Abstract

Neuromodulators in the brain are fundamental to neuronal functions and animal behaviors in health and diseases. The modulatory actions of neuromodulators highly rely on their spatiotemporal dynamics. Recent research has demonstrated the importance of both sustained and transient change in neuromodulators, likely due to tonic and phasic neuromodulator release. However, no traditional methods could simultaneously record both types of dynamics. Fluorescence lifetime of optical reporters could offer a solution because it both allows high temporal resolution and is impervious to sensor expression differences across chronic periods. Nevertheless, no fluorescence lifetime change across the entire classes of neuromodulator sensors was previously known. Here we find that several intensity-based neuromodulator sensors exhibit fluorescence lifetime responses. Demonstrating the advantage of fluorescence lifetime imaging, we show that lifetime measures in vivo neuromodulator dynamics both with high temporal resolution, and with consistency across animals and time. Additionally, we reason that the advantage of fluorescence lifetime imaging can be compromised by factors like autofluorescence in biological experiments. To explore the limits of fluorescence lifetime application in biological systems, we model the fluorescence lifetime signal from the sensors with non-sensor signals in biological applications and construct a flexible computational framework for realistic Fluorescence Lifetime Simulation for Biological Applications (FLiSimBA). Through simulations, we establish the quantitative limits of the insensitivity of fluorescence lifetime measurement to sensor expression in biological applications. Powered by FLiSimBA to push the technical boundary of fluorescence lifetime applications, we propose multiplexed dynamic imaging innovation that combines fluorescence intensity and lifetime measurement. This innovation can transform the number of signals that can be simultaneously monitored and enable a systems approach in studying signaling dynamics. Thus, we report a method that can simultaneously measure neuromodulator change over transient and chronic time scales, together with a computational framework that supports rigorous experimental design, accurate data interpretation and technological advancement. This method and computational framework promise to reveal the roles of multi-time scale neuromodulator dynamics in diseases, in response to therapies, and across development and aging.

Committee Chair

Yao Chen

Committee Members

Adam Kepecs; Daniel Kerschensteiner; Meaghan Creed; Mikhail Berezin

Degree

Doctor of Philosophy (PhD)

Author's Department

Biology & Biomedical Sciences (Neurosciences)

Author's School

Graduate School of Arts and Sciences

Document Type

Dissertation

Date of Award

12-19-2024

Language

English (en)

Author's ORCID

https://orcid.org/0000-0002-4269-3541

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