The detection, correlation, and comparison of peptide precursor and product ions from data independent LC-MS with data dependant LC-MS/MS.

The detection, correlation, and comparison of peptide and product ions from a data independent LC-MS acquisition strategy with data dependent LC-MS/MS is described. The data independent mode of acquisition differs from an LC-MS/MS data acquisition since no ion transmission window is applied with the first mass analyzer prior to collision induced disassociation. Alternating the energy applied to the collision cell, between low and elevated energy, on a scan-to-scan basis, provides accurate mass precursor and associated product ion spectra from every ion above the LOD of the mass spectrometer. The method therefore provides a near 100% duty cycle, with an inherent increase in signal intensity due to the fact that both precursor and product ion data are collected on all isotopes of every charge-state across the entire chromatographic peak width. The correlation of product to precursor ions, after deconvolution, is achieved by using reconstructed retention time apices and chromatographic peak shapes. Presented are the results from the comparison of a simple four protein mixture, in the presence and absence of an enzymatically digested protein extract from Escherichia coli. The samples were run in triplicate by both data dependant analysis (DDA) LC-MS/MS and data-independent, alternate scanning LC-MS. The detection and identification of precursor and product ions from the combined DDA search results of the four protein mixture were used for comparison to all other data. Each individual set of data-independent LC-MS data provides a more comprehensive set of detected ions than the combined peptide identifications from the DDA LC-MS/MS experiments. In the presence of the complex E. coli background, over 90% of the monoisotopic masses from the combined LC-MS/MS identifications were detected at the appropriate retention time. Moreover, the fragmentation pattern and number of associated elevated energy product ions in each replicate experiment was found to be very similar to the DDA identifications. In the case of the corresponding individual DDA LC-MS/MS experiment, 43% of the possible detectable peptides of interest were identified. The presented data illustrates that the time-aligned data from data-independent alternate scanning LC-MS experiments is highly comparable to the data obtained via DDA. The obtained information can therefore be effectively and correctly deconvolved to correlate product ions with parent precursor ions. The ability to generate precursor-product ion tables from this information and subsequently identify the correct parent precursor peptide will be illustrated in a companion manuscript.

Quantitative proteomic analysis by accurate mass retention time pairs.

Current methodologies for protein quantitation include 2-dimensional gel electrophoresis techniques, metabolic labeling, and stable isotope labeling methods to name only a few. The current literature illustrates both pros and cons for each of the previously mentioned methodologies. Keeping with the teachings of William of Ockham, "with all things being equal the simplest solution tends to be correct", a simple LC/MS based methodology is presented that allows relative changes in abundance of proteins in highly complex mixtures to be determined. Utilizing a reproducible chromatographic separations system along with the high mass resolution and mass accuracy of an orthogonal time-of-flight mass spectrometer, the quantitative comparison of tens of thousands of ions emanating from identically prepared control and experimental samples can be made. Using this configuration, we can determine the change in relative abundance of a small number of ions between the two conditions solely by accurate mass and retention time. Employing standard operating procedures for both sample preparation and ESI-mass spectrometry, one typically obtains under 5 ppm mass precision and quantitative variations between 10 and 15%. The principal focus of this paper will demonstrate the quantitative aspects of the methodology and continue with a discussion of the associated, complementary qualitative capabilities.