Integration of expression data in genome-scale metabolic network reconstructions

Frontiers in Physiology

Volumn 3 AUG, Issue , 2012, Pages

  Blazier, Anna S ^a   Papin, Jason A ^a  

^a University of Virginia   (United States)

Author keywords

Data integration; Expression data; Flux balance analysis; Metabolic networks; Transcriptomics

Indexed keywords

EID: 84866487453     PISSN: None     EISSN: 1664042X     Source Type: Journal    
DOI: 10.3389/fphys.2012.00299     Document Type: Short Survey

References (33)

1. Akesson, M., Forster, J., and Nielsen, J. (2004). Integration of gene expression data into genome-scale metabolic models. Metab. Eng. 6, 285-293.
2. Becker, S. A., and Palsson, B. O. (2008). Context-specific metabolic networks are consistent with experiments. PLoS Comput. Biol. 4:e1000082. doi: 10.1371/journal.pcbi.1000082
3. Cakir, T., Patil, K. R., Onsan, Z. I., Ulgen, K. O., Kirdar, B., and Nielsen, J. (2006). Integration of metabolome data with metabolic networks reveals reporter reactions. Mol. Syst. Biol. 2, 1-11.
4. Chandrasekaran, S., and Price, N. D (2010). Probabilistic integra- tive modeling of genome-scale metabolic and regulatory net works in Escherichia coli and Mycobacterium tuberculosis. Proc. Natl. Acad. Sci. U.S.A. 107, 17845-17850.
5. Chang, R. L., Ghamsari, L., Manichaikul, A., Hom, E. F., Balaji, S., Fu, W., Shen, Y., Hao, T., Palsson, B. O., Salehi-Ashtiani, K., and Papin, J. A. (2011). Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism. Mol. Syst. Biol. 7, 1-13.
6. Chavali, A. K., D'Auria, K. M., Hewlett, L., Pearson, R. D., and Papin, J. A. (2012). A metabolic net work approach for the identification and prioritization of antimicrobial drug targets. Tre n ds M icrob iol. 20, 113-123.
7. Colijn, C., Brandes, A., Zucker, J., Lun, D. S., Weiner, B., Farhat, M. R., Cheng, T. Y., Moody, D. B., Murray, M., and Galagan, J.E. (2009). Interpreting expression data with metabolic flux models: predicting Mycobacterium tuberculosis mycolic acid production. PLoS Comput. Biol. 5:e1000489. doi: 10.1371/journal.pcbi.1000489
8. Covert, M. W., Knight, E. M., Reed, J. L., Herrgard, M. J., and Palsson, B. O. (2004). Integrating high-throughput and computational data elucidates bacterial networks. Nature 429, 92-96.
9. Covert, M. W., and Palsson, B. O. (2002). Transcriptional regulation in constraints-based metabolic models of Escherichia coli. J. Biol. Chem. 277, 28058-28064.
10. Duarte, N. C., Becker, S. A., Jamshidi, N., Thiele, I., Mo, M. L., Vo, T. D., Srivas, R., and Palsson, B. O. (2007). Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc. Natl. Acad. Sci. U.S.A. 104, 1777-1782.
11. Gianchandani, E. P., Chavali, A. K., and Papin, J. A. (2009). The application of flux balance analysis in systems biology. Wiley Interdiscip. Rev. Syst. Biol. Med. 2, 372-382.
12. Griffin, T. J., Gygi, S. P., Ideker, T., Rist, B., Eng, J., Hood, L., and Aebersold, R. (2002). Complementary profiling of gene expression at the tran-scriptome and proteome levels in Saccharomyces cerevisiae. Mol. Cell. Proteomics 1, 323-333.
13. Gygi, S. P., Rochon, Y., Franza, B. R., and Aebersold, R. (1999). Correlation between protein and mRNA abundance in yeast. Mol. Cell. Biol. 19, 1720-1730.
14. Ideker, T., Thorsson, V., Ranish, J. A., Christmas, R., Buhler, J., Eng, J. K., Bumgarner, R., Goodlett, D. R., Aebersold, R., and Hood, L. (2001).Integrated genomic and proteomic analyses of a systematically perturbed metabolic network. Science 292, 929-933.
15. Jamshidi, N., and Palsson, B. O. (2010). Mass action stoichiometric simulation models: incorporating kinetics and regulation into stoichiometric models. Biophys. J. 98, 175-185.
16. Jensen, P. A., and Papin, J. A. (2011). Functional integration of a metabolic network model and expression data without arbitrary thresholding. Bioinformatics 27, 541-547.
17. Jerby, L., Shlomi, T., and Ruppin, E. (2010). Computational reconstruction of tissue-specific metabolic models: application to human liver metabolism. Mol. Syst. Biol. 6, 1-9.
18. Kauffman, K. J., Prakash, P., and Edwards, J. S. (2003). Advances in flux balance analysis. Curr. Opin. Biotechnol. 14, 491-496.
19. Lee, J. M., Gianchandani, E. P., and Papin, J. A. (2006). Flux balance analysis in the era of metabolomics. Brief. Bioinform. 7, 140-150.
20. Lewis, N. E., Nagarajan, H., and Palsson, B. O. (2012). Constraining the metabolic genotype-phenotype relationship using phylogeny of in silico methods. Nat. Rev. Microbiol. 10, 291-305.
21. 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., and Stephanopoulos, G. (2009). Linking high-resolution metabolic flux phenotypes and transcriptional regulation in yeast modulated by the global regulator Gcn4p. Proc. Natl. Acad. Sci. U.S.A. 106, 6477-6482.
22. Oberhardt, M. A., Goldberg, J. B., Hogardt, M., and Papin, J. A. (2010). Metabolic network analysis of Pseudomonas aeruginosa during chronic cystic fibrosis lung infection. J. Bacteriol. 192, 5534-5548.
23. Orth, J. D., Thiele, I., and Palsson, B. O. (2010). What is flux balance analysis? Nat. Biotechnol. 28, 245-248.
24. Palsson, B. O. (2002). In silico biology through omics. Nat. Biotechnol. 20, 649-650.
25. Pfau, T., Christian, N., and Ebenhoh, O. (2011). Systems approaches to modelling pathways and networks. Brief. Funct. Genomics 10, 266-279.
26. Price, N. D., Papin, J. A., Schilling, C. H., and Palsson, B. O. (2003). Genome-scale microbial in silico models: the constraints-based approach. Trends Microbiol. 21, 162-169.
27. Shlomi, T., Cabili, M. N., Herrgard, M. J., Palsson, B. O., and Ruppin, E. (2008). Network-based prediction of human tissue-specific metabolism. Nat. Biotechnol. 26, 1003-1010.
28. Sigurdsson, M. I., Jamshidi, N., Steingrimsson, E., Thiele, I., and Palsson, B. O. (2010). A detailed genome-wide reconstruction of mouse metabolism based on human recon 1. BMC Syst. Biol. 4, 140.
29. rd. (2003). Protein pathway and complex clustering of correlated mRNA and protein expression analyses in Saccharomyces cerevisiae. Proc. Natl. Acad. Sci. U.S.A. 100, 3107-3112.
30. Wessely, F., Barti, M., Guthke, R., Li, P., Schuster, S., and Kaleta, C. (2011). Optimal regulatory strategies for metabolic pathways in Escherichiacoli depending on protein costs. Mol. Syst. Biol. 7, 1-13.
31. Yizhak, K., Benyamini, T., Liebermeister, W., Ruppin, E., and Shlomi, T. (2010). Integrating quantitative proteomics and metabolomics with a genome-scale metabolic network model. Bioinformatics 26, i255-i260.
32. Zhang, W., Li, F., and Nie, L. (2010). Integrating multiple omics analysis for microbial biology:application and methodologies. Microbiology 156, 287-301
33. Zur, H., Ruppin, E., and Shlomi, T. (2010). iMAT: an integra-tive metabolic analysis tool. Bioinformatics 26, 3140-3314.