Literature DB >> 26435129

The 2012/2013 ABRF Proteomic Research Group Study: Assessing Longitudinal Intralaboratory Variability in Routine Peptide Liquid Chromatography Tandem Mass Spectrometry Analyses.

Keiryn L Bennett1, Xia Wang2, Cory E Bystrom3, Matthew C Chambers4, Tracy M Andacht5, Larry J Dangott6, Félix Elortza7, John Leszyk8, Henrik Molina9, Robert L Moritz10, Brett S Phinney11, J Will Thompson12, Maureen K Bunger13, David L Tabb14.   

Abstract

Questions concerning longitudinal data quality and reproducibility of proteomic laboratories spurred the Protein Research Group of the Association of Biomolecular Resource Facilities (ABRF-PRG) to design a study to systematically assess the reproducibility of proteomic laboratories over an extended period of time. Developed as an open study, initially 64 participants were recruited from the broader mass spectrometry community to analyze provided aliquots of a six bovine protein tryptic digest mixture every month for a period of nine months. Data were uploaded to a central repository, and the operators answered an accompanying survey. Ultimately, 45 laboratories submitted a minimum of eight LC-MSMS raw data files collected in data-dependent acquisition (DDA) mode. No standard operating procedures were enforced; rather the participants were encouraged to analyze the samples according to usual practices in the laboratory. Unlike previous studies, this investigation was not designed to compare laboratories or instrument configuration, but rather to assess the temporal intralaboratory reproducibility. The outcome of the study was reassuring with 80% of the participating laboratories performing analyses at a medium to high level of reproducibility and quality over the 9-month period. For the groups that had one or more outlying experiments, the major contributing factor that correlated to the survey data was the performance of preventative maintenance prior to the LC-MSMS analyses. Thus, the Protein Research Group of the Association of Biomolecular Resource Facilities recommends that laboratories closely scrutinize the quality control data following such events. Additionally, improved quality control recording is imperative. This longitudinal study provides evidence that mass spectrometry-based proteomics is reproducible. When quality control measures are strictly adhered to, such reproducibility is comparable among many disparate groups. Data from the study are available via ProteomeXchange under the accession code PXD002114.
© 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

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Year:  2015        PMID: 26435129      PMCID: PMC4762617          DOI: 10.1074/mcp.O115.051888

Source DB:  PubMed          Journal:  Mol Cell Proteomics        ISSN: 1535-9476            Impact factor:   5.911


  17 in total

1.  Platform for establishing interlaboratory reproducibility of selected reaction monitoring-based mass spectrometry peptide assays.

Authors:  A Prakash; T Rezai; B Krastins; D Sarracino; M Athanas; P Russo; M M Ross; H Zhang; Y Tian; V Kulasingam; A P Drabovich; C Smith; I Batruch; L Liotta; E Petricoin; E P Diamandis; D W Chan; M F Lopez
Journal:  J Proteome Res       Date:  2010-11-02       Impact factor: 4.466

2.  Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

Authors:  Gilbert S Omenn; David J States; Marcin Adamski; Thomas W Blackwell; Rajasree Menon; Henning Hermjakob; Rolf Apweiler; Brian B Haab; Richard J Simpson; James S Eddes; Eugene A Kapp; Robert L Moritz; Daniel W Chan; Alex J Rai; Arie Admon; Ruedi Aebersold; Jimmy Eng; William S Hancock; Stanley A Hefta; Helmut Meyer; Young-Ki Paik; Jong-Shin Yoo; Peipei Ping; Joel Pounds; Joshua Adkins; Xiaohong Qian; Rong Wang; Valerie Wasinger; Chi Yue Wu; Xiaohang Zhao; Rong Zeng; Alexander Archakov; Akira Tsugita; Ilan Beer; Akhilesh Pandey; Michael Pisano; Philip Andrews; Harald Tammen; David W Speicher; Samir M Hanash
Journal:  Proteomics       Date:  2005-08       Impact factor: 3.984

3.  MyriMatch: highly accurate tandem mass spectral peptide identification by multivariate hypergeometric analysis.

Authors:  David L Tabb; Christopher G Fernando; Matthew C Chambers
Journal:  J Proteome Res       Date:  2007-02       Impact factor: 4.466

4.  Proteomic parsimony through bipartite graph analysis improves accuracy and transparency.

Authors:  Bing Zhang; Matthew C Chambers; David L Tabb
Journal:  J Proteome Res       Date:  2007-08-04       Impact factor: 4.466

5.  Multi-site assessment of the precision and reproducibility of multiple reaction monitoring-based measurements of proteins in plasma.

Authors:  Terri A Addona; Susan E Abbatiello; Birgit Schilling; Steven J Skates; D R Mani; David M Bunk; Clifford H Spiegelman; Lisa J Zimmerman; Amy-Joan L Ham; Hasmik Keshishian; Steven C Hall; Simon Allen; Ronald K Blackman; Christoph H Borchers; Charles Buck; Helene L Cardasis; Michael P Cusack; Nathan G Dodder; Bradford W Gibson; Jason M Held; Tara Hiltke; Angela Jackson; Eric B Johansen; Christopher R Kinsinger; Jing Li; Mehdi Mesri; Thomas A Neubert; Richard K Niles; Trenton C Pulsipher; David Ransohoff; Henry Rodriguez; Paul A Rudnick; Derek Smith; David L Tabb; Tony J Tegeler; Asokan M Variyath; Lorenzo J Vega-Montoto; Asa Wahlander; Sofia Waldemarson; Mu Wang; Jeffrey R Whiteaker; Lei Zhao; N Leigh Anderson; Susan J Fisher; Daniel C Liebler; Amanda G Paulovich; Fred E Regnier; Paul Tempst; Steven A Carr
Journal:  Nat Biotechnol       Date:  2009-06-28       Impact factor: 54.908

6.  Quality control in LC-MS/MS.

Authors:  Thomas Köcher; Peter Pichler; Remco Swart; Karl Mechtler
Journal:  Proteomics       Date:  2011-02-07       Impact factor: 3.984

7.  The standard protein mix database: a diverse data set to assist in the production of improved Peptide and protein identification software tools.

Authors:  John Klimek; James S Eddes; Laura Hohmann; Jennifer Jackson; Amelia Peterson; Simon Letarte; Philip R Gafken; Jonathan E Katz; Parag Mallick; Hookeun Lee; Alexander Schmidt; Reto Ossola; Jimmy K Eng; Ruedi Aebersold; Daniel B Martin
Journal:  J Proteome Res       Date:  2007-08-21       Impact factor: 4.466

8.  Interlaboratory study characterizing a yeast performance standard for benchmarking LC-MS platform performance.

Authors:  Amanda G Paulovich; Dean Billheimer; Amy-Joan L Ham; Lorenzo Vega-Montoto; Paul A Rudnick; David L Tabb; Pei Wang; Ronald K Blackman; David M Bunk; Helene L Cardasis; Karl R Clauser; Christopher R Kinsinger; Birgit Schilling; Tony J Tegeler; Asokan Mulayath Variyath; Mu Wang; Jeffrey R Whiteaker; Lisa J Zimmerman; David Fenyo; Steven A Carr; Susan J Fisher; Bradford W Gibson; Mehdi Mesri; Thomas A Neubert; Fred E Regnier; Henry Rodriguez; Cliff Spiegelman; Stephen E Stein; Paul Tempst; Daniel C Liebler
Journal:  Mol Cell Proteomics       Date:  2009-10-26       Impact factor: 5.911

9.  A HUPO test sample study reveals common problems in mass spectrometry-based proteomics.

Authors:  Alexander W Bell; Eric W Deutsch; Catherine E Au; Robert E Kearney; Ron Beavis; Salvatore Sechi; Tommy Nilsson; John J M Bergeron
Journal:  Nat Methods       Date:  2009-06       Impact factor: 28.547

10.  Performance metrics for liquid chromatography-tandem mass spectrometry systems in proteomics analyses.

Authors:  Paul A Rudnick; Karl R Clauser; Lisa E Kilpatrick; Dmitrii V Tchekhovskoi; Pedatsur Neta; Niksa Blonder; Dean D Billheimer; Ronald K Blackman; David M Bunk; Helene L Cardasis; Amy-Joan L Ham; Jacob D Jaffe; Christopher R Kinsinger; Mehdi Mesri; Thomas A Neubert; Birgit Schilling; David L Tabb; Tony J Tegeler; Lorenzo Vega-Montoto; Asokan Mulayath Variyath; Mu Wang; Pei Wang; Jeffrey R Whiteaker; Lisa J Zimmerman; Steven A Carr; Susan J Fisher; Bradford W Gibson; Amanda G Paulovich; Fred E Regnier; Henry Rodriguez; Cliff Spiegelman; Paul Tempst; Daniel C Liebler; Stephen E Stein
Journal:  Mol Cell Proteomics       Date:  2009-10-16       Impact factor: 5.911

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  5 in total

1.  MSstatsQC: Longitudinal System Suitability Monitoring and Quality Control for Targeted Proteomic Experiments.

Authors:  Eralp Dogu; Sara Mohammad-Taheri; Susan E Abbatiello; Michael S Bereman; Brendan MacLean; Birgit Schilling; Olga Vitek
Journal:  Mol Cell Proteomics       Date:  2017-05-08       Impact factor: 5.911

2.  Quality Assessments of Long-Term Quantitative Proteomic Analysis of Breast Cancer Xenograft Tissues.

Authors:  Jian-Ying Zhou; Lijun Chen; Bai Zhang; Yuan Tian; Tao Liu; Stefani N Thomas; Li Chen; Michael Schnaubelt; Emily Boja; Tara Hiltke; Christopher R Kinsinger; Henry Rodriguez; Sherri R Davies; Shunqiang Li; Jacqueline E Snider; Petra Erdmann-Gilmore; David L Tabb; R Reid Townsend; Matthew J Ellis; Karin D Rodland; Richard D Smith; Steven A Carr; Zhen Zhang; Daniel W Chan; Hui Zhang
Journal:  J Proteome Res       Date:  2017-11-16       Impact factor: 4.466

Review 3.  A Review of the Scientific Rigor, Reproducibility, and Transparency Studies Conducted by the ABRF Research Groups.

Authors:  Sheenah M Mische; Nancy C Fisher; Susan M Meyn; Katia Sol-Church; Rebecca L Hegstad-Davies; Frances Weis-Garcia; Marie Adams; John M Ashton; Kym M Delventhal; Julie A Dragon; Laura Holmes; Pratik Jagtap; Kristopher E Kubow; Christopher E Mason; Magnus Palmblad; Brian C Searle; Christoph W Turck; Kevin L Knudtson
Journal:  J Biomol Tech       Date:  2020-04

4.  Variations of Histone Modification Patterns: Contributions of Inter-plant Variability and Technical Factors.

Authors:  Sylva Brabencová; Ivana Ihnatová; David Potěšil; Miloslava Fojtová; Jiří Fajkus; Zbyněk Zdráhal; Gabriela Lochmanová
Journal:  Front Plant Sci       Date:  2017-12-07       Impact factor: 5.753

5.  Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma.

Authors:  John A Bowden; Alan Heckert; Candice Z Ulmer; Christina M Jones; Jeremy P Koelmel; Laila Abdullah; Linda Ahonen; Yazen Alnouti; Aaron M Armando; John M Asara; Takeshi Bamba; John R Barr; Jonas Bergquist; Christoph H Borchers; Joost Brandsma; Susanne B Breitkopf; Tomas Cajka; Amaury Cazenave-Gassiot; Antonio Checa; Michelle A Cinel; Romain A Colas; Serge Cremers; Edward A Dennis; James E Evans; Alexander Fauland; Oliver Fiehn; Michael S Gardner; Timothy J Garrett; Katherine H Gotlinger; Jun Han; Yingying Huang; Aveline Huipeng Neo; Tuulia Hyötyläinen; Yoshihiro Izumi; Hongfeng Jiang; Houli Jiang; Jiang Jiang; Maureen Kachman; Reiko Kiyonami; Kristaps Klavins; Christian Klose; Harald C Köfeler; Johan Kolmert; Therese Koal; Grielof Koster; Zsuzsanna Kuklenyik; Irwin J Kurland; Michael Leadley; Karen Lin; Krishna Rao Maddipati; Danielle McDougall; Peter J Meikle; Natalie A Mellett; Cian Monnin; M Arthur Moseley; Renu Nandakumar; Matej Oresic; Rainey Patterson; David Peake; Jason S Pierce; Martin Post; Anthony D Postle; Rebecca Pugh; Yunping Qiu; Oswald Quehenberger; Parsram Ramrup; Jon Rees; Barbara Rembiesa; Denis Reynaud; Mary R Roth; Susanne Sales; Kai Schuhmann; Michal Laniado Schwartzman; Charles N Serhan; Andrej Shevchenko; Stephen E Somerville; Lisa St John-Williams; Michal A Surma; Hiroaki Takeda; Rhishikesh Thakare; J Will Thompson; Federico Torta; Alexander Triebl; Martin Trötzmüller; S J Kumari Ubhayasekera; Dajana Vuckovic; Jacquelyn M Weir; Ruth Welti; Markus R Wenk; Craig E Wheelock; Libin Yao; Min Yuan; Xueqing Heather Zhao; Senlin Zhou
Journal:  J Lipid Res       Date:  2017-10-06       Impact factor: 5.922

  5 in total

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