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Inferring the forces controlling metaphase kinetochore oscillations by reverse engineering system dynamics

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Armond, Jonathan W., Harry, Edward, McAinsh, Andrew D. and Burroughs, Nigel John (2015) Inferring the forces controlling metaphase kinetochore oscillations by reverse engineering system dynamics. PLoS Computational Biology, 11 (11). e1004607. doi:10.1371/journal.pcbi.1004607 ISSN 1553-7358.

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Official URL: http://dx.doi.org/10.1371/journal.pcbi.1004607

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Abstract

Kinetochores are multi-protein complexes that mediate the physical coupling of sister chromatids to spindle microtubule bundles (called kinetochore (K)-fibres) from respective poles. These kinetochore-attached K-fibres generate pushing and pulling forces, which combine with polar ejection forces (PEF) and elastic inter-sister chromatin to govern chromosome movements. Classic experiments in meiotic cells using calibrated micro-needles measured an approximate stall force for a chromosome, but methods that allow the systematic determination of forces acting on a kinetochore in living cells are lacking. Here we report the development of mathematical models that can be fitted (reverse engineered) to high-resolution kinetochore tracking data, thereby estimating the model parameters and allowing us to indirectly compute the (relative) force components (K-fibre, spring force and PEF) acting on individual sister kinetochores in vivo. We applied our methodology to thousands of human kinetochore pair trajectories and report distinct signatures in temporal force profiles during directional switches. We found the K-fibre force to be the dominant force throughout oscillations, and the centromeric spring the smallest although it has the strongest directional switching signature. There is also structure throughout the metaphase plate, with a steeper PEF potential well towards the periphery and a concomitant reduction in plate thickness and oscillation amplitude. This data driven reverse engineering approach is sufficiently flexible to allow fitting of more complex mechanistic models; mathematical models of kinetochore dynamics can therefore be thoroughly tested on experimental data for the first time. Future work will now be able to map out how individual proteins contribute to kinetochore-based force generation and sensing.

Item Type: Journal Article
Subjects: Q Science > QH Natural history
R Medicine > R Medicine (General)
Divisions: Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Biomedical Sciences > Cell & Developmental Biology
Faculty of Science, Engineering and Medicine > Science > Mathematics
Faculty of Science, Engineering and Medicine > Research Centres > Molecular Organisation and Assembly in Cells (MOAC)
Faculty of Science, Engineering and Medicine > Research Centres > Warwick Systems Biology Centre
Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School
Library of Congress Subject Headings (LCSH): Chromosomes -- Movements -- Mathematical models, Systems Biology, Biomedical engineering
Journal or Publication Title: PLoS Computational Biology
Publisher: Public Library of Science
ISSN: 1553-7358
Official Date: 30 November 2015
Dates:
DateEvent
30 November 2015Published
14 October 2015Accepted
24 July 2015Submitted
Volume: 11
Number: 11
Article Number: e1004607
DOI: 10.1371/journal.pcbi.1004607
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 15 December 2015
Date of first compliant Open Access: 18 December 2015
Funder: Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC), Wellcome Trust (London, England), Engineering and Physical Sciences Research Council (EPSRC)
Grant number: BB/1021353/1 (BBSRC) ; 106151/Z/14 (Wellcome Trust)

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