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Quantitative Characterization of Glycan-Receptor Binding of H9N2 Influenza A Virus Hemagglutinin

Overview of attention for article published in PLOS ONE, April 2013
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Title
Quantitative Characterization of Glycan-Receptor Binding of H9N2 Influenza A Virus Hemagglutinin
Published in
PLOS ONE, April 2013
DOI 10.1371/journal.pone.0059550
Pubmed ID
Authors

Karunya Srinivasan, Rahul Raman, Akila Jayaraman, Karthik Viswanathan, Ram Sasisekharan

Abstract

Avian influenza subtypes such as H5, H7 and H9 are yet to adapt to the human host so as to establish airborne transmission between humans. However, lab-generated reassorted viruses possessing hemagglutinin (HA) and neuraminidase (NA) genes from an avian H9 isolate and other genes from a human-adapted (H3 or H1) subtype acquired two amino acid changes in HA and a single amino acid change in NA that confer respiratory droplet transmission in ferrets. We previously demonstrated for human-adapted H1, H2 and H3 subtypes that quantitative binding affinity of their HA to α2→6 sialylated glycan receptors correlates with respiratory droplet transmissibility of the virus in ferrets. Such a relationship remains to be established for H9 HA. In this study, we performed a quantitative biochemical characterization of glycan receptor binding properties of wild-type and mutant forms of representative H9 HAs that were previously used in context of reassorted viruses in ferret transmission studies. We demonstrate here that distinct molecular interactions in the glycan receptor-binding site of different H9 HAs affect the glycan-binding specificity and affinity. Further we show that α2→6 glycan receptor-binding affinity of a mutant H9 HA carrying Thr-189→Ala amino acid change correlates with the respiratory droplet transmission in ferrets conferred by this change. Our findings contribute to a framework for monitoring the evolution of H9 HA by understanding effects of molecular changes in HA on glycan receptor-binding properties.

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Geographical breakdown

Country Count As %
United States 1 3%
Unknown 28 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 28%
Student > Ph. D. Student 5 17%
Student > Bachelor 4 14%
Student > Master 4 14%
Other 1 3%
Other 3 10%
Unknown 4 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 41%
Immunology and Microbiology 4 14%
Veterinary Science and Veterinary Medicine 3 10%
Chemistry 2 7%
Medicine and Dentistry 1 3%
Other 1 3%
Unknown 6 21%