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Therapeutic base editing of human hematopoietic stem cells

Nature Medicine volume 26, pages 535–541 (2020)Cite this article

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Abstract

Base editing by nucleotide deaminases linked to programmable DNA-binding proteins represents a promising approach to permanently remedy blood disorders, although its application in engrafting hematopoietic stem cells (HSCs) remains unexplored. In this study, we purified A3A (N57Q)-BE3 base editor for ribonucleoprotein (RNP) electroporation of human-peripheral-blood-mobilized CD34+ hematopoietic stem and progenitor cells (HSPCs). We observed frequent on-target cytosine base edits at the BCL11A erythroid enhancer at +58 with few indels. Fetal hemoglobin (HbF) induction in erythroid progeny after base editing or nuclease editing was similar. A single therapeutic base edit of the BCL11A enhancer prevented sickling and ameliorated globin chain imbalance in erythroid progeny from sickle cell disease and β-thalassemia patient-derived HSPCs, respectively. Moreover, efficient multiplex editing could be achieved with combined disruption of the BCL11A erythroid enhancer and correction of the HBB −28A>G promoter mutation. Finally, base edits could be produced in multilineage-repopulating self-renewing human HSCs with high frequency as assayed in primary and secondary recipient animals resulting in potent HbF induction in vivo. Together, these results demonstrate the potential of RNP base editing of human HSPCs as a feasible alternative to nuclease editing for HSC-targeted therapeutic genome modification.

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Fig. 1: Base editing the +58 BCL11A erythroid enhancer in human CD34+ HSPCs.
Fig. 2: Therapeutic base editing in SCD patient CD34+ HSPCs.
Fig. 3: Therapeutic and multiplex base editing in β-thalassemia patient CD34+ HSPCs.
Fig. 4: Efficient C>T base editing in HSCs.

Data availability

All requests for raw and analyzed data and materials are promptly reviewed by the Boston Children’s Hospital to verify if the request is subject to any intellectual property or confidentiality obligations. Any data and materials that can be shared will be released via a material transfer agreement. All raw and analyzed sequencing data can be found at the NCBI Sequence Read Archive (PRJNA604208).

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Acknowledgements

We appreciate useful discussions with D. Liu, M. Weiss, S. Tsai, C. Brendel and M. Peters. We thank R. Mathieu and the Boston Children’s Hospital flow cytometry staff for technical assistance, Z. Herbert and the Dana-Farber Cancer Institute molecular biology core for deep sequencing assistance and C. Brugnara, E. Esrick, D. Williams and the Boston Children’s Hospital clinical staff for assistance with β-thalassemia and SCD patient samples. We are grateful to the patients for their participation. L.P. was supported by the National Human Genome Research Institute (grant R00HG008399); S.A.W. was supported by the National Institute of Allergy and Infectious Diseases (grant R01AI117839) and the National Institute of General Medical Sciences (grant R01GM115911); and J.K.J. was supported by the National Institute of General Medical Sciences (grant R35 GM118158), the National Human Genome Research Institute (grant RM1 HG009490), the St. Jude Children’s Research Hospital Collaborative Research Consortium and the Desmond and Ann Heathwood MGH Research Scholar Award. D.E.B. was supported by the National Heart, Lung, and Blood Institute (grant P01HL053749), the St. Jude Children’s Research Hospital Collaborative Research Consortium and the Burroughs Wellcome Fund.

Author information

Author notes

  1. These authors contributed equally: Jing Zeng, Yuxuan Wu, Chunyan Ren.

Authors and Affiliations

  1. Division of Hematology/Oncology, Boston Children’s Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Broad Institute, Department of Pediatrics, Harvard Medical School, Boston, MA, USA

    Jing Zeng, Yuxuan Wu, Chunyan Ren, Jasmine Bonanno, Anne H. Shen, Devlin Shea, Qiuming Yao, Rachel Kim & Daniel E. Bauer

  2. Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China

    Yuxuan Wu

  3. Molecular Pathology Unit, Center for Cancer Research, and Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA

    Jason M. Gehrke, Kendell Clement, Qiuming Yao, Luca Pinello & J. Keith Joung

  4. Department of Molecular, Cell and Cancer Biology, Li Weibo Institute for Rare Diseases Research, University of Massachusetts Medical School, Worcester, MA, USA

    Kevin Luk & Scot A. Wolfe

  5. Department of Chemistry, Wellesley College, Wellesley, MA, USA

    Rachel Kim

  6. Department of Laboratory Medicine, Boston Children’s Hospital, Department of Pathology, Harvard Medical School, Boston, MA, USA

    John P. Manis

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

    Luca Pinello & J. Keith Joung

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  1. Jing Zeng
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Contributions

J.Z., Y.W., C.R., J.B. and D.S. performed experiments. J.M.G and J.K.J designed A3A (N57Q)-BE3 and shared constructs before publication. J.K.J. advised on off-target analysis experiments. C.R. and R.K. purified A3A (N57Q)-BE3 protein. A.H.S., K.C., Q.Y. and L.P. performed computational analyses. J.P.M. provided plerixafor-mobilized SCD HSPCs. K.L. and S.A.W. provided 3×NLS-SpCas9. J.Z. and D.E.B. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to Daniel E. Bauer.

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Competing interests

The authors declare competing financial interests; details are available in the online version of the paper. J.K.J. has financial interests in Beam Therapeutics, Editas Medicine, Excelsior Genomics, Pairwise Plants, Poseida Therapeutics, Transposagen Biopharmaceuticals and Verve Therapeutics (f/k/a 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. J.K.J. is a member of the Board of Directors of the American Society of Gene and Cell Therapy. J.M.G. and J.K.J. are co-inventors on a patent application describing the A3A (N57Q) BE3 variant used in this study. J.K.J. is also a co-inventor on various patents and patent applications that describe gene editing, base editing and epigenetic editing technologies. J.Z., Y.W., and D.E.B. are co-inventors on various patents related to therapeutic gene editing technologies.

Additional information

Peer review information Kate Gao was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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

Extended data

Extended Data Fig. 1 Purification of A3A (N57Q)-BE3 protein.

a, Purification strategy and profiles. A3A (N57Q)-BE3 protein was purified using nickel affinity, mono S cation exchange, and size exclusion columns. Desired fractions from 100% imidazole elution (nickel column tube 20–24), salt gradient elution (tube 25–35), and size exclusion (tube 11–15) were collected respectively. b, Protein purity validation. Protein purity was determined using SDS-PAGE and gel staining. Total clear protein lysate and ion exchange (IEX) samples and fractions were loaded on SDS-PAGE gel and stained with GelCode Blue to check the purity. After immobilized metal affinity chromatography and IEX, the protein purity was estimated to be more than 99%. The protein purification was performed once.

Source data

Extended Data Fig. 2 Base editing the +58 BCL11A erythroid enhancer in human healthy donor CD34+ HSPCs.

a, Heatmaps show the base edit frequencies following A3A (N57Q)-BE3:sgRNA-1617, sgRNA-1619 and sgRNA-1620 editing by deep sequence analysis. b, Correlation of C6 and C8 base edit frequencies following dose-response A3A (N57Q)-BE3:sgRNA-1620 editing. Data are analyzed using two-tailed nonparametric Spearman correlation. The Spearman correlation coefficient (r) is shown, P = 0.003, n = 3 independent donors. c, Correlation of base edit frequencies and HbF levels following dose-response A3A (N57Q)-BE3:sgRNA-1620 editing. Data are analyzed using two-tailed nonparametric Spearman correlation. The Spearman correlation coefficient (r) is shown, P = 0.003, n = 3 independent donors. d, Overall base editing frequencies at sgRNA-1620 C6 position in input CD34+ HSPCs following 1 cycle of electroporation (1 EP) and 2 cycles of electroporation (2 EP) by performing the second cycle of electroporation 24 h after first. Data are plotted as grand median, n = 2 healthy donors for 1 EP, n = 3 healthy donors for 2 EP. e, Viability of CD34+ HSPCs immediately prior to transplantation with 1 or 2 cycles of electroporation (EP) relative to mock. Each dot indicates an independent healthy donor. Data are plotted as grand median, n = 3 for mock, n = 2 healthy donors for 1 EP, n = 3 healthy donors for 2 EP.

Extended Data Fig. 3 Therapeutic and multiplex base editing in β-thalassemia patient CD34+HSPCs.

a, Heatmaps show the base edit frequencies of BCL11A enhancer (left two panels) and HBB promoter (right two panels) following single and multiplex editing. b, Left, Distribution of erythroid colonies by editing of BCL11A enhancer and HBB promoter following A3A (N57Q)-BE3:sgRNA-1620 + sgRNA-HBB-28 multiplex base editing. Right, The number and fraction of colonies based on alleles at BCL11A enhancer and HBB promoter. c, Hemoglobin measured by HPLC for A3A (N57Q)-BE3:sgRNA-1620 + sgRNA-HBB-28 multiplex base editing by number of edited loci (left) or by combination of alleles (right) in edited erythroid colonies.

Extended Data Fig. 4 Efficient base editing following HSPC xenotransplantation.

a, Overall frequencies of C base edits at sgRNA-1620 C6 position in sorted immunophenotypically enriched HSC or HPC populations by deep sequence analysis. n = 5 independent donors and analyzed using paired two-tailed Student’s t-test, * P = 0.03 compared with HPC. b, Overall frequencies of C base edits at sgRNA-1620 C6 position in Pyronin Y and Hoechst stained and sorted G0 and non-G0 including G1, S and G2/M phase CD34+ HSPCs. ns P>0.05 G0 compared with non-G0, n = 5 independent donors and analyzed using paired two-tailed Student’s t-test. c-g, Percentage of engrafted human B cells (c), granulocytes (d), monocytes (e), erythroid cells (f) and HSPCs (g) from mouse BM 16 weeks after primary transplantation. Data are plotted as grand median, n = 6 primary recipients from mock, n = 5 primary recipients from 1EP, n = 11 primary recipients from 2 EP. h-l, Correlation of overall human chimerism to individual lineages after primary transplantation. Data are analyzed using two-tailed nonparametric Spearman correlation. The Spearman correlation coefficients (r) and P values are shown. n = 6 primary recipients from mock, n = 5 primary recipients from 1EP, n = 11 primary recipients from 2 EP. m, Overall frequencies of C base edits in input CD34+ HSPCs and engrafted HSPCs, B cells, erythroid and BM by deep sequence analysis. Data are plotted as grand median and analyzed using unpaired two-tailed Student’s t-test. * P = 0.016 engrafted HSPCs compared with input HSPCs, * P = 0.02 engrafted B cells compared with input HSPCs, ** P = 0.004 engrafted erythroid compared with input HSPCs, ** P = 0.008 engrafted BM compared with input HSPCs following one cycle of electroporation. *** P = 0.0003 engrafted HSPCs compared with input HSPCs, ** P = 0.002 engrafted B cells compared with input HSPCs, *** P = 0.0001 engrafted erythroid compared with input HSPCs, *** P = 0.0003 engrafted BM compared with input HSPCs following two cycles of electroporation. n = 2 independent healthy donors HSPCs with 1 EP, n = 5 primary recipients with 1 EP. n = 3 independent healthy donors HSPCs with 2 EP, n = 7 primary mice for engrafted HSPCs, n = 10 primary mice for engrafted B cells and erythroid, n = 11 primary mice for engrafted BM. n, Percentage of engrafted human B cells, myeloid cells and CD19- CD33- cells 16 weeks after secondary transplantation from donors 6, 7 and 8. o-p, BCL11A expression by RT-qPCR in engrafted bone marrow human erythroid cells (o) and B cells (p) with 1 EP or 2 EP as compared to mock. Data are plotted as grand median and analyzed using Kolmogorov-Smirnov test, ns for nonsignificant, **P = 0.004, *** P = 0.0002, n = 6 primary recipients from mock, n = 5 primary recipients from 1 EP, n = 9 primary recipients from 2 EP engrafted erythroid, n = 11 primary recipients from 2 EP engrafted B cells.

Source data

Extended Data Fig. 5 Representative xenografted bone marrow flow cytometry analysis.

a–d, Live cells from engrafted mouse BM. e, Human cells gated from hCD45+ population, mouse cells gated from mCD45+ population. f, B cells gated from hCD45+ CD19+ population. g, Granulocytes gated from hCD45+ CD19-CD33dim with SSC high population. Monocytes gated from hCD45+ CD19-CD33+ with SSC low population. h, CD34+Lin- (HSPCs) gated from hCD45+CD19-CD33-CD34+population. T cells gated from hCD45+CD19-CD33-CD3+population. i, Erythroid cells gated from hCD45-mCD45-hCD235a+ population. 21 primary recipients and 21 secondary recipients analyzed by flow cytometry.

Extended Data Fig. 6 Guide RNA-dependent off-target potential of HSPC base editing.

a, Using the CasOFFinder tool, 59 potential genomic off-target sites with 3 or fewer mismatches to the on-target BCL11A enhancer sequence were identified. Each site was evaluated by amplicon deep sequencing. The samples include input HSPCs from donors 6, 7, and 8 with 1 or 2 cycles of RNP electroporation (1 EP or 2 EP) and corresponding engrafted bone marrow samples after primary transplantation (1° engrafted) and secondary transplantation (2° engrafted). Each dot represents the median edit frequency for the condition (with 2-11 samples per condition). Each input sample is from an independent donor. Each engraftment sample is from an independent mouse. * indicates off-target sites with difference in edit frequency between mock and edited samples of at least 0.1% and P<0.05. b, Allele frequency tables of OT1 and OT2 illustrate the condition with the highest off-targets edits, input HSPCs with 2 cycles of electroporation (2 EP) from donor 8. Base editing position indicated by arrow. c, On-target and off-target edits of OT1 and OT2 in individual samples from input HSPCs and engrafted bone marrow from primary and secondary recipients. d, Left, correlation of dose-dependent 1620 on-target edits and OT1 or OT2 off-target edits at RNP concentrations of 0, 10, 20, 30, 40, 50 µM with concentration proportional to fill color opacity. Data are analyzed using two-tailed nonparametric Spearman correlation. The Spearman correlation coefficients (r) and P values are shown. n = 1 healthy donor with 5 RNP concentration. Right, on-target to off-target edit ratios of OT1 or OT2 at RNP concentrations of 10–50 µM.

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Zeng, J., Wu, Y., Ren, C. et al. Therapeutic base editing of human hematopoietic stem cells. Nat Med 26, 535–541 (2020). https://doi.org/10.1038/s41591-020-0790-y

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