Biology subjects

Pietzsch, T.

Publications and source records attributed to Pietzsch, T..

6 recordsLinked to original sources

bioRxiv2025

Mastodon: the Command Center for Large-Scale Lineage-Tracing Microscopy Datasets

Understanding development in living organisms requires following the divisions, movements, and fates of cells across developing systems. While advances in microscopy have enabled whole-embryo imaging at the cellular level, extracting and analyzing cell lineages from these massive datasets remains a significant computational challenge. We present Mastodon, a scalable, extensible software platform for manual, semi-automated, and automated cell tracking in large images. A purpose-built graph model supports responsive performance for datasets with millions of annotations, making Mastodon a future-proof platform for cell lineage analysis. Built as a Fiji plugin, Mastodon enables interactive visualization, editing, and analysis of complex lineage trees, seamlessly integrated with the raw image data. Comprehension of cell lineages in complex three-dimensional geometries is facilitated by interoperability with the powerful open-source render engine Blender. In three distinct developmental contexts, we demonstrate how Mastodon will accelerate biological insights by providing user-friendly navigation and explorative analysis in complex lineage datasets.

bioinformatics↗

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

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↗

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↗

bioRxiv2021

Labkit: Labeling and Segmentation Toolkit for Big Image Data

We present LO_SCPLOWABKITC_SCPLOW, a user-friendly Fiji plugin for the segmentation of microscopy image data. It offers easy to use manual and automated image segmentation routines that can be rapidly applied to single- and multi-channel images as well as to timelapse movies in 2D or 3D. LO_SCPLOWABKITC_SCPLOW is specifically designed to work efficiently on big image data and enables users of consumer laptops to conveniently work with multiple-terabyte images. This efficiency is achieved by using ImgLib2 and BigDataViewer as the foundation of our software. Furthermore, memory efficient and fast random forest based pixel classification inspired by the Waikato Environment for Knowledge Analysis (Weka) is implemented. Optionally we harness the power of graphics processing units (GPU) to gain additional runtime performance. LO_SCPLOWABKITC_SCPLOW is easy to install on virtually all laptops and workstations. Additionally, LO_SCPLOWABKITC_SCPLOW is compatible with high performance computing (HPC) clusters for distributed processing of big image data. The ability to use pixel classifiers trained in LO_SCPLOWABKITC_SCPLOW via the ImageJ macro language enables our users to integrate this functionality as a processing step in automated image processing workflows. Last but not least, LO_SCPLOWABKITC_SCPLOW comes with rich online resources such as tutorials and examples that will help users to familiarize themselves with available features and how to best use LO_SCPLOWABKITC_SCPLOW in a number of practical real-world use-cases.

bioinformatics↗

bioRxiv2017

Reconstruction of cell lineages and behaviors underlying arthropod limb outgrowth with multi-view light-sheet imaging and tracking

During development coordinated cell behaviors orchestrate tissue and organ morphogenesis to suit the lifestyle of the organism. We have used here the crustacean Parhyale hawaiensis to study the cellular basis of limb development. Transgenic Parhyale embryos with fluorescently labeled nuclei were imaged at high spatiotemporal resolution with multi-view light-sheet fluorescence microscopy over several days of embryogenesis spanning appendage morphogenesis from early specification up to late differentiation stages. Cell tracking with a new tool called Massive Multi-view Tracker (MaMuT) enabled the reconstruction of the complete cell lineage of an outgrowing thoracic limb with single-cell resolution. In silico clonal analyses suggested that the limb primordium becomes subdivided from an early stage first into anterior-posterior and then into dorsal-ventral compartments whose boundaries intersect at the distal tip of the growing limb. Limb bud formation is associated with the spatial modulation of cell proliferation, while limb elongation is also driven by the preferential orientation of division of epidermal cells along the proximal-distal axis of growth. Cellular reconstructions were predictive of the expression patterns of limb development genes including the Decapentaplegic (Dpp) morphogen.\n\nHIGHLIGHTSO_LIMulti-view light-sheet microscopy of crustacean embryos from species Parhyale hawaiensis are ideal for cellular-level analysis of organ morphogenesis.\nC_LIO_LILineages of 3-dimensional organs were reconstructed at single-cell resolution with the Fiji/ImageJ plugin Massive Multi-view Tracker.\nC_LIO_LIThe Parhyale limb primordium undergoes early lineage restrictions associated with particular cell behaviors and patterns of gene expression.\nC_LIO_LIDifferential rates of cell proliferation and oriented cell divisions guide appendage proximal-distal outgrowth.\nC_LI

developmental biology↗