Modest increase of KIF11 expression exposes fragilities in the mitotic spindle, causing chromosomal instability.

Chromosomal instability (CIN), the process of increased chromosomal alterations, compromises genomic integrity and has profound consequences on human health. Yet, our understanding of the molecular and mechanistic basis of CIN initiation remains limited. We developed a high-throughput, single-cell, image-based pipeline employing deep-learning and spot-counting models to detect CIN by automatically counting chromosomes and micronuclei. To identify CIN-initiating conditions, we used CRISPR activation in human diploid cells to upregulate, at physiologically relevant levels, 14 genes that are functionally important in cancer. We found that upregulation of CCND1, FOXA1 and NEK2 resulted in pronounced changes in chromosome counts, and KIF11 upregulation resulted in micronuclei formation. We identified KIF11-dependent fragilities within the mitotic spindle; increased levels of KIF11 caused centrosome fragmentation, higher microtubule stability, lagging chromosomes or mitotic catastrophe. Our findings demonstrate that even modest changes in the average expression of single genes in a karyotypically stable background are sufficient for initiating CIN by exposing fragilities of the mitotic spindle, which can lead to a genomically diverse cell population.

KiT: a MATLAB package for kinetochore tracking.

UNLABELLED: During mitosis, chromosomes are attached to the mitotic spindle via large protein complexes called kinetochores. The motion of kinetochores throughout mitosis is intricate and automated quantitative tracking of their motion has already revealed many surprising facets of their behaviour. Here, we present 'KiT' (Kinetochore Tracking)-an easy-to-use, open-source software package for tracking kinetochores from live-cell fluorescent movies. KiT supports 2D, 3D and multi-colour movies, quantification of fluorescence, integrated deconvolution, parallel execution and multiple algorithms for particle localization. AVAILABILITY AND IMPLEMENTATION: KiT is free, open-source software implemented in MATLAB and runs on all MATLAB supported platforms. KiT can be downloaded as a package from http://www.mechanochemistry.org/mcainsh/software.php The source repository is available at https://bitbucket.org/jarmond/kit and under continuing development. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: jonathan.armond@warwick.ac.uk.

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 (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.

Probing microtubule polymerisation state at single kinetochores during metaphase chromosome motion.

Kinetochores regulate the dynamics of attached microtubule bundles (kinetochore-fibres, K-fibres) to generate the forces necessary for chromosome movements in mitosis. Current models suggest that poleward-moving kinetochores are attached to depolymerising K-fibres and anti-poleward-moving kinetochores to polymerising K-fibres. How the dynamics of individual microtubules within the K-fibre relate to poleward and anti-poleward movements is poorly understood. To investigate this, we developed a live-cell imaging assay combined with computational image analysis that allows eGFP-tagged EB3 (also known as MAPRE3) to be quantified at thousands of individual metaphase kinetochores as they undergo poleward and anti-poleward motion. Surprisingly, we found that K-fibres are incoherent, containing both polymerising and depolymerising microtubules ­ with a small polymerisation bias for anti-poleward-moving kinetochores. K-fibres also display bursts of EB3 intensity, predominantly on anti-poleward-moving kinetochores, equivalent to more coherent polymerisation, and this was associated with more regular oscillations. The frequency of bursts and the polymerisation bias decreased upon loss of kinesin-13, whereas loss of kinesin-8 elevated polymerisation bias. Thus, kinetochores actively set the balance of microtubule polymerisation dynamics in the K-fibre while remaining largely robust to fluctuations in microtubule polymerisation.

Single-cell states in the estrogen response of breast cancer cell lines.

Estrogen responsive breast cancer cell lines have been extensively studied to characterize transcriptional patterns in hormone-responsive tumors. Nevertheless, due to current technological limitations, genome-wide studies have typically been limited to population averaged data. Here we obtain, for the first time, a characterization at the single-cell level of the states and expression signatures of a hormone-starved MCF-7 cell system responding to estrogen. To do so, we employ a recently proposed model that allows for dissecting single-cell states from time-course microarray data. We show that within 32 hours following stimulation, MCF-7 cells traverse, most likely, six states, with a faster early response followed by a progressive deceleration. We also derive the genome-wide transcriptional profiles of such single-cell states and their functional characterization. Our results support a scenario where estrogen promotes cell cycle progression by controlling multiple, sequential regulatory steps, whose single-cell events are here identified.

A stochastic model dissects cell states in biological transition processes.

Many biological processes, including differentiation, reprogramming, and disease transformations, involve transitions of cells through distinct states. Direct, unbiased investigation of cell states and their transitions is challenging due to several factors, including limitations of single-cell assays. Here we present a stochastic model of cellular transitions that allows underlying single-cell information, including cell-state-specific parameters and rates governing transitions between states, to be estimated from genome-wide, population-averaged time-course data. The key novelty of our approach lies in specifying latent stochastic models at the single-cell level, and then aggregating these models to give a likelihood that links parameters at the single-cell level to observables at the population level. We apply our approach in the context of reprogramming to pluripotency. This yields new insights, including profiles of two intermediate cell states, that are supported by independent single-cell studies. Our model provides a general conceptual framework for the study of cell transitions, including epigenetic transformations.

Nonautonomous movement of chromosomes in mitosis.

Kinetochores are the central force-generating machines that move chromosomes during cell division. It is generally assumed that kinetochores move in an autonomous manner. However, we reveal here that movements of neighboring sister-kinetochore pairs in metaphase are correlated in a distance-dependent manner. This correlation increases in the absence of kinetochore oscillations or stable end-on attachments. This suggests that periodic movements of bioriented chromosomes limit the correlated motion of nonsisters. Computer simulations show that these correlated movements can occur when elastic crosslinks are placed between the K-fibers of oscillating kinetochores. Strikingly, inhibition of the microtubule crosslinking motor kinesin-5 Eg5 leads to an increase in nonsister correlation and impairs periodic oscillations. These phenotypes are partially rescued by codepletion of the kinesin-12 Kif15, demonstrating a function for kinesin-5 and kinesin-12 motors in driving chromosome movements, possibly as part of a crosslinking structure that correlates the movements of nonsister kinetochores.

Pulling nanotubes from supported bilayers.

The force required to form a nanoscale tube from a supported lipid bilayer (SLB) by pulling was measured using an atomic force microscope (AFM). The equilibrium membrane shape during an AFM pulling experiment was calculated and used to derive a general force-distance relationship for pulling a tube from an SLB. We compare these theoretical results with our experimental data and determine the tube radius, the force required to elongate the tube, and, consequently, the surface tension. For a dioleoylphosphatidylcholine (DOPC) SLB, the tension was found to be close to membrane rupture during the pulling experiment.

Force transduction by the microtubule-bound Dam1 ring.

The coupling between the depolymerization of microtubules (MTs) and the motion of the Dam1 ring complex is now thought to play an important role in the generation of forces during mitosis. Our current understanding of this motion is based on a number of detailed computational models. Although these models realize possible mechanisms for force transduction, they can be extended by variation of any of a large number of poorly measured parameters and there is no clear strategy for determining how they might be distinguished experimentally. Here we seek to identify and analyze two distinct mechanisms present in the computational models. In the first, the splayed protofilaments at the end of the depolymerizing MT physically prevent the Dam1 ring from falling off the end, and in the other, an attractive binding secures the ring to the microtubule. Based on this analysis, we discuss how to distinguish between competing models that seek to explain how the Dam1 ring stays on the MT. We propose novel experimental approaches that could resolve these models for the first time, either by changing the diffusion constant of the Dam1 ring (e.g., by tethering a long polymer to it) or by using a time-varying load.