Literature DB >> 27267409

Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system.

Scott B Crown1, Christopher P Long1, Maciek R Antoniewicz2.   

Abstract

13C-Metabolic flux analysis (13C-MFA) is a widely used approach in metabolic engineering for quantifying intracellular metabolic fluxes. The precision of fluxes determined by 13C-MFA depends largely on the choice of isotopic tracers and the specific set of labeling measurements. A recent advance in the field is the use of parallel labeling experiments for improved flux precision and accuracy. However, as of today, no systemic methods exist for identifying optimal tracers for parallel labeling experiments. In this contribution, we have addressed this problem by introducing a new scoring system and evaluating thousands of different isotopic tracer schemes. Based on this extensive analysis we have identified optimal tracers for 13C-MFA. The best single tracers were doubly 13C-labeled glucose tracers, including [1,6-13C]glucose, [5,6-13C]glucose and [1,2-13C]glucose, which consistently produced the highest flux precision independent of the metabolic flux map (here, 100 random flux maps were evaluated). Moreover, we demonstrate that pure glucose tracers perform better overall than mixtures of glucose tracers. For parallel labeling experiments the optimal isotopic tracers were [1,6-13C]glucose and [1,2-13C]glucose. Combined analysis of [1,6-13C]glucose and [1,2-13C]glucose labeling data improved the flux precision score by nearly 20-fold compared to widely use tracer mixture 80% [1-13C]glucose +20% [U-13C]glucose.
Copyright © 2016 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  E. coli; GC–MS; Integrated flux analysis; Isotopic labeling; Optimal tracer experiment design

Mesh:

Substances:

Year:  2016        PMID: 27267409      PMCID: PMC5891732          DOI: 10.1016/j.ymben.2016.06.001

Source DB:  PubMed          Journal:  Metab Eng        ISSN: 1096-7176            Impact factor:   9.783


  45 in total

1.  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

2.  Rapid metabolic analysis of Rhodococcus opacus PD630 via parallel 13C-metabolite fingerprinting.

Authors:  Whitney D Hollinshead; William R Henson; Mary Abernathy; Tae Seok Moon; Yinjie J Tang
Journal:  Biotechnol Bioeng       Date:  2015-09-04       Impact factor: 4.530

Review 3.  Parallel labeling experiments and metabolic flux analysis: Past, present and future methodologies.

Authors:  Scott B Crown; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2012-12-14       Impact factor: 9.783

4.  Sampling of intracellular metabolites for stationary and non-stationary (13)C metabolic flux analysis in Escherichia coli.

Authors:  Pierre Millard; Stéphane Massou; Christoph Wittmann; Jean-Charles Portais; Fabien Létisse
Journal:  Anal Biochem       Date:  2014-08-04       Impact factor: 3.365

5.  Metabolic flux analysis in a nonstationary system: fed-batch fermentation of a high yielding strain of E. coli producing 1,3-propanediol.

Authors:  Maciek R Antoniewicz; David F Kraynie; Lisa A Laffend; Joanna González-Lergier; Joanne K Kelleher; Gregory Stephanopoulos
Journal:  Metab Eng       Date:  2007-02-23       Impact factor: 9.783

6.  Effect of reversible reactions on isotope label redistribution--analysis of the pentose phosphate pathway.

Authors:  B D Follstad; G Stephanopoulos
Journal:  Eur J Biochem       Date:  1998-03-15

7.  Integrated 13C-metabolic flux analysis of 14 parallel labeling experiments in Escherichia coli.

Authors:  Scott B Crown; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2015-01-14       Impact factor: 9.783

8.  Modeling and experimental design for metabolic flux analysis of lysine-producing Corynebacteria by mass spectrometry.

Authors:  C Wittmann; E Heinzle
Journal:  Metab Eng       Date:  2001-04       Impact factor: 9.783

9.  Measuring the Composition and Stable-Isotope Labeling of Algal Biomass Carbohydrates via Gas Chromatography/Mass Spectrometry.

Authors:  Brian O McConnell; Maciek R Antoniewicz
Journal:  Anal Chem       Date:  2016-04-11       Impact factor: 6.986

10.  Evolution of E. coli on [U-13C]Glucose Reveals a Negligible Isotopic Influence on Metabolism and Physiology.

Authors:  Troy E Sandberg; Christopher P Long; Jacqueline E Gonzalez; Adam M Feist; Maciek R Antoniewicz; Bernhard O Palsson
Journal:  PLoS One       Date:  2016-03-10       Impact factor: 3.240

View more
  23 in total

1.  Fast growth phenotype of E. coli K-12 from adaptive laboratory evolution does not require intracellular flux rewiring.

Authors:  Christopher P Long; Jacqueline E Gonzalez; Adam M Feist; Bernhard O Palsson; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2017-09-23       Impact factor: 9.783

2.  Comprehensive metabolic modeling of multiple 13C-isotopomer data sets to study metabolism in perfused working hearts.

Authors:  Scott B Crown; Joanne K Kelleher; Rosanne Rouf; Deborah M Muoio; Maciek R Antoniewicz
Journal:  Am J Physiol Heart Circ Physiol       Date:  2016-08-05       Impact factor: 4.733

3.  Tracing insights into human metabolism using chemical engineering approaches.

Authors:  Thekla Cordes; Christian M Metallo
Journal:  Curr Opin Chem Eng       Date:  2016-09-10       Impact factor: 5.163

4.  Comprehensive analysis of glucose and xylose metabolism in Escherichia coli under aerobic and anaerobic conditions by 13C metabolic flux analysis.

Authors:  Jacqueline E Gonzalez; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2016-11-11       Impact factor: 9.783

5.  Dissecting the genetic and metabolic mechanisms of adaptation to the knockout of a major metabolic enzyme in Escherichia coli.

Authors:  Christopher P Long; Jacqueline E Gonzalez; Adam M Feist; Bernhard O Palsson; Maciek R Antoniewicz
Journal:  Proc Natl Acad Sci U S A       Date:  2017-12-18       Impact factor: 11.205

6.  13C metabolic flux analysis of three divergent extremely thermophilic bacteria: Geobacillus sp. LC300, Thermus thermophilus HB8, and Rhodothermus marinus DSM 4252.

Authors:  Lauren T Cordova; Robert M Cipolla; Adti Swarup; Christopher P Long; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2017-10-14       Impact factor: 9.783

7.  Metabolism of the fast-growing bacterium Vibrio natriegens elucidated by 13C metabolic flux analysis.

Authors:  Christopher P Long; Jacqueline E Gonzalez; Robert M Cipolla; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2017-10-16       Impact factor: 9.783

8.  13C metabolic flux analysis of microbial and mammalian systems is enhanced with GC-MS measurements of glycogen and RNA labeling.

Authors:  Christopher P Long; Jennifer Au; Jacqueline E Gonzalez; Maciek R Antoniewicz
Journal:  Metab Eng       Date:  2016-06-22       Impact factor: 9.783

9.  Ex vivo and in vivo stable isotope labelling of central carbon metabolism and related pathways with analysis by LC-MS/MS.

Authors:  Min Yuan; Daniel M Kremer; He Huang; Susanne B Breitkopf; Issam Ben-Sahra; Brendan D Manning; Costas A Lyssiotis; John M Asara
Journal:  Nat Protoc       Date:  2019-02       Impact factor: 13.491

10.  Simultaneous tracers and a unified model of positional and mass isotopomers for quantification of metabolic flux in liver.

Authors:  Stanislaw Deja; Xiaorong Fu; Justin A Fletcher; Blanka Kucejova; Jeffrey D Browning; Jamey D Young; Shawn C Burgess
Journal:  Metab Eng       Date:  2019-12-28       Impact factor: 9.783

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.