Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Scalable characterization of the PAM requirements of CRISPR–Cas enzymes using HT-PAMDA

Abstract

The continued expansion of the genome-editing toolbox necessitates methods to characterize important properties of CRISPR–Cas enzymes. One such property is the requirement for Cas proteins to recognize a protospacer-adjacent motif (PAM) in DNA target sites. The high-throughput PAM determination assay (HT-PAMDA) is a method that enables scalable characterization of the PAM preferences of different Cas proteins. Here, we provide a step-by-step protocol for the method, discuss experimental design considerations, and highlight how the method can be used to profile naturally occurring CRISPR–Cas9 enzymes, engineered derivatives with improved properties, orthologs of different classes (e.g., Cas12a), and even different platforms (e.g., base editors). A distinguishing feature of HT-PAMDA is that the enzymes are expressed in a cell type or organism of interest (e.g., mammalian cells), permitting scalable characterization and comparison of hundreds of enzymes in a relevant setting. HT-PAMDA does not require specialized equipment or expertise and is cost effective for multiplexed characterization of many enzymes. The protocol enables comprehensive PAM characterization of dozens or hundreds of Cas enzymes in parallel in <2 weeks.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: The role of the PAM in host defense and genome editing.
Fig. 2: Overview of HT-PAMDA workflow.
Fig. 3: Detailed experimental workflow for in vitro cleavage reactions and library preparation.
Fig. 4: Representations of Cas enzyme PAM preference.
Fig. 5: Expected results of an HT-PAMDA experiment.

Data availability

Source data for all figures are available in the NCBI Sequence Read Archive under BioProject ID PRJNA605711.

Code availability

Freely available open source code (under GNU General Public License v3.0) for HT-PAMDA analysis is available on the Kleinstiver Lab GitHub repository at https://github.com/kleinstiverlab/HT-PAMDA. The code in this protocol has been peer reviewed.

References

  1. 1.

    Makarova, K. S. et al. Evolutionary classification of CRISPR-Cas systems: a burst of class 2 and derived variants. Nat. Rev. Microbiol. 18, 67–83 (2020).

    CAS  Article  Google Scholar 

  2. 2.

    Anzalone, A. V., Koblan, L. W. & Liu, D. R. Genome editing with CRISPR–Cas nucleases, base editors, transposases and prime editors. Nat. Biotechnol. 38, 824–844 (2020).

    CAS  Article  Google Scholar 

  3. 3.

    Jinek, M. et al. A programmable dual-RNA–guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012).

    CAS  Article  Google Scholar 

  4. 4.

    Marraffini, L. A. & Sontheimer, E. J. Self vs. non-self discrimination during CRISPR RNA-directed immunity. Nature 463, 568–571 (2010).

    CAS  Article  Google Scholar 

  5. 5.

    Walton, R. T., Christie, K. A., Whittaker, M. N. & Kleinstiver, B. P. Unconstrained genome targeting with near-PAMless engineered CRISPR-Cas9 variants. Science 368, 290–296 (2020).

    CAS  Article  Google Scholar 

  6. 6.

    Gao, L. et al. Engineered Cpf1 variants with altered PAM specificities. Nat. Biotechnol. 35, 789–792 (2017).

    CAS  Article  Google Scholar 

  7. 7.

    Kleinstiver, B. P. et al. Engineered CRISPR-Cas12a variants with increased activities and improved targeting ranges for gene, epigenetic and base editing. Nat. Biotechnol. 37, 276–282 (2019).

    CAS  Article  Google Scholar 

  8. 8.

    Komor, A. C., Kim, Y. B., Packer, M. S., Zuris, J. A. & Liu, D. R. Programmable editing of a target base in genomic DNA without double-stranded DNA cleavage. Nature 533, 420–424 (2016).

    CAS  Article  Google Scholar 

  9. 9.

    Gaudelli, N. M. et al. Programmable base editing of A•T to G•C in genomic DNA without DNA cleavage. Nature 551, 464–471 (2017).

    CAS  Article  Google Scholar 

  10. 10.

    Biswas, A., Gagnon, J. N., Brouns, S. J. J., Fineran, P. C. & Brown, C. M. CRISPRTarget. RNA Biol. 10, 817–827 (2013).

    CAS  Article  Google Scholar 

  11. 11.

    Mendoza, B. J. & Trinh, C. T. In silico processing of the complete CRISPR-Cas spacer space for identification of PAM sequences. Biotechnol. J. 13, 1700595 (2018).

    Article  Google Scholar 

  12. 12.

    Karvelis, T., Gasiunas, G. & Siksnys, V. Methods for decoding Cas9 protospacer adjacent motif (PAM) sequences: a brief overview. Methods 121–122, 3–8 (2017).

    Article  Google Scholar 

  13. 13.

    Mojica, F. J. M., Díez-Villaseñor, C., García-Martínez, J. & Almendros, C. Short motif sequences determine the targets of the prokaryotic CRISPR defence system. Microbiology 155, 733–740 (2009).

    CAS  Article  Google Scholar 

  14. 14.

    Karvelis, T. et al. Rapid characterization of CRISPR-Cas9 protospacer adjacent motif sequence elements. Genome Biol. 16, 253 (2015).

    Article  Google Scholar 

  15. 15.

    Hirano, H. et al. Structure and engineering of Francisella novicida Cas9. Cell 164, 950–961 (2016).

    CAS  Article  Google Scholar 

  16. 16.

    Ran, F. A. et al. In vivo genome editing using Staphylococcus aureus Cas9. Nature 520, 186–191 (2015).

    CAS  Article  Google Scholar 

  17. 17.

    Hsu, P. D. et al. DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol. 31, 827–832 (2013).

    CAS  Article  Google Scholar 

  18. 18.

    Kleinstiver, B. P. et al. Engineered CRISPR-Cas9 nucleases with altered PAM specificities. Nature 523, 481–485 (2015).

    Article  Google Scholar 

  19. 19.

    Zetsche, B. et al. Cpf1 Is a single RNA-guided endonuclease of a class 2 CRISPR-Cas system. Cell 163, 759–771 (2015).

    CAS  Article  Google Scholar 

  20. 20.

    Kleinstiver, B. P. et al. Broadening the targeting range of Staphylococcus aureus CRISPR-Cas9 by modifying PAM recognition. Nat. Biotechnol. 33, 1293–1298 (2015).

    CAS  Article  Google Scholar 

  21. 21.

    Hu, J. H. et al. Evolved Cas9 variants with broad PAM compatibility and high DNA specificity. Nature 556, 57–63 (2018).

    CAS  Article  Google Scholar 

  22. 22.

    Leenay, R. T. et al. Identifying and visualizing functional PAM diversity across CRISPR-Cas systems. Mol. Cell 62, 137–147 (2016).

    CAS  Article  Google Scholar 

  23. 23.

    Marshall, R. et al. Rapid and scalable characterization of CRISPR technologies using an E. coli cell-free transcription-translation system. Mol. Cell 69, 146–157.e3 (2018).

    CAS  Article  Google Scholar 

  24. 24.

    Miller, S. M. et al. Continuous evolution of SpCas9 variants compatible with non-G PAMs. Nat. Biotechnol. 38, 471–481 (2020).

    CAS  Article  Google Scholar 

  25. 25.

    Kim, H. K. et al. High-throughput analysis of the activities of xCas9, SpCas9-NG and SpCas9 at matched and mismatched target sequences in human cells. Nat. Biomed. Eng. 4, 111–124 (2020).

    CAS  Article  Google Scholar 

  26. 26.

    Ondov, B. D., Bergman, N. H. & Phillippy, A. M. Interactive metagenomic visualization in a web browser. BMC Bioinformatics 12, 385 (2011).

    Article  Google Scholar 

  27. 27.

    Collias, D. et al. A positive, growth-based PAM screen identifies noncanonical motifs recognized by the S. pyogenes Cas9. Sci. Adv. 6, eabb4054 (2020).

    CAS  Article  Google Scholar 

  28. 28.

    Kim, D., Kim, D., Lee, G., Cho, S.-I. & Kim, J.-S. Genome-wide target specificity of CRISPR RNA-guided adenine base editors. Nat. Biotechnol. 37, 430–435 (2019).

    CAS  Article  Google Scholar 

  29. 29.

    Rohland, N. & Reich, D. Cost-effective, high-throughput DNA sequencing libraries for multiplexed target capture. Genome Res. 22, 939–946 (2012).

    CAS  Article  Google Scholar 

  30. 30.

    Tareen, A. & Kinney, J. B. Logomaker: beautiful sequence logos in Python. Bioinformatics 36, 2272–2274 (2020).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

We thank K. A. Christie for suggestions on the manuscript and A. A. Sousa for technical input on the development of the original PAMDA method. B.P.K. acknowledges support from NIH R00-CA218870, NIH P01-HL142494, a Career Development Award from the American Society of Gene & Cell Therapy, and the Margaret Q. Landenberger Research Foundation. J.K.J. acknowledges support from NIH R35 GM118158 and RM1 HG009490 for the development of the original PAMDA method.

Author information

Affiliations

Authors

Contributions

R.T.W. and B.P.K wrote the manuscript with input from all authors. R.T.W. developed the HT-PAMDA method in the B.P.K. laboratory; the original PAMDA method was developed by R.T.W. and B.P.K in the J.K.J. laboratory. All laboratory experiments for HT-PAMDA were performed by R.T.W. The original PAMDA software was developed by J.Y.H. and subsequently adapted for HT-PAMDA by R.T.W.

Corresponding author

Correspondence to Benjamin P. Kleinstiver.

Ethics declarations

Competing interests

All authors are inventors on patent applications filed by Partners HealthCare that describe gene-editing and/or epigenome-editing technologies; R.T.W. and B.P.K. are inventors on a patent application related to the HT-PAMDA method. B.P.K. is an advisor to Acrigen Biosciences and consults for Avectas Inc. and ElevateBio. J.K.J. has financial interests in Beam Therapeutics, Chroma Medicine (formerly known as YKY, Inc.), Editas Medicine, Excelsior Genomics, Pairwise Plants, Poseida Therapeutics, SeQure Dx, Inc., Transposagen Biopharmaceuticals, and Verve Therapeutics (formerly known as Endcadia). J.K.J.’s interests were reviewed and are managed by Massachusetts General Hospital and Partners HealthCare in accordance with their conflict of interest policies.

Additional information

Peer review information Nature Protocols thanks the anonymous reviewers for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Key reference using this protocol

Walton, R. T., Christie, K. A., Whittaker, M. N. & Kleinstiver, B. P. Science 368, 290–296 (2020): https://doi.org/10.1126/science.aba8853

Supplementary information

Supplementary Information

Supplementary Notes 1 and 2.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Walton, R.T., Hsu, J.Y., Joung, J.K. et al. Scalable characterization of the PAM requirements of CRISPR–Cas enzymes using HT-PAMDA. Nat Protoc 16, 1511–1547 (2021). https://doi.org/10.1038/s41596-020-00465-2

Download citation

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing