Evidence map›Paper›PMID 24622509›Full record

ArticleSoft matter2014

Hyperswarming adaptations in a bacterium improve collective motility without enhancing single cell motility.

Maxime Deforet, Dave van Ditmarsch, Carlos Carmona-Fontaine, Joao B Xavier

Abstract read
In one paragraph

Article in Soft matter, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.3field-weighted citation impact, top 8% of its field
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

18 citing papers in PubMed, 33 citations in OpenAlex.

  1. Article
  2. Article
  3. Swarming ofBiophysics reviews · 2023
    Review
  4. Article
  5. Review
  6. Evidence for biosurfactant-induced flow in corners and bacterial spreading in unsaturated porous media.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Metabolism and the Evolution of Social Behavior.Molecular biology and evolution · 2017
    Article
  13. Article
  14. Inhibition ofChemical science · 2016
    Article
  15. Article
  16. Article
  17. Article
  18. Type IV pili interactions promote intercellular association and moderate swarming of Pseudomonas aeruginosa.Proceedings of the National Academy of Sciences of the United States of America · 2014
    Article
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 at 3 institutions in 2 countries.

Maxime DeforetProgram in Computational Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA. xavierj@mskcc.org.
Dave van Ditmarsch
Carlos Carmona-Fontaine
Joao B Xavier
Memorial Sloan Kettering Cancer Center · USLaboratoire Jean Perrin · FRNew York University · US

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Engineering microbial social interactions: Towards new anti-biofilm therapiesDP2OD008440 · OD · SLOAN-KETTERING INST CAN RESEARCH · PI XAVIER, JOAO · 2011 to 2015
$2.9M
NCI NIH HHS P30 CA008748NCI NIH HHS U54 CA14896704NIH HHS DP2 OD008440NIH HHS DP2OD008440
6 · The paper itself

Abstract

Pseudomonas aeruginosa is a monoflagellated bacterium that can use its single polar flagellum to swim through liquids and move collectively over semisolid surfaces, a behavior called swarming. Previous studies have shown that experimental evolution in swarming colonies leads to the selection of hyperswarming bacteria with multiple flagella. Here we show that the advantage of such hyperswarmer mutants cannot be explained simply by an increase in the raw swimming speed of individual bacteria in liquids. Cell tracking of time-lapse microscopy to quantify single-cell swimming patterns reveals that both wild-type and hyperswarmers alternate between forward and backward runs, rather than doing the run-and-tumble characteristic of enteric bacteria such as E. coli. High-throughput measurement of swimming speeds reveals that hyperswarmers do not swim faster than wild-type in liquid. Wild-type reverses swimming direction in sharp turns without a significant impact on its speed, whereas multiflagellated hyperswarmers tend to alternate fast and slow runs and have wider turning angles. Nonetheless, macroscopic measurement of swimming and swarming speed in colonies shows that hyperswarmers expand faster than wild-type on surfaces and through soft agar matrices. A mathematical model explains how wider turning angles lead to faster spreading when swimming through agar. Our study describes for the first time the swimming patterns in multiflagellated P. aeruginosa mutants and reveals that collective and individual motility in bacteria are not necessarily correlated. Understanding bacterial adaptations to surface motility, such as hyperswarming, requires a collective behavior approach.

Indexed as

Adaptation, PhysiologicalBacterial AdhesionModels, BiologicalMutationPseudomonas aeruginosaQuorum Sensing

Identifiers

PMID24622509
PMCPMC3955847
OpenAlexW2154514017

What OpenQuestion holds

Textmetadata
LicenceTDM
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.