A kinetic model predicts SpCas9 activity, improves off-target classification, and reveals the physical basis of targeting fidelity

Behrouz Eslami-Mossallam, Misha Klein, Constantijn V.D. Smagt, Koen V.D. Sanden, Stephen K. Jones, John A. Hawkins, Ilya J. Finkelstein, Martin Depken*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
6 Downloads (Pure)

Abstract

The S. pyogenes (Sp) Cas9 endonuclease is an important gene-editing tool. SpCas9 is directed to target sites based on complementarity to a complexed single-guide RNA (sgRNA). However, SpCas9-sgRNA also binds and cleaves genomic off-targets with only partial complementarity. To date, we lack the ability to predict cleavage and binding activity quantitatively, and rely on binary classification schemes to identify strong off-targets. We report a quantitative kinetic model that captures the SpCas9-mediated strand-replacement reaction in free-energy terms. The model predicts binding and cleavage activity as a function of time, target, and experimental conditions. Trained and validated on high-throughput bulk-biochemical data, our model predicts the intermediate R-loop state recently observed in single-molecule experiments, as well as the associated conversion rates. Finally, we show that our quantitative activity predictor can be reduced to a binary off-target classifier that outperforms the established state-of-the-art. Our approach is extensible, and can characterize any CRISPR-Cas nuclease – benchmarking natural and future high-fidelity variants against SpCas9; elucidating determinants of CRISPR fidelity; and revealing pathways to increased specificity and efficiency in engineered systems.

Original languageEnglish
Article number1367
Number of pages10
JournalNature Communications
Volume13
Issue number1
DOIs
Publication statusPublished - 2022

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