Literature DB >> 27989585

The importance of accurately correcting for the natural abundance of stable isotopes.

Firas S Midani1, Michelle L Wynn2, Santiago Schnell3.   

Abstract

The use of isotopically labeled tracer substrates is an experimental approach for measuring in vivo and in vitro intracellular metabolic dynamics. Stable isotopes that alter the mass but not the chemical behavior of a molecule are commonly used in isotope tracer studies. Because stable isotopes of some atoms naturally occur at non-negligible abundances, it is important to account for the natural abundance of these isotopes when analyzing data from isotope labeling experiments. Specifically, a distinction must be made between isotopes introduced experimentally via an isotopically labeled tracer and the isotopes naturally present at the start of an experiment. In this tutorial review, we explain the underlying theory of natural abundance correction of stable isotopes, a concept not always understood by metabolic researchers. We also provide a comparison of distinct methods for performing this correction and discuss natural abundance correction in the context of steady state 13C metabolic flux, a method increasingly used to infer intracellular metabolic flux from isotope experiments.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Metabolic flux analysis; Natural abundance correction; Reproducibility; Stable isotopes

Mesh:

Substances:

Year:  2017        PMID: 27989585      PMCID: PMC5343595          DOI: 10.1016/j.ab.2016.12.011

Source DB:  PubMed          Journal:  Anal Biochem        ISSN: 0003-2697            Impact factor:   3.365


  55 in total

1.  Bidirectional reaction steps in metabolic networks: III. Explicit solution and analysis of isotopomer labeling systems.

Authors:  W Wiechert; M Möllney; N Isermann; M Wurzel; A A de Graaf
Journal:  Biotechnol Bioeng       Date:  1999       Impact factor: 4.530

2.  GC-MS analysis of amino acids rapidly provides rich information for isotopomer balancing.

Authors:  M Dauner; U Sauer
Journal:  Biotechnol Prog       Date:  2000 Jul-Aug

Review 3.  13C metabolic flux analysis.

Authors:  W Wiechert
Journal:  Metab Eng       Date:  2001-07       Impact factor: 9.783

4.  Determination of complex isotopomer patterns in isotopically labeled compounds by mass spectrometry.

Authors:  Mark E Jennings; Dwight E Matthews
Journal:  Anal Chem       Date:  2005-10-01       Impact factor: 6.986

5.  Elementary metabolite units (EMU): a novel framework for modeling isotopic distributions.

Authors:  Maciek R Antoniewicz; Joanne K Kelleher; Gregory Stephanopoulos
Journal:  Metab Eng       Date:  2006-09-17       Impact factor: 9.783

6.  INCA: a computational platform for isotopically non-stationary metabolic flux analysis.

Authors:  Jamey D Young
Journal:  Bioinformatics       Date:  2014-01-11       Impact factor: 6.937

7.  Correcting for the effects of natural abundance in stable isotope resolved metabolomics experiments involving ultra-high resolution mass spectrometry.

Authors:  Hunter Nb Moseley
Journal:  BMC Bioinformatics       Date:  2010-03-17       Impact factor: 3.169

8.  RhoC GTPase Is a Potent Regulator of Glutamine Metabolism and N-Acetylaspartate Production in Inflammatory Breast Cancer Cells.

Authors:  Michelle L Wynn; Joel A Yates; Charles R Evans; Lauren D Van Wassenhove; Zhi Fen Wu; Sydney Bridges; Liwei Bao; Chelsea Fournier; Sepideh Ashrafzadeh; Matthew J Merrins; Leslie S Satin; Santiago Schnell; Charles F Burant; Sofia D Merajver
Journal:  J Biol Chem       Date:  2016-04-25       Impact factor: 5.157

9.  A Computational Framework for High-Throughput Isotopic Natural Abundance Correction of Omics-Level Ultra-High Resolution FT-MS Datasets.

Authors:  William J Carreer; Robert M Flight; Hunter N B Moseley
Journal:  Metabolites       Date:  2013-09-25

10.  13CFLUX2--high-performance software suite for (13)C-metabolic flux analysis.

Authors:  Michael Weitzel; Katharina Nöh; Tolga Dalman; Sebastian Niedenführ; Birgit Stute; Wolfgang Wiechert
Journal:  Bioinformatics       Date:  2012-10-30       Impact factor: 6.937

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  17 in total

1.  Assessing the pentose phosphate pathway using [2, 3-13 C2 ]glucose.

Authors:  Min Hee Lee; Craig R Malloy; Ian R Corbin; Junjie Li; Eunsook S Jin
Journal:  NMR Biomed       Date:  2019-03-29       Impact factor: 4.044

2.  The quantitative relationship between isotopic and net contributions of lactate and glucose to the tricarboxylic acid (TCA) cycle.

Authors:  Minfeng Ying; Cheng Guo; Xun Hu
Journal:  J Biol Chem       Date:  2019-04-30       Impact factor: 5.157

3.  Mitochondrial function in liver cells is resistant to perturbations in NAD+ salvage capacity.

Authors:  Morten Dall; Samuel A J Trammell; Magnus Asping; Anna S Hassing; Marianne Agerholm; Sara G Vienberg; Matthew P Gillum; Steen Larsen; Jonas T Treebak
Journal:  J Biol Chem       Date:  2019-07-18       Impact factor: 5.157

4.  Metabolic engineering of Kluyveromyces marxianus for biomass-based applications.

Authors:  Gustavo Graciano Fonseca
Journal:  3 Biotech       Date:  2022-09-03       Impact factor: 2.893

Review 5.  Metabolomics and Isotope Tracing.

Authors:  Cholsoon Jang; Li Chen; Joshua D Rabinowitz
Journal:  Cell       Date:  2018-05-03       Impact factor: 41.582

6.  Analysis of Melanoma Cell Glutamine Metabolism by Stable Isotope Tracing and Gas Chromatography-Mass Spectrometry.

Authors:  David A Scott
Journal:  Methods Mol Biol       Date:  2021

Review 7.  Flux analysis of inborn errors of metabolism.

Authors:  D-J Reijngoud
Journal:  J Inherit Metab Dis       Date:  2018-01-09       Impact factor: 4.982

8.  Development and Application of FASA, a Model for Quantifying Fatty Acid Metabolism Using Stable Isotope Labeling.

Authors:  Joseph P Argus; Moses Q Wilks; Quan D Zhou; Wei Yuan Hsieh; Elvira Khialeeva; Xen Ping Hoi; Viet Bui; Shili Xu; Amy K Yu; Eric S Wang; Harvey R Herschman; Kevin J Williams; Steven J Bensinger
Journal:  Cell Rep       Date:  2018-12-04       Impact factor: 9.423

9.  Epstein-Barr-Virus-Induced One-Carbon Metabolism Drives B Cell Transformation.

Authors:  Liang Wei Wang; Hongying Shen; Luis Nobre; Ina Ersing; Joao A Paulo; Stephen Trudeau; Zhonghao Wang; Nicholas A Smith; Yijie Ma; Bryn Reinstadler; Jason Nomburg; Thomas Sommermann; Ellen Cahir-McFarland; Steven P Gygi; Vamsi K Mootha; Michael P Weekes; Benjamin E Gewurz
Journal:  Cell Metab       Date:  2019-06-27       Impact factor: 27.287

10.  Dimethylsulfoniopropionate Sulfur and Methyl Carbon Assimilation in Ruegeria Species.

Authors:  Joseph S Wirth; Tao Wang; Qiuyuan Huang; Robert H White; William B Whitman
Journal:  mBio       Date:  2020-03-24       Impact factor: 7.867

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