Activation of Islet Inflammation by Cytokine Signalling in Pancreatic b-cells
Understanding the Role of Protein Tyrosine Phosphatases
William James Stanley
ORCID: 0000-0001-8001-2359
Student Number: 515467
Submitted in Total Fulfilment of The Degree of
Doctor of Philosophy
March 2020
St. Vincent’s Institute of Medical Research
Department of Medicine (St. Vincent’s Hospital)
The University of Melbourne
Abstract:
Type 1 diabetes is characterised by the autoimmune destruction of insulin producing β- cells in the islets of Langerhans of the pancreas. Immune cells release pro-inflammatory cytokines such as interferon-g (IFN-g), tumour necrosis factor-a (TNF-a) and interleukin-
1b (IL-1b) into the islet microenvironment which activate phosphorylation cascades and gene expression in b-cells that increase their susceptibility to autoimmune attack and destruction. Protein tyrosine phosphatases (PTPs) regulate phosphorylation based signalling pathways and have previously been shown to negatively regulate IFN-g induced cell death of β-cells in vitro. We previously showed that during immune infiltration to the islet PTPs, including PTPN1 and PTPN6, are rendered catalytically inactive through oxidation resulting in loss of signal regulation. The overall aim of this thesis is to observe if antioxidant treatment can reduce autoimmune development in the NOD/Lt mouse through reduction of oxidised PTPs and dissect the role of PTPN1 and PTPN6 in the regulation of cytotoxic signalling events in the NIT-1 β-cell line and isolated NODPI islets in vitro.
Chapter 3 studies the effect of the mitochondrial targeted antioxidant mito-TEMPO on insulitis and diabetes development in the NOD/Lt mouse. Delivery of mito-TEMPO through drinking water reduced levels of oxidised PTPs in the pancreas of NOD/Lt mice but had no effect on the development of insulitis, activity or number of CD8+ and CD4+ T- cells in the periphery in NOD/Lt mice or diabetes development in a diabetes transfer model.
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Chapter 4 describes the regulation of cytokine signalling in NIT-1 cells and isolated
NODPI islets by PTPN1. Inhibition of PTPN1 activity reduced IFN-g, TNF-a and IL-1b induced death of NIT-1 cells in vitro. Activation of the IFN-g, TNF-a and IL-1b signalling pathways and downstream transcription of pro-inflammatory gene signatures associated with autoimmune diabetes were also reduced with PTPN1 inactivation. Furthermore,
PTPN1 inhibition reduced IFN-g induced MHC-I expression on the surface of NODPI β- cells and reduced the ability of autoreactive NOD8.3 CD8+ T-cells to destroy isolated
NOD/Lt islets. These studies showed that PTPN1 is a positive regulator of cytotoxic signalling in NIT-1 cells and NODPI islets and promotes immune cell mediated death, suggesting it may be a potential therapeutic target for type 1 diabetes.
Chapters 5&6 study the role of PTPN6 in cytokine signalling regulation in NIT-1 cells.
PTPN6 inhibition was found to enhance TNF-a induced NIT-1 cell death independent of
IFN-g and IL-1b in vitro. TNF-a induced JNK signalling was enhanced with PTPN6 inhibition which resulted in reduced anti-apoptotic BCL-2 protein expression and enhanced caspase-3 cleavage. Pan-caspase inhibition prevented TNF-a induced cell death suggesting that cells were dying through apoptosis. TNF-a induced cell death was also prevented with
RIPK1 inhibition which prevented enhanced caspase-8 cleavage in PTPN6 deficient cells.
Collectively these studies showed that PTPN6 negatively regulates TNF-a induced intrinsic and extrinsic apoptosis of β-cells in vitro.
Overall, the data indicate that PTPs play a nonredundant role in the regulation of cytotoxic signalling in NIT-1 cells and NODPI islets. This finding is consistent with results in other
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disease pathologies. The results provide a mechanistic insight into how PTPN1 and PTPN6 have opposite roles in regulating cytokine signalling, highlighting how PTPN1 antagonism and PTPN6 agonism may prove beneficial in reducing β-cell death in vitro. Whether these results are directly translatable into in vivo models of autoimmune diabetes remains undetermined. The use of PTPN1 inhibitors or PTPN6 agonists currently under development would allow direct translation of these results.
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Declaration:
I. The thesis comprises only their original work towards the Doctor of Philosophy
except where indicated in the preface.
II. Due acknowledgement has been made in the text to all other material used.
III. The thesis is fewer than the maximum word limit in length, exclusive of tables,
maps, bibliographies and appendices or that the thesis is 80,000 words as approved
by the Research Higher Degrees Committee.
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Preface:
I assess my contribution to the results described in each chapter to be:
Chapter 3: 95%
Chapter 4: 90%
Chapter 5: 95%
Chapter 6: 100%
The following list outlines the experiments performed by others or with assistance that have been included in the results section of this thesis:
Chapter 3:
§ Oxidised PTP immunoblot was performed by Dr. Esteban Gurzov.
Chapter 4:
§ PTPN1 deficient NIT-1 cells were generated in collaboration with Dr. Andrew
Sutherland.
§ 51Chromium release assay was performed with assistance by Dr. Prerak Trivedi.
Chapter 5:
§ PTPN6 deficient NIT-1 cells were generated in collaboration with Dr. Andrew
Sutherland.
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The following are a list of publications completed during the course of my PhD degree:
1. Stanley WJ, Trivedi PM, Sutherland AP, Thomas HE, Gurzov EN (2017). Differential regulation of pro- inflammatory cytokine signalling by protein tyrosine phosphatases in pancreatic β-cells. Journal of molecular endocrinology 59(4):325-337.
2. Stanley WJ, Litwak SA, Quah HS, Tan SM, Kay TW, Tiganis T, de Hann JB, Thomas He, Gurzov EN (2015). Inactivation of protein tyrosine phosphatases enhances interferon signalling in pancreatic islets. Diabetes 64(7):2489-96.
3. Pilkington EH, Lai M, Ge X, Stanley WJ, Wang B, Wang M, Kakinen A, Sani MA, Whittaker MR, Gurzov EN, Ding F, Quinn JF, Davis TP, Ke PC (2017). Star polymers reduce IAPP toxicity via accelerated amyloid aggregation. Biomacromolecules 18(12):4249-4260. 4. Litwak SA, Pang L, Galic S, Stanley WJ, Turatsinze JV, Loh K, Gough DJ, Eizirik D, Gurzov EN (2017). JNK activation of BIM promotes hepatic oxidative stress, steatosis and insulin resistance in obesity. Journal of Cell Biology 66(12):2973-2986.
5. Litwak SA, Loh K, Stanley WJ, Pappas EG, Wali J, Selck C, Strasser A, Thomas HE, Gurzov EN (2016). P53- upregulated-modulator-of-apoptosis (PUMA) deficiency affects food intake but does not impact on body weight or glucose homeostasis in diet-induced obesity. Scientific reports 6:23802.
6. Gurzov EN, Stanley WJ, Pappas EG, Thomas HE, Gough DJ (2016). The JAK/STAT pathway in obesity and diabetes. FEBS J 283:3002-15.
7. Pilkington EH, Gurzov EN, Kakinen A, Litwak SA, Stanley WJ, Davis TP, Ke PC (2016). Pancreatic β-cell membrane fluidity and toxicity induced by human islet amyloid polypeptide species. Scientific reports 6:21274.
8. Gurzov EN, Wang B, Pilkington EH, Chen P, Kakinen A, Stanley WJ, Litwak SA, Hanssen EG, Davis TP, Ding F, Ke PC (2016). Inhibition of hIAPP amyloid aggregation and pancreatic β-cell toxicity by OH- terminated PAMAM dendrimer. Small 12(12):1615-26.
9. Nedumpully-Govindan P, Gurzov EN, Chen P, Pilkington EH, Stanley WJ, Litwak SA, Davis TP, Ke PC, Ding F (2016). Graphene oxide inhibits hiAPP amyloid fibrillation and toxicity in insulin-producing NIT-1 cells. Physical Chemistry Chemical Physics 18(1):94- 100.
10. Litwak SA, Wali JA, Pappas E, Saadi H, Stanley WJ, Kay TW, Thomas HE, Gurzov EN (2015). Lipotoxic stress induces pancreatic beta cell death through modulation of Bcl-2 proteins by the ubiquitin/proteasome system. Journal of Diabetes Research 2015:280615.
11. Gurzov EN, Stanley WJ, Brodnicki TC, Thomas HE (2015). Protein tyrosine phosphatases: molecular switches in metabolism and diabetes. Trends in Endocrinology & Metabolism 26:30-9.
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Acknowledgements:
I am very thankful to my supervisors Dr. Esteban Gurzov and Prof. Helen Thomas for allowing me to undertake my PhD studies in the Immunology and Diabetes Unit at St.
Vincent’s Institute of Medical Research. I didn’t realise how difficult completing a PhD can be but their guidance and support pushed me to finish when I thought it would never end. I would also like to thank Prof. Natalie Sims, A/Prof Jörg Heierhorst and Dr. Amanda
Edgley for their wisdom and assistance when I needed it as well.
The Immunology and Diabetes Unit has been a pleasure to work in and I’m incredibly grateful to all the researchers for creating a wonderful work environment. In particular I’d like to thank Dr. Sara Litwak, Dr. Kate Graham and Stacey Fynch for technical assistance in the lab when I needed it. I also want to thank Dr. Andrew Sutherland and Dr. Prerak Trivedi for helping me with experiments I couldn’t have done alone.
Working at St. Vincent’s Institute of Medical Research has been fantastic and the staff are a pleasure to be around. I’m grateful for Dr. Rachel Mudge, Dr. Anne Johnston and the foundation for helping me apply for scholarships and rewarding me with a top up scholarship. I also thank the Harold Mitchell Foundation for awarding me a travel grant to travel to Belgium and present my work at the European Cell Death Organisation. I’d also like to thank the students for keeping my optimism up and general comradery. I’d also like to thank my parents, family and friends for making this whole process slightly less tedious and more enjoyable.
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Table of Contents:
Literature Review...... 1 1.1 Literature review methodology: ...... 2 1.2 Type 1 diabetes overview: ...... 3 1.2.1 Human islet immunopathology in type 1 diabetes: ...... 4 1.3 Mouse models of type 1 diabetes: ...... 5 1.3.1 The Non-Obese Diabetic (NOD)/Lt mouse:...... 5 1.3.2 Multiple low doses of streptozotocin model: ...... 8 1.4 Cytokine signalling in type 1 diabetes: ...... 9 1.4.1 Interferon signalling overview:...... 9 1.4.2 IFN-g signalling in b-cells sensitises to autoimmune destruction in the NOD/Lt mouse: ...... 11 1.4.3 Cell death overview: ...... 15 1.4.4 Apoptosis: ...... 16 1.4.5 Caspases: ...... 16 1.4.6 The intrinsic apoptotic pathway:...... 17 1.4.7 The extrinsic apoptotic pathway: ...... 18 1.4.8 Necroptosis: ...... 19 1.4.9 Canonical TNF-a signalling overview: ...... 20 1.4.10 Non-canonical TNF-a signalling overview: ...... 21 1.4.11 IL-1β signalling overview: ...... 23 1.4.12 IFN-g, TNF-a and IL-b induced b-cell dysfunction and apoptosis: ...... 25 1.4.13 Anti-cytokine therapies for T1D: ...... 29 1.5 Protein kinases, protein tyrosine phosphatases and autoimmune diabetes: ...... 30 1.5.1 Protein phosphorylation: ...... 30 1.5.2 Protein kinases: ...... 30 1.5.3 Protein tyrosine phosphatases: ...... 31 1.5.4 Protein tyrosine phosphatase biochemistry: ...... 32 1.5.5 PTP involvement in disease: ...... 34 1.5.6 Oxidative PTP inactivation in autoimmune diabetes: ...... 37 1.6 Hypothesis and aims: ...... 41 Materials and Methods ...... 42 2.1 Overall principal of the methodology: ...... 43
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2.2 Mouse details:...... 43 2.3 Diabetes incidence: ...... 44 2.4 Adoptive transfer of diabetic NOD/Lt splenocytes into NOD/Rag1 mice: ...... 44 2.5 Antioxidant storage and treatment:...... 45 2.6 Islet isolation: ...... 45 2.7 NIT-1 cell maintenance and cell treatments: ...... 46 2.8 CRISPR/Cas9 deletion of protein tyrosine phosphatases: ...... 47 2.9 Immunoblotting: ...... 49 2.10 mRNA extraction and real-time PCR: ...... 50 2.11 Haematoxylin and eosin histology: ...... 51 2.12 Insulin immunohistochemistry: ...... 52 2.13 Insulitis scoring: ...... 52 2.14 Cell viability: ...... 53 2.15 Flow cytometry analysis of MHC-I: ...... 54 2.16 Flow cytometry analysis of CD4+ and CD8+ T-cells:...... 55 2.17 51Chromium release assay: ...... 56 2.18 Statistical analysis: ...... 57 Targeting Oxidative Stress and Autoimmune Diabetes in NOD/Lt Mice with Antioxidants ...... 58 3.1 Summary: ...... 59 3.2 Introduction: ...... 60 3.3 Results: ...... 63 3.3.1 Antioxidant treatment in drinking water reduces PTP oxidation in NOD/Lt mice: 63 3.3.2 Mito-TEMPO in drinking water does not affect insulitis development in NOD/Lt mice: ...... 65 3.3.3 Mito-TEMPO treated drinking water does not affect T-cell development or activity in NOD/Lt mice: ...... 69 3.3.4 Mito-TEMPO treated drinking water does not affect diabetes transferred by NOD/Lt mice: ...... 72 3.4 Discussion: ...... 74 Role of PTPN1 in Regulation of Cytokine Signalling in Pancreatic b-cells 80 4.1 Summary: ...... 81 4.2 Introduction: ...... 82 4.3 Results: ...... 84
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4.3.1 Development of PTPN1 deficient NIT-1 cells: ...... 84 4.3.2 PTPN1 inactivation decreases cytokine induced NIT-1 cell death:...... 87 4.3.3 PTPN1 inactivation reduces IFN-γ induced gene expression in NIT-1 cells and NODPI islets...... 91 4.3.4 PTPN1 inactivation reduces IFN-γ induced MHC-I expression on β-cells and CD8+ T-cell mediated death of NODPI islets...... 94 4.3.5 PTPN1 positively regulates TNF-α induced MAPK signalling and gene expression in NIT-1 cells and NODPI islets: ...... 96 4.3.6 PTPN1 positively regulates IL-1β induced MAPK signalling and gene expression in NIT-1 cells and NODPI islets: ...... 100 4.4 Discussion: ...... 104 Role of PTPN6 in Regulation of Cytokine Signalling in Pancreatic b-cells 109 5.1 Summary: ...... 110 5.2 Introduction: ...... 111 5.3 Results: ...... 114 5.3.1 Development of PTPN6 deficient NIT-1 cells: ...... 114 5.3.2 PTPN6 inactivation enhances TNF-α induced NIT-1 cell death: ...... 117 5.3.3 PTPN6 does not regulate IFN-γ induced STAT1 signalling in NIT-1 cells: 121 5.3.4 PTPN6 negatively regulates TNF-α induced JNK signalling in NIT-1 cells: 122 5.3.5 PTPN6 positively regulates IL-1β induced MAPK signalling in NIT-1 cells: 123 5.3.6 PTPN6 negatively regulates JNK dependent expression of anti-apoptotic BCL-2 proteins: ...... 125 5.4 Discussion: ...... 129 PTPN6 Negatively Regulates TNF-a Induced RIPK1 Dependent Apoptosis in NIT-1 Cells ...... 133 6.1 Summary: ...... 134 6.2 Introduction: ...... 135 6.3 Results: ...... 137 6.3.1 Pan-caspase and RIPK1 inhibition protects PTPN6 sufficient and deficient NIT-1 cells from TNF-a induced death: ...... 137 6.3.2 P65 overexpression protects NIT-1 cells from RIPK1 dependent apoptosis: 139 6.4 Discussion: ...... 143
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General Discussion ...... 147 7.1 Thesis overview: ...... 148 7.2 Positive cytokine signalling regulated by PTPN1 and potential applications in current T1D therapies: ...... 149 7.3 PTPN6 as a possible target for autoimmune disorders: ...... 154 7.4 Substrate identification of PTPs: ...... 156 7.5 Concluding remarks: ...... 158 References: ...... 159
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List of Figures: Figure 1.1: Type 1 diabetes pathogenesis in the NOD/Lt mouse...... 6 Figure 1.2: IFN-g induced STAT1 signalling in b-cells...... 14 Figure 1.3: TNF-a induced MAPK and NF-kB signalling in b-cells...... 23 Figure 1.4: IL-1b induced MAPK and NF-kB signalling in b-cells...... 25 Figure 1.5: Mechanism of PTP hydrolysis based on murine PTPN1...... 33 Figure 1.6: Mechanism of oxidative inactivation of murine PTPN1...... 36 Figure 1.7: Model of how PTP oxidation affects cytokine signalling in b-cells...... 40 Figure 3.1: Western blot for pancreatic oxidised PTPs in antioxidant treated NOD/Lt mice...... 64 Figure 3.2: Insulitis analysis of 20 week old mito-TEMPO supplemented NOD/Lt mice...... 66 Figure 3.3: Insulitis analysis of 12 week old mito-TEMPO supplemented NOD/Lt mice...... 68 Figure 3.4: T-cell analysis of 12 week old mito-TEMPO supplemented NOD/Lt mice. . 72 Figure 3.5: Diabetes incidence of mito-TEMPO supplemented NOD/Rag1 mice...... 73 Figure 4.1: Expression of PTPN1 in human and murine islets...... 85 Figure 4.2: Western blot for PTPN1 expression in PTPN1 deleted NIT-1 cells...... 86 Figure 4.3: Cytotoxicity analysis of PTPN1 deficient and inhibited NIT-1 cells...... 88 Figure 4.4: Cytokine induced caspase-3 cleavage in PTPN1 deficient NIT-1 cells...... 90 Figure 4.5: IFN-γ induced STAT1 signalling in PTPN1 deficient and inhibited NIT-1 cells and PTPN1 inhibited islets...... 92 Figure 4.6: IFN-γ induced gene expression in PTPN1 inhibited NODPI islets...... 93 Figure 4.7: MHC-I expression and autoimmune destruction analysis of PTPN1 inhibited islets...... 95 Figure 4.8: TNF-α induced MAPK phosphorylation in PTPN1 deficient NIT-1 cells. .... 97 Figure 4.9: TNF-α induced gene expression in PTPN1 inhibited NODPI islets...... 99 Figure 4.10: IL-1β induced MAPK phosphorylation in PTPN1 deficient NIT-1 cells... 101 Figure 4.11: IL-1β induced gene expression in PTPN1 inhibited NODPI islets...... 102 Figure 5.1: Expression of PTPN6 in human and murine islets...... 115 Figure 5.2: PTPN6 expression in PTPN6 deficient NIT-1 cells...... 116 Figure 5.3: PTPN6 inactivation enhances TNF-α induced NIT-1 cell death...... 118 Figure 5.4: PTPN6 deletion enhances TNF-α induced caspase-3 cleavage in NIT-1 cells...... 120 Figure 5.5: PTPN6 does not regulate IFN-γ induced STAT1 signalling in NIT-1 cells. 121 Figure 5.6: PTPN6 negatively regulates TNF-α induced JNK phosphorylation in NIT-1 cells...... 123 Figure 5.7: PTPN6 positively regulates IL-1β induced JNK phosphorylation in NIT-1 cells...... 124 Figure 5.8: PTPN6 negatively regulates TNF-α induced anti-apoptotic BCL-2 protein expression in NIT-1 cells...... 126 Figure 5.9: PTPN6 negatively regulates JNK dependent TNF-α induced MCL-1 protein degradation in NIT-1 cells...... 128 Figure 6.1: Cytotoxicity analysis of NIT-1 cells with caspase and RIPK1 inhibition. ... 138 Figure 6.2: Cytotoxicity analysis of NIT-1 cells with p65 overexpression and RIPK1 inhibition...... 140
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Figure 6.3: Immunoblot analysis of TNF-α induced caspase cleavage of NIT-1 cells with p65 overexpression and RIPK1 inhibition...... 142
List of Tables: Table 2.1: CRISPR/Cas9 deletion strategy of protein tyrosine phosphatases...... 48 Table 2.2: List of antibodies used in immunoblotting...... 50 Table 2.3: List of primers used for real-time PCR...... 51 Table 2.4: List of antibodies used in immunohistochemistry...... 52 Table 2.5: List of antibodies used in MHC-I flow cytometry...... 55 Table 2.6: List of antibodies used in T-cell flow cytometry...... 56
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List of Abbreviations:
AES 2-Aminopropyltriethoxysilane
APAF Apoptotic Protease Activating Factor 1
ApoE Apolipoprotein E
ATP Adenosine Triphosphate
BAD BCL-2-Associated Death Promoter
BAK BCL-2 Homologous Antagonist Killer
BAX BCL-2-Like Protein 4
BCL-2 B-Cell Lymphoma 2
BCL-XL B-Cell Lymphoma-Extra Large
BID BH3 Interacting-Domain Death Agonist
BIM BCL-2 Like Protein 11
CCL C-C Motif Chemokine Ligand cFLIP FLICE-Like Inhibitory Protein cIAP Cellular Inhibitor of Apoptosis
Cr Chromium
CXCL C-X-C Motif Chemokine Ligand
DAB Diaminobenzidine
DAMP Danger Associated Molecular Pattern
DD Death Domain
DEPOD DEPhOsphorylation database
DISPHOS DISorder-enhanced PHOSphorylation predictor
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DNA Deoxyribonucleic Acid
DPX Dibutylphthalate Polystyrene Xylen
EYA Eyes Absent
FADD FAS-Associated DD Protein
GAD Glutamate Decarboxylase
GAS Gamma Activated Site
GPS Group-Based Prediction System
GPx Glutathione Peroxidase gRNA Guide RNA
HLA Human Leukocyte Antigen
I-Eak MHC Class II
ICA512 Islet Cell Antigen 512
ICAM-1 Intracellular Adhesion Molecule 1
IFN Interferon
IFNAR Interferon Alpha and Beta Receptor
IGRP Islet-Specific Glucose 6-Phosphatase Catalytic Subunit-Related Protein
IKK IκB Kinase
IL-1 Interleukin-1
IL-1R Interleukin-1 Receptor
IL-1RAP IL-1 Receptor Accessory Protein
IL-2rg Interleukin 2 Receptor Subunit Gamma iNOS Inducible Nitrous Oxide Synthase
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IRAK IL-1 Receptor Associated Kinase
JAK Janus Kinase
JNK c-Jun N-Terminal Kinase
LCK Lymphocyte-Specific Protein Tyrosine Kinase
LMPTP Low Molecular Weight PTP
LUBAC Linear Ubiquitination Assembly Complex
MAPK Mitogen Activated Protein Kinase
MCL-1 Myeloid Leukaemia Cell Differentiation Protein
MFI Mean Fluorescent Intensity
MHC Major Histocompatibility Complex
MLDS Multiple Low Doses of Streptozotocin
MLKL Mixed Lineage Kinase Domain Like Pseudokinase
MPTP Mitochondrial Permeability Transition Pore
MyD88 Myeloid Differentiation Primary Response 88
NAC N-Acetyl Cysteine
NADPH Nicotinamide Adenine Dinucleotide Phosphate
NCCD Nomenclature Committee on Cell Death
NEMO NFκB Essential Modulator
NF-kB Nuclear Factor-κB
NFAT Nuclear Factor of Activated T-Cells
NOD/Lt Non-Obese Diabetic/Lt Mouse
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NOX NADPH Oxidase
OCT Optimal Cutting Temperature Compound
OH Hydroxyl
PDX-1 Pancreatic and Duodenal Homeobox 1
PK Protein Kinase
PTK Protein Tyrosine Kinase
PTP Protein Tyrosine Phosphatase
PUMA p53 Upregulated Modulator of Apoptosis
Rag1 Recombination-Activating Genes 1
RIPA Radio Immunoprecipitation Assay
RIPK Receptor Interacting Protein
RNA Ribonucleic Acid
SNP Single Nucleotide Polymorphism
SOCS Suppressor of Cytokine Signalling
SOD Superoxide Dismutase
SS-31 Szeto-Schiller-31
STAT Single Transducer and Activator of Transcription sTNFR1 Soluble TNFR
STZ Streptozotocin
T1D Type 1 Diabetes
TAB TAK1-Binding Protein
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TAK Transforming Growth Factor β Activated Kinase
TCR T-cell Receptor
TNF Tumour Necrosis Factor
TNFR Tumour Necrosis Factor Receptor
TRADD TNFR-Associated DD Protein
TRAF TNFR-Associated Factor
TRAIL TNF-Related Apoptosis-Inducing Ligand
TXNIP Thioredoxin-Interacting Protein
TYK Tyrosine Kinase
WPD Tryptophan-Proline-Aspartic Acid
ZAP-70 Zeta-Chain-Associated Protein Kinase 70
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Literature Review
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Chapter 1: Literature Review
1.1 Literature review methodology:
The literature obtained for this review was sourced from the Pubmed database using journal access available through The University of Melbourne’s library resources in August 2018 before the original submission and December 2019 before resubmission. The following key word search terms were used in various Boolean ‘AND’ combinations:
§ Autoimmune diabetes or type 1 diabetes or T1D.
§ Beta cell or insulin producing cell or insulin producing beta cell.
§ Interferon gamma or IFN gamma or type 2 interferon.
§ Tumour necrosis factor alpha or TNF alpha.
§ Interleukin-1 beta or IL-1 beta.
§ Signal transducer and activator of transcription or STAT1
§ Mitogen activated protein kinase or MAPK or c-Jun N-terminal kinase or JNK or
c-Jun or p38 or nuclear factor kappa B or NF-kB.
§ Inducible nitric oxide synthase or iNOS or nitric oxide or NO or reactive oxygen
species or ROS or free oxygen radicals or oxidative stress.
§ Cell death or apoptosis or extrinsic apoptosis or intrinsic apoptosis or necroptosis.
§ Protein tyrosine phosphatase or PTP or PTPN1 or PTP1B or PTPN6 or SHP-1.
Studies that were excluded:
§ Studies in languages other than English.
Additional articles were identified through hand-searching of reference lists of relevant retrieved articles.
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Chapter 1: Literature Review
1.2 Type 1 diabetes overview:
Type 1 diabetes (T1D) is an islet specific autoimmune disease characterised by T-cell dependent destruction of insulin-producing β-cells of the pancreas. As β-cells are progressively destroyed by immune cells, patients lose the ability to release sufficient insulin from their remaining islet mass to lower blood sugar levels in response to increased blood glucose levels. This results in hyperglycaemia, which leads to a myriad of metabolic complications that are deadly if left untreated. Patients rely on constant glucose monitoring and multiple daily insulin injections or insulin pumps to manage blood sugar levels after meals to maintain glucose homeostasis.
Epidemiological studies reveal that incidence of disease has been increasing from
2% to 5% worldwide [1]. Around 140,000 Australians currently have T1D, with 6 new cases diagnosed each day. Genome wide association studies have revealed various single nucleotide polymorphisms (SNPs) that correlate with T1D [2, 3]. The most frequent of these low risk associations include human leukocyte antigen (HLA) complexes [4, 5], insulin [6], as well as smaller contributions from the protein tyrosine phosphatases PTPN22 and PTPN2 [7]. HLA molecules are the highest risk factor for T1D, indeed 90-95% of children with the disease carry the risk allele for this gene. However, only 5% of people that possess these susceptibility alleles develop disease, highlighting the low risk factor of these high frequency SNP associations. Currently the best clinical indicator for the progression to T1D is the presence of circulating islet autoantibodies. The presence of two or more of autoantibodies for insulin, glutamate decarboxylase (GAD) or islet cell antigen
512 (ICA512) confers ~70% progression to developing diabetes over 5 years in first degree relatives of individuals with T1D [8, 9].
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Chapter 1: Literature Review
Currently, the most feasible approaches to prevent or cure T1D consist of deleting or tolerising against the population of autoreactive immune cells and preserving, replacing or regenerating the remaining β-cell mass of the patient. These approaches have been widely studied in vitro and in mouse models of autoimmune diabetes, such as the NOD/Lt mouse.
1.2.1 Human islet immunopathology in type 1 diabetes:
While the genetic, epidemiological and peripheral immunity of T1D mentioned above have been studied for decades, studies of the pathology in the human pancreas are limited. These can be attributed to gaining research quality tissues because of difficulty in the access of pancreatic samples from the early stages of the disease and biopsies cannot be safely harvested without great risk of pancreatitis to the patient. However, multiple studies have demonstrated infiltration of immune cells into islets (insulitis) within pancreata collected from deceased T1D patients. Among these samples various immune cells could be detected using immunohistochemical approaches, including T & B lymphocytes, macrophages and dendritic cells [10-19]. Insulitis among these samples also varies in location and severity in the pancreas itself highlighting heterogeneity between patients. Immune cells can be located within islets and surrounding the islets with minimal to large amounts of cells infiltrated, and mainly in islets with residual β-cell populations [20]. Insulitis and β-cell destruction in humans takes place over years and continues after disease diagnosis. Indeed, insulin positive β-cells can be identified in human samples as late as 50 years after diagnosis [21, 22]. Currently most understanding of the pancreatic immunopathology stems from in vitro and in vivo models of the disease including cytotoxic studies of
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Chapter 1: Literature Review immortalised β-cells and murine models such as the NOD/Lt mouse which spontaneously develops autoimmune diabetes.
1.3 Mouse models of type 1 diabetes:
1.3.1 The Non-Obese Diabetic (NOD)/Lt mouse:
NOD/Lt mice develop a spontaneous and progressive autoimmune phenotype, presenting with insulitis and diabetes development similar to that of human T1D which will be termed
‘autoimmune diabetes’ in this study [23]. There is a gender difference in diabetes development in the NOD/Lt mouse where ~70% of female mice develop the disease, whereas ~40% of males develop disease in clean facility conditions with an appropriate diet. NOD/Lt mice develop immune infiltration in their islets from 4 weeks of age and generally become diabetic starting at around 12 weeks of age [24, 25]. Because of the similarities with human T1D, such as genetic association, autoantibody development and involvement of cytotoxic lymphocytes, NOD/Lt mice still remain one of the most useful and beneficial tools for researchers to study the autoimmune pathology.
A wide variety of genetically modified derivatives of NOD/Lt mice have been developed in an effort to further understand the islet pathology and immunological events that result in β-cell destruction. The mechanism of β-cell death in the NOD/Lt mouse occurs primarily by autoreactive CD8+ T-cell dependent destruction against insulin autoantigens [26-29] (Fig. 1.1). Lymphocytes and leukocytes, primarily macrophages and
CD4+ T-cells, present in NOD/Lt mouse insulitis also release various proinflammatory cytokines (including the interferon (IFN), tumour necrosis factor (TNF) and interleukin-1
(IL-1) families) that have been shown to be directly cytotoxic to isolated islets in vitro
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Chapter 1: Literature Review when stimulated in combinations, but with little effect when treated alone [30]. The effects of these cytokines in vivo are more complex and pleiotropic due to the presence of multiple bystander and immune cell subsets which release other signalling molecules that further complicate the inflammatory signalling events.
Figure 1.1: Type 1 diabetes pathogenesis in the NOD/Lt mouse.
Illustration outlining the basic model of T1D development based on NOD/Lt mouse studies. During the initiation of autoimmune diabetes genetic predisposition leads to the activation of innate immune cells, such as tissue resident macrophage, which recruit adaptive immune cells to the pancreas through the release of cytokines and chemokines.
Autoreactive T-cells then progressively deplete b-cell mass through direct interaction with
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Chapter 1: Literature Review antigen presenting molecules and further release cytokines which results in b-cell stress responses, including the release of chemokines and translation of pro-apoptotic factors, which result in a feed forward cycle of b-cell depletion. The loss of residual b-cell mass eventually results in insufficient insulin production and resultant hyperglycaemia and diabetes development.
While the NOD/Lt mouse model has provided substantial understanding of human islet autoimmunity, it is important to consider the differences between resultant autoimmune diabetes and clinical T1D. NOD/Lt mice were developed through inbreeding strategies thus represent a single genotype of the disease, whereas clinical disease presents with great genetic and morphological heterogeneity between separate patients [31, 32].
This is apparent in clinical samples taken from patients which show comparatively mild infiltration in select lobular areas of the pancreas, whereas NOD/Lt mice present typically with large amounts of uniform insulitis over whole pancreas sections [33, 34]. There is also a strong gender bias towards female mice developing diabetes in comparison to male mice
[35]. Several therapeutic approaches that have been successful in reducing or preventing diabetes in NOD/Lt mouse studies have also not translated into clinical trials. Current human models of the disease are sparse and access to clinical samples are difficult to acquire, limiting the ability to study immunological events in relevant human tissues. The
NOD/Lt and other mouse models also allow us to perform transgenic studies that manipulate important proteins and genes relevant to the disease that are not possible in humans. Nonetheless, the NOD/Lt mouse and decade’s worth of experimental evidence it
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Chapter 1: Literature Review has provided researchers will continue to be invaluable for our understanding of the disease.
1.3.2 Multiple low doses of streptozotocin model:
In addition to the NOD/Lt model and its genetic derivatives, other models of autoimmune diabetes have been studied in the pathogenesis of the disease. The induction of diabetes by injection of multiple low doses of the b-cell toxin streptozotocin (MLDS model) into mice on a C57BL/6 background has been used in particular to demonstrate a role for cytokines in acute b-cell destruction [36-38]. MLDS into rodents induces many histological and clinical features that are similar to that observed in human T1D such as immune cell infiltration and islet demise. Cytokine levels of the IFN, TNF and IL-1 families are also enhanced in pancreatic tissue extracts from mice treated with MLDS [39]. Oral treatment with thalidomide, an anti-inflammatory agent, into MLDS treated mice was shown to reduce pancreatic levels of these cytokines as well as reducing hyperglycaemia in mice further highlighting a role of these inflammatory molecules in disease progression [36].
While the MLDS model does induce expression of GAD autoantigen epitopes through generation of hydrogen peroxide [40], which are antigens also found in T1D patients, this model lacks background genetic association and spontaneous autoimmune development without the toxin stimulation. Thus the MLDS model does not truly replicate a pathogenic equivalent to human T1D, but does offer researchers the opportunity to study the effects of pharmaceutical compounds in synchronized groups of mice in short term studies (20-30 days).
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1.4 Cytokine signalling in type 1 diabetes:
As mentioned above, the NOD/Lt and MLDS autoimmune diabetic models have highlighted that cytokines from the IFN, TNF and IL-1 families are released during insulitis and are directly cytotoxic to isolated islets and b-cell lines in vitro when treated in combination with each other. Decades of research have shown that IFN-g, TNF-a and IL-
1b induce inflammatory signalling cascades in b-cells which impairs their function and sensitizes cells to death in vitro [41-43], although some findings have also highlighted protective effects from various signalling nodes in these pathways [44]. In vivo studies have also revealed the importance of components of these cytokine induced signalling pathways in the development of autoimmune diabetes. The IFN-g, TNF-a and IL-1b signalling pathways and their activity in b-cells are a main component of this study and will be discussed below.
1.4.1 Interferon signalling overview:
IFNs activate the Janus kinase/signal transducer and activator of transcription (JAK/STAT) signalling pathway through numerous tyrosine phosphorylation cascades triggered by receptor ligation [45]. IFN receptors are transmembrane receptors that lie as latent monomers in the cell membrane with a JAK associated to their intracellular face. Receptor activation occurs by ligand-mediated dimerisation, which triggers JAK autophosphorylation and JAK dependent phosphorylation of receptor tyrosine residues
[46]. These phosphotyrosyl residues act as SH2-domain dependent docking sites for STAT proteins [47]. Upon binding to the receptor, STAT proteins are phosphorylated by JAKs
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Chapter 1: Literature Review on a conserved tyrosine residue (~700), which causes their release and dimerisation with other phosphorylated STAT proteins [48]. Dimerised STAT proteins are imported to the nucleus where they bind to specific DNA elements, resulting in transcription of various target gene sets [47, 49]. Of these, suppressor of cytokine signalling (SOCS) proteins are upregulated, which then act as a negative feedback loop by inhibiting activity of JAK proteins, limiting signal activation [50, 51]. Protein tyrosine phosphatases (PTPs) also act as negative regulators of the pathway by inhibiting both JAK and STAT proteins [52-55]
(Fig. 1.2).
There are three types of IFN groups (type I, II and III) in the family and each alters downstream gene expression profiles through differential activation of the STAT protein families. Type-I IFNs include IFN-a and IFN-b which activate heterodimers and homodimers of STAT1/2/3 through JAK1 and tyrosine kinase 2 (Tyk2) dependent phosphorylation and act as important mediators of antiviral protection and innate immune responses [56-58]. IFN-γ is the sole member of the type-II IFN family and is generated by activated lymphocytes and natural killer cells [59]. IFN-γ predominately activates STAT1 homodimers by JAK1/2 dependent phosphorylation and stimulates cell-mediated immune responses for host protection against intracellular microorganisms [60-63] (Fig. 1.2). Type-
III IFNs are the most recent addition to the family and include IFN-l, which activates
STAT1/2 through JAK1/Tyk2 associated to a distinct heterodynamic receptor complex
[64, 65]. Type-III IFNs, similar to type-I IFNs, are involved in antiviral responses and induce a similar gene signature [66, 67]. The IFN-γ/STAT1 signalling cascade and its involvement in T1D and autoimmune diabetes will be critically discussed below.
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1.4.2 IFN-g signalling in b-cells sensitises to autoimmune destruction in the NOD/Lt
mouse:
Autoreactive CD8+ T-cells interact with HLA-I expressing β-cells in human T1D, contributing to β-cell demise [68-70]. HLA-I and the β2-microglobulin component of the
HLA complex are enhanced on human insulin positive β-cells in T1D pancreatic biopsy samples which correlates with the presence of activated STAT1 [71]. IFN-γ strongly induces STAT1 phosphorylation resulting in major histocompatibility complex-I (MHC-I, the mouse equivalent of HLA-I) expression on mouse β-cells as well as transcription of various downstream proapoptotic and proinflammatory molecules such as BH3-only proteins and chemoattractive proteins [21, 72, 73].
In vitro treatment of β-cell lines and isolated islets with IFN-g strongly induces
STAT1 phosphorylation over an extended kinetic period of time. β-cell lines have also revealed that IFN-g stimulation induces the expression of various chemoattractive proteins such as C-X-C motif chemokine ligand 9 (CXCL9), CXCL10, inducible nitic oxide synthase (iNOS) and MHC-I, all considered important in the pathology of T1D [53-55, 74,
75]. In vitro studies of TNF-a and IL-b signalling have also revealed that these cytokines alter the expression of numerous inflammatory transcripts associated with immune cell infiltration [76-81]. For example, TNF-a and IL-b induce transcription of various chemokines associated with the recruitment of immune cells to the islet including CXCL1,
C-C motif chemokine ligand 2 (CCL2), CCL5 and CCL20 and elevated levels of these chemokines have been recorded in the serum of patients with T1D [72, 82-84]. Similar to
IFN-g, excessive production and release of chemokines from b-cells is suggested to be a mechanism by which b-cells themselves promote further predisposition to diabetes by
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Chapter 1: Literature Review recruiting autoimmune cells to the islet, leading to further cell death. Indeed, some chemokines, such as CXCL10 (induced by IFN-g), are of interest as therapeutic targets for
T1D [85].
To further elucidate the role of IFN-γ in the development of autoimmune diabetes,
NOD/Lt mice were generated with deficiency of IFN-γ or its receptors, however they were not protected from development of insulitis and diabetes [86-89]. In contrast, NOD/Lt mice deficient in the STAT1 transcription factor were completely protected from development of diabetes and insulitis [90]. Overexpression of the potent IFN signalling inhibitor SOCS1 in β-cells resulted in significant protection from diabetes in the NOD/Lt model [91, 92], and complete protection in NOD8.3 mice [92, 93], which models CD8+ T-cell dependent induced diabetes. Similarly, STAT1-deficiency prevented b-cell destruction in the MLDS model [94]. These models suggest that STAT1 phosphorylation and signal transduction in
β-cells is important for T-cell dependent destruction and diabetes development in mice, however, is not induced solely by IFN-g (reviewed in [74]).
Type-I IFNs also induce STAT1 phosphorylation, which could explain why targeting IFN-γ alone is ineffective at preventing diabetes development. Deficiency of the interferon alpha and beta receptor subunit 1 (IFNAR1) alone does not protect from diabetes in NOD/Lt mice [95], suggesting there may be redundancy of these two families of interferons in STAT1 inactivation. SOCS1 overexpression inhibits both type-I and type-II
IFN signalling which supports this concept as both axes of STAT1 activation would be inhibited in this model. CD8+ T-cell dependent destruction of β-cells in the NOD/Lt mouse model requires STAT1 dependent upregulation of MHC-I on β-cells. Inhibition of MHC-I upregulation through the use of JAK inhibitors, blocking downstream STAT1 activation,
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Chapter 1: Literature Review has been shown to protect NOD/Lt mice against diabetes development and β-cell destruction which further supports that STAT1 inactivation in β-cells protects from T1D features [96].
Even though CD8+ T-cells are suggested to be the main cellular mediators of β-cell destruction, CD4+ T-cells also contribute to diabetes development through the expression and release of various cytokines (including IFN-g, TNF-a and IL-1b) and costimulatory factors [97]. The BDC2.5 transgenic mouse is useful for studying these cells as diabetogenic BDC2.5 CD4+ T-cells efficiently transfer diabetes to immunodeficient
NOD.SCID mice [98]. Interestingly, diabetes development is markedly reduced after transfer of BDC2.5 T-cells into irradiated STAT1 deficient or IFNgR-deficient hosts on the
NOD/Lt background [90, 99]. Contrary to this observation, overexpression of SOCS1 in b-cells of NOD4.1 mice, another model of CD4+ T-cell dependent diabetes, does not protect from insulitis or diabetes development, which suggests that cytokines that are regulated by SOCS1 in β-cells are redundant in CD4+ T-cell dependent diabetes [97]. The discrepancy between these two models of cytokine induced diabetes, in particular the IFN- g and STAT1 axis, shows that CD4+ T-cell mediated b-cell destruction remains unclear and requires further studies.
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Autoimmune Infiltration
Figure 1.2: IFN-g induced STAT1 signalling in b-cells.
Illustration outlining IFN-g induced STAT1 signalling and downstream translation in b- cells resulting in b-cell death. IFN-g release by immune cells leads to the activation of the
STAT1 transcription factor which leads to the production of chemokines, which recruit circulating autoreactive lymphocytes, and antigen presenting MHC-1 as well as iNOS.
CD8+ T-cell interaction and the pro-apoptotic effects of NO production lead to b-cell apoptosis and decreased b-cell mass.
Collectively these results show that IFN-g induced STAT1 signalling in b-cells is important in increasing visibility of these cells to autoreactive immune cells, resulting in destruction. IFN-g in combination with TNF-a and IL-1b also impairs b-cell function and triggers apoptotic cell death in vitro through activation of various signalling nodes [43, 74].
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Apoptotic cell death mechanisms, TNF-a and IL-1b signalling and their effects on b-cell destruction will be discussed below.
1.4.3 Cell death overview:
The life and development of an organism requires the process of programmed cell death for clearance of damaged, degenerate or infected cell populations. Approximately 1010 cells undergo programmed cell death every day in humans to maintain physiological tissue homeostasis [100]. Imbalance in cell death and proliferation, which can be the result of the loss of cell signalling regulation (such as protein hyperphosphorylation), can trigger tissue pathology. Resistance to undergo cell death can result in tumour development whereas enhanced cell death can result in impaired organ function for instance.
The mechanism of cell death and rapid clearance of remaining debris is important to protect the host from unwanted immune responses as well as alerting the immune system to internalised pathogens, such as viruses. Typically, cells die from a programmed form of suicide termed apoptosis and quickly undergo clearance by phagocytes. Once engulfed, phagocytes digest the leftover cell debris and present antigens to immune cells to alert of infection. Cells can also undergo a chaotic form of cell death called necrosis when exposed to extreme environmental conditions or adverse stimuli. Unlike apoptosis, necrosis is a passive process requiring no homeostatic mechanisms. Recently however, multiple lines of evidence have highlighted a novel programmed form of necrosis called necroptosis which can be activated by specific cytokines under certain conditions.
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1.4.4 Apoptosis:
Apoptosis (from the Greek meaning ‘falling off’ [101]) is the main physiological form of cell death where cells undergo genetically programmed ‘suicide’ when they are superfluous to tissue homeostasis (reviewed in [102]). Apoptosis results in nuclear condensation
(pyknosis) and partitioning of cellular components into membrane bound vesicles termed apoptotic bodies. These bodies are then rapidly engulfed by phagocytes (such as tissue specific macrophages) by the process of efferocytosis [103]. Apoptosis and rapid efferocytosis serve to protect the host from unwanted immune responses against dying cells as danger associated molecular patterns (DAMPs) remain enclosed inside the apoptotic bodies and are not released into the extracellular matrix. DAMPs, such as ATP, DNA and
RNA are released from cells upon extracellular membrane disruption and trigger an innate inflammatory response [104, 105], which is why rapid efferocytosis is pivotal to the process of apoptosis. DAMP release typically occurs with tissue trauma or lytic infections by necrosis which leads to a desirable innate immune response to trigger tissue healing
[105]. DAMPs can also be released when apoptotic bodies are not cleared by phagocytosis, leading to secondary necrosis of the apoptotic bodies [106]. Apoptosis can be triggered by two different pathways; the intrinsic mitochondrial pathway or the extrinsic death receptor pathway which both culminate in the activation of effector caspases.
1.4.5 Caspases:
Apoptosis is regulated by a family of cysteine proteases called caspases [107]. There are three broad groups of caspases; initiator caspases, executioner caspases and inflammatory caspases (not reviewed here). Initiator caspases (caspase-2, 8 and 9) serve as upstream
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“sensors” of apoptotic signalling and upon certain cytotoxic stimulation they form dimers which activates them by proximal autocatalytic cleavage [108, 109]. Activated initiator caspases cleave cysteine residues on numerous substrates, including those of executioner caspases. Executioner caspase (caspase-3, 6 and 7) cleavage induces a conformational change allowing them to form dimers and become active proteases leading to further caspase cleavage in a feedforward progression to apoptosis.
1.4.6 The intrinsic apoptotic pathway:
The intrinsic mitochondrial apoptotic pathway is the most common form of apoptosis induction as it is activated by numerous metabolic and genetic stress responses in the cell
[102]. Metabolic signalling includes extracellular signalling (cytokines & hormones) and stress responses (ATP production, hypoxia and endoplasmic reticulum stress) [110], whereas genetic stress typically involves DNA damage [111]. These responses alter the levels of B-cell lymphoma 2 (BCL-2) family proteins which are ultimately responsible for the activation of the intrinsic apoptotic pathway. The BCL-2 proteins are divided into two groups; pro-apoptotic and anti-apoptotic (reviewed in [112]). Pro-apoptotic proteins contain the sensitizing BH3-only pro-apoptotic proteins (BCL-2 like protein 11 (BIM), p53 upregulated modulator of apoptosis (PUMA), BH3 interacting-domain death agonist (BID) and BCL-2-associated death promoter (BAD)) and the multidomain pro-apoptotic proteins
(BCL-2-like protein 4 (BAX) & BCL-2 homologous antagonist killer (BAK)). The anti- apoptotic BCL-2 proteins (BCL-2, induced myeloid leukaemia cell differentiation protein
(MCL-1) and B-cell lymphoma-extra-large (BCL-XL)) bind to pro-apoptotic proteins, preferentially BH3-only proteins, to inactivate their activity [113, 114]. Upon stress
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Chapter 1: Literature Review induction BH3-only pro-apoptotic protein expression is typically induced whereas BCL-2 anti-apoptotic protein expression is decreased, possibly by proteasomal degradation. This ultimately leads to the release of BAX and BAK into the cytosol where they translocate to the mitochondria and form the mitochondrial permeability transition pore (MPTP) in the outer membrane [114]. MPTP formation releases mitochondrial cytochrome-c from the intermembrane space into the cytosol where it forms the apoptosome in complex with apoptotic protease activating factor 1 (APAF1) and caspase-9 [115]. This leads to the activation of caspase-9 and then downstream activation of caspase-3 and caspase-7, triggering apoptosis.
1.4.7 The extrinsic apoptotic pathway:
The extrinsic apoptotic pathway is triggered through activation of death receptors by ligation of cytokines including TNF-a, FAS and TNF-related apoptosis-inducing ligand
(TRAIL) [102]. Upon ligation, the cytoplasmic death domains of the receptor complex associates with the adaptor proteins TRADD or FADD [116]. TRADD and FADD then interact with procaspase-8 in the death-inducing signalling complex (DISC) which activates caspase-8 and downstream caspase-3 and caspase-7, triggering apoptosis [117].
Caspase-8 activity can also activate the intrinsic apoptotic pathway through cleavage and activation of the BH3-only apoptotic protein BID, thus potentiating apoptosis induction
[118, 119] (Fig. 1.3).
The extrinsic apoptotic pathway is tightly regulated by various pro-survival signals and checkpoints to prevent unnecessary apoptotic induction. These include various adaptor protein posttranslational modifications on the intracellular DISC as well as induction of the
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NF-kB pathway leading to anti-apoptotic protein translation [120]. Indeed, inactivation of various components of the extrinsic apoptotic pathway can activate different apoptotic pathways. Currently the TNF-a signalling pathway acts as the model of extrinsic apoptosis regulation and these signalling/regulation events are reviewed in the TNF-a (Sec. 1.4.9. &
1.4.10.).
1.4.8 Necroptosis:
In contrast to apoptosis, necrosis is an uncontrolled process of cell death which involves the loss of membrane integrity and release of the cellular contents in to the local microenvironment triggering inflammation after intense tissue injury [121]. Necrosis shares no similar morphological or molecular features to apoptosis but instead results in cellular swelling and DNA decondensation.
Necroptosis is a novel form of necrosis which is suggested to be the consequence of deregulated activity of specific cytokine signalling cascades, such as the TNF-a axis
[122-124]. Necroptosis relies on phosphorylation of the mixed lineage kinase domain like pseudokinase (MLKL) by functional receptor interacting protein kinase 3 (RIPK3) which leads to the oligomerisation of MLKL and translocation to the cell membrane which leads to membrane permebalisation and necrosis [125] (Fig. 1.3). The execution of the pathway still remains obscure due to the novel nature of the cell death mechanism, however it is known that RIPK1, RIPK3 and MLKL must be expressed in the cell to undergo necroptosis. In the context of TNF-a, RIPK1 has the ability to activate RIPK3 and MLKL when apoptosis is inhibited, such as with caspase inhibition [126]. Indeed RIPK3 deficient
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Chapter 1: Literature Review cells are protected from TNF-a induced cell death when caspases are inhibited, attributed to blockaded of necroptosis induction [127].
1.4.9 Canonical TNF-a signalling overview:
TNF-a expression and signalling is strongly linked to inflammatory diseases and cell death activation due to pro-apoptotic adaptor proteins in its receptor complex, however signal transduction is highly complicated and currently not fully understood [128-131]. TNF-a binds with latent tumour necrosis factor receptor 1 (TNFR1) and TNFR2 resulting in receptor trimerization and recruitment of the cytoplasmic death domain (DD) containing protein TNFR-associated DD protein (TRADD) which then begins to assemble the canonical signalling complex termed ‘complex I’ [132, 133]. TRADD then initiates intracellular signalling by recruiting receptor interacting protein kinase-1 (RIPK1), TNFR- associated factor-2 (TRAF2), cellular inhibitors of apoptosis-1/2 (cIAP1/2) and linear ubiquitin chain assembly complex (LUBAC) which acts as an E3 ubiquitin ligase, as well as FAS-associated death domain protein (FADD) [134, 135] (Fig. 1.3).
In a canonical TNF-a response, assembly of complex I leads to an active mitogen activated protein kinase (MAPK) and nuclear factor kappa B (NFkB) response [136, 137].
TNF-a induced MAPKs, such as c-Jun N-terminal kinase (JNK) and p38 [138], are tyrosine and threonine activated kinases which have numerous effects on the cell from pro- apoptotic protein expression to mitogenesis depending on the receptor ligand and physiological signalling condition. MAPKs are activated in a phosphorylation cascade by
MAPKKs and MAPKKKs, which activate each other in turn [139]. Upstream MAPKKs and MAPKKKs are activated by serine and threonine phosphorylation. TNF-a activates
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MAPKKKs through association of inactive MAPKKKs to TRAF2 in complex I leading to the induction of the phosphorylation cascade [140, 141].
The NFkB transcription factor is also canonically activated by the formation of complex I. Recruited ubiquitin ligases to complex I polyubiquitinate RIPK1 resulting in binding sites for TAK1-binding protein 2/3 (TAB2/3) and NFkB essential modulator
(NEMO) which allows recruitment and activation of transforming growth factor β- activated kinase 1 (TAK1) and IkB kinase a/b (IKKa/b) [142]. The activated IKK complex rapidly phosphorylates IkBa leading to its ubiquitylation-dependent proteasomal degradation [143], releasing active NFkB for nuclear translocation and multiple gene transcriptional responses, including many genes that are associated with cell death, including iNOS as well as pro-survival genes such as FLICE-like inhibitory protein
(cFLIP), highlighting it’s duality in modulating death responses [144-147]. cFLIP is a pro- survival protein due to its ability to bind and inactivate caspase-8, an initiator of apoptosis
[44]. Caspase-8 associates with FADD in complex I and has the ability to induce apoptosis when signalling components or posttranslational modifications of complex I are defective or inactive [148].
1.4.10 Non-canonical TNF-a signalling overview:
Pathological effects of TNF-a, such as cell death induction, occur when regulatory components of complex I are defective. Currently the most described non-canonical signalling pathway of TNF-a is receptor internalisation and induction of apoptosis through caspase-8 in a secondary complex termed complex IIa [149, 150]. Complex IIa is comprised of TRADD-FADD-caspase-8 and is internalised to the cytoplasm or lipid rafts
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Chapter 1: Literature Review of the cell where induction of apoptosis depends on levels of cFLIP [148]. If NFkB expression or induction is compromised, the levels of caspase-8 in complex IIa outweigh the anti-apoptotic potential of cFLIP leading to cell death induction.
In the past decade other non-canonical signalling events have begun to emerge from variants of complex I and remain contentious. These events reside in regulatory signalling events of complex I and posttranslational modifications upstream of NFkB induction.
Indeed inhibiting cIAPs, TAK1 and NEMO sensitize cells to death through RIPK1- dependent cell death [151, 152]. Cell death induction through these modifications have been suggested to be by promoting RIPK1-FADD-caspase-8 internalisation and apoptosis induction (complex IIb) or by necroptosis, facilitated by RIPK3 and MLKL [153, 154].
Recently the phosphorylation state of RIPK1 by IKKs has been shown to be a pivotal signalling node in these death responses, where serine hypophosphorylation of RIPK1 by
IKKa/b leads to either apoptosis or necroptosis induction [152, 155].
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Figure 1.3: TNF-a induced MAPK and NF-kB signalling in b-cells.
Illustration outlining TNF-a induced MAPK and NF-kB signalling in b-cells resulting in apoptotic and necroptotic cell death. TNF-a ligation results in the recruitment of complex
I which activates downstream MAPK and NFkB signalling, and when unregulated can result in apoptosis or necroptosis induction through RIPK3 activation.
1.4.11 IL-1β signalling overview:
IL-1β belongs to the IL-1 family which contains 11 members and are primarily involved in innate immune responses against exogenous pathogens. Typically IL-1β induces the expression of adhesion factors on endothelial cells to promote immune cell migration to
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Chapter 1: Literature Review infection sites [156, 157], however increased expression and secretion of IL-1β is associated with autoimmune diseases such as rheumatoid arthritis and T1D [158-160]. IL-
1β binds to IL-1R1 and IL-1 receptor accessory protein (IL-1RAP) which binds myeloid differentiation primary response 88 (MyD88) which then phosphorylates IL-1 receptor- associated kinase 1/2/4 (IRAK1/2/4) [161, 162]. Phosphorylation of IRAK1/2/4 then recruits and oligomerises TRAF6, where TRAF6-IRAK1/2 then migrate to the membrane to associate with TAK1 and TAB1/2 [163, 164]. This complex then migrates back to the cytosol where TAK1 is phosphorylated and activated which leads to IKK, MAPKKK and
MAPKK phosphorylation and activation, which results in NFkB and MAPK (JNK & p38) activation, respectively (Fig. 1.4). IL-1β signalling results in similar downstream gene profiles as TNF-a as they both result in the activation of NF-kB, JNK and p38 [165], however the IL-1β complex lacks the pro-apoptotic properties present in the TNF-a complex resulting in a much simpler signalling cascade. As TNF-a and IL-1β induce similar signalling cascades in β-cells their effects on signalling will be reviewed together.
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Figure 1.4: IL-1b induced MAPK and NF-kB signalling in b-cells.
Illustration outlining IL-1b induced MAPK and NF-kB signalling in b-cells. Ligation of
IL-1b results in the release of the TAK1/IRAK1 signalling complex into the cytoplasm which activates MAPK and NF-kB signalling cascades.
1.4.12 IFN-g, TNF-a and IL-b induced b-cell dysfunction and apoptosis:
As mentioned above TNF-a and IL-1b signalling is associated with the activation of cell death, predominantly by apoptotic measures [43, 80]. Indeed treatment of isolated rodent or purified human b-cells with TNF-a or IL-1b alone does not trigger apoptosis, but when stimulated with IFN-g around 50% of these cells undergo apoptosis suggesting these
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Chapter 1: Literature Review cytokines work synergistically to trigger cell death [166-173]. However, many studies fail to demonstrate the individual effects of these cytokines from IFN-g and a majority of studies focus on the effects of IL-1b signalling and not TNF-α in b-cell dysfunction. Thus the individual effects of TNF-α and IL-1b on β-cells still remain inconclusive but important signalling pathway nodes have been highlighted.
b-cells are inherently more susceptible to IL-1b signalling, b-cell dysfunction and downstream apoptosis induction as they express a higher density of IL-1 receptors than cells in other tissues [174]. Exposure of b-cells to IL-1b with or without IFN-g in vitro results in elevated cytosolic insulin and proinsulin and loss of insulin secretion in response to glucose due to decreased fusion of insulin granules to the b-cell membrane, resembling dysfunction similar to clinical disease [175-177]. These effects are suggested to be the result of IL-1b’s role in regulating phospholipidase D, protein kinase C and pancreas/duodenum homeobox protein 1 (PDX-1) signalling, which has a central role in b-cell development and insulin secretion. TNF-a has been shown to impair the secretion of insulin from b-cells without affecting glucose metabolism, possibly through enhanced lipotoxicity attributed to the ATP-binding cassette transporter A1 [178].
TNF-a and IL-b signalling results in the activation of the NF-kB transcription factor in b-cells which is strongly associated with b-cell dysfunction and death. Indeed, blockade of IL-b induced NF-kB signalling through an inhibitory IkB repressor protects b-cells from death [179, 180]. Using the same NF-kB repressor a microarray analysis revealed 66 genes that are suggested to be responsible for the resultant protective effect, including ER stress response genes and those involved in b-cell development and insulin production such as
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PDX-1 and insulin-1 [181]. NF-kB activates iNOS which is one of the strongest induced products of TNF-a and IL-b signalling and leads to the production of NO and free oxygen radicals in the cell [80, 81]. IFN-g induced STAT1 activation also induces iNOS expression and potentiates its expression when co-treated with IL-1b [182]. Transgenic overexpression of iNOS under the rat insulin promoter results in NO dependent diabetes and MLDS induced diabetes incidence is decreased in mice deficient for iNOS [183, 184].
b-cells are inherently sensitive to the effects of NO and other free oxygen radicals, such as ROS, as they express low levels of antioxidants including glutathione peroxidase
(GPx) which are responsible for the breakdown of these molecules [185, 186]. NO and
ROS also have a complex interplay with each other and can form peroxynitrite which reduces the abundance of the more toxic NO species and has been shown to preserve b- cell function [187]. Over accumulation of NO leads to decreased insulin gene expression and secretion, predisposing to hyperglycaemic conditions, and can lead to direct b-cell dysfunction by various mechanisms such as DNA and mitochondria damage which are required for physiological cell function. Indeed, islets from mice that express a dominant- negative IFN-g receptor are resistant to IFN-g and IL-1b mediated insulin secretion inhibition and direct DNA damage dependent on iNOS produced by b-cells [188].
IL-1b induces expression of SOCS1 and SOCS3 in a negative feedback loop which protects insulin producing cells from IL-1b induced apoptosis by inhibition of NF-kB and downstream iNOS induction [189-191]. Contradictory to these findings in murine models however, blockade of NO production with aminoguanidine and NG-nitro-L-arginine was found to have no effect on IFN-g, IL-b and TNF-α dependent loss of glucose dependent
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Chapter 1: Literature Review insulin release from human islets which suggests that human islets are more resistant to
NO-induced cell death [192]. Collectively these results show that iNOS and free oxygen radical production have dire effects on b-cell function and strongly correlate with the induction of apoptosis.
TNF-α and IL-1b stimulated MAPKs, in particular JNKs, are also associated with the induction β-cell death through post translational modification of anti-apoptotic BCL-2 proteins as well as by inducing iNOS, which is potentiated with the addition of IFN-g [166,
193, 194]. BCL-2 proteins are substrates of JNK and upon extended phosphorylation these proteins are targeted for degradation by the proteasome, which predisposes cells to death by apoptosis [195]. Various in vitro studies have also shown that JNK inhibition using small cell permeable inhibitors protect β-cells from various forms of cell death induction, including cytokines [196, 197]. Three distinct isoforms of JNK (JNK1-3) have also been identified and are expressed in β-cells and have distinct opposing roles in the regulation of
β-cell destruction by IFN-g, TNF-α and IL-1b [198]. Knockdown of JNK1 and JNK2 in
INS-1E cells with siRNAs was shown to protect from IFN-g, TNF-α and IL-1b induced apoptosis, whereas JNK3 knockdown potentiated cell death and this correlated with the phosphorylation state of c-Jun. These results suggest that TNF-α and IL-1b signal transduction further pre-disposes β-cells to cell death through sensitisation to apoptosis by reducing anti-apoptotic protein proteins, however these effects still remain confined to β- cell lines.
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1.4.13 Anti-cytokine therapies for T1D:
As there is overwhelming evidence that IFN-g, TNF-α and IL-b have critical roles in b- cell dysfunction and autoimmune diabetes development various anti-cytokine therapies have been developed in an attempt to reduce or prevent the disease with varying success.
IL-1 antagonism has been shown to improve b-cell function and reduce hyperglycaemia in
T2D preclinical models and patients [199-201]. IL-1 antagonism alone has shown virtually no protective effects in T1D animal models [202], however when combined with a suboptimal anti-CD3 antibody therapy there was a decrease in diabetes in the NOD/Lt mouse [203] but this has not been reproducible in other studies [204]. While anti-TNF therapies in murine models have shown both protective and destructive results in diabetes prevention, a clinical study using Etanercept to block TNF signalling in recent-onset T1D patients showed improved b-cell function and a lower insulin requirement in treated patients, however slow recruitment required this study to be terminated [202, 205]. While there are currently no inhibitors for STAT1 and targeting IFN-g or its receptor does not affect diabetes development in the NOD/Lt mice [75, 86], inhibition of STAT1 activating
JAK1/2 proteins using AZD1480 protects and reverses autoimmune diabetes development in the NOD/Lt mouse through inhibition of MHC-I upregulation [96]. This compound targets the same site as Ruxolitinib and Baricitinib, which are both clinically approved drugs, and could fast track this strategy into clinical trials for T1D. As preventing STAT1 activation has been successful in reducing diabetes development, understanding and identifying novel regulators of STAT1 phosphorylation, such as protein kinases and phosphatases, could provide new therapeutic targets for T1D.
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1.5 Protein kinases, protein tyrosine phosphatases and autoimmune diabetes:
PTPs are enzymes responsible for the dephosphorylation of intracellular proteins such as
STATs and MAPKs and are therapeutic targets for various diseases, including T2D [206].
PTPN2 and PTPN22 are also genetically associated with T1D [54, 55, 207]. Excessive oxidative stress caused by NO and ROS, such as in autoimmune diabetes, leads to irreversible inactivation of these enzymes and loss of phosphorylation regulation and aberrant cell signalling responses [208]. In the past decade understanding how these enzymes regulate cytokine signalling and affect b-cell dysfunction has been of great interest and is the focus of this thesis and will be discussed below.
1.5.1 Protein phosphorylation:
Cytokine induced protein phosphorylation is the most common form of reversible regulation of protein function and is highly dynamic and tightly regulated [209, 210].
Protein phosphorylation can affect a myriad of cellular functions including viability, replication, metabolism etc., which is why these signalling events are tightly regulated and widely studied in many diseases. Indeed, dysregulation of phosphorylation events are linked to numerous pathologies such as diabetes, cancer, arthritis and neurological deterioration [52, 211-213].
1.5.2 Protein kinases:
Phosphorylation occurs by an esterification reaction and requires three components: the enzyme, a donor ATP molecule and a recipient protein [214]. The superfamily of enzymes
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Chapter 1: Literature Review responsible for the catalysis of the esterification reaction are termed protein kinases (PKs).
PKs bind an ATP molecule in their active site then sequentially bind to their substrate through a consensus sequence, specifying their selectivity [215]. The γ-phosphate group of the ATP molecule is then transferred to the hydroxyl (OH-) side chain group of the amino acid substrate of the recipient protein [216, 217]. The phosphorylated protein is then released from the PK, followed by an ADP molecule. PKs are generally divided into two groups, determined by their amino acid specificity; serine/threonine-specific kinases and tyrosine specific kinases (PTKs) [218]. The structure of the active site cleft where the substrate protein binds to PKs is pivotal in determining their amino acid substrate specificity. This is due to the structural differences between serine and threonine amino acids in comparison to tyrosine amino acids [219], as tyrosine residues have a longer sidechain due to the presence of a benzene ring before the receptive hydroxyl group.
1.5.3 Protein tyrosine phosphatases:
As reviewed in Sec. 1.4, dysregulation of cell signalling can lead to dire pathological effects on cells and tissue under certain conditions. Posttranslational modifications, such as phosphorylation are among the most commonly reported dysregulated events, indeed tissue hyperphosphorylation strongly correlates with autoimmune conditions. As protein phosphorylation has such dynamic results on a cells activity another family of enzymes exist to counter regulate phosphorylation. These enzymes are termed protein phosphatases
(PPs) and they are responsible for dephosphorylation of proteins by the process of hydrolysis. Protein dephosphorylation requires three components (similar to kinases): the enzyme, a recipient water molecule and the phosphorylated substrate. Similar to PKs, PPs
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Chapter 1: Literature Review are described based on their substrate specificity (dual specific phosphatases and protein tyrosine phosphatases for example).
PTPs were initially described as a small family of ubiquitously expressed enzymes with general housekeeping roles [220]. Currently over 100 members of the PTP family have been described and subdivided into four classes based on substrate specificity and structure [221]. The class I non-receptor linked PTPs are currently the most understood family and are encoded by 17 genes on 12 different chromosomes. Class I PTPs, which contain ~90% of the family, are comprised of classical PTPs and dual specific phosphatases. Class II PTPs are low molecular weight phosphatases of which there is only one classified member, aptly named low molecular weight phosphatase (LMPTP). Class
III PTPs are the Cdc25 phosphatases of which there are three members (CDC25A-C). The
Class IV members are the haloacid dehydrogenase family and include the eyes absent
(EYA) subfamily and are the least understood due to a distinct catalytic mechanism from the others. The class I PTPs will be the only family reviewed here.
1.5.4 Protein tyrosine phosphatase biochemistry:
Description of the 3D structure of PTPs has allowed researchers to develop effective selective inhibitors with clinical applications, as well as for researchers to study the role of
PTPs in various pathologies. Typically, PTPs contain a twisted β-sheet core flanked by α- helices which create a binding pocket for substrates. 9Å deep within the pocket is the active site signature motif, (H/V)C(X)5R(S/T), which is conserved throughout all PTP species
[222]. This motif contains an invariant catalytic cysteine residue which binds to phosphotyrosyl-proteins to trigger hydrolysis (Fig. 1.5). The conserved cysteine residue
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Chapter 1: Literature Review binds to phosphotyrosyl proteins by its Sγ atom which acts as a first step nucleophile creating a phospho-enzyme intermediate [223]. The invariant arginine residue in the catalytic motif then forms bidenate hydrogen bonds to the phosphate group of the substrate to stabilize the reaction [224]. An aspartate residue on a tryptophan-proline-aspartic acid
(WPD) loop is also required for the reaction by acting as a first step electrophile and second step nucleophile [225]. Firstly, it protonates the oxygen atom of the phospho-enzyme intermediate, allowing release of the substrate from the enzyme, then accepts a proton from a H2O molecule held by a glutamine residue in the binding pocket [226], allowing the cysteine residue to act as an end point electrophile. This ultimately results in the release of the phosphate group from the enzyme and leaves the cysteine in a negatively charged state for the next reaction.
Figure 1.5: Mechanism of PTP hydrolysis based on murine PTPN1.
Illustration outlining the two step dephosphorylation of a tyrosine phosphorylated protein by murine PTPN1. When a phosphorylated tyrosine residue (pTyr, yellow) enters a PTP catalytic site it is stabilised by bidenate hydrogen bonds through an arginine residue
(Arg221, green) and binds to the active cystine reside (Cys215, blue) which acts as a first
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Chapter 1: Literature Review step nucleophile and donates an electron to the conserved aspartate residue in the WPD loop (Asp181, pink). The tyrosine based enzyme is then released from the active site where the aspartate residue then acts as a nucleophile and through a water molecule held by a glutamine residue (Gln262, aqua) donates an electron through the phosphate group to the cystine electrophile resulting in a negatively charged cystine reside and release of the phosphate group from the enzyme.
1.5.5 PTP involvement in disease:
As PTPs were progressively discovered to have specific regulatory functions, so did the understanding that many of them were involved in pathological mechanisms. Several PTPs have been found to be linked hereditarily and influence penetrance of a variety of autoimmune diseases, cancers and metabolic disorders, including PTPN1, PTPN2 and
PTPN22 [227]. Spontaneously developed mouse models have also shown involvement for
PTPs in chronic disorders that aren’t recorded to have human counterparts such as the autoimmune phenotype observed with PTPN6 deficiency in the motheaten mouse which develops granulocytic skin lesions and lethal pneumonitis within 3 weeks of birth [228].
PTPN2 and PTPN22 are associated with T1D, however they are also associated with various other autoimmune diseases such as inflammatory bowel disease, rheumatoid arthritis, lupus, graves and psoriasis [7, 52, 229, 230]. Indeed many PTPs are linked to different disorders with various forms of mutation output, for example PTPN11 is associated with Noonan syndrome which presents with skin, heart, ear and facial abnormalities through a gain of function mutation [231], whilst associated with Leopard syndrome which presents with growth retardation and cardiac abnormalities through a loss
34
Chapter 1: Literature Review of function mutation [232, 233]. Understanding how these PTPs are linked to their associated diseases is currently of great interest for therapeutic developments, indeed
PTPN1 inhibition therapies are currently in clinical studies to reduce obesity and enhance peripheral insulin sensitivity in type 2 diabetes (T2D) [234].
As diseases develop from PTP dysregulation of signalling pathways, studying how
PTPs lose regulation of their pathways is of great interest. Understanding the regulation of
PTP activity initially came from studies which showed that PTP phosphorylation can inactivate them by changing the 3D confirmation of the enzyme and blocking the substrate binding pocket, inhibiting the enzyme [235-237]. However recently focus has shifted to reversible and irreversible oxidative inactivation of the catalytic cysteine residue of PTPs.
The ability of PTPs to interact with substrates requires their active cysteine residue to be negatively charged in a thiolate state (S-) [223]. They are able to maintain this charge by inherently possessing a low pKa value in their active site of ~4 in comparison to other cysteine residues that are normally ~8 [238, 239]. This unique feature has consequences under oxidative stress, where there is excess ROS and NOS production in the cytoplasm for example. Excessive oxidative stress and free oxygen radical production can cause oxidation of the cysteine residue converting it to the sulphenic acid derivative (SOH) [240]
(Fig. 1.6). This is an example of reversible oxidation, as sulphenic inactivated PTPs can interact with antioxidants to remove the hydroxyl group and restore their cysteine residues to a negatively charged state. Under chronic oxidative stress conditions, such as in inflammatory settings, or with deficiency of antioxidant supplies to restore activity to sulphenically inactivated PTPs, they can become further oxidised which is irreversible.
This involves further oxidation of the sulphenic acid PTP form to the sulphinic (SO2H) and
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sulphonic (SO3H) acid derivatives [241] (Fig. 1.6). These derivatives are unable to interact with antioxidants and become catalytically dead. They are then targeted to the proteasome by ubiquitination resulting in degradation, rendering the cell susceptible to aberrant signalling events.
Figure 1.6: Mechanism of oxidative inactivation of murine PTPN1.
Illustration of reversible and irreversible oxidation of PTPs based on the active site cysteine residue of PTPN1. Oxidative stress (as shown by ROS here, red) and resultant free oxygen radicals oxidise cystine based PTPs to an inactive sulphenic state which intracellular reducing agents, such as antioxidants, can reactivate the enzyme (green). However, prolonged exposure to oxidative stress can result in the irreversible inactivation of PTPs active cystine residue (black).
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1.5.6 Oxidative PTP inactivation in autoimmune diabetes:
As in Sec. 1.4.12, the relationship between inflammatory cytokines, oxidative stress and b-cells is largely considered a negative one, resulting in impaired insulin secretion and cellular dysfunction in vivo or direct apoptosis in vitro [242-244]. This is partly attributed to the naturally low levels of antioxidant enzymes including superoxide dismutase (SOD), glutathione peroxidase and catalase [245] within the b-cell. The levels of catalase, which degrades hydrogen peroxide, are so low it is classed as a “disallowed gene” in b-cells [246,
247], meaning its expression is repressed in b-cells. This makes b-cells inherently more susceptible to PTP inactivation by oxidation due to the lower threshold of reducing agents.
Indeed, we have previously shown for the first time that PTPs are irreversibly oxidised in pancreatic homogenates from NOD/Lt mice with immune cell infiltration [53].
Furthermore, PTP inhibition using sodium pervanadate in isolated NODPI islets enhanced
IFN-g induced STAT1 signalling and resulted in enhanced death of purified human b-cells and islets without the requirement for co-stimulation with TNF-a or IL-1b, suggesting that globally PTPs negatively regulate IFN-g signalling in b-cells. This result is consistent with previous studies in vitro where reduced PTPN2 expression in the INS-1E b-cell also resulted in enhanced IFN-g induced STAT1 signalling and cell death activation [54, 55].
Deletion of the antioxidant glutathione peroxidase in murine islets also enhanced IFN-g induced STAT1 signalling and islet death which could be reduced with supplementation of the N-acetyl cysteine (NAC) antioxidant, presumably through prevention of free oxygen radical dependent PTP inactivation or enhanced reduction of reversibly inactivated PTPs.
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We were also able to detect expression of PTPN1, PTPN2 and PTPN6 in the irreversibly oxidised protein fractions taken from NOD/Lt mouse pancreata. As mentioned above,
PTPN2 is a well-known negative regulator of IFN-g signalling, however the individual roles for PTPN1 and PTPN6 in b-cells remains unknown (Fig. 1.7). PTPN1 is strongly associated with T2D and promotes hyperglycaemia and obesity in humans and mice [248-
252]. PTPN1 is also reported to negatively regulate JAK/STAT pathways, however no role has been described in the context of T1D [52, 253, 254]. PTPN6 is not associated with diabetes, however inhibition results in a lethal autoimmune pathology in the motheaten mouse [228, 255-258]. Collectively this suggests at least in vitro that oxidative stress accumulation results in PTP inactivation, leading to enhanced IFN-g induced STAT1 signalling and b-cell dysfunction and death.
There has been a large amount of research in the past 20 years dedicated to targeting oxidative stress associated with T2D with antioxidants to reduce the pathological effects of hyperglycaemia, such as vascular complications, and to improve the function of the residual b-cell mass [259, 260]. Indeed, delivery of the NAC antioxidant through drinking water has been shown to reduce hyperglycaemia and improve insulin secretion in the
Zucker diabetic fatty rat and db/db mouse models of T2D [261, 262]. This is more complicated in the setting of T1D as while oxidative stress associated vascular complications attributed to hyperglycaemia can still be targeted similarly [263], the b-cell pool is reduced due to autoimmune destruction so improving residual b-cell function is somewhat limited and remains largely unstudied. However as b-cells express low levels of antioxidants and we showed that antioxidant supplementation in vitro protected isolated islets from IFN-g induced death with glutathione peroxidase deficiency, there may be a
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Chapter 1: Literature Review beneficial role for antioxidant therapy during the development of autoimmune diabetes in vivo.
Gaps in our current understanding of the role of individual PTP function, downstream targets and signalling pathways in the crosstalk between the pancreas and immune cells in T1D, and their contribution to the development of diabetes at different stages of the disease remain to be clarified. Testing the present hypothesis that oxidation of PTPs is a contributing mechanism in autoimmunity will increase our understanding of
T1D pathogenesis and indicate novel targets for clinical interventions. For instance, identification of the mechanisms by which PTPs modulate cytokine activity may provide relevant and realistic targets for manipulation by pharmacological agents in the future, which leads to our hypothesis and aims.
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Figure 1.7: Model of how PTP oxidation affects cytokine signalling in b-cells.
Illustration outlining the current model of how PTP oxidation affects cytokine signalling in b-cells based on previous studies. As immune cells are recruited to the pancreas of
NOD/Lt mice, oxidative stress is enhanced in islets which results in PTP inactivation [52,
53]. The inactivation of PTPs leads to enhanced IFN-g signalling and induction of apoptosis in isolated islets and b-cell lines. PTPN2, which is known to negatively regulate IFN-g signalling and b-cell apoptosis, is inactivated in immune infiltrated islets [54, 55]. PTPN1 and PTPN6 are also inactivated but their regulation of cytokine signalling responses in b- cell remains unstudied.
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1.6 Hypothesis and aims:
Hypothesis:
During the progression to autoimmune diabetes, the NOD/Lt mouse develops pancreatic oxidative stress which results in PTP inactivation leading to excessive inflammatory cytokine signalling through enhanced phosphorylation and sensitisation to b-cell demise.
Intervention of oxidative stress development in the NOD/Lt mouse with oral delivery of antioxidants will relieve oxidative stress and reduce insulitis and autoimmune diabetes development. Individual inactivation of the PTPN1 and PTPN6 enzymes in b-cell lines, which we have previously shown to correlate with irreversibly inactivated PTPs in NOD/Lt mice, will result in enhanced IFN-g, TNF-a and/or IL-1b signalling, downstream gene transcription and trigger apoptosis allowing identification of which pathways these PTPs modulate.
Aim 1: To determine whether delivery of antioxidants through drinking water can reduce insulitis and autoimmune diabetes development in the NOD/Lt mouse.
Aim 2: To develop a PTPN1 deficient b-cell line and validate if PTPN1 regulates IFN-g,
TNF-a and/or IL-1b signalling.
Aim 3: To develop a PTPN6 deficient b-cell line and validate if PTPN6 regulates IFN-g,
TNF-a and/or IL-1b signalling.
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Materials and Methods
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Chapter 2: Materials and Methods
2.1 Overall principal of the methodology:
The methodology used for the following studies were based largely on optimized standard techniques and protocols already implemented in our laboratory using instruments accessible on the St. Vincent’s hospital campus. They focused primarily on either in vivo murine studies or in vitro biochemical studies using ex vivo tissue or b-cell lines to display a breadth of technical aptitude.
2.2 Mouse details:
NOD/Lt, NODPI, NOD/Rag1 and NOD8.3 mice were bred and maintained at St. Vincent’s
Institute. Experiments were approved by the institutional animal ethics committee. NODPI mice express proinsulin II under control of the MHC class II (I-Eak) promoter and do not develop diabetes as they are tolerant to proinsulin [264]. NODPI islets were used for our cytokine signalling studies as these mice remain on the NOD/Lt lineage and do not develop insulitis which would result in background signalling and interfere with our results. We have previously performed cytokine signalling response analysis of age matched NODPI and NOD/Lt islets to confirm that both responded similarly to the stimuli (data not shown).
NOD/Rag1 mice have severe immunodeficiency due to a knockout mutation of the recombination activating gene 1 (Rag1) and complete null allele of the IL-2 receptor common gamma chain (IL-2rg), required for T-cell development making them useful in immunological transfer studies [265]. NOD8.3 mice expressing T-cell receptor ab rearrangements recognizing the H2Kd restricted peptide (VYLKTNVFL) from islet- specific glucose 6-phosphatase catalytic subunit–related protein (IGRP) develop β-cell specific CD8+ T-cells which can be utilized in studying b-cell destruction in vitro [93].
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2.3 Diabetes incidence:
To monitor diabetes incidence mice were monitored weekly for urine glucose levels using glucose strips. Mice that tested positive for diabetes with urine glucose levels >15mM were then tested on consecutive days with blood glucose readings to compensate for false positive results and then mice were euthanized in accordance to ethical protocols.
2.4 Adoptive transfer of diabetic NOD/Lt splenocytes into NOD/Rag1 mice:
When female NOD/Lt mice were determined to be diabetic, mice were euthanized through cervical dislocation and the spleen was removed and stored in PBS on ice. The spleen was then passed through a 40µm cell strainer with agitation from a sterile syringe plunger and washing with cold PBS. Erythrocytes were then lysed with red cell lysis buffer.
Splenocytes were then counted and 5x106 cells were transferred into NOD/Rag1 hosts through intravenous injection into the tail vein. Heat lamps were used to visualize and expand the tail vein of the host mice to ease intravenous transfer. Female littermates of
NOD/Rag1 mice were also used in our transfer studies.
Diabetes transfer through splenocyte injection into immunocompromised hosts has been a standard methodology since their development in the 80s. They enable researchers to study the effects of pharmacological treatments before the onset of autoimmune diabetes, as NOD/Lt mice start to develop pathology after weening ceases. They also allow researchers to study various immune cell roles in autoimmune diabetes development as specific immune cells or transgenic immune cells can be purified before transfer. This model, while a quick indicator of diabetes progression, does not mirror the progression and
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development of autoreactive immune cells to diabetes development as with standard
NOD/Lt mice so this caveat must be taken into consideration.
2.5 Antioxidant storage and treatment:
Stock concentrations of 250mg/mL NAC (Sigma Aldrich) and 250mM mito-TEMPO
(Enzo Life Sciences) were made with double distilled water and stored in 1mL aliquots at
-20°C. Aliquots were then thawed and diluted in 250mL drinking water bottles to achieve working concentrations twice weekly for the continuation of experiments.
2.6 Islet isolation:
Human islets were acquired by collagenase digestion and density gradient centrifugation of human pancreata through the Tom Mandel islet transplantation program. Human pancreata were obtained, with informed consent from next-of-kin, from non-diabetic, heart-beating, brain-dead donors by the Australian Islet Transplant Consortium, and approved by the human ethics committees of the hospitals involved and the Australian Red
Cross.
Murine islets were isolated by bile duct cannulation and pancreas inflation with 3mL of collagenase P (0.5mg/mL, Roche), digestion in a 37°C heat bath with agitation and histopaque-1077 (Sigma-Aldrich) density gradient separation with unsupplemented RPMI
(Life technologies) as the low density collecting gradient. Undamaged islets were then picked under a microscope and recovered in CMRL (Life Technologies) supplemented with 10% FCS. A minimum of 100 islets of similar size were used per each experimental condition.
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2.7 NIT-1 cell maintenance and cell treatments:
Insulin producing NIT-1 cell lines [266] were cultured in DMEM (Life Technologies) supplemented with 10% FCS. Cytokine treatments were performed in serum free media and concentrations were selected based on previous time course and dose-dependent studies which showed desired signal transduction events [79, 80, 267, 268]. NIT-1 cells were treated with 10ng/mL of recombinant murine TNF-α (In Vitro Technologies) and/or
10U/mL of recombinant murine IFN-γ (Australian Biosearch) and/or 10ng/mL of recombinant murine IL-1b (R&D Systems). Islets were treated with 100ng/mL of recombinant TNF-α/ IL-1b and/or 100U/mL of recombinant IFN-γ. NIT-1 cells were treated with 10µM of the PTPN1 inhibitor (CAS 765317-72-4, Merck Millipore) or NSC
87877 (CAS 56932-43-5, Merck Millipore). Isolated islets were treated with 100µM of the
PTPN1 inhibitor. The concentrations of the PTPN1 and PTPN6 inhibitor were selected based on previous dose dependent studies and verified in our group prior the commencement of this project (data not shown) [269-272]. It is important to keep in mind that these two inhibitors are not completely specific as the PTPN1 inhibitor also inhibits
PTPN2 and NSC87877 also inhibits PTPN11 [272, 273]. NIT-1 cells were treated with
10µM of SP600125 (Sigma Aldrich) or 20µM of Nec-1 (Sigma Aldrich) or 50µM of Z-
VAD.FMK (Sigma Aldrich) and concentrations were selected based on previous studies
[274-277].
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2.8 CRISPR/Cas9 deletion of protein tyrosine phosphatases:
To delete PTPN6 or PTPN1 from NIT-1 cells, we employed a CRISPR/Cas9 exon deletion strategy incorporating the Cas9 D10A nickase mutant and four exon flanking guide RNA
(gRNA) sequences to minimize off target effects [278]. After primer annealing, double stranded oligonucleotide sequences containing gRNAs (sequences in Table. 2.1, BioRad) were cloned into pX335-U6-Chimeric BB-CBh-hSpCas9n(D10A), a gift from Feng Zhang
(Addgene plasmid #42335). Chemically competent Stbl3 E. coli (ThermoFisher) were transformed by heat shock and grown on LB plates containing ampicillin (50µg/mL).
Surviving colonies were then grown overnight in LB media and plasmid DNA purified using the AccuPrep Nano-Plus Plasmid Mini Extraction Kit (Bioneer) and validated by
Sanger sequencing at the Australian Genome Research Facility. The four targeting vectors were then transiently cotransfected with pEGFP-puro, a gift from Michael McVoy
(Addgene plasmid # 45561) using Lipofectamine 2000 (ThermoFisher) and transfected cells were selected with DMEM (Life Technologies) containing puromycin (10µg/mL) for
48 hours. Gene deficient cell lines were then identified via limiting dilution single cell cloning and screening by immunoblot for PTP expression.
Lipofectamine forms a cationic liposome complex with negatively charged nucleic acids and allows efficient fusion with negatively charged cell membranes for endocytosis
[279]. Delivery of Cas9 and sgRNAs with lipofectamine has been shown to transfect human pluripotent stem cells with an efficiency of 63% [280] and also transfect murine hair cells in vivo [281]. While we incorporated four sgRNAs in an attempt to minimize off target effects, newer CRISPR strategies such as paired nickases would be more appropriate as large non-specific gene segments have been shown to still be excised with “specific”
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sgRNAs [282]. However, the critical validation of the specific inactivation of PTPs is to restore the expression of the protein (e.g. Adenovirus-mediated).
Table 2.1: CRISPR/Cas9 deletion strategy of protein tyrosine phosphatases.
Target Gene: PTPN1 (Mouse) Exons Targeted: 6 to 8 Target Primer Upstream 1 5'-CACCGGTGCACACATGGGGTCTGTG-3' Sequences: Forward: Upstream 1 5'-AAACCACAGACCCCATGTGTGCACC-3' Reverse: Upstream 2 5'-CACCGCCCTCCTCAGTGCATCCAGC-3' Forward: Upstream 2 5'-AAACGCTGGATGCACTGAGGAGGGC-3' Reverse: Downstream 1 5'-CACCGGGGGGTGGGGTGAGAGGAAG-3' Forward: Downstream 1 5'-AAACCTTCCTCTCACCCCACCCCCC-3' Reverse: Downstream 2 5'-CACCGCCCACCCCCAACCCCAAGCC-3' Forward: Downstream 2 5'-AAACGGCTTGGGGTTGGGGGTGGGC-3' Reverse: Target Gene: PTPN6 (Mouse) Exons Targeted: 5 to 10 Target Primer Upstream 1 5'-CACCGTCTGTGCCCACTCTGGGACC-3' Sequences: Forward: Upstream 1 5'-AAACGGTCCCAGAGTGGGCACAGAC-3' Reverse: Upstream 2 5'-CACCGACAGAGGCCTGCTACCTGCC-3' Forward: Upstream 2 5'-AAACGGCAGGTAGCAGGCCTCTGTC-3' Reverse: Downstream 1 5'-CACCGTGCAATCCTTGGGACCCACA-3' Forward: Downstream 1 5'-AAACTGTGGGTCCCAAGGATTGCAC-3' Reverse: Downstream 2 5'-CACCGTGCACTCATGATATCAGGCT-3' Forward:
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Downstream 2 5'-AAACAGCCTGATATCATGAGTGCAC-3' Reverse:
2.9 Immunoblotting:
Islets and cells were washed with PBS and lysed with radio immunoprecipitation assay
(RIPA) buffer on ice. Lysates were then denatured at 100°C and resolved by 12%-20%
SDS-PAGE gel (depending on protein size) and transferred to a nitrocellulose membrane which was then blocked with 10% skim milk powder in TBST buffer to prevent background noise. Membranes were then incubated with primary antibody in 10% fetal bovine serum overnight at 4°C and secondary antibody in 10% skim milk powder for 1 h at room temperature. Membranes were washed with TBST between blocking and staining.
Horse radish peroxidase (HRP) complexes were then activated with enhanced chemiluminescence (ThermoFisher) and visualized on X-ray film (Fujifilm). Densitometry quantification was performed with ImageJ software. The list of antibodies used is provided in Table 2.2. Immunoblots visualized by chemiluminescence activated HRP on X-ray film is becoming somewhat of an outdated and unreliable protocol with technologies such as fluorescent tagged antibodies and quantitative LI-COR analysis becoming more accessible.
X-ray visualization can have large amounts of background noise and weak signals requiring hours of overexposure, however the antibodies used in this study had already been optimized for this technique to decrease these artefacts.
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Table 2.2: List of antibodies used in immunoblotting.
Antibody Supplier Catalogue # BCL-2 Cell Signalling 2870 BCL-XL Cell Signalling 2764 Caspase 8 Cell Signalling 4790 Cleaved caspase 3 Cell Signalling 9661 Goat anti-rabbit HRP Merck Pty Ltd 12-348 MCL-1 Cell Signalling 5453 Oxidised PTP R&D Systems RB01 p-c-Jun (S73) Cell Signalling 9146 p-JNK (T183/Y185) Cell Signalling 9255 p-p38 (T180/Y182) Cell Signalling 9211 p-STAT1 (Y701) Becton Dickinson 612132 PTPN1 Merck Pty Ltd 539741 PTPN6 Cell Signalling 3759 Rabbit anti-mouse HRP Dako P0260 α-tubulin Sigma Aldrich T9026 β-actin Cell Signalling 3700
2.10 mRNA extraction and real-time PCR: mRNA was extracted from islets using an Isolate II RNA Micro Kit (Bioline) and reverse transcribed with 600ng of RNA using the High Capacity cDNA Reverse Transcription Kit
(Applied Biosystems). Real-Time PCR was performed using the AmpiTaq Gold Kit
(Applied Biosystems) on a Lightcycler. RNA analysis was performed with the dCT and ddCT methods (true RNA levels and relative RNA levels, respectively) using β-actin as an internal control. The list of primers is provided in Table 2.3. RNA contamination risk was reduced by working on designated RNA only benches with equipment used only for these protocols. While real-time PCR is useful for examining large primer pools over a lot of
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samples, genes with low expression values can be missed or give artificial results at higher cycle numbers.
Table 2.3: List of primers used for real-time PCR.
Target Gene Assay ID Catalogue # Ccl2 Mm00441242_m1 4331182 Ccl5 Mm01302427_m1 4331182 Ccl20 Mm01268754_m1 4331182 Cxcl1 Mm04207460_m1 4351372 Cxcl9 Mm01345159_m1 4331182 Cxcl10 Mm00445235_m1 4331182 Nos2 Mm00440485_m1 4331182 Ptpn1 Mm00448427_m1 4331182 Ptpn2 Mm00501226_m1 4331182 Stat1 Mm01257286_m1 4331182
2.11 Haematoxylin and eosin histology:
Resected pancreata were stored in formalin at 4°C then processed for embedding in paraffin using an Excelsior AS tissue processor. Using a microtome, 5µm sections were adhered to
2-aminopropyltriethoxysilane (AES) coated slides with three layers of sections taken from the tissue a minimum of 200µm apart to achieve a representation of the whole pancreas.
Slides were then dewaxed using histolene and then stained with eosin (Amber Scientific) to visualise the cytoplasm and extracellular matrix. Slides were then washed with ethanol and counterstained with haematoxylin (Amber Scientific) to visualise the nuclei. Slides were then washed and dehydrated with ethanol and mounted with dibutylphthalate polystyrene xylen (DPX, Merck Millipore).
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2.12 Insulin immunohistochemistry:
Resected pancreata were snap frozen in cassettes with optimal cutting temperature compound (OCT, Sakura Finetek) using a liquid nitrogen bath. Using a cryostat, 5µm sections were adhered to AES coated slides and stored at -20°C, with three layers of sections taken from the tissue a minimum of 200µm apart to achieve a representation of the whole pancreas. Thawed sections were then stained with a Guinea pig anti-insulin antibody followed by an anti-guineapig HRP antibody. HRP complexes were then activated with diaminobenzidine (DAB, Sigma Aldrich) to visualise insulin positive cells as brown. Slides were then counterstained with haematoxylin to visualise the nuclei of the background tissue and mounted with Dako mounting medium (Agilent Technologies). The list of antibodies used is provided in Table 2.4. Using insulin immunohistochemistry for insulitis is beneficial as smaller islet cross sections can be easily visualised as opposed to
H&E scoring where they may be missed.
Table 2.4: List of antibodies used in immunohistochemistry.
Antibody Supplier Catalogue # Guineapig anti-insulin Dako A0564 Rabbit anti-guineapig HRP Dako P014102
2.13 Insulitis scoring:
Insulitis was scored blind using the following scale: 0 = no islet infiltration, 1 = peri-islet infiltration (0-25%), 2 = extensive peri-islet infiltration (25- 50%), 3 = intra-islet
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infiltration (50-75%), 4 = extensive intra-islet infiltration (>75%) or total islet destruction.
The percentage of islets with each score was calculated by addition of scores for the three sections. The final insulitis score for each pancreas was calculated as follows: ([0.25 x number of grade 1 islets] + [0.5 x number of grade 2 islets] + [0.75 x number of grade 3 islets] + number of grade 4 islets)/total number of estimated islets. A blind scoring methodology was utilised to prevent bias from the counter.
2.14 Cell viability:
Cell viability was evaluated by either Hoechst-33342 and propidium iodide DNA staining or Nicoletti DNA fragmentation analysis 48 h after cytokine stimulation [283]. DNA cell staining was performed with Hoechst-33342 (1μg/mL, Sigma Aldrich) and propidium iodide (1μg/mL, Invitrogen) in DMEM media. Percentage cell death was evaluated by counting a minimum of 2000 cells in each condition where live cells are visualised by blue fluorescence (Hoechst-33342) and dead cells visualised by red fluorescence (propidium iodide) under an inverted microscope using the DAPI channel. While this technique is useful as it shows a clear qualitative representation of the live and dead cells, dead cells can be removed during the washing and staining steps as they are not fixed which causes inaccuracy. To reduce counting errors, images were taken through the microscope and cells were counted using the ImageJ cell counter tool.
Nicoletti DNA fragmentation analysis was performed with cell permebalisation and staining with propidium iodide (1μg/mL, Invitrogen), 0.1% sodium citrate (wt/v) and 0.1%
Triton X-100 (v/v, Sigma Aldrich) in PBS. The PerCP-Cy5-5 channel was used for gating and fragmentation was measured as the percentage of events in the sub-G1 phase of the
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cell cycle profile. Data were collected on a BDFortessa and subsequently analysed on
FlowJo software. DNA fragmentation analysis is an effective method for analysing large amounts of cells efficiently, however the tryptic digestion and preparation for flow cytometry can cause further cell death and background noise which would be analysed. As both methodologies had their limitations we utilized both of them in our protocols.
2.15 Flow cytometry analysis of MHC-I:
MHC-I expression was measured on NIT-1 cells with a biotinylated H2Kd specific MHC-
I antibody (Table. 2.5), followed by FITC conjugation by streptavidin after 24 h of IFN-γ stimulation. NODPI islets were dispersed into single cells with as soft tryptic digest (4.5µM bovine trypsin and 2mM EDTA in PBS) and MHC-I was measured on β-cells using the biotinylated H2Kd specific MHC-I antibody with APC conjugation by streptavidin 48 h after IFN-γ stimulation. β-cells were gated from other islet cells by autofluorescence in the
FITC channel [284]. Propidium iodide (1μg/mL, Invitrogen) was used to exclude non- viable cells from analysis using the PerCP-Cy-5-5 channel. MHC-I data were collected by mean fluorescence intensity of the FITC channel for NIT-1 cells or APC channel for islets on a BDFortessa and subsequently analysed on FlowJo software. This technique is useful for measuring MHC-I expression in vitro as a readout of IFN-γ stimulation and studying how pharmacological inhibitors can alter this pathway, however the biological relevance of these experiments needs to be scrutinised as the in vivo expression of MHC-I and interaction with T-cells is a more complex relationship as MHC-I can be induced by a variety of cytokines.
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Table 2.5: List of antibodies used in MHC-I flow cytometry.
Antibody Supplier Catalogue # MHC-I (H-2Kd) Becton Dickinson 553564 Streptavidin-FITC Invitrogen SA1001 Streptavidin-APC Invitrogen SA1005
2.16 Flow cytometry analysis of CD4+ and CD8+ T-cells:
Spleens, pancreatic lymph nodes and inguinal lymph nodes were passed through a 40µm cell strainer with agitation of a sterile syringe plunger. Spleen supernatants were then treated with red cell lysis buffer to digest erythrocytes. Samples were then stained with anti-CD3 conjugated to V500, anti-CD11c, anti-CD11B, anti-B220 and anti-F4/80 conjugated to AlexaFluro450 (which acts as a ‘dump’ colour to gate out dendritic cells, B- cells and macrophage), anti-CD4 conjugated to APC-Cy7, anti-CD8 conjugated to PerCP-
Cy5.5, anti-CD69 conjugated to PE, anti-CD44 conjugated to PE-Cy7 and PD-1 conjugated to 610/20 and data was collected on a BDFortessa and subsequently analysed for cell numbers and mean fluorescent intensity on FlowJo software. The list of antibodies used is provided in Table 2.6. Single colour controls were used to compensate the various channels and propidium iodide (1μg/mL) was used to exclude dead cells.
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Table 2.6: List of antibodies used in T-cell flow cytometry.
Antibody Supplier Catalogue # B220-AlexaFluro450 (RA3-6B2) BioLegend 103228 CD11b-AlexaFluro450 (M1/70) BioLegend 101201 CD11c-AlexaFluro450 (N418) BioLegend 117301 CD3-V500 (500A2) BioLegend 152302 CD4-APC-Cy7 (GK1.5) BioLegend 100413 CD44-PE-Cy7 (IM7) BioLegend 103029 CD69-PE (H1.2F3) BioLegend 104507 CD8-APC (53-6.7) BioLegend 100711 F4/80-AlexaFluro450 (BM8) BioLegend 123101 PD-1-BV605 (29F.1A12) BioLegend 135219
2.17 51Chromium release assay:
Activated CD8+ T-cells recognizing the beta cell antigen islet-specific glucose 6- phosphatase catalytic subunit–related protein (IGRP) were generated by incubating 2x107
NOD8.3 mouse splenocytes with 2x106 irradiated NOD/Lt splenocytes loaded with 1
µmol/L IGRP peptide in RPMI (Life Technologies) supplemented with 10% FCS [285,
286]. After 2 days of incubation, dead cells were removed using a ficoll gradient and live cells were expanded with RPMI supplemented with 10% FCS containing 10 U/mL of IL-
2. Dead cells were removed again after another 2 days and live cells recultured with media containing IL-2 until cells were pointed in morphology indicating they were activated
(typically 2 to 4 days). These were then co-cultured overnight with NOD/Lt islets (10 islets/well, uniform shape and size) preloaded with 200μCi 51Chromium for 2 h. Media alone or media containing 2% Triton X-100 were used as controls for spontaneous
51Chromium release and total 51Chromium content of islets, respectively. The following day 51Chromium release into the harvested supernatant was measured using a gamma
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counter (PerkinElmer). Specific 51Chromium release was measured using the following equation: percent lysis = (test counts per minute − spontaneous counts per minute)/(total counts per minute − spontaneous counts per minute) × 100. 51Chromium release assays have been a standard cytotoxicity assay for decades however in recent years are becoming obsolete to non-radioactive alternatives such as real time assays that utilize fluorescent dyes [287].
2.18 Statistical analysis:
Data are the mean + SEM of three to eight independent experiments. Comparisons between groups were made by one-way ANOVA with Tukey correction, or by unpaired t-test when appropriate. Analysis was performed using version 7 of GraphPad Prism Software.
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Mice with Antioxidants
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3.1 Summary:
Oxidative stress attributed to overproduction of free oxygen radicals is linked to the resultant pathologies of many inflammatory diseases, including both T1D and T2D. In recent years there has been success in reducing T2D associated hyperglycaemia and increasing insulin release from the remaining b-cell mass with the supplementation of antioxidant treated drinking water in murine studies and similar results are currently being shown for T1D. Immune cell signalling studies have highlighted an important role for free oxygen radicals in the production of effector T-cells and reducing these radicals can reduce the pathological consequences of these cells in autoimmune diseases. Free oxygen radicals also inactivate PTPs which dysregulates key immunomodulatory signalling pathways in immune cells and b-cells, contributing to autoimmune diabetes development. Here we evaluated whether the supplementation of autoimmune diabetes susceptible NOD/Lt mice with the mitochondrial specific antioxidant mito-TEMPO in their drinking water could reduce the development of oxidative stress and downstream insulitis and diabetes development. While treatment with the antioxidant was successful in reducing pancreatic oxidised PTP levels, there was no difference in the development or severity of insulitis, generation of circulating effector CD4+ and CD8+ T-cells or resultant diabetes development in our murine studies. Collectively these results suggest that delivery of a mitochondrial specific antioxidant through drinking water alone, while a safe treatment, is non-effective in reducing factors associated with autoimmune diabetes development in mice. Future studies utilizing combination immunomodulatory therapies with antioxidants to restore active PTP levels could provide further insight into the complex interplay between autoreactive immune cells, b-cells and PTPs in autoimmune diabetes.
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3.2 Introduction:
Excessive oxidative stress is recognised to be a component of cellular damage and a pathological feature of a wide spectrum of human disease [288-290]. It occurs in cellular systems when the generation of free radicals such as ROS and RNS outweigh the capacity of reducing enzymes (such as dismutases, peroxidases, and catalases etc.) to reduce them to a less reactive state. Increasing experimental and clinical evidence have shown that enhanced oxidative stress is a central factor in both T1D and T2D and the development of downstream vascular complications associated with these diseases [52, 291-293].
The development of mature effector T-cells requires large amounts of ATP production which is achieved through various metabolic reprograming events [294].
During the early stages of T1D naïve T-cells interact with antigen presenting cells resulting in T-cell receptor (TCR) stimulation triggering the development of autoreactive effector T- cells that target and destroy b-cells. TCR induced phosphorylation events are tightly regulated by PTPs, including PTPN2 and PTPN22 which are genetically associated with
T1D [54, 55, 295-298], to prevent excessive signalling which can result in a loss of tolerance and the development of autoreactive cells [299, 300]. The maturation process of
T-cells requires naïve T-cells to switch to anabolic metabolism pathways including glycolysis and oxidative phosphorylation to generate ATP which generates ROS as a by- product [301, 302]. The generation of ROS, primarily at complex III in the electron transport chain in the mitochondria, is also crucial for the development of effector T-cells through activation of nuclear factor of activated T-cells (NFAT) which induces IL-2 expression and promotes T-cell differentiation [303].
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The invasion of autoreactive T-cells into the islet microenvironment also requires
ROS and RNS production, as well as cytokines such as TNF-a, IL-1b and IFN-g, as they induce expression of the adhesion molecules on endothelial cells, including intracellular adhesion molecule 1 (ICAM-1) and P-selectin, required for the autoreactive cells to attach and transverse the vascular endothelium into the islet [304, 305]. These factors are produced by macrophages in the islet microenvironment resulting in an enhanced inflammatory setting, further recruiting more circulating T-cells to the islet [306, 307].
TNF-a, IL-1b and IFN-g activate the NF-kB and STAT1 signalling pathways in b-cells which further enhances oxidative stress through the activation of iNOS which leads to the production of nitrous oxide species which directly damages the cell [308]. b-cells also inherently express low levels of antioxidant enzymes, such as superoxide dismutase, making them more sensitive to the negative cellular effects of ROS, RNS and oxidative stress accumulation [309, 310].
Previously we have shown that autoimmune infiltration results in higher levels of oxidative stress in the islets of NOD/Lt mice in comparison to NODPI islets, as shown by elevated tyrosine nitrosylation in the islets of infiltrated NOD/Lt islets [53]. NOD/Lt mice showed enhanced levels of oxidised PTPs in their pancreata which lead to enhanced IFN- g induced death of isolated islets and human b-cells in vitro. Deletion of the antioxidative enzyme GPx1 resulted in enhanced IFN-g induced islet death which could be reversed with supplementation of the antioxidant N-Acetyl Cysteine (NAC) in vitro suggesting that oxidative stress had a role in IFN-g induced islet demise. PTPN2 also negatively regulates
IFN-g induced death through the pro-apoptotic BH3-only protein Bim in INS-1E cells,
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primary rat b-cells and dispersed human islet cells in vitro [54, 55]. Recently it was shown that the female offspring of NOD/Lt mice supplemented with daily injections of NAC during pregnancy and lactation as well as female mice treated during infancy to adulthood had reduced oxidative stress (as determined by lipid peroxidation), spontaneous insulitis and diabetes development, highlighting a protective role for antioxidant treatment for autoimmune diabetes in vivo [311].
As PTPs are inactivated as oxidative stress and free radical production are induced during the development of autoimmune diabetes, here we wished to test whether the finding that antioxidants could protect islets from oxidative stress linked death in vitro could be transferred to an in vivo model of autoimmune diabetes with oral delivery, providing a less invasive administration than injections [311]. We hypothesised that supplementing NOD/Lt mice with antioxidants through their drinking water would reduce
PTP oxidation and the severity of insulitis and development of autoimmune diabetes. We show that while antioxidant treatment did reduce oxidation of PTPs in the pancreata of
NOD/Lt mice, there was no effect on the resulting insulitis or development of autoimmune diabetes.
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3.3 Results:
3.3.1 Antioxidant treatment in drinking water reduces PTP oxidation in NOD/Lt
mice:
Oxidative stress accumulation in NOD/Lt mouse islets leads to PTP oxidation which was implicated in enhanced cytokine induced islet death in vitro [53]. We therefore evaluated whether treatment of NOD/Lt mice with antioxidants could decrease pancreatic oxidised
PTP levels in vivo, indicating decreased oxidative stress and restoration of cell signalling regulation by PTPs. We decided to test the popular antioxidant NAC which has been shown to reduce oxidative stress and diabetes development in NOD/Lt mice with daily injections
[53, 311] and the mitochondrial targeted mito-TEMPO antioxidant. NAC is an effective free radical scavenger due to its ability to replenish the glutathione antioxidant in the cell and being a thiol-based molecule, it is stable and commercially cheap [312]. Mito-TEMPO is a mitochondrial specific scavenger of superoxide radicals due to its ability to translocate and accumulate several hundred-fold in the mitochondria intermembrane space [313].
To test the effectiveness of these antioxidants we supplied littermates of 6 week old female NOD/Lt mice with drinking water containing NAC for 8 weeks or mito-TEMPO for 14 weeks. Age-matched untreated female NOD/Lt mice were used as controls. At the end of the treatment period, pancreata were homogenised for immunoblotting of oxidised
PTPs as a qualitative indicator of oxidative stress. In both the control groups of NOD/Lt mice there were bands showing PTP oxidation at ~65kDa, 50kDa and 40kDa (Fig 3.1A), similar to what we had seen previously [53]. In both antioxidant supplemented groups there was a reduction in the levels of oxidised PTPs in comparison to the controls, with a more pronounced reduction in the mito-TEMPO treated group (Fig 3.1A, right). As the mito-
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TEMPO antioxidant was more effective at reducing PTP oxidation and mitochondrial derived free radicals have an important role in T-cell development and b-cell function, we decided to perform the following experiments with mito-TEMPO.
Figure 3.1: Western blot for pancreatic oxidised PTPs in antioxidant treated
NOD/Lt mice.
(A) Western blot showing oxidised PTP expression in NOD/Lt mouse pancreatic homogenates treated with the NAC or mito-TEMPO antioxidant. Mice were treated with
1mg/mL NAC (from 6 weeks to 14 weeks of age, left immunoblot) or 1mM mito-TEMPO
(from 6 weeks to 20 weeks of age, right immunoblot). Quantification to the right represent oxidised PTP densitometry (of the 50kDa bands) after correction for b-actin. Results are means ± SEM of two to three independent experiments. Statistical significance is shown as ***P < 0.001 using an unpaired student’s T-test.
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3.3.2 Mito-TEMPO in drinking water does not affect insulitis development in
NOD/Lt mice:
We next examined whether decreasing PTP oxidation in the pancreata of NOD/Lt mice with mito-TEMPO could reduce the severity of insulitis. Female litter mates were divided into two groups and were supplied with mito-TEMPO in drinking water from 6 weeks of age until 20 weeks of age and their pancreata were resected for insulitis scoring. At 6 weeks of age, NOD/Lt mice have minimal T-cell infiltration in the islets, and this increases over the time period of treatment. Most mice in our colony remain pre-diabetic at 20 weeks of age. No statistical difference in insulitis severity between the two groups of mice (with roughly 50% of scored islets showing infiltration) was calculated (Fig. 3.2A-C), however there were four mice in the mito-TEMPO treated group that showed virtually no insulitis
(T2, T6, T7 & T9, Fig. 3.2A).
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Figure 3.2: Insulitis analysis of 20 week old mito-TEMPO supplemented NOD/Lt mice. (A&B) Female NOD/Lt mice were supplied with 1mM mito-TEMPO in drinking water from 6 weeks to 20 weeks of age and three levels of each pancreata were blind scored by
H&E staining (0-4, : 0 = no islet infiltration, 1 = peri-islet infiltration (0-25%), 2 = extensive peri-islet infiltration (25- 50%), 3 = intra-islet infiltration (50-75%), 4 = extensive intra-islet infiltration (>75%) or total islet destruction) represented as a percentage bar graph. (A) shows individual mice and (B) shows pooled data for all mice.
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(C) Overall insulitis score for each treatment group. Results are represented as the overall score ± S.E.M. of 215 vehicle treated islets and 320 mito-TEMPO treated islets.
As insulitis typically begins at 4 weeks of age in female NOD/Lt mice beginning with infiltration of myeloid cells [23, 307], and oxidative inactivation of PTPs and oxidative stress at this time point may be important in promoting immune cell activation, we next evaluated whether mito-TEMPO delivered in drinking water at 4 weeks could reduce insulitis severity. We divided littermates of female NOD/Lt mice after weaning and treated with mito-TEMPO in their drinking water until they were 12 weeks of age and then resected their pancreata for insulitis scoring. There was no significant difference in insulitis severity between the mito-TEMPO treated mice and control group (Fig. 3.3).
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Figure 3.3: Insulitis analysis of 12 week old mito-TEMPO supplemented NOD/Lt mice. (A&B) (A&B) Female NOD/Lt mice were supplied with 1mM mito-TEMPO in drinking water from 4 weeks to 12 weeks of age and three levels of each pancreata were blind scored by insulin staining (0-4, : 0 = no islet infiltration, 1 = peri-islet infiltration (0-25%), 2 = extensive peri-islet infiltration (25- 50%), 3 = intra-islet infiltration (50-75%), 4 = extensive intra-islet infiltration (>75%) or total islet destruction) represented as a percentage bar graph. (A) shows individual mice and (B) shows pooled data for all mice.
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(C) Overall insulitis score for each treatment group. Results are represented as the overall score ± S.E.M. of 557 vehicle treated islets and 553 mito-TEMPO treated islets.
3.3.3 Mito-TEMPO treated drinking water does not affect T-cell development or
activity in NOD/Lt mice:
Mitochondrial derived ROS are important in T-cell maturation and PTP inactivation can lead to aberrant T-cell proliferation [300], therefore we examined whether the number of
T-cells or the levels of their activation markers were altered with the treatment of mito-
TEMPO. We isolated the spleens, draining pancreatic lymph nodes and non-draining inguinal lymph nodes from the previous group of mice that were treated from 4-12 weeks of age with mito-TEMPO.
First, we analysed the populations of CD3+ T-cells that were CD8+ and CD4+ in each of the organs. The number and percentages of CD3+CD8+ and CD3+CD4+ was not significantly altered with the addition of mito-TEMPO treated water (Fig 3.4). Next to study the activation state of T-cells we examined the expression of CD69+, CD44+ and PD-
1+, all surface markers used to distinguish activated, antigen-experienced cells from naïve
T-cells [314-316]. CD69, CD44 and PD-1 were expressed on all populations of CD3+CD8+ and CD3+CD4+ T-cells in all organs, with no significant difference in mean fluorescence intensity (MFI) with the addition of mito-TEMPO treated drinking water (Fig 3.4).
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A
Vehicle Mito-TEMPO
Inguinal Lymph Nodes Lymph Inguinal
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C B No. CD3+CD4+No. CD3+CD4+ Cells Cells No. CD3+CD8+No. CD3+CD8+ Cells Cells
2×106 2×106 600000 600000 Vehicle Vehicle Vehicle Vehicle Mito-TempoMitoMito-Tempo-TEMPO Mito-TempoMito-TEMPOMito-Tempo 1×106 1×106 400000 400000 No. Cells No. Cells 500000 500000 No. Cells 200000 No. Cells 200000
0 0 0 0 Spleen SpleenPLN PLNILN ILN Spleen SpleenPLN PLNILN ILN
D % CD3+CD4+% CD3+CD4+ Cells Cells E % CD3+CD8+% CD3+CD8+ Cells Cells
80 80 30 30 Vehicle Vehicle Vehicle Vehicle Mito-TempoMito-Tempo 60 60 Mito-TEMPO MitoMito-Tempo-TEMPOMito-Tempo 20 20
40 40 % Cells % Cells % Cells No. Cells 10 No. Cells 10 20 20
0 0 0 0 Spleen SpleenPLN PLNILN ILN Spleen SpleenPLN PLNILN ILN
F CD3+CD4+CD69+CD3+CD4+CD69+ G CD3+CD8+CD69+CD3+CD8+CD69+
600 600 400 400 Vehicle Vehicle Vehicle Vehicle Mito-TempoMito-Tempo Mito-TempoMito-Tempo Mito-TEMPO 300 300 Mito-TEMPO 400 400
200 200
200 200 CD69 (MFI) CD69 (MFI) CD69 (MFI) CD69 (MFI) 100 100
0 0 0 0 Spleen SpleenPLN PLNILN ILN Spleen SpleenPLN PLNILN ILN
H CD3+CD4+CD44+CD3+CD4+CD44+ I CD3+CD8+CD44+CD3+CD8+CD44+
10000 10000 5000 5000 Vehicle Vehicle Vehicle Vehicle 8000 8000 Mito-TempoMitoMito-Tempo-TEMPO 4000 4000 Mito-TempoMito-TEMPOMito-Tempo
6000 6000 3000 3000
4000 4000 2000 2000 CD44 (MFI) CD44 (MFI) CD44 (MFI) CD44 (MFI) 2000 2000 1000 1000
0 0 0 0 Spleen SpleenPLN PLNILN ILN Spleen SpleenPLN PLNILN ILN K J CD3+CD4+PD-1+CD3+CD4+PD-1+ CD3+CD8+PD-1+CD3+CD8+PD-1+
10000 10000 4000 4000 Vehicle Vehicle Vehicle Vehicle 8000 8000 Mito-TempoMito-Tempo Mito-TempoMito-Tempo Mito-TEMPO 3000 3000 Mito-TEMPO 6000 6000 2000 2000 PD-1 PD-1 4000 4000 PD-1 PD-1 1000 1000 2000 2000 71 0 0 0 0 Spleen SpleenPLN PLNILN ILN Spleen SpleenPLN PLNILN ILN Chapter 3: Targeting Oxidative Stress and Autoimmune Diabetes in NOD/Lt Mice with Antioxidants
Figure 3.4: T-cell analysis of 12 week old mito-TEMPO supplemented NOD/Lt mice. (A) Flow cytometry analysis and gating strategy representation. (B-K) T-cell analysis of the spleen, pancreatic lymph nodes and inguinal lymph nodes of female NOD/Lt mice supplemented with 1mM mito-TEMPO treated drinking water from 4 to 12 weeks of age.
CD4+ and CD8+ number and percentage (B-E) and the levels of CD69 (F&G), CD44
(H&I) and PD-1 (J&K) were analysed by flow cytometry. Quantifications represent the number of events or mean fluorescent intensity (MFI, represented by histograms) for each parameter. Results are scatterplots ± S.E.M. of six independent experiments, each dot representative of a single mouse. Statistical analysis was performed with an unpaired student t-test for each organ.
3.3.4 Mito-TEMPO treated drinking water does not affect diabetes transferred by
NOD/Lt mice:
To finally observe if delivering mito-TEMPO in drinking water has any effect on autoimmune diabetes development we performed an adoptive transfer assay into immunodeficient NOD/Rag1-deficient mice. 6-8 week old female NOD/Rag littermates were divided into two groups and one was supplied with water containing mito-TEMPO for two weeks before 5x106 splenocytes from diabetic female NOD/Lt mice were adoptively transferred through intravenous tail vein injection into both groups and then monitored for diabetes development. The pre-treated mito-TEMPO mice received continual antioxidant supplementation throughout the monitoring period. Both groups developed diabetes between approx. 40 days and 60 days post transfer at the same rate
(Fig. 3.5).
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A
100 Vehicle Mito-Tempo
50 Diabetic (%)
0 0 20 40 60 80 Days Post Transfer
Figure 3.5: Diabetes incidence of mito-TEMPO supplemented NOD/Rag1 mice. (A) 6-8 week old female NOD/Rag1 mice were supplemented with 1mM mito-TEMPO treated drinking water or vehicle for 2 weeks and then adoptively transferred with 5x106 diabetic female NOD/Lt splenocytes and monitored for diabetes development with urine glucose strips and conformational blood glucose tests. Results are represented as a survival curve of six mice per group.
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3.4 Discussion:
The results demonstrate that supplementation of drinking water with the mito-TEMPO antioxidant can partially reduce the oxidation of PTPs in the pancreata of NOD/Lt mice, however, does not affect T-cell phenotype, insulitis or autoimmune diabetes development in vivo.
T-cells are very “energetic” cells and require large amounts of ATP to be produced in short periods of time during development and expansion. Naïve T-cells primarily rely on oxidative phosphorylation to generate ATP but after activation they switch to glycolysis to sustain energy requirements [317]. However, ROS derived from oxidative phosphorylation are still essential in TCR signalling post activation [303, 318]. TCR activation results in an influx of calcium which interacts with calcineurin to activate NFAT to induce IL-2 expression, required for CD4+ and CD8+ T-cell expansion [319]. Interestingly defects in mitochondrial complex III, the main source of mitochondrial ROS production, decreases
IL-2 expression as ROS amplifies the calcineurin-NFAT signalling pathway [303]. ROS derived from mitochondrial complex I also further regulates IL-2 expression in the form of hydrogen peroxide through activation of the MAPK induced NF-kB signalling pathway, further highlighting the importance of ROS in T-cell expansion in vitro [318, 320-322].
Murine models have also highlighted the importance of ROS in modulating effector
T-cell function and development. Superoxide dismutase (SOD) is an enzyme responsible for catalysing free oxygen radicals into either oxygen or hydrogen peroxide, which can be further reduced into water molecules. Treatment of OT-1 ovalbumin-specific CD8+ T-cells with SOD mimetics reduces proliferation, cytokine production and lysis in vitro. SOD
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mimetics also induce CD4+ T-cell hyporesponsiveness and reduce effector function of
NOD/Lt and diabetogenic BDC2.5 TCR transgenic T cells [43, 323]. Supporting these findings, transfer of BDC2.5 CD4+ T-cells into immunodeficient mice treated with SOD mimetics blunted T-cell proliferation and inflammatory cytokine production [324].
The NOD.Ncf1m1J mouse expresses a dominant negative mutation of the p47 subunit of the NADPH oxidase (NOX) enzyme family which is required for ROS generation upon assembly of the enzyme at the cellular membrane, an alternate source of
ROS to the mitochondria [325, 326]. NOD/Lt mice lacking NOX-derived superoxide are protected from spontaneous diabetes development (~70% free from diabetes development)
[325]. Polyclonal stimulation in vitro showed a reduced inflammatory Th1 response and heightened Th17 response of NOD.Ncf1m1J CD4+ T-cells and reduced IFN-g production by
CD8+ T-cells [327]. Levels of naïve, effector and memory T-cells were similar between
NOD/Lt and NOD.Ncf1m1J mice which suggested that NOX-derived ROS were required for proinflammatory cytokine production and an effector immune cell response independent of circulating immune cell numbers.
PTPs genetically associated with T1D, namely PTPN2 and PTPN22, also affect the function and development of autoreactive T-cells through regulation of TCR signalling.
PTPN2 deficient T-cells display enhanced activation and proliferation through negative regulation of the lymphocyte-specific protein tyrosine kinase (LCK) adaptor protein of the
TCR [300]. Indeed, PTPN2 deficient CD8+ T-cells cross primed with b-cell self-antigens escape tolerance and result in b-cell destruction in the RIP-mOVA mouse model of autoimmune diabetes [328]. PTPN2 also negatively regulates IFN-g induced apoptosis in b-cells through modulation of the BH3-only apoptotic protein Bim [54, 55]. The missense
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C1858T polymorphism for PTP22 is strongly associated with T1D and leads to an arginine to tryptophan substitution (R620W) [295-297, 329, 330]. PTPN22, similarly to PTPN2, negatively regulates TCR signalling through dephosphorylation of LCK as well as x-chain- associated protein kinase 70 (ZAP-70) [331]. The function of the R620W mutation and
PTPN22 in general remain controversial in the development of autoimmune diabetes. In vitro and in vivo studies of T-cell development and function show that the R620W mutation results in gain of function [332, 333], loss of function [334, 335] or abnormal function
[336] upon TCR stimulation. Moreover, overexpression and silencing of PTPN22 have both been shown to attenuate TCR signalling and autoimmune development in the NOD/Lt mouse [337, 338]. Transient PTP oxidation has been reported after TCR stimulation, presumably by a burst in free radical production, and is suggested to be a mechanism to allow a strong initial signal that is then transiently inhibited as activity is restored [339].
Collectively these results show that ROS production, along with pro-inflammatory cytokine expression, act as another important signalling event in the production of effector
T-cells and depression of their production and PTP dysfunction leads to defects in T-cell development and activity.
In the present study we saw no difference between the number of activated T-cells or the ability of these cells to destroy b-cells resulting in insulitis when NOD/Lt mice were treated with the mito-TEMPO antioxidant. We also observed no effect on diabetes development with mito-TEMPO in a transfer model of autoimmune diabetes in NOD/Rag1 mice. The lack of effect on immune cells may be attributed to a barrier effect as mito-
TEMPO is a mitochondrial specific antioxidant where it accumulates in the intermembrane space. As it is organelle specific it would not be able to access cytosolic derived free
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radicals, such as those produced by NOX and iNOS induced by TNF-a, IL-1b and IFN-g, which would be accessed by SOD mimetics [313]. Free radicals are also released into the extracellular matrix during T1D pathogenesis, such as those produced by macrophages, to increase vascular permeability and invasion of circulating T-cells to the islet which would also not be targeted by mito-TEMPO [304, 305]. As mentioned above, mitochondrial complex III derived ROS are important in driving T-cell development through NFAT mediated IL-2 expression, however we did not measure the activity of NFAT or IL-2 and
ROS production with mito-TEMPO treatment in our murine studies which would inform us if the antioxidant had an effect in the mitochondria of T-cells.
The NOD.Ncf1m1J studies showed no difference in circulating effector T-cell numbers, similar to what we observed in the pancreatic lymph nodes and spleens of our antioxidant treated mice. It would be interesting to test the cytokine expression profiles of our CD4+ and CD8+ T-cells, in particular IFN-g and IL-2 production by NOD/Lt derived
T-cells treated with antioxidants in vitro to observe if their expression is blunted or polarised to a Th17 phenotype for example. We also only analysed antigen non-specific
CD8+ and CD4+ T-cell populations in our study which is not directly representational of T- cells involved in autoimmune diabetes. It would be interesting to also examine antigen- specific T-cell levels and activation markers using tetramer staining for b-cell specific peptides such as insulin or GAD [340-342]. As we observed reduced pancreatic PTP oxidation levels with NAC delivery, it would also be of interest to validate the recent study showing reduced autoimmune diabetes development mediated by NAC, except with oral delivery instead of daily injections as a less invasive delivery method [311].
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While our present study with mito-TEMPO showed no improvement in the outcome of autoimmune diabetes in NOD/Lt mice, other studies have observed beneficial effects of targeted antioxidant therapies in clinical studies, murine models of diabetes and vascular disease. The Szeto-Schiller-31 (SS-31) peptide selectively binds to cardiolipin and accumulates in the inner mitochondria membrane [343-345], similar to mito-TEMPO. A recent study showed that leukocytes from T2D patients exhibited elevated ROS concentration, calcium levels and ER stress markers which were all reduced by SS-31 treatment [346]. Furthermore, SS-31 treatment has been shown to reduce diabetic vascular complications and retinal damage associated with renal injury in the streptozotocin and db/db murine models of diabetes [347-349]. Similar protective preclinical results have been recorded using the NOX1/4 inhibitor GKT137831 in the apolipoprotein E deficient (ApoE-
/-) and OVE26 mouse models of diabetic nephropathy [350-352]. A randomised double- blind phase 2 clinical trial with oral delivery of the calcium-channel blocker Verapamil resulted in improved b-cell function and reduced insulin requirements and hypoglycaemic episodes in adults with recent-onset T1D over a 12-month period [353]. These results were attributed to reduced calcium-dependent thioredoxin-interacting protein (TXNIP) expression in b-cells with Verapamil mediated calcium channel blockade [354]. TXNIP is a cellular redox regulator and is the top glucose-induced gene in human islet microarray studies and mouse models have revealed that overexpression promotes b-cell apoptosis whereas deficiency promotes b-cell survival and reduces diabetes incidence [355-359].
Collectively these results suggest that pharmacological inhibition of key oxidative stress modulators in b-cells is an effective strategy to reduce b-cell destruction and diabetes development in murine models of autoimmune diabetes and recent-onset T1D patients.
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PTP dysfunction affects inflammatory signalling cascades in both b-cells and autoreactive T-cells during the development of autoimmune diabetes and oxidative stress accumulation contributes to this through PTP oxidation. As we saw a reduction in PTP oxidation in NOD/Lt mouse pancreata with the use of NAC and mito-TEMPO we would expect some degree of protection from b-cell destruction. While that was not the case in the present study, it would be interesting to repeat these experiments again using clinically validated antioxidants, combining treatment with agonists of key immunomodulatory
PTPs, such as PTPN2 with Mitoxantrone [360], or with T-cell depletion therapies like anti-
CD3 monoclonal antibodies [203] to further dissect the complex interplay between immune cells, b-cells and PTPs.
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cells
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4.1 Summary:
Transient pro-inflammatory cytokine release during innate immune responses is essential for the development of a robust recruitment of adaptive immune cells to clear pathological stimuli and restore tissue homeostasis. Excessive inflammatory cytokine release causes dysregulation in immune responses and can lead to autoimmune disease development such as T1D, rheumatoid arthritis and cancer. Inflammation further dysregulates cytokine signalling through oxidative inactivation of PTPs. PTPN1 was identified as being oxidised in the islets of NOD/Lt mice during T1D development therefore we hypothesised that its inactivation may fuel islet inflammation. In contrast, here we show that inactivation of
PTPN1 protected the NIT-1 b-cell line from cytokine induced death. Inactivation of PTPN1 reduced IFN-g induced STAT1 phosphorylation in NIT-1 cells and isolated NODPI islets.
Downstream transcription of STAT1 induced chemokines, iNOS and MHC-I were also reduced in NODPI islets. Furthermore, inhibition of PTPN1 protected isolated NOD/Lt islets from autoimmune destruction by NOD8.3+ T-cells. Inactivation of PTPN1 reduced
TNF-a and IL-1b induced JNK and c-Jun phosphorylation in NIT-1 cells. Downstream transcription of c-Jun and AP-1 induced iNOS was also reduced in isolated NODPI islets in the presence of a PTPN1 inhibitor. Collectively these results suggest that PTPN1 positively regulates IFN-g, TNF-a and IL-1b signalling in islets and its inactivation protects murine b-cells from immune mediated destruction.
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4.2 Introduction:
T1D is an organ specific autoimmune disease in which self-reactive T-cells destroy insulin- producing β-cells in the pancreas. Islet infiltrating immune cells, including T-cells and macrophages, secrete cytokines that enhance oxidative stress and further enhance immune infiltration. Cytokines released into the islet microenvironment, in particular IFN-γ, TNF-
α and IL-1β can promote β-cell destruction by inducing pro-apoptotic gene expression through phosphorylative signalling [53-55, 79, 80].
IFN-γ activates the STAT1 transcription factor by tyrosine phosphorylation
(Y701), facilitated by receptor-linked JAKs. Once activated, STAT1 dimers are imported to the nucleus and induce gamma-activated site (GAS) gene expression [74], which includes chemokines, iNOS and MHC-I, important for diabetes development in the
NOD/Lt mouse [361, 362]. Indeed, inhibition of STAT1 activity in the NOD/Lt mouse has been shown to protect from insulitis and diabetes development [90, 92, 96].
TNF-α and IL-1b stimulation activates downstream MAPKs including JNK and p38 by dual tyrosine and threonine phosphorylation. Cytokine-stimulated MAPKs, in particular JNKs, are associated with the induction of apoptosis in β-cells through activation of c-Jun dependent gene transcription and post translational modification of anti-apoptotic
BCL-2 proteins [80, 195]. Inhibiting JNK activity has been shown to protect β-cell lines from apoptosis induction in vitro. Anti-apoptotic BCL-2 proteins, such as BCL-2 and
MCL-1, are substrates of JNK [363-367], and upon extended phosphorylation of their BH3 binding domains these proteins are altered in their capacity to bind and inhibit pro- apoptotic BH3-only proteins or targeted for degradation by the proteasome, which predisposes cells to death by apoptosis.
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PTPs are a superfamily of enzymes that tightly regulate tyrosine phosphorylation dependent signalling. These enzymes are among the highest frequency risk alleles genetically associated with T1D, as shown by genome wide association studies (reviewed in [52]). PTPN2 is one of the risk alleles associated with T1D and has been shown to have a pivotal role in IFN-γ induced death of β-cells by negatively regulating downstream pro- apoptotic gene expression [54, 55]. However, the role of PTPs, other than PTPN2, in cytokine signalling regulation remains unknown.
The active site of PTPs are susceptible to oxidative inactivation in the presence of oxidative stress and free radicals. Chronic inflammation, such as insulitis in autoimmune diabetes can result in irreversible inactivation of PTPs and loss of regulation on phosphorylative signalling. Previously, we reported that PTPs are inactivated by inflammation-dependent oxidation in NOD/Lt mouse islets [53]. We also have shown that
PTPN1 is expressed in whole pancreas homogenates of diabetic NOD/Lt mice and that global PTP inactivation enhances cytotoxic cell signalling and gene transcription in b-cell lines and isolated NODPI islets. Here we wished to clarify firstly if PTPN1 is expressed in b-cells and if so what regulation it provides on IFN-g, TNF-a and IL-1b signalling cascades. We hypothesised that PTPN1 negative regulates the IFN-γ/STAT1 signalling cascade similarly to that reported with PTPN2 and global PTP inactivation. However, we demonstrate that PTPN1 positively regulates IFN-g, TNF-a and IL-1b induced signalling and downstream gene transcription in NIT-1 cells and isolated NODPI islets and ultimately protects NIT-1 cells from cytokine induced death, contrary to our hypothesis.
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4.3 Results:
4.3.1 Development of PTPN1 deficient NIT-1 cells:
To examine the role of PTPN1 in regulation of cytokine signalling in b-cells, we first evaluated its expression in islets of NOD/Lt mice and NODPI mice. We isolated islets from mice from 4 to 22 weeks of age and generated protein lysates for analysis. Immunoblot revealed PTPN1 was expressed in both NOD/Lt mouse islets and non-diabetic NODPI islets at similar levels over all ages (Fig. 4.1A). We then confirmed PTPN1 expression in human islet lysates from 6 non-diabetic organ donors (Fig. 4.1B). Consistent with our results, PTPN1 is reportedly expressed in FACS purified human and rat primary b-cells
[368, 369].
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Figure 4.1: Expression of PTPN1 in human and murine islets.
(A) Western blot showing PTPN1 expression in NOD/Lt and NODPI mouse islets. The intensity values of the proteins were corrected by the values of the β-actin loading control and are shown in arbitrary units (A.U.). Results are means ± S.E.M. of four independent experiments. (B) PTPN1 expression in human islets. Samples were acquired from six brain-dead non-diabetic organ donors and subjected to western blotting with antibodies detecting PTPN1 or α-tubulin as loading control. No significance was reported using a one-way ANOVA with Tukey correction.
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To study the effect of PTPN1 on regulation of IFN-g, TNF-a and IL-1b signalling, we utilized the NOD/Lt derived NIT-1 mouse b-cell line and primary NODPI islets. We generated a PTPN1-deficient b-cell line using a CRISPR/Cas9 exon deletion strategy in
NIT-1 cells as these cells are easily transfectable (for strategy refer to methods). We were successful in generating a single PTPN1 deficient NIT-1 cell line (Fig. 4.2A) with no protein of interest detected in comparison to the vector control population (transfected with the Cas9 D10A nickase without gRNA sequences).
Figure 4.2: Western blot for PTPN1 expression in PTPN1 deleted NIT-1 cells.
(A) Schematic of the CRISPR/Cas9 deletion strategy for PTPN1. Western blot demonstrate deletion of PTPN1 from NIT-1 cells. Results are representative of five independent experiments.
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4.3.2 PTPN1 inactivation decreases cytokine induced NIT-1 cell death:
Next we evaluated whether PTPN1 deficiency altered cell death of NIT-1 cells induced by the cytokines IFN-γ, IL-1β and TNF-α. NIT-1 cells are inherently sensitive to TNF-α induced cell death due to a deficiency in the p65/RelA subunit of the NF-kB complex leading to a defective protection response to death receptor signalling which was taken into consideration during viability analysis [80]. Cytotoxicity was initially evaluated by DNA fragmentation through Nicoletti staining and FACS analysis and results were confirmed by cell death quantification through Hoechst-33342/Propidium Iodide immunofluorescence.
Treatment of NIT-1 cells with IFN-γ and IL-1β alone did not affect DNA fragmentation, whereas TNF-α induced DNA fragmentation to ~40% in control NIT-1 cells (Fig. 4.3A-
F). Interestingly PTPN1 deficiency in NIT-1 cells reduced DNA fragmentation induced by
TNF-α alone to ~20% (Fig. 4.3B). The combination of IFN-γ with TNF-α further enhanced
DNA fragmentation in control NIT-1 cells whereas PTPN1 deficiency reduced DNA fragmentation by ~50% (Fig. 4.3A&B). We were able to reproduce the cytoprotective response of PTPN1 deficiency with the combination of IFN-γ with TNF-α using immunofluorescence cell death analysis (Fig. 4.3C&D). Combinations of IFN-γ or TNF-
α with IL-1β had negligible effects between PTPN1 sufficient and deficient NIT-1 cells
(Fig. 4.3E&F). Next using a PTPN1 selective inhibitor [269] we were able to confirm that
PTPN1 inhibition protects NIT-1 cells against IFN-γ and TNF-α induced cell death by
DNA fragmentation analysis (Fig. 4.3G). Interestingly the protective response seen against
TNF-α alone was not observed with the PTPN1 inhibitor.
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Figure 4.3: Cytotoxicity analysis of PTPN1 deficient and inhibited NIT-1 cells.
(A-D) PTPN1 deletion reduces cytokine induced death/DNA fragmentation of NIT-1 cells.
(A&B) DNA fragmentation of PTPN1 KO NIT-1 cells was assessed by Nicoletti staining of single cell suspensions and quantification of the sub-G1 phase of the cell cycle after 48 h of TNF-α and IFN-γ treatment. (C&D) PTPN1 KO NIT-1 cells were treated with TNF-
α and IFN-γ for 48 h and cell death was assessed by the ratio of Hoechst-33342 (blue, viable) to propidium iodide (red, dead) nuclei. Scale bar represents 10μm. (E&F) PTPN1
KO NIT-1 cells were treated with (E) IFN-γ or (F) TNF-α in combination with IL-1β for 88
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48 h and DNA fragmentation was assessed by Nicoletti staining of single cell suspensions and quantification of the sub-G1 phase of the cell cycle. (G) PTPN1 inhibited NIT-1 cells were treated with IFN-γ and TNF-α for 48 h and DNA fragmentation was assessed by
Nicoletti staining of single cell suspensions and quantification of the sub-G1 phase of the cell cycle. Results are means ± S.E.M. of four to eight independent experiments. Statistical significance is shown as *P < 0.05, **P < 0.01, ***P < 0.001 using a one-way ANOVA with Tukey correction.
Next to evaluate if NIT-1 cells were dying by apoptosis we analysed the cleavage of caspase-3 after stimulation with IFN-γ and TNF-α. Stimulation with TNF-α alone or IFN-
γ with TNF-α significantly increased caspase-3 cleavage in NIT-1 cells, however deletion of PTPN1 reduced cleavage to basal levels (Fig. 4.4A). Collectively these results suggest that PTPN1 has a prominent role in positively regulating IFN-γ and/or TNF-α signalling in NIT-1 cells resulting in cytokine induced cytotoxicity.
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Figure 4.4: Cytokine induced caspase-3 cleavage in PTPN1 deficient NIT-1 cells.
(A) PTPN1 knockout NIT-1 cells were treated with TNF-α and IFN-γ for 24 h and subjected to western blotting for cleaved caspase-3 and β-actin as loading control.
Quantification represents cleaved caspase-3 densitometry after correction for β-actin.
Results are means ± S.E.M. of three independent experiments. Statistical significance is shown as ***P < 0.001 using a one-way ANOVA with Tukey correction.
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4.3.3 PTPN1 inactivation reduces IFN-γ induced gene expression in NIT-1 cells and
NODPI islets.
As PTPN1 inhibition in vitro consistently resulted in reduced cytokine induced NIT-1 cell death, we hypothesized that PTPN1 is involved in regulation of IFN-γ signalling. IFN-γ potently activates the STAT1 transcription factor through tyrosine phosphorylation and the transportation of STAT1 homodimers to the nucleus resulting in gene transcription. To assess the impact of PTPN1 deficiency on IFN-γ signalling, we stimulated PTPN1 sufficient and deficient NIT-1 cells with IFN-γ over 24 hours and generated lysates for analysis. Immunoblot revealed that PTPN1 deficiency reduced IFN-γ induced STAT1 phosphorylation by ~50% over the 24-hour period (Fig. 4.5A). We then verified this result by studying the STAT1 phosphorylation kinetics in NIT-1 cells treated with the PTPN1 inhibitor. Immunoblot confirmed that PTPN1 inhibition reduced IFN-γ induced STAT1 phosphorylation in NIT-1 cells (Fig. 4.5B). To observe if this effect was conserved in islets, we isolated NODPI mouse islets and treated them with the PTPN1 inhibitor and IFN-γ for
8 hours. Immunoblot confirmed that inhibition of PTPN1 reduced STAT1 phosphorylation by ~50% in contrast to the vehicle treated control islets (Fig. 4.5C). Collectively these results suggest that PTPN1 positively regulates IFN-γ induced STAT1 signalling in NIT-
1 cells and NODPI islets in vitro.
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Figure 4.5: IFN-γ induced STAT1 signalling in PTPN1 deficient and inhibited NIT-
1 cells and PTPN1 inhibited islets.
(A-C) PTPN1 positively regulates IFN-γ signalling in β-cell lines and NODPI islets. (A)
PTPN1 knockout NIT-1 cells and (B) NIT-1 cells and (C) NODPI islets inhibited for
PTPN1 were treated with a time course of IFN-γ (24 h for NIT-1 cells and 8 h for NODPI islets) and subjected to western blotting for p-STAT1, PTPN1 and β-actin as loading control. Quantification below represents p-STAT1 densitometry after correction for β- actin. Results are means ± S.E.M. of four to seven independent experiments. Statistical significance is shown as *P < 0.05, **P < 0.01, ***P < 0.001 using a one-way ANOVA with Tukey correction.
IFN-γ induced STAT1 signalling results in transcription of numerous pro-inflammatory and pro-apoptotic genes reportedly involved in b-cell demise including iNOS and the T-
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cell recruiting chemokines CXCL9 and CXCL10 [74]. We therefore evaluated by quantitative PCR if PTPN1 inhibition affected downstream transcription of these products in isolated NODPI islets. 8 hours of IFN-γ stimulation induced expression Nos2, Cxcl9 and
Cxcl10, however PTPN1 inhibition reduced these to almost basal levels (Fig. 4.6A-C).
Real-time qPCR confirmed that this effect was independent of Stat1 expression as both the vehicle control and inhibitor treated groups had comparable expression levels (not shown).
Ptpn1 gene expression was reduced to basal levels with PTPN1 inhibition (Fig. 4.6D).
These data suggest that PTPN1 positively regulates upstream IFN-γ induced STAT1 phosphorylation and downstream gene expression.
Figure 4.6: IFN-γ induced gene expression in PTPN1 inhibited NODPI islets.
(A-D) NODPI islets inhibited for PTPN1 were treated with IFN-γ for 8 h and subjected to quantitative PCR for (A) Cxcl9, (B) Cxcl10, (C) Nos2 and (D) Ptpn1. Quantifications
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represent gene expression relative to Actb using the double dCT analysis (left) and the true
RNA levels using the dCT method (right). Results are means ± S.E.M. of four independent experiments. Statistical significance is shown as *P < 0.05, **P < 0.01, ***P < 0.001 using a one-way ANOVA with Tukey correction.
4.3.4 PTPN1 inactivation reduces IFN-γ induced MHC-I expression on β-cells and
CD8+ T-cell mediated death of NODPI islets.
IFN-γ induces STAT1 dependent MHC-I expression on β-cells and the presence of this antigen presentation complex is critical for autoimmune CD8+ T-cell recognition and destruction of β-cells in NOD/Lt mice [361]. Ablation of MHC-I protects β-cells from T- cell mediated death as the capacity for interaction between the cells is lost. As PTPN1 was found to positively regulate expression of downstream transcription products of STAT1 we evaluated whether PTPN1 inactivation altered IFN-γ induced MHC-I expression on
NIT-1 cells and NODPI β-cells. We treated NIT-1 cells and isolated NODPI islets with
IFN-γ and the PTPN1 inhibitor and measured surface MHC-I expression on b-cells by flow cytometry. IFN-γ induced the expression of MHC-I on all cell types and addition of the inhibitor reduced expression by ~50% on NIT-1 cells and ~20% on the NODPI β-cells
(Fig. 4.7A&B).
As PTPN1 inhibition reduced IFN-γ induced expression of MHC-I on isolated
NODPI β-cells we next tested whether this protected β-cells from autoreactive CD8+ T-cell mediated death. To test this, we performed a 51Cr release assay of PTPN1 inhibited NOD/Lt islets with autoreactive NOD8.3 CD8+ T-cells. NOD/Lt islets treated with the PTPN1 inhibitor were protected from NOD8.3 T-cell induced destruction by ~50% in comparison
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to control NOD/Lt islets (Fig. 4.7C). Our results demonstrate that PTPN1 positively
regulates IFN-γ induced MHC-I expression on β-cells and inhibition can protect islets from
autoimmune destruction.
A B
Research W J STANLEY and others PTPN1 and PTPN6 modulate 59:4 333 cytokine signalling in β-cells
C
* *
Figure 5 PTPN1 inactivation reducesFigure IFN-γ-induced 4.7: MHC-IMHC expression-I expression and protects and islets autoimmune from autoimmune destruction destruction. analysis (A, B and C) of PTPN1 PTPN1 positively regulates IFN-γ-induced MHC-I expression on β-cell lines and primary islets. PTPN1 inhibited MIN6 cells (A), NIT-1 cells (B) and NOD PI islets (C) were treated with IFN-γ (24 h for MIN6 and NIT-1 cells, 48 h for NOD PI islets) and MHC-I expression was assessed by fuorescently activated cell sorting. Quantifcations represent the Mean Fluorescentinhibited Intensity islets. (MFI) of MHC-I. Results are means ± S.E.M. of four independent experiments, **P < 0.01, ***P < 0.001. (D) PTPN1 inhibition protects islets from autoimmune destruction by NOD8.3 CD8+ T-cells. Islets were isolated from 4 to 6 week-old NOD/Lt mice and were treated with the PTPN1 inhibitor (100 µM) or vehicle overnight and were then loaded with 51Cr. These islets were then co-cultured with activated NOD8.3 CD8+ T-cells overnight at an effector:target(A&B) PTPN1 ratio of 20:1. positively Result is representativeregulates IFN of two-γ induced independent MHC experiments-I expression and shows on 51 CrNIT release-1 cells measurement and in triplicate. NODPI b-cells. PTPN1 inhibited (A) NIT-1 cells and (B) NODPI islets were treated with islets were treated with IFN-γ and the vehicle control or the TNF-α pathway and PTPN1 positively affects IFN-γ PTPN1 inhibitor and flow cytometry was performed to signalling. Furthermore, we showed that inactivation IFN-γ (24 h for NIT-1 cells and 48 h for NODPI islets) and MHC-I expression was assessed measure MHC-I expression. IFN-γ-induced the expression of each PTP could either predispose or protect β-cells of MHC-I on all cell types and addition of the inhibitor to death. by flow cytometry. Histograms above represent the MFI of each condition. Quantifications reduced expression by ~50% on MIN6 and NIT-1 cells and Studies related to the role of PTPN6 in T1D are ~20% on the islets (belowFig. 5A represent, B and C the). Moreover, Mean Fluorescent NOD Intensitylimited to (MFI) nephropathy of MHC- I. development Results are means (Denhez ± et al. islets treated with the PTPN1 inhibitor were protected 2015). PTPN6-deficient mice (motheaten mice) display a from NOD8.3 T-cell-induced destruction in comparison prominent95 autoimmune phenotype with development of to control islets, as measured by specific 51Cr release granulocytic skin lesions, arthritis, multiple autoantibodies (Fig. 5D). Our results demonstrate that PTPN1 regulates and succumb to lethal pneumonitis at the age of 2–3 weeks IFN-γ signalling in β-cells and islets and has potential as a (Green & Shultz 1975, Abram et al. 2013). The motheaten
Journal of Molecular Endocrinology therapeutic target for novel anti-inflammatory drugs. viable mouse, which expresses PTPN6 with ~50% reduced catalytic activity, display increased levels of TNF-α in the lung and serum (Thrall et al. 1997). When treated with a Discussion soluble TNF-α receptor 1 (sTNFR1), these mice display a Pancreatic β-cells are sensitive to the cytotoxic effects of 2-fold increase in lifespan (Su et al. 1998), highlighting TNF-α, IFN-γ and IL-1β through activation of the intrinsic the requirement for TNF-α in the pathogenesis of the apoptotic cascade (Thomas et al. 2006, Gurzov et al. 2009, autoimmunity caused by loss of PTPN6. Here, we describe Gurzov & Eizirik 2011, Moore et al. 2011, Santin et al. a mechanism by which PTPN6 inactivation promotes 2011). PTPN2 was the first example of PTP inactivation TNF-α-induced β-cell death by hyperactivation of JNK and sensitizing β-cells to death through hyperactivation of degradation of BCL-2 and MCL-1. PTPN6 has previously IFN-γ-induced STAT1-dependent BIM induction (Moore been shown to negatively regulate JNK phosphorylation et al. 2009, Santin et al. 2011). In addition, we showed induced by 4-hydroxy-2-nonenal in HBE1 cells (Rinna & that chronic oxidative stress developed during insulitis Forman 2008) as well as JNK-dependent IGF-1-induced in the NOD mouse inactivated PTPN2 and PTPN6 and MCF-7 breast cancer cell proliferation (Amin et al. 2011). enhanced IFN-γ-dependent STAT1 signalling, culminating JNK activity has also been linked to β-cell death in various in islet death by BIM induction (Stanley et al. 2015). These in vitro studies using IL-1β (Bonny et al. 2001, Gurzov et al. previous studies showed a link for in vivo PTP inactivation 2009). However, the activation of IL-1β-induced JNK was enhancing the sensitivity of β-cells to cytokine-induced slightly lower in PTPN6-deficient cells, which suggests that destruction. In the present study, we demonstrated that the role of PTPN6 in JNK signalling regulation is cytokine PTPN6 and PTPN1 have an important role in cytokine dependent. Inactivation of JNK2 also protects NOD.SCID signalling regulation. Thus, PTPN6 negatively regulates mice from diabetes development by adoptive transfer of
http://jme.endocrinology-journals.org © 2017 Society for Endocrinology Published by Bioscientifca Ltd. DOI: 10.1530/JME-17-0089 Printed in Great Britain Chapter 4: Role of PTPN1 in Regulation of Cytokine Signalling in Pancreatic b-cells
S.E.M. of four independent experiments. Statistical significance is shown as **P < 0.01,
***P < 0.001 using a one-way ANOVA with Tukey correction. (C) PTPN1 inhibition protects islets from autoimmune destruction by NOD8.3 CD8+ T-cells. Islets were isolated from 4 to 6-week-old NOD/Lt mice and were treated with the PTPN1 inhibitor (100μM) or vehicle overnight and were then loaded with 51Cr. These islets were then co-cultured with activated NOD8.3 CD8+ T-cells overnight at an effector:target ratio of 20:1. Result is representative of triplicate independent experiments and shows specific 51Cr release measurement. Statistical significance is shown as *P < 0.05 using an unpaired student t- test.
4.3.5 PTPN1 positively regulates TNF-α induced MAPK signalling and gene
expression in NIT-1 cells and NODPI islets:
As PTPN1 deletion reduced susceptibility of NIT-1 cells to TNF-a induced cell death, next we studied if this was the result of a positive regulatory role for PTPN1 in this signalling cascade (Fig 4.3). To evaluate whether PTPN1 positively regulates TNF-α signalling in
NIT-1 cells we studied the phosphorylation kinetics of tyrosine activated proteins over a time course of 24 hours. The MAPKs JNK and p38 are activated by dual phosphorylation of tyrosine and threonine residues and are the only two proteins activated by tyrosine phosphorylation in the TNF-a signalling pathway. We treated PTPN1 sufficient and deficient NIT-1 cells with TNF-α and generated lysates for analysis. Immunoblot revealed that JNK and p38 were activated in NIT-1 cells over the 24 hour period, however, MAPK signalling was completely ablated with PTPN1 deficiency (Fig. 4.8A&B). JNK activates the c-Jun kinase through serine phosphorylation which is responsible for downstream
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transcription, so next we evaluated c-Jun phosphorylation. Using the same lysates, we observed that c-Jun activation was completely ablated in PTPN1 deficient NIT-1 cells (Fig.
4.8C). These results suggest that PTPN1 positively regulates tyrosine phosphorylation events in the TNF-α signalling cascade, however the direct substrates remain unknown.
A B C
Figure 4.8: TNF-α induced MAPK phosphorylation in PTPN1 deficient NIT-1 cells.
PTPN1 knockout NIT-1 cells (A-C) were treated with a time course of TNF-α for 24 h and subjected to western blotting for (A) p-JNK, (B) p-p38, (C) p-c-Jun and β-actin.
Quantification below represents p-JNK, p-p38 and p-c-Jun densitometry after correction for β-actin. Results are means ± SEM of four independent experiments. Statistical significance is shown as *P < 0.05, **P < 0.01, ***P < 0.001 using a one-way ANOVA with Tukey correction.
Phosphorylated c-Jun activates the AP-1 transcription factor which transcribes a variety of downstream signalling molecules associated with inflammation including iNOS, CCL2,
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CCL5 and CXCL1 [42, 72]. As PTPN1 positively regulated JNK induced c-Jun activation we evaluated whether PTPN1 inhibition in primary NODPI islets reduced TNF-α induced expression of these transcripts. qPCR revealed that NODPI islets treated with TNF-α for 8 hours with or without the PTPN1 inhibitor had enhanced levels of Nos2, Ccl2 and Cxcl1 transcripts, however Ccl5 RNA levels were unaffected (Fig. 4.9A-D). PTPN1 inhibition reduced the relative expression of TNF-α induced Nos2, Ccl2 and Cxcl1 by ~50% however only true Nos2 RNA levels reflected this significant effect (a relative reduction in Ccl5 expression was observed with PTPN1 inhibition, however as RNA levels were not significantly affected this result is discounted) (Fig. 4.9A-D). TNF-α also significantly reduced the relative expression of Ptpn1 by ~50% with PTPN1 inhibition, however this was also not reflected in true RNA levels (Fig. 4.9E).
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Figure 4.9: TNF-α induced gene expression in PTPN1 inhibited NODPI islets.
(A-E) NODPI islets inhibited for PTPN1 were treated with TNF-α for 8 h and subjected to quantitative PCR for (A) Nos2, (B) Cxcl1, (C) Ccl2, (D) Ccl5 and (E) Ptpn1.
Quantifications represent gene expression relative to Actb using the double dCT analysis
(left) and the true RNA levels using the dCT method (right). Statistical significance is shown as *P < 0.1, **P < 0.01, ***P < 0.001 using a one-way ANOVA with Tukey correction.
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4.3.6 PTPN1 positively regulates IL-1β induced MAPK signalling and gene
expression in NIT-1 cells and NODPI islets:
IL-1b and TNF-α activate similar downstream signalling pathways through different upstream receptor interacting protein complexes. One of the major similarities in the two signalling pathways is the MAPK pathway. We therefore evaluated whether PTPN1 regulates IL-1b induced JNK and c-Jun activation. To do this we treated PTPN1 sufficient and deficient NIT-1 cells with IL-1b over a 1 hour time course as IL-1b is a fast-acting cytokine in comparison to TNF-α [370]. IL-1b stimulated both JNK and c-Jun phosphorylation in NIT-1 cells, but similar to TNF-α, PTPN1 deletion completely ablated both JNK and c-Jun activation (Fig 4.10A&B).
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A B
Figure 4.10: IL-1β induced MAPK phosphorylation in PTPN1 deficient NIT-1 cells.
(A and B) PTPN1 positively regulates IL-1β induced JNK and c-Jun signalling. PTPN1
KO NIT-1 cells were treated with a time course of IL-1β for 1 h and subjected to western blotting for (A) p-JNK and (B) p-c-Jun and α-tubulin. Quantification below represents (A) p-JNK and (B) p-c-Jun densitometry after correction for α-tubulin. Results are means ±
SEM of four independent experiments. Statistical significance is shown as **P < 0.01,
***P < 0.001 using a one-way ANOVA with Tukey correction.
IL-1b induced downstream AP-1 transcription products were also affected in isolated NODPI islets inhibited for PTPN1. IL-1b induced the relative expression of Nos2,
Ccl2, Ccl5 and Ccl20 after 8 hours, all of which were partially reduced by PTPN1 inhibition (Fig. 4.11A-D). However similar to the expression results observed with TNF-
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α and PTPN1 inhibition, only the Nos2 genes true RNA levels reflected a significant reduction in expression in this gene set. Ptpn1 gene expression was also significantly reduced by ~30% in islets inhibited for PTPN1, which was also reflected in the true RNA levels (Fig. 3.11E). These results suggest that PTPN1 positively regulates IL-1b induced iNOS expression in a feed forward cycle, similar to TNF-a signalling.
Figure 4.11: IL-1β induced gene expression in PTPN1 inhibited NODPI islets.
(A-E) NODPI islets inhibited for PTPN1 were treated with TNF-α for 8 h and subjected to quantitative PCR for (A) Nos2, (B) Ccl2, (C) Ccl5, (D) Ccl20 and (E) Ptpn1.
Quantifications represent gene expression relative to Actb using the double dCT analysis
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(left) and the true RNA levels using the dCT method (right). Results are means ± S.E.M. of four independent experiments. Statistical significance is shown as * P < 0.05, **P <
0.01, ***P < 0.001 using a one-way ANOVA with Tukey correction.
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4.4 Discussion:
The results demonstrate that PTPN1 positively regulates the TNF-a, IL-1b and IFN-γ signalling pathways and transcriptional responses in the NIT-1 b-cell line and NODPI islets in vitro. Inactivation of PTPN1 reduced the activation of various downstream signalling events and transcriptional responses induced by these cytokines which ultimately reduced cytotoxicity to the b-cell line. This is the first study to reveal a regulatory role of PTPN1 in these pro-inflammatory signalling pathways in b-cell lines and isolated primary islets and the first to show positive regulation of cytotoxic signalling provided by PTPs.
Activation of the STAT1 transcription factor by IFNs in β-cells has been shown to be critical for the pathogenesis of autoimmune diabetes in the NOD/Lt mouse. Indeed, STAT1 deficient NOD/Lt mice and NOD/Lt mice that overexpress SOCS1 in β-cells, a potent negative regulation of STAT1 signalling, are protected from insulitis and diabetes development [90, 92]. Inhibiting JAK1 and JAK2, which activate STAT1 in response to
IFN-γ has also been shown to protect and reverse diabetes development in the NOD/Lt mouse [96]. The insulitis reduction in these models is attributed to reduced chemokine production and MHC-I expression on β-cells, masking them from autoreactive immune cells [72, 96, 371]. We have shown that PTPN1 inactivation decreased IFN-γ induced
STAT1 phosphorylation and transcription of downstream genes, which enhanced islet viability when co-cultured with autoreactive CD8+ T-cells. The exact molecular mechanism of how PTPN1 results in decreased signalling remains unknown due to lack of protein interaction analysis in this study. PTPN1 can also negatively regulate leptin signalling through dephosphorylation of JAK2 and STAT3 [253]. This previous work and
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the present study suggest that regulation of cytokine signalling by PTPs is cell type specific.
For example, PTPN22 is reported to negatively regulate IFN-α induced STAT1 phosphorylation in hematopoietic progenitor cells [372], whilst positively regulating the same signalling pathway in P14 CD8+ T-cells [373]. Cellular deletion or transient inhibition of PTPs may also impair the basal physiological signalling network and non-specifically compromise further signalling responses which could further add to cell type specific phenotypes observed in PTP studies.
Excessive production of free oxygen radicals in pancreatic islets and β-cells may negatively affect β-cell function and contribute to their destruction. Indeed, iNOS induction has been demonstrated in both T1D and T2D islets and inhibition of NAPH oxidases, such as NOX1, that produce superoxide radicals protects β-cells from cytokine induced destruction [244, 374-376]. We have previously shown that NOD/Lt mouse islets with insulitis display high amounts of nitrosylation, which is indicative of oxidative stress, in comparison to NODPI mice free of insulitis [53]. It is also reported that serum antioxidant levels are reduced in patients with prediabetes and T1D in comparison to age matched controls suggesting that there is inherent susceptibility in the pathology to oxidative stress
[309, 310]. Here we demonstrate that IFN-γ, TNF-a and IL-1b induce mRNA expression of Nos2 in isolated mouse islets and that PTPN1 inhibition reduces expression induced by each cytokine. Thus, targeting PTPN1 may reduce the levels of oxidative stress induced by cytotoxic signalling during insulitis which may be beneficial for improving β-cell function or viability.
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Chemokines are among the first inflammatory mediators expressed during injury. The expression of CXCL10 in particular has been found to be enhanced in patients with T1D which attracts T-cells to the islet resulting in an aggressive Th1 phenotype [377]. The expression of CXCL10, CXCL9, CCL2, and CCL20 have also been found to be enhanced in NOD/Lt mice at early ages of life [83, 378-386]. Extensive microarray analysis of the
INS-1E β-cell line and purified rat β-cells have also shown that CXCL10 and CXCL9 are among the highest regulated chemokines induced by IFN-γ in combination with IL-1b and these are expressed in a STAT1 dependent manner [74]. Here we present that Cxcl10 and
Cxcl9 mRNA transcripts are induced by IFN-γ and Ccl2 and Ccl20 are induced by TNF-a and IL-1b in NODPI islets. Inhibition of PTPN1 reduced the expression of IFN-γ induced
Cxcl10 and Cxcl9, which supports that CXCL10 and CXCL9 expression is regulated by
STAT1, however had no effect on the true RNA levels of TNF-a and IL-1b induced Ccl2 and Ccl20, but did appear to trend towards a reduction in expression.
It was suggested that CXCL10 or its receptor (CXCR3) may be relevant targets after studying the RIP-LCMV-GP.NOD/Lt mouse model of diabetes. These mice express
LCMV-GP in β-cells and develop CD8+ T-cell induced diabetes after infection with LCMV and expressed high levels of CXCL10 during pathology. Indeed, deletion of CXCR3
(CXCL10s receptor) or treatment with an anti-CXCL10 antibody significantly delayed and prevented diabetes development [381, 382]. These results were then contradicted by various models and repeats of the RIP-LCMV-GP mouse lacking CXCL10 or its receptor, as well as the CXCR3-/-.NOD/Lt mouse which displayed accelerated diabetes onset [387,
388]. Recently, a dual therapy trialled on RIP-LCMV-GP mice with the anti-CXCL10 antibody and a suboptimal dose of anti-CD3 (which delays diabetes in the NOD/Lt mouse)
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showed improved remission than both monotherapies and higher levels of diabetic free mice after 170 days [85].
As PTPN1 was found to positively regulate cytokine induced activation of STAT1 and
MAPKs and downstream transcription of various inflammatory genes, targeting PTPN1 may be desirable to protect b-cells from dysfunction or destruction. However, we have previously shown that PTPs are globally inactivated by oxidative stress in diabetic NOD/Lt mouse pancreata. We also showed that global PTP inactivation in isolated NODPI islets enhanced IFN-γ induced STAT1 signalling and cytokine induced death [53]. Thus, targeting PTPN1 in pancreata with insulitis may not be feasible as PTPs are already inactive. In the previous chapter we showed that PTP oxidation can be reduced in NOD/Lt mice by oral treatment with antioxidants. It would be interesting to restore PTP activity in the NOD/Lt mouse with antioxidants such as NAC, then systemically inhibit PTPN1 and observe the effect on b-cell dysfunction and viability.
Historically the approach to develop inhibitors for PTPN1 was to target the active site to block phosphoprotein interaction. This approach was problematic as PTPN1 has a very similar active site structure to PTPN2, meaning that specificity of inhibitors remained uncertain [389]. However, in 2014 the PTPN1 specific inhibitor ‘MSI-1436’ was developed targeting the disordered C-terminal tail of PTPN1 with an inhibitory constant of
0.6µM [234]. This inhibitor has completed phase 1 clinical trials for obesity and T2D as
PTPN1 inhibition enhances insulin sensitivity in the liver and muscle and increases b-cell mass in islets of B6 mice. Thus, the benefits of PTPN1 inhibition in the context of T1D may not be limited to reducing cytokine signalling, but also enhancing peripheral insulin
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sensitivity reducing the strain on the remaining b-cell pool to compensate for hyperglycaemia.
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cells
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5.1 Summary:
Cytokine induced apoptosis is a tightly regulated and complex process to promote death induction only when required. Apoptosis can be trigged through various signalling cascades and directly through certain receptor complexes, both of which can be induced through TNF-a signalling. Dysregulation of TNF-a signalling is historically linked to cell death induction and is involved in numerous inflammatory disease processes. The motheaten mouse, which lacks PTPN6 activity, develops a lethal autoimmune phenotype which can be delayed by inhibition of TNF-a signalling. Immune cells release TNF-a into the islet microenvironment in the NOD/Lt mouse during insulitis and PTPN6 was identified as inactive in these mice, therefore we hypothesized that its inactivation would potentiate cell death induction. Here we show that PTPN6 inactivation enhances TNF-a induced NIT-1 cell death independent of IFN-g and IL-1b signalling. TNF-a induced JNK phosphorylation was enhanced with PTPN6 inactivation, however c-Jun and p38 phosphorylation were not affected. Enhanced JNK activation in PTPN6 deficient NIT-1 cells lead to decreased BCL-2 and MCL-1 protein expression which could be reversed by
JNK inhibition. Collectively these results suggest that PTPN6 negatively regulates TNF-a induced JNK signalling leading to decreased BCL-2 protein expression, predisposing NIT-
1 cells to TNF-a induced cell death.
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5.2 Introduction:
It is well documented that combinations of cytokines released by immune cells in T1D including IFN-γ, TNF-α and IL-1β, induce β-cell apoptosis in vitro. The apoptotic signal transduction pathways induced by these cytokines have been well documented and some components were briefly discussed in the previous chapter. These pathways are tightly regulated by various proteins such as PTPs and anti-apoptotic BCL-2 proteins to limit the activation of β-cell death.
Apoptosis is a complex and tightly regulated programmed form of cell death in which cells compartmentalize themselves for phagocytic clearance. Currently there are two main pathways, the intrinsic mitochondrial pathway and the extrinsic death receptor pathway
(discussed in the next chapter). When apoptosis is triggered through the intrinsic pathway the mitochondrial membrane alters, opening the mitochondrial permeability transition pore
(MPTP) [390]. The MPTP releases cytochrome-c from the intermembrane space of the mitochondria which binds to cytosolic Apaf-1 and procaspase-9 in a complex called the apoptosome [391, 392]. This complex leads to the activation of caspase-9 which then cleaves and activates caspase-3, triggering the execution pathway where the nucleus condenses, and the cytoskeleton rearranges into apoptotic bodies for clearance [393].
The intrinsic apoptotic pathway is regulated through the BCL-2 protein family
[394]. This family of proteins is comprised of two groups, the pro-apoptotic BH3-only proteins (Bim, Bax and Bak etc.) and anti-apoptotic BCL-2 proteins (MCL-1, BCL-2 and
BCL-XL etc.). The Multi-BH domain proteins Bax and Bak are responsible for opening the MPTP and releasing cytochrome-c from the mitochondria, however these proteins are
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Chapter 5: Role of PTPN6 in Regulation of Cytokine Signalling in Pancreatic b-cells held inactive by competitive binding to BCL-2 anti-apoptotic proteins [395]. When BH3- only proteins like Bim are upregulated or anti-apoptotic BCL-2 are downregulated, Bax and Bak are released due to loss of competitive binding and translocate to the mitochondria opening the pore [396]. The fine balance between these proteins can be altered by cytokine signalling or various other forms of cell stress, resulting in apoptosis.
Models of apoptosis induction of β-cells in vitro by IFN-γ rely on STAT1 induced transcription of pro-apoptotic BH3-only proteins, including Bim [74, 370, 397]. IFN-γ signalling alone however typically does not induce cell death of β-cell lines or isolated islets and requires either TNF-α or IL-1β as costimulatory signals. Enhanced IFN-γ signalling through loss of PTP activity however induces islet death in vitro through STAT1 dependent upregulation of Bim [53-55].TNF-α and IL-1b stimulated MAPKs, in particular
JNKs, are associated with the induction of apoptosis in β-cells through post translational modification of anti-apoptotic BCL-2 proteins [398, 399]. Anti-apoptotic BCL-2 proteins, such as BCL-2 and MCL-1, are substrates of JNK and upon extended phosphorylation of their BH3 binding domains these proteins are altered in their capacity to bind and inhibit pro-apoptotic BH3-only proteins or targeted for degradation by the proteasome, which predisposes cells to death by apoptosis [365, 400-402].
In the previous chapter we showed that PTPs have non-redundant roles in the regulation of cytokine induced β-cell death. PTPN6 is previously reported to negatively regulate both STAT1 and JNK signalling [403-405], and we have previously shown that
PTPN6 is inactivated by oxidation in diabetic NOD/Lt mouse pancreata [53]. PTPN6 inactivation is also associated with TNF-a signalling through the generation of the PTPN6
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Chapter 5: Role of PTPN6 in Regulation of Cytokine Signalling in Pancreatic b-cells deficient mouse, the motheaten mouse. These mice develop a severe autoimmune phenotype and succumb to lethal pneumonitis at ~3 weeks of age [228, 406]. These mice present with elevated levels of TNF-a in the lung and serum and treatment with TNF-a inhibitors increases the life span of these mice [407, 408]. As PTPN6 is reportedly a negative regulator of these pathways, in particular TNF-a, we hypothesise that inactivation of PTPN6 will enhance cell death.
In this study, we show that PTPN6 is expressed in mouse and human islets as well as the
NIT-1 b-cell line. We also demonstrate that PTPN6 negatively regulates TNF-a induced
JNK activity and reduced anti-apoptotic BCL-2 protein expression, predisposing cells to apoptotic induced cell death.
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5.3 Results:
5.3.1 Development of PTPN6 deficient NIT-1 cells:
To examine the role of PTPN6 in regulation of cytokine signalling in b-cells, we first evaluated its expression in islets of NOD/Lt mice and NODPI mice. Using the same lysates from the previous chapter immunoblot revealed PTPN6 was expressed in both NOD/Lt mouse islets and non-diabetic NODPI islets at similar levels over all ages (Fig. 5.1A). We then confirmed PTPN6 expression in human islet lysates from 6 non-diabetic organ donors
(Fig. 5.1B).
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Figure 5.1: Expression of PTPN6 in human and murine islets.
(A) Western blot demonstrates that PTPN6 is equally expressed in NOD/Lt and NODPI mouse islets. The intensity values of the proteins were corrected by the values of the β- actin loading control and are shown in arbitrary units (A.U.). Results are means ± S.E.M. of four independent experiments. (B) PTPN6 expression in human islets. Samples were acquired from six brain-dead non-diabetic organ donors and subjected to western blotting with antibodies detecting PTPN6 and α-tubulin as loading control. No statistical significance was reported with a one-way ANOVA with Tukey correction.
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A B C NODPI NOD/Lt NODPI NOD/Lt Sample 1 2 3 4 5 6 Age (Weeks) 4 15 22 4 15 22 Age (Weeks) 4 15 22 4 15 22
PTPN6 PTPN1 PTPN6
β-actin β-actin α-tubulin
Chapter 5: Role of PTPN60.75 in Regulation of Cytokine Signalling in Pancreatic b-cells 0.5 NODPI PTPN1
NOD/Lt 0.4 Similarly, to the previous chapter, to study the effect of PTPN6 on regulation of IFN-g, actin 0.5 α-tubulin -
actin 0.3 - / β
TNF-a and IL-1b signalling we generated a PTPN6-deficient NIT-1 b-cell line/ β using a 0.2 0.25 CRISPR/Cas9 exon deletion strategy. We were successful in generating a single 0.1PTPN6 PTPN6 PTPN6 PTPN1 PTPN1 deficient NIT-1 cell line (Fig. 5.2A0 ) with no protein of interest detected in comparison0 to 4 15 22 4 15 22 the vector control population (transfectedWeeks withWeeks the Cas9Weeks D10A nickase without gRNAWeeks Weeks Weeks sequences). D E A
PTPN6 Coding Direction PTPN1 Coding Direction
16 Target Exons 1 1 Target Exons 9
Vector Ctrl PTPN6 KO Vector Ctrl PTPN1 KO
PTPN6 PTPN1
β-actin β-actin
Figure 5.2: PTPN6 expression in PTPN6 deficient NIT-1 cells.
(A) Schematic of the CRISPR/Cas9 deletion strategy for PTPN6. Western blot demonstrate deletion of PTPN6 from NIT-1 cells. Results are the representatives of four independent experiments.
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Figure 1. Chapter 5: Role of PTPN6 in Regulation of Cytokine Signalling in Pancreatic b-cells
5.3.2 PTPN6 inactivation enhances TNF-α induced NIT-1 cell death:
As our previous in vitro cytotoxicity experiments effectively identified that PTPN1 positively regulated TNF-α and IFN-γ signalling we performed DNA fragmentation and
Hoechst-33342/Propidium Iodide immunofluorescence on PTPN6 deficient NIT-1 cells to observe differential signalling (Fig. 5.3A-D). Treatment of PTPN6 deficient NIT-1 cells with TNF-α alone enhanced DNA fragmentation from ~40% to ~60% (Fig. 5.3A&B).
Interestingly the combination of TNF-α and IFN-γ did not significantly further enhance cell death of PTPN6 deficient NIT-1 cells. We were able to replicate that PTPN6 deficiency enhances TNF-α induced NIT-1 cell death using immunofluorescence cell death analysis
(Fig. 5.3C&D). Similar to our experiments analysing PTPN1, combinations of IL-1β with
IFN-γ and TNF-α had no effect on DNA fragmentation (Fig. 5.3E&F). As TNF-α induced cell death of NIT-1 cells was consistently enhanced with PTPN6 deficiency we verified this effect using the PTPN6/PTPN11 dual specific inhibitor NSC87877. Consistent with our findings, NIT-1 cells treated with the NSC87877 inhibitor had enhanced TNF-α induced DNA fragmentation in comparison to PBS treated vehicles (Fig. 5.3G).
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A B 75 Vector Control PTPN6 KO Control PTPN6 Knockout α - 50 TNF + γ - IFN
Cell Death (%) Death Cell 25 Chapter 5: Role of PTPN6 in Regulation of Cytokine Signalling in Pancreatic b-cells
0 Ctrl IFN-γ TNF-α IFN-γ + TNF-α C A D B Vector Control PTPN6 KO 80 Control PTPN6 Knockout 60 α - 49.2 81.6 TNF
+ 40 γ - IFN 20 DNA Fragmentation (%) Fragmentation DNA
0 Ctrl IFN-γ TNF-α IFN-γ + TNF-α E AC F B DG Vector Control PTPN6 KO Vector Control PTPN6 KO 75 Vector Control PTPN6 KO Vector Control PTPN6 KO Control TNF-α TNF-α 0h 2h 4h 8h 24h 0h 2h 4h 8h 24h TNF-α 0h 2h 4h 8h 24h 0h 2h 4h 8h 24h 0h 2h 4h 8h 24h 0h 2h 4h 8h 24h PTPN6 Knockout
α BCL-2 MCL-1 p-JNK- 50
β-actinTNF β-actin β-actin + γ -
IFN 1.8 2 2.5 (%) Death Cell 25 Control Control Control PTPN6 Knockout PTPN6 Knockout 2 PTPN6 Knockout 1.5 1.2 actin - 1.5 0 actin / β - actin Ctrl 1 - IFN-γ TNF-α IFN-γ + / β
1 / β TNF-α 2
JNK - 1
- E F 0.6 G -
Cp 0.5 D
BCL 0.5 Vector Control PTPN6 KO 80MCL Control 0 0 0 PTPN6 Knockout 0h 2h 4h 8h 24h 0h 2h 4h 8h 24h 0h 2h 4h 8h 24h 60 α - 49.2 81.6 TNF
+ 40 γ - IFN 20 DNA Fragmentation (%) Fragmentation DNA
0 Ctrl IFN-γ TNF-α IFN-γ + TNF-α FigureE 5.3: PTPN6 inactivation Fenhances TNF-α induced NITG-1 cell death. Vector Control PTPN6 KO Vector Control PTPN6 KO Vector Control PTPN6 KO TNF-α 0h 2h 4h 8h 24h 0h 2h 4h 8h 24h (ATNF-D)-α 0hPTPN6 2h 4h 8h 24h deletion 0h 2h 4h 8h enhances 24h TNF - cytokineα 0h 2h 4h 8hinduced 24h 0h 2h 4hdeath/DNA 8h 24h fragmentationFigure of β -2.cell p-JNK BCL-2 MCL-1
lines.β-actin (A&B) DNA fragmentationβ-actin of PTPN6 KO NIT-1 cellsβ -wasactin assessed by Nicoletti
2 2.5 1.8 staining ofControl single cell suspensions and quantificationControl of the sub-G1 phaseControl of the cell cycle PTPN6 Knockout PTPN6 Knockout 2 PTPN6 Knockout 1.5 1.2 afteractin 48 h of TNF-α and IFN-γ treatment. (C&D) PTPN6 KO NIT-1 cells were treated - 1.5 actin / β - actin
1 - / β
1 / β 2
withJNK TNF-α and IFN-γ for 48 h and- cell death was assessed by the ratio of Hoechst-33342 1
- 0.6 -
p 0.5
BCL 0.5 (blue, viable) to propidium iodide (red, dead) nuclei. Scale barMCL represents 10μm. (E&F) 0 0 0 0h 2h 4h 8h 24h 0h 2h 4h 8h 24h 0h 2h 4h 8h 24h 118
Figure 2. Chapter 5: Role of PTPN6 in Regulation of Cytokine Signalling in Pancreatic b-cells
PTPN6 KO NIT-1 cells were treated with (E) IFN-γ or (F) TNF-α in combination with IL-
1β for 48 h and DNA fragmentation was assessed by Nicoletti staining of single cell suspensions and quantification of the sub-G1 phase of the cell cycle. (G) PTPN6 inhibited
NIT-1 cells were treated with TNF-α for 48 h and DNA fragmentation was assessed by
Nicoletti staining of single cell suspensions and quantification of the sub-G1 phase of the cell cycle. Results are means ± S.E.M. of four to six independent experiments. Statistical significance is shown as * P < 0.05, **P < 0.01, ***P < 0.001 using a one-way ANOVA with Tukey correction.
Next to evaluate if enhanced cytokine induced NIT-1 cell death caused by PTPN6 deficiency was due to enhanced apoptosis we performed an immunoblot for caspase-3 cleavage after IFN-γ and TNF-α stimulation. Immunoblot revealed that stimulation of
PTPN6 deficient NIT-1 cells with TNF-α alone or IFN-γ with TNF-α significantly increased caspase-3 cleavage in comparison to PTPN6 sufficient cells (Fig. 5.4A).
Collectively these results suggest that PTPN6 has a prominent role in negatively regulating
TNF-α signalling in this b-cell line resulting in enhanced cytokine induced apoptosis.
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Figure 5.4: PTPN6 deletion enhances TNF-α induced caspase-3 cleavage in NIT-1 cells.
(A) PTPN6 knockout NIT-1 cells were treated with TNF-α and IFN-γ for 24 h and subjected to western blotting for cleaved caspase-3 and β-actin as loading control.
Quantification represents cleaved caspase-3 densitometry after correction for β-actin.
Results are means ± S.E.M. of three independent experiments Statistical significance is shown as ***P < 0.001 using a one-way ANOVA with Tukey correction.
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5.3.3 PTPN6 does not regulate IFN-γ induced STAT1 signalling in NIT-1 cells:
As our cytotoxicity results didn’t clearly show if IFN-γ had an influence on the death of
PTPN6 deficient NIT-1 cells due to the robust results seen with TNF-α we first evaluated
IFN-γ induced STAT1 phosphorylation kinetics similarly to before. Immunoblot revealed that there was no difference in STAT1 phosphorylation over the 24 hour period between
PTPN6 deficient and control cells (Fig. 5.5A). Next, we verified this result with the
NSC87877 inhibitor which also revealed no difference in STAT1 phosphorylation between the vehicle control and inhibitor (Fig. 5.5B). These results showed that PTPN6 does not regulate IFN-γ signalling in NIT-1 cells suggesting that PTPN6 dependent cell death was caused by TNF-α.
A B
Figure 5.5: PTPN6 does not regulate IFN-γ induced STAT1 signalling in NIT-1 cells.
(A) PTPN6 knockout NIT-1 cells and (B) NIT-1 cells inhibited for PTPN6 were treated with a 24 hour time course of IFN-γ and subjected to western blotting for p-STAT1 and β- 121
Chapter 5: Role of PTPN6 in Regulation of Cytokine Signalling in Pancreatic b-cells actin as loading control. Quantification below represents p-STAT1 densitometry after correction for β-actin. Results are means ± S.E.M. of four independent experiments. No statistical significance was recorded with a one-way ANOVA with Tukey correction.
5.3.4 PTPN6 negatively regulates TNF-α induced JNK signalling in NIT-1 cells:
As our results from our cytotoxicity studies suggested that PTPN6 must negatively regulate
TNF-α induced cell death independent of IFN-γ we evaluated the kinetics of TNF-α induced JNK and p38 phosphorylation. We treated PTPN6 sufficient and deficient NIT-1 cells with TNF-α over 24 hours and generated lysates for analysis. Immunoblot revealed that JNK activation was enhanced over the 24 hour period with PTPN6 deficiency, however, interestingly p38 activity was not affected (Fig. 5.6A&B). As JNK induced c-
Jun kinase activity is responsible for downstream transcription we evaluated whether
PTPN6 deficiency exacerbated c-Jun phosphorylation. Interestingly we observed that c-
Jun activation was not affected by PTPN6 deficiency in NIT-1 cells (Fig. 5.6C). These results suggest that PTPN6 negatively regulates TNF-α induced JNK activity, independent of p38 and c-Jun.
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A B C
p-c-Jun
β-actin
Figure 5.6: PTPN6 negatively regulates TNF-α induced JNK phosphorylation in
NIT-1 cells.
PTPN6 knockout NIT-1 cells were treated with a time course of TNF-α for 24 h and subjected to western blotting for (A) p-JNK, (B) p-p38, (C) p-c-Jun and β-actin.
Quantification below represents p-JNK, p-p38 and p-c-Jun densitometry after correction for β-actin. Results are means ± SEM of four independent experiments. Statistical significance is shown as * P < 0.05, **P < 0.01, ***P < 0.001 using a one-way ANOVA with Tukey correction.
5.3.5 PTPN6 positively regulates IL-1β induced MAPK signalling in NIT-1 cells:
As we found that PTPN6 negatively regulated TNF-α induced JNK phosphorylation we next seeked to confirm if PTPN6 also regulated IL-1β induced JNK signalling. We treated
PTPN6 sufficient and deficient NIT-1 cells with IL-1β over 1 hour and generated lysates for analysis. Immunoblot revealed that neither JNK nor c-Jun phosphorylation were
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Chapter 5: Role of PTPN6 in Regulation of Cytokine Signalling in Pancreatic b-cells enhanced with PTPN6 deficiency, indeed JNK phosphorylation was slightly reduced with
PTPN6 deficiency (Fig. 5.7A&B). These results suggest that PTPN6 differentially regulates TNF-α and IL-1β induced JNK activity in NIT-1 cells.
A B
Figure 5.7: PTPN6 positively regulates IL-1β induced JNK phosphorylation in NIT-
1 cells.
(A and B) PTPN6 KO NIT-1 cells were treated with a time course of IL-1β for 1 h and subjected to western blotting for (A) p-JNK and (B) p-c-Jun and α-tubulin. Quantification below represents (A) p-JNK and (B) p-c-Jun densitometry after correction for α-tubulin.
Results are means ± SEM of four independent experiments Statistical significance is shown as **P < 0.01 using a one-way ANOVA with Tukey correction.
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5.3.6 PTPN6 negatively regulates JNK dependent expression of anti-apoptotic BCL-
2 proteins:
Our cytokine signalling results showed that PTPN6 negatively regulates TNF-α induced
JNK signalling in NIT-1 cells. TNF-α regulates anti-apoptotic BCL-2 protein levels in a variety of cell types altering the susceptibility of cells to apoptotic stimuli. The BCL-2 proteins; BCL-2, MCL-1 and BCL-XL are substrates of JNK, where JNK phosphorylates their BH3 binding domains targeting them for degradation, enhancing the susceptibility of the cell to apoptosis. Next, we wished to observe if PTPN6 deficiency could predispose
NIT-1 cells to TNF-α induced apoptosis JNK dependent BCL-2 protein degradation or altered expression.
Immunoblotting was used to measure the expression of anti-apoptotic BCL-2 proteins in PTPN6 deficient cells after TNF-α treatment. BCL-2 levels were enhanced after
24 h of TNF-α treatment in PTPN6 expressing but not in PTPN6 deficient cells (Fig. 5.8A).
Moreover, MCL-1 expression was reduced after 24h of treatment in wild type cells and was further reduced in PTPN6 deficient cells (Fig. 5.8B). BCL-XL expression was not affected by TNF-α treatment or PTPN6 deficiency (not shown).
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A B
Figure 5.8: PTPN6 negatively regulates TNF-α induced anti-apoptotic BCL-2 protein expression in NIT-1 cells.
PTPN6 knockout NIT-1 cells were treated with a time course of TNF-α for 24 h and subjected to western blotting for (A) BCL-2, (B) MCL-1 and β-actin. Quantification below represents BCL-2 and MCL-1 densitometry after correction for β-actin. Results are means
± SEM of four independent experiments Statistical significance is shown as **P < 0.01,
***P < 0.001 using a one-way ANOVA with Tukey correction.
Next, we wanted to validate that the reduction in MCL-1 protein expression in PTPN6 deficient cells was indeed JNK dependent. To do this we adopted the use of the cell permeable JNK specific inhibitor, SP600125, to inhibit JNKs activity in response to TNF-
α. We treated PTPN6 deficient NIT-1 cells with TNF-α along with SP600125 or the
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DMSO vehicle control for 24 hours, as this was when degradation was observed, and generated lysates for analysis. Immunoblot revealed that MCL-1 expression was significantly reduced with TNF-α stimulation in PTPN6 deficient cells, however with JNK inhibition, MCL-1 levels were partially recovered in PTPN6 deficient cells (Fig. 5.9A).
Taken together, these results demonstrate that the deletion of PTPN6 in NIT-1 cells enhances TNF-α induced JNK phosphorylation, resulting in decreased BCL-2 protein expression and enhanced susceptibility to TNF-α induced apoptosis.
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Figure 5.9: PTPN6 negatively regulates JNK dependent TNF-α induced MCL-1 protein degradation in NIT-1 cells.
PTPN6 knockout NIT-1 cells were treated with a time course of TNF-α for 24 h with or without JNK inhibition and subjected to western blotting for MCL-1 and β-actin.
Quantification below represents MCL-1 densitometry after correction for β-actin. Results are means ± SEM of three independent experiments. Statistical significance is shown as *
P < 0.05 using a one-way ANOVA with Tukey correction.
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5.4 Discussion:
The results demonstrate that PTPN6 negatively regulates TNF-a signalling and NIT-1 cell death in vitro. Inactivation of PTPN6 enhanced TNF-a induced JNK phosphorylation and reduced BCL-2 protein expression predisposing NIT-1 cells to death. This is the first study to reveal a regulatory role for PTPN6 in TNF-a signalling in a b-cell line and supports other cell line models showing PTPN6 negatively regulates JNK signalling in vitro.
Development of murine models for PTPN6 dysfunction have linked it to immune cell dysregulation, inflammatory pathologies and hyperactive cytokine signalling responses
[228, 255-258, 406-410]. PTPN6 deficient mice (motheaten mice) display a prominent autoimmune phenotype with development of granulocytic skin lesions, arthritis, multiple autoantibodies and succumb to lethal pneumonitis at the age of 2-3 weeks [228]. The generation of the motheaten viable mouse, which expresses PTPN6 with ~50% reduced catalytic activity, has allowed further dissection of the pathological phenotype of these mice as they survive until ~10 weeks of age [406]. Motheaten viable mice present with increased levels of TNF-α in the lung and serum during pneumonitis development [407,
408]. When treated with a soluble TNF-α receptor 1 (sTNFR1) to decrease signal transduction, they display a 2-fold increase in lifespan, highlighting the requirement for
TNF-α in the pathogenesis of the autoimmunity caused by loss of PTPN6.
TNF-α signalling is strongly linked to inflammatory diseases and cell death initiation as it induces numerous stress response signalling cascades and direct cell death machinery. Here we describe a mechanism by which PTPN6 inactivation promotes TNF-α induced NIT-1
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Chapter 5: Role of PTPN6 in Regulation of Cytokine Signalling in Pancreatic b-cells cell death in vitro through hyperactivation of JNK and reduction of the antiapoptotic proteins BCL-2 and MCL-1. PTPN6 has previously been shown to negatively regulate JNK phosphorylation induced by 4-Hydroxy-2-nonenal in HBE1 cells as well as JNK dependent
IGF-1 induced MCF-7 breast cancer cell proliferation [405, 411]. JNK activity has also been linked to β-cell death in various in vitro studies using IL-1β [412, 413], which activates similar MAPK signalling cascades to TNF-α. Streptozotocin (STZ) was also shown to activate JNK in primary islets and β-cells in vitro which was enhanced with pan- phosphatase inhibitor treatment suggesting that phosphatases are involved in JNK activation which supports our findings that PTPN6 regulates JNK in β-cells [197].
Treatment of RIN-5AH and βTC-6 insulin producing cells with the JNK inhibitor
SP600125 decreased STZ induced cell death confirming JNK is involved in STZ induced cell death [414]. Inactivation of JNK2 also protects NOD.SCID mice from diabetes development by adoptive transfer of diabetic NOD splenocytes, linking JNK to autoimmune dependent β-cell death in vivo [415].
BCL-2 proteins are responsible for the inhibition of proapoptotic BH3-only proteins and multi-BH domain proteins through competitive binding. Different BCL-2 protein members inhibit different proapoptotic proteins, for instance MCL-1 is responsible for inhibiting BIM and PUMA [416-419]. Stimulation of β-cells with pro-inflammatory cytokines reduces expression of MCL-1 while inducing expression of pro-apoptotic proteins, promoting cell death activation [420]. dsRNA and Coxsackievirus infection also reduce MCL-1 expression in β-cells through inhibition of protein synthesis and resulted in cell death induction [421]. Overexpression of MCL-1 in primary rat β-cells protects from cytokine induced death through reduced mitochondrial cytochrome c release and caspase-
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3 activation [420]. Cytokines were also found to decrease MCL-1 expression in human β- cells which could be partially rescued by ectopic overexpression suggesting that MCL-1 provides a cytoprotective response in both human and mouse β-cells [422]. We were able to show that PTPN6 deficiency potentiated JNK activation by TNF-α resulting in MCL-1 degradation and enhanced caspase-3 cleavage similar to the findings above. It would be interesting to study if MCL-1 overexpression in PTPN6 deficient NIT-1 cells protects from
TNF-α induced cell death which would suggest that deficiency results in the activation of the intrinsic apoptotic pathway.
Utilising the NIT-1 b-cell line has provided mechanistic links between PTPN1 (previous chapter) and PTPN6 and inflammatory cytokine signalling in our studies, however it is important to contextualise these results to this model unless validated in other b-cell lines or primary islets. The NIT-1 cell line was isolated from an insulinoma developed by expression of the SV40 large T-cell antigen gene under the rat insulin promoter [266], similar to other b-cell lines including the MIN6 line [423]. It also remains to date the only b-cell line on the NOD/Lt mouse background. These generation tactics, while useful, can lead to many artefacts in cellular function and signalling which has implications in signalling studies. The NIT-1 cell for instance is deficient in NF-kB signalling due to absence of the p65 subunit of the transcription factor which leads to the ablation of key translational responses, including iNOS induction [79, 80, 424]. Because of such abnormalities, our results pertaining to PTPN6 and TNF-a signalling should be validated in another b-cell line, such as the MIN6 or INS-1E lines [425], or in primary islets. It is possible that the results are only relevant in the context of diminished or defective NF-kB
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Chapter 5: Role of PTPN6 in Regulation of Cytokine Signalling in Pancreatic b-cells signalling. As NIT-1 cells still die after treatment with a cocktail of inflammatory cytokines, they still remain a useful tool for studying mechanisms of apoptosis and alternate forms of cell death which is discussed in the next chapter.
Our findings provide a mechanistic link to the motheaten mouse, where PTPN6 inactivation by oxidation during autoimmune pathologies, such as T1D, may lead to the hyperactivation of JNK in response to TNF-α culminating in enhanced cell death and autoimmunity.
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Apoptosis in NIT-1 Cells
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6.1 Summary:
Historically cell death was believed to be activated by either apoptosis or necrosis through redundant mechanisms. Current research has proven there are now twelve different forms of cell death that can be induced in vitro. TNF-a in particular has been shown to activate at least three different forms of cell death including RIPK1 dependent/independent apoptosis and necroptosis depending on the receptor complex composition and posttranslational modification state of the adaptor proteins. In the previous chapter we showed that PTPN6 negatively regulates TNF-a induced NIT-1 cell death however the exact mechanism remained unclear. We were able to show that caspase-3 cleavage was enhanced in PTPN6 deficient cells suggesting that apoptosis was executed, therefore we hypothesised that the death mechanism was by either RIPK1 dependent/independent apoptosis. Using the pan-caspase inhibitor Z-VAD.FMK we were able to show that apoptosis was induced instead of necroptosis as it protected against cell death. The RIPK1 inhibitor Nec-1 also fully protected against cell death suggesting that death was occurring by RIPK1 dependent apoptosis. NIT-1 cells are inherently susceptible to TNF-a induced cell death due to lack of the p65 subunit of the NF-kB transcription factor, presumably by caspase-8 activation by the loss of NF-kB induced cFLIP transcription. PTPN6 inhibition lead to enhanced caspase-8 cleavage which was also blocked by Nec-1 treatment or p65 overexpression. Collectively these results suggest that PTPN6 inactivation promotes TNF- a induced RIPK1 dependent apoptosis in NIT-1 cells, however the exact mechanism remains unknown but possibly involves caspase-8 activation.
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6.2 Introduction:
Historically, various cytotoxic signalling pathways were believed to converge on common molecular signalling nodes resulting in either apoptosis or necrosis initiation. However, cell death is no longer as simplistic as once believed and to date, twelve defined death mechanisms have been described [426-428]. Indeed, the Nomenclature Committee on Cell
Death (NCCD) recently published a comprehensive guide classifying these forms of cell death based on morphological, biochemical and functional perspectives [429]. TNF-a induced cell death is a model example of multiple mechanisms as it can promote intrinsic apoptosis, extrinsic apoptosis and necroptosis based on the expression and posttranslational modifications of the TNF receptor complex and adaptor proteins [430]. Thus TNF-a is a prominent inducer of tissue inflammation and is linked to many inflammatory diseases which could be representative of its role in multiple mechanisms of cell death induction. It is important to note that these mechanisms are mostly studied in vitro and their relevance to disease in vivo (such as in T1D or primary b-cells) remain to be determined.
A prime example of TNF-a signalling dysregulation, immune dysfunction and cell death stems from the development of PTPN6 deficient mice, termed motheaten mice.
Motheaten mice present a severe autoimmune phenotype and develop granulocytic skin lesions, arthritis, production of multiple autoantibodies and succumb to lethal pneumonitis by 2-3 weeks of age [228]. The motheaten viable mouse, which expresses PTPN6 with
~50% reduced catalytic activity, display increased levels of TNF-α in the lung and serum
[406]. When treated with a soluble TNF-α receptor 1 (sTNFR1), these mice display a 2- fold increase in lifespan, highlighting the requirement for TNF-α in the autoimmune pathology caused by loss of PTPN6 [407, 408].
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In the previous chapter we showed that NIT-1 cells deficient for PTPN6 were more susceptible to TNF-α induced cell death however the exact mechanism of cell death remained elusive. Caspase-3 cleavage was enhanced with PTPN6 deficiency suggesting that cell death may be activated through apoptosis as caspase-3 cleavage is one of the final effector mechanisms of apoptosis induction. NIT-1 cells are inherently susceptible to TNF- a induced cell death as they lack the p65 subunit of the NF-kB transcription factor [80].
Dysfunctional NF-kB signalling has been shown in other cell types to result in enhanced extrinsic apoptosis induction by failing to upregulate cFLIP to inhibit caspase-8 in the
RIPK1 receptor complex [146, 431-433]. This can lead to activation of RIPK1 dependent or RIPK1 independent apoptosis through receptor internalisation [434-436]. However this also results in predisposition to necroptosis induction due to dysregulation of the RIPK1 receptor complex, leading to RIPK3 activation and MLKL oligomerisation [437-439].
Inhibitors of cell death such as Z-VAD.FMK (which inhibits apoptosis through pan- caspase inhibition, [440-442]) and Nec-1 (which inhibits apoptosis and necroptosis through
RIPK1 inhibition, [443, 444]) have become useful in discerning the cell death mechanism activated and the molecular events leading to these mechanisms.
Understanding how all these death pathways are regulated still remains controversial and more kinetic studies are needed to define the molecular events of cytotoxic signalling to define them. As we observed increased TNF-a induced cell death in NIT-1 cells lacking PTPN6 this gives us an opportunity to describe the form of cell death activated and if the resultant cell death mechanism is altered with PTPN6 deficiency.
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6.3 Results:
6.3.1 Pan-caspase and RIPK1 inhibition protects PTPN6 sufficient and deficient
NIT-1 cells from TNF-a induced death:
We showed in chapter 5 that caspase-3 cleavage was enhanced in PTPN6 deficient cells treated with TNF-a which suggested cell death was caspase dependent. Caspase-3 activation is not limited to classical apoptosis induction, such as pro-apoptotic protein induction, but can also be induced by other receptor complexes such as FAS and TRAIL as well as introduction of granzymes to the cell [445-451]. Activation of caspases results in the morphological hallmarks of apoptosis such as DNA fragmentation. To determine if cell death was dependent on caspases, we performed DNA fragmentation analysis of
PTPN6 deficient cells with the pan-caspase inhibitor Z-VAD.FMK. Treatment of PTPN6 deficient cells enhanced TNF-a induced cell death from ~40% to ~60% as we had shown in the previous chapter (Figs. 6.1A-D). Pan-caspase inhibition significantly reduced
PTPN6 deficient cell death to basal levels with PTPN6 sufficient cells almost reaching significance (Fig. 6.1A&B). Caspase-8 can activate apoptosis when cells are treated with
TNF-a through receptor internalisation and activation of the DISC complex. DISC formation can be inhibited using the RIPK1 inhibitor Nec-1 so to determine if RIPK1 was involved in triggering cell death we reperformed DNA fragmentation analysis using Nec-
1. Inhibition of RIPK1 in both PTPN6 sufficient and deficient NIT-1 cells also fully protected from TNF-a induced cell death (Fig. 6.1C&D).
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Figure 6.1: Cytotoxicity analysis of NIT-1 cells with caspase and RIPK1 inhibition.
(A-D) Z-VAD.FMK and Nec-1 protect PTPN6 deficient and sufficient NIT-1 cells from
TNF-α induced death. DNA fragmentation of PTPN6 KO NIT-1 cells was assessed by
Nicoletti staining of single cell suspensions and quantification of the sub-G1 phase of the cell cycle after 48 h of TNF-α treatment with Z-VAD.FMK (A&B) or Nec-1 (C& D).
Results are means ± S.E.M. of three to four independent experiments. Statistical significance is shown as *P < 0.05, **P < 0.01, ***P < 0.001 using a one-way ANOVA with Tukey correction.
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6.3.2 P65 overexpression protects NIT-1 cells from RIPK1 dependent apoptosis:
As we were able to show that both caspase and RIPK1 inhibition were able to protect
PTPN6 deficient and sufficient NIT-1 cells from TNF-a induced cell death we next aimed to dissect the role of the RIPK1 complex in cell death induction. Caspase-8 and RIPK1 activity have an important role in the regulation of RIPK1 induced cell death mechanisms, as mentioned above it has the ability to induce apoptosis and necroptosis. NIT-1 cells lack the p65 subunit of the NF-kB complex which classically upregulates the caspase-8 inhibitor cFLIP to protect from apoptosis. We therefore studied NIT-1 cells that overexpress the p65 subunit of the NF-kB complex (NIT-1.p65), which are reported to be protected from TNF-a induced cell death presumably through restoration of cFLIP activity.
We performed DNA fragmentation analysis of NIT-1 cells and NIT-1.p65 cells to check if TNF-a induced cell death was prevented. DNA fragmentation was significantly reduced with p65 overexpression in comparison to both control and PTPN6 deficient NIT-
1 cells (Figs. 5.2A&B). The inclusion of Nec-1 significantly protected control and PTPN6 deficient NIT-1 cells from TNF-a induced cell death, however no significance was observed over the NIT-1.p65 cell groups. Because restoration of NF-kB signalling had the same effect as inhibition of RIPK1, these results suggest that PTPN6 deficiency results in further dysregulation of the RIPK1-caspase-8 node in apoptosis induction.
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Figure 6.2: Cytotoxicity analysis of NIT-1 cells with p65 overexpression and RIPK1 inhibition.
(A&B) p65 overexpression and Nec-1 protect NIT-1 cells from TNF-α induced death.
DNA fragmentation of NIT-1 cells was assessed by Nicoletti staining of single cell suspensions and quantification of the sub-G1 phase of the cell cycle after 48 h of TNF-α treatment with p65 over expression or Nec-1 treatment. Results are means ± S.E.M. of three independent experiments. Statistical significance is shown as *P < 0.05, ***P <
0.001, for TNF-α alone, or ###P < 0.001 for the combination with Nec-1, using a one-way
ANOVA with Tukey correction.
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Next, we performed immunoblotting for both caspase-3 and caspase-8 cleavage of all NIT-1 cell groups with or without Nec-1 and TNF-a to measure which caspases were affected by the restoration of NF-kB activity or inhibition of RIPK1 activity. Caspase-3 cleavage was significantly enhanced in TNF-a treated PTPN6 deficient cells in comparison to control cells and cleavage was ablated with the inclusion of Nec-1 (Figs. 5.3A&B). The active p-10 fragment of caspase-8 could also be observed in TNF-a treated PTPN6 deficient cells but not control cells and this was also reversed by Nec-1 inclusion (Fig.
5.3A, red box). Neither caspase-3 nor caspase-8 cleavage was observed in TNF-a treated
NIT-1.p65 cells with or without the inclusion of Nec-1. Collectively these results support the DNA fragmentation analysis above that PTPN6 deficiency leads to further RIPK1- caspase-8 activation than observed with the control cells resulting in caspase-3 cleavage and apoptosis induction.
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Figure 6.3: Immunoblot analysis of TNF-α induced caspase cleavage of NIT-1 cells with p65 overexpression and RIPK1 inhibition.
(A&B) p65 overexpression and Nec-1 protect NIT-1 cells from TNF-α induced caspase-3 and caspase-8 cleavage. NIT-1 cells were treated with TNF-α for 24 h with p65 overexpression and/or Nec-1 treatment and subjected to western blotting for cleaved caspase-3, cleaved caspase-8 (as shown as p-10 in the red box) and α-tubulin as loading control. Quantification represents cleaved caspase-3 densitometry after correction for α- tubulin. Results are means ± S.E.M. of three independent experiments. Statistical significance is shown as ***P < 0.001, for TNF-α alone, or ###P < 0.001 for the combination with Nec-1, using a one-way ANOVA with Tukey correction.
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6.4 Discussion:
The results demonstrate that RIPK1 activity has a role in TNF-α induced NIT-1 cell death in vitro and inhibition of caspases or RIPK1 protect PTPN6 deficient NIT-1 cells from enhanced TNF-α induced cell death. This is the first evidence for a role of RIPK1 regulating TNF-α induced NIT-1 cell death.
In the past decade there has been progress in understanding how the TNF-α receptor complex contributes to different forms of cell death, including RIPK1 dependent, RIPK1 independent and necroptotic cell death. The inactivation of various components of the
TNF-α receptor complex can lead to different cell death outcomes.
Typically, the initial membrane bound primary complex which drives MAPK and
NF-kB signalling (complex I) is stabilised by ubiquitin chains formed by IAPs and LUBAC
[452-454]. This complex is comprised of RIPK1, TRADD, TAK1, IKKα/b, FADD and caspase-8 [455, 456]. TAK1 and IKKα/b are responsible for the activation of MAPKs and
NF-kB which inhibit the activity of caspase-8, further stabilising the membrane bound complex [155, 436, 457]. If NF-kB signalling is inhibited then the complex can be internalised to trigger the cytosolic RIPK1-independent form of apoptosis dependent on caspase-8 (complex IIa, TRADD-FADD-caspase-8) [458, 459]. Serine phosphorylation of
RIPK1 by IKKα/b in the absence of NF-kB signalling prevents an alternative form of apoptosis dependent on RIPK1 and caspase-8 (complex IIb, RIPK1-FADD-caspase-8)
[151, 152]. When caspase-8 is inactive in the previous mentioned forms of cell death, caspase independent necroptosis is activated by RIPK1 and RIPK3 leading to MLKL oligomerisation and cell membrane disruption [126, 438, 439].
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Here in an attempt to decipher which form of cell death is triggered by TNF-α in
NIT-1 cells we utilized the pan-caspase inhibitor Z-VAD.FMK and the RIPK1 inhibitor
Nec-1. First, we were able to rule out necroptosis as caspase inhibition prevented NIT-1 cell death. NIT-1 cells are defective in NF-kB signalling due to lack of the p65 component of the heterodimer [80]. Indeed, restoration of NF-kB activation by p65 overexpression in
NIT-1 cells prevented cell death. The ability of NF-kB to protect from TNF-α induced cell death is attributed to induced expression of pro-survival genes such as cFLIP which inhibits caspase-8 activity preventing downstream caspase-3 cleavage [44, 145, 146, 432]. We were able to show caspase-3 cleavage in NIT-1 cells which was enhanced by PTPN6 deficiency and absent with p65 over expression. To understand the cross talk between PTPN6 and
TNF-α induced NF-kB signalling and cell death responses in NIT-1 cells experiments studying PTPN6 inhibition or deletion in NIT-1.p65 cells stimulated with TNF-α would need to be completed.
PTPN6 deficient cells also had caspase-8 cleavage as observed by the p-10 fragment which was not observed in PTPN6 sufficient cells or those that overexpress p65.
These results suggest that PTPN6 has a negative regulatory role at the receptor complex, however there are little to no tyrosine phosphorylation sites at this stage of the signalling complex, such as on RIPK1 which is primarily phosphorylated on serine residues. Z-
VAD.FMK is reported to trigger cell death by autocrine production of TNF-α in L929 cells through AP-1 activation when NF-kB signalling is inhibited [460]. AP-1 is activated by
JNK signalling and we have previously shown that PTPN6 deficiency enhances JNK activity, thus PTPN6 deficiency may enhance autocrine production of TNF-α in NIT-1 cells which could further influence their commitment to cell death. If hyper TNF-α induced
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JNK activity in PTPN6 deficient cells was able to induce further TNF-α expression this may force PTPN6 deficient cells to commit to caspase-8 induced cell death. Selective caspase-8 inhibitors are commercially available (IETD.FMK) and it would be interesting to reperform these experiments to observe if caspase-8 inhibition protects PTPN6 deficient cells from TNF-α induced cell death [461, 462].
We have also shown that RIPK1 activity is important in TNF-α induced cell death in NIT-1 cells as treatment with Nec-1 inhibited cell death induction and caspase cleavage.
This is suggestive that cells were committing to RIPK1 dependent apoptosis. However, typically TNF-α induced RIPK1 dependent apoptosis occurs within 12 hours of stimulation and NIT-1 cells required 48 hours of stimulation to observe cell death [151]. Whether NIT-
1 cells possess other abnormalities in the receptor complex that could affect the commitment to these various pathways is unclear. NIT-1 cells are derived from adenomas achieved by overexpression of the SV40 large T-antigen so it is probable that there are various other artefacts in this cell line that may affect signaling [266]. It would be of interest to characterize whether all receptor complex components are expressed in these cells, or indeed to reperform these experiments in another cell line model. Of note, the susceptibility of NIT-1 cells to TNF-a induced cell death is a particular feature of this b-cell line, as primary b-cells do not succumb to apoptosis induced by TNF-a alone.
Collectively these results show that TNF-α induced cell death in PTPN6 deficient and sufficient NIT-1 cells can be prevented by RIPK1 inhibition and requires the involvement of caspases. How PTPN6 directly regulates these processes remains unknown but could involve autocrine production of TNF-α further committing deficient cells to death induction. Further dissection of alternate TNF-α induced cell death regulated by
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RIPKs is still an understudied field but understanding these pathways is showing promise in improving in vivo studies of inflammatory disorders.
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7.1 Thesis overview:
Tyrosine phosphorylation has a pivotal role in the transduction and regulation of intracellular signals. The simple reaction of adding or removing a phosphate group from a tyrosine residue can alter cell function, proliferation, migration and survival. Currently, two PTPs are associated with T1D, PTPN22 and PTPN2 [2, 463, 464]. PTP variants associated with T1D have strong links to altered autoreactive lymphocyte function that exacerbate pathology [465, 466]. However, in the past decade studies have begun to shed light on a b-cell intrinsic role for PTPs in the negative regulation of inflammatory and cytotoxicity responses triggered by IFN-g in models of T1D [53-55].
In the first part of this study it was shown that delivery of mito-TEMPO through drinking water could partially reduce PTP oxidation in the pancreata of NOD/Lt mice, previously shown to contribute to IFN-g induced b-cell demise in vitro [53]. Mito-TEMPO did not affect immune-mediated insulitis or diabetes development, suggesting that this potential b- cell protective therapy could be combined with an immune therapy to prevent or delay diabetes.
In the second part of this study, I looked more closely at the roles of two PTPs, PTPN1 and
PTPN6, in cytokine signalling in beta cell lines and primary islets. I showed that PTPN1 possesses a positive regulatory role for the induction of IFN-g as well as TNF-a and IL-1b signalling in NIT-1 cells and isolated NODPI islets in vitro, opposite to that of previous reports for other PTPs in b-cells [53-55]. Inactivation of PTPN1 ablated tyrosine activated signalling cascades triggered by the afore mentioned cytokines, reduced induction of key
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inflammatory gene signatures and protected NOD/Lt islets from autoreactive T-cell induced death. These results highlight a novel role for targeting PTPN1 for a protective response to b-cells in autoimmune diabetes.
I then identified PTPN6 as a negative regulator of TNF-a induced NIT-1 cell death that correlated with JNK dependent BCL-2 protein reduction in vitro, previously unreported in b-cells. Moreover, I showed that cell death induced by TNF-a in PTPN6 deficient NIT-1 cells is regulated by the process of caspase and RIPK1 dependent apoptosis. NIT-1 cells are not identical to primary b-cells because they lack functional NF-kB signalling [79, 80], so these studies would need to be completed in NF-kB competent b-cell lines and primary cells to determine their relevance to T1Ds. Nevertheless, these results are of interest in expanding the understanding of TNF-a signalling regulation in cell death.
7.2 Positive cytokine signalling regulated by PTPN1 and potential applications in
current T1D therapies:
PTPN1 is expressed in all tissues of the human body and was the first PTP to be characterised, purified and sequenced a decade after the first PTK was cloned [467, 468].
It remains the fundamental example of PTPs and most enzymological understanding of this protein family stems from PTPN1 studies. What we know of PTPN1 comes from identification of its diverse set of substrates including components of the insulin receptor
(IR), JAK/STAT and MAPK signalling pathways and biochemical studies revealing how it alters their activity [52, 469-476].
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In chapter 4 we showed the cytoprotective effects that inactivation of PTPN1 provided to the NIT-1 b-cell line, however the direct mechanism by which PTPN1 regulates these pathways remains unknown. Our findings support many of the current models of IFN-g, TNF-a and IL-1b signalling in primary islets and b-cell lines in vitro. It confirms that IFN-g induced STAT1 signalling has a central role in presenting b-cell antigens to immune cells through upregulation of MHC-I molecules and decreased MHC-
I expression protects b-cells from autoimmune destruction [75, 92, 96, 361, 362]. It also supports that IFN-g, TNF-a and IL-1b induce the expression of iNOS and chemokine expression in primary islets and induce death of b-cell lines in vitro when treated in combination which can be decreased with reduced STAT1 and MAPK signalling [42, 43,
54, 55, 74, 166, 299, 370]. We were able to show that reduced IFN-g, TNF-a and IL-1b signalling with PTPN1 inhibition partially reduced iNOS, CXCL9 and CXCL10 transcription in primary islets, however we were not able to show a significant reduction in TNF-a and IL-1b induced chemokine transcription.
Most studies of PTPN1 describe its function as a direct negative regulator of its targets, such as insulin induced IR phosphorylation [477-479] or leptin induced JAK2 phosphorylation [253, 254]. However, studies in neuroinflammation have revealed a positive regulatory role for PTPN1 in LPS and TNF-a signalling similar to what we observed in NIT-1 cells and NODPI islets in chapter 4. Neuroinflammation is an innate immunological response in the nervous system and is a hallmark of neurodegenerative diseases such as Alzheimer’s disease and multiple sclerosis [480]. Resident immune cells in the brain including microglia and macrophages release cytokines, chemokines and generate NO [481], similar to the innate response observed in the pancreas of NOD/Lt
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mice. PTPN1 is highly expressed in the microglia of the hippocampus in Alzheimer’s disease, and is also observed in the hypothalamus in T2D [482, 483]. LPS injection to the brain enhanced PTPN1 protein levels resulting in enhanced expression of proinflammatory molecules including TNF-a and iNOS [484]. Indeed, in vitro and in vivo treatment with a the same PTPN1 inhibitor used in this study reduced LPS and TNF-a induced expression of iNOS, COX-2 and TNF-a transcripts similar to the reduced gene expression we observed in chapter 4. PTPN1 was found to indirectly positively regulate LPS and TNF-a induced neuroinflammation through the dephosphorylation of the inhibitory Y527 residue on Src kinase, leading to its activation and further induction of inflammatory signalling
[484]. Src kinase is expressed in b-cells and is known to contribute to STAT1, JNK and p38 activation, all of which were ablated by PTPN1 deletion [485-494]. Src kinase can be inhibited with the small molecular inhibitor PP2 [495, 496], so it would be interesting to utilize this compound to further study if PTPN1 regulates Src signalling and contributes to cytokine induced b-cell dysfunction in vitro.
Collectively these previous studies and our data show that PTPN1 inhibition is not only a desirable target for T2D and neuroinflammation, it could also potentially be beneficial in T1D. The success of JAK inhibitors in their ability to prevent and reverse diabetes development in the NOD/Lt mouse through blockade of STAT1 signalling is an exciting development in the T1D field [96]. Comparatively PTPN1 inhibition not only reduced IFN-g induced STAT1 signalling but also TNF-a and IL-1b induced MAPK signalling and downstream transcription of iNOS and MHC-I in isolated islets in vitro, thus targeting PTPN1 would potentially have a broader range of effects on critical cytotoxic signalling pathways in b-cells than JAK inhibitors. PTPN1 deficient mice exist on the B6
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lineage and have no abnormalities in development or growth indicating that inhibitory treatments would be unlikely to have dire effects on the host [471]. The next step in verifying our results would be to obtain islets from PTPN1 deficient B6 mice and reperform our experiments of PTPN1 inhibited NODPI islets to confirm the reduced IFN-g, TNF-a and IL-1b signalling responses we observed. This would be beneficial as global knockout of the protein would provide more reliable evidence than the use of a selective inhibitor and it would confirm that the PTPN1 inhibitor we have been using is working appropriately. Our preliminary in vitro studies would also need to be tested in human islets and in vivo and this could be performed with soluble inhibitors, such as the potent PTPN1 inhibitor MSI-1436 [234], or genetic models such as b-cell specific PTPN1 deficient
NOD/Lt mice. These would allow us to test whether PTPN1 inhibition could reduce b-cell destruction by autoreactive T-cells in spontaneous autoimmune diabetes or reduce the ability of b cells to be recognised by cytotoxic T-cells.
T1D therapies aim to prevent the development of autoimmunity in at risk individuals, ablate the progression from asymptomatic disease and preserve or replace residual b-cell mass in diabetic individuals at clinical onset. Many antigen-specific and non-antigen- specific immunotherapies have been tested in preclinical and clinical disease to reduce or reverse the ability of immune cells to target and destroy b-cells. Antigen-specific treatments for T1D alone, against insulin for example [497-501], while well tolerated in patients and NOD/Lt mice, have limited efficacy on established autoimmunity. Whereas non-antigen-specific immunomodulatory therapies (anti-CD3 monoclonal antibodies [502-
505] and IL-1 signalling blockade [202, 506] for example) can improve b-cell survival but
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increase the risk of severe side effects with the required long term administration. Because of these caveats, combination immunotherapeutic approaches to treat T1D [507-509], along with transplantation of human islet cells [510], are an appealing strategy as they enable us to target various pathological compartments that contribute to T1D, optimise clinical efficacy and also improve safety of the treatments.
It is becoming increasingly recognised that b-cell themselves are not passive bystanders in T1D development but also contribute to the disease through expression of
MHC-I, chemokines, cytokines and iNOS that attract autoreactive immune cells to the islet microenvironment. Reducing expression of these genes decreases visibility of b-cells from the immune system and protects them from destruction which is observed with the use of
JAK inhibitors [96]. In this study we have shown that oral delivery of antioxidants is a safe therapy to reduce oxidation of PTPs in NOD/Lt mice, including important immunomodulatory PTPs like PTPN2 [53], and PTPN1 inhibition reduces the expression of immune attractive gene signatures in vitro. Combining these two safe approaches with short term immunotherapies, such as anti-CD3 monoclonal antibody mediated depletion of immune cells may have a beneficial effect in preserving b-cell function and mass in T1D.
Restoration of islet mass and enhancement of b-cell function and insulin sensitivity are an important goal in many T1D therapies. Histological samples from T1D patients show that b-cell destruction takes place over many years and insulin positive cells can still be identified as late as 50 years after diagnosis indicating patients still retain some degree of b-cell mass [20]. Islet transplantation is a current treatment for T1D patients that suffer recurrent severe hypoglycaemic episodes and high levels of insulin independence and control of hypoglycaemia have been achieved in the short term [511-513]. However, the
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efficiency of this approach remains poor due to low survival rate of islets during isolation and post transplantation and scarcity of donors [514]. Because of this, agonists and antagonists that enhance b-cell insulin production, release and peripheral sensitivity, such as glucagon-like peptide 1 agonists [515, 516], Y1 receptor blockade [517] and the calcium channel blocker Verapamil [353] are becoming more of clinical interest for combination therapy in T1D and islet transplantation. As inhibition of PTPN1 activity enhances b-cell function, survival and plasticity [518, 519] while also enhancing insulin sensitivity in the liver [520-525] and muscle [526-528], it may also be of clinical interest to provide a multifaceted therapy in reducing the metabolic strain on residual b-cell mass in T1D patients and transplanted islets while protecting them from autoimmune destruction.
Indeed, the PTPN1 inhibitor MSI-1436 tested in phase 1 clinical trials for T2D and metastatic breast cancer or the more bioavailable analogue DPM-1001 would be directly translatable into these studies [234, 529, 530]. Collectively, these studies and the novel findings in this thesis suggest that the broad range of immunological and metabolic effects achieved with PTPN1 inhibition may be of clinical benefit in T1Ds.
7.3 PTPN6 as a possible target for autoimmune disorders:
Our finding that PTPN6 negatively regulates RIPK1 dependent apoptosis when NF-kB signalling is disrupted is a novel finding in the field of cell death and the first to our knowledge of a PTP regulating this pathway. Because of the previously discussed caveats with using NIT-1 cells as a model b-cell, our results that PTPN6 negatively regulates TNF- a induced JNK dependent death in NIT-1 cells would need to be tested in other b-cell lines and primary islets to demonstrate relevance to the wider literature of autoimmune diabetes.
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PTPN6 has been strongly linked to the regulation of immune cell signalling for over half a century after Jackson labs developed the spontaneous mutant motheaten and motheaten viable strains of B6 mice [228, 257, 406]. Negative regulation of TNF-a induced cell death by PTPN6 could help to explain the dire autoimmune pathology in the motheaten mouse as these mice present with elevated levels of TNF-a in their lungs after death by pneumonitis. Low PTPN6 activity results in the development of a myriad of autoimmune diseases including neutrophilic dermatosis, allergic asthma, rheumatoid arthritis and multiple sclerosis [531-535]. The vast number of defects resulting from
PTPN6 deficiency drove great interest in studying what signalling pathways were involved to find potential targets to treat autoimmune diseases. Neutrophilic dermatosis, including
Sweet’s syndrome, pyoderma gangrenosum and subcorneal pustular dermatosis are autoimmune diseases that result in skin lesions similar to those observed on the footpads of motheaten mice [536]. PTPN6 dysregulation was found to exacerbate the disease by sensitising neutrophils to IL-1a dependent RIPK1/TAK1 induced inflammatory gene expression [537].
In chapters 5&6 we showed that PTPN6 deficiency lead to dysregulation of the
RIPK1 and MAPK axis induced by TNF-a, which has a similar receptor signalling cascade to IL-1a, suggesting there may be overlapping targets in PTPN6 regulated pathologies.
Inhibitors for various components of IL-1a signalling have been developed to treat rheumatic diseases, including Syk and MyD88 inhibitors [538, 539], and are currently under investigation for neutrophilic dermatosis [536, 540]. We showed that inhibition of
RIPK1 with Nec-1 protected PTPN6 deficient NIT-1 cells from TNF-a induced death, however RIPK1 inhibition did not affect IL-1a induced neutrophilic inflammation. These
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results suggest that inhibiting cell death in contrast to inflammatory gene expression may be redundant [541].
PTPN6 agonists have recently become of interest for triple-negative breast cancer because of its role as a tumour suppressor gene [542-545]. STAT3 hyperactivity is strongly linked to triple-negative breast cancer and promotes proliferation, metastasis and survival
[546-548]. Nintedanib is a PTPN6 agonist which promotes enzymatic activity by altering
PTPN6 from its natural autoinhibitory conformation, opening access to the PTP active site and promoting apoptosis of cancer cells through STAT3 dephosphorylation in xenograft models of triple-negative breast cancer [543]. Nintedanib also reduces pulmonary fibrosis in mice and in 2015 begun a phase III clinical trial for systemic sclerosis associated interstitial lung disease through the SENSCIS study by Boehringer Ingelheim [549, 550].
The randomised, double-blind, placebo-controlled study concluded in November 2018 with 576 patients receiving treatment and no clinical benefit of Nintedanib observed for manifestation of systemic sclerosis. Collectively these data show that PTPN6 agonism could also be a potential therapeutic strategy for targeting autoimmune and autoinflammatory diseases which rely on hyperactive cytokine signalling.
7.4 Substrate identification of PTPs:
Identifying the interaction partners and/or substrates of PTPN1 and PTPN6 would be of great interest in future experiments. The gold standard approach for describing how PTPN1 and PTPN6 regulate the pathways described in this thesis would be to identify their direct substrates. This could be performed with the transfection and immunoprecipitation of competitive substrate trapping mutants followed by mass spectrometry for protein
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identification. Multiple substrate trapping mutants have been developed as molecular tools for identifying the proteins PTPN1 and PTPN6 interact with including PTPN1-
D181A/PTPN1-C215A and PTPN6-D419A, respectively [551-555]. Point mutations of amino acids that interact with the substrate to alanine residues prevent the substrate from dissociating from the transfected mutant. This technique would allow a precise proteomic approach to identify the majority of components each PTP interacts with after cytokine stimulation.
As there are no obvious targets for PTPN1 and PTPN6 in our models to explain our results, certain cell signalling prediction technologies and databases may prove useful to suggest potential substrates. These technologies for PTPs however are far inferior to those of kinases as there is an approximate decade discrepancy of research input between the two fields. This is apparent from the 305 PTP substrates identified on the human
DEPhOsphorylation database (DEPOD) in comparison to the 10257 kinase substrates on the RegPhos database [556, 557]. Computational technologies exist in an attempt to predict general phosphorylation sites that could be used as starting points for substrate identification. These include Group-Based prediction System (GPS) [558], DISorder- enhanced PHOSphorylation predictor (DISPHOS) [559], NetPhos [560], and GANNPhos
[561]. These, however, typically rely on possessing some knowledge of the substrate or phosphorylation site sequence and reverse predicting the substrate or phosphatase thus are not particularly useful for our models.
Future studies will be thus required to clarify the substrates of PTPN1 and PTPN6 in cytokine signalling in beta cells. For example, immunoprecipitation of the phosphatases in cytokine treated beta cell lines and isolated islets using mass spectrometry to detect all
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substrates at different time points. These are not trivial experiments, which go beyond the possibilities of the present thesis.
7.5 Concluding remarks:
In this thesis we describe how PTPN1 and PTPN6 contribute to inflammatory cytokine regulation in vitro models of autoimmune diabetes. We show that PTPN1 is a positive regulator of IFN-g, TNF-a and IL-1b and protects NOD/Lt islets from autoimmune destruction highlighting it as a potential target for autoimmune diabetes and further analysis. We also show that PTPN6 negatively regulates TNF-a signalling leading to enhanced NIT-1 cell death and could be used to further investigate cell death mechanisms in cytokine induced autoimmune disorders.
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References:
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554. Xie, Z.H., J. Zhang, and R.P. Siraganian, Positive regulation of c-Jun N-terminal kinase and TNF-alpha production but not histamine release by SHP-1 in RBL- 2H3 mast cells. J Immunol, 2000. 164(3): p. 1521-8. 555. Chen, Z., et al., Signaling thresholds and negative B cell selection in acute lymphoblastic leukemia. Nature, 2015. 521(7552): p. 357-61. 556. Duan, G., X. Li, and M. Kohn, The human DEPhOsphorylation database DEPOD: a 2015 update. Nucleic Acids Res, 2015. 43(Database issue): p. D531-5. 557. Lee, T.Y., et al., RegPhos: a system to explore the protein kinase-substrate phosphorylation network in humans. Nucleic Acids Res, 2011. 39(Database issue): p. D777-87. 558. Xue, Y., et al., GPS 2.0, a tool to predict kinase-specific phosphorylation sites in hierarchy. Mol Cell Proteomics, 2008. 7(9): p. 1598-608. 559. Iakoucheva, L.M., et al., The importance of intrinsic disorder for protein phosphorylation. Nucleic Acids Res, 2004. 32(3): p. 1037-49. 560. Blom, N., S. Gammeltoft, and S. Brunak, Sequence and structure-based prediction of eukaryotic protein phosphorylation sites. J Mol Biol, 1999. 294(5): p. 1351-62. 561. Tang, Y.R., et al., GANNPhos: a new phosphorylation site predictor based on a genetic algorithm integrated neural network. Protein Eng Des Sel, 2007. 20(8): p. 405-12.
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Minerva Access is the Institutional Repository of The University of Melbourne
Author/s: Stanley, William James
Title: Activation of islet inflammation by cytokine signalling in pancreatic beta cells: understanding the role of protein tyrosine phosphatases
Date: 2018
Persistent Link: http://hdl.handle.net/11343/235869
File Description: Final thesis file
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