Digital Spindle: A New Way to Explore Mitotic Functions by Whole Cell Data Collection and a Computational Approach

Opportunities and challenges for deep learning in cell dynamics research

The growth of artificial intelligence (AI) has led to an increase in the adoption of computer vision and deep learning (DL) techniques for the evaluation of microscopy images and movies. This adoption has not only addressed hurdles in quantitative analysis of dynamic cell biological processes but has also started to support advances in drug development, precision medicine, and genome-phenome mapping. We survey existing AI-based techniques and tools, as well as open-source datasets, with a specific focus on the computational tasks of segmentation, classification, and tracking of cellular and subcellular structures and dynamics. We summarise long-standing challenges in microscopy video analysis from a computational perspective and review emerging research frontiers and innovative applications for DL-guided automation in cell dynamics research.

Electrically tunable lenses - eliminating mechanical axial movements during high-speed 3D live imaging

The successful investigation of photosensitive and dynamic biological events, such as those in a proliferating tissue or a dividing cell, requires non-intervening high-speed imaging techniques. Electrically tunable lenses (ETLs) are liquid lenses possessing shape-changing capabilities that enable rapid axial shifts of the focal plane, in turn achieving acquisition speeds within the millisecond regime. These human-eye-inspired liquid lenses can enable fast focusing and have been applied in a variety of cell biology studies. Here, we review the history, opportunities and challenges underpinning the use of cost-effective high-speed ETLs. Although other, more expensive solutions for three-dimensional imaging in the millisecond regime are available, ETLs continue to be a powerful, yet inexpensive, contender for live-cell microscopy.

Imaging mitotic processes in three dimensions with lattice light-sheet microscopy

There are few technologies that can capture mitotic processes occurring in three-dimensional space with the desired spatiotemporal resolution. Due to such technical limitations, our understanding of mitosis, which has been studied since the early 1880s, is still incomplete with regard to mitotic processes and their regulatory mechanisms at a molecular level. A recently developed high-resolution type of light-sheet microscopy, lattice light-sheet microscopy (LLSM), has achieved unprecedented spatiotemporal resolution scans of intracellular spaces at the whole-cell level. This technology enables experiments that were not possible before (e.g., tracking of growth of every spindle microtubule end and discrimination of individual chromosomes in living cells), thus providing a new avenue for the analysis of mitotic processes. Herein, principles of LLSM technology are introduced, as well as experimental techniques that became possible with LLSM. In addition, issues remaining to be solved for use of this technology in mitosis research, big image data problems, are presented to help guide mitosis research into a new era.