Abstract

Forebrain precursor cells are dynamic during early brain development, yet the underlying molecular changes remain elusive. We observed major differences in transcriptional signatures of precursor cells from mouse forebrain at embryonic days E8.5 vs. E10.5 (before vs. after neural tube closure). Genes encoding protein biosynthetic machinery were strongly downregulated at E10.5. This was matched by decreases in ribosome biogenesis and protein synthesis, together with age-related changes in proteomic content of the adjacent fluids. Notably, c-MYC expression and mTOR pathway signaling were also decreased at E10.5, providing a potential driver for the effects on ribosome biogenesis and protein synthesis. Interference with c-MYC at E8.5 prematurely decreased ribosome biogenesis, while persistent c-MYC expression in cortical progenitors increased transcription of protein biosynthetic machinery and enhanced ribosome biogenesis, as well as enhanced progenitor proliferation leading to subsequent macrocephaly. These findings indicate large, coordinated changes in molecular machinery of forebrain precursors during early brain development.

Data availability

Sequencing data have been deposited in GEO under accession number GSE100421.

The following data sets were generated

Article and author information

Author details

  1. Kevin F Chau

    Department of Pathology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Morgan L Shannon

    Department of Pathology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Ryann M Fame

    Department of Pathology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8244-2624
  4. Erin Fonseca

    Department of Pathology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Hillary Mullan

    Department of Pathology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Matthew B Johnson

    Division of Genetics, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6909-5712
  7. Anoop K Sendamarai

    Department of Pathology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Mark W Springel

    Department of Pathology, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  9. Benoit Laurent

    Division of Newborn Medicine and Epigenetics Program, Department of Medicine, Boston Children's Hospital, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  10. Maria K Lehtinen

    Department of Pathology, Boston Children's Hospital, Boston, United States
    For correspondence
    maria.lehtinen@childrens.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7243-2967

Funding

National Science Foundation (Graduate Research Fellowship)

  • Kevin F Chau

National Institutes of Health (R01 NS088566)

  • Maria K Lehtinen

Pediatric Hydrocephalus Foundation (Research grant)

  • Maria K Lehtinen

Simons Foundation (SFARI Pilot Grant)

  • Maria K Lehtinen

New York Stem Cell Foundation (Robertson Investigator)

  • Maria K Lehtinen

National Institutes of Health (NIH T32 HL110852)

  • Kevin F Chau

National Institutes of Health (NIH T32 HL110852)

  • Ryann M Fame

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

Reviewing Editor

  1. Marianne Bronner, California Institute of Technology, United States

Ethics

Animal experimentation: All animal experimentation was carried out under protocols approved by the IACUC of Boston Children's Hospital (protocol number 17-10-3547R).

Version history

  1. Received: March 28, 2018
  2. Accepted: May 9, 2018
  3. Accepted Manuscript published: May 10, 2018 (version 1)
  4. Version of Record published: June 1, 2018 (version 2)

Copyright

© 2018, Chau 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

  • 5,287
    views
  • 742
    downloads
  • 70
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

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. Kevin F Chau
  2. Morgan L Shannon
  3. Ryann M Fame
  4. Erin Fonseca
  5. Hillary Mullan
  6. Matthew B Johnson
  7. Anoop K Sendamarai
  8. Mark W Springel
  9. Benoit Laurent
  10. Maria K Lehtinen
(2018)
Downregulation of ribosome biogenesis during early forebrain development
eLife 7:e36998.
https://doi.org/10.7554/eLife.36998

Share this article

https://doi.org/10.7554/eLife.36998

Further reading

    1. Neuroscience
    Mohsen Sadeghi, Reza Sharif Razavian ... Dagmar Sternad
    Research Article

    Natural behaviors have redundancy, which implies that humans and animals can achieve their goals with different strategies. Given only observations of behavior, is it possible to infer the control objective that the subject is employing? This challenge is particularly acute in animal behavior because we cannot ask or instruct the subject to use a particular strategy. This study presents a three-pronged approach to infer an animal’s control objective from behavior. First, both humans and monkeys performed a virtual balancing task for which different control strategies could be utilized. Under matched experimental conditions, corresponding behaviors were observed in humans and monkeys. Second, a generative model was developed that represented two main control objectives to achieve the task goal. Model simulations were used to identify aspects of behavior that could distinguish which control objective was being used. Third, these behavioral signatures allowed us to infer the control objective used by human subjects who had been instructed to use one control objective or the other. Based on this validation, we could then infer objectives from animal subjects. Being able to positively identify a subject’s control objective from observed behavior can provide a powerful tool to neurophysiologists as they seek the neural mechanisms of sensorimotor coordination.

    1. Neuroscience
    Yiyi Chen, Laimdota Zizmare ... Christoph Trautwein
    Research Article

    The retina consumes massive amounts of energy, yet its metabolism and substrate exploitation remain poorly understood. Here, we used a murine explant model to manipulate retinal energy metabolism under entirely controlled conditions and utilised 1H-NMR spectroscopy-based metabolomics, in situ enzyme detection, and cell viability readouts to uncover the pathways of retinal energy production. Our experimental manipulations resulted in varying degrees of photoreceptor degeneration, while the inner retina and retinal pigment epithelium were essentially unaffected. This selective vulnerability of photoreceptors suggested very specific adaptations in their energy metabolism. Rod photoreceptors were found to rely strongly on oxidative phosphorylation, but only mildly on glycolysis. Conversely, cone photoreceptors were dependent on glycolysis but insensitive to electron transport chain decoupling. Importantly, photoreceptors appeared to uncouple glycolytic and Krebs-cycle metabolism via three different pathways: (1) the mini-Krebs-cycle, fuelled by glutamine and branched chain amino acids, generating N-acetylaspartate; (2) the alanine-generating Cahill-cycle; (3) the lactate-releasing Cori-cycle. Moreover, the metabolomics data indicated a shuttling of taurine and hypotaurine between the retinal pigment epithelium and photoreceptors, likely resulting in an additional net transfer of reducing power to photoreceptors. These findings expand our understanding of retinal physiology and pathology and shed new light on neuronal energy homeostasis and the pathogenesis of neurodegenerative diseases.