The mamallian target of rapamycin (mTOR) is a protein implicated in a variety of cellular processes involving growth and division. In the context of the brain, it regulates synaptic plasticity and axon elongation; its dysfunction is implicated in the pathogenesis of multiple complex, heterogeneous neurodegenerative diseases. These include, but are not limited to Alzheimer’s Disease (AD), autism spectrum disorder (ASD), and epilepsy. mTOR boasts a deeply complex and far-reaching signalling cascade, and its activity affects the expression levels of a large number of proteins. As such, investigation of the proteins with whom mTOR interacts is a pertinent endeavor to the advancement of understanding the complex pathogenesis of neurodegenerative disease.
The complexity of this endeavor makes it a target well-poised for protein-protein interaction network (PPIN) analysis. Thus, using a previously recorded MS/MS dataset listing proteins whose expression levels change upon rapamycin administration, we set out to identify key proteins and characterize the properties of the mTOR interactome overall using a variety of toplogical measures and analytical techniques.
Using such techniques, we found that the in the PPIN created from our data, a certain subset of proteins subjected the network to particular fragility. Namely, the kinless hubs, which have high within-module degree as well as a large participation coefficient, show vulnerability exceeding that of even conventionally defined hub. Some of these kinless hubs exhibit critical structural roles in the PPIN such that their removal damages the overall efficiency of communication within the network at an individually observable level. Work is ongoing to further investigate these proteins and the potential biological implications of their importance in the network described in the present study.
Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/48390 |
Date | 12 March 2024 |
Creators | Stierer, Michael Patrick |
Contributors | Bragdon, Beth |
Source Sets | Boston University |
Language | en_US |
Detected Language | English |
Type | Thesis/Dissertation |
Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
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