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Information‐dependent LC ‐ MS / MS acquisition with exclusion lists potentially generated on‐the‐fly: Case study using a whole cell digest of C lostridium thermocellum
Author(s) -
McQueen Peter,
Spicer Vic,
Rydzak Thomas,
Sparling Richard,
Levin David,
Wilkins John A.,
Krokhin Oleg
Publication year - 2012
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201100425
Subject(s) - clostridium thermocellum , chromatography , mass spectrometry , chemistry , retention time , on the fly , electrospray ionization , computer science , cellulose , biochemistry , cellulase , operating system
We have developed a real‐time graphic‐processor‐unit‐based search engine capable of high‐quality peptide identifications in <500 μs per spectrum. The steps of peptide/protein identification, in‐silico prediction of all possible tryptic peptides from these proteins, and the prediction of their expected retention times and m/z values take less than 5 s per cycle over ∼3000 MS / MS spectra. This lays the foundation for information‐dependent acquisition with exclusion lists generated on‐the‐fly, as the instrument continues to acquire data. While a complete evaluation of the dynamic exclusion system requires the participation from instrument vendors, we conducted a series of model experiments using a whole cell tryptic digestion of the bacterium C lostridium thermocellum . We ran a series of five iterative LC ‐ MS / MS runs, adding a new exclusion list at each of four chromatographic “tripping points” – the elution times of the four standard peptides spiked into the sample. Retention times of these standard peptides were also used for real‐time “chromatographic calibration.” The dynamic exclusion approach gave a ∼5% increase in confident protein identification (for typical 2 h LC ‐ MS / MS run), and reduced the average number of identified peptides per protein from 4.7 to 2.9. Its application to a two‐times shorter gradient gave a ∼17% increase in proteins identified. Further improvements are possible for instruments with better mass accuracy, by employing a more accurate retention prediction algorithm and by developing better understanding of the possible chemical modifications and fragmentations produced during electrospray ionization.