Literature DB >> 27775219

Towards comprehensive and quantitative proteomics for diagnosis and therapy of human disease.

Paolo Cifani1, Alex Kentsis1,2.   

Abstract

Given superior analytical features, MS proteomics is well suited for the basic investigation and clinical diagnosis of human disease. Modern MS enables detailed functional characterization of the pathogenic biochemical processes, as achieved by accurate and comprehensive quantification of proteins and their regulatory chemical modifications. Here, we describe how high-accuracy MS in combination with high-resolution chromatographic separations can be leveraged to meet these analytical requirements in a mechanism-focused manner. We review the quantification methods capable of producing accurate measurements of protein abundance and posttranslational modification stoichiometries. We then discuss how experimental design and chromatographic resolution can be leveraged to achieve comprehensive functional characterization of biochemical processes in complex biological proteomes. Finally, we describe current approaches for quantitative analysis of a common functional protein modification: reversible phosphorylation. In all, current instrumentation and methods of high-resolution chromatography and MS proteomics are poised for immediate translation into improved diagnostic strategies for pediatric and adult diseases.
© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Biomedicine; Functional proteomics; Mass spectrometry; PTM; Pediatric disease; Protein quantification

Mesh:

Substances:

Year:  2016        PMID: 27775219      PMCID: PMC5243792          DOI: 10.1002/pmic.201600079

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  101 in total

1.  Towards defining the urinary proteome using liquid chromatography-tandem mass spectrometry. II. Limitations of complex mixture analyses.

Authors:  M T Davis; C S Spahr; M D McGinley; J H Robinson; E J Bures; J Beierle; J Mort; W Yu; R Luethy; S D Patterson
Journal:  Proteomics       Date:  2001-01       Impact factor: 3.984

2.  Absolute quantification of the G protein-coupled receptor rhodopsin by LC/MS/MS using proteolysis product peptides and synthetic peptide standards.

Authors:  David R Barnidge; Edward A Dratz; Therese Martin; Leo E Bonilla; Liam B Moran; Arnold Lindall
Journal:  Anal Chem       Date:  2003-02-01       Impact factor: 6.986

3.  Parallel Accumulation-Serial Fragmentation (PASEF): Multiplying Sequencing Speed and Sensitivity by Synchronized Scans in a Trapped Ion Mobility Device.

Authors:  Florian Meier; Scarlet Beck; Niklas Grassl; Markus Lubeck; Melvin A Park; Oliver Raether; Matthias Mann
Journal:  J Proteome Res       Date:  2015-11-13       Impact factor: 4.466

Review 4.  Reading protein modifications with interaction domains.

Authors:  Bruce T Seet; Ivan Dikic; Ming-Ming Zhou; Tony Pawson
Journal:  Nat Rev Mol Cell Biol       Date:  2006-07       Impact factor: 94.444

5.  Online automated in vivo zebrafish phosphoproteomics: from large-scale analysis down to a single embryo.

Authors:  Simone Lemeer; Martijn W H Pinkse; Shabaz Mohammed; Bas van Breukelen; Jeroen den Hertog; Monique Slijper; Albert J R Heck
Journal:  J Proteome Res       Date:  2008-02-29       Impact factor: 4.466

6.  Automated detection of inaccurate and imprecise transitions in peptide quantification by multiple reaction monitoring mass spectrometry.

Authors:  Susan E Abbatiello; D R Mani; Hasmik Keshishian; Steven A Carr
Journal:  Clin Chem       Date:  2009-12-18       Impact factor: 8.327

7.  Reduced-representation Phosphosignatures Measured by Quantitative Targeted MS Capture Cellular States and Enable Large-scale Comparison of Drug-induced Phenotypes.

Authors:  Jennifer G Abelin; Jinal Patel; Xiaodong Lu; Caitlin M Feeney; Lola Fagbami; Amanda L Creech; Roger Hu; Daniel Lam; Desiree Davison; Lindsay Pino; Jana W Qiao; Eric Kuhn; Adam Officer; Jianxue Li; Susan Abbatiello; Aravind Subramanian; Richard Sidman; Evan Snyder; Steven A Carr; Jacob D Jaffe
Journal:  Mol Cell Proteomics       Date:  2016-02-24       Impact factor: 5.911

8.  Proteomic and bioinformatic analysis of mammalian SWI/SNF complexes identifies extensive roles in human malignancy.

Authors:  Cigall Kadoch; Diana C Hargreaves; Courtney Hodges; Laura Elias; Lena Ho; Jeff Ranish; Gerald R Crabtree
Journal:  Nat Genet       Date:  2013-05-05       Impact factor: 38.330

Review 9.  Targeting EZH2 in cancer.

Authors:  Kimberly H Kim; Charles W M Roberts
Journal:  Nat Med       Date:  2016-02       Impact factor: 53.440

10.  A draft map of the mouse pluripotent stem cell spatial proteome.

Authors:  Andy Christoforou; Claire M Mulvey; Lisa M Breckels; Aikaterini Geladaki; Tracey Hurrell; Penelope C Hayward; Thomas Naake; Laurent Gatto; Rosa Viner; Alfonso Martinez Arias; Kathryn S Lilley
Journal:  Nat Commun       Date:  2016-01-12       Impact factor: 14.919

View more
  19 in total

Review 1.  Genomics, transcriptomics and proteomics to elucidate the pathogenesis of rheumatoid arthritis.

Authors:  Xinqiang Song; Qingsong Lin
Journal:  Rheumatol Int       Date:  2017-05-10       Impact factor: 2.631

2.  Semen Ziziphi Spinosae attenuates blood-brain barrier dysfunction induced by lipopolysaccharide by targeting the FAK-DOCK180-Rac1-WAVE2-Arp3 signaling pathway.

Authors:  Huayan Liu; Xin Zhang; Yujiao Liu; Nian Xin; Yulin Deng; Yujuan Li
Journal:  NPJ Sci Food       Date:  2022-06-02

Review 3.  In-Cell Labeling and Mass Spectrometry for Systems-Level Structural Biology.

Authors:  Juan D Chavez; Helisa H Wippel; Xiaoting Tang; Andrew Keller; James E Bruce
Journal:  Chem Rev       Date:  2021-07-07       Impact factor: 72.087

Review 4.  The Scope of Big Data in One Medicine: Unprecedented Opportunities and Challenges.

Authors:  Molly E McCue; Annette M McCoy
Journal:  Front Vet Sci       Date:  2017-11-16

Review 5.  Quantitative proteomics in lung cancer.

Authors:  Chantal Hoi Yin Cheung; Hsueh-Fen Juan
Journal:  J Biomed Sci       Date:  2017-06-14       Impact factor: 8.410

6.  Label-free quantitative proteomics identifies transforming growth factor β1 (TGF-β1) as an inhibitor of adipogenic transformation in OP9-DL1 cells and primary thymic stromal cells.

Authors:  Jianxin Tan; Yajun Wang; Siliang Wang; Simeng Wu; Zhe Yuan; Xike Zhu
Journal:  Cell Biosci       Date:  2019-06-14       Impact factor: 7.133

7.  Mass spectrometric identification of dystrophin, the protein product of the Duchenne muscular dystrophy gene, in distinct muscle surface membranes.

Authors:  Sandra Murphy; Kay Ohlendieck
Journal:  Int J Mol Med       Date:  2017-07-27       Impact factor: 4.101

8.  Serum Proteomics in African American Female Patients With Irritable Bowel Syndrome: An Exploratory Study.

Authors:  Kristen R Weaver; Gail D' Eramo Melkus; Jason Fletcher; Wendy A Henderson
Journal:  Nurs Res       Date:  2018 May/Jun       Impact factor: 2.381

9.  Serial-omics of P53-/-, Brca1-/- Mouse Breast Tumor and Normal Mammary Gland.

Authors:  Susanne B Breitkopf; Mateus De Oliveira Taveira; Min Yuan; Gerburg M Wulf; John M Asara
Journal:  Sci Rep       Date:  2017-11-06       Impact factor: 4.379

10.  Quantitative proteomics identified 3 oxidative phosphorylation genes with clinical prognostic significance in gastric cancer.

Authors:  Fei Su; Fen-Fang Zhou; Tao Zhang; Dan-Wen Wang; Da Zhao; Xiao-Ming Hou; Mao-Hui Feng
Journal:  J Cell Mol Med       Date:  2020-08-05       Impact factor: 5.310

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.