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Characterization and modulation of adult pancreatic β-cell maturity Szabat, Marta 2010

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 CHARACTERIZATION AND MODULATION OF ADULT PANCREATIC β-CELL MATURITY  by  Marta Szabat   B.E.Sc., B.Sc., The University of Western Ontario, 2004   A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  DOCTOR OF PHILOSOPHY in The Faculty of Graduate Studies (Genetics)   THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  August 2010   © Marta Szabat, 2010   ii ABSTRACT  The functional maturation and dedifferentiation of β-cells is central to diabetes pathogenesis and to β-cell replacement therapy. Despite its importance, the dynamics of adult β- cell maturation remain poorly understood because it has previously been difficult to study the process directly. A novel dual fluorescent reporter lentiviral vector was developed capable of tracking the differentiation status of single β-cells in culture. Using this labeling tool, an immature β-cell state was identified in adult primary human and mouse islets and β-cell lines. The immature β-cell state was characterized by Pdx1 promoter activity but undetectable insulin promoter activity. Lineage analysis of labeled single adult human, mouse and MIN6 β-cells revealed that a fraction of the immature β-cells underwent maturation over time in culture by robustly activating the insulin promoter. Immature β-cells also exhibited a significantly downregulated profile of mature β-cell genes. These cells had increased proliferation and a reduced glucose-stimulated insulin secreting function. In order to manipulate the adult β-cell maturation state, a screen for candidate growth/differentiation factors using image-based approaches was performed. Activin A and its antagonist follistatin were found to modulate adult β-cell maturity. Activin A had a strong negative effect on β-cell maturity, reducing insulin promoter activity, insulin secretion and the expression of mature β-cell genes. Follistatin reversed the effects of endogenous activin A and augmented β-cell maturity. These results uncovered a local autocrine/paracrine regulatory mechanism that controls the maturation state of adult β-cells. In addition, gene expression profiling at the whole genome level was used to analyze purified immature and mature β-cells from humans, mice and the MIN6 β-cell line. These analyses revealed that immature β-cells have increased expression of multiple islet hormones and have enriched expression levels of many genes known to be involved in pancreatic development, stem cell plasticity, proliferation and apoptosis. Conversely, mature β-cells are enriched in genes related to maintaining the mature β-cell phenotype. Collectively, these experiments contribute to the understanding of maturation and plasticity of adult pancreatic β- cells. The results have significant implications for islet regeneration and for in vitro generation of functional β-cells to treat diabetes.       iii  TABLE OF CONTENTS  Abstract ........................................................................................................................................... ii Table of Contents ........................................................................................................................... iii List of Tables ................................................................................................................................ vii List of Figures .............................................................................................................................. viii List of Abbreviations .......................................................................................................................x Acknowledgements ........................................................................................................................ xi Dedication ..................................................................................................................................... xii Co-authorship statement .............................................................................................................. xiii 1          Introduction ..........................................................................................................................1 1.1  Characterization of Functional Mature β-Cells .............................................................2   1.1.1  Molecular markers of mature β-cells .................................................................3   1.1.2  Adult β-cell heterogeneity .................................................................................4   1.1.3  Loss of functional β-cell maturity ......................................................................5  1.2  Maintenance of β-Cell Function ....................................................................................6   1.2.1  Role of transcription factors in β-cell function ..................................................7   1.2.2  Major signaling pathways regulating β-cell maturity ........................................8   1.3       Developmental Biology of the Pancreas ........................................................................9        1.3.1 Prenatal and postnatal β-cell maturation ..........................................................11   1.3.2       Adult β-cell maturation ....................................................................................12 1.4  Generation of Alternative β-Cell Sources ....................................................................12   1.4.1  Plasticity of mature pancreatic cells ................................................................12   1.4.2  In vitro and in vivo stem/progenitor cell-derived β-cells .................................13   1.4.3  Proliferation of adult β-cells ............................................................................14   1.4.4  Growth and differentiation factors for in vitro β-cell generation ....................15   1.5  New Tools for the Study and Generation of β-Cells ...................................................16   1.5.1  High-throughput screening and statistical design of experiments ...................16   1.5.2  Lineage tracing and labeling of cells ...............................................................17   1.6  Thesis Objectives .........................................................................................................18   1.7  References ....................................................................................................................20   iv 2  Maturation of Adult β-Cells Revealed by a Pdx1/Insulin Dual Reporter Lentivirus ........38   2.1  Introduction ..................................................................................................................38   2.2  Materials and Methods .................................................................................................39   2.2.1  Construction of lentiviral vectors, lentivirus production and infection ...........39   2.2.2  Cell culture and transfection ............................................................................39   2.2.3  Flow cytometry ................................................................................................40   2.2.4  Quantitative real-time RT-PCR .......................................................................41   2.2.5  Fluorescence microscopy and Ca2+ imaging ....................................................41   2.2.6  5-Bromo-2’-deoxyuridine (BrdU) labeling ......................................................41   2.2.7  Insulin secretion ...............................................................................................41   2.2.8  Data analysis and ethics ...................................................................................42   2.3  Results ..........................................................................................................................42   2.3.1  Heterogeneous Pdx1 and insulin gene expression in cultured human and mouse islet cells ...............................................................................................42   2.3.2  Cell fate tracking: maturation of Pdx1+/Inslow into Pdx1+/Ins+ cells................44   2.3.3  Gene expression profiling of β-cell maturation states .....................................48   2.3.4  Glucose responsiveness of mature and immature MIN6 β-cells .....................49   2.4  Discussion ....................................................................................................................49   2.5  References ....................................................................................................................55 3  Reciprocol Modulation of Adult β-Cell Maturity by Activin A and Follistatin ................59   3.1  Introduction ..................................................................................................................59   3.2  Materials and Methods .................................................................................................60   3.2.1  Cell culture .......................................................................................................60   3.2.2  Lentiviral vector production and infection ......................................................60   3.2.3  Screening and factorial design of experiments ................................................61   3.2.4  Flow cytometry and cell sorting ......................................................................61   3.2.5  Quantitative real-time RT-PCR .......................................................................62   3.2.6  5-Bromo-2’-deoxyuridine (BrdU) labeling ......................................................62   3.2.7  Hormone secretion ...........................................................................................62   3.2.8  Data analysis ....................................................................................................63  3.3  Results ..........................................................................................................................63   3.3.1  Screening for factors that modulate adult β-cell maturity ...............................63   3.3.2  Activin A reduces β-cell maturity ....................................................................66   v   3.3.3  Activin A decreases expression of insulin and mature β-cell genes ................66   3.3.4  Activin A increases β-cell proliferation ...........................................................67   3.3.5  Activin A decreases insulin secretion ..............................................................69   3.3.6  Follistatin reverses the effects of activin A ......................................................71  3.4  Discussion ....................................................................................................................71   3.5  References ....................................................................................................................77 4  Gene Expression Profiling and Lineage Tracing of Adult β-cell Maturation ....................81   4.1  Introduction ..................................................................................................................81   4.2  Materials and Methods .................................................................................................83   4.2.1  Cell culture, lentiviral vector production and infection ...................................83   4.2.2  Lineage tracing.................................................................................................83   4.2.3  Intraductal lentivirus injections ........................................................................84   4.2.4  Fluorescence activated cell sorting ..................................................................85   4.2.5  RNA extraction, cRNA generation and labeling and hybridization to to Illumina BeadChips .....................................................................................85   4.2.6  Microarray data analysis ..................................................................................86   4.2.7  Quantitative real-time RT-PCR .......................................................................86   4.2.8  Data analysis ....................................................................................................86  4.3  Results ..........................................................................................................................87   4.3.1  β-Cell maturation stages in vivo ......................................................................87  4.3.2  Lineage tracing of adult β-cell maturation .......................................................88   4.3.3  Analysis of gene expression profiles of immature and mature adult β-cells ...88   4.3.4  Immature adult β-cells have enriched expression levels of islet hormones and select genes involved in development, proliferation and apoptosis ..........92  4.3.5  Function-related genes are abundant in mature adult β-cells ..........................95   4.3.6  Defining the genetic profiles of adult β-cell maturation states ........................96   4.4  Discussion ....................................................................................................................99   4.5  References ..................................................................................................................107 5  Conclusions and Future Directions ..................................................................................115   5.1  Conclusions ................................................................................................................115   5.2  Future Directions .......................................................................................................122   5.3  References ..................................................................................................................126   vi Appendix A ..................................................................................................................................131 Appendix B ..................................................................................................................................138 Appendix C ..................................................................................................................................151 Appendix D ..................................................................................................................................170                                            vii  LIST OF TABLES  Table 4.1  A subset of differentially expressed genes selected based on known function From human, mouse and MIN6 microarrays .........................................................93 Table 4.2  Summary of microarray and qRT-PCR results for differentially expressed islet hormone genes ................................................................................................95 Table 4.3  Summary of expression patterns of all genes belonging to the solute carrier family differentially expressed in individual human, mouse and MIN6 microarrays.......96 Table 4.4  List of genes whose expression was investigated by qRT-PCR ............................98 Table A1  Pancreatic tissue donor information.....................................................................133 Table A2  Primers used in this study ....................................................................................133 Table B1  Growth and differentiation factors used in factorial experiments .......................143 Table B2  Factorial design factor combinations (factorial 1) ...............................................144 Table B3  Factorial design factor combinations (factorial 1) ...............................................147 Table B4  Primers used in this study ....................................................................................150 Table C1  Primers used in this study ....................................................................................151 Table C2  Differentially expressed genes from purified primary adult immature  Pdx1+/Inslow and mature Pdx1+/Ins+ mouse β-cells ..............................................153 Table C3  Differentially expressed genes from purified primary adult immature  Pdx1+/Inslow and mature Pdx1+/Ins+ human β-cells .............................................154 Table C4  Differentially expressed genes from purified primary adult immature Pdx1+/Inslow and mature Pdx1+/Ins+ MIN6 β-cells ..............................................164                 viii LIST OF FIGURES  Figure 1.1  Illustration of an islet of Langerhans .......................................................................3 Figure 2.1  Heterogeneous expression of insulin and Pdx1 in adult β-cells ............................43 Figure 2.2  Conversion of Pdx1-only cells to Pdx1/insulin-positive cells without division ....45 Figure 2.3  Short-term phenotypic fate tracking of sorted β-cells............................................46 Figure 2.4  Long-term phenotypic fate tracking of sorted β-cells ............................................47 Figure 2.5  Gene expression analysis of Pdx1+/Inslow and Pdx1+/Ins+ β-cells .........................48 Figure 2.6  Glucose responsiveness of mature and immature MIN6 β-cells ...........................50 Figure 3.1  Screening for factors that modulate adult β-cell maturation .................................65 Figure 3.2  Activin A decreases insulin expression and reduces maturation of immature  adult β-cells ............................................................................................................66 Figure 3.3  Activin A decreases expression of mature β-cell genes ........................................68 Figure 3.4  Activin A increases β-cell proliferation .................................................................69 Figure 3.5  Activin A decreases insulin secretion ....................................................................70 Figure 3.6  Follistatin increases expression of insulin gene and other mature β-cell genes ......................................................................................................................72 Figure 3.7  Follistatin reverses the effects of activin A on insulin secretion ...........................73 Figure 4.1  Heterogeneous β-cell maturity in primary mouse and human islets and MIN6 cells .............................................................................................................85 Figure 4.2  Confocal imaging of in vivo labeled mouse islets .................................................87 Figure 4.3  Lineage tracing of adult β-cell maturation .............................................................90 Figure 4.4  Genes expressed in immature Pdx1+/Inslow versus mature Pdx1+/Ins+ β-cells ......91 Figure 4.5  Differentially expressed genes grouped based on function ...................................94 Figure 4.6  Real-time RT-PCR analysis of immature and mature human and mouse  β-cells .....................................................................................................................96 Figure 5.1  A hierarchy model of adult pancreatic endocrine cell homeostasis .....................118 Figure A1  Schematic flow diagram of experimental methods ..............................................134 Figure A2  Immunocytochemical staining of sorted MIN6 cells ...........................................134 Figure A3  Heterogeneous immunocytochemical staining of insulin and Pdx1 in human and mouse islets ...................................................................................................135 Figure A4  Calculation of δ-cell contribution to Pdx1+/Inslow cell population .......................136   ix  Figure A5  Phenotypic fate tracking of sorted INS-1 cells at whole population level ...........136 Figure A6  Maturation of sorted INS-1 cells ..........................................................................137 Figure A7  Working model of adult β-cell maturation states .................................................137 Figure B1  Activin A dose–response .....................................................................................138 Figure B2  Sample FACS dot plot .........................................................................................139 Figure B3  Effect of activin A on cells expressing control lentiviral vectors ........................140 Figure B4  Gene expression of activin A-treated human islets ..............................................141 Figure B5  Activin A decreases insulin secretion from human islets ....................................141 Figure B6  Expression of activin A and its receptors in human islets ...................................142 Figure B7  Rate of activin A secretion from human islets .....................................................142 Figure C1  Purity of sorted Pdx1+/Inslow and Pdx1+/Ins+ MIN6 cells ....................................169                   x LIST OF ABBREVIATIONS  AUC Area under curve BrdU  5’-bromo-2’-deoxyuridine DMEM Dulbecco’s Modified Eagles Medium eGFP Enhanced green fluorescent protein FACS Fluorescence-activated cell sorting FBS Fetal bovine serum FCS  Forward scatter FIV Feline immunodeficiency virus HPAP Human placental alkaline phosphatase MIN6 Mouse insulinoma 6 MOI Multiplicity of infection mRFP Monomeric red fluorescent protein Pdx1 Pancreatic and duodenal homeobox 1 PI Propidium iodide qRT-PCR Quantitative real-time reverse transcriptase PCR RPMI Roswell Park Memorial Institute Medium SE Standard error TNE  Tris-NaCl-EDTA                             xi ACKNOWLEDGEMENTS  I would like to acknowledge my supervisor Dr. James Piret for his endless support, guidance and patience through this thesis. Without his genuine talks and motivating energy, this thesis would not have been completed. Thank you for the wonderful journey. I would also like to thank my committee members Dr. Rob Kay, Dr. Timothy Kieffer and Dr. James Johnson. Thank you to Dr. Kay for his wonderful career advice and general scientific knowledge. A special thank you goes out to Dr. Kieffer for his motivation and continual advice and scientific input into the work of this thesis. An eternal gratitude goes out to Dr. Johnson who has started me on many wonderful ideas that lead to many results of this thesis, and his consistent support and guidance throughout this entire process. Thank you for pushing me harder and believing in me, even when I didn’t think I could do it. Thank you to my good friend and collaborator Dr. Dan Luciani. His professional and personal support has really helped me make it until the end. I would also like to thank Jessica Hill, Betty Hu, Lindsey Marmolejo, Dr. Galina Soukhatcheva, Dr. Michael Riedel, Blair Gage, Carol Yang, Natasa Moravic-Balkanski, Chris Sherwood and Corinne Hoesli for advice and support at various stages during this thesis. Thank you also to the labs of Dr. Piret, Dr. Kieffer and Dr. Johnson for helpful advice and making this time very enjoyable. Thank you also to my parents and sister for their love and support. The work of this thesis is dedicated to my father who has endured the pain and suffering of living with type 1 diabetes for over thirty years. I hope that I have contributed to the diabetes research field in some small way that one day we will find a real cure and are able to prevent this devastating disease. I will be eternally grateful to my husband Mario Szabat who has spent the last decade of my university education waiting patiently for me to finally finish. Thank you for the ‘scientific wisdom’ and for coming with me to the lab so many times at night so that I wouldn’t be scared. Words cannot express how thankful I am for all the love and support that you have given me. Finally, thank you to my sweet son Maximilian Szabat for giving me the motivation and patience for life and for that smile that makes every failed experiment a thing of the past. This research was funded by the Canadian Institutes for Health Research, the Juvenile Diabetes Research Foundation, Michael Smith Foundation for Health Research and β-Cell Regeneration and the Stem Cell Network. I was supported by studentships from the Natural Sciences and Engineering Research Council, Michael Smith Foundation for Health Research, Canadian Institutes for Health Research and the University of British Columbia.   xii DEDICATION                  To my dad Janusz Bielas                             xiii CO-AUTHORSHIP STATEMENT  Chapter 2 was co-authored with Dan Luciani, James Piret and James Johnson. I conceived, designed and performed the experiments and analysis leading to Figures 2.1-2.5. I assisted in the experiments leading to Figure 2.6. I prepared the manuscript with assistance from all authors.  Chapter 3 was co-authored with James Johnson and James Piret. I conceived, designed, performed all experiments and analysis and prepared the manuscript with assistance from both authors.  Chapter 4 is co-authored with James Piret and James Johnson. I conceived, designed and performed the experiments and analysis leading to Figures 4.1, 4.3 and 4.6. I performed all the analysis of microarray data leading to Figures 4.4 and 4.5 and all tables. The microarray experiments were performed at the core facility of the Centre for Molecular Medicine and Therapeutics, Vancouver, BC.       1 1 INTRODUCTION  Diabetes is a multifactorial disorder and is defined by the loss of functional pancreatic islet β-cells. In type 1 diabetes mellitus, an autoimmune reaction gradually destroys the β-cells, whereas in type 2 diabetes mellitus, β-cells gradually lose their glucose-stimulated insulin secreting function, among other defects (1, 2). Other less common monogenic forms of diabetes, including maturity-onset diabetes of the young – MODY, are also defined by a loss of β-cell function caused by mutations in single genes that are important for β-cell development and maintenance of β-cell maturity (3). Consequently, diabetes is characterized by chronic hyperglycemia. There has been outstanding progress over the past decade in the treatment and prevention of type 1 and type 2 diabetes. A Canadian breakthrough in islet transplantation, known as the Edmonton Protocol, has shown that insulin independence can be restored via islet transplantation in patients with long- standing type 1 diabetes, with minimal side effects (4). Similar results were obtained by international multi-center clinical trials (5). Although islet transplantation offers hope of an improved treatment for type 1 diabetes and potentially even a cure, many challenges remain. A five year follow-up study reported that most islet transplant patients reverted back to insulin therapy after 15 months but maintained endogenous insulin production and had improved glucose control with reduced hypoglycemic episodes (6). The study emphasized that progress is needed to reduce immunosuppression while maintaining islet engraftment and function. Also, part of the success of the protocol can be attributed to the large number of islets used for transplantation (usually from more than one donor), making the widespread application of the protocol even more severely limited by the inadequate supply of pancreatic donor tissue. Numerous efforts to produce renewable sources of β-cells for cell replacement therapies are currently underway. To a considerable degree, these depend on a thorough understanding of β-cell development and normal β-cell physiology as a guide for directing the generation of new β-cells in vitro or in vivo. Understanding the molecular networks and signaling pathways engaged in adult β-cells also provide insight into putative adult β-cell plasticity that could be exploited for therapeutic purposes.      2 1.1 CHARACTERISTICS OF FUNCTIONAL MATURE β-CELLS  The majority of the adult pancreas is comprised of exocrine tissue including acinar and ductal cells, whose function is to secrete and deliver digestive enzymes into the intestine. The endocrine pancreas is made up of micro-organs called islets of Langerhans embedded throughout the exocrine pancreas. Pancreatic islets consist of five endocrine cell types: β-, α-, δ-, PP- and ε- cells that secrete insulin, glucagon, somatostatin, pancreatic polypeptide and ghrelin, respectively, into the blood to maintain glucose homeostasis (7, 8) (Figure 1.1). The cell-to-cell contact between islet cells afforded by the three-dimensional structure allows their rapid concerted action in regulating metabolism. β-Cells are the most prevalent cell type in pancreatic islets, however the adult islet architecture and cellular composition varies extensively between the dorsal and the ventral pancreas (9), as well as under various physiological and pathophysiological conditions such as pregnancy and diabetes (10). In addition, there are also variations between species. A normal young adult rodent islet consists of 60-80% β-cells forming its core with the remaining endocrine cells (15-20% α-cells, 5-10% δ-cells, <2% PP- and 1% ε- cells) mainly scattered among the islet mantle (11-13). Human islets typically have a lower β-to- α cell ratio with a composition of 48-59% β-cells, 33-46% α-cells, 10% δ-cells, few PP- and 1% ε-cells (8, 12). However, unlike rodent islets, human islet architecture remains controversial, with studies reporting various descriptions of endocrine cell organization from randomly scattered to a more organized core of β-cells (12, 14). The differences in islet architecture forming different autocrine and paracrine cell interactions likely contribute to heterogeneity and functional consequences in normal and disease states (12). The most important characteristic of a mature β-cell is its glucose-stimulated insulin secreting function and loss of this function leads to diabetes. Hence, the definition of a mature β- cell implies glucose-responsive insulin secreting function. Insulin is considered the master metabolic hormone because it has a global effect on the body in maintaining normoglycemia. As an autocrine hormone, insulin also regulates its own expression and that of pancreatic glucokinase (15, 16). The secretion of insulin is mediated initially by sensing and transport of increased extracellular glucose levels by glucose transporters, GLUT2 (rodents) or GLUT1 (also known as SLC2A1, humans) (17). Next, pancreatic glucokinase phosphorylates glucose, which gets metabolized to pyruvate and induces mitochondrial metabolism resulting in subsequent   3 elevation of the cytoplasmic ATP to ADP ratio. This causes closure of ATP-sensitive potassium channels (KIR6-2/SUR1) resulting in net membrane depolarization, opening of the voltage-gated            Figure 1.1  Illustration of an islet of Langerhans. Animated representation of a wild type pancreatic islet of Langerhans containing β-cells, α-cells, δ-cells, PP-cells and ε-cells that secrete insulin, glucagon, somatostatin, pancreatic polypeptide and ghrelin, respectively, into the blood stream. Adapted from Beta Cell Biology Consortium; Illustration by Jean-Philippe Cartailler © 2005 (http://www.betacell.org/content/articles/article panel.php ?aid= 13&pid=1). Date accessed: April 2010.   calcium channels (CAV1.2) and rapid influx of calcium, stimulating a complex signal transduction pathway leading to biphasic secretion of insulin (18, 19). The mobilization and membrane fusion of insulin-containing vesicles is mediated by vesicular and membrane receptors, VAMP-2/cellubrevin and SNAP-25/syntaxin-I, respectively (20), initially characterized in neurons (21).  1.1.1 MOLECULAR MARKERS OF MATURE β-CELLS The mature, functional β-cell phenotype can be identified by a panel of molecular markers. Naturally, robust insulin expression is a definitive marker of mature β-cells. The pancreatic and duodenal homeobox 1 (Pdx1) (also known as insulin promoter factor 1 (IPF1) in humans) is an essential transcription factor required for the formation of the pancreas during embryogenesis and pancreatic agenesis results from a homozygous deletion of the gene (22). Furthermore, PDX1 is a pancreatic progenitor cell marker since all pancreatic cells are derived from PDX1-positive progenitors in vivo (23). Pdx1 expression is also critical in maintaining the mature β-cell phenotype by modulating the expression of insulin and many other β-cell-specific   4 genes (24), among its other important functions. Hence, Pdx1 expression also defines a mature β-cell, however, the level of expression differs between developing and adult cells (25). This supports a gene dosage effect in the differential roles of the same gene, both spatially and temporally. Pdx1 is expressed in a wave-like pattern with high expression in early embryogenesis followed by decreased expression in endocrine progenitor cells and again high levels in differentiating and mature β-cells (25). Genes involved in the insulin secretion pathway are also important mature β-cell markers. Glut2 is a specific β-cell marker as it is only expressed in β-cells and not in other adult pancreatic endocrine cells (26). It detects changes in extracellular glucose and is the major transporter of glucose into the rodent β-cell (27, 28). The glucose regulated glucose sensor, glucokinase, is the rate limiting step in the insulin secretion pathway by regulating glycolytic flux (29). The ATP-dependent potassium channel subunit KIR6.2 is part of a hetero-octameric complex with SUR1, mediating glucose-stimulated insulin secretion via membrane conductance and it is a key marker of β-cell function (30). MAFA, NEUROD1 and PDX1 all contribute to the expression of the insulin gene (31). MAFA directly binds to the insulin promoter and is one of the only genes with absolute β-cell-specific expression in adult β-cells (32). After having a role in pancreatic morphogenesis, expression of Neurod1 also becomes restricted to mature β-cells where it strongly induces expression of the insulin gene (33, 34). Finally, the expression of Nkx6- 1 and Nkx2-2 is also critical for β-cell development and for adult β-cell function. NKX2-2 functions upstream of and transactivates Nkx6-1, which becomes restricted to β-cells in the adult (35, 36). Whether generated from stem cells or isolated from primary islets, functionally mature β-cells can be defined by the expression of these well studied markers of β-cell maturity: insulin, Pdx1, Glut1/2, glucokinase, Kir6.2, Mafa, Neurod1, Nkx6-1 and Nkx2-2, among other functionally important genes.  1.1.2 ADULT β-CELL HETEROGENEITY It has been well documented that the β-cell population exhibits heterogeneity in function and gene expression. Functional variability among individual, dispersed β-cells has been described extensively in terms of glucose induced redox state (37), calcium signaling (38), insulin biosynthetic activity (39, 40) and insulin secretion (41), with correlations to E-cadherin expression (42). Although β-cells in intact islets function as a synchronized unit (43, 44), individual β-cells display heterogeneous patterns of glucokinase and insulin protein levels (45,   5 46) and graded glucose-induced insulin promoter activities (47). In addition, changes in insulin staining and granule morphology was highly variable in intact islets after glucose stimulation in vivo (48). Dispersed adult β-cells also exhibit heterogeneous insulin and PDX1 staining (49). Recent studies have further established that single adult insulin-expressing cells have differential gene expression profiles (50, 51). Based on the observed functional β-cell heterogeneity, it was proposed that glucose-dependent insulin secretion relies on the step-wise recruitment of differentially responsive β-cells (52), however up to 30% of β-cells never become responsive to glucose, suggesting a possibly alternative functional role for these β-cells. Collectively, these findings could be explained by at least two possible scenarios. First, β-cells could exist in stable subpopulations with unique gene expression patterns that govern their ultimate phenotype and specialized function. This scenario could include one subpopulation of β-cells that represent a specialized pool of endocrine progenitors with limited replicative capacity (53-55). Alternatively, these studies could be detecting single β-cells that could be dedifferentiated to variable degrees and these subpopulations being defined by a unique gene expression pattern. Another aspect of adult β-cell heterogeneity is the notion of multihormonal cells. Although multihormonal cells are readily observed during pancreatic development (56-58), their presence in adult islets or at least their presumed function remains questionable. Nevertheless, recent studies of single cells have clearly demonstrated that a large number of adult islet cells express more than one hormone at the transcript level (50, 51). Many of these cells also co- expressed Pyy (50), an early endoderm marker that is also found in embryonic glucagon/insulin double-positive cells (59, 60). Since increased Pyy expression has been observed in chemically- induced diabetic and regenerating islets (61, 62), its presence in normal adult multihormonal islet cells suggests that these cells may represent adult endocrine progenitor cells that retain plasticity and are distinct from embryonic endocrine progenitors (63). Further evidence suggesting that multihormonal islet cells may retain plasticity comes from histochemical analysis of endocrine tumors, which contain dedifferentiated, non-functional multihormonal cells (64).  1.1.3  LOSS OF FUNCTIONAL β-CELL MATURITY The loss of pancreatic β-cell mass is a hallmark of type 1 diabetes (65). The few β-cells that remain in the pancreas of mouse models of type 1 diabetes are thoroughly degranulated (66), suggesting a loss of functional maturity. Loss of functional β-cell maturity may also hinder clinical islet transplantation. Transplanted islets show reduced insulin secretion profiles (67), as   6 well as impaired proinsulin processing necessary for proper β-cell function (68). Furthermore, β- cells of patients with type 2 diabetes also exhibit a considerable loss-of-function and dedifferentiation, as evidenced by the down-regulation of key β-cell genes such as glucose transporters and Pdx1 (69). Although it is generally believed that the loss of β-cell function is a direct result of chronic hyperglycemia caused by insulin resistance (70), it was suggested that a loss of the β-cell phenotype by decreased Glut2 expression could be a prerequisite for hyperglycemia rather than a consequence (71). Finally, achieving functional β-cell maturity is also a major obstacle to the generation of new β-cells in vitro from human embryonic stem cells (72) or replication of existing β-cells (73).  1.2 MAINTENANCE OF β-CELL FUNCTION  Theoretically, the maintenance of β-cell function would involve similar molecular pathways that initially define the mature β-cell phenotype. This notion is supported by studies of MODY, which is an autosomal dominant inherited form of diabetes linked to heterozygous mutations in single genes (3). There are currently eight known MODY genes: hepatocyte nuclear factor 4 A (HNF4α), glucokinase (GCK), hepatocyte nuclear factor 1 A (HNF1α), insulin promoter factor 1 (IPF1), hepatocyte nuclear factor 1 B (HNF1β), neurogenic differentiation 1 (NEUROD1) (3), kruppel-like factor 11 (KLF11) (74) and carboxyl-ester lipase (CEL) (75). However, new MODY genes are actively being identified (76), such as the novel B-lymphocyte kinase (BLK) locus (77), as not all MODY cases can be accounted for by mutations in these known genes (78). Most recently, mutations in the insulin gene have been implicated as a cause of MODY (79). The perturbed function or level of these genes leads to impaired β-cell function and diabetes, suggesting a need for active maintenance of key β-cell genes. Recent evidence of such a notion was shown for NEUROD1, since a β-cell specific knock-out of this gene resulted in immature β-cells with decreased function similar to neonatal β-cells (80). Likewise, active expression of MafA is also required to maintain the gene expression profile of mature β-cells (81). Similar active maintenance mechanisms exist in other terminally differentiated cell types such as neurons (82). Furthermore, many β-cell maturity genes have autoregulatory (83) and/or heteroregulatory feedback mechanisms with other genes (84, 85) helping to reinforce the β-cell phenotype. Insulin itself may participate in an autocrine feedback loop to maintain β-cell insulin expression and secretion (86).   7 1.2.1 ROLE OF TRANSCRIPTION FACTORS IN β-CELL FUNCTION Of the eight known MODY genes, six are transcription factors (87), which emphasize the crucial role of transcription factor networks in maintaining the differentiated state of a cell. In addition to its essential developmental role, PDX1 is crucial to the maintenance of β-cell function. As a transcription factor, one of its roles in the mature β-cell is to help maintain insulin expression and other mature β-cell genes including glucokinase and Glut2 (24). Other important roles attributed to PDX1 in adult β-cells include glucose sensing, insulin biosynthesis, insulin exocytosis (88), and maintaining β-cell mass by controlling the balance between β-cell apoptosis (89) and proliferation (90, 91). Even partial loss of PDX1 levels in β-cells leads to β-cell dysfunction and the development of diabetes (92-94). High glucose and insulin trigger the activation of PDX1 (95). This process is dependent upon PDX1 phosphorylation and its subsequent shuttling from the cytoplasm to the nucleus where it binds DNA target sites (96, 97). Accordingly under low glucose levels, PDX1 can be detected in the cytoplasm of β-cells and it translocates into the nucleus when the cells become activated (97). However, whether this occurs directly due to high glucose or via autocrine insulin signaling is unclear (49). The complex regulation of Pdx1 gene expression is accomplished by PDX1 itself (83) and numerous other transcription factors, including HNF3β (83), NEUROD1 (98) and MAFA (85). The transcription factor Mafa is one of the only genes expressed exclusively in mature β- cells. This restricted expression pattern demonstrates its importance in maintaining β-cell identity. In development, Mafa first appears only in insulin-expressing cells (99). MAFA was identified by its ability to induce insulin expression (32) via a synergism with PDX1 and NEUROD1 (100). Its expression is regulated by glucose, NKX2-2 and PDX1 (84, 101). Since MAFA also regulates the expression of Pdx1 (85), there appears to be a cooperative feedback regulation that allows these two transcription factors to maintain the mature β-cell phenotype. The master role of MAFA in maintaining β-cell function was validated by MAFA gain-of- function and loss-of-function studies, demonstrating that MAFA controls insulin expression directly and is also associated with indirect regulation of many other function-related β-cell genes (102). Although NKX2-2 has traditionally been viewed as a developmental factor directing endocrine differentiation (35), recent studies have implicated NKX2-2 in the maintenance of mature β-cell function. In mature β-cells, NKX2-2 was shown to bind directly to the insulin promoter along with PDX1, PAX6 and NEUROD1. However, surprisingly, it appeared to repress   8 insulin enhancer/promoter activity in vitro (103). Interestingly, a repressor form of NKX2-2 fully rescued α-cells and specified immature β-cells in Nkx2-2-null mice, but failed to restore mature β-cells (104). Furthermore, transgenic mice expressing a dominant repressor form of NKX2-2 in Nkx2-2 wild-type mice showed decreased expression of Nkx2-2, Mafa and reduced insulin production and secretion (105). These studies suggest that NKX2-2 alternately regulates β-cell development and the mature β-cell phenotype, acting as a repressor in early embryonic β-cell specification and then as an activator in mature β-cells. Indeed, Nkx2-2 itself was differentially regulated by different promoter regions in islet cell progenitors and mature islets (106). Until recently, Ngn3 was thought to be only expressed in endocrine progenitors before birth, where it controls endocrine and exocrine differentiation (107). The first study to robustly report the expression of Ngn3 message and protein production in normal adult islets also showed that Notch/NGN3 signaling regulates islet cell survival (108). Subsequently, NGN3 has been implicated in islet and β-cell maturation and function, in part through activation of the mature β- cell genes insulin, Glut2 and Mafa (109). Taken together, these studies demonstrate the elaborate context- and stage-dependent interactions between many vital β-cell genes involved in the maintainance of β-cell identity. Remarkably, many key transcription factors in adult β-cells regulate their own expression and that of each other forming a feedback mechanism for maintaining strong expression and reinforcing β-cell maturity and function.  1.2.2 MAJOR SIGNALING PATHWAYS REGULATING β-CELL MATURITY The TGFβ superfamily is one of the most widely expressed signaling pathways in eukaryotes, eliciting a plethora of effects in growth and differentiation of many organs (110). This family includes a large number of ligands of the TGFβ, BMP and activin subfamilies that signal through a combination of shared type I and type II transmembrane receptors (110, 111). Signals are transmitted via downstream effectors called SMADs that directly bind DNA target sites and regulate transcription (112). Pancreatic development is also governed by this signaling pathway via an interplay of inductive and suppressive signals. Initial pancreatic specification and patterning is achieved via activin signaling (113). Pancreatic morphogenesis and endocrine/exocrine cell fates are also controlled by the TGFβ/activin signaling pathways (114- 116). Many components of this pathway such as activins and their inhibitors (e.g. follistatin) are also expressed in adult β-cells (117, 118) and are involved in regulating insulin secretion (119,   9 120). These results suggest that active TGFβ signaling pathways also play a role in the maintenance of β-cell function and adult β-cell differentiation in an autocrine/paracrine manner. Indeed, components of the TGFβ pathway were differentially expressed during attempts to obtain in vitro β-cell differentiation from human islet depleted pancreatic tissue, suggesting a role for this pathway in this process (121).  Notch signaling is another critical pathway in development affecting aspects from proliferation and differentiation to apoptosis (122). Notch receptors bind membrane-bound ligands of the delta-like family on adjacent cells, resulting in cleavage of the intracellular part of the receptor, which traffics to the nucleus and activates expression of transcriptional repressor Hes genes via interaction with other transcription factors (123). HES repressors prevent the expression of downstream targets (e.g. Ngn3) in the receiving cell which attains a secondary, non-endocrine fate. The signaling cell assumes the primary cell fate as an endocrine progenitor (123). Appropriate regulation of notch signaling is also essential for pancreatic endocrine and exocrine specification and differentiation (107, 124, 125). The transient expression of the Notch target gene Ngn3 marks the endocrine progenitors that give rise to all adult islet cells (23). Interestingly, a recent study also revealed that each Ngn3-positive precursor is unipotent, committed to differentiating into only one type of endocrine cell (126). Much less is known about this pathway in adult islets. However, recent studies have demonstrated that components of the Notch pathway are expressed and functional in adult islets (108, 109). Activated NOTCH1 regulates β-cell survival (108) and NGN3 maintains β-cell maturity and function (109). Many other regulators of Notch signaling have been defined in other cell types such as neurons, including the opposing modulators Numb and Musashi (127, 128). Since endocrine cells share many gene networks with neurons, it will be interesting to establish if they are also expressed and functional in adult β-cells.  1.3 DEVELOPMENTAL BIOLOGY OF THE PANCREAS  Pancreatic specification of the endoderm occurs through signaling from adjacent germ layers (129). Endoderm formation itself requires the expression of Sox genes, specifically Sox17 (130). The dorsal pancreatic bud receives signals from the notochord, dorsal aorta and mesenchyme through soluble factors of the fibroblast growth factor (FGF) and transforming growth factor beta (TGFβ) families. FGF2 and activin B from the notochord repress Sonic   10 Hedgehog (Shh) allowing dorsal pancreatic specification (131). Mesenchyme-derived retinoic acid is also required for dorsal endoderm development (132). The ventral pancreatic bud is specified by escaping the inhibitory FGF signals that initiate liver formation (133) and by instructive bone morphogenic protein (BMP) and activin A signals from the cardiac mesoderm (134). The early pancreatic buds begin to express the essential pancreatic transcription Pdx1, and become multipotent pancreatic progenitors (23). Pancreatic bud formation and subsequent differentiation is regulated by a transcriptional network of genes, including members of the hepatocyte nuclear factor family (e.g. Hnf3β (FoxA2), Hnf1β and Hnf6, Ptf1a, Hb9, Hex and Isl1 (135). HNF3β initiates the expression of Pdx1, illustrating transcription factor hierarchy in development (136, 137). The buds then undergo branching morphogenesis into the surrounding mesenchyme that secretes FGF10 to promote expansion of epithelial pancreatic progenitor cells (138), marking what is called the primary transition. Another Sox gene, Sox9, is involved in the expansion of the PDX1-positive progenitor pool prior to endocrine differentiation (139). Most early endocrine cells that appear in the pancreatic buds show a heterogeneous gene expression pattern and are multihormonal, with predominantly glucagon, insulin and other hormones such as peptide YY (PYY) (50). At the start of the secondary transition, the two pancreatic buds rotate and fuse and endocrine/exocrine differentiation is initiated (140). Notch signaling regulates endocrine and exocrine cell fate choice via a mechanism known as lateral inhibition carried out by the pro-endocrine gene neurogenin 3 (Ngn3) (107, 122). The activation of Ngn3 in pancreatic progenitor cells appears to be initiated by HNF1a, HNF3β and HNF6 (141). The NGN3-positive cells express Notch ligands that bind Notch receptors, activating the Notch signaling pathway, in neighbouring cells leading to the expression of Hes1, a direct Ngn3 repressor (i.e. lateral inhibition), and adapting a secondary non-endocrine or exocrine cell fate (123). Follistatin secreted from the mesenchyme also plays a role in directing exocrine and limiting endocrine differentiation (115). NGN3 production marks the endocrine progenitors which can further differentiate into all of the islet endocrine cell types (23). As a transcription factor, NGN3 directly activates expression of endocrine genes such as Pax4 (142), Nkx2-2 (106) and Neurod1 (also known as Beta2) (143), consistent with its role as a pro-endocrine gene. The third developmental transition involves the organization of endocrine cells into islets, endocrine cell proliferation, islet remodeling and functional maturation after birth (140, 144). The specification of individual endocrine cells requires additional transcriptional programs. The paired homeobox transcription factors, Pax4 and Pax6, participate in this process.   11 Mice lacking Pax4 fail to develop β- and δ-cells but have an increased number of α-cells (145). Conversely, Pax6-null mice primarily lack α-cells (146). Hence the initial activation of Pax4 appears to specify the β- and δ-cell fates, whereas Pax6 expression in endocrine progenitors directs differentiation into α-cells, but also regulates insulin, glucagon and somatostatin gene expression in differentiated cells (147). α-Cell specification is mediated by Arx, which represses β- and δ-cell development, and hence performs the opposite role of Pax4 in β-cell specification (148). The β-cell lineage is further specified by the NK homeobox factors NKX2-2 and NKX6-1. Nkx2-2 is expressed upstream of Nkx6-1, which is later restricted to β-cells in mature islets (36). Finally, the terminal differentiation of β-cells appears to involve MAFB (149). The Maf family transcription factor directly regulates expression of the β-cell-specific genes Mafa, Pdx1, Nkx6-1, Glut2 (also known as Slc2a2), and insulin, participating in prenatal β-cell maturation (149), and becomes subsequently downregulated in β-cells (150). However, MAFB is involved in the maintenance of glucagon expression in mature α-cells (151). The subsequent production of MAFA exclusively in differentiated β-cells augments insulin expression (32), marking the mature β-cell phenotype. Although elucidation of molecular transcription factor networks during pancreatic development is commonly performed using rodent models, it appears that very similar pathways regulate human pancreas development (152).  1.3.1 PRENATAL AND POSTNATAL β-CELL MATURATION The functional maturation of β-cells only becomes complete several weeks after birth. Until then, fetal and neonatal β-cells have been reported to have a reduced response to glucose but respond to other nutrients such as amino acids (153, 154). The attenuated response to glucose is caused by immature glucose metabolism resulting in dysregulated ATP-sensitive potassium channels (155). However, continued exposure to glucose through feeding seems to induce the proliferation and maturation of immature β-cells (155). Hence, during the neonatal period, extensive islet remodeling occurs through a balance of β-cell proliferation and apoptosis resulting in increased β-cell mass (156-158). One of the mechanisms by which fetal and neonatal islets acquire their glucose-stimulated insulin secretion function appears to involve prolactin, a hormone produced during pregnancy and present in breast milk (159). It sensitizes the β-cell response to glucose by increasing the expression of the exocytotic machinery involved in insulin secretion (160, 161).   12 1.3.2 ADULT β-CELL MATURATION The concept of β-cell maturation in the normal adult pancreas is somewhat enigmatic. This phenomenon is well studied in adult islets from pregnant animals, during which the pancreas undergoes extensive adaptation to the increased demand for insulin during pregnancy. This results in enhanced sensitivity to glucose, increased β-cell proliferation, reduced apoptosis, increased insulin expression and secretion, among other changes (162). It appears that the same exogenous signals, such as lactogens and prolactins, that govern neonatal β-cell maturation also modulate the changes observed in the maternal pancreas (163, 164). However, the molecular mechanisms directing β-cell changes during pregnancy are only beginning to be uncovered (165, 166). Because β-cells share numerous signaling pathways and transcriptional networks with neurons during development and in adults (7, 167-169), similar molecular networks implicated in adult neurogenesis and maturation may also be involved in adult β-cell regeneration and maturation. For example, the WNT, BMP, SHH, Notch and insulin growth factor 1 receptor (IGF-1R) signaling pathways have confirmed roles in adult neurogenesis (170). Notably, Notch/NGN3 signaling was also shown to be required for adult β-cell maturation, survival and function (108, 109). Nevertheless, the process of β-cell maturation in normal adult islets is still largely unexplored.  1.4 GENERATION OF ALTERNATIVE β-CELL SOURCES  Alternative sources of β-cells are needed to replace β-cells destroyed in the type 1 diabetic pancreas, as the supply of donor islets for islet transplantation is limited. There are many potential avenues for generating replacement β-cells, including in vitro differentiation of islets or β-cells from embryonic stem cells, induced pluripotent stem cells or putative adult stem/progenitor cells, proliferation of existing adult β-cells, or cellular reprogramming of various adult cell types. In vivo regeneration efforts are also underway using similar approaches.  1.4.1 PLASTICITY OF MATURE PANCREATIC CELLS  The pancreas has a remarkable ability to modulate β-cell mass under physiological and pathophysiological states, as well as to regenerate after injury (171, 172). Evidence of pancreatic cell plasticity was also revealed in cultures of adult islets (173-175). Proliferating human islets   13 seem to adopt duct-like epithelial structures, concomitant with the loss of endocrine markers and emergence of ductal cell markers (173, 174), and this phenotype was reversed by soluble factors (174). Recently, lineage tracing confirmed that insulin-expressing β-cells dedifferentiate and acquire stem cell-like properties via an epithelial-to-mesenchymal transition (175). The exact mechanisms and environmental cues that promote such changes are not well understood. However, the insulin receptor signaling pathway seems to play a role in regulating β-cell mass in vivo (176). Remarkably, recent studies of cellular reprogramming showed that the cooperative action of only a few key transcription factors is needed to promote the plasticity of adult cells. The most notable examples are the generation of induced pluripotent stem cells from post- mitotic somatic cells (177, 178), including mature β-cells (179). Forced expression of Pdx1, Ngn3 and Mafa allowed the direct reprogramming of adult pancreatic acinar cells into functional, insulin-secreting β-cells in vivo (180). In addition, glucagon-expressing α-cells can be specified into β-cells by ectopic expression of Pax4 (181). Clearly, key genetic programs are sufficient for inducing the β-cell phenotype from a variety of different cell types and are important targets for therapeutic interventions. These studies substantiate the emerging notion that adult pancreatic cells retain extensive plasticity under specific conditions and offer hope of cell therapy for the treatment of diabetes.  1.4.2 IN VITRO AND IN VIVO STEM/PROGENITOR CELL-DERIVED β-CELLS Characteristic stem cell derivation of β-cells comes mainly from embryonic stem cells, as adult pancreatic stem/progenitor cells remain elusive. A protocol for the differentiation of embryonic stem cells into glucose-responsive insulin producing cells has been reported (182). Although the initial differentiation steps were performed in vitro into definitive endoderm then to pancreatic and endocrine progenitors, differentiation into pancreatic cells and final maturation steps were performed in vivo after implantation into mice (182). Hence, the complete understanding of the exogenous signals that are necessary and sufficient to direct terminal differentiation in vitro is still lacking. Nevertheless, activin A, retinoic acid, FGF10 and sonic hedgehog signaling inhibitor were critical for initial endoderm and pancreatic specification (72, 182), mimicking known steps in pancreatic development. Other approaches for embryonic stem cell differentiation towards the pancreatic lineage include high-throughput screening of natural chemical libraries to identify novel compounds capable of directing this process robustly (183).   14 In addition to embryonic stem cells, several potential sources of adult stem/progenitor cells have been proposed for the in vitro or in vivo generation of islets. For instance, adult stem cells derived from bone-marrow have been used in attempts to direct their differentiation into insulin-expressing cells (184, 185). However, the results of these studies have been questionable (186-189). Other potential adult stem/progenitor cells have been derived from skin, liver, spleen and pancreas (190-193). Prior to robust lineage tracing techniques, histological evidence was used to suggest that adult pancreatic progenitor cells reside in pancreatic duct cells (194, 195) and could generate new insulin-expressing cells in vitro (196, 197). However, the study by Dor et al. (198) showing that new β-cells in the adult pancreas are generated by replication of cells with insulin promoter activity, presumably existing β-cells, and this cast doubt on the existence of cells in the adult pancreas that meet the classical criteria of stem cells. Since then, significant efforts have been invested in identifying the putative pancreatic stem cells in vivo by lineage tracing and functional analyses. Some have reported that a rapidly dividing pancreatic progenitor cell does not exist under normal conditions and that all adult β-cells have a similar, slow proliferation rate and equally contribute to maintenance and regeneration of β-cell mass in adult islets (199, 200). However, this does not preclude alternative modes of β-cell genesis in adults. Indeed, after pancreatic injury, it has been reported that Ngn3-positive, facultative pancreatic progenitor cells, located in the pancreatic ductal lining and scattered among islets, participate in β-cell neogenesis (55). More recently, adult glucagon-expressing cells were shown to be β-cell precursors regenerating the β-cell population β-cell ablation with diphtheria toxin (201) and pancreatic duct cell ligation with almost complete endogeneous β-cell destruction with alloxan (202). On the basis of these study, it could be speculated that atypical progenitors not detected by the previous lineage tracing studies may exist and are activated in vitro or in vivo under specific conditions in the pancreatic islets (201-203), ducts (196, 204) or non-endocrine epithelial cells (205). Hence, more studies are needed to establish if such “progenitors” could have therapeutic potential.  1.4.3 PROLIFERATION OF ADULT β-CELLS An alternative approach to addressing the shortage of transplantable β-cells would be to induce the proliferation of existing β-cells in vitro. This approach seems plausible since proliferation of existing β-cells is the major physiological mechanism for β-cell maintenance and regeneration (198). However, β-cells induced to proliferate in culture rapidly lose insulin protein   15 and dedifferentiate to an immature state while maintaining PDX1 protein production (206). Lineage tracing provided conclusive evidence of the dedifferentiation of proliferating human and mouse β-cells in vitro (73). Novel high-throughput approaches are being used to find molecules that can induce the proliferation of normally quiescent β-cells (207). Efforts to redifferentiate expanded β-cells will likely also be needed.  1.4.4  GROWTH AND DIFFERENTIATION FACTORS FOR IN VITRO β-CELL GENERATION In establishing appropriate conditions for generating β-cells in vitro, the logical choice of culture medium additives would be factors that influence islet function and/or have a role in pancreatic development. Indeed, the most successful embryonic stem cell differentiation protocols were guided by developmental cues (72). For example, the significant role of retinoic acid in cell proliferation and differentiation has been extensively defined in embryonic development (208). In pancreatic development, retinoic acid seems to promote endocrine differentiation by inducing Pdx1 expression and suppressing the exocrine program (209). In keeping with its role in development, retinoic acid induced differentiation of mouse embryonic stem cells into the PDX1-positive endodermal lineage (210). Glucagon-like peptide-1 (GLP-1), an incretin hormone secreted by gastrointestinal cells, has major physiological roles related to metabolism such as glucose-dependent potentiation of insulin secretion and suppression of glucagon release (211). GLP-1 and its potent analog exendin-4 influenced differentiation of pancreatic ductal cell lines and human fetal pancreatic cells into insulin-expressing cells by activation of β-cell transcription factors such as PDX1 and HNF3β (212, 213). Exendin-4 also helped maintain β-cell function of transplanted islets (214). As members of the TGFβ family, activins have widespread biological functions in cell proliferation and differentiation (111) and are essential for proper pancreatic development (113, 116). The addition of high dose activin A was critical for the specification of definitive endoderm in embryonic stem cell cultures (72). A pancreatic cell mitogen, betacellulin, was also used in combination with activin A to increase the insulin content and number of insulin-positive cells in cultures of human fetal pancreatic cells (215). Insulin itself is a potent growth factor and at physiological doses can increase β-cell proliferation (216) and promote β-cell survival (49). Finally, glucose (or autocrine insulin) and exogenous insulin were shown to promote the cytoplasmic-nuclear shuttling and activation of PDX1 (49, 96). With a large selection of growth   16 factors and nutrients available, the challenge lies in systematically assessing their relative affects to select the levels that most effectively promote the generation of β-cells in vitro.  1.5 NEW TOOLS FOR THE STUDY AND GENERATION OF β-CELLS  Recent technological advances in imaging and molecular biology and the completion of the human genome project have allowed the transition from studying single genes, proteins or culture additives to whole genome, proteome and high-throughput screening platforms. However, appropriate implementation of such technologies requires the development of innovative methods for robust sample preparation and for analyzing large data sets to obtain reliable results.  1.5.1 HIGH-THROUGHPUT SCREENING AND STATISTICAL DESIGN OF EXPERIMENTS Gene array and proteomic technology have become routine practice in diabetes research (49, 121, 217, 218) and biology in general (219). This allows for analysis of entire signaling networks and their complex interactions with extracellular signals involved in specific biological systems. Similarly, many groups have turned to high-throughput screening of large natural extract or chemical libraries in search of novel factors that can improve β-cell function or increase the generation of β-cells in vitro (207, 220, 221). Such libraries have been used in the discovery of new anticancer agents (222). Although these approaches have a great potential to accelerate the discovery of new treatments for diseases, there are many challenges in the design of specific and quantitative assays, the set-up and implementation of high-throughput screens and appropriate statistical data analysis to achieve meaningful results. One possible solution to the experimental design and analysis challenge is at the heart of statistical design of experiments, often used in engineering science (223, 224). The optimization of culture conditions requires the systematic analysis of temporal and dose effects of multiple factors, in addition to environmental effects such as pH or temperature. Therefore, trying to elucidate optimized culture protocols by standard empirical methods, especially with high- throughput experiments, can quickly become unmanageable. Factorial design methodology can substantially decrease the number of experiments and identify the significant effects of single factors as well as multiple factor interactions, ultimately improving the rate and efficiency of high-throughput screening (225, 226). Typically, two-level fractional factorial designs are used   17 for initial screening experiments, followed by more sophisticated surface response designs (226). This technique was used to elucidate effects of combinations and concentrations of cytokines on hematopoietic stem cell expansion (224). Statistical software packages are available for the design and analysis of these screening experiments. The ultimate shift towards systems biology for elucidating signaling networks will benefit from improved statistical methods (227).  1.5.2 LINEAGE TRACING AND LABELING OF CELLS A primary challenge for implementing high-content, high-throughput screens is with the design of quantitative and reliable cell imaging assays. The discovery of fluorescent proteins has revolutionized cell biology (228). The engineering of the fluorescent protein spectrum from green (GFP) (229) and red (RFP) (230) to most recently blue (231) and far-red (232, 233) now allows for the development of multi-parameter imaging assays. Using this palette of fluorescent reporters, fusion proteins, promoter-reporter constructs and functional probes have been developed (234, 235). For example, a functional image-based assay using a fusion protein containing GFP and FOXO3a was developed to monitor the nuclear-cytoplasmic shuttling of FOXO3a and consequently used for high-throughput screening of chemicals capable of modulating the PI3K/Akt signaling pathway (235). Naturally, image-based and functional assays are only useful when the cell or protein of interest is well characterized. Therefore, for the purpose of generating β-cells in vitro, choosing appropriate differentiation stage-specific markers will be critical for effectively tracking β-cell maturity in culture. The study of stem/progenitor cells in the pancreas is complicated by the use of mixed cell populations. Lineage tracing of single cells using cell specific promoters is a highly convincing method showing the origin of differentiated cells. To date, clonal single cell analysis of pancreatic progenitor cells was mainly descriptive (193). Using novel high-content and high- throughput technology, large scale and quantitative single cell lineage analysis of putative pancreatic stem/progenitor cells can now be realized. Lineage labeled cells can also be purified using fluorescence activated cell sorting for downstream phenotypic characterization at the transcriptome level using microarray technology (50) or at the single cell level using optimized single cell PCR (51). Lineage labeling of rodent cells is accomplished by creating transgenic animals (198), however labeling of primary human cells is more challenging but has been a major focus for gene therapy applications (236). Transgene delivery into pancreatic cells has been commonly achieved using adenoviral vectors (237). However, the transient persistence of these vectors limits their long-term   18 application, such as for culture process development and lineage tracing. The major advantage of lentiviral vectors is their ability to infect and integrate into the genomes of primary, non-dividing cells (such as pancreatic islets), and they can provide long-term, stable transgene expression (238). Even intact human islets were efficiently infected using lentiviral vectors (239). Due to safety concerns, lentiviral vectors have been engineered to be replication defective by deletion of vital replication and accessory genes; in their place, the vectors contain the gene of interest and antibiotic-resistance genes (236). Thus, for recombinant virus production, helper vectors, devoid of cis-acting packaging signals, are co-transfected with an expression vector into packaging cell lines to allow production of the necessary viral packaging, structural, replication/integration proteins in trans (240). Russ et al. (73) developed a method to trace the fate of human β-cells in vitro by using the simultaneous infection of cells with two separate lentiviral vectors incorporating the Cre/lox recombination system. In conclusion, the development of cell specific labeling systems for the purification and lineage tracing of pancreatic cells will enable robust and sensitive high-content, high-throughput and quantitative studies of β-cell biology and differentiation fate.   1.6 THESIS OBJECTIVES  The enigmatic process of adult β-cell maturation has significant implications for diabetes pathogenesis, islet transplantation and potential diabetes therapies. Because adult β-cell mass retains the ability to adapt to physiological and pathophysiological conditions, it appears that β- cells or other putative β-cell progenitors are responsive to extracellular signals. In this regard, it is not known whether all β-cells have a similar potential for plasticity. In addition, despite the evidence for the heterogeneous nature of the β-cell phenotype, more work is needed to understand the implications of such heterogeneity. Fundamentally, the study of adult β-cell physiology would contribute to the understanding of how to maintain β-cell function and maturity, an important step in the development of alternative β-cell sources to treat diabetes. The underlying hypothesis was that adult pancreatic β-cells exist in both immature and mature differentiation states. The overall goal of this thesis was to define and manipulate the maturation states of adult β-cells. A secondary goal was to develop novel tools for studying cell culture development of pancreatic cells and β-cell differentiation fate by applying engineering   19 approaches to tackle biological questions. These tools and approaches should provide a means for more efficient and quantitative study of pancreatic β-cell biology specifically, and could also be applied to other biological systems. In Chapter two, the objective was to characterize adult β-cell heterogeneity and maturation states using novel image-based approaches. It was hypothesized that mature β-cells would co-express insulin and the essential transcription factor Pdx1, whereas immature cells would lack robust insulin expression but retain Pdx1 expression, similar to progenitor cells in development. Hence, the approach was to develop a dual reporter marking system containing two independent Pdx1 promoter-reporter and insulin promoter-reporter transgenes on a single vector. This kind of system would inherently label β-cells at various maturation states and allow fate tracking and the study of heterogeneity in Pdx1 and insulin expression in single cells. In Chapter three, the objective was to identify and characterize factors that could modify the expression of Pdx1 and/or insulin, and hence maturity, in cultured β-cells. The approach was to develop a quantitative screening assay that would allow systematic and simultaneous analysis of many exogenous factors and culture additives that could modulate the maturation state of adult β-cells. Being able to understand and improve β-cell maturity should ultimately contribute to the generation of functionally mature β-cells in vitro. Finally, the objectives of Chapter 4 were to further characterize adult β-cell maturity using live cell imaging and a whole genome approach and to generate a database of differentially expressed genes between the two β-cell maturation states, which could be of interest to the diabetes field in general. One aim was to define β-cell maturation states by unique gene expression profiles. 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Johnson et al. have also observed heterogeneous insulin and pancreatic duodenal homeobox 1 (PDX1) staining among dispersed human β-cells (2). Furthermore, glucose-induced insulin promoter function is heterogeneous among cells within the intact islet, exhibiting graded rather than on/off promoter activity (3). These reports suggested that there may be stable, independent subpopulations of β-cells. Other studies have focused on identifying a specialized pancreatic stem cell population or a pool of β-cell precursors, which would be expected to have functional characteristics distinct from mature β-cells (4, 5). Functional variability among dispersed primary β-cells has been well documented by measurements of glucose-induced redox state, calcium signaling, biosynthetic activity, and insulin secretion (6-9). β-Cell coupling in the intact islet allows for more uniform glucose-induced responses in the entire β-cell population of the islet (10-12). It is unclear, however, whether heterogeneity in gene expression and function of adult β-cells are linked. In contrast to these examples of β-cell heterogeneity, recent in vivo studies revealed that β-cells are relatively homogeneous with regard to their replicative capacity and their contribution to β-cell mass in adult islets (13-15). Thus, these new studies imply that β- cell populations may be more uniform than previously appreciated. The transcription factor, PDX1 is a master regulator of pancreatic development, islet survival, and β-cell function (16-20). Pdx1 haploinsufficiency leads to diabetes in humans and mice (18, 21, 22). Pdx1 is uniformly expressed in β-cell progenitors during embryonic development, in which it is required for the formation of the pancreas (16, 19). In the adult mouse, Pdx1 is clearly expressed in most, but not all, β-cells, and some δ-cells (23, 24). In this study, we sought to investigate the nature of Pdx1 and insulin phenotypic heterogeneity. We used a novel lentiviral dual reporter system containing the insulin and Pdx1 promoters. This allowed  1 A version of this chapter has been published. Szabat M, Luciani DS, Piret JM, Johnson JD (2009) Maturation of adult beta-cells revealed using a Pdx1/insulin dual-reporter lentivirus. Endocrinology 150:1627-1635   39 us to examine in detail the expression pattern of these genes in living primary human and mouse islet cells and MIN6 cells. Our results revealed that the majority of adult β-cells exhibited both Pdx1 and insulin promoter activity. However, a substantial number of cells were Pdx1-positive and insulin- negative/low (Pdx1+/Inslow). These insulin and Pdx1 expression profiles corresponded to different β-cell maturation states associated with distinct gene expression patterns. Many functionally immature Pdx1+/Inslow cells mature to become Pdx1/insulin-double positive without dividing. These findings are consistent with both reports of multiple adult β-cell phenotypes and with recent data showing that adult β-cells exist as a population of cells with a relatively uniform proliferation rate and life cycle.  2.2  MATERIALS AND METHODS  2.2.1 CONSTRUCTION OF LENTIVIRAL VECTORS, LENTIVIRUS PRODUCTION AND INFECTION A second generation feline immunodeficiency virus (FIV) vector based on pTiger was kindly provided by Dr. Garry Nolan (Stanford University, Stanford, CA). The original pTiger plasmid was modified as described in detail in the Supplemental Methods (Appendix A). All transfer vectors were constructed using the modified pTiger backbone (pTigerMCS) (Figure 2.1A). The dual-reporter vector was created by ligating the −410 bp rat Ins1 promoter-enhanced green fluorescent protein (eGFP) cassette from its original vector (gift from Dr. Timothy Kieffer, University of British Columbia, Vancouver, Canada) into the modified pTiger backbone containing a mouse Pdx1 promoter (−4530 bp)-monomeric red fluorescent protein (mRFP; a gift from Dr. Roger Tsien, University of California, San Diego, San Diego, CA) (25) cassette; the Pdx1 promoter was a gift from Dr. Jochen Seufert (Hospital of the Bavarian Julius-Maximilians University, Wurzburg, Germany). Single reporter vectors and CMV-containing vectors were created as controls. Virus production and infection was performed as described (26) (also see Supplementary Methods in Appendix A). Functional expression of each vector was tested in HepG2, Panc-1, HEK293, MIN6, and INS-1 cell lines as well as human and mouse islets.  2.2.2 CELL CULTURE AND TRANSFECTION Human islets were kindly provided by Dr. Garth Warnock and the Ike Barber Human Islet Transplant Laboratory (Vancouver General Hospital, Vancouver, British Columbia,  40 Canada), which has institutional review board approval for all procedures. Donor information is provided in Supplemental Table A1. Islets were washed in Hanks’ balanced salt solution and seeded in CMRL 1066 medium supplemented with 10% fetal bovine serum (FBS), 2 mM glutamine, 100 U/ml penicillin, and 100 μg/ml streptomycin and then cultured overnight in 5% CO2 at 37°C before infection the following day. One day before infection, islets were isolated from 10- to 12-wk-old C57BL/6J mice and cultured overnight in RPMI 1640 with 10 mM glucose. Islets were then dispersed as previously described (18) and seeded as single cells in clear-bottom 96-well plates or on glass coverslips. The MIN6 insulinoma cell line was a gift from Professor Jun-Ichi Miyazaki (University of Osaka, Osaka, Japan) (27). MIN6 cells were grown in 25 mM glucose DMEM, 10% FBS, 2 mM glutamine, 100 U/ml penicillin, and 100 μg/ml streptomycin at 5% CO2 at 37°C, unless otherwise stated. The rat INS-1 cells (gift from Dr. Bruce Verchere, Child and Family Research Institute, Vancouver, Canada) were grown in RPMI 1640, 10% FBS, 2 mM glutamine, 100 U/ml penicillin, 100 μg/ml streptomycin, 50 μM β-mercaptoethanol, 1 mM sodium pyruvate, and 10 mM HEPES and incubated as MIN6. Transfections of cell lines for functional plasmid testing before virus production were performed in 6-well plates using Lipofectamine 2000 according to the manufacturer’s instructions. All culture and transfection reagents were from Invitrogen (Burlington, Ontario, Canada), unless otherwise noted. A flow diagram and summary of the various experiments performed with each cell type is provided in Supplemental Figure A1.  2.2.3 FLOW CYTOMETRY For fluorescence-activated cell sorting (FACS), stably infected cells were lifted off plates using trypsin-EDTA and resuspended in PBS containing 5% FBS and kept on ice. Viral titering was performed using a FACSCalibur laser-based flow cytometer (BD Biosciences, Mississauga, Ontario, Canada). For phenotypic analysis and sorting of MIN6 and INS-1 cells infected with the dual-reporter lentivirus, the Influx sorter (Cytopeia) was used with an argon ion laser at 514 nm; emission filters were 625/25 bandpass for mRFP and 530/40 bandpass for green fluorescent protein. mRFP+-only and mRFP+/eGFP+ subpopulations were sorted into chilled complete medium for further analysis. Cell viability after sorting was approximately 97%. Cells were allowed to recover and attach to the culture dish for 4–6 h after sorting before experiments were performed.    41  2.2.4 QUANTITATIVE REAL-TIME RT-PCR Total RNA was purified using RNeasy minikit (QIAGEN, Valencia, CA) and used to prepare cDNA with 0.5 μg/μl oligo(deoxythymidine) using SuperScript first-strand synthesis system (Invitrogen) following the manufacturer’s instructions. Primers were designed to flank an intron and are listed in Supplemental Table A2. Quantitative RT-PCR was performed by using the Quantitect SYBR Green PCR kit (QIAGEN) in a LightCycler 480 real-time PCR system (Roche Diagnostics, Indianapolis, IN). For relative quantification of transcripts, cycle threshold values for each sample were normalized to glyceraldehyde-3-phosphate dehydrogenase (Gapdh).  2.2.5 FLUORESCENCE MICROSCOPY AND CA2+ IMAGING Cytosolic Ca2+ was imaged using fura-2-AM as previously described (28). For each cell, the eGFP and mRFP intensities (i.e. insulin and Pdx1 expression levels) were quantified using Slidebook software (Intelligent Imaging Innovations, Denver, CO) and correlated to the incremental area under the curve of the glucose- and depolarization-induced cytosolic Ca2+ responses. eGFP fluorescence was excited using an HQ470/40 excitation filter and mRFP using an HQ575/50 filter, neither of which negatively affected the fura-2 imaging. Although the excitation of fura-2 at 340 and 380 nm slightly cross-excites eGFP (<10%), this has no appreciable impact on the cytosolic Ca2+ measurements because the eGFP intensity is stable and the fura-2 recording is ratiometric.  2.2.6 5-BROMO-2’-DEOXYURIDINE (BRDU) LABELING Sorted Pdx1+/Inslow and Pdx1+/Ins+ MIN6 cells were cultured on coverslips overnight. Medium containing 10 μM BrdU (Kit I; Roche Applied Science, Que´bec, Canada) was added for 2 h the next day. Cells were then fixed and stained according to the manufacturer’s instructions. Cells were imaged using a Zeiss Axioplan2 microscope equipped with a Coolsnap HQ CCD camera (Photometrics, Tucson, AZ). Images were acquired with Metamorph (version 4.6r1; Universal Imaging Corp., Downingtown, PA), with each channel being individually optimized. An average of 200 DAPI-positive cells were counted for each sample (n = 3).  2.2.7 INSULIN SECRETION Insulin levels in media samples were measured using RIA (rat insulin RIA kit; Linco Research, St. Charles, MO). Infected MIN6 cells were sorted directly into 48-well plates  42 containing media with 2 mM glucose or 20 mM glucose (DMEM, 2 g/l insulin-free BSA, L- glutamine, penicillin/streptomycin). Cells were incubated at 37°C for 6 h; plates were then spun at 1000 rpm for 5 min. before collecting media samples.  2.2.8 DATA ANALYSIS AND ETHICS Data are presented as mean ± SE. Statistical significance was tested by Student’s unpaired t test. P < 0.05 was considered to be significant. All replicates are independent experiments that included separate infections of cells, sorting, and downstream analysis, as noted. All experiments were approved by the local institutional review boards for animal care and biohazard use, in accordance with national and international guidelines.  2.3  RESULTS  2.3.1 HETEROGENEOUS PDX1 AND INSULIN GENE EXPRESSION IN CULTURED HUMAN AND  MOUSE ISLET CELLS We developed a novel lentiviral dual-reporter system to investigate insulin and Pdx1 expression in cultured human and mouse islet cells. This FIV vector consists of a 4530-bp mouse Pdx1 promoter directing expression of mRFP (25) and a 410-bp rat Ins1 promoter driving the expression of eGFP (Figure 2.1A). Both promoters contain all the required DNA binding sites for full β-cell-specific expression (29, 30). The expression of each reporter was verified by immunocytochemical staining for PDX1 and insulin (Supplemental Figure A2 and data not shown) and RT-PCR (see below). Having both promoter-reporter gene cassettes on a single lentiviral vector allowed for simultaneous analysis of insulin and Pdx1 promoter activity in stably infected live cells. Insulin and Pdx1 expression in human islets was heterogeneous between cells (Figure 2.1B). As expected for β-cells, 80–85% of fluorescent cells expressed both genes. However, 15–20% of cells expressed only Pdx1 (mRFP), with little or no insulin (eGFP). This is in agreement with immunocytochemical staining of insulin and PDX1 in human and mouse islets (Supplemental Figure A3) and previous immunocytochemical results from Johnson et al. (2). A small fraction of these Pdx1+/Inslow cells may be δ-cells, which are known to constitute about 5% of islet cells (31, 32). In our human islet preparations, somatostatin-positive cells constituted 3.9 ± 1.8% of total islet cells (Supplemental Figure A4). We expect δ-cells should contribute approximately 3.4-6.8% to the population of Pdx1+/Inslow cells (see Supplemental Figure A4 for calculations).   Insulin+-only cells  were also  extremely rare  (<1%).  43                           Figure 2.1 Heterogeneous expression of insulin and Pdx1 in adult β-cells. A) Dual reporter gene expression vector on the pTiger backbone. B) Activities of the Ins1 and Pdx1 promoters in whole human islets did not appear uniform across the islet. Some cells expressed only Pdx1 (arrows). A very small number of cells also expressed only insulin (arrowhead). C) Dispersed and infected primary mouse islets showed heterogeneous expression of Ins1 and Pdx1; some cells expressed insulin (GFP) at a lower level than other cells despite similar Pdx1 (RFP) levels between the cells (arrows). D) Infected MIN6 β-cells showed a similar heterogeneous insulin and Pdx1 expression profile. E) High magnification of infected MIN6 cells illustrating heterogeneity of transgene expression patterns in representative single cells; dividing cell expressing faint RFP and very faint GFP (1), double-positive cell with high expression of each transgene (2), cell expressing GFP only (3), and cell expressing RFP only (4). A FIV pTiger 14.1 kb SIN/3’LTR WPRE RRE cPPT MCS eGFP rat Ins1 promoter mRFP mouse Pdx1 promoter AmpR AmpR promoter pCMV/5’LTR Packaging signal MCS GFP RFP 200 µm D 100 μm GFP RFP  Merge C  RFP 100 μm GFP  RFP GFP  Merge  Merge  Merge 20 µm GFP RFP DAPI Merge E 1 2 3 4 B  44 Infection of dispersed primary mouse islet cells revealed a nearly identical distribution of Pdx1- and insulin-expressing cells as was observed in human islets (Figure 2.1C). The heterogeneous expression of insulin and Pdx1 was also found in infected MIN6 and INS-1 β-cells (Figure 2.1D,E and Supplemental Figure A5, see below). Using large cultures of MIN6 cells permitted more precise quantitative analysis and allowed us to circumvent the problem of Pdx1-expressing non-β-cells found in primary islet cultures. Infection efficiency in cells lines ranged from 40 to 80%, based on CMV control vectors. Of the labeled MIN6 cells, we observed 73.2 ± 0.6% Pdx1+/Ins+ cells, 24.8 ± 0.4% Pdx1+/Inslow cells, and 2.0 ± 0.3% Ins+-only cells using FACS (see Figure 2.3A below). A similar phenotypic profile was observed in the rat INS-1 β-cell line (Supplemental Figure A5). Together, these results demonstrate that primary adult human and mouse β-cells, as well as β-cell lines, are phenotypically heterogeneous in terms of their insulin and PDX1 expression.  2.3.2 CELL FATE TRACKING: MATURATION OF PDX1+/INSLOW INTO PDX1+/INS+ CELLS We next tested whether the Pdx1+/Inslow β-cell phenotype represented a stable state. After tracking the fate of labeled and dispersed mouse islet cells over 3 d, we found that 2% of the Pdx1+/Inslow islet cells began to robustly express insulin, without dividing (Figure 2.2). To study this conversion phenomenon in a larger number of cells, we used the MIN6 cell line as a model system with a shorter life span than primary β-cells. First, infected MIN6 cells were FACS sorted based on their insulin and Pdx1 promoter activities (Figure 2.3A) and analyzed by real-time RT- PCR and immunocytochemistry. Ins1, eGFP, Pdx1, and mRFP mRNA levels were significantly higher in the sorted double-positive cells relative to the Pdx1+/Inslow cells (Figure 2.3B). Consistent with the mRNA results, PDX1 and insulin protein levels were also higher in the sorted double-positive cells (Supplemental Figure A2). Pdx1+/Inslow cells were either negative or very faintly positive for insulin protein. Next, we tracked the fate of the sorted MIN6 cell groups for 44 h. Immediately after sorting, the Pdx1+/Inslow cell population was about 98% pure. All of the cells in the enriched double-positive group expressed both reporters (Figure 2.3C and data not shown). Similar to what was observed in primary mouse β-cells, Pdx1+/Inslow MIN6 cells began to robustly express insulin without dividing (Figure 2.3D). Relative to the primary cells, the rate of conversion was much faster with 21% of Pdx1+/Inslow MIN6 cells maturing within 15 h of sorting. Both the level of insulin promoter activity (eGFP intensity) and the number of double-positive cells increased with time (Figure 2.3D, i–iii). By 44 h, more than half of the cells had become double positive. Similar conversion was observed in the rat INS-1 β-cell line  45 100 µm RFP GFP Merge RFP GFP Merge RFP GFP ge RFP *GFP Merge (Supplemental Figure A6). β-Cell lines thus undergo the same process of conversion as primary β-cells, albeit at faster rates, analogous to the differences in the turnover/life span of these cell types (33). Using the MIN6 cell line as a model system thus allowed us to study long-term culture and proliferation effects in labeled β-cells. This is inherently difficult to do in primary β- cells because they proliferate at an extremely slow rate and can be kept in culture for only a limited time (33). Thus, we analyzed the proliferation rates of the sorted and cultured Pdx1+/Inslow and Pdx1+/Ins+ MIN6 cells. BrdU incorporation by Pdx1+/Inslow cells (and their progeny) was 1.72-fold greater than for the double-positive cells (Figure 2.3E). Together, these data demonstrate that individual primary islet cells and cell lines can pass from a Pdx1- expressing stage into a stage at which both Pdx1 and insulin are strongly expressed.                     Figure 2.2 Conversion of Pdx1-only cells to Pdx1/insulin-positive cells without division. Dispersed and infected adult primary mouse islets were tracked manually over 4 d; more than 100 cells were imaged and tracked every 24 h. Two percent of the 15% Pdx1+/Inslow cells began to express insulin (GFP) over the culture period studied (arrow, white circle). Most other infected cells expressed both reporters (arrowheads).  46 DMer C 15h 29h 44h E 0 10 20 30 Pdx1+/Inslow Pdx1+/Ins+ 200 µm RFP/GFP 11.6% Pdx1+ 0.8% Ins+ 35.1% Pdx1+/Ins+ 52.5% (-) i 200 µm ii * iii * 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 Ins1 eGFP Pdx1 mRFP Pdx1+/Inslow Pdx1+/Ins+ * * ** ** B RFP/GFP A                    Figure 2.3 Short-term phenotypic fate tracking of sorted β-cells. Stably infected MIN6 cells were analyzed and sorted by FACS. A) Most infected cells expressed both reporters at 73.2 ± 0.6%. However, many cells expressed only Pdx1 (RFP) at 24.8 ± 0.4% or only insulin (GFP) at 2.0 ± 0.3% (n = 5). Of note is that the Ins1 promoter shows a graded response and the Pdx1 promoter appears on/off. The two subpopulations were sorted (based on the sorting gates shown) for further analysis. B) Real-time RT-PCR revealed that Ins1, eGFP, Pdx1, and mRFP were expressed at significantly higher levels in the Pdx1+/Ins+ population. *P < 0.05; **P < 0.01 (n = 4). C) Immediately after sorting, Pdx1+/Inslow cells were about 98% pure. D) More than 500 sorted Pdx1+/Inslow cells were tracked manually in culture over 44 h. Within 15 h after sorting, 21% Pdx1+/Inslow cells began expressing insulin, without dividing (arrows). Progressively more Pdx1+/Ins+ cells were seen at each consecutive time point at 15, 29, and 44 h (i–iii), respectively. Some Pdx1+/Inslow cells (arrowhead) and some Pdx1+/Ins+ cells (asterisks) also duplicated. E) BrdU incorporation was measured in sorted Pdx1+/Inslow and Pdx1+/Ins+ MIN6 cells. Pdx1+/Inslow cells were significantly more proliferative (P < 0.01; n = 3).   After these characterizations, the MIN6 populations were maintained in culture to study long-term phenotype changes. The enriched double-positive population remained 95.5 ± 2.7% Pdx1+/Ins+ after several months in culture (~10 passages; Figure 2.4A). Interestingly, after many  47 43.4% Pdx1+/Ins+ 0.2% Ins+ 7.3% (-) 49.2% Pdx1+ B 1.6% Pdx1+ 2.9% (-) 0.1% Ins+ 95.4% Pdx1+/Ins+ A GFP 200 µm  RFP  Merge C passages, the sorted Pdx1+/Inslow cells either converted into double-positive cells (45 ± 6.5%) or remained positive for only Pdx1 (51.4 ± 8.6%; Figure 2.4B). In this respect, similar results were obtained with the INS-1 β-cell line (Supplemental Figure A4B,C). Furthermore, when the Pdx1+/Inslow cells from the long term culture were sorted once more, the same conversion phenomenon was observed, and a similar FACS profile was obtained (data not shown). Next, we seeded the sorted Pdx1+/Inslow cells at low density and maintained them in culture for 20 d without passaging (medium replaced every 2–3 d). Many resulting cell clusters were positive for both Pdx1 and insulin but some clusters remained only positive for Pdx1 (Figure 2.4C). In agreement with these observations, preliminary results from a clonal assay using sorted Pdx1+/Inslow cells showed that 46% of these sorted Pdx1+/Inslow cells matured into double- positive cells and 54% remained positive for Pdx1 only (data not shown). Together, these results provide evidence that Pdx1+/Inslow β-cells may include at least two subgroups. Roughly half of these Pdx1+ cells can transition to a stable state with strong insulin promoter activity, whereas the remaining Pdx1+/Inslow cells maintain their insulin negative or low phenotype.              Figure 2.4 Long-term phenotypic fate tracking of sorted β-cells. A) Sorted double-positive cells maintained their Pdx1+/Ins+ phenotype (95.5 ± 2.7%). B) Whereas, sorted Pdx1+/Inslow cells converted into double-positive cells (45 ± 6.5%) and also maintained a significant Pdx1+/Inslow population (51.4 ± 8.6%) after several months in culture (~10 passages). Shown are representative FACS plots. C) Previously sorted single Pdx1+/Inslow MIN6 cells (from B) were cultured without passaging for 3 wk; large colonies from single or small cell clusters were formed. Many of the colonies were positive for both Pdx1 (RFP) and insulin (GFP), but some colonies remained only Pdx1 (RFP) positive (arrows).   48     0.0 0.4 0.8 1.2 1.6 2.0 2.4 Neurod1 Isl1 Nkx6-1 Mafa Hnf3b Pax6 Hnf1a Glut2 Gck Kir6.2 Sur1 Cav1.2 Pdx1+/Inslow Pdx1+/Ins+ ** ** * * B     0.0 0.4 0.8 1.2 Mafb Nkx2-2 Pax4 Hnf1b * 2.3.3 GENE EXPRESSION PROFILES OF β-CELL MATURATION STATES We analyzed the MIN6 cells, FACS sorted based on their insulin promoter activity, for possible differences in the expression of other genes associated with β-cell maturity and function. Real-time RT-PCR revealed that a number of key genes were differentially expressed between the Pdx1+/Ins+ and Pdx1+/Inslow cells (Figure 2.5). The transcription factors Mafa and Nkx6-1 were significantly increased in the double-positive cells. MAFA is an important transcription factor for insulin expression (34), and NKX6-1 is known to be important for maintaining the mature β-cell phenotype (35). Furthermore, glucose transporter 2 (Glut2) and glucokinase, both critical genes for mature β-cell function, were upregulated in the double-positive population, suggesting possible functional differences at the level of glucose sensing (Figure 2.5A). In addition, Neurod1 and Isl1 were modestly upregulated in these cells, albeit with only P < 0.1. Conversely, a number of genes involved in early islet development (e.g. Mafb, Nkx2-2, Pax4) were generally expressed at higher levels in the immature Pdx1+/Inslow cells (Figure 2.5B) (35, 36), suggesting that the cell populations differ with respect to maturity. In conjunction with the time-lapse studies, these results strongly suggest that the observed Pdx1+/Inslow β-cells are immature β-cells that eventually transition to a more mature state in which Pdx1 and insulin are coexpressed along with the up-regulation of mature β-cell genes.           Figure 2.5 Gene expression analysis of Pdx1+/Inslow and Pdx1+/Ins+ β-cells. Infected MIN6 cells were sorted and gene expression was analyzed by real-time RT-PCR. A) Genes involved in maintaining the mature β-cell phenotype were consistently upregulated in double-positive cells, relative to the Pdx1_/Inslow cells. B) However, Mafb being involved in β-cell maturation during development was upregulated in Pdx1+/Inslow cells. *P < 0.05; **P < 0.01 (n = 4). A  49 2.3.4 GLUCOSE RESPONSIVENESS OF MATURE AND IMMATURE MIN6 β-CELLS The differential expression of glucokinase and Glut2 in the Pdx1+/Inslow and Pdx1+/Ins+ populations prompted us to examine whether the degree of Pdx1 and insulin expression levels of individual β-cells correlated with their ability to sense glucose. Mixed populations of infected MIN6 cells were loaded with fura-2 and their cytosolic calcium imaged in response to 3, 10, or 30 mM glucose and depolarization with 30 mM KCl. As exemplified in Figure 2.6A,B, these experiments clearly demonstrated that Pdx1+/Inslow cells responded to glucose and KCl equally when compared with Pdx1/insulin double-positive cells. No apparent relationship was observed between the integrated calcium response of the individual cells and their levels of Pdx1 or insulin expression (Figure 2.6C,D). Similarly, no correlation was found between the calcium response to KCl and cellular eGFP or mRFP expression (R2 = 0.01 and R2 = 0.006, respectively; data not shown). Identical results were obtained with cells cultured overnight in 5 mM glucose-containing media (n = 22 cells, data not shown). Glucose-stimulated insulin secretion requires multiple steps downstream of glucose sensing. Thus, we analyzed basal and stimulated insulin secretion in cultures of Pdx1+/Inslow and Pdx1+/Ins+ MIN6 cells immediately after sorting. Within the 6 h incubation, cells secreted about 3% of their insulin content. The immature Pdx1+/Inslow cells secreted significantly less insulin at both 2 and 20 mM glucose compared with the mature double-positive cells (Figure 2.6E,F). These data suggest that the different maturation states are associated with functional differences in glucose-stimulated insulin secretion but not glucose sensing per se.  2.4  DISCUSSION  The present study was undertaken to investigate the nature of pancreatic β-cell heterogeneity. Using a novel dual reporter lentiviral vector, the expression levels of Pdx1 and insulin were monitored in real-time on a cell-by-cell basis. Our dual promoter-reporter construct provided an internal control for each expression cassette and eliminated the complexity of cell- to-cell transduction variability associated with the use of separate lentiviral constructs (37). The major conclusion of this investigation is that adult β-cells exist in distinct maturation states, defined by differential gene expression. This observation is consistent with previously noted β- cell heterogeneity. At any given time, a significant fraction of adult β-cells exists in an immature state from which a fraction transition into a more mature state (Supplemental Figure A7). These  50 findings are relevant to the understanding of adult β-cell turnover and differentiation, both of which are critical areas related to the pathogenesis of diabetes and the treatment of the disease.                          Figure 2.6 Glucose responsiveness of mature and immature MIN6 β-cells. A, B) Examples of cytosolic Ca2+ signals evoked by glucose and KCl in Pdx1+/Inslow (hatched trace) and Pdx1/Ins double-positive (black trace) MIN6 cells. C, D) In individual MIN6 cells, the expression levels of PDX1 (GFP intensity) and insulin (RFP intensity) do not correlate with the incremental area under the curve (IAUC) for the Ca2+ response to glucose. The Pdx1+/Inslow and Pdx1+/Ins+ cells from A and B are marked by arrowheads and arrows, respectively (n = 30 cells imaged in three independent experiments). E, F) Static insulin secretion assay performed on sorted Pdx1+/Inslow and Pdx1+/Ins+ MIN6 cells at 2 mM glucose (LG) and 20 mM glucose (HG). *P < 0.05; **P < 0.01; ***P < 0.001 (n = 7).  51 Many studies previously noted heterogeneity in gene expression between individual β- cells, leading to the proposal that separate, stable subpopulations of β-cells can be found in the pancreas (1, 38-40). Such heterogeneity was consistent with the idea that a specialized group of progenitor-like cells may contribute to the supply of new β-cells in the adult pancreas (4, 5). Conversely, recent studies using lineage tracing approaches have shown that adult β-cell mass is primarily controlled by the replication of insulin-expressing β-cells (14, 15) and that all β-cells contribute equally to β-cell mass adaptation in the adult mouse (13). Hence, these studies infer that β-cells are homogeneous in their replicative potential (14). Our data revealed neither a highly proliferative progenitor nor a completely homogenous β-cell population. Rather, our findings demonstrate that up to 25% of adult human, mouse, or MIN6 β-cells are characterized by an immature state somewhat resembling the β-cell precursors seen during fetal development. Specifically, they express Pdx1 but little or no insulin and have a higher relative proliferation rate and a unique gene expression profile that includes higher levels of Mafb. The remaining majority of β-cells are found in a mature state characterized by Pdx1 and insulin coexpression as well as significantly higher levels of Nkx6-1, Mafa, Glut2, and glucokinase, all genes that establish and maintain the differentiated β-cell phenotype (41). The transition of a fraction of the immature Pdx1+-only β-cells into a mature insulin- expressing phenotype is reminiscent of β-cell formation from Pdx1+ progenitors during embryogenesis (42). Islet remodeling and β-cell maturation during the neonatal period is governed by both expansion and apoptosis of insulin-positive β-cells (43), but considerably less is known about β-cell maturation in the adult. Our imaging experiments demonstrate that most of this β-cell maturation occurs independently of cell division. One of the most interesting differences between the immature and mature cells was the ratio of Mafa to Mafb. In the embryonic pancreas, Mafb is expressed before Mafa and is then downregulated in adult β-cells (44). Accordingly, we found that the Pdx1+/Ins+ β-cells had significantly higher Mafa expression levels. Because Mafa is an important transcription factor for insulin expression (34), it may help maintain the increased insulin levels of the mature β-cell population. The significantly higher expression of Mafb in the Pdx1+/Inslow cells further supports the concept of a transient immature stage. MAFB is required for β-cell maturation and directly regulates the expression of Mafa, Pdx1, Nkx6-1, Glut2, and insulin (36), all upregulated in our mature cells. Evidence has been recently presented that a combination of Ngn3, Mafa, and Pdx1 can reprogram adult mouse exocrine cells into insulin-producing cells in vivo (45).  52 During development, Pdx1 is expressed in a wave-like pattern. It is expressed at high levels in early embryogenesis and then at low-levels in the endocrine precursor cells, and finally it reappears at high levels in differentiating and mature β-cells (46). Absolute Pdx1 levels were lower in the immature Pdx1+/Inslow β-cells relative to mature double-positive cells. Presumably the low PDX1 levels are sufficient to help promote insulin expression during the maturation process, whereas the higher PDX1 levels in mature cells may help maintain their differentiated state and promote the increased expression of Glut2 and glucokinase (47, 48). FACS analysis also revealed that the activity of the insulin promoter transgene (GFP) showed a graded response spanning 2 orders of magnitude in GFP intensity without a clear distinction between GFP- positive and GFP-negative cells. On the other hand, there was a clear separation of positive and negative cells with respect to red fluorescent protein intensity, spanning 1 order of magnitude. Thus, the Pdx1 expression pattern in maturing adult β-cells shows an intriguing resemblance to the transition from endocrine precursors to differentiated β-cells during development. Our data point to the existence of distinct β-cell maturation states (Supplemental Figure A7). The immature Pdx1+/Inslow cells can be further divided into two groups by their ability to transition into mature cells in culture. It may be that specific levels of insulin expression define different differentiation potential. The extent to which these distinct subtypes of immature cells differ with respect to gene expression and function is an interesting question for future study. One possible explanation for these MIN6 subtypes could be attributed to the inherent heterogeneity of this cell line, with the co-existence of stable glucose-responsive and glucose- unresponsive cells (40). Our data from MIN6 cells suggest that a fraction of immature β-cells may proliferate at a higher rate relative to their mature counterparts. This result is consistent with the observation that a stable Pdx1+/Inslow population is maintained despite an ongoing maturation process and no apparent transition back from the mature to the immature state. Assuming that the relative rates of proliferation were similar in immature vs. mature primary cells, replication in both maturation states would still be slower than what would be expected from a stem cell. It thus seems unlikely that recent cell marking approaches would have been able to distinguish the low frequency divisions of this immature population (13, 14). Notably, PDX1-positive and insulin-low cells in glucose-infused rats were reported to not be proliferative (49). Although we demonstrate the presence of an adult progenitor-like stage, our results are consistent with data from Dor et al. (15) favoring the maintenance of adult β-cell mass by self-duplication. In that study, the constitutive expression of a heritable label relied on insulin promoter activity. The  53 very low insulin promoter activity in some immature β-cells would be enough to label them by this method and thus make them indistinguishable from β-cells in the mature state. Recent studies suggested intriguing in vivo physiological roles for cells similar to the immature β-cell population we characterized here. In rats, chronic mild glucose infusion resulted in increased numbers of small islet clusters composed of PDX1+/insulin− and PDX1+/insulinlow cells (49). Moreover, it has been reported that a pool of GLUT2+/insulin− cells appeared during β-cell regeneration after targeted β-cell ablation (50). It may be that Pdx1+/Inslow β-cells constitute a reservoir of cells that can be mobilized to contribute to the adaptive β-cell mass expansion evoked by conditions such as injury, pregnancy, or obesity. In addition to heterogeneity in gene expression, both in vivo and in vitro studies have demonstrated β-cell variability with respect to glucose responsiveness (6-9, 51). Our gene expression data showed significantly lower levels of Glut2 and glucokinase in immature cells. The insulin secretion data are consistent with the gene expression results in that the immature β- cells secrete less insulin in response to glucose, demonstrating functional β-cell heterogeneity. However, the mature and immature populations exhibited similar glucose-induced Ca2+ responses, indicating that the GLUT2 and glucokinase levels in immature cells are sufficient for glucose sensing. The expression of ATP dependent K+ channel subunits and voltage-dependent Ca2+ channels were similar in the two sorted populations, which is consistent with reports that insulin-secreting and –nonsecreting rat β-cells show similar electrophysiological characteristics (52). An implication of these findings is that β-cells are capable of responding to glucose before the activation of high insulin expression. The exact role of glucose signals in the immature β-cell is unclear. Conceivably glucose sensing must be in place before β-cells expend the energy required to synthesize and process insulin, and may play a regulatory role in the biosynthesis process itself (53). In neurons, Ca2+ signaling activity is required for differentiation-modulating gene expression programs (54), and Ca2+ signaling may also be important in the β-cell maturation process. Together, these findings suggest multiple levels of complexity underlying functional maturation in adult β-cells and that maturation state in part underlies functional heterogeneity. In summary, we describe cellular heterogeneity in the expression of two fundamentally important β-cell genes, insulin and Pdx1, and demonstrate that this heterogeneity reflects distinct maturation states. These findings are in agreement with previous observations of β-cell heterogeneity and are also compatible with the concept that adult β-cell mass is maintained largely by replication of a relatively homogeneous pool of existing β-cells. The MIN6 cells in  54 these identifiable maturation states may serve as convenient in vitro models for investigating β- cell maturation in an accelerated manner. 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Nature 444: 707-712    59 3 RECIPROCAL MODULATION OF ADULT β-CELL MATURITY BY ACTIVIN A AND FOLLISTATIN1  3.1 INTRODUCTION  The loss of functional pancreatic β-cell mass is a hallmark of diabetes. A fundamental understanding of pancreatic β-cell fate decisions and the process of β-cell maturation is imperative to correct this defect. Using a dual reporter lentiviral system to perform single-cell analysis of β-cell differentiation, we recently characterised a dynamic immature β-cell state in adult islet cells from humans and mice, distinguished by Pdx1 promoter activity prior to Ins1 promoter activity (Pdx1+/Inslow) (1). MIN6 β-cell maturation is marked by the acquisition of Ins1 promoter activity and takes less than 15 h (1). Functional β-cell mass can adapt to changes in metabolic demand resulting from obesity or pregnancy (2), suggesting that physiological and pathophysiological factors modulate the differentiation status of adult β-cells. In vitro and in vivo, pancreatic β-cells have also been stimulated to proliferate, dedifferentiate and transdifferentiate (3-5). The plasticity of adult human pancreatic tissue has significant implications for islet regeneration and for in vitro generation of functional β-cells. However, the specific conditions and molecular cues that drive these mechanisms remain to be elucidated. Here, our aim was to define factors that modulate the maturation state of adult β-cells. Factorial design of experiments (6) was used to compare multiple candidate growth and differentiation factors simultaneously. Based on factors reported to influence the development or differentiation of β-cells, we examined the effects of glucose (7), nicotinamide (8), exendin 4 (9), insulin (10, 11), IGF-1 (12), betacellulin (12), laminin-1 (13), epidermal growth factor (14), retinoic acid (15), gastrin17 (14), hepatocyte growth factor (16) and activin A (17). To date, the effects of these factors and their interactions have not been systematically compared in one study. Activins, members of the TGFβ superfamily, elicit numerous context-dependent effects on growth and differentiation (18). Activins control embryonic patterning of foregut-derived  1 A version of this chapter has been published. Szabat M, Johnson JD, Piret JM (2010) Reciprocol modulation of adult beta cell maturity by activin A and follistatin. Diabetologia 53: 1680-1689.  60 organs (19), have important roles in pancreatic development (20) and have been implicated in the control of insulin secretion (21, 22). Activins and their receptors are present in the developing pancreas and adult islet cells (23, 24). Follistatin, a potent endogenous activin antagonist, is also produced in adult islets (23, 24). These observations suggest that activins may play dynamic, tightly controlled autocrine and/or paracrine roles in adult islets. Here, using a novel image- based screening approach, activin A was found to dedifferentiate mature β-cells. Activin A decreased expression of insulin gene and other mature β-cell genes, while increasing β-cell proliferation. These effects were fully reversed by follistatin, which augmented the mature β-cell phenotype. Our data point to a powerful local regulatory system within islets, which controls the maturity of adult β-cells.  3.2 MATERIALS AND METHODS  3.2.1 CELL CULTURE Human islets were kindly provided by G. Warnock and the Ike Barber Human Islet Transplant Laboratory (Vancouver General Hospital, Vancouver, BC, Canada) and cultured as described (11). Mouse islets were isolated from 10- to 12-week-old C57BL/6J mice as described (25) and cultured overnight in RPMI 1640 with 10% (vol./vol.) FBS. MIN6 cells were cultured as described (1). Activin A and follistatin were purchased from R&D Systems (Minneapolis, MN, USA). All doses of activin A used in this study were at a saturating level (Supplemental Figure B1). Culture reagents were from Invitrogen (Burlington, ON, Canada), unless otherwise stated. Animal and human cell protocols were approved by the University of British Columbia, Canada in accordance with national guidelines.  3.2.2 LENTIVIRAL VECTOR PRODUCTION AND INFECTION The dual reporter pTiger Pdx1 monomeric red fluorescent protein (mRFP)–Ins1 enhanced green fluorescent protein (eGFP) and control pTigerCMVeGFP and pTigerIns1eGFP lentiviral vectors were used to label MIN6 cells; details on vector construction, virus generation, infection protocols and expression validation have been described elsewhere (1). Briefly, MIN6 cells were seeded in six-well plates the day before infection. Lentiviral vectors were added at a multiplicity of infection of ~1 in serum-free DMEM (with insulin–transferrin–selenium supplement and 0.2% (wt/vol.) BSA) and 8 μg/ml protamine sulphate. Plates were centrifuged for 2 h at 30°C, then cultured overnight at 32°C. Medium was changed to complete DMEM and expression was  61 monitored at least 72 h post-infection. After infection with lentivirus, cells have stable integration of the transgene(s), allowing long-term monitoring of reporter gene expression (26). Infection efficiency ranged from 40 to 80%. However, populations of infected MIN6 cells with a particular infection efficiency were used for an individual biological replicate (i.e. treated with activin A or non-treated control) and results were always normalized to the control within the same labelled population of cells, thereby controlling for differences in infection efficiency between preparations.  3.2.3 SCREENING AND FACTORIAL DESIGN OF EXPERIMENTS JMP 7.0.2 software (SAS Institute, Cary, NC, USA) was used to design two-level (i.e. zero dose and factor added) fractional factorial experiments to screen the effects of factors on Pdx1 and Ins1 promoter activities. Initially, 12 factors were chosen at concentrations based on previous reports or preliminary single factor experiments (data not shown; Supplemental Table B1). We then chose eight factors for the second screen. The factorial design is presented in Supplemental Tables B2 and B3. The day before treatment, labelled MIN6 cells were seeded at 10,000 cells/well (ViewPlate-96; Perkin Elmer, Waltham, MA, USA) as a heterogeneous unsorted population of cells containing Pdx1+/Inslow immature cells, Pdx1+/Ins+ mature cells and cells that were not labelled (i.e. negative for both reporters). Cells were washed with basal medium (DMEM containing 5.5 mM glucose, 0.2% (wt/vol.) BSA, 4 mM glutamine, 100 U/ml penicillin and 172 μM streptomycin) and factors were added to basal medium at concentrations and combinations described in Supplemental Tables B1–B3. After 48 h of culture, the nuclear stain Hoechst 33342 (0.32 μM; Invitrogen) was added 30 min prior to automated imaging using a high-content screening instrument (ArrayScan VTI; Cellomics, Pittsburgh, PA, USA). Hoechst- positive, GFP-positive and RFP-positive cells were identified using fluorescence intensity cut- offs and then automatically counted (Target Activation Bioapplication; Cellomics). Cell count and intensity results for each factorial run were analysed by JMP 7.0.2 statistical software to identify the significant effects within each experiment. This analysis included analysis of multiple internal replicates for each factor in various combinations. Graphs are presented as per cent effect of each factor on the given read-out relative to no factors added (i.e. basal medium).  3.2.4 FLOW CYTOMETRY AND CELL SORTING For FACS analysis and sorting, stably infected MIN6 cells were lifted off plates using trypsin-EDTA, resuspended in PBS containing 5% v/v FBS and kept on ice. The influx sorter  62 (BD Biosciences, San Jose, CA, USA) used was equipped with a tunable laser at 488 nm with filters 488LP and 531/40 for GFP, and a solid-state laser at 561 nm with filters 568LP and 624/40 for RFP. Pdx1+/Inslow and Pdx1+/Ins+ cells were simultaneously sorted into chilled medium before seeding and treatment with activin A. Analysis and sorting gates are shown in a sample FACS dot plot in Supplemental Figure B2.  3.2.5 QUANTITATIVE REAL-TIME RT-PCR Total RNA was purified using a kit (RNeasy; Qiagen, Mississauga, ON, USA) and used to prepare cDNA using SuperScript III First-Strand Synthesis SuperMix for quantitative RT- PCR (Invitrogen). Primers were designed to flank an intron and are listed in Supplemental Table B4. Quantitative RT-PCR was performed using SYBR GreenER qPCR SuperMix (Invitrogen) and 7500 Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). For relative quantification of transcripts, cycle threshold values for each sample were normalized to Gapdh.  3.2.6 5-BROMO-2’-DEOXYURIDINE (BRDU) LABELLING MIN6 cells were cultured for 48 h on 96-well microplates (ViewPlate-96; Perkin Elmer) with and without activin A in basal DMEM medium, after which 10 μM BrdU (Kit I; Roche Applied Science, Laval, QC, Canada) was added for 30 min prior to fixation and staining. Cells were imaged using an inverted microscope (Axiovert 200 M) equipped with a FLUAR 20× objective (Carl Zeiss, Thornwood, NY, USA). Images were analysed and quantified using a software package (SlideBook; Intelligent Imaging Innovations, Boulder, CO, USA). A minimum of 500 cells per sample were imaged and quantified.  3.2.7 HORMONE SECRETION For static incubation, cells in 24-well plates were washed once and incubated for 1 h at 37oC in 3 mM glucose Kreb’s buffer, which was then replaced for 2 h with 3 mM glucose, 20 mM glucose or 30 mM KCl Kreb’s buffer at 37oC. Buffer samples were analysed for insulin. Secreted insulin was measured using RIA (Linco/Millipore, Billerica, MA, USA). Secreted activin A was quantified using an immunoassay (Human/Mouse/Rat Activin A; R&D Systems).      63 3.2.8 DATA ANALYSIS Data are presented as means ± SEM. Differences between means were evaluated by Student’s paired or unpaired t tests, as appropriate. A P value of 0.05 or less was considered significant. A minimum of three independent experiments was performed, as noted.  3.3 RESULTS  3.3.1 SCREENING FOR FACTORS THAT MODULATE ADULT β-CELL MATURITY Two-level factorial designs were used to screen for significant single and interaction effects. Multiple growth factors and culture medium supplements were selected on the basis of previous reports of their mitogenic, differentiating or survival effects on pancreatic cells (Supplemental Table B1). The maturation state of MIN6 cells was monitored using the dual reporter Pdx1mRFP–Ins1eGFP lentivirus described by us previously (1) in the presence of chosen factors. Pdx1+/Ins+ cells (Figure 3.1A) and Pdx1+/Inslow cells (Figure 3.1B) are shown relative to the negative control (i.e. no factors added) from two factorial experiments. All single- factor effects and only significant interaction effects are shown. After the first screen, factors that had no significant effect or had significant negative effects on one cell type (without yielding a positive effect on the other, e.g. FBS and retinoic acid) were not considered for the second screen. For both screens, 10 mM glucose alone had a strong positive effect on the relative number of immature and mature MIN6 cells. This effect was probably due to increases in total cell number (data not shown). Similarly, 10 mM nicotinamide had a positive effect on both maturation states in our second screen, but only increased the mature β-cell numbers in our first screen. Exendin-4 had a significant negative effect on the mature β-cell population in both factorial experiments. Interestingly, activin A had a strong negative effect on mature β-cells, yet a highly significant positive effect on the relative percentage of immature β-cells (Figure 3.1). Upon removal of five factors in the second screen, this opposing effect of activin A was augmented by twofold. In addition, negative and positive interactions between activin A and glucose or nicotinamide, respectively, became significant in the second screen. Similar factorial design results were observed using the INS-1 cell line labelled with the same dual reporter lentivirus (data not shown). Significant factor effects, as well as factor interactions, were uncovered using statistical design of experiments. For follow-up studies, we selected activin A as the most interesting candidate involved in modulating the maturation state of adult β-cells.  64     Figure 3.1 Screening for factors that modulate adult β-cell maturation. Factorial design of experiments was used to screen for effects of various factors on Pdx1 and Ins1 promoter activity, and maturation state of dual labelled MIN6 cells. Graphs are shown for effects (% changes) on Pdx1+/Ins+ mature cells (A) and Pdx1+/Inslow immature cells (B) relative to control (no factors). Results are shown for two independent factorial runs. Statistical tests for significant effects were assessed within each experiment, inherently by way of several internal replicates of each factor in various combinations, using statistical software. Similar results were obtained when the graphs were represented using a read-out of Pdx1+/Inslow and Pdx1+/Ins+ cell counts rather than the per cent changes (data not shown). *P<0.05. ND, not done. Factors: GLU, glucose; ACTA, activin A; NIC, nicotinamide; EX4, exendin 4; INS, insulin; BTC, betacellulin; LAM1, laminin 1; EGF, epidermal growth factor; RA, retinoic acid; GAS17, gastrin-17; FBS, fetal bovine serum; HGF, hepatocyte growth factor.                       65 A B * * * * * * ND ND ND ND ND * * * ND * * * * * * * * * * * * * * ND ND ND ND ND ND * ND        –56 –48 –40 –32 –24 –16 –8 0 8 16 24 32 40 48 56        –56 –48 –40 –32 –24 –16 –8 0 8 16 24 32 40 48 56 Factorial Factorial Factorial Factorial *                                   66 3.3.2 ACTIVIN A REDUCES  β-CELL MATURITY The effects of activin A on the relative numbers of immature and mature β-cells were examined using larger cultures of Pdx1mRFP–Ins1eGFP dual labelled, unsorted MIN6 cells. Ins1 promoter activity (GFP intensity) was significantly decreased by 4 nM activin A after 72 h of culture (Figure 3.2A). Similar results were obtained using a control single Ins1eGFP reporter vector, whereas activin A had no effect on the activity of a control promoter (CMVeGFP) (Supplemental Figure B3). Pdx1 promoter activity (RFP intensity) from the dual reporter vector was also decreased with activin A (data not shown). Confirming the results of the factorial screens, activin A treatment significantly increased the relative number of Pdx1+/Inslow immature cells (Figure 3.2B), whereas it significantly decreased the number of Pdx1+/Ins+ mature cells (Figure 3.2C). We next tested the effects of activin A on the spontaneous maturation of purified immature Pdx1+/Inslow cells (1). FACS-sorted immature Pdx1+/Inslow MIN6 cells (>99% purity) were treated with activin A. This resulted in reduced Ins1 promoter activity (GFP levels) (Figure 3.2D), a higher number of immature cells and fewer mature Pdx1+/Ins+ cells relative to control (Figure 3.2E). These results suggest that activin A decreases insulin gene promoter activity and reduces the rate of spontaneous β-cell maturation.  3.3.3 ACTIVIN A DECREASES EXPRESSION OF INSULIN AND MATURE β-CELL GENES We analysed activin A-treated primary mouse islets and MIN6 cells for changes in the expression of genes associated with β-cell maturity and function. Real-time RT-PCR revealed that several key genes were differentially expressed between treated and control cells (Figure 3.3). Specifically, Ins1, Ins2, Pdx1, Mafa and Glut2 (also known as Slc2a2) were significantly decreased in activin A-treated primary mouse islets (Figure 3.3A). Mafa is an important transcription factor for insulin gene expression (27). Similarly, Ins1, Ins2, EGFP, Pdx1, MRFP, Mafa, Nkx6-1 and Glut2 were also downregulated by activin A treatment in MIN6 cells (Figure 3.3B). Conversely, important transcription factors involved in early islet development, e.g. Mafb and Ngn3, tended to be increased in activin A-treated MIN6 cells (Figure 3.3B) (28). These results are similar to our previous data comparing sorted immature and mature β-cells, for instance, with opposite changes in expression of Mafa and Mafb (1). In preliminary experiments, similar differential gene expression profiles were observed with activin A-treated human islet cells (Supplemental Figure B4). Together, these data strongly suggest that activin A negatively regulates adult β-cell maturity.   67  Figure 3.2 Activin A decreases insulin expression and reduces maturation of immature adult β- cells. Dual labelled, unsorted MIN6 cells treated with activin A (4 nM) for 72 h were analysed by FACS for (A) GFP (Ins1) expression and for (B) changes in Pdx1+/Inslow immature versus (C) Pdx1+/Ins+ mature cell numbers relative to non-treated control. AU, arbitrary units. D,E) Sorted immature Pdx1+/Inslow cells were allowed to mature into Pdx1+/Ins+ cells for 72 h with activin A (4 nM) to assess effects on their maturation relative to non-treated control. Cells were then analysed by FACS for (D) overall GFP levels and (E) relative changes in resulting immature versus mature cell populations (n=3). *P<0.05   3.3.4 ACTIVIN A INCREASES β-CELL PROLIFERATION Since activin A decreases mature β-cell gene expression, we investigated whether β-cell proliferation was also increased in treated cells. Indeed, after 30 min we saw a 2.8-fold increase in BrdU incorporation in activin A-treated MIN6 cells (Figure 3.4). Consistent with this, we observed an 11 ± 0.5% increase in total MIN6 cell number with activin A treatment compared with control in the factorial experiments (data not shown). We had previously shown that A *  0 80 120 E C 0.0 1.0 * * 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0   62.0 64.0 65.0 66.0 67.0 68.0 D *   1.0 * * Pdx1+/Ins+  0.4 0.6 0.8 1.0 1.2 Non-treated Activin A Pdx1+/Inslow 100 63.0 60 40 20 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.7 0.8 0.9 0.2 0.0 140  68 B A * * * * *   P d x 1 + / 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 2.2 Ins1 Ins2 Pdx1 Mafa Mafb Nkx6-1 Nkx2-2 Glut2 Gck Ngn3 Mouse islet cells * * * * * * * *    0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0 Ins1 Ins2 eGFP Pdx1 mRFP Mafa Mafb Nkx6-1 Glut2 Gck Ngn3 MIN6 cells Nkx2-2 immature MIN6 cells proliferated faster than mature cells (1). Taken together, these results, along with the decreased mature gene expression patterns, suggest that activin A shifts the maturation state of β-cells towards the Pdx1+/Inslow immature phenotype with an increased proliferation potential.                         Figure 3.3 Activin A decreases expression of mature β-cell genes. A) Primary mouse islets (n=4) and (B) dual labelled MIN6 cells (n=8) were cultured with activin A (4 nM) for 72 h and cDNA samples were analysed by real-time RT-PCR. *P<0.05     69 *   0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 Non-treated Activin A               Figure 3.4 Activin A increases β-cell proliferation. MIN6 cells were treated with activin A (4 nM) or non-treated for 72 h and 10 μM BrdU was added for 30 min prior to fixing and staining for BrdU incorporation (n=3). *P<0.05   3.3.5 ACTIVIN A DECREASES INSULIN SECRETION The large decrease in Glut2 expression along with other genes important for β-cell function in activin A-treated cells prompted us to examine the  effects of activin A on insulin secretion. Activin A significantly decreased insulin secretion in primary mouse islets (Figure 3.5A) and MIN6 cells (Figure 3.5B). In preliminary experiments, insulin secretion was also 14.5% lower from activin A-treated human islets (Supplemental Figure B5). Since previous studies have reported that acute activin A treatment of cultured rat and human islets increased insulin secretion (21, 22), we also examined the acute effects of 4 nM activin A in perifused mouse islets (Figure 3.5C). We did not observe an increase in insulin secretion by activin A in the presence of 3 mM or 20 mM glucose, nor did we observe depolarisation by 30 mM KCl. In fact, we observed that activin A tended to decrease glucose-stimulated insulin secretion, although the area under curve (AUC) was not significantly different.     70  * * A B C   0.0 0.2 0.4 0.6 0.8 1.0 1.2   0.0 0.2 0.4 0.6 0.8 1.0 1.2   0 200 400 600 800 1,000 1,200 1,400 1,600 1,800 2,000 2,200 0 20 40 60 80 100 120 140 160 180 Time (min) Non-treated Activin A Mouse islet MIN6 cells Non-treated Activin A 20 mM glucose 30 mM KCl 4 nM activin A                             Figure 3.5 Activin A decreases insulin secretion. A) Primary mouse islets and (B) MIN6 cells were treated with activin A (4 nM) or non-treated for 72 h; n=4, *P<0.05. C) A perifusion experiment was performed using primary mouse islets to assess acute effects of activin A (4 nM) versus non-treated on glucose-stimulated insulin secretion n=4; area under curve (AUC) not significant.     71 3.3.6 FOLLISTATIN REVERSES THE EFFECTS OF ACTIVIN A Pancreatic islets produce many secreted factors, which can act in an autocrine or paracrine manner. Studies have shown that mouse, rat and human pancreatic islet cells produce activin A and follistatin (23, 24, 29). We also detected the activin βA subunit, activin type II receptors (actRII and actRIIB) and activin type I receptor (actRIB/alk4) in human islets (Supplemental Figure B6). Mouse islets and MIN6 cells secreted 1 to 2 pM activin A per day per 200,000 cells into the culture media (Figure 3.6A). Human islets also secreted a variable concentration of activin A into the media depending on islet purity (Supplemental Figure B7). These data suggest that activin A is released from pancreatic islets, where it can act locally to regulate maturation state of adult β-cells. Follistatin is a specific and potent antagonist of activin A, preventing binding to its receptor (30). Indeed, follistatin completely reversed the effects of activin A on Ins1 promoter activity, MIN6 maturation state, insulin gene expression and the expression of maturity- associated genes (Figure 3.6). In some cases, follistatin not only reversed the effects of activin, but appeared to have significant effects of its own, suggesting the reversal of endogenous local activin signalling (Figure 3.6B–E). Since activin A decreased insulin secretion in primary mouse and human islets, and in MIN6 cells, we investigated whether follistatin could increase insulin secretion. Indeed, activin A significantly decreased, whereas follistatin increased insulin secretion from MIN6 cells over 72 h, albeit at a P value of 0.07 (Figure 3.7A). Co-treatment with activin A and follistatin significantly increased insulin secretion. Furthermore, glucose and KCl-stimulated insulin secretion was significantly reduced by activin A and increased by follistatin in MIN6 cells (Figure 3.7B). Collectively, these results suggest that activin A dedifferentiates adult β-cells, and follistatin blocks this effect and enhances β-cell maturation.   3.4 DISCUSSION  The present study sought to identify factors that modulate adult β-cell maturity. Using dual labelled MIN6 cells (1), candidate factors were systematically screened for their effects on Pdx1 and Ins1 promoter activities. The major finding of our study was that activin A and follistatin had powerful reciprocal effects on β-cell maturity. These results contribute to the understanding of maturation and plasticity in adult β-cells.  72 A * * * C * * D * * * * * * * * * * * * * * E * * * * * B * *     0 2 4 6 8 10 12 14 16 18 20    0 10 20 30 40 50 60 70     0 50 100 150 200 250 300 350               0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 Ins1 Ins2 eGFP Pdx1 mRFP Mafa Mafb Nkx6-1 Nkx2-2 Glut2 Gck Ngn3   0 1 2 3 4 5 6 7 8 9 MIN6 cells Mouse islet cells Non-treated Activin A Follistatin ActA+Fol Non-treated ActivinA Follistatin ActA+Fol                                Figure 3.6 Follistatin increases expression of insulin gene and other mature β-cell genes. A) Rate of activin A secretion from MIN6 cells and primary mouse islets was quantified. B-D) Dual labelled MIN6 cells were treated for 72 h with activin A (2 nM), follistatin (100 nM), both or non-treated and analysed by FACS for (B) GFP (Ins1) expression and for changes in (C) immature Pdx1+/Inslow versus (D) mature Pdx1+/Ins+ cell numbers. E) cDNA samples were analysed for changes in gene expression by real-time RT-PCR; n=3, *P<0.05  73 B * * * * * Glucose (20 mM) KCl (30 mM) A    0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 1    0 2 4 6 8 10 12 14 1     0 100 200 300 400 500 600 700 800 * * Non-treated Activin A Follistatin ActA+Fol Non-treated Activin A Follistatin                      Figure 3.7 Follistatin reverses the effects of activin A on insulin secretion. MIN6 cells were cultured for 72 h with activin A (2 nM), follistatin (100 nM), both or non-treated. A) Media samples with accumulated insulin over 72 h (n=4). B) Static incubation buffer samples (n=3) were analysed for insulin at 20 mM glucose and at (C) 30 mM KCl. *P<0.05   Factorial design offers insight into the complexity of interaction of various in vitro culture conditions, factors and nutrients, while substantially decreasing the number of experiments required (31). For example, our fractional factorial design for factorial 1 required 212−6 = 64, instead of 212 = 4096 individual treatments, if all combinations of 12 factors were screened. Thus, the statistical design of experiments, which is used much more frequently in engineering science, can be a valuable tool in screening experiments designed to elucidate important interaction effects (6, 32). The factorial design method revealed a number of interesting effects on adult β-cell maturity. For example, high glucose had highly significant  74 positive effects on the relative numbers of immature and mature β-cells. Nicotinamide is generally used in cell culture media as a vitamin supplement and has been shown to promote differentiation of pancreatic fetal cells into insulin-positive cells (8). In our screens, nicotinamide also had positive effects. While synergistic or negative interaction effects can be masked in conventional screening experiments, our statistical design uncovered hidden interactions of factors including synergy between nicotinamide and high glucose, FBS or exendin-4. However, upon removal of many negative or insignificant first screen factors (such as FBS, IGF-1, retinoic acid and gastrin17) from the second screen, these synergies were lost, but new synergies between nicotinamide and activin A or insulin were uncovered. While previous studies have generally shown beneficial effects of exendin-4 on β-cell function and survival (33, 34), we observed a significant negative effect of exendin-4 on β-cell maturity. Emerging evidence of pancreatic tissue plasticity suggests that normally quiescent, terminally differentiated pancreatic cells retain the potential to dedifferentiate, transdifferentiate or increase their proliferation after specific molecular cues in vitro and in vivo (3, 5, 35). Our findings support the notion that β-cell plasticity can be modified by external molecular cues. Activin A decreased Ins1 promoter activity, downregulated expression of several mature β-cell genes, increased proliferation and dampened insulin secretion in primary islets and MIN6 cells. Conversely, follistatin completely reversed the dedifferentiating effects of activin A. Both activin A and follistatin are produced in islets (23, 24), suggesting paracrine control of β-cell maturity. Interestingly, a preliminary experiment showed that the level of the activin βA subunit was increased in human islets treated with activin A (Supplemental Figure B4), supporting a positive feedback for autocrine or paracrine regulation of activin A expression. The mature β-cell phenotype is commonly defined by the expression of genes such as the insulin gene, Pdx1, Glut2, Mafa, Neurod1, glucokinase and Nkx6-1 (36). In our activin A-treated cells, genes associated with β-cell maturity, specifically Ins1, Ins2, Pdx1, Glut2, Nkx6-1 and Mafa were downregulated. Follistatin increased the expression of these genes. Consistent with these negative effects of activin A, the TGFβ/SMAD pathway is known to restrict pancreatic progenitor specification, in part by restraining Pdx1 expression during early embryonic development (37). The notion that activin A is a tonic negative regulator of β-cell differentiation and function in the adult islet is supported by a recent study showing that TGFβ/SMAD3 signalling repressed insulin gene and other mature β-cell genes and also that downregulation of Smad3 improved β-cell function (38). Bone morphogenetic protein (BMP) signalling, also  75 mediated via SMADs, prevented β-cell differentiation in zebrafish (39). Thus, both the TGFβ and BMP superfamilies appear to have suppressive roles in adult β-cell maturation. Activin A increased expression of Mafb and decreased that of Mafa in MIN6 cells, whereas follistatin had the opposite effect. This pattern of Mafa and Mafb expression in activin A-treated cells is consistent with a dedifferentiated, immature β-cell phenotype, as it occurs during endocrine development. In murine pancreas development, Mafb is expressed before Mafa, followed by Mafb downregulation in adult β-cells (40). Mafb is required for β-cell maturation and directly regulates expression of Mafa, Pdx1, Nkx6-1, Glut2 and insulin (28). Activin A did not increase Mafb expression in primary mouse islet cells, as it did in MIN6, probably because islet α-cells express high levels of Mafb (41) and a small increase in β-cell Mafb expression with activin A treatment might not have been detectable above control. Our group previously found that neurogenin 3 (NGN3) message and protein are present in adult human islets, mouse islets and MIN6 cells, where they are regulated by notch signalling (42). Subsequently, the presence of NGN3 protein has been confirmed by others and its role in the maintenance of adult β-cell maturity was suggested (43). It is possible that activin and follistatin have reciprocal effects on NGN3 levels in β-cells, but it remains to be determined whether NGN3 mediates the effects of activin or follistatin on key β-cell genes such as Mafa and Glut2. GLUT2 is required for glucose sensing, normal glucose homeostasis and insulin secretion (44). Glut2 was one of the most highly regulated candidate genes in activin A- or follistatin- treated islets and MIN6 cells. Similarly, Glut2 was significantly decreased in Pdx1+/Inslow immature β-cells (1). Consistent with our findings, Glut2 was elevated in Smad3 knockout islets (38). A strong reduction in Glut2 expression is an early indicator of β-cell stress and possibly dedifferentiation in many mouse models of glucose intolerance or diabetes (45), including mice with reduced Pdx1 (46). It will be interesting in future to examine the characteristics and plasticity of the population of adult pancreatic cells with low Glut2 expression. Our proliferation results with MIN6 cells are also consistent with another study that showed an approximately threefold increase in proliferation of primary rat β-cells treated with activin A (47). Collectively, activin A and follistatin appear to modulate the maturation state of adult β-cells, with activin A driving mature β-cells to a more progenitor-like phenotype with increased proliferation and decreased differentiation and function. Reports on activin A effects on insulin secretion are conflicting. Acute activin A treatment of cultured rat and human islets was reported to increase insulin secretion (21, 22);  76 however acutely treated MIN6 cells did not show increased secretion (29). In our study, activin A had no acute effect on glucose-stimulated insulin secretion in perifused isolated mouse islets, while prolonged activin A treatment significantly decreased insulin secretion. It is possible that any acute activin A effects on insulin secretion may be mediated through a SMAD-independent, non-transcriptional signalling mechanism (48). In addition to its effects on β-cell function, activin A has been reported to be a differentiation factor. In vitro, it appeared to direct pancreatic fetal cells into insulin-positive cells (17). Although activin A maintains pluripotency and self-renewal of embryonic stem cells (49), it is also required to induce stem cell differentiation into insulin-positive cells (50). Our results support a dedifferentiating role for activin A in adult β-cells. In this regard, activin A receptors, activin type I receptor and activin type II B receptor, were found to be expressed at a higher level in adult versus neonatal β-cells (S. Bonner-Weir, Harvard, Boston, MA, USA; personal communication), supporting a differential role for activin signalling at different stages of β-cell development. In summary, our results demonstrate that local factors, such as activin and follistatin, control the maturation status of adult β-cells. Identification of modulators of β-cell replication and maturation will help in the development of therapies designed to increase functional β-cell mass in vivo, as well as helping find alternative sources of transplantable β-cells in vitro.                 77 3.5 REFERENCES  1. Szabat M, Luciani DS, Piret JM, Johnson JD (2009) Maturation of adult beta-cells revealed using a Pdx1/insulin dual-reporter lentivirus. Endocrinology 150: 1627-1635  2. 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J Cell Sci 118: 3573-3584  49. Beattie GM, Lopez AD, Bucay N et al (2005) Activin A maintains pluripotency of human embryonic stem cells in the absence of feeder layers. Stem Cells 23: 489-495  50. D'Amour KA, Bang AG, Eliazer S et al (2006) Production of pancreatic hormone-expressing endocrine cells from human embryonic stem cells. Nat Biotechnol 24: 1392-1401   81 4 GENE EXPRESSION PROFILING AND LINEAGE TRACING OF ADULT β-CELL MATURATION1  4.1 INTRODUCTION  Despite its importance to the understanding and treatment of diabetes, the dynamics of adult β-cell maturation remain poorly understood in part because it has previously been difficult to study the process directly. We have recently developed a novel lentiviral dual fluorescent reporter system capable of tracking the differentiation status of individual β-cells (1). Using this reporter, we identified an immature β-cell state in human, mouse and MIN6 cells that was characterized by Pdx1 promoter activity, but undetected insulin promoter activity (1). A fraction of immature β-cells underwent maturation in culture by robustly increasing insulin promoter activity, concomitant with the increased expression of insulin and genes associated with mature β-cells. We have also demonstrated that the β-cell maturity can be modulated by soluble factors, including activin A and follistatin (2). However, many questions remain, including more details on this maturation phenomenon and which genes and pathways regulate β-cell maturity. Thus, the objectives of this study were to further characterize adult β-cell maturity using live cell imaging and genomics and to generate a database of differentially expressed genes between the two β-cell maturation states, which could be of interest to the diabetes field in general. Embryonic development of the pancreas and endocrine cells is well characterized compared to the enigmatic maturation process in adult β-cells. Both extrinsic and intrinsic signals guide the complex process of pancreatic organogenesis. The pancreas develops from the definitive endoderm, specifically marked by Pyy (3), which initially receives signals from the mesoderm and ectoderm to guide organ patterning (4). Signals from the notochord and dorsal aorta, specifically FGF2 and activin B, are required for initial pancreas specification by repressing Sonic Hedgehog (Shh) expression (5). This permits the expression of essential pancreas-specific genes such as Pdx1, which is required for pancreas development (6). Lineage tracing revealed that PDX1-positive pancreatic progenitors give rise to exocrine and endocrine cells (7). Notch signaling controls the choice between the maintenance of endocrine progenitors and subsequent endocrine differentiation or adopting an exocrine cell fate via its target gene  1 An expanded version of this chapter will be submitted for publication. Szabat M, Piret JM, Johnson JD. Gene expression profiling and lineage tracing of adult β-cell maturation.  82 Ngn3 (8). Hence, the expression of Ngn3 marks the endocrine progenitor cell pool (7). A differentiated islet contains, α-, β-, δ-, PP- and ε-cells that express glucagon, insulin, somatostatin, pancreatic polypeptide and ghrelin, respectively (9, 10). It can be expected that some aspects of embryonic development are also important in the maintenance of β-cell function and mature β-cell phenotype. This is supported by recent studies showing that NGN3 protein is expressed in adult islets (11), where it regulates apoptosis (11) and maintains the differentiated β-cell phenotype (12). Similarly, Pdx1 is expressed in a wave-like pattern during development and then maintained at a high level in mature β-cells (13) where it can be regulated by external cues (14) to control cell fate decisions (15). This variable level of gene expression further suggests a gene dosage effect in addition to the on/off expression of many genes involved in the maintenance of β-cell maturity. In addition to initial pancreas specification, the transforming growth factor beta (TGFβ)/activin signaling pathways play important roles in pancreatic morphogenesis and directing cells to endocrine or exocrine fates (16-18). TGFβ, activins, and BMPs along with their receptors are expressed in different combinations and levels throughout pancreatic development (19). Negative regulators of TFGβ signaling such as follistatin are also directly involved in pancreatic cell differentiation (20). As many components of the TGFβ family are also expressed in adult islets (21), their roles in the maintenance of mature β-cell function and fate are also likely context and cell-dependent. Multihormonal cells are common during pancreatic development in humans and mice (22-25). However, whether multihormonal cells exist in adult islet cells has only been investigated rigorously in recent studies. These recent studies have reported that insulin-positive β-cells in adults co-express several combinations of endocrine hormones (26, 27). Many of these cells also expressed Pyy (26). It is possible that some adult islet cells may retain plasticity and have the potential to revert back to a fetal-like stage where multiple hormones are expressed in individual cells, perhaps under conditions of extreme stress, such as diabetes (28, 29). Characterizing the plasticity of adult β-cells has important implications for β-cell regeneration and in vitro generation of functional β-cells.  Here, we first performed in vivo labeling of β-cells in mice with the previously described lentivirus that reports both Pdx1 and insulin promoter activities simultaneously (1). This experiment confirmed the observed in vitro heterogeneity in Pdx1 and insulin gene expression also exists in vivo. Next, we tracked the maturation events of individual human immature β-cells  83 and demonstrated that continuous maturation also occurs in some human cells as it does in primary mouse and MIN6 cells. Then, we performed gene expression profiling of purified immature β-cells and mature β-cells from human and mouse islets and MIN6 β-cells. Our results suggest that immature β-cells can be multihormonal and have enriched expression of specific genes known to be important in development as well as genes associated with proliferation and apoptosis. Conversely, mature adult β-cells have increased expression levels in many genes associated with mature β-cell function. In addition, many genes with potential roles in modulating β-cell maturity and plasticity were identified.  4.2 MATERIAL AND METHODS  4.2.1 CELL CULTURE, LENTIVIRAL VECTOR PRODUCTION AND INFECTION Human pancreata were isolated as described (30) and provided by Dr. Garth Warnock and the Ike Barber Clinical Islet Transplantation Laboratory (Vancouver General Hospital, British Columbia). Typically, islet preparations were 60-80% pure immediately after isolation, as assessed by dithizone staining and cultured as described (31). Mouse islets were isolated from 10-12 week-old C57BL/6J mice as described (32), hand-picked and cultured overnight in RPMI 1640 with 10% FBS and 11 mM glucose. Human and mouse islets were dispersed into single cells as described (33), seeded into tissue culture-treated 24-well plates and allowed to attach overnight before infection. MIN6 cells were cultured as described (1). The pTigerPdx1mRFP- Ins1eGFP dual reporter lentiviral vector was used to label β-cells from human and mouse islets as well as MIN6 cells. The infected cells were cultured for 5 days before sorting to allow maximum expression of reporters. Details on vector construction, virus generation, infection protocols and expression validation were described previously (1). All human tissue and animal protocols were approved by the University of British Columbia, in accordance with national guidelines.  4.2.2 LINEAGE TRACING Dispersed human islets were seeded onto 96-well optical bottom plates (PackardView-96, Perkin Elmer) in complete medium without phenol red and cultured overnight before infection, as described (1). Infected human islets were cultured for 5 days prior to imaging to achieve maximum reporter expression. Stably infected MIN6 cells were seeded as single cells in 96-well  84 optical bottom plates (PackardView-96) and allowed to attach overnight before imaging. The live cell nuclear stain Hoechst 33342 (0.2 µg/mL; Invitrogen) was added to human and MIN6 cells 30 minutes prior to automated imaging using the high-content screening instrument ImageXpressMICRO (Molecular Devices). Images were taken in 3 channels (DAPI, FITC, TRITC) every 3 hours for 3 days (for human cells) and every 2 hours for 1 day (for MIN6 cells) in controlled environmental conditions of 37oC and 5% CO2. Propidium iodide (PI) was used at 500 ng/ml (Sigma-Aldrich) to track cell death in MIN6 cells. PI fluoresces brightly upon passing through compromised plasma membranes and binding to DNA. Although the same TRITC channel was used to acquire mRFP and PI fluorescence, PI was distinguished by intense nuclear localization in apoptotic cells. Post-acquisition analysis was performed manually using Metamorph software (Molecular Devices).  4.2.3 INTRADUCTAL LENTIVIRUS INJECTIONS The intraductal injection protocol was performed as previously described (34) with the following modifications. Mice were anesthetized and the abdominal wall was opened by linea alba to expose the duodenum where the sphincter of Oddi and common bile duct were clearly visible. One microclamp was placed under the sphincter of Oddi, the second microclamp was applied on the bile duct just caudal to the liver, to prevent vector distribution to the duodenum and liver, respectively. A 30-G needle attached to a syringe containing 98 µl of concentrated lentivirus (1.7-3.2 x 106 TU/ml) in TNE buffer (pH 7.4) plus 2 µl of green food colour was inserted into the bile duct via the sphincter of Oddi. The solution was slowly injected and the point of entry was then sealed with a tissue adhesive. The microclamps were removed 1 minute post-injection. The abdomen was closed with a two-layer approach. Mice were allowed to recover on the heating pad for 30 minutes and returned to the housing room for further observation. All surgical procedures were performed with anesthesia and analgesia under the requirements of the University of British Columbia and national guidelines. Two months after injections, mice were sacrificed and islets were isolated as described (32), hand picked and immediately imaged without culture. The Olympus Fluoview 1000 confocal microscope (10x/0.30 UPlan FL N; 20x/0.75 UPlan SApo; and 60x/1.4 Oil Plan-Apochromat, Melville, NY) was used to image whole islets.     85 Mouse islets Human islets MIN6 cells 97.61 0.82 1.44 0.13 4.2.4 FLUORESCENCE ACTIVATED CELL SORTING Stably infected dispersed primary mouse islets, human islets or MIN6 cells were lifted off plates using trypsin-EDTA and resuspended in PBS containing 5% FBS and then kept on ice. The Influx sorter (Cytopeia) was equipped with a coherent 306 water cooled argon-ion tunable laser (wavelength 488 nm with filters 488LP and 531/40 for GFP) and a Cobolt Jive 561 nm solid-state laser (wavelength 561 nm with filters 568LP and 624/40 for RFP). Pdx1+/Inslow and Pdx1+/Ins+ cells were simultaneously sorted into chilled RLT buffer (Qiagen) with 1% 2- mercaptoethanol, according to the sorting gates shown in Figure 4.1.          Figure 4.1 Heterogeneous Pdx1 and Ins1 promoter activities in primary mouse and human islets and MIN6 cells. Cells were labeled with the Pdx1mRFP-Ins1eGFP dual reporter lentivirus and sorted for immature Pdx1+/Inslow (red square) and mature Pdx1+/Ins+ cells (green square) as shown by the sorting gates. Values represent % cells in each quadrant. Note: heterogeneous GFP and RFP expression from Ins1 and Pdx1 promoters, respectively, can be seen within each cell type shown, because three different subpopulations of cells can be distinguished by the quadrants relative to negative, non-labeled cells.   4.2.5 RNA EXTRACTION, CRNA GENERATION AND LABELING AND HYBRIDIZATION TO ILLUMINA BEADCHIPS Total RNA was purified using the RNeasy Micro kit (Qiagen) from cell lysates of sorted Pdx1+/Inslow and Pdx1+/Ins+ cells, according to the manufacturer’s instructions. The RNA was treated with Dnase1. All protocols after initial RNA purification were performed at the gene expression core of Centre for Molecular Medicine and Therapeutics (Vancouver, BC). RNA from primary mouse samples was amplified and cRNA generated using the Nugen Oviation Pico WTA System, according to the manufacturer’s instructions. The mouse cRNA was labeled according to the NuGEN Illumina Solution Application Note #2 and hybridized to MouseWG-6  86 v2.0 Expression BeadChip (Illumina, San Diego, CA), following the manufacturer’s protocol. RNA from human samples was amplified, cRNA generated and labeled using the TargetAmp™ 2-Round Biotin-aRNA Amplification Kit 3.0 (Epicentre Biotechnologies, Markham, ON). Labeled human cRNA was hybridized to the HumanWG-6 v3.0 Expression BeadChip (Illumina). cRNA from MIN6 cells was generated and biotin-labeled using a standard protocol provided by Illumina and hybridized to the MouseWG-6 v2.0 Expression BeadChip (Illumina). Cy3 fluorescence signals were quantitatively detected for downstream analysis.  4.2.6 MICROARRAY DATA ANALYSIS The mouse and human microarrays contained 45281 and 48803 probe sets, respectively. Although it is recognized that many genes are represented by multiple probe sets, it is common practice to consider the expression from each probe set as if it represented one gene (35, 36). The Gene Expression Analysis Module in BeanStudio 3.3 software (Illumina) was used to process the Illumina’s BeadChip data, which was subjected to background correction, normalization and the Illumina Custom differential expression algorithm. The detection p-value was used to determine whether a particular gene was detected against background noise. A particular probe set with a detection p-value <0.05 was considered “detected” (i.e. significantly expressed). Significantly and differentially expressed genes were selected based on a detection p-value of <0.05, diff. score of >⏐14⏐ and >2-fold expression difference.  4.2.7 QUANTITATIVE REAL-TIME RT-PCR Total RNA was purified using the RNeasy Micro kit (Qiagen) and used to prepare cDNA using SuperScript™ III First-Strand Synthesis SuperMix for qRT-PCR (Invitrogen). Primers were designed to flank an intron and are listed in Supplemental Table C1. qRT-PCR was performed by using the SsoFast™ EvaGreen® Supermix with Low ROX (Bio-Rad) and 7500 Real-Time PCR System (Applied Biosystems). For relative quantification of transcripts, Ct values for each sample were normalized to GAPDH.  4.2.8 DATA ANALYSIS Data are presented as means ± SE. Differences between means were evaluated by Student’s paired or unpaired t-tests, as appropriate. A P value of 0.05 or less was considered significant. A minimum of three independent experiments were performed. For the microarray experiments, three independent biological samples were used for hybridization onto single  87 BeadChips for MIN6 cells and primary mouse islets. For the human BeadChip, 2 individual human islet samples were used due to the scarcity of donor tissue.  4.3 RESULTS  4.3.1 β-CELL MATURATION STATES IN VIVO To confirm that the observed in vitro heterogeneity in Pdx1 and insulin expression in adult islets (1) also exists in vivo, mice were injected with the dual reporter lentiviral vector via the pancreatic duct. Low viral titres were used so as to resolve single cells by only labeling a small fraction. Eight weeks post-injection, harvested whole islets were immediately imaged for RFP and GFP expression using confocal and 2-photon microscopy. Consistent with the in vitro results, individual Pdx1+-only, Pdx1+/Inslow and Pdx1+/Ins1+ cells were readily visible in the islets from these in vivo infected mice (Figure 4.2). This experiment shows the feasibility of intra-ductal in vivo labeling of β-cells using lentiviral vectors and unequivocally demonstrates that the variability in Pdx1 and insulin gene expression observed in our in vitro studies (1, 37) also occurs in vivo.             Figure 4.2 Confocal imaging of in vivo labeled mouse islets. Isolated islets are shown from mice 8 weeks post-intraductal infection with the dual reporter lentivirus. Confocal microscopy was used to image through the centre plane of islets and representative images are shown. This demonstrates that the observed in vitro heterogeneity also exists in vivo. Pdx1+/Inslow cells (arrows) and Pdx1+-only cells are observed (arrowheads) along with a majority of Pdx1+/Ins+ cells (n=3).  300 μm   RFP GFP Merge Merge/DIC RFP GFP  88 4.3.2 LINEAGE TRACING OF ADULT β-CELL MATURATION We previously reported that immature Pdx1+/Inslow MIN6 cells continuously acquire insulin expression over time in culture (1). We also demonstrated that this event occurs in dispersed primary mouse islet cells with a frequency that correlates with their extremely slow proliferation rate (38, 39). Importantly, maturation of these Pdx1+ (or mRFP+) cells, as measured by the increased expression of eGFP from the Ins1 promoter, occurred in mouse islets without cell division (1). We wanted to further characterize the maturation events in MIN6 cells with respect to cell division. The kinetics of insulin and Pdx1 expression during death and cell division were also unclear. Lineage tracing of MIN6 cells revealed that most maturation events do not require cell division (Figure 4.3A). We also observed cell division of both mature (Figure 4.3A) and immature MIN6 cells (data not shown) without obvious changes in Pdx1 and Ins1 promoter activities. In addition, as dying cell nuclei become condensed and acquire PI staining, eGFP and mRFP levels become markedly decreased (Figure 4.3B). We also asked whether the maturation events could be documented in primary human β-cells. Indeed, a small number of immature Pdx1+/Inslow human cells acquire Ins1 promoter activity continuously yet slowly in culture (Figure 4.3C). These results suggest that the maturation process of immature β-cells does not require cell division.  4.3.3 ANALYSIS OF GENE EXPRESSION PROFILES OF IMMATURE AND MATURE ADULT β-CELLS In our previous work, we used a panel of selected known β-cell genes to define β-cell maturity (1). Here, our aim was to extend our characterization of the identified adult β-cell maturation states to a larger panel of genes in order to define genetic signatures of β-cell maturity. We performed microarray gene expression analysis of labeled and purified Pdx1+/Inslow and Pdx1+/Ins+ cells from primary mouse and human islets and MIN6 cells (Figure 4.1). The purity of sorted Pdx1+/Inslow and Pdx1+/Ins+ cells was consistently ~99% (Supplemental Figure C1). Sorting gates were set by cell size to minimize the inclusion of doublets and cell particles (data not shown). In addition, both promoters were shown by others to contain all of the β-cell specific enhancers that restrict endogenous expression to adult β-cells (40-47). Using the Illumina software (BeadStudio) to identify genes expressed at significant levels within each tissue type (i.e. p-value <0.05), we found 1.6%, 3.7% and 2.4% of genes present on the microarrays were expressed only by immature Pdx1+/Inslow mouse, human and MIN6 β-cells, respectively (Figure 4.4). By comparison, 4.4%, 5.8% and 2.5% of genes were expressed only by  89      Figure 4.3 Lineage tracing of adult β-cell maturation. A,B) MIN6 cells stably infected with the Pdx1mRFP-Ins1eGFP dual reporter lentivirus were tracked every 3 h for 72 h as single cells using high-content imaging technology. A) Cells expressing only RFP (Pdx1) at time point t1 (arrowheads) gradually acquired robust GFP expression (insulin) over time without dividing. A mature RFP/GFP double-positive cell becomes apoptotic over time, as evidenced by gradual nuclear condensation and stronger Hoechst fluorescence and nuclear PI acquisition (arrows). A cell that matured over the time points shown also divided at time point t4 (arrowhead, asterisk). B) As the RFP/GFP double- positive cells begin to die, the cells lose RFP and GFP fluorescence over time. Classic apoptotic nuclei are apparent (arrowheads, arrow) and one cell acquires PI staining (arrow).  C) Dispersed human islets were infected with the dual reporter lentivirus and imaged 5 days later. Cells were tracked every 3 h over a 72 h period. Four RFP+-only (Pdx1+) cells began to acquire GFP fluorescence at different time points (arrowheads versus asterix). Shown here are overlay images of 3 fluorescence channels and maturation is shown by the changing of cells from RFP+-only to orange to yellow with increasing GFP fluorescence.                    90 * * Hoechst Ins1 Pdx1   PI (nuclear) A t1 t2 t3 t4 Merge Pdx1  Ins1  Hoechst  PI B                   t1 t2 t3 t4 t5 t6 t7 t8 t9 t10 t11 t12 t13 t14 Pdx1  Ins1  Hoechst * * * C * * * * * * * * * * *  91 mature Pdx1+/Ins+ mouse, MIN6 and human β-cells, respectively (Figure 4.4). Next, we used 2 selection filters based on at least a 2-fold expression difference and a diff. score of > ⏐14⏐ to identify differentially expressed genes. As a result, we identified 59, 515, and 215 differentially expressed genes between immature and mature mouse, human and MIN6 β-cells, respectively. For complete lists of these differentially expressed genes passing all selection filters see Supplemental Tables C2-C4. It should be noted that genes referred to from the human microarray are identified in uppercase letters, mouse genes in lowercase letters and MIN6 genes in lowercase letters with an asterisk. In cases where one gene was identified in more than one microarray, the symbol format used represents the most highly expressed gene. For example, glucagon was significantly upregulated in both human and mouse immature β-cells, therefore Gcg (in lowercase) would represent both cell types because it was expressed at a higher lever in the mouse. A subset of 83 differentially expressed genes was systematically selected based on known functions and potential functions based on gene family associations reported in literature to be involved in development, proliferation, death and β-cell function/maturity. These were then analyzed for fold changes in expression levels between immature and mature β-cells (Table 4.1).                        Figure 4.4 Genes expressed in immature Pdx1+/Inslow versus mature Pdx1+/Ins+ β-cells. Venn diagrams illustrating genes that were significantly expressed (i.e. p-value <0.05) in (A) mouse, (B) human and (C) MIN6 β-cells. A Mouse B Human C MIN6  92 4.3.4 IMMATURE β-CELLS HAVE ENRICHED EXPRESSION LEVELS OF ISLET HORMONES AND SELECT GENES INVOLVED IN DEVELOPMENT, PROLIFERATION AND APOPTOSIS One of the objectives of this study was to define a gene expression pattern unique to immature adult β-cells in order to identify putative β-cell ‘progenitor’ markers. Of the subset of selected genes, several genes and genes in families with functions related to development, proliferation and apoptosis were upregulated in immature Pdx1+/Inslow β-cells (Table 4.1). Conversely, immature Pdx1+/Inslow β-cells had a decreased expression level of many genes associated with β-cell function such as transport proteins (Table 4.1). Immature β-cells from mouse and human islets had increased expression of pancreatic polypeptide (Ppy) and glucagon (Gcg). Human immature β-cells also expressed somatostatin (SST) and ghrelin (GHRL) at a much higher level than mature β-cells (Table 4.2). Remarkably, GHRL was the most strongly upregulated genes in the human microarray (Supplementary Table C3). Consistent with the progenitor-like phenotype of immature β-cells (1, 48), 12 of the 19 selected genes with previously reported roles in cellular differentiation and development were increased, such as musashi homolog 2 (MSI2), regulatory factor X 2 (RFX2), peptide YY (Pyy) and vimentin (VIM) (Table 4.1). Adhesion and extracellular matrix genes, such as CD36, mucin 13 (MUC13) and laminins, LAMB1 and Lamb3*, were also enriched in immature β-cells. Surprisingly, calcium/calmodulin-dependent protein kinase II gamma (CAMK2G), which regulates effects of calcium on insulin secretion in mature β-cells (49), and MAPK4 were increased in immature β- cells, whereas MAPK1 was decreased in immature cells. We previously showed that immature MIN6 cells have an increased proliferation rate (1). Indeed, 12 of the 15 selected genes involved in proliferation and associated with apoptosis were strongly upregulated in immature β-cells from human islets and MIN6 cells, including fibroblast activation protein (FAP), transmembrane 4 L six family member 4 (TM4SF4), caspase recruitment domain family member 11 (CARD11) and DNA-damage inducible transcripts 3 and 4 (Ddit3* and Ddit4*) (Table 4.1). Interestingly, several genes with functions related to diabetes were also enriched in immature β-cells such dipeptidyl-peptidase 4 (DPP4), leptin receptor (LEPR), tribbles homolog 3 (Trib3*) and sirtuin 5 (SIRT5). Another interesting gene upregulated in immature β-cells was syntaphilin (SNPH), which inhibits the formation of the SNARE complex and regulates vesicle exocytosis (50). Taken together, the enriched expression levels of many developmentally important genes and genes associated with proliferation in immature adult β-cells is consistent with a progenitor-like phenotype.  93 Table 4.1 A subset of differentially expressed genes selected based on known function from human, mouse and MIN6 microarrays. Immature β-cell   Mature β-cell Name Definition aFold Δ Name Definition aFold Δ Plasticity and developmental   Plasticiy and developmental PRG-3 Plasticity-related gene 3 11.695 BMP5 Bone morphogenetic protein 5  3.241 IRX2 Iroquois homeobox 2  6.300 TGFBR3 Transforming growth factor, b receptor 3 3.245 MSI2 Musashi homolog 2 2.527 GREM1 Gremlin 1 2.514 VIL1 Villin 1 4.734 DACH2 Dachshund homolog 2 2.740 RFX2 Regulatory factor X 2 2.200 IRX3 Iroquois homeobox 3  2.331 Pyy Peptide YY 2.698 DLK1 Delta-like 1 homolog 3.247 Klf4* Kruppel-like factor 4 2.794 FOXN2 Forkhead box N2 2.079 Sox11* SRY-box containing gene 11 2.807 BAMBI BMP and activin membrane-bound inhibitor 2.739 FSTL5 Follistatin-like 5  2.985 VIM Vimentin 1.990 FOXP4 Forkhead box P4 2.071 Cell adhesion and matrix  Cell adhesion and matrix CD36 Cluster of differentiation 36 4.054 ITGB7 Integrin, b7 12.741 MUC13 Mucin 13 4.050 LAMB1 Laminin, b1 2.033 Lamb3* Laminin, b3 3.021 β-cell function/maturity  β-cell function/maturity SNPH Syntaphilin 3.484 Pdx1 Pancreatic duodenal homeobox 1 2.205 CAMK2G Calcium/calmodulin-dependent protein kinase II γ 3.052 GCGR Glucagon receptor  2.058 MAPK4 Mitogen-activated protein kinase 4 3.399 IAPP Islet amyloid polypeptide 2.202    CAPN13 Calpain 13 6.115    G6PC2 Glucose-6-phosphatase 2 2.663    TIPRL TOR signaling pathway regulator-like  2.278    CALML4 Calmodulin-like 4 3.597    MAPK1 Mitogen-activated protein kinase 1 7.246 Islet hormones PPY Pancreatic polypeptide 11.211 Gcg Glucagon 5.286 SST Somtostatin 4.694 GHRL Ghrelin 27.56   94 Immature β-cell   Mature β-cell Name Definition aFold Δ Name Definition aFold Δ Diabetes-related  Diabetes-related SORBS1 Sorbin and SH3 domain containing 1 6.554 SIRT1 Sirtuin 1  2.189 DPP4 Dipeptidyl-peptidase 4 4.486 REG1A Regenerating islet-derived 1 alpha 2.289 LEPR Leptin receptor 2.429 Trib3* Tribbles homolog 3 2.901 SIRT5 Sirtuin 5 2.197 Death and proliferation  Death and proliferation CHN2 Chimerin 2 11.626 BMF Bcl2 modifying factor 3.843 FAP Fibroblast activation protein 5.126 CFLAR CASP8 and FADD-like apoptosis regulator 4.132 TM4SF4 Transmembrane 4 L six family member 4 3.671 DDX58 DEAD box polypeptide 58 2.058 PTP4A3 Protein tyrosine phosphatase type IVA 3  5.819 ALK Anaplastic lymphoma receptor tyrosine kinase 2.964 CARD11 Caspase recruitment domain family member 11 2.801 DAP Death-associated protein 2.360 DFFA DNA fragmentation factor alpha polypeptide 2.113 Ddit3* DNA-damage inducible transcripts 3  3.987 Ddit4* DNA-damage inducible transcripts 4 2.033 Anxa2* Annexin A2 3.335 Bbc3* Bcl2 binding component 3  2.108 Solute carrier/transport  Solute carrier/transport Slc4a1* Solute carrier family 4 (anion), member 1 2.686 Slc39a8* Solute carrier family 39 (metal ion), member 8 3.534 SLC5A1 Solute carrier family 5 (sodium/glucose), member 1 3.857 Slc39a9 Solute carrier family 39 (zinc transporter), member 9 2.203 SLC40A1 Solute carrier family 40 (iron-regulated), member 1 3.294 Slc2a3* Solute carrier family 2 (glucose), member 3  2.004 SLC44A3 Solute carrier family 44, member 3 2.880 Slc5a10* Solute carrier family 5 (sodium/glucose) , member 10  2.016 SLC22A4 Solute carrier family 22 (organic cation/ergothioneine), member 4 2.800 Slc14a2* Solute carrier family 14 (urea ), member 2 2.075 SLC7A14 Solute carrier family 7 (cationic amino acid), member 14 2.291 SLC2A2 Solute carrier family 2 (glucose), member 2  2.825 SLC35F4 Solute carrier family 35, member F4 2.271 SLC6A6 Solute carrier family 6 (neurotransmitter/taurine), member 6 2.326    SLC6A15 Solute carrier family 6, member 15 2.506    SLC17A6 Solute carrier family 17 (inorganic phosphate), member 6 2.924    SLC39A11 Solute carrier family 39 (metal ion transporter), member 11 2.941    SLC38A6 Solute carrier family 38, member 6 3.003    SLC16A10 Solute carrier family 16 (aromatic amino acid), member 10  3.268    SLC25A29 Solute carrier family 25, member 29, mitochondrial protein 3.413 a  Values represent relative increase in gene expression levels in immature Pdx1+/Inslow cells (left side) and mature Pdx1+/Ins+ cells (right side) NOTE: Human gene symbols (uppercase), mouse gene symbols (lowercase), MIN6 gene symbols (lowercase with asterisk)   95 Table 4.2 Summary of microarray and qRT-PCR results for differentially expressed islet hormone genesa.   Microarray Resultsb qRT-PCR Confirmationc Gene Symbol Human Mouse MIN6 Human Mouse MIN6 Gcg 2.436 5.286 0.745 9.287 7.456 0.309 GHRL 27.559 ND ND − − − Ppy 11.211 2.992 0.785 1.651 3.029 0.682 SST 4.694 3.181 0.833 2.994 0.673 2.264 a values represent expression levels of genes from Pdx1+/Inslow immature cells relative to Pdx1+/Ins+ mature cells b bold values represent significantly (p-value <0.05) and differentially expressed (diff. score > ⏐14⏐ and >2-fold) genes from the corresponding microarray (i.e. human, mouse, MIN6) c highlighted values from qRT-PCR results represent positive correlations in fold expression across at least 2 cell types ND - not detected (i.e. p-value >0.05 for microarray) '−' qRT-PCR confirmation not done   4.3.5 FUNCTION-RELATED GENES ARE ABUNDANT IN MATURE ADULT β-CELLS From the subset of selected genes, mature β-cells expressed several genes and genes in families known to be important for β-cell function at a high level, relative to immature β-cells. For example, consistent across all three microarrays, there was a striking increase in the number of solute carrier family of transport proteins enriched in mature β-cells (Table 4.1). Specifically, there were a total of 20 differentially expressed genes belonging to the solute carrier family from all three microarrarys (Supplementary Tables C2-C4). Of those, 13 were upregulated in mature β-cells. Similar trends of increased expression of these genes in mature β-cells were observed in the individual human, mouse and MIN6 microarrays (Table 4.3). The expression of zinc transporters Slc39a8* and Slc39a9 as well as glucose transporters such as SLC2A2 (GLUT2), all markers of functional glucose-responsive β-cells, was increased in mature β-cells. Interestingly, sirtuin 1 (SIRT1), a putative drug target for glucose homeostasis (51), was increased in mature β- cells by contrast to the mitochondrial SIRT5 in immature β-cells. Although genes in the TGFβ superfamily are commonly involved in developmental pathways, some genes and modulators in this signaling pathway were upregulated in mature β-cells, such as bone morphogenetic protein 5 (BMP5), gremlin 1 (GREM1) and TGFβ receptor 3 (TGFBR3). By contrast, other genes from the same family, including FSTL5 and BAMBI were enriched in immature β-cells. In addition, several function and maturity-related genes were enriched in mature β-cells including Pdx1,  96 glucagon receptor (GCGR), islet amyloid polypeptide (IAPP), and mitogen-activated protein kinase 1 (MAPK1) (Table 4.1). Overall, an abundance of genes upregulated in Pdx1+/Ins+ cells is consistent with a functionally mature β-cell phenotype.   Table 4.3 Summary of expression patterns of all genes belonging to the solute carrier family differentially expressed in individual human, mouse and MIN6 microarraysa.  Microarray Immature β-cells Mature β-cellsb TOTAL Human 6 8 14 Mouse 0 1 1 MIN6 1 4 5 TOTAL 7 13 20 a values represent the number of solute carrier family genes upregulated in immature or mature β-cells from the respective human, mouse or MIN6 microarray b NOTE: notice an increased number of these genes expressed at higher levels in mature β-cells   4.3.6 DEFINING THE GENETIC PROFILES OF ADULT β-CELL MATURATION STATES We previously reported the decreased expression in immature MIN6 cells of a selected panel of key β-cell genes associated with maturity and function (1). Hence, we wanted to verify that these same genes were also downregulated in immature primary mouse and human β-cells, as a positive control for qRT-PCR experiments prior to microarray follow-up. Indeed, INS/Ins1, Pdx1, Glut2 (mouse), GLUT1 (human), Mafa, and Nkx6.1 had decreased expression in immature primary β-cells (Figure 4.5). Mafb was enriched in immature human and mouse β-cells (Figure 4.5), similar to the MIN6 results (1). We chose several candidate differentially expressed genes from the microarray data for confirmation by qRT-PCR (Table 4.4). Some of these genes were chosen based on the objective to identify unique/novel cell surface markers differentially expressed on immature or mature β- cells for the purposes of cell purification without the need for genetic labeling. Accordingly, of the chosen genes for follow-up, 77% were confirmed in the respective cell type (i.e. human, mouse or MIN6 β-cells). Although a strong correlation between all three microarrays was not evident in the genes selected for follow-up, the qRT-PCR results showed that 55% of genes that were followed-up in at least 2 cell types had similar expression patterns (i.e. highlighted values in Table 4.4). For example, these genes with similar expression patterns enriched in immature β- cells included islet hormones (e.g. PPY, Gcg, SST) (Table 4.2), genes involved in apoptosis and proliferation (e.g. Ddit3*, Anxa2*), the definitive endoderm marker Pyy, as well as others (e.g.  97 Trib3*). Genes that were enriched in mature β-cells that had similar expression patterns in at least 2 cell types included transport proteins such as Slc39a9 and SLC2A2 (GLUT2), and the calcineurin inhibitor Rcan2. In summary, the majority of significantly and differentially expressed genes selected for follow-up were confirmed by qRT-PCR, providing more confidence for the results from the microarrays. Collectively, from the subset of selected genes, many genes involved in β-cell function were enriched in mature Pdx1+/Ins+ β-cells. Conversely, many genes associated with development and differentiation were enriched in Pdx1+/Inslow immature β-cells. These results are consistent with the notion that adult β-cells exist in different maturation states that can be distinguished by unique gene expression profiles.              Figure 4.5 Real-time RT-PCR analysis of immature and mature human and mouse β-cells. Decreased expression of mature β-cell genes in immature primary (A) human and (B) mouse Pdx1+/Inslow cells. Mafb expression is enriched in immature cells. *P<0.05 (n=3).           A B Pdx1+/Inslow Pdx1+/Ins+ 0.0 1.0 2.0 3.0 4.0 5.0 6.0 INS PDX1 GLUT1 MAFA NKX6-1 MAFB * * * * Ins1 Pdx1 Glut2 Mafa Mafb * 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 * * * *  98 Table 4.4 List of gene whose expression was investigated by qRT-PCRa   Microarray Resultsb qRT-PCR Confirmationc Gene Symbol Human Mouse MIN6 Human Mouse MIN6 Greb1* ND ND 11.872 ND ND 9.371 PPY 11.211 2.992 0.785 1.651 3.029 0.682 KCNIP1 7.949 0.844 1.330 6.096 − − Defb1* 1.256 1.168 7.439 1.921 1.158 6.946 Adcy8* ND ND 7.297 − 1.347 3.705 KCNJ2 5.336 ND ND 1.238 − − Gcg 2.436 5.286 0.745 9.287 7.456 0.309 GBP2 5.252 1.719 ND 0.998 − − Ecel1* 0.678 ND 5.188 0.224 ND 2.874 FAP 5.126 ND ND 6.177 − − Fxyd2* 0.745 ND 5.025 0.823 ND 1.730 SERPINA1 4.944 − − 2.664 − − SST 4.694 3.181 0.833 2.994 0.673 2.264 Npr2* 0.483 ND 4.382 0.474 1.039 2.455 FXYD5 4.066 ND 0.838 3.787 − − CD36 4.054 ND ND 6.216 − − MUC13 4.050 ND 1.012 4.096 − − Ddit3* 0.632 1.252 3.987 1.189 1.282 2.608 Anxa2* 0.987 ND 3.335 1.47 4.306 2.897 SLC40A1 3.294 0.817 1.016 3.03 − ND Trib3* 0.948 2.467 3.234 1.411 1.257 2.097 Lamb3* 1.536 ND 3.021 − − ND FSTL5 2.985 ND 1.443 2.39 − − TMEM145 2.977 − − 5.857 − − Klf4* 0.609 ND 2.907 ND 0.902 1.613 LMCD1 2.834 ND 1.044 ND − − CARD11 2.801 ND ND 2.325 − − BAMBI 2.739 ND ND 4.783 − − Pyy ND 2.698 0.837 3.91 3.305 1.076 DAP 2.360 0.700 1.039 1.764 − − SLC7A14 2.291 1.108 0.998 1.598 − − ELL2 2.129 ND 0.980 1.697 − − Sgk3 0.370 2.120 0.722 0.503 1.613 0.656 Bbc3* ND 1.190 2.108 1.212 0.843 1.159 Zfp598* − 1.100 2.050 − 0.613 0.852 TP53I3 2.022 − − 1.822 − − VIM 1.990 ND ND 3.147 − − Slc2a3* 0.793 ND 0.499 − 3.100 0.514 CA8 0.490 − − 0.709 − − GCGR 0.486 ND ND 0.622 − − NPY 0.484 ND 0.995 0.477 − − Slc14a2* 0.964 ND 0.483 − − − FOXN2 0.481 ND ND 0.684 − − Loc100045869* − ND 0.472 − 0.924 0.419 Slc39a9 0.672 0.454 0.792 − 0.524 0.808 IAPP 0.454 0.936 1.042 0.195 − − REG1A 0.437 − − 0.564 − −  99  Microarray Resultsb qRT-PCR Confirmationc Gene Symbol Human Mouse MIN6 Human Mouse MIN6 Zfp512 − 0.435 0.931 − 1.061 0.9 Rcan2 1.227 0.418 1.016 − 0.664 0.789 DDEF1 0.408 − − 0.281 − − Ctsc* 0.907 ND 0.390 − ND 0.492 G6PC2 0.376 0.616 0.911 0.302 − − SLC2A2 0.354 0.766 0.621 0.312 0.712 0.56 BMP5 0.309 ND ND 0.366 − − DLK1 0.308 ND 0.768 0.27 − − TGFBR3 0.308 ND ND 0.45 − − Slc39a8* 0.382 ND 0.283 − ND 0.368 Neu1 0.988 0.277 0.933 − 0.775 0.629 a values represent expression levels of genes from Pdx1+/Inslow immature cells relative to Pdx1+/Ins+ mature cells b bold values represent significantly (p-value <0.05) and differentially expressed (diff. score > ⏐14⏐ and >2-fold) genes from the corresponding microarray (i.e. human, mouse, MIN6) c highlighted values from qRT-PCR results represent positive correlations in fold expression in genes across at least 2 cell types ND - not detected (i.e. p-value >0.05 for microarray; Ct value >35 for qRT-PCR) '−' qRT-PCR confirmation not done or gene not present on microarray   4.4 DISCUSSION  Although β-cell maturation is well described during embryonic and perinatal development (52-54), much less is known about β-cell maturation and maintenance of β-cell function and fate in the adult. Hence, we performed lineage tracing and gene expression profiling of adult β-cell maturation states in mouse, human and MIN6 cells to provide insight into the enigmatic maturation process and the specific gene expression patterns and pathways involved. Lineage tracing of labeled human islets confirmed that human Pdx1+/Inslow β-cells are able to increase insulin promoter activity and become mature in culture, as previously shown for mouse and MIN6 β-cells (1). Lineage tracing of MIN6 cells revealed that the maturation process occurs continously and does not require proliferation. Our microarray results indicated that purified adult Pdx1+/Inslow cells have an enriched expression level of many genes and gene families associated with development and progenitor differentiation (26, 48). The genetic signature of Pdx1+/Ins+ cells is also consistent with a mature, functional β-cell phenotype (9). Together this establishes that adult β-cells exist in different maturation states defined by unique gene expression profiles and that the immature β-cells can undergo a maturation process that occurs  100 independently of proliferation. Generating a database of differentially expressed genes between the two maturation states of adult β-cells will provide markers and targets for studying β-cell plasticity and dedifferentiation, which could be valuable for the diabetes field in general. The loss of β-cell maturity and function (i.e. dedifferentiation) has hindered islet transplantation efforts (55, 56).  Many developmentally important genes that are not normally expressed at high levels in adult β-cells were strongly upregulated in immature Pdx1+/Inslow β-cells. Endocrine cells share numerous developmental pathways with neuronal cells (57). Plasticity-related gene 3 (PRG-3) is part of a gene family that is involved in neuronal plasticity (58). Strong differential expression of this gene in immature β-cells, suggests that it could also play a role in β-cell plasticity. Iroquois homeobox 2 (IRX2), a homeobox gene family member, has been implicated in the development of the nervous system (59) and was also abundantly expressed in immature β-cells. A detailed global gene expression study by Gu et al. (48) revealed Irx3, Klf5, Sox17, Sox11, Vil1, Vim, Mafb, and Anxa4 to be enriched in endoderm, Pdx1-positive pancreatic progenitors and Ngn3- positive endocrine progenitors. Our results showed that IRX2, Kfl4, Sox11, VIL1, VIM, Mafb and Anxa2, were upregulated in immature β-cells. Surprisingly however, IRX3 was enriched in human mature β-cells. Furthermore, Klf4 and Sox2 were part of a cocktail of four transcription factors used to generate induced pluripotent stem cells from human fibroblasts (60). Sox17 is essential for definitive endoderm formation (61) and patterning of the ventral pancreas where it is expressed at E8.5 along with Pdx1 (20). These studies implicate the SRY-box containing genes (Sox) to be involved in differentiation and modulating cellular plasticity (62). Taken together, based on this panel of genes, the gene expression profile of immature β-cells is comparable to that of progenitors during pancreatic development. Interestingly, vimentin (VIM) has been recently shown to be co-expressed in developing insulin-positive human and sheep β-cells, supporting a role for an epithelial–mesenchymal transition (EMT) during β-cell maturation and islet morphogenesis (63). In addition, lineage tracing has provided strong evidence for EMT in adult human β-cells induced to proliferate in vitro. These cells undergo rapid dedifferentiation with loss of mature β-cell genes such as insulin, Pdx1, Glut2, and glucokinase among others and also strongly acquire vimentin expression and other mesenchymal stem cell markers (64). Furthermore, a large scale gene expression study comparing expanded versus non-cultured human islets also noted the upregulation of mesenchymal stem cell markers, SOX4 and KLF4/5 (65). These studies are  101 consistent with our results showing that immature human and mouse adult β-cells have a dedifferentiated, progenitor-like phenotype (1). The reduced insulin secreting function of immature β-cells (1) is further supported by the increased expression of syntaphilin (SNPH) in these cells. Stored insulin release from β-cell granules involves vesicular and membrane proteins, VAMP-2/cellubrevin and SNAP- 25/syntaxin-1, respectively (66). SNPH negatively regulates vesicle exocytosis by binding to syntaxin-1, directly competing with SNAP-25 and inhibiting the formation of the SNARE complex (50). Surprisingly, calcium/calmodulin-dependent protein kinase II gamma (CAMK2G), a protein that modulates calcium signaling in the insulin secretion pathway (67) was increased in immature β-cells. Conceivably, calcium signaling and glucose sensing must be in place before robust expression of insulin and maturation of β-cells takes place. This notion is supported by our previous study where immature β-cells had decreased insulin secretion but similar glucose-stimulated Ca2+ profiles compared to mature β-cells (1). Furthermore, CAMK2G and Ca2+ signaling may also be involved in proliferation and differentiation, as was seen in myeloid leukemia cells and neurons (68, 69), respectively. One of the objectives of this research was to identify the genetic signature of immature adult β-cells and novel regulators of adult β-cell maturation. Several interesting candidate genes were identified such as Pyy, RFX2, and MSI2, each being significantly upregulated in primary immature β-cells. PYY is produced in a fraction of adult pancreatic α-cells and L-cells of the gut. It is expressed during the early stage of endocrine differentiation (E9.5) and co-localizes with glucagon/insulin bihormonal cells (70). Pyy was shown to be expressed exclusively in the definitive endoderm and foregut during early development (3), making it a good candidate marker for progenitor cells in the adult pancreas. Although only rare β-cells, 40% of α-cells, and all PP cells arise from Pyy-positive progenitors during pancreatic development (70), it will be interesting to investigate its role in adult β-cell maturation. We have also confirmed the expression of Pyy by qRT-PCR to be at least threefold higher in primary human and mouse immature β-cells (Table 4.2). Both Rfx3 (71) and Rfx6 (72) have been recently implicated to have novel roles in endocrine differentiation. RFX6 appears to act downstream of NGN3 in directing islet differentiation and Rfx6-null late embryonic pancreata have decreased expression of Pdx1, Mafa, Neurod1 (72). RFX transcription factors generally bind as dimers to their DNA binding sites (73). Since RFX6 interacts with RFX2 and RFX3 (74), the expression of RFX2 in immature β-  102 cells suggests that it may also regulate the expression of β-cell maturity genes and has a yet undefined role in β-cell maturation. The translational repressor Musashi (MSI), which has 2 mammalian homologues, is involved in regulating stem cell fate, including that of the intestine (75-78). Interestingly, MSI protein was found to be highly produced in a subset of adult mouse and human β-cells, with rare human cells expressing insulin, glucagon and MSI (personal communication, J. D. Johnson). In other developmental systems, MSI2 represses the translation of NUMB (75), a protein which activates the Notch signaling pathway and thus prevents the expression of Ngn3 (79). Because Ngn3 is required for β-cell maturation (12), it is possible that MSI2 could be involved in maintaining a pool of immature ‘progenitor-like’ β-cells by preventing Ngn3 expression. Elucidating these signaling pathways and mechanisms involved in modulating adult β-cell plasticity and maturation will be interesting topics for future study. In this study, it was verified by FACS that 10-35% of adult β-cells from humans, mice and MIN6 cells have an immature phenotype, as shown previously (1). The continuous, slow maturation of some immature human β-cells was also observed, as was previously seen in primary mouse islets and MIN6 cells (1). Maintaining a continuously maturing subpopulation of immature β-cells in adult islets and MIN6 β-cells would require a balance between maturation, proliferation and apoptosis. The increased expression of a few genes involved in proliferation in human immature β-cells is consistent with the increased proliferation rates observed in immature MIN6 cells (1). However, whether primary human and mouse immature β-cells also have increased proliferation rates in vitro requires further investigation. A number of genes involved in apoptosis were also enriched in immature β-cells, including CARD11, DAP, DFFA, Ddit3, Ddit4, Anxa2 and Bbc3. Anxa2 appears to be involved in proliferation and apoptosis via a p53- mediated mechanism (80). It will be interesting to quantify the maturation, proliferation and apoptosis rates in the immature and mature β-cell subpopulations to understand the intricate balance of maintaining homeostasis between the two phenotypes (81). A similar balance between proliferation, maturation and apoptosis occurs during islet remodeling and β-cell maturation in neonatal development (82). Perturbing this balance should shed light on the mechanism behind adult β-cell plasticity (2). One of the most interesting genes identified in immature human β-cells is a member of the superfamily of tetraspan membrane proteins, TM4SF4. This glycoprotein is highly expressed in regenerating liver, a subpopulation of hepatocyte stem cells and intenstinal epithelial cells (83, 84), where it regulates proliferation and progenitor cell fate. Recently, Tm4sf4 was identified via  103 microarray analysis to be highly upregulated in the developing pancreata of Nkx2.2-null mice (85). Its increased expression was localized to the embryonic ductal and endocrine compartment and partially co-localized with ghrelin-positive cells (85). Additionally, Tm4sf4 was also enriched in Ngn3-expressing endocrine progenitors (85) and in exocrine cells that were reprogrammed in vivo into the endocrine lineage (86). The upregulation of TM4SF4 in human immature β-cells is consistent with these studies supporting the role of TM4SF4 in regulating islet cell differentiation and suggests that it could also play a role in adult β-cell plasticity. Transmembrane and extracellular matrix proteins play critical roles in mediating the interaction between extracellular and intracellular environments making them attractive drug targets. Microarray analysis uncovered several adhesion and extracellular matrix genes such as CD36, MUC13, LAMB1, Lamb3*, FAP and DPP4 that were enriched in immature β-cells. The dipeptidylpeptidase protein FAP has been implicated in remodeling of the extracelluar matrix in epithelial tumors (87). It shares high sequence identity with the catalytic domains of CD36 and DPP4, both of which are associated with the pathology of type 2 diabetes and are important drug targets (88, 89). FAP is not normally expressed at high levels in adult human tissues, but it had a six-fold greater expression in immature human β-cells, confirmed by qRT-PCR. These results suggest that FAP may have functional significance in adult β-cell maturation. Identifying unique cell surface markers on immature adult β-cells would be useful for their purification without genetic manipulation and for ‘staging’ the maturation states of β-cells. Cell surface markers have been very useful for such purposes in the hematopoietic field (90). The microarray analysis also identified factors that modulate Akt signalling, such as Trib3* (91). Elevated Trib3 expression is associated with insulin resistance and Trib3 polymorphisms are associated with early-onset type 2 diabetes with islets showing impaired glucose-stimulated insulin secretion (92). Other differentially expressed genes implicated in the pathology of diabetes include SORBS1 (93), leptin receptor LEPR (94) and members of the sirtuin family SIRT1 and SIRT5 (51, 95). SIRT5 is a new member of the sirtuin family of proteins (95).  Sirtuins are important regulators of metabolism and have become novel drug targets for the treatment of type 2 diabetes (51), but SIRT5 has not yet been linked to a diabetes phenotype. However, the extent to which these genes are involved in β-cell maturation requires further investigation. An intriguing result from the microarray analysis was the identification of different components of common signaling pathways in both immature and mature β-cells. Members and  104 modulators of the TGFβ pathway play a critical role during pancreatic morphogenesis and endocrine development, including follistatin, BMPs and activins (16, 17, 20). FSTL5 and BAMBI were increased in immature β-cells, whereas BMP5, TGFBR3 and GREM1 were enriched in mature β-cells. The expression of GREM1, an inhibitor of TGFβ signaling, in mature β-cells is consistent with our previous study showing that suppression of endogenous activin A by follistatin improves β-cell function and maturity (2). Several genes of the TGFβ pathway were also changed during the initial culture, expansion and differentiation of islet-depleted ductal tissue (96). Components of the MAPK pathway were also differentially expressed. MAPK1 was enriched in mature β-cells, whereas MAPK4 was increased in immature β-cells. While MAPK1/ERK1 is crucial in mediating the effects of insulin and other growth factors on the β- cell (97), much less is known about the role of MAPK4 (98). Different expression levels of these genes at different β-cell maturation states could regulate adult β-cell fate and maturity. This notion is consistent with reported dynamic changes in the levels of TGFβ, activin, BMPs and their receptors during different stages of pancreatic development (19). These results demonstrate the complexity of spatial, temporal and cell-specific regulation of these pathways in β-cell maturation. The convergence of many different signaling pathways determines the ultimate phenotypic outcome. The genetic signature of purified mature β-cells identified in this study is consistent with their insulin secreting function. Besides the most common maturity related β-cell genes (insulin, Pdx1, Mafa, Glut2) enriched in mature β-cells were others including IAPP, G6PC2, Slc39a8* and Slc39a9, all confirmed by qRT-PCR. Genes related to β-cell function including glucose/zinc transporters were all increased in mature β-cells. These genes were downregulated in expanded islets (65), consistent with the loss of function observed in proliferating β-cells (99). The islet- specific G6PC2 is part of the glucose-6-phosphatase catalytic subunit family but appears to lack enzyme activity (100). It has been identified as a strong auto-antigen in type 1 diabetes and thus implicated in β-cell destruction (101). The downregulated expression of this gene in immature β- cells may allow these cells to escape immune destruction, as there is evidence that some β-cells remain in the pancreas of patients with type 1 diabetes but are thoroughly dedifferentiated, with few insulin granules (28). There have been numerous reports of multihormonal cells in the embryonic and fetal pancreas (22-24), however co-expression of islet hormones in adult islets remains controversial. From our microarray analysis, Gcg, PPY, SST and GHRL were among the most upregulated  105 genes in immature β-cells of humans and mice (the first three confirmed by qRT-PCR). Insulin also remained detected in immature β-cells, albeit at lower levels compared to mature β-cells (Figure 4.5). There is accumulating recent evidence for the expression of multiple hormones in single adult islet cells at the transcript (26, 27) and protein levels (26). Both studies detected multiple combinations of hormones expressed in single cells and many of these also expressed Pyy (26). Surprisingly, almost half of adult insulin-positive β-cells expressed at least one other hormone in addition to insulin (27). In the present study, purified mature β-cells from humans, mice and MIN6 cells also had detectable expression levels of all non-β-cell hormones except ghrelin (Table 4.2). The co-expression of insulin and other hormones was also detected at the protein level in cultured human β-cells that lose their insulin expression upon induced proliferation (99). Collectively, these studies and the results of this study provide strong evidence that multihormonal cells do exist in adult islets. Furthermore, these results are consistent with the notion that adult β-cells expressing multiple hormones have an immature, fetal-like phenotype, and may reflect their differentiation potential. Using the dual reporter lentivirus, it was possible to examine, for the first time, which adult “β-cells” (i.e. cells with low insulin) expressed the multiple hormones that have been reported by others. Very small sample sizes were obtained after FACS purification for primary cells, especially for mouse cells. Hence, cDNA amplification kits had to be used for purified human and mouse cells. Consequently, the list of significantly and differentially expressed genes likely resulted in under-representation of less abundant genes (102), especially evident in Table 4.4 for primary mouse genes. Small sample sizes may have partially contributed to the lack of correlation between the 3 microarray datasets. A stronger correlation across the 3 cell types (human, mouse, MIN6), was evident (in 55% of genes) with follow-up experiments using more sensitive qRT-PCR technology. However, some species differences should also be expected, as human and mouse islets and β-cells differ in many aspects such as islet architecture (103), proliferation (99, 104) and timing of β-cell differentiation (104-106). In addition, some differences can also be expected between primary cells and highly proliferative transformed MIN6 cells. Nevertheless, by performing three separate microarray experiments using samples from primary mouse and human β-cells as well as MIN6 cells improved the detection of less abundant genes in immature and mature β-cells that may have been missed by performing only a single microarray experiment. Collectively, by using three tissue types and confirmation of 77% of candidate genes by qRT-PCR provided more confidence in the results of this study.  106 In summary, our results demonstrate that heterogeneity in Pdx1 and insulin expression also occurs in vivo. A fraction of primary human immature β-cells undergo maturation in vitro marked by the increased activation of the insulin promoter. Gene expression profiling of different adult β-cell maturation states revealed that many genes and signaling pathways are differentially expressed. The gene expression pattern of immature adult β-cells shares some similarities with embryonic/fetal pancreatic progenitor cells. Further analysis of the gene expression profiles of adult β-cell maturity should uncover novel genes and pathways involved in the intricate processes of β-cell dedifferentiation and maturation, as well as in the maintenance of β-cell function. Defining a genetic signature of mature and immature β-cells should be useful in staging the maturity of cells during the differentiation process from stem/progenitor cells in vitro and during in vivo β-cell regeneration into functional insulin-producing cells. The identification of real-time maturation events and putative progenitor cell markers in human adult β-cells provides new evidence and tools for the study of β-cell plasticity, which could be exploited therapeutically.                    107 4.5 REFERENCES   1. Szabat M, Luciani DS, Piret JM, Johnson JD (2009) Maturation of adult beta-cells revealed using a Pdx1/insulin dual-reporter lentivirus. Endocrinology 150:1627-1635  2. 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Habener JF, Kemp DM, Thomas MK (2005) Minireview: transcriptional regulation in pancreatic development. Endocrinology 146:1025-1034    115 5 CONCLUSIONS AND FUTURE DIRECTIONS  5.1 CONCLUSIONS  Before islet transplantation can become more widespread for the treatment of type 1 diabetes, there would need to be alternative sources to overcome the shortage of donor islets. In vivo β-cell regeneration may provide a promising alternative approach for the treatment of both type 1 and type 2 diabetes, but it has been challenging to identify the appropriate cells that could be effectively targeted therapeutically. An improved understanding of normal β-cell biology and plasticity would contribute to developing strategies to overcoming these challenges. This thesis reports the existence of a significant immature β-cell population (10-35% of β-cells) in normal human and mouse adult islets as well as MIN6 cells. These purified cells were shown to have reduced insulin secreting function and a decreased expression of multiple mature β-cell genes. At least a fraction of the immature cells retained the ability to undergo maturation over time in culture by acquiring increased insulin promoter activity revealed by a novel dual reporter lentiviral vector using image-based lineage analysis (1). The application of statistical design of experiments to screen for factors that can modify the adult β-cell maturation state revealed novel activities of the local β-cell factors activin A and follistatin in modulating β-cell maturity (2). Finally, using a genomic approach, the gene expression profile of immature adult β-cells was found to be partially comparable to pancreatic/endocrine progenitors in development (3, 4). These immature β-cells had increased expression levels of multiple islet hormones and many genes with functions related to development and stem cell plasticity. The identification of putative progenitor cell markers and real-time maturation events in immature human adult β-cells provides novel tools and cell sources for the study of adult β-cell plasticity and these could be exploited therapeutically. Results presented in this thesis have significance for the study of β-cell progenitors. The terms precursor cell and progenitor cell are often used interchangeably and are frequently context-dependent. For example, some studies define a progenitor cell as a rapidly dividing cell type that gives rise to terminally differentiated, post-mitotic cells (5, 6). For other studies, part of the definition of a progenitor cell is that it does not proliferate rapidly (7). The term precursor was used in the context of a limited self-renewal capacity for cells that precede more differentiated cells (8). For the purposes of this Chapter, the term progenitor cell will be used for  116 both a precursor cell and progenitor cell to maintain consistent terminology; although, it is recognized that each term may suggest distinct cell properties. There are at least two non-exclusive possibilities that might explain the presence of the described immature β-cells in adult islets. First, at least part of the immature β-cell population could represent a slowly replicating pool of multihormonal endocrine/β-cell progenitors. This would imply that some of the immature cells could give rise to mature β-cells, which was in part shown by the maturation events documented in this thesis, and some could potentially also give rise to themselves and to other islet cell types based on their multihormonal facet (9). A second possibility could be that a fraction of adult β-cells are dedifferentiated into cells with a decreased level of insulin expression, which acquire progenitor-like properties. These could then restore their function by undergoing the maturation process. Such a concept is consistent with the results of Chapter 3, where it was shown that local islet factors such as activin A and follistatin can promote dedifferentiation and maturation, respectively. Both of these possibilities could be linked to the reported functional β-cell heterogeneity (10). Putative adult endocrine/β-cell progenitors may not need to retain substantial self-renewal capacity and could rather remain slow replicating (11) or encounter a “replication refractory period” (6). They could also still maintain some ‘primed’ or graded level of hormone production. A similar type of slow self-renewing adult progenitor cell pool was reported in the acinar cell population (12) and non-classical facultative Ngn3+ progenitors that became activated after extreme pancreatic injury also lacked extensive proliferative capacity (7). It is plausible that the putative adult endocrine progenitors could remain relatively quiescent under normal in vivo conditions, even lacking substantial maturation, and then exit this quiescent state when islet homeostasis is perturbed (e.g. injury (7)) or an increase in β-cell mass is stimulated (e.g. obesity or pregnancy (13)). After such stimuli in vivo, it could be reasoned that even one cell doubling of the 10-35% immature β-cells present in adult islets with subsequent maturation would result in a significant increase in β-cell mass. However, there may not even be a need for a cell doubling, just an increase in the maturation of the existing immature β-cells. Consequently, this type of slow replicating adult progenitor cell would not have been detected by lineage tracing methods searching for fast-dividing progenitors (5, 6). The lineage tracing study by Dor et al. (5) used the tamoxifen-inducible Cre/lox system in transgenic mice. In their system, the Ins1 promoter drives Cre recombinase expression in cells with presumably an active endogenous insulin promoter. After tamoxifen administration, the cytoplasmic Cre present in insulin-expressing cells is shuttled to the nucleus where it irreversibly  117 labels the cells and their progeny with the human placental alkaline phosphatase (HPAP) (‘pulse’). β-Cells were then examined for the HPAP label at different times after tamoxifen administration (‘chase’). The hypothesis of Dor et al. (5) was that if new β-cells were generated from a stem/progenitor cell source (i.e. cells not expressing insulin at the time of the ‘pulse’), the frequency of HPAP+/insulin+ β-cells would be gradually diluted over time. Conversely, if new β- cells were generated from existing insulin-expressing cells, the frequency of HPAP+/insulin+ β- cells should remain constant, as both labeled and unlabeled cells should divide at a similar rate with age or during regeneration. Their results showed the frequency of HPAP+/insulin+ cells remained the same after all ‘chase’ periods examined during normal growth or regeneration after 70% pancreatectomy. This study is consistent with the results of this thesis because a fraction of the Pdx1+/Inslow immature β-cells have low insulin promoter activity (since the Ins1 promoter activity was shown to be graded, not on/off) resulting in GFP protein levels below the level of detection. Consequently, low amounts of Cre protein in these cells could have resulted in Cre- mediated HPAP label production. With subsequent maturation (i.e. increase in detectable levels of insulin protein), these cells would have been identified as pre-existing, mature β-cells (5). Interestingly, a very recent study repeated the experiments of Dor et al. (5) but came to different conclusions (14). The study by Liu et al. (14) proposed a different hypothesis in which a HPAP+/insulin− progenitor cell that acquired insulin expression after a chase period would increase the number of HPAP+/insulin+ cells. Indeed, their results indicated that this was the case in normal postnatal growth and regeneration after toxic destruction of the β-cells. The origin and identity of the putative progenitor cells remains unclear. Interestingly, 50% of cells bearing HPAP (from previous insulin promoter activity) but not staining for insulin protein in normal uninjured animals had a molecular profile similar to the immature β-cells described in this thesis. Specifically, the HPAP+/insulin− cells had PDX1 and MAFB protein production, but lacked insulin and GLUT2 protein, reminiscent of a late stage endocrine progenitor in development (15). Again, low amounts of Cre protein in some of the immature β-cells could result in Cre- mediated HPAP label production, before acquiring robust insulin protein production. After β-cell injury, the abundance of HPAP+/PDX1+/MAFB+/insulin− cells increased to 80% suggesting an activation of the differentiation program in these cells. Single cell lineage tracing using time- lapse imaging along with immunohistochemical analysis of each maturation stage should provide more insight into the identity and fate of these putative endocrine or unipotent β-cell progenitors. The notion that some of the immature β-cells might be adult endocrine/β-cell progenitor cells can be described by a hierarchy model of adult endocrine cell homeostasis, similar to what  118 was described in a recent review (16), based on the well defined progenitor hierarchy in the hematopoetic system (17). In this model, rare but highly proliferative multipotent progenitors exist at the top of the hierarchy (Figure 5.1A). This type of multipotent progenitor has been isolated in vitro (18, 19), and could give rise to all pancreatic cell types including endocrine, acinar and ductal cells (the latter two cell types not shown in figure). A more abundant but less proliferative population of multihormonal endocrine progenitors exists lower in the hierarchy (7, 20). Next, lineage-specific unipotent progenitor cells would have even less proliferative and plasticity potential. Such unipotent Ngn3+ endocrine progenitors were described in development (8). The largest population at the bottom of the hierarchy comprise of mature islet cells. In such a model, replication of mature β-cells (5) and/or recruitment and differentiation of lineage-specific unipotent progenitors would be the main contributors to the maintenance and regeneration of β- cell mass in normal postnatal growth (5, 6, 21), milder injuries (i.e. >20% normal pancreas remaining) (5, 6, 22) and physiological stimuli such as obesity and pregnancy (6, 23). More severe pancreatic injury including duct ligation (7) or β-cell ablation (20) (i.e. <10% of normal pancreas or β-cells remaining) could activate higher level pancreatic/endocrine progenitors since most of the lower level mature cell types would be removed or destroyed. Based on this working model, the immature ‘β-cells’ described in this thesis could be categorized with the multihormonal endocrine progenitor cell level and/or the lineage-specific unipotent progenitor cell level (Figure 5.1A). This hierarchy hypothesis is based in part on the observed graded, continuous level of insulin promoter activity from negative to low to high across the β-cell population in dual labeled primary human and mouse islets and MIN6 cells described in Chapters 2 and 4 (Figure 5.1B). Hence, it is assumed that within each hierarchy level, individual cells could still exhibit heterogeneity in some genes, but overall as a population, each hierarchy level could be distinguished from another by a unique gene expression profile. In a hypothetical scenario of β-cell differentiation, the Pdx1+-only (i.e. RFP-positive only) multihormonal endocrine progenitor cells would gradually acquire insulin expression (i.e. GFP) differentiating into unipotent progenitors followed by robust insulin expression in mature β-cells, depicted by the continuous, graded level of insulin expression in Figure 5.1 (A,B). Collectively, it appears that the body of literature supporting the existence of adult pancreatic progenitors (24, 25) or the opposing concept that only β-cell replication contributes to postnatal β-cell mass (26) could be partially reconciled by the results of this thesis.    119                           Figure 5.1 A hierarchy model of adult pancreatic endocrine cell homeostasis. A) At the top of the hierarchy, rare multipotent pancreatic progenitor cells, that have been isolated in vitro (18, 19), would give rise to all pancreatic cells including endocrine cells, as well as acinar and ductal cells (not shown). A more abundant population of multihormonal endocrine progenitors could be activated with specific stimuli (20). A source of lineage-specific unipotent progenitors would be more numerous in number. The final largest population at the bottom of the hierarchy would consist of mature islet cells. In the case of mature β-cells, the dominant mechanism for normal adult β-cell growth could be replication of existing β-cells (5). Model modified from a review by Hsun Teresa Ku (16). B) Proposed mechanism for immature β-cell maturation without requiring division and a continuum of insulin expression levels between immature β-cells and mature β-cells.  A B  120 The hypothesis of a multihormonal endocrine progenitor is also supported by recent studies suggesting that adult glucagon-expressing cells retain the plasticity to generate insulin- positive β-cells in response to extreme β-cell destruction (20), genetic ablation of a plasticity gene in α-cells (27) and over-expression of PAX4 in α-cells (28). The opposite transdifferentiation from β-cells to α- and PP-cells was possible via ARX over-expression in adult β-cells (29). These studies report the appearance of at least some transient insulin/glucagon double-positive cells; however, the presence of other islet cell hormones in these studies was not investigated. Interestingly, an abundant subpopulation of adult β-cells was recently shown to be multihormonal (9). The early appearance of multihormonal and insulin/glucagon-positive cells during embryonic development previously suggested their role as endocrine progenitors (30). It was later shown that mature β-cells can be produced even after glucagon-expressing cells were mostly destroyed with diptheria toxin (with the opposite scenario also occurring), suggesting that these cell types can arise from distinct lineages during development and not only from the bihormonal insulin/glucagon-positive cells (31). It is possible however that these multihormonal cells are retained in adult islets and contribute to normal adult islet cell homeostasis and/or become stimulated to mature under physiological or pathophysiological conditions such as pregnancy and diabetes. In such a case, it is likely that the mechanisms of β-cell neogenesis in the adult do not directly recapitulate the early developmental pancreatic progenitor differentiation pathway (i.e. the fate of multihormonal cells appearing at the early developmental PDX1-positive progenitor cell stage). Instead, some transcriptional networks of later stage endocrine progenitors that are necessary to initiate differentiation into mature islet cells might be shared with such putative adult endocrine progenitors. This notion is consistent with the gene expression profile of immature β-cells described in Chapter 4, which has some similarities with endocrine cell development. Potential differences between adult and embryonic/fetal β-cell neogenesis could be attributed to differences in metabolic demand and different extracellular and intercellular stimuli, such as islet architecture and cellular location (32). Although the ability of the immature β-cells described in this thesis to generate other islet cell types has not been examined, this possibility cannot be ruled out. Such experiments would be necessary to provide more evidence for this working hypothesis. The second concept of dedifferentiated, immature β-cells residing in adult islets is consistent with studies of β-cell heterogeneity (10, 33-36). It is also consistent with studies describing dedifferentiated β-cells present in islets of type 2 diabetes patients (37). Insulin resistant and hyperglycemic obese mice also have β-cells with a loss of maturity (37). In mouse  121 models of type 1 diabetes, some β-cells remain in the pancreas but are also highly dedifferentiated (38). These cells of diabetic animals and patients have similar phenotypic profiles as the immature β-cells described in this thesis. Interestingly, patients with type 1 diabetes show an ongoing destruction and apparent regeneration of β-cells (39), which supports a possibility that dedifferentiated, immature β-cells or endocrine/β-cell progenitors could be actively maturing/differentiating into mature β-cells with the stimuli of diabetic conditions, which are then actively destroyed. It would be interesting to test if the β-cells of patients with diabetes have a larger number of immature Pdx1+/Inslow cells than in non-diabetic islets. Taken together, the work of this thesis complements studies of adult β-cell biology and regeneration. Indeed, the observed mix of immature and mature β-cell phenotypes is consistent with numerous reports on adult β-cell heterogeneity (10, 33-36). This work is also compatible with the concept that β-cell replication is the common physiological mechanism for the maintenance of adult β-cell mass (5, 6, 40), as well as the alternative notion that progenitor-cell- mediated mechanisms exist for adult β-cell neogenesis (7, 14, 20, 28, 41-44). It is conceivable that there is a balance between mature β-cell dedifferentiation, β-cell replication and progenitor cell differentiation to maintain β-cell homeostasis. However, to delineate the interplay between these mechanisms unequivocally requires further investigation. Collectively, the body of work reported in this thesis provides novel evidence for a potentially important source of β-cells that could be exploited for cell-based therapy to treat diabetes. This thesis also provides unique perspectives on the nature of β-cell progenitors. The notion that immature adult β-cells from humans, mice and MIN6 cells have properties of β-cell progenitors provides a novel pancreatic islet niche to be further explored in search of a cell population that could be targeted for β-cell regeneration in vivo. Alternatively, adult cells isolated from islets that have the potential for maturation in vitro and that can be modulated by exogenous factors could prove to be useful for expansion and maturation efforts to generate new β-cells. Defining a database with a network of genes differentially expression between the two β- cell maturation states provides a framework of candidate genes for investigation in the diabetes research field, and some of these could provide targets for manipulations to improve the proliferation and maturation of the immature β-cells. Finally, the detailed characterization of adult β-cell maturity contributes to the improved understanding of β-cell physiology in general.     122 5.2 FUTURE DIRECTIONS  An immature phenotype within the adult β-cell population was uncovered and characterized, however many questions remain pertaining to their putative function or reason for this observed heterogeneity. One possibility is that these cells provide a means for adaptation to environmental changes producing a mild stimulus, such as a high fat diet. It would be interesting to test if an increase in the number of immature β-cells and their subsequent maturation frequency could be correlated with the level of obesity in mice. As already proposed above, an increased doubling and/or frequency of maturation of the 10-35% of immature β-cells present in the normal pancreas into functional β-cells would result in a significant increase in β-cell mass that normally occurs with obesity (13). This hypothesis would be compatible with studies showing slowly replicating cells with insulin promoter activity (presumed to be β-cells) contributing to maintenance of β-cell mass (5, 6, 11, 40). In this case, primary immature β-cells may not have a detectable increase in proliferative capacity compared to mature β-cells, as was shown for MIN6 cells (1), and this aspect is also of interest for future studies. Another interesting extension of this work would be to quantify the relative numbers of immature and mature β-cells in mouse models of diabetes. Residual β-cells in type 1 diabetes mouse models are dedifferentiated (38), as are the β-cells in obese mice that become insulin resistant and hyperglycemic (37). These cells share similar phenotypic features with the immature β-cells described in this thesis. Using the NOD mouse model of spontaneous type 1 diabetes, it would be interesting to determine if the progression towards overt diabetes is correlated with increasing numbers of immature Pdx1+/Inslow cells. Similar experiments could be performed using human type 2 diabetes islet samples comparing the numbers of immature β-cells with non-diabetic human islets. Preliminary qRT-PCR results do suggest that purified Pdx1+/Inslow cells of type 2 diabetes patients have a lower expression of mature β-cell genes including insulin, PDX1, MAFA, NEUROD1, GLUT1 and NKX6.1 compared to immature β-cells from normal islets (data not shown). It is still unclear if there is a larger relative abundance of immature β-cells in the type 2 diabetic islets and if the immature β-cells from type 2 diabetic islets also have the ability to undergo maturation in culture. If indeed there is an increase in immature β-cell numbers with progression to diabetes, this would provide a target for using exogenous factors to stimulate maturation and for β-cell regeneration in vivo. Based on the results reported in Chapter 3, it may be feasible to generate new mature β- cells in vitro because β-cell plasticity can be modulated by exogenous factors (2). It is clear that  123 mature β-cells lose expression of insulin during in vitro expansion (45). Activin A stimulation appears to also dedifferentiate mature β-cells or specifically target the proliferation of immature β-cells. The increased plasticity potential of immature β-cells could be exploited by targeting a high-throughput screening of factors or small molecules (46) that would increase the immature Pdx1+/Inslow β-cell population. Using the expanded immature cells, a similar targeted screening approach could be used to increase the number of mature Pdx1+/Ins+ β-cells in a maturation step. A smaller scale version of such a screening approach was described in Chapter 3. As a collaborative side project of this thesis, with the objective to generate more β-cells in culture, the dual reporter lentivirus was used to label human islets and MIN6 cells which were then used in a high-content, high-throughput screen of a library of natural compounds from invertebrates (47). The gene expression results from Chapter 4 provide a significant database of genes to be explored. These may have potentially novel roles in β-cell maturation and could be candidate progenitor cell markers. Although the microarray analysis described in Chapter 4 provided some insight into the unique gene expression profiles of β-cell maturation states, a more detailed bioinformatic analysis of the entire microarray data set from all 3 microarrays is warranted. In addition, it will be important to confirm many more differentially expressed genes from the selected subset of genes in Chapter 4 by qRT-PCR and immunocytochemical staining. Following the initial confirmatory studies, knock-down and over-expression studies for a selected number of genes should provide insight into mechanisms involved in the enigmatic maturation process. This could be done using lentiviral-mediated delivery of RNAi (48) and candidate genes into dual labeled primary cells. A large number of cells would then be imaged using automated microscopy and quantified with phenotypic profiling software (49) to simultaneously assess changes to the rate of maturation and maturity state of the cells. One candidate transcription factor, RFX2, that was enriched in human immature β-cells, is of particular interest for future studies because it is negatively regulated by Notch signaling (50). Two other genes in the same transcription factor family, Rfx3 (51) and Rfx6 (52) appear to have a pro-endocrine function in development, acting downstream of Ngn3. Because RFX2 interacts with RFX6 and RFX3 (53) and the Notch/NGN3 pathway is active in adult islets (54, 55) suggests that RFX2 may also have an important role in β-cell maturation and plasticity. Future work would involve confirming the levels of Rfx2 expression in immature and mature β- cells from humans and mice. Electromobility shift assays (EMSA) could be performed to determine if RFX2 and RFX6 cooperatively bind their target DNA sites as was found for RFX3 and RFX6 (52). The extent to which these two transcription factors can activate a promoter  124 containing active binding sites could also be investigated. The Notch pathway could be manipulated by an inhibitor such as DAPT (54) and then the levels of RFX2 examined by western blot to confirm if it is a direct target of Notch signaling (50) in adult islets and β-cells. Overexpression and loss-of-function studies of Rfx2 in dual labeled β-cells could elucidate its role in modulating adult β-cell maturation and plasticity. To define the functional hierarchy of Rfx2 in the Notch signaling pathway, other components of the pathway could be examined such as Delta, Notch and Hes genes (56). Other genes reported to regulate Notch signaling in other systems such as Numb (57, 58), Musashi (58) and Ikaros (59, 60) could be explored with respect to Rfx2 and their roles in β-cell differentiation/maturation. Additionally, Ngn3 expression in hormone-positive embryonic cells or adult islets appears to be heterogeneous (3, 61). With its newly discovered roles in adult β-cells (54, 55), it will be interesting to uncover if Ngn3- expressing adult islet cells have greater plasticity than non-expressing/low-expressing cells and if the Ngn3-positive cells correlate with the abundance and phenotype of the immature β-cells described in this thesis. Collectively, this future work could provide a model mechanism for the regulation of adult β-cell maturity and the maintenance of putative β-cell progenitors, especially with respect to the role of the Notch signaling pathway. The results in Chapter 4 identified candidate cell surface markers of immature β-cells to enable live cell purification without genetic labeling. It would be interesting to compare live cell- surface stained and sorted GLUT2low, FAPhigh, MUC13high, CD36high cells to immature Pdx1+/Inslow cells labeled by the dual reporter lentivirus. As a secondary model for comparison, mouse Ins1 promoter (MIP)-GFP mouse islets (62) could be used to purify low insulin expressing cells (with low/undetectable GFP levels) and compare the expression levels of these surface markers in relation to purified MIP-GFP β-cells with high GFP expression levels. Human islet cells could then be labeled with these surface markers and purified to compare their phenotypic profiles to GFP-labeled and surface labeled mouse cells. This could potentially provide a genetically unmodified, purified human source of cells to study these putative β-cell progenitors in the context of expansion and subsequent maturation in vitro or as targets for in vivo regeneration. Finally, preliminary lineage tracing of β-cell maturation was reported in Chapters 2 and 4. However, it will be important to quantify and characterize the maturation events of many more individual human and mouse β-cells. Recently developed fluorescent proteins in the blue (63) and far-red spectrum (64, 65) now allow for 3- or 4-colour fluorescent protein labeling of primary islet cells. The Pdx1mRFP-Ins1eGFP dual reporter lentivirus can also be modified to  125 include the new fluorescent proteins and other promoters of candidate genes identified from the gene expression profiling studies in Chapter 4, such as Pyy to label immature β-cells. A FRET- based apoptosis sensor can be used as a reporter for apoptotic cells (66). Two dual reporter lentiviral vectors with different arrangements of promoter-reporter transgenes could be used to label cells with 4 colours. This would allow for real-time imaging of the kinetics of these promoters by lineage tracing large numbers of single cells over time using high-throughput, high-content screening platforms under a variety of culture conditions such as high/low glucose and activin A/follistatin to modulate the maturation rates. 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All transfer vectors were constructed using the modified pTiger backbone (pTigerMCS) (Fig. 1A). In addition to the dual reporter vector, single reporter vectors were created as controls. To create the pTigerIns1EGFP vector, the entire Ins1EGFP cassette containing the -410 bp rat Insulin I promoter and destabilized enhanced green fluorescent protein (pd2EGFP) in pGL3 basic vector (gift from Dr. Timothy Kieffer, University of British Columbia, Vancouver) was excised using MluI/XbaI and ligated into AscI/XbaI linearized pTigerMCS. PCR was used to extract monomeric red fluorescent protein (mRFP) from the pRSETB-mRFP1 vector (23) (gift from Dr. Roger Tsien, University of California, San Diego) to aid construction of pTigerPdx1mRFP. The PCR product was subcloned into the pDrive cloning vector (Qiagen, Mississauga, Ontario), then excised using SnaBI/NheI and ligated into HpaI/NheI digested pTigerMCS. The -4530 bp mouse Pdx1 promoter was excised from the pGL3 basic vector (generous gift from Dr. Jochen Seufert, Hospital of the Bavarian Julius- Maximilians University, Wurzburg, Germany) with XmaI/BsaWI and inserted into the XmaI linearized pTigerMCS-mRFP vector. The control pTigerCMVEGFP vector was constructed by ligating a blunted DraI/AseI CMVGFP fragment from the pGFP-C1 vector (Clontech) into the NruI linearized pTigerMCS vector. Finally, the dual reporter gene vector (Fig. 1A) was created by using recombinant PCR to extract the Ins1GFP cassette from the pGL3-410Ins1d2EGFP vector (and to engineer new NheI and PmeI restriction endonuclease sites. The PCR product was inserted into the pDrive cloning vector, verified by DNA sequencing, digested using NheI/PmeI and ligated into the NheI/PmeI digested pTigerPdx1mRFP vector.  A1.2 LENTIVIRUS PRODUCTION AND INFECTION Transfections for lentivirus production were performed using FuGENE6 transfection reagent (Roche Diagnostics) using a lipid: DNA ratio of 2.7 μl FuGENE: 1 μg DNA. The day  132 before transfection, 12x106 293T cells were plated in DMEM supplemented with 10% FBS, but no antibiotics, per 15 cm plate to achieve approximately 50% confluence at time of transfection. Transfections were performed using 32 μg structural protein vector CPRΔEnv, 13 μg envelope vector CI-VSVG, and 19.4 μg transfer vector per 15 cm plate. Viral pellets were resuspended overnight at 4oC in tris-NaCl-EDTA (TNE) and stored at -70oC until needed. Concentrated virus was titered using MIN6 cell line by serial dilution in 6-well plates and functional reporter gene expression assayed by FACS. Viral titers were consistently 1-4x106 TU/ml. Primary cells and cell lines were infected in multi-well culture plates as required using concentrated virus at a 4- fold dilution with culture medium in the presence of 8 μg/ml protamine sulfate. Cells with virus were centrifuged at 2500 rpm, 30oC for 1.5 hrs and incubated at 32oC overnight before changing to fresh medium. Reporter gene expression was assayed after 72 hrs post-infection in cell lines and 5 d post-infection in primary cells.  A1.3 IMMUNOCYTOCHEMISTRY Primary human islets cells were cultured on coverslips prior to fixation with 4% paraformaldehyde for 10 min. Sorted MIN6 cells were seeded onto coverslips and allowed to attach for 4 hours prior to fixation. Cells were then washed 3 times with PBS, permeabilized with 0.2% Triton-X for 20 min, followed by washing 3 times with PBS. Cells were blocked in serum- free protein block (DAKO) for 30 min. and incubated with the following primary antibodies dilutated in antibody diluent (DAKO): rabbit anti-Pdx1 (1:1000) (Chris Wright), guinea pig anti- insulin (1:200) (DAKO). After overnight incubation at 4oC, cells were washed 3 times with PBS and incubated with the following secondary antibodies for 1 hour at room temperature: goat anti- rabbit AlexaFluor 488, goat anti-rabbit AlexaFluor 594, goat anti-guinea pig AlexaFluor 488, all from Invitrogen and at 1:200 dilution in antibody diluent. Cells were then washed 3 times with PBS, counterstained and mounted on slides with Vectashield mounting medium with DAPI (Vector Laboratories).            133 SUPPLEMENTAL TABLES  Table A1 Pancreatic tissue donor information.  DONOR ID Cold Preservation (min) Culture Time (h) Age BWt. (kg) Islet Purity % BC59 677 36 69 64 90 BC61 510 36 41 70 60 BC62 180 24 29 85 80 BC68 630 36 61 109 80 BC69 120 48 67 80 90 BC70 200 48 61 90 70 BC71 390 20 50 60 90 BC79 257 36 42 70 70 BC84 337 48 24 135 85 BC89 149 36 56 70 80 BC109 185 36 18 70 70 * cold preservation time is the time from when cross clamping of aorta at organ retrieval to time of start of islet isolation; culture time is the time the isolated islets were cultured in suspension prior to receiving samples; islet purity was assessed by dithizone staining by islet transplant lab  Table A2 Primers used in this study.         Primer name Forward sequence (5’ to 3’) Reverse sequence (5’ to 3’) Amplicon size (bp) Ins1 TCAGAGACCATCAGCAAGCA GGGACCACAAAGATGCTGTT 134 Isl1 GGATTTGGAGTGGCATGCAG CACGCATCACGAAGTCGTTC 182 Neurod1 CGAGGCTCCAGGGTTATGAG CATGGCTTCAAGCTCGTCCT 200 Nkx2-2 CTTTCTACGACAGCAGCGACA TCCTTGTCATTGTCCGGTGA 160 Nkx6-1 ATCTTCTGGCCCGGAGTG TCTCTCTGGTCCTGCCAAG 192 Pax6 GGAGTGCCCTTCCATCTTTG AGCCAGGTTGCGAAGAACT 118 Glut2 CTGTGTCCAGCTTTGCAGTG CCATCAAGAGGGCTCCAGTC 129 Hnf3β/Foxa2 GTGAAGATGGAAGGGCACGA GCGGACATGCTCATGTATGTGT 131 Pdx1 GACCTTTCCCGAATGGAACC GTTCCGCTGTGTAAGCACC 135 Gapdh TGATGGGTGTGAACCACGAG GGCCATCCACAGTCTTCTGG 177 MafA TCACTCTGCCCACCATCAC TGACCTCCTCCTTGCTGAAG 198 Ngn3 TGCAGCCACATCAAACTCTC GGTCACCCTGGAAAAAGTGA 139 MafB GGTATAAACGCGTCCAGCAG CGAGTTTCTCGCACTTGACC 138 Hnf1a GCACACCCATGAAGACACAG CCTGTGGGCTCTTCAATCAG 121 Pax4 TCATCCCAGGCCTATCTCCA GGCCTCCAATCAGATGATGC 127 Hnf1b CTCCTCTCCACCCAACAAGA GCTGGGGAGACTTGCTGTA 141 Kir6.2 CCACGTCATCGACTCCAACA TGATGCCCGTGGTTTCTACC 116 Sur1 GCTGCTGGTGGAGATCAATG AGGTCCCCTTTGACAGCA 143 Gck GTTTTGTGTCGCAGGTGGAG GTGGACACGCTTTCACAGG 131 CaV1.2 GGAGACCATCCTGGTGGAG GCGCACTGAGTTCAGCAAG 146 eGFP AGAACGGCATCAAGGTGAAC TGCTCAGGTAGTGGTTGTCG 134 mRFP CCCCGTAATGCAGAAGAAGA CTTGGCCATGTAGGTGGTCT 153  134 Human or mouse islets (dispersed or whole) or cell lines (i.e. MIN6) Cells seeded onto tissue culture treated plates, allowed to attach overnight Cells infected with dual reporter lentivirus Infected cells used in various experiments • microscope imaging of live infected cells (fig.1) • FACS analysis and sorting (fig.3):   • BrdU staining (fig.3) • Immunocytochemistry (suppl. fig.2) • RT-PCR analysis (fig.3 & 5) • fate tracking of live cells (fig.3) • long-term culture (fig.4) • Ca2+ signaling (fig.6A,B,C,D) • Static insulin secretion assay (fig.6E&F) Human islets MIN6 cells Mouse islets • microscope imaging of live infected cells (fig.1) • fate tracking of live cells (fig.2) • Immunocytochemistry (data not shown) • microscope imaging of live infected cells (fig.1) • Immunocytochemistry (suppl. fig.3) FIV SUPPLEMENTAL FIGURES    Figure A1 Schematic flow diagram of experimental methods.                Figure A2 Immunocytochemical staining of sorted MIN6 cells. Stably infected MIN6 cells were sorted for RFP+-only (A,B) and double positive RFP/GFP (C,D) expression and stained for Pdx1 (A,C) and insulin (B,D).  RFP+-only cells stained positive for Pdx1 (A) but not insulin (B), whereas RPF/GFP double positive cells stained positive for both Pdx1 (C) and insulin (D) 200x magnification. Pdx1 DAPI Pdx1 DAPI Insulin DAPI A B C D Insulin DAPI  135                          Figure A3 Heterogeneous immunocytochemical staining of insulin and PDX1 in human and mouse islets. Cultured human islet cells were stained with insulin or PDX1 (or both) and cells with various insulin intensity levels could be found (A); a cell with strong insulin staining (arrowhead) and very low insulin staining are shown (arrow). A similar pattern of PDX1 staining showed cells with strong staining intensity (arrowhead) and weak staining intensity (arrow) (B). 200X magnification. Mouse islet sections were stained with insulin (C) and PDX1 (D). Notice heterogeneous levels of both proteins between individual cells.                 PDX1 Insulin DAPIInsulin DAPI A B C D  136               Figure A4  Calculation of δ-cell contribution to Pdx1+/Inslow cell population. Based on an average 20% infection rate of primary cells based on the CMV control vectors and average islet purity of 78.6% (Supplementary Table A1), the calculated number of infected and labeled (reporter expressing) δ-cells would be 0.61% of total infected cells (0.039x0.2x0.786). Assuming an average of 53.5% β-cells in human islets (Cabrera et al. (2006) PNAS 103: 2334), the calculated number of infected β-cells would be 8.41% (0.535x0.2x0.786), with a total of 9.02% (0.61%+8.41%) of infected cells which have the potential of expressing the reporters. Assuming up to 20% of labeled cells are Pdx1+/Inslow, 1.8% of total infected cells are immature (0.2x0.0902). With 0.61% of labeled cells being δ-cells and 1.8% of total cells being Pdx1+/Inslow, 33.8% of δ-cells could contribute to the Pdx1+/Inslow population (0.61%/1.8%), however only about 10-20% of δ-cells express Pdx1 (Oster et al. (1998) J Histochem Cytochem 46:707). Therefore, we can assume that approximately 3.38-6.78% of the Pdx1+/Inslow cells would be expected to be δ-cells.                 Figure A5 Phenotypic fate tracking of sorted INS-1 cells at whole population level. Stably infected INS-1 cells were analyzed and sorted by FACS. A: Most of the infected cells expressed both reporters at 87.2% and cells expressing only Pdx1 were at a 11.6% frequency. B: Sorted and cultured double positive cells maintained their Pdx1+/Ins+ phenotype at 98.1%; C: whereas sorted Pdx1+-only cells converted into double positive cells (28.6%) and also maintained a significant Pdx1+ population (70.8%), after 1 month in culture (~5 passages). 9.2% Pdx1+ 0.9% Ins+ 21.0 % (-) 69.0% Pdx1+/Ins+ A 1.7% Pdx1+ 0.2% Ins+ 1.9% (-) 96.2% Pdx1+/Ins+ B 24.3% Pdx1+ 0.5% Ins+ 15.1 % (-) 60.2% Pdx1+/Ins+ C DAPI Somatostatin Merge  137                     Figure A6 Maturation of sorted INS-1 cells. Stably infected INS-1 cells were sorted for Pdx1+/Ins- expression and cultured. Immediately after sorting, Pdx1+-only cells were >98% pure.  After 66 hours, many cells expressed insulin. 200x magnification.                   Figure A7 Working model of adult β-cell maturation states. A large number of adult β-cells exist in the immature state defined by expression of Pdx1 but little or no insulin. A major fraction of the immature cells transition to express insulin at a high level and other mature β-cell genes. The immature population also contains subpopulations of cells. The dynamic steady-state between the β-cell subpopulations is controlled by replication, death and maturation. Bright RFP GFP  μM μR1  Pdx1+/Ins+ μM = maturation μR = replication μD = death Pdx1+ /Inslow μR2 μD1 μD2 Immature β-cell State Mature β-cell State  138 APPENDIX B  SUPPLEMENTAL FIGURES                                       Figure B1 Activin A dose–response. No differences were observed between the range of doses examined in the effects of activin A on % Pdx1+/Inslow and Pdx1+/Ins+ cells. A) Dose–response experiment 1. B) Dose–response experiment 2.    139                                 Figure B2 Sample FACS dot plot. Sample plot schematically showing how the sorting gates were set up and how quantification of immature Pdx1+/Inslow and mature Pdx1+/Ins+ cells was performed. Gates separating cells positive for GFP and RFP (black lines) in dual labelled MIN6 cells were set up using control unlabelled cells and single reporter labelled cells (i.e. Pdx1mRFP only and Ins1eGFP only). The green and red gates were used to quantify GFP and RFP intensities using geometric mean, respectively. The blue gates were used to sort immature Pdx1+/Inslow cells and mature Pdx1+/Ins+ cells. Neg., negative          Pdx1+/Inslow Pdx1+/Ins+ Neg. Pdx1-/Ins+  140                                           Figure B3 Effect of activin A on cells expressing control lentiviral vectors. A) CMVeGFP or (B) single Ins1eGFP control vector labelled MIN6 cells treated for 72 h with activin A (2 nM) or follistatin (100 nM) were analysed by FACS for GFP (insulin) intensity.     Non-treated Activin A Follistatin  141                        Figure B4. Gene expression of activin A-treated human islets. Human islets were cultured with 4 nM activin A for 72 h and RNA samples were analyzed by real-time RT-PCR (n=1).                     Figure B5. Activin A decreases insulin secretion from human islets. Human islets were cultured with 4 nM activin A for 72h and media samples were taken for analysis by insulin RIA (n=2).  0.0 0.2 0.4 0.6 0.8 1.0 1.2 In su lin  s ec re tio n re la tiv e to  c on tro l Non-treated ActA treated 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 Insulin Pdx1 MafA MafB Nkx6.1 Nkx2.2 Glut2 ActA ActARII R el at iv e ge ne  e xp re ss io n  142                       Figure B6. Expression of activin A and its receptors in human islets. RNA from human islets was isolated and analyzed by real-time RT-PCR (n=2).                      Figure B7. Rate of activin A secretion from human islets quantified by activin ELISA (n=2). Note: the large difference in the amount of activin A secretion from islets of both donors reflects the purity of islets in the pancreatic tissue. 0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 actA alk2 alk4 actRII actRIIB G en e ex pr es si on  re la tiv e to  g ap dh 0 2000 4000 6000 8000 10000 12000 Human Islets A ct iv in  A  o ve r 7 2h  (p g/ m L) Donor 1 Donor 2  143 Table B1 Growth and differentiation factors used in factorial experiments Factor Known/potential effects Concentration References Source IGF-1 Promotes survival; mitogenic to pancreatic cells 6.7 nmol/l Huotari et al. 1998 R&D Systems Betacellulin Mitogenic to pancreatic fetal cells/cell lines, used with activin A 4 nmol/l Huotari et al. 1998; Demeterco et al. 2000 R&D Systems Insulin  Promotes glucose/AA uptake, mitogenic, promotes survival 0.2 nmol/l Beith et al. 2008 Sigma Exendin-4 GLP-1a analogue, induces differentiation of fetal/duct cells; improves beta cell function 9.5 nmol/l Zhou et al. 1999; Movassat et al. 2002; Ghofaili et al. 2007 Sigma Laminin1 Induces three-dimensional structures, promotes differentiation 11.8 nmol/l Jiang et al. 1999; Crisera et al. 2000 Invitrogen Retinoic acid  Promotes differentiation of PDX1+ endoderm 1 μmol/l Micallef et al. 2005 Calbiochem Activin A  Pancreatic differentiation factor  for many cell types (pancreatic fetal cells, ESb cells, liver cells) 4 nmol/l Demeterco et al. 2000 ; D’Amour et al. 2006; Zalzman et al. 2005 R&D Systems Gastrin-17  Increases PDX1/number of beta cells with EGF in duct cultures 1.4 μmol/l Suarez-Pinzon et al. 2005 Sigma EGF Increases PDX1/number of beta cells with Gastrin17 in duct cultures 10 nmol/l Suarez-Pinzon et al. 2005 Stem Cell Technologies  FBS Mitogen/survival supplement 10% cM. Szabat, preliminary experiment Invitrogen Glucose Promotes insulin expression/activation of Pdx1 10 mmol/l cM. Szabat, preliminary experiment; Rafiq et al. 2000 Sigma Nicotinamide Increases maturation of ESb/ duct/fetal cells into insulin+ cells 10 mmol/l Gao et al. 2003 ; Vaca et al. 2008; Otonkoski et al. 1993 Sigma Hepatocyte growth factor Mitogenic to pancreatic duct cells; induces differentiation of duct cells into insulin+ cells 0.25 nmol/l J. Piret, preliminary data; Zhan et al. 2009 Sigma aGLP-1, glucagon-like peptide 1; bES, embryonic stem cells; cPreliminary experiments were performed using 0.1%, 1% and 10% FBS, and 5 mmol/l, 10 mmol/l and 25 mmol/l glucose. 10% FBS had the strongest effect on total cell number. Glucose at 10 mmol/l and 25 mmol/l was at the saturating level for all cell effects, hence 10 mmol/l glucose was chosen   144 Table B2 Factorial design factor combinations (factorial 1).  Runa Patternb Blockc NIC EX4 INS IGF-1 BTC GLU FBS ACTA LAM1 EGF RA GAS17 1 000000000000 1 0 0 0 0 0 0 0 0 0 0 0 0 2 + − − ++++ −  − ++ −  1 1  −1  −1 1 1 1 1  −1  −1 1 1  −1 3 + −  − + − + − ++ −  − + 1 1  −1  −1 1  −1 1  −1 1 1  −1  −1 1 4 +++ − ++ −  −  −  − ++ 1 1 1 1  −1 1 1  −1  −1  −1  −1 1 1 5 ++ − ++ − ++ −  − ++ 1 1 1  −1 1 1  −1 1 1  −1  −1 1 1 6  − + − ++++ − + −  − + 1  −1 1  −1 1 1 1 1  −1 1  −1  −1 1 7 ++ − + −  −  −  − ++ −  −  1 1 1  −1 1  −1  −1  −1  −1 1 1  −1  −1 8  − + − + − + − + − ++ −  1  −1 1  −1 1  −1 1  −1 1  −1 1 1  −1 9  −  −  −  −  − + −  −  −  −  −  −  1  −1  −1  −1  −1  −1 1  −1  −1  −1  −1  −1  −1 10 + −  −  − + − + −  − + − + 1 1  −1  −1  −1 1  −1 1  −1  −1 1  −1 1 11 + − ++++ − + − + − + 1 1  −1 1 1 1 1  −1 1  −1 1  −1 1 12 + − + −  −  − + − + −  − + 1 1  −1 1  −1  −1  −1 1  −1 1  −1  −1 1 13 + − ++ − ++ − + − + −  1 1  −1 1 1  −1 1 1  −1 1  −1 1  −1 14  − + −  −  −  −  − + − + − + 1  −1 1  −1  −1  −1  −1  −1 1  −1 1  −1 1 15  −  −  − + −  −  −  −  −  − ++ 1  −1  −1  −1 1  −1  −1  −1  −1  −1  −1 1 1 16 + −  −  −  −  −  − ++ − + −  1 1  −1  −1  −1  −1  −1  −1 1 1  −1 1  −1 17 ++++ −  − ++++++ 1 1 1 1 1  −1  −1 1 1 1 1 1 1 18 000000000000 1 0 0 0 0 0 0 0 0 0 0 0 0 19  −  −  −  − ++++++++ 1  −1  −1  −1  −1 1 1 1 1 1 1 1 1 20  −  − +++ −  −  − ++++ 1  −1  −1 1 1 1  −1  −1  −1 1 1 1 1 21  − +++++ − ++ − + −  1  −1 1 1 1 1 1  −1 1 1  −1 1  −1 22  − + −  − + − + − + − + −  1  −1 1  −1  −1 1  −1 1  −1 1  −1 1  −1 23 ++ −  −  − + −  − ++++ 1 1 1  −1  −1  −1 1  −1  −1 1 1 1 1 24 + − + − + −  − + − ++ −  1 1  −1 1  −1 1  −1  −1 1  −1 1 1  −1 25 000000000000 1 0 0 0 0 0 0 0 0 0 0 0 0 26  − ++ − + −  − ++ −  − + 1  −1 1 1  −1 1  −1  −1 1 1  −1  −1 1 27  −  − ++ −  − ++ −  −  −  −  1  −1  −1 1 1  −1  −1 1 1  −1  −1  −1  −1 28 000000000000 1 0 0 0 0 0 0 0 0 0 0 0 0 29  −  − + − ++ −  − ++ −  −  1  −1  −1 1  −1 1 1  −1  −1 1 1  −1  −1 30  −  −  − ++ − ++++ −  −  1  −1  −1  −1 1 1  −1 1 1 1 1  −1  −1 31  −  − + −  − +++ −  − ++ 1  −1  −1 1  −1  −1 1 1 1  −1  −1 1 1 32 000000000000 1 0 0 0 0 0 0 0 0 0 0 0 0  145 Runa Patternb Blockc NIC EX4 INS IGF-1 BTC GLU FBS ACTA LAM1 EGF RA GAS17 33 ++ −  − ++++ −  −  −  −  1 1 1  −1  −1 1 1 1 1  −1  −1  −1  −1 34  − ++ −  −  − + −  − ++ −  1  −1 1 1  −1  −1  −1 1  −1  −1 1 1  −1 35  − +++ − ++ −  − + − + 1  −1 1 1 1  −1 1 1  −1  −1 1  −1 1 36 +++++ −  −  −  −  −  −  −  1 1 1 1 1 1  −1  −1  −1  −1  −1  −1  −1 37 +++ −  − +++++ −  −  1 1 1 1  −1  −1 1 1 1 1 1  −1  −1 38 000000000000 2 0 0 0 0 0 0 0 0 0 0 0 0 39  − + −  − ++ − + − + − + 2  −1 1  −1  −1 1 1  −1 1  −1 1  −1 1 40 ++ −  − + −  −  − ++++ 2 1 1  −1  −1 1  −1  −1  −1 1 1 1 1 41 +++ − + − ++++ −  −  2 1 1 1  −1 1  −1 1 1 1 1  −1  −1 42  − + − + −  − + − + −  − + 2 −1 1  −1 1  −1  −1 1  −1 1  −1  −1 1 43  −  − + − + − ++ −  − ++ 2  −1  −1 1  −1 1  −1 1 1  −1  −1 1 1 44  − + − ++ −  − + − ++ −  2  −1 1  −1 1 1  −1  −1 1  −1 1 1  −1 45 + −  − + −  − + −  − ++ −  2 1  −1  −1 1  −1  −1 1  −1  −1 1 1  −1 46 + −  −  − ++ − ++ − + −  2 1  −1  −1  −1 1 1  −1 1 1  −1 1  −1 47 + −  − ++ −  − ++ −  − + 2 1  −1  −1 1 1  −1  −1 1 1  −1  −1 1 48 + − + −  − + − + − ++ −  2 1  −1 1  −1  −1 1  −1 1  −1 1 1  −1 49 +++ −  −  −  −  −  −  − ++ 2 1 1 1  −1  −1  −1  −1  −1  −1  −1 1 1 50 ++ −  −  −  − ++ −  −  −  −  2 1 1  −1  −1  −1  −1 1 1  −1  −1  −1  −1 51  −  −  −  −  −  − ++++++ 2  −1  −1  −1  −1  −1  −1 1 1 1 1 1 1 52 ++++++++++++ 2 1 1 1 1 1 1 1 1 1 1 1 1 53 ++++ − + −  −  −  −  −  −  2 1 1 1 1  −1 1  −1  −1  −1  −1  −1  −1 54  −  −  − +++ −  −  −  − ++ 2  −1  −1  −1 1 1 1  −1  −1  −1  −1 1 1 55 000000000000 2 0 0 0 0 0 0 0 0 0 0 0 0 56 + − + − +++ − + −  − + 2 1  −1 1  −1 1 1 1  −1 1  −1  −1 1 57 + − ++ −  −  − + − + − + 2 1  −1 1 1  −1  −1  −1 1  −1 1  −1 1 58 ++ − +++ −  − ++ −  −  2 1 1  −1 1 1 1  −1  −1 1 1  −1  −1 59  − +++ −  −  − ++ − + −  2  −1 1 1 1  −1  −1  −1 1 1  −1 1  −1 60 000000000000 2 0 0 0 0 0 0 0 0 0 0 0 0 61  − ++ − +++ −  − ++ −  2  −1 1 1  −1 1 1 1  −1  −1 1 1  −1 62 + − +++ − + − + − + −  2 1  −1 1 1 1  −1 1  −1 1  −1 1  −1 63 ++ − + − +++ −  − ++ 2 1 1  −1 1  −1 1 1 1  −1  −1 1 1 64 000000000000 2 0 0 0 0 0 0 0 0 0 0 0 0 65  −  − ++ − + −  − ++++ 2  −1  −1 1 1  −1 1  −1  −1 1 1 1 1 66 000000000000 2 0 0 0 0 0 0 0 0 0 0 0 0  146 Runa Patternb Blockc NIC EX4 INS IGF-1 BTC GLU FBS ACTA LAM1 EGF RA GAS17 67  −  −  − + − +++++ −  −  2  −1  −1  −1 1  −1 1 1 1 1 1  −1  −1 68  − ++++ − + −  − + − + 2  −1 1 1 1 1  −1 1  −1  −1 1  −1 1 69  −  − ++++++ −  −  −  −  2  −1  −1 1 1 1 1 1 1  −1  −1  −1  −1 70  −  − + −  −  −  −  − ++ −  −  2  −1  −1 1  −1  −1  −1  −1  −1 1 1  −1  −1 71  −  −  −  − + −  −  −  −  −  −  −  2  −1  −1  −1  −1 1  −1  −1  −1  −1  −1  −1  −1 72  − + −  −  − ++ − + − + −  2  −1 1  −1  −1  −1 1 1  −1 1  −1 1  −1 73 + −  −  −  − ++ −  − + − + 2 1  −1  −1  −1  −1 1 1  −1  −1 1  −1 1 74  − ++ −  − + − ++ −  − + 2  −1 1 1  −1  −1 1  −1 1 1  −1  −1 1 ‘1 or +’ = factor added to well at the concentration specified in ESM Table1 ‘−1 or −’ = factor not added to this well (zero dose) ‘0’ = factor added to well at the mid-point or average concentration between −1 and 1 aRun—individual well of a 96-well plate bPattern—summary of the combinations of factors added to an individual well cBlock—individual runs were separated into two plates (blocks) to use only the inner 60 wells of 96-well plates, thus minimising error from evaporation in external wells Factor abbreviations: NIC, nicotinamide; EX4, exendin 4; INS, insulin; IGF-1, insulin-like growth factor -1; BTC, betacellulin; GLU, glucose; FBS, fetal bovine serum; ACTA, activin A; LAM1, laminin 1; EGF, epidermal growth factor; RA, retinoic acid; GAS17, gastrin-17.                147 Table B3 Factorial design factor combinations (factorial 2).  Runa Patternb Blockc IGF-1 BTC INS EX4 ACTA GLU NIC HGF 1 + − + − +++ −  1 1 −1 1   −1 1 1 1   −1 2 +++++ −  −  −  1 1 1 1 1 1   −1  −1  −1 3 + −  −  −  − +++ 1 1 −1  −1  −1  −1 1 1 1 4 ++ − + −  −  − + 1 1 1   −1 1  −1  −1  −1 1 5 + −  − + − + −  −  1 1  −1  −1 1  −1 1  −1  −1 6 ++ − +++ − + 1 1 1  −1 1 1 1  −1 1 7  − + −  − + −  −  −  1  −1 1  −1  −1 1  −1  −1  −1 8 00000000 1 0 0 0 0 0 0 0 0 9  − + −  −  − + −  −  1  −1 1  −1  −1  −1 1  −1  −1 10 + −  −  − + − ++ 1 1  −1  −1  −1 1  −1 1 1 11 ++++ − + −  −  1 1 1 1 1  −1 1  −1   −1 12  −  −  − + −  − + −  1  −1  −1  −1 1  −1  −1 1  −1 13  − ++ − ++ − + 1  −1 1 1  −1 1 1  −1 1 14 +++ − + − ++ 1 1 1 1  −1 1  −1 1 1 15 00000000 1 0 0 0 0 0 0 0 0 16  − ++ −  −  −  − + 1  −1 1 1  −1  −1  −1  −1 1 17  −  −  −  − ++ − + 1   −1  −1  −1  −1 1 1  −1 1 18 + − ++ −  −  − + 1 1  −1 1 1  −1  −1  −1 1 19 +++ −  − +++ 1 1 1 1  −1  −1 1 1 1 20 + − ++++ − + 1 1  −1 1 1 1 1  −1 1 21  − + − + − +++ 1  −1 1  −1 1  −1 1 1 1 22  −  − + −  − + −  −  1  −1  −1 1  −1  −1 1  −1  −1 23  −  −  − ++++ −  1  −1  −1  −1 1 1 1 1  −1 24  − + − ++ − ++ 1 −1 1  −1 1 1  −1 1 1 25  −  −  −  −  −  −  − + 1  −1  −1  −1  −1  −1  −1  −1 1 26  − ++++++ −  1  −1 1 1 1 1 1 1  −1 27  − +++ −  − + −  1  −1 1 1 1  −1  −1 1  −1 28 + − + −  −  − + −  1 1  −1 1  −1  −1  −1 1  −1 29  −  − + − + −  −  −  1  −1  −1 1  −1 1  −1  −1  −1  148 Runa Patternb Blockc IGF-1 BTC INS EX4 ACTA GLU NIC HGF 30 00000000 1 0 0 0 0 0 0 0 0 31 + −  − ++ −  −  −  1 1  −1  −1 1 1  −1  −1  −1 32 ++ −  −  −  − + −  1 1 1  −1  −1  −1  −1 1  −1 33  −  − ++ − +++ 1   −1  −1 1 1  −1 1 1 1 34 00000000 1 0 0 0 0 0 0 0 0 35 00000000 1 0 0 0 0 0 0 0 0 36 ++ −  − +++ −  1 1 1  −1  −1 1 1 1  −1 37  −  − +++ − ++ 1  −1  −1 1 1 1  −1 1 1 38  − + − +++ −  −  2  −1 1  −1 1 1 1  −1  −1 39 00000000 2 0 0 0 0 0 0 0 0 40  − + − + −  −  −  −  2  −1 1  −1 1  −1  −1  −1  −1 41 ++ − ++ − + −  2 1 1  −1 1 1  −1 1  −1 42 + − ++ − ++ −  2 1  −1 1 1  −1 1 1  −1 43  −  − + −  −  − ++ 2  −1  −1 1  −1  −1  −1 1 1 44  − ++++ −  − + 2  −1 1 1 1 1  −1  −1 1 45 00000000 2 0 0 0 0 0 0 0 0 46 + − + −  − + − + 2 1  −1 1  −1  −1 1  −1 1 47 ++++++++ 2 1 1 1 1 1 1 1 1 48  −  −  − ++ −  − + 2  −1  −1  −1 1 1  −1  −1 1 49  − + −  − ++++ 2  −1 1  −1  −1 1 1 1 1 50 00000000 2 0 0 0 0 0 0 0 0 51  − ++ − + − + −  2  −1 1 1  −1 1  −1 1  −1 52  − +++ − + − + 2  −1 1 1 1  −1 1  −1 1 53  −  − + − ++++ 2  −1  −1 1  −1 1 1 1 1 54 00000000 2 0 0 0 0 0 0 0 0 55 + −  −  − ++ −  −  2 1  −1  −1  −1 1 1  −1  −1 56 00000000 2 0 0 0 0 0 0 0 0 57 + − + − + −  − + 2 1  −1 1  −1 1  −1  −1 1 58  − ++ −  − ++ −  2  −1 1 1  −1  −1 1 1  −1 59 + −  − + −  − ++ 2 1  −1  −1 1  −1  −1 1 1 60 +++ − ++ −  −  2 1 1 1  −1 1 1  −1  −1  149 Runa Patternb Blockc IGF-1 BTC INS EX4 ACTA GLU NIC HGF 61  −  − ++++ −  −  2  −1  −1 1 1 1 1  −1  −1 62 +++ −  −  −  −  −  2 1 1 1  −1  −1  −1  −1  −1 63 + −  − +++++ 2 1   −1  −1 1 1 1 1 1 64  −  −  −  − + − + −  2  −1  −1  −1  −1 1  −1 1  −1 65  −  − ++ −  −  −  −  2  −1  −1 1 1  −1  −1  −1  −1 66  − + −  −  −  − ++ 2  −1 1  −1  −1  −1  −1 1 1 67  −  −  − + − + − + 2  −1  −1  −1 1  −1 1  −1 1 68 ++ − + − ++ −  2 1 1  −1 1  −1 1 1  −1 69  −  −  −  −  − ++ −  2  −1  −1  −1  −1  −1 1 1  −1 70 ++++ −  − ++ 2 1 1 1 1  −1  −1 1 1 71 ++ −  − + −  − + 2 1 1  −1  −1 1  −1  −1 1 72 ++ −  −  − + − + 2 1 1  −1  −1  −1 1  −1 1 73 + −  −  −  −  −  −  −  2 1  −1  −1  −1  −1  −1  −1  −1 74 + − +++ − + −  2 1  −1 1 1 1  −1 1  −1 ‘1 or +’ = factor added to well at the concentration specified in ESM Table1 ‘−1 or −’ = factor not added to this well (zero dose) ‘0’ = factor added to well at the mid-point or average concentration between −1 and 1 aRun—individual well of a 96-well plate bPattern—summary of the combinations of factors added to an individual well cBlock—individual runs were separated into two plates (blocks) to use only the inner 60 wells of 96-well plates, thus minimising error from evaporation in external wells Factor abbreviations: IGF-1, insulin-like growth factor -1; BTC, betacellulin; INS, insulin; EX4, exendin 4; ACTA, activin A; GLU, glucose; NIC, nicotinamide; HGF, hepatocyte growth factor.       150  Table B4 Primers used in the study   Primer name Forward sequence (5′ to 3′) Reverse sequence (5′ to 3′) Amplicon size (bp) Ins1 TCAGAGACCATCAGCAAGCA GGGACCACAAAGATGCTGTT 134 Ins2 GGAGCGTGGCTTCTTCTACA CAGTGCCAAGGTCTGAAGGT 115 Ngn3 TGCAGCCACATCAAACTCTC GGTCACCCTGGAAAAAGTGA 139 Nkx2-2 CTTTCTACGACAGCAGCGACA TCCTTGTCATTGTCCGGTGA 160 Nkx6-1 ATCTTCTGGCCCGGAGTG TCTCTCTGGTCCTGCCAAG 192 Glut2 CTGTGTCCAGCTTTGCAGTG CCATCAAGAGGGCTCCAGTC 129 Pdx1 GACCTTTCCCGAATGGAACC GTTCCGCTGTGTAAGCACC 135 Gapdh TGATGGGTGTGAACCACGAG GGCCATCCACAGTCTTCTGG 177 Mafa TCACTCTGCCCACCATCAC TGACCTCCTCCTTGCTGAAG 198 Mafb GGTATAAACGCGTCCAGCAG CGAGTTTCTCGCACTTGACC 138 Gck GTTTTGTGTCGCAGGTGGAG GTGGACACGCTTTCACAGG 131 eGFP AGAACGGCATCAAGGTGAAC TGCTCAGGTAGTGGTTGTCG 134 mRFP CCCCGTAATGCAGAAGAAGA CTTGGCCATGTAGGTGGTCT 153  151 APPENDIX C   SUPPLEMENTAL TABLES   Table C1 Primers used in the study. Primer namea Forward sequence (5’ to 3’) Reverse sequence (5’ to 3’) Amplicon size (bp) GREB1 AGCCCACCAATTCCCTATTC TCCTGCTGGGATGTCAATTT 129 Greb1 CTTCCTTACGCTCCAACACC GCTGGGTTCTAACCCTCCTT 149 PPY AATGCCACACCAGAGCAGAT AGCGTGTCCTCTTTGTGTCT 104 Ppy GACTATGCGACACCTGAGCA CCAGGAAGTCCACCTGTGTT 122 KCNIP1 CAGTGGTGTGGTCAACGAAG AACTTCACGGAGCCTGTCTG 129 DEFB1 CAGTCGCCATGAGAACTTCC AGAGACATTGCCCTCCACTG 144 Defb1 GCTGCCACCACTATGAAAACT CCTCCATGTTGAAGGCATTT 137 Adcy8 GAGCTGCCTTTCGACAACAT AATTTCCTCAGGCCCAGACT 126 KCNJ2 TCTTGGGAATTCTGGTTTGC TCAGCTGACATCCAGAGAACA 140 GCG CATTCACAGGGCACATTCAC CCCTTCAGCATGTCTCTCAA 147 Gcg ACTCACAGGGCACATTCAC CCTTCAGCATGCCTCTCAAA 145 GBP2 GCAGTTTGTGAGAGGGAAGC TTGGCAGATGCCTCTTCATT 143 ECEL1 CTGGCAGCATACAGGGTGTT CGTAGGTCGTCATGCTCTGA 137 Ecel1 TACAGTCAGCCTGGACGACA TCACTCTCCTCGTCTTGAGC 111 FAP TGCGGAATTTAATGATACGG CAACGGGATTCTTAGCTCCA 116 FXYD2 GCAGAGACAGCAGGAAGAGG TAGTAGAACGGGTCCACGTC 112 Fxyd2 GAAGTGCCACTGTTCCCATC AGGGATTCTCTGTCCCCTTG 137 SERPINA1 CTCACCCACGATATCATCACC CCCCATTGCTGAAGACCTTA 148 Sst CCCAGACTCCGTCAGTTTCT CCAGGGCATCATTCTCTGTC 121 SST CCCAGACTCCGTCAGTTTCT ATCATTCTCCGTCTGGTTGG 114 NPR2 CTGGATGTCTTTGGGGAGAG GGGGTTCTCGGTACGTGAT 142 Npr2 AGCCACCCACTTCATCAGAG TCTCCCCAAAGACATCAAGG 146 FXYD5 GGATGGGCCTCTAGTGACAG CTGTCTGGACGTCTGTGCTT 116 CD36 AGTTCTCAATCTGGCTGTGG TGGATCCCTATAGCCCCATAA 148 MUC13 CCCACCACAGAAGACAATCA TCTGCACAGGGATCATCTTG 116 DDIT3 TGGAAGCCTGGTATGAGGAC AGTCAGCCAAGCCAGAGAAG 140 Ddit3 CAGGAGGTCCTGTCCTCAGA GGACGCAGGGTCAAGAGTAG 102 ANXA2 CTCTACACCCCCAAGTGCAT CAATGGTGACCTCATCCACA 119 Anxa2 GCCCTTATGACATGCTGGAG GTACAGGGGCTTGTTCTGGA 101 SLC40A1 TGCAGGAGAAGACAGAAGCA ATAAAGCCACAGCCGATGAC 138 TRIB3 TGCCCTACAGGCACTGAGTA AGGCGTAGAGGAGCTGGGTA 145 Trib3 CGCTTTGTCTTCAGCAACTG CATGCTTGTCCCACAGAGAG 103 Lamb3 TCAGCTTCTTCGAGCCTCAT TGGAGTCACACTTGCAGCAT 101 FSTL5 TGTGTGGATCTGACGGAGAA CTTGCTGTATTCAGTAGTCTTGCAC 143 TMEM145 GCGACACTTTCCTGAGAAGC CTGGATGCCATTGACAATCTT 145 KLF4 TCCCATCTTTCTCCACGTTC AGTCGCTTCATGTGGGAGAG 112 Klf4 CACCTGGCGAGTCTGACAT AGAGAGTTCCTCACGCCAAC 137 LMCD1 TCCCACTTTTGACACCATCA GTCACTGGCTGCTTCTCCTT 105 CARD11 CCTGCGTCAGTGTAAGGTCA GGCTCTCCAAGAAGACCACA 149 BAMBI GATCGCCACTCCAGCTACAT GGCAGCATCACAGTAGCATC 102 PYY GGAGCTGAACCGCTACTACG CGTTTTGGAAAGAAGCGTGT 103 Pyy AGGAGCTGAGCCGCTACTAC GTCGCTGTCGTCTGTGAAGA 125  152 Primer namea Forward sequence (5’ to 3’) Reverse sequence (5’ to 3’) Amplicon size (bp) DAP TTGTGCAGAAACACCCACAT TGACCCCAGAGATGAACACA 111 SLC7A14 CTCACTAGCCAACCACACCA AGCCAGAAGGTCTGGGTATG 100 ELL2 AACCCGGTGGACCATATGTA GAGATGGTGCTGCTGCTATG 145 SGK3 AGGAAAGCTGCCCAAGTGTA CCATTCACTTCTTCCCACTGA 107 Sgk3 AGGAGAGCTGCCCAAGTGTA CTTCTGCCCACAGAGACCA 100 BBC3 CAGGATGAAATTTGGCATGG GAGATTGTACAGGACCCTCCA 149 Bbc3 ACGACCTCAACGCGCAGTA CTCCAGGATCCCTGGGTAAG 123 Zfp598 GCAGATGGAAAGGTGTTTGC GCACAACTTGCAGCAGAAGA 144 TP53I3 TCCTCATGCCTATCCCAGAG CACACCACTCAGTCCTGCAT 146 VIM AAAGTGTGGCTGCCAAGAAC TGTCTCCGGTACTCAGTGGA 136 Slc2a3 TGTGGCCATCTTCTCTGTTG TGGCCAGCAAGTTGACTAGA 107 CA8 GTGTGCCGAGACTGTGAAGT TGGTTTTCTCTTCCCCAGTG 146 GCGR CAGATGTGGGAGGCAGCTA AGGAAGTCCATCACCTGAGC 127 NPY CGCTGCGACACTACATCAAC TCTGGGAACATTTTCTGTGC 113 FOXN2 TTTGCTACTGCACCAACAGG ATTCCGGATCAACACACCAT 133 LOC100045869 GCCTCCCTTTGTGAGCTATG GAGTTGATGAGCGCCACTTT 117 Slc39a9 TGTCCCTTGTATTGGGCTTC GGTGGTGATTTTGGAACTGC 116 IAPP TGTGCTCTCTGTTGCATTGA CACCAAAGTTGTTGCTGGAA 140 REG1A CCTTTGTGGCCTCACTGATT CAATGCCCCAGGACTTGTAG 135 Zfp512 GCTGCCACTTCACAGGTTG TTGAGGAAGCTCGCGATAGT 108 Rcan2 CCGACGGGTTCGAATAAAT CCAAATGCAGTTTGTCTCCA 149 DDEF1 ACCGCGTTTGTCAAGTTTTC TCCTTTGACTCCCTTTAGGTCTC 135 Ctsc CGACATTAACTGCTCGGTGA CACAATCTCGAAGCCTTGGT 136 G6PC2 TAGCAGTCATTGGGGATTGG CAAGGCATGGACTTGAGTGA 117 SLC2A2 (GLUT2) ATGCTCTGGTCCCTGTCTGT CCCATCAAGAGAGCTCCAAC 146 Slc2a2 (Glut2) CTGTGTCCAGCTTTGCAGTG CCATCAAGAGGGCTCCAGTC 129 BMP5 ATACAAGGACCGGAGCAACA AGACAAGCCAACCCACATCT 149 DLK1 GACGGGGAGCTCTGTGATAG GGGCACAGGAGCATTCATAG 109 TGFBR3 GGTGCATGTCCTGAATCTCC CAGACTTGTGGTGGATGTGG 110 Slc39a8 CCAGCTGCACTTCAACCA CAGATGGCAGAGAAGTTCGAG 102 Neu1 AGAGATGTTTGCCCCTGGA CGTGGTCATCACTGAGGAGA 131 INS CCTGCAGCCCTTGGCC GTTGCAGTAGTTCTCCAGGTG 102 Ins1 TCAGAGACCATCAGCAAGCA GGGACCACAAAGATGCTGTT 134 MAFA TTCAGCAAGGAGGAGGTCAT AGTTGGCACTTCTCGCTCTC 128 MafA TCACTCTGCCCACCATCAC TGACCTCCTCCTTGCTGAAG 198 MAFB ATAAACGCGTCCAGCAGAAG CCTTGTAGGCGTCTCTCTCG 117 MafB GGTATAAACGCGTCCAGCAG CGAGTTTCTCGCACTTGACC 138 PDX1 CCCATGGATGAAGTCTACC GTCCTCCTCCTTTTTCCAC 262 Pdx1 GACCTTTCCCGAATGGAACC GTTCCGCTGTGTAAGCACC 135 SLC2A1 (GLUT1) GCTTCGTGCCCATGTATGT CTTGTTGCCCATGATGGAGT 137 NKX6.1 CGTTGGGGATGACAGAGAGT CCGAGTCCTGCTTCTTCTTG 111 Gapdh TGATGGGTGTGAACCACGAG GGCCATCCACAGTCTTCTGG 177 GAPDH CCCATCACCATCTTCCAGGAG CTTCTCCATGGTGGTGAAGACG 104 a Primer names in lowercase  and uppercase letters represent rodent and human genes, respectively.       153 Table C2 Differentially expressed genes from purified primary adult immature Pdx1+/Inslow and mature Pdx1+/Ins+ mouse β-cells.  SYMBOLa DEFINITION FOLD Δb Gcg glucagon 5.286 Ppy pancreatic polypeptide 2.992 Pyy peptide YY 2.698 Sgk3 serum/glucocorticoid regulated kinase 3 (Sgk3), transcript variant 2 2.120 LOC634015 PREDICTED: similar to Proteasome subunit beta type 3  0.499 Pop5 processing of precursor 5, ribonuclease P/MRP family (S. cerevisiae) 0.498 Hnrpdl heterogeneous nuclear ribonucleoprotein D-like 0.496 Krt7 keratin 7 0.493 Mrpl17 39S ribosomal protein L17, mitochondrial 0.493 Mcat malonyl CoA:ACP acyltransferase (mitochondrial) 0.492 Fubp3 far upstream element (FUSE) binding protein 3 0.492 Whsc2 Wolf-Hirschhorn syndrome negative elongation factor A  0.489 Rab33b RAB33B, member of RAS oncogene family 0.489 Lias lipoic acid synthetase  0.487 Tmem118 transmembrane protein 118 0.487 Ghitm growth hormone inducible transmembrane protein 0.486 Rab28 RAB28, member RAS oncogene family 0.486 Sec24c SEC24 related gene family, member C (S. cerevisiae) 0.483 Paip2b poly(A) binding protein interacting protein 2B 0.483 Serinc3 serine incorporator 3 0.482 EG626367 PREDICTED: predicted gene, EG626367 0.481 Zzz3 zinc finger, ZZ domain containing 3, transcript variant 1 0.481 Mia3 melanoma inhibitory activity 3 0.479 Pfdn5 prefoldin 5  0.479 Lmnb2 lamin B2 0.479 Tspan7 tetraspanin 7 0.477 Acbd3 acyl-Coenzyme A binding domain containing 3  0.477 Atp2b1 ATPase, Ca++ transporting, plasma membrane 1  0.474 Chchd1 coiled-coil-helix-coiled-coil-helix domain containing 1 0.473 Ndufb3 NADH dehydrogenase (ubiquinone) 1 beta subcomplex 3  0.471 2410016F01Rik RIKEN cDNA 2410016F01 gene 0.471 Afg3l2 AFG3(ATPase family gene 3)-like 2 (yeast)  0.467 Aldh1l2 aldehyde dehydrogenase 1 family, member L2  0.467 Aldh5a1 aldhehyde dehydrogenase family 5, subfamily A1  0.467 EG546325 predicted gene, EG546325 0.462 1700109H08Rik RIKEN cDNA 1700109H08 gene 0.462 Cog8 Conserved oligomeric Golgi complex subunit 8 0.462 Slc39a9 PREDICTED: solute carrier family 39 (zinc transporter), member 9 0.454 LOC100044087 PREDICTED: similar to brain protein 44 0.454 Pdx1 pancreatic and duodenal homeobox 1 0.454 1300018I05Rik Mus musculus RIKEN cDNA 1300018I05 gene 0.452 Tceb2 Mus musculus transcription elongation factor B (SIII), polypeptide 2 0.449 Flcn folliculin  0.438 Ppa1 pyrophosphatase (inorganic) 1 0.438 AW121567 expressed sequence AW121567  0.437 Zfp512 zinc finger protein 512 0.435 LOC100043906 PREDICTED: similar to nuclear pore-targeting complex component of 58 kDa  0.429 B230114H05Rik RIKEN cDNA B230114H05 gene 0.426 2410003P15Rik RIKEN cDNA 2410003P15 gene  0.424  154 SYMBOLa DEFINITION FOLD Δb Rnf11 ring finger protein 11  0.422 1300010F03Rik PREDICTED: RIKEN cDNA 1300010F03 gene 0.420 Rcan2 regulator of calcineurin 2, transcript variant 1 0.418 Sept11 septin 11 0.410 Psmb7 proteasome (prosome, macropain) subunit, beta type 7 0.405 H2afv Histone H2A.V 0.389 Psmd12 proteasome (prosome, macropain) 26S subunit, non-ATPase, 12 0.367 Rsn restin  0.361 JR_bGal_40 JeremyReiter_bGalactosidase_40 0.352 Neu1 neuraminidase 1 0.277  a Bold genes chosen for real-time RT-PCR follow-up experiments b Values represent differential expression of genes from immature Pdx1+/Inslow cells relative to mature Pdx1+/Ins+ cells   Table C3 Differentially expressed genes from purified primary adult immature Pdx1+/Inslow and mature Pdx1+/Ins+ human β-cells.  SYMBOLa DEFINITION FOLD Δb GHRL ghrelin/obestatin preprohormone 27.559 IL13RA2 interleukin 13 receptor, alpha 2 16.921 PRG-3 plasticity related gene 3,  variant 2 11.695 CHN2 chimerin (chimaerin) 2,  variant 2 11.626 FEV FEV (ETS oncogene family) 11.551 PPY pancreatic polypeptide 11.211 STK32B serine/threonine kinase 32B 11.007 F10 coagulation factor X 8.125 KCNIP1 Kv channel interacting protein 1,  variant 3 7.949 MAOB monoamine oxidase B, mitochondrial protein 7.475 DKFZp686H20120 cDNA DKFZp686H20120 7.448 BAIAP2L2 BAI1-associated protein 2-like 2 6.806 OVGP1 oviductal glycoprotein 1, 120kDa (mucin 9, oviductin) 6.759 SORBS1 sorbin and SH3 domain containing 1,  variant 3 6.554 IRX2 iroquois homeobox 2 6.300 FRMPD3 PREDICTED: FERM and PDZ domain containing 3 6.141 ASTN1 astrotactin 1,  variant 1 6.080 AMDHD1 amidohydrolase domain containing 1 5.854 PTP4A3 protein tyrosine phosphatase type IVA, member 3,  variant 2 5.819 STMN4 stathmin-like 4 5.588 HIST1H1A histone 1, H1a 5.498 FXYD3 FXYD domain containing ion transport regulator 3,  variant 1 5.497 CYP3A5 cytochrome P450, family 3, subfamily A, polypeptide 5 5.497 KCNJ2 potassium inwardly-rectifying channel, subfamily J, member 2 5.336 PDGFD platelet derived growth factor D,   variant 2 5.268 KCTD12 potassium channel tetramerisation domain containing 12 5.268 GBP2 guanylate binding protein 2, interferon-inducible 5.252 C20orf39 chromosome 20 open reading frame 39 5.222 FAP fibroblast activation protein, alpha 5.126 SERPINA1 serpin peptidase inhibitor, clade A , member 1, variant 2 4.944  155 SYMBOLa DEFINITION FOLD Δb VIL1 villin 1 4.734 IGFBP2 insulin-like growth factor binding protein 2 4.732 FXYD3 FXYD domain containing ion transport regulator 3,  variant 1 4.710 SST somatostatin (SST) 4.694 BVES blood vessel epicardial substance,  variant 5 4.670 SH3RF1 SH3 domain containing ring finger 1 4.666 SPINK1 serine peptidase inhibitor, Kazal type 1 4.620 DIRAS3 DIRAS family, GTP-binding RAS-like 3 4.552 LOC730357 PREDICTED: hypothetical protein LOC730357 4.516 LOC387763 PREDICTED: hypothetical LOC387763 4.514 PTP4A3 protein tyrosine phosphatase type IVA, member 3,  variant 2 4.493 DPP4 dipeptidyl-peptidase 4 (CD26, adenosine deaminase complexing protein 2) 4.486 TMEM176A transmembrane protein 176A 4.399 EIF2C3 eukaryotic translation initiation factor 2C, 3,  variant 2 4.333 ZMYM5 zinc finger, MYM-type 5,  variant 1 4.324 SERPINA1 serpin peptidase inhibitor, clade A , member 1, variant 3 4.261 4811759 cDNA clone IMAGE:4811759 4.243 CDS1 CDP-diacylglycerol synthase (phosphatidate cytidylyltransferase) 1 4.200 TNC  tenascin C (hexabrachion) 4.150 BTBD11 BTB (POZ) domain containing 11,  variant 1 4.102 FXYD5 FXYD domain containing ion transport regulator 5,  variant 2 4.066 CD36 cluster of differentiation 36 (thrombospondin receptor),  variant 1 4.054 MUC13 mucin 13, cell surface associated 4.050 HGD homogentisate 1,2-dioxygenase (homogentisate oxidase) 3.990 GRIA3 glutamate receptor, ionotrophic, AMPA 3,  variant flop 3.929 TNIP2 TNFAIP3 interacting protein 2 3.919 CDO1 cysteine dioxygenase, type I 3.878 SLC5A1 solute carrier family 5 (sodium/glucose cotransporter), member 1 3.857 C2orf44 chromosome 2 open reading frame 44 3.836 CNTN1 contactin 1,  variant 1 3.827 USH1C Usher syndrome 1C (autosomal recessive, severe),  variant b3 3.776 MR1 major histocompatibility complex, class I-related 3.756 BRI3BP BRI3 binding protein 3.748 NPHP4 nephronophthisis 4 3.727 CNOT6L CCR4-NOT ion complex, subunit 6-like 3.696 TM4SF4 transmembrane 4 L six family member 4 3.671 GC group-specific component (vitamin D binding protein) 3.667 AOX1 aldehyde oxidase 1 3.658 C10orf33 chromosome 10 open reading frame 33  3.656 PTP4A3 protein tyrosine phosphatase type IVA, member 3,  variant 2 3.649 CP ceruloplasmin (ferroxidase) 3.632 NPHP4 nephronophthisis 4 3.607 CHKA choline kinase alpha,  variant 2 3.597 SMOC1 SPARC related modular calcium binding 1,  variant 1 3.577 BCAR3 breast cancer anti-estrogen resistance 3 3.499 LOC344595 PREDICTED: hypothetical LOC344595 3.487 SNPH syntaphilin 3.484 TJP2 tight junction protein 2 (zona occludens 2),  variant 2 3.462 MYO10 myosin X 3.440 C20orf100 chromosome 20 open reading frame 100 3.424 MAPK4 mitogen-activated protein kinase 4 3.399 MS4A8B membrane-spanning 4-domains, subfamily A, member 8B 3.399  156 SYMBOLa DEFINITION FOLD Δb SOCS1 suppressor of cytokine signaling 1 3.361 FAM46A family with sequence similarity 46, member A 3.340 SLC40A1 solute carrier family 40 (iron-regulated transporter), member 1 3.294 GRIK2 glutamate receptor, ionotropic, kainate 2,  variant 1 3.289 KCNH4 potassium voltage-gated channel, subfamily H (eag-related), member 4 3.278 GPR64 G protein-coupled receptor 64,  variant 2 3.270 MAPK4 mitogen-activated protein kinase 4 3.255 PODN podocan 3.204 DRD1IP dopamine receptor D1 interacting protein 3.196 DUSP16 dual specificity phosphatase 16 3.193 TMEM176B transmembrane protein 176B 3.188 GPR64 G protein-coupled receptor 64,  variant 4 3.120 NNMT nicotinamide N-methyltransferase 3.113 C8B complement component 8, beta polypeptide 3.064 CAMK2G calcium/calmodulin-dependent protein kinase II gamma,  variant 5 3.052 GALNTL1 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase-like 1 3.023 LOC441763 PREDICTED: hypothetical LOC441763 3.004 LOC732150 PREDICTED: hypothetical protein LOC732150 2.987 FSTL5 follistatin-like 5 2.985 TMEM145  transmembrane protein 145 2.977 ALK anaplastic lymphoma receptor tyrosine kinase 2.964 GALNT13 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 13 2.906 SLC44A3 solute carrier family 44, member 3 2.880 PCSK7 proprotein convertase subtilisin/kexin type 7 2.870 LMCD1 LIM and cysteine-rich domains 1 2.834 NIH_MGC_84 602255030F1 NIH_MGC_84 cDNA clone IMAGE:4347391 5 2.828 CARD11 caspase recruitment domain family, member 11 2.801 SLC22A4 solute carrier family 22 (organic cation/ergothioneine transporter), member 4 2.800 FAM102B family with sequence similarity 102, member B 2.797 KIAA0574  mRNA for KIAA0574 protein, partial cds 2.791 CRH corticotropin releasing hormone 2.744 BAMBI BMP and activin membrane-bound inhibitor homolog (Xenopus laevis) 2.739 PDK4 pyruvate dehydrogenase kinase, isozyme 4 2.737 PTP4A2 PREDICTED: tyrosine phosphatase type IVA, member 2,  variant 5 2.725 RRAS related RAS viral (r-ras) oncogene homolog 2.703 CENPP centromere protein P 2.698 F11 coagulation factor XI (plasma thromboplastin antecedent) 2.691 THOC6 THO complex 6 homolog (Drosophila) 2.684 STS steroid sulfatase (microsomal), isozyme S 2.675 NARG2 NMDA receptor regulated 2,  variant 2 2.671 NMB neuromedin B,  variant 1 2.665 TDRD9 tudor domain containing 9 2.658 IDUA iduronidase, alpha-L 2.656  NCI_CGAP_Kid8 BX097044 NCI_CGAP_Kid8 cDNA clone IMAGp998G174867 2.652 C1orf76 chromosome 1 open reading frame 76 2.621 Sept10 septin 10 (SEPT10),  variant 2 2.610 TPPP3 tubulin polymerization-promoting protein family member 3 2.585 KCNJ8 potassium inwardly-rectifying channel, subfamily J, member 8 2.570 MSI2 musashi homolog 2 (Drosophila),  variant 1 2.527 LMO3 LIM domain only 3 (rhombotin-like 2),  variant 1 2.524  157 SYMBOLa DEFINITION FOLD Δb SH3KBP1 SH3-domain kinase binding protein 1,  variant 1 2.523 SUGT1 SGT1, suppressor of G2 allele of SKP1 (S. cerevisiae) 2.520 GPC6 glypican 6 2.502 SELENBP1 selenium binding protein 1 2.501 RGS4 regulator of G-protein signalling 4 2.492 FLJ41667 fis cDNA FLJ41667 fis, clone FEBRA2028366 2.489 ACOT4 acyl-CoA thioesterase 4 2.487 RAB3C RAB3C, member RAS oncogene family 2.485 ST7 suppression of tumorigenicity 7,  variant a 2.485 EFCAB4A EF-hand calcium binding domain 4A 2.484 MED29 mediator complex subunit 29 2.480 DOK4 docking protein 4 2.461 ABCA11 ATP-binding cassette, sub-family A, member 11 (pseudogene) 2.459 EIF2S2 eukaryotic translation initiation factor 2, subunit 2 beta, 38kDa 2.458 C19orf4 chromosome 19 open reading frame 4 2.453 GCG glucagon 2.436 LEPR leptin receptor,  variant 2 2.429 LOC26010 viral DNA polymerase-transactivated protein 6,  variant 2 2.428 FAM59B PREDICTED: family with sequence similarity 59, member B 2.416 SCCPDH saccharopine dehydrogenase (putative) 2.415 N4-HIS 1 ie90b04.y5 Melton Normalized Human Islet 4 N4-HIS 1 cDNA  2.412 MORG1 mitogen-activated protein kinase organizer 1 2.398 BCHE butyrylcholinesterase 2.382 C3orf23 chromosome 3 open reading frame 23,  variant 1 2.382 PDGFRL platelet-derived growth factor receptor-like 2.376 PIGN phosphatidylinositol glycan anchor biosynthesis, class N, variant 1 2.374 CECR6 cat eye syndrome chromosome region, candidate 6 2.373 DAP death-associated protein 2.360 TCEAL7 ion elongation factor A (SII)-like 7 2.347 Nb2HP  BX097190 Soares placenta Nb2HP cDNA clone IMAGp998G19212 2.346 FEZ1 fasciculation and elongation protein zeta 1 (zygin I),  variant 2 2.342 GRIA3 glutamate receptor, ionotrophic, AMPA 3,  variant flip 2.323 SEPSECS Sep (O-phosphoserine) tRNA:Sec (selenocysteine) tRNA synthase,  variant 2 2.318 PEG10 paternally expressed 10,  variant 1 2.307 BRP44 brain protein 44 2.294 SLC7A14 solute carrier family 7 (cationic amino acid transporter), member 14 2.291 1090207 mRNA full length insert cDNA clone EUROIMAGE 1090207 2.280 NARG1 NMDA receptor regulated 1 (NARG1) 2.276 SLC35F4 PREDICTED: solute carrier family 35, member F4 2.271 ATP2B4 ATPase, Ca++ transporting, plasma membrane 4,  variant 2 2.256 CGN cingulin 2.253 SULT4A1 sulfotransferase family 4A, member 1,  variant 2 2.241 GPR108 G protein-coupled receptor 108,  variant 1 2.231 CPNE8 copine VIII 2.218 PCNX pecanex homolog (Drosophila) 2.217 PLSCR4 phospholipid scramblase 4 2.209 PAFAH1B3 platelet-activating factor acetylhydrolase, isoform Ib, gamma subunit 29kDa 2.201 RFX2 regulatory factor X, 2 (influences HLA class II expression),  variant 2 2.200 LOC653610 PREDICTED: similar to Histone H2A.o (H2A/o) (H2A.2) (H2a-615) 2.199 SIRT5 sirtuin (silent mating type information regulation 2 homolog) 5 (S. cerevisiae), variant 2 2.197  158 SYMBOLa DEFINITION FOLD Δb NSUN7 NOL1/NOP2/Sun domain family, member 7 2.188 NSUN7 NOL1/NOP2/Sun domain family, member 7 2.158 C9orf127 chromosome 9 open reading frame 127 2.157 CAMK2G calcium/calmodulin-dependent protein kinase (CaM kinase) II gamma,  variant 4 2.155 KANK1 KN motif and ankyrin repeat domains 1,  variant 1 2.152 KIAA1244 brefeldin A-inhibited guanine nucleotide-exchange protein 3 2.147 SSRP1 structure specific recognition protein 1 2.141 ZNF23 zinc finger protein 23 (KOX 16) 2.139 ELL2 elongation factor, RNA polymerase II, 2 2.129 KCNJ6 potassium inwardly-rectifying channel, subfamily J, member 6 2.122 FKBP11 FK506 binding protein 11, 19 kDa 2.115 DFFA DNA fragmentation factor, 45kDa, alpha polypeptide, variant 2 2.113 PPP1R14C protein phosphatase 1, regulatory (inhibitor) subunit 14C 2.109 MTUS1 mitochondrial tumor suppressor 1, mitochondrial protein,  variant 1 2.094 TMEM125 transmembrane protein 125 2.090 HLA-G HLA-G histocompatibility antigen, class I, G 2.086 LOC81691 exonuclease NEF-sp 2.075 LOC92497 PREDICTED: hypothetical protein LOC92497 2.074 OSBPL6 oxysterol binding protein-like 6,  variant 1 2.073 FOXP4 forkhead box P4,  variant 1 2.071 UFD1L ubiquitin fusion degradation 1 like (yeast), variant 2 2.063 MARVELD3 MARVEL domain containing 3,  variant 1 2.055 TROVE2 TROVE domain family, member 2,  variant 1 2.055 REC8 REC8 homolog (yeast),  variant 1 2.047 ADSL adenylosuccinate lyase 2.035 LAMB1 laminin, beta 1 2.033 TP53I3 tumor protein p53 inducible protein 3,  variant 2 2.022 UCK2 uridine-cytidine kinase 2 2.019 UBXD4 UBX domain containing 4 2.012 VIM vimentin 1.823 SEC62 SEC62 homolog (S. cerevisiae) 0.499 PAPD4 PAP associated domain containing 4 0.495 PLCXD3 phosphatidylinositol-specific phospholipase C, X domain containing 3 0.494 IFIT1 interferon-induced protein with tetratricopeptide repeats 1,  variant 2 0.494 FLJ31407 fis cDNA FLJ31407 fis, clone NT2NE2000137 (RAR-related orphan receptor A) 0.493 MAN1C1 mannosidase, alpha, class 1C, member 1 0.493 NAV2 neuron navigator 2,  variant 2 0.493 PRDM10 PR domain containing 10,  variant  0.492 DKFZp686B24166 cDNA DKFZp686B24166 Hypothetical LOC151162 0.492 C21orf33 chromosome 21 open reading frame 33, mitochondrial protein,  variant 2 0.492 EPAS1 endothelial PAS domain protein 1 0.491 DKFZp761E1721 cDNA DKFZp761E1721 (from clone DKFZp761E1721) 0.491 NIF3L1 NIF3 NGG1 interacting factor 3-like 1 (S. pombe) 0.490 GLRB glycine receptor, beta 0.490 CA8 carbonic anhydrase VIII  0.490 SPRED2 sprouty-related, EVH1 domain containing 2 0.489 ROBO1 roundabout, axon guidance receptor, homolog 1 (Drosophila),  variant 2 0.489 ZFYVE26 zinc finger, FYVE domain containing 26 0.488 CXorf23 chromosome X open reading frame 23 0.488 ISCA1 iron-sulfur cluster assembly 1 homolog (S. cerevisiae) 0.487 CP110 CP110 protein 0.487  159 SYMBOLa DEFINITION FOLD Δb FLJ38215 fis NIH_MGC_141 cDNA FLJ38215 fis, clone FCBBF2000291 0.487 GCGR glucagon receptor 0.486 KIAA1219 KIAA1219 mRNA 0.486 DDX58 DEAD (Asp-Glu-Ala-Asp) box polypeptide 58 0.486 PLEKHM2 pleckstrin homology domain containing, family M (with RUN domain) member 2 0.485 NPY neuropeptide Y 0.484 PTPDC1 protein tyrosine phosphatase domain containing 1,  variant 1 0.483 MANBA mannosidase, beta A, lysosomal 0.483 NPR2 natriuretic peptide receptor B/guanylate cyclase B (atrionatriuretic peptide receptor B) 0.483 SOBP sine oculis binding protein homolog (Drosophila) 0.482 FOXN2 forkhead box N2 0.481 BIRC6 baculoviral IAP repeat-containing 6 (apollon) 0.480 C17orf48 chromosome 17 open reading frame 48 0.480 FBXO15 F-box protein 15 0.477 PITPNM1 phosphatidylinositol transfer protein, membrane-associated 1 0.476 TOX thymocyte selection-associated high mobility group box 0.476 C14orf140 chromosome 14 open reading frame 140,  variant 2 0.475 TSC22D1 TSC22 domain family, member 1,  variant 1 0.472 CITED2 Cbp/p300-interacting transactivator, with Glu/Asp-rich carboxy-terminal domain, 2 0.472 ALKBH1 alkB, alkylation repair homolog 1 (E. coli) 0.470 RASD1 RAS, dexamethasone-induced 1 0.470 HOPX HOP homeobox,  variant 3 0.468 RPP25 ribonuclease P/MRP 25kDa subunit 0.467 TMEM97 transmembrane protein 97 0.466 KIAA0367  KIAA0367, mRNA. 0.466 TMEM39A transmembrane protein 39A 0.463 FLJ35319 fis cDNA FLJ35319 fis, clone PROST2011577 0.462 DKFZp779M2422 cDNA DKFZp779M2422 (from clone DKFZp779M2422) 0.461 FAM58A family with sequence similarity 58, member A 0.460 ZFP37 zinc finger protein 37 homolog (mouse) 0.459 TSPAN1 tetraspanin 1 0.458 CDRT4 CMT1A duplicated region  4 0.458 ALDH3A2 aldehyde dehydrogenase 3 family, member A2,  variant 1 0.458 TMEM64 transmembrane protein 64  0.458 CCDC132 coiled-coil domain containing 132,  variant 1 0.457 SIRT1 sirtuin (silent mating type information regulation 2 homolog) 1 (S. cerevisiae) 0.457 NSUN4 NOL1/NOP2/Sun domain family, member 4  0.457 TSPAN13 tetraspanin 13  0.456 PPP1R10 protein phosphatase 1, regulatory (inhibitor) subunit 10 0.456 TBC1D4 TBC1 domain family, member 4 0.455 LOC646786 PREDICTED: similar to Afadin (AF-6 protein) 0.454 IAPP islet amyloid polypeptide  0.454 PAQR3 progestin and adipoQ receptor family member III  0.454 ERO1LB ERO1-like beta (S. cerevisiae)  0.454 ID3 inhibitor of DNA binding 3, dominant negative helix-loop-helix protein 0.454 NBEA neurobeachin 0.454 TIA1 TIA1 cytotoxic granule-associated RNA binding protein,  variant 2 0.453 PTPN3 protein tyrosine phosphatase, non-receptor type 3 0.452 TRIM39 tripartite motif-containing 39,  variant 2 0.451 CADM1 cell adhesion molecule 1,  variant 1 0.451  160 SYMBOLa DEFINITION FOLD Δb ITPR3 inositol 1,4,5-triphosphate receptor, type 3 0.450 FMO4 flavin containing monooxygenase 4  0.449 TMEM127 transmembrane protein 127  0.448 SRD5A1 steroid-5-alpha-reductase, alpha polypeptide 1 (3-oxo-5 alpha-steroid delta 4-dehydrogenase alpha 1) 0.448 TCN1 transcobalamin I (vitamin B12 binding protein, R binder family) 0.447 TMEM117 transmembrane protein 117 0.446 ARHGEF2 rho/rac guanine nucleotide exchange factor (GEF) 2  0.446 CBX7 chromobox homolog 7  0.444 ANKRD6 ankyrin repeat domain 6  0.444 PCSK1 proprotein convertase subtilisin/kexin type 1  0.444 UTP15 UTP15, U3 small nucleolar ribonucleoprotein, homolog (S. cerevisiae)  0.443 C9orf91 chromosome 9 open reading frame 91  0.441 CHST9 carbohydrate (N-acetylgalactosamine 4-0) sulfotransferase 9  0.441 LYRM5 LYR motif containing 5  0.441 APOBEC2 apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 2  0.440 SCNN1A sodium channel, nonvoltage-gated 1 alpha 0.440 TIPRL TIP41, TOR signaling pathway regulator-like (S. cerevisiae),  variant 1 0.439 EPGN epithelial mitogen homolog (mouse) (EPGN) 0.439 RNF26 ring finger protein 26  0.438 FLJ40058 fis cDNA FLJ40058 fis, clone TCOLN1000180 0.437 REG1A regenerating islet-derived 1 alpha  0.437 SYNE2 spectrin repeat containing, nuclear envelope 2,  variant 1 0.437 NCI_CGAP_Kid3 qk02b10.x1 NCI_CGAP_Kid3  cDNA clone IMAGE:1867771 3 0.437 ALKBH1 alkB, alkylation repair homolog 1 (E. coli) 0.434 PRSS23 protease, serine, 23 (PRSS23), mRNA. 0.433 FLJ38388 fis cDNA FLJ38388 fis, clone FEBRA2004485 0.433 C6orf64 chromosome 6 open reading frame 64 (C6orf64), mRNA. 0.432 B3GALNT1 beta-1,3-N-acetylgalactosaminyltransferase 1 (globoside blood group),  variant 2 0.432 MT0357 CM3-MT0357-260101-690-b10 MT0357  cDNA 0.431 SLC6A6 solute carrier family 6 (neurotransmitter transporter, taurine), member 6 0.430 IRX3 iroquois homeobox 3 (IRX3) 0.429 ALOX5 PREDICTED:  arachidonate 5-lipoxygenase 0.429 RBM12B RNA binding motif protein 12B  0.429 FLJ38153 fis cDNA FLJ38153 fis, clone DFNES1000083 0.428 BTN3A1 butyrophilin, subfamily 3, member A1 0.428 CD14 CD14 molecule,  variant 1 0.427 LXN latexin 0.427 PLEKHA5 pleckstrin homology domain containing, family A member 5  0.427 MSN moesin  0.424 GTPBP3 GTP binding protein 3 (mitochondrial),  variant V 0.424 GEM GTP binding protein overexpressed in skeletal muscle,  variant 2 0.421 KIAA0232 KIAA0232,  variant 1 0.419 TSHZ3 teashirt zinc finger homeobox 3  0.418 KCNJ16 potassium inwardly-rectifying channel, subfamily J, member 16,  variant 1 0.417 RANBP6 RAN binding protein 6 0.416 TRIM2 tripartite motif-containing 2  0.414 TTC31 tetratricopeptide repeat domain 31 0.414 IFI44 interferon-induced protein 44 0.412 RSBN1  round spermatid basic protein 1  0.411 DKFZp686N1644 cDNA DKFZp686N1644 (from clone DKFZp686N1644) 0.411  161 SYMBOLa DEFINITION FOLD Δb GPR177 G protein-coupled receptor 177,  variant 1 0.409 DDEF1 development and differentiation enhancing factor 1 0.408 PPP3CC protein phosphatase 3 (formerly 2B), catalytic subunit, gamma isoform 0.406 PROCR protein C receptor, endothelial (EPCR) 0.405 ACSL1 acyl-CoA synthetase long-chain family member 1 0.405 GPR177 G protein-coupled receptor 177,  variant 2 0.405 OSBPL8 oxysterol binding protein-like 8,  variant 2 0.403 TSPAN9 tetraspanin 9  0.403 RETSAT retinol saturase (all-trans-retinol 13,14-reductase)  0.402 TRIM37 tripartite motif-containing 37,  variant 1 0.400 WDR5 WD repeat domain 5,  variant 1 0.400 SLC6A15 solute carrier family 6, member 15,  variant 1 0.399 NEDD4L neural precursor cell expressed, developmentally down-regulated 4-like 0.399 TRIP6 thyroid hormone receptor interactor 6 0.398 GREM1 gremlin 1, cysteine knot superfamily, homolog (Xenopus laevis)  0.398 PANK1 pantothenate kinase 1,  variant beta 0.397 LOC653513 PREDICTED:  similar to phosphodiesterase 4D interacting protein isoform 2 0.397 NIN ninein (GSK3B interacting protein),  variant 2 0.396 LSM10 U7 small nuclear RNA associated 0.395 RASGRP1 RAS guanyl releasing protein 1 (calcium and DAG-regulated) 0.395 PPP2R2C protein phosphatase 2, regulatory subunit B, gamma isoform,  variant 2 0.394 GPR177 G protein-coupled receptor 177,  variant 2 0.394 ERO1LB ERO1-like beta (S. cerevisiae)  0.393 TTLL7 tubulin tyrosine ligase-like family, member 7 0.392 NQO1 NAD(P)H dehydrogenase, quinone 1,  variant 1 0.391 FLJ25252 fis cDNA FLJ25252 fis, clone STM03814 0.391 C5orf41 chromosome 5 open reading frame 41 0.386 SLC39A8 solute carrier family 39 (zinc transporter), member 8 0.382 GPRIN1 G protein regulated inducer of neurite outgrowth 1  0.378 ST6GAL1 ST6 beta-galactosamide alpha-2,6-sialyltranferase 1,  variant 2 0.377 G6PC2 glucose-6-phosphatase, catalytic, 2,  variant 1 0.376 CHPT1 choline phosphotransferase 1 0.370 USP21 ubiquitin specific peptidase 21,  variant 1 0.370 C9orf82 chromosome 9 open reading frame 82 0.370 BTBD7 BTB (POZ) domain containing 7,  variant 2 0.369 TMEM189 transmembrane protein 189 0.369 ZNF616 zinc finger protein 616 0.368 SCD5 stearoyl-CoA desaturase 5,  variant 1 0.368 CYYR1 cysteine/tyrosine-rich 1 0.367 C9orf135 chromosome 9 open reading frame 135 0.366 KLHL24 kelch-like 24 (Drosophila)  0.366 AFF1 AF4/FMR2 family, member 1 0.365 DACH2 dachshund homolog 2 (Drosophila) (DACH2) 0.365 CHSY1 chondroitin sulfate synthase 1 0.363 TLN2 talin 2  0.363 CYP2J2 cytochrome P450, family 2, subfamily J, polypeptide 2  0.361 UCHL1 ubiquitin carboxyl-terminal esterase L1 (ubiquitin thiolesterase)  0.361 MEIS3P1 Meis homeobox 3 pseudogene 1  0.361 LOC133993 PREDICTED: hypothetical LOC133993,  variant 2 0.359 PDE12 phosphodiesterase 12  0.359 CNGA3 cyclic nucleotide gated channel alpha 3,  variant 2 0.358  162 SYMBOLa DEFINITION FOLD Δb SIRT5 sirtuin (silent mating type information regulation 2 homolog) 5 ,variant 1 0.356 WRN Werner syndrome (WRN) 0.355 NBN nibrin (NBN),  variant 2 0.354 SLC2A2 solute carrier family 2 (facilitated glucose transporter), member 2  0.354 C3orf52 chromosome 3 open reading frame 52 0.353 HIST1H4C histone cluster 1, H4c  0.351 SPP1 secreted phosphoprotein 1, variant 1 0.351 PIGA phosphatidylinositol glycan anchor biosynthesis, class A , variant 3 0.351 PPTC7 PTC7 protein phosphatase homolog (S. cerevisiae)  0.351 XYLT1 xylosyltransferase I  0.350 C6orf115 chromosome 6 open reading frame 115  0.349 ASCL1 achaete-scute complex homolog 1 (Drosophila)  0.347 C12orf43 chromosome 12 open reading frame 43 0.347 NPTX2 neuronal pentraxin II  0.347 EXOC5 exocyst complex component 5 0.346 EIF5A2 eukaryotic translation initiation factor 5A2 0.345 ATP8B4 ATPase, class I, type 8B, member 4  0.344 FUT8 fucosyltransferase 8 (alpha (1,6) fucosyltransferase),  variant 3 0.344 SLC17A6 solute carrier family 17 (sodium-dependent inorganic phosphate cotransporter), member 6 0.342 PGM2 phosphoglucomutase 2 0.341 SLC39A11 solute carrier family 39 (metal ion transporter), member 11 0.340 PALM2 paralemmin 2,  variant 2 0.340 P2RY5 purinergic receptor P2Y, G-protein coupled, 5 0.340 LINGO2 leucine rich repeat and Ig domain containing 2  0.340 TAGLN3 transgelin 3,  variant 3 0.340 LPXN leupaxin 0.340 ACSM3 acyl-CoA synthetase medium-chain family member 3,  variant 1 0.339 CS0DF032YA11 full-length cDNA clone CS0DF032YA11 of Fetal brain 0.338 ENOX2 ecto-NOX disulfide-thiol exchanger 2,  variant 1 0.338 PRKCA protein kinase C, alpha  0.335 AGTPBP1 ATP/GTP binding protein 1  0.334 SLC38A6 solute carrier family 38, member 6 0.333 GPR177 G protein-coupled receptor 177,  variant 1 0.333 LOC728772 PREDICTED: similar to transmembrane protein 106A,  variant 1 0.333 UI-E-CK1-afh-j-02-0- UI 5 UI-E-CK1-afh-j-02-0-UI.r1 UI-E-CK1 cDNA clone UI-E-CK1-afh-j-02-0-UI 5 0.332 LOC728069 PREDICTED: hypothetical LOC728069 0.330 SEMA6A sema domain, transmembrane domain (TM), and cytoplasmic domain, (semaphorin) 6A 0.330 POLR1E polymerase (RNA) I polypeptide E, 53kDa 0.328 CYP27A1 cytochrome P450, family 27, subfamily A, polypeptide 1, mitochondrial protein 0.328 NAP5 Nck-associated protein 5,  variant 1 0.327 PFKFB2 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 2,  variant 1 0.323 PPAT phosphoribosyl pyrophosphate amidotransferase  0.323 LRRN3 leucine rich repeat neuronal 3 0.322 GRB10 growth factor receptor-bound protein 10,  variant 1 0.321 PPM1E protein phosphatase 1E (PP2C domain containing) 0.316 FEM1C fem-1 homolog c (C. elegans) 0.314 GOLT1B golgi transport 1 homolog B (S. cerevisiae) (GOLT1B), mRNA. 0.313 C10orf104 chromosome 10 open reading frame 104 0.311 ARHGAP30 Rho GTPase activating protein 30 (ARHGAP30),  variant 1 0.310  163 SYMBOLa DEFINITION FOLD Δb ZNF91 zinc finger protein 91 0.309 BMP5 bone morphogenetic protein 5 0.309 DLK1 delta-like 1 homolog (Drosophila)  0.308 TGFBR3 transforming growth factor, beta receptor III 0.308 SLC16A10 solute carrier family 16 (aromatic amino acid transporter), member 10  0.306 LHFP lipoma HMGIC fusion partner 0.305 SPSB1 splA/ryanodine receptor domain and SOCS box containing 1  0.305 RCBTB2 regulator of chromosome condensation (RCC1) and BTB (POZ) domain containing protein 2 0.303 CRSP6 cofactor required for Sp1 ional activation, subunit 6, 77kDa 0.301 GLIS3 GLIS family zinc finger 3,  variant 2 0.301 CABLES1 Cdk5 and Abl enzyme substrate 1,  variant 1 0.300 ITPR2 inositol 1,4,5-triphosphate receptor, type 2  0.294 cs17g03.y1 Human Retinal pigment epithelium/choroid: cs  cDNA clone cs17g03 5 0.294 DOCK2 dedicator of cytokinesis 2 0.294 SLC25A29 solute carrier family 25, member 29, nuclear gene mitochondrial protein 0.293 FANCG Fanconi anemia, complementation group G 0.292 ESR1 estrogen receptor 1  0.290 HADH hydroxyacyl-Coenzyme A dehydrogenase, mitochondrial protein 0.288 DNM3 dynamin 3  0.288 CTSK cathepsin K 0.287 FXYD2 FXYD domain containing ion transport regulator 2,  variant b 0.286 ENTPD3 ectonucleoside triphosphate diphosphohydrolase 3  0.284 ARHGAP10 Rho GTPase activating protein 10 0.283 CCDC77 coiled-coil domain containing 77  0.283 GPR177 G protein-coupled receptor 177,  variant 2 0.283 C6orf65 chromosome 6 open reading frame 65 0.280 MPP1 membrane protein, palmitoylated 1, 55kDa  0.278 CALML4 calmodulin-like 4,  variant 1 0.278 TTC26 tetratricopeptide repeat domain 26 0.276 EDEM1 ER degradation enhancer, mannosidase alpha-like 1 0.272 CCNG2 cyclin G2  0.268 LOC152195 hypothetical protein LOC152195 0.265 TUBGCP5 tubulin, gamma complex associated protein 5 0.262 ILDR1 immunoglobulin-like domain containing receptor 1 0.262 RILPL2 Rab interacting lysosomal protein-like 2 0.261 GALM galactose mutarotase (aldose 1-epimerase) 0.261 BMF Bcl2 modifying factor,  variant 4 0.260 NLRP2 NLR family, pyrin domain containing 2 0.259 GALNT10 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 10, variant 2 0.256 ACOX1 acyl-Coenzyme A oxidase 1, palmitoyl,  variant 2 0.256 FLJ38717 FLJ38717 protein, mRNA. 0.254 SUSD4 sushi domain containing 4,  variant 2 0.254 ZCRB1 zinc finger CCHC-type and RNA binding motif 1 0.253 PITPNC1 phosphatidylinositol transfer protein, cytoplasmic 1,  variant 1 0.249 CFLAR CASP8 and FADD-like apoptosis regulator 0.242 KIAA0408 KIAA0408, mRNA. 0.237 MLKL mixed lineage kinase domain-like 0.235 MAP6D1 MAP6 domain containing 1 0.234 HCST hematopoietic cell signal transducer,  variant 2 0.234 C10orf119 chromosome 10 open reading frame 119 0.232 RNASEL ribonuclease L (2',5'-oligoisoadenylate synthetase-dependent) 0.230  164 SYMBOLa DEFINITION FOLD Δb NIB BX095930 Soares infant brain 1NIBcDNA clone IMAGp998J16275 0.225 KCNG3 potassium voltage-gated channel, subfamily G, member 3,  variant 2 0.221 CYP2U1 cytochrome P450, family 2, subfamily U, polypeptide 1 0.219 PRIM1 primase, DNA, polypeptide 1 (49kDa) 0.219 VAV3 vav 3 guanine nucleotide exchange factor,  variant 1 0.213 DCBLD1 discoidin, CUB and LCCL domain containing 1 0.210 IGSF11 immunoglobulin superfamily, member 11,  variant 2 0.207 EFHD1 EF-hand domain family, member D1 0.205 ZDHHC15 zinc finger, DHHC-type containing 15 0.204 VAV3 vav 3 guanine nucleotide exchange factor,  variant 1 0.202 TAGLN3  transgelin 3,  variant 3 0.199 SFTPA1 surfactant, pulmonary-associated protein A1 0.198 OSBPL5 oxysterol binding protein-like 5,  variant 2 0.197 ANKRD37 ankyrin repeat domain 37 0.192 BMF Bcl2 modifying factor,  variant 2 0.188 ETS2 v-ets erythroblastosis virus E26 oncogene homolog 2 (avian) 0.185 LRRN3 leucine rich repeat neuronal 3,  variant 1 0.183 HCLS1 hematopoietic cell-specific Lyn substrate 1 0.182 NIH_MGC_85 AGENCOURT_6796899 NIH_MGC_85 cDNA clone IMAGE:5787825 5 0.174 ACPP acid phosphatase, prostate 0.164 CAPN13 calpain 13 0.164 GPNMB glycoprotein (transmembrane) nmb,  variant 2 0.150 MAMDC2 MAM domain containing 2 0.146 MAPK1 mitogen-activated protein kinase 1,  variant 1 0.138 CTSL2 cathepsin L2 (CTSL2) 0.136 FLJ23006 fis cDNA: FLJ23006 fis, clone LNG00414 0.125 YAF2 YY1 associated factor 2 0.120 CLEC4A C-type lectin domain family 4, member A (CLEC4A),  variant 4 0.109 CYP1B1 cytochrome P450, family 1, subfamily B, polypeptide 1 0.096 ITGB7 integrin, beta 7 0.078 GPNMB glycoprotein (transmembrane) nmb,  variant 1 0.057 a Bold genes chosen for real-time RT-PCR follow-up experiments b Values represent differential expression of genes from immature Pdx1+/Inslow cells relative to mature Pdx1+/Ins+ cells   Table C4 Differentially expressed genes from purified primary adult immature Pdx1+/Inslow and mature Pdx1+/Ins+ MIN6 β-cells.  SYMBOLa DEFINITION FOLD Δb Greb1 gene regulated by estrogen in breast cancer protein 18.933 Greb1 gene regulated by estrogen in breast cancer protein  11.872 Lgals3 lectin, galactose binding, soluble 3  10.290 LOC100047285 PREDICTED: similar to implantation serine proteinase 2  9.080 Defb1 defensin beta 1  7.439 Adcy8 adenylate cyclase 8  7.297 Abcc3 ATP-binding cassette, sub-family C (CFTR/MRP), member 3  7.178 LOC208080 LOC208080 6.076 Dgkb diacylglycerol kinase, beta  5.593 Dgkb diacylglycerol kinase, beta  5.260 Ecel1 endothelin converting enzyme-like 1  5.188  165 SYMBOLa DEFINITION FOLD Δb Fxyd2 FXYD domain-containing ion transport regulator 2,  variant b 5.025 Dgkb Diacylglycerol kinase beta 5.006 Atf3 activating ion factor 3  4.667 Espn espin (Espn),  variant 5 4.543 Egln3 EGL nine homolog 3 (C. elegans)  4.541 Adm adrenomedullin  4.402 Npr2 natriuretic peptide receptor 2  4.382 Fxyd2 FXYD domain-containing ion transport regulator 2,  variant b 4.124 Slc17a6 solute carrier family 17 (sodium-dependent inorganic phosphate cotransporter), member 6  4.115 C130008L17Rik C130008L17Rik 4.072 Ddit3 DNA-damage inducible  3  3.987 Galntl4 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase-like 4 3.984 Slc17a6 Slc17a6 3.931 Esr1 estrogen receptor 1 (alpha)  3.697 Olfml3 olfactomedin-like 3  3.661 Cdsn corneodesmosin  3.652 Lcn2 lipocalin 2  3.545 Ddit3 DNA-damage inducible  3  3.377 Anxa2 annexin A2  3.335 Cd97 CD97 antigen  3.326 Igfbp5 Igfbp5 3.243 Hspa1a heat shock protein 1A  3.243 Trib3 tribbles homolog 3 (Drosophila)  3.234 Osr2 odd-skipped related 2 (Drosophila)  3.195 Agt angiotensinogen (serpin peptidase inhibitor, clade A, member 8)  3.183 Wbscr27 Williams Beuren syndrome chromosome region 27 (human) 3.076 Cyp2s1 cytochrome P450, family 2, subfamily s, polypeptide 1  3.075 4930511H01Rik 4930511H01Rik 3.038 Fxyd2 FXYD domain-containing ion transport regulator 2,  variant a 3.038 Angptl6 Angptl6 3.036 Lamb3 laminin, beta 3  3.021 Steap1 six transmembrane epithelial antigen of the prostate 1 3.012 Dusp26 dual specificity phosphatase 26 (putative)  2.984 Unc5b unc-5 homolog B (C. elegans)  2.942 Spink4 Spink4 2.938 Gad1 glutamic acid decarboxylase 1  2.933 Klf4 Kruppel-like factor 4 (gut)  2.907 Trib3 tribbles homolog 3 (Drosophila)  2.901 6330416L11Rik 6330416L11Rik 2.872 Lhfpl2 lipoma HMGIC fusion partner-like 2  2.871 1700011M02Rik PREDICTED: RIKEN cDNA 1700011M02 gene 2.839 Cacna1g calcium channel, voltage-dependent, T type, alpha 1G subunit  2.815 Sox11 SRY-box containing gene 11 2.807 Pcsk6 PREDICTED: proprotein convertase subtilisin/kexin type 6,  variant 4  2.799 Klf4 Kruppel-like factor 4 (gut)  2.794 Adamtsl2 ADAMTS-like 2  2.789 Acox2 acyl-Coenzyme A oxidase 2, branched chain  2.765 Gad1 glutamic acid decarboxylase 1  2.753 Stbd1 starch binding domain 1 (Stbd1) 2.746 Trib3 tribbles homolog 3 (Drosophila)  2.709  166 SYMBOLa DEFINITION FOLD Δb Soat2 sterol O-acyltransferase 2  2.698 Sulf2 sulfatase 2 (Sulf2) 2.696 Slc4a1 solute carrier family 4 (anion exchanger), member 1  2.686 Pkd2l1 polycystic kidney disease 2-like 1  2.670 Wipf3 PREDICTED: WAS/WASL interacting protein family, member 3  2.626 2610040L17Rik 2610040L17Rik 2.626 Ccdc109b coiled-coil domain containing 109B  2.611 Myd116 myeloid differentiation primary response gene 116  2.607 Gpr120 G protein-coupled receptor 120  2.584 Prr7 proline rich 7 (synaptic)  2.580 9130213B05Rik RIKEN cDNA 9130213B05 gene  2.557 Mamdc2 MAM domain containing 2  2.542 scl0004023.1_57 scl0004023.1_57 2.528 B230386D16Rik B230386D16Rik 2.501 Id4 inhibitor of DNA binding 4  2.493 Adm2 adrenomedullin 2  2.488 Smtnl2 smoothelin-like 2  2.488 Pkp2 plakophilin 2  2.480 1700011M02Rik PREDICTED: RIKEN cDNA 1700011M02 gene  2.478 Elmo1 engulfment and cell motility 1, ced-12 homolog (C. elegans),  variant 2 2.478 Pmepa1 prostate transmembrane protein, androgen induced 1 2.473 Lor loricrin  2.472 4930415O10Rik 4930415O10Rik 2.466 Stat5a signal transducer and activator of ion 5A  2.463 Arhgef2 Arhgef2 2.444 2310005L22Rik 2310005L22Rik 2.423 Osr2 odd-skipped related 2 (Drosophila) 2.422 4933407L21Rik 4933407L21Rik 2.415 LOC100047090 PREDICTED: similar to VIP2 receptor for vasoactive intestinal peptide (VIP) (LOC100047090), misc RNA. 2.411 Rnf208 ring finger protein 208  2.405 1700007K13Rik RIKEN cDNA 1700007K13 gene 2.392 Map3k14 mitogen-activated protein kinase kinase kinase 14  2.384 Popdc3 popeye domain containing 3  2.368 Gm129 gene model 129, XM_907670 XM_920513 XM_920520 XM_920527 XM_920533 2.363 A530080P10 A530080P10 2.342 Ccng2 cyclin G2  2.337 H2-T23 histocompatibility 2, T region locus 23  2.327 Lbcl1 Lbcl1 2.322 Pkp2 plakophilin 2  2.322 Gm129 gene model 129, XM_907670 XM_920513 XM_920520 XM_920527 XM_920533 2.317 Rshl3 PREDICTED: radial spokehead-like 3  2.314 LOC100047427 PREDICTED: similar to thyroid hormone receptor 2.311 Nxf7 nuclear RNA export factor 7  2.292 B3gat1 beta-1,3-glucuronyltransferase 1 (glucuronosyltransferase P) 2.290 Trp53inp1 transformation related protein 53 inducible nuclear protein 1  2.289 Cd97 CD97 antigen  2.276 Tgif1 TGFB-induced factor homeobox 1  2.271 Rbpms RNA binding protein gene with multiple splicing,  variant 3 2.270 Chst2 carbohydrate sulfotransferase 2  2.270 Hspa1b heat shock protein 1B 2.265 Sox11 SRY-box containing gene 11  2.254  167 SYMBOLa DEFINITION FOLD Δb Rdm1 RAD52 motif 1 2.246 Dusp16 dual specificity phosphatase 16,  variant B1 2.216 Rnd3 Rho family GTPase 3 2.213 Trp53inp1 transformation related protein 53 inducible nuclear protein 1  2.210 Fbxo32 F-box protein 32  2.208 Dmrtc1a DMRT-like family C1a,  variant 1 2.204 5430405G05Rik 5430405G05Rik 2.200 LOC100046586 PREDICTED: similar to loop-tail protein 2 2.183 Sema4a sema domain, immunoglobulin domain (Ig), transmembrane domain (TM) and short cytoplasmic domain, (semaphorin) 4A 2.177 Spsb1 splA/ryanodine receptor domain and SOCS box containing 1 2.177 Gm129 gene model 129, XM_907670 XM_920513 XM_920520 XM_920527 XM_920533 2.174 Kiss1 KiSS-1 metastasis-suppressor 2.163 Prph peripherin  2.149 Tnnc1 troponin C, cardiac/slow skeletal  2.134 C030027H14Rik C030027H14Rik 2.132 Dusp16 dual specificity phosphatase 16,  variant B1 2.125 1810032O08Rik PREDICTED: RIKEN cDNA 1810032O08 gene, misc RNA. 2.119 3010003L21Rik PREDICTED: RIKEN cDNA 3010003L21 gene, misc RNA. 2.113 Rbpms RNA binding protein gene with multiple splicing (Rbpms),  variant 3 2.110 Hist1h2be histone cluster 1, H2be 2.110 Bbc3 BCL2 binding component 3 2.108 Gpr146 Gpr146 2.095 Hsd17b11 hydroxysteroid (17-beta) dehydrogenase 11 2.093 Srgap3 SLIT-ROBO Rho GTPase activating protein 3 2.088 Tnfrsf12a tumor necrosis factor receptor superfamily, member 12a  2.087 Dusp16 dual specificity phosphatase 16 (Dusp16),  variant A1 2.086 2010107G12Rik RIKEN cDNA 2010107G12 gene 2.083 LOC385019 LOC385019 2.073 6330404F12Rik 6330404F12Rik 2.061 Ppp1r3c protein phosphatase 1, regulatory (inhibitor) subunit 3C 2.060 Sema3a sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3A  2.053 Pou6f1 POU domain, class 6, ion factor 1  2.050 Zfp598 zinc finger protein 598 2.050 Sema6d sema domain, transmembrane domain (TM), and cytoplasmic domain, (semaphorin) 6D,  variant 1 2.049 Prph peripherin 2.049 2410006H16Rik PREDICTED: RIKEN cDNA 2410006H16 gene 2.048 Avpi1 arginine vasopressin-induced 1  2.042 Mgat4b mannoside acetylglucosaminyltransferase 4, isoenzyme B 2.041 1700016K19Rik RIKEN cDNA 1700016K19 gene 2.039 Chd5 chromodomain helicase DNA binding protein 5,  variant 1 2.038 AI118078 expressed sequence AI118078  2.034 Ddit4 DNA-damage-inducible  4  2.033 Trp53i11 transformation related protein 53 inducible protein 11 2.030 Irx2 iroquois homeobox 2 2.025 Dmrtc1a DMRT-like family C1a,  variant 3 2.023 Kcnd2 potassium voltage-gated channel, Shal-related family, member 2 2.021 Nfix nuclear factor I/X,  variant 3 2.018 Ctxn1 cortexin 1  2.017 Aebp1 AE binding protein 1 2.014 Stard5 StAR-related lipid transfer (START) domain containing 5 2.003  168 SYMBOLa DEFINITION FOLD Δb 6720475J19Rik PREDICTED: RIKEN cDNA 6720475J19 gene) 2.003 Myo18b PREDICTED: myosin XVIIIb 0.499 Slc2a3 solute carrier family 2 (facilitated glucose transporter), member 3  0.499 Vdr vitamin D receptor 0.499 2810030E01Rik RIKEN cDNA 2810030E01 gene  0.498 Pappa2 PREDICTED: pappalysin 2 0.497 Slc5a10 solute carrier family 5 (sodium/glucose cotransporter), member 10  0.496 Gabrg2 gamma-aminobutyric acid (GABA-A) receptor, subunit gamma 2,  variant 1 0.496 Taar1 trace amine-associated receptor 1  0.490 Iqcf5 PREDICTED: IQ motif containing F5 0.488 Gsta4 glutathione S-transferase, alpha 4  0.487 4432405B04Rik RIKEN cDNA 4432405B04 gene  0.485 Slc14a2 solute carrier family 14 (urea transporter), member 2,  variant 1 0.483 Tceal5 ion elongation factor A (SII)-like 5 0.482 Dclk1 doublecortin-like kinase 1  0.482 1600029I14Rik 1600029I14Rik 0.481 Magea2 melanoma antigen, family A, 2 0.479 Kcnh5 potassium voltage-gated channel, subfamily H (eag-related), member 5  0.476 2200002J24Rik 2200002J24Rik 0.473 LOC193690 LOC193690 0.472 LOC100045869 PREDICTED: similar to Limb expression 1 homolog (chicken)  0.472 Kirrel3 kin of IRRE like 3 (Drosophila) 0.471 scl0004010.1_24 scl0004010.1_24 0.469 BC028528 cDNA sequence BC028528  0.463 6530401P13 6530401P13 0.463 Mansc1 MANSC domain containing 1  0.457 BC028528 cDNA sequence BC028528  0.450 1190007F08Rik RIKEN cDNA 1190007F08 gene XM_921339 XM_921348 XM_921353 0.446 E230025E14Rik E230025E14Rik 0.442 Arhgap20 Arhgap20 0.433 eGFP eGFP 0.433 Ctsc cathepsin C 0.431 Sucla2 succinate-Coenzyme A ligase, ADP-forming, beta subunit, mitochondrial protein 0.426 Cntn3 Cntn3 0.425 Sparcl1 SPARC-like 1 (mast9, hevin)  0.410 A830039N20Rik A830039N20Rik 0.399 Cd248 CD248 antigen, endosialin 0.395 Ctsc cathepsin C 0.390 6330442E10Rik RIKEN cDNA 6330442E10 gene  0.380 Adam32 a disintegrin and metallopeptidase domain 32  0.380 Eraf erythroid associated factor  0.376 Lcp2 lymphocyte cytosolic protein 2  0.372 620807 predicted gene, 620807  0.371 Spry4 sprouty homolog 4 (Drosophila)  0.366 LOC382213 LOC382213 0.358 Tnfrsf9 tumor necrosis factor receptor superfamily, member 9,  variant 1 0.349 Olfr1463 olfactory receptor 1463 0.320 Gria3 glutamate receptor, ionotropic, AMPA3 (alpha 3)  0.318 Aass aminoadipate-semialdehyde synthase, nuclear gene mitochondrial protein 0.316 LOC666096 PREDICTED: similar to Xlr-related, meiosis regulated  0.313 C1qtnf1 C1q and tumor necrosis factor related protein 1  0.307 Slc39a8 solute carrier family 39 (metal ion transporter), member 8  0.283  169 SYMBOLa DEFINITION FOLD Δb Ankle2 ankyrin repeat and LEM domain containing 2  0.265 a Bold genes chosen for real-time RT-PCR follow-up experiments b Values represent differential expression of genes from immature Pdx1+/Inslow cells relative to mature Pdx1+/Ins+ cells   SUPPLEMENTAL FIGURES        Figure C1 Purity of sorted Pdx1+/Inslow and Pdx1+/Ins+ MIN6 cells. A) Representative FACS plots showing purity analysis after sorting of immature Pdx1+/Inslow (top) and mature Pdx1+/Ins+ (bottom) MIN6 cells. B) Corresponding fluorescence microscope images of sorted cells.      50 μm RFP GFP 98.9% Pdx1+ 0.9% Pdx1+/Ins+ 0% Ins+ 0.1% (-) 0.1 Pdx1+% 99.7% Pdx1+/Ins+ 0% Ins+ 0.2% (-) A B  170 APPENDIX D                          171                           172                                   173    174                                   175 

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