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Exercising Control When Control is Distributed

  • David A. Fell
  • Simon Thomas
Chapter
Part of the NATO Science Series book series (ASHT, volume 74)

Abstract

The major justification for studying flux control coefficients must be to understand how metabolic fluxes can be, or are, changed. Here, the theory of metabolic control analysis exposes a conundrum: it suggests that control is likely to be distributed over a number of pathway steps, and hence, because of the summation theorem, any individual flux control coefficient is likely to be less than one. Many of the experimental measurements of flux control coefficients have tended to confirm this expectation (Fell, 1992, 1997), with small values predominant. A notable exception has been mammalian glycogen synthesis from blood glucose in both liver (Agius et al. 1996; Agius 1998; see also Chapter 11 in this book) and muscle (Shulman & Rothman, 1996), but this may represent a less typical case in that it is a short pathway, so the flux control coefficients cannot be divided into many small increments. Furthermore, as a storage pathway, it is clearly more advantageous for the flux to respond to the glucose supply rather than to a hypothetical demand for glycogen, and this is aided by high flux control at the start of the pathway (though this also has potential adverse effects that are counteracted in muscle, at least, by means described later). This tendency of many pathways not to have a step with a large flux control coefficient has implications for the feasibility of making large changes in flux that can only be approximately predicted within control analysis. However, the finite change analysis of Small & Kacser (1993), though admittedly not precise, suggested that activation of a single enzyme would give a relatively much smaller change in flux unless its flux control coefficient were very close to 1.

Keywords

Metabolic Flux Universal Method Single Enzyme Flux Change Control Coefficient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media Dordrecht 2000

Authors and Affiliations

  • David A. Fell
    • 1
  • Simon Thomas
    • 2
  1. 1.School of Biological and Molecular SciencesOxford Brookes UniversityOxfordUK
  2. 2.Department of Biological SciencesBrunel UniversityUxbridgeUK

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