Research ArticleInflammation Open Access | 10.1172/jci.insight.179017

Kevin D. Mangum,1,2 Aaron denDekker,1,2 Qinmengge Li,3,4,5 Lam C. Tsoi,3,4,5 Amrita D. Joshi,1,2 William J. Melvin,1,2 Sonya J. Wolf,1,2 Jadie Y. Moon,1,2 Christopher O. Audu,1,2 James Shadiow,1,2 Andrea T. Obi,1,2 Rachael Wasikowski,3 Emily C. Barrett,1,2 Tyler M. Bauer,1,2 Kylie Boyer,1 Zara Ahmed,1 Frank M. Davis,1,2 Johann Gudjonsson,3 and Katherine A. Gallagher1,2

1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

Find articles by Ahmed, Z. in: JCI | PubMed | Google Scholar

1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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1Section of Vascular Surgery, Department of Surgery;

2Department of Microbiology and Immunology;

3Department of Dermatology;

4Department of Computation Medicine and Bioinformatics; and

5Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA.

Address correspondence to: Katherine A. Gallagher, Section of Vascular Surgery, Department of Surgery, University of Michigan, 1500 East Medical Center Drive, SPC 5867, Ann Arbor, Michigan 48109-5867, USA. Phone: 734.936.5820; Email: kgallag@med.umich.edu.

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Published October 22, 2024 - More info

Published in Volume 9, Issue 20 on October 22, 2024
JCI Insight. 2024;9(20):e179017. https://doi.org/10.1172/jci.insight.179017.
© 2024 Mangum et al. This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Published October 22, 2024 - Version history
Received: January 4, 2024; Accepted: August 23, 2024 View PDF Abstract

Macrophage transition from an inflammatory to reparative phenotype after tissue injury is controlled by epigenetic enzymes that regulate inflammatory gene expression. We have previously identified that the histone methyltransferase SETDB2 in macrophages drives tissue repair by repressing NF-κB–mediated inflammation. Complementary ATAC-Seq and RNA-Seq of wound macrophages isolated from mice deficient in SETDB2 in myeloid cells revealed that SETDB2 suppresses the inflammatory gene program by inhibiting chromatin accessibility at NF-κB–dependent gene promoters. We found that STAT3 was required for SETDB2 expression in macrophages, yet paradoxically, it also functioned as a binding partner of SETDB2 where it repressed SETDB2 activity by inhibiting its interaction with the NF-κB component, RELA, leading to increased RELA/NF-κB–mediated inflammatory gene expression. Furthermore, RNA-Seq in wound macrophages from STAT3-deficient mice corroborated this and revealed STAT3 and SETDB2 transcriptionally coregulate overlapping genes. Finally, in diabetic wound macrophages, STAT3 expression and STAT3/SETDB2 binding were increased. We have identified what we believe to be a novel STAT3/SETDB2 axis that modulates macrophage phenotype during tissue repair and may be an important therapeutic target for nonhealing diabetic wounds.

Graphical Abstract Introduction

Wound healing is characterized by 4 synchronous stages (hemostasis, inflammation, proliferation involving reepithelialization and contraction, and remodeling), and coordinated progression through each of these stages is essential for normal tissue repair (1, 2). During the inflammatory phase, macrophages exhibit increased expression and production of inflammatory cytokines that leads to phagocytosis and clearance of debris and also aids in the recruitment of other cells necessary for repair (3–5). After resolution of the initial inflammation, macrophages at the wound site transition to a reparative phenotype that is defined by increased expression of antiinflammatory mediators, and proinflammatory macrophages are replaced by new reparative macrophages, which sets the stage for fibroblast functions in the proliferative phase (2, 4, 6–16). The macrophage switch to a reparative phenotype is crucial for wound healing to progress from the inflammatory to the proliferative phase (2, 4, 6–15). The factors that control these transitions are not completely clear; however, our group and others have identified that chromatin-modifying enzymes (CMEs) that regulate the accessibility of transcription factors (TFs) to gene promoters play a critical role in controlling cell phenotype (17–22). In pathologic processes that result in nonhealing, such as occurs in type 2 diabetes (T2D), macrophages fail to transition to a reparative phenotype and remain in a chronic low-grade inflammatory state (10, 12, 18, 23). Related to this, our group has previously identified the histone methyltransferase SETDB2 — which trimethylates H3K9 at gene promoters, resulting in reduced inflammatory gene transcription — is decreased in diabetic wound tissue, leading to increased inflammatory gene expression and a sustained inflammatory response (21, 22). Although we previously identified that SETDB2 is upregulated in normal wound macrophages via an IFN-β/JAK/STAT mechanism, the specific downstream protein-protein interactions and precise mechanism by which SETDB2 results in chromatin accessibility and TF binding remain unknown. Identification of these specific interactions are important from a translational standpoint as the identification of a cell-specific target further downstream to control cell phenotype in tissue repair would be more targetable and have fewer off-target side effects.

The NF-κB signaling pathway is a driver inflammation in macrophages following tissue injury (24). The NF-κB family of TFs is composed of 5 members, or subunits, including RELA (p65), Rel (cRel), RelB, Nfkb1 (p50/p105), and Nfkb2 (p52/p100) (25). Distinct combinations between the different NF-κB components in the form of hetero- and homodimers dictate unique downstream transcriptional functions. Activation of NF-κB signaling by different upstream cytokines, pathogens, growth factors, etc. induces nuclear translocation of the different NF-κB subunits, where they can interact in unique combinatorial ways to regulate gene expression (26). RELA (p65) is one of the major NF-κB subunits activated by proinflammatory cytokines, and while it can directly bind DNA to modulate gene expression, it can also interact with other TFs to either activate or repress inflammatory gene expression (27, 28). Specifically, in cancer cells, RELA and STAT3 physically interact, thereby integrating the NF-κB and JAK/STAT signaling pathways (24, 29). Additionally, STAT3 activation has been found to activate RELA (24, 30). While the transcriptional interaction between RELA and STAT3 has been examined in the context of cancer, it is unclear whether this same mode of regulation exists in the context of macrophage-mediated inflammation during wound healing. Furthermore, we have previously shown that SETDB2 is a downstream transcriptional target of the IFN-β pathway, and IFN-β both increases SETDB2 expression and SETDB2 enrichment (along with associated H3K9me3) at NF-κB–dependent promoter regions within inflammatory genes (22). However, the specific transcriptional components involved in regulating SETDB2 at the NF-κB–dependent promoter region to control macrophage phenotype have not been identified.

Here, using both human tissue and murine transgenic models, we found that STAT3 interacts with SETDB2, regulating its ability to modulate inflammation in macrophages. Analysis of RNA-Seq and ATAC-Seq of wound macrophages isolated from our Setdb2fl/fl Lyz2Cre mice with a myeloid cell–specific deletion of Setdb2 revealed that SETDB2 repressed the inflammatory gene program by limiting chromatin accessibility at NF-κB–dependent gene regions. Using a combination of pharmacologic and siRNA-mediated approaches, we demonstrated that STAT3 physically interacted with SETDB2 to inhibit the SETDB2/NF-κB interaction, resulting in increased NF-κB–dependent gene expression. Interestingly, we also found that STAT3 was required for SETDB2 transcription. Thus, we identified a paradoxical relationship between STAT3 and SETDB2 in which STAT3 is required for SETDB2 expression but also limits its activity at the protein-protein level. As a translational corollary, Stat3fl/fl Lyz2Cre mice with a Stat3 gene deletion specifically in myeloid cells exhibited improved early wound healing. Stat3-deficient wound macrophages isolated from these mice revealed that STAT3 expression is dynamic throughout wound healing and serves to coregulate the inflammatory gene program with SETDB2, providing a mechanism for the tightly regulated control of macrophage phenotype. Furthermore, diabetic wound macrophages exhibited increased expression of STAT3 in murine and human wound samples as well as enhanced binding of STAT3 to SETDB2. We observed that this resulted in an imbalance of STAT3, leading to dysregulated STAT3/SETDB2 binding and an aberrant increase in NF-κB–mediated gene expression. Thus, inhibiting STAT3 at specific time points and preventing its binding to SETDB2 may therefore represent a promising therapeutic target for impaired diabetic wound healing.

Results

SETDB2 is enriched at NF-κB–dependent gene promoters in human and murine wound macrophages. In order to examine the downstream genes controlled by SETDB2 in wound macrophages and elucidate the exact transcriptional targets of SETDB2 that control macrophage phenotype, we performed FACS for CD3–CD19–Ly6G–CD11b+Ly6ChiGFP+ and CD3–CD19–Ly6G–CD11b+Ly6CloGFP+ cells from murine wounds in Setdb2fl/fl Lyz2Cre+mTmG mice and Setdb2fl/fl Lyz2Cre–mTmG littermate controls.In this system, successful genetic recombination leads to simultaneous excision of the Tomato reporter and activation of the GFP reporter, resulting in GFP expression in cells that have undergone successful Cre-mediated deletion of the floxed gene. Given that we had identified previously that SETDB2 exhibits its highest expression in wound macrophages at day 5 after wounding, we isolated day 5 wound macrophages from the Setdb2fl/fl Lyz2CremTmG mice to identify maximal alterations in the downstream transcriptional signatures in macrophages after SETDB2 deletion (22). Because Ly6C is a well-established surface marker designating the inflammatory macrophage subset, we further used FACS to separate the CD3–CD19–Ly6G–CD11b+GFP+ population into CD3–CD19–Ly6G–CD11b+GFP+Ly6Chi (Ly6Chi) and CD3–CD19–Ly6G–CD11b+GFP+Ly6Clo (Ly6Clo) subpopulations in order to delineate transcriptional differences based on inflammatory subtype. RNA-Seq analysis was performed in Ly6Chi and Ly6Clo subpopulations, and we identified gene expression profiles of these subtypes and examined how SETDB2 affected gene expression in these populations. As expected, we observed significant differences in the genes differentially expressed between Ly6Chi and Ly6Clo, which were further altered by SETDB2 deficiency (Figure 1A). Additionally, we found SETDB2 controlled expression of inflammatory genes that play a key role in wound repair, including Il1b, Il6, Il12, and Tnf, and these genes were further increased in the Ly6Chi population by SETDB2 deletion (Figure 1, B and C). A complete list of differentially expressed genes (DEGs) is listed in Supplemental Table 1 (supplemental material available online with this article; https://doi.org/10.1172/jci.insight.179017DS1). Importantly, many of the DEGs identified are well-known downstream targets of the TNF-α and IFN-β signaling pathways, which play critical roles in regulating inflammation during important biological processes, including wound healing (22, 31, 32). In support of SETDB2 regulating the inflammatory phenotype, these proinflammatory genes were more enriched in the Ly6Chi macrophage population, which exhibits an increased inflammatory signature compared with the Ly6Clo macrophage subtype. To further delineate the downstream pathways regulated by SETDB2, we performed gene ontology (GO) analysis on the DEGs, and it supported the unique transcriptional signatures between Ly6Chi and Ly6Clo subpopulations in wound macrophages (Figure 1D and Supplemental Figures 1–3). Additionally, pathways including immune response, response to LPS, and cytokine activity were also upregulated in Setdb2-deficient Ly6Chi macrophages, further supporting the role of SETDB2 in limiting the inflammatory phenotype of this subpopulation. Furthermore, pathway analysis of the Setdb2-deficient Ly6Chi macrophage subpopulation revealed increased activation of IL-1R and NF-κB signaling, providing additional support for SETDB2 in negatively regulating these inflammatory pathways (Supplemental Figure 4). Because changes in gene expression may not necessarily reflect alterations in chromatin structure due to SETDB2 deletion, we next performed ATAC-Seq on FACS-isolated CD3–CD19–Ly6G–CD11b+Ly6C+GFP+ cells from wounds of Setdb2fl/fl Lyz2Cre+ and Cre-negative controls to interrogate chromatin accessibility in Setdb2-deficient wound macrophages, with particular attention given to the inflammatory-related genes identified by RNA-Seq in Figure 1A. Our ATAC-Seq analysis identified increased chromatin accessibility within inflammatory genes (Il1b, Nfkb1, Relb, Rel, Cxcl2) in Setdb2-deficient Ly6Chi wound macrophages compared with Setdb2-competent Ly6Chi cells (Figure 1E) (Supplemental Table 2). There were 2 additional noteworthy findings from these initial unbiased sequencing results. First, as we had previously shown (22), SETDB2 leads to silencing of inflammatory genes by promoting a closed chromatin configuration via trimethylation of H3K9. Second, SETDB2 regulates chromatin accessibility in NF-κB–binding regions in inflammatory gene promoters, which again corroborated previous findings that SETDB2 transcriptionally targeted NF-κB–bound promoter regions. Since we identified that SETDB2 specifically regulates NF-κB–binding regions in the promoter regions of inflammatory genes, we sought to more specifically examine the interactions between SETDB2 and NF-κB at known NF-κB target genes. Murine BM-derived macrophages (BMDMs) were isolated and treated with IFN-β (10 U/mL; 8.5 ng/mL), which we previously determined to be a potent upstream regulator of SETDB2, with or without an NF-κB inhibitor (BAY 11-7082, 10 μM). ChIP analysis for H3K9me3, the repressive epigenetic mark deposited by SETDB2, at inflammatory gene promoters was then performed. IFN-β resulted in an expected increase in H3K9me3 at the Il1b and Tnf promoters, and this H3K9 trimethylation was reversed by treatment with an NF-κB inhibitor (Figure 1, F and G). Taken together, these data indicate that SETDB2 represses NF-κB–dependent inflammatory gene expression by regulating chromatin accessibility within these genes, and paradoxically, NF-κB positively regulates SETDB2 function at these gene promoters.

Figure 1

SETDB2 is enriched at NF-κB–dependent gene promoters in murine wound macrophages. Wound macrophages were isolated from Setdb2fl/fl Lyz2CremTmG murine wounds on day 5 after wounding, sorted into CD3–CD19–NK1.1–Ly6G–CD11b+Ly6Chi and CD3–CD19–NK1.1–Ly6G–CD11b+Ly6Clo populations, and then analyzed for gene expression by RNA-Seq and ATAC-Seq. (A) Heatmap of DEGs in wound macrophages isolated from Setdb2fl/fl Lyz2CremTmG murine wounds on day 5 after wounding. Wound macrophages were sorted into CD3–CD19–NK1.1–Ly6G–CD11b+Ly6Chi and CD3–CD19–NK1.1–Ly6G–CD11b+Ly6Clo populations and then analyzed for gene expression by RNA-Seq (12–15 mice per group, n = 3–5 independent experiments). (B) Venn diagram comparing upregulated and downregulated genes from RNA-Seq of wound macrophages (CD3–CD19– NK1.1–Ly6G–CD11b+Ly6Chi and CD3–CD19–NK1.1–Ly6G–CD11b+Ly6Clo) isolated from Setdb2fl/fl Lyz2CremTmG mouse wounds on day 5 after wounding. (C) Volcano plot of transcriptomic profiles from DEGs in CD3–CD19–NK1.1–Ly6G–CD11b+Ly6Chi wound macrophages from Setdb2fl/fl Lyz2CremTmG mice. (D) GO analysis of DEGs in CD3–CD19–NK1.1–Ly6G–CD11b+Ly6Chi wound macrophages from Setdb2fl/fl Lyz2CremTmG mice. (E) Inflammatory gene promoter regions differentially regulated by SETDB2 as determined by ATAC-Seq of wound macrophages (CD3–CD19–NK1.1–Ly6G–CD11b+Ly6C+ GFP+) isolated on day 5 from Setdb2fl/fl Lyz2CremTmG mice. Red bars indicate ATAC-Seq peaks relative to Cre-negative controls. Hashed red bars designate peaks that overlap promoter regions of listed genes. (F and G) H3K9me3 ChIP qPCR at the Il1b and Tnf promoters in murine BMDMs unstimulated or treated with IFN-β (10 U/mL; 8.5 ng/mL) or IFN-β and NF-κB inhibitor, BAY 11-7082 (10 μM). Data are representative of n = 3–5 independent experiments, with 12–15 mice per group per experiment. *P < 0.05, **P < 0.01, ***P < 0.001. Data are presented as the mean ± SEM. Two-tailed Student’s t test was used for comparison of 2 groups. For comparison among multiple groups, 2-way ANOVA followed by Newman-Keuls post hoc test was used.

STAT3 regulates SETDB2 expression in human and murine wound macrophages and is required for normal wound healing. We investigated the upstream transcription mechanisms regulating SETDB2 expression in macrophages in response to injury. We used a combination of in silico, in vitro, and in vivo approaches to identify TFs regulating expression of SETDB2. Because our group has previously identified that STAT proteins regulate SETDB2 expression, we analyzed the human SETDB2 promoter for predicted STAT binding sites. Using the publicly accessible database of TF binding, JASPAR, we examined various STAT protein binding sites and found that STAT3 was the most predominant STAT TF predicted to bind to the SETDB2 promoter. We identified 24 putative STAT3 binding sites within the human SETDB2 promoter, which also overlapped with multiple features of active transcription including H3K27Ac, H3K4me3, and open chromatin DNase Hypersensitive Sites (DHS), which were all identified using the UCSC Genome Browser (https://genome.ucsc.edu/) (Figure 2A) (33, 34). Although we had previously identified the importance of STAT1 in regulating SETDB2 in macrophages (22), based on our more recent and robust data of scRNA-Seq of human wounds as well as analysis of TF binding to the SETDB2 promoter, we determined that STAT3 was the most strongly and abundantly expressed STAT member in wound macrophages (Figure 2B). Additionally, to further examine the relationship between STAT3 and SETDB2, we performed Pearson correlation analysis in macrophages in our scRNA-Seq of skin wounds from patients. We found that STAT3 and SETDB2 exhibited a significant and very strong correlation in human wound macrophages (Figure 2C). Next, to confirm Stat3 binding to the Setdb2 promoter, we isolated murine macrophages and performed ChIP for Stat3. We identified significant Stat3 enrichment at the Setdb2 promoter over an IgG– control antibody (Figure 2D). To localize the effect of STAT3 function to the SETDB2 promoter, we cloned a 3 kb fragment of the human SETDB2 transcription start site into a pGL3 luciferase vector and measured its activity in BMDMs. As shown in Figure 2E, SETDB2 promoter activity increased 2-fold in BMDMs treated with IFN-β, and this increase was inhibited by treatment with the JAK1/3 inhibitor tofacitinib (100 μM). Furthermore, in vivo wound macrophages (CD3–CD19–Ly6G–CD11b+Ly6C+) isolated from Stat3fl/fl Lyz2Cre+ mice and Cre-negative littermate controls exhibited decreased Setdb2 expression (Figure 2F), and treatment of BMDMs with tofacitinib decreased Setdb2 expression (Figure 2G). Next, to examine STAT3 kinetics throughout normal wound healing, we harvested wound macrophages (CD3–CD19–NK1.1–Ly6G–CD11b+Ly6C+) from mice on days 0 and 5 after wounding and performed Western blotting for STAT3. STAT3 significantly decreased from day 0 to day 5, indicating that it is highly dynamic throughout wound healing (Figure 2H). Finally, to test the role of STAT3 in macrophages during wound repair, we wounded Stat3fl/fl Lyz2Cre+ and Cre-negative controls and measured wound size throughout healing using NIH ImageJ software. Myeloid cell–specific deletion of Stat3 resulted in smaller wounds at earlier time points; however, at day 5, loss of Stat3 in macrophages led to modestly larger wounds, suggesting that Stat3 regulates macrophage phenotype during wound repair in a time-dependent manner (Figure 2I). Taken together, these results suggest that STAT3 is dynamic throughout wound healing, drives SETDB2 expression in both human and murine wound macrophages during this process, and regulates wound healing in a time-dependent manner.

Figure 2

STAT3 is dynamic during wound repair and regulates SETDB2 in human and murine wound macrophages. (A) Gene structure of the human SETDB2 gene showing cloned fragment aligned with multiple active transcriptional features including DHS peaks, H3K27Ac, H3K4me3, and sequence conservation. (B) Dot plot of different STAT members expression from scRNA-Seq data of human wounds (n = 10 patients). (C) Scatterplot of SETDB2 and STAT3 expression in macrophages obtained from scRNA-Seq in human wounds with respective Pearson correlation analysis (n = 10 patients). (D) ChIP-qPCR for Stat3 binding at the mouse Setdb2 promoter compared with IgG negative control. (E) Luciferase activity of the 3 kb human SETDB2 promoter cloned into pGL3 and then transfected in BMDMs untreated or treated with IFN-β (10 U/mL; 8.5 ng/mL), or IFN-β plus tofacitinib (100 μM) for 4 hours. (F) qPCR analysis of Setdb2 expression in wound macrophages (CD3–CD19–NK1.1–Ly6G–CD11b+) isolated from Stat3fl/fl Lyz2Cre mice on day 5 after wounding compared with Cre– littermate control (n = 6 mice per group). (G) Setdb2 expression in BMDMs treated with IFN-β or IFN-β plus tofacitinib (n = 6–8 mice per group). (H) Representative Western blot and densitometry of murine whole wounds showing decreased levels of STAT3 at day 5 compared with day 0 after wounding (n = 3–4 mice at each time point). (I) Wound curve analysis in Stat3fl/fl Lyz2Cre mice compared with Cre– littermate controls all fed a normal diet (n = 8–12 mice per group in each experiment). All data are representative of n = 3–5 independent experiments. *P < 0.05, **P < 0.01, ****P < 0.0001. Data are presented as the mean ± SEM. Two-tailed Student’s t test was used for comparison of 2 groups. For comparison among multiple groups, 2-way ANOVA followed by Newman-Keuls post hoc test was used.

STAT3 inhibits the physical interaction between SETDB2 and NF-κB in wound macrophages. Since we identified that SETDB2 selectively targeted NF-κB–bound promoter regions and that NF-κB was required for SETDB2 activity at inflammatory gene promoters, we examined the protein-protein interactions between SETDB2 and NF-κB. Hence, we performed an expression-interaction analysis in macrophages from our single-cell RNA-Seq (scRNA-Seq) dataset of human wounds to identify candidate SETDB2 binding partners in a cell type–specific manner. We identified the highest interaction scores between SETDB2, RELA (NF-κB component) (interaction score 0.50), and STAT3 (interaction score 0.40) (Figure 3A). To confirm SETDB2 binding to 1 or more of these TFs, we performed glutathione-S-transferase (GST) pulldown assays using recombinant GST-SETDB2 versus a GST-only negative control in BMDM lysate. We identified NF-κB component p65 (RELA) and STAT3 as SETDB2 binding partners (