基于iTRAQ 技术的脂多糖刺激下奶牛乳腺上皮细胞的蛋白组学分析

doi:10.11843/j.issn.0366-6964.2016.09.014

Abstract

Abstract:

The aim of the present study was to screen differential expression proteins associated with inflammatory model of bovine mammary epithelial cells (BMECs) induced by lipopolysaccharide (LPS) using isobaric tags for relative and absolute quantification (iTRAQ) combined with 2-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS).Normal and LPS-treated bovine mammary epithelial cells were analyzed using iTRAQ combined with 2D-LC-MS/MS.Bioinformatics analyses of differentially expressed proteins were performed by means of Gene Ontology and PPI (Protein protein interaction）analysis.According to iTRAQ results，a total of 2 487 proteins were identified.Compared with normal BMECs，163 proteins were significantly up-regulated while 178 proteins were significantly down-regulated in response to LPS treatment.The bioinformatics analyses highlighted the effects of LPS treatment on milk proteins and fat synthesis such as αs1-casein，κ-casein and fatty acid synthase.Down-regulation of αs1-casein (CSN1S1) in BMECs was confirmed by Western blotting；α_s1-casein，κ-casein (CSN3) and fatty acid synthase (FASN) in culture medium were confirmed by ELISA.The results showed that LPS treatment significantly decreased the expression of αs1-casein in BMECs (P<0.05)，and also decreased the concentration of α_s1-caseins，κ-casein and fatty acid synthase in culture medium (P<0.05).In conclusion，LPS treatment could affect the synthesis of protein and fat in BMECs.

Key words:
bovine, mammary epithelial cell, iTRAQ technique, proteomics, LPS

CLC Number:

S823.2

LI Lian，TANG Juan，WU Jie，WANG Gen-lin. Analysis of Expression Protein Profiles of Bovine Mammary Epithelial Cell Based on Isobaric Tag for Relative and Absolute Quantification Proteomics and Bioinformatics Technique[J]. ACTA VETERINARIA ET ZOOTECHNICA SINICA, 2016, 47(9): 1853-1860.

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Analysis of Expression Protein Profiles of Bovine Mammary Epithelial Cell Based on Isobaric Tag for Relative and Absolute Quantification Proteomics and Bioinformatics Technique

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