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Evolution of CRISPR-associated endonucleases as inferred from resurrected proteins

Nature Microbiology volume 8, pages 77–90 (2023)Cite this article

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Abstract

Clustered regularly interspaced short palindromic repeats (CRISPR)-associated Cas9 is an effector protein that targets invading DNA and plays a major role in the prokaryotic adaptive immune system. Although Streptococcus pyogenes CRISPR–Cas9 has been widely studied and repurposed for applications including genome editing, its origin and evolution are poorly understood. Here, we investigate the evolution of Cas9 from resurrected ancient nucleases (anCas) in extinct firmicutes species that last lived 2.6 billion years before the present. We demonstrate that these ancient forms were much more flexible in their guide RNA and protospacer-adjacent motif requirements compared with modern-day Cas9 enzymes. Furthermore, anCas portrays a gradual palaeoenzymatic adaptation from nickase to double-strand break activity, exhibits high levels of activity with both single-stranded DNA and single-stranded RNA targets and is capable of editing activity in human cells. Prediction and characterization of anCas with a resurrected protein approach uncovers an evolutionary trajectory leading to functionally flexible ancient enzymes.

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Fig. 1: Phylogenetic and structural analysis of anCas endonucleases.
Fig. 2: Activity of anCas endonucleases on a supercoiled DNA substrate.
Fig. 3: PAM determination of anCas.
Fig. 4: HT-PAMDA assay.
Fig. 5: sgRNA test and nuclease activity of anCas on single-stranded substrates.
Fig. 6: Activity of anCas endonucleases in human HEK293T cells.

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Data availability

We have made available sequencing data. Other data supporting the findings of this study are available from the corresponding authors upon reasonable request. Plasmids for gene editing in human cells are available through Addgene (Supplementary Table 14 and https://www.addgene.org/Raul_Perez-Jimenez/). Plasmids for HT-PAMDA experiments are available through Addgene (Supplementary Tables 8–10 and www.addgene.org/Benjamin_Kleinstiver/). Sequencing data for PAM determination and gene editing experiments will be made available through the National Center for Biotechnology Information Sequence Read Archive (NCBI SRA) under BioProject ID PRJNA832610. Sequencing data for HT-PAMDA experiments will be made available through NCBI SRA under BioProject ID PRJNA832159. Source data are provided with this paper.

Code availability

Python script used for structure analysis can be found at spectrumBar.py and code used for sequence analysis is available via Zenodo at https://zenodo.org/record/3710516#.Y1plwHbMKUl.

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Acknowledgements

This work has been supported by grant nos. PID2019-109087RB-I00 (to R.P.-J.) and RTI2018-101223-B-I00 and PID2021-127644OB-I00 (to L.M.) from the Spanish Ministry of Science and Innovation. This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 964764 (to R.P.-J.). The content presented in this document represents the views of the authors, and the European Commission has no liability in respect to the content. We acknowledge financial support from the Spanish Foundation for the Promotion of Research of Amyotrophic Lateral Sclerosis. A.F. acknowledges Spanish Center for Biomedical Network Research on Rare Diseases (CIBERE) intramural funds (no. ER19P5AC756/2021). F.J.M.M. acknowledges research support by Conselleria d’Educació, Investigació, Cultura i Esport from Generalitat Valenciana, research project nos. PROMETEO/2017/129 and PROMETEO/2021/057. M.M. acknowledges funding from CIBERER (grant no. ER19P5AC728/2021). The work has received funding from the Regional Government of Madrid (grant no. B2017/BMD3721 to M.A.M.-P.) and from Instituto de Salud Carlos III, cofounded with the European Regional Development Fund ‘A way to make Europe’ within the National Plans for Scientific and Technical Research and Innovation 2017–2020 and 2021–2024 (nos. PI17/1659, PI20/0429 and IMP/00009; to M.A.M.-P. B.P.K. was supported by an MGH ECOR Howard M. Goodman Award and NIH P01 HL142494. We thank H. Stutzman for assistance with cloning plasmids, and Z. Herbert and M. Berkeley from the Molecular Biology Core Facilities at the Dana-Farber Cancer Institute for assistance with NextSeq sequencing.

Author information

Author notes

  1. These authors contributed equally: Borja Alonso-Lerma, Ylenia Jabalera.

Authors and Affiliations

  1. CIC nanoGUNE BRTA, San Sebastian, Spain

    Borja Alonso-Lerma, Ylenia Jabalera, Sara Samperio, Ane Quesada-Ganuza, Antonio Reifs & Raul Perez-Jimenez

  2. Servicio de Genética, Hospital Universitario Ramón y Cajal, IRYCIS and Centro de Investigaciones Biomédicas en Red de Enfermedades Raras, Madrid, Spain

    Matias Morin, Sergio Fernández-Peñalver, Lucia Soletto & Miguel A. Moreno-Pelayo

  3. Department of Molecular and Cellular Biology, National Centre for Biotechnology and Centre for Biomedical Network Research on Rare Diseases, Madrid, Spain

    Almudena Fernandez, Yolanda Benitez & Lluis Montoliu

  4. Center for Genomic Medicine and Department of Pathology, Massachusetts General Hospital, Boston, MA, USA

    Logan T. Hille, Rachel A. Silverstein & Benjamin P. Kleinstiver

  5. PhD Program in Biological and Biomedical Sciences, Harvard University, Boston, MA, USA

    Logan T. Hille & Rachel A. Silverstein

  6. INGEMM, Hospital Universitario La Paz, Madrid, Spain

    Yolanda Benitez

  7. Laboratorio de Estudios Cristalográficos, IACT, Armilla, Spain

    Jose A. Gavira

  8. Interuniversity Institute of Bioinformatics in Brussels, ULB-VUB, Brussels, Belgium

    Adrian Diaz & Wim Vranken

  9. Structural Biology Brussels, Vrije Universiteit Brussel, Brussels, Belgium

    Adrian Diaz & Wim Vranken

  10. Structural Biology Research Centre, VIB, Brussels, Belgium

    Wim Vranken

  11. Integra Therapeutics S.L., Barcelona, Spain

    Avencia Sanchez-Mejias & Marc Güell

  12. Department of Medicine and Life Sciences, Universitat Pompeu Fabra, Barcelona, Spain

    Marc Güell

  13. Dpto. Fisiología, Genética y Microbiología and Instituto Multidisciplinar para el Estudio del Medio ‘Ramón Margalef’, Universidad de Alicante, Alicante, Spain

    Francisco J. M. Mojica

  14. Department of Pathology, Harvard Medical School, Boston, MA, USA

    Benjamin P. Kleinstiver

  15. Ikerbasque Foundation for Science, Bilbao, Spain

    Raul Perez-Jimenez

Authors
  1. Borja Alonso-Lerma
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  2. Ylenia Jabalera
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Contributions

R.P.-J. conceived the project. R.P.-J., B.A.-L., B.P.K., A.S.-M., M.G., F.J.M.M., M.A.M.-P. and L.M. designed research and planned experiments. R.P.-J. performed phylogenetic analysis and ancestral sequence reconstruction. B.A.-L., Y.J. and S.S. cloned and expressed proteins and performed in vitro experiments. L.T.H. performed HT-PAMDA experiments. L.T.H., R.A.S. and B.P.K. analysed HT-PAMDA data. B.A.-L., Y.J,. S.S., M.M., A.F., Y.B., S.F.-P., L.S., A.S.-M., M.G., M.A.M.-P. and L.M. performed functional validation of anCas in mammalian cells, sequencing experiments and bioinformatic analysis. B.A.-L., Y.J., R.P.-J., J.A.G., A.R., A.D. and W.V. designed, analysed and represented structural data. All authors participated in discussions and provided ideas for the work. R.P.-J., F.J.M.M., M.A.M.-P. and L.M. wrote the original paper, and all authors revised and edited the manuscript.

Corresponding author

Correspondence to Raul Perez-Jimenez.

Ethics declarations

Competing interests

R.P.-J. and B.A.-L. are co-inventors on a patent application (European Patent Application EP21382474) filed by CIC nanoGUNE and licensed to Integra Therapeutics S.L. relating to work in this article. A.S.-M. and M.G. are cofounders of Integra Therapeutics S.L. B.P.K. is an inventor on patents and/or patent applications filed by Mass General Brigham that describe genome engineering technologies, including the HT-PAMDA method (WO2021151065). B.P.K. is a consultant for EcoR1 Capital and is an advisor to Acrigen Biosciences, Life Edit Therapeutics and Prime Medicine. The remaining authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Posterior probability distribution for each inferred residue of all ancestral anCas endonucleases.

The residue with the highest posterior probability is assigned at each position. The posterior average probability of each anCas is indicated in brackets. In all cases, posterior probability average is close to 1 except for FCA anCas which shows an average value of 0.74.

Extended Data Fig. 2 Alignment of the amino acid sequences from PAM interacting (PI) domain of anCas and SpCas9.

Percentage of identity of the different anCas sequences with respect to SpCas9.

Extended Data Fig. 3 List of important mutations and domain organization of anCas compared to SpCas9.

Mutations of the main residues involved in PAM recognition are marked in blue. These alterations suggest possible differences in PAM recognition abilities in FCA anCas and possibly in BCA anCas. Bottom figure depicts domain organization and structural alignment of SpCas9-FCA and SpCas9-PDCA anCas. Ancestral anCas are grey colored and SpCas9 colored by domains.

Extended Data Fig. 4 Structural predictions of anCas and SpCas9 by AlphaFold2.

Structures are colored by pLDDT score according to the color bar.

Extended Data Fig. 5 Activity of FCA anCas H838A endonuclease on a supercoiled DNA substrate.

(a) In vitro cleavage assay for anCas FCA H838A on a 4007 bp substrate at different reaction times showing nicked and linear fractions. (b) Quantification of total cleavage fraction at different reaction times and exponential fits (lines). (c) Quantification of fraction nicked at different times. (d) Quantification of DSB cleavage. Single-exponential fits were used to obtain kcleave and maximum fraction cleaved (amplitude). Values reported as mean, where n = 2.

Extended Data Fig. 6 PAM determination of anCas enzymes.

(a) Example of in vitro cleavage assay to obtain 278 bp fragment for NGS analysis. (b) Weblogo of the different PAM recognized by anCas and SpCas9. (c) Heatmaps illustrating the total reads for each of the possible 256 NNNN PAMs, analyzed from NGS of the 278 bp cleaved DNA fragments from panel a. (d) In vitro cleavage assay using the PAM sequence TCC.

Extended Data Fig. 7 HT-PAMDA determined PAM profiles of younger anCas enzymes.

PAM profiles of anCas enzymes and SpCas9 as determined by HT-PAMDA. Rate constants corresponding to Cas cleavage activity on each of the 256 NNNN PAMs are illustrated as mean log10 values of cleavage reactions against two unique spacer sequences. For comparison, the SpCas9 is re-plotted from Fig. 4.

Extended Data Fig. 8 Trans-activity of FCA anCas, BCA anCas and SpCas9 on M13 phage ssDNA.

Nonspecific M13 ssDNA cleavage with sgRNA and complementary (or not) 85nt ssDNA activator with no sequence homology to M13 circular ssDNA. FCA anCas can cleave the ssDNA substrate in the presence of the activator, whereas BCA anCAs and SpCas9 do not cleave the same substrate.

Extended Data Fig. 9 Analysis of the in vivo activity of anCas variants.

Alignments generated by Jalview program of the wild-type and the most frequent edited alleles (indels) detected by Mosaic Finder in (a) OCA2 and (b) TYR genes after NHEJ cell repair in HEK 293T cells. Heatmaps are shown underneath the alignments highlighting the frequencies of the top-7 most frequent alleles generated after cleavage and repair with SpCas9, PDCA, PCA, SCA and BCA anCas, once normalized with respect to the total number of indels for each Cas. The guide, the PAM and the DSB theoretical site are marked in the figure. For the mutation nomenclature of each allele, we consider the first nucleotide of the PAM as +1. Numbers within the allele sequences represent the length of insertions or deletion in the exact location indicated by the first figure. Example: -4Ins1, insertion of 1 nucleotide four bases upstream the PAM.

Extended Data Fig. 10 Traffic Light Reporter cleavage assay targeting gene TLR.

The relative NHEJ frequency is estimated by the number of RFP-positive cells and is normalized to SpCas9. Bars represent the average value of two independent experiments indicated by the black dots.

Supplementary information

Supplementary Information

Supplementary Figs. 1–5, Tables 1–16, Notes 1–4 and references.

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Source data

Source Data Fig. 1

Amino acid sequences of ancestral anCas.

Source Data Fig. 4

HT-PAMDA data summary.

Source Data Fig. 5

Unprocessed gels.

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Alonso-Lerma, B., Jabalera, Y., Samperio, S. et al. Evolution of CRISPR-associated endonucleases as inferred from resurrected proteins. Nat Microbiol 8, 77–90 (2023). https://doi.org/10.1038/s41564-022-01265-y

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