Uniform neural tissue models produced on synthetic hydrogels using standard culture techniques.

ABSTRACT

The aim of the present study was to test sample reproducibility for model neural tissues formed on synthetic hydrogels. Human embryonic stem (ES) cell-derived precursor cells were cultured on synthetic poly(ethylene glycol) (PEG) hydrogels to promote differentiation and self-organization into model neural tissue constructs. Neural progenitor, vascular, and microglial precursor cells were combined on PEG hydrogels to mimic developmental timing, which produced multicomponent neural constructs with 3D neuronal and glial organization, organized vascular networks, and microglia with ramified morphologies. Spearman's rank correlation analysis of global gene expression profiles and a comparison of coefficient of variation for expressed genes demonstrated that replicate neural constructs were highly uniform to at least day 21 for samples from independent experiments. We also demonstrate that model neural tissues formed on PEG hydrogels using a simplified neural differentiation protocol correlated more strongly to in vivo brain development than samples cultured on tissue culture polystyrene surfaces alone. These results provide a proof-of-concept demonstration that 3D cellular models that mimic aspects of human brain development can be produced from human pluripotent stem cells with high sample uniformity between experiments by using standard culture techniques, cryopreserved cell stocks, and a synthetic extracellular matrix. Impact statement Pluripotent stem (PS) cells have been characterized by an inherent ability to self-organize into 3D "organoids" resembling stomach, intestine, liver, kidney, and brain tissues, offering a potentially powerful tool for modeling human development and disease. However, organoid formation must be quantitatively reproducible for applications such as drug and toxicity screening. Here, we report a strategy to produce uniform neural tissue constructs with reproducible global gene expression profiles for replicate samples from multiple experiments.