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Mapping the Human Plasma Proteome by SCX-LC-IMS-MS

The advent of on-line multidimensional liquid chromatography-mass spectrometry has significantly impacted proteomic analyses of complex biological fluids such as plasma. However, there is general agreement that additional advances to enhance the peak capacity of such platforms are required to enhanc... Full description

Journal Title: Journal of the American Society for Mass Spectrometry 2007, Vol.18 (7), p.1249-1264
Main Author: Liu, Xiaoyun
Other Authors: Valentine, Stephen J , Plasencia, Manolo D , Trimpin, Sarah , Naylor, Stephen , Clemmer, David E
Format: Electronic Article Electronic Article
Language: English
Subjects:
Publisher: United States: Elsevier Inc
ID: ISSN: 1044-0305
Link: https://www.ncbi.nlm.nih.gov/pubmed/17553692
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recordid: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_2195767
title: Mapping the Human Plasma Proteome by SCX-LC-IMS-MS
format: Article
creator:
  • Liu, Xiaoyun
  • Valentine, Stephen J
  • Plasencia, Manolo D
  • Trimpin, Sarah
  • Naylor, Stephen
  • Clemmer, David E
subjects:
  • Analysis
  • Article
  • Blood Chemical Analysis - methods
  • Blood plasma
  • Blood Proteins - chemistry
  • Cation exchanging
  • Chromatography, High Pressure Liquid - methods
  • Chromatography, Ion Exchange - methods
  • Data sets
  • Homology
  • Humans
  • Ionic mobility
  • Ions
  • Liquid chromatography
  • Maps
  • Mass spectrometry
  • Peptide Mapping - methods
  • Physiological aspects
  • Plasmas (physics)
  • Proteins
  • Proteome - chemistry
  • Proteomics - methods
  • Scientific imaging
  • Separation
  • Spectrometry, Mass, Electrospray Ionization - methods
  • Spectroscopy
ispartof: Journal of the American Society for Mass Spectrometry, 2007, Vol.18 (7), p.1249-1264
description: The advent of on-line multidimensional liquid chromatography-mass spectrometry has significantly impacted proteomic analyses of complex biological fluids such as plasma. However, there is general agreement that additional advances to enhance the peak capacity of such platforms are required to enhance the accuracy and coverage of proteome maps of such fluids. Here, we describe the combination of strong-cation-exchange and reversed-phase liquid chromatographies with ion mobility and mass spectrometry as a means of characterizing the complex mixture of proteins associated with the human plasma proteome. The increase in separation capacity associated with inclusion of the ion mobility separation leads to generation of one of the most extensive proteome maps to date. The map is generated by analyzing plasma samples of five healthy humans; we report a preliminary identification of 9087 proteins from 37,842 unique peptide assignments. An analysis of expected false-positive rates leads to a high-confidence identification of 2928 proteins. The results are catalogued in a fashion that includes positions and intensities of assigned features observed in the datasets as well as pertinent identification information such as protein accession number, mass, and homology score/confidence indicators. Comparisons of the assigned features reported here with other datasets shows substantial agreement with respect to the first several hundred entries; there is far less agreement associated with detection of lower abundance components.
language: eng
source:
identifier: ISSN: 1044-0305
fulltext: no_fulltext
issn:
  • 1044-0305
  • 1879-1123
url: Link


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descriptionThe advent of on-line multidimensional liquid chromatography-mass spectrometry has significantly impacted proteomic analyses of complex biological fluids such as plasma. However, there is general agreement that additional advances to enhance the peak capacity of such platforms are required to enhance the accuracy and coverage of proteome maps of such fluids. Here, we describe the combination of strong-cation-exchange and reversed-phase liquid chromatographies with ion mobility and mass spectrometry as a means of characterizing the complex mixture of proteins associated with the human plasma proteome. The increase in separation capacity associated with inclusion of the ion mobility separation leads to generation of one of the most extensive proteome maps to date. The map is generated by analyzing plasma samples of five healthy humans; we report a preliminary identification of 9087 proteins from 37,842 unique peptide assignments. An analysis of expected false-positive rates leads to a high-confidence identification of 2928 proteins. The results are catalogued in a fashion that includes positions and intensities of assigned features observed in the datasets as well as pertinent identification information such as protein accession number, mass, and homology score/confidence indicators. Comparisons of the assigned features reported here with other datasets shows substantial agreement with respect to the first several hundred entries; there is far less agreement associated with detection of lower abundance components.
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subjectAnalysis ; Article ; Blood Chemical Analysis - methods ; Blood plasma ; Blood Proteins - chemistry ; Cation exchanging ; Chromatography, High Pressure Liquid - methods ; Chromatography, Ion Exchange - methods ; Data sets ; Homology ; Humans ; Ionic mobility ; Ions ; Liquid chromatography ; Maps ; Mass spectrometry ; Peptide Mapping - methods ; Physiological aspects ; Plasmas (physics) ; Proteins ; Proteome - chemistry ; Proteomics - methods ; Scientific imaging ; Separation ; Spectrometry, Mass, Electrospray Ionization - methods ; Spectroscopy
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descriptionThe advent of on-line multidimensional liquid chromatography-mass spectrometry has significantly impacted proteomic analyses of complex biological fluids such as plasma. However, there is general agreement that additional advances to enhance the peak capacity of such platforms are required to enhance the accuracy and coverage of proteome maps of such fluids. Here, we describe the combination of strong-cation-exchange and reversed-phase liquid chromatographies with ion mobility and mass spectrometry as a means of characterizing the complex mixture of proteins associated with the human plasma proteome. The increase in separation capacity associated with inclusion of the ion mobility separation leads to generation of one of the most extensive proteome maps to date. The map is generated by analyzing plasma samples of five healthy humans; we report a preliminary identification of 9087 proteins from 37,842 unique peptide assignments. An analysis of expected false-positive rates leads to a high-confidence identification of 2928 proteins. The results are catalogued in a fashion that includes positions and intensities of assigned features observed in the datasets as well as pertinent identification information such as protein accession number, mass, and homology score/confidence indicators. Comparisons of the assigned features reported here with other datasets shows substantial agreement with respect to the first several hundred entries; there is far less agreement associated with detection of lower abundance components.
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abstractThe advent of on-line multidimensional liquid chromatography-mass spectrometry has significantly impacted proteomic analyses of complex biological fluids such as plasma. However, there is general agreement that additional advances to enhance the peak capacity of such platforms are required to enhance the accuracy and coverage of proteome maps of such fluids. Here, we describe the combination of strong-cation-exchange and reversed-phase liquid chromatographies with ion mobility and mass spectrometry as a means of characterizing the complex mixture of proteins associated with the human plasma proteome. The increase in separation capacity associated with inclusion of the ion mobility separation leads to generation of one of the most extensive proteome maps to date. The map is generated by analyzing plasma samples of five healthy humans; we report a preliminary identification of 9087 proteins from 37,842 unique peptide assignments. An analysis of expected false-positive rates leads to a high-confidence identification of 2928 proteins. The results are catalogued in a fashion that includes positions and intensities of assigned features observed in the datasets as well as pertinent identification information such as protein accession number, mass, and homology score/confidence indicators. Comparisons of the assigned features reported here with other datasets shows substantial agreement with respect to the first several hundred entries; there is far less agreement associated with detection of lower abundance components.
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doi10.1016/j.jasms.2007.04.012
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