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Insulated transcriptional elements enable precise design of genetic circuits

Author

Listed:
  • Yeqing Zong

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Haoqian M. Zhang

    (Peking University
    Peking University)

  • Cheng Lyu

    (Peking University)

  • Xiangyu Ji

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Junran Hou

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Xian Guo

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Qi Ouyang

    (Peking University
    Peking University
    Peking University)

  • Chunbo Lou

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

Abstract

Rational engineering of biological systems is often complicated by the complex but unwanted interactions between cellular components at multiple levels. Here we address this issue at the level of prokaryotic transcription by insulating minimal promoters and operators to prevent their interaction and enable the biophysical modeling of synthetic transcription without free parameters. This approach allows genetic circuit design with extraordinary precision and diversity, and consequently simplifies the design-build-test-learn cycle of circuit engineering to a mix-and-match workflow. As a demonstration, combinatorial promoters encoding NOT-gate functions were designed from scratch with mean errors of 96% using our insulated transcription elements. Furthermore, four-node transcriptional networks with incoherent feed-forward loops that execute stripe-forming functions were obtained without any trial-and-error work. This insulation-based engineering strategy improves the resolution of genetic circuit technology and provides a simple approach for designing genetic circuits for systems and synthetic biology.

Suggested Citation

  • Yeqing Zong & Haoqian M. Zhang & Cheng Lyu & Xiangyu Ji & Junran Hou & Xian Guo & Qi Ouyang & Chunbo Lou, 2017. "Insulated transcriptional elements enable precise design of genetic circuits," Nature Communications, Nature, vol. 8(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:8:y:2017:i:1:d:10.1038_s41467-017-00063-z
    DOI: 10.1038/s41467-017-00063-z
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    Cited by:

    1. Jie Li & Haonan Zhang & Dongyu Li & Ya-Jun Liu & Edward A. Bayer & Qiu Cui & Yingang Feng & Ping Zhu, 2023. "Structure of the transcription open complex of distinct σI factors," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    2. Chenrui Qin & Yanhui Xiang & Jie Liu & Ruilin Zhang & Ziming Liu & Tingting Li & Zhi Sun & Xiaoyi Ouyang & Yeqing Zong & Haoqian M. Zhang & Qi Ouyang & Long Qian & Chunbo Lou, 2023. "Precise programming of multigene expression stoichiometry in mammalian cells by a modular and programmable transcriptional system," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    3. Judee A. Sharon & Chelsea Dasrath & Aiden Fujiwara & Alessandro Snyder & Mace Blank & Sam O’Brien & Lauren M. Aufdembrink & Aaron E. Engelhart & Katarzyna P. Adamala, 2023. "Trumpet is an operating system for simple and robust cell-free biocomputing," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    4. Bob Sluijs & Roel J. M. Maas & Ardjan J. Linden & Tom F. A. Greef & Wilhelm T. S. Huck, 2022. "A microfluidic optimal experimental design platform for forward design of cell-free genetic networks," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    5. Yuanli Gao & Lei Wang & Baojun Wang, 2023. "Customizing cellular signal processing by synthetic multi-level regulatory circuits," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

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