Evidence map›Paper›PMID 29889846›Full record

ArticlePLoS computational biology2018

Mechanical positioning of multiple nuclei in muscle cells.

Angelika Manhart, Stefanie Windner, Mary Baylies, Alex Mogilner

Abstract read
In one paragraph

Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
  2. Molecular regulation of myocyte fusion.Current topics in developmental biology · 2024
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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.

Angelika ManhartCourant Institute of Mathematical Sciences, New York University, New York, New York, United States of America.
Stefanie WindnerProgram in Developmental Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer, New York, New York, United States of America.
Mary BayliesProgram in Developmental Biology, Sloan Kettering Institute, Memorial Sloan Kettering Cancer, New York, New York, United States of America.ORCID 0000-0002-1626-8138
Alex MogilnerCourant Institute of Mathematical Sciences, New York University, New York, New York, United States of America.ORCID 0000-0001-5302-2404

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI SELWYN M VICKERS · 1985 to 2026
$347.4M
Mechanisms and Function of Myonuclear PositioningR01AR068128 · NIAMS · SLOAN-KETTERING INST CAN RESEARCH · PI BAYLIES, MARY K · 2014 to 2025
$5.1M
Sizing and Scaling in Functional Muscle CellsR01GM121971 · NIGMS · SLOAN-KETTERING INST CAN RESEARCH · PI BAYLIES, MARY K · 2017 to 2020
$1.8M
NCI NIH HHS P30 CA008748NIAMS NIH HHS R01 AR068128NIGMS NIH HHS R01 GM121971NIH HHS GM121971NIH HHS P30 CA 008748
6 · The paper itself

Abstract

Many types of large cells have multiple nuclei. In skeletal muscle fibers, the nuclei are distributed along the cell to maximize their internuclear distances. This myonuclear positioning is crucial for cell function. Although microtubules, microtubule associated proteins, and motors have been implicated, mechanisms responsible for myonuclear positioning remain unclear. We used a combination of rough interacting particle and detailed agent-based modeling to examine computationally the hypothesis that a force balance generated by microtubules positions the muscle nuclei. Rather than assuming the nature and identity of the forces, we simulated various types of forces between the pairs of nuclei and between the nuclei and cell boundary to position the myonuclei according to the laws of mechanics. We started with a large number of potential interacting particle models and computationally screened these models for their ability to fit biological data on nuclear positions in hundreds of Drosophila larval muscle cells. This reverse engineering approach resulted in a small number of feasible models, the one with the best fit suggests that the nuclei repel each other and the cell boundary with forces that decrease with distance. The model makes nontrivial predictions about the increased nuclear density near the cell poles, the zigzag patterns of the nuclear positions in wider cells, and about correlations between the cell width and elongated nuclear shapes, all of which we confirm by image analysis of the biological data. We support the predictions of the interacting particle model with simulations of an agent-based mechanical model. Taken together, our data suggest that microtubules growing from nuclear envelopes push on the neighboring nuclei and the cell boundaries, which is sufficient to establish the nearly-uniform nuclear spreading observed in muscle fibers.

Indexed as

AnimalsBiomechanical PhenomenaCell NucleusDrosophilaLarvaModels, BiologicalMuscle Fibers, Skeletal

Identifiers

PMID29889846
PMCPMC6013246

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.