Cortical interneuron function in autism spectrum condition.

Cortical interneurons (INs) are a diverse group of neurons that project locally and shape the function of neural networks throughout the brain. Multiple lines of evidence suggest that a proper balance of glutamate and GABA signaling is essential for both the proper function and development of the brain. Dysregulation of this system may lead to neurodevelopmental disorders, including autism spectrum condition (ASC). We evaluate the development and function of INs in rodent and human models and examine how neurodevelopmental dysfunction may produce core symptoms of ASC. Finding common physiological mechanisms that underlie neurodevelopmental disorders may lead to novel pharmacological targets and candidates that could improve the cognitive and emotional symptoms associated with ASC.

Development of a 3-D Organoid System Using Human Induced Pluripotent Stem Cells to Model Idiopathic Autism.

Autism spectrum condition (ASC) is a complex set of behavioral and neurological responses reflecting a likely interaction between autism susceptibility genes and the environment. Autism represents a spectrum in which heterogeneous genetic backgrounds are expressed with similar heterogeneity in the affected domains of communication, social interaction, and behavior. The impact of gene-environment interactions may also account for differences in underlying neurology and wide variation in observed behaviors. For these reasons, it has been difficult for geneticists and neuroscientists to build adequate systems to model the complex neurobiology causes of autism. In addition, the development of therapeutics for individuals with autism has been painstakingly slow, with most treatment options reduced to repurposed medications developed for other neurological diseases. Adequately developing therapeutics that are sensitive to the genetic and neurobiological diversity of individuals with autism necessitates personalized models of ASC that can capture some common pathways that reflect the neurophysiological and genetic backgrounds of varying individuals. Testing cohorts of individuals with and without autism for these potentially convergent pathways on a scalable platform for therapeutic development requires large numbers of samples from a diverse population. To date, human induced pluripotent stem cells (iPSCs) represent one of the best systems for conducting these types of assays in a clinically relevant and scalable way. The discovery of the four Yamanaka transcription factors (OCT3/4, SOX2, c-Myc, and KLF4) [1] allows for the induction of iPSCs from fibroblasts [2], peripheral blood mononuclear cells (PBMCs, i.e. lymphocytes and monocytes) [3, 4], or dental pulp cells [5] that retain the original genetics of the individual from which they were derived [6], making iPSCs a powerful tool to model neurophysiological conditions. iPSCs are a readily renewable cell type that can be developed on a small scale for boutique-style proof-of-principle phenotypic studies and scaled to an industrial level for drug screening and other high-content assays. This flexibility, along with the ability to represent the true genetic diversity of autism, underscores the importance of using iPSCs to model neurophysiological aspects of ASC.

High-throughput screening of human induced pluripotent stem cell-derived brain organoids.

BACKGROUND: The need for scalable high-throughput screening (HTS) approaches for 3D human stem cell platforms remains a central challenge for disease modeling and drug discovery. We have developed a workflow to screen cortical organoids across platforms. NEW METHOD: We used serum-free embryoid bodies (SFEBs) derived from human induced pluripotent stem cells (hiPSCs) and employed high-content imaging (HCI) to assess neurite outgrowth and cellular composition within SFEBs. We multiplexed this screening assay with both multi-electrode arrays (MEAs) and single-cell calcium imaging. RESULTS: HCI was used to assess the number of excitatory neurons (VGlut+) in experimental replicates of hiPSC-derived SFEBs, demonstrating experiment-to-experiment consistency. Neurite detection using HCI was applied to assess neurite morphology. MEA analysis showed that firing and burst rates in SFEBs decreased with blockade of NMDARs and AMPARs and increased with GABAR blockade. We also demonstrate effective combination of both MEA and HCI to analyze VGlut+ populations surrounding electrodes within MEAs. HCI-based (Ca2+) transient analysis revealed firing in individual cells surrounding active MEA electrodes. COMPARISON WITH EXISTING METHODS: Current methods to generate neural organoids show high degrees of variability, and often require sectioning or special handling for analysis. The protocol outlined in this manuscript generates SFEBs with high degree of consistency making them amenable to complex assays combining HTS and electrophysiology allowing for an in-depth, unbiased analysis. CONCLUSIONS: SFEBs can be used in combination with HTS to compensate for experimental variability common in 3D cultures, while significantly decreasing processing speed, making this an efficient starting point for phenotypic drug screening.