Inferring the Forces Controlling Metaphase Kinetochore Oscillations by Reverse Engineering System Dynamics.
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 (PE...
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Public Library of Science (PLoS)
2015-11-01
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| Series: | PLoS Computational Biology |
| Online Access: | https://doi.org/10.1371/journal.pcbi.1004607 |
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| author | Jonathan W Armond Edward F Harry Andrew D McAinsh Nigel J Burroughs |
| author_facet | Jonathan W Armond Edward F Harry Andrew D McAinsh Nigel J Burroughs |
| author_sort | Jonathan W Armond |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-91035537a0d249fc8b9d51c36d375eab |
| institution | OA Journals |
| issn | 1553-734X 1553-7358 |
| language | English |
| publishDate | 2015-11-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS Computational Biology |
| spelling | doaj-art-91035537a0d249fc8b9d51c36d375eab2025-08-20T02:34:06ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582015-11-011111e100460710.1371/journal.pcbi.1004607Inferring the Forces Controlling Metaphase Kinetochore Oscillations by Reverse Engineering System Dynamics.Jonathan W ArmondEdward F HarryAndrew D McAinshNigel J BurroughsKinetochores 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.https://doi.org/10.1371/journal.pcbi.1004607 |
| spellingShingle | Jonathan W Armond Edward F Harry Andrew D McAinsh Nigel J Burroughs Inferring the Forces Controlling Metaphase Kinetochore Oscillations by Reverse Engineering System Dynamics. PLoS Computational Biology |
| title | Inferring the Forces Controlling Metaphase Kinetochore Oscillations by Reverse Engineering System Dynamics. |
| title_full | Inferring the Forces Controlling Metaphase Kinetochore Oscillations by Reverse Engineering System Dynamics. |
| title_fullStr | Inferring the Forces Controlling Metaphase Kinetochore Oscillations by Reverse Engineering System Dynamics. |
| title_full_unstemmed | Inferring the Forces Controlling Metaphase Kinetochore Oscillations by Reverse Engineering System Dynamics. |
| title_short | Inferring the Forces Controlling Metaphase Kinetochore Oscillations by Reverse Engineering System Dynamics. |
| title_sort | inferring the forces controlling metaphase kinetochore oscillations by reverse engineering system dynamics |
| url | https://doi.org/10.1371/journal.pcbi.1004607 |
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