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Graphene Brain on a Chip Platform for the Study of Neurodegeneration

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Hui, Ernestine 


A complex network of interconnected neurons forms the brain. This network is disrupted in neurodegenerative diseases---such as Parkinson's disease (PD), and there are limited tools available to study the molecular mechanisms behind the degradation of the neuronal network. This indicates a gap in the understanding of how neurodegenerative diseases and PD initiate and propagate. Therefore, graphene microelectrode arrays (MEAs) were explored to bridge this gap. However, there are currently no protocols or methods available to fabricate reliably and apply the graphene MEAs for the study of neurodegeneration. This work demonstrates a new reproducible protocol for the fabrication of graphene MEAs, a new method for using the graphene MEAs---including analysing the simultaneous calcium imaging, electrophysiology, and super-resolution imaging data obtained, and a physiologically relevant application for the graphene MEAs in neurodegeneration research. The fabricated devices demonstrated a higher spatiotemporal resolution and lower impedance than commercially available MEAs, due to the properties of the graphene---such as the high transparency---as well as the fabrication techniques. Due to the higher spatiotemporal resolution provided by the graphene, the imaging of spontaneous neuronal activity, electrophysiology, and correlative imaging and electrophysiology recordings of neurons on a network level and a single-cell level could be obtained. In addition, the transparency allowed for the sub-cellular investigations of the degenerating neurons using super-resolution microscopy. A machine-learning model was used to classify the neuronal spikes and analyse the imaging and electrophysiology data. Using U18666A to induce Niemann-Pick disease type C, the graphene MEAs and methodology for simultaneous imaging and electrophysiology were validated. It was found that U18666A had a significant degenerative impact on the synchronicity, activity, connectivity, and morphology of the neurons---which was verified by electrophysiology, microscopy, correlative imaging and electrophysiology, and super-resolution microscopy. In addition, further investigations into PD were carried out and preliminary degenerative effects of cholesterol and alpha-synuclein combined were observed using the graphene MEAs. A reliable, reproducible, and valuable tool for the study of neurodegeneration has been developed. This protocol and methodology immediately allows researchers to investigate neurodegenerative diseases in depth, which expands and adds to the scientific knowledge pool for PD. A deeper understanding of neuronal pathology opens the doors for developing therapeutic interventions for other neurodegenerative diseases as well. Therefore, this work unleashes a new tool for the neuroscience and drug development communities.





Kaminski Schierle, Gabriele


4D Structured illumination microscopy, Alzheimer's disease, Brain-on-a-chip, Calcium imaging, Cholesterol, Correlative imaging and electrophysiology, Electrophysiology, GCaMP, Graphene, Laser writing, Lithography, Machine learning, Microelectrode arrays, Microfabrication, Microscopy, Nanofabrication, Neurodegeneration, Neuron, Niemann-Pick disease type C, Optical microscopy, Parkinson's disease, Protocol, Spike sorting algorithm, Structured illumination microscopy, Transparent microelectrode arrays, U18666A, Widefield microscopy, α-Synuclein


Doctor of Philosophy (PhD)

Awarding Institution

University of Cambridge
EPSRC (2341050)
EPSRC Centre for Doctoral Training in Graphene Technology