Abstract
A typical bottom-up protein identification workflow involves proteolytic digestion followed by identification of the resulting peptides by LC-MS/MS using data-dependent acquisition (DDA). Recent developments in chromatography, such as uHPLC and superficially porous Fused-core particles, offer significantly improved peptide resolutions. The narrow peak widths, often only several seconds, can permit a 15 minute LC run to have a similar peak capacity as a 60 minute run using a traditional HPLC approach. In theory these larger peak capacities should provide higher protein coverage and/or more protein identifications when incorporated into a proteomic workflow. However, we initially observed a decrease in protein coverage when implementing one of these faster chromatographic approaches, and the more we optimized the LC separation the worse or MS results. Careful data inspection revealed that the MS/MS spectra were of low quality because the automated MS/MS events were occurring on the tail of the chromatographic peaks. In other words, our new separation strategy was “too fast” for our DDA settings. These observations led us to develop a general strategy to optimize DDA settings. Method: Data was acquired using an Agilent 1100 Capillary LC system, using Halo Peptide ES-C18 columns online with ESI ion trap MS detection on a Thermo-Fisher LTQ MS with a Michrom captive spray interface. Data was searched with Mascot, and ProteoIQ (Nusep, Athens GA) was used for data comparisons. Results/Conclusions: We have demonstrated that with DDA optimization these higher resolution separations provided by this new LC strategy do indeed lead to superior results in the analysis of individual proteins, simple protein mixtures, and complex proteomic samples. For instance, we are able to decrease or LC-MS/MS analysis (run to run) time from 100 minutes to 20 minutes without the loss of protein coverage or protein identification.
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