Abstract
Quantitative proteomics aims to identify and quantify proteins in cells or organisms that have been obtained from different biological origin (e.g., “healthy vs. diseased”), that have received different treatments, or that have different genetic backgrounds. Protein expression levels can be quantified by labeling proteins with stable isotopes, followed by mass spectrometric analysis. Stable isotopes can be introduced in vitro by reacting proteins or peptides with isotope-coded reagents (e.g., iTRAQ, reductive methylation). A preferred way, however, is the metabolic incorporation of heavy isotopes into cells or organisms by providing the label, in the form of amino acids (such as in SILAC) or salts, in the growth media. The advantage of in vivo labeling is that it does not suffer from side reactions or incomplete labeling that might occur in chemical derivatization. In addition, metabolic labeling occurs at the earliest possible moment in the sample preparation process, thereby minimizing the error in quantitation. Labeling with the heavy stable isotope of nitrogen (i.e., 15N) provides an efficient way for accurate protein quantitation. Where the application of SILAC is mostly restricted to cell culture, 15N labeling can be used for micro-organisms as well as a number of higher (multicellular) organisms. The most prominent examples of the latter are Caenorhabditis elegans and Drosophila (fruit fly), two important model organisms for a range of regulatory processes underlying developmental biology. Here we describe in detail the labeling with 15N atoms, with a particular focus on fruit flies and C. elegans. We also describe methods for the identification and quantitation of 15N-labeled proteins by mass spectrometry and bioinformatic analysis.
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Gouw, J.W., Tops, B.B., Krijgsveld, J. (2011). Metabolic Labeling of Model Organisms Using Heavy Nitrogen (15N). In: Gevaert, K., Vandekerckhove, J. (eds) Gel-Free Proteomics. Methods in Molecular Biology, vol 753. Humana Press. https://doi.org/10.1007/978-1-61779-148-2_2
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DOI: https://doi.org/10.1007/978-1-61779-148-2_2
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