Induction of long-term potentiation and depression phenomena in human induced pluripotent stem cell-derived cortical neurons

Verification of the seizure liability of compounds based on their in vitro functional activity in cultured rat cortical neurons and co-cultured human iPSC-derived neurons with astrocytes and in vivo extrapolation to cerebrospinal fluid concentration

Methodical screening of safe and efficient drug candidate compounds is crucial for drug development. A high-throughput and accurate compound evaluation method targeting the central nervous system can be developed using in vitro neural networks. In particular, an evaluation system based on a human-derived neural network that can act as an alternative to animal experiments is desirable to avoid interspecific differences. A microelectrode array (MEA) is one such evaluation system, and can measure in vitro neural activity; however, studies on compound evaluation criteria and in vitro to in vivo extrapolation are scarce. In this study, we identified the parameters that can eliminate the effects of solvents from neural activity data obtained using MEA allow for accurate compound evaluation. Additionally, we resolved the issue associated with compound evaluation criteria during MEA using principal component analysis by considering the neuronal activity exceeding standard deviation (SD) of the solvent as indicator of seizurogenic potential. Overall, 10 seizurogenic compounds and three negative controls were assessed using MEA-based co-cultured human-induced pluripotent stem cell-derived neurons and astrocytes, and primary rat cortical neurons. In addition, we determined rat cerebrospinal fluid (CSF) concentrations during tremor and convulsion in response to exposure to test compounds. To characterize the in vitro to in vivo extrapolation and species differences, we compared the concentrations at which neuronal activity exceeding the SD range of the solvent was detectable using the MEA system and rat CSF concentration.

A functional neuron maturation device provides convenient application on microelectrode array for neural network measurement

BACKGROUND

Microelectrode array (MEA) systems are valuable for in vitro assessment of neurotoxicity and drug efficiency. However, several difficulties such as protracted functional maturation and high experimental costs hinder the use of MEA analysis requiring human induced pluripotent stem cells (hiPSCs). Neural network functional parameters are also needed for in vitro to in vivo extrapolation.

METHODS

In the present study, we produced a cost effective nanofiber culture platform, the SCAD device, for long-term culture of hiPSC-derived neurons and primary peripheral neurons. The notable advantage of SCAD device is convenient application on multiple MEA systems for neuron functional analysis.

RESULTS

We showed that the SCAD device could promote functional maturation of cultured hiPSC-derived neurons, and neurons responded appropriately to convulsant agents. Furthermore, we successfully analyzed parameters for in vitro to in vivo extrapolation, i.e., low-frequency components and synaptic propagation velocity of the signal, potentially reflecting neural network functions from neurons cultured on SCAD device. Finally, we measured the axonal conduction velocity of peripheral neurons.

CONCLUSIONS

Neurons cultured on SCAD devices might constitute a reliable in vitro platform to investigate neuron functions, drug efficacy and toxicity, and neuropathological mechanisms by MEA.

Neuron devices: emerging prospects in neural interfaces and recognition

Neuron interface devices can be used to explore the relationships between neuron firing and synaptic transmission, as well as to diagnose and treat neurological disorders, such as epilepsy and Alzheimer's disease. It is crucial to exploit neuron devices with high sensitivity, high biocompatibility, multifunctional integration and high-speed data processing. During the past decades, researchers have made significant progress in neural electrodes, artificial sensory neuron devices, and neuromorphic optic neuron devices. The main part of the review is divided into two sections, providing an overview of recently developed neuron interface devices for recording electrophysiological signals, as well as applications in neuromodulation, simulating the human sensory system, and achieving memory and recognition. We mainly discussed the development, characteristics, functional mechanisms, and applications of neuron devices and elucidated several key points for clinical translation. The present review highlights the advances in neuron devices on brain-computer interfaces and neuroscience research.

Development of a platform to investigate long-term potentiation in human iPSC-derived neuronal networks

Impairment of long-term potentiation (LTP) is a common feature of many pre-clinical models of neurological disorders; however, studies in humans are limited by the inaccessibility of the brain. Human induced pluripotent stem cells (hiPSCs) provide a unique opportunity to study LTP in disease-specific genetic backgrounds. Here we describe a multi-electrode array (MEA)-based assay to investigate chemically induced LTP (cLTP) across entire networks of hiPSC-derived midbrain dopaminergic (DA) and cortical neuronal populations that lasts for days, allowing studies of the late phases of LTP and enabling detection of associated molecular changes. We show that cLTP on midbrain DA neuronal networks is largely independent of the N-methyl-D-aspartate receptor (NMDAR) and partially dependent on brain-derived neurotrophic factor (BDNF). Finally, we describe activity-regulated gene expression induced by cLTP. This cLTP-MEA assay platform will enable phenotype discovery and higher-throughput analyses of synaptic plasticity on hiPSC-derived neurons.

An improved platform for cultured neuronal network electrophysiology: multichannel optogenetics integrated with MEAs

Cultured neuronal networks (CNNs) are powerful tools for studying how neuronal representation and adaptation emerge in networks of controlled populations of neurons. To ensure the interaction of a CNN and an artificial setting, reliable operation in both open and closed loops should be provided. In this study, we integrated optogenetic stimulation with microelectrode array (MEA) recordings using a digital micromirror device and developed an improved research tool with a 64-channel interface for neuronal network control and data acquisition. We determined the ideal stimulation parameters including light intensity, frequency, and duty cycle for our configuration. This resulted in robust and reproducible neuronal responses. We also demonstrated both open and closed loop configurations in the new platform involving multiple bidirectional channels. Unlike previous approaches that combined optogenetic stimulation and MEA recordings, we did not use binary grid patterns, but assigned an adjustable-size, non-binary optical spot to each electrode. This approach allowed simultaneous use of multiple input-output channels and facilitated adaptation of the stimulation parameters. Hence, we advanced a 64-channel interface in that each channel can be controlled individually in both directions simultaneously without any interference or interrupts. The presented setup meets the requirements of research in neuronal plasticity, network encoding and representation, closed-loop control of firing rate and synchronization. Researchers who develop closed-loop control techniques and adaptive stimulation strategies for network activity will benefit much from this novel setup.

Learning populations with hubs govern the initiation and propagation of spontaneous bursts in neuronal networks after learning

Spontaneous bursts in neuronal networks with propagation involving a large number of synchronously firing neurons are considered to be a crucial feature of these networks both in vivo and in vitro. Recently, learning has been shown to improve the association and synchronization of spontaneous events in neuronal networks by promoting the firing of spontaneous bursts. However, little is known about the relationship between the learning phase and spontaneous bursts. By combining high-resolution measurement with a 4,096-channel complementary metal-oxide-semiconductor (CMOS) microelectrode array (MEA) and graph theory, we studied how the learning phase influenced the initiation of spontaneous bursts in cultured networks of rat cortical neurons in vitro. We found that a small number of selected populations carried most of the stimulus information and contributed to learning. Moreover, several new burst propagation patterns appeared in spontaneous firing after learning. Importantly, these "learning populations" had more hubs in the functional network that governed the initiation of spontaneous burst activity. These results suggest that changes in the functional structure of learning populations may be the key mechanism underlying increased bursts after learning. Our findings could increase understanding of the important role that synaptic plasticity plays in the regulation of spontaneous activity.

High-Throughput PEDOT:PSS/PtNPs-Modified Microelectrode Array for Simultaneous Recording and Stimulation of Hippocampal Neuronal Networks in Gradual Learning Process

When it comes to mechanisms of brain functions such as learning and memory mediated by neural networks, existing multichannel electrophysiological detection and regulation technology at the cellular level does not suffice. To address this challenge, a 128-channel microelectrode array (MEA) was fabricated for electrical stimulation (ES) training and electrophysiological recording of the hippocampal neurons in vitro. The PEDOT:PSS/PtNPs-coated microelectrodes dramatically promote the recording and electrical stimulation performance. The MEA exhibited low impedance (10.94 ± 0.49 kohm), small phase delay (-12.54 ± 0.51°), high charge storage capacity (14.84 ± 2.72 mC/cm²), and high maximum safe injection charge density (4.37 ± 0.22 mC/cm²), meeting the specific requirements for training neural networks in vitro. A series of ESs at various frequencies was applied to the neuronal cultures in vitro, seeking the optimum training mode that enables the neuron to display the most obvious plasticity, and 1 Hz ES was determined. The network learning process, including three consecutive trainings, affected the original random spontaneous activity. Along with that, the firing pattern gradually changed to burst and the correlation and synchrony of the neuronal activity in the network have progressively improved, increasing by 314% and 240%, respectively. The neurons remembered these changes for at least 4 h. Collectively, ES activates the learning and memory functions of neurons, which is manifested in transformations in the discharge pattern and the improvement of network correlation and synchrony. This study offers a high-performance MEA revealing the underlying learning and memory functions of the brain and therefore serves as a useful tool for the development of brain functions in the future.

A functional hiPSC-cortical neuron differentiation and maturation model and its application to neurological disorders

The maturation and functional characteristics of human induced pluripotent stem cell (hiPSC)-cortical neurons has not been fully documented. This study developed a phenotypic model of hiPSC-derived cortical neurons, characterized their maturation process, and investigated its application for disease modeling with the integration of multi-electrode array (MEA) technology. Immunocytochemistry analysis indicated early-stage neurons (day 21) were simultaneously positive for both excitatory (vesicular glutamate transporter 1 [VGlut1]) and inhibitory (GABA) markers, while late-stage cultures (day 40) expressed solely VGlut1, indicating a purely excitatory phenotype without containing glial cells. This maturation process was further validated utilizing patch clamp and MEA analysis. Particularly, induced long-term potentiation (LTP) successfully persisted for 1 h in day 40 cultures, but only achieved LTP in the presence of the GABA_A receptor antagonist picrotoxin in day 21 cultures. This system was also applied to epilepsy modeling utilizing bicuculline and its correction utilizing the anti-epileptic drug valproic acid.

•

Characterization of human cortical neuronal differentiation to a mature phenotype

•

Microelectrode evaluation of development from a mixed to pure excitatory population

•

Utilization of defined culture stage to create an epilepsy model

•

Manipulation of immaturity with inhibitors for maintaining long-term potentiation

Principal Component Analysis to Distinguish Seizure Liability of Drugs in Human iPS Cell-Derived Neurons

Screening for drug discovery targeting the central nervous system requires the establishment of efficient and highly accurate toxicity test methods that can reduce costs and time while maintaining high throughput using the function of an in vitro neural network. In particular, an evaluation system using a human-derived neural network is desirable in terms of species difference. Despite the attention the microelectrode array (MEA) is attracting among the evaluation systems that can measure in vitro neural activity, an effective analysis method for evaluation of toxicity and mechanism of action has not yet been established. Here we established analytical parameters and multivariate analysis method capable of detecting seizure liability of drugs using MEA measurement of human iPS cell-derived neurons. Using the spike time series data of all drugs, we established periodicity as a new analytical parameter. Periodicity has facilitated the detection of responses to seizurogenic drugs, previously difficult to detect with conventional analytical parameters. By constructing a multivariate analytical method that identifies a parameter set that achieves an arbitrary condition, we found that the parameter set comprising total spikes, maximum frequency, inter maximum frequency interval, coefficient of variance of inter maximum frequency interval, and periodicity can uniformly detect the seizure liability of seizurogenic drugs with different mechanisms of action. Seizurogenic drugs were suggested to increase the regularity of the network burst in MEA measurements in human iPS cell-derived neurons.

Molecular Profiling of Human Induced Pluripotent Stem Cell-Derived Cells and their Application for Drug Safety Study

Drug-induced toxicity remains one of the leading causes of discontinuation of the drug candidate and post-marketing withdrawal. Thus, early identification of the drug candidates with the potential for toxicity is crucial in the drug development process. With the recent discovery of human- Induced Pluripotent Stem Cells (iPSC) and the establishment of the differentiation protocol of human iPSC into the cell types of interest, the differentiated cells from human iPSC have garnered much attention because of their potential applicability in toxicity evaluation as well as drug screening, disease modeling and cell therapy. In this review, we expanded on current information regarding the feasibility of human iPSC-derived cells for the evaluation of drug-induced toxicity with a focus on human iPSCderived hepatocyte (iPSC-Hep), cardiomyocyte (iPSC-CMs) and neurons (iPSC-Neurons). Further, we CSAHi, Consortium for Safety Assessment using Human iPS Cells, reported our gene expression profiling data with DNA microarray using commercially available human iPSC-derived cells (iPSC-Hep, iPSC-CMs, iPSC-Neurons), their relevant human tissues and primary cultured human cells to discuss the future direction of the three types of human iPSC-derived cells.

Functional and transcriptional characterization of complex neuronal co-cultures

Brain-on-a-chip systems are designed to simulate brain activity using traditional in vitro cell culture on an engineered platform. It is a noninvasive tool to screen new drugs, evaluate toxicants, and elucidate disease mechanisms. However, successful recapitulation of brain function on these systems is dependent on the complexity of the cell culture. In this study, we increased cellular complexity of traditional (simple) neuronal cultures by co-culturing with astrocytes and oligodendrocyte precursor cells (complex culture). We evaluated and compared neuronal activity (e.g., network formation and maturation), cellular composition in long-term culture, and the transcriptome of the two cultures. Compared to simple cultures, neurons from complex co-cultures exhibited earlier synapse and network development and maturation, which was supported by localized synaptophysin expression, up-regulation of genes involved in mature neuronal processes, and synchronized neural network activity. Also, mature oligodendrocytes and reactive astrocytes were only detected in complex cultures upon transcriptomic analysis of age-matched cultures. Functionally, the GABA antagonist bicuculline had a greater influence on bursting activity in complex versus simple cultures. Collectively, the cellular complexity of brain-on-a-chip systems intrinsically develops cell type-specific phenotypes relevant to the brain while accelerating the maturation of neuronal networks, important features underdeveloped in traditional cultures.

Functional characterization of human pluripotent stem cell-derived cortical networks differentiated on laminin-521 substrate: comparison to rat cortical cultures

Human pluripotent stem cell (hPSC)-derived neurons provide exciting opportunities for in vitro modeling of neurological diseases and for advancing drug development and neurotoxicological studies. However, generating electrophysiologically mature neuronal networks from hPSCs has been challenging. Here, we report the differentiation of functionally active hPSC-derived cortical networks on defined laminin-521 substrate. We apply microelectrode array (MEA) measurements to assess network events and compare the activity development of hPSC-derived networks to that of widely used rat embryonic cortical cultures. In both of these networks, activity developed through a similar sequence of stages and time frames; however, the hPSC-derived networks showed unique patterns of bursting activity. The hPSC-derived networks developed synchronous activity, which involved glutamatergic and GABAergic inputs, recapitulating the classical cortical activity also observed in rodent counterparts. Principal component analysis (PCA) based on spike rates, network synchronization and burst features revealed the segregation of hPSC-derived and rat network recordings into different clusters, reflecting the species-specific and maturation state differences between the two networks. Overall, hPSC-derived neural cultures produced with a defined protocol generate cortical type network activity, which validates their applicability as a human-specific model for pharmacological studies and modeling network dysfunctions.

Application of Microelectrode Array Approaches to Neurotoxicity Testing and Screening

Neurotoxicity can be defined by the ability of a drug or chemical to alter the physiology, biochemistry, or structure of the nervous system in a manner that may negatively impact the health or function of the individual. Electrophysiological approaches have been utilized to study the mechanisms underlying neurotoxic actions of drugs and chemicals for over 50 years, and in more recent decades, high-throughput patch-clamp approaches have been utilized by the pharmaceutical industry for drug development. The use of microelectrode array recordings to study neural network electrophysiology is a relatively newer approach, with commercially available systems becoming available only in the early 2000s. However, MEAs have been rapidly adopted as a useful approach for neurotoxicity testing. In this chapter, I will review the use of MEA approaches as they have been applied to the field of neurotoxicity testing, especially as they have been applied to the need to screen large numbers of chemicals for neurotoxicity and developmental neurotoxicity. In addition, I will also identify challenges for the field that when addressed will improve the utility of MEA approaches for toxicity testing.

In vitro Models for Seizure-Liability Testing Using Induced Pluripotent Stem Cells

The brain is the most complex organ in the body, controlling our highest functions, as well as regulating myriad processes which incorporate the entire physiological system. The effects of prospective therapeutic entities on the brain and central nervous system (CNS) may potentially cause significant injury, hence, CNS toxicity testing forms part of the “core battery” of safety pharmacology studies. Drug-induced seizure is a major reason for compound attrition during drug development. Currently, the rat ex vivo hippocampal slice assay is the standard option for seizure-liability studies, followed by primary rodent cultures. These models can respond to diverse agents and predict seizure outcome, yet controversy over the relevance, efficacy, and cost of these animal-based methods has led to interest in the development of human-derived models. Existing platforms often utilize rodents, and so lack human receptors and other drug targets, which may produce misleading data, with difficulties in inter-species extrapolation. Current electrophysiological approaches are typically used in a low-throughput capacity and network function may be overlooked. Human-derived induced pluripotent stem cells (iPSCs) are a promising avenue for neurotoxicity testing, increasingly utilized in drug screening and disease modeling. Furthermore, the combination of iPSC-derived models with functional techniques such as multi-electrode array (MEA) analysis can provide information on neuronal network function, with increased sensitivity to neurotoxic effects which disrupt different pathways. The use of an in vitro human iPSC-derived neural model for neurotoxicity studies, combined with high-throughput techniques such as MEA recordings, could be a suitable addition to existing pre-clinical seizure-liability testing strategies.

Toxicological evaluation of convulsant and anticonvulsant drugs in human induced pluripotent stem cell-derived cortical neuronal networks using an MEA system

Functional evaluation assays using human induced pluripotent stem cell (hiPSC)-derived neurons can predict the convulsion toxicity of new drugs and the neurological effects of antiepileptic drugs. However, differences in responsiveness depending on convulsant type and antiepileptic drugs, and an evaluation index capable of comparing in vitro responses with in vivo responses are not well known. We observed the difference in synchronized burst patterns in the epileptiform activities induced by pentylentetrazole (PTZ) and 4-aminopryridine (4-AP) with different action mechanisms using multi-electrode arrays (MEAs); we also observed that 100 µM of the antiepileptic drug phenytoin suppressed epileptiform activities induced by PTZ, but increased those induced by 4-AP. To compare in vitro results with in vivo convulsive responses, frequency analysis of below 250 Hz, excluding the spike component, was performed. The in vivo convulsive firing enhancement of the high γ wave and β wave component were observed remarkably in in vitro hiPSC-derived neurons with astrocytes in co-culture. MEA measurement of hiPSC-derived neurons in co-culture with astrocytes and our analysis methods, including frequency analysis, appear effective for predicting convulsion toxicity, side effects, and their mechanism of action as well as the comparison of convulsions induced in vivo.

Uncovering True Cellular Phenotypes: Using Induced Pluripotent Stem Cell-Derived Neurons to Study Early Insults in Neurodevelopmental Disorders

Animal models of neurodevelopmental disorders have provided invaluable insights into the molecular-, cellular-, and circuit-level defects associated with a plethora of genetic disruptions. In many cases, these deficits have been linked to changes in disease-relevant behaviors, but very few of these findings have been translated to treatments for human disease. This may be due to significant species differences and the difficulty in modeling disorders that involve deletion or duplication of multiple genes. The identification of primary underlying pathophysiology in these models is confounded by the accumulation of secondary disease phenotypes in the mature nervous system, as well as potential compensatory mechanisms. The discovery of induced pluripotent stem cell technology now provides a tool to accurately model complex genetic neurogenetic disorders. Using this technique, patient-specific cell lines can be generated and differentiated into specific subtypes of neurons that can be used to identify primary cellular and molecular phenotypes. It is clear that impairments in synaptic structure and function are a common pathophysiology across neurodevelopmental disorders, and electrophysiological analysis at the earliest stages of neuronal development is critical for identifying changes in activity and excitability that can contribute to synaptic dysfunction and identify targets for disease-modifying therapies.

Neural Subtype Specification from Human Pluripotent Stem Cells

Human pluripotent stem cells (hPSCs) provide a model to study early neural development, model pathological processes, and develop therapeutics. The generation of functionally specialized neural subtypes from hPSCs relies on fundamental developmental principles learned from animal studies. Manipulation of these principles enables production of highly enriched neural types with functional attributes that resemble those in the brain. Further development to promote faster maturation or aging as well as circuit integration will help realize the potential of hPSC-derived neural cells in disease modeling and cell therapy.

Disrupted neuronal maturation in Angelman syndrome-derived induced pluripotent stem cells

Angelman syndrome (AS) is a neurogenetic disorder caused by deletion of the maternally inherited UBE3A allele and is characterized by developmental delay, intellectual disability, ataxia, seizures and a happy affect. Here, we explored the underlying pathophysiology using induced pluripotent stem cell-derived neurons from AS patients and unaffected controls. AS-derived neurons showed impaired maturation of resting membrane potential and action potential firing, decreased synaptic activity and reduced synaptic plasticity. These patient-specific differences were mimicked by knocking out UBE3A using CRISPR/Cas9 or by knocking down UBE3A using antisense oligonucleotides. Importantly, these phenotypes could be rescued by pharmacologically unsilencing paternal UBE3A expression. Moreover, selective effects of UBE3A disruption at late stages of in vitro development suggest that changes in action potential firing and synaptic activity may be secondary to altered resting membrane potential. Our findings provide a cellular phenotype for investigating pathogenic mechanisms underlying AS and identifying novel therapeutic strategies.

A comparison of computational methods for detecting bursts in neuronal spike trains and their application to human stem cell-derived neuronal networks

We provide an unbiased quantitative assessment of eight existing methods for identifying bursts in neuronal spike trains. We reveal limitations in a number of commonly used burst detection techniques and provide recommendations for the best practice for accurate identification of bursts using existing techniques. An analysis of the ontogeny of bursting activity in a novel data set of recordings from human induced pluripotent stem cell-derived neuronal networks, using the highest-performing burst detectors from our study, is also presented.

Accurate identification of bursting activity is an essential element in the characterization of neuronal network activity. Despite this, no one technique for identifying bursts in spike trains has been widely adopted. Instead, many methods have been developed for the analysis of bursting activity, often on an ad hoc basis. Here we provide an unbiased assessment of the effectiveness of eight of these methods at detecting bursts in a range of spike trains. We suggest a list of features that an ideal burst detection technique should possess and use synthetic data to assess each method in regard to these properties. We further employ each of the methods to reanalyze microelectrode array (MEA) recordings from mouse retinal ganglion cells and examine their coherence with bursts detected by a human observer. We show that several common burst detection techniques perform poorly at analyzing spike trains with a variety of properties. We identify four promising burst detection techniques, which are then applied to MEA recordings of networks of human induced pluripotent stem cell-derived neurons and used to describe the ontogeny of bursting activity in these networks over several months of development. We conclude that no current method can provide “perfect” burst detection results across a range of spike trains; however, two burst detection techniques, the MaxInterval and logISI methods, outperform compared with others. We provide recommendations for the robust analysis of bursting activity in experimental recordings using current techniques.