Reconstitution reveals two paths of force transmission through the kinetochore
- University of Washington, United States
- Genentech Inc, United States
Abstract
Partitioning duplicated chromosomes equally between daughter cells is a microtubule-mediated process essential to eukaryotic life. A multi-protein machine, the kinetochore, drives chromosome segregation by coupling the chromosomes to dynamic microtubule tips, even as the tips grow and shrink through the gain and loss of subunits. The kinetochore must harness, transmit, and sense mitotic forces, as a lack of tension signals incorrect chromosome-microtubule attachment and precipitates error correction mechanisms. But though the field has arrived at a 'parts list' of dozens of kinetochore proteins organized into subcomplexes, the path of force transmission through these components has remained unclear. Here we report reconstitution of functional Saccharomyces cerevisiae kinetochore assemblies from recombinantly expressed proteins. The reconstituted kinetochores are capable of self-assembling in vitro, coupling centromeric nucleosomes to dynamic microtubules, and withstanding mitotically relevant forces. They reveal two distinct pathways of force transmission and Ndc80c recruitment.
Data availability
All data analyses during this study are included in the manuscript and supporting files. Source data files have been provided for Figures 2-5 and their supplements.
Article and author information
Author details
Grace Elizabeth Hamilton
Funding
National Institutes of Health (Training Grant in Molecular Biophysics T32 GM008268)
- Grace Elizabeth Hamilton
National Institutes of Health (R01 GM040506)
- Trisha N Davis
National Institutes of Health (R35 GM130293)
- Trisha N Davis
National Institutes of Health (R01 GM079373)
- Charles L Asbury
National Institutes of Health (R35 GM134842)
- Charles L Asbury
Genentech
- Yoana N Dimitrova
Genentech
- Cameron L Noland
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2020, Hamilton et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,810
- views
-
- 319
- downloads
-
- 16
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Reconstitution reveals two paths of force transmission through the kinetochore
eLife 9:e56582.
https://doi.org/10.7554/eLife.56582
Further reading
-
- Biochemistry and Chemical Biology
- Structural Biology and Molecular Biophysics
Nature has inspired the design of improved inhibitors for cancer-causing proteins.
-
- Biochemistry and Chemical Biology
Mutations in the kinase and juxtamembrane domains of the MET Receptor Tyrosine Kinase are responsible for oncogenesis in various cancers and can drive resistance to MET-directed treatments. Determining the most effective inhibitor for each mutational profile is a major challenge for MET-driven cancer treatment in precision medicine. Here, we used a deep mutational scan (DMS) of ~5764 MET kinase domain variants to profile the growth of each mutation against a panel of 11 inhibitors that are reported to target the MET kinase domain. We validate previously identified resistance mutations, pinpoint common resistance sites across type I, type II, and type I ½ inhibitors, unveil unique resistance and sensitizing mutations for each inhibitor, and verify non-cross-resistant sensitivities for type I and type II inhibitor pairs. We augment a protein language model with biophysical and chemical features to improve the predictive performance for inhibitor-treated datasets. Together, our study demonstrates a pooled experimental pipeline for identifying resistance mutations, provides a reference dictionary for mutations that are sensitized to specific therapies, and offers insights for future drug development.
