Literature DB >> 16889428

New algorithm for 15N/14N quantitation with LC-ESI-MS using an LTQ-FT mass spectrometer.

Victor P Andreev1, Lingyun Li, Tomas Rejtar, Qingbo Li, James G Ferry, Barry L Karger.   

Abstract

A new algorithm (QN) for the (15)N /(14)N quantitation of relative protein abundances in complex proteomic samples is described. QN takes advantage of the high resolution, mass accuracy and throughput of the hybrid mass spectrometer LTQ-FT MS. Peptide quantitation is based on MS peak intensity (measured in the FT MS), while peptide identification is performed in the MS/MS mode (measured in the LTQ linear ion trap). Accuracy of the protein abundance is enhanced by a novel scoring procedure, allowing filtering of less reliable measurements of peptide abundances. The performance of QN is illustrated in the relative quantitative analysis of M. acetivorans C2A cultures grown with carbon monoxide vs methanol as substrate. Roughly 1,000 proteins were quantitated with an average CV of 9% for the protein abundance ratios. QN performs quantitation without manual intervention, does not require high processing power, and generates files compatible with the Guidelines for Proteomic Data Publication.

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Year:  2006        PMID: 16889428     DOI: 10.1021/pr060105m

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  13 in total

1.  Protein turnover quantification in a multilabeling approach: from data calculation to evaluation.

Authors:  Christian Trötschel; Stefan P Albaum; Daniel Wolff; Simon Schröder; Alexander Goesmann; Tim W Nattkemper; Ansgar Poetsch
Journal:  Mol Cell Proteomics       Date:  2012-04-06       Impact factor: 5.911

2.  Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction.

Authors:  Magnus Palmblad; Davinia J Mills; Laurence V Bindschedler; Rainer Cramer
Journal:  J Am Soc Mass Spectrom       Date:  2007-07-26       Impact factor: 3.109

3.  Quantitative proteomics reveals a dynamic association of proteins to detergent-resistant membranes upon elicitor signaling in tobacco.

Authors:  Thomas Stanislas; David Bouyssie; Michel Rossignol; Simona Vesa; Jérôme Fromentin; Johanne Morel; Carole Pichereaux; Bernard Monsarrat; Françoise Simon-Plas
Journal:  Mol Cell Proteomics       Date:  2009-06-13       Impact factor: 5.911

4.  Find pairs: the module for protein quantification of the PeakQuant software suite.

Authors:  Martin Eisenacher; Michael Kohl; Sebastian Wiese; Romano Hebeler; Helmut E Meyer; Bettina Warscheid; Christian Stephan
Journal:  OMICS       Date:  2012-08-21

5.  Quantitative proteomic and microarray analysis of the archaeon Methanosarcina acetivorans grown with acetate versus methanol.

Authors:  Lingyun Li; Qingbo Li; Lars Rohlin; UnMi Kim; Kirsty Salmon; Tomas Rejtar; Robert P Gunsalus; Barry L Karger; James G Ferry
Journal:  J Proteome Res       Date:  2007-02       Impact factor: 4.466

6.  An unconventional pathway for reduction of CO2 to methane in CO-grown Methanosarcina acetivorans revealed by proteomics.

Authors:  Daniel J Lessner; Lingyun Li; Qingbo Li; Tomas Rejtar; Victor P Andreev; Matthew Reichlen; Kevin Hill; James J Moran; Barry L Karger; James G Ferry
Journal:  Proc Natl Acad Sci U S A       Date:  2006-11-13       Impact factor: 11.205

7.  Protein dynamics in iron-starved Mycobacterium tuberculosis revealed by turnover and abundance measurement using hybrid-linear ion trap-Fourier transform mass spectrometry.

Authors:  Prahlad K Rao; G Marcela Rodriguez; Issar Smith; Qingbo Li
Journal:  Anal Chem       Date:  2008-08-09       Impact factor: 6.986

Review 8.  Genomic and proteomic biomarkers for cancer: a multitude of opportunities.

Authors:  Michael A Tainsky
Journal:  Biochim Biophys Acta       Date:  2009-05-04

9.  A new algorithm using cross-assignment for label-free quantitation with LC-LTQ-FT MS.

Authors:  Victor P Andreev; Lingyun Li; Lei Cao; Ye Gu; Tomas Rejtar; Shiaw-Lin Wu; Barry L Karger
Journal:  J Proteome Res       Date:  2007-04-19       Impact factor: 4.466

10.  RAPID AND AUTOMATED PROCESSING OF MALDI-FTICR/MS DATA FOR N-METABOLIC LABELING IN A SHOTGUN PROTEOMICS ANALYSIS.

Authors:  Li Jing; I Jonathan Amster
Journal:  Int J Mass Spectrom       Date:  2009-10-15       Impact factor: 1.986

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