Brain organoids are artificially grown 3D aggregates that resemble the embryonic human brain, usually generated from human induced pluripotent stem cells (h-iPSC). MaxTwo, a multi-well high resolution microelectrode array (MEA) system, is best suited for long-term and label-free analysis of brain organoids. MaxTwo’s large sensor array at high-resolution enables recording of every active cell across multiple areas of biological samples.
Readout at different scales:
Network level (population spike times, bursts)
Cell level (individual spike time, waveform)
Sub-cellular level (spatially resolved waveforms)
Webinar
Watch our Organoids webinar that introduces high-resolution functional imaging of Brain Organoids
MaxTwo enables recording of neuronal activity at high spatio-temporal resolution and label-free electrical imaging of organoids.
“See” all the active cells on top of the array and identify the activity of each cell.
Detect small spikes from developing neurons and from cell compartments, such as axonal action potentials.
Analyze full organoids and determine initiation and propagation of network activity.
Microscopy image of three h-iPSC-derived organoids (DIV 60) overlaid with firing rate and amplitude activity maps.1
Pharmacological manipulation of network bursts in organoids
The network bursting activity of h-iPSC-derived cortical organoids (DIV 60) was modulated using NMDA (N-methyl-D-aspartic acid) receptor inhibitor 6-cyano-7-nitroquinoxaline-2,3-dione (CNQX) and an NMDA noncompetitive antagonist (MK801). CNQX decreased the network activity, but increased the mean spike firing rate and mean spike amplitude. MK801 decreased both the network burst activity and the mean spike firing rate, but did not affect the mean spike amplitude.1
Functional characterization of organoids modeling different brain regions
High-resolution allows to precisely identify and isolate active areas in all the analyzed preparations. The progressive complexity of the modeled regions correlates with an increased synchrony in the recorded network activity.2
Activity maps and distributions of spike amplitude and firing rate for a h-iPSC-derived fused (dorsal + ventral) cerebral organoid (DIV 56).
Network activity for distinct organoid preparations.
Effects of serotonin exposure during cerebellar maturation
Cerebellar dysfunction often involves a prominent loss of Purkinje cells (Taroni and DiDonato, 2004). Serotonin (5-hydroxytryptoamine, 5-HT) is reported in the regulation of the morphological maturation of Purkinje cells (Kondoh et al., 2004; Oostland and van Hooft, 2013). 5-HT treatment during the maturation protocol of cerebellar organoids is hypothesized to lead to higher efficiency of morphological and physiological maturation of Purkinje cells. Treated organoids showcase synchronized bursting activity, an indicator of synaptic maturation.2
Activity maps and distributions of spike amplitude and firing rate for a 5-HT-treated h-iPSC-derived cerebellar organoid (DIV 56).
Effect of 5-HT treatment on the network activity of a cerebellar organoid.
Single cell tracking in organoids
Neurons up to a depth of 100 μm (Frey et al., 2009; Obien et al., 2019) can be precisely detected and isolated in brain organoids. Electrical footprints and single cell-spiking patterns can be extracted to analyze signal propagation and cell activation dynamics.1
Traces expressing different activation patterns of the three identified neurons (left). Three neurons identified from one area of an organoid; circles indicate the electrode used to obtain the electrical footprints for each neuron (right).
Electrical footprints of the three identified neurons.
1 Data obtained in collaboration with Hopstem Bioengineering Co., Ltd., Hangzhou, Zhejiang, China. Organoid image on the first page, top right is courtesy of Dr. Anxin Wang. 2 Data obtained in collaboration with the Stem Cell Engineering Research Group (SCERG) at iBB – Institute for Biosciences and Bioengineering of Instituto Superior Técnico, Universidade de Lisboa, Portugal. Special thanks to Ana Rita Gomes, MsC, for carrying out the experiments.
@article{Beaubois2024,
title = {BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network},
author = {Romain Beaubois and Jérémy Cheslet and Tomoya Duenki and Giuseppe De Venuto and Marta Carè and Farad Khoyratee and Michela Chiappalone and Pascal Branchereau and Yoshiho Ikeuchi and Timothée Levi },
url = {https://www.nature.com/articles/s41467-024-48905-x},
doi = {10.1038/s41467-024-48905-x},
year = {2024},
date = {2024-06-20},
journal = {Nature Communications},
abstract = {Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders remain limited, pushing the exploration of promising alternative approaches such as electroceutics. Recent research in bioelectronics and neuromorphic engineering have fostered the development of the new generation of neuroprostheses for brain repair. However, achieving their full potential necessitates a deeper understanding of biohybrid interaction. In this study, we present a novel real-time, biomimetic, cost-effective and user-friendly neural network capable of real-time emulation for biohybrid experiments. Our system facilitates the investigation and replication of biophysically detailed neural network dynamics while prioritizing cost-efficiency, flexibility and ease of use. We showcase the feasibility of conducting biohybrid experiments using standard biophysical interfaces and a variety of biological cells as well as real-time emulation of diverse network configurations. We envision our system as a crucial step towards the development of neuromorphic-based neuroprostheses for bioelectrical therapeutics, enabling seamless communication with biological networks on a comparable timescale. Its embedded real-time functionality enhances practicality and accessibility, amplifying its potential for real-world applications in biohybrid experiments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Characterization and modeling of biological neural networks has emerged as a field driving significant advancements in our understanding of brain function and related pathologies. As of today, pharmacological treatments for neurological disorders remain limited, pushing the exploration of promising alternative approaches such as electroceutics. Recent research in bioelectronics and neuromorphic engineering have fostered the development of the new generation of neuroprostheses for brain repair. However, achieving their full potential necessitates a deeper understanding of biohybrid interaction. In this study, we present a novel real-time, biomimetic, cost-effective and user-friendly neural network capable of real-time emulation for biohybrid experiments. Our system facilitates the investigation and replication of biophysically detailed neural network dynamics while prioritizing cost-efficiency, flexibility and ease of use. We showcase the feasibility of conducting biohybrid experiments using standard biophysical interfaces and a variety of biological cells as well as real-time emulation of diverse network configurations. We envision our system as a crucial step towards the development of neuromorphic-based neuroprostheses for bioelectrical therapeutics, enabling seamless communication with biological networks on a comparable timescale. Its embedded real-time functionality enhances practicality and accessibility, amplifying its potential for real-world applications in biohybrid experiments.
@article{vanderMolen2024,
title = {RT-Sort: an action potential propagation-based algorithm for real time spike detection and sorting with millisecond latencies},
author = {Tjitse van der Molen and Max Lim and Julian Bartram and Zhuowei Cheng and Ash Robbins and David F. Parks and Linda R. Petzold and Andreas Hierlemann and David Haussler and Paul K. Hansma and Kenneth R. Tovar and Kenneth S. Kosik},
url = {http://biorxiv.org/lookup/doi/10.1101/2024.04.08.588620},
doi = {10.1101/2024.04.08.588620},
year = {2024},
date = {2024-04-12},
journal = {bioRxiv},
abstract = {With the use of high density multi electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes both in vivo and in vitro. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high fidelity sequential activations on adjacent electrodes, together with a convolutional neural network based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms±1.5ms (mean±STD) after the waveform trough while the recording remains ongoing. RT-Sort’s true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sort’s performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sort’s functionality on different types of recording hardware and electrode configurations.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
With the use of high density multi electrode recording devices, electrophysiological signals resulting from action potentials of individual neurons can now be reliably detected on multiple adjacent recording electrodes both in vivo and in vitro. Spike sorting assigns these signals to putative neural sources. However, until now, spike sorting can only be performed after completion of the recording, preventing true real time usage of spike sorting algorithms. Utilizing the unique propagation patterns of action potentials along axons detected as high fidelity sequential activations on adjacent electrodes, together with a convolutional neural network based spike detection algorithm, we introduce RT-Sort (Real Time Sorting), a spike sorting algorithm that enables the sorted detection of action potentials within 7.5ms±1.5ms (mean±STD) after the waveform trough while the recording remains ongoing. RT-Sort’s true real-time spike sorting capabilities enable closed loop experiments with latencies comparable to synaptic delay times. We show RT-Sort’s performance on both Multi-Electrode Arrays as well as Neuropixels probes to exemplify RT-Sort’s functionality on different types of recording hardware and electrode configurations.
@article{Tetzlaff2024,
title = {Characterizing and targeting glioblastoma neuron-tumor networks with retrograde tracing},
author = {Svenja K. Tetzlaff and Ekin Reyhan and C. Peter Bengtson and Julian Schroers and Julia Wagner and Marc C. Schubert and Nikolas Layer and Maria C. Puschhof and Anton J. Faymonville and Nina Drewa and Rangel L. Pramatarov and Niklas Wissmann and Obada Alhalabi and Alina Heuer and Nirosan Sivapalan and Joaquín Campos and Berin Boztepe and Jonas G. Scheck and Giulia Villa and Manuel Schröter and Felix Sahm and Karin Forsberg-Nilsson and Michael O. Breckwoldt and Claudio Acuna and Bogdana Suchorska and Dieter Henrik Heiland and Julio Saez-Rodriguez and Varun Venkataramani},
url = {http://biorxiv.org/lookup/doi/10.1101/2024.03.18.585565},
doi = {10.1101/2024.03.18.585565},
year = {2024},
date = {2024-03-22},
journal = {bioRxiv},
abstract = {Glioblastomas are invasive brain tumors with high therapeutic resistance. Neuron-to-glioma synapses have been shown to promote glioblastoma progression. However, a characterization of tumor-connected neurons has been hampered by a lack of technologies. Here, we adapted retrograde tracing using rabies viruses to investigate and manipulate neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across the brain engaging in widespread functional communication, with acetylcholinergic neurons driving glioblastoma invasion. We uncovered patient-specific and tumor cell state-dependent differences in synaptogenic gene expression associated with neuron-tumor connectivity and subsequent invasivity. Importantly, radiotherapy enhanced neuron-tumor connectivity by increased neuronal activity. In turn, simultaneous neuronal activity inhibition and radiotherapy showed increased therapeutic effects, indicative of a role for neuron-to-glioma synapses in contributing to therapeutic resistance. Lastly, rabies-mediated genetic ablation of tumor-connected neurons halted glioblastoma progression, offering a viral strategy to tackle glioblastoma. Together, this study provides a framework to comprehensively characterize neuron-tumor networks and target glioblastoma.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Glioblastomas are invasive brain tumors with high therapeutic resistance. Neuron-to-glioma synapses have been shown to promote glioblastoma progression. However, a characterization of tumor-connected neurons has been hampered by a lack of technologies. Here, we adapted retrograde tracing using rabies viruses to investigate and manipulate neuron-tumor networks. Glioblastoma rapidly integrated into neural circuits across the brain engaging in widespread functional communication, with acetylcholinergic neurons driving glioblastoma invasion. We uncovered patient-specific and tumor cell state-dependent differences in synaptogenic gene expression associated with neuron-tumor connectivity and subsequent invasivity. Importantly, radiotherapy enhanced neuron-tumor connectivity by increased neuronal activity. In turn, simultaneous neuronal activity inhibition and radiotherapy showed increased therapeutic effects, indicative of a role for neuron-to-glioma synapses in contributing to therapeutic resistance. Lastly, rabies-mediated genetic ablation of tumor-connected neurons halted glioblastoma progression, offering a viral strategy to tackle glioblastoma. Together, this study provides a framework to comprehensively characterize neuron-tumor networks and target glioblastoma.
@article{Voitiuk2024,
title = {A feedback-driven IoT microfluidic, electrophysiology, and imaging platform for brain organoid studies},
author = {Kateryna Voitiuk and Spencer T. Seiler and Mirella Pessoa de Melo and Jinghui Geng and Sebastian Hernandez and Hunter E. Schweiger and Jess L. Sevetson and David F. Parks and Ash Robbins and Sebastian Torres-Montoya and Drew Ehrlich and Matthew A.T. Elliott and Tal Sharf and David Haussler and Mohammed A. Mostajo-Radji and Sofie R. Salama and Mircea Teodorescu},
url = {http://biorxiv.org/lookup/doi/10.1101/2024.03.15.585237},
doi = {10.1101/2024.03.15.585237},
year = {2024},
date = {2024-03-17},
journal = {bioRxiv},
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.
One-Sentence Summary:
An IoT laboratory robotics system that enables touch-free feeding, imaging, and electrophysiology of brain organoids.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
One-Sentence Summary:
An IoT laboratory robotics system that enables touch-free feeding, imaging, and electrophysiology of brain organoids.
@article{Molen2023,
title = {Protosequences in human cortical organoids model intrinsic states in the developing cortex},
author = {Tjitse van der Molen and Alex Spaeth and Mattia Chini and Julian Bartram and Aditya Dendukuri and Zongren Zhang and Kiran Bhaskaran-Nair and Lon J. Blauvelt and Linda R. Petzold and Paul K. Hansma and Mircea Teodorescu and Andreas Hierlemann and Keith B. Hengen and Ileana L. Hanganu-Opatz and Kenneth S. Kosik and Tal Sharf},
url = {https://www.biorxiv.org/content/10.1101/2023.12.29.573646v1},
doi = {10.1101/2023.12.29.573646},
year = {2023},
date = {2023-12-30},
journal = {bioRxiv},
abstract = {Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Neuronal firing sequences are thought to be the basic building blocks of neural coding and information broadcasting within the brain. However, when sequences emerge during neurodevelopment remains unknown. We demonstrate that structured firing sequences are present in spontaneous activity of human brain organoids and ex vivo neonatal brain slices from the murine somatosensory cortex. We observed a balance between temporally rigid and flexible firing patterns that are emergent phenomena in human brain organoids and early postnatal murine somatosensory cortex, but not in primary dissociated cortical cultures. Our findings suggest that temporal sequences do not arise in an experience-dependent manner, but are rather constrained by an innate preconfigured architecture established during neurogenesis. These findings highlight the potential for brain organoids to further explore how exogenous inputs can be used to refine neuronal circuits and enable new studies into the genetic mechanisms that govern assembly of functional circuitry during early human brain development.
@article{Cai2023b,
title = {Brain organoid reservoir computing for artificial intelligence},
author = {Hongwei Cai and Zheng Ao and Chunhui Tian and Zhuhao Wu and Hongcheng Liu and Jason Tchieu and Mingxia Gu and Ken Mackie and Feng Guo },
url = {https://www.nature.com/articles/s41928-023-01069-w},
doi = {10.1038/s41928-023-01069-w},
year = {2023},
date = {2023-12-11},
journal = {Nature Electronics},
abstract = {Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function as most examples are built on digital electronic principles. Here we report an artificial intelligence hardware approach that uses adaptive reservoir computation of biological neural networks in a brain organoid. In this approach—which is termed Brainoware—computation is performed by sending and receiving information from the brain organoid using a high-density multielectrode array. By applying spatiotemporal electrical stimulation, nonlinear dynamics and fading memory properties are achieved, as well as unsupervised learning from training data by reshaping the organoid functional connectivity. We illustrate the practical potential of this technique by using it for speech recognition and nonlinear equation prediction in a reservoir computing framework.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations in artificial intelligence technologies. However, brain-inspired silicon chips are still limited in their ability to fully mimic brain function as most examples are built on digital electronic principles. Here we report an artificial intelligence hardware approach that uses adaptive reservoir computation of biological neural networks in a brain organoid. In this approach—which is termed Brainoware—computation is performed by sending and receiving information from the brain organoid using a high-density multielectrode array. By applying spatiotemporal electrical stimulation, nonlinear dynamics and fading memory properties are achieved, as well as unsupervised learning from training data by reshaping the organoid functional connectivity. We illustrate the practical potential of this technique by using it for speech recognition and nonlinear equation prediction in a reservoir computing framework.
@article{Ryu2023,
title = {Stress-free cell aggregation by using the CEPT cocktail enhances embryoid body and organoid fitness},
author = {Seungmi Ryu and Claire Weber and Pei-Hsuan Chu and Ben Ernest and Vukasin M Jovanovic and Tao Deng and Jaroslav Slamecka and Hyenjong Hong and Yogita Jethmalani and Hannah M Baskir and Jason Inman and John Braisted and Marissa B Hirst and Anton Simeonov and Ty C Voss and Carlos A Tristan and Ilyas Singeç},
url = {https://dx.doi.org/10.1088/1758-5090/ad0d13},
doi = {10.1088/1758-5090/ad0d13},
year = {2023},
date = {2023-12-11},
journal = {Biofabrication},
abstract = {Embryoid bodies (EBs) and self-organizing organoids derived from human pluripotent stem cells (hPSCs) recapitulate tissue development in a dish and hold great promise for disease modeling and drug development. However, current protocols are hampered by cellular stress and apoptosis during cell aggregation, resulting in variability and impaired cell differentiation. Here, we demonstrate that EBs and various organoid models (e.g., brain, gut, kidney) can be optimized by using the small molecule cocktail named CEPT (chroman 1, emricasan, polyamines, trans-ISRIB), a polypharmacological approach that ensures cytoprotection and cell survival. Application of CEPT for just 24 h during cell aggregation has long-lasting consequences affecting morphogenesis, gene expression, cellular differentiation, and organoid function. Various qualification methods confirmed that CEPT treatment enhanced experimental reproducibility and consistently improved EB and organoid fitness as compared to the widely used ROCK inhibitor Y-27632. Collectively, we discovered that stress-free cell aggregation and superior cell survival in the presence of CEPT are critical quality control determinants that establish a robust foundation for bioengineering complex tissue and organ models.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Embryoid bodies (EBs) and self-organizing organoids derived from human pluripotent stem cells (hPSCs) recapitulate tissue development in a dish and hold great promise for disease modeling and drug development. However, current protocols are hampered by cellular stress and apoptosis during cell aggregation, resulting in variability and impaired cell differentiation. Here, we demonstrate that EBs and various organoid models (e.g., brain, gut, kidney) can be optimized by using the small molecule cocktail named CEPT (chroman 1, emricasan, polyamines, trans-ISRIB), a polypharmacological approach that ensures cytoprotection and cell survival. Application of CEPT for just 24 h during cell aggregation has long-lasting consequences affecting morphogenesis, gene expression, cellular differentiation, and organoid function. Various qualification methods confirmed that CEPT treatment enhanced experimental reproducibility and consistently improved EB and organoid fitness as compared to the widely used ROCK inhibitor Y-27632. Collectively, we discovered that stress-free cell aggregation and superior cell survival in the presence of CEPT are critical quality control determinants that establish a robust foundation for bioengineering complex tissue and organ models.
@article{Elliott2023,
title = {Internet-Connected Cortical Organoids for Project-Based Stem Cell and Neuroscience Education},
author = {Matthew A. T. Elliott and Hunter E. Schweiger and Ash Robbins and Samira Vera-Choqqueccota and Drew Ehrlich and Sebastian Hernandez and Kateryna Voitiuk and Jinghui Geng and Jess L. Sevetson and Cordero Core and Yohei M. Rosen and Mircea Teodorescu and Nico O. Wagner and David Haussler and Mohammed A. Mostajo-Radji},
url = {https://www.eneuro.org/lookup/doi/10.1523/ENEURO.0308-23.2023},
doi = {10.1523/ENEURO.0308-23.2023},
year = {2023},
date = {2023-11-28},
journal = {eNeuro},
abstract = {The introduction of Internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell (PSC)-derived cortical organoids in two different settings: using microscopy to monitor organoid growth in an introductory tissue culture course and using high-density (HD) multielectrode arrays (MEAs) to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The introduction of Internet-connected technologies to the classroom has the potential to revolutionize STEM education by allowing students to perform experiments in complex models that are unattainable in traditional teaching laboratories. By connecting laboratory equipment to the cloud, we introduce students to experimentation in pluripotent stem cell (PSC)-derived cortical organoids in two different settings: using microscopy to monitor organoid growth in an introductory tissue culture course and using high-density (HD) multielectrode arrays (MEAs) to perform neuronal stimulation and recording in an advanced neuroscience mathematics course. We demonstrate that this approach develops interest in stem cell and neuroscience in the students of both courses. All together, we propose cloud technologies as an effective and scalable approach for complex project-based university training.
Sawada, Tomoyo; Barbosa, André R; Araujo, Bruno; McCord, Alejandra E; D’Ignazio, Laura; Benjamin, Kynon J M; Sheehan, Bonna; Zabolocki, Michael; Feltrin, Arthur; Arora, Ria; Brandtjen, Anna C; Kleinman, Joel E; Hyde, Thomas M; Bardy, Cedric; Weinberger, Daniel R; Paquola, Apuã C M; Erwin, Jennifer A
@article{Tomoyo2023,
title = {Recapitulation of Perturbed Striatal Gene Expression Dynamics of Donor’s Brains With Ventral Forebrain Organoids Derived From the Same Individuals With Schizophrenia},
author = {Tomoyo Sawada and André R. Barbosa and Bruno Araujo and Alejandra E. McCord and Laura D’Ignazio and Kynon J.M. Benjamin and Bonna Sheehan and Michael Zabolocki and Arthur Feltrin and Ria Arora and Anna C. Brandtjen and Joel E. Kleinman and Thomas M. Hyde and Cedric Bardy and Daniel R. Weinberger and Apuã C.M. Paquola and Jennifer A. Erwin},
url = {https://ajp.psychiatryonline.org/doi/10.1176/appi.ajp.20220723},
doi = {10.1176/appi.ajp.20220723},
issn = {0002-953X},
year = {2023},
date = {2023-11-02},
journal = {American Journal of Psychiatry},
abstract = {Objective:
Schizophrenia is a brain disorder that originates during neurodevelopment and has complex genetic and environmental etiologies. Despite decades of clinical evidence of altered striatal function in affected patients, studies examining its cellular and molecular mechanisms in humans are limited. To explore neurodevelopmental alterations in the striatum associated with schizophrenia, the authors established a method for the differentiation of induced pluripotent stem cells (iPSCs) into ventral forebrain organoids (VFOs).
Methods:
VFOs were generated from postmortem dural fibroblast–derived iPSCs of four individuals with schizophrenia and four neurotypical control individuals for whom postmortem caudate genotypes and transcriptomic data were profiled in the BrainSeq neurogenomics consortium. Individuals were selected such that the two groups had nonoverlapping schizophrenia polygenic risk scores (PRSs).
Results:
Single-cell RNA sequencing analyses of VFOs revealed differences in developmental trajectory between schizophrenia and control individuals in which inhibitory neuronal cells from the patients exhibited accelerated maturation. Furthermore, upregulated genes in inhibitory neurons in schizophrenia VFOs showed a significant overlap with upregulated genes in postmortem caudate tissue of individuals with schizophrenia compared with control individuals, including the donors of the iPSC cohort.
Conclusions:
The findings suggest that striatal neurons derived from high-PRS individuals with schizophrenia carry abnormalities that originated during early brain development and that the VFO model can recapitulate disease-relevant cell type–specific neurodevelopmental phenotypes in a dish.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Schizophrenia is a brain disorder that originates during neurodevelopment and has complex genetic and environmental etiologies. Despite decades of clinical evidence of altered striatal function in affected patients, studies examining its cellular and molecular mechanisms in humans are limited. To explore neurodevelopmental alterations in the striatum associated with schizophrenia, the authors established a method for the differentiation of induced pluripotent stem cells (iPSCs) into ventral forebrain organoids (VFOs).
Methods:
VFOs were generated from postmortem dural fibroblast–derived iPSCs of four individuals with schizophrenia and four neurotypical control individuals for whom postmortem caudate genotypes and transcriptomic data were profiled in the BrainSeq neurogenomics consortium. Individuals were selected such that the two groups had nonoverlapping schizophrenia polygenic risk scores (PRSs).
Results:
Single-cell RNA sequencing analyses of VFOs revealed differences in developmental trajectory between schizophrenia and control individuals in which inhibitory neuronal cells from the patients exhibited accelerated maturation. Furthermore, upregulated genes in inhibitory neurons in schizophrenia VFOs showed a significant overlap with upregulated genes in postmortem caudate tissue of individuals with schizophrenia compared with control individuals, including the donors of the iPSC cohort.
Conclusions:
The findings suggest that striatal neurons derived from high-PRS individuals with schizophrenia carry abnormalities that originated during early brain development and that the VFO model can recapitulate disease-relevant cell type–specific neurodevelopmental phenotypes in a dish.
@article{Lv2023,
title = {Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review},
author = {hiya Lv and Enhui He and Jinping Luo and Yaoyao Liu and Wei Liang and Shihong Xu and Kui Zhang and Yan Yang and Mixia Wang and Yilin Song and Yirong Wu and Xinxia Cai},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/advs.202301828},
doi = {10.1002/advs.202301828},
year = {2023},
date = {2023-10-23},
journal = {Advanced Science},
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.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
@article{Levi2023,
title = {BiœmuS: A new tool for neurological disorders studies through real-time emulation and hybridization using biomimetic Spiking Neural Network},
author = {Timothee Levi and Romain Beaubois and Jérémy Cheslet and Tomoya Duenki and Farad Khoyratee and Pascal Branchereau and Yoshiho Ikeuchi},
url = {https://www.researchsquare.com},
doi = {10.21203/rs.3.rs-3191285/v1},
year = {2023},
date = {2023-09-15},
journal = {Research Square},
abstract = {Characterization and modeling of biological neural networks is a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain and the different pathologies that can affect it. Recent researches in bioelectronics and neuromorphic engineering lead to the design of the new generation of neuroprosthesis. Here we show a novel real-time, biomimetic and energy-efficient neural network for bio-hybrid experiments and parallel emulation. This novel system is used to investigate and reproduce neural network dynamics. The setup is running on a digital platform using a System on Chip (SoC) featuring both Programmable Logic (PL) and processors in a Processing System (PS) part. The FPGA part is computing the biomimetic and real-time electrical activities of Hodgkin-Huxley neural network while the processors handle monitoring and communication. New methods of resource and power optimization has been applied to the FPGA to allow detailed neuron modeling with synapses showing short term plasticity. The system is validated by comparison with biological data and model. We also demonstrate the feasibility of bio-hybrid experiments with different bio-physical interface and different biological cells. The complete setup achieves communication with a fully flexible real-time device thus constituting a step towards neuromorphic-based neuroprosthesis for bioelectrical therapeutics.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Characterization and modeling of biological neural networks is a field opening to major advances in our understanding of the mechanisms governing the functioning of the brain and the different pathologies that can affect it. Recent researches in bioelectronics and neuromorphic engineering lead to the design of the new generation of neuroprosthesis. Here we show a novel real-time, biomimetic and energy-efficient neural network for bio-hybrid experiments and parallel emulation. This novel system is used to investigate and reproduce neural network dynamics. The setup is running on a digital platform using a System on Chip (SoC) featuring both Programmable Logic (PL) and processors in a Processing System (PS) part. The FPGA part is computing the biomimetic and real-time electrical activities of Hodgkin-Huxley neural network while the processors handle monitoring and communication. New methods of resource and power optimization has been applied to the FPGA to allow detailed neuron modeling with synapses showing short term plasticity. The system is validated by comparison with biological data and model. We also demonstrate the feasibility of bio-hybrid experiments with different bio-physical interface and different biological cells. The complete setup achieves communication with a fully flexible real-time device thus constituting a step towards neuromorphic-based neuroprosthesis for bioelectrical therapeutics.
@article{Cerina2023,
title = {The potential of in vitro neuronal networks cultured on Micro Electrode Arrays for biomedical research},
author = {Marta Cerina and Maria Carla Piastra and Monica Frega},
url = {https://iopscience.iop.org/article/10.1088/2516-1091/acce12},
doi = {10.1088/2516-1091/acce12},
year = {2023},
date = {2023-04-18},
journal = {Progress in Biomedical Engineering},
abstract = {In vitro neuronal models have become an important tool to study healthy and diseased neuronal circuits. The growing interest of neuroscientists to explore the dynamics of neuronal systems and the increasing need to observe, measure and manipulate not only single neurons but populations of cells pushed for technological advancement. In this sense, Micro-Electrode Arrays (MEAs) emerged as a promising technique, made of cell culture dishes with embedded micro-electrodes allowing non-invasive and relatively simple measurement of the activity of neuronal cultures at the network level. In the past decade, MEAs popularity has rapidly grown. MEA devices have been extensively used to measure the activity of neuronal cultures mainly derived from rodents. Rodent neuronal cultures on MEAs have been employed to investigate physiological mechanisms, study the effect of chemicals in neurotoxicity screenings, and model the electrophysiological phenotype of neuronal networks in different pathological conditions. With the advancements in human induced pluripotent stem cells (hiPSCs) technology, the differentiation of human neurons from the cells of adult donors became possible. hiPSCsderived neuronal networks on MEAs have been employed to develop patient-specific in vitro platforms to characterize the pathophysiological phenotype and to test drugs, paving the way towards personalized medicine. In this review, we first describe MEA technology and the information that can be obtained from MEA recordings. Then, we give an overview of studies in which MEAs have been used in combination with different neuronal systems (i.e., rodent 2D and 3D neuronal cultures, organotypic brain slices, hiPSCs-derived 2D and 3D neuronal cultures, and brain organoids) for biomedical research, including physiology studies, neurotoxicity screenings, disease modeling, and drug testing. We end by discussing potential, challenges and future perspectives of MEA technology, and providing some guidance for the choice of the neuronal model and MEA device, experimental design, data analysis and reporting for scientific publications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In vitro neuronal models have become an important tool to study healthy and diseased neuronal circuits. The growing interest of neuroscientists to explore the dynamics of neuronal systems and the increasing need to observe, measure and manipulate not only single neurons but populations of cells pushed for technological advancement. In this sense, Micro-Electrode Arrays (MEAs) emerged as a promising technique, made of cell culture dishes with embedded micro-electrodes allowing non-invasive and relatively simple measurement of the activity of neuronal cultures at the network level. In the past decade, MEAs popularity has rapidly grown. MEA devices have been extensively used to measure the activity of neuronal cultures mainly derived from rodents. Rodent neuronal cultures on MEAs have been employed to investigate physiological mechanisms, study the effect of chemicals in neurotoxicity screenings, and model the electrophysiological phenotype of neuronal networks in different pathological conditions. With the advancements in human induced pluripotent stem cells (hiPSCs) technology, the differentiation of human neurons from the cells of adult donors became possible. hiPSCsderived neuronal networks on MEAs have been employed to develop patient-specific in vitro platforms to characterize the pathophysiological phenotype and to test drugs, paving the way towards personalized medicine. In this review, we first describe MEA technology and the information that can be obtained from MEA recordings. Then, we give an overview of studies in which MEAs have been used in combination with different neuronal systems (i.e., rodent 2D and 3D neuronal cultures, organotypic brain slices, hiPSCs-derived 2D and 3D neuronal cultures, and brain organoids) for biomedical research, including physiology studies, neurotoxicity screenings, disease modeling, and drug testing. We end by discussing potential, challenges and future perspectives of MEA technology, and providing some guidance for the choice of the neuronal model and MEA device, experimental design, data analysis and reporting for scientific publications.
@article{Xu2023,
title = {Generation of functional posterior spinal motor neurons from hPSCs-derived human spinal cord neural progenitor cells},
author = {He Jax Xu and Yao Yao and Fenyong Yao and Jiehui Chen and Meishi Li and Xianfa Yang and Sheng Li and Fangru Lu and Ping Hu and Shuijin He and Guangdun Peng and Naihe Jing},
url = {https://cellregeneration.springeropen.com/articles/10.1186/s13619-023-00159-6},
doi = {10.1186/s13619-023-00159-6},
year = {2023},
date = {2023-03-23},
journal = {Cell Regeneration},
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.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
@article{Cai2023,
title = {Brain Organoid Computing for Artificial Intelligence},
author = {Hongwei Cai and Zheng Ao and Chunhui Tian and Zhuhao Wu and Hongcheng Liu and Jason Tchieu and Mingxia Gu and Ken Mackie and and Feng Guo},
url = {https://www.biorxiv.org/content/10.1101/2023.02.28.530502v1},
doi = {10.1101/2023.02.28.530502},
year = {2023},
date = {2023-03-01},
journal = {bioRxiv},
abstract = {Brain-inspired hardware emulates the structure and working principles of a biological brain and may address the hardware bottleneck for fast-growing artificial intelligence (AI). Current brain-inspired silicon chips are promising but still limit their power to fully mimic brain function for AI computing. Here, we develop Brainoware, living AI hardware that harnesses the computation power of 3D biological neural networks in a brain organoid. Brain-like 3D in vitro cultures compute by receiving and sending information via a multielectrode array. Applying spatiotemporal electrical stimulation, this approach not only exhibits nonlinear dynamics and fading memory properties but also learns from training data. Further experiments demonstrate real-world applications in solving non-linear equations. This approach may provide new insights into AI hardware.
},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Brain-inspired hardware emulates the structure and working principles of a biological brain and may address the hardware bottleneck for fast-growing artificial intelligence (AI). Current brain-inspired silicon chips are promising but still limit their power to fully mimic brain function for AI computing. Here, we develop Brainoware, living AI hardware that harnesses the computation power of 3D biological neural networks in a brain organoid. Brain-like 3D in vitro cultures compute by receiving and sending information via a multielectrode array. Applying spatiotemporal electrical stimulation, this approach not only exhibits nonlinear dynamics and fading memory properties but also learns from training data. Further experiments demonstrate real-world applications in solving non-linear equations. This approach may provide new insights into AI hardware.
@article{Magliaro2023,
title = {To brain or not to brain organoids},
author = {Chiara Magliaro and Arti Ahluwalia},
url = {https://www.frontiersin.org/journals/science/articles/10.3389/fsci.2023.1148873},
doi = {10.3389/fsci.2023.1148873},
year = {2023},
date = {2023-02-28},
journal = {Frontiers in Science},
abstract = {- Brain organoids are a unique template for engineering a new era of bio-inspired supercomputer technology.
- The power requirements for exploiting brain organoids may be higher than those of the most powerful computers.
- Further research is needed to accelerate sustainable solutions in brain organoid-leveraged supercomputing technologies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
- Brain organoids are a unique template for engineering a new era of bio-inspired supercomputer technology.
- The power requirements for exploiting brain organoids may be higher than those of the most powerful computers.
- Further research is needed to accelerate sustainable solutions in brain organoid-leveraged supercomputing technologies.
@article{EunheeKim2023,
title = {A Neurospheroid-Based Microrobot for Targeted Neural Connections in a Hippocampal Slice},
author = {Eunhee Kim and Sungwoong Jeon and Yoon-Sil Yang and Chaewon Jin and Jin-young Kim and Yong- Seok Oh and Jong-Cheol Rah and and Hongsoo Choi},
url = {https://onlinelibrary.wiley.com/doi/10.1002/adma.202208747?af=R},
doi = {https://doi.org/10.1002/adma.202208747},
year = {2023},
date = {2023-01-14},
journal = {Advanced Materials},
abstract = {Functional restoration by the re-establishment of cellular or neural connections remains a major challenge in targeted cell therapy and regenerative medicine. Recent advances in magnetically powered microrobots have shown potential for use in controlled and targeted cell therapy. In this study, a magnetic neurospheroid (Mag-Neurobot) that could form both structural and functional connections with an organotypic hippocampal slice (OHS) was assessed using an ex vivo model as a bridge toward in vivo application. The Mag-Neurobot consists of hippocampal neurons and superparamagnetic nanoparticles (SPIONs); it is precisely and skillfully manipulated by an external magnetic field. Furthermore, the results of patch-clamp recordings of hippocampal neurons indicated that neither the neuronal excitabilities nor the synaptic functions of SPION-loaded cells were significantly affected. Analysis of neural activity propagation using high-density multi-electrode arrays showed that the delivered Mag-Neurobot was functionally connected with the OHS. The applications of this study include functional verification for targeted cell delivery through the characterization of novel synaptic connections and the functionalities of transported and transplanted cells. The success of the Mag-Neurobot opens up new avenues of research and application; it offers a test platform for functional neural connections and neural regenerative processes through cell transplantation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Functional restoration by the re-establishment of cellular or neural connections remains a major challenge in targeted cell therapy and regenerative medicine. Recent advances in magnetically powered microrobots have shown potential for use in controlled and targeted cell therapy. In this study, a magnetic neurospheroid (Mag-Neurobot) that could form both structural and functional connections with an organotypic hippocampal slice (OHS) was assessed using an ex vivo model as a bridge toward in vivo application. The Mag-Neurobot consists of hippocampal neurons and superparamagnetic nanoparticles (SPIONs); it is precisely and skillfully manipulated by an external magnetic field. Furthermore, the results of patch-clamp recordings of hippocampal neurons indicated that neither the neuronal excitabilities nor the synaptic functions of SPION-loaded cells were significantly affected. Analysis of neural activity propagation using high-density multi-electrode arrays showed that the delivered Mag-Neurobot was functionally connected with the OHS. The applications of this study include functional verification for targeted cell delivery through the characterization of novel synaptic connections and the functionalities of transported and transplanted cells. The success of the Mag-Neurobot opens up new avenues of research and application; it offers a test platform for functional neural connections and neural regenerative processes through cell transplantation.
@article{Whye2023,
title = {A Robust Pipeline for the Multi‐Stage Accelerated Differentiation of Functional 3D Cortical Organoids from Human Pluripotent Stem Cells},
author = {Dosh Whye and Delaney Wood and Wardiya Afshar Saber and Erika M. Norabuena and Nina R. Makhortova and Mustafa Sahin and Elizabeth D. Buttermore},
url = {https://currentprotocols.onlinelibrary.wiley.com/doi/10.1002/cpz1.641},
doi = {doi.org/10.1002/cpz1.641},
year = {2023},
date = {2023-01-12},
journal = {Current Protocols},
abstract = {Disordered cellular development, abnormal neuroanatomical formations, and dysfunction of neuronal circuitry are among the pathological manifestations of cortical regions in the brain that are often implicated in complex neurodevelopmental disorders. With the advancement of stem cell methodologies such as cerebral organoid generation, it is possible to study these processes in vitro using 3D cellular platforms that mirror key developmental stages occurring throughout embryonic neurogenesis. Patterning-based stem cell models of directed neuronal development offer one approach to accomplish this, but these protocols often require protracted periods of cell culture to generate diverse cell types and current methods are plagued by a lack of specificity, reproducibility, and temporal control over cell derivation. Although ectopic expression of transcription factors offers another avenue to rapidly generate neurons, this process of direct lineage conversion bypasses critical junctures of neurodevelopment during which disease-relevant manifestations may occur. Here, we present a directed differentiation approach for generating human pluripotent stem cell (hPSC)-derived cortical organoids with accelerated lineage specification to generate functionally mature cortical neurons in a shorter timeline than previously established protocols. This novel protocol provides precise guidance for the specification of neuronal cell type identity as well as temporal control over the pace at which cortical lineage trajectories are established. Furthermore, we present assays that can be used as tools to interrogate stage-specific developmental signaling mechanisms. By recapitulating major components of embryonic neurogenesis, this protocol allows for improved in vitro modeling of cortical development while providing a platform that can be utilized to uncover disease-specific mechanisms of disordered development at various stages across the differentiation timeline.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Disordered cellular development, abnormal neuroanatomical formations, and dysfunction of neuronal circuitry are among the pathological manifestations of cortical regions in the brain that are often implicated in complex neurodevelopmental disorders. With the advancement of stem cell methodologies such as cerebral organoid generation, it is possible to study these processes in vitro using 3D cellular platforms that mirror key developmental stages occurring throughout embryonic neurogenesis. Patterning-based stem cell models of directed neuronal development offer one approach to accomplish this, but these protocols often require protracted periods of cell culture to generate diverse cell types and current methods are plagued by a lack of specificity, reproducibility, and temporal control over cell derivation. Although ectopic expression of transcription factors offers another avenue to rapidly generate neurons, this process of direct lineage conversion bypasses critical junctures of neurodevelopment during which disease-relevant manifestations may occur. Here, we present a directed differentiation approach for generating human pluripotent stem cell (hPSC)-derived cortical organoids with accelerated lineage specification to generate functionally mature cortical neurons in a shorter timeline than previously established protocols. This novel protocol provides precise guidance for the specification of neuronal cell type identity as well as temporal control over the pace at which cortical lineage trajectories are established. Furthermore, we present assays that can be used as tools to interrogate stage-specific developmental signaling mechanisms. By recapitulating major components of embryonic neurogenesis, this protocol allows for improved in vitro modeling of cortical development while providing a platform that can be utilized to uncover disease-specific mechanisms of disordered development at various stages across the differentiation timeline.
@article{Han2022,
title = {A functional neuron maturation device provides convenient application on microelectrode array for neural network measurement},
author = {Xiaobo Han and Naoki Matsuda and Yuto Ishibashi and Aoi Odawara and Sayuri Takahashi and Norie Tooi and Koshi Kinoshita and Ikuro Suzuki },
url = {https://biomaterialsres.biomedcentral.com/articles/10.1186/s40824-022-00324-z},
doi = {https://doi.org/10.1186/s40824-022-00324-z},
year = {2022},
date = {2022-12-20},
journal = {Biomaterials Research},
abstract = {Background
Microelectrode array (MEA) systems are valuable for in vitro assessment of neurotoxicity and drug efficiency. However, several difficulties such as protracted functional maturation and high experimental costs hinder the use of MEA analysis requiring human induced pluripotent stem cells (hiPSCs). Neural network functional parameters are also needed for in vitro to in vivo extrapolation.
Methods
In the present study, we produced a cost effective nanofiber culture platform, the SCAD device, for long-term culture of hiPSC-derived neurons and primary peripheral neurons. The notable advantage of SCAD device is convenient application on multiple MEA systems for neuron functional analysis.
Results
We showed that the SCAD device could promote functional maturation of cultured hiPSC-derived neurons, and neurons responded appropriately to convulsant agents. Furthermore, we successfully analyzed parameters for in vitro to in vivo extrapolation, i.e., low-frequency components and synaptic propagation velocity of the signal, potentially reflecting neural network functions from neurons cultured on SCAD device. Finally, we measured the axonal conduction velocity of peripheral neurons. Conclusions: Neurons cultured on SCAD devices might constitute a reliable in vitro platform to investigate neuron functions, drug efficacy and toxicity, and neuropathological mechanisms by MEA.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background
Microelectrode array (MEA) systems are valuable for in vitro assessment of neurotoxicity and drug efficiency. However, several difficulties such as protracted functional maturation and high experimental costs hinder the use of MEA analysis requiring human induced pluripotent stem cells (hiPSCs). Neural network functional parameters are also needed for in vitro to in vivo extrapolation.
Methods
In the present study, we produced a cost effective nanofiber culture platform, the SCAD device, for long-term culture of hiPSC-derived neurons and primary peripheral neurons. The notable advantage of SCAD device is convenient application on multiple MEA systems for neuron functional analysis.
Results
We showed that the SCAD device could promote functional maturation of cultured hiPSC-derived neurons, and neurons responded appropriately to convulsant agents. Furthermore, we successfully analyzed parameters for in vitro to in vivo extrapolation, i.e., low-frequency components and synaptic propagation velocity of the signal, potentially reflecting neural network functions from neurons cultured on SCAD device. Finally, we measured the axonal conduction velocity of peripheral neurons. Conclusions: Neurons cultured on SCAD devices might constitute a reliable in vitro platform to investigate neuron functions, drug efficacy and toxicity, and neuropathological mechanisms by MEA.
@article{VanLent2022,
title = {Downregulation of PMP22 ameliorates myelin defects in iPSC-derived human organoid cultures of CMT1A},
author = {Jonas Van Lent and Leen Vendredy and Elias Adriaenssens and Tatiana Da Silva Authier and Bob Asselbergh and Marcus Kaji and Sarah Weckhuysen and Ludo Van Den Bosch and Jonathan Baets and Vincent Timmerman},
url = {https://academic.oup.com/brain/advance-article/doi/10.1093/brain/awac475/6895197?login=false},
doi = {https://doi.org/10.1093/brain/awac475},
year = {2022},
date = {2022-12-12},
journal = {Brain},
abstract = {Charcot-Marie-Tooth (CMT) disease is the most common inherited disorder of the peripheral nervous system. CMT1A accounts for 40-50% of all cases and is caused by a duplication of the PMP22 gene on chromosome 17, leading to dysmyelination in the peripheral nervous system. Patient-derived models to study such myelination defects are lacking as the in vitro generation of human myelinating Schwann cells has proven to be particularly challenging. Here, we present an iPSC-derived organoid culture, containing various cell types of the peripheral nervous system, including myelinating human Schwann cells, which mimics the human peripheral nervous system. Single-cell analysis confirmed the peripheral nervous system-like cellular composition and provides insight into the developmental trajectory. We used this organoid-model to study disease signatures of CMT1A, revealing early ultrastructural myelin alterations, including increased myelin periodic line distance and hypermyelination of small axons. Furthermore, we observed the presence of onion bulb-like formations in a later developmental stage. These hallmarks were not present in the for CMT1A-corrected isogenic line or in a CMT2A iPSC line, supporting the notion that these alterations are specific to CMT1A. Downregulation of PMP22 expression using short-hairpin RNAs or a combinatorial drug consisting of baclofen, naltrexone hydrochloride and D-sorbitol, was able to ameliorate the myelin defects in CMT1A-organoids. In summary, this self-organizing organoid model is able to capture biologically meaningful features of the disease and capture the physiological complexity, forms an excellent model to study demyelinating diseases, and supports the therapeutic approach of reducing PMP22 expression.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Charcot-Marie-Tooth (CMT) disease is the most common inherited disorder of the peripheral nervous system. CMT1A accounts for 40-50% of all cases and is caused by a duplication of the PMP22 gene on chromosome 17, leading to dysmyelination in the peripheral nervous system. Patient-derived models to study such myelination defects are lacking as the in vitro generation of human myelinating Schwann cells has proven to be particularly challenging. Here, we present an iPSC-derived organoid culture, containing various cell types of the peripheral nervous system, including myelinating human Schwann cells, which mimics the human peripheral nervous system. Single-cell analysis confirmed the peripheral nervous system-like cellular composition and provides insight into the developmental trajectory. We used this organoid-model to study disease signatures of CMT1A, revealing early ultrastructural myelin alterations, including increased myelin periodic line distance and hypermyelination of small axons. Furthermore, we observed the presence of onion bulb-like formations in a later developmental stage. These hallmarks were not present in the for CMT1A-corrected isogenic line or in a CMT2A iPSC line, supporting the notion that these alterations are specific to CMT1A. Downregulation of PMP22 expression using short-hairpin RNAs or a combinatorial drug consisting of baclofen, naltrexone hydrochloride and D-sorbitol, was able to ameliorate the myelin defects in CMT1A-organoids. In summary, this self-organizing organoid model is able to capture biologically meaningful features of the disease and capture the physiological complexity, forms an excellent model to study demyelinating diseases, and supports the therapeutic approach of reducing PMP22 expression.
@article{Tran2022,
title = {Generation of Human Striatal-Midbrain Assembloids From Human Pluripotent Stem Cells to Model Alpha-Synuclein Propagation},
author = {Hoang-Dai Tran and Min-Kyoung Shin and Charlotte Denman and Run-Run Han and Bernd Kuhn and Gordon Arbuthnott and Junghyun Jo},
url = {https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4288935},
doi = {http://dx.doi.org/10.2139/ssrn.4288935},
year = {2022},
date = {2022-12-05},
journal = {Sneak Peek - Cell Press},
abstract = {Animal models of the pathology of Parkinson’s disease (PD) have provided most of the treatments to date, but the disease is restricted to human patients. In vitro models using human pluripotent stem cell-derived neural organoids have provided improved access to study PD etiology. Here, we generated human striatal and midbrain organoids and assembled both regionalized neural organoids to form human striatal-midbrain assembloids (hSMAs), mimicking a part of basal ganglia. Both the nigrostriatal and striatonigral pathways are present and electrophysiologically active in the hSMAs. hSMA development in the presence of increased alpha-synuclein (α-syn) from SNCA overexpression, induced nigrostriatal system damage, which is typical of the disease. Using the α-syn-mKO2 reporter and bimolecular fluorescence complementation system, we demonstrated that fluorescent α-syn is transported from the striatal area tothe dopaminergic (DA) neurons of the midbrain area. Furthermore, insoluble α-syn aggregated over time in DA neurons similar to Lewy bodies in human patients. Such assembloids are a compelling new platform to develop novel PD therapeutic strategies.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Animal models of the pathology of Parkinson’s disease (PD) have provided most of the treatments to date, but the disease is restricted to human patients. In vitro models using human pluripotent stem cell-derived neural organoids have provided improved access to study PD etiology. Here, we generated human striatal and midbrain organoids and assembled both regionalized neural organoids to form human striatal-midbrain assembloids (hSMAs), mimicking a part of basal ganglia. Both the nigrostriatal and striatonigral pathways are present and electrophysiologically active in the hSMAs. hSMA development in the presence of increased alpha-synuclein (α-syn) from SNCA overexpression, induced nigrostriatal system damage, which is typical of the disease. Using the α-syn-mKO2 reporter and bimolecular fluorescence complementation system, we demonstrated that fluorescent α-syn is transported from the striatal area tothe dopaminergic (DA) neurons of the midbrain area. Furthermore, insoluble α-syn aggregated over time in DA neurons similar to Lewy bodies in human patients. Such assembloids are a compelling new platform to develop novel PD therapeutic strategies.
@article{Sharf2022,
title = {Functional neuronal circuitry and oscillatory dynamics in human brain organoids},
author = {Sharf, Tal; Molen, Tjitse; Glasauer, Stella; Guzman, Elmer; Buccino, Alessio; Luna, Gabriel; Cheng, Zhuowei; Audouard, Morgane; Ranasinghe, Kamalini; Kudo, Kiwamu; Nagarajan, Srikantan; Tovar, Kenneth; Petzold, Linda; Hierlemann, Andreas; Hansma, Paul; and Kosik, Kenneth;
},
doi = {https://doi.org/10.1038/s41467-022-32115-4},
year = {2022},
date = {2022-07-29},
journal = {Nature Communications},
abstract = {Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiology of neuronal circuits within organoids remains under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we captured spontaneous extracellular activity from brain organoids derived from human induced pluripotent stem cells. We inferred functional connectivity from spike timing, revealing a large number of weak connections within a skeleton of significantly fewer strong connections. A benzodiazepine increased the uniformity of firing patterns and decreased the relative fraction of weakly connected edges. Our analysis of the local field potential demonstrate that brain organoids contain neuronal assemblies of sufficient size and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug action, and the effects of external stimuli upon neuronal networks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiology of neuronal circuits within organoids remains under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we captured spontaneous extracellular activity from brain organoids derived from human induced pluripotent stem cells. We inferred functional connectivity from spike timing, revealing a large number of weak connections within a skeleton of significantly fewer strong connections. A benzodiazepine increased the uniformity of firing patterns and decreased the relative fraction of weakly connected edges. Our analysis of the local field potential demonstrate that brain organoids contain neuronal assemblies of sufficient size and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug action, and the effects of external stimuli upon neuronal networks.
@article{Schroter2022,
title = {Functional imaging of brain organoids using high-density microelectrode arrays},
author = {Schröter, Manuel; Wang, Congwei; Terrigno, Marco; Hornauer, Philipp; Huang, Ziqiang; Jagasia, Ravi; Hierlemann, Andreas},
url = {https://link.springer.com/article/10.1557/s43577-022-00282-w},
year = {2022},
date = {2022-06-30},
journal = {MRS Bulletin},
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.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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.
@article{Paulsen2022,
title = {Autism genes converge on asynchronous development of shared neuron classes},
author = {Bruna Paulsen and Silvia Velasco and Amanda J. Kedaigle and Martina Pigoni and Giorgia Quadrato and Anthony J. Deo and Xian Adiconis and Ana Uzquiano and Rafaela Sartore and Sung Min Yang and Sean K. Simmons and Panagiotis Symvoulidis and Kwanho Kim and Kalliopi Tsafou and Archana Podury and Catherine Abbate and Ashley Tucewicz and Samantha N. Smith and Alexandre Albanese and Lindy Barrett and Neville E. Sanjana and Xi Shi and Kwanghun Chung and Kasper Lage and Edward S. Boyden and Aviv Regev andJoshua Z. Levin and Paola Arlotta },
url = {https://www.nature.com/articles/s41586-021-04358-6},
doi = {10.1038/s41586-021-04358-6},
year = {2022},
date = {2022-02-02},
journal = {Nature},
volume = {602},
pages = {268–273},
abstract = {Genetic risk for autism spectrum disorder (ASD) is associated with hundreds of genes spanning a wide range of biological functions1,2,3,4,5,6. The alterations in the human brain resulting from mutations in these genes remain unclear. Furthermore, their phenotypic manifestation varies across individuals7,8. Here we used organoid models of the human cerebral cortex to identify cell-type-specific developmental abnormalities that result from haploinsufficiency in three ASD risk genes—SUV420H1 (also known as KMT5B), ARID1B and CHD8—in multiple cell lines from different donors, using single-cell RNA-sequencing (scRNA-seq) analysis of more than 745,000 cells and proteomic analysis of individual organoids, to identify phenotypic convergence. Each of the three mutations confers asynchronous development of two main cortical neuronal lineages—γ-aminobutyric-acid-releasing (GABAergic) neurons and deep-layer excitatory projection neurons—but acts through largely distinct molecular pathways. Although these phenotypes are consistent across cell lines, their expressivity is influenced by the individual genomic context, in a manner that is dependent on both the risk gene and the developmental defect. Calcium imaging in intact organoids shows that these early-stage developmental changes are followed by abnormal circuit activity. This research uncovers cell-type-specific neurodevelopmental abnormalities that are shared across ASD risk genes and are finely modulated by human genomic context, finding convergence in the neurobiological basis of how different risk genes contribute to ASD pathology.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Genetic risk for autism spectrum disorder (ASD) is associated with hundreds of genes spanning a wide range of biological functions1,2,3,4,5,6. The alterations in the human brain resulting from mutations in these genes remain unclear. Furthermore, their phenotypic manifestation varies across individuals7,8. Here we used organoid models of the human cerebral cortex to identify cell-type-specific developmental abnormalities that result from haploinsufficiency in three ASD risk genes—SUV420H1 (also known as KMT5B), ARID1B and CHD8—in multiple cell lines from different donors, using single-cell RNA-sequencing (scRNA-seq) analysis of more than 745,000 cells and proteomic analysis of individual organoids, to identify phenotypic convergence. Each of the three mutations confers asynchronous development of two main cortical neuronal lineages—γ-aminobutyric-acid-releasing (GABAergic) neurons and deep-layer excitatory projection neurons—but acts through largely distinct molecular pathways. Although these phenotypes are consistent across cell lines, their expressivity is influenced by the individual genomic context, in a manner that is dependent on both the risk gene and the developmental defect. Calcium imaging in intact organoids shows that these early-stage developmental changes are followed by abnormal circuit activity. This research uncovers cell-type-specific neurodevelopmental abnormalities that are shared across ASD risk genes and are finely modulated by human genomic context, finding convergence in the neurobiological basis of how different risk genes contribute to ASD pathology.
@article{Sharf2021b,
title = {Human brain organoid networks},
author = {Tal Sharf and Tjitse van der Molen and Stella M.K. Glasauer and Elmer Guzman and Alessio P. Buccino and Gabriel Luna and Zhouwei Cheng and Morgane Audouard and Kamalini G. Ranasinghe and Kiwamu Kudo and Srikantan S. Nagarajan and Kenneth R. Tovar and Linda R. Petzold and Andreas Hierlemann and Paul K. Hansma and Kenneth S. Kosik},
url = {https://www.biorxiv.org/content/10.1101/2021.01.28.428643v2},
doi = {10.1101/2021.01.28.428643},
year = {2021},
date = {2021-09-23},
journal = {bioRxiv},
abstract = {Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays (26,400 electrodes) and shank electrodes (960 electrodes), we probed broadband and three-dimensional extracellular field recordings generated by spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single-unit activity extracted through spike sorting. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity, which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Treatment of the organoid with a benzodiazepine induced a reproducible signature response that shortened the inter-burst intervals, increased the uniformity of the firing pattern within each burst and decreased the population of weakly connected edges. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays (26,400 electrodes) and shank electrodes (960 electrodes), we probed broadband and three-dimensional extracellular field recordings generated by spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single-unit activity extracted through spike sorting. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity, which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Treatment of the organoid with a benzodiazepine induced a reproducible signature response that shortened the inter-burst intervals, increased the uniformity of the firing pattern within each burst and decreased the population of weakly connected edges. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.
@article{Sharf2021,
title = {Intrinsic network activity in human brain organoids},
author = {Tal Sharf and Tjitse van der Molen and Elmer Guzman and Stella M.K. Glasauer and Gabriel Luna and Zhouwei Cheng and Morgane Audouard and Kamalini G. Ranasinghe and Kiwamu Kudo and Srikantan S. Nagarajan and Kenneth R. Tovar and Linda R. Petzold and Paul K. Hansma and Kenneth S. Kosik},
url = {https://www.biorxiv.org/content/10.1101/2021.01.28.428643v1},
doi = {10.1101/2021.01.28.428643},
year = {2021},
date = {2021-01-28},
journal = {BioRxiv},
abstract = {Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we probed broadband and three-dimensional spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single unit activity. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Increasing the intrinsic inhibitory tone with a benzodiazepine altered the functional network graph of the organoid by suppressing the network skeleton. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. An ensemble of spikes phase-locked to theta frequency oscillations were strongly interconnected as a sub-network within the larger network in which they were embedded. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiological behavior of neuronal circuits within organoids remains relatively under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we probed broadband and three-dimensional spontaneous activity of human brain organoids. These recordings simultaneously captured local field potentials (LFPs) and single unit activity. From spiking activity, we estimated a directed functional connectivity graph of synchronous neural network activity which showed a large number of weak functional connections enmeshed within a network skeleton of significantly fewer strong connections. Increasing the intrinsic inhibitory tone with a benzodiazepine altered the functional network graph of the organoid by suppressing the network skeleton. Simultaneously examining the spontaneous LFPs and their phase alignment to spiking showed that spike bursts were coherent with theta oscillations in the LFPs. An ensemble of spikes phase-locked to theta frequency oscillations were strongly interconnected as a sub-network within the larger network in which they were embedded. Our results demonstrate that human brain organoids have self-organized neuronal assemblies of sufficient size, cellular orientation, and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug mechanisms, and the effects of external stimuli upon neuronal networks.
@article{Cowan2020,
title = {Cell Types of the Human Retina and Its Organoids at Single-Cell Resolution},
author = {Cameron S. Cowan and Magdalena Renner and Martina De Gennaro and Brigitte Gross-Scherf and David Goldblum and Yanyan Hou and Martin Munz and Tiago M. Rodrigues and Jacek Krol and Tamas Szikra and Rachel Cuttat and Annick Waldt and Panagiotis Papasaikas and Roland Diggelmann and Claudia P. Patino-Alvarez and Patricia Galliker and Stefan E. Spirig and Dinko Pavlinic and Nadine Gerber-Hollbach and Sven Schuierer and Aldin Srdanovic and Marton Balogh and Riccardo Panero and Akos Kusnyerik and Arnold Szabo and Michael B. Stadler and Selim Orgül and Simone Picelli and Pascal W. Hasler and Andreas Hierlemann and Hendrik P.N. Scholl and Guglielmo Roma and Florian Nigsch and Botond Roska},
url = {https://www.cell.com/cell/fulltext/S0092-8674(20)31004-7?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867420310047%3Fshowall%3Dtrue},
doi = {10.1016/j.cell.2020.08.013},
year = {2020},
date = {2020-09-17},
journal = {CellPress},
volume = {182},
pages = { 1623–1640},
abstract = {Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable “developed” state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Human organoids recapitulating the cell-type diversity and function of their target organ are valuable for basic and translational research. We developed light-sensitive human retinal organoids with multiple nuclear and synaptic layers and functional synapses. We sequenced the RNA of 285,441 single cells from these organoids at seven developmental time points and from the periphery, fovea, pigment epithelium and choroid of light-responsive adult human retinas, and performed histochemistry. Cell types in organoids matured in vitro to a stable “developed” state at a rate similar to human retina development in vivo. Transcriptomes of organoid cell types converged toward the transcriptomes of adult peripheral retinal cell types. Expression of disease-associated genes was cell-type-specific in adult retina, and cell-type specificity was retained in organoids. We implicate unexpected cell types in diseases such as macular degeneration. This resource identifies cellular targets for studying disease mechanisms in organoids and for targeted repair in human retinas.
@conference{Schroter2018,
title = {Mapping neuronal network dynamics in developing cerebral organoids},
author = {Manuel Schroter and Monika Girr and Julia Alicia Boos and Magdalena Renner and Mahshid Gazorpak and Wei Gong and Julian Bartram and Jan Muller and Andreas Hierlemann},
url = {https://www.frontiersin.org/10.3389/conf.fncel.2018.38.00066/event_abstract},
doi = {10.3389/conf.fncel.2018.38.00066},
year = {2018},
date = {2018-07-04},
address = {Reutlingen, Germany},
organization = {11th International Meeting on Substrate Integrated Microelectrode Arrays (MEA Meeting)},
abstract = {Cerebral organoids represent an attractive, novel model system to study early brain development in vitro (Di Lullo and Kriegstein, 2017). Although recent evidence shows that cerebral organoids do recapitulate fundamental milestones of early brain morphogenesis (Lancaster and Knoblich, 2014), the emergence and functionality of brain-organoid neuronal connectivity has not been studied systematically yet. In this study, we apply high-density micro-electrode arrays (MEAs) to record from developing mouse cerebral organoids and characterize their spontaneous neuronal activity. Results provide first evidence on the potential of MEAs as a platform to study the role of spontaneous neuronal activity during brain organoid development and formation of functional microcircuits. },
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Cerebral organoids represent an attractive, novel model system to study early brain development in vitro (Di Lullo and Kriegstein, 2017). Although recent evidence shows that cerebral organoids do recapitulate fundamental milestones of early brain morphogenesis (Lancaster and Knoblich, 2014), the emergence and functionality of brain-organoid neuronal connectivity has not been studied systematically yet. In this study, we apply high-density micro-electrode arrays (MEAs) to record from developing mouse cerebral organoids and characterize their spontaneous neuronal activity. Results provide first evidence on the potential of MEAs as a platform to study the role of spontaneous neuronal activity during brain organoid development and formation of functional microcircuits.
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