Self-capping of nucleoprotein filaments protects Newcastle Disease Virus genome
- Kunming Medical University, China
- ShanghaiTech University, China
- Chinese Academy of Sciences, China
- Yangzhou University, China
- Fujian Normal University, China
Abstract
Non-segmented negative-strand RNA viruses, such as Measles, Ebola and Newcastle disease viruses (NDV), encapsidate viral genomic RNAs into helical nucleocapsids which serve as the template for viral replication and transcription. Here, the clam-shaped nucleocapsid structure, where the NDV viral genome is sequestered, was determined at 4.8 Å resolution by cryo-electron microscopy. The clam-shaped structure is composed of two single-turn spirals packed in a back-to-back mode, and the tightly packed structure functions as a seed for nucleocapsid to assemble from both directions and grows into double-headed filaments with two separate RNA strings inside. Disruption of this structure by mutations on its loop interface yielded a single-headed unfunctional filament.
Data availability
The cryo-EM density map has been deposited in EMDB with the accession number EMD-9793. The atom coordinates of the structure have been deposited in PDB with the PDB ID 6JC3.
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The Cryo-EM structure of nucleoprotein-RNA complex of Newcastle disease virusRCSB Protein Data Bank, 6JC3.
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The Cryo-EM structure of nucleoprotein-RNA complex of Newcastle disease virusElectron Microscopy Data Bank, EMD-9793.
Article and author information
Author details
Funding
National Nature Science Foundation of China grant (31330019)
- Zhi-Jie Liu
National Nature Science Foundation of China grant (31770948)
- Songying Ouyang
National Nature Science Foundation of China grant (31570875)
- Songying Ouyang
National Natural Science Foundation of China grant (81590761)
- Songying Ouyang
the National Key R&D program of China (2017YFA0504800)
- Qing-Tao Shen
Yunnan Provincial Science and Technology Department Project (2016FC007)
- Zhi-Jie Liu
The Pujiang Talent program (17PJ1406700)
- Qing-Tao Shen
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Song et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Self-capping of nucleoprotein filaments protects Newcastle Disease Virus genome
eLife 8:e45057.
https://doi.org/10.7554/eLife.45057
Further reading
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- Immunology and Inflammation
- Microbiology and Infectious Disease
Coronavirus disease 2019 (COVID-19) is a respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that displays great variability in clinical phenotype. Many factors have been described to be correlated with its severity, and microbiota could play a key role in the infection, progression, and outcome of the disease. SARS-CoV-2 infection has been associated with nasopharyngeal and gut dysbiosis and higher abundance of opportunistic pathogens. To identify new prognostic markers for the disease, a multicentre prospective observational cohort study was carried out in COVID-19 patients divided into three cohorts based on symptomatology: mild (n = 24), moderate (n = 51), and severe/critical (n = 31). Faecal and nasopharyngeal samples were taken, and the microbiota was analysed. Linear discriminant analysis identified Mycoplasma salivarium, Prevotella dentalis, and Haemophilus parainfluenzae as biomarkers of severe COVID-19 in nasopharyngeal microbiota, while Prevotella bivia and Prevotella timonensis were defined in faecal microbiota. Additionally, a connection between faecal and nasopharyngeal microbiota was identified, with a significant ratio between P. timonensis (faeces) and P. dentalis and M. salivarium (nasopharyngeal) abundances found in critically ill patients. This ratio could serve as a novel prognostic tool for identifying severe COVID-19 cases.
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- Epidemiology and Global Health
- Microbiology and Infectious Disease
Background:
In many settings, a large fraction of the population has both been vaccinated against and infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, quantifying the protection provided by post-infection vaccination has become critical for policy. We aimed to estimate the protective effect against SARS-CoV-2 reinfection of an additional vaccine dose after an initial Omicron variant infection.
Methods:
We report a retrospective, population-based cohort study performed in Shanghai, China, using electronic databases with information on SARS-CoV-2 infections and vaccination history. We compared reinfection incidence by post-infection vaccination status in individuals initially infected during the April–May 2022 Omicron variant surge in Shanghai and who had been vaccinated before that period. Cox models were fit to estimate adjusted hazard ratios (aHRs).
Results:
275,896 individuals were diagnosed with real-time polymerase chain reaction-confirmed SARS-CoV-2 infection in April–May 2022; 199,312/275,896 were included in analyses on the effect of a post-infection vaccine dose. Post-infection vaccination provided protection against reinfection (aHR 0.82; 95% confidence interval 0.79–0.85). For patients who had received one, two, or three vaccine doses before their first infection, hazard ratios for the post-infection vaccination effect were 0.84 (0.76–0.93), 0.87 (0.83–0.90), and 0.96 (0.74–1.23), respectively. Post-infection vaccination within 30 and 90 days before the second Omicron wave provided different degrees of protection (in aHR): 0.51 (0.44–0.58) and 0.67 (0.61–0.74), respectively. Moreover, for all vaccine types, but to different extents, a post-infection dose given to individuals who were fully vaccinated before first infection was protective.
Conclusions:
In previously vaccinated and infected individuals, an additional vaccine dose provided protection against Omicron variant reinfection. These observations will inform future policy decisions on COVID-19 vaccination in China and other countries.
Funding:
This study was funded the Key Discipline Program of Pudong New Area Health System (PWZxk2022-25), the Development and Application of Intelligent Epidemic Surveillance and AI Analysis System (21002411400), the Shanghai Public Health System Construction (GWVI-11.2-XD08), the Shanghai Health Commission Key Disciplines (GWVI-11.1-02), the Shanghai Health Commission Clinical Research Program (20214Y0020), the Shanghai Natural Science Foundation (22ZR1414600), and the Shanghai Young Health Talents Program (2022YQ076).
