Evidence map›Paper›PMID 28649958›Full record

ArticlePhysical biology2017

Modeling mechanical interactions in growing populations of rod-shaped bacteria.

James J Winkle, Oleg A Igoshin, Matthew R Bennett, Krešimir Josić, William Ott

Open access · greenAbstract read
In one paragraph

Article in Physical biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

17 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Dissecting the physics of bacterial biofilms with agent-based simulations.Current opinion in solid state & materials science · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Mutant-Dependent Local Orientational Correlation in Biofilms ofInternational journal of molecular sciences · 2023
    Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Moran Model of Spatial Alignment in Microbial Colonies.Physica D. Nonlinear phenomena · 2019
    Article
  14. Statistics of noisy growth with mechanical feedback in elastic tissues.Proceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  15. Modeling cell population dynamics.In silico biology · 2019
    Article
  16. Article
  17. 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

5 authors at 3 institutions in 1 country.

James J WinkleDepartment of Mathematics, University of Houston, Houston, TX, United States of America.
Oleg A IgoshinDepartment of Bioengineering, Rice University, Houston, TX, United States of America.
Matthew R BennettDepartment of Bioengineering, Rice University, Houston, TX, United States of America.
Krešimir JosićDepartment of Mathematics, University of Houston, Houston, TX, United States of America.
William OttDepartment of Mathematics, University of Houston, Houston, TX, United States of America.
University of Houston · USCenter for Theoretical Biological Physics · USRice University · US

Funding

Expanding the utility of transcriptional bacterial computingR01GM117138 · NIGMS · RICE UNIVERSITY · PI BENNETT, MATTHEW R., JOSIC, KRESIMIR · 2016 to 2019
$2.0M
Experimental and mathematical analysis of delay in transcripitional signalingR01GM104974 · NIGMS · RICE UNIVERSITY · PI BENNETT, MATTHEW R. · 2012 to 2016
$1.4M
NIGMS NIH HHS R01 GM104974NIGMS NIH HHS R01 GM117138
6 · The paper itself

Abstract

Advances in synthetic biology allow us to engineer bacterial collectives with pre-specified characteristics. However, the behavior of these collectives is difficult to understand, as cellular growth and division as well as extra-cellular fluid flow lead to complex, changing arrangements of cells within the population. To rationally engineer and control the behavior of cell collectives we need theoretical and computational tools to understand their emergent spatiotemporal dynamics. Here, we present an agent-based model that allows growing cells to detect and respond to mechanical interactions. Crucially, our model couples the dynamics of cell growth to the cell's environment: Mechanical constraints can affect cellular growth rate and a cell may alter its behavior in response to these constraints. This coupling links the mechanical forces that influence cell growth and emergent behaviors in cell assemblies. We illustrate our approach by showing how mechanical interactions can impact the dynamics of bacterial collectives growing in microfluidic traps.

Indexed as

BacteriaBiomechanical PhenomenaCell ProliferationModels, BiologicalSynthetic Biology

Identifiers

PMID28649958
PMCPMC5745163
OpenAlexW2952788753

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.