Modeling the radial glia niche: Deciphering key mechanotransduction components

Abstract

[eng] Radial glial (RG) are the principal neural stem cells of the embryonic brain, giving rise to intermediate progenitors and fate-committed neural cell types, and serving as a mechanical scaffold for neuron migration and correct cortical patterning. The lack of RG cells in the adult brain is considered a hallmark of the reduced endogenous brain regenerative capacity in some species. From the mechanobiology point of view, brain histogenesis encompasses a continuum of mechanical cues, metabolic shifts and transcriptional changes that orchestrate the construction of a healthy brain through a fine-tuned balance of mechanotransducive processes. The use of biomaterial-based strategies provides an excellent opportunity to model the architectural features of the embryonic brain. Ln2PMMA is an RG biomimetic substrate of poly methyl methacrylate with 2μm linear topography that reproduced the surface properties and mechanical anisotropy of the RG niche during embryonic brain development, with the capability to induce cultured astrocytes to dedifferentiate into functional RG cells. Although the mechanotransducive components underlying this process are largely unknown. In this Doctoral Thesis, we used mouse cortical glial cultures and ln2PMMA RG biomimetic material as a robust biomechanical tool for the in vitro analysis of mechanotransducive mechanisms involved in RG linage differentiation, allowing us to define some of the mechano-electrical -metabolic and -nuclear components of the astrocyte-RG lineage progression in response to substrate biomechanical cues. First, we developed a unified image segmentation analysis, based on MATLAB algorithms, for the extraction of morphology parameters from subcellular structures, linked to biochemically identified cells from microscopy images. Second, we developed a multivariate logistic regression model for fitting RG probability based in nuclear morphology parameters and cell density. The application of this model to our experimental data revealed the existence of intrinsic RG nuclear constraints, and that nuclear deformation and changes in nuclear lamins ratio precedes the expression of NSC/RG markers. Third, by using pharmacological inhibitors and Ca2+ imaging, together with RG molecular markers, we determined the implication of excitatory and inhibitory mechanosensitive ion channels, changes in CaMKII activity and in intracellular calcium dynamics, in the biomechanical induction of RG. Fourth, we identified a metabolic switch from astrocyte to RG, involving changes in mitochondrial dynamics and a bias towards increased aerobic glycolysis and anabolic metabolism. Finally, the application of the RGM model to image datasets from mouse and human neural cells allows us to identify the evolutionary conservation of RG nuclear constraints. Converting our RGM model, and their future improved versions, into an invaluable tool with unsuspected possibilities for the analysis of brain development.