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Genetically encoding multiple functionalities into extracellular vesicles for the targeted delivery of biologics to T cells

Nature Biomedical Engineering (2023)Cite this article

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Abstract

The genetic modification of T cells has advanced cellular immunotherapies, yet the delivery of biologics specifically to T cells remains challenging. Here we report a suite of methods for the genetic engineering of cells to produce extracellular vesicles (EVs)—which naturally encapsulate and transfer proteins and nucleic acids between cells—for the targeted delivery of biologics to T cells without the need for chemical modifications. Specifically, the engineered cells secreted EVs that actively loaded protein cargo via a protein tag and that displayed high-affinity T-cell-targeting domains and fusogenic glycoproteins. We validated the methods by engineering EVs that delivered Cas9–single-guide-RNA complexes to ablate the gene encoding the C-X-C chemokine co-receptor type 4 in primary human CD4+ T cells. The strategy is amenable to the targeted delivery of biologics to other cell types.

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Fig. 1: Overview of the GEMINI strategy for genetically engineering multifunctional EVs.
Fig. 2: Display of scFvs on EVs mediates receptor-specific, targeted binding and uptake to T cells.
Fig. 3: Cargo protein is actively loaded into EVs via tagging with the ABI domain of the ABA dimerization system.
Fig. 4: Viral glycoprotein display on EVs mediates uptake by recipient T cells.
Fig. 5: EVs mediate functional delivery of Cas9 in primary human T cells.
Fig. 6: CD2 engagement and repeat dosing enhance EV-mediated functional cargo delivery and vary with vesicle subpopulation.

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Data availability

All reported experimental data and plasmid maps for all plasmids generated in this study are freely available at Zenodo (https://doi.org/10.5281/zenodo.10022991). Key plasmids used in this study are distributed by Addgene, with complete and annotated GenBank files available at https://www.addgene.org/Joshua_Leonard. The raw and analysed datasets generated during the study are available for research purposes from the corresponding author on reasonable request.

Code availability

The code for analysing HTS data is available at https://github.com/leonardlab/GEMINI-HTS under an open-source license.

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Acknowledgements

We thank R. D’Aquila for his support and guidance in starting this project. We thank I. Clerc for her assistance with the measles virus glycoproteins. J.N.L. discloses support for the research described in this study from Third Coast Center for AIDS Research, an NIH-funded centre (P30 AI117943), NIH grants R01AI165236 and R01AI150998 (J.F.H.), National Science Foundation (NSF) award 1844219 (J.N.L. and N. P. Kamat), Kairos Ventures (gift), and Syenex. This work was also supported by NSF Graduate Research Fellowship awards DGE-1324585 (to D.M.S.) and DGE-1842165 (to B.N.D.). Sanger sequencing was performed through the Northwestern University Sequencing Core (NUSeq) Core Facility of Northwestern’s Center for Genetic Medicine and a partnership with ACGT. NanoSight analysis was performed in the Analytical bioNanoTechnology Core Facility (ANTEC) of the Simpson Querrey Institute at Northwestern University. ANTEC is currently supported by the Soft and Hybrid Nanotechnology Experimental Resource (NSFECCS-1542205). We thank C. Wilke for her assistance with TEM. TEM was performed at the BioCryo facility of Northwestern University’s Atomic and Nanoscale Characterization Experimental (NUANCE) Center, which has received support from the Soft and Hybrid Nanotechnology Experimental Resource (NSF ECCS-1542205); the Materials Research Science and Engineering Centers (MRSEC) program (NSF DMR-1720139) at the Materials Research Center; the International Institute for Nanotechnology; and the State of Illinois, through the International Institute for Nanotechnology. It also made use of the CryoCluster equipment, which has received support from the Major Research Instrumentation (MRI) program (NSF DMR-1229693). We thank H. Edelstein for her assistance with confocal microscopy. Microscopy was performed at the Biological Imaging Facility at Northwestern University (RRID:SCR_017767), graciously supported by the Chemistry for Life Processes Institute, the Northwestern University Office for Research, and the Department of Molecular Biosciences. We thank P. Mehl for his assistance with FACS. Flow cytometry was performed at the Northwestern University Robert H. Lurie Comprehensive Cancer Center (RHLCCC) Flow Cytometry Facility, which is supported by a Cancer Center Support Grant (NCI CA060553). We thank J. Brink and S. Hockema at 496code for their assistance with HTS data analysis.

Author information

Authors and Affiliations

  1. Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA

    Devin M. Stranford, Beth N. DiBiase, Julius B. Lucks & Joshua N. Leonard

  2. Center for Synthetic Biology, Northwestern University, Evanston, IL, USA

    Devin M. Stranford, Katherine E. Berman, Luyi Cheng, Beth N. DiBiase, Michelle E. Hung, Julius B. Lucks & Joshua N. Leonard

  3. Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, USA

    Lacy M. Simons & Judd F. Hultquist

  4. Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL, USA

    Lacy M. Simons & Judd F. Hultquist

  5. Interdisciplinary Biological Sciences Training Program, Northwestern University, Evanston, IL, USA

    Katherine E. Berman, Luyi Cheng, Michelle E. Hung, Julius B. Lucks & Joshua N. Leonard

  6. Chemistry of Life Processes Institute, Northwestern University, Evanston, IL, USA

    Julius B. Lucks & Joshua N. Leonard

  7. Member, Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Evanston, IL, USA

    Joshua N. Leonard

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Contributions

D.M.S. and J.N.L. conceptualized the project and designed the experiments. D.M.S., B.N.D. and M.E.H. performed the experiments. D.M.S. and J.N.L. analysed the data. L.M.S. isolated, activated, and electroporated the primary T cells. K.E.B. and L.C. conducted the MiSeq runs. D.M.S. drafted the original manuscript and created the figures. J.N.L., J.F.H. and J.B.L. supervised the work. All authors reviewed, edited, and approved the final manuscript.

Corresponding author

Correspondence to Joshua N. Leonard.

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Competing interests

J.N.L. and D.M.S. are co-inventors on patent pending intellectual property that covers some technologies reported in this manuscript. J.N.L. and D.M.S. have financial interest in Syenex, which could potentially benefit from the outcomes of this research.

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Extended data

Extended Data Fig. 1 Different scFv display techniques result in different EV targeting properties.

a, Cartoon highlighting the structures of the PDGFR transmembrane domain scFv display and lactadherin C1C2 domain anchoring to phosphatidylserine. b, Expression of scFv constructs in EV producer cell lysates. 1 µg cell lysate was loaded per lane. Expected band sizes: ∼40 kDa and ∼75 kDa (black arrows). c, Loading of scFv constructs into EVs generated from cell lines in b. 5.0×108 EVs were loaded per lane. d, Binding of targeted EVs to Jurkat T cells following a 2 h incubation. e, Representative histograms corresponding to the summary data reported in d. The subpopulation of cells showing a skewed, high degree of exosome binding is indicated by the red box. f, Recipient Jurkat T cells were incubated for 1 h in the presence or absence of anti-CD2 antibodies prior to a 2 h incubation with EVs. g, Representative histograms corresponding to the summary data reported in f. Flow cytometry experiments were performed in biological triplicate, and error bars (panels d, f) indicate standard error of the mean. EV dTomato loading evaluations are presented in Supplementary Fig. 5. Statistical tests comprise two-tailed Student’s t-tests using the Benjamini-Hochberg method to reduce the false discovery rate. (*p < 0.05, **p < 0.01, ***p < 0.001). Exact p-values are reported in Supplementary Table 1.

Extended Data Fig. 2 The ABI domain increases EV-cargo loading independently of total protein expression.

a, Expression of EYFP and EYFP-ABI in the presence of anti-CD2 targeting constructs in transiently transfected HEK293FT cells analysed by flow cytometry. A key observation is that addition of the ABI domain does not increase overall cargo protein expression in producer cells. b, Repeat of EYFP-ABI EV loading trends in the presence of an scFv shown in Fig. 3c. c, Comparison of EYFP loading into EVs with and without an NLS with ABA-binding constructs and under ABA-induced dimerization conditions. Addition of an NLS did not substantially impact EYFP loading, nor did ABA-induced dimerization substantially impact loading of nuclear-localized cargo. Experiments were performed in biological triplicate, and error bars indicate standard error of the mean. Statistical tests comprise two-tailed Student’s t-tests using the Benjamini-Hochberg method to reduce the false discovery rate. (*p < 0.05, **p < 0.01, ***p < 0.001). Exact p-values are reported in Supplementary Table 1.

Extended Data Fig. 3 The ABI domain increases Cas9 loading into EVs, and Cas9-ABI retains function.

a, Expression of Cas9 fused to either the ABI or PYL domain in transiently transfected HEK293FT cells. 2 µg cell lysate was loaded per lane. Expected band sizes: ∼160, 183, and 195 kDa (arrows). b, Cartoon illustrating the Cas9 reporter construct. Successful editing by Cas9 results in the deletion of a stop codon and (in some random fraction of cases) a repair-mediated frame shift induces express dTomato. c, Absence of an NLS or presence of the ABI domain does not meaningfully reduce Cas9 editing efficiency in transiently transfected Jurkat T cells. Cells were analysed by flow cytometry 3 d post-transfection. Experiments were performed in biological triplicate, and error bars indicate standard error of the mean. Statistical tests comprise two-tailed Student’s t-tests using the Benjamini-Hochberg method to reduce the false discovery rate. (*p < 0.05, **p < 0.01, ***p < 0.001). Exact p-values are reported in Supplementary Table 1. Samples with high cellular autofluorescence were excluded from analysis. d, Full blot of Cas9 EV active loading data presented in Fig. 3e. e, Cellular expression of Cas9 with and without the ABI domain or an NLS. 2 µg cell lysate was loaded per lane.

Extended Data Fig. 4 Electroporation of recombinant Cas9-sgRNA ribonucleoprotein complexes into primary T cells confers dose-dependent editing of the genomic CXCR4 target locus.

a, Analysis of actively loaded Cas9 molecules per EV in vesicles displaying an anti-CD2 scFv and VSV-G. Lanes loaded with 4.0 × 108 (‘high’) or 2.0 × 108 (‘low’) EVs were compared to samples loaded with specified numbers of recombinant Cas9 molecules quantified based upon the manufacturer’s analysis (lanes 7-13). Expected band sizes (∼160 or 195 kDa, arrows) correspond to Cas9 +/- the ABI domain. b, Quantification of Cas9 RNPs per EV. Band intensities from Cas9 standards in a were plotted against Cas9 molecules loaded (blue points), and loading of Cas9 into EVs was calculated using a line fit to the linear regime of the recombinant Cas9 standard curve (purple points; light: MV, dark: exo); this analysis indicates a loading of ∼100 Cas9 molecules per EV. c, Frequency of indels detected at the Cas9-targeted CXCR4 locus after electroporation of CD4+ T cells with different doses of CXCR4-targeted RNPs. Doses of recombinant Cas9 that correspond to equivalent Cas9 molecules per cell as EV delivery and equivalent Cas9 editing efficiencies as EVs are highlighted in light and dark grey, respectively. Background subtraction was performed using an untreated control; treatment of T cells with RNPs complexed with a non-targeted sgRNA produces similar levels of apparent CXCR4 editing as did the untreated controls, likely indicating that these conditions both represent noise associated with this assay. d, Distributions of RNP-mediated edits, by type, as described in Fig. 5. The no treatment, non-diluted CXCR4 sgRNA treatment (maximum editing), and 500x sgRNA dilution (similar editing frequency as EV-mediated delivery of Cas9-sgRNA) conditions are shown.

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Stranford, D.M., Simons, L.M., Berman, K.E. et al. Genetically encoding multiple functionalities into extracellular vesicles for the targeted delivery of biologics to T cells. Nat. Biomed. Eng (2023). https://doi.org/10.1038/s41551-023-01142-x

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