1. Genetics and Genomics
Download icon

Drosophila PDGF/VEGF signaling from muscles to hepatocyte-like cells protects against obesity

  1. Arpan C Ghosh  Is a corresponding author
  2. Sudhir Gopal Tattikota
  3. Yifang Liu
  4. Aram Comjean
  5. Yanhui Hu
  6. Victor Barrera
  7. Shannan J Ho Sui
  8. Norbert Perrimon  Is a corresponding author
  1. Blavatnik Institute, Harvard Medical School, United States
  2. Harvard T H Chan Bioinformatics Core, United States
Research Article
  • Cited 0
  • Views 470
  • Annotations
Cite this article as: eLife 2020;9:e56969 doi: 10.7554/eLife.56969

Abstract

PDGF/VEGF ligands regulate a plethora of biological processes in multicellular organisms via autocrine, paracrine and endocrine mechanisms. We investigated organ-specific metabolic roles of Drosophila PDGF/VEGF-like factors (Pvfs). We combine genetic approaches and single-nuclei sequencing to demonstrate that muscle-derived Pvf1 signals to the Drosophila hepatocyte-like cells/oenocytes to suppress lipid synthesis by activating the Pi3K/Akt1/TOR signaling cascade in the oenocytes. Functionally, this signaling axis regulates expansion of adipose tissue lipid stores in newly eclosed flies. Flies emerge after pupation with limited adipose tissue lipid stores and lipid level is progressively accumulated via lipid synthesis. We find that adult muscle-specific expression of pvf1 increases rapidly during this stage and that muscle-to-oenocyte Pvf1 signaling inhibits expansion of adipose tissue lipid stores as the process reaches completion. Our findings provide the first evidence in a metazoan of a PDGF/VEGF ligand acting as a myokine that regulates systemic lipid homeostasis by activating TOR in hepatocyte-like cells.

Article and author information

Author details

  1. Arpan C Ghosh

    Genetics, Blavatnik Institute, Harvard Medical School, Boston, United States
    For correspondence
    arpan_ghosh@hms.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6553-938X
  2. Sudhir Gopal Tattikota

    Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0318-5533
  3. Yifang Liu

    Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Aram Comjean

    Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Yanhui Hu

    Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Victor Barrera

    Biostatistics, Harvard T H Chan Bioinformatics Core, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0590-4634
  7. Shannan J Ho Sui

    Biostatistics, Harvard T H Chan Bioinformatics Core, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
  8. Norbert Perrimon

    Genetics, Blavatnik Institute, Harvard Medical School, Boston, United States
    For correspondence
    perrimon@genetics.med.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.

Funding

American Heart Association (18POST33990414)

  • Arpan C Ghosh

National Institute of Arthritis and Musculoskeletal and Skin Diseases (5RO1AR05735210)

  • Norbert Perrimon

National Institutes of Health (P01CA120964)

  • Norbert Perrimon

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

Reviewing Editor

  1. Tania Reis, Univ Colorado, Denver, United States

Publication history

  1. Received: April 6, 2020
  2. Accepted: October 26, 2020
  3. Accepted Manuscript published: October 27, 2020 (version 1)

Copyright

© 2020, Ghosh 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

  • 470
    Page views
  • 165
    Downloads
  • 0
    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)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

Further reading

    1. Genetics and Genomics
    Kaushik Renganaath et al.
    Research Article Updated

    Sequence variation in regulatory DNA alters gene expression and shapes genetically complex traits. However, the identification of individual, causal regulatory variants is challenging. Here, we used a massively parallel reporter assay to measure the cis-regulatory consequences of 5832 natural DNA variants in the promoters of 2503 genes in the yeast Saccharomyces cerevisiae. We identified 451 causal variants, which underlie genetic loci known to affect gene expression. Several promoters harbored multiple causal variants. In five promoters, pairs of variants showed non-additive, epistatic interactions. Causal variants were enriched at conserved nucleotides, tended to have low derived allele frequency, and were depleted from promoters of essential genes, which is consistent with the action of negative selection. Causal variants were also enriched for alterations in transcription factor binding sites. Models integrating these features provided modest, but statistically significant, ability to predict causal variants. This work revealed a complex molecular basis for cis-acting regulatory variation.

    1. Evolutionary Biology
    2. Genetics and Genomics
    Tom Hill, Robert L Unckless
    Research Article Updated

    Hosts and viruses are constantly evolving in response to each other: as a host attempts to suppress a virus, the virus attempts to evade and suppress the host’s immune system. Here, we describe the recurrent evolution of a virulent strain of a DNA virus, which infects multiple Drosophila species. Specifically, we identified two distinct viral types that differ 100-fold in viral titer in infected individuals, with similar differences observed in multiple species. Our analysis suggests that one of the viral types recurrently evolved at least four times in the past ~30,000 years, three times in Arizona and once in another geographically distinct species. This recurrent evolution may be facilitated by an effective mutation rate which increases as each prior mutation increases viral titer and effective population size. The higher titer viral type suppresses the host-immune system and an increased virulence compared to the low viral titer type.