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  5. Directed evolution of VanR biosensor specificity in yeast

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Article
en
2020

Directed evolution of VanR biosensor specificity in yeast

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en
2020
Vol 1
Vol. 1
DOI: 10.1016/j.biotno.2020.01.002

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Jay D Keasling
Jay D Keasling

University of California, Berkeley

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Vasil D’Ambrosio
Subrata Pramanik
Kati Goroncy
+6 more

Abstract

Allosterically regulated transcription factors (aTFs) based biosensors from prokaryotes have been widely used to screen large gene libraries, stabilize engineered microbes from evolutionary drifting, and for detection of soil pollutants, among many other applications. However, even though aTF-based biosensors have been established as successful tools for bioengineering and remediation, rational engineering of aTF small molecule-specificity have so far not been demonstrated, highlighting the need for a deeper understanding of the sequence-function relationships that govern aTF allostery. Here, by combining directed evolution of a naïve library of VanR, a vanillic acid transcriptional regulator from Caulobacter crescentus in yeast, followed by saturation mutagenesis of selected positions we identify residues required for vanillic acid responsiveness, while at the same time maintaining responsiveness to vanillin. Selected single-position VanR mutants show both complete repression of transcription in the absence of any ligand, complete loss of vanillic acid responsiveness, while still maintaining high derepression in the presence of vanillin. By computational ligand docking analyses we also discuss the structure-function relationship single mutations can have on aTF specificity, an attribute potentially accounting for the wide-spread arise of aTF members belonging to the GntR superfamily of transcriptional regulators.

How to cite this publication

Vasil D’Ambrosio, Subrata Pramanik, Kati Goroncy, Tadas Jakočiūnas, David Schönauer, Mehdi D. Davari, Ulrich Schwaneberg, Jay D Keasling, Michael K. Jensen (2020). Directed evolution of VanR biosensor specificity in yeast. , 1, DOI: https://doi.org/10.1016/j.biotno.2020.01.002.

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Publication Details

Type

Article

Year

2020

Authors

9

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1016/j.biotno.2020.01.002

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