A Novel Three-Dimensional Skin Disease Model to Assess Macrophage Function in Diabetes

Abstract

A major challenge in the management of patients suffering from diabetes is the risk of developing nonhealing foot ulcers. Most in vitro methods to screen drugs for wound healing therapies rely on conventional 2D cell cultures that do not closely mimic the complexity of the diabetic wound environment. In addition, while three-dimensional (3D) skin tissue models of human skin exist, they have not previously been adapted to incorporate patient-derived macrophages to model inflammation from these wounds. In this study, we present a 3D human skin equivalent (HSE) model incorporating blood-derived monocytes and primary fibroblasts isolated from patients with diabetic foot ulcers (DFUs). We demonstrate that the monocytes differentiate into macrophages when incorporated into HSEs and secrete a cytokine profile indicative of the proinflammatory M1 phenotype seen in DFUs. We also show how the interaction between fibroblasts and macrophages in the HSE can guide macrophage polarization. Our findings take us a step closer to creating a human, 3D skin-like tissue model that can be applied to evaluate the response of candidate compounds needed for potential new foot ulcer therapies in a more complex tissue environment that contributes to diabetic wounds.

Impact statement

This study is the first to incorporate disease-specific, diabetic macrophages into a three-dimensional (3D) model of human skin. We show how to fabricate skin that incorporates macrophages with disease-specific fibroblasts to guide macrophage polarization. We also show that monocytes from diabetic patients can differentiate into macrophages directly in this skin disease model, and that they secrete a cytokine profile mimicking the proinflammatory M1 phenotype seen in diabetic foot ulcers. The data presented here indicate that this 3D skin disease model can be used to study macrophage-related inflammation in diabetes and as a drug testing tool to evaluate new treatments for the disease.

Introduction

A major challenge in the management of patients suffering from diabetes is the risk of developing nonhealing ulcers on the feet.^1,2 These chronic, nonhealing wounds can be exacerbated through ischemia, neuropathy, persistent pressure, inflammation, and infection; potentially leading to morbidity.^3,4 While many products exist to address this problem, as many as 50% of diabetic foot ulcers (DFUs) remain recalcitrant to these therapies. The need to better treat these wounds remains the highest priority in the treatment of these patients.

Most in vitro methods to screen drugs for wound healing therapies rely on conventional two-dimensional (2D) cell cultures that do not closely mimic the complexity of the diabetic wound environment. While valuable, these systems cannot fully simulate the cellular and tissue complexity of DFUs and are not highly predictive of in vivo tissue response,^5,6 While there are a variety of three-dimensional (3D) skin-like tissue models that have been used as a predictor of in vivo skin response,⁶ these tissues have not yet included a process for evaluating the inflammatory response, and particularly the role of macrophages, seen in DFUs. Drug screening for DFUs will require the use of 3D tissues that more closely approximate the diabetic wound environment and could be used to accelerate the screening and testing of new therapies.

We have previously developed a human skin equivalent (HSE) that models many aspects of DFUs by incorporating fibroblasts isolated from diabetic patients.^7,8 These tissues have been shown to recapitulate the impaired healing, altered keratinocyte crosstalk, and reduced production of extracellular matrix (ECM) seen in DFUs. Here, we move one step closer to comprehensively modeling these wounds by incorporating macrophages to approximate aspects of the inflammatory response seen in DFUs. This marks the first-time patient-specific macrophages that have been incorporated into 3D skin tissues.

Normal wound healing progression classically includes four phases: hemostasis, acute inflammation, proliferation, and maturation.^9,10 However, DFUs exhibit inflammation typified by a failure of macrophages present in the wound to shift their phenotype from M1 (inflammatory macrophages) to M2 (healing macrophages). These alterations in the inflammatory stage are accompanied by changes in the tissue environment that lead to an imbalance in functional cross talk between macrophages, fibroblasts, and keratinocytes. There is evidence that altered metabolic products in diabetes impair phagocytosis by macrophages and inhibit macrophage transition from a classically activated proinflammatory M1 phenotype to an alternatively activated inflammation-modulating M2 phenotype.^11,12 As a result, elevated levels of inflammatory macrophages persist in the wound site, along with increased concentrations of inflammatory chemokines, cytokines, and proteolytic enzymes.¹³ While the inflammatory state of macrophages in these tissues has been monitored in animal models,^14,15 the skin in rodents does not mimic the tissue environment typically seen in human DFUs. It has also been shown that when skin equivalents are grafted onto immunocompromised nondiabetic rats, that rat macrophages can migrate into the skin equivalent, where they recapitulate the normal M1 to M2 transition seen in normal wound healing.¹⁶ Human macrophages have previously been incorporated into HSEs to study their effect on tumor progression.¹⁷ By incorporating diabetic or control macrophages into diabetic HSEs, it may be possible to provide a new experimental skin-like tissue model that could aid in the translation of new research in DFUs into therapies.

In this study, we have fabricated a skin-like testing model in HSEs that mimics the diabetic wound repair microenvironment by incorporating DFU-derived fibroblasts and blood-derived monocytes isolated from patients with DFUs. We demonstrate that monocytes isolated from peripheral blood-derived mononuclear cells (PBMCs) from control and diabetic subjects can be incorporated into HSEs, where they differentiate into functional tissue macrophages. We next show evidence that macrophages isolated from the blood of diabetic subjects in our HSEs secrete a cytokine profile indicative of the proinflammatory, M1 phenotype seen in these wounds in vivo. Finally, we demonstrate that interactions between fibroblasts and macrophages in the HSE can impact macrophage polarization. Our findings illustrate that by increasing the complexity of the tissue microenvironment to more closely mimic that of DFUs, we can take an important step toward creating a drug screening platform that can be used to evaluate potential new therapies for diabetic patients.

Materials and Methods

Isolation of monocytes

Apheresis leukoreduction collars from anonymous donors were collected from the Brigham and Women's Hospital blood bank. Blood was also collected from two diabetic and two control subjects at Beth Israel Deaconess Medical Center and Tufts Medical Center under protocols approved by respective Institutional Review Boards. PBMCs were isolated using Ficoll-Paque PLUS Media (GE Healthcare, Chicago, IL). For the Apheresis leukoreduction collars, PBMCs were then cryopreserved in a 90% fetal bovine serum (FBS) and 10% dimethyl sulfoxide (DMSO) solution. After thawing, monocytes were isolated from PBMCs using magnetic-activated cell sorting (MACS) Monocyte Isolation Kit (Miltenyi Biotec, CA). For the blood collected from diabetic and control subjects, monocytes were immediately isolated before freezing using MACS Monocyte Isolation Kit (Miltenyi Biotec). Monocytes were then cryopreserved in a 90% FBS and 10% DMSO solution.

Isolation of fibroblasts

Fibroblasts were isolated from diabetic foot ulcers from three subjects (diabetic foot ulcer fibroblasts [DFUFs]) and three site matched non-diabetic controls (non-diabetic foot fibroblasts [NFFs]) as previously described, under a protocol approved by the Beth Israel Deaconess Medical Center Institutional Review Board.⁸ Fibroblasts were maintained in fibroblast growth media containing DMEM (1 g/L glucose; Thermo, Waltham, MA), 10% FBS (HyClone, Logan, UT), HEPES (Sigma-Aldrich, St. Louis, MO), and Pen/Strep/Fung (Thermo). All experiments were conducted using fibroblasts between passages 5 and 7.

Monocyte 2D polarization

Monocytes were seeded on 100 mm untreated Petri dishes at a density of 3 × 10⁶ cells/plate. Cells were cultured in RPMI media containing 10% heat inactivated FBS (Thermo), 1% HEPES (Thermo), 1% Pen/Strep (Thermo), 1% sodium pyruvate (Thermo), and 20 ng/mL macrophage colony stimulating factor (MCSF) (GoldBio, St Louis, MO). On day 5, supplemental cytokines were added to the media to polarize the macrophages.¹⁷ For M1 polarization, 100 ng/mL IFNγ (GoldBio) and 100 ng/mL LPS (Sigma, St. Louis, MO) were added. For M2A polarization, 40 ng/mL IL-4 (GoldBio) and 20 ng/mL IL-13 (Peprotech, Rocky Hill, NJ) were added. For M2C polarization, 40 ng/mL IL-10 (GoldBio) was added. In all cases, cells were cultured with polarizing factors for 48 h. After polarization, cells were dissociated using Accutase (MP Biomedicals) for 12 min and collected for analysis or incorporated into HSEs.

Flow cytometry

Dissociated macrophages were stained with a cocktail of antibodies, including CD163-FITC (#333617; BioLegend, San Diego, CA), HLADR-Pac Blue (#307623; BioLegend), CD206-APC/Cy7 (#321119; BioLegend), or with their respective isotype controls. 2 × 10⁴ cells for each condition were analyzed for mean fluorescence intensity (MFI) using an LSR-II and FlowJo software (Both BD Biosciences, San Jose, CA).

HSE construction

To monitor the effect on macrophages on 3D tissues, HSEs were constructed in triplicate wells as previously described.⁶ In brief, either NFFs or DFUFs and macrophages either polarized to M1, M2A, M2C, or unpolarized were mixed with type I collagen (Organogenesis, Canton, MA) to a final fibroblast concentration of 3 × 10⁵ cells/mL, and macrophage concentration of 2.2 × 10⁵ cells/mL. This concentration was chosen due to previous work. Collagen gels were then submerged in fibroblast growth media, the fibroblasts contracted and remodeled the collagen matrices over the course of 7 days. Then, 5 × 10⁵ keratinocytes (normal human keratinocytes [NHKs]) isolated from human neonatal foreskin were seeded in 50 μL of epidermal growth media (Organogenesis) on the surface of each collagen matrix. After 4 days, the constructs were raised to an air-liquid interface and fed from the bottom with cornification media (Organogenesis) containing 2% serum to enable epithelial differentiation for 1 week (Fig. 1). Tissue sections stained by hematoxylin and eosin (H&E) were used to evaluate the stratification and differentiation of the epidermis. Images were taken with a Nikon Eclipse 80i microscope and Spot Advanced software (Diagnostic Instruments, Sterling Heights, MI).

FIG. 1.

Development of an HSE tissue. (a) An acellular collagen layer is placed on the bottom of a 24 mm transwell membrane. (b) Fibroblasts with or without macrophages are mixed with bovine type 1 collagen and seeded on top. (c) The fibroblasts remodel and contract the collagen over the course of 1 week. (d) Neonatal human keratinocytes are seeded on top of the collagen matrix, where (e) they proliferate and begin differentiation. (f) The tissue is brought to an air-liquid interface to catalyze epithelial cornification. HSE, human skin equivalent. Color images are available online.

Antibody staining

To determine the presence and polarization state of macrophages in the HSEs, immunofluorescent double staining was performed, containing a pan macrophage marker and a marker for a specific polarization state. Frozen sections were cut at 7 μM onto slides. Slides were then fixed in either acetone or methanol, permeabilized in 0.1% Triton X-100, and blocked in 0.2% bovine serum albumin (BSA)/phosphate-buffered saline (PBS) containing 5% goat serum. The cells were incubated in primary antibody in 0.2% BSA/PBS overnight, and then incubated in secondary fluorescent antibodies for 45 min. Slides were then mounted with DAPI (Vector Laboratories, Burlingame, CA). Primary antibodies were as follows: Pan Macrophage: CD68 (AB 213363; Abcam, Cambridge, MA). M1 polarization: HLADR (AB80658; Abcam); M2A polarization: CD206 (MCA2519; Bio-Rad, Hercules, CA); and M2C polarization: CD163 (AB156769; Abcam). All secondary antibodies were used at 1:250 and sourced from Thermo. Slides were imaged using a Nikon Eclipse 80i microscope and either Spot Advanced software (Diagnostic Instruments) or Zeiss Blue (Oberkochen, Germany). Staining quantification was performed using ImageJ (NIH, Bethesda, MD). Quantification of HLADR-positive macrophages was performed by taking three images from three depths from three biological replicates for each condition. Data are shown as the ratio of cells in the dermis that were CD68 and HLADR double positive to cells that were only CD68 positive.

Secreted protein analysis

Supernatant from the HSE tissues was collected before seeding keratinocytes, and at the final day of epithelial cornification. The supernatant was analyzed using the Meso Scale Discovery Chemokine Panel 1 (human) Kit V-PLEX Plus (Meso Scale Diagnostics, Rockville, MD) and run according to the manufacturer's protocol. The plate was run on Meso Scale Diagnostics plate reader model 1250. Results were analyzed using Workbench 4.0 (Meso Scale Diagnostics) and Prism (GraphPad, San Diego, CA).

Supernatant was also collected from HSEs before seeding keratinocytes, and containing monocytes from control or diabetic subjects, and analyzed using Human IL-8/CXCL8 DuoSet ELISA kit, Human IL-6 DuoSet ELISA, and Human IL-1β/IL-1F2 DuoSet ELISA (All Bio-Techne, Minneapolis MN) according to the kit instructions. Plates were read at 450 nm on a SpectraMax M2 plate reader (Molecular Devices, San Jose, CA) and analyzed using ElisaAnalysis.com.

Statistics

Statistical analysis was performed using GraphPad Prism (GraphPad). Nonparametric t-test was used for data analysis and one-way ANOVA with Tukey's posttest was used for multiple comparisons, with p < 0.05 considered to be statistically significant.

Experiment

The methods described here were used in two types of experiments. First, we evaluate the ability of unpolarized or polarized macrophages to persist and function in HSEs. Monocytes from an anonymous donor were differentiated and polarized on plastic dishes, and then incorporated with DFUFs or NFFs into HSEs. Second, we evaluate the ability of monocytes to differentiate directly in the HSE, and examine the impact of incorporating patient-specific monocytes. Monocytes isolated from two patients with DFUs and from two control subjects were incorporated with fibroblasts from three patients with DFUs and three nondiabetic subjects in all combinations into HSEs.

Experimental Results

Blood monocytes can differentiate to macrophages and be polarized in 2D, monolayer culture

We first hoped to establish that macrophages derived from the peripheral blood of nondiabetic patients could be polarized to specific macrophage subtypes. To test this, PBMCs were isolated from apheresis leukoreduction collars from anonymous blood donors and sorted for their monocyte fraction using MACS. Isolated monocytes were then seeded on nontissue culture-treated plastic dishes. After 5 days, monocytes had attached to the dishes and were treated with cytokines to induce polarization to M1, M2A, or M2C phenotypes.¹⁷ Phase contrast images at day 7 show a varied morphology and density of the macrophages in 2D culture correlated with their polarization treatment (Fig. 2a). Unpolarized macrophages retained a more round to ovoid morphology and attached and spread on the plate, whereas M1 macrophages displayed a greater number of spindle-like cells. M2A and M2C macrophages show more refractive cells, as well as cells with a spindle-like morphology (Fig. 2a). When macrophages were detached and counted after 48 h of treatment, 16–50% of the number of cells seeded were recovered depending on the cellular polarization state.

FIG. 2.

Monocytes isolated from Apheresis leukoreduction collars can be differentiated and polarized in 2D. (a) Monocytes seeded onto Petri dishes attached to the dishes and showed varied morphology after treatment with polarization factors. Scale bars: 200 μm. (b) Staining of macrophages indicated that all were positive for CD68, a pan-macrophage marker. HLADR staining was most present in macrophages treated with M1 polarization factors, CD163 was most present in macrophages treated with M2C polarization factors, and CD206 was most present in macrophages treated with M2A polarization factors. Scale bars: 100 μm. (c) The MFI by flow cytometry was highest for each population in the marker correlating with their polarization state. 2D, two-dimensional; MFI, mean fluorescence intensity. Color images are available online.

Some of the dissociated cells were adhered to glass slides for immunofluorescent staining. All cells stained positive for CD68, confirming their macrophage phenotype (Fig. 2b). We next stained with surface markers indicative of each polarization state. HLADR-positive staining was identified in most macrophages polarized toward an M1 phenotype, while CD163- and CD206-positive staining was most visible in macrophages polarized toward M2C or M2A, respectively. However, all conditions showed a small number of positive stained macrophages for each marker. To further verify that cell staining reflected polarization that had occurred, we examined the MFI by flow cytometry. While all populations showed positive fluorescence for all macrophage markers, the MFI was highest for each in the marker associated with polarization state (Fig. 2c). These data confirmed our immunohistochemical staining and indicated that while mixed populations existed, polarization to different macrophage subsets had occurred, and that macrophages should be identifiable by staining with these markers after incorporation into HSEs. However, while macrophages could be successfully polarized and collected from plastic dishes, this process reduced the quantity of cells available for tissue fabrication.

Macrophages incorporated into HSEs demonstrate normal tissue development and epithelial differentiation

Macrophages expressing this range of cellular phenotypes were next incorporated into HSEs with either DFUFs or NFFs (Fig. 1). HSEs constructed both with and without macrophages displayed a thick dermis, and a fully differentiated stratified epithelium showing all morphologic layers seen in human skin. The connective tissues of HSEs showed fibroblasts with the typical, stellate cell morphology in the absence and presence of macrophages. Epithelial tissue differentiation was confirmed by staining for keratin 10 (K10), which showed normal tissue distribution that was strictly limited to keratinocytes above the basal layer (Fig. 3). This indicated that the incorporation of macrophages into HSEs did not have an adverse effect on the complete morphologic and biochemical differentiation of the overlying epithelium.

FIG. 3.

HSEs can be constructed with macrophages incorporated. H&E staining showed normal tissue development with a cellular dermal layer and full thickness epithelium with and without macrophages (a, b). Staining for K10 showed a differentiated epithelium both with and without macrophages (c, d). Scale bars: 100 μm. H&E, hematoxylin and eosin; K10, keratin 10. Color images are available online.

Macrophage polarization is directed to an M1 phenotype when cocultured with diabetic fibroblasts in HSEs

To assess the distribution of macrophages in HSEs, tissues were stained for CD68. Immunofluorescent staining indicated that CD68-positive cells were present throughout the connective tissue that were distinct from stellate-shaped fibroblasts, which did not stain positive for CD68, demonstrating the persistence of macrophages in HSEs. When HSEs were stained for an M1 marker (HLADR), an M2A marker, (CD206) and an M2C marker (CD163), a variety of macrophages with different surface marker expression were present in HSEs, regardless of the original polarization state of the macrophages used for tissue fabrication (Fig. 4a). HSEs fabricated with unpolarized macrophages displayed significantly more macrophages expressing the M1 marker, HLADR, compared with HSEs made with NFFs (p < 0.0001) (Fig. 4b). This suggested that the presence of DFUFs may be directing the naive macrophages toward an M1 phenotype through interactions between these two cell types.

FIG. 4.

Macrophages persist in HSEs. (a) Immunofluorescent staining for the pan-macrophage marker CD11b (green), indicated that macrophages were present in HSEs at the end of development. Nonspecific CD68 staining was seen in the epithelium. Staining for the M1 marker HLADR, M2A marker CD206, and M2C marker CD163 (all red) showed positive cells in most tissues, regardless of macrophage polarization state before tissue formation. Tissues were counterstained with Dapi (blue). Yellow demonstrates overlap between green and red. (b) In HSEs where macrophages were incorporated unpolarized, there were significantly higher numbers of HLADR-positive macrophages when incorporated with DFUFs versus NFFs. Scale bars: 100 μm. n = 6. Mean ± SD. ****p < 0.0001. DFUF, diabetic foot ulcer fibroblast; NFF, nondiabetic foot fibroblast. Color images are available online.

Macrophages play an active role in inflammatory cytokine secretion in HSEs

To assess cellular cross talk between fibroblasts and macrophages, we analyzed cytokine secretion from HSEs before the addition of keratinocytes. HSEs constructed with either DFUs or NFFs and containing macrophages secreted higher levels of IL-1β (p = 0.0014), IL-2 (p < 0.0001), IL-8 (p = 0.0003), IL-10 (p = 0.0039), IL-13 (p < 0.0001), and TNF-A (p < 0.0001) when compared to HSEs without macrophages (Fig. 5a–f). HSEs fabricated with DFUFs, both with and without macrophages, secreted higher levels of IL-6 (p < 0.0001) than tissues containing NFFs (Fig. 5g), however, the fibroblast source was not shown to play a significant role in the secretion of any of the other cytokines (data not shown). These data demonstrated that the presence of macrophages in HSEs caused the secretion of inflammatory cytokines, and that only specific cytokines (IL-6) were associated with the presence of diabetic patient-derived fibroblasts. As some of these cytokines can be produced by both macrophages and fibroblasts, it was not possible to assess the individual secretion from each cell type. It is possible that these inflammatory cytokine profiles can partially be explained by the cytokine cross talk between these two cell types.

FIG. 5.

Macrophages impact inflammatory cytokine secretion in HSEs. Multiplex cytokine analysis for IL-1β (a), IL-2 (b), IL-8 (c), IL-10 (d), IL-13 (e), and TNF-A (f) showed significantly higher quantities in HSEs containing macrophages than those without. IL-6 levels (g) were significantly higher in HSEs containing DFUFs compared to those with NFFs, regardless of the presence of macrophages. N = 12. Mean ± SD. **p < 0.01; ***p < 0.001; ****p < 0.0001.

HSEs constructed with diabetic patient-derived macrophages secrete significantly higher levels of M1 inflammatory cytokines

We next constructed HSEs containing monocytes isolated from PBMCs from two diabetic patients with DFUs and from two control subjects, to investigate the role of diabetic versus control macrophages and fibroblasts in HSEs. These monocytes were combined with fibroblasts from three diabetic patients (DFUs) and from three healthy control (NFFs) patients. Due to the relatively small amount of blood harvested from these patients (30 mL), monocytes were incorporated directly into HSEs without being polarized in 2D cultures. This also allowed us to determine if monocytes could differentiate and polarize directly in HSEs. Fabrication of HSEs in all combinations of fibroblasts and PBMCs resulted in well stratified, fully differentiated skin-like tissues as seen via H&E staining. Positive staining for HLADR demonstrates the presence of macrophages (Fig. 6). When HSE supernatant collected before seeding keratinocytes was analyzed by ELISA, HSEs containing macrophages from DFU subjects secreted significantly higher levels of IL-1β (p < 0.0001), IL-6 (p < 0.0001), and IL-8 (p < 0.0001) compared to those containing macrophages from control subjects. These data indicate that monocytes from diabetic patients can be differentiated into macrophages directly in our HSEs, and cause the HSEs to recapitulate a proinflammatory M1 phenotype as seen through cytokine secretion.

FIG. 6.

Diabetic monocytes secrete higher levels of inflammatory cytokines in HSEs. Blood monocytes from DFU (DM) or control subjects (CM) were incorporated into HSEs with DFUFs. (a–d) H&E staining indicated normal tissue development with monocytes from each subject incorporated. (e–h) Staining for HLADR indicated that monocytes differentiated into macrophages and expressed the HLADR marker. ELISA analysis for IL-1b (i), IL-6 (j), and IL-8 (k) showed significantly higher secretion levels in HSEs containing DM than CM, regardless of fibroblast source. Scale bars: 100 μm. Mean ± SD. n = 24. **** p < 0.0001. Color images are available online.

Discussion

DFUs are a debilitating complication of diabetes mellitus. Many DFUs are refractory to existing treatments and frequently lead to limb amputation and additional comorbidities. The development of effective therapies for DFUs has been hampered by the lack of predictive in vitro drug screening platforms. To address this need, we have established that DFU-derived fibroblasts and blood-derived monocytes isolated from patients with DFUs can be used to construct 3D disease models of human skin that mimic the diabetic tissue microenvironment. We demonstrate that PBMCs differentiate into macrophages when incorporated into HSEs and secrete a cytokine profile indicative of the proinflammatory M1 phenotype seen in DFUs. We also show how the interaction between fibroblasts and macrophages in the HSE can impact macrophage polarization. These data take us a step closer to creating a 3D skin disease model that can be applied to evaluate the response of candidate compounds needed for novel DFU therapies and for other complications of diabetes.

Macrophages have been shown to play an important regulatory role at key stages of wound healing. This is a function of their remarkable plasticity during different phases of the wound healing process.^18,19 M1 and M2 macrophage phenotypes represent two broad characterizations of functionally distinct macrophage subtypes^20,21 during normal wound healing. M1 polarized macrophages have undergone “classical activation” which is associated with proinflammatory, phagocytic activity. In contrast, M2 macrophage polarization or “alternative activation” stimulates keratinocyte and fibroblast migration and proliferation in concert with angiogenesis and fibroblast differentiation to myofibroblasts during the later stages of wound repair.^22,23 However, it is understood that this classification is somewhat simplified and that overlap exists between M1 and M2 states, resulting in phenotypes that exhibit features of both polarizations in the context of the complex wound microenvironment.²⁴

In normal wound healing, macrophages are recruited during the early, inflammatory phase of wound repair and function in recruitment of other inflammatory cells, release of cytokines and chemokines, and phagocytosis of neutrophils.^4,25 This prepares the wound for transition to the proliferative stage in normal healing, upon which macrophages function in the recruitment, activation, and proliferation of keratinocytes, endothelial cells and fibroblasts that alter ECM composition and direct tissue remodeling and healing. In diabetic wounds, the transition from the M1 to the M2 stage is suppressed, resulting in the maintenance of a chronic proinflammatory phenotype.^26,27 This leads to the sustained production of proinflammatory cytokines, chemokines, and proteases such as IL-6, TNF-a, Il-1b, and MMP-9, resulting in recruitment of additional inflammatory cells that are thought to limit wound closure.^22,28

The presence of DFU patient-derived fibroblasts and macrophages in this 3D tissue model faithfully reproduce the polarization to M1 macrophages and the cytokine profile seen in nonhealing, diabetic wounds in vivo. This creates a tissue model that can shift the cellular phenotype from a “healing” tissue environment to one that mimics the polarization state of the macrophages and the cytokine profile in DFUs in vivo. The elevation of a specific subset of inflammatory cytokines and the M1 versus M2 macrophage phenotypes are important biological endpoints that can be used to monitor the effect of candidate drugs in our tissue models.

By incorporating macrophages into our HSEs, we have shown that these cells can persist in the connective tissue as seen by immunohistochemical localization of macrophage subtype-specific markers. We demonstrate that PBMC-derived monocytes from diabetic patients stimulate production of M1 macrophage-derived, proinflammatory cytokines in these HSEs as is seen in patients with DFUs. We also provide evidence that the source of the fibroblasts (DFU vs. NFF) and their interaction with the incorporated macrophages may also play a role in macrophage polarization. Nonpolarized macrophages combined in tissues with DFU fibroblasts expressed HLADR in higher numbers, and higher levels of IL-6 were observed in tissues containing DFU versus NFF fibroblasts. Interestingly, the majority of cytokine secretions analyzed were not significantly impacted by the fibroblast source, further demonstrating the importance of including disease specific macrophages in creating a DFU disease model. We have also shown multiple approaches to developing macrophage containing HSEs, either through directly incorporating monocytes into HSEs without prior 2D culture or through polarizing macrophages in 2D culture before incorporation into these tissues.

Continued evaluation of this model will be necessary for its use in preclinical drug screening. Here, we highlight the interaction between fibroblasts and macrophages in HSEs to recreate the M1 phenotype seen in DFUs. For testing of therapies, it will be necessary to assess the potential of this model to transition from an inflammatory M1 to a healing M2 phenotype with nondiabetic cells. It will also be important to understand the role of keratinocyte-macrophage-fibroblast cross talk, which could enable the use of this system as a functional wound healing model. In addition, there are other inflammatory cell types such as neutrophils, and endothelium-lined blood vessels, which play a role in DFUs and are not found in our model. While we have shown that aspects of DFUs can be recapitulated using only fibroblasts, keratinocytes, and macrophages,^7,8 the value of adding additional complexity to this system must be investigated. Finally, testing this model with cells sourced from a larger number of DFU and control subjects will enable us to further understand how factors such as age, sex, and additional underlying conditions may impact the efficacy of drugs on wound repair in these complex 3D tissue models.

Previously, we have shown that a wound healing HSE model can mimic the impaired healing seen in DFUs.⁸ By demonstrating that patient-derived macrophages incorporated into our HSE model persist and are functionally responsive in the tissue microenvironment, we expect that this 3D skin disease model can eventually be used to accelerate the discovery and testing of new therapies for diabetic wounds.

Conclusion

In this article, we demonstrate methods for incorporating and evaluating macrophages in HSEs to create new techniques for disease modeling. We show two methods for incorporating macrophages in tissues, either by polarizing macrophages before incorporation, or by incorporating monocytes directly, where they differentiate into macrophages and polarize in the HSE. In addition, through the use of diabetic patient-sourced monocytes and fibroblasts in these tissues, we show that we can recapitulate aspects of the diabetic inflammatory phenotype seen in vivo. This research takes us one step closer to creating patient or disease-specific models of human skin, which can in the future be used for the testing of new potential therapies to treat DFUs.

Footnotes

Authors' Contributions

Conceptualization: A.S., A.V., D.M., and J.G. Formal Analysis: A.S. and T.W. Funding acquisition: A.V., D.M., and J.G. Investigation: A.S., T.W., M.L., and J.B. Methodology: A.S., T.R., S.R., G.T., A.M., and O.K. Project administration: A.S., A.V., D.M., and J.G. Resources: G.T., T.R., S.R., D.M., and A.V. Supervision: A.V., D.M., and J.G. Visualization: A.S. Writing—original draft: A.S., I.L., T.W., J.G., and A.V. Writing—review and editing: A.S., T.W., G.T., I.L., M.L., T.R., S.R., A.V., and J.G. All authors have reviewed and approved of the article before submission.

Disclaimer

This article has been submitted solely to this journal and is not published, in press or submitted elsewhere.

Acknowledgments

We thank Dr. Behzad Gerami-Naini, Dr. Megan Orzalli, and Dr. Mengqi Huang for their support.

Disclosure Statement

The authors state no competing financial interests exist.

Funding Information

This project was funded by grant DP3DK108224 awarded to Aristidis Veves, and grant 5R01DK098055 awarded to Jonathan Garlick, both from the National Institute of Diabetes and Digestive and Kidney Diseases.

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