Data-Dependent and Data-Independent Analyses

The type of mass spectrometric analysis performed for PTM detection depends on whether a single protein with a single PTM is being analyzed or if it is a global approach, such as a global phosphoproteomic analysis. When targeting a single protein or a subset of proteins for a PTM of interest, a straightforward strategy is to perform an enzymatic digestion followed by data-dependent MS/ MS analysis of peptides. In this approach, the intact molecular weight of each peptide in the full MS scan is analyzed, and then a selection of the most abundant peptides in the full MS scan are sequentially selected for fragmentation using one of several fragmentation methods. The resulting spectra are then analyzed either through de novo sequencing or more commonly using a search algorithm such as SEQUEST [30], Mascot [31], or Andromeda [32]. Peptides are then scored using an algorithm to calculate the false discovery rate or validated through manual spectral interpretation or by incorporation of a synthetic standard.

In traditional data-dependent acquisition (DDA), a proteomic sample is digested into peptides, separated often by reversed-phase chromatography, and ionized and analyzed by mass spectrometry. Typically instruments are programmed to select any ions that fall above a certain intensity threshold in full MS for subsequent MS/MS fragmentation. Although a powerful and highly utilized technique, the method is indeed biased to peptides that are of higher abundance, and lower level moieties such as post-translationally modified peptides may go undetected using DDA. Several years ago an alternative methodology called data-independent acquisition (DIA) was introduced which has slowly been gaining momentum [33]. In DIA analysis, all peptides within a defined mass-to-charge (m/z) window are subjected to fragmentation; the analysis is repeated as the mass spectrometer walks along the full m/z range. This results in the identification of lower level peptides, for example, post-translationally modified species present at substoichiometric levels compared to their nonmodified counterparts. It also allows accurate peptide quantification without being limited to profiling predefined peptides of interest and has proved useful in the biomarker community where quantitation on complex samples is routinely employed. The DIA method has matured in terms of utility over the past few years with the introduction of more user friendly and accurate search algorithms and spectral library search capabilities [34, 35]. Its utility as a tool to identify complex, low level, and isobaric amino acids has also recently been reported [36, 37].

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