Letter | Published:

mTOR controls mitochondrial oxidative function through a YY1–PGC-1α transcriptional complex

Nature volume 450, pages 736740 (29 November 2007) | Download Citation

Abstract

Transcriptional complexes that contain peroxisome-proliferator-activated receptor coactivator (PGC)-1α control mitochondrial oxidative function to maintain energy homeostasis in response to nutrient and hormonal signals1,2. An important component in the energy and nutrient pathways is mammalian target of rapamycin (mTOR), a kinase that regulates cell growth, size and survival3,4,5. However, it is unknown whether and how mTOR controls mitochondrial oxidative activities. Here we show that mTOR is necessary for the maintenance of mitochondrial oxidative function. In skeletal muscle tissues and cells, the mTOR inhibitor rapamycin decreased the gene expression of the mitochondrial transcriptional regulators PGC-1α, oestrogen-related receptor α and nuclear respiratory factors, resulting in a decrease in mitochondrial gene expression and oxygen consumption. Using computational genomics, we identified the transcription factor yin-yang 1 (YY1) as a common target of mTOR and PGC-1α. Knockdown of YY1 caused a significant decrease in mitochondrial gene expression and in respiration, and YY1 was required for rapamycin-dependent repression of those genes. Moreover, mTOR and raptor interacted with YY1, and inhibition of mTOR resulted in a failure of YY1 to interact with and be coactivated by PGC-1α. We have therefore identified a mechanism by which a nutrient sensor (mTOR) balances energy metabolism by means of the transcriptional control of mitochondrial oxidative function. These results have important implications for our understanding of how these pathways might be altered in metabolic diseases and cancer.

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Gene Expression Omnibus

Data deposits

Microarray data is available online through the Gene Expression Omnibus (GEO accession number GSE5332).

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Acknowledgements

We thank members of the Puigserver laboratory for helpful comments and discussions on this work; S.-H. Kim for technical assistance; M. Montminy for the anti-PGC-1α polyclonal antibody; D. Kwiatkowski for the TSC2-/- and TSC2+/+ murine embryonic fibroblasts; R. Abraham for the AU1-mTOR expression plasmid; and D. Sabatini for HA–raptor and Myc–rictor expression constructs. These studies were supported by a National Institutes of Health R21 grant (P.P.), a grant from the American Diabetes Association/Smith Family Foundation (V.K.M.) and a Burroughs Wellcome Career Award in the Biomedical Sciences (V.K.M.).

Author information

Affiliations

  1. Dana-Farber Cancer Institute and Department of Cell Biology, Harvard Medical School, Boston, Massachusetts 02115, USA

    • John T. Cunningham
    • , Joseph T. Rodgers
    • , Francisca Vazquez
    •  & Pere Puigserver
  2. Department of Cell Biology, Johns Hopkins University School of Medicine, Baltimore, Maryland 21205, USA

    • John T. Cunningham
    •  & Pere Puigserver
  3. Departments of Systems Biology and Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114, USA and Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts 02139, USA

    • Daniel H. Arlow
    •  & Vamsi K. Mootha

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Correspondence to Vamsi K. Mootha or Pere Puigserver.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Figures1-7 with Legends. A referenced Supplementary Methods are also contained as well as a list of oligonucleotide primers used in the text.

Excel files

  1. 1.

    Supplementary Table 1

    This file contains Supplementary Table 1 which is an Excel Spreadsheet of microarray data containing Affymetrix Probe Set ID, gene title, and expression values for 3 vehicle treated samples and 3 rapamycin treated samples.

  2. 2.

    Supplementary Table 2

    This file contains Supplementary Table 2 which is an Excel Spreadsheet of microarray data containing Affymetrix Probe Set ID, gene title, and expression values for 3 GFP-infected samples and 3 PGC-1α-infected samples.

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DOI

https://doi.org/10.1038/nature06322

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