Literature DB >> 25327420

Tools for monitoring system suitability in LC MS/MS centric proteomic experiments.

Michael S Bereman1.   

Abstract

With advances in liquid chromatography coupled to tandem mass spectrometry technologies combined with the continued goals of biomarker discovery, clinical applications of established biomarkers, and integrating large multiomic datasets (i.e. "big data"), there remains an urgent need for robust tools to assess instrument performance (i.e. system suitability) in proteomic workflows. To this end, several freely available tools have been introduced that monitor a number of peptide identification (ID) and/or peptide ID free metrics. Peptide ID metrics include numbers of proteins, peptides, or peptide spectral matches identified from a complex mixture. Peptide ID free metrics include retention time reproducibility, full width half maximum, ion injection times, and integrated peptide intensities. The main driving force in the development of these tools is to monitor both intra- and interexperiment performance variability and to identify sources of variation. The purpose of this review is to summarize and evaluate these tools based on versatility, automation, vendor neutrality, metrics monitored, and visualization capabilities. In addition, the implementation of a robust system suitability workflow is discussed in terms of metrics, type of standard, and frequency of evaluation along with the obstacles to overcome prior to incorporating a more proactive approach to overall quality control in liquid chromatography coupled to tandem mass spectrometry based proteomic workflows.
© 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Keywords:  Mass spectrometry; Quality control; Shewhart control charts; Statistical process control; System suitability; Technology

Mesh:

Substances:

Year:  2014        PMID: 25327420     DOI: 10.1002/pmic.201400373

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


  12 in total

1.  Optimizing High-Resolution Mass Spectrometry for the Identification of Low-Abundance Post-Translational Modifications of Intact Proteins.

Authors:  Lisa E Kilpatrick; Eric L Kilpatrick
Journal:  J Proteome Res       Date:  2017-08-08       Impact factor: 4.466

2.  Multiplexed peptide analysis using data-independent acquisition and Skyline.

Authors:  Jarrett D Egertson; Brendan MacLean; Richard Johnson; Yue Xuan; Michael J MacCoss
Journal:  Nat Protoc       Date:  2015-05-21       Impact factor: 13.491

3.  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

4.  An Automated Pipeline to Monitor System Performance in Liquid Chromatography-Tandem Mass Spectrometry Proteomic Experiments.

Authors:  Michael S Bereman; Joshua Beri; Vagisha Sharma; Cory Nathe; Josh Eckels; Brendan MacLean; Michael J MacCoss
Journal:  J Proteome Res       Date:  2016-10-04       Impact factor: 4.466

5.  SWATH-MS Protocols in Human Diseases.

Authors:  Maria Del Pilar Chantada-Vázquez; María García Vence; Antonio Serna; Cristina Núñez; Susana B Bravo
Journal:  Methods Mol Biol       Date:  2021

6.  BatMass: a Java Software Platform for LC-MS Data Visualization in Proteomics and Metabolomics.

Authors:  Dmitry M Avtonomov; Alexander Raskind; Alexey I Nesvizhskii
Journal:  J Proteome Res       Date:  2016-06-28       Impact factor: 4.466

Review 7.  Clinical applications of quantitative proteomics using targeted and untargeted data-independent acquisition techniques.

Authors:  Jesse G Meyer; Birgit Schilling
Journal:  Expert Rev Proteomics       Date:  2017-05       Impact factor: 3.940

8.  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

Review 9.  Proteomic Applications in Antimicrobial Resistance and Clinical Microbiology Studies.

Authors:  Ehsaneh Khodadadi; Elham Zeinalzadeh; Sepehr Taghizadeh; Bahareh Mehramouz; Fadhil S Kamounah; Ehsan Khodadadi; Khudaverdi Ganbarov; Bahman Yousefi; Milad Bastami; Hossein Samadi Kafil
Journal:  Infect Drug Resist       Date:  2020-06-16       Impact factor: 4.003

Review 10.  Quick microbial molecular phenotyping by differential shotgun proteomics.

Authors:  Duarte Gouveia; Lucia Grenga; Olivier Pible; Jean Armengaud
Journal:  Environ Microbiol       Date:  2020-03-11       Impact factor: 5.491

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