Insulin signaling controls neurotransmission via the 4eBP-dependent modification of the exocytotic machinery

  1. Rebekah Elizabeth Mahoney
  2. Jorge Azpurua
  3. Benjamin Eaton  Is a corresponding author
  1. University of Texas Health Sciences Center at San Antonio, United States

Abstract

Altered insulin signaling has been linked to widespread nervous system dysfunction including cognitive dysfunction, neuropathy, and susceptibility to neurodegenerative disease. However, knowledge of the cellular mechanisms underlying the effects of insulin on neuronal function is incomplete. Here we show that cell autonomous insulin signaling within the Drosophila CM9 motor neuron regulates the release of neurotransmitter via alteration of the synaptic vesicle fusion machinery. This effect of insulin utilizes the FOXO-dependent regulation of the thor gene, which encodes the Drosophila homologue of the eif-4e binding protein (4eBP). A critical target of this regulatory mechanism is Complexin, a synaptic protein known to regulate synaptic vesicle exocytosis. We find that the amounts of Complexin protein observed at the synapse is regulated by insulin and genetic manipulations of Complexin levels support the model that increased synaptic Complexin reduces neurotransmission in response to insulin signaling.

Article and author information

Author details

  1. Rebekah Elizabeth Mahoney

    Department of Physiology, Barshop Institute for aging and longevity studies, University of Texas Health Sciences Center at San Antonio, San Antonio, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jorge Azpurua

    Department of Physiology, University of Texas Health Sciences Center at San Antonio, San Antonio, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Benjamin Eaton

    Department of Physiology, University of Texas Health Sciences Center at San Antonio, San Antonio, United States
    For correspondence
    eatonb@uthscsa.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9807-5566

Funding

National Institute on Aging (T32-AG021890)

  • Rebekah Elizabeth Mahoney

National Institutes of Health (NS062811)

  • Benjamin Eaton

Lawrence Ellison Foundation (AG-NS-0415-07)

  • Benjamin Eaton

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

Copyright

© 2016, Mahoney 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

  • 2,088
    views
  • 442
    downloads
  • 25
    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. Rebekah Elizabeth Mahoney
  2. Jorge Azpurua
  3. Benjamin Eaton
(2016)
Insulin signaling controls neurotransmission via the 4eBP-dependent modification of the exocytotic machinery
eLife 5:e16807.
https://doi.org/10.7554/eLife.16807

Share this article

https://doi.org/10.7554/eLife.16807

Further reading

    1. Neuroscience
    Kayson Fakhar, Fatemeh Hadaeghi ... Claus C Hilgetag
    Research Article

    Efficient communication in brain networks is foundational for cognitive function and behavior. However, how communication efficiency is defined depends on the assumed model of signaling dynamics, e.g., shortest path signaling, random walker navigation, broadcasting, and diffusive processes. Thus, a general and model-agnostic framework for characterizing optimal neural communication is needed. We address this challenge by assigning communication efficiency through a virtual multi-site lesioning regime combined with game theory, applied to large-scale models of human brain dynamics. Our framework quantifies the exact influence each node exerts over every other, generating optimal influence maps given the underlying model of neural dynamics. These descriptions reveal how communication patterns unfold if regions are set to maximize their influence over one another. Comparing these maps with a variety of brain communication models showed that optimal communication closely resembles a broadcasting regime in which regions leverage multiple parallel channels for information dissemination. Moreover, we found that the brain’s most influential regions are its rich-club, exploiting their topological vantage point by broadcasting across numerous pathways that enhance their reach even if the underlying connections are weak. Altogether, our work provides a rigorous and versatile framework for characterizing optimal brain communication, and uncovers the most influential brain regions, and the topological features underlying their influence.

    1. Neuroscience
    Poortata Lalwani, Thad Polk, Douglas D Garrett
    Research Article

    Moment-to-moment neural variability has been shown to scale positively with the complexity of stimulus input. However, the mechanisms underlying the ability to align variability to input complexity are unknown. Using a combination of behavioral methods, computational modeling, fMRI, MR spectroscopy, and pharmacological intervention, we investigated the role of aging and GABA in neural variability during visual processing. We replicated previous findings that participants expressed higher variability when viewing more complex visual stimuli. Additionally, we found that such variability modulation was associated with higher baseline visual GABA levels and was reduced in older adults. When pharmacologically increasing GABA activity, we found that participants with lower baseline GABA levels showed a drug-related increase in variability modulation while participants with higher baseline GABA showed no change or even a reduction, consistent with an inverted-U account. Finally, higher baseline GABA and variability modulation were jointly associated with better visual-discrimination performance. These results suggest that GABA plays an important role in how humans utilize neural variability to adapt to the complexity of the visual world.