Kirigami electronics for long-term electrophysiological recording of human neural organoids and assembloids

PEDOT: PSS-Modified Organic Flexible and Implantable Microelectrode for Internal Bi-Directional Electrophysiology of Three-Dimensional Cardiomyocyte Spheroid

Three-dimensional (3D) cardiomyocyte spheroids are essential models to replicate cardiac structural and functional features in vitro. However, conventional planar and rigid microelectrode arrays (MEAs) suffer from low-quality electrophysiological recording of 3D cultures, due to limited contact areas and weak coupling between cells and MEA chips. Herein, we developed a PEDOT: PSS-modified organic flexible and implantable MEA (OFI-MEA) coupled with a self-developed integrated biosensing platform to achieve high-throughput, long-term, and stable bidirectional internal electrophysiology in 3D cardiomyocyte spheroids. Electrostimulation enhanced the functional performance of the 3D cardiomyocytes, causing a remarkable 2.69-fold increase in frequency. Furthermore, time-frequency analysis of the multisite electrophysiological signals to highlight diverse cell activity patterns in the spheroids. It provides a powerful tool to record electrophysiological signals of 3D cardiomyocyte spheroids, allowing continuing evaluation of cardiac dynamics and regulation of electrical signals, providing a novel evaluation strategy for cardiac disease model construction, drug screening, and cardiological research.

Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) affect 4.7% of the global population and are associated with delays in brain development and a spectrum of impairments that can lead to lifelong disability and even mortality. Identification of biomarkers for accurate diagnosis and medications for effective treatment are lacking, in part due to the historical use of preclinical model systems that do not translate well to the clinic for neurological disorders, such as rodents and heterologous cell lines. Human-induced pluripotent stem cells (hiPSCs) are a promising in vitro system for modeling NDDs, providing opportunities to understand mechanisms driving NDDs in human neurons. Functional assays, including patch clamping, multielectrode array, and imaging-based assays, are popular tools employed with hiPSC disease models for disease investigation. Recent progress in machine learning (ML) algorithms also presents unprecedented opportunities to advance the NDD research process. In this review, we compare two-dimensional and three-dimensional hiPSC formats for disease modeling, discuss the applications of functional assays, and offer insights on incorporating ML into hiPSC-based NDD research and drug screening.

Advances in physiological and clinical relevance of hiPSC-derived brain models for precision medicine pipelines

Precision, or personalized, medicine aims to stratify patients based on variable pathogenic signatures to optimize the effectiveness of disease prevention and treatment. This approach is favorable in the context of brain disorders, which are often heterogeneous in their pathophysiological features, patterns of disease progression and treatment response, resulting in limited therapeutic standard-of-care. Here we highlight the transformative role that human induced pluripotent stem cell (hiPSC)-derived neural models are poised to play in advancing precision medicine for brain disorders, particularly emerging innovations that improve the relevance of hiPSC models to human physiology. hiPSCs derived from accessible patient somatic cells can produce various neural cell types and tissues; current efforts to increase the complexity of these models, incorporating region-specific neural tissues and non-neural cell types of the brain microenvironment, are providing increasingly relevant insights into human-specific neurobiology. Continued advances in tissue engineering combined with innovations in genomics, high-throughput screening and imaging strengthen the physiological relevance of hiPSC models and thus their ability to uncover disease mechanisms, therapeutic vulnerabilities, and tissue and fluid-based biomarkers that will have real impact on neurological disease treatment. True physiological understanding, however, necessitates integration of hiPSC-neural models with patient biophysical data, including quantitative neuroimaging representations. We discuss recent innovations in cellular neuroscience that can provide these direct connections through generative AI modeling. Our focus is to highlight the great potential of synergy between these emerging innovations to pave the way for personalized medicine becoming a viable option for patients suffering from neuropathologies, particularly rare epileptic and neurodegenerative disorders.

Insulative Compression of Neuronal Tissues on Microelectrode Arrays by Perfluorodecalin Enhances Electrophysiological Measurements

Microelectrode array (MEA) techniques provide a powerful method for exploration of neural network dynamics. A critical challenge is to interface 3D neural tissues including neural organoids with the flat MEAs surface, as it is essential to place neurons near to the electrodes for recording weak extracellular signals of neurons. To enhance performance of MEAs, most research have focused on improving their surface treatment, while little attention has been given to improve the tissue-MEA interactions from the medium side. Here, a strategy is introduced to augment MEA measurements by overlaying perfluorodecalin (PFD), a biocompatible fluorinated solvent, over neural tissues. Laying PFD over cerebral organoids insulates and compresses the tissues on MEA, which significantly enhances electrophysiological recordings. Even subtle signals such as the propagation of action potentials in bundled axons of motor nerve organoids can be detected with the technique. Moreover, PFD stabilizes tissues in acute recordings and its transparency allows optogenetic manipulations. This research highlights the potential of PFD as a tool for refining electrophysiological measurements of in vitro neuronal cultures. This can open new avenues to leverage precision of neuroscientific investigations and expanding the toolkit for in vitro studies of neural function and connectivity.

Highly Stretchable 3D Microelectrode Array for Noninvasive Functional Evaluation of Cardiac Spheroids and Midbrain Organoids

Organoids are 3D biological models that recapitulate the complex structures and functions of human organs. Despite the rapid growth in the generation of organoids, in vitro assay tools are still limited to 2D forms. Thus, a comprehensive and continuous functional evaluation of the electrogenic organoids remains a challenge. Here, a highly stretchable 3D multielectrode array (sMEA) with protruding microelectrodes is presented for functional evaluation of electrogenic organoids. The optimized serpentine structures with bridge structures cover the surface of the organoids conformally even in immersion. The protruding microelectrodes form a stable contact with the organoids and allow electrophysiological recordings with high signal-to-noise ratio (SNR). sMEAs are fabricated in wafer-scale for repeatable, scalable, and mass production and packed into an easy-to-use, user-friendly, and robust microwell for fast dissemination of technology. The versatility of sMEA is validated by measuring electrophysiological signals from cardiac spheroids and midbrain organoids with a wide range of sizes from 500 to 1500 µm. Also, electrophysiological signals recorded with high SNR enable functional evaluation of the effects of drugs. The proposed sMEA with high SNR and user-friendly interface could be the key player in high-throughput drug screening, 3D spatiotemporal mapping of electrogenic organoids, and standardization of protocols for quality assessment.

Modelling human brain development and disease with organoids

Organoids are systems derived from pluripotent stem cells at the interface between traditional monolayer cultures and in vivo animal models. The structural and functional characteristics of organoids enable the modelling of early stages of brain development in a physiologically relevant 3D environment. Moreover, organoids constitute a tool with which to analyse how individual genetic variation contributes to the susceptibility and progression of neurodevelopmental disorders. This Roadmap article describes the features of brain organoids, focusing on the neocortex, and their advantages and limitations - in comparison with other model systems - for the study of brain development, evolution and disease. We highlight avenues for enhancing the physiological relevance of brain organoids by integrating bioengineering techniques and unbiased high-throughput analyses, and discuss future applications. As organoids advance in mimicking human brain functions, we address the ethical and societal implications of this technology.

PEDOT-based stretchable optoelectronic materials and devices for bioelectronic interfaces

The rapid development of wearable and implantable electronics has enabled the real-time transmission of electrophysiological signals in situ, thus allowing the precise monitoring and regulation of biological functions. Devices based on organic materials tend to have low moduli and intrinsic stretchability, making them ideal choices for the construction of seamless bioelectronic interfaces. In this case, as an organic ionic-electronic conductor, poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) has low impedance to offer a high signal-to-noise ratio for monitoring bioelectrical signals, which has become one of the most promising conductive polymers. However, the initial conductivity and stretchability of pristine PEDOT:PSS are insufficient to meet the application requirements, and there is a trade-off between their improvement. In addition, PEDOT:PSS has poor stability in aqueous environments due to the hygroscopicity of the PSS chains, which severely limits its long-term applications in water-rich bioelectronic interfaces. Considering the growing demands of multi-function integration, the high-resolution fabrication of electronic devices is urgent. It is a great challenge to maintain both electrical and mechanical performance after miniaturization, particularly at feature sizes below 100 μm. In this review, we focus on the combined improvement in the conductivity and stretchability of PEDOT:PSS, as well as the corresponding mechanisms in detail. Also, we summarize the effective strategies to improve the stability of PEDOT:PSS in aqueous environments, which plays a vital role in long-term applications. Finally, we introduce the reliable micropatterning technologies and PEDOT:PSS-based stretchable optoelectronic devices applied at bio-interfaces.

The e-Flower: A hydrogel-actuated 3D MEA for brain spheroid electrophysiology

Traditional microelectrode arrays (MEAs) are limited to measuring electrophysiological activity in two dimensions, failing to capture the complexity of three-dimensional (3D) tissues such as neural organoids and spheroids. Here, we introduce a flower-shaped MEA (e-Flower) that can envelop submillimeter brain spheroids following actuation by the sole addition of the cell culture medium. Inspired by soft microgrippers, its actuation mechanism leverages the swelling properties of a polyacrylic acid hydrogel grafted to a polyimide substrate hosting the electrical interconnects. Compatible with standard electrophysiology recording systems, the e-Flower does not require additional equipment or solvents and is ready to use with preformed 3D tissues. We designed an e-Flower achieving a curvature as low as 300 micrometers within minutes, a value tunable by the choice of reswelling media and hydrogel cross-linker concentration. Furthermore, we demonstrate the ability of the e-Flower to detect spontaneous neural activity across the spheroid surface, demonstrating its potential for comprehensive neural signal recording.

How is Excitotoxicity Being Modelled in iPSC-Derived Neurons?

Excitotoxicity linked either to environmental causes (pesticide and cyanotoxin exposure), excitatory neurotransmitter imbalance, or to intrinsic neuronal hyperexcitability, is a pathological mechanism central to neurodegeneration in amyotrophic lateral sclerosis (ALS). Investigation of excitotoxic mechanisms using in vitro and in vivo animal models has been central to understanding ALS mechanisms of disease. In particular, advances in induced pluripotent stem cell (iPSC) technologies now provide human cell-based models that are readily amenable to environmental and network-based excitotoxic manipulations. The cell-type specific differentiation of iPSC, combined with approaches to modelling excitotoxicity that include editing of disease-associated gene variants, chemogenetics, and environmental risk-associated exposures make iPSC primed to examine gene-environment interactions and disease-associated excitotoxic mechanisms. Critical to this is knowledge of which neurotransmitter receptor subunits are expressed by iPSC-derived neuronal cultures being studied, how their activity responds to antagonists and agonists of these receptors, and how to interpret data derived from multi-parameter electrophysiological recordings. This review explores how iPSC-based studies have contributed to our understanding of ALS-linked excitotoxicity and highlights novel approaches to inducing excitotoxicity in iPSC-derived neurons to further our understanding of its pathological pathways.

Bipolar electrochemical growth of conductive microwires for cancer spheroid integration: a step forward in conductive biological circuitry

The field of bioelectronics is developing exponentially. There is now a drive to interface electronics with biology for the development of new technologies to improve our understanding of electrical forces in biology. This builds on our recently published work in which we show wireless electrochemistry could be used to grow bioelectronic functional circuitry in 2D cell layers. To date our ability to merge electronics with in situ with biology is 3D limited. In this study, we aimed to further develop the wireless electrochemical approach for the self-assembly of microwires in situ with custom-designed and fabricated 3D cancer spheroids. Unlike traditional electrochemical methods that rely on direct electrical connections to induce currents, our technique utilises bipolar electrodes that operate independently of physical wired connections. These electrodes enable redox reactions through the application of an external electric field. Specifically, feeder electrodes connected to a power supply generate an electric field, while the bipolar electrodes, not physically connected to the feeder electrodes, facilitate the reduction of silver ions from the solution. This process occurs upon applying a voltage across the feeder electrodes, resulting in the formation of self-assembled microwires between the cancer spheroids.Thereby, creating interlinked bioelectronic circuitry with cancer spheroids. We demonstrate that a direct current was needed to stimulate the growth of conductive microwires in the presence of cell spheroids. Microwire growth was successful when using 50 V (0.5 kV/cm) of DC applied to a single spheroid of approximately 800 µm in diameter but could not be achieved with alternating currents. This represents the first proof of the concept of using wireless electrochemistry to grow conductive structures with 3D mammalian cell spheroids.

Interfacing Neuron-Motor Pathways with Stretchable and Biocompatible Electrode Arrays

ConspectusIn the field of neuroscience, understanding the complex interactions within the intricate neuron-motor system depends crucially on the use of high-density, physiological multiple electrode arrays (MEAs). In the neuron-motor system, the transmission of biological signals primarily occurs through electrical and chemical signaling. Taking neurons for instance, when a neuron receives external stimuli, it generates an electrical signal known as the action potential. This action potential propagates along the neuron's axon and is transmitted to other neurons via synapses. At the synapse, chemical signals (neurotransmitters) are released, allowing the electrical signal to traverse the synaptic gap and influence the next neuron. MEAs can provide unparalleled insights into neural signal patterns when interfacing with the nerve systems through their excellent spatiotemporal resolution. However, the inherent differences in mechanical and chemical properties between these artificial devices and biological tissues can lead to serious complications after chronic implantation, such as body rejection, infection, tissue damage, or device malfunction. A promising strategy to enhance MEAs' biocompatibility involves minimizing their thickness, which aligns their bending stiffness with that of surrounding tissues, thereby minimizing damage over time. However, this solution has its limits; the resulting ultrathin devices, typically based on plastic films, lack the necessary stretchability, restricting their use to organs that neither stretch nor grow.For practical deployments, devices must exhibit certain levels of stretchability (ranging from 20 to 70%), tailored to the specific requirements of the target organs. In this Account, we outline recent advancements in developing stretchable MEAs that balance stretchability with sufficient electrical conductivity for effective use in physiological research, acting as sensors and stimulators. By concentrating on the neuron-motor pathways, we summarize how the stretchable MEAs meet various application needs and examine their effectiveness. We distinguish between on-skin and implantable uses, given their vastly different requirements. Within each application scope, we highlight cutting-edge technologies, evaluating their strengths and shortcomings. Recognizing that most current devices rely on elastic films with a Young's modulus value between ∼0.5 and 5 MPa, we delve into the potential for softer MEAs, particularly those using multifunctional hydrogels for an optimizing tissue-device interface and address the challenges in adapting such hydrogel-based MEAs for chronic implants. Additionally, transitioning soft MEAs from lab to fab involves connecting them to a rigid adapter and external machinery, highlighting a critical challenge at the soft-rigid interface due to strain concentration, especially in chronic studies subject to unforeseen mechanical strains. We discuss innovative solutions to this integration challenge, being optimistic that the development of durable, biocompatible, stretchable MEAs will significantly advance neuroscience and related fields.

Beyond 25 years of biomedical innovation in nano-bioelectronics

Nano-bioelectronics, which blend the precision of nanotechnology with the complexity of biological systems, are evolving with innovations such as silicon nanowires, carbon nanotubes, and graphene. These elements serve applications from biochemical sensing to brain-machine interfacing. This review examines nano-bioelectronics' role in advancing biomedical interventions and discusses their potential in environmental monitoring, agricultural productivity, energy efficiency, and creative fields. The field is transitioning from molecular to ecosystem-level applications, with research exploring complex cellular mechanisms and communication. This fosters understanding of biological interactions at various levels, such as suggesting transformative approaches for ecosystem management and food security. Future research is expected to focus on refining nano-bioelectronic devices for integration with biological systems and on scalable manufacturing to broaden their reach and functionality.

Limitations of human brain organoids to study neurodegenerative diseases: a manual to survive

In 2013, M. Lancaster described the first protocol to obtain human brain organoids. These organoids, usually generated from human-induced pluripotent stem cells, can mimic the three-dimensional structure of the human brain. While they recapitulate the salient developmental stages of the human brain, their use to investigate the onset and mechanisms of neurodegenerative diseases still faces crucial limitations. In this review, we aim to highlight these limitations, which hinder brain organoids from becoming reliable models to study neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS). Specifically, we will describe structural and biological impediments, including the lack of an aging footprint, angiogenesis, myelination, and the inclusion of functional and immunocompetent microglia—all important factors in the onset of neurodegeneration in AD, PD, and ALS. Additionally, we will discuss technical limitations for monitoring the microanatomy and electrophysiology of these organoids. In parallel, we will propose solutions to overcome the current limitations, thereby making human brain organoids a more reliable tool to model neurodegeneration.

Human Brain In Vitro Model for Pathogen Infection-Related Neurodegeneration Study

Recent advancements in stem cell biology and tissue engineering have revolutionized the field of neurodegeneration research by enabling the development of sophisticated in vitro human brain models. These models, including 2D monolayer cultures, 3D organoids, organ-on-chips, and bioengineered 3D tissue models, aim to recapitulate the cellular diversity, structural organization, and functional properties of the native human brain. This review highlights how these in vitro brain models have been used to investigate the effects of various pathogens, including viruses, bacteria, fungi, and parasites infection, particularly in the human brain cand their subsequent impacts on neurodegenerative diseases. Traditional studies have demonstrated the susceptibility of different 2D brain cell types to infection, elucidated the mechanisms underlying pathogen-induced neuroinflammation, and identified potential therapeutic targets. Therefore, current methodological improvement brought the technology of 3D models to overcome the challenges of 2D cells, such as the limited cellular diversity, incomplete microenvironment, and lack of morphological structures by highlighting the need for further technological advancements. This review underscored the significance of in vitro human brain cell from 2D monolayer to bioengineered 3D tissue model for elucidating the intricate dynamics for pathogen infection modeling. These in vitro human brain cell enabled researchers to unravel human specific mechanisms underlying various pathogen infections such as SARS-CoV-2 to alter blood-brain-barrier function and Toxoplasma gondii impacting neural cell morphology and its function. Ultimately, these in vitro human brain models hold promise as personalized platforms for development of drug compound, gene therapy, and vaccine. Overall, we discussed the recent progress in in vitro human brain models, their applications in studying pathogen infection-related neurodegeneration, and future directions.

Rigor and reproducibility in human brain organoid research: Where we are and where we need to go

Human brain organoid models have emerged as a promising tool for studying human brain development and function. These models preserve human genetics and recapitulate some aspects of human brain development, while facilitating manipulation in an in vitro setting. Despite their potential to transform biology and medicine, concerns persist about their fidelity. To fully harness their potential, it is imperative to establish reliable analytic methods, ensuring rigor and reproducibility. Here, we review current analytical platforms used to characterize human forebrain cortical organoids, highlight challenges, and propose recommendations for future studies to achieve greater precision and uniformity across laboratories.

Versatile micro-electrode array to monitor human iPSC derived 3D neural tissues at air-liquid interface

Engineered 3D neural tissues made of neurons and glial cells derived from human induced pluripotent stem cells (hiPSC) are among the most promising tools in drug discovery and neurotoxicology. They represent a cheaper, faster, and more ethical alternative to in vivo animal testing that will likely close the gap between in vitro animal models and human clinical trials. Micro-Electrode Array (MEA) technology is known to provide an assessment of compound effects on neural 2D cell cultures and acute tissue preparations by real-time, non-invasive, and long-lasting electrophysiological monitoring of spontaneous and evoked neuronal activity. Nevertheless, the use of engineered 3D neural tissues in combination with MEA biochips still involves series of constraints, such as drastically limited diffusion of oxygen and nutrients within tissues mainly due to the lack of vascularization. Therefore, 3D neural tissues are extremely sensitive to experimental conditions and require an adequately designed interface that provides optimal tissue survival conditions. A well-suited technique to overcome this issue is the combination of the Air-Liquid Interface (ALI) tissue culture method with the MEA technology. We have developed a full 3D neural tissue culture process and a data acquisition system composed of high-end electronics and novel MEA biochips based on porous, flexible, thin-film membranes integrating recording electrodes, named as "Strip-MEA," to allow the maintenance of an ALI around the 3D neural tissues. The main motivation of the porous MEA biochips development was the possibility to monitor and to study the electrical activity of 3D neural tissues under different recording configurations, (i) the Strip-MEA can be placed below a tissue, (ii) or by taking advantage of the ALI, be directly placed on top of the tissue, or finally, (iii) it can be embedded into a larger neural tissue generated by the fusion of two (or more) tissues placed on both sides of the Strip-MEA allowing the recording from its inner part. This paper presents the recording and analyses of spontaneous activity from the three positioning configurations of the Strip-MEAs. Obtained results are discussed with the perspective of developing in vitro models of brain diseases and/or impairment of neural network functioning.

Open and remotely accessible Neuroplatform for research in wetware computing

Wetware computing and organoid intelligence is an emerging research field at the intersection of electrophysiology and artificial intelligence. The core concept involves using living neurons to perform computations, similar to how Artificial Neural Networks (ANNs) are used today. However, unlike ANNs, where updating digital tensors (weights) can instantly modify network responses, entirely new methods must be developed for neural networks using biological neurons. Discovering these methods is challenging and requires a system capable of conducting numerous experiments, ideally accessible to researchers worldwide. For this reason, we developed a hardware and software system that allows for electrophysiological experiments on an unmatched scale. The Neuroplatform enables researchers to run experiments on neural organoids with a lifetime of even more than 100 days. To do so, we streamlined the experimental process to quickly produce new organoids, monitor action potentials 24/7, and provide electrical stimulations. We also designed a microfluidic system that allows for fully automated medium flow and change, thus reducing the disruptions by physical interventions in the incubator and ensuring stable environmental conditions. Over the past three years, the Neuroplatform was utilized with over 1,000 brain organoids, enabling the collection of more than 18 terabytes of data. A dedicated Application Programming Interface (API) has been developed to conduct remote research directly via our Python library or using interactive compute such as Jupyter Notebooks. In addition to electrophysiological operations, our API also controls pumps, digital cameras and UV lights for molecule uncaging. This allows for the execution of complex 24/7 experiments, including closed-loop strategies and processing using the latest deep learning or reinforcement learning libraries. Furthermore, the infrastructure supports entirely remote use. Currently in 2024, the system is freely available for research purposes, and numerous research groups have begun using it for their experiments. This article outlines the system's architecture and provides specific examples of experiments and results.