Study on the Application of iTRAQ Technology in Retinal Apoptosis Protein in Diabetic Retinopathy Mice

Abstract
Figure/Table
References
Related Citation (2)

Download: PDF (5816 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Objective: Using isobaric tags for relative and absolute quantitation(iTRAQ) technology to study differential protein expression in the retinal tissue of DR mouse models, providing proteomic evidence at the protein level for the pathogenesis of DR. Methods: Firstly, establish diabetic mice and DR mice models, use iTRAQ technology to detect the retinal tissue samples of normal control group and DR model group mice, label the total retinal proteins of mice with iTRAQ reagent, and analyze them using mass spectrometry technology. Evaluate the differential proteins of the two groups using BioWorks TM 3.0 software, and conduct interaction feature analysis on the different proteins using the STRING website. Results: The iTRAQ technology detected a total of 406 different proteins between the diabetes and normal control groups, with 19 of them closely related to retinal cell apoptosis. Among them, significantly different proteins include acyl-CoA dehydrogenase short chain specific(ACADS), ataxin-10(ATXN10), BCL-2-associated X protein(BAX), caspase-3(CASP3), collagen type II α1 chain(COL4A2), glycyl-tRNA synthetase(GARS), glial fibrillary acidic protein(GFAP), legumain(LGMN), mucin-4(MUC4), N-myc downstream-regulated gene 1 protein (NDRG1), with ratios to internal controls in the normal group of 1.67, 2.06, 1.76, 2.16, 1.53, 1.87, 1.24, 1.61, 0.42, 0.56, respectively; and there is a potential functional association between GFAP, CASP3, and BAX proteins. Conclusion: In DR mice retinas, there are abnormal changes in the expression of a large number of apoptosis-related proteins. iTRAQ technology can effectively screen out key apoptosis proteins, among which GFAP, CASP3, and BAX may have adverse effects on the progression of DR by participating in the apoptosis process. The application of iTRAQ technology can provide new technical support for proteomic research on apoptosis proteins.

Key words： diabetes retinopathy retinal apoptosis protein relative and absolute quantitation(iTRAQ) technology mice

Received: 23 August 2023

PACS:

R774.1

Corresponding Authors: LIU Bin. E-mail: 191084514@qq.com

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	QUE Li-dan
	LIN Yi-long
	QIU Xiu-ping
	LIU Bin

Cite this article:

QUE Li-dan,LIN Yi-long,QIU Xiu-ping, et al. Study on the Application of iTRAQ Technology in Retinal Apoptosis Protein in Diabetic Retinopathy Mice[J]. Chinese Journal of Biomedical Engineering, 2023, 32(4): 161-169.

URL:

http://manu32.magtech.com.cn/Jwk_zgswyx_en/EN/ OR http://manu32.magtech.com.cn/Jwk_zgswyx_en/EN/Y2023/V32/I4/161

[1] Ntentakis DP, Correa V, Ntentaki AM, et al.Effects of newer-generation anti-diabetics on diabetic retinopathy:a critical review[J]. Graefes Arch Clin Exp Ophthalmol, 2023,262(3):717-752.
[2] Huang ST, Bair PJ, Chang SS, et al.Risk of diabetic retinopathy in patients with type 2 diabetes after SGLT-2 inhibitors: A nationwide population cohort study[J]. Clin Pharmacol Ther, 2023,115(1):95-103.
[3] Liu YJ, Wang Y, Xu LX, et al.Relationship between dietary patterns and diabetic microvascular complications in patients with type 2 diabetes mellitus[J]. Eur Rev Med Pharmacol Sci, 2023,27(18):8780-8794.
[4] Zou Y, Li S, Chen W, et al.Urine-derived stem cell therapy for diabetes mellitus and its complications: progress and challenges[J]. Endocrine, 2023,83:270-284.
[5] Zhang W, He Y, Zhang Y.CircRNA in ocular neovascular diseases: Fundamental mechanism and clinical potential[J]. Pharmacol Res, 2023:106946.
[6] Hussein RM.Long non-coding RNAs: The hidden players in diabetes mellitus-related complications[J]. Diabetes Metab Syndr, 2023,17(10):102872.
[7] Yuan L, Zhang L, Liu X, et al.Identification of differential immune cells and related diagnostic genes in patients with diabetic retinopathy[J]. Medicine(Baltimore), 2023,102(39):e35331.
[8] Shao Chen, Sun Wei.Influences of protein databeses in proteomic identification[J]. Chinese Journal of Biomedical Engineering, 2013,32(2):129-134.
(邵晨, 孙伟. 蛋白质数据库对蛋白质组鉴定的影响[J]. 中国生物医学工程学报,2013,32(2):129-134.)
[9] You H, Li H, Gou W. lncRNA HOTAIR promotes ROS generation and NLRP3 inflammasome activation by inhibiting Nrf2 in diabetic retinopathy[J]. Medicine (Baltimore), 2023,102(37):e35155.
[10] Yu DQ, Yu SP, Wu J, et al.LIN28A attenuates high glucose-induced retinal pigmented epithelium injury through activating SIRT1-dependent autophagy[J]. Int J Ophthalmol, 2023,16(9):1465-1474.
[11] Ngo HL, Huynh TQ, Tran N, et al.Proteomic analysis of ceftazidime and meropenem-exposed Pseudomonas aeruginosa ATCC 9027[J]. Proteome Sci, 2023,21(1):15.
[12] Gao Y, Suding Z, Wang L, et al. iTRAQ-based proteomic analysis reveals invasion-related proteins among three developmental stages of Eimeria necatrix[J]. J Proteomics, 2023,283-284:104939.
[13] Yang X, Jiang Z, He J, et al.iTRAQ-based quantitative proteomics unveils protein dynamics in the root of solanum melongena L. under waterlogging stress conditions[J]. Life (Basel), 2023,13(6):1399.
[14] Wen DJ, Ren XJ, Dong LJ, et al.New exploration of treatment target for proliferative diabetic retinopathy based on iTRAQ LC-MS/MS Proteomics[J]. Zhonghua Yan Ke Za Zhi, 2019,55(10):769-776.
[15] Ge L, Huang P, Miao H, et al.The new landscape of differentially expression proteins in placenta tissues of gestational diabetes based on iTRAQ proteomics[J]. Placenta, 2023,131:36-48.
[16] Shen L, Zhao D, Chen Y, et al.Comparative proteomics analysis of serum proteins in gestational diabetes during early and middle stages of pregnancy[J]. Proteomics Clin Appl, 2019,13(5):e1800060.
[17] Yan X, Wu Y, Zhong F, et al.iTRAQ and PRM-based quantitative proteomics in T2DM-susceptible and -tolerant models of Bama mini-pig[J]. Gene, 2018,675:119-127.
[18] Shao M, Chen J, Zheng S.Comparative proteomics analysis of myocardium in mouse model of diabetic cardiomyopathy using the iTRAQ technique[J]. Adv Clin Exp Med, 2018,27(11):1469-1475.
[19] Wang Min, Yin Mei, Li Baoying, et al.Apoptosis-associated proteins analysis of apoptosis of retina cell in diabetic mice using isobaric tags for relative and absolute quantitation[J]. Chinese Journal of Geriatrics, 2014,33(6):661-664.
(王敏, 尹梅, 李保应,等. 同位素标记相对和绝对定量技术的糖尿病小鼠视网膜细胞凋亡蛋白研究[J]. 中华老年医学杂志,2014,33(6):661-664.)
[20] Li M, Ma M, Li L.Development of novel isobaric tags enables accurate and sensitive multiplexed proteomics using complementary ions[J]. Anal Bioanal Chem, 2023.
[21] Poljak A, Raftery M, Polly P.Evaluating cellular viability by iTRAQ proteomic profiling[J]. Methods Mol Biol, 2023,2644:193-209.
[22] Yang J, Yuan X, Hao Y, et al.Proteins in pregnant swine serum promote the African swine fever virus replication: an iTRAQ-based quantitative proteomic analysis[J]. Virol J, 2023,20(1):54.
[23] Zhou G, Ma S, Yang M, et al.global quantitative proteomics analysis reveals the downstream signaling networks of Msx1 and Msx2 in myoblast differentiation[J]. Phenomics, 2022,2(3):201-210.
[24] Liu Y, Li Z, Guo D, et al.iTRAQ-based proteomic analysis of 17β-Estradiol-induced anti-proliferation and apoptosis in mouse thymic epithelial cells by disturbing ribosomal biogenesis[J]. IUBMB Life, 2022,74(11):1094-1114.
[25] Sinha I, Fogle RL, Gulfidan G, et al.Potential early markers for breast cancer: A proteomic approach comparing saliva and serum samples in a pilot study[J]. Int J Mol Sci, 2023,24(4):4164.
[26] Totoń-Zurańska J, Balazova L, Krskova K, et al.Plasma proteome alterations in prediabetic, obese Zucker rats - possible cardiovascular risk implications[J]. Gen Physiol Biophys, 2022,41(6):549-558.