for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical Biological Agency, Moscow, Russia
| | - Sergey M. Yudin
- Federal State Budgetary Institution “Centre for Strategic Planning and Management of Biomedical Health Risks” of the Federal Medical Biological Agency, Moscow, Russia
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11
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Ozhmegova EN, Savochkina TE, Prilipov AG, Tikhomirov E, Larichev VF, Sayfullin MA, Grebennikova TV. [Molecular epidemiological analysis of SARS-CoV-2 genovariants in Moscow and Moscow region]. Vopr Virusol 2023; 67:496-505. [PMID: 37264839 DOI: 10.36233/0507-4088-146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Indexed: 06/03/2023]
Abstract
INTRODUCTION SARS-CoV-2, a severe acute respiratory illness virus that emerged in China in late 2019, continues to spread rapidly around the world, accumulating mutations and thus causing serious concern. Five virus variants of concern are currently known: Alpha (lineage B.1.1.7), Beta (lineage B.1.351), Gamma (lineage P.1), Delta (lineage B.1.617.2), and Omicron (lineage B.1.1.529). In this study, we conducted a molecular epidemiological analysis of the most prevalent genovariants in Moscow and the region. The aim of the study is to estimate the distribution of various variants of SARS-CoV-2 in Moscow city and the Moscow Region. MATERIALS AND METHODS 227 SARS-CoV-2 sequences were used for analysis. Isolation of the SARS-CoV-2 virus was performed on Vero E6 cell culture. Sequencing was performed by the Sanger method. Bioinformatic analysis was carried out using software packages: MAFFT, IQ-TREE v1.6.12, jModelTest 2.1.7, Nextstrain, Auspice v2.34. RESULTS As a result of phylogenetic analysis, we have identified the main variants of the virus circulating in Russia that have been of concern throughout the existence of the pandemic, namely: variant B.1.1.7, which accounted for 30% (9/30), AY.122, which accounted for 16.7% (5/30), BA.1.1 with 20% (6/30) and B.1.1 with 33.3% (10/30). When examining Moscow samples for the presence of mutations in SARS-CoV-2 structural proteins of different genovariants, a significant percentage of the most common substitutions was recorded: S protein D614G (86.7%), P681H/R (63.3%), E protein T9I (20.0%); M protein I82T (30.0%), D3G (20.0%), Q19E (20.0%) and finally N protein R203K/M (90.0%), G204R/P (73.3 %). CONCLUSION The study of the frequency and impact of mutations, as well as the analysis of the predominant variants of the virus are important for the development and improvement of vaccines for the prevention of COVID-19. Therefore, ongoing molecular epidemiological studies are needed, as these data provide important information about changes in the genome of circulating SARS-CoV-2 variants.
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Affiliation(s)
- E N Ozhmegova
- National Research Center for Epidemiology and Microbiology named after honorary academician N.F. Gamaleya, Ministry of Health of the Russian Federation
| | - T E Savochkina
- National Research Center for Epidemiology and Microbiology named after honorary academician N.F. Gamaleya, Ministry of Health of the Russian Federation
| | - A G Prilipov
- National Research Center for Epidemiology and Microbiology named after honorary academician N.F. Gamaleya, Ministry of Health of the Russian Federation
| | - E Tikhomirov
- National Research Center for Epidemiology and Microbiology named after honorary academician N.F. Gamaleya, Ministry of Health of the Russian Federation
| | - V F Larichev
- National Research Center for Epidemiology and Microbiology named after honorary academician N.F. Gamaleya, Ministry of Health of the Russian Federation
| | - M A Sayfullin
- National Research Center for Epidemiology and Microbiology named after honorary academician N.F. Gamaleya, Ministry of Health of the Russian Federation
- Pirogov Russian National Research Medical University
| | - T V Grebennikova
- National Research Center for Epidemiology and Microbiology named after honorary academician N.F. Gamaleya, Ministry of Health of the Russian Federation
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12
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Palyanova N, Sobolev I, Alekseev A, Glushenko A, Kazachkova E, Markhaev A, Kononova Y, Gulyaeva M, Adamenko L, Kurskaya O, Bi Y, Xin Y, Sharshov K, Shestopalov A. Genomic and Epidemiological Features of COVID-19in the Novosibirsk Region during the Beginning of the Pandemic. Viruses 2022; 14:v14092036. [PMID: 36146842 PMCID: PMC9501018 DOI: 10.3390/v14092036] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 09/07/2022] [Accepted: 09/09/2022] [Indexed: 11/16/2022] Open
Abstract
In this retrospective, single-center study, we conducted an analysis of 13,699 samples from different individuals obtained from the Federal Research Center of Fundamental and Translational Medicine, from 1 April to 30 May 2020 in Novosibirsk region (population 2.8 million people). We identified 6.49% positive for SARS-CoV-2 cases out of the total number of diagnostic tests, and 42% of them were from asymptomatic people. We also detected two asymptomatic people, who had no confirmed contact with patients with COVID-19. The highest percentage of positive samples was observed in the 80+ group (16.3%), while among the children and adults it did not exceed 8%. Among all the people tested, 2423 came from a total of 80 different destinations and only 27 of them were positive for SARS-CoV-2. Out of all the positive samples, 15 were taken for SARS-CoV-2 sequencing. According to the analysis of the genome sequences, the SARS-CoV-2 variants isolated in the Novosibirsk region at the beginning of the pandemic belonged to three phylogenetic lineages according to the Pangolin classification: B.1, B.1.1, and B.1.1.129. All Novosibirsk isolates contained the D614G substitution in the Spike protein, two isolates werecharacterized by an additional M153T mutation, and one isolate wascharacterized by the L5F mutation.
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Affiliation(s)
- Natalia Palyanova
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
- Correspondence:
| | - Ivan Sobolev
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
| | - Alexander Alekseev
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
| | - Alexandra Glushenko
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
| | - Evgeniya Kazachkova
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
| | - Alexander Markhaev
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
| | - Yulia Kononova
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
| | - Marina Gulyaeva
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
- Department of Natural Science, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Lubov Adamenko
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
| | - Olga Kurskaya
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
| | - Yuhai Bi
- CAS Key Laboratory of Pathogenic Microbiology and Immunology, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Disease, Institute of Microbiology, Center for Influenza Research and Early-Warning (CASCIRE), Chinese Academy of Sciences (CAS), Beijing 100101, China
| | - Yuhua Xin
- China General Microbiological Culture Collection Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Kirill Sharshov
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
| | - Alexander Shestopalov
- Laboratory of Molecular Epidemiology and Biodiversity of Viruses, Research Institute of Virology, Federal Research Center of Fundamental and Translational Medicine, 630117 Novosibirsk, Russia
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13
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Attwood SW, Hill SC, Aanensen DM, Connor TR, Pybus OG. Phylogenetic and phylodynamic approaches to understanding and combating the early SARS-CoV-2 pandemic. Nat Rev Genet 2022; 23:547-562. [PMID: 35459859 PMCID: PMC9028907 DOI: 10.1038/s41576-022-00483-8] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/23/2022] [Indexed: 01/05/2023]
Abstract
Determining the transmissibility, prevalence and patterns of movement of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is central to our understanding of the impact of the pandemic and to the design of effective control strategies. Phylogenies (evolutionary trees) have provided key insights into the international spread of SARS-CoV-2 and enabled investigation of individual outbreaks and transmission chains in specific settings. Phylodynamic approaches combine evolutionary, demographic and epidemiological concepts and have helped track virus genetic changes, identify emerging variants and inform public health strategy. Here, we review and synthesize studies that illustrate how phylogenetic and phylodynamic techniques were applied during the first year of the pandemic, and summarize their contributions to our understanding of SARS-CoV-2 transmission and control.
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Affiliation(s)
- Stephen W Attwood
- Department of Zoology, University of Oxford, Oxford, UK.
- Pathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK.
| | - Sarah C Hill
- Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, London, UK
| | - David M Aanensen
- Centre for Genomic Pathogen Surveillance, Wellcome Genome Campus, Hinxton, UK
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Thomas R Connor
- Pathogen Genomics Unit, Public Health Wales NHS Trust, Cardiff, UK
- School of Biosciences, Cardiff University, Cardiff, UK
| | - Oliver G Pybus
- Department of Zoology, University of Oxford, Oxford, UK.
- Department of Pathobiology and Population Sciences, Royal Veterinary College, University of London, London, UK.
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14
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Singh AK, Laskar R, Banerjee A, Mondal RK, Gupta B, Deb S, Dutta S, Patra S, Ghosh T, Sarkar S, Ghosh S, Bhattacharya S, Roy D, Chakraborty A, Chowdhury M, Mahaptra S, Paul A, Mazumder A, Chowdhury A, Chatterjee SS, Sarkar A, Ray R, Pal K, Jana A, Barik G, Ganguly S, Chatterjee M, Majhi D, Bandopadhyay B, Das S, Maitra A, Biswas NK. Contrasting Distribution of SARS-CoV-2 Lineages across Multiple Rounds of Pandemic Waves in West Bengal, the Gateway of East and North-East States of India. Microbiol Spectr 2022; 10:e0091422. [PMID: 35852336 PMCID: PMC9430150 DOI: 10.1128/spectrum.00914-22] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 06/29/2022] [Indexed: 11/20/2022] Open
Abstract
The evolution of viral variants and their impact on viral transmission have been an area of considerable importance in this pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We analyzed the viral variants in different phases of the pandemic in West Bengal, a state in India that is important geographically, and compared the variants with other states like Delhi, Maharashtra, and Karnataka, located in other regions of the country. We have identified 57 pango-lineages in 3,198 SARS-CoV-2 genomes, alteration in their distribution, as well as contrasting profiles of amino acid mutational dynamics across different waves in different states. The evolving characteristics of Delta (B.1.617.2) sublineages and alterations in hydrophobicity profiles of the viral proteins caused by these mutations were also studied. Additionally, implications of predictive host miRNA binding/unbinding to emerging spike or nucleocapsid mutations were highlighted. Our results throw considerable light on interesting aspects of the viral genomic variation and provide valuable information for improved understanding of wave-defining mutations in unfolding the pandemic. IMPORTANCE Multiple waves of infection were observed in many states in India during the coronavirus disease 2019 (COVID19) pandemic. Fine-scale evolution of major SARS-CoV-2 lineages and sublineages during four wave-window categories: Pre-Wave 1, Wave 1, Pre-Wave 2, and Wave 2 in four major states of India: Delhi (North), Maharashtra (West), Karnataka (South), and West Bengal (East) was studied using large-scale virus genome sequencing data. Our comprehensive analysis reveals contrasting molecular profiles of the wave-defining mutations and their implications in host miRNA binding/unbinding of the lineages in the major states of India.
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Affiliation(s)
- Animesh K. Singh
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | | | - Anindita Banerjee
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | | | - Bishal Gupta
- School of Tropical Medicine, Kolkata, West Bengal, India
| | - Sonia Deb
- School of Tropical Medicine, Kolkata, West Bengal, India
| | - Shreelekha Dutta
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Subrata Patra
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Trinath Ghosh
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Sumanta Sarkar
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Shekhar Ghosh
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | | | - Debojyoti Roy
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | | | - Meghna Chowdhury
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Surajit Mahaptra
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Antara Paul
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Anup Mazumder
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | | | | | | | - Raja Ray
- Institute of Post-Graduate Medical Education and Research, Kolkata, West Bengal, India
| | - Kuhu Pal
- College of Medicine and JNM Hospital, Kalyani, West Bengal, India
| | - Angshuman Jana
- Bankura Sammilani Medical College, Bankura, West Bengal, India
| | - Goutam Barik
- Medical College and Hospital, Kolkata, West Bengal, India
| | - Swagata Ganguly
- Nil Ratan Sircar Medical College and Hospital, Kolkata, West Bengal, India
| | | | - Dipankar Majhi
- Department of Health and Family Welfare, Government of West Bengal, Kolkata, West Bengal, India
| | | | - Saumitra Das
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Arindam Maitra
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
| | - Nidhan K. Biswas
- National Institute of Biomedical Genomics, Kalyani, West Bengal, India
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15
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Sominina A, Danilenko D, Komissarov A, Karpova L, Pisareva M, Fadeev A, Konovalova N, Eropkin M, Stolyarov K, Shtro A, Burtseva E, Lioznov D. Resurgence of Influenza Circulation in the Russian Federation during the Delta and Omicron COVID-19 Era. Viruses 2022; 14:1909. [PMID: 36146716 PMCID: PMC9506591 DOI: 10.3390/v14091909] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 08/24/2022] [Accepted: 08/26/2022] [Indexed: 11/25/2022] Open
Abstract
Influenza circulation was substantially reduced after March 2020 in the European region and globally due to the wide introduction of non-pharmaceutical interventions (NPIs) against COVID-19. The virus, however, has been actively circulating in natural reservoirs. In summer 2021, NPIs were loosened in Russia, and influenza activity resumed shortly thereafter. Here, we summarize the epidemiological and virological data on the influenza epidemic in Russia in 2021-2022 obtained by the two National Influenza Centers. We demonstrate that the commonly used baseline for acute respiratory infection (ARI) is no longer sufficiently sensitive and BL for ILI incidence was more specific for early recognition of the epidemic. We also present the results of PCR detection of influenza, SARS-CoV-2 and other respiratory viruses as well as antigenic and genetic analysis of influenza viruses. Influenza A(H3N2) prevailed this season with influenza B being detected at low levels at the end of the epidemic. The majority of A(H3N2) viruses were antigenically and genetically homogenous and belonged to the clade 3C.2a1b.2a.2 of the vaccine strain A/Darwin/9/2021 for the season 2022-2023. All influenza B viruses belonged to the Victoria lineage and were similar to the influenza B/Austria/1359417/2021 virus. No influenza A(H1N1)pdm09 and influenza B/Yamagata lineage was isolated last season.
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Affiliation(s)
- Anna Sominina
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
| | - Daria Danilenko
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
| | - Andrey Komissarov
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
| | - Ludmila Karpova
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
| | - Maria Pisareva
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
| | - Artem Fadeev
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
| | - Nadezhda Konovalova
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
| | - Mikhail Eropkin
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
| | - Kirill Stolyarov
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
| | - Anna Shtro
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
| | - Elena Burtseva
- National Research Center for Epidemiology and Microbiology Named after N.F. Gamaleya, 123098 Moscow, Russia
| | - Dmitry Lioznov
- Smorodintsev Research Institute of Influenza, 197376 Saint Petersburg, Russia
- Department of Infectious Diseases and Epidemiology, First Pavlov State Medical University, 197022 Saint Petersburg, Russia
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16
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Kotov I, Saenko V, Borisova N, Kolesnikov A, Kondrasheva L, Tivanova E, Khafizov K, Akimkin V. Effective Approaches to Study the Genetic Variability of SARS-CoV-2. Viruses 2022; 14:v14091855. [PMID: 36146662 PMCID: PMC9504788 DOI: 10.3390/v14091855] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 08/18/2022] [Accepted: 08/19/2022] [Indexed: 11/16/2022] Open
Abstract
Significant efforts are being made in many countries around the world to respond to the COVID-19 pandemic by developing diagnostic reagent kits, identifying infected people, determining treatment methods, and finally producing effective vaccines. However, novel coronavirus variants may potentially reduce the effectiveness of all these efforts, demonstrating increased transmissibility and abated response to therapy or vaccines, as well as the possibility of false negative results in diagnostic procedures based on nucleic acid amplification methods. Since the end of 2020, several variants of concern have been discovered around the world. When information about a new, potentially more dangerous strain of pathogen appears, it is crucial to determine the moment of its emergence in a region. Eventually, that permits taking timely measures and minimizing new risks associated with the spreading of the virus. Therefore, numerous nations have made tremendous efforts to identify and trace these virus variants, which necessitates serious technological processes to sequence a large number of viral genomes. Here, we report on our experience as one of the primary laboratories involved in monitoring SARS-CoV-2 variants in Russia. We discuss the various approaches used, describe effective protocols, and outline a potential technique combining several methods to increase the ability to trace genetic variants while minimizing financial and labor costs.
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Affiliation(s)
- Ivan Kotov
- FSBI Central Research Institute for Epidemiology of the Federal Service for Surveillance of Consumer Rights Protection and Human Wellbeing, 111123 Moscow, Russia
- Moscow Institute of Physics and Technology, National Research University, 115184 Dolgoprudny, Russia
| | - Valeriia Saenko
- FSBI Central Research Institute for Epidemiology of the Federal Service for Surveillance of Consumer Rights Protection and Human Wellbeing, 111123 Moscow, Russia
| | - Nadezhda Borisova
- FSBI Central Research Institute for Epidemiology of the Federal Service for Surveillance of Consumer Rights Protection and Human Wellbeing, 111123 Moscow, Russia
| | - Anton Kolesnikov
- FSBI Central Research Institute for Epidemiology of the Federal Service for Surveillance of Consumer Rights Protection and Human Wellbeing, 111123 Moscow, Russia
| | - Larisa Kondrasheva
- FSBI Central Research Institute for Epidemiology of the Federal Service for Surveillance of Consumer Rights Protection and Human Wellbeing, 111123 Moscow, Russia
| | - Elena Tivanova
- FSBI Central Research Institute for Epidemiology of the Federal Service for Surveillance of Consumer Rights Protection and Human Wellbeing, 111123 Moscow, Russia
| | - Kamil Khafizov
- FSBI Central Research Institute for Epidemiology of the Federal Service for Surveillance of Consumer Rights Protection and Human Wellbeing, 111123 Moscow, Russia
- Correspondence:
| | - Vasily Akimkin
- FSBI Central Research Institute for Epidemiology of the Federal Service for Surveillance of Consumer Rights Protection and Human Wellbeing, 111123 Moscow, Russia
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17
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Shchur V, Spirin V, Sirotkin D, Burovski E, De Maio N, Corbett-Detig R. VGsim: Scalable viral genealogy simulator for global pandemic. PLoS Comput Biol 2022; 18:e1010409. [PMID: 36001646 PMCID: PMC9447924 DOI: 10.1371/journal.pcbi.1010409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 09/06/2022] [Accepted: 07/18/2022] [Indexed: 11/24/2022] Open
Abstract
Accurate simulation of complex biological processes is an essential component of developing and validating new technologies and inference approaches. As an effort to help contain the COVID-19 pandemic, large numbers of SARS-CoV-2 genomes have been sequenced from most regions in the world. More than 5.5 million viral sequences are publicly available as of November 2021. Many studies estimate viral genealogies from these sequences, as these can provide valuable information about the spread of the pandemic across time and space. Additionally such data are a rich source of information about molecular evolutionary processes including natural selection, for example allowing the identification of new variants with transmissibility and immunity evasion advantages. To our knowledge, there is no framework that is both efficient and flexible enough to simulate the pandemic to approximate world-scale scenarios and generate viral genealogies of millions of samples. Here, we introduce a new fast simulator VGsim which addresses the problem of simulation genealogies under epidemiological models. The simulation process is split into two phases. During the forward run the algorithm generates a chain of population-level events reflecting the dynamics of the pandemic using an hierarchical version of the Gillespie algorithm. During the backward run a coalescent-like approach generates a tree genealogy of samples conditioning on the population-level events chain generated during the forward run. Our software can model complex population structure, epistasis and immunity escape. We develop a fast and flexible simulation software package VGsim for modeling epidemiological processes and generating genealogies of large pathogen samples. The software takes into account host population structure, pathogen evolution, host immunity and some other epidemiological aspects. The computational efficiency of the package allows to simulate genealogies of tens of millions of samples, which is important, e.g., for SARS-CoV-2 genome studies.
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Affiliation(s)
- Vladimir Shchur
- International laboratory of statistical and computational genomics, HSE University, Moscow, Russia
- * E-mail:
| | - Vadim Spirin
- International laboratory of statistical and computational genomics, HSE University, Moscow, Russia
| | - Dmitry Sirotkin
- International laboratory of statistical and computational genomics, HSE University, Moscow, Russia
| | | | - Nicola De Maio
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering and Genomics Institute, UC Santa Cruz, California, United States of America
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18
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Ye C, Thornlow B, Hinrichs A, Kramer A, Mirchandani C, Torvi D, Lanfear R, Corbett-Detig R, Turakhia Y. matOptimize: a parallel tree optimization method enables online phylogenetics for SARS-CoV-2. Bioinformatics 2022; 38:3734-3740. [PMID: 35731204 PMCID: PMC9344837 DOI: 10.1093/bioinformatics/btac401] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 05/21/2022] [Accepted: 06/16/2022] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Phylogenetic tree optimization is necessary for precise analysis of evolutionary and transmission dynamics, but existing tools are inadequate for handling the scale and pace of data produced during the coronavirus disease 2019 (COVID-19) pandemic. One transformative approach, online phylogenetics, aims to incrementally add samples to an ever-growing phylogeny, but there are no previously existing approaches that can efficiently optimize this vast phylogeny under the time constraints of the pandemic. RESULTS Here, we present matOptimize, a fast and memory-efficient phylogenetic tree optimization tool based on parsimony that can be parallelized across multiple CPU threads and nodes, and provides orders of magnitude improvement in runtime and peak memory usage compared to existing state-of-the-art methods. We have developed this method particularly to address the pressing need during the COVID-19 pandemic for daily maintenance and optimization of a comprehensive SARS-CoV-2 phylogeny. matOptimize is currently helping refine on a daily basis possibly the largest-ever phylogenetic tree, containing millions of SARS-CoV-2 sequences. AVAILABILITY AND IMPLEMENTATION The matOptimize code is freely available as part of the UShER package (https://github.com/yatisht/usher) and can also be installed via bioconda (https://bioconda.github.io/recipes/usher/README.html). All scripts we used to perform the experiments in this manuscript are available at https://github.com/yceh/matOptimize-experiments. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Cheng Ye
- Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA 92093, USA
| | - Bryan Thornlow
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Angie Hinrichs
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Alexander Kramer
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Cade Mirchandani
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Devika Torvi
- Department of Bioengineering, University of California, San Diego, San Diego, CA 92093, USA
| | - Robert Lanfear
- Department of Ecology and Evolution, Research School of Biology, Australian National University, Canberra, ACT 2601, Australia
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA 95064, USA
| | - Yatish Turakhia
- Department of Electrical and Computer Engineering, University of California, San Diego, San Diego, CA 92093, USA
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19
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Klink GV, Safina KR, Garushyants SK, Moldovan M, Nabieva E, Komissarov AB, Lioznov D, Bazykin GA. Spread of endemic SARS-CoV-2 lineages in Russia before April 2021. PLoS One 2022; 17:e0270717. [PMID: 35857745 PMCID: PMC9299347 DOI: 10.1371/journal.pone.0270717] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 06/15/2022] [Indexed: 12/23/2022] Open
Abstract
In 2021, the COVID-19 pandemic was characterized by global spread of several lineages with evidence for increased transmissibility. Throughout the pandemic, Russia has remained among the countries with the highest number of confirmed COVID-19 cases, making it a potential hotspot for emergence of novel variants. Here, we show that among the globally significant variants of concern that have spread globally by late 2020, alpha (B.1.1.7), beta (B.1.351) or gamma (P.1), none have been sampled in Russia before the end of 2020. Instead, between summer 2020 and spring 2021, the epidemic in Russia has been characterized by the spread of two lineages that were rare in most other countries: B.1.1.317 and a sublineage of B.1.1 including B.1.1.397 (hereafter, B.1.1.397+). Their frequency has increased concordantly in different parts of Russia. On top of these lineages, in late December 2020, alpha (B.1.1.7) emerged in Russia, reaching a frequency of 17.4% (95% C.I.: 12.0%-24.4%) in March 2021. Additionally, we identify three novel distinct lineages, AT.1, B.1.1.524 and B.1.1.525, that have started to spread, together reaching the frequency of 11.8% (95% C.I.: 7.5%-18.1%) in March 2021. These lineages carry combinations of several notable mutations, including the S:E484K mutation of concern, deletions at a recurrent deletion region of the spike glycoprotein (S:Δ140-142, S:Δ144 or S:Δ136-144), and nsp6:Δ106-108 (also known as ORF1a:Δ3675-3677). Community-based PCR testing indicates that these variants have continued to spread in April 2021, with the frequency of B.1.1.7 reaching 21.7% (95% C.I.: 12.3%-35.6%), and the joint frequency of B.1.1.524 and B.1.1.525, 15.2% (95% C.I.: 7.6%-28.2%). Although these variants have been displaced by the onset of delta variant in May-June 2021, lineages B.1.1.317, B.1.1.397+, AT.1, B.1.1.524 and B.1.1.525 and the combinations of mutations comprising them that are found in other lineages merit monitoring.
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Affiliation(s)
- Galya V. Klink
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia
| | - Ksenia R. Safina
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
| | - Sofya K. Garushyants
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia
| | - Mikhail Moldovan
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
| | - Elena Nabieva
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
| | | | - Dmitry Lioznov
- Smorodintsev Research Institute of Influenza, Saint Petersburg, Russia
- First Pavlov State Medical University, Saint Petersburg, Russia
| | - Georgii A. Bazykin
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
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20
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Astakhova EA, Byazrova MG, Yusubalieva GM, Kulemzin SV, Kruglova NA, Prilipov AG, Baklaushev VP, Gorchakov AA, Taranin AV, Filatov AV. Functional Profiling of In Vitro Reactivated Memory B Cells Following Natural SARS-CoV-2 Infection and Gam-COVID-Vac Vaccination. Cells 2022; 11:1991. [PMID: 35805076 PMCID: PMC9265778 DOI: 10.3390/cells11131991] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 06/17/2022] [Accepted: 06/20/2022] [Indexed: 02/01/2023] Open
Abstract
Both SARS-CoV-2 infection and vaccination have previously been demonstrated to elicit robust, yet somewhat limited immunity against the evolving variants of SARS-CoV-2. Nevertheless, reports performing side-by-side comparison of immune responses following infection vs. vaccination have been relatively scarce. The aim of this study was to compare B-cell response to adenovirus-vectored vaccination in SARS-CoV-2-naive individuals with that observed in the COVID-19 convalescent patients six months after the first encounter with the viral antigens. We set out to use a single analytical platform and performed comprehensive analysis of serum levels of receptor binding domain (RBD)-specific and virus-neutralizing antibodies, frequencies of RBD-binding circulating memory B cells (MBCs), MBC-derived antibody-secreting cells, as well as RBD-specific and virus-neutralizing activity of MBC-derived antibodies after Gam-COVID-Vac (Sputnik V) vaccination and/or natural SARS-CoV-2 infection. Overall, natural immunity was superior to Gam-COVID-Vac vaccination. The levels of neutralizing MBC-derived antibodies in the convalescent patients turned out to be significantly higher than those found following vaccination. Our results suggest that after six months, SARS-CoV-2-specific MBC immunity is more robust in COVID-19 convalescent patients than in Gam-COVID-Vac recipients. Collectively, our data unambiguously indicate that natural immunity outperforms Gam-COVID-Vac-induced immunity six months following recovery/vaccination, which should inform healthcare and vaccination decisions.
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Affiliation(s)
- Ekaterina A. Astakhova
- Laboratory of Immunochemistry, National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, 115522 Moscow, Russia; (E.A.A.); (M.G.B.); (A.G.P.)
- Department of Immunology, Faculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia
| | - Maria G. Byazrova
- Laboratory of Immunochemistry, National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, 115522 Moscow, Russia; (E.A.A.); (M.G.B.); (A.G.P.)
- Department of Immunology, Faculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia
- Department of Immunology, Institute of Medicine, Peoples’ Friendship University of Russia (RUDN University), 117198 Moscow, Russia
| | - Gaukhar M. Yusubalieva
- Laboratory of Cell Technology, Federal Research and Clinical Center for Specialized Types of Medical Care and Medical Technologies of the FMBA of Russia, 115682 Moscow, Russia; (G.M.Y.); (V.P.B.)
| | - Sergey V. Kulemzin
- Laboratory of Immunogenetics, Institute of Molecular and Cellular Biology, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia; (S.V.K.); (A.A.G.); (A.V.T.)
| | - Natalia A. Kruglova
- Laboratory of Gene Therapy of Socially Significant Diseases, Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Institute of Gene Biology of the Russian Academy of Sciences, 119334 Moscow, Russia;
| | - Alexey G. Prilipov
- Laboratory of Immunochemistry, National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, 115522 Moscow, Russia; (E.A.A.); (M.G.B.); (A.G.P.)
- Laboratory of Molecular Genetics, N.F. Gamaleya National Research Center for Epidemiology and Microbiology, Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | - Vladimir P. Baklaushev
- Laboratory of Cell Technology, Federal Research and Clinical Center for Specialized Types of Medical Care and Medical Technologies of the FMBA of Russia, 115682 Moscow, Russia; (G.M.Y.); (V.P.B.)
| | - Andrey A. Gorchakov
- Laboratory of Immunogenetics, Institute of Molecular and Cellular Biology, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia; (S.V.K.); (A.A.G.); (A.V.T.)
| | - Alexander V. Taranin
- Laboratory of Immunogenetics, Institute of Molecular and Cellular Biology, Siberian Branch of the Russian Academy of Sciences, 630090 Novosibirsk, Russia; (S.V.K.); (A.A.G.); (A.V.T.)
| | - Alexander V. Filatov
- Laboratory of Immunochemistry, National Research Center Institute of Immunology, Federal Medical Biological Agency of Russia, 115522 Moscow, Russia; (E.A.A.); (M.G.B.); (A.G.P.)
- Department of Immunology, Faculty of Biology, Lomonosov Moscow State University, 119234 Moscow, Russia
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21
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COVID-19 pandemic in Saint Petersburg, Russia: Combining population-based serological study and surveillance data. PLoS One 2022; 17:e0266945. [PMID: 35704649 PMCID: PMC9200332 DOI: 10.1371/journal.pone.0266945] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 03/30/2022] [Indexed: 12/14/2022] Open
Abstract
Background The COVID-19 pandemic in Russia has already resulted in 500,000 excess deaths, with more than 5.6 million cases registered officially by July 2021. Surveillance based on case reporting has become the core pandemic monitoring method in the country and globally. However, population-based seroprevalence studies may provide an unbiased estimate of the actual disease spread and, in combination with multiple surveillance tools, help to define the pandemic course. This study summarises results from four consecutive serological surveys conducted between May 2020 and April 2021 at St. Petersburg, Russia and combines them with other SARS-CoV-2 surveillance data. Methods We conducted four serological surveys of two random samples (May–June, July–August, October–December 2020, and February–April 2021) from adults residing in St. Petersburg recruited with the random digit dialing (RDD), accompanied by a telephone interview to collect information on both individuals who accepted and declined the invitation for testing and account for non-response. We have used enzyme-linked immunosorbent assay CoronaPass total antibodies test (Genetico, Moscow, Russia) to report seroprevalence. We corrected the estimates for non-response using the bivariate probit model and also accounted the test performance characteristics, obtained from independent assay evaluation. In addition, we have summarised the official registered cases statistics, the number of hospitalised patients, the number of COVID-19 deaths, excess deaths, tests performed, data from the ongoing SARS-CoV-2 variants of concern (VOC) surveillance, the vaccination uptake, and St. Petersburg search and mobility trends. The infection fatality ratios (IFR) have been calculated using the Bayesian evidence synthesis model. Findings After calling 113,017 random mobile phones we have reached 14,118 individuals who responded to computer-assisted telephone interviewing (CATI) and 2,413 provided blood samples at least once through the seroprevalence study. The adjusted seroprevalence in May–June, 2020 was 9.7% (95%: 7.7–11.7), 13.3% (95% 9.9–16.6) in July–August, 2020, 22.9% (95%: 20.3–25.5) in October–December, 2021 and 43.9% (95%: 39.7–48.0) in February–April, 2021. History of any symptoms, history of COVID-19 tests, and non-smoking status were significant predictors for higher seroprevalence. Most individuals remained seropositive with a maximum 10 months follow-up. 92.7% (95% CI 87.9–95.7) of participants who have reported at least one vaccine dose were seropositive. Hospitalisation and COVID-19 death statistics and search terms trends reflected the pandemic course better than the official case count, especially during the spring 2020. SARS-CoV-2 circulation showed rather low genetic SARS-CoV-2 lineages diversity that increased in the spring 2021. Local VOC (AT.1) was spreading till April 2021, but B.1.617.2 substituted all other lineages by June 2021. The IFR based on the excess deaths was equal to 1.04 (95% CI 0.80–1.31) for the adult population and 0.86% (95% CI 0.66–1.08) for the entire population. Conclusion Approximately one year after the COVID-19 pandemic about 45% of St. Petersburg, Russia residents contracted the SARS-CoV-2 infection. Combined with vaccination uptake of about 10% it was enough to slow the pandemic at the present level of all mitigation measures until the Delta VOC started to spread. Combination of several surveillance tools provides a comprehensive pandemic picture.
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22
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Cao X, Hao G, Li YY, Wang M, Wang JX. On male urination and related environmental disease transmission in restrooms: From the perspectives of fluid dynamics. SUSTAINABLE CITIES AND SOCIETY 2022; 80:103753. [PMID: 35136716 PMCID: PMC8812150 DOI: 10.1016/j.scs.2022.103753] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 01/13/2022] [Accepted: 02/02/2022] [Indexed: 05/02/2023]
Abstract
Indoor transmission of COVID-19 is highly probable. Multiple sources have verified that the SARS-CoV-2 can be detected within toilets, and people can be infected in restrooms. There is a huge gap in the coronavirus transmission mechanism in restrooms. Understanding it can help to flatten the curve of the infected cases as well as prevent other viruses transmitted through the sewage or human body fluid. Previous studies have shown how simple actions in daily life (coughing, sneezing, or toilet flushing) contribute to virus transmission. This paper visually and quantitatively demonstrates that male urination, which is also a daily action, can agitate virus particles within the toilet and raise them, which may be the main promoter of cross-infection of COVID-19 in restrooms. Adopting numerical and experimental methods, we demonstrate that male urination can cause strong turbulent flow with an averaged urine impinging velocity of 2.3 m/s, which can act as an agitator to raise the virus particles. The climbing velocity of the airflow can be 0.75-1.05 m/s. The observed upwards flow will disturb and spread any lurking virus particles (not limited to SARS-CoV-2). Experiments demonstrated that the concentration of the airborne particle could be tripled during male urination. Corresponding precautions are offered as well to prepare the public to act properly when and after using facilities in restrooms for preventing emerging and re-emerging pandemics not limited to the current COVID-19, contributing to the sustainability of human society.
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Affiliation(s)
- Xiang Cao
- College of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou 225009, China
- School of Energy and Environment, Southeast University, Nanjing 210096, China
| | - Guanqiu Hao
- School of Energy and Environment, Southeast University, Nanjing 210096, China
| | - Yun-Yun Li
- School of Energy and Environment, Southeast University, Nanjing 210096, China
| | - Mengxiao Wang
- Department of Traditional Chinese Medicine, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Ji-Xiang Wang
- College of Electrical, Energy and Power Engineering, Yangzhou University, Yangzhou 225009, China
- Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology, Kowloon Hong Kong, China
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23
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Gladkikh A, Dedkov V, Sharova A, Klyuchnikova E, Sbarzaglia V, Kanaeva O, Arbuzova T, Tsyganova N, Popova A, Ramsay E, Totolian A. Epidemiological Features of COVID-19 in Northwest Russia in 2021. Viruses 2022; 14:v14050931. [PMID: 35632673 PMCID: PMC9147892 DOI: 10.3390/v14050931] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 04/27/2022] [Accepted: 04/27/2022] [Indexed: 01/30/2023] Open
Abstract
Appearing in Wuhan (China) and quickly spreading across the globe, the novel coronavirus infection quickly became a significant threat to global health. The year 2021 was characterized by both increases and decreases in COVID-19 incidence, and Russia was no exception. In this work, we describe regional features in the Northwestern federal district (FD) of Russia of the pandemic in 2021 based on Rospotrebnadzor statistics and data from SARS-CoV-2 genetic monitoring provided by the Saint Petersburg Pasteur Institute as a part of epidemiological surveillance. The epidemiological situation in the studied region was complicated by the presence of the megacity Saint Petersburg, featuring a high population density and its status as an international transport hub. COVID-19 incidence in the Northwestern FD fluctuated throughout the year, with two characteristic maxima in January and November. An analysis of fluctuations in the age structure, severity of morbidity, mortality rates, and the level of population vaccination in the region during the year is given. Assessment of epidemiological indicators was carried out in relation to changes in locally circulating genetic variants. It was seen that, during 2021, so-called variants of concern (VOC) circulated in the region (Alpha, Beta, Delta, Omicron), with Delta variant strains dominating from June to December. They successively replaced the variants of lines 20A and 20B circulating at the beginning of the year. An epidemiological feature of the northwestern region is the AT.1 variant, which was identified for the first time and later spread throughout the region and beyond its borders. Its share of the regional viral population reached 28.2% in May, and sporadic cases were observed until September. It has been shown that genetic variants of AT.1 lineages distributed in Russia and Northern Europe represent a single phylogenetic group at the base of the 20B branch on the global phylogenetic tree of SARS-CoV-2 strains. The progression of the COVID-19 pandemic occurred against the background of a vaccination campaign. The findings highlight the impact of vaccination on lowering severe COVID-19 case numbers and the mortality rate, despite ongoing changes in circulating SARS-CoV-2 genetic variants.
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Affiliation(s)
- Anna Gladkikh
- Saint Petersburg Pasteur Institute, 14 Ulitsa Mira, 197101 Saint Petersburg, Russia; (A.G.); (A.S.); (E.K.); (V.S.); (O.K.); (T.A.); (N.T.); (E.R.); (A.T.)
| | - Vladimir Dedkov
- Saint Petersburg Pasteur Institute, 14 Ulitsa Mira, 197101 Saint Petersburg, Russia; (A.G.); (A.S.); (E.K.); (V.S.); (O.K.); (T.A.); (N.T.); (E.R.); (A.T.)
- Martsinovsky Institute of Medical Parasitology, Tropical and Vector Borne Diseases, Sechenov First Moscow State Medical University, 119435 Moscow, Russia
- Correspondence: ; Tel.: +7-812-233-2149; Fax: +7-812-232-9217
| | - Alena Sharova
- Saint Petersburg Pasteur Institute, 14 Ulitsa Mira, 197101 Saint Petersburg, Russia; (A.G.); (A.S.); (E.K.); (V.S.); (O.K.); (T.A.); (N.T.); (E.R.); (A.T.)
| | - Ekaterina Klyuchnikova
- Saint Petersburg Pasteur Institute, 14 Ulitsa Mira, 197101 Saint Petersburg, Russia; (A.G.); (A.S.); (E.K.); (V.S.); (O.K.); (T.A.); (N.T.); (E.R.); (A.T.)
| | - Valeriya Sbarzaglia
- Saint Petersburg Pasteur Institute, 14 Ulitsa Mira, 197101 Saint Petersburg, Russia; (A.G.); (A.S.); (E.K.); (V.S.); (O.K.); (T.A.); (N.T.); (E.R.); (A.T.)
| | - Olga Kanaeva
- Saint Petersburg Pasteur Institute, 14 Ulitsa Mira, 197101 Saint Petersburg, Russia; (A.G.); (A.S.); (E.K.); (V.S.); (O.K.); (T.A.); (N.T.); (E.R.); (A.T.)
| | - Tatyana Arbuzova
- Saint Petersburg Pasteur Institute, 14 Ulitsa Mira, 197101 Saint Petersburg, Russia; (A.G.); (A.S.); (E.K.); (V.S.); (O.K.); (T.A.); (N.T.); (E.R.); (A.T.)
| | - Nadezhda Tsyganova
- Saint Petersburg Pasteur Institute, 14 Ulitsa Mira, 197101 Saint Petersburg, Russia; (A.G.); (A.S.); (E.K.); (V.S.); (O.K.); (T.A.); (N.T.); (E.R.); (A.T.)
| | - Anna Popova
- Federal Service on Consumer Protection and Human Well-Being Surveillance, 127994, Moscow, Russia;
| | - Edward Ramsay
- Saint Petersburg Pasteur Institute, 14 Ulitsa Mira, 197101 Saint Petersburg, Russia; (A.G.); (A.S.); (E.K.); (V.S.); (O.K.); (T.A.); (N.T.); (E.R.); (A.T.)
| | - Areg Totolian
- Saint Petersburg Pasteur Institute, 14 Ulitsa Mira, 197101 Saint Petersburg, Russia; (A.G.); (A.S.); (E.K.); (V.S.); (O.K.); (T.A.); (N.T.); (E.R.); (A.T.)
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24
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Raghwani J, du Plessis L, McCrone JT, Hill SC, Parag KV, Thézé J, Kumar D, Puvar A, Pandit R, Pybus OG, Fournié G, Joshi M, Joshi C. Genomic Epidemiology of Early SARS-CoV-2 Transmission Dynamics, Gujarat, India. Emerg Infect Dis 2022; 28:751-758. [PMID: 35203112 PMCID: PMC8962880 DOI: 10.3201/eid2804.212053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Limited genomic sampling in many high-incidence countries has impeded studies of severe respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic epidemiology. Consequently, critical questions remain about the generation and global distribution of virus genetic diversity. We investigated SARS-CoV-2 transmission dynamics in Gujarat, India, during the state's first epidemic wave to shed light on spread of the virus in one of the regions hardest hit by the pandemic. By integrating case data and 434 whole-genome sequences sampled across 20 districts, we reconstructed the epidemic dynamics and spatial spread of SARS-CoV-2 in Gujarat. Our findings indicate global and regional connectivity and population density were major drivers of the Gujarat outbreak. We detected >100 virus lineage introductions, most of which appear to be associated with international travel. Within Gujarat, virus dissemination occurred predominantly from densely populated regions to geographically proximate locations that had low population density, suggesting that urban centers contributed disproportionately to virus spread.
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25
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Klink GV, Safina KR, Nabieva E, Shvyrev N, Garushyants S, Alekseeva E, Komissarov AB, Danilenko DM, Pochtovyi AA, Divisenko EV, Vasilchenko LA, Shidlovskaya EV, Kuznetsova NA, Speranskaya AS, Samoilov AE, Neverov AD, Popova AV, Fedonin GG, Akimkin VG, Lioznov D, Gushchin VA, Shchur V, Bazykin GA. The rise and spread of the SARS-CoV-2 AY.122 lineage in Russia. Virus Evol 2022; 8:veac017. [PMID: 35371558 PMCID: PMC8966696 DOI: 10.1093/ve/veac017] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 02/15/2022] [Accepted: 03/04/2022] [Indexed: 11/14/2022] Open
Abstract
Delta has outcompeted most preexisting variants of SARS-CoV-2, becoming the globally predominant lineage by mid-2021. Its subsequent evolution has led to the emergence of multiple sublineages, most of which are well-mixed between countries. By contrast, here we show that nearly the entire Delta epidemic in Russia has probably descended from a single import event, or from multiple closely timed imports from a single poorly sampled geographic location. Indeed, over 90 per cent of Delta samples in Russia are characterized by the nsp2:K81N + ORF7a:P45L pair of mutations which is rare outside Russia, putting them in the AY.122 sublineage. The AY.122 lineage was frequent in Russia among Delta samples from the start, and has not increased in frequency in other countries where it has been observed, suggesting that its high prevalence in Russia has probably resulted from a random founder effect rather than a transmission advantage. The apartness of the genetic composition of the Delta epidemic in Russia makes Russia somewhat unusual, although not exceptional, among other countries.
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Affiliation(s)
- Galya V Klink
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Bol’shoi Karetnyi per., 19, Moscow 127051, Russia
| | - Ksenia R Safina
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Bol’shoi Karetnyi per., 19, Moscow 127051, Russia
- Skolkovo Institute of Science and Technology (Skoltech), Nobel st., Building 1, Moscow 121205, Russia
| | - Elena Nabieva
- Skolkovo Institute of Science and Technology (Skoltech), Nobel st., Building 1, Moscow 121205, Russia
| | - Nikita Shvyrev
- International Laboratory of Statistical and Computational Genomics, HSE University, Moscow, Russia
| | - Sofya Garushyants
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Bol’shoi Karetnyi per., 19, Moscow 127051, Russia
| | - Evgeniia Alekseeva
- Skolkovo Institute of Science and Technology (Skoltech), Nobel st., Building 1, Moscow 121205, Russia
| | - Andrey B Komissarov
- Smorodintsev Research Institute of Influenza, Prof. Popov 15/17, Saint Petersburg 197376, Russia
| | - Daria M Danilenko
- Smorodintsev Research Institute of Influenza, Prof. Popov 15/17, Saint Petersburg 197376, Russia
| | - Andrei A Pochtovyi
- Federal State Budget Institution ‘National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya’ of the Ministry of Health of the Russian Federation, Gamaleya st., 18, Moscow 123098, Russia
- Department of Virology, Biological Faculty, Lomonosov Moscow State University, Kolmogorov st., 1, building 73, Moscow 119192, Russia
| | - Elizaveta V Divisenko
- Federal State Budget Institution ‘National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya’ of the Ministry of Health of the Russian Federation, Gamaleya st., 18, Moscow 123098, Russia
| | - Lyudmila A Vasilchenko
- Federal State Budget Institution ‘National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya’ of the Ministry of Health of the Russian Federation, Gamaleya st., 18, Moscow 123098, Russia
| | - Elena V Shidlovskaya
- Federal State Budget Institution ‘National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya’ of the Ministry of Health of the Russian Federation, Gamaleya st., 18, Moscow 123098, Russia
| | - Nadezhda A Kuznetsova
- Federal State Budget Institution ‘National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya’ of the Ministry of Health of the Russian Federation, Gamaleya st., 18, Moscow 123098, Russia
| | | | - Anna S Speranskaya
- Central Research Institute for Epidemiology, Novogireyevskaya st., 3a, Moscow 111123, Russia
| | - Andrei E Samoilov
- Central Research Institute for Epidemiology, Novogireyevskaya st., 3a, Moscow 111123, Russia
- Saint Petersburg Pasteur Institute, Mira st., 14, Saint Petersburg 197101, Russia
| | - Alexey D Neverov
- Central Research Institute for Epidemiology, Novogireyevskaya st., 3a, Moscow 111123, Russia
| | - Anfisa V Popova
- Central Research Institute for Epidemiology, Novogireyevskaya st., 3a, Moscow 111123, Russia
| | - Gennady G Fedonin
- Central Research Institute for Epidemiology, Novogireyevskaya st., 3a, Moscow 111123, Russia
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Bol’shoi Karetnyi per., 19, Moscow 127051, Russia
- Moscow Institute of Physics and Technology, Institutskiy per., 9, Dolgoprudny, Moscow region 141701, Russia
| | | | - Vasiliy G Akimkin
- Central Research Institute for Epidemiology, Novogireyevskaya st., 3a, Moscow 111123, Russia
| | - Dmitry Lioznov
- Smorodintsev Research Institute of Influenza, Prof. Popov 15/17, Saint Petersburg 197376, Russia
- First Pavlov State Medical University, L’va Tolstogo st., 6-8, Saint Petersburg 197022, Russia
| | - Vladimir A Gushchin
- Federal State Budget Institution ‘National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya’ of the Ministry of Health of the Russian Federation, Gamaleya st., 18, Moscow 123098, Russia
- Department of Virology, Biological Faculty, Lomonosov Moscow State University, Kolmogorov st., 1, building 73, Moscow 119192, Russia
| | - Vladimir Shchur
- International Laboratory of Statistical and Computational Genomics, HSE University, Moscow, Russia
| | - Georgii A Bazykin
- Skolkovo Institute of Science and Technology (Skoltech), Nobel st., Building 1, Moscow 121205, Russia
- Institute for Information Transmission Problems (Kharkevich Institute), Russian Academy of Sciences, Bol’shoi Karetnyi per., 19, Moscow 127051, Russia
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26
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Lobinska G, Pauzner A, Traulsen A, Pilpel Y, Nowak MA. Evolution of resistance to COVID-19 vaccination with dynamic social distancing. Nat Hum Behav 2022; 6:193-206. [PMID: 35210582 DOI: 10.1038/s41562-021-01281-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 12/14/2021] [Indexed: 01/05/2023]
Abstract
The greatest hope for a return to normalcy following the COVID-19 pandemic is worldwide vaccination. Yet, a relaxation of social distancing that allows increased transmissibility, coupled with selection pressure due to vaccination, will probably lead to the emergence of vaccine resistance. We analyse the evolutionary dynamics of COVID-19 in the presence of dynamic contact reduction and in response to vaccination. We use infection and vaccination data from six different countries. We show that under slow vaccination, resistance is very likely to appear even if social distancing is maintained. Under fast vaccination, the emergence of mutants can be prevented if social distancing is maintained during vaccination. We analyse multiple human factors that affect the evolutionary potential of the virus, including the extent of dynamic social distancing, vaccination campaigns, vaccine design, boosters and vaccine hesitancy. We provide guidelines for policies that aim to minimize the probability of emergence of vaccine-resistant variants.
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Affiliation(s)
- Gabriela Lobinska
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel
| | - Ady Pauzner
- Berglas School of Economics, Tel Aviv University, Tel Aviv, Israel
| | - Arne Traulsen
- Department of Evolutionary Theory, Max-Planck-Institute for Evolutionary Biology, Ploen, Germany
| | - Yitzhak Pilpel
- Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.
| | - Martin A Nowak
- Department of Mathematics, Harvard University, Cambridge, MA, USA. .,Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
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27
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Gu H, Xie R, Adam DC, Tsui JLH, Chu DK, Chang LDJ, Cheuk SSY, Gurung S, Krishnan P, Ng DYM, Liu GYZ, Wan CKC, Cheng SSM, Edwards KM, Leung KSM, Wu JT, Tsang DNC, Leung GM, Cowling BJ, Peiris M, Lam TTY, Dhanasekaran V, Poon LLM. Genomic epidemiology of SARS-CoV-2 under an elimination strategy in Hong Kong. Nat Commun 2022; 13:736. [PMID: 35136039 PMCID: PMC8825829 DOI: 10.1038/s41467-022-28420-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 01/19/2022] [Indexed: 12/15/2022] Open
Abstract
Hong Kong employed a strategy of intermittent public health and social measures alongside increasingly stringent travel regulations to eliminate domestic SARS-CoV-2 transmission. By analyzing 1899 genome sequences (>18% of confirmed cases) from 23-January-2020 to 26-January-2021, we reveal the effects of fluctuating control measures on the evolution and epidemiology of SARS-CoV-2 lineages in Hong Kong. Despite numerous importations, only three introductions were responsible for 90% of locally-acquired cases. Community outbreaks were caused by novel introductions rather than a resurgence of circulating strains. Thus, local outbreak prevention requires strong border control and community surveillance, especially during periods of less stringent social restriction. Non-adherence to prolonged preventative measures may explain sustained local transmission observed during wave four in late 2020 and early 2021. We also found that, due to a tight transmission bottleneck, transmission of low-frequency single nucleotide variants between hosts is rare.
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Affiliation(s)
- Haogao Gu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Ruopeng Xie
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Dillon C Adam
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Joseph L-H Tsui
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Daniel K Chu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Lydia D J Chang
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Sammi S Y Cheuk
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Shreya Gurung
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Pavithra Krishnan
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Daisy Y M Ng
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Gigi Y Z Liu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Carrie K C Wan
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Samuel S M Cheng
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Kimberly M Edwards
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
| | - Kathy S M Leung
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
| | - Joseph T Wu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
| | - Dominic N C Tsang
- Centre for Health Protection, Department of Health, The Government of Hong Kong Special Administrative Region, Hong Kong, China
| | - Gabriel M Leung
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
| | - Benjamin J Cowling
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
| | - Malik Peiris
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong, China
| | - Tommy T Y Lam
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong, China
| | - Vijaykrishna Dhanasekaran
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
| | - Leo L M Poon
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong, China.
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28
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Astakhova EA, Byazrova MG, Yusubalieva GM, Larichev VF, Baklaushev VP, Filatov AV. High Heterogeneity of Virus-Neutralizing and RBD-Binding Activities of COVID-19 Convalescent Sera. Mol Biol 2022; 56:1028-1035. [PMCID: PMC9734827 DOI: 10.1134/s002689332206005x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 07/05/2022] [Accepted: 07/05/2022] [Indexed: 12/14/2022]
Abstract
The parameters of the humoral response are an important immunological characteristic of donors who recovered from COVID-19 and vaccinated individuals. Analysis of the level of virus-binding antibodies has become widespread. The most accurate predictor of effective immune protection against symptomatic SARS-CoV-2 infection is the activity of virus-neutralizing antibodies. We determined virus-neutralizing activities in plasma samples of individuals (n = 111) who had COVID-19 from April to September 2020. Three independent methods were used: conventional with live virus, with virus-like particles pseudotyped with spike protein, and a surrogate virus-neutralization test (cVNT, pVNT and sVNT, respectively). For comparison, the levels of IgG, IgA and IgM antibodies against the receptor-binding domain of the SARS-CoV-2 spike protein were also evaluated. The levels of virus-binding as well as virus-neutralizing antibodies in cVNT and pVNT showed high heterogeneity. A comparison of cVNT and pVNT results showed a high correlation, sVNT results also correlated well with both cVNT and pVNT. To the greatest extent, the level of IgG antibodies correlated with the results of cVNT, pVNT and sVNT. These results can be used in the selection of plasmas that are best suited for transfusion and treatment of acute COVID-19. In addition, data on the virus-neutralizing activity of plasma are important for the selection of potential donors, for the isolation of SARS-CoV-2-specific B-lymphocytes, in order to further generate monoclonal virus-neutralizing antibodies.
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Affiliation(s)
- E. A. Astakhova
- National Research Center “Institute of Immunology”, Federal Medical-Biological Agency, 115522 Moscow, Russia ,Immunology Department, Biological Faculty, Moscow State University, 119234 Moscow, Russia
| | - M. G. Byazrova
- National Research Center “Institute of Immunology”, Federal Medical-Biological Agency, 115522 Moscow, Russia ,Immunology Department, Biological Faculty, Moscow State University, 119234 Moscow, Russia ,Рeoples Friendship University of Russia (RUDN University) of Ministry of Science and Higher Education of Russia, 117198 Moscow, Russia
| | - G. M. Yusubalieva
- Federal Research and Clinical Center for Specialized Types of Medical Care and Medical Technologies, Federal Medical-Biological Agency, 115682 Moscow, Russia
| | - V. F. Larichev
- Gamaleya National Research Center for Epidemiology and Microbiology, Ministry of Health of the Russian Federation, 123098 Moscow, Russia
| | - V. P. Baklaushev
- Federal Research and Clinical Center for Specialized Types of Medical Care and Medical Technologies, Federal Medical-Biological Agency, 115682 Moscow, Russia
| | - A. V. Filatov
- National Research Center “Institute of Immunology”, Federal Medical-Biological Agency, 115522 Moscow, Russia ,Immunology Department, Biological Faculty, Moscow State University, 119234 Moscow, Russia
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29
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Perera D, Perks B, Potemkin M, Liu A, Gordon PMK, Gill MJ, Long Q, van Marle G. Reconstructing SARS-CoV-2 infection dynamics through the phylogenetic inference of unsampled sources of infection. PLoS One 2021; 16:e0261422. [PMID: 34910769 PMCID: PMC8673622 DOI: 10.1371/journal.pone.0261422] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 12/01/2021] [Indexed: 11/18/2022] Open
Abstract
The COVID-19 pandemic has illustrated the importance of infection tracking. The role of asymptomatic, undiagnosed individuals in driving infections within this pandemic has become increasingly evident. Modern phylogenetic tools that take into account asymptomatic or undiagnosed individuals can help guide public health responses. We finetuned established phylogenetic pipelines using published SARS-CoV-2 genomic data to examine reasonable estimate transmission networks with the inference of unsampled infection sources. The system utilised Bayesian phylogenetics and TransPhylo to capture the evolutionary and infection dynamics of SARS-CoV-2. Our analyses gave insight into the transmissions within a population including unsampled sources of infection and the results aligned with epidemiological observations. We were able to observe the effects of preventive measures in Canada's "Atlantic bubble" and in populations such as New York State. The tools also inferred the cross-species disease transmission of SARS-CoV-2 transmission from humans to lions and tigers in New York City's Bronx Zoo. These phylogenetic tools offer a powerful approach in response to both the COVID-19 and other emerging infectious disease outbreaks.
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Affiliation(s)
- Deshan Perera
- Department of Medicine, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, AB, Canada
| | - Ben Perks
- Department of Medicine, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, AB, Canada
| | - Michael Potemkin
- Department of Medicine, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, AB, Canada
| | - Andy Liu
- International Baccalaureate Diploma program, Sir Winston Churchill High School, Calgary, AB, Canada
| | - Paul M. K. Gordon
- Department of Medicine, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, AB, Canada
| | - M. John Gill
- Department of Medicine, Cumming School of Medicine, University of Calgary and Alberta Health Services, Calgary, AB, Canada
- Department of Microbiology, Immunology, and Infectious Diseases, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Quan Long
- Department of Biochemistry & Molecular Biology, Alberta Children’s Hospital Research Institute, University of Calgary, Calgary, AB, Canada
- Department of Medical Genetics, and Mathematics & Statistics, Alberta Children’s Hospital Research Institute, O’Brien Institute for Public Health, University of Calgary, Calgary, AB, Canada
| | - Guido van Marle
- Department of Microbiology, Immunology, and Infectious Diseases, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
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30
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Ye C, Thornlow B, Kramer A, McBroome J, Hinrichs A, Corbett-Detig R, Turakhia Y. Pandemic-scale phylogenetics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.12.03.470766. [PMID: 34927180 PMCID: PMC8679213 DOI: 10.1101/2021.12.03.470766] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
Phylogenetics has been central to the genomic surveillance, epidemiology and contact tracing efforts during the COVD-19 pandemic. But the massive scale of genomic sequencing has rendered the pre-pandemic tools inadequate for comprehensive phylogenetic analyses. Here, we discuss the phylogenetic package that we developed to address the needs imposed by this pandemic. The package incorporates several pandemic-specific optimization and parallelization techniques and comprises four programs: UShER, matOptimize, RIPPLES and matUtils. Using high-performance computing, UShER and matOptimize maintain and refine daily a massive mutation-annotated phylogenetic tree consisting of all SARS-CoV-2 sequences available in online repositories. With UShER and RIPPLES, individual labs - even with modest compute resources - incorporate newly-sequenced SARS-CoV-2 genomes on this phylogeny and discover evidence for recombination in real-time. With matUtils, they rapidly query and visualize massive SARS-CoV-2 phylogenies. These tools have empowered scientists worldwide to study the SARS-CoV-2 evolution and transmission at an unprecedented scale, resolution and speed.
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Affiliation(s)
- Cheng Ye
- University of California, San Diego; San Diego, CA 92093, USA
| | - Bryan Thornlow
- University of California, Santa Cruz; Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA 95064, USA
| | - Alexander Kramer
- University of California, Santa Cruz; Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA 95064, USA
| | - Jakob McBroome
- University of California, Santa Cruz; Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA 95064, USA
| | - Angie Hinrichs
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA 95064, USA
| | - Russell Corbett-Detig
- University of California, Santa Cruz; Santa Cruz, CA 95064, USA
- Genomics Institute, University of California, Santa Cruz; Santa Cruz, CA 95064, USA
| | - Yatish Turakhia
- University of California, San Diego; San Diego, CA 92093, USA
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31
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Klink GV, Safina K, Nabieva E, Shvyrev N, Garushyants S, Alekseeva E, Komissarov AB, Danilenko DM, Pochtovyi AA, Divisenko EV, Vasilchenko LA, Shidlovskaya EV, Kuznetsova NA, Samoilov AE, Neverov AD, Popova AV, Fedonin GG, Akimkin VG, Lioznov D, Gushchin VA, Shchur V, Bazykin GA. The rise and spread of the SARS-CoV-2 AY.122 lineage in Russia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.12.02.21267168. [PMID: 34909799 PMCID: PMC8669866 DOI: 10.1101/2021.12.02.21267168] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
BACKGROUND Delta has outcompeted most preexisting variants of SARS-CoV-2, becoming the globally predominant lineage by mid-2021. Its subsequent evolution has led to emergence of multiple sublineages, many of which are well-mixed between countries. AIM Here, we aim to study the emergence and spread of the Delta lineage in Russia. METHODS We use a phylogeographic approach to infer imports of Delta sublineages into Russia, and phylodynamic models to assess the rate of their spread. RESULTS We show that nearly the entire Delta epidemic in Russia has probably descended from a single import event despite genetic evidence of multiple Delta imports. Indeed, over 90% of Delta samples in Russia are characterized by the nsp2:K81N+ORF7a:P45L pair of mutations which is rare outside Russia, putting them in the AY.122 sublineage. The AY.122 lineage was frequent in Russia among Delta samples from the start, and has not increased in frequency in other countries where it has been observed, suggesting that its high prevalence in Russia has probably resulted from a random founder effect. CONCLUSION The apartness of the genetic composition of the Delta epidemic in Russia makes Russia somewhat unusual, although not exceptional, among other countries.
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Affiliation(s)
- Galya V. Klink
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia
| | - Ksenia Safina
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
| | - Elena Nabieva
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
| | - Nikita Shvyrev
- National Research University Higher School of Economics, Moscow, Russia
| | - Sofya Garushyants
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia
- Present address: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | | | | | | | - Andrei A. Pochtovyi
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, Moscow, Russia
- Department of Virology, Biological Faculty, Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Elizaveta V. Divisenko
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, Moscow, Russia
| | - Lyudmila A. Vasilchenko
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, Moscow, Russia
| | - Elena V. Shidlovskaya
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, Moscow, Russia
| | - Nadezhda A. Kuznetsova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, Moscow, Russia
| | | | - Andrei E. Samoilov
- Federal Budget Institution of Science “Central Research Institute for Epidemiology” of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor), Moscow, Russia
| | - Alexey D. Neverov
- Federal Budget Institution of Science “Central Research Institute for Epidemiology” of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor), Moscow, Russia
| | - Anfisa V. Popova
- Federal Budget Institution of Science “Central Research Institute for Epidemiology” of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor), Moscow, Russia
| | - Gennady G. Fedonin
- Federal Budget Institution of Science “Central Research Institute for Epidemiology” of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor), Moscow, Russia
| | | | - Vasiliy G. Akimkin
- Federal Budget Institution of Science “Central Research Institute for Epidemiology” of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor), Moscow, Russia
| | - Dmitry Lioznov
- Smorodintsev Research Institute of Influenza, Saint Petersburg, Russia
- First Pavlov State Medical University, Saint Petersburg, Russia
| | - Vladimir A. Gushchin
- Department of Virology, Biological Faculty, Lomonosov Moscow State University, 119991 Moscow, Russia
- https://corgi.center/en/ (see the list of consortium members in Supplementary File 1)
| | - Vladimir Shchur
- National Research University Higher School of Economics, Moscow, Russia
| | - Georgii A. Bazykin
- A.A. Kharkevich Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, Russia
- Skolkovo Institute of Science and Technology (Skoltech), Moscow, Russia
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32
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Shchur V, Spirin V, Sirotkin D, Burovski E, De Maio N, Corbett-Detig R. VGsim: scalable viral genealogy simulator for global pandemic. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.04.21.21255891. [PMID: 33948608 PMCID: PMC8095227 DOI: 10.1101/2021.04.21.21255891] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Accurate simulation of complex biological processes is an essential component of developing and validating new technologies and inference approaches. As an effort to help contain the COVID-19 pandemic, large numbers of SARS-CoV-2 genomes have been sequenced from most regions in the world. More than 5.5 million viral sequences are publicly available as of November 2021. Many studies estimate viral genealogies from these sequences, as these can provide valuable information about the spread of the pandemic across time and space. Additionally such data are a rich source of information about molecular evolutionary processes including natural selection, for example allowing the identification of new variants with transmissibility and immunity evasion advantages. To our knowledge, there is no framework that is both efficient and flexible enough to simulate the pandemic to approximate world-scale scenarios and generate viral genealogies of millions of samples. Here, we introduce a new fast simulator VGsim which addresses the problem of simulation genealogies under epidemiological models. The simulation process is split into two phases. During the forward run the algorithm generates a chain of population-level events reflecting the dynamics of the pandemic using an hierarchical version of the Gillespie algorithm. During the backward run a coalescent-like approach generates a tree genealogy of samples conditioning on the population-level events chain generated during the forward run. Our software can model complex population structure, epistasis and immunity escape. The code is freely available at https://github.com/Genomics-HSE/VGsim.
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Affiliation(s)
| | | | | | | | - Nicola De Maio
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Russell Corbett-Detig
- HSE University, Russian Federation
- Department of Biomolecular Engineering and Genomics Institute, UC Santa Cruz, California 95064
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33
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Sant’Anna FH, Muterle Varela AP, Prichula J, Comerlato J, Comerlato CB, Roglio VS, Mendes Pereira GF, Moreno F, Seixas A, Wendland EM. Emergence of the novel SARS-CoV-2 lineage VUI-NP13L and massive spread of P.2 in South Brazil. Emerg Microbes Infect 2021; 10:1431-1440. [PMID: 34184973 PMCID: PMC8284128 DOI: 10.1080/22221751.2021.1949948] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 06/24/2021] [Accepted: 06/26/2021] [Indexed: 12/16/2022]
Abstract
In this study, we analyzed 340 whole genomes of SARS-CoV-2, which were sampled between April and November 2020 in 33 cities of Rio Grande do Sul, South Brazil. We demonstrated the circulation of two novel emergent lineages, VUI-NP13L and VUI-NP13L-like, and five major lineages that had already been assigned (B.1.1.33, B.1.1.28, P.2, B.1.91, B.1.195). P.2 and VUI-NP13L demonstrated a massive spread in October 2020. Constant and consistent genomic surveillance is crucial to identify newly emerging SARS-CoV-2 lineages in Brazil and to guide decision making in the Brazilian Public Healthcare System.
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Affiliation(s)
| | - Ana Paula Muterle Varela
- Graduate Program in Biosciences, Federal University of Health Sciences of Porto Alegre (UFCSPA), Porto Alegre, Brazil
| | - Janira Prichula
- Graduate Program in Biosciences, Federal University of Health Sciences of Porto Alegre (UFCSPA), Porto Alegre, Brazil
| | | | | | | | | | - Flávia Moreno
- Department of Chronic Conditions and Sexually Transmitted Infections, Ministry of Health, Brasília, Brazil
| | - Adriana Seixas
- Graduate Program in Biosciences, Federal University of Health Sciences of Porto Alegre (UFCSPA), Porto Alegre, Brazil
| | - Eliana Márcia Wendland
- Hospital Moinhos de Vento, PROADI – SUS, Porto Alegre, Brazil
- Department of Community Health, Federal University of Health Sciences of Porto Alegre (UFCSPA), Porto Alegre, Brazil
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34
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Garushyants SK, Rogozin IB, Koonin EV. Template switching and duplications in SARS-CoV-2 genomes give rise to insertion variants that merit monitoring. Commun Biol 2021; 4:1343. [PMID: 34848826 PMCID: PMC8632935 DOI: 10.1038/s42003-021-02858-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 11/01/2021] [Indexed: 12/29/2022] Open
Abstract
The appearance of multiple new SARS-CoV-2 variants during the COVID-19 pandemic is a matter of grave concern. Some of these variants, such as B.1.617.2, B.1.1.7, and B.1.351, manifest higher infectivity and virulence than the earlier SARS-CoV-2 variants, with potential dramatic effects on the course of the pandemic. So far, analysis of new SARS-CoV-2 variants focused primarily on nucleotide substitutions and short deletions that are readily identifiable by comparison to consensus genome sequences. In contrast, insertions have largely escaped the attention of researchers although the furin site insert in the Spike (S) protein is thought to be a determinant of SARS-CoV-2 virulence. Here, we identify 346 unique inserts of different lengths in SARS-CoV-2 genomes and present evidence that these inserts reflect actual virus variance rather than sequencing artifacts. Two principal mechanisms appear to account for the inserts in the SARS-CoV-2 genomes, polymerase slippage and template switch that might be associated with the synthesis of subgenomic RNAs. At least three inserts in the N-terminal domain of the S protein are predicted to lead to escape from neutralizing antibodies, whereas other inserts might result in escape from T-cell immunity. Thus, inserts in the S protein can affect its antigenic properties and merit monitoring.
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Affiliation(s)
- Sofya K Garushyants
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Igor B Rogozin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Eugene V Koonin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.
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35
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Wagatsuma K, Sato R, Yamazaki S, Iwaya M, Takahashi Y, Nojima A, Oseki M, Abe T, Phyu WW, Tamura T, Sekizuka T, Kuroda M, Matsumoto HH, Saito R. Genomic Epidemiology Reveals Multiple Introductions of Severe Acute Respiratory Syndrome Coronavirus 2 in Niigata City, Japan, Between February and May 2020. Front Microbiol 2021; 12:749149. [PMID: 34777297 PMCID: PMC8581661 DOI: 10.3389/fmicb.2021.749149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Accepted: 10/04/2021] [Indexed: 01/19/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) has caused a serious disease burden and poses a tremendous public health challenge worldwide. Here, we report a comprehensive epidemiological and genomic analysis of SARS-CoV-2 from 63 patients in Niigata City, a medium-sized Japanese city, during the early phase of the pandemic, between February and May 2020. Among the 63 patients, 32 (51%) were female, with a mean (±standard deviation) age of 47.9 ± 22.3 years. Fever (65%, 41/63), malaise (51%, 32/63), and cough (35%, 22/63) were the most common clinical symptoms. The median Ct value after the onset of symptoms lowered within 9 days at 20.9 cycles (interquartile range, 17–26 cycles), but after 10 days, the median Ct value exceeded 30 cycles (p < 0.001). Of the 63 cases, 27 were distributed in the first epidemic wave and 33 in the second, and between the two waves, three cases from abroad were identified. The first wave was epidemiologically characterized by a single cluster related to indoor sports activity spread in closed settings, which included mixing indoors with families, relatives, and colleagues. The second wave showed more epidemiologically diversified events, with most index cases not related to each other. Almost all secondary cases were infected by droplets or aerosols from closed indoor settings, but at least two cases in the first wave were suspected to be contact infections. Results of the genomic analysis identified two possible clusters in Niigata City, the first of which was attributed to clade S (19B by Nexstrain clade) with a monophyletic group derived from the Wuhan prototype strain but that of the second wave was polyphyletic suggesting multiple introductions, and the clade was changed to GR (20B), which mainly spread in Europe in early 2020. These findings depict characteristics of SARS-CoV-2 transmission in the early stages in local community settings during February to May 2020 in Japan, and this integrated approach of epidemiological and genomic analysis may provide valuable information for public health policy decision-making for successful containment of chains of infection.
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Affiliation(s)
- Keita Wagatsuma
- Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Ryosuke Sato
- Niigata City Public Health and Sanitation Center, Niigata, Japan
| | - Satoru Yamazaki
- Niigata City Public Health and Sanitation Center, Niigata, Japan
| | - Masako Iwaya
- Niigata City Public Health and Sanitation Center, Niigata, Japan
| | | | - Akiko Nojima
- Niigata City Public Health and Sanitation Center, Niigata, Japan
| | - Mitsuru Oseki
- Division of Health Science, Niigata City Institute of Public Health and Environment, Niigata, Japan
| | - Takashi Abe
- Division of Bioinformatics, Graduate School of Science and Technology, Niigata University, Niigata, Japan
| | - Wint Wint Phyu
- Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Tsutomu Tamura
- Virology Section, Niigata Prefectural Institute of Public Health and Environmental Science, Niigata, Japan
| | - Tsuyoshi Sekizuka
- Pathogen Genomics Center, National Institute of Infectious Diseases, Tokyo, Japan
| | - Makoto Kuroda
- Pathogen Genomics Center, National Institute of Infectious Diseases, Tokyo, Japan
| | - Haruki H Matsumoto
- Division of Health and Welfare, Niigata Prefectural Government Office, Niigata, Japan
| | - Reiko Saito
- Division of International Health (Public Health), Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
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36
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Murall CL, Fournier E, Galvez JH, N'Guessan A, Reiling SJ, Quirion PO, Naderi S, Roy AM, Chen SH, Stretenowich P, Bourgey M, Bujold D, Gregoire R, Lepage P, St-Cyr J, Willet P, Dion R, Charest H, Lathrop M, Roger M, Bourque G, Ragoussis J, Shapiro BJ, Moreira S. A small number of early introductions seeded widespread transmission of SARS-CoV-2 in Québec, Canada. Genome Med 2021; 13:169. [PMID: 34706766 PMCID: PMC8550813 DOI: 10.1186/s13073-021-00986-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Accepted: 10/05/2021] [Indexed: 11/10/2022] Open
Abstract
Background Québec was the Canadian province most impacted by COVID-19, with 401,462 cases as of September 24th, 2021, and 11,347 deaths due mostly to a very severe first pandemic wave. In April 2020, we assembled the Coronavirus Sequencing in Québec (CoVSeQ) consortium to sequence SARS-CoV-2 genomes in Québec to track viral introduction events and transmission within the province. Methods Using genomic epidemiology, we investigated the arrival of SARS-CoV-2 to Québec. We report 2921 high-quality SARS-CoV-2 genomes in the context of > 12,000 publicly available genomes sampled globally over the first pandemic wave (up to June 1st, 2020). By combining phylogenetic and phylodynamic analyses with epidemiological data, we quantify the number of introduction events into Québec, identify their origins, and characterize the spatiotemporal spread of the virus. Results Conservatively, we estimated approximately 600 independent introduction events, the majority of which happened from spring break until 2 weeks after the Canadian border closed for non-essential travel. Subsequent mass repatriations did not generate large transmission lineages (> 50 sequenced cases), likely due to mandatory quarantine measures in place at the time. Consistent with common spring break and “snowbird” destinations, most of the introductions were inferred to have originated from Europe via the Americas. Once introduced into Québec, viral lineage sizes were overdispersed, with a few lineages giving rise to most infections. Consistent with founder effects, the earliest lineages to arrive tended to spread most successfully. Fewer than 100 viral introductions arrived during spring break, of which 7–12 led to the largest transmission lineages of the first wave (accounting for 52–75% of all sequenced infections). These successful transmission lineages dispersed widely across the province. Transmission lineage size was greatly reduced after March 11th, when a quarantine order for returning travellers was enacted. While this suggests the effectiveness of early public health measures, the biggest transmission lineages had already been ignited prior to this order. Conclusions Combined, our results reinforce how, in the absence of tight travel restrictions or quarantine measures, fewer than 100 viral introductions in a week can ensure the establishment of extended transmission chains. Supplementary Information The online version contains supplementary material available at 10.1186/s13073-021-00986-9.
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Affiliation(s)
- Carmen Lía Murall
- McGill Genome Centre, Montreal, QC, Canada.,Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada.,Département de Sciences Biologiques, Université de Montréal, Montreal, QC, Canada
| | - Eric Fournier
- Laboratoire de Santé Publique du Québec, Institut National de Santé Publique, Montreal, QC, Canada
| | - Jose Hector Galvez
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada
| | - Arnaud N'Guessan
- Département de Sciences Biologiques, Université de Montréal, Montreal, QC, Canada
| | - Sarah J Reiling
- McGill Genome Centre, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Pierre-Olivier Quirion
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada.,Calcul Québec, Montreal, QC, Canada
| | - Sana Naderi
- McGill Genome Centre, Montreal, QC, Canada.,Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada
| | - Anne-Marie Roy
- McGill Genome Centre, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Shu-Huang Chen
- McGill Genome Centre, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Paul Stretenowich
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada
| | - Mathieu Bourgey
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada
| | - David Bujold
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada
| | - Romain Gregoire
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada
| | | | | | | | - Réjean Dion
- Laboratoire de Santé Publique du Québec, Institut National de Santé Publique, Montreal, QC, Canada.,Ecole de santé publique, Université de Montréal, Montreal, QC, Canada
| | - Hugues Charest
- Laboratoire de Santé Publique du Québec, Institut National de Santé Publique, Montreal, QC, Canada
| | - Mark Lathrop
- McGill Genome Centre, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Michel Roger
- Laboratoire de Santé Publique du Québec, Institut National de Santé Publique, Montreal, QC, Canada.,Département de Microbiologie, infectiologie et Immunologie, Université de Montréal, Montreal, QC, Canada
| | - Guillaume Bourque
- McGill Genome Centre, Montreal, QC, Canada.,Canadian Center for Computational Genomics, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada
| | - Jiannis Ragoussis
- McGill Genome Centre, Montreal, QC, Canada.,Department of Human Genetics, McGill University, Montreal, QC, Canada.,Department of Bioengineering, McGill University, Montreal, QC, Canada
| | - B Jesse Shapiro
- McGill Genome Centre, Montreal, QC, Canada. .,Department of Microbiology and Immunology, McGill University, Montreal, QC, Canada. .,Département de Sciences Biologiques, Université de Montréal, Montreal, QC, Canada.
| | - Sandrine Moreira
- Laboratoire de Santé Publique du Québec, Institut National de Santé Publique, Montreal, QC, Canada
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37
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Huang J, Liu X, Zhang L, Zhao Y, Wang D, Gao J, Lian X, Liu C. The oscillation-outbreaks characteristic of the COVID-19 pandemic. Natl Sci Rev 2021; 8:nwab100. [PMID: 34676100 PMCID: PMC8344697 DOI: 10.1093/nsr/nwab100] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Affiliation(s)
- Jianping Huang
- Collaborative Innovation Center for Western Ecological Safety (CIWES), Lanzhou University, China
| | - Xiaoyue Liu
- Collaborative Innovation Center for Western Ecological Safety (CIWES), Lanzhou University, China
| | - Li Zhang
- Collaborative Innovation Center for Western Ecological Safety (CIWES), Lanzhou University, China
| | - Yingjie Zhao
- Collaborative Innovation Center for Western Ecological Safety (CIWES), Lanzhou University, China
| | - Danfeng Wang
- Collaborative Innovation Center for Western Ecological Safety (CIWES), Lanzhou University, China
| | - Jinfeng Gao
- Collaborative Innovation Center for Western Ecological Safety (CIWES), Lanzhou University, China
| | - Xinbo Lian
- Collaborative Innovation Center for Western Ecological Safety (CIWES), Lanzhou University, China
| | - Chuwei Liu
- Collaborative Innovation Center for Western Ecological Safety (CIWES), Lanzhou University, China
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38
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Long Term Immune Response Produced by the SputnikV Vaccine. Int J Mol Sci 2021; 22:ijms222011211. [PMID: 34681885 PMCID: PMC8537212 DOI: 10.3390/ijms222011211] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 10/13/2021] [Accepted: 10/13/2021] [Indexed: 01/08/2023] Open
Abstract
SputnikV is a vaccine against SARS-CoV-2 developed by the Gamaleya National Research Centre for Epidemiology and Microbiology. The vaccine has been shown to induce both humoral and cellular immune responses, yet the mechanisms remain largely unknown. Forty SputnikV vaccinated individuals were included in this study which aimed to demonstrate the location of immunogenic domains of the SARS-CoV-2 S protein using an overlapping peptide library. Additionally, cytokines in the serum of vaccinated and convalescent COVID-19 patients were analyzed. We have found antibodies from both vaccinated and convalescent sera bind to immunogenic regions located in multiple domains of SARS-CoV-2 S protein, including Receptor Binding Domain (RBD), N-terminal Domain (NTD), Fusion Protein (FP) and Heptad Repeats (HRs). Interestingly, many peptides were recognized by immunized and convalescent serum antibodies and correspond to conserved regions in circulating variants of SARS-CoV-2. This breadth of reactivity was still evident 90 days after the first dose of the vaccine, showing that the vaccine has induced a prolonged response. As evidenced by the activation of T cells, cellular immunity strongly suggests the high potency of the SputnikV vaccine against SARS-CoV-2 infection.
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39
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Borisova NI, Kotov IA, Kolesnikov AA, Kaptelova VV, Speranskaya AS, Kondrasheva LY, Tivanova EV, Khafizov KF, Akimkin VG. [Monitoring the spread of the SARS-CoV-2 (Coronaviridae: Coronavirinae: Betacoronavirus; Sarbecovirus) variants in the Moscow region using targeted high-throughput sequencing]. Vopr Virusol 2021; 66:269-278. [PMID: 34545719 DOI: 10.36233/0507-4088-72] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Accepted: 09/18/2021] [Indexed: 02/05/2023]
Abstract
INTRODUCTION Since the outbreak of the COVID-19 pandemic caused by SARS-CoV-2 novel coronavirus, the international community has been concerned about the emergence of mutations altering some biological properties of the pathogen like increasing its infectivity or virulence. Particularly, since the end of 2020, several variants of concern have been identified around the world, including Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), and Delta (B.1.617.2). However, the existing mechanism of detecting important mutations are not always effective enough, since only a relatively small part of all pathogen samples can be examined by whole genome sequencing due to its high cost. MATERIAL AND METHODS In this study, we have designed special primer panel and used it for targeted highthroughput sequencing of several significant S-gene (spike) regions of SARS-CoV-2. The Illumina platform averaged approximately 50,000 paired-end reads with a length of ≥150 bp per sample. This method was used to examine 579 random samples obtained from COVID-19 patients in Moscow and the Moscow region from February to June 2021. RESULTS This study demonstrated the dynamics of distribution of several SARS-CoV-2 strains and its some single mutations. It was found that the Delta strain appeared in the region in May 2021, and became prevalent in June, partially displacing other strains. DISCUSSION The obtained results provide an opportunity to assign the viral samples to one of the strains, including the previously mentioned in time- and cost-effective manner. The approach can be used for standardization of the procedure of searching for mutations in individual regions of the SARS-CoV-2 genome. It allows to get a more detailed data about the epidemiological situation in a region.
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Affiliation(s)
- N I Borisova
- FSBI «Central Research Institute for Epidemiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - I A Kotov
- FSBI «Central Research Institute for Epidemiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor); FSAEI HE «Moscow Institute of Physics and Technology (National Research University)»
| | - A A Kolesnikov
- FSBI «Central Research Institute for Epidemiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - V V Kaptelova
- FSBI «Central Research Institute for Epidemiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - A S Speranskaya
- FSBI «Central Research Institute for Epidemiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - L Yu Kondrasheva
- FSBI «Central Research Institute for Epidemiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - E V Tivanova
- FSBI «Central Research Institute for Epidemiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - K F Khafizov
- FSBI «Central Research Institute for Epidemiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
| | - V G Akimkin
- FSBI «Central Research Institute for Epidemiology» of the Federal Service for Supervision of Consumer Rights Protection and Human Welfare (Rospotrebnadzor)
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40
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Nemira A, Adeniyi AE, Gasich EL, Bulda KY, Valentovich LN, Krasko AG, Glebova O, Kirpich A, Skums P. SARS-CoV-2 transmission dynamics in Belarus in 2020 revealed by genomic and incidence data analysis. COMMUNICATIONS MEDICINE 2021; 1:31. [PMID: 35602211 PMCID: PMC9053244 DOI: 10.1038/s43856-021-00031-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 08/25/2021] [Indexed: 12/15/2022] Open
Abstract
Background Non-pharmaceutical interventions (NPIs) have been implemented worldwide to curb COVID-19 spread. Belarus is a rare case of a country with a relatively modern healthcare system, where highly limited NPIs have been enacted. Thus, investigation of Belarusian COVID-19 dynamics is essential for the local and global assessment of the impact of NPI strategies. Methods We integrate genomic epidemiology and surveillance methods to investigate the spread of SARS-CoV-2 in Belarus in 2020. We utilize phylodynamics, phylogeography, and probabilistic bias inference to study the virus import and export routes, the dynamics of the effective reproduction number, and the incidence of SARS-CoV-2 infection. Results Here we show that the estimated cumulative number of infections by June 2020 exceeds the confirmed case number by a factor of ~4 (95% confidence interval (2; 9)). Intra-country SARS-CoV-2 genomic diversity originates from at least 18 introductions from different regions, with a high proportion of regional transmissions. Phylodynamic analysis indicates a moderate reduction of the effective reproductive number after the introduction of limited NPIs, but its magnitude is lower than for developed countries with large-scale NPIs. On the other hand, the effective reproduction number estimate is comparable with that for the neighboring Ukraine, where NPIs were broader. Conclusions The example of Belarus demonstrates how countries with relatively low outward population mobility continue to be integral parts of the global epidemiological environment. Comparison of the effective reproduction number dynamics for Belarus and other countries reveals the effect of different NPI strategies but also emphasizes the role of regional Eastern European sociodemographic factors in the virus spread. Belarus is one of few European countries that has enacted limited measures to contain SARS-CoV-2, the virus that causes COVID-19. We study the genetic sequences of the SARS-CoV-2 virus circulating in Belarus and other countries in 2020 to investigate how it might have been imported into the country and spread there. We show that the virus was repeatedly imported from and exported to different regions, including a large portion of regional transmissions that occurred despite stricter measures implemented by Belarus’ neighbors. There was a moderate reduction of the virus reproductive number—a measure of virus transmission speed—after April 2020, but its magnitude was lower than for developed countries with more stringent epidemiological interventions. These findings shed light on the COVID-19 spread in Eastern Europe and highlight the impact of public health policies and of regional factors on this spread. Nemira et al. study the genomic epidemiology and phylodynamics of SARS-CoV-2 in Belarus. They identify potential introduction routes of the virus from other countries, determine that during the first wave of the pandemic the number of infections was likely several times higher than reported case numbers, and estimate the impact of early non-pharmaceutical interventions on SARS-CoV-2 transmission.
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Garushyants SK, Rogozin IB, Koonin EV. Insertions in SARS-CoV-2 genome caused by template switch and duplications give rise to new variants that merit monitoring. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.04.23.441209. [PMID: 33907754 PMCID: PMC8077628 DOI: 10.1101/2021.04.23.441209] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
The appearance of multiple new SARS-CoV-2 variants during the winter of 2020-2021 is a matter of grave concern. Some of these new variants, such as B.1.617.2, B.1.1.7, and B.1.351, manifest higher infectivity and virulence than the earlier SARS-CoV-2 variants, with potential dramatic effects on the course of the COVID-19 pandemic. So far, analysis of new SARS-CoV-2 variants focused primarily on point nucleotide substitutions and short deletions that are readily identifiable by comparison to consensus genome sequences. In contrast, insertions have largely escaped the attention of researchers although the furin site insert in the spike protein is thought to be a determinant of SARS-CoV-2 virulence and other inserts might have contributed to coronavirus pathogenicity as well. Here, we investigate insertions in SARS-CoV-2 genomes and identify 347 unique inserts of different lengths. We present evidence that these inserts reflect actual virus variance rather than sequencing errors. Two principal mechanisms appear to account for the inserts in the SARS-CoV-2 genomes, polymerase slippage and template switch that might be associated with the synthesis of subgenomic RNAs. We show that inserts in the Spike glycoprotein can affect its antigenic properties and thus merit monitoring. At least, three inserts in the N-terminal domain of the Spike (ins245IME, ins246DSWG, and ins248SSLT) that were first detected in 2021 are predicted to lead to escape from neutralizing antibodies, whereas other inserts might result in escape from T-cell immunity.
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Affiliation(s)
- Sofya K. Garushyants
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Igor B. Rogozin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
| | - Eugene V. Koonin
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA
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42
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Kumar S, Tao Q, Weaver S, Sanderford M, Caraballo-Ortiz MA, Sharma S, Pond SLK, Miura S. An Evolutionary Portrait of the Progenitor SARS-CoV-2 and Its Dominant Offshoots in COVID-19 Pandemic. Mol Biol Evol 2021; 38:3046-3059. [PMID: 33942847 PMCID: PMC8135569 DOI: 10.1093/molbev/msab118] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Global sequencing of genomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has continued to reveal new genetic variants that are the key to unraveling its early evolutionary history and tracking its global spread over time. Here we present the heretofore cryptic mutational history and spatiotemporal dynamics of SARS-CoV-2 from an analysis of thousands of high-quality genomes. We report the likely most recent common ancestor of SARS-CoV-2, reconstructed through a novel application and advancement of computational methods initially developed to infer the mutational history of tumor cells in a patient. This progenitor genome differs from genomes of the first coronaviruses sampled in China by three variants, implying that none of the earliest patients represent the index case or gave rise to all the human infections. However, multiple coronavirus infections in China and the United States harbored the progenitor genetic fingerprint in January 2020 and later, suggesting that the progenitor was spreading worldwide months before and after the first reported cases of COVID-19 in China. Mutations of the progenitor and its offshoots have produced many dominant coronavirus strains that have spread episodically over time. Fingerprinting based on common mutations reveals that the same coronavirus lineage has dominated North America for most of the pandemic in 2020. There have been multiple replacements of predominant coronavirus strains in Europe and Asia as well as continued presence of multiple high-frequency strains in Asia and North America. We have developed a continually updating dashboard of global evolution and spatiotemporal trends of SARS-CoV-2 spread (http://sars2evo.datamonkey.org/).
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Affiliation(s)
- Sudhir Kumar
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
- Department of Biology, Temple University, Philadelphia, PA, USA
- Center for Excellence in Genome Medicine and Research, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Qiqing Tao
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
- Department of Biology, Temple University, Philadelphia, PA, USA
| | - Steven Weaver
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
- Department of Biology, Temple University, Philadelphia, PA, USA
| | - Maxwell Sanderford
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
- Department of Biology, Temple University, Philadelphia, PA, USA
| | - Marcos A Caraballo-Ortiz
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
- Department of Biology, Temple University, Philadelphia, PA, USA
| | - Sudip Sharma
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
- Department of Biology, Temple University, Philadelphia, PA, USA
| | - Sergei L K Pond
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
- Department of Biology, Temple University, Philadelphia, PA, USA
| | - Sayaka Miura
- Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA, USA
- Department of Biology, Temple University, Philadelphia, PA, USA
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43
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Gushchin VA, Dolzhikova IV, Shchetinin AM, Odintsova AS, Siniavin AE, Nikiforova MA, Pochtovyi AA, Shidlovskaya EV, Kuznetsova NA, Burgasova OA, Kolobukhina LV, Iliukhina AA, Kovyrshina AV, Botikov AG, Kuzina AV, Grousova DM, Tukhvatulin AI, Shcheblyakov DV, Zubkova OV, Karpova OV, Voronina OL, Ryzhova NN, Aksenova EI, Kunda MS, Lioznov DA, Danilenko DM, Komissarov AB, Tkachuck AP, Logunov DY, Gintsburg AL. Neutralizing Activity of Sera from Sputnik V-Vaccinated People against Variants of Concern (VOC: B.1.1.7, B.1.351, P.1, B.1.617.2, B.1.617.3) and Moscow Endemic SARS-CoV-2 Variants. Vaccines (Basel) 2021; 9:779. [PMID: 34358195 PMCID: PMC8310330 DOI: 10.3390/vaccines9070779] [Citation(s) in RCA: 74] [Impact Index Per Article: 24.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 07/06/2021] [Accepted: 07/06/2021] [Indexed: 12/14/2022] Open
Abstract
Since the beginning of the 2021 year, all the main six vaccines against COVID-19 have been used in mass vaccination companies around the world. Virus neutralization and epidemiological efficacy drop obtained for several vaccines against the B.1.1.7, B.1.351 P.1, and B.1.617 genotypes are of concern. There is a growing number of reports on mutations in receptor-binding domain (RBD) increasing the transmissibility of the virus and escaping the neutralizing effect of antibodies. The Sputnik V vaccine is currently approved for use in more than 66 countries but its activity against variants of concern (VOC) is not extensively studied yet. Virus-neutralizing activity (VNA) of sera obtained from people vaccinated with Sputnik V in relation to internationally relevant genetic lineages B.1.1.7, B.1.351, P.1, B.1.617.2, B.1.617.3 and Moscow endemic variants B.1.1.141 (T385I) and B.1.1.317 (S477N, A522S) with mutations in the RBD domain has been assessed. The data obtained indicate no significant differences in VNA against B.1.1.7, B.1.617.3 and local genetic lineages B.1.1.141 (T385I), B.1.1.317 (S477N, A522S) with RBD mutations. For the B.1.351, P.1, and B.1.617.2 statistically significant 3.1-, 2.8-, and 2.5-fold, respectively, VNA reduction was observed. Notably, this decrease is lower than that reported in publications for other vaccines. However, a direct comparative study is necessary for a conclusion. Thus, sera from "Sputnik V"-vaccinated retain neutralizing activity against VOC B.1.1.7, B.1.351, P.1, B.1.617.2, B.1.617.3 as well as local genetic lineages B.1.1.141 and B.1.1.317 circulating in Moscow.
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Affiliation(s)
- Vladimir A. Gushchin
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
- Department of Virology, Biological Faculty, Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Inna V. Dolzhikova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Alexey M. Shchetinin
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Alina S. Odintsova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Andrei E. Siniavin
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
- Department of Molecular Neuroimmune Signalling, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Academy of Sciences, 117997 Moscow, Russia
| | - Maria A. Nikiforova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Andrei A. Pochtovyi
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
- Department of Virology, Biological Faculty, Lomonosov Moscow State University, 119991 Moscow, Russia
| | - Elena V. Shidlovskaya
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Nadezhda A. Kuznetsova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Olga A. Burgasova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
- Moscow Healthcare Department, 127006 Moscow, Russia;
- Department of Infectious Diseases, Peoples’ Friendship University of Russia (RUDN University), 117198 Moscow, Russia
| | - Liudmila V. Kolobukhina
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
- Moscow Healthcare Department, 127006 Moscow, Russia;
| | - Anna A. Iliukhina
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Anna V. Kovyrshina
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Andrey G. Botikov
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Aleksandra V. Kuzina
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Daria M. Grousova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Amir I. Tukhvatulin
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Dmitry V. Shcheblyakov
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Olga V. Zubkova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | | | - Olga L. Voronina
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Natalia N. Ryzhova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Ekaterina I. Aksenova
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Marina S. Kunda
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Dmitry A. Lioznov
- Smorodintsev Research Institute of Influenza, 197022 St. Petersburg, Russia; (D.A.L.); (D.M.D.); (A.B.K.)
- Department of Infectious Diseases and Epidemiology, First Pavlov State Medical University, 197022 St. Petersburg, Russia
| | - Daria M. Danilenko
- Smorodintsev Research Institute of Influenza, 197022 St. Petersburg, Russia; (D.A.L.); (D.M.D.); (A.B.K.)
| | - Andrey B. Komissarov
- Smorodintsev Research Institute of Influenza, 197022 St. Petersburg, Russia; (D.A.L.); (D.M.D.); (A.B.K.)
| | - Artem P. Tkachuck
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Denis Y. Logunov
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
| | - Alexander L. Gintsburg
- Federal State Budget Institution “National Research Centre for Epidemiology and Microbiology Named after Honorary Academician N F Gamaleya” of the Ministry of Health of the Russian Federation, 123098 Moscow, Russia; (A.M.S.); (A.S.O.); (A.E.S.); (M.A.N.); (A.A.P.); (E.V.S.); (N.A.K.); (O.A.B.); (L.V.K.); (A.A.I.); (A.V.K.); (A.G.B.); (A.V.K.); (D.M.G.); (A.I.T.); (D.V.S.); (O.V.Z.); (O.L.V.); (N.N.R.); (E.I.A.); (M.S.K.); (A.P.T.); (A.L.G.)
- Department of Infectiology and Virology, Federal State Autonomous Educational Institution of Higher Education I M Sechenov First Moscow State Medical University of the Ministry of Health of the Russian Federation (Sechenov University), 119435 Moscow, Russia
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Nikonova AA, Faizuloev EB, Gracheva AV, Isakov IY, Zverev VV. Genetic Diversity and Evolution of the Biological Features of the Pandemic SARS-CoV-2. Acta Naturae 2021; 13:77-88. [PMID: 34707899 PMCID: PMC8526184 DOI: 10.32607/actanaturae.11337] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 04/13/2021] [Indexed: 01/08/2023] Open
Abstract
The new coronavirus infection (COVID-19) represents a challenge for global health. Since the outbreak began, the number of confirmed cases has exceeded 117 million, with more than 2.6 million deaths worldwide. With public health measures aimed at containing the spread of the disease, several countries have faced a crisis in the availability of intensive care units. Currently, a large-scale effort is underway to identify the nucleotide sequences of the SARS-CoV-2 coronavirus that is an etiological agent of COVID-19. Global sequencing of thousands of viral genomes has revealed many common genetic variants, which enables the monitoring of the evolution of SARS-CoV-2 and the tracking of its spread over time. Understanding the current evolution of SARS-CoV-2 is necessary not only for a retrospective analysis of the new coronavirus infection spread, but also for the development of approaches to the therapy and prophylaxis of COVID-19. In this review, we have focused on the general characteristics of SARS-CoV-2 and COVID-19. Also, we have analyzed available publications on the genetic diversity of the virus and the relationship between the diversity and the biological properties of SARS-CoV-2, such as virulence and contagiousness.
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Affiliation(s)
- A. A. Nikonova
- Mechnikov Research Institute for Vaccines and Sera, Moscow, 105064 Russia
| | - E. B. Faizuloev
- Mechnikov Research Institute for Vaccines and Sera, Moscow, 105064 Russia
| | - A. V. Gracheva
- Mechnikov Research Institute for Vaccines and Sera, Moscow, 105064 Russia
| | - I. Yu. Isakov
- Mechnikov Research Institute for Vaccines and Sera, Moscow, 105064 Russia
| | - V. V. Zverev
- Mechnikov Research Institute for Vaccines and Sera, Moscow, 105064 Russia
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Zurochka A, Dobrinina M, Zurochka V, Hu D, Solovyev A, Ryabova L, Kritsky I, Ibragimov R, Sarapultsev A. Seroprevalence of SARS-CoV-2 Antibodies in Symptomatic Individuals Is Higher than in Persons Who Are at Increased Risk Exposure: The Results of the Single-Center, Prospective, Cross-Sectional Study. Vaccines (Basel) 2021; 9:627. [PMID: 34207919 PMCID: PMC8229032 DOI: 10.3390/vaccines9060627] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 06/03/2021] [Accepted: 06/08/2021] [Indexed: 01/08/2023] Open
Abstract
The present study aimed to assess antibody seropositivity prevalence among symptomatic individuals and individuals with a high risk of occupational exposure to SARS-CoV-2. Participants from Chelyabinsk (Russian Federation) who were at an increased risk of exposure to SARS-CoV-2 (high-risk group, n = 1091) and participants who either had symptoms consistent with COVID-19 or were suspected to have experienced COVID-19 in the past (symptomatic group, n = 692) were enrolled between 28 September and 30 December 2020. Blood samples were tested by enzyme-linked immunosorbent assay D-5501 SARS-Cov-2-IgG-EIA-BEST and D-5502 SARS-Cov-2-IgM-EIA-BEST (AO Vector-Best, Novosibirsk, Russia). The overall seropositivity rate was 28.33-28.53%. SARS-CoV-2 antibodies were detected in 17.23% (adjusted prevalence of 17.17-17.29%) of participants in the high-risk and 45.95% (adjusted prevalence of 45.91-46.24%) in the symptomatic group. Higher IgG and IgM titers were observed in women compared to men, as well as in participants in the symptomatic group compared to those in the high-risk group. The results indicate that the seroprevalence among residents in several Russian regions is low (28.38%) and inadequate to provide herd immunity. The lower seroprevalence among participants in the high-risk group may be attributed to the enforcement of healthcare protocols and the use of adequate personal protective equipment.
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Affiliation(s)
- Alexandr Zurochka
- School of Medical Biology, South Ural State University, 454080 Chelyabinsk, Russia; (A.Z.); (V.Z.)
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
| | - Maria Dobrinina
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
| | - Vladimir Zurochka
- School of Medical Biology, South Ural State University, 454080 Chelyabinsk, Russia; (A.Z.); (V.Z.)
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
| | - Desheng Hu
- Department of Integrated Traditional Chinese and Western Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 200092, China;
| | - Alexandr Solovyev
- NPO National Medical Association for the Development of the Expert Activities in the Field of Laboratory Diagnostics “MedLabExpert”, 117042 Moscow, Russia;
- LCC GMK MEDMA, 620102 Ekaterinburg, Russia
| | - Liana Ryabova
- Department of Propedeutics of Internal Diseases, South Ural State Medical University, 454092 Chelyabinsk, Russia;
| | - Igor Kritsky
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
- Institute of Natural Sciences and Mathematics, Ural Federal University Named after the First President of Russia, 620026 Ekaterinburg, Russia
| | - Roman Ibragimov
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
- Institute of Natural Sciences and Mathematics, Ural Federal University Named after the First President of Russia, 620026 Ekaterinburg, Russia
| | - Alexey Sarapultsev
- School of Medical Biology, South Ural State University, 454080 Chelyabinsk, Russia; (A.Z.); (V.Z.)
- Institute of Immunology and Physiology, Ural Branch of the Russian Academy of Science, 620049 Ekaterinburg, Russia; (M.D.); (I.K.); (R.I.)
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Gladkikh A, Dolgova A, Dedkov V, Sbarzaglia V, Kanaeva O, Popova A, Totolian A. Characterization of a Novel SARS-CoV-2 Genetic Variant with Distinct Spike Protein Mutations. Viruses 2021; 13:v13061029. [PMID: 34072569 PMCID: PMC8230012 DOI: 10.3390/v13061029] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 05/27/2021] [Accepted: 05/27/2021] [Indexed: 01/20/2023] Open
Abstract
The COVID-19 pandemic, which began in Wuhan (Hubei, China), has been ongoing for about a year and a half. An unprecedented number of people around the world have been infected with SARS-CoV-2, the etiological agent of COVID-19. Despite the fact that the mortality rate for COVID-19 is relatively low, the total number of deaths has currently already reached more than three million and continues to increase due to high incidence. Since the beginning of the pandemic, a large number of sequences have been obtained and many genetic variants have been identified. Some of them bear significant mutations that affect biological properties of the virus. These genetic variants, currently Variants of Concern (VoC), include the so-called United Kingdom variant (20I/501Y), the Brazilian variant (20J/501Y.V3), and the South African variant (20H/501Y.V2). We describe here a novel SARS-CoV-2 variant with distinct spike protein mutations, first obtained at the end of January 2021 in northwest Russia. Therefore, it is necessary to pay attention to the dynamics of its spread among patients with COVID-19, as well as to study in detail its biological properties.
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Affiliation(s)
- Anna Gladkikh
- Saint Petersburg Pasteur Institute, 197101 Saint Petersburg, Russia; (A.G.); (A.D.); (V.S.); (O.K.); (A.T.)
| | - Anna Dolgova
- Saint Petersburg Pasteur Institute, 197101 Saint Petersburg, Russia; (A.G.); (A.D.); (V.S.); (O.K.); (A.T.)
| | - Vladimir Dedkov
- Saint Petersburg Pasteur Institute, 197101 Saint Petersburg, Russia; (A.G.); (A.D.); (V.S.); (O.K.); (A.T.)
- Martsinovsky Institute of Medical Parasitology, Tropical and Vector Borne Diseases, Sechenov First Moscow State Medical University, 119991 Moscow, Russia
- Correspondence: ; Tel.: +7-812-233-2149; Fax: +7-812-232-9217
| | - Valeriya Sbarzaglia
- Saint Petersburg Pasteur Institute, 197101 Saint Petersburg, Russia; (A.G.); (A.D.); (V.S.); (O.K.); (A.T.)
| | - Olga Kanaeva
- Saint Petersburg Pasteur Institute, 197101 Saint Petersburg, Russia; (A.G.); (A.D.); (V.S.); (O.K.); (A.T.)
| | - Anna Popova
- Federal Service for Surveillance on Consumer Rights Protection and Human Well-Being, 127994 Moscow, Russia;
| | - Areg Totolian
- Saint Petersburg Pasteur Institute, 197101 Saint Petersburg, Russia; (A.G.); (A.D.); (V.S.); (O.K.); (A.T.)
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47
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Nemira A, Adeniyi AE, Gasich EL, Bulda KY, Valentovich LN, Krasko AG, Glebova O, Kirpich A, Skums P. SARS-CoV-2 transmission dynamics in Belarus revealed by genomic and incidence data analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2021:2021.04.13.21255404. [PMID: 33907756 PMCID: PMC8077579 DOI: 10.1101/2021.04.13.21255404] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Since the emergence of COVID-19, a series of non-pharmaceutical interventions (NPIs) has been implemented by governments and public health authorities world-wide to control and curb the ongoing pandemic spread. From that perspective, Belarus is one of a few countries with a relatively modern healthcare system, where much narrower NPIs have been put in place. Given the uniqueness of this Belarusian experience, the understanding its COVID-19 epidemiological dynamics is essential not only for the local assessment, but also for a better insight into the impact of different NPI strategies globally. In this work, we integrate genomic epidemiology and surveillance methods to investigate the emergence and spread of SARS-CoV-2 in the country. The observed Belarusian SARS-CoV-2 genetic diversity originated from at least eighteen separate introductions, at least five of which resulted in on-going domestic transmissions. The introduction sources represent a wide variety of regions, although the proportion of regional virus introductions and exports from/to geographical neighbors appears to be higher than for other European countries. Phylodynamic analysis indicates a moderate reduction in the effective reproductive number ℛ e after the introduction of limited NPIs, with the reduction magnitude generally being lower than for countries with large-scale NPIs. On the other hand, the estimate of the Belarusian ℛ e at the early epidemic stage is comparable with this number for the neighboring ex-USSR country of Ukraine, where much broader NPIs have been implemented. The actual number of cases by the end of May, 2020 was predicted to be 2-9 times higher than the detected number of cases.
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Affiliation(s)
- Alina Nemira
- Department of Computer Science, Georgia State University, Atlanta, Georgia, USA
| | | | - Elena L. Gasich
- Republican Research and Practical Center for Epidemiology and Microbiology, Minsk, Belarus
| | - Kirill Y. Bulda
- Republican Research and Practical Center for Epidemiology and Microbiology, Minsk, Belarus
| | | | - Anatoly G. Krasko
- Republican Research and Practical Center for Epidemiology and Microbiology, Minsk, Belarus
| | - Olga Glebova
- Department of Computer Science, Georgia State University, Atlanta, Georgia, USA
| | - Alexander Kirpich
- Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia, USA
| | - Pavel Skums
- Department of Computer Science, Georgia State University, Atlanta, Georgia, USA
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