UC San Diego

Cells execute specific responses to diverse environmental cues by encoding information in distinctly compartmentalized biochemical signaling reactions. Genetically encoded fluorescent biosensors enable the spatial and temporal monitoring of signaling events in live cells. Chapter 1 of this dissertation is a reprint of work submitted for publication, that introduces the concepts of compartmentalized signaling, genetically encoded fluorescent biosensors, and temporal and spatiotemporal deterministic computational modeling and then demonstrates the power of applying computational models to interpret biosensor experiments in complex biochemical networks in two case studies. Chapter 2 of this dissertation is a reprint of published work in which we demonstrate that a mutation on a solvent-exposed residue of a red fluorescent protein (RFP) leads to a brighter, more stably fluorescent RFP. We also show that this RFP enhances green-red FRET biosensors and can be incorporated into a spectrally orthogonal FRET biosensor multiplexing scheme to investigate the crosstalk between Src, Akt, and Extracellular Regulated Kinase (ERK) kinases in single cells. Chapter 3 is a reprint of published work wherein we demonstrate that a platform combing an open-source liquid handler with a fluorescent microscope can automate and enhance throughput of fluorescent biosensor imaging experiments in response to multiple compound stimulations. We demonstrate this platform using protein kinase A (PKA) and 3′,5′-cyclic adenosine monophosphate (cAMP) FRET biosensors to measure the signaling dynamics in response to varying concentrations of a single G-protein coupled receptor (GPCR) agonist, to a panel of GPCR agonists and antagonists, or to pH media exchanges. Finally, Chapter 4 is a conclusion where we summarize the findings and discuss future extensions of the work. This work describes three different methods that increase the utility of fluorescent biosensors experiments to investigate cell signaling phenomenon: quantitatively evaluating biosensor experimental data using computational models, developing a new red fluorescent protein and a three FRET biosensor multiplexing scheme, and engineering a platform that automates and increases throughput of fluorescent biosensor imaging experiments.