Publikationen Abteilung Neuronale Mechanik

Spinal cord injuries have devastating consequences for humans, as mammalian neurons of the central nervous system (CNS) cannot regenerate. In the peripheral nervous system (PNS), however, neurons may regenerate to restore lost function following injury. While mammalian CNS tissue softens after injury, how PNS tissue mechanics changes in response to mechanical trauma is currently poorly understood. Here we characterised mechanical rat nerve tissue properties before and after in vivo crush and transection injuries using atomic force microscopy-based indentation measurements. Unlike CNS tissue, PNS tissue significantly stiffened after both types of tissue damage. This nerve tissue stiffening strongly correlated with an increase in collagen I levels. Schwann cells, which crucially support PNS regeneration, became more motile and proliferative on stiffer substrates in vitro, suggesting that changes in tissue stiffness may play a key role in facilitating or impeding nervous system regeneration.

Local mechanical tissue properties are a critical regulator of cell function in the central nervous system (CNS) during development and disorder. However, we still don't fully understand how the mechanical properties of individual tissue constituents, such as cell nuclei or myelin, determine tissue mechanics. Here we developed a model predicting local tissue mechanics, which induces non-affine deformations of the tissue components. Using the mouse hippocampus and cerebellum as model systems, we show that considering individual tissue components alone, as identified by immunohistochemistry, is not sufficient to reproduce the local mechanical properties of CNS tissue. Our results suggest that brain tissue shows a universal response to applied forces that depends not only on the amount and stiffness of the individual tissue constituents but also on the way how they assemble. Our model may unify current incongruences between the mechanics of soft biological tissues and the underlying constituents and facilitate the design of better biomedical materials and engineered tissues. To this end, we provide a freely-available platform to predict local tissue elasticity upon providing immunohistochemistry images and stiffness values for the constituents of the tissue.

Biomechanical cues are instrumental in guiding embryonic development and cell differentiation. Understanding how these physical stimuli translate into transcriptional programs will provide insight into mechanisms underlying mammalian pre-implantation development. Here, we explore this type of regulation by exerting microenvironmental control over mouse embryonic stem cells. Microfluidic encapsulation of mouse embryonic stem cells in agarose microgels stabilizes the naive pluripotency network and specifically induces expression of Plakoglobin (Jup), a vertebrate homolog of β-catenin. Overexpression of Plakoglobin is sufficient to fully re-establish the naive pluripotency gene regulatory network under metastable pluripotency conditions, as confirmed by single-cell transcriptome profiling. Finally, we find that, in the epiblast, Plakoglobin was exclusively expressed at the blastocyst stage in human and mouse embryos - further strengthening the link between Plakoglobin and naive pluripotency in vivo. Our work reveals Plakoglobin as a mechanosensitive regulator of naive pluripotency and provides a paradigm to interrogate the effects of volumetric confinement on cell-fate transitions.

The basement membrane (BM) is a specialized extracellular matrix (ECM), which underlies or encases developing tissues. Mechanical properties of encasing BMs have been shown to profoundly influence the shaping of associated tissues. Here, we use the migration of the border cells (BCs) of the Drosophila egg chamber to unravel a new role of encasing BMs in cell migration. BCs move between a group of cells, the nurse cells (NCs), that are enclosed by a monolayer of follicle cells (FCs), which is, in turn, surrounded by a BM, the follicle BM. We show that increasing or reducing the stiffness of the follicle BM, by altering laminins or type IV collagen levels, conversely affects BC migration speed and alters migration mode and dynamics. Follicle BM stiffness also controls pairwise NC and FC cortical tension. We propose that constraints imposed by the follicle BM influence NC and FC cortical tension, which, in turn, regulate BC migration. Encasing BMs emerge as key players in the regulation of collective cell migration during morphogenesis.

Eph receptors and their membrane-bound ligands, ephrins, provide key signals in many developmental processes including neuronal guidance. However, despite immense progress in our understanding of Eph/ephrin signaling, discrepancies between in vitro and in vivo work remain. As axon pathfinding is regulated by chemical and mechanical signals, and the mechanical regulation of Eph/ephrin signaling is currently poorly understood, we here investigated the role of mechanical cues in this signaling pathway. Xenopus retinal neurons cultured on soft substrates mechanically resembling brain tissue had the opposite response to ephrinB1 compared to those cultured on glass. Furthermore, in vivo atomic force microscopy data showed that the Xenopus visual area of the brain, the optic tectum, becomes mechanically heterogenous as retinal neurons approach the diencephalon-tectum boundary and begin to innervate it. The stiffness gradient which develops correlates with both a cell density gradient and a concentration gradient of EphB expression detected by hybridization chain reaction. Since EphB/ephrinB signaling in Xenopus retinal neurons is affected by substrate stiffness in vitro, and a stiffness gradient develops across the optic tectum at the time of innervation, our data suggest that mechanical cues could be important in tuning retinotectal mapping through the regulation of chemical signaling. A similar regulation of chemical signaling through tissue mechanics is likely to be important across multiple aspects of neural development, as well as in other organ systems.