Evidence map›Paper›PMID 38950082›Full record

ArticlePLoS pathogens2024

Influenza A viral burst size from thousands of infected single cells using droplet quantitative PCR (dqPCR).

Geoffrey K Zath, Mallory M Thomas, Emma K Loveday, Dimitri A Bikos, Steven Sanche, Ruian Ke, Christopher B Brooke, Connie B Chang

Abstract read
In one paragraph

Article in PLoS pathogens, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Spatio-temporal modelling ofbioRxiv : the preprint server for biology · 2025
    Article
  6. Article
  7. Article
  8. Review
  9. Review
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

8 authors.

Geoffrey K ZathCenter for Biofilm Engineering, Montana State University, Bozeman, Montana, United States of America.
Mallory M ThomasCenter for Biofilm Engineering, Montana State University, Bozeman, Montana, United States of America.
Emma K LovedayCenter for Biofilm Engineering, Montana State University, Bozeman, Montana, United States of America.
Dimitri A BikosCenter for Biofilm Engineering, Montana State University, Bozeman, Montana, United States of America.
Steven SancheTheoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
Ruian KeTheoretical Biology and Biophysics, Los Alamos National Laboratory, Los Alamos, New Mexico, United States of America.
Christopher B BrookeDepartment of Microbiology, University of Illinois, Urbana-Champaign, Urbana, Illinois, United States of America.
Connie B ChangDepartment of Physiology and Biomedical Engineering, Mayo Clinic, Rochester, Minnesota, United States of America.ORCID 0000-0001-9555-8223

Funding

The effects of influenza virus genomic heterogeneity on replication dynamics and the host responseR01AI139246 · NIAID · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI BROOKE, CHRISTOPHER BYRON · 2018 to 2022
$1.9M
High-throughput droplet qRT-PCR microfluidic platform for quantification of virus from single cellsR56AI156137 · NIAID · MONTANA STATE UNIVERSITY - BOZEMAN · PI CHANG, CONNIE B · 2021 to 2021
$360k
NIAID NIH HHS R01 AI139246NIAID NIH HHS R56 AI156137
6 · The paper itself

Abstract

An important aspect of how viruses spread and infect is the viral burst size, or the number of new viruses produced by each infected cell. Surprisingly, this value remains poorly characterized for influenza A virus (IAV), commonly known as the flu. In this study, we screened tens of thousands of cells using a microfluidic method called droplet quantitative PCR (dqPCR). The high-throughput capability of dqPCR enabled the measurement of a large population of infected cells producing progeny virus. By measuring the fully assembled and successfully released viruses from these infected cells, we discover that the viral burst sizes for both the seasonal H3N2 and the 2009 pandemic H1N1 strains vary significantly, with H3N2 ranging from 101 to 104 viruses per cell, and H1N1 ranging from 101 to 103 viruses per cell. Some infected cells produce average numbers of new viruses, while others generate extensive number of viruses. In fact, we find that only 10% of the single-cell infections are responsible for creating a significant portion of all the viruses. This small fraction produced approximately 60% of new viruses for H3N2 and 40% for H1N1. On average, each infected cell of the H3N2 flu strain produced 709 new viruses, whereas for H1N1, each infected cell produced 358 viruses. This novel method reveals insights into the flu virus and can lead to improved strategies for managing and preventing the spread of viruses.

Indexed as

Influenza A Virus, H1N1 SubtypeInfluenza A Virus, H3N2 SubtypeInfluenza, HumanAnimalsDogsHumansInfluenza A virusMadin Darby Canine Kidney CellsReal-Time Polymerase Chain ReactionSingle-Cell AnalysisVirus Replication

Identifiers

PMID38950082
PMCPMC11244780

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.