Literature DB >> 17565973

Quantitative profile of five murine core proteomes using label-free functional proteomics.

Pedro R Cutillas1, Bart Vanhaesebroeck.   

Abstract

Analysis of primary animal and human tissues is key in biological and biomedical research. Comparative proteomics analysis of primary biological material would benefit from uncomplicated experimental work flows capable of evaluating an unlimited number of samples. In this report we describe the application of label-free proteomics to the quantitative analysis of five mouse core proteomes. We developed a computer program and normalization procedures that allow exploitation of the quantitative data inherent in LC-MS/MS experiments for relative and absolute quantification of proteins in complex mixtures. Important features of this approach include (i) its ability to compare an unlimited number of samples, (ii) its applicability to primary tissues and cultured cells, (iii) its straightforward work flow without chemical reaction steps, and (iv) its usefulness not only for relative quantification but also for estimation of absolute protein abundance. We applied this approach to quantitatively characterize the most abundant proteins in murine brain, heart, kidney, liver, and lung. We matched 8,800 MS/MS peptide spectra to 1,500 proteins and generated 44,000 independent data points to profile the approximately 1,000 most abundant proteins in mouse tissues. This dataset provides a quantitative profile of the fundamental proteome of a mouse, identifies the major similarities and differences between organ-specific proteomes, and serves as a paradigm of how label-free quantitative MS can be used to characterize the phenotype of mammalian primary tissues at the molecular level.

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Year:  2007        PMID: 17565973     DOI: 10.1074/mcp.M700037-MCP200

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  41 in total

1.  Specialized compartments of cardiac nuclei exhibit distinct proteomic anatomy.

Authors:  Sarah Franklin; Michael J Zhang; Haodong Chen; Anna K Paulsson; Scherise A Mitchell-Jordan; Yifeng Li; Peipei Ping; Thomas M Vondriska
Journal:  Mol Cell Proteomics       Date:  2010-08-31       Impact factor: 5.911

Review 2.  Overcoming key technological challenges in using mass spectrometry for mapping cell surfaces in tissues.

Authors:  Noelle M Griffin; Jan E Schnitzer
Journal:  Mol Cell Proteomics       Date:  2010-06-14       Impact factor: 5.911

3.  A self-validating quantitative mass spectrometry method for assessing the accuracy of high-content phosphoproteomic experiments.

Authors:  Pedro Casado; Pedro R Cutillas
Journal:  Mol Cell Proteomics       Date:  2010-10-24       Impact factor: 5.911

4.  Application of label-free quantitative peptidomics for the identification of urinary biomarkers of kidney chronic allograft dysfunction.

Authors:  Luis F Quintana; Josep M Campistol; Maria P Alcolea; Elisenda Bañon-Maneus; Amandaé Sol-González; Pedro R Cutillas
Journal:  Mol Cell Proteomics       Date:  2009-04-07       Impact factor: 5.911

5.  Maximizing peptide identification events in proteomic workflows using data-dependent acquisition (DDA).

Authors:  Nicholas W Bateman; Scott P Goulding; Nicholas J Shulman; Avinash K Gadok; Karen K Szumlinski; Michael J MacCoss; Christine C Wu
Journal:  Mol Cell Proteomics       Date:  2013-07-02       Impact factor: 5.911

6.  Targeting and imaging signature caveolar molecules in lungs.

Authors:  Kerri A Massey; Jan E Schnitzer
Journal:  Proc Am Thorac Soc       Date:  2009-08-15

7.  Isolation and proteomic analysis of the SYP61 compartment reveal its role in exocytic trafficking in Arabidopsis.

Authors:  Georgia Drakakaki; Wilhelmina van de Ven; Songqin Pan; Yansong Miao; Junqi Wang; Nana F Keinath; Brent Weatherly; Liwen Jiang; Karin Schumacher; Glenn Hicks; Natasha Raikhel
Journal:  Cell Res       Date:  2011-08-09       Impact factor: 25.617

8.  A straightforward and highly efficient precipitation/on-pellet digestion procedure coupled with a long gradient nano-LC separation and Orbitrap mass spectrometry for label-free expression profiling of the swine heart mitochondrial proteome.

Authors:  Xiaotao Duan; Rebeccah Young; Robert M Straubinger; Brian Page; Jin Cao; Hao Wang; Haoying Yu; John M Canty; Jun Qu
Journal:  J Proteome Res       Date:  2009-06       Impact factor: 4.466

9.  Proteomics and mass spectrometry: what have we learned about the heart?

Authors:  Shaan Chugh; Colin Suen; Anthony Gramolini
Journal:  Curr Cardiol Rev       Date:  2010-05

10.  Proteomic-based detection of a protein cluster dysregulated during cardiovascular development identifies biomarkers of congenital heart defects.

Authors:  Anjali K Nath; Michael Krauthammer; Puyao Li; Eugene Davidov; Lucas C Butler; Joshua Copel; Mikko Katajamaa; Matej Oresic; Irina Buhimschi; Catalin Buhimschi; Michael Snyder; Joseph A Madri
Journal:  PLoS One       Date:  2009-01-19       Impact factor: 3.240

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