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.

  • Article
  • Published:

Targeted genome editing in human repopulating haematopoietic stem cells

Abstract

Targeted genome editing by artificial nucleases has brought the goal of site-specific transgene integration and gene correction within the reach of gene therapy. However, its application to long-term repopulating haematopoietic stem cells (HSCs) has remained elusive. Here we show that poor permissiveness to gene transfer and limited proficiency of the homology-directed DNA repair pathway constrain gene targeting in human HSCs. By tailoring delivery platforms and culture conditions we overcame these barriers and provide stringent evidence of targeted integration in human HSCs by long-term multilineage repopulation of transplanted mice. We demonstrate the therapeutic potential of our strategy by targeting a corrective complementary DNA into the IL2RG gene of HSCs from healthy donors and a subject with X-linked severe combined immunodeficiency (SCID-X1). Gene-edited HSCs sustained normal haematopoiesis and gave rise to functional lymphoid cells that possess a selective growth advantage over those carrying disruptive IL2RG mutations. These results open up new avenues for treating SCID-X1 and other diseases.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Targeted integration into AAVS1 or IL2RG in umbilical cord blood CD34+ cells.
Figure 2: Transplantation of gene-targeted CD34+ cells in NSG mice.
Figure 3: Gene targeting in primitive versus committed progenitors.
Figure 4: Functional reconstitution of IL2RG in the lymphoid progeny of HSCs.
Figure 5: Targeted integration and IL2RG gene correction in bone-marrow-derived CD34+ cells from healthy donors and a subject with SCID-X1.

Similar content being viewed by others

References

  1. Mukherjee, S. & Thrasher, A. J. Gene therapy for PIDs: progress, pitfalls and prospects. Gene 525, 174–181 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Aiuti, A. et al. Lentiviral hematopoietic stem cell gene therapy in patients with Wiskott-Aldrich syndrome. Science 341, 1233151 (2013)

    Article  PubMed  PubMed Central  Google Scholar 

  3. Cavazzana-Calvo, M. et al. Transfusion independence and HMGA2 activation after gene therapy of human β-thalassaemia. Nature 467, 318–322 (2010)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  4. Cartier, N. et al. Hematopoietic stem cell gene therapy with a lentiviral vector in X-linked adrenoleukodystrophy. Science 326, 818–823 (2009)

    Article  ADS  CAS  PubMed  Google Scholar 

  5. Biffi, A. et al. Lentiviral hematopoietic stem cell gene therapy benefits metachromatic leukodystrophy. Science 341, 1233158 (2013)

    Article  PubMed  Google Scholar 

  6. Naldini, L. Ex vivo gene transfer and correction for cell-based therapies. Nature Rev. Genet. 12, 301–315 (2011)

    Article  CAS  PubMed  Google Scholar 

  7. Braun, C. J. et al. Gene therapy for Wiskott-Aldrich syndrome–long-term efficacy and genotoxicity. Science Transl. Med. 6, 227ra33 (2014)

    Article  Google Scholar 

  8. Cavazza, A., Moiani, A. & Mavilio, F. Mechanisms of retroviral integration and mutagenesis. Hum. Gene Ther. 24, 119–131 (2013)

    Article  CAS  PubMed  Google Scholar 

  9. Woods, N. B., Bottero, V., Schmidt, M., von Kalle, C. & Verma, I. M. Gene therapy: therapeutic gene causing lymphoma. Nature 440, 1123 (2006)

    Article  ADS  CAS  PubMed  Google Scholar 

  10. Gentner, B. et al. Identification of hematopoietic stem cell-specific miRNAs enables gene therapy of globoid cell leukodystrophy. Sci. Transl. Med. 2, 58ra84 (2010)

    Article  CAS  PubMed  Google Scholar 

  11. Urnov, F. D., Rebar, E. J., Holmes, M. C., Zhang, H. S. & Gregory, P. D. Genome editing with engineered zinc finger nucleases. Natl. Rev. 11, 636–646 (2010)

    Article  CAS  Google Scholar 

  12. Joung, J. K. & Sander, J. D. TALENs: a widely applicable technology for targeted genome editing. Nature Rev. Mol. Cell Biol. 14, 49–55 (2013)

    Article  CAS  Google Scholar 

  13. Sander, J. D. & Joung, J. K. CRISPR-Cas systems for editing, regulating and targeting genomes. Nature Biotechnol. 32, 347–355 (2014)

    Article  CAS  Google Scholar 

  14. Lombardo, A. et al. Gene editing in human stem cells using zinc finger nucleases and integrase-defective lentiviral vector delivery. Nature Biotechnol. 25, 1298–1306 (2007)

    Article  CAS  Google Scholar 

  15. Urnov, F. D. et al. Highly efficient endogenous human gene correction using designed zinc-finger nucleases. Nature 435, 646–651 (2005)

    Article  ADS  CAS  PubMed  Google Scholar 

  16. Gabriel, R. et al. An unbiased genome-wide analysis of zinc-finger nuclease specificity. Nature Biotechnol. 29, 816–823 (2011)

    Article  CAS  Google Scholar 

  17. Mussolino, C. et al. A novel TALE nuclease scaffold enables high genome editing activity in combination with low toxicity. Nucleic Acids Res. 39, 9283–9293 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ciccia, A. & Elledge, S. J. The DNA damage response: making it safe to play with knives. Mol. Cell 40, 179–204 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Tebas, P. et al. Gene editing of CCR5 in autologous CD4 T cells of persons infected with HIV. N. Engl. J. Med. 370, 901–910 (2014)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Holt, N. et al. Human hematopoietic stem/progenitor cells modified by zinc-finger nucleases targeted to CCR5 control HIV-1 in vivo. Nature Biotechnol. 28, 839–847 (2010)

    Article  CAS  Google Scholar 

  21. Provasi, E. et al. Editing T cell specificity towards leukemia by zinc finger nucleases and lentiviral gene transfer. Nature Med. 18, 807–815 (2012)

    Article  CAS  PubMed  Google Scholar 

  22. Lombardo, A. et al. Site-specific integration and tailoring of cassette design for sustainable gene transfer. Nature Methods 8, 861–869 (2011)

    Article  CAS  PubMed  Google Scholar 

  23. Zou, J. et al. Oxidase-deficient neutrophils from X-linked chronic granulomatous disease iPS cells: functional correction by zinc finger nuclease-mediated safe harbor targeting. Blood 117, 5561–5572 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Li, H. et al. In vivo genome editing restores haemostasis in a mouse model of haemophilia. Nature 475, 217–221 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Doulatov, S., Notta, F., Laurenti, E. & Dick, J. E. Hematopoiesis: a human perspective. Cell Stem Cell 10, 120–136 (2012)

    Article  CAS  PubMed  Google Scholar 

  26. Boitano, A. E. et al. Aryl hydrocarbon receptor antagonists promote the expansion of human hematopoietic stem cells. Science 329, 1345–1348 (2010)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  27. North, T. E. et al. Prostaglandin E2 regulates vertebrate haematopoietic stem cell homeostasis. Nature 447, 1007–1011 (2007)

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  28. Goessling, W. et al. Prostaglandin E2 enhances human cord blood stem cell xenotransplants and shows long-term safety in preclinical nonhuman primate transplant models. Cell Stem Cell 8, 445–458 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Escobar, G. et al. Genetic engineering of hematopoiesis for targeted IFN-alpha delivery inhibits breast cancer progression. Sci. Transl. Med. 6, 217ra213 (2014)

    Article  MathSciNet  Google Scholar 

  30. Milyavsky, M. et al. A distinctive DNA damage response in human hematopoietic stem cells reveals an apoptosis-independent role for p53 in self-renewal. Cell Stem Cell 7, 186–197 (2010)

    Article  CAS  PubMed  Google Scholar 

  31. Mohrin, M. et al. Hematopoietic stem cell quiescence promotes error-prone DNA repair and mutagenesis. Cell Stem Cell 7, 174–185 (2010)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Mátrai, J. et al. Hepatocyte-targeted expression by integrase-defective lentiviral vectors induces antigen-specific tolerance in mice with low genotoxic risk. Hepatology 53, 1696–1707 (2011)

    Article  PubMed  Google Scholar 

  33. Hockemeyer, D. et al. Efficient targeting of expressed and silent genes in human ESCs and iPSCs using zinc-finger nucleases. Nature Biotechnol. 27, 851–857 (2009)

    Article  CAS  Google Scholar 

  34. Miller, J. C. et al. An improved zinc-finger nuclease architecture for highly specific genome editing. Nature Biotechnol. 25, 778–785 (2007)

    Article  CAS  Google Scholar 

  35. Akatsuka, Y., Martin, E. G., Madonik, A., Barsoukov, A. A. & Hansen, J. A. Rapid screening of T-cell receptor (TCR) variable gene usage by multiplex PCR: application for assessment of clonal composition. Tissue Antigens 53, 122–134 (1999)

    Article  CAS  PubMed  Google Scholar 

  36. Wu, C. J. et al. Reconstitution of T-cell receptor repertoire diversity following T-cell depleted allogeneic bone marrow transplantation is related to hematopoietic chimerism. Blood 95, 352–359 (2000)

    CAS  PubMed  Google Scholar 

  37. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25, 1754–1760 (2009)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Li, H. et al. The sequence alignment/map format and SAMtools. Bioinformatics 25, 2078–2079 (2009)

    PubMed  PubMed Central  Google Scholar 

  39. Barnett, D. W., Garrison, E. K., Quinlan, A. R., Stromberg, M. P. & Marth, G. T. BamTools: a C++ API and toolkit for analyzing and managing BAM files. Bioinformatics 27, 1691–1692 (2011)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Larkin, M. A. et al. Clustal W and Clustal X version 2.0. Bioinformatics 23, 2947–2948 (2007)

    Article  CAS  PubMed  Google Scholar 

  41. Harris, D. T., Badowski, M., Balamurugan, A. & Yang, O. O. Long-term human immune system reconstitution in non-obese diabetic (NOD)-Rag (-)-γ chain (-) (NRG) mice is similar but not identical to the original stem cell donor. Clin. Exp. Immunol. 174, 402–413 (2013)

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Gattinoni, L. et al. A human memory T cell subset with stem cell-like properties. Nature Med. 17, 1290–1297 (2011)

    Article  CAS  PubMed  Google Scholar 

  43. Cieri, N. et al. IL-7 and IL-15 instruct the generation of human memory stem T cells from naive precursors. Blood 121, 573–584 (2013)

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank D. Weissman for advice on mRNA production and the whole Naldini laboratory for discussion, F. Benedicenti for help with MiSeq sequencing, L. Sergi Sergi, T. Plati, V. Valtolina, B. Camisa and A. Ranghetti for technical help. SR1 was provided by T. Boitano and M. Cooke under an MTA with the Genomics Institute of the Novartis Research Foundation. This work was supported by grants to L.N. from Telethon (TIGET grant D2) EU (FP7 222878 PERSIST, FP7 601958 SUPERSIST, ERC Advanced Grant 249845 TARGETINGGENETHERAPY) and the Italian Ministry of Health.

Author information

Authors and Affiliations

Authors

Contributions

P.G. designed experiments, performed research, interpreted data and wrote the manuscript. G.S. and G.E. performed research and interpreted data. T.D.T. performed mRNA production. C.F. characterized the corrective cDNA. A.C. and E.M. performed bioinformatics analysis of ZFN specificity. R.M. and D.M. developed the NSG human tumour rejection model. C.B. contributed to the T-cell studies. M.v.d.B. provided SCID-X1 patient cells. M.C.H. and P.D.G. provided ZFNs, interpreted data and edited the manuscript. B.G. set up culture conditions for HSC maintenance. A.L. and L.N. designed and supervised research, interpreted data and wrote the manuscript. L.N. coordinated the study. G.S. and G.E. contributed equally to this work. A.L. and L.N. share senior authorship.

Corresponding author

Correspondence to Luigi Naldini.

Ethics declarations

Competing interests

M.C.H. and P.D.G. are employees of Sangamo BioSciences Inc. P.G., A.L., L.N., M.C.H. and P.D.G. filed a patent application on the protocol for targeted integration in human HSPC.

Extended data figures and tables

Extended Data Figure 1 Optimization of gene targeting protocol in CD34+ cells.

We optimized the delivery platform, dose and timing of ZFNs and HDR donor template administration. a, Performance of different gene delivery platforms. Cord blood (CB) CD34+ cells were pre-stimulated with early acting cytokines for 24 h and transduced with GFP-encoding IDLV (MOI 5 × 102) or adenoviral vector serotype 5/35 (MOI 5 × 103), or electroporated with GFP-expressing mRNA (500 μg ml−1) or plasmid DNA (25 μg ml−1). The cells were analysed by flow cytometry at the indicated days after the procedure. Top: representative density plots of GFP expression 24 h post treatment. SSC, side scatter. Bottom: kinetics of transgene expression measured as a percentage of GFP+ cells (left) and relative GFP fluorescence intensity (RFI, measured as the ratio between the mean fluorescence intensity of the treated cells at each time point to the untreated cells) in arbitrary units (right). UT, untreated cells. mRNA electroporation outperformed all approaches tested in terms of frequency of transfected cells and protein expression level. Note that although IDLV infects the majority of cells in these conditions its expression is constrained by the unintegrated nature32. Because mRNA transfection drives a robust but short-lived spike of expression, it appeared best suited for ZFN delivery, allowing proficient activity of the nucleases at the genomic target site while avoiding prolonged exposure. b, Top: schematic representation (not in scale) of a plasmid DNA template used for in vitro mRNA transcription with the T7 promoter, the Kozak sequence and the XbaI restriction enzyme used for the plasmid linearization depicted. The protein domains of a ZFN are shown within the open reading frame (ORF). NLS, nuclear localization signal; ZFP, zinc finger protein; FokI, FokI nuclease domain. Middle: representative denaturing gel electrophoresis of in vitro transcribed mRNAs encoding for the pair of ZFNs specific for AAVS1, before (−) and after enzymatic polyadenylation (pA). The ZFN mRNAs were produced either as two separated transcripts (ZFN-L and ZFN-R) or as a single construct coding for both ZFNs linked by a Tav.2A self-cleavage peptide sequence (ZFN-L.2A.ZFN-R; bottom left). Bottom right: cord blood CD34+ cells were electroporated either with the two separate transcripts or with the single mRNA co-expressing both ZFNs. ZFN activity was measured on treated cells as percentage of NHEJ detected at the ZFN target site by Cel1 assay 10 days after electroporation. c, Dose–response for AAVS1 targeting ZFN mRNAs in CD34+ cells. Cord blood CD34+ cells were transduced with integrase-defective lentiviral vector (IDLV)14 bearing homology to the AAVS1 locus and expressing GFP, and then electroporated with the indicated escalating doses of AAVS1 ZFN mRNAs. ZFN activity was scored by measuring the extent of NHEJ-mediated repair at their genomic target site, and HDR was scored by the frequency of GFP+ cells obtained in liquid culture. Left: NHEJ measured by Cel1 assay at day 10 after electroporation for the indicated dose of mRNA. Means ± s.e.m. (n = 3). Right: percentages of GFP+ cells by flow cytometry 3 days after treatment. The percentages of viable cells (indicated on top of the histogram) were calculated as percentages of 7AAD negative cells gated on singlets. A dose-dependent increase in the percentage of NHEJ and GFP+ cells was observed for the first three mRNA doses, whereas the highest dose caused a significant reduction in the number of viable cells, and a reduction in the efficiency of gene targeting. Based on these data, we selected the dose of 175 µg ml−1 RNA to perform all further experiments. d, Choice of delivery platform for the HDR donor template. Cord blood CD34+ cells were either transduced with the AAVS1 donor IDLV and electroporated with the cognate ZFNs mRNAs, or co-electroporated with AAVS1 donor plasmid DNA and ZFN mRNAs. Left: cell viability measured by flow cytometry 3 days after electroporation, comparing untreated cells (UT) and gene-targeted cells using IDLV or plasmid as donor templates. ****P < 0.0001 (one-way ANOVA with Bonferroni’s multiple comparison post-test). Right: percentage of GFP+ cells using either donor templates. Means ± s.e.m. (UT, n = 3; IDLV, n = 18; plasmid, n = 10). *P < 0.05 (unpaired t-test). IDLV infection outperformed plasmid DNA electroporation in terms of the frequency of GFP+ cells and cell viability, consistent with our previous findings in other primary cell types14,22. e, Schedule optimization for ZFNs and donor template delivery. After one day of pre-stimulation, cord blood CD34+ cells were first transduced with the AAVS1 donor IDLV and then electroporated at the indicated hours post-infection with ZFN mRNAs (left) or, on the contrary, first electroporated with ZFN mRNAs and then transduced with IDLV (right). The time lines of the experiments are shown on top of the histograms. The percentages of GFP+ cells measured by flow cytometry 3 days after treatment and NHEJ measured by Cel1 assay 10 days after treatment are shown on bottom left. Bottom right: the percentage of GFP+ cells is expressed as fold to the percentage achieved in the same experiment with the best strategy on the left. The highest frequency of GFP+ cells was obtained by combining IDLV-based donor template delivery 24 h before ZFN mRNA electroporation. Sequential exposure to the two delivery platforms avoids competition for cell entry and minimizes mutual interference, probably due to activation of innate responses to exogenous nucleic acids or the timing of peak ZFN expression relative to IDLV reverse transcription and nuclear import.

Extended Data Figure 2 Impact on cell viability and specificity of integration in CD34+ cells treated for targeted integration.

a, Percentage of GFP+ cells measured in liquid culture 3 days after treatment as in Fig. 1b for targeted integration into AAVS1 or IL2RG and for the corresponding GFP+ colonies counted in CFC assays 2 weeks after plating. Means ± s.e.m. (n = 7 cord blood donors). ns, not significant (unpaired t-test). b, Representative bright-field and fluorescence microscopy images of GFP+ erythroid and myeloid colonies. Scale bar, 0.5 mm. ce, The impact of the gene-targeting procedure on the viability, proliferation and clonogenic output of the CD34+ cells was analysed. c, Representative growth curves of CD34+ cells treated for targeted integration or transduced with IDLV only or untreated (UT). d, Apoptosis analysis performed 24 h after treatment on cells in liquid culture and e, number of CFCs plated one day after the indicated treatments. Means ± s.e.m.; n = 2 or 3, respectively. Overall, there was a transient reduction in viable cell number 24 h after electroporation, also observed in CFC yield, which resulted from the combined exposure to electroporation, ZFN mRNA and IDLV. However, the surviving cells grew with similar kinetics as the untreated controls in liquid culture and gave rise to similar proportions of myeloid and erythroid colonies. f, g, Targeting specificity of integration. f, Southern blot (top) and PCR (bottom) analyses for targeted integration into IL2RG on iPSCs obtained by reprogramming GFP+ cells from Fig. 1c. UT, untreated cells. g, Genomic DNA from GFP+ colonies was analysed by PCR for targeted integration into AAVS1 or IL2RG. The gels show the PCR amplicons for either the 5′ or 3′ HDR integration junction at the genomic target site and a control locus (CCR5). The percentages of colonies positive for targeted integration by PCR are reported in Fig. 1d.

Extended Data Figure 3 Investigating lower gene-targeting efficiency in the more primitive cells.

a, Gating strategy used to identify subpopulations of cord blood cells according to expression of CD90, CD133 and CD34 surface markers. b, After 24 h of pre-stimulation, CD34+ cells were electroporated with 175 μg of GFP mRNA (the selected dose of a ZFN mRNA from Extended Data Fig. 1). Flow cytometry analysis was performed 2 days later using the gating strategy shown in Fig. 3a. Bars represent the percentage of GFP+ cells (plotted on left axis) while the line shows the level of transgene expression (plotted on the right axis as MFI, measured in arbitrary units). Means ± s.e.m. (n = 16 on 6 cord blood donors). c, CD34+ cells treated for targeted integration were sorted by FACS one day after electroporation according to the gating strategy shown in Fig. 3a. The sorted populations were sampled at the indicated times and levels of NHEJ at the ZFN target site (AAVS1) were determined by Cel1 assay (n = 3). d, Apoptosis analysis performed one day after electroporation on CD34+ cells transduced with IDLV and electroporated with ZFN mRNAs. Percentages of live (7AAD, AnnexinV), early apoptotic (7AAD, AnnexinV+), late apoptotic (7AAD+, AnnexinV+) and necrotic (7AAD+, AnnexinV) cells. Means ± s.e.m. (n = 5 on 4 cord blood donors). e, Representative growth curves of CD34+ cells cultured in the presence or not of SR1 and treated (TI) or not (UT) with the protocol described in Fig. 1b. Note that the TI and UT growth curves are reproduced from Extended Data Fig. 1c. Addition of SR1 to the culture did not change the proliferation rate of the cells. Because SR1 did not increase the total number of cells but the percentage of more primitive cells in culture (Fig. 3c), the absolute number of primitive cells is larger in cultures containing SR1.

Extended Data Figure 4 Long-term multilineage engraftment of gene-targeted CD34+ cells in primary and secondary NSG mice.

a, Percentages of human cells in the indicated organs of NSG mice 15–23 weeks after transplantation with CD34+ cells treated with the improved protocols from Fig. 3a with or without SR1. b, Percentage of the indicated lineages within human cells in peripheral blood of mice 14 weeks post-transplant. Means ± s.e.m. (48 h, n = 8; 48 h SR1, n = 11; 48 h PGE2, n = 3; 48 h PGE2 SR1, n = 6). Overall, the addition of SR1 and PGE2 to the in vitro culture did not significantly affect the in vivo differentiation of treated cells. Notably, the increased human engraftment achieved with the optimized culture conditions (as illustrated in Fig. 3g) correlates with increased T-cell output. c, Multi-lineage GFP marking in individual NSG mice transplanted with CD34+ cells treated with the indicated protocols for targeted integration. Percentages of GFP+ cells were calculated within the CD45+ Lin+ populations (represented with different data-point shapes) in different organs (represented by different data-point colours). The analysis was performed on peripheral blood 14 weeks after transplantation and on spleen and bone marrow at the end of the experiments. Only mice displaying ≥0.1% GFP+ cells are represented in the graph (n = 2 independent experiments). Note that when using the improved protocols for targeted integration GFP+ cells are found in multiple lineages in all mice. d, Analysis of the primitive human compartment in the bone marrow of transplanted mice from c. Top: gating strategy used to define progenitors (CD34+ CD38+), multilymphoid progenitors (MLPs; CD34+ CD38 CD90low/− CD45RA+), multipotent progenitors (MPPs; CD34+ CD38 CD90 CD45RA) and HSCs (CD34+ CD38 CD90+ CD45RA). Bottom: percentages of GFP+ cells within the defined populations. Means ± s.e.m. (48 h SR1, n = 4; 48 h PGE2, n = 3; 48 h PGE2 SR1, n = 5). e, DNA from total bone marrow cells of transplanted mice was analysed by PCR to determine TI into IL2RG. Each column represents one mouse. The schematics show the different sets of primers used to detect on-target insertions mediated by HDR or NHEJ (the latter shown with the vector in sense or reverse orientation with respect to IL2RG). Whereas evidence of HDR-mediated insertion of the cassette was retrieved from all mice assayed, there was also indication of some NHEJ-mediated integration of the donor IDLV. Trapping of IDLV at sites of NHEJ has been previously reported16. We note that our strategy could be adjusted to also exploit this type of insertion to drive transgene expression24 and potentially increase the overall efficiency of gene correction (see schematic in Fig. 4a). In such case, one should target insertion within an intron of the gene so that the splice acceptor site of the corrective cDNA is next in line for processing with the splice donor site of the upstream endogenous exon and any intervening sequence can be spliced out from the chimaeric transcript leading to reconstitution of a functional open reading frame (provided that the insertion occurred in the same orientation as gene transcription). An additional benefit of targeting an intronic sequence would be to spare exons from disruption by NHEJ, although this is of minor concern when dealing with already defective alleles. f, 15–23 weeks after the primary transplant, human CD34+ cells were purified from the bone marrow of 11 mice from c (mice were chosen among those best engrafted with GFP+ cells in the different CD34+ cell treatment groups) and transplanted (one mouse to one mouse) into 7–11-week-old NSG mice. Secondary recipient mice were monitored for engraftment of human CD45+ and GFP+ cells at 8 and 12 weeks post-transplant in peripheral blood, and on bone marrow at the end of the experiments. Top left: percentages of human cells in the indicated organs. Top right: percentages of the indicated lineages within the human cells. B cells were defined by expression of CD19 and myeloid cells were defined by expression of CD13 in peripheral blood or CD33 in bone marrow. Dots represent individual mice. Bottom left: percentages of GFP+ cells within the human graft in the indicated organs and (bottom right) within the indicated lineages, as on top. g, Human cells from the bone marrow of the top 2 engrafted secondary recipient mice from f were analysed by PCR for targeted integration into IL2RG.

Extended Data Figure 5 Expansion of lymphoid cells in the transplanted mice after tumour challenge.

a, Left: percentage of human cells in the peripheral blood of mice transplanted with male CD34+ cells treated as indicated for targeted integration into IL2RG. Analyses performed at the time of tumour injection (top panel) and 3 weeks later (bottom panel). Right: percentages of T and NK cells (CD3+ and CD16/56+ cells, respectively) measured within the human CD45+ cells in peripheral blood. b, Fold change in the absolute number of the indicated lineages in peripheral blood 3 weeks after tumour challenge. Means ± s.e.m. (24 h SR1, n = 5; 48 h SR1, n = 6; 48 h, n = 5). c, Counts of GFP+ and GFP T and NK cells in the peripheral blood of transplanted NSG mice before (top) and 3 weeks after (bottom) injection of the MDA-MB 231 tumour cell line engineered to express human IL-7, IL-15 and GM-CSF. Fold changes calculated from these values are plotted in Fig. 4e. d, Tumour growth in mice transplanted (n = 16) or not (n = 3) with treated CD34+ cells. ****P < 0.0001 (two-way ANOVA).

Extended Data Figure 6 Generation of T cells with substantial Vβ TCR diversity from the engrafted gene-targeted HSPCs.

a, Analysis of TCR Vβ repertoire performed on PBMCs from a healthy donor. The histogram shows the frequency distribution of the different complementarity-determining region 3 (CDR3) lengths identified within the indicated Vβ families. As expected from a highly polyclonal TCR repertoire, all Vβ families display a Gaussian distribution of the CDR3 lengths. b, Frequency distribution of the different CDR3 regions measured as in a for the GFP+ (left) and GFP (right) T cells harvested from the transplanted C1, C5 and A4 mice from Extended Data Fig. 5c. c, Complexity score36 assigned to each Vβ family for the samples shown in b. The sum of the scores for all the family is plotted in Fig. 4g. Note that all the samples analysed display similar TCR Vβ repertoire distributions, constrained for some families and more polyclonal for others, as might be expected for human T cells developed in haematochimaeric mice41, and that no significant differences are observed between the GFP+ and GFP cells. This finding indicates that the rate of gene targeting achieved in the transplanted stem/progenitor cells does not detectably limit the generation of a polyclonal and functional T-cell repertoire in vivo.

Extended Data Figure 7 Functional and phenotypic characterization of IL2RG-edited T cells harvested from transplanted NSG mice.

a, Graph showing the viability of GFP+ and GFP T cells harvested from the transplanted NSG mice (from Extended Data Fig. 6) or of T cells from peripheral blood of healthy donor (HD T cells), cultured in the presence (+ cyto) or absence (no cyto) of human IL-7 and IL-15. b, Left: representative density plots of GFP+ and GFP T cells harvested from mice, stained for CD8 (left) and CD4 (right). Right: GFP+ and GFP T cells harvested from mice were activated ex vivo with beads coated with anti-CD3 and anti-CD28-specific antibodies, and cultured with IL-7 and IL-15. CD4 and CD8 composition of GFP+ and GFP cells, measured during ex vivo culture, is shown (n = 3). c, Surface phenotype of CD4 and CD8 T cells from b and HD T cells at day 19 after stimulation. A representative plot (left) and histograms with medians + s.e.m. (right) are shown. T stem memory cells (TSCM) are defined as CD62L+ CD45RA+ (refs 42, 43), T central memory (TCM) as CD62L+ CD45RA, T effector memory (TEM) as CD62L CD45RA and terminal effectors (TEMRA) as CD62L CD45RA+. d, Production of IL-2 and IFN-γ by GFP+ or GFP T cells as in b, and by HD T cells after 6 h stimulation with PMA+ionomycin. A representative plot (left) and percentages of IL-2+ and IFN-γ+ cells are shown. P = ns (unpaired t-test). e, IFN-γ Elispot assay showing the frequencies of IFN-γ-producing cells from b challenged with the MDA-MB 231 tumour cell line at different effector to target ratios. PHA stimulation was used as positive control.

Extended Data Figure 8 Functionality of γ-chain-dependent signalling pathway in IL2RG-gene-edited T cells.

GFP+ or GFP T cells from the transplanted mice (as in Extended Data Figs 6 and 7) or T cells from the peripheral blood of healthy donor (HD T-cells) were exposed to the indicated doses of γ-chain-related cytokines. The phosphorylation levels of STAT5 on Y694 (pSTAT5), STAT3 on Y705 (pSTAT3) and AKT on S473 (pAKT) were measured at the indicated time points by flow cytometry analyses. a, Top: representative plots showing pSTAT5, pSTAT3 and pAKT. Each time point of analysis is labelled by a different concentration of the intracellular dye PBSE. Bottom: fold changes in the levels of pSTAT5, pSTAT3 and pAKT relative to the time 0 of stimulation with the indicated maximal doses of IL-15 and IL-2 (n = 3). Phosphorylation of STAT3 was used as a specificity control. P = ns (two-way ANOVA). b, Table showing the fold changes in the levels of pSTAT5 which are graphically represented in Fig. 4k. Statistics in the first column indicate significant change during time. ****P < 0.0001, ***P < 0.001 (two-way ANOVA). c, Heat map representing fold changes in pAKT and pSTAT3 levels after the indicated time of exposure (min) to increasing amounts of IL-2 or IL-15. P = ns between GFP+ and GFP cells (two-way ANOVA).

Extended Data Figure 9 Indel quantification on the intended ‘on’ target and candidate ‘off’ target genomic sites of IL2RG ZFNs.

a, Indel quantification expressed as percentage of the total number of reads for each sample and target. The untreated (UT) sample F is shown in the rightmost column. 0 values underlie undetected events due to low sequencing read coverage (see Supplementary Information). b, Table of P-values obtained comparing the number of indels for each target and its untreated control sample (Fisher’s exact test for contingency data). P-values allowed distinguishing real accumulation of indels (labelled with a green arrow close to the P-value) from background noise (marked with a yellow horizontal bar). Only SCARB1 and SLC31A1 show indels in samples A, B and D at a frequency significantly higher than the untreated sample. c, Indel frequency distribution along the amplified genomic sequences of the positive control IL2RG and the two loci that showed a low but significant off target activity, SCARB1 and SLC31A1. The x axis represents the amplified sequence in base pairs while the y axis shows for each base the percentage of reads that reported indels for each sample after noise subtraction (see Supplementary Information). Note that indels mainly occur in the central region of the amplicon, corresponding to the spacer between the genomic sequences expected to be bound by the ZFNs. d, Representative sequence alignments of retrieved indels in IL2RG (sample A), SCARB1 (from samples A and B) and SLC31A1 (from samples A and D) focusing the analysis on the region bearing identity or homology to the intended ZFN target sequence. For each sequence type the relative frequency of retrieval in the sample is reported as a percentage. As shown in c indels mostly occur in the central spacer region between the 2 ZFN binding sites (underlined).

Extended Data Figure 10 IL2RG gene correction in CD34+ cells from the bone marrow of a genotyped subject with SCID-X1.

a, Blood cell counts in the peripheral blood and bone marrow of a SCID-X1 male child carrying the R289X mutation in the IL2RG gene (see Supplementary Information) and showing virtual absence of T and NK cells. Asterisks in the left-most table indicate values calculated within the leukocyte gate. b, Left: representative density plots showing the cellular composition of a bone marrow harvest from a healthy donor (top) and the subject with SCID-X1 (bottom) after purification of nucleated cells (bone-marrow-derived mononuclear cells, BMMCs). Myeloid cells are stained for CD15 and CD33, B cells for CD19, T cells for CD3 and NK cells for CD16. Right: γ-chain expression within the indicated cell populations gated from the plots shown on the left. As expected from the missense R289X mutation, the γ-chain protein is expressed on the cell surface but it is not functional, as indicated by the absence of T and NK cells in the patient. In Fig. 5 we show normal expression of the γ-chain protein in the myeloid cell progeny of three gene-corrected CFCs from the patient cells (gene correction was proven by evidence of targeted integration in the only IL2RG allele of this male individual in the clonal CFC progeny and by the expression of the fusion transcript bearing the corrective cDNA). These data indicate normal γ-chain expression from the reconstituted allele in the edited patient cells. c, Bright-field and fluorescence microscopy images of the three GFP+ myeloid colonies obtained after IL2RG gene correction of SCID-X1 cells.

Supplementary information

Supplementary Information

This file contains Supplementary Text, Supplementary Figures, Supplementary Tables and a list of primers. (PDF 806 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Genovese, P., Schiroli, G., Escobar, G. et al. Targeted genome editing in human repopulating haematopoietic stem cells. Nature 510, 235–240 (2014). https://doi.org/10.1038/nature13420

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature13420

This article is cited by

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