ENDOPLASMIC RETICULUM STRESS IN PANCREATIC β-CELLS

ER STRESS AND CYTOKINE-MEDIATED β-CELL DYSFUNCTION AND APOPTOSIS

ANALYSIS OF THE ER STRESS RESPONSE IN A PANCREATIC β-CELL LINE EXPRESSING A FOLDING-DEFICIENT PROINSULIN-EGFP FUSION PROTEIN

By

Taila Hartley

A thesis submitted in conformity with the requirements

for the degree of Master of Science

Graduate Department of Biochemistry

University of Toronto

© Copyright by Taila Hartley 2009

ENDOPLASMIC RETICULUM STRESS IN PANCREATIC β-CELLS:

ER STRESS AND CYTOKINE-MEDIATED β-CELL DYSFUNCTION AND APOPTOSIS

ANALYSIS OF THE ER STRESS RESPONSE IN A PANCREATIC β-CELL CLONE EXPRESSING A FOLDING-DEFICIENT PROINSULIN-EGFP FUSION

PROTEIN

Taila Hartley

Master of Science, Graduate Department of Biochemistry, University of Toronto, 2009

ABSTRACT

Endoplasmic reticulum (ER) stress has been implicated in pancreatic β-cell loss

contributing to diabetes mellitus, however the molecular mechanisms of ER stress-

induced apoptosis are unclear. In the first project of this thesis, the contribution of ER

stress in proinflammatory cytokine-mediated β-cell dysfunction and apoptosis is

examined. Although exogenous cytokine treatment did induce unfolded protein

response (UPR) genes, increased chaperone capacity had no effect on apoptosis

induction, insulin biosynthesis and insulin secretion. Thus, ER stress is most likely not

an important pathway in cytokine toxicity under our experimental system. The second

project develops a pathophysiological model of ER stress based on the mutant

misfolded insulin of the Akita mouse. Microarray analysis was conducted and we

observed early induction of ER chaperone and ER-associated degradation (ERAD)

genes, followed by a large increase in pro-apoptotic genes with mutant insulin

expression. A detailed analysis of the ER stress response in this system is presented.

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ACKNOWLEDGEMENTS

This thesis would not have been possible without the input and encouragement

of numerous individuals, and to them I would like to express my sincere gratitude.

First and foremost, I would like to thank my supervisor, Dr. Allen Volchuk, for

his constant enthusiasm and open door over the last two years. His support and

encouragement in not only experimental work but in written work and presentations as

well, have allowed me to complete these projects to the best of my ability while at the

same time gaining valuable experiences. In particular, I would like to thank Allen for

the chance to present at the American Society for Cell Biology Conference (2008) in

San Francisco and the chance to help write a review paper published in the American

Journal of Physiology. I would also like to thank my committee members, Dr.

Williams and Dr. Grinstein for their helpful ideas and suggestions on my studies.

These projects would not have been completed without the help of numerous

technicians including Monika Sharma (UHN Microarray Facility), Doug Holmyard

(Mount Sinai Electron Microscopy Facility) and Leanne Jamieson (Sick Kids Flow

Cytometry Facility).

I would also like to thank the entire Volchuk lab, past and present, for providing

the best lab environment I have ever experienced. I have no doubt that Elida’s hard

work a couple of years ago provided me with a solid base to build my project and made

my life much easier. In addition, I need to thank Elida for her efforts in training me at

the beginning of my project. Liling’s incredibly hard work to keep the lab functioning

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smoothly are only topped by all of the effort she devotes to helping everyone in the lab

with new techniques and for that she is without a doubt the most valuable asset of the

entire lab. Thanks Liling. Tracy, my best biochemistry buddy and the most

phenomenal dance partner, your constant encouragement and help with everything

from life to cloning have made this thesis possible. Ravi, the source of all answers

whether about techniques or politics, thanks for being a great labmate. Madura, the

most generous person I know, it’s been incredible sharing the lab with you over the last

year. I’d also like to thank the new students of the lab, Akansha and Irmgard, as well

as the entire 10th floor of MaRS-TMDT for their encouragement and friendship.

Finally, I’d like to thank my family and friends who have been a constant

source of encouragement. Thanks mom and dad for keeping me out of trouble and

reminding me of the value of education. To my sisters (Kendra, Yasmin and Tara) and

brothers (Scott and Nick), thanks for always being only a phone call away. To

Brendon, thanks for making anywhere we are feel like home and standing by me

whatever decisions I make.

Last, but certainly not least, I’d like to thank the Banting and Best Diabetes

Centre for funding my work and giving me the opportunity to present my results on

several different occasions.

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TABLE OF CONTENTS

ABSTRACT II

ACKNOWLEDGEMENTS II

TABLE OF CONTENTS V

LIST OF FIGURES VIII

LIST OF ABBREVIATIONS X

CHAPTER 1: INTRODUCTION 1 1.1 THE ENDOPLASMIC RETICULUM 2 1.2 MOLECULAR CHAPERONES OF THE ER 4 1.2.1 GRP78 6 1.3 ER-RESIDENT PROTEIN DEGRADATION 8 1.3.1 ERAD I 8 1.3.2 ERAD II 11 1.4 ER STRESS AND THE UNFOLDED PROTEIN RESPONSE 12 1.4.1 PERK SIGNALING DURING THE ER STRESS RESPONSE 14 1.4.2 IRE1 SIGNALING DURING THE ER STRESS RESPONSE 16 1.4.3 ATF6 SIGNALING IN THE ER STRESS RESPONSE 17 1.4.4 RECOVERY FROM THE UNFOLDED PROTEIN RESPONSE 18 1.5 ER STRESS-INDUCED APOPTOSIS 19 1.4.1 CHOP 20 1.4.1 JNK 22 1.4.2 CASPASE-12 23 1.5 BIOSYNTHESIS AND SECRETION OF INSULIN IN PANCREATIC Β-CELLS 24 1.5.1 INSULIN BIOSYNTHESIS 25 1.5.2 MECHANISMS OF INSULIN RELEASE 26 1.6 ER STRESS IN PANCREATIC β-CELLS 28 1.7 MECHANISMS OF β-CELL DYSFUNCTION IN TYPE 1 AND TYPE 2 DIABETES 30 1.7.1 CYTOKINES, INTERLEUKIN-1β, INTERFERON-γ AND NITRIC OXIDE 32 1.7.2 CYTOKINES, ER STRESS, AND PANCREATIC β-CELL APOPTOSIS 35 1.7.3 CYTOKINES AND β-CELL DYSFUNCTION 38 1.8 RATIONALE AND HYPOTHESIS 40

CHAPTER 2: MATERIALS AND METHODS 42 2.1 CELL CULTURE 43 2.2 CYTOKINE PREPARATION, CELL TREATMENT AND LYSES 43 2.3 INFECTION OF INS-1E WITH GRP78 ADENOVIRUS (AD-GRP78) 44 2.4 REVERSE TRANSFECTION OF SHORT INTERFERING RNA (SIRNA) 45 2.5 MEASUREMENT OF XBP-1 MRNA SPLICING 45 2.6 RNA ISOLATION AND REAL-TIME QUANTITATIVE POLYMERASE CHAIN REACTION

(PCR) 46 2.7 ELECTRON MICROSCOPY 47 2.8 INSULIN SECRETION ASSAY AND RAT INSULIN RADIOIMMUNOASSAY (RIA) 48 2.9 WESTERN BLOT ANALYSIS 49 2.10 SUCROSE DENSITY FRACTIONATION 50

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2.11 IMMUNOPRECIPITATION 51 2.12 APOPTOSIS ASSAYS 52 2.12.1 ELISAPLUS CELL DEATH DETECTION KIT 52 2.12.2 FLOW CYTOMETRY-BASED APO-BRDU TUNEL ASSAY 52 2.13 MICROARRAY ANALYSIS 53 2.14 CLONING OF SDF2-L1 54 2.15 TRANSIENT TRANSFECTION 57 2.15 DATA ANALYSIS 58

CHAPTER 3: ER STRESS AND CYTOKINE-INDUCED PANCREATIC β-CELL DYSFUNCTION AND APOPTOSIS 59 3.1 INTRODUCTION 60 3.2 RESULTS 62 3.2.1 CYTOKINES INDUCE APOPTOSIS IN INS-1E CELLS. 62 3.2.2 CYTOKINES ACTIVATE AN EARLY ER STRESS RESPONSE IN INS-1E CELLS. 63 3.2.3 GRP78 OVEREXPRESSION OR TREATMENT WITH CHEMICAL CHAPERONE DOES NOT PROTECT INS-1E CELLS FROM CYTOKINE-INDUCED β-CELL APOPTOSIS. 66 3.2.4 GRP78/BIP KNOCKDOWN INCREASES INS-1E SUSCEPTIBILITY TO CYTOKINE- INDUCED

APOPTOSIS AND POTENTIATES THE EFFECTS OF CYTOKINES TO REDUCE PROINSULIN LEVELS. 67

3.2.5 GRP78 OVEREXPRESSION DOES NOT AMELIORATE CYTOKINE-INDUCED β-CELL DYSFUNCTION IN INSULIN BIOSYNTHESIS OR SECRETION. 70 3.2.6 EFFECT OF CYTOKINE TREATMENT ON RAT ISLET INSULIN BIOSYNTHESIS AND

SECRETION. 71 3.3 DISCUSSION 74 3.4 SUMMARY AND FUTURE DIRECTIONS 79

CHAPTER 4: ANALYSIS OF THE ER STRESS RESPONSE IN A PANCREATIC β-CELL LINE EXPRESSING A FOLDING-DEFICIENT PROINSULIN-EGFP FUSION PROTEIN 82 4.1 INTRODUCTION 83 4.1.1 METHODS: GENERATION AND CHARACTERIZATION OF THE INSULIN 2 (C96Y)-EGFP

STABLE INS-1 CELL LINE 85 4.2 RESULTS 87 4.2.1 THE ER STRESS RESPONSE TO INSULIN2 (C96Y)-EGFP EXPRESSION 90 4.2.2 MICROARRAY ANALYSIS OF INSULIN2 (C96Y)-EGFP EXPRESSION 90 4.2.3 INDUCTION OF APOPTOSIS FOLLOWING INS2 (C96Y)-EGFP EXPRESSION 97 4.3 DISCUSSION 102 4.4 SUMMARY AND FUTURE DIRECTIONS 109

APPENDIX 1: MICROARRAY RESULTS FROM THE ANALYSIS OF THE ER STRESS RESPONSE IN CLONE #4S2 112

APPENDIX 2: EXAMINING THE ROLE OF STROMAL DERIVED FACTOR 2-LIKE 1 IN PANCREATIC β-CELL ER STRESS AND APOPTOSIS 127 A2.1 RATIONALE AND HYPOTHESIS 128 A2.2 RESULTS 129 A2.2.1 SDF2L1 IS INDUCED IN MKR MICE, ANOTHER MODEL OF DIABETES 129

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A2.2.2 GENERATION OF EXPRESSION VECTORS FOR A FUNCTIONAL ANALYSIS OF SDF2L1 130 A2.3 SUMMARY AND FUTURE DIRECTIONS 132

REFERENCES 134

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LIST OF FIGURES

CHAPTER 1: INTRODUCTION

Figure 1.1 Functions of GRP78 in the ER.

Figure 1.2 Signaling in the unfolded protein response.

Figure 1.3 ER stress-induced apoptosis.

Figure 1.4 Insulin biosynthesis and glucose-stimulated insulin secretion.

Figure 1.5 Model of how cytokines may induce ER and potentially apoptosis in β-cells.

CHAPTER 3: ER STRESS AND CYTOKINE-INDUCED PANCREATIC β -CELL DYSFUNCTION AND APOPTOSIS

Figure 3.1 Cytokines induce cell death in the rat pancreatic β-cell line INS-1E.

Figure 3.2 Cytokine exposure induces the UPR in INS-1E cells.

Figure 3.3 Effect of GRP78 overexpression or PBA treatment on cytokine-induced apoptosis in INS-1E cells.

Figure 3.4 siRNA-mediated silencing of GRP78 expression in INS-1E cells renders them more susceptible to cytokine-induced apoptosis.

Figure 3.5 Effect of cytokine exposure on insulin biosynthesis and secretion in INS-1E cells.

Figure 3.6 Effect of cytokine exposure on insulin biosynthesis and secretion in rat islets.

CHAPTER 4: ANALYSIS OF THE ER STRESS RESPONSE IN A PANCREATIC β-CELL CLONE EXPRESSING A FOLDING-DEFICIENT PROINSULIN-EGFP FUSION PROTEIN

Figure 4.1 Induction of Insulin2 (C96Y)-EGFP protein expression in pTet-ON INS-1 cells by doxycyline.

Figure 4.2 Insulin2 (C96Y)-EGFP is localized to the ER while degradation products appear in the cytosol.

Figure 4.3 Effect of Insulin2 (C96Y)-EGFP expression on ER morphology.

Figure 4.4 ER stress signaling pathways are activated by Insulin2 (C96Y)-EGFP expression.

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Figure 4.5 Expression of Insulin2 (C96Y)-EGFP induces genes associated with the ER stress response.

Figure 4.6 Expression of Insulin2 (C96Y)-EGFP induces ERdj4 and Ero1β, but not ERdj5 and Ero1α.

Figure 4.7 Expression of Insulin2 (C96Y)-EGFP induces apoptosis.

Figure 4.8 The proteasome inhibitor lactacystin increases susceptibility of the mutant insulin expressing clone to apoptosis.

Figure 4.9 Expression of Insulin2 (C96Y)-EGFP does not result in activation of autophagy.

APPENDIX 2: EXAMINING THE ROLE OF STROMAL DERIVED FACTOR 2-LIKE 1 IN PANCREATIC β-CELL ER STRESS AND APOPTOSIS

Figure A2.1 Sdf2l1 mRNA is induced in MKR mice.

Figure A2.2 Test Transfection of PA-IRES-Sdf2l1 in HEK293T cells.

Figure A2.3 SDF2L1 expression with Insulin2 (C96Y)-EGFP expression.

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LIST OF ABBREVIATIONS

3-MA 3-Methyladenine

ADP adenosine diphosphate

ATF4 activating transcription factor 4

ATF6 activating transcription factor 6

ATP adenosine triphosphate

BiP immunoglobulin heavy chain binding protein

Ca2+ calcium

CHOP C/EBP (CCAAT/enhancer binding protein) homologous protein

CHX cycloheximide

CNX calnexin

CPA cyclopiazonic acid

CRT calreticulin

Ddit3 DNA-damage inducible transcript 3

Der1 degradation in the ER-1

DTT dithiothreitol

Dox doxycycline

EGFP enhanced green fluorescent protein

EDEM ER degradation enhancing α-mannosidase-like protein

x

eIF-2α eukaryotic initiation factor 2α

ER endoplasmic reticulum

ERAD ER-associated degradation

ERSE ER-stress response element

FACS fluorescence-activated cell sorting

FBS fetal bovine serum

G418 Geneticin

GADD34 growth arrest and DNA damage 34

GADD153 growth arrest and DNA damage 153

GRP78 glucose-regulated protein 78

HERP homocysteine inducible ER protein

Hrd1 hypoxia responsive domain 1

IL-1β interleukin 1beta

IFN-γ interferon-gamma

iNOS inducible nitric oxide synthase

I.P. immunoprecipitation

IRE1 inositol-requiring ER-to-nucleus signal kinase 1

JNK c-Jun NH2-terminal kinase

KATP ATP-sensitive K+ channels

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KRBH Krebs-Ringer bicarbonate buffer

LMA NG-methyl-L-arginine

LSB Laemmli sample buffer

MHC major histocompatibility complex

mRNA messenger RNA

NF-κB nuclear factor-κB

NMA NG-monomethyl-L-arginine

NO nitric oxide

NOS nitric oxide synthase

PBA phenylbutyric acid

PC1 proinsulin convertase 1

PC2 proinsulin convertase 2

PCR polymerase chain reaction

PDI protein-disulfide isomerase

PERK double-stranded RNA-activated protein kinase (PKR)-like ER kinase

PI3K phophatidylinositol-3’-kinase

RIA rat insulin radioimmunoassay

ROS reactive oxyen species

RNA ribonucleic acid

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rtTA reverse tetracycline-controlled transactivator

S1P site-1 protease

S2P site-2 protease

Sel1 suppressor of Lin12-like protein

SDF2-L1 stromal derived factor 2-like 1

SERCA sarco-endoplasmic reticulum Ca2+-ATPase pump

siRNA short interfering RNA

SNAP S-nitroso-Nacetyl-D,L-penicillamine

STAT1 signal transducers of activated transcription 1

Staur staurosporine

Tg thapsigargin

Tn tunicamycin

TNFα tumor necrosis factor-α

TRAF2 TNF receptor-associated factor 2

TRB3 tribbles 3

UGGT UDP glucose:glycoprotein glucosyltransferase

UPR unfolded protein response

UPRE unfolded protein response promoter element

XBP1 X-box binding protein 1

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CHAPTER 1: INTRODUCTION

1

This thesis consists of two distinct projects that focus on examining endoplasmic

reticulum stress-induced apoptosis in pancreatic β-cells using different model systems.

This chapter will therefore focus first on providing a basic introduction to ER function

under normal conditions and the concept of ER stress. The cell-survival pathways

involved in the management of ER stress and how chronic ER stress leads to apoptosis

will also be discussed. A detailed literature review of the effects of cytokines in

pancreatic β-cells will be presented as it pertains to the project described in Chapter 3.

Finally, pancreatic β-cell function, including insulin biosynthesis and secretion, will be

discussed as well as the effects of β-cell dysfunction in contributing to type 1 and type

2 diabetes.

1.1 The Endoplasmic Reticulum

The endoplasmic reticulum (ER) is a large membrane-bound organelle that

functions to support the biosynthesis of membrane and secretory proteins, which

account for approximately one third of all proteins in a eukaryotic cell.

Protein folding begins as the nascent polypeptide chain is cotranslationally

translocated through the ER membrane into the ER lumen. The unique environment of

the ER lumen allows for both oxidative protein folding as well as post-translational

modification. The presence of ER-residing chaperones, such as glucose-regulated

protein 78 (GRP78), and folding catalysts, such as protein disulfide isomerases (PDIs)

help maintain protein solubility while also increasing the rate of protein folding. This

is essential as only properly folded proteins are able to exit the ER in COPII vesicles

destined for the Golgi compartment. Once properly folded, polypeptides enter the

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anterograde trafficking pathway due to their interaction with specific cargo receptors

and components of the ER-budding vesicles that contain COPII assembly proteins. The

mechanisms that distinguish properly folded from improperly folded polypeptides are

complex and still unclear, however they will be discussed briefly in the section

pertaining to ER-associated degradation (1.3.1).

In addition to its involvement in membrane and secretory protein synthesis, the

ER has an important role in calcium storage and signaling. The resting intra-ER Ca2+

concentration is three to four orders of magnitude higher than the cytoplasm. This

gradient is generated by the sarco(endo)plasmic reticulum Ca2+ ATPase (SERCA)

pump, which pumps Ca2+ into the ER lumen (Berridge, 2002). The stored calcium is

used as a signaling molecule following regulated release into the cytosol, in addition to

being required for the function of certain ER chaperone proteins.

To monitor the ER and ensure that protein quality is not sacrificed for quantity,

the ER enlists a quality control system that monitors protein folding and ensures only

properly folded and assembled proteins are transported from the ER to the Golgi and

ultimately to their final destination. Diverse molecular chaperones and folding

enzymes reside in the ER and help maintain protein solubility while aiding in folding.

This system also includes a system for identifying terminally misfolded proteins and

targeting them for degradation. In addition, a variety of stressors can perturb ER

function and result in the accumulation of unfolded proteins. The quality control

system of the ER is able to monitor the ER lumen and recognize the accumulation of

unfolded proteins, triggering the unfolded protein response (UPR). Each of these

quality control systems will be discussed briefly in the sections to follow.

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1.2 Molecular chaperones of the ER

As soon as a portion of a nascent polypeptide is translocated into the ER folding

of the polypeptide into its tertiary structure may begin. In order to facilitate

polypeptide folding, a group of resident ER proteins, called molecular chaperones, bind

to and protect nascent chains from inappropriate interactions (Hendershot, 2004).

Chaperone binding thus protects nascent polypeptides from aggregating with other

exposed hydrophobic residues and patches in the ER lumen, effectively aiding proteins

in reaching their native conformations.

The components of two major ER chaperone systems have been examined

extensively. The first one is dependent on the presence of monoglucosylated N-linked

glycans on the unfolded proteins. As polypeptides are cotranslationally translocated

into the ER, Asn residues of Asn-X-Ser(Thr) sequences are glycosylated with

preassembled Glc3Man9GlcNAc2 oligosaccharides by oligosaccharyltransferase (OST).

The oligosaccharides are then processed by glucosidase-I and II, removing the outer

two glucoses and generating Glc1Man9GlcNAc2, which can be recognized and bound

by the ER chaperones calnexin (CNX) and calreticulin (CRT) (Sousa et al., 1992;

Hammond et al., 1994). CNX/CRT binding is dependent on the terminal glucose, and

cleavage of this glucose abrogates the interaction (Kornfeld and Kornfeld, 1985;

Trombetta and Parodi, 1992; Hebert et al., 1995). The glycoprotein is therefore

released from its interactions with CNX/CRT by removal of its terminal glucose by

glucosidase-II. If the protein is not properly folded, the terminal glucose is re-attached

by UDP-glucose:glycoprotein glucosyltransferase (UGGT), which is able to bind

unfolded regions on the substrate (Trombetta and Parodi, 1992), and CNX/CRT rebind

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to continue the cycle (Sousa et al., 1992; Hebert et al., 1995). If, however, the protein

is folded correctly, it will not be recognized by UGGT and will be transported out of

the ER.

How this system functions to promote protein folding is still unclear. One

theory contends that the hydrophobic patches of the folding glycoprotein are

sequestered between the extended arm domain and the globular lectin domain of CNX

and CRT. This sequestration reduces the chances of these patches aggregating with

other exposed hydrophobic patches (Williams et al., 2006). The recruitment of ERp57,

a member of the PDI family of thiol oxidoreductases, by CNX and CRT may also play

a role by enhancing disulphide formation and isomerization (High et al., 2000).

The second ER chaperone system only depends on the presence of hydrophobic

residues in unfolded regions on proteins. By masking these hydrophobic patches,

aggregation with other exposed hydrophobic patches is suppressed, promoting protein

folding. The most important component of this system is glucose-regulated protein 78

(GRP78), which is responsible for binding the unfolded protein (Flynn et al., 1991;

Blond-Elguindi et al., 1995) and is discussed in detail below. The presence of

interacting chaperones and co-chaperones in a multisubunit complex improves the

efficiency of folding using similar cycles to the CNX/CRT system of binding and

release from unfolded proteins. Studies on immunoglobulin heavy chains have

identified a multiprotein complex comprised of GRP78, GRP94, CaBP1, protein

disulfide isomerase (PDI), ERdj3, cyclophilin B, ERp72, GRP170, UDP-GT and

stromal-derived factor 2-like 1 (SDF2L1) (Meunier et al., 2002).

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1.2.1 GRP78

GRP78, also commonly referred to as immunoglobulin heavy chain Binding

Protein (BiP), is a member of the Heat shock protein 70 (Hsp70) chaperone family, and

was one of the first chaperones identified due to its interaction with incompletely

assembled subunits of antibody molecules (Haas, 1983). GRP78 is comprised of an

ATPase domain, a peptide-binding domain and a C-terminal domain with an unknown

function (King et al., 2001).

The chaperone function of GRP78, and all other Hsp70 family members, is

controlled by the hydrolysis of adenosine triphosphate (ATP). The ATP-bound state

represents an “open” configuration that is able to associate with unfolded proteins with

low affinity (Kassenbrock and Kelly, 1989; Wei and Hendershot, 1995; Bukau and

Horwich, 1998). The ATPase activity of GRP78 hydrolyzes ATP to ADP (adenosine

diphosphate), resulting in a conformational change that results in GRP78 having a high

affinity for the bound substrate. Conversion of GRP78 back to the low-affinity state is

then mediated through the exchange of ADP for ATP with the help of nucleotide

exchange factors (Schroder and Kaufman, 2005). The rate of the ATPase cycle is

highly influenced by the presence of co-factors such as the cochaperone DnaJ-like

proteins Erdj1-5 (Cheetham et al., 1998; Liberek, et al., 1991) and nucleotide exchange

factors, such as BiP-associated protein (BAP) (Chung et al., 2002). By continuously

binding and releasing the unfolded protein, GRP78 ensures that the unfolded protein

does not aggregate with other proteins, allowing the substrate to proceed towards an

increasingly folded state.

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Figure 1.1 Functions of GRP78 in the ER. Apart from its main role as an ER chaperone, aiding in the folding of unfolded polypeptides translocated into the ER lumen, GRP78 has a variety of other functions. These include maintaining the permeability of the ER membrane by sealing the luminal side of the SEC61 translocon, targeting proteins for ERAD, and calcium retention. In addition, when ER homeostasis is perturbed unfolded proteins accumulate in the ER lumen, a situation termed ER stress. GRP78 acts as the main regulatory protein for the ER stress response (discussed further in section 1.4).

Besides the exposed hydrophobic patches on unfolded proteins, GRP78 also

interacts with proteins (and ions) to function in a variety of other roles related to ER

homeostasis (Fig. 1.1). GRP78 is thought to maintain the permeability barrier of the

ER by sealing the luminal side of both inactive and active translocons (Alder et al.,

2005; Hamman et al., 1998). The simultaneous binding of GRP78 to both the

translocon and nascent polypeptide chain also infers a role for GRP78 in translocation

(Ma and Hendershot, 2004). GRP78 may have a role in targeting proteins for

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retrotranslocation during ER-associated degradation (ERAD) (discussed below)

(Skowronek et al., 1998; Cabral et al., 2002; Kabani et al., 2003). Furthermore, GRP78

can bind calcium (Ca2+) and has been shown to contribute to ER calcium storage

(Lièvremont et al., 1997). Finally, interactions between GRP78 and transmembrane

signal transducers in the ER membrane have been shown to regulate the Unfolded

Protein Response (UPR), which will be discussed in section 1.4.

1.3 Degradation of misfolded protein from the ER lumen

Many proteins folded in the ER fail to reach their correct conformation and,

after a lag period of 30-90 min, are disposed of (Lippincott-Schwartz et al., 1988). The

two major degradative pathways of the cell are the ubiquitin-proteasome system and

autophagy. Both pathways have been shown to degrade ER proteins in a process

termed ER-associated degradation (ERAD). ERAD I describes the process in which

misfolded proteins are retrotranslocated from the ER lumen to the cytosol and degraded

by the ubiquitin-proteasome, whereas ERAD II is the system in which portions of the

ER are encapsulated and degraded by autophagy.

1.3.1 ERAD I

ERAD I is a complicated and still unclear process that involves first

distinguishing terminally misfolded proteins from proteins that are still in the process of

being folded, targeting these misfolded proteins to the ER membrane, retrotranslocation

of the misfolded proteins back across the ER membrane into the cytosol, and finally

targeting of the misfolded protein for degradation by the ubiquitin-proteasome system.

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Evidence has suggested that misfolded glycoproteins are identified and removed

from the folding cycle with the help of ER mannosidase I, which operates by trimming

mannose residues from N-linked glycoproteins (De Virgilio et al., 1999; reviewed in

Cabral et al., 2001). These sugar moieties are recognized by the lectins EDEM and

OS9 (Bukau and Horwich, 1998; Lederkremer, 2009). Mutation experiments in yeast

have also shown that specific chaperones, such as calnexin and GRP78, may be

required for the degradation of some ERAD substrates (McCracken and Brodsky, 1996;

Plemper et al., 1997; Brodsky et al., 1999; Gillece et al., 1999). Recently, distinct

systems have been described that discriminate ERAD substrates based on the site of

their misfolded lesions (Ismail and Ng, 2006). Soluble and membrane-bound proteins

can have luminal (L) lesions and thus are targeted to the ERAD-L pathway. Membrane

proteins with misfolded cytoplasmic (C) domains are targeted to the ERAD-C pathway

and membrane proteins with lesions in their trans-membrane (M) domains are targeted

to ERAD-M. The components of both the ERAD-L and ERAD-C pathways were

analyzed in yeast by identifying protein complexes associated with the E3 ubiquitin

ligases Hrd1p and Doa10p, which define the ERAD-L and –C systems, respectively

(Carvalho et al., 2006). Besides Doa10p, the Doa10p complex contains an E2 complex

(Ubc7p and Cue1p) and the Cdc48p complex (described later) (Carvalho et al., 2006).

The Hrd1p complex includes Hrd3p and both the Ubc7p/Cue1p dimer as well as the

Cdc48p complex similar to the Doa10p complex (Gardner et al., 2000). In addition, the

Hrd1p complex includes Der1p, Yos9p, and Usa1p (Carvalho et al., 2006, Denic et al.,

2006). It seems that in a similar fashion to ERAD-L, the Hrd1p complex discriminates

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proteins destined for ERAD-M pathway as well however additional factors are most

likely required (Ismail and Ng, 2006).

Following selection, misfolded proteins are then exported to the cytoplasm.

Two different complexes of proteins have been identified as the possible channels

responsible for movement of the misfolded protein back across the ER membrane: the

Sec61α translocon complex (Plemper et al., 1997; Zhou and Schekman, 1999) and the

derlin-1 complex (Ye et al, 2004; Lilley and Ploegh, 2004). Irrespective of the channel

used, many studies have shown the retrotranslocation of ERAD substrates to be

catalyzed by a multiprotein complex containing Cdc48p/p97, Ufd1p, and Npl4p (Bays

and Hampton, 2002). Cdc48p-Ufd1p-Npl4p is thought to first bind to the polypeptide

backbone and subsequently mediate its ubiquitination, with the help of E2 enzymes and

E3 ubiquitin ligases (discussed below). ATP-hydrolysis by Cdc48p is then required to

complete retrotranslocation (Ye et al., 2003). The 19S cap of the proteasome may also

facilitate the retrotranslocation of some ERAD substrates (Lee, R.J. et al., 2004).

Once in the cytosol, proteins targeted for degradation are marked by

ubiquitination and are degraded by the 26S proteasome. Three distinct enzymes are

required to link ubiquitin onto proteins: E1 (ubiquitin-activating enzyme), E2

(ubiquitin-carrier or conjugating proteins), and E3 (ubiquitin-protein ligase), which

recognize a specific protein substrate and catalyzes the transfer of activated ubiquitin to

the client protein. As described above, HRD1 is an ER membrane protein that acts as

an E3 ubiquitin ligase in the ERAD system (Gardner et al., 2000; Wilhovsky et al.,

2000; Kaneko et al., 2002). SEL1 interacts with and stabilizes HRD1 (Gardner et al.,

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2000; Wilhovsky et al., 2000). Once ubiquitinated, ERAD substrates are then

recognized by the proteasome and degraded.

1.3.2 ERAD II

In addition to the ubiquitin-proteasome system, cells also rely on autophagy for

the degradation of cellular components. Autophagy is a catabolic process that involves

the degradation of cytoplasmic components using lysosomal machinery. There are

three types of autophagy – macroautophagy, microautophagy and chaperone-mediated

autophagy-, although the term “autophagy” usually refers to macroautophagy, and will

be referred to as such throughout this thesis. During autophagy, portions of the

cytoplasm (including organelles) are sequestered inside a double-membrane vesicle,

called an autophagosome. Although many questions still surround the mechanism of

autophagosome formation and the source of membrane (Reggiori, 2006), the story of

autophagy is quickly being delineated thanks to an exponential increase in the number

of studies on autophagy over the last decade.

The formation of autophagosomes is initiated by class III phophoinositide 3-

kinase (PI3K) (Cao and Klionsky, 2007) and begins with protein conjugation reactions

in which autophagy-related gene (Atg) 5 is conjugated to Atg12, which subsequently

forms a complex with Atg16L1 (Fujita et al., 2008). This complex can then act as an

E3 ligase and promote the conjugation of LC3 (Atg8 in yeast) to the phospholipid

phosphatidylethanolamine (Hanada et al., 2007; Ichimura et al., 2000; Noda et al.,

2008). Atg8 mediates tethering and hemifusion of liposomes containing Atg8-PE in an

in vitro system (Nakatogawa et al., 2007; Subramani and Farre, 2007), which may

account for membrane interactions during both the formation of autophagosomes and

11

their fusion with lysosomes. The Atg5-12-16Li complex is thought to localize LC3

conjugation to sites where autophagy occurs (Fujita et al., 2008) and this targeting may

be regulated by members of the Rab GTPase family (Itoh et al, 2008). Because LC3 is

covalently attached to membranes involved in autophagy, it serves as a powerful

marker to visualize the autophagy process (Kabeya et al., 2000). There are different

variations of autophagy depending on the organelle or substrates being degraded. In all

cases autophagy terminates with the delivery of cytoplasmic cargo into the lysosome

for degradation and recycling of macromolecular components.

Although misfolded protein accumulation in the ER has traditionally been

thought to be removed by ERAD I, recent studies have shown the importance of

autophagy in the ER stress response, a process that is discussed further in the next

section (Bernales et al., 2007; Hoyer-Hansen and Jaattela, 2007). There are several

examples of mutant versions of membrane or secretory proteins that aggregate in the

ER and appear to require the autophagy system for degradation (Fujita et al., 2008;

Perlmutter, 2006).

In addition to its role in degrading misfolded protein in the ER, autophagy is

also thought to counterbalance the ER distention that is commonly associated with

systems experiencing ER stress (Bernales et al., 2006).

1.4 ER Stress and the Unfolded Protein Response

The ER accommodates the challenge of folding and assembling a large

percentage of nascent proteins by enlisting a quality control system. Proteins can

misfold due to a variety of factors including: 1) mutations; 2) insufficient chaperone

capacity or cellular energy to promote chaperone-protein interaction; 3) depletion of

12

ER Ca2+; and 4) disruption of the ER redox state. Accumulation of misfolded proteins

in the ER lumen causes ER stress and activation of a signal response termed the

Unfolded Protein Response (UPR). The aim of the UPR is to alleviate ER stress and

restore ER homeostasis, and it does so by inducing a coordinated response that results

in four functionally distinct effects: 1) a transient decrease in overall translation,

reducing ER folding load; 2) an increase in the amount of ER chaperones to augment

the folding capacity of the ER; 3) an increase in translation of genes associated with

ER-associated degradation, to increase the number of irreversibly misfolded proteins

that are degraded; and finally, 4) if the stress is chronic and too severe for the cell to

recover, the UPR triggers apoptosis (Fig. 1.2). Three ER transmembrane proteins

transduce UPR signaling: double stranded RNA-activated kinase (PKR)-like ER kinase

(PERK), inositol requiring ER-to-nucleus signal kinase (IRE1), and activating

transcription factor (ATF) 6. All three of these stress sensors associate with

GRP78/BiP in their inactive states. When ER homeostasis is perturbed, GRP78 is

thought to preferentially interact with the unfolded/misfolded proteins, thus dissociating

from the UPR transducers. This hypothesis is supported by evidence that GRP78 is

released from all three transducers with the accumulation of misfolded proteins (Ma et

al., 2002; Shen et al, 2002; Liu et al, 2003). Another theory stipulates that the luminal

domain of IRE1 may be capable of directly binding unfolded proteins, which may

change its quaternary structure and induce autophosphorylation and UPR initiation

(Credle et al., 2005).

13

Figure 1.2 Signaling in the unfolded protein response. Three transmembrane signal transducers, IRE1, PERK and ATF6, regulate the UPR through their respective signaling cascades, producing four functionally distinct effects (numbered). Upon accumulation of unfolded protein in the ER lumen, GRP78 releases from the lumenal domains of all three sensors. PERK released of BiP dimerizes and autophosphorylates to activate its kinase activity. PERK then phosphorylates eIF2α, leading to translational attenuation (I). Upon activation by either GRP78 release or direct interaction with unfolded protein, IRE1 similarly dimerizes and upon activation selectively splices XBP1 mRNA, creating a potent transcription factor whose primary targets include genes involved in ERAD (II). ATF6 released from GRP78 is trafficked to the Golgi where its cytosolic fragment is cleaved and migrates to the nucleus to further regulate transcription of UPR-responsive genes, including chaperones (III). Finally, if the stress is chronic and severe, the UPR signals can result in cell apoptosis (IV).

1.4.1 PERK signaling during the ER stress response

PERK is a type I ER transmembrane serine/threonine protein kinase and is

responsible for the most immediate response to ER stress, attenuation of overall

translation (Kaufman, 2004). Once GRP78 releases from its interaction with PERK’s

luminal domain, PERK is able to dimerize, promoting trans-autophosphorylation and

14

activation (Harding et al., 2000). Activated PERK then phophorylates eukaryotic

initiation factor (eIF)2α, effectively inhibiting 80S ribosome assembly and the rate of

general translation initiation and protein synthesis (Shi et al., 1998; Harding et al.,

1999). Selected proteins, like ATF4, exhibit preferentially increased translation due to

the presence of inhibitory upstream open-reading frames (uORFs) within their 5’

untranslated region (UTR) (Hardig et al., 2000; Lu et al., 2004). ATF4 mRNA has two

uORFs prior to its initiation codon. The 5’ proximal uORF1 is a positive-acting

element that facilitates ribosome scanning and reinitiation at downstream coding

regions, whereas the second uORF2 is out of frame with the ATF4 sequence (Vattem

and Wek, 2004). In non-stressed cells, ribosomes scan downstream of uORF1, reinitiate

at the next coding region, uORF2, disrupting ATF4 translation. During stress, however,

the presence of high levels of phosphorylated eIF2α increases the time required for

scanning ribosomes to become competent to reinitiate translation. This delayed

reinitiation allows the ribosome’s to scan through the inhibitory uORF2 and instead

reinitiate at the ATF4 coding region (Vattem and Wek, 2004).

ATF4 is a transcription factor that regulates genes involved in amino acid

import, glutathione biosynthesis, and resistance to oxidative stress (Harding et al,

2003). ATF4 also induces the expression of the transcription factor CAAT/Enhancer

binding protein (C/EBP) homologous protein (CHOP/GADD153) (Ron, 2002;

Kaufman, 2004; Scheuner et al., 2001). PERK/eIF2α/ATF4 signaling is regulated by a

negative feedback loop, in which ATF4 induces the transcription of growth arrest and

DNA damage 34 (GADD34), an eIF2α phosphatase, resulting in translational recovery

(discussed in section 1.4.4).

15

1.4.2 IRE1 signaling during the ER stress response

IRE1 was the first component of the UPR response identified, and is the only

UPR response gene in yeast. Two mammalian homologues of yeast IRE1 have been

identified: IRE1α, which is conserved in all eukaryotic cells and expressed

ubiquitously (Tirasophon et al., 1998); and IRE1β, which is expressed only in intestinal

epithelial cells (Bertolotti et al., 2001). Although IRE1α and PERK ER lumenal

domains show only 20% identity, they have been reported to be functionally

interchangeable in sensing ER stress (Bertolotti et al., 2000). Under non-stress

conditions, IRE1 remains in an inactive monomeric form. Upon accumulation of

unfolded proteins in the ER lumen, IRE1 is activated, however the exact mechanism of

IRE1 activation is still unclear. Similar to PERK and ATF6, it is believed that the

release of GRP78 from IRE1 permits its dimerization and autophosphorylation.

Structural and mutation studies have also proposed, however, that IRE1 is capable of

binding misfolded proteins directly, causing conformational changes that permit a

similar dimerization and autophosphorylation (Credle et al., 2005).

Autophosphorylation of IRE1 activates its site-specific endoribonuclease

(RNase) activity (Tirasophon et al., 1998). The RNase activity of IRE1 initiates

splicing of a 26-base intron from the mRNA encoding the basic leucine zipper

containing transcription factor X-box binding protein (XBP1). This unconventional

splicing reaction is required for the translation of transcriptionally active XBP1

(Yoshida et al., 2001; Lee et al, 2002). XBP1 translocates to the nucleus and binds, in

the presence of nuclear factor (NF)-Y (Yamamoto et al., 2004), to ER stress response

elements (ERSE), an ER stress-specific consensus sequence within the promoter

16

sequence of target genes (Yamamoto et al, 2004; Lee et al, 2003). XBP1 activates

transcription of a subset of UPR genes encoding for some chaperones and ERAD

degradation machinery components (EDEM1, EDEM2, EDEM3, and Derlins1-3)

(Yoshida et al., 2003; Lee et al., 2003; Lee et al., 2002; Oda et al., 2006). In particular,

the series of genes expressing HRD1p and HRD3 is induced by the UPR through IRE1

in yeast (Travers et al., 2000). The human homologs for these genes have been

identified as HRD1 (Kaneko et al., 2002) and SEL1 (Mueller et al., 2006). These

proteins play an integral role in removing unfolded protein from the ER (Tsai et al.,

2002). Interestingly, in humans, the upregulation of HRD1 is similar to yeast in that it

is dependent on the IRE1 pathway; SEL1 however is dependent on the activation of the

ATF6 pathway (discussed in section 1.4.3) (Kaneko et al., 2007).

Cells lacking IRE1α and XBP1 have defective ERAD as well as reduced

secretory capacity and reduced cell survival (Molinari and Sitia, 2005). Moreover,

XBP1 activation has been shown to play a role in ER membrane biogenesis (Sriburi et

al., 2004), possibly to compensate for the increased demand for protein folding and

accumulation of misfolded protein during ER stress.

In addition to signaling via XBP1 mRNA cleavage, the ribonuclease activity of

IRE1 has been shown to degrade mRNA encoding proteins being translocated into the

ER lumen. This likely contributes to decreasing the load of new protein synthesis in

the ER (Hollien and Weissman, 2006).

1.4.3 ATF6 signaling in the ER stress response

The mammalian genome contains two ATF6 genes, ATF6α and ATFβ, both of

which are expressed in all tissues and are type II transmembrane proteins. Basic

17

leucine zipper and transcriptional activation domains are found in the cytosolic N-

terminal regions of both proteins. The majority of studies on ATF6 have focused on

ATF6α. Upon accumulation of misfolded proteins in the ER lumen, GRP78 is released

from ATF6α resulting in reduction of disulfide bridges in the lumenal domain allowing

for anterograde trafficking of ATF6α to the Golgi compartment. Once in the cis-Golgi

ATF6α is cleaved by site-1 protease (S1P) and site-2 protease (S2P) releasing the N-

terminal fragment that migrates to the nucleus to act as a transcription factor to enhance

induction of UPR genes (Haze et al, 1999; Ye et al., 2000; Yoshida et al., 2000).

Target genes of ATF6α include GRP78/BiP, GRP94, calreticulin, calnexin, as well as

proteins that catalyze protein folding such as PDI, ERP57, ERP72. ATF6α acts as a

coactivator of the UPR through interactions with NF-Y and XBP1 and is capable of

binding all three of the ER stress-response elements, ERSE, ERSE-II and the unfolded

protein response element (UPRE) (Yamamoto et al., 2004). Atf6α- and Atf6β-null

mice have been produced and show no significant phenotype (Wu et al., 2007;

Yamamoto et al., 2007). However, null mutations in both Atf6α and Atf6β die in early

murine embryonic development, suggesting that ATF6α and ATF6β have redundant

functions (Yamamoto et al., 2007).

1.4.4 Recovery from the Unfolded Protein Response

Signaling by the UPR is terminated under the influence of negative feedback

regulators. Recovery of translation is mediated by the dephosphorylation of PERK and

eIF2α by both a constitutively active regulator phopho-eIF2 phosphatase, CreP

(constitutive repressor of eIF2 phosphorylation), as well as a stress-induced regulator of

18

phospho-eIF2 phosphatase, GADD34 (growth arrest and DNA damage-inducible gene

34), both of which are subunits of the protein phosphatase holoenzyme PP1 (Wu and

Kaufman, 2006). The initial phosphorylation of eIF2α by PERK is also inhibited by a

UPR-induced gene product called p58IPK (58kDa PKR inhibitor) (Wu and Kaufman,

2006).

In yeast, Ptc2p, an Ire1p phosphatase, inactivates the IRE1p pathway

(Welihinda et al., 1998). However, the regulation of both the IRE1 and ATF6

pathways in higher eukaryotes remains to be established. Evidence has suggested that

the ubiquitin-proteasome system may play a role by targeting ATF6 for degradation

and thus downregulating its signaling and effects (Hong et al., 2004). Another

possibility is that as the UPR is activated, GRP78 levels increase, which prevents

activation of all three transmembrane UPR signal transducers by interacting with their

lumenal domains (Wu and Kaufman, 2006).

1.5 ER Stress-Induced apoptosis

Prolonged ER stress and activation of the UPR can induce apoptosis. Under

mild conditions of ER stress, the cell is able to protect itself and regains homeostasis.

If, however, the ER stress is too severe, and the cell protective responses are unable to

restore ER homeostasis, prolonged activation of the UPR triggers cell death. Both

mitochondrial-dependent and -independent pathways are thought to be involved in ER

stress-mediated cell death.

There are at least three known apoptotic pathways triggered by the ER: 1)

induction of CHOP; 2) IRE1α-mediated activation of apoptosis signal-regulating

kinase 1 (ASK1)/c-Jun amino-terminal kinase (JNK); and 3) cleavage and activation of

19

procaspase 12 (Fig. 1.3). Part of the complexity associated with ER-stress induced

apoptosis is that these three pathways are not single pathways, but have multiple

avenues in which they cross-talk. In addition, studies on ER-stress induced apoptosis

are complicated by the use of chemical reagents such as tunicamycin, thapsigargin and

reducing agents, which cause intense and persistent stress and may also have secondary

effects unrelated to ER stress per se.

1.5.1 CHOP

The most extensively studied ER stress-induced apoptotic pathway is mediated

by CHOP/GADD153. CHOP is a basic leucine zipper-containing transcription factor

that is induced primarily by the PERK-ATF4 pathway, but has been shown to be

induced by the IRE1 and ATF6 pathways as well (Wang et al., 1998; Ma et al., 2002).

The effects of its depletion and overexpression highlight CHOP’s role in ER stress-

induced apoptosis. CHOP-deficient cells are resistant to ER stress-induced apoptosis

(Zinszner et al., 1998) and overexpression of CHOP induces cell cycle arrest and

apoptosis (Kim et al., 2002). CHOP knockout has also been shown to protect β-cells

from apoptosis related to the accumulation of misfolded proinsulin (Oyadomari

et al., 2002) or exposure to nitric oxide (Oyadomari et al., 2001).

20

Figure 1.3. Pathways implicated in ER stress-induced apoptosis. (I) All three ER stress sensors lead to the induction of CHOP, which simultaneously downregulates the expression of anti-apoptotic Bcl-2 and induces pro-apoptotic genes. (II) Activated IRE1 recruits TRAF2, leading to the activation of ASK1 and JNK. JNK initiates mitochondria-mediated apoptosis (not shown). (III) Recruitment of TRAF2 to IRE1 permits the dissociation of TRAF2 from procaspase-12 on the ER membrane, making procaspase-12 available for activation. ER stress causes Bax and Bak to oligomerize and release Ca2+ from the ER, activating m-calpain and subsequently cleaving procaspase-12 to caspase-12. Active caspase-12 is then able to cleave and activate procaspase-9 activating downstream caspase cascades, including caspase-3. The cytosolic Ca2+ is also taken up by the mitochondria, causing depolarization of the inner mitochondrial membrane and cytochrome c release into the cytoplasm. This results in formation of the apoptosome (consisting of Apaf-1, cytochrome-c, ATP, and procaspase-9), activation of procaspase-9 and subsequent downstream caspases leading to apoptosis.

The mechanism by which CHOP elicits its effects are complex due to its ability

to induce the transcription of genes related to apoptosis while simultaneously

repressing the transcription of genes encoding proteins with protective functions.

21

Possible mediators of CHOP-induced apoptosis include Gadd34, death receptor 5

(DR5), tribbles 3 (TRB3), and the BCL2 homology 3 (BH3)-only containing B cell

lymphoma 2 (BCL2) family member BCL2 interacting mediator of cell death (BIM).

As previously discussed in section 1.3.4, GADD34 functions to dephosporylate eIF2α,

effectively restoring mRNA translation during the recovery from ER stress. Whereas

ideally this function would promote survival and a return to ER homeostasis, it has

been proposed that premature recovery may be detrimental to the cell through the

generation of reactive oxgen species (ROS) and increasing ER protein folding load

(Marciniak et al., 2004).

Cells may also be sensitized to ER stress-induced apoptosis by CHOP-mediated

downregulation of the expression of the anti-apoptotic factor BCL2 and depletion of

cellular glutathione (McCullough et al., 2005).

1.4.1 JNK

Apoptosis can also be induced through IRE1α-mediated activation of the

MAPK cascade. The cytoplasmic domain of IRE1α interacts with tumor necrosis

factor (TNF) receptor-associated factor (TRAF) 2, which then couples activation of

death receptors in the plasma membrane to the activation of c-Jun NH2-terminal kinase

(JNK) and stress-activated protein kinase (SAPK) (Urano et al., 2000). Studies have

also shown that IRE1α and TRAF2 interact with the MAPK apoptosis signal-regulating

kinase 1 (ASK1) to cause the phosphorylation and activation of JNK (Nishitoh et al.,

2002). TRAF2 has also been shown to signal ligation of the TNF receptor 1 (TNFR1)

to mediate apoptosis through the MAPKs JNK and p38 (Scheuner and Kaufman, 2008).

There is also evidence that IRE1 interacts with TNFR1 to form a complex with TRAF2

22

and ASK1 and mediate JNK activation. Reactive oxygen species (ROS) have also been

shown to activate ASK1 by disrupting its interaction with ASK1 thioredoxin (TDX) via

oxidation of TDX, thereby leading to activation of JNK and p38 MAP kinase and cell

death (Tobiume et al., 2002). Additionally, IRE1-TRAF2 activates ATF3, a

transcriptional repressor through JNK (Cai et al., 2000; Zhang et al., 2001). Dominant

negative TRAF2 as well as antisense ATF3 cDNA inhibited cell death by

homocysteine, which alters cellular redox potential causing ER stress (Zhang et al.,

2001). This result implicates the JNK-ATF3 pathway in ER stress-induced cell death.

1.4.2 Caspase-12

Upon ER stress, proapoptotic members of the Bcl2 family are recruited to the

ER membrane and activate caspase-12, while anti-apoptotic members are believed to

prevent this recruitment. One example is BIM (Bcl2-interacting mediator of cell death),

which translocates from the dynein rich compartment to the ER membrane and

activates caspase-12 upon ER stress. BCL-xL (BCL2-like 1) is an antiapoptotic factor

that binds BIM and inhibits its translocation (Morishima et al., 2004). Bcl2-homology

domain 3 (BH3-domain)-containing pro-apoptotic factors, such as BAX (Bcl2-

associated X protein) and BAK (Bcl-2 homologous antagonist/killer), which reside in

the ER and mitochondrial membranes, are also ER stress-induced apoptosis factors.

ER stress results in BAK and BAX oligomerization which may permit calcium efflux

into the cytoplasm, resulting in increased cytosolic calcium and activation of both

mitochondrial-dependent and -independent caspase cascades (Zong et al., 2003;

Scorrano et al., 2003). In vitro experiments have shown that micromolar to millimolar

increases in cytosolic calcium activate the calcium-dependent protease m-Calpain,

23

which subsequently cleaves and activates the ER-resident procaspase-12 (Nakagawa et

al., 2000). Active caspase-12 then cleaves and activates procaspase-9 and consequently

leads to the activation of the caspase cascade (Rao et al., 2002). Interestingly, the

activation of caspase-12 occurs in response to ER stress, but not other death stimuli

(Szegezdi et al., 2003; Nakagawa et al., 2000). Furthermore, caspase-12-deficient cells

are partially resistant to ER stress-induced apoptosis, but not to apoptosis induced by

other stimuli (Nakagawa et al., 2000). IRE1 recruits TRAF2, which interacts with

caspase-12 inferring that activation of caspase-12 may be linked with IRE1 signaling

(Yoneda et al., 2001).

Calcium released from the ER also enters the mitochondria and depolarizes the

inner membrane, causing the mitrochondrial outer membrane pore to release

cytochrome c and activate apoptosis protease-activating factor 2 (APAF-1)/procaspase-

9-dependent apoptosis (Crompton, 1999; Boya et al., 2002).

1.5 Biosynthesis and Secretion of Insulin in Pancreatic β-cells

Several organs maintain blood glucose to ensure it is at appropriate levels

during fasting as well as in post-prandial states. In the latter case, the pancreas, and

more specifically the pancreatic β-cells found in the islets of Langerhans, are essential

for blood glucose disposal. The β-cell is the only source of circulating insulin, which is

essential for both stimulating peripheral tissue glucose uptake and inhibiting liver

glucose production, among other metabolic effects (Taniguchi et al., 2006). Glucose is

the main metabolite responsible for regulating insulin secretion from the β-cell

(Ashcroft, 1980), although other metabolites such as free fatty acids can also stimulate

secretion and the process can be modulated by incretin hormones such as glucagon-like

24

peptide 1 (Nolan et al., 2006; Drucker 2007). In addition to stimulating insulin

secretion, glucose also stimulates insulin production, both by increasing insulin gene

transcription and increasing insulin translation (Vaulont et al., 2000; Melloul et al.,

2002; Wicksteed et al., 2003; Wicksteed et al., 2007).

1.5.1 Insulin biosynthesis

Like other secretory cells, β-cells have an extensive rough endoplasmic

reticulum and well-defined storage granules. In the case of β-cells these granules are

full of insulin microcrystals, and are rich in zinc and calcium. Insulin circulates in the

serum as monomers, forms dimers at micromolar concentrations and, in the presence of

zinc, forms hexamers (Baker et al., 1988). The monomer of insulin consists of an A

chain of 21 amino acids and a B chain of 30 amino acids with the N-terminus of the A

chain and the C-terminus of the B chain both being located on the molecule’s surface

about 8 Å apart (Dodson and Steiner, 1998). Two disulphide bonds join the A and B

chains (A7-B7; A20-B19), and one intra-chain disulphide bond is found on the A chain

(A6-A11).

Insulin is initially synthesized as preproinsulin on the rough endoplasmic

reticulum (RER) membrane (Fig. 1.4). The signal sequence stabilizes the ribosome on

the RER membrane, the B chain is translated next, followed by a connecting peptide,

then the A chain sequence (Steiner, 1981). In total, preproinsuin is 110 amino acids

(Dodson and Steiner, 1998). As the growing polypeptide is cotranslationally

translocated into the ER lumen, preproinsulin is converted to proinsulin by removal of

the signal sequence.

25

With the help of ER molecular chaperones, the protein is then folded to its

proper conformation, and proinsulin is trafficked from the ER to the Golgi apparatus.

The environment of the Golgi favors the zinc-containing hexameric form of insulin

(Huang and Arvan, 1995; Howell et al., 1978). The conversion of proinsulin to insulin

starts at the stage of granule formation (Dodson and Steiner, 1998) in which the

connecting peptide (C-peptide) is cleaved by the membrane-associated endoproteases

PC1/3 and PC2 as well as carboxypeptidase (Dodson and Steiner, 1998). Granule

maturation involves the acidification of the granule lumen, by the ATP-dependent

proton pump, resulting in a pH optimum for the endoproteases to convert proinsulin

into mature insulin. Granule maturation involves the removal of unnecessary

membrane proteins by clathrin coated vesicles, resulting in mature insulin storage

vesicles (Orci, 1982; Orci et al., 1985).

1.5.2 Mechanisms of insulin release

It is widely accepted that insulin secretory granules exist as two populations:

those that are readily releasable and responsible for the initial (first phase) of insulin

secretion, and the second reserve pool that is responsible for a more prolonged (second

phase) insulin secretion (Bratanova-Tochkova et al., 2002; Rorsman and Renstrom,

2003, Rutter, 2001).

The first phase of insulin secretion is mediated by a readily-releasable pool of

granules pre-docked at the cell surface membrane. This allows for the rapid calcium-

dependent fusion of the insulin granules with the plasma membrane. Glucose

metabolism results in an increase in the ATP/ADP ratio of the cytosol that in turn

deactivates ATP sensitive K+ channels (KATP channels). Inhibition of these channels is

26

A

B

Figure 1.4. Insulin biosynthesis and glucose-stimulated insulin secretion. A. Schematic representation of preproinsulin, proinsulin and mature insulin molecules. The red lines represent disulphide bonds. B. Schematic representation of insulin biosynthesis along the secretory pathway and the first and second phases of glucose-stimulated insulin secretion in pancreatic β-cells. Preproinsulin is transcribed then co-translationally translocated into the rough ER where its signal peptide is cleaved to form proinsulin. Once properly folded, and the correct disulfide bonds formed, proinsulin is trafficked to and then packed into insulin granules by the trans-Golgi. Prohormone convertases and carboxypeptidases proteolytically cleave proinsulin to produce insulin and C-peptide. The mature granules are then either trafficked either to the cell membrane or to the stored pool of insulin granules. Upon glucose stimulation, two phases of insulin secretion are initiated: the KATP channel-dependent first phase (green arrows); and the KATP channel-independent second phase (blue arrows). During the first phase, metabolism of glucose results in an increase in ATP/ADP ratio resulting in depolarization of the membrane due to closure of the KATP channel and increased Ca2+ entry through L-type Ca2+ channels, stimulating insulin release. The second phase of insulin secretion is not well understood, but it is believed to be dependent on increased intracellular Ca2+ concentrations resulting in the mobilization and secretion of the reserve storage granules.

27

largely responsible for the glucose-induced depolarization of the β-cell, resulting in

increased Ca2+ entry through voltage-dependent Ca2+ channels and subsequent

stimulation of exocytosis (Fig. 1.4B).

The second phase of insulin release is less well understood. However, it is

believed that a further increase in intracellular Ca2+ mediates the increase in the

secretory response. Unlike the first phase response, this pathway is KATP channel-

independent. One theory is that mitochondrial signals induce acylation of proteins

critical for the acceleration of the rate-limiting step in the second-phase of glucose-

stimulated insulin secretion (Straub and Sharp, 2004).

The first phase of insulin secretion is thought to be maximal 4 min after glucose

stimulation and the second phase is characterized by an increasing rate of secretion that

plateaus at approximately 30 min (Straub and Sharp, 2004).

1.6 ER Stress in Pancreatic β-cells

Pancreatic β-cells are secretory cells which produce and secrete large amounts

of insulin, thus making them particularly susceptible to ER stress and oxidative stress.

Glucose acutely increases insulin biosynthesis such that an estimated 40~50% of the

total cellular protein produced by the β-cell is insulin (Schuit et al., 1988). To

accommodate this large demand the β-cell has evolved an extensive ER (Eizirik et al.,

2008). Thus, it is not unexpected that the β-cell is very sensitive to conditions where

the ER protein folding capacity is not sufficient to meet folding demands. To mediate

the large burden on the cell and monitor ER homeostasis, β-cells highly express the ER

stress sensors IRE1 and PERK (Araki et al., 2003). The importance of a properly

functioning UPR is evident from the fact that perturbation of the UPR signaling

28

pathways in vivo leads to pancreatic β-cell death in animal models (Harding et al.,

2001; Scheuner et al., 2005; Zhang et al., 2002) and humans (Delepine et al., 2000).

PERK knockout mice are unable to regulate translation and are thus more susceptible to

ER stress, exhibiting hyperglycemia and increased β-cell apoptosis (Harding et al.,

2001). Similarly, mice with eIF2α (S51A) knocked-in also exhibited defects in their β-

cells (Scheuner et al., 2001).

ER stress is also a feature of pathological conditions associated with obesity

and diabetes. Excess nutrients (free fatty acids, glucose), amyloid deposits and

inflammatory cytokines have all been shown to induce ER stress in pancreatic β-cells

(Eizirik et al., 2008). These conditions induce the UPR pathways that attempt to

counteract ER stress. However, as discussed in section 1.4, chronic ER stress can lead

to apoptosis induction (Oyadomari and Mori, 2004), particularly in β-cells. It has been

hypothesized that chronic conditions associated with obesity over time may lead to

chronic ER stress-induced β-cell death and depletion of β-cell mass that results in type

2 diabetes (Ahren, 2005). Another example of chronic ER stress is the Akita mouse.

Rodents contain two insulin genes, insulin 1 and insulin 2, the transcripts of which are

both able to produce functional insulin. In the case of the Akita mouse, a missense

(C96Y) mutation in insulin 2 (Ins2) prevents formation of one of its disulfide bonds

between the A and B chains causing the proinsulin to misfold and accumulate in the ER

(Wang et al., 1999). Despite the presence of normal insulin 1 and one normal insulin 2

allele in the heterozygous Akita mouse, the mice develop diabetes due to a progressive

loss of functional β-cell mass caused by ER stress (Oyadomari et al., 2002, Wang et al.,

1999, Ron, 2002). Studies have shown that in heterozygous Ins2(C96Y/+), but not

29

homozygous Ins2(C96Y/C96Y) Akita mice, the homozygous disruption of CHOP

delayed the onset of diabetes (Oyadomari et al., 2002). This indicates that the

mechanism of cell death is only partially CHOP-dependent.

1.7 Mechanisms of β-cell dysfunction in Type 1 and Type 2 Diabetes

Diabetes mellitus is a group of metabolic diseases characterized by

hyperglycemia as a result of a dysfunction in insulin secretion (typically in the case of

type 1 diabetes) and/or insulin action (type 2) (American Diabetes Association, 2006).

The dysfunction in insulin signaling and associated hyperglycemia ultimately leads to

micro and macrovascular damage, causing long-term complications including

neuropathy, nephropathy, retinopathy and cardiovascular disease that significantly

affects quality of life and reduces life expectancy (American Diabetes Association,

2006). Pancreatic β-cells are central to blood glucose regulation and their excessive

loss and dysfunction is thought to be a cause of both of the major forms of diabetes,

type 1 and type 2.

Type 2 diabetes represents around 90% of cases of diabetes and results from a

combination of genetic and environmental factors that cause both peripheral insulin

resistance (in muscle, liver and adipose tissues) and impairment of β-cell function. In

particular, type 2 diabetics exhibit quantitative and qualitative defects in glucose

stimulated insulin secretion (Kahn, 2003; Ferrannini and Mari, 2004; Buchanan, 2003;

Del Prato et al., 2002; Marchetti et al., 2006). Growing evidence suggests that there is

no hyperglycemia without β-cell dysfunction in type 2 diabetes (Kahn, 2003;

Ferrannini and Mari, 2004; Rhodes, 2005).

30

Initially, β-cell mass is able to adapt to changes in metabolic homeostasis.

Obesity and insulin resistance results in an increase in β-cell mass through enhanced

replication and neogenesis as well as an increase β-cell size (Kahn, 2003; Ferrannini

and Mari, 2004). A decrease in β-cell mass signals the progression from insulin

resistance to diabetes and is caused primarily as a result of increased apoptosis and

inadequate β-cell replication and neogenesis (Donath and Halban, 2004; Saito et al.,

1978; Marchetti et al., 2006).

Several genes have been identified that may contribute to β-cell dysfunction in

type 2 diabetes, including some that encode proteins involved in glucose metabolism,

insulin signaling and various transcription factors (Trajkovski et al., 2006; Bell and

Polonski, 2001; Sladek et al., 2007). Glucose toxicity and lipotoxicity have also been

shown to have deleterious effects on β-cell function and viability (Poitout et al., 2002;

Unger, 2002; Prentki and Nolan, 2006; Cnop et al., 2006). In addition, a possible role

for chronic inflammation in type 2 diabetes is now under investigation (Donath et al.,

2003). Obesity, which is the biggest risk factor for the development of type 2 diabetes

is associated with low level chronic inflammation (Hotamisligil and Erbay, 2008).

The loss of β-cells in type 1 diabetes is the result of an autoimmune-mediated

mechanism in which chronic inflammation, called insulitis, causes the destruction of β-

cells. This destruction is mediated by factors that are released by/or expressed on the

immune cells, such as macrophages and T-cells, which invade the islets, and trigger

secondary pathways leading to cell death. The loss of functional β-cell mass related to

immune cell-mediated destruction may occur through direct contact with the activated

macrophages and T-cells, stimulation of cell death receptors such as CD95 (Bidere et

31

al., 2006), and/or through the exposure to soluble mediators secreted by these cells,

including cytokines (such as interleukin-1 (IL-1), interferon-γ (IFN-γ), and tumor

necrosis factor (TNF)), nitric oxide (NO), oxygen free radicals, or perforin and

granzymes released from the granules of cytotoxic T-cells (Eizirik and Mandrup-

Poulsen, 2001).

In vitro exposure of β-cells to IL-1β, or a combination of IL-1β and IFN-γ has

been shown to cause functional changes similar to those observed in pre-diabetic

patients, including elevated proinsulin/insulin levels (Hostens et al., 1999) and a

preferential loss of first-phase insulin secretion in response to glucose (Ohara-Imaizumi

et al., 2004). Although the β-cell dysfunction associated with inflammatory cytokines

may be due to nitric oxide production (Eizirik et al., 1996), the mechanism by which β-

cells are destroyed has still not been fully elucidated.

1.7.1 Cytokines, Interleukin-1β, Interferon-γ and Nitric oxide

Cytokines are produced by a variety of cells and cause changes in cellular

metabolism. They circulate throughout the body in the picomolar range and increase

up to 1,000-fold during trauma or infection (Gilman et al., 2001). Most cytokines have

major roles in the biological impact of host perturbations rather than regulate cellular

homeostasis. The classification of cytokines is typically based on their presumed

structures, cell of origin and action. IL-1 was one of the first cytokines described and

was studied for many years prior to actually being named. It was shown to cause fever,

stimulate lymphocyte responses, and cause degeneration in joints (Dinarello, 1994). In

actuality, it wasn’t until after 1984 that it was identified that IL-1 was composed of

32

more than one protein. The three original human IL-1 cDNAs identified were IL-1α,

IL-1β, and IL-1 receptor antagonist (IL-1Ra), which has been found to antagonize the

action of both the α and β forms (March et al., 1985; Eisenberg et al., 1991). Both the

α and β form are secreted by macrophages, monocytes and dendritic cells and have an

important role in the inflammatory response (March et al., 1985). During

inflammation, the three members of the IL-1 gene family are expressed and their

products compete for IL-1 receptor occupancy. The host response to external or

internal perturbations is thought to result, in part, from the net occupancy of IL-1α, IL-

1β, and IL-1Ra on IL-1 receptors (Dinarello, 1994).

Once bound by IL-1β, the IL-1 receptor activates the transcription factor

nuclear factor (NF)-κB in rodent and human islets (Eizirik et al., 2001). Inhibition of

NF-κB activation using an inhibitory κB (IκB) has been shown to protect pancreatic β-

cells from cytokine-induced apoptosis (Heimberg et al., 2001). Microarray analysis,

done using this same IκB super-repressor in β-cells, has identified 66 IL-1β-responsive

NF-κB-dependent genes, including genes coding for other cytokines and chemokines as

well as stress-related genes such as CHOP (Cardozo et al., 2001). Inducible nitric oxide

synthase (iNOS) has also been found to be regulated by NF-κB and over 50% of genes

modified after 12 h of cytokine exposure are secondary to iNOS-mediated NO

production (Darville and Eizirik, 1998; Kutlu et al., 2003). Studies using IL-1β alone

have confirmed activation of stress response genes, however, the majority of studies in

the field, have used a minimal combination of IL-1β and IFN-γ to induce apoptosis,

suggesting a synergistic effect of these two cytokines (Eizirik et al., 2001). It is

important to note, however, that one recent study in mouse MIN6 β-cells has found not

33

only evidence of ER stress but significant apoptosis using IL-1β alone (Wang et al.,

2009). The majority of studies, however, use a cocktail of cytokines in order to induce

apoptosis in mouse β-cells, which likely is more reflective of the pathological state.

Interferon-γ is a dimerized soluble cytokine and the only member of the type II

class of interferons (Gray and Goeddel, 1982). Aberrant production of IFN-γ has been

shown to result in a number of autoimmune disorders, including inflammatory bowel

disease, multiple sclerosis and diabetes mellitus (Bouma and Strober, 2003; Neurath et

al., 2002, Skurkovich and Skurkovich, 2003). For the most part, the nature of IFN-γ’s

effect has been attributed to its ability to stimulate and modulate the immune system.

IFN-γ is produced predominantly by natural killer (NK) and natural killer T cells as

part of the innate immune system, as well as by T-lymphocytes as a component of the

adaptive immune system.

The cellular response to IFN-γ is mediated through binding with its

heterotrimeric receptor consisting of both IFN-γ receptors 1 and 2 (IFNGR1 and

IFNGR2). Binding of IFN-γ to its receptor results in activation of the JAK-STAT

pathway, in which the tyrosine kinases JAK1 and JAK2 are activated and

phosphorylate the transcription factor STAT-1, which dimerizes and translocates to the

nucleus (Darnell et al., 1994). The exact mechanism by which IFN-γ synergizes with

IL-1β to cause cytokine-induced apoptosis is still unclear. Studies have proposed that it

may be through transcriptional regulation of key genes, a few of which are related to

the ER stress response and discussed in the next section. In addition, IFN-γ has been

shown to augment IL-1β-induced iNOS transcription and NO production (Cardozo et

al., 2005).

34

Nitric oxide (NO) is a messenger molecule that mediates a diverse array of

biological functions, such as vasodilation, neurotransmission, and immunity (Eizirik et

al., 1996). NO is produced by the enzyme nitric oxide synthase (NOS), in a reaction

that uses arginine as its main substrate (Mori, 2007). In the case of immune-mediated

β-cell damage, the most relevant form of NOS is its inducible form, iNOS (Eizirik et

al., 1996). IL-1β alone has been found to be sufficient to stimulate iNOS expression in

rat islets, while IL-1β plus IFN-γ or TNF-α are the minimal combination of cytokines

required to stimulate iNOS expression and NO production in mouse and human islets

(Lee et al, 2004). Although the mechanism underlying β-cell vunerability to NO is still

unclear, it is thought that NO induces DNA damage leading to cell death through the

poly (ADP)-ribose polymerase (PARP)/p53 pathway (Eizirik et al., 1996; Araki et al.,

2003). Evidence, however, has also suggested a p53-independent cell death signal

(Heller et al., 1995; Messmer and Brune, 1996) and recently, NO has been

hypothesized by several studies to disturb ER function and cause apoptosis through the

ER stress response in β-cells (Araki et al., 2003; Wang et al., 2009).

1.7.2 Cytokines, ER stress, and Pancreatic β-cell Apoptosis

ER stress has been implicated in the loss of β-cells and β-cell dysfunction in

diabetes and obesity (Araki et al., 2003; Laybutt et al., 2007; Oyadomari et al., 2002;

Wang et al., 1999). Inflammatory cytokines have been shown to cause ER stress

(summarized in Fig. 1.5) (Cnop et al., 2005; Lee et al., 2004), which may contribute to

causing β-cell dysfunction. Although it has been well established that NO is the

primary mediator of the inhibitory actions of cytokines, there exists a debate in the field

35

over the mechanisms responsible for cytokine-induced apoptosis and even more

specifically, whether ER stress contributes to the cytokine-induced β-cell death.

As previously described, pancreatic β-cells are heavily reliant on the

homeostasis of their ER. It is important that they maintain the resting free calcium

concentration of the ER lumen three to four orders of magnitude higher than the

cytosolic calcium concentration (Meldolesi and Pozan, 1995), as this gradient is

important for a variety of calcium-dependent processes. Disruptions in calcium

homeostasis result in the accumulation of unfolded proteins and activation of the

unfolded protein response. It has been proposed that IL-1β and IFN-γ cause ER stress

through NO production and subsequent downregulation of SERCA2b expression,

which results in reduced ER calcium levels (Cardozo et al, 2001; Oyadomari et al,

2001; Cardozo et al, 2005). Interestingly, although activation of the PERK and IRE1

pathways have been shown, cytokines neither activate ATF6, nor induce the ER

chaperone GRP78/BiP (Cardozo et al., 2005). Thus, it remains unclear whether

cytokines cause ER stress in β-cells and the extent to which this contributes to β-cell

death and dysfunction.

It is well established that if ER stress is chronic or severe, elements of the

apoptotic machinery are induced. These pathways include IRE-1α mediated caspase-

12 cleavage, activation of the JNK pathway, and activation of the transcription factor

CHOP. In vitro studies in β-cells have confirmed that all three of these pathways are

activated with cytokine exposure (Contreras et al., 2003; Cardozo et al., 2005;

Akerfeldt et al., 2008). Contreras et al. (2003) found that Bcl-2 overexpression

decreased caspase-12 activation by both ER stress transducers and cytokines in human

36

islets resulting in decreased cytokine-induced apoptosis in human islets. The inhibition

of JNK has also resulted in decreased thapsigargin- and cytokine-induced apoptosis

(Wang et al., 2009), and pancreatic islets isolated from CHOP knockout mice treated

with SNAP (an NO donor) did exhibit resistance to SNAP-induced apoptosis (Araki et

al., 2003). A combination of IL-1β and IFN-γ has also been shown to induce NF-kB-

dependent JunB in islets. In INS-1E cells, knockdown of JunB causes increased ER

stress and apoptosis (Gurzov et al., 2008).

Figure 1.5. Cytokine-induced ER stress in β-cells. The effects of IL-1β are indicated by the red arrows and those of IFN-γ are indicated by the green arrows. It should be noted that IFN-γ alone does not stimulate iNOS production. NO decreases SERCA2b expression and depletes the ER Ca2+ stores leading to ER stress and activation of the IRE1α and PERK pathways, but not ATF6.

37

In addition, studies in INS-1E cells showed that pretreatment with IFN-γ

decreased the basal level of mRNA expression of XBP1, GRP78, ORP150, Grp94 and

Sec61a, while increasing the CHOP mRNA level (Pirot et al., 2006). Pretreatment with

IFN-γ potentiated the ER stress-induced apoptosis associated with cyclopiazonic acid, a

SERCA inhibitor (Pirot et al., 2006). IFN-γ has also been shown in β-cells to stimulate

MHC class I and II molecules in the ER lumen (Pavlovic et al, 1997), which could lead

to an ER overload. Under certain conditions, this may cause ER stress and pancreatic

β-cell apoptosis (Sarvetnick et al., 1988; Grodsky et al., 1992).

Despite this large body of evidence, recent studies have cast doubt on the

contribution of ER stress to cytokine-induced apoptosis. Chambers et al. (2008) found

that whereas a knockdown in PERK resulted in enhanced cell death in tunicamycin-

treated cells, it had no effect in those cells exposed to IL-1 in RINm5F cells. This led

them to believe that the mechanisms of β-cell death are unrelated. Other studies have

used chemical chaperones such as PBA to determine whether increased folding

capacity has any effect on cytokine-induced apoptosis. PBA treatment of INS-1 β-cells

and rat islets had no effect on the cytokine-induced level of JNK but did decrease the

palmitate-induced level of JNK (Akerfeldt et al., 2008). This study also found that

knockdown of endogenous CHOP levels using CHOP siRNA protected these same

cells from palmitate- but not cytokine-induced cell death.

1.7.3 Cytokines and β-cell dysfunction

The cytotoxicity associated with cytokines and diabetes is not limited to β-cell

death, cytokines have also been shown to cause β-cell dysfunction in insulin

38

biosynthesis and secretion. In vitro exposure of human β-cells to IL-1β and IFN-γ

results in an elevated proinsulin/insulin ratio (Hostens et al., 1999) and a preferential

loss of first-phase insulin release (Ohara-Imaizumi et al., 2004). A similar reduction in

first-phase insulin secretion is observed early in development of type 2 diabetes (Pigon

et al., 1996). Similar to findings from studies on ER stress, the inhibitory actions of

cytokines on insulin biosynthesis are also dependent on the production of high levels of

NO and the mechanisms of action are still unclear (Corbett and McDaniel, 1992). NO

is believed to exert its inhibitory effects by targeting iron-sulfur-containing enzymes,

such as aconitase of the Krebs cycle and the electron transport chain, resulting in

inhibition of glucose oxidation to CO2 and reductions in cellular levels of ATP (Corbett

and McDaniel, 1992). This reduction in ATP is thought to be responsible for the

inhibitory actions of cytokines on insulin secretion, since glucose-stimulated insulin

secretion requires ATP-dependent inhibition of K+ channel activity, allowing for

depolarization and Ca2+ dependent exocytosis. A study by Vadakekalam et al. (1997)

suggests that apart from its effect on KATP channels, IL-1β may have other effects that

inhibit Ca2+-induced insulin secretion.

Cytokines have also been shown to cause dysfunction in insulin biosynthesis.

More specifically, type 2 diabetics have been shown to have an elevated

proinsulin/insulin ratio. A proteomics analysis of cytokine-treated INS-1E cells has

shown this elevated ratio is most likely a result of the down-regulation of PCSK1 and 2

(PC1/3 and 2 respectively in humans) (D’Hertog et al., 2007).

39

1.8 Rationale and hypothesis

When ER stress is severe and prolonged, cell death (apoptosis) is induced.

Although it is known that pancreatic β-cell loss plays a key role in the development of

diabetes and that ER stress occurs in pancreatic β-cells, much is still unclear. Some

important questions are what role does ER stress have in inflammatory cytokine-

induced pancreatic β-cell death and what is the nature of the ER stress response and

mechanism of chronic ER stress-induced β-cell death.

This thesis focuses on two main projects relating to the effects of ER stress in

pancreatic β-cells. The first project examines the contribution of ER stress in cytokine-

induced pancreatic β-cell apoptosis. Recent studies have shown that cytokines induce

the UPR, however the ATF6 pathway is not activated and cytokines do no induce the

expression of GRP78. Overexpression of GRP78 has been reported to protect a variety

of different cells from ER stress (Dorner et al., 1992, Laybutt et al., 2007; Lai et al.,

2008). We therefore hypothesize that an enhanced ability to respond to ER stress will

enable β-cells some protection from inflammatory cytokine-induced cell death. This

hypothesis is examined in Chapter 3 of this thesis.

The second project examines the ER stress response and ER stress-induced

apoptosis in a pancreatic β-cell culture model of the Akita mouse. A stable, inducible

pancreatic β-cell line has been generated in the lab that expresses a folding-deficient

insulin protein. The mutant insulin (C96Y) has an amino acid substitution that

precludes normal disulfide bond formation, similar to that of the Akita mouse discussed

in section 1.7. We hypothesize that induction of mutant insulin protein will induce ER

stress and apoptosis and that analysis of the changes in gene expression after induction

40

will allow for the identification of the transcriptional response, including potential

genes that regulate ER stress-induced apoptosis. This hypothesis was examined in

Chapter 4 of this thesis.

41

CHAPTER 2: MATERIALS and METHODS

42

2.1 Cell Culture

Rat INS-1 cells were obtained from the laboratory of Dr. Claus Wollheim

(University of Geneva) (Asfari et al., 1992) and were used to generate INS-1

Ins2(C96Y)-EGFP clone #4S2 as described in the introduction to Chapter 3. A

subclone of rat INS-1 cells (INS-1E) was obtained from Dr. Claes Wollheim (described

in Janjic et al., 1999). Both cell lines were maintained in complete RPMI 1640 (11.1

mM glucose, 1 mM sodium pyruvate, 10 mM HEPES), which had been supplemented

with 10% Fetal Bovine Serum (FBS), 2 mM L-glutamine, and 55 μM β-

mercaptoethanol as well as antibiotics (100 units/ml penicillin and 100 μg/ml

streptomycin). Cells were incubated at 37°C and 5% CO2 and the media was changed

every 3-4 days and trypsinized once the cells reached 70% confluency in the flask.

Clone #4S2 was supplemented with G418 and hygromycin every 7-8 days.

In Appendix 2, HEK293T cells were generously provided by Dr. James Rini

(University of Toronto) and maintained in Dulbecco’s modified E Media (DMEM)

supplemented with 10% FBS and 2 mM L-glutamine as well as antibiotics. Cells were

kept at 37°C and 5% CO2.

2.2 Cytokine Preparation, Cell Treatment and Lysis

The concentrations of cytokines were selected based on previous studies

(Cardozo et al, 2005; Kutlu et al, 2003; Pirot et al, 2007) examining ER stress in INS-

1E cells. For the cytokine experiments, recombinant rat interleukin-1β (IL-1β) and

recombinant rat interferon-γ in 0.1% BSA was diluted to a final concentration of 10

U/ml and 0.04 μg/ml, respectively. INS-1E cells were cultured on 12- or 24-well

43

plates, and clone #4S2 cells were cultured on 10 cm dishes, or 6- or 12-well plates

depending on the experiment. To induce mutant insulin expression in clone #4S2, 2

μg/ml doxycycline (dox) was added. Where applicable, 1 μM thapsigargin (6h) or 2

μg/ml tunicamycin (16h) were used as positive controls for induction of ER stress.

Staurosporine (0.3 μM) for 24 h was used as a positive control for apoptosis, whereas

50 and 100 nM of chloroquine for 16h were used as positive controls for inducing

autophagy. To collect whole cell lysates for the determination of both protein

concentration and to conduct all Western blot analyses, the cells were washed in PBS

and lysed in ice-cold lysis buffer which consisted of 1% Triton X-100, 20 mM HEPES

pH 7.4, 100 mM KCL, 2 mM EDTA, 1 mM PMSF, 10 μg/ml leupeptin, and 10 μg/ml

aprotinin. The cells were lysed on ice for 30 min and centrifuged at 13,000 rpm for 10

min at 4°C. The supernatants were then isolated and the protein concentrations were

determined with bicinchoninic acid (BCA) reagent (Pierce).

To inhibit the proteasome, 10 μM of lactacystin was added 6 h or 3 h prior to

lysis. Cells were lysed in either TX-100 lysis buffer (as described above) or in lysis

buffer supplied by the ELISA cell death detection kit (Roche).

2.3 Infection of INS-1E with GRP78 Adenovirus (Ad-GRP78)

One day prior to infection, 400,000 INS-1E cells were seeded onto 12-well

plates. The cells were infected with 9 × 108 pfu/ml of Ad-GRP78 or Ad-GFP and

incubated at 37°C and 5% CO2 for 2 h with gentle shaking every 30 min. Cells were

then washed with PBS and incubated at 37°C and 5% CO2 for 24 h in fresh media

44

(RPMI 1640) prior to further treatment. The recombinant GRP78 adenovirus was

constructed by Elida Lai.

2.4 Reverse Transfection of short interfering RNA (siRNA)

To knock down cellular mRNA of GRP78 and SDF2L1, cells were reverse

transfected using Lipofectamine RNAiMAX reagent. In brief, 12 pmol of GRP78

siRNA (Invitrogen), sdf2l1 siRNA (Invitrogen), GFP siRNA control (obtained from Dr.

Quathek Ouerfelli, Sloan-Kettering Institute) or no siRNA, were mixed in 200 μl of

Opti-MEM Medium (Invitrogen) supplemented with 2 μl of RNAiMAX Lipofectamine

Reagent (Invitrogen) in a new 12-well plate. The plate was incubated at room

temperature for 30 min. Meanwhile, the flask of cultured cells was trypsinized,

counted, and resuspended in complete RPMI 1640 media lacking antibiotics to a final

concentration of 100,000 cells/ml or 250,000 cells/ml for INS-1E and INS-1

Ins2(C96Y)-EGFP #4S2 respectively. Following the 30 min incubation, 1 ml of the

diluted cells (corresponding to 100,000 and 250,000 cells) was gently applied to the

side of each siRNA-containing well to obtain a final concentration of 10 nM

siRNA/Lipofectamine RNAiMAX complexes. The cells were then allowed to recover

overnight to recover prior to further treatment. The knockdowns were confirmed using

western blot and real-time PCR analysis as described below.

2.5 Measurement of XBP-1 mRNA Splicing

Rat XBP-1 cDNA was amplified by RT-PCR (QIAGEN OneStep RT-PCR kit)

using primers that flank the intron excised by IRE1 exonuclease activity as described

45

previously (Zhang et al., 2009). Total RNA was first isolated using Trizol reagent

(Invitrogen) followed by isolation using the RNeasy Mini Kit (Qiagen). RT-PCR was

conducted using the forward XBP-1 primer 5’- AAA CAG AGT AGC AGC ACA

GAC TGC -3’, the reverse XBP-1 primer 5’-TCC TTC TGG GTA GAC CTC TGG

GAG -3’ and the PCR protocol: 50 °C (30 min); 95°C (15 min); 30 cycles of [94°C (1

min), 62°C (1 min), 72 °C (1 min)]; 72 °C (10 min). The RT-PCR products were

visualized on a 3% agarose gel and visualized using ethidium bromide.

2.6 RNA Isolation and Real-Time Quantitative Polymerase Chain Reaction (PCR)

For real-time PCR analysis, total RNA was isolated from cells untreated or

treated with 2 μg/ml doxycycline for the indicated times using Trizol Reagent

(Invitrogen) and the RNeasy Mini Kit (Qiagen). Total RNA (1.95 μg) was reverse

transcribed to single-stranded cDNA using the High-Capacity cDNA Reverse

Transcription Kit (Applied Biosystems). The resulting cDNA was used for real-time

PCR analysis by the TaqMan Gene Expression system (Applied Biosystems). The

following primers were obtained from Applied Biosystems: CHOP (Rn00492098_g1),

ATF4 (Rn00824644_g1), GRP78 (Rn00565250_m1), PDI (Rn00564459_m1), ERO1la

(Rn00593473_m1), ERO1lb (Rn01520960_m1), SEL1 (Rn00710081_m1), ERdj4

(Rn00562259_m1), ERdj5 (Rn01486444_m1), SDF2L1 (Rn01404681_g1;

Mn00452079_m1), Ins2 (Rn01774648_g1), and β-actin (4352931E). Serial dilutions of

the control (INS-1 Ins2(C96Y)-EGFP #4S2 without doxycycline; INS-1E without

cytokines) cDNA were used to generate a standard curve. Reactions were run on an

ABI Prism 7900 HT Sequence Detection System (Applied Biosystems) using the

46

following protocol: 10 min at 95˚C, 40 cycles of 15 sec at 95˚C and 1 min at 60˚C. The

standard curve and corresponding values for each sample were determined by the SDS

2.1 software of the ABI Prism 7900HT instrument. Samples were run in triplicate.

Values were normalized to expression of β-actin mRNA and presented as a mean ±SE

of 3 independent experiments.

2.7 Electron Microscopy

Clone #4S2 cells were fixed in 2% glutaraldehyde (EM Sciences) in 0.15 M

Sorensen’s Phosphate Buffer (pH 7.4) (EM Sciences) for 30 min at room temperature.

The cells were washed twice with PBS and collected into new tubes. Samples were

prepared for transmission electron microscopy by the electron microscopy facility at

Mount Sinai Hospital (Toronto). Briefly, the cell pellets were fixed in 2%

glutaraldehyde in 0.1 M sodium cacodylate buffer (pH 7.3) for 2 h, rinsed with the

same buffer for 10 min, and post-fixed for 1.5 h in 1% OsO4. After rinsing with the

same buffer for 10 min, the cells were dehydrated through a graded ethanol series up to

100% ethanol. The cells were then embedded in Spurr resin in an oven at 65°C

overnight. Thin sections (~100 nm) were cut on an RMC MT6000 ultramicrotome.

The sections were placed on copper grids and stained with uranyl acetate (20 min) and

lead citrate (10 min). The grids were examined in a FEI Tecnai 20 transmission

electron microscope and images were captured on a Gatan Dualview digital camera.

47

2.8 Insulin Secretion Assay and Rat Insulin Radioimmunoassay (RIA)

To generate the insulin secretion data presented in Fig. 3.5, 300,000 INS-1E

cells were seeded onto 12-well plates. The cells were given two days to recover

37˚C/5% CO2 and infected or not with GRP78 or GFP adenovirus (described in Lai et

al., 2008). The following day (24h later), cells were treated with cytokines (10 U/ml

IL-1β and 0.04 μg/ml IFN-γ) and incubated at 37˚C/5% CO2 for another 48 hours.

Following the treatment, cells were washed twice in Krebs-Ringer Bicarbonate Buffer

(KRBH) buffer consisting of 128.8 mM NaCl, 4.8 mM KCl, 1.2 mM KH2PO

4, 1.2 mM

MgSO4, 2.5 mM CaCl

2, 5 mM NaHCO

3, 10 mM HEPES, pH 7.4 and supplemented

with 0.1% BSA but no glucose, and then incubated for 1 h in the same buffer. The

cells were then washed again in KRBH/0.1% BSA without glucose and then incubated

in 1 ml KRBH/0.1% BSA containing 2.8 mM or 15 mM glucose for 1 h. Following the

treatment, the cells were put on ice and 700 μl of the supernatant was collected,

centrifuged at 5,400 rpm for 5 min at 4˚C, the supernatants from the spin were

subsequently collected and kept at -80˚C. The insulin secreted into the medium was

measured by rat insulin radioimmunoassay (RIA) (Linco Research Inc.) according to

the manufacturer’s instructions. The remaining cells on the plate were lysed in ice-cold

lysis buffer (1% Triton X-100, 20 mM HEPES, pH 7.4, 100 mM KCl, 2 mM EDTA, 1

mM PMSF, 10 μg/ml leupeptin, and 10 μg/ml aprotinin, 10 mM NaF, 2 mM Na3VO4,

and 10 nM okadaic acid) and the protein concentration was determined with BCA

reagents (Pierce). The insulin secretion was expressed as the amount of insulin

released into the culture medium (in nanogram) per milligram of protein content in

48

each condition. The assays were performed in duplicate for each condition from at

least 3 independent experiments.

To measure the total insulin content in the cells, 1 μl of each of the 5 mM

glucose whole cell lysates was first diluted in 499 μl of ice-cold PBS. The resultant

dilution (10 μl) was then used to measure the total amount of insulin in the cells using

the rat insulin radioimmunoassay (RIA) (Linco Research Inc.) according to the

manufacturer’s instructions.

2.9 Western Blot Analysis

Cells were washed in PBS and lysed in ice-cold lysis buffer (1% Triton X-100,

20 mM HEPES, pH 7.4, 100 mM KCl, 2 mM EDTA, 1 mM PMSF, 10 μg/ml leupeptin,

and 10 μg/ml aprotinin, 10 mM NaF, 2 mM Na3VO4, and 10 nM okadaic acid) for 15-

20 min on ice. Lysates were centrifuged at 13,000 rpm for 10 min at 4°C and the

protein concentration in the supernatant was determined using the BCA protein assay

(Pierce). Equal amounts of protein were boiled in 2x LSB (Laemmli sample buffer)

supplemented with 10% β-mercaptoethanol and resolved by SDS-PAGE followed by

transfer to Hybond-ECL nitrocellulose membranes (GE Healthcare). The blots were

then blocked using a solution of 1% skim milk in 0.1% BSA/Western wash buffer

(WWB). WWB consists of PBS supplemented with 0.05% Tween-20 and 0.05% NP-

40. Following blocking, the blots were incubated overnight at 4 °C in primary antibody.

The following primary antibodies were used: Phospho-eIF2α (Cell Signaling, #9721;

1:250), GADD153/CHOP (Santa Cruz, sc-575; 1:500), anti-KDEL (StressGen, SPA-

827; 1:1000), insulin (Santa Cruz; 1:250), γ-tubulin (Sigma, T6557; 1:1000), polyclonal

anti-GFP (obtained from Dr. James E. Rothman, Yale University; 1:1000), monoclonal

49

anti-GFP (Clontech, 632381; 1:2000), cleaved caspase-3 (Cell Signaling, #9661S;

1:1000), monoclonal PDI (StressGen, SPA-891; 1:2000), polyclonal ubiquitin (Dako,

Z0458; 1:2000), stromal derived factor 2-like 1(Sigma, HPA005638; 1:500), GM130

(Transduction Laboratories, G65120; 1:500), Protein A (Sigma, P2921; 1:5000) and

LC3B antibody (Cell Signaling, #2775; 1:1000). The blots were then washed 3 times

for 15 minutes each time in WWB and incubated with secondary antibody conjugated

to HRP for one 1 h. The blots were then washed again, 3 times for 15 minutes and the

bands were detected with the enhanced chemiluminescence system (GE Healthcare).

For Figure 3.4 densitometry was performed by scanning the photographic film and

measuring the relative darkness of the bands using Scion Image software. For detection

of insulin and cleaved caspase-3 by immunoblotting, the samples were resolved using

4-12% NuPage gels (Invitrogen).

2.10 Sucrose Density Fractionation

Following doxycycline treatment for 72 hours, clone #4S2 cells were washed

with PBS and resuspended in homogenization buffer: (0.25 M Sucrose, 4 mM HEPES,

1 mM MgCl2, 1.5 mM EDTA containing a complete protease inhibitor tablet (Roche), 1

mM PMSF, 10 mM NaF, 2 mM Na3VO4, 10 nM okadaic acid). Cells were

homogenized on ice with 12 strokes using a ball-bearing cell homogenizer. The

resulting homogenate was applied to a 0.45 M to 2 M sucrose gradient and centrifuged

for 18 h at 30 000 rpm, 4˚C, in a Beckman L7 ultracentrifuge as outlined in (Reetz et

al., 1991). After ultracentrifugation, 0.5 ml fractions were taken from the top of the

50

gradient and labeled 1 to 25. From these fractions, 15 μl was resolved using 4-12% Nu-

PAGE gels (Invitrogen) and immunoblotted as described in section 2.9.

2.11 Immunoprecipitation

For the immunoprecipitation experiments in Fig. 4.2, 3,000,000 Clone #4S2

cells were seeded onto 10 cm dishes one day prior to experiments. The cells were then

treated with 2 μg/ml doxycycline for 48 h. Following treatments, the cells were

washed twice with ice-cold PBS and lysed in ice-cold 1% TX-100 buffer, scraped, and

incubated for 30 minutes at 4 °C. The lysates were then centrifuged at 13,000 rpm for

10 min at 4 °C and the protein concentration in the supernatant was determined using

the BCA protein assay (Pierce). To immunoprecipitate the mutant insulin, 10 μg of

mouse monoclonal anti-GFP antibody (Clontech, 6323681) was added to 250 μl of

each of the untreated control and doxycycline treated lysate supernatants. As a control,

mouse IgG was added to 250 μl of the doxycycline treated lysate. The samples were

allowed to incubate with rotation overnight at 4 °C. Following the incubation, the

samples were added in their entirety to 50 μl of washed (in lysis buffer) Protein-G

dynabeads and incubated for 2 h at 4 °C. The supernatants were transferred to clean

microcentrifuge tubes, and the beads were washed with lysis buffer 3 times for 5 min.

The samples were eluted from the pellets in 20 μl of SDS sample buffer. The eluted

pellets in their entirety and 10 μg of the transferred supernatants were visualized using

Western blot analysis as described above. The primary antibodies used for the Western

blot was polyclonal anti-GFP (obtained from Dr. James E. Rothman, Yale University).

51

2.12 Apoptosis assays

2.12.1 ELISAPLUS Cell Death Detection Kit

For all of the experiments examining cell viability presented in chapter 3 and

many of the experiments in chapter 4, apoptosis was measured using the Cell Death

Detection ELISAPLUS kit (Roche Diagnostics) according to the manufacturers

instructions. Briefly, one day prior to experiments INS-1E or clone #4S2 cells were

seeded in 12- or 24-well plates (400,000 and 200 000 cells/well respectively) and

treated as indicated in the figure legends. Following the treatments, the cells were

lysed and oligonucleosomes in the cytoplasm (indicative of apoptosis-associated DNA

degradation) were quantified according to the manufacturer’s instructions. Parallel

experiments were run and total protein concentration was measured. The relative

apoptotic signal was normalized for total protein. Control cells (in the case of clone

#4S2 cells, grown in the absence of doxycyline) had near background levels of

cytoplasmic oligonucleosomes and consequently all other treatment conditions were

normalized to this condition at each time point.

2.12.2 Flow Cytometry-based APO-BrdU TUNEL Assay

Terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL)

assays were performed using the APO-BrdU TUNEL Assay Kit (Invitrogen). Clone

#4S2 cells were treated as described in the figure legend (Fig. 4.7D), washed with

warm PBS, trypsinized, then stained with Fluor-647 dye-labeled anti-BrdU antibody,

according to the manufacturer’s protocols. After staining, the samples were analyzed in

a FACSCalibur flow cytometer (Becton Dickinson) at the Hospital for Sick Children

52

(Toronto) flow cytometry core facility. Cells were gated to exclude cell debris. To

standardize each sample and set the quadrants, negative controls (INS-1E cells and

clone #4S2 uninduced cells) and a positive control (provided by the APO-BrdU

TUNEL assay kit) were used. GFP and the Fluor-647 dye-labeled anti-BrdU antibody

were excited using the FL1 (530/30) and FL4 (661/16) lasers, respectively.

2.13 Microarray analysis

Microarray expression profiling was used to assess the global transcriptional

changes in response to Ins2(C96Y)-EGFP expression in clone #4S2 cells. Cells were

induced or not with doxycycline for 24 h, 48h or 5 days and total RNA was isolated

using Trizol Reagent (Invitrogen) followed by isolation using an RNeasy Mini Kit

(Qiagen). Assessment of RNA quality and microarray analysis was performed at the

University Health Network (Toronto) microarray centre. Briefly, following RNA

quality assessment with an Agilent BioAnalyzer, samples were reverse transcribed to

complementary DNA (cDNA). cDNA was purified with a cDNA purification module

from Affymetrix. Biotin was incorporated during in vitro transcription and purified

complementary RNA (cRNA) was then fragmented with a chemical reaction involving

zinc acetate. Labeled and fragmented cRNA (15 μg) was hybridized to Rat Genome

230 2.0 arrays (Affymetrix Genechip) for 17 h at 45°C at 60 rpm speed. The arrays

were stained and washed using GeneChip® Operating Software (GCOS) and fluidic

stations, which stain the GeneChips® with phycoerythrin-labeled Streptavidin (SAPE),

washes them, and then incubates the GeneChips® with biotinylated anti-streptavidin

antibody solution. All arrays are scanned using Affymetrix's 3000 7G scanner. The

53

data sets were analyzed using GeneSpring software (Version 7.1) (Agilent

Technologies) and statistical analysis was performed using GeneSpring software

according to the manufacturer’s specifications. Genes with a minimum 2-fold

difference between control and doxycycline-treated cells in at least two independent

experiments at 24 h, 48 h and 5 days are listed in Table I. The complete list of the gene

expression changes in each experiment is provided in the supplemental data section.

2.14 Cloning of SDF2-L1

For the project discussed in Appendix 2, the cDNA encoding Sdf2l1, which is

663 base pairs in length, was reverse transcribed from total RNA of clone #4S2 cells

exposed to tunicamycin for 16 h using the QIAGEN OneStep RT-PCR Kit according to

the manufacturer’s instructions. In brief, 100 ng of RNA was combined with Qiagen

RT-PCR buffer, One Step Enzyme mix, dNTPs, and the following primers, which

included the start and stop sites (bold) and were generated by ACGT Corporation

(Toronto, Canada):

Sdf2l1_forward 5’-ATGTTGGGCGCGAGCCGC-3’

Sdf2l1_reverse 5’-TCAGAGTTCATCGTGACCTGT-3’

The PCR protocol consisted of 30 min at 50˚C to reverse transcribe the RNA to DNA

followed by 15 min at 95˚C to initially activate the PCR and 35 cycles of denaturation

at 95˚C for 1 min, annealing at 60˚C for 1 min, and extension at 72˚C for 1 min. A final

10 minutes at 72˚C allowed for final extension. The RT-PCR products were visualized

on a 1.5% agarose gel and visualized using ethidium bromide. The 700bp band was gel

excised and purified from the gel using the Qiagen Gel Extraction Kit. The sdf2l1

54

cDNA was then cloned into TOPO®-TA (Invitrogen, Carlsbad, USA) following the

manufacturer’s instructions. TOPO-TA Cloning®* provides a highly efficient one-step

cloning strategy for the direct insertion of Taq polymerse-amplified PCR products into

a plasmid vector. Taq polymerase has a nontemplate-dependent terminal transferase

activity, which adds a single deoxyadenosine (A) to the 3’ ends of PCR products. The

linearized vector provided by the manufacturer has a single overhanging 3’-

deoxythymidine (T) residues allowing for the PCR insert to ligate efficiently with the

vector. The vector was then transformed into OneShot®TOP10 chemically competent

cells (Invitrogen, Carlsbad, USA). Plasmid DNA was purified using the QIAamp®

DNA Mini Kit (Qiagen, Maryland, USA), cut with EcoR1 and run on a 1.5% agarose

gel to verify the presence of the insert (Sdf2l1 cDNA). Two plasmids were selected for

sequencing (ACGT Corp., Toronto, ON).

The Sdf2l1 cDNA was then cloned from the TOPO vector into pcDNA3.1(-) by

digesting 1 μg of the TOPO-Sdf2l1 construct and pcDNA3.1 (-) vector using XhoI and

HindIII (New England Biolabs) and subsequent ligation using the Takara DNA ligation

kit Ver.2.1 (Takara, #6022). This construct was then transformed into DH5α cells and

plasmid DNA from ampicillin resistant clones was isolated using the QIAamp® DNA

Mini Kit (Qiagen, Maryland, USA). The presence of Sdf2l1 cDNA was verified by

digesting the plasmid with XhoI and HindIII and running the sample on a 1.5% agarose

gel and detecting the presence of an insert with ethidium bromide.

For recombinant adenovirus production, Sdf2l1 cDNA was cloned into

pShuttle-IRES-hrGFP-2 (Stratagene). The TOPO-Sdf2l1 construct and pShuttle-IRES-

hrGFP-2 (Stratagene) vector were digested using NotI and SpeI (New England Biolabs)

55

and ligated using solution I (Takara). This construct was then transformed into DH5α

cells and plated. The following day, kanamycin resistant clones were picked and

amplified overnight. Plasmid DNA was isolated using the QIAamp® DNA Mini Kit

(Qiagen, Maryland, USA) and the presence of Sdf2l1 cDNA was verified similarly to

above.

Both the pcDNA3.1(-)-Sdf2l1 and pShuttle-IRES-hrGFP-2-Sdf2l1 constructs

were amplified and isolated using the Qiagen Plasmid Midi Kit (Qiagen, Maryland,

USA).

For future structural studies of Sdf2l1 in a mammalian system, Sdf2l1 cDNA

has also been cloned into a PA-IRES vector generously supplied by Dr. James Rini

(University of Toronto, Canada). To make this construct, primers were designed which

encoded for a 5’ FseI digestion site as well as removal of the N-terminal signal

sequence, as it was already present in the vector upstream of protein A, and a 3’ Not1

digestion site as well as removal of the HDEL ER retention signal.

The designed primers were constructed by ACGT Corporation Inc (Toronto,

Ontario) incorporating the restriction sites FseI and NotI (bold italic). Their sequences

were as follows:

Sdf2l1_FseI

5’- CCCSCGAAGGCCGGCCCTCGAAGGCCAGCGCCGGGCTA -3’

Sdf2l1_Not1

5’- TTTTCCTTTTGCGGCCGCCTAACCTGTGGAGGGATCTGC -3’

The cDNA encoding Sdf2l1 was PCR amplified from 100 ng of pcDNA3.1(-)-Sdf2l1

construct combined with 150 ng of each of the designed primers. The PCR protocol

56

was as follows: 4 min at 94˚C, 32 cycles of 20 s at 94˚C, 20 s at 70˚C, 1 min at 72˚C,

followed by 3 min at 72˚C.

Running the PCR products on a 1.5% agarose gel and visualizing the bands

using ethidium bromide verified the amplification. The PCR product was then gel

purified and digested, along with the PA-IRES vector, using FseI (New England

Biolabs #R0588) and NotI (New England Biolabs #R0189) restriction enzymes. The

PA-IRES vector was then incubated for 20 min with Antarctic Phosphatase (New

England Biolabs #M0289) and both the digested products were run on a 1.5% agarose

gel and gel purified using the Invitrogen PureLink Quick gel extraction kit. The

digested vector and insert were then ligated using the Quick Ligation kit (New England

Biolabs) according to the manufacturer’s protocol. The ligated product was then

transformed into DH5α cells. Ampicillin resistant clones were then screened for

positive clones using PCR and the forward and reverse primers described above. The

PCR cycle used was as follows: 4 min at 94˚C, 32 cycles of 20 s at 94˚C, 20 s at 70˚C,

1 min at 72˚C, followed by 3 min at 72˚C. All of the PCR products were run on a 0.8%

agarose gel and visualized using ethidium bromide. Two positive clones were selected,

and the plasmid DNA was isolated using the QIAamp® DNA Mini Kit (Qiagen,

Maryland, USA). The DNA was then amplified even further and isolated using Qiagen

Plasmid Midi Kit (Qiagen, Maryland, USA).

2.15 Transient Transfection

To determine if the plasmids allowed for the overexpression of SDF2L1,

HEK293T cells were transiently transfected using Lipofectamine reagent. In brief,

57

300,000 cells were seeded onto a 12-well plate and incubated at 37 °C, 5% CO2

overnight. The following day, 50 μl of Opti-MEM medium (Invitrogen) was mixed

with 2 μl of Lipofectamine Reagent and incubated for 5 min. Following the incubation,

the Opti-MEM/Lipofectamine mix was added to 1 μg of the pA-IRES Sdf2l1 plasmid

DNA or the pA-IRES vector DNA alone (control) and incubated at room temperature

for 20 min. Warm DMEM (500 μl) media without antibiotics was then added to the

DNA mixture. The 12-well plate was taken from the incubator and the old media was

aspirated and replaced with the media containing the DNA. The plate was then placed

back into the incubator and incubated for 24 h. The transfection was confirmed using

Western blot analysis.

2.15 Data analysis

Results are presented as mean ±SE. Statistical significance between two

experimental conditions was analyzed using a two-sample t-test assuming equal

variance. Data from several or more groups was analyzed by ANOVA, followed by

Tukey post hoc test. P<0.05 was considered statistically significant.

58

CHAPTER 3: ER STRESS AND CYTOKINE-INDUCED PANCREATIC β-CELL DYSFUNCTION AND APOPTOSIS

The studies with rat islets in this chapter (Fig. 3.6) were performed by Liling Zhang.

59

3.1 Introduction

Chronic inflammation has been implicated as a mediator of pancreatic β-cell

loss in both of the major forms of diabetes, type 1 and type 2. In type 1 diabetes, an

autoimmune-mediated attack causes the destruction of a large proportion of β-cells

resulting in insufficient blood glucose regulation (Eizirik and Mandrup-Poulsen, 2001).

The pathogenesis of type 2 diabetes is more complicated involving both genetic and

environmental factors. However obesity, which is the biggest risk factor for type 2

diabetes development, is associated with low level chronic inflammation (Hotamisligil

and Erbay, 2008; Donath et al., 2003). In vitro exposure of β-cells to IL-1β, or a

combination of IL-1β and IFN-γ has been shown to cause functional changes similar to

those observed in pre-diabetic patients, including elevated proinsulin/insulin levels

(Hostens et al., 1999) and a preferential loss of first-phase insulin secretion in response

to glucose (Ohara-Imaizumi et al., 2004). Although the β-cell dysfunction associated

with inflammatory cytokines may be due to nitric oxide production (Eizirik et al.,

1996), the mechanism by which β-cells are destroyed has still not been fully elucidated.

Recently, some studies have implicated cytokine-induced ER stress as

potentially contributing to β-cell death and dysfunction (Eizirik et al., 1996). It is well

established that if ER stress is chronic or severe, elements of the apoptotic machinery

are induced (Oyadomari and Mori, 2004). It has been suggested that IL-1β and IFN-γ

cause ER stress through NO production and subsequent downregulation of SERCA2b

expression, which results in reduced ER calcium levels (Cardozo et al, 2001;

Oyadomari et al, 2001; Cardozo et al, 2005). In addition activation of the PERK and

IRE1 stress sensors has been detected in response to cytokines, although neither the

60

activation of ATF6, nor induction of the ER chaperone GRP78/BiP was observed

(Cardozo et al., 2005). In vitro studies have shown that all three ER stress-induced

apoptotic pathways are activated by cytokines: caspase-12 cleavage, activation of the

JNK pathway, and induction of the transcription factor CHOP (Contreras et al., 2003;

Cardozo et al., 2005; Akerfeldt et al., 2008).

Despite these findings, recent studies have cast doubt on the contribution of ER

stress to cytokine-induced β-cell apoptosis. Whereas PERK knockdown resulted in

enhanced cell death in tunicamycin-treated RINm5F cells, it had no effect in those cells

exposed to IL-1 (Chambers et al., 2008). Other studies have used chemical chaperones

such as PBA to determine whether increased folding capacity has any effect on

cytokine-induced apoptosis. PBA treatment of INS-1 β-cells and rat islets had no effect

on the cytokine-induced level of JNK, but did decrease the palmitate-induced level of

JNK (Akerfeldt et al., 2008). In addition, knockdown of endogenous CHOP levels

using CHOP siRNA has been found to protect INS-1 β-cells from palmitate- but not

cytokine-induced cell death.

Thus, the mechanism of cytokine-induced dysfunction and death in insulin-

producing pancreatic β-cells has not yet been fully elucidated. In this study we

examined the effect of inflammatory cytokines on β-cell apoptosis, insulin biosynthesis

and secretion and whether stress in the ER contributes to these effects.

61

3.2 Results

3.2.1 Cytokines induce apoptosis in INS-1E cells.

We first tested whether the combination of cytokines (10 U/ml IL-1β and 0.04

μg/ml IFN-γ) was able to induce apoptosis in INS-1E cells. We used two assays to

monitor apoptosis, an ELISA cell death detection kit, which measures the relative

amount of cytoplasmic mono and oligonucleosomes (indicative of apoptotic-related

DNA degradation), and activation of caspase-3. IL-1β + IFN-γ treatment caused a

significant increase in the amount of apoptotic cells in the population after 24 h, which

was more pronounced after 48h in comparison to both the non-treated and BSA

controls (Fig. 3.1A).

We examined whether cytokines induce the cleavage of caspase-3, a well-

established apoptosis marker, by western blot analysis. Although staurosporine-

treatment resulted in the appearance of cleaved caspase-3, none was detected in

response to cytokine treatment (Fig. 3.1B).

62

Figure 3.1. Cytokines induce cell death in the rat pancreatic β-cell line INS-1E. Cells were exposed for 8 h, 24 h or 48 h to 0.1% bovine serum albumin (BSA), IL-1β + IFN-γ (10 units/ml and 0.04 μg/ml respectively) or left untreated (control). Following the treatments, the cells were lysed and apoptosis was measured using a cell death detection ELISA kit (Roche). Apoptosis induction was normalized to the untreated control sample. *p<0.05, **p<0.001. In B, cells were washed in PBS, lysed and equal amounts of protein were resolved by Nu-PAGE and immunoblotted using anti-active caspase 3 and tubulin antibodies.

3.2.2 Cytokines activate an early ER stress response in INS-1E cells.

To determine if cytokines induce ER stress, we first examined the relative

mRNA levels of three well-known ER stress response genes using real-time PCR (Fig.

3.2A-C). Similar to previous studies (Cardozo et al., 2005) we observed no change in

the mRNA level of Grp78 after 8, 24 or 48 h of cytokine treatment (Fig. 3.2A).

However, an increase in the mRNA levels of both CHOP and ATF4 was observed after

63

8 h of cytokine treatment (Fig. 3.2B,C), an effect that was reversed by 24 h.

Interestingly, the level of ATF4 mRNA was significantly lower after 48 h of cytokine

treatment (Fig. 3.2C). ATF4 and CHOP are induced by the PERK ER stress pathway,

suggesting that cytokines can induce some ER stress in INS-1E cells. We also

examined the ability of cytokines to induce XBP-1 splicing, a marker for IRE1 pathway

activation. Treatment of INS-1E cells with cytokines for 8 (data not shown), 24 and 48

h resulted in no noticeable splicing of XBP-1 (Fig. 3.2D), indicating that IRE1 is not

activated under these experimental conditions.

UPR activation was also examined using Western blot analysis. Cytokine

treatment for 24 and 48 h resulted in an increase in CHOP protein levels (Fig. 3.2E).

This is consistent with the increase in CHOP mRNA observed by real-time PCR (Fig.

3.2B), although the increase in protein levels occurred later (24-48 h) of cytokine

treatment compared to 8 h for the mRNA. However, neither PDI (Fig. 3.2F) nor

GRP78 (Fig. 3.2G) levels were affected by cytokine treatment. Cytokine treatment (24

h) also resulted in lower steady-state proinsulin levels in INS-1E (Fig. 3.2H).

64

Figure 3.2. Cytokine exposure induces the UPR in INS-1E cells. Cells were treated for 8 h, 24 h or 48 h with IL-1β + IFN-γ (10 units/ml and 0.04 μg/ml respectively) or left untreated (control). A-C. Following treatment, total RNA was isolated and the mRNA levels relative to cellular β-actin of Grp78, CHOP, and ATF4 were analyzed by real-time PCR. Control cells treated with 2 μg/ml of tunicamycin for 16 h were used as a positive control for ER stress. In D, RNA was isolated from the cells and XBP-1 cDNA was amplified by RT-PCR using primers that flank the intron excised by IRE1 exonuclease activity. The unspliced form of XBP1 (uXBP-1, 480bp) and spliced form of XBP-1 (sXBP-1, 454bp) are indicated. In E-H, cells were washed in PBS, lysed, and 10 μg of protein were resolved by SDS-PAGE and immunoblotted with CHOP, PDI, GRP78, Proinsulin, GM130 and tubulin antibodies. GM130 and tubulin were used as loading controls.

65

3.2.3 GRP78 overexpression or treatment with chemical chaperone does not protect

INS-1E cells from cytokine-induced β-cell apoptosis.

GRP78 is an ER-resident chaperone that plays an integral role in the UPR

response, and was not induced with cytokine treatment. The lack of GRP78 induction

may hinder the ability of the β-cells to cope with ER stress. Overexpression of GRP78

has been shown to attenuate ER stress in β-cells (Laybutt et al., 2007; Lai et al., 2008).

Therefore, if cytokine-induced apoptosis is mediated through the ER stress response,

overexpression of GRP78 would be expected to ameliorate cytokine-induced cell death.

However, recent studies have shown that increased levels of GRP78 by transient

transfection with a GRP78 expression vector did not decrease cytokine-induced β-cell

apoptosis using a cytokine cocktail with concentrations of 50 U/ml of IL-1β and 500

U/ml IFN-γ (Akerfeldt et al., 2008). We therefore questioned whether overexpression

of GRP78 by adenoviral infection was capable of protecting INS-1E cells against

cytokine-induced apoptosis. Recombinant adenoviruses are commonly used to achieve

more robust transfection efficiency as pancreatic β-cells are difficult to transfect with

conventional methods (Antinozzi et al., 1999).

INS-1E cells were infected with recombinant GRP78- or GFP-expressing

control virus as described in the Methods, and then treated in the presence or absence of

cytokines for 24 h. An apparent overexpression of GRP78 was achieved (Fig. 3.3A).

The effect of GRP78 overexpression on cytokine-induced apoptosis was then measured

using the ELISA cell death detection kit. Cytokine-induced cell death was similar in

both the GFP and GRP78 overexpressing cells (Fig. 3.3B). GRP78 overexpression also

66

had no effect on the cytokine-induced increase in CHOP levels (Fig. 3.3C), which

would be expected to decrease if ER stress was significantly attenuated.

As an alternative approach to overexpressing GRP78, chemical chaperones have

been widely used to confer ER stress protection in a variety of cell types (Akerfeldt et

al., 2008; Ozcan et al., 2006). 4-Phenylbutyric acid (PBA) acts as a chemical

chaperone to reduce the load of unfolded proteins in the ER by improving the folding

capacity in a similar manner to GRP78. We thus tested the sensitivity of PBA treated

INS-1E cells to cytokine-induced apoptosis. Similar to the results with GRP78

overexpression, we found that PBA treatment did not ameliorate cytokine-induced β-

cell death, but tended to enhance cytokine-induced apoptosis (Fig. 3.3D).

3.2.4 GRP78/BiP knockdown increases INS-1E susceptibility to cytokine-induced

apoptosis and potentiates the effects of cytokines to reduce proinsulin levels.

We examined whether reducing ER chaperone capacity by depleting GRP78

affected cytokine-induced apoptosis. We knocked-down GRP78 expression using

siRNA in INS-1E cells and monitored the effect on cytokine-induced apoptosis. As

shown in Fig. 3.4A expression of GRP78 was reduced dramatically by GRP78 siRNA

compared to a control GFP siRNA. INS-1E cells depleted of GRP78 had higher levels

of apoptosis under control conditions compared to GFP siRNA-treated cells (Fig 3.4C).

Cytokine treatment induced apoptosis in both the control (GFP siRNA) and GRP78-

depleted cells. The level of apoptosis induction was significantly higher in GRP78

depleted cells treated with cytokines for 24 h compared to the cytokine-treated control

67

cells (Fig. 3.4C). The susceptibility of cells depleted of GRP78 was further exaggerated

with cytokine treatment for 48 hours (Fig. 3.4D).

* *

*

*

Figure 3.3 Effect of GRP78 overexpression or PBA treatment on cytokine-induced apoptosis in INS-1E cells. For A and B, INS-1E cells were infected with recombinant adenovirus expressing GFP or GRP78 as outlined in the Methods. After 24 h, the cells were treated with IL-1β (10 U/ml) + IFN-γ (0.04 μg/ml) or left untreated. In B, following the treatments, the cells were lysed and apoptosis was measured using a cell death detection ELISA kit (Roche) as described in the Methods. Shown are the mean ±SE of 3 independent experiments, normalized to the control sample. *p<0.05. In A and C, cells were washed in PBS, lysed and equal amounts of proteins were resolved by 10% SDS-PAGE and immunoblotted using anti-KDEL, tubulin, and CHOP. D. INS-1E cells were treated or not with PBA (2.5 mM) with or without IL-1β (10 U/ml) + IFN-γ (0.04 μg/ml) for 24 h. Following treatment, the cells were lysed and apoptosis was measured using a cell death detection ELISA kit (Roche) as described in the Methods. Shown are the mean ±SE of 3 independent experiments, normalized to untreated control cells. *p<0.05

68

In addition to increased β-cell apoptosis, cytokines have been shown to cause β-

cell dysfunction in insulin biosynthesis. We thus examined the effect of cytokine

treatment on proinsulin levels in INS-1E cells using western blot analysis. We found

that cytokine treatment for 24 h resulted in a decrease in proinsulin (Fig. 3.4A), an

effect that was quantified by densitometry (Fig. 3.4B). Interestingly, depletion of

endogenous GRP78 also resulted in a large decrease in proinsulin levels (Fig. 3.4AB).

Figure 3.4 siRNA-mediated silencing of GRP78 expression in INS-1E cells renders them more susceptible to cytokine-induced apoptosis. INS-1E cells were reverse transfected with GRP78 siRNA or control GFP siRNA using Lipofectamine RNAiMAX reagent (Invitrogen), and treated 24 h later with IL-1β (10 U/ml) + IFN-γ (0.04 μg/ml) for either 24 h (A,B) or 48 h (C). Following the treatments, the cells were either lysed and apoptosis measured using a cell death detection ELISA kit (Roche) or lysed in TX-100 lysis buffer. B. Densitometry for the gel in A was conducted using Scion image software and the proinsulin levels for each condition were normalized to each respective tubulin lane. Shown are the averages of the duplicate lanes. C-D. Apoptosis induction was normalized for protein in each condition and the results are presented relative to untreated cells (control). Each condition was performed in duplicate in each experiment. Shown are the mean ± SE of 3 independent experiments. In A, cells were washed in PBS, lysed and equal amounts of proteins were resolved by 10% SDS-PAGE and immunoblotted using anti-KDEL, proinsulin and tubulin antibodies.

69

3.2.5 GRP78 overexpression does not ameliorate cytokine-induced β-cell

dysfunction in insulin biosynthesis or secretion.

Because knocking-down GRP78 expression resulted in a more exaggerated

decrease in proinsulin levels, we questioned if overexpression of GRP78 would

ameliorate the cytokine-reduced proinsulin levels. GRP78 overexpressing cells have

slightly elevated steady-state proinsulin levels compared to controls (Lai et al., 2008),

suggesting that GRP78 may improve proinsulin biosynthesis and/or folding. We

observed by western blot analysis (Fig. 3.5A) and measurement of total cellular

proinsulin content (Fig. 3.5B) that overexpression of GRP78 has no effect on proinsulin

levels in cytokine-treated cells.

We also examined the effect of cytokines on insulin mRNA levels by real-time

quantitave PCR (Fig. 3.5C). We observed that Insulin2 mRNA levels were lower in

cytokine-treated cells, suggesting that the cytokine-induced decreases in proinsulin are

likely a result of decreased insulin mRNA levels. This decrease could be either due to

cytokine-mediated transcriptional regulation or premature mRNA degradation.

Cytokines have also been shown to decrease glucose-stimulated insulin secretion via a

mechanism that inhibits first-phase insulin secretion (Ohara-Imaizumi et al., 2004).

One mechanism that may account for this effect is cytokine treatment dissipates the

calcium gradient established between the ER and cytoplasm, resulting in defective

calcium signaling, a lower ATP/ADP ratio and inhibition of insulin granule release

mediated by KATP channels (Straub and Sharp, 2004). GRP78 is a calcium binding

protein that helps maintain high levels of ER calcium (Hendershot, 2004). Thus, we

examined whether the overexpression of GRP78 affects cytokine-mediated inhibition

70

of glucose-stimulated insulin secretion. As shown in Fig. 3.5D, overexpression of

GRP78 in INS-1E cells did not ameliorate cytokine-mediated inhibition of glucose-

stimulated insulin secretion in comparison to the GFP adenovirus control.

3.2.6 Effect of cytokine treatment on rat islet insulin biosynthesis and secretion.

We next examined the effect of cytokine treatment on insulin biosynthesis and

secretion in isolated rat islets. In contrast to the effect of cytokines in INS-1E cells,

cytokine treatment in rat islets resulted in an increase in steady-state proinsulin levels

(Fig. 3.6A) and tended to increase the total insulin content (Fig. 3.6B). Consistent with

the results in INS-1E cells, cytokine treatment in rat islets resulted in a decrease in

glucose-stimulated insulin secretion (Fig. 3.6C).

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Figure 3.5 Effect of cytokine exposure on insulin biosynthesis and secretion in INS-1E cells. A. INS-1E cells were infected with recombinant adenovirus expressing GFP or GRP78. After 24h, the cells were treated with IL-1β (10 U/ml) + IFN-γ (0.04 μg/ml) or left untreated. . Following treatment, the cells were lysed in TX-100 lysis buffer and equal amounts of protein were resolved by SDS-PAGE and immunoblotted for KDEL, proinsulin and tubulin. B. INS-1E cells were infected with recombinant adenovirus expressing GFP or GRP78. After 24h, the cells were treated with IL-1β + IFN-γ or left untreated. Following treatment, the cells were lysed in TX-100 lysis buffer and analyzed for total protein content using the rat insulin radioimmunoassay. C. INS-1E cells were left untreated or treated with IL-1β and IFN-γ for 8, 24, or 48 h. Following treatment, total RNA was isolated and the mRNA levels relative to cellular β-actin for Ins2 was analyzed by real-time PCR. D. INS-1E cells were infected with recombinant adenovirus expressing GFP or GRP78. After 24h, the cells were treated with IL-1β + IFN-γ or left untreated for 24h. Following treatment, the cells were exposed to either 2.8 mM or 16.7 mM glucose for 1h and the supernatants were analyzed using the rat insulin radioimmunoassay.

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Figure 3.6 Effect of cytokine exposure on insulin biosynthesis and secretion in rat islets. Rat islets were isolated and treated with cytokines for 48 h. Following treatment the cells were exposed to either 2.8 mM or 16.7 mM glucose for 1h. In A, cells were lysed in TX-100 lysis buffer and the protein content was measured. Equal amounts of protein were resolved by SDS-PAGE and immunoblotted for KDEL, proinsulin and tubulin. In B, following treatment, the cells were lysed in TX-100 lysis buffer and analyzed for total insulin content using the LINCO rat insulin assay. For C, following treatment, the supernatants were analyzed using the LINCO rat insulin assay.

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3.3 Discussion

In this study we have examined the contribution of ER stress in cytokine-

induced β-cell dysfunction and apoptosis in INS-1E, an insulinoma cell line that

possesses the characteristics of primary β-cells, including the ability to produce and

secrete insulin. INS-1 and INS-1 derived cell lines are widely used models to study the

mechanism of cytokine-induced β-cell dysfunction (Akerfeldt et al., 2008; Cardozo et

al., 2005; D’Hertog et al., 2007; Kutlu et al., 2003). Consistent with previous studies

(Akerfeldt et al., 2008; Cardozo et al., 2005; D’Hertog et al., 2007; Kutlu et al., 2003),

we found that cytokine treatment (IL-1β+IFNγ) resulted in a significant increase in

apoptosis after 24h, an effect that was exaggerated with longer treatment (48h) (Fig.

3.1A).

The molecular mechanism of cytokine-mediated apoptosis is still unclear.

While several signaling pathways have been proposed to play a role in cytokine-

mediated cell death (Cnop et al., 2005), it remains to be determined how these

pathways cooperate and their respective contributions to ultimately causing apoptosis.

A growing body of evidence has supported a role for mitochondrial-dependent

apoptotic pathways in cytokine-mediated β-cell apoptosis (Barbu et al., 2002; Papacio

et al., 2005; Chang et al., 2004). During this process, the inner mitochondrial

membrane is depolarized and causes the release of cytochrome c into the cytoplasm

resulting in activation of the caspase cascade. We examined whether caspase-3, an

important caspase in the apoptotic process (Tibbetts et al., 2003), was cleaved and

activated by combined IL-1β + IFN-γ in INS-1E cells. Interestingly, despite inducing

apoptosis we did not detect caspase-3 activation by 24 - 48 h cytokine treatment (Fig.

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3.1B). Caspase-3 activation has been observed in some studies using INS-1 cells

treated with cytokines (Akerfeldt et al., 2008; Grunnet et al., 2009), however these

studies used higher cytokine concentrations. Thus, the lack of activation of caspase-3

in our system supports a role for mitochondrial-independent apoptotic pathways in

cytokine-induced apoptosis. This result is consistent with a study examining the effect

of IL-1 in RINm5f cells (Chambers et al., 2008) which had no effect on caspase-3

activation but did induce apoptosis.

Cytokines have been shown to reduce ER calcium levels (Cardozo et al., 2005),

which in turn can cause ER stress. To examine if exposure of INS-1E cells to

cytokines resulted in the induction of ER stress we monitored activation of unfolded

protein response pathways and target genes. CHOP and ATF4 mRNA were induced at

8 h of cytokine treatment, but were back to basal levels by 24 h and ATF4 levels were

significantly lower after 48 h. This previously unreported result indicates an initial

activation of the PERK arm of the UPR response that is blunted with time. We also

examined the activation of the IRE1α pathway by assessing XBP1 splicing. XBP1 is a

key transcription factor in the induction of ER chaperones and genes from the ERAD

pathway (described in section 1.4.2) and splicing of the XBP1 mRNA is a widely used

marker for detection of ER stress. With our experimental protocol no XBP1 splicing

was detected at any time point of cytokine exposure. Lack of IRE1 activation suggests

that IL-1β + IFN-γ does not induce sufficient ER stress to activate IRE1 signaling, or

that somehow cytokines impair IRE1 signaling in the presence of ER stress. In

addition, typical UPR target genes such as GRP78 and PDI were not induced with

cytokine treatment (Fig. 3.2A and C). Thus, although early activation of the PERK

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pathway, which is induced by ER stress, was detected, lack of IRE1 activation or

induction of typical ER stress response genes suggests that minimal ER stress is

induced by our cytokine treatment protocol.

Some studies using cytokines in rat β-cells have observed XBP1 splicing

(Cardozo et al., 2005), while a recent study in INS-1E cells did not observe an increase

in XBP1 splicing with cytokine treatment (Akerfeldt et al., 2008). The inconsistencies

between the studies likely reflects the experimental approaches used and the cell system

studied. Depending on the cytokine mixture used and the length of treatment cytokines

can clearly induce ER stress to some extent. With our experimental protocol we detect

early activation of the PERK pathway, but undetectable IRE1 pathway activation and

no induction of UPR target genes. However, despite minimal ER stress the cytokines

induce significant apoptosis suggesting that at least with our experimental protocol, ER

stress is not a major factor in apoptosis induction.

Although we detected minimal ER stress as mentioned above, it is possible

that cytokines alter the ER stress response and the cell fails to induce essential ER

stress response genes. We observed no induction of GRP78 with cytokine treatment,

which is consistent with some studies (Cardozo et al., 2005). We therefore attempted

to increase the ability of INS-1E cells to deal with ER stress conditions by either

overexpressing GRP78 or increasing chaperone capacity using the chemical chaperone

PBA. We successfully overexpressed GRP78 using the same adenovirus described in

Lai et al. (2008), however, the overexpression failed to confer any protection from the

toxic effects of cytokines. Similarly, increasing the chaperone capacity of the ER using

the chemical chaperone PBA provided no protection. Recently, similar results have

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been reported in INS-1 cells in which GRP78 levels were increased using transient

transfection of a GRP78 expression vector (Akerfeldt et al., 2008). In addition, siRNA

silencing of CHOP has been shown to protect from palmitate-induced apoptosis, but

did not protect INS-1 cells from cytokine-induced cell death (Akerfeldt et al., 2008).

Interestingly, Chambers et al. (2008) found that PERK and IRE1α knockdown had no

effect on IL-1-induced apoptosis, whereas it had a profound effect with Tunicamycin

treatment. Thus, even though cytokines can induce some ER stress, ER stress is

unlikely to be primary contributor to apoptosis induction.

ER stress, however, may become a principle mechanism if the cell’s ability to

deal with ER stress is compromised. We found that depletion of endogenous GRP78

resulted in a dramatic increase in susceptibility of INS-1E cells to cytokines. This

result implies that in the presence of sufficient chaperone capacity, cells may be able to

deal with the ER stress associated with cytokine exposure, but in the absence of

sufficient chaperone capacity cytokine-induced apoptosis may in part be ER stress-

mediated.

In addition to causing cell death, cytokines also affect insulin biogenesis and

secretion in β-cells (Hostens et al., 1999; Ohara-Imaizumi et al., 2004). We therefore

examined the effect of cytokines on proinsulin expression in control cells and cells

depleted of chaperone capacity. We found that both cytokines and depletion of

endogenous GRP78 reduced proinsulin levels in INS-1E cells (Fig.3.4AB). This

suggests that GRP78 may play an important role in insulin biosynthesis. Our findings

led us to question whether GRP78 overexpression could counteract the effect of

cytokines on insulin. However, overexpression of GRP78 had no effect on cytokine-

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induced decreases in proinsulin levels, confirmed by both western blot analysis and

measurement of total proinsulin content of the cell (Fig. 3.5A and B). These data

suggest that the chaperone capacity of the ER may not be involved in the mechanism of

cytokine-induced proinsulin biogenesis dysfunction in INS-1E cells. The defect is

likely at the transcriptional level as cytokines significantly reduce insulin mRNA levels

(Fig 3.5C).

Interestingly, the decreased proinsulin levels observed in INS-1E cells with

cytokine treatment were not observed in rat islets, where cytokines increase proinsulin

levels (Fig. 3.6A and B). A study in human islets has reported a similar effect of

cytokines as we observed in rat islets (Hostens et al., 1999). Thus, there are differences

between INS-1E cells and primary cells in terms of how they react to cytokines. The

reason for this difference is unknown.

Cytokines however resulted in decreased glucose-stimulated insulin secretion

(GSIS) in both INS-1E and rat islets (Fig. 3.5D and 3.6C). This is consistent with a

previous study that showed that cytokine treatment inhibits the first phase of insulin

release, and that this inhibition is similar to that observed in prediabetic patients

(Ohara-Imaizumi et al., 2004). One theory proposes that the mechanism of cytokine-

mediated dysfunction in insulin secretion is through dissipation of the ER/cytoplasm

calcium gradient. We therefore reasoned that GRP78 overexpression might ameliorate

cytokine-induced inhibiton of insulin secretion, since GRP78 functions as a calcium

binding protein. However, we failed to observe any protection with GRP78

overexpression on GSIS inhibition (Fig. 3.5D). Interestingly, increasing calreticulin

levels caused an increase in ER Ca2+ stores as well as decreased cytokine-induced β-

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cell apoptosis (Oyadomari et al., 2001). It would be interesting to determine if

increased calreticulin levels would have an effect on cytokine-inhibited first-phase

insulin release.

3.4 Summary and Future directions

We have shown that a combination of the cytokines IL-1β + IFN-γ causes

significant apoptosis and dysfunction in INS-1E cells. This occurs in the absence of

significant ER stress, as monitored by UPR pathway activation and levels of ER stress

response genes. In addition, enhancing ER chaperone capacity failed to alleviate the

cytokine-induced apoptosis or dysfunction (reduced insulin levels and secretion).

However, cells depleted of chaperone capacity were more susceptible to cytokine-

induced apoptosis, thus ER stress may contribute to this effect under conditions where

ER chaperone capacity is reduced. As chronically elevated cytokines contribute to

causing β-cell dysfunction that results in diabetes it is important to understand in

molecular terms how they work.

In the present study, we looked at the involvement of ER stress in apoptosis

induced by exogenously treating cultured β-cells with the proinflammatory cytokines

IL-1β and IFN-γ. Despite our studies showing that ER stress may not be a contributing

pathway mediating cytokine-induced apoptosis and dysfunction in β-cells, it will be

important to continue doing studies examining the dose-response of INS-1E cells to

cytokines. Depending on the dose of cytokines and length of exposure, it appears that

β-cells exhibit variable levels of ER stress. It is therefore possible that ER stress

becomes a significant contributor to cytokine-induced apoptosis at higher

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concentrations of cytokines. In particular, studies examining the effect of JNK and

CHOP knockdown on cytokine-induced apoptosis at different cytokine-concentrations

would be interesting.

It will also be important to perform in vivo studies to examine the involvement

of proinflammatory cytokines in animal models of diabetes. Specifically, it is

important that studies be conducted that measure the exact concentration of cytokines

in and around the islets. Although studies have been able to measure the concentration

of cytokines in the blood, to our knowledge no study has accurately measured the level

of cytokines directly surrounding the islets. Because targeting adenovirus to the islet

cells in vivo is not possible, our lab has begun the process of generating a β-cell

specific GRP78 overexpressing knock-in mouse. Once this mouse has been generated,

it will be interesting to determine if it exhibits protection from cytokines as well as

other environmental factors associated with type 2 diabetes including lipotoxicity and

glucotoxicity. Studies have also shown that the oral administration of chemical

chaperones, such as PBA and taurine-conjugated ursodeoxycholic acid (TUDCA), into

animals resulted in protection from ER stress in cultured liver cells and obese and

diabetic mice (Ozcan et al., 2006). Studies could thus also be performed treating the

animals with these chemical chaperones to determine if they provide any protection in

β-cells.

The mechanisms of cytokine-induced dysfunction in β-cell insulin biosynthesis

and secretion should also be investigated in vivo. We showed that islets and cultured β-

cells exhibit different responses in insulin biosynthesis to exogenous cytokine

treatment. Future studies should also examine the mechanism of insulin mRNA

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regulation. Specifically, it would be interesting to determine if the effect of cytokines

on insulin mRNA is a pre- or post-transcriptional effect.

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CHAPTER 4: ANALYSIS OF THE ER STRESS RESPONSE IN A PANCREATIC β-CELL LINE EXPRESSING A FOLDING-DEFICIENT PROINSULIN-EGFP FUSION PROTEIN

The results presented in this chapter have been made into a manuscript and submitted to the Journal of Cell Science

Generation of the β-cell clone, Fig. 1A,C,D, and Fig 2A,B were performed by Elida Lai

ATF6 nuclear staining was performed by Tracy Teodoro

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4.1 Introduction

An increase in post-prandial blood glucose stimulates pancreatic β-cells to

secrete insulin, which mediates glucose disposal into tissues such as muscle and fat.

Glucose also acutely stimulates insulin translation, which replenishes the β-cell granule

stores that have been depleted during secretion (Ren et al., 2007). The effect of glucose

on translation increases the protein folding load in the endoplasmic reticulum (ER) of

the β-cell, which may transiently induce ER stress, a condition in which the folding

capacity of the ER is insufficient for the level of newly synthesized secretory proteins

and results in the accumulation of misfolded proteins. Such conditions are sensed by

ER localized stress sensors that mediate the unfolded protein response (UPR) (Ron and

Walter, 2007). This results in a transient reduction in translation efficiency to reduce

secretory protein load and induces chaperone capacity and ER-associated degradation

(ERAD). This type of ER stress may be a physiological situation the β-cell transiently

experiences during hyperglycemic conditions.

ER stress is also a feature of pathological conditions associated with obesity and

diabetes. Excess nutrients (free fatty acids, glucose), amyloid deposits and

inflammatory cytokines have all been shown to induce ER stress in pancreatic β-cells

(Eizirik et al., 2008). These conditions induce the UPR pathways that attempt to

counteract ER stress. Chronic ER stress, however, can lead to apoptosis induction

(Oyadomari and Mori, 2004), particularly in cell types with high secretory capacity

such as the β-cell. This is evident from the fact that perturbation of the UPR signaling

pathways in vivo leads to pancreatic β-cell death in animal models (Harding et al.,

2001; Scheuner et al., 2005; Zhang et al., 2002) and humans (Delepine et al., 2000). In

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addition, it has been hypothesized that chronic conditions associated with obesity over

time may lead to chronic ER stress-induced β-cell death and depletion of β-cell mass

that results in type 2 diabetes (Ahren, 2005).

A detailed temporal analysis of the UPR response in β-cells has not been

conducted. In addition the molecular mechanism of ER stress-induced apoptosis is still,

for the most part, unclear. ER stress in vitro and in vivo is typically studied using

pharmacological inducers of ER stress such as tunicamycin, reducing agents or

thapsigargin. However, these compounds cause intense ER stress that likely elicit

multiple responses in a short time frame, and the former two compounds likely induce

additional cellular responses independent of ER stress per se. The Akita mouse offers a

more physiological system that may mimic chronic ER stress specifically in β-cells in

vivo (Yoshioka et al., 1997). Expression of folding-deficient proinsulin in the Akita

mouse leads to pancreatic β-cell death as a result of ER stress and apoptosis (Wang et

al., 1999).

To study the ER stress response in pancreatic β-cells we developed a pancreatic

β-cell culture system based on the Akita mouse. Expression of a mutant proinsulin gene

(C96Y) fused to EGFP induced ER stress and apoptosis. In this study we examined the

temporal gene expression response resulting from induction of misfolded proinsulin

expression and the role of protein degradation in mediating survival in INS-1 β-cells

expressing misfolded proinsulin.

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4.1.1 Methods: Generation and characterization of the Insulin 2 (C96Y)-EGFP

stable INS-1 cell line

Prior to my arrival, a former graduate student in the Volchuk lab, Elida Lai, had

generated a stable pTet-ON INS-1 cell line that allows for doxycycline-inducible

expression of a mutant insulin EGFP fusion construct. The cell line was tested by

transient transfection of the insulin 2(C96Y)-EGFP fusion construct in the presence or

absence of doxycycline. Fusion protein expression was monitored by western blotting

and fluorescence microscopy. Expression of the fusion protein was doxycyline-

dependent and the fusion protein was localized intracellularly (Fig. 4.1A,B).

Interestingly, the expression of this construct also resulted in the production of a lower

migrating band, which may be due to proteolytic cleavage of the fusion construct in the

cell (Fig. 4.1A, arrow). A stable insulin 2(C96Y)-EGFP pTet-ON cell line was

generated by co-transfection with a hygromycin resistance plasmid. She isolated a

clone with inducible mutant insulin expression and fluorescence-activated cell sorting

was used to isolate GFP-positive cells (top 20%) after 48 h of doxycycline induction.

The sorted clone (designated clone #4S2) was expanded in media without doxycycline.

This clone exhibited low basal insulin 2(C96Y)-EGFP expression and a marked

induction following doxycycline treatment (Fig. 4.1C) with intracellular localization

(Fig. 4.1D).

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Figure 4.1 Induction of Insulin2 (C96Y)-EGFP protein expression in pTet-ON INS-1 cells by doxycyline. A-B. pTet-ON INS-1 #46 cells were transiently transfected with pTRE-Tight Ins2(C96Y)-EGFP construct in the presence or absence of 2 μg/ml doxycycline (Dox) for 48h. A. Cells were washed in PBS, lysed and 10 μg of protein were resolved by SDS-PAGE and immunoblotted using anti-insulin and EGFP antibodies. B. The cells were washed in PBS, fixed and mounted. GFP fluorescence was visualized using a laser confocal fluorescence microscope. C-D. A stable insulin(C96Y)-EGFP expressing INS1 clone (Clone #4S2), generated as described in the methods, was untreated (-Dox) or treated with 2 μg/ml doxycycline (+Dox) for the times indicated. The cells were washed in PBS, lysed and an equal amount of protein per condition was resolved by SDS-PAGE and immunoblotted using anti-GM130 and EGFP antibodies (C). D. EGFP fluorescence in fixed cells was visualized by confocal fluorescence microscopy.

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4.2 Results

In addition to the full-length fusion protein additional GFP immunoreactive

bands were observed in both TX-100 detergent whole cell lysates or lysates prepared

by direct lysis of the cells in SDS sample buffer (Fig. 4.2A). These fragments are likely

degradation products of the full-length fusion protein and most of the fragments could

not be efficiently immunoprecipiated using an anti-GFP antibody (Fig. 4.2B). The full-

length fusion protein localized to both ER and cytosol fractions by sucrose density

fractionation (Fig. 4.2C). Interestingly, the lower migrating degradation fragments

were present exclusively in the cytosol fractions, suggesting that degradation of the

fusion protein may occur in the cytosol. Endogenous proinsulin was found primarily in

the ER fractions as expected. The presence of soluble ER proteins in cytosolic fractions

is likely due to leakage during cell homogenization.

We examined the morphology of the stable cell line by electron microscopy

before and after doxycycline induction. In non-induced cells a normal ER morphology

was observed (Fig. 4.3A,B), whereas cells expressing Ins2(C96Y)-EGFP for three days

had an altered ER morphology (Fig. 4.3C,D). The ER was expanded and dilated

compared to control cells. The ER tended to be even more severely dilated in many of

the cells after six days of mutant protein expression (Fig. 4.3E,F). This morphology is

characteristic of unfolded protein accumulation and ER stress (Ron and Walter, 2007)

and has been observed in β-cells of the Akita mouse (Wang et al., 1999). In addition,

apoptotic cells were observed in the population expressing the fusion protein (Fig.

4.3C, arrowheads).

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Figure 4.2 Insulin 2(C96Y)-EGFP is localized to the ER while degradation products appear in the cytosol. A. Clone #4S2 cells were untreated (-Dox) or treated with 2 μg/ml doxycycline (+Dox) for 48 h. Following the treatments, the cells were washed in PBS and lysed in either 1% TX-100 lysis buffer (with protease inhibitors) or directly in SDS sample buffer with β-mercaptoethanol. Equal amounts of protein (or equal volumes) were resolved by SDS-PAGE and immunoblotted using anti-GM130 and GFP antibodies. B. Cells were untreated (Control) or treated for 48 h with 2 μg/ml of doxycycline before lysis and immunoprecipitation with anti-EGFP (rabbit, polyclonal) or control mouse IgG antibodies. The entire precipitate (pellets; P) and 10 μg of the supernatant (SN) were resolved by SDS-PAGE and immunoblotted using an anti-GFP (mouse, monoclonal) antibody. C. Cells were treated with 2 μg/ml doxycycline for 72 h, washed in PBS and homogenized in sucrose buffer as described in the methods. The homogenate was fractionated on a linear sucrose density gradient and an equal volume of each fraction was resolved by NuPAGE and immunoblotted using anti-GRP78, GFP and insulin antibodies.

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A B

DC

E F

Figure 4.3 Effect of Insulin2 (C96Y)-EGFP expression on ER morphology. Clone #4S2 cells untreated (A-B) or treated with 2 μg/ml doxycycline for 3 days (C-D) or 6 days (E-F) were washed in PBS and fixed in 2% glutaraldehyde/phosphate buffer. The cells were processed for transmission electron microscopy as described in the methods. ER structures in uninduced cells (B, open arrows), and distended ER structures in mutant insulin expressing cells following docycyline-induction (D-F, arrows) are indicated. The presence of apoptotic cells was evident in doxycyline-induced cells (C, arrowheads).

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4.2.1 The ER stress response to Insulin2 (C96Y)-EGFP expression

The morphological analysis indicated that the expression of Ins2(C96Y)-EGFP

was causing an accumulation of mutant insulin in the ER and causing ER stress. We

thus examined whether doxycycline-induced expression of Ins2(C96Y)-EGFP mutant

protein was activating the UPR signaling pathways. Ins2(C96Y)-EGFP expression was

induced for various times and activation of the ER stress-sensing pathways was

monitored. A small amount of spliced XBP-1, indicative of IRE1 activation, was

detected after 24 h of doxycyline induction and similar levels of spliced XBP-1 were

present throughout the induction period up to seven days (Fig. 4.4A). The levels of

phospho-eIF2α, indicative of PERK activation, were also increased (Fig. 4.4B), as were

the levels of active ATF6-p50 (Fig. 4.4C). Thus, expression of the mutant insulin

causes measurable activation of the ER stress pathways mediated by IRE1, PERK and

ATF6.

4.2.2 Microarray analysis of Insulin2 (C96Y)-EGFP expression

To examine the global transcriptional response to mutant insulin expression we

performed microarray analysis of the gene expression changes following Ins2 (C96Y)-

EGFP expression. Total RNA was prepared after 24 h, 48 h and 5 days of doxycycline

treatment from three independent experiments, reverse transcribed and hybridized on

Affymetrix rat genome arrays. Gene expression changes were examined and those that

were up-regulated or down-regulated by 2-fold at the various times are listed in the

Supplemental data. The number of differentially expressed genes was different between

the three time points. We noticed that many known ER stress-related genes were

induced at various times following mutant insulin expression. Shown in Table I are a

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Figure 4.4 ER stress signaling pathways are activated by Insulin2 (C96Y)-EGFP expression. Clone #4S2 cells were untreated (-Dox) or treated with 2 μg/ml doxycycline (+Dox) for the times indicated. Control INS-1 cells exposed to thapsigargin (Tg) or dithiothreitol (DTT) were used as a positive control. A. RNA was isolated from the cells and XBP-1 cDNA was amplified by RT-PCR using primers that flank the intron excised by IRE1 exonuclease activity. The unspliced form of XBP-1 (uXBP-1, 480bp) and spliced form of XBP-1 (sXBP-1, 454bp) are indicated. B. Clone #4S2 cells were treated as in (A), washed in PBS and lysed. Equal amounts of proteins were resolved by SDS-PAGE and immunoblotted with anti-phospho-eIF2α and GM130 antibodies. C. Clone #4S2 cells were treated with 1 mM dithiothreitol (DTT) or doxycycline as indicated and fixed for immunofluorescence labeling with anti-ATF6 antibody. The relative nuclear fluorescence of ATF6 was quantified. *p<0.05 relative to control.

selected list of genes induced >2-fold in at least two independent experiments at the

various time points. Several patterns emerged from this analysis. After 24 h of mutant

protein expression, the majority of the genes induced were ER localized chaperone

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genes (Dnajb9, Dnajc3, Dnajb11, Fkp11) as well as the ERAD-associated genes (Herp

and Sel1). The ER localized protein Sdf2l1 was the most abundantly induced gene

present in all three time points. In addition, the ATF4 and CHOP transcription factors,

target genes of the PERK-eIF2α pathway, were induced in two out of three

experiments at this early time point. TRB3 (Trib3), a putative target gene of CHOP

(Ohoka et al., 2005), was also induced in two out of three experiments.

Following 48 h of mutant protein expression a greater number of genes were

induced compared to 24 h (Table I and Supplemental data). Additional chaperone and

thiol oxidoreductase genes (Pdia2, Pdia3 and Pdia4) were up-regulated. The level of the

CHOP transcription factor was also significantly higher than at the 24 h time point.

However, the most abundantly transcribed gene at 48 h of mutant protein expression

was TRB3 (Trib3), a protein that has been implicated in apoptosis among other effects

(Hegedus et al., 2007; Ohoka et al., 2005). At this time point other genes including

protein transport genes and transcription factors were also up-regulated. By 5 days of

mutant protein expression the gene expression changes as monitored by microarray

were more variable between experiments than at the earlier time points. However, all

the chaperone genes observed at earlier time points were still elevated and additional

PDI family member genes (Pdia6 and Txndc4) were induced in two out of three

experiments. The levels of TRB3 were lower compared to 48 h mutant protein

expression, but still elevated. Interestingly, the levels of Sdf2l1, Creld2 and Armet

remained highly induced throughout the time course of mutant protein expression.

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Table I. Selected list of induced genes comparing uninduced cells to cells expressing insulin 2(C96Y)-GFP for 24 h, 48 h and 5 days identified by Affymetrix rat genome arrays. Mean fold change from three independent experiments for each time point is shown. Bold indicates the gene was induced in at least 2 independent experiments and italics indicates average induction value of multiple probes for the same gene.

Gene Name Entrez Function Fold Change Gene ID 24 h 48 h 5 days

Protein modification/ Folding Sdf2l1 680945 O-mannosylation? 5.7 4.7 10.9 Fkbp11 300211 Peptidyl-prolyl isomerase 2.9 3.9 4.3 Dnajb9/ ERdj4 24908 Protein folding 2.5 3 3.1 Dnajc3/ p58IPK 63880 Protein folding 2.3 2.8 4.2 Dnajb11/ ERdj3 360734 Protein folding 2.2 2.4 3 Pdia2 287164 PDI family, isomerase 3.1 2.7 Pdia3/ ERp57 29468 PDI family, isomerase 3.2 3.2Pdia4/ ERp70 116598 PDI family, isomerase 3.1 3.1 Hspa5/ GRP78 25617 ER Protein folding 2.6 Pdia6/ P5 286906 PDI family, isomerase 3Txndc4/ ERp44 298066 PDI family, isomerase 2

ER stress-inducible Herp 85430 ERAD 3.3 4.3 3.5Sel1h 314352 ERAD 2.5 2.7 2.6

Atf4 79255 Transcription factor 2.7 3 CHOP/ GADD153 29467 Transcription factor 2.5 3.5 2.7TRB3/ Trib3 246273 11.5 19.8 6.7

Transcription factors Mist1 25334 Transcription factor 2.9 3.2 3.7Atf5 282840 Transcription factor 2.4 3.3

Protein transport Kdelr3 315131 vesicle transport 2.1 2.9 3.8Tmed3 300888 protein transport 2.4 2.8

Selected Others: Creld2 362978 ER Protein folding? 3.6 3.6 7 Armet 315989 2.8 2.8 3.9 Myo1g 289785 Motor protein 2.3 2.9 2.5Ell3 296102 RNA polymerase II-like 3 2.1 2.2 3.6Magt1 116967 Magnesium transporter 2.1 2.3 2.4 Oat 64313 Ornithine aminotransferase 2 2.3 2.8

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Although some of the gene expression changes found were expected based on

the ER stress response induced in other models (discussed later), some genes predicted

to be increased were not observed, such as the ER chaperones GRP78 and PDI.

Microarray expression profiling can lead to false negatives due to inefficient probes.

Thus, we examined the mRNA and protein levels of several well-established targets of

the UPR pathways by real-time PCR and western blotting. An increase in the mRNA

and protein levels of GRP78 and CHOP was detected (Fig. 4.5A-D). Interestingly,

thapsigargin treatment for 6 h induced higher expression of CHOP protein in clone

#4S2 than in parental INS-1 cells, suggesting that clone #4S2 are more susceptible to

ER stress than control INS-1 cells (Fig 4.5D).

We also found by real-time PCR analysis that PDI and Sel1 were induced by

mutant insulin expression (Fig. 4.5E-G), substantiating the microarray results.

Furthermore, we found that Dnajb9/ERdj4 and Ero1β were induced (Fig. 4.6A,C).

However, not all UPR genes were induced as neither the mRNA levels of

Dnajb10/ERdj5, nor Ero1α oxidase, were affected (Fig. 4.6B,D).

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Figure 4.5 Expression of Insulin2 (C96Y)-EGFP induces genes associated with the ER stress response. Clone #4S2 cells were untreated (Control) or treated with 2 μg/ml doxycycline (+Dox) for the times indicated. A,C,E,F. Total RNA was isolated and the mRNA levels relative to cellular β-actin for Grp78 (A), Chop (C), PDI (E), and Sel1 (F) were analyzed by real-time PCR as outlined in the methods. Shown are the mean ± SE of 3 independent experiments. *p<0.05 relative to control. B,D. Clone #4S2 cells were treated as described above, washed in PBS, lysed and equal amounts of protein were resolved by SDS-PAGE and immunoblotted as indicated. Control INS-1 cells exposed to thapsigargin (Tg) were used as a positive control.

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Figure 4.6 Expression of Insulin2 (C96Y)-EGFP induces ERdj4 and Ero1β but not ERdj5 and Ero1α. Clone #4S2 cells were untreated (Control) or treated with 2 μg/ml doxycycline (+Dox) for the times indicated. Total RNA was isolated and the mRNA levels relative to cellular β-actin for ERdj4 (A), ERdj5 (B), Ero1α (C) and Ero1β (D) were measured.

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4.2.3 Induction of apoptosis following Ins2 (C96Y)-EGFP expression

Based on the microarray results it appears that the ER stress response to mutant

protein expression is biphasic. The early response involves up-regulation of genes

associated with protein folding and ERAD. Subsequently, at approximately 48 h of

mutant protein expression the levels of genes implicated in apoptosis became very

abundant, including CHOP and TRB3. We thus examined whether doxycycline-

induced expression of Ins2(C96Y)-EGFP mutant protein induces apoptosis. By light

microscopy many of the cells appear rounded in comparison to the control cells at

about 72 h of mutant protein expression, indicative of dead or dying cells (Fig. 4.7A,

arrows). To confirm that cell death was by apoptosis we measured cytoplasmic DNA-

associated histone complexes using a sensitive ELISA assay and found that 48 h to 7-

day treatment of doxycycline causes apoptosis in a time-dependent manner (Fig. 4.7B).

Western blot analysis also revealed a detectable increase in active caspase-3 by ~3 days

of mutant protein expression. To identify the relative percentage of apoptotic cells in

the mutant insulin expressing population we monitored apoptosis by TUNEL assay

using FACS analysis, which also allowed for the detection of mutant protein expression

by the GFP tag. Addition of doxycycline increased GFP fluorescence depicted on the y-

axis, compared to control cells not treated with doxycycline (Fig. 4.7D). The

percentage of apoptotic (TUNEL positive) cells is low and comparable to control cells

following 24 h doxycycline induction (Fig. 4.7D, left panels). However, mutant protein

expression following 5 days of doxycycline treatment leads to the induction of

apoptosis in approximately 14% of the population (Fig. 4.7D, right panel).

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Figure 4.7 Expression of Insulin2 (C96Y)-EGFP induces apoptosis. A. Clone #4S2 cells were treated or not with 2 μg/ml doxycycline for the indicated times, fixed and imaged by differential interference contrast microscopy. Potentially apoptotic cells with a rounded morphology are indicated (arrows). B-D. Clone #4S2 cells were treated with 2 μg/ml doxycycline for the indicated times. B. Following the treatments, the cells were lysed and apoptosis was measured using a cell death detection ELISA kit (Roche) as described in the methods. Shown are the mean ± SE of 4 independent experiments. *p<0.05. C. Cells were washed in PBS, lysed and equal amounts of proteins were resolved by Nupage and immunoblotted using anti-cleaved caspase-3 and γ-tubulin antibodies. D. Cells were fixed and labeled with Alexa Fluor 647 dye-labeled anti-BrdU antibody. Cells were analyzed by flow cytometry as described in the Methods. Cells in the upper left and right quadrants were classified as mutant insulin expressing, cells in the upper and lower right quadrants were classified as apoptotic based on BrdU staining. The total number of cells examined is shown below each chart, and the percentages of cells in each quadrant are indicated.

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The extent of apoptosis observed in the population expressing Ins2(C96Y)-

EGFP even for extended periods (>5 days) seemed rather low. We hypothesized that

the ER stress response in these cells, particularly the induction of ERAD genes, might

be responsible for maintaining cell survival by eliminating misfolded insulin and

preventing accumulation to toxic levels. We therefore examined whether inhibiting the

ERAD system might sensitize the cells to cell death. Cells were induced with

doxycycline for 48 h, treated or not with the proteasome inhibitor lactacystin and cell

apoptosis was monitored. Inhibition of the proteasome resulted in a significantly higher

percentage of apoptotic cells in the population (Fig. 4.8A). To confirm the inhibition of

the proteasome we ran a Western blot to show the accumulation of ubiquitinated

proteins in those cells exposed to lactacystin (Fig. 4.8B). This was also accompanied

by an increase in the levels of proinsulin-GFP fusion protein and degradation fragments

(Fig. 4.8B), suggesting that preventing ERAD increases misfolded protein levels and

induces greater ER stress.

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Figure 4.8 The proteasome inhibitor lactacystin increases susceptibility of the mutant insulin expressing clone to apoptosis. A. Clone #4S2 cells were untreated or treated with 2 μg/ml doxycycline for 48 h. Cells were then untreated or treated with 10 μM of lactacystin (LC) or an equivalent volume of DMSO for the times indicated. Cells were either lysed and apoptosis was measured using a cell death detection ELISA kit as described in the Methods. Shown are the mean ± SE of 3 independent experiments. *p<0.01. B. Following 42 h of doxycycline treatment, cells were untreated, or treated with 10 μM of lactacystin (LC) or an equivalent volume of DMSO for 6 h. The cells were washed in PBS and lysed. Cell lysates (left panel) or TX-100 insoluble material (right panel) were resolved by SDS-PAGE and immunoblotted using the indicated antibodies.

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The autophagy pathway has also been linked to protein degradation in the ER

stress response (Hoyer-Hansen and Jaattela, 2007). To examine if the autophagy system

is activated by mutant insulin expression we monitored the levels of LC3BII, which is

indicative of autophagy activation. Treatment of control cells with chloroquine resulted

in the appearance of LC3BII as has been reported previously (Sanjuan et al., 2007).

However, LCBII was not detectable in clone #4S2 treated with doxycycline (Fig. 4.9).

Thus, it does not appear that expression of Ins 2(C96Y)-EGFP significantly alters

autophagic activity.

Figure 4.9 Expression of Insulin2 (C96Y)-EGFP does not result in activation of LC3. Clone #4S2 cells were untreated or treated with 2 μg/ml doxycycline for 48 h. Following the treatments cells were washed in PBS and lysed. Equal amounts of protein were resolved by SDS-PAGE and immunoblotted using anti-LC3B and γ-tubulin antibodies. Chloroquine-treated cells were used as a positive control for LC3BII identification, a marker of autophagy induction.

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4.3 Discussion

The UPR is an essential mechanism by which cells respond to the accumulation

of misfolded protein in the ER that can occur either physiologically, as a result of acute

secretory protein load, or as a result of pathological insults that may impede protein

folding capacity. The basic ER stress response is well established and involves an acute

translational attenuation followed by the up-regulation of a transcriptional profile that

includes ER chaperone genes, ERAD components, traffic proteins, and other genes

(Ron and Walter, 2007). However, it is probable that different cell types have a unique

profile of up-regulated genes that are dependent on a particular cell’s function and

secretory proteins it produces. The goal of the present study was to examine the ER

stress response in the insulin producing pancreatic β-cell. Although ER stress can be

induced by chemical compounds such as tunicamycin, that inhibits N-linked

glycosylation, this form of ER stress likely induces multiple gene expression changes

simultaneously as potentially all secretory glycoproteins misfold. As such the ER stress

response to tunicamycin may not be reflective of a natural UPR response in β-cells.

Furthermore, the major secretory protein in β-cells is insulin, which does not contain

N-linked sugars and would not be directly affected by this compound. We therefore

developed a pancreatic β-cell culture model with inducible expression of a folding-

deficient insulin fusion protein based on the proinsulin mutation found in the Akita

mouse (Wang et al., 1999). The rationale behind this approach was that regulated

expression of a single misfolded protein would allow for a temporal characterization of

the UPR in β-cells.

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Using the tetracycline/doxycycline-regulated expression system we created a

double- stable INS-1 cell clone with stable integration of the pTet-ON regulatory

plasmid and the insulin C96Y-EGFP plasmid driven by the Tet/Dox-responsive

promoter. Basal expression of the mutant insulin is low, although detectable, in the

clone used for these studies. Following doxycyline addition the levels of mutant insulin

are markedly induced by 24 h, reaching maximal expression by ~72 h and are

subsequently maintained at this level for several days. Interestingly, we observed the

appearance of a prominent lower migrating band recognized by anti-GFP antibodies, in

addition to the mutant insulin fusion protein (Fig. 1 and 2). A similar cleavage product

has been detected with wild-type proinsulin tagged with GFP at the C-terminus and was

suggested to occur from non-specific cleavage of the fusion protein at some point along

the secretory pathway (Liu et al., 2007). In the case of the C96Y-mutant proinsulin the

cleavage products are not efficiently immunoprecipitated by anti-GFP antibodies and

are not detected in ER fractions. Thus, the smaller migrating bands recognized by GFP

antibodies are likely degradation products of proteolysis occurring in the cytoplasm.

Results from the sucrose density fractionation experiments and electron microscopy

suggest that the full-length mutant insulin fusion protein is retained in the ER, which is

consistent with a report showing that the C96Y (CA7Y) mutation in proinsulin results

in misfolding of the molecule and retention in the ER (Liu et al., 2007).

Expression of the mutant insulin fusion protein for 72 h leads to a swollen ER

lumen that is readily detectable in many cells and is indicative of misfolded protein

accumulation and a stressed ER. This result is similar to the phenotype observed in the

β-cells of Akita mice (Wang et al., 1999). As expected, expression of folding-deficient

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proinsulin-GFP fusion protein resulted in the induction of UPR pathways (PERK, IRE1

and ATF6).

To analyze the ER stress response in the cell line we performed microarray

expression profiling and real time PCR analysis following a time-course of mutant

protein expression. We chose time-points of mutant proinsulin-GFP expression when

no significant apoptosis was observed (24 h) and longer expression time points (48 h

and 5 days), when apoptotic cell death was detectable. After 24 h of mutant protein

expression when little or no apoptosis was observed in the population, the most

consistently induced genes were ER resident chaperone proteins (GRP78,

ERdj4/Dnajb9, p58IPK/Dnajc3, ERdj3/Dnajb11, Fkbp11) and an ERAD component

(Herp). The J-domain containing co-chaperone proteins (ERdj4, p58IPK, ERdj3) have

been shown to be induced by ER stress in various cell types (Cheetham and Caplan,

1998; Dong et al., 2008; Jin et al., 2008; Kurisu et al., 2003; Oyadomari et al., 2006;

Petrova et al., 2008; Rutkowski et al., 2007; Shen and Hendershot, 2005; Shen et al.,

2002). Recently, P58IPK and ERdj3 have been found to interact with misfolded

proteins in the ER prior to recruitment of the chaperone GRP78 (Jin et al., 2008;

Petrova et al., 2008; Rutkowski et al., 2007; Shen et al., 2002). In addition, these

proteins have also been implicated in targeting misfolded proteins for degradation via

the ERAD system (Dong et al., 2008; Oyadomari et al., 2006). Thus, expression of

misfolded insulin causes the induction of chaperone proteins early in an effort to fold

the mutant insulin. These chaperones are maintained at high levels throughout the time

course of mutant insulin induction and some may assist in degradation of the misfolded

molecule once folding is found to be futile (discussed below). The importance of

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P58IPK function in normal pancreatic β-cells in vivo is evidenced by increased

pancreatic β-cell apoptosis and hyperglycemia in knock-out mice (Ladiges et al., 2005).

The detailed molecular function of these co-chaperones in β-cells, however, has not

been examined.

Interestingly, although there are six mammalian DNAJ domain-containing

proteins, we only found a subset to be induced by mutant insulin expression. Notable

among those that were not up-regulated is ERdj5. Recently, expression of a folding-

deficient version of the secreted protein surfactant protein C in HEK293 cells caused

the induction of various ER stress response genes, including ERdj4 and ERdj5, which

were shown to be required for degradation of the folding-deficient surfactant protein C

(Dong et al., 2008). Interestingly, surfactant protein C, like proinsulin, contains

disulfide bonds, but is not glycosylated. Thus, it is interesting that we do not observe

induction of ERdj5 in β-cells expressing folding-deficient insulin. A recent report,

however, has shown that ERdj5 can interact with EDEM proteins and is required for

reducing disulfide bonds on misfolded, glycosylated proteins prior to retrotranslocation

(Ushioda et al., 2008). EDEM proteins were not induced by misfolded protein

expression, suggesting that proinsulin likely does not require EDEM/ERdj5 for its

degradation.

In eukaryotic cells, oxidative protein folding occurs in the ER and is

accomplished in part by the transfer of disulfide bonds from PDI to the newly

synthesized polypeptide (Reddy et al., 1996; Molinari and Helenius, 2000). This

process is made more efficient by the rapid re-oxidation of PDI by the ER

oxidoreductin (ERO) 1, an essential protein in yeast activated during the UPR (Pollard

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et al., 1998; Frand and Kaiser, 1998). Two human homologs of ERO1 have been

identified, ERO1α and ERO1β, and whereas their sequences and functions are similar,

their transcriptional patterns differ considerably. ERO1β has been shown to be

transcriptionally induced by ER stress causing agents, whereas ERO1α is not (Pagani et

al., 2000). Consistent with these studies, we found that misfolded insulin induced the

transcription of ERO1β but not that of ERO1α.

Ubiquitin-dependent ERAD is required for degrading misfolded insulin as

demonstrated by the induction of some ERAD genes (Herp and Sel1) and inhibiting the

26S proteasome sensitized the mutant insulin expressing cells to cell death. This also

resulted in an increase in the levels of putative degradation products of the mutant

proinsulin-GFP. A recent study has shown that disulfide bond-containing, non-

glycosylated proteins are targeted for ERAD degradation via a Herp-dependent

mechanism (Okuda-Shimizu and Hendershot, 2007). It is possible that mutant

proinsulin, or misfolded proinsulin under ER stress conditions, utilizes a similar

mechanism. This cell system should prove useful for the study of misfolded insulin

degradation.

Comparing the UPR response observed in our study to ER stress responses in

other cell types shows that some of the early chaperone genes induced by mutant

protein expression are not observed in other systems. For example, tunicamycin

treatment of neuroblastoma cells (Reimertz et al., 2003) or expression of a retroviral

protein in astrocytes, which induce ER stress (Antony et al., 2007), did not cause an up-

regulation of ERdj4/Dnajb9, p58IPK/Dnajc3, ERdj3/Dnajb11, Fkbp11. Importantly,

however, all of these genes have been shown to be induced by ER stress caused by

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prolonged palmitate exposure in cultured mouse MIN6 cells (Laybutt et al., 2007).

Saturated FFAs have been shown to induce ER stress in pancreatic β-cells and this may

contribute to β-cell dysfunction (Karaskov et al., 2006; Kharroubi et al., 2004; Laybutt

et al., 2007). In addition, a recent proteomic study examining islets from a diabetic

insulin resistant mouse model has shown that the protein and mRNA levels of some of

these genes (p58IPK/Dnajc3, ERdj3/Dnajb11, Fkbp11) are up-regulated (Lu et al.,

2008). Thus, the induction of these genes/proteins is likely important cell protective ER

stress response proteins in β-cells and detailed biochemical analysis of their function in

mediating proinsulin folding and/or degradation is warranted.

In addition to ER chaperone genes and ERAD components, several other genes

were found to be induced early as a result of mutant protein expression (Table I),

including Sdf2l1, Armet and Creld2. All three were abundantly up-regulated at both

early and late time points of mutant insulin expression. The exact functions of these

proteins in the ER stress response is largely undefined, although these proteins have

also been reported to be induced by ER stress-inducing compounds such as

tunicamycin in other cell types (Apostolou et al., 2008; Fukuda et al., 2001; Wu et al.,

2007).

In addition to the early response to mutant insulin expression, this model system

also allowed us to examine potential gene expression changes associated with ER

stress-induced cell death. An up-regulation of the pro-apoptotic transcription factor

CHOP and TRB3 was evident by 24 h of mutant insulin expression, which is indicative

of PERK pathway activation and is likely to be a normal physiological response. At this

time point no significant apoptosis is detected in the population. After 48 h of mutant

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insulin expression, however, the levels of CHOP and TRB3 were significantly higher,

which coincided with detection of apoptosis in the population. Thus, sustained

increases in the levels of CHOP and TRB3 may tilt cells towards apoptosis induction.

Pancreatic β-cells of CHOP-deficient heterozygous Akita mice are partially protected

from cell death (Oyadomari et al., 2002), indicating that CHOP has a role in apoptosis

induction, although clearly other factors are involved . In the mutant insulin expressing

cell line the most highly induced gene after 48 h was TRB3. This protein has recently

been shown to be induced by the PERK-ATF4-CHOP pathway and has been implicated

in mediating apoptosis (Hegedus et al., 2007; Ohoka et al., 2005), and more recently

implicated in hyperglycemia-induced pancreatic β-cell death (Qian et al., 2008). The

mechanism of this effect however is unknown. It appears that prolonged expression of

the mutant insulin created chronic induction of the UPR pathways, which ultimately

leads to prolonged CHOP and TRB3 expression. Whether TRB3 is responsible for

apoptosis induction and how much of the apoptosis is TRB3-depenent in this model

system requires future study.

Despite the abundant up-regulation of CHOP and TRB3 in response to mutant

insulin expression, the level of apoptotic cells in the population remained rather low,

even after long-term expression of the mutant construct. This is likely because one of

the main cell protective effects induced by the UPR, ERAD, is also up-regulated.

Inhibition of ERAD by inhibiting the cytosolic proteasome sensitizes the cells to

apoptosis, supporting the notion that the ERAD pathway may support cell survival by

the continuous degradation of misfolded insulin. Although, autophagy has been

potentially associated with the ER stress response and the degradation of ER

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components (Hartley et al., 2009), this pathway does not appear to be activated in cells

expressing mutant insulin. However, future studies are required to determine if

autophagy contributes to mutant insulin degradation in this cell line.

4.4 Summary and Future directions

In summary, we have developed a model β-cell line that allows for

pathophysiological ER stress induction based on the Akita mouse. This mouse strain

expresses a mutant insulin 2 gene (C96Y), which prevents normal proinsulin folding

causing ER stress and eventual β-cell apoptosis. We developed a double-stable

pancreatic β-cell line (pTet-ON INS-1) with inducible expression of insulin 2(C96Y)

fused to EGFP. Expression of the mutant insulin resulted in activation of the ER stress

pathways (PERK, IRE1 and ATF6) and caused dilation of the ER. To identify gene

expression changes resulting from mutant insulin expression we performed microarray

expression profiling and real time PCR experiments. We observed an induction of ER

chaperone and ERAD genes after 24 h and a large increase in pro-apoptotic genes

(CHOP and TRB3) following 48 h of mutant insulin expression. The latter changes

occurred at a time when general apoptosis was detected in the cell population, although

the relative amount of cell death was low. Inhibiting the proteasome during expression

of the mutant insulin significantly increased the levels of apoptotic cells, indicating that

the ERAD pathway is protecting the cells by maintaining degradation of the mutant

insulin.

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The β-cell model of ER stress described in this study has allowed for a detailed

characterization of the ER stress response induced by misfolded insulin expression and

to identify both cell protective and possible cell destructive genes. It will be important

to next conduct the molecular characterization of the function of these genes where

limited or no mechanistic information currently exists. In particular, this system may

allow for a detailed characterization of how ER stress induces apoptosis and the

mechanism by which the misfolded mutant insulin is degraded by the ERAD pathway.

Projects have already begun in the Volchuk lab examining the role of a few of

these genes. Homocysteine-inducible ER stress Protein (HERP) is an ER stress-

inducible protein that has been implicated in maintenance of ER Ca2+ homeostasis

(Chigurupati et al., 2009) and ERAD (Kim et al., 2008). We hypothesize that HERP

also plays a role in mutant insulin degradation and that the overexpression of HERP

will help protect clone #4S2 from ER stress associated with mutant insulin expression.

Preliminary studies have already begun including the production of a HERP-expressing

adenovirus. Knockdown of HERP results in accumulation of mutant insulin suggesting

that it does play a role in mutant insulin degradation. Knockdown of HERP also causes

increased susceptibility of clone cells to mutant insulin expression.

Plans are also under way to study the role of TRB3 in ER stress. As mentioned

in the discussion, TRB3 is induced by the PERK-ATF4-CHOP pathway and is thought

to regulate CHOP (Hegedus et al., 2007; Ohoka et al., 2005), however its mechanism is

still not understood. Similar to the studies in HERP, it would be interesting to delineate

the role of TRB3 in the ER-stress induced apoptosis by performing overexpression and

knockdown experiments in cell culture models of beta-cells. We hypothesize that TRB3

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plays an integral role in ER stress-dependent cell death and that its overexpression will

render beta cells more susceptible to ER stress, while its knockdown will result in

increased cell survival.

In addition, the gene encoding a little-known protein, stromal-derived factor 2-

like 1 (SDF2L1), was also induced with mutant insulin expression. This amino acid

sequence of SDF2L1 bears similarity to the central hydrophilic part of protein O-

mannosyltransferase (Pmt) proteins of Saccharomyces cerevisiae, as well as their

human homologues, POMT1 and POMT2 (Fukuda et al., 2001). Given the abundant

induction of SDF2L1 expression in our model system of ER stress and the limited

information available, I decided to examine the role of SDF2L1 in ER stress, ER stress-

induced apoptosis and insulin biosynthesis. I hypothesize that SDF2L1 is an essential

component of the ER stress response responsible for assisting in either protein folding

or potentially ER-associated degradation. The preliminary data examining this

hypothesis is presented in Appendix 2.

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APPENDIX 1: MICROARRAY RESULTS FROM THE ANALYSIS OF THE ER STRESS RESPONSE IN CLONE #4S2

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This appendix provides the results from the microarray analysis conducted in

chapter 4. The first set of tables (A1-A3) present all of the Affymetrix gene probes

whose expression increased or decreased by at least 2 fold between doxycycline-treated

vs. control, untreated INS-1 Clone #4S2 cells. Data from three independent

experiments for three doxycycline treatment time points (24 h, 48 h, 5 days) is shown.

The gene probe descriptions are provided and available by the GeneSpring software.

The bold font indicates probes whose expression was changed in all three experiments,

while the regular font indicates genes that were changed in at least 2 of the three

independent experiments.

The final table (A4) presents expression data for well substantiated genes

derived from the data presented in Tables S1-3. This selected table lists the putative

functions of the genes derived from the NCBI database. Data from three independent

experiments for all doxycyline treatment time points (24h, 48h and 5 days) is shown.

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Table A1. Up- and down-regulated genes (24 h)

Up-Regulated Genes (24h)

Fold Change

Probe ID N=1 N=2 N=3 Avg Description 1378133_at 17.09 11.73 14.41 Transcribed locus

1386321_s_at 12.63 15.63 14.13

EST105188 Rat PC-12 cells, untreated Rattus norvegicus cDNA clone RPCAG66 3' end, mRNA sequence.

1370694_at 9.023 14.9 11.96 tribbles homolog 3 (Drosophila) 1370695_s_at 11.55 10.4 10.98 tribbles homolog 3 (Drosophila) 1393018_at 5.483 10.9 8.19 Transcribed locus

1389573_at 6.436 9.549 7.99Similar to RIKEN cDNA 1810008K03 (predicted)

1383434_at 6.749 7.527 7.14

Transcribed locus, strongly similar to NP_115866.1 mitochondrial ribosomal protein L41 [Homo sapiens]

1373043_at 7.262 4.654 5.088 5.67Stromal cell-derived factor 2-like 1 (predicted)

1376958_at 3.592 6.363 4.98Similar to serine (or cysteine) proteinase inhibitor, clade B, member 9

1383661_at 3.087 4.585 3.84 Transcribed locus 1375088_at 3.61 3.885 3.75 Transcribed locus

1377016_at 4.245 3.059 3.578 3.63Similar to RIKEN cDNA 5730592L21 (predicted)

1379785_at 3.291 3.511 3.40 Transcribed locus

1367741_at 2.206 3.361 4.266 3.28

homocysteine-inducible, endoplasmic reticulum stress-inducible, ubiquitin-like domain member 1

1387212_at 2.847 2.996 2.92muscle, intestine and stomach expression 1

1372653_at 2.822 2.72 3.05 2.86 FK506 binding protein 11 (predicted)

1392541_at 2.82 2.722 2.926 2.82Similar to RIKEN cDNA A030007L17; EST AA673177 (predicted)

1372352_at 2.875 2.741 2.677 2.76Arginine-rich, mutated in early stage tumors (predicted)

1376284_at 2.448 2.962 2.71Similar to transcriptional intermediary factor 1 delta

1392955_at 2.566 2.842 2.70Sel1 (suppressor of lin-12) 1 homolog (C. elegans)

1367624_at 2.447 2.955 2.70 activating transcription factor 4 1372665_at 2.303 3.071 2.69 Phosphoserine aminotransferase 1 1376121_at 2.641 2.637 2.64 PHD finger protein 10 (predicted) 1376178_at 2.209 3.04 2.502 2.58 DNA-damage inducible transcript 3 1375388_at 2.364 2.794 2.58 Glucose regulated protein, 58 kDa

1382232_at 2.481 2.64 2.56Glutamic pyruvate transaminase (alanine aminotransferase) 2 (predicted)

1389660_at 2.121 2.958 2.54 Amphoterin induced gene and ORF 3

1387116_at 2.417 2.602 2.556 2.53DnaJ (Hsp40) homolog, subfamily B, member 9

1369590_a_at 2.038 2.917 2.48 DNA-damage inducible transcript 3

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1383978_at 2.266 2.307 2.847 2.47 Huntingtin interactor protein E

1376073_at 2.387 2.498 2.44Sel1 (suppressor of lin-12) 1 homolog (C. elegans)

1393961_at 2.075 2.414 2.706 2.40 Huntingtin interactor protein E 1372601_at 2.086 2.708 2.40 Activating transcription factor 5 1376845_at 2.044 2.701 2.37 Putative ISG12(b) protein 1367847_at 2.256 2.466 2.36 nuclear protein 1

1372808_at 2.153 2.562 2.36

Similar to methylenetetrahydrofolate dehydrogenase (NAD) (EC 1.5.1.15) / methenyltetrahydrofolate cyclohydrolase (EC 3.5.4.9) precursor – mouse

1376098_a_at 2.083 2.234 2.627 2.31 Myosin IG (predicted)

1373313_at 2.213 2.351 2.28Sel1 (suppressor of lin-12) 1 homolog (C. elegans)

1370073_at 2.326 2.273 2.221 2.27 protein kinase inhibitor p58 1388942_at 2.278 2.19 2.23 Transcribed locus

1389308_at 2.053 2.414 2.23DnaJ (Hsp40) homolog, subfamily B, member 11 (predicted)

1392616_at 2.322 2.023 2.17

UI-R-Y0-ve-h-04-0-UI.s1 UI-R-Y0 Rattus norvegicus cDNA clone UI-R-Y0-ve-h-04-0-UI 3', mRNA sequence.

1392920_at 2.181 2.027 2.091 2.10Elongation factor RNA polymerase II-like 3 (predicted)

1389422_at 2.072 2.117 2.09 Transcribed locus

1375637_at 2.069 2.11 2.09Similar to RIKEN cDNA 1110003E01 (predicted)

1369868_at 2.075 2.105 2.037 2.07 implantation-associated protein

1373079_at 2.093 2.03 2.06

Transcribed locus, weakly similar to XP_342574.1 PREDICTED: similar to Csr1 [Rattus norvegicus]

1372870_at 2.089 2.015 2.05

KDEL (Lys-Asp-Glu-Leu) endoplasmic reticulum protein retention receptor 3 (predicted)

1367729_at 2.003 2 2.00 ornithine aminotransferase Down-Regulated Genes (24h)

Fold

Change Probe ID N=1 N=2 N=3 Avg Description 1368607_at 0.481 0.488 0.48 cytochrome P450, 4a12 1393559_at 0.464 0.464 0.46 Transcribed locus 1377404_at 0.448 0.462 0.46 Stanniocalcin 1 1396101_at 0.432 0.426 0.43 Stanniocalcin 1 1386530_at 0.383 0.442 0.41 Transcribed locus 1369888_at 0.384 0.382 0.38 glucagon 1387623_at 0.368 0.362 0.37 stanniocalcin 1

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Table A2. Up- and down-regulated genes (48 h)

Up-Regulated Genes (48h)

Fold Change

Probe ID N=1 N=2 N=3 Avg Description 1370694_at 20.59 15.47 26.74 20.93 tribbles homolog 3 (Drosophila) 1370695_s_at 25.27 17.87 12.57 18.57 tribbles homolog 3 (Drosophila) 1378133_at 22.43 16.61 15.17 18.07 Transcribed locus

1386321_s_at 17.28 18.11 10.99 15.46

EST105188 Rat PC-12 cells, untreated Rattus norvegicus cDNA clone RPCAG66 3' end, mRNA sequence.

1393018_at 11.64 13.81 13.28 12.91 Transcribed locus

1383434_at 9.899 10.32 14.58 11.60

Transcribed locus, strongly similar to NP_115866.1 mitochondrial ribosomal protein L41 [Homo sapiens]

1376958_at 6.115 9.632 10.38 8.71Similar to serine (or cysteine) proteinase inhibitor, clade B, member 9

1389573_at 8.712 9.455 6.978 8.38Similar to RIKEN cDNA 1810008K03 (predicted)

1376845_at 4.331 5.674 5.568 5.19 Putative ISG12(b) protein

1373043_at 4.167 4.543 5.291 4.67Stromal cell-derived factor 2-like 1 (predicted)

1367741_at 3.653 5.626 3.701 4.33

homocysteine-inducible, endoplasmic reticulum stress-inducible, ubiquitin-like domain member 1

1375088_at 4.016 5.158 3.648 4.27 Transcribed locus 1372653_at 3.524 4.09 4.092 3.90 FK506 binding protein 11 (predicted)

1377016_at 3.44 3.82 3.645 3.64Similar to RIKEN cDNA 5730592L21 (predicted)

1372665_at 3.448 3.259 3.903 3.54 Phosphoserine aminotransferase 1 1369590_a_at 3.325 3.453 3.599 3.46 DNA-damage inducible transcript 3 1372601_at 3.68 3.063 3.07 3.27 Activating transcription factor 5 1379785_at 3.037 2.895 3.607 3.18 Transcribed locus

1387212_at 3.256 3.472 2.8 3.18muscle, intestine and stomach expression 1

1375388_at 3.436 2.867 3.15 Glucose regulated protein, 58 kDa 1370007_at 2.919 3.391 3.112 3.14 protein disulfide isomerase associated 4

1392541_at 3.292 2.988 3.092 3.12Similar to RIKEN cDNA A030007L17; EST AA673177 (predicted)

1367847_at 2.791 3.366 3.1 3.09 nuclear protein 1

1392798_at 2.79 3.306 3.151 3.08Protein disulfide isomerase, pancreatic (predicted)

1372808_at 3.155 2.884 3.149 3.06

Similar to methylenetetrahydrofolate dehydrogenase (NAD) (EC 1.5.1.15) / methenyltetrahydrofolate cyclohydrolase (EC 3.5.4.9) precursor - mouse

1383661_at 3.229 2.668 3.131 3.01 Transcribed locus 1367624_at 3 2.949 3.064 3.00 activating transcription factor 4

1387116_at 2.74 3.492 2.745 2.99DnaJ (Hsp40) homolog, subfamily B, member 9

116

1388942_at 3.216 2.852 2.803 2.96 Transcribed locus

1392955_at 3.159 2.73 2.957 2.95Sel1 (suppressor of lin-12) 1 homolog (C. elegans)

1376284_at 3.39 2.334 3.119 2.95Similar to transcriptional intermediary factor 1 delta

1373787_at 3.268 2.256 3.284 2.94Solute carrier family 6 (neurotransmitter transporter, glycine), member 9

1376178_at 3.273 2.525 2.90 DNA-damage inducible transcript 3

1382232_at 3.011 2.37 3.297 2.89Glutamic pyruvate transaminase (alanine aminotransferase) 2 (predicted)

1372870_at 2.33 3.091 3.248 2.89

KDEL (Lys-Asp-Glu-Leu) endoplasmic reticulum protein retention receptor 3 (predicted)

1376098_a_at 2.609 3.228 2.821 2.89 Myosin IG (predicted) 1383978_at 2.438 3.204 2.694 2.78 Huntingtin interactor protein E

1373313_at 2.714 2.78 2.819 2.77Sel1 (suppressor of lin-12) 1 homolog (C. elegans)

1372352_at 2.723 2.908 2.647 2.76Arginine-rich, mutated in early stage tumors (predicted)

1370073_at 2.718 2.74 2.807 2.76 protein kinase inhibitor p58

1371818_at 2.779 2.426 2.847 2.68Exportin, tRNA (nuclear export receptor for tRNAs) (predicted)

1393961_at 2.662 2.765 2.589 2.67 Huntingtin interactor protein E

1381749_at 2.712 2.592 2.66 2.65

Transcribed locus, weakly similar to NP_001002778.1 hypothetical protein LOC442814 [Mus musculus]

1368391_at 2.687 2.504 2.636 2.61solute carrier family 7 (cationic amino acid transporter, y+ system), member 1

1393799_at 2.623 2.41 2.52 Unc-5 homolog B (C. elegans) 1379097_at 2.822 2.274 2.364 2.49 Transcribed locus 1375964_at 2.28 2.69 2.435 2.47 Phosphoserine phosphatase (predicted)

1376073_at 2.229 2.401 2.654 2.43Sel1 (suppressor of lin-12) 1 homolog (C. elegans)

1392616_at 2.288 2.555 2.42

UI-R-Y0-ve-h-04-0-UI.s1 UI-R-Y0 Rattus norvegicus cDNA clone UI-R-Y0-ve-h-04-0-UI 3', mRNA sequence.

1389308_at 2.184 2.65 2.408 2.41DnaJ (Hsp40) homolog, subfamily B, member 11 (predicted)

1376281_at 2.694 2.069 2.38 Similar to hypothetical protein FLJ22349

1393983_at 2.534 2.125 2.472 2.38Exportin, tRNA (nuclear export receptor for tRNAs) (predicted)

1388628_at 2.147 2.536 2.419 2.37 Integral type I protein 1389422_at 2.467 2.322 2.278 2.36 Transcribed locus 1373160_at 2.092 2.453 2.487 2.34 Similar to HTPAP protein 1369868_at 2.264 2.416 2.34 implantation-associated protein 1368622_at 2.466 2.21 2.34 fructose-1,6-bisphosphatase 2 1372602_at 2.068 2.821 2.084 2.32 Similar to genethonin 1 (predicted) 1367729_at 2.055 2.533 2.301 2.30 ornithine aminotransferase 1374746_at 2.517 2.076 2.283 2.29 Ab1-152

1368392_at 2.505 2.172 2.179 2.29Solute carrier family 7 (cationic amino acid transporter, y+ system), member 1

1371735_at 2.423 2.128 2.28

Transcribed locus, strongly similar to XP_579758.1 PREDICTED: hypothetical protein XP_579758 [Rattus norvegicus]

117

1383401_at 2.344 2.31 2.121 2.26 Similar to Testis derived transcript 1388395_at 2.112 2.313 2.317 2.25 G0/G1 switch gene 2 (predicted)

1391451_at 2.274 2.216 2.25Phosphoenolpyruvate carboxykinase 2 (mitochondrial) (predicted)

1373079_at 2.383 2.087 2.258 2.24

Transcribed locus, weakly similar to XP_342574.1 PREDICTED: similar to Csr1 [Rattus norvegicus]

1389660_at 2.595 2.036 2.083 2.24 Amphoterin induced gene and ORF 3

1373418_at 2.334 2.14 2.24Glutamyl-prolyl-tRNA synthetase (predicted)

1398879_at 2.227 2.24 2.23 Similar to hypothetical protein MGC8721 1374034_at 2.202 2.261 2.23 Cysteinyl-tRNA synthetase (predicted)

1375637_at 2.277 2.165 2.22Similar to RIKEN cDNA 1110003E01 (predicted)

1376121_at 2.368 2.052 2.21 PHD finger protein 10 (predicted) 1387915_at 2.066 2.339 2.216 2.21 Ratsg2 1389733_at 2.181 2.025 2.398 2.20 Methionine-tRNA synthetase (predicted)

1368308_at 2.322 2.171 2.094 2.20myelocytomatosis viral oncogene homolog (avian)

1373374_at 2.004 2.172 2.383 2.19 LIM domain only 4 (predicted)

1392920_at 2.243 2.258 2.013 2.17Elongation factor RNA polymerase II-like 3 (predicted)

1395363_at 2.144 2.163 2.15 Methionine-tRNA synthetase (predicted)

1388521_at 2.152 2.149 2.15

Pyrroline-5-carboxylate synthetase (glutamate gamma-semialdehyde synthetase) (predicted)

1376418_a_at 2.16 2.092 2.13 Isoleucine-tRNA synthetase (predicted)

1379812_at 2.156 2.085 2.12Nicotinamide N-methyltransferase (predicted)

1385110_at 2.235 2.001 2.12Similar to RIKEN cDNA 1110003E01 (predicted)

1375877_at 2.126 2.08 2.10 Synaptotagmin 4

1394435_at 2.098 2.107 2.10Vang, van gogh-like 1 (Drosophila) (predicted)

1372704_at 2.108 2.042 2.124 2.09 Similar to RIKEN cDNA 2310008M10 1389409_at 2.111 2.022 2.11 2.08 Similar to Testis derived transcript

1379910_at 2.024 2.132 2.08

Transcribed locus, strongly similar to XP_222863.3 PREDICTED: similar to UDP-N-acteylglucosamine pyrophosphorylase 1 homolog [Rattus norvegicus]

1393364_at 2.043 2.105 2.07 Cation-chloride cotransporter 9 1375441_at 2.127 2.006 2.07 Seryl-aminoacyl-tRNA synthetase 1

1388695_at 2.034 2.099 2.07Serine hydroxymethyl transferase 2 (mitochondrial) (predicted)

1389439_at 2.093 2.01 2.05 Transcribed locus 1376754_at 2.052 2.041 2.05 Cysteinyl-tRNA synthetase (predicted) 1385706_at 2.02 2.02 2.02 Similar to Testis derived transcript Down-Regulated Genes (48h) Fold

118

Change Probe ID N=1 N=2 N=3 Avg Description 1385491_at 0.481 0.468 0.47 Similar to KIAA1183 protein 1393109_at 0.425 0.498 0.48 0.47 CDNA clone IMAGE:7302574 1368641_at 0.467 0.468 0.465 0.47 wingless-related MMTV integration site 4

1368559_at 0.464 0.468 0.47proprotein convertase subtilisin/kexin type 1

1371541_at 0.484 0.445 0.46 Myosin, light polypeptide kinase (predicted) 1368902_at 0.461 0.466 0.46 p21 (CDKN1A)-activated kinase 3 1378927_at 0.492 0.439 0.449 0.46 Transcribed locus

1387698_at 0.458 0.466 0.455 0.46potassium inwardly rectifying channel, subfamily J, member 11

1382989_at 0.428 0.488 0.46

Transcribed locus, strongly similar to NP_082821.1 hypothetical protein LOC73458 [Mus musculus]

1374432_at 0.433 0.477 0.46 Activated leukocyte cell adhesion molecule 1394475_at 0.494 0.425 0.443 0.45 Transcribed locus 1368514_at 0.453 0.451 0.458 0.45 monoamine oxidase B 1398431_at 0.462 0.475 0.423 0.45 Carbonic anhydrase 8 (predicted) 1394973_at 0.427 0.476 0.45 Phosphodiesterase 1C 1377659_at 0.413 0.487 0.45 Myeloid leukemia factor 1 (predicted) 1378315_at 0.445 0.489 0.399 0.44 Transcribed locus

1369782_a_at 0.407 0.462 0.452 0.44potassium inwardly rectifying channel, subfamily J, member 11

1368607_at 0.401 0.423 0.486 0.44 cytochrome P450, 4a12 1391727_at 0.404 0.465 0.43 Transcribed locus 1384460_at 0.422 0.433 0.437 0.43 Transcribed locus 1384587_at 0.387 0.408 0.473 0.42 Transcribed locus 1370234_at 0.428 0.384 0.43 0.41 Fibronectin 1 1383798_at 0.364 0.488 0.384 0.41 Similar to CDNA sequence BC026682 1382294_at 0.387 0.42 0.40 Activated leukocyte cell adhesion molecule 1370781_a_at 0.44 0.362 0.40 Kv channel-interacting protein 1 1378496_at 0.422 0.378 0.40 Transcribed locus 1390530_at 0.399 0.368 0.383 0.38 Transcribed locus 1368854_at 0.39 0.407 0.341 0.38 Visinin-like 1 1368853_at 0.342 0.449 0.347 0.38 visinin-like 1 1393894_at 0.393 0.35 0.37 Cytochrome P450, 4a12 1376398_at 0.279 0.408 0.398 0.36 CDNA clone IMAGE:7302574 1370750_a_at 0.349 0.366 0.364 0.36 interleukin 1 receptor, type I 1369457_a_at 0.249 0.302 0.328 0.29 synaptotagmin-like 4 1393559_at 0.297 0.273 0.277 0.28 Transcribed locus 1377404_at 0.261 0.266 0.315 0.28 Stanniocalcin 1 1386530_at 0.307 0.226 0.259 0.26 Transcribed locus 1396101_at 0.261 0.238 0.278 0.26 Stanniocalcin 1 1387623_at 0.204 0.257 0.222 0.23 stanniocalcin 1 1369888_at 0.125 0.155 0.155 0.15 glucagon

119

Table A3. Up- and down-regulated genes (5 d)

Up-Regulated Genes (5d) Fold Change Probe ID N=1 N=2 N=3 Avg Description

1373043_at 12.41 16.22 4.089 10.91Stromal cell-derived factor 2-like 1 (predicted)

1377016_at 5.943 12.49 2.47 6.97Similar to RIKEN cDNA 5730592L21 (predicted)

1370694_at 4.375 10.63 7.50 tribbles homolog 3 (Drosophila) 1370695_s_at 4.23 7.409 5.82 tribbles homolog 3 (Drosophila)

1383434_at 4.828 6.698 5.76

Transcribed locus, strongly similar to NP_115866.1 mitochondrial ribosomal protein L41 [Homo sapiens]

1392541_at 5.432 6.574 2.484 4.83Similar to RIKEN cDNA A030007L17; EST AA673177 (predicted)

1389573_at 2.533 6.393 4.46Similar to RIKEN cDNA 1810008K03 (predicted)

1372653_at 5.73 3.997 3.067 4.26 FK506 binding protein 11 (predicted) 1370073_at 4.72 5.582 2.305 4.20 protein kinase inhibitor p58 1376845_at 3.523 4.785 4.15 Putative ISG12(b) protein 1388942_at 3.705 5.692 2.787 4.06 Transcribed locus 1389422_at 2.962 6.791 2.34 4.03 Transcribed locus

1372352_at 4.628 4.436 2.619 3.89Arginine-rich, mutated in early stage tumors (predicted)

1372870_at 3.891 3.785 3.84

KDEL (Lys-Asp-Glu-Leu) endoplasmic reticulum protein retention receptor 3 (predicted)

1373676_at 3.137 5.91 2.282 3.78

UI-R-AF1-aas-f-08-0-UI.s1 UI-R-AF1 Rattus norvegicus cDNA clone UI-R-AF1-aas-f-08-0-UI 3', mRNA sequence.

1387212_at 5.101 2.228 3.66muscle, intestine and stomach expression 1

1392920_at 2.271 5.005 3.64Elongation factor RNA polymerase II-like 3 (predicted)

1367741_at 3.14 3.954 3.55

homocysteine-inducible, endoplasmic reticulum stress-inducible, ubiquitin-like domain member 1

1368593_at 4.201 2.716 3.46 CD1d1 antigen 1368896_at 4.142 2.768 3.46 MAD homolog 7 (Drosophila) 1383978_at 3.487 4.46 2.3 3.42 Huntingtin interactor protein E 1376319_at 4.61 2.075 3.34 Transcribed locus

1379910_at 2.101 4.519 3.31

Transcribed locus, strongly similar to XP_222863.3 PREDICTED: similar to UDP-N-acteylglucosamine pyrophosphorylase 1 homolog [Rattus norvegicus]

1382944_at 3.417 3.059 3.24 Transcribed locus 1375388_at 3.287 3.182 3.23 Glucose regulated protein, 58 kDa

1387116_at 3.466 2.834 3.084 3.13DnaJ (Hsp40) homolog, subfamily B, member 9

1370007_at 3.06 3.651 2.661 3.12 protein disulfide isomerase associated 4

120

1379097_at 2.119 5.174 2.105 3.13 Transcribed locus 1370859_at 3.403 2.665 3.03 Thioredoxin domain containing 7 1368762_at 3.603 2.326 2.96 ubiquitin D

1389308_at 2.861 3.902 2.117 2.96DnaJ (Hsp40) homolog, subfamily B, member 11 (predicted)

1376284_at 2.321 3.588 2.95Similar to transcriptional intermediary factor 1 delta

1367627_at 3.636 2.201 2.92glycine amidinotransferase (L-arginine:glycine amidinotransferase)

1392955_at 3.193 2.636 2.91Sel1 (suppressor of lin-12) 1 homolog (C. elegans)

1370197_a_at 3.351 2.407 2.88 Protein kinase C, zeta 1367847_at 3.068 2.626 2.85 nuclear protein 1

1390250_x_at 2.073 3.604 2.84Atpase, class I, type 8B, member 2 (predicted)

1367729_at 2.342 3.844 2.191 2.79 ornithine aminotransferase 1388628_at 2.832 3.374 2.166 2.79 Integral type I protein 1393961_at 2.92 3.217 2.191 2.78 Huntingtin interactor protein E

1392798_at 2.573 2.796 2.778 2.72Protein disulfide isomerase, pancreatic (predicted)

1392616_at 2.66 2.949 2.486 2.70

UI-R-Y0-ve-h-04-0-UI.s1 UI-R-Y0 Rattus norvegicus cDNA clone UI-R-Y0-ve-h-04-0-UI 3', mRNA sequence.

1369590_a_at 3.158 2.219 2.69 DNA-damage inducible transcript 3 1376178_at 3.222 2.1 2.66 DNA-damage inducible transcript 3 1392317_at 2.216 3.035 2.63 Transcribed locus 1370283_at 3.186 2.612 2.034 2.61 heat shock 70kD protein 5

1372013_at 3.065 2.12 2.59Interferon induced transmembrane protein 1 (predicted)

1392701_at 2.671 2.507 2.59Similar to GDP-mannose pyrophosphorylase B

1376098_a_at 2.886 2.201 2.54 Myosin IG (predicted)

1389218_at 2.137 2.938 2.54UDP-glucose ceramide glucosyltransferase-like 1

1373313_at 2.555 2.454 2.50Sel1 (suppressor of lin-12) 1 homolog (C. elegans)

1393713_at 2.066 2.885 2.48 Similar to GDP-mannose 4, 6-dehydratase

1373079_at 2.552 2.385 2.47

Transcribed locus, weakly similar to XP_342574.1 PREDICTED: similar to Csr1 [Rattus norvegicus]

1386946_at 2.351 2.575 2.46 carnitine palmitoyltransferase 1, liver 1369868_at 3.01 2.096 2.233 2.45 implantation-associated protein

1377346_at 2.365 2.457 2.41

Transcribed locus, moderately similar to NP_001007591.1 hypothetical protein LOC433886 [Mus musculus]

1376073_at 2.613 2.238 2.43Sel1 (suppressor of lin-12) 1 homolog (C. elegans)

1377633_a_at 2.163 2.609 2.39 LOC500719

1372034_at 2.265 2.432 2.35Similar to hypothetical protein MGC29390 (predicted)

1371579_at 2.067 2.593 2.33Clone UI-R-FJ0-cpu-m-15-0-UI unknown mRNA

1379680_at 2.243 2.364 2.30 Transcribed locus

121

1388857_at 2.027 2.57 2.30 SEC23B (S. cerevisiae) (predicted) 1374185_at 2.368 2.163 2.27 Stannin 1370817_at 2.263 2.261 2.26 Sec11-like 3 (S. cerevisiae) 1372704_at 2.521 2.084 2.084 2.23 Similar to RIKEN cDNA 2310008M10 1373160_at 2.418 2.018 2.22 Similar to HTPAP protein

1376712_at 2.063 2.345 2.20Thioredoxin domain containing 4 (endoplasmic reticulum) (predicted)

1387205_at 2.148 2.142 2.15 RT1 class Ib, locus M3

1388981_at 2.004 2.204 2.10Similar to ADP-ribosylation factor GTPase-activating protein 3 (ARF GAP 3)

1382040_at 2.093 2.099 2.10Glutamyl-prolyl-tRNA synthetase (predicted)

1393643_at 2.057 2.126 2.09 Reticulocalbin (predicted)

1372298_at 2.039 2.03 2.03Thioredoxin domain containing 4 (endoplasmic reticulum) (predicted)

Down-Regulated Genes (5d) Fold Change Probe ID N=1 N=2 N=3 Avg Description 1369792_at 0.488 0.48 0.48 G protein-coupled receptor 6 1367593_at 0.48 0.437 0.46 selenoprotein W, muscle 1 1393516_at 0.48 0.436 0.46 Transcribed locus 1397214_at 0.379 0.496 0.44 Transcribed locus

1373636_at 0.453 0.416 0.43Sparc/osteonectin, cwcv and kazal-like domains proteoglycan 1 (predicted)

1393482_at 0.454 0.399 0.43 Transcribed locus 1391541_at 0.454 0.397 0.43 Transcribed locus 1368840_at 0.432 0.398 0.42 LR8 protein

1369949_at 0.493 0.293 0.39Lutheran blood group (Auberger b antigen included)

1368854_at 0.445 0.341 0.39 Visinin-like 1 1392492_at 0.339 0.446 0.39 Transcribed locus 1393733_at 0.299 0.469 0.38 Transcribed locus 1368483_a_at 0.308 0.442 0.38 slit homolog 1 (Drosophila)

1391007_s_at 0.326 0.42 0.37Potassium inwardly rectifying channel, subfamily J, member 11

1368902_at 0.404 0.338 0.37 p21 (CDKN1A)-activated kinase 3 1394097_at 0.331 0.386 0.36 Transcribed locus 1368123_at 0.267 0.448 0.36 insulin-like growth factor 1 receptor 1375958_at 0.244 0.465 0.35 Similar to Hypothetical protein MGC28888 1394475_at 0.389 0.306 0.35 Transcribed locus

1390263_at 0.372 0.315 0.34

Transcribed locus, weakly similar to NP_002428.1 MpV17 transgene, murine homolog, glomerulosclerosis; Mpv17, human homolog of glomerulosclerosis and nephrotic syndrome [Homo sapiens]

1394422_at 0.184 0.497 0.34 Similar to hypothetical protein FLJ23033 1393559_at 0.418 0.359 0.241 0.34 Transcribed locus 1368607_at 0.368 0.31 0.34 cytochrome P450, 4a12

1387698_at 0.489 0.158 0.369 0.34potassium inwardly rectifying channel, subfamily J, member 11

1375469_at 0.208 0.467 0.34 SWI/SNF related, matrix associated, actin

122

dependent regulator of chromatin, subfamily a, member 4

1375199_at 0.188 0.484 0.34 Transcribed locus 1378927_at 0.341 0.327 0.33 Transcribed locus 1384460_at 0.425 0.243 0.33 Transcribed locus 1393109_at 0.381 0.269 0.33 CDNA clone IMAGE:7302574

1396252_at 0.194 0.442 0.32

Transcribed locus, strongly similar to XP_533245.2 PREDICTED: similar to vascular endothelial growth factor B [Canis familiaris]

1370781_a_at 0.229 0.391 0.31 Kv channel-interacting protein 1 1383798_at 0.308 0.305 0.31 Similar to CDNA sequence BC026682 1391079_at 0.134 0.471 0.30 Transcribed locus 1378315_at 0.396 0.208 0.30 Transcribed locus 1375723_at 0.102 0.495 0.30 Transcribed locus

1387155_at 0.224 0.364 0.29proprotein convertase subtilisin/kexin type 2

1371020_at 0.090 0.475 0.28 RIM binding protein 2

1382064_at 0.209 0.355 0.28Similar to 4933407C03Rik protein (predicted)

1370234_at 0.429 0.248 0.167 0.28 Fibronectin 1 1398289_a_at 0.132 0.428 0.28 corticotropin releasing hormone receptor 1 1384587_at 0.276 0.283 0.28 Transcribed locus 1382989_at 0.162 0.393 0.28 corticotropin releasing hormone receptor 1 1393555_at 0.313 0.238 0.28 Heat shock 90kDa protein 1, beta 1368641_at 0.471 0.093 0.261 0.28 wingless-related MMTV integration site 4 1377404_at 0.499 0.117 0.197 0.27 Stanniocalcin 1 1390436_at 0.11 0.424 0.27 Autophagy 7-like (S. cerevisiae) (predicted) 1391843_at 0.132 0.395 0.26 Similar to elongation protein 4 homolog 1370750_a_at 0.042 0.481 0.26 interleukin 1 receptor, type I 1396101_at 0.488 0.068 0.221 0.26 Stanniocalcin 1

1368778_at 0.077 0.431 0.25solute carrier family 6 (neurotransmitter transporter, taurine), member 6

1389868_at 0.080 0.424 0.25 Similar to RCK 1387623_at 0.464 0.075 0.186 0.24 stanniocalcin 1

1378904_at 0.062 0.405 0.23

Transcribed locus, strongly similar to NP_766449.1 hypothetical protein LOC241919 [Mus musculus]

1369782_a_at 0.038 0.428 0.23potassium inwardly rectifying channel, subfamily J, member 11

1389986_at 0.019 0.383 0.20 LOC499304 1376398_at 0.198 0.194 0.20 CDNA clone IMAGE:7302574 1369888_at 0.13 0.151 0.14 glucagon 1369457_a_at 0.102 0.155 0.13 synaptotagmin-like 4

123

Table A4. Genes Induced >2-fold by Ins2(C96Y) Expression (5 day) (N=2-3)

Gene Name Entrez Affymetrix Function Fold Change Gene ID Probe ID N=1 N=2 N=3 Protein modification/ folding Sdf2l1 680945 1373043_at O-mannosylation? 12.41 16.22 4.089 Fkbp11 300211 1372653_at Peptidyl-prolyl isomerase 5.73 3.997 3.067 Dnajc3/ p58IPK 63880 1370073_at ER Protein folding 4.72 5.582 2.305 Dnajb9/ ERdj4 24908 1387116_at ER Protein folding 3.466 2.834 3.084 Dnajb11/ ERdj3 360734 1389308_at ER Protein folding 2.861 3.902 2.117 Pdia2 287164 1392798_at PDI family, isomerase 2.573 2.796 2.778 Hspa5/ GRP78 25617 1370283_at ER Protein folding 3.186 2.612 2.034 Pdia3/ERp57 29468 1375388_at PDI family, isomerase 3.287 3.182 Pdia4/ ERp70 116598 1370007_at PDI family, isomerase 3.06 3.651 2.661 Pdia6/ P5 286906 1370859_at PDI family, isomerase 3.403 2.665 Txndc4/ ERp44 298066 1372298_at PDI family, isomerase 2.039 2.03 ER stress-inducible Herp 85430 1367741_at ERAD 3.14 3.954 Sel1h 314352 1392955_at ERAD 3.193 2.636 1376073_at 2.613 2.238 1373313_at 2.555 2.454 CHOP/ GADD153 29467 1369590_a_at Transcription factor 3.158 2.219 TRB3/ Trib3 246273 1370694_at 4.375 10.63 1370695_s_at 4.23 7.409 Other Transcription factors Mist1 25334 1387212_at Transcription factor 5.101 2.228 Protein transport Tmed3 300888 1388628_at protein transport 2.832 3.374 2.166 Kdelr3 315131 1372870_at Vesicle transport 3.891 3.785 Sec23b 362226 1388857_at protein transport 2.027 2.57 ARF GAP3 503165 1388981_at protein transport 2.004 2.204 Others: Creld2 362978 1377016_at ER Protein folding? 5.943 12.49 2.47 Armet 315989 1372352_at 4.628 4.436 2.619 Oat 64313 1367729_at Ornithine aminotransferase 2.342 3.844 2.191 Magt1 116967 1369868_at Magnesium transporter 3.01 2.096 2.233 Dc2 362040 1372704_at Oligosaccharyltransferase 2.521 2.084 2.084 complex subunit

Pycr1 287877 1383434_at Pyrroline-5-carboxylate reductase 4.828 6.698

124

Chac1 362196 1389573_at Cation transport regulator-like 1 2.533 6.393

isg12(b) 299269 1376845_at Adipocytokine? 3.523 4.785 Ell3 296102 1392920_at RNA polymerase II-like 3 2.271 5.005 Uap1 498272 1379910_at UDP-N-acetylglucosamine 2.101 4.519 pyrophosphorylase Nupr1 113900 1367847_at Nuclear protein 3.068 2.626

Gmppb 363145 1392701_at GDP-mannose pyrophosphorylase 2.671 2.507

Myo1g 289785 1376098_a_at Motor protein 2.886 2.201

Gmds 291095 1393713_at GDP-mannose 4, 6-dehydratase 2.066 2.885

LOC680782 680782 1371579_at Signal peptidase complex subunit 2.067 2.593

Sec11c 266758 1370817_at Signal peptidase complex sub. 2.263 2.261

RTI-M3 24747 1387205_at Surface glycoprotein 2.148 2.142

Eprs 289352 1382040_at Glutamyl-prolyl-rRNA synthetase 2.093 2.099

Rcn1 362182 1393643_at Reticulocalbin 1 2.057 2.126 Down-Regulated Genes Gene Name Entrez Function Fold Change Gene ID N=1 N=2 N=3

Stc1 81801 1377404_at calcium/phosphate regulation 0.499 0.117 0.197

1396101_at 0.488 0.068 0.221 1387623_at 0.464 0.0756 0.186

Wnt4 84426 1368641_at Signal transducer in development 0.471 0.0934 0.261

Kcnj11 83535 1387698_at Voltage gated ion channel 0.489 0.158 0.369 1369782_a_at 0.0381 0.428 1391007_s_at 0.326 0.42 Sytl4 140594 1369457_a_at Beta-cell exocytosis 0.102 0.155 Gcg 24952 1369888_at Hormone 0.13 0.151 Slc6a6 29464 1368778_at Ion, taurine transporter 0.0779 0.431 Il1r1 25663 1370750_a_at IL-1 receptor 0.0428 0.481 Hsp90ab1 301252 1393555_at ER chaperone 0.313 0.238 Crhr1 58959 1382989_at Membrane receptor 0.162 0.393 1398289_a_at 0.132 0.428

Fn1 25661 1370234_at Component of extracellular matrix 0.429 0.248 0.167

Rimbp2 266780 1371020_at Binding protein 0.0905 0.475 Pcsk2 25121 1387155_at Endoproteolytic cleavage 0.224 0.364 Kcnip1 65023 1370781_a_at Ion transport regulator 0.229 0.391 Smarca4 171379 1375469_at Chromatin remodelling 0.208 0.467

Cyp4a12 266674 1368607_at Hydroxylase, electron carrier 0.368 0.31

Igf1r 25718 1368123_at Igf-1 receptor 0.267 0.448 Pak1 29431 1368902_at Ser/Thr kinase 0.404 0.338 slit1 65047 1368483_a_at Nervous system development 0.308 0.442 Bcam 78958 1369949_at Adhesion molecule 0.493 0.293

Vsnl1 24877 1368854_at Calcium dependent signalling 0.445 0.341

Tmem176b 171411 1368840_at Cell differentiation 0.432 0.398

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Sepw1 25545 1367593_at Possible antioxidant activity 0.48 0.437 Gprc6a 294394 1369792_at G-protein coupled receptor 0.488 0.48

126

APPENDIX 2: EXAMINING THE ROLE OF STROMAL DERIVED FACTOR 2-LIKE 1 IN PANCREATIC β-CELL ER STRESS AND APOPTOSIS

127

As mentioned in the future directions one of the aims stemming from the project

presented in Chapter 4 is to examine in molecular detail the function of some of the

genes induced by the ER stress response from the microarray analysis. The gene that I

have been focusing on encodes for a protein called stromal-cell derived factor 2-like 1

(SDF2L1). It was the most highly up-regulated gene for each time point of mutant

protein expression. This appendix will provide a brief introduction to SDF2L1 by first

reviewing the available literature, then describing preliminary results as well as the

future directions for this project.

A2.1 Rationale and Hypothesis

SDF2L1 is a recently identified protein that bears an HDEL-ER retention-like

motif at its C-terminus (Fukuda et al., 2001). Its amino acid sequence has no significant

hydrophobic regions and has been shown to have significant similarity to the central

hydrophilic part of protein O-mannosyltransferase (Pmt) proteins of Saccharomyces

cerevisiae, as well as their human homologues, POMT1 and POMT2 (Fukuda et al.,

2001). SDF2L1 is induced by the ER stress-causing reagents tunicamycin and A23187,

a calcium ionophore. Interestingly, SDF2L1 was identified by cross-linking to be a

component of a large ER-localized multiprotein complex comprised of molecular

chaperones and co-chaperones, consisting of BiP, PDI ERdj3, GRP94, CaBP1, UDP-

glucosyltransferase, ERp72, cyclophilin B and GRP170, indicating a possible role for

SDF2l1 in protein folding (Meunier et al., 2002).

Recently, Rhesus macaque SDF2L1 was identified through a yeast two-hybrid

screen as an interactor of all three immature defensins, α-, β-, and θ- (Tongaonkar and

128

Selsted, 2009). Defensins are antimicrobial peptides that have been found to contribute

to the innate immunity of all species studied to date. Interestingly, in similar fashion to

insulin, defensins contain three disulfide bonds and are packaged into secretory

granules. Amongst the different defensins, alph and beta have a similar tertiary

structure and are expressed in a variety of tissues. Theta defensins have only been

identified in Old world monkeys and orangutans and are the only known circular

peptide in animals. Studies on the interaction between SDF2L1 and defensins have

shown that the nature of the interaction is similar for the α- and β- subfamilies.

However the nature of the interaction with the θ-defensins is unique. This study

speculated that SDF2L1 could play a role in the maturation/trafficking of defensins at a

common step to all three subfamilies

Given the abundant induction of SDF2L1 expression in our model system of ER

stress and the limited information available, we decided to examine the role of SDF2L1

in ER stress, ER-stress induced apoptosis and insulin biosynthesis. We hypothesize

that SDF2L1 is an essential component of the ER stress response responsible for

assisting in either protein folding or potentially ER-associated degradation.

A2.2 Results

A2.2.1 SDF2L1 is induced in MKR mice, another model of diabetes.

Prior to detailed functional analysis of SDF2L1 function in β-cells, it was

important to determine if the induction of SDF2L1 occurs in other models of diabetes,

and not specifically in our cellular model of ER stress. To examine this, we obtained

total RNA samples from islets of 8 week old wild type and diabetic MKR mice from

129

Dr. Mike Wheeler (University of Toronto). MKR mice express a dominant-negative

form of insulin growth factor receptor 1 (IGF1R), which is capable of binding with

wild type IGF1R and the insulin receptor. This causes insulin resistance and

hyperglycemia by 6 weeks of age (Lu et al, 2008). Real-time PCR analysis showed

that these mice also exhibited induction of SDF2L1, confirming that SDF2L1 is

induced in islets of diabetic animals and is likely to be a bona-fide gene induced by

pathological ER stress (Fig. A2.1).

Figure A2.1. Sdf2l1 mRNA is induced in MKR mice. Real-time PCR analysis using total RNA isolated from 8 week old MKR and WT islets. mRNA levels relative to cellular β-actin for SDF2L1 was analyzed as outlined in the Methods. Shown is the mean ± SE of 3 independent experiments. *p<0.05 relative to control.

A2.2.2 Generation of Expression Vectors for a Functional Analysis of SDF2L1

In preparation for a functional analysis of SDF2L1 I have generated and tested

several reagents. I have cloned, as described in the Methods section, sdf2l1 from rat

INS-1 cells into both pcDNA3.1(-), and pShuttle-GFP vectors. The latter will be used

to generate recombinant adenovirus to overexpress SDF2L1 for functional studies.

130

In addition, I have cloned SDF2L1 cDNA into a pA-IRES construct (in collaboration

with Dr. Jim Rini) that will allow us to produce the protein in mammalian cells for both

biochemical studies and structural determination. Transient transfection of this vector

into HEK293T cells has shown that we get abundant expression of the SDF2L1

construct (Fig.A2.2) and that this expression is identifiable using both of the

commercially available anti-protein A and anti-sdf2l1 antibodies.

Figure A2.2. Test transfection of PA-IRES-Sdf2l1 in HEK293T cells. HEK293T cells were transiently transfected as described in Methods. Following transfection, the cells were washed in PBS, lysed, and 10 μg of protein was resolved by SDS-PAGE and immunoblotted with protein A and Sdf2l1 antibodies.

131

The recent discovery of a commercial antibody should prove useful to studies

examining the function of SDF2L1. As shown in Figure A2.3, a time-dependent

upregulation of SDF2L1 is observed with mutant insulin expression.

Figure A2.3. SDF2L1 expression with mutant insulin induction. Clone #4S2 cells were untreated (Control) or treated with 2 μg/ml doxycycline (+Dox) for the times indicated. To act as positive controls, INS-1E and Clone #4S2 cells were treated with tunicamycin for 16h. Following treatment, the cells were washed in PBS, lysed and equal amounts of protein were resolved by 10% SDS-PAGE and immunoblotted using anti-SDF2L1 and tubulin antibodies.

Finally, preliminary experiments using real-time PCR analysis have shown that

SDF2L1 siRNAs effectively knock down sdf2l1 mRNA (data not shown).

A2.3 Summary and Future Directions

Sdf2l1 has been identified as one of the most upregulated genes with mutant

insulin induction. Though no functional information is available for the protein, it has

been identified as an ER stress-inducible gene homologous to the O-mannosylating

Pmt/rt protein family. Our plan is to conduct a functional analysis of this protein to

132

identify its role in ER-stress in pancreatic β-cells. Specifically, we plan on constructing

an SDF2L1-expressing adenovirus, which will allow us to overexpress SDF2L1 in

cultured β-cells and analyze the effect on mutant insulin degradation. We will also be

performing knockdown experiments to investigate the effect of SDF2L1 depletement

on β-cell viability and mutant insulin biosynthesis and degradation. We hypothesize

that SDF2L1 is involved in either the degradation of misfolded insulin in the ER or

functions as a molecular chaperone protein that promotes insulin folding. Structural

studies will also be conducted using the protein A construct generated in collaboration

with the Rini lab.

133

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