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Crosslinked ionizable lipids reprogram dendritic cell metabolism for potent mRNA vaccination

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Abstract

Modulating metabolism in immune cells is an effective approach to induce desired immune responses. Here we develop a lipid nanoparticle (LNP) capable of metabolic reprogramming of dendritic cells for mRNA vaccine applications. Using imidoester-based conjugation chemistry, we design a crosslinked ionizable lipid, C12-2aN, which possesses intrinsic metabolic modulatory properties. This multifunctional ionizable lipid not only promotes effective mRNA expression by facilitating endosomal escape but also stimulates glycolysis through mTORC2 pathway activation. As both an mRNA carrier and a metabolic modulator, C12-2aN LNPs lead to potent vaccine efficacy in both SARS-CoV-2 and OVA cancer vaccine models, resulting in stronger neutralization of pseudovirus infection and improved survival rates, respectively, compared with control LNPs without the crosslinker. Moreover, C12-2aN LNPs outperformed FDA-approved LNPs in terms of reduced off-target delivery and lower immunogenicity. Overall, the integration of mRNA delivery and metabolic reprogramming induced by the ionizable lipid component presents significant potential for next-generation mRNA LNP vaccines.

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Fig. 1: Design and evaluation of an imidoester crosslinker-based ionizable lipid library for dendritic cell mRNA transfection.
Fig. 2: Structural simulation and in vitro mRNA delivery evaluation of amine-N-based ionizable lipids.
Fig. 3: C12-2aNP-mediated in vitro metabolic reprogramming of dendritic cells.
Fig. 4: C12-2aNP-mediated in vivo metabolic reprogramming of dendritic cells and alleviation of LNP-related side effects.
Fig. 5: Immune responses induced by spike protein RBD mRNA-loaded C12-2aNP for SARS-CoV-2 vaccination in mice.
Fig. 6: Immune responses induced by OVA-mRNA-loaded C12-2aNP for cancer vaccination in mice.

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Data availability

The data supporting the findings of this study are available within the Article and its Supplementary Information. Bulk RNA-sequencing data have been deposited in the NCBI Sequence Read Archive (accession number PRJNA1183400). Single-cell RNA-sequencing data has been deposited in the NCBI Sequence Read Archive (accession number PRJNA1314823). Source data are provided with this paper.

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Acknowledgements

M.J.M. acknowledges support from an American Cancer Society Research Scholar Grant (RSG-22-122-01-ET). E.L.H., A.M.M. and E.F. acknowledge support from an NSF Graduate Research Fellowship (award number 1845298). Data for this manuscript were generated in the University of Pennsylvania’s CDB Microscopy Core and Small Animal Imaging Core Facility (RRID:SCR_022385). Data were also generated in the Penn Cytomics and Cell Sorting Shared Resource Laboratory at the University of Pennsylvania (RRID: SCR_022376) and the Pancreatic Islet Cell Biology Core, which is supported by the University of Pennsylvania Diabetes Research Center (DRC).

Author information

Author notes

  1. These authors contributed equally: Dongyoon Kim, Ningqiang Gong.

Authors and Affiliations

  1. Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA

    Dongyoon Kim, Ningqiang Gong, Emily L. Han, Jinjin Wang, Ellie Feng, Amanda M. Murray, Qiangqiang Shi, So-Jeong Moon, Kaitlin Mrksich & Michael J. Mitchell

  2. Department of Pharmacy, Yonsei University, Incheon, Republic of Korea

    Dongyoon Kim

  3. Department of Integrative Biotechnology, Yonsei University, Incheon, Republic of Korea

    Dongyoon Kim

  4. Department of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Mohamad-Gabriel Alameh

  5. Department Key Laboratory of Structure-Based Drug Design and Discovery of Ministry of Education, Shenyang Pharmaceutical University, Shenyang, China

    Hanxun Wang

  6. Department of Chemistry, University of Pennsylvania, Philadelphia, PA, USA

    Il-Chul Yoon

  7. Department of HY-KIST Bio-Convergence, Hanyang University, Seoul, Republic of Korea

    So-Jeong Moon

  8. Penn Institute for RNA Innovation, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Drew Weissman & Michael J. Mitchell

  9. Cardiovascular Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Drew Weissman & Michael J. Mitchell

  10. Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Michael J. Mitchell

  11. Institute for Regenerative Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Michael J. Mitchell

  12. Abramson Cancer Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Michael J. Mitchell

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Contributions

D.K., N.G. and M.J.M. conceived the project and designed the experiments. The experiments were performed by D.K., N.G., M.-G.A., E.L.H., I.-C.Y., H.W., E.F., Q.S. and S.-J.M. and interpreted by all authors. D.K. prepared the figures and wrote the manuscript. D.K., E.L.H., J.W., A.M.M., E.F., K.M., D.W. and M.J.M. edited and revised the manuscript. All authors reviewed the manuscript and figures and approved the final version for submission.

Corresponding author

Correspondence to Michael J. Mitchell.

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Competing interests

D.K., N.G. and M.J.M. have filed a patent on the LNP technology discussed in this manuscript (application no. PCT/US25/51511). The remaining authors declare no competing interests.

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Nature Materials thanks John T. Wilson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Information (download PDF )

Supplementary Notes 1–5, Figs. 1–39, methods, discussion and references.

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Source data

Source Data Fig. 1 (download XLSX )

Statistical source data for the lipid-screening results.

Source Data Fig. 2 (download XLSX )

Statistical source data for the lipid-screening results.

Source Data Fig. 3 (download XLSX )

Statistical source data for the cellular metabolic activity results.

Source Data Fig. 4 (download XLSX )

Statistical source data for the in vivo biodistribution and safety analysis.

Source Data Fig. 5 (download XLSX )

Statistical source data for the SARS-CoV-2 vaccine study.

Source Data Fig. 6 (download XLSX )

Statistical source data for the cancer vaccine study.

Source Data Fig. 3 (download JPG )

Unprocessed western blots.

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Kim, D., Gong, N., Alameh, MG. et al. Crosslinked ionizable lipids reprogram dendritic cell metabolism for potent mRNA vaccination. Nat. Mater. (2026). https://doi.org/10.1038/s41563-026-02512-x

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