Organoids are miniature, self-organizing organs grown in a dish from stem cells. Since the landmark 2009 demonstration by Tato Sato and colleagues that single Lgr5-positive intestinal stem cells can build crypt-villus structures in vitro, intestinal organoids have become a cornerstone model for studying organ homeostasis, cellular differentiation and disease. Yet most measurements of organoid behavior rely on endpoint snapshots or destructive single-cell sequencing, which destroys the spatial and temporal context in which cellular decisions actually unfold. Live imaging promises to close that gap, but it demands careful balancing: cells must be kept healthy for days, light exposure must not damage the tissue, and the resulting mountain of image data must be converted into trackable, analyzable cell histories.

The new workflow, developed by Willem Kasper Spoelstra, Xuan Zheng, Rutger N. U. Kok and colleagues under the supervision of Sander J. Tans and Jeroen S. van Zon, integrates every step of that challenge into a single pipeline. It begins with sample preparation of intestinal organoids grown in extracellular matrix domes, followed by optional experimental interventions such as drug treatments, laser ablations to perturb individual cells, and fluorescence recovery after photobleaching, or FRAP, to measure protein dynamics. The organoids are then imaged continuously with standard confocal microscopy for approximately 120 hours — five full days — capturing cell divisions, migrations, deaths and differentiation events as they happen.

A distinctive feature of the protocol is what happens after imaging ends. Rather than discarding the sample, researchers fix and permeabilize the very same organoids in situ, then apply multiplexed antibody staining to label a panel of cell type markers. This combination is powerful: the live images supply the lineage tree, the family history of every tracked cell, while the endpoint antibody stain reveals what each cell ultimately became. By overlaying the two data types, researchers can infer when and where cell fate decisions were made along each lineage — for example, identifying the exact generation at which a stem cell’s descendants committed to becoming secretory cells.

Quantifying gene expression during the imaging phase relies on fluorescent reporters, genetically encoded markers whose brightness reports the activity of specific genes or signaling pathways. The protocol details how to measure fluorescence intensity along tracked lineages, so that a researcher can follow, cell by cell and division by division, how a WNT-responsive reporter waxes and wanes as a stem cell transitions toward differentiation. For perturbation experiments, the same quantitative framework applies: a laser-ablated cell’s recovery or the redistribution of fluorescence after photobleaching can be tracked against the lineage background, revealing how single-cell damage propagates — or fails to propagate — through the epithelium.

Central to the analysis stage is OrganoidTracker, an open-source software package developed by the same group. The tool combines machine-learning-based cell detection with efficient manual error correction, and a recent upgrade published in Nature Methods in 2025 introduced accurate error prediction, flagging the tracking decisions most likely to be wrong so that human curation effort is spent where it matters most. In the new protocol, OrganoidTracker reconstructs lineage trees from the five-day movies, links each cell to its antibody-stained endpoint identity, and exports fluorescence measurements along family trees for downstream statistical analysis. The software, along with raw data and analysis code, is publicly available through Zenodo and GitHub, making the entire workflow reproducible by other laboratories.

The authors emphasize that organoid health is the linchpin of everything downstream. The protocol dedicates substantial attention to optimizing imaging conditions, including warnings about common culprits of compromised cultures: dimethyl sulfoxide carryover from drug stocks, ethanol toxicity and, above all, phototoxicity from excessive laser exposure. Supplementary data accompanying the paper show how repeated antibody-stripping procedures gradually degrade certain epitopes such as EpCAM, and how most organoids retain their shape, size and position through fixation, stripping and re-staining, though a small fraction are lost or deform along the way. Such practical guidance — much of it hard-won trial and error — is precisely what distinguishes a publishable method from a protocol others can actually reproduce.

Technically, the workflow handles both 3D organoids embedded in matrix and 2D organoid sheets, and it spans dynamic timescales from minutes, appropriate for FRAP recovery curves, to days, appropriate for multi-generation lineage dynamics. The full experimental protocol takes about two weeks end to end, and the required skills are deliberately modest: organoid culturing and standard live-cell confocal microscopy. That accessibility matters, because the barrier to quantitative organoid imaging has often been the perceived need for exotic light-sheet setups or bespoke analysis pipelines. By demonstrating that long-term quantification is achievable on a conventional confocal microscope with freely available software, the authors lower the entry threshold for labs worldwide.

The scientific payoff of the approach is already evident in the team’s earlier work, on which parts of the protocol data rest. A 2022 eLife study from the group showed that mother cells control daughter cell proliferation in intestinal organoids to minimize fluctuations in tissue-level proliferation, a finding only visible through multi-generation lineage tracking. A 2023 Science Advances paper mapped organoid cell fate dynamics in space and time, and a 2025 Science study by Daniel Krueger and colleagues, a co-author here, demonstrated that epithelial tension controls intestinal cell extrusion — again using live imaging combined with perturbation. The new protocol effectively packages the methods behind these discoveries into a transferable form that other labs can adopt and adapt.

Beyond the gut, the implications stretch across organoid biology. Because the core logic — long-term live imaging, in situ fixation, multiplexed staining, machine-learning-assisted tracking and lineage reconstruction — is model-agnostic, the workflow can be extended to airway, liver, gastric and cancer organoids, and it complements emerging label-free imaging approaches and spatial transcriptomics methods. As organoids move from proof-of-concept models toward drug screening, disease modeling and even regenerative medicine, the ability to quantify not just what cells are but how they got there — their lineages, their expression trajectories, their responses to perturbation — becomes essential. This protocol provides a rigorous, open blueprint for doing exactly that, at a timescale where the real dynamics of tissue life actually play out.

Subject of Research: A protocol for long-term quantitative live imaging and lineage reconstruction of dynamic cellular processes in intestinal organoids

Article Title: Quantitative imaging of dynamic processes in intestinal organoids

Article References: Spoelstra, W. K., Zheng, X., Kok, R. N. U., Huelsz-Prince, G., Betjes, M., Ender, P., Goos, Y., Kuentzelmann, K. A., Klumpe, H. E., Krueger, D., Wang, D., Clevers, H., Tans, S. J., & van Zon, J. S. (2026). Quantitative imaging of dynamic processes in intestinal organoids. Nature Protocols. https://doi.org/10.1038/s41596-026-01432-z

Image Credits: AI Generated

DOI: 10.1038/s41596-026-01432-z

Keywords: intestinal organoids, live-cell imaging, cell lineage tracking, OrganoidTracker, fluorescent reporters, laser ablation, FRAP, multiplexed antibody staining, cell differentiation, confocal microscopy, stem cells, quantitative imaging