This title appears in the Scientific Report :
2016
Please use the identifier:
http://hdl.handle.net/2128/12964 in citations.
Please use the identifier: http://dx.doi.org/10.1007/s00253-015-7090-3 in citations.
Transcription factor-based biosensors in biotechnology: current state and future prospects
Transcription factor-based biosensors in biotechnology: current state and future prospects
Living organisms have evolved a plethora of sensing systems for the intra- and extracellular detection of small molecules, ions or physical parameters. Several recent studies have demonstrated that these principles can be exploited to devise synthetic regulatory circuits for metabolic engineering st...
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Personal Name(s): | Mahr, Regina |
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Frunzke, Julia (Corresponding author) | |
Contributing Institute: |
Biotechnologie; IBG-1 |
Published in: | Applied microbiology and biotechnology, 100 (2016) 1, S. 79 - 90 |
Imprint: |
Berlin
Springer
2016
|
DOI: |
10.1007/s00253-015-7090-3 |
Document Type: |
Journal Article |
Research Program: |
Biotechnology |
Link: |
OpenAccess OpenAccess |
Publikationsportal JuSER |
Please use the identifier: http://dx.doi.org/10.1007/s00253-015-7090-3 in citations.
Living organisms have evolved a plethora of sensing systems for the intra- and extracellular detection of small molecules, ions or physical parameters. Several recent studies have demonstrated that these principles can be exploited to devise synthetic regulatory circuits for metabolic engineering strategies. In this context, transcription factors (TFs) controlling microbial physiology at the level of transcription play a major role in biosensor design, since they can be implemented in synthetic circuits controlling gene expression in dependency of, for example, small molecule production. Here, we review recent progress on the utilization of TF-based biosensors in microbial biotechnology highlighting different areas of application. Recent advances in metabolic engineering reveal TF-based sensors to be versatile tools for strain and enzyme development using high-throughput (HT) screening strategies and adaptive laboratory evolution, the optimization of heterologous pathways via the implementation of dynamic control circuits and for the monitoring of single-cell productivity in live cell imaging studies. These examples underline the immense potential of TF-based biosensor circuits but also identify limitations and room for further optimization. |