Coupling Between Atpase and Force-Generating Attachment-Detachment Cycles of Actomyosin In Vitro
Part of the
Advances in Experimental Medicine and Biology
book series (AEMB, volume 332)
We have developed a high resolution force measurement system in vitro by manipulating a single actin filament attached to a microneedle. The system could resolve forces less than a piconewton, and has time resolution in the submillisecond range. We have used this system to detect force fluctuations produced by individual molecular interactions. We observed large force fluctuations during isometric force generations. Noise analysis of the force fluctuations showed that the force was produced by stochastic and independent attachment-detachment cycles between actin and myosin heads, and one force-generating attachment-detachment cycle corresponded to each ATPase cycle. But, the force fluctuations almost completely disappeared during sliding at the velocities of 20 to 70% of the maximum one at zero load. The analysis indicated that myosin heads produced an almost constant force for most (probably > 70%) of the ATPase cycle time, i. e., the duty ratio > 0.7. Since the myosin step size was given as (velocity) × (the duty ratio) × (the ATPase cycle time, 30 ms), it was calculated to be 40 to 110 nm, corresponding to velocities of 20 to 70 % of the maximum one (9μm/s), respectively. These values are much greater than the displacement by a single attachment-detachment cycle of actomyosin (10–20 nm), indicating that multiple force-generating attachment-detachment cycles correspond to each ATPase cycle during sliding at velocities of > 20 % of the maximum one. In conclusion, the coupling between the ATPase and the force-generating attachment-detachment cycles of actomyosin is not rigidly determined in a one-to-one fashion but is variable depending on the load.
KeywordsActin Filament Power Density Spectrum Myosin Head Duty Ratio Thick Filament
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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