Literature DB >> 22577014

The development of selected reaction monitoring methods for targeted proteomics via empirical refinement.

Michael S Bereman1, Brendan MacLean, Daniela M Tomazela, Daniel C Liebler, Michael J MacCoss.   

Abstract

Software advancements in the last several years have had a significant impact on proteomics from method development to data analysis. Herein, we detail a method, which uses our in-house developed software tool termed Skyline, for empirical refinement of candidate peptides from targeted proteins. The method consists of four main steps from generation of a testable hypothesis, method development, peptide refinement, to peptide validation. The ultimate goal is to identify the best performing peptide in terms of ionization efficiency, reproducibility, specificity, and chromatographic characteristics to monitor as a proxy for protein abundance. It is important to emphasize that this method allows the user to perform this refinement procedure in the sample matrix and organism of interest with the instrumentation available. Finally, the method is demonstrated in a case study to determine the best peptide to monitor the abundance of surfactant protein B in lung aspirates.
© 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2012        PMID: 22577014      PMCID: PMC3643124          DOI: 10.1002/pmic.201200042

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


  52 in total

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4.  More than 100,000 detectable peptide species elute in single shotgun proteomics runs but the majority is inaccessible to data-dependent LC-MS/MS.

Authors:  Annette Michalski; Juergen Cox; Matthias Mann
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5.  Annual summary of vital statistics: 2000.

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Review 6.  Genetic disorders of surfactant proteins.

Authors:  Aaron Hamvas; F Sessions Cole; Lawrence M Nogee
Journal:  Neonatology       Date:  2007-06-07       Impact factor: 4.035

7.  Annual summary of vital statistics--2002.

Authors:  Elizabeth Arias; Marian F MacDorman; Donna M Strobino; Bernard Guyer
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8.  High sensitivity detection of plasma proteins by multiple reaction monitoring of N-glycosites.

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9.  Using iRT, a normalized retention time for more targeted measurement of peptides.

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10.  Human Proteinpedia: a unified discovery resource for proteomics research.

Authors:  Kumaran Kandasamy; Shivakumar Keerthikumar; Renu Goel; Suresh Mathivanan; Nandini Patankar; Beema Shafreen; Santosh Renuse; Harsh Pawar; Y L Ramachandra; Pradip Kumar Acharya; Prathibha Ranganathan; Raghothama Chaerkady; T S Keshava Prasad; Akhilesh Pandey
Journal:  Nucleic Acids Res       Date:  2008-10-23       Impact factor: 16.971

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  35 in total

1.  TGFβ-Responsive HMOX1 Expression Is Associated with Stemness and Invasion in Glioblastoma Multiforme.

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Journal:  Stem Cells       Date:  2016-07-04       Impact factor: 6.277

2.  Using Data Independent Acquisition (DIA) to Model High-responding Peptides for Targeted Proteomics Experiments.

Authors:  Brian C Searle; Jarrett D Egertson; James G Bollinger; Andrew B Stergachis; Michael J MacCoss
Journal:  Mol Cell Proteomics       Date:  2015-06-22       Impact factor: 5.911

Review 3.  Mass spectrometry: A platform for biomarker discovery and validation for Alzheimer's and Parkinson's diseases.

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4.  Mass Spectrometry Analysis of Lysine Posttranslational Modifications of Tau Protein from Alzheimer's Disease Brain.

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Review 5.  The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics.

Authors:  Lindsay K Pino; Brian C Searle; James G Bollinger; Brook Nunn; Brendan MacLean; Michael J MacCoss
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6.  A Cell-Surface Membrane Protein Signature for Glioblastoma.

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7.  Data-independent-acquisition mass spectrometry for identification of targeted-peptide site-specific modifications.

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8.  Deciphering Multifactorial Resistance Phenotypes in Acinetobacter baumannii by Genomics and Targeted Label-free Proteomics.

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9.  Rapid assessment of RNAi-mediated protein depletion by selected reaction monitoring mass spectrometry.

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10.  Design, implementation and multisite evaluation of a system suitability protocol for the quantitative assessment of instrument performance in liquid chromatography-multiple reaction monitoring-MS (LC-MRM-MS).

Authors:  Susan E Abbatiello; D R Mani; Birgit Schilling; Brendan Maclean; Lisa J Zimmerman; Xingdong Feng; Michael P Cusack; Nell Sedransk; Steven C Hall; Terri Addona; Simon Allen; Nathan G Dodder; Mousumi Ghosh; Jason M Held; Victoria Hedrick; H Dorota Inerowicz; Angela Jackson; Hasmik Keshishian; Jong Won Kim; John S Lyssand; C Paige Riley; Paul Rudnick; Pawel Sadowski; Kent Shaddox; Derek Smith; Daniela Tomazela; Asa Wahlander; Sofia Waldemarson; Corbin A Whitwell; Jinsam You; Shucha Zhang; Christopher R Kinsinger; Mehdi Mesri; Henry Rodriguez; Christoph H Borchers; Charles Buck; Susan J Fisher; Bradford W Gibson; Daniel Liebler; Michael Maccoss; Thomas A Neubert; Amanda Paulovich; Fred Regnier; Steven J Skates; Paul Tempst; Mu Wang; Steven A Carr
Journal:  Mol Cell Proteomics       Date:  2013-05-20       Impact factor: 5.911

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