Reduced Vglut2/Slc17a6 Gene Expression Levels throughout the Mouse Subthalamic Nucleus Cause Cell Loss and Structural Disorganization Followed by Increased Motor Activity and Decreased Sugar Consumption.

The subthalamic nucleus (STN) plays a central role in motor, cognitive, and affective behavior. Deep brain stimulation (DBS) of the STN is the most common surgical intervention for advanced Parkinson's disease (PD), and STN has lately gained attention as target for DBS in neuropsychiatric disorders, including obsessive compulsive disorder, eating disorders, and addiction. Animal studies using STN-DBS, lesioning, or inactivation of STN neurons have been used extensively alongside clinical studies to unravel the structural organization, circuitry, and function of the STN. Recent studies in rodent STN models have exposed different roles for STN neurons in reward-related functions. We have previously shown that the majority of STN neurons express the vesicular glutamate transporter 2 gene (Vglut2/Slc17a6) and that reduction of Vglut2 mRNA levels within the STN of mice [conditional knockout (cKO)] causes reduced postsynaptic activity and behavioral hyperlocomotion. The cKO mice showed less interest in fatty rewards, which motivated analysis of reward-response. The current results demonstrate decreased sugar consumption and strong rearing behavior, whereas biochemical analyses show altered dopaminergic and peptidergic activity in the striatum. The behavioral alterations were in fact correlated with opposite effects in the dorsal versus the ventral striatum. Significant cell loss and disorganization of the STN structure was identified, which likely accounts for the observed alterations. Rare genetic variants of the human VGLUT2 gene exist, and this study shows that reduced Vglut2/Slc17a6 gene expression levels exclusively within the STN of mice is sufficient to cause strong modifications in both the STN and the mesostriatal dopamine system.

In silico dynamic molecular interaction networks for the discovery of new therapeutic targets.

Systems biology has emerged as a major trend in biological research during the past decade. As living organisms are described in more and more detail, it aims at filling the gap between understanding basic molecular processes and complex biological systems in which new properties often emerge from the combination of these elementary processes. This approach culminates in the development of computer-based mathematical models of physiological and pathophysiological processes. We review the state of the art in dynamic modelling, with emphasis on two complementary approaches: the modelling of small systems that is mostly developed by academic teams and aims at understanding generic biological properties, and the modelling of large systems that is mostly implemented by industrial companies and aims at the generation of new therapeutic strategies. We also provide an example of such large-scale modelling applied to the identification of drug targets for neurodegeneration.