Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Metabolic regulation of dermal fibroblasts contributes to skin extracellular matrix homeostasis and fibrosis

Abstract

Extracellular matrix (ECM) homeostasis is essential for normal tissue function, and its disruption by iatrogenic injury, trauma, or disease results in fibrosis. Skin ECM homeostasis is maintained by a complex process that involves an integration of cytokine and environmental mediators. However, it is unclear, in both normal and disease states, how these multifactorial processes converge to shift ECM homeostasis towards accumulation or degradation. Here we show a consistent downregulation in fatty acid oxidation (FAO) and upregulation of glycolysis in fibrotic skin and in normal skin with abundant ECM. Perturbation of glycolysis and FAO pathway enzymes reveals their reciprocal effects in ECM upregulation and downregulation, respectively. Increasing peroxisome proliferator-activated receptor (PPAR) signalling, an inducer of the FAO pathway, generates a catabolic fibroblast phenotype characterised by inhibition of ECM transcription and enhanced ECM internalization and lysosomal degradation. In contrast, suppression of glycolysis inhibits ECM gene transcription and protein levels, independently of an intact FAO pathway or PPAR signalling. Moreover, we show that CD36, a multifunctional fatty acid transporter, connects the metabolic state of fibroblasts with their capacity for ECM regulation, as internalization and degradation of collagen-1 is abrogated in fibroblasts lacking CD36. Finally, restoring FAO and upregulating CD36 reduces ECM accumulation in murine skin fibrosis. These findings indicate that metabolic perturbation of ECM homeostasis may have broad implications for therapies aimed at ECM regulation, such as fibrosis, regenerative medicine, and ageing.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: ECM accumulation in normal and fibrotic skin corresponds to a shift in metabolism from FAO to glycolysis.
Fig. 2: Enhancing FAO induces a catabolic fibroblast that downregulates ECM transcription and enhances ECM degradation.
Fig. 3: CD36 is metabolically regulated in fibroblasts and crucial for collagen-1 degradation.
Fig. 4: Pharmacological and cellular therapy restores FAO in skin and reduces ECM accumulation.

Data availability

Transcriptomic data can be found on the National Center for Biotechnology Information (NCBI) gene expression omnibus (GEO) using ID GSE98157 for murine RNA-seq data and GSE98159 for human HT-12 array data. Software parameters have been uploaded onto Github: https://github.com/bhklab/SkinFibrosis. The data that support the plots within this paper and other findings of this study are available from the corresponding authors upon reasonable request.

References

  1. 1.

    Watt, F. M. Mammalian skin cell biology: at the interface between laboratory and clinic. Science 346, 937–940 (2014).

    CAS  Article  Google Scholar 

  2. 2.

    Vander Heiden, M. G., Cantley, L. C. & Thompson, C. B. Understanding the Warburg Effect: the metabolic requirements of cell proliferation. Science 324, 1029–1033 (2009).

  3. 3.

    Kelly, B. & O’Neill, L. A. Metabolic reprogramming in macrophages and dendritic cells in innate immunity. Cell Res. 25, 771–784 (2015).

    Article  Google Scholar 

  4. 4.

    Stone, H. B., Coleman, C. N., Anscher, M. S. & McBride, W. H. Effects of radiation on normal tissue: consequences and mechanisms. Lancet Oncol. 4, 529–536 (2003).

    CAS  Article  Google Scholar 

  5. 5.

    Mehta, A. S. & Blodgett, T. M. Retroperitoneal fibrosis as a cause of positive FDG PET/CT. J. Radiol. Case Rep. 5, 35–41 (2011).

  6. 6.

    Justet, A. et al. [18F]FDG PET/CT predicts progression-free survival in patients with idiopathic pulmonary fibrosis. Respir. Res. 18, 74 (2017).

    Article  Google Scholar 

  7. 7.

    Kok, H. M., Falke, L. L., Goldschmeding, R. & Nguyen, T. Q. Targeting CTGF, EGF and PDGF pathways to prevent progression of kidney disease. Nat. Rev. Nephrol. 10, 700–711 (2014).

    CAS  Article  Google Scholar 

  8. 8.

    Higgins, D. F. et al. Hypoxic induction of Ctgf is directly mediated by Hif-1. Am. J. Physiol. Ren. Physiol. 287, F1223–F1232 (2004).

    CAS  Article  Google Scholar 

  9. 9.

    Lamb, J. et al. The Connectivity Map: using gene-expression signatures to connect small molecules, genes, and disease. Science 313, 1929–1935 (2006).

    CAS  Article  Google Scholar 

  10. 10.

    Vanella, L. et al. Caffeic acid phenethyl ester regulates PPAR’s levels in stem cells-derived Adipocytes. PPAR Res. 2016, 7359521 (2016).

    Article  Google Scholar 

  11. 11.

    Isono, M., Chen, S., Hong, S. W., Iglesias-de la Cruz, M. C. & Ziyadeh, F. N. Smad pathway is activated in the diabetic mouse kidney and Smad3 mediates TGF-beta-induced fibronectin in mesangial cells. Biochem. Biophys. Res. Commun. 296, 1356–1365 (2002).

    CAS  Article  Google Scholar 

  12. 12.

    McCulloch, C. A. G. & Knowles, G. C. Deficiencies in collagen phagocytosis by human fibroblasts in vitro: a mechanism for fibrosis? J. Cell. Physiol. 155, 461–471 (1993).

    CAS  Article  Google Scholar 

  13. 13.

    Febbraio, M., Hajjar, D. P. & Silverstein, R. L. CD36: a class B scavenger receptor involved in angiogenesis, atherosclerosis, inflammation, and lipid metabolism. J. Clin. Invest. 108, 785–791 (2001).

    CAS  Article  Google Scholar 

  14. 14.

    Zhang, P., Tang, Y., Li, N.-G., Zhu, Y. & Duan, J.-A. Bioactivity and chemical synthesis of caffeic acid phenethyl ester and its derivatives. Molecules 19, 16458–16476 (2014).

    Article  Google Scholar 

  15. 15.

    Coburn, C. T. et al. Defective uptake and utilization of long chain fatty acids in muscle and adipose tissues of CD36 knockout mice. J. Biol. Chem. 275, 32523–32529 (2000).

    CAS  Article  Google Scholar 

  16. 16.

    Vincent, A. S. et al. Human skin keloid fibroblasts display bioenergetics of cancer cells. J. Invest. Dermatol. 128, 702–709 (2008).

    CAS  Article  Google Scholar 

  17. 17.

    Ring, A., Le Lay, S., Pohl, J., Verkade, P. & Stremmel, W. Caveolin-1 is required for fatty acid translocase (FAT/CD36) localization and function at the plasma membrane of mouse embryonic fibroblasts. Biochim. Biophys. Acta 1761, 416–423 (2006).

    CAS  Article  Google Scholar 

  18. 18.

    Del Galdo, F. et al. Decreased expression of caveolin 1 in patients with systemic sclerosis: crucial role in the pathogenesis of tissue fibrosis. Arthritis Rheum. 58, 2854–2865 (2008).

    Article  Google Scholar 

  19. 19.

    Castello-Cros, R. et al. Scleroderma-like properties of skin from caveolin-1-deficient mice: implications for new treatment strategies in patients with fibrosis and systemic sclerosis. Cell Cycle 10, 2140–2150 (2011).

    CAS  Article  Google Scholar 

  20. 20.

    Xie, N. et al. Glycolytic reprogramming in myofibroblast differentiation and lung fibrosis. Am. J. Respir. Crit. Care. Med. 192, 1462–1474 (2015).

    CAS  Article  Google Scholar 

  21. 21.

    Kang, H. M. et al. Defective fatty acid oxidation in renal tubular epithelial cells has a key role in kidney fibrosis development. Nat. Med. 21, 37–46 (2015).

    CAS  Article  Google Scholar 

  22. 22.

    Lovisa, S., Zeisberg, M. & Kalluri, R. Partial epithelial-to-mesenchymal transition and other new mechanisms of kidney fibrosis. Trends Endocrinol. Metab. 27, 681–695 (2016).

    CAS  Article  Google Scholar 

  23. 23.

    Stone, H. B. Leg contracture in mice: an assay of normal tissue response. Int. J. Radiat. Oncol. Biol. Phys. 10, 1053–1061 (1984).

    CAS  Article  Google Scholar 

  24. 24.

    Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 7, 562–578 (2012).

    CAS  Article  Google Scholar 

  25. 25.

    Dutta, T. et al. Concordance of changes in metabolic pathways based on plasma metabolomics and skeletal muscle transcriptomics in type 1 diabetes. Diabetes 61, 1004–1016 (2012).

    CAS  Article  Google Scholar 

  26. 26.

    Pfaffl, M. W. Relative expression software tool (REST(C)) for group-wise comparison and statistical analysis of relative expression results in real-time PCR. Nucleic Acids Res. 30, 36e–36e (2002).

    Article  Google Scholar 

  27. 27.

    Ran, F. A. et al. Genome engineering using the CRISPR-Cas9 system. Nat. Protoc. 8, 2281–2308 (2013).

    CAS  Article  Google Scholar 

  28. 28.

    Dennler, S. et al. Direct binding of Smad3 and Smad4 to critical TGF beta-inducible elements in the promoter of human plasminogen activator inhibitor-type 1 gene. EMBO J. 17, 3091–3100 (1998).

    CAS  Article  Google Scholar 

  29. 29.

    Khan, M. et al. mTORC2 controls cancer cell survival by modulating gluconeogenesis. Cell Death Discov. 1, 15016 (2015).

    CAS  Article  Google Scholar 

  30. 30.

    Jiang, P. et al. P53 regulates biosynthesis through direct inactivation of glucose-6-phosphate dehydrogenase. Nat. Cell Biol. 13, 310–316 (2011).

    CAS  Article  Google Scholar 

  31. 31.

    Irizarry, R. A. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics 4, 249–264 (2003).

    Article  Google Scholar 

  32. 32.

    Smirnov, P. et al. PharmacoGx: an R package for analysis of large pharmacogenomic datasets. Bioinformatics 32, 1244–1246 (2016).

    CAS  Article  Google Scholar 

  33. 33.

    Rousseeuw, P. J. Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. J. Comput. Appl. Math. 20, 53–65 (1987).

    Article  Google Scholar 

Download references

Acknowledgements

This research was funded by the Canadian Institutes of Health Research, the Canadian Cancer Society Research Institute, the Physicians Services Incorporated Foundation, the Harry Barbarian Research Grant, the Mariano Elia Chair in Head and Neck Cancer Research, the Campbell Family Institute for Cancer Research, the Ministry of Health and Long-Term Care, and the Princess Margaret Cancer Centre Head and Neck Translational Program, with philanthropic funding from the Wharton family and Joe’s Team.

Author information

Affiliations

Authors

Contributions

X.Z., L.S.G., K.Y., D.G., R.G., I.W., S.V.B., L.A., B.H.-K., and F.-F.L. participated in the research design. X.Z, P.P., .H.P., A.H., J.H.L., and J.W. conducted experiments. X.Z., L.S.G., L.A., B.H.-K. contributed new reagents or analytic tools. G.Z., L.S.G., P.P., H.P., A.H., J.H.L. and J.W. performed data analysis. X.Z., L.S.G., P.P., K.Y., D.G., R.G., S.V.B., L.A., B.H.-K., and F.-F.L. wrote or contributed to the writing of the manuscript.

Corresponding authors

Correspondence to Xiao Zhao or Fei-Fei Liu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Supplementary information

Supplementary Information

Supplementary Figures 1–35 and Supplementary Tables 1 and 2

Reporting Summary

Supplementary Dataset 1

qRT–PCR primers

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zhao, X., Psarianos, P., Ghoraie, L.S. et al. Metabolic regulation of dermal fibroblasts contributes to skin extracellular matrix homeostasis and fibrosis. Nat Metab 1, 147–157 (2019). https://doi.org/10.1038/s42255-018-0008-5

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing