High-fat diet enhances starvation-induced hyperactivity via sensitizing hunger-sensing neurons in Drosophila

  1. Rui Huang  Is a corresponding author
  2. Tingting Song
  3. Haifeng Su
  4. Zeliang Lai
  5. Wusa Qin
  6. Yinjun Tian
  7. Xuan Dong
  8. Liming Wang  Is a corresponding author
  1. Chongqing University, China
  2. Shenzhen Bay Laboratory, China
  3. Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, China
  4. Zhejiang University, China

Abstract

The function of the central nervous system to regulate food intake can be disrupted by sustained metabolic challenges such as high-fat diet (HFD), which may contribute to various metabolic disorders. Previously, we showed that a group of octopaminergic (OA) neurons mediated starvation-induced hyperactivity, an important aspect of food-seeking behavior (Yu et al., 2016). Here we find that HFD specifically enhances this behavior. Mechanistically, HFD increases the excitability of these OA neurons to a hunger hormone named adipokinetic hormone (AKH), via increasing the accumulation of AKH receptor (AKHR) in these neurons. Upon HFD, excess dietary lipids are transported by a lipoprotein LTP to enter these OA+AKHR+ neurons via the cognate receptor LpR1, which in turn suppresses autophagy-dependent degradation of AKHR. Taken together, we uncover a mechanism that links HFD, neuronal autophagy, and starvation-induced hyperactivity, providing insight in the reshaping of neural circuitry under metabolic challenges and the progression of metabolic diseases.

Data availability

Sequencing data have been deposited in GEO under accession codes GSE129601 and GSE129602.All behavioral data are uploaded in Supplementary Data File 1.Mass spectrometry data is updated in Supplementary Data File 2.

The following data sets were generated

Article and author information

Author details

  1. Rui Huang

    Chongqing University, Chongqing, China
    For correspondence
    huangrui85@cqu.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
  2. Tingting Song

    Shenzhen Bay Laboratory, Shenzhen, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Haifeng Su

    Institute of Neuroscience, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China
    Competing interests
    The authors declare that no competing interests exist.
  4. Zeliang Lai

    Shenzhen Bay Laboratory, Shenzhen, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Wusa Qin

    Shenzhen Bay Laboratory, Shenzhen, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Yinjun Tian

    Life Sciences Institute, Zhejiang University, Hangzhou, China
    Competing interests
    The authors declare that no competing interests exist.
  7. Xuan Dong

    Life Sciences Institute, Zhejiang University, Hangzhou, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Liming Wang

    Life Sciences Institute, Zhejiang University, Hangzhou, China
    For correspondence
    lmwang83@zju.edu.cn
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7256-8776

Funding

National Natural Science Foundation of China (31522026)

  • Liming Wang

National Natural Science Foundation of China (31800883)

  • Rui Huang

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

Copyright

© 2020, Huang 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

  • 4,984
    views
  • 788
    downloads
  • 41
    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. Rui Huang
  2. Tingting Song
  3. Haifeng Su
  4. Zeliang Lai
  5. Wusa Qin
  6. Yinjun Tian
  7. Xuan Dong
  8. Liming Wang
(2020)
High-fat diet enhances starvation-induced hyperactivity via sensitizing hunger-sensing neurons in Drosophila
eLife 9:e53103.
https://doi.org/10.7554/eLife.53103

Share this article

https://doi.org/10.7554/eLife.53103

Further reading

    1. Neuroscience
    Hannah Bos, Christoph Miehl ... Brent Doiron
    Research Article

    Synaptic inhibition is the mechanistic backbone of a suite of cortical functions, not the least of which are maintaining network stability and modulating neuronal gain. In cortical models with a single inhibitory neuron class, network stabilization and gain control work in opposition to one another – meaning high gain coincides with low stability and vice versa. It is now clear that cortical inhibition is diverse, with molecularly distinguished cell classes having distinct positions within the cortical circuit. We analyze circuit models with pyramidal neurons (E) as well as parvalbumin (PV) and somatostatin (SOM) expressing interneurons. We show how, in E – PV – SOM recurrently connected networks, SOM-mediated modulation can lead to simultaneous increases in neuronal gain and network stability. Our work exposes how the impact of a modulation mediated by SOM neurons depends critically on circuit connectivity and the network state.

    1. Immunology and Inflammation
    2. Neuroscience
    Jeremy M Shea, Saul A Villeda
    Research Article

    During aging, microglia – the resident macrophages of the brain – exhibit altered phenotypes and contribute to age-related neuroinflammation. While numerous hallmarks of age-related microglia have been elucidated, the progression from homeostasis to dysfunction during the aging process remains unresolved. To bridge this gap in knowledge, we undertook complementary cellular and molecular analyses of microglia in the mouse hippocampus across the adult lifespan and in the experimental aging model of heterochronic parabiosis. Single-cell RNA-Seq and pseudotime analysis revealed age-related transcriptional heterogeneity in hippocampal microglia and identified intermediate states of microglial aging that also emerge following heterochronic parabiosis. We tested the functionality of intermediate stress response states via TGFβ1 and translational states using pharmacological approaches in vitro to reveal their modulation of the progression to an activated state. Furthermore, we utilized single-cell RNA-Seq in conjunction with in vivo adult microglia-specific Tgfb1 conditional genetic knockout mouse models to demonstrate that microglia advancement through intermediate aging states drives transcriptional inflammatory activation and hippocampal-dependent cognitive decline.