Biology subjects

Preibisch, S.

Publications and source records attributed to Preibisch, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Organelle Volume Facilitates Spindle Positioning During C. elegans Female Meiosis

Cortical positioning of oocyte meiotic spindles is required for reducing chromosome number by segregating chromosomes into polar bodies. In C. elegans, kinesin-1 transports membrane-bound organelles inward into a central ball that is hypothesized to push the meiotic spindle outward. Using focused ion beam scanning electron microscopy, we found that the percent volume occupied by membrane-bound organelles was 28% in a mature oocyte that has completed endocytosis of the yolk precursor, vitellogenin, compared to 17% in a less mature oocyte that has not yet endocytosed vitellogenin. We therefore hypothesized that blocking endocytosis of vitellogenin would reduce the size of the central ball of organelles packed inward by kinesin-1 and limit outward movement of the spindle. Depletion of vitellogenin or proteins required for endocytosis resulted in a smaller central volume of kinesin-coated organelles and defective spindle positioning. A computer simulation of a simple exclusion model faithfully recapitulated wildtype and mutant spindle position phenotypes. These results support a volume exclusion model for positioning acentriolar meiotic spindles.

cell biology↗

bioRxiv2026

Machine learning-guided spatial omics for tissue-scale discovery of cell-type-specific architectures

Multiplexed protein imaging enables spatially resolved analysis of molecular organization in tissues, but existing spatial proteomics platforms remain constrained in scalability, throughput, and integration with RNA measurements and interpretable computational analysis. Here, we present an integrated spatial omics framework that combines highly multiplexed protein and RNA imaging with explainable machine learning to map cell-type-specific molecular and structural architectures at tissue scale. Using this platform, we simultaneously profiled up to 46 proteins and 79 RNA species across [~]370,000 cells in intact mouse brain tissue at diffraction-limited subcellular resolution ([~]260 nm). We developed a scalable, open-source computational pipeline for large-scale image processing and analysis, and show that nuclear protein and chromatin features alone are sufficient to accurately classify brain cell types and their spatial organization. Incorporation of explainable deep learning further enabled identification of human-interpretable, cell-type-specific subnuclear structural features directly from imaging data, with independent quantitative validation. Together, this integrated experimental and computational framework enables tissue-scale spatial proteomics-based cell-type classification and structural feature discovery, providing a broadly applicable platform for mechanistic studies, high-content screening, and translational applications.

systems biology↗

bioRxiv2025

Sexual dimorphism in the complete connectome of the Drosophila male central nervous system

Sex differences in behaviour exist across all animals, typically under strong genetic regulation. In Drosophila, fruitless/doublesex transcription factors can identify dimorphic neurons but their organisation into functional circuits remains unclear. We present the connectome of the entire Drosophila male central nervous system. This contains 166,691 neurons spanning the brain and nerve cord, fully proofread and annotated including fruitless/doublesex expression and 11,691 types. We provide the first comprehensive comparison between male and female brain connectomes to synaptic resolution, finding 7,205 isomorphic, 114 dimorphic, 262 male-specific and 69 female-specific types. This resource enables analysis of full sensory-to-motor circuits underlying complex behaviours and the impact of dimorphic elements. Sex-specific/dimorphic neurons are concentrated in higher brain centres while the sensory and motor periphery are largely isomorphic. Within higher centres, male-specific connections are organised into hotspots defined by male-specific neurons or arbours. Numerous circuit switches reroute sensory information to form antagonistic circuits controlling opposing behaviours.

neuroscience↗

bioRxiv2024

Data Release: High-Resolution Imaging and Segmentation of P7 Mouse Tissue Microarchitecture Using FIB-SEM and Machine Learning

This report presents a comprehensive data release exploring the tissue microarchitecture of P7 aged mice using Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) combined with machine learning-based segmentations of nuclei. The study includes high-resolution 3D volumes and nucleus segmentations for seven vital tissues--pancreas, liver, kidney, heart, thymus, hippocampus, and skin--from a single mouse. The detailed datasets are openly accessible onOpenOrganelle.org, providing a valuable resource for the scientific community to support further research and collaboration.

cell biology↗

bioRxiv2024

Deep-Tissue Spatial Omics: Imaging Whole-Embryo Transcriptomics and Subcellular Structures at High Spatial Resolution

The inherent limitations of fluorescence microscopy, notably the restricted number of color channels, have long constrained comprehensive spatial analysis in biological specimens. Here, we introduce cycleHCR technology that leverages multicycle DNA barcoding and Hybridization Chain Reaction (HCR) to surpass the conventional color barrier. cycleHCR facilitates high-specificity, single-shot imaging per target for RNA and protein species within thick specimens, mitigating the molecular crowding issues encountered with other imaging-based spatial omics techniques. We demonstrate whole-mount transcriptomics imaging of 254 genes within an E6.5[~]7.0 mouse embryo, achieving precise three-dimensional gene expression and cell fate mapping across a specimen depth of [~] 310 {micro}m. Utilizing expansion microscopy alongside protein cycleHCR, we unveil the complex network of 10 subcellular structures in primary mouse embryonic fibroblasts. Furthermore, in mouse hippocampal slice, we image 8 protein targets and profile the transcriptome of 120 genes, uncovering complex gene expression gradients and cell-type specific nuclear structural variances. cycleHCR provides a unifying framework for multiplex RNA and protein imaging, offering a quantitative solution for elucidating spatial regulations in deep tissue contexts for research and potentially diagnostic applications.

developmental biology↗

bioRxiv2024

Analysis of developmental gene expression using smFISH and in silico staging of C. elegans embryos

Regulation of transcription during embryogenesis is key to development and differentiation. To study transcript expression throughout Caenorhabditis elegans embryogenesis at single-molecule resolution, we developed a high-throughput single-molecule fluorescence in situ hybridization (smFISH) method that relies on computational methods to developmentally stage embryos and quantify individual mRNA molecules in single embryos. We applied our system to sdc-2, a zygotically transcribed gene essential for hermaphrodite development and dosage compensation. We found that sdc-2 is rapidly activated during early embryogenesis by increasing both the number of mRNAs produced per transcription site and the frequency of sites engaged in transcription. Knockdown of sdc-2 and dpy-27, a subunit of the dosage compensation complex (DCC), increased the number of active transcription sites for the X chromosomal gene dpy-23 but not the autosomal gene mdh-1, suggesting that the DCC reduces the frequency of dpy-23 transcription. The temporal resolution from in silico staging of embryos showed that the deletion of a single DCC recruitment element near the dpy-23 gene causes higher dpy-23 mRNA expression after the start of dosage compensation, which could not be resolved using mRNAseq from mixed-stage embryos. In summary, we have established a computational approach to quantify temporal regulation of transcription throughout C. elegans embryogenesis and demonstrated its potential to provide new insights into developmental gene regulation.

developmental biology↗

bioRxiv2024

Connectome-driven neural inventory of a complete visual system

Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brains volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the flys visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the [~]53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.

neuroscience↗

bioRxiv2024

Visualizing sarcomere and cellular dynamics in skeletal muscle to improve cell therapies

The giant striated muscle protein titin integrates into the developing sarcomere to form a stable myofilament system that is extended as myocytes fuse. The logistics underlying myofilament assembly and disassembly have started to emerge with the possibility to follow labeled sarcomere components. Here, we generated the mCherry knock-in at titins Z-disk to study skeletal muscle development and remodeling. We find titins integration into the sarcomere tightly regulated and its unexpected mobility facilitating a homogenous distribution of titin after cell fusion - an integral part of syncytium formation and maturation of skeletal muscle. In adult mCherry-titin mice, treatment of muscle injury by implantation of titin-eGFP myoblasts reveals how myocytes integrate, fuse and contribute to the continuous myofilament system across cell boundaries. Unlike in immature primary cells, titin proteins are retained at the proximal nucleus and do not diffuse across the whole syncytium with implications for future cell-based therapies of skeletal muscle disease.

cell biology↗

bioRxiv2023

A Connectome of the Male Drosophila Ventral Nerve Cord

Animal behavior is principally expressed through neural control of muscles. Therefore understanding how the brain controls behavior requires mapping neuronal circuits all the way to motor neurons. We have previously established technology to collect large-volume electron microscopy data sets of neural tissue and fully reconstruct the morphology of the neurons and their chemical synaptic connections throughout the volume. Using these tools we generated a dense wiring diagram, or connectome, for a large portion of the Drosophila central brain. However, in most animals, including the fly, the majority of motor neurons are located outside the brain in a neural center closer to the body, i.e. the mammalian spinal cord or insect ventral nerve cord (VNC). In this paper, we extend our effort to map full neural circuits for behavior by generating a connectome of the VNC of a male fly.

neuroscience↗

bioRxiv2023

PEELing: an integrated and user-centric platform for cell-surface proteomics analysis

SummaryMolecular compartmentalization is vital for cellular physiology. Spatially-resolved proteomics allows biologists to survey protein composition and dynamics with subcellular resolution. Here we present PEELing, an integrated package and user-friendly web service for analyzing spatially- resolved proteomics data. PEELing assesses data quality using curated or user-defined references, performs cutoff analysis to remove contaminants, connects to databases for functional annotation, and generates data visualizations--providing a streamlined and reproducible workflow to explore spatially-resolved proteomics data. Availability and ImplementationPEELing and its tutorial are publicly available at https://peeling.janelia.org/. A Python package of PEELing is available at https://github.com/JaneliaSciComp/peeling/. ContactTechnical support for PEELing: peeling@janelia.hhmi.org.

systems biology↗

bioRxiv2023

OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself - OME-Zarr - along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.

bioinformatics↗

bioRxiv2022

A scalable implementation of the recursive least-squares algorithm for training spiking neural networks

Training spiking recurrent neural networks on neuronal recordings or behavioral tasks has become a popular way to study computations performed by the nervous system. As the size and complexity of neural recordings increase, there is a need for efficient algorithms that can train models in a short period of time using minimal resources. We present optimized CPU and GPU implementations of the recursive least-squares algorithm in spiking neural networks. The GPU implementation can train networks of one million neurons, with 100 million plastic synapses and a billion static synapses, about 1000 times faster than an unoptimized reference CPU implementation. We demonstrate the codes utility by training a network, in less than an hour, to reproduce the activity of > 66, 000 recorded neurons of a mouse performing a decision-making task. The fast implementation enables a more interactive in-silico study of the dynamics and connectivity underlying multi-area computations. It also admits the possibility to train models as in-vivo experiments are being conducted, thus closing the loop between modeling and experiments.

neuroscience↗

bioRxiv2022

Architecture and dynamics of a novel desmosome-endoplasmic reticulum organelle

The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signaling, and lipid transfer. Using high-resolution volume electron microscopy, we find that the ER forms a previously unknown association with keratin intermediate filaments and desmosomal cell-cell junctions. Peripheral ER assembles into mirror image-like arrangements at desmosomes and exhibits nanometer proximity to keratin filaments and the desmosome cytoplasmic plaque. ER tubules exhibit stable associations with desmosomes, and perturbation of desmosomes or keratin filaments alters ER organization and mobility. These findings indicate that desmosomes and the keratin cytoskeleton pattern the distribution of the ER network. Overall, this study reveals a previously unknown subcellular architecture defined by the structural integration of ER tubules with an epithelial intercellular junction. One-Sentence SummaryThe desmosome adhesive junction regulates the organization and dynamics of the endoplasmic reticulum network.

cell biology↗

bioRxiv2022

Long-term imaging reveals behavioral plasticity during C. elegans dauer exit

During their lifetime, animals must adapt their behavior to survive in changing environments. This ability requires the nervous system to adjust through dynamic expression of neurotransmitters and receptors but also through growth, spatial reorganization and connectivity while integrating external stimuli. For instance, despite having a fixed neuronal cell lineage, the nematode Caenorhabditis elegans nervous system remains plastic throughout its development. Here, we focus on a specific example of nervous system plasticity, the C. elegans dauer exit decision. Under unfavorable conditions, larvae will enter the non-feeding and non-reproductive dauer stage and adapt their behavior to cope with a new environment. Upon improved conditions, this stress resistant developmental stage is actively reversed to resume reproductive development. However, how different environmental stimuli regulate the exit decision mechanism and thereby drive the larvas behavioral change is unknown. To fill this gap, we developed a new open hardware method for long-term imaging (12h) of C. elegans larvae. We identified dauer-specific behavioral motifs and characterized the behavioral trajectory of dauer exit in different environments to identify key decision points. Combining long-term behavioral imaging with transcriptomics, we find that bacterial ingestion triggers a change in neuropeptide gene expression to establish post-dauer behavior. Taken together, we show how a developing nervous system can robustly integrate environmental changes, activate a developmental switch and adapt the organisms behavior to a new environment.

animal behavior and cognition↗

bioRxiv2021

Image-based representation of massive spatial transcriptomics datasets

We present STIM, an imaging-based computational framework focused on visualizing and aligning high-throughput spatial sequencing datasets. STIM is built on the powerful, scalable ImgLib2 and BigDataViewer (BDV) image data frameworks and thus enables novel development or transfer of existing computer vision techniques to the sequencing domain characterized by datasets with irregular measurement-spacing and arbitrary spatial resolution, such as spatial transcriptomics data generated by multiplexed targeted hybridization or spatial sequencing technologies. We illustrate STIMs capabilities by representing, interactively visualizing, 3D rendering, automatically registering and segmenting publicly available spatial sequencing data from 13 serial sections of mouse brain tissue, and from 19 sections of a human metastatic lymph node.

bioinformatics↗

bioRxiv2021

Automated Reconstruction of Whole-Embryo Cell Lineages by Learning from Sparse Annotations

We present a method for automated nucleus identification and tracking in time-lapse microscopy recordings of entire developing embryos. Our method combines deep learning and global optimization to enable complete lineage reconstruction from sparse point annotations, and uses parallelization to process multi-terabyte light-sheet recordings, which we demonstrate on three common model organisms: mouse, zebrafish, Drosophila. On the most difficult dataset (mouse), our method correctly reconstructs 75.8% of cell lineages spanning 1 hour, compared to 31.8% for the previous state of the art, thus enabling biologists to determine where and when cell fate decisions are made in developing embryos, tissues, and organs.

bioinformatics↗

bioRxiv2021

Cap-dependent translation initiation monitored in living cells

Despite extensive biochemical, genetic, and structural studies, a complete understanding of mRNA translation initiation is still lacking. Imaging methodologies able to resolve the binding dynamics of translation factors at single-cell and single-molecule resolution are necessary to fully elucidate regulation of this paramount process. We fused tags suitable for live imaging to eIF4E, eIF4G1 and 4E-BP1 without affecting their function. We combined Fluorescence Correlation Spectroscopy (FCS) and Single-Particle Tracking (SPT) to interrogate the binding dynamics of initiation factors to the 5cap. Both FCS and SPT were able to detect eIF4E:eIF4G1 binding to the mRNA in the cytoplasm of proliferating cells and neuronal processes. Upon inhibition of phosphorylation by mTOR, 4E-BP1:eIF4E complexes rapidly dissociated from the 5cap followed by eIF4G1 dissociation. Imaging of the binding dynamics of individual translation factors in living cells revealed the temporal regulation of translation at unprecedented resolution.

cell biology↗

bioRxiv2021

A noncatalytic activity of the H4K20 demethylase DPY-21 regulates condensin DC binding

Condensin is a multi-subunit SMC complex that binds to and compacts chromosomes. Here we addressed the regulation of condensin binding dynamics using C. elegans condensin DC, which represses X chromosomes in hermaphrodites for dosage compensation. We established fluorescence recovery after photobleaching (FRAP) using the SMC4 homolog DPY-27 and showed that a well-characterized ATPase mutation abolishes its binding. Next, we performed FRAP in the background of several chromatin modifier mutants that cause varying degrees of X-chromosome derepression. The greatest effect was in a null mutant of the H4K20me2 demethylase DPY-21, where the mobile fraction of condensin DC reduced from [~]30% to 10%. In contrast, a catalytic mutant of dpy-21 did not regulate condensin DC mobility. Hi-C data in the dpy-21 null mutant showed little change compared to wild type, uncoupling Hi-C measured long-range DNA contacts from transcriptional repression of the X chromosomes. Together, our results indicate that DPY-21 has a non-catalytic role in regulating the dynamics of condensin DC binding, which is important for transcription repression.

cell biology↗