Applications and Tuning Strategies for Transcription Factor-Based Metabolite Biosensors

被引:12
|
作者
Zhou, Gloria J. [1 ]
Zhang, Fuzhong [1 ,2 ,3 ]
机构
[1] Washington Univ, Dept Energy Environm & Chem Engn, St Louis, MO 63130 USA
[2] Washington Univ, Div Biol & Biomed Sci, St Louis, MO 63130 USA
[3] Washington Univ, Inst Mat Sci & Engn, St Louis, MO 63130 USA
来源
BIOSENSORS-BASEL | 2023年 / 13卷 / 04期
基金
美国国家卫生研究院;
关键词
transcription factor; biosensor tuning; biosensor applications; transcriptional control; translational control; high-throughput screening; dynamic regulation; metabolic heterogeneity; TO-CELL VARIATION; ESCHERICHIA-COLI; DYNAMIC-RANGE; BINDING; CIRCUITS; SYNTHASE; PATHWAY; DESIGN; ACID; TIME;
D O I
10.3390/bios13040428
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Transcription factor (TF)-based biosensors are widely used for the detection of metabolites and the regulation of cellular pathways in response to metabolites. Several challenges hinder the direct application of TF-based sensors to new hosts or metabolic pathways, which often requires extensive tuning to achieve the optimal performance. These tuning strategies can involve transcriptional or translational control depending on the parameter of interest. In this review, we highlight recent strategies for engineering TF-based biosensors to obtain the desired performance and discuss additional design considerations that may influence a biosensor's performance. We also examine applications of these sensors and suggest important areas for further work to continue the advancement of small-molecule biosensors.
引用
收藏
页数:14
相关论文
共 50 条
  • [21] Transcription Factor-Based Genetic Engineering in Microalgae
    Mochdia, Keiichi
    Tamaki, Shun
    PLANTS-BASEL, 2021, 10 (08):
  • [22] Development of a Transcription Factor-Based Lactam Biosensor
    Zhang, Jingwei
    Barajas, Jesus F.
    Burdu, Mehmet
    Ruegg, Thomas L.
    Dias, Bryton
    Keasling, Jay D.
    ACS SYNTHETIC BIOLOGY, 2017, 6 (03): : 439 - 445
  • [23] Transcription factor-based biosensors and inducible systems in non-model bacteria: current progress and future directions
    Kim, Nancy M.
    Sinnott, Riley W.
    Sandoval, Nicholas R.
    CURRENT OPINION IN BIOTECHNOLOGY, 2020, 64 (64) : 39 - 46
  • [24] Tuning the dynamic range of 1-butanol-responsive transcription factor-based biosensor in Escherichia coli
    Kim, Nancy
    Sandoval, Nicholas
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2019, 257
  • [25] A transcription factor-based mechanism for mouse heterochromatin formation
    Bulut-Karslioglu, Aydan
    Perrera, Valentina
    Scaranaro, Manuela
    de la Rosa-Velazquez, Inti Alberto
    van de Nobelen, Suzanne
    Shukeir, Nicholas
    Popow, Johannes
    Gerle, Borbala
    Opravil, Susanne
    Pagani, Michaela
    Meidhof, Simone
    Brabletz, Thomas
    Manke, Thomas
    Lachner, Monika
    Jenuwein, Thomas
    NATURE STRUCTURAL & MOLECULAR BIOLOGY, 2012, 19 (10) : 1023 - U78
  • [26] A Transcription Factor-Based Biosensor for Detection of Itaconic Acid
    Hanko, Erik K. R.
    Minton, Nigel P.
    Malys, Naglis
    ACS SYNTHETIC BIOLOGY, 2018, 7 (05): : 1436 - 1446
  • [27] A factor-based risk model for multifactor investment strategies
    Abergel, Frederic
    Bellone, Benoit
    Soupe, Francois
    JOURNAL OF RISK, 2022, 24 (04): : 1 - 22
  • [28] Transcription Factor-Based Strategies to Generate Neural Cell Types from Human Pluripotent Stem Cells
    Canals, Isaac
    Quist, Ella
    Ahlenius, Henrik
    CELLULAR REPROGRAMMING, 2021, 23 (04) : 206 - 220
  • [29] Development of a Transcription Factor-Based Diamine Biosensor in Corynebacterium glutamicum
    Zhao, Nannan
    Song, Jie
    Zhang, Hao
    Lin, Ying
    Han, Shuangyan
    Huang, Yuanyuan
    Zheng, Suiping
    ACS SYNTHETIC BIOLOGY, 2021, 10 (11): : 3074 - 3083
  • [30] Transcription Factor-Based Drug Design in Anticancer Drug Development
    Athanasios G. Papavassiliou
    Molecular Medicine, 1997, 3 : 799 - 810