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Modularization and response curve engineering of a naringenin-responsive transcriptional biosensor

Brecht De Paepe (UGent) , Jo Maertens (UGent) , Bartel Vanholme (UGent) and Marjan De Mey (UGent)
(2018) ACS SYNTHETIC BIOLOGY. 7(5). p.1303-1314
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Abstract
To monitor the intra-and extracellular environment of micro-organisms and to adapt their metabolic processes accordingly, scientists are reprogramming nature's myriad of transcriptional regulatory systems into transcriptional biosensors, which are able to detect small molecules and, in response, express specific output signals of choice. However, the naturally occurring response curve, the key characteristic of biosensor circuits, is typically not in line with the requirements for real-life biosensor applications. In this contribution, a natural LysR-type naringenin-responsive biosensor circuit is developed and characterized with Escherichia coli as host organism. Subsequently, this biosensor is dissected into a clearly defined detector and effector module without loss of functionality, and the influence of the expression levels of both modules on the biosensor response characteristics is investigated. Two collections of ten unique synthetic biosensors each are generated. Each collection demonstrates a unique diversity of response curve characteristics spanning a 128-fold change in dynamic and 2.5-fold change in operational ranges and 3-fold change in levels of Noise, fit for a wide range of applications, such as adaptive laboratory evolution, dynamic pathway control and high-throughput screening methods. The established biosensor engineering concepts, and the developed biosensor collections themselves, are of use for the future development and customization of biosensors in general, for the multitude of biosensor applications and as a compelling alternative for the commonly used LadI-, TetR- and AraC-based inducible circuits.
Keywords
RHIZOBIUM-LEGUMINOSARUM, ESCHERICHIA-COLI, NOD-BOX, HERBASPIRILLUM-SEROPEDICAE, BIOSYNTHETIC PATHWAYS, NODULATION GENES, BINDING-SITES, PROTEIN, COMBINATORIAL, METABOLITES, transcriptional biosensors, response curve engineering, naringenin, dynamic range, operational range, Escherichia coli

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Citation

Please use this url to cite or link to this publication:

Chicago
De Paepe, Brecht, Jo Maertens, Bartel Vanholme, and Marjan De Mey. 2018. “Modularization and Response Curve Engineering of a Naringenin-responsive Transcriptional Biosensor.” Acs Synthetic Biology 7 (5): 1303–1314.
APA
De Paepe, Brecht, Maertens, J., Vanholme, B., & De Mey, M. (2018). Modularization and response curve engineering of a naringenin-responsive transcriptional biosensor. ACS SYNTHETIC BIOLOGY, 7(5), 1303–1314.
Vancouver
1.
De Paepe B, Maertens J, Vanholme B, De Mey M. Modularization and response curve engineering of a naringenin-responsive transcriptional biosensor. ACS SYNTHETIC BIOLOGY. 2018;7(5):1303–14.
MLA
De Paepe, Brecht, Jo Maertens, Bartel Vanholme, et al. “Modularization and Response Curve Engineering of a Naringenin-responsive Transcriptional Biosensor.” ACS SYNTHETIC BIOLOGY 7.5 (2018): 1303–1314. Print.
@article{8567872,
  abstract     = {To monitor the intra-and extracellular environment of micro-organisms and to adapt their metabolic processes accordingly, scientists are reprogramming nature's myriad of transcriptional regulatory systems into transcriptional biosensors, which are able to detect small molecules and, in response, express specific output signals of choice. However, the naturally occurring response curve, the key characteristic of biosensor circuits, is typically not in line with the requirements for real-life biosensor applications. In this contribution, a natural LysR-type naringenin-responsive biosensor circuit is developed and characterized with Escherichia coli as host organism. Subsequently, this biosensor is dissected into a clearly defined detector and effector module without loss of functionality, and the influence of the expression levels of both modules on the biosensor response characteristics is investigated. Two collections of ten unique synthetic biosensors each are generated. Each collection demonstrates a unique diversity of response curve characteristics spanning a 128-fold change in dynamic and 2.5-fold change in operational ranges and 3-fold change in levels of Noise, fit for a wide range of applications, such as adaptive laboratory evolution, dynamic pathway control and high-throughput screening methods. The established biosensor engineering concepts, and the developed biosensor collections themselves, are of use for the future development and customization of biosensors in general, for the multitude of biosensor applications and as a compelling alternative for the commonly used LadI-, TetR- and AraC-based inducible circuits.},
  author       = {De Paepe, Brecht and Maertens, Jo and Vanholme, Bartel and De Mey, Marjan},
  issn         = {2161-5063},
  journal      = {ACS SYNTHETIC BIOLOGY},
  keyword      = {RHIZOBIUM-LEGUMINOSARUM,ESCHERICHIA-COLI,NOD-BOX,HERBASPIRILLUM-SEROPEDICAE,BIOSYNTHETIC PATHWAYS,NODULATION GENES,BINDING-SITES,PROTEIN,COMBINATORIAL,METABOLITES,transcriptional biosensors,response curve engineering,naringenin,dynamic range,operational range,Escherichia coli},
  language     = {eng},
  number       = {5},
  pages        = {1303--1314},
  title        = {Modularization and response curve engineering of a naringenin-responsive transcriptional biosensor},
  url          = {http://dx.doi.org/10.1021/acssynbio.7b00419},
  volume       = {7},
  year         = {2018},
}

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