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dCas9 regulator to neutralize competition in CRISPRi circuits

Author

Listed:
  • Hsin-Ho Huang

    (Massachusetts Institute of Technology)

  • Massimo Bellato

    (University of Pavia)

  • Yili Qian

    (Massachusetts Institute of Technology)

  • Pablo Cárdenas

    (Massachusetts Institute of Technology)

  • Lorenzo Pasotti

    (University of Pavia)

  • Paolo Magni

    (University of Pavia)

  • Domitilla Del Vecchio

    (Massachusetts Institute of Technology
    Massachusetts Institute of Technology)

Abstract

CRISPRi-mediated gene regulation allows simultaneous control of many genes. However, highly specific sgRNA-promoter binding is, alone, insufficient to achieve independent transcriptional regulation of multiple targets. Indeed, due to competition for dCas9, the repression ability of one sgRNA changes significantly when another sgRNA becomes expressed. To solve this problem and decouple sgRNA-mediated regulatory paths, we create a dCas9 concentration regulator that implements negative feedback on dCas9 level. This allows any sgRNA to maintain an approximately constant dose-response curve, independent of other sgRNAs. We demonstrate the regulator performance on both single-stage and layered CRISPRi-based genetic circuits, zeroing competition effects of up to 15-fold changes in circuit I/O response encountered without the dCas9 regulator. The dCas9 regulator decouples sgRNA-mediated regulatory paths, enabling concurrent and independent regulation of multiple genes. This allows predictable composition of CRISPRi-based genetic modules, which is essential in the design of larger scale synthetic genetic circuits.

Suggested Citation

  • Hsin-Ho Huang & Massimo Bellato & Yili Qian & Pablo Cárdenas & Lorenzo Pasotti & Paolo Magni & Domitilla Del Vecchio, 2021. "dCas9 regulator to neutralize competition in CRISPRi circuits," Nature Communications, Nature, vol. 12(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21772-6
    DOI: 10.1038/s41467-021-21772-6
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    Cited by:

    1. Kirill Sechkar & Harrison Steel & Giansimone Perrino & Guy-Bart Stan, 2024. "A coarse-grained bacterial cell model for resource-aware analysis and design of synthetic gene circuits," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    2. Carlos Barajas & Hsin-Ho Huang & Jesse Gibson & Luis Sandoval & Domitilla Vecchio, 2022. "Feedforward growth rate control mitigates gene activation burden," Nature Communications, Nature, vol. 13(1), pages 1-10, December.

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