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Patterned cardiomyocytes on microelectrode arrays as a functional, high information content drug screening platform.

ABSTRACT: Cardiac side effects are one of the major causes of drug candidate failures in preclinical drug development or in clinical trials and are responsible for the retraction of several already marketed therapeutics. Thus, the development of a relatively high-throughput, high information content tool to screen drugs and toxins would be important in the field of cardiac research and drug development. In this study, recordings from commercial multielectrode arrays were combined with surface patterning of cardiac myocyte monolayers to enhance the information content of the method; specifically, to enable the measurement of conduction velocity, refractory period after action potentials and to create a functional re-entry model. Two drugs, 1-Heptanol, a gap junction blocker, and Sparfloxacin, a fluoroquinone antibiotic, were tested in this system. 1-Heptanol administration resulted in a marked reduction in conduction velocity, whereas Sparfloxacin caused rapid, irregular and unsynchronized activity, indicating fibrillation. As shown in these experiments, patterning of cardiac myocyte monolayers solved several inherent problems of multielectrode recordings, increased the temporal resolution of conduction velocity measurements, and made the synchronization of external stimulation with action potential propagation possible for refractory period measurements. This method could be further developed as a cardiac side effect screening platform after combination with human cardiomyocytes.

SUBMITTER: Natarajan A

PROVIDER: S-EPMC3102308 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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Patterned cardiomyocytes on microelectrode arrays as a functional, high information content drug screening platform.

Natarajan Anupama A Stancescu Maria M Dhir Vipra V Armstrong Christopher C Sommerhage Frank F Hickman James J JJ Molnar Peter P

Biomaterials 20110331 18

Cardiac side effects are one of the major causes of drug candidate failures in preclinical drug development or in clinical trials and are responsible for the retraction of several already marketed therapeutics. Thus, the development of a relatively high-throughput, high information content tool to screen drugs and toxins would be important in the field of cardiac research and drug development. In this study, recordings from commercial multielectrode arrays were combined with surface patterning o ...[more]

PMID: 21453966

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Project description:Drug-induced arrhythmia is one of the most common causes of drug development failure and withdrawal from market. This study tested whether human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) combined with a low-impedance microelectrode array (MEA) system could improve on industry-standard preclinical cardiotoxicity screening methods, identify the effects of well-characterized drugs, and elucidate underlying risk factors for drug-induced arrhythmia. hiPSC-CMs may be advantageous over immortalized cell lines because they possess similar functional characteristics as primary human cardiomyocytes and can be generated in unlimited quantities.Pharmacological responses of beating embryoid bodies exposed to a comprehensive panel of drugs at 65 to 95 days postinduction were determined. Responses of hiPSC-CMs to drugs were qualitatively and quantitatively consistent with the reported drug effects in literature. Torsadogenic hERG blockers, such as sotalol and quinidine, produced statistically and physiologically significant effects, consistent with patch-clamp studies, on human embryonic stem cell-derived cardiomyocytes hESC-CMs. False-negative and false-positive hERG blockers were identified accurately. Consistent with published studies using animal models, early afterdepolarizations and ectopic beats were observed in 33% and 40% of embryoid bodies treated with sotalol and quinidine, respectively, compared with negligible early afterdepolarizations and ectopic beats in untreated controls.We found that drug-induced arrhythmias can be recapitulated in hiPSC-CMs and documented with low impedance MEA. Our data indicate that the MEA/hiPSC-CM assay is a sensitive, robust, and efficient platform for testing drug effectiveness and for arrhythmia screening. This system may hold great potential for reducing drug development costs and may provide significant advantages over current industry standard assays that use immortalized cell lines or animal models.

Project description:IntroductionCell-cell communication plays a pivotal role in biological systems' coordination and function. Electrical properties have been linked to specification and differentiation of stem cells into targeted progeny, such as neurons and cardiomyocytes. Currently, there is a critical need in developing new ways to complement fluorescent indicators, such as Ca2+-sensitive dyes, for direct electrophysiological measurements of cells and tissue. Here, we report a unique transparent and biocompatible graphene-based electrical platform that enables electrical and optical investigation of human embryonic stem cell-derived cardiomyocytes' (hESC-CMs) intracellular processes and intercellular communication.MethodsGraphene, a honeycomb sp2 hybridized two-dimensional carbon lattice, was synthesized using low pressure chemical vapor deposition system, and was tested for biocompatibility. Au and graphene microelectrode arrays (MEAs) were fabricated using well-established microfabrication methods. Au and graphene MEAs were interfaced with hESC-CMs to perform both optical and electrical recordings.ResultsOptical imaging and Raman spectroscopy confirmed the presence of monolayer graphene. Viability assay showed biocompatibility of graphene. Electrochemical characterization proved graphene's functional activity. Nitric acid treatment further enhanced the electrochemical properties of graphene. Graphene electrodes' transparency enabled both optical and electrical recordings from hESC-CMs. Graphene MEA detected changes in beating frequency and field potential duration upon β-adrenergic receptor agonist treatment.ConclusionThe transparent graphene platform enables the investigation of both intracellular and intercellular communication processes and will create new avenues for bidirectional communication (sensing and stimulation) with electrically active tissues and will set the ground for investigations reported diseases such as Alzheimer, Parkinson's disease and arrhythmias.

Project description:AbstractStudies have provided evidence that human cerebral organoids (hCOs) recapitulate fundamental milestones of early brain development, but many important questions regarding their functionality and electrophysiological properties persist. High-density microelectrode arrays (HD-MEAs) represent an attractive analysis platform to perform functional studies of neuronal networks at the cellular and network scale. Here, we use HD-MEAs to derive large-scale electrophysiological recordings from sliced hCOs. We record the activity of hCO slices over several weeks and probe observed neuronal dynamics pharmacologically. Moreover, we present results on how the obtained recordings can be spike-sorted and subsequently studied across scales. For example, we show how to track single neurons across several days on the HD-MEA and how to infer axonal action potential velocities. We also infer putative functional connectivity from hCO recordings. The introduced methodology will contribute to a better understanding of developing neuronal networks in brain organoids and provide new means for their functional characterization.Impact statementHuman cerebral organoids (hCOs) represent an attractive in vitro model system to study key physiological mechanisms underlying early neuronal network formation in tissue with healthy or disease-related genetic backgrounds. Despite remarkable advances in the generation of brain organoids, knowledge on the functionality of their neuronal circuits is still scarce. Here, we used complementary metal-oxide-semiconductor (CMOS)-based high-density microelectrode arrays (HD-MEAs) to perform large-scale recordings from sliced hCOs over several weeks and quantified their activity across scales. Using single-cell and network metrics, we were able to probe aspects of hCO neurophysiology that are more difficult to obtain with other techniques, such as patch clamping (lower yield) and calcium imaging (lower temporal resolution). These metrics included, for example, extracellular action potential (AP) waveform features and axonal AP velocity at the cellular level, as well as functional connectivity at the network level. Analysis was enabled by the large sensing area and the high spatiotemporal resolution provided by HD-MEAs, which allowed recordings from hundreds of neurons and spike sorting of their activity. Our results demonstrate that HD-MEAs provide a multi-purpose platform for the functional characterization of hCOs, which will be key in improving our understanding of this model system and assessing its relevance for translational research.Graphical abstractSupplementary informationThe online version contains supplementary material available at 10.1557/s43577-022-00282-w.

Project description:High-density microelectrode arrays can be used to record extracellular action potentials from hundreds to thousands of neurons simultaneously. Efficient spike sorters must be developed to cope with such large data volumes. Most existing spike sorting methods for single electrodes or small multielectrodes, however, suffer from the "curse of dimensionality" and cannot be directly applied to recordings with hundreds of electrodes. This holds particularly true for the standard reference spike sorting algorithm, principal component analysis-based feature extraction, followed by k-means or expectation maximization clustering, against which most spike sorters are evaluated. We present a spike sorting algorithm that circumvents the dimensionality problem by sorting local groups of electrodes independently with classical spike sorting approaches. It is scalable to any number of recording electrodes and well suited for parallel computing. The combination of data prewhitening before the principal component analysis-based extraction and a parameter-free clustering algorithm obviated the need for parameter adjustments. We evaluated its performance using surrogate data in which we systematically varied spike amplitudes and spike rates and that were generated by inserting template spikes into the voltage traces of real recordings. In a direct comparison, our algorithm could compete with existing state-of-the-art spike sorters in terms of sensitivity and precision, while parameter adjustment or manual cluster curation was not required. NEW & NOTEWORTHY We present an automatic spike sorting algorithm that combines three strategies to scale classical spike sorting techniques for high-density microelectrode arrays: 1) splitting the recording electrodes into small groups and sorting them independently; 2) clustering a subset of spikes and classifying the rest to limit computation time; and 3) prewhitening the spike waveforms to enable the use of parameter-free clustering. Finally, we combined these strategies into an automatic spike sorter that is competitive with state-of-the-art spike sorters.

Dataset Information

Patterned cardiomyocytes on microelectrode arrays as a functional, high information content drug screening platform.

Publications

Patterned cardiomyocytes on microelectrode arrays as a functional, high information content drug screening platform.

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