| dc.description.abstract | Live-cell movies generate terabytes of data. However, manual analysis of this data is
prone to error and can easily exhaust days of research time, thus limiting the insights
that can be gleaned from cutting edge microscopes. Automated analysis has been
hard because of discontinuities between the distinct frames of 3D live-cell movies.
We present SpinX, a comprehensive and extensible computational framework which
bridges the gaps between discontinuous frames in time lapse movies by utilising
state-of-the-art Deep Learning technologies and modelling for 3D reconstruction
of highly mobile subcellular structures. Using SpinX, we are now in a position
to precisely track and analyse the movements of multiple subcellular structures
within minutes, including the cell cortex, chromosomes and the mitotic spindle.
We demonstrate the utility of SpinX by employing it to define the precise roles of
spindle movement regulators that ultimately determine the plane of cell division. We
illustrate the extensibility of SpinX by showing how it can also be used to infer the
regulation of complex cortex-microtubule interactions. Our analyses reveal previously
unrecognised roles for the evolutionarily conserved Dynein motor and MARK2/Par1
polarity kinase in regulating the 3D movements of the mitotic spindle. Thus, SpinX
provides an exciting opportunity to study spindle dynamics in relation to the cell
cortex using hundreds of time-resolved 3D movies in a novel way. | en_US |
