Literature DB >> 23114423

Designer labels for plant metabolism: statistical design of isotope labeling experiments for improved quantification of flux in complex plant metabolic networks.

Shilpa Nargund1, Ganesh Sriram.   

Abstract

Metabolic fluxes are powerful indicators of cell physiology and can be estimated by isotope-assisted metabolic flux analysis (MFA). The complexity of the compartmented metabolic networks of plants has constrained the application of isotope-assisted MFA to them, principally because of poor identifiability of fluxes from the measured isotope labeling patterns. However, flux identifiability can be significantly improved by a priori design of isotope labeling experiments (ILEs). This computational design involves evaluating the effect of different isotope label and isotopomer measurement combinations on flux identifiability, and thereby identifying optimal labels and measurements toward evaluating the fluxes of interest with the highest confidence. This article reports ILE designs for two major, compartmented plant metabolic pathways - the pentose phosphate pathway (PPP) and γ-aminobutyric acid (GABA) shunt. Together, these pathways represent common motifs in plant metabolism including duplication of pathways in different subcellular compartments, reversible reactions and cyclic carbon flow. To compare various ILE designs, we employed statistical A- and D-optimality criteria. Our computations showed that 1,2-(13)C Glc is a powerful and robust label for the plant PPPs, given currently popular isotopomer measurement techniques (single quadrupole mass spectrometry [MS] and 2-D nuclear magnetic resonance [NMR]). Further analysis revealed that this label can estimate several PPP fluxes better than the popular label 1-(13)C Glc. Furthermore, the concurrent measurement of the isotopomers of hexose and pentose moieties synthesized exclusively in the cytosol or the plastid compartments (measurable through intracellular glucose or sucrose, starch, RNA ribose and histidine) considerably improves the identifiability of PPP fluxes in the individual compartments. Additionally, MS-derived isotopomer measurements outperform NMR-derived measurements in identifying PPP fluxes. The potency of 1,2-(13)C Glc can be improved substantially by combining it with other labels (e.g. 3-(13)C Glc, 1-(13)C Glc and U-(13)C Glc) in parallel ILEs. For the GABA shunt, we calculated that 100% 2-(13)C Ala and 100% U-(13)C Gln constitute the best labels. We anticipate that the ILE designs presented in this article can enhance the quality of flux estimates in these two complex plant pathways. In the future, these ILE designs can be further improved by leveraging recent analytical and computational developments in isotope-assisted MFA.

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Year:  2012        PMID: 23114423     DOI: 10.1039/c2mb25253h

Source DB:  PubMed          Journal:  Mol Biosyst        ISSN: 1742-2051


  9 in total

Review 1.  Publishing 13C metabolic flux analysis studies: a review and future perspectives.

Authors:  Scott B Crown; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2013-09-08       Impact factor: 9.783

2.  Quantification of peptide m/z distributions from 13C-labeled cultures with high-resolution mass spectrometry.

Authors:  Doug K Allen; Joshua Goldford; James K Gierse; Dominic Mandy; Christine Diepenbrock; Igor G L Libourel
Journal:  Anal Chem       Date:  2014-01-21       Impact factor: 6.986

3.  OpenFLUX2: (13)C-MFA modeling software package adjusted for the comprehensive analysis of single and parallel labeling experiments.

Authors:  Mikhail S Shupletsov; Lyubov I Golubeva; Svetlana S Rubina; Dmitry A Podvyaznikov; Shintaro Iwatani; Sergey V Mashko
Journal:  Microb Cell Fact       Date:  2014-11-19       Impact factor: 5.328

4.  Investigation of useful carbon tracers for 13C-metabolic flux analysis of Escherichia coli by considering five experimentally determined flux distributions.

Authors:  Kousuke Maeda; Nobuyuki Okahashi; Yoshihiro Toya; Fumio Matsuda; Hiroshi Shimizu
Journal:  Metab Eng Commun       Date:  2016-06-07

5.  Metabolic analyses elucidate non-trivial gene targets for amplifying dihydroartemisinic acid production in yeast.

Authors:  Ashish Misra; Matthew F Conway; Joseph Johnnie; Tabish M Qureshi; Bao Lige; Anne M Derrick; Eddy C Agbo; Ganesh Sriram
Journal:  Front Microbiol       Date:  2013-07-26       Impact factor: 5.640

6.  Experimental evidence and isotopomer analysis of mixotrophic glucose metabolism in the marine diatom Phaeodactylum tricornutum.

Authors:  Yuting Zheng; Andrew H Quinn; Ganesh Sriram
Journal:  Microb Cell Fact       Date:  2013-11-14       Impact factor: 5.328

7.  Rapid in situ 13C tracing of sucrose utilization in Arabidopsis sink and source leaves.

Authors:  Frederik Dethloff; Isabel Orf; Joachim Kopka
Journal:  Plant Methods       Date:  2017-10-18       Impact factor: 4.993

8.  A Pareto approach to resolve the conflict between information gain and experimental costs: Multiple-criteria design of carbon labeling experiments.

Authors:  Katharina Nöh; Sebastian Niedenführ; Martin Beyß; Wolfgang Wiechert
Journal:  PLoS Comput Biol       Date:  2018-10-31       Impact factor: 4.475

Review 9.  Metabolic Flux Analysis-Linking Isotope Labeling and Metabolic Fluxes.

Authors:  Yujue Wang; Fredric E Wondisford; Chi Song; Teng Zhang; Xiaoyang Su
Journal:  Metabolites       Date:  2020-11-06
  9 in total

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