Cell-cell signaling and cell-fate decisions are essential for organ assembly, but how these molecular events translate into the physical properties and cell behaviors that drive development remains poorly understood. In the zebrafish lateral line, developing pairs of sensory hair cells undergo symmetry-breaking mediated by Notch signaling, leading to one cell becoming Notch-ON (receiver state) and its sibling becoming Notch-OFF (sender state). These cells then undergo coordinated movements that ensure that Notch-OFF cells are always positioned anterior to their Notch-ON sisters. Finally, the Notch state of cells determines the polarity of these cells' actin bundles. However, the cellular mechanisms and molecular programs that guide polarity-specific behaviors remain largely unknown. Here, using time-lapse imaging and a new 3D segmentation and tracking pipeline, we demonstrate that sister cells actively move in opposite directions: Notch-OFF cells migrate anteriorly while Notch-ON cells move posteriorly, enabling robust rotations when cells are initially mispositioned. Using single-cell RNA sequencing, we identify fate-dependent transcriptional programs and show that the differentially expressed kinase stk32a is required for proper navigation and hair bundle placement in Notch-ON cells. Strikingly, loss of stk32a reveals an underlying chiral bias in cell-pair rotations, suggesting the existence of an additional, previously unrecognized axis of symmetry breaking beyond the Notch-mediated fate decision.

Classical microscopy, which captures data without adjusting settings in real time, sometimes limits our ability to track the dynamics of living, moving, and growing samples. An illustrative example is mapping the development of neuromasts. These zebrafish mechanosensory organs can exit the field of view during live experiments due to elongation of the body axis during growth. Previous works on tracking neuromast rely on nuclei fluorescence imaging as a tracking channel, however, prolonged excitation can lead to phototoxicity and photobleaching. Here we report DynaTrack, a label-agnostic smart tracking pipeline for mapping organ development during long-term live imaging. By integrating quantitative phase reconstruction and virtual staining inference into the imaging loop, we utilize the gentleness of bright-field imaging to track the neuromast and fluorescence channels for other readouts. During classical imaging experiments, the neuromasts exited the field of view after similar to 12 h. In contrast, DynaTrack tracked 73 of 75 when using virtual staining, with experiment durations up to 70.5 h. Moreover, virtual staining yielded consistent neuromast displacement tracking throughout four shift-estimation algorithms, demonstrating its robustness. Finally, DynaTrack is implemented using open-source modules and is extensible to additional microscopes, tracking channels, and dynamic imaging problems.

Summary The conserved core planar cell polarity (PCP) pathway orients cells and subcellular structures within an epithelium through asymmetric protein localization and intercellular communication(1–4). In vestibular organs and lateral-line neuromasts, mechanosensory hair cells are interspersed among support cells and form opposing hair-bundle orientations along a shared axis, enabling bidirectional sensitivity to head motion and water flow, respectively(5–9). In zebrafish neuromasts, Notch-mediated lateral inhibition gives rise to two hair-cell populations, distinguished by differential Emx2 expression, that orient their cell-intrinsic polarity machinery differently relative to a PCP-dependent tissue-wide axis(10–14). However, it remains unclear how PCP proteins are organized across hair cells and support cells to achieve both opposing hair-bundle orientations and tissue-wide alignment, and whether PCP signaling remains required after hair-bundle polarity is established. Combining quantitative spatial mapping of the core PCP protein Vangl2 with cell-type-specific and temporally controlled protein degradation, we show that hair cells and support cells make distinct yet coordinated contributions to the polarized Vangl2 organization within neuromasts and to bidirectional hair-bundle polarity. Support-cell Vangl2 facilitates tissue-wide alignment of hair bundles along the anteroposterior axis, whereas hair-cell Vangl2 is required to generate opposing hair-bundle orientations along this axis. Vangl2 degradation after hair bundles have formed disrupts their tissue-wide alignment, showing that planar polarity is actively maintained rather than fixed after establishment. Together, these findings reveal how Vangl2-dependent PCP signaling is distributed across distinct cell types within a heterogeneous epithelium to generate opposing polarity outcomes and remains necessary to preserve tissue-level planar organization.

Tracking live cells across two-dimensional, three-dimensional (3D) and multichannel time-lapse recordings is crucial for understanding tissue-scale biological processes. Despite advancements in imaging technology, accurately tracking cells remains challenging, particularly in complex and crowded tissues where cell segmentation is often ambiguous. We present Ultrack, a versatile and scalable cell tracking method that tackles this challenge by considering candidate segmentations derived from multiple algorithms and parameter sets. Ultrack leverages temporal consistency to select optimal segments, ensuring robust performance even under segmentation uncertainty. We validate our method on diverse datasets, including terabyte-scale developmental time-lapse recordings of zebrafish, fruit fly and nematode embryos, as well as multicolor and label-free cellular imaging. We demonstrate that Ultrack achieves superior or comparable performance in the cell tracking challenge, particularly when tracking densely packed 3D embryonic cells over extended periods. Moreover, we propose an approach to tracking validation via dual-channel sparse labeling that enables high-fidelity ground-truth generation, pushing the boundaries of long-term cell tracking assessment. Our method is freely available as a Python package with Fiji and Napari plugins and can be deployed in a high-performance computing environment, facilitating widespread adoption by the research community.

An animal’s ability to interact with its environment relies on the brain's capacity to distinguish between patterns of sensory information. To investigate this, we used the posterior lateral line system of larval zebrafish, composed of mechanosensory neuromasts innervated by neurons from the posterior lateral line ganglion. Using single-neuromast optogenetic stimulation and whole-brain calcium imaging, we developed a precise and flexible approach to examine sensory processing. Stimulating individual neuromasts revealed that second-order circuits show diverse selectivity despite lacking topographic organization. We further show that complex combinations of neuromast stimulation are encoded by sparse neuronal ensembles within the medial octavolateralis nucleus (MON) and that neuromast input integrates nonlinearly. This approach provides a powerful method for spatiotemporal interrogation of the zebrafish lateral line, sheds light on how neuromast input is integrated in the brain, and positions this system as a valuable model for studying whole-brain sensory encoding.

Correlative live-cell imaging of landmark organelles—such as nuclei, nucleoli, cell membranes, nuclear envelope and lipid droplets—is critical for systems cell biology and drug discovery. However, achieving this with molecular labels alone remains challenging. Virtual staining of multiple organelles and cell states from label-free images with deep neural networks is an emerging solution. Virtual staining frees the light spectrum for imaging molecular sensors, photomanipulation or other tasks. Current methods for virtual staining of landmark organelles often fail in the presence of nuisance variations in imaging, culture conditions and cell types. Here we address this with Cytoland, a collection of models for robust virtual staining of landmark organelles across diverse imaging parameters, cell states and types. These models were trained with self-supervised and supervised pre-training using a flexible convolutional architecture (UNeXt2) and augmentations inspired by image formation of light microscopes. Cytoland models enable virtual staining of nuclei and membranes across multiple cell types—including human cell lines, zebrafish neuromasts, induced pluripotent stem cells (iPSCs) and iPSC-derived neurons—under a range of imaging conditions. We assess models using intensity, segmentation and application-specific measurements obtained from virtually and experimentally stained nuclei and membranes. These models rescue missing labels, correct non-uniform labelling and mitigate photobleaching. We share multiple pre-trained models, open-source software (VisCy) for training, inference and deployment, and the datasets. Ziwen Liu et al. report Cytoland, an approach to train robust models to virtually stain landmark organelles of cells and address the generalization gap of current models. The training pipeline, models and datasets are shared under open-source permissive licences.

The ability of animals to interact with their environment hinges on the brain's capacity to distinguish between patterns of sensory information and accurately attribute them to specific sensory organs. The mechanisms by which neuronal circuits discriminate and encode the source of sensory signals remain elusive. To address this, we utilized as a model the posterior lateral line system of larval zebrafish, which is used to detect water currents. This system comprises a series of mechanosensory organs called neuromasts, which are innervated by neurons from the posterior lateral line ganglion. By combining single-neuromast optogenetic stimulation with whole-brain calcium imaging, we developed a novel approach to investigate how inputs from neuromasts are processed. Upon stimulating individual neuromasts, we observed that neurons in the brain of the zebrafish show diverse selectivity properties despite a lack of topographic organization in second-order circuits. We further demonstrated that complex combinations of neuromast stimulation are represented by sparse ensembles of neurons within the medial octavolateralis nucleus (MON) and found that neuromast input can be integrated nonlinearly. Our approach offers an innovative method for spatiotemporally interrogating the zebrafish lateral line system and presents a valuable model for studying whole-brain sensory encoding.

Elucidating organismal developmental processes requires a comprehensive understanding of cellular lineages in the spatial, temporal, and molecular domains. In this study, we introduce Zebrahub, a dynamic atlas of zebrafish embryonic development that integrates single-cell sequencing time course data with lineage reconstructions facilitated by light-sheet microscopy. This atlas offers high-resolution and in-depth molecular insights into zebrafish development, achieved through the sequencing of individual embryos across ten developmental stages, complemented by reconstructions of cellular trajectories. Zebrahub also incorporates an interactive tool to navigate the complex cellular flows and lineages derived from light-sheet microscopy data, enabling in silico fate-mapping experiments. To demonstrate the versatility of our multimodal resource, we utilize Zebrahub to provide fresh insights into the pluripotency of neuro-mesodermal progenitors (NMPs) and the origins of a joint kidney-hemangioblast progenitor population.

Dynamic imaging of landmark organelles, such as nuclei, cell membrane, nuclear envelope, and lipid droplets enables image-based phenotyping of functional states of cells. Multispectral fluorescent imaging of landmark organelles requires labor-intensive labeling, limits throughput, and compromises cell health. Virtual staining of label-free images with deep neural networks is an emerging solution for this problem. Multiplexed imaging of cellular landmarks from scattered light and subsequent demultiplexing with virtual staining saves the light spectrum for imaging additional molecular reporters, photomanipulation, or other tasks. Published approaches for virtual staining of landmark organelles are fragile in the presence of nuisance variations in imaging, culture conditions, and cell types. This paper reports model training protocols for virtual staining of nuclei and membranes robust to label-free imaging parameters, cell states, and cell types. We developed a flexible and scalable convolutional architecture, named UNeXt2, for supervised training and self-supervised pre-training. The strategies we report here enable robust virtual staining of nuclei and cell membranes in multiple cell types, including neuromasts of zebrafish, across a range of imaging conditions. We assess the models by comparing the intensity, segmentations, and application-specific measurements obtained from virtually stained and experimentally stained nuclei and membranes. The models rescue the missing label, non-uniform expression of labels, and photobleaching. We share three pre-trained models, named VSCyto3D, VSCyto2D, and VSNeuromast, as well as VisCy, a PyTorch-based pipeline for training, inference, and deployment that leverages the modern OME-Zarr format. ### Competing Interest Statement The authors have declared no competing interest.

Correlative computational microscopy can accelerate imaging and modeling of cellular dynamics by relaxing trade-offs inherent to dynamic imaging. Existing computational microscopy frameworks are either specialized or overly generic, limiting use to fixed configurations or domain experts. We introduce WaveOrder, a generalist wave-optical framework for imaging the architectural order of biomolecules. WaveOrder reconstructs diverse specimen properties from multi-channel acquisitions, with or without fluorescence. It provides a unified representation of linear optical properties and differentiable physics-based image formation models spanning widefield, confocal, light-sheet, and oblique label-free geometries. WaveOrder uses physics-informed ML to auto-tune model parameters and solve blind shift-variant restoration problems. This open-source, PyTorch-based framework enables scalable quantitative imaging across scales from organelles to adult zebrafish, and improves restoration of cellular structures in high-throughput experiments. We validate WaveOrder on diverse imaging applications, demonstrating its ability to recover biomolecular structure beyond the limits of existing approaches.

Zebrafish, a widely used model organism in developmental and biomedical research, offers several advantages such as external fertilization, embryonic transparency, and genetic similarity to humans. However, traditional methods for introducing exogenous genetic material into zebrafish embryos, particularly microinjection, pose significant technical challenges and limit throughput. To address this, we developed a novel approach utilizing Lipofectamine LTX for the efficient delivery of nucleic acids into zebrafish embryos by lipid-based transfection. Our protocol bypasses the need for microinjection, offering a cost-effective, high-throughput, and user-friendly alternative. This protocol out-lines new strategies for gene delivery in zebrafish to enhance the efficiency and scope of genetic studies in this model system.

In a developing nervous system, axonal arbors often undergo complex rearrangements before neural circuits attain their final innervation topology. In the lateral line sensory system of the zebrafish, developing sensory axons reorganize their terminal arborization patterns to establish precise neural microcircuits around the mechanosensory hair cells. However, a quantitative understanding of the changes in the sensory arbor morphology and the regulators behind the microcircuit assembly remain enigmatic. Here, we report that Semaphorin7A (Sema7A) acts as an important mediator of these processes. Utilizing a semi-automated three-dimensional neurite tracing methodology and computational techniques, we have identified and quantitatively analyzed distinct topological features that shape the network in wild-type and Sema7A loss-of-function mutants. In contrast to those of wild-type animals, the sensory axons in Sema7A mutants display aberrant arborizations with disorganized network topology and diminished contacts to hair cells. Moreover, ectopic expression of a secreted form of Sema7A by non-hair cells induces chemotropic guidance of sensory axons. Our findings propose that Sema7A likely functions both as a juxtracrine and as a secreted cue to pattern neural circuitry during sensory organ development.

Tracking live cells across 2D, 3D, and multi-channel time-lapse recordings is crucial for understanding tissue-scale biological processes. Despite advancements in imaging technology, achieving accurate cell tracking remains challenging, particularly in complex and crowded tissues where cell segmentation is often ambiguous. We present Ultrack, a versatile and scalable cell-tracking method that tackles this challenge by considering candidate segmentations derived from multiple algorithms and parameter sets. Ultrack employs temporal consistency to select optimal segments, ensuring robust performance even under segmentation uncertainty. We validate our method on diverse datasets, including terabyte-scale developmental time-lapses of zebrafish, fruit fly, and nematode embryos, as well as multi-color and label-free cellular imaging. We show that Ultrack achieves state-of-the-art performance on the Cell Tracking Challenge and demonstrates superior accuracy in tracking densely packed embryonic cells over extended periods. Moreover, we propose an approach to tracking validation via dual-channel sparse labeling that enables high-fidelity ground truth generation, pushing the boundaries of long-term cell tracking assessment. Our method is freely available as a Python package with Fiji and napari plugins and can be deployed in a high-performance computing environment, facilitating widespread adoption by the research community.

16 In a developing nervous system, axonal arbors often undergo complex rearrangements before 17 neural circuits attain their final innervation topology. In the lateral line sensory system of the zebrafish, developing sensory axons reorganize their terminal arborization patterns to establish precise neural microcircuits around the mechanosensory hair cells. However, a quantitative 20 understanding of the changes in the sensory arbor morphology and the regulators behind the 21 microcircuit assembly remain enigmatic. Here, we report that Semaphorin7A (Sema7A) acts 22 as an important mediator of these processes. Utilizing a semi-automated three-dimensional 23 neurite tracing methodology and computational techniques, we have quantitatively analyzed 24 the morphology of the sensory arbors in wild-type and Sema7A loss-of-function mutants. In 25 contrast to those of wild-type animals, the sensory axons in Sema7A mutants display aberrant 26 arborizations with diminished contacts to hair cells. Moreover, ectopic expression of a secreted 27 form of Sema7A by non-hair cells induces chemotropic guidance of sensory axons. Our 28 findings demonstrate that Sema7A functions both as a juxtracrine and as a secreted cue to 29 pattern neural circuitry during sensory organ development.

Planar cell polarity (PCP) proteins localize asymmetrically to instruct cell polarity within the tissue plane, with defects leading to deformities of the limbs, neural tube and inner ear. Wnt proteins are evolutionarily conserved polarity cues, yet Wnt mutants display variable PCP defects; thus, how Wnts regulate PCP remains unresolved. Here, we have used the developing cochlea as a model system to show that secreted Wnts regulate PCP through polarizing a specific subset of PCP proteins. Conditional deletion of Wntless or porcupine, both of which are essential for secretion of Wnts, caused misrotated sensory cells and shortened cochlea - both hallmarks of PCP defects. Wntless-deficient cochleae lacked the polarized PCP components dishevelled 1/2 and frizzled 3/6, while other PCP proteins (Vangl1/2, Celsr1 and dishevelled 3) remained localized. We identified seven Wnt paralogues, including the major PCP regulator Wnt5a, which was, surprisingly, dispensable for planar polarization in the cochlea. Finally, Vangl2 haploinsufficiency markedly accentuated sensory cell polarization defects in Wntless-deficient cochlea. Together, our study indicates that secreted Wnts and Vangl2 coordinate to ensure proper tissue polarization during development.

Actively regulated symmetry breaking, which is ubiquitous in biological cells, underlies phenomena such as directed cellular movement and morphological polarization. Here we investigate how an organ-level polarity pattern emerges through symmetry breaking at the cellular level during the formation of a mechanosensory organ. Combining theory, genetic perturbations, and in vivo imaging assisted by deep learning, we study the development and regeneration of the fluid-motion sensors in the zebrafish’s lateral line. We find that two interacting symmetry-breaking events — one mediated by biochemical signaling and the other by cellular mechanics — give rise to a novel form of collective cell migration, which produces a mirror-symmetric polarity pattern in the receptor organ.

The development of mechanosensory epithelia, such as those of the auditory and vestibular systems, results in the precise orientation of mechanosensory hair cells. After division of a precursor cell in the zebrafish's lateral line, the daughter hair cells differentiate with opposite mechanical sensitivity. Through a combination of theoretical and experimental approaches, we show that Notch1a-mediated lateral inhibition produces a bistable switch that reliably gives rise to cell pairs of opposite polarity. Using a mathematical model of the process, we predict the outcome of several genetic and chemical alterations to the system, which we then confirm experimentally. We show that Notch1a downregulates the expression of Emx2, a transcription factor known to be involved in polarity specification, and acts in parallel with the planar-cell-polarity system to determine the orientation of hair bundles. By analyzing the effect of simultaneous genetic perturbations to Notch1a and Emx2, we infer that the gene-regulatory network determining cell polarity includes an undiscovered polarity effector.

The development of mechanosensory epithelia, such as those of the auditory and vestibular systems, results in the precise orientation of mechanosensory hair cells and consequently directional sensitivity. After division of a precursor cell in the zebrafish’s lateral line, the daughter hair cells differentiate with opposite mechanical sensitivity. Through a combination of theoretical and experimental approaches, we show that Notch1a-mediated lateral inhibition produces a bistable switch that reliably gives rise to cell pairs of opposite polarity. Using our mathematical model of the process, we predict the outcome of several genetic and chemical alterations to the system, which we then confirm experimentally. We show that Notch1a downregulates the expression of Emx2, a transcription factor known to be involved in polarity specification, and acts in parallel with the planar-cell-polarity system to determine the orientation of hair bundles. By analyzing the effect of simultaneous genetic perturbations to Notch1a and Emx2 we infer that the generegulatory network determining cell polarity includes undiscovered polarity effectors.