PhD Candidate The Salk Institute La Jolla, CA, United States
Abstract: Understanding key events of Alzheimer’s disease (AD) etiology resulting in neuronal network dysregulation is essential for illuminating the cause of memory loss in AD. Functional, human derived brain tissues that represent the diverse genetic background and cellular subtypes contributing to sporadic AD (sAD) are limited. Human induced pluripotent stem cell (iPSC) derived brain organoids recapitulate some features of AD-like pathology, providing a tool for investigating the relationship between AD pathology and neural cell dysregulation leading to cognitive decline. However, the percentage of astrocytes is often lower in brain organoids than in human brains. Our lab has developed protocols for the generation of astrocyte-enriched brain organoids (AEOs) containing amounts of astrocytes exceeding those of non-astrocyte enriched brain organoid protocols. We generated AEOs from the iPSCs of sAD patient and non-AD donor controls. AEOs were cultured for 7.5 to 10 months to achieve complex neural network organization comprised of both inhibitory and excitatory neurons. Using Axion Biosystems 16 electrode, multielectrode array (MEA) technology, we explored functional, neuronal network activity patterns of sAD compared to control derived AEOs. sAD AEOs have an impaired ability to organize spiking and bursting activity into complex patterns of network bursts as demonstrated by a decrease in reverberating burst patterns in sAD AEOs relative to controls. sAD AEOs also show decreased functional connectivity, indicated by using a spike time tiling coefficient that revealed a decrease in correlated electrode activity, when compared to control AEOs. To explore mechanisms that could be contributing to the disruption of complex bursting patterns and decreased functional connectivity of sAD AEOs, we performed pharmacological treatments, single-cell RNA-sequencing (scRNA-seq), and immunohistochemistry. Together, this data suggests a dysregulation in the inhibitory to excitatory ratio of AD AEO neural networks compared to control AEOs.
