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|3D microenvironments for in vitro modeling of alzheimer’s disease
|Ranjan, Vivek Damodar
|Nanyang Technological University
|Ranjan, V. D. (2020). 3D microenvironments for in vitro modeling of alzheimer’s disease. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/146832
|Alzheimer’s disease (AD) has become increasingly prevalent owing to the rise in aging population, heightening life-expectancy, and lack of effective treatments. Understanding AD pathogenesis requires the development and study of model systems which can ideally mirror all aspects of the disease. Increasing evidence indicates the superiority of three-dimensional (3D) in vitro cell culture platforms over conventionally used two-dimensional (2D) monolayer cultures in mimicking native in vivo microenvironments. However, existing 3D culture models of AD rely on engineered cell lines which overexpress mutant genes or aggregate-based cultures with heterogeneities in composition, biological properties and cell differentiation stages. These limitations motivate exploration of alternative in vitro substrate-based human neuronal AD models with better reproducibility and matrix uniformity. In this study, tissue engineering techniques are leveraged on for fabrication of three novel biomaterial-based scaffolding platforms for achieving in vitro 3D neuronal culture. These include: a graphene oxide hydrogel-based electroconductive substrate fabricated via physical crosslinking; a synthetic polymer-based hollow microfiber substrate fabricated via core-shell electrospinning; and a synthetic polymer-based, non-woven fibrillar substrate fabricated via wet electrospinning. All three platforms were evaluated in terms of cell encapsulation, distribution, viability, proliferation, neuronal differentiation and neurite formation to determine their feasibility for facilitating long-term 3D neuronal culture. Data from immunocytochemistry clearly indicate wet electrospun, non-woven poly(lactic-co-glycolic acid) (PLGA) microtopographic scaffolds to be the most suitable substrate in terms of design criteria encompassing both physical and biological properties. The highly porous fibrillar scaffolds supported enhanced infiltration, uniform distribution and long-term survival of human stem cell-derived neurons. In addition, the microfiber scaffold stiffness was found to mimic the elasticity of native brain tissue, indicating its capability to promote realistic physiological responses in cellular phenotypes. Next, key neural stem cell features including proliferation and differentiation in 3D culture were compared with Petri dish-based 2D monolayer controls. The 3D fibrillar microenvironment reduced cell proliferation and significantly accelerated both neuronal and glial differentiation within seven days of culture. Finally, the scaffolds were interfaced with familial AD (FAD) patient induced pluripotent stem cells (iPSC)-derived neurons for in vitro modeling of early-stage AD pathogenesis. The differentiated neurons in 3D PLGA scaffold-based culture exhibited significant amplification in pathogenic amyloid-beta 42 (Aβ42) and phospho-tau (p-tau) levels between diseased and age-matched controls. Furthermore, spontaneous expression levels of these pathogenic markers in 3D culture were more pronounced compared with corresponding 2D monolayer control cultures. Taken together, the present findings represent the first demonstration of interfacing 3D synthetic polymer-based fibrillar scaffolds with iPSC-derived human neuronal cultures to robustly recapitulate and accelerate early-stage AD pathogenesis. Moreover, it serves as a simple, standardisable and easy to implement in vitro platform, which facilitates highly efficient neuronal differentiation and significantly faster maturation compared with conventional monolayer cultures. This platform can be further broadened for modeling of other complex neurodegenerative diseases as well as evaluation of prospective therapeutic candidates.
|Interdisciplinary Graduate School (IGS)
|NTU Institute for Health Technologies
|This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).
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Updated on Feb 24, 2024
Updated on Feb 24, 2024
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