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:

In vivo genome editing of human haematopoietic stem cells for treatment of blood disorders using mRNA delivery

Nature Biomedical Engineering (2025)Cite this article

Subjects

Abstract

Ex vivo autologous haematopoietic stem cell (HSC) gene therapy provides a promising treatment option for haematological disorders. However, current methods involve complex processes and chemotherapeutic conditioning, leading to limited accessibility for treatment and major side effects. Here we develop antibody-free targeted lipid nanoparticles (LNPs) for mRNA delivery to HSCs in vivo, enabling efficient base editing of the γ-globin gene (HBG1/2) promoter target in human HSCs to reactivate fetal haemoglobin in derived erythroid cells. Delivery of ABE8e/sgRNA mRNA with optimized LNPs achieves efficient in vivo base editing of HBG1/2 in transfusion-dependent β-thalassaemia (TDT) patient-derived HSCs engrafted in immunodeficient NCG-X mice, showing restored globin chain balance in erythroid cells. Our research indicates that using LNPs for genome editor delivery achieves efficient editing of endogenous genes of human HSCs. This non-viral delivery system eliminates the need for collecting or mobilizing HSCs, providing a potent and one-time treatment potential for blood disorders such as sickle cell disease and TDT.

Access through your institution
Buy or subscribe

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

Access options

Access through your institution

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

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

Fig. 1: High-throughput screening of the HBG promoter using ABE8e to identify efficient sgRNAs that can elevate HbF levels in CD34+ HSPCs.
Fig. 2: Efficient base editing to induce HbF expression in CD34+ HSPCs from β-thalassaemia patients and in immunodeficient mice.
Fig. 3: Efficient in vivo base editing by LNP-mediated mRNA/sgRNA delivery in humanized mice.
Fig. 4: Intravenous administration of LNP-168-Cre in Ai14 mice resulted in efficient tdTomato+ cell expression of BM HSPCs.
Fig. 5: LNP-mediated ABE8e mRNA delivery leads to therapeutic base editing in β-thalassaemia patient CD34+ HSPCs.
Fig. 6: Safety-related assessments of the LNP-168-ABE8e-PCSK9 in vivo treatment.

Similar content being viewed by others

Data availability

ATAC and CUT&Tag sequencing data generated in this article can be found at the National Center for Biotechnology Information’s database with accession no. PRJNA880685. Source data for the figures are provided with this paper.

Code availability

The code used for analysing ATAC and CUT&Tag sequencing data is available at https://github.com/wqiudao/mRNA-HSCedit (ref. 75).

References

  1. Esrick, E. B. et al. Post-transcriptional genetic silencing of BCL11A to treat sickle cell disease. N. Engl. J. Med. 384, 205–215 (2021).

    Article  CAS  PubMed  Google Scholar 

  2. Frangoul, H. et al. CRISPR-Cas9 gene editing for sickle cell disease and β-thalassemia. N. Engl. J. Med. 384, 252–260 (2021).

    Article  CAS  PubMed  Google Scholar 

  3. Fu, B. et al. CRISPR-Cas9-mediated gene editing of the BCL11A enhancer for pediatric β0/β0 transfusion-dependent β-thalassemia. Nat. Med. 28, 1573–1580 (2022).

    Article  CAS  PubMed  Google Scholar 

  4. Germino-Watnick, P. et al. Hematopoietic stem cell gene-addition/editing therapy in sickle cell disease. Cells 11, 1843 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Cavazzana, M., Bushman, F. D., Miccio, A., Andre-Schmutz, I. & Six, E. Gene therapy targeting haematopoietic stem cells for inherited diseases: progress and challenges. Nat. Rev. Drug Discov. 18, 447–462 (2019).

    Article  CAS  PubMed  Google Scholar 

  6. Ferrari, G., Thrasher, A. J. & Aiuti, A. Gene therapy using haematopoietic stem and progenitor cells. Nat. Rev. Genet. 22, 216–234 (2021).

    Article  CAS  PubMed  Google Scholar 

  7. Daikeler, T., Tichelli, A. & Passweg, J. Complications of autologous hematopoietic stem cell transplantation for patients with autoimmune diseases. Pediatr. Res. 71, 439–444 (2012).

    Article  CAS  PubMed  Google Scholar 

  8. Aiuti, A., Pasinelli, F. & Naldini, L. Ensuring a future for gene therapy for rare diseases. Nat. Med. 28, 1985–1988 (2022).

    Article  CAS  PubMed  Google Scholar 

  9. Li, C. et al. In vivo HSC prime editing rescues sickle cell disease in a mouse model. Blood 141, 2085–2099 (2023).

    CAS  PubMed  PubMed Central  Google Scholar 

  10. Wang, H. et al. In vivo hematopoietic stem cell gene therapy ameliorates murine thalassemia intermedia. J. Clin. Invest. 129, 598–615 (2019).

    Article  PubMed  Google Scholar 

  11. Richter, M. et al. In vivo hematopoietic stem cell transduction. Hematol. Oncol. Clin. North Am. 31, 771–785 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Jung, H. N., Lee, S. Y., Lee, S., Youn, H. & Im, H. J. Lipid nanoparticles for delivery of RNA therapeutics: current status and the role of in vivo imaging. Theranostics 12, 7509–7531 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Hou, X., Zaks, T., Langer, R. & Dong, Y. Lipid nanoparticles for mRNA delivery. Nat. Rev. Mater. 6, 1078–1094 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Raguram, A., Banskota, S. & Liu, D. R. Therapeutic in vivo delivery of gene editing agents. Cell 185, 2806–2827 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Zong, Y., Lin, Y., Wei, T. & Cheng, Q. Lipid nanoparticle (LNP) enables mRNA delivery for cancer therapy. Adv. Mater. 35, e2303261 (2023).

    Article  PubMed  Google Scholar 

  16. Musunuru, K. et al. In vivo CRISPR base editing of PCSK9 durably lowers cholesterol in primates. Nature 593, 429–434 (2021).

    Article  CAS  PubMed  Google Scholar 

  17. Rothgangl, T. et al. In vivo adenine base editing of PCSK9 in macaques reduces LDL cholesterol levels. Nat. Biotechnol. 39, 949–957 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Qiu, M. et al. Lung-selective mRNA delivery of synthetic lipid nanoparticles for the treatment of pulmonary lymphangioleiomyomatosis. Proc. Natl Acad. Sci. USA 119, e2116271119 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Shi, D., Toyonaga, S. & Anderson, D. G. In vivo RNA delivery to hematopoietic stem and progenitor cells via targeted lipid nanoparticles. Nano Lett. 23, 2938–2944 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Zak, M. M. & Zangi, L. Lipid nanoparticles for organ-specific mRNA therapeutic delivery. Pharmaceutics 13, 1675 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Xu, Y., Golubovic, A., Xu, S., Pan, A. & Li, B. Rational design and combinatorial chemistry of ionizable lipids for RNA delivery. J. Mater. Chem. B 11, 6527–6539 (2023).

    Article  CAS  PubMed  Google Scholar 

  22. Breda, L. et al. In vivo hematopoietic stem cell modification by mRNA delivery. Science 381, 436–443 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Richter, M. F. et al. Phage-assisted evolution of an adenine base editor with improved Cas domain compatibility and activity. Nat. Biotechnol. 38, 883–891 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Kurita, R. et al. Establishment of immortalized human erythroid progenitor cell lines able to produce enucleated red blood cells. PLoS ONE 8, e59890 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Traxler, E. A. et al. A genome-editing strategy to treat β-hemoglobinopathies that recapitulates a mutation associated with a benign genetic condition. Nat. Med. 22, 987–990 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Cheng, L. et al. Single-nucleotide-level mapping of DNA regulatory elements that control fetal hemoglobin expression. Nat. Genet. 53, 869–880 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Yen, J. et al. TRIAMF: a new method for delivery of Cas9 ribonucleoprotein complex to human hematopoietic stem cells. Sci. Rep. 8, 16304 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  29. Wu, Y. et al. Highly efficient therapeutic gene editing of human hematopoietic stem cells. Nat. Med. 25, 776–783 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Ravi, N. S. et al. Identification of novel HPFH-like mutations by CRISPR base editing that elevate the expression of fetal hemoglobin. eLife 11, e65421 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Kaczynski, J., Cook, T. & Urrutia, R. Sp1- and Kruppel-like transcription factors. Genome Biol. 4, 206 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Doetzlhofer, A. et al. Histone deacetylase 1 can repress transcription by binding to Sp1. Mol. Cell. Biol. 19, 5504–5511 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Feng, D. & Kan, Y. W. The binding of the ubiquitous transcription factor Sp1 at the locus control region represses the expression of beta-like globin genes. Proc. Natl Acad. Sci. USA 102, 9896–9900 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. McIntosh, B. E. et al. Nonirradiated NOD,B6.SCID Il2rγ−/−KitW41/W41 (NBSGW) mice support multilineage engraftment of human hematopoietic cells. Stem Cell Rep. 4, 171–180 (2015).

    Article  CAS  Google Scholar 

  35. Chang, K.-H. et al. Long-term engraftment and fetal globin induction upon BCL11A gene editing in bone-marrow-derived CD34+ hematopoietic stem and progenitor cells. Mol. Ther. Methods Clin. Dev. 4, 137–148 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Gundry, M. C. et al. Highly efficient genome editing of murine and human hematopoietic progenitor cells by CRISPR/Cas9. Cell Rep. 17, 1453–1461 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Han, J. et al. In vivo delivery of CRISPR-Cas9 using lipid nanoparticles enables antithrombin gene editing for sustainable hemophilia A and B therapy. Sci. Adv. 8, eabj6901 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Li, B. et al. Combinatorial design of nanoparticles for pulmonary mRNA delivery and genome editing. Nat. Biotechnol. 41, 1410–1415 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Kim, J. et al. Engineering lipid nanoparticles for enhanced intracellular delivery of mRNA through inhalation. ACS Nano 16, 14792–14806 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Guimarães, P. P. G. et al. In vivo bone marrow microenvironment siRNA delivery using lipid-polymer nanoparticles for multiple myeloma therapy. Proc. Natl Acad. Sci. USA 120, e2215711120 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  41. Han, X. et al. An ionizable lipid toolbox for RNA delivery. Nat. Commun. 12, 7233 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Li, B. et al. Enhancing the immunogenicity of lipid-nanoparticle mRNA vaccines by adjuvanting the ionizable lipid and the mRNA. Nat. Biomed. Eng. 7, 280 (2023).

    Google Scholar 

  43. Qiu, M., Li, Y., Bloomer, H. & Xu, Q. Developing biodegradable lipid nanoparticles for intracellular mRNA delivery and genome editing. Acc. Chem. Res. 54, 4001–4011 (2021).

    Article  CAS  PubMed  Google Scholar 

  44. Li, C. et al. Single-dose MGTA-145/plerixafor leads to efficient mobilization and in vivo transduction of HSCs with thalassemia correction in mice. Blood Adv. 5, 1239–1249 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Akinc, A. et al. Targeted delivery of RNAi therapeutics with endogenous and exogenous ligand-based mechanisms. Mol. Ther. 18, 1357–1364 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Tarab-Ravski, D. et al. Delivery of therapeutic RNA to the bone marrow in multiple myeloma using CD38-targeted lipid nanoparticles. Adv. Sci. 10, e2301377 (2023).

    Article  Google Scholar 

  47. Jain, R. et al. MicroRNAs enable mRNA therapeutics to selectively program cancer cells to self-destruct. Nucleic Acid Ther. 28, 285–296 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Madisen, L. et al. A robust and high-throughput Cre reporting and characterization system for the whole mouse brain. Nat. Neurosci. 13, 133–140 (2010).

    Article  CAS  PubMed  Google Scholar 

  49. Yavuz, A. et al. DLin-MC3-containing mRNA lipid nanoparticles induce an antibody Th2-biased immune response polarization in a delivery route-dependent manner in mice. Pharmaceutics 15, 1009 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Pietras, E. M. et al. Functionally distinct subsets of lineage-biased multipotent progenitors control blood production in normal and regenerative conditions. Cell Stem Cell 17, 35–46 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Monopoli, M. P., Aberg, C., Salvati, A. & Dawson, K. A. Biomolecular coronas provide the biological identity of nanosized materials. Nat. Nanotechnol. 7, 779–786 (2012).

    Article  CAS  PubMed  Google Scholar 

  52. Dilliard, S. A., Cheng, Q. & Siegwart, D. J. On the mechanism of tissue-specific mRNA delivery by selective organ targeting nanoparticles. Proc. Natl Acad. Sci. USA 118, e2109256118 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Chen, D., Ganesh, S., Wang, W. & Amiji, M. The role of surface chemistry in serum protein corona-mediated cellular delivery and gene silencing with lipid nanoparticles. Nanoscale 11, 8760–8775 (2019).

    Article  CAS  PubMed  Google Scholar 

  54. Miao, L. et al. Synergistic lipid compositions for albumin receptor mediated delivery of mRNA to the liver. Nat. Commun. 11, 2424 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Wirth, F., Lubosch, A., Hamelmann, S. & Nakchbandi, I. A. Fibronectin and its receptors in hematopoiesis. Cells 9, 2717 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Koo, J. et al. Evaluation of fibrinogen self-assembly: role of its αC region. J. Thromb. Haemost. 8, 2727–2735 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Koo, J. et al. Control of anti-thrombogenic properties: surface-induced self-assembly of fibrinogen fibers. Biomacromolecules 13, 1259–1268 (2012).

    Article  CAS  PubMed  Google Scholar 

  58. Monopoli, M. P. et al. Physical-chemical aspects of protein corona: relevance to in vitro and in vivo biological impacts of nanoparticles. J. Am. Chem. Soc. 133, 2525–2534 (2011).

    Article  CAS  PubMed  Google Scholar 

  59. Liu, Q. et al. Hi-TOM: a platform for high-throughput tracking of mutations induced by CRISPR/Cas systems. Sci. China Life Sci. 62, 1–7 (2019).

    Article  PubMed  Google Scholar 

  60. Bae, S., Park, J. & Kim, J. S. Cas-OFFinder: a fast and versatile algorithm that searches for potential off-target sites of Cas9 RNA-guided endonucleases. Bioinformatics 30, 1473–1475 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Métais, J. Y. et al. Genome editing of HBG1 and HBG2 to induce fetal hemoglobin. Blood Adv. 3, 3379–3392 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  62. Swingle, K. L. et al. Ionizable lipid nanoparticles for in vivo mRNA delivery to the placenta during pregnancy. J. Am. Chem. Soc. 145, 4691–4706 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Sanjana, N. E., Shalem, O. & Zhang, F. Improved vectors and genome-wide libraries for CRISPR screening. Nat. Methods 11, 783–784 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160–W165 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Kluesner, M. G. et al. EditR: a method to quantify base editing from Sanger Sequencing. CRISPR J. 1, 239–250 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Clement, K. et al. CRISPResso2 provides accurate and rapid genome editing sequence analysis. Nat. Biotechnol. 37, 224–226 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Buenrostro, J. D., Wu, B., Chang, H. Y. & Greenleaf, W. J. ATAC-seq: a method for assaying chromatin accessibility genome-wide. Curr. Protoc. Mol. Biol. 109, 21.29.1–21.29.9 (2015).

    Article  PubMed  Google Scholar 

  68. Yan, F., Powell, D. R., Curtis, D. J. & Wong, N. C. From reads to insight: a hitchhiker’s guide to ATAC-seq data analysis. Genome Biol. 21, 22 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Kaya-Okur, H. S., Janssens, D. H., Henikoff, J. G., Ahmad, K. & Henikoff, S. Efficient low-cost chromatin profiling with CUT&Tag. Nat. Protoc. 15, 3264–3283 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  72. Finn, J. D. et al. A single administration of CRISPR/Cas9 lipid nanoparticles achieves robust and persistent in vivo genome editing. Cell Rep. 22, 2227–2235 (2018).

    Article  CAS  PubMed  Google Scholar 

  73. Kim, M. et al. Engineered ionizable lipid nanoparticles for targeted delivery of RNA therapeutics into different types of cells in the liver. Sci. Adv. 7, eabf4398 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Kiel, M. J. et al. SLAM family receptors distinguish hematopoietic stem and progenitor cells and reveal endothelial niches for stem cells. Cell 121, 1109–1121 (2005).

    Article  CAS  PubMed  Google Scholar 

  75. Wang, Q. D. mRNA‑HSCedit [Computer software]. GitHub https://github.com/wqiudao/mRNA-HSCedit (2021).

Download references

Acknowledgements

We acknowledge R. Kurita and Y. Nakamura for providing the HUDEP-2 cells, and M. Qiu for offering valuable advice on LC–MS detection and data analysis. The flow cytometry experiments were performed at the Flow Cytometry Core Facility of the School of Life Sciences, East China Normal University. We thank staff member Y. Zhang for help with flow cytometry data collection. This work was supported by the National Key R&D Program of China 2023YFC3403401 and 2024YFA1803301 (Y.W.), grants from the Shanghai Municipal Commission for Science and Technology 23HC1400400 (Y.W.), the National Science Foundation of China grant 82270125 (Y.W.), the National Program for Support of Top-Notch Young Professionals (Y.W.), the Scientific Research of BSKY XJ2020025 (D.L.) from Anhui Medical University, and the Anhui Province Fund for Excellent Young Scholars 2024AH030022 (D.L.).

Author information

Author notes

  1. These authors contributed equally: Saijuan Xu, Dan Liang.

Authors and Affiliations

  1. Shanghai Frontiers Science Center of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Shanghai, China

    Saijuan Xu, Qiudao Wang, Yan Cheng, Feiyan Zhao, Gongrui Sun & Yuxuan Wu

  2. Department of Obstetrics and Gynecology, the First Affiliated Hospital of Anhui Medical University, Hefei, China

    Dan Liang

  3. NHC Key Laboratory of Study on Abnormal Gametes and Reproductive Tract, Anhui Medical University, Hefei, China

    Dan Liang

  4. YolTech Therapeutics, Shanghai, China

    Da Xie, Yang Gui, Haokun Zhang, Changrui Feng, Wendan Ren, Yuming Lu, Zi Jun Wang & Yuxuan Wu

  5. Department of Hematology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China

    Yang Yang & Yongrong Lai

  6. School of Pharmaceutical Sciences, Shanghai Jiao Tong University, Shanghai, China

    Lin Li

  7. Xiangya Hospital, Central South University, Hunan, China

    Bin Fu

  8. School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China

    Yuming Lu

Authors
  1. Saijuan Xu
    View author publications

    Search author on:PubMed Google Scholar

  2. Dan Liang
    View author publications

    Search author on:PubMed Google Scholar

  3. Qiudao Wang
    View author publications

    Search author on:PubMed Google Scholar

  4. Yan Cheng
    View author publications

    Search author on:PubMed Google Scholar

  5. Da Xie
    View author publications

    Search author on:PubMed Google Scholar

  6. Yang Gui
    View author publications

    Search author on:PubMed Google Scholar

  7. Haokun Zhang
    View author publications

    Search author on:PubMed Google Scholar

  8. Changrui Feng
    View author publications

    Search author on:PubMed Google Scholar

  9. Feiyan Zhao
    View author publications

    Search author on:PubMed Google Scholar

  10. Wendan Ren
    View author publications

    Search author on:PubMed Google Scholar

  11. Gongrui Sun
    View author publications

    Search author on:PubMed Google Scholar

  12. Yang Yang
    View author publications

    Search author on:PubMed Google Scholar

  13. Lin Li
    View author publications

    Search author on:PubMed Google Scholar

  14. Yongrong Lai
    View author publications

    Search author on:PubMed Google Scholar

  15. Bin Fu
    View author publications

    Search author on:PubMed Google Scholar

  16. Yuming Lu
    View author publications

    Search author on:PubMed Google Scholar

  17. Zi Jun Wang
    View author publications

    Search author on:PubMed Google Scholar

  18. Yuxuan Wu
    View author publications

    Search author on:PubMed Google Scholar

Contributions

Y. Lu, Z.J.W. and Y.W. conceived and supervised this study. S.X. and D.L. conducted most of the cell and animal experiments and analysed data with the help of Y.C., F.Z., H.Z. and G.S. Q.W. and C.F. performed the bioinformatics analysis. W.R. and D.X. conducted the mRNA and LNPs production. L.L. assisted with the proteomics analysis. Z.J.W. and Y.G. designed and synthesized the library of ionizable lipids. Y.Y., Y. Lai and B.F. recruited β-thalassaemia patients to collect CD34+ cells. S.X., D.L., Y. Lu, Z.J.W. and Y.W. wrote the paper. All authors contributed to the paper and approved its final version.

Corresponding authors

Correspondence to Yuming Lu, Zi Jun Wang or Yuxuan Wu.

Ethics declarations

Competing interests

Y. Lu, Z.J.W. and Y.W. are scientific co-founders at YolTech Therapeutics. D.X., W.R., Y.G., H.Z. and C.F. are employees of YolTech Therapeutics. YolTech Therapeutics has filed patents (CN114989182A, CN116162071A, PCT/CN2023/100791, PCT/CN2023/100823 and PCT/CN2023/106421) on the technology described in this paper. The other authors declare no competing interests.

Peer review

Peer review information

Nature Biomedical Engineering thanks the anonymous reviewers for their contribution to the peer review of this work.

Additional information

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

Extended data

Extended Data Fig. 1 Highly efficient editing of HBG promoter in CD34+ HSPCs.

a. Heat map showing the pearson correlation of mock and ABE8e edited cells transcriptomes as measured by RNA-seq. The number in each cell represents the correlation coefficient. b. Flow cytometry plots showing the expression of the erythroid maturation markers CD71 and CD235a in vitro differentiation of HUDEP-2 cells. c. Flow cytometry plots showing the expression of the RBCs maturation markers CD71 and CD235a after in vitro differentiation of ABE8e RNP edited CD34+ cells. d. Enucleation rates in erythroid cells following in vitro differentiation of ABE8e RNP edited and un-edited CD34+ cells. e. Base-editing rates in bulk base-edited cells in high and low HbF cells after in vitro differentiation of ABE8e RNP edited CD34+ cells. The T-C conversion rate of sgRNA-25 in CD34+ cells was measured by deep sequencing and quantified with CRISPResso2. f. Representative RP-HPLC chromatograms of erythroid cells derived from in vitro differentiation of edited CD34+ HSPCs. Protein levels of β-like globin by genome editing mediated by ABE8e/BCL11A Enh, ABE8e/sgRNA-25, ABE8e/sgRNA-35 and ABE8e/sgRNA-41 were analyzed. Three independent experiments were performed. Data are plotted as the mean ± s.d.

Source data

Extended Data Fig. 2 The γ-globin expression was rapidly activated following base editing at the sgRNA-25 target site within the HBG promoter.

a. Schematic diagram of the sequence of the γ-globin promoter of CD34+ promoter editing cells. The left arrow indicates the sequence position of sgRNA-25, and the two upward arrows indicate the targeted bases. b. ATAC-seq of in vitro differentiation of ABE8e RNP edited and un-edited CD34+ cells. c. SP1 CUT& Tag profiles in the β-globin cluster. Antibodies and cell types for each track are shown on the right. The promoters of duplicated γ-globin genes (HBG2 and HBG1) are highlighted in gray. d. Zoomed-in view of the HBG2 and HBG1 promoter regions. The sequence of sgRNA-25 is highlighted in orange. Heatmap comparison of signals in primary human CD34+-derived erythroid cells with or without sgRNA-25 base editing within binding sites. e. The enrichment curve of the CUT&Tag binding signal in the upstream and downstream 3-kb regions of the gene body and TSS region. f. Heat map comparison of overlapping peaks CUT&TAG.

Extended Data Fig. 3 Structures of ionizable lipids in Library A and the base editing efficiency of BM cells in mice treated with different LNPs.

a. Library A contains structures of various head groups and tails in ionizable lipids. b. The top-performing ionizable lipid structures within library A were determined by analyzing the editing efficiency of BM cells in mice treated with 35 different LNP-ABE8e-PCSK9 formulations (intravenous injection, 2 mg/kg of LNP-ABE8e-PCSK9, n = 3-4 mice).

Source data

Extended Data Fig. 4 Structures of ionizable lipids in Library B and the base editing efficiency of BM cells in mice treated with different LNPs.

a. Library B contains structures of various head groups and tails in ionizable lipids. b. The top-performing ionizable lipid structures within library B were determined by analyzing the editing efficiency of BM cells in mice treated with 32 different LNP-ABE8e-PCSK9 formulations (intravenous injection, 2 mg/kg of LNP-ABE8e-PCSK9, n = 3-4 mice).

Source data

Extended Data Fig. 5 Structures of ionizable lipids in Library C and the base editing efficiency of BM cells in mice treated with different LNPs.

a. Library C contains structures of various head groups and tails in ionizable lipids. b. The top-performing ionizable lipid structures within library C were determined by analyzing the editing efficiency of BM cells in mice treated with 25 different LNP-ABE8e-PCSK9 formulations (intravenous injection, 2 mg/kg of LNP-ABE8e-PCSK9, n = 3-4 mice).

Source data

Extended Data Fig. 6 Efficient HSPCs editing by LNP-028-ABE8e-HBG in immunodeficient mice.

a-c. BM was collected two weeks after the second-dose and fifth-dose injections of LNP-028-ABE8e-HBG, and then analyzed by flow cytometry for human cell chimerism (a), multilineage reconstitution (b), or human erythroid cells (c) in the BM. d. Base editing efficiency was assessed in vitro using differentiated erythroid cells derived from the BM cells of engrafted mice after injection of LNP-028-ABE8e-HBG. e. The γ-globin expression was analyzed by RT-qPCR in erythroid cells that were differentiated in vitro from BM cells edited by LNP-028-ABE8e-HBG. f. Enucleation of in vitro differentiated erythroid cells from LNP-028-ABE8e-HBG edited BM cells. For figs. a-f, each symbol represents a mouse, and there were a total of n = 3 mice. g. After LNP-028-ABE8e-HBG edited BM cells were transplanted into NCG-X mice, the chimerism level of human cells among the transplanted BM cells was analyzed by flow cytometry 16 weeks post-transplantation. h. The percentage of engrafted human B cells, myeloid cells, and CD19-CD33- cells among the transplanted BM cells was assessed after 16 weeks of transplantation using flow cytometry (n = 5 mice). i. After 16 weeks of transplantation, deep sequencing analysis was conducted to evaluate the base editing efficiency at positions A5 and A6 within different hematopoietic cell populations derived from the engrafted BM cells (n = 4 mice). All statistical significances in the figures were analyzed using one-way ANOVA with Dunnett’s multiple comparisons test, and data represent mean ± SD. Statistical analysis showed NS for second- and fifth-dose groups compared with the un-edited control in panels a and c. Panel d also showed NS between non-mobilized and mobilized groups, but p < 0.0001 was observed for both doses. Panel e confirmed p < 0.0001 for second- and fifth-dose, while panel g showed NS for the same comparison.

Source data

Extended Data Fig. 7 Structures of ionizable lipids in the second optimization of Library A.

A second combinatorial library A contains structures of various head groups and tails in 49 different ionizable lipids.

Extended Data Fig. 8 LNP-168-mRNA efficiently delivers to BM cells and editing following intravenous administration.

a. Representative IVIS bioluminescence images of all organs 24 hours after injection of LNP-168-Luc at a dose of 1 mg/kg. A representative sample set of various tissues and organs dissected from these mice was analyzed 10 minutes after the administration of D-luciferin. b. Quantification of the total flux intensity in the LNP- MC3-Luc (left) and LNP- 168-Luc (right) groups (n = 3 mice). c. Expression of tdTomato+ cells in mouse lymphoid, Gr1+ and CD11b+ myeloid cells in BM cells from Ai14 mice after administration of LNP-168-Cre (n = 5 mice). d. Semiquantitative PCR of genomic DNA isolated from BM cells of Ai14 mice after administration of LNP-168-Cre (n = 3 mice). * 271 bp, Cre-recombinase edited gDNA region and * 1142 bp, unedited region is indicated. Data are shown as mean ± SD.

Source data

Extended Data Fig. 9 Proteomics study of protein coronas formed on LNP-168-Luc.

a. Schematic showing the use of mass spectrometry in the analysis of LNPs mRNA with proteins in the plasma interactions. b. Heat map of the average abundance of proteins with distinct biological functions in the protein coronas of LNP-168-Luc. c. Quantification of percentage of total proteins of the top three protein components in the protein corona of the LNP-168-Luc is shown. Data are representative of three biologically independent replicates. Data are shown as mean ± SD.

Extended Data Fig. 10 Assessment of off-target editing in vitro and in vivo.

a. Thirty-eight potential genomic sgRNA-25 off-target sites in total were evaluated by amplicon deep sequencing and quantified with CRISPResso2. To assess potential off-target effects, we examined the editing positions targeting A5 (OT1–7, OT9–14, OT17–18, OT21, OT25, OT29–38), A6 (OT8, OT15, OT19–20, OT22, OT23–24, OT26–28), and A15 (OT16), which were identified as mutation hotspots. For all sites, the off-target sites with difference in edit frequency between mock and edited samples of less 0.15%. b. Ten potential genomic sgRNA-25 off-target sites were evaluated by amplicon deep sequencing in BM cells from engrafted mice after LNP-028-ABE8e-HBG injection. For all sites, the off-target sites with difference in edit frequency between mock and edited samples of less 0.12%. c. HBG ABE8e cleavage sites are indicated by inverted triangles. Quantitative PCR (qPCR) primers targeting the intergenic sequence between the cleavage sites are indicated (red arrows). The larger deletion presumed to arise from simultaneous ssDNA breaks in HBG2 and HBG1, with the loss of the intervening 4.9-kb, is shown (dotted line). Primers for Δ 366-bp denote a quantitative qPCR assay that detects deletions ≥366-nt upstream of the cleavage site in HBG1. d. The analysis of large fragment deletions was conducted following the electroporation of ABE8e RNP and Cas9 RNP in human CD34+ cells. e. Five days post ABE8e RNP editing, base editing efficiency in CD34+ cells were examined using deep sequence analysis. f. Five days post Cas9 RNP editing, indel frequency in CD34+ cells were analyzed by synthego. g. β-like globin gene expression was analyzed by RT-qPCR in erythroid cells differentiated in vitro from ABE8e and Cas9 RNP-edited CD34+ HSPCs. All data are representative of three biologically independent replicates. All statistical significances in the figures were analyzed using one-way ANOVA with Dunnett’s multiple comparisons test, and data represent mean ± SD. Statistical analysis showed p < 0.0001 for sgRNA-25, sgRNA-35, and sgRNA-41 in ABE8e RNP groups compared with Cas9 RNP controls, as shown in panels d and g.

Source data

Supplementary information

Source data

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Xu, S., Liang, D., Wang, Q. et al. In vivo genome editing of human haematopoietic stem cells for treatment of blood disorders using mRNA delivery. Nat. Biomed. Eng (2025). https://doi.org/10.1038/s41551-025-01480-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41551-025-01480-y

Search

Advanced 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