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The major cap-binding protein eIF4E regulates lipid homeostasis and diet-induced obesity

Nature Metabolism volume 3, pages 244–257 (2021)Cite this article

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Abstract

Obesity is a global epidemic leading to increased mortality and susceptibility to comorbidities, with few viable therapeutic interventions. A hallmark of disease progression is the ectopic deposition of lipids in the form of lipid droplets in vital organs such as the liver. However, the mechanisms underlying the dynamic storage and processing of lipids in peripheral organs remain an outstanding question. Here, we show an unexpected function for the major cap-binding protein, eIF4E, in high-fat-diet-induced obesity. In response to lipid overload, select networks of proteins involved in fat deposition are altered in eIF4E-deficient mice. Specifically, distinct messenger RNAs involved in lipid metabolic processing and storage pathways are enhanced at the translation level by eIF4E. Failure to translationally upregulate these mRNAs results in increased fatty acid oxidation, which enhances energy expenditure. We further show that inhibition of eIF4E phosphorylation genetically—and by a potent clinical compound—restrains weight gain following intake of a high-fat diet. Together, our study uncovers translational control of lipid processing as a driver of high-fat-diet-induced weight gain and provides a pharmacological target to treat obesity.

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Fig. 1: eIF4E is required for HFD-induced obesity.
Fig. 2: Fatty liver development and pathway analysis through eIF4E during HFD.
Fig. 3: Translational control through eIF4E regulates lipid-processing/storage proteins.
Fig. 4: Dynamic lipid storage in liver cells in relation to eIF4E activity.
Fig. 5: Increased mitochondrial activity and energy expenditure with reduced eIF4E.
Fig. 6: Pharmacological inhibition of eIF4E activity protects mice from diet-induced obesity and steatosis.

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Data availability

The mass spectrometry proteomics data have been deposited with the ProteomeXchange46 Consortium via the PRIDE partner repository with the dataset identifier PXD023440. The SwissProt database (SwissProt.2019.07.31) was used for mouse subset comparison of data. All remaining data are available within the manuscript and Supplementary information. eIF4E+/− mice can be made available following completion of a material agreement transfer with D.R. Further information and requests for resources should be directed to D.R. for fulfilment. Source data are provided with this paper.

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Acknowledgements

We thank members of the Ruggero laboratory for discussion, and the Mouse Pathology, Preclinical Therapeutics, and Biomedical Imaging Core facilities at UCSF for their assistance in our study. We thank J. Blecha at UCSF for synthesis of [18F]FTHA. We thank eFFECTOR Therapeutics for supplying eFT508. We thank the VUMC Hormone Assay & Analytical Services and Lipid Core and the Children’s Medical Center Research Institute at the University of Texas Southwestern Medical Center for performance and analysis of targeted metabolomics. Mass spectrometry was provided by the Mass Spectrometry Resource at UCSF (A.L. Burlingame, Director) supported by the Dr Miriam and Sheldon G. Adelson Medical Research Foundation and the UCSF Program for Breakthrough Biomedical Research. C.S.C. was funded by the American Cancer Society (no. PF-14-212-01-RMC). H.Y. is funded by the American Heart Association (no. P0540503). Y.O. is supported by the JSPS Overseas Research Fellowships. S.K. is supported by NIH (no. DK97441). D.R. is a Leukemia and Lymphoma Society Scholar. This research was funded by NIH grant nos. R01CA184624 (D.R.) and R35CA242986 (D.R.) and by the American Cancer Society RP-19-181-01-RMC (American Cancer Society Research Professor Award) (D.R.). The VUMC Cores are supported by NIH grant nos. DK059637 (MMPC) and DK020593 (DRTC).

Author information

Author notes

  1. Crystal S. Conn

    Present address: Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, USA

  2. These authors contributed equally: Crystal S. Conn, Haojun Yang.

Authors and Affiliations

  1. Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, CA, USA

    Crystal S. Conn, Haojun Yang, Harrison J. Tom, Alma L. Burlingame & Davide Ruggero

  2. School of Medicine and Department of Urology, University of California, San Francisco, CA, USA

    Crystal S. Conn, Haojun Yang, Harrison J. Tom & Davide Ruggero

  3. Diabetes Center, University of California, San Francisco, CA, USA

    Kenji Ikeda, Yasuo Oguri & Shingo Kajimura

  4. Department of Cell and Tissue Biology, University of California, San Francisco, CA, USA

    Kenji Ikeda, Yasuo Oguri & Shingo Kajimura

  5. Department of Pharmaceutical Chemistry, University of California, San Francisco, CA, USA

    Juan A. Oses-Prieto, Supna Nair & Alma L. Burlingame

  6. Children’s Research Institute and Department of Pediatrics, University of Texas Southwestern Medical Center, Dallas, TX, USA

    Hieu Vu & Ralph J. DeBerardinis

  7. Department of Pathology, University of California, San Francisco, CA, USA

    Ryan M. Gill

  8. Howard Hughes Medical Institute, UT Southwestern Medical Center, Dallas, TX, USA

    Ralph J. DeBerardinis

  9. Department of Cellular and Molecular Pharmacology, University of California, San Francisco, CA, USA

    Davide Ruggero

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Contributions

C.S.C., H.Y. and D.R. designed the experimental outline and wrote the manuscript. D.R. supervised the project. C.S.C., H.Y. and H.J.T. performed experiments. K.I., Y.O., H.V., S.N., J.A.O.-P., S.K., R.M.G., R.J.D. and A.L.B. assisted with experiments and analysis and provided research expertise.

Corresponding authors

Correspondence to Haojun Yang or Davide Ruggero.

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Competing interests

R.J.D. is an advisor for Agios Pharmaceuticals. D.R. is a shareholder of eFFECTOR Therapeutics, Inc. and a member of its scientific advisory board. Other authors declare no competing interests.

Additional information

Peer review information Nature Metabolism thanks Andrew Murray, Nahum Sonenberg and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: George Caputa.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 eIF4E dose does not influence growth, movement, or food intake.

a, Body weight for WT and eIF4E+/− C57BL/6 J male mice on regular chow diet for indicated durations (n = 20, 6, 3 for each genotype). Values represent the mean ± SEM, of independent biological replicates. b, Whole body fat percentage by Echo-MRI data of mice on regular diet (n = 6, 6). c, Monitored food intake of regular chow diet in mice over 24 hr (n = 6, 6). d, Monitored movement of mice on regular chow diet over 24 hr (n = 6, 6). Violin plots show all independent biological replicates with the median as a dotted black line and the upper and lower quartiles as light grey lines.

Extended Data Fig. 2 Metabolic hormones, fat tissue, adipogenesis and thermogenesis are not altered by eIF4E dose.

a, Leptin and other metabolic hormone concentrations in plasma of mice on labelled diets for 20 weeks (n = 4 for WT mice, n = 3 for eIF4E+/−). b, Indicated tissue weight relative to body weight per mouse; WAT is from perigonadal region (PGF). Violin plots show all independent biological replicates with the median as a dotted black line and the upper and lower quartiles as light grey lines. c, Representative images of H&E stained BAT and WAT from mice on HFD 20 weeks, (reviewed n = 4, 4 per tissue) WAT quantified in (d). Scale bar represents 100 um (BAT) and 200 um (WAT) . d, Lipid droplet quantification by size per mouse, left, and average across mice (n = 4, 4), right. e, Seeded inguinal (Ing) white adipocytes on day 0 of stimulating adipogenesis, day 4, and day 6 after oil red staining of lipids (repeated in triplicate per tissue, with biological replicates per genotype). Black scale bar represents 50 µm. f, Seeded brown adipose tissue (BAT) isolated adipocytes on day 0 of stimulating adipogenesis, day 4, and day 6 after oil red staining of lipids (repeated in triplicate per tissue, with biological replicates per genotype). Black scale bar represents 50 µm. g, Relative transcript levels in WAT tissue (n = 4, 3 of independent biological replicates with mean ± SEM). h, Representative immunoblots from BAT and WAT from mice on HFD 20 weeks, left, and quantification of UCP1 protein levels (n = 3, 3 of independent biological replicates with mean ± SEM), right. All values are taken of independent biological replicates, ns = P > 0.05, unpaired two-tailed Student’s t test.

Source data

Extended Data Fig. 3 Global protein synthesis remains unperturbed by eIF4E dose on HFD in liver tissue.

Representative polysome profiles from in vivo liver tissue from mice on HFD for 20 weeks.

Extended Data Fig. 4 eIF4E dose has select metabolic effects, altering lipolysis but not lipid uptake.

a, Relative proliferation at indicated time points in AML12 cells (n = 3, 3). Violin plots show all independent replicates with the median as a dotted black line and the upper and lower quartiles as light grey lines. b, Representative flow plots from AML12 cells stained with AnnexinV and PI, left, with relative viability quantified, right (n = 3, 3 independent replicates). c, Representative polysome profile from AML12 cells. d, Representative qPCR analysis of Plin2 mRNA isolated from sucrose gradient fractions of AML12WT and AML124e+/− cells treated with oleic acid for 4 hr. Values correspond to the percentage of total mRNA across the fractions with free ribosomal subunits correspond to fractions 3-5, 80 S monosome or low polysome fractions 6-10, and high polysomes within fractions 11-14 (n = 3, 3 technical replicates, mean ± SEM, *P < 0.05; ****P < 0.0001 by unpaired, two-tailed Student’s t test). e, qPCR analysis of Plin2 mRNA of AML12WT and AML124e+/− cells treated with oleic acid for 4 hours (n = 3, 3 independent replicates, mean ± SEM, ****P < 0.00004 unpaired, two-tailed Student’s t test). f, Representative qPCR analysis of β-actin mRNA isolated from sucrose gradient fractions (n = 3, 3 technical replicates).

Extended Data Fig. 5 Circulating lipids and 18F-FTHA lipid uptake into metabolic tissues.

a, Free fatty acids quantified in plasma from mice on 20 weeks HFD (n = 5 WT per diet, 3 eIF4E+/− per diet), mean ± SEM, comparison between Chow and HFD groups, *P < 0.013 by unpaired, two-tailed Student’s t test. b, Lipids quantified in plasma from mice on 20 weeks HFD (n = 5 WT per diet, 3 eIF4E+/− per diet), mean ± SEM, comparison on HFD LDL *P = 0.0317; comparison between Chow and HFD groups, ****P < 0.00005 by unpaired, two-tailed Student’s t test. c, 18F-FTHA expression in ROI drawn per tissue indicated (n = 1 per Chow mice as representative [based on maximum scan time for stability of isotope]; n = 3, 3 independent biological mice per experimental HFD group).

Extended Data Fig. 6 Metabolomics grouping by genotype highlighting top altered detected compounds.

a, Ortho PLS-DA plots each point represents an individual sample of mouse liver from 20 weeks on HFD, and how similar that sample is per all detected compounds compared to others run. eIF4E+/− liver samples clustered similar and separate from WT liver samples (n = 3, 5 respectively). b, Heatmap depicting the top 10% of metabolites increased or decreased across those detected (64/320). Lipids and carnitines showed strongest trend.

Extended Data Fig. 7 A decrease in eIF4E dose increases lipolysis and mitochondria numbers.

a, Relative glycerol released from cells after 3 hr as an index of lipolysis levels in AML12 cells in basal condition or with 100 μM isoproterenol stimulation (n = 3, 3 independent replicates per group), mean ± SEM, ns = P > 0.05; *P = 0.016; by two-way ANOVA. Glycerol levels were normalized by cell number. b, Relative mitochondria abundance. (n = 3, 3 independent replicates per group), mean ± SEM, ns = P > 0.05; *P = 0.043; by two-way ANOVA.

Extended Data Fig. 8 PPAR and FAO pathway expression is independent of eIF4E effects during HFD-induced obesity.

a, Heatmap of KEGG pathway proteins depicted relative expression color coded log2 (fold change) (Log2FC) across biological triplicates of WT and eIF4E+/− livers on HFD (n = 3 per group of independent biological replicates). b, qPCR analysis of relative mRNA levels of labelled transcripts in WT or eIF4E+/− (n = 4, 4 independent biological replicates, mean ± SD) liver on HFD for 20 weeks, β-actin was used as internal control. c, Representative immunoblots of targets from mass spectral analysis between diets and genotypes (validated in three or more independent biological replicates). d, Representative qPCR analysis of Scd1 isolated from sucrose gradient fractions of WT or eIF4E+/− liver on HFD. Values correspond to the percentage of total mRNA across the fractions where free ribosomal subunits correspond to lower fractions 1-5, 80 S monosome or low polysome fractions 6-10, and high polysomes within fractions 11-14 (n = 3, 3 technical replicates); mean ± SD, *P < 0.05; **P < 0.01; by unpaired two tailed Student’s t test. e, f, Whole-body oxygen consumption rate of WT and eIF4E+/− mice on HFD for three days per 12 hr cycle (n = 6, 6). Violin plots show all data points with a black dotted line indicating the median and light gray lines for the upper and lower quartiles; *P < 0.05; **P < 0.01; *** P < 0.005; ****P < 0.0001 by two-way ANOVA.

Source data

Extended Data Fig. 9 Genetic loss of eIF4E S209 or eFT508 treatment during HFD prevents weight gain in liver tissue.

a, Representative immunoblots for mTOR signaling. Same samples were loaded on two gels to capture large and small proteins (blots marked by vertical black line), left, and quantification, right, in indicated samples (n = 3 or more independent biological samples). Data represents mean ± SEM, *P = 0.019; ***P = 0.0002 by unpaired, two-tailed Student’s t test. b, Liver tissue or Brain (control tissue) weight from mice after 18 weeks on HFD with either Vehicle or eFT508 treatment (n = 3, 4 independent biological samples); mean ± SEM, ****P < 0.0001, unpaired, two-tailed Student’s t test. c, Food intake, average per day, per mouse on either Chow or HFD with Vehicle or eFT508 (n = 4, 4). d, qPCR analysis of relative mRNA levels of labelled transcripts in Vehicle or eFT508 treated (n = 3, 3) liver on HFD for 20 weeks, β-actin was used as internal control. e, Representative immunoblots between treatment, protein amount was quantified independently by Mass spectral analysis (n = 3, 3 independent biological replicates). f, Heatmap of depicted relative expression color coded log2 (fold change) (Log2FC) across independent biological samples from WT, eIF4E+/−, eIF4ES209A livers as labeled.

Source data

Supplementary information

Supplementary Information

Gating strategy for AML12 cells.

Reporting Summary

Supplementary Tables

Supplementary Tables 1–7. Supplementary Table 1. Proteins significantly upregulated in WT liver following HFD from TMT–MS; related to Fig. 2. Supplementary Table 2. Proteins altered by HFD in WT liver and limited by eIF4E during diet-induced obesity in liver from TMT–MS; related to Fig. 2. Supplementary Table 3. Functional annotation of gene set enrichment proteins altered by HFD in WT liver and significantly downregulated in eIF4E+/− liver; related to Fig. 2. Supplementary Table 4. Metabolites alerted by eIF4E dose in liver during HFD. Supplementary Table 5. Proteins in WT liver following HFD and significantly altered in liver from eIF4E+/– mice. Supplementary Table 6. Proteins altered by HFD in WT liver and limited by eIF4E and that were also downregulated with eFT508 treatment during diet-induced obesity, from TMT–MS; related to Fig. 6. Supplementary Table 7. Proteins altered by WT liver following HFD and significantly downregulated in liver from eIF4ES209A mice.

Source data

Source Data Fig. 2

Pathologist scoring in Excel format.

Source Data Fig. 3

Unprocessed immunoblots and/or gels.

Source Data Fig. 4

Unprocessed immunoblots and/or gels.

Source Data Fig. 5

Unprocessed immunoblots and/or gels.

Source Data Fig. 6

Unprocessed immunoblots and/or gels.

Source Data Extended Data Fig. 2

Unprocessed immunoblots and/or gels.

Source Data Extended Data Fig. 8

Unprocessed immunoblots and/or gels.

Source Data Extended Data Fig. 9

Unprocessed immunoblots and/or gels.

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Conn, C.S., Yang, H., Tom, H.J. et al. The major cap-binding protein eIF4E regulates lipid homeostasis and diet-induced obesity. Nat Metab 3, 244–257 (2021). https://doi.org/10.1038/s42255-021-00349-z

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