Introduction
A critical issue in the actual debate around the astrocyte-neuron lactate shuttle hypothesis is whether lactate produced within the brain by astrocytes can be taken up and metabolized by neurons upon activation. Although there is ample evidence that neurons can efficiently use lactate as an energy substrate, at least in vitro 1 , few experimental data exist to indicate that it is indeed the case in vivo 2 . In order to address this question, we used a modeling approach to determine which parameters are essential and sufficient to explain typical brain lactate kinetics observed upon activation.
Method
On the basis of a previously validated model taking into account the compartmentalization of energy metabolism 3 , we derived a mathematical model of brain lactate kinetics, including cellular lactate production or consumption, regional cerebral blood flow, exchanges through the blood brain barrier and extracellular pH variation. This model was applied to published data describing the changes in extracellular lactate levels following activation 4 .
Results and Discussion
Results show that the initial dip in the extracellular lactate concentration observed at the onset of stimulation requires a rapid uptake within a cellular compartment which is most likely neurons. Moreover, an increase in uptake occurring with repetitive stimulation explains the more pronounced dip observed as the extracellular lactate concentration reaches higher levels due to activation of astrocytic glycolysis. In contrast, neither increased lactate washout, due to the enhancement of blood flow, nor diffusion parameters could explain such patterns. It is concluded that instead of being a major fact against the ANLS hypothesis, the initial dip in brain lactate levels, observed both in animals 4 and in humans 5 , strongly suggests that lactate consumption by neurons occurs from the very start of stimulation. These data concur with recent demonstrations of a net lactate transfer between astrocytes and neurons in vivo.
Footnotes
Acknowledgements
This work was supported by the Fondation pour la Recherche Médicale and the Action Concertée Incitative ‘Neurosciences Intégratives et Computationelles’ (French Ministry of Research).
