Effects of Diabetes and Hoxa3 Upon Macrophage Function

EFFECTS OF DIABETES AND HOXA3 UPON MACROPHAGE FUNCTION

A thesis submitted to The University of Manchester for the degree of

Doctor of Philosophy Developmental Biology

in the Faculty Life Sciences

2015

MATTHEW BURGESS

FACULTY OF LIFE SCIENCES

List of contents

List of contents ...... 2 List of figures ...... 7 List of tables ...... 9 Declaration ...... 12 Copyright statement ...... 12 Acknowledgement ...... 13 The author ...... 14 1 Introduction ...... 15 1.1 Cutaneous wound healing ...... 15 1.1.1 Inflammatory phase ...... 17 1.1.2 Inflammation and the chronic wound ...... 19 1.1.3 Proliferation phase ...... 19 1.1.4 The proliferation phase and chronic wounds ...... 20 1.1.5 Neovascularisation ...... 21 1.1.6 Neovascularisation and chronic wounds ...... 23 1.1.7 Remodelling phase ...... 25 1.2 Macrophages ...... 25 1.2.1 Origins of macrophages ...... 25 1.2.2 Maturation and activation ...... 26 1.2.3 Myeloid cells and neovascularisation ...... 28 1.2.4 Macrophages and diabetes ...... 29 1.3 Endothelial progenitor cells ...... 30 1.3.1 Origins of endothelial progenitor cells...... 30 1.3.2 Isolation of endothelial progenitor cells ...... 31 1.3.3 Roles of endothelial progenitor cells in neovascuarisation ...... 35 1.4 Transcriptional basis of lineage plasticity ...... 37 1.4.1 Reprogramming in haematopoiesis ...... 38 1.4.2 The epigenetic landscape – erythroid/monocyte fate...... 40 1.5 Hypothesis and Experimental Aims ...... 41 1.5.1 Investigation of the phenotypic differences between non-diabetic and diabetic macrophages ...... 41 1) Differentiation of macrophages in models of diabetes ...... 41 2) Activation potential of diabetic macrophages ...... 42 3) Interaction of diabetic macrophages with neovascularisation ...... 42

1.5.2 Identification of transcription factors with monocytic to endothelial reprogramming potential...... 43 1) Identification of transcription factors to be tested for endothelial reprogramming potential ...... 43 2) Development of an assay to screen transcription factors for monocytic to endothelial reprogramming ...... 43 3) Assess the effects of the validated transcription factors upon THP-1 cell phenotype in the transdifferentiation assay ...... 44 1.5.3 Investigation of the effects of Hoxa3 transcriptional activity upon macrophages 44 1) Effects of Hoxa3 upon macrophage development ...... 44 2) Effects of Hoxa3 upon macrophage activation ...... 45 3) Effects of Hoxa3 upon macrophage interactions with neovascularisation ...... 45 2 Materials and methods ...... 46 2.1 Cell culture ...... 46 2.1.1 Cell lines ...... 46 2.1.2 Cell Culture ...... 46 RAW 264.7 cells...... 46 bEnd.5 ...... 47 L929 cells ...... 47 THP-1 cells ...... 47 HUVECs ...... 48 2.1.3 Primary cell lines ...... 48 Murine primary bone marrow cells ...... 48 Macrophage activation ...... 49 2.1.4 Cryostorage of cells ...... 50 2.1.5 Nucleofection ...... 50 2.1.6 Conditioned medium culture ...... 54 Calcium phosphate transfection ...... 54 Conditioned medium collection ...... 55 Treatment of cells with SP.Hoxa3.mCherry conditioned medium ...... 55 Pleiotrophin and macrophage colony stimulating factor supplemented medium...... 56 2.1.7 Neovascularisation assays ...... 56 2.2 PCR ...... 58 2.2.1 RNA extraction ...... 58 2.2.2 DNase treatment ...... 58 2.2.3 cDNA generation ...... 59

2.2.4 Quantitative PCRs ...... 59 TaqMan real time PCRs ...... 59 SYBR real-time PCRs ...... 59 Relative expression analysis ...... 60 2.2.5 Generation of pCRII-TOPO pleiotrophin ...... 64 2.2.6 Sub-cloning of pcDNA3.1/myc-His pleiotrophin ...... 65 2.2.7 Colony PCR ...... 66 2.3 Western blotting ...... 66 2.3.1 Reagents ...... 66 2.3.2 Whole cell protein lysate extraction ...... 67 2.3.3 Cytosolic and nuclear fraction protein lysate extractions ...... 67 2.3.4 Protein quantification ...... 68 2.3.5 SDS-PAGE protein separation gels ...... 68 2.3.6 Membrane transfer ...... 68 2.3.7 Western blotting ...... 69 2.3.8 Membrane stripping ...... 69 2.4 Microscopy ...... 69 2.4.1 Immunostaining of RAW cells ...... 69 2.4.2 Light and fluorescence microscopy ...... 70 2.4.3 Confocal microscopy ...... 70 2.5 Image analysis ...... 71 2.5.1 General image preparation ...... 71 2.5.2 GFP+ macrophage morphology ...... 71 2.5.3 BCIP/NBT anti-CD31 stained neovascularisation assays ...... 71 2.6 Animals ...... 73 2.7 Statistical Analysis ...... 74 3 Diabetes dysregulates macrophage activation ...... 76 3.1 Diabetes and macrophage maturation ...... 76 3.1.1 Effects of glucose concentration on macrophage gene expression in RAW mouse macrophages ...... 77 3.1.2 Macrophage marker expression in non-diabetic and diabetic derived mouse bone marrow macrophages ...... 79 3.1.2 Macrophage marker expression in streptozotocin induced type-1 diabetic rat bone marrow macrophages ...... 82 3.2 Activation ...... 83 3.2.1 Diabetic derived mouse bone marrow macrophages expression of activation markers 84

3.3 Neovascularisation ...... 89 3.3.1 Neovascularisation assays with activated macrophages cultured from diabetic derived bone marrow cells ...... 89 3.3.2 Effects of neovascularisation assay culture upon macrophage phenotype ...... 94 3.3.3 Early monocytic cells and neovascularisation ...... 99 3.4 Discussion ...... 101 4 Myeloid to endothelial transdifferentiation to promote wound healing ...... 108 4.1 Identification of novel genes that may induce myeloid to endothelial transdifferentiation ...... 109 4.1.1 Expression of putative pro-neovascularisation transcription factors in myeloid and endothelial cells ...... 112 4.1.2 Development of cell culture assay for myeloid to endothelial reprogramming115 4.1.3 Testing Pleiotrophin Nucleofection for endothelial reprogramming ...... 119 4.1.4 Testing pleiotrophin protein treatment for endothelial reprogramming ...... 121 4.2 Hoxa3 and protein transduction ...... 123 4.2.1 Hoxa3 expression in monocytes and endothelial cells ...... 123 4.2.2 Hoxa3 protein transduction in monocytes/macrophages ...... 124 4.3.2 Testing Hoxa3 protein transduction for endothelial reprogramming ...... 127 4.3 Discussion ...... 128 5 Hoxa3 protein transduction alters the macrophage phenotype in non-diabetic and diabetic macrophages ...... 136 5.1 Hoxa3 treatment of bone marrow derived macrophages ...... 136 5.1.1 Effects of SP.Hoxa3.mCherry conditioned medium treatment upon differentiating mouse macrophages ...... 137 5.1.2 Effects of SP.Hoxa3.mCherry conditioned medium treatment upon differentiating rat macrophages ...... 141 5.1.3 Cx3cr1 expression analysis for further insights into SP.Hoxa3.mCherry protein transduction and macrophage maturation ...... 145 5.2 Activation potential in bone marrow derived macrophages treated with Hoxa3 during differentiation ...... 147 5.2.1 Activation of non-diabetic mouse macrophages treated with Hoxa3 ...... 147 5.2.2 Activation of type 2 diabetic mouse macrophages treated with Hoxa3 ...... 152 5.3 Hoxa3 treated macrophages and Neovascularisation ...... 157 5.3.1 Interaction of SP.Hoxa3.mCherry treated bone marrow macrophages with neovascularisation assays ...... 157 5.3.2 Effects of neovascularisation assay culture upon macrophage phenotype ..... 163 5.3.3 Endothelial gene expression in SP.Hoxa3.mCherry treated macrophages ...... 165 5.4 Discussion ...... 167

6 General Discussions ...... 175 6.1 Diabetes alters macrophage function ...... 175 6.2 Diabetic macrophages impair angiogenesis in vitro ...... 177 6.3 Transdifferentiation as a potential diabetic wound therapy ...... 178 6.4 Treatment of macrophages with Hoxa3 may rescue their maturation phenotype.. 180 6.5 Treatment with Hoxa3 has differential effects on the pro-angiogenic potential of non- diabetic and diabetic macrophages ...... 181 6.6 The diabetic macrophage phenotype in the wound is dependent on both macrophage intrinsic and extrinsic changes ...... 183 6.7 The use of cell culture systems as a model of in vivo ...... 185 6.8 The implications of tissue resident macrophages ...... 187 6.9 Review of experimental aims and future investigations ...... 188 6.9.1 Differentiation of macrophages in models of diabetes ...... 188 6.9.2 Activation potential of diabetic macrophages ...... 189 6.9.3 Interaction of diabetic macrophages with neovascularisation ...... 189 6.9.4 Identification of transcription factors to be tested for endothelial reprogramming potential...... 190 6.9.5 Development of an assay to screen transcription factors for monocytic to endothelial reprogramming ...... 190 6.9.6 Assess the effects of the validated transcription factors upon THP-1 cell phenotype in the transdifferentiation assay ...... 190 6.9.7 Effects of Hoxa3 upon macrophage development ...... 191 6.9.8 Effects of Hoxa3 upon macrophage activation ...... 191 6.9.9 Effects of Hoxa3 upon macrophage interactions with neovascularization ...... 192 6.9 Summary ...... 193 7 References ...... 196 8 Appendices ...... 224 8.1 Vectors ...... 224 8.1.1 pCRII-TOPO pleiotrophin ...... 224 8.1.2 pcDNA3.1/myc-His pleiotrophin ...... 226 8.1.3 pSecTag2 mCherry ...... 228 8.1.4 pSecTag2 Hoxa3.mCherry ...... 231

Word count 44955

List of figures

Figure 1.1 Overview of the phases of wound healing in healthy mouse ...... 16 Figure 1.2 Accumulation of inflammatory cells during cutaneous wound healing ...... 18 Figure 1.3 Cellular processes of neovascularisation ...... 23 Figure 1.4 Origins of endothelial progenitor cells...... 32 Figure 1.5 A culture based derivation of endothelial progenitor cells ...... 34 Figure 1.6 Cross antagonistic switches in erythroid/monocytic lineage selection ...... 39 Figure 2.1 Optimisation of Nucleofection cell density ...... 52 Figure 2.2 Optimisation of Nucleofection culture medium ...... 53 Table 2.2 TaqMan primers ...... 61 Figure 2.3 Representative SYBR primer validation for rat Hsp90 quantitative real time PCR 64 Figure 2.4 Processing of angiogenesis assay macrophage images for morphology analysis72 Figure 3.1 Growth of RAW mouse macrophages in low and high glucose culture medium 78 Figure 3.2 In vitro differentiation of macrophages from bone marrow derived cells ...... 80 Figure 3.3 In vitro macrophage maturation from non-diabetic and type 2 diabetic mouse bone marrow cells ...... 81 Figure 3.4 In vitro macrophage maturation from non-diabetic and type 1 diabetic rat bone marrow cells 83 Figure 3-5 Activation markers in polarised non-diabetic mouse macrophages ...... 85 Figure 3-6 Activation markers in polarised diabetic mouse macrophages ...... 86 Figure 3-7 Differential expression of activation markers between non-diabetic and diabetic mouse macrophages ...... 87 Figure 3.8 Vessel formation in diabetic and non-diabetic macrophage angiogenesis assay co-culture 90 Figure 3.9 Vessel formation in diabetic and non-diabetic macrophage angiogenesis assay co-culture 93 Figure 3.10 Validation of activated macrophages used in neovascularisation assays ...... 95 Figure 3.11 Non-diabetic and diabetic activated macrophage morphology over neovascularisation assay co-culture ...... 96 Figure 3.12 Endothelial markers in models of diabetic myeloid lineage cells ...... 100 Figure 4.1 Expression of putative pro-neovascularisation transcription factors in human cell cultures 113 Figure 4.2 Expression of putative pro-neovascularisation transcription factors in murine cell cultures 114 Figure 4.3 Nucleofection of THP-1 monocytes with pleiotrophin ...... 117 Figure 4.4 Markers for monocytic to endothelial transdifferentiation ...... 118

Figure 4.5 THP-1 monocytes Nucleofected with Pleiotrophin transdifferentiation assay 120 Figure 4.6 THP-1 monocytes cultured with recombinant human pleiotrophin transdifferentiation assay ...... 122 Figure 4.7 Expression profile of Hoxa3 in diabetic macrophages ...... 125 Figure 4.8 Treatment of RAW cells with SP.Hoxa3.mCherry protein transduction ...... 126 Figure 4.9 RAW cells grown with SP.Hoxa3.mCherry conditioned medium ...... 128 Figure 5.1: Macrophage maturation marker expression in non-diabetic mouse macrophages with SP.Hoxa3.mCherry conditioned medium ...... 138 Figure 5.2 Macrophage maturation marker expression in type 2 diabetic mouse macrophages in SP.Hoxa3.mCherry conditioned medium ...... 141 Figure 5.3 Macrophage maturation marker expression in non-diabetic rat macrophages in SP.Hoxa3.mCherry conditioned medium ...... 142 Figure 5.4 Macrophage maturation marker expression in type 1 diabetic rat macrophages in SP.Hoxa3.mCherry conditioned medium ...... 145 Figure 5.5: Cx3cr1 expression in mouse macrophages in SP.Hoxa3.mCherry conditioned medium 146 Figure 5-6 Activation markers in non-diabetic mouse macrophages in SP.mCherry conditioned medium then polarised ...... 149 Figure 5-7 Activation markers in non-diabetic mouse macrophages in SP.Hoxa3.mCherry conditioned medium then polarised ...... 150 Figure 5-8 Effect of SP.Hoxa3.mCherry on activation markers in non-diabetic mouse macrophages 151 Figure 5-9 Activation markers in type 2 diabetic mouse macrophages in SP.mCherry conditioned medium then polarised ...... 153 Figure 5-10 Activation markers in type 2 diabetic mouse macrophages in SP.Hoxa3.mCherry conditioned medium then polarised ...... 154 Figure 5-11 Effect of SP.Hoxa3.mCherry on activation markers in type 2 diabetic mouse macrophages 155 Figure 5.12: Vessel formation in SP.mCherry and SP.Hoxa3.mCherry treated macrophage neovascularisation assay co-culture ...... 159 Figure 5.13 Vessel formation in SP.mCherry and SP.Hoxa3.mCherry treated macrophage neovascularisation assay co-culture ...... 161 Figure 5.14 Vessel formation in SP.mCherry and SP.Hoxa3.mCherry treated macrophage neovascularisation assay untreated well comparisons ...... 162 Figure 5.15 SP.Hoxa3.mCherry or SP.mCherry treated macrophage morphology over neovascularisation assay co-culture ...... 164 Figure 5.16 Expression of endothelial markers in murine macrophages treated with SP.Hoxa3.mCherry conditioned medium ...... 165 Figure 6.1 Summary of results ...... 194

List of tables

Table 2.1 Antibodies ...... 49 Table 2.3 SYBR PCR primer pairs...... 63 Table 4.1 Neovascularisation transcription factor cluster ...... 110 Table 4.2 Functional summary of putative pro-neovascularisation transcription factor ..... 110

List of abbreviations

AP Alkaline phosphatase PMSF 1% Phenylmethanesulfonyl fluoride APS ammonium persulfate PVDF Polyvinylidene fluoride CEC circulating endothelial cells qRT-PCR quantitative real time CMP common myeloid progenitors polymerase chain reaction DTT dithiothreitol SDS Sodium dodecyl sulphate EDTA Ethylenediaminetetraacetic acid TBS Tris buffered saline ESC embryonic stem cells TEMED N,N,N′,N′- FBS fetal bovine serum Tetramethylethylenediam- ine GMP granulocyte/macrophage progenitors WBR Western blocking reagent

HRP horseradish peroxidase

HSC haematopoietic stem cell

HUVEC Human Umbilical Vein Endothelial Cells

IFNγ Interferon gamma

LC Langerhans cell

LSB Laemmli sample buffer

LTA lipoteichoic acid

M-CSF macrophage colony stimulating factor

MEP megakaryocyte/erythroid progenitor

MNC mononuclear cell

MSC mesenchymal stromal/stem cells

OEC outgrowth endothelial cells

PBS phosphate buffered saline

PcGs Polycomb group protein

PFA paraformaldehyde

PMA Phorbol 12-myristate 13- acetate

Abstract

The University of Manchester Matthew Burgess 27/09/2015 PhD Developmental Biology Effects of Diabetes and Hoxa3 upon macrophage function Chronic non-healing wounds commonly present in patients with diabetes. These wounds are characterised by elevated numbers of immature leukocytes and M1 macrophages and reduced numbers of endothelial cells and M2 macrophages, impairing wound healing resolution. Topical treatment of murine diabetic wounds with a Hoxa3 gene expression vector redresses the balance of inflammatory and pro-healing cells within the lesion, reducing excessive inflammation and rescuing the wound healing phenotype. In this thesis I present experiments to further understanding of how diabetes alters the macrophage phenotype and how this may cause the decreased endothelial cell and M2 macrophage numbers in the diabetic wound. In vitro culture was used to characterize the intrinsic changes of diabetic macrophages isolated from the environmental effects of the diabetic wound milieu. These same systems were used to develop a cell culture system for the promotion of monocytic to endothelial transdifferentiation. Finally the in vitro macrophage culture system was used to assess the effects of Hoxa3 treatment upon diabetic macrophages and how Hoxa3 transcriptional activity in macrophages may contribute to the restoration of wound healing. In vitro cultured diabetic macrophages were observed to raise an increased response to classical and alternative activation signals that may contribute to the excessive inflammatory state of diabetic cutaneous wounds. Treatment of these macrophages for four days with a Hoxa3 conditioned medium protein transduction system upregulated the expression of the plasminogen activator urokinase receptor gene Plaur and enhanced the expression of macrophage maturation markers. These macrophages also exhibit an enhanced response to classical activation stimuli, a reduced alternative activation response. In an in vitro neovascularisation assay Hoxa3 treated macrophages inhibit vessel growth. These effects of Hoxa3 treatment of diabetic macrophages are unexpected based on the rescue of the inflammatory phenotype with Hoxa3 treatment of diabetic wounds. Non-diabetic macrophages were also treated for four days with a Hoxa3 conditioned medium and exhibited upregulation of macrophage maturation markers. These macrophages showed no difference in activation state polarisation compared to macrophages grown in a control conditioned medium but did upregulate activation markers in unstimulated cells. This may be indicative of a priming for response to low levels of activation stimuli. The Hoxa3 treated non-diabetic cells also promoted the formation of vessel networks in a neovascularisation co-culture assay, possibly through the promotion of angiogenesis. These results suggest that diabetes directly effects the maturation and inflammatory phenotype of macrophages and that Hoxa3 treatment rescues the impaired maturation phenotype and may stimulate macrophage populations to a pro-angiogenic state.

Declaration

The bioinformatics comparison between early and late endothelial progenitor cells described in section 4.1 was submitted by Ian O’Neill in support of an application for a Master of Research degree at the University of Manchester. No other portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or institute of learning. Copyright statement

i. The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the “Copyright”) and s/he has given The University of Manchester certain rights to use such Copyright, including for administrative purposes. ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as amended) and regulations issued under it or, where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made. iii. The ownership of certain Copyright, patents, designs, trade marks and other intellectual property (the “Intellectual Property”) and any reproductions of copyright works in the thesis, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions. iv. Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=487), in any relevant Thesis restriction declarations deposited in the University Library, The University Library’s regulations (see http://www.manchester.ac.uk/library/aboutus/regulations) and in The University’s policy on Presentation of Theses.

Acknowledgement

I would like to thank Dr Charlotte Allen of the University of Manchester for the gift of the bEND.5 cells for this research. The streptozotocin induced type-1 rat work was performed in collaboration with Dr Natalie Gardiner of the University of Manchester. Dr Sam Griffiths-Jones and Ian O’Neill for providing the endothelial progenitor cell bioinformatics comparison.

The support of the University of Manchester BSF staff, and Mike Jackson of the Flow Cytometry core facility has been invaluable during this research.

The help and support of all members of the Healing Foundation and developmental biology unit past and present should be acknowledged for assistance in the establishment of numerous experimental protocols, and making the smith building a pleasant place to be a scientist.

Past members of the Mace lab, Dr Tanja Torbica and Athina Papaemmanouil, and current members Dr Kate Wicks, Hadeel Al Sadoun, Salma Alrdahe and Marzieh Kamjoo have all assisted and offered support throughout this thesis.

Thanks to Dr’s Mathew Hardman and Kimberly Mace for their guidance and support throughout. Kimberley especially has always been incredibly supportive and her infectious enthusiasm for science is a constant inspiration to push on and achieve.

Finally thanks must go to my wife Dr Julia Draper for her constant love and support through my research and to both out families.

I’m currently in a strange hallucinogenic fugue state of sleep deprivation from the last month of finishing this thesis yet still can’t think of a job I’d enjoy more than this. Thanks again to Kim for giving me the chance to return to research.

Props to the rodents, in memory of Vic and Bob.

The author

Matthew graduated from Oxford University in 2006 with a 2.1 MBioch in Molecular and Cellular Biochemistry. During the undergraduate course he spent 17 weeks in the lab of Dr Marella de Bruijin and the Weatherall Institute of Molecular Medicine contributing to their investigations into novel enhancer regulators for RUNX1 (Nottingham et al., 2007). After graduating Matthew spent two years of dPhil course at the University of Oxford in the laboratory of Professor Kay Davies investigating the functional properties of the intermediate filament Syncoilin (Clarke et al., 2010, Kemp et al., 2009, McCullagh et al., 2008). Leaving this lab he joined the Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences and the groups of Professor Andrew Carr and associate Professor Philippa Hulley initially as a research assistant before joining the team responsible for the establishment of the central biobank at the centre (Chaudhury et al., 2011). Having acquired an interest in regenerative medicine during these studies Matthew applied to join Dr Kimberly Mace to study for his PhD. The last four years have been spent exploring the functions of the diabetic macrophage and potential mechanisms to rescue the diabetic phenotype as presented in this thesis.

1 Introduction

The successful repair of a lesion in mammalian organs requires the orchestration of multiple factors including wound resident and recruited cells, the extracellular environment within the lesion and the release of signalling molecules throughout the wound and beyond (Werner and Grose, 2003). A wide array of tissue pathologies are characterised by the dysregulation of this process including diabetic non-healing wounds, psoriasis and metastatic tumour growth (Mahdavian Delavary et al., 2011). An understanding of the cellular mechanisms underlying wound healing will also confer understanding of the pathological imbalances and how they may be rectified (Hart, 2002b, Wicks et al., 2014). 1.1 Cutaneous wound healing

Cutaneous wound healing is an orchestrated process between a diverse range of cells including platelets, macrophages, leukocytes, fibroblasts, endothelial cells and keratinocytes, and a cocktail of signalling proteins and enzymes (Shaw and Martin, 2009b). Traditionally this process has been divided into three or more phases based on the major processes occurring: inflammation, proliferation and maturation/remodeling (Baum and Arpey, 2005). This outline provides a useful structure for describing the progression of wound healing but it is important to remember that it is a gross simplification of a highly complex series of events. Each phase overlaps with the next and the time-span for each phase will vary with multiple factors such as the health of the subject, severity of the wound and genetic susceptibilities (Figure 1.1).

*Injury Prolifera ve Inﬂammatory Remodelling

0 min Day 2 4 6 7 Several weeks Many

I R C E H G d c

a F

ﬂ months

o n

Figure 1.1 Overview of the phases of wound healing in healthy mouse Progression of acute wound healing in the mouse. Exact timing are variable from many factors including health and wound size. Haemostasis is rapidly induced through blood clotting and vasoconstriction of the local vasculature. The clot is a key scaffold for scab formation. Inflammation. Neutrophils accumulate at the wound site, clearing cellular debris and foreign matter which in turn stimulates pro-inflammatory cytokine release. Cytokines drive the recruitment of monocytes to the wound site and their differentiation to activated macrophages. Macrophages become the predominant source of debris phagocytosis and release growth factors to stimulate progression to the proliferative phase. Adaptive immune response cells arrive at the wound to handle any remaining infectious agents. Proliferation. Extracellular matrix is converted to granulation tissue by fibroblasts. Contraction of the wound edge and re- epithelialisation of the epidermis by keratinocytes migrating across the granulation tissue from surrounding healthy tissue. Perfusion of the wound site re-established through the sprouting of new vessels from the surviving capillary bed and the condensation of bone-marrow derived endothelial precursors to form new vessels at the wound site. The remaining wound resident macrophages switch to a pro-healing phenotype, secreting factors to promote these processes. Remodelling. Once re-epithelialisation has closed the epidermal surface, remodelling of the underlying tissue begins. The granulation tissue contracts and the collagen network gradually modified to a tensile and elastic state similar to that of unwounded skin.

1.1.1 Inflammatory phase

The key aim of the inflammatory phase is to sterilise the wound site and create a barrier to isolate it from the external environment. The external barrier consists of a clot formed by the aggregation of platelets and secreted fibrin, whilst vasoconstriction stops the flow of further blood to and from the wound site. Once formed, the fibrin and platelets within the clot provide the first signals to activate the innate immune response, including chemokine (C-C motif) ligand 5 (CCL5), thrombin, transforming growth factor (TGF)-β, platelet derived growth factor (PDGF) and vascular endothelial growth factor (VEGF) (Su et al., 2009). These chemo-attractants, and others released by the injured tissue and any infectious agents attract the first inflammatory cells, such as neutrophils, to the wound (Maraganore, 1993).

Skin resident immune cells including Langerhans cells, mast cells and γδ T cells, and neutrophils leaked from vascular damage are typically the first immune cells at the wound (Noli and Miolo, 2001, Jameson et al., 2004, Cumberbatch et al., 2000). These cells along with platelets secrete factors to produce the inflammatory environment, including the complement cascade (Bahou and Gnatenko, 2004). Secretion of histamine reverses the initial vasoconstriction and converts the vessels to a leaky state to aid further inflammatory cell infiltration.

Neutrophils arrive at the wound site through the circulation within hours post injury (Figure 1.2). Changes in the surface adhesion proteins on the luminal endothelial cells bind the neutrophils, causing them to roll along the vessel walls. Integrins expressed at the wound site tightly bind the neutrophils, leading to their migration out of the vessels to start the process of removing foreign particles and bacteria (Hart, 2002a). This also stimulates the production of further pro-inflammatory cytokines including interleukin (IL)-1α, IL-1β, IL-6 and tumour necrosis factor (TNF)-α (Werner and Grose, 2003). Further circulating monocytes migrate from the vessels along these new cytokine gradients towards the wound, where they differentiate along the pro-inflammatory M1 axis (Daley et al., 2010).

T cells

Macrophages

Neutrophils

Mast cells

Haemostasis Inflammatory Proliferative Remodelling

Figure 1.2 Accumulation of inflammatory cells during cutaneous wound healing Throughout wound healing leukocyte cells play a role in its successful resolution. Tissue resident mast cells degranulate to contribute to the initialisation of the inflammatory response. In combination with platelet derived cytokines these signals drive the recruitment of neutrophils with numbers peaking early in the inflammatory phase. At the same time monocytes arrive from circulation and differentiate to macrophages, reaching maximum density late in inflammation. Late in inflammation T-cells begin to appear at the wound site aiding the clearing of infection and potentially aiding wound remodelling. Adapted from Koh et al., 2011.

By the end of the inflammatory phase, macrophages are the most abundant cell type at the wound site. The role of clearance of cellular debris and remaining foreign material switches to these cells, and any pathogens in the wound will be presented to incoming T-cells to trigger the adaptive immune response. Macrophages that remain after this phase are thought to convert to pro-healing M2 phenotypes (Khallou-Laschet et al., 2010), that promote collagen production, angiogenesis and re-epithelialisation, and thus progression to the proliferative phase.

1.1.2 Inflammation and the chronic wound

Pro-inflammatory macrophages are important for the preparation of the wound site for subsequent regenerative phases of repair, but do not appear to have a direct role in the promotion of regeneration itself. Ablation of the macrophages during the inflammatory phase leads to impaired vascularisation and re-epithelialization, but also minimised scar formation (Lucas et al., 2010).

Conversely, an excessive inflammatory response and associated elevation in macrophage numbers is observed in non-healing chronic wounds (Loots et al., 1998). The elevated number of macrophages drives a cycle of inflammation that inhibits the resolution of inflammation (Eming et al., 2002). This phenotype is demonstrated by the Leptin receptor mutant mouse, which consistently develops type II diabetes and displays severely impaired healing characterised by chronic inflammation (Wetzler et al., 2000). Macrophages within the diabetic wound display increased sensitivity to the inflammatory signals released into the wound and elevated inflammasome activity in response to these signals (Mirza et al., 2014). In hypertrophic wounds levels of pro- inflammatory cytokines are elevated, including TGF-β and PDGF, suggesting a hyperactive inflammatory response lead by pro-inflammatory macrophages (van der Veer et al., 2009). Inhibition of these growth factors has been observed to rescue hypertrophic wounds (van der Veer et al., 2009).

1.1.3 Proliferation phase

The proliferation phase is characterised by a switch to active repair of the wound site with granulation tissue filling the lesion, replacement of damaged vasculature, and closure of the wound surface by re-epithelialisation. Similarly the cells present switch from mainly pro-inflammatory phenotypes to a pro-healing phenotype.

The most striking cellular change is the switch from a predominantly pro-inflammatory M1 macrophage population to a pro-healing M2 macrophage population (Gordon, 2003). A significant proportion of the M2 population originates from pro-inflammatory M1 macrophages switching their activation state (Sica and Mantovani, 2012). This process may be driven by the phagocytosis of apoptotic cells within the wound inducing a phenotypic change from M1 to M2 or the recruitment of new M2 macrophages to the

wound site. The M2 macrophages suppress the previous inflammatory and T helper-1 responses, whilst promoting angiogenesis, remodelling andfibrosis (Mahdavian Delavary et al., 2011, Knipper et al., 2015).

The granulation tissue is a collagen rich matrix, produced predominantly by skin resident fibroblasts and fresh myofibroblasts differentiated from mesenchymal stromal/stem cells (MSCs) (Ross et al., 1970). This matrix provides both the environment for further remodelling later in healing and substrate for the migration of further cells to contract and close the wound. The myofibroblasts drive contraction of the wound edge, whilst fibroblasts and keratinocytes migrate across the granulation tissue to complete closure through re-epithelialisation (Martinez-Ferrer et al., 2010). A wedge of cells progresses across the surface via contact guidance, with migrating keratinocytes and the leading edge followed by proliferating keratinocytes forming the new epidermis. The temporary matrix of the granulation tissue is essential for mediating this migration when the basement membrane has been breached in the lesion (Geer and Andreadis, 2003).

1.1.4 The proliferation phase and chronic wounds

Chronic wounds are characterised by excessive inflammation but there is also a significant reduction in neovascularisation and a delay in re-epithelialisation. Like the excessive inflammatory response this is thought to be due to a loss of balance in the cell phenotypes and cytokines in the wound environment. Ablation of macrophages during this phase, when they are predominantly pro-healing, causes a similar delayed healing phenotype with decreased granulation tissue, endothelial cell apoptosis and a failure in wound closure (Lucas et al., 2010). Impaired clearance of dead cells by diabetic M1 macrophages inhibits their switch to the pro-healing M2 phenotype associated with transition to the proliferation phase (Khanna et al., 2010). Excessive fibrosis can also delay wound healing. Blocking the action of macrophage secreted PDGF reduces fibrosis and accelerates wound healing (Mori et al., 2008). A lack of neovascularisation is commonly observed in diabetic wounds, and may be attributed to a defect in macrophage behaviour and EPC mobilisation (Liu and Velazquez, 2008).

1.1.5 Neovascularisation

Regeneration of the vasculature is required to facilitate the perfusion of the new wound tissue. In adult wound healing the two predominant methods of neovascularisation are angiogenesis and vasculogenesis (Bauer et al., 2005). A third process, arteriogenesis, converts vasculature to a specialised artery morphology but is not usually relevant to cutaneous wounds (Buschmann et al., 2003).

Angiogenesis occurs when endothelial cells in the existing blood vessel lumen sprout outwards to form new vessel cords (Figure 1.3, A). Firstly the existing endothelial tube is destabilised with the weakening of cell-cell contacts and degradation of basement membrane, this is driven in wound healing by macrophage and platelet produced VEGF, PDGF and TGF-β. The fibrin matrix of the granulation tissue also provide pro-angiogenic signals, as well as providing a scaffold for endothelial cell migration (Velazquez et al., 2002). Matrix metalloproteinases (MMPs) digest the extracellular matrix (ECM) proteins in the basement membrane and in the granulation tissue as the cells migrate into the wound site (Burbridge et al., 2002).

The activating stimuli drive endothelial cells to become migratory but only a few cells end up leading an angiogenic sprout. Which cells become these sprouting ‘tip cells’ is determined by VEGF signalling and Notch-Delta cell sorting (Herbert and Stainier, 2011). VEGFR2 signalling drives an endothelial cell to begin sprouting and become a tip cell, whilst also up-regulating Dll4 and thus increasing Notch signalling in neighbouring cells. This increased Notch signal reduces VEGFR signalling and so blocks the tip fate in these cells. The repressed cells become stalk cells that follow the tip cell as it migrates away from the parent vessel and maintain its connection to the daughter vessel. The stalk cells mature and undergo lumenogenesis to form the basis of a new vessel (Iruela-Arispe and Davis, 2009).

The new sprout will continue to grow along the pro-angiogenic cytokines until it contacts other endothelial cells. It will then undergo anastomosis where the two tubes fuse to form a continuous lumen through which blood can flow and feed the wound site. Like most stages of wound healing macrophages have been implicated in assisting this process (Fantin et al., 2010{Chambers, 2013 #1622, Chambers et al., 2013). The

treatment of in vitro and in vivo angiogenic assays with M2 activated macrophages promotes angiogenesis whereas M1 macrophages inhibit (Jetten et al., 2014b). Macrophages can also have differential effects between their direct interactions with endothelial cells and the release of cytokines into the environment. Counterintuitively conditioned medium from the same M1 cells promotes angiogenesis, secreting VEGF-A to stimulate the outgrowth of angiogenic sprouts (Jetten et al., 2014b, Gu et al., 2013). In vivo the secretion of multiple chemokines by M2 macrophages potently promotes angiogenesis (Owen and Mohamadzadeh, 2013).

Vasculogenesis is the de novo formation of new vessel cords from endothelial progenitors. These cords of cells then mature to form tubular vessels (Figure 1.3, B). Originally observed in the formation of the first foetal vasculature, this form of vascular regeneration also occurs in hypoxic tissues (Asahara et al., 1999). A haemangioblast, or haemangioblast like cell, that resides within the bone marrow is thought to be the source of endothelial progenitors that contribute vasculogenesis (Tepper et al., 2005). The differentiation of haemangioblasts into endothelial progenitor cells (EPCs) will be discussed in full in a later section on EPCs.

The mobilisation of these immature EPCs into circulation is thought to be induced by elevated levels of circulating VEGF, granulocyte monocyte colony-stimulating factor (GM-CSF), granulocyte colony stimulating factor (G-CSF), placental growth factor, erythropoietin, stromal cell-derived factor-1, and estrogens released from the wound site (Aicher et al., 2005). The activation of stem cells within the bone marrow by these cytokines may induce the secretion of MMPs that releases c-Kit substrate from the bone marrow ECM. Signalling through c-Kit expressed by EPCs is then thought to trigger their release into circulation (Heissig et al., 2003). The mature EPCs in circulation enter the wound site where they have been observed to coalesce into cords of endothelial cells, which are then thought to undergo a similar process of final maturation to tubular vessels as the angiogenic sprouts. Not all EPCs will contribute directly to the new vessels, others have been seen to remain as individual cells in the wound site and are thought to act as a further source of pro-angiogenic signals (Awad et al., 2006).

Tip cell Stalk cell EPCs

B: Vasculogenesis A: Angiogenesis

Figure 1.3 Cellular processes of neovascularisation The generation of new vasculature in the adult can occur by two main processes, angiogenesis and vasculogenesis. A) Angiogenesis. The extension of the existing vessel network via the sprouting of new vessels. Pro-angiogenic signals reach the existing vessels, inducing endothelial cells to exit quiescence. Cell to cell contacts are weakened and the basement membrane degraded. A small number of endothelial cells will switch to a ‘tip cell’ phenotype and migrate towards the pro-angiogenic factors. Signals from the tip cell block further tip cell differentiation forcing a ‘stalk cell’ phenotype upon the following endothelial cells, which form the new vascular lumen. B) Vasculogenesis. The denovo formation of vessels at sites of damage. Pro-angiogenic signals reach the bone marrow, inducing the mobilisation of endothelial progenitor cells (EPCs) into circulation. EPCs leave circulation through the dilated vessel walls surrounding the wound site and coalesce in the granulation tissue to form new vessels and release further pro- angiogenic cytokines.

1.1.6 Neovascularisation and chronic wounds

Chronic diabetic wounds exhibit a marked impairment in neovascularisation, eventually leading to the formation of ischemia. The absence of neovascularisation in diabetic wounds is due to more than the lack of inflammation resolution. In other systems of induced neovascularisation lacking the chronic inflammation of diabetic wounds there is still a decreased expression of many angiogenic factors including Ang-1, FLT-1, Hif-1α, Tie-2 and VEGF correlating with the loss of vessel repair (Schurmann et al., 2014). Treatment with one or more of these factors can partially rescue neovascularisation in diabetic lesions (Balaji et al., 2015).

The vascular cells that contribute to neovascularisation also have impaired function. Diabetic EPCs are defective and do not repair ischemic vascular damage like non-diabetic counterparts (Caballero et al., 2007). These cells have impaired migration, adhesion, proliferation, differentiation and ability to integrate into existing vasculature (Urbich and Dimmeler, 2004, Fadini et al., 2006b). There are also fewer of these cells present in the circulation in diabetic patients and animal models pre-lesion (Awad et al., 2006, Fadini et al., 2006a). This functional deficit in diabetic endothelial cells can even initiate the formation of diabetic venous ulcers, where the veins are unable to withstand the hydrostatic pressure and transudate. This excess fluid in the extravascular space causes a fibrin sleeve to form around the capillaries, starving the surrounding tissue of oxygen and nutrients thus starting ulceration (Bauer et al., 2005). Furthermore, these faulty vessels can then actively inhibit wound repair by reducing the release of cytokines and even sequester pro-healing cytokines from the sites of regeneration (Falanga, 2004).

The chronic wound environment is also inhibitory to vessel growth. The excess of pro- inflammatory cytokines and significantly reduced pro-angiogenic cytokines blocks angiogenesis (Duckworth et al., 2004). Pro-inflammatory mediators including C-reactive protein and TNFα are in part responsible for the reduced EPC numbers and survival (Verma et al., 2004, Seeger et al., 2005). The addition of pro-angiogenic cytokines to non-healing wounds has had partial success but suggests a multi-factor disease etiology. PDGF treatment has been observed to rescue some chronic wounds at early stages of intervention when the damage to the granulation tissue and remaining vasculature is minimal (Mulder, 2001, Falanga, 2004). Treatments with VEGF-A expressing plasmids has also had moderate success to enhance angiogenesis and wound healing but only induces the formation of young non-functional capillaries whose further development is still inhibited by the anti-angiogenic environment (Falanga, 2004).

Overall the insufficient and deficient vasculature in the chronic diabetic wound makes a significant contribution to maintenance of the non-healing phenotype and is another key focus when considering targets for wound healing resolution.

1.1.7 Remodelling phase

With the epidermal barrier reconstituted by the end of the proliferative phase the skin has regained one of its key functions. However, the wound site still consists of a collagen rich and highly cellular granulation tissue that lacks the tensile and elastic properties of normal skin. Over the timespan of remodelling the collagen network will be re- structured into organised elastic fibrils, excess capillaries are truncated, and most of the endothelial cells, macrophages and fibroblasts removed by migration or apoptosis (Gurtner et al., 2008). Chronic wounds can be characterised as caught at the interphase between the inflammatory and proliferative phases. A chronic wound will only enter the remodelling phase upon successful treatment to reduce the excessive inflammation and induce tissue regeneration, including neovascularisation. 1.2 Macrophages

Macrophages are key regulators of tissue homeostasis with numerous specialised roles including phagocytosis, endocytosis, secretion, microbial killing, chemotaxis, adhesion and trophic functions (Mosser and Edwards, 2008). The majority of adult macrophages originate from the haematopoietic stem/progenitor cells (HSCs) of the bone marrow niche, although a minority population of long term tissue resident macrophages are also established during embryogenesis (Martinez and Gordon, 2014).

1.2.1 Origins of macrophages

In the steady state of the host the HSCs maintain a reservoir of circulating peripheral blood mononuclear cells (PBMCs). These cells originate from a common myeloid progenitor (CMP) differentiated from HSCs in the bone marrow. The CMPs give rise to monoblasts, pro-monocytes and finally monocytes that are released from the bone marrow into the circulation. These cells will extravasate and infiltrate tissue at a low level to replenish tissue-specific macrophage populations, or infiltrate en mass upon inflammation stimuli (Gordon and Taylor, 2005). In the circulation it has been proposed that the monocytes further mature in the absence of tissue recruitment signals (Sunderkotter et al., 2004). Furthermore, these various stages of circulatory maturation may contribute differently macrophage populations with more mature monocytes

specific to the replenishment of tissue macrophages and the less mature monocytes only becoming recruited as part of inflammation (Geissmann et al., 2003).

The release of monocytes into the circulation, and the initial recruitment of inflammatory monocytes to sites of tissue damage is CCR2 dependent (Tsou et al., 2007). Myeloid cells lacking this receptor are unable to respond to sites of injury (Willenborg et al., 2012, Serbina and Pamer, 2006). A second chemokine receptor CX3CR1 works in opposition of CCR2 in the bone marrow, restricting the release of monocytes into the circulation (Jacquelin et al., 2013). CX3CR1 is required for the crawling of monocytes along the lumen of the vessels and may also have a role to play in inflammatory recruitment through similar cell adhesion modulation (Imai et al., 1997, Auffray et al., 2007).

It has also been proposed that during embryogenesis the primitive monocytes and/or first definitive monocytes colonize tissues and specialise as tissue resident macrophages (Randolph et al., 1999, Ginhoux et al., 2010). There is not yet a consensus on how these tissue resident macrophages are maintained; exacerbated by the use of the term resident for both embryonically established tissue macrophages and bone marrow originated macrophages. A picture is starting to appear of different contributions of self- renewal and bone marrow replenishment across different organs but how this may correlate with macrophage functions in each tissue is unclear (Ginhoux et al., 2010, Schulz et al., 2012, Yona et al., 2013). The skin may be a tissue where both occur (Hoeffel et al., 2015, Willenborg et al., 2012).

1.2.2 Maturation and activation

Maturation and activation in macrophages are closely linked. Traditional “maturation” signals also perturb the activation spectrum and similarly the milieu of activation signals at sites of injury promotes monocyte to macrophage differentiation. Infiltrating monocytes and macrophages have receptors for multiple maturation signals including lineage-determining growth factors, T helper (Th) cell cytokines, B cells, and host and microbial breakdown products (Martinez and Gordon, 2014). In wound healing these early maturation signals are predominantly pro-inflammatory. Interferon gamma (IFN- γ) produced by Th-1 cells, along with natural killer cells and tissue macrophages

promotes the acquisition of a classical, inflammatory M1 phenotype (Pace et al., 1983). Tumour necrosis factor (TNF) is produced by macrophages and acts in concert with IFN- γ to also stimulate classical activation (O'Shea and Murray, 2008). Microbial products such as LPS, muramyl dipeptide and lipoteichoic acid are recognized by Toll-like receptors (TLRs) on macrophages stimulating M1 activation (Yamamoto and Takeda, 2010). TLR signaling induces the production of further inflammatory cytokines, chemokines and antigen presentation molecules. Granulocyte/macrophage colony stimulating factor (GM-CSF) is secreted by parenchymal cells and macrophages. Treatment of monocytes or macrophages promotes macrophage maturation in some tissues (alveolar macrophages) but also promotes the response to M1 stimuli with a similar subsequent cytokine production to TLR stimulation (Hansen et al., 2008, Dranoff and Mulligan, 1994). Other factors thought to contribute to promoting M1 types of activation are IL-1β and IL-6.

Classical activation is typified by macrophage microbicidal functions. M1 macrophages secrete pro-inflammatory cytokines such as those previously described, produce free radicals including nitric oxide, and engulf bacteria and cellular debris (O'Shea and Murray, 2008, Dale et al., 2008). Alternative, or M2 activation is characterised by the secretion of pro-healing cytokines and matrix-reorganisation functions (Hesse et al., 2001, Bleau et al., 1999). However, conforming to the dogma that macrophage activation is a spectrum or array of states rather than two opposing extremes, multiple subtypes of alternative activation have been characterised (Martinez et al., 2008). M2a macrophages are ‘traditional’ alternatively activated macrophages implicated in promoting wound healing. M2b macrophages are immunomodulatory and M2c macrophages contribute to tissue remodelling. Perhaps indicative of further bifurcation of macrophage populations in the future, an M2d population has also been proposed and a similar yet distinct tumour associated macrophage (TAM) that promotes tumour growth and vascularisation (Ferrante and Leibovich, 2012, Solinas et al., 2010). The long- term tissue resident macrophage is also thought to sit on the M2 side of the activation spectrum based on their gene expression (Mantovani et al., 2002).

IL-4 and IL-13 produced by Th-2 cells, eosinophils, basophils and macrophages are general promoters of M2 phenotype, stimulating the expression of key alternative

markers like CD163 and inhibiting classical associated phagocytosis (Murray et al., 2014). Immune complexes as bound by Fcγ receptors in concert with previous LPS activation triggers the M2b or type II activation state (Edwards et al., 2006, Sironi et al., 2006). These macrophages exert immunoregulatory functions and drive type II immune responses. M2c activation is stimulated by glucocorticoids from the adrenal glands, IL- 10 from most leukocytes and TGF-β from phagocytic macrophages (Ehrchen et al., 2007, Park-Min et al., 2005, Fadok et al., 1998). These macrophages may regulate autoimmune interactions and limit inflammation (Glocker et al., 2009). Macrophage colony stimulating factor (M-CSF) primarily promotes the maturation of monocytes to macrophages but also modulates the response to activation signals to favour M2 activation states (Martinez et al., 2006).

Overall it is important to remember that activation state classifications are dependent upon in vitro stimulation experiments. With the complicated mix of stimuli present at sites of macrophage recruitment clearly delineated subsets may not occur. It is likely that the regulation of macrophage activation will continue to become more complicated as factors including miRNAs, epigenetics and extracellular matrix interactions are investigated (Graff et al., 2012, Ivashkiv, 2013).

1.2.3 Myeloid cells and neovascularisation

Monocytes and macrophages of multiple activation states have been observed to regulate the formation and repair of the vasculature. The more mature circulating monocytes can respond to early signals of angiogenesis by the secretion of VEGF-A (Subimerb et al., 2010). These cells also favour differentiation to M2 macrophages that further promote angiogenesis and reduce inflammation. However, these cells also inhibited neovascularisation highlighting the need for multiple avenues of treatment (Marchetti et al., 2011). Tumour associated macrophages (TAMs) are recruited by the hypoxic signals from growing tumours (Hagemann et al., 2006). TAMs promote angiogenesis and tumour growth by secreting VEGF, PDGF and TGF-β, whilst inhibiting inflammatory responses (Hao et al., 2012). Neutrophils originate from the CMPs and initiate the inflammatory environment. A subset of neutrophils may be recruited to the

high VEGF concentrations at sites of angiogenesis where they further enhance vessel growth (Christoffersson et al., 2012).

Non-tumorigenic macrophages also regulate neovascularisation. Post CCR2 dependent tissue infiltration, a subpopulation of the inflammatory macrophage population expresses VEGF-A to induce angiogenic sprouting (Willenborg et al., 2012). In matrigel angiogenesis assays M2a and M2c macrophages promote the accumulation of endothelial cells (Jetten et al., 2014b). Conversely M1 macrophages inhibit tube formation. The secreted factors from macrophages are also pro-angiogenic with conditioned medium from non-activated macrophages, M1, M2a and M2c macrophages all promoting tube formation. The non-activated macrophages express low levels of Fgf1, Ccl2, Pgf, and Thbs1. M1 macrophages express Vegfa, Mif and Thbs1. M2a macrophages express Fgf2, Fgf1, Ccl2, and high levels of Pgf. M2c macrophages express Thbs1 and high levels of Pgf (Jetten et al., 2014b). Macrophages modify the extracellular matrix for vessel formation in an MMP-12 and TIMP-1 dependent manner (Anghelina et al., 2006, Oh et al., 1999). Macrophages also prepare the sites of angiogenic sprouting, lead the growth of these sprouts through the modification of the ECM and chaperone the fusion of these tips to other vessels (Fantin et al., 2010, Bourghardt Peebo et al., 2011). These cells are phenotypically similar to tumour associated macrophages but have also been reported to secrete VEGF in an M1 like manner (Gu et al., 2013).

Similar to other healing processes it appears that whilst an excess of one cell type such as M1 macrophages is detrimental to neovascularisation, no one cell type is solely detrimental to vascular regeneration. A coordinated action of multiple macrophage subtypes is required for success of neovascularisation including cells that classically contribute to the inflammatory state.

1.2.4 Macrophages and diabetes

The macrophage phenotype is altered in diabetes beyond that described in chronic wound pathologies (1.1.2). Inflammatory macrophages accumulate in the adipose tissue and release cytokines that may contribute to type 2 insulin resistance (Lumeng et al., 2007a, Lumeng et al., 2007b). This increased inflammatory activation may be due to the increased turnover of adipose cell debris in obesity. Adipose cell breakdown releases

chemokines including CCL2 that recruit further macrophages increasing the propensity for chronic inflammation (Bastard et al., 2006). It has also been proposed that similar phenotypic changes to an inflammatory state in tissue macrophages contributes to cardiovascular disease in type 2 diabetes. An increased expression of pro-coagulant factors by inflammatory macrophages could contribute to the increased atherosclerotic and cardiovascular risk (Bastard et al., 2006). Macrophages are also observed to accumulate at sites of lipid deposition within the thickening areas of blood vessels in a PPARγ dependent manner. These cells exhibit an inflammatory phenotype increasing lesion size (Fernandez, 2008).

The trend towards inflammatory macrophages at many sites of diabetic pathologies suggests a global low level chronic inflammation defect is established even before the inflammatory stimuli of cutaneous lesion formation. 1.3 Endothelial progenitor cells

There is a large body of evidence for a low frequency heterogeneous population of circulatory progenitor cells that contribute to both the angiogenic endothelium and the de-novo production of neo-vasculature in regenerating ischemic tissues (Tepper et al., 2005). The definitive characterisation of this population has remained elusive due to their heterogeneous nature and the absence of an absolute antigenic marker (Bertolini et al., 2006).

1.3.1 Origins of endothelial progenitor cells

Endothelial lineage cells in the peripheral blood can originate from either the bone marrow as EPCs or the vessel endothelium as circulating endothelial cells (Figure 1.4). Based on functional isolation protocols the bone marrow derived EPC populations can be broadly divided into two sub-sets of early and late outgrowth, named after their time of appearance in isolation cultures (Hur et al., 2004). The circulating endothelial cells (CECs) originate from mature endothelial cells that shear off the luminal surface of the blood vessels. Bone marrow transplant experiments suggest these CECs comprise the majority of the circulating endothelial population in healthy individuals with only 5% of the endothelial marker positive cells originating from the donor bone marrow, which is

equivalent to only 0.002% of all circulating mononuclear cells(Peichev et al., 2000, Lin et al., 2000). However, the rarer BM-derived cells show greater angiogenic potential and a more progenitor-like phenotype than CECs (Hur et al., 2004). Vascular damage can induce the mobilisation of these BM-derived progenitors, the antigenic profile of these cells suggesting that they are not CECs released from the vessel wall by the trauma (Gill et al., 2001).

The bone marrow origin of EPCs has been well characterised using the transplant of bone marrow from GFP positive donor animals into non-fluorescent hosts. GFP positive cells with an endothelial phenotype can be observed in circulation and integrating into the existing vasculature at very low levels (Shi et al., 1998, Asahara et al., 1999). There is less known about the bone marrow resident cells from which EPCs originate. Bone marrow transplantation of a specific subset of cells expressing the surface markers c-kit and Sca-1, and negative for the lineage markers characterising mature blood cells (B220, Gr-1, Mac-1, CD4, CD8), so closely related to pluripotent haemopoietic stem cells (Spangrude et al., 1988), was able to reconstitute both the EPC and haematopoietic potential (Bailey et al., 2004). This suggested the existence of an adult, haemangioblast- like cell that can produce daughter cells for both endothelial and haematopoietic lineages. Daughter cells in these transplants integrated into both the portal vein endothelium (CD31+/vWF+) and the circulating haematopoietic cell population (CD45+), and persisted at these sites for many months.

1.3.2 Isolation of endothelial progenitor cells

Endothelial progenitor cells were first isolated from blood as CD34+ mononuclear cells (MNCs) that grew adherent colonies when cultured in vitro (Asahara et al., 1997). This isolation has since been refined to purify two separate sub-populations. These are defined as immature early EPCs (eEPCs) and the more mature late EPCs; also referred to as outgrowth endothelial cells (OECs) (Hur et al., 2004). The traditional method of differentially isolating these two populations is still in vitro culture, but there has also been research into the surface antigen profiles of these two populations that may facilitate isolation by cell sorting.

Figure 1.4 Origins of endothelial progenitor cells A) Endothelial progenitor cells differentiate from a haemangioblast or haemangioblast-like cell in the adult bone marrow. The haemangioblast divides asymmetrically to produce either haemopoietic progenitor cells or angioblasts. The haemopoietic progenitor cell will give rise to all myeloid and lymphoid cells but can also produce monocytic early EPCs. The angioblast leaves the bone marrow and matures in the circulation to late EPCs. There is some evidence that some early EPCs may also mature into late EPCs when in circulation. Both cells can contribute to the formation of sheets of mature endothelial cells but late EPCs appear to have far greater potential for this terminal differentiation. The currently understood antigen profiles for these cells is shown. It can be seen than late EPCs share an antigen profile similar to that of mature endothelial cells, whereas early EPCs have a more progenitor-like state similar to that of monocytes. B) Mature endothelial cells shear off the luminal wall at constant low rate in the healthy vasculature. In circulation these cells de-differentiate to a more progenitor-like state call circulating endothelial cells. Circulating endothelial cells contribute to the slow turnover of vascular endothelial cells in healthy vessels and act in greater numbers to drive the repair of vascular damage.

The culture method of isolation is an adaptation of the original Asahara method (Figure 1.5). Mononuclear cells are separated from blood by density gradient centrifugation and cultured on a collagen or fibronectin substrate in an endothelial medium. Early EPCs appear within the first week as weakly adherent cells with an endothelial cell-like spindle shape. Serial culture over four to eight weeks selects against the early EPCs whose numbers crash, leaving strongly adherent late EPCs (Prater et al., 2007, Hur et al., 2004). The late EPCs form cobblestone sheets of cells similar to differentiated endothelial cells and are clonogenic forming colonies of endothelial cells from a single cell. CECs can also be seen in these cultures within the first week as adherent cells, but unlike EPCs lack the ability to expand in numbers.

Isolation of pure populations of EPCs, or EPC subpopulations by surface marker selection has been difficult due to the absence of an endothelial progenitor specific antigen. The endothelial lineage is positive for markers such as vascular endothelial (VE)- cadherin/CD144, CD31, VEGFR2/Flk-1 or CD146 but these will also purify mesenchymal or haematopoietic cells (Kim et al., 2005, Duda et al., 2006). The haematopoietic contamination can be removed with a negative selection against haematopoietic markers such as CD45.

Some differentially expressed surface markers have been used to identify eEPCs or OECs. As described in the original Asahara EPC paper, CD34 will enrich a sample for late EPCs but will also be contaminated with CECs, and in human samples haematopoietic cells (Pelosi et al., 2002). In human blood samples, and some mouse studies, the ‘stemness’ marker CD133 (Prom1) has been used to separate late EPCs from bone marrow resident haematopoietic precursors expressing the marker(Peichev et al., 2000, Mace et al., 2009). In mouse CD117 has also been similarly used to delineate EPCs from CECs but is again expressed in early bone marrow progenitors as well (Bertolini et al., 2006) (Figure 1.4).

MNCs Platelets & plasma MNCs

Erythrocytes & granulocytes B

early EPCs

late EPCs

Figure 1.5 A culture based derivation of endothelial progenitor cells The isolation of early and late EPCs by in vitro culture follows the same general protocol. A) Mononuclear cells are isolate from blood by a separation method such as Percoll density gradient centrifugation. B) Cells are plated on a solid culture matrix such as collagen in an endothelial cell growth medium. After one week of culture the non-adherent fraction will be rich in early EPCs. C) Serial re-plating of the adherent cells, over a period of three to five weeks will enrich for colonies of late EPCs.

The source of cells will also complicate the phenotype and surface marker expression of EPCs. Very few late EPCs can be isolated from the bone marrow, with early EPCs being the main endothelial progenitors present. When cultured in conditions for the isolation of late EPCs endothelial markers such as vWF and CD34 were expressed at a lower level in cells from bone marrow compared to peripheral blood (Amini et al., 2012). Similarly EPCs isolated from umbilical cord blood had reduced expression of endothelial markers compared to those from peripheral blood (Ingram et al., 2004).

1.3.3 Roles of endothelial progenitor cells in neovascuarisation

Endothelial progenitor cells have been observed to be potently pro-angiogenic. In GFP bone marrow transplant experiments EPCs have been observed to incorporate into the vasculature of multiple organs at a low rate, but this contribution is elevated in angiogenic conditions (Asahara et al., 1999). Both skin excision wounds and muscle ischemia significantly increased the numbers of EPCs at the site of insult and integrating into the neovasculature. Similarly elevated numbers were observed in the highly angiogenic environment of induced tumours. This appears to be an angiogenesis specific recruitment, with of the presence of EPCs at the tumour site coinciding with the switch of micrometastases to angiogenic macrometastases (Gao et al., 2008). Ablation of angiogenesis and EPCs with Id1 gene suppression significantly reduced the number of micrometastases undergoing the angiogenic switch. In the angiogenesis defective Id1 Id3 null mouse line the transplantation of wild-type bone marrow, or VEGFR2+ bone marrow cells could rescue the angiogenic process. However, this rescue may also be due to the recovery of other pro-angiogenic signals by the early progenitors that would be included in the VEGFR2+ population (Ruzinova et al., 2003).

EPCs respond to pro-angiogenic signals such as VEGF. Treatment of corneal surfaces with VEGF greatly stimulates angiogenesis with a parallel increase in the numbers of endothelial cells seen at the site of application (Shaked et al., 2005). More significantly the strength of the angiogenic response upon VEGF treatment correlated with the number of EPCs present at the site before application. Further links between EPC numbers and neovascularisation such as increased numbers of circulating EPCs in patients with vascular pathologies and a correlation between levels of CD34+VEGFR2+

cells (likely to be OECs and CECs) and coronary artery disease survival rates have also been observed (Werner et al., 2005, Parfenova et al., 2010, Gill et al., 2001). However, there is the possibility that this is not an elevation of EPCs released from the bone marrow but an increased release of CECs from the vasculature during damage. The function of EPCs is likely to be intimately linked to haematopoietic lineages. Co-culture with macrophages or megakaryocytes promoted the formation of large EPC colonies from CD34+ cells in vitro (Kwon et al., 2014). Culture of EPCs with T lymphocytes accelerated the growth of early EPCs.

The roles of eEPCs and late EPCs in neovascularisation appears to differ. Early EPCs have been observed to play a mostly indirect role, releasing further cytokines at sites of neovascularisation to drive the regenerative process (Kinnaird et al., 2004). The late EPCs are thought to be the cells observed to integrate directly into the vasculature promoting the formation of new vessels (Asahara et al., 1999). These differential roles in neovascularisation fit the monocytic nature of eEPCs and endothelial nature of late EPCs.

Application of human CD14+ or CD34+CD14- cells to diabetic mouse limb ischemia has been observed to have differential effects. The late EPC enriched CD34+CD14- population were seen to have a greater contribution to healing in this model than the monocyte/eEPCs CD14+ population (Sivan-Loukianova et al., 2003, Awad et al., 2006). Ischemic limbs injected with CD34+CD14- cells showed significantly improved healing compared to CD14+ cells. However, injections of both cells gave an intermediate level of improvement, suggesting a negative element in the CD14+ population, possibly macrophages. The numbers of cells integrating into the vasculature were lower than other reports, but it is likely that the mouse model was rejecting the human cells.

The population of CD34+ endothelial cells, OECs and CECs, is reduced in diabetes and is likely to contribute to the impaired healing phenotype (Awad et al., 2005). The treatment of mouse diabetic wounds with the Hoxa3 transcription factor rescues the impaired wound healing and angiogenesis in the diabetic mouse. Associated with this improvement there is an increase in mature CD34+CD133- endothelial progenitor cells at the wound site and CD34+CD133+ progenitors in circulation (Mace et al., 2009). Diabetes also seems to directly alter EPC function; EPCs isolated from diabetic rats

exhibited reduced differentiation, increased apoptosis and an impaired migratory phenotype. Diabetic derived EPCs also performed poorer in ischemic hind limb vascular repair compared to their non-diabetic counterparts (Kuliszewski et al., 2013).

Bone marrow derived endothelial progenitor cells play a key role in driving angiogenesis, specifically late EPCs that have the potential to drive the formation of new vessels via vasculogenesis. Endothelial progenitor cells appear to share an origin in the bone marrow with the haematopoietic lineage with both cells derived from the multipotent haemangioblast. With this shared origin cells may be amenable to their conversion between the haematopoietic and endothelial lineages. 1.4 Transcriptional basis of lineage plasticity

Work investigating cell differentiation over the last two decades has revealed that fate determination is not always the rigid linear progression that was previously proposed. It is a plastic and analogue process that can be overridden or diverted toward a different fate by the perturbation of complex sets of transcription factors that direct its progression (Graf and Enver, 2009). At any point a single progenitor cell can be at one of three states, or in transition between them: differentiation into a lineage, self- renewal, or quiescence. These different fates are controlled by networks of transcription factors promoting or repressing each state.

Perturbing the balance of this network can alter the outcome of these cell fate decisions. The transfer of nuclei between cells can rapidly reprogram the host cell such that it adopts the donor’s lineage via the new network of transcription factors (Gurdon and Melton, 2008). This reprogramming can also be achieved solely through the addition or removal of transcription factors. Transcription factors will not always drive a cell to a new fate. Somatic cell nuclear transfer into a denucleated oocyte can de-differentiate the somatic nucleus to a totipotent state. The ease with which cells are reprogrammed by the oocyte is related to the differentiation state of the donor cell. Less differentiated cells are more amenable to somatic reprogramming.

1.4.1 Reprogramming in haematopoiesis

Primitive myelopoiesis in Xenopus occurs in haematopoietic progenitor cells marked for the myeloid fate by C/EBPα expression. Overexpression of C/EBPα at this time in development converts non-haematopoietic cells into myeloid progenitors, and a knockdown of C/EBPα inhibits the differentiation of haematopoietic progenitors to myeloid cells (Chen et al., 2009d). Similarly in the mammal the haematopoietic stem cell is thought to originate from the dorsal aorta endothelium (Swiers et al., 2013, Lancrin et al., 2009, de Bruijn et al., 2002).

Overexpression of C/EBPα in most definitive haematopoietic lineages is also able to convert them to monocytes, including T cells, B cell, megakaryocyte/erythroid progenitor (MEP) and common lymphoid progenitor (CLP) cells (Fukuchi et al., 2006). Ectopic expression of GATA-1 in CLPs, B cells, common myeloid progenitors (CMPs) and granulocyte/macrophage progenitors (GMPs) induces all four cell populations to transdifferentiate to the MEP lineage (Iwasaki et al., 2003). Loss of GATA-1 expression in MEPs causes their de-differentiation to multipotent progenitor cells.

Non-committed progenitors early in the differentiation of haematopoietic lineages are plastic in their fate and can be reprogrammed by the modification of expression of only one transcription factor.

A GATA-1 PU.1 GATA-1 PU.1

GATA-1 PU.1

CMP

GATA-1 PU.1

MEP GMP B

EPO1 GATA-2

GATA-1 PU.1

Figure 1.6 Cross antagonistic switches in erythroid/monocytic lineage selection A) Selection between two fates can be modelled as a hillock topped by a basin. Balanced expression of two or more opposing transcription factors maintains a progenitor cell within this basin, in this example the common myeloid progenitor (CMP). When the expression of one transcription factor sufficiently exceeds the others a cell may escape this basin and progress downhill to the next stable transcriptional network. The CMP can differentiate to a megakaryocyte/erythroid progenitor (MEP) with GATA-1, or a granulocyte/macrophage progenitor (GMP) with PU.1. B: The base construct of a cross-antagonistic switch is two transcription factors that inhibit the expression or activity of the other, whist promoting the further activity of self through a positive feedback loop. In the case of GATA-1 and PU.1 the proteins have been to directly interact to antagonise the others action. EPO1 drives differentiation to the erythroid lineage by indirectly activating GATA-1 through phosphatidylinositol 3-kinase/Akt.

1.4.2 The epigenetic landscape – erythroid/monocyte fate

Progenitor cells are thought to exist through a balance of these multiple fate signals forming stable solutions of transcriptional activity. This has been described as analogous to a three-dimensional epigenetic hill with basins at the stable states (Figure 1.6) (Waddington, 1957). As described in the primitive myelopoiesis example, adding or removing transcription factors will disrupt the balance at a basin allowing a cell to escape downhill to the next stable state.

The differentiation of CMPs has been a key model for understanding this process (Figure 1.6) (Orkin and Zon, 2008). Common myeloid progenitors can mature into MEPs or GMPs, forming the erythroid and monocytic arms of haematopoiesis. The balance between these two fates is a cross antagonistic signalling between GATA-1 and PU.1 (SPI-1), favouring erythroid and monocyte respectively. Each transcription factor promotes the further expression of itself whist inhibiting the expression of the other factor. Knockdown of GATA-1 removes the inhibition on PU.1, allowing it to reach a threshold level of expression and specify the cell as an GMP. Conversely, inhibition of PU.1 releases GATA-1 expression and causes the cell to acquire a MEP fate (Rhodes et al., 2005). Mathematical modelling of this network of transcription factors in CMPs has supported this interpretation of fate selection (Huang et al., 2007).

The epigenetic landscape model can also be used to interpret the reprogramming of one cell type to another. Fates with fewer branches between them are closer on the hill and thus would be expected to be easier to reprogram between. This could either be by laterally moving to the other fate, or reverting to a common progenitor between the two fates before re-differentiating to the new lineage (Graf and Enver, 2009). Reprogramming has been demonstrated in the erythroid/monocyte model system, re- introduction of GATA-1 into GMPs redirects their commitment to the megakaryocyte/erythroid line (Iwasaki and Akashi, 2007). The same expression of GATA- 1 was also seen to re-program cells that split before the erythroid/monocyte lineage selection, reprogramming common lymphoid progenitors to the erythroid lineage.

Reprogramming of monocytes to endothelial cells/endothelial progenitor cells has recently been demonstrated using the secreted growth factor Pleiotrophin (Sharifi et al., 2006). Full-length human Pleiotrophin expressed in a monocytic cell line drove the reprogramming of the cells to an endothelial fate. Myeloid-endothelial plasticity is a two way street, endothelial progenitor cells have also been reprogrammed to a monocytic phenotype (Shi et al., 2014). This demonstrated that monocytes, a cell type over- represented in the chronic wound, may be converted to endothelial progenitors and endothelial cells, cells that are lost in the same chronic wounds. 1.5 Hypothesis and Experimental Aims

1.5.1 Investigation of the phenotypic differences between non- diabetic and diabetic macrophages

Diabetic pathologies such as non-healing wounds are characterised by an expanded population of inflammatory cells including monocytes and macrophages, reduced pro- healing populations including endothelial progenitor cells, and an associated failure in vascular regeneration (Wetzler et al., 2000, Mirza et al., 2014, Mace et al., 2009, Schurmann et al., 2014). Understanding the mechanisms underlying this cellular dysregulation will provide new avenues for the treatment of these conditions. This project intended to investigate the phenotypic changes that diabetes confers upon the macrophage population independent of the environmental effects of the diabetic wound.

1) Differentiation of macrophages in models of diabetes

In the early stages of wound inflammation monocytes and macrophages are predominantly less mature. As wound healing progresses the macrophage population matures. In diabetes the early inflammatory phase persists and is associated with excessive numbers of immature inflammatory cells (Mirza and Koh, 2011). I hypothesised that a diabetes induced impairment in macrophage maturation may contribute to this excessive inflammatory state and the impairment of wound healing.

To test this hypothesis macrophage cell lines were cultured in diabetic conditioned and their phenotype assessed by gene expression to identify differences in their maturation potential. Similarly macrophages were differentiated from the bone marrow of animal models of diabetes; both streptozotocin-induced type 1 diabetic rats and genetically induced type 2 diabetic mice.

2) Activation potential of diabetic macrophages

During the early phases of wound healing wound associated macrophages exhibit a mostly inflammatory, classical phenotype. As wound healing progresses to regenerative processes there is a switch in activation state to a predominantly pro healing, alternative phenotype (Khallou-Laschet et al., 2010, Gordon, 2003). The excessive inflammatory character of diabetic wounds suggests that this progression is dysregulated. I hypothesised that diabetes is changing the phenotype of the wound macrophages promoting or enhancing their response to classical activation signals whilst suppressing their response to alternative activation stimuli.

To investigate the effects of diabetes upon macrophage response to activation signals, mouse diabetic macrophages were to be treated with classical and alternative activation stimuli. Expression of markers of activation would be used to measure stimuli response.

3) Interaction of diabetic macrophages with neovascularisation

Tissue neovascularisation is regulated by direct macrophage interactions and indirect macrophage led environmental modulation (Bourghardt Peebo et al., 2011, Bian et al., 2003). The excessive inflammation in diabetic wounds is associated with impaired blood vessel regeneration and endothelial progenitor populations. I hypothesised that diabetic macrophages have altered interactions with the vasculature and environment, and have impaired pro-neovascularisation activity or inhibit these processes.

Co-culture of neovascularisation assays with macrophages was used to assess the differential effects of diabetic macrophages upon vascular growth.

Injection of non-diabetic macrophages into diabetic wounds and diabetic macrophages into non-diabetic wound would be use test for effects upon neovascularisation, as visualised by CD31 staining of endothelial cells.

1.5.2 Identification of transcription factors with monocytic to endothelial reprogramming potential

The plasticity between monocytic and endothelial precursors may provide a novel mechanism for redressing the imbalance in inflammatory and pro-healing populations in diabetic wounds (Mace et al., 2009, Schmeisser et al., 2001). Inflammatory monocytes are easily isolated from the peripheral blood and could be transdifferentiated by transcription factor treatment to endothelial progenitors (Seager Danciger et al., 2004, Chen et al., 2009a). These progenitors contribute to the generation of a pro-angiogenic wound environment and directly integrate with the regenerating vasculature (Asahara et al., 1999). I hypothesised that transcription factors upregulated as endothelial progenitors mature could be used in gene therapy treatment to promote the transdifferentiation of monocytes to an endothelial progenitor cell phenotype.

1) Identification of transcription factors to be tested for endothelial reprogramming potential

Nine neovascularisation associated transcription factors were previously identified bioinformatically in a gene expression comparison between early and late endothelial progenitor cells. To validate their upregulation as endothelial progenitors matured expression in multiple monocytic and endothelial systems would be investigated to confirm their differential expression.

2) Development of an assay to screen transcription factors for monocytic to endothelial reprogramming

THP-1 cells have been well documented as being amenable to endothelial reprogramming. The pleiotropic growth factor pleiotrophin is reported to

drive monocytic to endothelial transdifferentiation (Sharifi et al., 2006). I hypothesise that pleiotrophin would be a suitable positive control for the development of a non-lentiviral THP-1 expression system to assay the reprogramming potential of the validated transcription factors.

3) Assess the effects of the validated transcription factors upon THP- 1 cell phenotype in the transdifferentiation assay

Each validated transcription factor would be transfected into THP-1 cells and tested for endothelial reprogramming by expression of endothelial markers. Successfully reprogrammed cells would then be assessed for a functional role in angiogenesis in in vitro assays as well as testing their application to wound healing models.

1.5.3 Investigation of the effects of Hoxa3 transcriptional activity upon macrophages

The treatment of diabetic wounds with a Hoxa3 expression construct was previously shown to accelerate diabetic wound healing (Mace et al., 2005). This improvement was associated with a reduction of inflammatory bone marrow derived cells and an increase in pro-angiogenic cells of a bone marrow origin (Mace et al., 2009). Vascular repair was also rescued in the treated wounds. The effects of Hoxa3 upon endothelial and epithelial cells has been documented, but as with diabetes the direct effects of Hoxa3 upon macrophages is not known. I hypothesised that Hoxa3 treatment of macrophages would rescue any diabetes-induced changes in their function and convert them to a pro-healing phenotype that contributes to wound healing. A Hoxa3 protein transduction system would be used to test Hoxa3 transcriptional activity and function during macrophage maturation.

1) Effects of Hoxa3 upon macrophage development

To test the effects of Hoxa3 upon the differentiation of macrophages, macrophage cell lines and bone marrow macrophages from rat (type 1) and mouse (type 2) diabetic models would be treated with Hoxa3 conditioned

medium during their in vitro differentiation and gene expression analysed for changes in their maturation phenotype.

2) Effects of Hoxa3 upon macrophage activation

Mouse bone marrow derived macrophages would be stimulated with activating signals after their Hoxa3 treatment to test if Hoxa3 altered their response to classical or alternative stimuli. Cell activation was to be tested by the expression of markers of macrophage activation.

3) Effects of Hoxa3 upon macrophage interactions with neovascularisation

To test if Hoxa3 treatment altered macrophage interactions with vascular repair Hoxa3 treated cells would be applied to neovascularisation assays and the extent of vessel growth assessed. Bioinformatics analysis of whole wound gene expression profiles in diabetic wounds and macrophages treated with Hoxa3 expression plasmid and protein transduction respectively would be used to identify pathways of Hoxa3 action.

2 Materials and methods

2.1 Cell culture

2.1.1 Cell lines

RAW 264.7 cells were obtained from American Type Culture Collection (ATCC, TIB-71). L929 cells were obtained from ATCC (ATCC, CCL-1). THP-1 cells were obtained from ATCC (ATCC, TIB-202). Human Umbilical Vein Endothelial Cells (HUVECs) were obtained from ATCC (ATCC, CRL-1730). bEND.5 cells were derived from BALB/c mice primary brain endothelial cells with polyoma middle T oncogene and received as a gift from Dr

Charlotte Allen, University of Manchester (Wagner and Risau, 1994).

2.1.2 Cell Culture

All cell cultures densities and live/dead counts by Trypan Blue (Sigma Aldrich, T8154) staining were recorded at time of passage to identify any changes in cell behaviour. Fresh cultures were started if growth rates decelerated or the proportion of dead cells increased. As a general rule lines were not extended beyond the 20th passage irrespective of good performance in these checks.

RAW 264.7 cells

RAW 264.7 cells were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) (Sigma Aldrich, F9665), 100 U/mL Penicillin and 100 µg/mL Streptomycin (Pen/Strep, Sigma Aldrich, P0781). DMEM was used with two concentrations of glucose, denoted in the results as ‘low glucose’ at 1000 mg/L (Sigma Aldrich, D6046) and ‘high glucose’ at 4500 mg/L (Sigma Aldrich, D6429). Cells were seeded for serial culture at 2x105 cells/mL in 12mL of culture medium for

2 o T75cm cell culture flasks (Corning, 430720U) at 37 C, 5% (v/v) CO2 in humidified incubators. Cells were passaged every two to three days by disruption with a plastic cell scraper when the concentration in suspension would be approximately 8-10x105 cells/mL. Live cells were collected at the bottom of a Falcon tube (Corning, 430790 or 430828) by centrifugation at 400 xg for five minutes then re-suspended in fresh medium

for counting. Counts of viable cells were performed on a haemocytometer with a 1:1 mix of cell solution and Trypan blue.

For imaging experiments cells were seeded in six well plates (Corning Costar, 3516) at a lower density of 1x105 cells/mL to ensure single cells were present for imaging. bEnd.5 bEnd.5 cells were cultured in high glucose DMEM supplemented with 10% FBS, 100 U/mL Penicillin and 100 µg Streptomycin. Cells were seeded for serial culture at 2x105

2 o cells/mL in 12mL of culture medium for T75cm cell culture flasks at 37 C, 5% (v/v) CO2 in humidified incubators. Cells were passaged every two to three days. To passage cells were washed in PBS without Ca2+ and Mg2+ (Sigma Aldrich, D8537), disrupted with 1x Trypsin-EDTA, re-suspended in fresh culture medium and 8-10x105 cells/mL returned to a fresh T-75 flask.

L929 cells

L929 cells were cultured in high glucose DMEM supplemented with 10% FBS, 100 U/mL

o Penicillin and 100 µg/mL Streptomycin in T75 flasks for seven days at 37 C, 5% (v/v) CO2 in humidified incubators. To passage cells were washed in PBS without Ca2+ and Mg2+ (Sigma Aldrich, D8537), disrupted with 1x Trypsin-EDTA, diluted 1:10 in fresh culture medium and returned to a fresh T-75 flask. These cells were grown for 7-14 days until confluent for conditioned medium collection.

THP-1 cells

THP-1 cells were cultured in Iscove’s Modified Dulbecco’s Medium (IMDM, Sigma Aldrich, I6529) supplemented with 10% human serum (Sigma Aldrich, H4522), 100 U/mL Penicillin, 100 µg/mL Streptomycin, 1x none essential amino acids (NEAA, Sigma Aldrich, M7145), and 1 mM Sodium Pyruvate (Sigma Aldrich, S8636). Cells were seeded for serial culture at 2x105 cells/mL in 12 mL of culture medium for T75 cell culture flasks (Corning,

o 430720U) at 37 C, 5% (v/v) CO2 in humidified incubators. Cells suspensions were passaged every two to three days when the concentration would be approximately 8- 10x105 cells/mL.

HUVECs

HUVECs were cultured in Endothelial Basal Medium (Lonza, CC-3121) supplemented with the EBM bullet pack containing growth factors, supplements and serum (Lonza, CC3124), and 100 U/mL Penicillin and 100 µg/mL Streptomycin. T75 cell culture flasks were coated with gelatine by incubation with a Stericup Steritop (Millipore, SCVPU11RE) filtered 0.1% gelatine PBS (with Ca2+ Mg2+) solution (Sigma Aldrich, G9391; Sigma Aldrich, D8662) for 30 minutes at 37oC. The excess solution was then removed and the surface washed with PBS before cell culture use. Cells were seeded for up to three serial cultures at 8x105 cells in 12mL per flask and fed with fresh culture medium every two to three days until 90% confluent. To passage adherent cells were disrupted with 1x Trypsin-EDTA (Sigma Aldrich, T3924), re-suspended in fresh culture medium and 8x105 cells in 12mL returned to a fresh gelatine coated T-75 flask.

2.1.3 Primary cell lines

Murine primary bone marrow cells

Bone marrow growth medium was prepared from DMEM, supplemented with 10% FBS, 100 U/mL Penicillin and 100 µg/mL Streptomycin, and 10% L929 cell conditioned medium to provide M-CSF. Femur and tibia bones were dissected from freshly euthanized mice or rats, cleaned of surrounding tissue and placed into sterile PBS without Ca2+ and Mg2+. In a microbiology safety cabinet the bone tuberosities were removed to expose the bone shaft and bone marrow flushed from the cavity into bone marrow growth medium with a 27 gauge needle (BD Biosciences, 305136). Flushed bone marrow was dissociated to a single cell suspension by passing through a 19 gauge needle (BD Biosciences, 301500) a minimum of 20 times then a 70µm cell filter (BD Biosciences, 252350) to remove remaining aggregates. Counts of viable cells were performed on a haemocytometer with a 1:1 mix of cell solution and Trypan blue.

Cell suspension was adjusted to a concentration of 4.2x105 cells/mL in bone marrow growth medium and 12 mL added to 10 cm plastic culture dishes (Corning, 430167) to give a total cell count of 5x106 cells per plate. Plates were fed with 6 mL of bone marrow growth medium after four days and the medium replaced with 12 mL of fresh bone marrow growth medium six days after seeding. By day seven the cultures comprised

predominantly of macrophages. Plates were cultured in humidified incubators at 37oC,

5% (v/v) CO2.

Macrophage activation

In vitro cultured macrophages were activated to an M1 or M2 polarised state by the replacement of bone marrow growth medium with DMEM (Sigma Aldrich, D6429) containing no FBS (serum starved), 100 U/mL Penicillin and 100 µg/mL Streptomycin and activating ligands. For M1 polarisation these ligands were; 100 ng/mL murine Interferon gamma (IFNγ, Sigma Aldrich, I4777) and 100 ng/mL Escherichia coli derived Lipopolysaccharides (LPS, Sigma Aldrich, L4391). For M2 polarisation these ligands were; 50µg/mL anti IFNγ (Bio X Cell, BE0055, Table 2.1) and 20ng/mL murine Interleukin-4 (IL4, Peprotech, 214-14). Cells were grown in the required activation medium for 18-24 hours before processing for analysis. Control cells were grown in serum starved medium without any activating ligands.

Table 2.1 Antibodies

Target Host Working Clone Conjugation Supplier Product dilution code Primary antibodies Mouse Rat N/A XMG1.2 None Bio X Cell BE0055 IFNγ Human Rabbit 1:1000 Polyclonal None Abcam ab9106 Myc tag 6-Histidine Rabbit 1:1000 Polyclonal None Novus NBP1-46791 epitope tag Biologicals mCherry Rabbit 1:1000 Polyclonal None BioVision 5993-100 tag Human Mouse 1:400 Monoclonal None Cellworks V2a Kit CD31 Secondary antibodies Rabbit IgG Goat 1:50000 Polyclonal HRP Abcam ab6721 Rabbit IgG Donkey 1:500 Polyclonal eFluor 488 Life A21206 Technologies Mouse IgG Goat 1:500 Polyclonal AP Cellworks V2a Kit

Table of all antibodies used in experimental procedures.

2.1.4 Cryostorage of cells

Macrophages were processed for liquid nitrogen storage for future use where required. Cryostorage medium was made fresh from 90% FBS/10% DMSO (Sigma Aldrich, D2650), macrophages disrupted from adherent culture by cell scraper, pelleted as per cell passaging and re-suspended in cryostorage medium at 2.5x106 cells/mL. Cryostorage medium cell suspension was immediately transferred in 1mL aliquots to 1.6mL cryovials (Nunc, 377267), placed in a room temperature ‘Mr Frosty’ freezing container (Thermo Scientific, 5100-0001) loaded with isopropanol (P/7490/17, Fisher Scientific) and frozen in a -80oC freezer before transfer to liquid nitrogen storage.

To thaw cells from cryostorage vials were placed in a 37oC water bath until a frozen core is separated from the walls of the cryovial. The vial was then sterilised with ethanol and the contents transferred to a 50mL Falcon tube on ice. Over 5 minutes 6mL of cold macrophage growth medium was added to the cells with frequent gentle shaking to mix. The volume was then increased to 10mL of medium and the cells left at room temperature for 10 minutes before pelleting at 380g room temperature for 5 minutes. The supernatant was carefully removed and the cells re-suspended in fresh medium and diluted to an appropriate density for further application.

2.1.5 Nucleofection

The suppliers protocol for human monocyte Nucleofector kit (Lonza, VPA-1007) was adapted for use with THP-1 cells based on literature and personal optimisation (Schnoor et al., 2009). A gradient of cell densities was treated for expression of the pmaxGFP control vector to identify the quantity of cells generating minimal cell death and the highest number of cells expressing the transgene (Figure 2.1, A). Counts of live and dead cells at 48 and 96 hours post Nucleofection suggested an increase in the proportion of dead cells as cell density increased at 48 hours (Figure 2.1, B). Using the known numbers of input cells these percentages were used to calculate an estimate of the number of live cells remaining per treatment (Figure 2.1, C). The proportion of GFP+ cells was also counted to calculate cell densities (Figure 2.1, D). This showed a possible trend towards a smaller fraction of GFP+ cells as density increased. Finally the total number of live cells was used with the percentage of GFP positive cells to calculate a total number of GFP+

live cells (Figure 2.1, E). As such 4x105 cells per Nucleofection was used for all experiments.

Two different base culture media were also tested to try to increase the cell survival. Cells were grown in medium based on either DMEM or IMDM both before and after Nucleofection (Figure 2.2, A). No significant difference was found between the percentage of live cells of the two culture mediums (Figure 2.2, B). Similarly there was no difference in the proportion of GFP+ cells with the two mediums (Figure 2.2, C). With no significant difference between the two IMDM was selected as the basal growth medium for the THP-1 cells due to its use in other published THP-1 Nucleofection experiments.

A 2x104 10x104 25x104 50x104 100x104

B C Live cells 150 Live cells 80

100 al cells

t 40

Cells t 50

% % of 20

0 0 2 0 5 0 0 0 0 2 0 5 0 0 0 0 1 2 5 0 0 5 1 2 5 0 0 5 1 2 2 1 2 2 Cell input (x104) 48 96 Cell input (x104) D E GFP positive cells GFP positive live cells 60 1000

800 40

600

al cells

o Cells t 400 20

% % of 200

0 0 2 0 5 0 0 2 0 5 0 0 1 2 5 0 1 2 5 0 1 1 4 4 Cell input (x10 ) Cell input (x10 ) Figure 2.1 Optimisation of Nucleofection cell density THP-1 cells Nucleofected with pmaxGFP (eGFP) control vector at a range of cell densities. A) Representative images of THP-1 cells 60 hours post Nucleofection. Scale bar 100 µm. B) Proportions of live cells present at 48 and 96 hours post Nucleofection. C) Using the input cell density an estimation of the total number of live cells was calculated. D) Proportions of GFP positive cells present at 60 hours post Nucleofection. E) Using the total number of live cells an estimation of the total number of GFP positive cells was calculated. Two experimental repeats.

A DMEM IMDM

B C Live cells GFP positive cells 30 60

20 40

al cells

t t

o o

t t

10 20

% % of % of

0 0

M M M M D E D E M M M M I D I D

Base culture medium Base culture medium Figure 2.2 Optimisation of Nucleofection culture medium THP-1 cells Nucleofected with eGFP control vector whilst being grown and recovered in medium using IMDM or DMEM as a base. A) Representative images of THP-1 cells 60 hours post Nucleofection. Scale bar 100µm. B) Proportions of live cells present at 96 hours post Nucleofection. C) Proportion of GFP positive cells present at 60 hours post Nucleofection. Two experimental repeats.

The final Nucleofection protocol was as such; THP-1 cells were split into a fresh T-75 flask at 2x105 cells/mL 24 hours before Nucleofection. Before Nucleofection a 12 well

o plate was pre-warmed in a 37 C CO2 incubator with 1.5mL of recovery medium per well, with two wells for each Nucleofection sample. Recovery medium consisted IMDM (Sigma Aldrich, I6529) with 20% human serum, 100 U/mL Penicillin, 100 µg/mL Streptomycin, 1x NEAA, and 1 mM Sodium Pyruvate. The Phorbol 12-myristate 13- acetate (PMA) treatment used in the published adjustment was removed because macrophage differentiation was not desired.

For the transfection 4x105 cells were pelleted at 200 xg for 10 minutes per treatment and re-suspended in 100µL of room temperature Nucleofector solution mix. Up to 5 µg of expression plasmid was added to the cell suspension. This consisted of either 2 µg of the supplier’s pmaxGFP plasmid for control transfections or a mix of 4µg the experimental plasmid with 1 µg of pmaxGFP as a transfection control. The cell plasmid mix was transferred to the Nucleofection cuvette and processed in a Nucleofector I (Amaxa) on the program Y-01. The Nucleofected cell mix was then transferred to the

o pre-warmed recovery medium and incubated at 37 C 5%CO2 for four hours. The cells were then returned to THP-1 culture medium.

2.1.6 Conditioned medium culture

Calcium phosphate transfection

293T cells were transfected with either pSecTag2 mCherry or pSecTag2 Hoxa3.mCherry vector using calcium phosphate transfection. 24 hours before transfection 293T cells were freshly passaged into 10cm dishes at 5 to 10% confluence. With healthy 293T cells this should provide plates at 40-50% confluence for the transfection. Immediately before the transfection the culture medium was replaced with fresh 293T medium. For each plate 10 µg of the plasmid was added to 61 µL of 2 M CaCl2 and H2O to a total volume of 500 µL. This solution is gently mixed by flicking before slow drop-wise addition to 500 µL of 2x Hank’s Balanced Salt Solution (HBSS; 0.274 M NaCl, 0.5 mM Na2HPO4, 15.5 mM HEPES, pH 7.0). The solution was gently pipetted three times to mix then applied drop-wise to the 293T culture plate ensuring the full surface area of cells was exposed. Each plate was left one minute for the precipitate to settle then carefully

o returned to the 37 C 5% CO2 incubator. Ideally this was performed at the end of the day such that the cells were incubated with the plasmid for 12-16 hours overnight before the transfection medium was removed and replaced with fresh medium. Expression of the mCherry reporter was confirmed by fluorescence microscopy and the plates used to harvest SP.mCherry or SP.Hoxa3.mCherry conditioned medium. Medium from untransfected 293T cells was also collected as an additional experimental control where required.

Conditioned medium collection

Conditioned medium was collected daily from 293T cells transfected with SP.mCherry or SP.Hoxa3.mCherry for up to three days based on the appearance of the cultures and the maintenance of mCherry reporter fluorescence. Medium from the cultures was aspirated by 10mL syringe and passed through a 45 µm filter (Merck Millipore, SLHA025NB) to remove any cells in suspension. This medium was then used fresh for Hoxa3 protein transduction experiments or stored at -20oC in aliquots of up to 50mL for future use. Once thawed or collected fresh the medium was used within one week.

L929 conditioned medium was collected from L929 flasks after 7-14 days of culture and passed through a 45 µm filter to remove any cells in suspension. Medium was stored in aliquots of up to 50 mL for future use. Once thawed the medium was used within one week. Conditioned medium from L929 cells contains macrophage colony stimulating factor (M-CSF). L929 conditioned medium is used to stimulate the differentiation of haematopoietic and myeloid progenitor cells, from both mouse and rat to a macrophage phenotype (Boltz-Nitulescu et al., 1987, Wiltschke et al., 1989, Dreymueller et al., 2013).

Treatment of cells with SP.Hoxa3.mCherry conditioned medium

Sample cultures were supplemented with SP.Hoxa3.mCherry conditioned medium, the SP.mCherry conditioned medium or untreated 293T control mediums daily for all experiments. For RAW cell optimisation experiments 4mL of 1x105 cells/mL of RAW cells in normal culture medium was added per well of a six well plate. To these cultures 1mL of conditioned medium was added daily. Three and six days post seeding the culture medium was removed and replaced with 3mL fresh RAW cell culture medium and 1mL conditioned medium. Murine macrophages were grown in supplemented medium for

the last four days of their maturation from bone marrow cells. For macrophage conditioned medium treatments 5x106 cells in 12 mL of bone marrow cell medium were added to each 10 cm culture dish. Three days after seeding 4 mL of conditioned medium was added to each plate. Four days after seeding 4 mL of conditioned medium with 10% L929 conditioned medium was added to each plate. Five days after seeding 4 mL of conditioned medium was added to each plate. Six days after seeding the culture medium was removed and replaced with 8mL of bone marrow culture medium and 4 mL of conditioned medium with 10% L929 conditioned medium. Conditioned medium was not added to the activating cytokine supplemented mediums. For six well plates the volume of conditioned medium was reduced in proportion to the smaller culture volume. Cells were cultured in 3mL of bone marrow cell medium and 1 mL of conditioned medium was added on the treatment days.

Pleiotrophin and macrophage colony stimulating factor supplemented medium

THP-1 cells were cultured in THP-1 medium supplement with human recombinant pleiotrophin and macrophage colony stimulating factor (M-CSF) replicating a previously published protocol (Chen et al., 2009a). Six well plates were coated with rat tail collagen I (Fisher Scientific, A1048301) by adding 1mL per well of a 50 µg/mL solution diluted from stock in 0.02 M acetic acid and incubating at room temperature for one hour. Excess solution was then removed and the wells washed three times with PBS before use. 2x105 cells were added to each well in THP-1 culture medium and grown in a 37oC

5% CO2 incubator. One hour after plating recombinant human M-CSF (R&D Systems, 216-MC-025) to a final concentration of 10 ng/mL was added to half the experimental cultures. At 24 hours and five days post plating recombinant human pleiotrophin (R&D Systems, 252-PL-050) to a final concentration of 50 ng/mL was added to all experimental cultures. Untreated controls were grown on Collagen I plates in THP-1 medium. Eight days after the initial treatment all cultures were harvested for analysis.

2.1.7 Neovascularisation assays

The V2a Kit (Cellworks) was used to perform neovascularisation assays, providing the human fibroblasts and HUVECs that form the cellular basis of the assay, culture medium

for seeding the cells and for the neovascularisation assay, and positive and negative

o control compounds. All media were always equilibrated in a 37 C 5% CO2 incubator for at least 30 minutes. On day 1 0.2 mL of seeding medium was added to each well of the provided 24 well plate and placed in the incubator to equilibrate. Vials of HUVECs and fibroblasts were quickly thawed in a 37 oC water bath and added to 3 mL of pre- equilibrated seeding medium in 15 mL Falcon tubes. Cell density was determined by counting with a haemocytometer and adjusted to 6x104 cells/mL of HUVECs and 12x104 cells/mL of human fibroblasts. 100 µL of each cell suspension was added to the 0.2 mL of seeding medium in the wells such that each well contained 0.4 mL of seeding medium with 6x103 HUVECs and 1.2x104 fibroblasts. On day two the seeding medium was very carefully removed with a serological pipette avoiding disrupting the cell sheet and replaced with 0.4 mL of angiogenesis growth medium. To the positive control wells 0.4 mL of growth medium with 2 ng/mL of VEGF was added and to the negative control wells 0.4 mL of growth medium with 20 µM of suramin a VEGFR antagonist. The control wells were fed with fresh growth medium with VEGF or suramin every two days.

Also on day two frozen macrophages of the phenotype and treatment required for the neovascularisation assay were thawed as described in (2.1.4) and cultured for 24 hours in bone marrow growth medium to recover from cryostorage. On day three the cultured macrophages were washed with PBS and then disrupted from their culture by cell scraper and re-suspended at 5x104 cells/mL in angiogenic growth medium. Medium was aspirated carefully from the relevant experimental assay wells and 0.4 mL of the macrophage suspension added. Similarly macrophages were thawed on days four and six for addition to the experimental wells on days five and seven.

For the remaining days the medium was replaced every two days (9, 11, and 13) with fresh angiogenic growth medium as before, except for the control wells that still received the VEGF and suramin containing media. On Day 15 the plate was processed for imaging of the vessel network as described in (2.5.3). If any wells were to be left unused during the assay they were filled with 1 mL sterile PBS to avoid any differences in rate of evaporation across the assay plate. The manufacturer was unable to disclose the glucose concentration of the culture mediums provided for the assay, but could

confirm that it is below 1000 mg/L, removing the potential of diabetic-like changes occurring to the cells within the assay. 2.2 PCR

2.2.1 RNA extraction

Extraction of RNA was performed with TRIzol reagent (15596, Life Technologies) as per the manufacturer’s protocol. Cells were suspended in 1 volume of TRIzol reagent at approximately 750 µL per 107 cells, either from a disrupted cell pellet if harvested from a suspension or addition to adherent cell cultures then disruption by the blunt end of a sterile pipette tip. Cells were lysed in the TRIzol suspension by pipetting for at least 20 times. To the lysate solution was added 5 µL of GlycoBlue co-precipitant (AM9515, Life Technologies) to aid RNA pellet visualisation and 0.2 volumes of chloroform (1010219, Fisher Scientific). The solution was vigorously shaken by hand for at least 15 seconds then incubated at room temperature for three minutes to initiate phase separation. Samples were then centrifuged at 12000 xg for 15 minutes at 4 oC and the upper aqueous phase containing the RNA transferred to a fresh centrifuge tube. 0.5 volumes of 100% isopropanol was added and the tube mixed by vortex for 30 seconds then incubated at room temperature for 10 minutes. RNA was pelleted by centrifugation at 12000 xg for 10 minutes at 4oC and the supernatant removed. The pellet was washed in 1 volume of 75% ethanol and centrifuged at 7500 xg for 5 minutes at 4oC. The supernatant was discarded and the pellet air dried for 10 minutes, then re-suspended in an appropriate volume of nuclease free water (normally 45 µL) at 60oC for 15 minutes. RNA concentration was measured by Nanodrop (ND-1000, Thermo Scientific). Samples then proceeded to DNase treatment.

2.2.2 DNase treatment

Contamination of RNA samples with any remaining genomic DNA was removed with DNase I digestion. RNA samples were treated with the RNase-Free DNase set (79254, Qiagen). RNA solutions were made to a volume of 45 µL and 5 µL of the 10x RDD buffer and 1.25 µL DNaseI to give a final activity of 3.75 KU per reaction. Reactions were

incubated at 37 oC for 10 minutes then transferred to 80 oC for a further 10 minutes to denature the enzyme.

RNA concentration was checked by Nanodrop and then stored at -80 oC to await further analysis.

2.2.3 cDNA generation

First strand cDNA generation was performed by reverse transcriptase reaction using Bioscript transcriptase (Bioline, BIO-27036), 1:1:1:1 mix of dNTPs (Bioline, BIO-39036, BIO-39037, BIO-39038, BIO-39039) random hexamer primers (Bioline, BIO-38028) and oligo dT18 primers (Bioline, BIO-38029). Transcriptase negative and template negative controls were performed for all reactions to check for contamination of the sample and reagents respectively. An initial denaturing step was performed with the template and primers before the addition of the transcriptase, buffer and RNaseOUT ribonuclease Inhibitor (Life Technologies, 10777-019).

2.2.4 Quantitative PCRs

TaqMan real time PCRs

TaqMan quantitative real-time PCRs were performed using a constant amount of cDNA diluted in H2O added to 0.5 µL of TaqMan assay for the desired target and 5 µL of TaqMan Fast Universal PCR master mix (4352042, Life Technologies) in a total reaction volume of 10 µL. A complete list of assays is given (Table 2.2). All reactions were run in duplicate or triplicate in MicroAmp Fast optical 96-well plates (4346906, Life

Technologies) on a StepOne Plus Real-Time PCR system (4376600, Life Technologies). Ct values were set to an experiment consistent threshold of 0.2 and exported from the StepOne Software (Life Technologies) for further analysis.

SYBR real-time PCRs

SYBR quantitative real-time PCRs were performed using a constant amount of cDNA across an experiment diluted in H2O added to Fast SYBR green Master Mix (Life Technologies, 4385612) with 10 µM of forward and reverse primers. A complete list of assays is given (Table 2.3). All reactions were run in duplicate or triplicate on MicroAmp

Fast optical 96-well plates (Life Technologies, 4346906) on a StepOne Plus Real-Time

PCR system (4376600, Life Technologies). CT values were set to an experiment consistent threshold of 0.2 and exported from the StepOne Software (Life Technologies) for further analysis.

Relative expression analysis

Exported CT values were processed using Excel 2013 (Microsoft). Genes were compared across intended experimental comparisons in reactions with the same template amount to confirm their suitability as reference targets. Where possible two such genes were identified for each experiment and their average CT calculated to minimise any remaining variation between experimental states.

Relative expression for genes of interest was calculated using the 2-ΔΔCt method (Livak and Schmittgen, 2001). For SYBR real-time PCRs all the amplification efficiencies of each primer pair was determined by template serial dilutions to ensure the assumptions made for calculating relative expression were valid (Figure 2.3, A). All primers were checked to fit to a semi-log regression on a log2 plot of template dilution. R square values for this fit are given for all SYBR primer pairs used (Table 2.4). Melt curves were also performed for each primer pair (Figure 2.3, B). All primer pairs were check for a

o strong single melt point (Tm) near to 60 C and a small shoulder at temperatures below the melt point.

Table 2.2 TaqMan primers Target Assay ID Amplicon Figure Assay Design Transcripts Length (Base pairs) Mouse Ccl2 Mm00441242_m1 74 3.5; 3.8; 5.6- Probe spans exons 1 11 Cd14 Mm00438094_g1 69 3.1; 3.3; 4.9; Probe spans exons 1 5.1; 5.2 Cd34 Mm00519283_m1 61 4.9; 5.16 Probe spans exons 2 Cdc42 Mm01194005_g1 116 4.8 Probe spans exons 2 Cdh5 Mm00486938_m1 69 3.9; 4.9; 5.16 Probe spans exons 1 Cited2 Mm00516121_m1 72 4.2; Probe spans exons 1 Cx3cr1 Mm02620111_s1 107 5.5 Primers and probe 1 within single exon Emr1 Mm00802529_m1 92 3.1; 3.3; 4.9; Probe spans exons 1 5.1; 5.2 Foxc1 Mm01962704_s1 153 4.2; Probe within exon 1 Foxo1 Mm00490672_m1 74 4.2; Probe spans exons 1 Hey2 Mm00469280_m1 85 4.2; Probe spans exons 1 Hist2h2aa1 Mm00501974_s1 57 3.1; 3.3; 3.5; Primers and probe 1/1 /2 3.8; 4.2; 5.1; within single exon 5.2; 5.5-11; 5.16 Hoxa3 Mm01326402_m1 71 4.7, 4.9; 5.1; Probe spans exons 1 5.2; 5.6-9; Hsp90ab1 Mm00833431_g1 167 3.1; 3.3; 3.5; Probe spans exons 1 3.8; 4.2; 5.1; 5.2; 5.5-11; 5.16 Id1 Mm00775963_g1 147 4.2; Probe spans exons 1 Itgam Mm00434455_m1 69 3.1; 3.3; 4.9; Probe spans exons 2 5.1; 5.2 Meox2 Mm00801881_s1 73 4.2; Probe spans exons 1 Nr2f2 Mm00772789_m1 65 4.2; Probe spans exons 2 Plaur Mm00440911_m1 72 4.8; 5.1; 5.2 Probe spans exons 1 Prom1 Mm00477115_m1 67 4.9 Probe spans exons 8 Ptn Mm01132688_m1 61 4.3; Probe spans exons 1 Sox18 Mm00656049_g1 73 4.2; Probe spans exons 1 Tbx1 Mm00448948_m1 88 4.2; Probe spans exons 2 Tgfb1 Mm01178820_m1 59 3.5; 3.8; 5.6- Probe spans exons 1 11 Tnf Mm00443258_m1 81 3.5; 3.8; 5.6- Probe spans exons 2 11 Vwf Mm00550376_m1 63 3.9; 4.9; 5.16 Probe spans exons 1

Human 18S Hs99999901_s1 187 4.1; 4.3; 4.4- Probe spans exons 1 6 ACTB Hs01060665_g1 63 4.1; 4.3; 4.4- Probe spans exons 1 6 CD68 Hs02836816_g1 70 4.4-6 Probe spans exons 2 CEBPA Hs00269972_s1 77 4.4-6 Primers and probe 1 within single exon CITED2 Hs01897804_s1 106 4.1: Primers and probe 3 within single exon FOXC1 Hs00559473_s1 61 4.1: Primers and probe 1 within single exon FOXO1 Hs01054576_m1 90 4.1: Probe spans exons 1 HEY2 Hs00232622_m1 111 4.1: Probe spans exons 1 ID1 Hs03676575_s1 100 4.1: Primers and probe 2 within single exon MEOX2 Hs00232248_m1 71 4.1: Probe spans exons 1 NR2F2 Hs01594285_m1 124 4.1: Probe spans exons 2 PECAM1 Hs00169777_m1 65 4.4-6 Probe spans exons 1 PROM1 Hs01009250_m1 75 4.4-6 Probe spans exons 7 PTN Hs00383235_m1 76 4.3; Probe spans exons 1 RPL37A Hs01102345_m1 125 4.1; 4.3; 4.4- Probe spans exons 1 6 RUNX1 Hs00257856_s1 61 4.4-6 Primers and probe 1 within single exon SOX18 Hs00746079_s1 149 4.1; Primers and probe 1 within single exon SPI1 Hs02786711_m1 85 4.4-6 Probe spans exons 2 SPIB Hs00162150_m1 65 4.4-6 Probe spans exons 4 TBX1 Hs00271949_m1 53 4.1; Probe spans exons 3 VWF Hs01109446_m1 56 4.4-6 Probe spans exons 1

Table of all TaqMan assays used in experimental procedures. All assays manufactured by Life Technologies.

Table 2.3 SYBR PCR primer pairs

Target Forward Primer Amp Figure Assay Design R Reverse Primer length Factor (base pairs) Mouse H2a GTCGTGGCAAGCAAGGAG 182 3.5; 3.8; Amplicon within exon 0.973 GATCTCGGCCGTTAGGTACTC 5.6-11 5 Nos2 CCCTTCAATGGTTGGTACATGG 158 3.5; 3.8; Amplicon crosses 0.996 ACATTGATCTCCGTGACAGCC 5.6-11 exon boundary 5 CD86 TTGTGTGTGTTCTGGAAACGGAG 202 3.5; 3.8; Amplicon crosses 0.974 AACTTAGAGGCTGTGTTGCTGGG 5.6-11 exon boundaries Arg1 GAACACGGCAGTGGCTTTAAC 155 3.5; 3.8; Amplicon within exon 0.979 TGCTTAGCTCTGTCTGCTTTGC 5.6-11 2 Chi3l3 TCTGGGTACAAGATCCCTGAA 97 3.5; 3.8; Amplicon crosses 0.997 TTTCTCCAGTGTAGCCATCCTT 5.6-11 exon boundary 3 Mrc1 TCTTTGCCTTTCCCAGTCTCC 241 3.5; 3.8; Amplicon crosses 0.941 TGACACCCAGCGGAATTTC 5.6-11 exon boundary 9 Rat ActB CACCCGCGAGTACAACCTTC 257 3.4; 5.3-4; Amplicon crosses 0.977 GGATGCCTCTCTTGCTCTGG 4.7; 5.1-5 exon boundaries 7 CD14 TCAGAATCTACCGACCATGAAGC 150 3.4; 5.3-4 Amplicon within exon 0.996 GGCTGCGGATCTGAGAAGTT 2 CD34 GAGTCCCACAGGAGAAAGGC 182 5.16 Amplicon within exon 0.948 GTTGTCTTGCTGAATGGCCG 4 Emr1 GGCTTCTGGGGAGCTTACAA 228 3.4; 5.3-4 Amplicon crosses 0.978 ATAGCGCAAGCTGTCTGGTT exon boundaries 9 H2a CGTGCACCGTCTGCTTTACAA 192 3.4; 3.9; Amplicon within exon 0.934 AGCTCCTCATCGTTGCGAATG 4.7; 5.1-5.5 2 Hsp90 AGTTGGACAGCGGGAAAGAG 286 2.3; 3.4; Amplicon crosses 0.997 GACTCCCAGGCATACTGCTC 3.9; exon boundary 7 Hoxa3 CTGCACCCTCTACCCTCTCT 251 4.7; 5.1-5.4 Amplicon within exon 0.612 GCACACACACACGGAAAGAC 3 Itgam CATGACCACCTCCTGCTTGT 258 3.4; 5.3-4; Amplicon crosses 0.991 GCCACCGGCTTCATTCATCA 5.1-4 exon boundaries 1 PlauR CAGACCCACGTCAACCTCTC 238 5.1-4 Amplicon within exon 0.992 AATACAGCACGCCTGTCCTC 1 vWF CCATCTCACTCAGGTGTCCG 152 3.9; 5.16 Amplicon crosses 0.757 AGGCCAGAGCATTCCCAATC exon boundary 5

Table of all SYBR primer pairs used in experimental procedures. R factor for the fit of Ct response in serial template dilutions on a Log2 scale.

A Hsp90 rat SYBR primer pair B Hsp90 rat SYBR primer pair

20 y = -3.002ln(x) + 16.82 er (-R) t

C epor

t 18 r

v ti

16 a

v Deri 14 0.0625 0.125 0.25 0.5 1 2 o Dilution factor Temperature C Figure 2.3 Representative SYBR primer validation for rat Hsp90 quantitative real time PCR All SYBR primer pairs were validated for experimental use. A) Serial dilutions of template cDNA with rat Hsp90 primer pair, plotted on a log2 scale of dilution factor. B) Melt curve for a single dilution sample with the rat Hsp90 primer pair.

2.2.5 Generation of pCRII-TOPO pleiotrophin

Full length mouse pleiotrophin was cloned from whole cutaneous wound RNA pool. Template cDNA was generated using Bioscript II reverse transcriptase as described (2.2.4). Pleiotrophin open reading frame was amplified using Phusion polymerase (New England Biolabs, M0530) selected for its proofreading function. Reaction mixes were made to the manufacturer’s instructions with HF buffer, dNTPs, DMSO, amplification primers and polymerase. Amplification primers were PtnMF2 (AAAGGCAGCCAGCTAGTCAG) and PtnMR1 (ATCCAGCATCTTCTCCTGTT). Reaction mixes were run on a pre-heated thermocycler with the following program:

98 oC 30 seconds

[98 oC 10 seconds, gradient 49 oC to 68 oC 30 seconds, 72 oC 15 seconds] 35 cycles

72 oC 10 minutes, 4 oC hold.

Immediately after amplification and aliquot of the reaction was taken to check product sizes on a 1% agarose gel whilst 0.2 µL of Taq polymerase (Roche, 11146165001) was

added to the rest of the reaction and incubated at 72 oC for 15 minutes to generate A- tail overhands for TOPO cloning. Reactions were stored at 4 oC ready for the next step.

PCR products were mixed with the pCRII-TOPO vector (Thermo Fisher, K4650) as per the manufacturer’s instructions and incubated at room temperature for five minutes for TA ligation. TOP10 competent cells were thawed on ice and 2 µL of the PCR vector mix added per vial of cells. pUC19 vector and water were run as transformation controls. Reactions were incubated on ice for 30 minutes then heat shock treated at 42 oC for 30 seconds before returning to ice. 250 µL of S.O.C medium was added to each reaction and incubated on a rotary shaker at 37oC for one hour to recover. During incubation LB agar plates (Sigma Aldrich, L2897) containing 50 µg/mL Carbenicillin (Sigma Aldrich, C1613) and 40 µg/mL Xgal (Sigma Aldrich, B4252) were pre warmed at 37oC. 10-50 µL of transformed TOP 10 cells was added to each plate with a spreader and incubated overnight at 37oC for colonies growth. White colonies were picked for colony PCR screening and growth in LB broth with 50 µg/mL Carbenicillin for plasmid extraction with the QIAprep spin Miniprep Kit (Qiagen, 27104) as per the manufacturer’s instructions.

2.2.6 Sub-cloning of pcDNA3.1/myc-His pleiotrophin

The pleiotrophin open reading frame was excised from pCRII-TOPO pleiotrophin by EcoRI digest (New England Biolabs, R3101). Similarly the pcDNA3.1/myc-His A vector was linearised by EcoRI digest and treated with Calf intestinal phosphatase (New England Biolabs, M0290) to prevent self re-annealing. The digestion products were separated on a 1% agarose gel, the desired bands excised on a trans-illuminator and purified with the QIAquick Gel Extraction Kit (Qiagen, 28704) as per the manufacturer’s instructions.

The purified pleiotrophin and pcDNA3.1/myc-His digestion products were ligated with T4 DNA ligase (New England Biolabs, M0202) and incubated overnight at 16oC. TOP10 cells were transformed with ligation reaction products as described (2.2.5). Colonies were picked for colony PCR screening and the plasmid from successful clones extracted with the QIAprep spin Miniprep Kit as per the manufacturer’s instructions. Sequence integrity and reading frame alignment of the clone was verified by DNA sequencing with a 3730 DNA Analyser (Applied Biosystems), service provided by Manchester University

DNA Sequencing Facility. The fully verified clone was grown in 1 L of LB broth with 50 µg/mL Carbenicillin and plasmid purified with the EndoFree Plasmid Mega Kit (Qiagen, 12381) as per the manufacturer’s instructions. Plasmid was quantified by Nanodrop, aliquoted and stored at -20oC for future use.

The PtnMR1 primer contains a base pair change to mutate the stop codon in the pleiotrophin open reading frame to facilitate the read through to the myc and his tag sequences to generate the tagged pleiotrophin protein.

2.2.7 Colony PCR

Colony PCR were performed with Taq DNA polymerase, dNTP mix and the desired primer pair. For pCRII-TOPO pleiotrophin the cloning primers PtnMF2 and PtnMR1 were used to check for insertion. For pcDNA3.1/myc-His pleiotrophin the 5’ MCS T7 priming site primer and PtnMR1 were used to both check insertion and correct orientation. Colonies were spiked with a sterile pipette tip and dipped into a tube containing 50 µL of the PCR reaction mix. Samples were loaded onto a thermocycler and run on the following program:

98 oC 30 seconds

[98 oC 10 seconds, 60oC 30 seconds, 72 oC 15 seconds] 32 cycles

72 oC 10 minutes, 4 oC hold.

Samples were separate on a 1% agarose gel to check for the presence of bands and their size relative to a standards ladder. 2.3 Western blotting

2.3.1 Reagents

RIPA lysis buffer consisted of 1% Triton X-100 (Sigma Aldrich, T8787), 1% Sodium deoxycholate (Sigma Aldrich, D6750), 0.1% Sodium dodecyl sulphate (SDS; Sigma Aldrich, L3771) in 1x PBS supplemented with 1% Phenylmethanesulfonyl fluoride (PMSF) solution (Sigma Aldrich, P7626), 1% sodium orthovanadate solution (Sigma, S6508) and 1% protease inhibitor cocktail solution (Sigma, S8820).

Lysis buffer consisted of 0.01 M HEPES, 0.01 M KCl, 0.1 mM Ethylenediaminetetraacetic acid (EDTA; Sigma Aldrich, E6758), 0.4% NP40 (Sigma Aldrich, NP40S) in H2O supplemented with 1mM DTT (Sigma Aldrich, 43815), 1% protease inhibitor cocktail solution and 1 µM lactacystin (Sigma Aldrich, L6785).

Extraction buffer consisted of 0.02 M HEPES, 0.4 M NaCl, 1mM EDTA in H2O supplemented with 1mM DTT, 1% protease inhibitor cocktail solution and 1 µM lactacystin.

5x Laemmli sample buffer (LSB) consisted of 50% glycerol (Sigma Aldrich, G5516), 0.06 M Tris-Hcl, pH6.8, 2% SDS, 1% Bromophenol blue (Sigma Aldrich, B0126), 5% β- mercaptoethanol (Sigma Aldrich, M3148) in H2O.

5x SDS-PAGE running buffer consisted of 0.124 M Tris Base (Sigma Aldrich, T1503), 0.96

M glycine, 0.017 M SDS in H2O.

10% SDS-PAGE gels were freshly made with 10% separating gel (4 mL H2O, 5 mL Protogel [30%; National diagnostics, EC-890], 5.6 mL 1 M Tris-HCl pH8.8, 150 µL 10% SDS, 100 µL 10% ammonium persulfate [APS; Sigma Aldrich, A3678], 24 µL N,N,N′,N′- Tetramethylethylenediamine [TEMED; Sigma Aldrich, T9281]) in Bio-Rad casting plates, topped with 4.2% stacking gel (3.61 mL H2O, 700 µL Protogel 650 µL 1 M Tris-HCl pH6.8, 38.8 µL 10% SDS, 50 µL 10% APS, 12 µL TEMED) with well comb.

2.3.2 Whole cell protein lysate extraction

Adherent cells or pelleted cells were washed twice with PBS then suspended in 50-200 µL cold RIPA lysis buffer. Adherent cells were released with a plastic cell scraper. Cells were disrupted by pipetting multiple times then incubated in RIPA lysis buffer at 4oC for four minutes. Suspensions were centrifuged at 14000 xg 15 minutes 4oC to pellet cellular debris and the protein lysate supernatant aliquoted for immediate quantification and storage at -20oC.

2.3.3 Cytosolic and nuclear fraction protein lysate extractions

Adherent cells or pelleted cells were washed twice with PBS then suspended in 500- 1000 µL cold lysis buffer. Adherent cells were released with a plastic cell scraper. Cells were transferred to an Eppendorf tube and centrifuged at 14000 rpm 1 minute 4oC to

pellet cell nuclei and the cytoplasmic fraction supernatant aliquoted for immediate quantification and storage at -20oC. Nuclear pellet was re-suspended in 100 µL cold lysis buffer and incubated at 4oC for a further ten minutes to lyse any remaining cells. Cells were centrifuged at 14000 rpm 10 minutes 4oC to pellet cell nuclei and the supernatant discarded. Nuclear pellet was re-suspended in 80 µL of extraction buffer by pipetting and incubated on a nutator for 10 minutes at 4oC. Solution was centrifuged at 14000 rpm 10 minutes 4oC to pellet nuclear debris and the nuclear protein lysate supernatant aliquoted for immediate quantification and storage at -20oC.

2.3.4 Protein quantification

Protein lysate concentrations were calculated using a Bradford dye assay (Sigma Aldrich, B6916) relative to a bovine serum albumin (BSA; Sigma Aldrich, A2153) standard curve. 200 µL of Bradford reagent was added to 10 µL of each sample or standard in a 96 well flat bottomed plate (Costar, CLS3997) and incubated at room temperature to develop. Absorbance at 595 nm wavelength was measured with a Tecan GENios microplate reader.

2.3.5 SDS-PAGE protein separation gels

Protein samples were separated on 10% separating SDS-PAGE gels. 20 µg of protein lysate was mixed with 5X Laemmli sample buffer in a total volume of 30 µL and denatured by incubation at 100 OC for five minutes. Protein ladder 10-250 kDa (NEB, P7703) was loaded into a well as molecular weight standard. Gels were run in 1x SDS- PAGE running buffer in a Mini-PROTEAN Electrophoresis cell (Bio-Rad) at 200 V.

2.3.6 Membrane transfer

Separated protein bands were transferred to Polyvinylidene fluoride (PVDF) membranes using the Trans-Blot Turbo Transfer System (Bio-Rad) and Trans-Bot Turbo PVDF Transfer Packs (Bio-Rad, 1704157) as per the manufacturer’s instructions. Once protein had transferred to the PVDF membrane, ladder positions and experimental identification were added with a pencil and the membrane placed in 1x Tris buffered saline (TBS) for further processing. Membranes were incubated in Ponceau solution and imaged to confirm protein separation and transfer.

2.3.7 Western blotting

Membranes were washed with TBS then blocked for four hours in TBS 0.1% Tween-20 (Sigma Aldrich, P1379) with 5% Western blocking reagent (WBR; Roche diagnostics, 11921673001). Membranes were then washed with TBS-Tween for 10 minutes, excess solution removed by blotting, coated with primary antibody diluted in 5% WBR TBS- Tween and incubated in a humidified chamber 90 minutes. Membranes were washed three times in TBS-Tween for 10 minutes each, excess solution removed by blotting, coated with secondary antibody diluted in 5% WBR TBS-Tween and incubated in a humidified chamber for one hour. Membranes were washed three times in TBS-Tween for 10 minutes each then one 10 minute wash in TBS. Excess solution was removed by blotting and membranes coated with Pierce ECL Western Blotting Substrate (Thermo Scientific, 32106) for one minute in the dark. Excess reagent was poured off the membrane and Kodak Biomax XAR film exposed to the membrane in a film cassette for an appropriate exposure time. Films were developed on a JP 33 Film Processor, all films were handled in a dark room until developed. Primary and secondary antibodies are listed (Table 2.1).

2.3.8 Membrane stripping

For serial probing membranes were washed with TBS for 10 minutes on a nutator. The medium removed and membranes incubated with Restore Plus Western Blot Stripping Buffer (Thermo Scientific, 46430) in a 50mL falcon tube in the dark on a rotor for 30 minutes. Blot was washed for 10 minutes in TBS then successful stripping confirmed with Western Blotting Substrate as before (2.3.7). 2.4 Microscopy

2.4.1 Immunostaining of RAW cells

Raw cells were cultured on No1 18mm diameter coverslips (Scientific Laboratory Supplies, MIC3110) in six well plates for immunostaining experiments. At the end of culture medium was removed from the wells and wells incubated with freshly made cold 4% paraformaldehyde (PFA; Sigma Aldrich, P6148) in TBS for 10 minutes at 4oC to fix.

Solution was removed and wells washed three times with TBS for five minutes each time. Coverslips were then removed from the wells and transferred to a humidified chamber for all further incubations. Coverslips were blocked with 1x WBR in TBS-Tween for one hour. Buffer was then aspirated and primary antibody diluted in 0.1x WBR in TBS-Tween applied and coverslips incubated overnight at 4oC. Buffer was aspirated and coverslips washed by the application of 0.1x WBR in TBS for three incubations of five minutes each. Buffer was aspirated and secondary antibody diluted in 1x WBR in TBS- Tween was applied. Coverslips were incubated for 1 hour in the dark. Buffer was aspirated and coverslips washed by the application of 0.1x WBR in TBS for three incubations of five minutes each in the dark. Buffer was aspirated and coverslips carefully dried with tissue before the application of Prolong Gold Antifade reagent with DAPI (Life Technologies, P36935) and pressed onto a clean microscope slides (Scientific Laboratory Supplies, MIC3040). Slides were left to set in the dark at room temperature for 24 hours. Cells were imaged by confocal microscopy (2.4.3) and slides stored at - 20oC.

2.4.2 Light and fluorescence microscopy

Light and fluorescence microscopy was performed on an inverted Olympus IX70 microscope (Olympus Corporation) with a QIClick CCD monochrome camera using the QCapture Suit PLUS software (01-QIClick-R-F-M-12-C, QImaging). BCIP/NBT anti-CD31 stained neovascularisation assay images were captured at 4X magnification. GFP+ macrophages in neovascularisation assay co-culture were captured at 20X magnification.

Colour light microscopy was performed on an upright Nikon eclipse 80i microscope with a DS-Fi1 CCD colour camera using the NIS elements software (Nikon Instruments).

2.4.3 Confocal microscopy

Scanning confocal microscopy was performed on an Olympus FLUOVIEW FV1000 system using the Olympus FLUOVIEW software (Olympus Corporation). RAW cells cultured in conditioned medium and processed for immunostaining to the mCherry tag protein were captured at multiple depths through the cells at 40x magnification.

2.5 Image analysis

2.5.1 General image preparation

Images were processed in ImageJ to prepare for addition to figures (Schneider et al., 2012). A background subtraction was run to remove any non-uniformities in light transmission/fluorescence across the image. Maximum and minimum pixel values were adjusted if required. For all processing the original image was saved separately.

2.5.2 GFP+ macrophage morphology

Images were processed in ImageJ for morphology counts. A macro for batch processing the images was used to subtract the background (200 pixel rolling), invert the lookup table and enhance the contrast to 0.35 saturation to make the cells black with a defined outline. Output images were then processed in Photoshop (Adobe Systems) with each cell isolated and assigned to one of seven morphology types manually (Figure 2.4). Three images were used for each time-point and treatment and the average counts calculated.

2.5.3 BCIP/NBT anti-CD31 stained neovascularisation assays

Images were batch processed with the Angiosys vessel analysis program as per the manufacturer’s instructions (Adaptrix). The image was first smoothened using a Gaussian blur, then a threshold layer was generated based on a set pixel value to highlight the CD31+ vessels and the area in number of pixels recorded. This threshold map was then used to generate a skeleton map of vessels using a minimum starting width of 10 µm. The tubule skeleton map was cleaned of small, non-vessel structures of 10 pixels or less then analysed for tubule length, number, and number of junctions. The automatic thresholding and skeleton mapping for each image was verified by eye to avoid false positives and negatives and minimal adjustments made when appropriate. Five images were captured per well in a cross formation from the centre of each well (Figure 2.5).

A B

C D ﬁlapodia Trapezoid

Two arms

Hyperplasic

Single arm

Figure 2.4 Processing of angiogenesis assay macrophage images for morphology analysis Image processing and analysis workflow for macrophage morphology. A) Fluorescence microscopy images of GFP+ murine macrophages in co-culture with human fibroblasts and endothelial cells. B) Each image processed with rolling background subtraction, greyscale inversion and enhanced contrast to aid cell outline identification. C) Each cell was assesses by eye and assigned to a cell morphology type arranged in rows. D) Multiple processed images were used to identify general cell morphology types for this assessment.

A B

C D

Figure 2.5: Image processing for neovascularisation assay tubule network analysis

Image processing and analysis workflow for tubule networks. A) Greyscale images of BCIP/NBT anti-CD31 stained neovascularisation assays. B) Images were smoothened with a Guassian blur then a threshold image generated to mark the CD31 positive staining. From this the CD31 positive pixel area was measured. C) The threshold mask was then reduced down to a single pixel width skeleton map of the vessel network. D) This image was cleaned of any remaining small non-vessel structures of 10 pixels or less before the network was measured for number of vessels, number of junctions and the length of each vessel. Representative images of the process generated in ImageJ. Yellow scale bar equivalent to 200 µm.

2.6 Animals

All animals used for the work presented in this thesis were house at the University of Manchester animal care facility. All procedures were approved by the local ethical review committee and the Home Office. Leprdb/db and Leprdb/+ mice were purchased from the Jackson Laboratory (Bar Harbor, ME) and Harlan (Oxfordshire, UK). All animals were used between 8 and 16 weeks of age, and were age and sex matched to controls on the

same C57BL/6 background. The hind limbs of male Wistar rats for bone marrow cell isolation were the gift of Dr Natalie Gardiner of the University of Manchester. Diabetes was induced in the rats with freshly made Streptozotocin (STZ) saline solution (55mg/kg), administered by intraperitoneal injection following an overnight fast. Diabetes was verified three days post the start of treatment as a blood glucose of greater than 15mmol/L. Diabetic and sex and age matched controls were maintained for 12 weeks before euthanasia (Ali et al., 2014). 2.7 Statistical Analysis

RAW cells cultured in low and high glucose, gene expression analysis eight experimental repeats, compared by paired T test. Cell counts 13 experimental repeats, compared by paired T test.

Non-diabetic and diabetic derived mouse bone marrow macrophages, gene expression analysis nine experimental repeats, compared by paired T test. FACS analysis six experimental repeats, compared by paired T test. Cell counts nine experimental repeats, compared by paired T test.

Non-diabetic and diabetic derived rat bone marrow macrophages gene expression analysis seven experimental repeats, compared by paired T test. Cell counts five experimental repeats, compared by paired T test.

Activated non-diabetic and diabetic derived mouse bone marrow macrophages gene expression analysis eight experimental repeats. Activation states within phenotype compared by one-way ANOVA. Phenotypes within activation state compared by paired T-test.

Neovascularisation assay quantifications for activated non-diabetic and diabetic derived mouse bone marrow macrophages, two experimental repeats. Wells compared to untreated control well by one-way ANOVA. Phenotypes compared by paired T-test.

Validation of macrophage activation states for the neovascularisation assay two experimental repeat. Activation states compared by one-way ANOVA.

THP-1 to HUVEC comparisons six experimental repeats, compared by Mann-Whitney test.

RAW to bEnd.5 cell comparisons five experimental repeats, compared by Mann-Whitney test.

THP-1 Nucleofection optimisation four experimental repeats.

THP-1 Nucleofection with pleiotrophin three experimental repeats per time-point. Compared by two-way ANOVA across all time-points and unpaired T-test between treatments at day four.

THP-1 supplemented medium experiments three experimental repeats. Samples compared by two way ANOVA.

RAW cells treated with conditioned medium five experimental repeats. Comparisons of 293T, SP.mCherry, and SP.Hoxa3.mCherry by one way ANOVA. Comparisons of SP.mCherry and Sp.Hoxa3.mCherry at day 2 and day 4 were compared with multiple T– tests using the Holm-Sidak method.

Mouse bone marrow derived macrophages treated with SP.mCherry or SP.Hoxa3.mCherry, gene expression analysis seven experimental repeats, compared by T test. Cell counts seven experimental repeats, compared by T test. FACS analysis six experimental repeats compared by T test. All data normalised to SP.mCherry to reduce variation from experimental repeats.

Rat bone marrow derived macrophages treated with SP.mCherry or SP.Hoxa3.mCherry, gene expression analysis six experimental repeats, compared by T test. Cell counts six experimental repeats, compared by T test. All data normalised to SP.mCherry to reduce variation from experimental repeats.

Activated macrophages from SP.mCherry or SP.Hoxa3.mCherry treated with bone morrow derived cultures, gene expression analysis six experimental repeats, activation states compared by two way ANOVA. Comparisons of SP.mCherry to SP.Hoxa3.mCherry treated sets by multiple T tests using the Holm-Sidak method.

Neovascularisation assay quantifications for non-diabetic and diabetic derived mouse bone marrow macrophages treated with conditioned medium, three experimental repeats. Wells compared to untreated control well by one-way ANOVA. Treatments compared by paired T-test.

3 Diabetes dysregulates macrophage activation

The overarching aim for this chapter was to investigate how diabetes may alter the phenotype and function of macrophages. Macrophages are understood to be key mediators of the wound healing process, both promoting inflammation and the repair and regeneration of new tissue by other cells (Mosser and Edwards, 2008). Many diabetic pathologies including non-healing cutaneous wounds are characterised by an excessive inflammatory phenotype that is likely to play an important role in disease aetiology (Loots et al., 1998). To test how diabetes may alter the macrophage phenotype cell lines grown in diabetic conditions and murine macrophages cultured from animal models of diabetes were assayed for markers of their functional properties. The macrophage population in diabetic wounds is thought to be predominantly immature, pro-inflammatory macrophages (Mirza and Koh, 2011). As such the maturation potential and response to activation stimuli were assessed by the expression of genetic markers post stimulation of macrophage differentiation, and after polarisation to a classical or alternative activation state respectively. Neovascularisation is also impaired in diabetic wounds (Bauer et al., 2005). To test in diabetic changes in macrophage phenotype have a role to play in this phenomenon the effects of non-diabetic and diabetic derived macrophages upon a model of vascular growth was also performed. 3.1 Diabetes and macrophage maturation

The inflammatory cell population within most tissues includes both resident macrophages and monocytic precursors that are derived from the haematopoietic bone marrow and enter the tissue from the blood (Okabe and Medzhitov, 2014, Hashimoto et al., 2013, Chow et al., 2013, Schafer et al., 2012). In many tissues including the skin, tissue damage induces inflammation triggering a significant increase in the numbers of bone marrow derived monocytic cells and macrophages at the site of injury (Frangogiannis et al., 2003, Willenborg et al., 2012, MacDonald et al., 2010, Little et al., 2014). Early in the inflammatory phase of cutaneous wounds ‘less mature’ monocytic cells and macrophages have been observed to be more common, with a shift to ‘more mature’ macrophages as inflammation progresses and resolves into the proliferative phase (Crane et al., 2014, Koh and DiPietro, 2011, Little et al., 2014). In diabetic wounds

there is an excessive number of these early macrophages that is thought to contribute to the impaired healing phenotype (Mace et al., 2009, Mirza and Koh, 2011). I hypothesised that the diabetic environment could be altering the maturation of macrophages from their bone marrow precursors and contribute to the excessive inflammation in diabetic pathologies.

3.1.1 Effects of glucose concentration on macrophage gene expression in RAW mouse macrophages

RAW 264.7 cells are a macrophage-like cell line derived from BALB/C mice after an immortalising transformation. To investigate if the elevated glucose environment of diabetes altered the macrophage phenotype, RAW cells were cultured in euglycaemic (4-8 mM) and hyperglycaemic (10-20 mM) conditions. RAW cell medium with 1000mg/L (5.5 mM) of glucose was used as ‘low glucose’ conditions and medium with 4500mg/L (25 mM) glucose was used as ‘high glucose’ conditions (higher than hyperglycaemia but established culture conditions for RAW cells). Cells were acclimatised to the glucose concentration for three passages of 48 hours and then harvested at subsequent passages for analysis.

After three rounds of culture the morphology of the cells exhibited some differences between the low and high glucose treatments when observed by phase microscopy (Figure 3.1, A). Cells grown in high glucose conditions tended to show more clumps of rounded cells whilst the low glucose cells were more likely to display adherent filopodia. These morphologies were similar to the appearance of RAW cells observed when at a high density and low density respectively. Total cell counts at the time of culture passage corroborated this observation, with the high glucose conditions yielding significantly more cells per plate (Figure 3.1, B). This suggests that any morphological differences are due to an increased proliferation rate (or increased cell survival) from the elevated supply of glucose.

Expression of markers of macrophage phenotype were assessed in these samples by quantitative real time PCR (qRT-PCR). No significant difference was observed in the three markers tested, CD14, Emr1 (the transcript encoding F4/80) and Itgam in the cells exposed to high glucose (Figure 3.1, C). Overall, these results did not support that

growth of RAW 264.7 cells in an elevated glucose concentration triggered macrophage maturation defects.

A B Cell counts 50

40 **

ose c

w w Glu o

L 20 Million Cells

10 ose c 0 e e s s o o c c lu lu G G High Glu High w h o ig L H C CD14 Emr1 Itgam 1.0 0.15 0.4

ession 0.8

r 0.3 0.10 0.6 0.2 0.4 0.05

e mRNA Exp e mRNA 0.1

v 0.2

a el

R 0.0 0.00 0.0 e e e e e e s s s s s s o o o o o o c c c c c c lu lu lu lu lu lu G G G G G G w h w h w h o ig o ig o ig L H L H L H Culture conditions Figure 3.1 Growth of RAW mouse macrophages in low and high glucose culture medium Phase microscopy images of RAW mouse macrophages cultured in DMEM with low (1000 mg/L) and high (4500 mg/L) glucose concentrations for 72 hours (A). Yellow scale bar equivalent to 100 µm. Cell counts as millions per flask after three days culture (B). Expression levels of mRNAs for macrophage phenotype (C) normalised to reference genes H2a and Hsp90. Asterisk denotes a significant difference between the low and high glucose culture samples, ** p<0.01. Paired T- test of eight experimental repeats.

3.1.2 Macrophage marker expression in non-diabetic and diabetic derived mouse bone marrow macrophages

Immortalising transformation of RAW 264.7 cells may alter macrophage differentiation, so in vitro culture of primary bone marrow cells from mice was used as a second model to investigate the effects of diabetes upon macrophage maturation. Bone marrow cells were harvested from the tibia and femurs of 8-16 week old C57BL/6 mice either heterozygous of homozygous for the Leprdb mutation. Mice homozygous for this mutation develop a type-2-like diabetes (Lee et al., 1996, Hummel et al., 1966). These cells were cultured in bone marrow growth medium containing macrophage colony- stimulating factor (M-CSF) for seven days to stimulate the differentiation of haematopoietic progenitors to macrophages then analysed for markers of the macrophage phenotype (Figure 3.2). Non-diabetic mouse blood glucose is comparable to human euglycaemia at 1000 – 1500 mg/L, the Leprdb/db mouse has a blood glucose level of 3500 – 4000 mg/L so comparable to hyperglycaemia (Arakawa et al., 2001).

Mature macrophages at the end of the seven day culture show similar morphology from non-diabetic and diabetic animals when imaged by phase microscopy (Figure 3.3, A). Total numbers of cells in each plate were not significantly different for the two sources, compared to the elevated count seen in the diabetic analogue high glucose RAW cells (Figure 3.3,B). Expression of markers of macrophage phenotype were assessed by qRT- PCR (Figure 3.3 C). Diabetic derived macrophages showed a significantly increased level of CD14 mRNA but no significant change in the other markers tested, Emr1 and Itgam. Levels of these markers at the cell surface were also assessed by flow cytometry (Figure 3.3, D). All markers displated a single peak histogram suggestive of a relatively homogenous population so median fluorescence was assessed as a measure of surface expression levels. The increased CD14 expression seen at the mRNA level was not reciprocated by cell surface protein levels as determined by median cell fluorescence. The other markers F4/80 (protein product of Emr1) and Cd11b (Itgam) were similarly not significantly different in the diabetic derived samples. Overall these results do not support a difference in the maturation of non-diabetic or diabetic bone marrow cells to

macrophages in an in vitro system. However, the elevation of CD14 mRNA levels in the

diabetic samples may be indicative of an altered monocytic phenotype.

y 2 y 5 y

a a

D D

y 1 y 4 y 7 y

a a a

D D D

y y 0 y 3 6 y

a a a

D D D

Figure 3.2 In vitro differentiation of macrophages from bone marrow derived cells Phase microscopy time-course of bone marrow derived cells cultured in bone marrow culture medium supplemented with L929 conditioned medium (M-CSF). Yellow scale equivalent to 100 µm.

A B Cell count 500

400

300 NDb 200

Million Cells 100

0 b b D D

N Db

C CD14 Emr1 Itgam

s 2.0 4 4

ession k r * 1.5 3 3

1.0 2 2

tion mar a

r 0.5 1 1

e mRNA Exp e mRNA

ti M a 0.0 0 0

el b b b b b b D D D D D D R N N N

D CD14 F4/80 CD11b

s 1.5 1.5 1.5

e k

escence 1.0 1.0 1.0

r ace mar f 0.5 0.5 0.5

Cell sur 0.0 0.0 0.0 Median Median Fluo b b b b b b D D D D D D N N N Phenotype Figure 3.3 In vitro macrophage maturation from non-diabetic and type 2 diabetic mouse bone marrow cells A) Phase microscopy images of mouse bone marrow derived macrophages after seven days in vitro differentiation from non-diabetic (NDb) and type 2 diabetic (Db) mice. Yellow scale bar equivalent to 100 µm. B) Cell counts as millions per 10 cm plate after differentiation culture. C) Expression levels of macrophage marker mRNA, expression levels normalised to reference genes H2a and Hsp90. D) Cell surface marker fluorescence analysis. Fluorescence measurements are normalised to the non-diabetic value to reduce variation from fluorescence intensity calibration between experiments. Asterisk denotes a significant difference between the diabetic and non- diabetic samples, * p<0.05. Paired T-test, six experimental repeats.

3.1.2 Macrophage marker expression in streptozotocin induced type-1 diabetic rat bone marrow macrophages

The animal model described so far is typically viewed as type-2 diabetic system, simulating the elevated blood glucose and insulin resistance seen in type-2 diabetes patients (Kharroubi and Darwish, 2015). To see if type 1 diabetes also had minimal effects upon macrophage maturation in these assays, and if a non-genetic based animal model would give similar results we used streptozotocin treated rats (Motyl and McCabe, 2009). Wistar rats were treated with streptozotocin for 12 weeks to ablate their beta islets, stopping the production of insulin and inducing a type-1 diabetes phenotype. After 12 weeks of treatment the establishment of diabetes is confirmed by a blood glucose concentration of greater than 15 mMol/L . These and carrier treated control rats were then culled to collect bone marrow cells from their tibia and femurs. Bone marrow cells were grown for seven days in bone marrow culture medium containing M-CSF to stimulate their differentiation to macrophages. Phase microscopy of the rat cells after differentiation to macrophages showed minimal differences between the non-diabetic and diabetic samples (Figure 3.4, A). No significant difference was seen between cell densities after differentiation (Figure 3.4, B).

The differentiated cells were assayed for the expression of macrophage markers by qRT- PCR (Figure 3.4, C). None of the markers tested were expressed significantly higher in the diabetic derived samples. Overall these results suggest that type-1 diabetic derived macrophages behave similarly to their type-2 counterparts in that their ex vivo maturation does not appear to be affected by their diabetic origins.

A B Cell count 50

40 NDb

20 Million cells

10 Db 0 b b D D N C CD14 Emr1 Itgam

1.5 3 1.5

ession r

xp 1.0 2 1.0 e

0.5 1 0.5

e e mRNA

a el

R 0.0 0 0.0 b b b b b b D D D D D D N N N Phenotype Figure 3.4 In vitro macrophage maturation from non-diabetic and type 1 diabetic rat bone marrow cells A) Phase microscopy images of rat bone marrow derived macrophages from non-diabetic controls (NDb) and Streptozotocin induced type 1 diabetic (Db) rats. Yellow scale bar 100 µm. B) Cell counts as millions per 10cm plate after differentiation culture. C) Expression levels of macrophage markers by mRNA. Expression levels of mRNAs are normalised to reference genes H2a, ActinB and Hsp90. No significant differences between samples in T-tests of seven experimental repeats. 3.2 Activation

Maturation of monocytic precursors to macrophages is but one of the stages in the acquisition of wound associated macrophage phenotypes. This maturation also appears to be intimately linked to the various activation states that a macrophage can exhibit. During the early inflammatory phase wound associated macrophages are predominantly at the inflammatory, or M1, end of the activation spectrum. With wound healing progression toward proliferation and angiogenesis the macrophage population shifts in

activation states to a predominately pro-healing alternative, or M2 activation state (Mahdavian Delavary et al., 2011, Koh and DiPietro, 2011, Little et al., 2014). The excessive accumulation of macrophages in the chronic wound is associated with the persistent inflammatory state of both the wound and the macrophages (Mirza et al., 2014, Hazra et al., 2013). I hypothesised that diabetes could alter the phenotype of myeloid progenitors in the bone marrow such that the macrophage phenotype is biased toward an inflammatory state. This could explain the low level chronic inflammation in diabetes and the elevated inflammatory response in diabetic wounds (Lumeng et al., 2007a, Mirza et al., 2014).

3.2.1 Diabetic derived mouse bone marrow macrophages expression of activation markers

The in vitro culture of bone marrow derived macrophages was used to test the response of non-diabetic and type-2-like diabetic cells to activation stimuli. These macrophages were cultured from the bone marrow of homozygote Leprdb/db diabetic mice and their non-diabetic heterozygote counterparts as before (3.1.2) then stimulated to inflammatory, M1, or alternative, M2, activation. Control cells were also grown without activating stimuli to test the untreated state between non-diabetic and diabetic cells. M1 activation was induced with IFNγ and LPS in serum starved conditions, M2 activation with IL-4 and IFNγ, and non-activated controls were grown in serum starved conditions. All treatments were for 16-24 hours.

After culture all cells appeared to be of a lower density, possibly due to the change of medium to serum starved conditions. Activated non-diabetic cells displayed their previously reported morphological differences with classically activated cells enlarging with many presenting multiple filopodia and cell process whereas alternatively activated macrophages were predominantly elongated with neurite like processes (Figure 3.5 A). Activation state of the cells post treatment was assayed by gene expression by qRT-PCR using well characterised M1 and M2 associated genes. All four classical activation genes tested (Ccl2, CD86, Nos2 and Tnf) were significantly different in the cells stimulated with classical cytokines in multi-sample variance analysis to both the non-activated controls and alternatively activated cells (Figure 3.5, B).

A Non-activated Classically activated Alternatively activated

B Classical Markers Ccl2 CD86 2.0 1.0 * 0.8 1.5 ** 0.6 1.0 0.4 0.5 0.2

0.0 0.0 ession

r NA CA AA NA CA AA

e e Exp Nos2 Tnf

v 15 1.5 ti

a ** el

R * 10 1.0

5 0.5

0 0.0 NA CA AA NA CA AA Sample C Alternative Markers Arg1 Chi3l3 0.5 0.15 * 0.4 * 0.10 0.3

0.2 0.05 0.1

0.0

ession 0.00

r NA CA AA NA CA AA

e e Exp Mrc1 Tgfb1

v 1.0 1.5 ti a *

el 0.8 R 1.0 0.6

0.4 * 0.5 0.2

0.0 0.0 NA CA AA NA CA AA Sample Figure 3-5 Activation markers in polarised non-diabetic mouse macrophages A) Phase microscopy of mouse bone marrow derived macrophages polarised with activation cytokines. Yellow scale bar 50 µm. B) Expression levels of classical activation markers. C) Expression of alternative activation markers. Expression normalised to reference genes H2a and Hsp90. Asterisk denotes a significant difference between activation states when analysed by two way ANOVA. * p<0.05, ** p<0.01. Eight experimental repeats.

A Non-activated Classically activated Alternatively activated

tic

e Diab

B Classical Markers Ccl2 CD86 4 2.0 ** 3 1.5 *

2 1.0

1 0.5

0 0.0 ession

r NA CA AA NA CA AA

e e Exp Nos2 Tnf

v 15 2.0 ti

a **

el *

R 1.5 10

1.0

5 0.5

0 0.0 NA CA AA NA CA AA Sample C Alternative Markers Arg1 Chi3l3 0.5 2.0

0.4 * 1.5 * 0.3 1.0 0.2 0.5 0.1

0.0 0.0 ession

r NA CA AA NA CA AA

e e Exp Mrc1 Tgfb1

v 0.8 1.5 ti

a ** el

R 0.6 1.0 0.4 ** 0.5 0.2

0.0 0.0 NA CA AA NA CA AA Sample Figure 3-6 Activation markers in polarised diabetic mouse macrophages A) Phase microscopy of mouse bone marrow derived macrophages polarised with activation cytokines. Yellow scale bar 50 µm. B) Expression levels of classical activation markers. C) Expression of alternative activation markers. Expression normalised to reference genes H2a and Hsp90. Asterisk denotes a significant difference between activation states when analysed by two way ANOVA. * p<0.05, ** p<0.01. Eight experimental repeats.

A Ccl2 CD86 4 ** 2.0 3 1.5

2 1.0

ession 1 0.5

r xp e 0 Classical activation Nos2 Tnf markers

15 2.0 ** e e mRNA

v 1.5

ti 10 a

el 1.0 R 5 0.5 Non-diabetic

0 0.0 Diabetic Non- Classically Alternatively Non- Classically Alternatively activated activated activated activated activated activated B Arg1 Chi3l3 0.5 2.0 ** 0.4 1.5 0.3 1.0 0.2

ession 0.5

r 0.1 xp e 0.0 0.0 Alternative activation Mrc1 Tgfb1 markers 1.0 2.0

e e mRNA 0.8

v 1.5 ti

a 0.6

el 1.0 R 0.4 0.5 0.2 Non-diabetic

0.0 0.0 Diabetic Non- Classically Alternatively Non- Classically Alternatively activated activated activated activated activated activated Cytokine treatment Figure 3-7 Differential expression of activation markers between non-diabetic and diabetic mouse macrophages A) Relative expression levels of classical activation markers in non-diabetic and type 2 diabetic bone marrow derived macrophages polarised with activation cytokines. B) Relative expression levels of alternative activation markers in bone marrow derived macrophages. Expression normalised to reference genes H2a and Hsp90. Asterisk over brackets denotes significant difference between non-diabetic and diabetic derived samples in paired T-tests, ** p<0.01. Eight experimental repeats.

The four alternative activation genes (Arg1, Chi3l3, Mrc1 and Tgfb1) were similarly upregulated in the alternatively stimulated in multi-sample variance analysis (Figure 3.5, C).

Cultures of activated type 2 diabetic derived mouse bone marrow macrophages displayed the same morphology as the non-diabetic cells (Figure 3.6, A). Activation states of the cells post treatment was assessed by expression of classical and alternative activation genes. All four classical activation genes (Figure 3.6, B) and all four alternative activation genes (Figure 3.6, C) were significantly differentially expressed in classically and alternative activated cells respectively in multi-factor variance analysis.

Paired analysis was performed for each activation state between the non-diabetic and diabetic samples. No difference was detected between phenotypes in the non-activated samples, suggesting that the diabetic environment alone does not drive or inhibit an activation state. When diabetic macrophages were stimulated to the M1 activation state they expressed a significantly higher level of two of the classical activation markers, Ccl2 and Tnf (Figure 3.7, A). CD86 (p<0.09) also trended towards elevated expression in the diabetic classically activated macrophages. This may indicate an increased sensitivity to M1 type signals or that diabetic macrophages have a greater capacity for inflammatory activation. Interestingly when diabetic macrophages were stimulated with M2 activation signals they also expressed a significantly higher level of one of the alternative markers, Chi3l3, and did not downregulate any of the other markers tested (Figure 3.7 B). There was no significant difference in the markers for the opposing activation state when classically or alternatively activated between the diabetic and non-diabetic derived samples (i.e. M2 markers in classically activated macrophages and M1 markers in alternatively activated).

Together these results suggest that rather than a diabetic environment induced shift towards the inflammatory state as hypothesised, the diabetic macrophages become hyperpolarised to either activation state at the gene expression level.

3.3 Neovascularisation

Diabetic wounds shown an absence of blood vessel regeneration and endothelial progenitors compared to non-diabetic counterparts as expected for their hyper- inflammatory state (Mace et al., 2005, Mace et al., 2009, Awad et al., 2005). Myeloid cells have been implicated to contribute to the regulation of neovascularisation including macrophages(Chambers et al., 2013). Diabetes was observed to elevate the macrophage response to activation signals, which may therefore perturb their functional interactions with vessel repair. As such I hypothesised that the diabetes induced changes in macrophage phenotype could alter neovascularisation interactions and contribute to its absence in diabetic wounds.

3.3.1 Neovascularisation assays with activated macrophages cultured from diabetic derived bone marrow cells

An in vitro model of blood vessel development was used to model the effects of diabetic and non-diabetic activated murine macrophages upon neovascularisation. In brief this model uses a heterogeneous culture of human fibroblasts and human umbilical vein endothelial cells (HUVECs) in a pro-angiogenic culture medium in which both the process of vasculogenesis and angiogenesis will form a network of capillary-like tubules. The fibroblast in the assay provide a substrate for tubule formation and are proposed facilitate the formation of vessels more like those observed in vivo than other acellular substrates. In this assay vasculogenesis is thought to occur up to day four or five, based on time lapse imaging of the V2A assay using GFP+ HUVECs provided by the manufacturer (CellWorks, https://youtu.be/RhfRZ-1iwRQ). Angiogenic sprouting from these vessels is observed with these GFP+ HUVECs from day five onwards. To ensure freshly activated macrophages were present during both vasculogenesis and angiogenesis, activated murine macrophages (generated as per the previous activation experiments in 3.2.1) were added on days two, four and six. The culture medium in this assay is confirmed to contain a glucose concentration of less than 1000 mg/L so will not cause any diabetes-like changes to the phenotype of the fibroblasts and endothelial cells, or the experimental input macrophages.

D3 D5 D7

NDb

Non-Acti

NDb

ally Acti

Classi

NDb

ely Acti

ern

t Al

D9 D11 D13

NDb

Non-Acti

NDb

ally Acti

Classi

NDb

ely Acti

ern t

Al Figure 3.8 Vessel formation in diabetic and non-diabetic macrophage angiogenesis assay co-culture Light and fluorescence microscopy images of GFP+ murine macrophages in co-culture with human fibroblasts and endothelial cells over assay time course. Red lines indicate likely vessel structures. Yellow scale bar equivalent to 50 µm.

GFP+ macrophages were used in one of the experimental repeats to attempt to track their interactions with the nascent vessels (Figure 3.8). Evaluation of composite images of the fibroblast and HUVEC bed and fluorescent imaging of the GFP+ macrophages was unable to identify any vessel like structures in any of the treated wells until day seven of the assay. This meant any potential interactions of macrophages and HUVECs during vasculogenesis could not be judged. In the time points where vessels could be identified (Days 9, 11 and 13) no consistent alignment with macrophages could be seen, nor association with vessel junctions. This was irrespective of macrophage origin phenotype or activation state, instead macrophages appeared to align with the fibroblast bed. This suggests that the bone marrow derived macrophages do not interact directly with HUVECs during angiogenesis in this assay.

Neovascularisation assays were fixed and stained for CD31 to visualise the vessel network for image analysis (Figure 3.9, A). Image analysis software was used measure the area of each well covered by HUVEC vessels and generate a skeleton of the vessel network to derive further measures such as tubule length (Figure 3.9, B). None of the measures generated from the images of each well showed a significant difference between the diabetic and non-diabetic derived macrophage samples. These results suggest that there is no difference between diabetic and non-diabetic derived macrophages in regulating the process of neovascularisation.

ed t a v ely ely acti v ti a ern t Al amin r Su ed t a v ally ally acti c Classi ed t a e r t n U ed t a v Non-acti GF

tic e Non-Diab tic e Diab A

B CD31+ Field Area Total Tubule Length Average Tubule Length ** ** ** 3 2.5 1.5

2.0 2 1.0

1.5 els x 1.0 Pi 1 0.5 0.5

0 0.0 0.0

d F in d d d d F in d d d d F in d d d te G te te te te G te te te te G te te te a E m a a a a E m a a a a E m a a a e V ra v v v e V ra v v v e V ra v v v tr u ti ti ti tr u ti ti ti tr u ti ti ti n S c c c n S c c c n S c c c U -a a a U -a a a U -a a a n ly ly n ly ly n ly ly o l e o l e o l e N a v N a v N a v ic ti ic ti ic ti s a s a s a s rn s rn s rn la e la e la e C lt C lt C lt A A A Number of Tubules Total Tubule Junctions Junctions per length

4 ** 5 ** 2.5 **

4 2.0 3 3 1.5 2

2 1.0 ubules T 1 1 0.5

0 0 0.0

Treatment NDb Db Figure 3.9 Vessel formation in diabetic and non-diabetic macrophage angiogenesis assay co-culture A) Representative light microscopy images of anti-CD31 stained day 14 angiogenesis assay wells developed with BCIP/NBT. Images aligned to centre of each assay well. Yellow scale bar is equivalent to 1 mm. B) Image analysis of Day 14 assay vessels as stained with anti-CD31 (PECAM- 1). VEGF and suramin treated wells presented as positive and negative controls respectively. Activation states for non-diabetic (NDb) and diabetic (Db) macrophages. All values are normalised to the untreated control wells for that experiment. Significant differences from other treatments signified by brackets, origin between NDb and Db indicative of the same difference for both phenotypes. ** p<0.01. Two experimental repeats.

3.3.2 Effects of neovascularisation assay culture upon macrophage phenotype

To provide activated macrophages for the three treatment time points activated macrophages were put into cryostorage and thawed the day before addition to the neovascularisation so the cells could recover from the thawing process in the relevant activation medium. The activation states of the macrophages was confirmed by qRT-PCR immediately before addition to the assay (Figure 3.10). The classical and alternatively activated samples of non-diabetic and diabetic macrophages appeared to still be polarised in their respective activation state. In the non-diabetic macrophages the classical activation marker Ccl2 was significantly higher in classical compared to alternatively activated cells. Nos2 (p<0,06) and Tnf (p<0.10) also trended towards still being higher in M1 polarised cells (Figure 3.10, A). Alternative activation marker Tgfb1 was significantly higher in alternative compared to classically activated cells (Figure 3.10, B).

In the type 2 diabetic macrophages the classical activation markers Ccl2, CD86 and Nos2 were significantly higher in classical compared to alternatively activated cells (Figure 3.10, C). The alternative activation marker Tgfb1 was significantly higher in alternative compared to classically activated cells. Mrc1 (p<0.09) also trended towards still being higher in M2 polarised cells (Figure 3.10, D).For both non-diabetic and diabetic activated macrophages it appeared that the thawing and recover process generated more variance in gene expression between samples.

A Ccl2 CD86 Nos2 Tnf 2.0 1.0 5 2.5

1.5 0.8 4 2.0 0.6 3 1.5 1.0 0.4 2 1.0 0.5 0.2 1 0.5

0.0 0.0 0 0.0 tic

e A A A A A A A A A A A A N C A N C A N C A N C A B Arg1 Chi3l3 Mrc1 Tgfb1

Non-diab 2.0 1.5 0.6 2.5

1.5 2.0 1.0 0.4 * 1.5 1.0 1.0 0.5 0.2 0.5 0.5

0.0 0.0 0.0 0.0 ession

r A A A A A A A A A A A A N C A N C A N C A N C A

C e Exp

v Ccl2 CD86 Nos2 Tnf ti

a 2.5 4 3 4 el R 2.0 3 3 2 1.5 2 2 1.0 1 0.5 1 * 1 0.0 0 0 0 A A A A A A A A A A A A

tic N C A N C A N C A N C A e D

Diab Arg1 Chi3l3 Mrc1 Tgfb1 5 3 0.4 4

4 0.3 3 2 3 * 0.2 2 2 1 1 0.1 1 0 0 0.0 0 A A A A A A A A A A A A N C A N C A N C A N C A Activation state Figure 3.10 Validation of activated macrophages used in neovascularisation assays A) Expression levels of mRNA markers for classical activation in macrophages derived from non- diabetic mouse bone marrow. B) Expression levels of markers of alternative activation in macrophages derived from non-diabetic bone marrow. C) Classical activation markers in diabetic bone marrow macrophages. D) Alternative activation markers in diabetic bone marrow macrophages. Expression levels of mRNAs are normalised to reference genes H2a and Hsp90. Activation states of macrophages were non-activated (NA), classically activated (CA) or alternatively activated (AA). Asterisk over brackets denotes a significant difference between activation states. * P<0.05. Two experimental repeats.

Having confirmed the macrophages retained their activation state after recovery from cryostorage the cells were assessed for changes in their morphology during co-culture in the neovascularisation assay. The pro-neovascularisation conditions of the neovascularisation assay may themselves have altered the phenotype of the macrophages. The GFP+ images of the macrophages throughout the co-culture experiments (Figure 3.8) were used to track the morphology of the macrophages to see if it gave any indication of a phenotypic change over time. Images were processed to generate a threshold map that was used to sort cells into seven different morphology types; small monocytic, trapezoid cells characteristic of mature non-activated macrophages, large monocytic cells, hyperplasic cells, cells with multiple filopodia, cells with two neurite-like arms and cells with one neurite-like arm (2.5.2; Figure 2.4).

Percentage plots of these seven cell types during the activated non-diabetic and type 2 diabetic derived macrophage co-cultures showed that the proportion of these morphologies did change as the assay progressed (Figure 3.11). The days after addition of a batch of macrophages, days three, five and seven appeared most similar to the proportions of morphologies pure cultures of activated macrophages. Over the remaining days the morphology proportions for all sample types drifted towards a similar distribution such that by day 13 all wells shared a similar morphology distribution. This may be indicative of phenotypic drift in the activation state and explain the similar vessel network scores across treatments.

Figure 3.11 Non-diabetic and diabetic activated macrophage morphology over neovascularisation assay co-culture Morphology analysis of florescence microscopy images of activated A) non-diabetic and B) type 2 diabetic derived GFP+ bone marrow macrophages during neovascularisation assay co-culture. Day 0 samples were macrophage cultures before addition to the assay. All other timepoints are imaged in the neovascularisation assay. Mp indicates the addition of macrophages to the culture wells on day 2, day 4 and day 6.

a i c i s m s r a l apod a m l i p r f r e a - ll l i t a ge g l o pe r n u y i m w S monocytic Trapezoid La monocytic H M T S NDb y 13 y a D y 11 y a D y 9 y a D y 7 y a D Mp y 5 y a D Mp y 3 y a D Mp y 0 y

ed t a v Non-acti ed t a v acti ally c Classi ed t a v acti ely v ti a ern t Al

a i c i s m s r a l apod a m l i p r f r e a - ll l i t a ge g l o pe r n u y i m w S monocytic Trapezoid La monocytic H M T S Db y 13 y a D y 11 y a D y y 9 a D y 7 y a D Mp y 5 y a D Mp y 3 y a D Mp y 0 y

ed t a v Non-acti ed t a v acti ally c Classi ed t a v acti ely v ti a ern t Al

3.3.3 Early monocytic cells and neovascularisation

RAW cells were a unique model in the comparisons between non-diabetic and diabetic (or diabetic like) conditions due to their mixed monocytic/macrophage phenotype in freshly passaged cultures. In the macrophage maturation analysis all qRT-PCR experiments used the endothelial genes vWF and Cdh5 as negative controls (expected to be absent or expressed at a very low level). It was noticed that the early endothelial marker vWF was expressed in the low glucose cultured RAW cells and that this expression was signficantly downregulated in the high glucose sample (Figure 3.12, A). The late endothelial marker Cdh5 expressed in more mature endothelial cells saw no significant difference in expression levels between high and low glucose culture. It has been reported that some monocytes possess plasticity to endothelial lineage and may contribute to vessel formation (Subimerb et al., 2010, Anghelina et al., 2006). The numbers of these cells is decreased in diabetes (Tamarat et al., 2004). Therefore I hypothesised that this downregulation in high glucose could be indicative of the loss of these endothelial/pro-angiogenesis properties.

Whilst I was unable to fully investigate this theory in this thesis, to initially assess if the expression of vWF in low glucose cultured RAW cells was biologically relevant I compared the expression level to a commited endothelial cell culture. The endothelial cell line bEND.5 was used (Figure 3.12, B). The expression of Cdh5 in the RAW cells was 0.000025 times the relative expression measured in the endothelial cells. The expression of vWF in the low glucose RAW cells was comparable to that observed in the endothelial cells, and in a multifactor analysis the high glucose RAW cell sample was significantly lower than both the low glucose RAW and bEND.5 samples.

No significant difference was observed in vWF expression levels between the non- diabetic and diabetic bone marrow derived macrophages from either mouse or rat (Figure 3.12, C). This would likely be due to their being a homogenous culture of lineage committed macrophages rather than the mixed monocyte/macrophage population of the RAW cells, or that the change in expression in those cells is a specific response to the glucose concentration.

A B vWF vWF 0.05 0.05

0.04 0.04

0.03 0.03

0.02 0.02

0.01 0.01 ** ** 0.00 0.00 e e s s W W 5 o o d c c A A n

u u R R E ession

ession l l e e b r r G G s s o o w h c c o ig u u L l l

H G G e e Exp e e Exp h

w g v v o i

L H

ti ti

a a el

el Cdh5 Cdh5 R R 0.000025 0.6 *** 0.000020 0.4 0.000015

0.000010 0.2 0.000005

0.000000 0.0 e e s s W W 5 o o d c c A A n u u R R E l l e e b G G s s o o w h c c o ig u u L l l H G G w h o ig L H Sample Sample C vWF 0.10 0.00006

0.08

ession 0.00004 r 0.06

e e Exp 0.04

v 0.00002

ti a

el 0.02 R

0.00 0.00000 b b b b D D D D N N Mouse macrophages Rat Macrophages Figure 3.12 Endothelial markers in models of diabetic myeloid lineage cells A) Expression levels of mRNAs for endothelial phenotype normalised to reference genes H2a and Hsp90 in RAW cells grown in low or high glucose culture medium. B) The same expression levels in comparison to the murine endothelial cell line bEnd.5. C) Bone marrow derived macrophages from mouse and rat did not show a decrease in vWF expression between non- diabetic (NDb) and diabetic (Db) samples. Asterisk denotes a significant difference between the low and high glucose culture samples, or of bEnd.5 compared to the two other samples, ** p<0.01, *** p<0.001. Five experimental repeats.

100

3.4 Discussion

The original aim for the experiments presented in this chapter was to investigate how diabetes may alter the phenotype and function of macrophages. In vitro culture systems with cell lines and bone marrow derived cells were used to separate the diabetic macrophages from the environmental effects that the target tissue environment introduces (Lavin et al., 2014, Wetzler et al., 2000). Three models of diabetes were tested for differences in macrophage maturation markers; the murine macrophage cell line RAW264.7 cultured in high glucose conditions, genetically type 2 diabetic mouse bone marrow derived macrophages and chemically induced type 1 diabetic rat bone marrow macrophages. At the start of these experiments it was hypothesised that diabetes would impair macrophage maturation.

Growth of RAW cells in high glucose conditions increased the final number of cells after 48 hours in culture in comparison to the low glucose controls, suggesting accelerated cell proliferation or a reduced rate of cell death. Cell morphology also differed between glucose concentrations with low glucose cells adherent with multiple filopodia, whereas high glucose cell cultures featured more clumps of rounded, monocytic cells. These morphological differences may be indicative of a maturation difference between the cultures. However during maintenance passages of RAW cells a similar difference was observed between freshly passaged low density cells and confluent high density cells, and the representative images for low and high density cells in the ATCC data sheet for this cell line. This may mean that the morphological differences are due to the elevated cell density after 48 hours culture in high glucose conditions. Serial dilutions of RAW cells in low and high glucose could be used to produce cultures of a comparable final density to negate this difference.

In the murine bone marrow derived macrophages no significant difference in cell density was observed between non-diabetic and diabetic cells after seven days in differentiation culture. There are multiple potential explanations for this difference compared to the RAW cells. The immortalising transformation of the RAW cells may alter their response to diabetic conditions, compared to primary cell cultures. The removal of non-adherent cells during the removal of old culture medium six days into culture may negate any

101

differences in proliferation of the primary cell lines. The difference in cell proliferation may be due to the increased glucose concentration, so culture of non-diabetic and diabetic macrophages, both in high glucose concentration conditions will proliferate at the same rate. Publication of high glucose promoting proliferation and inhibiting cell death in RAW cells through miRNA-21 supports the latter interpretation (Shang et al., 2015).

In the RAW cells high glucose culture had no significant effect upon markers of macrophage phenotype. Similar treatments of RAW cells have found differences in expression of activation genes in response to high glucose. High glucose RAW cells were reported to increase their classical activation in response to lipoteichoic acid (LTA) and LPS (de Souza et al., 2008, Hua et al., 2012) and decrease interleukin-1β release in non- activated cells (Hill et al., 1998). CD14 and Emr1 have been previously used as macrophage markers in RAW cells so should be acceptable reporters of macrophage phenotype (Khazen et al., 2005, Im et al., 2007). It has been reported that CD14 and other protein expression as measured by median surface protein fluorescence can change without a corresponding change in mRNA level so the FACS analysis should have been extended to the RAW cells (Frey and De Maio, 2007, Hamilton et al., 2013). In human cells CD14 expression level decreases as monocytes mature to macrophages, but there is no clear report of similar downregulation in murine cells (Gantner et al., 1997).

Mouse macrophages cultured from diabetic animals significantly increased their CD14 mRNA expression. This could be indicative of an altered maturation phenotype with an increase in the per cell expression level, or could be indicative of more CD14 positive cells but this was not reciprocated in the FACS analysis. Neither of the other two markers were different between the diabetic and non-diabetic samples. Rat macrophages showed no change in marker expression. These results did not fit reports of macrophage maturation during wound healing where isolated CD11b+ cells from diabetic mice lacked the increased Emr-1/F4/80 expression over time observed in their non-diabetic counterparts (Mirza and Koh, 2011). Similar in vitro culture experiments with bone marrow derived macrophages have also been reported since the start of this set of experiments (Bannon et al., 2013). After six days of culture diabetic derived cells expressed significantly less Emr1 and significantly more Cd11b. In median fluorescence

102

analysis CD11b and F4/80 were significantly reduced. Aside from the extra day of culture these experiments were performed identically to those reported here. The absence of downregulation and upregulation of F4/80 must be due to experimental variation (possibly between batches of the L929 medium used to promote differentiation) or that the extra day of maturation reduced the differences between non-diabetic and diabetic samples. No difference between the rat macrophages may also indicate poor sensitivity from the culture assays, or that type 1 diabetes has a differential effect upon macrophages.

Overall these results suggest that diabetes has no effect upon the maturation of macrophages in vitro. This result does not support my original hypothesis or fit the reports of impaired diabetic macrophage maturation both within diabetic wounds and similar in vitro experiments.

The activation potential of diabetic macrophages was hypothesised to be biased towards classical activation fitting the enhanced and persistent inflammatory phenotype of diabetic wounds. Mouse bone marrow macrophages were activated after the seven days in vitro maturation. The diabetic macrophages expressed higher levels of classical markers when stimulated to classical activation but also expressed higher levels of alternative markers when alternatively activated. These results suggested that rather than a bias to classical activation as hypothesised diabetic macrophages respond to a greater degree to both classical and alternative signals. It has been assumed that the activation treatments used are saturating such that all cells will become activated. However, in the absence of any per cell analysis in these experiments it is possible that these gene expression results are also indicative of more cells becoming activated rather than the activation itself being more significant. These results closely match the response of in vitro activated diabetic macrophages from similar experiments (Bannon et al., 2013).

RAW cells were not tested for their activation potential due to there being no difference in their macrophage maturation with high glucose treatment. However, the reports of high glucose cultured macrophages to have increased response to classical activation stimuli LPS and LTA means their full response to classical and alternative polarisation may be worth future investigation (Im et al., 2007, Khazen et al., 2005).

103

Overall the expression of activation markers does not completely fit the original hypothesis. Whilst the response to classical activation cytokines was significantly increased in diabetic derived macrophages, the response to alternative activation was similarly increased. However, this response may still fit with the behaviour of macrophages reported in diabetic wounds. The excessive inflammatory response would contribute to the inflammatory phenotype of diabetic wounds, which may then be preventing the switch to a pro-healing alternative phenotype.

Activated macrophages have been well documented to have differential effects upon neovascularisation in multiple pathologies. Macrophages on the M2 axis of the activation spectrum have been observed to promote angiogenesis whereas M1 polarised macrophages exhibit an inhibitory effect (Jetten et al., 2014b, Hagemann et al., 2009, He and Marneros, 2014, Mosser and Edwards, 2008). The increased expression of activation markers in response to activation stimuli may be indicative of a hyperpolarisation response, whereby the cells become activated to the extremes of the activation spectrum (Bannon et al., 2013). This may increase the inhibitory effects of M1 macrophages early in wound healing. Alternatively if more cells are becoming activated this could still contribute to elevated inflammatory environment observed in diabetic wounds. Both mechanisms would fit the reduced vascular repair observed in diabetic wounds (Mirza and Koh, 2011).

No significant difference in the development of the vessel networks in the neovascularisation assays was observed between the activation states, or the non- diabetic and diabetic derived macrophages. Tracking of GFP+ macrophages during the angiogenesis assay was not able to identify any interaction with vessels during angiogenic budding. Similarly because the HUVEC cells could not be identified amongst the fibroblast cell bed any interaction of GFP macrophages with vasculogenesis could not be assessed. Wells were only imaged once every two days (the day after cell or medium addition) so the time resolution may not have been frequent enough to capture interactions events. The use of HUVEC cells labelled with a second fluorophore would facilitate the live tracking of both the endothelial and macrophage populations throughout the assay. Activated macrophages predominantly regulate angiogenesis by remodelling the environment and the release of signalling molecules so direct

104

interaction with the vascular network at this stage may also not be expected (Owen and Mohamadzadeh, 2013, Chambers et al., 2013).

These results did not support the original hypothesis of diabetes increasing M1 angiogenesis inhibition and/or reducing M2 angiogenesis promotion. The results of non- activated macrophages also did not detect the previously reported actions of M1 and M2 macrophages upon angiogenesis so the assay may require further optimisation. A simpler assay of SVECs and macrophage co-culture on Matrigel reported that M2 macrophages promoted the formation of vessel like networks after 24 hours and the macrophages localised along the vessels, especially at branching points (Jetten et al., 2014b). Similarly in vivo Matrigel plug assays, where a plug of Matrigel loaded with macrophages was injected into the abdomen of mice for 14 days incubation, M2 macrophages enhanced the infiltration of host CD31+ cells (Jetten et al., 2014b). The in vitro system was also used to test the effects of macrophage conditioned medium and found non-activated, classically activated and alternatively activated macrophage conditioned medium all promoted angiogenesis.

The difference in protocols may account for the different responses. The published in vitro assay used twice as many macrophages as endothelial cells in one addition, whereas the experiments in this work used twice as many macrophages applied every two days. The higher total number of macrophages may have had an inhibitory effect on general HUVEC growth if competition for culture medium was occurring. The positive effects of M2 macrophages would still expected to be seen though. The longer culture time towards fully developed tubules in my assays may have missed the differences in macrophage effect compared to their 24 hour incubation. Live tracking with fluorescently labelled endothelial cells would facilitate the analysis of vessel development at the earlier time points where differences may be evident. Alternatively the neovascularisation assay could be stopped at an earlier time point and processed as before.

The activation state of the macrophages before their addition to the assay was confirmed by qRT-PCR. Classical and alternative activation was not significantly altered by the cryostorage of macrophages to facilitate the addition at multiple assay time

105

points. A final check that this doesn’t affect the assay could be to add a single batch of fresh activated macrophages to the neovascularisation assay.

The culture medium for the tube formation assay was not given (Jetten et al., 2014b). Differences in the angiogenesis growth medium in the neovascularisation assays may also alter assay results. Morphology of the GFP+ macrophages throughout the assay suggested that the phenotype of the macrophages changed and converged over the 14 days of the assay. This could be driven by the angiogenesis growth medium or interactions with the fibroblasts and HUVECs in the co-culture. The 24 hour culture in the tube formation assay is likely not long enough to see these changes in phenotype. The Matrigel plug assays were performed for 14 days like the neovascularisation assays but the only supplement added was fibroblast growth factor so again may be different to the supplements added to the angiogenesis growth medium.

Endothelial markers were used as negative controls in the macrophage maturation experiments. Whilst the macrophage maturation markers were unchanged by high glucose culture, the early endothelial marker vWF was significantly downregulated. Furthermore the expression level in low glucose cultured cells was comparable to mature endothelial cells. The plasticity of early monocytic precursors between endothelial and myeloid lineages has been well documented (Li et al., 2011, Rehman et al., 2003, Shi et al., 2014). The reduced expression of one of the genes expressed early in endothelial differentiation in cells in diabetic conditions may be indicative of reduced endothelial potential. This would fit the reduced endothelial progenitor cell counts in diabetic wounds (Kuliszewski et al., 2013, Awad et al., 2005).(Lombardo et al., 2012). However, in diabetes plasma and endothelia cell levels of vWF protein are increased, potentially in response to angiopathic damage (Kessler et al., 1998). Furthermore, the expression of vWF does not appear to be glucose dependent, suggesting the downregulation I observed in high glucose RAW cells is a myeloid specific response (Porta et al., 1991).

Diabetic macrophages show no significant difference in macrophage maturation across three in vitro models of diabetes. This differs from other reports of diabetes impairing macrophage maturation. Differences were seen in the activation of diabetic macrophages, with genetic markers of activation suggesting an elevated activation in

106

response to both classical and alternative stimuli. With inflammation occurring early in the healing process this could contribute to the excessive inflammatory response seen in diabetic non-healing wounds. An in vitro neovascularisation assay using these activated macrophages reported no effects of either diabetes or activation state. This differs to other reports of the effects of non-diabetic activated macrophages upon similar in vitro angiogenesis assays and the effects of diabetes upon angiogenesis in diabetic wounds. In the RAW cells a mixed population of monocyte and macrophage cells is observed. The endothelial gene vWF was significantly downregulated in the high glucose cultured samples compared to the low glucose cultured cells. vWF is an early marker of endothelial differentiation and may be indicative of endothelial potential in the less mature monocytic cells. This potential monocytic-endothelial transdifferentiation has been proposed as a mechanism in multiple pathologies where there is an imbalance between inflammation and tissue growth.

107

4 Myeloid to endothelial transdifferentiation to promote wound healing

In the previous chapter a decrease in expression of vWF was observed in the RAW 264.7 macrophage cell line when cultured in high glucose conditions. This was of note due to the plasticity of monocytic and endothelial lineages. Transdifferentiation between monocytic and endothelial lineages has been well characterised. The adult haematopoietic stem cell (HSC) population is thought to originate via transdifferentiation from the dorsal aorta endothelium, the haemangioblast (Lancrin et al., 2009, Swiers et al., 2013, Padron-Barthe et al., 2014, Gordon-Keylock and Medvinsky, 2011, de Bruijn et al., 2002). Overexpression of C/EBPα in Xenopus during primitive myelopoiesis expands the haematopoietic compartment converting hematopoietic cells to myeloid progenitor (Chen et al., 2009c, Costa et al., 2008) . Culture of CD14+ human monocytes in endothelial conditions upregulates the expression of multiple markers of endothelial lineage and promotes endothelial like tube forming potential (Schmeisser et al., 2001, Fernandez Pujol et al., 2000). Co-culture of endothelial progenitor cells (EPCs) with mesenchymal stem cells may cause them to acquire a monocytic phenotype (Shi et al., 2014)

EPCs are thought to originate from multiple sites including the bone marrow and vascular lining (Rehman et al., 2003, Asahara et al., 1999). Likely to be a heterogeneous population, EPCs can be categorised into subtypes based on their behaviour in in vitro culture (Hur et al., 2004). Immature, monocytic early EPCs (eEPCs) appear early in the culture of blood mononuclear cells on endothelial promoting substrates, whereas mature late EPCs (lEPCs) expressing more endothelial markers appear after weeks of serial culture.

Transdifferentiation between myeloid and endothelial cell fate has been proposed as a mechanism to treat multiple pathologies where there is an excess of one cell type such as metastatic transition tumours (Gao et al., 2008, Asahara et al., 1999), or hyper inflammation (Hazra et al., 2013, Mace et al., 2009). The downregulation of vWF in high glucose cultures fits this established narrative of reduced EPC populations in diabetes. I

108

was hypothesised that conversion of a proportion of the excessive inflammatory cell population to endothelial lineage cells could rescue the resolution of diabetic chronic wounds by reducing inflammation and increasing the number of pro-healing endothelial progenitor cells.

A bioinformatics comparison of human monocytic and endothelial cells was used to identify transcription factors expressed to a significantly higher level in the endothelial sample. Gene expression and protein transduction techniques were then assessed for their suitability to test these transcription factors for their transdifferentiating potential. The pleiotrophic growth factor pleiotrophin was used as a positive control for these tests. Finally, these techniques would be used to attempt to convert monocytic cell lines to an endothelial lineage using the identified transcription factors. 4.1 Identification of novel genes that may induce myeloid to endothelial transdifferentiation

A previous member of our research group Ian O’Neill used comparative genomics to attempt to identify transcription factors that could be exploited for myeloid to endothelial transdifferentiation. Microarray data from a comparison between human monocytes, eEPCs, lEPCs and mature endothelial cells (Accession# GSE20283) was analysed, which was originally published to suggest the monocytic nature of eEPCs and the endothelial nature of lEPCs (Medina et al., 2010). Differential gene expression analysis between the the eEPC and lEPC data sets was performed with the Limma R package and genes with a greater than 1.5 fold change in expression between the data sets to p<0.05 identified (Smyth, 2004).

From the two microarray data sets, 5557 significantly differentially expressed genes were identified. Of these, 2946 were expressed higher in the lEPC population. DAVID clustering was used to select for transcription factors (GO:0003700) from the list of genes and the annotation clusters for neovascularisation selected (Huang et al., 2007). Nine transcription factor genes were significantly upregulated in the lEPC dataset and found in the neovascularisation annotation cluster (Table 4.1). An overview of the links to neovascularisation for these genes is given (Table 4.2).

109

Table 4.1 Neovascularisation transcription factor cluster

Annotation Cluster 12, Enrichment Score: 3.18 Term Count PValue Genes GO:0001568~blood 9 2.68E-05 TBX1, ID1, FOXC1, SOX18, MEOX2, TBX1, HEY2, vessel development CITED2, FOXO1A, NR2F2 GO:0001944~vasculature 9 3.18E-05 TBX1, ID1, FOXC1, SOX18, MEOX2, TBX1, HEY2, development CITED2, FOXO1A, NR2F2 GO:0048514~blood 8 8.00E-05 TBX1, ID1, FOXC1, SOX18, MEOX2, TBX1, HEY2, vessel morphogenesis CITED2, NR2F2 GO:0001525 4 3.70E-02 TBX1, ID1, SOX18, MEOX2, TBX1 ~angiogenesis GO:0016477~cell 5 4.78E-02 TBX1, ID1, FOXC1, TBX1, NR2F1, NR2F2 migration

The second most enriched annotation cluster for transcription factors, significantly upregulated in the late endothelial progenitor cell sample set, was process associated with neovascularisation. The five gene ontology (GO) sets consisted of the same nine transcription factors.

Table 4.2 Functional summary of putative pro-neovascularisation transcription factor

Gene Roles References CITED2 Null mutation embryonic lethal: cardiac defects, laterality defects, (Bamforth et al., (Mrg1, adrenal agenesis, neural crest defects, exencephaly, delayed 2001, Lopes Floro p35srj) development of placenta, liver, lung, eye and gonads. et al., 2011, Cited2 conditional null cornea show impaired corneal healing. Bhattacharya et al., Downregulated in aged tendon stem/progenitor cells that show 1999, Freedman et reduced proliferative potential. al., 2003, Agrawal Maintenance of adult haematopoietic stem cells as co-factor of CBP. et al., 2008, Lou et Repress transcription of HIF-dependent genes, counterintuitive al., 2011, Chen et when HIF promotes angiogenesis. al., 2009b, Zhou et Induced by HIF proteins in intervertebral disks where suppresses al., 2010) VEGF expression. Implicated in classical activation of macrophages, again counterintuitive to promoting angiogenesis. FOXC1 Expressed in eye, cardiovascular endothelial and mesenchymal cells, (Kume et al., 2001, (Fkhl7) urogenital system and skeletal bone from embryonic development. Lehmann et al., Regulates expression of FOXO1a in the eye, required to survive 2003, Berry et al., oxidative stress. 2008, Seo et al., Regulates expression of TBX1 during heart morphogenesis, 2006, Seo and stimulates cell proliferation. Kume, 2006, Porter Specification of arterial fate in antagonism to NR2F2. Lymphatic et al., 2005) sprouting. Upregulated by TIMP-1, a promoter of wound healing and angiogenesis. FOXO1a Organogenesis, mediation of insulin signalling, tumourigenesis and (Kousteni, 2011, angiogenesis. Furuyama et al., Failed cardiovascular morphogenesis in null mice. Null endothelial 2004, Matsukawa cells do not respond normally to VEGF. Shorter vessels lacking et al., 2009, smooth muscle.

110

FOXO1 signalling induced by TGF-β and VEGF-A. Siqueira et al., Induced by TGF-β in diabetic wounds driving pro-inflammatory and 2010) pro-apoptosis genes. HEY2 Peripheral nervous system patterning. (Leimeister et al., (Hesr1, Zebrafish orthologue implicated in development of aorta and 1999, Zhong et al., Chf1) arterial venous speciation of the vascular endothelial cells, 2001, Hayashi and promoting arterial fate. As such linked to FOXC1 activity. Kume, 2008, Partial inhibition of Dll4 reduces Hey2 expression and improves neo- Trindade et al., angiogenesis. 2012, Weijers et Upregulated in proliferating endothelial cells. al., 2010) ID1 Loss of Id genes ablates neovascularisation and bone marrow EPC (Ruzinova et al., populations. 2003, Ruzinova and Id1 and Id3 double knockouts die of cardiac defects during gestation Benezra, 2003, Qiu and show delayed healing of wounds with defective angiogenesis. et al., 2011, Zhao Promotes cell growth, proliferation and dedifferentiation. et al., 2011, Sikder Promotes migration and tubulogenesis in vitro. et al., 2003) Associated with angiogenesis in tumours.

MEOX2 Expressed in smooth muscle and endothelial cells of the (Gorski and Leal, (Gax) cardiovascular system. 2003, Chen and Down regulates the cells responses to pro-angiogenic signals. But Gorski, 2008) low levels may be pro-angiogenic. Down regulated by miR-130a in cells stimulated by pro-angiogenic factors. NR2F2 Promotes tumour angiogenesis through regulation of Tie2 in (Qin et al., 2010a, (Coup- endothelial cells. Qin et al., 2010b, TFII) Loss of expression impairs angiogenesis. You et al., 2005) Forms part of the arterial, venous, lymphatic sorting network with FoxC1, Notch and Prox1. Promotes venous state. SOX18 Transiently expressed in vascular endothelial cells during their (Herpers et al., differentiation. 2008, Darby et al., Induced during neovascularisation in wound healing and 2001, Young et al., tumourigenesis. 2006, Irrthum et Required for differentiation of lymphatic endothelial cells. al., 2003) Linked to defects in human vascular and lymphatic vessels, and hair follicles. TBX1 Highly expressed in adult hair follicle stem cells. (Trempus et al., Required for cardiac and craniofacial skeletal muscle 2007, Guo et al., morphogenesis. 2011, Jerome and Null mice present parathyroid hypoplasia, craniofacial Papaioannou, abnormalities, cleft palate and malformed cardiac outflow tract. 2001)

Summary of published functional roles associated with blood vessel growth for the nine transcription factor genes in the neovascularisation annotation cluster.

111

4.1.1 Expression of putative pro-neovascularisation transcription factors in myeloid and endothelial cells

Representative cell cultures for monocytic and endothelial lineages were used to validate the nine transcription factors identified in the EPC comparative genomics experiment. For human cells the monocytic leukemia cell line THP-1, and human umbilical vein endothelial cells (HUVECs) were selected. In both cases the reference genes were validated in qPCRs of two cell types using equal amounts of cDNA input to ensure equal expression and two references used to minimise any remaining variability. Relative gene expression levels for the nine vascular associated transcription factors were assessed with RT-qPCR on cDNA from confluent cell cultures (Figure 4.1). Five of the nine transcription factors tested were expressed significantly higher in the endothelial cells compared to the myeloid cells (FOXC1, FOXO1, ID1, NR2F2, SOX18), two showed no difference in expression (HEY2, TBX1) and two were significantly decreased in the endothelial cells compared to the myeloid cells (CITED2, MEOX2).

As a second set of samples, murine cell lines were also tested for their expression of these transcription factors. RAW 264.7 cells were used as a monocytic sample and primary mouse brain microvascular endothelial (bEnd5) cells for the endothelial sample. Likewise cDNA was generated from RNA isolated from confluent cell cultures and analysed by RT-qPCR for expression of the putative pro-neovascularisation transcription factors (Figure 4.2). Eight of the transcription factors were expressed significantly higher in the endothelial cells (Foxc1, Foxo1, Hey2, Id1, Meox2, Nr2f2, Sox18, Tbx1) with only Cited2 significantly decreased in those cells.

These results taken together identified FOXC1, FOXO1, ID1, NR2F2, and SOX18 as strong initial candidates to test for myeloid to endothelial cell reprogramming. Transfection of these monocytic cell lines with gene expression vector constructs for these genes would be used to assay their reprogramming potential.

112

CITED2 FOXC1 FOXO1 0.004 0.0010 0.0015 ** 0.0008 0.003 ** 0.0010 0.0006 0.002 0.0004 0.0005 0.001 * 0.0002

0.000 0.0000 0.0000

-1 C -1 C -1 C P E P E P E H V H V H V T U T U T U H H H HEY2 ID1 MEOX2 6.0 10-7 0.0015 0.000020 ** 0.000015

4.0 10-7 0.0010 ession

r 0.000010

xp e -7 e 2.0 10 0.0005

v 0.000005

a el R 0 0.0000 0.000000 **

-1 C -1 C -1 C P E P E P E H V H V H V T U T U T U H H H NR2F2 SOX18 TBX1 0.0005 0.0015 0.0015

0.0004 * 0.0010 ** 0.0010 0.0003

0.0002 0.0005 0.0005 0.0001

0.0000 0.0000 0.0000

-1 C -1 C -1 C P E P E P E H V H V H V T U T U T U H H H Sample Figure 4.1 Expression of putative pro-neovascularisation transcription factors in human cell cultures Expression levels of mRNAs for the nine neovascularisation associated transcription factors in monocytic THP-1 cells and human umbilical vein endothelial cells (HUVECs). Expression levels normalised to reference genes RPL37a and ACTB. Asterisk denotes a significant difference between the two cell types, * p<0.05, ** p<0.01.

113

Cited2 Foxc1 Foxo1 1.0 0.020 0.15

0.8 ** 0.015 * 0.10 0.6 0.010 0.4 0.05 0.005 0.2 **

0.0 0.000 0.00 5 5 5 W d W d W d A n A n A n R E R E R E b b b Hey2 Id1 Meox2 0.03 0.08 0.08 *** * 0.06 0.06 *

ession 0.02 r

0.04 0.04 e e Exp

v 0.01 ti

a 0.02 0.02

el R

0.00 0.00 0.00 5 5 5 W d W d W d A n A n A n R E R E R E b b b Nr2f2 Sox18 Tbx1 0.4 *** 0.05 0.004 ** 0.04 *** 0.3 0.003 0.03 0.2 0.002 0.02 0.1 0.001 0.01

0.0 0.00 0.000 5 5 5 W d W d W d A n A n A n R E R E R E b b b Sample Figure 4.2 Expression of putative pro-neovascularisation transcription factors in murine cell cultures Expression levels of mRNAs for the nine neovascularisation associated transcription factors in murine monocytic RAW cells and endothelial bEnd5 cells. Expression levels normalised to reference genes H2a and Hsp90. Asterisk denotes a significant difference between the two cell types, * p<0.05, ** p<0.01, *** p<0.001.

114

4.1.2 Development of cell culture assay for myeloid to endothelial reprogramming

To test for genes that promote myeloid to endothelial reprogramming THP-1 cell cultures were to be transfected with gene expression constructs via Nucleofection. A previously published method optimised for THP-1 cells was adopted (Schnoor et al., 2009). THP-1 cells were selected for these assays for their monocytic nature, compared to the predominately macrophage RAW cells. This should mean there are closer on the transcriptomic landscape to, and more amenable for transdifferentiation to, endothelial cells. The pleiotropic growth factor pleiotrophin has been published with the potential to drive myeloid to endothelial reprogramming (Sharifi et al., 2006, Chen et al., 2009a) so was used to test our Nucleofection protocols. Murine Pleiotrophin was cloned into the pcDNA3.1/myc-His A expression construct for THP-1 Nucleofection (Methods 2.2.6). The Nucleofection kit pmaxGFP control vector was used as a transfection reporter.

THP-1 cells Nucleofected with either pmaxGFP or a combination of pcDNA3.1/myc-His pleiotrophin and pmaxGFP plasmids expressed the eGFP reporter up to four days post treatment (Figure 4-3, A). By eight days only 10% of the THP-1 cells were still GFP positive and cell counts at 24 hours and four days post Nucleofection suggested a constant loss of expression over time (Figure 4-3, B). This was in parallel with the cells losing their clear round appearance under phase microscopy in a manner suggestive of cell death. This was confirmed by counts of live and dead cells at four days post Nucleofection with only 20% of the cells identified as live (Figure 4-3, C). No significant difference was observed between the control and pleiotrophin treated samples suggesting that the cell death was a product of the transfection method rather than specific to pleiotrophin expression. Expression of pleiotrophin in the Nucleofected samples at day four was confirmed by quantitative real-time PCR for murine pleiotrophin RNA (Figure 4-3, E) and Western blotting for the c-Myc and 6-His tags on the recombinant pleiotrophin protein (Figure 4-3, F). Pleiotrophin RNA was still detectable in some of the samples eight days post Nucleofection but was highly variable, probably due to the ongoing cell death.

115

A B Day 1 GFP positive cells 80 ***

eGFP al cells

t 40

o t

20 % % of

0 tn

P 1 4 8 Day C Live cells 30 Day 4

al cells

o t

eGFP 10 % % of

0 P n F t G P e

tn Treatement P D Hs Pleiotrophin 8.0 10 -7 **

Day 8 6.0 10 -7

4.0 10 -7

2.0 10 -7 eGFP

-1 C P E H V T U H Sample

tn E Ms Pleiotrophin P 0.003

ession 0.002 r

F xp e

1 2 e *

v 0.001 ti

Myc a

el R 1 eGFP His 0.000 2 Ptn 0 4 8 Day eGFP Ptn

116

Figure 4.3 Nucleofection of THP-1 monocytes with pleiotrophin THP-1 cells Nucleofected with pmaxGFP (eGFP) control vector or pcDNA3.1/myc-His pleiotrophin expression vector with eGFP. A) Representative images of THP-1 cells one, four and eight days post Nucleofection. Scale bar 100µm. B) Proportions of GFP positive cells at one, four and eight days. C) Proportions of live cells at four days post transfection in Nucleofected THP-1 cells. D) Expression levels of human pleiotrophin mRNA in THP-1 cells and HUVECs. E) Expression levels of murine pleiotrophin mRNA in THP-1 cells before, and four and eight days post Nucleofection. Expression levels normalised to reference genes RPL37a and 18S. F) Western blotting of protein extracts from THP-1 cells one day post Nucleofection. Primary antibodies targeted the c-Myc and 6-His tags of the expression construct. Asterisk denotes a significant difference between the two cell types, * p<0.05, *** p<0.001.

Gene expression analysis was to be used to screen treated cells for evidence of transdifferentiation process. CEBPa, SPI1(PU.1), SPIB and RUNX1 were selected as transcription factors key to the early specification of the myeloid lineage from early progenitors (Chen et al., 2009d, Fukuchi et al., 2006, Orkin and Zon, 2008, Rhodes et al., 2005, Huang et al., 2008). These were expressed in untreated THP-1 samples and would be expected to become downregulated as transdifferentiating cells exit the myeloid lineage as evidenced by their absence in HUVEC samples (Figure 4.4, A). CD68 is associated with myeloid differentiation and was included as a control for macrophage maturation (in humans there is also some expression in mature endothelial cells) (Gottfried et al., 2008). Tests with unstimulated THP-1 cells, THP-1 cells stimulated to macrophage differentiation with PMA and HUVEC samples confirmed marker expression, as expression levels of each of these genes were significantly higher in THP- 1 cells than HUVECs and greatly higher in macrophage differentiated THP-1 cells (Figure 4.4, B). PROM1(CD133), PECAM1 and vWF were used as markers of endothelial lineage. PROM1 in particular is expressed in the late EPCs that are the target cell of monocytic to endothelial differentiation (Mace et al., 2009, Peichev et al., 2000). PROM1 would be expected to peak as cells entered the late EPC state whilst PECAM1 and vWF will increase with endothelial phenotype. This was mirrored in the THP-1 and HUVEC reference samples (Figure 4.4, C) These genes were next used to test the pleiotrophin Nucleofected cells for evidence of endothelial reprogramming.

117

A CEBPa SPI1 SPIB 0.06 0.025 ** 0.0015 ** 0.020 ** 0.04 0.0010 0.015

0.010 0.02 0.0005 0.005

0.00 0.000 0.0000

ession -1 C -1 C -1 C r P E P E P E H V H V H V

xp T U T U T U

H H H

e v

ti B

a RUNX1 CD68 el R *** * 0.020 * 0.0015

0.015

ession 0.0010 r

0.010 xp

e e

v 0.0005 ti

0.005 a

el R

0.000 0.0000

-1 C -1 A C P E P M E H V H P V T U T U H -1 H P H T Sample Sample C PROM1 PECAM1 vWF 0.000005 0.5 0.15 ** * 0.000004 0.4

ession 0.10

r 0.000003 0.3

xp e

e 0.000002 0.2

v 0.05

ti a

el 0.000001 0.1 R

0.000000 0.0 0.00

-1 C -1 C -1 C P E P E P E H V H V H V T U T U T U H H H Sample Figure 4.4 Markers for monocytic to endothelial transdifferentiation A) Expression levels of markers for monocytic lineage in THP-1 cells and HUVECs. B) Expression levels of macrophage maturation marker CD68 in THP-1 cells, THP-1 PMA differentiated macrophages and HUVECs. C) Expression levels of endothelial lineage markers in THP-1 cells and HUVECs. Expression levels normalised to reference genes RPL37a and ACTB except for CD68 where only RPL37a was a suitable reference (not equally expressed between THP-1 and HUVEC). Asterisk denotes a significant difference between the cell types in Mann-Whitney tests, * p<0.05, ** p<0.01, *** p<0.001. Six experimental repeats.

118

4.1.3 Testing Pleiotrophin Nucleofection for endothelial reprogramming

The Pleiotrophin test Nucleofection experiments did not survive for a period of time to ideally test for transdifferentiation but it was possible that there was enough time to detect the early signs of reprogramming with the downregulation of the myeloid lineage associated transcription factors and the upregulation of the EPC associated PROM1. The RNA samples extracted from the THP-1 cells four days post Nucleofection with his/myc- tagged pleiotrophin were assayed for their expression of these genes by qRT-PCR. The day 8 samples were also checked but were highly variable in both the experimental and pmaxGFP control samples from the excessive cell death as previously described.

Four days after Nucleofection there was little to no change in the expression levels of the markers tested, with only the myeloid specific transcription factor SPI1 significantly upregulated in the Pleiotrophin treated samples compared to untreated controls (Figure 4.5, A). However, there was no significant difference in the expression of SPI1 between the pmaxGFP transfected controls and the pleiotrophin treated samples suggesting that at least part of this upregulation is a response to the Nucleofection process rather than pleiotrophin expression. CD68 (p<0.15) also appeared to trend towards upregulation with Pleiotrophin expression (Figure 4.5, B). Critically there is no significant upregulation of the endothelial progenitor marker PROM1 or the more mature endothelial markers PECAM1 and vWF (Figure 4.5, C). The unchanged endothelial marker expression, together with the slight increase in some myeloid markers, suggested that transdifferentiation was not occurring in these experiments over the timeframe available.

Whilst longer exposure to Pleiotrophin may still drive endothelial transdifferentiation as reported elsewhere, in this Nucleofection experimental design poor cell survival in concurrence with the loss of reporter expression over time made this assay unreliable.

119

A CEBPa SPI1 0.004 0.0020 * 0.003 0.0015

0.002 0.0010

0.001 0.0005

0.000 0.0000

ession 0 P n 0 P n r y F t y F t a G P a G P D e 4 D e 4 4 y 4 y y a y a a D a D

e e Exp D D

v SPIB RUNX1 ti

a 0.00010 0.0005 el R 0.00008 0.0004

0.00006 0.0003

0.00004 0.0002

0.00002 0.0001

0.00000 0.0000 0 P n 0 P n y F t y F t a G P a G P D e 4 D e 4 4 y 4 y y a y a a D a D B D Sample D CD68 0.006

ession 0.004

e e

v 0.002

el R 0.000 0 P n y F t a G P D e 4 4 y y a a D D Sample

C PROM1 PECAM1 vWF 4.0 10-7 0.0010 6.0 10-7

0.0008 3.0 10-7

ession -7

r 4.0 10 0.0006 xp -7 e 2.0 10

e 0.0004 v 2.0 10-7 ti -7 a 1.0 10

0.0002

el R 0 0.0000 0 0 0 P tn P tn 0 P tn y F y F P y F P a G P a G a G e 4 D e 4 D e 4 D y y 4 y 4 a 4 a y a y y a D a D a D D D Sample D Figure 4.5 THP-1 monocytes Nucleofected with Pleiotrophin transdifferentiation assay A) Expression levels of markers for monocytic lineage in THP-1 cells pre-Nucleofection and four days post Nucleofection with pmaxGFP control plasmid (eGFP) or pcDNA3.1/myc-His Pleiotrophin plasmid (Ptn). B) Expression levels of macrophage maturation marker CD68 in the same samples. C) Expression levels of endothelial lineage markers in the three samples. Expression levels normalised to reference genes RPL37a and ACTB. Asterisk denotes a significant difference between samples in two way ANOVA, * p<0.05. Three experimental repeats.

120

4.1.4 Testing pleiotrophin protein treatment for endothelial reprogramming

A final test of Pleiotrophin driven transdifferentiation was performed by treating THP-1 monocytes with recombinant protein. This method had been reported to drive transdifferentiation in THP-1 cells when pre-treated with M-CSF (Chen et al., 2009a). The expected benefit of this method was the avoidance of the cell death triggered by the Nucleofection protocol facilitating longer courses of treatment. A switch from murine to human Pleiotrophin was also made in case the mismatch with the human THP-1 cells was also a cause of the negative results. Cells were treated with Pleiotrophin or with an initial treatment of M-CSF followed by Pleiotrophin for up to eight days on Collagen I coated plates.

THP-1 cells were harvested at four and eight days into the treatment and assayed for expression of the transdifferentiation markers as before (Figure 4.6). Similar to the Nucleofection experiments there was no conclusive evidence that pleiotrophin was driving endothelial transdifferentiation aside from a significant upregulation of vWF at day eight in the pleiotrophin treated sample compared to the untreated cells (Figure 4.6, C). However, this upregulation was not significant in the M-CSF + pleiotrophin sample, counter to the previously published results. The other endothelial markers PROM1 and PECAM1, and the myeloid markers (CEBPa, SPI1, SPIB, RUNX1 and CD68) were all unchanged (Figure 4.6, A and B). Culture upon Collagen I may even have had a greater effect upon the gene expression profile of the cells, irrespective of treatment, with CEBPa and PECAM1 decreasing with time in culture and SPI1, PROM1 and vWF increasing.

The results of this work suggested that Pleiotrophin was not a suitable positive control for endothelial transdifferentiation in these experiments. Nucleofection of THP-1 cells was also detrimental to cell survival and unsuitable for the long term expression required to test genetic reprogramming.

121

A SPI1 CEBPa ** 0.10 * 0.03 * *** 0.08 0.02 0.06

0.04 0.01 0.02

ession 0.00 0.00 r 0 4 8 0 4 8

e e Exp SPIB RUNX1 v

ti 0.0008 0.020

el R 0.0006 0.015

0.0004 0.010

0.0002 0.005

0.0000 0.000 0 4 8 0 4 8 B Day CD68 0.04

0.03

ession r

0.02

e e Exp

v ti

a 0.01

el R

0.00 0 4 8 Day vWF * C PROM1 PECAM1 ** 1.5 10 -6 ** 0.020 0.000006 * * * 0.015 -6

ession 1.0 10 0.000004 r

0.010 e e Exp

v 5.0 10 -7 0.000002 ti

a 0.005

el R

0 0.000 0.000000 0 4 8 0 4 8 0 4 8 Day UT PTN M-CSF + PTN Figure 4.6 THP-1 monocytes cultured with recombinant human pleiotrophin transdifferentiation assay A) Expression levels of markers for monocytic lineage in THP-1 cells grown on Collagen I without treatment (UT), with recombinant human Pleiotrophin (PTN), or a combination of recombinant human Macrophage Colony Stimulating Factor and Pleiotrophin (M-CSF + PTN). B) Expression levels of macrophage maturation gene CD68 in the same samples. C) Expression of endothelial lineage markers in the treated samples. Cultures were observed over eight days. Expression levels normalised to reference genes RPL37a and ACTB. Asterisk with bracket denotes a significant difference in comparisons of the treatments at one time point by paired T test, * p<0.05, ** p<0.01, p<0.001. Three experimental repeats.

122

4.2 Hoxa3 and protein transduction

Protein addition of the putative pro-neovascularisation transcription factors to the culture medium was not a viable method of testing their reprogramming potential due to their inability to cross the membrane barriers into the cell and the nucleus beyond. Unlike these genes, the Hox protein family of transcription factors possesses the well documented property of traversing phospholipid bilayers, facilitating application to cells as a protein (Mahdipour et al., 2011, Chatelin et al., 1996, Auvray et al., 2012, Balayssac et al., 2006). Hoxa3 treatment of diabetic wounds has been reported to redress the balance of inflammatory to regenerative bone marrow derived cells within the wound, improving healing outcome (Mace et al., 2009). Improved proliferation and migration of keratinocytes, and enhanced angiogenesis are some or all of the effectors of the Hoxa3 treatment but it is not known if Hoxa3 has any effect upon the monocytes and macrophages within the wound (Mace et al., 2005). I hypothesised that reprogramming of the excessive inflammatory cell population to an endothelial state could be one of the mechanisms by which Hoxa3 rescues diabetic wound healing.

4.2.1 Hoxa3 expression in monocytes and endothelial cells

Hoxa3 was marginally upregulated in the eEPC to lEPC comparison (1.024 times in lEPC, p value 0.0375) from which the putative pro-neovascularisation transcription factors were selected and promotes endothelial cell fate in haemogenic endothelium during embryonic development (Iacovino et al., 2011). Expression levels in models of diabetes were measured by qRT-PCR (Figure 4.7, A). In the RAW cell model Hoxa3 (p<0.06) trended towards higher expression in high glucose cultures compared to low glucose cultures, but in murine bone marrow derived macrophages Hoxa3 expression trended towards decreased in diabetic derived cells (p<0.06). This decrease was significant in rat derived cells. Hoxa3 expression was also measured in activated mouse macrophages cultured from non-diabetic and diabetic bone marrow cells (Figure 4.7, B). No significant difference in expression levels was observed between non-diabetic and diabetic samples of non-activated, classically activated and alternatively activated cells. Hoxa3 was seen to be significantly decreased in classically activated macrophages compared to those polarised to an alternatively activated state. Hoxa3 RNA levels were also significantly

123

higher in the endothelial cell line bEnd.5 compared to RAW monocyte/macrophages (Figure 4.7, C).

All together, elevated Hoxa3 expression in lEPCs and the endothelial cell line tested may be indicative of the potential to drive monocytic to endothelial transdifferentiation.

4.2.2 Hoxa3 protein transduction in monocytes/macrophages

Protein transduction using Hoxa3 membrane traversal potential was used to test its capacity to promote myeloid to endothelial transdifferentiation to avoid the problems encountered with Nucleofection as previously described. The third helix of the Hox protein family homeodomain facilitates the uptake of Hox proteins by target cells crossing both the plasma and nuclear membranes (Derossi et al., 1994). Addition of the immunoglobulin κ-light chain to the N-terminus of Hoxa3 enhances secretion and a C- terminal mCherry tag facilitates visualisation of protein production and uptake localisation (Amsellem et al., 2003, Dupont et al., 2007). Expression constructs for SP.mCherry and SP.Hoxa3.mCherry were transfected into 293T cells using the calcium phosphate method and expression was tracked by mCherry fluorescence (Figure 4.8, A). Conditioned medium from transfected 293T cells was harvested and added to RAW cell cultures for 24 hour. The treated cells were then fixed and assayed for protein uptake by immunostaining for the mCherry tag. Optical sections through the cells suggested that tagged protein was reaching of nucleus in SP.Hoxa3.mCherry treated cells. Whereas the nuclear staining was weaker in the SP.mCherry treated samples and all staining absent in cells treated with media from untransfected 293T cells (Figure 4.8, B).

124

A Hoxa3 RAW cells Mouse macrophages Rat macrophages 0.00008 0.00020 1.5

0.00006 0.00015

ession 1.0 r

0.00004 0.00010 * e e Exp

v 0.5 ti

a 0.00002 0.00005

el R

0.00000 0.00000 0.0 e e b s s b b b o o D D D D c c N N lu lu G G w h o ig L H B C Mouse activated macrophages Cell Lines

0.0005 0.015 NDb 0.0004 Db ***

ession 0.010 r 0.0003 * e e Exp 0.0002

v 0.005 ti

a *

el 0.0001 R

0.0000 0.000

d d d W 5 te te te d a a a A n v v v R E ti ti ti b c c c -a a a n ly ly o l e a v N ic i s t s a a rn l e C lt A Sample Figure 4.7 Expression profile of Hoxa3 in diabetic macrophages A) Expression levels of Hoxa3 in RAW monocyte/macrophages grown in low or high glucose medium, mouse and rat bone marrow derived macrophages from non-diabetic (NDb) and diabetic (Db) animals. B) Expression levels of Hoxa3 in mouse classically activated and alternatively activated macrophages from non-diabetic and diabetic animals. C) Expression levels of Hoxa3 in RAW and bEnd.5 cell lines. Expression levels normalised to H2a and Hsp90 in RAW and mouse macrophage samples, and H2a, Actb and Hsp90 in rat macrophage samples. Asterisk denotes a significant difference between samples in paired T-test (low or high glucose, NDb or Db, RAW or bEnd.5). For activation state asterisk denotes a significantly lower expression in the classically activated samples in two way ANOVA. * p<0.05, *** p<0.001. All five experimental repeats.

125

A SP.mCherry SP.Hoxa3.mCherry B Untreated SP.mCherry SP.Hoxa3.mCherry

Phase + mCher

r mCher

DAPI mCh DAPI mCh DAPI mCh mCh mCh mCh 1 2 3 4 5 6 7 kDa 28

98 62 49

PlauR Cdc42 0.06 ** 0.6

ession 0.04 0.4

r e e Exp

v 0.02 0.2

el R

0.00 0.0 T y y T y y 3 rr rr 3 rr rr 9 e e 9 e e 2 h h 2 h h C C C C .m .m .m .m 3 3 P a P a S x S x o o .H .H P P S S Treatment Figure 4.8 Treatment of RAW cells with SP.Hoxa3.mCherry protein transduction Production of conditioned medium in 293T cells and uptake by RAW cells. A) Expression of mCherry marker in 293T cells transfected with SP.mCherry and SP.Hoxa3.mCherry. Scale bar 200 µm. B) Confocal microscopy through the nucleus of RAW macrophages in conditioned medium from untransfected, SP.mCherry and SP.Hoxa3.mCherry transfect 293T cells. Scale bar 10 µm. C) Western blots for mCherry tag in samples from SP.mCherry and SP.Hoxa3.mCherry treated cells. Lane 1, Conditioned medium, lane 2, conditioned medium treated RAW cell cytoplasmic fraction, lane 3, treated RAW cell nuclear fraction, lane 4, treated RAW cell whole lysate, lane 5, untreated RAW cell whole lysate, lane 6, transfected 293T feeder cells, lane 7, untransfected 293T cells. D) Expression levels of Plaur and Cdc42 in RAW macrophages in conditioned medium from untransfected 293T cells (293T), or 293T cells transfected with SP.mCherry or SP.Hoxa3.mCherry. Expression levels normalised to H2a and Hsp90. Asterisk denotes a significant difference between treatments, ** p<0.01. Representative images of three experimental repeats. Gene expression five experimental repeats.

126

Protein extracts were collected from the 293T and RAW cells and probed on Western blot for the same mCherry tag (Figure 4.8, C). Protein could be detected in the 293T cells and conditioned medium of both the SP.mCherry and SP.Hoxa3.mCherry transfected samples, whereas the RAW cells treated with SP.Hoxa3.mCherry had stronger bands in the whole cell and cytosolic samples than RAW cells treated with SP.mCherry. A weak band appeared to be present in the nuclear fraction of SP.Hoxa3.mCherry treated RAW cells. Target genes for Hoxa3 in monocytes and macrophages are not know but two genes, Plaur/uPar and Cdc42 were amongst those upregulated in human microvascular endothelial cells (HMECs) transfected with a HOXA3 expression plasmid (Mace et al., 2005). Expression of Plaur was significantly increased in RAW cells treated with SP.Hoxa3.mCherry with double the relative expression of the SP.mCherry treated controls (Figure, 4.8, D). Expression of Cdc42 was not significantly different, although showed a trend (p<0.10) of upregulation.

Overall multiple tests of RAW cells with SP.Hoxa3.mCherry conditioned medium suggested that the RAW cells were taking in the expressed Hoxa3.mCherry protein and that this protein was able to alter the gene expression patterns of these cells. Longer term cultures with conditioned medium were then used to test the potential to drive transdifferentiation of RAW cell cultures.

4.3.2 Testing Hoxa3 protein transduction for endothelial reprogramming

RAW cells were cultured for eight days in media supplemented daily with conditioned medium containing either SP.mCherry or SP.Hoxa3.mCherry. Samples were collected at two, four and eight days of culture and assayed for expression of myeloid and endothelial markers. Two of the three monocytic markers tested, CD14 and Itgam were significantly upregulated at four days into the culture (Figure 4.9, A). None of the endothelial markers tested were significantly different between the SP.mCherry and SP.Hoxa3.mCherry treated at any of the time points tested (Figure 4.9, B).

These results suggest that Hoxa3 is not able to drive monocytic to endothelial transdifferentiation over the treatment time tested. The upregulation of two monocytic genes may instead be indicative of Hoxa3 driven changes in macrophage maturation.

127

A CD14 Emr1 Itgam 1.0 0.20 0.4

0.8 0.15 0.3 **

ession * r 0.6 0.10 0.2

0.4 e e Exp v 0.05 0.1

ti 0.2 a

el 0.0 0.00 0.0 R 2 4 8 2 4 8 2 4 8 y y y y y y y y y a a a a a a a a a D D D D D D D D D B Hoxa3 Prom1 0.0020

10-6 0.0015 10-6 SP.mCherry 0.0010 10-6 SP.Hoxa3.mCherry 0.0005 10-7

0.0000 0 ession

r 2 4 8 2 4 8 y y y y y y a a a a a a D D D D D D

e e Exp CD34 Cdh5 vWF

v 0.0005 0.00015 0.00015

ti a

el 0.0004 R 0.00010 0.00010 0.0003

0.0002 0.00005 0.00005 0.0001

0.0000 0.00000 0.00000 2 4 8 2 4 8 2 4 8 y y y y y y y y y a a a a a a a a a D D D D D D D D D Timepoint Figure 4.9 RAW cells grown with SP.Hoxa3.mCherry conditioned medium A) Relative expression of monocytic genes CD14, Emr1 and Itgam in RAW cells in SP.mCherry or SP.Hoxa3.mCherry conditioned medium over eight days. B) Relative expression of endothelial genes Hoxa3, Prom1, CD34, Cdh5 and vWF in RAW cells in SP.mCherry or SP.Hoxa3.mCherry conditioned medium over eight days. Expression levels normalised to H2a and Hsp90. Asterisk denotes a significant difference between treatments in paired T-tests of that time point, * p<0.05, ** p<0.01. Five experimental repeats. 4.3 Discussion

The original hypothesis of attempting to drive monocytic to endothelial transdifferentiation with transcription factor expression was unable to be fully tested in these experiments. Nucleofection was selected for the stable expression of potential reprogramming factors due to its reported high transfection efficiency and previous use with THP-1 monocytes (Mellott et al., 2013). Viral transfection can also generate stable

128

transgene expression in cell lines but was not selected due to the concerns of its use in clinical settings including toxicity and oncogenesis (Thomas et al., 2003). Oncogenic transformation is of particular concern if monocytic to endothelial is in the future to be used in inflammatory pathologies such as diabetic wounds because a similar transformation is already associated with tumour metastasis (Gao et al., 2008, Zhang et al., 2006).

Despite multiple rounds of optimisation the Nucleofection protocol was never able to produce stable transfected cells that persisted beyond eight days of culture in sufficient numbers. Adjustments were made to the composition of the manufacturers recommended recovery medium and the human monocyte Nucleofection kit, rather than the THP-1 cell line Nucleofection kit, was used to improve the transfection efficiency as reported (Schnoor et al., 2009). These alterations were an improvement over pilot studies using the THP-1 cell line kit and provided recovery medium but were not sufficient to rescue the high rate of cell death. Since these experiments have been run, further optimisations of electroporation have been published that might improve the experimental outcome, especially with respect to cell survival. Treatment of human umbilical cord mesenchymal stromal cells with a Rho-associated coiled-coil kinase (ROCK) inhibitor during the Nucleofection protocol significantly improved the survival of the cells when tested at 24 and 48 hours post Nucleofection (Mellott et al., 2014). Unfortunately longer time points were not reported.

The intended positive control gene pleiotrophin did not drive monocytic to endothelial transdifferentiation in both Nucleofection transfection of THP-1 cells and treatment with recombinant protein. Expression of pleiotrophin in THP-1 cells by a retroviral transfection conferred the expression of endothelial genes and the transformed cells were able to contribute to angiogenesis (Sharifi et al., 2006). The use of retroviral transformation, or of murine rather than human pleiotrophin open reading from might have caused the different response in my experiments.

To account for the difference in species between effector (murine pleiotrophin) and target cell (human THP-1 cells) human recombinant pleiotrophin was also tested. The experimental protocol previously reported to drive endothelial transdifferentiation in human CD14+ blood monocytes was followed (Chen et al., 2009a). Again my

129

experiments were unable to replicate the endothelial transdifferentiation reported. THP-1 cells may respond differently to the treatment, however THP-1 cells were treated with the conditioned medium of multiple myeloma cells that secreted pleiotrophin and still significantly upregulated endothelial markers and integrated into vascular structures. A similar study has since been published using THP-1 cells grown on gelatine and treated with recombinant human pleiotrophin (Palmieri et al., 2015).

Pleiotrophin expression is induced by PDGF, which is released at the wound site (Li et al., 1992). Pleiotrophin is also upregulated at sites of cerebral ischemia in local macrophages, astrocytes and endothelial cells (Yeh et al., 1998). However, expression of pleiotrophin in cutaneous excisional wounds at seven days post wounding showed no significant difference between non-diabetic and diabetic animals (Mace, personal communication). Pleiotrophin was considered only as a positive control and not a potential factor for the treatment of diabetic wounds due to its multiple reported links to tumorigenesis (Papadimitriou et al., 2009). NIH 3T3 cells transfected with pleiotrophin expression plasmids formed tumour growths when injected into nude mice (Chauhan et al., 1993). Patient multiple myeloma cells secrete pleiotrophin into the patient serum, with levels of serum pleiotrophin correlating with clinical outcome (Yeh et al., 2006).

Nine transcription factors associated with neovascularisation were identified in a gene expression comparison of early and late EPC populations. The expression of these genes was assessed in murine and human monocytic and endothelial cells, where FOXC1, FOXO1, ID1, NR2F2, and SOX18 were significantly upregulated in the endothelial samples. Whilst I was unable to develop an experimental system to test if any of these genes could promote monocyte to endothelial transdifferentiation they are still of future interest. FOXC1 has been implicated in the regulation of the vasculature in multiple tissues. In the developing mouse brain Foxc1 expression is required for the formation of functional vessels, with haemorrhaging occurring in Foxc1 loss of function mutants (Prasitsak et al., 2015, Siegenthaler et al., 2013). However, deletion of Foxc1 in the neural crest lineage lead to aberrant vessel growth suggesting that Foxc1 plays a role in both proangiogenic and anti-angiogenic processes (Koo and Kume, 2013). Foxc1 and

130

Foxc2 is thought to regulated the specification of arterial fate and antagonise arterial fate promotion by Nr2f2 (Seo et al., 2006).

Foxo1 is thought to be a mediator of vessel growth. Foxo1 null embryonic stem cells grown in vessel forming conditions develop shorter vessels than their wild type counterparts and lack smooth muscle. This may be due to errors in cytoskeletal remodelling in these cells (Park et al., 2009). The induction of vessel growth through FoxO1 signalling is controlled upstream by the growth factors TGF-β and VEGF-A (Matsukawa et al., 2009). The phenotype of the Foxo1 null mouse is due to altered endothelial cell function, with endothelial cell specific ablation phenocopying the global Foxo1 knockout (Dharaneeswaran et al., 2014). However, similar to Foxc1, antiangiogenic effects of Foxo1 have also been reported (Kim et al., 2015). Foxo1 is also expressed in M2 macrophages (but not M1 macrophages) and is implicated in the effects of hyperglycaemia with reduced Foxo1 expression promoting M1 activation (Chung et al., 2015). Foxo1 is upregulated in wound healing. Partial deletion of Foxo1 accelerates wound healing by enhancing keratinocyte migration, reducing granulation tissue formation and decreasing collagen deposition, and reduced inflammation. Foxo1 is significantly upregulated in inflamed fibrotic scars. No change in angiogenesis was observed in the wound tissue of Foxo1 partial knockdowns (Mori et al., 2014).

Id1 is strongly implicated in angiogenesis (Ruzinova et al., 2003, Gao et al., 2008). Id1 and Id3 double knockouts exhibit delayed cutaneous wound healing and impaired angiogenesis (Zhao et al., 2011). Id1 is also a negative regulator of haematopoiesis as might be expected for a transcription factor that could promote monocyte to endothelial transdifferentiation (Hong et al., 2011). In small cell lung cancer expression of Id1 and Id3 is intimately linked to tumour growth by promoting angiogenesis and inhibiting cell death (Chen et al., 2014). In TGF-β stimulated differentiation of human embryonic stem cells (hESCs) to endothelia cells Id1 expression is inhibited, whereas during tube formation Id1 expression was required (Huan et al., 2015). Multiple isoforms of Id1 may have differential roles in the regulation of cell proliferation. The Id1b isoform has been reported to inhibit cell cycle progression and proliferation, whereas Id1a promotes proliferation (Manrique et al., 2015).

131

Nr2f2 is selectively expressed in venous endothelial cells (Pereira et al., 1999). Transcriptional regulation by Nr2f2 is linked to promoting tumour angiogenesis through the regulation of Angiopoietin1/Tie2 signalling upon endothelial cells, with loss of expression inhibiting both angiogenesis in the adult and the growth of tumours due to impaired vascularisation (Qin et al., 2010a). It is also thought to regulate the endothelial cell led sprouting of new vessels in tumour angiogenesis through the repression of VEGFR-1 expression (Qin et al., 2010b). A balance between Notch, Prox1 and Nr2f2 signalling is thought to regulate the sorting of arterial, venous and lymphatic endothelial cells, with Nr2f2 promoting venous differentiation (You et al., 2005, Xu et al., 2015). Gene expression comparison between normal and NR2F2 knockdown in human endometrial stromal cells suggests that NR2F2 inhibits inflammation (Li et al., 2013b). This would fit the role of driving monocytic to endothelial transdifferentiation.

Sox18 expression is implicated in the maturation of the vasculature. It is transiently expressed in vascular endothelial cells during their differentiation (Herpers et al., 2008, Samant et al., 2011) and induced during the angiogenic phase of wound healing or tumourigenesis (Darby et al., 2001). Sox18 null tumours grow slower and present fewer vessels based on endothelial markers. A similar inhibition of vessel/tube formation is observed with perturbation of Sox18 levels in vitro (Young et al., 2006). Sox18 is important for the generation of endothelial sheets with barrier function, inducing the expression of the tight junction associated protein Claudin-5. This is an important step in the maturation of vessels (Fontijn et al., 2008).

It is noted that these genes are expressed at different points in endothelial and vascular development. Foxc1 and Foxo1 may have differential effects promoting vasculogenesis during embryonic development but inhibiting angiogenesis in mature tissues. Id1 is reported to be inhibited during the differentiation of EPCs but required for tubule formation. Sox18 promotes the maturation of tubules to functional vessels and interplay between Foxc1, Foxo1 and Nr2f2 regulates arterial and venous fate. To successfully convert monocytes to endothelial cells a combination of these transcription factors may be required.

Hoxa3 was considered as a potential transcription factor to drive endothelial reprogramming due to its higher expression in endothelial cells and alternatively

132

activated macrophages, reduced expression in diabetic macrophages and links to angiogenesis in wound healing. Skin grafts containing Hoxa3 secreting fibroblasts accelerate wound closure and increased vascular density (Kuo et al., 2014). Expression of Hoxa3 in endothelial cells increases their migration, and in diabetic wounds the rescue of Hoxa3 expression also improves angiogenesis and wound closure (Mace et al., 2005). Bone marrow derived monocytes and endothelial progenitors are likely to both contribute to the diabetic phenotype and Hoxa3 driven rescue alters the populations of these cells (Mace et al., 2009). Hoxa3 also regulates the phenotypes of haematopoietic progenitor cells. Hoxa3 expression restricts the domain of the haemogenic endothelium by promoting endothelial lineage and inhibiting the specification of haematopoietic progenitors (Iacovino et al., 2011). Haematopoietic progenitors transfected with a Hoxa3 expression construct favour the differentiation of the pro-angiogenic Gr- 1+CD11b+ myeloid population. This myeloid subset is reduced from diabetic derived haematopoietic progenitors and Hoxa3 treatment rescues the diabetic defect (Mahdipour et al., 2011).

RAW cells were treated with Hoxa3 protein to test for endothelial reprogramming. Uptake of the mCherry tagged Hoxa3 protein was tracked by Western blotting and immunofluorescence for the mCherry tag. This system has been used for Hoxb4 and Hoxa3 protein transduction in haematopoietic progenitors (Amsellem et al., 2003, Mahdipour et al., 2011). Confocal imaging showed both the SP.mCherry and SP.Hoxa3.mCherry in the cytoplasmic space of the RAW macrophage. Uptake of the SP.mCherry control protein was unexpected because it lacks an uptake peptide like the one in Hox family proteins. RAW cells are known to exhibit phagocytic behaviour and this may be the cause of intracellular localisation of SP.mCherry (Caracciolo et al., 2015, Tian et al., 2015, Zhu et al., 2014). Optical sections through the nucleus suggested that only SP.Hoxa3.mCherry was entering the nucleus as observed in haematopoietic progenitors. Western blotting for the mCherry tag from nuclear extracts was not as strong as was observed in haematopoietic progenitors. If phagocytosis was the cause of the cytoplasmic SP.mCherry, phagocytosis may also be removing some of the SP.Hoxa3.mCherry protein from the conditioned medium reducing the amount reaching

133

the nucleus. Immunoprecipitation of the mCherry tag could be used to increase the sensitivity of the Western blot analysis.

Downstream genes of Hoxa3 in the macrophage are not known. In human microvascular endothelial cells constitutively expressing HOXA3 the genes CDC42 and PLAUR were upregulated compared to untreated cells (Mace et al., 2005). A significant upregulation of Plaur and a trend towards upregulation of Cdc42 compared to the SP.mCherry control suggested that these genes also respond to Hoxa3 transcriptional activity in macrophages, and that the SP.Hoxa3.mCherry protein was transcriptionally active. Whilst the SP.mCherry and SP.Hoxa3.mCherry treated samples were significantly different, RAW cells treated with conditioned medium from untransfected 293T cells were similar to the SP.Hoxa3.mCherry treated samples. This suggests that something within the conditioned medium itself alters the RAW cell phenotype. Potential causes would be that cytotoxic stress from calcium phosphate transfection releases extra cell signals into the conditioned medium that stimulated the RAW cells (Mostaghaci et al., 2015). Calcium phosphate transfection with plasmids lacking the secretion peptide tag could be used to test that this effect is from the transfection not the secreted protein. Alternatively, if phagocytosis is occurring that could be altering the cell phenotype. Treatment with phagocytosis inhibitors could be used to test if this is occurring and may also increase the amount of Hoxa3 protein reaching the nucleus (Sbarra and Shirley, 1963, Hong et al., 2013).

SP.Hoxa3.mCherry treatment of up to eight days did not induce the expression of endothelial genes. However two control macrophage markers CD14 and Itgam were upregulated at four days of treatment. This may be indicative of a promotion of macrophage maturation with more expression positive macrophages or an overall increase in the per cell expression. Increased expression of CD14 and CD11b was induced in a phosphatidylinositol 3-kinase (PI3K) dependent manner in monocytes treated with calcitriol, a PI3K stimulating hormone (Moeenrezakhanlou et al., 2008). In comparisons of the non-diabetic and type 2 diabetic wound macrophage populations decreased expression of CD11b and Emr1 was used to characterise the impaired maturation of diabetic macrophages (Bannon et al., 2013).

134

Nine pro-neovascular transcription factors were identified in comparative gene expression analysis between early and late EPCs. Five of the genes, FOXC1, FOXO1, ID1, NR2F2, and SOX18, were expressed significantly higher in validation comparisons of monocytic and endothelial cells. Pleiotrophin was used as a control gene for the development of a cell transfection protocol to test the potential of these genes to drive monocyte to endothelial transdifferentiation but was unable to replicate previous reports of this activity. The expression of Hoxa3 in macrophages and endothelial cells was assessed. Hoxa3 expression was decreased in diabetic macrophages and down regulated in classically activated macrophages. As previously reported Hoxa3 expression was high in endothelial cells. Protein transduction of RAW macrophages was performed to test if reprogramming of macrophages to an endothelial phenotype contributed to Hoxa3 rescue of diabetic wounds. No change in endothelial markers was observed, but CD11b and CD14 were upregulated by four days of Hoxa3 treatment suggesting an effect upon the macrophage phenotype.

135

5 Hoxa3 protein transduction alters the macrophage phenotype in non-diabetic and diabetic macrophages

This main aim of this chapter was to investigate the direct effects of Hoxa3 expression upon macrophage phenotype and function, and how this may correlate to the pro- healing effects of Hoxa3 expression in the wound. In the previous chapter SP.Hoxa3.mCherry conditioned medium was shown to be internalised by murine RAW macrophage cells and alter the expression of potential Hoxa3 target genes but did not drive endothelial transdifferentiation as originally hypothesised. However, expression of two macrophage markers was upregulated after four days of treatment with the SP.Hoxa3.mCherry conditioned medium. Previously, enforced expression of Hoxa3 within the diabetic wound was shown to accelerate healing and reduce the excessive inflammatory cell population but any direct effects of Hoxa3 upon macrophages were unknown (Mace et al., 2009, Mace et al., 2005). To investigate if Hoxa3 could drive changes in the macrophage phenotype, which may have contributed to the wound healing observations, the in vitro macrophage culture system was used for the targeted treatment of macrophages with SP.Hoxa3.mCherry. The excessive immature, pro- inflammatory macrophage population in diabetic wounds was rescued by the Hoxa3 whole wound treatment, so the Hoxa3 treated macrophages were assessed for any changes in their maturation and activation potential by the expression of genetic markers. The deficit in neovascularisation was also rescued by the Hoxa3 whole wound treatment, so the Hoxa3 treated macrophages were applied to a model of vascular growth to assess their effects upon neovascularisation. 5.1 Hoxa3 treatment of bone marrow derived macrophages

Two macrophage markers, CD14 and Itgam, were upregulated in RAW cells grown with SP.Hoxa3.mcherry conditioned medium. Diabetic wounds contain an excess of immature inflammatory macrophages that is thought to become resolved with the

136

Hoxa3 expression vector treatment of those wounds (Mirza and Koh, 2011, Mace et al., 2009). Driving the differentiation of these macrophages may be one of the mechanisms through which Hoxa3 expression contributes to the rescue of wound healing.

5.1.1 Effects of SP.Hoxa3.mCherry conditioned medium treatment upon differentiating mouse macrophages

Bone marrow cells were harvested and differentiated to macrophages with M-CSF supplemented medium over seven days as previously described. From day three onwards, 4mL of SP.Hoxa3.mCherry conditioned medium was added daily to the developing cultures for uptake into the myeloid cells as they matured. This timeframe was selected based on four days of treatment being the time point where differential CD14 and Itgam expression was observed in RAW cells and that days two to three was when cells with a macrophage morphology began to appear in the differentiation cultures (Figure 3.2).

After seven days of culture the average cell density of non-diabetic derived mouse macrophages showed no significant difference between those supplemented with SP.mCherry conditioned medium and those with the SP.Hoxa3.mCherry medium (Figure 5.1, B). Gene expression analysis of these cells was performed by quantitative real time PCR. A significant increase in the potential Hoxa3 responsive gene Plaur was not seen in this experiment but did appear to trend (p<0.15) towards upregulated expression (Figure 5.1, C). Markers of macrophage maturation (CD14, Emr1 and Itgam) were also checked for their response to SP.Hoxa3.mCherry treatment and no significant difference was seen in any of the genes tested (Figure 5.1, D). Similarly the surface protein level of these markers was assessed by FACS analysis. For all markers a single discrete population was observed and the median fluorescence of the markers did not show a significant change with treatment, although F4/80 did trend (p<0.08) towards increased medium fluorescence after SP.Hoxa3.mCherry culture (Figure 5.1, E).

The same protein transduction experiments were also performed during the culture of bone marrow derived macrophages isolated from type 2 diabetic mice (Figure 5.2, A). As previously described the diabetic macrophages may have impaired maturation and thus could amplify any positive effects treatment with SP.Hoxa3.mCherry might have.

137

Similar to the non-diabetic cells no significant change in final cell counts was observed between SP.mCherry and SP.Hoxa3.mCherry treatments (Figure 5.2, B). Plaur again may be trending (p<0.15) towards increased expression in the SP.Hoxa3.mCherry treated cells but was not significant (Figure 5.2, C). Any SP.Hoxa3.mCherry driven increase in macrophage maturation markers did appear to be more pronounced in the diabetic macrophages, with Emr1 significantly increasing in expression and Itgam (p<0.09) possibly trending towards increase (Figure 5.2, D). This increase was not matched in the cell surface fluorescence with F4/80 significantly decreased and all markers showed a single positive population that did not change in size between treatments (Figure 5.2, E).

Overall these results suggest that Plaur expression is downstream of Hoxa3 transcription factor activity in macrophages. They may also indicate that SP.Hoxa3.mCherry protein transduction promotes the expression of macrophage maturation associated genes during in vitro differentiation. This effect can be most prominently seen in maturation impaired diabetic derived macrophages.

Figure 5.1: Macrophage maturation marker expression in non-diabetic mouse macrophages with SP.Hoxa3.mCherry conditioned medium A) Phase microscopy images of mouse bone marrow derived macrophages supplemented with SP.mCherry or SP.Hoxa3.mCherry conditioned medium for the last four days of their differentiation. Yellow scale bar equivalent to 100 µm. B) Cell counts as millions per 10cm plate after differentiation culture. C) Expression levels of Hoxa3 and Plaur in treated cells. D) Expression levels of macrophage marker mRNA, normalised to reference genes H2a and Hsp90. Relative expression normalised to the SP.mCherry control. E) Cell surface marker fluorescence analysis. Median fluorescence normalised to the SP.mCherry control. No measurements were significantly different between treatments. Cell counts and gene expression seven samples, surface marker analysis five samples.

138

A B Cell Count

500 y r 400

300 .mCher

P 200 S

Million Cells 100

y 0 r a3. y y x rr rr

o e e h h C C

.H .m .m 3 P P a mCher S x S o .H P S C Hoxa3 Plaur

2.0 1.5

ession r 1.5

xp 1.0 e

1.0

0.5

e e mRNA

v ti

a 0.0 0.0

el y y y y rr rr rr rr R e e e e h h h h C C C C .m .m .m .m 3 3 P a P a S x S x o o .H .H P P S S

D CD14 Emr1 Itgam s

r 1.5 1.5 1.5

ession

k r

xp 1.0 1.0 1.0

e tion mar

a 0.5 0.5 0.5

e e mRNA

a ti

a 0.0 0.0 0.0 M

el y y y y y y rr rr rr rr rr rr R e e e e e e h h h h h h C C C C C C .m .m .m .m .m .m 3 3 3 P a P a P a S x S x S x o o o .H .H .H P P P S S S

E CD14 F4/80 CD11b

s 1.5 1.5 1.5

e k

escence 1.0 1.0 1.0

r ace mar f 0.5 0.5 0.5

Cell sur 0.0 0.0 0.0 Median Fluo Median y y y y y y rr rr rr rr rr rr e e e e e e h h h h h h C C C C C C .m .m .m .m .m .m 3 3 3 P a P a P a S x S x S x o o o .H .H .H P P P S S S Treatment 139

A B Cell Count

500 y r 400

300 .mCher

P 200 S

Million Cells 100

y 0 r a3. y y x rr rr

o e e h h C C

.H .m .m 3 P P a mCher S x S o .H P S C Hoxa3 Plaur

2.5 1.5 ession r 2.0

xp 1.0 e 1.5

1.0 0.5

e e mRNA 0.5

v ti

a 0.0 0.0

el y y y y rr rr rr rr R e e e e h h h h C C C C .m .m .m .m 3 3 P a P a S x S x o o .H .H P P S S

D CD14 Emr1 Itgam s

r 1.5 1.5 1.5 e

ession *

k r

xp 1.0 1.0 1.0

e tion mar

a 0.5 0.5 0.5

e e mRNA

a ti

a 0.0 0.0 0.0 M

el y y y y y y rr rr rr rr rr rr R e e e e e e h h h h h h C C C C C C .m .m .m .m .m .m 3 3 3 P a P a P a S x S x S x o o o .H .H .H P P P S S S

E CD14 F4/80 CD11b

s 1.5 1.5 2.0

e k 1.5

escence 1.0 1.0 r

1.0 ace mar f 0.5 0.5 0.5

Cell sur 0.0 0.0 0.0 Median Median Fluo y y y y y y rr rr rr rr rr rr e e e e e e h h h h h h C C C C C C .m .m .m .m .m .m 3 3 3 P a P a P a S x S x S x o o o .H .H .H P P P S S S Treatment 140

Figure 5.2 Macrophage maturation marker expression in type 2 diabetic mouse macrophages in SP.Hoxa3.mCherry conditioned medium A) Phase microscopy images of type 2 diabetic mouse bone marrow derived macrophages treated with SP.mCherry or SP.Hoxa3.mCherry conditioned medium for the last four days of their differentiation. Yellow scale bar equivalent to 100 µm. B) Cell counts as millions per 10cm plate after differentiation culture. C) Expression levels of Hoxa3 and Plaur in treated cells. D) Expression levels of macrophage marker mRNA, normalised to reference genes H2a and Hsp90. Relative expression normalised to the SP.mCherry control. E) Cell surface marker fluorescence analysis. Median fluorescence normalised to the SP.mCherry control. Asterisk denotes a significant difference between treatments in T-test. * p<0.05. Cell counts and gene expression seven samples, surface marker analysis five samples.

5.1.2 Effects of SP.Hoxa3.mCherry conditioned medium treatment upon differentiating rat macrophages

The decreased macrophage maturation marker expression was not seen in type 1 diabetic rat derived cells, however they did show a significant decrease in Hoxa3 expression compared to their non-diabetic cohorts so were also tested with the SP.Hoxa3.mCherry conditioned medium treatment. As per the mouse macrophage cultures, bone marrow cells were cultured for seven days in M-CSF supplemented growth medium and 4mL of conditioned medium added daily from day three. Similar to the mouse cells, the visual appearance of the treated non-diabetic rat macrophages did not appear to differ and there was no significant change in the number of cells per treated plate (Figure 5.3, A, B). Plaur was significantly upregulated in the SP.Hoxa3.mCherry treated cells but Hoxa3 was significantly downregulated (Figure 5.3, C). One of the macrophage maturation markers, CD14, was significantly upregulated with SP.Hoxa3.mCherry treatment whereas Itgam was unchanged and Emr1 trended (p<0.07) towards downregulation (Figure 5.3, D). In Streptozotocin induced type 1 diabetic rat macrophages there was similarly minimal change in morphological appearance and cell density when treated with SP.Hoxa3.mCherry conditioned medium (Figure 5.4, A, B). Similar to the diabetic mouse cells, Plaur and Hoxa3 were significantly upregulated in the diabetic rat cells treated with SP.Hoxa3.mCherry (Figure 5.4, C). Of

141

the macrophage markers Itgam was significantly upregulated whilst CD14 and Emr1 were unchanged (Figure 5.4, D). FACS analysis was not performed with these samples so it cannot be determined if this is an increase per cell expression or an increase in positive cells.

These results further support Plaur as a reporter of Hoxa3 activity in macrophages of multiple species. The expression of macrophage maturation markers was less clear in rat cells compared to macrophages grown from mouse bone marrow but CD14 and Itgam upregulation do suggest that SP.Hoxa3.mCherry treatment has an effect on the macrophage phenotype.

Figure 5.3 Macrophage maturation marker expression in non-diabetic rat macrophages in SP.Hoxa3.mCherry conditioned medium A) Phase microscopy images of rat bone marrow derived macrophages supplemented with SP.mCherry or SP.Hoxa3.mCherry conditioned medium for the last four days of differentiation. Yellow scale bar equivalent to 100 µm. B) Cell counts as millions per 10 cm plate after differentiation culture. C) Expression levels of Hoxa3 and Plaur in treated cells. D) Expression levels of macrophage marker mRNA, normalised to reference genes H2a, ActB and Hsp90. Asterisk denotes a significant difference between treatments in T-test. * p<0.05. Cell counts and gene expression six samples.

142

A B Cell Count

y r 40

30 .mCher

P 20

S Million Cells

10 y

r 0

a3. x ry ry o r r e e h h

.H C C

P .m .m mCher P 3 S a S x o .H P S C Hoxa3 Plaur

1.5 2.0 ession

r * 1.5

xp 1.0 e

* 1.0

0.5

e e mRNA

v ti

a 0.0 0.0

el y y y y rr rr rr rr R e e e e h h h h C C C C .m .m .m .m 3 3 P a P a S x S x o o .H .H P P S S

D CD14 Emr1 Itgam s

r 2.0 1.5 1.5

ession k r * 1.5

xp 1.0 1.0 e

1.0 tion mar

a 0.5 0.5 e

r 0.5

e e mRNA

a ti

a 0.0 0.0 0.0 M

el y y y y y y rr rr rr rr rr rr R e e e e e e h h h h h h C C C C C C .m .m .m .m .m .m 3 3 3 P a P a P a S x S x S x o o o .H .H .H P P P S S S

Treatment

143

A B Cell Count

y r

.mCher P

S 20

Million Cells y

r 0

a3. x ry ry o r r e e h h

.H C C

P .m .m mCher P 3 S a S x o .H P S C Hoxa3 Plaur

2.5 * 2.5 ession

r 2.0 2.0 * xp e 1.5 1.5

1.0 1.0

e e mRNA 0.5 0.5

v ti

a 0.0 0.0

el y y y y rr rr rr rr R e e e e h h h h C C C C .m .m .m .m 3 3 P a P a S x S x o o .H .H P P S S

D CD14 Emr1 Itgam s

r 1.5 1.5 2.0

ession

k r 1.5 *

xp 1.0 1.0 e

1.0 tion mar

a 0.5 0.5 e

r 0.5

e e mRNA

a ti

a 0.0 0.0 0.0 M

el y y y y y y rr rr rr rr rr rr R e e e e e e h h h h h h C C C C C C .m .m .m .m .m .m 3 3 3 P a P a P a S x S x S x o o o .H .H .H P P P S S S

Treatment

144

Figure 5.4 Macrophage maturation marker expression in type 1 diabetic rat macrophages in SP.Hoxa3.mCherry conditioned medium A) Phase microscopy images of rat bone marrow derived macrophages from Streptozotocin induced type 1 diabetic rats treated with SP.mCherry or SP.Hoxa3.mCherry conditioned medium for the last four days of their differentiation. Yellow scale bar 100 µm. B) Cell counts as millions per 10 cm plate after differentiation culture. C) Expression levels of Hoxa3 and Plaur in treated cells. D) Expression levels of macrophage marker mRNA, normalised to reference genes H2a, Actb and Hsp90. Asterisk denotes a significant difference between treatments in T-test. * p<0.05. Cell counts and gene expression six samples.

5.1.3 Cx3cr1 expression analysis for further insights into SP.Hoxa3.mCherry protein transduction and macrophage maturation

To further investigate this potential effect of Hoxa3 protein treatment upon macrophage maturation the chemokine receptor Cx3cr1 was also assayed for its expression in the previous experiments. Cx3cr1 is expressed in phagocytic inflammatory cells including microglia and macrophages and in many tissues the increase in Cx3cr1 expression can be used to track the maturation of myeloid cells (Little et al., 2014, Crane et al., 2014, Segerer et al., 2002, Hughes et al., 2002). Cx3cr1 expression in diabetic derived mouse macrophages was not significantly different from non-diabetic macrophages, fitting the similar expression of the other maturation markers previously tested (Figure 5.5, A). In SP.Hoxa3.mCherry treatments expression levels of Cx3cr1 supported the trends seen with other macrophage markers. Expression was significantly higher in RAW cells grown with SP.Hoxa3.mCherry conditioned medium four days into treatment (Figure 5.5, B), the same time point of increased CD14 and Itgam expression. In SP.Hoxa3.mCherry treated non-diabetic derived mouse bone marrow macrophages there was a trend (p<0.15) towards increased Cx3cr1 expression (Figure 5.5, C) and a significant upregulation in type 2 diabetic mouse macrophages with SP.Hoxa3.mCherry (Figure 5.5, D). Again these fit the trend towards increased macrophage markers in non- diabetic cells and the stronger indication with significant upregulation of some of the markers in diabetic cells.

145

Cx3cr1 gene expression appears to be a useful reporter for the differentiation of myeloid cells to macrophages in an in vitro model similarly to its published use in vivo. Upregulation in murine cells treated with SP.Hoxa3.mCherry further supports the conclusion that Hoxa3 in differentiating macrophages promotes maturation as observed by the expression of multiple markers of macrophage lineage. This may rescue the impaired maturation seen in diabetic wounds and contribute to the rescue of impaired diabetic cutaneous healing.

A B Mouse macrophages RAW macrophages 0.4 0.3 * SP.mCherry SP.Hoxa3.mCh

0.3 ession

ession 0.2

r r xp

xp 0.2

e e

e e v

v 0.1 ti

ti 0.1

a a

el el R R 0.0 0.0 b b 2 4 8 D D y y y N a a a D D D C D NDb mouse macrophages Db mouse macrophages 1.5 1.5

* ession

ession 1.0 1.0

r r

xp xp

e e

e e v

v 0.5 0.5

ti ti

a a

el el R R 0.0 0.0

y h y h rr C rr C e e h .m h .m 3 3 C a C a .m x .m x P o P o S .H S .H P P S S Sample Figure 5.5: Cx3cr1 expression in mouse macrophages in SP.Hoxa3.mCherry conditioned medium Expression of Cx3cr1 in A) non-diabetic and type 2 diabetic mouse bone marrow derived macrophages, B) RAW macrophages in SP.mCherry or SP.Hoxa3.mCherry conditioned medium for two, four and eight days, C) non-diabetic mouse bone marrow derived macrophages in conditioned medium for the last four days of their differentiation, D) type 2 diabetic mouse bone marrow derived macrophages in conditioned medium for the last four days of their differentiation. All sample expression relative to reference genes H2a and Hsp90. Asterisk denotes a significant difference between samples in paired T-Tests, * p<0.05. Seven experimental repeats per bone marrow macrophage pairing, five per RAW macrophages.

146

5.2 Activation potential in bone marrow derived macrophages treated with Hoxa3 during differentiation

Comparison of the in vitro activation of bone marrow derived macrophages from non- diabetic and diabetic mice suggested that diabetic macrophages exhibit an elevated response to activation signals. The effect Hoxa3 has upon macrophage maturation may extend to altering macrophage maturation potential but my also attenuate the increased activation response to inflammatory or alternative stimuli, which could also alter diabetic wound healing outcome.

5.2.1 Activation of non-diabetic mouse macrophages treated with Hoxa3

The in vitro culture of bone marrow derived macrophages was used to test macrophage response to activation stimuli. Bone marrow cells were differentiated and treated with SP.mCherry or SP.Hoxa3.mCherry conditioned medium during the last four days of their maturation as before (5.1.1). Cultures were then stimulated to inflammatory M1 activation, alternative M2 activation or non-activated controls.

Treatment with the SP.mCherry control medium did not inhibit the response of non- diabetic derived mouse bone marrow macrophages to activation cytokines as assessed by expression of genetic markers of activation. All four classical activation genes tested (Ccl2, CD86, Nos2 and Tnf) were significantly different in the cells stimulated with classical cytokines in multi-sample variance analysis to both the non-activated controls and alternatively activated cells (Figure 5.6, B). The alternative activation genes were similarly upregulated in the alternatively stimulated cells with Chi3l3 and Mrc1 significantly different (Figure 5.6, C).

The response to activating cytokines was similar in non-diabetic macrophages treated with SP.Hoxa3.mCherry. All four classical markers were significantly higher in the classically activated cells (Figure 5.7, B) and Mrc1 and Chi3l3 were significantly

147

upregulated in the macrophages treated with alternative activation signals (Figure 5.7, C).

To assess any changes in activation potential with Hoxa3 treatment, response to each activation signal was compared between cells treated with SP.mCherry and SP.Hoxa3.mCherry. Due to multiple factors of variation being introduced between animals, conditioned medium batches, and activation cytokines experimental repeats were each normalised to the SP.mCherry sample before analysis. Treatment of non- diabetic macrophages with SP.Hoxa3.mCherry did not significantly alter the subsequent response to classical or alternative cytokines with only Hoxa3 significantly upregulated in the alternatively activated pairing (Figure 5.8). Significant differences between the SP.mCherry and SP.Hoxa3.mCherry treated samples were observed in the cells not treated with activating cytokines. Three of the four classical activation markers (Ccl2, CD86 and Tnf) were significantly upregulated (Figure 5.8, A) and the alternative activation marker Chi3l3 was significantly upreguated (Figure 5.9, B). Mrc1 (p<0.08) trended towards increased expression in the SP.Hoxa3.mCherry treated cells.

The increased activation marker expression in non-activated cells is still significantly less than that of cells treated with the corresponding activation cytokine, as previously determined by the multi-sample variance analysis for each gene, but may be indicative of the macrophages treated with SP.Hoxa3.mCherry being primed for response to activation signals. Alternatively, in the absense of per cell analysis, such as by FACS or immunoflourescence it may be that a few cells are becoming activated by the Hoxa3 treatment and therefore increasing the average expression when assessed as a population such as in the qRT-PCR analysis.

148

A Non-activated Classically activated Alternatively activated

B Classical Markers Ccl2 CD86 2.5 2.5

2.0 * 2.0 ***

1.5 1.5

1.0 1.0

0.5 0.5

0.0 0.0 ession r A A A A A A N C A N C A

e e Exp Nos2 Tnf

v 25 1.5 ti

a ***

el 20

R *** 1.0 15

10 0.5 5

0 0.0 A A A A A A N C A N C A Sample C Alternative Markers Arg1 Chi3l3 0.8 0.3 ** 0.6 0.2

0.4

0.1 0.2

0.0 0.0 ession r A A A A A A N C A N C A

e e Exp Mrc1 Tgfb1 Hoxa3

v 2.0 1.5 0.0006 ti

a ** el

R 1.5 1.0 0.0004

1.0

0.5 0.0002 0.5

0.0 0.0 0.0000 A A A A A A A A A N C A N C A N C A Sample Figure 5-6 Activation markers in non-diabetic mouse macrophages in SP.mCherry conditioned medium then polarised A) Phase microscopy of mouse bone marrow derived macrophages treated with SP.mCherry for four days then polarised with activation cytokines. Yellow scale bar 50 µm. B) Expression levels of classical activation markers. C) Expression of alternative activation markers and Hoxa3. Expression normalised to reference genes H2a and Hsp90. Asterisk denotes a significant difference between activation states when analysed by two way ANOVA. * p<0.05, ** p<0.01, *** p<0.005. Six experimental repeats.

149

A Non-activated Classically activated Alternatively activated

B Classical Markers Ccl2 CD86 2.5 * 2.5 2.0 2.0 ***

1.5 1.5

1.0 1.0

0.5 0.5

0.0 0.0 ession r A A A A A A N C A N C A

e e Exp Nos2 Tnf

v 25 2.0 ti a *** el 20 ***

R 1.5 15 1.0 10 0.5 5

0 0.0 A A A A A A N C A N C A Sample C Alternative Markers Arg1 Chi3l3 0.8 0.25 **

0.6 0.20

0.15 0.4 0.10 0.2 0.05

0.0 0.00 ession r A A A A A A N C A N C A

e e Exp Mrc1 Tgfb1 Hoxa3

v 2.5 1.5 0.0008 ti

a ***

el 2.0

R 0.0006 1.0 1.5 0.0004 1.0 0.5 0.0002 0.5

0.0 0.0 0.0000 A A A A A A A A A N C A N C A N C A Sample Figure 5-7 Activation markers in non-diabetic mouse macrophages in SP.Hoxa3.mCherry conditioned medium then polarised A) Phase microscopy of mouse bone marrow derived macrophages treated with SP.Hoxa3.mCherry for four days then polarised with activation cytokines. Yellow scale bar 50 µm. B) Expression levels of classical activation markers. C) Expression of alternative activation markers and Hoxa3. Expression normalised to reference genes H2a and Hsp90. Asterisk denotes a significant difference between activation states when analysed by two way ANOVA. * p<0.05, ** p<0.01, *** p<0.005. Six experimental repeats.

150

A Classical Markers Ccl2 CD86 3 * 4 *

3 2

1 1

ession 0 0 r NA CA AA NA CA AA

Nos2 Tnf e e Exp

v 2.0 2.5

ti ** a

el 2.0

R 1.5

1.5 1.0 1.0

0.5 0.5 SP.mCherry SP.Hoxa3.mCherry 0.0 0.0 NA CA AA NA CA AA Sample B Alternative markers Arg1 Chi3l3 2.0 4 * 1.5 3

1.0 2

0.5 1 SP.mCherry SP.Hoxa3.mCherry

ession 0.0 0 r NA CA AA NA CA AA

Mrc1 Tgfb1 Hoxa3 e e Exp

v 2.5 1.5 3

ti * a

el 2.0 R 1.0 2 1.5

1.0 0.5 1 0.5

0.0 0.0 0 NA CA AA NA CA AA NA CA AA Sample Figure 5-8 Effect of SP.Hoxa3.mCherry on activation markers in non-diabetic mouse macrophages A) Relative expression levels of classical activation markers in non-diabetic bone marrow derived macrophages treated with SP.mCherry or SP.Hoxa3.mCherry conditioned medium for four days then polarised with activation cytokines. B) Relative expression levels of alternative activation markers in bone marrow derived macrophages in conditioned medium. Expression normalised to reference genes H2a and Hsp90. Asterisk over brackets denotes significant difference between the conditioned medium treatments in paired T-tests, * p<0.05, ** p<0.01. Six experimental repeats.

151

5.2.2 Activation of type 2 diabetic mouse macrophages treated with Hoxa3

Type 2 diabetic bone marrow derived macrophages were treated with conditioned medium during their differentiation then stimulated with activating cytokines as per the non-diabetic macrophages (5.2.1). Similar to the non-diabetic cells, diabetic bone marrow derived macrophages treated with SP.mCherry responded to both classical and alternative activation cytokines as assayed by gene expression (Figure 5.9). All four classical activation markers were significantly different in the classically stimulated cells in multi-sample variance analysis (Figure 5.9, B). Two of the alternatively activated genes (Chi3l3 and Tgfb1) were significantly different in the alternatively activated samples (Figure 5.9, C).

The response to activating cytokines was similar in type 2 diabetic macrophages treated with SP.Hoxa3.mCherry. All four classical markers were significantly higher in the classically activated cells (Figure 5.10, B) and Arg1, Mrc1 and Tgfb1 were significantly upregulated in the macrophages treated with alternative activation signals (Figure 5.7, C).

152

A Non-activated Classically activated Alternatively activated

B Classical Markers Ccl2 CD86 5 ** 1.5 4 * 1.0 3

2 0.5 1

0 0.0 ession r A A A A A A N C A N C A

e e Exp Nos2 Tnf

v 15 2.5

ti a

el 2.0 ** R 10 * 1.5

1.0 5 0.5

0 0.0 A A A A A A N C A N C A Sample C Alternative Markers Arg1 Chi3l3 0.4 0.20

0.3 0.15 *

0.2 0.10

0.1 0.05

0.0 0.00 ession r A A A A A A N C A N C A

e e Exp Mrc1 Tgfb1 Hoxa3

v 0.20 1.5 2.0

a el

R 0.15 1.5 1.0 0.10 * 1.0 0.5 0.05 0.5 *

0.00 0.0 0.0 A A A A A A A A A N C A N C A N C A Sample Figure 5-9 Activation markers in type 2 diabetic mouse macrophages in SP.mCherry conditioned medium then polarised A) Phase microscopy of mouse bone marrow derived macrophages treated with SP.mCherry for four days then polarised with activation cytokines. Yellow scale bar 50 µm. B) Expression levels of classical activation markers. C) Expression of alternative activation markers and Hoxa3. Expression normalised to reference genes H2a and Hsp90. Asterisk denotes a significant difference between activation states when analysed by two way ANOVA. * p<0.05, ** p<0.01. Eight experimental repeats.

153

A Non-activated Classically activated Alternatively activated

B Classical Markers Ccl2 CD86 4 1.5 * * 3 1.0

0.5 1

0 0.0 ession r A A A A A A N C A N C A

e e Exp Nos2 Tnf v 15 2.0

ti ** a

el **

R 1.5 10

1.0

5 0.5

0 0.0 A A A A A A N C A N C A Sample C Alternative Markers Arg1 Chi3l3 0.3 0.10

* 0.08 0.2 0.06

0.04 0.1 0.02

0.0 0.00 ession r A A A A A A N C A N C A

e e Exp Mrc1 Tgfb1 Hoxa3

v 0.3 1.5 1.5 ti

a *

el R 0.2 1.0 1.0 * 0.1 0.5 0.5

0.0 0.0 0.0 A A A A A A A A A N C A N C A N C A Sample Figure 5-10 Activation markers in type 2 diabetic mouse macrophages in SP.Hoxa3.mCherry conditioned medium then polarised A) Phase microscopy of mouse bone marrow derived macrophages treated with SP.Hoxa3.mCherry for four days then polarised with activation cytokines. Yellow scale bar 50 µm. B) Expression levels of classical activation markers. C) Expression of alternative activation markers and Hoxa3. Expression normalised to reference genes H2a and Hsp90. Asterisk denotes a significant difference between activation states when analysed by two way ANOVA. * p<0.05, ** p<0.01. Eight experimental repeats.

154

A Classical Markers Ccl2 CD86 2.0 2.0 * 1.5 1.5

1.0 1.0

0.5 0.5

ession 0.0 0.0 r NA CA AA NA CA AA

Nos2 Tnf e e Exp

v 2.5 * 1.5 ti a * *

el 2.0 R 1.0 1.5

1.0 0.5 0.5 SP.mCherry SP.Hoxa3.mCherry 0.0 0.0 NA CA AA NA CA AA Sample B Alternative markers Arg1 Chi3l3 2.0 2.0

1.5 1.5 * 1.0 1.0

0.5 0.5 SP.mCherry SP.Hoxa3.mCherry

ession 0.0 0.0 r NA CA AA NA CA AA

Mrc1 Tgfb1 Hoxa3 e e Exp

v 1.5 1.5 1.5

el R 1.0 1.0 1.0

0.5 0.5 0.5

0.0 0.0 0.0 NA CA AA NA CA AA NA CA AA Sample Figure 5-11 Effect of SP.Hoxa3.mCherry on activation markers in type 2 diabetic mouse macrophages A) Relative expression levels of classical activation markers in type 2 diabetic bone marrow derived macrophages treated with SP.mCherry or SP.Hoxa3.mCherry conditioned medium for four days then polarised with activation cytokines. B) Relative expression levels of alternative activation markers in diabetic bone marrow derived macrophages in conditioned medium. Expression normalised to reference genes H2a and Hsp90. Asterisk over brackets denotes significant difference between the conditioned medium treatments in paired T-tests, * p<0.05. Six experimental repeats.

155

Response to each activation signal was compared between cells treated with SP.mCherry and SP.Hoxa3.mCherry, again with each pairing normalised to the SP.mCherry treated sample to reduce experimental variation. Treatment of diabetic derived macrophages with SP.Hoxa3.mCherry did not reduce the expression of activation associated genes as predicted. Two of the classical activation markers (Ccl2 and Nos2) were significantly increased in cells that were treated with SP.Hoxa3.mCherry then classically activated (Figure 5.11, A). Nos2 was also significantly upregulated in alternatively activated cell treatment pairs and Tnf significantly downregulated. The only significant change in alternative activation markers was a downregulation of Chi3l3 in SP.Hoxa3.mCherry treated with cells that remained non-activated (Figure 5.11, B). Arg1 (p<0.18) and Chi3l3 (p<0.13) potentially trended towards downregulation in alternative activated treatment pairs. The activation treatment is thought to induce a near homogenous population of activated cells, however in the absence of a per cell analysis it is possible that this could alternatively be indicative of an increase in the number of activated cells with classical stimuli and a decrease with alternative activation stimuli.

Overall not all of the differentially expressed genes between the SP.mCherry and SP.Hoxa3.mCherry treated pairings conform to simple uniform alteration in activation potential. However, three of the four classical markers are significantly increased or trending towards increased expression in both activation states whilst there is no indication of increased alternative activation in diabetic derived cells treated with SP.Hoxa3.mCherry. Arg1 and Chi3l3 may even decrease in alternatively activated Hoxa3 treated cells. Together these results suggest that rather than reducing the activation response observed in in vitro activated diabetic macrophages as hypothesised, SP.Hoxa3.mCherry treatment further enhances the classical activation phenotype whilst reducing alternative activation.

156

5.3 Hoxa3 treated macrophages and Neovascularisation

Treatment with SP.Hoxa3.mCherry conditioned medium appears to affect the maturation and activation potential of bone marrow derived macrophages. To see if either of these changes in phenotype affect interactions between vascular repair and macrophages, neovascularisation assays were performed in co-culture with macrophages after they had undergone the SP.mCherry or SP.Hoxa3.mCherry treatment during their maturation.

5.3.1 Interaction of SP.Hoxa3.mCherry treated bone marrow macrophages with neovascularisation assays

GFP+ macrophages were used in one of the experimental repeats to attempt to track their interactions with the nascent vessels (Figure 5.12). Composite images of the fibroblast and HUVEC bed and fluorescent imaging of the GFP+ macrophages were unable to identify any vessel like structures in any of the treated wells until day seven of the assay. As discussed previously this meant the timeframe of vasculogenesis was missed so endothelial cell macrophage interactions during the formation of new vessels could not be assessed. Similar to the activated macrophage neovascularisation assays no consistent alignment of vessel and macrophages could be observed in the images taken over days nine, 11 and 13 when vessels could be identified. As such no evidence of interactions with angiogenic sprouting could be found in these images. As observed in the activated macrophage neovascularisation assays the conditioned medium treated macrophages were observed to align with the fibroblast bed over these time points.

Neovascularisation assays were fixed and stained for CD31 to visualise the vessel network (Figure 5.13, A) and processed for image analysis as before (Figure 5.13, B). Paired analysis of the non-diabetic derived co-cultures identified the SP.Hoxa3.mCherry treated macrophage wells to contain vascular networks containing more tubules, of a shorter tubule length and with more junctions per unit tubule length (as expected based on the previous measurements). Similarly the CD31+ area (p<0.16), total tubule length (p<0.17) and total number of junctions (p<0.06) trended towards being increased in the SP.Hoxa3.mCherry treated macrophage wells. Together these suggest that a change in

157

the macrophage phenotype driven by SP.Hoxa3.mCherry treatment can promote a small but statistically significant increase in neovascularisation. The increase in junctions per length may be indicative that angiogenic sprouting is the cause of or contributes to this difference.

Diabetic derived macrophages treated with SP.Hoxa3.mCherry affected the neovascularisation co-cultures in a different manner to their non-diabetic cohorts (Figure 5.13, B). Paired analysis of the SP.mCherry and SP.Hoxa3.mCherry treated diabetic macrophage co-cultures suggested the wells of Hoxa3 treated macrophages contained vascular networks with a reduced tubule number, reduced number of tubule junctions, increased average tubule length and decreased number of junctions per unit tubule length. The decreased junctions per length may again indicate a change in the frequency of angiogenic sprouting in these cultures.

The diabetic macrophage alone may also have a negative effect upon neovascularisation. In paired comparisons the vascular network scores of diabetic derived macrophage co-cultures were repeatedly significantly different from the untreated control well, irrespective of SP.Hoxa3.mCherry treatment (Figure 5.14). CD31+ field area, total tubule length and total number of tubule junctions were all decreased in Db treated samples. The number of junctions per unit length of tubule was also significantly decreased in the SP.Hoxa3.mCherry treated diabetic co-cultures compared to the untreated wells.

Overall these experiments suggest that SP.Hoxa3.mCherry treatment has differential effects upon the actions of non-diabetic and diabetic derived bone marrow macrophages in neovascularisation assay co-culture. In non-diabetic cells Hoxa3 enhances pro-neovascular interactions, which may include angiogenic sprouting, whereas in diabetic cells Hoxa3 inhibits these pro-neovascular interactions or may even convey an anti-neovascular phenotype.

158

D3 D5 D7

.mCher

NDb r

a3.mCher

.mCher

a3.mCher

P S

D9 D11 D13

.mCher

NDb

a3.mCher

.mCher

a3.mCher

.H P S Figure 5.12: Vessel formation in SP.mCherry and SP.Hoxa3.mCherry treated macrophage neovascularisation assay co-culture Light and fluorescence microscopy images of GFP+ murine macrophages in co-culture with human fibroblasts and endothelial cells over assay time course. Red lines indicate likely vessel structures. GFP+ macrophages added to the assay after four days of treatment with conditioned medium. Yellow scale bar is equivalent to 50 µm.

159

amin y r r Su a3.mCher x o .H P S ed t a e r t n y r U .mCher P S GF

tic e Non-Diab tic e Diab

160

B CD31+ Field Area Total Tubule Length Average Tubule Length 4 2.5 1.5 * * 3 2.0 1.0 1.5

els 2 x 1.0 Pi 0.5 1 0.5

0 0.0 0.0

d F in b b d F in b b d F in b b te G D D te G D D te G D D a E m N a E m N a E m N e V ra e V ra e V ra tr u tr u tr u n S n S n S U U U

Number of Tubules Total Tubule Junctions Junctions per length

5 6 2.5

4 2.0 4 3 1.5 * * 2 * 1.0 ubules *

T 2 1 ** 0.5

0 0 0.0

d F in b b d F in b b d F in b b te G D D te G D D te G D D a E m N a E m N a E m N e V ra e V ra e V ra tr u tr u tr u n S n S n S U U U Treatment SP.mCherry SP.Hoxa3.mCherry Figure 5.13 Vessel formation in SP.mCherry and SP.Hoxa3.mCherry treated macrophage neovascularisation assay co-culture Angiogenesis assays co-cultured with SP.mcherry or SP.Hoxa3.mCherry treated macrophages from two days into the assay A) Representative light microscopy images of anti-CD31 stained day 14 angiogenesis assay wells developed with BCIP/NBT. Images aligned to centre of each assay well. Yellow scale bar equivalent to 1mm. B) Image analysis of day 14 assay vessels as stained with anti-CD31 (PECAM-1). Asterisks denote a significant difference between the SP.mCherry and SP.Hoxa3.mCherry treated cells in paired T-tests, * p<0.05, ** p<0.01. VEGF and suramin treated wells presented as positive and negative controls respectively and were significantly different in one way ANOVA to the untreated control. All values are normalised to the untreated control well.

161

CD31+ Field Area Total Tubule Length Average Tubule Length 1.5 * * 1.5 1.5 * *

1.0 1.0 1.0

els x

Pi 0.5 0.5 0.5

0.0 0.0 0.0 UT NDb Db UT NDb Db UT NDb Db

Number of Tubules Total Tubule Junctions Junctions per length

2.0 1.5 1.5 * ** ** 1.5 1.0 1.0

1.0 ubules

T 0.5 0.5 0.5

0.0 0.0 0.0 UT NDb Db UT NDb Db UT NDb Db

Treatment SP.mCherry SP.Hoxa3.mCherry Figure 5.14 Vessel formation in SP.mCherry and SP.Hoxa3.mCherry treated macrophage neovascularisation assay untreated well comparisons Angiogenesis assays co-cultured with SP.mcherry or SP.Hoxa3.mCherry treated macrophages from two days into the assay. Image analysis of day 14 assay vessels as stained with anti-CD31 (PECAM-1). Paired t-test analysis between non-diabetic (NDb) and diabetic (Db) macrophages treated with SP.mCherry or SP.Hoxa3.mCherry experimental wells and the untreated (UT) control wells. Asterisk denotes a significant difference between the untreated and the experimental samples in paired T-tests, * p<0.05, ** p<0.01. All values are normalised to the untreated control well.

162

5.3.2 Effects of neovascularisation assay culture upon macrophage phenotype

The in vitro activation of culture macrophages was used to generate a homogenous as possible population of polarised activation states. In vivo the cytokine milieu is far more heterogeneous and macrophages are observed to plastically convert along a spectrum of activation states. As such it is possible that the pro-neovascularisation conditions of the neovascularisation assay were themselves altering the phenotype of the macrophages applied to the co-culture.

GFP+ images of the macrophages throughout the co-culture experiments (Figure 5.12) were used to track the morphology of the macrophages to see if it gave any indication of a phenotypic change over time. Images were processed to generate a threshold map that was used to sort cells into seven different morphology types; small monocytic, trapezoid cells characteristic of mature non-activated macrophages, large monocytic cells, hyperplasic cells, cells with multiple filopodia, cells with two neurite-like arms and cells with one neurite-like arm (2.5.2; Figure 2.4).

Percentage plots of macrophage morphology were generated for the co-cultures of non- diabetic or type 2 diabetic macrophages that were treated with SP.mCherry or SP.Hoxa3.mCherry conditioned medium during their differentiation (Figure 5.15). Cell morphology proportions converged to a similar distribution for all four cell treatments by the end of the neovascularisation assay, despite the differences in cell network scores reported in this chapter (5.3.1). Such gross cell morphology may not be indicative of the phenotypic differences in these macrophages responsible for the changes in neovascularisation.

In summary, the distribution of macrophage cell morphologies in neovascularisation assay co-culture changes over time in the assay. This may be indicative of changes in phenotype from those of the original input cells but further investigation would be required to confirm this and understand how this would affect the assay results.

163

Mp Mp Mp

Day 0 Day 3 Day 5 Day 7 Day 9 Day 11 Day 13

.mCher

NDb

a3.mCher

.mCher

a3.mCher

P S

Small monocytic Trapezoid Large monocytic Hyperplasic Multi-filapodia Two arms Single arm Figure 5.15 SP.Hoxa3.mCherry or SP.mCherry treated macrophage morphology over neovascularisation assay co-culture Morphology analysis of florescence microscopy images of SP.mCherry or SP.Hoxa3.mCherry treated non-diabetic and type 2 diabetic derived GFP+ bone marrow macrophages during neovascularisation assay co-culture. Day 0 samples were macrophage cultures before addition to the assay but after the four days conditioned medium treatment. Mp indicates the addition of macrophages to the culture wells on day 2, day 4 and day 6.

164

5.3.3 Endothelial gene expression in SP.Hoxa3.mCherry treated macrophages

Expression of endothelial marker genes was assessed by qRT-PCR in murine macrophages treated with SP.Hoxa3.mCherry during their differentiation to check for any signs of endothelial reprogramming (Figure 5.16). In non-diabetic mouse macrophages SP.Hoxa3.mCherry treatment significantly decreased Cdh5 (Figure 5.16, A). In type 2 diabetic mouse macrophages treatment with SP.Hoxa3.mCherry had no effect upon the three genes tested (Figure 5.17, B). Non-diabetic and type 1 diabetic rat macrophages treated with SP.Hoxa3.mCherry similarly had no significant difference in trended towards upregulated CD34 (p<0.09) and downregulated vWF (p<0.11) in both phenotypes (Figure 5.16, C).

Overall these results support the conclusion from the previous chapters work with RAW macrophages that SP.Hoxa3.mCherry is unable to drive endothelial transdifferentiation over the time spans tested.

Figure 5.16 Expression of endothelial markers in murine macrophages treated with SP.Hoxa3.mCherry conditioned medium Murine bone marrow derived macrophages were assayed for expression of endothelial markers post four day treatment with SP.Hoxa3.mCherry or control SP.mCherry conditioned medium. A) Endothelial genes in non-diabetic mouse bone marrow macrophages. B) Endothelial genes in type 2 diabetic mouse bone marrow macrophages. C) Endothelial genes in non-diabetic rat bone marrow macrophages. D) Endothelial genes in Streptozotocin induced type 1 diabetic rat bone marrow macrophages. Relative expression normalised to reference genes H2a and Hsp90 in mouse samples, H2a, Actb and Hsp90 in rat samples. Asterisk denotes significant difference between conditioned medium treatments in paired T-tests, ** p<0.05. All samples six experimental repeats.

165

A NDb mouse CD34 Cdh5 vWF 1.5 1.5 1.5

ession 1.0 1.0 1.0

e e

v 0.5 0.5 ** 0.5

a el R 0.0 0.0 0.0 y y y y y y rr rr rr rr rr rr e e e e e e h h h h h h C C C C C C .m .m .m .m .m .m 3 3 3 P a P a P a S x S x S x o o o .H .H .H P P P S S S Sample

B Db mouse CD34 Cdh5 vWF

1.5 1.5 1.5

ession r

1.0 1.0 1.0

e v

ti 0.5 0.5 0.5

el R

0.0 0.0 0.0 y y y y y y rr rr rr rr rr rr e e e e e e h h h h h h C C C C C C .m .m .m .m .m .m 3 3 3 P a P a P a S x S x S x o o o .H .H .H P P P S S S Sample C NDb rat D Db rat CD34 vWF CD34 vWF

4 1.5 3 1.5

ession ession r r 3

1.0 2 1.0

xp xp

e e e

e 2

v v ti

ti 0.5 1 0.5 a

a 1

el el

R R

0 0.0 0 0.0 y y y y y y y y rr rr rr rr rr rr rr rr e e e e e e e e h h h h h h h h C C C C C C C C .m .m .m .m .m .m .m .m 3 3 3 3 P a P a P a P a S x S x S x S x o o o o .H .H .H .H P P P P S S S S Sample Sample

166

5.4 Discussion

Bone marrow macrophages were treated with conditioned medium from SP.Hoxa3.mCherry transfected 293T cells. SP.mCherry conditioned medium was used as a control for non-Hoxa3 factors in the conditioned medium. In RAW cells, and non- diabetic and type 1 diabetic rat macrophages Plaur was significantly upregulated by the Hoxa3 treatment. In mouse macrophages there was a trend towards upregulation. This is strong evidence that Plaur is downstream of Hoxa3 transcriptional activity in macrophages. Plaur is a receptor for urokinase plasminogen activator (Del Rosso et al., 1985). Plaur was tested as a potential Hoxa3 responsive gene due to its role downstream of Hoxa3 in keratinocytes. In endothelial cells expressing a HOXA3 transgene PLAUR was upregulated and functional PLAUR signalling was required for Hoxa3 induced migration (Mace et al., 2005, Daniel and Groves, 2002). Plaur expression is also induced during epidermal regeneration and deletion of its inhibitor accelerates wound closure (Nuutila et al., 2012, Li et al., 2000). Upregulation in the treated macrophages may be indicative of the acquisition of a pro-angiogenic phenotype. Expression in stromal macrophages associated with small cell lung cancers and lung squamous cell carcinomas was linked to metastatic transformation (Hedbrant et al., 2015). Expression in tumour-associated macrophages in colorectal cancer patients was also a marker of poor prognosis (Illemann et al., 2014). Confirmation by time course observation of this upregulation and identification of a suitable functional link would be worthwhile to confirm Plaur is part of Hoxa3 effects upon macrophages.

Expression of macrophage markers was measured to investigate the effects of Hoxa3 upon macrophage phenotype. In non-diabetic mouse and rat cells Emr1/F4/80 was upregulated, whereas in diabetic cells Itgam was upregulated. As reported in the previous chapter (4.2.3) RAW cells treated with SP.Hoxa3.mCherry for the same period of time upregulated CD14 and Itgam. These results suggested a macrophage maturation promoting phenotype. Differences in Emr1 gene expression response between the experimental systems may be indicative of different roles of Hoxa3 across species. Tissue regeneration responses vary across mouse inbred strains (Rai et al., 2012, Manigrasso and O'Connor, 2008, Moran et al., 2015) and Hoxa3 post segmentation function can vary between species in some tissues (Chen et al., 2010). It would be

167

interesting to assess the expression of Hoxa3 in other healing pathologies to see if a shared mechanism exists. Elevated CD14 and Cd11b expression have been associated with macrophage maturation in response to PI3K stimulation (Moeenrezakhanlou et al., 2008). PI3k signalling is implicated in the closure of embryonic wounds in Xenopus, enhancing Rac andCdc42 activity (a target of Hoxa3 in endothelial cells) stimulating the migration of wound edge cells (Li et al., 2013a). Rat macrophages upregulated CD14 and pro-inflammatory cytokines when stimulated with LPS (Liu et al., 2015). Human THP-1 monocytes also upregulate CD14 and CD11b expression when stimulated to macrophage differentiation with PMA (Schwende et al., 1996). However, CD14 expression and surface fluorescence may not be an ideal reporter of monocyte and macrophage maturation due to reports of its surface fluorescence changing without a corresponding change in mRNA levels, and the production of secreted CD14 protein that will not be detected in flow analysis (Blondin et al., 1997, Frey and De Maio, 2007, Hamilton et al., 2013).

To clarify the effects of Hoxa3 upon macrophage maturation, the expression of Cx3cr1 was also assessed. Cx3cr1gfp reporter expression has been used in multiple inflammatory systems to track the maturation of circulatory monocytes to mature tissue macrophages (Little et al., 2014). This would also facilitate the assessment of individual cells and if the gene expression changes reported here are indicative of an overall shift in expression levels or in fact changes in the numbers of specific myeloid subpopulations. Cx3cr1 expression is required for the establishment of tissue resident macrophages, recruitment of macrophages to the wound site, and its expression in bone marrow lineage cells is required for successful wound healing (Yona et al., 2013, Ishida et al., 2008).

No change was observed between non-diabetic and diabetic mouse macrophages, fitting the results from chapter three (3.1.2). As previously discussed this absence of a diabetic macrophage maturation phenotype does not match previous reports of impaired macrophage maturation in diabetes (Wicks et al., 2015, Bannon et al., 2013, Mirza and Koh, 2011). Hoxa3 treatment of RAW cells and diabetic mouse bone marrow macrophages significantly upregulated Cx3cr1 expression, whist Hoxa3 treated non- diabetic murine macrophages trended towards increased Cx3cr1 expression. Together

168

with the upregulation of the other macrophage markers in parts across these experimental systems these results suggest that SP.Hoxa3.mCherry treatment promotes macrophage maturation in vitro. This promotion of maturation may contribute to the Hoxa3 driven rescue of diabetic wound healing (Mace et al., 2005, Mace et al., 2009). The greater effect/significance of Hoxa3 upon Cx3cr1 expression in diabetic animals may also fit observations of impaired diabetic macrophage maturation. Cx3cr1 expression and macrophage maturation is also associated with the early signs of M2 polarisation (Veremeyko et al., 2013).

A similar protocol of SP.Hoxa3.mCherry treatment or mouse macrophages has been performed by our research group (Al Sadoun, submitted for review). The original aim of this work was to investigate the effects of Hoxa3 upon the macrophage phenotype, rather than an attempting to promote transdifferentiation so a shorter treatment was used. Conditioned medium was applied to bone marrow macrophage differentiation cultures on the final 24 hours of differentiation (day 6). A similar suit of macrophage maturation markers was used to assess effects upon the differentiation of bone marrow macrophages. Both non-diabetic and diabetic derived macrophages upregulated Emr1 mRNA, with a less significant increase in diabetic cells matching the trend observed in my mouse macrophages. Only the non-diabetic macrophages upregulated Itgam whereas Itgam upregulation was only observed in the diabetic macrophages of my treatments. Mean fluorescence of F4/80 was increased in both non-diabetic and diabetic derived macrophages, yet in my experiments F4/80 was only upregulated in non-diabetic cells. Csf1r and CD115 were also upregulated in non-diabetic and diabetic macrophages with this shorter Hoxa3 treatment. Hoxa3 stimulated upregulation of Spi1 in treated cells may be a mechanism for the increase in of the maturation markers. Interestingly Spi1 mRNA levels were decreased in diabetic derived macrophages. Overall the results from a shorter Hoxa3 protein treatment produced a similar increase in macrophage maturation markers to my four day treatments but to more significant results. This could be due to differential effects of Hoxa3 upon cells earlier in macrophage differentiation protocol. Alternatively, multiple batches of conditioned medium were required for four day treatment and the use of multiple conditioned

169

medium batches may have introduced extra experimental variation that reduced the power of the comparison.

The activation potential was predicted to be altered by Hoxa3 treatment to attenuate the enhanced activation of diabetic macrophages. This hypothesis was not confirmed in these experiments. Treatment of diabetic macrophages with SP.Hoxa3.mcherry instead further increased the expression of the classical markers Ccl2 and Nos2 and downregulated the alternative markers Arg1 and Chi3l3 in their respective activation states. This further promotion of classical activation does not fit the reported pro- healing effects of Hoxa3 treatment diabetic wounds, which exhibit excessive inflammation (Bannon et al., 2013, Mirza and Koh, 2011). The macrophages from the 24 hour conditioned medium experiments discussed earlier were also tested for their activation potential (Al Sadoun, submitted for review). Hoxa3 treatment of both non- diabetic and diabetic macrophages reduced their expression of the same classical activation genes used in my experiments. Conversely, Hoxa3 treatment significantly upregulated three of the alternative activation genes Tgfb, Mrc1 and Chi3l3 in both non- diabetic and diabetic derived macrophages. These results were also confirmed by measurement of cytokine production. Secretion of classical activation cytokines nitric oxide, IL-12 and TNF were reduced by SP.Hoxa3.mCherry treatment in both non-diabetic and diabetic derived cells and alternative cytokines arginase and TGF-β increased in secretion. With all other experimental factors the same, the extended and earlier treatment of differentiating macrophage cultures must be the cause of this difference. Phagocytosis of a proportion of the conditioned medium protein was proposed as an explanation of the cytoplasmic localisation of SP.Hoxa3.mCherry and SP.mCherry in RAW cell experiments (4.2.2). Phagocytosis and classical activation are thought to be closely linked so if the conditioned medium is triggering phagocytosis in these cells the longer treatment may be biasing classical activation (Kapoor et al., 2015). However, similar immunofluorescence images of macrophages treated with conditioned medium did not detect as prominent cytoplasmic localisation in the 24 hour treatments. Immunofluorescent processing of four day treated macrophages should be performed to see how they compare.

170

Non-diabetic macrophages also did not respond as hypothesised. Unlike the diabetic macrophages no difference was observed in the response to activation cytokines between SP.mCherry and SP.Hoxa3.mCherry treated. Instead a significant increase in activation markers was observed in the non-activate samples. Ccl2, CD86 and Tnf were significantly upregulated classical markers and Chi3l3 and Mrc1 were increased alternative markers. This may be indicative of a ‘priming’ of non-activated macrophages for response to both classical and alternative activation signals (Wu et al., 2014, Weisser et al., 2011, Perry and Holmes, 2014). If Hoxa3 treatment does prime activation this effect may not be detected in the activated samples due to the treatments being designed for full polarisation to classical or alternative phenotype. A titration of concentrations of the activating stimuli could be used to test if SP.Hoxa3.mCherry treatment makes the non-diabetic macrophages more sensitive to activating cytokines. Alternatively the Hoxa3 treatment may be stimulating a few cells in the population to become activated and this is increasing the average mRNA level as assayed by qRT-PCR. Immunofluorescence and/or FACS analysis would determine if this is happening in these experiments.

Macrophages treated with SP.Hoxa3.mCherry altered the formation of vessel networks in neovascularisation assays at a small but signficant level. Non-diabetic macrophages treated with Hoxa3 increased the vessel network scores in treated wells. The significant increase in the number of tubules and the number of junctions per unit of tubule length may indicate an increase in angiogenic sprouting. A trend towards increased vessel area and total length suggest that vasculogenesis is also promoted. As a fraction of the figures from the VEGF stimulated networks this increase was very small, but compared to the SP.mCherry control Hoxa3 treatment caused a 1.2 times increase in tubules and junctions. Pro angiogenic changes in other cells in concert with this macrophage specific change may be what is required to improve neovascularisation in vivo.

GFP+ macrophages were used to attempt to observe interactions between vessels and macrophages during the formation of new vessels and the sprouting of angiogenic vessels. Similar to the neovascularisation assays with activated macrophages (3.3.1) vessels could not be identified until day nine at the earliest so interactions during vasculogenesis could not be judge. Unlike the activated macrophages, direct

171

interactions of monocytes and macrophages with the aggregating cell columns can regulate vasculogenesis. Macrophages in Matrigel plugs inserting into mice have been observed to align in bead structures and digest the matrix to clear a path for nascent vessels (Anghelina et al., 2006). Monocytes and macrophages co-localise with the endothelial cells in choroidal angiogenesis assays (Bian et al., 2003, Oh et al., 1999). Application of macrophages along with EPCs to a hind-limb ischemia model accelerates the integration of the EPCs to the vasculature (Kwon et al., 2014). Macrophages are also thought to interact with vessels during angiogenic sprouting. A macrophage population has been implicated in the clearing of extracellular matrix for new vascular buds and facilitate the growth of the angiogenic sprout (Bourghardt Peebo et al., 2011). Macrophages have also been implicated in the fusion of the angiogenic tip cells at the leading edge of growing vessels (Fantin et al., 2010). Such close associations with sprouting vessels could not be observed in the neovascularisation assays but the identification of newly sprouting vessels was also difficult under phase microscopy. The use of live imaging assays either with labelled HUVECs in combination with GFP+ macrophages could facilitate the observation of these interactions. Myeloid cells similar to the non-polarised macrophages also promote angiogenesis through modification of the environment. Treatment of diabetic wounds with macrophages primed with TNF-α and IFN-γ improved the wound healing phenotype by stimulating angiogenesis and re- epithelization, and secreting VEGF (Gu et al., 2013).

The application of SP.Hoxa3.mCherry treated diabetic macrophages had an unexpected negative effect upon the formation of vascular networks. Reduced numbers of tubules and junctions, and a decrease in the number of junctions per unit tubule length may indicate an inhibition of angiogenic sprouting and the de-novo formation of new vessels by vasculogenesis. Also of note was that in these experiments diabetic derived macrophages significantly inhibited network growth when compared to untreated control wells. As described for the non-diabetic cells, this change is not as signficant as the VEGF inhibitor suramin but is 90% the number of tubules and junctions of the SP.mCherry treated control cells.

The distribution of macrophage morphologies was changed during the neovascularisation co-culture. Despite this differential effects were detected between

172

the SP.mCherry and SP.Hoxa3.mCherry treated samples. It could be hypothesised that the morphological changes are indicative of the macrophages responding to an angiogenic environment. The potential activation state priming that was observed in non-activated, non-diabetic macrophages treated with Hoxa3 conditioned medium could enhance the macrophage response to this environment and increase strength of the positive interactions with the assay. The results of the diabetic macrophages in these assays may also correlate with the macrophage polarised activation findings. If SP.Hoxa3.mCherry treatment of diabetic cells is reducing their response to alternative activation signals compared to the SP.mCherry control then these cells would not respond as strongly to the angiogenic environment. This hypothesis could be tested by the culture of Hoxa3 treated macrophages in angiogenic growth medium and their activation state tested, although if the HUVEC and fibroblast cells also contribute to this effect digestion of the assays and isolation of the GFP+ macrophages may be a more thorough experiment.

Hoxa3 treatment did not induce endothelial transdifferentiation in mouse or rat bone marrow derived macrophages. This was to be expected from the upregulation of macrophage markers. In the rat cells there was a trend towards upregulation of CD34 with SP.Hoxa3.mCherry treatment in both non-diabetic and diabetic derived cells, but also a concurrent trend towards vWF downregulation. CD34 upregulation in rats may be indicative of reversion to a lineage progenitor state but this would be counter indicative to the upregulation of macrophage markers.

SP.Hoxa3.mCherry conditioned medium treatment of RAW macrophage cells, mouse bone marrow derived macrophages and rat bone marrow macrophages promotes their maturation. This upregulation compared to the control SP.mCherry protein treatment was more pronounced in diabetic derived macrophages and may be a recovery of the impaired macrophage maturation that has been reported by other groups. Expression of the urokinase plasminogen activator receptor Plaur is promoted by Hoxa3 protein transduction. The expression of endothelial markers in these cells was checked and no indications that endothelial reprogramming was occurring were found. Treatment of non-diabetic macrophages did not alter their response to classical and alternative activation stimuli, but elevated both classical and alternative marker expression in

173

untreated cells. In diabetic macrophages Hoxa3 conditioned medium treatment enhanced the response to classical stimuli and reduced their response to alternative stimuli. These activation responses may correlate with the effects of Hoxa3 treated non- diabetic and diabetic macrophages upon vessel formation in neovascularisation assay co-cultures. Non-diabetic macrophages treat with Hoxa3 conditioned medium increased vascular growth whereas Hoxa3 cultured diabetic macrophages impaired neovascularisation.

174

6 General Discussions

Diabetes is well documented to cause impaired wound healing (Mirza and Koh, 2011, Bannon et al., 2013, Awad et al., 2005). The dysregulation of a wide array of cells within the wound environment has been observed in diabetes and associated with the non- healing phenotype. To assess the changes that may occur in diabetic macrophages in vitro assays of macrophage function were performed. These assays enabled the observation of macrophage function independent of the changes diabetes makes to the wound environment and non-macrophage cell lineages such that any phenotypic differences would solely be from the diabetic phenotype established in the bone marrow cells. 6.1 Diabetes alters macrophage function

Investigations of macrophage function both within the diabetic wound and in vitro cultures similar to my own have reported a diabetes driven impairment in macrophage maturation (Mirza and Koh, 2011, Bannon et al., 2013). The difference between in vivo results may be explained by contributions from the diabetic wound environment, yet the in vitro conditions used by Bannon to stimulate macrophage differentiation were identical to those used myself (personal communication). That the subsequent in vitro activation of the diabetic derived macrophages gave a similar elevate activation response to both classical and alternative stimuli as reported in this thesis suggests that our treatments are both maintaining the different cell phenotypes.

To test the effects upon macrophage maturation and residency in the wound, Cx3cr1GFP reporter mice could be crossed with the C57B/L6db/db diabetic mouse. This would facilitate the tracking of macrophage maturation during diabetic wound healing via FACS analysis of the GFP reporter and other markers of monocytic and macrophage subpopulations (Little et al., 2014).

RAW cells cultured in high glucose conditions also showed no significant difference in maturation marker expression compared to their low glucose controls. High glucose has been reported to increase the classical activation of RAW cells to classical stimuli (Hua et al., 2012, de Souza et al., 2008). It would be interesting to see if the high glucose RAW

175

cells in my treatments also exhibit an increased response to both classical and alternative activation like the diabetic mouse macrophages.

The cytokine levels of IL-1β, IFN-γ, and IL-10 in diabetic wounds suggest an impairment in the transition from classical to alternative activation (Mirza and Koh, 2011). Multiple macrophage processes have been implicated in the block of M1 to M2 transition. Macrophages within the diabetic wound have been reported to exhibit impaired efferocytosis, which contributed to the elevated pro-inflammatory cytokine concentration and inhibited the conversion of these macrophages to an alternative activation state (Khanna et al., 2010). The increased inflammasome activity of diabetic macrophages may also contribute to the consistent classical activation (Mirza et al., 2014). The gene expression of markers of classical and alternative activation were elevated in their respective activation state in both the work in this thesis and Bannon (Bannon et al., 2013). Bannon proposed that diabetic macrophages have a innate hyperpolarisation phenotype that drives these enhanced activation responses. Characterization of macrophage activation in diabetic wounds at four and six days post wounding showed the same hyper inflammation phenotype that has been described for the whole wound. It is likely that the early inflammation signals in the wound trigger classical activation of the macrophages then their hyperpolarization in concert with the other inflammatory cells in the wound create the excessive inflammatory environment. This would suppress the alternative activation of macrophages irrespective of their hyperpolarization potential for alternative signals.

Alternatively or additionally the work of (Khanna et al., 2010) suggests an impairment of plasticity in diabetic macrophages. This would prove an interesting avenue of future investigation that takes advantage of the ease of activation in the in vitro system. Macrophages can be polarized to the classical activation state, then stimulated with alternative signals and assayed for their polarization to the secondary state. It could be hypothesized that diabetic derived macrophages will not switch to the secondary state as completely as non-diabetic derived macrophages. This has already been performed in a genetic model of atherosclerosis (Khallou-Laschet et al., 2010).

176

6.2 Diabetic macrophages impair angiogenesis in vitro

Alternatively activated macrophages have been reported to promote angiogenesis both in vivo and in vitro (Jetten et al., 2014b). In the neovascularization assays in this thesis the positive effects of M2 polarized macrophages were not observed. This may be due to the macrophages losing their activation state, or the need to further optimize the addition of macrophages to the assay. This could include both the number of macrophages applied and a single application of macrophages at the start of the assay to avoid thawing stress. Such optimisation may also affect the size of the changes seen with Hoxa3 treatment in these assays. However, non-diabetic M2 polarized macrophages applied to excisional wounds retained their phenotype for 15 days, even in diabetic wounds (Jetten et al., 2014a). The plasticity experiments described in (6.1) would help contribute to our understanding of what is happening in these assays.

In the future the neovascularization experiments could be expanded to include medium conditioned by activated macrophages. The application of conditioned medium to the neovascularisation assays would assess the effects of macrophage secrete factors upon vessel formation. This would require the culture of macrophages specifically for conditioned medium generation because the activation medium must be replaced post activation then before collection so the activation cytokines do not interfere with the neovascularization assay. This has already been performed by others for non-diabetic macrophages and saw differences between the effects of macrophages and their conditioned medium. The conditioned medium from non-activated, classically activated and alternatively activated macrophages promoted tubule formation (Jetten et al., 2014b). This was different to the inhibition described when classically activated cells were added to these assays. This may be linked to the observations of macrophages leading angiogenic sprouts by clearing extracellular matrix (Bourghardt Peebo et al., 2011, Fantin et al., 2010). VEGF expression by M1 macrophages in particular may play a role (Jetten et al., 2014b, Gu et al., 2013).

The use of fluorescently labeled HUVECs for future assays, in combination with the GFP+ labelled macrophages, could facilitate the live imaging of the assay and the identification of any points of interaction between the macrophages and the nascent vessels and/or

177

angiogenic sprouts. This would also facilitate the analysis of the vessel network at any point in its growth and may detect differences between the treatments that were lost by the day 14 time point. 6.3 Transdifferentiation as a potential diabetic wound therapy

Pleiotrophin has been reported to drive monocytic to endothelial transdifferentiation in multiple papers before and since the work in this thesis had been performed (Sharifi et al., 2006, Palmieri et al., 2015, Chen et al., 2009a). As such the failure of pleiotrophin to drive endothelial programming in the two methods reported in this thesis must be due to an as yet unidentified factor in the experimental design inhibiting reprogramming. A likely candidate would be the use of high glucose medium (these experiments were performed before the RAW cell high glucose analysis). High glucose downregulated the early endothelial gene vWF which may be indicative of repression of the endothelial phenotype. There are also multiple reports of reduced endothelial cell progenitors in diabetic animals (Lombardo et al., 2012, Mace et al., 2009, Ling et al., 2012). Culture of EPCs in high glucose conditions for four days severely impaired their function reducing migration and tube forming, and increasing apoptosis (Chen et al., 2012). Repeating the conditioned medium experiments with low glucose could facilitate endothelial reprogramming. However, the original lentiviral transformation of THP-1 cells with pleiotrophin did specify the use of ATCC recommended culture conditions, which uses medium with the high glucose concentration.

Of a higher priority would be the establishment of a stable gene transfer method in monocytes to test endothelial reprogramming with the transcription factors identified and verified in this thesis (FOXC1, FOXO1, ID1, NR2F2, and SOX18). Despite the original concerns about oncogenesis, the use of a lentiviral method as per the THP-1 pleiotrophin experiment may be the best option for testing these transcription factors. Alternatively, recently published improvements to the Nucleofection protocol might reduce the cell death burden (Mellott et al., 2014). Unfortunately this ROCK inhibitor protocol was not tested for the sort of longer term expression that would be required to test endothelial reprogramming.

178

Hoxa3 protein transduction was also tested for its potential to promote endothelial transdifferentiation. No indication of reprogramming was observed except for an upregulation of CD34 in rat bone marrow derived macrophages. CD34 expression in rats is characteristic of the lineage progenitors for many tissue types (Jin et al., 2014, Hinescu et al., 2008, Sahin et al., 2008). However the concurrent upregulation of macrophage markers does not fit a reprogramming interpretation.

The use of macrophages may have reduced the possibility of endothelial transdifferentiation due to them being more differentiated than the monocytes used in most reports. The CD34 response in rat macrophages only may have been linked to their slower differentiation in culture compared to mouse macrophages. Other rat macrophage differentiation protocols have used a higher concentration of L929 conditioned medium or a longer differentiation culture, possibly to account for this observation (Wiltschke et al., 1989, Boltz-Nitulescu et al., 1987). This could mean that earlier progenitors were being treated with Hoxa3 compared to the same time point of mouse bone marrow experiments. Treatment with Hoxa3 at different time points in macrophage differentiation, and the assaying of the monocyte/macrophage phenotype across the differentiation protocol might reveal new effects of the Hoxa3 treatment. This is particularly appropriate due to the differing effects of Hoxa3 upon macrophage activation between twenty-four hours and four days of treatment (Al Sadoun, submitted for review). Pilot studies were attempted with THP-1 monocytes treated with SP.Hoxa3.mCherry conditioned medium to see if monocytes were more amenable to Hoxa3 driven reprogramming. The results were similar to those of the macrophages with no change in endothelial markers and a possible upregulation of macrophage maturation markers.

Culture on gelatine or other potentially pro-endothelial matrices could be applied to the Nucleofection and Hoxa3 protein transduction protocols to see if that enhances transdifferentiation (Palmieri et al., 2015, Schmeisser et al., 2001).

179

6.4 Treatment of macrophages with Hoxa3 may rescue their maturation phenotype

Treatment of macrophages with Hoxa3 conditioned medium appeared to improve their maturation phenotype. If we discount the similar maturation between non-diabetic and diabetic derived macrophages in this thesis and accept the reports of impaired maturation this could be interpreted as a rescue of the diabetic phenotype (Bannon et al., 2013, Mirza and Koh, 2011). Diabetic macrophages have been reported to have impaired chemotaxis, migration and adhesion in vitro (Bannon et al., 2013). The Hoxa3 treated macrophages should also be assessed for the rescue of these properties. The upregulation of Plaur in Hoxa3 treated cells further supports the potential for Hoxa3 to rescue migration defects. In endothelial and epithelial cells Plaur expression is required for epidermal regeneration and Hoxa3 induced migration (Li et al., 2000, Mace et al., 2005, Nuutila et al., 2012). Plaur expression should be further investigated in the Hoxa3 protein transduction of macrophages to test if it is a transcriptional target of Hoxa3 and if an effect upon migration occurs, that Plaur is a functional requirement for that effect.

The rat macrophages did appear to differentiate to macrophages slower than their mouse counterparts so the Hoxa3 treatment may have targeted earlier myeloid intermediates as well as the originally intended monocytes and macrophages. In the RAW cell conditioned medium treatments significant upregulation was detected at four days of treatment but no longer significant at eight days of treatment. This may be suggestive of different effects as cells mature. The different effects on bone marrow derived macrophage activation from twenty-four hours and four days treatment with conditioned medium may also be due to the treatment of cells in an earlier developmental intermediate. Investigation of the effects of Hoxa3 treatment at multiple time points during in vitro differentiation could be a worthwhile avenue of future work.

To investigate the effects of Hoxa3 upon macrophage activation in more detail and in an in vivo system with environmental contributions a cross of the Cx3cr1gfp reporter mouse with the type 2 diabetic C57B/L6db/db strain could be made. The Cx3cr1gfp mouse can be used to track the maturation of circulatory monocytes to mature tissue macrophages by FACS analysis (Ishida et al., 2008, Little et al., 2014, Yona et al., 2013). Excisional wounds

180

would be made in the diabetic Cx3cr1 reporter mice and Hoxa3 treatment with methylcellulose-mediated gene transfer performed as per (Mace et al., 2009). Wounds would be excised at one four and seven days to assess the maturation of the macrophage populations within the wound. Wound matrix is enzymatically digested to generate a single cell suspension for FACS analysis (Little et al., 2014, Wicks et al., 2015).

If Hoxa3 promotes macrophage maturation and function it may be worth investigating its role in other healing pathologies. A sensible introductory step for this would be to assess the expression of Hoxa3 within these pathologies compared to healthy controls. This could begin with the culture of bone marrow derived macrophages of ovariectomized mice that also exhibit impaired wound healing (Emmerson et al., 2012, Hardman et al., 2008). 6.5 Treatment with Hoxa3 has differential effects on the pro-angiogenic potential of non- diabetic and diabetic macrophages

Treatment of macrophages with Hoxa3 had different effects upon non-diabetic and diabetic macrophages and their potential regulation of angiogenesis. Non-diabetic macrophages cultured with Hoxa3 conditioned medium upregulated markers of both classical and alternative activation markers in non-activated cells, and showed no difference in expression when stimulated to classical and alternative states. This ‘primed’ state of non-activated macrophages may contribute to their promotion of vessel growth in neovascularization assays if the angiogenic environment is promoting the alternative activation of the macrophages in the assay. To test the macrophage priming hypothesis titrations of activation cytokines could be performed. If Hoxa3 is priming macrophages for subsequent activation it would be expected that a lower concentration of activation cytokines is required to stimulate the expression of activation markers compared to control cells.

Diabetic macrophages treated with Hoxa3 conditioned medium favored classical activation, further upregulating their expression of classical markers and downregulating the expression of alternative activation markers. This response may also

181

correlate with a negative regulation of vessel growth in neovascularization assays if these cells do not respond to a pro-angiogenic environment as strongly. In these neovascuarisation assays diabetic cells treated with the SP.mCherry control vector also had a negative effect upon angiogenesis compared to the untreated control wells. A negative effect of non-activated cells was expected but not observed in the previous non-diabetic to diabetic comparison of cells without conditioned medium treatment. This may be due to the 24 hours in serum starved conditions of this previous experiment (as required for the activated samples) or even increased statistical sensitivity due to the Hoxa3 experiments being run in triplicate rather than duplicate. Alternative this inhibition of neovascularisation may be due to effects of calcium phosphate transfection upon the conditioned medium. In the Cdc42 and Plaur gene expression analysis RAW cells treated with conditioned medium from SP.mCherry transfected 293T cells trended towards lower expression than RAW cells with conditioned medium from untransfected 293T cells. This suggests that something within the conditioned medium itself alters the RAW cell phenotype. Alterations in the 293T secretome could be cause by cytotoxic stress from calcium phosphate transfection (Mostaghaci et al., 2015) or phagocytosis by the macrophages of the SP.mCherry and SP.Hoxa3.mCherry protein.

If these neovascularisation assays were to be repeated the use of fluorescently labelled HUVECs and macrophages would facilitate the live imaging of the co-cultures and a thorough investigation of the local interactions of the macrophages as the vessel structures form. To assess how these cells interact with the vasculature in vivo Hoxa3 treated macrophages would be injected into non-diabetic and diabetic excision wounds at the outset of vascular repair four day post wounding. Effects upon wound repair and vascular regeneration would be assessed histologically.

The effects of four days Hoxa3 protein treatment on macrophage activation do not match those of the 24 hour treatment (Al Sadoun, submitted for review). In the 24 hour treatment the effect upon macrophage activation was as originally hypothesised; classical activation was reduced in Hoxa3 treated cells and alternative activation promoted for both non-diabetic and diabetic derived macrophages. As previously discussed this different effect from 24 hour treatment may be due to different earlier cell populations being treated with Hoxa3 at the start of the four day treatment. Other

182

potential mechanisms could be other non Hoxa3 factors secreted into the conditioned medium as stimulated by calcium phosphate transfection, or it may just be increased variation in the amount of Hoxa3 present in the culture medium supplemented with SP.Hoxa3.mCherry conditioned medium from multiple batches of transfected 293T cells.

The variations in transfection efficiency of 293T cell between experiments may be indicative of concentrations amounts of SP.Hoxa3.mCherry being secreted into the conditioned medium. It is also possible that conditioned medium concentrations vary with each daily collection. This is not ideal for consistent treatment of target cells with conditioned medium over multiple days. We are now developing bacterial and insect cell protein expression system to purify Hoxa3 myc-His tagged protein for future experiments. This will enable the use of a consistent amount of Hoxa3 in experimental repeats and reduce experimental variation. The production of functional protein will have to be carefully assessed to ensure the different post-translational modifications from a bacterial expression system (Hochkoeppler, 2013). The identification of Plaur as a downstream target of Hoxa3 in macrophages will be of great use for these validations.

The protein secretion system was originally chosen for these experiments due to its potential for a constant treatment of cells in co-culture. The establishment of stably transfected feeder cells with the SP.Hoxa3.mCherry expression plasmid could also be used to generate a constant supply of Hoxa3 generated in human cells (Mahdipour et al., 2011). 6.6 The diabetic macrophage phenotype in the wound is dependent on both macrophage intrinsic and extrinsic changes

The culture of macrophages in vitro from bone marrow precursors means that any phenotypic differences observed must have been established whilst still residing in the bone marrow of the diabetic animal as a haematopoietic progenitor. The altered potential of diabetic HSCs has also been reported in type 1 diabetic mice (Hazra et al., 2013). HSCs from the diabetic mice showed impaired colony forming ability in vitro and

183

reduced differentiation to endothelial progenitors. More monocytic and granulocyte- monocyte precursor colonies were formed.

These long term diabetic induced changes in cell potential may be maintained by changes in epigenetic regulation. The Cebpa promoter in diabetic derived Gr-1+ cells exhibits decreased H3K27 acetylation signifying reduced active chromatin. This was matched by reduced mRNA levels and impaired myeloid differentiation (Wicks et al., 2015). Vascular smooth muscle cells isolated from type 2 diabetic mice exhibit a persistent inflammatory phenotype in culture and have significantly decreased inhibitory H3K9me3 histone modifications at the promoters of multiple inflammatory genes (Villeneuve et al., 2008). Interestingly culture of non-diabetic SMECs in high glucose conditions was sufficient to induce a similar upregulation of inflammatory genes and decrease promotor H3K9me3 presence. This further supports the use of high glucose conditions as a model for diabetes, and the unintended effects that high glucose culture might have had upon my non-diabetic to diabetic derived macrophage comparisons. In normal wound healing Polycomb group protein (PcGs) family member family members Eed, Ezh2 and Suz12 were transiently downregulated during repair whereas lysine demethylase that remove the chromatin marks led down by the PcG proteins are upregulated (Shaw and Martin, 2009a). Interestingly PcGs target Polycomb Response Elements (PREs) that regulated the segmented Hox gene expression during embryonic dorsal ventral patterning (Simon et al., 1992).

However, diabetic transformations in other tissues also alters the environment and its regulation of macrophage function. Treatment of endothelial cells with high glucose conditions increased the migration rate of CD14+ monocytes across the endothelium and promoted their differentiation to macrophages (these are ‘non-diabetic’ macrophages) (Gappa-Fahlenkamp and Shukla, 2009). The aberrant inflammatory response in diabetes is driven by both the haematopoietic inflammatory cells and other lineages within the wound. The elevated pro-inflammatory cytokine signals that attract and retain neutrophils, monocytes and macrophages is contributed to by the secretion of macrophage inflammatory protein-2 and macrophage chemoattractant protein-1 by wound keratinocytes (Wetzler et al., 2000). The proposed hyperpolarisation of diabetic macrophages to activation signals observed in vitro did not fit the original hypothesis of

184

impaired alternative activation, however the pro-inflammatory changes to the non- macrophage populations will promote classical activation. As such a hyperpolarisation phenotype would still fit the excessive inflammation observed in vivo. Analysis of activation states in vivo have since further clarified the nature of macrophages in diabetic wounds (Bannon et al., 2013). At four and seven days post wounding there is an increased proportion of classically activated and reduced alternatively activated macrophages.

The failure of injected M2 polarised macrophages to enhance angiogenesis in excisional wounds further highlights the importance of the whole wound cell population in the regulation of macrophage function and wound healing (Jetten et al., 2014a). That diabetic cells responded differently to the Hoxa3 treatment in terms of their activation potential and interactions with neovascularisation assays also illustrates the complex interactions that must be at play between the intrinsic effects of diabetes and the wound environment. Diabetic Gr-1+ cells isolated from wounds and bone marrow have defective expression of chemokine receptors CCR2 and CxCR2 that may facilitate the differential response of diabetic cells to their environment (Wicks et al., 2015).

To fully dissect the intrinsic and extrinsic effects of diabetes on macrophage phenotype the injection of in vitro differentiated cells into non-diabetic and diabetic derived cells would be used. The use of GFP+ or RFP+ donor cells would also be used so the injected macrophages can be identified in histological analysis of wound healing post injection (Mace et al., 2009). This could even be combined with the further investigations of macrophage maturation using the Cx3cf1GFP as the donor animal to test the effects of the diabetic wound upon the maturation of non-diabetic macrophages. The potential of diabetes to alter response to the same environmental cues would mean the addition of non-diabetic into diabetic animal would be also of interest. 6.7 The use of cell culture systems as a model of in vivo

A core aspect of the experiments presented in this thesis is the use of in vitro cell culture systems and how this relates to the intrinsic and extrinsic effects as discussed. Cell culture systems were used because it meant I could assess the intrinsic effects that diabetes establishes in macrophages isolated from any secondary effects that diabetes

185

has upon other macrophage interacting cells. The RAW 264.7 cell line has been regularly used as a model of murine macrophages (Amura et al., 1998, Levin et al., 2012, Zhu et al., 2014). In the context of this work the RAW cells meant I could investigate the effects of a diabetes-like hyperglycemia specifically upon differentiated macrophages.

Murine bone marrow derived macrophages will have had their diabetic phenotype established in the bone marrow of the diabetic animal as haematopoietic stem/precursor cells, potentially in an epigenetic manner (Wicks et al., 2015, Wicks et al., 2014). By culturing these progenitors to macrophages in vitro I still removed any effects upon their phenotype from interactions with other diabetic cell types during their maturation in the circulation, and upon their extravasation and infiltration of the target tissue, in this case cutaneous wounds. This means the differences in maturation and activation observed between non-diabetic and diabetic derived cells in mine and Bannon’s work is established in the bone marrow.

This isolation from other extrinsic factors (aside from the high glucose) is useful to establish that diabetes does directly modulate macrophage function but it is also important to remember that in vitro systems are never a perfect model of in vivo systems. For example, macrophage differentiation in vivo is not driven solely by a bulk stimulation with M-CSF, as was used in these culture systems. This could mean that the maturation defects seen here are specific to M-CSF stimulation. Similarly the culture methods can themselves affect macrophage activation potential and there are many more activation stimuli than those used in our polarisation experiments (Mosser and Edwards, 2008, Martinez and Gordon, 2014). M-CSF has been reported to promote M2 activation states and so the differentiation protocol may also be altering the activation experiments if these effects persist into the activation stimuli treatments (Martinez et al., 2006). Overall these considerations highlight the power of in vitro systems, but also the need to validate their results in the context of in vivo systems to put these results into context.

Similar considerations must be made for the treatment of cells in an in vitro system with Hoxa3 conditioned medium and how these results may correlate with the effects of whole wound Hoxa3 expression plasmid treatment (Mace et al., 2005). This is the first time the effects of Hoxa3 transcription factor activity (as inferred from Plaur expression)

186

in macrophages has been reported. The effects do not correlate with the changes in macrophage population observed in the whole wound expression treatment. This may be because the macrophages as treated in vitro were not phenotypically the same as those in the wound or that the greater effector of Hoxa3 driven changes in the wound are the other cells observed to express the plasmid; endothelial and epithelial cells (Mace et al., 2005). 6.8 The implications of tissue resident macrophages

The experimental design of the experiments in this thesis did not consider the role of resident macrophages in inflammation and repair. Resident macrophages are established during the primitive wave of haematopoiesis and colonize their target tissue (Orkin and Zon, 2008, Ginhoux et al., 2010). These cells will not be found in bone marrow derived macrophages. Similarly macrophages that mature in the bloodstream may not be accurately represented in bone marrow derived macrophage cultures (Auffray et al., 2007). In some tissues such as the brain these resident cells will clonogenically self- renew their tissue population for the organism’s lifespan entirely independent of definitive bone marrow haematopoiesis (Ginhoux et al., 2010). Other tissues identified to contain such independent primitive wave established include the liver, lung alveolar, spleen and peritoneum (Yona et al., 2013, Schulz et al., 2012).

In the gut the initial influx and proliferation of monocytes is dependent on CCR2 mediated recruitment of circulatory monocytes (Little et al., 2014). Subsequently the recruited and resident macrophages acquire an alternative phenotype but the resident macrophages do not proliferate and expand like in the previously mentioned tissues. The resident population of macrophages in the skin is thought to be the Langerhans cells (LCs) and are derived from both the yolk sac macrophages (minor fraction) and fetal monocytes (Hoeffel et al., 2012, Hoeffel et al., 2015). In cutaneous wound inflammation CCR2 signaling is required for the recruitment of circulating blood monocytes that differentiate into pro-angiogenic macrophages essential for the induction of angiogenesis and tissue repair responses (Willenborg et al., 2012). In CCR2 myeloid- restricted deletion circulating monocytes are unable to enter the wound site leading to a reduced wound monocyte/macrophage population. These cells appear to be essential

187

for tissue vascularisation, tissue growth and myofibroblast differentiation whereas scar formation and wound closure are unaffected by their absence from the wound. Faster wound healing may be associated with higher numbers of LCs, including in diabetic foot ulcers (Stojadinovic et al., 2013, Koschwanez et al., 2015). The contribution of tissue resident macrophages in cutaneous wound healing is not well understood but it does appear that both resident and recruited macrophages contribute to successful wound healing and should be considered in future experimental design.

The use of the Cx3cr1gfp reporter mouse and bone marrow chimeras from Cx3cr1gfp RFP+ animals could be used to further investigate the roles of resident and recruited macrophages in cutaneous wound healing and diabetic wounds. The RFP marker would enable the separation of RFP+GFPhi mature recruited macrophages from the reconstituted bone marrow and RFP-GFPhi tissue resident macrophages. This is a very involved, multi-procedure experiment and would be performed after confirmation of the simpler GFP+ macrophage injections and diabetic Cx3cr1gfp wound healing analysis. 6.9 Review of experimental aims and future investigations

6.9.1 Differentiation of macrophages in models of diabetes

I hypothesized that diabetes impaired macrophage maturation. No maturation phenotype was observed in diabetic macrophage models. This was counter to the observations of macrophage maturation defects in diabetic wounds and in similar in vitro models by other investigators. A more thorough investigation of the differentiation of macrophages at multiple time points in their differentiation may resolve the differences between my results and those of the literature. The differential responses observed in my RAW cell glucose concentration experiments and other published investigations into the effects of high glucose culture may also suggest that the use of high glucose medium for macrophage differentiation cultures may also have been altering the phenotype of the non-diabetic macrophages. Repeating these experiments with low glucose concentrations may also reveal a different response.

188

A C57B/L6db/db Cx3cr1gfp reporter mouse will enable the detailed observation of monocyte to macrophage maturation by the digestion and FACS analysis of wound tissue at multiple time points of healing in lean and diabetic mice.

6.9.2 Activation potential of diabetic macrophages

I hypothesised that diabetes would favour the classical activation of macrophages. Enhancement of classical activation was observed but an increase in alternative activation in response to alternative stimuli was also detected. This may be indicative of a hyperpolarisation phenotype for diabetic derived macrophages. Future investigations could include the activation potential of RAW cells cultured in high glucose and low glucose medium and of rat macrophages see if a similar response occurs in these models.

Serial activation experiments should be performed to test the hypothesis that diabetes impairs the classical to alterative activation switch. Protein expression confirmation of these experiments should have been performed. These have been thoroughly performed in (Bannon et al., 2013) so a novel approach could be to look at the interplay of activation and maturation in FACS analysis of digested diabetic wounds in Cx3cr1gfp reporter animals.

For all these experiments an amendment of the differentiation protocol to use low glucose medium should be considered.

6.9.3 Interaction of diabetic macrophages with neovascularisation

I hypothesised that diabetes would impair the positive effects of M2 and inhibitory effects of M1 macrophages upon neovascularisation. In these experiments no difference was seen between non-diabetic and diabetic derived cells, however there was also no difference between non-diabetic M1 and M2 macrophage treatments. This suggests that for use with activated macrophages the neovascularisation assay requires further optimisation. The activated macrophages should be checked for plasticity of their activation state in angiogenesis growth medium.

Future neovascularisation tests will be prepared with fluorescently labeled HUVECs to facilitate the live or time lapse imaging of vessel growth and interactions of separately

189

labeled macrophages. The effects of these macrophages when injected into the non- diabetic and diabetic wound should also be tested to assess their in vivo effects.

6.9.4 Identification of transcription factors to be tested for endothelial reprogramming potential

Expression of transcription factors in monocytic and endothelial cells was used to validate the differential expression of neovascularisation associated transcription factors identified in a bioinformatics comparison of early and late EPCs. Five of the genes; FOXC1, FOXO1, ID1, NR2F2, and SOX18 were significantly upregulated in endothelial cells. HEY2, MEOX2 and TBX1 were only upregulated in the murine cells. The genes upregulated in both human and murine cell comparisons would be tested first for monocytic to endothelial reprogramming.

6.9.5 Development of an assay to screen transcription factors for monocytic to endothelial reprogramming

Pleiotrophin was proposed as a positive control for the generation of a Nucleofection based method of transgene gene expression to test transcription factors for endothelial reprogramming potential. Rounds of optimisation were unable to generate a Nucleofection protocol where transfected cells survived beyond four days, which was insufficient to detect Pleiotrophin driven monocytic to endothelial transdifferentiation. I was unable to replicate a published endothelial reprogramming of monocytes by treatment with M-CSF and pleiotrophin on a gelatine substrate.

In the future low glucose culture conditions would be tested because high glucose may be inhibiting the endothelial lineage and ROCK inhibitors could be tested to prevent cell death. However, adoption of lentiviral transfection for this assay is probably a simpler method for testing the expression of the transcription factors. 6.9.6 Assess the effects of the validated transcription factors upon THP-1 cell phenotype in the transdifferentiation assay

Because the assay establishment was not successful the transcription factors could not be tested for reprogramming potential.

190

Protein transduction of Hoxa3 using the SP.Hoxa3.mCherry expression construct was tested instead. Expression of potential target gene Plaur were upregulated in Hoxa3 treated macrophages from both mouse and rat. Treatment with Hoxa3 did not promote endothelial transdifferentiation.

In the future we are establishing a purified bacterially expressed Hoxa3 protein system to facilitate the consistent application of a known concentration of Hoxa3 in our experimental treatments. Use of this in all the following aims would be recommended to clarify the effects of Hoxa3.

6.9.7 Effects of Hoxa3 upon macrophage development

Hoxa3 treatment of diabetic derived macrophages was hypothesised to rescue the effects of diabetes and promote macrophage maturation. Gene expression analysis of Hoxa3 treated macrophages did suggest a promotion of macrophage maturation. This went beyond the hypothesis and occurred in both non-diabetic and diabetic derived macrophages. There did appear to be a more significant effect with the treatment of diabetic derived macrophages.

Upregulation of the now macrophage putative Hoxa3 responsive gene Plaur, and the published impairment in diabetes of macrophage chemotaxis, migration and adhesion since the start of this thesis identify this as an important area of future investigation. Efferocytosis is also impaired in diabetic macrophages and would be worth characterising in Hoxa3 treated macrophages. If migration is enhanced by Hoxa3 treatment a requirement for functional Plaur would be hypothesised and tested by antibody ablation.

6.9.8 Effects of Hoxa3 upon macrophage activation

I hypothesised that Hoxa3 treatment would rescue the effects of diabetes upon macrophage maturation, originally hypothesising a reduction of classical activation and enhancement of alternative activation before the observations of elevated responses to both of these stimuli with diabetic macrophages in vitro. Four days of Hoxa3 conditioned medium treatment did not confirm either hypothesis. Treatment of non-diabetic cells had no effect upon the response to classical or alternative stimuli but did upregulate

191

both classical and alternative markers in non-activated macrophages. This may be indicative of priming these macrophages for future activation. Hoxa3 treatment of diabetic derived macrophages enhanced their response to classical stimuli and inhibited their response to alternative stimuli.

Future work should focus on the validation of this phenotype by protein expression markers to confirm the differential response compared to 24 hours of Hoxa3 treatment, which confirmed to my original hypothesis. Plaur expression in activated macrophages should be measured due to its expression in tumour associated macrophages promoting metastatic transformation. The priming of non-diabetic macrophages by Hoxa3 treatment would be investigated by titration of activation signals in vitro. The effects of Hoxa3 upon macrophage activation plasticity should also be investigated. Bioinformatically comparing Hoxa3 treated diabetic wounds to untreated controls, and Hoxa3 treated cultured monocytes and macrophages will be used to identify more Hoxa3 responsive genes to identify other functional pathways that Hoxa3 expression modulates. The interplay of maturation and activation could again be investigated using Cx3Cr1gfp mice.

6.9.9 Effects of Hoxa3 upon macrophage interactions with neovascularization

I hypothesised that macrophages treated with Hoxa3 would promote neovascularisation. Hoxa3 treated non-diabetic macrophages did promote vessel formation in neovascularisation assays in a manner that may be indicative of promoting angiogenic sprouting. Diabetic derived macrophages treated with Hoxa3 inhibited vessel formation in a manner that may be indicative of inhibition of both vasculogenesis and angiogenic sprouting.

Future neovascularisation tests could be prepared with fluorescently labeled HUVECs to facilitate the live or time lapse imaging of vessel growth, which would confirm the inferences of which angiogenic process hoxa3 treated macrophages regulate. The effects of these macrophages when injected into the non-diabetic and diabetic wound should also be tested to assess their in vivo effects. If the neovascularisation assay for untreated cells is optimized and reports significant differences in the response to

192

activated macrophages, the effects of macrophages treated with Hoxa3 and then activated would also be tested in neovascularisation assays. 6.9 Summary

Diabetic macrophages exhibit an elevated response to classical and alternative activation signals that may be indicative of a hyperpolarisation phenotype and is likely to contribute to the excessive inflammatory state of diabetic cutaneous wounds. Treatment of these macrophages for four days with a Hoxa3 conditioned medium upregulates the expression of the plasminogen activator urokinase receptor gene Plaur and enhances the expression of macrophage maturation markers. These macrophages exhibit an enhanced response to classical activation stimuli, a reduced alterative activation response and inhibit the growth of HUVEC vessels in an in vitro neovascularisation assay. These effects of Hoxa3 treatment of diabetic macrophages are unexpected based on the rescue of the inflammatory phenotype with Hoxa3 treatment of diabetic wounds. Non-diabetic macrophages were also treated for four days with a Hoxa3 conditioned medium and exhibited a similar upregulation of macrophage maturation markers. These macrophages showed no difference in activation state polarisation compared to macrophages treated with a control conditioned medium but did upregulate activation markers in unstimulated cells. This may be indicative of a priming for response to low levels of activation stimuli. The Hoxa3 treated non-diabetic cells also promoted the formation of vessel networks in a neovascularisation co-culture assay, possibly through the promotion of angiogenesis (Figure 6.1).

193

+ ? + * Endothelial transdifferentation Endothelial Apoptosis and anti-proliferation Wound migration and retention Activation Endothelial transdifferentationEndothelial and Apoptosis anti-proliferation migration Wound retentionand Activation Monocyte/ macrophage medium * Conditioned Monocyte/ macrophage B D ? Endothelial transdifferentation Endothelial Apoptosis and anti-proliferation Wound migration and retention Activation Endothelial transdifferentation Endothelial and Apoptosis anti-proliferation migration Wound retention and Activation Monocyte/ macrophage medium Conditioned Monocyte/ A macrophage C Figure 6.1 Summary of results A) Baseline observations of non-diabetic cells in vitro. Monocytes differentiated to macrophages. Macrophages can become activated to both activation states and secrete both pro-inflammatory and pro-regeneration/neovascularisation signalling molecules. Macrophages can migrate towards the wound site on chemotaxic gradients and are retained at the wound during the early phases of healing. B) Macrophages from diabetic animals have an impaired maturation phenotype. They hyperpolarise to activation signals but in the wound this is effectively a hyper classical activation due to the inflammatory environment. These macrophages secrete an increased amount of pro-inflammatory signalling molecules. No effect was observed in cell numbers. These cells have impaired chemotaxis, migration and adhesion. C) Macrophages from non-diabetic animals treated with Hoxa3 conditioned medium for four days have increased maturation. Macrophages may be primed for activation and have a pro- neovascularisation phenotype. D) Diabetic macrophages treated with Hoxa3 for four days have

194

a greater increase in maturation over their untreated counterparts. Cells respond to classical activation to a more significant extent than non-diabetic cells and have a negative effect upon neovascularisation. In both Hoxa3 treated populations wound retention and migration is a key area of future interest based on the negative effects of diabetes on these properties and the associations of Hoxa3 responsive gene Plaur to migration in macrophages

.*Using the results of (Bannon et al., 2013). +Conflicting results from 24 hours and four days Hoxa3 treatment, four day results presented in figure.

195

7 References

AGRAWAL, A., GAJGHATE, S., SMITH, H., ANDERSON, D. G., ALBERT, T. J., SHAPIRO, I. M. & RISBUD, M. V. 2008. Cited2 modulates hypoxia-inducible factor-dependent expression of vascular endothelial growth factor in nucleus pulposus cells of the rat intervertebral disc. Arthritis and rheumatism, 58, 3798-808. AICHER, A., ZEIHER, A. M. & DIMMELER, S. 2005. Mobilizing endothelial progenitor cells. Hypertension, 45, 321-5. ALI, S., DRISCOLL, H. E., NEWTON, V. L. & GARDINER, N. J. 2014. Matrix metalloproteinase-2 is downregulated in sciatic nerve by streptozotocin induced diabetes and/or treatment with minocycline: Implications for nerve regeneration. Experimental neurology, 261, 654-65. AMINI, A. R., LAURENCIN, C. T. & NUKAVARAPU, S. P. 2012. Differential analysis of peripheral blood- and bone marrow-derived endothelial progenitor cells for enhanced vascularization in bone tissue engineering. Journal of orthopaedic research : official publication of the Orthopaedic Research Society. AMSELLEM, S., PFLUMIO, F., BARDINET, D., IZAC, B., CHARNEAU, P., ROMEO, P. H., DUBART-KUPPERSCHMITT, A. & FICHELSON, S. 2003. Ex vivo expansion of human hematopoietic stem cells by direct delivery of the HOXB4 homeoprotein. Nature medicine, 9, 1423-7. AMURA, C. R., KAMEI, T., ITO, N., SOARES, M. J. & MORRISON, D. C. 1998. Differential regulation of lipopolysaccharide (LPS) activation pathways in mouse macrophages by LPS-binding proteins. Journal of immunology, 161, 2552-60. ANGHELINA, M., KRISHNAN, P., MOLDOVAN, L. & MOLDOVAN, N. I. 2006. Monocytes/macrophages cooperate with progenitor cells during neovascularization and tissue repair: conversion of cell columns into fibrovascular bundles. The American journal of pathology, 168, 529-41. ARAKAWA, K., ISHIHARA, T., OKU, A., NAWANO, M., UETA, K., KITAMURA, K., MATSUMOTO, M. & SAITO, A. 2001. Improved diabetic syndrome in C57BL/KsJ- db/db mice by oral administration of the Na(+)-glucose cotransporter inhibitor T-1095. British journal of pharmacology, 132, 578-86. ASAHARA, T., MASUDA, H., TAKAHASHI, T., KALKA, C., PASTORE, C., SILVER, M., KEARNE, M., MAGNER, M. & ISNER, J. M. 1999. Bone marrow origin of endothelial progenitor cells responsible for postnatal vasculogenesis in physiological and pathological neovascularization. Circulation research, 85, 221-8. ASAHARA, T., MUROHARA, T., SULLIVAN, A., SILVER, M., VAN DER ZEE, R., LI, T., WITZENBICHLER, B., SCHATTEMAN, G. & ISNER, J. M. 1997. Isolation of putative progenitor endothelial cells for angiogenesis. Science, 275, 964-7. AUFFRAY, C., FOGG, D., GARFA, M., ELAIN, G., JOIN-LAMBERT, O., KAYAL, S., SARNACKI, S., CUMANO, A., LAUVAU, G. & GEISSMANN, F. 2007. Monitoring of blood vessels and tissues by a population of monocytes with patrolling behavior. Science, 317, 666-70.

196

AUVRAY, C., DELAHAYE, A., PFLUMIO, F., HADDAD, R., AMSELLEM, S., MIRI-NEZHAD, A., BROIX, L., YACIA, A., BULLE, F., FICHELSON, S. & VIGON, I. 2012. HOXC4 homeoprotein efficiently expands human hematopoietic stem cells and triggers similar molecular alterations as HOXB4. Haematologica, 97, 168-78. AWAD, O., DEDKOV, E. I., JIAO, C., BLOOMER, S., TOMANEK, R. J. & SCHATTEMAN, G. C. 2006. Differential healing activities of CD34+ and CD14+ endothelial cell progenitors. Arteriosclerosis, thrombosis, and vascular biology, 26, 758-64. AWAD, O., JIAO, C., MA, N., DUNNWALD, M. & SCHATTEMAN, G. C. 2005. Obese diabetic mouse environment differentially affects primitive and monocytic endothelial cell progenitors. Stem cells, 23, 575-83. BAHOU, W. F. & GNATENKO, D. V. 2004. Platelet transcriptome: the application of microarray analysis to platelets. Seminars in thrombosis and hemostasis, 30, 473- 84. BAILEY, A. S., JIANG, S., AFENTOULIS, M., BAUMANN, C. I., SCHROEDER, D. A., OLSON, S. B., WONG, M. H. & FLEMING, W. H. 2004. Transplanted adult hematopoietic stems cells differentiate into functional endothelial cells. Blood, 103, 13-9. BALAJI, S., HAN, N., MOLES, C., SHAABAN, A. F., BOLLYKY, P. L., CROMBLEHOLME, T. M. & KESWANI, S. G. 2015. Angiopoietin-1 improves endothelial progenitor cell- dependent neovascularization in diabetic wounds. Surgery, 158, 846-56. BALAYSSAC, S., BURLINA, F., CONVERT, O., BOLBACH, G., CHASSAING, G. & LEQUIN, O. 2006. Comparison of penetratin and other homeodomain-derived cell- penetrating peptides: interaction in a membrane-mimicking environment and cellular uptake efficiency. Biochemistry, 45, 1408-20. BAMFORTH, S. D., BRAGANCA, J., ELORANTA, J. J., MURDOCH, J. N., MARQUES, F. I., KRANC, K. R., FARZA, H., HENDERSON, D. J., HURST, H. C. & BHATTACHARYA, S. 2001. Cardiac malformations, adrenal agenesis, neural crest defects and exencephaly in mice lacking Cited2, a new Tfap2 co-activator. Nature genetics, 29, 469-74. BANNON, P., WOOD, S., RESTIVO, T., CAMPBELL, L., HARDMAN, M. J. & MACE, K. A. 2013. Diabetes induces stable intrinsic changes to myeloid cells that contribute to chronic inflammation during wound healing in mice. Disease models & mechanisms, 6, 1434-47. BASTARD, J. P., MAACHI, M., LAGATHU, C., KIM, M. J., CARON, M., VIDAL, H., CAPEAU, J. & FEVE, B. 2006. Recent advances in the relationship between obesity, inflammation, and insulin resistance. European cytokine network, 17, 4-12. BAUER, S. M., BAUER, R. J. & VELAZQUEZ, O. C. 2005. Angiogenesis, vasculogenesis, and induction of healing in chronic wounds. Vascular and endovascular surgery, 39, 293-306. BAUM, C. L. & ARPEY, C. J. 2005. Normal cutaneous wound healing: clinical correlation with cellular and molecular events. Dermatologic surgery : official publication for American Society for Dermatologic Surgery [et al.], 31, 674-86; discussion 686.

197

BERRY, F. B., SKARIE, J. M., MIRZAYANS, F., FORTIN, Y., HUDSON, T. J., RAYMOND, V., LINK, B. A. & WALTER, M. A. 2008. FOXC1 is required for cell viability and resistance to oxidative stress in the eye through the transcriptional regulation of FOXO1A. Human molecular genetics, 17, 490-505. BERTOLINI, F., SHAKED, Y., MANCUSO, P. & KERBEL, R. S. 2006. The multifaceted circulating endothelial cell in cancer: towards marker and target identification. Nature reviews. Cancer, 6, 835-45. BHATTACHARYA, S., MICHELS, C. L., LEUNG, M. K., ARANY, Z. P., KUNG, A. L. & LIVINGSTON, D. M. 1999. Functional role of p35srj, a novel p300/CBP binding protein, during transactivation by HIF-1. Genes & development, 13, 64-75. BIAN, Z. M., ELNER, S. G., YOSHIDA, A. & ELNER, V. M. 2003. Human RPE-monocyte co- culture induces chemokine gene expression through activation of MAPK and NIK cascade. Experimental eye research, 76, 573-83. BLEAU, G., MASSICOTTE, F., MERLEN, Y. & BOISVERT, C. 1999. Mammalian chitinase-like proteins. EXS, 87, 211-21. BLONDIN, C., LE DUR, A., CHOLLEY, B., CAROFF, M. & HAEFFNER-CAVAILLON, N. 1997. Lipopolysaccharide complexed with soluble CD14 binds to normal human monocytes. European journal of immunology, 27, 3303-9. BOLTZ-NITULESCU, G., WILTSCHKE, C., HOLZINGER, C., FELLINGER, A., SCHEINER, O., GESSL, A. & FORSTER, O. 1987. Differentiation of rat bone marrow cells into macrophages under the influence of mouse L929 cell supernatant. Journal of leukocyte biology, 41, 83-91. BOURGHARDT PEEBO, B., FAGERHOLM, P., TRANEUS-ROCKERT, C. & LAGALI, N. 2011. Time-lapse in vivo imaging of corneal angiogenesis: the role of inflammatory cells in capillary sprouting. Investigative ophthalmology & visual science, 52, 3060-8. BURBRIDGE, M. F., COGE, F., GALIZZI, J. P., BOUTIN, J. A., WEST, D. C. & TUCKER, G. C. 2002. The role of the matrix metalloproteinases during in vitro vessel formation. Angiogenesis, 5, 215-26. BUSCHMANN, I., KATZER, E. & BODE, C. 2003. Arteriogenesis - is this terminology necessary? Basic research in cardiology, 98, 1-5. CABALLERO, S., SENGUPTA, N., AFZAL, A., CHANG, K. H., LI CALZI, S., GUBERSKI, D. L., KERN, T. S. & GRANT, M. B. 2007. Ischemic vascular damage can be repaired by healthy, but not diabetic, endothelial progenitor cells. Diabetes, 56, 960-7. CARACCIOLO, G., PALCHETTI, S., COLAPICCHIONI, V., DIGIACOMO, L., POZZI, D., CAPRIOTTI, A. L., LA BARBERA, G. & LAGANA, A. 2015. Stealth effect of biomolecular corona on nanoparticle uptake by immune cells. Langmuir : the ACS journal of surfaces and colloids. CHAMBERS, S. E., O'NEILL, C. L., O'DOHERTY, T. M., MEDINA, R. J. & STITT, A. W. 2013. The role of immune-related myeloid cells in angiogenesis. Immunobiology, 218, 1370-5.

198

CHATELIN, L., VOLOVITCH, M., JOLIOT, A. H., PEREZ, F. & PROCHIANTZ, A. 1996. Transcription factor hoxa-5 is taken up by cells in culture and conveyed to their nuclei. Mechanisms of development, 55, 111-7. CHAUDHURY, S., DICKO, C., BURGESS, M., VOLLRATH, F. & CARR, A. J. 2011. Fourier transform infrared spectroscopic analysis of normal and torn rotator-cuff tendons. The Journal of bone and joint surgery. British volume, 93, 370-7. CHAUHAN, A. K., LI, Y. S. & DEUEL, T. F. 1993. Pleiotrophin transforms NIH 3T3 cells and induces tumors in nude mice. Proceedings of the National Academy of Sciences of the United States of America, 90, 679-82. CHEN, D., FOROOTAN, S. S., GOSNEY, J. R., FOROOTAN, F. S. & KE, Y. 2014. Increased expression of Id1 and Id3 promotes tumorigenicity by enhancing angiogenesis and suppressing apoptosis in small cell lung cancer. Genes & cancer, 5, 212-25. CHEN, H., CAMPBELL, R. A., CHANG, Y., LI, M., WANG, C. S., LI, J., SANCHEZ, E., SHARE, M., STEINBERG, J., BERENSON, A., SHALITIN, D., ZENG, Z., GUI, D., PEREZ-PINERA, P., BERENSON, R. J., SAID, J., BONAVIDA, B., DEUEL, T. F. & BERENSON, J. R. 2009a. Pleiotrophin produced by multiple myeloma induces transdifferentiation of monocytes into vascular endothelial cells: a novel mechanism of tumor- induced vasculogenesis. Blood, 113, 1992-2002. CHEN, J., CHEN, S., ZHANG, C., ZHANG, L., XIAO, X., DAS, A., ZHAO, Y., YUAN, B., MORRIS, M., ZHAO, B. & CHEN, Y. 2012. Transfusion of CXCR4-primed endothelial progenitor cells reduces cerebral ischemic damage and promotes repair in db/db diabetic mice. PloS one, 7, e50105. CHEN, L., ZHAO, P., WELLS, L., AMEMIYA, C. T., CONDIE, B. G. & MANLEY, N. R. 2010. Mouse and zebrafish Hoxa3 orthologues have nonequivalent in vivo protein function. Proceedings of the National Academy of Sciences of the United States of America, 107, 10555-60. CHEN, Y., CARLSON, E. C., CHEN, Z. Y., HAMIK, A., JAIN, M. K., DUNWOODIE, S. L. & YANG, Y. C. 2009b. Conditional deletion of Cited2 results in defective corneal epithelial morphogenesis and maintenance. Developmental biology, 334, 243-52. CHEN, Y., COSTA, R. M., LOVE, N. R., SOTO, X., ROTH, M., PAREDES, R. & AMAYA, E. 2009c. C/EBPalpha initiates primitive myelopoiesis in pluripotent embryonic cells. Blood, 114, 40-8. CHEN, Y. & GORSKI, D. H. 2008. Regulation of angiogenesis through a microRNA (miR- 130a) that down-regulates antiangiogenic homeobox genes GAX and HOXA5. Blood, 111, 1217-26. CHEN, Y. H., YANG, C. M., CHANG, S. P. & HU, M. L. 2009d. C/EBP beta and C/EBP delta expression is elevated in the early phase of ethanol-induced hepatosteatosis in mice. Acta pharmacologica Sinica, 30, 1138-43. CHOW, A., HUGGINS, M., AHMED, J., HASHIMOTO, D., LUCAS, D., KUNISAKI, Y., PINHO, S., LEBOEUF, M., NOIZAT, C., VAN ROOIJEN, N., TANAKA, M., ZHAO, Z. J., BERGMAN, A., MERAD, M. & FRENETTE, P. S. 2013. CD169(+) macrophages provide a niche promoting erythropoiesis under homeostasis and stress. Nature medicine, 19, 429-36.

199

CHRISTOFFERSSON, G., VAGESJO, E., VANDOOREN, J., LIDEN, M., MASSENA, S., REINERT, R. B., BRISSOVA, M., POWERS, A. C., OPDENAKKER, G. & PHILLIPSON, M. 2012. VEGF-A recruits a proangiogenic MMP-9-delivering neutrophil subset that induces angiogenesis in transplanted hypoxic tissue. Blood, 120, 4653-62. CHUNG, S., RANJAN, R., LEE, Y. G., PARK, G. Y., KARPURAPU, M., DENG, J., XIAO, L., KIM, J. Y., UNTERMAN, T. G. & CHRISTMAN, J. W. 2015. Distinct role of FoxO1 in M- CSF- and GM-CSF-differentiated macrophages contributes LPS-mediated IL-10: implication in hyperglycemia. Journal of leukocyte biology, 97, 327-39. CLARKE, W. T., EDWARDS, B., MCCULLAGH, K. J., KEMP, M. W., MOORWOOD, C., SHERMAN, D. L., BURGESS, M. & DAVIES, K. E. 2010. Syncoilin modulates peripherin filament networks and is necessary for large-calibre motor neurons. Journal of cell science, 123, 2543-52. COSTA, R. M., SOTO, X., CHEN, Y., ZORN, A. M. & AMAYA, E. 2008. spib is required for primitive myeloid development in Xenopus. Blood, 112, 2287-96. CRANE, M. J., DALEY, J. M., VAN HOUTTE, O., BRANCATO, S. K., HENRY, W. L., JR. & ALBINA, J. E. 2014. The monocyte to macrophage transition in the murine sterile wound. PloS one, 9, e86660. CUMBERBATCH, M., DEARMAN, R. J., GRIFFITHS, C. E. & KIMBER, I. 2000. Langerhans cell migration. Clinical and experimental dermatology, 25, 413-8. DALE, D. C., BOXER, L. & LILES, W. C. 2008. The phagocytes: neutrophils and monocytes. Blood, 112, 935-45. DALEY, J. M., BRANCATO, S. K., THOMAY, A. A., REICHNER, J. S. & ALBINA, J. E. 2010. The phenotype of murine wound macrophages. Journal of leukocyte biology, 87, 59- 67. DANIEL, R. J. & GROVES, R. W. 2002. Increased migration of murine keratinocytes under hypoxia is mediated by induction of urokinase plasminogen activator. The Journal of investigative dermatology, 119, 1304-9. DARBY, I. A., BISUCCI, T., RAGHOENATH, S., OLSSON, J., MUSCAT, G. E. & KOOPMAN, P. 2001. Sox18 is transiently expressed during angiogenesis in granulation tissue of skin wounds with an identical expression pattern to Flk-1 mRNA. Laboratory investigation; a journal of technical methods and pathology, 81, 937-43. DE BRUIJN, M. F., MA, X., ROBIN, C., OTTERSBACH, K., SANCHEZ, M. J. & DZIERZAK, E. 2002. Hematopoietic stem cells localize to the endothelial cell layer in the midgestation mouse aorta. Immunity, 16, 673-83. DE SOUZA, L. F., JARDIM, F. R., SAUTER, I. P., DE SOUZA, M. M. & BERNARD, E. A. 2008. High glucose increases RAW 264.7 macrophages activation by lipoteichoic acid from Staphylococcus aureus. Clinica chimica acta; international journal of clinical chemistry, 398, 130-3. DEL ROSSO, M., DINI, G. & FIBBI, G. 1985. Receptors for plasminogen activator, urokinase, in normal and Rous sarcoma virus-transformed mouse fibroblasts. Cancer research, 45, 630-6.

200

DEROSSI, D., JOLIOT, A. H., CHASSAING, G. & PROCHIANTZ, A. 1994. The third helix of the Antennapedia homeodomain translocates through biological membranes. The Journal of biological chemistry, 269, 10444-50. DHARANEESWARAN, H., ABID, M. R., YUAN, L., DUPUIS, D., BEELER, D., SPOKES, K. C., JANES, L., SCIUTO, T., KANG, P. M., JAMINET, S. C., DVORAK, A., GRANT, M. A., REGAN, E. R. & AIRD, W. C. 2014. FOXO1-mediated activation of Akt plays a critical role in vascular homeostasis. Circulation research, 115, 238-51. DRANOFF, G. & MULLIGAN, R. C. 1994. Activities of granulocyte-macrophage colony- stimulating factor revealed by gene transfer and gene knockout studies. Stem cells, 12 Suppl 1, 173-82; discussion 182-4. DREYMUELLER, D., DENECKE, B., LUDWIG, A. & JAHNEN-DECHENT, W. 2013. Embryonic stem cell-derived M2-like macrophages delay cutaneous wound healing. Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society, 21, 44-54. DUCKWORTH, W. C., FAWCETT, J., REDDY, S. & PAGE, J. C. 2004. Insulin-degrading activity in wound fluid. The Journal of clinical endocrinology and metabolism, 89, 847-51. DUDA, D. G., COHEN, K. S., DI TOMASO, E., AU, P., KLEIN, R. J., SCADDEN, D. T., WILLETT, C. G. & JAIN, R. K. 2006. Differential CD146 expression on circulating versus tissue endothelial cells in rectal cancer patients: implications for circulating endothelial and progenitor cells as biomarkers for antiangiogenic therapy. Journal of clinical oncology : official journal of the American Society of Clinical Oncology, 24, 1449- 53. DUPONT, E., PROCHIANTZ, A. & JOLIOT, A. 2007. Identification of a signal peptide for unconventional secretion. The Journal of biological chemistry, 282, 8994-9000. EDWARDS, J. P., ZHANG, X., FRAUWIRTH, K. A. & MOSSER, D. M. 2006. Biochemical and functional characterization of three activated macrophage populations. Journal of leukocyte biology, 80, 1298-307. EHRCHEN, J., STEINMULLER, L., BARCZYK, K., TENBROCK, K., NACKEN, W., EISENACHER, M., NORDHUES, U., SORG, C., SUNDERKOTTER, C. & ROTH, J. 2007. Glucocorticoids induce differentiation of a specifically activated, anti- inflammatory subtype of human monocytes. Blood, 109, 1265-74. EMING, S. A., SMOLA, H. & KRIEG, T. 2002. Treatment of chronic wounds: state of the art and future concepts. Cells, tissues, organs, 172, 105-17. EMMERSON, E., CAMPBELL, L., DAVIES, F. C., ROSS, N. L., ASHCROFT, G. S., KRUST, A., CHAMBON, P. & HARDMAN, M. J. 2012. Insulin-like growth factor-1 promotes wound healing in estrogen-deprived mice: new insights into cutaneous IGF- 1R/ERalpha cross talk. The Journal of investigative dermatology, 132, 2838-48. FADINI, G. P., SARTORE, S., BAESSO, I., LENZI, M., AGOSTINI, C., TIENGO, A. & AVOGARO, A. 2006a. Endothelial progenitor cells and the diabetic paradox. Diabetes care, 29, 714-6.

201

FADINI, G. P., SCHIAVON, M., CANTINI, M., BAESSO, I., FACCO, M., MIORIN, M., TASSINATO, M., DE KREUTZENBERG, S. V., AVOGARO, A. & AGOSTINI, C. 2006b. Circulating progenitor cells are reduced in patients with severe lung disease. Stem cells, 24, 1806-13. FADOK, V. A., BRATTON, D. L., KONOWAL, A., FREED, P. W., WESTCOTT, J. Y. & HENSON, P. M. 1998. Macrophages that have ingested apoptotic cells in vitro inhibit proinflammatory cytokine production through autocrine/paracrine mechanisms involving TGF-beta, PGE2, and PAF. The Journal of clinical investigation, 101, 890- 8. FALANGA, V. 2004. The chronic wound: impaired healing and solutions in the context of wound bed preparation. Blood cells, molecules & diseases, 32, 88-94. FANTIN, A., VIEIRA, J. M., GESTRI, G., DENTI, L., SCHWARZ, Q., PRYKHOZHIJ, S., PERI, F., WILSON, S. W. & RUHRBERG, C. 2010. Tissue macrophages act as cellular chaperones for vascular anastomosis downstream of VEGF-mediated endothelial tip cell induction. Blood, 116, 829-40. FERNANDEZ, A. Z. 2008. Peroxisome proliferator-activated receptors in the modulation of the immune/inflammatory response in atherosclerosis. PPAR research, 2008, 285842. FERNANDEZ PUJOL, B., LUCIBELLO, F. C., GEHLING, U. M., LINDEMANN, K., WEIDNER, N., ZUZARTE, M. L., ADAMKIEWICZ, J., ELSASSER, H. P., MULLER, R. & HAVEMANN, K. 2000. Endothelial-like cells derived from human CD14 positive monocytes. Differentiation; research in biological diversity, 65, 287-300. FERRANTE, C. J. & LEIBOVICH, S. J. 2012. Regulation of Macrophage Polarization and Wound Healing. Advances in wound care, 1, 10-16. FONTIJN, R. D., VOLGER, O. L., FLEDDERUS, J. O., REIJERKERK, A., DE VRIES, H. E. & HORREVOETS, A. J. 2008. SOX-18 controls endothelial-specific claudin-5 gene expression and barrier function. American journal of physiology. Heart and circulatory physiology, 294, H891-900. FRANGOGIANNIS, N. G., MENDOZA, L. H., REN, G., AKRIVAKIS, S., JACKSON, P. L., MICHAEL, L. H., SMITH, C. W. & ENTMAN, M. L. 2003. MCSF expression is induced in healing myocardial infarcts and may regulate monocyte and endothelial cell phenotype. American journal of physiology. Heart and circulatory physiology, 285, H483-92. FREEDMAN, S. J., SUN, Z. Y., KUNG, A. L., FRANCE, D. S., WAGNER, G. & ECK, M. J. 2003. Structural basis for negative regulation of hypoxia-inducible factor-1alpha by CITED2. Nature structural biology, 10, 504-12. FREY, T. & DE MAIO, A. 2007. Increased expression of CD14 in macrophages after inhibition of the cholesterol biosynthetic pathway by lovastatin. Molecular medicine, 13, 592-604. FUKUCHI, Y., SHIBATA, F., ITO, M., GOTO-KOSHINO, Y., SOTOMARU, Y., KITAMURA, T. & NAKAJIMA, H. 2006. Comprehensive analysis of myeloid lineage conversion using mice expressing an inducible form of C/EBP alpha. The EMBO journal, 25, 3398- 410.

202

FURUYAMA, T., KITAYAMA, K., SHIMODA, Y., OGAWA, M., SONE, K., YOSHIDA-ARAKI, K., HISATSUNE, H., NISHIKAWA, S., NAKAYAMA, K., IKEDA, K., MOTOYAMA, N. & MORI, N. 2004. Abnormal angiogenesis in Foxo1 (Fkhr)-deficient mice. The Journal of biological chemistry, 279, 34741-9. GANTNER, F., KUPFERSCHMIDT, R., SCHUDT, C., WENDEL, A. & HATZELMANN, A. 1997. In vitro differentiation of human monocytes to macrophages: change of PDE profile and its relationship to suppression of tumour necrosis factor-alpha release by PDE inhibitors. British journal of pharmacology, 121, 221-31. GAO, D., NOLAN, D. J., MELLICK, A. S., BAMBINO, K., MCDONNELL, K. & MITTAL, V. 2008. Endothelial progenitor cells control the angiogenic switch in mouse lung metastasis. Science, 319, 195-8. GAPPA-FAHLENKAMP, H. & SHUKLA, A. S. 2009. The effect of short-term, high glucose concentration on endothelial cells and leukocytes in a 3D in vitro human vascular tissue model. In vitro cellular & developmental biology. Animal, 45, 234-42. GEER, D. J. & ANDREADIS, S. T. 2003. A novel role of fibrin in epidermal healing: plasminogen-mediated migration and selective detachment of differentiated keratinocytes. The Journal of investigative dermatology, 121, 1210-6. GEISSMANN, F., JUNG, S. & LITTMAN, D. R. 2003. Blood monocytes consist of two principal subsets with distinct migratory properties. Immunity, 19, 71-82. GILL, M., DIAS, S., HATTORI, K., RIVERA, M. L., HICKLIN, D., WITTE, L., GIRARDI, L., YURT, R., HIMEL, H. & RAFII, S. 2001. Vascular trauma induces rapid but transient mobilization of VEGFR2(+)AC133(+) endothelial precursor cells. Circulation research, 88, 167-74. GINHOUX, F., GRETER, M., LEBOEUF, M., NANDI, S., SEE, P., GOKHAN, S., MEHLER, M. F., CONWAY, S. J., NG, L. G., STANLEY, E. R., SAMOKHVALOV, I. M. & MERAD, M. 2010. Fate mapping analysis reveals that adult microglia derive from primitive macrophages. Science, 330, 841-5. GLOCKER, E. O., KOTLARZ, D., BOZTUG, K., GERTZ, E. M., SCHAFFER, A. A., NOYAN, F., PERRO, M., DIESTELHORST, J., ALLROTH, A., MURUGAN, D., HATSCHER, N., PFEIFER, D., SYKORA, K. W., SAUER, M., KREIPE, H., LACHER, M., NUSTEDE, R., WOELLNER, C., BAUMANN, U., SALZER, U., KOLETZKO, S., SHAH, N., SEGAL, A. W., SAUERBREY, A., BUDERUS, S., SNAPPER, S. B., GRIMBACHER, B. & KLEIN, C. 2009. Inflammatory bowel disease and mutations affecting the interleukin-10 receptor. The New England journal of medicine, 361, 2033-45. GORDON-KEYLOCK, S. & MEDVINSKY, A. 2011. Endothelio-hematopoietic relationship: getting closer to the beginnings. BMC biology, 9, 88. GORDON, S. 2003. Alternative activation of macrophages. Nature reviews. Immunology, 3, 23-35. GORDON, S. & TAYLOR, P. R. 2005. Monocyte and macrophage heterogeneity. Nature reviews. Immunology, 5, 953-64. GORSKI, D. H. & LEAL, A. J. 2003. Inhibition of endothelial cell activation by the homeobox gene Gax. The Journal of surgical research, 111, 91-9.

203

GOTTFRIED, E., KUNZ-SCHUGHART, L. A., WEBER, A., REHLI, M., PEUKER, A., MULLER, A., KASTENBERGER, M., BROCKHOFF, G., ANDREESEN, R. & KREUTZ, M. 2008. Expression of CD68 in non-myeloid cell types. Scandinavian journal of immunology, 67, 453-63. GRAF, T. & ENVER, T. 2009. Forcing cells to change lineages. Nature, 462, 587-94. GRAFF, J. W., DICKSON, A. M., CLAY, G., MCCAFFREY, A. P. & WILSON, M. E. 2012. Identifying functional microRNAs in macrophages with polarized phenotypes. The Journal of biological chemistry, 287, 21816-25. GU, X. Y., SHEN, S. E., HUANG, C. F., LIU, Y. N., CHEN, Y. C., LUO, L., ZENG, Y. & WANG, A. P. 2013. Effect of activated autologous monocytes/macrophages on wound healing in a rodent model of experimental diabetes. Diabetes research and clinical practice, 102, 53-9. GUO, C., SUN, Y., ZHOU, B., ADAM, R. M., LI, X., PU, W. T., MORROW, B. E. & MOON, A. 2011. A Tbx1-Six1/Eya1-Fgf8 genetic pathway controls mammalian cardiovascular and craniofacial morphogenesis. The Journal of clinical investigation, 121, 1585-95. GURDON, J. B. & MELTON, D. A. 2008. Nuclear reprogramming in cells. Science, 322, 1811-5. GURTNER, G. C., WERNER, S., BARRANDON, Y. & LONGAKER, M. T. 2008. Wound repair and regeneration. Nature, 453, 314-21. HAGEMANN, T., BISWAS, S. K., LAWRENCE, T., SICA, A. & LEWIS, C. E. 2009. Regulation of macrophage function in tumors: the multifaceted role of NF-kappaB. Blood, 113, 3139-46. HAGEMANN, T., WILSON, J., BURKE, F., KULBE, H., LI, N. F., PLUDDEMANN, A., CHARLES, K., GORDON, S. & BALKWILL, F. R. 2006. Ovarian cancer cells polarize macrophages toward a tumor-associated phenotype. Journal of immunology, 176, 5023-32. HAMILTON, R. T., BHATTACHARYA, A., WALSH, M. E., SHI, Y., WEI, R., ZHANG, Y., RODRIGUEZ, K. A., BUFFENSTEIN, R., CHAUDHURI, A. R. & VAN REMMEN, H. 2013. Elevated protein carbonylation, and misfolding in sciatic nerve from db/db and Sod1(-/-) mice: plausible link between oxidative stress and demyelination. PloS one, 8, e65725. HANSEN, G., HERCUS, T. R., MCCLURE, B. J., STOMSKI, F. C., DOTTORE, M., POWELL, J., RAMSHAW, H., WOODCOCK, J. M., XU, Y., GUTHRIDGE, M., MCKINSTRY, W. J., LOPEZ, A. F. & PARKER, M. W. 2008. The structure of the GM-CSF receptor complex reveals a distinct mode of cytokine receptor activation. Cell, 134, 496- 507. HAO, N. B., LU, M. H., FAN, Y. H., CAO, Y. L., ZHANG, Z. R. & YANG, S. M. 2012. Macrophages in tumor microenvironments and the progression of tumors. Clinical & developmental immunology, 2012, 948098.

204

HARDMAN, M. J., EMMERSON, E., CAMPBELL, L. & ASHCROFT, G. S. 2008. Selective estrogen receptor modulators accelerate cutaneous wound healing in ovariectomized female mice. Endocrinology, 149, 551-7. HART, J. 2002a. Inflammation. 1: Its role in the healing of acute wounds. Journal of wound care, 11, 205-9. HART, J. 2002b. Inflammation. 2: Its role in the healing of chronic wounds. Journal of wound care, 11, 245-9. HASHIMOTO, D., CHOW, A., NOIZAT, C., TEO, P., BEASLEY, M. B., LEBOEUF, M., BECKER, C. D., SEE, P., PRICE, J., LUCAS, D., GRETER, M., MORTHA, A., BOYER, S. W., FORSBERG, E. C., TANAKA, M., VAN ROOIJEN, N., GARCIA-SASTRE, A., STANLEY, E. R., GINHOUX, F., FRENETTE, P. S. & MERAD, M. 2013. Tissue-resident macrophages self-maintain locally throughout adult life with minimal contribution from circulating monocytes. Immunity, 38, 792-804. HAYASHI, H. & KUME, T. 2008. Foxc transcription factors directly regulate Dll4 and Hey2 expression by interacting with the VEGF-Notch signaling pathways in endothelial cells. PloS one, 3, e2401. HAZRA, S., JARAJAPU, Y. P., STEPPS, V., CABALLERO, S., THINSCHMIDT, J. S., SAUTINA, L., BENGTSSON, N., LICALZI, S., DOMINGUEZ, J., KERN, T. S., SEGAL, M. S., ASH, J. D., SABAN, D. R., BARTELMEZ, S. H. & GRANT, M. B. 2013. Long-term type 1 diabetes influences haematopoietic stem cells by reducing vascular repair potential and increasing inflammatory monocyte generation in a murine model. Diabetologia, 56, 644-53. HE, L. & MARNEROS, A. G. 2014. Doxycycline inhibits polarization of macrophages to the proangiogenic M2-type and subsequent neovascularization. The Journal of biological chemistry, 289, 8019-28. HEDBRANT, A., WIJKANDER, J., SEIDAL, T., DELBRO, D. & ERLANDSSON, A. 2015. Macrophages of M1 phenotype have properties that influence lung cancer cell progression. Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine. HEISSIG, B., WERB, Z., RAFII, S. & HATTORI, K. 2003. Role of c-kit/Kit ligand signaling in regulating vasculogenesis. Thrombosis and haemostasis, 90, 570-6. HERBERT, S. P. & STAINIER, D. Y. 2011. Molecular control of endothelial cell behaviour during blood vessel morphogenesis. Nature reviews. Molecular cell biology, 12, 551-64. HERPERS, R., VAN DE KAMP, E., DUCKERS, H. J. & SCHULTE-MERKER, S. 2008. Redundant roles for sox7 and sox18 in arteriovenous specification in zebrafish. Circulation research, 102, 12-5. HESSE, M., MODOLELL, M., LA FLAMME, A. C., SCHITO, M., FUENTES, J. M., CHEEVER, A. W., PEARCE, E. J. & WYNN, T. A. 2001. Differential regulation of nitric oxide synthase-2 and arginase-1 by type 1/type 2 cytokines in vivo: granulomatous pathology is shaped by the pattern of L-arginine metabolism. Journal of immunology, 167, 6533-44.

205

HILL, J. R., KWON, G., MARSHALL, C. A. & MCDANIEL, M. L. 1998. Hyperglycemic levels of glucose inhibit interleukin 1 release from RAW 264.7 murine macrophages by activation of protein kinase C. The Journal of biological chemistry, 273, 3308-13. HINESCU, M. E., POPESCU, L. M., GHERGHICEANU, M. & FAUSSONE-PELLEGRINI, M. S. 2008. Interstitial Cajal-like cells in rat mesentery: an ultrastructural and immunohistochemical approach. Journal of cellular and molecular medicine, 12, 260-70. HOCHKOEPPLER, A. 2013. Expanding the landscape of recombinant protein production in Escherichia coli. Biotechnology letters, 35, 1971-81. HOEFFEL, G., CHEN, J., LAVIN, Y., LOW, D., ALMEIDA, F. F., SEE, P., BEAUDIN, A. E., LUM, J., LOW, I., FORSBERG, E. C., POIDINGER, M., ZOLEZZI, F., LARBI, A., NG, L. G., CHAN, J. K., GRETER, M., BECHER, B., SAMOKHVALOV, I. M., MERAD, M. & GINHOUX, F. 2015. C-Myb(+) erythro-myeloid progenitor-derived fetal monocytes give rise to adult tissue-resident macrophages. Immunity, 42, 665-78. HOEFFEL, G., WANG, Y., GRETER, M., SEE, P., TEO, P., MALLERET, B., LEBOEUF, M., LOW, D., OLLER, G., ALMEIDA, F., CHOY, S. H., GRISOTTO, M., RENIA, L., CONWAY, S. J., STANLEY, E. R., CHAN, J. K., NG, L. G., SAMOKHVALOV, I. M., MERAD, M. & GINHOUX, F. 2012. Adult Langerhans cells derive predominantly from embryonic fetal liver monocytes with a minor contribution of yolk sac-derived macrophages. The Journal of experimental medicine, 209, 1167-81. HONG, L., KENNEY, S. R., PHILLIPS, G. K., SIMPSON, D., SCHROEDER, C. E., NOTH, J., ROMERO, E., SWANSON, S., WALLER, A., STROUSE, J. J., CARTER, M., CHIGAEV, A., URSU, O., OPREA, T., HJELLE, B., GOLDEN, J. E., AUBE, J., HUDSON, L. G., BURANDA, T., SKLAR, L. A. & WANDINGER-NESS, A. 2013. Characterization of a Cdc42 protein inhibitor and its use as a molecular probe. The Journal of biological chemistry, 288, 8531-43. HONG, S. H., LEE, J. H., LEE, J. B., JI, J. & BHATIA, M. 2011. ID1 and ID3 represent conserved negative regulators of human embryonic and induced pluripotent stem cell hematopoiesis. Journal of cell science, 124, 1445-52. HUA, K. F., WANG, S. H., DONG, W. C., LIN, C. Y., HO, C. L. & WU, T. H. 2012. High glucose increases nitric oxide generation in lipopolysaccharide-activated macrophages by enhancing activity of protein kinase C-alpha/delta and NF-kappaB. Inflammation research : official journal of the European Histamine Research Society ... [et al.], 61, 1107-16. HUAN, Q., WANG, Y., YANG, L., CUI, Y., WEN, J., CHEN, J. & CHEN, Z. J. 2015. Expression and function of the ID1 gene during transforming growth factor-beta1-induced differentiation of human embryonic stem cells to endothelial cells. Cellular reprogramming, 17, 59-68. HUANG, G., ZHANG, P., HIRAI, H., ELF, S., YAN, X., CHEN, Z., KOSCHMIEDER, S., OKUNO, Y., DAYARAM, T., GROWNEY, J. D., SHIVDASANI, R. A., GILLILAND, D. G., SPECK, N. A., NIMER, S. D. & TENEN, D. G. 2008. PU.1 is a major downstream target of AML1 (RUNX1) in adult mouse hematopoiesis. Nature genetics, 40, 51-60.

206

HUANG, S., GUO, Y. P., MAY, G. & ENVER, T. 2007. Bifurcation dynamics in lineage- commitment in bipotent progenitor cells. Developmental biology, 305, 695-713. HUGHES, P. M., BOTHAM, M. S., FRENTZEL, S., MIR, A. & PERRY, V. H. 2002. Expression of fractalkine (CX3CL1) and its receptor, CX3CR1, during acute and chronic inflammation in the rodent CNS. Glia, 37, 314-27. HUMMEL, K. P., DICKIE, M. M. & COLEMAN, D. L. 1966. Diabetes, a new mutation in the mouse. Science, 153, 1127-8. HUR, J., YOON, C. H., KIM, H. S., CHOI, J. H., KANG, H. J., HWANG, K. K., OH, B. H., LEE, M. M. & PARK, Y. B. 2004. Characterization of two types of endothelial progenitor cells and their different contributions to neovasculogenesis. Arteriosclerosis, thrombosis, and vascular biology, 24, 288-93. IACOVINO, M., CHONG, D., SZATMARI, I., HARTWECK, L., RUX, D., CAPRIOLI, A., CLEAVER, O. & KYBA, M. 2011. HoxA3 is an apical regulator of haemogenic endothelium. Nature cell biology, 13, 72-8. ILLEMANN, M., LAERUM, O. D., HASSELBY, J. P., THURISON, T., HOYER-HANSEN, G., NIELSEN, H. J. & CHRISTENSEN, I. J. 2014. Urokinase-type plasminogen activator receptor (uPAR) on tumor-associated macrophages is a marker of poor prognosis in colorectal cancer. Cancer medicine, 3, 855-64. IM, S. A., LEE, Y. R., LEE, Y. H., OH, S. T., GERELCHULUUN, T., KIM, B. H., KIM, Y., YUN, Y. P., SONG, S. & LEE, C. K. 2007. Synergistic activation of monocytes by polysaccharides isolated from Salicornia herbacea and interferon-gamma. Journal of ethnopharmacology, 111, 365-70. IMAI, T., HIESHIMA, K., HASKELL, C., BABA, M., NAGIRA, M., NISHIMURA, M., KAKIZAKI, M., TAKAGI, S., NOMIYAMA, H., SCHALL, T. J. & YOSHIE, O. 1997. Identification and molecular characterization of fractalkine receptor CX3CR1, which mediates both leukocyte migration and adhesion. Cell, 91, 521-30. INGRAM, D. A., MEAD, L. E., TANAKA, H., MEADE, V., FENOGLIO, A., MORTELL, K., POLLOK, K., FERKOWICZ, M. J., GILLEY, D. & YODER, M. C. 2004. Identification of a novel hierarchy of endothelial progenitor cells using human peripheral and umbilical cord blood. Blood, 104, 2752-60. IRRTHUM, A., DEVRIENDT, K., CHITAYAT, D., MATTHIJS, G., GLADE, C., STEIJLEN, P. M., FRYNS, J. P., VAN STEENSEL, M. A. & VIKKULA, M. 2003. Mutations in the transcription factor gene SOX18 underlie recessive and dominant forms of hypotrichosis-lymphedema-telangiectasia. American journal of human genetics, 72, 1470-8. IRUELA-ARISPE, M. L. & DAVIS, G. E. 2009. Cellular and molecular mechanisms of vascular lumen formation. Developmental cell, 16, 222-31. ISHIDA, Y., GAO, J. L. & MURPHY, P. M. 2008. Chemokine receptor CX3CR1 mediates skin wound healing by promoting macrophage and fibroblast accumulation and function. Journal of immunology, 180, 569-79. IVASHKIV, L. B. 2013. Epigenetic regulation of macrophage polarization and function. Trends in immunology, 34, 216-23.

207

IWASAKI, H. & AKASHI, K. 2007. Myeloid lineage commitment from the hematopoietic stem cell. Immunity, 26, 726-40. IWASAKI, H., MIZUNO, S., WELLS, R. A., CANTOR, A. B., WATANABE, S. & AKASHI, K. 2003. GATA-1 converts lymphoid and myelomonocytic progenitors into the megakaryocyte/erythrocyte lineages. Immunity, 19, 451-62. JACQUELIN, S., LICATA, F., DORGHAM, K., HERMAND, P., POUPEL, L., GUYON, E., DETERRE, P., HUME, D. A., COMBADIERE, C. & BOISSONNAS, A. 2013. CX3CR1 reduces Ly6Chigh-monocyte motility within and release from the bone marrow after chemotherapy in mice. Blood, 122, 674-83. JAMESON, J. M., SHARP, L. L., WITHERDEN, D. A. & HAVRAN, W. L. 2004. Regulation of skin cell homeostasis by gamma delta T cells. Frontiers in bioscience : a journal and virtual library, 9, 2640-51. JEROME, L. A. & PAPAIOANNOU, V. E. 2001. DiGeorge syndrome phenotype in mice mutant for the T-box gene, Tbx1. Nature genetics, 27, 286-91. JETTEN, N., ROUMANS, N., GIJBELS, M. J., ROMANO, A., POST, M. J., DE WINTHER, M. P., VAN DER HULST, R. R. & XANTHOULEA, S. 2014a. Wound administration of M2- polarized macrophages does not improve murine cutaneous healing responses. PloS one, 9, e102994. JETTEN, N., VERBRUGGEN, S., GIJBELS, M. J., POST, M. J., DE WINTHER, M. P. & DONNERS, M. M. 2014b. Anti-inflammatory M2, but not pro-inflammatory M1 macrophages promote angiogenesis in vivo. Angiogenesis, 17, 109-18. JIN, X., WANG, F., LIU, X., LIANG, B., CHEN, Z., HE, J., ZHANG, H. & ZHANG, J. 2014. Negative correlation of CD34+ cells with blood-brain barrier permeability following traumatic brain injury in a rat model. Microcirculation, 21, 696-702. KAPOOR, N., NIU, J., SAAD, Y., KUMAR, S., SIRAKOVA, T., BECERRA, E., LI, X. & KOLATTUKUDY, P. E. 2015. Transcription factors STAT6 and KLF4 implement macrophage polarization via the dual catalytic powers of MCPIP. Journal of immunology, 194, 6011-23. KEMP, M. W., EDWARDS, B., BURGESS, M., CLARKE, W. T., NICHOLSON, G., PARRY, D. A. & DAVIES, K. E. 2009. Syncoilin isoform organization and differential expression in murine striated muscle. Journal of structural biology, 165, 196-203. KESSLER, L., WIESEL, M. L., ATTALI, P., MOSSARD, J. M., CAZENAVE, J. P. & PINGET, M. 1998. Von Willebrand factor in diabetic angiopathy. Diabetes & metabolism, 24, 327-36. KHALLOU-LASCHET, J., VARTHAMAN, A., FORNASA, G., COMPAIN, C., GASTON, A. T., CLEMENT, M., DUSSIOT, M., LEVILLAIN, O., GRAFF-DUBOIS, S., NICOLETTI, A. & CALIGIURI, G. 2010. Macrophage plasticity in experimental atherosclerosis. PloS one, 5, e8852. KHANNA, S., BISWAS, S., SHANG, Y., COLLARD, E., AZAD, A., KAUH, C., BHASKER, V., GORDILLO, G. M., SEN, C. K. & ROY, S. 2010. Macrophage dysfunction impairs resolution of inflammation in the wounds of diabetic mice. PloS one, 5, e9539.

208

KHARROUBI, A. T. & DARWISH, H. M. 2015. Diabetes mellitus: The epidemic of the century. World journal of diabetes, 6, 850-67. KHAZEN, W., M'BIKA J, P., TOMKIEWICZ, C., BENELLI, C., CHANY, C., ACHOUR, A. & FOREST, C. 2005. Expression of macrophage-selective markers in human and rodent adipocytes. FEBS letters, 579, 5631-4. KIM, I., YILMAZ, O. H. & MORRISON, S. J. 2005. CD144 (VE-cadherin) is transiently expressed by fetal liver hematopoietic stem cells. Blood, 106, 903-5. KIM, S. Y., KO, Y. S., PARK, J., CHOI, Y., PARK, J. W., KIM, Y., PYO, J. S., YOO, Y. B., LEE, J. S. & LEE, B. L. 2015. Forkhead Transcription Factor FOXO1 Inhibits Angiogenesis in Gastric Cancer in Relation to SIRT1. Cancer research and treatment : official journal of Korean Cancer Association. KINNAIRD, T., STABILE, E., BURNETT, M. S., LEE, C. W., BARR, S., FUCHS, S. & EPSTEIN, S. E. 2004. Marrow-derived stromal cells express genes encoding a broad spectrum of arteriogenic cytokines and promote in vitro and in vivo arteriogenesis through paracrine mechanisms. Circulation research, 94, 678-85. KNIPPER, J. A., WILLENBORG, S., BRINCKMANN, J., BLOCH, W., MAASS, T., WAGENER, R., KRIEG, T., SUTHERLAND, T., MUNITZ, A., ROTHENBERG, M. E., NIEHOFF, A., RICHARDSON, R., HAMMERSCHMIDT, M., ALLEN, J. E. & EMING, S. A. 2015. Interleukin-4 Receptor alpha Signaling in Myeloid Cells Controls Collagen Fibril Assembly in Skin Repair. Immunity, 43, 803-16. KOH, T. J. & DIPIETRO, L. A. 2011. Inflammation and wound healing: the role of the macrophage. Expert reviews in molecular medicine, 13, e23. KOO, H. Y. & KUME, T. 2013. FoxC1-dependent regulation of vascular endothelial growth factor signaling in corneal avascularity. Trends in cardiovascular medicine, 23, 1- 4. KOSCHWANEZ, H., VURNEK, M., WEINMAN, J., TARLTON, J., WHITING, C., AMIRAPU, S., COLGAN, S., LONG, D., JARRETT, P. & BROADBENT, E. 2015. Stress-related changes to immune cells in the skin prior to wounding may impair subsequent healing. Brain, behavior, and immunity. KOUSTENI, S. 2011. FoxO1: a molecule for all seasons. Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research, 26, 912-7. KULISZEWSKI, M. A., WARD, M. R., KOWALEWSKI, J. W., SMITH, A. H., STEWART, D. J., KUTRYK, M. J. & LEONG-POI, H. 2013. A direct comparison of endothelial progenitor cell dysfunction in rat metabolic syndrome and diabetes. Atherosclerosis, 226, 58-66. KUME, T., JIANG, H., TOPCZEWSKA, J. M. & HOGAN, B. L. 2001. The murine winged helix transcription factors, Foxc1 and Foxc2, are both required for cardiovascular development and somitogenesis. Genes & development, 15, 2470-82. KUO, J. H., CUEVAS, I., CHEN, A., DUNN, A., KURI, M. & BOUDREAU, N. 2014. Secreted HoxA3 Promotes Epidermal Proliferation and Angiogenesis in Genetically

209

Modified Three-Dimensional Composite Skin Constructs. Advances in wound care, 3, 605-613. KWON, S. M., LEE, J. H., LEE, S. H., JUNG, S. Y., KIM, D. Y., KANG, S. H., YOO, S. Y., HONG, J. K., PARK, J. H., KIM, J. H., KIM, S. W., KIM, Y. J., LEE, S. J., KIM, H. G. & ASAHARA, T. 2014. Cross talk with hematopoietic cells regulates the endothelial progenitor cell differentiation of CD34 positive cells. PloS one, 9, e106310. LANCRIN, C., SROCZYNSKA, P., STEPHENSON, C., ALLEN, T., KOUSKOFF, V. & LACAUD, G. 2009. The haemangioblast generates haematopoietic cells through a haemogenic endothelium stage. Nature, 457, 892-5. LAVIN, Y., WINTER, D., BLECHER-GONEN, R., DAVID, E., KEREN-SHAUL, H., MERAD, M., JUNG, S. & AMIT, I. 2014. Tissue-resident macrophage enhancer landscapes are shaped by the local microenvironment. Cell, 159, 1312-26. LEE, G. H., PROENCA, R., MONTEZ, J. M., CARROLL, K. M., DARVISHZADEH, J. G., LEE, J. I. & FRIEDMAN, J. M. 1996. Abnormal splicing of the leptin receptor in diabetic mice. Nature, 379, 632-5. LEHMANN, O. J., SOWDEN, J. C., CARLSSON, P., JORDAN, T. & BHATTACHARYA, S. S. 2003. Fox's in development and disease. Trends in genetics : TIG, 19, 339-44. LEIMEISTER, C., EXTERNBRINK, A., KLAMT, B. & GESSLER, M. 1999. Hey genes: a novel subfamily of hairy- and Enhancer of split related genes specifically expressed during mouse embryogenesis. Mechanisms of development, 85, 173-7. LEVIN, M. C., LIDBERG, U., JIRHOLT, P., ADIELS, M., WRAMSTEDT, A., GUSTAFSSON, K., GREAVES, D. R., LI, S., FAZIO, S., LINTON, M. F., OLOFSSON, S. O., BOREN, J. & GJERTSSON, I. 2012. Evaluation of macrophage-specific promoters using lentiviral delivery in mice. Gene therapy, 19, 1041-7. LI, B., POZZI, A. & YOUNG, P. P. 2011. TNFalpha accelerates monocyte to endothelial transdifferentiation in tumors by the induction of integrin alpha5 expression and adhesion to fibronectin. Molecular cancer research : MCR, 9, 702-11. LI, F., GONCALVES, J., FAUGHNAN, K., STEINER, M. G., PAGAN-CHARRY, I., ESPOSITO, D., CHIN, B., PROVIDENCE, K. M., HIGGINS, P. J. & STAIANO-COICO, L. 2000. Targeted inhibition of wound-induced PAI-1 expression alters migration and differentiation in human epidermal keratinocytes. Experimental cell research, 258, 245-53. LI, J., ZHANG, S., SOTO, X., WOOLNER, S. & AMAYA, E. 2013a. ERK and phosphoinositide 3-kinase temporally coordinate different modes of actin-based motility during embryonic wound healing. Journal of cell science, 126, 5005-17. LI, X., LARGE, M. J., CREIGHTON, C. J., LANZ, R. B., JEONG, J. W., YOUNG, S. L., LESSEY, B. A., PALOMINO, W. A., TSAI, S. Y. & DEMAYO, F. J. 2013b. COUP-TFII regulates human endometrial stromal genes involved in inflammation. Molecular endocrinology, 27, 2041-54. LI, Y. S., GURRIERI, M. & DEUEL, T. F. 1992. Pleiotrophin gene expression is highly restricted and is regulated by platelet-derived growth factor. Biochemical and biophysical research communications, 184, 427-32.

210

LIN, Y., WEISDORF, D. J., SOLOVEY, A. & HEBBEL, R. P. 2000. Origins of circulating endothelial cells and endothelial outgrowth from blood. The Journal of clinical investigation, 105, 71-7. LING, L., SHEN, Y., WANG, K., JIANG, C., FANG, C., FERRO, A., KANG, L. & XU, B. 2012. Worse clinical outcomes in acute myocardial infarction patients with type 2 diabetes mellitus: relevance to impaired endothelial progenitor cells mobilization. PloS one, 7, e50739. LITTLE, M. C., HURST, R. J. & ELSE, K. J. 2014. Dynamic changes in macrophage activation and proliferation during the development and resolution of intestinal inflammation. Journal of immunology, 193, 4684-95. LIU, M., ZHANG, Y., XIONG, J. Y., WANG, Y. & LV, S. 2015. Etomidate Mitigates Lipopolysaccharide-Induced CD14 and TREM-1 Expression, NF-kappaB Activation, and Pro-inflammatory Cytokine Production in Rat Macrophages. Inflammation. LIU, Z. J. & VELAZQUEZ, O. C. 2008. Hyperoxia, endothelial progenitor cell mobilization, and diabetic wound healing. Antioxidants & redox signaling, 10, 1869-82. LIVAK, K. J. & SCHMITTGEN, T. D. 2001. Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods, 25, 402-8. LOMBARDO, M. F., IACOPINO, P., CUZZOLA, M., SPINIELLO, E., GARREFFA, C., FERRELLI, F., COPPOLA, A., SACCARDI, R., PIAGGESI, A., PIRO, R., MANNINO, D., GROSSI, G., LAURO, D. & IRRERA, G. 2012. Type 2 diabetes mellitus impairs the maturation of endothelial progenitor cells and increases the number of circulating endothelial cells in peripheral blood. Cytometry. Part A : the journal of the International Society for Analytical Cytology, 81, 856-64. LOOTS, M. A., LAMME, E. N., ZEEGELAAR, J., MEKKES, J. R., BOS, J. D. & MIDDELKOOP, E. 1998. Differences in cellular infiltrate and extracellular matrix of chronic diabetic and venous ulcers versus acute wounds. The Journal of investigative dermatology, 111, 850-7. LOPES FLORO, K., ARTAP, S. T., PREIS, J. I., FATKIN, D., CHAPMAN, G., FURTADO, M. B., HARVEY, R. P., HAMADA, H., SPARROW, D. B. & DUNWOODIE, S. L. 2011. Loss of Cited2 causes congenital heart disease by perturbing left-right patterning of the body axis. Human molecular genetics, 20, 1097-110. LOU, X., SUN, S., CHEN, W., ZHOU, Y., HUANG, Y., LIU, X., SHAN, Y. & WANG, C. 2011. Negative feedback regulation of NF-kappaB action by CITED2 in the nucleus. Journal of immunology, 186, 539-48. LUCAS, T., WAISMAN, A., RANJAN, R., ROES, J., KRIEG, T., MULLER, W., ROERS, A. & EMING, S. A. 2010. Differential roles of macrophages in diverse phases of skin repair. Journal of immunology, 184, 3964-77. LUMENG, C. N., BODZIN, J. L. & SALTIEL, A. R. 2007a. Obesity induces a phenotypic switch in adipose tissue macrophage polarization. The Journal of clinical investigation, 117, 175-84.

211

LUMENG, C. N., DEYOUNG, S. M., BODZIN, J. L. & SALTIEL, A. R. 2007b. Increased inflammatory properties of adipose tissue macrophages recruited during diet- induced obesity. Diabetes, 56, 16-23. MACDONALD, K. P., PALMER, J. S., CRONAU, S., SEPPANEN, E., OLVER, S., RAFFELT, N. C., KUNS, R., PETTIT, A. R., CLOUSTON, A., WAINWRIGHT, B., BRANSTETTER, D., SMITH, J., PAXTON, R. J., CERRETTI, D. P., BONHAM, L., HILL, G. R. & HUME, D. A. 2010. An antibody against the colony-stimulating factor 1 receptor depletes the resident subset of monocytes and tissue- and tumor-associated macrophages but does not inhibit inflammation. Blood, 116, 3955-63. MACE, K. A., HANSEN, S. L., MYERS, C., YOUNG, D. M. & BOUDREAU, N. 2005. HOXA3 induces cell migration in endothelial and epithelial cells promoting angiogenesis and wound repair. Journal of cell science, 118, 2567-77. MACE, K. A., RESTIVO, T. E., RINN, J. L., PAQUET, A. C., CHANG, H. Y., YOUNG, D. M. & BOUDREAU, N. J. 2009. HOXA3 modulates injury-induced mobilization and recruitment of bone marrow-derived cells. Stem cells, 27, 1654-65. MAHDAVIAN DELAVARY, B., VAN DER VEER, W. M., VAN EGMOND, M., NIESSEN, F. B. & BEELEN, R. H. 2011. Macrophages in skin injury and repair. Immunobiology, 216, 753-62. MAHDIPOUR, E., CHARNOCK, J. C. & MACE, K. A. 2011. Hoxa3 promotes the differentiation of hematopoietic progenitor cells into proangiogenic Gr- 1+CD11b+ myeloid cells. Blood, 117, 815-26. MANIGRASSO, M. B. & O'CONNOR, J. P. 2008. Comparison of fracture healing among different inbred mouse strains. Calcified tissue international, 82, 465-74. MANRIQUE, I., NGUEWA, P., BLEAU, A. M., NISTAL-VILLAN, E., LOPEZ, I., VILLALBA, M., GIL-BAZO, I. & CALVO, A. 2015. The inhibitor of differentiation isoform Id1b, generated by alternative splicing, maintains cell quiescence and confers self- renewal and cancer stem cell-like properties. Cancer letters, 356, 899-909. MANTOVANI, A., SOZZANI, S., LOCATI, M., ALLAVENA, P. & SICA, A. 2002. Macrophage polarization: tumor-associated macrophages as a paradigm for polarized M2 mononuclear phagocytes. Trends in immunology, 23, 549-55. MARAGANORE, J. M. 1993. Thrombin, thrombin inhibitors, and the arterial thrombotic process. Thrombosis and haemostasis, 70, 208-11. MARCHETTI, V., YANES, O., AGUILAR, E., WANG, M., FRIEDLANDER, D., MORENO, S., STORM, K., ZHAN, M., NACCACHE, S., NEMEROW, G., SIUZDAK, G. & FRIEDLANDER, M. 2011. Differential macrophage polarization promotes tissue remodeling and repair in a model of ischemic retinopathy. Scientific reports, 1, 76. MARTINEZ-FERRER, M., AFSHAR-SHERIF, A. R., UWAMARIYA, C., DE CROMBRUGGHE, B., DAVIDSON, J. M. & BHOWMICK, N. A. 2010. Dermal transforming growth factor- beta responsiveness mediates wound contraction and epithelial closure. The American journal of pathology, 176, 98-107.

212

MARTINEZ, F. O. & GORDON, S. 2014. The M1 and M2 paradigm of macrophage activation: time for reassessment. F1000prime reports, 6, 13. MARTINEZ, F. O., GORDON, S., LOCATI, M. & MANTOVANI, A. 2006. Transcriptional profiling of the human monocyte-to-macrophage differentiation and polarization: new molecules and patterns of gene expression. Journal of immunology, 177, 7303-11. MARTINEZ, F. O., SICA, A., MANTOVANI, A. & LOCATI, M. 2008. Macrophage activation and polarization. Frontiers in bioscience : a journal and virtual library, 13, 453- 61. MATSUKAWA, M., SAKAMOTO, H., KAWASUJI, M., FURUYAMA, T. & OGAWA, M. 2009. Different roles of Foxo1 and Foxo3 in the control of endothelial cell morphology. Genes to cells : devoted to molecular & cellular mechanisms, 14, 1167-81. MCCULLAGH, K. J., EDWARDS, B., KEMP, M. W., GILES, L. C., BURGESS, M. & DAVIES, K. E. 2008. Analysis of skeletal muscle function in the C57BL6/SV129 syncoilin knockout mouse. Mammalian genome : official journal of the International Mammalian Genome Society, 19, 339-51. MEDINA, R. J., O'NEILL, C. L., SWEENEY, M., GUDURIC-FUCHS, J., GARDINER, T. A., SIMPSON, D. A. & STITT, A. W. 2010. Molecular analysis of endothelial progenitor cell (EPC) subtypes reveals two distinct cell populations with different identities. BMC medical genomics, 3, 18. MELLOTT, A. J., FORREST, M. L. & DETAMORE, M. S. 2013. Physical non-viral gene delivery methods for tissue engineering. Annals of biomedical engineering, 41, 446-68. MELLOTT, A. J., GODSEY, M. E., SHINOGLE, H. E., MOORE, D. S., FORREST, M. L. & DETAMORE, M. S. 2014. Improving viability and transfection efficiency with human umbilical cord wharton's jelly cells through use of a ROCK inhibitor. Cellular reprogramming, 16, 91-7. MIRZA, R. & KOH, T. J. 2011. Dysregulation of monocyte/macrophage phenotype in wounds of diabetic mice. Cytokine, 56, 256-64. MIRZA, R. E., FANG, M. M., WEINHEIMER-HAUS, E. M., ENNIS, W. J. & KOH, T. J. 2014. Sustained inflammasome activity in macrophages impairs wound healing in type 2 diabetic humans and mice. Diabetes, 63, 1103-14. MOEENREZAKHANLOU, A., SHEPHARD, L., LAM, L. & REINER, N. E. 2008. Myeloid cell differentiation in response to calcitriol for expression CD11b and CD14 is regulated by myeloid zinc finger-1 protein downstream of phosphatidylinositol 3-kinase. Journal of leukocyte biology, 84, 519-28. MORAN, M. M., VIRDI, A. S., SENA, K., MAZZONE, S. R., MCNULTY, M. A. & SUMNER, D. R. 2015. Intramembranous bone regeneration differs among common inbred mouse strains following marrow ablation. Journal of orthopaedic research : official publication of the Orthopaedic Research Society, 33, 1374-81.

213

MORI, R., SHAW, T. J. & MARTIN, P. 2008. Molecular mechanisms linking wound inflammation and fibrosis: knockdown of osteopontin leads to rapid repair and reduced scarring. The Journal of experimental medicine, 205, 43-51. MORI, R., TANAKA, K., DE KERCKHOVE, M., OKAMOTO, M., KASHIYAMA, K., KIM, S., KAWATA, T., KOMATSU, T., PARK, S., IKEMATSU, K., HIRANO, A., MARTIN, P. & SHIMOKAWA, I. 2014. Reduced FOXO1 expression accelerates skin wound healing and attenuates scarring. The American journal of pathology, 184, 2465- 79. MOSSER, D. M. & EDWARDS, J. P. 2008. Exploring the full spectrum of macrophage activation. Nature reviews. Immunology, 8, 958-69. MOSTAGHACI, B., SUSEWIND, J., KICKELBICK, G., LEHR, C. M. & LORETZ, B. 2015. Transfection system of amino-functionalized calcium phosphate nanoparticles: in vitro efficacy, biodegradability, and immunogenicity study. ACS applied materials & interfaces, 7, 5124-33. MOTYL, K. & MCCABE, L. R. 2009. Streptozotocin, type I diabetes severity and bone. Biological procedures online, 11, 296-315. MULDER, G. D. 2001. Diabetic foot ulcers: old problems--new technologies. Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association, 16, 695-8. MURRAY, P. J., ALLEN, J. E., BISWAS, S. K., FISHER, E. A., GILROY, D. W., GOERDT, S., GORDON, S., HAMILTON, J. A., IVASHKIV, L. B., LAWRENCE, T., LOCATI, M., MANTOVANI, A., MARTINEZ, F. O., MEGE, J. L., MOSSER, D. M., NATOLI, G., SAEIJ, J. P., SCHULTZE, J. L., SHIREY, K. A., SICA, A., SUTTLES, J., UDALOVA, I., VAN GINDERACHTER, J. A., VOGEL, S. N. & WYNN, T. A. 2014. Macrophage activation and polarization: nomenclature and experimental guidelines. Immunity, 41, 14- 20. NOLI, C. & MIOLO, A. 2001. The mast cell in wound healing. Veterinary dermatology, 12, 303-13. NOTTINGHAM, W. T., JARRATT, A., BURGESS, M., SPECK, C. L., CHENG, J. F., PRABHAKAR, S., RUBIN, E. M., LI, P. S., SLOANE-STANLEY, J., KONG, A. S. J. & DE BRUIJN, M. F. 2007. Runx1-mediated hematopoietic stem-cell emergence is controlled by a Gata/Ets/SCL-regulated enhancer. Blood, 110, 4188-97. NUUTILA, K., SILTANEN, A., PEURA, M., BIZIK, J., KAARTINEN, I., KUOKKANEN, H., NIEMINEN, T., HARJULA, A., AARNIO, P., VUOLA, J. & KANKURI, E. 2012. Human skin transcriptome during superficial cutaneous wound healing. Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society, 20, 830-9. O'SHEA, J. J. & MURRAY, P. J. 2008. Cytokine signaling modules in inflammatory responses. Immunity, 28, 477-87. OH, H., TAKAGI, H., TAKAGI, C., SUZUMA, K., OTANI, A., ISHIDA, K., MATSUMURA, M., OGURA, Y. & HONDA, Y. 1999. The potential angiogenic role of macrophages in the formation of choroidal neovascular membranes. Investigative ophthalmology & visual science, 40, 1891-8.

214

OKABE, Y. & MEDZHITOV, R. 2014. Tissue-specific signals control reversible program of localization and functional polarization of macrophages. Cell, 157, 832-44. ORKIN, S. H. & ZON, L. I. 2008. Hematopoiesis: an evolving paradigm for stem cell biology. Cell, 132, 631-44. OWEN, J. L. & MOHAMADZADEH, M. 2013. Macrophages and chemokines as mediators of angiogenesis. Frontiers in physiology, 4, 159. PACE, J. L., RUSSELL, S. W., SCHREIBER, R. D., ALTMAN, A. & KATZ, D. H. 1983. Macrophage activation: priming activity from a T-cell hybridoma is attributable to interferon-gamma. Proceedings of the National Academy of Sciences of the United States of America, 80, 3782-6. PADRON-BARTHE, L., TEMINO, S., VILLA DEL CAMPO, C., CARRAMOLINO, L., ISERN, J. & TORRES, M. 2014. Clonal analysis identifies hemogenic endothelium as the source of the blood-endothelial common lineage in the mouse embryo. Blood, 124, 2523-32. PALMIERI, D., MURA, M., MAMBRINI, S. & PALOMBO, D. 2015. Effects of Pleiotrophin on endothelial and inflammatory cells: Pro-angiogenic and anti-inflammatory properties and potential role for vascular bio-prosthesis endothelialization. Advances in medical sciences, 60, 287-293. PAPADIMITRIOU, E., MIKELIS, C., LAMPROPOULOU, E., KOUTSIOUMPA, M., THEOCHARI, K., TSIRMOULA, S., THEODOROPOULOU, C., LAMPROU, M., SFAELOU, E., VOURTSIS, D. & BOUDOURIS, P. 2009. Roles of pleiotrophin in tumor growth and angiogenesis. European cytokine network, 20, 180-90. PARFENOVA, H., LEFFLER, C. W., TCHERANOVA, D., BASUROY, S. & ZIMMERMANN, A. 2010. Epileptic seizures increase circulating endothelial cells in peripheral blood as early indicators of cerebral vascular damage. American journal of physiology. Heart and circulatory physiology, 298, H1687-98. PARK-MIN, K. H., ANTONIV, T. T. & IVASHKIV, L. B. 2005. Regulation of macrophage phenotype by long-term exposure to IL-10. Immunobiology, 210, 77-86. PARK, S. H., SAKAMOTO, H., TSUJI-TAMURA, K., FURUYAMA, T. & OGAWA, M. 2009. Foxo1 is essential for in vitro vascular formation from embryonic stem cells. Biochemical and biophysical research communications, 390, 861-6. PEICHEV, M., NAIYER, A. J., PEREIRA, D., ZHU, Z., LANE, W. J., WILLIAMS, M., OZ, M. C., HICKLIN, D. J., WITTE, L., MOORE, M. A. & RAFII, S. 2000. Expression of VEGFR-2 and AC133 by circulating human CD34(+) cells identifies a population of functional endothelial precursors. Blood, 95, 952-8. PELOSI, E., VALTIERI, M., COPPOLA, S., BOTTA, R., GABBIANELLI, M., LULLI, V., MARZIALI, G., MASELLA, B., MULLER, R., SGADARI, C., TESTA, U., BONANNO, G. & PESCHLE, C. 2002. Identification of the hemangioblast in postnatal life. Blood, 100, 3203- 8. PEREIRA, F. A., QIU, Y., ZHOU, G., TSAI, M. J. & TSAI, S. Y. 1999. The orphan nuclear receptor COUP-TFII is required for angiogenesis and heart development. Genes & development, 13, 1037-49.

215

PERRY, V. H. & HOLMES, C. 2014. Microglial priming in neurodegenerative disease. Nature reviews. Neurology, 10, 217-24. PORTA, M., LA SELVA, M. & MOLINATTI, P. A. 1991. von Willebrand factor and endothelial abnormalities in diabetic microangiopathy. Diabetes care, 14, 167- 72. PORTER, J. F., SHARMA, S., WILSON, D. L., KAPPIL, M. A., HART, R. P. & DENHARDT, D. T. 2005. Tissue inhibitor of metalloproteinases-1 stimulates gene expression in MDA-MB-435 human breast cancer cells by means of its ability to inhibit metalloproteinases. Breast cancer research and treatment, 94, 185-93. PRASITSAK, T., NANDAR, M., OKUHARA, S., ICHINOSE, S., OTA, M. S. & ISEKI, S. 2015. Foxc1 is required for early stage telencephalic vascular development. Developmental dynamics : an official publication of the American Association of Anatomists, 244, 703-11. PRATER, D. N., CASE, J., INGRAM, D. A. & YODER, M. C. 2007. Working hypothesis to redefine endothelial progenitor cells. Leukemia : official journal of the Leukemia Society of America, Leukemia Research Fund, U.K, 21, 1141-9. QIN, J., CHEN, X., XIE, X., TSAI, M. J. & TSAI, S. Y. 2010a. COUP-TFII regulates tumor growth and metastasis by modulating tumor angiogenesis. Proceedings of the National Academy of Sciences of the United States of America, 107, 3687-92. QIN, J., CHEN, X., YU-LEE, L. Y., TSAI, M. J. & TSAI, S. Y. 2010b. Nuclear receptor COUP- TFII controls pancreatic islet tumor angiogenesis by regulating vascular endothelial growth factor/vascular endothelial growth factor receptor-2 signaling. Cancer research, 70, 8812-21. QIU, J., WANG, G., HU, J., PENG, Q. & ZHENG, Y. 2011. Id1-induced inhibition of p53 facilitates endothelial cell migration and tube formation by regulating the expression of beta1-integrin. Molecular and cellular biochemistry, 357, 125-33. RAI, M. F., HASHIMOTO, S., JOHNSON, E. E., JANISZAK, K. L., FITZGERALD, J., HEBER-KATZ, E., CHEVERUD, J. M. & SANDELL, L. J. 2012. Heritability of articular cartilage regeneration and its association with ear wound healing in mice. Arthritis and rheumatism, 64, 2300-10. RANDOLPH, G. J., INABA, K., ROBBIANI, D. F., STEINMAN, R. M. & MULLER, W. A. 1999. Differentiation of phagocytic monocytes into lymph node dendritic cells in vivo. Immunity, 11, 753-61. REHMAN, J., LI, J., ORSCHELL, C. M. & MARCH, K. L. 2003. Peripheral blood "endothelial progenitor cells" are derived from monocyte/macrophages and secrete angiogenic growth factors. Circulation, 107, 1164-9. RHODES, J., HAGEN, A., HSU, K., DENG, M., LIU, T. X., LOOK, A. T. & KANKI, J. P. 2005. Interplay of pu.1 and gata1 determines myelo-erythroid progenitor cell fate in zebrafish. Developmental cell, 8, 97-108. ROSS, R., EVERETT, N. B. & TYLER, R. 1970. Wound healing and collagen formation. VI. The origin of the wound fibroblast studied in parabiosis. The Journal of cell biology, 44, 645-54.

216

RUZINOVA, M. B. & BENEZRA, R. 2003. Id proteins in development, cell cycle and cancer. Trends in cell biology, 13, 410-8. RUZINOVA, M. B., SCHOER, R. A., GERALD, W., EGAN, J. E., PANDOLFI, P. P., RAFII, S., MANOVA, K., MITTAL, V. & BENEZRA, R. 2003. Effect of angiogenesis inhibition by Id loss and the contribution of bone-marrow-derived endothelial cells in spontaneous murine tumors. Cancer cell, 4, 277-89. SAHIN, M. B., SCHWARTZ, R. E., BUCKLEY, S. M., HEREMANS, Y., CHASE, L., HU, W. S. & VERFAILLIE, C. M. 2008. Isolation and characterization of a novel population of progenitor cells from unmanipulated rat liver. Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society, 14, 333-45. SAMANT, G. V., SCHUPP, M. O., FRANCOIS, M., MOLERI, S., KOTHINTI, R. K., CHUN, C. Z., SINHA, I., SELLARS, S., LEIGH, N., PRAMANIK, K., HORSWILL, M. A., REMADEVI, I., LI, K., WILKINSON, G. A., TABATABAI, N. M., BELTRAME, M., KOOPMAN, P. & RAMCHANDRAN, R. 2011. Sox factors transcriptionally regulate ROBO4 gene expression in developing vasculature in zebrafish. The Journal of biological chemistry, 286, 30740-7. SBARRA, A. J. & SHIRLEY, W. 1963. Phagocytosis Inhibition and Reversal. I. Effect of Glycolytic Intermediates and Nucleotides on Particle Uptake. Journal of bacteriology, 86, 259-65. SCHAFER, D. P., LEHRMAN, E. K., KAUTZMAN, A. G., KOYAMA, R., MARDINLY, A. R., YAMASAKI, R., RANSOHOFF, R. M., GREENBERG, M. E., BARRES, B. A. & STEVENS, B. 2012. Microglia sculpt postnatal neural circuits in an activity and complement- dependent manner. Neuron, 74, 691-705. SCHMEISSER, A., GARLICHS, C. D., ZHANG, H., ESKAFI, S., GRAFFY, C., LUDWIG, J., STRASSER, R. H. & DANIEL, W. G. 2001. Monocytes coexpress endothelial and macrophagocytic lineage markers and form cord-like structures in Matrigel under angiogenic conditions. Cardiovascular research, 49, 671-80. SCHNEIDER, C. A., RASBAND, W. S. & ELICEIRI, K. W. 2012. NIH Image to ImageJ: 25 years of image analysis. Nature methods, 9, 671-5. SCHNOOR, M., BUERS, I., SIETMANN, A., BRODDE, M. F., HOFNAGEL, O., ROBENEK, H. & LORKOWSKI, S. 2009. Efficient non-viral transfection of THP-1 cells. Journal of immunological methods, 344, 109-15. SCHULZ, C., GOMEZ PERDIGUERO, E., CHORRO, L., SZABO-ROGERS, H., CAGNARD, N., KIERDORF, K., PRINZ, M., WU, B., JACOBSEN, S. E., POLLARD, J. W., FRAMPTON, J., LIU, K. J. & GEISSMANN, F. 2012. A lineage of myeloid cells independent of Myb and hematopoietic stem cells. Science, 336, 86-90. SCHURMANN, C., SCHMIDT, N., SEITZ, O., PFEILSCHIFTER, J. & FRANK, S. 2014. Angiogenic response pattern during normal and impaired skin flap re-integration in mice: a comparative study. Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery, 42, 1710-6.

217

SCHWENDE, H., FITZKE, E., AMBS, P. & DIETER, P. 1996. Differences in the state of differentiation of THP-1 cells induced by phorbol ester and 1,25- dihydroxyvitamin D3. Journal of leukocyte biology, 59, 555-61. SEAGER DANCIGER, J., LUTZ, M., HAMA, S., CRUZ, D., CASTRILLO, A., LAZARO, J., PHILLIPS, R., PREMACK, B. & BERLINER, J. 2004. Method for large scale isolation, culture and cryopreservation of human monocytes suitable for chemotaxis, cellular adhesion assays, macrophage and dendritic cell differentiation. Journal of immunological methods, 288, 123-34. SEEGER, F. H., HAENDELER, J., WALTER, D. H., ROCHWALSKY, U., REINHOLD, J., URBICH, C., ROSSIG, L., CORBAZ, A., CHVATCHKO, Y., ZEIHER, A. M. & DIMMELER, S. 2005. p38 mitogen-activated protein kinase downregulates endothelial progenitor cells. Circulation, 111, 1184-91. SEGERER, S., HUGHES, E., HUDKINS, K. L., MACK, M., GOODPASTER, T. & ALPERS, C. E. 2002. Expression of the fractalkine receptor (CX3CR1) in human kidney diseases. Kidney international, 62, 488-95. SEO, S., FUJITA, H., NAKANO, A., KANG, M., DUARTE, A. & KUME, T. 2006. The forkhead transcription factors, Foxc1 and Foxc2, are required for arterial specification and lymphatic sprouting during vascular development. Developmental biology, 294, 458-70. SEO, S. & KUME, T. 2006. Forkhead transcription factors, Foxc1 and Foxc2, are required for the morphogenesis of the cardiac outflow tract. Developmental biology, 296, 421-36. SERBINA, N. V. & PAMER, E. G. 2006. Monocyte emigration from bone marrow during bacterial infection requires signals mediated by chemokine receptor CCR2. Nature immunology, 7, 311-7. SHAKED, Y., BERTOLINI, F., MAN, S., ROGERS, M. S., CERVI, D., FOUTZ, T., RAWN, K., VOSKAS, D., DUMONT, D. J., BEN-DAVID, Y., LAWLER, J., HENKIN, J., HUBER, J., HICKLIN, D. J., D'AMATO, R. J. & KERBEL, R. S. 2005. Genetic heterogeneity of the vasculogenic phenotype parallels angiogenesis; Implications for cellular surrogate marker analysis of antiangiogenesis. Cancer cell, 7, 101-11. SHANG, Y. Y., FANG, N. N., WANG, F., WANG, H., WANG, Z. H., TANG, M. X., PENG, J., ZHANG, Y., ZHANG, W. & ZHONG, M. 2015. MicroRNA-21, induced by high glucose, modulates macrophage apoptosis via programmed cell death 4. Molecular medicine reports, 12, 463-9. SHARIFI, B. G., ZENG, Z., WANG, L., SONG, L., CHEN, H., QIN, M., SIERRA-HONIGMANN, M. R., WACHSMANN-HOGIU, S. & SHAH, P. K. 2006. Pleiotrophin induces transdifferentiation of monocytes into functional endothelial cells. Arteriosclerosis, thrombosis, and vascular biology, 26, 1273-80. SHAW, T. & MARTIN, P. 2009a. Epigenetic reprogramming during wound healing: loss of polycomb-mediated silencing may enable upregulation of repair genes. EMBO reports, 10, 881-6. SHAW, T. J. & MARTIN, P. 2009b. Wound repair at a glance. Journal of cell science, 122, 3209-13.

218

SHI, Q., RAFII, S., WU, M. H., WIJELATH, E. S., YU, C., ISHIDA, A., FUJITA, Y., KOTHARI, S., MOHLE, R., SAUVAGE, L. R., MOORE, M. A., STORB, R. F. & HAMMOND, W. P. 1998. Evidence for circulating bone marrow-derived endothelial cells. Blood, 92, 362-7. SHI, Y., KRAMER, G., SCHRODER, A., KIRKPATRICK, C. J., SEEKAMP, A., SCHMIDT, H. & FUCHS, S. 2014. Early endothelial progenitor cells as a source of myeloid cells to improve the pre-vascularisation of bone constructs. European cells & materials, 27, 64-79; discussion 79-80. SICA, A. & MANTOVANI, A. 2012. Macrophage plasticity and polarization: in vivo veritas. The Journal of clinical investigation, 122, 787-95. SIEGENTHALER, J. A., CHOE, Y., PATTERSON, K. P., HSIEH, I., LI, D., JAMINET, S. C., DANEMAN, R., KUME, T., HUANG, E. J. & PLEASURE, S. J. 2013. Foxc1 is required by pericytes during fetal brain angiogenesis. Biology open, 2, 647-59. SIKDER, H. A., DEVLIN, M. K., DUNLAP, S., RYU, B. & ALANI, R. M. 2003. Id proteins in cell growth and tumorigenesis. Cancer cell, 3, 525-30. SIMON, J., CHIANG, A. & BENDER, W. 1992. Ten different Polycomb group genes are required for spatial control of the abdA and AbdB homeotic products. Development, 114, 493-505. SIQUEIRA, M. F., LI, J., CHEHAB, L., DESTA, T., CHINO, T., KROTHPALI, N., BEHL, Y., ALIKHANI, M., YANG, J., BRAASCH, C. & GRAVES, D. T. 2010. Impaired wound healing in mouse models of diabetes is mediated by TNF-alpha dysregulation and associated with enhanced activation of forkhead box O1 (FOXO1). Diabetologia, 53, 378-88. SIRONI, M., MARTINEZ, F. O., D'AMBROSIO, D., GATTORNO, M., POLENTARUTTI, N., LOCATI, M., GREGORIO, A., IELLEM, A., CASSATELLA, M. A., VAN DAMME, J., SOZZANI, S., MARTINI, A., SINIGAGLIA, F., VECCHI, A. & MANTOVANI, A. 2006. Differential regulation of chemokine production by Fcgamma receptor engagement in human monocytes: association of CCL1 with a distinct form of M2 monocyte activation (M2b, Type 2). Journal of leukocyte biology, 80, 342-9. SIVAN-LOUKIANOVA, E., AWAD, O. A., STEPANOVIC, V., BICKENBACH, J. & SCHATTEMAN, G. C. 2003. CD34+ blood cells accelerate vascularization and healing of diabetic mouse skin wounds. Journal of vascular research, 40, 368-77. SMYTH, G. K. 2004. Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Statistical applications in genetics and molecular biology, 3, Article3. SOLINAS, G., SCHIAREA, S., LIGUORI, M., FABBRI, M., PESCE, S., ZAMMATARO, L., PASQUALINI, F., NEBULONI, M., CHIABRANDO, C., MANTOVANI, A. & ALLAVENA, P. 2010. Tumor-conditioned macrophages secrete migration-stimulating factor: a new marker for M2-polarization, influencing tumor cell motility. Journal of immunology, 185, 642-52. SPANGRUDE, G. J., HEIMFELD, S. & WEISSMAN, I. L. 1988. Purification and characterization of mouse hematopoietic stem cells. Science, 241, 58-62.

219

STOJADINOVIC, O., YIN, N., LEHMANN, J., PASTAR, I., KIRSNER, R. S. & TOMIC-CANIC, M. 2013. Increased number of Langerhans cells in the epidermis of diabetic foot ulcers correlates with healing outcome. Immunologic research, 57, 222-8. SU, C. Y., KUO, Y. P., TSENG, Y. H., SU, C. H. & BURNOUF, T. 2009. In vitro release of growth factors from platelet-rich fibrin (PRF): a proposal to optimize the clinical applications of PRF. Oral surgery, oral medicine, oral pathology, oral radiology, and endodontics, 108, 56-61. SUBIMERB, C., PINLAOR, S., LULITANOND, V., KHUNTIKEO, N., OKADA, S., MCGRATH, M. S. & WONGKHAM, S. 2010. Circulating CD14(+) CD16(+) monocyte levels predict tissue invasive character of cholangiocarcinoma. Clinical and experimental immunology, 161, 471-9. SUNDERKOTTER, C., NIKOLIC, T., DILLON, M. J., VAN ROOIJEN, N., STEHLING, M., DREVETS, D. A. & LEENEN, P. J. 2004. Subpopulations of mouse blood monocytes differ in maturation stage and inflammatory response. Journal of immunology, 172, 4410-7. SWIERS, G., BAUMANN, C., O'ROURKE, J., GIANNOULATOU, E., TAYLOR, S., JOSHI, A., MOIGNARD, V., PINA, C., BEE, T., KOKKALIARIS, K. D., YOSHIMOTO, M., YODER, M. C., FRAMPTON, J., SCHROEDER, T., ENVER, T., GOTTGENS, B. & DE BRUIJN, M. F. 2013. Early dynamic fate changes in haemogenic endothelium characterized at the single-cell level. Nature communications, 4, 2924. TAMARAT, R., SILVESTRE, J. S., LE RICOUSSE-ROUSSANNE, S., BARATEAU, V., LECOMTE- RACLET, L., CLERGUE, M., DURIEZ, M., TOBELEM, G. & LEVY, B. I. 2004. Impairment in ischemia-induced neovascularization in diabetes: bone marrow mononuclear cell dysfunction and therapeutic potential of placenta growth factor treatment. The American journal of pathology, 164, 457-66. TEPPER, O. M., CAPLA, J. M., GALIANO, R. D., CERADINI, D. J., CALLAGHAN, M. J., KLEINMAN, M. E. & GURTNER, G. C. 2005. Adult vasculogenesis occurs through in situ recruitment, proliferation, and tubulization of circulating bone marrow- derived cells. Blood, 105, 1068-77. THOMAS, C. E., EHRHARDT, A. & KAY, M. A. 2003. Progress and problems with the use of viral vectors for gene therapy. Nature reviews. Genetics, 4, 346-58. TIAN, Y., YU, M., LI, Z., HAN, J., YANG, L. & HAN, S. 2015. Optical Tracking of Phagocytosis with an Activatable Profluorophore Metabolically Incorporated into Bacterial Peptidoglycan. Analytical chemistry, 87, 8381-6. TREMPUS, C. S., DANG, H., HUMBLE, M. M., WEI, S. J., GERDES, M. J., MORRIS, R. J., BORTNER, C. D., COTSARELIS, G. & TENNANT, R. W. 2007. Comprehensive microarray transcriptome profiling of CD34-enriched mouse keratinocyte stem cells. The Journal of investigative dermatology, 127, 2904-7. TRINDADE, A., DJOKOVIC, D., GIGANTE, J., BADENES, M., PEDROSA, A. R., FERNANDES, A. C., LOPES-DA-COSTA, L., KRASNOPEROV, V., LIU, R., GILL, P. S. & DUARTE, A. 2012. Low-dosage inhibition of Dll4 signaling promotes wound healing by inducing functional neo-angiogenesis. PloS one, 7, e29863.

220

TSOU, C. L., PETERS, W., SI, Y., SLAYMAKER, S., ASLANIAN, A. M., WEISBERG, S. P., MACK, M. & CHARO, I. F. 2007. Critical roles for CCR2 and MCP-3 in monocyte mobilization from bone marrow and recruitment to inflammatory sites. The Journal of clinical investigation, 117, 902-9. URBICH, C. & DIMMELER, S. 2004. Endothelial progenitor cells: characterization and role in vascular biology. Circulation research, 95, 343-53. VAN DER VEER, W. M., BLOEMEN, M. C., ULRICH, M. M., MOLEMA, G., VAN ZUIJLEN, P. P., MIDDELKOOP, E. & NIESSEN, F. B. 2009. Potential cellular and molecular causes of hypertrophic scar formation. Burns : journal of the International Society for Burn Injuries, 35, 15-29. VELAZQUEZ, O. C., SNYDER, R., LIU, Z. J., FAIRMAN, R. M. & HERLYN, M. 2002. Fibroblast- dependent differentiation of human microvascular endothelial cells into capillary-like 3-dimensional networks. FASEB journal : official publication of the Federation of American Societies for Experimental Biology, 16, 1316-8. VEREMEYKO, T., SIDDIQUI, S., SOTNIKOV, I., YUNG, A. & PONOMAREV, E. D. 2013. IL- 4/IL-13-dependent and independent expression of miR-124 and its contribution to M2 phenotype of monocytic cells in normal conditions and during allergic inflammation. PloS one, 8, e81774. VERMA, S., KULISZEWSKI, M. A., LI, S. H., SZMITKO, P. E., ZUCCO, L., WANG, C. H., BADIWALA, M. V., MICKLE, D. A., WEISEL, R. D., FEDAK, P. W., STEWART, D. J. & KUTRYK, M. J. 2004. C-reactive protein attenuates endothelial progenitor cell survival, differentiation, and function: further evidence of a mechanistic link between C-reactive protein and cardiovascular disease. Circulation, 109, 2058- 67. VILLENEUVE, L. M., REDDY, M. A., LANTING, L. L., WANG, M., MENG, L. & NATARAJAN, R. 2008. Epigenetic histone H3 lysine 9 methylation in metabolic memory and inflammatory phenotype of vascular smooth muscle cells in diabetes. Proceedings of the National Academy of Sciences of the United States of America, 105, 9047-52. WADDINGTON, C. H. 1957. The strategy of the genes; a discussion of some aspects of theoretical biology, London,, Allen & Unwin. WAGNER, E. F. & RISAU, W. 1994. Oncogenes in the study of endothelial cell growth and differentiation. Seminars in cancer biology, 5, 137-45. WEIJERS, E. M., VAN WIJHE, M. H., JOOSTEN, L., HORREVOETS, A. J., DE MAAT, M. P., VAN HINSBERGH, V. W. & KOOLWIJK, P. 2010. Molecular weight fibrinogen variants alter gene expression and functional characteristics of human endothelial cells. Journal of thrombosis and haemostasis : JTH, 8, 2800-9. WEISSER, S. B., MCLARREN, K. W., VOGLMAIER, N., VAN NETTEN-THOMAS, C. J., ANTOV, A., FLAVELL, R. A. & SLY, L. M. 2011. Alternative activation of macrophages by IL- 4 requires SHIP degradation. European journal of immunology, 41, 1742-53. WERNER, N., KOSIOL, S., SCHIEGL, T., AHLERS, P., WALENTA, K., LINK, A., BOHM, M. & NICKENIG, G. 2005. Circulating endothelial progenitor cells and cardiovascular outcomes. The New England journal of medicine, 353, 999-1007.

221

WERNER, S. & GROSE, R. 2003. Regulation of wound healing by growth factors and cytokines. Physiological reviews, 83, 835-70. WETZLER, C., KAMPFER, H., STALLMEYER, B., PFEILSCHIFTER, J. & FRANK, S. 2000. Large and sustained induction of chemokines during impaired wound healing in the genetically diabetic mouse: prolonged persistence of neutrophils and macrophages during the late phase of repair. The Journal of investigative dermatology, 115, 245-53. WICKS, K., TORBICA, T. & MACE, K. A. 2014. Myeloid cell dysfunction and the pathogenesis of the diabetic chronic wound. Seminars in immunology, 26, 341- 53. WICKS, K., TORBICA, T., UMEHARA, T., AMIN, S., BOBOLA, N. & MACE, K. A. 2015. Diabetes inhibits Gr-1+ myeloid cell maturation via Cebpa deregulation. Diabetes. WILLENBORG, S., LUCAS, T., VAN LOO, G., KNIPPER, J. A., KRIEG, T., HAASE, I., BRACHVOGEL, B., HAMMERSCHMIDT, M., NAGY, A., FERRARA, N., PASPARAKIS, M. & EMING, S. A. 2012. CCR2 recruits an inflammatory macrophage subpopulation critical for angiogenesis in tissue repair. Blood, 120, 613-25. WILTSCHKE, C., NEMET, H., HOLZINGER, C., GESSL, A., PERNERSTORFER, T., FORSTER, O. & BOLTZ-NITULESCU, G. 1989. Murine recombinant GM-CSF-driven rat bone marrow cell differentiation and factors suppressing cell proliferation. Immunobiology, 179, 145-58. WU, C., XUE, Y., WANG, P., LIN, L., LIU, Q., LI, N., XU, J. & CAO, X. 2014. IFN-gamma primes macrophage activation by increasing phosphatase and tensin homolog via downregulation of miR-3473b. Journal of immunology, 193, 3036-44. XU, M., QIN, J., TSAI, S. Y. & TSAI, M. J. 2015. The role of the orphan nuclear receptor COUP-TFII in tumorigenesis. Acta pharmacologica Sinica, 36, 32-6. YAMAMOTO, M. & TAKEDA, K. 2010. Current views of toll-like receptor signaling pathways. Gastroenterology research and practice, 2010, 240365. YEH, H. J., HE, Y. Y., XU, J., HSU, C. Y. & DEUEL, T. F. 1998. Upregulation of pleiotrophin gene expression in developing microvasculature, macrophages, and astrocytes after acute ischemic brain injury. The Journal of neuroscience : the official journal of the Society for Neuroscience, 18, 3699-707. YEH, H. S., CHEN, H., MANYAK, S. J., SWIFT, R. A., CAMPBELL, R. A., WANG, C., LI, M., LEE, H. J., WATERMAN, G., GORDON, M. S., MA, J., BONAVIDA, B. & BERENSON, J. R. 2006. Serum pleiotrophin levels are elevated in multiple myeloma patients and correlate with disease status. British journal of haematology, 133, 526-9. YONA, S., KIM, K. W., WOLF, Y., MILDNER, A., VAROL, D., BREKER, M., STRAUSS-AYALI, D., VIUKOV, S., GUILLIAMS, M., MISHARIN, A., HUME, D. A., PERLMAN, H., MALISSEN, B., ZELZER, E. & JUNG, S. 2013. Fate mapping reveals origins and dynamics of monocytes and tissue macrophages under homeostasis. Immunity, 38, 79-91.

222

YOU, L. R., LIN, F. J., LEE, C. T., DEMAYO, F. J., TSAI, M. J. & TSAI, S. Y. 2005. Suppression of Notch signalling by the COUP-TFII transcription factor regulates vein identity. Nature, 435, 98-104. YOUNG, N., HAHN, C. N., POH, A., DONG, C., WILHELM, D., OLSSON, J., MUSCAT, G. E., PARSONS, P., GAMBLE, J. R. & KOOPMAN, P. 2006. Effect of disrupted SOX18 transcription factor function on tumor growth, vascularization, and endothelial development. Journal of the National Cancer Institute, 98, 1060-7. ZHANG, N., ZHONG, R., PEREZ-PINERA, P., HERRADON, G., EZQUERRA, L., WANG, Z. Y. & DEUEL, T. F. 2006. Identification of the angiogenesis signaling domain in pleiotrophin defines a mechanism of the angiogenic switch. Biochemical and biophysical research communications, 343, 653-8. ZHAO, Q., BECK, A. J., VITALE, J. M., SCHNEIDER, J. S., GAO, S., CHANG, C., ELSON, G., LEIBOVICH, S. J., PARK, J. Y., TIAN, B., NAM, H. S. & FRAIDENRAICH, D. 2011. Developmental ablation of Id1 and Id3 genes in the vasculature leads to postnatal cardiac phenotypes. Developmental biology, 349, 53-64. ZHONG, T. P., CHILDS, S., LEU, J. P. & FISHMAN, M. C. 2001. Gridlock signalling pathway fashions the first embryonic artery. Nature, 414, 216-20. ZHOU, Z., AKINBIYI, T., XU, L., RAMCHARAN, M., LEONG, D. J., ROS, S. J., COLVIN, A. C., SCHAFFLER, M. B., MAJESKA, R. J., FLATOW, E. L. & SUN, H. B. 2010. Tendon- derived stem/progenitor cell aging: defective self-renewal and altered fate. Aging cell, 9, 911-5. ZHU, F., YUE, W. & WANG, Y. 2014. The nuclear factor kappa B (NF-kappaB) activation is required for phagocytosis of staphylococcus aureus by RAW 264.7 cells. Experimental cell research, 327, 256-63.

223

8 Appendices

8.1 Vectors

8.1.1 pCRII-TOPO pleiotrophin

M13 Reverse Primer Pleiotrophin Start site M13 (-20) Forward Primer AGCGCCCAATACGCAAACCGCCTCTCCCCGCGCGTTGGCCGATTCATTAATGCAGCTGGCACG ACAGGTTTCCCGACTGGAAAGCGGGCAGTGAGCGCAACGCAATTAATGTGAGTTAGCTCACT CATTAGGCACCCCAGGCTTTACACTTTATGCTTCCGGCTCGTATGTTGTGTGGAATTGTGAGCG GATAACAATTTCACACAGGAAACAGCTATGACCATGATTACGCCAAGCTATTTAGGTGACACT ATAGAATACTCAAGCTATGCATCAAGCTTGGTACCGAGCTCGGATCCACTAGTAACGGCCGCC AGTGTGCTGGAATTCGCCCTTAAAGGCAGCCAGCTAGTCAGCGAGGACCTCTGCAAGCCAAA AAATGTCGTCCCAGCAATATCAGCAGCAACGTAGAAAATTTGCAGCTGCCTTCCTGGCATTGA TTTTCATCTTGGCAGCTGTGGACACTGCTGAGGCCGGGAAGAAAGAGAAACCTGAAAAAAAG GTGAAAAAGTCTGACTGTGGAGAATGGCAGTGGAGTGTGTGCGTGCCTACCAGCGGGGACT GTGGATTGGGCACCCGGGAGGGCACTCGCACTGGCGCCGAGTGCAAACAGACCATGAAGAC TCAGAGATGTAAGATCCCTTGCAACTGGAAGAAGCAGTTTGGAGCTGAGTGCAAGTACCAGT TCCAGGCTTGGGGAGAATGTGACCTCAATACCGCCTTGAAGACCAGAACTGGCAGCCTGAAG CGAGCTCTGCACAATGCTGACTGTCAGAAAACTGTCACCATCTCCAAGCCCTGTGGCAAGCTC ACCAAGCCCAAGCCTCAAGCGGAGTCAAAGAAGAAGAAAAAGGAAGGCAAGAAACAGGAG AAGATGCTGGATAAGGGCGAATTCTGCAGATATCCATCACACTGGCGGCCGCTCGAGCATGC ATCTAGAGGGCCCAATTCGCCCTATAGTGAGTCGTATTACAATTCACTGGCCGTCGTTTTACAA CGTCGTGACTGGGAAAACCCTGGCGTTACCCAACTTAATCGCCTTGCAGCACATCCCCCTTTCG CCAGCTGGCGTAATAGCGAAGAGGCCCGCACCGATCGCCCTTCCCAACAGTTGCGCAGCCTG AATGGCGAATGGACGCGCCCTGTAGCGGCGCATTAAGCGCGGCGGGTGTGGTGGTTACGCG CAGCGTGACCGCTACACTTGCCAGCGCCCTAGCGCCCGCTCCTTTCGCTTTCTTCCCTTCCTTTC TCGCCACGTTCGCCGGCTTTCCCCGTCAAGCTCTAAATCGGGGGCTCCCTTTAGGGTTCCGATT TAGTGCTTTACGGCACCTCGACCCCAAAAAACTTGATTAGGGTGATGGTTCACGTAGTGGGCC ATCGCCCTGATAGACGGTTTTTCGCCCTTTGACGTTGGAGTCCACGTTCTTTAATAGTGGACTC TTGTTCCAAACTGGAACAACACTCAACCCTATCTCGGTCTATTCTTTTGATTTATAAGGGATTTT GCCGATTTCGGCCTATTGGTTAAAAAATGAGCTGATTTAACAAAAATTTAACGCGAATTTTAAC AAAATTCAGGGCGCAAGGGCTGCTAAAGGAAGCGGAACACGTAGAAAGCCAGTCCGCAGAA ACGGTGCTGACCCCGGATGAATGTCAGCTACTGGGCTATCTGGACAAGGGAAAACGCAAGCG CAAAGAGAAAGCAGGTAGCTTGCAGTGGGCTTACATGGCGATAGCTAGACTGGGCGGTTTTA TGGACAGCAAGCGAACCGGAATTGCCAGCTGGGGCGCCCTCTGGTAAGGTTGGGAAGCCCT GCAAAGTAAACTGGATGGCTTTCTTGCCGCCAAGGATCTGATGGCGCAGGGGATCAAGATCT GATCAAGAGACAGGATGAGGATCGTTTCGCATGATTGAACAAGATGGATTGCACGCAGGTTC

224

TCCGGCCGCTTGGGTGGAGAGGCTATTCGGCTATGACTGGGCACAACAGACAATCGGCTGCT CTGATGCCGCCGTGTTCCGGCTGTCAGCGCAGGGGCGCCCGGTTCTTTTTGTCAAGACCGACC TGTCCGGTGCCCTGAATGAACTGCAGGACGAGGCAGCGCGGCTATCGTGGCTGGCCACGACG GGCGTTCCTTGCGCAGCTGTGCTCGACGTTGTCACTGAAGCGGGAAGGGACTGGCTGCTATT GGGCGAAGTGCCGGGGCAGGATCTCCTGTCATCCCACCTTGCTCCTGCCGAGAAAGTATCCAT CATGGCTGATGCAATGCGGCGGCTGCATACGCTTGATCCGGCTACCTGCCCATTCGACCACCA AGCGAAACATCGCATCGAGCGAGCACGTACTCGGATGGAAGCCGGTCTTGTCGATCAGGATG ATCTGGACGAAGAGCATCAGGGGCTCGCGCCAGCCGAACTGTTCGCCAGGCTCAAGGCGCGC ATGCCCGACGGCGAGGATCTCGTCGTGACCCATGGCGATGCCTGCTTGCCGAATATCATGGTG GAAAATGGCCGCTTTTCTGGATTCATCGACTGTGGCCGGCTGGGTGTGGCGGACCGCTATCA GGACATAGCGTTGGCTACCCGTGATATTGCTGAAGAGCTTGGCGGCGAATGGGCTGACCGCT TCCTCGTGCTTTACGGTATCGCCGCTCCCGATTCGCAGCGCATCGCCTTCTATCGCCTTCTTGAC GAGTTCTTCTGAATTGAAAAAGGAAGAGTATGAGTATTCAACATTTCCGTGTCGCCCTTATTCC CTTTTTTGCGGCATTTTGCCTTCCTGTTTTTGCTCACCCAGAAACGCTGGTGAAAGTAAAAGAT GCTGAAGATCAGTTGGGTGCACGAGTGGGTTACATCGAACTGGATCTCAACAGCGGTAAGAT CCTTGAGAGTTTTCGCCCCGAAGAACGTTTTCCAATGATGAGCACTTTTAAAGTTCTGCTATGT GGCGCGGTATTATCCCGTATTGACGCCGGGCAAGAGCAACTCGGTCGCCGCATACACTATTCT CAGAATGACTTGGTTGAGTACTCACCAGTCACAGAAAAGCATCTTACGGATGGCATGACAGTA AGAGAATTATGCAGTGCTGCCATAACCATGAGTGATAACACTGCGGCCAACTTACTTCTGACA ACGATCGGAGGACCGAAGGAGCTAACCGCTTTTTTGCACAACATGGGGGATCATGTAACTCG CCTTGATCGTTGGGAACCGGAGCTGAATGAAGCCATACCAAACGACGAGCGTGACACCACGA TGCCTGTAGCAATGGCAACAACGTTGCGCAAACTATTAACTGGCGAACTACTTACTCTAGCTTC CCGGCAACAATTAATAGACTGGATGGAGGCGGATAAAGTTGCAGGACCACTTCTGCGCTCGG CCCTTCCGGCTGGCTGGTTTATTGCTGATAAATCTGGAGCCGGTGAGCGTGGGTCTCGCGGTA TCATTGCAGCACTGGGGCCAGATGGTAAGCCCTCCCGTATCGTAGTTATCTACACGACGGGGA GTCAGGCAACTATGGATGAACGAAATAGACAGATCGCTGAGATAGGTGCCTCACTGATTAAG CATTGGTAACTGTCAGACCAAGTTTACTCATATATACTTTAGATTGATTTAAAACTTCATTTTTA ATTTAAAAGGATCTAGGTGAAGATCCTTTTTGATAATCTCATGACCAAAATCCCTTAACGTGAG TTTTCGTTCCACTGAGCGTCAGACCCCGTAGAAAAGATCAAAGGATCTTCTTGAGATCCTTTTT TTCTGCGCGTAATCTGCTGCTTGCAAACAAAAAAACCACCGCTACCAGCGGTGGTTTGTTTGCC GGATCAAGAGCTACCAACTCTTTTTCCGAAGGTAACTGGCTTCAGCAGAGCGCAGATACCAAA TACTGTTCTTCTAGTGTAGCCGTAGTTAGGCCACCACTTCAAGAACTCTGTAGCACCGCCTACA TACCTCGCTCTGCTAATCCTGTTACCAGTGGCTGCTGCCAGTGGCGATAAGTCGTGTCTTACCG GGTTGGACTCAAGACGATAGTTACCGGATAAGGCGCAGCGGTCGGGCTGAACGGGGGGTTC GTGCACACAGCCCAGCTTGGAGCGAACGACCTACACCGAACTGAGATACCTACAGCGTGAGC TATGAGAAAGCGCCACGCTTCCCGAAGGGAGAAAGGCGGACAGGTATCCGGTAAGCGGCAG GGTCGGAACAGGAGAGCGCACGAGGGAGCTTCCAGGGGGAAACGCCTGGTATCTTTATAGT CCTGTCGGGTTTCGCCACCTCTGACTTGAGCGTCGATTTTTGTGATGCTCGTCAGGGGGGCGG AGCCTATGGAAAAACGCCAGCAACGCGGCCTTTTTACGGTTCCTGGCCTTTTGCTGGCCTTTTG CTCACATGTTCTTTCCTGCGTTATCCCCTGATTCTGTGGATAACCGTATTACCGCCTTTGAGTGA GCTGATACCGCTCGCCGCAGCCGAACGACCGAGCGCAGCGAGTCAGTGAGCGAGGAAGCGG AAG

225

8.1.2 pcDNA3.1/myc-His pleiotrophin pcDNA3.1 m/h A+ mcs new EcoRI cut T7 promoter/priming site reverse pcRII mcs PtnF2 Myc epitope His tag BGH Reverse priming site

GACGGATCGGGAGATCTCCCGATCCCCTATGGTGCACTCTCAGTACAATCTGCTCTGATGCCG CATAGTTAAGCCAGTATCTGCTCCCTGCTTGTGTGTTGGAGGTCGCTGAGTAGTGCGCGAGCA AAATTTAAGCTACAACAAGGCAAGGCTTGACCGACAATTGCATGAAGAATCTGCTTAGGGTTA GGCGTTTTGCGCTGCTTCGCGATGTACGGGCCAGATATACGCGTTGACATTGATTATTGACTA GTTATTAATAGTAATCAATTACGGGGTCATTAGTTCATAGCCCATATATGGAGTTCCGCGTTAC ATAACTTACGGTAAATGGCCCGCCTGGCTGACCGCCCAACGACCCCCGCCCATTGACGTCAAT AATGACGTATGTTCCCATAGTAACGCCAATAGGGACTTTCCATTGACGTCAATGGGTGGAGTA TTTACGGTAAACTGCCCACTTGGCAGTACATCAAGTGTATCATATGCCAAGTACGCCCCCTATT GACGTCAATGACGGTAAATGGCCCGCCTGGCATTATGCCCAGTACATGACCTTATGGGACTTT CCTACTTGGCAGTACATCTACGTATTAGTCATCGCTATTACCATGGTGATGCGGTTTTGGCAGT ACATCAATGGGCGTGGATAGCGGTTTGACTCACGGGGATTTCCAAGTCTCCACCCCATTGACG TCAATGGGAGTTTGTTTTGGCACCAAAATCAACGGGACTTTCCAAAATGTCGTAACAACTCCG CCCCATTGACGCAAATGGGCGGTAGGCGTGTACGGTGGGAGGTCTATATAAGCAGAGCTCTC TGGCTAACTAGAGAACCCACTGCTTACTGGCTTATCGAAATTAATACGACTCACTATAGGGAG ACCCAAGCTGGCTAGTTAAGCTTGGTACCGAGCTCGGATCCACTAGTCCAGTGTGGTGGAATT CGCCCTTAAAGGCAGCCAGCTAGTCAGCGAGGACCTCTGCAAGCCAAAAAATGTCGTCCCAG CAATATCAGCAGCAACGTAGAAAATTTGCAGCTGCCTTCCTGGCATTGATTTTCATCTTGGCAG CTGTGGACACTGCTGAGGCCGGGAAGAAAGAGAAACCTGAAAAAAAGGTGAAAAAGTCTGA CTGTGGAGAATGGCAGTGGAGTGTGTGCGTGCCTACCAGCGGGGACTGTGGATTGGGCACC CGGGAGGGCACTCGCACTGGCGCCGAGTGCAAACAGACCATGAAGACTCAGAGATGTAAGA TCCCTTGCAACTGGAAGAAGCAGTTTGGAGCTGAGTGCAAGTACCAGTTCCAGGCTTGGGGA GAATGTGACCTCAATACCGCCTTGAAGACCAGAACTGGCAGCCTGAAGCGAGCTCTGCACAAT GCTGACTGTCAGAAAACTGTCACCATCTCCAAGCCCTGTGGCAAGCTCACCAAGCCCAAGCCT CAAGCGGAGTCAAAGAAGAAGAAAAAGGAAGGCAAGAAACAGGAGAAGATGCTGGATAAG GGCGAATTCTGCAGATATCCAGCACAGTGGCGGCCGCTCGAGTCTAGAGGGCCCTTCGAACA AAAACTCATCTCAGAAGAGGATCTGAATATGCATACCGGTCATCATCACCATCACCATTGAGTT TAAACCCGCTGATCAGCCTCGACTGTGCCTTCTAGTTGCCAGCCATCTGTTGTTTGCCCCTCCCC CGTGCCTTCCTTGACCCTGGAAGGTGCCACTCCCACTGTCCTTTCCTAATAAAATGAGGAAATT GCATCGCATTGTCTGAGTAGGTGTCATTCTATTCTGGGGGGTGGGGTGGGGCAGGACAGCAA GGGGGAGGATTGGGAAGACAATAGCAGGCATGCTGGGGATGCGGTGGGCTCTATGGCTTCT GAGGCGGAAAGAACCAGCTGGGGCTCTAGGGGGTATCCCCACGCGCCCTGTAGCGGCGCAT TAAGCGCGGCGGGTGTGGTGGTTACGCGCAGCGTGACCGCTACACTTGCCAGCGCCCTAGCG CCCGCTCCTTTCGCTTTCTTCCCTTCCTTTCTCGCCACGTTCGCCGGCTTTCCCCGTCAAGCTCTA

226

AATCGGGGGCTCCCTTTAGGGTTCCGATTTAGTGCTTTACGGCACCTCGACCCCAAAAAACTT GATTAGGGTGATGGTTCACGTAGTGGGCCATCGCCCTGATAGACGGTTTTTCGCCCTTTGACG TTGGAGTCCACGTTCTTTAATAGTGGACTCTTGTTCCAAACTGGAACAACACTCAACCCTATCT CGGTCTATTCTTTTGATTTATAAGGGATTTTGCCGATTTCGGCCTATTGGTTAAAAAATGAGCT GATTTAACAAAAATTTAACGCGAATTAATTCTGTGGAATGTGTGTCAGTTAGGGTGTGGAAAG TCCCCAGGCTCCCCAGCAGGCAGAAGTATGCAAAGCATGCATCTCAATTAGTCAGCAACCAGG TGTGGAAAGTCCCCAGGCTCCCCAGCAGGCAGAAGTATGCAAAGCATGCATCTCAATTAGTCA GCAACCATAGTCCCGCCCCTAACTCCGCCCATCCCGCCCCTAACTCCGCCCAGTTCCGCCCATT CTCCGCCCCATGGCTGACTAATTTTTTTTATTTATGCAGAGGCCGAGGCCGCCTCTGCCTCTGA GCTATTCCAGAAGTAGTGAGGAGGCTTTTTTGGAGGCCTAGGCTTTTGCAAAAAGCTCCCGGG AGCTTGTATATCCATTTTCGGATCTGATCAAGAGACAGGATGAGGATCGTTTCGCATGATTGA ACAAGATGGATTGCACGCAGGTTCTCCGGCCGCTTGGGTGGAGAGGCTATTCGGCTATGACT GGGCACAACAGACAATCGGCTGCTCTGATGCCGCCGTGTTCCGGCTGTCAGCGCAGGGGCGC CCGGTTCTTTTTGTCAAGACCGACCTGTCCGGTGCCCTGAATGAACTGCAGGACGAGGCAGCG CGGCTATCGTGGCTGGCCACGACGGGCGTTCCTTGCGCAGCTGTGCTCGACGTTGTCACTGAA GCGGGAAGGGACTGGCTGCTATTGGGCGAAGTGCCGGGGCAGGATCTCCTGTCATCTCACCT TGCTCCTGCCGAGAAAGTATCCATCATGGCTGATGCAATGCGGCGGCTGCATACGCTTGATCC GGCTACCTGCCCATTCGACCACCAAGCGAAACATCGCATCGAGCGAGCACGTACTCGGATGG AAGCCGGTCTTGTCGATCAGGATGATCTGGACGAAGAGCATCAGGGGCTCGCGCCAGCCGAA CTGTTCGCCAGGCTCAAGGCGCGCATGCCCGACGGCGAGGATCTCGTCGTGACCCATGGCGA TGCCTGCTTGCCGAATATCATGGTGGAAAATGGCCGCTTTTCTGGATTCATCGACTGTGGCCG GCTGGGTGTGGCGGACCGCTATCAGGACATAGCGTTGGCTACCCGTGATATTGCTGAAGAGC TTGGCGGCGAATGGGCTGACCGCTTCCTCGTGCTTTACGGTATCGCCGCTCCCGATTCGCAGC GCATCGCCTTCTATCGCCTTCTTGACGAGTTCTTCTGAGCGGGACTCTGGGGTTCGCGAAATG ACCGACCAAGCGACGCCCAACCTGCCATCACGAGATTTCGATTCCACCGCCGCCTTCTATGAA AGGTTGGGCTTCGGAATCGTTTTCCGGGACGCCGGCTGGATGATCCTCCAGCGCGGGGATCT CATGCTGGAGTTCTTCGCCCACCCCAACTTGTTTATTGCAGCTTATAATGGTTACAAATAAAGC AATAGCATCACAAATTTCACAAATAAAGCATTTTTTTCACTGCATTCTAGTTGTGGTTTGTCCAA ACTCATCAATGTATCTTATCATGTCTGTATACCGTCGACCTCTAGCTAGAGCTTGGCGTAATCA TGGTCATAGCTGTTTCCTGTGTGAAATTGTTATCCGCTCACAATTCCACACAACATACGAGCCG GAAGCATAAAGTGTAAAGCCTGGGGTGCCTAATGAGTGAGCTAACTCACATTAATTGCGTTGC GCTCACTGCCCGCTTTCCAGTCGGGAAACCTGTCGTGCCAGCTGCATTAATGAATCGGCCAAC GCGCGGGGAGAGGCGGTTTGCGTATTGGGCGCTCTTCCGCTTCCTCGCTCACTGACTCGCTGC GCTCGGTCGTTCGGCTGCGGCGAGCGGTATCAGCTCACTCAAAGGCGGTAATACGGTTATCC ACAGAATCAGGGGATAACGCAGGAAAGAACATGTGAGCAAAAGGCCAGCAAAAGGCCAGGA ACCGTAAAAAGGCCGCGTTGCTGGCGTTTTTCCATAGGCTCCGCCCCCCTGACGAGCATCACA AAAATCGACGCTCAAGTCAGAGGTGGCGAAACCCGACAGGACTATAAAGATACCAGGCGTTT CCCCCTGGAAGCTCCCTCGTGCGCTCTCCTGTTCCGACCCTGCCGCTTACCGGATACCTGTCCG CCTTTCTCCCTTCGGGAAGCGTGGCGCTTTCTCATAGCTCACGCTGTAGGTATCTCAGTTCGGT GTAGGTCGTTCGCTCCAAGCTGGGCTGTGTGCACGAACCCCCCGTTCAGCCCGACCGCTGCGC CTTATCCGGTAACTATCGTCTTGAGTCCAACCCGGTAAGACACGACTTATCGCCACTGGCAGCA GCCACTGGTAACAGGATTAGCAGAGCGAGGTATGTAGGCGGTGCTACAGAGTTCTTGAAGTG GTGGCCTAACTACGGCTACACTAGAAGAACAGTATTTGGTATCTGCGCTCTGCTGAAGCCAGT TACCTTCGGAAAAAGAGTTGGTAGCTCTTGATCCGGCAAACAAACCACCGCTGGTAGCGGTG

227

GTTTTTTTGTTTGCAAGCAGCAGATTACGCGCAGAAAAAAAGGATCTCAAGAAGATCCTTTGA TCTTTTCTACGGGGTCTGACGCTCAGTGGAACGAAAACTCACGTTAAGGGATTTTGGTCATGA GATTATCAAAAAGGATCTTCACCTAGATCCTTTTAAATTAAAAATGAAGTTTTAAATCAATCTA AAGTATATATGAGTAAACTTGGTCTGACAGTTACCAATGCTTAATCAGTGAGGCACCTATCTCA GCGATCTGTCTATTTCGTTCATCCATAGTTGCCTGACTCCCCGTCGTGTAGATAACTACGATAC GGGAGGGCTTACCATCTGGCCCCAGTGCTGCAATGATACCGCGAGACCCACGCTCACCGGCT CCAGATTTATCAGCAATAAACCAGCCAGCCGGAAGGGCCGAGCGCAGAAGTGGTCCTGCAAC TTTATCCGCCTCCATCCAGTCTATTAATTGTTGCCGGGAAGCTAGAGTAAGTAGTTCGCCAGTT AATAGTTTGCGCAACGTTGTTGCCATTGCTACAGGCATCGTGGTGTCACGCTCGTCGTTTGGTA TGGCTTCATTCAGCTCCGGTTCCCAACGATCAAGGCGAGTTACATGATCCCCCATGTTGTGCAA AAAAGCGGTTAGCTCCTTCGGTCCTCCGATCGTTGTCAGAAGTAAGTTGGCCGCAGTGTTATC ACTCATGGTTATGGCAGCACTGCATAATTCTCTTACTGTCATGCCATCCGTAAGATGCTTTTCTG TGACTGGTGAGTACTCAACCAAGTCATTCTGAGAATAGTGTATGCGGCGACCGAGTTGCTCTT GCCCGGCGTCAATACGGGATAATACCGCGCCACATAGCAGAACTTTAAAAGTGCTCATCATTG GAAAACGTTCTTCGGGGCGAAAACTCTCAAGGATCTTACCGCTGTTGAGATCCAGTTCGATGT AACCCACTCGTGCACCCAACTGATCTTCAGCATCTTTTACTTTCACCAGCGTTTCTGGGTGAGC AAAAACAGGAAGGCAAAATGCCGCAAAAAAGGGAATAAGGGCGACACGGAAATGTTGAATA CTCATACTCTTCCTTTTTCAATATTATTGAAGCATTTATCAGGGTTATTGTCTCATGAGCGGATA CATATTTGAATGTATTTAGAAAAATAAACAAATAGGGGTTCCGCGCACATTTCCCCGAAAAGT GCCACCTGACGTC 8.1.3 pSecTag2 mCherry

Yellow = CMV prom, and then SP peptide from Ig kappa leader sequence Blue = BamHI site used for cloning Pink = MCR from TOPO TA cloning vector pCRII Red = mCherry ORF Turquoise = XhoI site for cloning

228

GACGGATCGGGAGATCTCCCGATCCCCTATGGTCGACTCTCAGTACAATCTGCTCTGATGCCG CATAGTTAAGCCAGTATCTGCTCCCTGCTTGTGTGTTGGAGGTCGCTGAGTAGTGCGCGAGCA AAATTTAAGCTACAACAAGGCAAGGCTTGACCGACAATTGCATGAAGAATCTGCTTAGGGTTA GGCGTTTTGCGCTGCTTCGCGATGTACGGGCCAGATATACGCGTTGACATTGATTATTGACTA GTTATTAATAGTAATCAATTACGGGGTCATTAGTTCATAGCCCATATATGGAGTTCCGCGTTAC ATAACTTACGGTAAATGGCCCGCCTGGCTGACCGCCCAACGACCCCCGCCCATTGACGTCAAT AATGACGTATGTTCCCATAGTAACGCCAATAGGGACTTTCCATTGACGTCAATGGGTGGACTA TTTACGGTAAACTGCCCACTTGGCAGTACATCAAGTGTATCATATGCCAAGTACGCCCCCTATT GACGTCAATGACGGTAAATGGCCCGCCTGGCATTATGCCCAGTACATGACCTTATGGGACTTT CCTACTTGGCAGTACATCTACGTATTAGTCATCGCTATTACCATGGTGATGCGGTTTTGGCAGT ACATCAATGGGCGTGGATAGCGGTTTGACTCACGGGGATTTCCAAGTCTCCACCCCATTGACG TCAATGGGAGTTTGTTTTGGCACCAAAATCAACGGGACTTTCCAAAATGTCGTAACAACTCCG CCCCATTGACGCAAATGGGCGGTAGGCGTGTACGGTGGGAGGTCTATATAAGCAGAGCTCTC TGGCTAACTAGAGAACCCACTGCTTACTGGCTTATCGAAATTAATACGACTCACTATAGGGAG ACCCAAGCTGGCTAGCCACCATGGAGACAGACACACTCCTGCTATGGGTACTGCTGCTCTGGG TTCCAGGTTCCACTGGTGACGCGGCCCAGCCGGCCAGGCGCGCCGTACGAAGCTTGGTACCG AGCTCGGATCCACTAGTAACGGCCGCCAGTGTGCTGGAATTCGCCCTTGTCGCCACCATGGTG AGCAAGGGCGAGGAGGATAACATGGCCATCATCAAGGAGTTCATGCGCTTCAAGGTGCACAT GGAGGGCTCCGTGAACGGCCACGAGTTCGAGATCGAGGGCGAGGGCGAGGGCCGCCCCTAC GAGGGCACCCAGACCGCCAAGCTGAAGGTGACCAAGGGTGGCCCCCTGCCCTTCGCCTGGGA CATCCTGTCCCCTCAGTTCATGTACGGCTCCAAGGCCTACGTGAAGCACCCCGCCGACATCCCC GACTACTTGAAGCTGTCCTTCCCCGAGGGCTTCAAGTGGGAGCGCGTGATGAACTTCGAGGA CGGCGGCGTGGTGACCGTGACCCAGGACTCCTCCCTGCAGGACGGCGAGTTCATCTACAAGG TGAAGCTGCGCGGCACCAACTTCCCCTCCGACGGCCCCGTAATGCAGAAGAAGACCATGGGC TGGGAGGCCTCCTCCGAGCGGATGTACCCCGAGGACGGCGCCCTGAAGGGCGAGATCAAGC AGAGGCTGAAGCTGAAGGACGGCGGCCACTACGACGCTGAGGTCAAGACCACCTACAAGGC CAAGAAGCCCGTGCAGCTGCCCGGCGCCTACAACGTCAACATCAAGTTGGACATCACCTCCCA CAACGAGGACTACACCATCGTGGAACAGTACGAACGCGCCGAGGGCCGCCACTCCACCGGCG GCATGGACGAGCTGTACAAGTAAAAGGGCGAATTCTGCAGATATCCATCACACTGGCGGCCG CTCGAGGAGGGCCCGAACAAAAACTCATCTCAGAAGAGGATCTGAATAGCGCCGTCGACCAT CATCATCATCATCATTGAGTTTAAACCCGCTGATCAGCCTCGACTGTGCCTTCTAGTTGCCAGC CATCTGTTGTTTGCCCCTCCCCCGTGCCTTCCTTGACCCTGGAAGGTGCCACTCCCACTGTCCTT TCCTAATAAAATGAGGAAATTGCATCGCATTGTCTGAGTAGGTGTCATTCTATTCTGGGGGGT GGGGTGGGGCAGGACAGCAAGGGGGAGGATTGGGAAGACAATAGCAGGCATGCTGGGGAT GCGGTGGGCTCTATGGCTTCTGAGGCGGAAAGAACCAGCTGGGGCTCTAGGGGGTATCCCCA CGCGCCCTGTAGCGGCGCATTAAGCGCGGCGGGTGTGGTGGTTACGCGCAGCGTGACCGCTA CACTTGCCAGCGCCCTAGCGCCCGCTCCTTTCGCTTTCTTCCCTTCCTTTCTCGCCACGTTCGCC GGCTTTCCCCGTCAAGCTCTAAATCGGGGCATCCCTTTAGGGTTCCGATTTAGTGCTTTACGGC ACCTCGACCCCAAAAAACTTGATTAGGGTGATGGTTCACGTAGTGGGCCATCGCCCTGATAGA CGGTTTTTCGCCCTTTGACGTTGGAGTCCACGTTCTTTAATAGTGGACTCTTGTTCCAAACTGG AACAACACTCAACCCTATCTCGGTCTATTCTTTTGATTTATAAGGGATTTTGGGGATTTCGGCCT ATTGGTTAAAAAATGAGCTGATTTAACAAAAATTTAACGCGAATTAATTCTGTGGAATGTGTG TCAGTTAGGGTGTGGAAAGTCCCCAGGCTCCCCAGCAGGCAGAAGTATGCAAAGCATGCATC TCAATTAGTCAGCAACCAGGTGTGGAAAGTCCCCAGGCTCCCCAGCAGGCAGAAGTATGCAA

229

AGCATGCATCTCAATTAGTCAGCAACCATAGTCCCGCCCCTAACTCCGCCCATCCCGCCCCTAA CTCCGCCCAGTTCCGCCCATTCTCCGCCCCATGGCTGACTAATTTTTTTTATTTATGCAGAGGCC GAGGCCGCCTCTGCCTCTGAGCTATTCCAGAAGTAGTGAGGAGGCTTTTTTGGAGGCCTAGGC TTTTGCAAAAAGCTCCCGGGAGCTTGTATATCCATTTTCGGATCTGATCAGCACGTGTTGACAA TTAATCATCGGCATAGTATATCGGCATAGTATAATACGACAAGGTGAGGAACTAAACCATGGC CAAGTTGACCAGTGCCGTTCCGGTGCTCACCGCGCGCGACGTCGCCGGAGCGGTCGAGTTCT GGACCGACCGGCTCGGGTTCTCCCGGGACTTCGTGGAGGACGACTTCGCCGGTGTGGTCCGG GACGACGTGACCCTGTTCATCAGCGCGGTCCAGGACCAGGTGGTGCCGGACAACACCCTGGC CTGGGTGTGGGTGCGCGGCCTGGACGAGCTGTACGCCGAGTGGTCGGAGGTCGTGTCCACG AACTTCCGGGACGCCTCCGGGCCGGCCATGACCGAGATCGGCGAGCAGCCGTGGGGGCGGG AGTTCGCCCTGCGCGACCCGGCCGGCAACTGCGTGCACTTCGTGGCCGAGGAGCAGGACTGA CACGTGCTACGAGATTTCGATTCCACCGCCGCCTTCTATGAAAGGTTGGGCTTCGGAATCGTTT TCCGGGACGCCGGCTGGATGATCCTCCAGCGCGGGGATCTCATGCTGGAGTTCTTCGCCCACC CCAACTTGTTTATTGCAGCTTATAATGGTTACAAATAAAGCAATAGCATCACAAATTTCACAAA TAAAGCATTTTTTTCACTGCATTCTAGTTGTGGTTTGTCCAAACTCATCAATGTATCTTATCATG TCTGTATACCGTCGACCTCTAGCTAGAGCTTGGCGTAATCATGGTCATAGCTGTTTCCTGTGTG AAATTGTTATCCGCTCACAATTCCACACAACATACGAGCCGGAAGCATAAAGTGTAAAGCCTG GGGTGCCTAATGAGTGAGCTAACTCACATTAATTGCGTTGCGCTCACTGCCCGCTTTCCAGTCG GGAAACCTGTCGTGCCAGCTGCATTAATGAATCGGCCAACGCGCGGGGAGAGGCGGTTTGCG TATTGGGCGCTCTTCCGCTTCCTCGCTCACTGACTCGCTGCGCTCGGTCGTTCGGCTGCGGCGA GCGGTATCAGCTCACTCAAAGGCGGTAATACGGTTATCCACAGAATCAGGGGATAACGCAGG AAAGAACATGTGAGCAAAAGGCCAGCAAAAGGCCAGGAACCGTAAAAAGGCCGCGTTGCTG GCGTTTTTCCATAGGCTCCGCCCCCCTGACGAGCATCACAAAAATCGACGCTCAAGTCAGAGG TGGCGAAACCCGACAGGACTATAAAGATACCAGGCGTTTCCCCCTGGAAGCTCCCTCGTGCGC TCTCCTGTTCCGACCCTGCCGCTTACCGGATACCTGTCCGCCTTTCTCCCTTCGGGAAGCGTGG CGCTTTCTCAATGCTCACGCTGTAGGTATCTCAGTTCGGTGTAGGTCGTTCGCTCCAAGCTGGG CTGTGTGCACGAACCCCCCGTTCAGCCCGACCGCTGCGCCTTATCCGGTAACTATCGTCTTGAG TCCAACCCGGTAAGACACGACTTATCGCCACTGGCAGCAGCCACTGGTAACAGGATTAGCAG AGCGAGGTATGTAGGCGGTGCTACAGAGTTCTTGAAGTGGTGGCCTAACTACGGCTACACTA GAAGGACAGTATTTGGTATCTGCGCTCTGCTGAAGCCAGTTACCTTCGGAAAAAGAGTTGGTA GCTCTTGATCCGGCAAACAAACCACCGCTGGTAGCGGTGGTTTTTTTGTTTGCAAGCAGCAGA TTACGCGCAGAAAAAAAGGATCTCAAGAAGATCCTTTGATCTTTTCTACGGGGTCTGACGCTC AGTGGAACGAAAACTCACGTTAAGGGATTTTGGTCATGAGATTATCAAAAAGGATCTTCACCT AGATCCTTTTAAATTAAAAATGAAGTTTTAAATCAATCTAAAGTATATATGAGTAAACTTGGTC TGACAGTTACCAATGCTTAATCAGTGAGGCACCTATCTCAGCGATCTGTCTATTTCGTTCATCC ATAGTTGCCTGACTCCCCGTCGTGTAGATAACTACGATACGGGAGGGCTTACCATCTGGCCCC AGTGCTGCAATGATACCGCGAGACCCACGCTCACCGGCTCCAGATTTATCAGCAATAAACCAG CCAGCCGGAAGGGCCGAGCGCAGAAGTGGTCCTGCAACTTTATCCGCCTCCATCCAGTCTATT AATTGTTGCCGGGAAGCTAGAGTAAGTAGTTCGCCAGTTAATAGTTTGCGCAACGTTGTTGCC ATTGCTACAGGCATCGTGGTGTCACGCTCGTCGTTTGGTATGGCTTCATTCAGCTCCGGTTCCC AACGATCAAGGCGAGTTACATGATCCCCCATGTTGTGCAAAAAAGCGGTTAGCTCCTTCGGTC CTCCGATCGTTGTCAGAAGTAAGTTGGCCGCAGTGTTATCACTCATGGTTATGGCAGCACTGC ATAATTCTCTTACTGTCATGCCATCCGTAAGATGCTTTTCTGTGACTGGTGAGTACTCAACCAA GTCATTCTGAGAATAGTGTATGCGGCGACCGAGTTGCTCTTGCCCGGCGTCAATACGGGATAA

230

TACCGCGCCACATAGCAGAACTTTAAAAGTGCTCATCATTGGAAAACGTTCTTCGGGGCGAAA ACTCTCAAGGATCTTACCGCTGTTGAGATCCAGTTCGATGTAACCCACTCGTGCACCCAACTGA TCTTCAGCATCTTTTACTTTCACCAGCGTTTCTGGGTGAGCAAAAACAGGAAGGCAAAATGCC GCAAAAAAGGGAATAAGGGCGACACGGAAATGTTGAATACTCATACTCTTCCTTTTTCAATAT TATTGAAGCATTTATCAGGGTTATTGTCTCATGAGCGGATACATATTTGAATGTATTTAGAAAA ATAAACAAATAGGGGTTCCGCGCACATTTCCCCGAAAAGTGCCACCTGACGTC

8.1.4 pSecTag2 Hoxa3.mCherry

Yellow = CMV prom, and then SP peptide from Ig kappa leader sequence Blue = BamHI site used for cloning Pink = MCR from TOPO TA cloning vector pCRII Violet = Hoxa3 ORF Red = mCherry ORF Turquoise = XhoI site for cloning

NB: This sequence contains silent point mutations (marked by white highlighting) when compared to NCBI/Genbank Hoxa3 sequence. GACGGATCGGGAGATCTCCCGATCCCCTATGGTCGACTCTCAGTACAATCTGCTCTGATGCCG CATAGTTAAGCCAGTATCTGCTCCCTGCTTGTGTGTTGGAGGTCGCTGAGTAGTGCGCGAGCA AAATTTAAGCTACAACAAGGCAAGGCTTGACCGACAATTGCATGAAGAATCTGCTTAGGGTTA GGCGTTTTGCGCTGCTTCGCGATGTACGGGCCAGATATACGCGTTGACATTGATTATTGACTA GTTATTAATAGTAATCAATTACGGGGTCATTAGTTCATAGCCCATATATGGAGTTCCGCGTTAC ATAACTTACGGTAAATGGCCCGCCTGGCTGACCGCCCAACGACCCCCGCCCATTGACGTCAAT AATGACGTATGTTCCCATAGTAACGCCAATAGGGACTTTCCATTGACGTCAATGGGTGGACTA TTTACGGTAAACTGCCCACTTGGCAGTACATCAAGTGTATCATATGCCAAGTACGCCCCCTATT GACGTCAATGACGGTAAATGGCCCGCCTGGCATTATGCCCAGTACATGACCTTATGGGACTTT CCTACTTGGCAGTACATCTACGTATTAGTCATCGCTATTACCATGGTGATGCGGTTTTGGCAGT ACATCAATGGGCGTGGATAGCGGTTTGACTCACGGGGATTTCCAAGTCTCCACCCCATTGACG

231

TCAATGGGAGTTTGTTTTGGCACCAAAATCAACGGGACTTTCCAAAATGTCGTAACAACTCCG CCCCATTGACGCAAATGGGCGGTAGGCGTGTACGGTGGGAGGTCTATATAAGCAGAGCTCTC TGGCTAACTAGAGAACCCACTGCTTACTGGCTTATCGAAATTAATACGACTCACTATAGGGAG ACCCAAGCTGGCTAGCCACCATGGAGACAGACACACTCCTGCTATGGGTACTGCTGCTCTGGG TTCCAGGTTCCACTGGTGACGCGGCCCAGCCGGCCAGGCGCGCCGTACGAAGCTTGGTACCG AGCTCGGATCCACTAGTAACGGCCGCCAGTGTGCTGGAATTCGCCCTTAACATCGCGATGCAA AAAGCGACCTACTACGACAGCTCAGCGATCTACGGTGGCTACCCCTACCAAGCAGCCAATGG GTTCGCTTACAATGCCAGTCAGCAGCCATACGCGCCGTCCGCCGCTCTGGGCACCGATGGCGT TGAGTACCATCGACCTGCCTGCTCCCTCCAGTCTCCCGCCAGCGCTGGGGGCCACCCCAAAAC TCATGAGCTGAGCGAAGCTTGTCTGCGCACCCTGAGCGGCCCTCCTAGTCAGCCCCCAGGCCT GGGTGAACCACCTTTGCCTCCACCTCCTCCCCAGGCAGCGCCCCCAGCGCCCCAGCCTCCACA GCCCCCACCACAGCCCCCTGCGCCCACCCCTGCAGCTCCTCCGCCTCCCTCGTCTGTCTCTCCCC CTCAAAGTGCCAACAGCAACCCTACCCCTGCCAGCACAGCCAAGAGCCCCCTGCTCAACTCTCC CACCGTGGGCAAACAAATCTTTCCCTGGATGAAAGAGTCAAGGCAGAACACTAAGCAGAAAA CCAGCGGCTCCAGCTCAGGGGAGAGCTGCGCTGGTGACAAGAGCCCGCCTGGGCAGGCCTC GTCCAAGCGCGCGCGCACGGCGTACACGAGCGCGCAGCTGGTAGAGCTGGAGAAGGAGTTC CACTTCAACCGCTACCTATGCCGGCCGCGCCGGGTGGAGATGGCCAACCTGCTGAACCTCACC GAGCGCCAGATCAAGATCTGGTTCCAGAACCGCCGCATGAAGTACAAGAAAGACCAGAAGG GCAAAGGCATGCTGACCTCGTCTGGGGGCCAGTCCCCAAGTCGGAGCCCTGTGCCTCCCGGT GCAGGAGGCTATCTGAATTCTATGCATTCGCTGGTCAACAGTGTCCCATATGAGCCCCAGTCA CCCCCTCCTTTCTCCAAGCCTCCCCAAGGCGCCTATGGGTTGCCTCCGGCCTCCTACCCTGCTCC CCTGCCCAGCTGCGCTCCCCCACCTCCCCCACAGAAACGCTACACAGCGGCGGGGTCAGGCGC AGGGGGCACCCCTGACTACGACCCGCATGCTCACGGCCTGCAGGGCAATGGCAGCTATGGGA CCCCACACTTACAGGGAAGCCCCGTCTTCGTGGGGGGCAGCTATGTGGAGCCCATGAGCAAC TCTGGGCCACTCTTTGGCCTAACTCACCTCCCCCACACCACCTCGGCTGCCATGGACTACGGGG GCACTGGGCCGCTGGGCAGCGGACACCACCATGGGCCGGGGCCTGGGGAGCCACACCCCAC CTACACGGACCTTACTGCCCACCATCCTTCTCAGGGAAGGATTCAGGAAGCGCCCAAGCTCAC CCACCTAGTGAGTAAGGGCGAGGAGGATAACATGGCCATCATCAAGGAGTTCATGCGCTTCA AGGTGCACATGGAGGGCTCCGTGAACGGCCACGAGTTCGAGATCGAGGGCGAGGGCGAGG GCCGCCCCTACGAGGGCACCCAGACCGCCAAGCTGAAGGTGACCAAGGGTGGCCCCCTGCCC TTCGCCTGGGACATCCTGTCCCCTCAGTTCATGTACGGCTCCAAGGCCTACGTGAAGCACCCC GCCGACATCCCCGACTACTTGAAGCTGTCCTTCCCCGAGGGCTTCAAGTGGGAGCGCGTGATG AACTTCGAGGACGGCGGCGTGGTGACCGTGACCCAGGACTCCTCCCTGCAGGACGGCGAGTT CATCTACAAGGTGAAGCTGCGCGGCACCAACTTCCCCTCCGACGGCCCCGTAATGCAGAAGAA GACCATGGGCTGGGAGGCCTCCTCCGAGCGGATGTACCCCGAGGACGGCGCCCTGAAGGGC GAGATCAAGCAGAGGCTGAAGCTGAAGGACGGCGGCCACTACGACGCTGAGGTCAAGACCA CCTACAAGGCCAAGAAGCCCGTGCAGCTGCCCGGCGCCTACAACGTCAACATCAAGTTGGAC ATCACCTCCCACAACGAGGACTACACCATCGTGGAACAGTACGAACGCGCCGAGGGCCGCCA CTCCACCGGCGGCATGGACGAGCTGTACAAGTAAAAGGGCGAATTCTGCAGATATCCATCAC ACTGGCGGCCGCTCGAGGAGGGCCCGAACAAAAACTCATCTCAGAAGAGGATCTGAATAGCG CCGTCGACCATCATCATCATCATCATTGAGTTTAAACCCGCTGATCAGCCTCGACTGTGCCTTCT AGTTGCCAGCCATCTGTTGTTTGCCCCTCCCCCGTGCCTTCCTTGACCCTGGAAGGTGCCACTC CCACTGTCCTTTCCTAATAAAATGAGGAAATTGCATCGCATTGTCTGAGTAGGTGTCATTCTAT TCTGGGGGGTGGGGTGGGGCAGGACAGCAAGGGGGAGGATTGGGAAGACAATAGCAGGCA

232

TGCTGGGGATGCGGTGGGCTCTATGGCTTCTGAGGCGGAAAGAACCAGCTGGGGCTCTAGG GGGTATCCCCACGCGCCCTGTAGCGGCGCATTAAGCGCGGCGGGTGTGGTGGTTACGCGCAG CGTGACCGCTACACTTGCCAGCGCCCTAGCGCCCGCTCCTTTCGCTTTCTTCCCTTCCTTTCTCG CCACGTTCGCCGGCTTTCCCCGTCAAGCTCTAAATCGGGGCATCCCTTTAGGGTTCCGATTTAG TGCTTTACGGCACCTCGACCCCAAAAAACTTGATTAGGGTGATGGTTCACGTAGTGGGCCATC GCCCTGATAGACGGTTTTTCGCCCTTTGACGTTGGAGTCCACGTTCTTTAATAGTGGACTCTTG TTCCAAACTGGAACAACACTCAACCCTATCTCGGTCTATTCTTTTGATTTATAAGGGATTTTGG GGATTTCGGCCTATTGGTTAAAAAATGAGCTGATTTAACAAAAATTTAACGCGAATTAATTCTG TGGAATGTGTGTCAGTTAGGGTGTGGAAAGTCCCCAGGCTCCCCAGCAGGCAGAAGTATGCA AAGCATGCATCTCAATTAGTCAGCAACCAGGTGTGGAAAGTCCCCAGGCTCCCCAGCAGGCA GAAGTATGCAAAGCATGCATCTCAATTAGTCAGCAACCATAGTCCCGCCCCTAACTCCGCCCAT CCCGCCCCTAACTCCGCCCAGTTCCGCCCATTCTCCGCCCCATGGCTGACTAATTTTTTTTATTT ATGCAGAGGCCGAGGCCGCCTCTGCCTCTGAGCTATTCCAGAAGTAGTGAGGAGGCTTTTTTG GAGGCCTAGGCTTTTGCAAAAAGCTCCCGGGAGCTTGTATATCCATTTTCGGATCTGATCAGC ACGTGTTGACAATTAATCATCGGCATAGTATATCGGCATAGTATAATACGACAAGGTGAGGAA CTAAACCATGGCCAAGTTGACCAGTGCCGTTCCGGTGCTCACCGCGCGCGACGTCGCCGGAG CGGTCGAGTTCTGGACCGACCGGCTCGGGTTCTCCCGGGACTTCGTGGAGGACGACTTCGCC GGTGTGGTCCGGGACGACGTGACCCTGTTCATCAGCGCGGTCCAGGACCAGGTGGTGCCGGA CAACACCCTGGCCTGGGTGTGGGTGCGCGGCCTGGACGAGCTGTACGCCGAGTGGTCGGAG GTCGTGTCCACGAACTTCCGGGACGCCTCCGGGCCGGCCATGACCGAGATCGGCGAGCAGCC GTGGGGGCGGGAGTTCGCCCTGCGCGACCCGGCCGGCAACTGCGTGCACTTCGTGGCCGAG GAGCAGGACTGACACGTGCTACGAGATTTCGATTCCACCGCCGCCTTCTATGAAAGGTTGGGC TTCGGAATCGTTTTCCGGGACGCCGGCTGGATGATCCTCCAGCGCGGGGATCTCATGCTGGA GTTCTTCGCCCACCCCAACTTGTTTATTGCAGCTTATAATGGTTACAAATAAAGCAATAGCATC ACAAATTTCACAAATAAAGCATTTTTTTCACTGCATTCTAGTTGTGGTTTGTCCAAACTCATCAA TGTATCTTATCATGTCTGTATACCGTCGACCTCTAGCTAGAGCTTGGCGTAATCATGGTCATAG CTGTTTCCTGTGTGAAATTGTTATCCGCTCACAATTCCACACAACATACGAGCCGGAAGCATAA AGTGTAAAGCCTGGGGTGCCTAATGAGTGAGCTAACTCACATTAATTGCGTTGCGCTCACTGC CCGCTTTCCAGTCGGGAAACCTGTCGTGCCAGCTGCATTAATGAATCGGCCAACGCGCGGGG AGAGGCGGTTTGCGTATTGGGCGCTCTTCCGCTTCCTCGCTCACTGACTCGCTGCGCTCGGTC GTTCGGCTGCGGCGAGCGGTATCAGCTCACTCAAAGGCGGTAATACGGTTATCCACAGAATC AGGGGATAACGCAGGAAAGAACATGTGAGCAAAAGGCCAGCAAAAGGCCAGGAACCGTAAA AAGGCCGCGTTGCTGGCGTTTTTCCATAGGCTCCGCCCCCCTGACGAGCATCACAAAAATCGA CGCTCAAGTCAGAGGTGGCGAAACCCGACAGGACTATAAAGATACCAGGCGTTTCCCCCTGG AAGCTCCCTCGTGCGCTCTCCTGTTCCGACCCTGCCGCTTACCGGATACCTGTCCGCCTTTCTCC CTTCGGGAAGCGTGGCGCTTTCTCAATGCTCACGCTGTAGGTATCTCAGTTCGGTGTAGGTCG TTCGCTCCAAGCTGGGCTGTGTGCACGAACCCCCCGTTCAGCCCGACCGCTGCGCCTTATCCG GTAACTATCGTCTTGAGTCCAACCCGGTAAGACACGACTTATCGCCACTGGCAGCAGCCACTG GTAACAGGATTAGCAGAGCGAGGTATGTAGGCGGTGCTACAGAGTTCTTGAAGTGGTGGCCT AACTACGGCTACACTAGAAGGACAGTATTTGGTATCTGCGCTCTGCTGAAGCCAGTTACCTTC GGAAAAAGAGTTGGTAGCTCTTGATCCGGCAAACAAACCACCGCTGGTAGCGGTGGTTTTTTT GTTTGCAAGCAGCAGATTACGCGCAGAAAAAAAGGATCTCAAGAAGATCCTTTGATCTTTTCT ACGGGGTCTGACGCTCAGTGGAACGAAAACTCACGTTAAGGGATTTTGGTCATGAGATTATCA AAAAGGATCTTCACCTAGATCCTTTTAAATTAAAAATGAAGTTTTAAATCAATCTAAAGTATAT

233

ATGAGTAAACTTGGTCTGACAGTTACCAATGCTTAATCAGTGAGGCACCTATCTCAGCGATCT GTCTATTTCGTTCATCCATAGTTGCCTGACTCCCCGTCGTGTAGATAACTACGATACGGGAGGG CTTACCATCTGGCCCCAGTGCTGCAATGATACCGCGAGACCCACGCTCACCGGCTCCAGATTT ATCAGCAATAAACCAGCCAGCCGGAAGGGCCGAGCGCAGAAGTGGTCCTGCAACTTTATCCG CCTCCATCCAGTCTATTAATTGTTGCCGGGAAGCTAGAGTAAGTAGTTCGCCAGTTAATAGTTT GCGCAACGTTGTTGCCATTGCTACAGGCATCGTGGTGTCACGCTCGTCGTTTGGTATGGCTTC ATTCAGCTCCGGTTCCCAACGATCAAGGCGAGTTACATGATCCCCCATGTTGTGCAAAAAAGC GGTTAGCTCCTTCGGTCCTCCGATCGTTGTCAGAAGTAAGTTGGCCGCAGTGTTATCACTCATG GTTATGGCAGCACTGCATAATTCTCTTACTGTCATGCCATCCGTAAGATGCTTTTCTGTGACTG GTGAGTACTCAACCAAGTCATTCTGAGAATAGTGTATGCGGCGACCGAGTTGCTCTTGCCCGG CGTCAATACGGGATAATACCGCGCCACATAGCAGAACTTTAAAAGTGCTCATCATTGGAAAAC GTTCTTCGGGGCGAAAACTCTCAAGGATCTTACCGCTGTTGAGATCCAGTTCGATGTAACCCA CTCGTGCACCCAACTGATCTTCAGCATCTTTTACTTTCACCAGCGTTTCTGGGTGAGCAAAAAC AGGAAGGCAAAATGCCGCAAAAAAGGGAATAAGGGCGACACGGAAATGTTGAATACTCATA CTCTTCCTTTTTCAATATTATTGAAGCATTTATCAGGGTTATTGTCTCATGAGCGGATACATATT TGAATGTATTTAGAAAAATAAACAAATAGGGGTTCCGCGCACATTTCCCCGAAAAGTGCCACC TGACGTC

234