Biology subjects

Hugger, J.

Publications and source records attributed to Hugger, J..

2 recordsLinked to original sources

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↗

bioRxiv2022

MorphoFeatures: unsupervised exploration of cell types, tissues and organs in volume electron microscopy

Electron microscopy (EM) provides a uniquely detailed view of cellular morphology, including organelles and fine subcellular ultrastructure. While the acquisition and (semi-)automatic segmentation of multicellular EM volumes is now becoming routine, large-scale analysis remains severely limited by the lack of generally applicable pipelines for automatic extraction of comprehensive morphological descriptors. Here, we present a novel unsupervised method for learning cellular morphology features directly from 3D EM data: a convolutional neural network delivers a representation of cells by shape and ultrastructure. Applied to the full volume of an entire three-segmented worm of the annelid Platynereis dumerilii, it yields a visually consistent grouping of cells supported by specific gene expression profiles. Integration of features across spatial neighbours can retrieve tissues and organs, revealing, for example, a detailed organization of the animal foregut. We envision that the unbiased nature of the proposed morphological descriptors will enable rapid exploration of very different biological questions in large EM volumes, greatly increasing the impact of these invaluable, but costly resources.

developmental biology↗