Literature DB >> 31532393

Phylodynamic theory of persistence, extinction and speciation of rapidly adapting pathogens.

Le Yan1, Richard A Neher2, Boris I Shraiman1.   

Abstract

Rapidly evolving pathogens like influenza viruses can persist by changing their antigenic properties fast enough to evade the adaptive immunity, yet they rarely split into diverging lineages. By mapping the multi-strain Susceptible-Infected-Recovered model onto the traveling wave model of adapting populations, we demonstrate that persistence of a rapidly evolving, Red-Queen-like state of the pathogen population requires long-ranged cross-immunity and sufficiently large population sizes. This state is unstable and the population goes extinct or 'speciates' into two pathogen strains with antigenic divergence beyond the range of cross-inhibition. However, in a certain range of evolutionary parameters, a single cross-inhibiting population can exist for times long compared to the time to the most recent common ancestor ([Formula: see text]) and gives rise to phylogenetic patterns typical of influenza virus. We demonstrate that the rate of speciation is related to fluctuations of [Formula: see text] and construct a 'phase diagram' identifying different phylodynamic regimes as a function of evolutionary parameters.
© 2019, Yan et al.

Entities:  

Keywords:  evolution; extinction; host/pathogen; physics of living systems; speciation; virus

Mesh:

Substances:

Year:  2019        PMID: 31532393      PMCID: PMC6809594          DOI: 10.7554/eLife.44205

Source DB:  PubMed          Journal:  Elife        ISSN: 2050-084X            Impact factor:   8.140


  44 in total

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5.  Predicting evolution from the shape of genealogical trees.

Authors:  Richard A Neher; Colin A Russell; Boris I Shraiman
Journal:  Elife       Date:  2014-11-11       Impact factor: 8.140

6.  Genetic diversity and the structure of genealogies in rapidly adapting populations.

Authors:  Michael M Desai; Aleksandra M Walczak; Daniel S Fisher
Journal:  Genetics       Date:  2012-12-05       Impact factor: 4.562

7.  Traveling waves in a model of influenza A drift.

Authors:  Juan Lin; Viggo Andreasen; Renato Casagrandi; Simon A Levin
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8.  The genomic and epidemiological dynamics of human influenza A virus.

Authors:  Andrew Rambaut; Oliver G Pybus; Martha I Nelson; Cecile Viboud; Jeffery K Taubenberger; Edward C Holmes
Journal:  Nature       Date:  2008-04-16       Impact factor: 49.962

9.  Mapping person-to-person variation in viral mutations that escape polyclonal serum targeting influenza hemagglutinin.

Authors:  Juhye M Lee; Rachel Eguia; Seth J Zost; Saket Choudhary; Patrick C Wilson; Trevor Bedford; Terry Stevens-Ayers; Michael Boeckh; Aeron C Hurt; Seema S Lakdawala; Scott E Hensley; Jesse D Bloom
Journal:  Elife       Date:  2019-08-27       Impact factor: 8.140

10.  TreeTime: Maximum-likelihood phylodynamic analysis.

Authors:  Pavel Sagulenko; Vadim Puller; Richard A Neher
Journal:  Virus Evol       Date:  2018-01-08
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  7 in total

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Journal:  Proc Natl Acad Sci U S A       Date:  2022-05-31       Impact factor: 12.779

4.  Limited Predictability of Amino Acid Substitutions in Seasonal Influenza Viruses.

Authors:  Pierre Barrat-Charlaix; John Huddleston; Trevor Bedford; Richard A Neher
Journal:  Mol Biol Evol       Date:  2021-06-25       Impact factor: 16.240

5.  The evolutionary origin of the universal distribution of mutation fitness effect.

Authors:  Ayuna Barlukova; Igor M Rouzine
Journal:  PLoS Comput Biol       Date:  2021-03-08       Impact factor: 4.475

6.  Forecasting emergence of COVID-19 variants of concern.

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Journal:  PLoS One       Date:  2022-02-24       Impact factor: 3.240

7.  Antigenic waves of virus-immune coevolution.

Authors:  Jacopo Marchi; Michael Lässig; Aleksandra M Walczak; Thierry Mora
Journal:  Proc Natl Acad Sci U S A       Date:  2021-07-06       Impact factor: 11.205

  7 in total

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