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A Simple and Scalable Strategy for Analysis of Endogenous Protein Dynamics

The ability to analyze protein function in a native context is central to understanding cellular physiology. This study explores whether tagging endogenous proteins with a reporter is a scalable strategy for generating cell models that accurately quantitate protein dynamics. Specifically, it investi...

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Detalles Bibliográficos
Autores principales: Schwinn, Marie K., Steffen, Leta S., Zimmerman, Kris, Wood, Keith V., Machleidt, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7265437/
https://www.ncbi.nlm.nih.gov/pubmed/32488146
http://dx.doi.org/10.1038/s41598-020-65832-1
Descripción
Sumario:The ability to analyze protein function in a native context is central to understanding cellular physiology. This study explores whether tagging endogenous proteins with a reporter is a scalable strategy for generating cell models that accurately quantitate protein dynamics. Specifically, it investigates whether CRISPR-mediated integration of the HiBiT luminescent peptide tag can easily be accomplished on a large-scale and whether integrated reporter faithfully represents target biology. For this purpose, a large set of proteins representing diverse structures and functions, some of which are known or potential drug targets, were targeted for tagging with HiBiT in multiple cell lines. Successful insertion was detected for 86% of the targets, as determined by luminescence-based plate assays, blotting, and imaging. In order to determine whether endogenously tagged proteins yield more representative models, cells expressing HiBiT protein fusions either from endogenous loci or plasmids were directly compared in functional assays. In the tested cases, only the edited lines were capable of accurately reproducing the anticipated biology. This study provides evidence that cell lines expressing HiBiT fusions from endogenous loci can be rapidly generated for many different proteins and that these cellular models provide insight into protein function that may be unobtainable using overexpression-based approaches.