Functional assessment of in vitro neuronal networks-of relevance for disease modelling and drug testing-can be performed using multi-electrode array (MEA) technology. However, the handling and... Show moreFunctional assessment of in vitro neuronal networks-of relevance for disease modelling and drug testing-can be performed using multi-electrode array (MEA) technology. However, the handling and processing of the large amount of data typically generated in MEA experiments remains a huge hurdle for researchers. Various software packages have been developed to tackle this issue, but to date, most are either not accessible through the links provided by the authors or only tackle parts of the analysis. Here, we present ''MEA-ToolBox'', a free open-source general MEA analytical toolbox that uses a variety of literature-based algorithms to process the data, detect spikes from raw recordings, and extract information at both the single-channel and array-wide network level. MEA-ToolBox extracts information about spike trains, burst-related analysis and connectivity metrics without the need of manual intervention. MEA-ToolBox is tailored for comparing different sets of measurements and will analyze data from multiple recorded files placed in the same folder sequentially, thus considerably streamlining the analysis pipeline. MEA-ToolBox is available with a graphic user interface (GUI) thus eliminating the need for any coding expertise while offering functionality to inspect, explore and post-process the data. As proof-of-concept, MEA-ToolBox was tested on earlier-published MEA recordings from neuronal networks derived from human induced pluripotent stem cells (hiPSCs) obtained from healthy subjects and patients with neurodevelopmental disorders. Neuronal networks derived from patient's hiPSCs showed a clear phenotype compared to those from healthy subjects, demonstrating that the toolbox could extract useful parameters and assess differences between normal and diseased profiles. Show less
Giacomelli, E.; Sala, L.; Ward-van Oostwaard, D.; Bellin, M. 2021
Background: Human induced pluripotent stem cells (hiPSCs) and their derivative cardiomyocytes (hiPSCCMs) have been successfully used to study the electrical phenotype of cardiac ion channel... Show moreBackground: Human induced pluripotent stem cells (hiPSCs) and their derivative cardiomyocytes (hiPSCCMs) have been successfully used to study the electrical phenotype of cardiac ion channel diseases. However, strategies to mature CMs and more comprehensive systems recapitulating the heart complexity are required to advance our ability to capture adult phenotypes. Methods: We differentiated wild-type (WT) and long QT syndrome type 1 (LQT1) hiPSCs into CMs, endothelial cells and cardiac fibroblasts. The three cell types were combined to form three-dimensional (3D) spheroids, termed "cardiac microtissues" (cMTs) and the electrophysiological properties were measured using 96-well multi-electrode arrays. Results: LQT1 cMTs displayed prolonged field potential duration compared to WT controls, thus recapitulating the typical feature of LQTS. Isoprenaline caused a positive chronotropic effect on both LQT1 and WT cMTs. The 96-well multi-electrode array format proved suitable to detect electrical changes directly in the 3D tissues. Conclusions: 3D hiPSC cMTs are a scalable tool that can be used to identify LQT electrical hallmarks and drug responses. We anticipate this tool can be adopted by pharmaceutical companies to screen cardioactive compounds. (c) 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Show less
