Deconvolving mutational patterns of poliovirus outbreaks reveals its intrinsic fitness landscape

  • Ahmed A. Quadeer
  • , John P. Barton
  • , Arup K. Chakraborty
  • , Matthew R. McKay

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Vaccination has essentially eradicated poliovirus. Yet, its mutation rate is higher than that of viruses like HIV, for which no effective vaccine exists. To investigate this, we infer a fitness model for the poliovirus viral protein 1 (vp1), which successfully predicts in vitro fitness measurements. This is achieved by first developing a probabilistic model for the prevalence of vp1 sequences that enables us to isolate and remove data that are subject to strong vaccine-derived biases. The intrinsic fitness constraints derived for vp1, a capsid protein subject to antibody responses, are compared with those of analogous HIV proteins. We find that vp1 evolution is subject to tighter constraints, limiting its ability to evade vaccine-induced immune responses. Our analysis also indicates that circulating poliovirus strains in unimmunized populations serve as a reservoir that can seed outbreaks in spatio-temporally localized sub-optimally immunized populations.

Original languageEnglish
Article number377
JournalNature Communications
Volume11
Issue number1
DOIs
StatePublished - 17 Jan 2020
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2020, The Author(s).

Funding

This work was initiated upon a discussion between A.K.C. and David Baltimore. We thank Raymond Louie and Saqib Sohail for helpful discussions. This research was funded by the Hong Kong Research Grant Council General Research Fund with Project 16234716 (to M.R.M.), and a Harilela endowment (to M.R.M.). A.A.Q. was supported by the Hong Kong Ph.D. Fellowship Scheme (HKPFS) and A.K.C. was supported by the Ragon Institute of MGH, MIT, & Harvard.

FundersFunder number
Hong Kong Research Grant Council General Research Fund16234716
Massachusetts General Hospital
Massachusetts Institute of Technology
Ragon Institute of MGH, MIT and Harvard

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

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