Literature DB >> 21328538

Quality control of nano-LC-MS systems using stable isotope-coded peptides.

Julia Maria Burkhart1, Thomas Premsler, Albert Sickmann.   

Abstract

In analytical sciences, there is a general need for quality control to assess whether a product or a process meets defined requirements. Especially in proteomics, which implies analysis of ten thousands of analytes within a complex mixture, quality control to validate LC-MS performance and method setup is inevitable to achieve day-to-day-, inter-system-, as well as inter-user reproducibility. Thus, results deriving from LC-MS analyses can be benchmarked and the need for system maintenance can be revealed. In particular with the advent of label-free quantification of peptides and proteins, which above all depends on highly stable and reproducible LC separations, HPLC performance has to be appropriately monitored throughout the entire analytical procedure to assure quality and validity of the obtained data. Oftentimes, proteolytic digests of standard proteins are used in this context; however, this approach implies some limitations, such as inadequate batch-to-batch reproducibility, limited (if any) dynamic range and compositional inflexibility. Here, we present an alternative strategy of nano-LC-MS/MS quality control based on a mixture of synthetic peptides covering the entire LC-gradient as well as a dynamic range of more than two orders of magnitude. Thus, (i) reproducibility of LC separation, (ii) MS performance (including limit of detection, identification and quantification), as well as (iii) overall nano-LC-MS system performance and reproducibility can be routinely monitored even in highly complex samples.
Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2011        PMID: 21328538     DOI: 10.1002/pmic.201000604

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


  7 in total

1.  Tyr728 in the kinase domain of the murine kinase suppressor of RAS 1 regulates binding and activation of the mitogen-activated protein kinase kinase.

Authors:  Claudia Sibilski; Thomas Mueller; Laxmikanth Kollipara; René P Zahedi; Ulf R Rapp; Thomas Rudel; Angela Baljuls
Journal:  J Biol Chem       Date:  2013-10-24       Impact factor: 5.157

2.  Rapid Assessment of Contaminants and Interferences in Mass Spectrometry Data Using Skyline.

Authors:  Matthew J Rardin
Journal:  J Am Soc Mass Spectrom       Date:  2018-04-17       Impact factor: 3.109

3.  DO-MS: Data-Driven Optimization of Mass Spectrometry Methods.

Authors:  R Gray Huffman; Albert Chen; Harrison Specht; Nikolai Slavov
Journal:  J Proteome Res       Date:  2019-05-28       Impact factor: 4.466

4.  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

5.  QCloud: A cloud-based quality control system for mass spectrometry-based proteomics laboratories.

Authors:  Cristina Chiva; Roger Olivella; Eva Borràs; Guadalupe Espadas; Olga Pastor; Amanda Solé; Eduard Sabidó
Journal:  PLoS One       Date:  2018-01-11       Impact factor: 3.240

6.  Combination of Proteogenomics with Peptide De Novo Sequencing Identifies New Genes and Hidden Posttranscriptional Modifications.

Authors:  B Blank-Landeshammer; I Teichert; R Märker; M Nowrousian; U Kück; A Sickmann
Journal:  mBio       Date:  2019-10-15       Impact factor: 7.867

7.  The STRIPAK signaling complex regulates dephosphorylation of GUL1, an RNA-binding protein that shuttles on endosomes.

Authors:  Valentina Stein; Bernhard Blank-Landeshammer; Kira Müntjes; Ramona Märker; Ines Teichert; Michael Feldbrügge; Albert Sickmann; Ulrich Kück
Journal:  PLoS Genet       Date:  2020-09-30       Impact factor: 5.917

  7 in total

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