Evidence map›Paper›PMID 39523366›Full record

ArticleNature communications2024

Mechanical power is maximized during contractile ring-like formation in a biomimetic dividing cell model.

Ryota Sakamoto, Michael P Murrell

Erratum issuedAbstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. 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.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Ryota SakamotoDepartment of Biomedical Engineering, Yale University, 10 Hillhouse Avenue, New Haven, CT, USA. ryota.sakamoto@yale.edu.ORCID 0000-0002-7762-3682
Michael P MurrellDepartment of Biomedical Engineering, Yale University, 10 Hillhouse Avenue, New Haven, CT, USA. michael.murrell@yale.edu.ORCID 0000-0001-6788-2077

Funding

Systems analysis of phenotypic switch in control of cancer invasionU54CA209992 · NCI · YALE UNIVERSITY · PI LEVCHENKO, ANDRE · 2016 to 2021
$10.1M
Universal Roles of Force Generation and Transmission in Biological SystemsR01GM126256 · NIGMS · PURDUE UNIVERSITY · PI KIM, TAEYOON · 2017 to 2021
$2.3M
Human Frontier Science Program (HFSP) RGY0073/2018NCI NIH HHS U54 CA209992NIGMS NIH HHS R01 GM126256Yale University (Yale) Yale start-up funds
6 · The paper itself

Abstract

The spatial and temporal dynamics of forces in cells coordinate essential behaviors like division, polarization, and migration. While intracellular signaling initiates contractile ring assembly during cell division, how mechanical forces coordinate division and their energetic costs remain unclear. Here, we develop an in vitro model where myosin-induced stress drives division-like shape changes in giant unilamellar vesicles (GUVs, liposomes). Myosin activity is controlled by light patterns globally or locally at the equator. Global activation causes slow, shallow cleavage furrows due to a tug-of-war between the equatorial and polar forces. By contrast, local activation leads to faster, deeper, and symmetric division as equatorial forces dominate. Dissociating the actin cortex at the poles is crucial for inducing significant furrowing. During furrowing, actomyosin flows align actin filaments parallel to the division plane, forming a contractile ring-like structure. Mechanical power is not greatest during contraction, but is maximized just before furrowing. This study reveals the quantitative relationship between force patterning and mechanical energy during division-like shape changes, providing insights into cell division mechanics.

Indexed as

ActomyosinCell DivisionActin CytoskeletonActinsAnimalsBiomechanical PhenomenaBiomimeticsModels, BiologicalMyosinsUnilamellar LiposomesActinsActomyosinMyosinsUnilamellar Liposomes

Identifiers

PMID39523366
PMCPMC11551154

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Registered trials

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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.