Prediction of metabolic fluxes from gene expression data with Huber penalty convex optimization function

Molecular BioSystems

Volumn 13, Issue 5, 2017, Pages 901-909

  Zhang, Shao Wu ^a   Gou, Wang Long ^a   Li, Yan ^a  

^a NORTHWESTERN POLYTECHNICAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ESCHERICHIA COLI PROTEIN; SACCHAROMYCES CEREVISIAE PROTEIN; TRANSCRIPTOME;

ALGORITHM; BIOLOGY; ESCHERICHIA COLI; GENETIC DATABASE; GENETICS; METABOLIC FLUX ANALYSIS; METABOLISM; PROCEDURES; SACCHAROMYCES CEREVISIAE; WEB BROWSER;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; ESCHERICHIA COLI; ESCHERICHIA COLI PROTEINS; METABOLIC FLUX ANALYSIS; METABOLIC NETWORKS AND PATHWAYS; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS; TRANSCRIPTOME; WEB BROWSER;

EID: 85021732951     PISSN: 1742206X     EISSN: 17422051     Source Type: Journal    
DOI: 10.1039/c6mb00811a     Document Type: Article

References (50)

1. R. J. DeBerardinis C. B. Thompson Cellular metabolism and disease: what do metabolic outliers teach us? Cell 2012 148 1132 1144
2. P. P. Hsu D. M. Sabatini Cancer cell metabolism: Warburg and beyond Cell 2008 134 703 707
3. R. J. Shaw Glucose metabolism and cancer Curr. Opin. Cell Biol. 2006 18 598 608
4. Y. Asgari Z. Zabihinpour A. Salehzadeh-Yazdi F. Schreiberb A. Masoudi-Nejada Alterations in cancer cell metabolism: the Warburg effect and metabolic adaptation Genomics 2015 105 275 281
5. L. Li X. Zhou W. K. Ching P. Wang Predicting enzyme targets for cancer drugs by profiling human metabolic reactions in NCI-60 cell lines BMC Bioinf. 2010 11 501
6. N. Zamboni S. M. Fendt M. Rühl U. Sauer 13C-based metabolic flux analysis Nat. Protoc. 2009 4 878 892
7. P. F. Suthers A. P. Burgard M. S. Dasika F. Nowroozic S. Van Dienb J. D. Keaslingc C. D. Maranasa Metabolic flux elucidation for large-scale models using 13 C labeled isotopes Metab. Eng. 2007 9 387 405
8. W. Wiechert M. Möllney S. Petersen A. A. De Graaf A universal framework for 13 C metabolic flux analysis Metab. Eng. 2001 3 265 283
9. U. Sauer Metabolic networks in motion: 13C-based flux analysis Mol. Syst. Biol. 2006 2 62
10. A. Bordbar J. M. Monk Z. A. King B. Ø. Palsson Constraint-based models predict metabolic and associated cellular functions Nat. Rev. Genet. 2014 15 107 120
11. J. S. Edwards M. Covert B. Palsson Metabolic modelling of microbes: the flux-balance approach Environ. Microbiol. 2002 4 133 140
12. M. R. Antoniewicz Methods and advances in metabolic flux analysis: a mini-review J. Ind. Microbiol. Biotechnol. 2015 42 317 325
13. M. K. Kim D. S. Lun Methods for integration of transcriptomic data in genome-scale metabolic models Comput. Struct. Biotechnol. J. 2014 11 59 65
14. D. Machado M. Herrgård Systematic evaluation of methods for integration of transcriptomic data into constraint-based models of metabolism PLoS Comput. Biol. 2014 10 e1003580
15. J. D. Orth I. Thiele B. Ø. Palsson What is flux balance analysis? Nat. Biotechnol. 2010 28 245 248
16. C. Colijn A. Brandes J. Zucker D. S. Lun B. Weiner M. R. Farhat T. Y. Cheng D. Branch Moody M. Murray J. E. Galagan Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production PLoS Comput. Biol. 2009 5 e1000489
17. K. K. Min L. Anatoliy J. K. James S. L. Desmond E-Flux2 and SPOT: validated methods for inferring intracellular metabolic flux distributions from transcriptomic data PLoS One 2016 11 e0157101
18. S. A. Becker B. O. Palsson Context-specific metabolic networks are consistent with experiments PLoS Comput. Biol. 2008 4 e1000082
19. T. Shlomi M. N. Cabili M. J. Herrgård B. Ø. Palsson E. Ruppin Network-based prediction of human tissue-specific metabolism Nat. Biotechnol. 2008 26 1003 1010
20. H. Zur E. Ruppin T. Shlomi iMAT: an integrative metabolic analysis tool Bioinformatics 2010 26 3140 3142
21. D. Lee K. Smallbone W. B. Dunn E. Murabito C. L. Winder D. B. Kell P. Mendes N. Swainston Improving metabolic flux predictions using absolute gene expression data BMC Syst. Biol. 2012 6 73
22. H. S. Song J. Reifman A. Wallqvist Prediction of metabolic flux distribution from gene expression data based on the flux minimization principle PLoS One 2014 9 e112524
23. E. P. Gianchandani A. K. Chavali J. A. Papin The application of flux balance analysis in systems biology Wiley Interdiscip. Rev.: Syst. Biol. Med. 2010 2 372 382
24. I. Famili J. Förster J. Nielsen B. O. Palsson Saccharomyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network Proc. Natl. Acad. Sci. U. S. A. 2003 100 13134 13139
25. S. S. Fong B. Ø. Palsson Metabolic gene-deletion strains of Escherichia coli evolve to computationally predicted growth phenotypes Nat. Genet. 2004 36 1056 1058
26. K. Raman N. Chandra Flux balance analysis of biological systems: applications and challenges Briefings Bioinf. 2009 10 435 449
27. R. U. Ibarra J. S. Edwards B. O. Palsson Escherichia coli K-12 undergoes adaptive evolution to achieve in silico predicted optimal growth Nature 2002 420 186 189
28. A. M. Feist C. S. Henry J. L. Reed M. Krummenacker A. R. Joyce P. D. Karp L. J. Broadbelt V. Hatzimanikatis B. Ø. Palsson A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information Mol. Syst. Biol. 2007 3 121
29. N. C. Duarte M. J. Herrgård B. Ø. Palsson Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model Genome Res. 2004 14 1298 1309
30. N. C. Duarte S. A. Becker N. Jamshidi I. Thiele M. L. Mo T. D. Vo R. Srivas B. Ø. Palsson Global reconstruction of the human metabolic network based on genomic and bibliomic data Proc. Natl. Acad. Sci. U. S. A. 2007 104 1777 1782
31. Y. K. Oh B. O. Palsson S. M. Park C. H. Schilling R. Mahadevan Genome-scale reconstruction of metabolic network in Bacillus subtilis based on high-throughput phenotyping and gene essentiality data J. Biol. Chem. 2007 282 28791 28799
32. M. A. Oberhardt J. Puchałka K. E. Fryer V. A. Dos Santos J. A. Papin Genome-scale metabolic network analysis of the opportunistic pathogen Pseudomonas aeruginosa PAO1 J. Bacteriol. 2008 190 2790 2803
33. J. Puchałka M. A. Oberhardt M. Godinho A. Bielecka D. Regenhardt K. N. Timmis J. A. Papin V. A. Dos Santos Genome-Scale Reconstruction and Analysis of the Pseudomonas putid a KT2440 Metabolic Network Facilitates Applications in Biotechnology PLoS Comput. Biol. 2008 4 e1000210
34. P. Hanegraaf E. Muller The dynamics of the macromolecular composition of biomass J. Theor. Biol. 2001 212 237 251
35. H. G. Holzhütter The principle of flux minimization and its application to estimate stationary fluxes in metabolic networks Eur. J. Biochem. 2004 271 2905 2922
36. A. S. Blazier J. A. Papin Integration of expression data in genome-scale metabolic network reconstructions Front. Physiol. 2012 3 299
37. M. Åkesson J. Förster J. Nielsen Integration of gene expression data into genome-scale metabolic models Metab. Eng. 2004 6 285 293
38. D. R. Hyduke N. E. Lewis B. Ø. Palsson Analysis of omics data with genome-scale models of metabolism Mol. BioSyst. 2013 9 167 174
39. M. W. Covert E. M. Knight J. L. Reed M. J. Herrgard B. O. Palsson Integrating high-throughput and computational data elucidates bacterial networks Nature 2004 429 92 96
40. I. Thiele B. Ø. Palsson A protocol for generating a high-quality genome-scale metabolic reconstruction Nat. Protoc. 2010 5 93 121
41. A. Mardinoglu J. Nielsen Systems medicine and metabolic modelling J. Intern. Med. 2012 271 142 154
42. M. A. Oberhardt B. Ø. Palsson J. A. Papin Applications of genome-scale metabolic reconstructions Mol. Syst. Biol. 2009 5 320
43. E. Simeonidis N. D. Price Genome-scale modeling for metabolic engineering J. Ind. Microbiol. Biotechnol. 2015 42 327 338
44. B. D. Heavner K. Smallbone B. Barker P. Mendes L. P. Walker Yeast 5 - an expanded reconstruction of the Saccharomyces cerevisiae metabolic network BMC Syst. Biol. 2012 6 55
45. A. K. Holm L. M. Blank M. Oldiges A. Schmid C. Solem P. R. Jensen G. N. Vemuri Metabolic and transcriptional response to cofactor perturbations in Escherichia coli J. Biol. Chem. 2010 285 17498 17506
46. D. Ramkrishna D. S. Kompala G. T. Tsao Are microbes optimal strategists? Biotechnol. Prog. 1987 3 121 126
47. H. G. Holzhütter The principle of flux minimization and its application to estimate stationary fluxes in metabolic networks Eur. J. Biochem. 2004 271 14 2905 2922
48. S. Boyd and L. Vandenberghe, Convex optimization, Cambridge University Press, 2004
49. P. J. Huber Robust estimation of a location parameter Ann. Math. Stat. 1964 35 1 73 101
50. CVX: Matlab Software for Disciplined Convex Programming, http://cvxr.com/cvx, accessed October 2016