Literature DB >> 33084301

Partial Isotope Profiles Are Sufficient for Protein Turnover Analysis Using Closed-Form Equations of Mass Isotopomer Dynamics.

Rovshan G Sadygov1.   

Abstract

Metabolic labeling with atom-based heavy isotopes, followed by liquid chromatography coupled with mass spectrometry (LC-MS), has been a powerful technique for studies of proteome and metabolome. In proteomics, the protein turnover of thousands of proteins can be estimated from the gradual incorporation of 2H or 15N in the diet. Software tools have been developed to automate the estimation of protein turnover. Traditionally, the turnover has been estimated using the time course of the depletion of the normalized abundance of monoisotopes. While the bioinformatic aspects of peak detection and integration, time course modeling, and uncertainty estimation have progressed, mass isotopomer dynamics during label incorporation has only been modeled from approximate approaches or numerical simulations. We derive closed-form equations that describe the dynamics of mass isotopomers during metabolic labeling with an atom-based stable isotope. The derived equations create an alternative method for estimating label incorporation. They also provide opportunities for estimation of precursor-product relationships in species or systems where they are unknown. The equations are useful in bioinformatic tools for analyzing mass spectral data from metabolic labeling.

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Year:  2020        PMID: 33084301      PMCID: PMC8880304          DOI: 10.1021/acs.analchem.0c03343

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  26 in total

1.  Equilibration of (2)H labeling between body water and free amino acids: enabling studies of proteome synthesis.

Authors:  Kithsiri Herath; Gowi Bhat; Paul L Miller; Sheng-Ping Wang; Alison Kulick; Genevieve Andrews-Kelly; Christopher Johnson; Rory J Rohm; Michael E Lassman; Stephen F Previs; Douglas G Johns; Brian K Hubbard; Thomas P Roddy
Journal:  Anal Biochem       Date:  2011-04-27       Impact factor: 3.365

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.  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

4.  Calculation of the Protein Turnover Rate Using the Number of Incorporated 2H Atoms and Proteomics Analysis of a Single Labeled Sample.

Authors:  Serguei Ilchenko; Andrew Haddad; Prabodh Sadana; Fabio A Recchia; Rovshan G Sadygov; Takhar Kasumov
Journal:  Anal Chem       Date:  2019-11-05       Impact factor: 6.986

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.  Measurement of human plasma proteome dynamics with (2)H(2)O and liquid chromatography tandem mass spectrometry.

Authors:  John C Price; William E Holmes; Kelvin W Li; Nicholas A Floreani; Richard A Neese; Scott M Turner; Marc K Hellerstein
Journal:  Anal Biochem       Date:  2011-09-14       Impact factor: 3.365

7.  High-Throughput Measurement of Lipid Turnover Rates Using Partial Metabolic Heavy Water Labeling.

Authors:  Byoungsook Goh; Jinwoo Kim; Seungwoo Seo; Tae-Young Kim
Journal:  Anal Chem       Date:  2018-05-11       Impact factor: 6.986

8.  Isotopologue distributions of peptide product ions by tandem mass spectrometry: quantitation of low levels of deuterium incorporation.

Authors:  Benlian Wang; Gang Sun; David R Anderson; Minghong Jia; Stephen Previs; Vernon E Anderson
Journal:  Anal Biochem       Date:  2007-04-02       Impact factor: 3.365

9.  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

10.  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

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  2 in total

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

Authors:  Rovshan G Sadygov
Journal:  J Proteome Res       Date:  2021-03-04       Impact factor: 4.466

2.  Protein turnover models for LC-MS data of heavy water metabolic labeling.

Authors:  Rovshan G Sadygov
Journal:  Brief Bioinform       Date:  2022-03-10       Impact factor: 11.622

  2 in total

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