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Pro-regenerative biomaterials recruit immunoregulatory dendritic cells after traumatic injury

Nature Materials volume 23, pages 147–157 (2024)Cite this article

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Abstract

During wound healing and surgical implantation, the body establishes a delicate balance between immune activation to fight off infection and clear debris and immune tolerance to control reactivity against self-tissue. Nonetheless, how such a balance is achieved is not well understood. Here we describe that pro-regenerative biomaterials for muscle injury treatment promote the proliferation of a BATF3-dependent CD103+XCR1+CD206+CD301b+ dendritic cell population associated with cross-presentation and self-tolerance. Upregulation of E-cadherin, the ligand for CD103, and XCL-1 in injured tissue suggests a mechanism for cell recruitment to trauma. Muscle injury recruited natural killer cells that produced Xcl1 when stimulated with fragmented extracellular matrix. Without cross-presenting cells, T-cell activation increases, pro-regenerative macrophage polarization decreases and there are alterations in myogenesis, adipogenesis, fibrosis and increased muscle calcification. These results, previously observed in cancer progression, suggest a fundamental mechanism of immune regulation in trauma and material implantation with implications for both short- and long-term injury recovery.

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Fig. 1: Pro-regenerative and pro-fibrotic materials recruit a diverse range of innate immune cells.
Fig. 2: BATF3-dependent cross-presenting dendritic cells are enriched by pro-regenerative scaffolds and peak by 7 days post-injury.
Fig. 3: Pro-regenerative materials induce a mixed type-2/regulatory lymphocyte phenotype that regulates scavenger receptor expression on macrophages and dendritic cells.
Fig. 4: Loss of cross-presenting cells results in over-activation of T cells and attenuation of pro-regenerative macrophage polarization.
Fig. 5: Upregulation of XCL-1 in NK cells and E-cadherin in muscle infiltrate is associated with tissue damage and material implantation.
Fig. 6: BATF3 regulates post-injury tissue development including myogenesis, adipogenesis, fibrosis and calcification.

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Data availability

Data generated or analysed during this study are provided in the Supplementary Information. Further data are available from the corresponding author upon request. Source data are provided with this paper.

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Acknowledgements

We would like to thank R. Germain, Y. Belkaid, M. Wolf, R. Tussiwand and B. Warner for helpful conversations, and V. Sundaresan for organizational assistance and review of the manuscript. We also acknowledge M. Bur and L. Portnoy for oversight of the animal study protocols. This work was funded by the intramural research program of the National Institute of Biomedical Imaging and Bioengineering, NIH. The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views, opinions or policies of the NIH and the Department of Health and Human Services (HHS). Mention of trade names, commercial products or organizations does not imply endorsement by the US Government.

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Author notes

  1. These authors contributed equally: Ravi Lokwani, Aditya Josyula, Tran B. Ngo.

Authors and Affiliations

  1. Section on Immunoengineering, Biomedical Engineering and Technology Acceleration Center, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA

    Ravi Lokwani, Aditya Josyula, Tran B. Ngo, Sabrina DeStefano, Daphna Fertil, Mondreakest Faust, Kenneth M. Adusei, Minhaj Bhuiyan, Aaron Lin, Maria Karkanitsa, Efua Maclean, Parinaz Fathi & Kaitlyn Sadtler

  2. Unit for Nanoengineering and Microphysiological Systems, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA

    Aaron Lin & Parinaz Fathi

  3. Advanced Imaging and Microscopy Resource, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, USA

    Yijun Su, Jiamin Liu & Harshad D. Vishwasrao

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Contributions

Conceptualization: K.S. Methodology and investigation: R.L., T.B.N., S.D., D.F., K.M.A., M.B., A.J., A.L., M.F., M.K., E.M., P.F., H.D.V. and K.S. Data analysis: R.L., T.B.N., D.F., A.J., P.F., Y.S., J.L., H.D.V. and K.S. Writing (original draft): R.L. and K.S. Writing (review and editing): R.L., T.B.N., A.J., M.K. and K.S. Funding and supervision: K.S.

Corresponding author

Correspondence to Kaitlyn Sadtler.

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Competing interests

R.L., T.B.N. and K.S. have filed a provisional US patent application (US63/367,994) related to the work described in this paper. The remaining authors declare no competing interests.

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Extended data

Extended Data Fig. 1 Material preparation and injury model.

(a) Protein profile of native versus decellularized ECM via SDS-PAGE and Coomassie blue stain. (b) Double stranded DNA (dsDNA) quantification in native, mechanically scraped, and decellularized tissue as a function of starting tissue weight (n = 2, native; n = 3, scraped and decell), ANOVA with Tukey’s posthoc correction for multiple comparisons. (c–e) Hematoxylin and eosin (H&E) staining of native (c), mechanically scraped (d), and decellularized (e) tissue with inset of picrosirius red brightfield and polarized light of final product. (f) ECM powder pre-hydration (g) polyethylene powder. (h) Image of injury generated in quadriceps muscle group with (i) application of ECM scaffold after injury. (j) Sheet form ECM at 7 days post-injury (dpi) showing retention in injury space. (k) Cleared tissue light sheet microscopy of control injury space at 63 dpi showing permanent loss of volume at injury site. (l) Light sheet image of ECMtx muscle injury at 7 dpi. Representative of n = 3 mice. (m) H&E of injury-material interface at 7-, 21-, and 42-days post-injury. Scale bar = 500 μm. (n) Muscle weight (n = 3, control; n = 4 ECMtx) Mann−Whitney test (two-tailed). (o) grip strength (n = 3) at 63 dpi. Mann-Whitney test (two-tailed). (p) Gene expression (n = 4, ECMtx; n = 5 PEtx) of Gli1 (p = 0.012) and Col1a1 (p = 0.013). ANOVA with Šídák’s multiple comparisons test. (q) Picrosirius red (PSR) staining of polyethylene particles at 7-, 21-, and 42-dpi at the capsule (skin facing), center of implant, and muscle interface. (r) Transverse histopathologic comparison (H&E) of an uninjured quadriceps (top) versus an injured muscle with ECM at 7 days post injury (bottom). (s) Example of PSR image processing for quantification. (t) Brightfield quantification of PSR staining. ANOVA with Tukey’s posthoc correction for multiple comparisons (u) Red (dense collagen) channel staining index in polarized light. ANOVA with Tukey’s posthoc correction for multiple comparisons (v) Green (less dense collagen) channel staining index in polarized light (h – j, n = 3 mice averaged from n = 5 fields of view per mouse). Data are means ± SEM. * = P < 0.05, ** = P < 0.01, *** = P < 0.001.

Source data

Extended Data Fig. 2 Immune cell populations over time.

Immune cell infiltration as a proportion of live CD45+ immune cells. (a) 3 (b) 7 (c) 21 (d) 42 days post-injury. N = 5 mice. (e) Major myeloid populations at 7 days in ECM particulate/powder (white) versus intact sheets (blue), n = 5 mice. (f) Hematoxylin and Eosin (H&E) of muscle-implant interface and ECM-capsule interface. (g) Major myeloid populations at 7 days in PE particulate (white, n = 5 mice) versus large (>2 mm, blue, n = 2 mice) beads (h) Picrosirius red (left) and H&E (right) of large 2 mm beads. Box plots are median with interquartile range, whiskers are minimum to maximum. ANOVA with Tukey post-hoc correction for multiple comparisons (a – d) or Šídák’s multiple comparisons test (e, g). * = P < 0.05, ** = P < 0.01, *** = P < 0.001, **** = P < 0.0001.

Source data

Extended Data Fig. 3 Phenotyping markers of macrophages and dendritic cells.

(a) MHCII+ antigen presenting cells in the wound microenvironment at 7 days post injury as a proportion of live CD45 + MHCII+ cells, n = 5 (b) MHCII+ macrophages (F4/80 + CD68 + MHCII+) (c) MHCII- Macrophages (F4/80 + CD68 + MHCII-) (d) DCs (CD11c+MHCII+). Black/grey = control injury; teal = ECMtx injury; pink = PEtx injury. Bars are mean for b – d. (e) CD103 mean fluorescence intensity, and (f) XCR1 mean fluorescence intensity on dendritic cells (black), MHCII+ macrophages (blue), and MHCII- macrophages (yellow). (a–f) n = 4 mice, control; n = 5 uninjured, ECMtx, PEtx. (g) Hierarchical clustering of FlowSOM-derived cell populations, Normalized min = 0, max = 100. Box plots are median with interquartile range, whiskers are minimum to maximum. ANOVA with Tukey post-hoc correction for multiple comparisons. * = P < 0.05, ** = P < 0.01, *** = P < 0.001, **** = P < 0.0001.

Source data

Extended Data Fig. 4 Dendritic cell profiling in injury space.

(a) Dendritic cell phenotyping by CD103 and XCR1 expression in CD11c+MHCIIhi DCs at 3−, 7-, 21−, and 42-days post-injury. (n = 5 mice, ANOVA with Tukey’s post-hoc correction for multiple comparisons) (b) Xcr1 gene expression by RT-PCR in muscle homogenate and single cells isolated from injured muscle. (n = 5 mice, Kruskall-Wallis with FDR correction for multiple comparisons). (c) Representative FACS plots of CD11c+MHCII+ dendritic cells in three treatment groups. Green = XCR1 + CD103+ tDCs; purple = XCR1-CD103− dendritic cells. (d) tDC quantification with particulate and larger geometries (n = 2 mice PE large geometry; n = 5 mice ECMtx and PE particulate, unpaired t-test, two-tailed, not significant). (e) Xcr1 gene expression in WT (black) and Batf3−/− mice (red), (n = 5 mice). Data are means ± SEM, ANOVA with Šídák’s multiple comparisons test. Box plots are median with interquartile range, whiskers are minimum to maximum. * = P < 0.05, ** = P < 0.01, *** = P < 0.001, **** = P < 0.0001. Panel b created with BioRender.com.

Source data

Extended Data Fig. 5 Dendritic cell phenotyping in local tissue, draining lymph node, and peripheral blood.

(a–b) Repeatability of findings across litters and species. XCR1 + CD103+ cells are present in multiple runs with mice from (a) different litters (n = 5 mice per litter, ANOVA with Šídák’s multiple comparisons test) and (b) species (rat data extracted from raw data used generated in PMID 35462366). (c) CD103 + XCR1+ Dendritic cells in the skin overlying a muscle injury at 7 days post-injury in an ECM-treated mouse, as a proportion of CD11c+MHCII+ dendritic cells. (n = 3 skin; and n = 5 muscle, mean ± SEM, unpaired t-test, two-tailed, p = 0.0003) (d) DC expression of CD8α, CD103, and XCR1 in injured muscle tissue (purple), peripheral blood (green), and draining (inguinal) lymph node (blue), n = 5 mice, representative of at least 2 independent experiments. Box plots are median with interquartile range, whiskers are minimum to maximum. * = P < 0.05; ** = P < 0.01, *** = P < 0.001.

Source data

Extended Data Fig. 6 Adaptive immune responses in wild type and Batf3−/− mice.

(a) UMAP of lymphoid populations in muscle at 7 days post-injury. (b) tSNE of lymphoid populations in muscle at 7 days post-injury. (c) Treg populations in peripheral blood at 21 days post-injury, n = 5 mice, ANOVA with Tukey post-hoc correction for multiple comparisons. (d) Treg populations in draining (inguinal) lymph node at 21 days post-injury, n = 5 mice, ANOVA with Tukey post-hoc correction for multiple comparisons. (e) ST2+ regulatory B cells as a proportion of total B cells in the draining lymph node at 7 days post-injury, n = 5 mice (Control, ECM, PE), n = 3 mice (uninjured). WT (black), Batf3-/- (red), Uninjured WT (grey), ANOVA with Šídák’s multiple comparisons test (f) Activation phenotype of T cells in uninjured muscle versus 7 days post-injury. (g) Cytokine/Chemokine profile, log2 fold change over uninjured control, n = 5 mice. (h) Representative blots quantified in g. (i) RT-PCR of immune genes in muscle injury at 7 days post-injury. (n = 10 mice Il10, Il4, IlTgfb1, Xcl1; n = 5 mice all other genes, ANOVA with Šídák’s multiple comparisons test) (j) Count of Tregs and iTregs in the muscle of WT v Batf3−/− mice at 7 days post-injury, WT (black) Batf3-/- (red) n = 4 mice (PEtx WT) n = 5 mice all others, ANOVA with Šídák’s multiple comparisons test. Data are means ± SEM (panels e, j). Box plots are median with interquartile range, whiskers = minimum to maximum. * = P < 0.05, ** = P < 0.01. *** = P < 0.001. **** = P < 0.0001.

Source data

Extended Data Fig. 7 Systemic immune responses in wild type and Batf3−/− mice.

(a) UMAP (top row) of lymphoid populations in draining lymph node (ILN) at 7 days post-injury. tSNE (bottom row) of lymphoid populations in ILN at 7 days post-injury. (b–d) Proportion of (b) B cells (c) αβ T cells and (d) γδ T cells in ILN in WT v Batf3−/− mice, ANOVA with Šídák’s multiple comparisons test. (e) Proportion of B cells positive for XCR1 and CD103. ANOVA with Šídák’s multiple comparisons test (f) Proportion of γδ T cells positive for XCR1 and CD103, ANOVA with Šídák’s multiple comparisons test. (g) Activation of CD103 + XCR1+ non-myeloid cells over time. (h) Proportion of XCR1 and CD103 positive non-myeloid cells over time. (i) Xcr1 gene expression in CD103 + XCR1 + T and B cells compared to CD103-XCR1− T and B cells; n = 5 mice, Paired t-test, two-tailed. (j) Proportion of T cells that are CD103 + XCR1+ in lymph node (ILN), peripheral blood, and muscle. Control = black, ECMtx = teal, PEtx = pink. Data are means ± SEM, n = 5 mice. Tukey with ANOVA post-hoc (k) Example flow cytometry plot showing CD103 + XCR1 + T cells (blue) versus other T cells (grey). (l–n) Expression of CD103 and XCR1 on (l) CD4+ FoxP3+ (m) CD4 + HELIOS+, and (n) CD8 + HELIOS+ Tregs. Control = black, ECMtx = teal, PEtx = pink. Data are means ± SEM. n = 5 mice (t = 7, 21 days), n = 3 mice (t = 0). (o) Activation of gamma delta T cells in the inguinal lymph node of WT and Batf3−/- mice. Dark blue = active (CD62L-CD44+), Medium blue = central memory (CD62L-CD44-), Light blue = Naïve (CD62L + CD44-). Blood 21 days = active, n = 5. Grey band = range in uninjured mice, n = 3. Data are means ± SEM. ANOVA with Šídák’s multiple comparisons test, * = P < 0.05, ** = P < 0.01. *** = P < 0.001. **** = P < 0.0001. WT (black) Batf3−/− (red). Box plots are median with interquartile range, whiskers = minimum to maximum.

Source data

Extended Data Fig. 8 Gene expression in WT and Batf3-/- mice.

(a) Cdh1 (encoding E-Cadherin) expression in Control, ECM, and PE. Data are mean ± SEM, n = 5 mice ANOVA with Šídák’s multiple comparisons test (b) Col1a1 (encoding Collagen I) expression with all samples from all treatment groups pooled (n = 15 mice), unpaired t-test, two-tailed.

Source data

Extended Data Fig. 9 Gating strategy for myeloid panel.

(a) Representative plots and gates from sample stained with 22 color myeloid phenotyping panel. Example data are from 7 days post-injury. (b) Fluorescence Minus One (FMO) Controls for select myeloid markers. FMO’s from select myeloid panel markers at 7 days post-injury in macrophage (top row) and dendritic cell (bottom row) populations. Grey = unstained control, black dashed line = FMO, red = full stained control.

Source data

Extended Data Fig. 10 Lymphoid panel gating strategy.

Displayed is a representative sample from the inguinal lymph node at 21 days post-injury.

Source data

Supplementary information

Supplementary Information

Legend for Supplementary Video 1 and Discussion.

Reporting Summary

Supplementary Video 1

Three-dimensional reconstruction of the light-sheet microscopy data.

Supplementary Table 1

Reagent list for antibodies and PCR primers.

Source data

Source Data Figs. 1–6

Source data for all the graphs and statistics for Figs. 1–6. Separate tabs are listed for each sheet with the statistics immediately following the raw data.

Source Data Extended Data Figs. 1–10

Source data for all the graphs and statistics for Extended Data Figs. 1–10. Separate tabs are listed for each sheet with the statistics immediately following the raw data.

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Lokwani, R., Josyula, A., Ngo, T.B. et al. Pro-regenerative biomaterials recruit immunoregulatory dendritic cells after traumatic injury. Nat. Mater. 23, 147–157 (2024). https://doi.org/10.1038/s41563-023-01689-9

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