1. Deciphering Peripheral Taste Neuron Diversity: Using Genetic Identity to Bridge Taste Bud Innervation Patterns and Functional Responses.
- Author
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Ohman, Lisa C., Huang, Tao, Unwin, Victori A., Singh, Aditi, Walters, Brittany, Whiddon, Zachary D., and Krimm, Robin F.
- Subjects
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TASTE buds , *INNERVATION , *STIMULUS & response (Psychology) , *AVERSIVE stimuli , *NEURONS , *TASTE - Abstract
Peripheral taste neurons exhibit functional, genetic, and morphological diversity, yet understanding how or if these attributes combine into taste neuron types remains unclear. In this study, we used male and female mice to relate taste bud innervation patterns to the function of a subset of proenkephalin-expressing (Penk+) taste neurons. We found that taste arbors (the portion of the axon within the taste bud) stemming from Penk+ neurons displayed diverse branching patterns and lacked stereotypical endings. The range in complexity observed for individual taste arbors from Penk+ neuronsmirrored the entire population, suggesting that taste arbor morphologies are not primarily regulated by the neuron type. Notably, the distinguishing feature of arbors from Penk+ neurons was their propensity to come within 110 nm (in apposition with) different types of taste-transducing cells within the taste bud. This finding is contrary to the expectation of genetically defined taste neuron types that functionally represent a single stimulus. Consistently, further investigation of Penk+ neuron function revealed that they are more likely to respond to innately aversive stimuli--sour, bitter, and high salt concentrations-- as compared with the full taste population. Penk+ neurons are less likely to respond to nonaversive stimuli--sucrose, umami, and low salt--compared with the full population. Our data support the presence of a genetically defined neuron type in the geniculate ganglion that is responsive to innately aversive stimuli. This implies that genetic expression might categorize peripheral taste neurons into hedonic groups, rather than simply identifying neurons that respond to a single stimulus. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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