Literature DB >> 15517975

Proteomic analyses using an accurate mass and time tag strategy.

Ljiljana Pasa-Tolić1, Christophe Masselon, Richard C Barry, Yufeng Shen, Richard D Smith.   

Abstract

An accurate mass and time (AMT) tag approach for proteomic analyses has been developed over the past several years to facilitate comprehensive high-throughput proteomic measurements. An AMT tag database for an organism, tissue, or cell line is established by initially performing standard shotgun proteomic analysis and, most importantly, by validating peptide identifications using the mass measurement accuracy of Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) and liquid chromatography (LC) elution time constraint. Creation of an AMT tag database largely obviates the need for subsequent MS/MS analyses, and thus facilitates high-throughput analyses. The strength of this technology resides in the ability to achieve highly efficient and reproducible one-dimensional reversed-phased LC separations in conjunction with highly accurate mass measurements using FTICR MS. Recent improvements allow for the analysis of as little as picrogram amounts of proteome samples by minimizing sample handling and maximizing peptide recovery. The nanoproteomics platform has also demonstrated the ability to detect >10(6) differences in protein abundances and identify more abundant proteins from subpicogram amounts of samples. The AMT tag approach is poised to become a new standard technique for the in-depth and high-throughput analysis of complex organisms and clinical samples, with the potential to extend the analysis to a single mammalian cell.

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Year:  2004        PMID: 15517975     DOI: 10.2144/04374RV01

Source DB:  PubMed          Journal:  Biotechniques        ISSN: 0736-6205            Impact factor:   1.993


  51 in total

1.  Application of survival analysis methodology to the quantitative analysis of LC-MS proteomics data.

Authors:  Carmen D Tekwe; Raymond J Carroll; Alan R Dabney
Journal:  Bioinformatics       Date:  2012-05-24       Impact factor: 6.937

2.  Machine learning based prediction for peptide drift times in ion mobility spectrometry.

Authors:  Anuj R Shah; Khushbu Agarwal; Erin S Baker; Mudita Singhal; Anoop M Mayampurath; Yehia M Ibrahim; Lars J Kangas; Matthew E Monroe; Rui Zhao; Mikhail E Belov; Gordon A Anderson; Richard D Smith
Journal:  Bioinformatics       Date:  2010-05-21       Impact factor: 6.937

3.  Proteomic profiling of a layered tissue reveals unique glycolytic specializations of photoreceptor cells.

Authors:  Boris Reidel; J Will Thompson; Sina Farsiu; M Arthur Moseley; Nikolai P Skiba; Vadim Y Arshavsky
Journal:  Mol Cell Proteomics       Date:  2010-12-20       Impact factor: 5.911

4.  DeMix-Q: Quantification-Centered Data Processing Workflow.

Authors:  Bo Zhang; Lukas Käll; Roman A Zubarev
Journal:  Mol Cell Proteomics       Date:  2016-01-04       Impact factor: 5.911

5.  Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification.

Authors:  Chad R Weisbrod; Jimmy K Eng; Michael R Hoopmann; Tahmina Baker; James E Bruce
Journal:  J Proteome Res       Date:  2012-02-21       Impact factor: 4.466

Review 6.  New mass spectrometry technologies contributing towards comprehensive and high throughput omics analyses of single cells.

Authors:  Sneha P Couvillion; Ying Zhu; Gabe Nagy; Joshua N Adkins; Charles Ansong; Ryan S Renslow; Paul D Piehowski; Yehia M Ibrahim; Ryan T Kelly; Thomas O Metz
Journal:  Analyst       Date:  2019-01-28       Impact factor: 4.616

7.  A proteomic study of the HUPO Plasma Proteome Project's pilot samples using an accurate mass and time tag strategy.

Authors:  Joshua N Adkins; Matthew E Monroe; Kenneth J Auberry; Yufeng Shen; Jon M Jacobs; David G Camp; Frank Vitzthum; Karin D Rodland; Richard C Zangar; Richard D Smith; Joel G Pounds
Journal:  Proteomics       Date:  2005-08       Impact factor: 3.984

8.  Application of the accurate mass and time tag approach to the proteome analysis of sub-cellular fractions obtained from Rhodobacter sphaeroides 2.4.1. Aerobic and photosynthetic cell cultures.

Authors:  Stephen J Callister; Miguel A Dominguez; Carrie D Nicora; Xiaohua Zeng; Christine L Tavano; Samuel Kaplan; Timothy J Donohue; Richard D Smith; Mary S Lipton
Journal:  J Proteome Res       Date:  2006-08       Impact factor: 4.466

Review 9.  Advances in proteomics data analysis and display using an accurate mass and time tag approach.

Authors:  Jennifer S D Zimmer; Matthew E Monroe; Wei-Jun Qian; Richard D Smith
Journal:  Mass Spectrom Rev       Date:  2006 May-Jun       Impact factor: 10.946

10.  Characterization of strategies for obtaining confident identifications in bottom-up proteomics measurements using hybrid FTMS instruments.

Authors:  Aleksey V Tolmachev; Matthew E Monroe; Samuel O Purvine; Ronald J Moore; Navdeep Jaitly; Joshua N Adkins; Gordon A Anderson; Richard D Smith
Journal:  Anal Chem       Date:  2008-10-15       Impact factor: 6.986

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