Biology subjects

Hierlemann, A.

Publications and source records attributed to Hierlemann, A..

35 records · Page 2Linked to original sources

bioRxiv2022

A CMOS-based highly scalable flexible neural electrode interface

Perception, thoughts, and actions are encoded by the coordinated activity of large neuronal populations spread over large areas. Using thin film electrocorticography (ECoG) arrays, this cortical activity has been used to decode speech and individual finger movements, enabling neuroprosthetics, and to localize epileptic foci. However, the connectorization of these multi-thousand channel thin-film arrays to external circuitry is challenging; current state-of-the-art methods are complex, bulky, and unscalable. We address this shortcoming by developing an electrode connector based on an ultra-conformable thin film electrode array that self-assembles onto hard silicon chip sensors, such as microelectrode arrays (MEAs) or camera sensors enabling large channel counts at high density. The interconnects are formed using microfabricated electrode pads suspended by thin support arms, termed flex2chip. Capillary-assisted assembly drives the pads to deform towards the chip surface, and van der Waals forces maintain this deformation, establishing mechanical and Ohmic contact onto individual pixels. We demonstrate a 2200-channel array with a channel density of 272 channels / mm2 connected to the MEA through the flex2chip interconnection method. Thin film electrode arrays connected through the flex2chip successfully measured extracellular action potentials ex vivo. Furthermore, in a transgenic mouse model for absence epilepsy, Scn8a+/-, we observed highly variable propagation trajectories at micrometer scales, even across the duration of a single spike- and-wave discharge (SWD).

bioengineering↗

bioRxiv2022

3D in vitro blood-brain-barrier model for investigating barrier insults

The blood-brain-barrier (BBB) prevents that harmful substances in the blood enter the brain, and barrier disruption has been associated with a variety of central-nervous-system diseases. In vitro BBB models enable to recapitulate the BBB behavior in a controlled environment to investigate how the barrier reacts to stress events and external insults. Here, we present a human-cell-based BBB platform with integrated, transparent electrodes to monitor barrier tightness in real time at high spatiotemporal resolution. The BBB model includes human cerebral endothelial cells and primary human pericytes and astrocytes in a three-dimensional arrangement within a pump-free, open microfluidic platform. With our platform, we demonstrate that oxygen-glucose deprivation (OGD), which mimics the characteristics of an ischemic insult, induces a rapid remodeling of the cellular actin structures and subsequent morphological changes in the endothelial cells. High-resolution live imaging showed the formation of large actin stress-fiber bundles in the endothelial layer during OGD application, which ultimately led to cell shrinkage and barrier breakage. Simultaneous electrical measurements showed a rapid decrease of the barrier electrical resistance before the appearance of the stress fibers, which indicates that the barrier function is compromised already before the appearance of drastic morphological changes. The results demonstrate that our BBB platform recapitulates the main barrier functions in vitro and can be used to investigate the rapid reorganization of the BBB upon application of external stimuli.

bioengineering↗

bioRxiv2022

A multi-modal fitting approach to construct single-neuron models with patch clamp and high-density microelectrode arrays

In computational neuroscience, multicompartment models are among the most biophysically realistic representations of single neurons. Constructing such models usually involves the use of the patch-clamp technique to record somatic voltage signals under different experimental conditions. The experimental data are then used to fit the many parameters of the model. While patching of the soma is currently the gold-standard approach to build multicompartment models, several studies have also evidenced a richness of dynamics in dendritic and axonal sections. Recording from the soma alone makes it hard to observe and correctly parameterize the activity of non-somatic compartments. In order to provide a richer set of data as input to multicompartment models, we here investigate the combination of somatic patch-clamp recordings with recordings of high-density micro-electrode arrays (HD-MEAs). HD-MEAs enable the observation of extracellular potentials and neural activity of neuronal compartments at sub-cellular resolution. In this work, we introduce a novel framework to combine patch-clamp and HD-MEA data to construct multicompartment models. We first validate our method on a ground-truth model with known parameters and show that the use of features extracted from extracellular signals, in addition to intracellular ones, yields models enabling better fits than using intracellular features alone. We also demonstrate our procedure using experimental data by constructing cell models from in vitro cell cultures. The proposed multi-modal fitting procedure has the potential to augment the modeling efforts of the computational neuroscience community and to provide the field with neuronal models that are more realistic and can be better validated. Author SummaryMulticompartment models are one of the most biophysically detailed representations of single neurons. The vast majority of these models are built using experimental data from somatic recordings. However, neurons are much more than just their soma and one needs recordings from distal neurites to build an accurate model. In this article, we combine the patch-clamp technique with extracellular high-density microelectrode arrays (HD-MEAs) to compensate this shortcoming. In fact, HD-MEAs readouts allow one to record the neuronal signal in the entire axonal arbor. We show that the proposed multi-modal strategy is superior to the use of patch clamp alone using an existing model as ground-truth. Finally, we show an application of this strategy on experimental data from cultured neurons.

neuroscience↗

bioRxiv2022

Microphysiological Drug-Testing Platform For Identifying Responses To Prodrug Treatment In Primary Leukemia

Despite increasing survival rates of pediatric leukemia patients over the past decades, the outcome of some leukemia subtypes has remained dismal. Drug sensitivity and resistance testing on patient-derived leukemia samples provide important information to tailor treatments for high-risk patients. However, currently used well-based drug screening platforms have imitations in predicting the effects of prodrugs, a class of therapeutics that require metabolic activation to become effective. To address this issue, we developed a microphysiological drug-testing platform that enables co-culturing of patient-derived leukemia cells, human bone marrow mesenchymal stromal cells, and human liver microtissues within the same microfluidic platform. This platform also enables to control the physical interaction between the diverse cell types. We were able to recapitulate hepatic prodrug activation of ifosfamide in our platform, which is very difficult in traditional well-based assays. By testing the susceptibility of primary patient-derived leukemia samples to the prodrug ifosfamide, we identified sample-specific sensitivities to ifosfamide in primary leukemia samples. We found that our microfluidic platform enabled the recapitulation of physiologically relevant conditions and the testing of prodrugs including short-lived and unstable metabolites. The platform holds great potential for clinical translation and precision chemotherapy selection.

bioengineering↗

bioRxiv2022

Downregulating α-synuclein in iPSC-derived dopaminergic neurons mimics electrophysiological phenotype of the A53T mutation

Parkinsons disease (PD) is a common debilitating neurodegenerative disorder, characterized by a progressive loss of dopaminergic (DA) neurons. Mutations, gene dosage increase, and single nucleotide polymorphisms in the -synuclein-encoding gene SNCA either cause or increase the risk for PD. However, neither the function of -synuclein in health and disease, nor its role throughout development is fully understood. Here, we introduce DeePhys, a new tool that allows for data-driven functional phenotyping of neuronal cell lines by combining electrophysiological features inferred from high-density microelectrode array (HD-MEA) recordings with a robust machine learning workflow. We apply DeePhys to human induced pluripotent stem cell (iPSC)-derived DA neuron-astrocyte co-cultures harboring the prominent SNCA mutation A53T and an isogenic control line. Moreover, we demonstrate how DeePhys can facilitate the assessment of cellular and network-level electrophysiological features to build functional phenotypes and to evaluate potential treatment interventions. We find that electrophysiological features across all scales proved to be highly specific for the A53T phenotype, enabled to predict the genotype and age of individual cultures with high accuracy, and revealed a mutant-like phenotype after downregulation of -synuclein.

neuroscience↗

bioRxiv2022

Homophilic wiring principles underpin neuronal network topology in vitro

Economic efficiency has been a popular explanation for how networks self-organize within the developing nervous system. However, the precise nature of the economic negotiations governing this putative organizational principle remains unclear. Here, we address this question further by combining large-scale electrophysiological recordings, to characterize the functional connectivity of developing neuronal networks in vitro, with a generative modeling approach capable of simulating network formation. We find that the best fitting model uses a homophilic generative wiring principle in which neurons form connections to other neurons which are spatially proximal and have similar connectivity patterns to themselves. Homophilic generative models outperform more canonical models in which neurons wire depending upon their spatial proximity either alone or in combination with the extent of their local connectivity. This homophily-based mechanism for neuronal network emergence accounts for a wide range of observations that are described, but not sufficiently explained, by traditional analyses of network topology. Using rodent and human monolayer and organoid cultures, we show that homophilic generative mechanisms can accurately recapitulate the topology of emerging cellular functional connectivity, representing an important wiring principle and determining factor of neuronal network formation in vitro.

neuroscience↗

bioRxiv2022

Inferring monosynaptic connections from paired dendritic spine Ca2+ imaging and large-scale recording of extracellular spiking

Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages as i) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, ii) it provides precise information of presynaptic spiking, and iii) postsynaptic spine Ca2+ signals and, finally, iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.

neuroscience↗

bioRxiv2021

Human neural networks with sparse TDP-43 pathology reveal NPTX2 misregulation in ALS/FTLD

Human cellular models of neurodegeneration require reproducibility and longevity, which is necessary for simulating these age-dependent diseases. Such systems are particularly needed for TDP-43 proteinopathies1,2, which involve human-specific mechanisms3-6 that cannot be directly studied in animal models. To explore the emergence and consequences of TDP-43 pathologies, we generated iPSC-derived, colony morphology neural stem cells (iCoMoNSCs) via manual selection of neural precursors7. Single-cell transcriptomics (scRNA-seq) and comparison to independent NSCs8, showed that iCoMoNSCs are uniquely homogenous and self-renewing. Differentiated iCoMoNSCs formed a self-organized multicellular system consisting of synaptically connected and electrophysiologically active neurons, which matured into long-lived functional networks. Neuronal and glial maturation in iCoMoNSC-derived cultures was similar to that of cortical organoids9. Overexpression of wild-type TDP-43 in a minority of iCoMoNSC-derived neurons led to progressive fragmentation and aggregation, resulting in loss of function and neurotoxicity. scRNA-seq revealed a novel set of misregulated RNA targets coinciding in both TDP-43 overexpressing neurons and patient brains exhibiting loss of nuclear TDP-43. The strongest misregulated target encoded for the synaptic protein NPTX2, which was consistently misaccumulated in ALS and FTLD patient neurons with TDP-43 pathology. Our work directly links TDP-43 misregulation and NPTX2 accumulation, thereby highlighting a new pathway of neurotoxicity.

neuroscience↗

bioRxiv2021

speedingCARs: accelerating the engineering of CAR T cells by signaling domain shuffling and single-cell sequencing

Chimeric antigen receptors (CARs) consist of an extracellular antigen-binding region fused to intracellular signaling domains, thus enabling customized T cell responses against target cells. Due to the low-throughput process of systematically designing and functionally testing CARs, only a small set of immune signaling domains have been thoroughly explored, despite their major role in T cell activation, effector function and persistence. Here, we present speedingCARs, an integrated method for engineering CAR T cells by signaling domain shuffling and functional screening by single-cell sequencing. Leveraging the inherent modularity of natural signaling domains, we generated a diverse library of 180 unique CAR variants, which were genomically integrated into primary human T cells by CRISPR-Cas9. Functional and pooled screening of the CAR T cell library was performed by co-culture with tumor cells, followed by single-cell RNA sequencing (scRNA-seq) and single-cell CAR sequencing (scCAR-seq), thus enabling high-throughput profiling of multi-dimensional cellular responses. This led to the discovery of several CAR variants that retained the ability to kill tumor cells, while also displaying diverse transcriptional signatures and T cell phenotypes. In summary, speedingCARs substantially expands and characterizes the signaling domain combinations suited for CAR design and supports the engineering of next-generation T cell therapies.

synthetic biology↗

bioRxiv2021

An automated method for precise axon reconstruction from recordings of high-density micro-electrode arrays

Neurons communicate with each other by sending action potentials through their axons. The velocity of axonal signal propagation describes how fast electrical action potentials can travel, and can be affected in a human brain by several pathologies, including multiple sclerosis, traumatic brain injury and channelopathies. High-density microelectrode arrays (HD-MEAs) provide unprecedented spatio-temporal resolution to extracellularly record neural electrical activity. The high density of the recording electrodes enables to image the activity of individual neurons down to subcellular resolution, which includes the propagation of axonal signals. However, axon recon-struction, to date, mainly relies on a manual approach to select the electrodes and channels that seemingly record the signals along a specific axon, while an automated approach to track multiple axonal branches in extracellular action-potential recordings is still missing. In this article, we propose a fully automated approach to reconstruct axons from extracellular electrical-potential landscapes, so-called "electrical footprints" of neurons. After an initial electrode and channel selection, the proposed method first constructs a graph, based on the voltage signal amplitudes and latencies. Then, the graph is interrogated to extract possible axonal branches. Finally, the axonal branches are pruned and axonal action-potential propagation velocities are computed. We first validate our method using simulated data from detailed reconstructions of neurons, showing that our approach is capable of accurately reconstructing axonal branches. We then apply the reconstruction algorithm to experimental recordings of HD-MEAs and show that it can be used to determine axonal morphologies and signal-propagation velocities at high throughput. We introduce a fully automated method to reconstruct axonal branches and estimate axonal action-potential propagation velocities using HD-MEA recordings. Our method yields highly reliable and reproducible velocity estimations, which constitute an important electrophysiological feature of neuronal preparations.

neuroscience↗

bioRxiv2020

Electrophysiological Phenotype Characterization of Human iPSC-Derived Neuronal Cell Lines by Means of High-Density Microelectrode Arrays

Recent advances in the field of cellular reprogramming have opened a route to study the fundamental mechanisms underlying common neurological disorders. High-density microelectrode-arrays (HD-MEAs) provide unprecedented means to study neuronal physiology at different scales, ranging from network through single-neuron to subcellular features. In this work, we used HD-MEAs in vitro to characterize and compare human induced-pluripotent-stem-cell (iPSC)-derived dopaminergic and motor neurons, including isogenic neuronal lines modeling Parkinsons disease and amyotrophic lateral sclerosis. We established reproducible electrophysiological network, single-cell and subcellular metrics, which were used for phenotype characterization and drug testing. Metrics such as burst shapes and axonal velocity enabled the distinction of healthy and diseased neurons. The HD-MEA metrics could also be used to detect the effects of dosing the drug retigabine to human motor neurons. Finally, we showed that the ability to detect drug effects and the observed culture-to-culture variability critically depend on the number of available recording electrodes.

neuroscience↗

bioRxiv2020

Versatile live-cell activity analysis platform for characterization of neuronal dynamics at single-cell and network level

Chronic imaging of neuronal networks in vitro has provided fundamental insights into mechanisms underlying neuronal function. Existing labeling and optical imaging methods, however, cannot be used for continuous and long-term recordings of the dynamics and evolution of neuronal networks, as fluorescence indicators can cause phototoxicity. Here, we introduce a versatile platform for label-free, comprehensive and detailed electrophysiological live-cell imaging of various neurogenic cells and tissues over extended times. We report on a novel dual-mode high-density microelectrode array, which can simultaneously record in i) full-frame mode with 19,584 recording sites and ii) high-signal-to-noise mode with 246 channels. We set out to demonstrate the capabilities of this platform with recordings from primary and iPSC-derived neuronal cultures and tissue preparations over several weeks, providing detailed morpho-electrical phenotypic parameters at subcellular, cellular and network level. Moreover, we developed reliable analysis tools with drastically increased throughput for extracting axonal morphology and conduction parameters.

neuroscience↗

bioRxiv2019

Cell types of the human retina and its organoids at single-cell resolution: developmental convergence, transcriptomic identity, and disease map

How closely human organoids recapitulate cell-type diversity and cell-type maturation of their target organs is not well understood. We developed human retinal organoids with multiple nuclear and synaptic layers. We sequenced the RNA of 158,844 single cells from these organoids at six 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 and the transcriptomes of organoid cell types converged towards the transcriptomes of adult peripheral retinal cell types. The expression of disease-associated genes was significantly 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 adult human retinas.

neuroscience↗

bioRxiv2019

Massively Parallel Microwire Arrays Integrated with CMOS chips for Neural Recording

Multi-channel electrical recordings of neural activity in the brain is an increasingly powerful method revealing new aspects of neural communication, computation, and prosthetics. However, while planar silicon-based CMOS devices in conventional electronics scale rapidly, neural interface devices have not kept pace. Here, we present a new strategy to interface silicon-based chips with three-dimensional microwire arrays, providing the link between rapidly-developing electronics and high density neural interfaces. The system consists of a bundle of microwires mated to large-scale microelectrode arrays, such as camera chips. This system has excellent recording performance, demonstrated via single unit and local-field potential recordings in isolated retina and in the motor cortex or striatum of awake moving mice. The modular design enables a variety of microwire types and sizes to be integrated with different types of pixel arrays, connecting the rapid progress of commercial multiplexing, digitisation and data acquisition hardware together with a three-dimensional neural interface.

neuroscience↗

bioRxiv2019

CHIME: CMOS-hosted in-vivo microelectrodes for massively scalable neuronal recordings

Mammalian brains consist of 10s of millions to 100s of billions of neurons operating at millisecond time scales, of which current recording techniques only capture a tiny fraction. Recording techniques capable of sampling neural activity at such temporal resolution have been difficult to scale: The most intensively studied mammalian neuronal networks, such as the neocortex, show layered architecture, where the optimal recording technology samples densely over large areas. However, the need for application-specific designs as well as the mismatch between the threedimensional architecture of the brain and largely two-dimensional microfabrication techniques profoundly limits both neurophysiological research and neural prosthetics.\n\nHere, we propose a novel strategy for scalable neuronal recording by combining bundles of glass-ensheathed microwires with large-scale amplifier arrays derived from commercial CMOS of in-vitro MEA systems or high-speed infrared cameras. High signal-to-noise ratio (<20 V RMS noise floor, SNR up to 25) is achieved due to the high conductivity of core metals in glass-ensheathed microwires allowing for ultrathin metal cores (down to <1 m) and negligible stray capacitance. Multi-step electrochemical modification of the tip enables ultra-low access impedance with minimal geometric area and largely independent of core diameter. We show that microwire size can be reduced to virtually eliminate damage to the blood-brain-barrier upon insertion and demonstrate that microwire arrays can stably record single unit activity.\n\nCombining microwire bundles and CMOS arrays allows for a highly scalable neuronal recording approach, linking the progress of electrical neuronal recording to the rapid scaling of silicon microfabrication. The modular design of the system allows for custom arrangement of recording sites. Our approach of employing bundles of minimally invasive, highly insulated and functionalized microwires to lift a 2-dimensional CMOS architecture into the 3rd dimension can be translated to other CMOS arrays such as electrical stimulation devices.

neuroscience↗

bioRxiv2018

The axon initial segment drives the neuron’s extracellular action potential

Extracellular voltage fields produced by a neurons action potentials provide a primary means for studying neuron function, yet their biophysical sources remain ambiguous. The neurons soma and dendrites are thought to drive the extracellular action potential (EAP), while the axon is usually ignored. However, by recording voltages of single neurons in dissociated rat cortical cultures and Purkinje cells in acute mouse cerebellar slices at hundreds of sites, we find instead that the axon initial segment dominates the EAP, and, surprisingly, the soma shows little or no influence. As expected, this signal has negative polarity (charge entering the cell) and initiates at the distal end. Interestingly, signals with positive polarity (charge exiting the cell) occur near some but not all dendritic branches and occur after a delay. Such basic knowledge about which neuronal compartments contribute to the extracellular voltage field is important for interpreting results from all electrical readout schemes. Moreover, this finding shows that changes in the AIS position and function can be observed in high spatiotemporal detail by means of high-density extracellular electrophysiology.\n\nKey points summaryO_LIThe neurons soma and dendrites are thought to give rise to its extracellular voltage signal, while signals from the axon are usually considered negligible.\nC_LIO_LIInstead, we found that the largest amplitude of the extracellular signal originates from the axon initial segment, not from the soma.\nC_LIO_LIThis finding shows that changes in the AIS position and function can be observed in high spatiotemporal detail by means of high-density extracellular electrophysiology.\nC_LI\n\nAbbreviations

neuroscience↗

bioRxiv2017

Network Analysis Of High-Density Microelectrode Recordings

A high-density microelectrode arrays (HDMEA) with 3,150 electrodes per square millimetre was used to capture neuronal activity across various scales, including axons, dendrites, and networks. We present a new method for high-throughput segmentation of axons based on the spatial smoothness of signal delays. Comparison with both ground truth and receiver operator characteristics shows that the new segmentation method outperforms previous methods based on the signal-amplitude-to-noise ratio. Structural and functional neuronal network connectivity were reconstructed using a common extension of \"Peters rule\" and a inter-spike histogram method, respectively. Approximately one third of these connections are putative chemical synapses. We evaluated the spike patterns but did not find evidence for \"polychronisation\" (non-synchronous but precisely timed spike sequences). The developed framework can be used to investigate the relationship between the topology of neuronal connections and emerging temporal spike patterns observed in dissociated neuronal cultures.

neuroscience↗