Bayesian data driven modelling of kinetochore dynamics: space-time organisation of the human metaphase plate

Mitosis is a complex self-organising process that achieves high fidelity separation of duplicated chromosomes into two daughter cells through capture and alignment of chromosomes to the spindle mid-plane. Chromosome movements are driven by kinetochores, multi-protein machines that attach chromosomes to microtubules (MTs), both controlling and generating directional forces. Using lattice light sheet microscopy imaging and automated near-complete tracking of kinetochores at fine spatio-temporal resolution, we produce a detailed atlas of kinetochore metaphase-anaphase dynamics in untransformed human cells (RPE1). We determined the support from this dataset for 17 models of metaphase dynamics using Bayesian inference, demonstrating (1) substantial sister asymmetry that transversely organises the metaphase plate (MPP), (2) substantial spatial organisation of KT dynamic properties within the MPP, and (3) mechanical parameter time dependence, K-fiber forces tuning over the last 5 mins of metaphase towards a set point referred to as the anaphase ready state. These spatio-temporal trends are robust to spindle assembly pathways that are error-prone, suggesting the underpinning processes of kinetochore heterogeneity are intrinsic to mitosis and possibly by design.