Semiochemical responsive olfactory sensory neurons are sexually dimorphic and plastic
Abstract
Understanding how genes and experiences work in concert to generate phenotypic variability will provide a better understanding of individuality. Here, we considered this in the main olfactory epithelium, a chemosensory structure with over a thousand distinct cell types in mice. We identified a subpopulation of olfactory sensory neurons, defined by receptor expression, whose abundances were sexually dimorphic. This subpopulation of olfactory sensory neurons was over-represented in sex-separated mice and robustly responsive to sex-specific semiochemicals. Sex-combined housing led to an attenuation of the dimorphic representations. Single-cell sequencing analysis revealed an axis of activity-dependent gene expression amongst a subset of the dimorphic OSN populations. Finally, the pro-apoptotic gene Bax is necessary to generate the dimorphic representations. Altogether, our results suggest a role of experience and activity in influencing homeostatic mechanisms to generate a robust sexually dimorphic phenotype in the main olfactory epithelium.
Data availability
Sequencing data have been deposited in GEO under accession codes GSE160272.
Article and author information
Author details
Funding
National Institute on Deafness and Other Communication Disorders (DC014423)
- Eric Block
- Hiroaki Matsunami
National Institute on Deafness and Other Communication Disorders (DC016224)
- Hiroaki Matsunami
National Science Foundation (1556207)
- Hiroaki Matsunami
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocol A128-19-06 at Duke University.
Copyright
© 2020, Vihani et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,559
- views
-
- 304
- downloads
-
- 25
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Neuroscience
Techniques that enable precise manipulations of subsets of neurons in the fly central nervous system (CNS) have greatly facilitated our understanding of the neural basis of behavior. Split-GAL4 driver lines allow specific targeting of cell types in Drosophila melanogaster and other species. We describe here a collection of 3060 lines targeting a range of cell types in the adult Drosophila CNS and 1373 lines characterized in third-instar larvae. These tools enable functional, transcriptomic, and proteomic studies based on precise anatomical targeting. NeuronBridge and other search tools relate light microscopy images of these split-GAL4 lines to connectomes reconstructed from electron microscopy images. The collections are the result of screening over 77,000 split hemidriver combinations. Previously published and new lines are included, all validated for driver expression and curated for optimal cell-type specificity across diverse cell types. In addition to images and fly stocks for these well-characterized lines, we make available 300,000 new 3D images of other split-GAL4 lines.
-
- Neuroscience
Co-active or temporally ordered neural ensembles are a signature of salient sensory, motor, and cognitive events. Local convergence of such patterned activity as synaptic clusters on dendrites could help single neurons harness the potential of dendritic nonlinearities to decode neural activity patterns. We combined theory and simulations to assess the likelihood of whether projections from neural ensembles could converge onto synaptic clusters even in networks with random connectivity. Using rat hippocampal and cortical network statistics, we show that clustered convergence of axons from three to four different co-active ensembles is likely even in randomly connected networks, leading to representation of arbitrary input combinations in at least 10 target neurons in a 100,000 population. In the presence of larger ensembles, spatiotemporally ordered convergence of three to five axons from temporally ordered ensembles is also likely. These active clusters result in higher neuronal activation in the presence of strong dendritic nonlinearities and low background activity. We mathematically and computationally demonstrate a tight interplay between network connectivity, spatiotemporal scales of subcellular electrical and chemical mechanisms, dendritic nonlinearities, and uncorrelated background activity. We suggest that dendritic clustered and sequence computation is pervasive, but its expression as somatic selectivity requires confluence of physiology, background activity, and connectomics.