Browsing by Subject "Odorant receptor"

Deciphering natural odor plumes with dynamic changes in odor concentrations presents a common challenge to all animals. A fundamental challenge in studying the organization principles of the olfactory system to encode odor concentration information is the lack of comprehensively identified sets of activated odorant receptors (ORs) across an odorant concentration range inside freely behaving animals. In mammals, this has recently become feasible with high-throughput sequencing-based methods that identify populations of odorant activated ORs in vivo. In this study, we characterized the mouse OR repertoires activated by two odorants, acetophenone (ACT) and 2,5-dihydro-2,4,5-trimethylthiazoline (TMT), from 0.01% to 100% (v/v) concentrations. We also investigated the OR repertoires for structural derivatives of TMT (component of fox odor) such as 2­methyl-2-thiazoline (2MT) and 2,4,5-Trimethylthiazole (nTMT) and 2-sec-butyl-4,5-dihydrothiazole (SBT) for 1% and 100% (v/v) concentrations. We used a combination of in vivo, in situ and in silico approaches to investigate ORs with distinct sensitivities to the tested odorants. We examined Olfr923, which we identified to be one of the most sensitive ACT ORs based on our pS6-IP-Seq data. Using a mouse line that genetically labels Olfr923 positive axons, we provide evidence that ACT activates the Olfr923 glomerulus in the olfactory bulb. This study sheds light on the active process in which unique OR repertoires may collectively facilitate the discrimination of odorant concentrations. Together, these odorant receptors may shape the dynamic aspects of olfactory sensitivity and facilitate odorant intensity coding.

In mammals, the perception of smell starts with the activation of odorant receptors (ORs) by volatile molecules in the environment. Mammalian genomes typically encode large numbers of ORs, with approximately 400 intact ORs in human and more than 1000 in mouse. Central to the question of how olfactory stimuli are represented at the peripheral level is defining the ligand selectivity and activity regulation of ORs.

Processing of chemosensory signals in the brain is dynamically regulated in part by an animal’s physiological state. The Matsunami lab previously reported that type 3 muscarinic acetylcholine receptors (M3-Rs) physically interact with odorant receptors (ORs) to promote odor-induced responses in a heterologous expression system. However, it is not known how M3-Rs affect the ability of olfactory sensory neurons (OSNs) to respond to odors. In chapter 2, I demonstrate that the activation of M3-Rs inhibits the recruitment of β-arrestin-2 to ORs, resulting in a potentiation of odor-induced response in OSNs. These results suggest a role for acetylcholine in modulating olfactory processing at the initial stages of signal transduction in the olfactory system.

Understanding odor coding requires comprehensive mapping between odorant receptors and corresponding odorants. In chapter 3, I present a high-throughput in vivo method to identify repertoires of odorant receptors activated by odorants, using phosphorylated ribosome immunoprecipitation of mRNA from olfactory epithelium of odor-stimulated mice followed by RNA-Seq. This approach screens endogenously expressed odorant receptors against an odorant in one set of experiments, using awake and freely behaving mice. In combination with validations in a heterologous system, we identify sets of odorant receptors for two odorants, acetophenone and 2,5-dihydro-2,4,5-trimethylthiazoline (TMT), encompassing 69 receptor-odorant pairs. I also identified shared amino acid residues specific to the acetophenone or TMT receptors, and developed a model to predict receptor activation. This study provides a means to understand the combinatorial coding of odors in vivo.

Understanding how we detect our environment is crucial to understanding how life evolved and now functions. Volatile chemicals from our surroundings are sensed by our olfactory system, a primitive sense that organisms have relied on for survival for millions of years. Mammals express a large family of odorant receptor (OR) genes in the sensory neurons in the nose that mediate this chemosensation. Each mature olfactory sensory neuron (OSN) expresses a single allele of a single OR gene at one time although in the absence of a functional gene OSNs can switch to another OR gene. A functional OR can inhibit the expression of another OR by co-opting the unfolded protein response (UPR). How OSNs make their initial OR gene choice and the mechanisms by which the ORs interact with UPR factors remain unknown.

In this study, I make use of a double knock out mouse that has RTP1 and RTP2, proteins required for the efficient surface trafficking of ORs in heterologous cells, to study the gene regulation of ORs during a large-scale perturbation of the trafficking of ORs to the cell surface. We initially generate and validate the RTP1 and RTP2 double knock out mouse (RTP1,2DKO) and show that consistent with our heterologous expression system, the mutant mice have OR trafficking defects. These OR trafficking defects give rise to higher rates of cell death and the mutant mice have fewer mature OSNs. Surprisingly we identified a subset of ORs that were overrepresented in the RTP1,2DKO animals. Some of these ORs can target the cell surface in the absence of the RTPs. This finding gave rise to two cohorts of ORs, those that are underrepresented in the mutants and presumably dependent on the RTPs for cell surface trafficking and ORs that are overrepresented in RTP1,2DKO. We show that OSNs expressing underrepresented receptors were more likely to be unable to terminate UPR had a higher tendency to switch the OR it was expressing. Using these two cohorts we showed that the trafficking of ORs to the cell surface is a crucial step in the stabilization of the expression of the OR. In the absence of this cell surface trafficking the OSN is unable to terminate the UPR pathway and either undergoes cell death or OR gene switching.

The mammalian olfactory system uses a large family of odorant receptors to detect and discriminate amongst a myriad of volatile odor molecules. The odorant receptors are similar in protein sequence, but their ligand selectivities dramatically differ. It is not clear how the protein sequences determine the responsiveness of odorant receptors. In this study, I attempt to establish the link between the protein sequences of odorant receptors and their ligand selectivity.

Starting from the response profiles of hundreds of mouse odorant receptors to an odorant generated from my previous work, I used machine learning and variable selection methods to identify properties of amino acid residues that predict receptor response. This leads to protein sequence-based models for odorant receptor response prediction. The models trained with mouse odorant receptor data can predict human odorant receptor responses.