Literature DB >> 26519184

Dissecting the iTRAQ Data Analysis.

Suruchi Aggarwal1, Amit Kumar Yadav2.   

Abstract

In the era of large-scale quantitative biology, mass spectrometry-based quantitative proteomics is progressively becoming indispensable for gaining insights into the biological systems at molecular level. Various quantitative study designs rely on chemical tagging approaches to study disease, stress, or drug response and temporal studies aiming at disease/developmental progression in a biological system. Isobaric tags for relative and absolute quantitation (iTRAQ) is one of the most popular chemical labeling techniques which allows four, six, or eight samples to be multiplexed in a single run. As the iTRAQ tag has a balancer group to equalize all states of a labeled peptide to same mass, the differentially labeled iTRAQ peptides are mixed before chromatography and elute as a single combined peak in MS. This enhances the peptide signal and quantitation is performed during MS/MS along with sequencing, where reporter ions of different masses are released to give relative quantitation. Known amount of a spiked-in protein can also help in absolute quantitation of the proteins in a sample.

Keywords:  Chemical labeling; Quantitative proteomics; Relative protein quantitation; Statistics; iTRAQ

Mesh:

Substances:

Year:  2016        PMID: 26519184     DOI: 10.1007/978-1-4939-3106-4_18

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


  8 in total

1.  Studying Autophagy Using a TMT-Based Quantitative Proteomics Approach.

Authors:  Kiran Bala Sharma; Suruchi Aggarwal; Amit Kumar Yadav; Sudhanshu Vrati; Manjula Kalia
Journal:  Methods Mol Biol       Date:  2022

2.  iTRAQ-Based Quantitative Proteomic Analysis of Intestines in Murine Polymicrobial Sepsis with Hydrogen Gas Treatment.

Authors:  Yi Jiang; Yingxue Bian; Naqi Lian; Yaoqi Wang; Keliang Xie; Chao Qin; Yonghao Yu
Journal:  Drug Des Devel Ther       Date:  2020-11-12       Impact factor: 4.162

3.  HyperQuant-A Computational Pipeline for Higher Order Multiplexed Quantitative Proteomics.

Authors:  Suruchi Aggarwal; Ajay Kumar; Shilpa Jamwal; Mukul Kumar Midha; Narayan Chandra Talukdar; Amit Kumar Yadav
Journal:  ACS Omega       Date:  2020-05-07

Review 4.  Quantitative Proteomics Using Isobaric Labeling: A Practical Guide.

Authors:  Xiulan Chen; Yaping Sun; Tingting Zhang; Lian Shu; Peter Roepstorff; Fuquan Yang
Journal:  Genomics Proteomics Bioinformatics       Date:  2022-01-08       Impact factor: 6.409

5.  Dataset generated using hyperplexing and click chemistry to monitor temporal dynamics of newly synthesized macrophage secretome post infection by mycobacterial strains.

Authors:  Ajay Kumar; Shilpa Jamwal; Mukul Kumar Midha; Baseerat Hamza; Suruchi Aggarwal; Amit Kumar Yadav; Kanury V S Rao
Journal:  Data Brief       Date:  2016-09-05

6.  Identification of Potential Biomarkers for Rhegmatogenous Retinal Detachment Associated with Choroidal Detachment by Vitreous iTRAQ-Based Proteomic Profiling.

Authors:  Zhifeng Wu; Nannan Ding; Mengxi Yu; Ke Wang; Shasha Luo; Wenjun Zou; Ying Zhou; Biao Yan; Qin Jiang
Journal:  Int J Mol Sci       Date:  2016-12-07       Impact factor: 5.923

7.  Adipose-Derived Mesenchymal Stem Cells Enhance Ovarian Cancer Growth and Metastasis by Increasing Thymosin Beta 4X-Linked Expression.

Authors:  Yijing Chu; Min You; Jingjing Zhang; Guoqiang Gao; Rendong Han; Wenqiang Luo; Tingting Liu; Jianxin Zuo; Fuling Wang
Journal:  Stem Cells Int       Date:  2019-10-20       Impact factor: 5.443

8.  iTRAQ-based proteomic analysis reveals key proteins affecting cardiac function in broilers that died of sudden death syndrome.

Authors:  Hongmei Ning; Yunli Cui; Xiaochao Song; Lingli Chen; Zhihong Yin; Liushuai Hua; Fei Ren; Yu Suo; Xinrui Wang; Hongli Zhang; Dongfang Hu; Yaming Ge
Journal:  Poult Sci       Date:  2019-12-01       Impact factor: 3.352

  8 in total

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