Biology subjects

Haase, R.

Publications and source records attributed to Haase, R..

At least 19 recordsLinked to original sources

bioRxiv2026

MyoL-Dependent Coupling of Preconoidal Rings to Conoid Is Required for Motility in Toxoplasma gondii

Apicomplexan parasites are unified by their apical complex, a structure of cytoskeletal elements and secretory organelles. At its core lies the conoid, made of spiraling tubulin fibers essential for parasite motility and invasion. In Toxoplasma gondii, conoid extrusion and retraction through the apical polar ring is powered by Myosin H, ultimately regulating gliding motility. The conoid is capped by three preconoidal rings (PCRs), critical for extrusion and motility as they anchor formin 1, which produces filamentous actin needed for both processes. We demonstrate here that PCR composition and stability differ between daughter and mature cells and that Pcr2 and Pcr3 adopt a half-ring localization. The non-functional head containing Myosin-like protein MyoL, a previously unrecognized PCR component, is essential for gliding motility and invasion. Its depletion partially detaches PCRs from the conoid, highlighting its role as a mechanical tether. Targeted mutagenesis identifies the neck and tail regions of MyoL as critical for localization and function. Together, these findings illuminate the architecture and functional organization of the PCR in T. gondii, a structure conserved across several Apicomplexa.

microbiology↗

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

Cell size reduction scales spindle elongation but not chromosome segregation in C. elegans

How embryos adapt their internal cellular machinery to reductions in cell size during development remains a fundamental question in cell biology1-11. Here, we use high-resolution lattice light-sheet fluorescence microscopy and automated image analysis to quantify lineage-resolved mitotic spindle and chromosome segregation dynamics from the 2-to 64-cell stages in Caenorhabditis elegans embryos. While spindle length scales with cell size across both wild-type and size-perturbed embryos, chromosome segregation dynamics remain largely invariant, suggesting that distinct mechanisms govern these mitotic processes. Combining femtosecond laser ablation12,13 with large-scale electron tomography14, we find that central spindle microtubules mediate chromosome segregation dynamics and remain uncoupled from cell size across all stages of early development. In contrast, spindle elongation is driven by cortically anchored motor proteins and astral microtubules, rendering it sensitive to cell size12,13,15-17. Incorporating these experimental results into an extended stoichiometric model for both the spindle and chromosomes, we find that allowing only cell size and microtubule catastrophe rates to vary reproduces elongation dynamics across development. The same model also accounts for centrosome separation and pronuclear positioning in the one-cell C. elegans embryo18, spindle-length scaling across nematode species spanning ~100 million years of divergence17, and spindle rotation in human cells19. Thus, a unified stoichiometric framework provides a predictive, mechanistic account of spindle and nuclear dynamics across scales and species.

cell biology↗

bioRxiv2025

Fluorescence Lifetime Unmixing: A New Workflow for FLIM Live-Cell Imaging

Fluorescence lifetime imaging microscopy (FLIM) translates the duration of excited states of fluorophores into lifetime information as additional source of contrast in images of biological samples. This offers the possibility to separate fluorophores particularly beneficial in case of similar excitation spectra. Here, we demonstrate the distinction of fluorescent molecules based on FLIM phasor analysis, called lifetime unmixing, in live-cell imaging using open-source software for analysis. We showcase two applications using Caenorhabditis elegans as a model system. First, we unmixed the highly spectrally overlapping fluorophores mCherry and mKate2 to distinctively track tagged proteins in six-dimensional datasets to investigate cell division in the developing early embryo. Second, we unmixed fluorescence of tagged proteins of interest from masking natural autofluorescence in adult hermaphrodites. For FLIM data handling and workflow implementation, we developed the open-source plugin napari-FLIM-phasor-plotter to implement conversion, visualization, analysis and reuse of FLIM data of different formats. Our work thus advances technical applications and bioimage data management and analysis in FLIM microscopy for life science research.

cell biology↗

bioRxiv2025

Zero-Shot, Big-Shot, Active-Shot - How to estimate cell confluence, lazily

Mesenchymal stem cell therapy shows promising results for difficult-to-treat diseases, but standardized manufacturing requires robust quality control through automated cell confluence monitoring. While deep learning can automate confluence estimation, research on cost-effective dataset curation and the role of foundation models in this task remains limited. We systematically investigate the most effective strategies for confluence estimation, focusing on active learning-based dataset curation, goal-specific labeling, and leveraging foundation models for zero-shot inference. Here, we show that zero-shot inference with the Segment Anything Model (SAM) achieves excellent confluence estimation without any task-specific training, outperforming fine-tuned smaller models. Further, our findings demonstrate that active learning does not significantly improve model dataset curation compared to random selection in homogeneous cell datasets. We show that goal-specific, simplified labeling strategies perform comparably to precise annotations while substantially reducing annotation effort. These results challenge common assumptions about dataset curation: neither active learning nor extensive fine-tuning provided significant benefits for our specific use case. Instead, we found that leveraging SAMs zero-shot capabilities and targeted labeling strategies offers the most cost-effective approach to automated confluence estimation. Our work provides practical guidelines for implementing automated cell monitoring in MSC manufacturing, demonstrating that extensive dataset curation may be unnecessary when foundation models can effectively handle the task out of the box.

bioinformatics↗

bioRxiv2024

Timely neurogenesis enables increased nuclear packing order during neuronal lamination

The coordination of cell proliferation, migration, and differentiation is crucial for organogenesis in many tissues, including the central nervous system and other organs that arise from pseudostratified epithelia (PSE). PSE feature densely packed elongated epithelial cells, with nuclei positioned along the apicobasal cell axis in a cell cycle-dependent manner. Also, PSE serve as organ precursors in diverse developmental contexts across evolution. While the role of nuclear movements in PSE has been extensively studied, less is known about whether and how their nuclear packing arrangements and changes of packing state influence tissue morphogenesis. To address this, we analyzed nuclear shapes, sizes and neighborhood statistics by segmenting nuclei in 3D and over development in zebrafish retinal neuroepithelia (RNE). We find that in PSE nuclei exhibit orientational, nematic-like order but remain positionally disordered. This pattern is conserved in other, less packed, neuroepithelia, like the hindbrain, suggesting that nematic-like order is a hallmark of pseudostratification. Our analysis during retinal development also revealed that nuclear packing density increases, approaching theoretical packing limits for disordered monodisperse ellipsoids at stages when the tissue transitions to a laminated neuronal structure. As neurogenesis progresses, nuclear shapes are remodeled, enabling the RNE to shift to a crystalline, ordered structure, while maintaining orientational alignment. Failure to initiate neurogenesis results in severe tissue deformations due to increased buckling instability. Our results thus show an instance where nuclear shape and nuclear positioning and their changes are essential for proper retinal morphogenesis, a phenomenon most likely also found in other tissue arrangements.

developmental biology↗

bioRxiv2024

RNG2 tethers the conoid to the apical polar ring in Toxoplasma gondii: a key mechanism in parasite motility and invasion

In Toxoplasma gondii, the conoid is a dynamic organelle composed of spiraling tubulin fibers that extrudes during egress, gliding motility, and invasion. This organelle traverses the apical polar ring (APR) in response to calcium waves and plays a critical role in controlling parasite motility. While the actomyosin-dependent extrusion of the conoid is beginning to be understood, the mechanism by which it is anchored apically to the APR remains unclear. RNG2, a protein localized at both the conoid and the APR, has emerged as a key candidate for this function. By combining iterative ultrastructure expansion microscopy and immunoelectron microscopy we discovered that RNG2 forms 22 tethers between the APR and the conoid. The unique biochemical properties of RNG2, including several proteolytic processing events and its ability to form concatenations, enable it to function as a dynamic bridge between these structures. Conditional depletion of RNG2 resulted in the conoid organelle detaching from the APR without compromising the integrity of its structure, thereby confirming RNG2 essential tethering role. Although microneme secretion remains normal, parasites lacking RNG2 were unable to move and impaired in rhoptry discharge, highlighting the conoids crucial role in parasite motility and invasion. RNG2 is a pivotal protein that ensures conoid functionality in Coccidia.

microbiology↗

bioRxiv2024

Single-cell multidimensional profiling of tumor cell heterogeneity in supratentorial ependymomas

Supratentorial ependymomas are aggressive childhood brain cancers that retain features of neurodevelopmental cell types and segregate into molecularly and clinically distinct subgroups, suggesting different developmental roots. The developmental signatures as well as microenvironmental factors underlying aberrant cellular transformation and behavior across each supratentorial ependymoma subgroup are unknown. Here we integrated single cell- and spatial transcriptomics, as well as in vitro and in vivo live-cell imaging to define supratentorial ependymoma cell states, spatial organization, and dynamic behavior within the neural microenvironment. We find that individual tumor subgroups harbor two distinct progenitor-like cell states reminiscent of early human brain development and diverge in the extent of neuronal or ependymal differentiation. We further uncover several modes of spatial organization of these tumors, including a high order architecture influenced by mesenchymal and hypoxia signatures. Finally, we identify an unappreciated role for brain-resident cells in shifting supratentorial ependymoma cellular heterogeneity towards neuronal-like cells that co-opt immature neuronal morphology and invasion mechanisms. Collectively, these findings provide a multidimensional framework to integrate transcriptional and phenotypic characterization of tumor heterogeneity in supratentorial ependymoma and its potential clinical implications.

cancer biology↗

bioRxiv2024

Benchmarking Large Language Models for Bio-Image Analysis Code Generation

In the computational age, life-scientists often have to write Python code to solve bio-image analysis (BIA) problems. Many of them have not been formally trained in programming though. Code-generation, or coding assistance in general, with Large Language Models (LLMs) can have a clear impact on BIA. To the best of our knowledge, the quality of the generated code in this domain has not been studied. We present a quantitative benchmark to estimate the capability of LLMs to generate code for solving common BIA tasks. Our benchmark currently consists of 57 human-written prompts with corresponding reference solutions in Python, and unit-tests to evaluate functional correctness of potential solutions. We demonstrate our benchmark here and compare 18 state-of-the-art LLMs. To ensure that we will cover most of our community needs we also outline mid- and long-term strategies to maintain and extend the benchmark by the BIA open-source community. This work should support users in deciding for an LLM and also guide LLM developers in improving the capabilities of LLMs in the BIA domain.

bioinformatics↗

bioRxiv2024

Gliding motility of the diatom Craspedostauros australis correlates with the intracellular movement of raphid-specific myosins

Raphid diatoms are one of the few eukaryotes capable of gliding motility, which is remarkably fast and allows for quasi-instantaneous directional reversals. Besides other mechanistic models, it has been suggested that an actomyosin system provides the force for diatom gliding. However, in vivo data on the dynamics of actin and myosin in diatoms are lacking. In this study we demonstrate that the raphe-associated actin bundles required for diatom movement do not exhibit a directional turnover of subunits and thus their dynamics do not contribute directly to force generation. By phylogenomic analysis we identified four raphid diatom-specific myosins in Craspedostauros australis (CaMyoA-D) and investigated their in vivo localization and dynamics through GFP-tagging. Only CaMyoB-D but not CaMyoA exhibited coordinated movement during gliding, consistent with a role in force generation. The characterization of raphid diatom-specific myosins lays the foundation for unraveling the molecular mechanisms that underlie the gliding motility of diatoms.

cell biology↗

bioRxiv2024

Gut Analysis Toolbox: Automating quantitative analysis of enteric neurons

The enteric nervous system (ENS) plays an important role in coordinating gut function. The ENS consists of an extensive network of neurons and glial cells within the wall of the gastrointestinal tract. Alterations in neuronal distribution, function, and type are strongly associated with enteric neuropathies and gastrointestinal (GI) dysfunction and can serve as biomarkers for disease. However, current methods for assessing neuronal counts and distribution suffer from undersampling. This is partly due to challenges associated with imaging and analyzing large tissue areas, and operator bias due to manual analysis. Here, we present the Gut Analysis Toolbox (GAT), an image analysis tool designed for characterization of enteric neurons and their neurochemical coding using 2D images of GI wholemount preparations. GAT is developed for the Fiji distribution of ImageJ. It has a user-friendly interface and offers rapid and accurate cell segmentation. Custom deep learning (DL) based cell segmentation models were developed using StarDist. GAT also includes a ganglion segmentation model which was developed using deepImageJ. In addition, GAT allows importing of segmentation generated by other software. DL models have been trained using ZeroCostDL4Mic on diverse datasets sourced from different laboratories. This captures the variability associated with differences in animal species, image acquisition parameters, and sample preparation across research groups. We demonstrate the robustness of the cell segmentation DL models by comparing them against the state-of-the-art cell segmentation software, Cellpose. To quantify neuronal distribution GAT applies proximal neighbor-based spatial analysis. We demonstrate how the proximal neighbor analysis can reveal differences in cellular distribution across gut regions using a published dataset. In summary, GAT provides an easy-to-use toolbox to streamline routine image analysis tasks in ENS research. GAT enhances throughput allowing unbiased analysis of larger tissue areas, multiple neuronal markers and numerous samples rapidly.

neuroscience↗

bioRxiv2023

NanoPyx: super-fast bioimage analysis powered by adaptive machine learning

To overcome the challenges posed by large and complex microscopy datasets, we have developed NanoPyx, an adaptive bioimage analysis framework designed for high-speed processing. At the core of NanoPyx is the Liquid Engine, an agent-based machine-learning system that predicts acceleration strategies for image analysis tasks. Unlike traditional single-algorithm methods, the Liquid Engine generates multiple CPU and GPU code variations using a meta-programming system, creating a competitive environment where different algorithms are benchmarked against each other to achieve optimal performance under the user"s computational environment. In initial experiments focusing on super-resolution analysis methods, the Liquid Engine demonstrated an over 10-fold computational speed improvement by accurately predicting the ideal scenarios to switch between algorithmic implementations. NanoPyx is accessible to users through a Python library, code-free Jupyter notebooks, and a napari plugin, making it suitable for individuals regardless of their coding proficiency. Furthermore, the optimisation principles embodied by the Liquid Engine have broader implications, extending their applicability to various high-performance computing fields.

bioinformatics↗

bioRxiv2023

Zebrahub - Multimodal Zebrafish Developmental Atlas Reveals the State Transition Dynamics of Late Vertebrate Pluripotent Axial Progenitors

Elucidating the developmental processes of organisms 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 trajectory reconstructions. 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 multi-modal resource, we utilize Zebrahub to provide fresh insights into the pluripotency of Neuro-Mesodermal Progenitors (NMPs). Our publicly accessible web-based platform, Zebrahub, is a foundational resource for studying developmental processes at both transcriptional and spatiotemporal levels, providing researchers with an integrated approach to exploring and analyzing the complexities of cellular lineages during zebrafish embryogenesis.

developmental biology↗

bioRxiv2022

Nanoscopy of organelles and tissues with iterative ultrastructure expansion microscopy (iU-ExM)

Expansion microscopy is an approach of super-resolution fluorescence microscopy that does not yet achieve the precision of nanoscopy techniques such as single-molecule light microscopy (SMLM). Here, we developed an iterative ultrastructure expansion microscopy approach (iU-ExM), which now matches the SMLM resolution as demonstrated using standard references such as the nuclear pores. Applicable to both cells and tissues, iU-ExM allows a broad research community to access high precision super-resolution microscopy.

cell biology↗

bioRxiv2022

Conoid extrusion serves as gatekeeper for entry of glideosome components into the pellicular space to control motility and invasion in Apicomplexa

Members of the Apicomplexa are defined by apical cytoskeletal structures and secretory or-ganelles, tailored for motility and invasion. Gliding is powered by actomyosin-dependent rearward translocation of apically secreted transmembrane adhesins. In Toxoplasma gondii, the conoid, composed of a cone of spiraling tubulin fibers and apposed preconoidal rings (PCRs), is an enigmatic, dynamic organelle of undefined function. Here we mapped five new components of the PCRs and deduce that the structure serves as a pivotal hub for actin polymerization and glideosome assembly. F-actin produced by Formin1 on the PCRs is used by Myosin H to generate the force for conoid extrusion. A set of B-box-type zinc finger domain containing proteins conserved in Apicomplexa is indispensable for PCRs formation, conoid extrusion and motility in Toxoplasma and Plasmodium. Conoid dynamics directs the flux of F-actin to the pellicular space, acting as dynamic gatekeeper to tightly control parasite motility during invasion and egress.

microbiology↗

bioRxiv2021

Growth rate as a modulator of tooth patterning during adaptive radiations

Tooth classes are a mammalian innovation that has contributed to the evolutionary success of mammals. However, our understanding of how tooth classes have evolved and diversified remains limited. Here, we use the evolutionary radiation of noctilionoid bats, the most diverse clade of mammals in terms of diet type, as a model system to show how the tooth developmental program evolved during the adaptation to new diet types. We combined morphological, developmental, cellular, and modeling approaches, to investigate the developmental differences between two tooth classes, molars and premolars and the mechanisms driving their diversification. We demonstrate that tooth classes develop through independent developmental cascades that deviate from classical models. Then we showed that the dramatic diversification of tooth number and size is driven by the modulation of the growth rate of the jaw, explaining the rapid gain/loss of teeth during the evolution of this clade. Finally, we propose a mathematical model that recapitulates the successive appearance of tooth buds and supports the hypothesis that growth acts as a key driver of the evolution of tooth number and size by tinkering with reaction/diffusion processes. Our results demonstrate developmental independence between mammalian tooth classes and provide a mechanism to explain their rapid diversification. More broadly, these results reveal how simple modifications of one developmental mechanism by another can drive the evolution of repeated structures during adaptive radiations.

evolutionary biology↗

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↗

bioRxiv2021

Revisiting the role of Toxoplasma gondii ERK7 in the maintenance and stability of the apical complex

Toxoplasma gondii ERK7 is known to contribute to the integrity of the apical complex and to be involved only in the final step of the conoid biogenesis. In the absence of ERK7, mature parasites lose their conoid complex and are unable to glide, invade or egress from host cells. In contrast to a previous report, we show here that depletion of ERK7 phenocopies the depletion of the apical cap proteins AC9 or AC10. The absence of ERK7 leads to the loss of the apical polar ring, the disorganization of the basket of subpellicular microtubules and an impairment in micronemes secretion. Ultra-expansion microscopy (U-ExM) coupled to NHS-Ester staining on intracellular parasites offers an unprecedented level of resolution and highlights the disorganization of the rhoptries as well as the dilated plasma membrane at the apical pole in the absence of ERK7. Comparative proteomics analysis of wild-type and ERK7 or AC9 depleted parasites led to the disappearance of known, predicted, as well as putative novel components of the apical complex. In contrast, the absence of ERK7 led to an accumulation of microneme proteins, resulting from the defect in exocytosis of the organelles. ImportanceThe conoid is an enigmatic, dynamic organelle positioned at the apical tip of the coccidian subgroup of the Apicomplexa, close to the apical polar ring (APR) from which the subpellicular microtubules (SPTMs) emerge and at the site of microneme and rhoptry secretory organelles exocytosis. In Toxoplasma gondii, the conoid protrudes concomitantly to microneme secretion, during egress, motility and invasion. The conditional depletion of the apical cap structural protein AC9 or AC10 leads to a disorganization of SPTMs as well as the loss of APR and conoid that result in microneme secretion defect and block in motility, invasion and egress. We show here that depletion of the kinase ERK7 phenocopies completely AC9 and AC10 mutants. Moreover, the combination of ultrastructure expansion microscopy with an NHS ester staining revealed that ERK7 depleted parasites exhibit a dilated apical plasma membrane and a mis-positioning of the rhoptry organelles.

microbiology↗