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Transcription Factor‐Based Biosensors in High‐Throughput Screening: Advances and Applications
Author(s) -
Cheng Feng,
Tang XiaoLing,
Kardashliev Tsvetan
Publication year - 2018
Publication title -
biotechnology journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.144
H-Index - 84
eISSN - 1860-7314
pISSN - 1860-6768
DOI - 10.1002/biot.201700648
Subject(s) - biosensor , synthetic biology , computational biology , robustness (evolution) , biology , transcription factor , metabolic engineering , computer science , genetics , gene , biochemistry
The molecular mechanisms that cells use to sense changes in the intra‐ and extracellular environment are increasingly utilized in synthetic biology to build genetic reporter constructs for various applications. Although in nature sensing can be RNA‐mediated, most existing genetically‐encoded biosensors are based on transcription factors (TF) and cognate DNA sequences. Here, the recent advances in the integration of TF‐based biosensors in metabolic and protein engineering screens whereas distinction is made between production‐driven and competitive screening systems for enzyme evolution under physiological conditions are discussed. Furthermore, the advantages and disadvantages of existing TF‐based biosensors are examined with respects to dynamic range, sensitivity, and robustness, and compared to other screening approaches. The application examples discussed in this review demonstrate the promising potential TF‐based biosensors hold as screening tools in laboratory evolution of proteins and metabolic pathways, alike.

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