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Compartment modeling for mammalian protein turnover studies by stable isotope metabolic labeling.

ABSTRACT: Protein turnover studies on a proteome scale based on metabolic isotopic labeling can provide a systematic understanding of mechanisms for regulation of protein abundances and their transient behaviors. At this time, these large-scale studies typically utilize a simple kinetic model to extract protein dynamic information. Although many high-quality, protein isotope incorporation data are available from those experiments, accurate and additionally useful protein dynamic information cannot be extracted from the experimental data by use of the simple kinetic models. In this paper, we describe a formal connection between data obtained from elemental isotope labeling experiments and the well-known compartment modeling, and we demonstrate that an appropriate application of a compartment model to turnover of proteins from mammalian tissues can indeed lead to a better fitting of the experimental data.

SUBMITTER: Guan S

PROVIDER: S-EPMC3923578 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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Compartment modeling for mammalian protein turnover studies by stable isotope metabolic labeling.

Guan Shenheng S Price John C JC Ghaemmaghami Sina S Prusiner Stanley B SB Burlingame Alma L AL

Analytical chemistry 20120419 9

Protein turnover studies on a proteome scale based on metabolic isotopic labeling can provide a systematic understanding of mechanisms for regulation of protein abundances and their transient behaviors. At this time, these large-scale studies typically utilize a simple kinetic model to extract protein dynamic information. Although many high-quality, protein isotope incorporation data are available from those experiments, accurate and additionally useful protein dynamic information cannot be extr ...[more]

PMID: 22444387

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Project description:BackgroundThe length of time that a protein remains available to perform its function is significantly influenced by its turnover rate. Knowing the turnover rate of proteins involved in different processes is important to determining how long a function might progress even when the stimulus has been removed and no further synthesis of the particular proteins occurs. In this article, we describe the use of 15N-metabolic labeling coupled to GC-MS to follow the turnover of free amino acids and LC-MS/MS to identify and LC-MS to follow the turnover of specific proteins in Chlamydomonas reinhardtii.ResultsTo achieve the metabolic labeling, the growth medium was formulated with standard Tris acetate phosphate medium (TAP) in which14NH4Cl was replaced with 15NH415NO3 and (14NH4)6Mo7O24.4H2O was replaced with Na2MoO4.2H2O. This medium designated 15N-TAP allowed CC-125 algal cells to grow normally. Mass isotopic distribution revealed successful 15N incorporation into 13 amino acids with approximately 98% labeling efficiency. Tryptic digestion of the 55 kDa SDS-PAGE bands from 14N- and 15N-labeled crude algal protein extracts followed by LC-MS/MS resulted in the identification of 27 proteins. Of these, five displayed peptide sequence confidence levels greater than 95% and protein sequence coverage greater than 25%. These proteins were the RuBisCo large subunit, ATP synthase CF1 alpha and beta subunits, the mitochondrial protein (F1F0 ATP synthase) and the cytosolic protein (S-adenosyl homocysteine hydroxylase). These proteins were present in both labeled and unlabeled samples. Once the newly synthesized 15N-labeled free amino acids and proteins obtained maximum incorporation of the 15N-label, turnover rates were determined after transfer of cells into 14N-TAP medium. The t½ values were determined for the three plastid proteins (RuBisCo, ATP synthase CF1 alpha and beta) by following the reduction of the 15N-fractional abundance over time.ConclusionWe describe a more rapid and non-radioactive method to measure free amino acid and protein turnover. Our approach is applicable for determination of protein turnover for various proteins, which will lead to a better understanding of the relationship between protein lifetime and functionality.

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Compartment modeling for mammalian protein turnover studies by stable isotope metabolic labeling.

Publications

Compartment modeling for mammalian protein turnover studies by stable isotope metabolic labeling.

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