IsoDesign: A software for optimizing the design of 13C-metabolic flux analysis experiments

Biotechnology and Bioengineering

Volumn 111, Issue 1, 2014, Pages 202-208

  Millard, Pierre ^a,b,c   Sokol, Serguei ^a,b,c   Letisse, Fabien ^a,b,c   Portais, Jean Charles ^a,b,c  

^a INSA   (France)

^b UMR792 INGÉNIERIE DES SYSTÈMES BIOLOGIQUES ET DES PROCÉDÉS   (France)

^c CNRS   (France)

Author keywords

13C metabolic flux analysis; Experimental design; Isotope labeling experiments; MS; NMR

Indexed keywords

BIOLOGICAL COMMUNITY; FLUX ANALYSIS; ISOTOPE LABELING EXPERIMENTS; ISOTOPIC COMPOSITION; MS; OPEN SOURCE LICENSE; SYSTEMS BIOLOGY; VISUALIZATION MODULES;

DESIGN OF EXPERIMENTS; ISOTOPES; METABOLISM; NUCLEAR MAGNETIC RESONANCE; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; OPTIMIZATION; STATISTICS;

EXPERIMENTS;

CARBON 13; CARBON;

13C METABOLIC FLUX ANALYSIS; ARTICLE; CALCULATION; CARBON NUCLEAR MAGNETIC RESONANCE; CITRIC ACID CYCLE; COMPUTER PROGRAM; EXPERIMENTAL DESIGN; FLOW MEASUREMENT; INFORMATION PROCESSING; ISODESIGN; LINEAR SYSTEM; MASS SPECTROMETRY; MEASUREMENT ACCURACY; METABOLIC ENGINEERING; METABOLISM; METABOLITE; MONTE CARLO METHOD; PENTOSE PHOSPHATE CYCLE; PROTON NUCLEAR MAGNETIC RESONANCE; SYSTEMS BIOLOGY; TANDEM MASS SPECTROMETRY; METABOLIC FLUX ANALYSIS; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE; PROCEDURES; SOFTWARE;

CARBON ISOTOPES; METABOLIC FLUX ANALYSIS; NUCLEAR MAGNETIC RESONANCE, BIOMOLECULAR; RESEARCH DESIGN; SOFTWARE;

EID: 84888048369     PISSN: 00063592     EISSN: 10970290     Source Type: Journal    
DOI: 10.1002/bit.24997     Document Type: Article

References (23)

1. Antoniewicz MR, Kelleher JK, Stephanopoulos G. 2006. Determination of confidence intervals of metabolic fluxes estimated from stable isotope measurements. Metab Eng 8(4):324-337.
2. Arita M. 2003. In silico atomic tracing by substrate-product relationships in Escherichia coli intermediary metabolism. Genome Res 13(11):2455-2466.
3. Chen J, Zheng H, Liu H, Niu J, Liu J, Shen T, Rui B, Shi Y. 2007. Improving metabolic flux estimation via evolutionary optimization for convex solution space. Bioinformatics 23(9):1115-1123.
4. Crown SB, Antoniewicz MR. 2012. Selection of tracers for 13C-metabolic flux analysis using elementary metabolite units (EMU) basis vector methodology. Metab Eng 14(2):150-161.
5. Crown SB, Ahn WS, Antoniewicz MR. 2012. Rational design of 13C-labeling experiments for metabolic flux analysis in mammalian cells. BMC Syst Biol 6(1):43.
6. Ishii N, Nakahigashi K, Baba T, Robert M, Soga T, Kanai A, Hirasawa T, Naba M, Hirai K, Hoque A, Ho PY, Kakazu Y, Sugawara K, Igarashi S, Harada S, Masuda T, Sugiyama N, Togashi T, Hasegawa M, Takai Y, Yugi K, Arakawa K, Iwata N, Toya Y, Nakayama Y, Nishioka T, Shimizu K, Mori H, Tomita M. 2007. Multiple high-throughput analyses monitor the response of E. coli to perturbations. Science 316(5824):593-597.
7. Iwatani S, Yamada Y, Usuda Y. 2008. Metabolic flux analysis in biotechnology processes. Biotechnol Lett 30(5):791-799.
8. Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M. 2006. From genomics to chemical genomics: New developments in KEGG. Nucleic Acids Res 34(Database issue):D354-D357.
9. Kiefer P, Nicolas C, Letisse F, Portais JC. 2007. Determination of carbon labeling distribution of intracellular metabolites from single fragment ions by ion chromatography tandem mass spectrometry. Anal Biochem 360(2):182-188.
10. Libourel IG, Gehan JP, Shachar-Hill Y. 2007. Design of substrate label for steady state flux measurements in plant systems using the metabolic network of Brassica napus embryos. Phytochemistry 68(16-18):2211-2221.
11. Massou S, Nicolas C, Letisse F, Portais JC. 2007. NMR-based fluxomics: Quantitative 2D NMR methods for isotopomers analysis. Phytochemistry 68(16-18):2330-2340.
12. Metallo CM, Walther JL, Stephanopoulos G. 2009. Evaluation of 13C isotopic tracers for metabolic flux analysis in mammalian cells. J Biotechnol 144(3):167-174.
13. Mollney M, Wiechert W, Kownatzki D, de Graaf AA. 1999. Bidirectional reaction steps in metabolic networks: IV. Optimal design of isotopomer labeling experiments. Biotechnol Bioeng 66(2):86-103.
14. Nicolas C, Kiefer P, Letisse F, Kromer J, Massou S, Soucaille P, Wittmann C, Lindley ND, Portais JC. 2007. Response of the central metabolism of Escherichia coli to modified expression of the gene encoding the glucose-6-phosphate dehydrogenase. FEBS Lett 581(20):3771-3776.
15. Quek LE, Wittmann C, Nielsen LK, Kromer JO. 2009. OpenFLUX: Efficient modelling software for 13C-based metabolic flux analysis. Microb Cell Fact 8:25.
16. Ruhl M, Rupp B, Noh K, Wiechert W, Sauer U, Zamboni N. 2012. Collisional fragmentation of central carbon metabolites in LC-MS/MS increases precision of (1)(3)C metabolic flux analysis. Biotechnol Bioeng 109(3):763-771.
17. Sokol S, Millard P, Portais JC. 2012. Influx_s: Increasing numerical stability and precision for metabolic flux analysis in isotope labeling experiments. Bioinformatics 28(5):687-693.
18. Walther JL, Metallo CM, Zhang J, Stephanopoulos G. 2012. Optimization of 13C isotopic tracers for metabolic flux analysis in mammalian cells. Metab Eng 14(2):162-171.
19. Weitzel M, Noh K, Dalman T, Niedenfuhr S, Stute B, Wiechert W. 2013. 13CFLUX2 high-performance software suite for (13)C-metabolic flux analysis. Bioinformatics 29(1):143-145.
20. Wiechert W. 2001. 13C metabolic flux analysis. Metab Eng 3(3):195-206.
21. Wiechert W, Mollney M, Petersen S, de Graaf AA. 2001. A universal framework for 13C metabolic flux analysis. Metab Eng 3(3):265-283.
22. Yoo H, Antoniewicz MR, Stephanopoulos G, Kelleher JK. 2008. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. J Biol Chem 283(30):20621-20627.
23. Zhao J, Shimizu K. 2003. Metabolic flux analysis of Escherichia coli K12 grown on 13C-labeled acetate and glucose using GC-MS and powerful flux calculation method. J Biotechnol 101(2):101-117.