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Landscape dynamic network biomarker analysis reveals the tipping point of transcriptome reprogramming to prevent skin photodamage
Chengming Zhang1,2,† , Hong Zhang3,† , Jing Ge1 , Tingyan Mi3 , Xiao Cui3 , Fengjuan Tu3 , Xuelan Gu3,* , Tao Zeng4,* , Luonan Chen1,5,6,7,*
1State 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
2University of the Chinese Academy of Sciences, Chinese Academy of Sciences, Beijing 100049, China
3Unilever Research & Development Centre Shanghai, Shanghai 200335, China
4Bio-Med Big Data Center, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
5School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
6Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou 310024, China
7Guangdong Institute of Intelligence Science and Technology, Zhuhai 519031, China
These authors contributed equally to this work.
*Correspondence to:Xuelan Gu , Email:Xuelan.Gu@unilever.com Tao Zeng , Email:zengtao@sibs.ac.cn Luonan Chen , Email:lnchen@sibs.ac.cn
J Mol Cell Biol, Volume 13, Issue 11, November 2021, 822-833,  https://doi.org/10.1093/jmcb/mjab060
Keyword: single-sample network, tipping point, UVB irradiation, living skin equivalent model, time series data, skin lightening

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.