Literature DB >> 30270626

Expanding the Use of Spectral Libraries in Proteomics.

Eric W Deutsch1, Yasset Perez-Riverol2, Robert J Chalkley3, Mathias Wilhelm4, Stephen Tate5, Timo Sachsenberg6, Mathias Walzer2, Lukas Käll7, Bernard Delanghe8, Sebastian Böcker9, Emma L Schymanski10, Paul Wilmes10, Viktoria Dorfer11, Bernhard Kuster4,12, Pieter-Jan Volders13, Nico Jehmlich14, Johannes P C Vissers15, Dennis W Wolan16, Ana Y Wang16, Luis Mendoza1, Jim Shofstahl17, Andrew W Dowsey18, Johannes Griss19, Reza M Salek20, Steffen Neumann21,22, Pierre-Alain Binz23, Henry Lam24, Juan Antonio Vizcaíno2, Nuno Bandeira25, Hannes Röst26.   

Abstract

The 2017 Dagstuhl Seminar on Computational Proteomics provided an opportunity for a broad discussion on the current state and future directions of the generation and use of peptide tandem mass spectrometry spectral libraries. Their use in proteomics is growing slowly, but there are multiple challenges in the field that must be addressed to further increase the adoption of spectral libraries and related techniques. The primary bottlenecks are the paucity of high quality and comprehensive libraries and the general difficulty of adopting spectral library searching into existing workflows. There are several existing spectral library formats, but none captures a satisfactory level of metadata; therefore, a logical next improvement is to design a more advanced, Proteomics Standards Initiative-approved spectral library format that can encode all of the desired metadata. The group discussed a series of metadata requirements organized into three designations of completeness or quality, tentatively dubbed bronze, silver, and gold. The metadata can be organized at four different levels of granularity: at the collection (library) level, at the individual entry (peptide ion) level, at the peak (fragment ion) level, and at the peak annotation level. Strategies for encoding mass modifications in a consistent manner and the requirement for encoding high-quality and commonly seen but as-yet-unidentified spectra were discussed. The group also discussed related topics, including strategies for comparing two spectra, techniques for generating representative spectra for a library, approaches for selection of optimal signature ions for targeted workflows, and issues surrounding the merging of two or more libraries into one. We present here a review of this field and the challenges that the community must address in order to accelerate the adoption of spectral libraries in routine analysis of proteomics datasets.

Entities:  

Keywords:  Dagstuhl Seminar; Proteomics Standards Initiative; formats; mass spectrometry; meeting report; spectral libraries; standards

Mesh:

Substances:

Year:  2018        PMID: 30270626      PMCID: PMC6443480          DOI: 10.1021/acs.jproteome.8b00485

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  74 in total

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2.  Automated approach for quantitative analysis of complex peptide mixtures from tandem mass spectra.

Authors:  John D Venable; Meng-Qiu Dong; James Wohlschlegel; Andrew Dillin; John R Yates
Journal:  Nat Methods       Date:  2004-09-29       Impact factor: 28.547

3.  Quantitative proteomic analysis by accurate mass retention time pairs.

Authors:  Jeffrey C Silva; Richard Denny; Craig A Dorschel; Marc Gorenstein; Ignatius J Kass; Guo-Zhong Li; Therese McKenna; Michael J Nold; Keith Richardson; Phillip Young; Scott Geromanos
Journal:  Anal Chem       Date:  2005-04-01       Impact factor: 6.986

Review 4.  Scoring proteomes with proteotypic peptide probes.

Authors:  Bernhard Kuster; Markus Schirle; Parag Mallick; Ruedi Aebersold
Journal:  Nat Rev Mol Cell Biol       Date:  2005-07       Impact factor: 94.444

5.  Using annotated peptide mass spectrum libraries for protein identification.

Authors:  R Craig; J C Cortens; D Fenyo; R C Beavis
Journal:  J Proteome Res       Date:  2006-08       Impact factor: 4.466

6.  Unique ion signature mass spectrometry, a deterministic method to assign peptide identity.

Authors:  Jamie Sherman; Matthew J McKay; Keith Ashman; Mark P Molloy
Journal:  Mol Cell Proteomics       Date:  2009-06-25       Impact factor: 5.911

7.  A uniform proteomics MS/MS analysis platform utilizing open XML file formats.

Authors:  Andrew Keller; Jimmy Eng; Ning Zhang; Xiao-jun Li; Ruedi Aebersold
Journal:  Mol Syst Biol       Date:  2005-08-02       Impact factor: 11.429

8.  MSFragger: ultrafast and comprehensive peptide identification in mass spectrometry-based proteomics.

Authors:  Andy T Kong; Felipe V Leprevost; Dmitry M Avtonomov; Dattatreya Mellacheruvu; Alexey I Nesvizhskii
Journal:  Nat Methods       Date:  2017-04-10       Impact factor: 28.547

9.  Conserved peptide fragmentation as a benchmarking tool for mass spectrometers and a discriminating feature for targeted proteomics.

Authors:  Umut H Toprak; Ludovic C Gillet; Alessio Maiolica; Pedro Navarro; Alexander Leitner; Ruedi Aebersold
Journal:  Mol Cell Proteomics       Date:  2014-03-12       Impact factor: 5.911

10.  2016 update of the PRIDE database and its related tools.

Authors:  Juan Antonio Vizcaíno; Attila Csordas; Noemi del-Toro; José A Dianes; Johannes Griss; Ilias Lavidas; Gerhard Mayer; Yasset Perez-Riverol; Florian Reisinger; Tobias Ternent; Qing-Wei Xu; Rui Wang; Henning Hermjakob
Journal:  Nucleic Acids Res       Date:  2015-11-02       Impact factor: 16.971

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2.  Acquiring and Analyzing Data Independent Acquisition Proteomics Experiments without Spectrum Libraries.

Authors:  Lindsay K Pino; Seth C Just; Michael J MacCoss; Brian C Searle
Journal:  Mol Cell Proteomics       Date:  2020-04-20       Impact factor: 5.911

Review 3.  Prediction of peptide mass spectral libraries with machine learning.

Authors:  Jürgen Cox
Journal:  Nat Biotechnol       Date:  2022-08-25       Impact factor: 68.164

4.  DIALib-QC an assessment tool for spectral libraries in data-independent acquisition proteomics.

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Journal:  Nat Commun       Date:  2020-10-16       Impact factor: 14.919

5.  Calibr improves spectral library search for spectrum-centric analysis of data independent acquisition proteomics.

Authors:  Jen-Hung Wang; Wai-Kok Choong; Ching-Tai Chen; Ting-Yi Sung
Journal:  Sci Rep       Date:  2022-02-07       Impact factor: 4.379

Review 6.  Review of Liquid Chromatography-Mass Spectrometry-Based Proteomic Analyses of Body Fluids to Diagnose Infectious Diseases.

Authors:  Hayoung Lee; Seung Il Kim
Journal:  Int J Mol Sci       Date:  2022-02-16       Impact factor: 5.923

7.  Augmentation of MS/MS Libraries with Spectral Interpolation for Improved Identification.

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Journal:  J Chem Inf Model       Date:  2022-07-29       Impact factor: 6.162

8.  mzMLb: A Future-Proof Raw Mass Spectrometry Data Format Based on Standards-Compliant mzML and Optimized for Speed and Storage Requirements.

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