From genome to cellular phenotype-a role for metabolic flux analysis?

More than 20 genomes have been completely sequenced, and the first draft of the complete human genome is expected this year. This barrage of information should eventually lead to a better understanding of cellular physiology, which in turn may then be exploited to advance human health, agricultural production, and industrial fermentation. If the physiology of the organism under study is relatively well understood, such as for Escherichia coli or yeast, the compilation of this sequence data to reconstruct metabolic pathways may seem a reasonable challenge. However, if there is only limited biochemical information available, such as for Treponema pallidum (the causative agent of syphilis), a partial list of putative enzymes is unlikely to allow metabolic networks and cellular phenotypes to be established. Realistically, a list of genes alone is not enough to understand the pathophysiology or manipulate the metabolism of T. pallidum. Thus, a robust method of converting a list of putative enzymes into a set of metabolic pathways could be a powerful bioinformatic tool. In this issue, Schuster et al. discuss a means of defining pathways rigorously and show how to express their constitutive activities as the sum of "elementary flux modes", each of which represents a minimal sequence of steps that can in principle operate independantly of any others.