Development of novel metabolite-responsive transcription factors via transposon-mediated protein fusion

Abstract 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...

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Published in:Protein engineering, design and selection design and selection, 2018-02, Vol.31 (2), p.55-63
Main Authors: Younger, Andrew K D, Su, Peter Y, Shepard, Andrea J, Udani, Shreya V, Cybulski, Thaddeus R, Tyo, Keith E J, Leonard, Joshua N
Format: Article
Language:English
Subjects:
Biosensing Techniques - methods
DNA Transposable Elements
Escherichia coli - genetics
Escherichia coli - metabolism
Escherichia coli Proteins - genetics
Escherichia coli Proteins - metabolism
Original
Protein Domains
Transcription Factors - genetics
Transcription Factors - metabolism
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Summary:Abstract 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.
ISSN:1741-0126
1741-0134
DOI:10.1093/protein/gzy001