Follow this and additional works at:

Transcription

1 University of Miami Scholarly Repository Open Access Dissertations Electronic Theses and Dissertations De-Regulation of MicroRNA and Gene Expression in Diabetic Foot Ulcers Lead to a Dampened Inflammatory Response, Inefficient DNA Repair and Inhibition of Cell Migration Horacio A. Ramirez University of Miami, horacio.a.ramirez@gmail.com Follow this and additional works at: Recommended Citation Ramirez, Horacio A., "De-Regulation of MicroRNA and Gene Expression in Diabetic Foot Ulcers Lead to a Dampened Inflammatory Response, Inefficient DNA Repair and Inhibition of Cell Migration" (2016). Open Access Dissertations This Open access is brought to you for free and open access by the Electronic Theses and Dissertations at Scholarly Repository. It has been accepted for inclusion in Open Access Dissertations by an authorized administrator of Scholarly Repository. For more information, please contact repository.library@miami.edu.

2 UNIVERSITY OF MIAMI DE-REGULATION OF MICRORNA AND GENE EXPRESSION IN DIABETIC FOOT ULCERS LEAD TO A DAMPENED INFLAMMATORY RESPONSE, INEFFICIENT DNA REPAIR AND INHIBITION OF CELL MIGRATION By Horacio Adrian Ramirez A DISSERTATION Submitted to the Faculty of the University of Miami in partial fulfillment of the requirements for the degree of Doctor of Philosophy Coral Gables, Florida August 2016

3 2016 Horacio Adrian Ramirez All Rights Reserved

4 UNIVERSITY OF MIAMI A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy DE-REGULATION OF MICRORNA AND GENE EXPRESSION IN DIABETIC FOOT ULCERS LEAD TO A DAMPENED INFLAMMATORY RESPONSE, INEFFICIENT DNA REPAIR AND INHIBITION OF CELL MIGRATION Horacio Adrian Ramirez Approved: Derek Dykxhoorn, Ph.D. Associate Professor, John T. Macdonald Foundation Department of Human Genetics Abigail Hackam, Ph.D. Associate Professor, Department of Ophthalmology Tongyu Wikramanayake, Ph.D. Research Associate Professor, Department of Dermatology and Cutaneous Surgery Joaquin Jimenez, M.D. Research Professor, Department of Dermatology and Cutaneous Surgery Marjana Tomic-Canic, Ph.D. Professor, Department of Dermatology and Cutaneous Surgery Guillermo Prado, Ph.D. Dean of the Graduate School

5 RAMIREZ, HORACIO ADRIAN (Ph.D., Human Genetics and Genomics) De-Regulation of MicroRNA and Gene Expression (August 2016) in Diabetic Foot Ulcers Lead to a Dampened Inflammatory Response, Inefficient DNA Repair and Inhibition of Cell Migration Abstract of a dissertation at the University of Miami. Dissertation supervised by Professor Marjana Tomic-Canic. No. of pages in text. (104) Diabetic foot ulcers (DFUs) are a common and severe type of chronic wound of which molecular pathophysiology is poorly understood, resulting in slow development of new and efficacious treatments. The aim of this study was to identify cellular functions that contribute to pathophysiology of DFUs as compared to the acute wounds, by using genomic profiling. I postulated that de-regulation of DFU-specific genes and micrornas (mirs) play an important role in the development of a chronic wound phenotype. I utilized a bedside-to-bench approach in which DFU tissue samples from patients, non-neuropathic diabetic (DFS) and non-diabetic foot skin (NFS) biopsies were used to generate microarray expression profiles and mir PCR expression profiles. Comparison of the expression profiles of DFS and NFS revealed only minor mir and gene expression changes between these two sets of samples, which was further supported by histo-morphometric assessments, suggesting that diabetes causes subtle changes to foot skin itself. Next, I compared the DFU gene expression profiles to the foot skin (FS) profiles (NFS and DFS) identifying a set of differentially expressed genes in DFUs. To select specific genes unique for DFUs I performed additional comparison of DFU list of genes to publically available human skin acute wound (AW) profiles. I used Ingenuity Pathway

6 Analysis (IPA) software to do functional enrichment and comparative analysis between them and found down-regulation of gene expression and suppressed DNA repair mechanisms among processes uniquely enriched in DFUs. Genes involved in DNA-repair mechanisms were down-regulated in DFUs, suggesting impairment in this process, which was confirmed by increased presence of phospho-histone H2A.X (γ-h2ax), a known marker for double strand DNA damage. In contrast, the inflammatory response that was highly induced in AW was not effectively up-regulated in DFUs. Furthermore, I examined potential upstream-regulators of these DFU-specific genes and identified mir-15b-5p as predicted to be up-regulated in DFUs but not in AWs. I tested mir-15b-5p expression in DFUs by qpcr and confirmed its up-regulation in all samples of DFUs, but not in AW. Moreover, mir-15b-5p was identified as an upstream regulator of multiple genes suppressed in DFUs including IKBKB, PIK3R1, and WEE1. Further, its induction can be triggered by infection with Staphylococcus aureus, one of the most common pathogens found in DFUs. Lastly, I compared DFU mir profiles to AW mir profiles generated from an ex-vivo acute wound model. mir-193b-3p was found to be induced in DFUs, but down-regulated in AWs. Transfection of mir-193b-3p in the human keratinocytes, resulted in inhibition of scratch wound assay in vitro, even in the presence of the pro-migratory hsa-mir-31-5p or hsa-mir-15b-5p. These results imply that mir-193b-3p has a major role in inhibiting keratinocyte migration in DFUs. Surprisingly, S. aureus infection was also found to induce mir-193b-3p in human ex-vivo wounds. In summary, I discovered novel mechanisms that contribute to the pathogenesis of DFUs, which may be triggered by the presence of S. aureus. On one hand, up-regulation of mir-

7 15b-5p may lead to suppression of DNA repair mechanisms and dampened inflammatory response through suppression of WEE1 and IKBKB among other genes, whereas on the other hand, mir-193b-3p dominantly inhibits keratinocyte migration resulting in nonmigratory epidermal edge characteristic of DFUs. These mechanisms identify potential targets for development of novel therapeutic and diagnostic approaches.

8 ACKNOWLEDGEMENTS To Dr. Marjana Tomic-Canic for her great mentorship, patience and guidance throughout this journey. To Dr. Irena Pastar and Dr. Olivera Stojadinovic for training me and being such terrific comentors. To my lab mates for helping me with my projects. To the faculty in the Human Genetics and Genomics Program for the education and knowledge provided. Also, I would like to acknowledge Dori McLean for her assistance with all the administrative tasks, constant follow ups and reminders. To the Department of Dermatology for such stimulating work environment. To Dr. Jorge Torres-Muñoz for his teachings inside and outside the lab To my friends, old ones and new ones, that accompanied me in the good times but also in the tough ones. To my family, especially to my parents, who in spite of the distance, were always there to listen to me and support me, and also to keep me on track. iii

9 TABLE OF CONTENTS List of Figures... vi List of Tables... viii List of Abbreviations... ix Chapter 1. Introduction Clinical problem: diabetic foot ulcers Complications of diabetes Diagnosis, treatments and approved therapies for diabetic foot ulcers The cutaneous wound healing process The role of keratinocytes in wound healing, inflammation and epithelialization Phenotypic changes observed in chronic wounds Molecular pathogenesis of chronic wounds Inflammation in chronic wounds Chronic wound alterations in epidermis during the proliferative phase Chronic wound alterations in dermis during the proliferative phase MicroRNAs as regulators of gene expression MicroRNAs in cutaneous wound healing Hypothesis and study design Chapter 2. Methods Tissue samples Laser Capture Microdissection (LCM), microrna extraction and profiling from epidermis mrna profiling (microarrays) Real-time qpcr for microrna and gene expression analysis Protein isolation and western blot H&E, immuno-peroxidase staining Immunofluorescence Cell culture and transfection Luciferase assays Scratch wound assay Cell viability assay Stimulation of cell motility and Phalloidin staining Bacterial strains and growth Conditions Human ex vivo wound infection model iv

10 2.15. Statistical analyses Chapter 3. Subtle differences between Diabetic and non-diabetic skin Epidermal mir profiles show minor differences between DFS and NFS Validation of the mir epidermal expression in skin Transcriptomes of diabetic and non-diabetic foot skin reveal small differences Histological evaluation shows no observable differences between DFS and NFS Lymphocytes, blood vessels, and keratinocyte proliferation are similar between DFS and NFS Chapter conclusion Chapter 4. Transcriptional changes in DFUs DFU gene expression profiling and comparison with AW transcriptome Functional enrichment and comparative analysis of DFU and AW Comparative analyses between DFUs and AWs shows distinct subset of genes regulated in the same direction Network analysis and gene expression validation DFUs exhibit down-regulation of DNA repair mechanisms and subsequent increased DNA damage Mir-15b-5p up-regulation in DFUs leads to diminished Inflammatory Response and DNA Repair S. aureus infection causes induction of mir-15b-5p and subsequent suppression of IKBKB and WEE Chapter conclusion Chapter 5. mir expression in the epidermis of DFUs microrna expression in the epidermis of DFUs Ex-vivo acute wound mir profiling and comparison with DFU mir profiles mir-193b-3p inhibits cell migration and has a dominant effect over other mirs mir-193b-3p prevents formation of stress fibers S. aureus infection induces mir-193b-3p and inhibits wound healing ex vivo Chapter conclusion Chapter 6. Conclusions and future directions Summary and conclusions Future directions Appendix References v

11 LIST OF FIGURES Figure 1.1. H&E staining of human normal skin and the non-healing edge of a chronic wound Figure 1.2. microrna processing and gene targeting Figure 1.3. Proposed experimental design for identification and validation of differentially expressed genes in DFUs Figure 1.4. Proposed experimental design for identification, validation and functional evaluation of differentially expressed mirs in DFUs Figure 3.1. MicroRNA expression profiling show minimal differences between diabetic and non-diabetic foot epidermis Figure 3.2. mir-31-3p and mir-31-5p show a trend of up-regulation in epidermis of DFS which correlates with the expression in full-thickness biopsies Figure 3.3. Gene expression profiling between diabetic and non-diabetic foot skin reveals small set of genes de-regulated in DFS Figure 3.4. Evaluation of the morphology of DFS shows no major differences in comparison to NFS Figure 3.5. Quantification of lymphocytes, blood vessels and proliferating keratinocytes show similar numbers between DFS and NFS Figure 4.1. Representative H&E staining of full thickness biopsies from DFU and FS.. 43 Figure 4.2. Microarray analysis of differentially expressed genes between DFU and AW Figure 4.3. Enriched functions and processes in DFU and AW Figure 4.4. Network analysis and gene expression validation of DFU de-regulated genes Figure 4.5. DNA repair mechanism related genes are suppressed in DFU Figure 4.6. mir-15b-5p is up-regulated in DFUs and target several regulatory genes Figure 4.7. mir-15b-5p suppresses IKBKB, WEE1, and PIK3R1 expression in HaCaT cells Figure 4.8. mir-15b-5p targets the 3 UTRs of IKBKB and WEE Figure 4.9. Infection of ex-vivo wounds inhibits wound healing Figure mir-15b-5p is induced in AW infected with S. aureus and targets IKBKB and WEE Figure Scheme showing how mir-15b-5p regulates many processes involved in pathophysiology of DFUs Figure 5.1. Laser capture microdissection (LCM) and mir profiling of epidermis from DFUs and FS vi

12 Figure 5.2. Validation of mir expression by qpcr in LCM captured epidermis and full thickness DFU biopsies Figure 5.3. mir-31-5p, mir-135b-5p, mir-199a-3p and mir-214-3p expression in ex-vivo AW model Figure 5.4. Comparative analysis of regulated mirs between DFUs and AWs Figure 5.5. In vitro scratch wound assay using single mir mimics Figure 5.6. mir-193b-3p does not influence cell viability Figure 5.7. In vitro scratch wound assay using combination of mir mimics Figure 5.8. mir-193b-3p prevents formation of stress fibers in keratinocytes Figure 5.9. MiR-193b-3p is induced in S. aureus infected human acute wounds vii

13 LIST OF TABLES Table 2.1. Patient demographics, and sample information Table 2.2. List of primers used for qpcr Table 2.3. List of antibodies used for Western blots Table 2.4. List of antibodies used for immune-peroxidase staining Table 3.1. List of differentially expressed genes between DFS and NFS Table 4.1. Expanded functional enrichment of the DNA replication, recombination and repair category Table 4.2. Top regulated functions obtained from IPA functional enrichment analysis obtained from the oppositely regulated genes in DFUs and AWs Table 4.3. Top 30 down- and up-regulated genes in both DFUs and AWs (sorted by AW expression) Table 5.1. List of differentially expressed mirs in the epidermis of DFUs when compared to FS Table 5.2. mir expression correlation between LCM captured epidermis and full thickness skin biopsies Table 5.3. List of differentially expressed mirs during ex-vivo AW healing Table 5.4. mir-193b-3p predicted targets involved in cell migration that are specifically down-regulated in DFUs viii

14 LIST OF ABBREVIATIONS AW: Acute wound cscc: cutaneous squamous cell carcinoma DFS: Diabetic Foot Skin DFU: Diabetic Foot Ulcer DM: Diabetes mellitus ECM: Extracellular matrix EGF: Epidermal growth factor FDA: U.S. Food and Drug Administration FGF: Fibroblast growth factor FS: Foot Skin (including both diabetic and non-diabetic) GEO: Gene Expression Omnibus HB-EGF: Heparin-binding EGF-like growth factor IRB: Institutional review board LPS: lipopolysaccharide mir: microrna NFS: Non-diabetic Foot Skin PDGF: Platelet-derived growth factor TGF-α: Transforming growth factor alpha TGF-β: Transforming growth factor beta UTR: Untranslated region ix

15 CHAPTER 1. INTRODUCTION 1.1. Clinical problem: diabetic foot ulcers The world-wide diabetic population among adults was approximately 8-9% (~350 million) in 2014 (1, 2). The incidence of diabetes is rapidly increasing and, if the current trend is maintained, its prevalence is expected to rise even higher in the near future, possibly affecting a third of the U.S. adult population by the year 2050 (1, 3). Currently, there are approximately 29.1 million diabetic people in the U.S. alone (4). Various complications of diabetes, including foot problems such as ulcers, infection and gangrene, are a major cause of hospitalization (5). Among these, diabetic foot ulcers (DFUs) are relatively common, occurring annually in up to 5% of diabetic individuals, with a lifetime risk up to 25% (6-8). The economic burden of DFUs, one of the most devastating complications of diabetes, is an estimated $9-13 billion/year in addition to the overall costs of diabetes (9). These ulcers frequently become infected, fail to heal in a timely fashion and may lead to amputation (10-12). In fact, around 60% of non-traumatic lower limb amputations occur in people with diabetes (4). The presence of neuropathic foot ulcer is an independent mortality factor and patients with DFUs show mortality rates higher than patients with breast or colon cancer (13, 14). Thus, DFUs produce longer hospitalization periods, reduce quality of life (15, 16), and cause higher morbidity and mortality (17) Complications of diabetes Multiple complications have been associated with diabetes mellitus (DM), and approximately a third of the diabetic population exhibit cutaneous manifestations (18). Chronic foot ulcers, dermopathy, acquired perforating dermatosis, and calciphylaxis, are among the most common ones (19). As mentioned before, one of the most challenging 1

16 2 complications are DFUs, due to their high morbidity, mortality, and devastating consequences (4, 20-23). The molecular pathogenesis of DFU is complex and involves multiple factors, including neuropathy, ischemia, impaired immune function and infection (20, 24). DM also often causes corneal manifestations including keratopathy, superficial punctate keratitis, erosions and endothelial abnormalities. Sometimes, similarly to skin, diabetic patients exhibit delayed corneal healing following surgery or injury (25, 26). In spite of the urgent medical need, molecular mechanisms leading to the inhibition of healing in diabetic population are still not well understood. In addition to epithelial complications, diabetic individuals may develop macro- and microvascular problems (27), abnormal angiogenesis (28), humoral and cellular immune deficiencies, infections (29), extracellular matrix changes and fibrosis (30) nephropathy and neuropathy (27), among others. Most of these complications, have been reported in other tissues and are commonly found in DFUs (31), but it is not clear if their role is causal or consequential in the impairment of wound healing Diagnosis, treatments and approved therapies for diabetic foot ulcers Even though the incidence of diabetes, and subsequently DFUs, has been on the rise in the past decade, up to this day there are no efficacious treatments. The treatment for DFU is not simple and includes adequate perfusion, frequent debridement, infection control and pressure (load) release (10, 32). However, even the wounds that are adequately managed may not heal in a proper time frame and are more likely to become infected, require hospitalization and even limb amputation (32). Around 40% of neuropathic ulcers fail to heal after 12 weeks of good wound care and 30% of wounds fail to heal after 20 weeks (33). This shows that a large percentage of diabetic ulcers are hard-to-heal, even when

17 3 constantly treated by standard of wound care. In the past years, few therapies and devices were approved by the FDA to treat DFUs involving growth factor therapy using human recombinant PDGF-bb or skin equivalents (23). However, these therapies are expensive and in spite their approval by the FDA, they have shown efficacy of no more than 50-60% in the best cases (34-36), which, added to the high recurrence of these ulcers and the associated problems previously discussed, support the urgent need of the development of new and more effective therapies. Another important fact is that lack of good surrogate markers of wound closure makes the treatment strategy highly inefficient (37). Having a good healing predictor (either a predictive biomarker or a surrogate clinical endpoints) would provide physicians with the opportunity to change clinical protocols, initiate more aggressive treatments at appropriate times or validate their efficacy more effectively, which in turn will improve healing outcomes, quality of life and reduce time and cost of treatment. Unfortunately, the only promising predictive marker to detect hard-to-heal wounds relies on the measurement of the wound area reduction after 4 weeks of standard of care and weekly wound measurements. Wounds with areas reduced by less than approximately 50% are less likely to heal after 12 weeks of treatment. (6, 32). Because of this, it is imperative to understand the molecular mechanisms leading to the chronic state of these wounds in order to tailor new treatment strategies that can be applied to prevent, control or close DFUs The cutaneous wound healing process After an injury, a cascade of events leading to restoration of the skin barrier is set in motion. The wound healing process is timely ordered and proceeds through overlapping phases,

18 4 comprising hemostasis, inflammation, proliferation, and remodeling. (23, 38, 39). Each of these phases involves multiple cellular components that interact with each other through several molecules that have to be precisely controlled spatially, in duration and intensity. (23, 38-40). The first step of this cascade is coagulation and hemostasis which occur immediately after a wound is created to quickly stop blood and fluid loss but also to provide a provisional matrix for other cells to infiltrate and migrate towards the injury (41, 42). Vascular smooth muscles temporarily constrict the injured blood vessels to reduce bleeding due to a reflex mechanism (41). Simultaneously, the coagulation cascade is activated causing platelet aggregation and the formation of a clot consisting of fibronectin, fibrin, vitronectin and thrombospondin which serves as a physical barrier to stop bleeding but also as a scaffold for the incoming cells (41, 43). During this step, platelets degranulate, releasing multiple growth factors and cytokines including PDGF, TGFβ, and EGF and the complement is activated producing C3a and C5a which attract and activate neutrophils, macrophages, endothelial cells, fibroblasts and keratinocytes resulting in the initiation of the inflammatory phase (23, 44, 45). Neutrophils are the first inflammatory cells migrating into the wound (24-36h) to clear dead cells and infectious microorganisms by phagocytosis or releasing neutrophil extracellular traps (NETs) (45, 46). The activity of neutrophils is short to prevent host tissue damage and excessive inflammation and it is controlled by their apoptosis and NETosis once the infection is controlled (41, 47). Next, macrophages make their appearance at the wound site 48-72h after injury to take over the clearance of microorganisms as well as cell debris left by neutrophils but also to act as regulatory cells by secreting TGF-α, TGF-β, HB-EGF, FGFs and collagenase which activate fibroblasts,

19 5 endothelial cells and keratinocytes (41). Once the injury has been stabilized the proliferative phase is set in motion which comprise the proliferation and migration of fibroblasts, keratinocytes, endothelial cells and others to the wound site (23, 41, 42). During this phase new tissue formation begins; once in the wound site fibroblasts produce collagens and other matrix proteins, proteoglycans, hyaluronic acid and several others, and together with macrophages replace the provisional fibrin matrix with granulation tissue. By the end of the proliferative phase, fibroblasts differentiate into contractile myofibroblasts which also contribute to pull the wound edges together (48, 49). Simultaneously, endothelial cells, mostly stimulated by VEGFA and FGF2, together with other cells start forming new blood vessels (angiogenesis) and sprout capillaries to vascularize the tissue that is being formed (42, 48). The other key process during the proliferative phase is epithelialization which starts hours after injury and continues until the barrier is restored. Keratinocytes from the wound edge become activated and migrate over the provisional matrix to close the gap, while the cells at the edge begin to proliferate (40, 48). Lastly, the remodeling phase of the wound takes over. This stage starts with granulation tissue formation and can last over a year, after wound closure is achieved, and consists of the reorganization of the initially highly disorganized connective tissue and the recovery of its physical properties (41). During this stage the majority of macrophages, endothelial cells and myfibroblasts leave the wound or undergo apoptosis leaving only a few cells which together with fibroblasts carry out the remodeling by secreting matrix metalloproteinases (MMPs) and shifting the matrix backbone from mainly type III collagen to mainly type I (42). A fine balance between synthesis and degradation of the matrix is

20 6 regulated by the production of matrix molecules, MMPs and their respective tissue inhibitors (TIMPs). By the end of the process, most of the tensile strength of the skin is regained (41) The role of keratinocytes in wound healing, inflammation and epithelialization Keratinocytes are the major cellular component of the epidermis, the outermost layer of the skin. The main function of the epidermis is to provide a physical barrier by limiting the loss of fluids and to protect the organism from external substances and pathogens (50-52). Keratinocytes are perpetually maintaining this barrier through a process involving terminal differentiation in which they change from a proliferative state in the basal layer to more differentiated states while they migrate outwards through the granular layer, to finally becoming the flattened and crosslinked dead cell remainder of the cornified layer (50-52). Furthermore, keratinocytes are not only responsible for maintenance of the epidermis but they are also a key element in its repair through the previously mentioned epithelialization process, as well as in the coordination of the overall wound healing process by recruiting, stimulating, and coordinating other cell types (40, 53). Immediately after wounding, keratinocytes release stored IL-1 which acts as one of the first signals to stimulate and attract other cells to the wound site, trigger inflammation, but also to activate keratinocytes to a migratory phenotype (53). In addition, keratinocytes respond, interact and coordinate other cell functions through a variety of growth factors and cytokines including TGFβ and activins, EGF and FGF family members, GM-CSF, IGF and others. The secretion of TGFβ is highly induced by keratinocytes, platelets and macrophages upon injury and it is required for mounting a proper inflammatory response and granulation tissue formation (53-55).

21 7 Keratinocyte function and epithelialization is also regulated by signaling molecules produced by other cells. FGF7 for example, which is produced by fibroblasts and immune cells but not keratinocytes, is a potent keratinocyte proliferation and migration stimulant and acts in a paracrine manner through the FGFR2-IIIb receptor which is specific for keratinocytes (56, 57). It is important to mention that epithelialization is also used as a defining parameter of wound healing given that a breach in the barrier provides access for infection. This is the case for chronic wounds, in which this process is impaired among others that are discussed below. Therefore, a wound is considered healed only if it is 100% epithelialized, which is the only criteria used as clinical endpoint by the FDA Phenotypic changes observed in chronic wounds During acute wound healing each of the phases mentioned before have a defined temporal and spatial distribution, whereas in chronic ulcers this process is altered and seems to remain in a chronic inflammatory state, leading to a delayed or non-healing phenotype (58-61). As the name implies, chronic wounds are wounds that fail to execute the wound healing process appropriately. Molecular pathogenesis of DFUs as well as other chronic wounds is not completely understood and the causes by which the healing process is impaired remain unknown. It has been observed that chronic wounds in general share certain characteristics such as: impairment in epithelialization, whereby there is loss of control of migration, proliferation and differentiation of keratinocytes compared to acute wound healing and healthy epidermis. In chronic wounds, keratinocytes are found in a hyperproliferative state at the non-healing edge, and mitotically active cells can be found in suprabasal layers of the epidermis, whereas in healthy skin suprabasal cells would have

22 8 exited mitosis and begun terminal differentiation (Figure 1.1). Also other typical characteristics of chronic wounds related to irregular function of keratinocytes are parakeratosis (presence of nuclei in cornified layer) and hyperkeratosis (thick cornified layer) (Figure 1.1) (58, 59, 62, 63). All these characteristics indicate de-regulation of keratinocyte activation and differentiation. The tissue samples from chronic DFUs used in this study were validated based on these specific histopathological characteristics, as described in details in the experimental procedures. FS DFU Hyper and parakeratotic cornified layer Cornified layer Epidermis Hyperproliferative epidermis Figure 1.1. H&E staining of human normal skin and the non-healing edge of a chronic wound. Left: H&E staining of human normal skin; right panel: non-healing edge of a chronic wound (right). Arrows indicate cell nuclei Molecular pathogenesis of chronic wounds DFUs, similar to all other types of chronic wounds, seem to develop from multifactorial causes involving both extrinsic and intrinsic factors (64, 65). The extrinsic factors include physical stresses such as excessive pressure or repeated trauma and wound infection (64, 65) while the intrinsic factors that may impair healing in diabetic patients involve the alteration of the function of multiple cell types including keratinocytes, fibroblasts, leukocytes and others, resulting in an abnormal and prolonged inflammatory response, improper formation and remodeling of the extracellular matrix, impaired infection

23 9 clearance, neuropathy, macro- and micro-vascular dysfunctions and reduced reepithelialization (65-69). The molecular changes underlying these observations seem to be vast and affect virtually every stage and cell type in the wound healing process, in particular in the inflammatory and proliferative phase of wound healing as it will be discussed below Inflammation in chronic wounds An aberrant and prolonged inflammatory response is a common denominator in chronic wounds that contributes to poor healing. During normal acute wound healing a tightly regulated, but very robust, inflammatory response is necessary to set the healing process in motion, trigger the immune response, avoid infection, remove debris, and induce cell proliferation (70). However, if inflammation is not controlled and is prolonged it may cause excessive tissue damage, induction of MMPs, reduced synthesis of collagen, and inhibition of epithelialization (65, 67, 70). The prolonged inflammatory response has been associated and influenced by many causes. Higher serum levels of advanced glycation end-products (AGEs) in diabetic individuals can result in a subclinical chronic inflammatory state and interfere with collagen synthesis (65, 67). Also, uncontrolled diabetes and neuropathy can change the number of infiltrating cells in the skin. It was observed that there is higher numbers of inflammatory cells in forearm skin of neuropathic individuals (71, 72), but not in non-neuropathic ones (73). Surprisingly, the opposite has also been observed in studies done in mouse models, where reduced number of infiltrates as well as abnormal function of macrophages in diabetic wounds was observed compared to the non-diabetic littermates (74-76). Reduced number of infiltrates in diabetic mouse wound models leads to deficient

24 10 dead cell clearance, aberrant cytokine and chemokine secretion and wound infection (74-76) Chronic wound alterations in epidermis during the proliferative phase Upon acute injury, healthy keratinocytes undergo a process known as activation in which they become hyperproliferative, migratory, more responsive to growth factors by augmenting the expression of surface receptors and secreting several signaling molecules required for wound healing (77-81). However, as mentioned earlier, this activation is not properly executed by keratinocytes in chronic wounds. The results reported by Stojadinovic et. al. from a gene expression study from another type of chronic wound, venous ulcers, suggest that some aspects of the activation process may be triggered, but are not properly executed such as de-regulation of genes that control cell cycle, resulting in uncontrolled proliferation (82, 83). Furthermore, chronic ulcers exhibit nuclear localization of β-catenin and overexpression of its downstream target c-myc that may also contribute to changes in cellular proliferation. (58). C-myc is a well-studied oncogene known to increase proliferation and apoptosis and cause transformation of mammalian cells (84, 85). Interestingly, c-myc overexpression in keratinocytes leads to impaired migration as it was shown in a transgenic mouse model by Waikel et al (84) and confirmed in our lab in a human ex-vivo wound model (58). The activation of β-catenin not only increases expression of c-myc but it can also block EFG response in keratinocytes and synergize with glucocorticoid signaling to repress K6/K16 contributing even more to inhibition of their migration, deregulation of growth and differentiation. (58, 59). Our laboratory also reported that activation of β-catenin and c-myc in non-healing edge of chronic wounds promotes cycling of epidermal stem cells leading to their depletion (83).

25 11 Another molecular change important for the development of chronic wounds seems to be the inability of the cells to mount proper responses to signaling molecules (20, 58, 59, 86). An example of this is TGFβ signaling, which can act as suppressor of cell proliferation and is required for keratinocytes to exit the activated state and return to a basal phenotype (55, 77, 87). This pathway is impaired in venous ulcers due to a lower expression of TGFβ receptors in the cell surface and reduced activation of Smad2, a crucial mediator of the TGFβ signaling pathway (86). These findings indicate that keratinocytes in chronic ulcers become activated and proliferate, although, in contrast to an acute wound response, this activation is only partial or is halted as they cannot migrate or differentiate properly. Part of this issue appears to be due to the fact that they cannot respond to signaling molecules present in the wound as a consequence of down-regulation of receptors or genes involved in the signaling pathways Chronic wound alterations in dermis during the proliferative phase As previously mentioned, wound healing is a multi-cellular response and keratinocytes are not the only cells that contribute to healing or are affected in non-healing wounds. Fibroblasts from DFUs are deficient in de-novo synthesis of ECM, show altered cytokine expression, including diminished pro-angiogenic factors and can also recapitulate the hyperproliferative and non-migratory phenotype of the epidermal cells in organotypic cocultures with normal keratinocytes (66). ECM degradation is increased in DFUs due to higher MMP production (70). MMPs including MMP1, 2, 8, 9, 14 and 26 have been shown to have a high expression in DFUs (88-91) and their balance with their respective inhibitors (tissue inhibitor of metalloproteinases, TIMP) are disrupted (37). Higher MMP1/TIMP1 ratio is correlated with healing (92), while higher MMP9/MMP1 ratio is associated with

26 12 poor healing outcomes (90). Furthermore, TIMP2 was also found to be down-regulated in DFUs which also support the idea of a highly proteolytic environment and decreased quality of ECM in DFUs (93) MicroRNAs as regulators of gene expression Due to deregulation of multiple signaling factors and pathways in DFUs, we postulated that major gene expression regulators, mirs, play a role in pathogenesis. MiRs are known to have the potential to affect multiple genes and networks simultaneously, which control spatial and temporal execution of the process of wound healing, including inflammatory response, cellular migration and tissue growth. Hence, understanding regulation and signaling by mirs in DFUs could also provide an important key to better understand the pathophysiology and open new possibilities for new therapies and diagnostic biomarkers. MiRs are short non-coding RNAs of approximately 22 nucleotides long that can act as post-transcriptional gene expression repressors by targeting the mrna to degradation, storage into p-bodies or simply blocking its translation (51, 94-96). They are synthesized by the RNA polymerase II, similarly to mrna, but they go through a number of processing steps by different enzymes in the nucleus and cytoplasm to give the mature mir which is assembled into a complex called RISC (RNA induced silencing complex) (Figure 1.2). In order to exert its function, the mir in this complex interacts with the 3 UTR of mrnas through Watson-Crick base pairing of a conserved 6 8 bp seed sequence. (97-99). In addition, mirs are known to exert their effects both locally and systemically, whereby they are often exported in extracellular vesicles or exosomes and enter circulation (100). The importance of mir relies on the fact that a single mir molecule can target and regulate a few hundred genes and vice versa, a single gene can be targeted by multiple mirs, so

27 13 they regulate several if not all cell processes, including cell survival, differentiation and homeostasis, and they have been found to be deregulated in multiple diseases such as immune diseases, various types of cancer and even skin affections like psoriasis and more recently chronic wounds ( ). De-regulation of signaling pathways is one of the known factors that contributes to non-healing wound phenotype, and therefore it is reasonable to expect that a specific set of mir may contribute to the observed de-regulation. However, the evidence of mirs implicated in DFUs is very limited and thus this work seeks to elucidate the role of these regulatory RNAs in the pathogenesis of chronic wounds. Figure 1.2. microrna processing and gene targeting. mirs are transcribed by RNA polymerase II as primary transcripts (pri-mir). Then they are processed by a Drosha-DGCR8 complex resulting in a mir hairpin precursor (pre-mir) of approximately 70 nucleotides. The pre-mir is exported to the cytoplasm by exporting-5 where it is further processed by the endoribonuclease Dicer to generate 22 nucleotide duplexes. One of the strands of the processed duplexes is incorporated into a RISC complex (RNA induced silencing complex) together with Ago2. The RISC complex can then bind to 3 UTR of target genes repressing their translation, leading them to storage in P-bodies or to degradation (96) MicroRNAs in cutaneous wound healing The functions of mirs in skin were first evidenced in mice with a Dicer (an endoribonuclease involved in the processing of mirs) conditional knockout in epidermis, which had an abnormal organization of the epidermis, impaired hair follicle development and increased cell proliferation ( ). Furthermore, specific mirs were identified to be

28 14 differentially expressed in epidermis or in hair follicle and not in other skin cell types (108). Among those mirs, the keratinocyte-specific mir-203 plays an essential part in skin morphogenesis and keratinocyte differentiation by targeting p63 in the suprabasal layers of the epidermis, while it is not present in the basal layer allowing p63 to maintain the proliferative state of keratinocytes and initiate their stratification (106, ). This mir was found to be deregulated in psoriasis, where in contrast with its function in normal skin, it is found up-regulated in hyper-proliferative keratinocytes (106). Interestingly, it has also been found to be up regulated in epidermis of venous ulcers (105). It is important to note that psoriasis and chronic wounds share some traits such as a hyper-proliferative, thickened epidermis and a chronic inflammation state which may lead us to think that they could share common molecular pathology. Other examples for mir regulating keratinocyte function, proliferation and/or migration in epidermis and wound healing are mir-483-3p (113), mir-205 (114), and mir-125b, (115) which will be discussed in the following sections. mir-483-3p is up regulated at later stages of wound healing to stop keratinocyte migration and proliferation by targeting MK2, KI67, and YAP1 (113), while mir-125b was found down-regulated in psoriatic lesions and to promote proliferation and differentiation of keratinocytes through regulation of FGFR2 (115). On the other hand, mir-205 can induce cell migration through targeting of SHIP2 and cytoskeleton remodeling (114). So far, the cell function regulation by mirs extend not only to keratinocytes but virtually to any cell type in the body. Moreover, they have been found to play a role in almost every step of the wound healing process, from epithelialization and keratinocyte differentiation as mentioned above, to inflammation, granulation tissue formation and fibroblast

29 15 functions, and angiogenesis. (51, 109). Very often, similar mirs are found in multiple types of pathologies, including cancers, metabolic disease etc (51, ). Furthermore, our lab identified a specific set of mirs and their role in venous ulcers, another common type of chronic wound (105). Using information from gene expression profiles previously generated in our lab, we were able to identify a set of mirs with aberrant expression in these chronic wounds compared to normal skin. Among of these, mir-21 and mir-130a were confirmed to target several genes relevant to wound healing including early growth response factor 3 (EGR3) and leptin receptor (LepR). Furthermore, mir-21 and mir-130a functionally inhibited epithelialization in a human ex-vivo wound model and in an in vivo rat wound model. (105). The transcription factor EGR3 has been predicted to promote keratinocyte migration in silico (119) and it is rapidly induced upon EGF signaling pathway activation (120). On the other hand, leptin is a hypoxia-inducible pleiotropic cytokine essential for wound healing and leptin null (ob/ob) or leptin receptor null (db/db) mice are characterized by severe impairment of healing and serve as model for pathological wound closure (105, 121). More importantly, leptin has been shown to enhance wound reepithelialization when topically applied (122). This study identified specific mirs that are triggering mechanisms that inhibit healing and play an important role in pathophysiology of chronic venous ulcers. In the current study I identified mir molecules that were specifically deregulated in DFUs Hypothesis and study design Based on previously discussed literature and the molecular changes in other chronic wounds, I hypothesize that there are both transcriptional and mirs expression changes in DFUs that play an important role in the development of a chronic wound phenotype by

30 16 targeting multiple cellular functions and processes. Therefore, the goal of this work is to determine the overall molecular changes in the pathogenesis of DFUs and particularly the involvement of mirs in the regulation of these changes that lead to the inhibition of healing. This could potentially facilitate the discovery of new affected pathways, deregulated mirs, their target genes, and identify potential biomarkers, novel therapeutic targets and treatments for DFUs. To achieve this goal, I proposed to generate mrna and mir expression profiles from DFU, diabetic foot skin (DFS) and non-diabetic foot skin (NFS) and compare these profiles to those from human acute wounds with the goal of identifying genes, mirs and their related processes that are specifically de-regulated in DFUs. The outline of the experimental design is shown in Figure 1.3 and Figure 1.4. First, I proposed to compare both mir and gene expression profiles from DFS and NFS in order to identify possible differences that may explain or predispose to inhibition of healing in diabetic patients and validate the results using PCR, western blots and/or immunohistochemical techniques. Next, based on these results I proposed to generate a list of regulated genes in DFUs in comparison to DFS and NFS and compare this list to one generated from publically available gene expression profiles from human AW in order to find uniquely de-regulated genes in DFUs. I proposed to use Ingenuity Pathway Analysis (IPA) to carry out functional enrichment analyses and identify cellular functions and processes that are de-regulated in DFUs in comparison to AWs. Finally, I proposed to use a similar approach to identify mirs that are regulated in DFUs by comparing DFU mir profiles to those obtained from FS. In addition, comparative

31 17 analyses of DFU to mir profiles generated from ex-vivo AWs will lead to identification of mirs specifically de-regulated in DFUs. The mir expression in DFUs and AW would be validated using qpcr. Possible mir downstream targets and affected processes will be selected using the previously generated gene expression profiles and evaluated using IPA. Figure 1.3. Proposed experimental design for identification and validation of differentially expressed genes in DFUs. = experimental validations and results, = analysis results, = technical methods and analysis, = source materials. Providing that inhibition of migration is one of the hallmarks of pathophysiology of DFUs I proposed to focus on mirs that inhibit epithelialization. An in-vitro wound model as well

32 18 as a three-dimensional organotypic skin culture of fibroblasts and keratinocytes will be utilized to further validate the effects of the DFU-specific mirs. Figure 1.4. Proposed experimental design for identification, validation and functional evaluation of differentially expressed mirs in DFUs. = experimental validations and results, = analysis results, = technical methods and analysis, = source materials.

33 CHAPTER 2. METHODS 2.1. Tissue samples DFU samples were obtained from patients receiving standard care at the University of Miami Hospital. Sample collection was approved by the University of Miami Institutional Review Board (protocol number # ) and signed consent was obtained for the participation in the study. Both non-diabetic and non-neuropathic diabetic (type 2) skin specimens were obtained as discarded tissue from patients undergoing podiatric surgery at the University of Miami Hospital and, as such, was found to be exempt under 45 CFR by the IRB at the University of Miami Miller School of Medicine. They did not contain any of the 18 identifiers noted in the privacy rule and therefore no informed consent was obtained. Demographics of patients are presented in Table 2.1. Verbal consent was approved by IRB and was not documented. Skin biopsies were either stored in RNA later (Applied Biosystems, Carlsbad, CA, USA) for subsequent RNA isolation, snap frozen for protein isolation or fixed in formalin for paraffin embedding. Sample Age Gender Etnicity Ulcer HgbA1c % (M/F) (AA/A/H/HW/W) duration/location (mmol/mol) DFU 44 F H 6 months 11.8 (105) DFU 33 M H 18 months 12.7 (115) DFU 54 M W 8 months n/a DFU 59 M H 6 weeks 6 (42) DFU 60 M H 2 months 6.8 (51) DFU 64 M A 2 years 8.4 (68) DFU 30 M AA 7 years 11.8 (105) DFU 42 M H 2 years 5.6 (38) DFS 62 F AA Dorsal DFS 59 M AA Plantar DFS 65 M W Plantar DFS 53 M HW Plantar NFS 48 F HW Dorsal NFS 83 F HW Plantar NFS 43 M HW Medial Table 2.1. Patient demographics, and sample information. AA = African-American, A= Asian, H = Hispanic, HW = Hispanic White, W = White 19

34 Laser Capture Microdissection (LCM), microrna extraction and profiling from epidermis Between 16 and 20 sections 8-10µm thick were cut from the formalin-fixed paraffin embedded tissue blocks of DFU, non-diabetic and diabetic foot skin, placed on Arcturus PEN-membrane glass slides (Life Technologies, Carlsbad, CA, USA) and dried at 37 C for 1-2 hours. LCM was carried out on an Arcturus Veritas laser capture microdissection instrument and the epidermis was collected on CapSure Macro LCM Caps (Life Technologies). The caps were transferred to a tube containing 60µl of deparaffinization buffer (QIAGEN Inc., Valencia, CA, USA) and total RNA, including the mir fraction, was extracted using the FFPE mirneasy kit (QIAGEN Inc.) according to the manufacturer s instructions. Total RNA concentration of the samples was quantified using NanoDrop 2000 (NanoDrop products, Wilmington, DE) and the RNA quality of these samples was determined by RTqPCR of SNORD48 and mir-21 using the commercially available platforms mircury LNA (Exiqon, Woburn, MA, USA) or Quanta qscript microrna Quantification System (Quanta BioSciences, Inc., Gaithersburg, MD, USA). The mir profiles for the epidermis of 6 DFUs was generated using the mir Ready-to-Use PCR panels V2 (Exiqon), while 3 NFS and 3 DFS profiles were generated using the mir Ready-to-Use PCR panels V3 (Exiqon) following the manufacturer s specifications. The Ct values were normalized to the stably expressed reference gene SNORD49 using the Exiqon GenEX software and the expression levels in the NFS and DFS were compared. The qpcr profiling raw and normalized data for the NFS and DFS profiles are publically available in GEO database under the super series GSE The qpcr profiling raw and normalized data for the DFU profiles will be made publically available in GEO database.

35 21 Total RNA including the mir fraction was extracted from the samples using the QIAGEN mirneasy mini kit and following the manufacturer s instructions. The RNA quality was assessed using the AGILENT bioanalyzer (Agilent Technologies, Palo Alto, CA, USA) to estimate the RNA integrity number (RIN). Samples with a RIN higher than 5 were used for mrna profiling as described below mrna profiling (microarrays) The methods for tissue specimen preparation and hybridization utilized were previously described by the Tomic-Canic lab (82, 123, 124). All processing and analysis of microarrays were performed according to standard protocols at the University of Miami Microarray Core Facility. Briefly, between 100 to 300 ng of total RNA was reverse transcribed, amplified, then the sense strand cdna synthesized, labeled, and hybridized on arrays. The amplified, fragmented and biotin-labeled cdnas were hybridized to the Affymetrix GeneChip Human Gene 2.0 ST microarray according to the manufacturer s recommendations. Arrays were washed and stained using Affymetrix Fluidic stations 450 and scanned using Affymetrix GeneChip scanner G. Image analysis was performed using the Affymetrix Command Console Software (AGCC). Resulting CEL files were imported into Expression Console Software (Affymetrix, Santa Clara, CA, USA) and underwent gene level normalization and signal summarization. The output files from this step were imported in Transcriptome Analysis Console (TAC) 2.0 Software (Affymetrix, Santa Clara, CA, USA) to identify differentially expressed genes and carry out clustering analysis. Genes with an FDR lower than 0.05 and a fold-change greater than 2 were considered differentially expressed and qpcr of multiple genes were carried out to validate

36 22 the results of the arrays. Microarray profiles for DFS and NFS are publically available in GEO database under the super series GSE Acute wound healing (AW) profiles were obtained from GEO (GSE28914, (125)) processed and analyzed as described above. Profiles from AWs 3 days post-wounding were compared to unwounded controls. The lists of differentially regulated genes with their fold change expression in both DFUs and AWs were imported into Ingenuity Pathway Analysis software (IPA, QIAGEN, Valencia, CA). Pathway and network analyses were carried out independently for DFUs and AW followed by comparison analysis. The specific genes networks were built using the IPA network builder tools (126) Real-time qpcr for microrna and gene expression analysis The qscript microrna Quantification System (Quanta BioSciences, Inc., Gaithersburg, MD, USA) was used for microrna expression. Briefly, cdna was synthesized from total RNA including the microrna fraction using the qscript microrna cdna Synthesis Kit. 50 pg of initial RNA were used per PCR reaction on a CFX Connect Real-Time PCR Detection System (Bio-rad, Hercules, CA, USA). SNORD48 was used as a reference gene to normalize the mir expression. For gene expression, cdna was made with qscript cdna Synthesis kit (Quanta BioSciences Inc., Gaithersburg, MD, USA). ARPC2 was used as a reference gene for normalization. Primers were either obtained from the Harvard primer bank or designed with PrimerQuest Tool ( using default parameters and selecting primers covering the intron/exon junctions when available.

37 23 All real-time PCR reactions were done in triplicate using the PerfeCTa SYBR Green SuperMix (Quanta BioSciences) and the relative gene expression was calculated with the ddct method. Gene Name Forward primer 5-3 Reverse primer 5-3 S100A9 GGTCATAGAACACATCATGGAGG GGCCTGGCTTATGGTGGTG KRT16 GACCGGCGGAGATGTGAAC CTGCTCGTACTGGTCACGC SERPINB3 CGCGGTCTCGTGCTATCTG ATCCGAATCCTACTACAGCGG SPINK7 CCCCTGCCCCATCACATAC AGCAACTTCCATCGTGAAGAAA LGR5 CACCTCCTACCTAGACCTCAGT CGCAAGACGTAACTCCTCCAG OR2A4 CACTTTTGCTGTCACAGAATGTC CGGCCAAGACCATGTTCTCAT JAM2 AACTGGGTCGGAGTGTCTC GGGGCACTAACTTCACAACGA PIK3R1 TGGACGGCGAAGTAAAGCATT AGTGTGACATTGAGGGAGTCG IKBKB CTGGCCTTTGAGTGCATCAC CGCTAACAACAATGTCCACCT ATF2 CTGGCCTTTGAGTGCATCAC CGCTAACAACAATGTCCACCT FGF2 AGTGTGTGCTAACCGTTACCT ACTGCCCAGTTCGTTTCAGTG IGF1 GCTCTTCAGTTCGTGTGTGGA GCCTCCTTAGATCACAGCTCC MMP1 CTCTGGAGTAATGTCACACCTCT TGTTGGTCCACCTTTCATCTTC IL8 ACTGAGAGTGATTGAGAGTGGAC AACCCTCTGCACCCAGTTTTC PI3 CACGGGAGTTCCTGTTAAAGG TCTTTCAAGCAGCGGTTAGGG CXCL5 AGCTGCGTTGCGTTTGTTTAC TGGCGAACACTTGCAGATTAC PTGS2 TAAGTGCGATTGTACCCGGAC TTTGTAGCCATAGTCAGCATTGT IL6 AACAACCTGAACCTTCCAAAGA TCAACTCCAAAAGACCAGTGA IL1A AGATGCCTGAGATACCCAAAACC CCAAGCACACCCAGTAGTCT MSH2 AGTCAGAGCCCTTAACCTTTTTC GAGAGGCTGCTTAATCCACTG WEE1 AACAAGGATCTCCAGTCCACA GGGCAAGCGCAAAAATATCTG RAD50 TACTGGAGATTTCCCTCCTGG AGACTGACCTTTTCACCATGC TP53 GAGGTTGGCTCTGACTGTACC TCCGTCCCAGTAGATTACCAC KIT CGTTCTGCTCCTACTGCTTCG CCCACGCGGACTATTAAGTCT ARCP2 TCCGGGACTACCTGCACTAC GGTTCAGCACCTTGAGGAAG IKBKB 3 UTR AAAGAGCTCAGTGCTTGGAGTACGGTTTG CCCTCTAGACACACACAATCAGCAGGAG WEE1 3 UTR AAAGAGCTCCCTGAACACTGTGACAAGA CCCTCTAGAAGTCAAAGACAAGTGCAAACA Table 2.2. List of primers used for qpcr Protein isolation and western blot Proteins were extracted using Tissue-PE LB Kit (Geno technology, MO) and protein lysates were resolved on 4 20% Tris-Glycine Gels (Bio-Rad, Hercules, CA), and transferred to polyvinylidene difluoride membranes (PVDF, Applied Biosystems). Membranes were probed with the primary antibodies over-night. Primary antibodies and

38 24 their corresponding dilutions are listed in Table 2.3. Membranes were incubated with their appropriate horseradish peroxidase-conjugated secondary antibodies 1:4000 (Cell Signaling, Danvers, MA) and developed using an enhanced chemiluminescence detection system (Amersham Biosciences, Arlington Heights, IL). For loading control we used anti ARPC2 antibody (Santa Cruz, Dallas, TX). The band densities were quantified with Image lab software (Bio-Rad, Hercules, CA, USA). Antibody Species Dilution Manufacturer Catalog # IKBKB Rabbit-Poly 1:1000 Sigma-Aldrich HPA UL p-h2ax (Ser139) Rabbit-Mab 1:1000 Cell Signaling 9718S ARPC2 Rabbit-Mab 1:2000 Cell Signaling ab Table 2.3. List of antibodies used for Western blots H&E, immuno-peroxidase staining The formalin fixed, paraffin embedded tissue was cut in 7 µm sections using a microtome. Slides containing sections were deparaffinized with xylene (EMD, Gibbstown, NJ, USA), rehydrated, and hematoxylin and eosin stained or further processed for immuno-staining as described previously [42]. Endogenous peroxidase activity was quenched with 0.3% H2O2 in methanol and washed with distilled water. The slides were then incubated in Dako target retrieval solution (Dako, Carpinteria, CA, USA) for 30 minutes at 95 C for antigen retrieval, allowed to cool down, and then treated with Background punisher (MACH1 kit, Biocare Medical, Concord, CA, USA). Primary antibodies were diluted in 5% bovine serum albumin (Sigma-Aldrich, St. Louis, MO, USA) in TBS and applied to the samples. Primary antibodies and their corresponding dilutions are listed in Table 2.4. All antibodies were incubated overnight at 4 C, except for the anti CD45, which was incubated for 30 min at room temperature. The detection and chromogenic reaction was carried out using the MACH 1 Universal HRP-Polymer Detection system (Biocare Medical, Concord, CA, USA) and following manufacturer s instructions. Picrosirius red (Electron Microscopy

39 25 Sciences, Hatfield PA, USA) staining was carried out following manufacturer s instructions. All slides were analyzed with a Nikon Eclipse E 400 microscope and digital images were obtained using a Qimaging camera and NIS-Elements BR3.10 software. Quantification of CD45 positive cells, Ki67 positive cells, and CD31 positive blood vessels was performed using ImageJ software (NIH, Bethesda, NJ, USA). Briefly five (20X) images of each section were taken randomly and the positive cells or structures were counted within a rectangular dermal area of mm 2 (1000x500 pixels). For Ki67 quantification, positive cells were counted from the total epidermal section and normalized to the epidermal area. Antibody Species Dilution Manufacturer Catalog # LEPR Rabbit-Poly 1:1000 Abcam ab5593 CD31 Mouse-Mab 1:25 Adb Serotec MCA1746GA CD45 Mouse-Mab 1:100 Dako M0701 Ki67 Rabbit-Poly 1:500 Abcam ab15580 S100A9 Mouse-Mab 1:100 Abcam ab22506 Table 2.4. List of antibodies used for immune-peroxidase staining Immunofluorescence 7 μm thick formalin fixed, paraffin embedded tissue sections were sliced on a microtome (HM 315, Carl Zeiss) and mounted on slides. Sections were deparaffinized with xylene (EMD, Gibbstown, NJ, USA), rehydrated, and hematoxylin and eosin (H&E) stained or further processed for immuno-staining as described previously (73). Sections were heated in 95 C water bath in Target Retrieval Solution (DAKO Corporation, Carpinteria, CA) for antigen retrieval, and blocked with 5% bovine serum albumin (BSA). The slides were incubated with anti MSH2 (H-300) rabbit polyclonal antibody 1:50 (Santa-Cruz, Santa Cruz, CA) overnight at 4 C. Signal was visualized using Alexa-Fluor 488 (Invitrogen, Carlsbad, CA) secondary antibody and slides were mounted with mounting media

40 26 containing 4',6-diamidino-2-phenylindole (DAPI; Vector Laboratories, Burlingame, CA) to visualize the cell nuclei. Nikon Eclipse E800 microscope was used for visualization and digital images were collected using the NIS Elements BR 3.2 software (Nikon) Cell culture and transfection The human keratinocyte cell line HaCaT (AddexBio, San Diego, CA) were cultured an maintained at 37 C (5% CO2) in DMEM without calcium (Gibco, Life technologies, Carlsbad, CA) supplemented with fetal bovine serum (FBS, 10% v/v final concentration, GE Hyclone Laboratories, Logan, Utah, USA) and penicillin-streptomycin with l- glutamine (Gibco, Life technologies, Carlsbad, CA). Cells were seeded 24h before transfection at a cell density of 10 5 cells/well in 24 well plates. Transfection was carried out using Attractene reagent (QIAGEN, Valencia, CA) following manufacturer s guidelines. 25 nm mimic or control (GE Dharmacon, Lafayette, CO) was used per well. Cells were harvested 48h after transfection for RNA and protein extraction or scratched after 24 hours for a scratch wound assays Luciferase assays The 3 UTRs of the WEE1 and IKBKB human genes were amplified by PCR from human genomic DNA with primers containing restriction sites for SacI and XbaI (see Table for primer sequences). The amplified fragments were cloned into the SacI and XbaI sites of the pmirglo Dual-Luciferase mir Target expression vector (Promega Corporation, Madison, WI). Cultures and transfections were carried out as described above using 600 ng of vector containing the UTRs and 25 nm of mir-15b-5p mimic or control in HEK293T cells (Applied Biological Materials, Richmond, Canada).

41 27 The luciferase reporter assay was done using the Dual-Glo Luciferase Assay system (Promega Corporation) 24 h after transfection according to the manufacturer's protocol Scratch wound assay Cells were seeded and transfected as described above. 24h after transfection cells were incubated with 4µg/ml Mitomycin C (Sigma) for 1h, washed 3 times with sterile PBS and a scratch wound was created in the cell monolayer using a 200 µl tip. The gap created was photographed at the initial scratch time and 48 hrs after using an Olympus microscope CK40 with an attached camera AmScope MU800 (AmScope, Irvine, CA). The scratch area was measured using ImageJ software ( and the % wound closure was calculated as ((initial gap area-48h gap area)/initial gap area)* Cell viability assay Cells were seeded and transfected with mir mimics or controls as described in section hrs after transfection cells were trypsinized and stained with trypan blue and counted. The viability of the cells was calculated as (# viable cells)/(# viable + # non-viable cells)* Stimulation of cell motility and Phalloidin staining Primary human keratinocytes were seeded in 8-well chamber slides (Thermo Fisher Scientific, Waltham, MA) at 10,000 cells/well and grown in complete KSFM media for 24hrs prior to mir-mimic transfection. 24 hours post-transfection, cells were switched to basal KSFM and treated with DMSO (vehicle), 100ng/ml EGF for 1min (for visualization of filopodia), 10ng/ml EGF for 5min (for visualization of lamellipodia) or 1 unit/ml CN01 (cytoskeleton, Denver, CO) for 20min (for visualization of stress fibers). Cells were

42 28 washed once in PBS and fixed in 3.7% paraformaldehyde for 10min. Then the fixed cells were washed once in PBS and permeabilized using 0.5% Triton/PBS for 5min. After 3 washes with PBS, cells were incubated with 100nM rhodamine phalloidin for 30min, washed 3 times with PBS and then visualized using epifluorescent Nikon Eclipse E400 microscope equipped with a QImaging QICAM 12-bit Fast 1394 camera Bacterial strains and growth Conditions Methicillin-resistant S. aureus USA (127), USA300 JE2 (128), and isolate from the DFUs were used. Todd-Hewitt broth supplemented with 0.2% yeast extract (THY) served as the growth medium, while oxacillin resistance screening agar base (OXOID, Carlsbad, CA) was used as selective media for colony forming units (CFU) quantification Human ex vivo wound infection model Acute wounds were generated from healthy human skin samples as described previously by the Tomic-Canic Lab (86, 105, 129). The subcutaneous fat was trimmed from skin prior to generating wounds under sterile conditions and a 3 mm punch (Acuderm, Fort Lauderdale, FL) was used to make wounds in the epidermis through the reticular dermis. The 3 mm discs of epidermis were excised using sterile scissors. 8 mm skin discs containing the 3 mm wound in the center, were excised using a 8 mm biopsy punch (Acuderm). The wounded skin specimens were immediately transferred to air-liquid interface with DMEM medium (Life Science, Carlsbad, CA) supplemented with 10% FBS (GE Hyclone Laboratories). The bacteria were grown over night in THY medium at 37 C and then harvested by centrifugation, washed twice in PBS and re-suspended in DMEM. The bacterial density was adjusted to an OD600 of 0.1 ( x10 8 ) colony-forming units (CFU)/ml and 10 μl of the bacterial stock solution was used to infect the wounds. The

43 29 infected and non-infected (control) skin samples were incubated at 37 C in a humidified atmosphere of 5% CO2 for four days. CFUs were quantified from both infected and noninfected wounds 4 days post-wounding. Tissues were either used for CFU determination, or fixed in 4% paraformaldehyde (Sigma-Aldrich) for H&E and histomorphometic analyses (86, 105, 129), or preserved in RNA later (Ambion, Carlsbad, CA) for subsequent RNA isolation Statistical analyses Data were analyzed using the software Prism (Graphpad, La Jolla, CA, USA). Statistical significance between groups was determined using Mann-Whiteny U-test or Student s t- test. Pearson or Spearman s correlation coefficients were used to determine correlations between different groups. A difference between groups was considered significant when p-value 0.05.

44 CHAPTER 3. SUBTLE DIFFERENCES BETWEEN DIABETIC AND NON- DIABETIC SKIN 3.1. Epidermal mir profiles show minor differences between DFS and NFS I used laser capture microdissection (LCM) to identify differentially expressed mirs in epidermis of DFS and NFS that may affect the skin capacity to heal. The epidermis from 3 DFS and 3 NFS formalin fixed paraffin embedded (FFPE) tissue samples containing keratinocytes was captured after evaluation of their morphology as previously described (63). I isolated total RNA from the captured epidermis and generated mir expression profiles using Ready-to-Use PCR panels v3. These panels include 752 human mirs. I detected 198 mirs expressed in the foot skin keratinocytes after data processing and elimination of low expression mirs (Ct > 35). The clustering and principal component analysis (PCA) did not show any specific segregation of the DFS and NFS groups (Figure 3.1 A) and only 5 mirs were differentially expressed between them (unadjusted p-value <0.05). Both top up-regulated mirs in DFS, mir-31-5p and mir-31-3p, corresponded to the same stem-loop precursor (hsa-mir-31) and exhibited an increase of expression higher than a 10 fold while the other 3 mirs (mir-338-3p, p and -10b-5p) were downregulated in DFS compared to NFS (Figure 3.1 B). However, none of these mirs passed the statistical significance cut-off when multiple testing correction was applied (Figure 3.1 B). 30

45 31 A. B. Figure 3.1. MicroRNA expression profiling show minimal differences between diabetic and non-diabetic foot epidermis. A. Heatmap and clustering analysis of NFS and DFS does not reveal any specific segregation of samples. B. list of micrornas differentially expressed in the epidermis of DFS in comparison to NFS (t-test, unadjusted p<0.05). However, none of these mirs were significantly regulated after multiple testing correction (FDR>0.05) Validation of the mir epidermal expression in skin microrna DFS/NFS Fold change P-Value P (Benjamini- Hochberg) hsa-mir-31-3p hsa-mir-31-5p hsa-mir-10b-5p hsa-mir-136-5p hsa-mir-338-3p I confirmed the expression of the top induced mirs individually in both epidermis and full thickness skin samples (Figure 3.2). Not surprisingly, there was a high correlation of mir- 31-3p and mir-31-5p expression between the laser captured epidermis and full thickness biopsies (n=6, mir-31-3p Spearman s ρ=0.94, p=0.017; mir-31-5p Spearman s ρ=0.82, p=0.072) (Figure 3.2), suggesting that highly cellular epidermis is major contributor of the profiles within full thickness specimens. I also tested the expression of these mirs in a larger set of 10 DFS and 10 NFS samples collected prospectively and found a high variability of their expression levels among individual tissue samples (Figure 3.2). Even though there is an observable trend towards a higher expression of both mir-31-3p and mir-31-5p in DFS, the difference was not statistical significant (p>0.05). Madhyastha et. al. identified mir expression in the skin of a spontaneous type 2 diabetic mouse model, KKAY mouse. Surprisingly, I did not find de-regulation of the mirs identified by that study (130). Also, none of the mirs identified above were found in the diabetic mice simply because they were not covered by the arrays utilized in that work, which contained a smaller number of mirs. One possibility that may explain this, is the

46 32 multifactorial causes of diabetes in humans or the inter-species differences, which were not contemplated completely by the use of KKAY mice. A. hsa-m ir -31-3p LCM hsa-m ir -31-3p F u ll th ick n ess hsa-m ir -31-3p R elative expression R elative expression F u ll th ick n ess B. DFS NFS hsa-m ir -31-5p LCM DFS NFS hsa-m ir -31-5p F u ll th ick n ess LCM hsa-m ir -31-5p R elative expression R elative expression F u ll th ick n ess DFS NFS DFS NFS LCM Figure 3.2. mir-31-3p and mir-31-5p show a trend of up-regulation in epidermis of DFS which correlates with the expression in full-thickness biopsies. A. mir-31-3p expression in DFS and NFS in epidermis (n=3 group, unpaired t-test, p=0.1141) and full thickness (n=10 group, Mann-Whitney U test, p=0.0730). Correlation (n=6, Pearson R 2 = p=0.1741, Spearman R , p=0.0167). B. mir-31-5p expression in DFS and NFS epidermis (n=3 group, unpaired t-test, p=0.0720) and full thickness (n=10 group, Mann-Whitney U test, p=0.3150). Correlation (n=6, Pearson R 2 = p=0.0451, Spearman R , p=0.0722) Diabetic patients sometimes exhibit delayed corneal healing after surgery or injury (26). Funari et. al. found differentially expressed mirs in human corneas of diabetic individuals (26), associating their role in delayed healing in the corneal epithelium. This is indicative that skin could be less affected by DM than cornea, at least at the mir level. Alternatively, patients in this study, which had not developed neuropathy, could represent a subset of

47 33 individuals with shorter duration of diabetes and/or better controlled diabetes compared to those who exhibit delayed corneal healing. It is important to mention that individual variability was present within both DFS and NFS groups, underscoring the inherent differences in each patient s skin. One may argue that subtle differences found in mir expression between DFS and NFS could have larger biological significance, since they show a trend of de-regulation, even though they did not achieve statistical significance. Taking into account that mirs have the potential to regulate hundreds of genes, small changes can have significant biological impact. MiR-31 in particular, is up-regulated in psoriasis, a skin disease that, similar to DFUs, exhibits a hyperproliferative epidermis, parakeratosis, and unresolved inflammation. In this case serine/threonine kinase 40 (STK40) is targeted by mir-31-5p, resulting in increased expression of proinflammatory cytokines and chemokines (131). mir-31 regulates cell differentiation and proliferation, which are processes de-regulated also in DFUs (132, 133). However, in spite of exhibiting a trend of induction of mir-31 in DFS, there are no observable morphological differences in epidermal differentiation or inflammation, nor increased expression of the proliferation marker Ki67 (see section 3.4 and 3.5). In addition, none of the down-regulated genes were predicted targets of mir-31. Although, I cannot exclude the possibility of mir-31 affecting target genes post-transcriptionally without reducing the mrna levels Transcriptomes of diabetic and non-diabetic foot skin reveal small differences Next, I used the Affymetrix GeneChip Human Gene 2.0 ST microarrays to investigate differential mrna expression between full thickness DFS and NFS. I found only 36 genes out of the 40,716 transcripts present in the arrays, differentially expressed between DFS

48 34 and NFS ( 2 fold change, uncorrected p< 0.05). In the case of mrna, unlike with mir, the heat maps and cluster analysis showed a distinct grouping of DFS and NFS (Figure 3.3 A). 22 genes were down-regulated and 14 were up-regulated in DFS compared to NFS, but similarly to the mir profiling, none of these passed the multiple correction testing (Table 3.1). Among deregulated genes, there are genes belonging to different functional categories that may be related to wound healing such as cell adhesion and migration, epithelial function and homeostasis, inflammation and immune response, etc. There are multiple suppressed genes encoding T cell receptors (TRAJ14, TRAJ19, TRAJ31 and TRAJ38), possibly indicating abnormal T cell function in DFS. Moreover, the down-regulation trend of β tryptases (TBSP2) could also indicate a lack of mast cells, as β tryptases appear to be the main isoenzymes in mast cells (134). I used a larger sample set to verify 7 of the top regulated genes by qpcr and found Serpin Peptidase Inhibitor Clade B Member 3 (SERPINB3), Leucine-Rich Repeat Containing G Protein-Coupled Receptor 5 (LGR5), and Olfactory Receptor Family 2 Subfamily A Member 4 (OR2A4) to be differentially regulated in DFS versus NFS (n=10 per group, p<0.05) (Figure 3.3 B). S100 Calcium Binding Protein A9 (S100A9) showed a trend of induction in DFS but did not reach statistical significance (p=0.06). Both SERPINB3 and S100A9 are inflammatory response modulators ( ). They are highly inducible in keratinocytes, and also have been found to be de-regulated in inflammatory venous ulcers (82), and other inflammatory skin diseases including psoriasis (137, 138), atopic dermatitis (135, 137), and skin cancer (136). SERPINB3/B4 is supposed to take part in the initiation of the acute inflammatory response, in part by regulating S100A8/A9 (137) which are damage-associated molecular pattern (DAMP) molecules

49 35 normally expressed at low levels in keratinocytes strongly inducible by a variety of cytokines and physical stresses. After activation they dimerize to induce pro-inflammatory cytokine and chemokine expression but also keratinocyte proliferation, probably working in a positive feedback mechanism (139). I also performed immuno-peroxidase staining of S100A9 to verify the gene expression data and to see whether the changes were more noticeable in the protein level. Consistent with what I had previously found by qpcr, the majority of DFS tested (67%) showed similar S100A9 staining intensity as NFS (Figure 3.3 C upper panel), while the other 33%, had remarkably more intense staining in the epidermis compared to NFS (Figure 3.3 C lower panel). This high individual variability in the expression of S100A9 in DFS, with some individuals showing a similar expression to NFS while others had several fold induction, could indicate that some individuals are more prone to inflammation. OR2A4 and LGR5 are G protein coupled receptors. The olfactory receptor OR2A4 is mostly uncharacterized although some olfactory receptors have been found to be involved in cytokinesis (140) and chemosensing in tissues including renal epithelium (141) while LGR5 is a known hair follicle stem cell marker (142) and may potentiate the canonical Wnt signaling pathway (143). However, their roles in volar skin and wound healing has not been described yet. Finally, I cannot disregard the possibility that the subtle differences I found in both mir and mrna expression profiles between DFS and NFS could be of biological importance and may point to a subset of diabetic individuals with a more uncontrolled or longer history of diabetes, which are more likely to develop neuropathy, arterial disease, ulcers or slow healing ulcers, however, a bigger sample size is required to better characterize such subpopulation of patients.

50 36 A. B. DFS NFS R elative expression * * NFS NFS NFS DFS DFS DFS * JAM 2 LGR5 OR2A4 KRT16 S100A9 SPINK 7 SERPINB3 Figure 3.3. Gene expression profiling between diabetic and non-diabetic foot skin reveals small set of genes deregulated in DFS. A. Heatmap and clustering analysis of differentially C. expressed genes showing the distinct segregation of NFS and DFS. B. PCR validation of differentially regulated genes in full thickness biopsies. All the genes tested followed the same trend of up- or downregulation observed from the microarray data, SERPINB3, LGR5, and OR2A4 reached statistical significance. Plots indicate sample distribution D. and median. (*p<0.05, N = 10 samples per group). C. S100A9 immuno-peroxidase staining of DFS shows variable expression whereby 67% of DFS showed similar expression to NFS (upper panel), while the other 33% showed much greater expression compared to NFS (D, lower panel). D. LEPR immuno-peroxidase staining shows signal throughout the epidermis of both DFS and NFS with no difference in localization or staining intensity. S100A9 LEPR

51 37 Fold Change (DFS/NFS) P-value Gene Symbol Description Function JAM2 junctional adhesion molecule 2 adhesion SCNN1G sodium channel, non-voltage-gated 1, gamma subunit ion transport KRT6A keratin 6A cell proliferation, KRT16 keratin 16 cytoskeleton organization XDH xanthine dehydrogenase SPRR1B small proline-rich protein 1B differentiation S100A9 S100 calcium binding protein A9 Migration SERPINB4 serpin peptidase inhibitor, clade B (ovalbumin), member SERPINB3 serpin peptidase inhibitor, clade B (ovalbumin), member 3 Proteolysis SPINK7 serine peptidase inhibitor, Kazal type 7 (putative) TPSB2, tryptase beta 2 (gene/pseudogene), tryptase TPSAB1 alpha/beta HLA-DPB1 major histocompatibility complex, class II, DP beta CYSLTR1 cysteinyl leukotriene receptor TRAJ19 T cell receptor alpha joining TRAJ38 T cell receptor alpha joining TRAJ31 T cell receptor alpha joining 31 T-cell receptor TRAJ14 T cell receptor alpha joining GSTM5 glutathione S-transferase mu RNF39 ring finger protein FMO2 flavin containing monooxygenase 2 (non-functional) WIF1 WNT inhibitory factor 1 Wnt pathway OR2A7 olfactory receptor, family 2, subfamily A, member OR2A4 olfactory receptor, family 2, subfamily A, member 4 G-protein coupled LGR5 leucine-rich repeat containing G protein-coupled receptor receptor RNASE1 ribonuclease, RNase A family, 1 (pancreatic) Endonuclease FLJ10489 uncharacterized protein FLJ RN5S387 RNA, 5S ribosomal RN5S44 RNA, 5S ribosomal SDHAP2 succinate dehydrogenase complex, subunit A, flavoprotein pseudogene H2BFXP H2B histone family, member X, pseudogene OR2A20P, olfactory receptor, family 2, subfamily A, member OR2A9P 20 pseudogene; member 9 pseudogene LOC kinesin family member 27 pseudogene PTPN20C protein tyrosine phosphatase, non-receptor type 20C FNDC1 fibronectin type III domain containing FAM182A family with sequence similarity 182, member A LOC uncharacterized LOC Cell Adhesion, migration Epithelial function, homeostasis Inflammation, Immune response Metabolism Signal transduction Unknown function Table 3.1. List of differentially expressed genes between DFS and NFS. Genes differentially expressed ( 2 fold, unadjusted p 0.05) between diabetic and nondiabetic full thickness skin biopsies and their respective roles in different cellular processes. Even though its expression was not differentially regulated in DFS according to microarrays I determined the expression level of the Leptin receptor (LEPR), which has important role in wound healing and its ablation in mice lead to diabetes and delayed healing. In fact, it has been widely used as a model for impaired wound closure (144).

52 38 Moreover, the Tomic-Canic lab has shown that LEPR is down-regulated in venous ulcers of non-diabetic patients (105). The immuno-peroxidase staining of LEPR in DFS showed epidermal staining of both DFS and NFS with a similar intensity (Figure 3.3 D) suggesting that down-regulation of LEPR is not required for the development of a chronic wound, instead, it inhibits healing after a wound has already occurred. Thus, its reduction in expression in human ulcers could be a consequence of the ulceration rather than its cause. It is important to consider that, even though I found a small number of gene expression changes between DFS and NFS, there could be a variety of differences between DFS and NFS that are not represented by the transcriptional regulation of genes, such as post transcriptional regulation, protein modifications and even genetic variation. For example, 5 single nucleotide polymorphisms (SNPs) in the TLR4 gene and one in the MMP9 promoter have been associated with type 2 Diabetes and DFUs (145, 146). Some of the SNPs in the TLR4 are known to negatively impact the function of TLR4 in other diseases such as Crohn s diseases or cancer (145), while the SNP in the promoter of MMP9 results in increased expression in an Indian population, possibly resulting in increased matrix degradation in DFUs (146). Thus, it is possible that other genetic variations may be associated with impaired healing in DFS by altering the function of genes which is not covered by the transcriptional profiling Histological evaluation shows no observable differences between DFS and NFS The normal plantar skin histology is composed of a thick cornified layer and a thick ridged epidermis with all epidermal layers identifiable. I evaluated the DFS histological morphology and found that it is virtually indistinguishable from NFS in morphology or thickness (Figure 3.4 A). No evidence of any morphological characteristics of DFUs, such

53 39 as hyperproliferative epidermis, parakeratosis, hyper-keratosis, or fibrosis was found in DFS. Based on changes in extracellular matrix (ECM), including collagen production (147), growth factors (148), and ECM remodeling proteins (149), previously reported in different tissues of diabetic animals (144, 150), I decided to assess collagen orientation and fiber composition using picrosirius red staining under polarized light microscopy. Again, I did not find major differences in fiber composition or orientation as both DFS and NFS exhibited the characteristic basket-weave collagen orientation (Figure 3.4 B). Taken together these findings suggest that unwounded skin from non-neuropathic diabetic patients is not predisposed to poor healing. DFS NFS A. B. Picrosirius red H&E D E E Figure 3.4. Evaluation of the morphology of DFS shows no major differences in comparison to NFS. A. H&E staining and histology assessment of DFS and NFS showing similar skin morphology between them. E = epidermis, D= dermis. B. Picrosirius red staining under polarized light shows no difference in collagen fiber alignment and thickness between DFS and NFS.

54 Lymphocytes, blood vessels, and keratinocyte proliferation are similar between DFS and NFS Immune dysfunctions and increased prevalence of infections have been associated with Diabetes (29). The uncontrolled hyperglycemia, can lower the number of circulating lymphocytes and increase their apoptosis (151). Thus, I quantified the number of lymphocytes in DFS and NFS using CD45 immunohistochemistry (Figure 3.5 A) and found similar numbers of CD45 + lymphocytes in DFS and NFS. Another common feature of diabetes is the development of microvascular complications including retinopathy, nephropathy, and neuropathy due to abnormal angiogenesis or capillary function (27, 28). Therefore, using CD31 immuno-peroxidase staining (Figure 3.5 B) I quantified blood vessels in the dermis of both DFS and NFS. Again, both diabetic and non-diabetic subjects have similar numbers of blood vessels in the foot skin. In line with these results, Haemmerle et al reported no differences in numbers of blood vessels and lymphocytes between diabetic and non-diabetic skin (152). However, they did find higher lymph vessel density in diabetic skin. Also they showed gene expression changes in lymphatic endothelial cells related to inflammation, lymphatic vessel remodeling and lymphangiogenesis among others (152). Several mirs had also been found to be potentially involved in such changes (153). The fact that I did not find them deregulated in this study suggests possible cell-type specific expression. In contrast, blood vessels and lymphocytes numbers were found increased in forearm skin from neuropathic diabetic individuals (71). The differences in experimental design, particularly the source and location may offer an explanation for the discrepancy in these findings. I profiled the tissue samples from diabetic patients that did not show signs of neuropathy, or compromised circulation. Therefore it could be that the increased numbers of lymphocytes

55 41 and blood vessels are consequence of diabetic-related neuropathy rather than diabetes itself. In addition, body location may also contribute. DFS NFS Lym phocytes 500 A. B. CD31 CD45 #CD45+ cells/m m 2 # blood vessels/m m DFS NFS Blood vessels DFS NFS K i67 C. Ki67 #K i67+ epiderm al cells/m m DFS NFS Figure 3.5. Quantification of lymphocytes, blood vessels and proliferating keratinocytes show similar numbers between DFS and NFS. A. Immuno-peroxidase staining and quantification for the lymphocyte marker CD45. B. endothelial cell marker CD31 staining. C. Proliferation marker Ki67 staining showing that proliferative keratinocytes were located in the basal layer of the skin, as expected. No differences were found in the number of lymphocytes (p=0.71, unpaired ttest), blood vessels (p=0.43, unpaired ttest) and proliferating keratinocytes (p=0.29, unpaired ttest) between DFS and NFS. Bar graphs indicate mean and SD.

56 42 Nevertheless, neither diabetes nor presence of neuropathy affected healing significantly in a randomized controlled clinical trial of 228 patients with chronic venous ulcers (154), further supporting the idea that DM does not necessarily predispose for poor cutaneous healing. Lastly, one of the hallmarks of the non-healing chronic wound is the presence of epidermal hyperproliferation (58) and thus I searched for indication of this phenotype in DFS and NFS by evaluation of the levels of cell proliferation marker Ki67 by immuno-peroxidase staining. I found higher variability in the number of Ki67 positive cells in the epidermis of DFS, with no statistical difference in comparison to NFS (Figure 3.5 C). Altogether, from these results I conclude that DFS and NFS have comparable levels of cellular components important for wound healing: lymphocytes, blood vessels, and proliferating keratinocytes Chapter conclusion By using mrna/mir profiling and detailed histological and morphological evaluation of DFS only minor molecular, cellular, and tissue changes were found in intact diabetic skin. These data indicate that there may not be an intrinsic inability of diabetic skin to heal or predispose it to ulcer development and, additional factors such as glucose control, duration of DM, neuropathy or additional diabetic complications are important contributors to wound formation and inhibition of healing observed in patients suffering from DFUs. This also implies that preventive care including frequent assessments of neuropathy and vascular supply could reduce the incidence of DFUs, improve the quality of life of the diabetic population, and reduce overall healthcare costs.

57 CHAPTER 4. TRANSCRIPTIONAL CHANGES IN DFUs 4.1. DFU gene expression profiling and comparison with AW transcriptome To find out transcriptional changes in DFUs I used full thickness tissue samples collected from the wound edge of the DFUs, and the normal and diabetic foot skin described in the previous chapter. The processing of the samples was carried out as previously described (63). Samples were also stained with H&E to confirm inclusion of epidermis and dermis and also histopathological characteristics of chronic wounds (58) including hyperkeratosis and a thickened epidermis (Figure 4.1). DFU FS E E D D Figure 4.1. Representative H&E staining of full thickness biopsies from DFU and FS. DFU samples exhibit a thicker epidermis than normal foot skin. E= Epidermis, D= Dermis. Scale bars: 500µm. I generated the transcriptional profiles of 6 DFUs and 6 FS (3 NFS and 3 DFS) full thickness samples using the Affymetrix Hugene 2.0 st microarrays and used the Affymetrix software package to carry out a differential gene expression analysis. In parallel, I also compared the profiles of AWs and control normal skin (NS) from previously publishedpublically available data ((125); GSE28914). In both cases, either DFUs or AWs had very distinct gene expression signatures when compared to FS or NS respectively, as it can be observed in the heatmaps and cluster analysis in Figure 4.2 A. 43

58 44 I found 3900 significantly regulated genes between DFU and FS (FDR 0.05), in contrast to 3156 regulated genes in AWs. DFUs exhibited an overall down-regulation of gene expression with 75% (2829 genes) of the genes being suppressed, in comparison to 50% (1073) down-regulated in AWs (Figure 4.2 B). Only 641 genes (172 up and 469 downregulated) were consistently regulated in both DFUs and AWs, while 163 genes were regulated in opposite direction. Most of the regulated genes, represent the specific expression signature of DFU. A. B. DFU 3900 Up Up AW 3165 Down Down FS DFU NS AW Figure 4.2. Microarray analysis of differentially expressed genes between DFU and AW. A. heatmaps showing distinct segregation of both DFU and AW when compared to their unwounded skin controls. B. Numbers of regulated transcripts in DFU and AW compared to unwounded foot or normal skin respectively. There were more regulated genes in DFUs compared to AWs and also the majority of them were down-regulated (75%) in contrast to AWs which show approximately 50% down-regulated genes Functional enrichment and comparative analysis of DFU and AW Given a number of differentially expressed genes, I used the software Ingenuity pathway analysis (IPA)(126) to better comprehend what cellular functions and processes were altered in DFUs when compared to AWs. I performed enrichment analyses in both DFU and AW complete gene lists separately followed by a comparative analysis. Both DFUs

59 45 and AWs showed enrichment of unique subsets as well as overlapping functional processes (Figure 4.3), which was expected given that chronic wounds are likely to have pathologically altered expression of genes which are also regulated during the acute wound healing (23). The specific processes enriched from the DFU differentially expressed genes include suppression of gene expression, DNA replication, recombination and repair, carbohydrate metabolism and post-translational modifications (Figure 4.3 top panel). The suppression of DFU gene expression which showed an average activation score (z-score) of -3 was consistent with the fact of an overall down-regulation of transcripts observed in DFUs (Figure 4.2 B). The following most enriched category was DNA replication, recombination and repair which was down-regulated, and within this category the repair of DNA sub-category was found to be highly suppressed in DFUs but not enriched in AWs (z-score = -5.2, Table 4.1). On the other hand, IPA analysis identified several functions and processes specifically induced in AWs but not enriched in DFUs including vitamin and mineral metabolism, molecular transport, cell-mediated immune response, and antimicrobial response (Figure 4.3, middle panel). Following these results, the shared enriched functions and processes between DFUs and AWs also suggested diminished activation of the immune/inflammatory response in DFUs (Figure 4.3, bottom panel). Not surprisingly, several other critical processes for wound healing such as cellular function and maintenance, lipid metabolism, cellular growth and proliferation, cellular movement, were highly enriched in both DFUs and AWs, however, not only were the p- values less significant in DFUs (Figure 4.3) but the activation z scores were also lower

60 46 and in some cases oppositely regulated in DFUs. For example, Immune cell trafficking, inflammatory response and cell movement were highly activated in AWs (z-score > 2) but insufficiently in DFUs (Figure 4.3, bottom panel). DFU only DFU AW DFU and AW AW only Figure 4.3. Enriched functions and processes in DFU and AW. Functional enrichment analysis carried out using IPA software showing combined categories and their average activation scores (Z-scores). Various wound healing related processes are significantly enriched in both DFU and AW, however both activation scores and p-values have marked differences in multiple processes. Next, I carried out a similar functional enrichment analysis but with the subset of genes that are only oppositely regulated. Similarly to what was described above, this analysis also showed suppression of inflammatory response in DFUs in contrast to its induction in AWs

61 47 (Table 4.2). Furthermore, the top regulated category, infection of Mammalia, was induced in DFUs (z-score = 2.9), but inhibited in AWs. Even though there is some overlap in genes regulated in both DFUs and AWs, several processes, and in particular inflammatory/immune response are not properly activated in DFUs in comparison to AWs. DFUs are known to be prone to infection (155, 156) and our data provides molecular insights to this observation. The inability of DFUs to clear infection could be driven by the observed impaired inflammatory/immune response. The DFUs gene expression profiling and comparative analyses with AWs also provide the paradigm shifting idea that DFUs exhibit a deficient inflammatory response in comparison to AWs. Contrary to the common belief that the inflammation is exacerbated in DFUs (72, 157) and should be suppressed, our data suggest that a more robust inflammatory response would kick-start the healing process to resemble an acute healing process. Functional Category Sub-category DNA replication, recombination and repair Table 4.1. Expanded functional enrichment of the DNA replication, recombination and repair category. DFU/FS Z-score AW/NS Z-score (-log p-value) DFU/FS (-log p-value) AW/NS DNA damage response of cells Infinity DNA replication Infinity replication of centriole Infinity binding of DNA Infinity DNA recombination Infinity metabolism of DNA Infinity synthesis of DNA Infinity repair of DNA Infinity maintenance of telomeres Infinity

62 48 Top Regulated Functions Average Z-score DFU AW infection of mammalia quantity of leukocytes activation of cells invasion of cells engulfment of cells Shock Response binding of cells cell movement metabolism of DNA antimicrobial response proliferation of smooth muscle cells quantity of germ cells endotoxin shock response metabolism of protein binding of blood cells migration of cells Table 4.2. Top regulated functions obtained from IPA functional enrichment analysis obtained from the oppositely regulated genes in DFUs and AWs Comparative analyses between DFUs and AWs shows distinct subset of genes regulated in the same direction I detected 641 genes regulated in the same direction between DFUs and AWs. Interestingly, the fold changes of these genes in many cases were not similar (Table 4.3). Although these genes are being regulated in the same direction of expression (i.e., induced or repressed), these differences in expression levels may have different biological consequences. DFUs are characterized by an unresolved and prolonged inflammatory stage (82, 158), partly due to over-expression of some of pro-inflammatory molecules including S100A9, IL-8 and IL-6 (82, 158). Consistently with this, I found increased expression of these genes in both DFUs and AWs, however the expression levels were surprisingly higher in AWs. For example, IL-8, showed an induction 100-fold higher in AWs than in DFUs (when each is compared to their respective controls). Other pro-inflammatory molecules such as IL-1B, SERPINB4, IL-8, CXCL5, IL-6 as well as some MMPs (MMP1, 3, 10, 9 and 12) also showed higher levels in AWs than DFUs (Table 4.3). This pattern was also observed in down-regulated genes. Differentiation markers of keratinocytes including KRT1, KRT2,

63 49 LOR, DSC1, LCE1B, LCE2B and FLG had a stronger suppression in AWs than in DFUs (Table 4.3). Gene Symbol DFU/FS AW d3/ns KRT ELMOD IL SERPINA DSC LCE2B AADACL FLG LOR KRT FLG LCE1B CHP CD ARG OMD ABHD12B CDHR DCT LAMB FABP MLANA POF1B SLC46A OGN BTC POU2F KY TYRP HAL Gene Symbol Table 4.3. Top 30 down- and up-regulated genes in both DFUs and AWs (sorted by AW expression) Network analysis and gene expression validation To further investigate what possible genes could drive the global changes in gene expression and cellular functions observed in DFUs, I took advantage of IPA network generator tools and created regulatory networks which consist of uniquely enriched upstream regulators and their regulated genes for either DFUs or AWs (Figure 4.4 A). The DFU/FS AW d3/ns MMP SERPINB IL MMP PI S100A7A CXCL MMP S100A SPINK S100A PTGS PTHLH CCNA SERPINA AREG LIPG PPBP IL MMP IL1B TREM KRT MMP KLK CD UPP SERPINE KYNU IL

64 50 functional analysis of these networks showed enrichment of multiple functions and processes required for proper wound healing including inflammatory response, differentiation, migration, proliferation, chemotaxis and angiogenesis induced in AW but reduced in DFUs similar to overall gene expression analysis (Figure 4.4 A) suggesting an impaired activity of these processes in DFUs in comparison to AWs. Essentially, this reduced number of genes is sufficient to explain most of the functional differences observed between DFUs and AWs, as the genes in these networks are key regulators in most of those processes. The DFU regulatory network consisted of suppressed regulatory genes and transcription factors belonging to several pathways which were not differentially expressed in AWs. These include IKBKB, phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), activating transcription factor 2 (ATF2), among others. First, I validated the microarray expression of PIK3R1, IKBKB, ATF2, FGF2, and IGF, that play a role in wound healing (44) and are related to inflammatory response. All of them were significantly downregulated in DFUs compared to FS confirming array data (Figure 4.4 B). IKBKB, which is an activator of the NF-kB pathway and inflammatory response (159), was also confirmed to be down-regulated at the protein level in DFUs (Figure 4.4 C). Its inhibition can reduce the inflammatory response and pro-inflammatory cytokine production in response to LPS treatment (159), and may contribute to diminished ability of DFU tissue to respond to infection. In addition, suppression of PIK3R1 and subsequent inhibition of PIK3/AKT pathway, could also affect the de-regulation of inflammatory response observed in DFUs.

65 51 On the other hand, the network analysis showed an array of pro-inflammatory cytokines, chemokines and other immune related genes specifically up-regulated in the AW (e.g. CCL2, CCL5, TLR2, TLR4, MYD88, TNFSF12, and PTPRC) (Figure 4.4 A). None of the genes in this network are up-regulated in the DFU profiles and some of them (PTPRC, NOD1, STAT4 SELP, DPP4 and IRAK3) are down-regulated in DFUs further supporting the notion of diminished inflammatory response in DFUs. CCL2 was found to be downregulated in wounds of diabetic (db/db) mice compared to control wounds causing a delay in the chemotaxis of macrophages to wound, and thus a delayed inflammatory response in the diabetic mice (160). Furthermore, a single treatment of CCL2 restored a similar macrophage response to the control mice. CCL5/CCR5 interaction have been shown to be important for neovascularization and recruitment of endothelial progenitors cells in mice (161), which are processes diminished in diabetic mice wound healing (162). In addition, the diabetic mice also exhibit a down-regulation of SDF1 (CXCL12 in humans) in the wounds which contributes to the reduced neovascularization and recruitment of endothelial progenitors cells and it is also down-regulated in DFUs but not in AWs (162). TNFSF12, another pro-inflammatory factor, has also been associated with the inflammatory response in acute wound healing and diseases involving chronic inflammation (reviewed in (163, 164)) which is only up-regulated in AWs but not in DFUs. These molecules and their related pathways are crucial not only for the recruitment of immune cells during wound healing (42, 44, 165), but also required for epithelialization (166). According to these data, the acute inflammatory response involves the temporal overexpression of several pro-inflammatory factors not observed in DFUs, which suggests

66 52 that this process is not induced in DFUs, but rather impaired, never reaching the threshold of an acute response in order to continue with the process of healing, leading to a suboptimal chronic inflammation. I conclude that DFUs exhibit a partial but chronic inflammatory response which may not be reaching the threshold of an acute inflammatory wound phase required to start an appropriate healing response DFUs exhibit down-regulation of DNA repair mechanisms and subsequent increased DNA damage Suppression of genes involved in DNA repair mechanisms in DFUs (p-value = 4.6x10-6, Table 4.1, Figure 4.3, Figure 4.4 A) was an unexpected finding of the DFU transcriptome enrichment analysis and has not been previously reported. This category was also enriched in the network built from DFU specific gene signature (Figure 4.4 A). I validated microarray expression data and down-regulation of the DNA repair related genes WEE1, MSH2, RAD50, transformation-related protein 53 (TP53) and Tyrosine-Protein Kinase Kit (KIT) by qpcr (Figure 4.5 A). I also confirmed suppression of MSH2 protein level by immunofluorescence staining (Figure 4.5 B). MSH2 can form two heterodimeric complexes MutSα (with MSH6) and MutSβ (with MSH3) which recognize and repair DNA mismatch or small insertion deletion loops respectively and its mutations cause DNA repair deficiency and genomic instability (167). Moreover, WEE1, RAD50 and FGF2, are known to be important for double strand break (DSB) repair ( ). RAD50 is directly involved in the process initiating and coordinating DSB repair (168), whereas WEE1 and FGF2 are not directly executing DNA repair, although they are required for a successful repair process. WEE1 is a DNA damage G2-M checkpoint kinase which stops DNA replication and arrests the cell cycle after DNA damage occurs (169, 170). FGF2 involvement in DNA repair is still obscure, even though its signaling pathway is induced

67 53 in irradiated keratinocyte progenitor cells and its abrogation resulted in excessive DNA damage (171). In addition to the previously mentioned genes, inhibition of the PI3K/AKT pathway can result in delayed recovery of DNA damage after radiation (172, 173), thus down-regulation of PIK3R1 could also contribute to diminished DNA repair observed in DFUs. In addition, DFUs exhibit an increased oxidative environment caused by multiple factors such as increased glucose, down-regulation of NRF2 (174) and the presence of bacteria (175, 176) among others. The increased levels of reactive oxygen species (ROS) found in DFUs may result in increased DNA damage and, because DNA repair genes are suppressed in DFUs, I hypothesized that DFU should exhibit increased double strand DNA breaks. I tested the level of a phosphorylated-h2a (p-h2ax), a known marker of DNA damage, in DFUs by western blotting. p-h2ax was highly present in DFUs, but not in control foot skin, confirming the presence of double stranded DNA breaks (Figure 4.5 C). IL1A has been found to be a direct sensor of DNA damage recently, acting as a trigger for tissue repair and inflammation upon DNA breaks (177). Consistently, I detected IL1A upregulation in DFUs by qpcr (Figure 4.5 D), which suggests that the higher expression of IL1A in DFUs could be due to increased DNA damage. Taken together, these data show novel insights into the role of suppressed DNA repair mechanisms and increased DNA damage in inhibition of healing in patients with DFUs.

68 54 A. DFU-specific gene Network Inflammatory response DNA repair - Transcription - Differentiation Migration Proliferation Chemotaxis Angiogenesis AW-specific gene Network B. PIK 3R1 IKBKB ATF2 FGF2 IG F1 1.5 ** 1.5 ** 1.5 *** 2.0 * 2.0 C. R elative expression DFU FS DFU DFU FS MW (Kda) DFU FS Figure 4.4. Network analysis and gene expression validation of DFU de-regulated genes. A. Network analysis of the genes de-regulated uniquely in DFUs (left) or AWs (right). The networks were built using IPA focusing on genes with known regulatory functions. Enrichment analysis of these DFU- and AW-specific networks showed highly significant either inactivation or activation of important functions related to wound healing in DFUs or AWs respectively (middle); green=suppression; red=induction. For a larger version of these networks see Figure A. 1 in the Appendix. B. qpcr validation of microarray data. PIK3R1, IKBKB, ATF2 and FGF2 showed significant down-regulation in DFU compared to FS. IGF1 showed a trend of down-regulation but it did not reach statistical significance. FS DFU FS R elative expression IKBKB D FU DFU * FS FS

69 55 C. Western blot showing suppression of IKBKB in DFU compared to FS; graph represents quantification of the western blot (n=5 per group, unpaired t-test was used to determine statistical significance, * = p-value<0.05, ** = p-value < 0.01, *** = p-value < 0.001). A. M SH2 WEE1 RAD50 TP53 KIT 1.5 ** 2.0 * 1.5 *** 1.5 *** 1.5 ** R elative expression DFU FS DFU FS DFU FS DFU FS DFU FS B. FS DFU MSH2 D E E D E D C. D. IL1A 60 * Figure 4.5. DNA repair mechanism related genes are suppressed in DFU. A. qpcr validation of DNA repair genes in DFUs. WEE1, MSH2, RAD50, TP53 and KIT are down-regulated in DFUs compared to FS. B. Immuno-fluorescence staining showing decreased expression of MSH2 in DFUs compared to FS. E=epidermis; D=Dermis; white dashed line demarcates. C. p-h2ax western blot confirming the presence of DNA double strand breaks in DFUs but not control FS. D. qpcr showing relative gene expression of IL1A in DFUs compared to FS (n=5 per group, unpaired t-test was used to determine statistical significance, * = p-value<0.05, ** = p-value < 0.01, *** = p-value < 0.001). R elative expression DFU FS

70 Mir-15b-5p up-regulation in DFUs leads to diminished Inflammatory Response and DNA Repair To find possible upstream regulators of the genes and cellular functions found altered in DFU profiles, I used the up-stream prediction tools from IPA to analyze the list of regulated genes in both DFUs and AWs. This analysis detected a significant enrichment for mir- 15b-5p target genes within all DFU regulated genes (Z-score=4.5, p-value=1.02x10-09) and DFU specific networks (Z-score=1.5, p-value=1.02x10-06) but not in AW regulated genes. The predicted targets of mir-15b-5p included MSH2, RAD50, FG2, WEE1, IGF1, PIK3R1 and IKBKB (Figure 4.6 A), all of which are associated with the diminished inflammatory response and impaired DNA repair mechanisms observed in DFUs. Thus, I hypothesized that increased expression of mir15b-5p in DFUs could down-regulate its target genes leading to suppressed inflammatory response and DNA damage repair. Following these predictions, I used qpcr to confirm that mir-15b-5p is over-expressed in DFUs in comparison to FS. (Figure 4.6 B). In contrast, I found that mir-15b-5p expression is down-regulated following wounding in an ex-vivo human acute wound model (Figure 4.6 B). To test if mir-15b-5p can regulate the expression of its target genes, I transfected the human keratinocyte cell line HaCaT with the synthetic mimic-mir-15b-5p or a control mimic-mir. This in vitro over-expression of mir-15b-5p caused a statistically significant down-regulation of IKBKB, PIK3R1 and WEE1, and a reduction MSH2 and RAD50 (Figure 4.7). Next, I generated pmirglo luciferase reporter vectors containing the 3 UTRs of IKBKB and WEE1. The co-transfection of either of these vectors with mir- 15b-5p in HEK293T cells resulted in a significant reduction in the luciferase reporter signal

71 57 in comparison to the ones co-transfected with the mimic control confirming direct targeting (Figure 4.8). A. B. hsa-m ir -15b-5p hsa-mir-15b-5p in AW R elative expression DFU * NFS N orm alized relative expression Figure 4.6. mir-15b-5p is up-regulated in DFUs and target several regulatory genes. A. mir-15b-5p predicted targets, processes and pathways, from network build using IPA. B. mir-15b-5p expression in DFUs and AWs measured by qpcr. (DFU, n=6 per group, unpaired t-test was used to determine statistical significance, AW n=3 per time-point, paired t-test was used to determine statistical significance, * = p-value<0.05). 0h 48h 7d * Together this data suggests that mir-15b-5p can affect multiple signaling pathways such as NF-KB, IL6, IL8, IL12, PI3K/AKT, PTEN (178, 179). Furthermore by suppressing the key regulator genes IKBKB and PIK3R1, mir-15b-5p is affecting the inflammatory phase of wound healing (Figure 4.6 A). Moreover, the induction of mir-15b has been linked to increased p-h2ax levels and DNA breaks in cancer cells through targeting of WEE1 (180), providing a direct association between mir-15b-5p over expression and the inhibition of DNA repair mechanisms detected in DFUs.

72 58 R elative E xp ression IKBKB * m im ic ctrl m im ic 15b-5p M SH2 R elative E xp ression WEE1 * m im ic ctrl m im ic 15b-5p FGF2 R elative E xp ression PIK 3R1 ** m im ic ctrl m im ic 15b-5p RAD50 Figure 4.7. mir-15b-5p suppresses IKBKB, WEE1, and PIK3R1 expression in HaCaT cells. The expression of the target genes was measured 48h after transfection of HaCaT with mir-15b-5p mimic or ctrl mimic. (n=3 per condition, paired t-test was used to determine statistical significance, * = p- value<0.05, ** = p- value<0.01). R elative E xp ression R elative E xp ression R elative E xp ression m im ic ctrl m im ic 15b-5p m im ic ctrl m im ic 15b-5p m im ic ctrl m im ic 15b-5p N orm alized R ela tiv e lu cifera se activ ity IKBKB 3' UTR *** m im ic ctrl mimic 15b-5p N orm alized R ela tiv e lu cifera se activ ity WEE1 3' UTR ** m im ic ctrl mimic 15b-5p Figure 4.8. mir-15b-5p targets the 3 UTRs of IKBKB and WEE1. Luciferase reporter assay showing down-regulation of luciferase activity in cells co-transfected with reporter vector and mir-15b-5p mimic. The luciferase activity was measured 24h after transfection. Experiments were carried out in triplicates, unpaired t-test was used to determine statistical significance, * = p-value<0.05, ** = p-value < 0.01, *** = p-value <

73 S. aureus infection causes induction of mir-15b-5p and subsequent suppression of IKBKB and WEE1 Up-regulation of the mir-15 family has been found to be mediated by reactive oxygen species (ROS) (181) which are commonly found in ulcer environment, partly due to bacterial presence (175, 176). This suggests a potential mechanism by which mir-15b-5p may be induced in DFUs. S. aureus is the most common bacterial colonizer found in DFUs (182, 183) and although the mechanisms of S. aureus mediated inhibition of healing in animal models are being studied (127), the contribution of S. aureus to chronicity of DFU and suppression of healing are not fully elucidated. In order to determine whether S. aureus infection could induce mir-15b-5p in wounds, I infected ex vivo wounds with the clinical S. aureus isolates, which resulted in inhibition of epithelialization as observed with H&E and keratin 6 (K6) immunofluorescence staining. (Figure 4.9). Furthermore, S. aureus wound infection induced mir-15b-5p and suppressed its target genes IKBKB and WEE1 (Figure 4.10). PIK3R1 also showed a trend of down-regulation in response to infection although it did not reach statistical significance. This suggests that colonization or infection of DFUs by S. aureus can lead to mir-15b-5p overexpression which in turn may have detrimental effects in the inflammatory response and DNA repair mechanisms, at least in part, by targeting IKBKB and WEE1 respectively.

74 60 Ctrl S. aureus ET Ctrl S. aureus K6 DAPI K6 DAPI Figure 4.9. Infection of ex-vivo wounds inhibits wound healing. Upper panels: H&E staining of wound edges; lower panel: K6 immunofluorescence staining on non-infected ex vivo human wound (Ctrl) and S. aureus infected wound. Black arrowheads indicate initial site of wounding. Red arrowheads and dashed white line indicate bacterial aggregates. ET= epithelia tongue. m ir -15b-5p IKBKB WEE1 PIK 3R1 R elative E xp ression ** R elative E xp ression * R elative E xp ression * R elative E xp ression C trl S. aureus C trl S. aureus C trl S. aureus C trl S. aureus Figure mir-15b-5p is induced in AW infected with S. aureus and targets IKBKB and WEE1. Expression of mir-15b-5p, IKBKB, WEE1 and PIK3R1 measured by qpcr 4 days after wounding and infection of ex-vivo acute wound model. (n=3 per condition, paired t-test was used to determine statistical significance, * = p-value<0.05, ** = p-value<0.01)

75 Chapter conclusion DFUs had been previously found to be in a prolonged inflammatory state, mostly because of the-expression of the pro-inflammatory cytokines IL-1, IL-6, IL-8 and TNFα, although, the vast majority of the components, molecules and signaling pathways of the inflammatory response were disregarded. The microarray and comparative genomic analyses between DFUs and AWs described in this section, revealed that this chronic inflammatory state in DFUs is deficient in comparison to AWs. This diminished inflammatory phenotype is caused by induction of mir-15b-5p and subsequent suppression of regulatory genes and pathways including NF-κB and PI3K/AKT. Furthermore, lack of up-regulation of several other chemotactic factors such as CCL2 and CCL5 also contributes to insufficient inflammatory response in DFUs, as these chemokines are required for the recruitment of immune and pro-angiogenic cells needed for an adequate healing response. Most studies focus only on a few of the pro-inflammatory factors mentioned above, and thus assume that decreasing inflammation in DFUs could be beneficial for the healing of these ulcers. Unlike those more specific studies, I took a comprehensive strategy and investigated the pathophysiology of DFU using a broader perspective. The data generated in this work suggest that even if these few pro-inflammatory molecules are reduced, many others have to be up-regulated, at least in a time controlled manner, in order to restore the proper response seen in AWs. In addition, I found that genes involved in DNA repair mechanisms are specifically suppressed in DFUs, but not in AWs. I found several genes involved in this function to be down-regulated in DFUs, some of which are targeted by mir-15b-5p. I also showed that there is increased DNA damage in DFUs, as a functional consequence of the lack of repair. Finally, I found that S. aureus infection induces mir- 15b-5p and thus contributes to this impairment of DNA repair mechanism, which leads to

76 62 persistent DNA damage. Consequently, this unresolved DNA damage, can in turn, increase the expression of IL-1A which further facilitates the chronic inflammatory state observed in DFUs (Figure 4.11). This represents a novel molecular pathway featuring mir-15b-5p as one of major regulators of the pathophysiology of DFUs, and could serve as a new potential therapeutic target. Figure Scheme showing how mir-15b-5p regulates many processes involved in pathophysiology of DFUs. S. aureus colonization in DFUs leads to over-expression of mir-15b-5p resulting in increased DNA damage through suppression of WEE1 and chronic diminished inflammation by targeting IKBKB. DNA repair mechanisms are further inhibited by downregulation of multiple genes in DFUs including MSH2, RAD50, KIT, FGF2 and TP53. DNA damage feeds into a positive feedback loop by causing the release of IL1A.

77 CHAPTER 5. MIR EXPRESSION IN THE EPIDERMIS OF DFUs 5.1. microrna expression in the epidermis of DFUs Given the large number of de-regulated genes and cellular processes in DFUs it is likely that mir-15b-5p is not the only mir aberrantly expressed in DFUs. Using LCM and microrna profiling, I sought to investigate which other mirs were de-regulated in the epidermis of DFUs that may contribute to the pathophysiology and inhibition of healing in these chronic ulcers. I used LCM to capture the epidermis from 6 DFUs (Figure 5.1 A) and extract total RNA including the mir fraction. MiR expression profiles were generated using Ready-to-Use PCR panels v2. These panels can detect 752 human mirs out of which, after quality control and data processing, I detected 177 mirs expressed in the epidermis of DFUs. I combined these data with the previously generated FS profiles in order to determine which mirs were differentially expressed in the epidermis of DFUs. As expected, in this case, clustering and principal component analysis (PCA) showed a distinct segregation between DFUs and FS (Figure 5.1 B). I found 82 differentially expressed mirs between DFUs and FS (46 up- and 36 down-regulated, FC 1.5, FDR 0.05) (Table 5.1). I selected 2 top induced (hsa-mir-31-5p and 135b-5p) and top suppressed mirs (hsa-mir- 199a-3p and 214-3p) for individual PCR confirmation in LCM captured epidermis as well as full thickness skin samples (Figure 5.2). Similarly to what I found in NFS and DFS, there is a high correlation between the mir expression in epidermis and full thickness biopsies, which implies that the expression of mirs in skin is mainly driven by epidermal expression. (Table 5.2). The role of mir-31-5p in skin biology and pathology (psoriasis) has been briefly discussed in Chapter 3. In addition, mir-31-5p was found to play an active part during early stages 63

78 64 of acute wound healing to promote keratinocyte migration and proliferation by targeting EMP1 (184). The other highly induced mir in DFUs is mir-135b-5p, which is known to be up-regulated in cutaneous squamous cell carcinoma (cscc), and promotes cell migration by targeting LZTS1 (185). It is also found in psoriatic lesions and is possibly involved in controlling keratinocyte differentiation (186). On the other hand, the two suppressed mirs, mir-199a-3p and mir-214-3p have been shown to inhibit migration and invasion of breast cancer cells and have tumor suppressor activity. Conversely, their downregulation promotes cell migration and invasion (187, 188). Furthermore, mir-214-3p inhibits keratinocyte proliferation and hair follicle development (189). Based on all these findings, coupled with data described in Chapter 4 regarding overlap between transcriptomes of AWs and DFUs, one can speculate that these particular mirs may belong to an acute wound healing mir signature rather than an abnormal DFU-specific mir signature. A. B. FS DFU Figure 5.1. Laser capture microdissection (LCM) and mir profiling of epidermis from DFUs and FS. A. Picture of DFU sample before (upper panel) and after LCM. B. Clustering analysis of mir profiles from epidermis of FS and DFUs showing distinct clustering of the samples.

79 65 (DFU) vs (FS) Fold change P (Benjamini- Hochberg) hsa-mir p E-06 hsa-mir-31-5p E-02 hsa-mir-31-3p E-03 hsa-mir E-04 hsa-mir-135b-5p E-03 hsa-mir E-05 hsa-mir-520h E-03 hsa-mir-424-5p E-05 hsa-mir-141-5p E-04 hsa-mir p E-04 hsa-mir-21-3p E-03 hsa-mir E-05 hsa-mir-331-3p E-05 hsa-mir-593-3p E-04 hsa-mir-182-5p E-03 hsa-mir-18b-5p E-04 hsa-mir-185-5p E-05 hsa-let-7a-3p E-03 hsa-mir-502-5p E-05 hsa-mir-483-3p E-04 hsa-mir-663a E-04 hsa-mir-615-3p E-03 hsa-mir-132-3p E-03 hsa-mir-27a-3p E-05 hsa-mir E-02 hsa-mir E-02 hsa-mir p E-03 hsa-mir-17-5p E-03 hsa-mir E-03 hsa-mir E-02 hsa-mir-187-3p E-02 hsa-mir p E-05 hsa-mir-425-3p E-02 hsa-mir-143-5p E-02 hsa-let-7f-2-3p E-04 hsa-mir-590-5p E-02 hsa-mir-21-5p E-03 hsa-mir-15b-5p E-03 hsa-mir-491-5p E-05 hsa-mir E-03 hsa-mir-744-3p E-02 hsa-mir-34c-3p E-03 hsa-mir-17-3p E-03 hsa-mir-708-5p E-02 hsa-mir-193b-3p E-02 hsa-mir E-02 (DFU) vs (FS) Fold change P (Benjamini- Hochberg) hsa-mir-199a-3p E-04 hsa-mir-214-3p E-05 hsa-mir-199b-5p E-04 hsa-mir-199a-5p E-04 hsa-mir-497-5p E-04 hsa-mir-150-5p E-03 hsa-let-7c E-05 hsa-mir-145-5p E-03 hsa-let-7d-5p E-05 hsa-mir-29b-3p E-03 hsa-mir-126-5p E-03 hsa-mir-181b-5p E-03 hsa-mir-98-5p E-03 hsa-mir-25-3p E-03 hsa-mir-222-3p E-03 hsa-mir-224-5p E-05 hsa-mir-193a-5p E-04 hsa-mir-29a-3p E-02 hsa-mir-130a-3p E-03 hsa-let-7i-5p E-04 hsa-mir-125a-5p E-02 hsa-mir E-02 hsa-mir-126-3p E-02 hsa-mir-181a-5p E-03 hsa-mir-29c-3p E-02 hsa-mir-93-3p E-02 hsa-mir-196b-5p E-02 hsa-mir-142-3p E-02 hsa-mir-452-5p E-02 hsa-mir-221-3p E-03 hsa-mir-151a-5p E-02 hsa-mir-324-5p E-02 hsa-mir-23b-3p E-03 hsa-let-7f-5p E-02 hsa-mir-378a-3p E-02 hsa-let-7g-5p E-02 Table 5.1. List of differentially expressed mirs in the epidermis of DFUs when compared to FS. MiRs with a FC 1.5 and multiple testing corrected P-value 0.05 were considered significantly regulated.

80 66 hsa-m ir -31-5p LCM hsa-m ir -31-5p F u ll th ick n ess hsa-m ir -135b-5p LCM hsa-m ir -135b-5p F u ll th ick n ess R elative expression *** R elative expression **** R elative expression **** R elative expression * DFU FS DFU FS DFU FS DFU FS hsa-m ir-199a-3p LCM hsa-m ir-199a-3p F u ll th ick n ess hsa-mir-214-3p LCM hsa-mir-214-3p F u ll th ick n ess R elative expression R elative expression ** R elative expression R elative expression ** DFU FS DFU FS DFU FS DFU FS Figure 5.2. Validation of mir expression by qpcr in LCM captured epidermis and full thickness DFU biopsies. Four of the most regulated mirs were tested. In all cases full thickness biopsies show similar expression to the epidermal mir. (n=6 per group, unpaired t-test was used to determine statistical significance, * = p-value 0.05, ** = p-value 0.01, *** = p-value 0.001, **** = p-value ). mir LCM vs Full thickness correlation (spearman s ρ) p- value hsa-mir-31-5p hsa-mir-135b-5p hsa-mir-199a-3p hsa-mir-214-3p Table 5.2. mir expression correlation between LCM captured epidermis and full thickness skin biopsies. Spearman s correlation was used to estimate the correlations between epidermis and full thickness biopsies. (n=10 samples per group)

81 Ex-vivo acute wound mir profiling and comparison with DFU mir profiles I measured the expression of mir-31-5p, mir-135b-5p, mir-199a-3p and mir-214-3p in a human ex-vivo AW model by qpcr. I found that mir-31-5p and mir-135b-5p were upregulated after wounding and mir-199a-3p and mir-214-3p were down-regulated (Figure 5.3), which confirmed that there is an overlap in mir expression profiles between DFUs and AWs. hsa-m ir-31-5p in AW hsa-m ir-135b-5p in AW N orm alized relative expression N orm alized relative expression h 24h 48h 96h 0h 24h 48h 96h hsa-m ir-199a-3p in AW hsa-mir-214-3p in AW N orm alized relative expression N orm alized relative expression h 24h 48h 96h 0h 24h 48h 96h Figure 5.3. mir-31-5p, mir-135b-5p, mir-199a-3p and mir-214-3p expression in exvivo AW model. MiR expression was measured by qpcr in triplicate of two different biological replicates (independent wounding experiments). To select for mirs specifically de-regulated in DFU, I used a similar approach as previously described for gene expression analyses (Chapters 3 and 4). I generated ex-vivo acute wound mir profiles using nanostring. After removal of mirs with low expression and/or incomplete data I detected 188 mirs expressed in AWs. Next, I compared generated

82 68 lists of differentially expressed mirs by comparing 48h or 7d wounds to the 0h control. Genes that were up- or down-regulated ( FC 1.5, unadjusted p-value 0.05) were considered differentially regulated. The majority (41 out of 50) of differentially expressed mirs were found to be down-regulated in either 48h or 7d while only 9 were up-regulated (Table 5.3). The comparison between the DFUs and AWs differentially expressed mirs revealed a very small number of overlapping mirs that are regulated in the same direction. Majority of mirs were specifically regulated either in DFUs or AW. Only 3 mirs, hsa-mir-15b-5p, has-mir-193b-3p and mir-590-5p were oppositely regulated between DFUs and AWs, all of which are up-regulated in DFUs but down-regulated in AWs (Figure 5.4 A). I had previously identified mir-15b-5p to be specifically up-regulated in DFUs and showed that it may target genes such as IKBKB and WEE1, which are involved in regulation of the inflammatory response and DNA repair. MiR-590-5p belongs to the mir- 21 family and shares its seed sequence as well as many predicted gene targets. This family was found enriched and up-regulated in venous leg ulcers from microarray profiling data by Dr. Tomic-Canic s lab (105). mir-21-5p was shown to target LEPR and EGR3, and to inhibit wound closure in a rat model and in the ex-vivo human wound model (105). The third, mir from the small set of oppositely regulated mir between DFUs and AWs, and arguably the most interesting, is the tumor suppressor mir-193b-3p, which is particularly suppressed in aggressive cscc and was found to target KRAS and MAX (190). Furthermore, over-expression of mir-193b-3p inhibited keratinocyte proliferation and invasion (190). Therefore, I validated the suppression of hsa-mir-193b-3p in the ex-vivo acute wound model by qpcr and confirmed its up-regulation in DFUs (Figure 5.4 B).

83 69 (AW) vs (NS) Fold change 48h Fold change 7d p-value 48h p-value 7d hsa-mir-155-5p E E-02 hsa-mir-188-5p E E-01 hsa-mir p E E-01 hsa-mir-362-5p E E-01 hsa-mir-642a-5p E E-01 hsa-mir-96-5p E E-01 hsa-mir-132-3p E E-02 hsa-mir-135b-5p E E-01 hsa-mir-21-5p E E-01 (AW) vs (NS) Fold change 48h Fold change 7d p-value 48h p-value 7d hsa-mir E E-05 hsa-mir-125b-5p E E-03 hsa-mir-127-3p E E-02 hsa-mir-136-5p E E-09 hsa-mir-140-3p E E-09 hsa-mir-143-3p E E-03 hsa-mir-149-5p E E-02 hsa-mir-181c-5p E E-04 hsa-mir-190a E E-03 hsa-mir p E E-02 hsa-mir-191-5p E E-02 hsa-mir-223-3p E E-02 hsa-mir-296-5p E E-04 hsa-mir-301a-3p E E-04 hsa-mir-32-5p E E-02 hsa-mir-330-3p E E-03 hsa-mir-337-5p E E-02 hsa-mir-340-5p E E-04 hsa-mir-362-3p E E-03 hsa-mir-377-3p E E-04 hsa-mir-382-5p E E-02 hsa-mir-409-3p E E-07 hsa-mir E E-02 hsa-mir E E-03 hsa-mir-450a-5p E E-04 hsa-mir-451a E E-01 hsa-mir-455-3p E E-06 hsa-mir-514a-3p E E-03 hsa-mir-514b-5p E E-01 hsa-mir E E-01 hsa-mir E E-03 hsa-mir-769-5p E E-05 hsa-mir-142-3p E E-02 hsa-mir-145-5p E E-06 hsa-mir-196b-5p E E-02 hsa-mir-214-3p E E-03 hsa-mir-29a-3p E E-02 hsa-mir-324-5p E E-02 hsa-mir-15b-5p E E-02 hsa-mir-193b-3p E E-04 hsa-mir-590-5p E E-03 Table 5.3. List of differentially expressed mirs during ex-vivo AW healing. MiRs with a FC 1.5 and unadjusted P-value 0.05 were considered significantly regulated.

84 70 A. DFU 82 Up 40 6 Up AW 50 Oppositely regulated mirs Down Down mir FC AW FC DFU hsa-mir-15b-5p hsa-mir-193b-3p hsa-mir-590-5p B. hsa-m ir-193b-3p in AW hsa-m ir -193b-3p ** N orm alized relative expression * R elative expression h 48h 7d DFU NFS Figure 5.4. Comparative analysis of regulated mirs between DFUs and AWs. A minor overlap in mir expression was found between DFU and AWs, with 9 mirs regulated in the same direction and 3 oppositely regulated. A. Venn diagram showing overlap between the differentially regulated mirs between DFUs and AW. B. qpcr validation of mir-193b-3p and mir-31 in AW and DFUs. (DFU, n=6 per group, unpaired t-test was used to determine statistical significance, AW n=3 per time-point, paired t-test was used to determine statistical significance, * = p-value 0.05, ** = p-value 0.01, *** = p-value 0.001, **** = p-value ) 5.3. mir-193b-3p inhibits cell migration and has a dominant effect over other mirs As mentioned above, mir-193b-3p has been shown recently to inhibit keratinocyte invasion, however, the effects of mir-15b-5p or the combined effects of these in keratinocyte migration have not been evaluated. I carried out in-vitro scratch wound assay and keeping in line with the data that show multiple mirs over-expressed in DFUs, i.e. environment in which there is simultaneous presence of more than a single mir, I tested

85 71 the effects of these mirs individually or in combination. I found that both mir-15b-5p and mir-31-5p mimic promoted keratinocyte migration significantly, whereas mir-193b-3p inhibited migration (Figure 5.5). This inhibition of wound closure seem to be only due to inhibition of cell migration, rather than the effect of cell viability or proliferation because transfection of mir-193b-3p did not show any significant effect in either cell viability or proliferation in mitomycin treated HaCaT cells (Figure 5.6). Mimic Ctrl Mimic 193b-3p Mimic 15b-5p Mimic 31-5p 0h 48h % m igrated area M igration assay * ** ** Figure 5.5. In vitro scratch wound assay using single mir mimics. mir-193b-3p inhibits cell migration while mir-15b-5p and mir-31-5p promote wound closure (n=3, unpaired t-test was used to determine statistical significance, * = p-value 0.05, ** = p-value 0.01). 0 m im ic C trl mimic 193b-3p mimic 15b-5p m im ic 31-5p

86 72 total num ber of cells V iability # cells(*1000)/w ell % viab le cells h 24h 48h 0h 24h 48h m im ic C trl mimic 193b-3b Figure 5.6. mir-193b-3p does not influence cell viability. Cells were transfected with mimic 193b-3p or mimic control, treated with mitomycin 24h post-transfection and counted afterwards in presence of trypan blue to determine cell viability. No significant difference was found between mir-193b-3p and mimic control at any time point. Next, I tested the effects of co-transfecting mir-193b-3p with either mir-31-5p or mir- 15b-5p using the same in vitro system. In both cases, mir-193b-3p abolished the positive effects of these mirs in cell migration and showed a dominant inhibitory effect (Figure 5.7). This inhibition of potentially beneficial effects of mir-15b-5p or mir-31-5p in promoting cell migration, may result in collateral effects, such as mir-15b-5p mediated suppression of DNA-repair mechanisms or inflammatory response which I discussed in the previous chapter and that may be detrimental for wound healing. Thus, mir-193b-3p may be a major contributor of overall pathophysiology of DFUs.

87 73 Mimic Ctrl Mimic 193b-3p Mimic 193b-5p + Mimic 15b-5p + Mimic 31-5p 0h 48h % m igrated area M igration assay * Figure 5.7. In vitro scratch wound assay using combination of mir mimics. Overexpression of mir-193b-3p in the presence of either mir- 15b-5p or mir-31-5p inhibits cell migration indicating mir- 193b-3p has a dominant effect over these pro-migratory mirs. (n=3, unpaired t-test was used to determine statistical significance, * = p-value 0.05, ** = p-value 0.01). 0 m im ic C trl mimic 193b-3p + 15b-5p mimic 193b-3p p 5.4. mir-193b-3p prevents formation of stress fibers mir-193b-3p had been previously found to inhibit invasion by targeting KRAS and MAX (190). However, mir-193b-3p show a dominant inhibitory effect over other pro-migratory mirs suggesting that it might be affecting the cytoskeletal machinery. In order to determine which aspect of the cell movement process mir-193b-3p is affecting primary keratinocytes were transfected with either mir-193b-3p or control mimic, followed by stimulation by either EGF for 1 minute (to induce filopodia formation), 5 minutes (to induce lamellipodia formation) or calpeptin (CN01) for 20 minute (to induce stress fiber formation). In each

88 74 case the actin cytoskeleton was visualized using phalloidin-rhodamine staining. Unstimulated cells, as well as EGF treated cells did not show morphological differences between cells transfected with mimic control or mimic 193b-3p. However, in CN01 treated HaCaT cells there was reduction of stress fiber formation in the presence of mir-193b-3p when compared to mimic control transfected cells (Figure 5.8). This data suggest that mir- 193b-3p may impair cell migration by disrupting stress fiber formation. Furthermore, it also points towards targeting regulation of Rho GTPases or their down-stream targets (191, 192). Vehicle CNO1 EGF Mimic ctrl Mimic 193b-3p Figure 5.8. mir-193b-3p prevents formation of stress fibers in keratinocytes. Phalloidin staining of human primary keratinocytes transfected with mimic ctrl or mimic 193b-3p and treated with vehicle, CNO1 (stimulant of stress fibers formation) or EGF (stimulant of phillipodia and lamelipodia). Lastly, IPA analysis identified 16 mir-193b-3p possible target genes that are directly or indirectly involved in cell migration and are uniquely down-regulated in DFUs (Table 5.4). Some of the genes of this list have been already implicated in keratinocyte migration ( ). For example, keratinocytes derived from MAP3K1 knockout mice are defective in TGF-β and activin induced migration and show reduced formation of actin stress fibers

89 75 (193), similarly to what is observed from mimic 193b-3p transfected keratinocytes. One has to recognize that inhibition of keratinocyte migration in DFUs is likely a result of multiple signals originating from keratinocytes as well as from cross-talk with other cellular compartments. Nevertheless, the findings that mir-193b-3p is dominant inhibitor of keratinocyte migration, possibly targeting multiple genes related to this cellular process that leads to inhibition of stress fibers points towards an important mechanism that contributes to inhibition of healing in DFUs. Predicted Target FC DFU/FS FC AW/NS KIT -8.5 NC MKL2-6.3 NC ARHGEF6-5.2 NC ATM -4.2 NC MAP3K1-3.7 NC LRP6-3.6 NC TNS1-3.4 NC ETV6-3.2 NC JAK2-3.2 NC IGFBP5-3.1 NC TCF4-2.7 NC SOS2-2.4 NC LPP -2.3 NC RNF7-2.1 NC ETV5-2.1 NC TGFB2-2.0 NC Table 5.4. mir-193b-3p predicted targets involved in cell migration that are specifically down-regulated in DFUs S. aureus infection induces mir-193b-3p and inhibits wound healing ex vivo mir-193b-3p was found to be up-regulated in mouse blood upon infection with S. aureus (196). Thus, I took advantage of the human ex-vivo infection model used in chapter 4.7 to test the expression of mir-193b-3p by qpcr. I found that mir-193b-3p is induced in all S. aureus infected wounds when compared to the control, although it did not reach statistical significance (Figure 5.9). As described before, the S. aureus infected wounds

90 76 showed inhibition of epithelizalition, which is consistent with the finding that mir-193b- 3p inhibits keratinocyte migration. This suggests, that mir-193b-3p may play a key role in the inhibition of healing in DFUs and its induction is, at least in part, caused by S. aureus infection. mir-193b-3p 4 p= 0.1 R elative E xp ression C trl S. aureus Figure 5.9. MiR-193b-3p is induced in S. aureus infected human acute wounds. qpcr measuring the expression of mir-193b-3p (n=3 per timepoint, paired t-test was used to determine statistical significance) Chapter conclusion The mir profiling of the epidermis of DFUs detected 82 regulated mirs in comparison with FS. Of these, I validated has-mir-31-5p, mir-135b-5, mir-199a-3p and mir-214 in full thickness biopsies, and found a high correlation of mir expression between epidermis and full thickness biopsies. I then tested the expression of these mirs in a human ex-vivo acute wound healing model, and surprisingly found that all 4 mirs were regulated in the same direction as in DFUs. This indicates that, similarly to the transcriptome profiling, there is an AW mir signature within the DFU mir expression profiles. In order to identify mirs uniquely regulated in DFUs I carried out nanostring mir profiling of the ex-vivo acute wounds and compared these profiles to those of DFUs. Interestingly, only 9 mirs were regulated in the same direction between DFUs and AWs, whereas 3 mirs were oppositely regulated: mir-193b-3p, mir-590-5p, and previously identified, mir-15b-5p. In vitro keratinocyte scratch wound assays revealed that mir-15b-5p promotes

91 77 keratinocyte migration whereas mir-193b-3p inhibits it. Interestingly, co-transfection of mir-193b-3p together with mir-15b-5p or another pro-migratory mir-31-5p, resulted in inhibition of cell migration indicating that mir-193b-3p has a dominant inhibitory effect in cell migration. Furthermore, mir-193b-3p was found to inhibit formation of stress fibers in keratinocytes, which are essential for proper directional cell migration. This finding points out that mir-193b-3p could potentially target some members of the Rho family of GTPases or its regulatory pathway members. Further IPA analysis revealed several potential target genes involved in cell migration. However, further investigation is required to elucidate the mechanism by which mir-193b-3p can inhibit the formation of stress fibers and thus impair cell migration in patients. Finally, using the ex-vivo wound infection model I discovered that mir-193b-3p is induced by S. aureus infection, in a similar fashion as mir-15b-5p. The activation of mir-193b-3p by S. aureus may offer an explanation as to why in spite of the infection-induced promigratory mir-15b-5p, S. aureus infection inhibits epithelialization and wound closure. Taken together, these data suggests that mir-193b-3p plays a key role in the inhibition of epithelialization in DFUs, and its induction is, at least in part, caused by S. aureus infection. It remains to be determined whether once mir-193b-3p is induced, resolution of infection could restore the normal level or if its induction is enough to lock the wound in a chronic wound status. Overall, these findings identify mir-193b-3p and/or its targets as potential novel therapeutic targets in the treatments of DFUs.

92 CHAPTER 6. CONCLUSIONS AND FUTURE DIRECTIONS 6.1. Summary and conclusions DFUs are a complex disease with severe consequences such as lower limb amputations, which result in a 5-year mortality rate higher than some types of cancers. Unfortunately, this condition is often overlooked and development of efficacious treatments has been slow. Currently, there are only 3 therapies approved by the FDA for safety and the last efficacious therapy came out more than 10 years ago. All of these therapies are not only expensive and require multiple treatments, but also have an efficacy lower than 50%, thus hard-to-heal diabetic foot ulcers still pose a serious threat for the diabetic population. The development of these ulcers is multifactorial and the molecular causes of this disease are still largely unknown. In recent years, Dr. Tomic-Canic s lab and others have shown gene and mir expression changes occurring in venous ulcers, another common type of chronic wounds, however to the best of my knowledge, up to this date no study has addressed this in DFUs. Based on this evidence, I proposed that gene and mir transcriptional profiling of DFUs could offer new insights on the molecular pathogenesis of these ulcers and open up new possibilities for future therapeutic targets. I first compared the mir and transcriptional profiles of non-neuropathic diabetic foot skin (DFS) with non-diabetic foot skin (NFS) in order to determine whether diabetes per se could cause transcriptional changes that may be responsible or predispose the skin to impaired healing. Surprisingly, I found minor differences in both mir and transcriptional profiles between them. In addition, no phenotypic differences were found between DFS and NFS, including histological assessment, number of blood vessels, number of lymphocytic infiltrates and number of proliferating epidermal cells. This suggested that 78

93 79 diabetes per se, might not be sufficient to alter skin enough cause inhibition of healing and other indirect factors associated with severe diabetes such as neuropathy or insufficient circulation to the lower limbs are more important. Thus, controlling diabetes could play a pivotal role in the prevention of this disease. Next, I carried out transcriptional profiling of DFUs. I generated a list of differentially expressed genes in DFUs and AW (from publically available data) by comparing their transcriptional profiles to all foot skin (FS, including DFS and NFS) or unwounded skin respectively. I then compared these lists to identify genes de-regulated in DFUs which were not part of an AW response. Most differentially expressed genes in DFUs were downregulated and did not overlap with transcripts regulated in the AW profiles. Given the large amount of regulated genes in DFUs and AWs, I took a functional approach instead of comparing individual genes. I used IPA to carry out functional enrichment and pathway analyses and compare DFUs and AWs. As expected, many AW healing processes were found to be enriched in both DFUs and AWs, however in DFUs they were less significantly enriched and less activated based on predicted activation values (z-scores). Among these, inflammatory and immune responses were particularly interesting. Although it is widely accepted that DFUs show excessive inflammation, this would not be the case according to the data presented here. Although some pro-inflammatory molecules and cytokines such as IL1A, IL6 and IL8 were up-regulated in DFUs, many other crucial ones such as CCL2 and CCL5, which are induced in AWs, are not. In addition, regulators of inflammation such as ATF2, FGF2 and IKBKB were suppressed in DFUs. The last one, IKBKB, is a key positive regulator of the NF-κB pathway which may further cause an abnormal and partially dampened inflammatory response.

94 80 Unexpectedly, DNA repair response was also reduced in DFUs but not in AWs. Several key genes involved in DNA damage repair, such as MSH2, WEE1, RAD50, KIT and TP53 were selectively down-regulated in DFUs, and subsequently there was increased DNA damage in DFUs. These results open up new possibilities for potential therapeutic targets, and I further speculate that it may also explain why some chronic wounds give rise to malignancies (197) as increased damage and impaired DNA repair can result in mutations and genomic instability. Up-stream regulator analysis of all differentially expressed genes in DFUs identified mir- 15b-5p (and its family) to be up-regulated in DFUs but not in AWs. Furthermore, it was predicted to target many genes from the DFU specific regulatory network. These targets include regulators of inflammatory response and also DNA repair mechanisms such as IKBKB, PIK3R1, WEE1, IGF1, MSH2, FGF2 and RAD50. mir-15b-5p was confirmed to be up-regulated in DFUs and slightly suppressed in ex-vivo acute wound healing by qpcr. Moreover, mir-15b-5p transfection in the keratinocyte cell line HaCaT caused downregulation of IKBKB, PIK3R1 and WEE1 suggesting that mir-15b-5p can regulate multiple pathways and cellular functions by targeting key regulatory genes. IKBKB and WEE1 UTRs were later confirmed to be targets of mir-15b-5p by luciferase reporter assays. I further investigated the cause of mir-15b-5p induction in DFUs, and discovered that S. aureus, which commonly colonize DFUs, can increase mir-15b-5p and indeed downregulate IKBKB and WEE1 in an ex-vivo acute wound healing model resulting in inhibition of healing. This means that the presence of this pathogen can alter the

95 81 inflammatory and immune responses, and also down-regulate DNA-repair mechanisms by up-regulating mir-15b-5p. In order to identify other potential mirs that could contribute to inhibition of wound healing, I carried out mir profiles of DFUs as well as ex-vivo human AW model. In addition to mir-15b-5p, I found mir-193b-5p and mir-590-5p were also up-regulated in DFUs but down-regulated in AWs. I focused on mir-193b-3p because it had been previously found to be a tumor suppressor often down-regulated in squamous cell carcinomas (190), and to inhibit keratinocyte invasion and proliferation. I confirmed this results using an in-vitro scratch wound assay in which transfection of mir-193b-3p significantly reduced keratinocyte migration. Furthermore, not only did mir-193b-3p inhibit migration by itself, but it also had a dominant inhibitory effect over other promigratory mirs such as mir-31-5p or mir-15b-5p. Altogether these data suggest that inhibition of healing in DFUs is regulated by at least the combined effects both mir-193b- 3p and mir-15b-5p, which can impair keratinocyte migration and affect inflammation and DNA repair, respectively. Lastly, I also showed that S. aureus increases the expression of mir-193b-3p, and this may explain why even though mir-15b-5p can increase keratinocyte migration, infected wounds still fail to re-epithelialize. To the best of my knowledge this is the first comprehensive analysis that has aimed to understand the overall molecular changes leading to inhibition of healing and the role of mirs (and their target genes) in regulating key cellular processes altered in DFUs Future directions In this work I presented novel insights to the pathophysiology of DFUs in which mirs seem to be playing a determining role in regulating expression of key genes that control

96 82 inflammatory response, DNA repair and cell migration. I have presented evidence for the altered state of these three processes in DFUs, however, several mechanistic details remain to be elucidated and more importantly, whether the expression of these mirs or their target genes could be manipulated to reverse the chronic phenotype. These questions pose significant challenges given the lack of a strong working model to recapitulate the disease in the lab. Most studies these days utilize murine or porcine models, and even though they can provide useful knowledge for some aspects of wound healing, it translatability to the human condition is not ideal. Given the limitations of these models, another strategy one can use to test some aspects of wound healing, in particular epithelialization is the human ex-vivo model I have used in this work. However, in spite of being a human model, it lacks many components of the wound healing process such as most immune cells as well as the lack of endothelial cells or blood perfusion. Also, the availability of skin as well as the possibilities of manipulation are very limited. One way to circumvent some of these issues, is to use organotypic co-cultures in which a three-dimensional skin equivalent is reconstituted from its primordial constituents, collagen, human fibroblasts and human keratinocytes. While this is a very artificial system, its availability and manipulability pose important advantages over the ex-vivo model. It is possible to make virtually unlimited amounts of it, and the cells can be genetically manipulated before the co-culture. Using this system, one could use lentiviruses to introduce an inducible construct carrying a particular mir, in this case, either mir-15b-5p or mir-193b-3p, generate a functional skin equivalent, wound it, and then induce the expression of these mirs to identify whether they are sufficient to inhibit epithelialization. Like these, many other possibilities exist. In an ideal situation, some of the findings made in the present work could be validated using

97 83 such a system but also could be used to establish a human delayed healing model to test and identify new drugs or therapeutic agents that could reverse these effects. I have started establishing such system in the lab, in which I have replaced human primary keratinocytes by the keratinocyte cell line HaCaT. These organotypic cultures can be wounded and they are able to recapitulate the re-epithelialization process to close the wounds within 7 days, similarly to what happens in the human ex-vivo model. The next steps to take is to create stable HaCaT lines which utilize a drug-dependent inducible system to express mir-193b- 3p and mir-15b-5p, so the skin can be reconstituted under normal conditions and these mirs could be over-expressed after wounding similarly to what happens in DFUs. Another important aspect of this work that is worth pursuing, is the use of topical delivery system to locally manipulate the mir expression levels by using mir mimics or antagomirs. The previously mentioned model could also be used to evaluate the effects of such delivery systems in a more human-like condition. For example, we could test whether the use of a topical delivery of a mir-193b-3p antagomir promotes migration and restores epithelialization capabilities or, because these mimics and antagomirs can be used in combinations, which combination of mimics and antagomirs could be used to restore healing. Hopefully this model can be used to further advance this research both to complement findings from animal models in a more human environment but also to find new potential therapeutic targets to restore the healing capacity of chronic wounds.

98 APPENDIX Figure A. 1. Enlarged version of figure 4.4. Network analysis of the genes de-regulated uniquely in DFUs (left) or AWs (right). The networks were built using IPA focusing on genes with a known regulatory functions. Enrichment analysis of these DFUand AW-specific networks showed highly significant either inactivation or activation of important functions related to wound healing in DFUs or AWs respectively (middle); green = suppression; red = induction. 84