All-optical assay to study biological neural networks

• Main Author: Afshar Saber, Wardiya
• Format: Dissertation
• Language: English
• Published: University of St Andrews 2019
• Subjects: Alzheimer's disease; Degeneration; Nervous system; Neurons; Optogenetics; Physiology; Stem cells; TA1522.A4; Technological innovations; Treatment
• DOI: 10.17630/10023-19051

As life span increases, neurodegenerative diseases such as dementia, Parkinson's disease, Huntington's disease, amyotrophic lateral sclerosis become an emerging problem in modern society. In particular Alzheimer's disease (AD), characterized by a progressive cognitive impairment and memory loss, is the dominant cause of disability in people aged over 60. Due to the lack of accurate models, understanding the disease mechanisms and developing a cure for AD remains challenging. However, a novel approach based on human induced pluripotent stem cell (iPSC) technology may offer an opportunity to overcome the limitations of the current models. These cells obtained by reprogramming patient's somatic cells such as fibroblasts can be differentiated in vitro into various types of neural cells which further develop complex networks. To explore these heterogeneous neural networks, it is often critical to understand the activity of multiple neurons and how they communicate with each other. The work presented in this thesis focuses on the development of the first molecular optogenetic tool called OptoCaMP used in an all-optical assay enabling simultaneous stimulation and calcium imaging of a large population of neurons with a single-cell readout. This assay was further adapted to study the spread of excitation in a network thus allowing the quantification of its connectivity. The application of this assay in conditions where the neuronal connectivity was enhanced or decreased successfully demonstrated its sensitivity to changes in connectivity. This assay together with the iPSC technology bring the promise to greatly improve disease models studies and drug screening platforms.