Differential expression of proteins and identification of disease biomarkers
Differential expression profiling has been extensively used by the transcriptomic community to study quantitative differences between different conditions using microarrays. This always represents differences at the RNA level which need not always correlate with the protein amounts. SILAC provides an in vivo strategy to label the proteins with different stable isotopic forms of the aminoacids which makes it possible to monitor quantitative differences at the protein level between different conditions. This has been successfully used in studying differential protein expression to identify disease biomarkers by analyzing secretomes in case of pancreatic cancer, and Age-related macular degeneration (AMD) and differential membrane proteomics in case of breast cancer.
Gronborg et al., have used this strategy to do differential secretome proteomics in case of pancreatic cancer. Human pancreatic ductal epithelial cell line (HPDE) was grown in normal media and the pancreatic cancer cell line (Panc1) was grown in media supplemented with heavy isotopic forms of arginine and lysine (13C6). The media was harvested, proteins were resolved on a SDS PAGE and LC-MS/MS was carried out following trypsin digestion.
Similar approach has been undertaken by An et al., to identify differentially expressed proteins by human retinal pigment epithelium cell cultures derived from donors with age related macular degeneration and RPE cells from age matched healthy donors.
Majority of biomarkers and drug targets are membrane associated proteins. Liang et al., have used SILAC to do differential membrane proteomics in breast cancer to identify proteins that are differentially expressed on the surface of a breast cancer cell when compared to its normal.
Cell signaling dynamics
Following stimulation by an extracellular ligand, signal is often transduced into the nucleus through various protein intermediates that transmit information from one to another through various post translational modifications. Majority of such signal tranduction pathways use reversible phosphorylation as a means of transmitting signals. SILAC has been efficiently used by Olsen et al., to study temporal dynamics of signaling pathways by exploiting phosphorylation based enrichment methods coupled to mass spectrometry. The cells stimulated for different time points by the same ligand have been labeled with different isotopic forms of aminoacids thus making it possible to do quantiative measurements of a particular phospho peptide at various time points. This method has been successfully used to do temporal dynamic studies of EGFR pathway.
Analysis of yeast pheromone signaling pathway
Yeast is a prototype for all eukaryotic cells. It is one of the well studied cell systems and several of these studies have given substantial insight into finer details of numerous biological processes. GPCR (G-protein coupled receptor) signaling is one such area where yeast has been widely used as a model system. This has provided key insights into mitogen activated protein kinase pathways, including the pheromone response involved in mating of yeast cells. By using IMAC (immobilized metal affinity chromatography) based phospho peptide enrichment strategy following SILAC, Gruhler et al., have done quantitative proteomics to study pheromone induced phosphorylation changes in a yeast cell. This study made use of a yeast strain that is auxotrophic to arginine and lysine which were grown in a media containing heavy arginine and lysine (13C6) and wild type yeast grown in a normal media with light amino acids.
Identification of methylation sites
Methylation is one of the most important post translational modifications associated with several biological functions. It occurs predominantly on arginine and lysine residues. Traditionally, methods involving tritium methyl labeling have had fair amount of success but are restricted to studying one protein at a time following a laborious process. Ong et al., have efficiently used heavy methyl SILAC in which the cells were allowed to grow in media containing [13CD3] methionine, the cells metabolically convert [13CD3] methionine to the sole biological methyl donor [13CD3]S-adenosyl methionine. After few cell divisions in this media, all the in vivo methylation sites will be labeled with heavy methyl group. By using antibody based pull down of methylated proteins followed by liquid chromatography-tandem mass spectrometry, methylation sites have been identified.
Identification of protease substrates
One of the recent studies has used SILAC to identify the substrates of a bacterial protease. Neher et al., have generated a mutant protease that is able to bind to its substrate but lacks the capability to cleave it. Two bacterial cell populations were differentially labeled by growing one in a media containing naturally abundant isotopic form of lysine(12C6) and the other containing stable isotopic form of lysine(13C6) that is 6 daltons heavier. To identify the protease substrates in response to an environmental stress, they have used the wild type and the substrate trapping mutant protease to pull down the proteins from the bacterial lysates followed by mass spectrometry. This quantitative mass spectrometry approach has allowed them to identify the proteins that were abundant in the trap pull down when compared to the wild type thus providing the potential protease substrates.
Study of protein complexes/protein interactions
Several protein complexes exist in a cell which are involved in executing a plethora of functions. Identifying individual subunits that form these protein complex is an important step towards understanding the function of these complexes. 26 s proteasome is one such protein complex involved in protein degradation inside a cell. Yeast, a single cell eukaryote is a clean and simple system to study such complex macromolecules. Guerrero et al., have developed and used a novel approach called QTAX (quantitative analysis of tandem affinity purified in vivo cross-linked (X) protein complexes) to decipher in vivo protein protein interactions and applied this to globally map the 26 S proteasome interaction network in yeast. The SILAC strategy was successfully used in this setting to quantitatively distinguish the proteasome complex and its interacting proteins from background proteins.
Analysis of signaling pathways and effect of pharmacological inhibitors
Kinases form a major class of protein molecules that drive several signaling pathways involved in cell growth and differentiation. Aberrant activity of several kinases has now been attributed to the cause and progression of many cancers. EGFR family of receptor tyrosine kinases have found a lot of attention in the recent years due to their involvement in several malignancies. Pharmacological inhibitors that are capable of binding and inhibiting these receptors are being extensively studied to treat cancers that are caused or driven by these receptors. Her2(ERBB2) is one such receptor that has been associated with breast cancer. Though several Her2 inhibitors are now being tested to treat breast cancer patients with Her2 overexpression, the signaling intermediates and the effect of inhibitors on the pathways governed by Her2 are largely unknown. Bose et al., have addressed this issue by doing a phosphoproteomic analysis of Her2 signaling using 3T3 cells with basal levels of Her2, 3T3s overexpressing Her2 and the overexpressing cells treated with pharmacological inhibitors. They have done three state SILAC comparison using normal arginine (12C6), 13C6-Arg (6Da heavier), and 13C6,15N4-Arg (10Da heavier).
Apoptosis is an essential process for the development and maintenance of cellular homeostasis of higher eukaryotes. Nucleus assumes a central role in apoptosis where rapid chromatin condensation and DNA fragmentation occurs. During this event, several proteins shuttle in and out of nucleus which engage in a wide variety of activities. SILAC being an in vivo labeling strategy allows one to monitor these dynamically changing proteomes between sub-cellular organelles. To characterize these dynamic changes in the nuclear proteome, Hwang et al., have carried out quantitative proteomics by labeling control cell population with heavy isotopic forms of leucine(13C6) and lysine (13C6,15N2)and cells that are destined to undergo apoptosis with light leucine and lysine (12C6).