1
|
Patel D, Shetty S, Acha C, Pantoja IEM, Zhao A, George D, Gracias DH. Microinstrumentation for Brain Organoids. Adv Healthc Mater 2024:e2302456. [PMID: 38217546 DOI: 10.1002/adhm.202302456] [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: 07/30/2023] [Revised: 12/10/2023] [Indexed: 01/15/2024]
Abstract
Brain organoids are three-dimensional aggregates of self-organized differentiated stem cells that mimic the structure and function of human brain regions. Organoids bridge the gaps between conventional drug screening models such as planar mammalian cell culture, animal studies, and clinical trials. They can revolutionize the fields of developmental biology, neuroscience, toxicology, and computer engineering. Conventional microinstrumentation for conventional cellular engineering, such as planar microfluidic chips; microelectrode arrays (MEAs); and optical, magnetic, and acoustic techniques, has limitations when applied to three-dimensional (3D) organoids, primarily due to their limits with inherently two-dimensional geometry and interfacing. Hence, there is an urgent need to develop new instrumentation compatible with live cell culture techniques and with scalable 3D formats relevant to organoids. This review discusses conventional planar approaches and emerging 3D microinstrumentation necessary for advanced organoid-machine interfaces. Specifically, this article surveys recently developed microinstrumentation, including 3D printed and curved microfluidics, 3D and fast-scan optical techniques, buckling and self-folding MEAs, 3D interfaces for electrochemical measurements, and 3D spatially controllable magnetic and acoustic technologies relevant to two-way information transfer with brain organoids. This article highlights key challenges that must be addressed for robust organoid culture and reliable 3D spatiotemporal information transfer.
Collapse
Affiliation(s)
- Devan Patel
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Saniya Shetty
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Chris Acha
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Itzy E Morales Pantoja
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Alice Zhao
- Department of Biology, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - Derosh George
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
| | - David H Gracias
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
- Department of Chemistry, Johns Hopkins University, Baltimore, MD, 21218, USA
- Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, MD, 21218, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, 21218, USA
- Sidney Kimmel Comprehensive Cancer Center (SKCCC), Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
- Center for MicroPhysiological Systems (MPS), Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| |
Collapse
|
2
|
Saglam-Metiner P, Yildirim E, Dincer C, Basak O, Yesil-Celiktas O. Humanized brain organoids-on-chip integrated with sensors for screening neuronal activity and neurotoxicity. Mikrochim Acta 2024; 191:71. [PMID: 38168828 DOI: 10.1007/s00604-023-06165-4] [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: 10/10/2023] [Accepted: 12/21/2023] [Indexed: 01/05/2024]
Abstract
The complex structure and function of the human central nervous system that develops from the neural tube made in vitro modeling quite challenging until the discovery of brain organoids. Human-induced pluripotent stem cells-derived brain organoids offer recapitulation of the features of early human neurodevelopment in vitro, including the generation, proliferation, and differentiation into mature neurons and micro-macroglial cells, as well as the complex interactions among these diverse cell types of the developing brain. Recent advancements in brain organoids, microfluidic systems, real-time sensing technologies, and their cutting-edge integrated use provide excellent models and tools for emulation of fundamental neurodevelopmental processes, the pathology of neurological disorders, personalized transplantation therapy, and high-throughput neurotoxicity testing by bridging the gap between two-dimensional models and the complex three-dimensional environment in vivo. In this review, we summarize how bioengineering approaches are applied to mitigate the limitations of brain organoids for biomedical and clinical research. We further provide an extensive overview and future perspectives of the humanized brain organoids-on-chip platforms with integrated sensors toward brain organoid intelligence and biocomputing studies. Such approaches might pave the way for increasing approvable clinical applications by solving their current limitations.
Collapse
Affiliation(s)
- Pelin Saglam-Metiner
- Department of Bioengineering, Faculty of Engineering, Ege University, Izmir, Turkey
- Department of Translational Neuroscience, Division of Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Ender Yildirim
- Department of Mechanical Engineering, Middle East Technical University, Ankara, Turkey
- ODTÜ MEMS Center, Ankara, Turkey
| | - Can Dincer
- Department of Microsystems Engineering (IMTEK), University of Freiburg, Freiburg, Germany
- FIT Freiburg Center for Interactive Materials and Bioinspired Technologies, University of Freiburg, Freiburg, Germany
| | - Onur Basak
- Department of Translational Neuroscience, Division of Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands
| | - Ozlem Yesil-Celiktas
- Department of Bioengineering, Faculty of Engineering, Ege University, Izmir, Turkey.
| |
Collapse
|
3
|
Bedoyan E, Reddy JW, Kalmykov A, Cohen-Karni T, Chamanzar M. Adaptive frequency-domain filtering for neural signal preprocessing. Neuroimage 2023; 284:120429. [PMID: 37923279 DOI: 10.1016/j.neuroimage.2023.120429] [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: 07/07/2023] [Revised: 10/17/2023] [Accepted: 10/25/2023] [Indexed: 11/07/2023] Open
Abstract
Electrical interference from various sources is a common issue for experimental extracellular electrophysiology recordings collected using multi-electrode array neural recording systems. This interference deteriorates the signal-to-noise ratio (SNR) of the raw electrophysiology signals and hampers the accuracy of data post-processing using techniques such as spike-sorting. Traditional signal processing methods to digitally remove electrical interference during post-processing include bandpass filtering to limit the signal to the relevant spectral range of the biological data, e.g., the spikes band (300 Hz - 7 kHz), targeted notch filtering to remove power line interference from standard alternating current mains electricity and common reference removal to minimize noise common to all electrodes. These methods require a priori knowledge of the frequency of the interfering signal source to address the unique electromagnetic interference environment of each experimental setup. We discuss an adaptive method for automatically removing narrow-band electrical interference through a spectral peak detection and removal (SPDR) step that can be applied during post-processing of the recorded data, based on the intuition that tall, narrowband signals localized in the signal spectrum correspond to interference, rather than the activity of neurons. A spectral peak prominence (SPP) threshold is used to detect these peaks in the frequency domain, which will then be removed via notch filtering. We applied this method to simulated waveforms and also experimental electrophysiology data collected from cerebral organoids to demonstrate its effectiveness for removing unwanted interference without significantly distorting the neural signals. We discuss that proper selection of the SPP threshold is required to avoid over-filtering, which can result in distortion of the electrophysiology data. We also compare the firing-rate activity in the filtered electrophysiology with fluorescence calcium imaging, a secondary cellular activity marker, to quantify signal distortion and provide bounds on SNR-based optimization of the SPP threshold. The adaptive filtering technique demonstrated in this paper is a powerful method that can automatically detect and remove interband interference in recorded neural signals, potentially enabling data collection in more naturalistic settings where external interference signals are difficult to eliminate.
Collapse
Affiliation(s)
- Esther Bedoyan
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Jay W Reddy
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Anna Kalmykov
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Tzahi Cohen-Karni
- Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Department of Material Science and Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Maysamreza Chamanzar
- Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Department of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
| |
Collapse
|
4
|
Lavekar SS, Patel MD, Montalvo-Parra MD, Krencik R. Asteroid impact: the potential of astrocytes to modulate human neural networks within organoids. Front Neurosci 2023; 17:1305921. [PMID: 38075269 PMCID: PMC10702564 DOI: 10.3389/fnins.2023.1305921] [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: 10/02/2023] [Accepted: 11/08/2023] [Indexed: 02/12/2024] Open
Abstract
Astrocytes are a vital cellular component of the central nervous system that impact neuronal function in both healthy and pathological states. This includes intercellular signals to neurons and non-neuronal cells during development, maturation, and aging that can modulate neural network formation, plasticity, and maintenance. Recently, human pluripotent stem cell-derived neural aggregate cultures, known as neurospheres or organoids, have emerged as improved experimental platforms for basic and pre-clinical neuroscience compared to traditional approaches. Here, we summarize the potential capability of using organoids to further understand the mechanistic role of astrocytes upon neural networks, including the production of extracellular matrix components and reactive signaling cues. Additionally, we discuss the application of organoid models to investigate the astrocyte-dependent aspects of neuropathological diseases and to test astrocyte-inspired technologies. We examine the shortcomings of organoid-based experimental platforms and plausible improvements made possible by cutting-edge neuroengineering technologies. These advancements are expected to enable the development of improved diagnostic strategies and high-throughput translational applications regarding neuroregeneration.
Collapse
Affiliation(s)
| | | | | | - R. Krencik
- Department of Neurosurgery, Center for Neuroregeneration, Houston Methodist Research Institute, Houston, TX, United States
| |
Collapse
|
5
|
Phouphetlinthong O, Partiot E, Bernou C, Sebban A, Gaudin R, Charlot B. Protruding cantilever microelectrode array to monitor the inner electrical activity of cerebral organoids. LAB ON A CHIP 2023; 23:3603-3614. [PMID: 37489118 DOI: 10.1039/d3lc00294b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
Stem cell-derived cerebral organoids are artificially grown miniature organ-like structures mimicking embryonic brain architecture. They are composed of multiple neural cell types with 3D cell layer organization exhibiting local field potential. Measuring the extracellular electrical activity by means of conventional planar microelectrode arrays is particularly challenging due to the 3D architecture of organoids. In order to monitor the intra-organoid electrical activity of thick spheroid-shaped samples, we developed long protruding microelectrode arrays able to penetrate the inner regions of cerebral organoids to measure the local potential of neurons within the organoids. A new microfabrication process has been developed which, thanks to the relaxation of internal stresses of a stack of materials deposited over a sacrificial layer, allows one to build a protruding cantilever microelectrode array placed at the apex of beams which rise vertically, over two hundred microns. These slender beams inserted deeply into the organoids give access to the recording of local field potential from neurons buried inside the organoid. This novel device shall provide valuable tools to study neural functions in greater detail.
Collapse
Affiliation(s)
- Oramany Phouphetlinthong
- IES, Institut d'Electronique et des Systèmes, UMR 5214 CNRS, Montpellier, France
- University of Montpellier, Montpellier, France.
| | - Emma Partiot
- IRIM, Institut de Recherche en Infectiologie de Montpellier, UMR 9004 CNRS, Montpellier, France
- University of Montpellier, Montpellier, France.
| | - Corentin Bernou
- IRIM, Institut de Recherche en Infectiologie de Montpellier, UMR 9004 CNRS, Montpellier, France
- University of Montpellier, Montpellier, France.
| | - Audrey Sebban
- IES, Institut d'Electronique et des Systèmes, UMR 5214 CNRS, Montpellier, France
- University of Montpellier, Montpellier, France.
| | - Raphael Gaudin
- IRIM, Institut de Recherche en Infectiologie de Montpellier, UMR 9004 CNRS, Montpellier, France
- University of Montpellier, Montpellier, France.
| | - Benoit Charlot
- IES, Institut d'Electronique et des Systèmes, UMR 5214 CNRS, Montpellier, France
- University of Montpellier, Montpellier, France.
| |
Collapse
|
6
|
McDonald M, Sebinger D, Brauns L, Gonzalez-Cano L, Menuchin-Lasowski Y, Mierzejewski M, Psathaki OE, Stumpf A, Wickham J, Rauen T, Schöler H, Jones PD. A mesh microelectrode array for non-invasive electrophysiology within neural organoids. Biosens Bioelectron 2023; 228:115223. [PMID: 36931193 DOI: 10.1016/j.bios.2023.115223] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 03/07/2023] [Accepted: 03/10/2023] [Indexed: 03/13/2023]
Abstract
Organoids are emerging in vitro models of human physiology. Neural models require the evaluation of functional activity of single cells and networks, which is commonly measured by microelectrode arrays. The characteristics of organoids clash with existing in vitro or in vivo microelectrode arrays. With inspiration from implantable mesh electronics and growth of organoids on polymer scaffolds, we fabricated suspended hammock-like mesh microelectrode arrays for neural organoids. We have demonstrated the growth of organoids enveloping these meshes and the culture of organoids on meshes for up to one year. Furthermore, we present proof-of-principle recordings of spontaneous electrical activity across the volume of an organoid. Our concept enables a new class of microelectrode arrays for in vitro models of three-dimensional electrically active tissue.
Collapse
Affiliation(s)
- Matthew McDonald
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Markwiesenstr. 55, 72770, Reutlingen, Germany; Max Planck Institute for Molecular Biomedicine, Röntgenstr. 20, 48149, Münster, Germany
| | - David Sebinger
- Max Planck Institute for Molecular Biomedicine, Röntgenstr. 20, 48149, Münster, Germany
| | - Lisa Brauns
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Markwiesenstr. 55, 72770, Reutlingen, Germany; Max Planck Institute for Molecular Biomedicine, Röntgenstr. 20, 48149, Münster, Germany
| | - Laura Gonzalez-Cano
- Max Planck Institute for Molecular Biomedicine, Röntgenstr. 20, 48149, Münster, Germany
| | | | - Michael Mierzejewski
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Markwiesenstr. 55, 72770, Reutlingen, Germany; Max Planck Institute for Molecular Biomedicine, Röntgenstr. 20, 48149, Münster, Germany
| | - Olympia-Ekaterini Psathaki
- Max Planck Institute for Molecular Biomedicine, Röntgenstr. 20, 48149, Münster, Germany; University of Osnabrück, CellNanOs (Center of Cellular Nanoanalytics), Integrated Bioimaging Facility iBiOs, Barbarastr. 11, 49076, Osnabrück, Germany
| | - Angelika Stumpf
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Markwiesenstr. 55, 72770, Reutlingen, Germany
| | - Jenny Wickham
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Markwiesenstr. 55, 72770, Reutlingen, Germany
| | - Thomas Rauen
- Max Planck Institute for Molecular Biomedicine, Röntgenstr. 20, 48149, Münster, Germany.
| | - Hans Schöler
- Max Planck Institute for Molecular Biomedicine, Röntgenstr. 20, 48149, Münster, Germany
| | - Peter D Jones
- NMI Natural and Medical Sciences Institute at the University of Tübingen, Markwiesenstr. 55, 72770, Reutlingen, Germany.
| |
Collapse
|
7
|
Morales Pantoja IE, Smirnova L, Muotri AR, Wahlin KJ, Kahn J, Boyd JL, Gracias DH, Harris TD, Cohen-Karni T, Caffo BS, Szalay AS, Han F, Zack DJ, Etienne-Cummings R, Akwaboah A, Romero JC, Alam El Din DM, Plotkin JD, Paulhamus BL, Johnson EC, Gilbert F, Curley JL, Cappiello B, Schwamborn JC, Hill EJ, Roach P, Tornero D, Krall C, Parri R, Sillé F, Levchenko A, Jabbour RE, Kagan BJ, Berlinicke CA, Huang Q, Maertens A, Herrmann K, Tsaioun K, Dastgheyb R, Habela CW, Vogelstein JT, Hartung T. First Organoid Intelligence (OI) workshop to form an OI community. Front Artif Intell 2023; 6:1116870. [PMID: 36925616 PMCID: PMC10013972 DOI: 10.3389/frai.2023.1116870] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 02/08/2023] [Indexed: 03/08/2023] Open
Abstract
The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22-24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.
Collapse
Affiliation(s)
- Itzy E. Morales Pantoja
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Lena Smirnova
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Alysson R. Muotri
- Department of Pediatrics and Cellular and Molecular Medicine, School of Medicine, University of California, San Diego, San Diego, CA, United States
- Center for Academic Research and Training in Anthropogeny (CARTA), Archealization Center (ArchC), Kavli Institute for Brain and Mind, University of California, San Diego, San Diego, CA, United States
| | - Karl J. Wahlin
- Viterbi Family Department of Ophthalmology & the Shiley Eye Institute, UC San Diego, La Jolla, CA, United States
| | - Jeffrey Kahn
- Berman Institute of Bioethics, Johns Hopkins University, Baltimore, MD, United States
| | - J. Lomax Boyd
- Berman Institute of Bioethics, Johns Hopkins University, Baltimore, MD, United States
| | - David H. Gracias
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, United States
- Department of Chemistry, Johns Hopkins University, Baltimore, MD, United States
- Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, MD, United States
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD, United States
- Center for Microphysiological Systems (MPS), Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Oncology and Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Timothy D. Harris
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, United States
| | - Tzahi Cohen-Karni
- Departments of Biomedical Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
- Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Brian S. Caffo
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States
| | - Alexander S. Szalay
- Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
- Department of Physics and Astronomy, Krieger School of Arts and Sciences, Johns Hopkins University, Baltimore, MD, United States
- Mark Foundation Center for Advanced Genomics and Imaging, Johns Hopkins University, Baltimore, MD, United States
| | - Fang Han
- Department of Statistics and Economics, University of Washington, Seattle, WA, United States
| | - Donald J. Zack
- Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Ralph Etienne-Cummings
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Akwasi Akwaboah
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - July Carolina Romero
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Dowlette-Mary Alam El Din
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Jesse D. Plotkin
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Barton L. Paulhamus
- Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
| | - Erik C. Johnson
- Department of Research and Exploratory Development, Johns Hopkins University Applied Physics Laboratory, Laurel, MD, United States
| | - Frederic Gilbert
- Philosophy Program, School of Humanities, University of Tasmania, Hobart, TAS, Australia
| | | | | | - Jens C. Schwamborn
- Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Eric J. Hill
- School of Biosciences, College of Health and Life Sciences, Aston University, Birmingham, United Kingdom
| | - Paul Roach
- Department of Chemistry, School of Science, Loughborough University, Loughborough, Leicestershire, United Kingdom
| | - Daniel Tornero
- Department of Biomedical Sciences, Institute of Neuroscience, University of Barcelona, Barcelona, Spain
- Clinic Hospital August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Barcelona, Spain
| | - Caroline Krall
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
- Department of Molecular and Comparative Pathobiology, Johns Hopkins University, Baltimore, MD, United States
| | - Rheinallt Parri
- Aston Pharmacy School, College of Health and Life Sciences, Aston University, Birmingham, United Kingdom
| | - Fenna Sillé
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Andre Levchenko
- Department of Biomedical Engineering, Yale Systems Biology Institute, Yale University, New Haven, CT, United States
| | - Rabih E. Jabbour
- Department of Bioscience and Biotechnology, University of Maryland Global Campus, Rockville, MD, United States
| | | | - Cynthia A. Berlinicke
- Department of Ophthalmology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Qi Huang
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Alexandra Maertens
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Kathrin Herrmann
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Katya Tsaioun
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Raha Dastgheyb
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Christa Whelan Habela
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Joshua T. Vogelstein
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States
| | - Thomas Hartung
- Center for Alternatives to Animal Testing (CAAT), Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, United States
- Center for Alternatives to Animal Testing (CAAT)-Europe, University of Konstanz, Konstanz, Germany
| |
Collapse
|
8
|
Huang Q, Tang B, Romero JC, Yang Y, Elsayed SK, Pahapale G, Lee TJ, Morales Pantoja IE, Han F, Berlinicke C, Xiang T, Solazzo M, Hartung T, Qin Z, Caffo BS, Smirnova L, Gracias DH. Shell microelectrode arrays (MEAs) for brain organoids. SCIENCE ADVANCES 2022; 8:eabq5031. [PMID: 35977026 PMCID: PMC9385157 DOI: 10.1126/sciadv.abq5031] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 07/06/2022] [Indexed: 05/30/2023]
Abstract
Brain organoids are important models for mimicking some three-dimensional (3D) cytoarchitectural and functional aspects of the brain. Multielectrode arrays (MEAs) that enable recording and stimulation of activity from electrogenic cells offer notable potential for interrogating brain organoids. However, conventional MEAs, initially designed for monolayer cultures, offer limited recording contact area restricted to the bottom of the 3D organoids. Inspired by the shape of electroencephalography caps, we developed miniaturized wafer-integrated MEA caps for organoids. The optically transparent shells are composed of self-folding polymer leaflets with conductive polymer-coated metal electrodes. Tunable folding of the minicaps' polymer leaflets guided by mechanics simulations enables versatile recording from organoids of different sizes, and we validate the feasibility of electrophysiology recording from 400- to 600-μm-sized organoids for up to 4 weeks and in response to glutamate stimulation. Our studies suggest that 3D shell MEAs offer great potential for high signal-to-noise ratio and 3D spatiotemporal brain organoid recording.
Collapse
Affiliation(s)
- Qi Huang
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Bohao Tang
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21287, USA
| | - July Carolina Romero
- Center for Alternatives to Animal Testing, Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Yuqian Yang
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | | | - Gayatri Pahapale
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Tien-Jung Lee
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Itzy E. Morales Pantoja
- Center for Alternatives to Animal Testing, Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Fang Han
- Department of Statistics, University of Washington, Seattle, WA 98195, USA
| | - Cynthia Berlinicke
- Department of Ophthalmology, Johns Hopkins University School of Medicine, Wilmer Eye Institute, Baltimore, MD 21287, USA
| | - Terry Xiang
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Mallory Solazzo
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Thomas Hartung
- Center for Alternatives to Animal Testing, Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
- CAAT-Europe, University of Konstanz, 78464 Konstanz, Germany
- Environmental Metrology & Policy Program, Georgetown University, Washington, DC, 20057, USA
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Zhao Qin
- Department of Civil and Environmental Engineering, Syracuse University, Syracuse, NY 13244, USA
| | - Brian S. Caffo
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Lena Smirnova
- Center for Alternatives to Animal Testing, Department of Environmental Health and Engineering, Bloomberg School of Public Health and Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
- Environmental Metrology & Policy Program, Georgetown University, Washington, DC, 20057, USA
| | - David H. Gracias
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Materials Science and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Chemistry, Johns Hopkins University, Baltimore, MD 21218, USA
- Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Laboratory for Computational Sensing and Robotics (LCSR), Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| |
Collapse
|
9
|
Bod RB, Rokai J, Meszéna D, Fiáth R, Ulbert I, Márton G. From End to End: Gaining, Sorting, and Employing High-Density Neural Single Unit Recordings. Front Neuroinform 2022; 16:851024. [PMID: 35769832 PMCID: PMC9236662 DOI: 10.3389/fninf.2022.851024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 05/06/2022] [Indexed: 11/15/2022] Open
Abstract
The meaning behind neural single unit activity has constantly been a challenge, so it will persist in the foreseeable future. As one of the most sourced strategies, detecting neural activity in high-resolution neural sensor recordings and then attributing them to their corresponding source neurons correctly, namely the process of spike sorting, has been prevailing so far. Support from ever-improving recording techniques and sophisticated algorithms for extracting worthwhile information and abundance in clustering procedures turned spike sorting into an indispensable tool in electrophysiological analysis. This review attempts to illustrate that in all stages of spike sorting algorithms, the past 5 years innovations' brought about concepts, results, and questions worth sharing with even the non-expert user community. By thoroughly inspecting latest innovations in the field of neural sensors, recording procedures, and various spike sorting strategies, a skeletonization of relevant knowledge lays here, with an initiative to get one step closer to the original objective: deciphering and building in the sense of neural transcript.
Collapse
Affiliation(s)
- Réka Barbara Bod
- Laboratory of Experimental Neurophysiology, Department of Physiology, Faculty of Medicine, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mureş, Târgu Mureş, Romania
| | - János Rokai
- Integrative Neuroscience Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- School of PhD Studies, Semmelweis University, Budapest, Hungary
| | - Domokos Meszéna
- Integrative Neuroscience Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Richárd Fiáth
- Integrative Neuroscience Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - István Ulbert
- Integrative Neuroscience Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Gergely Márton
- Integrative Neuroscience Group, Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| |
Collapse
|
10
|
Raghuram V, Werginz P, Fried SI, Timko BP. Morphological Factors that Underlie Neural Sensitivity to Stimulation in the Retina. ADVANCED NANOBIOMED RESEARCH 2022; 1. [PMID: 35399546 DOI: 10.1002/anbr.202100069] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Retinal prostheses are a promising therapeutic intervention for patients afflicted by outer retinal degenerative diseases like retinitis pigmentosa and age-related macular degeneration. While significant advances in the development of retinal implants have been made, the quality of vision elicited by these devices remains largely sub-optimal. The variability in the responses produced by retinal devices is most likely due to the differences between the natural cell type-specific signaling that occur in the healthy retina vs. the non-specific activation of multiple cell types arising from artificial stimulation. In order to replicate these natural signaling patterns, stimulation strategies must be capable of preferentially activating specific RGC types. To design more selective stimulation strategies, a better understanding of the morphological factors that underlie the sensitivity to prosthetic stimulation must be developed. This review will focus on the role that different anatomical components play in driving the direct activation of RGCs by extracellular stimulation. Briefly, it will (1) characterize the variability in morphological properties of α-RGCs, (2) detail the influence of morphology on the direct activation of RGCs by electric stimulation, and (3) describe some of the potential biophysical mechanisms that could explain differences in activation thresholds and electrically evoked responses between RGC types.
Collapse
Affiliation(s)
- Vineeth Raghuram
- Boston VA Healthcare System, 150 S Huntington Ave, Boston, MA 02130, USA.,Dept. of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA 02155, USA.,Dept. of Neurosurgery, Massachusetts General Hospital - Harvard Medical School, 50 Blossom Street, Boston, MA, 02114
| | - Paul Werginz
- Institute for Analysis and Scientific Computing, Vienna University of Technology, Wiedner Hauptstrasse 8-10, Vienna, Austria.,Dept. of Neurosurgery, Massachusetts General Hospital - Harvard Medical School, 50 Blossom Street, Boston, MA, 02114
| | - Shelley I Fried
- Boston VA Healthcare System, 150 S Huntington Ave, Boston, MA 02130, USA.,Dept. of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA 02155, USA.,Dept. of Neurosurgery, Massachusetts General Hospital - Harvard Medical School, 50 Blossom Street, Boston, MA, 02114
| | - Brian P Timko
- Dept. of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA 02155, USA
| |
Collapse
|
11
|
Le Floch P, Li Q, Lin Z, Zhao S, Liu R, Tasnim K, Jiang H, Liu J. Stretchable Mesh Nanoelectronics for 3D Single-Cell Chronic Electrophysiology from Developing Brain Organoids. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2106829. [PMID: 35014735 PMCID: PMC8930507 DOI: 10.1002/adma.202106829] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2021] [Revised: 12/26/2021] [Indexed: 05/13/2023]
Abstract
Human induced pluripotent stem cell derived brain organoids have shown great potential for studies of human brain development and neurological disorders. However, quantifying the evolution of the electrical properties of brain organoids during development is currently limited by the measurement techniques, which cannot provide long-term stable 3D bioelectrical interfaces with developing brain organoids. Here, a cyborg brain organoid platform is reported, in which "tissue-like" stretchable mesh nanoelectronics are designed to match the mechanical properties of brain organoids and to be folded by the organogenetic process of progenitor or stem cells, distributing stretchable electrode arrays across the 3D organoids. The tissue-wide integrated stretchable electrode arrays show no interruption to brain organoid development, adapt to the volume and morphological changes during brain organoid organogenesis, and provide long-term stable electrical contacts with neurons within brain organoids during development. The seamless and noninvasive coupling of electrodes to neurons enables long-term stable, continuous recording and captures the emergence of single-cell action potentials from early-stage brain organoid development.
Collapse
Affiliation(s)
- Paul Le Floch
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Qiang Li
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Zuwan Lin
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Siyuan Zhao
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Ren Liu
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Kazi Tasnim
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Han Jiang
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
| | - Jia Liu
- School of Engineering and Applied Sciences, Harvard University, Boston, MA 02134, USA
- Corresponding author.
| |
Collapse
|
12
|
Garg R, Roman DS, Wang Y, Cohen-Karni D, Cohen-Karni T. Graphene nanostructures for input-output bioelectronics. BIOPHYSICS REVIEWS 2021; 2:041304. [PMID: 35005709 PMCID: PMC8717360 DOI: 10.1063/5.0073870] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 12/03/2021] [Indexed: 01/01/2023]
Abstract
The ability to manipulate the electrophysiology of electrically active cells and tissues has enabled a deeper understanding of healthy and diseased tissue states. This has primarily been achieved via input/output (I/O) bioelectronics that interface engineered materials with biological entities. Stable long-term application of conventional I/O bioelectronics advances as materials and processing techniques develop. Recent advancements have facilitated the development of graphene-based I/O bioelectronics with a wide variety of functional characteristics. Engineering the structural, physical, and chemical properties of graphene nanostructures and integration with modern microelectronics have enabled breakthrough high-density electrophysiological investigations. Here, we review recent advancements in 2D and 3D graphene-based I/O bioelectronics and highlight electrophysiological studies facilitated by these emerging platforms. Challenges and present potential breakthroughs that can be addressed via graphene bioelectronics are discussed. We emphasize the need for a multidisciplinary approach across materials science, micro-fabrication, and bioengineering to develop the next generation of I/O bioelectronics.
Collapse
Affiliation(s)
- Raghav Garg
- Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Daniel San Roman
- Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Yingqiao Wang
- Department of Materials Science and Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Devora Cohen-Karni
- Preclinical education biochemistry, Lake Erie College of Osteopathic Medicine at Seton Hill, Greensburg, Pennsylvania 15601, USA
| | | |
Collapse
|