Literature DB >> 23382426

The evolutionary dynamics of receptor binding avidity in influenza A: a mathematical model for a new antigenic drift hypothesis.

Hsiang-Yu Yuan1, Katia Koelle.   

Abstract

The most salient feature of influenza evolution in humans is its antigenic drift. This process is characterized by structural changes in the virus's B-cell epitopes and ultimately results in the ability of the virus to evade immune recognition and thereby reinfect previously infected hosts. Until recently, amino acid substitutions in epitope regions of the viral haemagglutinin were thought to be positively selected for their ability to reduce antibody binding and therefore were thought to be responsible for driving antigenic drift. However, a recent hypothesis put forward by Hensley and co-workers posits that cellular receptor binding avidity is the dominant phenotype under selection, with antigenic drift being a side effect of these binding avidity changes. Here, we present a mathematical formulation of this new antigenic drift model and use it to show how rates of antigenic drift depend on epidemiological parameters. We further use the model to evaluate how two different vaccination strategies can impact antigenic drift rates and ultimately disease incidence levels. Finally, we discuss the assumptions present in the model formulation, predictions of the model, and future work that needs to be done to determine the consistency of this hypothesis with known patterns of influenza's genetic and antigenic evolution.

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Year:  2013        PMID: 23382426      PMCID: PMC3678328          DOI: 10.1098/rstb.2012.0204

Source DB:  PubMed          Journal:  Philos Trans R Soc Lond B Biol Sci        ISSN: 0962-8436            Impact factor:   6.237


  38 in total

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Authors:  W M Fitch; R M Bush; C A Bender; N J Cox
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2.  The influenza virus resource at the National Center for Biotechnology Information.

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3.  Prevention and Control of Influenza: recommendations of the Advisory Committee on Immunization Practices (ACIP).

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4.  Structural analysis of the hot spots in the binding between H1N1 HA and the 2D1 antibody: do mutations of H1N1 from 1918 to 2009 affect much on this binding?

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Journal:  Bioinformatics       Date:  2011-07-22       Impact factor: 6.937

5.  The dynamics of cocirculating influenza strains conferring partial cross-immunity.

Authors:  V Andreasen; J Lin; S A Levin
Journal:  J Math Biol       Date:  1997-08       Impact factor: 2.259

6.  Phenotypic expression of HA-NA combinations in human-avian influenza A virus reassortants.

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Journal:  Arch Virol       Date:  1996       Impact factor: 2.574

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Authors:  Martha I Nelson; Edward C Holmes
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8.  Absolute humidity and the seasonal onset of influenza in the continental United States.

Authors:  Jeffrey Shaman; Virginia E Pitzer; Cécile Viboud; Bryan T Grenfell; Marc Lipsitch
Journal:  PLoS Biol       Date:  2010-02-23       Impact factor: 8.029

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Authors:  Justin Lessler; Steven Riley; Jonathan M Read; Shuying Wang; Huachen Zhu; Gavin J D Smith; Yi Guan; Chao Qiang Jiang; Derek A T Cummings
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Review 10.  Non-pharmaceutical public health interventions for pandemic influenza: an evaluation of the evidence base.

Authors:  Julia E Aledort; Nicole Lurie; Jeffrey Wasserman; Samuel A Bozzette
Journal:  BMC Public Health       Date:  2007-08-15       Impact factor: 3.295

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  6 in total

1.  The effects of a deleterious mutation load on patterns of influenza A/H3N2's antigenic evolution in humans.

Authors:  Katia Koelle; David A Rasmussen
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2.  How sticky should a virus be? The impact of virus binding and release on transmission fitness using influenza as an example.

Authors:  Andreas Handel; Victoria Akin; Sergei S Pilyugin; Veronika Zarnitsyna; Rustom Antia
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3.  Evolutionary epidemiology: preparing for an age of genomic plenty.

Authors:  O G Pybus; C Fraser; A Rambaut
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2013-02-04       Impact factor: 6.237

4.  Human mobility networks and persistence of rapidly mutating pathogens.

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Journal:  R Soc Open Sci       Date:  2017-03-15       Impact factor: 2.963

Review 5.  An Antigenic Thrift-Based Approach to Influenza Vaccine Design.

Authors:  Jai S Bolton; Hannah Klim; Judith Wellens; Matthew Edmans; Uri Obolski; Craig P Thompson
Journal:  Vaccines (Basel)       Date:  2021-06-16

6.  The Evolutionary Dynamics of Stochastic Epidemic Model with Nonlinear Incidence Rate.

Authors:  Dan Li; Jing'an Cui; Meng Liu; Shengqiang Liu
Journal:  Bull Math Biol       Date:  2015-09-14       Impact factor: 1.758

  6 in total

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