Structural robustness of metabolic networks with respect to multiple knockouts.
We present a generalised framework for analysing structural robustness of metabolic networks, based on the concept of elementary flux modes (EFMs). Extending our earlier study on single knockouts [Wilhelm, T., Behre, J., Schuster, S., 2004. Analysis of structural robustness of metabolic networks. IEE Proc. Syst. Biol. 1(1), 114-120], we are now considering the general case of double and multiple knockouts. The robustness measures are based on the ratio of the number of remaining EFMs after knockout vs. the number of EFMs in the unperturbed situation, averaged over all combinations of knockouts. With the help of simple examples we demonstrate that consideration of multiple knockouts yields additional information going beyond single-knockout results. It is proven that the robustness score decreases as the knockout depth increases. We apply our extended framework to metabolic networks representing amino acid anabolism in Escherichia coli and human hepatocytes, and the central metabolism in human erythrocytes. Moreover, in the E. coli model the two subnetworks synthesising amino acids that are essential and those that are non-essential for humans are studied separately. The results are discussed from an evolutionary viewpoint. We find that E. coli has the most robust metabolism of all the cell types studied here. Considering only the subnetwork of the synthesis of non-essential amino acids, E. coli and the human hepatocyte show about the same robustness.
Behre
Jörn
J
Faculty of Biology and Pharmaceutics, Section of Bioinformatics, Friedrich Schiller University Jena, Ernst-Abbe-Platz 2, D-07743 Jena, Germany. jbehre@minet.uni-jena.de
Wilhelm
Thomas
T
von Kamp
Axel
A
Ruppin
Eytan
E
Schuster
Stefan
S
D000596:Amino Acids / Q000096:biosynthesis; D004912:Erythrocytes / Q000378:metabolism; D004926:Escherichia coli / Q000378:metabolism; D022781:Hepatocytes / Q000378:metabolism; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics / Q000502:physiology*; D008954:Models, Biological; D017384:Sequence Deletion
D000596:Amino Acids