Calcium-Dependent Hyperexcitability in Human Stem Cell-Derived Rett Syndrome Neuronal Networks.

Background: Mutations in MECP2 predominantly cause Rett syndrome and can be modeled in vitro using human stem cell-derived neurons. Patients with Rett syndrome have signs of cortical hyperexcitability, such as seizures. Human stem cell-derived MECP2 null excitatory neurons have smaller soma size and reduced synaptic connectivity but are also hyperexcitable due to higher input resistance. Paradoxically, networks of MECP2 null neurons show a decrease in the frequency of network bursts consistent with a hypoconnectivity phenotype. Here, we examine this issue. Methods: We reanalyzed multielectrode array data from 3 isogenic MECP2 cell line pairs recorded over 6 weeks (n = 144). We used a custom burst detection algorithm to analyze network events and isolated a phenomenon that we termed reverberating super bursts (RSBs). To probe potential mechanisms of RSBs, we conducted pharmacological manipulations using bicuculline, EGTA-AM, and DMSO on 1 cell line (n = 34). Results: RSBs, often misidentified as single long-duration bursts, consisted of a large-amplitude initial burst followed by several high-frequency, low-amplitude minibursts. Our analysis revealed that MECP2 null networks exhibited increased frequency of RSBs, which produced increased bursts compared with isogenic controls. Bicuculline or DMSO treatment did not affect RSBs. EGTA-AM selectively eliminated RSBs and rescued network burst dynamics. Conclusions: During early development, MECP2 null neurons are hyperexcitable and produce hyperexcitable networks. This may predispose them to the emergence of hypersynchronic states that potentially translate into seizures. Network hyperexcitability depends on asynchronous neurotransmitter release that is likely driven by presynaptic Ca2+ and can be rescued by EGTA-AM to restore typical network dynamics.

Directed differentiation of human hindbrain neuroepithelial stem cells recapitulates cerebellar granule neurogenesis.

Cerebellar granule neurons (CGNs) are the most abundant neurons in the human brain. Dysregulation of their development underlies movement disorders and medulloblastomas. It is suspected that these disorders arise in progenitor states of the CGN lineage, for which human models are lacking. Here, we have differentiated human hindbrain neuroepithelial stem (hbNES) cells to CGNs in vitro using soluble growth factors, recapitulating key progenitor states in the lineage. We show that hbNES cells are not lineage committed and retain rhombomere 1 regional identity. Upon differentiation, hbNES cells transit through a rhombic lip (RL) progenitor state at day 7, demonstrating human specific sub-ventricular cell identities. This RL state is followed by an ATOH1+ CGN progenitor state at day 14. By the end of a 56-day differentiation procedure, we obtain functional neurons expressing CGN markers GABAARα6 and vGLUT2. We show that sonic hedgehog promotes GABAergic lineage specification and CGN progenitor proliferation. Our work presents a new model with which to study development and diseases of the CGN lineage in a human context.

Multielectrode Arrays for Functional Phenotyping of Neurons from Induced Pluripotent Stem Cell Models of Neurodevelopmental Disorders.

In vitro multielectrode array (MEA) systems are increasingly used as higher-throughput platforms for functional phenotyping studies of neurons in induced pluripotent stem cell (iPSC) disease models. While MEA systems generate large amounts of spatiotemporal activity data from networks of iPSC-derived neurons, the downstream analysis and interpretation of such high-dimensional data often pose a significant challenge to researchers. In this review, we examine how MEA technology is currently deployed in iPSC modeling studies of neurodevelopmental disorders. We first highlight the strengths of in vitro MEA technology by reviewing the history of its development and the original scientific questions MEAs were intended to answer. Methods of generating patient iPSC-derived neurons and astrocytes for MEA co-cultures are summarized. We then discuss challenges associated with MEA data analysis in a disease modeling context, and present novel computational methods used to better interpret network phenotyping data. We end by suggesting best practices for presenting MEA data in research publications, and propose that the creation of a public MEA data repository to enable collaborative data sharing would be of great benefit to the iPSC disease modeling community.

SHANK2 mutations associated with autism spectrum disorder cause hyperconnectivity of human neurons.

Heterozygous loss-of-function mutations in SHANK2 are associated with autism spectrum disorder (ASD). We generated cortical neurons from induced pluripotent stem cells derived from neurotypic and ASD-affected donors. We developed sparse coculture for connectivity assays where SHANK2 and control neurons were differentially labeled and sparsely seeded together on a lawn of unlabeled control neurons. We observed increases in dendrite length, dendrite complexity, synapse number, and frequency of spontaneous excitatory postsynaptic currents. These findings were phenocopied in gene-edited homozygous SHANK2 knockout cells and rescued by gene correction of an ASD SHANK2 mutation. Dendrite length increases were exacerbated by IGF1, TG003, or BDNF, and suppressed by DHPG treatment. The transcriptome in isogenic SHANK2 neurons was perturbed in synapse, plasticity, and neuronal morphogenesis gene sets and ASD gene modules, and activity-dependent dendrite extension was impaired. Our findings provide evidence for hyperconnectivity and altered transcriptome in SHANK2 neurons derived from ASD subjects.