Literature DB >> 22468137

Isobaric labeling and data normalization without requiring protein quantitation.

Phillip D Kim1, Bhavinkumar B Patel, Anthony T Yeung.   

Abstract

Isobaric multiplexed quantitative proteomics can complement high-resolution sample isolation techniques. Here, we report a simple workflow exponentially modified protein abundance index (emPAI)-MW deconvolution (EMMOL) for normalizing isobaric reporter ratios within and between experiments, where small or unknown amounts of protein are used. EMMOL deconvolutes the isobaric tags for relative and absolute quantification (iTRAQ) data to yield the quantity of each protein of each sample in the pool, a new approach that enables the comparison of many samples without including a channel of reference standard. Moreover, EMMOL allows using a sufficient quantity of control sample to facilitate the peptide fractionation (isoelectric-focusing was used in this report), and mass spectrometry MS/MS sequencing yet relies on the broad dynamic range of iTRAQ quantitation to compare relative protein abundance. We demonstrated EMMOL by comparing four pooled samples with 20-fold range differences in protein abundance and performed data normalization without using prior knowledge of the amounts of proteins in each sample, simulating an iTRAQ experiment without protein quantitation prior to labeling. We used emPAI, the target protein MW, and the iTRAQ reporter ratios to calculate the amount of each protein in each of the four channels. Importantly, the EMMOL-delineated proteomes from separate iTRAQ experiments can be assorted for comparison without using a reference sample. We observed no compression of expression in iTRAQ ratios over a 20-fold range for all protein abundances. To complement this ability to analyze minute samples, we report an optimized iTRAQ labeling protocol for using 5 μg protein as the starting material.

Keywords:  EMMOL; LCM; iTRAQ; optimization; proteome

Mesh:

Substances:

Year:  2012        PMID: 22468137      PMCID: PMC3313697          DOI: 10.7171/jbt.12-2301-002

Source DB:  PubMed          Journal:  J Biomol Tech        ISSN: 1524-0215


  26 in total

1.  Addressing accuracy and precision issues in iTRAQ quantitation.

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2.  Search for cancer markers from endometrial tissues using differentially labeled tags iTRAQ and cICAT with multidimensional liquid chromatography and tandem mass spectrometry.

Authors:  Leroi DeSouza; Georg Diehl; Mary Joe Rodrigues; Jingzhong Guo; Alexander D Romaschin; Terence J Colgan; K W Michael Siu
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3.  Exponentially modified protein abundance index (emPAI) for estimation of absolute protein amount in proteomics by the number of sequenced peptides per protein.

Authors:  Yasushi Ishihama; Yoshiya Oda; Tsuyoshi Tabata; Toshitaka Sato; Takeshi Nagasu; Juri Rappsilber; Matthias Mann
Journal:  Mol Cell Proteomics       Date:  2005-06-14       Impact factor: 5.911

4.  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

5.  Quantitative membrane proteomics applying narrow range peptide isoelectric focusing for studies of small cell lung cancer resistance mechanisms.

Authors:  Hanna Eriksson; Johan Lengqvist; Joel Hedlund; Kristina Uhlén; Lukas M Orre; Bengt Bjellqvist; Bengt Persson; Janne Lehtiö; Per-Johan Jakobsson
Journal:  Proteomics       Date:  2008-08       Impact factor: 3.984

6.  Biomarker discovery from pancreatic cancer secretome using a differential proteomic approach.

Authors:  Mads Grønborg; Troels Zakarias Kristiansen; Akiko Iwahori; Rubens Chang; Raghunath Reddy; Norihiro Sato; Henrik Molina; Ole Nørregaard Jensen; Ralph H Hruban; Michael G Goggins; Anirban Maitra; Akhilesh Pandey
Journal:  Mol Cell Proteomics       Date:  2005-10-08       Impact factor: 5.911

7.  Time-resolved mass spectrometry of tyrosine phosphorylation sites in the epidermal growth factor receptor signaling network reveals dynamic modules.

Authors:  Yi Zhang; Alejandro Wolf-Yadlin; Phillip L Ross; Darryl J Pappin; John Rush; Douglas A Lauffenburger; Forest M White
Journal:  Mol Cell Proteomics       Date:  2005-06-11       Impact factor: 5.911

8.  Proteomic analyses of pancreatic cyst fluids.

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Journal:  Pancreas       Date:  2009-03       Impact factor: 3.327

9.  Absolute quantification of potential cancer markers in clinical tissue homogenates using multiple reaction monitoring on a hybrid triple quadrupole/linear ion trap tandem mass spectrometer.

Authors:  Leroi V DeSouza; Alexander D Romaschin; Terence J Colgan; K W Michael Siu
Journal:  Anal Chem       Date:  2009-05-01       Impact factor: 6.986

10.  Peptides OFFGEL electrophoresis: a suitable pre-analytical step for complex eukaryotic samples fractionation compatible with quantitative iTRAQ labeling.

Authors:  Jérôme Chenau; Sylvie Michelland; Jonathan Sidibe; Michel Seve
Journal:  Proteome Sci       Date:  2008-02-26       Impact factor: 2.480

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  8 in total

1.  CONSTANd : A Normalization Method for Isobaric Labeled Spectra by Constrained Optimization.

Authors:  Evelyne Maes; Wahyu Wijaya Hadiwikarta; Inge Mertens; Geert Baggerman; Jef Hooyberghs; Dirk Valkenborg
Journal:  Mol Cell Proteomics       Date:  2016-06-14       Impact factor: 5.911

2.  Immunodepletion plasma proteomics by tripleTOF 5600 and Orbitrap elite/LTQ-Orbitrap Velos/Q exactive mass spectrometers.

Authors:  Kelly A Jones; Phillip D Kim; Bhavinkumar B Patel; Steven G Kelsen; Alan Braverman; Derrick J Swinton; Philip R Gafken; Lisa A Jones; William S Lane; John M Neveu; Hon-Chiu E Leung; Scott A Shaffer; John D Leszyk; Bruce A Stanley; Todd E Fox; Anne Stanley; Michael J Hall; Heather Hampel; Christopher D South; Albert de la Chapelle; Randall W Burt; David A Jones; Levy Kopelovich; Anthony T Yeung
Journal:  J Proteome Res       Date:  2013-09-19       Impact factor: 4.466

Review 3.  Emerging proteomic technologies for elucidating context-dependent cellular signaling events: A big challenge of tiny proportions.

Authors:  Sarah J Parker; Koen Raedschelders; Jennifer E Van Eyk
Journal:  Proteomics       Date:  2015-02-10       Impact factor: 3.984

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

Authors:  Stephanie M Cologna; Christopher A Crutchfield; Brian C Searle; Paul S Blank; Cynthia L Toth; Alexa M Ely; Jaqueline A Picache; Peter S Backlund; Christopher A Wassif; Forbes D Porter; Alfred L Yergey
Journal:  J Proteome Res       Date:  2015-09-03       Impact factor: 4.466

5.  Assessment of two immunodepletion methods: off-target effects and variations in immunodepletion efficiency may confound plasma proteomics.

Authors:  Bhavinkumar B Patel; Carlos A Barrero; Alan Braverman; Phillip D Kim; Kelly A Jones; Dian Er Chen; Russell P Bowler; Salim Merali; Steven G Kelsen; Anthony T Yeung
Journal:  J Proteome Res       Date:  2012-10-29       Impact factor: 4.466

Review 6.  Quantitative Proteomics Using Isobaric Labeling: A Practical Guide.

Authors:  Xiulan Chen; Yaping Sun; Tingting Zhang; Lian Shu; Peter Roepstorff; Fuquan Yang
Journal:  Genomics Proteomics Bioinformatics       Date:  2022-01-08       Impact factor: 6.409

7.  Proteomics analysis reveals protein expression differences for hypopharyngeal gland activity in the honeybee, Apis mellifera carnica Pollmann.

Authors:  Ting Ji; Zhenguo Liu; Jie Shen; Fang Shen; Qin Liang; Liming Wu; Guohong Chen; Miguel Corona
Journal:  BMC Genomics       Date:  2014-08-08       Impact factor: 3.969

8.  Isobaric Matching between Runs and Novel PSM-Level Normalization in MaxQuant Strongly Improve Reporter Ion-Based Quantification.

Authors:  Sung-Huan Yu; Pelagia Kyriakidou; Jürgen Cox
Journal:  J Proteome Res       Date:  2020-09-16       Impact factor: 4.466

  8 in total

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