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Villoutreix, P.

Publications and source records attributed to Villoutreix, P..

2 recordsLinked to original sources

Multiscale analysis of 3D nuclear morphology reveals new insights into growth plate organization in mice

The shape of the nucleus is tightly associated with cell morphology, the mechanical environment, and differentiation and transcriptional states. Yet, imaging of nuclei in three dimensions while preserving the spatial context of the tissue has been highly challenging. Here, using the embryonic tibial growth plate as a model for cell differentiation, we study nuclear morphology by imaging cleared samples by light-sheet fluorescence microscopy. Next, we quickly segmented tens of thousands of nuclei using several open-source tools including machine learning. Finally, segmented nuclei underwent morphometric analysis and 3D spatial reconstruction using newly designed algorithms. Our method revealed differences in nuclear morphology between chondrocytes at different differentiation stages. Additionally, we identified different morphological patterns in opposing growth plates, such as gradients of volume and surface area, as well as features characteristic of specific growth plate zones, such as sphericity and orientation. Altogether, this work supports a link between nuclear morphology and cell differentiation. Moreover, it demonstrates the suitability of our approach for studying the relationships between nuclear morphology and organ development.\n\nAuthor summaryThere has been a growing interest in the relationship between nuclear morphology and its regulation of gene expression. However, to study global patterns of nuclear morphology within a tissue we must address the problem of acquiring and analyzing multiscale data, ranging from the tissue level through to subcellular resolution. We have established a new pipeline that enables acquisition and segmentation of hundreds of thousands of nuclei at a resolution that allows quantitative analysis. Moreover we have developed new algorithms that allow superimposing morphological aspects of hundreds of thousands of nuclei onto a visual representation of the entire tissue, allowing us to study nuclear morphology at an organ level. Using mouse growth plates as a model for the relationship between nuclear morphology and tissue differentiation, we show that nuclei change different aspects of their morphology during chondrocyte differentiation. Growth plates are usually described generically in the literature, suggesting they lack unique characteristics. We challenge this dogma by showing that morphological features such as volume distribute differently in opposing growth plates. Altogether, this work highlights the possible role of nuclear shape in the regulation of cell differentiation and demonstrates that our approach enables the study of nuclear morphology patterns within a tissue.

developmental biology

Synthesizing developmental trajectories

Dynamical processes in biology are studied using an ever-increasing number of techniques, each of which brings out unique features of the system. One of the current challenges is to develop systematic approaches for fusing heterogeneous datasets into an integrated view of multivariable dynamics. We demonstrate that heterogeneous data fusion can be successfully implemented within a semi-supervised learning framework that exploits the intrinsic geometry of high-dimensional datasets. We illustrate our approach using a dataset from studies of pattern formation in Drosophila. The result is a continuous trajectory that reveals the joint dynamics of gene expression, subcellular protein localization, protein phosphorylation, and tissue morphogenesis. Our approach can be readily adapted to other imaging modalities and forms a starting point for further steps of data analytics and modeling of biological dynamics.

developmental biology