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Automated identification of sequence-tailored Cas9 proteins using massive metagenomic data

Author

Listed:
  • Matteo Ciciani

    (Cellular and Integrative Biology, University of Trento)

  • Michele Demozzi

    (Cellular and Integrative Biology, University of Trento)

  • Eleonora Pedrazzoli

    (Cellular and Integrative Biology, University of Trento)

  • Elisabetta Visentin

    (Cellular and Integrative Biology, University of Trento)

  • Laura Pezzè

    (Alia Therapeutics)

  • Lorenzo Federico Signorini

    (Cellular and Integrative Biology, University of Trento
    Tel Aviv University)

  • Aitor Blanco-Miguez

    (Cellular and Integrative Biology, University of Trento)

  • Moreno Zolfo

    (Cellular and Integrative Biology, University of Trento)

  • Francesco Asnicar

    (Cellular and Integrative Biology, University of Trento)

  • Antonio Casini

    (Alia Therapeutics)

  • Anna Cereseto

    (Cellular and Integrative Biology, University of Trento)

  • Nicola Segata

    (Cellular and Integrative Biology, University of Trento)

Abstract

The identification of the protospacer adjacent motif (PAM) sequences of Cas9 nucleases is crucial for their exploitation in genome editing. Here we develop a computational pipeline that was used to interrogate a massively expanded dataset of metagenome and virome assemblies for accurate and comprehensive PAM predictions. This procedure allows the identification and isolation of sequence-tailored Cas9 nucleases by using the target sequence as bait. As proof of concept, starting from the disease-causing mutation P23H in the RHO gene, we find, isolate and experimentally validate a Cas9 which uses the mutated sequence as PAM. Our PAM prediction pipeline will be instrumental to generate a Cas9 nuclease repertoire responding to any PAM requirement.

Suggested Citation

  • Matteo Ciciani & Michele Demozzi & Eleonora Pedrazzoli & Elisabetta Visentin & Laura Pezzè & Lorenzo Federico Signorini & Aitor Blanco-Miguez & Moreno Zolfo & Francesco Asnicar & Antonio Casini & Anna, 2022. "Automated identification of sequence-tailored Cas9 proteins using massive metagenomic data," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-34213-9
    DOI: 10.1038/s41467-022-34213-9
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    References listed on IDEAS

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    1. Eleonora Pedrazzoli & Michele Demozzi & Elisabetta Visentin & Matteo Ciciani & Ilaria Bonuzzi & Laura Pezzè & Lorenzo Lucchetta & Giulia Maule & Simone Amistadi & Federica Esposito & Mariangela Lupo &, 2024. "CoCas9 is a compact nuclease from the human microbiome for efficient and precise genome editing," Nature Communications, Nature, vol. 15(1), pages 1-12, December.

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