Integrated, automated maintenance, expansion and differentiation of 2D and 3D patient-derived cellular models for high throughput drug screening.

Patient-derived cellular models become an increasingly powerful tool to model human diseases for precision medicine approaches. The identification of robust cellular disease phenotypes in these models paved the way towards high throughput screenings (HTS) including the implementation of laboratory advanced automation. However, maintenance and expansion of cells for HTS remains largely manual work. Here, we describe an integrated, complex automated platform for HTS in a translational research setting also designed for maintenance and expansion of different cell types. The comprehensive design allows automation of all cultivation steps and is flexible for development of methods for variable cell types. We demonstrate protocols for controlled cell seeding, splitting and expansion of human fibroblasts, induced pluripotent stem cells (iPSC), and neural progenitor cells (NPC) that allow for subsequent differentiation into different cell types and image-based multiparametric screening. Furthermore, we provide automated protocols for neuronal differentiation of NPC in 2D culture and 3D midbrain organoids for HTS. The flexibility of this multitask platform makes it an ideal solution for translational research settings involving experiments on different patient-derived cellular models for precision medicine.

Screening of a neuronal cell model of tau pathology for therapeutic compounds.

We have developed a cell-based phenotypic automated high-content screening approach for N2a cells expressing the pro-aggregant repeat domain of tau protein (tauRDΔK), which allows analysis of a chemogenomic library of 1649 compounds for their effect on the inhibition or stimulation of intracellular tau aggregation. We identified several inhibitors and stimulators of aggregation and achieved a screening reproducibility >85% for all data. We identified 18 potential inhibitors (= 1.1% of the library) and 10 stimulators (= 0.6% of the library) of tau aggregation in this cell model of tau pathology. The results provide insights into the regulation of cellular tau aggregation and the pathways involved in this process (e.g., involving signaling via p38 mitogen-activated protein kinase, histone deacetylases, vascular endothelial growth factor, rho/ROCK). For example, inhibitors of protein kinases (e.g., p38) can reduce tau aggregation, whereas inhibitors of deacetylases (histone deacetylases) can enhance aggregation. These observations are compatible with reports that phosphorylated or acetylated tau promotes pathology.