MudPIT, Multidimensional protein identification technology

This multidimensional protein identification technology (MudPIT) specifically incorporates a strong cationic exchange (SCX) column in tandem with an RP column to achieve maximal resolution and exquisite sensitivity. MudPIT is effective for studying complex proteomes such as mammalian cellular samples. It has been applied to large-scale protein characterization with identification of up to 1484 proteins from yeast in a single experiment.12... 

MS, either after electrophoretic separation and proteolysis or independently of 2DE [e.g., as in Multidimensional Protein Identification Technology (MudPIT), Ref. 21, also see Sec. 3.1.3), as a stand-alone system for protein identification. 

Another subsynaptic fraction derived directly from presynaptic specializations, the presynaptic particle fraction (PPF) can be separated from PSD by adjusting the pH of Triton X-100 extraction of isolated trans-synaptic scaffolds. As one might expect, it has been shown that the major proteins of the PPF, clathrin and dynamin, are concentrated in the presynaptic compartment (Phillips et al. 2005). These investigators used multidimensional protein identification technology (MudPIT) to compare the PPF and the PSD fraction. Of 341 proteins identified, 50 localized in the PPF, 231 in the PSD fraction, and 60 were found to be common to both fractions. The PPF was also characterized by a low proportion of actin and actin-associated proteins along with a high proportion of vesicle proteins. The authors concluded that the PPF consists of presynaptic proteins not cormected to the actin-based synaptic framework and that clathrin may be an anchorage scaffold for many presynaptic proteins. 

PS—alkyne probe, followed by a CC reaction to introduce a biotin tag with a tobacco etch virus (TEV) protease cleavage site. Tagged proteins were then enriched with streptavidin beads and subsequendy digested by trypsin. The supernatant contained peptide fragments of the enriched proteins and was, in contrast to the previous procedure, saved for subsequent analysis by multidimensional protein identification technology (MudPIT), a novel two-dimensional LC—MS/MS analysis method that will be discussed in more detail... 

Washburn MP (2004) Utilisation of proteomics datasets generated via multidimensional protein identification technology (MudPIT). Brief Funct Genomic Proteomic 3(3) 280-286... 

At times, the effect of separation by charge and by mass is combined in the same column with the use of a biphasic matrix the distal half of the column is filled with HPLC resin for separation based on the mass of proteins, and the proximal half of the column is packed with ion exchange matrix separating the proteins based on the charge. This biphasic column is used when the elution buffer for the two systems is the same or compatible. Such separation by a biphasic column is suitable for the multidimensional protein identification technology (mudPIT) by mass spectroscopy. 

T. Kislinger, A. O. Gramolini, D. H. MacLennan, and A. Emili, Multidimensional protein identification technology (MUDPIT) technical overview of a profiling method optimized for the comprehensive proteomic investigation of normal and diseased heart tissue, J. Am. Soc. Mass Spectrom. 16, 1207-1220 (2005). 

Rinas, A., Jones, L.M. (2015) Fast Photochemical Oxidation of Proteins Coupled to Multidimensional Protein Identification Technology (MudPIT) Expanding Footprinting Strategies to Complex Systems. J. Am. Soc. Mass Spectrom. 26 540-546. 

Figure 24,24 The high-throughput multidimensional protein identification technology (MudPIT) process. (Reprinted from International Journal for Parasitology, December 4, 32(13), Carucci, D.J. Yates, J. R. 3rd Florens, L. Exploring the Proteome of Plasmodium, pp. 1539-1542, Copyright 2002, with permission from Elsevier.)...

Large-scale protein identification by 2D-LC-MS/MS is also referred to as multidimensional protein identification technology (MudPIT) [73,74,220]. With this approach, protein identification relies solely on MS/MS data. It has been shown, however, that including the LC retention time as peptide-specific information can improve the quality of protein identification significantly. 

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