The ATP paradox is the expression of an economizing fuel mechanism.
ABSTRACT The strong negative correlation between glycolytic flux and intracellular ATP concentration observed in yeast has long been an intriguing and counterintuitive phenomenon, which has been referred to as the ATP paradox. Herein, using principles of irreversible thermodynamics it was shown that if the ATP-consuming pathways are more sensitive to extracellular glucose than glycolysis, then upon glucose addition glycolysis performance can switch from an efficient working regime to a dissipative regime, and vice versa, depending on glucose availability. The efficient regime represents a good compromise between high output power and low dissipation, whereas the dissipative working regime offers a higher output power although at a high glucose cost. The physiological and evolutionary implications of this switch strategy are discussed.
Article: Decomposing complex reaction networks using random sampling, principal component analysis and basis rotation.[show abstract] [hide abstract]
ABSTRACT: Metabolism and its regulation constitute a large fraction of the molecular activity within cells. The control of cellular metabolic state is mediated by numerous molecular mechanisms, which in effect position the metabolic network flux state at specific locations within a mathematically-definable steady-state flux space. Post-translational regulation constitutes a large class of these mechanisms, and decades of research indicate that achieving a network flux state through post-translational metabolic regulation is both a complex and complicated regulatory problem. No analysis method for the objective, top-down assessment of such regulation problems in large biochemical networks has been presented and demonstrated. We show that the use of Monte Carlo sampling of the steady-state flux space of a cell-scale metabolic system in conjunction with Principal Component Analysis and eigenvector rotation results in a low-dimensional and biochemically interpretable decomposition of the steady flux states of the system. This decomposition comes in the form of a low number of small reaction sets whose flux variability accounts for nearly all of the flux variability in the entire system. This result indicates an underlying simplicity and implies that the regulation of a relatively low number of reaction sets can essentially determine the flux state of the entire network in the given growth environment. We demonstrate how our top-down analysis of networks can be used to determine key regulatory requirements independent of specific parameters and mechanisms. Our approach complements the reductionist approach to elucidation of regulatory mechanisms and facilitates the development of our understanding of global regulatory strategies in biological networks.BMC Systems Biology 04/2009; 3:30. · 3.15 Impact Factor