Literature DB >> 20058174

iTRAQ-based shotgun neuroproteomics.

Tong Liu1, Jun Hu, Hong Li.   

Abstract

Shotgun proteomics involves the analysis of <span class="Chemical">peptides obtained by enzymatic digestions of proteins and subsequent ide<span class="Chemical">ntification via tandem mass spectrometry. This approach is an effective method for studying global protein expression in neuronal systems. The method described here is a quantitative shotgun neuroproteomics method using amine-specific isobaric tags for a relative and absolute quantitation (iTRAQ)-based workflow. We will provide the technical details for sample preparation, two-dimensional liquid chromatography, tandem mass spectrometry, database search, and statistical analysis to identify differentially expressed proteins. We will use a recent study on a rat model of multiple sclerosis, experimental autoimmune encephalomyelitis to illustrate the successful application of this method.

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Year:  2009        PMID： 20058174      PMCID： PMC4640694          DOI： 10.1007/978-1-59745-562-6_14

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


  16 in total

Review 1.  Shotgun proteomics: tools for the analysis of complex biological systems.

Authors:  Christine C Wu; Michael J MacCoss
Journal:  Curr Opin Mol Ther       Date:  2002-06

2.  Protein labeling by iTRAQ: a new tool for quantitative mass spectrometry in proteome research.

Authors:  Sebastian Wiese; Kai A Reidegeld; Helmut E Meyer; Bettina Warscheid
Journal:  Proteomics       Date:  2007-02       Impact factor: 3.984

3.  Quantitative proteome analysis using isotope-coded affinity tags and mass spectrometry.

Authors:  Yuzuru Shiio; Ruedi Aebersold
Journal:  Nat Protoc       Date:  2006       Impact factor: 13.491

4.  Evaluation of multidimensional chromatography coupled with tandem mass spectrometry (LC/LC-MS/MS) for large-scale protein analysis: the yeast proteome.

Authors:  Junmin Peng; Joshua E Elias; Carson C Thoreen; Larry J Licklider; Steven P Gygi
Journal:  J Proteome Res       Date:  2003 Jan-Feb       Impact factor: 4.466

5.  Identification and quantification of basic and acidic proteins using solution-based two-dimensional protein fractionation and label-free or 18O-labeling mass spectrometry.

Authors:  Wells W Wu; Guanghui Wang; Ming-Jiun Yu; Mark A Knepper; Rong-Fong Shen
Journal:  J Proteome Res       Date:  2007-05-17       Impact factor: 4.466

6.  Post-translational modifications in the rat lumbar spinal cord in experimental autoimmune encephalomyelitis.

Authors:  Jennifer E Grant; Jun Hu; Tong Liu; Mohit R Jain; Stella Elkabes; Hong Li
Journal:  J Proteome Res       Date:  2007-06-13       Impact factor: 4.466

7.  Optimized proteomic analysis of a mouse model of cerebellar dysfunction using amine-specific isobaric tags.

Authors:  Jun Hu; Jin Qian; Oleg Borisov; Sanqiang Pan; Yan Li; Tong Liu; Longwen Deng; Kenneth Wannemacher; Michael Kurnellas; Christa Patterson; Stella Elkabes; Hong Li
Journal:  Proteomics       Date:  2006-08       Impact factor: 3.984

8.  Improved peak detection and quantification of mass spectrometry data acquired from surface-enhanced laser desorption and ionization by denoising spectra with the undecimated discrete wavelet transform.

Authors:  Kevin R Coombes; Spiridon Tsavachidis; Jeffrey S Morris; Keith A Baggerly; Mien-Chie Hung; Henry M Kuerer
Journal:  Proteomics       Date:  2005-11       Impact factor: 3.984

9.  iTRAQ is a useful method to screen for membrane-bound proteins differentially expressed in human natural killer cell types.

Authors:  Troy C Lund; Lorraine B Anderson; Valarie McCullar; Leeann Higgins; Gong H Yun; Bartek Grzywacz; Michael R Verneris; Jeffrey S Miller
Journal:  J Proteome Res       Date:  2007-02       Impact factor: 4.466

10.  i-Tracker: for quantitative proteomics using iTRAQ.

Authors:  Ian P Shadforth; Tom P J Dunkley; Kathryn S Lilley; Conrad Bessant
Journal:  BMC Genomics       Date:  2005-10-20       Impact factor: 3.969
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  7 in total

1.  Chronic exposure to light reverses the effect of maternal separation on proteins in the prefrontal cortex.

Authors:  J J Dimatelis; D J Stein; V A Russell
Journal:  J Mol Neurosci       Date:  2013-07-25       Impact factor: 3.444

Review 2.  Isobaric labeling-based relative quantification in shotgun proteomics.

Authors:  Navin Rauniyar; John R Yates
Journal:  J Proteome Res       Date:  2014-11-04       Impact factor: 4.466

3.  Quantitative proteomic analysis of sphere-forming stem-like oral cancer cells.

Authors:  Kaori Misuno; Xiaojun Liu; Sizhe Feng; Shen Hu
Journal:  Stem Cell Res Ther       Date:  2013       Impact factor: 6.832

4.  Neuroproteome changes after ischemia/reperfusion injury and tissue plasminogen activator administration in rats: a quantitative iTRAQ proteomics study.

Authors:  Zamir Merali; Meah MingYang Gao; Tim Bowes; Jian Chen; Kenneth Evans; Andrea Kassner
Journal:  PLoS One       Date:  2014-05-30       Impact factor: 3.240

5.  Quantitative Proteomic Analysis Reveals Molecular Adaptations in the Hippocampal Synaptic Active Zone of Chronic Mild Stress-Unsusceptible Rats.

Authors:  Jian Zhou; Zhao Liu; Jia Yu; Xin Han; Songhua Fan; Weihua Shao; Jianjun Chen; Rui Qiao; Peng Xie
Journal:  Int J Neuropsychopharmacol       Date:  2015-09-12       Impact factor: 5.176

6.  Plasma proteomics reveals coagulation, inflammation, and metabolic shifts in H-type hypertension patients with and without acute ischemic stroke.

Authors:  Feng Zhou; Lv Zhou; Tie Guo; Nianzhen Wang; Haizhen Hao; Yanhui Zhou; Dan Yu
Journal:  Oncotarget       Date:  2017-11-01

7.  iTRAQ-based quantitative proteomic analysis provides insight for molecular mechanism of neuroticism.

Authors:  Lei Tian; Hong-Zhao You; Hao Wu; Yu Wei; Min Zheng; Lei He; Jin-Ying Liu; Shu-Zhen Guo; Yan Zhao; Ren-Lai Zhou; Xingang Hu
Journal:  Clin Proteomics       Date:  2019-11-08       Impact factor: 3.988
  7 in total

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