Stable Isotope Labeling by Amino acids in Cell culture (SILAC) is a simple, robust, yet powerful approach in mass spectrometry (MS)-based quantitative proteomics. SILAC labels cellular proteomes through normal metabolic processes, incorporating non-radioactive, stable isotope containing amino acids in newly synthesized proteins. Growth medium is prepared where natural (‘light’) amino acids are replaced by ‘heavy’ SILAC amino acids. Cells grown in this medium incorporate the heavy amino acids after five cell doublings and SILAC amino acids have no effect on cell morphology or growth rates. When light and heavy cell populations are mixed, they remain distinguishable by MS and protein abundances are determined from the relative MS signal intensities. A variant of the approach, Triple Encoding SILAC, allows three protein populations to be compared simultaneously. SILAC provides accurate relative quantification without any chemical derivatization or manipulation and enables steady-state proteome quantification or pulse-chase experiments.
Co-precipitating interacting proteins with an epitope tagged protein as the affinity bait is a popular approach to characterize a protein’s functional role in the cell. Classically performed with western blotting, applying proteomics instead provides an unbiased and sensitive readout of proteins interacting directly with the bait or in a larger protein complex. This proteomics experiment can identify co-precipitating proteins from a specific biological pathway, providing enormous insight into the functional role of the bait molecule. We have successfully applied proteins, small-molecules and nucleic acids as affinity baits in proteomics.
More recently, quantitative proteomics has been applied to this experimental paradigm to distinguish proteins bound specifically to the molecular bait versus non-specific protein interactions with linker regions or the solid support itself. Enrichment of proteins by affinity reagents can be compared using quantitative proteomics, discriminating interacting proteins from ones that bind non-specifically to beads. Current LC-MS analyses are very sensitive and most pull-down experiments yield many false positive, non-specifically bound proteins. By using the quantitative ratios to identify bona fide protein-small-molecule interactions amongst the non-specific interactions, the need for ad hoc optimization of experimental conditions in each pull-down experiment is diminished. Importantly, the usual trade-off between sensitivity and specificity of the affinity enrichment experiment is mitigated by the use of the quantitative information.
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