Literature DB >> 16037072

Characterization of mouse spleen cells by subtractive proteomics.

Francisco J Dieguez-Acuna1, Scott A Gerber, Shohta Kodama, Joshua E Elias, Sean A Beausoleil, Denise Faustman, Steven P Gygi.   

Abstract

Major analytical challenges encountered by shotgun proteome analysis include both the diversity and dynamic range of protein expression. Often new instrumentation can provide breakthroughs in areas where other analytical improvements have not been successful. In the current study, we utilized new instrumentation (LTQ FT) to characterize complex protein samples by shotgun proteomics. Proteomic analyses were performed on murine spleen tissue separated by magnetic beads into distinct CD45- and CD45+ cell populations. Using shotgun protein analysis we identified approximately 2,000 proteins per cell group by over 12,000 peptides with mass deviations of less than 4.5 ppm. Datasets obtained by LTQ FT analysis provided a significant increase in the number of proteins identified and greater confidence in those identifications and improved reproducibility in replicate analyses. Because CD45- and not CD45+ cells are able to regenerate functional pancreatic islet cells in a mouse model of type I diabetes, protein expression was further compared by a subtractive proteomic approach in search of an exclusive protein expression profile in CD45- cells. Characterization of the proteins exclusively identified in CD45- cells was performed using gene ontology terms via the Javascript GoMiner. The CD45- cell subset readily revealed proteins involved in development, suggesting the persistence of a fetal stem cell in an adult animal.

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Year:  2005        PMID: 16037072     DOI: 10.1074/mcp.M500137-MCP200

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


  23 in total

Review 1.  Generating and navigating proteome maps using mass spectrometry.

Authors:  Christian H Ahrens; Erich Brunner; Ermir Qeli; Konrad Basler; Ruedi Aebersold
Journal:  Nat Rev Mol Cell Biol       Date:  2010-10-14       Impact factor: 94.444

2.  Data analysis strategy for maximizing high-confidence protein identifications in complex proteomes such as human tumor secretomes and human serum.

Authors:  Huan Wang; Hsin-Yao Tang; Glenn C Tan; David W Speicher
Journal:  J Proteome Res       Date:  2011-10-18       Impact factor: 4.466

Review 3.  Advances and challenges in liquid chromatography-mass spectrometry-based proteomics profiling for clinical applications.

Authors:  Wei-Jun Qian; Jon M Jacobs; Tao Liu; David G Camp; Richard D Smith
Journal:  Mol Cell Proteomics       Date:  2006-08-03       Impact factor: 5.911

4.  Sub part-per-million mass accuracy by using stepwise-external calibration in fourier transform ion cyclotron resonance mass spectrometry.

Authors:  Richard L Wong; I Jonathan Amster
Journal:  J Am Soc Mass Spectrom       Date:  2006-08-24       Impact factor: 3.109

5.  Parts-per-billion mass measurement accuracy achieved through the combination of multiple linear regression and automatic gain control in a Fourier transform ion cyclotron resonance mass spectrometer.

Authors:  D Keith Williams; David C Muddiman
Journal:  Anal Chem       Date:  2007-06-01       Impact factor: 6.986

Review 6.  Accurate mass measurements in proteomics.

Authors:  Tao Liu; Mikhail E Belov; Navdeep Jaitly; Wei-Jun Qian; Richard D Smith
Journal:  Chem Rev       Date:  2007-07-25       Impact factor: 60.622

7.  A quantitative analysis software tool for mass spectrometry-based proteomics.

Authors:  Sung Kyu Park; John D Venable; Tao Xu; John R Yates
Journal:  Nat Methods       Date:  2008-03-16       Impact factor: 28.547

8.  Proteomics identifies multipotent and low oncogenic risk stem cells of the spleen.

Authors:  Francisco Dieguez-Acuña; Shohta Kodama; Yoshiaki Okubo; Ana Cristina Paz; Steven P Gygi; Denise L Faustman
Journal:  Int J Biochem Cell Biol       Date:  2009-12-18       Impact factor: 5.085

9.  Transcriptional interference among the murine beta-like globin genes.

Authors:  Xiao Hu; Susan Eszterhas; Nicolas Pallazzi; Eric E Bouhassira; Jennifer Fields; Osamu Tanabe; Scott A Gerber; Michael Bulger; James Douglas Engel; Mark Groudine; Steven Fiering
Journal:  Blood       Date:  2006-10-31       Impact factor: 22.113

10.  Salivary proteomics for oral cancer biomarker discovery.

Authors:  Shen Hu; Martha Arellano; Pinmanee Boontheung; Jianghua Wang; Hui Zhou; Jiang Jiang; David Elashoff; Roger Wei; Joseph A Loo; David T Wong
Journal:  Clin Cancer Res       Date:  2008-10-01       Impact factor: 12.531

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