Journal
JOURNAL OF NEUROSCIENCE METHODS
Volume 261, Issue -, Pages 128-134Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.jneumeth.2016.01.006
Keywords
Synaptosomes; Insulin responsiveness; Insulin signaling; Insulin receptor phosphorylation
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Funding
- NIH/NIA grant [1R01AG042890]
- Mitchell Center for Neurodegenerative Diseases
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Background: Studying the insulin signaling response at the synapse is an important approach to understand molecular mechanisms involved in disease-related neurodegenerative processes. New method: We developed a method for studying the insulin responsiveness at the synaptic level by isolating functional synaptosomes from fresh or frozen tissue and exposing them to insulin in the presence of ATP (a critical step) to detect insulin receptor (IR) activation. Results: We performed an ATP dose-response curve, insulin dose-response curve, and insulin response time course to optimize this method. We also demonstrated that our protocol reflects the degree of insulin responsiveness in vivo by using an animal model of known insulin resistance, AtENPP1-Tg mice. Comparison with existing method(s): This method is advantageous over other methods detecting IR in total brain homogenates due to the ability to detect IR response without confounding contributions from other cell areas and cell types also expressing IR. Furthermore, ex vivo insulin stimulation can be compared to baseline synaptosomes obtained from the same animal which improves reliability and statistical power while decreasing the number of animals required to perform individual experiments. Conclusions: We have developed a reliable, efficient method to measure insulin-driven ex vivo phosphorylation of the synaptosomal insulin receptor that can reliably reflect the pre-existing insulin responsiveness status in the CNS of the animal. To the best of our knowledge, this is the first evidence of stimulation of isolated synaptosomes with insulin and a promising new technique to study the synaptic CNS insulin responsiveness under physiological or disease conditions. (C) 2016 Elsevier B.V. All rights reserved.
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