ASTRALIS SIGNED

Project "ASTRALIS" data sheet

The following table provides information about the project.

 Partnership

Take a look of project's partnership.

Map

 Project objective

ASTRALIS proposes all-optical strategies to shed light on holes in our understanding of how intracellular signaling complexity, downstream of specific G protein-coupled receptors (GPCRs), is generated in the brain. We focus on the understudied cells of the brain, astrocytes, which are highly interconnected but electrically silent, and signal through GPCRs and second messengers in response to norepinephrine (NE). We use them as models to study whether intracellular signaling in vivo is governed extrinsically, by noradrenergic afferent fibers releasing neuromodulators in defined spatiotemporal patterns –and therefore by receptor-specific activation dynamics– or rather intrinsically, by compartmentalization of cellular components, resulting in spatiotemporally different signaling outputs. During the outgoing phase, I will use advanced optical approaches to: (1) measure the spatiotemporal dimension of NE release in vivo, and (2) characterize the cellular and subcellular heterogeneity of astrocytic signals in response to NE in vitro and their relevance to the circuit, by simultaneously monitoring astrocytic and neuronal activity. During the incoming phase, I will (3) combine knowledge generated within the outgoing phase about in vivo noradrenergic signaling with the optical technologies developed by the host lab, in order to dissect the contribution of receptor dynamics to the spatiotemporally defined signaling of adrenoceptors. Significance: Current strategies to study intracellular signaling downstream of GPCRs widely neglect the spatiotemporal component of the inputs to which receptors are exposed naturally. Clarifying these aspects of receptor function would radically change the way we probe and study these proteins. In addition, elucidating the largely disregarded contribution of astrocytes in noradrenergic signaling at the cellular and network level will help understand the pathophysiology of related disorders and conceive better therapeutic strategies.