TY - JOUR
T1 - Quantification of microtubule stutters
T2 - dynamic instability behaviors that are strongly associated with catastrophe
AU - Mahserejian, Shant M.
AU - Scripture, Jared P.
AU - Mauro, Ava J.
AU - Lawrence, Elizabeth J.
AU - Jonasson, Erin M.
AU - Murray, Kristopher S.
AU - Li, Jun
AU - Gardner, Melissa
AU - Alber, Mark
AU - Zanic, Marija
AU - Goodson, Holly V.
N1 - Publisher Copyright:
© 2022 Mahserejian, Scripture, et al.
PY - 2022/3/1
Y1 - 2022/3/1
N2 - 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.
AB - 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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U2 - 10.1091/mbc.E20-06-0348
DO - 10.1091/mbc.E20-06-0348
M3 - Article
C2 - 35108073
AN - SCOPUS:85125553800
SN - 1059-1524
VL - 33
JO - Molecular biology of the cell
JF - Molecular biology of the cell
IS - 3
M1 - ar22
ER -