1
|
Habibey R, Striebel J, Meinert M, Latiftikhereshki R, Schmieder F, Nasiri R, Latifi S. Engineered modular neuronal networks-on-chip represent structure-function relationship. Biosens Bioelectron 2024; 261:116518. [PMID: 38924816 DOI: 10.1016/j.bios.2024.116518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 06/18/2024] [Accepted: 06/20/2024] [Indexed: 06/28/2024]
Abstract
Brain function is substantially linked to the highly organized modular structure of neuronal networks. However, the structure of in vitro assembled neuronal circuits often exhibits variability, complicating the consistent recording of network functional output and its correlation to network structure. Therefore, engineering neuronal structures with predefined geometry and reproducible functional features is essential to precisely model in vivo neuronal circuits. Here, we engineered microchannel devices to assemble 2D and 3D modular networks. The microchannel devices were coupled with a multi-electrode array (MEA) electrophysiology system to enable recordings from circuits. Each network consisted of 64 modules connected to their adjacent modules by micron-sized channels. Modular circuits within microchannel devices showed enhanced activity and functional connectivity traits. This includes metrics such as connection weights, clustering coefficient, global efficiency, and the number of hub neurons with higher betweenness centrality. In addition, modular networks demonstrated an increased functional modularity score compared to the randomly formed circuits. Neurons within individual modules displayed uniform network characteristics and predominantly participated in their respective functional communities within the same or neighboring physical modules. These observations highlight that the modular network structure promotes the development of segregated functional connectivity traits while simultaneously enhancing the efficiency of overall network connectivity. Our findings emphasize the significant impact of physical constraints on the activity patterns and functional organization within engineered modular networks. These circuits, characterized by stable modular architecture and intricate functional dynamics-key features of the brain networks-offer a robust in vitro model for advancing neuroscience research.
Collapse
Affiliation(s)
- Rouhollah Habibey
- Department of Ophthalmology, Medical Faculty, University of Bonn, Bonn, Germany; CRTD - Center for Regenerative Therapies TU Dresden, 01307, Dresden, Germany; Dept. Neuroscience, Italian Institute of Technology. Genova, Italy.
| | - Johannes Striebel
- Department of Ophthalmology, Medical Faculty, University of Bonn, Bonn, Germany
| | - Melissa Meinert
- Department of Ophthalmology, Medical Faculty, University of Bonn, Bonn, Germany
| | - Roshanak Latiftikhereshki
- Department of Computer Engineering, Faculty of Engineering, Kermanshah Branch, Azad University, Kermanshah, Iran
| | - Felix Schmieder
- Laboratory of Measurement and Sensor System Technique, Faculty of Electrical and Computer Engineering, TU Dresden, Helmholtzstraße 18, 01069, Dresden, Germany
| | - Rohollah Nasiri
- Division of Nanobiotechnology, Department of Protein Science, Science for Life Laboratory, KTH Royal Institute of Technology, Solna, Sweden; AIMES, Center for the Advancement of Integrated Medical and Engineering Sciences, Department of Neuroscience, Karolinska Institute, Solna, Sweden
| | - Shahrzad Latifi
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Department of Neuroscience, Rockefeller Neuroscience Institute West Virginia University, Morgantown, WV, 26506, USA
| |
Collapse
|
2
|
Cartiglia M, Costa F, Narayanan S, Bui CVH, Ulusan H, Risi N, Haessig G, Hierlemann A, Cardes F, Indiveri G. A 4096 channel event-based multielectrode array with asynchronous outputs compatible with neuromorphic processors. Nat Commun 2024; 15:7163. [PMID: 39169023 DOI: 10.1038/s41467-024-50783-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 07/19/2024] [Indexed: 08/23/2024] Open
Abstract
Bio-signal sensing is pivotal in medical bioelectronics. Traditional methods focus on high sampling rates, leading to large amounts of irrelevant data and high energy consumption. We introduce a self-clocked microelectrode array (MEA) that digitizes bio-signals at the pixel level by encoding changes as asynchronous digital address-events only when they exceed a threshold, significantly reducing off-chip data transmission. This novel MEA comprises a 64 × 64 electrode array, an asynchronous 2D-arbiter, and an Address-Event Representation (AER) communication block. Each pixel operates autonomously, monitoring voltage fluctuations from cellular activity and producing digital pulses for significant changes. Positive and negative signal changes are encoded as "up" and "down" events and are routed off-chip via the asynchronous arbiter. We present results from chip characterization and experimental measurements using electrogenic cells. Additionally, we interface the MEA to a mixed-signal neuromorphic processor, demonstrating a prototype for end-to-end event-based bio-signal sensing and processing.
Collapse
Affiliation(s)
- Matteo Cartiglia
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland.
| | - Filippo Costa
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
- Department of Neurosurgery, University Hospital Zurich, Zurich, Switzerland
| | - Shyam Narayanan
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Cat-Vu H Bui
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Hasan Ulusan
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Nicoletta Risi
- Bio-Inspired Circuits and Systems Lab, Zernike Institute for Advanced Materials, University of Groningen, Groningen, Netherlands
- Groningen Cognitive Systems and Materials Center, University of Groningen, Groningen, Netherlands
| | - Germain Haessig
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Fernando Cardes
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Giacomo Indiveri
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
| |
Collapse
|
3
|
Peng H, Kopic I, Potfode SR, Teshima TF, Boustani GA, Hiendlmeier L, Wang C, Hussain MZ, Özkale B, Fischer RA, Wolfrum B. Laser-patterned epoxy-based 3D microelectrode arrays for extracellular recording. NANOSCALE 2024; 16:14295-14301. [PMID: 39011647 DOI: 10.1039/d4nr01727g] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/17/2024]
Abstract
Microelectrode arrays are commonly used to study the electrophysiological behavior of cells. Recently, there has been a growing interest in fabricating three-dimensional microelectrode arrays. Here, we present a novel process for the fast fabrication of epoxy-based 3D microelectrode array platforms with the assistance of laser-patterning technology. To this end, we photopatterned 3D pillars as scaffolds using epoxy-based dry films. Electrodes and conductor traces were fabricated by laser patterning of sputtered platinum films on top of the 3D structures, followed by deposition of parylene-C for insulation. Microelectrodes at the tip of the 3D structures were exposed using a vertical laser ablation process. The final electrodes demonstrated a low impedance of ∼10 kΩ at 1 kHz in electrochemical impedance spectroscopy measurements under physiological conditions. We investigated the maximum compression force of the 3D structures, which could withstand approximately 0.6 N per pillar. The 3D microelectrode arrays were used to record extracellular signals from HL-1 cells in culture as a proof of principle. Our results show regular firing of action potentials recorded at the tip of the 3D structures, demonstrating the possibility of recording cell signals in non-planar environments.
Collapse
Affiliation(s)
- Hu Peng
- Neuroelectronics, Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Hans-Piloty-Str. 1, 85748, Garching, Germany
| | - Inola Kopic
- Neuroelectronics, Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Hans-Piloty-Str. 1, 85748, Garching, Germany
| | - Shivani Ratnakar Potfode
- Neuroelectronics, Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Hans-Piloty-Str. 1, 85748, Garching, Germany
| | - Tetsuhiko F Teshima
- Neuroelectronics, Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Hans-Piloty-Str. 1, 85748, Garching, Germany
- Medical & Health Informatics Laboratories NTT Research Incorporated, 940 Stewart Dr, Sunnyvale, CA 94085, USA
| | - George Al Boustani
- Neuroelectronics, Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Hans-Piloty-Str. 1, 85748, Garching, Germany
| | - Lukas Hiendlmeier
- Neuroelectronics, Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Hans-Piloty-Str. 1, 85748, Garching, Germany
| | - Chen Wang
- Microrobotic Bioengineering Lab (MRBL), Department of Electrical Engineering, TUM School of Computation, Information, and Technology, Technical University of Munich, Hans-Piloty-Str. 1, Garching 85748, Germany
| | - Mian Zahid Hussain
- Chair of Inorganic and Metal-Organic Chemistry, School of Natural Sciences and Catalysis Research Centre, Department of Chemistry, Technical University of Munich, Lichtenbergstr. 4, 85748 Garching, Germany
| | - Berna Özkale
- Microrobotic Bioengineering Lab (MRBL), Department of Electrical Engineering, TUM School of Computation, Information, and Technology, Technical University of Munich, Hans-Piloty-Str. 1, Garching 85748, Germany
| | - Roland A Fischer
- Chair of Inorganic and Metal-Organic Chemistry, School of Natural Sciences and Catalysis Research Centre, Department of Chemistry, Technical University of Munich, Lichtenbergstr. 4, 85748 Garching, Germany
| | - Bernhard Wolfrum
- Neuroelectronics, Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Hans-Piloty-Str. 1, 85748, Garching, Germany
- Medical & Health Informatics Laboratories NTT Research Incorporated, 940 Stewart Dr, Sunnyvale, CA 94085, USA
| |
Collapse
|
4
|
Liu Y, Jia H, Sun H, Jia S, Yang Z, Li A, Jiang A, Naya Y, Yang C, Xue S, Li X, Chen B, Zhu J, Zhou C, Li M, Duan X. A high-density 1,024-channel probe for brain-wide recordings in non-human primates. Nat Neurosci 2024; 27:1620-1631. [PMID: 38914829 DOI: 10.1038/s41593-024-01692-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/23/2024] [Indexed: 06/26/2024]
Abstract
Large-scale neural population recordings with single-cell resolution across the primate brain remain challenging. Here we introduce the Neuroscroll probe that isolates single neuronal activities simultaneously from 1,024 densely spaced channels that are flexibly distributed across the shank of the probe. The Neuroscroll probe length is easily tunable for individual probes from 10 mm to 90 mm, covering the brain size of non-human primates and humans, and the probes remain intact and functional after repeated bending deformations. The Neuroscroll probes provided reliable recordings from large neural populations with high chronic stability up to 105 weeks in rats. Recording with each Neuroscroll probe yielded hundreds of well-isolated single units simultaneously from multiple brain regions distributed across the entire depth of the rhesus macaque brain. With the thousand simultaneously recorded channels, unprecedented probe length, excellent mechanical stability and flexible recording site distribution, the Neuroscroll probes enable a wide range of new experimental paradigms in system neuroscience studies with great versatility.
Collapse
Affiliation(s)
- Yang Liu
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
| | - Huilin Jia
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
| | - Hongji Sun
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
| | - Shengyi Jia
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
| | - Ziqian Yang
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Ao Li
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
| | - Anqi Jiang
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
| | - Yuji Naya
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing Key Laboratory of Behavioral and Mental Health, Peking University, Beijing, China
| | - Cen Yang
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
| | - Shengyuan Xue
- School of Psychological and Cognitive Sciences, Peking University, Beijing, China
| | - Xiaojian Li
- CAS Key Laboratory of Brain Connectome and Manipulation, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Bingyan Chen
- CAS Key Laboratory of Brain Connectome and Manipulation, Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China
| | - Jingjun Zhu
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- National Biomedical Imaging Centre, Peking University, Beijing, China
| | - Chenghao Zhou
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Minning Li
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Xiaojie Duan
- Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
- National Biomedical Imaging Centre, Peking University, Beijing, China.
| |
Collapse
|
5
|
Marciuš T, Deftu AF, Vuka I, Braeken D, Sapunar D. Electrophysiological properties of dorsal root ganglion neurons cultured on 3D silicon micro-pillar substrates. J Neurosci Methods 2024; 407:110143. [PMID: 38670536 DOI: 10.1016/j.jneumeth.2024.110143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/27/2024] [Accepted: 04/20/2024] [Indexed: 04/28/2024]
Abstract
BACKGROUND Silicon-based micro-pillar substrates (MPS), as three-dimensional cell culture platforms with vertically aligned micro-patterned scaffolding structures, are known to facilitate high-quality growth and morphology of dorsal root ganglion (DRG) sensory neurons, promote neurite outgrowth and enhance neurite alignment. However, the electrophysiological aspects of DRG neurons cultured on silicon MPSs have not been thoroughly investigated, which is of greatest importance to ensure that such substrates do not disrupt neuronal homeostasis and function before their widespread adoption in diverse biomedical applications. NEW METHOD We conducted whole-cell patch-clamp recordings to explore the electrophysiological properties of DRG neurons cultured on MPS arrays, utilizing a custom-made upright patch-clamp setup. RESULTS Our findings revealed that DRG neurons exhibited similar electrophysiological responses on patterned MPS samples when compared to the control planar glass surfaces. Notably, there were no significant differences observed in the action potential parameters or firing patterns of action potentials between neurons grown on either substrate. COMPARISON WITH EXISTING METHODS In the current study we for the first time confirmed that successful electrophysiological recordings can be obtained from the cells grown on MPS. CONCLUSION Our results imply that, despite the potential alterations caused by the cumulative trauma of tissue harvest and cell dissociation, essential functional cell properties of DRG neurons appear to be relatively maintained on MPS surfaces. Therefore, vertically aligned silicon MPSs could be considered as a potentially effective three-dimensional system for supporting a controlled cellular environment in culture.
Collapse
Affiliation(s)
- Tihana Marciuš
- Laboratory for Pain Research, University of Split School of Medicine, Split 21000, Croatia
| | - Alexandru-Florian Deftu
- Pain Center, Department of Anesthesiology, Lausanne University Hospital and Department of Fundamental Neurosciences, University of Lausanne, Lausanne 1011, Switzerland
| | - Ivana Vuka
- Technology Transfer Office, Department of Science and Innovation, University of Split, Split 21000, Croatia
| | - Dries Braeken
- Life Sciences Technologies, Imec, Leuven 3001, Belgium
| | - Damir Sapunar
- Laboratory for Pain Research, University of Split School of Medicine, Split 21000, Croatia.
| |
Collapse
|
6
|
Buccino AP, Damart T, Bartram J, Mandge D, Xue X, Zbili M, Gänswein T, Jaquier A, Emmenegger V, Markram H, Hierlemann A, Van Geit W. A Multimodal Fitting Approach to Construct Single-Neuron Models With Patch Clamp and High-Density Microelectrode Arrays. Neural Comput 2024; 36:1286-1331. [PMID: 38776965 DOI: 10.1162/neco_a_01672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 02/20/2024] [Indexed: 05/25/2024]
Abstract
In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of nonsomatic compartments. In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density microelectrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at subcellular resolution. In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures. The proposed multimodal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and provide the field with neuronal models that are more realistic and can be better validated.
Collapse
Affiliation(s)
- Alessio Paolo Buccino
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Tanguy Damart
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Julian Bartram
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Darshan Mandge
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Xiaohan Xue
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Mickael Zbili
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Tobias Gänswein
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Aurélien Jaquier
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Vishalini Emmenegger
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Henry Markram
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland
| | - Andreas Hierlemann
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, 4056 Basel, Switzerland
| | - Werner Van Geit
- Blue Brain Project, École polytechnique fédérale de Lausanne, Campus Biotech, 1202 Geneva, Switzerland Present address: Foundation for Research on Information Technologies in Society (IT'IS), Zurich 8004, Switzerland
| |
Collapse
|
7
|
Kasuba KC, Buccino AP, Bartram J, Gaub BM, Fauser FJ, Ronchi S, Kumar SS, Geissler S, Nava MM, Hierlemann A, Müller DJ. Mechanical stimulation and electrophysiological monitoring at subcellular resolution reveals differential mechanosensation of neurons within networks. NATURE NANOTECHNOLOGY 2024; 19:825-833. [PMID: 38378885 PMCID: PMC11186759 DOI: 10.1038/s41565-024-01609-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Accepted: 01/12/2024] [Indexed: 02/22/2024]
Abstract
A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control.
Collapse
Affiliation(s)
| | | | - Julian Bartram
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Benjamin M Gaub
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Felix J Fauser
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | | | | | - Sydney Geissler
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Michele M Nava
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
| | - Daniel J Müller
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
| |
Collapse
|
8
|
Voitiuk K, Seiler ST, Pessoa de Melo M, Geng J, Hernandez S, Schweiger HE, Sevetson JL, Parks DF, Robbins A, Torres-Montoya S, Ehrlich D, Elliott MAT, Sharf T, Haussler D, Mostajo-Radji MA, Salama SR, Teodorescu M. A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.15.585237. [PMID: 38559212 PMCID: PMC10979982 DOI: 10.1101/2024.03.15.585237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
The analysis of tissue cultures, particularly brain organoids, takes a high degree of coordination, measurement, and monitoring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Unified by an Internet of Things (IoT) architecture, our approach enables continuous, communicative interactions among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids and monitor their neuronal activity. The organoids are cultured in custom, 3D-printed chambers attached to commercial microelectrode arrays for electrophysiology monitoring. Periodic feeding is achieved using programmable microfluidic pumps. We developed computer vision fluid volume estimations of aspirated media, achieving high accuracy, and used feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a 7-day study of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated experimental samples maintained robust neural activity throughout the experiment, comparable with the control samples. The automated system enabled hourly electrophysiology recordings that revealed dramatic temporal changes in neuron firing rates not observed in once-a-day recordings.
Collapse
|
9
|
Ell M, Bui MT, Kigili S, Zeck G, Prado-López S. Assessment of chemotherapeutic effects on cancer cells using adhesion noise spectroscopy. Front Bioeng Biotechnol 2024; 12:1385730. [PMID: 38803844 PMCID: PMC11128629 DOI: 10.3389/fbioe.2024.1385730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 04/12/2024] [Indexed: 05/29/2024] Open
Abstract
With cancer as one of the leading causes of death worldwide, there is a need for the development of accurate, cost-effective, easy-to-use, and fast drug-testing assays. While the NCI 60 cell-line screening as the gold standard is based on a colorimetric assay, monitoring cells electrically constitutes a label-free and non-invasive tool to assess the cytotoxic effects of a chemotherapeutic treatment on cancer cells. For decades, impedance-based cellular assays extensively investigated various cell characteristics affected by drug treatment but lack spatiotemporal resolution. With progress in microelectrode fabrication, high-density Complementary Metal Oxide Semiconductor (CMOS)-based microelectrode arrays (MEAs) with subcellular resolution and time-continuous recording capability emerged as a potent alternative. In this article, we present a new cell adhesion noise (CAN)-based electrical imaging technique to expand CMOS MEA cell-biology applications: CAN spectroscopy enables drug screening quantification with single-cell spatial resolution. The chemotherapeutic agent 5-Fluorouracil exerts a cytotoxic effect on colorectal cancer (CRC) cells hampering cell proliferation and lowering cell viability. For proof-of-concept, we found sufficient accuracy and reproducibility for CAN spectroscopy compared to a commercially available standard colorimetric biological assay. This label-free, non-invasive, and fast electrical imaging technique complements standardized cancer screening methods with significant advances over established impedance-based approaches.
Collapse
Affiliation(s)
- Maximilian Ell
- Institute of Biomedical Electronics, Faculty of Electrical Engineering and Information Technology, TU Wien, Vienna, Austria
| | - Mai Thu Bui
- Institute of Biomedical Electronics, Faculty of Electrical Engineering and Information Technology, TU Wien, Vienna, Austria
| | - Seyda Kigili
- Institute of Solid State Electronics, Faculty of Electrical Engineering and Information Technology, TU Wien, Vienna, Austria
| | - Günther Zeck
- Institute of Biomedical Electronics, Faculty of Electrical Engineering and Information Technology, TU Wien, Vienna, Austria
| | - Sonia Prado-López
- Institute of Solid State Electronics, Faculty of Electrical Engineering and Information Technology, TU Wien, Vienna, Austria
| |
Collapse
|
10
|
Spitz S, Schobesberger S, Brandauer K, Ertl P. Sensor-integrated brain-on-a-chip platforms: Improving the predictive validity in neurodegenerative research. Bioeng Transl Med 2024; 9:e10604. [PMID: 38818126 PMCID: PMC11135156 DOI: 10.1002/btm2.10604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 08/31/2023] [Accepted: 09/12/2023] [Indexed: 06/01/2024] Open
Abstract
Affecting millions of individuals worldwide, neurodegenerative diseases (NDDs) pose a significant and growing health concern in people over the age of 60 years. Contributing to this trend are the steady increase in the aging population coupled with a persistent lack of disease-altering treatment strategies targeting NDDs. The absence of efficient therapeutics can be attributed to high failure rates in clinical trials and the ineptness of animal models in preceding preclinical studies. To that end, in recent years, significant research effort has been dedicated to the development of human cell-based preclinical disease models characterized by a higher degree of predictive validity. However, a key requirement of any in vitro model constitutes the precise knowledge and replication of the target tissues' (patho-)physiological microenvironment. Herein, microphysiological systems have demonstrated superiority over conventional static 2D/3D in vitro cell culture systems, as they allow for the emulation and continuous monitoring of the onset, progression, and remission of disease-associated phenotypes. This review provides an overview of recent advances in the field of NDD research using organ-on-a-chip platforms. Specific focus is directed toward non-invasive sensing strategies encompassing electrical, electrochemical, and optical sensors. Additionally, promising on- and integrable off-chip sensing strategies targeting key analytes in NDDs will be presented and discussed in detail.
Collapse
Affiliation(s)
- Sarah Spitz
- Faculty of Technical ChemistryVienna University of TechnologyViennaAustria
- Present address:
Department of Mechanical Engineering and Biological EngineeringMassachusetts Institute of TechnologyCambridgeMassachusettsUSA
| | | | | | - Peter Ertl
- Faculty of Technical ChemistryVienna University of TechnologyViennaAustria
| |
Collapse
|
11
|
Song SS, Druschel LN, Conard JH, Wang JJ, Kasthuri NM, Ricky Chan E, Capadona JR. Depletion of complement factor 3 delays the neuroinflammatory response to intracortical microelectrodes. Brain Behav Immun 2024; 118:221-235. [PMID: 38458498 DOI: 10.1016/j.bbi.2024.03.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 01/26/2024] [Accepted: 03/02/2024] [Indexed: 03/10/2024] Open
Abstract
The neuroinflammatory response to intracortical microelectrodes (IMEs) used with brain-machine interfacing (BMI) applications is regarded as the primary contributor to poor chronic performance. Recent developments in high-plex gene expression technologies have allowed for an evolution in the investigation of individual proteins or genes to be able to identify specific pathways of upregulated genes that may contribute to the neuroinflammatory response. Several key pathways that are upregulated following IME implantation are involved with the complement system. The complement system is part of the innate immune system involved in recognizing and eliminating pathogens - a significant contributor to the foreign body response against biomaterials. Specifically, we have identified Complement 3 (C3) as a gene of interest because it is the intersection of several key complement pathways. In this study, we investigated the role of C3 in the IME inflammatory response by comparing the neuroinflammatory gene expression at the microelectrode implant site between C3 knockout (C3-/-) and wild-type (WT) mice. We have found that, like in WT mice, implantation of intracortical microelectrodes in C3-/- mice yields a dramatic increase in the neuroinflammatory gene expression at all post-surgery time points investigated. However, compared to WT mice, C3 depletion showed reduced expression of many neuroinflammatory genes pre-surgery and 4 weeks post-surgery. Conversely, depletion of C3 increased the expression of many neuroinflammatory genes at 8 weeks and 16 weeks post-surgery, compared to WT mice. Our results suggest that C3 depletion may be a promising therapeutic target for acute, but not chronic, relief of the neuroinflammatory response to IME implantation. Additional compensatory targets may also be required for comprehensive long-term reduction of the neuroinflammatory response for improved intracortical microelectrode performance.
Collapse
Affiliation(s)
- Sydney S Song
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, United States.
| | - Lindsey N Druschel
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, United States.
| | - Jacob H Conard
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States.
| | - Jaime J Wang
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, United States.
| | - Niveda M Kasthuri
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, United States.
| | - E Ricky Chan
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH 44106, United States.
| | - Jeffrey R Capadona
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, United States.
| |
Collapse
|
12
|
Zhang X, Dou Z, Kim SH, Upadhyay G, Havert D, Kang S, Kazemi K, Huang K, Aydin O, Huang R, Rahman S, Ellis‐Mohr A, Noblet HA, Lim KH, Chung HJ, Gritton HJ, Saif MTA, Kong HJ, Beggs JM, Gazzola M. Mind In Vitro Platforms: Versatile, Scalable, Robust, and Open Solutions to Interfacing with Living Neurons. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2306826. [PMID: 38161217 PMCID: PMC10953569 DOI: 10.1002/advs.202306826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/12/2023] [Indexed: 01/03/2024]
Abstract
Motivated by the unexplored potential of in vitro neural systems for computing and by the corresponding need of versatile, scalable interfaces for multimodal interaction, an accurate, modular, fully customizable, and portable recording/stimulation solution that can be easily fabricated, robustly operated, and broadly disseminated is presented. This approach entails a reconfigurable platform that works across multiple industry standards and that enables a complete signal chain, from neural substrates sampled through micro-electrode arrays (MEAs) to data acquisition, downstream analysis, and cloud storage. Built-in modularity supports the seamless integration of electrical/optical stimulation and fluidic interfaces. Custom MEA fabrication leverages maskless photolithography, favoring the rapid prototyping of a variety of configurations, spatial topologies, and constitutive materials. Through a dedicated analysis and management software suite, the utility and robustness of this system are demonstrated across neural cultures and applications, including embryonic stem cell-derived and primary neurons, organotypic brain slices, 3D engineered tissue mimics, concurrent calcium imaging, and long-term recording. Overall, this technology, termed "mind in vitro" to underscore the computing inspiration, provides an end-to-end solution that can be widely deployed due to its affordable (>10× cost reduction) and open-source nature, catering to the expanding needs of both conventional and unconventional electrophysiology.
Collapse
Affiliation(s)
- Xiaotian Zhang
- Carl R. Woese Institute for Genomic BiologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Zhi Dou
- Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Seung Hyun Kim
- Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Gaurav Upadhyay
- Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Daniel Havert
- Department of PhysicsIndiana University BloomingtonBloomingtonIN47405USA
| | - Sehong Kang
- Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Kimia Kazemi
- Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Kai‐Yu Huang
- Department of Chemical and Biomolecular EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Onur Aydin
- Carl R. Woese Institute for Genomic BiologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Raymond Huang
- Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Saeedur Rahman
- Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Austin Ellis‐Mohr
- Department of Electrical and Computer EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Hayden A. Noblet
- Molecular and Integrative PhysiologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
- Neuroscience ProgramUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Ki H. Lim
- Molecular and Integrative PhysiologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Hee Jung Chung
- Carl R. Woese Institute for Genomic BiologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
- Molecular and Integrative PhysiologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
- Neuroscience ProgramUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
- Beckman Institute for Advanced Science and TechnologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Howard J. Gritton
- Beckman Institute for Advanced Science and TechnologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
- Department of Comparative BiosciencesUniversity of Illinois at Urbana–ChampaignUrbanaIL61802USA
| | - M. Taher A. Saif
- Carl R. Woese Institute for Genomic BiologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
- Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - Hyun Joon Kong
- Carl R. Woese Institute for Genomic BiologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
- Department of Chemical and Biomolecular EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| | - John M. Beggs
- Department of PhysicsIndiana University BloomingtonBloomingtonIN47405USA
| | - Mattia Gazzola
- Carl R. Woese Institute for Genomic BiologyUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
- Department of Mechanical Science and EngineeringUniversity of Illinois at Urbana–ChampaignUrbanaIL61801USA
| |
Collapse
|
13
|
Xiang Y, Shi K, Li Y, Xue J, Tong Z, Li H, Li Z, Teng C, Fang J, Hu N. Active Micro-Nano-Collaborative Bioelectronic Device for Advanced Electrophysiological Recording. NANO-MICRO LETTERS 2024; 16:132. [PMID: 38411852 PMCID: PMC10899154 DOI: 10.1007/s40820-024-01336-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 12/28/2023] [Indexed: 02/28/2024]
Abstract
The development of precise and sensitive electrophysiological recording platforms holds the utmost importance for research in the fields of cardiology and neuroscience. In recent years, active micro/nano-bioelectronic devices have undergone significant advancements, thereby facilitating the study of electrophysiology. The distinctive configuration and exceptional functionality of these active micro-nano-collaborative bioelectronic devices offer the potential for the recording of high-fidelity action potential signals on a large scale. In this paper, we review three-dimensional active nano-transistors and planar active micro-transistors in terms of their applications in electro-excitable cells, focusing on the evaluation of the effects of active micro/nano-bioelectronic devices on electrophysiological signals. Looking forward to the possibilities, challenges, and wide prospects of active micro-nano-devices, we expect to advance their progress to satisfy the demands of theoretical investigations and medical implementations within the domains of cardiology and neuroscience research.
Collapse
Affiliation(s)
- Yuting Xiang
- Department of Chemistry, Zhejiang-Israel Joint Laboratory of Self-Assembling Functional Materials, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310058, People's Republic of China
- Department of Obstetrics and Gynecology, The Tenth Affiliated Hospital, Southern Medical University, Dongguan, 523059, People's Republic of China
- Dongguan Key Laboratory of Major Diseases in Obstetrics and Gynecology, Dongguan, 523059, People's Republic of China
| | - Keda Shi
- Department of Lung Transplantation and General Thoracic Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, People's Republic of China
| | - Ying Li
- School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, 310053, People's Republic of China
| | - Jiajin Xue
- General Surgery Department, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children's Health, Hangzhou, 310052, People's Republic of China
| | - Zhicheng Tong
- Department of Orthopedics, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322005, People's Republic of China
| | - Huiming Li
- Department of Orthopedics, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322005, People's Republic of China
| | - Zhongjun Li
- Department of Obstetrics and Gynecology, The Tenth Affiliated Hospital, Southern Medical University, Dongguan, 523059, People's Republic of China.
- Dongguan Key Laboratory of Major Diseases in Obstetrics and Gynecology, Dongguan, 523059, People's Republic of China.
| | - Chong Teng
- Department of Orthopedics, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, 322005, People's Republic of China.
| | - Jiaru Fang
- School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, People's Republic of China.
| | - Ning Hu
- Department of Chemistry, Zhejiang-Israel Joint Laboratory of Self-Assembling Functional Materials, ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310058, People's Republic of China.
- General Surgery Department, Children's Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Children's Health, Hangzhou, 310052, People's Republic of China.
| |
Collapse
|
14
|
Lewis CM, Boehler C, Liljemalm R, Fries P, Stieglitz T, Asplund M. Recording Quality Is Systematically Related to Electrode Impedance. Adv Healthc Mater 2024:e2303401. [PMID: 38354063 DOI: 10.1002/adhm.202303401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 01/19/2024] [Indexed: 02/16/2024]
Abstract
Extracellular recordings with planar microelectrodes are the gold standard technique for recording the fast action potentials of neurons in the intact brain. The introduction of microfabrication techniques has revolutionized the in vivo recording of neuronal activity and introduced high-density, multi-electrode arrays that increase the spatial resolution of recordings and the number of neurons that can be simultaneously recorded. Despite these innovations, there is still debate about the ideal electrical transfer characteristics of extracellular electrodes. This uncertainty is partly due to the lack of systematic studies comparing electrodes with different characteristics, particularly for chronically implanted arrays over extended time periods. Here a high-density, flexible, and thin-film array is fabricated and tested, containing four distinct electrode types differing in surface material and surface topology and, thus, impedance. It is found that recording quality is strongly related to electrode impedance with signal amplitude and unit yield negatively correlated to impedance. Electrode impedances are stable for the duration of the experiment (up to 12 weeks) and recording quality does not deteriorate. The findings support the expectation from the theory that recording quality will increase as impedance decreases.
Collapse
Affiliation(s)
| | - Christian Boehler
- Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110, Freiburg, Germany
- BrainLinks-BrainTools Center, University of Freiburg, 79110, Freiburg, Germany
| | - Rickard Liljemalm
- Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110, Freiburg, Germany
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Deutschordenstraße 46, 60528, Frankfurt, Germany
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Kapittelweg 29, 6525 EN, Nijmegen, Netherland
| | - Thomas Stieglitz
- Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110, Freiburg, Germany
- BrainLinks-BrainTools Center, University of Freiburg, 79110, Freiburg, Germany
| | - Maria Asplund
- Department of Microsystems Engineering (IMTEK), University of Freiburg, 79110, Freiburg, Germany
- BrainLinks-BrainTools Center, University of Freiburg, 79110, Freiburg, Germany
- Department of Microtechnology and Nanoscience, Chalmers University of Technology, Kemivägen 9, Gothenburg, 41258, Sweden
| |
Collapse
|
15
|
Hornauer P, Prack G, Anastasi N, Ronchi S, Kim T, Donner C, Fiscella M, Borgwardt K, Taylor V, Jagasia R, Roqueiro D, Hierlemann A, Schröter M. DeePhys: A machine learning-assisted platform for electrophysiological phenotyping of human neuronal networks. Stem Cell Reports 2024; 19:285-298. [PMID: 38278155 PMCID: PMC10874850 DOI: 10.1016/j.stemcr.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 12/18/2023] [Accepted: 12/20/2023] [Indexed: 01/28/2024] Open
Abstract
Reproducible functional assays to study in vitro neuronal networks represent an important cornerstone in the quest to develop physiologically relevant cellular models of human diseases. Here, we introduce DeePhys, a MATLAB-based analysis tool for data-driven functional phenotyping of in vitro neuronal cultures recorded by high-density microelectrode arrays. DeePhys is a modular workflow that offers a range of techniques to extract features from spike-sorted data, allowing for the examination of functional phenotypes both at the individual cell and network levels, as well as across development. In addition, DeePhys incorporates the capability to integrate novel features and to use machine-learning-assisted approaches, which facilitates a comprehensive evaluation of pharmacological interventions. To illustrate its practical application, we apply DeePhys to human induced pluripotent stem cell-derived dopaminergic neurons obtained from both patients and healthy individuals and showcase how DeePhys enables phenotypic screenings.
Collapse
Affiliation(s)
- Philipp Hornauer
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland.
| | - Gustavo Prack
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland
| | - Nadia Anastasi
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche, 4070 Basel, Switzerland
| | - Silvia Ronchi
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland
| | - Taehoon Kim
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland
| | | | - Michele Fiscella
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland; MaxWell Biosystems AG, 8047 Zürich, Switzerland
| | - Karsten Borgwardt
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland; Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
| | - Verdon Taylor
- Department of Biomedicine, University of Basel, 4031 Basel, Switzerland
| | - Ravi Jagasia
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche, 4070 Basel, Switzerland
| | - Damian Roqueiro
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland; Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche, 4070 Basel, Switzerland
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland
| | - Manuel Schröter
- Department of Biosystems Science and Engineering, ETH Zürich, 4056 Basel, Switzerland
| |
Collapse
|
16
|
Hruska-Plochan M, Wiersma VI, Betz KM, Mallona I, Ronchi S, Maniecka Z, Hock EM, Tantardini E, Laferriere F, Sahadevan S, Hoop V, Delvendahl I, Pérez-Berlanga M, Gatta B, Panatta M, van der Bourg A, Bohaciakova D, Sharma P, De Vos L, Frontzek K, Aguzzi A, Lashley T, Robinson MD, Karayannis T, Mueller M, Hierlemann A, Polymenidou M. A model of human neural networks reveals NPTX2 pathology in ALS and FTLD. Nature 2024; 626:1073-1083. [PMID: 38355792 PMCID: PMC10901740 DOI: 10.1038/s41586-024-07042-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 01/08/2024] [Indexed: 02/16/2024]
Abstract
Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1, which involve human-specific mechanisms2-5 that cannot be directly studied in animal models. Here, to explore the emergence and consequences of TDP-43 pathologies, we generated induced pluripotent stem cell-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors6. Single-cell transcriptomics and comparison to independent neural stem cells7 showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks (which we designate iNets). Neuronal and glial maturation in iNets was similar to that of cortical organoids8. Overexpression of wild-type TDP-43 in a minority of neurons within iNets led to progressive fragmentation and aggregation of the protein, resulting in a partial loss of function and neurotoxicity. Single-cell transcriptomics revealed a novel set of misregulated RNA targets in TDP-43-overexpressing neurons and in patients with TDP-43 proteinopathies exhibiting a loss of nuclear TDP-43. The strongest misregulated target encoded the synaptic protein NPTX2, the levels of which are controlled by TDP-43 binding on its 3' untranslated region. When NPTX2 was overexpressed in iNets, it exhibited neurotoxicity, whereas correcting NPTX2 misregulation partially rescued neurons from TDP-43-induced neurodegeneration. Notably, NPTX2 was consistently misaccumulated in neurons from patients with amyotrophic lateral sclerosis and frontotemporal lobar degeneration with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby revealing a TDP-43-dependent pathway of neurotoxicity.
Collapse
Affiliation(s)
| | - Vera I Wiersma
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Katharina M Betz
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- SIB Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
| | - Izaskun Mallona
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- SIB Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
| | - Silvia Ronchi
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
- MaxWell Biosystems AG, Zurich, Switzerland
| | - Zuzanna Maniecka
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Eva-Maria Hock
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Elena Tantardini
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Florent Laferriere
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Sonu Sahadevan
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Vanessa Hoop
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Igor Delvendahl
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | | | - Beatrice Gatta
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Martina Panatta
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | | | - Dasa Bohaciakova
- Department of Histology and Embryology, Faculty of Medicine, Masaryk University Brno, Brno, Czech Republic
| | - Puneet Sharma
- Department of Chemistry, Biochemistry and Pharmaceutical Sciences, University of Bern, Bern, Switzerland
- NCCR RNA and Disease Technology Platform, Bern, Switzerland
| | - Laura De Vos
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
| | - Karl Frontzek
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Adriano Aguzzi
- Institute of Neuropathology, University of Zurich, Zurich, Switzerland
| | - Tammaryn Lashley
- Queen Square Brain Bank for Neurological diseases, Department of Movement Disorders, UCL Institute of Neurology, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Mark D Robinson
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
- SIB Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
| | | | - Martin Mueller
- Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | | |
Collapse
|
17
|
Wallace JL, Pollen AA. Human neuronal maturation comes of age: cellular mechanisms and species differences. Nat Rev Neurosci 2024; 25:7-29. [PMID: 37996703 DOI: 10.1038/s41583-023-00760-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/12/2023] [Indexed: 11/25/2023]
Abstract
The delayed and prolonged postmitotic maturation of human neurons, compared with neurons from other species, may contribute to human-specific cognitive abilities and neurological disorders. Here we review the mechanisms of neuronal maturation, applying lessons from model systems to understand the specific features of protracted human cortical maturation and species differences. We cover cell-intrinsic features of neuronal maturation, including transcriptional, epigenetic and metabolic mechanisms, as well as cell-extrinsic features, including the roles of activity and synapses, the actions of glial cells and the contribution of the extracellular matrix. We discuss evidence for species differences in biochemical reaction rates, the proposed existence of an epigenetic maturation clock and the contributions of both general and modular mechanisms to species-specific maturation timing. Finally, we suggest approaches to measure, improve and accelerate the maturation of human neurons in culture, examine crosstalk and interactions among these different aspects of maturation and propose conceptual models to guide future studies.
Collapse
Affiliation(s)
- Jenelle L Wallace
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
| | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA.
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
| |
Collapse
|
18
|
Duru J, Rüfenacht A, Löhle J, Pozzi M, Forró C, Ledermann L, Bernardi A, Matter M, Renia A, Simona B, Tringides CM, Bernhard S, Ihle SJ, Hengsteler J, Maurer B, Zhang X, Nakatsuka N. Driving electrochemical reactions at the microscale using CMOS microelectrode arrays. LAB ON A CHIP 2023; 23:5047-5058. [PMID: 37916299 PMCID: PMC10661664 DOI: 10.1039/d3lc00630a] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 10/25/2023] [Indexed: 11/03/2023]
Abstract
Precise control of pH values at electrode interfaces enables the systematic investigation of pH-dependent processes by electrochemical means. In this work, we employed high-density complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) as miniaturized systems to induce and confine electrochemical reactions in areas corresponding to the pitch of single electrodes (17.5 μm). First, we present a strategy for generating localized pH patterns on the surface of the CMOS MEA with unprecedented spatial resolution. Leveraging the versatile routing capabilities of the switch matrix beneath the CMOS MEA, we created arbitrary combinations of anodic and cathodic electrodes and hence pH patterns. Moreover, we utilized the system to produce polymeric surface patterns by additive and subtractive methods. For additive patterning, we controlled the in situ formation of polydopamine at the microelectrode surface through oxidation of free dopamine above a threshold pH > 8.5. For subtractive patterning, we removed cell-adhesive poly-L-lysine from the electrode surface and backfilled the voids with antifouling polymers. Such polymers were chosen to provide a proof-of-concept application of controlling neuronal growth via electrochemically-induced patterns on the CMOS MEA surface. Importantly, our platform is compatible with commercially available high-density MEAs and requires no custom equipment, rendering the findings generalizable and accessible.
Collapse
Affiliation(s)
- Jens Duru
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Arielle Rüfenacht
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Josephine Löhle
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Marcello Pozzi
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Csaba Forró
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Linus Ledermann
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Aeneas Bernardi
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Michael Matter
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - André Renia
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | | | - Christina M Tringides
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Stéphane Bernhard
- Macromolecular Engineering Laboratory, Department of Mechanical and Process Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland
| | - Stephan J Ihle
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Julian Hengsteler
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Benedikt Maurer
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Xinyu Zhang
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| | - Nako Nakatsuka
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, Eidgenössische Technische Hochschule (ETH) Zürich, Switzerland.
| |
Collapse
|
19
|
Chitale S, Wu W, Mukherjee A, Lannon H, Suresh P, Nag I, Ambrosi CM, Gertner RS, Melo H, Powers B, Wilkins H, Hinton H, Cheah M, Boynton ZG, Alexeyev A, Sword D, Basan M, Park H, Ham D, Abbott J. A semiconductor 96-microplate platform for electrical-imaging based high-throughput phenotypic screening. Nat Commun 2023; 14:7576. [PMID: 37990016 PMCID: PMC10663594 DOI: 10.1038/s41467-023-43333-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 11/06/2023] [Indexed: 11/23/2023] Open
Abstract
High-content imaging for compound and genetic profiling is popular for drug discovery but limited to endpoint images of fixed cells. Conversely, electronic-based devices offer label-free, live cell functional information but suffer from limited spatial resolution or throughput. Here, we introduce a semiconductor 96-microplate platform for high-resolution, real-time impedance imaging. Each well features 4096 electrodes at 25 µm spatial resolution and a miniaturized data interface allows 8× parallel plate operation (768 total wells) for increased throughput. Electric field impedance measurements capture >20 parameter images including cell barrier, attachment, flatness, and motility every 15 min during experiments. We apply this technology to characterize 16 cell types, from primary epithelial to suspension cells, and quantify heterogeneity in mixed co-cultures. Screening 904 compounds across 13 semiconductor microplates reveals 25 distinct responses, demonstrating the platform's potential for mechanism of action profiling. The scalability and translatability of this semiconductor platform expands high-throughput mechanism of action profiling and phenotypic drug discovery applications.
Collapse
Affiliation(s)
| | - Wenxuan Wu
- CytoTronics Inc., Boston, MA, USA
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | - Avik Mukherjee
- Department of System Biology, Harvard Medical School, Boston, MA, USA
| | | | | | | | | | - Rona S Gertner
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | | | | | | | - Henry Hinton
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA
| | | | | | | | | | - Markus Basan
- Department of System Biology, Harvard Medical School, Boston, MA, USA
| | - Hongkun Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Department of Physics, Harvard University, Cambridge, MA, USA.
| | - Donhee Ham
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
| | - Jeffrey Abbott
- CytoTronics Inc., Boston, MA, USA.
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Department of Physics, Harvard University, Cambridge, MA, USA.
| |
Collapse
|
20
|
Lv S, He E, Luo J, Liu Y, Liang W, Xu S, Zhang K, Yang Y, Wang M, Song Y, Wu Y, Cai X. Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2301828. [PMID: 37863819 PMCID: PMC10667858 DOI: 10.1002/advs.202301828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/22/2023] [Revised: 09/04/2023] [Indexed: 10/22/2023]
Abstract
In situ physiological signals of in vitro neural disease models are essential for studying pathogenesis and drug screening. Currently, an increasing number of in vitro neural disease models are established using human-induced pluripotent stem cell (hiPSC) derived neurons (hiPSC-DNs) to overcome interspecific gene expression differences. Microelectrode arrays (MEAs) can be readily interfaced with two-dimensional (2D), and more recently, three-dimensional (3D) neural stem cell-derived in vitro models of the human brain to monitor their physiological activity in real time. Therefore, MEAs are emerging and useful tools to model neurological disorders and disease in vitro using human iPSCs. This is enabling a real-time window into neuronal signaling at the network scale from patient derived. This paper provides a comprehensive review of MEA's role in analyzing neural disease models established by hiPSC-DNs. It covers the significance of MEA fabrication, surface structure and modification schemes for hiPSC-DNs culturing and signal detection. Additionally, this review discusses advances in the development and use of MEA technology to study in vitro neural disease models, including epilepsy, autism spectrum developmental disorder (ASD), and others established using hiPSC-DNs. The paper also highlights the application of MEAs combined with hiPSC-DNs in detecting in vitro neurotoxic substances. Finally, the future development and outlook of multifunctional and integrated devices for in vitro medical diagnostics and treatment are discussed.
Collapse
Affiliation(s)
- Shiya Lv
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Enhui He
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
- The State Key Lab of Brain‐Machine IntelligenceZhejiang UniversityHangzhou321100China
| | - Jinping Luo
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Yaoyao Liu
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Wei Liang
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Shihong Xu
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Kui Zhang
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Yan Yang
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Mixia Wang
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Yilin Song
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Yirong Wu
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| | - Xinxia Cai
- State Key Laboratory of Transducer TechnologyAerospace Information Research InstituteChinese Academy of SciencesBeijing100190China
- University of Chinese Academy of SciencesBeijing100049China
| |
Collapse
|
21
|
Duru J, Maurer B, Giles Doran C, Jelitto R, Küchler J, Ihle SJ, Ruff T, John R, Genocchi B, Vörös J. Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays. Biosens Bioelectron 2023; 239:115591. [PMID: 37634421 DOI: 10.1016/j.bios.2023.115591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 07/25/2023] [Accepted: 08/10/2023] [Indexed: 08/29/2023]
Abstract
Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks' early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.
Collapse
Affiliation(s)
- Jens Duru
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Benedikt Maurer
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Ciara Giles Doran
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Robert Jelitto
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Joël Küchler
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Stephan J Ihle
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Tobias Ruff
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Robert John
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| | - Barbara Genocchi
- Computational Biophysics and Imaging Group, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.
| | - János Vörös
- Laboratory of Biosensors and Bioelectronics, Institute for Biomedical Engineering, University and ETH Zurich, Gloriastrasse 35, Zurich, 8092, Switzerland.
| |
Collapse
|
22
|
Song S, Druschel LN, Chan ER, Capadona JR. Differential expression of genes involved in the chronic response to intracortical microelectrodes. Acta Biomater 2023; 169:348-362. [PMID: 37507031 PMCID: PMC10528922 DOI: 10.1016/j.actbio.2023.07.038] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 07/13/2023] [Accepted: 07/23/2023] [Indexed: 07/30/2023]
Abstract
Brain-Machine Interface systems (BMIs) are clinically valuable devices that can provide functional restoration for patients with spinal cord injury or improved integration for patients requiring prostheses. Intracortical microelectrodes can record neuronal action potentials at a resolution necessary for precisely controlling BMIs. However, intracortical microelectrodes have a demonstrated history of progressive decline in the recording performance with time, inhibiting their usefulness. One major contributor to decreased performance is the neuroinflammatory response to the implanted microelectrodes. The neuroinflammatory response can lead to neurodegeneration and the formation of a glial scar at the implant site. Historically, histological imaging of relatively few known cellular and protein markers has characterized the neuroinflammatory response to implanted microelectrode arrays. However, neuroinflammation requires many molecular players to coordinate the response - meaning traditional methods could result in an incomplete understanding. Taking advantage of recent advancements in tools to characterize the relative or absolute DNA/RNA expression levels, a few groups have begun to explore gene expression at the microelectrode-tissue interface. We have utilized a custom panel of ∼813 neuroinflammatory-specific genes developed with NanoString for bulk tissue analysis at the microelectrode-tissue interface. Our previous studies characterized the acute innate immune response to intracortical microelectrodes. Here we investigated the gene expression at the microelectrode-tissue interface in wild-type (WT) mice chronically implanted with nonfunctioning probes. We found 28 differentially expressed genes at chronic time points (4WK, 8WK, and 16WK), many in the complement and extracellular matrix system. Further, the expression levels were relatively stable over time. Genes identified here represent chronic molecular players at the microelectrode implant sites and potential therapeutic targets for the long-term integration of microelectrodes. STATEMENT OF SIGNIFICANCE: Intracortical microelectrodes can record neuronal action potentials at a resolution necessary for the precise control of Brain-Machine Interface systems (BMIs). However, intracortical microelectrodes have a demonstrated history of progressive declines in the recording performance with time, inhibiting their usefulness. One major contributor to the decline in these devices is the neuroinflammatory response against the implanted microelectrodes. Historically, neuroinflammation to implanted microelectrode arrays has been characterized by histological imaging of relatively few known cellular and protein markers. Few studies have begun to develop a more in-depth understanding of the molecular pathways facilitating device-mediated neuroinflammation. Here, we are among the first to identify genetic pathways that could represent targets to improve the host response to intracortical microelectrodes, and ultimately device performance.
Collapse
Affiliation(s)
- Sydney Song
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, United States
| | - Lindsey N Druschel
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, United States
| | - E Ricky Chan
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, OH 44106, United States
| | - Jeffrey R Capadona
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, United States; Advanced Platform Technology Center, Louis Stokes Cleveland Veterans Affairs Medical Center, Cleveland, OH 44106, United States.
| |
Collapse
|
23
|
Van den Eeckhoudt R, Christiaens AS, Ceyssens F, Vangalis V, Verstrepen KJ, Boon N, Tavernier F, Kraft M, Taurino I. Full-electric microfluidic platform to capture, analyze and selectively release single cells. LAB ON A CHIP 2023; 23:4276-4286. [PMID: 37668159 DOI: 10.1039/d3lc00645j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/06/2023]
Abstract
Current single-cell technologies require large and expensive equipment, limiting their use to specialized labs. In this paper, we present for the first time a microfluidic device which demonstrates a combined method for full-electric cell capturing, analyzing, and selectively releasing with single-cell resolution. All functionalities are experimentally demonstrated on Saccharomyces cerevisiae. Our microfluidic platform consists of traps centered around a pair of individually accessible coplanar electrodes, positioned under a microfluidic channel. Using this device, we validate our novel Two-Voltage method for trapping single cells by positive dielectrophoresis (pDEP). Cells are attracted to the trap when a high voltage (VH) is applied. A low voltage (VL) holds the already trapped cell in place without attracting additional cells, allowing full control over the number of trapped cells. After trapping, the cells are analyzed by broadband electrochemical impedance spectroscopy. These measurements allow the detection of single cells and the extraction of cell parameters. Additionally, these measurements show a strong correlation between average phase change and cell size, enabling the use of our system for size measurements in biological applications. Finally, our device allows selectively releasing trapped cells by turning off the pDEP signal in their trap. The experimental results show the techniques potential as a full-electric single-cell analysis tool with potential for miniaturization and automation which opens new avenues towards small-scale, high throughput single-cell analysis and sorting lab-on-CMOS devices.
Collapse
Affiliation(s)
- Ruben Van den Eeckhoudt
- Micro- and Nanosystems (MNS), Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium.
| | - An-Sofie Christiaens
- Chemical and Biochemical Reactor Engineering and Safety (CREaS), Department of Chemical Engineering, KU Leuven, Leuven, Belgium
| | - Frederik Ceyssens
- Micro- and Nanosystems (MNS), Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium.
- Leuven Institute for Micro- and Nanoscale Integration (LIMNI), KU Leuven, Leuven, Belgium
| | - Vasileios Vangalis
- VIB - KU Leuven Center for Microbiology, Leuven, Belgium
- CMPG Laboratory for Genetics and Genomics, KU Leuven, Leuven, Belgium
| | - Kevin J Verstrepen
- VIB - KU Leuven Center for Microbiology, Leuven, Belgium
- CMPG Laboratory for Genetics and Genomics, KU Leuven, Leuven, Belgium
| | - Nico Boon
- Center for Microbial Ecology and Technology (CMET), Faculty of Bioscience Engineering, Ghent University, Ghent, Belgium
| | - Filip Tavernier
- MICAS, Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium
| | - Michael Kraft
- Micro- and Nanosystems (MNS), Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium.
- Leuven Institute for Micro- and Nanoscale Integration (LIMNI), KU Leuven, Leuven, Belgium
| | - Irene Taurino
- Micro- and Nanosystems (MNS), Department of Electrical Engineering (ESAT), KU Leuven, Leuven, Belgium.
- Semiconductor Physics, Department of Physics and Astronomy, KU Leuven, Leuven, Belgium
| |
Collapse
|
24
|
Radivojevic M, Rostedt Punga A. Functional imaging of conduction dynamics in cortical and spinal axons. eLife 2023; 12:e86512. [PMID: 37606618 PMCID: PMC10444024 DOI: 10.7554/elife.86512] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Accepted: 08/09/2023] [Indexed: 08/23/2023] Open
Abstract
Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here, we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-cm-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 m of cortical and spinal axons in total and found specific features in their structure and function.
Collapse
|
25
|
Astle DE, Johnson MH, Akarca D. Toward computational neuroconstructivism: a framework for developmental systems neuroscience. Trends Cogn Sci 2023; 27:726-744. [PMID: 37263856 DOI: 10.1016/j.tics.2023.04.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 01/05/2023] [Accepted: 04/19/2023] [Indexed: 06/03/2023]
Abstract
Brain development is underpinned by complex interactions between neural assemblies, driving structural and functional change. This neuroconstructivism (the notion that neural functions are shaped by these interactions) is core to some developmental theories. However, due to their complexity, understanding underlying developmental mechanisms is challenging. Elsewhere in neurobiology, a computational revolution has shown that mathematical models of hidden biological mechanisms can bridge observations with theory building. Can we build a similar computational framework yielding mechanistic insights for brain development? Here, we outline the conceptual and technical challenges of addressing this theory gap, and demonstrate that there is great potential in specifying brain development as mathematically defined processes operating within physical constraints. We provide examples, alongside broader ingredients needed, as the field explores computational explanations of system-wide development.
Collapse
Affiliation(s)
- Duncan E Astle
- Department of Psychiatry, University of Cambridge, Cambridge, CB2 2QQ, UK; MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK.
| | - Mark H Johnson
- Department of Psychology, University of Cambridge, Cambridge, CB2 3EB, UK; Centre for Brain and Cognitive Development, Birkbeck, University of London, London, WC1E 7JL, UK
| | - Danyal Akarca
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, CB2 7EF, UK
| |
Collapse
|
26
|
Chitale S, Wu W, Mukherjee A, Lannon H, Suresh P, Nag I, Ambrosi CM, Gertner RS, Melo H, Powers B, Wilkins H, Hinton H, Cheah M, Boynton Z, Alexeyev A, Sword D, Basan M, Park H, Ham D, Abbott J. A semiconductor 96-microplate platform for electrical-imaging based high-throughput phenotypic screening. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.01.543281. [PMID: 37333319 PMCID: PMC10274629 DOI: 10.1101/2023.06.01.543281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Profiling compounds and genetic perturbations via high-content imaging has become increasingly popular for drug discovery, but the technique is limited to endpoint images of fixed cells. In contrast, electronic-based devices offer label-free, functional information of live cells, yet current approaches suffer from low-spatial resolution or single-well throughput. Here, we report a semiconductor 96-microplate platform designed for high-resolution real-time impedance "imaging" at scale. Each well features 4,096 electrodes at 25 µm spatial resolution while a miniaturized data interface allows 8× parallel plate operation (768 total wells) within each incubator for enhanced throughputs. New electric field-based, multi-frequency measurement techniques capture >20 parameter images including tissue barrier, cell-surface attachment, cell flatness, and motility every 15 min throughout experiments. Using these real-time readouts, we characterized 16 cell types, ranging from primary epithelial to suspension, and quantified heterogeneity in mixed epithelial and mesenchymal co-cultures. A proof-of-concept screen of 904 diverse compounds using 13 semiconductor microplates demonstrates the platform's capability for mechanism of action (MOA) profiling with 25 distinct responses identified. The scalability of the semiconductor platform combined with the translatability of the high dimensional live-cell functional parameters expands high-throughput MOA profiling and phenotypic drug discovery applications.
Collapse
|
27
|
Zips S, Huang B, Hotte S, Hiendlmeier L, Wang C, Rajamani K, Buriez O, Al Boustani G, Chen Y, Wolfrum B, Yamada A. Aerosol Jet-Printed High-Aspect Ratio Micro-Needle Electrode Arrays Applied for Human Cerebral Organoids and 3D Neurospheroid Networks. ACS APPLIED MATERIALS & INTERFACES 2023. [PMID: 37469180 DOI: 10.1021/acsami.3c06210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Abstract
The human brain is a complex and poorly accessible organ. Thus, new tools are required for studying the neural function in a controllable environment that preserves multicellular interaction and neuronal wiring. In particular, high-throughput methods that alleviate the need for animal experiments are essential for future studies. Recent developments of induced pluripotent stem cell technologies have enabled in vitro modeling of the human brain by creating three-dimensional brain tissue mimic structures. To leverage these new technologies, a systematic and versatile approach for evaluating neuronal activity at larger tissue depths within the regime of tens to hundreds of micrometers is required. Here, we present an aerosol-jet- and inkjet-printing-based method to fabricate microelectrode arrays, equipped with high-aspect ratio μ-needle electrodes that penetrate 3D neural network assemblies. The arrays have been successfully applied for electrophysiological recordings on interconnected neurospheroids formed on an engineered substrate and on cerebral organoids, both derived from human induced pluripotent stem cells.
Collapse
Affiliation(s)
- Sabine Zips
- Neuroelectronics─Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Boltzmannstr. 11, 85748 Garching, Germany
| | - Boxin Huang
- PASTEUR, Department of Chemistry, École Normale Supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
| | - Salammbô Hotte
- PASTEUR, Department of Chemistry, École Normale Supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
| | - Lukas Hiendlmeier
- Neuroelectronics─Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Boltzmannstr. 11, 85748 Garching, Germany
| | - Chen Wang
- Neuroelectronics─Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Boltzmannstr. 11, 85748 Garching, Germany
| | - Karthyayani Rajamani
- PASTEUR, Department of Chemistry, École Normale Supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
| | - Olivier Buriez
- PASTEUR, Department of Chemistry, École Normale Supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
| | - George Al Boustani
- Neuroelectronics─Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Boltzmannstr. 11, 85748 Garching, Germany
| | - Yong Chen
- PASTEUR, Department of Chemistry, École Normale Supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
| | - Bernhard Wolfrum
- Neuroelectronics─Munich Institute of Biomedical Engineering, Department of Electrical Engineering, TUM School of Computation, Information and Technology, Technical University of Munich, Boltzmannstr. 11, 85748 Garching, Germany
| | - Ayako Yamada
- PASTEUR, Department of Chemistry, École Normale Supérieure, PSL University, Sorbonne Université, CNRS, 75005 Paris, France
| |
Collapse
|
28
|
Miyahara Y, Shimba K, Kotani K, Jimbo Y. Development of a Hypersensitivity Evaluation Method for Cultured Sensory Neurons Using Electrical Activity Recording. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083422 DOI: 10.1109/embc40787.2023.10340773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Investigation of hypersensitivity caused by peripheral sensitization progression is important for developing novel pain treatments. Existing methods cannot record plastic changes in neuronal activity because they occur over a few days. We aimed to establish an efficient method to evaluate neuronal activity alterations caused by peripheral sensitization on high-density microelectrode arrays (HD-MEAs) which can record neuronal activity for a long time. Rat dorsal root ganglion (DRG) neurons were dissected from rat embryos and cultured on HD-MEAs. DRG neurons were labeled with NeuO, live staining dye. Neurons were detected with the fluorescence signal and electrodes were selected with the fluorescence images. The number of DRG neurons, whose activity were recorded, detected based on fluorescence observation was five times greater than that based on neuronal activity. Analysis of changes in neuronal activity observed in pharmacological stimulation experiments suggested that substance P induced peripheral sensitization and enhanced capsaicin sensitivity. In addition, results of immunofluorescence staining suggested that peripheral sensitization occurred mostly in neurons that co-expressed transient receptor potential vanilloid 1 (TRPV1) and neurokinin 1 receptor (NK1R). In conclusion, we established an efficient method for assessing the effects of peripheral sensitization on DRG neurons cultured on HD-MEAs.
Collapse
|
29
|
Madugula SS, Vilkhu R, Shah NP, Grosberg LE, Kling A, Gogliettino AR, Nguyen H, Hottowy P, Sher A, Litke AM, Chichilnisky EJ. Inference of Electrical Stimulation Sensitivity from Recorded Activity of Primate Retinal Ganglion Cells. J Neurosci 2023; 43:4808-4820. [PMID: 37268418 PMCID: PMC10312054 DOI: 10.1523/jneurosci.1023-22.2023] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 05/22/2023] [Accepted: 05/24/2023] [Indexed: 06/04/2023] Open
Abstract
High-fidelity electronic implants can in principle restore the function of neural circuits by precisely activating neurons via extracellular stimulation. However, direct characterization of the individual electrical sensitivity of a large population of target neurons, to precisely control their activity, can be difficult or impossible. A potential solution is to leverage biophysical principles to infer sensitivity to electrical stimulation from features of spontaneous electrical activity, which can be recorded relatively easily. Here, this approach is developed and its potential value for vision restoration is tested quantitatively using large-scale multielectrode stimulation and recording from retinal ganglion cells (RGCs) of male and female macaque monkeys ex vivo Electrodes recording larger spikes from a given cell exhibited lower stimulation thresholds across cell types, retinas, and eccentricities, with systematic and distinct trends for somas and axons. Thresholds for somatic stimulation increased with distance from the axon initial segment. The dependence of spike probability on injected current was inversely related to threshold, and was substantially steeper for axonal than somatic compartments, which could be identified by their recorded electrical signatures. Dendritic stimulation was largely ineffective for eliciting spikes. These trends were quantitatively reproduced with biophysical simulations. Results from human RGCs were broadly similar. The inference of stimulation sensitivity from recorded electrical features was tested in a data-driven simulation of visual reconstruction, revealing that the approach could significantly improve the function of future high-fidelity retinal implants.SIGNIFICANCE STATEMENT This study demonstrates that individual in situ primate retinal ganglion cells of different types respond to artificially generated, external electrical fields in a systematic manner, in accordance with theoretical predictions, that allows for prediction of electrical stimulus sensitivity from recorded spontaneous activity. It also provides evidence that such an approach could be immensely helpful in the calibration of clinical retinal implants.
Collapse
Affiliation(s)
- Sasidhar S Madugula
- Neurosciences PhD Program, Stanford University, Stanford, California 94305
- School of Medicine, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Ramandeep Vilkhu
- Department of Electrical Engineering, Stanford University, Stanford, California 94305
| | - Nishal P Shah
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Department of Electrical Engineering, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Lauren E Grosberg
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Facebook Reality Labs, Facebook, Mountain View, California 94040
| | - Alexandra Kling
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Alex R Gogliettino
- Neurosciences PhD Program, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Huy Nguyen
- Department of Neurosurgery, Stanford University, Stanford, California 94305
| | - Paweł Hottowy
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, Krakow, Poland 30-059
| | - Alexander Sher
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, California 95064
| | - Alan M Litke
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, California 95064
| | - E J Chichilnisky
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Department of Ophthalmology, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| |
Collapse
|
30
|
Gogliettino AR, Madugula SS, Grosberg LE, Vilkhu RS, Brown J, Nguyen H, Kling A, Hottowy P, Dąbrowski W, Sher A, Litke AM, Chichilnisky EJ. High-Fidelity Reproduction of Visual Signals by Electrical Stimulation in the Central Primate Retina. J Neurosci 2023; 43:4625-4641. [PMID: 37188516 PMCID: PMC10286946 DOI: 10.1523/jneurosci.1091-22.2023] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 05/08/2023] [Accepted: 05/10/2023] [Indexed: 05/17/2023] Open
Abstract
Electrical stimulation of retinal ganglion cells (RGCs) with electronic implants provides rudimentary artificial vision to people blinded by retinal degeneration. However, current devices stimulate indiscriminately and therefore cannot reproduce the intricate neural code of the retina. Recent work has demonstrated more precise activation of RGCs using focal electrical stimulation with multielectrode arrays in the peripheral macaque retina, but it is unclear how effective this can be in the central retina, which is required for high-resolution vision. This work probes the neural code and effectiveness of focal epiretinal stimulation in the central macaque retina, using large-scale electrical recording and stimulation ex vivo The functional organization, light response properties, and electrical properties of the major RGC types in the central retina were mostly similar to the peripheral retina, with some notable differences in density, kinetics, linearity, spiking statistics, and correlations. The major RGC types could be distinguished by their intrinsic electrical properties. Electrical stimulation targeting parasol cells revealed similar activation thresholds and reduced axon bundle activation in the central retina, but lower stimulation selectivity. Quantitative evaluation of the potential for image reconstruction from electrically evoked parasol cell signals revealed higher overall expected image quality in the central retina. An exploration of inadvertent midget cell activation suggested that it could contribute high spatial frequency noise to the visual signal carried by parasol cells. These results support the possibility of reproducing high-acuity visual signals in the central retina with an epiretinal implant.SIGNIFICANCE STATEMENT Artificial restoration of vision with retinal implants is a major treatment for blindness. However, present-day implants do not provide high-resolution visual perception, in part because they do not reproduce the natural neural code of the retina. Here, we demonstrate the level of visual signal reproduction that is possible with a future implant by examining how accurately responses to electrical stimulation of parasol retinal ganglion cells can convey visual signals. Although the precision of electrical stimulation in the central retina was diminished relative to the peripheral retina, the quality of expected visual signal reconstruction in parasol cells was greater. These findings suggest that visual signals could be restored with high fidelity in the central retina using a future retinal implant.
Collapse
Affiliation(s)
- Alex R Gogliettino
- Neurosciences PhD Program, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Sasidhar S Madugula
- Neurosciences PhD Program, Stanford University, Stanford, California 94305
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Stanford School of Medicine, Stanford University, Stanford, California 94305
| | - Lauren E Grosberg
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Department of Neurosurgery, Stanford University, Stanford, California 94305
| | - Ramandeep S Vilkhu
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Department of Electrical Engineering, Stanford University, Stanford, California 94305
| | - Jeff Brown
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Department of Electrical Engineering, Stanford University, Stanford, California 94305
| | - Huy Nguyen
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
| | - Alexandra Kling
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Department of Neurosurgery, Stanford University, Stanford, California 94305
| | - Paweł Hottowy
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, 30-059, Kraków, Poland
| | - Władysław Dąbrowski
- Faculty of Physics and Applied Computer Science, AGH University of Science and Technology, 30-059, Kraków, Poland
| | - Alexander Sher
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, Santa Cruz, California 95064
| | - Alan M Litke
- Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, Santa Cruz, California 95064
| | - E J Chichilnisky
- Hansen Experimental Physics Laboratory, Stanford University, Stanford, California 94305
- Department of Neurosurgery, Stanford University, Stanford, California 94305
- Department of Electrical Engineering, Stanford University, Stanford, California 94305
- Department of Ophthalmology, Stanford University, Stanford, California 94305
| |
Collapse
|
31
|
Wang P, Wu EG, Uluşan H, Phillips A, Rose Hays M, Kling A, Zhao ET, Madugula S, Vilkhu RS, Vasireddy PK, Hier- lemann A, Hong G, Chichilnisky E, Melosh NA. Direct-print three-dimensional electrodes for large- scale, high-density, and customizable neural inter- faces. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.30.542925. [PMID: 37398164 PMCID: PMC10312573 DOI: 10.1101/2023.05.30.542925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Silicon-based planar microelectronics is a powerful tool for scalably recording and modulating neural activity at high spatiotemporal resolution, but it remains challenging to target neural structures in three dimensions (3D). We present a method for directly fabricating 3D arrays of tissue-penetrating microelectrodes onto silicon microelectronics. Leveraging a high-resolution 3D printing technology based on 2-photon polymerization and scalable microfabrication processes, we fabricated arrays of 6,600 microelectrodes 10-130 μm tall and at 35-μm pitch onto a planar silicon-based microelectrode array. The process enables customizable electrode shape, height and positioning for precise targeting of neuron populations distributed in 3D. As a proof of concept, we addressed the challenge of specifically targeting retinal ganglion cell (RGC) somas when interfacing with the retina. The array was customized for insertion into the retina and recording from somas while avoiding the axon layer. We verified locations of the microelectrodes with confocal microscopy and recorded high-resolution spontaneous RGC activity at cellular resolution. This revealed strong somatic and dendritic components with little axon contribution, unlike recordings with planar microelectrode arrays. The technology could be a versatile solution for interfacing silicon microelectronics with neural structures and modulating neural activity at large scale with single-cell resolution.
Collapse
Affiliation(s)
- Pingyu Wang
- Department of Materials Science and Engineering, Stanford University
| | - Eric G. Wu
- Department of Electrical Engineering, Stanford University, Stanford University
| | - Hasan Uluşan
- Department of Biosystems Science and Engineering in Basel, ETH Zürich
| | - A.J. Phillips
- Department of Electrical Engineering, Stanford University, Stanford University
| | | | | | - Eric T. Zhao
- Department of Chemical Engineering, Stanford University
| | | | - Ramandeep S. Vilkhu
- Department of Electrical Engineering, Stanford University, Stanford University
| | | | | | - Guosong Hong
- Department of Materials Science and Engineering, Stanford University
| | - E.J. Chichilnisky
- Department of Neurosurgery, Stanford University
- Hansen Experimental Physics Laboratory, Stanford University
| | | |
Collapse
|
32
|
Girardi G, Zumpano D, Goshi N, Raybould H, Seker E. Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules. BIOSENSORS 2023; 13:601. [PMID: 37366967 DOI: 10.3390/bios13060601] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 05/23/2023] [Accepted: 05/24/2023] [Indexed: 06/28/2023]
Abstract
The gut-brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints.
Collapse
Affiliation(s)
- Gregory Girardi
- Department of Biomedical Engineering, University of California-Davis, Davis, CA 95616, USA
| | - Danielle Zumpano
- Department of Anatomy, Physiology and Cell Biology, School of Veterinary Medicine, University of California-Davis, Davis, CA 95616, USA
| | - Noah Goshi
- Department of Biomedical Engineering, University of California-Davis, Davis, CA 95616, USA
| | - Helen Raybould
- Department of Anatomy, Physiology and Cell Biology, School of Veterinary Medicine, University of California-Davis, Davis, CA 95616, USA
| | - Erkin Seker
- Department of Electrical and Computer Engineering, University of California-Davis, Davis, CA 95616, USA
| |
Collapse
|
33
|
Iyer V, Issadore DA, Aflatouni F. The next generation of hybrid microfluidic/integrated circuit chips: recent and upcoming advances in high-speed, high-throughput, and multifunctional lab-on-IC systems. LAB ON A CHIP 2023; 23:2553-2576. [PMID: 37114950 DOI: 10.1039/d2lc01163h] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Since the field's inception, pioneers in microfluidics have made significant progress towards realizing complete lab-on-chip systems capable of sophisticated sample analysis and processing. One avenue towards this goal has been to join forces with the related field of microelectronics, using integrated circuits (ICs) to perform on-chip actuation and sensing. While early demonstrations focused on using microfluidic-IC hybrid chips to miniaturize benchtop instruments, steady advancements in the field have enabled a new generation of devices that expand past miniaturization into high-performance applications that would not be possible without IC hybrid integration. In this review, we identify recent examples of labs-on-chip that use high-resolution, high-speed, and multifunctional electronic and photonic chips to expand the capabilities of conventional sample analysis. We focus on three particularly active areas: a) high-throughput integrated flow cytometers; b) large-scale microelectrode arrays for stimulation and multimodal sensing of cells over a wide field of view; c) high-speed biosensors for studying molecules with high temporal resolution. We also discuss recent advancements in IC technology, including on-chip data processing techniques and lens-free optics based on integrated photonics, that are poised to further advance microfluidic-IC hybrid chips.
Collapse
Affiliation(s)
- Vasant Iyer
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
| | - David A Issadore
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
- Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Firooz Aflatouni
- Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
| |
Collapse
|
34
|
Muzzi L, Di Lisa D, Falappa M, Pepe S, Maccione A, Pastorino L, Martinoia S, Frega M. Human-Derived Cortical Neurospheroids Coupled to Passive, High-Density and 3D MEAs: A Valid Platform for Functional Tests. Bioengineering (Basel) 2023; 10:bioengineering10040449. [PMID: 37106636 PMCID: PMC10136157 DOI: 10.3390/bioengineering10040449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 03/31/2023] [Indexed: 04/29/2023] Open
Abstract
With the advent of human-induced pluripotent stem cells (hiPSCs) and differentiation protocols, methods to create in-vitro human-derived neuronal networks have been proposed. Although monolayer cultures represent a valid model, adding three-dimensionality (3D) would make them more representative of an in-vivo environment. Thus, human-derived 3D structures are becoming increasingly used for in-vitro disease modeling. Achieving control over the final cell composition and investigating the exhibited electrophysiological activity is still a challenge. Thence, methodologies to create 3D structures with controlled cellular density and composition and platforms capable of measuring and characterizing the functional aspects of these samples are needed. Here, we propose a method to rapidly generate neurospheroids of human origin with control over cell composition that can be used for functional investigations. We show a characterization of the electrophysiological activity exhibited by the neurospheroids by using micro-electrode arrays (MEAs) with different types (i.e., passive, C-MOS, and 3D) and number of electrodes. Neurospheroids grown in free culture and transferred on MEAs exhibited functional activity that can be chemically and electrically modulated. Our results indicate that this model holds great potential for an in-depth study of signal transmission to drug screening and disease modeling and offers a platform for in-vitro functional testing.
Collapse
Affiliation(s)
- Lorenzo Muzzi
- Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS), University of Genoa, 16145 Genoa, Italy
| | - Donatella Di Lisa
- Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS), University of Genoa, 16145 Genoa, Italy
| | - Matteo Falappa
- 3Brain AG, 8808 Pfäffikon, Switzerland
- Corticale Srl., 16145 Genoa, Italy
| | - Sara Pepe
- Department of Experimental Medicine (DIMES), University of Genoa, 16132 Genoa, Italy
| | | | - Laura Pastorino
- Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS), University of Genoa, 16145 Genoa, Italy
| | - Sergio Martinoia
- Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS), University of Genoa, 16145 Genoa, Italy
| | - Monica Frega
- Department of Clinical Neurophysiology, University of Twente, 7522 NB Enschede, The Netherlands
- Department of Human Genetics, Radboudumc, Donders Institute for Brain, Cognition, and Behaviour, 6500 HB Nijmegen, The Netherlands
| |
Collapse
|
35
|
Xu HJ, Yao Y, Yao F, Chen J, Li M, Yang X, Li S, Lu F, Hu P, He S, Peng G, Jing N. Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells. CELL REGENERATION (LONDON, ENGLAND) 2023; 12:15. [PMID: 36949352 PMCID: PMC10033800 DOI: 10.1186/s13619-023-00159-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 02/24/2023] [Indexed: 03/24/2023]
Abstract
Spinal motor neurons deficiency results in a series of devastating disorders such as amyotrophic lateral sclerosis (ALS), spinal muscular atrophy (SMA) and spinal cord injury (SCI). These disorders are currently incurable, while human pluripotent stem cells (hPSCs)-derived spinal motor neurons are promising but suffered from inappropriate regional identity and functional immaturity for the study and treatment of posterior spinal cord related injuries. In this study, we have established human spinal cord neural progenitor cells (hSCNPCs) via hPSCs differentiated neuromesodermal progenitors (NMPs) and demonstrated the hSCNPCs can be continuously expanded up to 40 passages. hSCNPCs can be rapidly differentiated into posterior spinal motor neurons with high efficiency. The functional maturity has been examined in detail. Moreover, a co-culture scheme which is compatible for both neural and muscular differentiation is developed to mimic the neuromuscular junction (NMJ) formation in vitro. Together, these studies highlight the potential avenues for generating clinically relevant spinal motor neurons and modeling neuromuscular diseases through our defined hSCNPCs.
Collapse
Affiliation(s)
- He Jax Xu
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yao Yao
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Fenyong Yao
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Jiehui Chen
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Meishi Li
- University of Chinese Academy of Sciences, Beijing, China
- Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
| | - Xianfa Yang
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, China
- Guangzhou Laboratory/Bioland Laboratory, Guangzhou, 510005, China
| | - Sheng Li
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China
- Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 20023, China
| | - Fangru Lu
- Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China
| | - Ping Hu
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, China
- Guangzhou Laboratory/Bioland Laboratory, Guangzhou, 510005, China
- Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, 20023, China
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China
| | - Shuijin He
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
| | - Guangdun Peng
- University of Chinese Academy of Sciences, Beijing, China.
- Center for Cell Lineage and Development, CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cell and Regenerative Medicine, GIBH-HKU Guangdong-Hong Kong Stem Cell and Regenerative Medicine Research Centre, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, 510530, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
- Center for Cell Lineage and Atlas, Bioland Laboratory, Guangzhou, 510005, China.
| | - Naihe Jing
- State Key Laboratory of Cell Biology, CAS Center for Excellence in Molecular Cell Science, Shanghai Institute of Biochemistry and Cell Biology, Chinese Academy of Sciences, Shanghai, 200031, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Guangzhou Laboratory/Bioland Laboratory, Guangzhou, 510005, China.
- Institute for Stem Cell and Regeneration, Chinese Academy of Sciences, Beijing, 100101, China.
| |
Collapse
|
36
|
Xu S, Liu Y, Yang Y, Zhang K, Liang W, Xu Z, Wu Y, Luo J, Zhuang C, Cai X. Recent Progress and Perspectives on Neural Chip Platforms Integrating PDMS-Based Microfluidic Devices and Microelectrode Arrays. MICROMACHINES 2023; 14:709. [PMID: 37420942 DOI: 10.3390/mi14040709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 03/17/2023] [Accepted: 03/19/2023] [Indexed: 07/09/2023]
Abstract
Recent years have witnessed a spurt of progress in the application of the encoding and decoding of neural activities to drug screening, diseases diagnosis, and brain-computer interactions. To overcome the constraints of the complexity of the brain and the ethical considerations of in vivo research, neural chip platforms integrating microfluidic devices and microelectrode arrays have been raised, which can not only customize growth paths for neurons in vitro but also monitor and modulate the specialized neural networks grown on chips. Therefore, this article reviews the developmental history of chip platforms integrating microfluidic devices and microelectrode arrays. First, we review the design and application of advanced microelectrode arrays and microfluidic devices. After, we introduce the fabrication process of neural chip platforms. Finally, we highlight the recent progress on this type of chip platform as a research tool in the field of brain science and neuroscience, focusing on neuropharmacology, neurological diseases, and simplified brain models. This is a detailed and comprehensive review of neural chip platforms. This work aims to fulfill the following three goals: (1) summarize the latest design patterns and fabrication schemes of such platforms, providing a reference for the development of other new platforms; (2) generalize several important applications of chip platforms in the field of neurology, which will attract the attention of scientists in the field; and (3) propose the developmental direction of neural chip platforms integrating microfluidic devices and microelectrode arrays.
Collapse
Affiliation(s)
- Shihong Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yaoyao Liu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yan Yang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kui Zhang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Wei Liang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zhaojie Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yirong Wu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jinping Luo
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chengyu Zhuang
- Department of Orthopaedics, Rujing Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Xinxia Cai
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100190, China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
37
|
Kim T, Chen D, Hornauer P, Emmenegger V, Bartram J, Ronchi S, Hierlemann A, Schröter M, Roqueiro D. Predicting in vitro single-neuron firing rates upon pharmacological perturbation using Graph Neural Networks. Front Neuroinform 2023; 16:1032538. [PMID: 36713289 PMCID: PMC9874697 DOI: 10.3389/fninf.2022.1032538] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Accepted: 12/13/2022] [Indexed: 01/12/2023] Open
Abstract
Modern Graph Neural Networks (GNNs) provide opportunities to study the determinants underlying the complex activity patterns of biological neuronal networks. In this study, we applied GNNs to a large-scale electrophysiological dataset of rodent primary neuronal networks obtained by means of high-density microelectrode arrays (HD-MEAs). HD-MEAs allow for long-term recording of extracellular spiking activity of individual neurons and networks and enable the extraction of physiologically relevant features at the single-neuron and population level. We employed established GNNs to generate a combined representation of single-neuron and connectivity features obtained from HD-MEA data, with the ultimate goal of predicting changes in single-neuron firing rate induced by a pharmacological perturbation. The aim of the main prediction task was to assess whether single-neuron and functional connectivity features, inferred under baseline conditions, were informative for predicting changes in neuronal activity in response to a perturbation with Bicuculline, a GABA A receptor antagonist. Our results suggest that the joint representation of node features and functional connectivity, extracted from a baseline recording, was informative for predicting firing rate changes of individual neurons after the perturbation. Specifically, our implementation of a GNN model with inductive learning capability (GraphSAGE) outperformed other prediction models that relied only on single-neuron features. We tested the generalizability of the results on two additional datasets of HD-MEA recordings-a second dataset with cultures perturbed with Bicuculline and a dataset perturbed with the GABA A receptor antagonist Gabazine. GraphSAGE models showed improved prediction accuracy over other prediction models. Our results demonstrate the added value of taking into account the functional connectivity between neurons and the potential of GNNs to study complex interactions between neurons.
Collapse
Affiliation(s)
- Taehoon Kim
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- Machine Learning and Computational Biology Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Dexiong Chen
- Machine Learning and Computational Biology Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Philipp Hornauer
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Vishalini Emmenegger
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Julian Bartram
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Silvia Ronchi
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Andreas Hierlemann
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Manuel Schröter
- Bioengineering Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
| | - Damian Roqueiro
- Machine Learning and Computational Biology Laboratory, Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland
- SIB Swiss Institute of Bioinformatics, Zurich, Switzerland
| |
Collapse
|
38
|
McSweeney D, English J, Howell E, Ribbe F, Pak C. Measuring Neuronal Network Activity Using Human Induced Neuronal Cells. Methods Mol Biol 2023; 2683:235-245. [PMID: 37300780 DOI: 10.1007/978-1-0716-3287-1_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Synchronous firing of neurons, often referred to as "network activity" or "network bursting," is an indication of a mature and synaptically connected network of neurons. We previously reported this phenomenon in 2D human neuronal in vitro models (McSweeney et al. iScience 25:105187, 2022). Using induced neurons (iNs) differentiated from human pluripotent stem cells (hPSCs) coupled with high-density microelectrodes arrays (HD-MEAs), we probed the underlying patterns of neuronal activity and found irregularities in network signaling across mutant states (McSweeney et al. iScience 25:105187, 2022). Here, we describe methods for plating cortical excitatory iNs differentiated from hPSCs on top of HD-MEAs and culturing iNs to maturity, examples of representative human wild-type Ngn2-iN data, and troubleshooting tips and tricks for the experimenter interested in integrating HD-MEAs into one's research approach.
Collapse
Affiliation(s)
- Danny McSweeney
- Graduate Program in Molecular and Cellular Biology, University of Massachusetts Amherst, Amherst, MA, USA
- Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Jay English
- Graduate Program in Molecular and Cellular Biology, University of Massachusetts Amherst, Amherst, MA, USA
- Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Ethan Howell
- Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, MA, USA
| | - Fumiko Ribbe
- Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, MA, USA
| | - ChangHui Pak
- Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, MA, USA.
| |
Collapse
|
39
|
Habibey R, Striebel J, Schmieder F, Czarske J, Busskamp V. Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays. Front Neurosci 2022; 16:951964. [PMID: 36267241 PMCID: PMC9578684 DOI: 10.3389/fnins.2022.951964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 09/06/2022] [Indexed: 11/13/2022] Open
Abstract
Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.
Collapse
Affiliation(s)
- Rouhollah Habibey
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Bonn, Germany
| | - Johannes Striebel
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Bonn, Germany
| | - Felix Schmieder
- Laboratory of Measurement and Sensor System Technique, Faculty of Electrical and Computer Engineering, TU Dresden, Dresden, Germany
| | - Jürgen Czarske
- Laboratory of Measurement and Sensor System Technique, Faculty of Electrical and Computer Engineering, TU Dresden, Dresden, Germany
- Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany
- Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany
- School of Science, Institute of Applied Physics, TU Dresden, Dresden, Germany
| | - Volker Busskamp
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Bonn, Germany
- *Correspondence: Volker Busskamp,
| |
Collapse
|
40
|
Lee J, Gänswein T, Ulusan H, Emmenegger V, Saguner AM, Duru F, Hierlemann A. Repeated and On-Demand Intracellular Recordings of Cardiomyocytes Derived from Human-Induced Pluripotent Stem Cells. ACS Sens 2022; 7:3181-3191. [PMID: 36166837 PMCID: PMC7613763 DOI: 10.1021/acssensors.2c01678] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Pharmaceutical compounds may have cardiotoxic properties, triggering potentially life-threatening arrhythmias. To investigate proarrhythmic effects of drugs, the patch clamp technique has been used as the gold standard for characterizing the electrophysiology of cardiomyocytes in vitro. However, the applicability of this technology for drug screening is limited, as it is complex to use and features low throughput. Recent studies have demonstrated that 3D-nanostructured electrodes enable to obtain intracellular signals from many cardiomyocytes in parallel; however, the tedious electrode fabrication and limited measurement duration still remain major issues for cardiotoxicity testing. Here, we demonstrate how porous Pt-black electrodes, arranged in high-density microelectrode arrays, can be used to record intracellular-like signals of cardiomyocytes at large scale repeatedly over an extended period of time. The developed technique, which yields highly parallelized electroporations using stimulation voltages around 1 V peak-to-peak amplitude, enabled intracellular-like recordings at high success rates without causing significant alteration in key electrophysiological features. In a proof-of-concept study, we investigated electrophysiological modulations induced by two clinically applied drugs, nifedipine and quinidine. As the obtained results were in good agreement with previously published data, we are confident that the developed technique has the potential to be routinely used in in vitro platforms for cardiotoxicity screening.
Collapse
Affiliation(s)
- Jihyun Lee
- Corresponding Authors Jihyun Lee — Bio Engineering Laboratory, ETH Zurich, 4058 Basel, Switzerland; ® Phone: +41 (0)61 387 31 28; jihyun.lee@ bsse.ethz.ch; Andreas Hierlemann — Bio Engineering Laboratory, ETH Zurich, 4058 Basel, Switzerland; Phone: +41 (0)61 387 31 50;
| | | | | | | | | | | | - Andreas Hierlemann
- Corresponding Authors Jihyun Lee — Bio Engineering Laboratory, ETH Zurich, 4058 Basel, Switzerland; ® Phone: +41 (0)61 387 31 28; jihyun.lee@ bsse.ethz.ch; Andreas Hierlemann — Bio Engineering Laboratory, ETH Zurich, 4058 Basel, Switzerland; Phone: +41 (0)61 387 31 50;
| |
Collapse
|
41
|
McSweeney D, Gabriel R, Jin K, Pang ZP, Aronow B, Pak C. CASK loss of function differentially regulates neuronal maturation and synaptic function in human induced cortical excitatory neurons. iScience 2022; 25:105187. [PMID: 36262316 PMCID: PMC9574418 DOI: 10.1016/j.isci.2022.105187] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 08/30/2022] [Accepted: 09/20/2022] [Indexed: 12/14/2022] Open
Abstract
Loss-of-function (LOF) mutations in CASK cause severe developmental phenotypes, including microcephaly with pontine and cerebellar hypoplasia, X-linked intellectual disability, and autism. Unraveling the pathological mechanisms of CASK-related disorders has been challenging owing to limited human cellular models to study the dynamic roles of this molecule during neuronal maturation and synapse development. Here, we investigate cell-autonomous functions of CASK in cortical excitatory induced neurons (iNs) generated from CASK knockout (KO) isogenic human embryonic stem cells (hESCs) using gene expression, morphometrics, and electrophysiology. While immature CASK KO iNs show robust neuronal outgrowth, mature CASK KO iNs display severe defects in synaptic transmission and synchronized network activity without compromising neuronal morphology and synapse numbers. In the developing human cortical excitatory neurons, CASK functions to promote both structural integrity and establishment of cortical excitatory neuronal networks. These results lay the foundation for future studies identifying suppressors of such phenotypes relevant to human patients.
Collapse
Affiliation(s)
- Danny McSweeney
- Graduate Program in Molecular and Cellular Biology, UMass Amherst, Amherst, MA 01003, USA,Department of Biochemistry and Molecular Biology, UMass Amherst, Amherst, MA 01003, USA
| | - Rafael Gabriel
- Department of Biochemistry and Molecular Biology, UMass Amherst, Amherst, MA 01003, USA
| | - Kang Jin
- Departments of Biomedical Informatics, Pediatrics, University of Cincinnati, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Zhiping P. Pang
- Child Health Institute of New Jersey and Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ 08901, USA
| | - Bruce Aronow
- Departments of Biomedical Informatics, Pediatrics, University of Cincinnati, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH 45229, USA
| | - ChangHui Pak
- Department of Biochemistry and Molecular Biology, UMass Amherst, Amherst, MA 01003, USA,Corresponding author
| |
Collapse
|
42
|
Sterin I, Santos AC, Park S. Neuronal Activity Reporters as Drug Screening Platforms. MICROMACHINES 2022; 13:1500. [PMID: 36144123 PMCID: PMC9504476 DOI: 10.3390/mi13091500] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 08/25/2022] [Accepted: 09/06/2022] [Indexed: 06/16/2023]
Abstract
Understanding how neuronal activity changes and detecting such changes in both normal and disease conditions is of fundamental importance to the field of neuroscience. Neuronal activity plays important roles in the formation and function of both synapses and circuits, and dysregulation of these processes has been linked to a number of debilitating diseases such as autism, schizophrenia, and epilepsy. Despite advances in our understanding of synapse biology and in how it is altered in disease, the development of therapeutics for these diseases has not advanced apace. Many neuronal activity assays have been developed over the years using a variety of platforms and approaches, but major limitations persist. Current assays, such as fluorescence indicators are not designed to monitor neuronal activity over a long time, they are typically low-throughput or lack sensitivity. These are major barriers to the development of new therapies, as drug screening needs to be both high-throughput to screen through libraries of compounds, and longitudinal to detect any effects that may emerge after continued application of the drug. This review will cover existing assays for measuring neuronal activity and highlight a live-cell assay recently developed. This assay can be performed with easily accessible lab equipment, is both scalable and longitudinal, and can be combined with most other established methods.
Collapse
Affiliation(s)
- Igal Sterin
- Department of Neurobiology, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| | - Ana C. Santos
- Department of Neurobiology, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
- Center for Neuroscience, University of California, Davis, Davis, CA 95618, USA
| | - Sungjin Park
- Department of Neurobiology, University of Utah School of Medicine, Salt Lake City, UT 84112, USA
| |
Collapse
|
43
|
Habibey R, Rojo Arias JE, Striebel J, Busskamp V. Microfluidics for Neuronal Cell and Circuit Engineering. Chem Rev 2022; 122:14842-14880. [PMID: 36070858 PMCID: PMC9523714 DOI: 10.1021/acs.chemrev.2c00212] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
The widespread adoption of microfluidic devices among the neuroscience and neurobiology communities has enabled addressing a broad range of questions at the molecular, cellular, circuit, and system levels. Here, we review biomedical engineering approaches that harness the power of microfluidics for bottom-up generation of neuronal cell types and for the assembly and analysis of neural circuits. Microfluidics-based approaches are instrumental to generate the knowledge necessary for the derivation of diverse neuronal cell types from human pluripotent stem cells, as they enable the isolation and subsequent examination of individual neurons of interest. Moreover, microfluidic devices allow to engineer neural circuits with specific orientations and directionality by providing control over neuronal cell polarity and permitting the isolation of axons in individual microchannels. Similarly, the use of microfluidic chips enables the construction not only of 2D but also of 3D brain, retinal, and peripheral nervous system model circuits. Such brain-on-a-chip and organoid-on-a-chip technologies are promising platforms for studying these organs as they closely recapitulate some aspects of in vivo biological processes. Microfluidic 3D neuronal models, together with 2D in vitro systems, are widely used in many applications ranging from drug development and toxicology studies to neurological disease modeling and personalized medicine. Altogether, microfluidics provide researchers with powerful systems that complement and partially replace animal models.
Collapse
Affiliation(s)
- Rouhollah Habibey
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Ernst-Abbe-Straße 2, D-53127 Bonn, Germany
| | - Jesús Eduardo Rojo Arias
- Wellcome─MRC Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge CB2 0AW, United Kingdom
| | - Johannes Striebel
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Ernst-Abbe-Straße 2, D-53127 Bonn, Germany
| | - Volker Busskamp
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Ernst-Abbe-Straße 2, D-53127 Bonn, Germany
| |
Collapse
|
44
|
Jia X, Shao W, Hu N, Shi J, Fan X, Chen C, Wang Y, Chen L, Qiao H, Li X. Learning populations with hubs govern the initiation and propagation of spontaneous bursts in neuronal networks after learning. Front Neurosci 2022; 16:854199. [PMID: 36061604 PMCID: PMC9433803 DOI: 10.3389/fnins.2022.854199] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 07/29/2022] [Indexed: 11/13/2022] Open
Abstract
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.
Collapse
Affiliation(s)
- Xiaoli Jia
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Wenwei Shao
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Nan Hu
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Jianxin Shi
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Xiu Fan
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Chong Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Youwei Wang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Liqun Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Huanhuan Qiao
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| | - Xiaohong Li
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin, China
| |
Collapse
|
45
|
Xue X, Buccino AP, Saseendran Kumar S, Hierlemann A, Bartram J. Inferring monosynaptic connections from paired dendritic spine Ca 2+imaging and large-scale recording of extracellular spiking. J Neural Eng 2022; 19. [PMID: 35931040 DOI: 10.1088/1741-2552/ac8765] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/05/2022] [Indexed: 11/12/2022]
Abstract
Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it onin vitrorecordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages asi) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree,ii) it provides precise information of presynaptic spiking, andiii) postsynaptic spine Ca2+signals and, finally,iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.
Collapse
Affiliation(s)
- Xiaohan Xue
- D-BSSE, ETH Zürich, Mattenstrasse 26, Basel, 4058, SWITZERLAND
| | | | | | | | - Julian Bartram
- D-BSSE, ETH Zürich, Mattenstrasse 26, Basel, 4058, SWITZERLAND
| |
Collapse
|
46
|
Jung HS, Jung WB, Wang J, Abbott J, Horgan A, Fournier M, Hinton H, Hwang YH, Godron X, Nicol R, Park H, Ham D. CMOS electrochemical pH localizer-imager. SCIENCE ADVANCES 2022; 8:eabm6815. [PMID: 35895813 PMCID: PMC9328676 DOI: 10.1126/sciadv.abm6815] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 06/10/2022] [Indexed: 05/27/2023]
Abstract
pH controls a large repertoire of chemical and biochemical processes in water. Densely arrayed pH microenvironments would parallelize these processes, enabling their high-throughput studies and applications. However, pH localization, let alone its arrayed realization, remains challenging because of fast diffusion of protons in water. Here, we demonstrate arrayed localizations of picoliter-scale aqueous acids, using a 256-electrochemical cell array defined on and operated by a complementary metal oxide semiconductor (CMOS)-integrated circuit. Each cell, comprising a concentric pair of cathode and anode with their current injections controlled with a sub-nanoampere resolution by the CMOS electronics, creates a local pH environment, or a pH "voxel," via confined electrochemistry. The system also monitors the spatiotemporal pH profile across the array in real time for precision pH control. We highlight the utility of this CMOS pH localizer-imager for high-throughput tasks by parallelizing pH-gated molecular state encoding and pH-regulated enzymatic DNA elongation at any selected set of cells.
Collapse
Affiliation(s)
- Han Sae Jung
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Woo-Bin Jung
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Jun Wang
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Jeffrey Abbott
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | | | | | - Henry Hinton
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Young-Ha Hwang
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | | | - Robert Nicol
- Broad Institute of MIT and Harvard, 415 Main Street, Cambridge, MA 02142, USA
| | - Hongkun Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA 02138, USA
- Department of Physics, Harvard University, Cambridge, MA 02138, USA
| | - Donhee Ham
- John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| |
Collapse
|
47
|
Suppression without inhibition: how retinal computation contributes to saccadic suppression. Commun Biol 2022; 5:692. [PMID: 35821404 PMCID: PMC9276698 DOI: 10.1038/s42003-022-03526-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 05/23/2022] [Indexed: 11/08/2022] Open
Abstract
Visual perception remains stable across saccadic eye movements, despite the concurrent strongly disruptive visual flow. This stability is partially associated with a reduction in visual sensitivity, known as saccadic suppression, which already starts in the retina with reduced ganglion cell sensitivity. However, the retinal circuit mechanisms giving rise to such suppression remain unknown. Here, we describe these mechanisms using electrophysiology in mouse, pig, and macaque retina, 2-photon calcium imaging, computational modeling, and human psychophysics. We find that sequential stimuli, like those that naturally occur during saccades, trigger three independent suppressive mechanisms in the retina. The main mechanism is triggered by contrast-reversing sequential stimuli and originates within the receptive field center of ganglion cells. It does not involve inhibition or other known suppressive mechanisms like saturation or adaptation. Instead, it relies on temporal filtering of the inherently slow response of cone photoreceptors coupled with downstream nonlinearities. Two further mechanisms of suppression are present predominantly in ON ganglion cells and originate in the receptive field surround, highlighting another disparity between ON and OFF ganglion cells. The mechanisms uncovered here likely play a role in shaping the retinal output following eye movements and other natural viewing conditions where sequential stimulation is ubiquitous.
Collapse
|
48
|
Mahadevan A, Codadu NK, Parrish RR. Xenon LFP Analysis Platform Is a Novel Graphical User Interface for Analysis of Local Field Potential From Large-Scale MEA Recordings. Front Neurosci 2022; 16:904931. [PMID: 35844228 PMCID: PMC9285004 DOI: 10.3389/fnins.2022.904931] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Accepted: 06/08/2022] [Indexed: 11/24/2022] Open
Abstract
High-density multi-electrode array (HD-MEA) has enabled neuronal measurements at high spatial resolution to record local field potentials (LFP), extracellular action potentials, and network-wide extracellular recording on an extended spatial scale. While we have advanced recording systems with over 4,000 electrodes capable of recording data at over 20 kHz, it still presents computational challenges to handle, process, extract, and view information from these large recordings. We have created a computational method, and an open-source toolkit built in Python, rendered on a web browser using Plotly’s Dash for extracting and viewing the data and creating interactive visualization. In addition to extracting and viewing entire or small chunks of data sampled at lower or higher frequencies, respectively, it provides a framework to collect user inputs, analyze channel groups, generate raster plots, view quick summary measures for LFP activity, detect and isolate noise channels, and generate plots and visualization in both time and frequency domain. Incorporated into our Graphical User Interface (GUI), we also created a novel seizure detection method, which can be used to detect the onset of seizures in all or a selected group of channels and provide the following measures of seizures: distance, duration, and propagation across the region of interest. We demonstrate the utility of this toolkit, using datasets collected from an HD-MEA device comprising of 4,096 recording electrodes. For the current analysis, we demonstrate the toolkit and methods with a low sampling frequency dataset (300 Hz) and a group of approximately 400 channels. Using this toolkit, we present novel data demonstrating increased seizure propagation speed from brain slices of Scn1aHet mice compared to littermate controls. While there have been advances in HD-MEA recording systems with high spatial and temporal resolution, limited tools are available for researchers to view and process these big datasets. We now provide a user-friendly toolkit to analyze LFP activity obtained from large-scale MEA recordings with translatable applications to EEG recordings and demonstrate the utility of this new graphic user interface with novel biological findings.
Collapse
Affiliation(s)
- Arjun Mahadevan
- Department of Cellular and Molecular Biology, Xenon Pharmaceuticals Inc., Burnaby, BC, Canada
| | - Neela K. Codadu
- Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, United Kingdom
| | - R. Ryley Parrish
- Department of Cellular and Molecular Biology, Xenon Pharmaceuticals Inc., Burnaby, BC, Canada
- *Correspondence: R. Ryley Parrish,
| |
Collapse
|
49
|
Schröter M, Wang C, Terrigno M, Hornauer P, Huang Z, Jagasia R, Hierlemann A. Functional imaging of brain organoids using high-density microelectrode arrays. MRS BULLETIN 2022; 47:530-544. [PMID: 36120104 PMCID: PMC9474390 DOI: 10.1557/s43577-022-00282-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/02/2022] [Indexed: 05/31/2023]
Abstract
ABSTRACT Studies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization. IMPACT STATEMENT Human cerebral organoids (hCOs) represent an attractive in vitro model system to study key physiological mechanisms underlying early neuronal network formation in tissue with healthy or disease-related genetic backgrounds. Despite remarkable advances in the generation of brain organoids, knowledge on the functionality of their neuronal circuits is still scarce. Here, we used complementary metal-oxide-semiconductor (CMOS)-based high-density microelectrode arrays (HD-MEAs) to perform large-scale recordings from sliced hCOs over several weeks and quantified their activity across scales. Using single-cell and network metrics, we were able to probe aspects of hCO neurophysiology that are more difficult to obtain with other techniques, such as patch clamping (lower yield) and calcium imaging (lower temporal resolution). These metrics included, for example, extracellular action potential (AP) waveform features and axonal AP velocity at the cellular level, as well as functional connectivity at the network level. Analysis was enabled by the large sensing area and the high spatiotemporal resolution provided by HD-MEAs, which allowed recordings from hundreds of neurons and spike sorting of their activity. Our results demonstrate that HD-MEAs provide a multi-purpose platform for the functional characterization of hCOs, which will be key in improving our understanding of this model system and assessing its relevance for translational research. SUPPLEMENTARY INFORMATION The online version contains supplementary material available at 10.1557/s43577-022-00282-w.
Collapse
Affiliation(s)
- Manuel Schröter
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Congwei Wang
- NRD, F. Hoffmann-La Roche Ltd., Roche Innovation Center Basel, Basel, Switzerland
| | - Marco Terrigno
- NRD, F. Hoffmann-La Roche Ltd., Roche Innovation Center Basel, Basel, Switzerland
| | - Philipp Hornauer
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Ziqiang Huang
- EMBL Imaging Centre, European Molecular Biology Laboratory (EMBL), Heidelberg, Germany
| | - Ravi Jagasia
- NRD, F. Hoffmann-La Roche Ltd., Roche Innovation Center Basel, Basel, Switzerland
| | - Andreas Hierlemann
- Bio Engineering Laboratory, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| |
Collapse
|
50
|
Chang C, Furukawa T, Asahina T, Shimba K, Kotani K, Jimbo Y. Coupling of in vitro Neocortical-Hippocampal Coculture Bursts Induces Different Spike Rhythms in Individual Networks. Front Neurosci 2022; 16:873664. [PMID: 35677356 PMCID: PMC9168126 DOI: 10.3389/fnins.2022.873664] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 04/15/2022] [Indexed: 11/21/2022] Open
Abstract
Brain-state alternation is important for long-term memory formation. Each brain state can be identified with a specific process in memory formation, e.g., encoding during wakefulness or consolidation during sleeping. The hippocampal-neocortical dialogue was proposed as a hypothetical framework for systems consolidation, which features different cross-frequency couplings between the hippocampus and distributed neocortical regions in different brain states. Despite evidence supporting this hypothesis, little has been reported about how information is processed with shifts in brain states. To address this gap, we developed an in vitro neocortical-hippocampal coculture model to study how activity coupling can affect connections between coupled networks. Neocortical and hippocampal neurons were cultured in two different compartments connected by a micro-tunnel structure. The network activity of the coculture model was recorded by microelectrode arrays underlying the substrate. Rhythmic bursting was observed in the spontaneous activity and electrical evoked responses. Rhythmic bursting activity in one compartment could couple to that in the other via axons passing through the micro-tunnels. Two types of coupling patterns were observed: slow-burst coupling (neocortex at 0.1–0.5 Hz and hippocampus at 1 Hz) and fast burst coupling (neocortex at 20–40 Hz and hippocampus at 4–10 Hz). The network activity showed greater synchronicity in the slow-burst coupling, as indicated by changes in the burstiness index. Network synchronicity analysis suggests the presence of different information processing states under different burst activity coupling patterns. Our results suggest that the hippocampal-neocortical coculture model possesses multiple modes of burst activity coupling between the cortical and hippocampal parts. With the addition of external stimulation, the neocortical-hippocampal network model we developed can elucidate the influence of state shifts on information processing.
Collapse
Affiliation(s)
- ChihHsiang Chang
- Department of Precision Engineering, School of Engineering, The University of Tokyo, Tokyo, Japan
- *Correspondence: ChihHsiang Chang
| | - Takuma Furukawa
- Department of Precision Engineering, School of Engineering, The University of Tokyo, Tokyo, Japan
| | - Takahiro Asahina
- Department of Precision Engineering, School of Engineering, The University of Tokyo, Tokyo, Japan
| | - Kenta Shimba
- Department of Precision Engineering, School of Engineering, The University of Tokyo, Tokyo, Japan
| | - Kiyoshi Kotani
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Yasuhiko Jimbo
- Department of Precision Engineering, School of Engineering, The University of Tokyo, Tokyo, Japan
| |
Collapse
|