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)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM102203-01A1
Application #
8456412
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Edmonds, Charles G
Project Start
2013-08-21
Project End
2018-05-31
Budget Start
2013-08-21
Budget End
2014-05-31
Support Year
1
Fiscal Year
2013
Total Cost
$304,000
Indirect Cost
$114,000
Name
Sanford Research/Usd
Department
Type
DUNS #
050113252
City
Sioux Falls
State
SD
Country
United States
Zip Code
57104
Johnson, Tyler B; Mechels, Keegan; Anderson, Ruth Ellen et al. (2018) Characterization of a recurrent missense mutation in the forkhead DNA-binding domain of FOXP1. Sci Rep 8:16161
Roux, Kyle J; Kim, Dae In; Burke, Brian et al. (2018) BioID: A Screen for Protein-Protein Interactions. Curr Protoc Protein Sci 91:19.23.1-19.23.15
Brudvig, J J; Cain, J T; Schmidt-Grimminger, G G et al. (2018) MARCKS Is Necessary for Netrin-DCC Signaling and Corpus Callosum Formation. Mol Neurobiol 55:8388-8402
Birendra Kc; May, Danielle G; Benson, Benjamin V et al. (2017) VRK2A is an A-type lamin-dependent nuclear envelope kinase that phosphorylates BAF. Mol Biol Cell 28:2241-2250
Kim, Dae In; Jensen, Samuel C; Noble, Kyle A et al. (2016) An improved smaller biotin ligase for BioID proximity labeling. Mol Biol Cell 27:1188-96
Forred, Benjamin J; Neuharth, Skyla; Kim, Dae In et al. (2016) Identification of Redox and Glucose-Dependent Txnip Protein Interactions. Oxid Med Cell Longev 2016:5829063
Mehus, Aaron A; Anderson, Ruthellen H; Roux, Kyle J (2016) BioID Identification of Lamin-Associated Proteins. Methods Enzymol 569:3-22
Kim, Dae In; Roux, Kyle J (2016) Filling the Void: Proximity-Based Labeling of Proteins in Living Cells. Trends Cell Biol 26:804-817
Kim, Dae In; Jensen, Samuel C; Roux, Kyle J (2016) Identifying Protein-Protein Associations at the Nuclear Envelope with BioID. Methods Mol Biol 1411:133-46
Alam, Samer G; Lovett, David; Kim, Dae In et al. (2015) The nucleus is an intracellular propagator of tensile forces in NIH 3T3 fibroblasts. J Cell Sci 128:1901-11

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