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Stable isotope labeling by amino acids in cell culture
About: Stable isotope labeling by amino acids in cell culture is a research topic. Over the lifetime, 1410 publications have been published within this topic receiving 68901 citations.
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TL;DR: SILAC is a simple, inexpensive, and accurate procedure that can be used as a quantitative proteomic approach in any cell culture system and is applied to the relative quantitation of changes in protein expression during the process of muscle cell differentiation.
5,653 citations
TL;DR: An approach for the accurate quantification and concurrent sequence identification of the individual proteins within complex mixtures based on isotope-coded affinity tags and tandem mass spectrometry is described.
Abstract: We describe an approach for the accurate quantification and concurrent sequence identification of the individual proteins within complex mixtures. The method is based on a class of new chemical reagents termed isotope-coded affinity tags (ICATs) and tandem mass spectrometry. Using this strategy, we com- pared protein expression in the yeast Saccharomyces cerevisiae, using either ethanol or galactose as a carbon source. The measured differences in protein expression correlated with known yeast metabolic function under glucose-repressed conditions. The method is redundant if multiple cysteinyl residues are present, and the relative quantification is highly accurate because it is based on stable isotope dilution techniques. The ICAT approach should provide a widely applicable means to compare quantitatively glob- al protein expression in cells and tissues.
4,893 citations
TL;DR: In-solution, online and on-column protocols for stable isotope dimethyl labeling of sample amounts ranging from sub-micrograms to milligrams are described, which uses inexpensive reagents and is applicable to virtually any sample.
Abstract: Accurate quantification of protein expression in biological systems is an increasingly important part of proteomics research. Incorporation of differential stable isotopes in samples for relative protein quantification has been widely used. Stable isotope incorporation at the peptide level using dimethyl labeling is a reliable, cost-effective and undemanding procedure that can be easily automated and applied in high-throughput proteomics experiments. Although alternative multiplex quantitative proteomics approaches introduce isotope labels at the organism level ('stable isotope labeling by amino acids in cell culture' (SILAC)) or enable the simultaneous analysis of eight samples (isobaric tagging for relative and absolute quantification (iTRAQ)), stable isotope dimethyl labeling is advantageous in that it uses inexpensive reagents and is applicable to virtually any sample. We describe in-solution, online and on-column protocols for stable isotope dimethyl labeling of sample amounts ranging from sub-micrograms to milligrams. The labeling steps take approximately 60–90 min, whereas the full protocol including digestion and (two-dimensional) liquid chromatography-mass spectrometry takes approximately 1.5–3 days to complete.
1,291 citations
TL;DR: The present method is general and affords a quantitative description of cellular differences at the level of protein expression and modification, thus providing information that is critical to the understanding of complex biological phenomena.
Abstract: A mass spectrometry-based method is described for simultaneous identification and quantitation of individual proteins and for determining changes in the levels of modifications at specific sites on individual proteins. Accurate quantitation is achieved through the use of whole-cell stable isotope labeling. This approach was applied to the detection of abundance differences of proteins present in wild-type versus mutant cell populations and to the identification of in vivo phosphorylation sites in the PAK-related yeast Ste20 protein kinase that depend specifically on the G1 cyclin Cln2. The present method is general and affords a quantitative description of cellular differences at the level of protein expression and modification, thus providing information that is critical to the understanding of complex biological phenomena.
1,071 citations
TL;DR: Comparison of protein levels of essentially all endogenous proteins in haploid yeast cells to their diploid counterparts spans more than four orders of magnitude in protein abundance with no discrimination against membrane or low level regulatory proteins.
Abstract: Mass spectrometry is a powerful technology for the analysis of large numbers of endogenous proteins. However, the analytical challenges associated with comprehensive identification and relative quantification of cellular proteomes have so far appeared to be insurmountable. Here, using advances in computational proteomics, instrument performance and sample preparation strategies, we compare protein levels of essentially all endogenous proteins in haploid yeast cells to their diploid counterparts. Our analysis spans more than four orders of magnitude in protein abundance with no discrimination against membrane or low level regulatory proteins. Stable-isotope labelling by amino acids in cell culture (SILAC) quantification was very accurate across the proteome, as demonstrated by one-to-one ratios of most yeast proteins. Key members of the pheromone pathway were specific to haploid yeast but others were unaltered, suggesting an efficient control mechanism of the mating response. Several retrotransposon-associated proteins were specific to haploid yeast. Gene ontology analysis pinpointed a significant change for cell wall components in agreement with geometrical considerations: diploid cells have twice the volume but not twice the surface area of haploid cells. Transcriptome levels agreed poorly with proteome changes overall. However, after filtering out low confidence microarray measurements, messenger RNA changes and SILAC ratios correlated very well for pheromone pathway components. Systems-wide, precise quantification directly at the protein level opens up new perspectives in post-genomics and systems biology.
941 citations