Biology subjects

Wolny, A.

Publications and source records attributed to Wolny, A..

10 recordsLinked to original sources

bioRxiv2024

A deep learning-based toolkit for 3D nuclei segmentation and quantitative analysis in cellular and tissue context

We present a new set of computational tools that enable accurate and widely applicable 3D segmentation of nuclei in various 3D digital organs. We developed a novel approach for ground truth generation and iterative training of 3D nuclear segmentation models, which we applied to popular CellPose, PlantSeg, and StarDist algorithms. We provide two high-quality models trained on plant nuclei that enable 3D segmentation of nuclei in datasets obtained from fixed or live samples, acquired from different plant and animal tissues, and stained with various nuclear stains or fluorescent protein-based nuclear reporters. We also share a diverse high-quality training dataset of about 10,000 nuclei. Furthermore, we advanced the MorphoGraphX analysis and visualization software by, among other things, providing a method for linking 3D segmented nuclei to their surrounding cells in 3D digital organs. We found that the nuclear-to-cell volume ratio varies between different ovule tissues and during the development of a tissue. Finally, we extended the PlantSeg 3D segmentation pipeline with a proofreading script that uses 3D segmented nuclei as seeds to correct cell segmentation errors in difficult-to-segment tissues. Summary StatementWe present computational tools that allow versatile and accurate 3D nuclear segmentation in plant organs, enable the analysis of cell-nucleus geometric relationships, and improve the accuracy of 3D cell segmentation.

plant biology↗

bioRxiv2023

Temporal variability and cell mechanics control robustness in mammalian embryogenesis

How living systems achieve precision in form and function despite their intrinsic stochasticity is a fundamental yet open question in biology. Here, we establish a quantitative morphomap of pre-implantation embryogenesis in mouse, rabbit and monkey embryos, which reveals that although blastomere divisions desynchronise passively without compensation, 8-cell embryos still display robust 3D structure. Using topological analysis and genetic perturbations in mouse, we show that embryos progressively change their cellular connectivity to a preferred topology, which can be predicted by a simple physical model where noise and actomyosin-driven compaction facilitate topological transitions lowering surface energy. This favours the most compact embryo packing at the 8- and 16-cell stage, thus promoting higher number of inner cells. Impairing mitotic desynchronisation reduces embryo packing compactness and generates significantly more cell mis-allocation and a lower proportion of inner-cell-mass-fated cells, suggesting that stochasticity in division timing contributes to achieving robust patterning and morphogenesis.

developmental biology↗

bioRxiv2022

COORDINATION BETWEEN EMBRYO GROWTH AND TROPHOBLAST MIGRATION UPON IMPLANTATION DELINEATES MOUSE EMBRYOGENESIS

Implantation marks a key transition in mammalian development. The role of embryo-uterus interaction in periimplantation development is however poorly understood due to inaccessibility in utero. Here, we develop an engineered uterus-like microenvironment to recapitulate mouse development ex vivo up to E5.25 and discover an essential role of integrin-mediated trophoblast adhesion to the uterine matrix. Light-sheet microscopy shows that trophoblast cells undergo Rac1-dependent collective migration upon implantation, displacing Reicherts membrane and generating space for egg cylinder growth. The key role of coordination between trophoblast migration and embryo growth is verified by experimentally manipulating the migration velocity and geometry of the engineered uterus. Modeling the implanting embryo as a wetting droplet links the tissue shape dynamics to underlying changes in trophoblast adhesion and suggests that the corresponding tension release facilitates egg cylinder formation. Together, this study provides mechanisms by which dynamic embryo-uterus interactions play an essential role in peri-implantation development.

developmental biology↗

bioRxiv2021

From shallow to deep: exploiting feature-based classifiers for domain adaptation in semantic segmentation

The remarkable performance of Convolutional Neural Networks on image segmentation tasks comes at the cost of a large amount of pixelwise annotated images that have to be segmented for training. In contrast, feature-based learning methods, such as the Random Forest, require little training data, but never reach the segmentation accuracy of CNNs. This work bridges the two approaches in a transfer learning setting. We show that a CNN can be trained to correct the errors of the Random Forest in the source domain and then be applied to correct such errors in the target domain without retraining, as the domain shift between the Random Forest predictions is much smaller than between the raw data. By leveraging a few brushstrokes as annotations in the target domain, the method can deliver segmentations that are sufficiently accurate to act as pseudo-labels for target-domain CNN training. We demonstrate the performance of the method on several datasets with the challenging tasks of mitochondria, membrane and nuclear segmentation. It yields excellent performance compared to microscopy domain adaptation baselines, especially when a significant domain shift is involved.

bioinformatics↗

bioRxiv2021

A robust ex vivo system to study cellular dynamics underlying mouse peri-implantation development

Upon implantation, mammalian embryos undergo major morphogenesis and key developmental processes such as body axis specification and gastrulation. However, limited accessibility obscures study of these crucial processes. Here, we develop an ex vivo Matrigel-collagen-based culture to recapitulate mouse development from E4.5 to 6.0. Our system not only recapitulates embryonic growth, axis initiation, and overall 3D architecture in 49% of cases, its compatibility with light-sheet microscopy enables study of cellular dynamics through automatic cell segmentation. We find that upon implantation, release of the increasing tension in the polar trophectoderm is necessary for its constriction and invagination. The resulting extra-embryonic ectoderm plays a key role in growth, morphogenesis and patterning of the neighboring epiblast, which subsequently gives rise to all embryonic tissues. This 3D-ex vivo system thus offers an unprecedented access to peri-implantation development for in toto monitoring, measurement and spatio-temporally controlled perturbation, revealing a mechano-chemical interplay between extra-embryonic and embryonic tissues.

developmental biology↗

bioRxiv2020

Integration of Cell Growth and Asymmetric Division During Lateral Root Initiation In Arabidopsis thaliana

Lateral root formation determines to a large extent the ability of plants to forage their environment and thus their growth. In Arabidopsis thaliana and other angiosperms, lateral root initiation requires radial cell expansion and several rounds of anticlinal cell divisions that give rise to a central core of small pericycle cells, which express different markers than the larger surrounding cells. These small central cells then switch their plane of divisions to periclinal, and give rise to seemingly morphologically similar daughter cells that have different identities and establish the different cell types of the new root. Although the execution of these two types of divisions is tightly regulated and essential for the correct development of the lateral root, we know little about their geometrical features. Here we analyse a four-dimensional reconstruction of the first stages of lateral root formation and analyze the geometric features of the anticlinal and periclinal divisions. We identify that the periclinal divisions of the small central cells are morphologically dissimilar and asymmetric. We show that mother cell volume is different when looking at anticlinal versus periclinal divisions and the repeated anticlinal divisions do not lead to reduction in cell volume although cells are shorter. Finally, we show that cells undergoing a periclinal division are characterized by a strong cell expansion. Our results indicate that cells integrate growth and division to precisely partition their volume upon division during the first two stages of lateral root formation.

plant biology↗

bioRxiv2020

A digital 3D reference atlas reveals cellular growth patterns shaping the Arabidopsis ovule

A fundamental question in biology is how morphogenesis integrates the multitude of distinct processes that act at different scales, ranging from the molecular control of gene expression to cellular coordination in a tissue. Investigating morphogenesis of complex organs strongly benefits from three-dimensional representations of the organ under study. Here, we present a digital analysis of ovule development from Arabidopsis thaliana as a paradigm for a complex morphogenetic process. Using machine-learning-based image analysis we generated a three-dimensional atlas of ovule development with cellular resolution. It allows quantitative stage- and tissue-specific analysis of cellular patterns. Exploiting a fluorescent reporter enabled precise spatial determination of gene expression patterns, revealing subepidermal expression of WUSCHEL. Underlying the power of our approach, we found that primordium outgrowth progresses evenly, discovered a novel mode of forming a new cell layer, and detected a new function of INNER NO OUTER in restricting cell proliferation in the nucellus. Moreover, we identified two distinct subepidermal cell populations that make crucial contributions to ovule curvature. Our work demonstrates the expedience of a three-dimensional digital representation when studying the morphogenesis of an organ of complex cellular architecture and shape that eventually consists of 1,900 cells.

plant biology↗

bioRxiv2020

Microscopy-based assay for semi-quantitative detection of SARS-CoV-2 specific antibodies in human sera

Emergence of the novel pathogenic coronavirus SARS-CoV-2 and its rapid pandemic spread presents numerous questions and challenges that demand immediate attention. Among these is the urgent need for a better understanding of humoral immune response against the virus as a basis for developing public health strategies to control viral spread. For this, sensitive, specific and quantitative serological assays are required. Here we describe the development of a semi-quantitative high-content microscopy-based assay for detection of three major classes (IgG, IgA and IgM) of SARS-CoV-2 specific antibodies in human samples. The possibility to detect antibodies against the entire viral proteome together with a robust semi-automated image analysis workflow resulted in specific, sensitive and unbiased assay which complements the portfolio of SARS-CoV-2 serological assays. The procedure described here has been used for clinical studies and provides a general framework for the application of quantitative high-throughput microscopy to rapidly develop serological assays for emerging virus infections.

microbiology↗

bioRxiv2020

Ultrastructural Visualization of 3D Chromatin Folding Using Serial Block-Face Scanning Electron Microscopy and In Situ Hybridization (3D-EMISH)

The human genome is extensively folded into 3-dimensional organization, yet the detailed 3D chromatin folding structures have not been fully visualized due to the lack of robust and ultra- resolution imaging capability. Here, we report the development of a novel electron microscopy method that combines serial block-face scanning electron microscopy with in situ hybridization (3D-EMISH) to visualize 3D chromatin folding at targeted genomic regions with ultra-resolution (5x5x30 nm in xyz dimensions, respectively). We applied 3D-EMISH to human lymphoblastoid cells at a 1.7 Mb segment of the genome and visualized a large number of distinctive 3D chromatin folding structures in high ultra-resolution. We further quantitatively characterized the reconstituted chromatin folding structures by identifying sub-domains, and uncovered a high level of heterogeneity in chromatin folding ultrastructures, suggestive of extensive dynamic fluidity in 3D chromatin states.

genomics↗

bioRxiv2020

Accurate And Versatile 3D Segmentation Of Plant Tissues At Cellular Resolution

Quantitative analysis of plant and animal morphogenesis requires accurate segmentation of individual cells in volumetric images of growing organs. In the last years, deep learning has provided robust automated algorithms that approach human performance, with applications to bio-image analysis now starting to emerge. Here, we present PlantSeg, a pipeline for volumetric segmentation of plant tissues into cells. PlantSeg employs a convolutional neural network to predict cell boundaries and graph partitioning to segment cells based on the neural network predictions. PlantSeg was trained on fixed and live plant organs imaged with confocal and light sheet microscopes. PlantSeg delivers accurate results and generalizes well across different tissues, scales, and acquisition settings. We present results of PlantSeg applications in diverse developmental contexts. PlantSeg is free and open-source, with both a command line and a user-friendly graphical interface.

plant biology↗