Expanding the Use of Spectral Libraries in Proteomics

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 capture 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.

Toward Completion of the Human Proteome Parts List: Progress Uncovering Proteins That Are Missing or Have Unknown Function and Developing Analytical Methods

“…28 This year, the Proteomics Standards Initiative reports from the October 2017 Dagstuhl Seminar on Computational Proteomics and its April 2018 Heidelberg Workshop a framework for organizing the desired metadata for spectra using a controlled vocabulary in a spectral library. 29 This review addresses four levels of granularity, the library (collection), the individual peptide ion, the peak fragment ion, and the peak annotation level, as well as strategies for comparing spectra, generating representative spectra for a library, selecting optimal signature ions for targeted workflows, and merging two or more libraries. The rapid development of data-independent acquisition (DIA) workflows has spurred new interest in spectral libraries to analyze extracted ion chromatograms for peptide ions, whereas targeted workflows (SRM/PRM) increasingly rely on large-scale spectral libraries to determine which proteotypic peptides and fragment ions to monitor.…”

Peak identification and quantification by proteomic mass spectrogram decomposition

“…With the reference as strong prior knowledge, library searching can be performed relatively quickly and provides better identification. [13][14][15] We examined protMSD for analyzing a larger proteome of whole E. coli cell lysate with a 70min gradient using a dictionary of all theoretical peptides. However, the memory on a common desktop was not sufficient.…”

“…Despite the size of the computational tasks, which involve several million elements, the computation time and space required by protMSD are manageable on a common desktop computer, based on code optimization and appropriate choices of libraries for sparse computation, particularly, scipy-sparse. 15 For proteome-scale application using the E. coli sample, protMSD with the concept of library searching could reduce the running time to 24.17 minutes for all processing. The memory footprints for all sample processings were less than 2 GB.…”

Modified cysteine S-phosphopeptide standards for mass spectrometry-based proteomics

“…Thus, generating a reference MS-library of the model peptides, categorized by sequence, pCys-position, and pI values, would be a worthwhile effort. The methodological utility of spectral libraries has already been proven in detailed studies of phosphorylation events such as arginine phosphorylation in Staphylococcus aureus (Marx et al 2013;Junker et al 2018;Deutsch et al 2019).…”