Recent developments in mass spectrometry (MS)-based metabolomic approaches are helping to establish lipid molecules as critical mediators of signal transduction in the nervous system. The endocannabinoid (eCB) 2-arachidonoylglycerol (2-AG), for example, serves as a key metabolic hub connecting the endogenous cannabinoid system (ECS) and pro-inflammatory eicosanoid production in the brain. In this manner, 2-AG signaling pathways modulate pain, anxiety, neuroinflammation, and neurodegeneration and have thus attracted considerable pharmaceutical interest for the treatment of nervous system diseases. Global increases in brain 2-AG, however, can also cause a range of undesirable side-effects. The multiplicity and differential distribution of 2-AG metabolic enzymes may provide a means to target specific brain 2-AG stores to fully capitalize on the development of 2-AG-based therapeutics with acceptable safety profiles. We hypothesize that the inhibition of distinct 2-AG biosynthetic and degradative enzymes will modulate the ECS/eicosanoid signaling network in specific brain cellular compartments to produce anti-inflammatory and neuroprotective effects, while limiting detrimental consequences observed with global ECS agonism or antagonism. This proposal describes experiments that leverage newly generated tools to selectively disrupt 2-AG metabolic enzymes together with the power of MS-based lipidomics to define novel enzymatic targets for the development of eCB-based therapeutics. First, we will map the cellular anatomy of 2-AG degradation pathways in the mouse brain. Specifically, we will use targeted and untargeted lipidomic profiling to examine the compartmentalization of the major brain 2-AG hydrolases (MAGL, ABHD6 and ABHD12) in neurons vs. glia, as well as to characterize cell type-specific metabolic alterations following genetic deletion of these enzymes. Second we will determine whether the inhibition of diacylglycerol lipases (DAGL) a and b, the two main 2-AG biosynthetic enzymes in the brain, can selectively modulate the brain ECS/eicosanoid network. By taking advantage of DAGLa or b knockout mice, we will map the cellular distribution of these two enzymes in the nervous system and assess how their inactivation alters pools of eCBs/eicosanoids basally and in experimental paradigms of neuroinflammation. Finally, we will carry out MS-based metabolic imaging of the anatomical distribution of 2-AG in the brain. We will use a novel Nanostructure-initiator Mass Spectrometry (NIMS) imaging platform to characterize the distribution of 2-AG levels in different brain regions basally and after inhibitio of 2-AG metabolic enzymes. In summary, this project will push the frontiers of applying cutting- edge lipidomic technologies to characterize the cellular and anatomical compartmentalization of the ECS/eicosanoid signaling network and its role in brain intercellular communication, as well as aid the development of novel eCB-based therapeutics for the treatment of nervous system diseases.

Public Health Relevance

The endogenous cannabinoid (eCB) 2-Arachidonoylglycerol (2-AG) is a key metabolic hub connecting signaling networks in the brain that regulate numerous physiological processes. Modulation of brain 2-AG holds great promise for the treatment of pain, mood disorders, and neurodegenerative diseases, but global alterations in this metabolite are also associated with undesirable side-effects. This proposal uses cutting-edge lipidomic technologies to examine the cellular anatomy of brain 2-AG metabolism and identify new avenues to selectively modulate this lipid and fully capitalize on the development of eCB-based therapeutics.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01GM109315-02
Application #
8744300
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Okita, Richard T
Project Start
2013-09-30
Project End
2017-08-31
Budget Start
2014-09-01
Budget End
2015-08-31
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Scripps Research Institute
Department
Type
DUNS #
City
La Jolla
State
CA
Country
United States
Zip Code
92037
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