Biology subjects

Burroughs, N.

Publications and source records attributed to Burroughs, N..

3 recordsLinked to original sources

bioRxiv2025

Attenuation of mosaic aneuploidy and erroneous first mitotic division of human embryos

Human reproduction is inherently inefficient1 and 1 in 6 people worldwide suffer infertility. In vitro fertilisation (IVF) can help some couples conceive, but only ~30% of cycles are successful. One factor affecting IVF efficacy is mitotic-origin (mosaic) aneuploidy in which embryos contain a mixture of cells with different numbers of chromosomes2. We previously showed that chromosome segregation error phenotypes are frequent in the first mitotic division of the human embryo3. However, the cause of these errors and impact on daughter cell karyotype is unknown. Here, using live chromosome imaging and next generation sequencing we show that activation of the microtubule depolymerase KIF2C reduces chromosome segregation errors and mitotic-origin aneuploidy at the 2-cell stage. The number of first divisions that show alternative cleavage patterns (associated with failed embryo development in IVF clinics) are also reduced with KIF2C activation. Our findings demonstrate that modulation of microtubule dynamics is a potential therapeutic route to improving human embryo quality and IVF outcomes.

cell biology↗

bioRxiv2021

Computational modelling and near-complete kinetochore tracking reveal how chromosome dynamics during cell division are co-ordinated in space and time

Mitotic chromosome segregation is a self-organising process that achieves high fidelity separation of 46 duplicated chromosomes into two daughter cells. Chromosomes must be captured by the microtubule-based spindle, aligned at the spindle equator where they undergo oscillatory motion (metaphase) and then pulled to opposite spindle poles (anaphase). These large and small-scale chromosome movements are driven by kinetochores, multi-protein machines, that link chromosomes to microtubules and generate directional forces. Through automated near-complete tracking of kinetochores at fine spatio-temporal resolution over long timescales, we produce a detailed atlas of kinetochore dynamics throughout metaphase and anaphase in human cells. We develop a hierarchical biophysical model of kinetochore dynamics and fit this model to 4D lattice light sheet experimental data using Bayesian inference. We demonstrate that location in the metaphase plate is the largest factor in the variation in kinetochore dynamics, exceeding the variation between cells, whilst within the spindle there is local spatio-temporal coordination between neighbouring kinetochores of directional switching events, kinetochore-fibre (K-fibre) polymerization/depolymerization state and the segregation of chromosomes. Thus, metaphase oscillations are robust to variation in the mechanical forces throughout the spindle, whilst the spindle environment couples kinetochore dynamics across the plate. Our methods provide a framework for detailed quantification of chromosome dynamics during mitosis in human cells.

cell biology↗

bioRxiv2018

A Hidden Markov Model for Detecting Confinement in Single Particle Tracking Trajectories

State-of-the-art single particle tracking (SPT) techniques can generate long trajectories with high temporal and spatial resolution. This offers the possibility of mechanistically interpreting particle movements and behaviour in membranes. To this end, a number of statistical techniques have been developed that partition SPT trajectories into states with distinct diffusion signatures, allowing a statistical analysis of diffusion state dynamics and switching behaviour. Here we develop a confinement model, within a hidden Markov framework, that switches between phases of free diffusion, and confinement in a harmonic potential well. By using a Markov chain Monte Carlo (MCMC) algorithm to fit this model, automated partitioning of individual SPT trajectories into these two phases is achieved, which allows us to analyse confinement events. We demonstrate the utility of this algorithm on a previously published dataset, where gold nanoparticle (AuNP) tagged GM1 lipids were tracked in model membranes. We performed a comprehensive analysis of confinement events, demonstrating that there is heterogeneity in the lifetime, shape, and size of events, with confinement size and shape being highly conserved within trajectories. Our observations suggest that heterogeneity in confinement events is caused by both individual nanoparticle characteristics and the binding site environment. The individual nanoparticle heterogeneity ultimately limits the ability of iSCAT to resolve molecular dynamics to the order of the tag size; homogeneous tags could potentially allow the resolution to be taken below this limit by deconvolution methods. In a wider context, the presented harmonic potential well confinement model has the potential to detect and characterise a wide variety of biological phenomena, such as hop diffusion, receptor clustering, and lipid rafts.

biophysics↗