Abstract
We present an effectively computable measure of functional gene similarity that is based on metabolic gene activity across a variety of growth media. We applied this measure to 750 genes comprising the metabolic network of the budding yeast. Comparing the in silico computed functional similarities to those obtained by using experimental expression data, we show that our computational method captures similarities beyond those that are obtained by the topological analysis of metabolic networks, thus revealing—at least in part—dynamic characteristics of gene function. We also suggest that network centrality partially explains functional centrality (i.e. the number of functionally highly similar genes) by reporting a significant correlation between the two. Finally, we find that functional similarities between topologically distant genes occur between genes with different GO annotations.
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References
Jeong, H., Tombor, B., Albert, R., Oltavi, Z., Barabasi, A.: The large-scale organization of metabolic networks. Nature 407, 651–654 (2000)
Ravasz, E., Somera, A., Mongru, D., Oltvai, Z., Barabasi, A.: Hierarchical organization of modularity in metabolic networks. Science 297, 1551–1555 (2002)
Kharchenko, P., Church, G.M., Vitkup, D.: Expression dynamics of a cellular metabolic network. Molecular Systems Biology 1, E1–E6 (2005)
Chen, L., Vitkup, D.: Predicting genes for orphan metabolic activities using phylogenetic profiles. Genome Biol. 7, R17 (2006)
Famili, I., Forster, J., Nielsen, J., Palsson, B.Ø.: 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 100, 13134–13139 (2003)
Zaslaver, A., Mayo, A., Rosenberg, R., Bashkin, P., Sberro, H., et al.: Just-in-time transcription program in metabolic pathways. Nat. Genet. 36, 486–491 (2004)
Schuster, S., Dandekar, T., Fell, D.: Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering. Trends Biotechnol. 17, 53–60 (1999)
Schuster, S., Klamt, S., Weckwerth, W., Moldenhauer, F., Pfeiffer, T.: Use of network analysis of metabolic systems in bioengineering. Bioprocess and Biosystems Engineering 24, 363–372 (2002)
Reed, J., Palsson, B.: Genome-scale in silico models of e. coli have multiple equivalent phenotypic states: assessment of correlated reaction subsets that comprise network states. Genome Res. 14, 1797–1805 (2004)
Bilu, Y., Shlomi, T., Barkai, N., Ruppin, E.: Conservation of expression and sequence of metabolic genes is reflected by activity across metabolic states. PLoS Comp. Bio. (in press, 2006)
Fell, D., Small, J.: Fat synthesis in adipose tissue. An examination of stoichiometric constraints. Biochem. J. 238, 781–786 (1986)
Kauffman, K., Prakash, P., Edwards, J.: Advances in flux balance analysis.. Curr. Opin. Biotechnol. 14, 491–496 (2003)
Price, N.D., Reed, J.L., Palsson, B.Ø.: Genome-scale Models of Microbial Cells: Evaluating the consequences of constraints. Nature Reviews Microbiology 2, 886–897 (2004)
Varma, A., Palsson, B.: Metabolic capabilities of Escherichia coli: II. Optimal growth patterns. J. Theor. Biol. 165, 503–522 (1993)
Schilling, C.H., Edwards, J.S., Palsson, B.: Toward metabolic phenomics: analysis of genomic data using flux balances. Biotechnol. Prog. 15, 288–295 (1999)
Fell, D.: Understanding the Control of Metabolism. Portland Press, London (1996)
Schilling, C.H., Edwards, J.S., Letscher, D., Palsson, B.Ø.: Combining pathway analysis with flux balance analysis for the comprehensive study of metabolic systems. Biotechnol. Bioeng. 71, 286–306 (2000)
Vanderbei, R.J.: Linear Programming: Foundations and Extensions. Kluwer Academic Publishers, Boston (1996)
Edwards, J., Ibarra, R., Palsson, B.: In silico predictions of Escherichia coli metabolic capabilities are consistent with experimental data. Nat. Biotechnol. 19, 125–130 (2001)
Badarinarayana, V., Estep, P.W., Shendure, J., Edwards, J., Tavazoie, S., Lam, F., Church, G.M.: Selection analyses of insertional mutants using subgenic-resolution arrays. Nat. Biotechnol. 19, 1060–1065 (2001)
Duarte, N., Herrgard, M., Palsson, B.Ø.: Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. Genome Res. 14, 1298–1309 (2004)
Segre, D., Vitkup, D., Church, G.: Analysis of optimality in natural and perturbed metabolic networks. Proc. Natl. Acad. Sci. U S A 99, 15112–15117 (2002)
Shlomi, T., Berkman, O., Ruppin, E.: Regulatory on/off minimization of metabolic flux changes after genetic perturbations. Proc. Natl. Acad. Sci. U S A 102, 7695–7700 (2005)
Kuepfer, L., Sauer, U., Blank, L.M.: Metabolic functions of duplicate genes in Saccharomyces cerevisiae. Genome Res. 15, 1421–1430 (2005)
Mahadevan, R., Schilling, C.: The effects of alternate optimal solutions in constraint-based genome-scale metabolic models. Metab. Eng. 5, 264–276 (2003)
Almaas, E., Oltvai, Z., Barabasi, A.: The activity reaction core and plasticity of metabolic networks. PLoS Comput. Biol. 1, 68 (2005)
Salton, G., McGill, M.J.: Introduction to Modern Information Retrieval. McGraw-Hill, New-York (1983)
Hughes, T., et al.: Flux analysis of underdetermined metabolic networks: the quest for the missing constraints. Cell 102, 109–126 (2000)
Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P.: Numerical Recipes in C++: the art of scientific computing. Cambridge University Press, Cambridge (2002)
Ashburner, M., et al.: Gene Ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000)
Issel-Tarver, L., et al.: Saccharomyces Genome Database. Methods Enzymol 350, 329–346 (2002)
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Rokhlenko, O., Shlomi, T., Sharan, R., Ruppin, E., Pinter, R.Y. (2006). Flux-Based vs. Topology-Based Similarity of Metabolic Genes. In: Bücher, P., Moret, B.M.E. (eds) Algorithms in Bioinformatics. WABI 2006. Lecture Notes in Computer Science(), vol 4175. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11851561_26
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DOI: https://doi.org/10.1007/11851561_26
Publisher Name: Springer, Berlin, Heidelberg
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