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Affinity selection of DNA-binding protein complexes using mRNA display.
Seiji Tateyama1, Kenichi Horisawa, Hideaki Takashima
1Department of Biosciences and Informatics, Faculty of Science and Technology, Keio University, 3-14-1, Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan.
Nucleic Acids Research
|February 16, 2006
Summary
This study introduces mRNA display for identifying DNA-binding protein complexes, crucial for understanding gene regulation. The method efficiently enriches known and novel transcription factor interactions from complex libraries.
Area of Science:
- Molecular Biology
- Genomics
- Biochemistry
Background:
- Understanding DNA-protein interactions is key to mapping genome-wide transcriptional regulatory networks.
- Transcription factors often form heterooligomeric complexes to bind DNA, necessitating methods to study these interactions.
Purpose of the Study:
- To develop and validate a novel mRNA display application for the in vitro selection of DNA-binding protein heterodimeric complexes.
- To demonstrate the system's capability in identifying known and diverse AP-1 family transcription factors.
Main Methods:
- Utilized mRNA display technology for in vitro selection of DNA-binding protein complexes.
- Employed a TPA-responsive element (TRE) as bait DNA under optimized selection conditions.
- Screened a model library and a library derived from mouse brain poly A(+) RNA.
Main Results:
- Simultaneously enriched known interactors c-fos and c-jun approximately 100-fold in one selection round from a model library.
- Successfully identified various AP-1 family genes (c-jun, c-fos, junD, junB, atf2, b-atf) from a mouse brain-derived library after six rounds.
- Demonstrated the system's ability to identify diverse DNA-binding protein complexes in a single experiment.
Conclusions:
- The developed mRNA display selection system is effective for identifying multiple DNA-binding protein complexes simultaneously.
- This method holds significant promise for discovering novel DNA-binding transcription factor complexes, essential for comprehensive network analysis.