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Engineering Split-Luciferase Assay Systems for Detection of Protein Solubility
Neurodegenerative diseases are a significant public health epidemic. Often these diseases are associated with protein misfolding that results in the formation of insoluble protein fibrils, known as amyloids. As such, these fibrils have been a major focus of research and a target for potential therapeutics, necessitating assays that can probe and determine the efficacy of drug candidates in biologically relevant settings. Prior methods for quantifying fibril formation and drug efficacy against fibril formation have relied on small molecular probes or genetically encodable fusion proteins that produce colorimetric or fluorescent signals. Herein, we describe the engineering of a series of genetically encodable protein solubility assays utilizing a rapidly and spontaneously reassembling split-nanoluciferase (Nluc) platform that is capable of reporting on changes in protein solubility in living cells due to mutation within the disease related protein of interest or the presence of aggregation inhibitors using bioluminescence. We apply the split-Nluc assay to a variety of disease-relevant proteins, namely amyloid-beta (Alzheimer's disease), alpha-synuclein (Parkinson’s disease), amylin (diabetes mellitus), and huntingtin (Huntington's disease). Additionally, we provide a general protocol for the design and implementation of the assay. Lastly, we improve on the assay and show its ability to report on genetically encodable inhibitors of aggregation. Taken together, this work provides a robust bioluminescence assay platform for evaluating the influence of mutations as well as inhibitors on protein solubility in living cells. In the long term, the assays outlined herein could be utilized to identify modulations of protein aggregation with potential use as research tools and in the clinic.
Nelson, Travis J, "Engineering Split-Luciferase Assay Systems for Detection of Protein Solubility" (2020). ETD collection for University of Nebraska - Lincoln. AAI27955278.