ArticleNature communications2025
Systematic comparison and base-editing-mediated directed protein evolution and functional screening yield superior auxin-inducible degron technology.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Systematic evaluation of tools for auxin-inducible protein degradation in budding yeast.Molecular biology of the cell · 2026Article
- Spatial Chromatin Organization Across the Cell Cycle: Insights from Auxin-Inducible Protein Depletion.Cells · 2025Review
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7 authors.
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Abstract
Biological mechanisms are inherently dynamic, requiring precise and rapid manipulations for effective characterization. Traditional genetic manipulations operate on long timescales, making them unsuitable for studying dynamic processes or characterizing essential genes, where chronic depletion can cause cell death. We compare five inducible protein degradation systems-dTAG, HaloPROTAC, IKZF3, and two auxin-inducible degrons (AID) using OsTIR1 and AtFB2-evaluating degradation efficiency, basal degradation, target recovery after ligand washout, and ligand impact. This analysis identifies OsTIR1-based AID 2.0 as the most robust system. However, AID 2.0's higher degradation efficiency comes with target-specific basal degradation and slower recovery rates. To address these limitations, we employ base-editing-mediated mutagenesis followed by several rounds of functional selection and screening. This directed protein evolution generates several gain-of-function OsTIR1 variants, including S210A, that significantly enhance the overall degron efficiency. The resulting degron system, named AID 2.1, maintains effective target protein depletion with minimal basal degradation and faster recovery after ligand washout, enabling characterization and rescue experiments for essential genes. Our comparative assessment and directed evolution approach provide a reference dataset and improved degron technology for studying gene functions in dynamic biological contexts.
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