Literature DB >> 16846381

Identification of differentiating neural progenitor cell markers using shotgun isobaric tagging mass spectrometry.

Kamran Salim1, Laura Kehoe, Marjorie S Minkoff, James G Bilsland, Ignacio Munoz-Sanjuan, Paul C Guest.   

Abstract

The use of neural precursor cells (NPCs) represents a promising repair strategy for many neurological disorders. This requires an understanding of the molecular events and biological features that regulate the self-renewal of NPCs and their differentiation into neurons, astrocytes, and oligodendendrocytes. In this study, we have characterized the proteomic changes that occur upon differentiation of these cells using the novel iTRAQ labeling chemistry for quantitative mass spectrometry. In total, 55 distinct proteins underwent expression changes during NPC differentiation. This included 14 proteins that were identified by our previous two-dimensional difference gel electrophoresis (2D-DIGE) analysis of differentiating mouse neurospheres. The importance of the iTRAQ approach was demonstrated by the identification of additional proteins that were not resolved by the 2D-DIGE technology. The proteins identified by the iTRAQ approach included growth factors, signaling molecules, proliferating cell-specific proteins, heat shock proteins, and other proteins involved in the regulation of metabolism and the transcriptional and translational machinery. Further characterization of the identified proteins should provide greater insight into the mechanisms involved in regulation of neurogenesis in the adult central nervous system and potentially that of other proliferating cell types, including peripheral stem cells or cancer cells.

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Year:  2006        PMID: 16846381     DOI: 10.1089/scd.2006.15.461

Source DB:  PubMed          Journal:  Stem Cells Dev        ISSN: 1547-3287            Impact factor:   3.272


  9 in total

1.  A statistical model for iTRAQ data analysis.

Authors:  Elizabeth G Hill; John H Schwacke; Susana Comte-Walters; Elizabeth H Slate; Ann L Oberg; Jeanette E Eckel-Passow; Terry M Therneau; Kevin L Schey
Journal:  J Proteome Res       Date:  2008-06-26       Impact factor: 4.466

Review 2.  Quantitative neuroproteomics: classical and novel tools for studying neural differentiation and function.

Authors:  Luca Colucci-D'Amato; Annarita Farina; Johannes P C Vissers; Angela Chambery
Journal:  Stem Cell Rev Rep       Date:  2011-03       Impact factor: 5.739

3.  Bayesian Analysis of iTRAQ Data with Nonrandom Missingness: Identification of Differentially Expressed Proteins.

Authors:  Ruiyan Luo; Christopher M Colangelo; William C Sessa; Hongyu Zhao
Journal:  Stat Biosci       Date:  2009-11

4.  Protein quantitation using iTRAQ: Review on the sources of variations and analysis of nonrandom missingness.

Authors:  Ruiyan Luo; Hongyu Zhao
Journal:  Stat Interface       Date:  2012-01-01       Impact factor: 0.582

5.  Quantitative proteomics of caveolin-1-regulated proteins: characterization of polymerase i and transcript release factor/CAVIN-1 IN endothelial cells.

Authors:  Alberto Dávalos; Carlos Fernández-Hernando; Grzegorz Sowa; Behrad Derakhshan; Michelle I Lin; Ji Y Lee; Hongyu Zhao; Ruiyan Luo; Christopher Colangelo; William C Sessa
Journal:  Mol Cell Proteomics       Date:  2010-06-28       Impact factor: 5.911

6.  Temporal analysis of neural differentiation using quantitative proteomics.

Authors:  Raghothama Chaerkady; Candace L Kerr; Arivusudar Marimuthu; Dhanashree S Kelkar; Manoj Kumar Kashyap; Marjan Gucek; John D Gearhart; Akhilesh Pandey
Journal:  J Proteome Res       Date:  2009-03       Impact factor: 4.466

7.  Quantitative comparison of IMAC and TiO2 surfaces used in the study of regulated, dynamic protein phosphorylation.

Authors:  Xiquan Liang; Geir Fonnum; Mahbod Hajivandi; Torkel Stene; Nini H Kjus; Erlend Ragnhildstveit; Joseph W Amshey; Paul Predki; R Marshall Pope
Journal:  J Am Soc Mass Spectrom       Date:  2007-08-14       Impact factor: 3.109

8.  The role of proteomics in depression research.

Authors:  Daniel Martins-de-Souza; Laura W Harris; Paul C Guest; Christoph W Turck; Sabine Bahn
Journal:  Eur Arch Psychiatry Clin Neurosci       Date:  2009-12-09       Impact factor: 5.270

9.  Mass spectrometry-based proteomics for the analysis of chromatin structure and dynamics.

Authors:  Monica Soldi; Alessandro Cuomo; Michael Bremang; Tiziana Bonaldi
Journal:  Int J Mol Sci       Date:  2013-03-06       Impact factor: 5.923

  9 in total

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