Electrophysiological Characterization of iPSC-derived Cortical Neurons Using Automated Patch Clamp

Human-induced pluripotent stem cells (hiPSCs) can be differentiated into many cell types, including neurons and cardiomyocytes, and therefore constitute a novel way to model human diseases¹. However, hiPSC-based applications are often challenged by the variability among differentiation batches, even when using iPSC lines originating from a single donor, and by heterogeneity among specific cell types derived from iPSCs². Here we demonstrate the application of high throughput electrophysiological measurements using our automated patch clamp (APC) platform, Qube 384, for characterization of iPSC-derived cortical neurons.

Generic cortical neurons were differentiated from iPSCs using small molecules under dual-SMAD inhibition conditions³. The cells were handled and differentiated in parallel, and a total of three independent differentiation batches were carried out. We conducted an electrophysiological analysis of the endogenous ion channel expression in the three different batches of iPSC neurons. In agreement with sequencing data, the measurements revealed a good reproducibility between the three iPSC batches with 60 % – 70 % of the investigated cells expressing voltage-gated Na⁺ (Na_v) channels and 60 % – 80 % expressing voltage-gated K⁺ (Kv) channels. Furthermore, filtering the measurements for the ion channel of interest, allowed a thorough biophysical and pharmacological investigation of the individual ion channels.

Finally, we compared iPSC-derived neurons from a patient (proband) carrying a missense mutation in cyclin-dependent kinase-like 5 (CDKL5) (c.871T>C, p.Cys291Arg), who was clinically diagnosed to present with classic CDKL5 Deficiency Disorder (CDD), with cells derived from an isogenic control. Using immunostaining, whole transcriptome analysis, and electrophysiological measurements we found that proband neurons were larger and had a more immature morphology, suggesting that they do not differentiate as efficiently as the control neurons.