Adipose Derived Stem Cell Osteogenic Differentiation: a Study

ADIPOSE DERIVED STEM CELL OSTEOGENIC DIFFERENTIATION: A STUDY

OF THE INFLUENCE OF EXTRACELLULAR MATRIX ON THE

DIFFERENTIATION PROCESS

Heather Adeline Bradbury Coan

A Dissertation Submitted to the Graduate Faculty of

WAKE FOREST UNIVERISTY GRADUATE SCHOOL OF ARTS AND SCIENCES

in Partial Fulfillment of the Requirements

for the Degree of

DOCTOR OF PHILOSOPHY

in the Molecular Genetics and Genomics Program

May 2011

Winston-Salem, North Carolina

Approved By

Mark Van Dyke, Ph.D., Advisor

Stephen Walker, Ph.D., Chair

Barbara D. Boyan, Ph.D.

Mark O. Lively, Ph.D.

Shay Soker, Ph.D.

ACKNOWLEDGMENTS

I first want to thank my advisor Dr. Mark Van Dyke. As a mentor and friend,

Mark has provided me with guidance and support throughout my entire graduate student career. His unwavering support and confidence in my abilities allowed me to pursue my degree with the knowledge that I could learn to do anything in the lab with time and practice. This project, although largely outside of Mark’s area of expertise, took shape through his guidance and vision as well as his willingness to entrust the details to me.

My future success can be attributed to Mark’s dedication to me as a student.

Additionally, I owe thanks to my program director Dr. Mark Lively. As an ―old school‖ scientist, his attention to detail has taught me to pay attention to things which might seem minor however often play the biggest role in the success of an experiment.

The dedication he has shown me throughout this process is greatly appreciated. Also, thanks to my committee members Dr. Shay Soker, Dr. Steve Walker, and Dr. Barbara

Boyan. The suggestions and input each of them provided in experimental design and concepts were vital to this project.

Others, too many to mention, who have helped throughout this project include many past and present lab members. Chris Booth, a friend and student researcher has helped me with experiments for the past four years. Emily Moorefield, Dr. David Mack,

Dr. Thaleia Teli, Drs. Amber and Matt Stern, as well as the Van Dyke research group, have all provided vital input into the project design and goals.

Additionally however, I want to thank several past teachers and professors whose excitement and enthusiasm for science led me down this career path. Mr. Mike Smith

―Smitty‖, my high school biology professor was first to spark my interest in the sciences.

I give him credit for my choice to pursue science as a college degree path. Two professors at Appalachian State University, Dr. Jeffrey Butts, and Dr. Mary Connell, were also a large influence on me as a student. Dr. Butts, my advisor, was always a source of support and aid throughout my college career. Dr. Mary Connell, my molecular biology professor however, gave me my first taste of success in a scientific lab setting as well as provided support and advice while I was applying for graduate school programs.

Finally, I want to thank my family. My parents, brothers, and grandparents have all provided support and love throughout this process. My parents, Kevin and Barb

Bradbury, instilled in me my work ethic and the confidence to pursue anything I wanted to do. I owe them everything for providing me with a childhood full of learning experiences and unending opportunities. I could not ask for two more perfect people to model my life after. I also want to thank my in-laws Martha and Chuck Saffer, as well as

Jim Coan and Suzanna Blanchard for providing me with love and support.

And last of all, my wonderful husband, Beau Coan and my sweet daughter

Adeline Coan. Each has provided their own brand of support throughout the process.

Beau has been my rock and my support to lean on when I thought this process would never end. He has supported me and pushed me forward every step of the way. Adeline, my darling girl, who has made the process fun and brought perspective to what otherwise can be a long and arduous journey. I hope one day, she will pursue whatever passions she has, as I’ve been lucky to be able to pursue mine. Finally, to the other two family members ―the boys‖ Doc and Wyatt my two border collies who have forced me to get off my butt while writing and take them on walks and runs!

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TABLE OF CONTENTS

PAGE

LIST OF FIGURES …………………………………………………...... v

LIST OF TABLES ……………………………………………………….. ix

LIST OF ABBREVIATIONS ……………………………………….. xi

ABSTRACT ……………………………………………………….. xiv

INTRODUCTION ……………………………………………………….. 1

MATERIALS AND METHODS ……………………………………….. 12

RESULTS:

Chapter 1. Creating an Osteogenic Differentiation Expression Profile for Human Adipose Derived Stem Cells using Whole Transcriptome Profiling and ECM-Related Gene Expression Profiling ……………………….. 34

Chapter 2. Cell-Secreted Matrices Modulate Osteogenic Differentiation of Adipose Derived Stem Cells ……. 61

Chapter 3. Dermatopontin in the Extracellular Matrix may Enhance Osteogenic Differentiation of Adipose Derived Stem Cells ……………………………….. 117

DISCUSSION AND CONCLUSIONS ………………………………... 138

REFERENCES ………………………………………………………... 166

APPENDIX 1 ADSC Isolation ………………………………... 185

APPENDIX 2 ADSC Flow Cytometry Characterization ………… 186

APPENDIX 3 ECM: Characterization of Day 11 and Day 16 Differential Protein Content using 2D Gel Electrophoresis, LC/MS/MS, and Mascot Searches …. 188

APPENDIX 4 QPCR Confirmation of Genes Identified Through Gene Analysis ………………………………… 194

SCHOLASTIC VITA ………………………………………………… 201

LIST OF FIGURES

PAGE

MATERIALS AND METHODS

Figure 1. Gene array experimental design. 21

Figure 2. Gene array analysis workflow. 22

Figure 3. Histogram comparing raw data to RMA-normalized data. 23

Figure 4. Design and construction of Lenti_DPT construct. 29

CHAPTER 1

Figure 1. Osteogenic transcription factor RUNX2 mRNA expression increases with time in culture during BM induced osteogenesis. 36

Figure 2. Alkaline phosphatase enzyme activity and mRNA levels increase with time in culture during BM induced osteogenic differentiation. 37

Figure 3. ADSC induced to differentiate deposit calcium in the form of a mineralized matrix; ADSC in maintenance medium do not. 39

Figure 4. Mature osteoblast marker osteocalcin mRNA and protein levels are significantly increased by day 21 in differentiation. 40

Figure 5. Hierarchical gene clustering of time points in differentiation. 44

Figure 6. Differentiation factors important in activating adipogenesis. 54

Figure 7. Adipose terminal differentiation markers (FABP4 and FAS) and adipokines (Leptin and Adipsin). 55

Figure 8. Hierarchical gene clustering of ECM-rg at time points in osteogenesis. 57

CHAPTER 2

Figure 1. ECM deposited on culture dish during osteogenic differentiation. 62

Figure 2. Increased calcium deposition on ECM coated dishes visualized with alizarin red. 63 v

Figure 3. RUNX2 mRNA expression increases for cells induced to differentiate on day 16 and day 24 ECM. 64

Figure 4. mRNA expression of bone related genes osteopontin (OPN) and osteoprotegerin (OPG) increases when cells are induced to differentiate on day 16 ECM. 66

Figure 5. mRNA expression of bone related genes transcription factor 4 (ATF4), and alkaline phosphatase (ALP) increases when cells are induced to differentiate on day 16 ECM. 67

Figure 6. Significant increases in mRNA and protein levels of osteocalcin were observed in cells induced to differentiate on day 16 ECM. 68

Figure 7. Gene arrays grouped by overall similarity in expression profiles. 71

Figure 8. Heat map indicating high (red) or low (green) expression of genes clustered on the bases of similar expression in Experimental 1. 73

Figure 9. Heat map indicating high (red) or low (green) expression of genes clustered on the bases of similar expression in Experimental 2. 74

Figure 10. Venn diagrams for each time point with each of the groups (Control in blue, Experimental 1 in yellow, and Experimental 2 in green). 94

Figure 11. Gene expression of adipose differentiation factors, PPARγ and C/EBPα important in activating adipogenesis, shows differential expression among the groups. 104

Figure 12. Gene expression of adipose differentiation factors, C/EBPβ and C/EBPδ important in activating adipogenesis, shows differentiation expression among the groups. 105

Figure 13. Gene expression of adipose terminal differentiation markers fatty acid binding protein 4 and fatty acid synthase varies between groups. 106

Figure 14. Gene expression of adipokines leptin and adipsin varies between groups. 107

Figure 15. Heat map indicating high (red) or low (green) expression of ECM-rgs clustered on the basis similar expression patterns. 109

Figure 16. Heat map indicating high (red) or low (green) expression of ECM-rg clustered on the bases of similar expression in Experimental 1. 112

Figure 17. Heat map indicating high (red) or low (green) expression of ECM-rg clustered on the bases of similar expression in Experimental 2. 113

CHAPTER 3

Figure 1. Dermatopontin mRNA expression increases during osteogenic differentiation in Control and Experimental 1 groups. 119

Figure 2. Dermatopontin protein levels increase dramatically between days 10 and 16 in the Controls as observed through western blotting. 120

Figure 3. HEK293T cells transfected with Lenti_DPT construct. 121

Figure 4. Cell sorting of ADSC exposed to Lenti_DPT viral supernatant showed low infection efficiency. 122

Figure 5. Cell sorting enriched Lenti_DPT infected ADSC population. 123

Figure 6. ADSC infected with Lenti_DPT and sorted using ZsGreen express high levels of DPT mRNA. 124

Figure 7. Dermatopontin protein in ADSC_DPT cells increases corresponding to an increase in DPT gene overexpression driven by the Lentiviral infection. 125

Figure 8. Cell sorting enriched Lenti_DPT infected ADSC population cultured for 30 days maintain fluorescence. 126

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Figure 10. Gene expression of TAZ and Wnt5A is downregulated at day 21 in ADSC_DPT cells compared to Controls. 130

Figure 11. Gene expression of RUNX2 increases in DPT_ECM seeded cells at day 21 compared to Day 21 Control and Experimental 1. 132

Figure 12. Gene expression of osteocalcin increases in DPT_ECM seeded cells at day 21 compared to Day 21 Control and Experimental 1. 133

Figure 13. Gene expression of TAZ increases in DPT_ECM seeded cells at day 21 compared to Day 21 Control and Experimental 1. 135

Figure 14. Gene expression of Wnt5A is high in DPT_ECM seeded cells at day 21 however not significant compared to Day 21 Control and Experimental 1. 136

DISCUSSION AND CONCLUSIONS

Figure 1. Time points (red) in this work and how they relate to maturational phases observed in osteogenesis. 141

Figure 2. Time points how they relate to maturational phases observed in osteogenesis of Control group compared to Experimental 1 group. 154

APPENDIX 1

Figure 1_A1. ADSC isolation procedure. 185

APPENDIX 2

Figure 1_A2. ADSC Line #2, passage 2 flow cytometry results. 186

APPENDIX 3

Figure 1_A3. 2D gels of ECM isolated from day 11 and day 16. 192

APPENDIX4

Figure 1_A4. QPCR confirmation of Lines 1 & 3 on TCP and day 16 ECM for RUNX2 (A), ALP (B), and Osteocalcin (C). 195

Figure 2_A4. QPCR confirmation of genes identified through gene array analysis. 200

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LIST OF TABLES

PAGE

MATERIALS AND METHODS

Table I. ADSC osteogenesis-related genes identified and screened for with QPCR. 17

CHAPTER 1

Table I. Gene ontology categories mapped to specific clades observed in heat map expression. 45

Table II. List of skeletal system development genes highly enriched and significantly expressed at day 21 in osteogenesis. 46

Table III. STEM analysis expression clusters and related GO terms. 50

Table IV. Top 20 upregulated genes at each time point. 52

Table V. Gene ontology categories associated with ECM-rgs. 59

CHAPTER 2

Table I. Gene ontology categories mapped to specific clades observed in heat map expression of Experimental 1 and 2. 75

Table II. List of skeletal system development genes highly enriched and significantly expressed at day 21 in Experimental 1. 78

Table III. STEM expression clusters and related GO categories for Experimental 1 time course. 86

Table IV. STEM expression clusters and related GO categories for Experimental 2 timecourse. 91

Table V. Gene ontology categories mapped to shared genes generated using Venny at each time point. 95

Table VI. Gene ontology categories mapped to individual group expressed genes for each time point generated using Venny. 96

Table VII. Top 20 genes expressed at each time point in Experimental 1. 100

Table VIII. Top 20 genes expressed at each time point in Experimental 2. 101

Table IX. Gene ontology categories associated with ECM-rg expressed at high levels at each time point listed in Experimental 1. 114

Table X. Gene ontology categories associated with ECM-rg expressed at high levels at each time point listed in Experimental 2. 115

APPENDIX 2

Table I_A2. Percentage of ADSC expressing MSC-related markers at Various passage numbers in the ADSC Lines #1, #2, and #3. 187

APPENDIX 3

Table I_A3. Mascot identification of differential spot analysis for 2D gels. 193

LIST OF ABBREVIATIONS

A/A Antibiotic Antimycotic aa Ascorbic Acid-2-phosphate

ADSC Adipose Derived Stem Cells

ADSC_DPT Adipose Derived Stem Cells Overexpressing Dermatopontin

AEC Affymetrix Expression Console

ALP Alkaline Phosphatase

AMM Adipose Maintenance Medium

ANOVA Analysis of Variation

ATF4 Activating Transcription Factor 4

BGP β-glycerophosphate

BM Bone Medium

BMP Bone Morphogenetic Protein

BMSC Bone Marrow Derived Mesenchymal Stem Cells

BTE Bone Tissue Engineering cDNA Complementary DNA

DAVID Database for Annotation, Visualization, and Discovery

DHMRI David H. Murdock Research Institute

DMEM Dulbecco’s Modified Eagle Medium

DPT Dermatopontin

DPT_ECM ECM isolated from ADSC overexpressing Dermatopontin

DX Dexamethasone

ECM Extracellular Matrix

ECM-rg Extracellular Matrix Related Genes

ELISA Enzyme Linked Immunosorbant Assay

EtOH Ethanol

Exon Array Affymetrix GeneChip Human Exon 1.0 ST Array

FBS Fetal Bovine Serum

FDR False Discovery Rate

FTIR Fourier Transform Infrared Spectrometry

GO Gene Ontology

HEK293T Human Embryonic Kidney 293T cells

IGF Insulin-like Growth Factor

IRB Institutional Review Board

IRES Internal Ribosome Entry Site

Lenti_DPT Lentivirus Dermatopontin Green Fluorescent Vector Construct

Lenti_vector Lentivirus Vector Alone Without Dermatopontin Gene Insert

LR Log Ratio

LRR Leucine Rich Repeat mRNA Messenger RNA

MSC Mesenchymal Stem Cell

OCN Osteocalcin

OPG Osteoprotegerin

OPN Osteopontin

OS Osteogenic Supplements

PBS Phosphate-Buffered Saline

PNPP p-nitrophenyl phosphate

PPARγ Peroxisome Proliferator-Activated Receptor Gamma

P/S Penicillin/ Streptomycin

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QC Quality Control

QPCR Quantitative Polymerase Chain Reaction

RMA Robust Multichip Average

RUNX2 Runt-Related Transcription Factor 2

SD Standard Deviation

SDS-PAGE Sodium Dodecyl Sulfate Polyacrylamide Gel Electrophoresis

SVF Stromal Vascular Fraction

TCA Trichloracetic Acid

TCP Tissue Culture Plastic

TE/RM Tissue Engineering and Regenerative Medicine

TGF Transforming Growth Factor

VDR Vitamin D Receptor

XRD X-Ray Diffraction

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ABSTRACT

Heather Adeline Bradbury Coan

ADIPOSE DERIVED STEM CELL OSTEOGENIC DIFFERENTIATION: A STUDY

OF THE INFLUENCE OF EXTRACELLULAR MATRIX ON THE

DIFFERENTIATION PROCESS

Dissertation under the direction of Dr. Mark Van Dyke, Ph.D., Assistant Professor Institute for Regenerative Medicine

Mesenchymal stem cells (MSC) are an important component of many tissue engineering and regenerative medicine (TE/RM) strategies. Their multipotential characteristics make them extremely useful as a source of cells for TE/RM applications.

Adipose-derived stem cells (ADSC) represent one type of MSC and have many characteristics which make them a clinically relevant source of MSC. Specifically, in the field of bone tissue engineering (BTE), ADSC are commonly used for in vitro osteogenesis studies. Although these cells display similar characteristics as bone marrow-derived stem cells (BMSC), the mechanisms and pathways that these cells utilize to differentiate down the osteogenic pathway are still unclear. Specific differences exist between BMSC and ADSC osteogenesis; however more detailed analysis of how the two

MSC types differ will be important for enhanced clinical relevance of ADSC. Chapter 1 of this work identified important components of ADSC osteogenesis, providing an osteogenesis template for Chapters 2 and 3 which focus on the modulation of ADSC osteogenesis.

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Osteogenic differentiation of MSC is an important concept for the field of BTE.

The identification of biological factors which can influence MSC osteogenic lineage specification is important in developing a broader understanding of how complex microenvironments play a role in differentiation. In Chapter 2, we demonstrate that

ADSC osteogenesis is enhanced through interaction with extracellular matrices (ECM) secreted from the midpoint in osteogenesis. We show that not only are osteogenic markers highly enriched compared to ADSC induced on tissue culture plastic (Controls), was also show that osteogenic maturational phases occur more rapidly in the presence of this ECM.

Finally, in Chapter 3, we demonstrate that a direct correlation may exist between

ECM-related genes (ECM-rg) expressed at a particular time point and the corresponding activity of the secreted and corresponding entrained proteins from that same time point.

We show that Dermatopontin (DPT), highly expressed at day 16 in osteogenesis, has an effect on differentiation. Specifically, abundant DPT in the ECM (obtained through lentiviral infection), induces high expression of osteogenic genes; higher than cells seeded onto ECM as shown in Chapter 2.

INTRODUCTION

The use of multipotential cells for tissue engineering and regenerative medicine applications is of extreme importance. These two areas of study have the potential to change the way modern medicine functions as well as treats disease by changing paradigms of disease management. The switch in paradigms, from treatment of a diseased or damaged organ to replacement of that organ, warrants the need for multipotential cells capable of replacing the damaged or diseased organ’s cells. This need for appropriate cell types has driven researchers to identify previously unknown sources of multipotential cells, otherwise referred to as mesenchymal stem cells (MSC).

Many of these newly identified cell types are identified as tissue-specific MSC and have been identified in a variety of tissues including fat, bone marrow, muscle, umbilical cord, amniotic fluid, placenta, dental pulp, tendons, synovial membrane, and skeletal muscle

[1-9].

The expansion of tissue engineering and regenerative medicine (TE/RM) related studies have also resulted in an explosion of MSC-related peer-reviewed literature.

Published studies range from initial characterization of the cell type, isolation, and differentiation potential to more clinically relevant studies concerning in vivo capabilities upon implantation. These studies, although equally important for advancement of

TE/RM cell-based applications, are generally biased towards more clinically relevant goals. With a broader focus on clinical translation of these cells types, the underlying events occurring in MSC-specific differentiation are understudied [10-12]. This dearth of information on MSC differentiation is especially pronounced in newly identified MSC types and may be a limiting factor in the translation of these cells into the clinic [13, 14]. 1

The use of MSC in TE/RM applications is multifaceted. Much of the research in this field is focused on the concept of MSC implantation in vivo, either as part of a scaffolding system designed to augment a damaged organ, or alone as a cell-based therapy. Classical tissue engineering is designed to create the organ ex vivo for implantation in vivo with all required components; essentially creating a mature, functional organ for replacement of the damaged one. Other uses of MSC in TE/RM research include testing a biomaterial’s inductive or growth/maintenance enhancing properties, testing novel inductive factors in vitro, as well as determining essential networks and pathways involved in the differentiation process. Specifically, these studies may provide information on relevant mechanisms of inducing and or suppressing endogenous cell growth in vivo, bypassing the need for MSC implantation altogether.

Ultimately, MSC studies are important for the reasons explained above. They may provide an autologous cell source for ex vivo organ/tissue generation. They may also give clues to the body’s natural ability to heal defects, which could be leveraged to induce in situ tissue and organ repair or re-growth. With these concepts in mind, the need for a more in-depth understanding of MSC differentiation is of extreme importance in the fields of TE/RM.

Bone Tissue Engineering

The field of bone tissue engineering (BTE) is one that would benefit from more in-depth studies of MSC differentiation. Currently, injuries requiring replacement of bone or boney tissue exceed 2.2 million worldwide and present significant costs to healthcare industries [15]. Bone defects result from numerous events including trauma,

2 cancer, birth defects, and fractures resulting from osteoporotic bones, and create significant obstacles in surgical reconstruction [16-19]. Treatment for small bone defects often includes the use of autograft or allograft bone which can have adverse effects [20-

22]. Specifically, autografts (the most commonly used graft material), has limitations such as donor bone supply, donor site morbidity and pain, as well as graft resorption and incomplete union of the graft with native bone [23, 24]. Similar problems of cell infiltration and resorption exist with allografts. Additionally, allografts tend to be mechanically weaker, as well as present a small risk of disease transmission [25]. Large defects are typically considered untreatable with biological substitutes [23]. This lack of an ideal bone graft material has led researchers to investigate alternative bone graft materials through the use of TE/RM applications.

Typical BTE studies focus on the mechanical and physical properties of bone tissue, attempting to create substitutes with appropriate mechanical properties while maintaining correct pore sizes for cellular infiltration and growth [23]. These substitutes are often synthetic in nature and lack a biological component [23]. Failure of these synthetic bone substitutes is often attributed to a lack of biocompatibility, as well as a lack of osteogenic capacity (the ability of the substitute to maintain osteogenic progenitors, precursors, and mature cells), cellular infiltration, and vascularization [26,

27]. Arguably, an approach focused on the cells involved in bone tissue, may yield a more functional and lasting bone substitute.

Previous work demonstrating a dynamic and complicated system of bone cell types involved in bone homeostasis, injury repair, mineral metabolism, and remodeling reveals the importance of cells in bone tissue [28]. The ability of bone to repair itself

3 naturally is well known. Through dynamic and coordinated activity of osteoclasts and osteoblasts, bone is constantly being remodeled [29]. Understanding the coordinated activity of bone cell types and how it relates to bone formation is an important aspect in bone tissue engineering; one which is often overlooked when designing substitute materials with specific mechanical and physical properties. Creating bone substitutes designed to compliment these events may ultimately provide a more successful BTE material for use in bone defects.

Mesenchymal Stem Cells Importance in Bone Tissue Engineering

The usefulness of MSC in BTE is underscored by the biological role of MSC in vivo. MSC found in bone marrow (BMSC), also termed mesenchymal stromal cells, skeletal stem cells, and bone marrow stromal cells, can differentiate down the osteogenic lineage, providing mature osteoblasts for bone deposition and healing purposes [30].

This behavior makes them the ideal candidates for BTE cell-based applications.

MSC were originally isolated from bone marrow [30]. However, populations of cells from other sources display similar multipotential properties. The term MSC is now used more broadly to encompass other multipotential cells with similar capacity to differentiate down other lineages. Alternate sources of MSC include fat, bone marrow, muscle, umbilical cord, amniotic fluid, placenta, dental pulp, tendons, synovial membrane, and skeletal muscle [1-9]. These MSC types commonly express similar cell surface markers to bone marrow MSC. However, little is known about the specific differences in these cells, including whether they follow similar or diverging differentiation patterns [12, 31]. Additionally, the heterogeneity of these cell populations

4 is well known, but how that affects cell behavior and differentiation potential is less well known. Several studies have indicated that within some of the above mentioned MSC types, specific populations display less or more differentiation potential [32]. Ultimately, a better understanding of MSC starting populations as well as diverging or similar differentiation pathways will enable more clinically relevant and controlled studies to be performed on MSC for BTE applications.

Adipose Derived Stem Cells in Bone Tissue Engineering

Adipose derived stem cells (ADSC) are widely studied due to their multipotential capacity, as well as their high clinical relevance. In terms of clinical relevance, ADSC are easy to obtain, represent a readily available source of MSC, and are isolated in high numbers compared to BMSC [33-40]. Having been described in the literature as preadipocytes, stromal cells, processed lipoaspirate cells, multipotential adipose derived stem cells and ADSC, the name ADSC was recommended recently in order to create less confusion in the field [41]. A surprisingly large number of recent studies (compared to the length of time ADSC have been recognized as multipotential stem cells) have focused on ADSC relevance to TE/RM. The clinical implications of such easily obtained cells have led many groups to quickly move forward with in vivo experiments. However, differences between the behavior of ADSC and other MSC types could affect the choice of cells used for therapy and lack of this knowledge could adversely affect clinical outcomes. One example is the wide use of bone morphogenetic proteins (BMP) to modulate osteogenesis [41]. Recent evidence suggests that BMP does not act as aggressively or at all on ADSC differentiating down the osteogenic lineage compared to

5 marrow derived cells [43]. This points out the need to use highly characterized cell sources with controllable and predictable properties. The work described in Chapter 1 and 2 is an attempt to shed more light on the underlying genes and events present in

ADSC undergoing osteogenesis.

MSC Osteogenesis

As mentioned previously, events accompanying ADSC differentiation down the osteogenic lineage are not fully known. However, progression of stem or progenitor cells derived from bone marrow has provided some general information on what is expected of

MSC differentiation to bone. Specifically, the multipotential nature of these cells is of importance in early commitment phases of differentiation. Especially relevant for ADSC is the osteogenic versus adipogenic pathway. Several key transcription factors play a role in these two main pathways; runt-related transcription factor 2 (RUNX2; crucial in osteoblast differentiation) and peroxisome-proliferator activated receptor gamma

(PPARγ; crucial in adipogenic differentiation) [28, 44-49]. Other factors important in osteogenesis include osterix (a transcription factor downstream of RUNX2), BMP, and

Wnt signaling [50, 51].

The transition of MSC to a mature osteoblast has been characterized in defined maturational stages. Although more recent studies suggest the presence of a minimum of seven distinct stages, 3 stages are well characterized and represent an easy to identify sequences of events [52-58]. The three stages are defined as 1) proliferation, 2) extracellular matrix development and maturation (matrix maturational phase), and 3) mineralization. Early proliferation of differentiating MSC is typically associated with

6 expression of histones and proto-oncogenes (c-fos and c-myc); post-proliferatively, cyclins B and E are upregulated [53-55]. During the matrix maturational phase, expression of osteoid or nonmineralized bone matrix genes occurs, and in general, the matrix is prepared or rendered competent for the next phase, mineralization [55]. The last phase, mineralization, occurs concomitant with mature osteoblast markers.

Although MSC osteogenic differentiation has been characterized at some levels, much more work is needed to fully study the range of variability observed in different progenitor, precursor, and stem cell types differentiating to mature osteoblasts. For example, a diverse array of osteoblast gene profiles is observed under different experimental conditions [54, 59-62]. As Jane Aubin states in Chapter 4 of Principal’s of

Bone Biology ―intracellular heterogeneity in expressed gene repertoires may characterize osteoblast development and differentiation‖ [51]. Specifically, the dynamics of MSC differentiation and control of the differentiation process are complex. Heterogeneity may be a result of complex signaling and cell interactions occurring to create microstructural variations throughout the in vivo environment [59].

A range of studies have been designed to address the variation in gene expression and osteoblast-related markers observed under differing experimental conditions [63-69].

However, the majority of studies are designed for BMSC and very few have presented in- depth analysis on ADSC osteogenesis. In Chapter 1 of this work, we show that ADSC induced with dexamethasone (DX) and supplemented with ascorbic acid (aa) and beta- glycerol phosphate (BGP) follow the well known maturational phases proliferation, matrix maturation, and mineralization. However, we also show that mRNA expression of mature osteoblast related markers, including osteocalcin, is relatively low.

Comparison of gene array data presented in Chapter 1 with published data sets for

ADSC osteogenesis may reveal key similarities in highly expressed genes as well as upregulated gene categories at specific time points. These similarities as well as differences may be important in identifying an osteogenic differentiation profile for

ADSC.

Also of interest in Chapter 1 is the concept of identifying an extracellular matrix- related gene expression profile. Specifically, genes with known affiliation, localization, or secretion into the extracellular environment will be identified. An osteogenic ECM- related gene expression profile generated by mapping changes occurring in the ECM- related genes (ECM-rg) of differentiating ADSC may result in a more in-depth understanding of signaling and events associated with ADSC osteogenesis. ECM-rg profiling may filter out intracellular housekeeping gene processes and signaling events.

This will leave extracellular signaling events and secreted proteins (which are often tissue-specific) for analysis and possibly yield more information on how the cells are differentiating.

Ultimately, results from this chapter may underscore both the importance of understanding underlying signaling events during ADSC differentiation, as well as the relation of these events to other MSC differentiation paradigms.

ECM Role in Cell Commitment

Previous studies defining the role of ECM in lineage specification indicate that in addition to the passive structural role of many ECM proteins, some may assist in cell commitment, as well as act as modulators in the differentiation process [70-77].

Specifically, interaction with hyaluronic acid has been shown to effect embryonic stem cells through maintenance of the pluripotent state [78]. Alternatively, some ECM proteins such as fibronectin and collagen have been implicated in the induction of MSC osteogenesis [78]. Several studies have shown that the ECM secreted by cells undergoing differentiation may actually modify or actively participate in feedback mechanisms and signaling during lineage restriction [70, 71, and 76]. Results from

Chapter 1 indicate that genes coding for specific extracellular components may provide a framework for identifying osteogenic maturational stages. Additionally it would be surprising if those same ECM-rg were not involved in the differentiation process itself.

That is, rather than acting as a tool for characterization, ECM-rg may code for proteins which actively participate in and modulate ADSC osteogenesis, and therefore have the potential to be used as tools in TE/RM applications.

In Chapter 2 we describe the effect of cell-secreted ECM on ADSC osteogenesis.

With the understanding that our ADSC cells progress through well known maturational phases of osteogenesis (Chapter 1), we were able to isolate ECM secreted at time points in the various maturational stages in order to create ―maturational stage specific‖ ECM coatings on which to grow our ADSC. Previous studies have examined the effect of tissue specific ECM on MSC undergoing lineage specification [77]. Many of these studies indicate that mature ECM isolated from various tissue types can induce or support differentiation into lineages consistent with the ECM source [77]. For this reason, the working hypothesis for Chapter 2 was that cell-secreted ECM from later maturational stages (mineralization and mature osteoblast stages) would have more of an osteogenic affect on ADSC, thereby supporting more efficient, faster osteogenic differentiation.

Also of interest was the concept of dynamic changes in the ECM protein content, which might have an impact on the differentiation process. Several studies have examined the ECM secreted by BMSC during osteogenesis for a role in modulating differentiation [73-76]. Results are variable between the studies (e.g. one study suggests that ECM secreted early in differentiation has more osteogenic affect; however another study suggests ECM secreted at a midpoint in osteogenesis has a higher osteogenic affect). However, both conclude that the ECM has profound effects on the differentiation process and that more work is needed to define the exact relationship of the ECM to the osteogenic differentiation process.

In most ECM-related studies, a mechanism by which the ECM modulates osteogenic differentiation remains elusive. In Chapter 2, we attempt to shed more light on the effect ECM has on ADSC osteogenesis. By examining pathways and genes upregulated in ECM-modulated osteogenesis, we may be able to begin the process of developing hypotheses on how the ECM can affect the differentiation process and ultimately understand more fully how ADSC differentiate down the osteogenic lineage.

Dermatopontin a Extracellular Matrix Protein Expressed During Osteogenesis

The complex nature of ECM coupled with a lack of understanding on how ADSC differentiate down the osteogenic lineage make discerning the mechanisms of ECM enhanced differentiation observed in Chapter 2 difficult. However, ECM proteins of interest can be identified through analysis of ECM-related genes highly expressed during osteogenesis (Chapter 2).

Much of the published work concerning the effect of individual ECM components on osteogenesis has centered on the more abundant matrix proteins including collagen and fibronectin as well as noncollagenous ECM components common in mineralized tissue including hydroxyapatite [78]. Also commonly observed are the influences of synthetic ECM-mimicking scaffolds as well as various growth factors [15]. However, small ECM components, often referred to as matricellular proteins, may have equally important roles in modulating the differentiation process and are much less studied [79].

Matricellular proteins are insoluble ECM components, which do not typically play a role in structure and stabilization of cells and tissues or have dual roles both in structure and in cell related processes such as adherence, signaling, growth factor binding, etc [80]. A focus on the lesser-known ECM components present during ADSC osteogenesis may ultimately reveal key proteins involved in the differentiation process.

One ECM-rg highly expressed during osteogenesis is dermatopontin (DPT). A 22 kDa tyrosine-rich matrix protein, dermatopontin is found at high levels in demineralized bone matrix [81-83]. Very few studies have been performed to identify the specific importance of dermatopontin in various tissues. Some of the identified roles of dermatopontin include mediation of cell adhesion, a communication link between cells and ECM, enhancement of transforming growth factor β activity, inhibiting of cell proliferation, collagen fibril formation, as well as BMP binding [83-87]. Of interest in osteogenesis may be DPT’s role in BMP binding, a report of DPT being a downstream target of the vitamin D receptor (VDR), as well as localization in mineralizing tissues

[82, 83]. In Chapter 3, we investigate the effect of DPT on ADSC osteogenesis.

MATERIALS AND METHODS

Adipose Derived Stem Cell Isolation, Culture, Differentiation, and Characterization

Adipose Derived Stem Cell Isolation and Culture

Adipose tissue was obtained from female patients undergoing elective abdominoplasty under a protocol approved by the Wake Forest University School of

Medicine Institutional Review Board (IRB). Adipose derived stem cells were isolated as previously described [40]. Briefly, fat tissue was washed 3x with sterile phosphate- buffered saline (PBS) containing 5% Antibiotic/ Antimycotic (A/A) and minced with sterile scissors. Tissue was digested with an equal volume of 0.075% Collagenase Type I

(Worthington Biochemical Corporation Lakewood, NJ) suspended in PBS containing 2%

A/A. The sample was pipetted up and down several times to further facilitate digestion.

o The digest was incubated for 30 minutes at 37 C, 5% CO2. The digest was neutralized by addition of Dulbecco’s Modified Eagle Medium (DMEM) high glucose (Gibco,

Invitrogen) supplemented with 10% heat inactivated fetal bovine serum (FBS) (Gibco).

The digested tissue was transferred to 50mL conical tubes and centrifuged 3000rpm for 5 minutes. Supernatant and floating adipocytes were aspirated leaving the cell pellet. The pellet containing the stromal vascular fraction (SVF) was resuspended in adipose maintenance media (AMM); DMEM high glucose, 10% FBS, 1% A/A (Gibco) and passed through 100µm and 40µm cell strainers before plating onto 150mm untreated tissue culture plates (TCP) (Appendix 1). Plated cells were selected for the plastic adherent population within the SVF, thereby enriching the population for adipose progenitor cells or adipose derived stem cells. Specifically, following straining and

12 plating, cells were allowed to adhere for 24 hours. Following the 24 hours, nonadherent cells were washed off with PBS and new medium was added to the cells. Flow cytometry was performed to confirm markers consistent with previously characterized

ADSC populations [33, 36, 28, 40] (Appendix 2). ADSC were maintained in AMM at

o 37 C, 5% CO2 and were labeled ADSC line #1. Subsequent experiments were performed using cells from passage 2-4. Two additional cells lines were established and were derived from different donors. ADSC cell line #2 was used for the majority of experiments. Confirmation experiments were performed on lines #1 and #3. Unless otherwise noted, data represents experiments performed on ADSC line #2.

Osteogenic Differentiation

Bone differentiation of ADSC was performed according to the method of Zuk et al. with minor adjustments [40]. Briefly, stem cells were plated onto tissue culture dishes at 3000 cells/cm2. Cells underwent a ―preinduction‖ growth period of approximately 2 days until they reached ~70% confluence in AMM. Bone media (BM) consisting of

DMEM low-glucose (Gibco, Invitrogen) supplemented with 10% FBS, 1% AA, and osteogenic supplements (OS) (100 nM dexamethasone (DX; Sigma), 10mM β- glycerophosphate (BGP; Calbiochem), 0.05 mM ascorbic acid-2-phosphate (aa; Sigma)) was added following the preinduction growth period. Media was changed every 3-4 days.

Characterization of Osteogenic Phenotype

Following osteogenic differentiation, cultures were subjected to characterization in order to confirm differentiation down the osteogenic lineage, as well as to illustrate the robustness and efficiency of differentiation.

Alkaline Phosphatase Assay: Alkaline phosphatase (AP), an enzyme expressed by cells, is a marker of osteogenic lineage specification. Cells were assayed for AP at the approximated midpoint in differentiation (typically days 15-18) [40]. Briefly, media was aspirated and 0.15% Triton-X-100 added to each dish. Plates were incubated with shaking for 30 minutes followed by addition of p-nitrophenyl phosphate (PNPP) to each dish. Following addition of PNPP, plates were incubated 30 minutes in the dark at room temperature. Subsequent addition of 3M NaOH stopped the reaction. Absorbencies were read at 405nm.

Alkaline Phosphatase Stain: AP was visualized with staining in order to observe uniformity of the cells in relationship to AP deposition. Cultures were stained for AP at similar time points as the previously described AP assay. Media was removed and cultures washed 2x with PBS. Cells were fixed in 4% paraformaldehyde for 2 minutes.

Cells were rinsed with PBS 3x. Staining solution (0.25% Napthol AS-MX phosphate alkaline solution (Sigma), Fast Violet B salt (Sigma) in ultrapure H2O) was added with gentle shaking for 30 minutes.

Alizarin Red S Assay: Late osteoblast differentiation is marked by significant increases in deposition of calcium when cells are cultured in the presence of a phosphate source. Calcium deposition can be measured using the Alizarin Red S assay. The assay was performed on differentiating cultures and, in the absence of dystrophic

14 mineralization, would be expected to stain for calcium only when terminally differentiated osteoblasts are present. Briefly, cultures were washed with cold phosphate buffered saline (PBS) and fixed in 70% ethanol (EtOH). Calcium was stained with 0.5%

Alizarin Red S (Sigma) at pH 4.1- 4.3, incubated for 3 minutes, and washed with water and 70% EtOH. Matrix mineralization was quantified in relation to other cultures by extraction of Alizarin Red S with 100mM cetylpyridinium chloride (Sigma) at room temperature and absorbencies read at 540nm.

Human Osteocalcin Enzyme Linked Immosorbant Assay (ELISA) (GENWAY): In cell-mediated or non-dystrophic mineralizing cultures undergoing osteogenesis, calcium deposition should occur concomitantly with mRNA expression of and deposition of bone matrix protein osteocalcin (bone gamma carboxyglutamic acid protein, BGLAP).

Terminal differentiation of osteogenic cultures should be marked by increases in osteocalcin both in protein and messenger RNA (mRNA) expression. Protein secretion of osteocalcin into the media was assayed using GENWAY’s hOST ELISA assay.

Briefly, 24 hours prior to media collection, cells were switched to serum-free BM. Media was collected at specific time points and stored at -80oC until use. For protein quantification, 25µl calibrator, controls, and samples were pipetted into appropriate wells. 100µl anti-OST-HRP conjugate was added to wells and incubated for 2 hours at room temperature. Wells were washed 3x with included wash solution followed by addition of chromogenic solution. Plates were incubated 30 minutes at room temperature in the dark. Stop solution was added and absorbencies read at 450nm with the reference filter set at 630nm.

Quantitative RT-PCR (QPCR) for Osteogenic Related Gene Expression: Total

RNA was extracted from cells in culture at various time points using Perfect Pure RNA

Fibrous Tissue Kit (for heavily mineralized cultures) and Cell Culture Kit according to the manufacturer’s instructions (5Prime). Extracted RNA was quantified using Thermo

Scientific Nanodrop and reverse-transcribed into cDNA using oligo (dT) primers and

SuperScript II (Invitrogen). Taqman Universal PCR Master Mix Kit (Applied

Biosystems) was used with 0.5µg total RNA for each reaction. Reactions were performed using Applied Biosystems ABI 7300 Real-Time PCR System. Relative expression of the genes of interest were determined following normalization to the level of a housekeeping gene, 18s RNA, and according to the method of Livak and Schmittgen

[88] (Table I).

Gene Name or Applied Relevance to Bone/ Encoded Protein Symbol Biosystems Relevance to Bone 18s RNA Hs03003631_g1 Housekeeping gene with stable expression PPARУ Hs00234592_m1 Important in adipocyte differentiation, expression decreases during osteogenesis BGLAP Hs00609452_g1 Bone extracellular matrix protein, deposited (osteocalcin) by mature osteoblasts RUNX2 Hs01047978_m1 Transcription factor associated with osteogenesis Alkaline Hs01029144_m1 Enzyme produced by mature osteoprogenitors; Phosphatase peaks in expression at the midpoint in differentiation DLX5 Hs00193291_m1 Expressed during osteogenesis Osteoprotegerin Hs00900358_m1 Expressed in osteoblasts, inhibitory factor for osteoclastogenesis ATF4 Hs00909569_g1 Transcriptional regulator of osteoblast genes, regulates osteocalcin expression SP7 (osterix) Hs00541729_m1 Transcription factor downstream of RUNX2, important for full osteoblast differentiation *TAZ Hs00210007_m1 Co-activates RUNX2, represses PPARγ [89] Osteopontin (SPP1) Hs00960641_m1 Role in the maintenance of bone, expressed in two peaks during osteogenesis Osteomodulin Hs00192325_m1 RGD-containing glycoprotein found in bone extracellular matrix *Osteocrin Hs00898258_m1 Secreted protein; modulates bone growth [90] *Wnt5A Hs00998537_m1 Highly enriched and significant in ADSC cells used in these experiments; may be associated with ADSC osteogenesis [91] *Dermatopontin Hs00355356_m1 Highly enriched and significant in ADSC cells at day 16, extracellular matrix protein in bone, downstream target of Vitamin D [82, 83] *ROR2 Hs00896176_m1 Receptor for Wnt5A [92] *FKBP5 Hs01561006_m1 Binds FK506 (an inhibitor of bone formation in vivo [66] *CPM Hs00266395_m1 Observed as highly expressed during osteogenesis[66, 93] *Sortilin 1 Hs00361747_m1 Sequesters LPL an inhibitor of mineralization [94] *Cadherin 11, Hs00901475_m1 Commitment to osteogenesis in MSC [95] type 2 *APOD Hs00155794_m1 High expression in Experimental 1 *GRIA1 Hs00181348_m1 High expression in Experimental 1 Table I. ADSC osteogenesis-related genes identified and screened for with QPCR. Genes of interest listed with primer used for QPCR assays and relevance to osteogenesis. The * denotes genes identified through gene array analysis

ECM Isolation and Preparation

ECM was isolated from ADSCs undergoing lineage specification at specific time points along the differentiation pathway. Isolated ECM was used for two purposes: reseeding experiments in order to determine the ECM’s osteogenic capacity at specific time points in the differentiation as well as characterization and analysis of ECM composition.

Characterization and Analysis of ECM

ECM isolated from time days 11 and 16 in the differentiation process was used for characterization of specific ECM proteins. Methods and results from ECM characterization experiments are included in Appendix 3.

Isolation of ECM for Reseeding Experiments

ECM was isolated from days 3, 6, 9, 12, 15, 18, 21, 24, and 27 in the osteogenic differentiation process using protocols described below.

Decellularization of Cells in Culture: Decellularization of cultures (cells removed leaving ECM intact on dishes) was performed using two methods: Sigma’s

Acellularization Kit according to the manufacturer’s instructions (Sigma discontinued the kit midway through the project), and a detergent lysis/decellularization protocol, both briefly described here.

Sigma kit: Briefly, cultures were washed 2x with PBS. Sterile filtered acellularization buffer (acell buffer) was added to the dish at the specified concentration and allowed to incubate. Once cells were removed, ECM coated dishes were incubated with 100µg DNAse I (5Prime) and 100µg RNAse A (5Prime) for 1 hour at 37oC. ECM

18 coated dishes were then washed 2x with PBS and stored in PBS spiked with 1% A/A at

4oC up to one week prior to being re-seeded with fresh ADSC.

Detergent Lysis: Detergent lysis and removal of cellular components was performed according to [75,76] and is briefly described here. Cultures were washed 2x with PBS. PBS supplemented with 0.5% TritonX-100 and 20mM NH4OH was added gently and allowed to incubate approximately 5 minutes at 37oC. After visual confirmation of cell removal, ECM coated dishes were incubated with 100µg DNAse I

(5Prime) and 100µg RNAse A (5Prime) for 1 hour at 37oC. ECM coated dishes were washed 2x PBS and stored as described above until use.

Gene Arrays

Prior to and during osteogenesis of cells in culture, gene array analysis was used to assess genes, networks, pathways, and gene categories associated with undifferentiated

ADSCs as well as ADSCs undergoing osteogenic lineage specification. Patterns observed at time points during the differentiation process were compared to previously identified patterns associated with mesenchymal stem cell (MSC) mediated osteogenesis.

Additionally, gene categories and patterns were compared between time points as well as experimental groups in order to determine stages of osteogenesis as well as enhancement of osteogenic phenotype of cells in culture.

Microarray Experimental Design: Microarrays were performed on ADSCs in culture at a variety of time points and experimental conditions (Figure 1). Gene array samples and time points included: ADSC on TCP undifferentiated (day 0), ADSC plus

OS (days 3, 10, 16, 21) referred to as the Control Group, ADSC on day 16 ECM plus OS

(days 3, 10, 16, 21) referred to as Experimental 1 Group, and ADSC on day 11 ECM plus

OS (days 3, 10, 16, 21) referred to as Experimental 2 Group. Gene arrays were performed using ADSC Line #2 with three replicates per time point. RNA was isolated using a 5Prime RNA isolation kit and arrays performed using Affymetrix GeneChip

Human Exon 1.0 ST Array (Affymetrix Inc.) (exon arrays). Hybridization was performed per Affymetrix protocols by the David H. Murdock Research Institute

(DHMRI).

Figure1. Gene array experimental design. Arrays were performed on ADSC Line #2. Three replicates were performed for each time point under each of the specified experimental conditions. Confirmation experiments were carried out in Line #1, #2, and #3.

Microarray Analysis: Array analysis was performed using an assortment of software and programs (Figure 2). Raw data files (CEL files) were obtained from

DHMRI and imported into Affymetrix Expression Console (AEC). AEC was used to generate CHP files. CHP files were normalized to median CHP intensity. Background correction, normalization, and probe summarization were performed using Robust

Multichip Averaging RMA [96]. Data was analyzed for quality control (QC) (Figure 3).

Normalized intensity values were mapped to gene summarization and annotation using

AEC and uploaded into Excel based add-on, BRB array tools. Analyses were performed

21 using BRB-ArrayTools developed by Dr. Richard Simon and BRB-ArrayTools

Development Team [97]. Differentially expressed genes were detected between groups and time points using t-test adjusted with Benjamini and Hochburg False Discovery Rate

(FDR) method [98].

Figure 2. Gene array analysis workflow.

Raw Data

RMA-Normalized Data

Figure 3. Histogram comparing raw data to RMA-normalized data. Results used for QC analysis of gene array data set.

Between group comparisons were used to determine shared pathways and gene categories. Tracking gene changes throughout the differentiation process enabled determination of patterns associated with osteogenesis shared both between groups as well as uniquely expressed in one or more group. Highly enriched and significant genes were filtered by setting specific criteria including p values ≤ 0.01 and p values ≤ 0.05 and log ratios (LR) ± 1 and LR ± 0.6. By tracking significant and enriched gene changes identified with the above parameters, a ―differentiation‖ specific expression profile could be created for each of the three groups of time points (Control Group; Experimental 1

Group; Experimental 2 Group). The differentiation specific expression profile tracked genes that were significant and enriched in at least one time point comparison within the specified group. Additionally, comparisons of group associated time points back to day 0

(the undifferentiated state), allowed for tracking of ―overall progress‖ from a stem cell state down the osteogenic lineage. Finally, across ―treatment‖ group comparisons

(comparison of similar time points in Controls, Experimental 1, and Experimental 2) allowed for analysis of how ECM affected cell differentiation.

Changes in gene expression compared as described above were tracked using a variety of software programs. Heat maps generated using Cluster 3.0 [99] and TreeView

[100] allowed for visualization of differentiation specific expression profiles between groups. Venn diagrams were generated from Venny [101]. Gene annotation and ontology were searched using The Database for Annotation, Visualization, and Integrated

Discovery (DAVID) [102, 103] as well as SOURCE software [104]. Pathway and gene networks were visualized using KEGG pathway analysis [102, 103]. Timepoints were compared and contrasted using STEM software [105, 106] ECM related genes were 24 identified using both SOURCE and DAVID software. Individual gene intensities were compared across groups and time points using GraphPad Prism 5 (GraphPad Software,

Inc.).

Lentiviral-Mediated Overexpression of Dermatopontin

Stable overexpression of DPT was achieved through lentiviral-mediated overexpression. ADSC overexpressing DPT were induced to differentiate on TCP and used for two separate downstream analyses: analysis of overexpression of DPT in cells induced to differentiate on TCP alone, as well as analysis of cells re-seeded onto ECM from ADSC overexpressing DPT.

Cell Culture: Human Embryonic Kidney 293T cells (HEK293T) were obtained as a gift from Dr. Colin Bishop. Cells were maintained in DMEM (Gibco, Invitrogen) supplemented with 10% FBS, 1% L-glutamine, and 1% P/S.

Construction of Recombinant Lentivirus: A clone containing the DPT gene was obtained from Invitrogen (MGC Full Length (IRAT) Human Dermatopontin Clone) in the form of plasmid DNA contained in a bacterial carrier (pCMV-SPORT6). Plasmid

DNA was expanded through bacterial culture and subsequent plasmid isolation (Qiagen,

Plasmid Maxi Prep). The DPT gene was sequenced to ensure the expected sequence (T7 and SP6 primers a gift from Dr. Jan Rohozinski). The lentivirus vector, pLVX-EFLα-

IRES-ZsGreen1, was obtained from Clontech. Lentivirus Dermatopontin Green

Fluorescent Vector Construct (Lenti_DPT) was created through restriction digests (EcoRI

& XbaI, New England BioLabs) that cut the DPT gene out of the plasmid vector and subsequently ligated into the cut Lenti vector using T4 DNA Ligase (New England

BioLabs) (Figure 4). Lenti_DPT construct was transformed into TOP10 E.coli cells and expanded through bacterial culture and subsequent plasmid isolation.

B XbaI Cut Site

EcoRI Cut Site

AATTC Dermatopontin Gene T G AGATC (EcoRI Sticky End) (XbaI Sticky End)

A) Plasmid containing dermatopontin gene clone (vector map use approved by NIH Mammalian Gene Consortium). B) Cut sites for isolation of gene from plasmid and generation of sticky ends are indicated in red and blue. C) Resulting digested fragment contains dermatopontin gene with EcoRI and XbaI sticky ends.

E CGGTGAATTC CTCGAGACTA GTTCTAGAGC GGCCGCGGAT

GCCACTTAAG GAGCTCTGAT CAAGATCTCG CCGGCGCCTA

EcoRI Cut Site XbaI Cut Site

XbaI Sticky End

EcoRI Sticky End

D) Lentiviral plasmid vector containing IRES and ZsGreen with cut sites indicated (E).

F Digested dermatopontin + Digested LentiVector

(T4 DNA Ligase Reaction)

F) Ligation reaction of DPT gene with pLVX lenti vector. G) Resulting ligated region containing DPT gene inside of the lentivector.

Figure 4. Design and construction of Lenti_DPT construct.

Transfection of HEK293T Cells to Produce Virus: HEK293T cells were plated onto gelatin coated dishes at a density of 1.3x104cells/cm2 and allowed to grow overnight to approximately 80% confluence. Cells were transfected using FuGene HD (Roche) according to manufacturer’s instructions. Briefly, packaging vector (psPAX2), envelope vector (pMD2.G) (packaging and envelope vectors: gifts from Dr. Colin Bishop) and

Lenti_DPT or Lenti_vector alone (control without gene insert), were added to DMEM unsupplemented at a ratio of 1:2:3 (packaging : envelope : gene insert), respectively.

FuGene HD was added to DNA at a ratio of 4:1 (Fugene: DNA). The DNA/FuGene HD mixture was incubated 20 minutes. Prior to dropwise addition of DNA/FuGene HD mix, medium on HEK293T cells was changed to HEK293T medium minus antibiotic (P/S).

Cells were maintained in transfection medium overnight and then changed to fresh medium. Transfection efficiency was monitored via fluorescent microscope (Zeiss,

Axiovert). Viral supernatants were collected 48 and 72 hours post transfection, combined, filtered at 0.45µm, and stored at -80oC until further use.

Infection of ADSCs with Viral Supernatants: ADSC were plated at a density of 1 x 104 cells/cm2 and allowed to grow overnight to approximately 60 – 70% confluence.

Cells underwent multiple infections with virus containing medium at a ratio of 1:5 (virus medium: AMM) in the presence of 8ng/mL polybrene (1,5-dimethyl-1,5- diazaundecamethylene polymethobromide, hexadimethrine bromide, Sigma).

Progressive increases in infected cells (as monitored through fluorescence) were observed. After a third infection, cells were sorted using ZsGreen fluorescence

(excitation 493nm; emission 505nm) as the selective agent. QPCR was used to determine increased DPT mRNA expression in the positive ZsGreen sorted cells versus the cells

30 negative for ZsGreen. Subsequent experiments were performed on ZsGreen fluorescing cells only. All subsequent experiments included control cells in parallel that were infected with Lenti Vector alone without DPT gene insert.

Overexpressed DPT Affect on Osteogenesis

ADSC overexpressing DPT were used for several experiments in order to determine the affect of high DPT protein expression on osteogenesis.

Overexpression of DPT in Cultures Seeded onto TCP: ADSC overexpressing

DPT (ADSC_DPT) were seeded onto TCP and induced to differentiate as described previously. At time points (days 3, 10, 16, and 21) in the differentiation process, media and RNA were collected for Western Blot analysis to track stable DPT overexpression and QPCR analysis of bone related markers. At day 21, Alizarin Red stain was used to visualize calcium deposition. Immunofluorescence was also used to compare DPT expression in Lenti Vector infected cells and Lenti-DPT infected cells to ensure stable overexpression of DPT.

DPT_ECM Isolation and Culture: The assumption that DPT is overexpressed as a secreted ECM protein was tested by isolating ECM from day 16 in

ADSC_DPT cells induced to differentiate as previously described. Undifferentiated

ADSC were then seeded onto the DPT_ECM and induced to differentiate. Western blot,

QPCR, Alizarin Red, and Immunofluorescence were used as described above to access

ADSC differentiation on DPT_ECM.

Western Blot: Cell lysates collected from ADSC_DPT undergoing osteogenesis was used for confirmation of overexpression of DPT. Cell lysates containing secreted

31 protein was loaded onto SDS-PAGE, Tris-HCl gels and separated by relative size.

Separated proteins were transferred to Immobilon P membranes (Millipore Corporation) and membranes probed with primary antibody for DPT (Novus Biologicals) and GAPDH

(loading control; AbCam). Secondary horseradish peroxidase-conjugated antibodies

(Roche Molecular Biochemicals) were used and protein bands visualized using a chemiluminescence detection system (ECL lit; Amersham).

Statistical Analysis

Quantitative data from non-gene array experiments as well as single gene comparisons from gene arrays were subjected to statistical analysis. Data obtained from

QPCR, ELISA, alkaline phosphates assays, and alizarin red assays were all analyzed.

All replicate data was averaged and expressed as mean +/- standard deviation (SD).

These data were compared between different treatment groups as well as against different time points within the same groups. GraphPad Prism software was used for standard t- tests as well as analysis of variance (ANOVA) to determine significance at p ≤ 0.05.

Specifically, analysis of multiple experimental groups with multiple time points

(Controls, Experimental 1, and Experimental 2) was performed using Two Way ANOVA with Bonferroni’s post hoc analysis to compare replicate means of individual experimental group time points to the same time point control. Multiple group comparisons with only one time point for comparison were analyzed using One Way

ANOVA with Tukey’s Multiple Comparison post hoc analysis. Single group comparisons of multiple time points (e.g. Control day 0, 3, 10, 16, and 21) were

32 compared using One Way ANOVA with Tukey’s Multiple Comparison post hoc analysis.

Sample size was determined through power calculations based on preliminary data.

CHAPTER ONE

CREATING AN OSTEOGENIC DIFFERENTIATION EXPRESSION PROFILE FOR

HUMAN ADIPOSE DERIVED STEM CELLS USING WHOLE TRANSCRIPTOME

PROFILING AND ECM-RELATED GENE EXPRESSION PROFILING

The osteogenic potential of ADSC isolated and cultured in vitro has been established [33-41]. However, published studies reveal degrees of variation between

ADSC line’s ability to differentiate down the osteogenic lineage [11]. Some of the variation observed may be accounted for with the patient’s age and sex. Additionally, the method of ADSC isolation as well as whether undifferentiated cells were subjected to sorting based on MSC marker expression may affect osteogenic potential of these cells

[107, 28]. Unfortunately, stringent analysis of what affects ADSC differentiation potential has not been performed. Also lacking in published studies are in-depth analyses of the mechanisms and important genes involved in ADSC osteogenic differentiation.

We present here, a detailed profile of ADSC undergoing osteogenesis (dexamethasone induction and ascorbic acid, beta-glycerol phosphate supplementation). We also provide an alternate method of assessing ADSC osteogenic differentiation and osteogenic maturational phase determination through profiling extracellular matrix related gene expression during osteogenesis.

Osteogenic Potential of ADSC

With commonly used osteogenic assessment assays, we determined that ADSCs isolated for these experiments were capable of undergoing osteogenic lineage specification. These assays were performed prior to gene array hybridization.

ADSCs isolated as described above were induced to differentiate along the osteogenic lineage. Osteogenic potential of the ADSC lines was assessed through verification of several osteogenesis related markers. Runt-related transcription factor 2

(RUNX2), a member of the runt homology domain transcription factor family (also called Cbfa 1 in earlier publications), is vital in bone development, both in vivo and in osteogenic cultures induced in vitro [45-49]. Expression of RUNX2 during osteogenesis of ADSC, as well as any type of MSC osteogenesis, would be expected to increase as cells undergo osteogenic lineage specification [44, 48]. All ADSC cell lines used in these experiments increase progressively in the expression of RUNX2 mRNA, as verified through QPCR, during dexamethasone (DX) induced osteogenic differentiation (Figure

1).

Figure 1. Osteogenic transcription factor RUNX2 mRNA expression increases with time in culture during BM induced osteogenesis. RUNX2 mRNA expression quantified relative to levels of housekeeping gene 18s RNA. Points represent mean fold change of 4 replicates normalized to Day 0 RUNX2 expression. Figure represents ADSC line #2; results were comparable in lines 1 & 3. Error bars are displayed as standard deviation (SD).

Alkaline phosphatase (ALP) is often used as an indication that cells are undergoing osteogenic lineage specification [52]. The ALP enzyme is an important component of osteogenesis, which typically peaks in expression prior to mineralization

[52]. High levels of enzyme activity as well as a peak in mRNA expression were observed in all ADSC cells lines undergoing DX induced osteogenic differentiation

(Figure 2).

* *

Figure 2. Alkaline phosphatase enzyme activity and mRNA levels increase with time in culture during BM induced osteogenic differentiation. A) ALP activity relative to Day 0 presented as mean fold change increases versus Day 0 undifferentiated cells. AMM group refers to cells in maintenance medium at specified time points; BM group refers to cells in bone medium at specified time points. Error bars are displayed with SD. Statistical significance was determined with a two way ANOVA and Bonferroni’s post hoc analysis. Significance for each BM group is denoted with * and equals p≤0.05 compared to the same time point in AMM group. Each group consisted of 4 replicates. B) ALP mRNA expression quantified relative to levels of housekeeping gene 18s RNA. Points represent mean fold change of 4 replicates normalized to Day 0. Error bars are displayed with SD. Figures represent ADSC line #2; results were comparable in lines 1 & 3. 37

One of the most commonly used markers of osteogenic differentiation is the ability of differentiating cells to deposit a mineralized matrix when cultured in the presence of a mineral inducing medium [108, 109]. However, the widespread use of mineralization assays alone (Alizarin Red to stain calcium and Von Kossa to stain

Phosphates) may be less instructive on determining whether the cells have truly differentiated [108, 109]. In the absence of more descriptive mineralization analyses such as Fourier Transform Infrared Spectroscopy (FTIR) or X-Ray Diffraction (XRD), mineralization should be assessed for the occurrence concomitant with expression of mature osteoblast related genes, specifically osteocalcin (OCN) [108]. ADSCs used in these studies mineralized robustly when cultured in the presence of BM (Figure 3) with the exception of ADSC Line #1 which underwent mineralization to a lesser degree than

Lines #2, and #3. Specifically, mineralization was not evident in cultures until approximately day 20 in Lines #2 and 3 and day 25 in Line #1. However, calcium deposition was robust at day 27 and beyond. In comparison, expression of osteocalcin mRNA was low throughout differentiation with a small but significant peak in mRNA expression at day 21. Osteocalcin levels secreted into the medium however, showed marked and significant increases in osteocalcin beginning at day 21 and continuing through day 30 (Figure 4). ADSC Line # 1 demonstrated reduced osteocalcin mRNA expression levels as well as secreted protein levels similar to reduction in mineralization when compared to the other two ADSC lines.

Relative Calcium Deposition A 40 AMM * BM 30

Fold Change Fold 10 * 0

BM AMM ADSC Media Treatment Days 16, 21, 27 B

Figure 3. ADSC induced to differentiate deposit calcium in the form of a mineralized matrix; ADSC in maintenance medium do not. A) Calcium deposition measured through Alizarin Red S quantification presented as mean fold change relative to day 10. AMM group refers to cells in maintenance medium at specified time points; BM group refers to cells in bone medium at specified time points. Error bars are displayed with SD. Statistical significance was determined with a two way ANOVA and Bonferroni’s post hoc analysis. Significance for each BM group is denoted with * and equals p≤0.05 compared to the same time point in AMM group. Each group consisted of 4 replicates. B) Alizarin Red S stain for calcium deposition at specific time points in BM and AMM. Photos are representative of 6 replicates for each time point. Figures represent ADSC Line #2. Results were comparable in Line #3. However, Line #1 exhibited significantly less calcium deposition.

A *

Figure 4. Mature osteoblast marker osteocalcin mRNA and protein levels are significantly increased by day 21 in differentiation. A) OCN mRNA expression quantified relative to levels of housekeeping gene 18s RNA. Points represent mean fold change of 4 replicates normalized to Day 0. Error bars are displayed with SD. Statistical significance was determined with one way ANOVA and Dunnet’s post hoc analysis for comparison of significance to Day 0 control. Significance was denoted with a *; p≤0.05. B) Levels of OCN secreted into medium during differentiation expressed as ng/mL media at specified time points. Bars represent mean concentration for each of the 4 replicates. Error bars were displayed with SD. Statistical significance was determined with one way ANOVA and Tukey’s post hoc analysis for comparison of significance across all groups. Significance was denoted with * and p≤0.05. All groups were significant in comparison to one another with the exception of Day 16 to Day 0. Figures represent ADSC Line #2. Results were comparable in Line #3. However, Line #1 exhibited no significant increases in osteocalcin mRNA expression as well as protein levels when compared to day 0.

Gene Array Analysis of ADSC-Mediated Osteogenesis

ADSCs have been identified as an extremely important multipotential cell for use in regenerative medicine applications [44]. As a readily available, abundant source of stem cells, ADSC may have applicability for many diverse fields of use including bone specific applications [34]. Many groups have reported the osteogenic capacity of ADSC both in vivo and in vitro [33-44]. However, less widely reported are in-depth analyses of gene level changes occurring across the differentiation process of these cells [66, 68, 69].

Differences between a more commonly used cell type in bone differentiation, bone marrow stem cells (BMSC), and ADSC have been published. However, the specific mechanisms that drive ADSC differentiation are largely unknown [11].

Comparing Gene Expression at Specific Time Points

To characterize gene expression changes occurring as osteogenesis progressed,

RNA was collected at days 0 (undifferentiated), 3, 10, 16, and 21 and exon arrays performed on ADSC Line #2. Individual gene confirmation experiments were performed on all cell lines (Lines 1, 2, 3). An osteogenic differentiation-specific profile was generated through comparisons of increasing time points to day 0 (Figure 5). Time point comparisons revealed specific clusters of genes expressed as differentiation progressed that fit with previously recorded maturational stages of differentiating MSC [55] (Table

I). Specifically, cells at day 3 in osteogenesis expressed genes which associated with the following ontology categories: cell cycle, M phase, nuclear division as well as bone morphogenic protein (BMP) signaling pathway, transforming growth factor beta (TGFβ)

41 receptor, and small mothers against decapentaplegic (SMAD) proteins. Day 10 cells displayed similar expression of cell cycle related genes as well as cell-cell signaling, angiogenesis, and cytokine related gene categories. These two timepoints correspond with proliferative maturational stage gene expression as mentioned previously where cells undergo a proliferative stage prior to committing to the osteogenic lineage.

However, expression of early osteogenic signaling associated genes and pathways is present in order to ―jump-start‖ the system [55]. Following the proliferative stage, cells undergo a matrix maturation stage followed by matrix mineralization [55]. An increase in matrix associated gene expression was observed in day 16 cells followed by genes associated with the skeletal system development category at day 21.

The list of genes up-regulated in the ontology category skeletal system development and expressed at day 21 provides some insight into bone-related genes highly and significantly enriched in ADSC cell Line #2 during osteogenesis (Table II).

Of particular note is AE binding protein, which encodes a gene expressed in osteoblasts and fat and may enhance proliferation while suppressing adipocyte differentiation [110].

This particular gene increases over the differentiation period, and is expressed highest at day 21. WW domain containing transcription regulator 1, also known as TAZ, co- activates RUNX2 dependant gene transcription while repressing PPARγ dependant gene transcription and is also increasingly expressed throughout differentiation peaking at day

21 [89]. Activin A receptor IIA, BMP receptor type IB, chemokine-like receptor 1, frizzled-related protein, glycoprotein (transmembrane) nmb, all IGF related genes, osteocrin, tuftelin, immunoglobulin superfamily member 10, vitamin D receptor, and stanniocalcin may also be important in ADSC-related osteogenesis observed in Line #2

42 for high expression at day 21 and possible influence on osteogenesis [90, 110-117].

Receptor tyrosine kinase orphan-like receptor 2 may be of specific interest in ADSC Line

#2 mediated osteogenesis for potential involvement in regulation of Wnt5A (a Wnt pathway published for specific importance in ADSC osteogenic differentiation) [92].

Day 3 Day 10 Day 16 Day 21

Figure 5. Hierarchical gene clustering of time points in differentiation. Heat map indicating high (red) or low (green) expression of genes clustered on the basis of similar expression. Genes included had a minimum of p≤0.01 and LR±1 when compared to day 0. Clades numbered on left indicate gene ontologies mapped to that region.

Clade Ontology Categories 1 Secreted (days 10, 16, 21) Extracellular Glycoprotein Signal Peptide 2 Signal (days 16 & 21) Extracellular Region Skeletal System Dev. 3 Cell-cell signaling (day 10) Extracellular Region Angiogenesis Cytokine Activity 4 Transmembrane receptor (day 3) Signal BMP signaling pathway TGF beta receptor signaling SMAD protein 5 M Phase (day 3 & 10) Cell cycle phase

Table I. Gene ontology categories mapped to specific clades observed in heat map expression. Clades labeled with days corresponding to red or high expression in parentheses below. Categories included met criteria of adjusted p≤0.05 and DAVID enrichment score ≥ 2.

ID Gene Name 8132557 AE binding protein 1 7926679 KIAA1217 8091422 WW domain containing transcription regulator 1 8045587 activin A receptor, type IIA 7898693 alkaline phosphatase, liver/bone/kidney 8096511 bone morphogenetic protein receptor, type IB 7919815 cathepsin K 7966089 chemokine-like receptor 1 8174513 chordin-like 1 7918064 collagen, type XI, alpha 1 8057506 frizzled-related protein 8131844 glycoprotein (transmembrane) nmb 8106252 hexosaminidase B (beta polypeptide) 8091537 immunoglobulin superfamily, member 10 7965873 insulin-like growth factor 1 (somatomedin C) 7937772 insulin-like growth factor 2 (somatomedin A) 8058857 insulin-like growth factor binding protein 5 7995681 matrix metallopeptidase 2 8084814 Osteocrin 8095080 platelet-derived growth factor receptor, alpha polypeptide 7906954 pre-B-cell leukemia homeobox 1 7908924 proline/arginine-rich end leucine-rich repeat protein 8155898 proprotein convertase subtilisin/kexin type 5 8162283 receptor tyrosine kinase-like orphan receptor 2 7935116 retinol binding protein 4, plasma 8120043 runt-related transcription factor 2 8149825 stanniocalcin 1 8078350 transforming growth factor, beta receptor II (70/80kDa) 7905428 tuftelin 1 7962689 vitamin D (1,25- dihydroxyvitamin D3) receptor 7926916 zinc finger E-box binding homeobox 1

Table II. List of skeletal system development genes highly enriched and significantly expressed at day 21 in osteogenesis. Genes had a p≤0.01 and LR±1.

Short Time-Series Expression Miner (STEM) software was used for analysis of time points in order to create profiles of gene ontologies representing the time points across differentiation. This software is unique in that the algorithms used are designed specifically for time point analyses and allow the user to visualize expression in terms of linear change across time rather than through individual comparisons. Expression profiles as well as clusters of profiles with similar expression trends can be generated.

Ultimately, the output is given in terms of profile trends across time points, that is, upwards trends (increasing expression with increasing time points), downward trends, and spiked trends where a middle spike in expression is observed.

STEM analysis of time points 0, 3, 10, 16, and 21 days revealed 8 defined profiles. Of the 8 profiles, 2 were unclustered, and 6 were clustered into 2 groups of 3.

Expression trends associated with clusters were as follows:

Cluster 1: Three individual profiles, each representing a downward trend in gene

expression as differentiation progressed.

Cluster 2: Three individual profiles, each representing an upward trend in gene

expression as differentiation progressed.

Unclustered Profile 1: One individual profile, representing a downward spike in

gene expression at day 3 followed by an overall upward trend.

Unclustered Profile 2: One individual profile, representing an immediate spike

in gene expression at day 3 followed by a leveling off of expression as

differentiation progressed.

Cluster 1 revealed general decreases through differentiation in signal sequence binding, clatherin coat, pigment granule, SMAD binding, and BMP signaling among others (Table

III). Early osteogenic induction events decreased as differentiation progressed to a more mature osteogenic cell type as would be expected. Cluster 2 represented a general upward trend in gene expression. GO categories in Cluster 2 included olfactory receptor activity, G-protein receptor activity and bone resorption among others. The two unclustered profiles both displayed GO categories related to protein kinase and MAPK activity.

Cluster 1

Category Category Name Corrected Fold ID p-value GO:0005048 signal sequence binding 0.01 2.1 GO:0030119 AP-type membrane coat adaptor complex 0.018 1.9 GO:0030118 clathrin coat 0.016 1.8 GO:0048770 pigment granule <0.001 1.8 GO:0006487 protein N-linked glycosylation 0.004 1.6 GO:0018196 peptidyl-asparagine modification 0.002 1.6 GO:0046332 SMAD binding <0.001 1.5 GO:0030510 regulation of BMP signaling pathway <0.001 1.5 GO:0019538 protein metabolic process <0.001 1.3

Cluster 2

Category Category Name Corrected Fold ID p-value GO:0044255 cellular lipid metabolic process 0.05 2.5 GO:0004984 olfactory receptor activity <0.001 2.1 GO:0007606 sensory perception of chemical stimulus <0.001 2 GO:0004930 G-protein coupled receptor activity <0.001 1.7 GO:0004888 transmembrane receptor activity <0.001 1.6 GO:0035121 bone resorption 0.016 1.5

Unclustered Profile 1

Category Category Name Corrected Fold ID p-value GO:0010769 regulation of cell morphogenesis involved 0.01 3.7 in differentiation GO:0060284 regulation of cell development 0.002 2.4 GO:0000165 MAPKKK cascade 0.04 2.1 GO:0016055 Wnt receptor signaling pathway 0.01 2.0

Unclustered Profile 2

Category Category Name Corrected Fold ID p-value GO:0071173 spindle assembly checkpoint <0.001 33.5 GO:0007094 mitotic cell cycle spindle assembly <0.001 28.8 checkpoint GO:0001525 Angiogenesis 0.034 6 GO:0045859 regulation of protein kinase activity <0.001 5.8 GO:0043405 regulation of MAP kinase activity <0.001 4.8 GO:0042325 regulation of phosphorylation <0.001 4.4 GO:0000165 MAPKKK cascade <0.001 3.7

Table III. STEM analysis expression clusters and related GO terms. Categories included in tables for each cluster were significant (p≤0.05) and upregulated by a fold change of at 1.5 or higher. Categories representing redundant biological processes (e.g. angiogenesis and blood vessel development) were listed only by the category with the highest fold change. Baseline categories representing housekeeping processes were also screened out in order to reduce the amount of gene categories listed. All bone-related categories which met the criteria described above were included.

Highly Enriched Genes

Analysis of highly expressed genes at each time point revealed similarities across time points, as well as potential vital genes involved in ADSC differentiation. Analysis of the top 20 genes at each time point compared to day 0 revealed a pattern of expression which was similar to previously reported osteogenic expression patterns of both ADSC and BMSC [64, 66] (Table IV). Specifically, carboxypeptidase M (CPM), FK506 binding protein (FKBP5), ADH1B, Corin, and Osteomodulin (OMD) have been

50 previously reported for expression at high levels in ADSC and BMSC undergoing osteogenesis [66]. ADSC cells used in these experiments express high levels of

STEAP4 and RERG throughout the differentiation process as well. Specifically, FKBP5 was studied for its ubiquitous expression in ADSC lineage restriction notwithstanding a specific lineage and may play a vital role in early processes involved in MSC lineage specification [66]. Overexpression of FKBP5 in this study may reinforce its importance in the differentiation process.

Other genes expressed more transiently at high levels included, C13orf15,

GPM6B, IGFBP2, SAMHD1, FMO2, FMO3, and MAOA, all of which have been observed at high expression levels during ADSC and/or BMSC osteogenic differentiation. High similarity of the ADSC cells used in these experiments to previously reported gene array data may suggest a common pathway involved in the

ADSC differentiation processes.

Of specific interest for a possible role in ADSC differentiation (as determined through searches of relevant published studies) observed here are HHIP, IGFBP2, FRZB and GPM6B. HHIP was expressed at high levels in day 3 and day 10 cells. It is a hedgehog interacting protein which is important in hedgehog signaling (a morphogen involved in developmental processes) [118]. IGFBP2 is highly expressed at days 10 and

16 and is important in activating IGF-1/ AKT and β-catenin signaling pathways, which ultimately play a role in skeletal acquisition [28]. FRZB is a known modulator of Wnt signaling, whereas GPM6B may be involved in cell differentiation [114].

Top 20 Upregulated Genes for Each Time Point Control Day 3 Control Day 10 Control Day 16 Control Day 21 Symbol LR Symbol LR Symbol LR Symbol LR *CPM 5.3 *CPM 5.4 *CPM 5.4 *CPM 5.3 *FKBP5 4.8 *FKBP5 4.8 *FKBP5 4.9 *FKBP5 4.9 *ADH1B 4.7 *ADH1B 5.4 *ADH1B 5.4 *ADH1B 5.6 *CORIN 4.6 *CORIN 5.0 *CORIN 5.9 *CORIN 5.7 STEAP4 4.4 STEAP4 6.6 STEAP4 5.1 STEAP4 4.8 RERG 4.4 RERG 4.6 RERG 4.6 RERG 4.4 *OMD 4.0 *OMD 4.8 *OMD 4.9 *OMD 4.4 ESCO2 4.3 PDGFRL 4.3 PDGFRL 4.3 PDGFRL 3.9 CDK1 4.3 MYPN 4.0 MYPN 3.8 MYPN 3.8 KIF20A 4.3 FRZB 3.9 FRZB 5.5 FRZB 5.0 MKI67 4.2 *C13orf15 3.7 *C13orf15 4.0 *C13orf15 4.0 SHCBP1 4.2 *GPM6B 3.7 *GPM6B 4.3 *GPM6B 4.9 CASC5 4.1 SLC7A2 3.7 SLC7A2 4.5 SLC7A2 3.9 DTL 4.1 *IGFBP2 3.8 *IGFBP2 4.3 LMO3 4.1 CEP55 4.0 PDK4 3.8 *TNFSF10 4.2 *TNFSF10 4.3 DLGAP5 4.7 DLGAP5 4.2 MCTP1 4.6 MCTP1 4.7 HHIP 4.6 HHIP 4.0 *SAMHD1 4.0 *SAMHD1 3.9 DEPDC1 4.4 DEPDC1 3.8 *FMO2 4.3 *FMO2 3.9 ANLN 4.3 ANLN 3.8 *FMO3 3.8 SEPP1 3.9 PBK 4.1 PBK 3.7 CCDC68 3.8 *MAOA 3.9

Table IV. Top 20 upregulated genes at each time point. Top 20 genes expressed at each time point as measured by log ratio versus day 0 with a minimum p≤0.05. Colors indicate shared expression of genes across time points. *Can be linked to similar studies of ADSC and/or BMSC osteogenic differentiation.

Adipogenic Transdifferentiation

A heterogeneous population of progenitor cells is unlikely to produce a homogenous population of differentiated cells. Aside from differing maturational stages of osteogenic cells, some ADSC cells are likely to transdifferentiate towards the adipogenic lineage. In order to access adipogenic differentiation of these cultures, specific adipogenic-related markers were selected from gene array data for analysis.

Markers included C/EBPβ, C/EBPδ, C/EBPα, and PPARγ which together coordinate adipogenic gene expression. Other genes selected for analysis included fatty acid synthase and fatty acid binding protein 4 (genes expressed in terminally differentiated adipocytes), leptin and adipsin (adipokines) [67]. As expected, expression of some adipocyte markers either increases (PPARγ) or remain fairly uniform (C/EBPα) rather than dropping off completely, indicating that some cells may be transdifferentiating

(Figure 6). Terminal differentiation marker fatty acid synthase drops in expression for the duration of osteogenesis while fatty acid binding protein 4 spikes initially at day 3 and then drops slightly for the remainder of differentiation. In contrast, adipokines leptin and adipsin both increase significantly throughout osteogenesis (Figure 7).

Figure 6. Differentiation factors important in activating adipogenesis. mRNA expressed in terms of normalized mean probe intensity values for each of the 3 gene array replicates. Error bars displayed with SD.

Figure 7. Adipose terminal differentiation markers (FABP4 and FAS) and adipokines (Leptin and Adipsin). mRNA expressed in terms of normalized mean probe intensity values for each of the 3 gene array replicates. Error bars displayed with SD.

ECM as a Modulator and/or Indicator of Differentiation

Previous work indicates that the ECM may play a role in lineage restriction of

MSC down particular pathways [73-76]. Several studies have shown that the ECM secreted by cells undergoing differentiation may actually modify or actively participate in feedback mechanisms and signaling during lineage restriction [75, 76]. Another study suggests that the ECM may be as instructive in determining cellular phenotype or status of differentiation as transcription factors and cellular markers, thereby creating a means of assaying cell state or maturity through the analysis of ECM related gene expression alone [69].

Using gene expression data, an ECM-related gene profile was created for the

ADSCs undergoing lineage restriction. First, ECM related genes (ECM-rg) were defined as genes which code for proteins residing in the extracellular space, or which are secreted into the extracellular environment. ECM-rg were mined out of the 32,321 gene ID’s associated with exon arrays using DAVID software and SOURCE software as mentioned in the Methods section. A total of 1895 genes were documented as being extracellular or secreted. Similar to overall gene expression, comparisons were made of ECM-rgs at time points across differentiation to day 0 creating an ECM-rg differentiation specific profile

(Figure 8). A total of 340 ECM-rgs were differentially expressed across differentiation

(p≤0.05; LR±0.6).

Day 3 Day 10 Day 16 Day 21

Figure 8. Hierarchical gene clustering of ECM-rg at time points in osteogenesis. Heat map indicating high (red) or low (green) expression of ECM-rg clustered on the basis of similar expression patterns. Genes were selected from each time point had a p≤0.05 and LR±0.6 compared to day 0.

Ontology searches of ECM-rg enriched at specific time points yielded a profile very similar to the overall gene expression profile listed previously but with more detail related specifically to osteogenic differentiation (Table V). Much of the intracellular signaling pathways and maintenance pathways involved in cell differentiation as well as homeostasis were filtered out through selection of ECM-rgs alone. Specifically, rather than cell cycle related genes obscuring other events occurring at day 3 and 10, ECM-rg reveal ontologies enriched for signaling, peptidase activity, and BMP/TGFβ signaling at day 3. Day 10 provides information on TGFβ, MSC differentiation, as well as skeletal system development, all of which failed to show up as enriched in overall gene expression comparisons. Other important categories at day 16 included IGF binding, netrin (a domain common in Wnt signaling pathway proteins), CUB (a domain involved in membrane binding of development related proteins such as BMP), leucine rich repeat, collagen, as well as skeletal development. Day 21 revealed similar results as day 16, indicating that the cells may have reached a similar maturational point in terms of ECM by these two time points. Specifically, similar expression of ECM related genes at these two time points may indicate that the ECM being deposited is in a more mature state as would be expected of osteoid-like unmineralized bone matrix.

ECM Related Gene Expression Time Enrichment Gene Ontology Category Adjusted Point Score pValue Day 3 15.77 Signal 4.10E-05 7.66 Disulfide bond 2.70E-06 2.26 Peptidase activity 8.50E-04 2 BMP/TGFβ Signaling Pathway 8.30E-03 Day 20.43 Signal 9.70E-16 10 4.75 Wound healing 4.90E-05 3.74 Response to hypoxia 2.20E-03 2.76 TGFβ, N-terminal 4.50E-02 2.67 Mesenchymal stem cell differentiation 1.80E-02 2.05 Skeletal system development 4.30E-02 Day 4.68 IGF binding 1.60E-05 16 3.55 Netrin module 1.60E-03 2.84 Collagen 2.60E-03 2.46 CUB 3.20E-03 2.41 ECM structure organization 2.50E-03 2.29 Leucine-rich repeat 2.50E-02 2.26 Skeletal system development 4.20E-02 Day 17.88 Signal 4.30E-15 21 5.85 Response to wounding 6.10E-11 5.19 Skeletal system development 1.20E-04 4.9 Cell adhesion 1.10E-04 4.69 IGF binding 3.40E-05 3.83 Wnt signaling pathway 7.20E-06 2.46 Collagen 3.90E-03

Table V. Gene ontology categories associated with ECM-rgs. Genes searched were included in heat map above and met a criteria of p≤0.05 and LR±0.6.

Confirmation of Genes of Interest in Cell Lines #1, #2, and #3

Genes of interest selected for confirmation experiments are included in Appendix

4. Most genes showed similar expression in all cell lines undergoing osteogenesis.

Chapter 1 Conclusions

ADSC, when induced with osteogenic supplements, can undergo osteogenic lineage specification as determined with QPCR of osteogenic markers, mineralization

59 assays, and alkaline phosphatase assays. Gene array analysis of the osteogenic process reveals defined groups of genes expressed at the four time points chosen to study. These genes may indicate the specific location of the cells along the osteogenic pathway.

Additionally, analysis of expression trends during the differentiation process revealed signaling pathways which may be important during osteogenesis: including MAP kinase signaling and BMP signaling. Highly expressed genes are similarly expressed in other published osteogenic studies showing a correlation to the broader MSC osteogenic differentiation literature. Finally, the mapping of ECM-rg changes during osteogenesis provided insight into how the ECM and ECM related genes might indicate specific tissue and cell differentiation states.

CHAPTER TWO

CELL-SECRETED MATRICES MODULATE OSTEOGENIC DIFFERENTIATION

OF ADIPOSE DERIVED STEM CELLS

ADSC in Vitro Deposit ECM under Osteogenic Conditions

ADSCs undergoing osteogenic differentiation begin to deposit extracellular matrix (ECM) on the bottom of the culture dish soon after plating and attachment.

Beginning at day 3 in differentiation, cells can be removed leaving a layer of ECM coating the culture dish. Following decellularization, the ECM appears filamentous and mesh-like on the bottom of the culture dish (Figure 1). By removing cells at progressive time points in differentiation, ECM can be isolated from representative stages in the differentiation process. Previous studies suggest that ECM secreted by differentiating cells may possess osteogenic activity [73-76]. Additionally, ECM deposited at specific time points has been shown to possess varying degrees of osteogenic activity [75, 76].

Figure 1. ECM deposited on culture dish during osteogenic differentiation. Matrices were isolated using Sigma Decellularization kit. Photo taken at 10x magnification.

Screening of ECM for Osteogenic Activity

To determine whether ADSC used in these experiments secreted ECM with osteogenic activity, cells were induced to differentiate down the osteogenic lineage. At 3,

6, 9, 12, 15, 18, 21, 24, and 27 days in differentiation, cells were removed leaving culture dishes coated with ECM. ECM-coated culture dishes were then re-seeded with undifferentiated ADSC and induced to differentiate down the osteogenic lineage using

Dexamethasone (DX) supplemented media.

Cells re-seeded onto ECM at time points described above were characterized for modulation in osteogenic differentiation when compared to controls (cells induced to differentiate on tissue culture plastic or TCP). Alizarin Red S staining for calcium deposition revealed heavy mineralization by cells grown on ECM deposited from day 16

62 in differentiation and beyond (Figure 2). Similar calcium deposition is not observed until day 30 on TCP in bone media (BM) induced control cells. Moreover, day 16 cells on

TCP in BM do not display calcium deposition, indicating that calcium has not been deposited into the matrix at the time of ECM isolation. Cells seeded onto ECM deposited at earlier stages in differentiation (day 11 and before) display little to no calcium deposition.

Figure 2. Increased calcium deposition on ECM coated dishes visualized with alizarin red. A) Top box shows calcium deposition by ADSC induced to differentiate in BM for 21 days on ECM from progressive time points in differentiation. Day 16 ECM appears to have a substantial effect on calcium deposition compared to earlier time points. Similar staining in cultures grown on TCP does not occur until day 30 (bottom panel).

Several ECM-reseeded time points were selected for analysis of bone-related transcription factor RUNX2 mRNA expression. Specifically, cells re-seeded onto day 6,

11, 16, and 24 ECMs were used for RUNX2 mRNA analysis (Figure 3). Comparisons were made to the same time point of cells on TCP induced to differentiate in BM. Earlier and enhanced RUNX2 expression was observed in cells seeded onto day 16 and day 24

ECM when compared to TCP controls. Cells seeded onto ECM from day 6 and day 11 displayed similar or decreased levels of RUNX2 mRNA expression when compared to

TCP controls.

* * * *

* *

Figure 3. RUNX2 mRNA expression increases for cells induced to differentiate on day 16 and day 24 ECM. mRNA is quantified relative to the level of housekeeping gene 18s RNA. TCP refers to ADSC induced to differentiate on tissue culture plastic at time points listed. 6ECM, 11ECM, 16 ECM, and 24ECM refer to cells seeded onto ECM obtained from osteogenic differentiating cells at the day listed (day 6, 11, 16, and 24). Points represent mean fold change of 4 replicates normalized to day 0. Error bars are displayed with standard deviation (SD). Statistical significance was determined with two way ANOVA and Bonferroni’s post hoc analysis. Significance for each group is denoted with * and equals p≤0.01 compared to same time point control on TCP.

Comparison of Osteogenic Properties of Day 11 ECM and Day 16 ECM Using Single

Gene Expression Analysis

Screening of ECM for osteogenic properties revealed contrasts between ECM secreted at day 11 versus ECM secreted at day 16 during osteogenesis. More in-depth comparisons between cells induced to differentiate seeded onto day 11 ECM and day 16

ECM, as well as cells seeded and induced on TCP, were performed. For ease of differentiating between the two ECM time points, groups are referred to as Experimental

1 (cells seeded onto day 16 ECM and induced to differentiate), Experimental 2 (cells seeded onto day 11 ECM and induced to differentiate), and Controls (cells seeded onto

TCP and induced to differentiate).

Comparison of individual bone-related genes between control and experimental groups revealed earlier and enhanced expression of genes in the Experimental 1 group.

Specifically, osteopontin (OPN), osteoprotegerin (OPG), and activating transcription factor 4 (ATF4) all demonstrate earlier or enhanced expression during differentiation

(Figure 4 & 5). In contrast, neither experimental group demonstrated earlier or enhanced expression of alkaline phosphatase compared to the control group, although these results may not be conclusive as alkaline phosphatase is known for its transient expression pattern and the peak expression may have been missed (Figure 5). In addition, mature osteoblast marker, osteocalcin gene expression and protein levels were enhanced in the

Experimental 1 group compared to both control and Experimental 2 groups (Figure 6).

* *

* * * * *

Figure 4. mRNA expression of bone related genes osteopontin (OPN) and osteoprotegerin (OPG) increases when cells are induced to differentiate on day 16 ECM. mRNA is quantified relative to the level of housekeeping gene 18s RNA. Bars represent time points under control, Experimental 1, and Experimental 2 conditions and are expressed as mean fold change of 4 replicates normalized to day 10 control. Error bars are displayed with standard deviation (SD). Statistical significance was determined with two way ANOVA and Bonferroni’s post hoc analysis. Significance for each group is denoted with * and equals p≤0.05 compared to same time point control on TCP.

* * *

* *

Figure 5. mRNA expression of bone related genes transcription factor 4 (ATF4), and alkaline phosphatase (AP) increases when cells are induced to differentiate on day 16 ECM. mRNA is quantified relative to the level of housekeeping gene 18s RNA. Bars represent time points under control, Experimental 1, and Experimental 2 conditions and are expressed as mean fold change of 4 replicates normalized to day 10 control. Error bars are displayed with standard deviation (SD). Statistical significance was determined with two way ANOVA and Bonferroni’s post hoc analysis. Significance for each group is denoted with * and equals p≤0.05 compared to same time point control on TCP.

A * * *

* *

Figure 6. Significant increases in mRNA and protein levels of osteocalcin were observed in cells induced to differentiate on day 16 ECM. A) Osteocalcin (OCN) mRNA expression quantified relative to levels of housekeeping gene 18s RNA. Bars represent time points under control, Experimental 1, and Experimental 2 conditions and are expressed as mean fold change of 4 replicates normalized to day 10 control. Error bars are displayed with standard deviation (SD). Statistical significance was determined with two way ANOVA and Bonferroni’s post hoc analysis. Significance for each group is denoted with * and equals p≤0.05 compared to same time point control on TCP. B) Levels of OCN secreted into medium during differentiation expressed as ng/mL media at day 30 under control and Experimental 1 and 2 conditions. Bars represent mean concentration for each of the 4 replicates. Error bars were displayed with SD. Statistical significance was determined with one way ANOVA and Tukey’s post hoc analysis for comparison of significance across all groups. Significance was denoted with * and p≤0.05. All groups were significant in comparison to one another.

Gene Array Analysis of ECM-Modulated Osteogenesis

Several important genes and/or mechanisms involved in ADSC-mediated osteogenesis were identified in the previous chapter. Published studies indicate that some pathways and networks may be of importance in ADSC-specific differentiation. Several of these pathways include canonical Wnt signaling, as well as non-canonical Wnt5A signaling and MAPK-ERK [28]. Additionally, BMP inductive activity, an event typically associated with osteogenic morphogenesis, is under scrutiny for studies suggesting a lack of activity in ADSC-mediated osteogenesis [43]. Ultimately, the elucidation of pathways, networks, and genes involved in ADSC osteogenesis is of importance in determining the overall therapeutic potential of ADSC in bone healing applications.

Specifically, the form of osteogenic induction used may be important in establishing the pathways involved in ADSC osteogenesis.

In an attempt to study ADSC osteogenic induction conditions, which may more closely resemble in vivo conditions, the ECM’s affect on osteogenesis was measured with gene expression analysis using gene arrays as described in the methods section. To characterize changes occurring across time points in cells induced to differentiate on

ECM from day 11 and day 16 in osteogenesis, RNA was obtained from re-seeded cells at days 3, 10, 16, and 21 and submitted to exon array hybridization. All gene array experiments were performed on ADSC Line #2 with individual gene confirmation experiments in separate lines (1, 2, and 3).

Clustering Gene Arrays

Gene arrays were clustered on the basis of similarities in whole array expression profiles (Figure 7). On average, replicates were highly similar with the exception of several Experimental group 2 replicates. Control arrays grouped closely together, with all time points showing close relation to one another. As observed in Chapter 1, days 3 and 10 were most similar to one another, while days 16 and 21 showed high similarity.

This may lend more validity to the observation made in Chapter 1 that day 10 and 16 represent a shift in maturational phase of the cells. Additionally, Experimental group1, on average, shows a closer relationship to controls than to Experimental group 2, possibly indicating that the two groups are following similar osteogenic pathways. Interestingly,

Experimental 2 more closely associates with the expression profile of day 0 than other groups.

Figure 7. Gene arrays grouped by overall similarity in expression profiles. Whole array clustering based on normalized expression values. Individual arrays displayed as timepoint_Experimental Group or Control (e.g. Day 3 Experimental 1 displayed as 3_Exp.1); Controls listed in black, Experimental 1 listed in red and Experimental 2 listed in blue.

Comparing Gene Expression at Specific Time Points

As performed with control group gene array data, osteogenic expression profiles were created through comparisons of increasing time points to day 0 in both

Experimental 1 and Experimental 2 groups (Figures 8 & 9). Gene expression patterns in the two groups, as well as the control group listed in Chapter 1 (Figure 5, Ch.1) were comparable in expression of some gene-related ontology categories, however they also showed differences. Specifically, all three groups were characterized by early, high expression of cell cycle related genes (Table I). In the control group, cell cycle related genes were highly expressed both at day 3 and at day 10. However, high expression of cell cycle related gene categories did not continue into day 10 in both Experimental groups 1 and 2. Specifically, a shift was observed in gene expression patterns relating to skeletal system development in Experimental group 1 when compared to the control.

Following an attenuated period of cell proliferation, skeletal system development related gene categories began to appear as being up-regulated as early as day 10 and continued through day 21. Additionally, gene categories which might be associated with a more mature osteogenic culture were observed at day 21, including regulation of osteoclast differentiation, Wnt signaling, and skeletal system development.

In contrast to gene ontology categories enriched in Experimental group 1,

Experimental group 2 displayed much less organized expression clustering. Cell cycle gene categories were present at day 3, however, categories enriched at later time points showed very little pattern and/or relation to bone. Some categories enriched at days 16 and 21 included wound healing, regulation of smooth muscle cell proliferation, laminin

G, and thrombospondin type I.

Day 3 Day 10 Day 16 Day 21 B

Figure 8. Heat map indicating high (red) or low (green) expression of genes clustered on the bases of similar expression in Experimental 1. Genes had a minimum p≤0.01 and LR±1 when compared to day 0. Clusters of highly expressed genes are labeled with boxes and letters (A, B, C, D) and indicate gene clusters searched for ontology categories.

Day 3 Day 10 Day 16 Day 21 A

B C

Figure 9. Heat map indicating high (red) or low (green) expression of genes clustered on the bases of similar expression in Experimental 2. Genes had a minimum p≤0.01 and LR±1 when compared to day 0. Clusters of highly expressed genes are labeled with boxes and letters (A, B, C, D) and indicate gene clusters searched for ontology categories.

Experimental 1 Experimental 2 Clade Ontology Clade Ontology Categories Categories A Cell cycle related A Cell cycle related (numerous cell cycle (numerous cell cycle (day 3) related categories) (day 3) related categories) B Signal B Glycoprotein Pattern binding ECM days Skeletal system Cell adhesion (10, 16, 21) development (days 16, 21) Collagen LRR12 Wound healing Vesicle Immunoglobulin Wnt signaling LRR Positive regulation of smooth muscle cell proliferation

C ECM C Glycoprotein Response to vitamin D Cell adhesion (days 16, 21) Cell adhesion (day 16 partial, Laminin G Skeletal system 21 ) Thrombospondin type I development Anti-apoptosis Muscle system process D Signal ECM (days10 partial, Cell adhesion 16, 21) Skeletal system development Response to nutrient LRR12 Wnt signaling Gamma carboxyglutamic acid Regulation of osteoclast differentiation

Table I. Gene ontology categories mapped to specific clades observed in heat map expression of Experimental 1 and 2. Clades labeled with days corresponding to red or high expression in parenthesis below. Categories included met criteria of adjusted p≤0.05 and DAVID enrichment score ≥ 2.

By mapping the list of genes in the ontology category skeletal system development, a more in-depth look at day 16 ECM enhanced osteogenesis was performed

(Table II). Of interest for high expression in Experimental 1 osteogenesis and not controls are osteogenic genes highlighted in yellow below. Specifically, several osteogenesis related genes show direct relevance to the enhanced osteogenenic phenotype of cells seeded onto day 16 ECM. Bone gamma carboxyglutamate protein, otherwise known as osteocalcin, is highly expressed in ECM seeded cells and is an important gene associated with mature osteoblasts, and does not show up as highly expressed in control groups. Cadherin 11 has been implicated for its direct influence on MSC osteogenic differentiation as well as its high expression in osteoblast-like cells [95, 119, 120].

Additionally, upregulation of cadherin 11 may be associated with commitment to osteogenesis instead of adipogenesis in the MSC differentiation pathway [121] and may play an important role in the enhanced osteogenic phenotype observed in Experimental group 1.

Other genes of interest in Experimental group1 osteogenesis may include inhibin beta A, involved in activin A complex and TGFβ signaling [122], matrilin 3, involved in extracellular filamentous networks and bone and cartilage homeostasis [123, 124], as well as odd-skipped related 2, a gene associated with tooth development [125-127].

Several other genes including similar to zinc finger AN1-type domain 5, secreted phophoprotein 1, and TNFRSFM11b (Osteoprotegerin) have relevance to mineralization processes [28, 128]. WW domain containing transcription regulator 1 (TAZ) is present in

Control groups, however is expressed at high levels earlier in Experimental 1 and may represent an important gene involved in the early switch from adipogenesis to

76 osteogenesis [89]. Finally, sortilin may be of specific interest in ADSC osteogenesis because of a reported role in binding and sequestering lipoprotein lipase, an inhibitor of matrix mineralization [94].

ID Gene Name 8132557 AE binding protein 1 8045587 activin A receptor, type IIA 7898693 alkaline phosphatase, liver/bone/kidney 7906140 bone gamma-carboxyglutamate (gla) protein; polyamine-modulated factor 1 7979241 bone morphogenetic protein 4 8001800 cadherin 11, type 2, OB-cadherin (osteoblast) 7919815 cathepsin K 8129082 collagen, type X, alpha 1 7918064 collagen, type XI, alpha 1 8127563 collagen type XII 8057506 frizzled-related protein 8131844 glycoprotein (transmembrane) nmb 8162179 growth arrest-specific 1 8091537 immunoglobulin superfamily, member 10 8139207 inhibin beta A 7965873 insulin-like growth factor 1 (somatomedin C) 8058857 insulin-like growth factor binding protein 5 8050537 matrilin 3 7961514 matrix Gla protein 7973336 MMP14 (membrane inserted) 7995681 MMP2 (gelatinase A) 8086207 noggin 8147573 odd-skipped related 2 (drosophilia) 8095080 platelet-derived growth factor receptor, alpha polypeptide 8115099 platelet-derived growth factor receptor, beta polypeptide 7908924 proline/arginine-rich end leucine-rich repeat protein 8155898 proprotein convertase subtilisn/kexin type 5 8162283 receptor tyrosine kinase-like orphan receptor 2 8120043 runt-related transcription factor 2 8096301 secreted phosphoprotein 1 8161747 similar to zinc finger AN1-type domain 5 7918323 sortilin 1 8149825 stanniocalcin 1 8156826 transforming growth factor, beta receptor I 7905428 tuftelin 1 8152512 tumor necrosis factor receptor superfamily, member 11b 7962689 vitamin D (1,25- dihydroxyvitamin D3) receptor 8091422 WW domain containing transcription regulator 1 7943984 zinc finger and BTB domain containing 16

Table II. List of skeletal system development genes highly enriched and significantly expressed at day 21 in Experimental 1. All genes had a p≤0.01 and LR±1 in comparison to day 0. Rows highlighted in yellow were observed at high expression levels in Experimental 1 and not controls listed in Chapter 1.

As described in chapter 1, STEM software was used in order to create expression trends associated with the time point gene array data for each experimental group. STEM analysis of Experimental 1 revealed 13 defined profiles for the time course. Of the 13 defined profiles, 12 mapped to defined clusters and one remained unclustered, representing a total of 5 profile clusters and one unclustered profile (Table III). By identifying profiles in the time course experiment, STEM software provided a more in- depth look at changes occurring across time points.

Cluster 1 corresponded to two STEM profiles and represented a spike in expression at day 3, followed by a slight decrease and leveling off in expression levels.

As observed in heat map analysis, cell cycle related categories were overly represented in this profile. Additionally, several categories, unobserved in previous analyses, included

MAP kinase activity, epidermal growth factor receptor signaling, JAK-STAT, as well as chordate embryonic development, several of which can be directly linked to osteogenesis

[28]. Specific genes of interest found in chordate embryonic development gene ontology

(GO) category include odd-skipped related 2, noggin, sox5, cyclin B2, MEOX2,

HS6ST1, and EPB41L5, all of which play important roles in early embryonic development and may be important in the transient spike in expression at day 3 [28, 125-

127, 129, 130].

Cluster 2 corresponded to two STEM profiles and represented a downward spike in expression at day 3 followed by an upward trend and leveling off. GO categories observed here included collagen, type I interferon signaling, vasculature development, skeletal system development, response to insulin stimulus, chordate embryonic development, as well as heparin binding among others. Genes of interest in the skeletal

79 system development category may include TPP1, AE binding protein1, LRP6, SULF2, cadherin 11, PCSK5, ZFANDI, and ROR2 [92, 95, 110,119-121,131-134]. Genes included in this profile may have biological significance for a short downregulation during early osteogenic initiation events at day 3.

Cluster 3 corresponded to two STEM profiles and represented an upward spike in expression at day 3 followed by an extreme down-regulation of expression in the later time points. Of interest in this cluster are BMP signaling, an early event involved in osteogenesis [51], skeletal system and cartilage development, both of which may represent transient genes expressed in the differentiation progression. Genes included in the skeletal system development category may be of specific interest for their short spike in expression at day 3, indicating that these skeletal genes may also play an active role in the osteogenic pathway occurring in Experimental 1 group. Some genes of interest include RARG, TIPARP, DLX2, FGFRL1, PRRX2, EDN1, WHSC1, TBX3 and EBP

[135, 136].

Cluster 4 corresponded to three STEM profiles and represented a gradual increase in expression over the time course of differentiation. GO categories of interest in this cluster included regulation of progesterone stimulus, ossification, skeletal system development, heparin binding, odontogenesis, and regulation of cartilage development, all of which may represent genes important in the osteogenic differentiation process in

Experimental 1. Some genes of interest in the skeletal system development category include, THRB, Wnt5A, BMP4, ENPP1, BMPR1B, RUNX2, BGLAP, MTN3; many of which represent more mature osteoblast related genes [45-49, 91, 92, 123, 124].

Cluster 5 corresponded to three STEM profiles and represented a decrease in expression levels until day 16 followed by a short spike in expression at day 21. Of interest in this cluster are genes related to cell adhesion and Wnt signaling. Finally, one unclustered profile represented a short decrease in expression followed by a spike and leveling off. Categories in this cluster included proteolysis and response to wounding.

Cluster 1 (Experimental 1)

Category Category Name Corrected Fold ID p-value GO:0000940 condensed chromosome outer <0.001 29.6 kinetochore (cell cycle related) GO:0046870 cadmium ion binding <0.001 25.4 GO:0022402 cell cycle process <0.001 6 GO:0043405 regulation of MAP kinase activity <0.001 3 GO:0007173 epidermal growth factor receptor <0.001 3.8 signaling pathway GO:0007259 JAK-STAT cascade 0.03 2.9 GO:0043009 chordate embryonic development 0.05 1.6

Cluster 2 (Experimental 1)

Category Category Name Corrected Fold ID p-value GO:0005581 collagen <0.001 8 GO:0060337 type I interferon-mediated signaling 0.006 7.3 pathway GO:0061138 morphogenesis of a branching <0.001 4.1 epithelium GO:0001501 skeletal system development <0.001 3 GO:0001944 vasculature development <0.001 2.9 GO:0072358 cardiovascular system development 0.016 2.7 GO:0032868 response to insulin stimulus <0.001 2.7 GO:0007155 cell adhesion 0.01 2.4 GO:0008201 heparin binding 0.05 2.5 GO:0044421 extracellular region part 0.002 2.2 GO:0043009 chordate embryonic development <0.001 2.2 GO:0010033 response to organic substance 0.006 2.1 GO:0009653 anatomical structure morphogenesis 0.002 2 GO:0007165 signal transduction <0.001 1.6 GO:0051716 cellular response to stimulus <0.001 1.5 GO:0007275 multicellular organismal 0.022 1.5 development

Cluster 3 (Experimental 1)

Category Category Name Corrected Fold ID p-value GO:0000083 regulation of transcription involved 0.02 16 in G1/S phase of mitotic cell cycle GO:0032993 protein-DNA complex <0.001 11 GO:0033002 muscle cell proliferation <0.003 4.1 GO:0030509 BMP signaling pathway <0.004 3.9 GO:0051216 cartilage development 0.04 2.7 GO:0001944 vasculature development <0.002 2.2 GO:0001501 skeletal system development 0.01 2.2

Cluster 4 (Experimental 1)

Category Category Name Corrected Fold ID p-value GO:0032570 response to progesterone stimulus 0.03 13.4 GO:0061035 regulation of cartilage development <0.001 12 GO:0006956 complement activation 0.004 11.6 GO:0045778 positive regulation of ossification <0.001 11.3 GO:0043255 regulation of carbohydrate <0.001 11.3 biosynthetic process GO:0010463 mesenchymal cell proliferation <0.001 10.6 GO:0030316 osteoclast differentiation <0.001 9.7 GO:0030500 regulation of bone mineralization <0.001 9.4 GO:0051384 response to glucocorticoid stimulus <0.001 8.3 GO:0042476 odontogenesis 0.014 6.3 GO:0030335 positive regulation of cell migration 0.01 5 GO:0030155 regulation of cell adhesion 0.03 4.6 GO:0009725 response to hormone stimulus <0.001 4.2 GO:0032868 response to insulin stimulus 0.01 4.1 GO:0042598 vesicular fraction 0.016 4 GO:0031667 response to nutrient levels 0.004 3.9 GO:0009719 response to endogenous stimulus <0.001 3.9 GO:0008201 heparin binding <0.001 3.5 GO:0045597 positive regulation of cell 0.016 3.4 differentiation GO:0001501 skeletal system development 0.04 3.4 GO:0007169 transmembrane receptor protein <0.001 3.3 tyrosine kinase signaling pathway GO:0031012 extracellular matrix 0.032 3.2 GO:0007167 enzyme linked receptor protein <0.001 3.1 signaling pathway GO:0005626 insoluble fraction <0.001 2.8 GO:0043067 regulation of programmed cell death 0.028 2.2 GO:0007166 cell surface receptor linked signaling <0.001 2.2 pathway

Cluster 5 (Experimental 1)

Category ID Category Name Corrected Fold p-value GO:0006695 cholesterol biosynthetic process <0.001 16.9 GO:0007155 cell adhesion <0.001 4.3 GO:0016055 Wnt receptor signaling pathway <0.001 3.2 GO:0044421 extracellular region part <0.001 3.1 GO:0000904 cell morphogenesis involved in <0.001 3 differentiation GO:0055114 oxidation-reduction process 0.044 2.6 GO:0007399 nervous system development <0.001 2.2 GO:0007167 enzyme linked receptor protein <0.001 2.1 signaling pathway GO:0071944 cell periphery <0.001 1.8

Unclustered 1 (Experimental 1)

Category Category Name Corrected Fold ID p-value GO:0051239 regulation of multicellular <0.001 3.9 organismal process GO:0006508 proteolysis <0.001 3.8 GO:0009611 response to wounding 0.01 3.5

Table III. STEM expression clusters and related GO categories for Experimental 1 time course. Categories included in tables for each cluster were significant (p≤0.05) and upregulated by a fold change of at 1.5 or higher. Categories representing redundant biological processes (e.g. angiogenesis and blood vessel development) were listed only by the category with the highest fold change. Baseline categories representing housekeeping processes were also screened out in order to reduce the amount of gene categories listed. All bone-related categories which met the criteria described above were included regardless of redundancy.

STEM analysis of Experimental 2 revealed 11 defined profiles for the time course. Of the 11 defined profiles, 9 mapped to defined clusters and two remained unclustered, representing a total of 4 profile clusters and two unclustered profiles (Table

IV). By identifying profiles in the time course experiment, STEM software provided a more in-depth look at changes occurring across time points. Specifically, STEM analysis for the Experimental 2 group provided some insight into events which failed to show up in heat map comparisons, which are likely due to a larger experimental variation observed in this group.

Cluster 1 corresponded to 2 STEM profiles and represented an increase in expression at day 3 followed by a gradual decrease in expression for the remainder of the experimental time points. Similar to observations made in heat map comparisons, the spike at day 3 was associated with cell cycle related categories. Additionally, other categories included wound healing, negative regulation of MAP kinase, hemostasis, coagulation as well as calmodulin binding.

Cluster 2 corresponded to three STEM profiles and represented a downward spike in expression at day 3 followed by a general upward trend. A variety of interesting categories were associated with this cluster including type I interferon, skeletal system development, placenta development, collagen binding response to hypoxia and cell adhesion. Some skeletal system genes of interest included LTBP3, SCIN, EXTL1,

TOB1, and JUNB. Interestingly, several genes expressed in this profile may be associated with negative regulation of osteoblast differentiation including TOB1 [137].

Cluster 3 corresponded to two STEM profiles and represented a downward spike in expression at day 3 followed by an upward spike and leveling off. Categories of interest

87 in this cluster included cardiovascular system development, collagen, integrin mediated signaling and cardiovascular development.

Cluster 4 corresponded to two STEM profiles and represented a general upward trend throughout differentiation. Categories in this cluster included muscle structure development, kidney development, and fat cell differentiation. Additionally, unclustered profile 1 represented a transient spike in expression at day 3 followed by a spike at day

21, and corresponded to cell proliferation, toll-like receptor 4, and MAPKKK categories.

Finally, unclustered profile 2 represented a spike in expression at day 3 followed by a general downward trend in expression and included RNA processing.

Cluster 1 (Experimental 2)

Category Category Name Corrected Fold ID p-value GO:0000796 condensin complex <0.001 29.4 GO:0001556 oocyte maturation 0.004 13.6 GO:0007049 cell cycle <0.001 5.8 GO:0006996 organelle organization <0.001 3.9 GO:0043407 negative regulation of MAP kinase 0.02 3.2 activity GO:0033554 cellular response to stress <0.001 3.1

GO:0071900 regulation of protein 0.004 3 serine/threonine kinase activity GO:0016462 pyrophosphatase activity <0.001 2.6 GO:0042060 wound healing 0.002 2.4 GO:0050817 coagulation 0.006 2.4 GO:0007599 hemostasis 0.006 2.4 GO:0005516 calmodulin binding 0.03 2.1

Cluster 2 (Experimental 2)

Category Category Name Corrected Fold ID p-value GO:0032370 positive regulation of lipid transport 0.06 11.2 GO:0002675 positive regulation of acute 0.06 11.2 inflammatory response GO:0006956 complement activation 0.008 7.7 GO:0005518 collagen binding 0.002 7.4 GO:0060337 type I interferon-mediated signaling <0.001 6.6 pathway GO:0001890 placenta development 0.09 4.4 GO:0001666 response to hypoxia 0.002 4 GO:0019221 cytokine-mediated signaling <0.001 3.8 pathway GO:0001501 skeletal system development 0.006 3 GO:0007155 cell adhesion <0.001 2.7 GO:0008219 cell death <0.001 1.9

Cluster 3 (Experimental 2)

Category ID Category Name Corrected Fold p-value GO:0005581 collagen <0.001 13.3 GO:0030198 extracellular matrix organization <0.001 9.7 GO:0007229 integrin-mediated signaling 0.0346 7.1 pathway GO:0072358 cardiovascular system <0.001 3.3 development GO:0009887 organ morphogenesis 0.016 2.8 GO:0009653 anatomical structure <0.001 2.1 morphogenesis

Cluster 4 (Experimental 2)

Category Category Name Corrected Fold ID p-value GO:0060337 type I interferon-mediated signaling <0.001 19.5 pathway GO:0019221 cytokine-mediated signaling <0.001 6.9 pathway GO:0045444 fat cell differentiation 0.04 6.2 GO:0001822 kidney development 0.03 5.3 GO:0031012 extracellular matrix <0.001 4.4 GO:0061061 muscle structure development 0.006 3.8 GO:0010033 response to organic substance <0.001 2.8 GO:0007166 cell surface receptor linked signaling <0.001 2.3 pathway

Unclustered 1 (Experimental 2)

Category Category Name Corrected Fold ID p-value GO:0071222 cellular response to 0.002 21.8 lipopolysaccharide GO:0008009 chemokine activity <0.001 20.3 GO:0051403 stress-activated MAPK cascade 0.002 15.7 GO:0034138 toll-like receptor 3 signaling 0.002 14.8 pathway GO:0034142 toll-like receptor 4 signaling <0.001 14.5 pathway GO:0034134 toll-like receptor 2 signaling 0.002 14.4 pathway GO:0002756 MyD88-independent toll-like 0.004 13.1 receptor signaling pathway GO:0001664 G-protein-coupled receptor binding 0.016 7 GO:0042127 regulation of cell proliferation <0.001 3.8 GO:0050789 regulation of biological process <0.001 1.6

Unclustered 2 (Experimental 2)

Category Category Name Corrected Fold ID p-value GO:0000377 RNA splicing, via transesterification 0.004 11 reactions with bulged adenosine as nucleophile GO:0006396 RNA processing <0.001 6.5 GO:0044428 nuclear part <0.001 3.7

Table IV. STEM expression clusters and related GO categories for Experimental 2 timecourse. Categories included in tables for each cluster were significant (p≤0.05) and upregulated by a fold change of at 1.5 or higher. Categories representing redundant biological processes (e.g. angiogenesis and blood vessel development) were listed only by the category with the highest fold change. Baseline categories representing housekeeping processes were also screened out in order to reduce the amount of gene categories listed. All bone-related categories which met the criteria described above were included regardless of redundancy.

In order to compare single time points in each of the groups, Venn diagrams were used to track gene expression patterns at each time point for all three groups [101].

Diagrams were prepared by choosing genes with a minimum significance and log ratio between the time point and day 0 (p≤0.05; LR±0.6). In this manner, shared genes in all groups could be tracked, as well as shared genes in two of the groups, and individually expressed genes which did not meet minimum significance and expression criteria in any other group at that time point (Figure 10). By following Venn diagram patterns at each separate time point, broad similarities between restriction pathways could be tracked in the Control and Experimental 1 groups, as well as the diverging differentiation pathway

91 of Experimental 2. Genes shared by all three groups started out at 544 on day 3.

However, as differentiation progressed in each of the groups the number dwindled to 225 at day 10, 177 at day 16, and 178 at day 21. Additionally, throughout the differentiation process Control and Experimental 1 group shared consistently high numbers of genes at each of the time points (i.e. 312, 421, 405, 369 at days 3, 10, 16, 21, respectively). In contrast, Experimental 2 shared a high number of 131 genes with Experimental 1 at day

3. However, diverging differentiation pathways may have lead Experimental 2 to share much fewer genes at later time points. This observation is corroborated by a high similarity of day 3 Experimental 2 arrays with day 3 Experimental 1 shown in Figure 7.

Following gene ontology categories mapped to the different Venn diagram groupings revealed key information about the diverging osteogenic differentiation patterns observed in each of the groups. Specifically, shared genes in all three groups for each time point revealed few enriched categories, however a common theme among the three groups included cell cycle related categories as well as protein kinase activity

(Table V). As observed previously, Control and Experimental 1 groups shared most similarities in terms of osteogenic differentiation. This observation was supported by a large number of significant and enriched gene categories shared between the two groups at all time points. Some of the shared categories, which may be important in a common osteogenic pathway that the two groups share, include: ECM, positive regulation of protein kinase, regulation of MAPKKK, response to wounding, LRR 12, and JAK-STAT signaling pathway. Experimental 1 and 2, as well as Control and Experimental 2 share very few gene categories.

Individually expressed genes for each group at each of the time points revealed some key differences between the Control group and Experimental 1 group, which display similar osteogenic expression patterns in other types of analyses (Table VI).

Specifically, by spreading genes into various categories using Venn diagrams, the bone- related genes expressed solely in Control groups, were not high enough in number to result in enriched bone-related gene categories. However, this same process of gene categorization using Venny resulted in highly expressed bone-related categories at all time points in Experimental 1. Bone-related categories observed at day 3 included skeletal system development, embryonic skeletal system morphogenesis, and odontogenesis. Days 10, 16, and 21 also included skeletal system related categories among others. Interestingly, the genes solely expressed at day 3 in Experimental 1 reveal an emphasis on early bone development related genes. Most of these genes are retained only in Experimental 1 for the time course, or highly expressed transiently at day 3 and

10 and then downregulated at later time points with no expression in the Control or

Experimental 2 group. These genes, known regulators and/or factors important in early embryonic bone development may play an important role in the initiation of earlier and more robust osteogenesis observed in Experimental 1 cells. Some of the genes of interest at day 3 which were highly expressed in Experimental 1 include, GLI family zinc finger

3, SIX homeobox 1, Sox 5, T-box 3, DLX2, DLX5, forkhead box C2, homeobox C11, homeobox C9, homeobox C5, and tolloid-like 1.

Day 3 Day 10

Day 16 Day 21

Figure 10. Venn diagrams for each time point with each of the groups (Control in blue, Experimental 1 in yellow, and Experimental 2 in green). Genes were included for significance in comparison to day 0 (p≤0.05; LR±0.6).

Shared Shared Shared Shared (C, E1, E2) (C & E1) (E1 & E2) (C & E2) Day Cell cycle Cell cycle N/A RNA splicing 3 related Angiogenesis Day Cell cycle Metal-thiolate DNA Sliceosome 10 related cluster metabolic Response to organic process Protein Kinase substance Activity Glycoprotein Chordate ECM embryonic Cell division development Positive regulation of protein kinase Reg. of MAPKKK Cell migration Angiogenesis Response to wounding Day Cell cycle Mitosis Nucleosome Tetraspanin, 16 related Response to organic conserved site substance Protein kinase Anchoring junction MSC activity Response to differentiation wounding RhoGAP Cadmium Day Cadmium Cell cycle Metal-thiolate Tetraspanin, 21 ECM Regulation of cluster conserved site Disulfide bond protein kinase Negative reg. of cascade response to GTPase regulation external activity stimulus Hormone binding Carbohydrate LRR 12 binding Secreted Growth factor binding Laminin G Jak Stat Signaling

Table V. Gene ontology categories mapped to shared genes generated using Venny at each time point. Genes included were obtained from Venn diagram data and had a p≤0.05 and LR ±0.6. Abbreviations, C stands for Control, E1: Experimental 1, and E2: Experimental 2. N/A refers to no significantly enriched categories under that particular condition. Categories were considered enriched and significant with a DAVID enrichment score of ≥ 2 and p≤0.05.

Control Alone Experimental 1 Alone Experimental 2 Alone Day Pleckstrin RNA splicing N/A 3 homology type Skeletal System Development Embryonic Skeletal System morphogenesis Odontogenesis ncRNA tRNA Chaperone Winged helix repressor Day Cell cycle related Cell-substrate junction/focal N/A 10 Protein complex adhesion biogenesis Insoluble fraction Organelle lumen Phosphotyrosine interaction region Lipid biosynthetic Domain SH3 activity Skeletal System Development Day RNA splicing Metallothionein, vertebrates Signal 16 Cellular Negative regulation of apoptosis Secreted polysaccharide Regulation of protein modification CUB domain metabolic process process Chemotaxis Bone development LRR 12 Response to organic substance Neuron Response to endogenous stimulus projection Gamma-carboxyglutamic acid morphogenesis Skeletal system development Day mRNA processing Pleckstrin homology Response to 21 Gamma-carboxyglutamic acid-rich wounding domain Glycoprotein Response to hormone stimulus Cytokine activity Metal-thiolate cluster Angiogenesis Negative regulation of cell death Maternal Tight junction placenta dev. Skeletal system development Apoptosis Lactation

Table VI. Gene ontology categories mapped to individual group expressed genes for each time point generated using Venny. Genes included were obtained from Venn diagram data and had a p≤0.05 and LR ±0.6. N/A refers to no significantly enriched categories under that particular condition. Categories were considered enriched and significant with a DAVID enrichment score of ≥ 2 and p≤0.05.

Highly Enriched Genes

Analysis of highly expressed genes at each time point revealed similarities across time points, as well as potential vital genes involved in ADSC differentiation. Analysis of the top 20 genes at each time point in Experimental 1 compared to day 0 revealed a pattern of expression that was similar to the control group with a few differences (Table

VII). Specifically, many of the highly expressed genes were shared between Control and

Experimental 1; of the 20 genes highest expressed at each time point, less than a 4th of the genes were different between the two groups. As observed in Chapter 1 (Table IV,

Ch.1), FKBP5, CPM, and OMD were highly expressed across all time points in

Experimental 1. Additionally, many of the other genes observed with possible importance to ADSC osteogenesis were present, including ADH1B, CORIN, C13orfC15,

GPM6B, RERG, FMO2, SAMHD1, and FRZB.

Of specific interest for high expression in Experimental group 1 were several genes which may provide clues to the robust osteogenic differentiation observed in

Experimental 1. KIAA0101, a thyroid associated gene highly expressed at day 3 in

Experimental 1 may be important for its role in regulation of F box protein turnover. F box proteins, can play a role in β-catenin degradation which is an important protein involved in Wnt-induced bone formation [138, 139]. APOD, a gene highly expressed at days 10, 16, and 21 in Experimental 1, has been observed in other MSC osteogenesis gene array experiments [66]. The APOD gene is homologous to retinol binding protein

4, plasma (also observed as being significantly expressed in Experimental 1) and is upregulated by a glucocorticoid response element [66]. Another gene of interest which has been observed in MSC osteogenesis is GRIA1; highly expressed at days 10 and 16 in

Experimental 1. This gene codes for a glutamate receptor. Although several studies have observed contrasting effects of glutamate on osteogenic differentiation, the receptor may be important in regulating cell fate in MSC lineage restriction [140, 141].

Two other genes are highly expressed at day 21 in Experimental 1, and may be of importance in the differentiation process. PRELP, a leucine rich repeat (LRR) protein found in cartilage, is expressed at high levels in growth plates and has heparin binding domains which are often observed in bone-related ECM proteins [142-144].

Dermatopontin (DPT), highly expressed at day 21, may be of specific importance in these experiments. Specifically, DPT was observed as being highly expressed at day 16 in

Control cells as presented in preceding pages (Figure 15) and may be an important component of the ECM on which Experimental 1 cells were cultured. Due to a known role as a downstream vitamin D receptor (VDR) target, as well as a proposed role in modulating cellular response to ECM and growth factors, DPT may be an important factor in modulating osteogenesis observed in Experimental 1 [82].

The top 20 genes in Experimental 2 displayed much less similarity to Control and

Experimental 1 (Table VIII). Compared to the top 20 genes expressed in the Control group at each time point, many similarly expressed genes were observed at day 3.

However, the similarity at day 10 and 16 was much less with no overlap in the highest expressed genes at 21. Specifically, many of the highly expressed genes at day 3, 10, and

16 were associated with cell cycle and proliferation including DGAP5, DEPDC1,

ESCO2, ANLN, CDK1, DTL, and CASC5. A theme common at day 16 and 21 for the highly expressed genes was functional involvement in inflammatory responses, or immune response (IFI44L, MX1, MX2, OAS2, IL13RA2, IL8, IL33, CXCL10, and

CCL20). However, there were several genes including PLAU and HAS2 which may have involvement in bone related activity; specifically endochondral ossification [28,

145]. Finally, ENPP1 highly expressed at day 16 is involved in bone mineralization

[146]. Although, previous data shown in this chapter indicates that the osteogenic differentiation of cells in Experimental 2 is not robust, some skeletal system related genes have been observed in Experimental 2 and could indicate that a small percentage of these cells are differentiating down the osteogenic lineage. These highly expressed genes involved in bone related processes might provide clues to the differentiation of these cells.

Top 20 Upregulated Genes for Each Time Point (Experimental 1) Exp. 1 Day 3 Exp. 1 Day 10 Exp. 1 Day 16 Exp. 1 Day 21 Symbol LR Symbol LR Symbol LR Symbol LR *FKBP5 4.3 *FKBP5 4.6 *FKBP5 4.5 *FKBP5 4.6 *CPM 4.1 *CPM 5.1 *CPM 4.7 *CPM 4.6 *OMD 4.1 *OMD 4.6 *OMD 4.5 *OMD 4.9 SULT1B1 4.3 STEAP4 4.4 STEAP4 4.7 STEAP4 4.1 HIST1H3B 4.3 *ADH1B 4.9 *ADH1B 4.6 *ADH1B 4.8 HIST1H1B 4.3 *CORIN 5.1 *CORIN 4.6 *CORIN 5.0 CEP55 4.3 *C13orf15 4.4 *C13orf15 5.0 *C13orf15 5.0 KIAA0101 4.2 *APOD 3.8 *APOD 4.0 *APOD 4.0 PBK 4.1 *GPM6B 3.7 *GPM6B 4.0 *GPM6B 4.2 CASC5 4.1 RERG 4.7 RERG 4.9 RERG 4.8 CDC20 4.1 *SAMHD1 3.8 *SAMHD1 3.9 *SAMHD1 4.0 DLGAP5 4.6 *MAOA 3.5 *FMO2 3.6 *FMO2 4.0 DEPDC1 4.6 NRK 3.5 FRZB 3.5 FRZB 4.2 HIST1H2BM 4.5 HHIP 4.0 MCTP1 3.3 MCTP1 3.8 MYPN 4.0 MYPN 3.5 CCDC68 3.3 CCDC68 3.7 ANLN 4.6 ANLN 3.5 *FMO3 3.2 *FMO3 3.4 DTL 4.5 CNR1 3.9 CNR1 3.3 METTL7A 3.7 ESCO2 4.1 *GRIA1 3.8 *GRIA1 3.4 PRELP 3.6 KIF20A 4.4 KIF20A 3.6 KIF20A 3.3 DPT 3.3 MKI67 4.3 MKI67 3.4 MKI67 3.3 SEPP1 3.9

Table VII. Top 20 genes expressed at each time point in Experimental 1. Genes were measured by log ratio to day 0 with a minimum p≤0.05. Colors indicate shared expression of genes across time points. Genes denoted with * can be linked to similar studies of ADSC and/or BMSC osteogenic differentiation. Genes listed in Bold/Italics can be found in Control Top 20 genes.

100

Top 20 Upregulated Genes for Each Time Point (Experimental 2) Exp. 2 Day 3 Exp. 2 Day 10 Exp. 2 Day 16 Exp. 2 Day 21 Symbol LR Symbol LR Symbol LR Symbol LR DLGAP5 4.5 DLGAP5 3.3 DLGAP5 2.8 IL8 5.5 DEPDC1 4.3 DEPDC1 2.8 DEPDC1 2.5 IL1RN 4.9 KIF20A 4.3 KIF20A 3.1 KIF20A 2.7 IL33 4.7 MKI67 4.2 MKI67 3.0 MKI67 2.5 CXCL10 4.7 ESCO2 4.1 ESCO2 3.0 ESCO2 2.6 SLC16A6 4.6 HHIP 4.2 HHIP 2.7 IFI44L 2.8 IFI44L 3.5 CDK1 3.9 CDK1 2.7 MX2 2.8 MX2 3.4 PBK 4.1 PBK 2.8 ETV1 2.7 RSAD2 4.5 DTL 4.1 DTL 2.6 PLAT 2.7 AREG 4.5 CASC5 4.0 CASC5 2.8 PLAU 3.2 SERPINB2 4.4 CEP55 4.0 CEP55 2.4 HAS2 2.6 CCL20 4.3 KIAA0101 4.0 KIAA0101 2.6 ESM1 2.6 IL1B 4.2 CDKN3 3.8 CDKN3 2.7 MX1 2.6 EREG 4.2 SHCBP1 3.8 SHCBP1 2.8 TSPAN2 2.6 PTGS2 3.9 ANLN 4.3 ANLN 2.7 SLC14A1 3.2 AREG 3.8 CDC20 3.9 IFI44L 2.6 OAS2 2.5 TM4SF1 3.7 NCAPG 3.8 AIM1 2.6 IL13RA2 3.1 RAB27B 3.5 NUF2 3.8 CENPF 2.5 HERC6 2.5 NR4A2 3.5 FAM111B 3.7 NCAPG 2.5 ENPP1 2.5 MMP1 3.4 HIST1H2BM 4.0 TFPI2 2.9 TFPI2 2.8 TFPI2 4.4

Table VIII. Top 20 genes expressed at each time point in Experimental 2. Genes were measured by log ratio to day 0 with a minimum p≤0.05. Colors indicate shared expression of genes across time points. Genes denoted with * can be linked to similar studies of ADSC and/or BMSC osteogenic differentiation. Genes listed in Bold/Italics can be found in Control Top 20 genes.

101

Adipogenic Transdifferentiation

As observed in Chapter 1, a heterogeneous population of progenitor cells such as the ADSC cells used in these experiments, are unlikely to produce a homogenous population of differentiated cells. Specifically, ADSC induced to differentiate on TCP

(the control group), display several adipogenic related gene markers (Figures 6 & 7, Ch.

1), observations of osteogenic expression profiles generated here indicate that cells on day 16 ECM (Experimental 1) are differentiating down the osteogenic pathway more robustly and sooner. One mechanism by which the ECM may enhance osteogenesis could be an inhibition of adipogenic differentiation, making it more likely that the cells would undergo osteogenesis. In order to access adipogenic differentiation of these cultures, adipogenic-related markers were selected from gene array data for analysis.

Markers included C/EBPβ, C/EBPδ, C/EBPα, and PPARγ, which together coordinate adipogenic gene expression. Other genes selected for analysis included fatty acid synthase and fatty acid binding protein 4 (genes expressed in terminally differentiated adipocytes), as well as leptin and adipsin (adipokines) [67].

Although a decrease in adipogenic markers might explain one mechanism of action for the enhanced ECM-mediated osteogenic differentiation in Experimental group

1, the results did not provide enough evidence to indicate that adipogenesis was being inhibited. Expression of adipocyte marker PPARγ did decrease significantly at days 16 and 21 compared to the controls for both experimental groups. However, other markers including C/EBPα, C/EBPβ and C/EBPγ remain fairly constant or even display some upregulation at later time points in both Experimental 1 and 2 (Figure 11 & 12).

Additionally, terminal differentiation marker fatty acid binding protein 4 and fatty acid

102 synthase either remain constant or show an increase in gene expression for Experimental

1 and 2. In contrast, however, adipokines leptin and adipsin both decrease when compared to controls at later time points (Figure 13 & 14).

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Figure 11. Gene expression of adipose differentiation factors, PPARγ and C/EBPα important in activating adipogenesis, shows differential expression among the groups. mRNA expressed in terms of mean normalized probe intensity ± SD for each of the 3 gene array replicates. Statistical significance was determined with two way ANOVA and Bonferroni’s post hoc analysis. Significance to same time point control is denoted with * for both Experimental 1 and 2, # for Experimental 1 significance, and & for Experimental 2 significance. Samples with p≤0.05 were considered statistically significant.

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* #

* # *

Figure 12. Gene expression of adipose differentiation factors, C/EBPβ and C/EBPδ important in activating adipogenesis, shows differentiation expression among the groups. mRNA expressed in terms of mean normalized probe intensity ± SD for each of the 3 gene array replicates. Statistical significance was determined with two way ANOVA and Bonferroni’s post hoc analysis. Significance to same time point control is denoted with * for both Experimental 1 and 2, # for Experimental 1 significance, and & for Experimental 2 significance. Samples with p≤0.05 were considered statistically significant.

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# * *

Figure 13. Gene expression of adipose terminal differentiation markers fatty acid binding protein 4 and fatty acid synthase varies between groups. mRNA expressed in terms of mean normalized probe intensity ± SD for each of the 3 gene array replicates. Statistical significance was determined with two way ANOVA and Bonferroni’s post hoc analysis. Significance to same time point control is denoted with * for both Experimental 1 and 2, # for Experimental 1 significance, and & for Experimental 2 significance. Samples with p≤0.05 were considered statistically significant.

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& *

Figure 14. Gene expression of adipokines leptin and adipsin varies between groups. mRNA expressed in terms of mean normalized probe intensity ± SD for each of the 3 gene array replicates. Statistical significance was determined with two way ANOVA and Bonferroni’s post hoc analysis. Significance to same time point control is denoted with * for both Experimental 1 and 2, # for Experimental 1 significance, and & for Experimental 2 significance. Samples with p≤0.05 were considered statistically significant.

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ECM as a Modulator and/or Indicator of Differentiation

As mentioned in Chapter 1 and increasingly apparent from data presented here, the ECM has profound effects on the differentiation process. Specifically, ECM secreted at the midpoint in differentiation of ADSC down the osteogenic lineage, possesses osteogenic qualities. The enhancing effect of ECM from day 16 on differentiation is pronounced. In contrast, ECM from day 11 seems to have varying effects on osteogenesis, which are not as pronounced as day 16 ECM. Chapter 1 examined the osteogenic profile of ADSC differentiating on TCP under supplemented media induction.

An important shift observed in the differentiation process occurred between days 10 and

16. The shift corresponded with a previously identified restriction point in maturational phase of the cells. At day 10, the cells were undergoing proliferation and remained in the proliferation phase of differentiation. However, at day 16, gene expression correlated with a lack of mineralization of cultures at this time point and indicated a shift to matrix maturation phase of differentiation [55]. This shift fits with observed differences in osteogenic properties of the ECM secreted at these two time points. A comparison of changes in ECM-related gene (ECM-rg) expression at these two time points in the control cells may reveal potential genes that code for proteins involved in the observed change in osteogenic quality of the ECM.

As described in Chapter 1, ECM-rg were identified as genes which code for proteins residing in the extracellular space, or that are secreted into the extracellular environment. ECM-rgs were compared between days 10 and 16 of the control group.

Only highly enriched and significant genes (p≤0.01; LR±1) were included. Of the 1895 genes documented as being ECM-rg, 28 genes met the selection criteria described above

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(Figure 15). Several genes listed have documented relevance to bone including

ADAMTS15, TGFB2, ENPP2, FST, GPC3, LEP, IGFBP5, CHRDL1, PCSK1,

COL11A1, DPT, TNC and FRZB.

Figure 15. Heat map indicating high (red) or low (green) expression of ECM-rgs clustered on the basis similar expression patterns. Genes included were categorized as ECM-rg and selected for enrichment and significance (p≤0.01; LR±1) between days 10 and 16 in Control cells.

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An ECM-rg profile was created for both experimental groups by comparing

ECM-rgs at time points across differentiation to day 0 (Figures 16 & 17). In Chapter 1,

Control group ECM-rg expression revealed an expression profile with higher potential to describe underlying osteogenic events. By selecting only ECM-rgs, many of the housekeeping events and intracellular signaling events were screened out. This resulted in an expression profile designed to track secreted proteins; proteins which often play an important role in cell behavior as well as characterizing a tissue type [147]. Experimental group 1 cells (cells seeded onto day 16 ECM) differentiate faster and more robustly as determined by experiments described above. ECM-rg expression would be expected to corroborate this observation as well as potentially provide more information on the underlying events. Additionally, ECM-rg expression may lend more insight into events occurring in Experimental 2.

As expected, ECM-rg profiles for both Experimental 1 and 2 provided insight into events occurring across differentiation. Specifically, by tracking enriched gene ontology categories at each time point, a more in-depth view of differentiation was observed

(Tables IX & X). Experimental 1, day 3 included categories such as IGF binding, collagen catabolic process, Wnt receptor signaling, regulation of ossification, and osteogenesis. Osteogenic related categories were not enriched in previous whole genome analyses at day 3, indicating that ECM-rg profiling may provide key information on early events which might otherwise have been obscured by cell cycle related categories.

Additionally, day 10 displayed categories such as heparin binding, skeletal system development, cartilage development, TGFβ, IGF binding, Wnt signaling, gamma- carboxyglutamic acid rich domain, and JAK-STAT, providing a much more in-depth

110 look at gene categories in day 10. Day 16 categories included gamma-carboxyglutamic acid rich domain, skeletal system development, frizzled related, as well as TGFβ.

Finally, day 21 revealed gene categories skeletal system development, cell adhesion, collagen, frizzled, regulation of ossification, and odontogenesis.

ECM-rg profiling in Experimental 2 revealed obvious differences in ECM-rg expression patterns. Some of the categories observed included thrombospondin, type I repeat at day 3 and 16, TGFβ signaling at day 10, scavenger receptor activity and von

Willebrand factor, type A at day 16, as well as a mix of cell differentiation categories at day 21 including skeletal system development, epithelial cell development, and erythrocyte differentiation.

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Day 3 Day 10 Day 16 Day 21

Figure 16. Heat map indicating high (red) or low (green) expression of ECM-rg clustered on the bases of similar expression in Experimental 1. Genes were selected with a p≤0.05 and LR±0.6 compared to day 0.

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Day 3 Day 10 Day 16 Day 21

Figure 17. Heat map indicating high (red) or low (green) expression of ECM-rg clustered on the bases of similar expression in Experimental 2. Genes were selected with a p≤0.05 and LR±0.6 compared to day 0.

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ECM Related Gene Expression (Experimental 1) Time Enrichment Gene Ontology Category Adjusted Point Score p Value Day 3 6.33 Insulin-like growth factor binding 3.80E-06 4.61 Blood vessel morphogenesis 2.50E-07 4.54 EGF-like, type III 7.10E-07 2.71 Collagen catabolic process 5.20E-03 2.68 Growth factor activity 2.00E-05 2.56 Regulation of ossification 1.80E-02 2.39 Leucine-rich repeat 8.20E-03 2 Osteogenesis 3.50E-02 2 Wnt receptor signaling pathway 1.80E-02 Day 10 6.62 Heparin binding 2.80E-06 5.28 Response to nutrient levels 2.50E-07 3.99 Skeletal system development 2.60E-05 3.62 EGF calcium-binding 2.80E-05 3.47 Growth factor activity 5.80E-07 3.46 Cartilage development 1.80E-03 3.02 TGFβ 1.10E-04 3 Netrin 7.10E-03 2.79 Insulin-like growth factor binding 2.00E-02 2.7 Wnt receptor signaling pathway 3.00E-03 2.48 Gamma-carboxyglutamic acid-rich 5.60E-02 2.45 Jak-STAT cascade 4.00E-05 Day 16 4.88 Response to nutrient levels 3.90E-07 3.78 Gamma-carboxyglutamic acid-rich 3.90E-03 3.65 Growth factor activity 1.30E-06 3.5 Skeletal system development 1.50E-05 3.3 Frizzled related 1.90E-04 3.19 TGFβ receptor signaling pathway 5.00E-02 Day 21 7.24 Growth factor activity 1.30E-07 5.02 Skeletal system development 3.50E-07 4.75 Cell adhesion 4.20E-04 4.41 Collagen 8.20E-05 3.9 Response to nutrient levels 1.50E-05 3.42 Gamma-carboxyglutamic acid-rich 7.20E-03 3.16 EGF calcium-binding 1.20E-03 2.84 Frizzled related 2.50E-05 2.82 Regulation of ossification 2.30E-02 2.04 Odontogenesis 2.30E-02

Table IX. Gene ontology categories associated with ECM-rg expressed at high levels at each time point listed in Experimental 1. Genes searched were included in heat map above and met a criteria of p≤0.05 and LR±0.6.

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ECM Related Gene Expression (Experimental 2) Time Enrichment Gene Ontology Category Adjusted Point Score p Value Day 3 2.66 Thrombospondin, type I repeat 3.00E-03 2.42 Regulation of cell proliferation 2.80E-03 Day 10 2 TGFβ signaling pathway 2.30E-02 Day 16 4.28 Thrombospondin, type I repeat 6.30E-04 4.05 Collagen 1.20E-06 3.84 Scavenger receptor activity 2.70E-03 3.22 ECM-receptor interaction 4.10E-03 2.73 Polysaccharide binding 8.60E-03 2.63 von Willebrand factor, Type A 9.50E-03 2.61 Secretory granule 4.70E-04 Day 21 10.67 Cytokine activity 3.30E-20 10.01 Heparin binding 2.60E-10 4.32 Metalloprotease 6.60E-08 3.63 Laminin G, thrombospondin type, N- 9.60E-04 terminal 3.62 Epithelial cell differentiation 6.30E-05 3.18 Skeletal system development 1.90E-03 3.13 Blood vessel development 4.60E-03 2.75 Wnt signaling pathway 1.20E-03 2.38 Erythrocyte differentiation pathway 1.60E-03

Table X. Gene ontology categories associated with ECM-rg expressed at high levels at each time point listed in Experimental 2. Genes searched were included in heat map above and met a criteria of p≤0.05; LR±0.6

Confirmation of Genes of Interest in Cell Lines #1 & #3

Genes of interest selected for confirmation experiments are included in Appendix

4. Most genes showed similar expression in all cell lines undergoing osteogenesis.

Chapter 2 Conclusions

ECM deposited by ADSC at the midpoint in osteogenesis (Day 16), possesses osteogenic activity. Cells seeded onto this ECM and induced to differentiate in the presence of bone medium progress more rapidly toward a mature osteoblast state than cells on TCP alone in bone medium. Gene array analysis of cells seeded onto ECM 115

(Experimental 1 and Experimental 2) revealed faster progression of cells in Experimental

1 through osteogenic maturational phases. This faster progression to an osteogenic state was also accompanied by early osteogenic markers which were not present in Control cells. Additionally, expression trends during differentiation in Experimental 1 revealed many more signaling related pathways including JAK-STAT, MAPK, EGF signaling, interferon signaling, BMP signaling, tyrosine kinase signaling, and Wnt signaling: all of which may be important in the osteogenic differentiation of Experimental 1 cells.

Alternatively, Experimental 2 cells (grown on day 11 ECM) do not display an enhanced osteogenic phenotype. Finally, as observed in Chapter 1, the mapping of ECM-rg expression throughout the differentiation process revealed an osteogenic specific profile and identified some unique gene categories not present in whole genome analysis.

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CHAPTER THREE

DERMATOPONTIN IN THE EXTRACELLULAR MATRIX MAY ENHANCE

OSTEOGENIC DIFFERENTIATION OF ADIPOSE DERIVED STEM CELLS

Dermatopontin (DPT), an extracellular matrix (ECM) component of many tissue types, is not well characterized in terms of its functional roles. A total of 32 publications can be found in PUBMED describing DPT as an ECM protein, which acts largely as a mediator between the cell and the extracellular environment [85]. Functional roles attributed to DPT include binding, possible modulation of the activity of BMPs and

TGFβ, cell adhesion, collagen and fibronectin fibril formation, as well as roles in cell proliferation (probably due to modulation of TGFβ activity) [83, 86].

A working hypothesis in Chapter 2 is that a direct correlation may exist between

ECM-related genes (ECM-rg) expressed at a particular time point and the corresponding activity of the secreted and corresponding entrained proteins from that same time point.

Therefore, we hypothesized that ECM-rgs highly expressed at day 16 may individually be involved in the modulation of osteogenesis observed in Chapter 2 by causing the build-up of the coded protein in the ECM and acting as the source of outside-in signaling cues. We observed high gene expression of DPT in ADSC induced to differentiate down the osteogenic lineage, particularly at day 16 where the deposited ECM was shown to have enhanced osteogenic properties.

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In order to test whether DPT plays a role in the enhanced differentiation observed when cells were seeded onto day 16 matrices (i.e. matrices which should contain DPT), we overexpressed the DPT gene in ADSC using stable lentiviral infection. ADSC overexpressing the gene for DPT (ADSC_DPT) were then induced to differentiate down the osteogenic lineage. ADSC_DPT were used for two purposes: to collect RNA following the differentiation period, and to isolate ECM at day 16 (which should contain high levels of DPT protein). Isolated ECM from cells overexpressing DPT (DPT_ECM) was reseeded as described in Chapter 2 and Materials and Methods with undifferentiated

ADSC and the cells induced with osteogenic supplements. Differentiation down the osteogenic lineage of ADSC_DPT and cells reseeded onto DPT_ECM was characterized for modulation of the differentiation process.

Dermatopontin Gene Expression Increases with Time in Culture during Osteogenesis

Dramatic increases in DPT gene expression were observed in cells undergoing osteogenesis between days 10 and 16 on TCP (Control group) (Figure 1). The increase in

DPT gene expression observed between days 10 and 16 in the Control group was shifted to an earlier increase in cells seeded onto day 16 ECM (Experimental 1 group) (Figure 1) as the data showed a significant increase in DPT gene expression between days 3 and 10 in Experimental 1. The shift in DPT gene expression of Experimental 1 cells also fit with an overall shift in expression of bone related genes in the Experimental 1 group to earlier time points. The shift in earlier expression of bone markers parallel with an increase in

DPT gene expression may indicate that DPT is an important source of outside-in signaling for ADSC osteogenic differentiation.

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Figure 1. Dermatopontin (DPT) mRNA expression increases during osteogenic differentiation in Control and Experimental 1 groups. DPT mRNA is expressed in terms of normalized mean probe intensity values ± SD for each of the 3 gene array replicates. Statistical significance was determined with two way ANOVA and Bonferroni’s post hoc analysis for comparison of individual time points between Control and Experimental 1. Significance was denoted with a *; p≤0.05.

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Dermatopontin Protein Levels Increase between Days 10 and 16 during Osteogenesis

A dramatic increase in gene expression of dermatopontin was observed between day 10 and 16 Control cells. This increase in gene expression was paralleled by an increase in dermatopontin protein content within the cell lysate as observed through western blot (Figure 2). Specifically at day 10, Control cells showed very little antibody binding for dermatopontin in the expected size range. However, at day 16, Control cells displayed an increase in antibody binding at the expected 22kD size. The loading control

GAPDH indicated that similar protein levels were loaded onto the gels.

Figure 2. Dermatopontin protein levels increase dramatically between days 10 and 16 in the Controls as observed through western blotting.

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Transfection of Human Embryonic Kidney Cells with Lentivirus Dermatopontin Vector

Human embryonic kidney (HEK293T) cells were transfected with the Lentiviral dermatopontin construct (Lenti_DPT), packaging vector, and envelope vector described in Materials and Methods. The construct contained an internal ribosome entry site

(IRES) which allowed a fluorescing agent (ZsGreen) to be expressed in concert with the dermatopontin gene in transfected cells. Transfection efficiency was determined visually with fluorescent microscope images. The majority of cells fluoresced green (Figure 3).

Figure 3. HEK293T cells transfected with Lenti_DPT construct. Left photo cells visualized with GFP fluorescence, right photo same field of view; cells visualized without fluorescence magnified 10X.

Infection of ADSC with Lenti_DPT virus containing supernatant

Viral supernatants obtained from HEK293T transfection were used for infection of ADSC. Much lower efficiency was observed in ADSC infection compared to

HEK293T transfection. Cell sorting revealed only 5% of ADSC fluoresced green indicating infection with the Lenti_DPT virus (Figure 4). Fluorescence observed in

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ADSC infected with virus was also attenuated compared to HEK293T cells. However, cell sorting allowed for a relatively pure population of ADSC overexpressing DPT

(Figure 5).

4.8%

Figure 4. Cell sorting of ADSC exposed to Lenti_DPT viral supernatant showed low infection efficiency. Gating of cells positive for ZsGreen (excitation 493nm; emission 505nm) revealed 4.8% of ADSCs were ZsGreen positive.

ADSC Line #2 displayed here.

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Prior to sorting: ADSC infected with Lenti_DPT viral supernatant

Following sorting: ADSC infected with Lenti_DPT viral supernatant

Figure 5. Cell sorting enriched Lenti_DPT infected ADSC population. Left photo cells observed with GFP fluorescence, right photo same cells without fluorescence magnified 10X.

Dermatopontin Gene Expression in Sorted ZsGreen Positive Cells

Following cell sorting, DPT mRNA expression was measured using QPCR in order to determine whether infected ADSC cells positive for ZsGreen expressed DPT at high levels compared to cells negative for ZsGreen. QPCR revealed high expression of

DPT in Lenti_DPT infected cells. Control cells infected with the Lentivirus vector alone

(Lenti_vector) containing ZsGreen but not Dermatopontin did not express high levels of

DPT mRNA (Figure 6).

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Figure 6. ADSC infected with Lenti_DPT and sorted using ZsGreen expressed high levels of DPT mRNA. mRNA is quantified relative to the level of housekeeping gene 18s RNA, expressed as mean ± SD of 4 replicates, and normalized to ZsGreen (-). Statistical significance was determined using one-way ANOVA with Tukey’s post hoc analysis for multiple group comparisons. Significance was denoted with *; p≤0.05. Lenti_DPT ZsGreen (+) displayed significant DPT expression compared to both groups.

ADSC Line #2 is displayed here, Lines #1 and #3 show similar results.

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Overexpression of Dermatopontin Gene Resulted in Increased Dermatopontin Protein Expression

Following cell sorting, ADSC_DPT cells were cultured for 16 days in BM. Cell lysates were obtained from ADSC_DPT and used for western blot analysis of DPT

(Figure 7). ADSC_DPT cells displayed increased DPT banding at the expected size range compared to Control cells at day 16 in bone medium. Additionally, ADSC_DPT displayed increased DPT protein expression compared to Lenti_vector cells in bone medium at day 16 (cells infected with the Lenti vector alone without the DPT gene insert). These results indicate that Lentiviral-driven overexpression of the DPT gene results in overexpression of the protein as well.

Figure 7. Dermatopontin protein in ADSC_DPT cells increases corresponding to an increase in DPT gene overexpression driven by the Lentiviral infection.

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Stable Overexpression of Dermatopontin throughout Differentiation

Lentiviral induced expression of genes is in theory, stable [148]. However, in order to monitor whether ADSC_DPT dividing cells in vitro maintain lentiviral induced expression, fluorescence was monitored for 30 days in vitro (Figure 8). It is assumed, that if lentiviral driven fluorescence of ZsGreen is maintained during the culture period, overexpression of the DPT gene should also be maintained. Fluorescence of ADSC_DPT cells was maintained throughout the culture period. However, the percentage of fluorescing cells was hard to determine visually both because cells became confluent and because fluorescence was maintained at a low level as observed in initial infection images.

ADSC_DPT 30 days in culture

Figure 8. Cell sorting enriched Lenti_DPT infected ADSC population cultured for 30 days maintain fluorescence. Left photo cells observed with GFP fluorescence, right photo same cells without fluorescence magnified 10X.

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Analysis of Dermatopontin Overexpression Affect on Osteogenic Differentiation

ADSC_DPT were induced to differentiate using osteogenic supplements as described in Materials and Methods. At day 21, osteogenic genes were assessed using

QPCR. Assuming overabundance of DPT would enhance osteogenic differentiation, we expected to see an increase in expression of osteogenic markers. However, expression of osteogenic markers was significantly downregulated in ADSC_DPT compared to controls (ADSC induced to differentiate on TCP). Specifically, RUNX2, a transcription factor vital in osteogenic differentiation of MSC, was expressed at much lower levels than the control at day 21. Osteocalcin, often used as a marker for mature osteoblasts, is expressed during late stage osteogenesis and can indicate whether cultures have fully differentiated [109]. Expression of osteocalcin mRNA was also attenuated in

ADSC_DPT cultures (Figure 9). Of note was a similar expression pattern of both

RUNX2 and osteocalcin genes in control cells induced on TCP compared to cells infected with the Lenti_vector alone without the DPT gene. This indicated that low expression of osteogenic genes was not an artifact of cell stress induced by sorting conditions as Lenti_vector infected cells were sorted and cultured under exact conditions as ADSC_DPT.

Two genes of interest identified in Chapters 1 and 2 were also used for QPCR analyses. WW domain containing transcription regulator 1, also referred to as TAZ, was identified in Chapter 1 for high expression in ADSC induced to differentiate on TCP

(Control group) as well as in Experimental 1 cells induced to differentiate on day 16

ECM (Chapter 2). TAZ may be an important modulator of ADSC osteogenesis because

127 its role in co-activating RUNX2 dependant gene transcription while repressing PPARγ dependant gene transcription [89]. Expression of TAZ, like RUNX2 and osteocalcin, was downregulated in cells overexpressing DPT (Figure 10). Another gene of interest,

Wnt5A, involved in non-canonical Wnt signaling and implicated for a potential role in

ADSC osteogenesis [91], was also observed at high levels in both Control cells in

Chapter 1 and Experimental 1 cells in Chapter 2. Similar downregulation of Wnt5A was observed in ADSC_DPT cells (Figure 10).

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Figure 9. Gene expression of RUNX2 and osteocalcin is downregulated at day 21 in ADSC_DPT cells compared to Controls and Lenti_vector alone cells induced to differentiate down the osteogenic lineage. mRNA is quantified relative to the level of housekeeping gene 18s RNA, expressed as mean ± SD of 4 replicates and normalized to day 0. Statistical significance was determined using one way ANOVA with Bonferroni’s post hoc analysis for comparison to day 21 Control cells. Significance was denoted with *; p≤0.05.

ADSC Line #2 is displayed here, Lines #1 and #3 show similar results.

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Figure 10. Gene expression of TAZ and Wnt5A is downregulated at day 21 in ADSC_DPT cells compared to Controls. mRNA is quantified relative to the level of housekeeping gene 18s RNA, expressed as mean ± SD of 4 replicates and normalized to day 0. Statistical significance was determined using unpaired t test. Significance was denoted with *; p≤0.05.

ADSC Line #2 is displayed here, Lines #1 and #3 show similar results.

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Analysis of Dermatopontin-Containing ECM Affect on Osteogenesis

ADSC_DPT cells induced with osteogenic supplements were also used for isolation of ECM at day 16. ECM secreted from ADSC_DPT (DPT_ECM) should contain abundant amounts of DPT. Undifferentiated ADSC were seeded onto DPT_ECM in order to observe whether the presence of abundant DPT had an effect on osteogenesis.

After observing downregulation of osteogenic genes in ADSC_DPT cells induced to differentiate on TCP (observed in Figures 9 and 10 above), similar expression patterns were expected for cells induced to differentiate on DPT_ECM.

Surprisingly, in general, expression of osteogenic related genes was upregulated in cells seeded onto DPT_ECM at day 21 compared to Controls and Experimental 1 cells

(cells seeded onto day 16 ECM as described in Chapter 2). Specifically, RUNX2 expression was significantly higher than both Control cells on TCP and Experimental 1 cells on day 16 ECM (Figure 11). Osteocalcin gene expression was also significantly higher than both Controls at day 21 on TCP and Experimental 1 cells on day 16 ECM

(Figure 12). ECM was also isolated from ADSC infected with the Lenti_vector alone.

ADSC were seeded onto this ECM and induced to differentiate as another control.

Expression of osteogenic markers for cells on Lenti_vector alone ECM would be expected to show similar patterns to Experimental 1 cells. Assuming lentiviral infection did not result in insertion of viral components into genomic areas important in osteogenesis, this ECM should be essentially equal to ECM used in Experimental 1 cells.

Expression of RUNX2 in these cells was similar to Experimental 1 expression. However, in the case of osteocalcin, expression was not statistically significant to DPT_ECM seeded cells.

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* # $

Figure 11. Gene expression of RUNX2 increases in DPT_ECM seeded cells at day 21 compared to Day 21 Control and Experimental 1. mRNA is quantified relative to the level of housekeeping gene 18s RNA, expressed as mean ± SD of 4 replicates and normalized to day 0. Statistical significance was determined using one way ANOVA with Tukey’s post hoc analysis for multiple group comparisons. Significance was denoted with * for significance to Day 21 Control, # for significance to Experimental 1; and $ for significance to Lenti_vector alone ECM seeded cells (VA_ECM_RS). p≤0.05 was considered statistically significant.

ADSC Line #2 is displayed here, Lines #1 and #3 show similar results.

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* #

Figure 12. Gene expression of osteocalcin increases in DPT_ECM seeded cells at day 21 compared to Day 21 Control and Experimental 1. mRNA is quantified relative to the level of housekeeping gene 18s RNA, expressed as mean ± SD of 4 replicates and normalized to day 0. Statistical significance was determined using one way ANOVA with Tukey’s post hoc analysis for multiple group comparisons. Significance was denoted with * for significance to Day 21 Control, # for significance to Experimental 1; and $ for significance to Lenti_vector alone ECM seeded cells (VA_ECM_RS); p≤0.05 was considered statistically significant.

ADSC Line #2 is displayed here, Lines #1 and #3 show similar results.

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Two other genes mentioned above for a role in ADSC osteogenesis identified in previously published papers as well as in Chapters 1 and 2 are TAZ and Wnt5A. High expression of these genes was observed in cells seeded onto DPT_ECM. Specifically, cells seeded onto DPT_ECM expressed TAZ at much higher levels compared to day 21 controls. However, expression was not significant compared to Experimental 1 cells

(Figure 13). Wnt5A, was expressed at high levels in cells seeded onto DPT_ECM.

However, expression was not significant compared to either Controls at day 21 or to

Experimental 1 cells (Figure 14).

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* #

Figure 13. Gene expression of TAZ increases in DPT_ECM seeded cells at day 21 compared to Day 21 Control and Experimental 1. mRNA is quantified relative to the level of housekeeping gene 18s RNA, expressed as mean ± SD of 4 replicates and normalized to day 0. Statistical significance was determined using one way ANOVA with Tukey’s post hoc analysis for multiple group comparisons. Significance was denoted with * for significance to Day 21 Control, # for significance to Experimental 1; p≤0.05 was considered statistically significant.

ADSC Line #2 is displayed here, Lines #1 and #3 show similar results.

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Figure 14. Gene expression of Wnt5A is high in DPT_ECM seeded cells at day 21 however not significant compared to Day 21 Control and Experimental 1. mRNA is quantified relative to the level of housekeeping gene 18s RNA, expressed as mean ± SD of 4 replicates and normalized to day 0. Statistical significance was determined using one way ANOVA with Tukey’s post hoc analysis for multiple group comparisons. All groups were significant (p≤0.05) to ADSC_DPT cells (Lenti_DPT) induced to differentiate on TCP.

ADSC Line #2 is displayed here, Lines #1 and #3 show similar results.

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Chapter 3 Conclusions

Dermatopontin, an extracellular matrix protein highly expressed at day 16 in

ADSC osteogenesis, may enhance osteogenic differentiation. Specifically, extreme upregulation of osteogenic markers was observed for cells seeded onto ECM containing abundant quantities of DPT and induced with bone medium. This may indicate an important role for DPT in the induction of MSC toward the osteogenic lineage.

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DISCUSSION AND CONCLUSIONS

ADSC Osteogenesis Follows Common Paradigms of MSC Osteogenic Differentiation

In Chapter 1, ADSC differentiation down the osteogenic lineage is examined.

Comparisons of ADSC osteogenesis observed in Chapter 1 are made to existing pathways observed in other published studies on ADSC as well as BMSC studies. The overall similarity to previously observed osteogenesis paradigms is an important theme in

Chapter 1 and can relate this study to a broader body of work examining MSC differentiation.

Brief characterization of ADSC used for this work demonstrated that they express bone related genes, secrete alkaline phosphatase, and mineralize heavily in the presence of high phosphate containing medium when subjected to culture in osteogenic media.

They also secrete osteocalcin approximately concomitant with mineralization. However, mRNA expression of osteocalcin is relatively low and may indicate that some of the mineralization observed in these cells is due to the high phosphate concentrations present in the medium. These high phosphate concentrations can induce dystrophic mineralization, which is often mis-identified as a marker for osteoblast differentiation

[109]. Despite low osteocalcin expression, characterization of these cells indicate that they behave in a similar fashion to previously published ADSC lines undergoing differentiation [33, 40].

Hierarchical Clustering of Genes Across Time Points in Differentiation

In order to gain more in-depth information on ADSC osteogenesis, gene arrays were performed at four time points spanning the differentiation process and compared to

138 undifferentiated ADSC (day 0). Genes clustered on the basis of similar expression patterns were displayed through the use of heat maps. This method of visualizing gene expression changes across time points allowed for a differentiation-specific profile to be created. Specifically, groups of genes which clustered together with similar expression patterns could be tracked across the differentiation process. By mapping gene ontology categories back to these gene clusters, patterns could be observed in the differentiation process.

Observed patterns indicated that the ADSC used in this work follow well-defined maturational phases of osteogenic differentiation [55]. The three stages are defined as 1) proliferation, 2) extracellular matrix development and maturation (matrix maturational phase), and 3) mineralization. High expression of cell cycle related genes at both day 3 and 10 indicate that the cells at these two time points are still in the proliferation phase of differentiation under normal osteogenic culture conditions. Although cell cycle related genes typically obscured other gene ontology categories, early signaling events associated with osteogenesis were also observed at day 3, indicating that the cells were responding to the osteogenic supplements through signaling pathways. One of the gene ontology categories observed at day 3 was BMP signaling.

The increase in expression of extracellular matrix related gene categories at days

10, 16, and 21 may indicate a switch to the onset of the matrix maturational phase of differentiation at day 10. This appeared to be followed by a complete switch to this phase at day 16 when the cells are no longer expressing cell cycle related genes.

Although the overlap observed at day 10 in proliferation and matrix maturation related genes may seem to conflict with defined maturational phases, cell heterogeneity may be a

139 contributing factor in the observation of overlap in these two phases. Nevertheless, previously published work on BMSC maturational phases indicate that a natural overlap exists as cells pass through the various maturational phases [55].

At days 16 and 21, genes associated with the ontology category skeletal system development are highly expressed and indicate that the cells may be making the switch to more mature osteoblasts or osteoprogenitors. A side-by-side comparison of gene array data with in vitro mineralization assays performed in Chapter 1 suggest that at day 21,

ADSC used in this work are just beginning to enter the mineralization phase as determined by the onset of quantifiable mineralization.

The differentiation-specific profile generated using clustering analysis and gene ontology searches fit well with the defined maturational phases of osteogenesis.

Visualization of how our time points fit with maturational phases is important for understanding the differentiation process observed in ADSC used for this work. Using a figure modified from Gary Stein and Jane Lian’s work, time points used for gene array analysis are mapped to the corresponding maturational phase of osteogenesis (Figure 1)

[55].

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Figure 1. Time points (red) in this work and how they relate to maturational phases observed in osteogenesis. Figure modified from Stein and Lian [55].

In addition to gene ontology categories observed across time points, an analysis of highly expressed bone-related genes is important in determining factors involved in

ADSC osteogenesis. Highly expressed genes which were present in the gene ontology category skeletal system development are listed in Chapter 1. Two genes which may be of specific interest in ADSC osteogenesis include TAZ (WW domain containing transcriptional regulator 1) and ROR2 (receptor tyrosine kinase orphan-like receptor 2).

TAZ may be an important component required for the activation of osteogenesis in ADSC. Specifically, MSC are understood to differentiate down the osteogenic lineage at the detriment of the adipogenic lineage in part through suppression of PPARγ by Wnt

β-catenin signaling[149-151]. While in the undifferentiated state, the cells are poised to enter either of these two pathways [28]. Minor changes in the microenvironment and/or signaling that these cells receive can shift the balance to favor one particular pathway

[28, 152]. At the divergence of the pathways are two transcription factors, RUNX2

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(osteogenic) and PPARγ (adipogenic), each thought to be vital for the individual lineages

[28]. TAZ co-activates RUNX2 dependant gene transcription while at the same time repressing PPARγ dependant gene transcription and therefore may be an important component in ADSC osteogenic lineage specification [89].

Another gene of interest observed in the skeletal system development gene ontology category highly expressed at days 16 and 21 is ROR2. ROR2 is a cell surface receptor that forms homodimers upon Wnt5A binding and results in downstream signaling events ultimately enhancing bone formation [92]. Specifically, Wnt5A has been implicated as an important component of ADSC osteogenesis [51]. Although canonical Wnt signaling is often implicated as being directly involved in the induction of

MSC osteogenic differentiation, non-canonical signaling through Wnt5A may be an important component of ADSC differentiation [91]. High expression of ROR2, as well as Wnt5A, during osteogenesis observed in Chapter 1 may implicate them in ADSC osteogenesis.

STEM Analysis of Genes Grouped by Expression Trends during Differentiation Revealed

Unique Gene Ontology Categories

Another method of grouping genes was performed using STEM software. Rather than defining singular expression events for a gene at a specific time point, genes were grouped based on similar expression trends during differentiation. This allowed for genes that otherwise may not be considered statistically significant when compared between two time points to be reported in the dataset as significant for having a specific expression trend [105, 106]. Rather than maturational phase information, STEM analysis

142 provided information on gene ontologies which were grouped together for changes in expression following similar patterns and tended to identify signaling pathways more readily than cell phenotype related ontology categories.

The importance of processes involved throughout differentiation was illustrated with this software. For example, categories observed for a decrease in expression throughout differentiation included BMP signaling and SMAD binding, each of which plays an important role in ―jump-starting‖ the differentiation process and might be expected to decrease with time as feedback loops begin to play a role in differentiation

[51]. Additionally, specific expression patterns related to MAP kinase and protein kinase activity may be of importance in the osteogenic differentiation of ADSC as well as in the progression from a stem like cell through the maturational phases to a mature osteoblast

[132, 153, 154].

Analysis of Highly Expressed Genes Reveal Similarities to Other ADSC and BMSC

Studies

Highly expressed genes during ADSC osteogenesis showed similar expression to previously published gene array studies focusing on MSC osteogenesis [66]. The similarity observed in the highest expressed genes underscored a common theme in

ADSC and MSC osteogenesis. Although these genes have been previously reported as being highly expressed during osteogenesis, few of them are implicated for a specific role in differentiation. Of interest for high expression in this work, as well as in other published studies, include CPM (carboxypeptidase M), FKBP5 (FK506 binding protein),

OMD (osteomodulin) and IGFBP2 [66].

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CPM is a membrane bound zinc-dependant protease [66]. High gene expression is observed in ADSC used for this work as well as in previously published studies [66].

Of interest may be CPM’s ability to bind and form a heterodimer with kinin B1 (a receptor commonly expressed in osteoblasts), which can lead to G-protein coupled receptor signaling [93]. G-protein coupled receptor activity was also observed in STEM analysis for having a profile with an increase in expression over the differentiation period.

FKBP5 codes for a binding protein that is highly expressed across all time points in ADSC differentiating to bone, both in this body of work and observed in other studies

[66]. Commonly used immunosuppressant NFAT (nuclear factor of activated T-cells), inhibitors of bone mass, regulate bone resorption processes [155]. One example of

NFAT inhibitors of bone mass is FK506 [156]. The FKBP5 protein is understood to bind

FK506 and may mediate calcineurin inhibition [157]. Activated through a glucocorticoid receptor [66], the dexamethasone (a glucocorticoid) induced osteogenic differentiation process may directly modulate this particular gene, which has been proposed to be vital in ADSC as well as BMSC osteogenesis [66].

OMD is an ECM keratan sulfate proteoglycan commonly found in bone [142].

High expression of OMD during osteogenesis is cited in several other studies and may be an important component of MSC osteogenesis [66]. Specifically, tyrosine sulfate domains within the proteoglycan have been reported to bind heparin binding proteins and may play a role in binding and sequestering of growth factors and cytokines which might mediate the differentiation process [142]. Other possible functions may include the mediation of cell attachment through RGD sequences and collagen fibril binding [28].

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IGFBP2 is highly expressed as well and is important in activating IGF-1/ AKT and β-catenin signaling pathways [158-161]. Specifically, heparin binding domains on

IGFBP2 may act independently to stimulate bone formation [161]. This activity may be independent of previously suggested roles in supporting bone formation by transporting

IGFs [158-160].

Adipogenic Marker Expression Indicates Cells may be Transdifferentiating

As mentioned previously, MSC in the undifferentiated state are often delicately balanced between the two lineages (osteogenic and adipogenic). With the correct stimulus, MSC can move down a particular lineage to the exclusion of the other pathway

[149-152]. However, in the case of commonly used in vitro differentiation protocols, dexamethasone (DX) is used as the inductive agent for both osteogenesis and adipogenesis [67]. Although the validity of using DX in osteogenic differentiation is questioned (for many reasons especially due to inhibition of bone formation observed in vivo), this protocol is still widely used and can induce most multipotent cells to undergo osteogenesis in vitro [162, 163]. The use of different concentrations of DX in both protocols may create microenvironmental variations in DX concentration depending on cell numbers and plating consistency. These variations may result in simultaneous differentiation down both lineages in the same culture dish.

Additionally, the mechanisms responsible for pushing MSC down a specific lineage are not completely clear, and various other factors might also induce adipogenic lineage specification. Cells differentiating down the adipogenic lineage reduce the number of cells available to undergo osteogenesis due to a loss of plasticity and

145 multipotential ability conferred on committed cells [10]. Therefore, transdifferentiation produces heterogeneous cultures of adipogenic and osteogenic cells. This may be counterproductive in tissue engineering and regenerative medicine applications and an insight into adipogenic marker expression can be helpful in determining whether a population of cells is homogenous in regards to the osteogenic lineage.

In Chapter 1, we observed differential gene expression of adipogenic markers.

Specifically, PPARγ, a master regulator and transcription factor required for adipogenic differentiation [28, 151], increases in expression until day 10 and then levels off. This expression pattern might indicate that there are some cells which are transdifferentiating down the adipogenic pathway. However, analysis of other transcription factors (C/EBPα,

C/EBPβ, C/EBPδ) reveals very little change in expression patterns throughout differentiation. Markers of mature adipocytes, fatty acid binding protein 4 (FABP4) and fatty acid synthase (FAS), showed ambiguous expression patterns. FABP4 displays an early increase in expression at day 3 but then levels off. However, FAS decreases substantially throughout differentiation. In summary, there is evidence to indicate that some ADSC are expressing adipogenic markers and may be transdifferentiating.

Two other genes of interest involved in adipogenesis were observed for an increase in expression during osteogenesis of cultures. Leptin and adipsin are adipokines that should be secreted by cells in the adipogenic lineage [67]. High expression of these two adipokines might indicate that cells are in fact transdifferentiating. However, in vivo a complex network of heterogeneous cell types in the marrow environment (where MSC reside) has shown that crosstalk exists between fat cells of the marrow and MSC [164,

165]. Adipokines secreted by these fat cells have been reported to affect osteogenesis

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[164, 166, and 167]. An increase in expression of adipokines observed here may indicate transdifferentiation. However, it is possible that adipokines secreted by these cells may actually be beneficial to the process of osteogenesis.

ECM-Related Gene Expression during Osteogenesis

The ECM is often overlooked in studies concerning MSC differentiation. The focus on extracellular or secreted modulators of osteogenesis is typically centered on cytokines and soluble growth factors which directly affect the process [168]. Changes occurring in ECM and ECM-related gene expression are often considered to be the cell’s attempt at re-creating the structural environment required for the specific tissue type [69,

72]. However, to view the ECM in this manner is similar to equating bone to a singular structural role in the body. Bone, like the ECM, is involved in many complex and important processes in addition to a playing vital role in structural integrity. By observing changes in ECM-related gene expression both of insoluble ECM components and soluble growth factors, we were able to create an osteogenic differentiation profile of

ECM-related genes.

The rationale behind observing ECM-related gene changes centers on the concept that secreted products often serve tissue-specific roles and/or roles in influencing cell behavior [69, 72]. Soluble growth factors typically demonstrate the capacity to influence cell behavior [80]. Insoluble ECM components are often considered tissue-specific and can aid in identifying a specific lineage depending on the extracellular proteins present

[69]. Some ECM components have known roles in binding and sequestering growth factors, as well as modulating their activity. Also of interest are matricellular proteins,

147 which are small insoluble proteins in the ECM, which do not play a role in structural processes but may influence cell behavior in a number of ways including regulating cell attachment [80].

In addition to the tissue-specific nature of ECM, much of what is observed in gene array analysis are housekeeping processes and intracellular signaling events associated with cell maintenance as well as processes such as proliferation (as observed at days 3 and 10 in this work). Although the presence of proliferation related gene categories helped to place the cells at a particular maturational phase, other cell processes that might be occurring at those time points were obscured by the vast number of cell cycle related genes. The creation of an ECM-related gene expression profile, should in theory, thin out these cell cycle related genes and potentially provide more insight into events occurring during those two time points.

By visualizing ECM-related gene expression with hierarchical clustering and heat maps, expression patterns throughout the differentiation process emerged. Gene ontology categories could then be mapped back to specific areas of high expression on the heat map. Day 3 showed similar results as previous whole transcriptome expression analysis described above. However, cell cycle related genes as well as SMAD binding were not included; indicating that visualizing expression with ECM related genes is a valid method for screening out intracellular events.

At day 10, several categories were present which did not show up in previous expression analyses. Specifically, TGFβ N-terminal, MSC differentiation, and skeletal system development all mapped to highly expressed ECM gene clusters at this time point.

Of interest may be genes in MSC differentiation and skeletal system development

148 categories. Expression analysis described above indicates that day 10 cells are beginning to move into the matrix maturational phase of osteogenesis. Genes which code for secreted products involved in MSC differentiation and skeletal system development at this time point may be important in modulating this transition.

Also observed in ECM-related gene expression at days 16 and/or 21 was IGF binding, Wnt signaling, and skeletal system development gene categories. IGFs are important modulators of osteogenesis [28]. The high expression of IGF binding-related genes may indicate a vital role in ADSC differentiation. Additionally, as stated previously, Wnts are a vital component of osteogenesis and high expression of Wnt signaling proteins as well as modulators of the Wnt signaling pathway would be expected to play an important role in ADSC osteogenesis [28].

Cell-Secreted Matrices Modulate ADSC Osteogenesis

In Chapter 2, ADSC differentiation down the osteogenic lineage in the presence of cell-secreted matrices is examined. Comparisons to cells induced to differentiate on tissue culture plastic (i.e. Control group; described in Chapter 1 and above) are made and used to support the hypothesis that ECM secreted by differentiating cells enhances osteogenic differentiation. Implications of this work may be important in creating more biologically relevant differentiation protocols and osteogenic biomaterials, as well as expanding current knowledge on factors affecting and/or driving osteogenesis in ADSC.

Several published studies indicate that BMSC are affected by ECM secreted during differentiation [73-76]. Reports of the most relevant time point for isolation of this ECM, however, are variable. In fact, three groups performing three separate studies

149 all describe different time points for optimal osteogenic activity of the ECM. In order to determine which time point was optimal for this work, we did an initial investigation of several time points across differentiation. This initial characterization, described in

Chapter 2, supported using ECM isolated from the midpoint in osteogenesis (day 16).

Specifically, undifferentiated cells seeded onto ECM from varying time points were induced to differentiate down the osteogenic lineage. After 21 days, mineralization as well as RUNX2 mRNA expression were analyzed. Heavy mineralization was deposited by cells seeded onto day 16 matrices. However, minimal mineralization was observed in cells seeded onto day 11 matrices. As indicated previously, calcium deposition (by cells grown in the presence of mineralization inducing medium) does not necessarily indicate an osteoblastic phenotype [109]. However, the extreme differences observed between cells seeded onto days 11 and 16 ECM were of interest, particularly because cells induced to differentiate on day 11 ECM did not mineralize heavily even after 30 days in culture.

Examination of RUNX2 mRNA expression in cells seeded onto ECM at varying time points indicated that increased calcium deposition did in fact correlate with increased RUNX2 expression of cells seeded onto day 16 ECM as well as ECM from time points after day 16. Likewise, cells seeded onto day 11 ECM and ECM prior to day

11 displayed similar or decreased levels of RUNX2 mRNA compared to Controls.

Subsequent experiments were performed using ECM from these two time points as comparisons, in addition to Controls on TCP (cells on day 16 ECM are referred to

Experimental 1 and cells on day 11 ECM are referred to Experimental 2).

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Single Gene Comparisons Indicate that ECM from Day 16 Enhances Osteogenesis

Brief comparison of Controls with Experimental 1 and 2 indicated that

Experimental 1 cells expressed osteogenic related genes much sooner and at higher levels than both the Control and Experimental 2. Specifically, osteopontin (OPN), osteoprotegerin (OPG), activating transcription factor 4 (ATF4), alkaline phosphatase

(ALP) and osteocalcin (OCN) were all analyzed. With the exception of ALP, each gene was upregulated sooner and at higher levels in Experimental 1 cells. ALP was the only gene which showed decreased expression. However, the typical expression pattern of

ALP is observed as a transient spike in mRNA [55], and without analyzing all days throughout differentiation it is not entirely certain that the spike was not missed. In addition, OCN as described above is an important gene for identifying mature osteoblasts

[55]. mRNA levels of OCN are highly expressed and correlate with an increase in OCN protein levels observed at day 30 in comparison to day 30 Control and Experimental 1.

This data, taken with earlier and increased mineralization of cells seeded onto day 16

ECM, indicates that the ECM is promoting osteogenic differentiation of these cells to create a more rapid and robust differentiation of the ADSC in culture.

Whole Array Clustering

Arrays were clustered on the basis of normalized whole array signals in order to observe how arrays grouped together and to get an idea of how similar groups were in comparison to one another. Specifically, individual treatment groups (i.e. Controls at all time points; Experimental 1 at all time points; Experimental 2 at all time points) were

151 most similar to each other, with the exception of some variability observed in

Experimental 2 replicates. Of interest was a closer relationship of Controls and

Experimental 1 groups to each other than to Experimental 2. This relationship may indicate that the microenvironments of these cultures are more similar than different, and as a consequence the cells are going down similar pathways in terms of lineage specification.

Hierarchical Clustering of Gene Array Data Revealed a Shift in Maturational Phases of Cells in Experimental 1

In order to gain more in-depth information on ECM-modulated osteogenesis, gene arrays were performed at four time points spanning the differentiation process and compared to undifferentiated ADSC (day 0) as described above for Chapter 1 Controls.

Genes clustered on the basis of similar expression patterns were displayed through the use of heat maps. In this way, differentiation-specific profiles could be created and compared to Controls. Specific details on how the differentiation process is modulated by ECM were identified.

Control cells follow a well established pattern of osteogenic maturational phases.

Time points chosen for this group are well matched to yield information on specific phases in differentiation. However, by keeping the same time points used in Controls, the shift in gene expression patterns observed in Experimental 1 make placing these cells at specific maturational phases more difficult. Specifically, similar to Control day 3,

Experimental 1 cells at day 3 express genes related to cell cycle ontologies and indicate that the cells are proliferating at this time point. In contrast to Controls, an attenuated proliferation period is observed as cell cycle related genes are not carried over into day

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10. The presence of skeletal system development gene categories expressed at day 10 however, indicate that the cells are much further along in the differentiation process than

Control cells at the same time point. Maintenance of skeletal system development related gene expression at days 16 and 21 indicates that the cells may be differentiating to more mature osteoblasts and/or that more cells in culture are undergoing the differentiation process.

Likewise, an examination of Experimental 2 gene clustering provides information to support the inhibition of osteogenesis. Much more variation is observed in gene arrays for these cells and gene ontology groups including immunoglobulin, smooth muscle cell proliferation and laminin G do not indicate that these cells are undergoing osteogenesis; at least not the majority of these cells.

As described for Control cells, an understanding of how Experimental 1 cells fit into the maturational phases of osteogenesis is an important part of understanding how the differentiation process has been modulated. By analyzing gene expression data alongside of mineralization and phenotypic changes occurring in vitro, time points in

Experimental 1 can be placed as described below in Figure 2 using a modified figure from Gary Stein and Jane Lian’s work [55].

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Figure 2. Time points how they relate to maturational phases observed in osteogenesis of Control group compared to Experimental 1 group. Figure modified from Stein and Lian [55].

In addition to gene ontology categories observed across time points, an analysis of highly expressed bone-related genes may be important in determining factors involved in

ADSC osteogenesis. Highly expressed genes which were present in the gene ontology category skeletal system development are listed in Chapter 2. Of interest may be the addition of skeletal system development genes not observed in Chapter 1 Controls.

Specifically, two genes show high expression in Experimental 1 group and not controls, cadherin 11, type 2 (CDH11) and odd skipped-related 2 (OSR2).

Cadherin 11, often referred to as osteoblast cadherin, is highly expressed in osteoblast cells [119]. CDH11 has been observed as being upregulated in MSC undergoing osteogenesis and may play an important role in osteogenic lineage

154 commitment rather than adipogenesis in MSC [95]. Cell-cell interactions, which are mediated by CDH11, have been reported to enhance MSC differentiation down the osteogenic lineage [120]. High expression of CDH11 in Experimental 1 cells may be an important factor involved in the differentiation process observed in this group.

OSR2 is a zinc finger transcription factor. Little is known about the downstream factors modulated by OSR2. However, this gene has been implicated primarily in tooth development [127]. More recently however, OSR2 has been identified as a transcription factor involved in regulating osteoblast proliferation [125]. The increased expression of

OSR2 in Experimental 1 cells may implicate it as a factor important in the enhanced osteogenesis observed in this work.

STEM Analysis Revealed Unique Gene Ontology Categories Which Reveal More In-

Depth Differences between Controls and Experimental Groups

Another method of grouping genes was performed using STEM software as described for Chapter 1 Controls. Rather than defining singular expression events for a gene at a specific time point, genes were grouped based on similar expression trends during differentiation. Specifically, STEM analysis provided information on gene ontologies that were grouped together for changes in expression following similar patterns.

Of interest in Experimental 1 were the ontology categories related to signaling events. Similar to Controls, MAP kinase signaling was found to be associated with an expression profile for Experimental 1. Additionally, EGF signaling, JAK-STAT, and

Wnt signaling related categories were present, all of which can be implicated in

155 osteogenesis [51, 169, 170]. Also of interest was the category heparin binding. Heparin binding domains are found in many signaling pathway proteins [171, 172]. Some of the more notable pathways and proteins which are affected by heparin binding include EGF,

IGFBP2, and Wnts (all of which are observed in this work) [161, 172-175].

In Experimental 2, many previously unidentified categories were revealed.

Unfortunately, an overall understanding of what is occurring in cells from Experimental 2 still remains elusive with STEM analysis. Categories including negative regulation of

MAPK, skeletal, muscle, fat, and kidney development, toll-like receptors, among others, were clustered into defined profiles. The only conclusion that can be made with STEM analysis from Experimental 2 is that the cells do not display gene ontologies and pathways similar to Controls and Experimental 1.

Venn Diagrams Reveal Uniquely Expressed Genes and Shared Genes between Groups

Venn diagrams were used as a tool to group genes into categories based on whether they were shared across experimental conditions or individually expressed under one experimental condition. By making comparisons to day 0, significant and enriched genes for each time point were identified and used in Venn diagram analysis. The data obtained from these comparisons provided an interesting look at overall trends observed between groups, as well as genes which were expressed individually in specific categories.

Analysis of shared genes between all three groups revealed group divergence. At day 3, a high number of genes were shared between the groups. However, as differentiation progressed, the number of shared genes decreased until a limited number

156 of genes, likely involved in housekeeping related functions, were shared at days 16 and

21. Similar to observations made in whole array clustering as described earlier, a large number of genes were shared between the Controls and Experimental 1 group throughout differentiation. This may support the postulate that the Control group and Experimental 1 group are more similar. Likewise, Experimental 2 shared a much smaller number of genes with the other two groups.

Also of specific interest were genes which were expressed solely in one group at a particular time point. By searching gene ontologies related to these individual groups of genes, unique events associated with only that group could be described. Of extreme interest was the presence of embryonic skeletal system morphogenesis related genes solely expressed at day 3 in Experimental 1. Many of these genes can be implicated in early embryonic limb development as well as bone formation and patterning. Upon closer examination, these genes appeared to be unique to Experimental 1 throughout differentiation, and may be a key component in the ECM modulation of osteogenesis observed in this group.

Analysis of Highly Expressed Genes Reveal Similarities to Controls and Important

Differences in Highly Expressed Experimental 1 Genes

Analysis of the most highly expressed genes at all time points in Experimental 1 and 2 were compared to Control genes discussed above and listed in Chapter 1. Some similarities existed between the datasets. However, there were some differences that may be important in defining how osteogenesis was affected by the ECM.

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Similar high expression of FKBP5, OMD, and CPM was observed in

Experimental 1 compared to Controls. As discussed previously, these three genes may play a key role in MSC osteogenic differentiation. However, several genes were observed as being highly expressed in Experimental 1 that were not found at as high levels in Controls; KIAA0101, PRELP, and dermatopontin (DPT) are a few of them.

KIAA0101 is a thyroid associated gene highly expressed at day 3 in Experimental

1. This gene may be important for its role in regulation of F box protein turnover. F box proteins can play a role in β-catenin degradation, an important protein involved in Wnt- induced bone formation [138, 139]. High expression of KIAA0101 in Experimental 1 may have important implications for modulating Wnt signaling in these cells.

PRELP, a leucine rich repeat (LRR) protein found in cartilage, is expressed at high levels in growth plates and has heparin binding domains which are often observed in bone-related ECM proteins and are highly represented in this dataset [143]. PRELP has been implicated in promoting osteogenesis as well as in the inhibition of osteoclastogenesis and may represent an important component of Experimental 1 osteogenesis [144].

Dermatopontin was identified as being highly expressed at day 21 in

Experimental 1 and may be of specific importance in these experiments. DPT may be an important component of the ECM on which Experimental 1 cells were cultured as discussed in Chapter 3. Due to a known role as a downstream vitamin D receptor (VDR) target, as well as a proposed role in modulating cellular response to ECM and growth factors, DPT may be an important factor in modulating osteogenesis observed in

Experimental 1 [81-87].

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Experimental 2 highly expressed genes revealed very little similarity to the other two groups. Of note however, were highly expressed genes involved in inflammatory and immune responses.

Adipogenic Marker Expression in Experimental 1 and 2 Groups

As discussed previously, adipogenic marker expression may reveal whether cells in culture are transdifferentiating down the adipogenic lineage. Although it was expected that adipose related genes would decrease in Experimental 1 cells due to increased osteogenic genes, this was not observed. PPARγ did decrease over time in culture of

Experimental 1 cells compared to the Controls. However, other adipogenic markers typically displayed either increased expression or similar expression patterns as Controls.

ECM-Related Gene Expression in Experimental 1 and 2

As discussed previously, the identification of ECM-related gene profiles during lineage specification may reveal important events in differentiating cells. Although most gene categories identified in this manner were not new, many of the previously identified categories were more significantly enriched. Additionally, separate analyses described above including hierarchical clustering, STEM analysis, and Venn diagrams, each revealed unique gene ontology categories. However, many of these categories were present in ECM-related gene profiling, indicating that ECM-related gene profiling may be highly relevant for use in determining cell lineages and pathways in differentiation.

The presence of bone-related categories at day 3 in ECM-related gene expression confirmed Venn diagram analysis of skeletal related genes present in Experimental 1 at

159 this early time point. Similar to Controls, various signaling related categories, which might be essential in cell behavior, were also observed here. Some of these categories included IGF binding, EGF-like, Wnt signaling, heparin binding, EGF calcium binding,

JAK-STAT, TGFβ, and Frizzled.

As observed previously for Experimental 2, varied gene ontology groups represented the time course. Although some of the ontology groups could be linked to having relevance to osteogenesis (skeletal system development), conflicting gene ontologies were also observed include epithelial cell differentiation, blood vessel development, and erythrocyte differentiation pathway. Firm conclusions cannot be made about the exact nature of Experimental 2 cultures over the time course. However, one observation may warrant a closer look at the behavior of cells in Experimental 2 for follow-up experiments.

Specifically, as noted in the whole array clustering performed in Chapter 2, the later time points in Experimental 2 are much closer to the undifferentiated ADSC (day 0) cells in terms of hierarchical clustering on overall gene expression patterns. Also observed, in arrays performed on undifferentiated ADSC, was the expression of many cell lineage-related genes. For example, osteopontin and osteoprotegerin were observed at fairly high expression levels at day 0. Other lineage specific genes expressed at day 0 could be mapped to differentiation pathways including muscle cell differentiation, nerve cell differentiation, adipocyte differentiation, epithelial cell differentiation, and kidney development. Some MSC literature suggests that multipotential cells reside in a state of

―readiness‖ where they are primed to undergo lineage specification down a number of pathways [10, 176-179]. While in this state, they transiently express lineage specific or

160 lineage related genes, in preparation for differentiation [176-179]. While Experimental 1 cells were grown on ECM secreted by committed osteoprogenitors (as identified through maturational phase determination), Experimental 2 cells were grown on ECM secreted by proliferating cells which may not have been committed down the osteogenic lineage.

Therefore, the similar expression patterns observed in undifferentiated ADSC and cells in

Experimental 2 might indicate that some of these cells may be remaining in the undifferentiated state; sustained through growth on the ―proliferation‖ ECM. More in- depth studies however, would need to be performed to determine the maintenance of an undifferentiated state in Experimental 2 cells.

Dermatopontin in the Extracellular Matrix Enhances Osteogenic Differentiation of

ADSC

ECM-related gene profiles during osteogenesis may reveal a more in-depth understanding of events surrounding lineage specific differentiation. In Chapter 2 we describe enhanced osteogenic differentiation on day 16 matrices. A closer examination of ECM-related genes expressed differentially between days 11 and 16 in the Controls

(cells which secreted the ECM) revealed important components of the day 16 matrices.

Specifically, dermatopontin was identified as being highly expressed at day 16 compared to day 11.

Dermatopontin (DPT) is an extracellular matrix (ECM) component of many tissue types. DPT acts largely as a mediator between the cell and the extracellular environment

[81-87]. Functional roles attributed to DPT include binding, possible modulation of the

161 activity of BMPs and TGFβ, cell adhesion, collagen and fibronectin fibril formation, as well as roles in cell proliferation [81-87].

A working hypothesis in Chapter 2 is that a direct correlation may exist between

ECM-related genes expressed at a particular time point and the corresponding activity of the secreted and entrained proteins from that same time point. We observed high gene expression of DPT in ADSC induced to differentiate down the osteogenic lineage, particularly at day 16 where the deposited ECM was shown to have enhanced osteogenic properties. High expression of DPT at day 16 in Controls was supported by high gene expression of DPT shifted to an earlier time point in Experimental 1 cells (as observed for most osteogenic genes in this group). In Experimental 1 cells, an increase in expression of DPT was observed at day 10, indicating that the gene followed patterns similar to other important osteogenic genes in Experimental 1.

In Chapter 3 we tested whether DPT played a role in the enhanced differentiation observed when cells were seeded onto day 16 matrices (i.e. matrices which should contain DPT) by overexpressing the DPT gene in ADSC using stable lentiviral infection.

ADSC overexpressing the gene for DPT (ADSC_DPT) were then induced to differentiate down the osteogenic lineage. ADSC_DPT were used for two purposes: to collect RNA following the differentiation period, and to isolate ECM at day 16 (which should contain high levels of DPT protein). Isolated ECM from cells overexpressing DPT (DPT_ECM) was reseeded with undifferentiated ADSC and the cells induced with osteogenic supplements. Differentiation down the osteogenic lineage of ADSC_DPT and undifferentiated ADSC reseeded onto DPT_ECM was characterized for modulation of the differentiation process.

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Overexpression of Dermatopontin in ADSC Inhibits Expression of Bone Related Genes

ADSC_DPT cells induced to differentiate displayed a dramatic decrease in osteogenic genes RUNX2, osteocalcin, TAZ and Wnt5A compared to Controls and to cells infected with a lentiviral vector containing ZsGreen without the DPT gene insert.

The observation that lentiviral infected cells without DPT can be induced to express osteogenic markers reveals that the infection and viral insertion alone did not tax the cells to the extent that they could not differentiate. However, it would seem that the overexpression of DPT does alter the cells and somehow inhibits them from differentiating. Possible reasons for this may be the stress induced by overexpressing a secreted protein that might negatively affect the differentiation process in these cells; however no precedent for this in published literature could be found. Other potential reasons, would need further investigation, however feedback loops may exist which might cause shut off of the vitamin D receptor (VDR) and it’s downstream products

(VDR was identified as an upstream receptor involved in DPT production) [82].

Dermatopontin in the ECM Enhances Osteogenic Differentiation of ADSC

After observing severe downregulation of osteogenic genes in ADSC_DPT cells, we expected to see similar results in cells seeded onto ECM containing super-abundant amounts of DPT (DPT_ECM). However, cells seeded onto DPT_ECM and induced to differentiate displayed significant increases in the osteogenic genes selected for analysis.

Comparisons were made to Controls as well as to Experimental 1 cells. In general, cells seeded onto DPT_ECM displayed significant increases in osteogenic markers compared

163 to both these groups. The addition of another control group also supported these observations. ECM was isolated from cells infected with the lentiviral vector containing

ZsGreen without the DPT gene insert. Undifferentiated cells were seeded onto this ECM and induced to differentiate. This group, in all respects, should mirror results from

Experimental 1, as long as lentiviral insertion into the cells did not have an effect on the

ECM. As expected, similar expression patterns were observed between this group and

Experimental 1 cells. These results indicate that DPT may be an important component of day 16 matrices and may play a vital role in the enhancement of osteogenesis observed in

Chapter 2 for cells seeded onto day 16 matrices.

CONCLUSIONS

The identification of networks and genes important in ADSC osteogenesis is a vital component of pushing these cells closer to the clinic. However, an ingrained limitation to tissue engineering and regenerative medicine therapeutics (which would use

ADSC) is the lack of appropriate environmental signals which are disturbed upon removal of cells from their natural environment. Also a limitation to the use of MSC and therefore ADSC is the inability to replicate in vitro results with in vivo results [28] which ultimately can be traced to the extremely different microenvironments observed by these cells [10, 28].

In this study, we discuss ADSC osteogenic differentiation under commonly utilized differentiation conditions. However, we also attempt to replicate a more

164 appropriate microenvironment by growing these cells on ECM. The ECM may be a important factor in modulating MSC stem cell behavior as determined in other cell types

[70, 180-182]. The obvious benefits of providing a source of outside-in signaling as well as a substrate for these cells to attach to and migrate on is underscored by the enhanced differentiation observed in Chapter 2. Additionally, enhanced osteogenic differentiation observed when ADSC were cultured on Dermatopontin-containing ECM, suggests that

DPT may be an important modulator of osteogenesis. Ultimately, studies such as these will be vital as tissue engineering and regenerative medicine applications attempt to re- create in vivo environments ex vivo.

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APPENDIX 1

ADSC ISOLATION

(Photos kindly provided by Dr. Thaleia Teli)

Adipose tissue PBS washing  Mince Tissue  obtained from elective abdominoplasty 

Digest, equal volume Centrifuge, aspirate Pass cell suspension collagenase I  floating through 100µm and cake and supernatant  40µm strainer

Figure 1_A1. ADSC isolation procedure.

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APPENDIX 2

ADSC Flow Cytometry Characterization (data kindly provided by Dr. Thaleia Teli)

Figure 1_A2. ADSC Line #2, passage 2 flow cytometry results.

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ADSC Line #s 1, 2, and 3 cell surface markers characterized through flow cytometry expressed below using percentage of cells positive for each marker. Lines 1, 2, and 3 were used for experiments with #2 representing the majority of experiments, and #1 & #3 used in confirmation experiments.

Marker Line #1, p2 Line #1, p5 Line #2, p2 Line #2, p4 Line #3, p2 CD13 99.72 98.43 96.9 89.5 97.54 CD29 2.57 0.96 2.96 0.07 0.12 CD14 2.96 0.22 1.06 0.02 0.08 CD44 99.51 99.0 96.34 78.95 94.83 CD45 13.54 0.31 1.09 0.34 10.64 CD73 98.6 82.03 88.31 0.56 79.05 CD105 99.66 97.94 95.45 69.96 92.76 CD166 88.08 48.27 48.85 0.66 12.82 Vimentin 43.26 1.69 24.41 0.3 3.01 Table I_A2. Percentage of ADSC expressing MSC-related markers at various passage numbers in the ADSC Lines #1, #2, and #3.

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APPENDIX 3

ECM: Characterization of day 11 and day 16 differential protein content using 2D gel

electrophoresis, LC/MS/MS, and Mascot searches.

Materials and Methods

Isolation of ECM for Characterization and Analysis

Re-seeding experiments, revealed stark contrasts in osteogenic capacity of ECM secreted at day 11 in osteogenesis and day 16 in osteogenesis with the latter time point displaying enhanced osteogenic potential. ECM characterization was performed using these two time points as comparisons due to their opposing effects on the differentiation process.

Decellularization of Cells in Culture: Cells were removed from dishes as described on in Materials and Methods (Sigma Kit and Lysis protocol). However, extensive washing was added both at the beginning of each protocol prior to cell removal and at the end of the protocol following removal of cells. DNAse and RNAse treatments were not performed. Washing included 2x serum free medium washes, 2x PBS washes, and 2x nano-pure H2O washes (H2O washes only after cell removal). Washing was vital in order to remove serum proteins present (FBS in media) in culture which acted to obscure endogenous ECM proteins in downstream applications. Following cell removal and wash steps, ECM was scraped off, desalted, and washed with acetone/trichloracetic acid (TCA). The resulting protein pellet was dissolved using 8M urea, 3% CHAPS, and

100mM DTT (Rehydration Buffer, Bio-Rad). ECM in solution was centrifuged and the soluble supernatant used for downstream applications.

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Soluble Fraction Protein Concentration Determination: To verify appropriate protein concentrations of soluble fractions for downstream 2D electrophoresis, protein concentration was determined using Peterson’s Modified Lowry method of total protein quantification [1].

2D Gel Electrophoresis: The BioRad Protein 2-D gel electrophoresis system

(BioRad Laboratories) was used. ECM samples from day 11 ECM and day 16 ECM in rehydration buffer were loaded onto ReadyStrip IPG isoelectric focusing strips.

Isoelectric focusing and the second dimension SDS polyacrylamide gel electrophoresis were conducted according to the manufacturer’s instructions. Gels were stained with

Bio-Safe stain and the de-stained gels scanned using a flat bed digital scanner. Gel images were analyzed for differentially distributed protein spots. Spots not common in the ECM preps or showing differential expression were further characterized by digestion and ion trap mass spectrometry.

In-Gel Digestion of Gel Plugs from 2D Gels: This method was adapted for digestion of small pieces of polyacrylamide gels from either 1D or 2D gels that have been stained with Coomassie blue, silver, or Sypro Ruby. The gel pieces were typically less than 3mm in diameter. All work was performed in a laminar flow hood supplied with

HEPA filtered air. All equipment and reagents within the hood were handled carefully with gloved hands and personal protective equipment to minimize exposure of the samples to environmental keratin. Following reduction and alkylation of proteins in the gel pieces, trypsin was added in an ammonium bicarbonate buffer to digest the proteins for up to 24 hours. Peptides from the digestion were extracted using acetonitrile

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(CH3CN) in 5% formic acid and concentrated to approximately 20μL prior to analysis by mass spectrometry.

Ion Trap Mass Spectrometry: Peptides obtained from in-gel digestion and multidimensional chromatography were subjected to electrospray ionization mass spectrometry individually using a non-electrospray ionization source on a Bruker Esquire

HCT ion trap mass spectrometer. Peptides were separated by reverse phase chromatography using 0.05% formic acid as the aqueous mobile phase and CH3CN as the mobile phase modifier. As analytes elute from the reverse phase column, they are sprayed directly into the source of the ion trap and analyzed. All mass spectra were searched against the most currently available protein sequence databases using Mascot

(Matrix Science, Ltd.) operated on an in-house Dell server. Analysis of ECM proteins separated by 2D gels was used to identify changes in protein expression patterns under experimental conditions. The overall strategy is similar to that reported by Taniguchi et. al. [2], wherein protein expression changes including single phosphorylation events were discerned between groups.

Results

2D gel analysis of protein isolated from day 11 and day 16 in ADSC osteogenesis revealed differential protein banding (Figure 1_A3). Spots selected from the gels and subjected to tryptic digestion followed by LC/MS/MS and Mascot searches revealed several key differences in proteins present at the time points. Table I_A3 lists identified proteins from the labeled areas for each 2D gel. Of interest is the increase in collagen banding observed in boxes A and B at day 16 when compared to day 11. This increase in

190 collagen corresponds with results presented in Chapter 1 indicating that cells at day 16 in differentiation are within a matrix maturational stage of osteogenesis where key matrix components are being expressed and deposited in the form of unmineralized osteoid.

Additionally, the presence of histone H4, a commonly used marker of proliferation at day

11 may indicate that the cells are within the proliferation phase of osteogenesis at that time point. Day 16 did not show protein banding at the histone H4 location which would fit with the concept that these cells have passed out of the proliferation phase.

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Day 11 ECM

A B

Day 16 ECM

A B

Figure 1_A3. 2D gels of ECM isolated from day 11 and day 16. Labeled boxes indicate areas of differential spot analysis. Isoelectric focusing was performed on IPG 3- 11 strips and subsequent SDS-PAGE gels were 12% Tris/HCl.

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Labeled Box MS/MS and Mascot Identification

A Prepro alpha 2 type I collagen, Collagen type I B Prepro alpha (1) collagen, Collagen type I alpha 2 isoform CRA b C Histone H4, Similar to histone H4 Table I_A3. Mascot identification of differential spot analysis from 2D gels.

REFERENCES

1. Peterson, G. L. 1977. A simplification of the protein assay method of Lowry et al. which is more generally applicable. Anal. Biochem. 83:346-356.

2. Taniguchi, T., I. Garcia-Higuera, B. Xu, P. R. Andreassen, R. C. Gregory, S. T. Kim, W. S. Lane, M. B. Kastan, and A. D. D'Andrea. 2002. Convergence of the fanconi anemia and ataxia telangiectasia signaling pathways. Cell. 109:459-472.

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APPENDIX 4

QPCR Confirmation of Genes Identified Through Gene Analysis

A Relative RUNX2 Expression 150 Line 1 * Line 3 100 Line1_RS_16ECM Line3_RS_16ECM

50 Fold Change Fold

Day 10Day 21 Day 10Day 21 Day 10Day 21 Day 10Day 21 Days in Culture

B Relative ALP Expression 15 Line 1 Line 3 * 10 Line1_RS_16ECM Line3_RS_16ECM

5 Fold Change Fold

* 0

Day 10Day 21 Day 10Day 21 Day 10Day 21 Day 10Day 21 Days in Culture

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Relative OCN Expression C 15 Line 1 Line3 10 Line1_RS_16ECM Line3_RS_16ECM

5 Fold Change Fold

Day 10Day 21 Day 10Day 21 Day 10Day 21 Day 10Day 21

Figure 1_A4. QPCR confirmation of Lines 1 & 3 on TCP and day 16 ECM for RUNX2 (A), ALP (B), and Osteocalcin (C). mRNA is quantified relative to the level of housekeeping gene 18s RNA. Bars represent time points for Lines 1 and 3 and are expressed as mean fold change of 3 replicates normalized to day 0 control. Error bars are displayed with standard deviation (SD). Statistical significance was determined with two way ANOVA and Bonferroni’s post hoc analysis. Significance for each group is denoted with * and equals p≤0.05 compared to same time point ADSC cell line on TCP.

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Relative Sortilin Gene Expression 100 * Controls_TCP 80 D16ECM

40 Fold Change Fold 20