Challenges in Physiological Phenotyping of hiPSC-Derived Neurons: From 2D Cultures to 3D Brain Organoids

Electrophysiological characterization of sourced human iPSC-derived motor neurons

Induced pluripotent stem cell (iPSC)-derived motor neurons provide a powerful platform for studying motor neuron diseases. These cells enable human-specific modeling of disease mechanisms and high-throughput drug screening. While commercially available iPSC-derived motor neurons offer a convenient alternative to time-intensive differentiation protocols, their electrophysiological properties and maturation require comprehensive evaluation to validate their utility for research and therapeutic applications. In this study, we characterized the electrophysiological properties of commercially available iPSC-derived motor neurons. Immunofluorescence confirmed the expression of motor neuron-specific biomarkers, indicating successful differentiation and maturation. Electrophysiological recordings revealed stable passive membrane properties, maturation-dependent improvements in action potential kinetics, and progressive increases in repetitive firing. Voltage-clamp analyses confirmed the functional expression of key ion channels, including high- and low-voltage-activated calcium channels, TTX-sensitive and TTX-insensitive sodium channels, and voltage-gated potassium channels. While the neurons exhibited hallmark features of motor neuron physiology, high input resistance, depolarized resting membrane potentials, and limited firing capacity suggest incomplete electrical maturation. Altogether, these findings underscore the potential of commercially available iPSC-derived motor neurons as a practical resource for MND research, while highlighting the need for optimized protocols to support prolonged culture and full maturation.

The Endo-GeneScreen Platform Identifies Drug-Like Probes that Regulate Endogenous Protein Levels within Physiological Contexts

Traditional phenotypic drug discovery platforms have suffered from poor scalability and a lack of mechanistic understanding of newly discovered phenotypic probes. To address this, we created Endo- GeneScreen (EGS), a high-throughput enabled screening platform that identifies bioactive small molecules capable of regulating endogenous protein expression encoded by any preselected target gene within a biologically appropriate context. As a proof-of-concept, EGS successfully identified drug candidates that up-regulate endogenous expression of neuronal Syngap1, a gene that causes a neurodevelopmental disorder when haploinsufficient. For example, SR-1815, a previously unknown and undescribed kinase inhibitor, alleviated major cellular consequences of Syngap1 loss-of-function by restoring normal SynGAP protein levels and dampening neuronal hyperactivity within haploinsufficient neurons. Moreover, we demonstrate that EGS assays accelerate preclinical development of identified drug candidates and facilitate mode-of-action deconvolution studies. Thus, EGS identifies first-in-class bioactive small molecule probes that promote biological discovery and precision therapeutic development.

A systematic review and embryological perspective of pluripotent stem cell-derived autonomic postganglionic neuron differentiation for human disease modeling

Human autonomic neuronal cell models are emerging as tools for modeling diseases such as cardiac arrhythmias. In this systematic review, we compared 33 articles applying 14 different protocols to generate sympathetic neurons and 3 different procedures to produce parasympathetic neurons. All methods involved the differentiation of human pluripotent stem cells, and none employed permanent or reversible cell immortalization. Almost all protocols were reproduced in multiple pluripotent stem cell lines, and over half showed evidence of neural firing capacity. Common limitations in the field are a lack of three-dimensional models and models that include multiple cell types. Sympathetic neuron differentiation protocols largely mirrored embryonic development, with the notable absence of migration, axon extension, and target-specificity cues. Parasympathetic neuron differentiation protocols may be improved by including several embryonic cues promoting cell survival, cell maturation, or ion channel expression. Moreover, additional markers to define parasympathetic neurons in vitro may support the validity of these protocols. Nonetheless, four sympathetic neuron differentiation protocols and one parasympathetic neuron differentiation protocol reported more than two-thirds of cells expressing autonomic neuron markers. Altogether, these protocols promise to open new research avenues of human autonomic neuron development and disease modeling.

Peering into the mind: unraveling schizophrenia's secrets using models

Schizophrenia (SCZ) is a complex mental disorder characterized by a range of symptoms, including positive and negative symptoms, as well as cognitive impairments. Despite the extensive research, the underlying neurobiology of SCZ remain elusive. To overcome this challenge, the use of diverse laboratory modeling techniques, encompassing cellular and animal models, and innovative approaches like induced pluripotent stem cell (iPSC)-derived neuronal cultures or brain organoids and genetically engineered animal models, has been crucial. Immortalized cellular models provide controlled environments for investigating the molecular and neurochemical pathways involved in neuronal function, while iPSCs and brain organoids, derived from patient-specific sources, offer significant advantage in translational research by facilitating direct comparisons of cellular phenotypes between patient-derived neurons and healthy-control neurons. Animal models can recapitulate the different psychopathological aspects that should be modeled, offering valuable insights into the neurobiology of SCZ. In addition, invertebrates' models are genetically tractable and offer a powerful approach to dissect the core genetic underpinnings of SCZ, while vertebrate models, especially mammals, with their more complex nervous systems and behavioral repertoire, provide a closer approximation of the human condition to study SCZ-related traits. This narrative review provides a comprehensive overview of the diverse modeling approaches, critically evaluating their strengths and limitations. By synthesizing knowledge from these models, this review offers a valuable source for researchers, clinicians, and stakeholders alike. Integrating findings across these different models may allow us to build a more holistic picture of SCZ pathophysiology, facilitating the exploration of new research avenues and informed decision-making for interventions.

Using 2D and 3D pluripotent stem cell models to study neurotropic viruses

Understanding the impact of viral pathogens on the human central nervous system (CNS) has been challenging due to the lack of viable human CNS models for controlled experiments to determine the causal factors underlying pathogenesis. Human embryonic stem cells (ESCs) and, more recently, cellular reprogramming of adult somatic cells to generate human induced pluripotent stem cells (iPSCs) provide opportunities for directed differentiation to neural cells that can be used to evaluate the impact of known and emerging viruses on neural cell types. Pluripotent stem cells (PSCs) can be induced to neural lineages in either two- (2D) or three-dimensional (3D) cultures, each bearing distinct advantages and limitations for modeling viral pathogenesis and evaluating effective therapeutics. Here we review the current state of technology in stem cell-based modeling of the CNS and how these models can be used to determine viral tropism and identify cellular phenotypes to investigate virus-host interactions and facilitate drug screening. We focus on several viruses (e.g., human immunodeficiency virus (HIV), herpes simplex virus (HSV), Zika virus (ZIKV), human cytomegalovirus (HCMV), SARS-CoV-2, West Nile virus (WNV)) to illustrate key advantages, as well as challenges, of PSC-based models. We also discuss how human PSC-based models can be used to evaluate the safety and efficacy of therapeutic drugs by generating data that are complementary to existing preclinical models. Ultimately, these efforts could facilitate the movement towards personalized medicine and provide patients and physicians with an additional source of information to consider when evaluating available treatment strategies.

Spontaneous and Perturbational Complexity in Cortical Cultures

Dissociated cortical neurons in vitro display spontaneously synchronized, low-frequency firing patterns, which can resemble the slow wave oscillations characterizing sleep in vivo. Experiments in humans, rodents, and cortical slices have shown that awakening or the administration of activating neuromodulators decrease slow waves, while increasing the spatio-temporal complexity of responses to perturbations. In this study, we attempted to replicate those findings using in vitro cortical cultures coupled with micro-electrode arrays and chemically treated with carbachol (CCh), to modulate sleep-like activity and suppress slow oscillations. We adapted metrics such as neural complexity (NC) and the perturbational complexity index (PCI), typically employed in animal and human brain studies, to quantify complexity in simplified, unstructured networks, both during resting state and in response to electrical stimulation. After CCh administration, we found a decrease in the amplitude of the initial response and a marked enhancement of the complexity during spontaneous activity. Crucially, unlike in cortical slices and intact brains, PCI in cortical cultures displayed only a moderate increase. This dissociation suggests that PCI, a measure of the complexity of causal interactions, requires more than activating neuromodulation and that additional factors, such as an appropriate circuit architecture, may be necessary. Exploring more structured in vitro networks, characterized by the presence of strong lateral connections, recurrent excitation, and feedback loops, may thus help to identify the features that are more relevant to support causal complexity.