RESUMEN
BACKGROUND: Alzheimer's disease (AD), a progressive neurodegenerative disorder, is becoming increasingly prevalent as our population ages. It is characterized by the buildup of amyloid beta plaques and neurofibrillary tangles containing hyperphosphorylated-tau. The current treatments for AD do not prevent the long-term progression of the disease and pre-clinical models often do not accurately represent its complexity. Bioprinting combines cells and biomaterials to create 3D structures that replicate the native tissue environment and can be used as a tool in disease modeling or drug screening. METHODS: This work differentiated both healthy and diseased patient-derived human induced pluripotent stems cells (hiPSCs) into neural progenitor cells (NPCs) that were bioprinted using the Aspect RX1 microfluidic printer into dome-shaped constructs. The combination of cells, bioink, and puromorphamine (puro)-releasing microspheres were used to mimic the in vivo environment and direct the differentiation of the NPCs into basal forebrain-resembling cholinergic neurons (BFCN). These tissue models were then characterized for cell viability, immunocytochemistry, and electrophysiology to evaluate their functionality and physiology for use as disease-specific neural models. RESULTS: Tissue models were successfully bioprinted and the cells were viable for analysis after 30- and 45-day cultures. The neuronal and cholinergic markers ß-tubulin III (Tuj1), forkhead box G1 (FOXG1), and choline acetyltransferase (ChAT) were identified as well as the AD markers amyloid beta and tau. Further, immature electrical activity was observed when the cells were excited with potassium chloride and acetylcholine. CONCLUSIONS: This work shows the successful development of bioprinted tissue models incorporating patient derived hiPSCs. Such models can potentially be used as a tool to screen promising drug candidates for treating AD. Further, this model could be used to increase the understanding of AD progression. The use of patient derived cells also shows the potential of this model for use in personalized medicine applications.
RESUMEN
Three-dimensional bioprinting utilizes additive manufacturing processes that combine cells and a bioink to create living tissue models that mimic tissues found in vivo. Stem cells can regenerate and differentiate into specialized cell types, making them valuable for research concerning degenerative diseases and their potential treatments. 3D bioprinting stem cell-derived tissues have an advantage over other cell types because they can be expanded in large quantities and then differentiated to multiple cell types. Using patient-derived stem cells also enables a personalized medicine approach to the study of disease progression. In particular, mesenchymal stem cells (MSC) are an attractive cell type for bioprinting because they are easier to obtain from patients in comparison to pluripotent stem cells, and their robust characteristics make them desirable for bioprinting. Currently, both MSC bioprinting protocols and cell culturing protocols exist separately, but there is a lack of literature that combines the culturing of the cells with the bioprinting process. This protocol aims to bridge that gap by describing the bioprinting process in detail, starting with how to culture cells pre-printing, to 3D bioprinting the cells, and finally to the culturing process post-printing. Here, we outline the process of culturing MSCs to produce cells for 3D bioprinting. We also describe the process of preparing Axolotl Biosciences TissuePrint - High Viscosity (HV) and Low Viscosity (LV) bioink, the incorporation of MSCs to the bioink, setting up the BIO X and the Aspect RX1 bioprinters, and necessary computer-aided design (CAD) files. We also detail the differentiation of 2D and 3D cell cultures of MSC to dopaminergic neurons, including media preparation. We have also included the protocols for viability, immunocytochemistry, electrophysiology, and performing a dopamine enzyme-linked immunosorbent assay (ELISA), along with the statistical analysis. Graphical overview.