Application Note 24

Stable Isotope Labeling in Mammals with ¹⁵N Spirulina

Daniel B. McClatchy, Jeffrey Savas, and John R. Yates, III

The Scripps Research Institute, La Jolla, CA 92037 USA

Quantitative mass spectrometry (MS) has emerged as a powerful tool for biological research. Quantitative MS typically utilizes proteins labeled with heavy stable isotopes (e.g., ¹⁵N, ¹⁸O, or ¹³C). Labeled or “heavy” peptides maintain the same chemical characteristics as unlabeled or “light” peptides and co-elute into the mass spectrometer from liquid chromatography columns. In the mass spectrometer they are easily distinguished by their mass. Algorithms are then used to extract the light and heavy peptide ion chromatograms, which represent the peptide’s abundance. The light/heavy ratios are used to infer relative protein abundance. By mixing the same labeled protein standard with different unlabeled protein samples, changes in relative abundance can be determined between biological conditions.

Stable isotopes can be incorporated into peptides in vitro or in vivo. There are numerous covalent tags, such as iTRAQ^®, that react with specific amino acid side chains in vitro. A potential pitfall of these in vitro labeling techniques is the light and heavy samples are mixed after sample preparation and can introduce systematic errors in the quantitative analysis. Alternatively, metabolic labeling uses the cell’s own translational machinery to incorporate heavy isotopes into the entire proteome. Metabolic labeling allows for the light and heavy samples to be mixed prior to any sample preparation. Metabolic labeling is routinely performed in biological systems, such as bacteria, yeast, or mammalian cell culture, that grow rapidly and where the nutritional source is easily manipulated.

To study animal models of disease, the technique stable isotope labeling in mammals (SILAM) was developed to introduce ¹⁵N comprehensively into an entire rodent. In this application note, we describe the rodent-labeling process, experimental design, data analysis, and applications of SILAM.

Read more by downloading the application note.