Peptide-Centric Proteome Analysis: An Alternative Strategy for the Analysis of Tandem Mass Spectrometry Data

Abstract

In mass spectrometry-based bottom-up proteomics, data-independent acquisition is an emerging technique because of its comprehensive and unbiased sampling of precursor ions. However, current data-independent acquisition methods use wide precursor isolation windows, resulting in cofragmentation and complex mixture spectra. Thus, conventional database searching tools that identify peptides by interpreting individual tandem MS spectra are inherently limited in analyzing data-independent acquisition data. Here we discuss an alternative approach, peptide-centric analysis, which tests directly for the presence and absence of query peptides. We discuss how peptide-centric analysis resolves some limitations of traditional spectrum-centric analysis, and we outline the unique characteristics of peptide-centric analysis in general. Tandem mass spectrometry has become the technology of choice for proteome characterization. In a typical bottom-up proteomic experiment, a mixture of proteins is proteolytically digested into peptides, separated by liquid chromatography, and analyzed using tandem mass spectrometry. The ultimate goal is to identify and quantify proteins by detecting and quantifying individual peptides, thereby shedding light on the underlying cellular mechanisms or phenotype. Several modes of data acquisition have been developed for bottom-up proteomics. The most commonly applied mode uses data-dependent acquisition (DDA) 1 , in which tandem MS (MS/MS) spectra are acquired from the dissociation of precursor ions selected from an MS survey spectrum. Constrained by the speed of instrumentation, DDA can sample only a subset of precursor ions for MS/MS characterization, generally targeting the top-N most abundant ions detected in the most recent survey spectrum. In addition, DDA is typically coupled with a method referred to as "dynamic exclusion" (1) that attempts to prevent reselection of the same m/z for some specified period of time. These acquisition strategies greatly increase proteome coverage and extend the dynamic range of detection for shotgun proteomics. The resulting MS/MS spectra are typically analyzed using sequence database searching software such as SEQUEST, Mascot, X!Tandem, MaxQuant, Comet, MS-GFϩ, or OMSSA (2-8). Because these algorithms identify peptides by first associating each individual spectrum with a matching peptide sequence and then aggregating the thus matched spectra into a list of identified peptides, we refer to them as "spectrum-centric analyses." In spectrum-centric analysis, spectra are most commonly interpreted using database searching, but can also be interpreted using de novo sequencing (9 -11), or by searching against a spectrum library (12-14). For the past two decades, spectrum-centric analysis has been an essential driving force for the development of large-scale shotgun proteomics using DDA.DDA is a powerful and well-established technique for LC-MS/MS data acquisition. By targeting precursor ions observed in MS survey scans with highly selective MS/MS scans, DDA generates a l...

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

“…For example, Ting et al presented a perspective on spectrum-centric analysis versus peptide-centric analysis, the latter of which assesses the probability that a peptide is present without requiring a spectral library [47]. This ‘peptide-centric analysis’ has been implemented in the software PECAN, which tests directly for statistical probability that the query peptides are present [47]. Another tool recently introduced by our group makes use of uDIA and isotopic labeling to assess absolute stoichiometry of lysine acetylation and succinylation [53].…”

The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics

“…Data‐independent acquisition (DIA) such as Sequential Window Acquisition of all Theoretical Fragment ion spectra (SWATH) forgo pre‐programmed precursor‐fragment pairs, widening the isolation windows to activate all ions in a pre‐specified mass‐to‐charge (m/z) range. A detailed review of DIA methodology can be found elsewhere, including peptide‐centric approaches to DIA . It is also possible, through MS1 filtering informatics techniques, to use data dependent acquisition (DDA) for quantitative analysis as opposed to conventional detection analysis.…”

Site-specific analysis of changes in the glycosylation of proteins in liver cirrhosis using data-independent workflow with soft fragmentation

“…However, methods for quantitative comparisons of site-specific protein glycoforms have only begun to emerge (9). While the comparative analysis of proteins by data independent acquisition (DIA) has improved the efficiency of quantitative proteomics analyses (20;21), applications of DIA methods to the analysis of posttranslational modifications are limited and virtually non-existent for glycoproteins (22). In this paper, we introduce a workflow for DIA analysis of N-glycopeptides under soft CID fragmentation conditions and document applicability of the glycopeptide DIA (Glycopeptide SWATH or GP-SWATH) workflow to the comparative analysis of fucosylated complex glycoforms of ten abundant plasma glycoprotein groups in the context of liver cirrhosis.…”