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A generalizable Cas9/sgRNA prediction model using machine transfer learning with small high-quality datasets

Author

Listed:
  • Dalton T. Ham

    (Schulich School of Medicine and Dentistry)

  • Tyler S. Browne

    (Schulich School of Medicine and Dentistry)

  • Pooja N. Banglorewala

    (Schulich School of Medicine and Dentistry)

  • Tyler L. Wilson

    (Tesseraqt Optimization Inc)

  • Richard K. Michael

    (Tesseraqt Optimization Inc)

  • Gregory B. Gloor

    (Schulich School of Medicine and Dentistry)

  • David R. Edgell

    (Schulich School of Medicine and Dentistry)

Abstract

The CRISPR/Cas9 nuclease from Streptococcus pyogenes (SpCas9) can be used with single guide RNAs (sgRNAs) as a sequence-specific antimicrobial agent and as a genome-engineering tool. However, current bacterial sgRNA activity models struggle with accurate predictions and do not generalize well, possibly because the underlying datasets used to train the models do not accurately measure SpCas9/sgRNA activity and cannot distinguish on-target cleavage from toxicity. Here, we solve this problem by using a two-plasmid positive selection system to generate high-quality data that more accurately reports on SpCas9/sgRNA cleavage and that separates activity from toxicity. We develop a machine learning architecture (crisprHAL) that can be trained on existing datasets, that shows marked improvements in sgRNA activity prediction accuracy when transfer learning is used with small amounts of high-quality data, and that can generalize predictions to different bacteria. The crisprHAL model recapitulates known SpCas9/sgRNA-target DNA interactions and provides a pathway to a generalizable sgRNA bacterial activity prediction tool that will enable accurate antimicrobial and genome engineering applications.

Suggested Citation

  • Dalton T. Ham & Tyler S. Browne & Pooja N. Banglorewala & Tyler L. Wilson & Richard K. Michael & Gregory B. Gloor & David R. Edgell, 2023. "A generalizable Cas9/sgRNA prediction model using machine transfer learning with small high-quality datasets," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41143-7
    DOI: 10.1038/s41467-023-41143-7
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    References listed on IDEAS

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    1. Carolin Anders & Ole Niewoehner & Alessia Duerst & Martin Jinek, 2014. "Structural basis of PAM-dependent target DNA recognition by the Cas9 endonuclease," Nature, Nature, vol. 513(7519), pages 569-573, September.
    2. Elitza Deltcheva & Krzysztof Chylinski & Cynthia M. Sharma & Karine Gonzales & Yanjie Chao & Zaid A. Pirzada & Maria R. Eckert & Jörg Vogel & Emmanuelle Charpentier, 2011. "CRISPR RNA maturation by trans-encoded small RNA and host factor RNase III," Nature, Nature, vol. 471(7340), pages 602-607, March.
    3. Benjamin P. Kleinstiver & Michelle S. Prew & Shengdar Q. Tsai & Ved V. Topkar & Nhu T. Nguyen & Zongli Zheng & Andrew P. W. Gonzales & Zhuyun Li & Randall T. Peterson & Jing-Ruey Joanna Yeh & Martin J, 2015. "Engineered CRISPR-Cas9 nucleases with altered PAM specificities," Nature, Nature, vol. 523(7561), pages 481-485, July.
    4. Thomas A. Hamilton & Gregory M. Pellegrino & Jasmine A. Therrien & Dalton T. Ham & Peter C. Bartlett & Bogumil J. Karas & Gregory B. Gloor & David R. Edgell, 2019. "Efficient inter-species conjugative transfer of a CRISPR nuclease for targeted bacterial killing," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    5. Andrew D Fernandes & Jean M Macklaim & Thomas G Linn & Gregor Reid & Gregory B Gloor, 2013. "ANOVA-Like Differential Expression (ALDEx) Analysis for Mixed Population RNA-Seq," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-15, July.
    6. Mazhar Adli, 2018. "The CRISPR tool kit for genome editing and beyond," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    7. E. A. Moreb & M. D. Lynch, 2021. "Genome dependent Cas9/gRNA search time underlies sequence dependent gRNA activity," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    8. Dipankar Baisya & Adithya Ramesh & Cory Schwartz & Stefano Lonardi & Ian Wheeldon, 2022. "Genome-wide functional screens enable the prediction of high activity CRISPR-Cas9 and -Cas12a guides in Yarrowia lipolytica," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    9. Marie-Ève Dupuis & Manuela Villion & Alfonso H. Magadán & Sylvain Moineau, 2013. "CRISPR-Cas and restriction–modification systems are compatible and increase phage resistance," Nature Communications, Nature, vol. 4(1), pages 1-7, October.
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