Literature DB >> 26700038

Sample Preparation Approaches for iTRAQ Labeling and Quantitative Proteomic Analyses in Systems Biology.

Christos Spanos1, J Bernadette Moore2.   

Abstract

Among a variety of global quantification strategies utilized in mass spectrometry (MS)-based proteomics, isobaric tags for relative and absolute quantitation (iTRAQ) are an attractive option for examining the relative amounts of proteins in different samples. The inherent complexity of mammalian proteomes and the diversity of protein physicochemical properties mean that complete proteome coverage is still unlikely from a single analytical method. Numerous options exist for reducing protein sample complexity and resolving digested peptides prior to MS analysis. Indeed, the reliability and efficiency of protein identification and quantitation from an iTRAQ workflow strongly depend on sample preparation upstream of MS. Here we describe our methods for: (1) total protein extraction from immortalized cells; (2) subcellular fractionation of murine tissue; (3) protein sample desalting, digestion, and iTRAQ labeling; (4) peptide separation by strong cation-exchange high-performance liquid chromatography; and (5) peptide separation by isoelectric focusing.

Entities:  

Keywords:  High-performance liquid chromatography; Isoelectric focusing; Mass spectrometry; Proteomics; Subcellular fractionation; iTRAQ

Mesh:

Substances:

Year:  2016        PMID: 26700038     DOI: 10.1007/978-1-4939-3341-9_2

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  7 in total

1.  Quantitative iTRAQ proteomics reveal the proteome profiles of bone marrow mesenchymal stem cells after cocultures with Schwann cells in vitro.

Authors:  Han Ding; Ang Li; Chao Sun; Jianping Zhang; Jun Shang; Haoshuai Tang; Junjin Li; Min Wang; Xiaohong Kong; Zhijian Wei; Shiqing Feng
Journal:  Ann Transl Med       Date:  2022-09

2.  Integrated transcriptomic and proteomic analyses reveal ɑ-lipoic acid-regulated cell proliferation via Grb2-mediated signalling in hepatic cancer cells.

Authors:  Lan Yang; Xiliang Wang; Juan Xu; Ya Wen; Manqiao Zhang; Jingxiao Lu; Rongfu Wang; Xiaojuan Sun
Journal:  J Cell Mol Med       Date:  2018-03-25       Impact factor: 5.310

3.  Multi-scale, whole-system models of liver metabolic adaptation to fat and sugar in non-alcoholic fatty liver disease.

Authors:  Elaina M Maldonado; Ciarán P Fisher; Dawn J Mazzatti; Amy L Barber; Marcus J Tindall; Nicholas J Plant; Andrzej M Kierzek; J Bernadette Moore
Journal:  NPJ Syst Biol Appl       Date:  2018-08-20

4.  Proteomic analysis of differentially expressed proteins in the serum of patients with acute renal allograft rejection using iTRAQ labelling technology.

Authors:  Yue Zhang; Minglin Ou; Hua Lin; Liusheng Lai; Huaizhou Chen; Jiejing Chen; Weiguo Sui; Wen Xue; Ruohan Zhang; Qing Gan; Donge Tang; Xuyong Sun; Jianhui Dong; Qiang Yan; Yong Dai
Journal:  Mol Med Rep       Date:  2020-07-06       Impact factor: 2.952

5.  ITRAQ-Based Proteomics Analysis Reveals the Effect of Neoliensinine on KCl-Induced Vascular Smooth Muscle Contraction by Inhibiting Regulatory Light Chain Phosphorylation.

Authors:  Guang-Ming Yang; Ke Yan; Peng Wang; Jun-Li Zhang; Zi-Hao Pan; Yang Pan
Journal:  Front Pharmacol       Date:  2019-09-11       Impact factor: 5.810

6.  Proteomic identification and characterization of hepatic glyoxalase 1 dysregulation in non-alcoholic fatty liver disease.

Authors:  Christos Spanos; Elaina M Maldonado; Ciarán P Fisher; Petchpailin Leenutaphong; Ernesto Oviedo-Orta; David Windridge; Francisco J Salguero; Alexandra Bermúdez-Fajardo; Mark E Weeks; Caroline Evans; Bernard M Corfe; Naila Rabbani; Paul J Thornalley; Michael H Miller; Huan Wang; John F Dillon; Alberto Quaglia; Anil Dhawan; Emer Fitzpatrick; J Bernadette Moore
Journal:  Proteome Sci       Date:  2018-02-14       Impact factor: 2.480

7.  Identification of Candidate Biomarkers in Malignant Ascites from Patients with Hepatocellular Carcinoma by iTRAQ-Based Quantitative Proteomic Analysis.

Authors:  Jinyan Zhang; Rong Liang; Jiazhang Wei; Jiaxiang Ye; Qian He; Jiazhou Ye; Yongqiang Li; Zhihui Liu; Yan Lin
Journal:  Biomed Res Int       Date:  2018-09-23       Impact factor: 3.411

  7 in total

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