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Enantiomer-dependent and modification-free DNA matrix as an adjuvant for subunit vaccines against SARS-CoV-2 or pneumococcal infections

Nature Biomedical Engineering volume 9, pages 2043–2067 (2025) Cite this article

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Abstract

The emergence of novel infectious disease has intensified demand for more advanced vaccine development and more potent adjuvants to enhance immunogenicity. Here we introduce a dynamic DNA supramolecular matrix assembled from five unmodified, short DNA single strands, serving as a safe, multifaceted adjuvant platform. This DNA matrix elicits a robust humoral response with minimal adverse effects, generating potent neutralizing antibodies and conferring robust protection against SARS-CoV-2 and Streptococcus pneumoniae infections. Its dynamic colloidal feature prolongs the in vivo retention of both DNA and antigen, facilitating lymphatic-targeted transportation and presentation. This process leads to a robust pro-inflammatory response in both the vaccinated site and draining lymph node, which, in turn, promotes the recruitment and activation of immune cells, leading to a rapid, effective antigen-specific antibody response. The enhanced function of DNA matrix depends on the canonical TLR9–MyD88 signalling axis in dendritic cells. In addition, only right-handed, not left-handed, chirality of the DNA strands forms d-DNA matrix and promotes immune activations. Thus, this DNA matrix functions as an all-in-one adjuvant platform, opening promising avenues for future vaccine design.

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Fig. 1: DNA matrix is a safe potent adjuvant for subunit vaccines.
The alternative text for this image may have been generated using AI.
Fig. 2: DNA matrix promotes prophylactic efficacy of vaccine.
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Fig. 3: DNA matrix enhances lymphatic-targeted transport and prolongs retention.
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Fig. 4: DNA matrix disintegration into nanoclusters enhances phagocytosis and cellular activation.
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Fig. 5: Dynamic DNA matrix efficiently activates innate immune responses in the dLN, promoting adaptive immune responses.
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Fig. 6: The adjuvanticity of DNA matrix depends on the TLR9–MyD88 pathway.
The alternative text for this image may have been generated using AI.
Fig. 7: The innate responses induced by DNA matrix through the TLR9–MyD88 pathway in DCs are essential for adjuvanticity.
The alternative text for this image may have been generated using AI.
Fig. 8: DNA matrix activates immune response in a modification-free but enantiomer- and multiple CG sequence-dependent manner.
The alternative text for this image may have been generated using AI.

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Data availability

The RNA-seq data generated in this study are available via the Gene Expression Omnibus under accession number GSE290067 (ref. 110). All data supporting the results in this study are available within the paper and its Supplementary Information. Source data are provided with this paper.

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Acknowledgements

We thank W. Mo (Xiamen University) for the ZBP-1-TKO mice; L. Wu (Tsinghua University) for the AIM2-TKO and K5-Cre mice; H. Yin (Tsinghua University) for the cGAS-TKO; Z. Jiang (Peking University) for STING-TKO mice; X. Hu (Tsinghua University) for the TLR2-TKO mice; H. Qi (Tsinghua University) for the CCR5-TKO and CCR7-TKO mice; J.-R. Zhang (Tsinghua University) for the TRIF-TKO, CCR2-TKO and TLR7- TKO mice; Q. Sun (Sun Yat-sen University) for the TLR9-TKO mice, which were established by S. Wan (Gannan Medical College); B. Hou (Chinese Academy of Science Institute of Biophysics) for the MyD88flox/flox and CD11c-Cre mice. We acknowledge the Laboratory Animal Resource Center at Tsinghua University for assistance with animal experiments. We thank E. Kong (Xinxiang Medical University) for the CAL-1 cell line. We thank B. Hou (Chinese Academy of Science Institute of Biophysics), M. Zhu (Chinese Academy of Science Institute of Biophysics), Y. Xiang (Tsinghua University), W. Zeng (Tsinghua University) and Y. Shi (Tsinghua University) for scientific discussions. We thank J. Wang (Tsinghua University) and J.-R. Zhang (Tsinghua University) for support with mice infection experiments; F. Pei and X. Zheng (Beijing Bio-Institute Biological Products Co., Ltd.) for supporting with neutralizing antibody detection; and J. Bi and J. Yang (Tsinghua University) for support with research on mechanism. This work was supported by grants from the Ministry of Science and Technology of China Grants (2021YFC2302403 to C.L., 2021YFC2300500 to W.L., 2022YFA1206400 to Y.R.Y. and 2022YFC2303400 to J.L.), the National Natural Science Foundation of China (32141004 to W.L., 81825010 to W.L., 21821001 to D.L., 21890731 to D.L., 21534007 to D.L., 22277017 to Y.R.Y. and 92169210 to J.L.), the Beijing Natural Science Foundation (23Z30090 to W.L.), the Strategic Priority Research Program of Chinese Academy of Sciences (XDB0770000 to Y.R.Y.). This work was also supported by research funds from the Tsinghua University Spring Breeze Fund, Center for Life Sciences, Institute for Immunology at Tsinghua University, and Vanke School of Public Health at Tsinghua University.

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  1. These authors contributed equally: Cuifeng Li, Yuxin Li, Bini Zhou, Tong Li, Xiaohui Wei.

Authors and Affiliations

  1. The First Affiliated Hospital of Anhui Medical University and Institute of Clinical Immunology, Anhui Medical University, Hefei, China

    Cuifeng Li

  2. State Key Laboratory of Membrane Biology, School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Institute for Immunology, China Ministry of Education Key Laboratory of Protein Sciences, Beijing Key Lab for Immunological Research on Chronic Diseases, Beijing Tsinghua Changgung Hospital, Tsinghua University, Beijing, China

    Cuifeng Li, Yuxin Li, Tong Li, Jiachen Zhang, Zhenglin Ji, Wenbo Sun, Ji Gao, Xin Min & Wanli Liu

  3. Engineering Research Center of Advanced Rare Earth Materials (Ministry of Education), Department of Chemistry, Tsinghua University, Beijing, China

    Bini Zhou, Yujie Li, Chenyou Zhu, Bo Yang & Dongsheng Liu

  4. NHC Key Laboratory of Human Disease Comparative Medicine, Beijing Key Laboratory for Animal Models of Emerging and Reemerging Infectious Diseases, Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences and Comparative Medicine Center, Peking Union Medical College, Beijing, China

    Xiaohui Wei, Jing Wu, Binbin Zhao, Jing Xue & Jiangning Liu

  5. CAS Key Laboratory of Nanosystem and Hierarchical Fabrication, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Beijing, China

    Kun Chen & Yuhe R. Yang

  6. State Key Laboratory of Chemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing, China

    Wenlong Chen, Xiaobin Dai & Li-Tang Yan

  7. CAS Key Laboratory of Colloid Interface and Chemical Thermodynamics, Institute of Chemistry, Chinese Academy of Sciences, Beijing, China

    Ziwei Shi

  8. University of Chinese Academy of Sciences, Beijing, China

    Ziwei Shi & Yuhe R. Yang

  9. Center for Infectious Disease Research, School of Medicine, Tsinghua University, Beijing, China

    Chen Yang & Qiang Ding

  10. CAS Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China

    Lin Lin & Baidong Hou

  11. CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences, Beijing, China

    Wei Yang, Min Wang & Yi Shi

  12. Key Laboratory of Medical Molecular Virology (MOE/NHC/CAMS), School of Basic Medical Sciences; Shanghai Institute of Infectious Disease and Biosecurity; Biosafety Level 3 Laboratory, Shanghai Medical College, Shanghai Frontiers Science Center of Pathogenic Microbes and Infection, Fudan University, Shanghai, China

    Zezhong Liu & Lu Lu

  13. Department of Basic Medical Sciences, Center for Infectious Disease Research, School of Medicine, Tsinghua University, Beijing, China

    Yaping Liu & Linqi Zhang

  14. Key Lab of Organic Optoelectronics and Molecular Engineering, Department of Chemistry, Tsinghua University, Beijing, China

    Jiang-Fei Xu

  15. Laboratory of Dynamic Immunobiology, Institute for Immunology, Tsinghua University, Beijing, China

    Hai Qi

  16. Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hong Kong, China

    Dongsheng Liu

  17. PolyU Shenzhen Research Institute, The Hong Kong Polytechnic University, Shenzhen, China

    Dongsheng Liu

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  1. Cuifeng Li
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Contributions

W.L., D.L., Y.R.Y., J.L., C.L. and Yuxin Li designed the experiments. C.L., Yuxin Li, T.L. and B. Zhou performed the majority of the experiments and analysed the data. X.W., K.C., W.C., Z.S., X.D., J.Z., C.Y., Z.J., W.S., J.G., J.W., B. Zhao, X.M., Yujie Li, L. Lin, W.Y., M.W., Z.L., Y. Liu, C.Z., B.Y., J.-F.X. and L.-T.Y. contributed to specific experiments and data analysis. Y.S., L. Lu, L.Z., Q.D., J.X., B.H. and H.Q. contributed to the design of the experiments. W.L., D.L., Y.R.Y., C.L., Yuxin Li. and B. Zhou wrote the paper. All authors read and approved the contents of the paper.

Corresponding authors

Correspondence to Jiangning Liu, Yuhe R. Yang, Dongsheng Liu or Wanli Liu.

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The authors declare no competing interests.

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Nature Biomedical Engineering thanks Ju Hee Ryu, John Wilson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Assessment of DNA matrix adjuvant function.

a, OVA-specific IgG subtypes. Mice (n = 4/group) were i.pl. immunized with OVA ± DNA matrix, Alum, or CpG (20 μg) on day 0. Sera were collected on day 14. b and c, Flow cytometry analysis and quantification of percentage of IL-4+ and IFN-γ+ cells in CD4 T cells from pLNs 10 d.p.i. Mice (n = 6/group) were i.pl. immunized with OVA ± DNA matrix, Alum, or CpG (20 μg). d, OVA-specific IgG titers for C57BL/6 mice or BALB/c mice on day 14 post i.pl. immunization with OVA alone, or together with DNA matrix (n = 6/group). e, NP-specific IgG3 titers for C57BL/6 mice on day 14 post i.pl. immunization with NP12-ficoll (10 μg) ± DNA matrix (1.07 mg) (n = 6/group). f, Anti-DNA IgG titers were quantified. C57BL/6 mice (n = 5/group) were immunized with SARS-CoV-2 HexaPro Spike-trimer (5 μg) (i.pl.) ± DNA matrix or Alum on days 0, 14, 100, and 200. Sera were collected on day 214 to monitor DNA-specific binding IgG. Calf thymus DNA fragments were used for plate coating. Serum from murine SLE model was used as the positive control to detect DNA specific IgG (n = 3). g and h, Effects of different treatment on thermal hyperalgesia of C57BL/6 mice. Mice were i.pl. immunized by OVA ± Alum (1:1), DNA matrix or CFA (1:1), were measured by hot plate at indicated time points (g) or specified at 72 h (h) (n = 3/group). Data are shown as mean ± s.e.m. Statistical significance was determined by unpaired two-tailed t test (a, e, h), one- way ANOVA (c, f) or two-way ANOVA with Tukey correction (d, g). Data are representative of at least two independent experiments.

Source data

Extended Data Fig. 2 DNA matrix improve the delivery of DNA molecules and antigen.

a, Image of denature gel electrophoresis: main bands (blue rectangle), degraded bands (orange rectangle). The quantitative analysis of band intensity was shown. 10 μL DNA matrix, or DNA solution (Y) with equimolar amounts was incubated with an equal volume of FBS at 37 °C for 24 h or 72 h, respectively. Degradation status was measured by gel electrophoresis. b, Image of gold nanoparticle diffusion. c, Quantification of OVA retention in vitro. DNA matrix was mixed with OVA (100 μg), and PBS (100 μL) was added to the upper layer. OVA in supernatant was monitored. d, Quantification of total radiant efficiency of Cy5.5 in kidney, liver, and iLN. C57BL/6 mice were sacrificed at 12 h or 36 h after i.pl. injection with Cy5.5-labeled DNA solution (L) (1.07 mg) or Cy5.5-labeled DNA matrix (1.07 mg), respectively. Indicated organs were collected and subjected to an IVIS Spectrum system (n = 3/group). e-h, Detection of in vivo distribution of antigen. C57BL/6 mice (n = 3/group) were i.pl. injected with OVA-Cy5 (5 μg) alone, or together with DNA solution (Y) (1.07 mg) or DNA matrix (1.07 mg). Tissues were collected at 48 h.p.i. e, Representative IVIS images of pLN and quantification of total radiant efficiency of Cy5 in pLNs. f, Gating strategies of flow cytometry analysis for g and h. g, Flow cytometry analysis and percentages of OVA-Cy5+ cells in dLNs (n = 3/group) 48 h.p.i. h, Numbers of total OVA-Cy5+ cells, OVA-Cy5+ B cells, and OVA-Cy5+ DCs in dLNs (n = 3/group) 48 h.p.i. Data are shown as mean ± s.e.m. Statistical significance was determined by two-way ANOVA (d) or one-way ANOVA with Tukey correction (e, h). Data are representative of two independent experiments.

Source data

Extended Data Fig. 3 DNA matrix disintegrate into nanoclusters and promote antigen internalization.

a, Correlation function of adjuvant DNA in the supernatant after soaking in PBS for 4-72 hours in vitro. b, Dynamic light scattering (DLS) analysis of particle size distribution of adjuvant DNA in the supernatant after soaking in PBS supplemented with 10 % FBS for 4-72 hours in vitro. c, Schematic of the Y-scaffold and linker DNA building blocks. d, Graphical representation of the patchy particle model. e, The initial state of the simulation system. f, The DNA matrix network formed after 107 times steps. The box size is 100σ × 100σ × 100σ. Data are representative of three independent experiments. g, Schematic diagram of stimulation and sample collection schedule for h. BMDCs were incubated with OVA-FITC (10 μg / mL) and DNA matrix (1, 10, or 100 μg / mL). Samples were collected at 5 min, 30 min, 60 min, and 120 min later. h, Flow cytometry analysis and quantification of OVA-FITC (MFI) in BMDCs (n = 3/group). i, Representative image of immunofluorescence staining (left panel) of BMDCs. BMDCs were collected after incubation with OVA-FITC (10 μg / mL) and Cy5.5-DNA matrix (100 μg / mL) for 30 min, fixed with 4 % PFA, and stained with DAPI (blue). Scale bars are 5 μm. Correlation between OVA and DNA matrix was determined by Pearson’s correlation coefficient (right panel) (n = 15). Data are shown as mean ± s.e.m. Partial element created in BioRender.com (g). Statistical significance was determined by two-way ANOVA with Tukey correction (h). Data are representative of two independent experiments.

Source data

Extended Data Fig. 4 DNA matrix induce efficient innate responses.

a-d, mRNA expression of IL-1β, CCL4, IL-6 and IFN-β in footpads were measured by RT-qPCR (n = 3/group). RNA was isolated from footpads of mice post i.pl. immunization with DNA matrix (1.07 mg) or Alum (1:1) at indicated time points. e, mRNA expression of IL-1β, CCL4, IL-6 and CCL2 in footpads was measured by RT-qPCR (n = 3/group). RNA was isolated from footpads of mice 12 h post i.pl. immunized with DNA matrix (1.07 mg), DNA solution (L) (1.07 mg), or DNA solution (Y) (1.07 mg) (n = 3/group). Data are shown as mean ± s.e.m. Statistical significance was determined by two-way ANOVA with Tukey correction (e). Data are representative of two independent experiments.

Source data

Extended Data Fig. 5 DNA matrix leads to LN expansion by recruiting circulating lymphocytes, and directly activates DCs.

C57BL/6 mice were i.pl. immunized with DNA solution (Y) (1.07 mg) or DNA matrix (1.07 mg), respectively. 12 h or 36 h after injection, cells from popliteal LNs were harvested and subjected to flow cytometry analysis (n = 3/group). a, Total cell number of popliteal LNs were counted 12 h.p.i. b, Flow cytometry analysis of macrophages (F4/80+), B cells (B220+), and DCs (B220- F4/80- CD11c+ MHCII+) of pLNs 36 h.p.i. c and d, Flow cytometry analysis and quantification of resident DC and migratory DCs in pLN 36 h after DNA solution (Y) or DNA matrix injection. e, Flow cytometry analysis of MFI of CD86 in B cells (F4/80- B220+) in pLNs 36 h.p.i with Cy5.5 labelled DNA matrix. Data are shown as mean ± s.e.m. Statistical significance was determined by one-way ANOVA (a) or two-way ANOVA (d) with Tukey correction. Data are representative of three independent experiments.

Source data

Extended Data Fig. 6 DNA matrix induces quick and efficient innate responses in pLNs.

a-d, mRNA expression of IL-1β, CCL4, IL-6 and IFN-β in pLNs were measured by RT-qPCR (n = 3/group). RNA was isolated from pLNs of mice post i.pl. immunization with DNA matrix (1.07 mg) or Alum (1:1) at indicated time points. e, Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway analysis of upregulated DEGs in DNA matrix group compared with PBS control. f and g, mRNA expression of IL-6 and IL-12b in BMDCs were measured by RT-qPCR (n = 3/group). BMDCs were pretreated with or without R406 (2.5 μM) for 30 min, and then stimulated with or without DNA matrix (10 μg/mL) for another 6 hours. Data are shown as mean ± s.e.m. Statistical significance was determined by two-way ANOVA with Tukey correction (f, g). Data are representative of two independent experiments.

Source data

Extended Data Fig. 7 The adjuvanticity of DNA matrix does not depend on CCR5, CCR2, or TLR2 pathway.

a and b, OVA-specific IgG titers was measured by ELISA. WT, MyD88 TKO and TLR9 TKO C57BL/6 mice were i.pl. immunized with OVA (100 μg) combined with Alum (1:1) on day 0 and day 14, and then serum was collected on day 21 (n = 4 or 5/group). c and d, OVA-specific IgG titers were measured by ELISA. WT and TLR2 KO (n = 3/group) (c) or chemokine receptors KO (n = 6 in CCR5 KO group, n = 4 in CCR2 KO group) (d) mice were i.pl. immunized with OVA (100 μg) combined with DNA matrix (1.07 mg). After 14 days, serum was collected for ELISA. Data are shown as mean ± s.e.m. Statistical significance was determined by unpaired two-tailed t-test (a-d). Data are representative of two independent experiments.

Source data

Extended Data Fig. 8 DNA matrix-induced innate responses in dLN are dependent on TLR9-MyD88 pathway.

a, Statistical analysis of average radiant efficiency of various tissues of Fig. 7b (n = 3/group). b, Statistical analysis of average radiant efficiency of pLNs of Fig. 7c (n = 4/group). c and d, Proportion (c) and MFI (d) of DNA cy5.5+ cells in pLN analyzed by flow cytometry was quantified (n = 3/group). WT or MyD88 KO mice were i.pl. immunized with Cy5.5-labeled DNA matrix (1.07 mg), and pLN were collected 36 h later. e, mRNA expression of IL-1β, CCL4, and CCL2 in footpad was measured by RT-qPCR (n = 3/group). RNA was isolated from footpad of WT or MyD88 KO mice 12 h post i.pl. immunization with DNA matrix (1.07 mg). f and g, Representative fluorescence IVIS image (f) and statistical analysis of average radiant efficiency (g) of various tissues. Tissues were collected from WT and TLR9 TKO mice (n = 3/group) 36 h post injection (i.pl.) with Cy5.5-DNA matrix. h, Correlation between TLR9 and DNA matrix was determined by Pearson’s correlation coefficient (n = 20). i, BLI analysis showing the binding and dissociation curves of CpG ODN with mTLR9 protein. Data are shown as mean ± s.e.m. Statistical significance was determined by unpaired two-tailed t-test (b-d) or one-way ANOVA with Tukey correction (e). Data are representative of two independent experiments.

Source data

Extended Data Fig. 9 DNA matrix induce immunostimulation in human cells.

a, mRNA expression of murine TLR9 in reference populations. Data are obtained from ImmGen ULI RNASeq database. b, mRNA expression of human TLR9 in reference populations. Data are obtained from the Human Protein Atlas database. c, mRNA expression of IL-6, TNF-α and CCL4 in hPBMCs was measured by RT-qPCR (n = 3/group). hPBMCs were pretreated with or without CQ (10 μM) for 30 min, followed by stimulation with or without DNA matrix (100 μg/mL) for another 6 hours. d, mRNA expression of IL-6, TNF-α and CCL4 in CAL-1 was measured by RT-qPCR (n = 3/group). CAL-1 cells were exposed to human GM-CSF (10 ng/mL) for 3 days, and then pretreated with or without CQ (10 μM) for 30 min, followed by stimulation with or without DNA matrix (100 μg/mL) for 3 hours. Data are shown as mean ± s.e.m. Statistical significance was determined by one-way ANOVA with Tukey correction (c and d). Data are representative of two independent experiments.

Source data

Extended Data Fig. 10 DNA matrix induced higher antibody response in a multiple CG sequences-dependent manner.

a, mRNA expression of indicated genes in footpad (n = 3/group). b and c, The molecular weight and sequence information of ssDNA in DNA matrix-12 and DNA matrix-56, respectively. Purple colored sequences are sticky ends, and red colored sequences are sequences of CpG 1018 and poly (dA:dT). d, mRNA expression of IL-6, IL-1β and CCL4 in BMDCs was measured by RT-qPCR (n = 3/group). BMDCs were stimulated with 1 mg / mL DNA matrix, DNA matrix-12, or DNA matrix-56 for 6 hours. e, Schematic diagram of inversion CG to GC in Y1 and Y2 ssDNA to form GC-DNA matrix. f, The molecular weight and sequence information of ssDNA in GC-DNA matrix. Purple colored sequences are sticky ends and yellow highlighted parts are single GC-swapped sequences resembling known CpG sequence. g, Schematic diagram of experimental design for Fig. 8l. C57BL/6 mice were i.pl. immunized with OVA (100 μg) alone, or together with original DNA matrix (CG) or GC-DNA matrix on day 0. Sera were collected on day 14. h, The molecular weight and sequence information of ssDNA in tGC-DNA matrix. Red colored sequences are GC-swapped positions. i, OVA-specific IgG titers in sera were measured (n = 6/group). C57BL/6 mice were i.pl. immunized with OVA (100 μg) alone, or together with DNA matrix (300 μg) or CpG DNA (PD) (300 μg) in a total volume of 10 μL on days 0. Sera were collected on day 14 for ELISA. Data are shown as mean ± s.e.m. Partial elements were created in BioRender.com (e, g). Statistical significance was determined by one-way ANOVA (i) or two-way ANOVA (a) with Tukey correction. Data are representative of two independent experiments.

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Li, C., Li, Y., Zhou, B. et al. Enantiomer-dependent and modification-free DNA matrix as an adjuvant for subunit vaccines against SARS-CoV-2 or pneumococcal infections. Nat. Biomed. Eng 9, 2043–2067 (2025). https://doi.org/10.1038/s41551-025-01431-7

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