Literature DB >> 26288259

An Efficient Approach to Evaluate Reporter Ion Behavior from MALDI-MS/MS Data for Quantification Studies Using Isobaric Tags.

Stephanie M Cologna1, Christopher A Crutchfield2, Brian C Searle3, Paul S Blank4, Cynthia L Toth1, Alexa M Ely1, Jaqueline A Picache1, Peter S Backlund2, Christopher A Wassif1, Forbes D Porter1, Alfred L Yergey2.   

Abstract

Protein quantification, identification, and abundance determination are important aspects of proteome characterization and are crucial in understanding biological mechanisms and human diseases. Different strategies are available to quantify proteins using mass spectrometric detection, and most are performed at the peptide level and include both targeted and untargeted methodologies. Discovery-based or untargeted approaches oftentimes use covalent tagging strategies (i.e., iTRAQ, TMT), where reporter ion signals collected in the tandem MS experiment are used for quantification. Herein we investigate the behavior of the iTRAQ 8-plex chemistry using MALDI-TOF/TOF instrumentation. The experimental design and data analysis approach described is simple and straightforward, which allows researchers to optimize data collection and proper analysis within a laboratory. iTRAQ reporter ion signals were normalized within each spectrum to remove peptide biases. An advantage of this approach is that missing reporter ion values can be accepted for purposes of protein identification and quantification without the need for ANOVA analysis. We investigate the distribution of reporter ion peak areas in an equimolar system and a mock biological system and provide recommendations for establishing fold-change cutoff values at the peptide level for iTRAQ data sets. These data provide a unique data set available to the community for informatics training and analysis.

Entities:  

Keywords:  MALDI-MS; fold-change; iTRAQ; quality control; quantitative proteomics; time-of-flight

Mesh:

Substances:

Year:  2015        PMID: 26288259      PMCID: PMC5571863          DOI: 10.1021/acs.jproteome.5b00254

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


  31 in total

1.  Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search.

Authors:  Andrew Keller; Alexey I Nesvizhskii; Eugene Kolker; Ruedi Aebersold
Journal:  Anal Chem       Date:  2002-10-15       Impact factor: 6.986

2.  BootstRatio: A web-based statistical analysis of fold-change in qPCR and RT-qPCR data using resampling methods.

Authors:  Ramon Clèries; Jordi Galvez; Meritxell Espino; Josepa Ribes; Virginia Nunes; Miguel López de Heredia
Journal:  Comput Biol Med       Date:  2012-01-24       Impact factor: 4.589

3.  Addressing accuracy and precision issues in iTRAQ quantitation.

Authors:  Natasha A Karp; Wolfgang Huber; Pawel G Sadowski; Philip D Charles; Svenja V Hester; Kathryn S Lilley
Journal:  Mol Cell Proteomics       Date:  2010-04-10       Impact factor: 5.911

4.  Balancing robust quantification and identification for iTRAQ: application of UHR-ToF MS.

Authors:  Saw Yen Ow; Josselin Noirel; Malinda Salim; Caroline Evans; Rod Watson; Phillip C Wright
Journal:  Proteomics       Date:  2010-06       Impact factor: 3.984

5.  Statistical analysis of relative labeled mass spectrometry data from complex samples using ANOVA.

Authors:  Ann L Oberg; Douglas W Mahoney; Jeanette E Eckel-Passow; Christopher J Malone; Russell D Wolfinger; Elizabeth G Hill; Leslie T Cooper; Oyere K Onuma; Craig Spiro; Terry M Therneau; H Robert Bergen
Journal:  J Proteome Res       Date:  2008-01-04       Impact factor: 4.466

6.  Measuring and managing ratio compression for accurate iTRAQ/TMT quantification.

Authors:  Mikhail M Savitski; Toby Mathieson; Nico Zinn; Gavain Sweetman; Carola Doce; Isabelle Becher; Fiona Pachl; Bernhard Kuster; Marcus Bantscheff
Journal:  J Proteome Res       Date:  2013-07-02       Impact factor: 4.466

7.  Minimising iTRAQ ratio compression through understanding LC-MS elution dependence and high-resolution HILIC fractionation.

Authors:  Saw Yen Ow; Malinda Salim; Josselin Noirel; Caroline Evans; Phillip C Wright
Journal:  Proteomics       Date:  2011-05-04       Impact factor: 3.984

8.  Integral quantification accuracy estimation for reporter ion-based quantitative proteomics (iQuARI).

Authors:  Marc Vaudel; Julia M Burkhart; Sonja Radau; René P Zahedi; Lennart Martens; Albert Sickmann
Journal:  J Proteome Res       Date:  2012-08-30       Impact factor: 4.466

9.  Increasing throughput in targeted proteomics assays: 54-plex quantitation in a single mass spectrometry run.

Authors:  Robert A Everley; Ryan C Kunz; Fiona E McAllister; Steven P Gygi
Journal:  Anal Chem       Date:  2013-05-23       Impact factor: 6.986

10.  i-Tracker: for quantitative proteomics using iTRAQ.

Authors:  Ian P Shadforth; Tom P J Dunkley; Kathryn S Lilley; Conrad Bessant
Journal:  BMC Genomics       Date:  2005-10-20       Impact factor: 3.969

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  1 in total

Review 1.  A Comprehensive Guide for Performing Sample Preparation and Top-Down Protein Analysis.

Authors:  Matthew P Padula; Iain J Berry; Matthew B O Rourke; Benjamin B A Raymond; Jerran Santos; Steven P Djordjevic
Journal:  Proteomes       Date:  2017-04-07
  1 in total

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