Chemo-mechanical control of neural stem cell differentiation.

摘要

Cellular processes such as adhesion, proliferation, and differentiation are controlled in part by cell interactions with the microenvironment. Cells can sense and respond to a variety of stimuli, including soluble and insoluble factors (such as proteins and small molecules) and externally applied mechanical stresses. Mechanical properties of the environment, such as substrate stiffness, have also been suggested to play an important role in cell processes. The roles of both biochemical and mechanical signaling in fate modification of stem cells have been explored independently. However, very few studies have been performed to study well-controlled chemo-mechanotransduction. The objective of this work is to design, synthesize, and characterize a chemo-mechanical substrate to encourage neuronal differentiation of C17.2 neural stem cells. In Chapter 2, Polyacrylamide (PA) gels of varying stiffnesses are functionalized with differing amounts of whole collagen to investigate the role of protein concentration in combination with substrate stiffness. As expected, neurons on the softest substrate were more in number and neuronal morphology than those on stiffer substrates. Neurons appeared locally aligned with an expansive network of neurites. Additional experiments would allow for statistical analysis to determine if and how collagen density impacts C17.2 differentiation in combination with substrate stiffness. Due to difficulties associated with whole protein approaches, a similar platform was developed using mixed adhesive peptides, derived from fibronectin and laminin, and is presented in Chapter 3. The matrix elasticity and peptide concentration can be individually modulated to systematically probe the effects of chemo-mechanical signaling on differentiation of C17.2 cells. Polyacrylamide gel stiffness was confirmed using rheological techniques and found to support values published by Yeung et al. [1]. Cellular growth and differentiation were assessed by cell counts, immunocytochemistry (ICC), and neurite measurements. Data indicates that chemo-mechanical signaling is highly combinatorial in directing differentiation of C17.2s along a neuronal lineage in vitro. Chapter 4 discusses the design, synthesis, and characterization of a novel nanomaterial platform to investigate ligand-receptor binding. PEGylated nanoparticles were successfully synthesized and found to be relatively homogenous in size and morphology, as observed by transmission electron microscopy. However, successful binding of RGD peptide to the nanoparticle was not confirmed. Finally, a method for proteomic analysis of the C17.2 secretome is discussed in Chapter 5. Secreted proteins are of great importance as they can both influence cell behaviors as well as act as biomarkers of differentiation. Methods have been selected and optimized for protein extraction and two dimensional gel electrophoresis to be followed by mass spectrometry and protein identification. A temporal analysis of unique proteins expressed by C17.2s will result in a differentiation timeline. Deducing the dynamics of neuronal cell secretions will greatly contribute to the characterization of the C17.2 cell line and improve its relevance as a neural stem cell model. Overall, results illustrate the importance of chemical and mechanical cues in manipulating neural stem cell fate. These material platforms in combination with the further characterization of the C17.2 neural stem cells could have a great impact in the fields of neuronal biology, translational therapeutics, and pharmaceutical research.