Development of novel metabolite-responsive transcription factors via transposon-mediated protein fusion
| Autor: | Keith E. J. Tyo, Joshua N. Leonard, Andrea J Shepard, Thaddeus R Cybulski, Peter Su, Andrew K. D. Younger, Shreya V. Udani |
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| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Transposable element Bioengineering Biosensing Techniques macromolecular substances Computational biology 010402 general chemistry 01 natural sciences Biochemistry Metabolic engineering 03 medical and health sciences Synthetic biology Maltose-binding protein Protein Domains Transcription (biology) Escherichia coli Molecular Biology Transcription factor Zinc finger biology Chemistry Escherichia coli Proteins technology industry and agriculture 0104 chemical sciences 030104 developmental biology DNA Transposable Elements biology.protein Original Article Biosensor Transcription Factors Biotechnology |
| Zdroj: | Protein Engineering, Design and Selection. 31:55-63 |
| ISSN: | 1741-0134 1741-0126 |
| DOI: | 10.1093/protein/gzy001 |
| Popis: | Naturally evolved metabolite-responsive biosensors enable applications in metabolic engineering, ranging from screening large genetic libraries to dynamically regulating biosynthetic pathways. However, there are many metabolites for which a natural biosensor does not exist. To address this need, we developed a general method for converting metabolite-binding proteins into metabolite-responsive transcription factors—Biosensor Engineering by Random Domain Insertion (BERDI). This approach takes advantage of an in vitro transposon insertion reaction to generate all possible insertions of a DNA-binding domain into a metabolite-binding protein, followed by fluorescence activated cell sorting to isolate functional biosensors. To develop and evaluate the BERDI method, we generated a library of candidate biosensors in which a zinc finger DNA-binding domain was inserted into maltose binding protein, which served as a model well-studied metabolite-binding protein. Library diversity was characterized by several methods, a selection scheme was deployed, and ultimately several distinct and functional maltose-responsive transcriptional biosensors were identified. We hypothesize that the BERDI method comprises a generalizable strategy that may ultimately be applied to convert a wide range of metabolite-binding proteins into novel biosensors for applications in metabolic engineering and synthetic biology. |
| Databáze: | OpenAIRE |
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