Information-dependent LC-MS/MS acquisition with exclusion lists potentially generated on-the-fly: case study using a whole cell digest of Clostridium thermocellum |
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Authors: | McQueen Peter Spicer Vic Rydzak Thomas Sparling Richard Levin David Wilkins John A Krokhin Oleg |
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Affiliation: | Manitoba Centre for Proteomics and Systems Biology, Winnipeg, Canada. |
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Abstract: | 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 Clostridium 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. |
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Keywords: | Information‐dependent acquisition Peptide retention prediction RP HPLC Shotgun proteomics Technology |
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