Functional Characterization of Human iPSC-Derived Neural Networks using MEA Systems for in vitro Modeling of Psychiatric Disorders

Abstract

Psychiatric disorders are associated with major societal, personal issues and comprise 13% of the global burden of disease. They are heritable and present a complex pathophysiology, characterized by hundreds of genetic variants which are cumulated together and provoke a specific psychiatric disorder. Although a considerable progress has been made in the identification of genetics variants, the way a cellular phenotype is related to a gene expression caused by biological pathways remains unclear. Significant effort has been focused, over the last years, on psychiatric diseases modeling, to investigate the complex, polygenic neurobiological nature of these disorders. Human induced pluripotent stem cell (iPSC) technology has been widely used for in vitro disease modeling. Human iPSCs can be readily derived from patients and differentiated into any cell type including neurons. The functional characterization of neurons constitutes a challenging procedure and different electrophysiological techniques can be applied. A hallmark of a non-invasive technique, in which the neuronal network dynamics can be observed, is the Microelectrode Array (MEA) measurements. The functional characterization of neuronal activity contributes to the cellular phenotype investigation of neuronal cultures, derived from patients who are affected by psychiatric disorders. The cellular phenotypes could be used as readouts for high-throughput pharmacological screenings and enhance the development of new drugs. In the current thesis project, the combination of a long-term neural differentiation protocol with extracellular MEA measurements was implemented, to assess the spontaneous and synchronized network activity of human iPSC-derived neural cultures. This protocol generates both neurons and astrocytes from a common neural progenitor cell (NPC) into a control ratio (60:40). A commercial MEA system (Multiwell-MEA, Multi Channel Systems, GmbH, Germany) was used for extracellular recordings on the neural populations. Additionally, a spike sorting analysis was performed for spike waveform observation. Experimental results presented a robust network activity derived from neural populations cultivated in neuronal medium (BrainPhys), for a period of ten weeks in vitro. Neuronal activity was characterized in terms of cumulative firing rate (CFR) per cell culture and mean firing rate (MFR) per electrode. Results showed a peak CFR of 1700 spikes/minute/culture (±260 SEM) and a peak MFR of 215 spikes/minute/electrode (±22.5 SEM). Additionally, a bursting activity was constantly detected on a scale of 270 burst/10 minutes/culture (±31 SEM), during the period of ten weeks in vitro. A spike sorting analysis verified the successful monitoring of spikes’ waveforms derived from the same unit of neurons in a two-week period. 88% of the detected waveform patterns presented a normalized cross-correlation higher than 0.9, which reinforced the argument that the electrodes detected electrical activity derived from the same unit of neurons in a constant way. This project contributes to the creation of an optimized functional readout of human neural model in vitro, which, in a long-term vision, could be used as reference point for comparison between healthy and diseased cell lines derived from patients with psychiatric disorders.