Genome Biology (Oct 2017)

Crossing enhanced and high fidelity SpCas9 nucleases to optimize specificity and cleavage

  • Péter István Kulcsár,
  • András Tálas,
  • Krisztina Huszár,
  • Zoltán Ligeti,
  • Eszter Tóth,
  • Nóra Weinhardt,
  • Elfrieda Fodor,
  • Ervin Welker

DOI
https://doi.org/10.1186/s13059-017-1318-8
Journal volume & issue
Vol. 18, no. 1
pp. 1 – 17

Abstract

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Abstract Background The propensity for off-target activity of Streptococcus pyogenes Cas9 (SpCas9) has been considerably decreased by rationally engineered variants with increased fidelity (eSpCas9; SpCas9-HF1). However, a subset of targets still generate considerable off-target effects. To deal specifically with these targets, we generated new “Highly enhanced Fidelity” nuclease variants (HeFSpCas9s) containing mutations from both eSpCas9 and SpCas9-HF1 and examined these improved nuclease variants side by side to decipher the factors that affect their specificities and to determine the optimal nuclease for applications sensitive to off-target effects. Results These three increased-fidelity nucleases can routinely be used only with perfectly matching 20-nucleotide-long spacers, a matching 5′ G extension being more detrimental to their activities than a mismatching one. HeFSpCas9 exhibit substantially improved specificity for those targets for which eSpCas9 and SpCas9-HF1 have higher off-target propensity. The targets can also be ranked by their cleavability and off-target effects manifested by the increased fidelity nucleases. Furthermore, we show that the mutations in these variants may diminish the cleavage, but not the DNA-binding, of SpCas9s. Conclusions No single nuclease variant shows generally superior fidelity; instead, for highest specificity cleavage, each target needs to be matched with an appropriate high-fidelity nuclease. We provide here a framework for generating new nuclease variants for targets that currently have no matching optimal nuclease, and offer a simple means for identifying the optimal nuclease for targets in the absence of accurate target-ranking prediction tools.

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