13C metabolic flux analysis of recombinant expression hosts

Current Opinion in Biotechnology

Volumn 30, Issue , 2014, Pages 238-245

  Young, Jamey D ^a,b  

^a VANDERBILT UNIVERSITY   (United States)

^b VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

METABOLIC FLUX ANALYSIS; RECOMBINANT EXPRESSION;

CARBON 13; RECOMBINANT PROTEIN; CARBON; GLUCOSE;

ASPERGILLUS NIGER; BACILLUS SUBTILIS; COMPUTER PROGRAM; EMU BV METHOD; EXPERIMENTAL DESIGN; GENETIC ALGORITHM; GLYCOLYSIS; GLYCOSYLATION; ISOTOPE LABELING; ISOTOPICALLY NONSTATIONARY METABOLIC FLUX ANALYSIS; MAMMAL; MASS SPECTROMETRY; METABOLIC FLUX ANALYSIS; NONHUMAN; NUCLEAR MAGNETIC RESONANCE; PICHIA PASTORIS; PROTEIN EXPRESSION; REFERRED TO AS DYNAMIC METABOLIC FLUX ANALYSIS; REVIEW; STOICHIOMETRY; TANDEM MASS SPECTROMETRY; ULTRA HIGH RESOLUTION MASS SPECTROMETRY; METABOLISM; MICROBIOLOGY;

CARBON ISOTOPES; GLUCOSE; INDUSTRIAL MICROBIOLOGY; METABOLIC FLUX ANALYSIS; METABOLIC NETWORKS AND PATHWAYS; RECOMBINANT PROTEINS; SOFTWARE;

EID: 84910058077     PISSN: 09581669     EISSN: 18790429     Source Type: Journal    
DOI: 10.1016/j.copbio.2014.10.004     Document Type: Review

References (89)

1. Vishwanathan N., Le H., Le T., Hu W.S. Advancing biopharmaceutical process science through transcriptome analysis. Curr Opin Biotechnol 2014, 30C:113-119.
2. Heffner K.M., Hizal D.B., Kumar A., Shiloach J., Zhu J., Bowen M.A., Betenbaugh M.J. Exploiting the proteomics revolution in biotechnology: from disease and antibody targets to optimizing bioprocess development. Curr Opin Biotechnol 2014, 30C:80-86.
3. Moxley J.F., Jewett M.C., Antoniewicz M.R., Villas-Boas S.G., Alper H., Wheeler R.T., Tong L., Hinnebusch A.G., Ideker T., Nielsen J., et al. Linking high-resolution metabolic flux phenotypes and transcriptional regulation in yeast modulated by the global regulator Gcn4p. Proc Natl Acad Sci U S A 2009, 106:6477-6482.
4. Burgess S.C., He T., Yan Z., Lindner J., Sherry A.D., Malloy C.R., Browning J.D., Magnuson M.A. Cytosolic phosphoenolpyruvate carboxykinase does not solely control the rate of hepatic gluconeogenesis in the intact mouse liver. Cell Metab 2007, 5:313-320.
5. Fan J., Ye J., Kamphorst J.J., Shlomi T., Thompson C.B., Rabinowitz J.D. Quantitative flux analysis reveals folate-dependent NADPH production. Nature 2014, 510:298-302.
6. Lewis C.A., Parker S.J., Fiske B.P., McCloskey D., Gui D.Y., Green C.R., Vokes N.I., Feist A.M., Vander Heiden M.G., Metallo C.M. Tracing compartmentalized NADPH metabolism in the cytosol and mitochondria of Mammalian cells. Mol Cell 2014, 55:253-263.
7. Möllney M., Wiechert W., Kownatzki D., de Graaf A.A. Bidirectional reaction steps in metabolic networks: IV. Optimal design of isotopomer labeling experiments. Biotechnol Bioeng 1999, 66:86-103.
8. 13C isotopic tracers for metabolic flux analysis in mammalian cells. J Biotechnol 2009, 144:167-174.
9. Antoniewicz M.R., Kelleher J.K., Stephanopoulos G. Determination of confidence intervals of metabolic fluxes estimated from stable isotope measurements. Metab Eng 2006, 8:324-337.
10. 13C isotopic tracers for metabolic flux analysis in mammalian cells. Metab Eng 2012, 14:162-171.
11. 13C-metabolic flux analysis using elementary metabolite units (EMU) basis vector methodology. Metab Eng 2012, 14:150-161.
12. 13C-labeling experiments for metabolic flux analysis in mammalian cells. BMC Syst Biol 2012, 6:43.
13. Crown S.B., Antoniewicz M.R. Parallel labeling experiments and metabolic flux analysis: past, present and future methodologies. Metab Eng 2013, 16:21-32.
14. 13C]glutamine provide new insights into CHO cell metabolism. Metab Eng 2013, 15:34-47.
15. 13C metabolic flux analysis. Metab Eng 2012, 14:533-541.
16. Leighty R.W., Antoniewicz M.R. COMPLETE-MFA: complementary parallel labeling experiments technique for metabolic flux analysis. Metab Eng 2013, 20:49-55.
17. 13C metabolic flux analysis: optimal design of isotopic labeling experiments. Curr Opin Biotechnol 2013, 24:1116-1121.
18. Wiechert W., Noh K. Isotopically non-stationary metabolic flux analysis: complex yet highly informative. Curr Opin Biotechnol 2013, 24:979-986.
19. 13C metabolic flux analysis. Methods Mol Biol 2013, 985:367-390.
20. Antoniewicz M.R. Dynamic metabolic flux analysis-tools for probing transient states of metabolic networks. Curr Opin Biotechnol 2013, 24:973-978.
21. 13C labeling experiments at metabolic nonstationary conditions: an exploratory study. BMC Bioinform 2008, 9:152.
22. Baxter C.J., Liu J.L., Fernie A.R., Sweetlove L.J. Determination of metabolic fluxes in a non-steady-state system. Phytochemistry 2007, 68:2313-2319.
23. Antoniewicz M.R., Kraynie D.F., Laffend L.A., Gonzalez-Lergier J., Kelleher J.K., Stephanopoulos G. Metabolic flux analysis in a nonstationary system: fed-batch fermentation of a high yielding strain of E. coli producing 1,3-propanediol. Metab Eng 2007, 9:277-292.
24. 13C-labeled metabolic flux analysis of a fed-batch culture of elutriated Saccharomyces cerevisiae. FEMS Yeast Res 2007, 7:511-526.
25. Noguchi Y., Young J.D., Aleman J.O., Hansen M.E., Kelleher J.K., Stephanopoulos G. Effect of anaplerotic fluxes and amino acid availability on hepatic lipoapoptosis. J Biol Chem 2009, 284:33425-33436.
26. Jazmin L.J., O'Grady J.P., Ma F., Allen D.K., Morgan J.A., Young J.D. Isotopically nonstationary MFA (INST-MFA) of autotrophic metabolism. Methods Mol Biol 2014, 1090:181-210.
27. 13C flux analysis. Metab Eng 2011, 13:656-665.
28. 13C gluconate tracer method for accurate determination of the pentose phosphate pathway split-ratio in Penicillium chrysogenum. Metab Eng 2008, 10:178-186.
29. 13C-metabolic flux ratio analysis. Biotechnol Bioeng 2013, 110:3164-3176.
30. 13C flux analysis of Myc-induced metabolic reprogramming in B-cells. Metab Eng 2013, 15:206-217.
31. Ahn W.S., Antoniewicz M.R. Metabolic flux analysis of CHO cells at growth and non-growth phases using isotopic tracers and mass spectrometry. Metab Eng 2011, 13:598-609.
32. 13C labeling data. Biotechnol Bioeng 2008, 99:1170-1185.
33. 13C labeling experiments. J Biotechnol 2007, 129:249-267.
34. Young J.D., Allen D.K., Morgan J.A. Isotopomer measurement techniques in metabolic flux analysis II: mass spectrometry. Methods Mol Biol 2014, 1083:85-108.
35. Truong Q.X., Yoon J.M., Shanks J.V. Isotopomer measurement techniques in metabolic flux analysis I: nuclear magnetic resonance. Methods Mol Biol 2014, 1083:65-83.
36. Kiefer P., Nicolas C., Letisse F., Portais J.C. Determination of carbon labeling distribution of intracellular metabolites from single fragment ions by ion chromatography tandem mass spectrometry. Anal Biochem 2007, 360:182-188.
37. 13C metabolic flux analysis. Biotechnol Bioeng 2012, 109:763-771.
38. Choi J., Grossbach M.T., Antoniewicz M.R. Measuring complete isotopomer distribution of aspartate using gas chromatography/tandem mass spectrometry. Anal Chem 2012, 84:4628-4632.
39. Choi J., Antoniewicz M.R. Tandem mass spectrometry: a novel approach for metabolic flux analysis. Metab Eng 2011, 13:225-233.
40. Antoniewicz M.R. Tandem mass spectrometry for measuring stable-isotope labeling. Curr Opin Biotechnol 2013, 24:48-53.
41. 13C metabolic flux analysis of plants. Phytochemistry 2007, 68:2197-2210.
42. 13C analysis. Appl Environ Microbiol 2011, 77:1816-1821.
43. 13C peptide label measurements. Plant J 2014, 77:476-486.
44. 13C NMR can differentiate alternative routes of pyruvate metabolism in living cancer cells. J Biol Chem 2014, 289:6212-6224.
45. Tang Y., Pingitore F., Mukhopadhyay A., Phan R., Hazen T.C., Keasling J.D. Pathway confirmation and flux analysis of central metabolic pathways in Desulfovibrio vulgaris hildenborough using gas chromatography-mass spectrometry and Fourier transform-ion cyclotron resonance mass spectrometry. J Bacteriol 2007, 189:940-949.
46. 13C mass isotopologue profiles under non-steady-state conditions. BMC Biol 2011, 9:37.
47. 13C metabolic flux analysis. Metab Eng 2001, 3:265-283.
48. Young J.D. INCA: a computational platform for isotopically non-stationary metabolic flux analysis. Bioinformatics 2014, 30:1333-1335.
49. 13C-based metabolic flux analysis. Biomed Res Int 2014, 2014:627014.
50. Hiller K., Wegner A., Weindl D., Cordes T., Metallo C.M., Kelleher J.K., Stephanopoulos G. NTFD-a stand-alone application for the non-targeted detection of stable isotope-labeled compounds in GC/MS data. Bioinformatics 2013, 29:1226-1228.
51. 13C-metabolic flux analysis experiments. Biotechnol Bioeng 2014, 111:202-208.
52. 13C metabolic flux analysis studies: a review and future perspectives. Metab Eng 2013, 20:42-48.
53. 13C-based metabolic flux analysis. Nat Protoc 2009, 4:878-892.
54. Tepper N., Shlomi T. An integrated computational approach for metabolic flux analysis coupled with inference of tandem-MS collisional fragments. Bioinformatics 2013, 29:3045-3052.
55. Carreer W.J., Flight R.M., Moseley H.N. A computational framework for high-throughput isotopic natural abundance correction of omics-level ultra-high resolution FT-MS datasets. Metabolites 2013, 3.
56. Boghigian B.A., Seth G., Kiss R., Pfeifer B.A. Metabolic flux analysis and pharmaceutical production. Metab Eng 2010, 12:81-95.
57. 13C NMR. Biotechnol Bioeng 1995, 45:292-303.
58. 13C-lactate nuclear magnetic resonance spectroscopy and metabolite balancing. Biotechnol Bioeng 2001, 74:528-538.
59. Templeton N., Dean J., Reddy P., Young J.D. Peak antibody production is associated with increased oxidative metabolism in an industrially relevant fed-batch CHO cell culture. Biotechnol Bioeng 2013, 110:2013-2024.
60. Sengupta N., Rose S.T., Morgan J.A. Metabolic flux analysis of CHO cell metabolism in the late non-growth phase. Biotechnol Bioeng 2011, 108:82-92.
61. Sheikholeslami Z., Jolicoeur M., Henry O. Elucidating the effects of postinduction glutamine feeding on the growth and productivity of CHO cells. Biotechnol Prog 2014, 30:535-546.
62. Sheikholeslami Z., Jolicoeur M., Henry O. Probing the metabolism of an inducible mammalian expression system using extracellular isotopomer analysis. J Biotechnol 2013, 164:469-478.
63. Templeton N., Lewis A., Dorai H., Qian E.A., Campbell M.P., Smith K.D., Lang S.E., Betenbaugh M.J., Young J.D. The impact of anti-apoptotic gene Bcl-2δ expression on CHO central metabolism. Metab Eng 2014, 25C:92-102.
64. Heyland J., Fu J., Blank L.M., Schmid A. Quantitative physiology of Pichia pastoris during glucose-limited high-cell density fed-batch cultivation for recombinant protein production. Biotechnol Bioeng 2010, 107:357-368.
65. Nocon J., Steiger M.G., Pfeffer M., Sohn S.B., Kim T.Y., Maurer M., Russmayer H., Pflugl S., Ask M., Haberhauer-Troyer C., et al. Model based engineering of Pichia pastoris central metabolism enhances recombinant protein production. Metab Eng 2014, 24:129-138.
66. 13C-metabolic flux analysis in heterologous cellulase production by Bacillus subtilis genome-reduced strain. J Biotechnol 2014, 179:42-49.
67. Driouch H., Melzer G., Wittmann C. Integration of in vivo and in silico metabolic fluxes for improvement of recombinant protein production. Metab Eng 2012, 14:47-58.
68. Young J.D. Metabolic flux rewiring in mammalian cell cultures. Curr Opin Biotechnol 2013, 24:1108-1115.
69. Butler M., Spearman M. The choice of mammalian cell host and possibilities for glycosylation engineering. Curr Opin Biotechnol 2014, 30C:107-112.
70. McAtee A.G., Templeton N., Young J.D. Role of CHO central carbon metabolism in controlling the quality of secreted biotherapeutic proteins. Pharm Bioproc 2014, 2:63-74.
71. Burleigh S.C., van de Laar T., Stroop C.J., van Grunsven W.M., O'Donoghue N., Rudd P.M., Davey G.P. Synergizing metabolic flux analysis and nucleotide sugar metabolism to understand the control of glycosylation of recombinant protein in CHO cells. BMC Biotechnol 2011, 11:95.
72. Nakajima K., Ito E., Ohtsubo K., Shirato K., Takamiya R., Kitazume S., Angata T., Taniguchi N. Mass isotopomer analysis of metabolically labeled nucleotide sugars and N- and O-glycans for tracing nucleotide sugar metabolisms. Mol Cell Proteomics 2013, 12:2468-2480.
73. Sauer U. High-throughput phenomics: experimental methods for mapping fluxomes. Curr Opin Biotechnol 2004, 15:58-63.
74. Ahn W.S., Antoniewicz M.R. Towards dynamic metabolic flux analysis in CHO cell cultures. Biotechnol J 2012, 7:61-74.
75. 13C-metabolic flux analysis. Bioinformatics 2013, 29:143-145.
76. 13C metabolic flux analysis. BMC Syst Biol 2011, 5:129.
77. 13C-glucose experiments. BMC Bioinform 2005, 6:209.
78. Sokol S., Millard P., Portais J.C. influx_s: increasing numerical stability and precision for metabolic flux analysis in isotope labelling experiments. Bioinformatics 2012, 28:687-693.
79. Yoo H., Antoniewicz M.R., Stephanopoulos G., Kelleher J.K. Quantifying reductive carboxylation flux of glutamine to lipid in a brown adipocyte cell line. J Biol Chem 2008, 283:20621-20627.
80. 13C-based metabolic flux analysis. Microb Cell Fact 2009, 8:25.
81. Murphy T.A., Young J.D. ETA: robust software for determination of cell specific rates from extracellular time courses. Biotechnol Bioeng 2013, 110:1748-1758.
82. Wegner A., Weindl D., Jager C., Sapcariu S.C., Dong X., Stephanopoulos G., Hiller K. Fragment formula calculator (FFC): determination of chemical formulas for fragment ions in mass spectrometric data. Anal Chem 2014, 86:2221-2228.
83. Poskar C.H., Huege J., Krach C., Franke M., Shachar-Hill Y., Junker B.H. iMS2Flux-a high-throughput processing tool for stable isotope labeled mass spectrometric data used for metabolic flux analysis. BMC Bioinform 2012, 13:295.
84. Millard P., Letisse F., Sokol S., Portais J.C. IsoCor: correcting MS data in isotope labeling experiments. Bioinformatics 2012, 28:1294-1296.
85. Hiller K., Hangebrauk J., Jager C., Spura J., Schreiber K., Schomburg D. MetaboliteDetector: comprehensive analysis tool for targeted and nontargeted GC/MS based metabolome analysis. Anal Chem 2009, 81:3429-3439.
86. Shannon P., Markiel A., Ozier O., Baliga N.S., Wang J.T., Ramage D., Amin N., Schwikowski B., Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003, 13:2498-2504.
87. Droste P., Miebach S., Niedenfuhr S., Wiechert W., Noh K. Visualizing multi-omics data in metabolic networks with the software Omix: a case study. Biosystems 2011, 105:154-161.
88. 1H] COSY NMR spectroscopy. Metab Eng 2010, 12:138-149.
89. 13C-based metabolic flux analysis. Metab Eng 2014, 21:34-45.