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Continuous directed evolution of a compact CjCas9 variant with broad PAM compatibility

Nature Chemical Biology volume 20, pages 333–343 (2024)Cite this article

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Abstract

CRISPR–Cas9 genome engineering is a powerful technology for correcting genetic diseases. However, the targeting range of Cas9 proteins is limited by their requirement for a protospacer adjacent motif (PAM), and in vivo delivery is challenging due to their large size. Here, we use phage-assisted continuous directed evolution to broaden the PAM compatibility of Campylobacter jejuni Cas9 (CjCas9), the smallest Cas9 ortholog characterized to date. The identified variant, termed evoCjCas9, primarily recognizes N4AH and N5HA PAM sequences, which occur tenfold more frequently in the genome than the canonical N3VRYAC PAM site. Moreover, evoCjCas9 exhibits higher nuclease activity than wild-type CjCas9 on canonical PAMs, with editing rates comparable to commonly used PAM-relaxed SpCas9 variants. Combined with deaminases or reverse transcriptases, evoCjCas9 enables robust base and prime editing, with the small size of evoCjCas9 base editors allowing for tissue-specific installation of A-to-G or C-to-T transition mutations from single adeno-associated virus vector systems.

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Fig. 1: PACE and PANCE to broaden the PAM compatibility of CjCas9.
Fig. 2: Characterization of the PAM compatibility of evoCjCas9.
Fig. 3: Indel formation rates of evoCjCas9 compared to CjCas9 and other commonly used RNA-guided endonucleases.
Fig. 4: Base and prime editing with CjCas9 and evoCjCas9.
Fig. 5: In vivo genome editing with compact evoCjCas9 ABE and CBE.

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Data availability

Plasmids and sequences of evoCjCas9 constructs are available on Addgene: evoCjCas9 (194059), evoCjCas9–ABE8e (194060), evoCjCas9–BE4max (194061), evoCjCas9–eAID (194062), evoCjCas9–PEmax∆RnH (194063), evoCjCas9–TadCDd (202558), LentiGuide_CjCas9-Puro (202564), AAV-P3-evoCjCas9-ABE8e (202559), AAV-hSyn-evoCjCas9-ABE8e (202561), AAV-P3-evoCjCas9-eAID (202562) and AAV-P3-evoCjCas9-TadCDd (202563). Measured editing rates are provided in Supplementary Data 3–7. DNA-sequencing data are available on NCBI Sequence Read Archive (PRJNA893560). Source data are provided with this paper.

Code availability

Custom code used in the data analysis presented here is available as Supplementary Code 1 and on GitHub (https://github.com/Schwank-Lab/evoCjCas9).

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Acknowledgements

We thank the Functional Genomics Center Zurich for technical support and access to instruments at the University of Zurich and ETH Zurich; the Genome Engineering and Measurement Lab at the University of Zurich and ETH Zurich and S. Kreutzer for preparing CHANGE-seq libraries; the mRNA platform at UZH/USZ and S. Pascolo, J. Frei and C. Wyss for production and purification of RNAs; the viral vector facility of UZH and J.-C. Paterna and M. Rauch for production of AAVs; J. Häberle and N. Rimann for support with blood sample analysis; S. Melkonyan for assistance in data visualization; and L. Villiger and members of the Schwank lab for discussions. We thank M. Pacesa for comments on the manuscript. This work was supported by the Swiss National Science Foundation (SNSF) grant numbers 310030_185293 and 310030_214936 (to G.S.) and 31003A_182567 (to M.J.), Novartis Foundation for Medical-Biological Research number FN20-0000000203 (to D.B.), SNSF Spark fellowship number 196287 (to D.B.), the URPP Itinerare (to G.S. and D.B.) and the ETH PhD fellowship (to L.S. and K.F.M.). M.J. is an International Research Scholar of the Howard Hughes Medical Institute and Vallee Scholar of the Bert L & N Kuggie Vallee Foundation.

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Authors and Affiliations

  1. Institute of Pharmacology and Toxicology, University of Zurich, Zurich, Switzerland

    Lukas Schmidheini, Nicolas Mathis, Kim Fabiano Marquart, Tanja Rothgangl, Lucas Kissling, Desirée Böck, Jingrui Priscilla Wang & Gerald Schwank

  2. Institute of Molecular Health Sciences, ETH Zurich, Zurich, Switzerland

    Lukas Schmidheini & Kim Fabiano Marquart

  3. Department of Biochemistry, University of Zurich, Zurich, Switzerland

    Christelle Chanez & Martin Jinek

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Contributions

L.S. and G.S. designed the study and wrote the manuscript. L.S., K.F.M., N.M., T.R., C.C., D.B. and J.P.W. performed and analyzed in vitro experiments. L.S., T.R., L.K. and K.F.M. performed and analyzed in vivo experiments. C.C. and M.J. purified proteins and provided field-specific expertise. L.S., N.M., K.F.M., T.R., D.B. and C.C. prepared figures. All authors reviewed the manuscript.

Corresponding author

Correspondence to Gerald Schwank.

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Competing interests

L.S. and G.S. have filed a patent application based on evolved CjCas9 variants (European Patent Application No. 23175382.3). All other authors have no competing interests.

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Nature Chemical Biology thanks Feng Gu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Contribution of consensus mutations in CjCas9 on PAM relaxation.

HT-PAMDA characterization of enCjCas9 (top) with introduced PAM relaxing mutations (bottom) illustrating their PAM preference at PAM positions 5 to 8. The log10 rate constant represents the mean of two replicates against two distinct spacer sequences.

Source data

Extended Data Fig. 2 Indel formation with CjCas9 and evoCjCas9 on endogenous target sites.

a,b, Indel frequencies of CjCas9 and evoCjCas9 on 14 non-canonical and 10 canonical PAM sites in HEK293T cells with selection harvested 9 days (a) or without selection 4 days (b) post transfection. Bars (a, b) represent mean with error bars representing standard error of the mean of three independent biological replicates performed on separate days (n = 3). Individual data points as black dots.

Source data

Extended Data Fig. 3 Indel formation rates with CjCas9 and evoCjCas9 at target sites with different PAMs.

Mean indel frequency in self-targeting libraries on canonical (a) and non-canonical (b) PAM sites. Bars represent mean with error bars representing standard error of the mean, with individual data points (n) of biological triplicates shown as black dots (a) and indicated above error bars (a, b). The in vitro PAMDA assay (Fig. 2a) revealed few motifs recognized by CjCas9 that lie outside of the simplified N3VRYAC motif (for example N3MACAN), albeit with low efficiency. We define sequences that fall outside of N3VRYAC as non-canonical motifs for the purpose of simplification.

Source data

Extended Data Fig. 4 Prime editing rates with CjCas9 and evoCjCas9 on endogenous target sites.

Prime editing and corresponding unintended editing frequencies of CjCas9 and evoCjCas9-PE∆RnH on 3 canonical and 7 non-canonical target sites in HEK293T cells. Bars represent mean with error bars representing standard error of the mean. Individual data points of biological replicates (n = 3) as black dots.

Source data

Extended Data Fig. 5 Cytosine base editing with CjCas9 and evoCjCas9 on sites in the Pcsk9 locus.

Editing frequency (C-to-T) with eAID or TadCDd CBEs with one or two C-terminal UGI domains in Neuro-2a cells. Bars represent mean with error bars representing standard error of the mean of three independent biological replicates performed on separate days (n = 3), unless otherwise noted. Individual data points as black dots.

Source data

Extended Data Fig. 6 In vivo genome editing with the evoCjCas9-TadCDd cytosine BE.

Observed editing at the targeted Pcsk9 site with an AAV construct containing the evoCjCas9-TadCDd base editor. Bars represent mean with error bars representing standard error of the mean, with data points shown as black dots representing independent samples.

Source data

Supplementary information

Supplementary Information

Supplementary Figs. 1–10 and Table 1, legends for Supplementary Data 1–8 and Supplementary Code 1.

Reporting Summary

Supplementary Data 1

Consensus reads of UMI-linked nanopore sequencing.

Supplementary Data 2

PAM preference of all assessed CjCas9 variants derived with HT-PAMDA.

Supplementary Data 3

Self-targeting library sequences with indel and editing rates generated with CjCas9, evoCjCas9 and BE constructs.

Supplementary Data 4

Self-targeting library sequences with editing rates generated with CjCas9 and evoCjCas9 on target-matched PAM library.

Supplementary Data 5

Self-targeting library sequences with indel rates generated with CjCas9, SaCas9, SauriCas9, SpCas9, Nme2Cas9, CasMINI and TnpB and their PAM-relaxed variants.

Supplementary Data 6

Self-targeting library sequences containing on- and off-target sequences, with indel rates generated by CjCas9, enCjCas9 and evoCjCas9.

Supplementary Data 7

Self-targeting library sequences with editing rates generated with CjCas9–PE∆RnH and evoCjCas9–PE∆RnH in HEK293T and K562 cells.

Supplementary Data 8

Primer sequences used in cloning.

Supplementary Code 1

Collection of scripts used to evaluate Nanopore and NGS sequencing data.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 4

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Extended Data Fig. 1–6

Statistical source data.

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Schmidheini, L., Mathis, N., Marquart, K.F. et al. Continuous directed evolution of a compact CjCas9 variant with broad PAM compatibility. Nat Chem Biol 20, 333–343 (2024). https://doi.org/10.1038/s41589-023-01427-x

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