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Coupling of microtubule bundles isolates them from local disruptions to set the structural stability of the anaphase spindle.

Lina CarliniFioranna RendaMelissa C PamulaAlexey KhodjakovTarun M Kapoor
Published in: Proceedings of the National Academy of Sciences of the United States of America (2022)
Chromosome segregation requires load-bearing interactions across kinetochore fibers and antiparallel microtubule bundles, which constitute the spindle midzone. Mechanical properties of kinetochore fibers have been characterized during metaphase, when the mitotic spindle achieves steady state. However, it has been difficult to probe the mechanics of the spindle midzone that elongates during anaphase. Here, we combine superresolution expansion and electron microscopies, lattice light-sheet imaging, and laser microsurgery to examine how midzone organization sets its mechanics. We find that individual midzone bundles extend out to multiple positions across chromosomes and form multiple apparent microtubule-based connections with each other. Across the spindle's short axis, these microtubule bundles exhibit restricted, submicrometer-amplitude motions, which are weakly correlated on <10s timescales. Severing individual midzone bundles near their center does not substantially affect positions of neighboring bundles, nor the overall structural stability of the midzone. In contrast, severing multiple midzone bundles or individual bundles at their chromosome-proximal ends significantly displaces neighboring microtubule bundles. Together, these data suggest a model wherein multiple midzone connections both reinforce its structure and mechanically isolate individual bundles from local perturbations. This feature sets the robust midzone architecture to accommodate disruptions, including those which result from lagging chromosomes, and achieve stereotypic outputs, such as proper chromosome separation.
Keyphrases
  • magnetic resonance
  • cell cycle
  • machine learning
  • gene expression
  • copy number
  • cell proliferation
  • deep learning
  • functional connectivity
  • genome wide
  • solar cells