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A physicochemical model of odor sampling

We present a general physicochemical sampling model for olfaction, based on established pharmacological laws, in which arbitrary combinations of odorant ligands and receptors can be generated and their individual and collective effects on odor representations and olfactory performance measured. Indi...

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Autores principales: Gronowitz, Mitchell E., Liu, Adam, Qiu, Qiang, Yu, C. Ron, Cleland, Thomas A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8221795/
https://www.ncbi.nlm.nih.gov/pubmed/34115747
http://dx.doi.org/10.1371/journal.pcbi.1009054
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author Gronowitz, Mitchell E.
Liu, Adam
Qiu, Qiang
Yu, C. Ron
Cleland, Thomas A.
author_facet Gronowitz, Mitchell E.
Liu, Adam
Qiu, Qiang
Yu, C. Ron
Cleland, Thomas A.
author_sort Gronowitz, Mitchell E.
collection PubMed
description We present a general physicochemical sampling model for olfaction, based on established pharmacological laws, in which arbitrary combinations of odorant ligands and receptors can be generated and their individual and collective effects on odor representations and olfactory performance measured. Individual odor ligands exhibit receptor-specific affinities and efficacies; that is, they may bind strongly or weakly to a given receptor, and can act as strong agonists, weak agonists, partial agonists, or antagonists. Ligands interacting with common receptors compete with one another for dwell time; these competitive interactions appropriately simulate the degeneracy that fundamentally defines the capacities and limitations of odorant sampling. The outcome of these competing ligand-receptor interactions yields a pattern of receptor activation levels, thereafter mapped to glomerular presynaptic activation levels based on the convergence of sensory neuron axons. The metric of greatest interest is the mean discrimination sensitivity, a measure of how effectively the olfactory system at this level is able to recognize a small change in the physicochemical quality of a stimulus. This model presents several significant outcomes, both expected and surprising. First, adding additional receptors reliably improves the system’s discrimination sensitivity. Second, in contrast, adding additional ligands to an odorscene initially can improve discrimination sensitivity, but eventually will reduce it as the number of ligands increases. Third, the presence of antagonistic ligand-receptor interactions produced clear benefits for sensory system performance, generating higher absolute discrimination sensitivities and increasing the numbers of competing ligands that could be present before discrimination sensitivity began to be impaired. Finally, the model correctly reflects and explains the modest reduction in odor discrimination sensitivity exhibited by transgenic mice in which the specificity of glomerular targeting by primary olfactory neurons is partially disrupted.
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spelling pubmed-82217952021-07-07 A physicochemical model of odor sampling Gronowitz, Mitchell E. Liu, Adam Qiu, Qiang Yu, C. Ron Cleland, Thomas A. PLoS Comput Biol Research Article We present a general physicochemical sampling model for olfaction, based on established pharmacological laws, in which arbitrary combinations of odorant ligands and receptors can be generated and their individual and collective effects on odor representations and olfactory performance measured. Individual odor ligands exhibit receptor-specific affinities and efficacies; that is, they may bind strongly or weakly to a given receptor, and can act as strong agonists, weak agonists, partial agonists, or antagonists. Ligands interacting with common receptors compete with one another for dwell time; these competitive interactions appropriately simulate the degeneracy that fundamentally defines the capacities and limitations of odorant sampling. The outcome of these competing ligand-receptor interactions yields a pattern of receptor activation levels, thereafter mapped to glomerular presynaptic activation levels based on the convergence of sensory neuron axons. The metric of greatest interest is the mean discrimination sensitivity, a measure of how effectively the olfactory system at this level is able to recognize a small change in the physicochemical quality of a stimulus. This model presents several significant outcomes, both expected and surprising. First, adding additional receptors reliably improves the system’s discrimination sensitivity. Second, in contrast, adding additional ligands to an odorscene initially can improve discrimination sensitivity, but eventually will reduce it as the number of ligands increases. Third, the presence of antagonistic ligand-receptor interactions produced clear benefits for sensory system performance, generating higher absolute discrimination sensitivities and increasing the numbers of competing ligands that could be present before discrimination sensitivity began to be impaired. Finally, the model correctly reflects and explains the modest reduction in odor discrimination sensitivity exhibited by transgenic mice in which the specificity of glomerular targeting by primary olfactory neurons is partially disrupted. Public Library of Science 2021-06-11 /pmc/articles/PMC8221795/ /pubmed/34115747 http://dx.doi.org/10.1371/journal.pcbi.1009054 Text en © 2021 Gronowitz et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Gronowitz, Mitchell E.
Liu, Adam
Qiu, Qiang
Yu, C. Ron
Cleland, Thomas A.
A physicochemical model of odor sampling
title A physicochemical model of odor sampling
title_full A physicochemical model of odor sampling
title_fullStr A physicochemical model of odor sampling
title_full_unstemmed A physicochemical model of odor sampling
title_short A physicochemical model of odor sampling
title_sort physicochemical model of odor sampling
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8221795/
https://www.ncbi.nlm.nih.gov/pubmed/34115747
http://dx.doi.org/10.1371/journal.pcbi.1009054
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