Processing strategies and software solutions for data‐independent acquisition in mass spectrometry

Abstract

Data-independent acquisition (DIA) offers several advantages over data-dependent acquisition (DDA) schemes for characterizing complex protein digests analyzed by LC-MS/MS. In contrast to the sequential detection, selection, and analysis of individual ions during DDA, DIA systematically parallelizes the fragmentation of all detectable ions within a wide m/z range regardless of intensity, thereby providing broader dynamic range of detected signals, improved reproducibility for identification, better sensitivity, and accuracy for quantification, and, potentially, enhanced proteome coverage. To fully exploit these advantages, composite or multiplexed fragment ion spectra generated by DIA require more elaborate processing algorithms compared to DDA. This review examines different DIA schemes and, in particular, discusses the concepts applied to and related to data processing. Available software implementations for identification and quantification are presented as comprehensively as possible and examples of software usage are cited. Processing workflows, including complete proprietary frameworks or combinations of modules from different open source data processing packages are described and compared in terms of software availability and usability, programming language, operating system support, input/output data formats, as well as the main principles employed in the algorithms used for identification and quantification. This comparative study concludes with further discussion of current limitations and expectable improvements in the short- and midterm future.

An algorithm to correct saturated mass spectrometry ion abundances for enhanced quantitation and mass accuracy in omic studies

“…Saturation correction is also relevant to data-independent acquisition (DIA) MS analyses, which are continuous MS/MS maps for all eluting LC peaks [30,31]. The datasets of the BSA tryptic digest spiked at different concentration in the yeast background were acquired in DIA mode by alternating low and high collision energy to generate MS and MS/MS spectra.…”

Genomic variability and protein species — Improving sequence coverage for proteogenomics

“…A critical point in DIA is to match the fragment ion spectra to the corresponding precursor ions. This can be done by superimposing the chromatographic elution profiles of peptide precursor and fragment ions (socalled spectral deconvolution) or by matching fragment ion spectra to spectral libraries [22][23][24]. Multiple peptides may co-elute within the selection window of DDA resulting in mixed or "chimeric" fragment ion spectra notably when analyzing highly complex peptide mixtures that exceed the separation capacity of the chromatographic column.…”

Ranking Fragment Ions Based on Outlier Detection for Improved Label-Free Quantification in Data-Independent Acquisition LC–MS/MS

“…8 Because DIA systematically parallelizes the fragmentation of all detectable ions within a wide m/z range regardless of intensity, it is particularly suitable to perform more consistent and accurate quantification by extracted ion chromatograms (XICs) at the fragment ion level. 9 Indeed, Venable et al 10 observed that the selectivity afforded by XICs at the MS/MS level resulted in reduced noise with an average signal-to-noise improvement of 3.5-fold, as well as a larger dynamic range (by at least a factor of 2) compared to precursor ion XICs from MS spectra. Along the same line, Gillet et al 11 illustrated how SWATH, in combination with targeted data extraction using information from spectral libraries (generated experimentally by surveying the sample of interest by DDA or in silico from public repositories), allows consistent quantification of proteins/peptides and displays highly correlated values compared to SRM.…”