Landscape dynamic network biomarker analysis reveals the tipping point of transcriptome reprogramming to prevent skin photodamage.

Chengming Zhang, Hong Zhang, Jing Ge, Tingyan Mi, Xiao Cui, Fengjuan Tu, Xuelan Gu, Tao Zeng, Luonan Chen
Author Information
  1. Chengming Zhang: State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China. ORCID
  2. Hong Zhang: Unilever Research & Development Centre Shanghai, Shanghai 200335, China.
  3. Jing Ge: State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China.
  4. Tingyan Mi: Unilever Research & Development Centre Shanghai, Shanghai 200335, China.
  5. Xiao Cui: Unilever Research & Development Centre Shanghai, Shanghai 200335, China.
  6. Fengjuan Tu: Unilever Research & Development Centre Shanghai, Shanghai 200335, China.
  7. Xuelan Gu: Unilever Research & Development Centre Shanghai, Shanghai 200335, China.
  8. Tao Zeng: Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  9. Luonan Chen: State Key Laboratory of Cell Biology, Shanghai Institute of Biochemistry and Cell Biology, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences, Shanghai 200031, China. ORCID

Abstract

Skin, as the outmost layer of human body, is frequently exposed to environmental stressors including pollutants and ultraviolet (UV), which could lead to skin disorders. Generally, skin response process to ultraviolet B (UVB) irradiation is a nonlinear dynamic process, with unknown underlying molecular mechanism of critical transition. Here, the landscape dynamic network biomarker (l-DNB) analysis of time series transcriptome data on 3D skin model was conducted to reveal the complicated process of skin response to UV irradiation at both molecular and network levels. The advanced l-DNB analysis approach showed that: (i) there was a tipping point before critical transition state during pigmentation process, validated by 3D skin model; (ii) 13 core DNB genes were identified to detect the tipping point as a network biomarker, supported by computational assessment; (iii) core DNB genes such as COL7A1 and CTNNB1 can effectively predict skin lightening, validated by independent human skin data. Overall, this study provides new insights for skin response to repetitive UVB irradiation, including dynamic pathway pattern, biphasic response, and DNBs for skin lightening change, and enables us to further understand the skin resilience process after external stress.

Keywords

References

  1. Natl Sci Rev. 2019 Jul;6(4):775-785 [PMID: 34691933]
  2. Mutat Res. 2005 Apr 1;571(1-2):153-73 [PMID: 15748645]
  3. Brief Bioinform. 2014 Mar;15(2):229-43 [PMID: 23620135]
  4. Sci Bull (Beijing). 2020 May 30;65(10):842-853 [PMID: 36659203]
  5. Sci Bull (Beijing). 2021 Nov 30;66(22):2265-2270 [PMID: 36654453]
  6. Phys Life Rev. 2021 Jul;37:103-107 [PMID: 33887574]
  7. Aging Cell. 2013 Aug;12(4):622-34 [PMID: 23590226]
  8. Cell Physiol Biochem. 2018;49(4):1492-1498 [PMID: 30205399]
  9. J Invest Dermatol. 2007 Nov;127(11):2585-95 [PMID: 17597826]
  10. Cancer Res. 2012 Dec 15;72(24):6382-92 [PMID: 23222305]
  11. Sci Rep. 2017 Feb 21;7:42990 [PMID: 28220902]
  12. Nucleic Acids Res. 2016 Dec 15;44(22):e164 [PMID: 27596597]
  13. PLoS One. 2009 Oct 30;4(10):e7651 [PMID: 19888454]
  14. Mol Cell. 2018 Nov 1;72(3):444-456.e7 [PMID: 30401431]
  15. J Invest Dermatol. 1997 Aug;109(2):187-93 [PMID: 9242506]
  16. Gut. 2016 Jul;65(7):1186-201 [PMID: 26860770]
  17. Sci Rep. 2018 May 31;8(1):8498 [PMID: 29855560]
  18. Med Res Rev. 2014 May;34(3):455-78 [PMID: 23775602]
  19. Sci Rep. 2012;2:342 [PMID: 22461973]
  20. Biogerontology. 2017 Aug;18(4):499-516 [PMID: 28702744]
  21. Int J Mol Sci. 2013 Jun 07;14(6):12222-48 [PMID: 23749111]
  22. Nat Commun. 2018 Feb 14;9(1):678 [PMID: 29445139]
  23. PLoS One. 2011;6(12):e29241 [PMID: 22195030]
  24. Am J Epidemiol. 2006 Jun 1;163(11):982-8 [PMID: 16624969]
  25. Genomics Proteomics Bioinformatics. 2020 Jun;18(3):256-270 [PMID: 32736037]
  26. FEBS J. 2013 Nov;280(22):5682-95 [PMID: 24107168]
  27. Toxicol Appl Pharmacol. 2013 Jun 1;269(2):89-99 [PMID: 23545178]
  28. Exp Dermatol. 2019 Jun;28(6):742-746 [PMID: 30339718]
  29. Methods. 2014 Jun 1;67(3):334-43 [PMID: 24561825]
  30. Biochim Biophys Acta. 2015 May;1849(5):506-16 [PMID: 24704206]
  31. Virchows Arch. 2019 May;474(5):539-550 [PMID: 30756182]
  32. Oxid Med Cell Longev. 2017;2017:6851464 [PMID: 29213352]
  33. J Transl Med. 2015 Jun 13;13:189 [PMID: 26070628]
  34. Brief Bioinform. 2020 Sep 25;21(5):1641-1662 [PMID: 31711128]
  35. Sci Rep. 2012;2:813 [PMID: 23230504]
  36. J Recept Signal Transduct Res. 2015;35(6):634-9 [PMID: 26498464]
  37. J Invest Dermatol. 2010 Jun;130(6):1685-96 [PMID: 20147966]
  38. J Invest Dermatol. 2011 Aug;131(8):1692-700 [PMID: 21562572]
  39. Clujul Med. 2016;89(1):72-81 [PMID: 27004028]

MeSH Term

Biomarkers
Collagen Type VII
Humans
Transcriptome

Chemicals

Biomarkers
COL7A1 protein, human
Collagen Type VII

Word Cloud

Created with Highcharts 10.0.0skinprocessnetworkresponseirradiationdynamictippingpointUVBbiomarkeranalysisdatamodellighteninghumanincludingultravioletUVmolecularcriticaltransitionl-DNBtimeseriestranscriptome3DvalidatedcoreDNBgenesSkinoutmostlayerbodyfrequentlyexposedenvironmentalstressorspollutantsleaddisordersGenerallyBnonlinearunknownunderlyingmechanismlandscapeconductedrevealcomplicatedlevelsadvancedapproachshowedthat:statepigmentationii13identifieddetectsupportedcomputationalassessmentiiiCOL7A1CTNNB1caneffectivelypredictindependentOverallstudyprovidesnewinsightsrepetitivepathwaypatternbiphasicDNBschangeenablesusunderstandresilienceexternalstressLandscaperevealsreprogrammingpreventphotodamagelivingequivalentsingle-sample

Similar Articles

Cited By