4.4 Article

Quantification of microtubule stutters: dynamic instability behaviors that are strongly associated with catastrophe

Journal

MOLECULAR BIOLOGY OF THE CELL
Volume 33, Issue 3, Pages -

Publisher

AMER SOC CELL BIOLOGY
DOI: 10.1091/mbc.E20-06-0348

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Funding

  1. National Science Foundation (NSF) [MCB-1244593, MCB-1817966, MCB-1817632]
  2. National Institutes of Health (NIH) [R35GM119552]
  3. National Institutes of Health Integrated Biological Systems Training in Oncology [T32CA119925]
  4. University of Massachusetts Amherst
  5. NSF-GFRP [DGE-1313583]
  6. Dolores Zohrab Liebmann Fund

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This article introduces a statistical tool called STADIA for automated dynamic instability analysis of microtubules (MTs). It demonstrates that stutters, which are intermediate behaviors during MT growth and shortening, precede most catastrophes, suggesting their mechanistic involvement in catastrophes. The study also reveals that the anticatastrophe factor CLASP2 promotes the return of stuttering MTs to growth. STADIA enables a more comprehensive and data-driven analysis of MT dynamics and provides new opportunities for studying the mechanisms and regulation of MT behavior.
Microtubules (MTs) are cytoskeletal fibers that undergo dynamic instability (DI), a remarkable process involving phases of growth and shortening separated by stochastic transitions called catastrophe and rescue. Dissecting DI mechanism(s) requires first characterizing and quantifying these dynamics, a subjective process that often ignores complexity in MT behavior. We present a Statistical Tool for Automated Dynamic Instability Analysis (STADIA) that identifies and quantifies not only growth and shortening, but also a category of intermediate behaviors that we term stutters. During stutters, the rate of MT length change tends to be smaller in magnitude than during typical growth or shortening phases. Quantifying stutters and other behaviors with STADIA demonstrates that stutters precede most catastrophes in our in vitro experiments and dimer-scale MT simulations, suggesting that stutters are mechanistically involved in catastrophes. Related to this idea, we show that the anticatastrophe factor CLASP2. works by promoting the return of stuttering MTs to growth. STADIA enables more comprehensive and data-driven analysis of MT dynamics compared with previous methods. The treatment of stutters as distinct and quantifiable DI behaviors provides new opportunities for analyzing mechanisms of MT dynamics and their regulation by binding proteins.

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