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

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,...

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Autores principales: Mahserejian, Shant M., Scripture, Jared P., Mauro, Ava J., Lawrence, Elizabeth J., Jonasson, Erin M., Murray, Kristopher S., Li, Jun, Gardner, Melissa, Alber, Mark, Zanic, Marija, Goodson, Holly V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The American Society for Cell Biology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250389/
https://www.ncbi.nlm.nih.gov/pubmed/35108073
http://dx.doi.org/10.1091/mbc.E20-06-0348
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author Mahserejian, Shant M.
Scripture, Jared P.
Mauro, Ava J.
Lawrence, Elizabeth J.
Jonasson, Erin M.
Murray, Kristopher S.
Li, Jun
Gardner, Melissa
Alber, Mark
Zanic, Marija
Goodson, Holly V.
author_facet Mahserejian, Shant M.
Scripture, Jared P.
Mauro, Ava J.
Lawrence, Elizabeth J.
Jonasson, Erin M.
Murray, Kristopher S.
Li, Jun
Gardner, Melissa
Alber, Mark
Zanic, Marija
Goodson, Holly V.
author_sort Mahserejian, Shant M.
collection PubMed
description 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 CLASP2γ 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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spelling pubmed-92503892022-07-07 Quantification of microtubule stutters: dynamic instability behaviors that are strongly associated with catastrophe Mahserejian, Shant M. Scripture, Jared P. Mauro, Ava J. Lawrence, Elizabeth J. Jonasson, Erin M. Murray, Kristopher S. Li, Jun Gardner, Melissa Alber, Mark Zanic, Marija Goodson, Holly V. Mol Biol Cell Articles 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 CLASP2γ 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. The American Society for Cell Biology 2022-02-28 /pmc/articles/PMC9250389/ /pubmed/35108073 http://dx.doi.org/10.1091/mbc.E20-06-0348 Text en © 2022 Mahserejian, Scripture, et al. “ASCB®,” “The American Society for Cell Biology®,” and “Molecular Biology of the Cell®” are registered trademarks of The American Society for Cell Biology. https://creativecommons.org/licenses/by-nc-sa/4.0/This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication it is available to the public under an Attribution–Noncommercial-Share Alike 4.0 International Creative Commons License.
spellingShingle Articles
Mahserejian, Shant M.
Scripture, Jared P.
Mauro, Ava J.
Lawrence, Elizabeth J.
Jonasson, Erin M.
Murray, Kristopher S.
Li, Jun
Gardner, Melissa
Alber, Mark
Zanic, Marija
Goodson, Holly V.
Quantification of microtubule stutters: dynamic instability behaviors that are strongly associated with catastrophe
title Quantification of microtubule stutters: dynamic instability behaviors that are strongly associated with catastrophe
title_full Quantification of microtubule stutters: dynamic instability behaviors that are strongly associated with catastrophe
title_fullStr Quantification of microtubule stutters: dynamic instability behaviors that are strongly associated with catastrophe
title_full_unstemmed Quantification of microtubule stutters: dynamic instability behaviors that are strongly associated with catastrophe
title_short Quantification of microtubule stutters: dynamic instability behaviors that are strongly associated with catastrophe
title_sort quantification of microtubule stutters: dynamic instability behaviors that are strongly associated with catastrophe
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9250389/
https://www.ncbi.nlm.nih.gov/pubmed/35108073
http://dx.doi.org/10.1091/mbc.E20-06-0348
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