Evidence map›Paper›PMID 28415180›Full record

ArticlePhysical review. E2017

Reversals and collisions optimize protein exchange in bacterial swarms.

Aboutaleb Amiri, Cameron Harvey, Amy Buchmann, Scott Christley, Joshua D Shrout, Igor S Aranson, Mark Alber

Open access · greenAbstract read
In one paragraph

Article in Physical review. E, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.9field-weighted citation impact, top 27% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 3 institutions in 1 country.

Aboutaleb AmiriDepartment of Physics, University of Notre Dame, Notre Dame, Indiana 46556, USA.
Cameron HarveyDepartment of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, Indiana 46556, USA.
Amy BuchmannDepartment of Mathematics, Tulane University, New Orleans, Louisiana 70118, USA.
Scott ChristleyUT Southwestern Medical Center, Dallas, Texas 75390, USA.
Joshua D ShroutDepartment of Civil and Environmental Engineering, University of Notre Dame, Notre Dame, Indiana 46556, USA.
Igor S AransonDepartment of Biomedical Engineering, Pennsylvania State University, University Park, Pennsylvania 16802, USA and Materials Science Division, Argonne National Laboratory, Argonne, Illinois 60439, USA.
Mark AlberDepartment of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, Indiana 46556, USA and Department of Mathematics, University of California, Riverside, California 92521, USA.
University of Notre Dame · USSouthwestern Medical CenterTulane University · US

Funding

Combined multiscale modeling and experimental study of bacterial swarmingR01GM095959 · NIGMS · UNIVERSITY OF NOTRE DAME · PI ALBER, MARK · 2012 to 2015
$1.1M
Study of the interplay of motility mechanisms during swaming of Myxococcus xanthuR01GM100470 · NIGMS · UNIVERSITY OF NOTRE DAME · PI ALBER, MARK · 2011 to 2013
$770k
NIGMS NIH HHS R01 GM095959NIGMS NIH HHS R01 GM100470
6 · The paper itself

Abstract

Swarming groups of bacteria coordinate their behavior by self-organizing as a population to move over surfaces in search of nutrients and optimal niches for colonization. Many open questions remain about the cues used by swarming bacteria to achieve this self-organization. While chemical cue signaling known as quorum sensing is well-described, swarming bacteria often act and coordinate on time scales that could not be achieved via these extracellular quorum sensing cues. Here, cell-cell contact-dependent protein exchange is explored as a mechanism of intercellular signaling for the bacterium Myxococcus xanthus. A detailed biologically calibrated computational model is used to study how M. xanthus optimizes the connection rate between cells and maximizes the spread of an extracellular protein within the population. The maximum rate of protein spreading is observed for cells that reverse direction optimally for swarming. Cells that reverse too slowly or too fast fail to spread extracellular protein efficiently. In particular, a specific range of cell reversal frequencies was observed to maximize the cell-cell connection rate and minimize the time of protein spreading. Furthermore, our findings suggest that predesigned motion reversal can be employed to enhance the collective behavior of biological synthetic active systems.

Indexed as

Bacterial Physiological PhenomenaModels, BiologicalBacterial ProteinsComputer SimulationMovementMyxococcus xanthusTime FactorsBacterial Proteins

Identifiers

PMID28415180
PMCPMC5508969
OpenAlexW2595724674

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.