Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Ensemble-level organization of human kinetochores and evidence for distinct tension and attachment sensors

Emanuele Roscioli, Tsvetelina E. Germanova, Christopher A. Smith, Peter A. Embacher, Muriel Erent, Amelia I. Thompson, Nigel J. Burroughs, View ORCID ProfileAndrew D. McAinsh
doi: https://doi.org/10.1101/685248
Emanuele Roscioli
1Centre for Mechanochemical Cell Biology and Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Tsvetelina E. Germanova
1Centre for Mechanochemical Cell Biology and Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Christopher A. Smith
1Centre for Mechanochemical Cell Biology and Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, UK
3Metabolic Research Laboratories and MRC Metabolic Diseases Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Peter A. Embacher
2Mathematics Institute, University of Warwick, Coventry, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Muriel Erent
1Centre for Mechanochemical Cell Biology and Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Amelia I. Thompson
1Centre for Mechanochemical Cell Biology and Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Nigel J. Burroughs
1Centre for Mechanochemical Cell Biology and Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, UK
2Mathematics Institute, University of Warwick, Coventry, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: a.d.mcainsh@warwick.ac.uk
Andrew D. McAinsh
1Centre for Mechanochemical Cell Biology and Division of Biomedical Sciences, Warwick Medical School, University of Warwick, Coventry, UK
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Andrew D. McAinsh
  • For correspondence: a.d.mcainsh@warwick.ac.uk
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Summary

Kinetochores are multi-protein machines that form dynamic attachments to microtubules and generate the forces for 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 colour subpixel fluorescence localisation to define how six protein subunits from the major kinetochore complexes CCAN, MIS12, NDC80, KNL1, RZZ and the checkpoint proteins Bub1 and Mad2 are organised in the human kinetochore. This reveals how the kinetochore outer plate is a liquid crystal-like system with high nematic order and largely invariant to loss of attachment or tension except for two mechanical sensors. Firstly, Knl1 unravelling relays tension and secondly NDC80 jack-knifes under microtubule detachment, with only the latter wired up to the checkpoint signalling system. This provides insight into how kinetochores integrate mechanical signals to promote error-free chromosome segregation.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
Back to top
PreviousNext
Posted June 28, 2019.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Ensemble-level organization of human kinetochores and evidence for distinct tension and attachment sensors
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Ensemble-level organization of human kinetochores and evidence for distinct tension and attachment sensors
Emanuele Roscioli, Tsvetelina E. Germanova, Christopher A. Smith, Peter A. Embacher, Muriel Erent, Amelia I. Thompson, Nigel J. Burroughs, Andrew D. McAinsh
bioRxiv 685248; doi: https://doi.org/10.1101/685248
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Ensemble-level organization of human kinetochores and evidence for distinct tension and attachment sensors
Emanuele Roscioli, Tsvetelina E. Germanova, Christopher A. Smith, Peter A. Embacher, Muriel Erent, Amelia I. Thompson, Nigel J. Burroughs, Andrew D. McAinsh
bioRxiv 685248; doi: https://doi.org/10.1101/685248

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Cell Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4394)
  • Biochemistry (9611)
  • Bioengineering (7108)
  • Bioinformatics (24909)
  • Biophysics (12639)
  • Cancer Biology (9977)
  • Cell Biology (14375)
  • Clinical Trials (138)
  • Developmental Biology (7966)
  • Ecology (12130)
  • Epidemiology (2067)
  • Evolutionary Biology (16004)
  • Genetics (10937)
  • Genomics (14761)
  • Immunology (9885)
  • Microbiology (23700)
  • Molecular Biology (9490)
  • Neuroscience (50953)
  • Paleontology (370)
  • Pathology (1544)
  • Pharmacology and Toxicology (2688)
  • Physiology (4030)
  • Plant Biology (8676)
  • Scientific Communication and Education (1512)
  • Synthetic Biology (2402)
  • Systems Biology (6446)
  • Zoology (1346)