Literature DB >> 33661639

Using Heavy Mass Isotopomers for Protein Turnover in Heavy Water Metabolic Labeling.

Rovshan G Sadygov1.   

Abstract

Metabolic labeling followed by LC-MS-based proteomics is a powerful tool to study proteome dynamics in high-throughput experiments both in vivo and in vitro. High mass resolution and accuracy allow differentiation in isotope profiles and the quantification of partially labeled peptide species. Metabolic labeling duration introduces a time domain in which the gradual incorporation of labeled isotopes is recorded. Different stable isotopes are used for labeling. Labeling with heavy water has advantages because it is cost-effective and easy to use. The protein degradation rate constant has been modeled using exponential decay models for the relative abundances of mass isotopomers. The recently developed closed-form equations were applied to study the analytic behavior of the heavy mass isotopomers in the time domain of metabolic labeling. The predictions from the closed-form equations are compared with the practices that have been used to extract degradation rate constants from the time-course profiles of heavy mass isotopomers. It is shown that all mass isotopomers, except for the monoisotope, require data transformations to obtain the exponential depletion, which serves as a basis for the rate constant model. Heavy mass isotopomers may be preferable choices for modeling high-mass peptides or peptides with a high number of labeling sites. The results are also applicable to stable isotope labeling with other atom-based labeling agents.

Entities:  

Keywords:  dynamics of mass isotopomers; metabolic labeling; protein turnover; rate constant estimation from heavy mass isotopomers

Mesh:

Substances:

Year:  2021        PMID: 33661639      PMCID: PMC8167932          DOI: 10.1021/acs.jproteome.0c00873

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  24 in total

1.  An efficient method to calculate the aggregated isotopic distribution and exact center-masses.

Authors:  Jürgen Claesen; Piotr Dittwald; Tomasz Burzykowski; Dirk Valkenborg
Journal:  J Am Soc Mass Spectrom       Date:  2012-02-15       Impact factor: 3.109

2.  d2ome, Software for in Vivo Protein Turnover Analysis Using Heavy Water Labeling and LC-MS, Reveals Alterations of Hepatic Proteome Dynamics in a Mouse Model of NAFLD.

Authors:  Rovshan G Sadygov; Jayant Avva; Mahbubur Rahman; Kwangwon Lee; Sergei Ilchenko; Takhar Kasumov; Ahmad Borzou
Journal:  J Proteome Res       Date:  2018-10-19       Impact factor: 4.466

3.  Systems-wide proteomic analysis in mammalian cells reveals conserved, functional protein turnover.

Authors:  Sidney B Cambridge; Florian Gnad; Chuong Nguyen; Justo Lorenzo Bermejo; Marcus Krüger; Matthias Mann
Journal:  J Proteome Res       Date:  2011-11-03       Impact factor: 4.466

4.  A Simple Light Isotope Metabolic Labeling (SLIM-labeling) Strategy: A Powerful Tool to Address the Dynamics of Proteome Variations In Vivo.

Authors:  Thibaut Léger; Camille Garcia; Laetitia Collomb; Jean-Michel Camadro
Journal:  Mol Cell Proteomics       Date:  2017-08-18       Impact factor: 5.911

5.  Metabolite Spectral Accuracy on Orbitraps.

Authors:  Xiaoyang Su; Wenyun Lu; Joshua D Rabinowitz
Journal:  Anal Chem       Date:  2017-05-18       Impact factor: 6.986

6.  Measuring protein synthesis using metabolic ²H labeling, high-resolution mass spectrometry, and an algorithm.

Authors:  Takhar Kasumov; Serguey Ilchenko; Ling Li; Nadia Rachdaoui; Rovshan G Sadygov; Belinda Willard; Arthur J McCullough; Stephen Previs
Journal:  Anal Biochem       Date:  2011-01-20       Impact factor: 3.365

Review 7.  Mass isotopomer distribution analysis: a technique for measuring biosynthesis and turnover of polymers.

Authors:  M K Hellerstein; R A Neese
Journal:  Am J Physiol       Date:  1992-11

8.  Measuring protein synthesis by mass isotopomer distribution analysis (MIDA).

Authors:  C Papageorgopoulos; K Caldwell; C Shackleton; H Schweingrubber; M K Hellerstein
Journal:  Anal Biochem       Date:  1999-02-01       Impact factor: 3.365

9.  Molecular Isotopic Distribution Analysis (MIDAs) with adjustable mass accuracy.

Authors:  Gelio Alves; Aleksey Y Ogurtsov; Yi-Kuo Yu
Journal:  J Am Soc Mass Spectrom       Date:  2013-11-20       Impact factor: 3.109

10.  Assessment of cardiac proteome dynamics with heavy water: slower protein synthesis rates in interfibrillar than subsarcolemmal mitochondria.

Authors:  Takhar Kasumov; Erinne R Dabkowski; Kadambari Chandra Shekar; Ling Li; Rogerio F Ribeiro; Kenneth Walsh; Stephen F Previs; Rovshan G Sadygov; Belinda Willard; William C Stanley
Journal:  Am J Physiol Heart Circ Physiol       Date:  2013-03-01       Impact factor: 5.125

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