This technique is used for analysis of complex proteome samples (e.g., cell lysates, subcellular fractions) or multiprotein complexes (e.g., ribosomes or spliceosomes). This approach is often termed "shotgun" proteome analysis, because it is analogous to the shotgun sequencing approaches used in genome sequencing.
In contrast to 2D gel-based proteome analyses, the protein mixture is not first separated into components. Instead, the proteins are digested together to produce a highly complex mixture of peptides.
These peptides are analyzed by multidimensional LC-MS-MS and the MS-MS spectra are mapped to database peptide and protein sequences. This approach is the most powerful means of identifying the component proteins of a complex sample.
It is not uncommon for a multidimensional LC-MS-MS analysis to generate several thousand peptide identifications from a complex sample. The large data sets can be handled with new Bioinformatics Tools.
The objective of the approach is to obtain MS-MS spectra of as many of the peptides in the mixture as possible. This is accomplished by multidimensional peptide separations, typically combining strong cation exchange chromatography to separate the peptide mixture into 5-20 fractions, which then are individually analyzed by reverse phase LC-MS-MS. The multidimensional separation "spreads out" the complex peptide mixture into ion exchange fractions, which each contain fewer peptides
The sum of the identifications done on all the fractions is much greater than the number of identifications that could be done in a single reverse phase LC-MS-MS run. This approach has been referred to in the literature as MudPIT (Multidimensional Protein Identification Technique) and DALPC (Direct Analysis of Large Protein Complexes) and there are many variations of the basic approach.
While this approach is most commonly applied to identify components of complex protein mixtures or multiprotein complexes, multidimensional LC-MS-MS is also useful for identifying modified proteins. This is particularly true when modifications are of low stoichiometry or low abundance, as the modified peptides would be difficult to detect in complex mixtures. Multidimensional LC-MS-MS can be combined with stable isotope tagging to enable estimation of quantitative changes in complex proteome samples.