1. Physics of Living Systems

Adaptation of olfactory receptor abundances for efficient coding

  1. Tiberiu Tesileanu  Is a corresponding author
  2. Simona Cocco
  3. Remi Monasson
  4. Vijay Balasubramanian
  1. Flatiron Institute, United States
  2. École Normale Supérieure, France
  3. University of Pennsylvania, United States
https://doi.org/10.7554/eLife.39279
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  1. Tiberiu Tesileanu
  2. Simona Cocco
  3. Remi Monasson
  4. Vijay Balasubramanian
(2019)
Adaptation of olfactory receptor abundances for efficient coding
eLife 8:e39279.
https://doi.org/10.7554/eLife.39279
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Abstract

Olfactory receptor usage is highly heterogeneous, with some receptor types being orders of magnitude more abundant than others. We propose an explanation for this striking fact: the receptor distribution is tuned to maximally represent information about the olfactory environment in a regime of efficient coding that is sensitive to the global context of correlated sensor responses. This model predicts that in mammals, where olfactory sensory neurons are replaced regularly, receptor abundances should continuously adapt to odor statistics. Experimentally, increased exposure to odorants leads variously, but reproducibly, to increased, decreased, or unchanged abundances of different activated receptors. We demonstrate that this diversity of effects is required for efficient coding when sensors are broadly correlated, and provide an algorithm for predicting which olfactory receptors should increase or decrease in abundance following specific environmental changes. Finally, we give simple dynamical rules for neural birth and death processes that might underlie this adaptation.

Data availability

All the code necessary to reproduce our results and the figures from the paper is available on GitHub, at https://github.com/ttesileanu/OlfactoryReceptorDistribution. The olfactory receptor affinity data were originally published in Hallem et al. (2006) and Saito et al. (2009), and the olfactory receptor expression levels in mouse were originally published in Ibarra-Soria et al. (2017).

The following previously published data sets were used

Article and author information

Author details

  1. Tiberiu Tesileanu

    Center for Computational Biology, Flatiron Institute, New York, United States
    For correspondence
    ttesileanu@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3107-3088

  2. Simona Cocco

    Laboratoire de Physique Statistique, École Normale Supérieure, Paris, France
    Competing interests
    The authors declare that no competing interests exist.

  3. Remi Monasson

    Laboratoire de Physique Théorique, École Normale Supérieure, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4459-0204

  4. Vijay Balasubramanian

    Department of Physics, University of Pennsylvania, Philadelphia, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-6497-3819

Funding

Simons Foundation (400425)

  • Vijay Balasubramanian

Aspen Center for Physics (PHY-160761)

  • Vijay Balasubramanian

Swartz Foundation

  • Tiberiu Tesileanu

National Science Foundation (PHY-1734030)

  • Tiberiu Tesileanu
  • Vijay Balasubramanian

US-Israel Binational Science Foundation (2011058)

  • Vijay Balasubramanian

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Upinder Singh Bhalla, Tata Institute of Fundamental Research, India

Version history

  1. Received: July 3, 2018
  2. Accepted: February 13, 2019
  3. Accepted Manuscript published: February 26, 2019 (version 1)
  4. Version of Record published: March 4, 2019 (version 2)

Copyright

© 2019, Tesileanu 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.

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  1. Tiberiu Tesileanu
  2. Simona Cocco
  3. Remi Monasson
  4. Vijay Balasubramanian
(2019)
Adaptation of olfactory receptor abundances for efficient coding
eLife 8:e39279.
https://doi.org/10.7554/eLife.39279

Share this article

https://doi.org/10.7554/eLife.39279

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