Literature DB >> 28749931

Quantitative, multiplexed workflow for deep analysis of human blood plasma and biomarker discovery by mass spectrometry.

Hasmik Keshishian1, Michael W Burgess1, Harrison Specht1, Luke Wallace1, Karl R Clauser1, Michael A Gillette1,2, Steven A Carr1.   

Abstract

Proteomic characterization of blood plasma is of central importance to clinical proteomics and particularly to biomarker discovery studies. The vast dynamic range and high complexity of the plasma proteome have, however, proven to be serious challenges and have often led to unacceptable tradeoffs between depth of coverage and sample throughput. We present an optimized sample-processing pipeline for analysis of the human plasma proteome that provides greatly increased depth of detection, improved quantitative precision and much higher sample analysis throughput as compared with prior methods. The process includes abundant protein depletion, isobaric labeling at the peptide level for multiplexed relative quantification and ultra-high-performance liquid chromatography coupled to accurate-mass, high-resolution tandem mass spectrometry analysis of peptides fractionated off-line by basic pH reversed-phase (bRP) chromatography. The overall reproducibility of the process, including immunoaffinity depletion, is high, with a process replicate coefficient of variation (CV) of <12%. Using isobaric tags for relative and absolute quantitation (iTRAQ) 4-plex, >4,500 proteins are detected and quantified per patient sample on average, with two or more peptides per protein and starting from as little as 200 μl of plasma. The approach can be multiplexed up to 10-plex using tandem mass tags (TMT) reagents, further increasing throughput, albeit with some decrease in the number of proteins quantified. In addition, we provide a rapid protocol for analysis of nonfractionated depleted plasma samples analyzed in 10-plex. This provides ∼600 quantified proteins for each of the ten samples in ∼5 h of instrument time.

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Year:  2017        PMID: 28749931      PMCID: PMC6057147          DOI: 10.1038/nprot.2017.054

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  44 in total

1.  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

2.  iTRAQ labeling is superior to mTRAQ for quantitative global proteomics and phosphoproteomics.

Authors:  Philipp Mertins; Namrata D Udeshi; Karl R Clauser; D R Mani; Jinal Patel; Shao-en Ong; Jacob D Jaffe; Steven A Carr
Journal:  Mol Cell Proteomics       Date:  2011-12-30       Impact factor: 5.911

3.  A pipeline that integrates the discovery and verification of plasma protein biomarkers reveals candidate markers for cardiovascular disease.

Authors:  Terri A Addona; Xu Shi; Hasmik Keshishian; D R Mani; Michael Burgess; Michael A Gillette; Karl R Clauser; Dongxiao Shen; Gregory D Lewis; Laurie A Farrell; Michael A Fifer; Marc S Sabatine; Robert E Gerszten; Steven A Carr
Journal:  Nat Biotechnol       Date:  2011-06-19       Impact factor: 54.908

4.  Analysis of the acidic proteome with negative electron-transfer dissociation mass spectrometry.

Authors:  Graeme C McAlister; Jason D Russell; Neil G Rumachik; Alexander S Hebert; John E P Syka; Lewis Y Geer; Michael S Westphall; David J Pagliarini; Joshua J Coon
Journal:  Anal Chem       Date:  2012-03-01       Impact factor: 6.986

5.  Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics.

Authors:  Ruth Hüttenhain; Martin Soste; Nathalie Selevsek; Hannes Röst; Atul Sethi; Christine Carapito; Terry Farrah; Eric W Deutsch; Ulrike Kusebauch; Robert L Moritz; Emma Niméus-Malmström; Oliver Rinner; Ruedi Aebersold
Journal:  Sci Transl Med       Date:  2012-07-11       Impact factor: 17.956

6.  Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips.

Authors:  Juri Rappsilber; Matthias Mann; Yasushi Ishihama
Journal:  Nat Protoc       Date:  2007       Impact factor: 13.491

7.  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

8.  MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics.

Authors:  Lily Ting; Ramin Rad; Steven P Gygi; Wilhelm Haas
Journal:  Nat Methods       Date:  2011-10-02       Impact factor: 28.547

9.  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

Review 10.  Isobaric labeling-based relative quantification in shotgun proteomics.

Authors:  Navin Rauniyar; John R Yates
Journal:  J Proteome Res       Date:  2014-11-04       Impact factor: 4.466

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  40 in total

1.  A Novel Differential Ion Mobility Device Expands the Depth of Proteome Coverage and the Sensitivity of Multiplex Proteomic Measurements.

Authors:  Sibylle Pfammatter; Eric Bonneil; Francis P McManus; Satendra Prasad; Derek J Bailey; Michael Belford; Jean-Jacques Dunyach; Pierre Thibault
Journal:  Mol Cell Proteomics       Date:  2018-07-14       Impact factor: 5.911

2.  The power of proteomics to monitor senescence-associated secretory phenotypes and beyond: toward clinical applications.

Authors:  Nathan Basisty; Abhijit Kale; Sandip Patel; Judith Campisi; Birgit Schilling
Journal:  Expert Rev Proteomics       Date:  2020-05-19       Impact factor: 3.940

3.  High-speed Analysis of Large Sample Sets - How Can This Key Aspect of the Omics Be Achieved?

Authors:  Rainer Cramer
Journal:  Mol Cell Proteomics       Date:  2020-08-12       Impact factor: 5.911

4.  Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data.

Authors:  Vera Ignjatovic; Philipp E Geyer; Krishnan K Palaniappan; Jessica E Chaaban; Gilbert S Omenn; Mark S Baker; Eric W Deutsch; Jochen M Schwenk
Journal:  J Proteome Res       Date:  2019-10-11       Impact factor: 4.466

Review 5.  Sample Multiplexing Strategies in Quantitative Proteomics.

Authors:  Albert B Arul; Renã A S Robinson
Journal:  Anal Chem       Date:  2018-12-18       Impact factor: 6.986

6.  Small-protein Enrichment Assay Enables the Rapid, Unbiased Analysis of Over 100 Low Abundance Factors from Human Plasma.

Authors:  Dylan J Harney; Amy T Hutchison; Zhiduan Su; Luke Hatchwell; Leonie K Heilbronn; Samantha Hocking; David E James; Mark Larance
Journal:  Mol Cell Proteomics       Date:  2019-07-15       Impact factor: 5.911

Review 7.  A Review on Quantitative Multiplexed Proteomics.

Authors:  Nishant Pappireddi; Lance Martin; Martin Wühr
Journal:  Chembiochem       Date:  2019-04-18       Impact factor: 3.164

Review 8.  Identification and Quantification of Proteoforms by Mass Spectrometry.

Authors:  Leah V Schaffer; Robert J Millikin; Rachel M Miller; Lissa C Anderson; Ryan T Fellers; Ying Ge; Neil L Kelleher; Richard D LeDuc; Xiaowen Liu; Samuel H Payne; Liangliang Sun; Paul M Thomas; Trisha Tucholski; Zhe Wang; Si Wu; Zhijie Wu; Dahang Yu; Michael R Shortreed; Lloyd M Smith
Journal:  Proteomics       Date:  2019-05       Impact factor: 3.984

9.  Algorithmic assessment of cellular senescence in experimental and clinical specimens.

Authors:  J Kohli; B Wang; S M Brandenburg; N Basisty; K Evangelou; M Varela-Eirin; J Campisi; B Schilling; V Gorgoulis; M Demaria
Journal:  Nat Protoc       Date:  2021-04-28       Impact factor: 13.491

10.  SOD1 is a Possible Predictor of COVID-19 Progression as Revealed by Plasma Proteomics.

Authors:  Benhong Xu; Yuxuan Lei; Xiaohu Ren; Feng Yin; Weihua Wu; Ying Sun; Xiaohui Wang; Qian Sun; Xifei Yang; Xin Wang; Renli Zhang; Zigang Li; Shisong Fang; Jianjun Liu
Journal:  ACS Omega       Date:  2021-06-24
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