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A highly efficient transgene knock-in technology in clinically relevant cell types

Nature Biotechnology volume 42, pages 458–469 (2024)Cite this article

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Abstract

Inefficient knock-in of transgene cargos limits the potential of cell-based medicines. In this study, we used a CRISPR nuclease that targets a site within an exon of an essential gene and designed a cargo template so that correct knock-in would retain essential gene function while also integrating the transgene(s) of interest. Cells with non-productive insertions and deletions would undergo negative selection. This technology, called SLEEK (SeLection by Essential-gene Exon Knock-in), achieved knock-in efficiencies of more than 90% in clinically relevant cell types without impacting long-term viability or expansion. SLEEK knock-in rates in T cells are more efficient than state-of-the-art TRAC knock-in with AAV6 and surpass more than 90% efficiency even with non-viral DNA cargos. As a clinical application, natural killer cells generated from induced pluripotent stem cells containing SLEEK knock-in of CD16 and mbIL-15 show substantially improved tumor killing and persistence in vivo.

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Fig. 1: SLEEK achieves the highest transgene cargo KI efficiency currently in the field.
Fig. 2: SLEEK generates superior KI efficiencies to current strategies across cell types.
Fig. 3: SLEEK enables multiplex editing and near-homogeneous KI of functional cargos in primary T cells and NK cells.
Fig. 4: SLEEK DKI of CD16 and mbIL-15 into iPSCs led to efficient ADCC killing of tumor cells and increased persistence with differentiated iNK cells.
Fig. 5: SLEEK DKI of CD16 and mbIL-15 led to potent iNK-mediated tumor killing in vivo.

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Data availability

Source data are provided with this paper. Unprocessed flow cytometry and microscopy images for Figs. 1–5 are provided as Source Data File 1, and numerical values for plotted data in Figs. 1–5 are provided as Source Data File 2. DNA constructs, gRNAs, primers, ddPCR probes, Digenome-Seq results and rhAmp-Seq panel of potential off-target candidate sites are listed in the Supplementary Table. All numerical data values used to generate figures in the Supplementary Information can be found in Supplementary Data. Raw flow cytometry plots and representative gating strategies, as well as uncropped microscopy and gel images, are provided in the Supplementary Information under Supplementary Notes. High-throughput sequencing data have been deposited in the National Center for Biotechnology Informationʼs Sequence Read Archive database (accession code PRJNA947757) and can be found at http://www.ncbi.nlm.nih.gov/bioproject/947757 (ref. 62). Source data are provided with this paper.

Code availability

Custom code used to analyze Digenome-Seq data is available at the Editas Medicine GitHub page at https://github.com/editasmedicine/digenomitas. Custom code used to identify candidate in silico off-target sites is also available at the Editas Medicine GitHub (https://github.com/editasmedicine/calitas).

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Acknowledgements

We would like to thank additional members of the Editas Computational Biology, Informatics and Sequencing groups for generation and pipeline analysis of sequencing data. We thank R. Naines, C. Wang, J. Yao and H. An for providing primary cells for studies. We would like to thank J. Getgano, K. Gareau, E. Goncz, S. Zhang, J. Moon, K. Tsiounis and J. Schafer for support in the development of key assays and protocols. We would like to thank members of BlueRock Therapeutics LP for their support and collaboration related to engineering and culturing iPSCs. We would like to thank A. Dee for paper preparation support. Several graphics in the figures (cells in Fig. 1a, cells in Fig. 2a,h, cells in Fig. 3a,d,g, mouse schematic in Fig. 5a, cells in Supplementary Fig. 5c, cells in Supplementary Fig. 9c,e, cells in Supplementary Fig. 10a, cells in Supplementary Fig. 11a–c, cells in Supplementary Fig. 12c, cells in Supplementary Fig. 13a and cells in Supplementary Fig. 14a,b) were created with BioRender. We would like to thank Porterhouse Medical for graphic design support.

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  1. These authors contributed equally: Alexander G. Allen, Samia Q. Khan, Carrie M. Margulies, Ramya Viswanathan.

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  1. Editas Medicine, Cambridge, MA, USA

    Alexander G. Allen, Samia Q. Khan, Carrie M. Margulies, Ramya Viswanathan, Swarali Lele, Laura Blaha, Sean N. Scott, Kaitlyn M. Izzo, Alexandra Gerew, Rithu Pattali, Nadire R. Cochran, Carl S. Holland, Amy H. Zhao, Stephen E. Sherman, Michael C. Jaskolka, Meng Wu, Aaron C. Wilson, Xiaoqi Sun, Dawn M. Ciulla, Deric Zhang, Jacqueline D. Nelson, Peisheng Zhang, Patrizia Mazzucato, Yan Huang, Georgia Giannoukos, Eugenio Marco, Michael Nehil, John A. Follit, Kai-Hsin Chang, Mark S. Shearman, Christopher J. Wilson & John A. Zuris

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Contributions

A.G.A, S.Q.K., C.M.M., R.V., S.L., S.N.S., K.M.I., A.G., R.P., N.R.C., C.S.H., A.H.Z., S.E.S., M.C.J., M.W., A.C.W., D.M.C., D.Z., Y.H., J.D.N., P.Z. and P.M. performed experiments and analyzed data. L.B., X.S., J.A.F. and J.A.Z. analyzed data. A.G.A., S.Q.K., C.M.M., R.V., S.L., L.B., S.E.S., M.C.J., X.S., G.G., E.M., M.N., J.A.F., K.Z., K.-H.C., M.S.S., C.J.W. and J.A.Z. wrote the paper.

Corresponding author

Correspondence to John A. Zuris.

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Competing interests

All authors were employees and shareholders of Editas Medicine at the time the work was performed. J.A.Z. and C.M.M. are inventors on patent WO2021226151A2 that has been filed by Editas Medicine relating to this work.

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Nature Biotechnology thanks Fyodor Urnov and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–18 as well as raw images of supplementary figure flow cytometry plots, microscopy images and western blot uncropped gels.

Reporting Summary

Supplementary Table 1

List of plasmid constructs, gRNAs, ddPCR and RT–qPCR primers, Digenome-Seq and rHampSeq specificity data.

Supplementary Data 1

Numerical data used to generate graphed figures in the Supplementary Information file.

Source data

Source Data Fig. 1, Fig. 2, Fig. 3 and Fig. 5

Contains all raw flow cytometry plots, microscopy images, IVIS images and histology images from main text figures.

Source Data Fig. 1, Fig. 2, Fig. 3, Fig. 4, Fig. 5

Contains raw numerical data for all graphs in main text figures.

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Allen, A.G., Khan, S.Q., Margulies, C.M. et al. A highly efficient transgene knock-in technology in clinically relevant cell types. Nat Biotechnol 42, 458–469 (2024). https://doi.org/10.1038/s41587-023-01779-8

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