No abstract

Corynebacterium glutamicum is a biotin-auxotrophic bacterium and some strains efficiently produce glutamic acid under biotin-limiting conditions. In an effort to understand C. glutamicum metabolism under biotin limitation, growth of the type strain ATCC 13032 was investigated in batch cultures and a time-course analysis was performed. A transient excretion of organic acids was observed and we focused our attention on lactate synthesis. Lactate synthesis was due to the ldh-encoded l-lactate dehydrogenase (Ldh). Features of Ldh activity and ldh transcription were analysed. The ldh gene was shown to be regulated at the transcriptional level by SugR, a pleiotropic transcriptional repressor also acting on most phosphotransferase system (PTS) genes. Electrophoretic mobility shift assays (EMSAs) and site-directed mutagenesis allowed the identification of the SugR-binding site. Effector studies using EMSAs and analysis of ldh expression in a ptsF mutant revealed fructose 1-phosphate as a highly efficient negative effector of SugR. Fructose 1,6-bisphosphate also affected SugR binding.

89-95.] does not take into account experimental evidence for correlations between enzyme concentrations in the cell. We investigated the implications of two causes of linear correlations: competition between enzymes, which is a mere physical adaptation of the cell to the limitation of resources and space, and regulatory correlations, which result from the existence of regulatory networks. These correlations generate redistribution of enzyme concentrations when the concentration of an enzyme varies; this may dramatically alter the flux and metabolite concentration curves. In particular, negative correlations cause the flux to have a maximum value for a defined distribution of enzyme concentrations. Redistribution coefficients of enzyme concentrations allowed us to calculate the Ôcombined response coefficientÕ that quantifies the response of flux or metabolite concentration to a perturbation of enzyme concentration.Keywords: biochemical modelling; cellular constraint; flux; metabolite; response coefficient.The introduction of the metabolic control theory by Kacser & Burns [1] and Heinrich & Rapoport [2] was a great improvement in our understanding of the control of metabolism (for a review see [3]). Numerous extensions to the classical theory have been proposed to get rid of some restrictive hypotheses of the initial theory. Extensions exist, for example, for nonproportionality of the rates of reaction to enzyme concentration [4], enzyme-enzyme interaction [5,6], time-varying systems [7,8], or supply-demand analysis [9]. Nevertheless, most studies have neglected the correlations that exist between enzyme amounts in the cell.Concentration is a key parameter for enzyme activity. Changes in expression of enzyme genes play a central role in the physiology of the cell, and dramatic modifications of the cell proteome are consistently observed over development and differentiation, or in response to environmental changes (see http://us.expasy.org for examples in various species). In addition, genetic studies have revealed natural variability for enzyme concentration, for instance for alcohol dehydrogenase in Drosophila [10] or lactate dehydrogenase in Fundulus heteroclitus [11]. Other examples can also be found [12,13]. Quantitative proteomic approaches have confirmed that a majority of proteins/enzymes can display a large range of variation within species [14][15][16][17][18][19]. Those physiological or genetic variations are expected to be interdependent. There is evidence for cellular constraints that induce a variation of concentration of some enzymes in response to a variation of others. These correlations between enzyme concentrations undoubtedly have an impact on the behaviour of metabolic systems, and hence on their evolution. Two kinds of correlations will be studied in this paper. The first one will be referred to as competition. It is a mere physical adaptation of the cell to energetic or steric constraints. The second one results from regulatory networks. It will be referred to as regulation.Competitive con...