Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering

doi:10.1016/S0167-7799(98)01290-6

Trends in Biotechnology

Volume 17, Issue 2, 1 February 1999, Pages 53-60

https://doi.org/10.1016/S0167-7799(98)01290-6 Get rights and content

Abstract

Rational metabolic engineering requires powerful theoretical methods such as pathway analysis, in which the topology of metabolic networks is considered. All metabolic capabilities in steady states are composed of elementary flux modes, which are minimal sets of enzymes that can each generate valid steady states. The modes of the fructose-2,6-bisphosphate cycle, the combined tricarboxylic-acid-cycle–glyoxylate-shunt system and tryptophan synthesis are used here for illustration. This approach can be used for many biotechnological applications such as increasing the yield of a product, channelling a product into desired pathways and in functional reconstruction from genomic data.

Section snippets

Theoretical methods

In biochemical modelling, a technical distinction is usually made between external and internal metabolites (see Glossary). The reversibility or irreversibility of enzymatic reactions is known in most cases, even when the kinetic parameters are unknown. (Reversible reactions can be directed in either direction under physiological conditions, such as the reactions shared by glycolysis and gluconeogenesis; irreversible reactions include those of most kinases and phosphatases.) A great many

The tricarboxylic acid cycle and adjacent reactions

In the reaction scheme of the tricarboxylic acid (TCA) cycle, glyoxylate shunt and adjacent amino acid metabolism (Fig. 2 ), all cofactors (such as ATP and NAD) are considered as external, as are 2-phosphoglycerate (PG), NH₃ and CO₂ (that is, their concentrations are assumed to be unaffected by the reactions in the scheme). All of the enzymes shown are present in wild-type Escherichia coli. By contrast, alanine aminotransferase appears to be absent from E. coli; its function is probably carried

What does it all mean?

Elementary modes are idealized situations; the question is, do they occur in living cells? Usually, demands are mixed so that the flux distribution is a superposition of several modes. However, cellular metabolism can support radically different flux distributions in response to different environmental stimuli¹. When microorganisms grow on single substrates, all pathways that use other substrates are down-regulated; even if a mixture of carbon sources is provided, catabolite repression causes

Optimal conversion yields

In many situations, the biosynthesis of a product is feasible by a number of different routes. It is then interesting to determine the way in which the molar yield (that is, the product:substrate ratio) is maximal for the desired product and minimal for byproducts1, 11, 12, 15. The optimal flux distributions might not always be obtainable but it is nevertheless interesting to calculate the upper limits for yield and productivity, to know the best that can be expected.

After determining the

Future directions

Various extensions of the elementary-modes approach are worth pursuing. It is certainly interesting to adapt the method for protein biosynthesis. The stoichiometric coefficients of amino acid utilization in protein synthesis can be estimated from the average amino acid composition of proteins. However, these coefficients are not normally integers, nor are they sufficiently certain. The same problem occurs with the P:O ratio in oxidative phosphorylation. It has turned out that the stoichiometric

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Trends in Biotechnology

FocusDetection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering

Abstract

Section snippets

Theoretical methods

The tricarboxylic acid cycle and adjacent reactions

What does it all mean?

Optimal conversion yields

Future directions

J. Biol. Chem.

Trends Biotechnol.

Curr. Top. Cell. Regul.

Trends Biotechnol.

J. Theor. Biol.

J. Biol. Chem.

Curr. Biol.

J. Biotechnol.

Science

Biotechnol. Bioeng.

Biotechnol. Bioeng.

Biochem. J.

Biotechnol. Bioeng.

Focus
Detection of elementary flux modes in biochemical networks: a promising tool for pathway analysis and metabolic engineering