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Optimization of Plasma Sample Pretreatment for Quantitative Analysis Using iTRAQ Labeling and LC-MALDI-TOF/TOF

Shotgun proteomic methods involving iTRAQ (isobaric tags for relative and absolute quantitation) peptide labeling facilitate quantitative analyses of proteomes and searches for useful biomarkers. However, the plasma proteome's complexity and the highly dynamic plasma protein concentration range...

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Detalles Bibliográficos
Autores principales: Luczak, Magdalena, Marczak, Lukasz, Stobiecki, Maciej
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4079693/
https://www.ncbi.nlm.nih.gov/pubmed/24988083
http://dx.doi.org/10.1371/journal.pone.0101694
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author Luczak, Magdalena
Marczak, Lukasz
Stobiecki, Maciej
author_facet Luczak, Magdalena
Marczak, Lukasz
Stobiecki, Maciej
author_sort Luczak, Magdalena
collection PubMed
description Shotgun proteomic methods involving iTRAQ (isobaric tags for relative and absolute quantitation) peptide labeling facilitate quantitative analyses of proteomes and searches for useful biomarkers. However, the plasma proteome's complexity and the highly dynamic plasma protein concentration range limit the ability of conventional approaches to analyze and identify a large number of proteins, including useful biomarkers. The goal of this paper is to elucidate the best approach for plasma sample pretreatment for MS- and iTRAQ-based analyses. Here, we systematically compared four approaches, which include centrifugal ultrafiltration, SCX chromatography with fractionation, affinity depletion, and plasma without fractionation, to reduce plasma sample complexity. We generated an optimized protocol for quantitative protein analysis using iTRAQ reagents and an UltrafleXtreme (Bruker Daltonics) MALDI TOF/TOF mass spectrometer. Moreover, we used a simple, rapid, efficient, but inexpensive sample pretreatment technique that generated an optimal opportunity for biomarker discovery. We discuss the results from the four sample pretreatment approaches and conclude that SCX chromatography without affinity depletion is the best plasma sample preparation pretreatment method for proteome analysis. Using this technique, we identified 1,780 unique proteins, including 1,427 that were quantified by iTRAQ with high reproducibility and accuracy.
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spelling pubmed-40796932014-07-08 Optimization of Plasma Sample Pretreatment for Quantitative Analysis Using iTRAQ Labeling and LC-MALDI-TOF/TOF Luczak, Magdalena Marczak, Lukasz Stobiecki, Maciej PLoS One Research Article Shotgun proteomic methods involving iTRAQ (isobaric tags for relative and absolute quantitation) peptide labeling facilitate quantitative analyses of proteomes and searches for useful biomarkers. However, the plasma proteome's complexity and the highly dynamic plasma protein concentration range limit the ability of conventional approaches to analyze and identify a large number of proteins, including useful biomarkers. The goal of this paper is to elucidate the best approach for plasma sample pretreatment for MS- and iTRAQ-based analyses. Here, we systematically compared four approaches, which include centrifugal ultrafiltration, SCX chromatography with fractionation, affinity depletion, and plasma without fractionation, to reduce plasma sample complexity. We generated an optimized protocol for quantitative protein analysis using iTRAQ reagents and an UltrafleXtreme (Bruker Daltonics) MALDI TOF/TOF mass spectrometer. Moreover, we used a simple, rapid, efficient, but inexpensive sample pretreatment technique that generated an optimal opportunity for biomarker discovery. We discuss the results from the four sample pretreatment approaches and conclude that SCX chromatography without affinity depletion is the best plasma sample preparation pretreatment method for proteome analysis. Using this technique, we identified 1,780 unique proteins, including 1,427 that were quantified by iTRAQ with high reproducibility and accuracy. Public Library of Science 2014-07-02 /pmc/articles/PMC4079693/ /pubmed/24988083 http://dx.doi.org/10.1371/journal.pone.0101694 Text en © 2014 Luczak et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Luczak, Magdalena
Marczak, Lukasz
Stobiecki, Maciej
Optimization of Plasma Sample Pretreatment for Quantitative Analysis Using iTRAQ Labeling and LC-MALDI-TOF/TOF
title Optimization of Plasma Sample Pretreatment for Quantitative Analysis Using iTRAQ Labeling and LC-MALDI-TOF/TOF
title_full Optimization of Plasma Sample Pretreatment for Quantitative Analysis Using iTRAQ Labeling and LC-MALDI-TOF/TOF
title_fullStr Optimization of Plasma Sample Pretreatment for Quantitative Analysis Using iTRAQ Labeling and LC-MALDI-TOF/TOF
title_full_unstemmed Optimization of Plasma Sample Pretreatment for Quantitative Analysis Using iTRAQ Labeling and LC-MALDI-TOF/TOF
title_short Optimization of Plasma Sample Pretreatment for Quantitative Analysis Using iTRAQ Labeling and LC-MALDI-TOF/TOF
title_sort optimization of plasma sample pretreatment for quantitative analysis using itraq labeling and lc-maldi-tof/tof
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4079693/
https://www.ncbi.nlm.nih.gov/pubmed/24988083
http://dx.doi.org/10.1371/journal.pone.0101694
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