Expanding the Use of Spectral Libraries in Proteomics
Year: 2018
Type: review
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.
Source: Journal of Proteome Research
Authors: Eric W. Deutsch, Yasset Perez-Riverol, Robert J. Chalkley, Mathias Wilhelm, Stephen Tate, Timo Sachsenberg, Mathias Walzer, Lukas Käll, Bernard Delanghe, Sebastian Böcker, Emma L. Schymanski, Paul Wilmes, Viktoria Dorfer, Bernhard Kuster, Pieter-Jan Volders, Nico Jehmlich, Johannes P. C. Vissers, Dennis W. Wolan, Ana Y. Wang, Luis Mendoza, Jim Shofstahl, Andrew W. Dowsey, Johannes Griss, Reza M. Salek, Steffen Neumann, Pierre-Alain Binz, Henry Lam, Juan Antonio Vizcaíno, Nuno Bandeira, Hannes Röst
Institutions: Institute for Systems Biology, European Bioinformatics Institute, University of California, San Francisco, Technical University of Munich, Sciex (Canada), University of Tübingen, Science for Life Laboratory, KTH Royal Institute of Technology, Thermo Fisher Scientific (Germany), Friedrich Schiller University Jena, University of Luxembourg, Luxembourg Centre for Systems Biomedicine, University of Applied Sciences Upper Austria, VIB-UGent Center for Medical Biotechnology, Helmholtz Centre for Environmental Research, Waters (United Kingdom), Scripps Research Institute, Thermo Fisher Scientific (United States), University of Bristol, Medical University of Vienna, Centre international de recherche sur le cancer, German Centre for Integrative Biodiversity Research, Leibniz Institute of Plant Biochemistry, Centre Hospitalier Universitaire Vaudois, Hong Kong University of Science and Technology, University of California San Diego, University of Toronto, Donnelly Centre for Cellular and Biomolecular Research
Language: English
Subfield: Spectroscopy
Field: Chemistry
Domain: Physical Sciences
Open Access status: green
Funders: World Health Organization, Wellcome Trust, Bundesministerium für Bildung und Forschung, Research Grants Council, University Grants Committee, National Institutes of Health, University of California, San Diego, Medical Research Council, Biotechnology and Biological Sciences Research Council, Natural Environment Research Council, National Institute of General Medical Sciences, National Institute of Biomedical Imaging and Bioengineering
Awards: G1344931536, G1443135587, The PRIDE database: A proteomics data hub in the life sciences, G1841486075, Belgium: Taming the application of statistics in proteomics and metabolomics, Big Data for Discovery Science, Building tandem mass spectral libraries for proteomics in the Big Data Era, Advancing data and metadata standards for proteomics mass spectra, G339059223, ProteomeTools - Translation des menschlichen Proteoms in molekulare und digitale Werkzeuge für die Wirkstoffentwicklung, die personalisierte Medizin und die Forschung in den Lebenswissenschaften, Teilprojekt A, G3855322314, de.NBI - Etablierungsphase - Leistungszentrum CiBi - Zentrum für integrative Bioinformatik, G4950536974, G5210260432, G5257154096, Center for Computational Mass Spectrometry, Development of Trans Proteomic Pipeline, an Analysis Suite for Mass Spectrometry, G6454556865, The PRIDE database: A proteomics data hub in the life sciences, G681206065, Bilateral NSF/BIO-BBSRC: Bayesian Quantitative Proteomics, Bilateral NSF/BIO-BBSRC: Bayesian Quantitative Proteomics, In silico mass spectrometry for biologists: Tools and resources for next-generation proteomics, G8640799587, G8645344291
OpenAlex ID: W2895719302