Cell division is a tightly regulated mechanism, notably in tissues where malfunctions can lead to tumour formation or developmental defects. This is particularly true in land plants, where cells cannot relocate and therefore cytokinesis determines tissue topology. In plants, cell division is executed in radically different manners than in animals, with the appearance of new structures and the disappearance of ancestral mechanisms. Whilst F-actin and microtubules closely co-exist, recent studies mainly focused on the involvement of microtubules in this key process. Here, we used a root tracking system to image the spatio-temporal dynamics of both F-actin reporters and cell division markers in dividing cells embedded in their tissues. In addition to the F-actin accumulation at the phragmoplast, we observed and quantified a dynamic apico-basal enrichment of F-actin from the prophase/metaphase transition until the end of the cytokinesis.

The ability of plants to sense and orient their root growth towards gravity is studied in many laboratories. It is known that manual analysis of image data is subjected to human bias. Several semi-automated tools are available for analysing images from flatbed scanners, but there is no solution to automatically measure root bending angle over time for vertical-stage microscopy images. To address these problems, we developed ACORBA, which is an automated software that can measure root bending angle over time from vertical-stage microscope and flatbed scanner images. ACORBA also has a semi-automated mode for camera or stereomicroscope images. It represents a flexible approach based on both traditional image processing and deep machine learning segmentation to measure root angle progression over time. As the software is automated, it limits human interactions and is reproducible. ACORBA will support the plant biologist community by reducing labour and increasing reproducibility of image analysis of root gravitropism.

Stem cell fates are spatio-temporally regulated during plant development. Time-lapse imaging of fluorescence reporters is the most widely used method for spatio-temporal analysis of biological processes. However, excitation light for imaging fluorescence reporters causes autofluorescence and photobleaching. Unlike fluorescence reporters, luminescence proteins do not require excitation light, and therefore offer an alternative reporter for long-term and quantitative spatio-temporal analysis. We established an imaging system for luciferase, which enabled monitoring cell fate marker dynamics during vascular development in a vascular cell induction system called VISUAL. Single cells expressing the cambium marker, proAtHB8:ELUC, had sharp luminescence peaks at different time points. Furthermore, dual-color luminescence imaging revealed spatio-temporal relationships between cells that differentiated into xylem or phloem, and cells that transitioned from procambium to cambium. This imaging system enables not only the detection of temporal gene expression, but also facilitates monitoring of spatio-temporal dynamics of cell identity transitions at the single cell level.

Single-cell analysis is important to understand how individual cells work and respond at the cell population level. Experimental single-cell isolation techniques, including dilution, fluorescence-activated cell sorting, microfluidics, and micromanipulation, have been developed in recent decades. However, such applications typically require large cell populations and skilled professionals. Additionally, these methods are unsuitable for sequential analysis before and after cell isolation. In this study, we propose a method for target cell isolation using automated infrared laser-mediated disruption of pollen grains in pollen populations. Germination of the target pollen was observed at the same location as that before laser irradiation, and germinated pollen grains were enriched in the cell population. Pollination of laser-irradiated bulk pollen populations also showed that the target pollen preferentially germinated on the stigma. This method is expected to facilitate physiological analyses of target cells at the single-cell level and effectively produce seeds derived from target pollen.