Evidence map›Paper›PMID 28170438›Full record

ArticlePLoS pathogens2017

The effective rate of influenza reassortment is limited during human infection.

Ashley Sobel Leonard, Micah T McClain, Gavin J D Smith, David E Wentworth, Rebecca A Halpin, Xudong Lin, Amy Ransier, Timothy B Stockwell, Suman R Das, Anthony S Gilbert and 5 more

Abstract read
In one paragraph

Article in PLoS pathogens, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 1 pooled it
–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

34 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

15 authors.

Ashley Sobel LeonardDepartment of Biology, Duke University, Durham, North Carolina, United States of America.
Micah T McClainDuke Center for Applied Genomics and Precision Medicine, Durham, North Carolina, United States of America.
Gavin J D SmithProgramme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore.ORCID 0000-0001-5031-468X
David E WentworthJ. Craig Venter Institute, Rockville, Maryland, United States of America.
Rebecca A HalpinJ. Craig Venter Institute, Rockville, Maryland, United States of America.
Xudong LinJ. Craig Venter Institute, Rockville, Maryland, United States of America.
Amy RansierJ. Craig Venter Institute, Rockville, Maryland, United States of America.
Timothy B StockwellJ. Craig Venter Institute, Rockville, Maryland, United States of America.ORCID 0000-0002-3595-4539
Suman R DasJ. Craig Venter Institute, Rockville, Maryland, United States of America.ORCID 0000-0003-2496-9724
Anthony S GilberthVivo PLC, The QMB Innovation Centre, Queen Mary, University of London, London, United Kingdom.
Rob Lambkin-WilliamshVivo PLC, The QMB Innovation Centre, Queen Mary, University of London, London, United Kingdom.ORCID 0000-0003-2107-0174
Geoffrey S GinsburgDuke Center for Applied Genomics and Precision Medicine, Durham, North Carolina, United States of America.ORCID 0000-0003-4739-9808
Christopher W WoodsDuke Center for Applied Genomics and Precision Medicine, Durham, North Carolina, United States of America.
Katia KoelleDepartment of Biology, Duke University, Durham, North Carolina, United States of America.
Christopher J R IllingworthDepartment of Genetics, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0002-0030-2784

Funding

MEDICAL SCIENTIST TRAINING PROGRAMT32GM007171 · NIGMS · DUKE UNIVERSITY · PI KONTOS, CHRISTOPHER D · 1985 to 2021
$31.2M
The J. Craig Venter Institute Genome Center for Infectious DiseasesU19AI110819 · NIAID · J. CRAIG VENTER INSTITUTE, INC. · PI TAN, GENE · 2014 to 2018
$29.7M
Resource Core 3 - Metabolomics CoreP30AG028716 · NIA · DUKE UNIVERSITY · PI Virginia B Kraus · 2006 to 2026
$24.6M
Understanding Transmission with Integrated Genetic and Epidemiologic InferenceU54GM111274 · NIGMS · FRED HUTCHINSON CANCER RESEARCH CENTER · PI VESPIGNANI, ALESSANDRO · 2014 to 2018
$12.5M
NIAID NIH HHS HHSN272200900007CNIAID NIH HHS HHSN272201400006CNIAID NIH HHS U19 AI110819NIA NIH HHS P30 AG028716NIGMS NIH HHS T32 GM007171NIGMS NIH HHS U54 GM111274Wellcome Trust 101239/Z/13/Z
6 · The paper itself

Abstract

We characterise the evolutionary dynamics of influenza infection described by viral sequence data collected from two challenge studies conducted in human hosts. Viral sequence data were collected at regular intervals from infected hosts. Changes in the sequence data observed across time show that the within-host evolution of the virus was driven by the reversion of variants acquired during previous passaging of the virus. Treatment of some patients with oseltamivir on the first day of infection did not lead to the emergence of drug resistance variants in patients. Using an evolutionary model, we inferred the effective rate of reassortment between viral segments, measuring the extent to which randomly chosen viruses within the host exchange genetic material. We find strong evidence that the rate of effective reassortment is low, such that genetic associations between polymorphic loci in different segments are preserved during the course of an infection in a manner not compatible with epistasis. Combining our evidence with that of previous studies we suggest that spatial heterogeneity in the viral population may reduce the extent to which reassortment is observed. Our results do not contradict previous findings of high rates of viral reassortment in vitro and in small animal studies, but indicate that in human hosts the effective rate of reassortment may be substantially more limited.

Indexed as

Models, GeneticHumansInfluenza, HumanOrthomyxoviridaeSelection, Genetic

Identifiers

PMID28170438
PMCPMC5315410

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.