MOLECULAR MARKERS OF OBESITY AND DIABETESeprints.qut.edu.au/35762/1/Christopher_Swagell_Thesis.pdf · MOLECULAR MARKERS OF OBESITY AND DIABETES ... diets that are high in monounsaturated

MOLECULAR MARKERS OF OBESITY AND DIABETES

Christopher Dean Swagell

Bachelor of Science (Honours) University of Queensland

CRC for Diagnostics School of Life Sciences

Institute of Health and Biomedical Innovation Queensland University of Technology

Brisbane, Australia

A thesis submitted for the degree of Doctor of Philosophy at the Queensland University of Technology, 2007.

http://www.ihbi.qut.edu.au/

http://www.ihbi.qut.edu.au/

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Dedications

I dedicate this thesis to my mentor Phil and my family Bill, Lucy and David.

We finally got there!

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Declaration

The work presented in this thesis has not been previously submitted for a degree or diploma at this or any other higher education institution. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person(s) except where due reference is made.

Signed: ………………………………………

Christopher Dean Swagell

Date: ………………

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Abstract

Recently it has been shown that the consumption of a diet high in saturated fat is

associated with impaired insulin sensitivity and increased incidence of type 2 diabetes.

In contrast, diets that are high in monounsaturated fatty acids (MUFAs) or

polyunsaturated fatty acids (PUFAs), especially very long chain n-3 fatty acids (FAs),

are protective against disease. However, the molecular mechanisms by which saturated

FAs induce the insulin resistance and hyperglycaemia associated with metabolic

syndrome and type 2 diabetes are not clearly defined.

It is possible that saturated FAs may act through alternative mechanisms compared to

MUFA and PUFA to regulate of hepatic gene expression and metabolism. It is

proposed that, like MUFA and PUFA, saturated FAs regulate the transcription of target

genes. To test this hypothesis, hepatic gene expression analysis was undertaken in a

human hepatoma cell line, Huh-7, after exposure to the saturated FA, palmitate. These

experiments showed that palmitate is an effective regulator of gene expression for a

wide variety of genes. A total of 162 genes were differentially expressed in response to

palmitate. These changes not only affected the expression of genes related to nutrient

transport and metabolism, they also extend to other cellular functions including,

cytoskeletal architecture, cell growth, protein synthesis and oxidative stress response.

In addition, this thesis has shown that palmitate exposure altered the expression patterns

of several genes that have previously been identified in the literature as markers of risk

of disease development, including CVD, hypertension, obesity and type 2 diabetes. The

altered gene expression patterns associated with an increased risk of disease include

apolipoprotein-B100 (apo-B100), apo-CIII, plasminogen activator inhibitor 1, insulin-

like growth factor-I and insulin-like growth factor binding protein 3. This thesis reports

the first observation that palmitate directly signals in cultured human hepatocytes to

regulate expression of genes involved in energy metabolism as well as other important

genes.

Prolonged exposure to long-chain saturated FAs reduces glucose phosphorylation and

glycogen synthesis in the liver. Decreased glucose metabolism leads to elevated rates of

lipolysis, resulting in increased release of free FAs. Free FAs have a negative effect on

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insulin action on the liver, which in turn results in increased gluconeogenesis and

systemic dyslipidaemia. It has been postulated that disruption of glucose transport and

insulin secretion by prolonged excessive FA availability might be a non-genetic factor

that has contributed to the staggering rise in prevalence of type 2 diabetes. As

glucokinase (GK) is a key regulatory enzyme of hepatic glucose metabolism, changes in

its activity may alter flux through the glycolytic and de novo lipogenic pathways and

result in hyperglycaemia and ultimately insulin resistance. This thesis investigated the

effects of saturated FA on the promoter activity of the glycolytic enzyme, GK, and

various transcription factors that may influence the regulation of GK gene expression.

These experiments have shown that the saturated FA, palmitate, is capable of decreasing

GK promoter activity. In addition, quantitative real-time PCR has shown that palmitate

incubation may also regulate GK gene expression through a known FA sensitive

transcription factor, sterol regulatory element binding protein-1c (SREBP-1c), which

upregulates GK transcription.

To parallel the investigations into the mechanisms of FA molecular signalling, further

studies of the effect of FAs on metabolic pathway flux were performed. Although

certain FAs reduce SREBP-1c transcription in vitro, it is unclear whether this will result

in decreased GK activity in vivo where positive effectors of SREBP-1c such as insulin

are also present. Under these conditions, it is uncertain if the inhibitory effects of FAs

would be overcome by insulin. The effects of a combination of FAs, insulin and

glucose on glucose phosphorylation and metabolism in cultured primary rat hepatocytes

at concentrations that mimic those in the portal circulation after a meal was examined.

It was found that total GK activity was unaffected by an increased concentration of

insulin, but palmitate and eicosapentaenoic acid significantly lowered total GK activity

in the presence of insulin. Despite the fact that total GK enzyme activity was reduced in

response to FA incubation, GK enzyme translocation from the inactive, nuclear bound,

to active, cytoplasmic state was unaffected. Interestingly, none of the FAs tested

inhibited glucose phosphorylation or the rate of glycolysis when insulin is present.

These results suggest that in the presence of insulin the levels of the active, unbound

cytoplasmic GK are sufficient to buffer a slight decrease in GK enzyme activity and

decreased promoter activity caused by FA exposure. Although a high fat diet has been

associated with impaired hepatic glucose metabolism, there is no evidence from this

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thesis that FAs themselves directly modulate flux through the glycolytic pathway in

isolated primary hepatocytes when insulin is also present.

Therefore, although FA affected expression of a wide range of genes, including GK, this

did not affect glycolytic flux in the presence of insulin. However, it may be possible

that a saturated FA-induced decrease in GK enzyme activity when combined with the

onset of insulin resistance may promote the dys-regulation of glucose homeostasis and

the subsequent development of hyperglycaemia, metabolic syndrome and type 2

diabetes.

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Keywords cDNA microarray analysis; Gene expression; Saturated fatty acid; Palmitate;

Hepatocytes; Glucokinase; Microarray analysis; Monounsaturated fatty acid;

Polyunsaturated fatty acid; Oleate; Eicosapentaenoic acid; Human hepatic cell line;

Fatty acid signalling; Fatty acids; Glycolysis; Insulin; Primary rat hepatocytes

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List of Publications, Manuscripts and Patents The following collection of publications and manuscripts were prepared in conjunction with the thesis. Other non-related material that was generated over the duration of the thesis examination period is also listed. Thesis Associated Research Manuscripts Swagell CD, Henly DC, Morris CP. Expression analysis of a human hepatic cell line in response to palmitate. Biochemical and Biophysical Research Communications 2005: Mar 11; 328(2):432-441. (Impact Factor 2005 – 3.0) Swagell CD, Morris CP, Henly DC. Effect of fatty acids, glucose, and insulin on hepatic glucose uptake and glycolysis. Nutrition 2006: Jun 22(6):672-678. (Impact Factor 2005 – 2.1) Swagell CD, Henly DC, Morris CP. Regulation of human hepatocyte gene expression by fatty acids. Biochemical and Biophysical Research Communications 2007: Oct 19; 362(2):374-380. (Impact Factor 2005 – 3.0) Thesis Associated Abstracts Swagell CD, Rutherford P, Henly DC, Morris CP. Effects of Fatty Acids on Glucokinase Activity and Hepatic Glucose Metabolism. 10th Annual Scientific Proceedings (September 2001) – Australasian Society for the Study of Obesity. Ryan LK, Swagell CD, Morris CP, Henly DC. Leptin May Inhibit Lipogenesis in a Liver Cell Line by Reducing Glucokinase mRNA Concentrations. Proceedings of the Australian Health and Medical Research Congress (2002). Ryan LK, Swagell CD, Morris CP, Henly DC. Leptin Down-Regulates its Receptor in a Human Hepatic Cell Line. ComBio (September 2003). Non-Associated Research Publications Lawford BR, Young RMcD, Swagell CD, Barnes M, Burton SC. Ward W, Heslop K, Shadforth S, van Daal A, Morris CP. The C/C genotype of the C957T polymorphism of the dopamine D2 receptor (DRD2) is associated with schizophrenia. Schizophrenia Research. 2004; 73:31-37. (Impact Factor 2005 – 4.2) Young RMcD, Lawford BR, Swagell CD, Hughes IP, Connor JP, Feeney GFX, van Daal A, Morris CP. The C allele of the c.957C>T polymorphism of the dopamine D2 receptor gene is associated with alcohol dependence. Submitted – Neuroscience Letters. (Impact Factor 2005 – 3.1) Lawford BR, Swagell CD, Young RMcD, Barnes M, Burton SC, Ritchie T, Hughes I, Noble E, van Daal A, Morris CP. The DRD2-region 957C/TaqI A1 haplotype is associated with schizophrenia. Submitted - American Journal of Psychiatry. (Impact Factor 2005 – 8.3) Non-Associated Patents Lawford BR, Young RMcD, Swagell CD, van Daal A, Morris CP (Inventors). Compositions and Methods. PCT patent application (WO2005118843 - 2005-12-15 - Lodged May 2004).

Lawford BR, Young RMcD, Swagell CD, Hughes I, Voisey J, Morris CP (Inventors). Diagnostic Methods and Agents. US provisional patent application (60/885837 - Lodged Jan 2007).

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Acknowledgements

I would like to thank my family Bill, Lucy and David for their support and

understanding over this long journey. I would also like to acknowledge The

Queensland University of Technology, the Institute of Health and Biomedical

Innovation and particularly the Cooperative Research Centre (CRC) for Diagnostics for

giving me this fantastic opportunity and for providing financial support. A special

mention goes to all of the CRC staff and students that over the years have made this

chapter of my life fun and more enjoyable, you know who you are! Especially, the

thesis writing posse of Chris and Anna who helped make those late night/early morning

writing and printing sessions a little easier. Also, I must thank Debra Henly for the

amount of effort and expertise she has provided throughout my PhD.

But most of all I would like to thank Phil for his overwhelming acceptance, inspiration

and belief in me, for which I have a great appreciation and respect. This has been the

most rewarding, trying and emotional time that I have experienced in my life and I will

never forget it!

I would also like to acknowledge a number of groups and facilities that have helped me

throughout the years of my PhD. I would also like to thank the Microarray Facility and

the Brain Institute at the University of Queensland and Applied Biosystems for

providing assistance over my PhD.

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Abbreviations ABCA1 – ATP binding cassette A1

ACC – Acetyl CoA carboxylase

ADRP – Adipose differentiation related protein

AGE – Advanced glycation end-products

AMV – Avian myeloblastosis virus

Apo – Apolipoprotein

bHLH-LZ – Basic helix-loop-helix leucine zipper

BSA – Bovine serum albumin

CAD – Coronary artery disease

cDNA – Complimentary deoxyribonucleic acid

CDK4 – Cyclin dependent kinase 4

CoA – Coenzyme A

cRNA – Complimentary ribonucleic acid

CHD – Coronary heart disease

CRE – cAMP response element

CVD – Cardiovascular disease

DHA – Docosahexaenoic acid

DMEM –Dulbecco’s modified Eagle’s medium

dNTP – Deoxyribonucleotide triphosphate

EDTA – Ethylenediaminetetraacetic acid

EIF – Eukaryotic translation initiation factor

EPA – Eicosapentaenoic acid

FA – Fatty acid

FAS – Fatty acid synthase

FDFT1 – Farnesyl-diphosphate farnesyl transferase

FDPS – Farnesyl pyrophosphate synthetase

G-6-P – Glucose 6-phosphate

GK – Glucokinase

GKRP – Glucokinase regulatory protein

GPX4 – Phospholipid hydroperoxide glutathione peroxidase

GSH – Glutathione

GST – Glutathione S-transferase

H2O2 – hydrogen peroxide

HDL – High-density lipoprotein

HEPES – 4-2-hydroxyethyl-1-piperazineethanesulfonic acid

HGF – Hepatic growth factor

HNF-4α – Hepatocyte nuclear factor-4α

Hsp90 – Heat shock protein 90

IDL – Intermediate density lipoprotein

IGF-I – Insulin-like growth factor I

IR – Insulin receptor

IRS – Insulin receptor substrate

IGFBP3 – Insulin-like growth factor binding protein 3

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IL-6 – Interleukin-6

JAK – Janus kinase

LBR – Lamin B receptor

LDL – Low-density lipoprotein

LIPA – Lysosomal acid lipase

LXR – Liver X receptor

MODY – Maturity onset diabetes of the young

mRNA – Messenger ribonucleic acid

MRP2 – Multi-drug resistance protein

MUFA – Monounsaturated fatty acid

NADH – nicotinamide adenine dinucleotide

NO – Nitric oxide

NFKB1 – Nuclear factor kappa B

nSREBP – Nuclear sterol regulatory element binding protein

Ob-R – Leptin receptor

P59 – Protein 59

PAI-1 – Plasminogen activator inhibitor 1

PBS – Phosphate buffered saline

PD – Pyruvate dehydrogenase

PDK1 – 3-phosphoinositide dependent kinase 1

PKB – Protein kinase B

PI(3)K – phosphoinositide 3-kinase

PUFA – Polyunsaturated fatty acid

PPAR – Peroxisomal proliferator activated receptor

PPRE – Peroxisome proliferator response element

q-PCR – Quantitative real-time polymerase chain reaction

RECK – Reversion-inducing-cysteine-rich protein with Kazal motifs

ROS – Reactive oxygen species

RXR – Retinoic acid receptor

SCD – Stearyl-CoA desaturase

SDS – Sodium dodecyl sulphate

SRE – Sterol regulatory element

SREBP – Sterol regulatory element binding protein

SEPP1 – Selenoprotein P

SSC – Sodium chloride sodium citrate

STAT – Signal transducer and activator of transcription

TG – Triglyceride

TGFB2 – Transforming growth factor β2

TNF – Tumour necrosis factor

TNFR1 – Tumour necrosis factor receptor 1

VLDL – Very low-density lipoprotein

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Table of Contents

Title page 1

Dedications 3

Declaration 5

Abstract 7

Keywords 11

List of Publications, Manuscripts and Patents 13

Acknowledgments 15

Abbreviations 16

Table of Contents 18

CHAPTER ONE – INTRODUCTION 21

1.1 Description of Scientific Problem Investigated 23

1.2 Overall Objective of the Thesis 24

1.3 Specific Aims of the Thesis 25

1.4 Account of Scientific Progress Linking the Scientific Papers 25

CHAPTER TWO – LITERATURE REVIEW 33

2.1 Obesity 35

2.1.1 Mutations Associated with Obesity 37

2.2 Metabolic Syndrome 37

2.3 Type 2 Diabetes 38

2.3.1 Maturity-Onset Diabetes of the Young 40

2.4 Risk Factors Associated with Obesity, Metabolic Syndrome and Type 2 Diabetes 40

2.4.1 Insulin Resistance 41

2.4.2 Hyperglycaemia 43

2.4.3 Oxidative Stress 43

2.4.4 Diabetic Dyslipidaemia 45

2.4.5 Hypertension 45

2.4.6 Microvascular Complications 46

2.5 Key Hormones Influencing Metabolic Syndrome and Type 2 Diabetes 47

2.5.1 Insulin 47

2.5.2 Insulin Signalling 48

2.5.3 Leptin 49

2.5.4 Leptin Signalling 50

2.6 Key Enzyme Involved in Insulin Action and Hepatic Glycolysis 50

2.6.1 Glucokinase 50

2.6.2 Regulation of Glucokinase 51

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2.6.3 Other Enzymes Involved in Glucose Metabolism 53

2.7 Current Treatments of Metabolic Syndrome and Type 2 Diabetes 53

2.7.1 Lipid-Lowering Agents 53

2.7.2 Hypoglycaemic Agents 54

2.7.3 Hypertensive Agents 55

2.8 Dietary Lipids and a High Fat Diet 55

2.8.1 Lipids 55

2.8.2 Fatty Acid Homeostasis 56

2.8.3 High Fat Diet, Hepatic Glycolysis and Gluconeogenesis 57

2.8.4 High Fat Diet and Insulin Resistance 59

2.9 Transcription Factors Involved in Fatty Acid Signalling 61

2.9.1 Sterol Regulatory Element Binding Protein-1c 61

2.9.2 Liver X Receptor α 62

2.9.3 Hepatocyte Nuclear Factor-4α 63

2.9.4 Peroxisomal Proliferator Activated Receptor α 63

2.9.5 Fatty Acid Gene Regulation 65

2.10 Summary 67

2.11 Bibliography 68

CHAPTER THREE – RESULTS 85

Statement of Authorship 87

Expression Analysis of a Human Hepatic Cell Line in Response to Palmitate 89

CHAPTER FOUR – RESULTS 101


Regulation of Human Hepatocyte Gene Expression by Fatty Acids 105

Appendix 4.1 113

CHAPTER FIVE – RESULTS 123


Effect of Fatty Acids, Glucose, and Insulin on Hepatic Glucose Uptake and Glycolysis 127

Appendix 5.1 135

CHAPTER SIX – GENERAL DISCUSSION 143

General Discussion 145

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Chapter 1 - Introduction

CHAPTER ONE

INTRODUCTION

Chapter 1 – Introduction

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1.1 Description of Scientific Problem Investigated

Type 2 diabetes is a slow onset disease arising most often in older individuals [1],

although the frequency is now increasing among children [2]. Type 2 diabetes is

characterised by insulin deficiency coupled with insulin resistance that leads to a

disturbance in glucose metabolism, ultimately resulting in chronic hyperglycaemia and

dyslipidaemia [1; 3; 4; 5]. Approximately 200 million people worldwide are affected by

type 2 diabetes and it is predicted that up to 350 million individuals will develop the

disease by the year 2030 [6]. Type 2 diabetes has a massive impact on the health of

Australians as the 6th leading cause of death in Australia [7] and is responsible for an

enormous public health and social burden. The Australian health system expenditure on

type 2 diabetes was estimated at around 800 million dollars in 2001 [8]. In addition,

cardiovascular disease (CVD) is responsible for up to 80% of deaths in people suffering

from type 2 diabetes [9; 10]. Other complications associated with diabetes include

retinopathy, nephropathy and neuropathy.

Type 2 diabetes arises from a combination of multiple genetic and environmental

factors [1; 11]. The consumption of a diet high in saturated fatty acids (FAs) has been

associated with an increased incidence of type 2 diabetes as well as atherosclerosis and

some forms of cancer [12]. In contrast, some diets are protective against the

development of diabetes and disorders such as atherosclerosis and dyslipidaemia [13].

These include diets that are high in monounsaturated FAs (MUFAs), such as the

“Mediterranean diet”, and diets high in very long chain n-3 polyunsaturated FAs

(PUFAs), derived from fish oils. One explanation for the increasing incidence of type 2

diabetes may be an increased amount of saturated fat in the diet. Although it is well

known that excessive weight gain and an obese state frequently precede the

development of type 2 diabetes, it is not clear whether specific dietary fat intake

contributes to the development of the diabetic state.

FAs have long been known to be associated with certain metabolic disorders, but it is

only recently that the effects of individual FAs on gene regulation have been

investigated. Since genomic profiling microarray technologies have become available

studies that identify genes that are regulated by FAs are being performed [14; 15; 16;

17]. Recent evidence has identified that certain nutrients, including FAs, are important

regulators of gene expression. Previously identified transcription factors include the


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“FA sensors”, peroxisomal proliferator activated receptors (PPARs), and the mediator

of insulin action, sterol regulatory element binding protein-1c (SREBP-1c). Therefore,

the focus of this research was to investigate the effects exhibited by FAs on hepatic

gene expression and metabolism.

1.2 Overall Objective of the Thesis

The aim of this project is to understand the role of fat in the development of

pathological conditions such as metabolic syndrome and type 2 diabetes. In particular,

this thesis focuses on the molecular mechanisms underlying the dysregulation of

glucose and lipid metabolism in the liver.

This thesis may provide important information on the relationship between FAs and

hepatic gene regulation that could potentially identify diagnostically useful molecular

markers to detect those at risk of developing metabolic syndrome and type 2 diabetes.

These markers could also be used to monitor the effectiveness of dietary modification

and lifestyle changes. This thesis may provide data that could allow the identification

of key targets for the development of prevention strategies and treatments for metabolic

syndrome and type 2 diabetes.

Hypothesis

We propose that saturated fat alters the regulation of hepatic gene expression

contributing to the development of impaired glucose metabolism, hyperglycaemia,

metabolic syndrome and type 2 diabetes.

In addition, we propose that saturated fatty acids specifically alter the regulation of the

key hepatic enzyme glucokinase (GK), contributing to perturbations of whole body

glucose homeostasis.

The Model

In this thesis we attempted to isolate the direct effects of FAs on gene regulation in the

liver from secondary whole body physiological effects of dietary fats. In order to do

this we used primary hepatocytes and cultured hepatic cell lines incubated in the

presence of FAs.


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1.3 Specific Aims of the Thesis

Characterise novel mRNA expression patterns in response to the saturated FA,

palmitate, by microarray analysis in a human hepatic cell line. Identify potential gene targets that are regulated by FA in the liver, that may be

associated with an increased risk of disease development. Confirm altered gene expression identified by microarray analysis by

quantitative real time-PCR. Compare changes in the short-term gene regulation by saturated, MUFAs and

PUFAs by microarray analysis in a human hepatic cell line. Identify regulatory elements in the GK promoter and characterise the

transcription factors that interact with them.

Identify specific FA regulation of transcription factors and other important

metabolic genes involved in GK gene transcription by using quantitative real

time-PCR.

Investigate the effect of FAs on GK enzyme activity and the cellular distribution

of the GK enzyme.

Characterise FA mediated regulation of glucose phosphorylation, glycolysis and

β-oxidation.

1.4 Account of Scientific Progress Linking the Scientific Papers

Previously, microarray studies have focused on transcriptional responses to fatty acids

in cultured pancreatic β-cells [14] and clonal insulin-producing cells and in vivo using

high fat fed mice [15; 17]. These studies have identified that FAs can directly signal

and regulate gene expression in both systems. However, to date there have been no

investigations into the direct effect of FA on gene expression in hepatic tissue. This

issue was addressed in Chapter Three by measuring the effect of palmitate on gene

expression in cultured hepatocytes.

Several MUFAs and PUFAs have been shown to be potent regulators of gene

transcription in liver. For example, PUFAs act to reduce SREBP-1c mRNA levels [18]

while PPARα is activated upon PUFA binding [19]. PPARα activation increases the

rate of transcription of a number of target genes involved in lipid and cholesterol

metabolism [20]. In addition, SREBP-1c has emerged as a major mediator of insulin


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action on hepatic expression of genes involved in glycolysis and de novo lipogenesis,

such as GK [21; 22]. GK is the main regulatory enzyme controlling hepatic glucose

metabolism and glycolytic flux. It catalyses the phosphorylation of glucose to glucose

6-phosphate and is activated by insulin. Therefore, alterations in GK gene expression

may contribute to perturbations in glucose homeostasis, resulting in hyperglycaemia. In

order to identify the role that saturated fat plays in the regulation of glucose

homeostasis, Chapter Four describes that analysis of GK promoter activity in cultured

hepatocytes, in addition to quantitative real-time PCR analysis of transcription factors

that regulate GK in response to palmitate.

Metabolic syndrome is characterised by hyperglycaemia and insulin insensitivity. One

explanation for this can be illustrated by maturity-onset diabetes of the young (MODY-

2), which is caused by a mutation in the GK gene that results in a mild form of type 2

diabetes [23; 24]. While studies have shown that GK does not contribute to a genetic

predisposition to the common form of type 2 diabetes, it may be that dietary fat is a non-

genetic factor that perturbs GK expression. Reduced GK expression could decrease the

flux through the glycolytic pathway, resulting in increased plasma glucose

concentration and development of hyperglycaemia and type 2 diabetes. Therefore, in

Chapter Five investigations into the effect of fat on GK enzyme activity, glucose

phosphorylation, glycolysis and β-oxidation were performed in isolated primary rat

hepatocytes.

Chapter Three – Expression analysis of a human hepatic cell line in response to palmitate.

Biochemical and Biophysical Research Communications 2005; 328:432-441.

Due to the lack of data focusing on the direct effects of FA signalling in hepatic tissue,

in Chapter Three we utilised microarray gene expression analysis to investigate the

signalling of the saturated FA, palmitate, in a human hepatic cell line, Huh-7. This is the

first report showing that palmitate regulates expression of numerous genes via direct

molecular signalling mechanisms in cultured human hepatocyte cell line. Observations

of altered hepatic regulation in response to palmitate include genes that are involved in

FA transport, cholesterol catabolism, oxidative stress response, cell cycle, cell growth

and proliferation. This thesis also identified several genes that are differentially

regulated upon palmitate exposure that have been previously reported as markers of


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increased disease risk. These genes include apolipoprotein-B100 (apo-B100) that is

implicated in obesity, hypertension and diabetes [25], and apo-CIII, which is associated

with high levels of apo-CIII-containing very low density lipoproteins (VLDLs) and

hypertriglyceridemia [26]. Other genes associated with disease include the up-regulated

plasminogen activator inhibitor-1, which is associated with renal fibrosis and diabetic

nephropathy, and the down-regulated insulin-like growth factor-I and insulin-like

growth factor binding protein-3 that are characteristic of a diabetic state [27]. This in

vitro molecular study supports in vivo data that saturated FA is a potential contributor to

the development of diseases, such as metabolic syndrome and type 2 diabetes.

Chapter Four – Regulation of gene expression by fatty acids in human hepatic cell lines.

Submitted November 2006 - Experimental Cell Research.

In Chapter Three, palmitate was shown to be a regulator of hepatic gene expression

after 48 hours exposure. Chapter Four of this thesis reports the effects of palmitate on

GK promoter activity and the possible role of palmitate in regulating GK gene

expression. Palmitate reduced GK promoter activity after 48 hours in the human

hepatic cell line, Huh-7, transfected with GK reporter constructs. In addition,

quantitative real-time PCR analysis of SREBP-1c expression, a positive regulator of GK

gene transcription, revealed a reduction in mRNA levels in response to palmitate,

possibly explaining the observed reduction of GK promoter activity. This thesis has

generated evidence implicating a possible role of palmitate in the perturbation hepatic

gene expression in Huh-7 cells. A second study was carried out to compare the effects

of saturated FA, MUFA and PUFA in a second cell line, HepG2. A microarray

expression analysis was performed to identify direct short-term regulation of hepatic

gene expression after 1.5 hours. This comparison revealed that MUFAs and PUFAs

initiate a similar pattern of hepatic gene regulation, while saturated FA failed to initiate

a short-term regulatory response in hepatic cells.

Chapter Five – Effect of fatty acids, glucose, and insulin on hepatic glucose uptake and

glycolysis. Nutrition 2006: Jun 22(6):672-678.

As GK promoter activity and SREBP-1c mRNA expression was reduced by palmitate,

Chapter Five of this thesis examines the effects of FA and insulin signalling on GK

enzyme activity and glucose metabolism in cultured primary rat hepatocytes at


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concentrations that mimic those after a meal. This thesis identified that the saturated

FA, palmitate, and the PUFA, eicosapentaenoic acid, significantly lowered total GK

enzyme activity, even in the presence of the activator insulin. In addition, the

translocation of GK enzyme from the inactive, nuclear bound, to the active cytoplasmic

state was unaffected by FA exposure, possibly indicating an overall reduction in the

availability of cytoplasmic GK to phosphorylate glucose. However, all of the FAs

tested failed to inhibit glucose phosphorylation and flux through the glycolytic in the

presence of insulin. This suggests that in these experimental conditions the level of

residual cytoplasmic GK is sufficient to buffer a decrease in GK enzyme activity

induced by FA exposure. However, it is possible that the onset of insulin resistance or

loss of insulin action is necessary before the effects of FAs on hepatic glucose

metabolism are observed. This observation is consistent with the conclusion that the

presence of FAs in a normal mixed meal may have little direct effect on the capacity of

the liver to uptake, phosphorylate and metabolise glucose. Alternatively, FAs may

affect the liver indirectly, for example by modulating the production of hormones such

as insulin or glucagon by the pancreas.


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[14] A.K. Busch, D. Cordery, G.S. Denyer, and T.J. Biden, Expression profiling of palmitate- and oleate-regulated genes provides novel insights into the effects of chronic lipid exposure on pancreatic beta-cell function. Diabetes 51 (2002) 977-87.

[15] S. Kim, I. Sohn, J.I. Ahn, K.H. Lee, and Y.S. Lee, Hepatic gene expression profiles in a long-term high-fat diet-induced obesity mouse model. Gene 340 (2004) 99-109.

[16] J. Xiao, S. Gregersen, M. Kruhoffer, S.B. Pedersen, T.F. Orntoft, and K. Hermansen, The effect of chronic exposure to fatty acids on gene expression in clonal insulin-producing cells: studies using high density oligonucleotide microarray. Endocrinology 142 (2001) 4777-84.

[17] V. de Fourmestraux, H. Neubauer, C. Poussin, P. Farmer, L. Falquet, R. Burcelin, M. Delorenzi, and B. Thorens, Transcript profiling suggests that differential


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metabolic adaptation of mice to a high fat diet is associated with changes in liver to muscle lipid fluxes. J Biol Chem 279 (2004) 50743-53.

[18] J. Xu, M. Teran-Garcia, J.H. Park, M.T. Nakamura, and S.D. Clarke, Polyunsaturated fatty acids suppress hepatic sterol regulatory element-binding protein-1 expression by accelerating transcript decay. Journal of Biological Chemistry 276 (2001) 9800-7.

[19] S.A. Kliewer, S.S. Sundseth, S.A. Jones, P.J. Brown, G.B. Wisely, C.S. Koble, P. Devchand, W. Wahli, T.M. Willson, J.M. Lenhard, and J.M. Lehmann, Fatty acids and eicosanoids regulate gene expression through direct interactions with peroxisome proliferator-activated receptors alpha and gamma. Proc Natl Acad Sci U S A 94 (1997) 4318-23.

[20] B. Desvergne, and W. Wahli, Peroxisome proliferator-activated receptors: nuclear control of metabolism. Endocr Rev 20 (1999) 649-88.

[21] M. Foretz, C. Guichard, P. Ferre, and F. Foufelle, Sterol regulatory element binding protein-1c is a major mediator of insulin action on the hepatic expression of glucokinase and lipogenesis-related genes. [see comments.]. Proceedings of the National Academy of Sciences of the United States of America 96 (1999) 12737-42.

[22] S.Y. Kim, H.I. Kim, T.H. Kim, S.S. Im, S.K. Park, I.K. Lee, K.S. Kim, and Y.H. Ahn, SREBP-1c mediates the insulin-dependent hepatic glucokinase expression. J Biol Chem 279 (2004) 30823-9.

[23] P. Froguel, M. Vaxillaire, F. Sun, G. Velho, H. Zouali, M.O. Butel, S. Lesage, N. Vionnet, K. Clement, F. Fougerousse, and et al., Close linkage of glucokinase locus on chromosome 7p to early-onset non-insulin-dependent diabetes mellitus. Nature 356 (1992) 162-4.

[24] M. Stoffel, P. Froguel, J. Takeda, H. Zouali, N. Vionnet, S. Nishi, I.T. Weber, R.W. Harrison, S.J. Pilkis, S. Lesage, and et al., Human glucokinase gene: isolation, characterization, and identification of two missense mutations linked to early-onset non-insulin-dependent (type 2) diabetes mellitus. Proc Natl Acad Sci U S A 89 (1992) 7698-702.

[25] B. Glowinska, M. Urban, A. Koput, and M. Galar, New atherosclerosis risk factors in obese, hypertensive and diabetic children and adolescents. Atherosclerosis 167 (2003) 275-86.

[26] S.J. Lee, L.A. Moye, H. Campos, G.H. Williams, and F.M. Sacks, Hypertriglyceridemia but not diabetes status is associated with VLDL containing apolipoprotein CIII in patients with coronary heart disease. Atherosclerosis 167 (2003) 293-302.

[27] A. Heald, R. Stephens, and J.M. Gibson, The insulin-like growth factor system and diabetes--an overview. Diabet Med 23 Suppl 1 (2006) 19-24.

Chapter 2 – Literature Review


33

CHAPTER TWO

LITERATURE REVIEW


34


35

2.1 Obesity

During the mid 20th century an unprecedented change in caloric availability has taken

place in many Western and developing countries. One explanation is that throughout

human history recurrent cycles of under-nutrition and preloading of calories for

subsequent energy utilisation has been the normal pattern of human nutrition. However,

in today’s society this has been replaced with continuous over-nutrition. This

consequence has been greatly amplified by a permanent state of under exertion imposed

by sedentary lifestyles and advances in modern technologies. It is now obvious that

diseases of long-term over-nutrition have become increasingly prevalent [1]. This is

due to the overwhelming incapability of compensatory mechanisms that normally buffer

the metabolic change in calorie balance and short-term over-nutrition. Obesity is now

so common within the world’s population that it has replaced malnutrition and

infectious diseases as the most significant contributor to ill health [2]. The current

epidemic of obesity poses a significant public health problem as it now afflicts more

than 300 million people worldwide [3]. The global epidemic of obesity results from a

combination of programmed genetic susceptibility, increased availability of high-energy

foods and decreased requirement for physical activity in modern society.

Obesity can be defined as excess adiposity to an extent that is detrimental to an

individual’s health. The body mass index (BMI) is commonly used as a measure of

obesity with a BMI of 18.5 – 24.9 kg/m2 defining the desirable range in Caucasians

(Table 1). An individual’s BMI is calculated by dividing their weight in kilograms (kg)

by their height in metres squared (m2). However, it must be recognised that individual

BMI measurements may differ in the actual degree of adiposity and does not

differentiate between muscle and adipose tissue. This means that individuals such as

athletes, who have a high muscle to fat ratio, can be defined as ‘overweight’. Another

measurement of obesity that can be used to asses the distribution of body fat is the

waist-to-hip ratio (WHR). The WHR is the measurement of the ratio of an individual’s

waist circumference to hip circumference. Abdominal fat is associated with more

health problems than carrying extra weight around their hips or thighs. A WHR of 0.90

or less is considered healthy for men and a ratio of 0.80 or less is considered a sign of

good health for women. A WHR of 1 or higher signals an increased risk of ill health.

Other more practical methods to measure body fat include ‘skin-fold’ thickness and

‘bioelectrical impedance’ analysis. These methods can measure the percentage of body


36

fat by using skin fold callipers and the bioelectrical impedance of an individual’s body

tissue conductivity to electricity, respectively.

Table 1 – BMI Classification of Obesity [4].

Obesity is a principal independent risk factor for type 2 diabetes and an excess of body

fat, especially visceral obesity [5], and the duration of obesity [6] has a range of

potentially harmful consequences. Increasing weight gain and obesity leads to adverse

metabolic effects on blood pressure, cholesterol and triglyceride (TG) levels, and insulin

resistance. In addition, weight gain leads to insulin resistance through several

mechanisms placing a greater demand on the pancreatic capacity to produce insulin,

which also declines with age, leading to the development of clinical type 2 diabetes.

Physical inactivity, which is both a cause and consequence of weight gain, also

contributes to insulin resistance. Obesity is also associated with hypertension,

dyslipidaemia (characterised by increased levels of TGs, cholesterol and low-density

lipoproteins (LDLs) and decreased levels high-density lipoproteins (HDLs)), insulin

resistance (characterised by increased blood insulin levels), impaired glucose tolerance

and, type 2 diabetes [7; 8; 9; 10]. Furthermore, risks of coronary heart disease (CHD),

cardiovascular disease (CVD), ischemic stroke and type 2 diabetes increase steadily

with an increasing BMI.

Obesity can be considered to be a single disorder with multiple causes. Body weight is

determined by an interaction between genetic, environmental and psychosocial factors

acting through the physiological mediators of energy intake and expenditure [2].

Obesity runs in families but the influence of the genetic aetiology of obesity may be

exacerbated by non-genetic factors, such as dietary intake. Apart from rare obesity-

associated syndromes, the genetic influences seem to operate through susceptibility

genes. Such genes may increase the risk, however alone they are not essential or

sufficient to explain the development of disease. Candidate genes for obesity can be

chosen for their possible involvement in body fat composition, anatomical distribution

of fat, food intake and energy metabolism and expenditure. Implicit to the susceptible-

Weight Status BMI (kg/m2) Risk Underweight ≤ 18.5 Increased

Normal 18.5 - 24.9 Normal Overweight 25.0 - 29.9 Increased

Obese 30.0 or above High


37

gene hypothesis is the role of environmental factors that unmask latent tendencies to

develop obesity. However, predictions about possible interactions between genes and

the environment are difficult because there may be a delay in an individual’s exposure

to an ‘obesogenic’ environment, and/or alterations in lifestyle and the uncertainty about

the precise timing of weight gain.

2.1.1 Mutations Associated with Obesity

Genes that predispose to obesity in humans and animals have already been identified

and indicate the importance of genetic factors that are associated with the development

of disease [11]. The protein produced from the leptin gene is involved in the regulation

of food intake and energy expenditure and mutations in this gene result in morbidly

obese humans and rats. Similarly, mutations in the leptin receptor exhibit the same

phenotype, however these mutations are very rare and there is little evidence that the

vast majority of overweight individuals carry mutations in leptin or its receptor.

Candidate genes associated with human obesity also include receptors that are important

in mechanisms of thermogenesis, such as β3-adrenergic-receptor gene and the family of

uncoupling proteins [2; 12]. Other factors involved in appetite regulation include

neuropeptides. These include neuropeptide Y and agouti-related protein, that stimulate

appetite and decrease metabolic rate respectively, and α-melanocyte stimulating

hormone (α-MSH) that inhibits appetite and increases metabolic rate. α-MSH acts

through a family of melanocortin receptors, mutations in which are relatively common

in severely obese individuals, representing approximately 3-5% of the obese population.

2.2 Metabolic Syndrome

The metabolic syndrome is associated with increased risk of type 2 diabetes and CVD

and is thought to be a major component of these modern day epidemics that affects at

least one in five adults. The metabolic syndrome is characterised by a cluster of

metabolic abnormalities including abdominal obesity, decreased HDL cholesterol,

elevated TGs, elevated blood pressure, impaired glucose regulation and

hyperinsulinaemia with underlying insulin resistance (Box 1) [13]. Although the

pathogenesis of the metabolic syndrome is poorly understood, it is likely that a

sedentary lifestyle and dietary factors combined with genetic factors contribute to its

development.


38

• Central obesity (defined as waist circumference ≥ 94 cm for men and ≥ 80 cm for women) plus any two of the following four factors: • raised serum triglyceride level (≥ 1.7mmol/L) • reduced serum HDL-cholesterol level (< 1.03mmol/L in males and < 1.29mmol/L in females), (or specific treatment for these lipid abnormalities) • raised blood pressure (systolic blood pressure ≥ 130mmHg or diastolic blood pressure ≥ 85mmHg), or treatment of previously diagnosed hypertension • impaired fasting glycaemia (fasting plasma glucose ≥ 5.6mmol/L), or previously diagnosed type 2 diabetes Box 1 – The 2005 International Diabetes Federation definition of the metabolic

syndrome [14; 15].

The most important feature of the metabolic syndrome is the association with type 2

diabetes and atherosclerotic CVD. Prospective studies have shown that individuals with

metabolic syndrome are twice as likely to die, three times more likely to suffer a

myocardial infarction [16] and five times more likely to develop type 2 diabetes than

those who do not [17]. In addition it has been estimated that approximately 29% of

Australians aged over 25 have the metabolic syndrome [18].

2.3 Type 2 Diabetes

Type 2 diabetes or non-insulin dependent diabetes is a slow onset disease arising most

often in older individuals [7], however the frequency of this disease is now increasing

among children [19]. Type 2 diabetes is one of the most pressing health problems in the

world today and accounts for up to 85-90% of all diabetic cases [20]. According to the

2004-05 National Heath Survey 582,800 Australians (approximately 3% of the

population) reported having type 2 diabetes and it is predicted that by the year 2010

approximately 1 million Australians will have developed it. In addition, the worldwide

incidence of type 2 diabetes is projected to increase from approximately 135 million in

1995 to 299 million in 2025 [21].

Type 2 diabetes is characterised by the chronic elevation of blood glucose levels above

normal range and a progressive deterioration of insulin regulation that ultimately results

in the development of insulin resistance. Further characteristics of type 2 diabetes and

insulin resistance include post prandial hyperglycaemia, increased hepatic glucose

production and abnormalities in carbohydrate, lipid and protein metabolism [22; 23; 24;

25]. Insulin resistance is initially characterised by hyperinsulinaemia that is followed


39

by a decrease in efficiency of insulin signalling of glucose metabolism in liver, muscle

and adipose tissue. Initially, hyperinsulinaemia compensates for this decrease in insulin

signalling, therefore preserving normal glucose tolerance. However, this is followed by

either increases in insulin resistance or decreases in insulin secretory response, or both,

that results in the development of impaired glucose tolerance and hyperglycaemia.

Diagnosis of type 2 diabetes generally occurs after 40 years of age and many diabetics

are obese. It is estimated that up to 44% of type 2 diabetics within Australia are obese

[23]. In addition, type 2 diabetes is associated with a 2- to 4-fold increased risk of

developing CVD [26] and is the major cause of mortality in diabetic patients,

accounting for up to 80% of all deaths [27; 28; 29]. This has been attributed to the

clustering of several risk factors including insulin resistance, hypertension, obesity and

dyslipidaemia [30; 31]. Furthermore, poorly controlled or undiagnosed type 2 diabetes

can lead to further complications including retinopathy, nephropathy, peripheral and

autonomic neuropathy, stroke and CVD.

There is convincing evidence that type 2 diabetes has a genetic component as studies

show a high concordance rate among monozygotic twins of approximately 41-55% [31].

Similarly, offspring of parents suffering from type 2 diabetes and longitudinal studies of

families have shown that insulin resistance is a major risk factor for the development of

the disease [32; 33]. Monogenic forms of diabetes have been identified such as

maturity-onset diabetes of the young (MODY) and maternally inherited diabetes with

deafness (MIDD) however these cases are difficult to identify and are only account for a

small percentage of those suffering from diabetes. Although a genetic component has

been identified for a small number of those affected from diabetes, it does not explain

the majority of diabetes cases. However, recent evidence has shown that type 2 diabetes

is associated with environmental factors such as lifestyle and diet. Recent studies

suggest that type 2 diabetes is a polygenic disease involving numerous polymorphisms

in many genes that encode proteins involved in insulin signalling, insulin secretion and

intermediary metabolism in combination with the additional impact of environmental

factors, such as diet and fat intake.


40

2.3.1 Maturity-Onset Diabetes of the Young

MODY is a genetically heterogeneous monogenic form of type 2 diabetes. It is

estimated that these mutations account for 2-5% of those suffering from type 2 diabetes

[34]. These monogenic forms are characterised by early age of diagnosis, usual before

25 years of age, autosomal dominant inheritance and defective glucose-stimulated

insulin secretion. Clinical studies have shown that prediabetic MODY subjects have

normal insulin sensitivity but suffer from abnormal glucose-stimulated insulin secretion,

suggesting that pancreatic β-cell dysfunction may be the primary defect of the disorder.

A number of monogenic forms of diabetes have been identified involving mutations in

several different genes resulting in 6 subtypes of MODY. Mutations in these genes

provide insight into the cascade of transcriptional factors that control the expression

pancreatic β-cell gene expression.

MODY-1, MODY-3 and MODY-5 are characterised by mutations located in the

hepatocyte nuclear factor-4α (HNF-4α), HNF-1α and HNF-1β genes, respectively [35;

36; 37]. Mutations in these genes result in severe defects in glucose tolerance, glucose-

stimulated insulin secretion and renal function [38]. HNF-4α is also a known regulator

of glucokinase (GK) gene expression that may further contribute to the development of

MODY-1. Another subtype of MODY is caused by a mutation in the GK gene

(MODY-2) causing a mild form of type 2 diabetes due to a reduction in GK affinity for

glucose [39]. MODY-4 is characterised by mutations in the insulin promoter factor-1

gene which is involved in early embryonic development of the pancreas [40].

Phenotypes of MODY-4 range from normal to impaired glucose tolerance to overt type

2 diabetes [41]. Finally, MODY-6 results from a mutation in the NEUROD1 gene that

is involved in the development and function of pancreatic islet cells [42]. However, the

identification of these rare mutations does not directly identify genetic causes of obesity

and diabetes in the population as a whole. This suggests that environmental factors,

such as diet, combined with a predisposed genetic background may be necessary to

result in the development of type 2 diabetes.

2.4 Risk Factors Associated with Obesity, Metabolic Syndrome and Type 2

Diabetes

The first CVD associated with obesity and type 2 diabetes to be identified was coronary

artery disease (CAD) [43]. A second group of disorders now threatens to replace it as a


41

major health problem in Western societies, the complications of obesity, which includes

insulin resistance, hyperglycaemia, dyslipidaemia and hypertension [10]. A large

increase in body fat is accompanied by profound changes in physiological functions.

Generalised obesity results in alterations in total blood volume and cardiac function,

whereas the distribution of fat around the thoracic cage and abdomen restricts

respiratory expiration altering respiratory function. The intra-abdominal visceral

deposition of adipose tissue, which characterises upper body obesity, is a major

contributor to the development of hypertension, elevated plasma insulin concentrations

and insulin resistance, dyslipidaemia and type 2 diabetes [44]. In addition, different fat

deposits vary in their responsiveness to hormones that regulate lipolysis which also

varies according to fat distribution [45]. Cortisol may also contribute to enhanced

lipolysis by further inhibiting the anti-lipolytic effect of insulin. These factors all

contribute to an exaggerated release of free fatty acids (FAs) from abdominal adipocytes

into the portal system. Free FAs have a deleterious effect on insulin signalling in the

liver and contribute to increased hepatic gluconeogenesis and hepatic glucose release

that is observed in obesity.

Patients with type 2 diabetes are at high risk of developing a range of debilitating

complications that can lead to premature disability and death. Mortality rates are two to

three times higher among diabetic patients than in the rest of the population.

Approximately 75% of deaths among patients with type 2 diabetes are due to CHD,

with such patients experiencing a more than doubled risk of heart attack or stroke [27;

28]. In addition, microvascular complications can result in nephropathy and is a leading

cause of renal disease in diabetics [46]. Furthermore, as many as 40% of non-insulin

diabetics develop evidence of hepatic steatosis, or ‘fatty liver’, which is a condition that

leads to hepatic fibrosis and cirrhosis in a subset of individuals [47].

2.4.1 Insulin Resistance

Insulin resistance is characterised by increases in blood insulin levels and an inability to

suppress hepatic glucose production. Insulin stimulates the removal of blood glucose

and inhibits gluconeogenesis and the release of glucose by the liver and acts to prevent

the breakdown of TGs to free FAs in adipose tissue. However, insulin resistance results

in impaired glucose tolerance via a number of mechanisms including resistance to

peripheral glucose uptake and metabolism, impaired glycogen synthesis and increased


42

gluconeogenesis in the liver. This can develop as a result of a number of factors such as

reduced number of insulin receptors, impaired insulin receptor binding or a disruption in

post-receptor insulin-signalling transduction.

Figure 2.1 – Fatty acid intake and mechanism of insulin resistance [48].

Hepatic lipid accumulation is associated with the development of insulin resistance and

results in an impaired suppression of hepatic glucose output by insulin (Figure 2.1)

[49]. The accumulation of hepatic lipids appears to be most likely due to an increased

delivery of TGs from adipose tissue and/or dietary FAs to the liver [50]. In obese

individuals, especially those with high levels of abdominal obesity, hypertension and

dyslipidaemia, the ability of insulin to exert these effects is impaired. In addition,

individuals predisposed to type 2 diabetes have a compromised ability of pancreatic β-

cells to secrete insulin, resulting in incomplete suppression of hepatic glucose

production increasing levels of hyperglycaemia [51]. In addition, increased portal free

FA flux to the liver stimulates gluconeogenesis further contributing to the development

of hyperglycaemia [52].

Insulin resistance has been shown to be the best predictor of diabetes and is the central

and underlying feature of type 2 diabetes [53] and is caused by a number of factors

including obesity, sedentary lifestyle, pregnancy, hormone imbalance and dietary intake

[22; 23]. Insulin resistance has been shown to correlate with CAD [54; 55; 56] and


43

hyperinsulinaemia and is a positive independent risk for CHD [57]. Insulin resistance

also contributes to the development of cardiovascular risk factors, including

dyslipidaemia, hypertension, type 2 diabetes and impaired fibrinolysis.

2.4.2 Hyperglycaemia

Hyperglycaemia is characterised by raised levels of circulating blood glucose levels. In

adults the normal blood glucose levels range from 4-8 mmol/l. Hyperglycaemia results

as a consequence of insulin resistance due to a decreased ability of tissues, such as the

liver and muscle, to take up, phosphorylate and metabolise glucose. In addition,

hyperglycaemia reduces nitric oxide (NO) availability, due to increases in oxidative

stress levels, thereby reducing the efficacy of an endothelium-derived vasodilator

system that participates in vasculature homeostasis [58]. Furthermore, hyperglycaemia

increases the levels of oxidation of LDLs and glycated LDLs. Oxidised LDLs are

important modulators of atherosclerosis and cardiovascular death that promote

inflammation and the formation of atheromatous plaques.

Acute hyperglycaemia has been shown to impair endothelial function [59] and patients

with poor long-term glycaemic control show more evidence of early atherosclerosis

[60]. Poor glycaemic control can result in an increase of microvascular disease, for

example, a 1% increase in glycated haemoglobin may result in a 70% increased

incidence of retinopathy [61]. In addition, circulating advanced glycation end-products

(AGEs) bind to plasma lipoproteins and delay their clearance, a mechanism that has

been implicated in dyslipidaemia and diabetic nephropathy.

2.4.3 Oxidative Stress

Oxidative stress plays a key role in the pathogenesis of vascular complications and in

type 2 diabetes. Hyperglycaemia-induced oxidative stress directly promotes endothelial

dysfunction via several mechanisms including glucose autoxidation, the formation of

AGEs and activation of the polyol pathway (Figure 2.2) [62]. Other circulating factors

that are elevated in diabetics, include free FAs and leptin, and contribute to increase

production of reactive oxygen species (ROS).


44

Figure 2.2 – Overview of reactive oxygen species sources in diabetes and their links to

atherosclerosis [62]. Abbreviations: oxLDL, oxidised LDL, FFA, free fatty acids, AGEs, advanced

glycation end-products, VSMC, vascular smooth muscle cells, ROS, reactive oxygen species.

Intracellular hyperglycaemia leads to increased levels of glucose autoxidation leading to

the overproduction of nicotinamide adenine dinucleotide (NADH) and flavin adenosine

dinucleotide. Excess NADH generates an increase in the mitochondrial proton gradient

and electrons are transferred to oxygen resulting in superoxide production [63]. It is

thought that mitochondrial-derived superoxide causes increased diacylglycerol synthesis

and subsequent protein kinase C activation [64].

AGE formation is the result of an irreversible non-enzymatic covalent bonding of

ketone or aldehyde groups of reducing sugars to free amino acid groups of proteins and

other molecules [65]. In diabetic patients, AGE has been implicated in atherosclerotic

lesions and tissue AGE concentrations increase with the severity of disease [66]. AGEs

are proposed to contribute to atherosclerosis by modifying the extracellular matrix and

circulating lipoproteins, as well as binding to the AGE receptor that is present on many

vascular cells [65]. This is mediated through AGE receptor production of ROS,

possibly via NAD(P)H oxidase [67], and the subsequent activation of transcription

factors and expression of inflammatory mediators [68; 69].

The polyol pathway also contributes to increased ROS generation through the

involvement of the enzymes aldose reductase and sorbitol dehydrogenase. The first


45

enzyme, aldose reductase, is responsible for the reduction of glucose to sorbitol using

NADPH. Under normal conditions this conversion of glucose to sorbitol is a minor

reaction, however during hyperglycaemia up to 30-35% of glucose is metabolised by

this pathway [70]. The activity of this pathway results in a decreased availability of

NADPH, which in turn reduces glutathione regeneration and NO synthase activity,

thereby increasing oxidative stress levels [64]. The second enzyme, sorbitol

dehydrogenase, oxidises sorbitol to fructose with the generation of NADH. This

increased NADH production can also induce mitochondrial superoxide production via

NAD(P)H oxidase activity [71].

2.4.4 Diabetic Dyslipidaemia

Diabetic dyslipidaemia is a cluster of potentially atherogenic plasma lipid and

lipoprotein abnormalities. In type 2 diabetics, dyslipidaemia is associated with impaired

endothelial function [72] and is an important and common risk factor for CVD [73].

CVD is the world’s leading cause of morbidity and mortality. Importantly,

dyslipidaemia frequently precedes type 2 diabetes, indicating that a disturbance of lipid

metabolism may be the primary event in the development of type 2 diabetes. The three

major characteristics of dyslipidaemia include increased levels of plasma TGs,

increased levels of small-dense LDL cholesterol and reduced concentrations of HDL

cholesterol [74; 75].

LDLs are also associated with endothelial dysfunction [76] and are an independent risk

factor for CHD [77]. LDLs are smaller and more-dense than HDLs and have an

increased tendency to undergo oxidation [78], especially when glycated in the presence

of hyperglycaemia and enhanced oxidative stress [79]. In addition to the reduction of

HDL cholesterol levels, the HDL particles are modified and are smaller and denser [80].

This alteration in HDL particle size is due to increased lipolysis of TG rich particles

[81].

2.4.5 Hypertension

The development of stroke and microvascular disease in diabetic patients is associated

with hypertension. Hypertension can be defined as a systolic blood pressure above 140

mmHg or a diastolic blood pressure above 90 mmHg (Expert panel on detection 2002).

The risk of hypertension is approximately five times higher among the obese population


46

and approximately two times higher in the diabetic population compared to non-obese

and non-diabetic populations, respectively [82; 83; 84]. In addition, up to two-thirds of

cases of hypertension are linked with excessive weight gain [85], and 85% of

hypertension arises in individuals with BMI values above 25 kg/m2. Hypertension is

associated with the development of microvascular complications, stroke and

atherosclerosis via trauma to arterial endothelium and possible contribution to plaque

growth. In Australia, 69% of diabetic patients have hypertension [86], identifying this

condition as a major contributor to cardiovascular mortality in type 2 diabetes [82; 83].

Hypertension has also been shown to be independently associated with insulin

resistance [87], and insulin resistance may precede the development of hypertension

[88]. Several mechanisms have been proposed to explain the association of insulin

resistance and hypertension that include an increased sympathetic nervous system

activity [89], proliferation of vascular smooth muscle cells, altered cation transport [90],

increased sodium reabsorption [91] and a deficiency in the production of NO [92].

2.4.6 Microvascular Complications

Microvascular complications associated with type 2 diabetes include retinopathy,

nephropathy and peripheral neuropathy that may lead to blindness, renal failure and

limb amputation, respectively [93]. Individuals with insulin resistance including those

suffering type 2 diabetes, visceral obesity and hypertension have a tendency to exhibit

impaired endothelium-dependent vasodilatation. Evidence suggests that endothelial

injury, activation and dysfunction are associated with early events in atherogenesis [94].

Hyperglycaemia, dyslipidaemia and hypertension can also cause damage to the

endothelium resulting in an imbalance in endothelial production of vasoconstrictors

when compared to vasodilators. In particular, there is a decrease in NO production

which has potent antiatherogenic affects including modulation of platelet aggregation

and adhesion, reduced lipid peroxidation, monocyte adhesion and vascular smooth

muscle cell proliferation [95].

Diabetic retinopathy is a leading cause of blindness and visual disability causing

damage to the small blood vessels in the retina, resulting in loss of vision. Retinopathy

is prevalent in about 15% of patients who have had type 2 diabetes for more than 15

years. In addition, approximately 2% of diabetic sufferers become blind, while about


47

10% develop severe visual handicap [96]. Nephropathy develops in approximately 20%

of people with type 2 diabetes. Abnormalities associated with nephropathy can be

detected in most patients who have had diabetes for five to ten years and are associated

with an increase in cardiovascular mortality [97; 98]. In addition, peripheral neuropathy

can cause sensory loss in feet and legs resulting in the loss of protective sensation which

is a leading cause for limb amputation [93].

2.5 Key Hormones Influencing Type 2 Diabetes

2.5.1 Insulin

Insulin is an anabolic hormone with powerful effects on a range of physiological

processes involving mitogenic and metabolic events. The most important and examined

role of insulin is its regulation of glucose homeostasis. The maintenance of normal

glucose metabolism requires a tightly coordinated control of insulin secretion and

action. Insulin is stored in granules in pancreatic β-cells and is secreted in response to

increasing plasma glucose levels [99]. Elevated insulin levels stimulate glucose uptake

in hepatic, skeletal and adipose tissue, increases in glycogen synthesis and

gluconeogenesis and inhibition of glycogenolysis, ultimately reducing plasma glucose

levels. Malfunction of either release of insulin by pancreatic β-cells (ie β-cell

dysfunction) or insulin action (ie peripheral insulin resistance) leads to the development

of type 2 diabetes.

Insulin is a member of a gene family that includes insulin-like growth factors I, II and

relaxin. The insulin gene is transcribed and translated as pre-proinsulin, which is

cleaved to produce insulin. Expression of the insulin gene is under the control of

glucose concentrations, in which glucose binds to a glucose response element

stimulating gene expression. Insulin is a major regulator of hepatic glucose metabolism

and controls the expression of specific hepatic genes. For example, the glucokinase

(GK) gene encoding the first enzyme involved in hepatic glycolysis is dependent on

insulin for its transcription [100; 101; 102]. In addition to these well established short-

term actions, insulin exerts a number of long term effects, many of which are mediated

by changes in gene regulation involved in amino acid uptake, lipid metabolism, cell

growth, development and survival [103].


48

2.5.2 Insulin Signalling

Insulin signalling and transduction involves a series of phosphorylation events that

occur through the activity of certain protein kinases [104; 105]. Insulin binds to the

insulin receptor (IR), which comprises of two extracellular α-subunits involved in

ligand binding and two intracellular β-subunits that transduce the insulin signal to the

cell. These subunits are linked by disulphide binds to form a heterodimeric complex

[106]. The β-subunits have intrinsic tyrosine kinase activity that, upon insulin binding,

activates intracellular signalling proteins by phosphorylation of tyrosine residues [107].

Figure 2.3 – Regulation of insulin signalling [108]. Abbreviations: INS – insulin, IGF –

insulin-like growth factor, IGF1R – insulin-like growth factor 1 receptor, PTB – phosphotyrosine-binding

domain, PH – pleckstrin homology domain, TNFαR – tumour necrosis factor α receptor, IL-6R –

interleukin-6 receptor, GLP-1r – glucagon-like peptide-1 receptor, pY – phosphotyrosine, pS –

phosphoserine, PKC – protein kinase C, E2 – ubiquitin conjugating enzymes, Jnk – c-Jun N-terminal

kinase,, for other abbreviations refer to text.

Insulin binding to its receptor stimulates receptor tyrosine autophosphorylation and

subsequent recruitment of the insulin-receptor substrate (IRS) (Figure 2.3) [109]. IRS-

1 is responsible for insulin action in muscle, while IRS-2 is specific for propagating the

insulin signal in the liver [110]. IR tyrosine phosphorylation facilitates the docking of

IRS through binding of the phosphotyrosine-binding domain. The C terminal of the IRS


49

contains numerous tyrosine and serine phosphorylation sites that bind common effector

enzymes including phosphoinositide 3-kinase (PI(3)K), the phosphatase SHP2 and the

tyrosine kinase fyn [108]. The PI(3)K is activated during the association with IRS

proteins and converts PI(4,5)P2 to PI(3,4,5)P3 that recruits protein kinase B (PKB) and

3-phosphoinositide-dependent kinase-1 (PDK1) to the plasma membrane where PDK1

activates PKB. PKB activation results in the phosphorylation of many substrates that

are involved in cell survival, regulation of growth and glycogen synthesis and the

control of gene expression.

Other mechanisms of insulin that effect the regulation of insulin signalling and the

development of insulin resistance include inflammation and activity of protein or lipid

phosphatases. Proinfammatory cytokines including interleukin-6 (IL-6) and tumour

necrosis factor-α (TNF- α) are secreted from leukocytes during inflammation and

adipose tissue. TNF-α regulates various kinases including the activation of c-Jun kinase

(Jnk) that phosphorylates serine residues of IRS-1 and IRS-2 resulting in the inhibition

of insulin-stimulated tyrosine phosphorylation [111]. In addition, IL-6 increases the

expression of genes that mediate ubiquitin-mediated degradation of IRS-1 and IRS-2

promoting insulin resistance. IL-6 induces the expression of SOCS proteins, SOCS1

and SOCS2 that recruit the ubiquitin based ligase, elongin B and C, into the IRS-protein

complex to mediate ubiquitinylation [112]. Ubiquitin-mediated degradation of IRS-1

and IRS-2 may be the mechanism of cytokine-induced insulin resistance that contributes

to diabetes and β-cell failure.

2.5.3 Leptin

The main physiological regulator of body weight is leptin. Leptin acts as an adiposity

signal in a negative feedback loop that regulates food intake and energy expenditure.

Leptin is produced predominantly by white adipose tissue and plasma leptin

concentrations correlate directly with the percentage of body fat [113]. The amount of

adipose tissue mass, bodyweight and appetite is controlled by leptin via receptors in the

hypothalamus and other tissues by decreasing food intake and increasing energy

expenditure and thermogenesis [114; 115].

Insulin secretion stimulates leptin release that results in a raised expression of lipolytic

genes. The role of leptin is to protect non-adipose tissues from non-oxidative


50

metabolism of FAs during time periods of over nutrition by increasing β-oxidative

metabolism of surplus FAs and reducing lipogenesis [116]. In addition, leptin has been

shown to repress acetyl CoA carboxylase (ACC) and fatty acid synthase (FAS) gene

expression which play a key role in lipid synthesis. At an individual’s stable weight the

amount of circulating leptin promotes a state in which food intake equals energy

expenditure. However, in obese humans, leptin signalling does not result in decreased

food consumption. This is due to leptin resistance or insensitivity. Environmental

factors such as a high fat diet have been shown to affect leptin sensitivity leading to

leptin resistance although the basis for this is poorly understood.

2.5.4 Leptin Signalling

Signal transduction of leptin signalling is dependent on the phosphorylation of the leptin

receptor, Ob-R. Ob-R is a single membrane spaning receptor of the cytokine-receptor

superfamily [117]. Five splice variants of the Ob-R have been identified that contain

truncated cytoplasmic domains designated Ob-RA, Ob-RC to Ob-RF [118; 119]. Ob-RB

is the long isoform that contains a 303 amino acid cytoplasmic domain that signals by

activating Janus kinase -2 (JAK-2). Activation of JAK-2 subsequently phosphorylates

the signal transducer and activator of transcription-3 (STAT3) [120]. Phosphorylation

of STAT3 initiates dimerisation and translocation into the nucleus and the induction of

gene expression [121].

In the hypothalamus, leptin binds to Ob-RB stimulating specific signalling cascades that

result in the inhibition of several orexigenic neuropeptides, while stimulating several

anorexigenic peptides. The down-regulation of orexigenic peptides by leptin includes

neuropeptide Y, melanin-concentrating hormone, orexins and agouti-related protein.

The anorexigenic neuropeptides that are up-regulated are α-melanocyte-stimulating

hormone, which acts on melanocortin-4 receptor, cocaine and amphetamine-regulated

transcript and corticotrophin-releasing-hormone [122].

2.6 Key Enzyme Involved in Insulin Action and Hepatic Glycolysis

2.6.1 Glucokinase

Key enzymes involved in lipid biosynthesis and glycolysis may also provide important

information about the mechanisms that lead to the development of obesity and type 2


51

diabetes. GK is the major regulatory enzyme of hepatic glucose metabolism,

controlling the supply of substrate to the glycolytic, lipogenic, glycogenic and pentose

phosphate pathway. GK is the liver specific member of the hexokinase family of

enzymes that catalyses the rate limiting step of glycolysis by phosphorylating glucose

resulting in the subsequent synthesis of glucose 6-phosphate (G-6-P). As GK regulates

hepatic glucose and lipid metabolism, changes in the regulation of GK may result in

significant changes in glycolysis and lipogenesis. This suggests that an impairment of

GK activity may play a major role in precipitating glucose intolerance and the

development of type 2 diabetes [123].

2.6.2 Regulation of Glucokinase

The regulation of GK activity is complex. The GK gene can be transcribed from two

different promoters. Extrahepatic expression is initiated from the β-cell specific

promoter localised 20 kilobases upstream of the gene, whereas hepatic expression is

controlled by the liver specific promoter adjacent to the GK gene [124; 125]. Together

these isoforms of GK act to co-ordinately regulate plasma blood glucose concentrations

and homeostasis [126]. In pancreatic β-cells, GK acts as a ‘glucose sensor’ ensuring

that insulin release is appropriate to the plasma glucose concentration in which glucose

phosphorylation is tightly coupled to insulin secretion (Weinhouse, 1976; Megalson and

Matchinsky, 1983) (Matchinsky et al, 1998). In liver, GK is thought to be essential for

the unique metabolic functions of this tissue and is subjected to both transcriptional and

post-translational control mechanisms. Under basal glucose concentrations (<5.5mM)

the majority of hepatic GK is bound to the GK regulatory protein (GKRP) in the

nucleus (16-181), however when subjected to high glucose concentrations (10-30mM),

GK is released from the GKRP and translocates into the cytoplasm where it exists in an

unbound state and becomes active (14,151). GK plays an important role in the

maintenance of blood glucose concentrations (Ferre et al, 1996), and impairment of GK

activity may play a significant role in precipitating glucose intolerance in response to a

high fat diet (Chrisholm and O’Dea, 1987).

Insulin and glucagon (via cAMP) both play a role in the regulation of expression of the

GK gene [100; 102; 127; 128; 129]. Insulin increases, whereas glucagon decreases, GK

gene transcription [130; 131]. After a meal, the increase in blood glucose leads to


52

induction of liver glycolysis, glycogenesis, and lipogenesis. In this situation, the

increasing plasma insulin concentrations stimulate GK synthesis and increases glucose

phosphorylation to G-6-P [132; 133]. Unlike hexokinases, GK is not inhibited by G-6-

P, therefore this metabolite could be involved in the stimulation of GK gene expression

in response to increases in blood glucose levels. Some studies performed in vitro on

cultured hepatocytes indicate that GK activation is necessary for the induction of

glycolysis and glycogen synthesis [134].

The transcriptional regulation of GK is under the control of a number of transcription

factors including sterol regulatory element binding protein-1c (SREBP-1c), liver X

receptor α (LXRα), HNF-4α and peroxisomal proliferator activated receptorγ (PPARγ).

Insulin-induced GK gene expression is mediated through SREBP-1c, a potent activator

of gene transcription [135; 136; 137]. This has been demonstrated by the identification

of two functional sterol regulatory elements (SREs) in the rat GK promoter [138]. In

addition, SREBP-1c basal expression levels are mediated by the induction of LXRα

[139; 140; 141]. Furthermore, a functionally active HNF-4α responsive element has

been identified in the rat GK promoter and has been shown to induce GK promoter

activity [142]. Recently, it has been shown that PPARγ can activate GK gene

transcription in response to increasing glucose concentrations [143].

In addition to changes in the rate of transcription of the GK gene, alterations in the

kinetic regulation of the protein can also affect its activity. The kinetic properties of GK

and the regulation of GK levels by insulin and glucagon may lead to a situation in which

GK has a key role in regulating and integrating glucose metabolism in the liver. In the

liver, but not the pancreas, GK activity is regulated by a 68 kDa GK regulatory protein

(GKRP), which competitively inhibits GK binding to glucose [144]. In the presence of

low (5 mM) concentrations of glucose, GK is bound to a GKRP in the nucleus of the

cell and is inactivated [145]. When glucose concentrations rise (>20mM) or in the

presence of a number of activators including sorbitol, fructose and fructose 1-phosphate,

GK and the GKRP dissociate. GK then translocates into the cytoplasm, and becomes

active, and consequently increases the rate of glucose phosphorylation [145]. In

addition, transgenic mice with additional copies of the GK gene exhibit increased

hepatic glucose metabolism and as a result, blood glucose concentrations are diminished


53

[146]. Conversely, ‘knock-out’ mice lacking the hepatic, but not the pancreatic GK

gene, exhibits mild hyperglycaemia and impaired glucose metabolism [146; 147]. This

data further support the importance of the role GK plays in the pathogenesis of type 2

diabetes.

2.6.3 Other Enzymes Involved in Glucose Metabolism

Key enzymes involved in lipid biosynthesis, fatty acid oxidation and glycolysis may

also provide important information about the mechanisms that lead to obesity and

diabetes. These enzymes include acetyl CoA carboxylase (ACC) and fatty acid

synthase (FAS), involved in lipid biosynthesis and GK, the initial step of glycolytic

pathway. GK is the major regulatory enzyme of hepatic glucose metabolism,

controlling the supply of substrate to the glycolytic, lipogenic, glycogenic and pentose

phosphate pathway. GK is a member of the hexokinase family of enzymes that

catalyses the synthesis of glucose-6-phosphate (G-6-P) from glucose and ATP. GK is

found predominantly in hepatocytes and pancreatic β-cells and plays an important role

in the maintenance of blood glucose concentrations [126]. This suggests that an

impairment of GK activity may play a major role in precipitating glucose intolerance in

response to a high fat diet [123; 148].

Long-chain fatty acids and their derivatives are not only constituents of cellular

structures, they also function as regulatory molecules affecting all phases of cellular

activities. ACC is the rate-limiting enzyme in the biogenesis of long-chain fatty acids

[149]. ACC catalyses the carboxylation of acetyl-CoA that results in the production of

malonyl-CoA. Malonyl-CoA is then used for long-chain fatty acid synthesis by the

multifunctional enzyme, FAS, which catalysis the synthesis of palmitic acid [150; 151].

Genes belonging to the lipogenic pathway have a more complex regulation than

glycolytic genes because their expression depends on both high insulin and glucose

concentrations and glucose metabolism regulated by GK [133].

2.7 Current Treatments of Type 2 Diabetes

2.7.1 Lipid-Lowering Agents

Two classes of lipid-lowering agents are currently being used as therapeutic treatments

to decrease the risk of CAD, myocardial infarction and stroke in type 2 diabetics. The


54

first class, fibrates, exhibit lipid-modulating effects that are mediated through their

capability to mimic the structure of free FAs [152]. PPARα is the molecular target of

fibrates, such as gemfibrozil, which is used in the treatment of hypertriglyceridaemia

[153; 154]. Fibrate binding and activation of PPARα alters the expression of genes

involved in HDL-cholesterol metabolism including apo-AI and apo-AII, lipoprotein

lipase, scavenger receptor B1 and ABCAI. In conditions of dyslipidaemia, fibrates

promote a reduction in VLDL and LDL and increase HDL fractions attenuating an

atherogenic lipid profile [155].

A second class of lipid-lowering agents, statins, have been shown to be effective in

reducing cardiac death and CAD in diabetic subjects [156; 157]. Statins are 3-hydroxy-

3-methylglutaryl-CoA reductase inhibitors and act to lower cholesterol synthesis.

Statins prevent atherosclerotic macrovascular complications and postpone the

development of microvascular complications, such as nephropathy and retinopathy. In

addition, statins may attenuate inflammation, oxidative stress, coagulation, platelet

aggregation and improve insulin resistance, fibrinolysis and endothelial functions and

help to prevent thrombosis [158; 159]. Increasing evidence suggests that statins are the

current treatment of choice to prevent vascular complications in diabetic patients with

hypercholesterolemia [160].

2.7.2 Hypoglycaemic Agents

Three classes of pharmacological agents have been recommended for the treatment of

hyperglycaemia that include: 1) Sulfonylureas and thiazolidinediones (act to increase

insulin sensitivity), 2) Biguanides (acts to suppress hepatic glucose production) and 3)

α-glucosidase inhibitors (alter gastrointestinal tract glucose absorption).

Sulfonylureas bind to an ATP-dependent K+ (KATP) channel on the cell membrane of

pancreatic beta cells. This inhibits a tonic, hyperpolarizing outflux of potassium, which

causes the electric potential over the membrane to become more positive. This

depolarization opens voltage-gated Ca2+ channels. The rise in intracellular calcium

leads to increased fusion of insulin granulae with the cell membrane, and therefore

increased secretion of (pro)insulin. There is some evidence that sulfonylureas also

sensitize β-cells to glucose, that they limit glucose production in the liver, that they

decrease lipolysis (breakdown and release of fatty acids by adipose tissue) and decrease

http://en.wikipedia.org/wiki/Adenosine_triphosphate

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http://en.wikipedia.org/wiki/Beta_cell

http://en.wikipedia.org/wiki/Depolarization

http://en.wikipedia.org/wiki/Calcium

http://en.wikipedia.org/wiki/Insulin

http://en.wikipedia.org/wiki/Liver

http://en.wikipedia.org/wiki/Fatty_acid

http://en.wikipedia.org/wiki/Adipose_tissue


55

clearance of insulin by the liver. Sulfonylureas exert their beneficial effects on glucose

homeostasis by increasing insulin sensitivity and reducing blood glucose level [161;

162]. In addition, sulfonylureas affect lipid metabolism by elevating plasma HDL-

cholesterol by reducing the number of small-dense LDL particles and plasma TG levels.

In monotherapy, sulfonylureas induce a significant decrease of fasting blood glucose

[163; 164] that is maintained over time [165].

Thiazolidinediones, also known as "glitazones", bind to PPARγ, a type of nuclear

regulatory proteins involved in transcription of genes regulating glucose and lipid

metabolism. These PPARs act on Peroxisome Proliferator Responsive Elements

(PPRE). The PPREs influence insulin sensitive genes, which enhance production of

mRNAs of insulin dependent enzymes. The final result is better use of glucose by the

cells.

The biguanide, metformin, reduces intestinal glucose absorption, increases peripheral

tissue uptake of circulating blood glucose and reduces hepatic glucose production. In

addition, metformin reduces insulin requirements for adequate glucose metabolism,

though has little effect on insulin secretion [166; 167]. Acarbose is an inhibitor of the

α-glucosidase enzyme that reduces postprandial blood glucose by suppressing

carbohydrate absorption from the small intestine [168].

2.7.3 Hypertensive Agents

Antihypertensive therapy in diabetic individuals includes the administration of

angiotensin converting enzyme (ACE) inhibitors. ACE inhibitors offer a cardio

protective effect that may be related to their beneficial effects on endothelial function.

They act to prolong the action of bradykinin via the inhibition of the enzymatic

breakdown leading to increased blood flow. ACE inhibitor therapy may also improve

insulin resistance associated with hypertension and type 2 diabetes, this is possibly due

to the role of bradykinin in insulin-stimulated glucose uptake.

2.8 Dietary Lipids and a High Fat Diet

2.8.1 Lipids

Lipids are a heterogeneous group of water insoluble and organic molecules that consist

of long-chain FAs. In the body, lipids are utilised as an energy source, cellular

http://en.wikipedia.org/wiki/Thiazolidinedione

http://en.wikipedia.org/wiki/Peroxisome_proliferator-activated_receptors


56

membranes components and precursors of molecules involved in numerous biological

processes including steroid hormones, vitamins, bile acids and eicosanoids. Major

forms of clinically important lipids found in human plasma include cholesterol,

cholesteryl esters, TGs, phospholipids and glycolipids. TGs are stored within adipose

tissue which supplies other tissues with energy in the form of free FAs. Lipids are

continually synthesised and metabolised in cells such that their steady-state levels are

maintained. When the metabolism of lipids is disturbed or disrupted various

pathological disorders can develop including dyslipidaemia, obesity and type 2 diabetes.

2.8.2 Fatty Acid Homeostasis

In the fed state, which in humans is up to four hours after a meal, carbohydrates and

lipids enter the circulation in the form of glucose and chylomicrons, respectively. The

majority of dietary glucose is taken up by the liver for glycogen synthesis or

metabolised via glycolysis (Figure 2.4). In the fed state, hepatic GK is induced by

increasing insulin levels via insulin-induced activation of SREBP-1c. Increased GK

enzyme activity promotes the metabolism of glucose via glycolysis to produce to acetyl-

CoA [136; 137]. Acetyl-CoA is a precursor for lipogenesis and the production of FAs.

The FAs that are produced via lipogenesis are subsequently converted to TGs and

packaged into VLDLs for transport to adipose tissue for storage.

Long-chain FAs and their derivatives are not only constituents of cellular structures,

they also function as regulatory molecules affecting all phases of cellular activities.

ACC is the rate-limiting enzyme in the biogenesis of long-chain FAs [149]. ACC

catalyses the carboxylation of acetyl CoA resulting in the generation of malonyl CoA.

Malonyl CoA is then used for long-chain FA synthesis by the multifunctional enzyme,

FAS, which catalysis the synthesis of palmitate [150; 151]. Genes belonging to the

lipogenic pathway have a more complex regulation than glycolytic genes because their

expression depends on both high insulin and glucose concentrations and glucose

metabolism regulated by GK [133].


57

Figure 2.4 – Glycolytic and lipogenic pathways in the liver (adapted from [169]). Abbreviations: GK, glucokinase, L-PK, liver pyruvate kinase, ACC, acetyl CoA carboxylase, FAS, fatty

acid synthase.

The energy requirement of non-adipose tissues is tightly coupled to FA delivery. For

example, plasma free FA levels rise during exercise and fasting to meet metabolic

energy needs. In metabolically active tissues, an increase in the level of FA oxidation

results in a decreased level of non-oxidised FAs present in these cells. However, during

chronic over-nutrition and decreased metabolic activity, FA influx into tissues may

exceed FA usage. This leads to a compensatory up-regulation of FA oxidation that is

required to maintain intracellular FA homeostasis. It has been suggested that a surplus

of FAs may up-regulate PPARα and oxidative machinery to prevent an over-

accumulation of non-oxidised lipids [170; 171; 172; 173; 174]. PPARα is a member of

the family of transcription factors involved in the up-regulation of FA oxidative

enzymes including, carnitine palmitoyl transferase-1 and acyl CoA oxidase [170; 171].

2.8.3 High Fat Diet, Hepatic Glycolysis and Gluconeogenesis

The saturated fat, palmitate, has been shown to inhibit glycolysis in liver by a

mechanism also associated with glucose sparing [175]. Berry et al. [176] have shown


58

that the inhibition of hepatic glycolysis during FA oxidation is associated with

substantial enhancement of flux through the glucose/G-6-P cycle, and consequent

glucose sparing. Glucose sparing is the process whereby glucose is taken up by the

liver and phosphorylated to G-6-P, but is immediately recycled to glucose without

undergoing further metabolism [176]. A role of glucose cycling has been implicated in

the development of hyperglycaemia and is associated with type 2 diabetes [177; 178].

In hepatocytes from streptozotocin-induced insulin-dependent diabetic rats, increased

rates of glucose cycling partly resulted in elevated rates of endogenous FA oxidation

[179]. As endogenous FA oxidation may be increased in the liver of high fat fed rats, it

is possible that glucose cycling may be enhanced, thereby contributing to the

development of hyperglycaemia.

Hue et al. suggest that the catalysis of glucose phosphorylation by GK is inhibited by

fatty acyl-CoA [175; 180]. The addition of FA also stimulates gluconeogenesis in liver

cells that is due to an enhanced rate of FA oxidation increasing the concentration of

acetyl-CoA. Excess acetyl CoA allosterically activates pyruvate carboxylase, the

enzyme that catalyses the conversion of pyruvate to oxaloacetate. It has been suggested

that the stimulation of gluconeogenesis by FAs is a result of the activation of this

enzyme [181]. In addition, pyruvate dehydrogenase (PD) is allosterically inhibited by

acetyl-CoA [182]. PD is responsible for the conversion of pyruvate to acetyl CoA. A

decreased in PD activity results in an increased concentration of pyruvate, a precursor

for gluconeogenesis. Therefore, this may contribute to an increase in the rate of glucose

synthesis from the gluconeogenic precursors, pyruvate and lactate.

The inhibitory effects of FA oxidation on hepatic glycolysis and glucose utilisation have

been associated with a decrease in the cellular concentration of fructose 1,6-

bisphosphate [175; 176]. This decline has been attributed to an inhibition of 6-

phosphofructo-1-kinase contributing to decreases of flux through glycolysis [183].

Similarly the effect of the GKRP is greatly reinforced by fructose 6-phosphate and

antagonised by fructose 1, 6-bisphosphate. This results in the increased activity of

GKRP to sequester GK inhibiting enzyme translocation to the cytoplasm. This

ultimately reduces the amount of active cytoplasmic GK available to phosphorylate and

metabolise glucose. A reduction in hepatic GK activity has been shown to contribute to

the metabolic perturbations seen in high fat fed animals [127; 128; 145].


59

2.8.4 High Fat Diet and Insulin Resistance

Evidence strongly suggests that insulin resistance and type 2 diabetes arise from both

the combination of multiple genetic and environmental factors [7; 184]. One factor that

may contribute to the increasing incidence of type 2 diabetes is the consumption of a

diet that is high in fat, particularly saturated fats [128; 185]. The accumulation of

intracellular FAs, especially in hepatic tissue, appears to play an important role in the

pathogenesis of insulin resistance [50]. Insulin resistance, induced as a result of a high

intake of saturated fat, impairs glucose uptake and metabolism in a number of tissues.

In liver, a high fat diet causes hyperglycaemia and is associated with a loss of the

insulin-induced inhibition of hepatic gluconeogenesis and insulin-induced stimulation of

hepatic glycolysis [186]. In muscle, a high fat diet decreases insulin-stimulated glucose

uptake and reduces insulin-stimulated oxidative and non-oxidative glucose disposal

[123; 127]. In adipose tissue, a high fat diet has been associated with a decrease in

insulin-stimulated glucose uptake, although this does not appear to play a major role in

diet-induced hyperglycaemia [187]. This may not be a direct effect of insulin

insensitivity but may be associated with an increase in the supply of FA to the liver

[128; 188].

Prolonged exposure to long-chain FAs reduces glucose phosphorylation and glycogen

synthesis in liver. Decreased glucose metabolism leads to elevated rates of lipolysis

resulting in increased release of free FAs. Free FAs have a negative effect on the action

of insulin on the liver, which in turn results in increased gluconeogenesis and systemic

dyslipidaemia. This is believed to be due to increasing levels of long-chain FAs being

incorporated into the plasma membrane of the cell, resulting in a decreased ability of

insulin to bind its receptor in target tissues and transduce a signal [189]. These factors

contribute to the prevailing systemic hyperinsulinaemia and consequently to decreased

skeletal insulin sensitivity with reduced glucose uptake and decreased glucose

stimulated insulin release [190; 191].

The elevation in plasma free FA concentration leads to an inappropriate maintenance of

glucose production and an impairment of hepatic glucose utilisation (impaired glucose

tolerance). Reduced hepatic clearance of insulin leads to increased peripheral

(systemic) insulin concentrations and to a further down-regulation of insulin receptors.

In the initial phases of this process, the pancreas can respond by maintaining a state of


60

compensatory hyperinsulinaemia preventing glucose tolerance. With increasing plasma

concentrations of free FAs, the insulin resistant individual cannot continue to maintain

this state of compensatory hyperinsulinaemia and hyperglycaemia prevails.

Hyperinsulinaemia and insulin resistance are both significant correlates of a

dyslipoproteinaemic state and contribute to the characteristic alterations of plasma lipid

profile associated with obesity: elevated fasting plasma triglyceride concentration,

reduced HDL-cholesterol, marginal elevations of cholesterol and LDL-cholesterol

concentrations and increased number of apo-B-carrying lipoproteins [2].

Circulating free FAs are elevated in insulin-resistant states and have also been suggested

to contribute to insulin resistance in muscle by reducing glucose transport or inhibiting

glucose phosphorylation [192]. Elevated free FA levels have been shown to be

associated with a reduction in insulin-stimulated insulin-receptor substrate-1 (IRS-1)

phosphorylation and IRS-1-associated PI(3)K activity [192]. The reduced PI(3)K

activity may be due to a direct effect of intramuscular free FAs on PI(3)K or alterations

in upstream insulin signalling events. This reduction in kinase activity is believed to be

responsible for perturbations in the translocation of the glucose transporter 4 (GLUT4)

to the plasma membrane and may be responsible for a decreased level of glucose

uptake. A decreased level of glucose transport and phosphorylation causes a reduction

in muscle glycogen synthesis and is paralleled by a decrease in glucose oxidation. In

addition, recent studies have shown that an increase in saturated FA [193; 194] and

refined carbohydrate intake and decreased dietary fibre intake [195] can also result in

reduced insulin sensitivity and abnormal glucose tolerance.

Saturated FAs decrease insulin sensitivity by decreasing membrane fluidity and

reducing the translocation and activity of GLUT4. Increased FA uptake coupled with

deficient FA oxidation lead to cellular damage and lipotoxicity as a result of increased

TG accumulation. High levels of circulating FAs increase FA translocase expression

and FA transport proteins within muscle tissue. This leads to lower FA oxidation due to

decreased carnitine palmitoyl transferase activity as a result of increased malonyl CoA

concentrations, reduced glycogen synthase activity and impairment of insulin signalling

and glucose transport [48].


61

2.9 Transcription Factors Involved in Fatty Acid Signalling

2.9.1 Sterol Regulatory Element Binding Protein-1c

SREBPs have been established as a family of transcription factors that regulate the

expression of a range of enzymes responsible for endogenous cholesterol, TG, FA and

phospholipid synthesis [137; 196]. SREBPs belong to the basic helix-loop-helix-

leucine zipper (bHLH-LZ) family that consist of three isoforms SREBP-1a, -1c and -2.

SREBP-1a and -1c are produced from the same gene through alternative transcription

start sites and SREBP-2 is transcribed from a separate gene. In liver, SREBP-1c is the

predominantly expressed isoform and is a major target of insulin action inducing

glucose metabolism and regulation of FA synthesis [137]. In contrast, SREBP-2 is

relatively selective in transcriptionally activating cholesterol biosynthetic genes [197].

SREBPs are synthesised as membrane bound precursors localised to the endoplasmic

reticulum and nuclear envelope. Activation of SREBP occurs through the sequential

two-step cleavage process, catalysed by the SREBP cleavage activating protein, to

release the mature NH2-terminal active domain containing the bHLH-LZ domain. The

bHLH-LZ domain contains a nuclear localisation signal that binds directly to importin

and facilitates SREBP transport into the nucleus, where the nuclear form of SREBP is

designated (nSREBP). Within the nucleus, nSREBP binds to the sterol regulatory

element (SRE) which is an enhancer region present in target genes that is able to

activate transcription.

Increased levels of SREBP-1c protein cleavage and subsequent activation are

responsible for increased levels of glucose metabolism and lipogenesis. SREBP-1c

expression is decreased during fasting but increases markedly upon carbohydrate

feeding. Insulin has been shown to induce SREBP-1c transcription leading to increases

of both ER membrane-bound precursors and the nuclear form of the transcription factor

[198]. The effects of insulin on SREBP-1c expression are mediated by a PI(3)K

dependent pathway [198; 199]. However, the downstream effectors remain unclear,

however evidence suggests that both PKB/Akt [199; 200] and PKCλ may be involved

[201]. The insulin-induced activation of SREBP-1c explains the ability of insulin to

enhance the conversion of glucose to FAs.


62

SREBP-1c transcription can also be induced by the activation of LXRα to generate FAs

required for the formation of cholesterol esters to buffer free cholesterol concentrations

[202]. LXRα mediates basal expression levels of SREBP-1c via retinoic acid receptor

(RXR) and LXR DNA binding sites in the SREBP-1c promoter [139; 140; 141]. In

addition to the regulation of SREBP-1c through LXRα activation, the LXR response

elements are required for the full induction of SREBP-1c by insulin. This has lead to

the hypothesis that SREBP-1c induction by insulin may be due to increased activity of

LXRα though insulin-induced increases in the production of LXR ligands [203].

2.9.2 Liver X Receptor α

LXRα is a nuclear hormone receptor with high levels of hepatic expression and is

activated by oxysterols and derivatives of the cholesterol synthetic pathway. The role of

LXRα is to induce the expression of a number of genes involved in cholesterol efflux

and clearance [204]. LXRα expression is predominately restricted to tissues involved in

lipid metabolism including liver, kidney, small intestine, spleen and adipose tissue

[205]. LXRs bind to their target DNA sequence as a heterodimer with RXR that can be

activated by ligands for either LXR or RXR. LXRs control the expression of several

genes required in cholesterol metabolism including CYP7A1, that is involved in the

conversion of cholesterol to bile salts, and other genes involved in cholesterol efflux

including ATP-binding cassette A1 transporter [206] and apolipoprotein E [207].

LXRs also modulate lipoprotein metabolism through the control of modifying enzymes

such as lipoprotein lipase [208], cholesterol ester transfer protein [209], and

phospholipid transfer protein [210]. In addition, LXRα has been shown to play a role in

the up-regulation of FA and TG synthesis and secretion by directly inducing SREBP-1c

gene expression, thereby regulating the expression of genes inducing FAS, stearoyl-

CoA desaturase-1 (SCD-1) and ACC [211]. It has also been found that LXRα can

directly stimulate FAS [212] and ACC [213] transcription through LXRα regulatory

elements present in their promoters. Recent evidence indicates that LXRα may also act

as an insulin mediating factor in the liver and play a key role in insulin-stimulated

lipogenesis [214]. This possibility is due to the fact that SREBP-1c is a LXRα target

and that LXR has been shown to induce basal SREBP-1c gene expression [139; 140;


63

141]. Due to these observations, it has been postulated that maximal stimulation of

lipogenic gene expression requires the activation of gene transcription from both

SREBP-1c and LXRα.

2.9.3 Hepatocyte Nuclear Factor-4α

HNF-4α is a member of the nuclear receptor family of transcription factors and is highly

expressed in the liver and acts as a positive transcriptional regulator of many hepatic

genes [215]. HNF-4α binds DNA as a homodimer and its activity is modulated by the

high affinity binding of long chain fatty acyl-CoA [216]. In addition, HNF-4α is

acetylated [217], phosphorylated [218] and can bind SMADS 3 and 4, suggesting that

its activity may be controlled by multiple pathways [219]. Gene knock-out studies of

the HNF-4α gene disrupt a large number of genes involved in many aspects of mature

hepatocyte function. This evidence suggests that HNF-4α acts as a positive

transcriptional regulator of hepatic genes that involve the control of energy metabolism,

xenobiotic detoxification, bile acid synthesis and serum protein production [220].

Recently, HNF-4α has been suggested to play a broader role in the hepatic and

pancreatic regulation of glucose homeostasis and can transcriptionally induce hepatic

GK gene expression [142]. This suggests a potential role of HNF-4α regulation in the

development of type 2 diabetes.

2.9.4 Peroxisomal Proliferator Activated Receptor α

Peroxisomal proliferator-activated receptors (PPARs) are a family of nuclear hormone

receptors that function as transcription factors. PPARs act through target genes to

regulate diverse aspects of lipid metabolism, including FA oxidation, adipocyte

development, lipoprotein metabolism and glucose homeostasis [221]. PPARs bind the

promoter as a heterodimer bound to RXR and modify target gene transcription after

binding to specific peroxisomal proliferator response elements (PPREs) [165].

Activation of gene transcription can take place through ligand binding of either the

PPAR or RXR receptor, however binding of both ligands induces a more potent

activator of transcription [222]. Target genes of PPARs belong to lipid transport and

metabolism pathways and are subjected to regulation of gene transcription by FAs.

PPARs act as FA sensors and transduce nutritional stimuli into changes in gene

expression.


64

The PPARα isoform is highly expressed in tissues displaying a high catabolic rate of

FAs such as liver, skeletal muscle, heart and kidney [221]. PPARα regulates a number

of genes involved in β-oxidation and is also a major regulator of energy homeostasis.

These genes participate in aspects of lipid catabolism such as FA uptake though

membranes, FA binding in cells, FA oxidation (in microsomes, peroxisomes and

mitochondria) and lipoprotein transport and assembly. Activation of PPARα increases

β-oxidation stimulating energy production but also shortens long-chain fatty acids

preventing lipid accumulation and toxicity. In liver, PPARα activation leads to the up-

regulation of FA transport protein and long-chain acyl-CoA synthetase genes [154;

223]. In addition, PPARα increases apo-AI and apo-AII while decreasing apo-CIII

levels resulting in increased HDL levels and decreased TG levels [224].

In the fasting state, the energy sources of the body shift from carbohydrate and lipid

metabolism towards lipid metabolism. FAs stored during feeding are released from

adipocytes and taken up by the liver and are oxidised to acetyl-CoA and subsequently

ketone bodies. These processes are strongly stimulated by PPARα, expression of which

is elevated during fasting [225]. In addition, FAs are ligands for PPARs, therefore it is

possible that FAs released from adipose tissue can stimulate their own metabolism by

PPARα activation. Experiments with PPARα null mice show that PPARα is important

in the hepatic response to fasting. During fasting, these mice suffer from defects in FA

oxidation and ketogenesis. This results in elevated plasma free FAs, hypoketonaemia,

hypothermia and hypoglycaemia [225; 226]. The hypoglycaemia emphasises the

important interplay between FA and glucose metabolism in energy homeostasis.

Interestingly, PPARs take an important part in the control of factors involved in the

development of cardiovascular disease, particularly in patients with type 2 diabetes.

These factors include the regulation of glucose and lipid metabolism, endothelium

function, inflammation, thrombosis and fibrinolysis. Thus, the use of PPARs agonists in

clinical practice has not only the potential to improve glucose and lipid metabolism but

also to reduce atherosclerosis in diabetic patients.


65

2.9.5 Fatty Acid Gene Regulation

Dietary FAs regulate gene expression by controlling the activity or abundance of key

transcription factors. Investigations into the FA regulation of hepatic gene expression

have identified that SREBP-1c, LXRα, HNF-4α and PPARα are important in the

control of glycolysis and lipogenesis (Figure 2.5) [227; 228]. Non-esterified FAs

directly bind PPARα, HNF-4α, RXR and LXRα acting like hydrophobic hormones that

control gene expression [227]. However, FAs can also regulate other transcription

factors, such as SREBP-1c, through indirect mechanisms. Recently, SREBP-1c and

PPARα have been established as key targets for polyunsaturated FAs (PUFAs) in the

control of hepatic gene expression, in which PPARα induces FA oxidation and SREBP-

1c induces FA synthesis.

Figure 2.5 – Regulation of hepatic gene expression by non-esterified fatty acids [228]. Abbreviations: ChREBP, carbohydrate response element binding protein, FABP, fatty acid binding

protein, HNF-4α, hepatocyte nuclear factor-4α, LXR, liver X receptor, NEFA, non-esterified fatty acid,

PPAR, peroxisomal proliferator activated receptor, RXR, retinoic acid receptor.

Dietary PUFAs have been well established as negative regulators of hepatic lipogenesis

[229; 230]. Shimano et al. (1999) showed that suppression of lipogenic gene expression

by PUFAs in the liver was primarily due to a decrease in the mature form of SREBP-1c


66

[231]. This suppression of hepatic gene expression is caused by three independent

mechanisms. Firstly, the abundance of the mature SREBP-1c protein in the liver is

decreased by dietary PUFA exposure primarily at a posttranslational level. PUFA does

not accelerate the degradation of SREBP-1c mature protein, however it interferes with

the proteolytic cleavage of mature SREBP-1c protein resulting in an immediate

suppression of lipogenic gene transcription [232; 233; 234]. Secondly, PUFAs

accelerate the decay of SREBP-1c mRNA which in turn lowers the hepatic content of

SREBP-1c precursor [232]. Thirdly, the basal transcription of the SREBP-1c gene

requires an endogenous sterol that activates LXR. The LXRs enhance transcription of

the SREBP-1c gene by binding to a consensus recognition sequence in the enhancer

region.

This anti-lipogenic action of PUFA reflects decreases in mRNA levels of hepatic

enzymes including GK, ACC, FAS, SCD, ATP citrate lyase, malic enzymes, G-6-P

dehydrogenase and pyruvate kinase. Similarly, SREBP-1c mRNA levels are decreased

when cells are exposed to monounsaturated FAs (MUFAs) and PUFAs. SREBP-1 gene

knockout studies have shown that mice had severely impaired levels hepatic mRNA

transcription of FA synthetic genes, such as ACC, FAS and SCD [231]. In addition,

PUFAs have been shown to down-regulate GK, ACC, FAS and SCD expression by

reducing levels of mature/nuclear SREBP-1c [47]. The outcome is a lower capacity for

lipogenesis, and a decrease in hepatic triglyceride output [229; 230; 232].

In rodent liver and hepatoma cells, transcription of the SREBP-1c gene is stimulated by

oxysterols that bind to LXRα. LXRα regulates the expression of genes involved in

hepatic bile acid synthesis [235]. Unsaturated FAs act as competitive antagonists to

LXRα, which explains the ability of unsaturated FAs to lower levels of SREBP-1c

mRNA [236]. This data suggests that SREBP-1c may be a master gene for the

regulation of lipid and glucose metabolism in the liver and could be a gene involved in

metabolic dysfunctions, such as type 2 diabetes, obesity and hepatic insulin resistance

syndromes [137; 237].

The transcriptional activity of HNF-4α is activated upon saturated FA binding, while

binding of PUFAs inhibits the effects on HNF-4α gene transcription [238]. HNF-4α


67

can regulate the expression of hepatic genes involved in lipoprotein metabolism (apo-

CII, apo-CIII, apo-AII and apo-IV), iron metabolism (transferrin), carbohydrate

metabolism (L-pyruvate kinase, glucose-6-phosphatase) and bile acid synthesis

(CYP7A) [228]. In addition, saturated FAs and PUFAs can stimulate the induction of

PPARα target genes of lipid and carbohydrate metabolism [239]. PPARα is

responsible for increasing the rate of transcription of genes such as, acyl CoA synthase,

acyl CoA oxidase, carnitine acyl transferase-1, FA transport protein, FA binding protein

and SCD [240].

2.10 Summary

Obesity is a widespread disease of increasing prevalence, and therefore is rapidly

becoming a major health issue in modern society. 60% of the Australian population is

overweight and more than 5% have type 2 diabetes, representing an enormous cost to

individuals with these conditions and the community at large. A number of mutations

have been identified in genes that are involved in the development of obesity and

diabetes. However, these mutations only account for 3-5% of the overweight

population. In experimental animals, a high saturated FA intake rapidly induces

hyperglycaemia, insulin resistance and impairs glucose uptake and metabolism in a

number of tissues. Enzymes involved in glucose and lipid metabolism in the liver, such

as GK, are important factors in the regulation of blood glucose levels in which

perturbations may lead to the development of disease such as metabolic syndrome and

type 2 diabetes. In contrast, a diet high in MUFAs or PUFAs may actually protect

against the development of these disorders. However, the molecular mechanisms of FA

regulation have not yet been fully elucidated.

We propose that consumption of a diet high in saturated fat results in alterations

in the regulation of hepatic gene expression via a direct mechanism of FA signalling

that contributes to the development of the metabolic syndrome and type 2 diabetes.

Specifically, FA may be able to directly regulate metabolism in the liver by altering the

rate of transcription of key target genes involved in glucose and lipid metabolism. As a

specific example we propose that alterations in the regulation of hepatic GK enzyme

activity may contribute to perturbations of whole body glucose homeostasis that result

from consumption of a diet high in saturated fat.


68

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Chapter 3 – Expression Analysis of a Human Hepatic Cell Line in Response to Palmitate

CHAPTER THREE

EXPRESSION ANALYSIS OF A HUMAN HEPATIC CELL LINE IN RESPONSE TO PALMITATE

Christopher D. Swagell a, Debra C. Henly b,c, C. Phillip Morris a.

a Cooperative Research Centre for Diagnostics, Queensland University of Technology, GPO Box 2434, Brisbane, Qld 4001, Australia.

b School of Molecular and Microbial Sciences, University of Queensland,

Brisbane, Qld 4067, Australia.

c School of Health Sciences, Bond University, Gold Coast, Qld 4229, Australia.

Biochemical and Biophysical Research Communications

328: Mar 11; 432-441 (2005)


86

Chapter 3 - Expression Analysis of a Human Hepatic Cell Line in Response to Palmitate __

STATEJ\1ENT OF AUTHORSHIP

EXPRESSION ANALYSIS OF A HUMAN HEPATIC CELL LINE IN RESPONSE TO PALMITATE

Biochemical and Biophysical Research Communications 328 (2005) 432-441

SwageU, C.D. (candidate) Involved in the conception and design of the project, generated all experimental data, interpreted and analysed all experimental data and wrote the manuscript.

Signed: .... Date:

Henly, D.c' (supervisor) Involved in the conception and design of the project, assisted in the interpretation and analysis of all experimental data and critically reviewed the manuscript.

Signed: ........ . Date: ..

Morris, c'P. (supervisor) Involved in the conception and design of the project, assisted in the interpretation and analysis of an experimental data and critically reviewed the manuscript.

Signed: Date: .~ o4L~ 1~>Gb • 4 ~ • ~ eo. ~ ••••

87


88

halla

Due to copyright restrictions, this article is not available here. Please consult the hardcopy thesis available from QUT Library or view the published version online at: http://dx.doi.org/10.1016/j.bbrc.2004.12.188

Chapter 4 – Regulation of Human Hepatocyte Gene Expression by Fatty Acids

CHAPTER FOUR

REGULATION OF HUMAN HEPATOCYTE GENE EXPRESSION BY FATTY ACIDS

Christopher D. Swagell a, Debra C. Henly b, C. Phillip Morris a.


b School of Health Sciences, Bond University, Gold Coast, Qld 4229, Australia.

Biochemical and Biophysical Research Communications

362(2): Oct 19; 374-380 (2007)


102

Chapter 4 --- Regulation of Human Hepatocyte Gene Expression by_ Fatty Acids

STATEl\1ENT OF AUTHORSHIP

REGULATION OF HUMAN HEPATOCYTE GENE EXPRESSION BY FATTY ACIDS

Experimental Cell Research (Submitted November 2006)

SwageU, C.D. (candidate) Involved in the conception and design of the project, generated all experimental data, interpreted and analysed all experimental data and wrote the manuscript.

Signed: . Date:

Henly, D.C. (supervisor) Involved in the conception and design of the project, assisted in the interpretation and analysis of all experimental data and critically reviewed the manuscript.

Date:

Morris, C.P. (supervisor) Involved in the conception and design of the project, assisted in the interpretation and analysis of all experimental data and critically reviewed the manuscript.

Date: ;l - 1-

103


104

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113

CHAPTER FOUR

APPENDIX 4.1


114


115

Appendix 4.1

Table A4.1 Genes up-regulated by FAs in HepG2 cells after 1.5 h of incubation

Up-regulated by more than 2-folda

Affymetrix Accession

no. Gene Description Palmitate Oleate EPA

216153_x_at Reversion-inducing-cysteine-rich protein with Kazal motifs 2.0 9.5 15.2 218792_s_at B-box and SPRY domain containing - 5.6 2.9 214315_x_at calreticulin - 5.4 4.2 200988_s_at proteasome activator subunit 3 (PA28 γ; Ki) - 4.8 3.3 217117_x_at mucin 3B - 3.8 3.7 205328_at claudin 10 - 3.7 5.8 204404_at solute carrier family 12 (Na/K/Cl transporters), member 2 - 3.5 3.0 216309_x_at jerky homolog (mouse) - 3.5 - 211456_x_at MT-1H-like protein - 3.4 2.6 212064_x_at Myc-associated zinc finger protein - 3.3 2.7 205752_s_at glutathione S-transferase M5 - 3.2 3.2 36888_at KIAA0841 - 3.2 - 207435_s_at serine/arginine repetitive matrix 2 - 3.0 - 212859_x_at metallothionein 2A - 3.0 2.8 201875_s_at Myelin protein zero-like 1 - 2.9 - 205967_at histone 1, H4f - 2.5 2.1

201783_s_at v-rel reticuloendotheliosis viral oncogene homolog A, nuclear factor of kappa light polypeptide gene enhancer in β-cells 3, p65 (avian) - 2.4 2.6

216954_x_at ATP synthase, H+ transporting, mitochondrial F1 complex, O subunit - 2.4 2.3 213297_at nucleolar protein family A, member 2 - - 3.3 217499_x_at Olfactory receptor, family 7, subfamily E, member 37 pseudogene - - 2.6 218020_s_at testis expressed sequence 27 - - 2.6 48659_at Invasion inhibitory protein 45 - - 2.5 209703_x_at Methyltransferase like 7A - - 2.4 202474_s_at host cell factor C1 (VP16-accessory protein) - - 2.3 58367_s_at Zinc finger protein 419 - - 2.1

a Fold changes were determined by microarray hybridisation (n = 2 microarrays/treatment) of individual

cell cultures exposed to 150 μM palmitate, 150 μM oleate and 50 μM EPA.

(-) mRNA expression profiles that were not significantly altered when compared to control incubations.


116

Table A4.2 Genes down-regulated by FAs in HepG2 cells after 1.5 h of incubation

Down-regulated by more than 2-fold

Affymetrix Accession

no. Gene Description Palmitate Oleate EPA

204176_at Kelch-like 20 (drosophila) 3.4 12.5 10.0 217294_s_at Human a enolase like 1 (ENO1L1) mRNA, partial cds. - 11.1 6.7 201123_s_at eukaryotic translation initiation factor 5A - 8.3 9.1

201742_x_at splicing factor, arginine/serine-rich 1 (splicing factor 2, alternate splicing factor) - 6.7 6.7

201711_x_at RAN binding protein 2 - 6.3 4.5 200730_s_at Protein tyrosine phosphatase type IVA, member 1 - - 4.5 212092_at paternally expressed 10 - 5.9 - 204427_s_at coated vesicle membrane protein - 5.6 - 200598_s_at tumor rejection antigen (gp96) 1 - 5.6 4.8 206108_s_at splicing factor, arginine/serine-rich 6 - 5.6 6.3

215780_s_at SET translocation (myeloid leukemia-associated) similar to SET protein (Phosphatase 2A inhibitor I2PP2A) (Template activating factor I) (TAF-I)

- - 6.3

200638_s_at tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide - 5.6 5.6

213562_s_at squalene epoxidase - 5.3 3.8 209243_s_at paternally expressed 3 - 4.8 - 208750_s_at ADP-ribosylation factor 1 - 4.8 4.0 202118_s_at copine III - 4.5 4.0 200728_at ARP2 actin-related protein 2 homolog (yeast) - - 4.0 211090_s_at H. sapiens protein-serine/threonine kinase gene - 4.5 4.3 208677_s_at basigin (OK blood group) - - 4.3 202581_at heat shock 70kDa protein 1B - 4.3 4.2 216449_x_at heat shock protein 90KDa β (Grp94) member 1 - - 4.2

216607_s_at Human lanosterol 14-a demethylase (CYP51P2) processed pseudogene - 4.3 3.3

202397_at nuclear transport factor 2 - 4.3 4.8 208853_s_at calnexin - 4.3 4.3 203803_at prenylcysteine oxidase 1 - 4.2 3.7 214845_s_at calumenin - 4.2 3.7 208116_s_at mannosidase, class 1A, member 1 - 4.2 3.7 218036_x_at CGI-07 protein - - 3.7

202236_s_at solute carrier family 16 (monocarboxylic acid transporters), member 1 - - 3.7

217749_at coatomer protein complex, subunit γ - - 3.7 214720_x_at septin 10 - 4.2 4.5 201435_s_at eukaryotic translation initiation factor 4E - 4.0 3.0 210337_s_at ATP citrate lyase - 4.0 3.6 200008_s_at GDP dissociation inhibitor 2 - 4.0 3.6 201946_s_at chaperonin containing TCP1, subunit 2 (b) - 3.8 2.9 220235_s_at receptor-interacting factor 1 - 3.8 2.8 210371_s_at retinoblastoma binding protein 4 - 3.8 3.8

213111_at phosphatidylinositol-3-phosphate/phosphatidylinositol 5-kinase, type III - 3.8 3.1

201830_s_at neuroepithelial cell transforming gene 1 - 3.8 3.4 219948_x_at hypothetical protein FLJ21934 - - 3.4 217777_s_at butyrate-induced transcript 1 - - 3.4 217826_s_at ubiquitin-conjugating enzyme E2, J1 (UBC6 homolog, yeast) 3.7 3.1 208840_s_at Ras-GTPase activating protein SH3 domain-binding protein 2 - 3.6 3.2 201633_s_at Cytochrome b5 type B (outer mitochondrial membrane) - - 3.3


117

200729_s_at ARP2 actin-related protein 2 homolog (yeast) - - 3.3

216607_s_at Human lanosterol 14-α demethylase (CYP51P2) processed pseudogene - - 3.3

201399_s_at translocation associated membrane protein 1 - 3.6 - 220386_s_at echinoderm microtubule associated protein like 4 - 3.6 3.6 203819_s_at IGF-II mRNA-binding protein 3 - 3.6 3.6 210470_x_at non-POU domain containing, octamer-binding - 3.6 2.9 208654_s_at CD164 antigen, sialomucin - - 2.9 217725_x_at PAI-1 mRNA-binding protein - 3.4 3.0 201132_at heterogeneous nuclear ribonucleoprotein H2 (H') - - 3.0

203716_s_at dipeptidylpeptidase 4 (CD26, adenosine deaminase complexing protein 2) - 3.3 2.6

200946_x_at glutamate dehydrogenase 1 - 3.3 3.1 201445_at calponin 3, acidic - 3.3 3.2 209551_at Yip1 domain family, member 4 - - 3.2 202069_s_at isocitrate dehydrogenase 3 (NAD+) a - 3.2 2.9

211048_s_at protein disulfide isomerase related protein (calcium-binding protein, intestinal-related) - 3.2 -

201146_at nuclear factor (erythroid-derived 2)-like 2 - 3.1 - 218294_s_at nucleoporin 50kDa - 3.1 3.7 202133_at transcriptional co-activator with PDZ-binding motif (TAZ) - 3.0 3.3 202223_at Homo sapiens integral membrane protein 1 (ITM1) - 3.0 2.8 201291_s_at topoisomerase (DNA) II a 170kDa - - 2.8 202783_at nicotinamide nucleotide transhydrogenase - 3.0 3.0 200890_s_at signal sequence receptor, a (translocon-associated protein a) - 2.9 2.7 211953_s_at karyopherin (importin) b3 - 2.9 2.6 202527_s_at MAD, mothers against decapentaplegic homolog 4 (Drosophila) - - 2.6 212515_s_at DEAD (Asp-Glu-Ala-Asp) box - - 2.6 209585_s_at multiple inositol polyphosphate histidine phosphatase, 1 - 2.9 2.9 208852_s_at calnexin - 2.8 2.7 201872_s_at ATP-binding cassette, sub-family E (OABP), member 1 - 2.8 2.4 200847_s_at Transmembrane protein 66 - - 2.4 200866_s_at prosaposin - - 2.4 218578_at hyperparathyroidism 2 (with jaw tumor) - - 2.4

200656_s_at procollagen-proline, 2-oxoglutarate 4-dioxygenase (proline 4-hydroxylase), (protein disulfide isomerase; thyroid hormone binding protein p55)

- 2.8 3.0

201444_s_at ATPase, H+ transporting, lysosomal accessory protein 2 - 2.8 2.4 200751_s_at heterogeneous nuclear ribonucleoprotein C (C1/C2) - 2.7 2.4 208932_at protein phosphatase 4 (formerly X), catalytic subunit - 2.6 3.0 200889_s_at signal sequence receptor, a (translocon-associated protein a) - 2.5 2.3 200052_s_at interleukin enhancer binding factor 2, 45kDa - 2.5 2.3 211074_at Homo sapiens folate binding protein - 2.4 2.1 212154_at syndecan 2 - 2.4 2.6

203102_s_a mannosyl (α-1,6-)-glycoprotein β-1,2-N-acetylglucosaminyltransferase - 2.4 2.5

214091_s_at PLASMA GLUTATHIONE PEROXIDASE PRECURSOR (HUMAN) - 2.3 2.6

200782_at annexin A5 - 2.1 2.3 a Fold changes were determined by microarray hybridisation (n = 2 microarrays/treatment) of individual

cell cultures exposed to 150 μM palmitate, 150 μM oleate and 50 μM EPA.

(-) mRNA expression profiles that were not significantly altered when compared to control incubations.


118

Table A4.3 Additional MatInspector Promoter Analysis for “Regulation of Human Hepatocyte Gene Expression by Fatty Acids” MatInspector analysis of the hepatic glucokinase promoter showing the positive strand orientation. Numbering of the binding site position starts from the 5′ end and continues to the transcription start site. The Matrix Family Library Version 6.0 (November 2005) was used in this analysis

Position Core sim. Matrix sim. Sequence

Further Information (red: ci-value > 60 Family/matrix

from - to capitals: core sequence)

V$STAT/STAT.01 Signal transducers and activators of transcription

21 - 39 1 0.924 tctattttgGGAAagc

gat

V$CEBP/CEBPB.01 CCAAT/enhancer binding protein beta

23 - 37 1 0.949 tattttggGAAAgcg

V$RBPF/RBPJK.02 Mammalian transcriptional repressor RBP-Jkappa/CBF1

24 - 38 1 0.948 atttTGGGaaagcga

V$IKRS/IK2.01 Ikaros 2, potential regulator of lymphocyte differentiation

25 - 37 1 0.993 ttttGGGAaagcg

V$CLOX/CDP.02 Transcriptional repressor CDP 30 - 48 0.846 0.81 ggaaagcgATCAatc

gtgt

V$CSEN/DREAM.01

Downstream regulatory element-antagonist modulator, Ca2+-binding protein of the neuronal calcium sensors family that binds DRE sites as a tetramer

45 - 55 1 0.95 gtGTCAagggg

V$CAAT/NFY.01 Nuclear factor Y (Y-box binding factor)

64 - 78 1 0.917 ctggCCAAtcttggg

V$AP2F/AP2.01 Activator protein 2 121 - 135 0.83 0.904 cttGCCAgtggcagc

V$MEF2/SL1.01

Member of the RSRF (related to serum response factor) protein family from Xenopus laevis

128 - 150 0.803 0.895 gtggcagCTAAtttta

gcagagc

V$HOXF/GSH1.01 Homeobox transcription factor Gsh-1

129 - 145 1 0.863 tggcagcTAATtttag

c

V$HEAT/HSF1.03 Heat shock factor 1 150 - 174 0.763 0.782 cttggagatgccAGCA

agtgcagag

V$EVI1/MEL1.03 MEL1 (MDS1/EVI1-like gene 1) DNA-binding domain 2

168 - 184 1 0.955 tgcagagGATGttgg

gg

V$RXRF/VDR_RXR.03

Bipartite binding site of VDR/RXR heterodimers without a spacer between directly repeated motifs

207 - 231 0.823 0.757 aaagGATTaagaggt

gtctgaacct

V$OCTB/TST1.01 POU-factor Tst-1/Oct-6 208 - 220 1 0.941 aaggATTAagagg

V$HEAT/HSF2.02 Heat shock factor 2 223 - 247 1 0.959 tctgaacctcatAGAA

gagtccaga

V$HEAT/HSF1.01 Heat shock factor 1 233 - 257 1 0.891 atagaagagtccAGA

Atgtcctggg

V$GREF/GRE.01

Glucocorticoid receptor, C2C2 zinc finger protein binds glucocorticoid dependent to GREs

238 - 256 0.893 0.911 agagtccagaatGTC

Ctgg

V$TALE/MEIS1.01 Binding site for monomeric Meis1 homeodomain protein

261 - 271 1 0.96 tgcTGTCacaa

V$MYBL/VMYB.02 v-Myb 274 - 286 1 0.996 cctAACGgcctct

V$OCT1/OCT1.05 Octamer-binding factor 1 287 - 301 0.95 0.915 tcCATCccatttatg

V$SRFF/SRF.03 Serum response factor 289 - 307 1 0.845 catcccatttATGGctg

tt

V$XBBF/RFX1.01 X-box binding protein RFX1 308 - 326 1 0.912 tgggttcaagGCAAct

taa V$SF1F/SF1.01 SF1 steroidogenic factor 1 310 - 322 1 0.965 ggttCAAGgcaac

V$NKXH/HMX2.01 Hmx2/Nkx5-2 homeodomain 319 - 333 1 0.94 caaCTTAaggagatt

http://www.genomatix.de/online_help/help/scores.html?s=66b491c8a220e32f1e7e87e8c543bb18#csim

http://www.genomatix.de/online_help/help/scores.html?s=66b491c8a220e32f1e7e87e8c543bb18#csim

http://www.genomatix.de/online_help/help/scores.html?s=66b491c8a220e32f1e7e87e8c543bb18#msim

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$STAT.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$CEBPB.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$RBPJK.02

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$IK2.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$CDP.02

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$DREAM.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$NFY.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$AP2.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$SL1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$GSH1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$HSF1.03

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$MEL1.03

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$VDR_RXR.03

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$VDR_RXR.03

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$TST1.01



http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$GRE.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$MEIS1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$VMYB.02

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$OCT1.05

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$SRF.03

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$RFX1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$SF1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$HMX2.01


119

transcription factor

V$PAX2/PAX2.01 Zebrafish PAX2 paired domain protein

328 - 350 1 0.785 gagattctataacagta

AAACaa

V$FKHD/HFH2.01 HNF-3/Fkh Homolog 2 (FOXD3)

342 - 358 0.806 0.914 gtaaaacaAAAAatct

g

V$SORY/SRY.01 Sex-determining region Y gene product

343 - 355 1 0.93 taaaACAAaaaat

V$CABL/CABL.01 Multifunctional c-Abl src type tyrosine kinase

344 - 354 1 0.997 aaAACAaaaaa

V$NKXH/HMX2.02 Hmx2/Nkx5-2 homeodomain transcription factor

357 - 371 1 0.849 tgattaAAACgcata

V$EGRF/NGFIC.01 Nerve growth factor-induced protein C

380 - 396 0.754 0.827 cttgGGGTggggggt

gt V$SP1F/GC.01 GC box elements 380 - 394 0.872 0.897 cttggGGTGgggggt

V$EGRF/WT1.01 Wilms Tumor Suppressor 382 - 398 1 0.979 tggggTGGGgggtgt

ca

V$EKLF/BKLF.01 Basic krueppel-like factor (KLF3)

382 - 398 1 0.964 tgGGGTggggggtgt

ca

V$MAZF/MAZR.01 MYC-associated zinc finger protein related transcription factor

382 - 394 1 0.894 tggggtGGGGggt

V$SP1F/TIEG.01

TGFbeta-inducible early gene (TIEG) / Early growth response gene alpha (EGRalpha)

385 - 399 1 0.915 ggtGGGGggtgtcag

V$CSEN/DREAM.01

Downstream regulatory element-antagonist modulator, Ca2+-binding protein of the neuronal calcium sensors family that binds DRE (downstream regulatory element) sites as a tetramer

393 - 403 1 0.978 gtGTCAgggca

V$OCTP/OCT1P.01 Octamer-binding factor 1, POU-specific domain

431 - 443 1 0.931 tgtATATgcacag

V$OCT1/OCT1.01 Octamer-binding factor 1 433 - 447 1 0.771 taTATGcacaggtgc

V$MYOD/TAL1_E2A.01

Complex of Lmo2 bound to Tal-1, E2A proteins, and GATA-1, half-site 1

436 - 452 1 0.98 atgcaCAGGtgccctt

c

V$ZBPF/ZNF202.01

Transcriptional repressor, binds to elements found predominantly in genes that participate in lipid metabolism

446 - 468 1 0.756 gcccttCCCAtctgccc

cccacc

V$NEUR/NEUROG.01 Neurogenin 1 and 3 (ngn1/3) binding sites

450 - 462 1 0.944 ttcCCATctgccc

V$ZBPF/ZNF219.01 Kruppel-like zinc finger protein 219

453 - 475 1 0.947 ccatctgCCCCccacc

cccgccc

V$ZBPF/ZBP89.01 Zinc finger transcription factor ZBP-89

457 - 479 1 0.966 ctgccccccaCCCCcg

ccccatg

V$ZBPF/ZNF219.01 Kruppel-like zinc finger protein 219

460 - 482 1 0.998 ccccccaCCCCcgccc

catgcca

V$RREB/RREB1.01 Ras-responsive element binding protein 1

462 - 476 1 0.853 cCCCAcccccgcccc

V$ZBPF/ZF9.01 Core promoter-binding protein (CPBP) with 3 Krueppel-type zinc fingers

463 - 485 1 0.872 cccacccCCGCcccat

gccatgg

V$MINI/MUSCLE_INI.02 Muscle Initiator Sequence 469 - 487 0.96 0.875

cccgccCCATgccatggcc

V$CREB/ATF.01 Activating transcription factor 551 - 571 1 0.906 actgtgTGACgagcat

cgtca

V$PAX3/PAX3.01 Pax-3 paired domain protein, expressed in embryogenesis

565 - 583 1 0.804 aTCGTcaacccctccg

cag

V$NOLF/OLF1.01 Olfactory neuron-specific factor

584 - 606 1 0.824 gtgaaaTCCCacgag

gatccccc V$NFKB/NFKAPPAB50.01 NF-kappaB (p50) 594 - 606 0.75 0.876 acgAGGAtccccc

V$STAF/STAF.01 Se-Cys tRNA gene transcription activating factor

600 - 622 1 0.792 atccCCCActattcaca

agtctg

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$PAX2.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$HFH2.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$SRY.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$CABL.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$HMX2.02

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$NGFIC.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$GC.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$WT1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$BKLF.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$MAZR.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$TIEG.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$DREAM.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$OCT1P.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$OCT1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$TAL1_E2A.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$TAL1_E2A.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ZNF202.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$NEUROG.01


http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ZBP89.01


http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$RREB1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ZF9.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$MUSCLE_INI.02

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$MUSCLE_INI.02

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ATF.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$PAX3.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$OLF1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$NFKAPPAB50.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$NFKAPPAB50.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$STAF.01


120

V$OCTP/OCT1P.01 Octamer-binding factor 1, POU-specific domain

605 - 617 0.789 0.874 ccaCTATtcacaa

V$OAZF/ROAZ.01 Rat C2H2 Zn finger protein involved in olfactory neuronal differentiation

632 - 648 1 0.738 tgGCACacagggctc

ct

V$AREB/AREB6.01 AREB6 (Atp1a1 regulatory element binding factor 6)

651 - 663 1 0.943 tgcctACCTgttt

V$AREB/AREB6.04 AREB6 (Atp1a1 regulatory element binding factor 6)

655 - 667 1 0.991 tacctGTTTcgag

V$SP1F/GC.01 GC box elements 698 - 712 0.872 0.891 tgaagGGTGgggtgg

V$EKLF/BKLF.01 Basic krueppel-like factor (KLF3)

700 - 716 1 0.964 aaGGGTggggtggg

agt

V$MAZF/MAZR.01 MYC-associated zinc finger protein related transcription factor

700 - 712 1 0.88 aagggtGGGGtgg

V$EGRF/EGR2.01 Egr-2/Krox-20 early growth response gene product

703 - 719 0.766 0.804 ggtgGGGTgggagtg

gg

V$EGRF/WT1.01 Wilms Tumor Suppressor 705 - 721 1 0.945 tggggTGGGagtggg

ca

V$ZFIA/ZID.01 Zinc finger with interaction domain

721 - 733 1 0.86 agGCTCcagccac

V$DICE/DICE.01 Downstream Immunoglobulin Control Element, interacting factor: BEN

739 - 753 1 0.851 taacCTCTccacagc

V$GREF/PRE.01 Progesterone receptor binding site

755 - 773 1 0.868 agtccaaccagTGTTc

tgt V$CREB/TAXCREB.02 Tax/CREB complex 773 - 793 0.75 0.727

tcatccTGTCtcatagccctg

V$TALE/TGIF.01 TG-interacting factor belonging to TALE class of homeodomain factors

804 - 814 1 1 ctttGTCAaac

V$E2TF/E2.01 BPV bovine papilloma virus regulator E2

816 - 832 0.852 0.886 cgaccccacgTGGTtc

t

V$HIFF/HIF1.02 Hypoxia inducible factor, bHLH / PAS protein family

817 - 831 1 0.98 gaccccaCGTGgttc

V$EBOX/USF.01 Upstream stimulating factor 818 - 832 1 0.994 acccCACGtggttct

V$BNCF/BNC.01 Basonuclin, cooperates with USF1 in rDNA PolI transcription

824 - 842 1 0.894 cgtggttcttTGTCctg

gc

V$HMTB/MTBF.01 Muscle-specific Mt binding site

877 - 885 1 0.938 gggtATTTc

V$TBPF/ATATA.01 Avian C-type LTR TATA box 877 - 893 0.75 0.821 gggtattTCAGgagcc

a

V$ZBPF/ZF9.01 Core promoter-binding protein (CPBP) with 3 Krueppel-type zinc fingers

884 - 906 0.923 0.948 tcaggagCCACccctc

aggcccg

V$ETSF/ELK1.02 Elk-1 907 - 923 1 0.913 ttagtgcGGAAgtcctt V$AP4R/TAL1BETAITF2.01 Tal-1beta/ITF-2 heterodimer 966 - 982 0.765 0.859

tgcaaCAGGtggcctca

V$MYOD/MYOGENIN.01

Myogenic bHLH protein myogenin (myf4)

966 - 982 1 0.934 tgcaACAGgtggcctc

a

V$STAF/ZNF76_143.01

ZNF143 is the human ortholog of Xenopus Staf, ZNF76 is a DNA binding protein related to ZNF143 and Staf

1002 - 1024

1 0.793 cttcCCCAacgacccc

tgggttg

V$RREB/RREB1.01 Ras-responsive element binding protein 1

1005 - 1019

1 0.855 cCCCAacgacccctg

V$GLIF/ZIC2.01 Zinc finger transcription factor, Zic family member 2

1007 - 1021

1 0.89 ccaacgaCCCCtggg

V$CP2F/CP2.01 CP2 1015 - 1033

1 0.92 ccCTGGgttgtcctctc

ag

.

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$OCT1P.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ROAZ.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$AREB6.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$AREB6.04

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$GC.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$BKLF.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$MAZR.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$EGR2.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$WT1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ZID.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$DICE.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$PRE.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$TAXCREB.02

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$TAXCREB.02

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$TGIF.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$E2.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$HIF1.02

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$USF.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$BNC.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$MTBF.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ATATA.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ZF9.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ELK1.02

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$TAL1BETAITF2.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$TAL1BETAITF2.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$MYOGENIN.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$MYOGENIN.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ZNF76_143.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ZNF76_143.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$RREB1.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$ZIC2.01

http://www.genomatix.de/cgi-bin/matinspector_prof/matrix_help.pl?s=66b491c8a220e32f1e7e87e8c543bb18;NAME=V$CP2.01


122

Chapter 5 – Effect of Fatty Acids, Glucose, and Insulin on Hepatic Glucose Uptake and Glycolysis

CHAPTER FIVE

EFFECT OF FATTY ACIDS, GLUCOSE, AND INSULIN ON HEPATIC GLUCOSE UPTAKE AND GLYCOLYSIS

Christopher D. Swagell a, C. Phillip Morris a, Debra C. Henly b,c.


b School of Molecular and Microbial Sciences, University of Queensland,

Brisbane, Qld 4067, Australia.

c School of Health Sciences, Bond University, Gold Coast, Qld 4229, Australia.

Nutrition 22: 672-678 (2006)


124

Chapter 5 - Effect of Fatty Acids, Glucose, and Insulin on Hepatic Glucose Uptake and Glycolysis

STATEMENT OF AUTHORSHIP

EFFECT OF FATTY ACIDS, GLUCOSE, AND INSULIN ON HEPATIC GLUCOSE UPTAKE AND GLYCOLYSIS

Nutrition 22 (2006) 672-678

Swagell, C.D. (candidate) Involved in the conception and design of the project, generated all experimental data, interpreted and analysed all experimental data and wrote the manuscript.

Signed: .......... "p'~ Date:

Morris, c.P. (supervisor) Involved in the conception and design of the project, assisted in the interpretation and analysis of all experimental data and critically reviewed the manuscript.

~_-..::t_. ~ ~ " -------

Signed: ........... ~ --- Date: " :~\:-.. l.\:: .<?S' ...... .

Henly, D.C. (supervisor) Involved in the conception and design of the project, assisted in interpretation and analysis of all experimental data and critically reviewed the manuscript.

. c' ~,....... -SIgned: .. ~ .. :~ ...... ::;::::::: ........ . Date: . J0::"}. ~.,,: .Y.~ ..... .

125


126

halla

Due to copyright restrictions, this article is not available here. Please consult the hardcopy thesis available from QUT Library or view the published version online at: http://dx.doi.org/10.1016/j.nut.2006.03.005


135

CHAPTER FIVE

APPENDIX 5.1


136


137

Appendix 5.1

Additional Detailed Methods for “EFFECT OF FATTY ACIDS, GLUCOSE, AND

INSULIN ON HEPATIC GLUCOSE UPTAKE AND GLYCOLYSIS”

Glucokinase Enzyme Kinetic Measurements

Glucokinase Assay

To measure total GK activity, hepatocytes were washed with 150 mM NaCl and then

lysed with 600 μL of 250 mM sucrose, 20 mM MOPS, 3 mM EDTA and 2 mg/mL

digitonin, pH 7.4. After 8 minutes of incubation with this buffer, the cell lysate was

removed and centrifuged at 14,000 g for 5 minutes.

To measure the activity of GK in the unbound, cytoplasmic fraction, cells were initially

washed with 150 mM NaCl. To lyse the plasma membrane, cells were incubated with

600 μL of 300 mM sucrose, 2 mM DTT, 5 mM MgCl2, 3 mM HEPES, 0.04 mg/mL

digitonin, pH 7.2. The lysate containing the cytoplasmic fraction was removed from the

well and centrifuged at 14,000 g for 5 minutes, the supernatant was removed and the

activity of GK assayed. After removal of the cytoplasmic fraction from the well, 600

μL of 150 mM KCl, 3 mM HEPES, 2 mM DTT, 0.05 mg/mL digitonin, pH 7.2 was

added to the well to release the non-cytoplasmic fraction. After scraping the well, the

buffer containing the bound GK fraction was removed and centrifuged. The supernatant

was assayed for GK activity.

Glucose + ATP → Glucose-6-phosphate + ADP

Glucose-6-phosphate + NAD+ → 6-Phosphogluconate + NADH + H+

The NADH concentration formed according to the reaction above, measured by the

change in absorbance at 340 nm, is proportional to the amount of glucokinase enzyme

(GK – glucokinase, G6PDH – glucose-6-phosphate dehydrogenase).

The GK activity kinetic assay was performed in a 96 well plate that contained 100 µL of

buffer (100 mM glucose, 100 mM TRIS, 100 mM KCL, 12 mM MgCl, 1 mM EDTA,

GK

G6PDH


138

2.5 mM Dithiothreitol, 5 mM ATP, 0.5 mM NAD+), pH 8.0 that was incubated at 37°C

for 10 mins. Add 60 µL of cell lysate and 20 µL G6PDH (Leuconostoc mesenteroides,

1 U/L) to the preheated buffer in the 96 well plate. Assays were incubated at 37°C and

measurements were taken at 340 nm for 20 mins at 5 sec intervals. Activity was

expressed as mUnits/mg protein where 1 mUnit represents 1 nmol glucose

phosphorylated per minute at 37oC.

The protein content of the cell fractions was measured by a Bradford assay using a

BioRad (California, USA) protein assay kit.

Purification and Neutralisation of Incubated Culture Medium

Culture medium isolated from cell culture incubations were neutralised to precipitate

unwanted cellular protein from supernatant in preparation for spectrophotometric

analysis. At 48 h 1 mL of medium was removed from cell culture incubations and 1 mL

of 1 M perchloric acid (PCA) was added to each sample and incubated on ice for 20

mins. Samples were centrifuged at 14 000g for 5 mins and supernatant removed

without disturbing the pellet. The samples were neutralised with approximately 260 µL

of MOPS solution (2 M KOH, 0.3 M MOPS, 100 mM KCL). The pH of the solution

should fall with the range pH 5-5 – 7.0, if below pH 5.5 then add 10 µL of MOPS

solution and measure pH. If the pH is over 7.0 then add 10 µL of PCA and pH again,

continue until the pH falls within range. Incubate samples on ice for 30 mins and

centrifuge at 14 000g for 3 mins. Remove supernatant and perform spectrophotometric

assays or store at -20oC.

Spectrophotometric Measurements

Lactate Assay

The amount of lactate present in the culture medium was measured in a 96 well plate

that contained 100 µL of buffer (100 mM TRIS, 100 mM KCL, 12 mM MgCl, 1 mM

EDTA, 2.5 mM Dithiothreitol, 5 mM ATP and 0.5 mM NAD+, pH 8.0) and was

incubated at 37°C for 10 mins. Add 60 µL of neutralised culture medium and 20 µL

lactate dehydrogenase (LDH) (27.3 kU/L) to the preheated buffer in the 96 well plate.

Assays were incubated at 37°C and measurements were taken at 340 nm for 20 mins or

until the readings stabilised.


139

L-Lactate + NAD+ + Hydrazine Hydrate → Pyruvate Hydrazine + NADH + H+


change in absorbance at 340 nm, is proportional to the amount of L-lactate.

Pyruvate Assay

The amount of pyruvate present in the culture medium was measured in a 96 well plate

that contained 100 µL of buffer (100 mM TRIS, 100 mM KCL, 12 mM MgCl, 1 mM

EDTA, 2.5 mM Dithiothreitol, 5 mM ATP and 0.5 mM NADH, pH 8.0), and was

incubated at 37°C for 10 mins. Add 60 µL of neutralised culture medium and 20 µL

LDH (27.3 kU/L) to the preheated buffer in the 96 well plate. Assays were incubated at

37°C and measurements were taken at 340 nm for 20 mins or until the readings

stabilised.

Pyruvate + NADH + H+ ↔ Lactate + NAD+


change in absorbance at 340 nm, is proportional to the amount of pyruvate.

Acetoacetate Assay

The amount of acetoacetate present in the culture medium was measured in a 96 well

plate that contained 100 µL of buffer (100 mM TRIS, 100 mM KCL, 12 mM MgCl, 1

mM EDTA, 2.5 mM Dithiothreitol, 5 mM ATP and 0.5 mM NADH, pH 8.0), and was

incubated at 37°C for 10 mins. Add 60 µL of neutralised culture medium and 20 µL 3-

hydroxybuturate dehydrogenase (3-HBDH) (530 U/L) to the preheated buffer in the 96

well plate. Assays were incubated at 37°C and measurements were taken at 340 nm for

20 mins or until the readings stabilised.

Acetoacetate + NADH + H+ ↔ D-3-Hydroxybuturate + NAD+


change in absorbance at 340 nm, is proportional to the amount of acetoacetate.

LDH

3-HBDH

LDH


140

3-Hydroxybuturate Assay

The amount of 3-hydroxybuturate present in the culture medium was measured in a 96

well plate that contained 100 µL of buffer (100 mM TRIS, 100 mM KCL, 12 mM

MgCl, 1 mM EDTA, 2.5 mM Dithiothreitol, 5 mM ATP and 0.5 mM NAD+, pH 8.0),

and was incubated at 37°C for 10 mins. Add 60 µL of neutralised culture medium and

20 µL 3-HBDH (710 U/L) to the preheated buffer in the 96 well plate. Assays were

incubated at 37°C and measurements were taken at 340 nm for 20 mins or until the

readings stabilised.

D-3-Hydroxybutrurate + NAD+ ↔ Acetoacetate + NADH + H+


change in absorbance at 340 nm, is proportional to the amount of D-hydroxybuturate.

Isotopic Glucose Phosphorylation and Glycolysis Measurements

To measure rates of glucose phosphorylation and glycolysis, liver cells were cultured

for 24 h with 2 nM or 10 nM insulin and 15 mM glucose in combination with the fatty

acid to be tested. At the end of this period, the culture medium was replaced with fresh

medium containing 15 mM [2-3H]glucose (0.75 μCi) to measure glucose

phosphorylation or 15 mM [6-3H]glucose (0.75 μCi) (New England Nuclear, Boston

USA) to measure glycolytic flux. The incubations were continued for a further 24 h and

samples collected for analysis at the end of this time. Radiolabelled products of glucose

metabolism (lactate, pyruvate, amino acids, and water) were separated from glucose by

ion exchange chromatography. Rates of glucose phosphorylation were measured as 3H2O released from [2-3H]glucose. Glycolysis was estimated from the recovery of

isotope derived from [6-3H]glucose in H2O, lactate, pyruvate and amino acids. In all

experiments, there was at least 90% recovery of isotope.

Column Preparation:

For each separation three columns are required that gravity feed into one another. The

top column contains H+ resin, the middle column contains acetate resin and the bottom

column contains borate resin. The columns are plugged with dacron wool and wash

HBDH


141

with 2 mL of water. Add 8 mL (equivalent to 2 cm) of the appropriate resin each

column and elute with 5 mL of water, repeat three times. Join the columns in the

appropriate order and wash twice with 5 mL of water.

Separation of Metabolites

Load 1 mL of supernatant onto the top column and wash sample onto the column twice

with 0.5 mL water and discard eluate. Place a collection vessel under the bottom

column and wash five times with 5 mL of water and collect the eluate. Mix the pooled

eluate and take 1 mL for counting (This fraction contains 3H-water). Remove and

separate the columns for individual elution of bound fractions.

Top Column:

Wash the column with 5 mL of water, repeat and discard the eluate. Place a collection

vessel under the bottom column and elute with 5 mL of 2N NH4OH, repeat four times

and collect the eluate. Mix the pooled eluate and take 1 mL for counting (This fraction

contains amino acids).

Middle Column:


vessel under the bottom column and elute with 5 mL of 1M acetic acid, repeat six times

and collect the eluate. Mix the pooled eluate and take 1 mL for counting (This fraction

contains the lactate). Place a new collection vessel under the column and elute with 5

mL 4N formic acid, repeat five times. Mix the pooled eluate and take 1 mL for

counting (This fraction contains pyruvate).

Bottom Column:


vessel under the bottom column and elute with 5 mL of 1M acetic acid, repeat four

times and collect the eluate. Mix the pooled eluate and take 1 mL for counting (This

fraction contains glucose).

1 mL of samples eluted from the columns was mixed with 5 mL of Ready Safe

scintillation cocktail mixture. Scintillation counting was performed on the LS 6500

Scintillation System (Beckman).

Chapter 6 – General Discussion


143

CHAPTER SIX

GENERAL DISCUSSION


144


145

6.1 General Discussion

This thesis was based on the hypothesis that diets containing high levels of saturated FA

may alter hepatic gene regulation via direct mechanisms of FA signalling. It was

further proposed that these alterations in gene expression may contribute to impaired

glucose metabolism that ultimately results in the development of hyperglycaemia and

insulin insensitivity that leads to the onset of metabolic syndrome and type 2 diabetes.

The human hepatoma cell lines and isolated primary rat hepatocytes used in this study

were chosen facilitate the characterisation of direct FA signalling from secondary,

endocrine or long-term signalling events seen in whole animal studies.

This thesis aimed to define the molecular mechanisms of FA signalling that are

involved in hepatic gene regulation and nutrient metabolism. The evidence obtained

from this study contributes to the current literature and identifies a potential role for

saturated FA in the development of metabolic syndrome and cardiovascular disease

(CVD). Specifically, this thesis demonstrates that saturated FA can reduce hepatic

glucokinase (GK) promoter activity and GK enzyme activity in addition to regulating

transcription factors that influence GK gene transcription that may perturb glucose

metabolism. In addition, this work identified for the first time that saturated FA altered

the expression of genes that have previously been shown to be associated with

metabolic disease states, including metabolic syndrome, CVD and type 2 diabetes.

6.2 Palmitate Differentially Regulates Hepatic Gene Expression

Metabolic syndrome and CVD are characterised by a number of risk factors that are

associated with the development disease. Work reported in this thesis provides

convincing evidence that the saturated FA, palmitate, contributes to the development of

these risk factors. These include alterations in expression of genes involved in

lipoprotein metabolism, oxidative stress response, cholesterol synthesis and fibrinolysis.

Specifically, genes altered by palmitate that are associated with increased risk include,

apolipoprotein-B100 (apo-B100), apo-CIII, plasminogen activator inhibitor-1 (PAI-1),

insulin-like growth factor-I (IGF-I) and insulin-like growth factor binding protein 3

(IGFBP3).

Insights into the mechanisms by which a high saturated fat diet may induce

macrovascular disease, such as atherosclerosis, are also provided in this thesis.


146

Namely:

1. an increase of apo-B100 gene expression may indicate an increased production

of apo-B100-containing atherogenic lipoprotein particles.

2. the observed increase in the expression of the apo-AII gene may reduce reverse

cholesterol efflux to the liver and facilitate cholesterol deposition in peripheral

tissues.

3. increases in cholesterolgenic gene expression may indicate an increase in

cholesterol production.

4. the observed increase in the level of apo-CIII gene expression may reduce

triglyceride (TG) catabolism and promote increased levels of hepatic TG

secretion.

5. the induction of oxidative stress response genes may indicate an increase in

oxidative stress and/or potential depletion of the antioxidant, glutathione.

6.3 Palmitate Increases the Production of Atherogenic Lipoproteins

This thesis has demonstrated that hepatic apo-B100 mRNA expression was up-regulated

in response to high levels of palmitate (Figure 6.1). This data suggest that palmitate

may promote a state of increased atherogenic lipoprotein particle production that has

previously been shown in the literature to be associated with an increased risk of

developing CHD [1]. In addition, it has been identified that increased apo-B100 levels

are associated with an increased risk of obesity, hypertension and type 2 diabetes in

adolescents [2] and is strongly associated with CHD in men aged 45-76 years [3].

Therefore, the evidence from this thesis may further implicate the role of palmitate as a

predisposing environmental factor that contributes to the development of these

metabolic disease states. Furthermore, as only one apo-B100 molecule is present on

each lipoprotein particle [4], it can be used to predict the total number of circulating

atherogenic plasma lipoprotein particles present in an individual. This observation

provides the potential of using circulating apo-B100 levels as an indicator of a high

dietary intake of saturated FA that may be used to predict the risk of metabolic disease

development in healthy individuals.


147

Figure 6.1 – Diagrammatical representation of saturated FA regulation of gene

expression. Genes in green are up-regulated and genes in red are down-regulated. Abbreviations: TG – triglyceride, C – cholesterol, NEFA – non-esterified fatty acid, apo – apolipoprotein,

HL – hepatic lipase, LPL – lipoprotein lipase, ADRP – adipose differentiation-related protein, FDPS –

farnesyl pyrophosphate synthetase, FDFT1 – farnesyl-diphosphate farnesyl transferase, VLDL – very

low-density lipoprotein, sVLDL – small very low-density lipoprotein, LDL – low-density lipoprotein,

sLDL – small low-density lipoprotein IDL – intermediate-density lipoprotein, HDL – high-density

lipoprotein, HDLR – high-density lipoprotein receptor.

This thesis has also provided evidence that palmitate exposure results in increased

hepatic apo-AII and ABCA1 gene expression (Figure 6.1). Previously, it has been

shown that transgenic mice over-expressing apo-AII exhibit a decreased capacity to

promote in vitro cellular cholesterol efflux [5]. This suggests the possibility that

palmitate may reduce the anti-atherogenic effects exhibited by HDLs and result in

excess cholesterol accumulation in peripheral tissues. In addition to a possible

Apo-AIApo-CIII C

TGC

TGC

C Apo-B100

Apo-B100C

TGC

Apo-B100

Apo-B100Apo-CIII

ApoE

ApoE

Rev

erse

Cho

lest

erol

Tra

nspo

rt

Liver

LDL

VLDL

sLDL

IDL

sVLDL

Apo-B100

ApoE

Apo-CIII

Extrahepatic Tissue

Apo-AII

HDL ABCA1

HL

LPL

TGC

HDLR

LDLADRPFDPS

FDFT1

Atherogenic

Atherogenic

Atherogenic

Atherogenic

Atherogenic

Anti-atherogenic

CETP

NEFA

TGCC

Apo-AIApo-CIII C

TGC

TGC

C Apo-B100

Apo-B100C

TGC

Apo-B100

Apo-B100Apo-CIII

ApoE

ApoE

Rev

erse

Cho

lest

erol

Tra

nspo

rt

Liver

LDL

VLDL

sLDL

IDL

sVLDL

Apo-B100

ApoE

Apo-CIII

Extrahepatic Tissue

Apo-AII

HDL ABCA1

HL

LPL

TGC

HDLR

LDLADRPFDPS

FDFT1

Atherogenic

Atherogenic

Atherogenic

Atherogenic

Atherogenic

Anti-atherogenic

CETP

NEFA

TGCC


148

reduction in reverse cholesterol transport, this thesis identifies that palmitate increases

the expression of cholesterolgenic genes, including farnesyl pyrophosphate synthetase

and farnesyl-diphosphate farnesyl transferase (Figure 6.1). This may indicate increased

production of cholesterol that ultimately leads to a raised level of cholesterol-rich

circulating atherogenic lipoprotein particles. This suggests that palmitate exposure may

reduce HDL mediated reverse cholesterol transport from peripheral tissues to the liver,

increase cholesterol synthesis and potentially promote cholesterol deposition and

accumulation in vascular tissue, thereby increasing the risk of developing

atherosclerosis.

6.5 Palmitate Increases Apo-CIII Gene Expression

Evidence generated from this thesis suggests that a diet high in saturated FA may

contribute to increased hepatic TG secretion by raising apo-CIII levels. Plasma apo-

CIII has been recognised as a useful marker that is associated with TG-rich lipoproteins

and is an indicator of coronary disease risk in healthy individuals [6; 7]. Plasma apo-

CIII is associated with apo-B100-containing and apo-AI-containing lipoproteins and has

the ability to exchange between TG-rich lipoproteins and HDLs. In healthy individuals,

the majority of apo-CIII is bound to HDL, whereas in hypertriglyceridaemic

individuals, apo-CIII is mainly bound to TG-rich particles [8]. Hypertriglyceridaemia is

characterised by increased levels of apo-CIII containing VLDLs which play a crucial

role in the identification of atherosclerosis risk and development of CHD [9].

In addition, elevated plasma apo-CIII levels have been identified in diabetic subjects

[10] and have been shown to delay the apo-E-dependent uptake and metabolism of TG-

rich particles by the liver. This is due to the suppression of lipoprotein lipase and/or

hepatic lipase activity and a reduced binding of TG-rich particles and their remnants to

the LDL receptor [11; 12]. Recently, it has been demonstrated that overweight or

insulin insensitive individuals also have increased levels of VLDL-apo-CIII and this is

linked to an increased production of TG-rich VLDLs [13].

6.6 Palmitate Exposure Alters Gene Expression that Depletes Antioxidant

Availability and Raises Oxidative Stress Levels

In this thesis we demonstrate that palmitate exposure alters the expression of oxidative

stress response genes that could potentially result in the depletion of glutathione (GSH),


149

a potent antioxidant. Increased expression of selenoprotein P, phospholipid

hydroperoxide glutathione peroxidase, glutathione S-transferase A2, glutathione S-

transferase P and multi-drug resistance protein suggests that hepatic oxidative stress

response has increased in response to palmitate. In addition, a number of genes that are

reported to induce glutamate cysteine ligase expression were down-regulated, including

activator-1 and nuclear factor kappa-B. Glutamate cysteine ligase is responsible for the

production of GSH, and therefore decreased glutamate cysteine ligase expression may

result in reduced GSH production. This data suggests that a possible depletion of GSH,

combined with a decrease in GSH production, could lead to an increased level of free

radical formation and oxidative stress exposure in the liver.

Increased free radical production coupled with GSH depletion may promote increased

oxidation of lingering TG and cholesterol-rich LDLs in the circulation. Oxidised-LDLs

exhibit an impaired ability to dock to LDL-receptors lengthening the time that oxidised-

LDLs remain in the circulation. When combined with a reduced ability to facilitate

reverse cholesterol efflux, this may increase cholesterol deposition within vascular

tissue and contribute to the development of atherosclerosis and CVD. The regulation of

genes identified in this thesis may explain the connection between a high saturated FA

intake and the progression from hypertriglyceridaemia to the development of

atherosclerosis and CVD.

6.7 Palmitate Decreases IGF-I and IGFBP3 Expression

The insulin-like growth factor (IGF) system plays an important role in the control of

cellular growth, metabolism and survival. Biological increases in the availability of IGF

activity can predispose to certain cancers, while a deficiency appears to increase the risk

of diabetes and CHD [14]. Circulating IGFs are highly regulated by specific IGFBPs.

Of these, IGFBP-3 accounts for more than 90% of circulating IGF activity. In addition,

when IGFs are bound to IGFBPs the half-life of bound IGF is greatly enhanced.

Recently, it has been shown that individuals with obesity, dyslipidaemia, hypertension

and insulin resistance have significantly lower levels of IGF-I [15]. Furthermore,

circulating IGF-I levels are shown to decrease with increasing blood glucose

concentrations and with the duration of diabetes [16]. IGF-I gene knockout animals

display hyperinsulinaemia and skeletal muscle insulin resistance [17]. Additionally, a


150

polymorphism in the IGF-I gene promoter has been shown to be associated with an

increased risk of type 2 diabetes and CVD [18; 19; 20]. Changes in IGF-I regulation

have been linked to a reduction in insulin sensitivity, which has been shown to precede

the development of type 2 diabetes [14]. In this thesis, we have shown that palmitate

incubation decreased IGF-I and IGFBP3 gene expression.

6.8 Palmitate Alters Expression of Fibrinolytic Genes

A further complication of diabetes is nephropathy, which is characterised by excessive

accumulation of extracellular matrix (ECM) in the kidney. The regulatory process of

ECM synthesis and degradation is controlled by the plasminogen activator

(PA)/plasmin/PAI system. This system involves the conversion of plasminogen to

plasmin that is catalysed by PA which is under the regulation of PAI-1. Increased levels

of PAI-1 reduce PA activity, which results in increased ECM deposition that is a

characteristic of pathological conditions associated with renal fibrosis and excessive

ECM accumulation in the kidney, such as diabetic nephropathy [21]. In addition,

hydrogen peroxide has been shown to up-regulate PAI-1 mRNA and protein expression

and the basal expression of PAI-1 is increased upon depletion of cellular GSH [22]. In

this thesis, we observed an increase in the hepatic gene expression level of PAI-1 upon

palmitate incubation. This may indicate an effect of saturated FA on hepatic ECM

remodelling that promotes ECM accumulation similar to that observed in pathological

conditions, such as diabetic nephropathy. If our observation of changes in expression of

PAI-1 in response to saturated fat translates into increased PAI-1 levels in blood, a diet

high in saturated fat may induce a prothrombotic state that could contribute to the

development of atherosclerotic plaque formation.

6.9 MUFAs and PUFAs are Potent Regulators of Gene Expression

Epidemiological studies have shown an inverse correlation with intake of

monounsaturated FAs (MUFAs) and polyunsaturated FAs (PUFAs) and the

development of CVD such as atherosclerosis [23; 24]. Recently, it has been shown that

the degree of unsaturation of dietary FAs can affect plasma lipoprotein composition as

well as the expression of adhesion molecules and other pro-inflammatory factors that

influence the thrombogenicity that is associated with atherosclerosis development.

Evidence suggests that both MUFAs and PUFAs appear to reduce total and LDL-

cholesterol compared with saturated FAs [25; 26] and protect against atherosclerosis


151

[24]. In contrast, a high intake of saturated FA is strongly correlated with death from

CHD [27].

Evidence from this thesis has shown that MUFAs and PUFAs may promote the

expression of a panel of genes that would be protective against the development of

metabolic syndrome and atherosclerotic risk if expressed in vivo. These include a

reduction in the mRNA expression of squalene epoxidase by both MUFAs and PUFAs

and decreased PAI-1 binding protein mRNA expression. Both of these changes would

be expected to potentially reduce cholesterol synthesis and the further risk of

thrombosis. This is in contrast to longer-term palmitate incubations that showed

increased expression levels of the cholesterolgenic genes farnesyl pyrophosphate

synthetase and farnesyl-diphosphate farnesyl transferase.

6.10 Palmitate Reduces Glucokinase Promoter and Enzyme Activity

In this thesis we proposed that alterations in the regulation of hepatic glucokinase (GK)

activity contribute to perturbation of whole body glucose homeostasis as a result of the

consumption of a diet high in saturated fat. Chapter four of this thesis identified that

palmitate exposure can alter GK gene regulation and promoter activity that may be

implicated in the dys-regulation of glucose homeostasis. Insulin increases the

expression of sterol regulatory element binding protein-1c(SREBP-1c) which is known

to induce hepatic GK gene expression [28]. In contrast to previous studies [29], we

observed a modest reduction in SREBP-1c mRNA levels upon palmitate incubation.

Furthermore, palmitate was capable of causing a significant reduction in hepatic GK

promoter activity. Therefore, this study has identified that palmitate can reduce GK

promoter activity through the reduction in SREBP-1c gene expression in vitro. If this

translates into similar changes in vivo, saturated fat consumption would result in

reduced GK enzyme production and reduced uptake and glucose metabolism in the

liver.

6.11 Palmitate Failed to Reduce Glucose Phosphorylation and Glycolytic Flux in

the Presence of Insulin

This study demonstrated that in the presence of insulin, palmitate exposure significantly

reduced total GK enzyme activity [30]. However, the rates of glucose phosphorylation

and glycolytic flux remained unchanged upon palmitate exposure. In addition,


152

investigations into the distribution of free GK and bound GK indicated that there was no

evidence that the interaction between GK and glucokinase regulatory protein was

altered in response to incubations with palmitate. Furthermore, in our experimental

conditions, we identified an excess of residual unbound GK enzyme that may explain

the failure of palmitate to significantly reduce the rate of glucose phosphorylation and

glycolytic flux, despite showing a significant reduction in GK enzyme activity.

This observation of reduced hepatic GK promoter and enzyme activity, due to palmitate

incubation, may bring to light an underlying factor of hyperglycaemia. For example, in

insulin responsive individuals, insulin action may provide a sufficient level of GK gene

expression that compensates for saturated FA-induced inhibition of GK expression and

enzyme activity. However, in insulin-resistant individuals, saturated FA-induced

inhibition may be sufficient to reduce normal glucose metabolism. Circulating free FAs

are elevated in insulin-resistant states and have been suggested to contribute to insulin

resistance by reducing glucose transport or inhibiting glucose phosphorylation [31].

Therefore, high levels of prolonged saturated FA exposure in combination with the

onset of insulin resistance may promote the dys-regulation of glucose phosphorylation,

inhibiting the flux through glycolysis leading to the development of hyperglycaemia and

onset of type 2 diabetes.

6.12 Implications of this thesis

Previously, human studies have attempted to evaluate the relationship between total fat

intake and obesity, metabolic syndrome and type 2 diabetes. This thesis supports the

hypothesis that a consumption of a diet high in saturated fat is associated with the

development of these conditions. In addition, this thesis contributes to the current

literature defining the potential molecular mechanisms of saturated FA signalling in the

liver that may contribute to the development of metabolic syndrome and type 2 diabetes.

The treatment of metabolic syndrome and type 2 diabetes aims to improve insulin

sensitivity and to prevent the associated metabolic and cardiovascular abnormalities that

are characteristic of these disease states. Since many individuals with metabolic

syndrome are overweight, dietary modification should be primarily focused on weight

reduction. Evidence generated for this thesis provides support that dietary modification

for the treatment of metabolic syndrome should incorporate a limited intake of saturated


153

fat. In addition, a moderately increased consumption of MUFA and PUFA should be

encouraged as they do not induce similar detrimental metabolic effects when compared

to saturated FA.

This thesis also identifies genes that could be used as markers of increased risk of

developing metabolic syndrome and type 2 diabetes as a result of high saturated fat

consumption. These gene markers could be used as potential targets to identify those

who are at risk of developing metabolic disease and could also be used to monitor the

effectiveness of modified diets, such as a reduced saturated fat intake, and lifestyle

changes. This thesis supports the established observation that saturated fat plays a

major role in the development of metabolic syndrome, type 2 diabetes and

macrovascular complications, including atherosclerosis and CVD.

6.13 Future Directions

The data that has been generated from this thesis has provided evidence that FAs can

directly regulate hepatic gene expression that has the potential to translate into

alterations of metabolic pathway flux, especially glucose metabolism. Therefore, the

further characterisation of saturated FA signalling of GK promoter activity would target

the site-directed mutagenesis of the SREBP-1c regulatory element (SRE) core

nucleotide sequence. This would identify the contribution of the reduction of GK

promoter activity that is due to saturated FA regulation of SREBP-1c. Further

investigations into the remaining 10% reduction of promoter activity would involve the

generation of smaller deletion constructs of the pGK3-GKD vector to localise the

regulatory promoter region. This would be followed by site-directed mutagenesis of

potential regulatory elements to identify novel transcription factor binding sites that are

involved in saturated FA regulation of SREBP-1c.

Further observations from time-course q-PCR analysis data from this thesis have also

provided evidence that FAs are able to directly regulate hepatic gene expression of a

number of transcription factors. This data showed that palmitate did not alter hepatic

gene expression at 1.5 hours but was sufficient to directly regulate hepatic gene

expression at 48 hours. These observations indicate that palmitate may require longer

incubation periods to induce changes in gene regulation and suggest that the subsequent

time periods used in this study were not sufficient to detect significant changes in


154

metabolic gene expression that could translate into perturbations of metabolic pathway

flux and glucose metabolism. Therefore, time-course analysis should be performed to

investigate longer time periods of 72 and 96 hours up to and including one week. To

follow on from this point, the observation that EPA and oleate could significantly alter

hepatic gene expression after the short-term 1.5 hour incubation suggests an increased

ability to directly regulate hepatic mRNA expression levels. Therefore, a

comprehensive comparison of the direct signalling effects of saturated, MUFA and

PUFA at a longer incubation period should also be performed to allow a comparison of

expression patterns that may be distinctly regulated by these individual FAs.

Finally, the investigations of the effects of FAs signalling and translation into metabolic

effects in the absence of insulin and/or insulin-resistant conditions should be further

explored. It is possible that FA induced reduction of glucose metabolism may only

become apparent after the onset of insulin resistance. Therefore, measurements of the

rate of glucose phosphorylation and glycolysis could be performed on primary

hepatocytes isolated from insulin receptor knockout mice or in the absence of insulin.

These results could be compared to insulin responsive hepatocytes in an attempt to

differentiate the effect of FA signalling observed within these two independent states.

6.14 Major Findings of this Thesis

1. The saturated FA, palmitate, initiated a transcriptional response of hepatic

gene expression in the Huh-7 cell line after 48 hours of incubation. A total

of 162 genes displayed altered gene expression upon palmitate exposure.

2. A number of markers of risk that are associated with metabolic syndrome,

CVD and type 2 diabetes were differentially regulated upon palmitate

exposure. These genes include apo-B100, apo-CIII, PAI-1, IGF-I and

IGFBP3.

3. An increased level of mRNA expression of genes involved in oxidative

stress response was observed upon palmitate exposure.

4. Expression analysis of the hepatic GK promoter identified that palmitate

incubation resulted in reduced promoter activity after 48 hours.

5. Incubation periods of 48 hours resulted in palmitate regulating the

expression of hepatic transcription factors involved in the regulation of


155

glycolysis and FA oxidation. Palmitate incubation resulted in the reduction

of SREBP-1c mRNA levels while increasing PPAR mRNA levels.

6. A short-term incubation period of 1.5 hours with palmitate failed to induce

significant changes in the regulation of hepatic gene expression.

7. Short-term incubation periods of 1.5 hours with the MUFA, oleate and

PUFA, EPA, initiated similar patterns of changes in hepatic gene regulation.

8. GK enzyme activity was reduced by palmitate and EPA incubations after 48

hours in primary rat hepatocyte.

9. Incubation of palmitate, oleate, linolenate, EPA and DHA failed to affect the

interaction and distribution of GK and GKRP.

10. Incubation of primary rat hepatocytes with palmitate, oleate, linolenate, EPA

and DHA failed to reduce glucose phosphorylation, glycolytic flux and β-

oxidation in the presence of insulin.


156

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MOLECULAR MARKERS OF OBESITY AND DIABETESeprints.qut.edu.au/35762/1/Christopher_Swagell_Thesis.pdf · MOLECULAR MARKERS OF OBESITY AND DIABETES ... diets that are high in monounsaturated