Presented Poster at ISSCR 2023

Title

ENABLING NEXT GENERATION FUNCTIONAL CHARACTERIZATION OF HUMAN NEURAL ORGANOIDS

In this poster you can learn more about how you can:

• Identify & isolate active areas of a 3D cellular model using a powerful user-friendly approach
• Measure the electrical activity of self-organizing in vitro cellular models
• Characterize iPSC-derived neural organoids at subcellular resolution

Abstract

Mammalian organs, such as the brain, are challenging to study being inaccessible to direct optical observation and experimental manipulation. However, recent advances in stem cell research allowed to develop novel three-dimensional (3D) culture techniques, such as neural organoids, resembling cell type diversity, developmental processes and function of human brain.

Measuring the electrical activity of self-organizing in vitro cellular models in real time and label-free add valuableinsights into the complexity of their functional structure. As such, high-density microelectrode arrays (HD-MEAs) provide unprecedented means for non-invasive in vitro electrophysiological recordings, and can be used to acquire live measurements from iPSC-derived neural organoids, contributing to study neuronal development and/or to model neurological disorders.

Here, we used a HD-MEA platform featuring 26,400 electrodes per well (MaxWell Biosystems AG, Switzerland) to capture live the fast propagating extracellular action potentials in neural organoids at different scales, from network through single-neuron with high spatio-temporal resolution and low noise. Metrics, such as firing rate, spike amplitude, network burst profile and other network features, were extrapolated in a parallelized manner. Furthermore, at the subcellular level, we tracked the propagating action potentials across axonal branches to compute and characterize the conduction velocity across multiple neurons within the network of individual iPSC-derived neural organoids.

Our single- and multi-well HD-MEA platforms, together with the extracted parameters highlighted in this study, provide an uniquely powerful user-friendly approach for identifying and isolating active areas of a 3D cellular model in both acute recordings and longitudinal studies. This not only allows long-term disease modelling but also efficientcompound testing on stem cell-derived in-vitro models.

Please complete the form below: