Combinatorial Signaling in the Dopamine Receptor System

Author: Gregrowicz, Jan M.

Year: 2027

Degree: Dissertation (Ph.D.)

Advisor: Elowitz, Michael B.

Committee Members: Phillips, Robert B.; Bois, Justin S.; Shapiro, Mikhail G.; Elowitz, Michael B.

Option: Biochemistry and Molecular Biophysics

DOI: 10.7907/ppbv-4f87

Abstract

The brain coordinates animal behavior through neuromodulators acting on a large family of G protein-coupled receptors. Dopamine acts through five receptor subtypes divided into two functionally opposing families. The type-1 family couples to stimulatory G proteins and increases cyclic adenosine monophosphate, while the type-2 family couples to inhibitory G proteins and suppresses it. Although these families are classically viewed as operating in distinct neuronal populations, single-cell measurements reveal frequent co-expression of opposing receptors. This poses a fundamental question: how does a single cell integrate a single ligand acting on opposing receptors to produce a coherent response?

This thesis develops a quantitative framework to answer this. We first build a multiplexed single-cell assay that simultaneously quantifies surface receptor abundance and dynamic cyclic adenosine monophosphate output, manipulates transducers or effectors by targeted transcript knockdown, and reads the second messenger through a ratiometric biosensor. Combining this assay with mathematical modeling, we then ask how a single cell resolves opposing inputs, and finally return to single-cell transcriptomes of the human brain to project the resulting integration logic onto native neuronal populations.

Single-receptor responses are well described by a modified operational model routinely used in pharmacology, but combinations of opposing receptors defy simple additive integration. At saturating dopamine, the stimulatory pathway unexpectedly dominates. We trace this discrepancy to the adenylyl cyclase layer, where different cyclase isoforms vary both in their sensitivity to inhibition by the inhibitory G protein alpha subunit and in their responsiveness to the free beta-gamma subunits released when G proteins activate. Targeted knockdown yields per-isoform parameters that accurately predict the combinatorial signaling landscape without additional free parameters. Brain-wide co-expression analysis confirms that receptors, G proteins, and cyclase isoforms form cell-type-specific combinations, and the model predicts that identical inputs produce divergent outputs across these cell types. Thus, effector enzyme composition emerges as a crucial determinant of signaling specificity.

Chapter 1 reviews G protein-coupled receptor signaling and argues for treating combinatorial signaling as a cellular system property. Chapter 2 details the single-cell assay, the mathematical framework that resolves signal integration at the adenylyl cyclase layer, and the transcriptomic analysis that extends this logic to striatal cell types. Chapter 3 outlines a systems-level research program for G protein-coupled receptor signaling, focusing on effector coincidence detection and compartmentalized second-messenger biology.

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