Cell Biology

Cellulose synthase complexes (CSCs) play a central role in plant cell wall formation. Their dynamic behavior at the plasma membrane leads to the deposition of cellulose microfibrils into the apoplastic space, thereby shaping the architecture and mechanical properties of the cell wall. Although previous imaging studies have provided important insights into CSC dynamics and localization, standardized and reproducible workflows for quantitative measurements of CSC speed and density remain limited. Here, we present a reproducible live-cell imaging and analysis workflow for quantifying the speed and density of fluorescently labeled CSCs at the plasma membrane in Arabidopsis thaliana. The protocol integrates optimized spinning-disk confocal imaging, surface-based projection of z-stack recordings, automated detection of diffraction-limited CSCs foci, and kymograph-based speed measurements using freely available tools in Fiji. While selected steps, such as region of interest definition and parameter selection for spot detection or trajectory analysis, remain user-guided, these decisions are constrained to well-defined stages within an otherwise standardized pipeline, thereby reducing variability and improving reproducibility across experiments. The workflow has been validated across multiple tissues, reporter lines, genetic backgrounds, and perturbation conditions in Arabidopsis and enables robust comparative analysis of CSC dynamics. Beyond CSCs, this workflow is expected to be adaptable to other fluorescently labeled proteins that appear as diffraction-limited foci at or near the plasma membrane.

Centrosomes are dynamic organelles critical for mitotic spindle assembly and cilia formation. Here, I describe a protocol for quantifying relative centrosomal protein abundance in Drosophila melanogaster embryos using radial profile analysis of fluorescence intensity. The method involves embryo collection, manual dechorionation, mounting for live imaging, confocal microscopy, and subsequent image analysis. Radial profiling allows quantification of relative protein abundance together with its spatial distribution at the centrosome, providing either relative or normalized intensity profiles. I then outline how this approach can be integrated with complementary techniques such as fluorescence recovery after photobleaching (FRAP) and super-resolution imaging, in this case, three-dimensional structured illumination microscopy (3D-SIM). Combining radial fluorescence profiling with these imaging modalities enables high-resolution, quantitative analysis of dynamic centrosome assembly in a genetically tractable system.

Time-lapse into immunofluorescence (TL into IF) imaging combines the wealth of information acquired during live-cell imaging with ease of access for static immunofluorescence markers. In the field of mechanobiology, connecting live and static imaging to visualize cell biology dynamics is often troublesome. For instance, nuclear blebs are deformations of the nucleus that often rupture spontaneously, leading to changes in the molecular composition of the nucleus and the nuclear bleb. Current techniques to connect cellular dynamics and their downstream effects via live-cell imaging, followed by immunofluorescence, often require third-party analysis programs or stage position measurements to accurately track cells. This protocol simplifies the connection between live and static imaging by utilizing a gridded imaging dish. In our protocol, cells are plated on a dish with an engraved coordinate plane. Individual cells are then matched from when the time-lapse ends to the immunofluorescence images simply by their known coordinate location. Overall, TL into IF offers a straightforward method for connecting dynamic live-cell with static immunofluorescence imaging, in an easy and accessible tool for cell biologists.

The deep learning revolution has accelerated discovery in cell biology by allowing researchers to outsource their microscopy analyses to a new class of tools called cell segmentation models. The performance of these models, however, is often constrained by the limited availability of annotated data for them to train on. This limitation is a consequence of the time cost associated with annotating training data by hand. To address this bottleneck, we developed Cell-APP (cellular annotation and perception pipeline), a tool that automates the annotation of high-quality training data for transmitted-light (TL) cell segmentation. Cell-APP uses two inputs—paired TL and fluorescence images—and operates in two main steps. First, it extracts each cell’s location from the fluorescence images. Then, it provides these locations to the promptable deep learning model μSAM, which generates cell masks in the TL images. Users may also employ Cell-APP to classify each annotated cell; in this case, Cell-APP extracts user-specified, single-cell features from the fluorescence images, which can then be used for unsupervised classification. These annotations and optional classifications comprise training data for cell segmentation model development. Here, we provide a step-by-step protocol for using Cell-APP to annotate training data and train custom cell segmentation models. This protocol has been used to train deep learning models that simultaneously segment and assign cell-cycle labels to HeLa, U2OS, HT1080, and RPE-1 cells.

Plasma membrane–associated condensates driven by liquid–liquid phase separation represent a novel mechanism of receptor-mediated signaling transduction, serving as mesoscale platforms that concentrate signaling molecules and modulate reaction kinetics. Condensate formation is a highly dynamic process that occurs within seconds to minutes following receptor activation. Here, we present methods for de novo reconstituting liquid-like condensates on supported lipid bilayers and assessing the condensate fluidity using fluorescence recovery after photobleaching (FRAP). This protocol encompasses supported lipid bilayer preparation, condensation imaging, and FRAP analysis using total internal reflection fluorescence (TIRF) microscopy. Supported lipid bilayers provide a membrane-mimicking environment for receptor signaling cascades, offering mechanistic insights into protein–protein and lipid–protein interactions amid micron-scale condensates. The protocol can also be adapted to study condensates associated with the internal membranes of the Golgi apparatus, mitochondria, and other organelles.

Repetitive increases of intracellular calcium ions (Ca²⁺ oscillations) control cellular functions in various biological events, including meiotic resumption after fertilization. Sperm-derived substances enter the cytoplasm of mature oocytes by sperm fusion, causing Ca²⁺ oscillations. Sperm-independent Ca²⁺ oscillations are also induced in immature oocytes isolated from the ovaries of neonatal to adult mice. The presence of Ca²⁺ oscillations may contribute to subsequent oocyte quality; however, its physiological role and molecular mechanism are unclear. Here, we describe a method of collecting immature oocytes from the ovaries of juvenile (12, 15, and 21 days after birth) and adult mice and monitoring their Ca²⁺ oscillations. Since mouse oocytes are larger than other types of cells, they are a useful model for studying spatiotemporal patterns and the mechanism of Ca²⁺ oscillations in various types of cells. This method can be applied to other rodents due to similarities in oocyte size and developmental processes. Furthermore, the use of various fluorescent probes enables visualization of organelle rearrangement. The mechanism of interaction between oocytes and somatic cells differs between juvenile and adult mice. Therefore, two distinct methods are employed for oocyte collection.

Neuronal survival in vitro is usually used as a parameter to assess the effect of drug treatments or genetic manipulation in a disease condition. Easy and inexpensive protocols based on neuronal metabolism, such as 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), provide a global view of protective or toxic effects but do not allow for the monitoring of cell survival at the single neuronal level over time. By utilizing live imaging microscopy with a high-throughput microscope, we monitored transduced primary cortical neurons from 7–21 days in vitro (DIV) at the single neuronal level. We established a semi-automated analysis pipeline that incorporates data stratification to minimize the misleading impact of neuronal trophic effects due to plating variability; here, we provide all the necessary commands to reproduce it.

Toxoplasma gondii is an apicomplexan parasite that infects a wide variety of eukaryotic hosts and causes toxoplasmosis. The cell cycle of T. gondii exhibits a distinct architecture and regulation that differ significantly from those observed in well-studied eukaryotic models. To better understand the tachyzoite cell cycle, we developed a fluorescent ubiquitination-based cell cycle indicator (FUCCI) system that enables real-time visualization and quantitative assessment of the different cell cycle phases via immunofluorescence microscopy. Quantitative immunofluorescence and live-cell imaging of the ToxoFUCCI^S probe with specific cell cycle markers revealed substantial overlap between cell cycle phases S, G₂, mitosis, and cytokinesis, further confirming the intricacy of the apicomplexan cell cycle.

Flagellate stages of green microalgae such as Trebouxia are only partially characterised, with recent evidence suggesting that they are involved in both sexual and asexual reproduction. Conventional methods based on fixed samples in light, confocal, or electron microscopy provide only static observations and prevent real-time monitoring of living cells. To overcome this limitation, we have developed a simple and cost-effective protocol for observing Trebouxia flagellate cells over several days by coating microscopy slides with Bold’s basal medium. The method preserves cell viability and allows repeated imaging of motile cells in the same areas so that their behaviour and development can be continuously observed. In this way, qualitative observations, such as flagellate cell release, motility, and gamete fusion, can be combined with quantitative analyses of cell morphology. The protocol has proven to be robust and reproducible and was applied to several Trebouxia species. Compared to existing techniques, it allows the monitoring of dynamic processes and provides a powerful tool to study specific life stages not only in Trebouxia but also in other unicellular and colonial green algae.

Expansion microscopy (ExM) is an innovative and cost-effective super-resolution imaging technique that enables nanoscale visualization of biological structures using conventional fluorescence microscopes. By physically enlarging biological specimens, ExM circumvents the diffraction limit and has become an indispensable tool in cell biology. Ongoing methodological advances have further enhanced its spatial resolution, labeling versatility, and compatibility with diverse sample types. However, ExM imaging is often hindered by sample drift during image acquisition, caused by subtle movements of the expanded hydrogel. This drift can distort three-dimensional reconstruction, compromising both visualization accuracy and quantitative analysis. To overcome this limitation, we developed 3D-Aligner, an advanced and user-friendly image analysis software that computationally corrects sample drift in fluorescence microscopy datasets, including but not limited to those acquired using ExM. The algorithm accurately determines drift trajectories across image stacks by detecting and matching stable background features, enabling nanometer-scale alignment to restore structural fidelity. We demonstrate that 3D-Aligner robustly corrects drift across ExM datasets with varying expansion factors and fluorescent labels. This protocol provides a comprehensive, step-by-step workflow for implementing drift correction in ExM datasets, ensuring reliable three-dimensional imaging and quantitative assessment.