Literature DB >> 28194965

Extensive Peptide Fractionation and y1 Ion-Based Interference Detection Method for Enabling Accurate Quantification by Isobaric Labeling and Mass Spectrometry.

Mingming Niu1, Ji-Hoon Cho, Kiran Kodali, Vishwajeeth Pagala, Anthony A High, Hong Wang2, Zhiping Wu, Yuxin Li, Wenjian Bi, Hui Zhang, Xusheng Wang, Wei Zou1, Junmin Peng.   

Abstract

Isobaric labeling quantification by mass spectrometry (MS) has emerged as a powerful technology for multiplexed large-scale protein profiling, but measurement accuracy in complex mixtures is confounded by the interference from coisolated ions, resulting in ratio compression. Here we report that the ratio compression can be essentially resolved by the combination of pre-MS peptide fractionation, MS2-based interference detection, and post-MS computational interference correction. To recapitulate the complexity of biological samples, we pooled tandem mass tag (TMT)-labeled Escherichia coli peptides at 1:3:10 ratios and added in ∼20-fold more rat peptides as background, followed by the analysis of two-dimensional liquid chromatography (LC)-MS/MS. Systematic investigation shows that quantitative interference was impacted by LC fractionation depth, MS isolation window, and peptide loading amount. Exhaustive fractionation (320 × 4 h) can nearly eliminate the interference and achieve results comparable to the MS3-based method. Importantly, the interference in MS2 scans can be estimated by the intensity of contaminated y1 product ions, and we thus developed an algorithm to correct reporter ion ratios of tryptic peptides. Our data indicate that intermediate fractionation (40 × 2 h) and y1 ion-based correction allow accurate and deep TMT profiling of more than 10 000 proteins, which represents a straightforward and affordable strategy in isobaric labeling proteomics.

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Year:  2017        PMID: 28194965      PMCID: PMC5467445          DOI: 10.1021/acs.analchem.6b04415

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  40 in total

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Journal:  Anal Chem       Date:  2011-11-04       Impact factor: 6.986

2.  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

3.  Quantitative protein analysis by mass spectrometry.

Authors:  Vishwajeeth R Pagala; Anthony A High; Xusheng Wang; Haiyan Tan; Kiran Kodali; Ashutosh Mishra; Kanisha Kavdia; Yanji Xu; Zhiping Wu; Junmin Peng
Journal:  Methods Mol Biol       Date:  2015

Review 4.  Protein biomarker discovery and validation: the long and uncertain path to clinical utility.

Authors:  Nader Rifai; Michael A Gillette; Steven A Carr
Journal:  Nat Biotechnol       Date:  2006-08       Impact factor: 54.908

Review 5.  Proteomics by mass spectrometry: approaches, advances, and applications.

Authors:  John R Yates; Cristian I Ruse; Aleksey Nakorchevsky
Journal:  Annu Rev Biomed Eng       Date:  2009       Impact factor: 9.590

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

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Journal:  Mol Cell Proteomics       Date:  2014-09-08       Impact factor: 5.911

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Journal:  Proteomics       Date:  2014-12-15       Impact factor: 3.984

10.  Gas-phase purification enables accurate, multiplexed proteome quantification with isobaric tagging.

Authors:  Craig D Wenger; M Violet Lee; Alexander S Hebert; Graeme C McAlister; Douglas H Phanstiel; Michael S Westphall; Joshua J Coon
Journal:  Nat Methods       Date:  2011-10-02       Impact factor: 28.547

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2.  ALS-FTLD-linked mutations of SQSTM1/p62 disrupt selective autophagy and NFE2L2/NRF2 anti-oxidative stress pathway.

Authors:  Zhiqiang Deng; Junghyun Lim; Qian Wang; Kerry Purtell; Shuai Wu; Gloria M Palomo; Haiyan Tan; Giovanni Manfredi; Yanxiang Zhao; Junmin Peng; Bo Hu; Shi Chen; Zhenyu Yue
Journal:  Autophagy       Date:  2019-07-30       Impact factor: 16.016

3.  Targeted MultiNotch MS3 Approach for Relative Quantification of N-Glycans Using Multiplexed Carbonyl-Reactive Isobaric Tags.

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Journal:  Anal Chem       Date:  2017-12-14       Impact factor: 6.986

4.  Deep Multilayer Brain Proteomics Identifies Molecular Networks in Alzheimer's Disease Progression.

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Journal:  Neuron       Date:  2020-01-08       Impact factor: 17.173

5.  27-Plex Tandem Mass Tag Mass Spectrometry for Profiling Brain Proteome in Alzheimer's Disease.

Authors:  Zhen Wang; Kaiwen Yu; Haiyan Tan; Zhiping Wu; Ji-Hoon Cho; Xian Han; Huan Sun; Thomas G Beach; Junmin Peng
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6.  Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification.

Authors:  Anthony A High; Haiyan Tan; Vishwajeeth R Pagala; Mingming Niu; Ji-Hoon Cho; Xusheng Wang; Bing Bai; Junmin Peng
Journal:  J Vis Exp       Date:  2017-11-15       Impact factor: 1.355

7.  Control of Early B Cell Development by the RNA N6-Methyladenosine Methylation.

Authors:  Zhong Zheng; Linda Zhang; Xiao-Long Cui; Xianbin Yu; Phillip J Hsu; Ruitu Lyu; Haiyan Tan; Malay Mandal; Michelle Zhang; Hui-Lung Sun; Arantxa Sanchez Castillo; Junmin Peng; Marcus R Clark; Chuan He; Haochu Huang
Journal:  Cell Rep       Date:  2020-06-30       Impact factor: 9.423

8.  Proteomic studies of bone and skeletal health outcomes.

Authors:  Carrie M Nielson; Jon M Jacobs; Eric S Orwoll
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9.  Regulation of MAGE-A3/6 by the CRL4-DCAF12 ubiquitin ligase and nutrient availability.

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10.  Identification of Therapeutic Targets in Rhabdomyosarcoma through Integrated Genomic, Epigenomic, and Proteomic Analyses.

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