Biology subjects

van Zon, J. S.

Publications and source records attributed to van Zon, J. S..

10 recordsLinked to original sources

bioRxiv2026

NuclearIDTracker resolves intestinal cell identity and lineage dynamics through nuclear phenotypic signatures

Organoid models have transformed our understanding of intestinal renewal. Fluorescent imaging has been extensively used to identify key cell types and their differentiation pathways, but immunofluorescence provides only static readouts, whereas live imaging requires fluorescent-reporter engineering and is constrained by limited multiplexing and spectral overlap. Here, we introduce NuclearIDTracker, an explainable machine-learning framework that infers cell identity directly from 3D nuclear segmentations. Using a single nuclear marker, NuclearIDTracker accurately classifies intestinal cell types and integrates with single-cell tracking to resolve lineages and reconstruct dynamic state transitions during organoid development. We show that TA-like cells, rather than stem cells, drive early crypt formation and generate enterocyte and Paneth lineages, as well as the stem-cell population, which emerges only later and subsequently replenishes the TA-like compartment. Following stem-cell ablation, crypt regeneration was not driven by a single discrete cell type. Instead, multiple epithelial populations converged on a proliferative regenerative state with a nuclear phenotypic signature that resembled, but remained distinct from, that of homeostatic TA-like cells, and a YAP/TAZ-associated fetal-like transcriptional signature. Thus, nuclear phenotypic signatures resolve cell identity and reveal coordinated epithelial plasticity during crypt regeneration. NuclearIDTracker establishes a non-perturbative tool to quantify cell identity and state dynamics at single-cell resolution, revealing previously inaccessible biological dynamics and expanding the toolkit for studying epithelial homeostasis, regeneration, and disease.

cell biology↗

bioRxiv2024

Mature tuft cell phenotypes are sequentially expressed along the intestinal crypt-villus axis following cytokine-induced tuft cell hyperplasia

Intestinal tuft cells are epithelial sentinels that trigger host defense upon detection of parasite-derived compounds. While representing interesting targets for immunomodulatory therapies in inflammation-driven intestinal diseases, their detailed functioning is poorly understood. Although two distinct intestinal tuft cell types have been described, we reveal common intermediary transcriptomes among tuft cells in mouse and human. Tuft cell-specific reporter knock-ins in organoids show that the two tuft types are sequentially expressed transcriptomic states that represent different maturation stages. Moreover, cytokines interleukin-4 and interleukin-13 only induce lineage specification to Nrep+ tuft-1 cells, while BMP and cholinergic signalling advance differentiation towards immune-related ChAT+ tuft-2 phenotypes. Functionally, both tuft cell states have chemosensory capacity and respond to stimuli like succinate, but reaction probability increases during tuft cell maturation. Our tuft type-specific reporters and optimized differentiation strategy in organoids provide an experimental platform to study the functioning of tuft cells and their unique chemosensory properties.

cell biology↗

bioRxiv2024

Desynchronization between timers provokes transient arrest during C. elegans development

In multicellular organisms, development entails the progression of diverse cellular processes that need to be temporally coordinated. During C. elegans postembryonic development, the events of molting and cell divisions progress in parallel during four larval stages and are modulated by external cues such as temperature and nutrient availability. While seam cell divisions occur predominantly before ecdysis of the cuticle, the order of the events can change, suggesting that they are controlled by independent mechanisms. Here, we have analyzed the impact of reduced insulin signaling in molting and in stage-specific cell divisions. We find that reduced insulin signaling in the daf-2(e1370) allele delays both of these events but has a larger impact on the timing of cell divisions, thus increasing the desynchrony between the events. The relative delay in seam cell divisions leads to a delay in the initiation of the subsequent stage of the molting program, providing a mechanism for resynchronization of developmental processes to the beginning of the larval stages.

developmental biology↗

bioRxiv2022

Mother cells control daughter cell proliferation in intestinal organoids to minimize proliferation fluctuations

During renewal of the intestine, cells are continuously generated by proliferation. Proliferation and differentiation must be tightly balanced, as any bias towards proliferation results in uncontrolled exponential growth. Yet, the inherently stochastic nature of cells raises the question how such fluctuations are limited. We used time-lapse microscopy to track all cells in crypts of growing mouse intestinal organoids for multiple generations, allowing full reconstruction of the underlying lineage dynamics in space and time. Proliferative behavior was highly symmetric between sister cells, with both sisters either jointly ceasing or continuing proliferation. Simulations revealed that such symmetric proliferative behavior minimizes cell number fluctuations, explaining our observation that proliferating cell number remained constant even as crypts increased in size considerably. Proliferative symmetry did not reflect positional symmetry, but rather lineage control through the mother cell. Our results indicate a concrete mechanism to balance proliferation and differentiation with minimal fluctuations, that may be broadly relevant for other tissues.

cell biology↗

bioRxiv2022

Minimizing cell number fluctuations in self-renewing tissues with a stem cell niche

Self-renewing tissues require that a constant number of proliferating cells is maintained over time. This maintenance can be ensured at the single-cell level or the population level. Maintenance at the population level leads to fluctuations in the number of proliferating cells over time. Often, it is assumed that those fluctuations can be reduced by increasing the number of asymmetric divisions, i.e. divisions where only one of the daughter cells remains proliferative. Here, we study a model of cell proliferation that incorporates a stem cell niche of fixed size, and explicitly model the cells inside and outside the niche. We find that in this model fluctuations are minimized when the difference in growth rate between the niche and the rest of the tissue is maximized and all divisions are symmetric divisions, producing either two proliferating or two non-proliferating daughters. We show that this optimal state leaves visible signatures in clone size distributions and could thus be detected experimentally.

cell biology↗

bioRxiv2020

Functional modules from variable genes: Leveraging percolation to analyze noisy, high-dimensional data

While measurement advances now allow extensive surveys of gene activity (large numbers of genes across many samples), interpretation of these data is often confounded by noise — expression counts can differ strongly across samples due to variation of both biological and experimental origin. Complimentary to perturbation approaches, we extract functionally related groups of genes by analyzing the standing variation within a sampled population. To distinguish biologically meaningful patterns from uninterpretable noise, we focus on correlated variation and develop a novel density-based clustering approach that takes advantage of a percolation transition generically arising in random, uncorrelated data. We apply our approach to two contrasting RNA sequencing data sets that sample individual variation — across single cells of fission yeast and whole animals of C. elegans worms — and demonstrate robust applicability and versatility in revealing correlated gene clusters of diverse biological origin, including cell cycle phase, development/reproduction, tissue-specific functions, and feeding history. Our technique exploits generic features of noisy high-dimensional data and is applicable, beyond gene expression, to feature-rich data that sample population-level variability in the presence of noise.Significance Statement Gene expression largely determines the fate of each cell and ultimately the development and behavior of the whole organism. Whereas most of our knowledge on gene regulatory networks has been obtained from perturbation experiments (e.g. manipulating environmental conditions, genotype, or other physiological variables), here we develop an alternative approach based on the analysis of naturally occurring variations across individuals within a population. Using both single-cell and whole-animal RNA sequencing data, we demonstrate how a rich set of co-regulated gene modules can be uncovered from transcriptomic variability of individuals within unperturbed populations. To robustly extract interpretable clusters from the strong noise background, we devise a novel, versatile clustering approach based on network theory. With a foundation in the generic behavior of random networks near their percolation critical point, our method is broadly applicable, beyond gene expression, to any noisy, high-dimensional data that sample variation across individuals within a population.Competing Interest StatementThe authors have declared no competing interest.View Full Text

systems biology↗

bioRxiv2020

Mechanism of life-long maintenance of neuron identity despite molecular fluctuations

Cell fate is maintained over long timescales, yet molecular fluctuations can lead to spontaneous loss of this differentiated state. We uncovered a mechanism that explains life-long maintenance of ASE neuron fate in C. elegans by the terminal selector transcription factor CHE-1. Fluctuations in CHE-1 level are buffered by the reservoir of CHE-1 bound at its target promoters, which ensure continued che-1 expression by preferentially binding the che-1 promoter. We validated this mechanism by showing that che-1 expression was resilient to induced transient CHE-1 depletion, while both expression of CHE-1 targets and ASE function were lost. We identified a 130 bp che-1 promoter fragment responsible for this resilience, with deletion of a homeodomain binding site in this fragment causing stochastic loss of ASE identity long after its determination. Because network architectures that support this mechanism are highly conserved in cell differentiation, it may explain stable cell fate maintenance in many systems.

developmental biology↗

bioRxiv2020

OrganoidTracker: efficient cell tracking using machine learning and manual error correction

Time-lapse microscopy is routinely used to follow cells within organoids, allowing direct study of division and differentiation patterns. There is an increasing interest in cell tracking in organoids, which makes it possible to study their growth and homeostasis at the single-cell level. As tracking these cells by hand is prohibitively time consuming, automation using a computer program is required. Unfortunately, organoids have a high cell density and fast cell movement, which makes automated cell tracking difficult. In this work, a semi-automated cell tracker has been developed. To detect the nuclei, we use a machine learning approach based on a convolutional neural network. To form cell trajectories, we link detections at different time points together using a min-cost flow solver. The tracker raises warnings for situations with likely errors. Rapid changes in nucleus volume and position are reported for manual review, as well as cases where nuclei divide, appear and disappear. When the warning system is adjusted such that virtually error-free lineage trees can be obtained, still less than 2% of all detected nuclei positions are marked for manual analysis. This provides an enormous speed boost over manual cell tracking, while still providing tracking data of the same quality as manual tracking.

bioinformatics↗

bioRxiv2018

Long-term expanding human airway organoids for disease modelling.

Organoids are self-organizing 3D structures grown from stem cells that recapitulate essential aspects of organ structure and function. Here we describe a method to establish long-term-expanding human airway organoids from broncho-alveolar biopsies or lavage material. The pseudostratified airway organoid epithelium consists of basal cells, functional multi-ciliated cells, mucus-producing goblet cells, and CC10-secreting club cells. Airway organoids derived from cystic fibrosis (CF) patients allow assessment of CFTR function in an organoid swelling assay. Organoid culture conditions also allow gene editing as well as the derivation of various types of lung cancer organoids. Respiratory syncytial virus (RSV) infection recapitulated central disease features and dramatically increases organoid cell motility, found to be driven by the non-structural viral NS2 protein. We conclude that human airway organoids represent versatile models for the in vitro study of hereditary, malignant, and infectious pulmonary disease.

cell biology↗

bioRxiv2018

Multiple sources of variability drive a stochastic cell fate decision in C. elegans

During development, cell fate decisions are often highly stochastic, but with the frequency of the different possible fates tightly controlled. To understand how signaling networks control the cell fate frequency of such random decisions, we studied the stochastic decision of the Caenorhabditis elegans P3.p cell to either fuse to the hypodermis or assume vulva precursor cell fate. Using time-lapse microscopy to measure the single-cell dynamics of two key inhibitors of cell fusion, the Hox gene LIN-39 and Wnt signaling through the {beta}-catenin BAR-1, we uncovered significant variability in the dynamics of LIN-39 and BAR-1 levels. Most strikingly, we observed that BAR-1 accumulated in a single, 1-4 hour pulse at the time of the P3.p cell fate decision, with strong variability both in pulse slope and time of pulse onset. We found that the time of BAR-1 pulse onset was delayed relative to the time of cell fusion in mutants with low cell fusion frequency, linking BAR-1 pulse timing to cell fate outcome. Overall, a model emerged where animal-to-animal variability in LIN-39 levels and BAR-1 pulse dynamics biases cell fate by modulating their absolute level at the time cell fusion is induced. Our results highlight that timing of cell signaling dynamics, rather than its average level or amplitude, could play an instructive role in determining cell fate.\n\nArticle summaryWe studied the stochastic decision of the Caenorhabditis elegans P3.p cell to either fuse to the hypodermis or assume vulva precursor cell fate. We uncovered significant variability in the dynamics of LIN-39/Hox and BAR-1/{beta}-catenin levels, two key inhibitors of cell fusion. Surprisingly, we observed that BAR-1 accumulated in a 1-4 hour pulse at the time of the P3.p cell fate decision, with variable pulse slope and time of pulse onset. Our work suggests a model where animal-to-animal variability in LIN-39 levels and BAR-1 pulse dynamics biases cell fate by modulating their absolute level at the time cell fusion is induced.

developmental biology↗