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      Implications for human odor sensing revealed from the statistics of odorant-receptor interactions

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          Abstract

          Binding of odorants to olfactory receptors (ORs) elicits downstream chemical and neural signals, which are further processed to odor perception in the brain. Recently, Mainland and colleagues have measured more than 500 pairs of odorant-OR interaction by a high-throughput screening assay method, opening a new avenue to understanding the principles of human odor coding. Here, using a recently developed minimal model for OR activation kinetics, we characterize the statistics of OR activation by odorants in terms of three empirical parameters: the half-maximum effective concentration EC 50, the efficacy, and the basal activity. While the data size of odorants is still limited, the statistics offer meaningful information on the breadth and optimality of the tuning of human ORs to odorants, and allow us to relate the three parameters with the microscopic rate constants and binding affinities that define the OR activation kinetics. Despite the stochastic nature of the response expected at individual OR-odorant level, we assess that the confluence of signals in a neuron released from the multitude of ORs is effectively free of noise and deterministic with respect to changes in odorant concentration. Thus, setting a threshold to the fraction of activated OR copy number for neural spiking binarizes the electrophysiological signal of olfactory sensory neuron, thereby making an information theoretic approach a viable tool in studying the principles of odor perception.

          Author summary

          Despite the decades of research, quantitative details of human olfaction have remained largely unexplored. However, a high-throughput measurement has recently been carried out to produce dose-response data between a set of odorants and a repertoire of human olfactory receptors. We characterized each pair of odorant-receptor interaction in terms of EC50, efficacy, and basal level, a strategy often adopted in biochemical, pharmacological sciences to describe the response of receptors to cognate ligands. The distributions of EC50 values and efficacies acquired from the analysis provide glimpses into how human olfactory receptors are tuned to odorants. Specifically, the response of human ORs is optimized around ∼ 100 μM of odorant. Next, the efficacies of OR responses to odorants are bi-exponentially distributed, which indicates that the strength of odorant-OR interaction is classified into strong and weak subgroups. By showing that the stochastic response of individual receptor to odorant can effectively be binarized at cellular level through olfactory processes, we also provide a theoretical basis for an information theoretical approach in studying the principles of odor perception.

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          Most cited references44

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          Combinatorial receptor codes for odors.

          The discriminatory capacity of the mammalian olfactory system is such that thousands of volatile chemicals are perceived as having distinct odors. Here we used a combination of calcium imaging and single-cell RT-PCR to identify odorant receptors (ORs) for odorants with related structures but varied odors. We found that one OR recognizes multiple odorants and that one odorant is recognized by multiple ORs, but that different odorants are recognized by different combinations of ORs. Thus, the olfactory system uses a combinatorial receptor coding scheme to encode odor identities. Our studies also indicate that slight alterations in an odorant, or a change in its concentration, can change its "code," potentially explaining how such changes can alter perceived odor quality.
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            Physics of chemoreception.

            Statistical fluctuations limit the precision with which a microorganism can, in a given time T, determine the concentration of a chemoattractant in the surrounding medium. The best a cell can do is to monitor continually the state of occupation of receptors distributed over its surface. For nearly optimum performance only a small fraction of the surface need be specifically adsorbing. The probability that a molecule that has collided with the cell will find a receptor is Ns/(Ns + pi a), if N receptors, each with a binding site of radius s, are evenly distributed over a cell of radius a. There is ample room for many indenpendent systems of specific receptors. The adsorption rate for molecules of moderate size cannot be significantly enhanced by motion of the cell or by stirring of the medium by the cell. The least fractional error attainable in the determination of a concentration c is approximately (TcaD) - 1/2, where D is diffusion constant of the attractant. The number of specific receptors needed to attain such precision is about a/s. Data on bacteriophage absorption, bacterial chemotaxis, and chemotaxis in a cellular slime mold are evaluated. The chemotactic sensitivity of Escherichia coli approaches that of the cell of optimum design.
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              Allelic inactivation regulates olfactory receptor gene expression.

              We suggest a model in which a hierarchy of controls is exerted on the family of odorant receptor genes to assure that a sensory neuron expresses a single receptor from a family of 1000 genes. We propose that a cis-regulatory element directs the stochastic expression of only one gene from a large array of linked receptor genes. Moreover, only one allelic array encoding multiple receptor genes is active in an individual neuron. We demonstrate that in a neuron expressing a given receptor, expression derives exclusively from one allele. In addition, we observe that alleles encoding the odorant receptors are replicated asynchronously, a phenomenon consistently associated with allelic inactivation. This model, involving inactivation of one allelic array and cis control of the active array, provides a mechanism such that individual neurons express one or a small number of receptors.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS Comput Biol
                PLoS Comput. Biol
                plos
                ploscomp
                PLoS Computational Biology
                Public Library of Science (San Francisco, CA USA )
                1553-734X
                1553-7358
                May 2018
                21 May 2018
                : 14
                : 5
                : e1006175
                Affiliations
                [1 ] School of Computational Sciences, Korea Institute for Advanced Study, Seoul, Korea
                [2 ] Department of Chemistry and Biochemistry, Queens College, City University of New York, Queens, New York, United States of America
                [3 ] PhD programs in Chemistry and Physics, and Initiative for Theoretical Sciences, Graduate Center, City University of New York, New York, New York, United States
                University of Maryland School of Pharmacy, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-5700-7823
                http://orcid.org/0000-0002-4844-7237
                Article
                PCOMPBIOL-D-18-00430
                10.1371/journal.pcbi.1006175
                5983876
                29782484
                f71c9f97-43a4-4f4d-b9a3-103f981f04e4
                © 2018 Bak et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 March 2018
                : 4 May 2018
                Page count
                Figures: 5, Tables: 1, Pages: 16
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000086, Directorate for Mathematical and Physical Sciences;
                Award ID: CHE-1362926
                Award Recipient :
                The support for SJJ came from the National Science Foundation (CHE-1362926). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Physical Sciences
                Materials Science
                Materials by Attribute
                Odorants
                Biology and Life Sciences
                Cell Biology
                Cellular Types
                Animal Cells
                Neurons
                Afferent Neurons
                Olfactory Receptor Neurons
                Biology and Life Sciences
                Neuroscience
                Cellular Neuroscience
                Neurons
                Afferent Neurons
                Olfactory Receptor Neurons
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Cell Signaling
                G-Protein Signaling
                Biology and Life Sciences
                Neuroscience
                Sensory Perception
                Sensory Receptors
                Biology and Life Sciences
                Psychology
                Sensory Perception
                Sensory Receptors
                Social Sciences
                Psychology
                Sensory Perception
                Sensory Receptors
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Sensory Receptors
                Biology and Life Sciences
                Neuroscience
                Sensory Perception
                Smell
                Biology and Life Sciences
                Psychology
                Sensory Perception
                Smell
                Social Sciences
                Psychology
                Sensory Perception
                Smell
                Biology and Life Sciences
                Physiology
                Sensory Physiology
                Olfactory System
                Medicine and Health Sciences
                Physiology
                Sensory Physiology
                Olfactory System
                Biology and Life Sciences
                Neuroscience
                Sensory Systems
                Olfactory System
                Biology and Life Sciences
                Neuroscience
                Sensory Perception
                Sensory Receptors
                Olfactory Receptors
                Biology and Life Sciences
                Psychology
                Sensory Perception
                Sensory Receptors
                Olfactory Receptors
                Social Sciences
                Psychology
                Sensory Perception
                Sensory Receptors
                Olfactory Receptors
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Sensory Receptors
                Olfactory Receptors
                Biology and Life Sciences
                Biochemistry
                Proteins
                Transmembrane Receptors
                G Protein Coupled Receptors
                Biology and Life Sciences
                Cell Biology
                Signal Transduction
                Transmembrane Receptors
                G Protein Coupled Receptors
                Custom metadata
                vor-update-to-uncorrected-proof
                2018-06-01
                All relevant data are within the paper and its Supporting Information files.

                Quantitative & Systems biology
                Quantitative & Systems biology

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