Evidence map›Paper›PMID 23684622›Full record

ArticleCell metabolism2013

Dynamic adipocyte phosphoproteome reveals that Akt directly regulates mTORC2.

Sean J Humphrey, Guang Yang, Pengyi Yang, Daniel J Fazakerley, Jacqueline Stöckli, Jean Y Yang, David E James

Open access · hybridAbstract read
In one paragraph

Article in Cell metabolism, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 244 papers.

0numbers the graph read from it
0cells of the map it votes in
244citing papers in PubMed
15.7field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

244 citing papers in PubMed, 426 citations in OpenAlex.

  1. Review
  2. The role of mTORC2/RICTOR in immune cells and inflammatory diseases.Inflammation research : official journal of the European Histamine Research Society ... [et al.] · 2026
    Review
  3. Review
  4. Review
  5. Caveolae mechanics in cellular functions and disease.Nature reviews. Molecular cell biology · 2026
    Review
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  10. Review
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  14. Article
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  17. Sex-specific phosphoproteome responses to calorie restriction and insulin in skeletal muscle from older rats.The journals of gerontology. Series A, Biological sciences and medical sciences · 2025
    Article
  18. Article
  19. Article
  20. Article

184 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Sean J HumphreyDiabetes and Obesity Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia; Biological Mass Spectrometry Unit, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia.
Guang YangDiabetes and Obesity Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia.
Pengyi YangDiabetes and Obesity Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia; School of Mathematics and Statistics, University of Sydney, Camperdown, New South Wales 2006, Australia.
Daniel J FazakerleyDiabetes and Obesity Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia; Biological Mass Spectrometry Unit, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia.
Jacqueline StöckliDiabetes and Obesity Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia.
Jean Y YangSchool of Mathematics and Statistics, University of Sydney, Camperdown, New South Wales 2006, Australia.
David E JamesDiabetes and Obesity Program, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia; Biological Mass Spectrometry Unit, Garvan Institute of Medical Research, Darlinghurst, New South Wales 2010, Australia. Electronic address: d.james@garvan.org.au.
Garvan Institute of Medical Research · AUUniversity of Sydney · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A major challenge of the post-genomics era is to define the connectivity of protein phosphorylation networks. Here, we quantitatively delineate the insulin signaling network in adipocytes by high-resolution mass spectrometry-based proteomics. These data reveal the complexity of intracellular protein phosphorylation. We identified 37,248 phosphorylation sites on 5,705 proteins in this single-cell type, with approximately 15% responding to insulin. We integrated these large-scale phosphoproteomics data using a machine learning approach to predict physiological substrates of several diverse insulin-regulated kinases. This led to the identification of an Akt substrate, SIN1, a core component of the mTORC2 complex. The phosphorylation of SIN1 by Akt was found to regulate mTORC2 activity in response to growth factors, revealing topological insights into the Akt/mTOR signaling network. The dynamic phosphoproteome described here contains numerous phosphorylation sites on proteins involved in diverse molecular functions and should serve as a useful functional resource for cell biologists.

Indexed as

3T3 CellsAdaptor Proteins, Signal TransducingAdipocytesAnimalsCarrier ProteinsCell LineInsulinMass SpectrometryMechanistic Target of Rapamycin Complex 2MiceMultiprotein ComplexesPhosphatidylinositol 3-KinasesPhosphorylationProteomeProteomicsProto-Oncogene Proteins c-aktAdaptor Proteins, Signal TransducingCarrier ProteinsInsulinMapkap1 protein, mouseMechanistic Target of Rapamycin Complex 2Multiprotein ComplexesPhosphatidylinositol 3-KinasesProteomeProto-Oncogene Proteins c-aktTOR Serine-Threonine Kinases

Identifiers

PMID23684622
PMCPMC3690479
OpenAlexW2101771026

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.