Introduction: A multidimensional LC-LC-MS/MS method has been reported in the literature (Nature (1999) 17:676-682) as a powerful tool for large-scale protein analysis. The method provides high resolution, automation, high throughput and the ability to analyze a complicated mixture of proteins in a single run. In this paper, we use an automated two-dimensional (2D) capillary LC with tandem mass spectrometry (MS/MS) for the analysis of complicated protein mixtures. This 2D system utilizes two HPLC pumps, one strong cation exchange column, two reverse phase C 18 columns and an ion trap tandem mass spectrometer for the high throughput analysis of proteins.
Methods: Protein mixtures from cell lysates are digested and loaded onto a strong cation exchange column and then gradually released to a 0.18 mm diameter C18 column by elution with salt steps of increasing molarity. After loading, the peptide mixture is separate by a reverse phase HPLC and analyzed by a LCQ™ Deca XP mass spectrometer with a microflow electro-spray interface. The protein and peptide sequence is identified by comparison of theoretical and actual MS/MS spectra via TurboSEQUEST™ software.
Preliminary Data: Total cell extracts from human A431 cells were analyzed by both 1D and 2D LC-MS/MS. For a 1D separation, the gradient profile has a significant effect on the number of proteins that can be identified by their MS/MS spectra. A 30 minute gradient only identified 16 proteins. Extending the gradient profile to 480 minutes increases the number of proteins identified to 105. The use of 2D LC-MS/MS enabled the identification of many more proteins than 1D LC-MS/MS. The eight step salt gradient with 30 minute reverse phase separations (total run time of 5 hours) is able to identify 144 proteins. The 20 hour run provides the best results with 491 proteins identified. The 2D LC-MS/MS clearly provides more resolution and identifies more proteins than 1D LC-MS/MS.
When compared to the current two-dimensional electrophoresis-MS method, this on-line 2D LC-MS/MS system has advantages of higher identification capacity, higher sensitivity, higher throughput and a higher degree of automation. Thus, we reveal here an essential tool for proteomic analysis.
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