iTRAQ-based quantitative proteomic analysis and bioinformatics study of proteins in pterygia

被引:5
|
作者
Linghu, Dandan [1 ,2 ,3 ]
Guo, Lili [1 ,2 ,3 ]
Zhao, Yinghua [4 ]
Liu, Zhiming [1 ,2 ,3 ]
Zhao, Mingwei [1 ,2 ,3 ]
Huang, Lvzhen [1 ,2 ,3 ]
Li, Xiaoxin [1 ,2 ,3 ]
机构
[1] Peking Univ, Peoples Hosp, Dept Ophthalmol, Beijing, Peoples R China
[2] Minist Educ, Key Lab Vis Loss & Restorat, Beijing, Peoples R China
[3] Beijing Key Lab Diag & Therapy Retinal & Choroid, Beijing, Peoples R China
[4] Peking Univ, Sch Life Sci, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
CD34; GO analysis; iTRAQ analysis; MMP-10; Pterygia; Western-blot; SQUAMOUS-CELL CARCINOMA; GROWTH-FACTOR; MATRIX METALLOPROTEINASE-10; CONJUNCTIVAL AUTOGRAFT; BODY FIBROBLASTS; EXPRESSION; BINDING; MMP-10; OVEREXPRESSION; PATHOGENESIS;
D O I
10.1002/prca.201600094
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Purpose: To analyze proteins in the tissue of pterygia, and to investigate their potential roles in pterygia, using the comparative proteomic technique of Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) coupled with offline 2DLC-MS/MS, Western-bolt. Method: The tissue of pterygia and healthy conjunctiva was collected from 10 pterygia patients (6 females, 4 males; average age was 52 years old; average course of disease was 6 years) in our hospital from September, 2015 to March, 2016. iTRAQ was used to analyze proteins in the patients' pterygia and healthy conjunctiva. Proteins with a fold change of >2. 0 or <0. 5 were considered to be significantly differentially expressed (with corrected p-values of <0. 1). The identified proteins were subjected to subsequent gene ontology analysis using the DAVID database. Then we confirmed the targeted proteins with western-blot. Results: 156 proteins that expressed differently between the pterygia and healthy conjunctiva were identified using iTRAQ analysis. Of these proteins, 18 were down-regulated, and 138 were up-regulated. On the basis of biological processes in gene ontology, the identified proteins were mainly involved in cellular process, metabolic process, developmental process, location, cellular component organization, Among these proteins, matrix Metalloproteinase 10 (MMP-10) and CD34 may have potential roles in the pathogenesis of pterygia. Then we confirmed with Western-bolt that MMP-10 and CD34 were up-regulated in pterygia. Conclusion: This study is the first to identify 156 proteins associated with pterygia with iTRAQ technology. Data in our study will aid in providing a better understanding of pterygia.
引用
收藏
页数:7
相关论文
共 50 条
  • [41] iTRAQ-based quantitative proteomic analysis reveals metabolic changes in overwintering Scylla paramamosain at two different salinities
    Zhou, Junming
    Li, Na
    Wang, Huan
    Wang, Chunlin
    Mu, Changkao
    AQUACULTURE RESEARCH, 2021, 52 (08) : 3757 - 3770
  • [42] iTRAQ-Based Quantitative Proteomic Analysis of Chemically Induced Aquilaria sinensis Provides Insights into Agarwood Formation Mechanism
    Ye, Wei
    Zhang, Weimin
    Liu, Taomei
    Zhu, Muzhi
    Li, Saini
    Li, Haohua
    Huang, Zilei
    Gao, Xiaoxia
    PROTEOMICS, 2018, 18 (20)
  • [43] iTRAQ-Based Quantitative Proteomic Analysis of Pseudostellaria heterophylla from Geo-Authentic Habitat and Cultivated Bases
    Hua, Yujiao
    Wang, Chengcheng
    Wang, Shengnan
    Liu, Zixiu
    Liu, Xunhong
    Zou, Lisi
    Gu, Wei
    Luo, Yiyuan
    Liu, Juanxiu
    CURRENT PROTEOMICS, 2019, 16 (03) : 231 - 245
  • [44] iTRAQ-based quantitative proteomic analysis for identification of biomarkers associated with emodin against severe acute pancreatitis in rats
    Xiang, Hong
    Zhang, Qingkai
    Wang, Danqi
    Xia, Shilin
    Wang, Guijun
    Zhang, Guixin
    Chen, Hailong
    Wu, Yingjie
    Shang, Dong
    RSC ADVANCES, 2016, 6 (76): : 72447 - 72457
  • [45] iTRAQ-based proteomic analysis after mesenchymal stem cell line transplantation for ischemic stroke
    Mitaki, Shingo
    Nagai, Atsushi
    Wada, Yasuko
    Onoda, Keiichi
    Sheikh, Abdullah Md
    Adachi, Erika
    Matsumoto, Ken-ichi
    Yamaguchi, Shuhei
    BRAIN RESEARCH, 2020, 1742
  • [46] iTRAQ-based quantitative proteomic analysis of porcine uterine fluid during pre-implantation period of pregnancy
    He, Yanjuan
    Zang, Xupeng
    Kuang, Jingjing
    Yang, Huaqiang
    Gu, Ting
    Yang, Jie
    Li, Zicong
    Zheng, Enqin
    Xu, Zheng
    Cai, Gengyuan
    Wu, Zhenfang
    Hong, Linjun
    JOURNAL OF PROTEOMICS, 2022, 261
  • [47] iTRAQ-based proteomic analysis of the hippocampus of pentylenetetrazole-kindled epileptic rats
    Xu, Weiye
    Zhang, Siyuan
    Feng, Yanyan
    Zhang, Chen
    Xiao, Yeqing
    Tian, Fafa
    INTERNATIONAL JOURNAL OF DEVELOPMENTAL NEUROSCIENCE, 2021, 81 (02) : 125 - 141
  • [48] iTRAQ-based quantitative proteomic analysis in vernalization-treated faba bean (Vicia faba L.)
    Cao, Yun-Ying
    Bian, Xiao-Chun
    Chen, Mo-Xian
    Xia, Li-Ru
    Zhang, Jianhua
    Zhu, Fu-Yuan
    Wu, Chun-Fang
    PLOS ONE, 2017, 12 (11):
  • [49] iTRAQ-based comparative proteomic analysis of cells infected with Eimeria tenella sporozoites
    Zhao, Zongping
    Zhao, Qiping
    Zhu, Shunhai
    Huang, Bing
    Lv, Ling
    Chen, Ting
    Yan, Ming
    Han, Hongyu
    Dong, Hui
    PARASITE, 2019, 26
  • [50] Transcriptomic and iTRAQ-Based Quantitative Proteomic Analyses of inap CMS in Brassica napus L.
    Wang, Aifan
    Kang, Lei
    Yang, Guangsheng
    Li, Zaiyun
    PLANTS-BASEL, 2022, 11 (19):