TY - JOUR A1 - Eigen, Lennart A1 - Wölfer, Jan A1 - Baum, Daniel A1 - Van Le, Mai-Lee A1 - Werner, Daniel A1 - Dean, Mason N. A1 - Nyakatura, John A. T1 - Comparative architecture of the tessellated boxfish (Ostracioidea) carapace JF - Communications Biology Y1 - 2024 U6 - https://doi.org/10.1038/s42003-024-07119-z VL - 7 ER - TY - JOUR A1 - Harth, Philipp A1 - Udvary, Daniel A1 - Boelts, Jan A1 - Baum, Daniel A1 - Macke, Jakob H. A1 - Hege, Hans-Christian A1 - Oberlaender, Marcel T1 - Dissecting origins of wiring specificity in dense cortical connectomes JF - bioRxiv N2 - Wiring specificity in the cortex is observed across scales from the subcellular to the network level. It describes the deviations of connectivity patterns from those expected in randomly connected networks. Understanding the origins of wiring specificity in neural networks remains difficult as a variety of generative mechanisms could have contributed to the observed connectome. To take a step forward, we propose a generative modeling framework that operates directly on dense connectome data as provided by saturated reconstructions of neural tissue. The computational framework allows testing different assumptions of synaptic specificity while accounting for anatomical constraints posed by neuron morphology, which is a known confounding source of wiring specificity. We evaluated the framework on dense reconstructions of the mouse visual and the human temporal cortex. Our template model incorporates assumptions of synaptic specificity based on cell type, single-cell identity, and subcellular compartment. Combinations of these assumptions were sufficient to model various connectivity patterns that are indicative of wiring specificity. Moreover, the identified synaptic specificity parameters showed interesting similarities between both datasets, motivating further analysis of wiring specificity across species. Y1 - 2024 U6 - https://doi.org/10.1101/2024.12.14.628490 ER - TY - JOUR A1 - Boelts, Jan A1 - Harth, Philipp A1 - Gao, Richard A1 - Udvary, Daniel A1 - Yanez, Felipe A1 - Baum, Daniel A1 - Hege, Hans-Christian A1 - Oberlaender, Marcel A1 - Macke, Jakob H. T1 - Simulation-based inference for efficient identification of generative models in computational connectomics JF - PLOS Computational Biology N2 - Recent advances in connectomics research enable the acquisition of increasing amounts of data about the connectivity patterns of neurons. How can we use this wealth of data to efficiently derive and test hypotheses about the principles underlying these patterns? A common approach is to simulate neuronal networks using a hypothesized wiring rule in a generative model and to compare the resulting synthetic data with empirical data. However, most wiring rules have at least some free parameters, and identifying parameters that reproduce empirical data can be challenging as it often requires manual parameter tuning. Here, we propose to use simulation-based Bayesian inference (SBI) to address this challenge. Rather than optimizing a fixed wiring rule to fit the empirical data, SBI considers many parametrizations of a rule and performs Bayesian inference to identify the parameters that are compatible with the data. It uses simulated data from multiple candidate wiring rule parameters and relies on machine learning methods to estimate a probability distribution (the 'posterior distribution over parameters conditioned on the data') that characterizes all data-compatible parameters. We demonstrate how to apply SBI in computational connectomics by inferring the parameters of wiring rules in an in silico model of the rat barrel cortex, given in vivo connectivity measurements. SBI identifies a wide range of wiring rule parameters that reproduce the measurements. We show how access to the posterior distribution over all data-compatible parameters allows us to analyze their relationship, revealing biologically plausible parameter interactions and enabling experimentally testable predictions. We further show how SBI can be applied to wiring rules at different spatial scales to quantitatively rule out invalid wiring hypotheses. Our approach is applicable to a wide range of generative models used in connectomics, providing a quantitative and efficient way to constrain model parameters with empirical connectivity data. Y1 - 2023 U6 - https://doi.org/10.1371/journal.pcbi.1011406 VL - 19 IS - 9 ER - TY - JOUR A1 - Okafornta, Chukwuebuka William A1 - Farhadifar, Reza A1 - Fabig, Gunar A1 - Wu, Hai-Yin A1 - Köckert, Maria A1 - Vogel, Martin A1 - Baum, Daniel A1 - Haase, Robert A1 - Shelley, Michael J. A1 - Needleman, Daniel J. A1 - Müller-Reichert, Thomas T1 - Cell size reduction scales spindle elongation but not chromosome segregation in C. elegans JF - bioRxiv N2 - How embryos adapt their internal cellular machinery to reductions in cell size during development remains a fundamental question in cell biology. 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 ablation with large-scale electron tomography, 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 size. 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 embryo, spindle-length scaling across nematode species spanning ~100 million years of divergence, and spindle rotation in human cells. Thus, a unified stoichiometric framework provides a predictive, mechanistic account of spindle and nuclear dynamics across scales and species. Y1 - 2025 U6 - https://doi.org/10.1101/2025.10.13.681585 ER - TY - JOUR A1 - Boelts, Jan A1 - Harth, Philipp A1 - Gao, Richard A1 - Udvary, Daniel A1 - Yanez, Felipe A1 - Baum, Daniel A1 - Hege, Hans-Christian A1 - Oberlaender, Marcel A1 - Macke, Jakob H T1 - Simulation-based inference for efficient identification of generative models in connectomics JF - bioRxiv N2 - Recent advances in connectomics research enable the acquisition of increasing amounts of data about the connectivity patterns of neurons. How can we use this wealth of data to efficiently derive and test hypotheses about the principles underlying these patterns? A common approach is to simulate neural networks using a hypothesized wiring rule in a generative model and to compare the resulting synthetic data with empirical data. However, most wiring rules have at least some free parameters and identifying parameters that reproduce empirical data can be challenging as it often requires manual parameter tuning. Here, we propose to use simulation-based Bayesian inference (SBI) to address this challenge. Rather than optimizing a single rule to fit the empirical data, SBI considers many parametrizations of a wiring rule and performs Bayesian inference to identify the parameters that are compatible with the data. It uses simulated data from multiple candidate wiring rules and relies on machine learning methods to estimate a probability distribution (the `posterior distribution over rule parameters conditioned on the data') that characterizes all data-compatible rules. We demonstrate how to apply SBI in connectomics by inferring the parameters of wiring rules in an in silico model of the rat barrel cortex, given in vivo connectivity measurements. SBI identifies a wide range of wiring rule parameters that reproduce the measurements. We show how access to the posterior distribution over all data-compatible parameters allows us to analyze their relationship, revealing biologically plausible parameter interactions and enabling experimentally testable predictions. We further show how SBI can be applied to wiring rules at different spatial scales to quantitatively rule out invalid wiring hypotheses. Our approach is applicable to a wide range of generative models used in connectomics, providing a quantitative and efficient way to constrain model parameters with empirical connectivity data. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:0297-zib-89890 ER - TY - JOUR A1 - Kiewisz, Robert A1 - Fabig, Gunar A1 - Conway, William A1 - Baum, Daniel A1 - Needleman, Daniel A1 - Müller-Reichert, Thomas T1 - Three-dimensional structure of kinetochore-fibers in human mitotic spindles JF - eLife N2 - During cell division, kinetochore microtubules (KMTs) provide a physical linkage between the chromosomes and the rest of the spindle. KMTs in mammalian cells are organized into bundles, so-called kinetochore-fibers (k-fibers), but the ultrastructure of these fibers is currently not well characterized. Here we show by large-scale electron tomography that each k-fiber in HeLa cells in metaphase is composed of approximately nine KMTs, only half of which reach the spindle pole. Our comprehensive reconstructions allowed us to analyze the three-dimensional (3D) morphology of k-fibers and their surrounding MTs in detail. We found that k-fibers exhibit remarkable variation in circumference and KMT density along their length, with the pole-proximal side showing a broadening. Extending our structural analysis then to other MTs in the spindle, we further observed that the association of KMTs with non-KMTs predominantly occurs in the spindle pole regions. Our 3D reconstructions have implications for KMT growth and k-fiber self-organization models as covered in a parallel publication applying complementary live-cell imaging in combination with biophysical modeling (Conway et al., 2022). Finally, we also introduce a new visualization tool allowing an interactive display of our 3D spindle data that will serve as a resource for further structural studies on mitosis in human cells. Y1 - 2022 U6 - https://doi.org/10.7554/eLife.75459 VL - 11 SP - e75459 ER - TY - JOUR A1 - Eigen, Lennart A1 - Baum, Daniel A1 - Dean, Mason N. A1 - Werner, Daniel A1 - Wölfer, Jan A1 - Nyakatura, John A. T1 - Ontogeny of a tessellated surface: carapace growth of the longhorn cowfish Lactoria cornuta JF - Journal of Anatomy N2 - Biological armors derive their mechanical integrity in part from their geometric architectures, often involving tessellations: individual structural elements tiled together to form surface shells. The carapace of boxfish, for example, is comprised of mineralized polygonal plates, called scutes, arranged in a complex geometric pattern and nearly completely encasing the body. In contrast to artificial armors, the boxfish exoskeleton grows with the fish; the relationship between the tessellation and the gross structure of the armor is therefore critical to sustained protection throughout growth. To clarify whether or how the boxfish tessellation is maintained or altered with age, we quantify architectural aspects of the tessellated carapace of the longhorn cowfish Lactoria cornuta through ontogeny (across nearly an order of magnitude in standard length) and in a high-throughput fashion, using high-resolution microCT data and segmentation algorithms to characterize the hundreds of scutes that cover each individual. We show that carapace growth is canalized with little variability across individuals: rather than continually adding scutes to enlarge the carapace surface, the number of scutes is surprisingly constant, with scutes increasing in volume, thickness, and especially width with age. As cowfish and their scutes grow, scutes become comparatively thinner, with the scutes at the edges (weak points in a boxy architecture) being some of the thickest and most reinforced in younger animals and thinning most slowly across ontogeny. In contrast, smaller scutes with more variable curvature were found in the limited areas of more complex topology (e.g. around fin insertions, mouth, and anus). Measurements of Gaussian and mean curvature illustrate that cowfish are essentially tessellated boxes throughout life: predominantly zero curvature surfaces comprised of mostly flat scutes, and with scutes with sharp bends used sparingly to form box edges. Since growth of a curved, tiled surface with a fixed number of tiles would require tile restructuring to accommodate the surface’s changing radius of curvature, our results therefore illustrate a previously unappreciated advantage of the odd boxfish morphology: by having predominantly flat surfaces, it is the box-like body form that in fact permits a relatively straightforward growth system of this tessellated architecture (i.e. where material is added to scute edges). Our characterization of the ontogeny and maintenance of the carapace tessellation provides insights into the potentially conflicting mechanical, geometric and developmental constraints of this species, but also perspectives into natural strategies for constructing mutable tiled architectures. Y1 - 2022 U6 - https://doi.org/10.1111/joa.13692 VL - 241 IS - 3 SP - 565 EP - 580 PB - Wiley ER - TY - JOUR A1 - Schmidt-Ehrenberg, Johannes A1 - Baum, Daniel A1 - Hege, Hans-Christian T1 - Visually stunning - Molecular conformations JF - The Biochemist Y1 - 2001 VL - 23 IS - 5 SP - 22 EP - 26 ER - TY - JOUR A1 - Hoch, Hannelore A1 - Wessel, Andreas A1 - Asche, Manfred A1 - Baum, Daniel A1 - Beckmann, Felix A1 - Bräunig, Peter A1 - Ehrig, Karsten A1 - Mühlethaler, Roland A1 - Riesemeier, Heinrich A1 - Staude, Andreas A1 - Stelbrink, Björn A1 - Wachmann, Ekkehard A1 - Weintraub, Phyllis A1 - Wipfler, Benjamin A1 - Wolff, Carsten A1 - Zilch, Mathias T1 - Non-Sexual Abdominal Appendages in Adult Insects Challenge a 300 Million Year Old Bauplan JF - Current Biology Y1 - 2014 U6 - https://doi.org/10.1016/j.cub.2013.11.040 VL - 24 IS - 1 SP - R16 EP - R17 ER - TY - JOUR A1 - Lindow, Norbert A1 - Baum, Daniel A1 - Leborgne, Morgan A1 - Hege, Hans-Christian T1 - Interactive Visualization of RNA and DNA Structures JF - IEEE Transactions on Visualization and Computer Graphics N2 - The analysis and visualization of nucleic acids (RNA and DNA) is playing an increasingly important role due to their fundamental importance for all forms of life and the growing number of known 3D structures of such molecules. The great complexity of these structures, in particular, those of RNA, demands interactive visualization to get deeper insights into the relationship between the 2D secondary structure motifs and their 3D tertiary structures. Over the last decades, a lot of research in molecular visualization has focused on the visual exploration of protein structures while nucleic acids have only been marginally addressed. In contrast to proteins, which are composed of amino acids, the ingredients of nucleic acids are nucleotides. They form structuring patterns that differ from those of proteins and, hence, also require different visualization and exploration techniques. In order to support interactive exploration of nucleic acids, the computation of secondary structure motifs as well as their visualization in 2D and 3D must be fast. Therefore, in this paper, we focus on the performance of both the computation and visualization of nucleic acid structure. We present a ray casting-based visualization of RNA and DNA secondary and tertiary structures, which enables for the first time real-time visualization of even large molecular dynamics trajectories. Furthermore, we provide a detailed description of all important aspects to visualize nucleic acid secondary and tertiary structures. With this, we close an important gap in molecular visualization. Y1 - 2019 U6 - https://doi.org/10.1109/TVCG.2018.2864507 VL - 25 IS - 1 SP - 967 EP - 976 ER -