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Hierarchical composition of reliable recombinase logic devices

Author

Listed:
  • Sarah Guiziou

    (Université de Montpellier)

  • Pauline Mayonove

    (Université de Montpellier)

  • Jerome Bonnet

    (Université de Montpellier)

Abstract

A major goal of synthetic biology is to reprogram living organisms to solve pressing challenges in manufacturing, environmental remediation, and healthcare. Recombinase devices can efficiently encode complex logic in many species, yet current designs are performed on a case-by-case basis, limiting their scalability and requiring time-consuming optimization. Here we provide a systematic framework for engineering reliable recombinase logic devices by hierarchical composition of well-characterized, optimized recombinase switches. We apply this framework to build a recombinase logic device family supporting up to 4-input Boolean logic within a multicellular system. This work enables straightforward implementation of multicellular recombinase logic and will support the predictable engineering of several classes of recombinase devices to reliably control cellular behavior.

Suggested Citation

  • Sarah Guiziou & Pauline Mayonove & Jerome Bonnet, 2019. "Hierarchical composition of reliable recombinase logic devices," Nature Communications, Nature, vol. 10(1), pages 1-7, December.
    • Handle: RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-08391-y
    DOI: 10.1038/s41467-019-08391-y
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    Cited by:

    1. Cassandra J. Maranas & Wesley George & Sarah K. Scallon & Sydney VanGilder & Jennifer L. Nemhauser & Sarah Guiziou, 2024. "A history-dependent integrase recorder of plant gene expression with single-cell resolution," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Sarah Guiziou & Cassandra J. Maranas & Jonah C. Chu & Jennifer L. Nemhauser, 2023. "An integrase toolbox to record gene-expression during plant development," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Brian D. Huang & Dowan Kim & Yongjoon Yu & Corey J. Wilson, 2024. "Engineering intelligent chassis cells via recombinase-based MEMORY circuits," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    4. Alex J. H. Fedorec & Neythen J. Treloar & Ke Yan Wen & Linda Dekker & Qing Hsuan Ong & Gabija Jurkeviciute & Enbo Lyu & Jack W. Rutter & Kathleen J. Y. Zhang & Luca Rosa & Alexey Zaikin & Chris P. Bar, 2024. "Emergent digital bio-computation through spatial diffusion and engineered bacteria," Nature Communications, Nature, vol. 15(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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