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Computational predicting the human infectivity of H7N9 influenza viruses isolated from avian hosts.
Sun, Yeping; Zhang, Kun; Qi, Heyuan; Zhang, He; Zhang, Shuang; Bi, Yuhai; Wu, Linhuan; Sun, Lei; Qi, Jianxun; Liu, Di; Ma, Juncai; Tien, Po; Liu, Wenjun; Li, Jing.
Affiliation
  • Sun Y; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Zhang K; Philips Institute for Oral Health Research, School of Dentistry, Virginia Commonwealth University, Richmond, Virginia, USA.
  • Qi H; Information Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Zhang H; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Zhang S; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Bi Y; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Wu L; Information Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Sun L; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Qi J; Savaid Medical School, University of Chinese Academy of Sciences, Beijing, China.
  • Liu D; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Ma J; CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China.
  • Tien P; Information Center, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Liu W; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
  • Li J; CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China.
Transbound Emerg Dis ; 68(2): 846-856, 2021 Mar.
Article in En | MEDLINE | ID: mdl-32706427
ABSTRACT
The genome composition of a given avian influenza virus is the primary determinant of its potential for cross-species transmission from birds to humans. Here, we introduce a viral genome-based computational tool that can be used to evaluate the human infectivity of avian isolates of influenza A H7N9 viruses, which can enable prediction of the potential risk of these isolates infecting humans. This tool, which is based on a novel class weight-biased logistic regression (CWBLR) algorithm, uses the sequences of the eight genome segments of an H7N9 strain as the input and gives the probability of this strain infecting humans (reflecting its human infectivity). We examined the replication efficiency and the pathogenicity of several H7N9 avian isolates that were predicted to have very low or high human infectivity by the CWBLR model in cell culture and in mice, and found that the strains with high predicted human infectivity replicated more efficiently in mammalian cells and were more infective in mice than those that were predicted to have low human infectivity. These results demonstrate that our CWBLR model can serve as a powerful tool for predicting the human infectivity and cross-species transmission risks of H7N9 avian strains.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Influenza, Human / Influenza A Virus, H7N9 Subtype / Influenza in Birds Type of study: Prognostic_studies / Risk_factors_studies Limits: Animals / Humans Language: En Journal: Transbound Emerg Dis Journal subject: MEDICINA VETERINARIA Year: 2021 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Influenza, Human / Influenza A Virus, H7N9 Subtype / Influenza in Birds Type of study: Prognostic_studies / Risk_factors_studies Limits: Animals / Humans Language: En Journal: Transbound Emerg Dis Journal subject: MEDICINA VETERINARIA Year: 2021 Document type: Article Affiliation country: China