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Related Experiment Videos

Force production by depolymerizing microtubules: load-velocity curves and run-pause statistics

C S Peskin1, G F Oster

  • 1Courant Institute of Mathematical Sciences, New York, New York 10012, USA.

Biophysical Journal
|December 1, 1995
PubMed
Summary

Microtubule depolymerization drives chromosome transport. A new model explains how ATP enhances this minus-end transport, even though ATP powers kinesin motors in the opposite direction.

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Area of Science:

  • Cell Biology
  • Biophysics
  • Molecular Motors

Background:

  • Microtubule depolymerization is known to drive minus-end-directed chromosome transport during mitosis.
  • In vitro experiments show a paradoxical enhancement of this transport by ATP, which normally fuels kinesin motors for plus-end movement.

Purpose of the Study:

  • To develop a mathematical model explaining the ATP-enhanced, depolymerization-driven, minus-end-directed transport of kinesin-coated microspheres.
  • To elucidate the mechanism behind the counterintuitive effect of ATP on microtubule-based transport.

Main Methods:

  • Development of a mathematical model incorporating microsphere-facilitated microtubule depolymerization.
  • Derivation of the force-velocity relationship for the modeled system.
  • Simulation of the stochastic process of microsphere transport and analysis of trajectory statistics.

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Main Results:

  • The model predicts that a microsphere at the microtubule plus end enhances depolymerization, thereby promoting minus-end transport.
  • A unique force-velocity curve was derived, showing maximal velocity at a positive load, not zero load.
  • Simulated trajectories exhibited characteristic runs and pauses, with statistics that allowed parameter determination.

Conclusions:

  • The mathematical model successfully explains the paradoxical enhancement of minus-end-directed transport by ATP.
  • The findings highlight a novel mechanism where motor proteins and depolymerization dynamics interact to regulate intracellular transport.
  • The model's predictive power and ability to determine parameters from simulated trajectories offer insights into motor protein behavior.