Light-at-night exposure affects brain development through pineal allopregnanolone-dependent mechanisms

  1. Shogo Haraguchi  Is a corresponding author
  2. Masaki Kamata
  3. Takuma Tokita
  4. Kei-ichiro Tashiro
  5. Miku Sato
  6. Mitsuki Nozaki
  7. Mayumi Okamoto-Katsuyama
  8. Isao Shimizu
  9. Guofeng Han
  10. Vishwajit Sur Chowdhury
  11. Xiao-Feng Lei
  12. Takuro Miyazaki
  13. Joo-ri Kim-Kaneyama
  14. Tomoya Nakamachi
  15. Kouhei Matsuda
  16. Hirokazu Ohtaki
  17. Toshinobu Tokumoto
  18. Tetsuya Tachibana
  19. Akira Miyazaki
  20. Kazuyoshi Tsutsui  Is a corresponding author
  1. Waseda University, Japan
  2. Kyushu University, Japan
  3. Showa University School of Medicine, Japan
  4. University of Toyama, Japan
  5. Shizuoka University, Japan
  6. Ehime University, Japan

Abstract

The molecular mechanisms by which environmental light conditions affect cerebellar development are incompletely understood. We showed that circadian disruption by light-at-night induced Purkinje cell death through pineal allopregnanolone (ALLO) activity during early life in chicks. Light-at-night caused the loss of diurnal variation of pineal ALLO synthesis during early life and led to cerebellar Purkinje cell death, which was suppressed by a daily injection of ALLO. The loss of diurnal variation of pineal ALLO synthesis induced not only reduction in pituitary adenylate cyclase-activating polypeptide (PACAP), a neuroprotective hormone, but also transcriptional repression of the cerebellar Adcyap1 gene that produces PACAP, with subsequent Purkinje cell death. Taken together, pineal ALLO mediated the effect of light on early cerebellar development in chicks.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files for Figures 1-10 have been deposited to Dryad DOI: https://doi.org/10.5061/dryad.k6g8b53

The following data sets were generated

Article and author information

Author details

  1. Shogo Haraguchi

    Department of Biology, Waseda University, Tokyo, Japan
    For correspondence
    shogo.haraguchi@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8731-3311
  2. Masaki Kamata

    Department of Biology, Waseda University, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  3. Takuma Tokita

    Department of Biology, Waseda University, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  4. Kei-ichiro Tashiro

    Department of Biology, Waseda University, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  5. Miku Sato

    Department of Biology, Waseda University, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  6. Mitsuki Nozaki

    Department of Biology, Waseda University, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  7. Mayumi Okamoto-Katsuyama

    Department of Applied Chemistry, School of Science and Engineering, Waseda University, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  8. Isao Shimizu

    Department of Applied Chemistry, School of Science and Engineering, Waseda University, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  9. Guofeng Han

    Laboratory of Stress Physiology and Metabolism, Graduate School of Bioresource and Bioenvironmental Science, Kyushu University, Fukuoka, Japan
    Competing interests
    The authors declare that no competing interests exist.
  10. Vishwajit Sur Chowdhury

    Laboratory of Stress Physiology and Metabolism, Graduate School of Bioresource and Bioenvironmental Science, Kyushu University, Fukuoka, Japan
    Competing interests
    The authors declare that no competing interests exist.
  11. Xiao-Feng Lei

    Department of Biochemistry, Showa University School of Medicine, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  12. Takuro Miyazaki

    Department of Biochemistry, Showa University School of Medicine, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  13. Joo-ri Kim-Kaneyama

    Department of Biochemistry, Showa University School of Medicine, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  14. Tomoya Nakamachi

    Laboratory of Regulatory Biology, Graduate School of Science and Engineering, University of Toyama, Toyama, Japan
    Competing interests
    The authors declare that no competing interests exist.
  15. Kouhei Matsuda

    Laboratory of Regulatory Biology, Graduate School of Science and Engineering, University of Toyama, Toyama, Japan
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8253-5230
  16. Hirokazu Ohtaki

    Department of Anatomy, Showa University School of Medicine, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  17. Toshinobu Tokumoto

    Integrated Bioscience Section, Graduate School of Science and Technology, Shizuoka University, Shizuoka, Japan
    Competing interests
    The authors declare that no competing interests exist.
  18. Tetsuya Tachibana

    Department of Agrobiological Science, Faculty of Agriculture, Ehime University, Matsuyama, Japan
    Competing interests
    The authors declare that no competing interests exist.
  19. Akira Miyazaki

    Department of Biochemistry, Showa University School of Medicine, Tokyo, Japan
    Competing interests
    The authors declare that no competing interests exist.
  20. Kazuyoshi Tsutsui

    Department of Biology, Waseda University, Tokyo, Japan
    For correspondence
    k-tsutsui@waseda.jp
    Competing interests
    The authors declare that no competing interests exist.

Funding

Japan Society for the Promotion of Science (15K18571)

  • Shogo Haraguchi

Takeda Science Foundation

  • Shogo Haraguchi

Ichiro Kanehara Foundation for the Promotion of Medical Sciences and Medical Care

  • Shogo Haraguchi

Kao Corporation

  • Shogo Haraguchi

Naito Foundation

  • Shogo Haraguchi

Narishige Zoological Science Foundation

  • Shogo Haraguchi

Yamaguchi Endocrine Research Foundation

  • Shogo Haraguchi

Suntory Foundation for Life Sciences

  • Shogo Haraguchi

Japan Society for the Promotion of Science (22227002)

  • Kazuyoshi Tsutsui

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

Ethics

Animal experimentation: The experimental protocols (2011-A090, 2012-A003, 2013-A010, 2014-A063, 2015-A012, 29M050, 30M047) were in accordance with the Guide for the Care and Use of Laboratory Animals of Waseda University or Showa University, Japan.

Reviewing Editor

  1. Vatsala Thirumalai, National Centre for Biological Sciences, India

Publication history

  1. Received: January 18, 2019
  2. Accepted: September 29, 2019
  3. Accepted Manuscript published: September 30, 2019 (version 1)
  4. Version of Record published: November 12, 2019 (version 2)

Copyright

© 2019, Haraguchi 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

  • 1,878
    Page views
  • 270
    Downloads
  • 15
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

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)

  1. Shogo Haraguchi
  2. Masaki Kamata
  3. Takuma Tokita
  4. Kei-ichiro Tashiro
  5. Miku Sato
  6. Mitsuki Nozaki
  7. Mayumi Okamoto-Katsuyama
  8. Isao Shimizu
  9. Guofeng Han
  10. Vishwajit Sur Chowdhury
  11. Xiao-Feng Lei
  12. Takuro Miyazaki
  13. Joo-ri Kim-Kaneyama
  14. Tomoya Nakamachi
  15. Kouhei Matsuda
  16. Hirokazu Ohtaki
  17. Toshinobu Tokumoto
  18. Tetsuya Tachibana
  19. Akira Miyazaki
  20. Kazuyoshi Tsutsui
(2019)
Light-at-night exposure affects brain development through pineal allopregnanolone-dependent mechanisms
eLife 8:e45306.
https://doi.org/10.7554/eLife.45306

Further reading

    1. Neuroscience
    Jan Boelts et al.
    Research Advance Updated

    Inferring parameters of computational models that capture experimental data are a central task in cognitive neuroscience. Bayesian statistical inference methods usually require the ability to evaluate the likelihood of the model—however, for many models of interest in cognitive neuroscience, the associated likelihoods cannot be computed efficiently. Simulation-based inference (SBI) offers a solution to this problem by only requiring access to simulations produced by the model. Previously, Fengler et al. introduced likelihood approximation networks (LANs, Fengler et al., 2021) which make it possible to apply SBI to models of decision-making, but require billions of simulations for training. Here, we provide a new SBI method that is substantially more simulation efficient. Our approach, mixed neural likelihood estimation (MNLE), trains neural density estimators on model simulations to emulate the simulator, and is designed to capture both the continuous (e.g., reaction times) and discrete (choices) data of decision-making models. The likelihoods of the emulator can then be used to perform Bayesian parameter inference on experimental data using standard approximate inference methods like Markov Chain Monte Carlo sampling. We demonstrate MNLE on two variants of the drift-diffusion model and show that it is substantially more efficient than LANs: MNLE achieves similar likelihood accuracy with six orders of magnitude fewer training simulations, and is significantly more accurate than LANs when both are trained with the same budget. Our approach enables researchers to perform SBI on custom-tailored models of decision-making, leading to fast iteration of model design for scientific discovery.

    1. Computational and Systems Biology
    2. Neuroscience
    Vasileios Dimakopoulos et al.
    Research Article

    The maintenance of items in working memory (WM) relies on a widespread network of cortical areas and hippocampus where synchronization between electrophysiological recordings reflects functional coupling. We investigated the direction of information flow between auditory cortex and hippocampus while participants heard and then mentally replayed strings of letters in WM by activating their phonological loop. We recorded local field potentials from the hippocampus, reconstructed beamforming sources of scalp EEG, and – additionally in four participants – recorded from subdural cortical electrodes. When analyzing Granger causality, the information flow was from auditory cortex to hippocampus with a peak in the [4 8] Hz range while participants heard the letters. This flow was subsequently reversed during maintenance while participants maintained the letters in memory. The functional interaction between hippocampus and the cortex and the reversal of information flow provide a physiological basis for the encoding of memory items and their active replay during maintenance.