1. Cell Biology
Download icon

Impaired skeletal muscle mitochondrial pyruvate uptake rewires glucose metabolism to drive whole-body leanness

  1. Arpit Sharma
  2. Lalita Oonthonpan
  3. Ryan D Sheldon
  4. Adam J Rauckhorst
  5. Zhiyong Zhu
  6. Sean C Tompkins
  7. Kevin Cho
  8. Wojciech J Grzesik
  9. Lawrence R Gray
  10. Diego A Scerbo
  11. Alvin D Pewa
  12. Emily M Cushing
  13. Michael C Dyle
  14. James E Cox
  15. Chris Adams
  16. Brandon S Davies
  17. Richard K Shields
  18. Andrew W Norris
  19. Gary Patti
  20. Leonid V Zingman
  21. Eric B Taylor  Is a corresponding author
  1. University of Iowa, United States
  2. Washington University in St Louis, United States
  3. University of Utah, United States
Research Article
  • Cited 16
  • Views 3,990
  • Annotations
Cite this article as: eLife 2019;8:e45873 doi: 10.7554/eLife.45873

Abstract

Metabolic cycles are a fundamental element of cellular and organismal function. Among the most critical in higher organisms is the Cori Cycle, the systemic cycling between lactate and glucose. Here, skeletal muscle-specific Mitochondrial Pyruvate Carrier (MPC) deletion in mice diverted pyruvate into circulating lactate. This switch disinhibited muscle fatty acid oxidation and drove Cori Cycling that contributed to increased energy expenditure. Loss of muscle MPC activity led to strikingly decreased adiposity with complete muscle mass and strength retention. Notably, despite decreasing muscle glucose oxidation, muscle MPC disruption increased muscle glucose uptake and whole-body insulin sensitivity. Furthermore, chronic and acute muscle MPC deletion accelerated fat mass loss on a normal diet after high fat diet-induced obesity. Our results illuminate the role of the skeletal muscle MPC as a whole-body carbon flux control point. They highlight the potential utility of decreasing muscle pyruvate utilization to ameliorate obesity and type 2 diabetes.

Article and author information

Author details

  1. Arpit Sharma

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  2. Lalita Oonthonpan

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Ryan D Sheldon

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  4. Adam J Rauckhorst

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  5. Zhiyong Zhu

    Department of Internal Medicine, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  6. Sean C Tompkins

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  7. Kevin Cho

    Department of Chemistry, Washington University in St Louis, St. Louis, United States
    Competing interests
    The authors declare that no competing interests exist.

  8. Wojciech J Grzesik

    Fraternal Order of the Eagles Diabetes Research Center (FOEDRC), University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  9. Lawrence R Gray

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  10. Diego A Scerbo

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  11. Alvin D Pewa

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  12. Emily M Cushing

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9495-802X

  13. Michael C Dyle

    Department of Internal Medicine, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  14. James E Cox

    Department of Biochemistry, University of Utah, Salt Lake City, United States
    Competing interests
    The authors declare that no competing interests exist.

  15. Chris Adams

    Department of Internal Medicine, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  16. Brandon S Davies

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  17. Richard K Shields

    Department of Physical Therapy and Rehabilitation Science, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  18. Andrew W Norris

    Department of Biochemistry, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  19. Gary Patti

    FOEDRC Metabolomics Core Facility, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3748-6193

  20. Leonid V Zingman

    Department of Internal Medicine, University of Iowa, Iowa City, United States
    Competing interests
    The authors declare that no competing interests exist.

  21. Eric B Taylor

    Department of Biochemistry, University of Iowa, Iowa City, United States
    For correspondence
    eric-taylor@uiowa.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4549-6567

Funding

National Institutes of Health (DK104998)

  • Eric B Taylor

National Institutes of Health (GM007337)

  • Sean C Tompkins

National Institutes of Health (HL007638)

  • Adam J Rauckhorst

National Institutes of Health (DK101183)

  • Lawrence R Gray

American Diabetes Association (1-18-PDF-060)

  • Adam J Rauckhorst

National Institutes of Health (DK112751)

  • Diego A Scerbo

National Institutes of Health (AR059190)

  • Eric B Taylor

National Institutes of Health (HD084645)

  • Richard K Shields

National Institutes of Health (HD082109)

  • Richard K Shields

National Institutes of Health (DK092412)

  • Leonid V Zingman

National Institutes of Health (ES028365)

  • Gary Patti

National Institutes of Health (HL130146)

  • Brandon S Davies

National Institutes of Health (HL007344)

  • Ryan D Sheldon

National Institutes of Health (DK116522)

  • Ryan D Sheldon

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

Ethics

Animal experimentation: Animal work was performed in accordance with the University of Iowa Animal Use and Care Committee (IACUC). The University of Iowa IACUC is accredited by AALACi (#000833), is a Registered United States Department of Agriculture research facility (USDA No. 42-R-0004), and has PHS Approved Animal Welfare Assurance (#D16-00009).

Reviewing Editor

  1. David E James, The University of Sydney, Australia

Publication history

  1. Received: February 7, 2019
  2. Accepted: July 15, 2019
  3. Accepted Manuscript published: July 15, 2019 (version 1)
  4. Accepted Manuscript updated: July 18, 2019 (version 2)
  5. Version of Record published: August 6, 2019 (version 3)

Copyright

© 2019, Sharma 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

  • 3,990
    Page views
  • 692
    Downloads
  • 16
    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)

Categories and tags

Research organism

Further reading

    1. Biochemistry and Chemical Biology
    2. Cell Biology

    Complementary biosensors reveal different G-protein signaling modes triggered by GPCRs and non-receptor activators

    Mikel Garcia-Marcos
    Research Article Updated

    It has become evident that activation of heterotrimeric G-proteins by cytoplasmic proteins that are not G-protein-coupled receptors (GPCRs) plays a role in physiology and disease. Despite sharing the same biochemical guanine nucleotide exchange factor (GEF) activity as GPCRs in vitro, the mechanisms by which these cytoplasmic proteins trigger G-protein-dependent signaling in cells have not been elucidated. Heterotrimeric G-proteins can give rise to two active signaling species, Gα-GTP and dissociated Gβγ, with different downstream effectors, but how non-receptor GEFs affect the levels of these two species in cells is not known. Here, a systematic comparison of GPCRs and three unrelated non-receptor proteins with GEF activity in vitro (GIV/Girdin, AGS1/Dexras1, and Ric-8A) revealed high divergence in their contribution to generating Gα-GTP and free Gβγ in cells directly measured with live-cell biosensors. These findings demonstrate fundamental differences in how receptor and non-receptor G-protein activators promote signaling in cells despite sharing similar biochemical activities in vitro.

    1. Cell Biology
    2. Developmental Biology

    The recycling endosome protein Rab25 coordinates collective cell movements in the zebrafish surface epithelium

    Patrick Morley Willoughby et al.
    Research Article Updated

    In emerging epithelial tissues, cells undergo dramatic rearrangements to promote tissue shape changes. Dividing cells remain interconnected via transient cytokinetic bridges. Bridges are cleaved during abscission and currently, the consequences of disrupting abscission in developing epithelia are not well understood. We show that the Rab GTPase Rab25 localizes near cytokinetic midbodies and likely coordinates abscission through endomembrane trafficking in the epithelium of the zebrafish gastrula during epiboly. In maternal-zygotic Rab25a and Rab25b mutant embryos, morphogenic activity tears open persistent apical cytokinetic bridges that failed to undergo timely abscission. Cytokinesis defects result in anisotropic cell morphologies that are associated with a reduction of contractile actomyosin networks. This slows cell rearrangements and alters the viscoelastic responses of the tissue, all of which likely contribute to delayed epiboly. We present a model in which Rab25 trafficking coordinates cytokinetic bridge abscission and cortical actin density, impacting local cell shape changes and tissue-scale forces.

    1. Cell Biology
    2. Computational and Systems Biology

    Artistoo, a library to build, share, and explore simulations of cells and tissues in the web browser

    Inge M N Wortel, Johannes Textor
    Tools and Resources

    The Cellular Potts Model (CPM) is a powerful in silico method for simulating biological processes at tissue scale. Their inherently graphical nature makes CPMs very accessible in theory, but in practice, they are mostly implemented in specialised frameworks users need to master before they can run simulations. We here present Artistoo (Artificial Tissue Toolbox), a JavaScript library for building 'explorable' CPM simulations where viewers can change parameters interactively, exploring their effects in real time. Simulations run directly in the web browser and do not require third-party software, plugins, or back-end servers. The JavaScript implementation imposes no major performance loss compared to frameworks written in C++; Artistoo remains sufficiently fast for interactive, real time simulations. Artistoo provides an opportunity to unlock CPM models for a broader audience: Interactive simulations can be shared via a URL in a zero-install setting. We discuss applications in CPM research, science dissemination, open science, and education.