↓ Skip to main content

Curvature-Sensitive Kinesin Binding Can Explain Microtubule Ring Formation and Reveals Chaotic Dynamics in a Mathematical Model

Overview of attention for article published in Bulletin of Mathematical Biology, September 2018
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

blogs
1 blog
twitter
7 X users

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
37 Mendeley
Title
Curvature-Sensitive Kinesin Binding Can Explain Microtubule Ring Formation and Reveals Chaotic Dynamics in a Mathematical Model
Published in
Bulletin of Mathematical Biology, September 2018
DOI 10.1007/s11538-018-0505-4
Pubmed ID
Authors

Simon P. Pearce, Matthias Heil, Oliver E. Jensen, Gareth Wyn Jones, Andreas Prokop

Abstract

Microtubules are filamentous tubular protein polymers which are essential for a range of cellular behaviour, and are generally straight over micron length scales. However, in some gliding assays, where microtubules move over a carpet of molecular motors, individual microtubules can also form tight arcs or rings, even in the absence of crosslinking proteins. Understanding this phenomenon may provide important explanations for similar highly curved microtubules which can be found in nerve cells undergoing neurodegeneration. We propose a model for gliding assays where the kinesins moving the microtubules over the surface induce ring formation through differential binding, substantiated by recent findings that a mutant version of the motor protein kinesin applied in solution is able to lock-in microtubule curvature. For certain parameter regimes, our model predicts that both straight and curved microtubules can exist simultaneously as stable steady states, as has been seen experimentally. Additionally, unsteady solutions are found, where a wave of differential binding propagates down the microtubule as it glides across the surface, which can lead to chaotic motion. Whilst this model explains two-dimensional microtubule behaviour in an experimental gliding assay, it has the potential to be adapted to explain pathological curling in nerve cells.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Researcher 7 19%
Student > Master 5 14%
Student > Bachelor 2 5%
Professor 2 5%
Other 4 11%
Unknown 8 22%
Readers by discipline Count As %
Physics and Astronomy 6 16%
Agricultural and Biological Sciences 6 16%
Mathematics 5 14%
Engineering 5 14%
Biochemistry, Genetics and Molecular Biology 4 11%
Other 4 11%
Unknown 7 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 01 November 2018.
All research outputs
#2,646,488
of 23,105,443 outputs
Outputs from Bulletin of Mathematical Biology
#66
of 1,106 outputs
Outputs of similar age
#56,517
of 341,609 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#3
of 41 outputs
Altmetric has tracked 23,105,443 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,106 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 94% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 341,609 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 41 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.