Evidence map›Paper›PMID 31953427›Full record

ArticleNature communications2020

Deconvolving mutational patterns of poliovirus outbreaks reveals its intrinsic fitness landscape.

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

Abstract read
In one paragraph

Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed.

  1. Review
  2. Bioengineering hybrid artificial life.Frontiers in bioinformatics · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ahmed A QuadeerDepartment of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China.ORCID http://orcid.org/0000-0002-5295-9067
John P BartonDepartment of Physics and Astronomy, University of California, Riverside, CA, 92521, USA.
Arup K ChakrabortyDepartment of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA. arupc@mit.edu.
Matthew R McKayDepartment of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China. m.mckay@ust.hk.ORCID http://orcid.org/0000-0002-8086-2545

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Genetic FitnessMutationMutation RateAntigens, ViralCapsid ProteinsComputational BiologyDisease OutbreaksEvolution, MolecularHIVHumansModels, GeneticPhylogenyPoliomyelitisPoliovirusPrevalenceProbabilityAntigens, ViralCapsid ProteinsViral ProteinsViral VaccinesVP1 protein, Poliovirus

Identifiers

PMID31953427
PMCPMC6969152

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.