Discovery-based relative quantification is an analytical approach that allows the scientist to determine relative protein abundance changes across a set of samples simultaneously and without the requirement for prior knowledge of the proteins involved.
To understand the functions of individual proteins and their place in complex biological systems, it is often necessary to measure changes in protein abundance relative to changes in the state of the system. These measurements have traditionally been performed using Western blot analyses. More recently, modern proteomics has evolved to include a variety of technologies for the routine quantitative analyses of both known and unknown targets. Discovery-based relative quantification is an analytical approach that allows the scientist to determine relative protein abundance changes across a set of samples simultaneously and without the requirement for prior knowledge of the proteins involved. Here we describe three commonly used techniques for relative quantitation of unknown protein/peptide targets using mass spectrometry.
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Overview
Workflow Overview for SILAC Quantitation
SILAC-based quantitation is a powerful and widely used technique for identifying and quantifying relative changes in complex protein samples. It can be applied to complex biomarker discovery and systems biology studies as well as to isolated proteins and protein complexes. As its name implies, SILAC involves labeling protein samples in vivo with a heavy-isotope-labeled form of an amino acid. Inclusion of the labeled amino acid in cell or tissue culture media results in replacement of the natural light amino acid with the heavy form in newly synthesized proteins. Cells grown under differing experimental conditions (and in heavy or light media) can be mixed and all subsequent processing steps can be performed on the combined sample. This serves to greatly reduce sample handling variability, resulting in more accurate quantitation. Additionally, the labeled peptides do not require any specific fragmentation modality, meaning the samples can be analyzed by CID, ETD, and/or HCD fragmentation, which leads to the identification of more peptides.
Literature Highlights
Original SILAC paper:
Ong SE, Blagoev B, et al.
Mol Cell Proteomics. 2002 May;1(5):376-86.
Deeb SJ, D'Souza R, et al.
Mol Cell Proteomics. 2012 Mar 21.
Download the Brochure Thermo Scientific Solutions for Quantitative Proteomics
Sample Preparation
Sample Preparation Workflow for SILAC Quantitation
Stable isotope labeling with amino acids in cell culture (SILAC) is a method for MS-based quantitation of differential protein abundances in two to three samples. SILAC involves metabolic incorporation of ‘heavy’ 13C- and/or 15N-labeled amino acids into proteins of actively growing cells using specially formulated media and dialyzed serum. Typical experiments involve growing two cell populations that are identical except that one of them contains the ‘light’ form and the other the ‘heavy’ form of particular amino acids (e.g. both 12C6,14N2 L-lysine with 12C8,14N2 L-arginine and 13C6,15N2 L-lysine with 13C8,15N2 L-arginine, respectively). The heavy and light amino acids are incorporated into proteins through natural cellular protein synthesis. Following alteration of the proteome in one sample, by such processes as chemical treatment or genetic manipulation, equal numbers of cells from both cell populations are combined and proteins are isolated and digested. The resulting peptides are then identified and quantified by MS. As labeled and unlabeled samples are combined during the initial steps of sample preparation, SILAC minimizes the quantitative error inherent in handling separate samples in parallel.
The protein preparation steps that follow the combination of heavy- and light-labeled cells can vary widely depending on the goal of the experiments. The mixing of the samples permits a variety of enrichment techniques including fractionation and immunoprecipitation at both the protein and/or peptide level. These techniques can improve the detection of abundance changes for both low-abundance proteins and post-translational modifications such as phosphorylation and/or glycosylation. In the most typical SILAC-based experiment, cells are grown in media containing light and heavy versions of lysine and arginine and then the proteins are digested into a peptide mixture with trypsin, which cleaves C-terminal to lysine and arginine residues. This approach is designed to result in a peptide mixture with one heavy label per peptide.
A step-by-step SILAC procedure including supplementation of media, incorporation of heavy isotope-labeled amino acids, and determination of isotope incorporation efficiency can be downloaded here.
Literature Highlights
Original SILAC paper:
Ong SE, Blagoev B, et al.
Mol Cell Proteomics. 2002 May;1(5):376-86.
Super-SILAC allows classification of diffuse large B-cell lymphoma subtypes by their protein express...
Deeb SJ, D'Souza R, et al.
Mol Cell Proteomics. 2012 Mar 21.
Everley PA, Krijgsveld J, et al.
Mol Cell Proteomics. 2004 Jul;3(7):729-35.
Functional and quantitative proteomics using SILAC
Mann M.
Nat Rev Mol Cell Biol. 2006 Dec;7(12):952-8.
Related Products
Link to download a comprehensive Mass Spectrometry Sample Preparation Handbook
A wide selection of SILAC isotope labeling reagents and kits are commercially available. The kits contain all of the reagents needed for comparing two or three sample types in a wide variety of mammalian cell lines. They are compatible with many Thermo Scientific protein/peptide enrichment technologies.
Detailed information for all Thermo Scientific SILAC products can be found here.
Mass Spectrometry
Mass Spectrometry Workflow for SILAC Quantitation
As peptides labeled with “heavy” and “light” amino acids have negligible differences in their LC partitioning behavior, they co-elute during online reverse-phase column separation and, therefore, are detected simultaneously during MS analysis. Depending on the heavy isotopes used (for example, 13C6 L-Arginine, 13C6 15N4 L-Arginine, 3C6 L-Lysine, and/or 13C6 15N2 L-Lysine), the precursor ion pairs (or triplets) for any given peptide species will be separated by a specific mass. This mass difference is used to detect and assign related peptide ions. Their relative intensities are then used to determine the relative abundances of the corresponding protein in the original cell populations. The accuracy of the results are very dependent on both the quality of the LC separation (to reduce the number of co-eluting species) and the resolving power of the mass spectrometer (to resolve co-eluting isobaric species). This is especially important for samples of high complexity and/or high dynamic range.
For quantitative mass spectrometry, LC gradients greater than one hour with columns at least 15 cm in length are recommended. Sample load quantities should be optimized to maximize base-peak separation and reproducibility, and to minimize precursor-ion overlap.
In contrast to reporter-ion-based quantitation methods, precursor-based quantitation methods (including SILAC and label-free quantitation), do not impose limits on the types of fragmentation approach that can be used for MS/MS. Consequently, CID, ETD, and/or HCD fragmentation can all be used, which can lead to the identification of more peptides by virtue of the complementary nature of these fragmentation types (1).
Another unique feature of the Orbitrap-based platforms is the “mass tags” feature in the data acquisition software, which restricts data-dependent MS/MS to single precursors in SILAC pairs. This eliminates the acquisition of redundant spectra, permitting deeper quantitative penetration into the proteome.
References
Scheffler K, Damoc E, Moehring T.
Application Note 30217
Literature Highlights
Comprehensive mass- spectrometry-based proteome quantification of haploid versus diploid yeast
de Godoy LM, Olsen JV, et al.
Nature. 2008 Oct 30;455(7217):1251-4.
Deeb SJ, D'Souza R, et al.
Mol Cell Proteomics. 2012 Mar 21.
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Data Analysis
Data Analysis Workflow for SILAC Quantitation
Quantitation is performed at the MS level by comparing the intensities of the light- and heavy-labeled precursor ions at high resolution. Proteins are identified using the accurate-mass precursor information combined with CID, ETD, and/or HCD fragmentation data. The relative peak intensities of multiple distinct peptides from each protein are averaged to determine the overall relative abundance of the protein (and thus the fold-change) between the experimental and control conditions.
Peptide SILAC ratios can be calculated using the ‘Precursor Ions Quantifier’ node in Thermo Scientific Proteome Discoverer software (version 1.2 or later) along with a pre-built Quantification Method included with the software). Custom quantification methods can also be created by editing the SILAC duplex and triplex method.
For detailed step-by-step information about quantitative analysis using Proteome Discoverer™ software and to download a free 60-day demonstration version of Proteome Discoverer software version 1.3, please visit the Thermo Scientific Proteomics Software Portal.
Resources
Brochure: Thermo Scientific Proteome Discoverer: Mass Informatics Platform for Protein Scientists
Poster: A New Software for Automated, High-Throughput Quantitative Proteomics
LINKS
Proteome Discoverer Software
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