@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 = {3D Culture, HD-MEA, MaxTwo, MEA Metrics, MEA Technology, Organoids, Primary Neuronal Cell Culture},
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{Fenton2024,
title = {Hyperexcitability and translational phenotypes in a preclinical mouse model of SYNGAP1-Related Intellectual Disability},
author = {Timothy A Fenton and Olivia Y Haouchine and Elizabeth L Hallam and Emily M Smith and Kiya C Jackson and Darlene Rahbarian and Cesar Canales and Anna Adhikari and Alexander S Nord and Roy Ben-Shalom and Jill L Silverman},
url = {https://www.researchsquare.com/article/rs-4067746/v1},
doi = {10.21203/rs.3.rs-4067746/v1},
year = {2024},
date = {2024-03-19},
journal = {Research Square},
abstract = {Disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability (SRID). Without functional SynGAP1 protein, individuals are developmentally delayed and have prominent features of intellectual disability, motor impairments, and epilepsy. Over the past two decades, there have been numerous discoveries indicting the critical role of Syngap1. Several rodent models with a loss of Syngap1 have been engineered identifying precise roles in neuronal structure and function, as well as key biochemical pathways key for synapse integrity. Homozygous loss of Syngap1 is lethal. Heterozygous mutations of Syngap1 result in a broad range of behavioral phenotypes. Our in vivo functional data, using the mouse model from the Huganir laboratory, corroborated earlier reported behaviors including robust hyperactivity and deficits in learning and memory in young adults. In extension, we report impairments in slow wave sleep, a critical component of the domain of sleep. We characterized Syngap1+/- mice by using neurophysiology collected with wireless, telemetric electroencephalography (EEG). Syngap1+/- mice also exhibited elevated spiking events and spike trains, in addition to elevated power, most notably in the delta frequency band. For the first time, we illustrated how primary neurons from Syngap1+/- mice function and display increased network firing activity, greater bursts, and shorter inter-burst intervals between peaks by employing high density microelectrode arrays (HD-MEA). Our reported data bridge in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate quantitative, translational biomarkers in vivo and in vitro that can be utilized for the development of and efficacy assessment of targeted treatments for SRID.},
keywords = {Activity Scan Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Network Assay, Primary Neuronal Cell Culture, Spike Sorting},
pubstate = {published},
tppubtype = {article}
}
Disruption of SYNGAP1 directly causes a genetically identifiable neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability (SRID). Without functional SynGAP1 protein, individuals are developmentally delayed and have prominent features of intellectual disability, motor impairments, and epilepsy. Over the past two decades, there have been numerous discoveries indicting the critical role of Syngap1. Several rodent models with a loss of Syngap1 have been engineered identifying precise roles in neuronal structure and function, as well as key biochemical pathways key for synapse integrity. Homozygous loss of Syngap1 is lethal. Heterozygous mutations of Syngap1 result in a broad range of behavioral phenotypes. Our in vivo functional data, using the mouse model from the Huganir laboratory, corroborated earlier reported behaviors including robust hyperactivity and deficits in learning and memory in young adults. In extension, we report impairments in slow wave sleep, a critical component of the domain of sleep. We characterized Syngap1+/- mice by using neurophysiology collected with wireless, telemetric electroencephalography (EEG). Syngap1+/- mice also exhibited elevated spiking events and spike trains, in addition to elevated power, most notably in the delta frequency band. For the first time, we illustrated how primary neurons from Syngap1+/- mice function and display increased network firing activity, greater bursts, and shorter inter-burst intervals between peaks by employing high density microelectrode arrays (HD-MEA). Our reported data bridge in-vitro electrophysiological neuronal activity and function with in vivo neurophysiological brain activity and function. These data elucidate quantitative, translational biomarkers in vivo and in vitro that can be utilized for the development of and efficacy assessment of targeted treatments for SRID.
@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 = {Activity Scan Assay, HD-MEA, MaxOne, MEA Metrics, MEA Technology, Microfluidics, Organoids},
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{Habibollahi2023,
title = {Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks},
author = {Forough Habibollahi and Brett J. Kagan and Anthony N. Burkitt and Chris French },
url = {https://www.nature.com/articles/s41467-023-41020-3},
doi = {https://doi.org/10.1038/s41467-023-41020-3},
year = {2023},
date = {2023-08-30},
journal = {Nature Communications},
abstract = {Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of ‘Pong’ to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition.},
keywords = {2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}
Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of ‘Pong’ to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition.
@article{Bartram2023b,
title = {Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking},
author = {Julian Bartram and Felix Franke and Sreedhar Saseendran Kumar and Alessio Paolo Buccino and Xiaohan Xue and Tobias Gänswein and Manuel Schröter and Taehoon Kim and Krishna Chaitanya Kasuba and Andreas Hierlemann},
url = {https://elifesciences.org/reviewed-preprints/86820},
doi = {10.7554/eLife.86820},
year = {2023},
date = {2023-05-17},
journal = {eLife},
abstract = {Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general.},
keywords = {HD-MEA, MaxOne, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting},
pubstate = {published},
tppubtype = {article}
}
Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general.
@article{Habibey2022,
title = {Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays},
author = {Rouhollah Habibey and Johannes Striebel and Felix Schmieder and Jürgen Czarske and Volker Busskamp},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2022.951964/full},
doi = {10.3389/fnins.2022.951964},
year = {2022},
date = {2022-10-04},
journal = {Frontiers in Neuroscience},
abstract = {Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.},
keywords = {2D Neuronal Culture, CMOS, HD-MEA, IPSC, MaxOne, MEA Metrics, Modeling, Spike Sorting},
pubstate = {published},
tppubtype = {article}
}
Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.
Presenting measurements of neuronal preparations with a novel CMOS-based microelectrode array at high-spatiotemporal-resolution on subcellular, cellular, and network level.
J. Müller, M. Ballini, P. Livi, Y. Chen, M. Radivojevic, A. Shadmani, V. Viswam, I. L. Jones, M. Fiscella, R. Diggelmann, A. Stettler, U. Frey, D. J. Bakkum, and A. Hierlemann, “High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels,” Lab Chip, vol. 15, no. 13, pp. 2767–2780, May 2015.
Reviewing the current understanding of microelectrode signals and the techniques for analyzing them, with focus on the ongoing advancements in microelectrode technology (in vivo and in vitro) and recent advanced microelectrode array measurement methods that facilitate the understanding of single neurons and network function.
M. E. J. Obien, K. Deligkaris, T. Bullmann, D. J. Bakkum, and U. Frey, “Revealing Neuronal Function through Microelectrode Array Recordings,” Front. Neurosci., 8:423, Jan 2015.
A high-resolution CMOS-based microelectrode array featuring 1,024 low-noise readout channels, 26,400 electrodes at a density of 3,265 electrodes per mm2, including on-chip 10bit ADCs and consuming only 75 mW.
M. Ballini, J. Muller, P. Livi, Y. Chen, U. Frey, A. Stettler, A. Shadmani, V. Viswam, I. L. Jones, D. Jackel, M. Radivojevic, M. K. Lewandowska, W. Gong, M. Fiscella, D. J. Bakkum, F. Heer, and A. Hierlemann, “A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro,” IEEE Journal of Solid-State Circuits, vol. 49, no. 11, pp. 2705-2719, 2014.
Demonstrating a method to electrically visualize action potential propagation on axons and revealing
large variations in velocity.
D. J. Bakkum, U. Frey, M. Radivojevic, T. L. Russell, J. Muller, M. Fiscella, H. Takahashi, and A. Hierlemann, “Tracking axonal action potential propagation on a high-density microelectrode array across hundreds of sites,” Nature Communications, 4:2181, Jul 2013.
Recording and modeling extracellular action potentials of Purkinje cells at subcellular resolution.
U. Frey, U. Egert, F. Heer, S. Hafizovic, and A. Hierlemann, “Microelectronic System for High-Resolution Mapping of Extracellular Electric Fields Applied to Brain Slices,” Biosensors and Bioelectronics, vol. 24, no. 7, pp. 2191-2198, 2009.
Controlling BMP-2 expression to modulate the electrophysiological properties of cardiomyocytes using an HD-MEA for detailed monitoring.
C. D. Sanchez-Bustamante, U. Frey, J. M. Kelm, A. Hierlemann, and M. Fussenegger,
“Modulation of Cardiomyocyte Electrical Properties Using Regulated Bone Morphogenetic Protein-2 Expression,” Tissue Engineering Part A, vol. 14, no. 12, pp. 1969-1988, 2008.
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