Measurement of protein turnover rates by heavy water labeling of nonessential amino acids

Busch, Robert; Kim, Yoo-Kyeong; Neese, Richard A.; Schade-Serin, Valerie; Collins, Michelle; Awada, Mohamad; Gardner, J. L.; Beysen, Carine; Marino, Michael; Misell, Lisa; Hellerstein, Marc K.

doi:10.1016/j.bbagen.2005.12.023

Cited by 225 publications

(316 citation statements)

References 39 publications

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“…This result suggests the method can detect small levels of enrichment, even for very low natural abundance levels. The ability to detect such low enrichment may be extremely valuable for measuring the incorporation of isotopically enriched amino acids into proteins [31][32][33].Overall, the results presented in Table 4 compare favorably with similar work for derivatized amino acids [34][35][36]. These studies used ESI with either ion trap or QMS, as well as fast atom bombardment ionization-QMS.…”

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Inaccuracies in selected ion monitoring determination of isotope ratios obviated by profile acquisition: nucleotide 18O/16O measurements

Cassano

Wang

Anderson

et al. 2007

Analytical Biochemistry

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Precise and accurate measurements of isotopologue distributions (IDs) in biological molecules are needed for the determination of isotope effects, quantitation by isotope dilution and quantifying isotope tracers employed in both metabolic and biophysical studies. While single ion monitoring (SIM) yields significantly greater sensitivity and signal/noise than profile mode acquisitions, we show that small changes in the SIM window width and/or center can alter experimentally determined isotope ratios by up to 5%, resulting in significant inaccuracies. This inaccuracy is attributed to mass granularity, the differential distribution of digital data points across the m/z ranges sampled by SIM. Acquiring data in the profile mode and fitting the data to an equation describing a series of equally spaced and identically shaped peaks eliminates the inaccuracies associated with mass granularity with minimal loss of precision. Additionally a method of using the complete ID profile data that inherently corrects for "spillover" and for the natural abundance ID has been used to determine 18 Keywords isotope ratio; isotopologue distribution; mass isotopomer distribution; tandem mass spectrometry; heavy atom isotope effect; oxygen-18; nucleotide; mass granularity; whole molecule mass spectrometry 1 This work supported by NIH grants GM56740 (M.E.H.), R33 DK07029 (VEA & SP) and a HHMI predoctoral fellowship (A.G.C.). *Corresponding Authors: Vernon E. Anderson and Michael E. Harris, Department of Biochemistry, Case Western Reserve University School of Medicine, Cleveland, OH 44106-4935, Phone: 216-368-2511 (VEA); 216-368-4779 (MEH), Fax: 216-368-3419, Email: vernon.anderson@case.edu; michael.harris@cwru.edu. 3 Current address: Department of Chemistry, Drew University, Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. NIH Public Access Author ManuscriptAnal Biochem. Author manuscript; available in PMC 2008 August 1. Published in final edited form as:Anal Biochem. 2007 August 1; 367(1): 28-39. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptHeavy atom isotope effects generated by substituting 13 C, 15 N or 18 O are important tools for probing the mechanisms and transition states of chemical reactions [1], including enzymecatalyzed reactions [2][3][4][5][6][7]. Because the observed effects for isotopic substitution of heavy atoms are extremely small, typically a few percent, they cannot be determined by direct comparison of experimentally determined rate constants. Instead, heavy atom isotope effects are generally measured by internal competition methods that...

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Inaccuracies in selected ion monitoring determination of isotope ratios obviated by profile acquisition: nucleotide 18O/16O measurements

Cassano

Wang

Anderson

et al. 2007

Analytical Biochemistry

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“…For example, the abundance and mass vector for hydrogen are given by: (9) The atomic μ-domain isotope distribution functions can be conveniently expressed in terms of the vectors â j and m̂j: (10) The molecular formula for a peptide is expressed as H νH C νC N νN O νO S νS , where the ν j are the number of atoms of each type. The molecular formula can be equivalently expressed as vector n̂ of length n elements whose indices are the set of ν j : (11) The set of atomic μ-domain functions can be similarly arranged into a vector F̂n(μ): (12) The μ-domain molecular isotope distribution function can be expressed in the compact form (13) where the exponentiation of the vector accumulates the product of the appropriate μ-domain functions, giving an equivalent expression to eq 4. These expressions give a compact formalism that will facilitate subsequent discussion of residue-based μ-domain functions.…”

Section: Vector Formalism For Calculation Of Isotope Distributions Inmentioning

confidence: 99%

“…An additional atom type, C* must be defined for the 13 C-labeled atoms, and the residue compositions are given by: (30) which gives the following residue vectors for the unlabeled and labeled leucine residues, respectively:…”

Section: Description Of Fractional Residue Labelingmentioning

confidence: 99%

“…It is straightforward to define a variable fractional 13 Cenrichment in analogy to the fractional 15 N-labeling described above. The abundance vector for the new fractionally labeled C* atom is specified as: (33) These expressions provide an analytical description of a combination of fractional residue and fractional atom labeling that can be used for least-squares fitting of fractionally labeled peptides.…”

Section: Description Of Fractional Residue Labelingmentioning

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Quantitative Analysis of Isotope Distributions In Proteomic Mass Spectrometry Using Least-Squares Fourier Transform Convolution

et al. 2008

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Quantitative proteomic mass spectrometry involves comparison of the amplitudes of peaks resulting from different isotope labeling patterns, including fractional atomic labeling and fractional residue labeling. We have developed a general and flexible analytical treatment of the complex isotope distributions that arise in these experiments, using Fourier transform convolution to calculate labeled isotope distributions and least-squares for quantitative comparison with experimental peaks. The degree of fractional atomic and fractional residue labeling can be determined from experimental peaks at the same time as the integrated intensity of all of the isotopomers in the isotope distribution. The approach is illustrated using data with fractional 15 N-labeling and fractional 13 C-isoleucine labeling. The least-squares Fourier transform convolution approach can be applied to many types of quantitive proteomic data, including data from stable isotope labeling by amino acids in cell culture and pulse labeling experiments.Stable isotope labeling in cells coupled with mass spectrometry has many important applications in the analysis of protein expression, modification, turnover, and metabolism. 1 Cells and organisms can be isotopically labeled by supplying labeled precursors in the form of nutrients such as amino acids, glucose, and ammonia. These labeled precursors are incorporated into proteins, whose resulting isotope labeling patterns reflect their abundance and the dynamics of protein synthesis and turnover. The era of quantitative proteomics began with experiments where mixtures of unlabeled control cells and 15 N-labeled or isotope depleted test cells were quantitatively analyzed to determine protein expression and phosphorylation levels. 2,3 More recently, the SILAC technique was developed based on specific amino acid labeling of cells for quantitative analysis of protein expression, modification, and turnover. 4-6The two basic classes of quantitative metabolic labeling approaches are the stable isotope labeling by amino acids in cell culture (SILAC) experiments and pulse labeling experiments, both of which have been implemented in a variety of ways. 7 In the SILAC method, independent samples are prepared with different labeling patterns that are mixed prior to mass spectrometry analysis. For pulse labeling experiments, labels that are added to the growth medium are taken up to metabolically label the proteome, which generates fractionally enriched proteins from a

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Pulse‐Chase Analysis for Studying Protein Synthesis and Maturation

Fritzsche

Springer

2014

CP Protein Science

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Pulse-chase analysis is a well-established and highly adaptable tool for studying the life cycle of endogenous proteins, including their synthesis, folding, subunit assembly, intracellular transport, post-translational processing, and degradation. This unit describes the performance and analysis of a radiolabel pulse-chase experiment for following the folding and cell surface trafficking of a trimeric murine MHC class I glycoprotein. In particular, the unit focuses on the precise timing of pulse-chase experiments to evaluate early/short-time events in protein maturation in both suspended and strictly adherent cell lines. The advantages and limitations of radiolabel pulse-chase experiments are discussed, and a comprehensive section for troubleshooting is provided. Further, ways to quantitatively represent pulse-chase results are described, and feasible interpretations on protein maturation are suggested. The protocols can be adapted to investigate a variety of proteins that may mature in very different ways.

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Measurement of protein turnover rates by heavy water labeling of nonessential amino acids

Cited by 225 publications

References 39 publications

Inaccuracies in selected ion monitoring determination of isotope ratios obviated by profile acquisition: nucleotide 18O/16O measurements

Inaccuracies in selected ion monitoring determination of isotope ratios obviated by profile acquisition: nucleotide 18O/16O measurements

Quantitative Analysis of Isotope Distributions In Proteomic Mass Spectrometry Using Least-Squares Fourier Transform Convolution

Pulse‐Chase Analysis for Studying Protein Synthesis and Maturation

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