Identification of protein-protein interactions and defining the protein composition of distinct subcellular structures are frequently essential to uncovering the mechanisms underlying human health and disease. Yet these activities often present considerable methodological barriers. Current approaches to investigate candidate protein-interactions include yeast-2-hybrid analysis and complex purification schemes that, despite being powerful tools in this endeavor, inherently possess considerable limitations in their application. For example, the yeast-two-hybrid method to assess protein interactions introduces a highly artificial test environment. Complex purification is limited to interactions that are strog enough to survive solubilization or may require chemical crosslinkers. Characterizing the protein constituency of specific subcellular compartments requires isolation to considerable purity, frequently a difficult or insurmountable task. We have developed an approach called BioID that uses a biotin ligase tethered to bait proteins to label neighboring proteins in live cells, facilitting their isolation and identification. When applied to lamin-A, a nuclear envelope constituent with limited solubility, over 50% of the proteins identified by BioID are known to interact with or predominantly reside in close proximity to lamin-A. The remaining candidates likely represent proteins whose distribution is only partially NE-associated and/or are poorly characterized. These results provide a compelling proof-of-principle for the potential of BioID to screen for relevant protein interactions. This project is designed to define the capabilities and limitations f BioID in the following ways: 1) Determining the broad potential of this method to identify candidate protein interactions and testing its application to monitor temporospatial differences in protein behavior. 2) Applying BioID to map the protein constituency of distinct subcellular domains that have proved refractory to traditional approaches. 3) Defining the efficacy of BioID in diverse subcellular domains. By expanding our understanding of BioID with the results of these studies, we will provide the research community with fundamental knowledge of the capabilities and limitations of this method. This will enhance the efficiency of application of BioD to a broad array of projects relevant to human health and disease.

Public Health Relevance

With the human genome sequenced, attention has shifted towards the challenging task of characterizing the protein products of that genome, in part by mapping the interactions between proteins that contribute to human health and disease. This project seeks to expand our understanding of a new method to identify the proximity and interactions between proteins in living cells. This method, called BioID, has the potential to advance the rate at which scientists characterize proteins and their interactions, information necessary to understand the mechanisms of, and design therapies for, human disease.

Agency
National Institute of Health (NIH)
Type
Research Project (R01)
Project #
5R01GM102203-02
Application #
8724524
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Edmonds, Charles G
Project Start
Project End
Budget Start
Budget End
Support Year
2
Fiscal Year
2014
Total Cost
Indirect Cost
Name
Sanford Research/Usd
Department
Type
DUNS #
City
Sioux Falls
State
SD
Country
United States
Zip Code
57104
Kim, Dae In; Birendra, K C; Zhu, Wenhong et al. (2014) Probing nuclear pore complex architecture with proximity-dependent biotinylation. Proc Natl Acad Sci U S A 111:E2453-61