Paper

Quantification of Microtubule Stutters: Dynamic Instability Behaviors that are Strongly Associated with Catastrophe

Li, Jun, Zanic, Marija, Goodson, Holly V, Scripture, Jared P, Lawrence, Elizabeth J, Mahserejian, Shant M, Jonasson, Erin M, Gardner, Melissa, Alber, Mark, Murray, Kristopher S, Mauro, Ava J

2020

Overview

ABSTRACT 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 dynamic instability 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), which 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 dimer-scale MT simulations and in vitro experiments, suggesting that stutters are mechanistically involved in catastrophes. Related to this idea, we show that the anti-catastrophe factor CLASP2γ works by promoting the return of stuttering MTs to growth. STADIA enables more comprehensive and data-driven analysis of MT dynamics compared to 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. Competing Interest Statement The authors have declared no competing interest. Footnotes * ↵* Co-first authors * This version of the manuscript has been thoroughly revised. Particularly significant is the new 'parameter sweep' analysis (provided in Supplement Sections 2,3 and 4) that demonstrates the robustness of the method and its conclusions.

• Publisher: Cold Spring Harbor Laboratory Press,Cold Spring Harbor Laboratory
• Subject: Catastrophes / Cell Biology / Growth rate / Instability / Learning algorithms / Microtubules / Phase transitions