Literature DB >> 17015437

Extent of modifications in human proteome samples and their effect on dynamic range of analysis in shotgun proteomics.

Michael L Nielsen1, Mikhail M Savitski, Roman A Zubarev.   

Abstract

The complexity of the human proteome, already enormous at the organism level, increases further in the course of the proteome analysis due to in vitro sample evolution. Most of in vitro alterations can also occur in vivo as post-translational modifications. These two types of modifications can only be distinguished a posteriori but not in the process of analysis, thus rendering necessary the analysis of every molecule in the sample. With the new software tool ModifiComb applied to MS/MS data, the extent of modifications was measured in tryptic mixtures representing the full proteome of human cells. The estimated level of 8-12 modified peptides per each unmodified tryptic peptide present at >or=1% level is approaching one modification per amino acid on average. This is a higher modification rate than was previously thought, posing an additional challenge to analytical techniques. The solution to the problem is seen in improving sample preparation routines, introducing dynamic range-adjusted thresholds for database searches, using more specific MS/MS analysis using high mass accuracy and complementary fragmentation techniques, and revealing peptide families with identification of additional proteins only by unfamiliar peptides. Extensive protein separation prior to analysis reduces the requirements on speed and dynamic range of a tandem mass spectrometer and can be a viable alternative to the shotgun approach.

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Year:  2006        PMID: 17015437     DOI: 10.1074/mcp.M600248-MCP200

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


  29 in total

1.  Computational analysis of unassigned high-quality MS/MS spectra in proteomic data sets.

Authors:  Kang Ning; Damian Fermin; Alexey I Nesvizhskii
Journal:  Proteomics       Date:  2010-07       Impact factor: 3.984

2.  Fast multi-blind modification search through tandem mass spectrometry.

Authors:  Seungjin Na; Nuno Bandeira; Eunok Paek
Journal:  Mol Cell Proteomics       Date:  2011-12-20       Impact factor: 5.911

3.  Protein PTMs: post-translational modifications or pesky trouble makers?

Authors:  Ralph A Bradshaw; Katalin F Medzihradszky; Robert J Chalkley
Journal:  J Mass Spectrom       Date:  2010-10       Impact factor: 1.982

4.  Protein identification by spectral networks analysis.

Authors:  Nuno Bandeira; Dekel Tsur; Ari Frank; Pavel A Pevzner
Journal:  Proc Natl Acad Sci U S A       Date:  2007-04-02       Impact factor: 11.205

Review 5.  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

6.  Whole proteome analysis of post-translational modifications: applications of mass-spectrometry for proteogenomic annotation.

Authors:  Nitin Gupta; Stephen Tanner; Navdeep Jaitly; Joshua N Adkins; Mary Lipton; Robert Edwards; Margaret Romine; Andrei Osterman; Vineet Bafna; Richard D Smith; Pavel A Pevzner
Journal:  Genome Res       Date:  2007-08-09       Impact factor: 9.043

7.  In-depth analysis of tandem mass spectrometry data from disparate instrument types.

Authors:  Robert J Chalkley; Peter R Baker; Katalin F Medzihradszky; Aenoch J Lynn; A L Burlingame
Journal:  Mol Cell Proteomics       Date:  2008-07-24       Impact factor: 5.911

8.  Toward proteome-scale identification and quantification of isoaspartyl residues in biological samples.

Authors:  Hongqian Yang; Eva Y M Fung; Alexander R Zubarev; Roman A Zubarev
Journal:  J Proteome Res       Date:  2009-10       Impact factor: 4.466

9.  Comparative proteogenomics: combining mass spectrometry and comparative genomics to analyze multiple genomes.

Authors:  Nitin Gupta; Jamal Benhamida; Vipul Bhargava; Daniel Goodman; Elisabeth Kain; Ian Kerman; Ngan Nguyen; Noah Ollikainen; Jesse Rodriguez; Jian Wang; Mary S Lipton; Margaret Romine; Vineet Bafna; Richard D Smith; Pavel A Pevzner
Journal:  Genome Res       Date:  2008-04-21       Impact factor: 9.043

10.  DeltAMT: a statistical algorithm for fast detection of protein modifications from LC-MS/MS data.

Authors:  Yan Fu; Li-Yun Xiu; Wei Jia; Ding Ye; Rui-Xiang Sun; Xiao-Hong Qian; Si-Min He
Journal:  Mol Cell Proteomics       Date:  2011-02-14       Impact factor: 5.911

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