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Tunable translation-level CRISPR interference by dCas13 and engineered gRNA in bacteria

Author

Listed:
  • Giho Kim

    (Seoul National University)

  • Ho Joon Kim

    (Seoul National University)

  • Keonwoo Kim

    (Seoul National University)

  • Hyeon Jin Kim

    (Seoul National University)

  • Jina Yang

    (Jeju National University)

  • Sang Woo Seo

    (Seoul National University
    Seoul National University
    Seoul National University
    Seoul National University)

Abstract

Although CRISPR-dCas13, the RNA-guided RNA-binding protein, was recently exploited as a translation-level gene expression modulator, it has still been difficult to precisely control the level due to the lack of detailed characterization. Here, we develop a synthetic tunable translation-level CRISPR interference (Tl-CRISPRi) system based on the engineered guide RNAs that enable precise and predictable down-regulation of mRNA translation. First, we optimize the Tl-CRISPRi system for specific and multiplexed repression of genes at the translation level. We also show that the Tl-CRISPRi system is more suitable for independently regulating each gene in a polycistronic operon than the transcription-level CRISPRi (Tx-CRISPRi) system. We further engineer the handle structure of guide RNA for tunable and predictable repression of various genes in Escherichia coli and Vibrio natriegens. This tunable Tl-CRISPRi system is applied to increase the production of 3-hydroxypropionic acid (3-HP) by 14.2-fold via redirecting the metabolic flux, indicating the usefulness of this system for the flux optimization in the microbial cell factories based on the RNA-targeting machinery.

Suggested Citation

  • Giho Kim & Ho Joon Kim & Keonwoo Kim & Hyeon Jin Kim & Jina Yang & Sang Woo Seo, 2024. "Tunable translation-level CRISPR interference by dCas13 and engineered gRNA in bacteria," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49642-x
    DOI: 10.1038/s41467-024-49642-x
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    References listed on IDEAS

    as
    1. Xiaolong Cheng & Zexu Li & Ruocheng Shan & Zihan Li & Shengnan Wang & Wenchang Zhao & Han Zhang & Lumen Chao & Jian Peng & Teng Fei & Wei Li, 2023. "Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Chen Dong & Jason Fontana & Anika Patel & James M. Carothers & Jesse G. Zalatan, 2018. "Synthetic CRISPR-Cas gene activators for transcriptional reprogramming in bacteria," Nature Communications, Nature, vol. 9(1), pages 1-11, December.
    3. Chen Dong & Jason Fontana & Anika Patel & James M. Carothers & Jesse G. Zalatan, 2018. "Author Correction: Synthetic CRISPR-Cas gene activators for transcriptional reprogramming in bacteria," Nature Communications, Nature, vol. 9(1), pages 1-1, December.
    4. Bo Zhang & Yangmiao Ye & Weiwei Ye & Vanja Perčulija & Han Jiang & Yiyang Chen & Yu Li & Jing Chen & Jinying Lin & Siqi Wang & Qi Chen & Yu-San Han & Songying Ouyang, 2019. "Two HEPN domains dictate CRISPR RNA maturation and target cleavage in Cas13d," Nature Communications, Nature, vol. 10(1), pages 1-11, December.
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