Mechanisms of chemosensory recognition

NIH RePORTER · NIH · R01 · $428,743 · view on reporter.nih.gov ↗

Abstract

ABSTRACT The olfactory system encodes and analyzes odorants. Chemicals bind to members of large families of receptor proteins tuned to different chemical features. While we have a comprehensive inventory of the receptor genes that underlie olfactory detection, we are far from having a similarly comprehensive understanding of the chemical features detected by olfactory systems. This proposal leverages four developments—the ability to record the output of an entire olfactory system (the vomeronasal system), a large and structurally-rigid class of odorants (sulfated, carboxylated, and glucuronidated steroids), a new tool to identify the receptor gene(s) that have particular ligand detection profiles, and a new tool for ectopically expressing a chosen receptor gene and studying its function—to develop the first system-wide understanding of how an olfactory system represents the chemical world. The overarching goal is to develop insights analogous to (and with similar predictive power to) the role of cone photoreceptor tuning curves in our understanding of color vision. The specific aims of the proposal are (1) to reveal new principles of combinatorial coding through a system-wide analysis of the vomeronasal system’s coverage, redundancy, and specificity via a large ligand screen and quantitative analysis of the structural features required for activating each receptor; and (2) to reveal relationships between receptor sequence and odorant structure by deorphanizing a large subfamily of vomeronasal receptor genes. Preliminary data suggest that structural rigidity of steroid metabolites contributes greatly to the tractability of these aims, supporting quantitative and predictive analysis on a system-wide scale.

Key facts

NIH application ID
10870101
Project number
5R01DC020034-03
Recipient
WASHINGTON UNIVERSITY
Principal Investigator
Timothy Holy
Activity code
R01
Funding institute
NIH
Fiscal year
2024
Award amount
$428,743
Award type
5
Project period
2022-07-01 → 2027-06-30