In vivo analysis of metabolic dynamics inSaccharomyces cerevisiae : I. Experimental observations

Revisiting the Crabtree/Warburg effect in a dynamic perspective: a fitness advantage against sugar-induced cell death

The mechanisms behind the Warburg effect in mammalian cells, as well as for the similar Crabtree effect in the yeast Saccharomyces cerevisiae, are still a matter of debate: why do cells shift from the energy-efficient respiration to the energy-inefficient fermentation at high sugar concentration?

This review reports on the strong similarities of these phenomena in both cell types, discusses the current ideas, and provides a novel interpretation of their common functional mechanism in a dynamic perspective. This is achieved by analysing another phenomenon, the sugar-induced-cell-death (SICD) occurring in yeast at high sugar concentration, to highlight the link between ATP depletion and cell death.

The integration between SICD and the dynamic functioning of the glycolytic process, suggests that the Crabtree/Warburg effect may be interpreted as the avoidance of ATP depletion in those conditions where glucose uptake is higher than the downstream processing capability of the second phase of glycolysis. It follows that the down-regulation of respiration is strategic for cell survival allowing the allocation of more resources to the fermentation pathway, thus maintaining the cell energetic homeostasis.

Towards stable kinetics of large metabolic networks: Nonequilibrium potential function approach

While the biochemistry of metabolism in many organisms is well studied, details of the metabolic dynamics are not fully explored yet. Acquiring adequate in vivo kinetic parameters experimentally has always been an obstacle. Unless the parameters of a vast number of enzyme-catalyzed reactions happened to fall into very special ranges, a kinetic model for a large metabolic network would fail to reach a steady state. In this work we show that a stable metabolic network can be systematically established via a biologically motivated regulatory process. The regulation is constructed in terms of a potential landscape description of stochastic and nongradient systems. The constructed process draws enzymatic parameters towards stable metabolism by reducing the change in the Lyapunov function tied to the stochastic fluctuations. Biologically it can be viewed as interplay between the flux balance and the spread of workloads on the network. Our approach allows further constraints such as thermodynamics and optimal efficiency. We choose the central metabolism of Methylobacterium extorquens AM1 as a case study to demonstrate the effectiveness of the approach. Growth efficiency on carbon conversion rate versus cell viability and futile cycles is investigated in depth.