Abstract
SummaryKinetochores are multi-protein machines that form dynamic attachments to microtubules and control chromosome segregation. High fidelity is ensured because kinetochores can monitor attachment status and tension, using this information to activate checkpoints and error-correction mechanisms. To explore how kinetochores achieve this, we used two- and three-color subpixel fluorescence localization to define how proteins from six major complexes (CCAN, MIS12, NDC80, KNL1, RZZ, and SKA) and the checkpoint proteins Bub1, Mad1, and Mad2 are organized in the human kinetochore. This reveals how the outer kinetochore has a high nematic order and is largely invariant to the loss of attachment or tension, except for two mechanical sensors. First, Knl1 unravels to relay tension, and second, NDC80 undergoes jackknifing and loss of nematic order under microtubule detachment, with only the latter wired up to the checkpoint signaling system. This provides insight into how kinetochores integrate mechanical signals to promote error-free chromosome segregation.
Highlights
Human kinetochores are multi-megadalton-sized protein machines that assemble on the centromeres of every sister chromatid and provide an attachment site for the tips of $20 dynamic spindle microtubules
Measurement of 3D Euclidian Distances between Kinetochore Proteins To obtain insight into the 3-dimensional (3D) nanoscale architecture of the human kinetochore, we deployed an image acquisition and computational pipeline that outputs the 3D Euclidian distances (D3D) between differentially labeled kinetochore proteins in near-diploid hTERT-RPE1 cells. One limitation of this approach is the overestimation of mean distances (Suzuki et al, 2018)
This is because Euclidian distances cannot be negative leading to a positive bias in the D3D distribution; in other words, distances are overestimated (Figure 1A; Table S1; Methods S1). To correct for this bias, we developed an algorithm to infer the true Euclidian distance (DEC) between two fluorophores. This algorithm goes beyond previous methods (Churchman et al, 2005; Suzuki et al, 2018) by taking into account the anisotropic point spread function in 3D datasets
Summary
Human kinetochores are multi-megadalton-sized protein machines that assemble on the centromeres of every sister chromatid and provide an attachment site for the tips of $20 dynamic spindle microtubules (the kinetochore [K]-fiber). Kinetochores must coordinate microtubule dynamics within the K-fiber and maintain attachment during phases of growth and shrinkage, coupling the energy release from microtubule depolymerization to do work (Auckland and McAinsh, 2015; Rago and Cheeseman, 2013). These kinetochore-microtubule attachments are essential for the accurate segregation of chromosomes in all eukaryotes. There is limited understanding of how this machinery adapts to changes in microtubule occupancy and/or the imposition of pushing and pulling forces These are important questions because a substantial body of work indicates that kinetochores must be able to sense changes in tension and occupancy (Long et al, 2019), sensors that underpin decision making and error correction of the kinetochore. Kinetochores appear to be able to ‘‘count’’ the number of bound microtubules
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