Biology subjects

Schoeneberg, J.

Publications and source records attributed to Schoeneberg, J..

9 recordsLinked to original sources

bioRxiv2025

Whole-cell particle-based digital twin simulations from 4D lattice light-sheet microscopy data

We present a framework for performing whole-cell digital twin simulations which integrates 4D (x,y,z,t) lattice light-sheet microscopy (LLSM) data with particle-based reaction-diffusion modeling to capture intracellular organelle dynamics. Using imaging data from Cal27 cells, we construct digital twins that incorporate mitochondrial networks, microtubule networks, dynein and kinesin motors, the plasma membrane, and the nucleus. Passive diffusive mitochondrial dynamics are parameterized using stochastic reaction-diffusion simulations in ReaDDy, while active transport is modeled explicitly by incorporating motor-driven transport along a diffusing, polarized microtubule network. Our simulations accurately reproduce experimentally observed mitochondrial dynamics across pharmacological microtubule depolymerization conditions and reproduce the mitochondrial response to intermediate perturbations without explicit re-parameterization. This novel meso-scale digital twin framework offers a bridge between atomic-scale whole-cell simulations and experimental time and length scales.

cell biology↗

bioRxiv2024

LiveLattice: Real-time visualization of tilted light-sheet microscopy data using a memory-efficient transformation algorithm

Light-sheet fluorescence microscopy (LSFM), a prominent fluorescence microscopy technique, offers enhanced temporal resolution for imaging biological samples in four dimensions (4D; x, y, z, time). Some of the most recent implementations, including inverted selective plane illumination microscopy (iSPIM) and lattice light-sheet microscopy (LLSM), rely on a tilting of the sample plane with respect to the light sheet of 30-45 degrees to ease sample preparation. Data from such tilted-sample-plane LSFMs require subsequent deskewing and rotation for proper visualization and analysis. Such transformations currently demand substantial memory allocation. This poses computational challenges, especially with large datasets. The consequence is long processing times compared to data acquisition times, which currently limits the ability for live-viewing the data as it is being captured by the microscope. To enable the fast preprocessing of large light-sheet microscopy datasets without significant hardware demand, we have developed WH-Transform, a novel GPU-accelerated memory-efficient algorithm that integrates deskewing and rotation into a single transformation, significantly reducing memory requirements and reducing the preprocessing run time by at least 10-fold for large image stacks. Benchmarked against conventional methods and existing software, our approach demonstrates linear scalability. Processing large 3D stacks of up to 15 GB is now possible within one minute using a single GPU with 24 GB of memory. Applied to 4D LLSM datasets of human hepatocytes, human lung organoid tissue, and human brain organoid tissue, our method outperforms alternatives, providing rapid, accurate preprocessing within seconds. Importantly, such processing speeds now allow visualization of the raw microscope data stream in real time, significantly improving the usability of LLSM in biology. In summary, this advancement holds transformative potential for light-sheet microscopy, enabling real-time, on-the-fly data processing, visualization, and analysis on standard workstations, thereby revolutionizing biological imaging applications for LLSM, SPIM and similar light microscopes.

cell biology↗

bioRxiv2023

Self-supervised deep learning uncovers the semantic landscape of drug-induced latent mitochondrial phenotypes

Imaging-based high-content screening aims to identify substances that modulate cellular phenotypes. Traditional approaches screen compounds for their ability to shift disease phenotypes toward healthy phenotypes, but these end point-based screens lack an atlas-like mapping between phenotype and cell state that covers the full spectrum of possible phenotypic responses. In this study, we present MitoSpace: a novel mitochondrial phenotypic atlas that leverages self-supervised deep learning to create a semantically meaningful latent space from images without relying on any data labels for training. Our approach employs a dataset of [~]100,000 microscopy images of Cal27 and HeLa cells treated with 25 drugs affecting mitochondria, but can be generalized to any cell type, cell organelle, or drug library with no changes to the methodology. We demonstrate how MitoSpace enhances our understanding of the range of mitochondrial phenotypes induced by pharmacological interventions. We find that i) self-supervised learning can automatically uncover the semantic landscape of drug induced latent mitochondrial phenotypes and can map individual cells to the correct functional area of the drug they are treated with, ii) the traditional classification of mitochondrial morphology along a fragmented to fused axis is more complex than previously thought, with additional axes being identified, and iii) latent spaces trained in a self-supervised manner are superior to those trained with supervised models, and generalize to other cell types and drug conditions without explicit training on those cell types or drug conditions. Future applications of MitoSpace include creating mitochondrial biomarkers for drug discovery and determining the effects of unknown drugs and diseases for diagnostic purposes.

pharmacology and toxicology↗

bioRxiv2022

MitoTNT: Mitochondrial Temporal Network Tracking for 4D live-cell fluorescence microscopy data

Mitochondria form a network in the cell that rapidly changes through fission, fusion, and motility. This four-dimensional (4D, x,y,z,time) temporal network has only recently been made accessible through advanced imaging methods such as lattice light-sheet microscopy. Quantitative analysis tools for the resulting datasets however have been lacking. Here we present MitoTNT, the first-in-class software for Mitochondrial Temporal Network Tracking in 4D live-cell fluorescence microscopy data. MitoTNT uses spatial proximity and network topology to compute an optimal tracking. Tracking is >90% accurate in dynamic spatial mitochondria simulations and are in agreement with published motility results in vitro. Using MitoTNT, we reveal correlated mitochondrial movement patterns, local fission and fusion fingerprints, asymmetric fission and fusion dynamics, cross-network transport patterns, and network-level responses to pharmacological manipulations. MitoTNT is implemented in python with a JupyterLab interface. The extendable and user-friendly design aims at making temporal network tracking accessible to the wider mitochondria community.

cell biology↗

bioRxiv2021

Actin force generation in vesicle formation: mechanistic insights from cryo-electron tomography

Actin assembly provides force for a multitude of cellular processes. Compared to actin assembly- based force production during cell migration, relatively little is understood about how actin assembly generates pulling forces for vesicle formation. Here, cryo-electron tomography revealed actin filament number, organization, and orientation during clathrin-mediated endocytosis in human cells, showing that force generation is robust despite variance in network organization. Actin dynamics simulations incorporating a measured branch angle indicate that sufficient force to drive membrane internalization is generated through polymerization, and that assembly is triggered from [~]4 founding "mother" filaments, consistent with tomography data. Hip1R actin filament anchoring points are present along the entire endocytic invagination, where simulations show that it is key to pulling force generation, and along the neck, where it targets filament growth and makes internalization more robust. Actin cytoskeleton organization described here allowed direct translation of structure to mechanism with broad implications for other actin-driven processes. Highlights- Filament anchorage points are key to pulling force generation and efficiency. - Native state description of CME-associated actin force-producing networks. - Branched actin filament assembly is triggered from multiple mother filaments. - Actin force production is robust despite considerable network variability.

cell biology↗

bioRxiv2020

Xist-seeded nucleation sites form local concentration gradients of silencing proteins to inactivate the X-chromosome

The long non-coding RNA Xist exploits numerous effector proteins to progressively induce gene silencing across the X chromosome and form the inactive X (Xi)-compartment. The mechanism underlying formation of the chromosome-wide Xi-compartment is poorly understood. Here, we find that formation of the Xi-compartment is induced by [~]50 locally confined granules, where two Xist RNA molecules nucleate supra-molecular complexes (SMCs) of interacting proteins. Xist-SMCs are transient structures that concentrate rapidly recycling proteins in the X by increasing protein binding affinity. We find that gene silencing originates at Xist-SMCs and propagates across the entire chromosome over time, achieved by Polycomb-mediated coalescence of chromatin regions and aggregation, via its intrinsically disordered domains, of the critical silencing factor SPEN. Our results suggest a new model for X chromosome inactivation, in which Xist RNA induces macromolecular crowding of heterochromatinizing proteins near distinct sites which ultimately increases their density throughout the chromosome. This mechanism enables deterministic gene silencing without the need for Xist ribonucleoprotein complex-chromatin interactions at each target gene.

cell biology↗

bioRxiv2020

Adaptive actin organization counteracts elevated membrane tension to ensure robust endocytosis

Clathrin-mediated endocytosis (CME) robustness under elevated membrane tension is maintained by actin assembly-mediated force generation. However, whether more actin assembles at endocytic sites in response to increased load, as has been observed in lamellipodia, has not previously been investigated. Here actin network ultrastructure at CME sites was examined under low and high membrane tension. Actin and N-WASP spatial organization indicate that actin polymerization initiates at the base of clathrin-coated pits and that the network then grows away from the plasma membrane. Actin network height at individual CME sites was not coupled to coat shape, raising the possibility that local differences in mechanical load feedback on assembly. By manipulating membrane tension and Arp2/3 complex activity we tested the hypothesis that actin assembly at CME sites increases in response to elevated load. Indeed, in response to elevated membrane tension, actin grew higher, resulting in greater coverage of the clathrin coat, and CME slowed. When membrane tension was elevated and the Arp2/3 complex was inhibited, shallow clathrin-coated pits accumulated, indicating that this adaptive mechanism is especially crucial for coat curvature generation. We propose that actin assembly increases in response to increased load to ensure CME robustness over a range of plasma membrane tensions.

cell biology↗

bioRxiv2019

Direct comparison of clathrin-mediated endocytosis in budding and fission yeast reveals conserved and evolvable features

AbstractConserved proteins drive clathrin-mediated endocytosis (CME), which universally involves a burst of actin assembly. To gain fundamental mechanistic insights into this process, a side-by-side quantitative comparison of CME was performed on two distantly related yeast species. Though endocytic protein abundance in S. pombe and S. cerevisiae are more similar than previously thought, membrane invagination speed and depth are two-fold greater in fission yeast than in budding yeast. In both yeasts, Arp2/3 complex activation drives membrane invagination when triggered by the accumulation of [~]70 WASP molecules. In contrast to budding yeast, WASP-mediated actin nucleation activity plays an essential role in fission yeast endocytosis. Genetics and live-cell imaging revealed core CME spatiodynamic similarities between the two yeasts, though two-zone actin assembly is a fission yeast-specific mechanism, which is not essential for CME. These studies identified conserved CME mechanisms and species-specific adaptations and have broad implications that extend from yeast to humans.

cell biology↗

bioRxiv2018

ATP-dependent force generation and membrane scission by ESCRT-III and Vps4

The ESCRTs catalyze reverse-topology scission from the inner face of membrane necks in HIV budding, multivesicular endosome biogenesis, cytokinesis, and other pathways. We encapsulated a minimal ESCRT module consisting of ESCRT-III subunits Snf7, Vps24, and Vps2, and the AAA+ ATPase Vps4 such that membrane nanotubes reflecting the correct topology of scission could be pulled from giant vesicles. Upon ATP release by photo-uncaging, this system was capable of generating forces within the nanotubes in a manner dependent upon Vps4 catalytic activity, Vps4 coupling to the ESCRT-III proteins, and membrane insertion by Snf7. At physiological concentrations, single scission events were observed that correlated with forces of ~6 pN, verifying predictions that ESCRTs are capable of exerting forces on membranes. Imaging of scission with subsecond resolution revealed Snf7 puncta at the sites of membrane cutting, directly verifying longstanding predictions for the ESCRT scission mechanism.\n\nOne Sentence SummaryESCRT-III and Vps4 were reconstituted from within the interior of nanotubes pulled from giant vesicles, revealing that this machinery couples ATP-dependent force production for membrane scission.

biophysics↗