Institute of Physiological Chemistry, Ulm University

Head of Institute: Prof. Dr. Thomas Wirth

Functional analysis of hepatic FOXO3signalling in glucose and lipid metabolism

DISSERTATIONDissertation submitted in partial fulfillment of the requirements for the

degree of PhD (Dr. rer. nat)

Faculty of Natural Sciences

University of Ulm

Presented by

Sarah GulFrom Pakistan

2014

Dean: Prof. Dr. Joachim Ankerhold

First reviewer: Prof. Dr. Thomas Wirth

Institute of Physiological Chemistry

Ulm University

Second reviewer: Prof. Dr. Martin Wagner

Centre for Internal Medicine

Ulm University Medical Center

Ulm University

Day doctorate awarded: 19th May 2014

Table of Contents

1

Table of Contents

Table of contents 1

Summary 4

Abbreviations 6

1 Introduction 121.1 Forkhead transcription factors 12

1.1.1 Forkhead box subclass O 12

1.1.2 Regulation of FoxO signalling 14

1.2 Role of FoxO transcription factors in metabolism 16

1.2.1 Role of FoxO transcription factors in the liver regulating

glucose homeostasis 17

1.2.2 Role of FoxO transcription factors in lipid metabolism 20

1.2.3 Role of FoxO transcription factors in pancreatic β-cells 21

1.3 Liver is a “complex metabolic” organ 21

1.3.1 Regulation of hepatic glucose production 24

1.3.2 Regulation of transcription factors controlling gluconeogenesis 25

1.3.3 Regulation of hepatic lipid metabolism 28

1.4 Diabetes mellitus 29

1.4.1 Type 2 diabetes mellitus 30

1.4.2 Obesity and type 2 diabetes 32

1.4.3 Factors controlling β-cell mass and type 2 diabetes 34

1.4.4 Molecular mechanism of insulin resistance 34

1.4.5 Genetics of type 2 diabetes 36

1.4.6 Animal models of type 2 diabetes 37

1.5 Metformin 39

1.5.1 Metformin as an anti-hyperglycemic agent 40

1.5.2 Mechanism of metformin action 41

1.6 Aims of the study 45

2 Materials and Methods 462.1. Mice 46

2.1.1 Animal studies 46

2.1.2 Doxycycline administration 46

2.1.3 Metformin administration 46

Table of Contents

2

2.2 Genotyping 47

2.2.1 Isolation of genomic DNA 47

2.2.2 Polymerase chain reaction (PCR) 47

2.3 In Vivo Bioluminescence imaging 48

2.4 Metabolic studies 48

2.4.1 Glucose Tolerance Test (GTT) and Insulin Tolerance Test (ITT) 48

2.4.2 Animal studies 49

2.4.3 Enzyme-linked immunosorbent assay (ELISA) 49

2.5 Protein biochemistry 49

2.5.1 Protein extraction with dignam C buffer 49

2.5.2 Protein concentration measurement by Bradford method 50

2.5.3 In vitro Luciferase reporter gene activity measurement 50

2.5.4 Western blotting 50

2.6 RNA Analysis 52

2.6.1 RNA extraction and cDNA synthesis 52

2.6.2 Gene expression analysis 54

2.7 Histology 54

2.7.1 Liver tissue preparation 54

2.7.2 Immunofluorescence staining of paraffin embedded sections 55

2.7.3 Immunofluorescence image aquisition and processing 56

2.7.4 Quantification of TUNEL staining, Cd45 and Insulin staining 56

2.7.5 Immunohistochemical staining of paraffin embedded sections 56

2.7.6 PAS staining for Glycogen 57

2.8 Statistical analysis 57

2.9 Reagents and Materials 58

2.9.1 General chemicals 58

2.9.2 Buffers and solutions 59

2.9.3 Protein biochemistry materials 60

2.9.4 Histology and microscopy materials 61

2.9.5 Molecular biology materials 61

2.9.6 General laboratory materials 62

3 Laboratoryequipment 62

3.1 General laboratory equipment 62

3.2 Histology and microscopy equipment 63

Table of Contents

3

4 Software 64

3 Results 653.1 Generation of transgenic mice with inducible liver-specific expression of

constitutively active FOXO3 65

3.1.1 Tetracycline regulated expression of a constitutively active FOXO3 allele

driven by the LAP promotor 65

3.2 Perinatal induction of FOXO3CA results in lethal phenotype 66

3.2.1 liver-specific expression of FOXO3CA 66

3.2.2 FOXO3CA activation affects size and structure of hepatocytes and induces

liverdysfunction and metabolic abnormalities 69

3.2.3 FOXO3CA activation in younger animals induces autophagy 72

3.3 FOXO3CA activation in adult animals 73

3.3.1 Expression pattern of FOXO3CA transgene 73

3.3.2 FOXO3CA activation in adult animals is not associated with

growth defect 76

3.3.3 FOXO3CA activation results in altered hepatic morphology 76

3.3.4 FOXO3CA activation induces moderate hepatocyte damage 77

3.3.5 Hepatocellular FOXO3 activation induces metabolic abnormalities 80

3.3.6 Activation of catabolic pathways by expression of constitutively

active FOXO3 82

3.3.7 Continuous expression of constitutively active FOXO3 in the liver induces

loss of gluconeogenic potential 88

3.3.8 FOXO3CA activation in the liver induces subordinate

pancreatic hyperplasia 89

3.4 Metformin normalizes FOXO3-induced distorted glucose

and insulin metabolism 91

3.5. FOXO3-induced activation of global catabolism, hepatocyte atrophy, or

hepatocyte damage were reversed after Metformin administration 96

4 Discussion 1025 References 1166 Appendix 135Declaration 154Acknowledgement 155Curriculum Vitae 156

Summary

4

Summary

Type 2 diabetes mellitus is a complex metabolic disorder characterized by high blood

glucose levels and insulin resistance that occur as a consequence of uncontrolled

gluconeogenesis that is failed to be suppressed by insulin. It is a major worldwide

health care problem affecting the quality of life. The physiological processes

contributing to insulin resistance in type 2 diabetes remain enigmatic. Therefore,

there is a continuous need to identify molecular events responsible for type 2

diabetes and insulin resistance and this could help to discover new targets for the

improvement of anti-diabetic drugs. Currently metformin is the most widely used oral

anti-diabetic drug that inhibits hepatic glucose production, although the underlying

molecular mechanism is not completely understood. FoxO transcription factors

represent key downstream targets of insulin and growth factors regulating energy

metabolism. However the interplay between different FoxO family members in

metabolism is far from being understood. Although it had been suggested that FoxO1

is the major executer for regulation of insulin signalling mediated glucose. In addition

to FoxO1, FoxO3 is also significantly expressed in the liver its contribution to

metabolic regulation has however not been thoroughly analysed. Interestingly FoxO3

genotypes are associated with insulin sensitivity phenotypes and longevity in humans

suggesting that FoxO3 is critical for metabolic control.

Therefore in order to understand the importance of FoxO3 function in the liver in a

time- and cell-type specific manner, we generated transgenic (FoxO3CAHep) mice

that allow the conditional expression of a constitutively active FoxO3 allele. We

crossed transgenic mice carrying the tetracyclin-regulated transactivator (tTA) under

the control of liver-activator protein promoter with transgenic mice bearing a

constitutively active form of the FoxO3 allele (FoxO3CA) controlled by tTA-

responsive promoter.

Here we demonstrate that FoxO3 is a key regulator of hepatic glucose and lipid

metabolism in transgenic mice. FoxO3 activation led to progressive hepatocyte

atrophy in the absence of significant inflammation and apoptosis with moderate

hepatocyte damage. Perinatal activation of FoxO3 results in lethal phenotype and the

transgenic animals survived showed hypoglycemic phenotype with moderate

upregulation of autophagy-associated genes. However, FoxO3 activation in adult

animals showed hyperglycemic, hyperinsulinemic phenotype followed by up-

Summary

5

regulation of gluconeogenesis-associated genes. The elevated blood glucose levels

in transgenic mice are coupled with impaired glucose tolerance and impaired insulin

sensitivity. Furthermore expression of FoxO3CA results in activation of catabolic

pathways in transgenic mice including increased glycogenolysis, inhibition of lipid

synthesis and activation of lipid β-oxidation. Consistently the results from gene

expression profiles indicated up-regulation of genes involved in lipid and glucose

catabolic pathways and down-regulation of anabolic genes as shown previously in

type 2 diabetic subjects. This suggests that FoxO3 activates catabolic pathways to

provide substrates and energy for enhanced gluconeogenesis.

For our surprise the disease progression in transgenic mice showed hypoglycemia,

might be as a consequence of beginning of liver failure or this could be due to high

insulin production by pancreatic β-cells. Indeed the transgenic mice showed

significantly higher insulin levels followed by pancreatic hyperplasia. It is plausible

that the pancreatic hyperplasia in transgenic mice could arise might be due to the

normal compensatory response of pancreas to enhanced insulin secretion or several

other reasons.

Strikingly FoxO3CA-induced metabolic alterations in glucose and lipid metabolism

were completely normalized after metformin treatment in mice expressing

constitutively active FoxO3. Taken together our findings suggest that dysbalanced

FoxO3 activity in the liver results in insulin resistance. Therefore tight regulation of

FoxO3 activity would be very crucial and agents controlling hepatic FoxO3 system

may represent therapeutic tools to prevent type 2 diabetes.

Abbreviations

6

Abbreviations

AMPK Adenosine mono-phosphate (AMP)-activated protein kinase

AMPKα1α2 AMPK alpha1 and alpha 2

Ab Antibody

APS Ammonium persulfate

ADA American Diabetes Association

ApoCIII Apolipoprotein C3

ALT Alanine aminotransferase

ATG1 Autophagy related gene 1

ATG5 Autophagy related gene 5

ATG12 Autophagy related gene 12

AST Aspartate aminotransferase

ALP Alkaline phosphatase

AdipoR1/2 Adiponectin receptor 1 and 2

AMP Adenosine mono-phosphate

ATP Adenosine tri-phosphate

Acc Acetyl-CoA carboxylase

BSA Bovine serum albumin

CA Constitutively active

CD45 cluster of differentiation 45

cDNA Complementary DNA

CPT1α Carnitine palmitoyltransferase 1α

CREB cAMP response element-binding protein

CRTC2 CREB-regulated transcriptional coactivator2

CRE cAMP-response element

CNS Central nervous system

DOX Doxycycline

DNL De novo lipogenesis

DNA Deoxyribonucleicacid

DKO Double knockout

DLKO Akt1 Akt2 knockout

dNTP Deoxynucleotide triphosphate

Abbreviations

7

DTT Dithiothreitol

Dil Dilution

DAPI 4´,6-diamidino-2-phenylindole

ER Endoplasmicreticullum

ERK Extracellular regulated kinase

EDTA Ethylenediamine tetraacetic acid

ELISA Enzyme-linked immunosorbent assay

Echs Enoyl-CoA hydratase

ERK Extracellular signal-regulated kinases

FOXO3CA Constitutively active FOXO3

FTO Fat mass and obesity related gene

FFA Free fatty acid

Fabp5 Fatty acid binding protein 5

Fas Fatty acid synthase

Fbpase Fructose-1,6-biphosphatase

FOXO1ADA Constitutively nuclear mutant FOXO1

G6pc Glucose-6-phosphatase

GTT Glucose tolerance test

Glut2 Glucose transporter

Gck Glucokianse

GEO Gene expression Omnibus

GCKR Glucokinase regulatory protein

GWAS Genome wide association and linkage studies

GLP-1 Glucagon-like-peptide 1

GR Glucocorticoid receptor

GRE Glucocorticoid receptor binding element

Gckr Glucokinase regulatory protein

HPRT Hypoxanthine-guanine phosphoribosyltransferase gene

HbA1c Glycated haemoglobin A1c

HNF Hepatic nuclear factor

HNF4α Hepatic nuclear factor-4α

HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid

HGF Hepatocyte growth factor

HFD High fat diet

Abbreviations

8

IR Insulin receptor

ITT Insulin tolerance test

IB Immunoblot

IF Immunofluorscence

IHC Immunohistochemistry

i.p. Intraperitoneally

IKK IκB kinase

Irs1/Irs2KO Insulin receptor substrate1and 2 knockout

IKK2CA IKK2 constitutively active

IKKβ IκB kinase subunit β

IFG Impaired fasting glucose

InsR Insulin receptor

IGT Impaired glucose tolerance

IGFBP1 Insulin like growth factor binding protein 1

IRS1 Insulin receptor substrate-1

IRS2 Insulin receptor substrate-2

JNK c-Jun N-terminal kinases

KLF15 Krüpple-like factor 15

K8/18 Keratin 8/18

LKB1 Liver kinase B1

LKB1-KO Liver kinase B1 knockout

LPCKO Liver parenchymal knockout

Lepr Leptin receptor

LPL Lipoprotein lipase

L-p110αKO Liver-specific deletion of catlytic subunit of PI3K (p110α)

LD Lipid droplets

LAP Liver activator protein

LIRKO Liver-specific insulin receptor knockout mice

LW/BW Liver weight/ Body weight

MTP Microsomal triglyceride transfer protein

MEK1 Mitogen activated protein kinase1

NADPH Nicotinamide adenine dinucleotide phosphate

NFAT Nuclear factor of activated T-cells

OGTT Oral glucose tolerance test

Abbreviations

9

OCT1 Oragnic cation transporter 1

OCT2 Oragnic cation transporter 2

PKB Protein kinase B

P53 Cellular tumor antigen/ Tumor suppressor

PBS Phosphate buffer saline

PCR Polymerase chain reaction

PAGE Polyacryamide gel electrophoresis

rpm Revolutions per minute

Pygl Glycogen phosphorylase

Pepck Phosphoenolpyruvate carboxykinase

Pdk4 Pyruvate dehydogenase kinase 4

PKA Protein kinase A

PI3K Phosphatidylinsositol 3-kinase

PAS Periodic Acid Schiffs

Pdx-1 Pancreatic and duodenal homeobox 1

PIP3 Phosphatidylinositol (3,4,5)-triphosphate

PTEN Phosphatase and tension homologue

Pklr Pyruvate kinase liver

PGC-1α Peroxisome proliferator activated receptor γ coactivator-1α

q-PCR Quantitative realtime-PCR

RLU Relative light units

RNA Ribonucleic acid

RIPA Radio immunoprecipitation assay

RBCs Erthrocytes/ Red blood cells

Rb Rabbit

Rb and P53 Tumor suppressor genes

RT Room temperature

SD Standard deviation

Srebp1 Sterol regulatory element-binding protein 1c

STK11 Serine/Threonine kinase 11

SDS Sodiumdodecylsulfate

SAT Subcutaneous adipose tissue

SOCS Supressors of cytokine signalling proteins

SD Standard deviation

Abbreviations

10

SIRT1 NAD-dependent deacetylase sirtuin 1

STZ Streptozotocin

SHP Small heterodimer partner

SHIP SH2-containing inositol phosphatase 1

SPF Specific pathogen-free

S253 Serine253

S315 Serine315

tTA Tetracycline-responsive transactivator

tetO Tet operator/ tetracyclin response element

T2D Type 2 Diabetes mellitus

TUNEL Terminal deoxynucleotidyl transferase dUTP nick end labeling

TBS Tris buffer saline

TEMED Tetramethyethylenediamine

TNT buffer Tris-Nacl-Tween buffer

TKO Triple knockout

Trb3 Psuedokianse tribble homologue 3

TG Triglycerides

T32 Threonine 32

TAK1 Transforming growth factor (TGF)-β-activated kinase 1

TE Tris-EDTA

TBE Tris-buffer saline

TCA Tricarboxylicacid cycle

UAE United Arab Emirates

UPL Universal probe libraray

UV Ultravoilet irradiation

VLDL Very low density lipoprotein

WHO World Health Organization

WT Wild type

XBP1 X-box binding protein 1

ZFR Zucker fatty rat

ZDR Zucker diabetic rat

µg Microgram

µl Microlitre

7Wk 7-week

Abbreviations

11

9Wk 9-week

6Wk 6-week

5Wk 5-week

(-)Met Without Metformin

(+)Met3D With Metformin 3-days

(+)Met3W With Metformin 3-weeks

Introduction

12

1 Introduction

1.1 Forkhead transcription factors

The family of forkhead box proteins belongs to a major group of transcription factors

present in all eukaryotes. Thus are transcriptional regulators characterized by

conserved DNA-binding domain called “Forkhead box”. Forkhead box is a 110

amino-acid region located in the central portion of molecules and is classified as

winged helix structure. The family of forkhead transcription factors has many

subgroups ranging from (Forkhead Box A-S). An important subgroup of forkhead box

proteins is the FoxO subgroup (Greer and Brunet 2005; Calnan and Brunet 2008).

1.1.1 Forkhead box subclass O

The O branch of the large Forkhead family of transcription factors is highly conserved

evolutionarily and ubiquitously expressed (Huang and Tindall 2007; Calnan and

Brunet 2008). The prototypes of the FoxO family were first described in

Caenorhabditis elegans and drosophila demonstrating the task of FOXO proteins as

the downstream targets of insulin-like signalling involved in the modulation of

longevity and metabolism. Mammals contain four members of the Forkhead family

such as FOXO1, FOXO3, FOXO4 and FOXO6. The FOXO family was initially

described in human tumors as three members of Forkhead family; FOXO1, FOXO3

and FOXO4 were identified at chromosomal translocations in human cancers (Galili,

Davis et al. 1993; Davis, D'Cruz et al. 1994; Parry, Wei et al. 1994; Borkhardt, Repp

et al. 1997). FOXO1, FOXO3, FOXO4 are widely distributed and are expressed in

almost all tissues whereas FOXO6 is largely specific to neurons. FOXO transcription

factors attaches to DNA in the form of monomers on conserved consensus core

recognition motif TTGTTTAC in the nucleus. FOXO transcription factors perform

diversified function by binding to the consensus core recognition motif and promote

the transcriptional activities of genes regulating glucose metabolism, cell cycle arrest,

apoptosis, stress resistance, autophagy, cellular atrophy in response to oxidative

stress and DNA damage (Figure 1) (Hwangbo, Gershman et al. 2004; Kenyon 2010;

Eijkelenboom and Burgering 2013).

Introduction

13

Figure 1: Functions of FoxO transcription factors (Eijkelenboom and Burgering2013). FOXO transcription factors perform diversified functions and hence function as the regulators

for homeostasis during the process of fasting and feeding. FOXO transcription factors get activated in

response to any metabolic stress e.g starvation, growth factor deprivation and oxidative stress. FOXO

transcription factors perform various functions by up-regulating a series of target genes involved in the

regulation of gluconeogenesis, cell-cycle arrest, differentiation, DNA repair, autophagy and apoptosis.

FoxO transcription factors perform overlapping functions and it is still unknown

whether these factors share similar target genes or have different subsets of target

genes. The complexity of FoxO transcription factors is supported by the notion that

mice missing three main FoxO isoforms exhibit different phenotypes. Homozygous

FoxO1 knockout mice are embryonically lethal (Hosaka, Biggs et al. 2004) due to

defective angiogenesis. FoxO3 knockout mice produce premature ovarian failure and

FoxO4 knockout mice are with no obvious phenotype (Paik, Kollipara et al. 2007). It

is also evidenced that FoxO transcription factors perform redundant functions and

Introduction

14

each of these can compensate to some degree for the loss of the other as triplet

conditional knockout leads to severe abnormalities in hematopoietic systems which

was not observed in double or single knockout combinations (Nakae, Oki et al. 2008;

Tikhanovich, Cox et al. 2013). However some specificity is contributed among FoxO

members as FoxO1 performs a major role in the regulation of glucose homeostasis

and FoxO3 is an important factor for longevity in invertebrates, mice and humans

(Brunet, Bonni et al. 1999; van der Horst and Burgering 2007; Sedding 2008; Willcox,

Donlon et al. 2008; Flachsbart, Caliebe et al. 2009) and it is strongly correlated with

antioxidant stress response and tumor suppressor activity (Huang and Tindall 2007;

Myatt and Lam 2007; Paik, Kollipara et al. 2007).

1.1.2 Regulation of FoxO signalling

FoxO transcription factors are the downstream targets of insulin/PI3K/PKB/AKT

signalling pathway. During fed/unstressed conditions binding of insulin or

growthfactors to their tyrosine kinase receptors prompt the recruitment and activation

of the serine/threonine kinase Akt and phosphoinositide kinase (PI3K) which results

in inactivation of FoxO transcription factors through AKT induced phosphorylation of

FoxO transcription factors at conserved three amino acids (FoxO3: T32, S253,

S315). This subsequently results in rapid relocalization of FoxO transcription factors

from the nucleus to cytoplasm. Phosphorylated FoxO transcription factors

respectively interact with 14-3-3 proteins, which function as molecular chaperons to

remove FoxO proteins out of the nucleus (Brunet, Bonni et al. 1999; Brunet, Kanai et

al. 2002) (Figure 2). Conversely during fasted/stressed conditions in the absence of

growth factors and insulin FoxO transcription factors localizes in the nucleus to

upregulate a series of target genes (Greer and Brunet 2005).

Introduction

15

Figure 2: FoxO transcription factors are activated in response to Insulinsignalling pathway adapted from (Greer and Brunet 2005). During feeding/unstressed

conditions activated insulin-signalling results in phophorylation/inactivation and proteosomal

degradation of FOXO transcription factors. FOXO trancription factors are no longer in the nucleus to

regulate their metabolic target genes. In contrast during starved/stressed conditions due to absence of

insulin and growth factors FOXO transcription factors gets activated, move into the nucleus, bind to

their promoters to upregulate the series of metabolic target genes.

Additionally cellular stress conditions can also cause activation of FoxO transcription

factors via AMPK (Greer, Banko et al. 2009), or under oxidative stress conditions via

JNK mediated phosphorylation (Eijkelenboom and Burgering 2013). FoxO

transcription factors are also modulated in response to several post translational

modifications acetylation, ubiquitination and phosphorylation which results in altered

subcellular localization, a modulated transcriptional-regulatory activity and change in

protein stability (Greer and Brunet 2005).

Introduction

16

1.2 Role of FoxO transcription factors in metabolism

FoxO transcription factors are involved in the metabolism regulation through their

effects in various organs such as liver, pancreas, adipose tissue and skeletal muscle.

Alterations in FoxO function in simple organisms affects the process of aging and

lead to metabolic disorders including diabetes. This can be hypothesized from the list

of known target genes which play an important role in metabolism (Table 1) (Barthel,

Schmoll et al. 2005). The role of FoxO proteins in the context of regulating glucose

homeostasis in the liver and pancreas will be discussed in the following sections.

Table 1: Metabolic selected FoxO target genes (Barthel, Schmoll et al. 2005)

Genes FoxO-effect Organ or cell type Metabolic effects ReferencesG6Pase Upregulation Liver, Kidney Increased

gluconeogenesis(Schmoll, Walkeret a l . 2000),(Nakae, Kitamuraet al. 2001)

G6Pasetransporter

Upregulation Liver Increasedgluconeogenesis

(Kallwellis-Opara,Zaho et al. 2003)

PEPCK Upregulation Liver, Kidney Increasedgluconeogenesis

(Nakae, Kitamuraet a l . 2001;Altomonte, Richteret al. 2003), (Hall,Yamasaki et al.2000)

IGFBP-1 Upregulation Liver Inhibition of IGF-1 (Guo, Rena et al.1999; Yeagley,Guo et al. 2001)(Hall, Yamasaki etal. 2000)

PGC-1α Upregulation Liver Increasedgluconeogenesis

(Daitoku,Yamagata et al.2003)

PDK4 Upregulation Muscle, Liver Glucose saving (Furuyama,Kitayama et al.2003).(Kwon,Huang et al. 2004)

LPL Upregulation Muscle Triglycerideclearance, fattyacid metabolism

(Kwon, Huang etal. 2004)

HMG-CoAsynthase

Upregulation Liver K e t o n e b o d yproduction

(Nadal, Marrero etal. 2002)

PDX-1 Downregulation Pancreatic β-cell Inhibition of β -celldifferentiation

Kitamura, T. et al,2002,

P21 Upregulation Adipocyte Inhibition of fat-celldifferentiation

(Nakae, Kitamuraet al. 2003)

AdipoR1/2 Upregulation Liver, Muscle F a t t y a c i doxidation, glucoseuptake

(Tsuchida,Yamauchi et al.2004)

Introduction

17

1.2.1 Role of FoxO trancription factors in the liver regulating Glucosehomeostasis

As outlined above the major role of hepatic FoxO proteins includes the regulation of

gluconeogenesis and among the FoxO subgroup FoxO1 was shown as the major

insulin-regulated transcription factor involved in the modulation of hepatic glucose

production (Nakae, Kitamura et al. 2001; Accili and Arden 2004). It was shown in

mouse models of insulin resistance that FoxO1 transcription factors are deregulated

(Cheng, Guo et al. 2009) consistently gluconeogenic genes glucose-6-phosphatase

(G6pc), phosphoenolpyruvate carboxykinase (Pepck) and pyruvate-dehydrogenase

kinase 4 (Pdk4) are up-regulated during insulin resistance, fasting, type 2 diabetes,

insulin deficiency state and downregulated at postprandial state by insulin (O'Brien

and Granner 1996; O'Brien, Streeper et al. 2001). Accordingly mice with liver-specific

inactivation of FoxO1 showed hypoglycemia, decreased gluconeogenic gene

expression and enhanced glucose tolerance (Matsumoto, Pocai et al. 2007).

Furthermore (Altomonte, Richter et al. 2003) showed that hepatic inhibition of FoxO1

in diabetic mice rescues the diabetic phenotype of insulin resistance by lowering the

gluconeogenic gene expression. Consistently it was shown that targeting FoxO1 in

diet-induced obese mice using antisense oligoneucleotides reduced G-6pc and

Pepck gene expression with improved glucose tolerance and decreased hepatic

glucose production in the liver (Samuel, Choi et al. 2006). In line with these studies

haploinsufficiency of FoxO1 (Nakae, Biggs et al. 2002) in InsR haploinsufficient mice

rescued the loss of insulin sensitivity by reducing the hepatic gluconeogenic gene

expression. Additionally ablation of hepatic FoxO1 in mice lacking the insulin receptor

substrates IRS1 and IRS2 rescues the insulin resistance and hepatic lipid

abnormalities (Matsumoto, Pocai et al. 2007; Dong, Copps et al. 2008). It was further

reported that hepatic deletion of all three FoxO isoforms (FoxO1, FoxO3, FoxO4) in

mice showed more pronounced fasting hypoglycemia, improved glucose tolerance

and enhanced insulin sensitivity (Haeusler, Kaestner et al. 2010; Zhang, Li et al.

2012; Xiong, Tao et al. 2013) (Table 2).

Introduction

18

Table 2: Characteristic metabolic features of hepatic FoxO-null mouse models(Estall 2012)

Genotype(liverspecific)

Background Glycemia Insulin Serumlipids

Hepaticlipids

Ref

Foxo1-/- WTIRSR-/-

IRS1/2-/-

WT + STZdb/db

DecreasedDecreasedDecreasedDecreasedDecreased

––ResistantResistantDepletedResistantb

––DecreasedIncreaseda

Increased––

––Decreased––––––

Zhang et al.2012Mutsomotoetal.2007Dong et al. 2008Haeusler et al.2010Zhang et al.2012

Foxo3-/- WTdb/db

––––

––Resistantb

––––

––––

Zhang et al.2012Zhang et al.2012

Foxo4-/- WT –– –– –– Zhang et al.2012

Foxo1/3-/- WTWTdb/db

DecreasedDecreasedDecreased

DecreasedDecreasedResistantb

NRIncreasedIncreased

NRIncreased––

Haeusler et al.2010Zhang et al.2012Zhang et al.2012

Foxo1/4-/- WT Decreased NR –– NR Zhang et al.2012

Foxo3/4-/- WT –– NR –– NR Zhang et al.2012

Foxo1/3/4-/- WTWTWT + HFDWT

DecreasedNRNRDecreased

DecreasedNRResistantb

NR

NR––IncreasedIncreased

NRIncreasedIncreasedNR

Haeusler et al.2010Tao et al. 2011Tao et al. 2011Zhang et al.2012

HFD, High fat diet; STZ, Streptozotocin; WT, Wild type;__, no significant change; NR, not reported.a with ageb db/db mouse insulin resistance due to obesity.

However, it is important to know that in triple knockout studies the effects achieved

are redundant or in a synergistic manner still remains unknown, as the relative

contributions of individual FoxO proteins were not addressed.

In contrast constitutive activation of FoxO1 in the liver (Zhang, Patil et al. 2006)

results in impaired hepatic glucose production through increased expression of

gluconeogenic genes G-6-pc, Pepck. Additionally, gain-of-function of FoxO1 in the

liver paradoxically increases insulin sensitivity and leads to steatosis (Matsumoto,

Introduction

19

Han et al. 2006). Of interest under certain conditions FoxO1 gain of functions in the

liver results in insulin sensitivity through its increased ability to phophorylate Akt in

Trb3 (Tribbles homologue 3)-dependent or -independent manner (Matsumoto, Han et

al. 2006; Naimi, Gautier et al. 2007). Activation of FoxO1 in insulin resistance states

may improve insulin sensitivity through induction of Irs2 (Ide, Shimano et al. 2004).

Interestingly several mouse models demonstrated that hepatic deletion of insulin

receptor (IR) (Michael, Kulkarni et al. 2000), the p110 a form of PI3K(Sopasakis, Liu

et al. 2010), AKT2 (Cho, Mu et al. 2001) or AKT1 and AKT2 (Lu, Wan et al. 2012)

and IRS1/IRS2 (Dong, Copps et al. 2008) all result in insulin resistance and diabetes.

The ablation of IR, Akt1/Akt2, IRS1/IRS2 lead to constitutive activation of FoxO

transcription factors and as a consequence aberrant gluconeogenesis is observed

(Figure 3).

Figure 3: Knockout mouse models that leads to constitutive activation of FoxOtranscription factors.

FoxO transcription factors also interact with other coactivators and transcription

factors for regulating gucose homeostasis e.g PGC1α, HNF4 and CREB (Herzig,

Long et al. 2001; Yoon, Puigserver et al. 2001; Puigserver, Rhee et al. 2003;

Schilling, Oeser et al. 2006) and deactylases SIRT1 (Frescas, Valenti et al. 2005).

Introduction

20

Several novel mechanisms have also been shown to regulate glucose metabolism

such that interaction of FoxO1 with XBP-1. XBP-1 is the transcription factor involved

in insulin sensitivity and it was evidenced that direct binding of XBP-1 to FoxO1

directs it to the proteosomal degradation (Zhou, Lee et al. 2011). Similarly

glycosylation modifications promote the activation of FoxO transcription factors and

hence cause the upregulation of gluconeogenic target genes (Housley, Udeshi et al.

2009).

1.2.2 Role of FoxO transcription factors in lipid metabolism

FoxO transcription factors play an important role in regulating lipid metabolism. As

shown later the role of glucokinase (GCK) (Figure 5) in assisting lipogenesis it was

shown that constitutive activation of FoxO1 in the liver results in down-regulation of

the glycolytic enzymes pyruvate kinase and glucokinase subsequently and

decreased sterol/lipid synthesis results in reduced concentration of triglycerides in

transgenic mice (Zhang, Patil et al. 2006). In a similar mouse model (Matsumoto,

Han et al. 2006; Qu, Altomonte et al. 2006) enhanced lipogenesis and liversteatosis

was observed. However inhibition of FoxO1 in the liver does not change glucokinase

expression (Altomonte, Richter et al. 2003). It was evidenced that downstream of

insulin signaling SREBP-1c, HNF4 and hypoxia-inducible factor 1 regulate

glucokinase expression in addition to FoxO proteins (Roth, Curth et al. 2004). The

disparity observed in accordance with insulin sensitivity and lipogenesis results from

the feedback loop that increases insulin signalling thereby regulating lipid metabolism

in a FoxO1-independent manner through SREBP-1c. Additionally these differences

could be caused due to variation in experimental models, extent of overexpression,

and the time of judgement on the subject of fasting and feeding (Gross, van den

Heuvel et al. 2008). In addition FoxO1 plays an important insulin-dependent role in

assembly and perseverance of very low-density lipoproteins (VLDL) in circulation.

This effect is attained via transcriptional regulation of ApoCIII and microsomal

triglyceride transfer protein (MTP) that plays a pivotal role in regulating the circulation

of triglycerides during the periods of starvation (Kamagate, Qu et al. 2008). ApoCIII

function as lipoprotein lipase (LPL) inhibitor the enzyme involved in hydrolysis of TG

in VLDL and chylomicrons. FoxO1 increases the transcriptional activity and secretion

of ApoCIII during fasting and thus extends the endurance of VLDL in circulation

Introduction

21

(Altomonte, Cong et al. 2004). Importantly during insulin resistance states, due to

continous activation of FoxO1 results in hypertriglyceridemia and hyperglycemia

(Kim, Zhang et al. 2011). Consistently elevated ApoCIII levels are linked with

impaired hydrolysis and defective clearence of TG culminating in accumulation of TG

and augmenting hypertriglyceridemia (Ito, Azrolan et al. 1990; Shachter 2001).

1.2.3 Role of FoxO transcription factors in pancreatic β-cells

Glucose homeostasis is dependent on genuine beta cell function and on pancreatic

beta cell mass. Among the forkhead transcription factors FoxO1 is predominently

expressed in the pancreas and regulates pancreatic and duodenal homeobox factor-

1 (Pdx-1) (Kitamura, Nakae et al. 2002). It was shown that haploinsufficiency of

FoxO1 restores the insulin sensitivity in insulin resistant Irs2 knockout mice by

increasing β-cell proliferation and restoring Pdx-1 expression (Nakae, Biggs et al.

2002). On the other hand gain-of-function of FoxO1 in the liver and pancreatic β-cells

leads to diabetes owing to combined effect of elevated hepatic glucose production

and altered β-cell compensation due to reduced Pdx-1 expression (Nakae, Biggs et

al. 2002). FoxO1 by inhibiting FoxA2 decreases Pdx-1 expression and β-cell

proliferation (Kitamura, Nakae et al. 2002), FoxA2 is another member of the fork

head family function as positive regulator of Pdx-1 expression (Lee, Sund et al.

2002). During metabolic stress conditions FoxO1 attenuate the replication of β-cells

and neogenesis but maintains the identity and function of β-cells. Conversely in Type

2 diabetes FoxO1 participates in diverse mechanisms including ER, oxidative,

hypoxic stress, inflammation, raised apoptosis, inadequate proliferation,

unconstrained autophagy and dedifferentiation results in β-cell dysfunction (Kitamura

2013). The significance of fine-tuning FoxO1 action in β-cells may provide therapeutic

targets against type 2 diabetes (Buteau and Accili 2007; Kluth, Mirhashemi et al.

2011).

1.3 Liver is a " complex metabolic " organ

Multicellular organisms have developed systematic nutrient storage strategies in

evolution. Controlled by hormones as well as energy sensors and nutrient, the

metabolic system reacts to environmental conditions by storing or utilizing nutrients.

Introduction

22

This system optimizes metabolic balance, e.g. lack of metabolites in glucose

metabolism will stimulate catabolic pathways like glycogenolysis or lipid β-oxidation

(Sun, Miller et al. 2012). The liver is a central organ for metabolic regulation including

glucose homeostasis regulating glucose transport, gluconeogenesis, glycolysis,

glycogenesis, glycogenolysis and integrates both cell-nonautonomous and cell-

autonomous mechanisms to command glucose release into the blood stream (Lin

and Accili 2012). During the postprandial period the elevated levels of plasma

glucose stimulate insulin secretion from pancreatic β-cells. Insulin, after binding to its

receptors on the plasma membrane of liver, muscle, and adipose tissues activates

glycogenesis and glycolysis in liver and muscle simultaneously inhibiting hepatic

glycogenolysis and gluconeogenesis to avert hyperglycemia (Saltiel and Kahn 2001).

Additionally, insulin stimulates the synthesis of triglycerides through de novo

lipogenesis and prompting the mobilization of triglycerides from liver to adipose

tissue. As a consequence blood glucose levels are reduced in the body by the action

of insulin (Jitrapakdee 2012). During starvation, pancreatic α-cells secrete glucagon

in response to low blood glucose levels (Jiang and Zhang 2003) which triggers fat

mobilization from adipose tissue to skeletal muscle for β-oxidation. As a result many

substrates are released which serve as precursor for hepatic gluconeogenesis. In

short-term glycogenolysis and in long-term gluconeogenesis are the sources for

glucose production. The glucose released serves as a fuel for brain and red blood

cells / erthrocytes (RBCs) (Figure 4).

Introduction

23

Figure 4: Effects of Insulin and Glucagon during starvation and feeding

(Jitrapakdee 2012) A. During feeding conditions in response to glucose insulin released from

pancreatic beta cells acts on its target tissues liver and muscles to promote glycolysis and

glycogenesis. Insulin also promotes de novo lipogenesis and mobilization of triglycerides in liver and

adipose tissue. B. In fasting glucagon released from pancreatic alpha cells stimulate fat mobilization

and β -oxidation from adipose tissue to skeletal muscle to provide increased substrates for

glycogenolysis and gluconeogenesis in the liver. The glucose released serves as a fuel for brain and

RBCs. RBC, red blood cell; TG, triglycetides; FFA, free fatty acid; yellow hexagons, glucose; pink

circles, insulin; white circles, triglycerides; green circles, glucagon.

Gluconeogenesis occurs predominantly in the liver and is regulated at the

transcriptional level of key enzymes, like phosphoenolpyruvate carboxykinase

(Pepck) (Hanson and Reshef 1997), glucose-6-phosphatase (G6pc) (Zhang, Patil et

al. 2006), and pyruvate-dehydrogenase kinase 4 (Pdk4). Pdk4 inhibits pyruvate

dehydrogenase by phosphorylation providing pyruvate as gluconeogenic substrates

(Wei, Tao et al. 2011). Two other critical enzymes are pyruvate carboxylase (Pc)

(Utter and Keech 1960) and fructose-1,6-biphosphatase (Fbpase) (O'Brien and

Granner 1996). These enzymes are involved in the direct rapid regulation of hepatic

glucose production.

Introduction

24

1.3.1 Regulation of hepatic glucose production

Glucose after intestinal absorption enters the hepatocytes (Figure 5) (Bechmann,

Hannivoort et al. 2012). Glucose transporter 2 (Glut2) internalises glucose through

the hepatocytes membrane. In hepatocytes, liver glucokinase (GCK) converts

glucose to glucose-6-phosphate (Agius 2008). Mutations in GCK have been

correlated with the pathogenesis of insulin resistance in diabetes (Miller, Anand et al.

1999; Cuesta-Munoz, Tuomi et al. 2010). Glucose-6-phophate is the most critical

intermediate in the regulation of hepatic glucose metabolism, it is degraded during

glycolysis to provide energy and the final product pyruvate is decraboxylated to

acetyle-CoA which enters into intramitochondrial TCA cycle finally linking glucose

and lipid metabolism as acetyle-CoA is the substrate for de novo lipogenesis (DNL).

Furthermore, glucose-6-phosphate can be degraded in the pentose phosphate

pathway shunt further providing the reduction equivalents (NADPH) for DNL.

Figure 5: Regulation on hepatic glucose metabolism (Bechmann, Hannivoort et

Introduction

25

al. 2012). A. The insulin-independent glucose transporter 2 (GLUT-2) pump glucose over the

membrane. Glucokinase regulatory protein (GCKR) induces a confirmational change to export

glucokinase (GCK) in the cytoplasm. Glucokinase then phosphorylate glucose to glucose-6-phosphate

(Glu-6-P). Nuclear receptor signalling and insulin transcriptionally regulate Glucokinase. B. The central

intermediate in hepatic glucose metabolism is glucose-6-phosphate it is degraded in glycolysis to

provide energy in the form of ATP and results in production of pyruvate, which enters into

tricarboxylicacid (TCA) cycle. Glucose-6-phosphate is degraded in pentose phosphate pathway shunt

to provide NADPH a substrate for de novo lipogenesis (DNL). Acetyl-CoA also links glucose and lipid

metabolism and serve as a substrate for DNL.

1.3.2 Regulation of transcription factors controlling gluconeogenesis

In response to hypoglycemic conditions during fasting pancreatic α-cells secrete

glucagon. Activation of glucagon signalling increases cAMP levels, which stimulate

protein kinase A (PKA) activity, and eventually promotes CREB phosphorylation

(Authier and Desbuquois 2008). CREB is critical regulator of the hepatic

gluconeogenic programme in mice (Koo, Flechner et al. 2005). CREB-regulated

transcriptional coactivator 2 (CRTC2 also reffered to as TORC2) (Shaw, Lamia et al.

2005) enters into the nucleus to interact with phospho-CREB and binds to cAMP-

response element (CRE) to regulate the expression of gluconeogenic target genes

like phosphoenolpyruvatecarboxykinase (PEPCK) and glucose-6-phosphatase

(G6Pase) (Mayr and Montminy 2001). During this period another coactivator, the

NAD-dependent deacetylase sirtuin-1 (SIRT1) is activated, which deacetylates

peroxisome proliferator activated receptor γ-1α (PGC-1α) (Nemoto, Fergusson et al.

2005) (Brunet, Sweeney et al. 2004; Rodgers and Puigserver 2007) and FoxO

transcription factors (Frescas, Valenti et al. 2005). PGC-1α interacts with FoxO1 and

with hepatic nuclear factor-4 to regulate the expression of gluconeogenic target

genes (Li, Monks et al. 2007). Additionaly, increased glucocorticoid concentrations

during fasting allows binding of glucocorticoid receptors (GR) to their respective

binding elements (GRE) in the nucleus to regulate the transcription of gluconeogenic

target genes (Schoneveld, Gaemers et al. 2004). On the other hand during feeding

states, insulin signalling gets activated and results in phosphorylation of FoxO and

CRTC2 hence transcriptional inactivation and cytoplasmic exclusion (Brunet 2004).

High levels of insulin also limit SIRT1 activity, which results in PGC-

1α transcriptional inactivation. Transcriptional activities of several hepatic nuclear

Introduction

26

factors (HNFs) are modulated by interaction with the corepressor “small heterodimer

partner (SHP)” (Yamagata, Daitoku et al. 2004) and DAX1 the dosage-sensitive sex

reversal adrenal hypoplasia congenital critical region on the X chromosome gene 1

(DAX-1). Both DAX-1 and SHP function as corepressors and expressed in the liver in

response to fed conditions (Nedumaran, Hong et al. 2009). All these events lead to

transcriptional inactivation and attenuation of hepatic glucose production during

feeding conditions (Figure 6).

Introduction

27

Figure 6: Hepatic transcriptional modulation of gluconeogenic enzymesG6Pase and PEPCK during fasting (A) and Feeding (B) conditions (Jitrapakdee2012)

A. During fasting conditions due to low glucose level pancreatic α-cells release glucagon and

glucocorticoids. The resulting activation of glucagon signalling signals several transcription factors

involved in the regulation of gluconeogesis such as PGC-1a, CREB, CRTC2, FOXO1 to move into the

nucleus and bind to their respective promoters to regulate gluconeogenic enzymes such as glucose-6

-phosphatase (G6Pase) and phosphoenolpyruvatecarboxykinase (PEPCK). B. However, during

feeding conditions insulin released from pancreatic β-cells in response to high glucose levels results in

activation of insulin signalling that inactivate and cause nuclear exclusion of transcription factors such

as FOXO1 and CRTC2 critical for gluconeogenesis. In addition certain other transcription factors

important for glconeogenesis such as hepatic nuclear factors (HNFs) and PGC-1α are modulated by

corepressors such as SHP and DAX-1 resulting in overall inhibition of gluconeogenesis during feeding

conditions.

1.3.3 Regulation of hepatic Lipid metabolism

Fattyacids are metabolized with in the hepatocytes to yield energy serving as a feul

during the process of starvation. Under normal physiologic conditions free fatty acids

(FFA) derived from lipid breakdown in the adipose tissue are taken up by fatty acid

transporters (FATP2 and FATP5) into the hepatocytes under the control of insulin

Introduction

28

signalling and nuclear receptor (Figure 7). Fatty acids are oxidized

intramitochondrially thereby generating acetyl-CoA that enters into the tricarboxylic

acid cycle (TCA). Triglycerides (TAGs) synthesized from denovo lipogenesis are

stored in the form of lipid droplets (LP) or packaged into very low-density lipoprotein

(VLDL) and thus released into blood stream. Depending upon the nutritional status

fatty acids are again released from the lipid droplet by the process of autophagy to

provode energy. (Shibata, Yoshimura et al. 2009; Singh, Kaushik et al. 2009). An

impaired hepatic glucose and lipid metabolism leads to the development of type2

diabetes (Bouche, Serdy et al. 2004).

Figure 7: Hepatic lipid metabolism (Bechmann, Hannivoort et al. 2012)

Under normal physiological conditions fatty acids enter into the hepatocytes and oxidized

intramitochondrially to release energy and acetyl-CoA that enter into TCA cycle. Triglycerides

synthesized are either stored as lipid droplets LP or package into very low-density lipoprotein VLDL.

The LD also serves as a source of feul during caloric restriction and is released by the process of

autophagy.

Introduction

29

1.4 Diabetes mellitus

Diabetes mellitus is represented by high blood glucose levels (Table 3) as a result of

insufficient insulin action for the body´s need. It is a major healthcare problem

because it increases the risk for several other diseases e.g cardiovascular disease,

renal failure, and peripheral neuropathy. As a consequence it places a severe

economic burden on healthcare systems and governments. It is a heterogeneous

disorder with insulin resistance and pancreatic β-cell dysfuntion. (Nolan, Damm et al.

2011; Ashcroft and Rorsman 2012).

Table 3: Diagnostic criteria for diabetes, Imapired fasting glucose (IFG),Impaired glucose tolerance (IGT) (Nolan, Damm et al. 2011)

Diabetes

(WHO and ADA)

IFG and IGT

(WHO)

Prediabetes

(ADA)

HbA 1c ≥6.5% NA ≥ 5.7% and < 6.5%

Fasting plasmaglucose (mmol/L)

≥ 7.0 (≥ 126 mg/dl) IFG ≥ 6.1 and < 7.0 ≥ 5.6 and < 7.0

75g OGTT post-

load plasma

glucose (mmol/L)

2h,≥11.1(≥ 200 mg/dl) IGT 2h ≥ 7.8 and < 11.1 2h ≥ 7.8 and < 11.1

Random glucose

(mmol/L)

≥11.1 (≥ 200 mg/dl) with

classic symptoms

NA NA

Although the diagnostic criteria of World health organization (WHO) and American

diabetes association (ADA) for diabetes are identical, the measures to assess

intermediate hyperglycemia or prediabetes are different. IFG: impaired fasting

glucose, IGT: impaired glucose tolerance, HbA1c: glycated haemoglobin A1c. NA:

not applicable, OGTT: oral glucose tolerance testing.

1.4.1 Type 2 Diabetes mellitus

Type 2 diabetes mellitus is a complex disorder characterized by hyperglycemia, and

altered lipid metabolism caused by β-cell dysfunction (mainly impaired insulin

Introduction

30

secretion) and inactivity, overnutrition, obesity and peripheral insulin resistance

(Nolan, Damm et al. 2011; Ashcroft and Rorsman 2012). Type 2 diabetes accounts

for almost 90% of diabetes cases worldwide. The prevelance of diabetes is higher in

middle-income and upper-middle countries. When people become richer they often

eat more fat-rich and sugar-rich diet and are less physically active. The International

Diabetes Federation in 2011 announced that 336 million people across the world are

suffering from type 2 diabetes and the disease leads to 4.6 million deaths each year.

The highest death rate (more than one million) occurs in China and less than a

million are in India. The highest prevelance of diabetes occurs in Middle East

countries due to their rapid economic development with Qatar having (23%) the

highest prevelance in the world followed by (19%) in United arab emirates (UAE),

Egypt and Saudi Arabia (Scully 2012) (Ashcroft and Rorsman 2012).

Hyperglycemia is an increase of blood sugar levels it occurs as a result of insufficient

insulin production or enough insulin is being produced from pancreatic β-cells but the

body is not making an effective use of insulin followed by insulin resistance and type

2 diabetes. Under insulin resistance conditions insulin production by pancreatic β-

cells increases to meet the high demand resulting in an increase of β-cell mass and

compensatory hyperinsulinemia. The major contributors of insulin resistance and

impaired glucose tolerance are obesity and overweight. Abormalities in hormones

such as impaired insulin secretion, impaired glucagon secretion, reduced secretion of

the incretin glucagon-like-peptide1 (GLP-1), reduced glucose uptake by skeletal

muscle and adipose tissue, and increased concentration of other counter regulatory

hormones promotes insulin resistance and hyperglycemia in type 2 diabetes

(Tahrani, Bailey et al. 2011) (Figure 8).

Introduction

31

Figure 8: Pathogenesis of hyperglycemia in type 2 diabetes (Tahrani, Bailey etal. 2011) Impaired action of multiorgan system resulting in hyperglycemia in type2 diabetes.

Impaired secretion of hormones e.g reduced secretion of incretin hormones glucagon like peptide1

(GLP-1), increased glucagon secretion hyperglucagonemia, impaired insulin secretion, uncontrolled

hepatic glucose production by the liver, Impairment of neurotransmitter function in the brain,

decreased uptake of glucose in skeletal muscle, abnormalities in the reabsorption of glucose in the

kidney, elevated lipolysis and impaired glucose uptake by adipose tissue, all these abnormalities

culminates in hyperglycemia in type 2 diabetes.

1.4.2 Obesity and type2 diabetes

The catastrophic increase in T2D over the last 50 years is due to the concomitant

increase in Obesity. The major risk factor in type 2 diabetes is obesity as it reduces

insulin sensitivity in peripheral tissues by directly affecting the β-cell function (Donath,

Dalmas et al. 2013). From the very first studies it was shown that increased adipose

tissue, in the upper body is correlated with diabetes (Vague 1996). In obesity

primarily muscle and liver insulin resistance are involved due to enhanced adipose

tissue derived free fatty acids stimulating triglyceride accumulation in liver and

muscle (Perseghin, Petersen et al. 2003). Interestingly most obese people with

insulin-resistance states do not develop type 2 diabetes because their β-cell are able

Introduction

32

to compensate for increase demand of insulin secretion and this is influenced by their

strong genetic constitution (Bergman 2005; Ashcroft and Rorsman 2012). Many

healthy overnourished obese individuals do not develop diabetes they safely deposit

the excess calories to subcutaneous adipose tissue (SAT) rather then to skeletal

muscle, liver, heart and islet β-cell as a result the key organs of the body are not

effected due to following processes including compensation of islet β-cell,

development of minimal insulin resistance and less increase in liver fat (Wajchenberg

2000; Stefan, Kantartzis et al. 2008) (Figure 9). Conversely susceptible

overnourished people develop diverse metabolic defects: inability of β-cell to

compensate for fuel surfeit, hyperadiponectinemia, adipose tissue inflammation,

impaired hepatic glucose production and devlopment of peripheral insulin resistance

(Kahn 2003; Defronzo 2009). A strong interplay between genetics, diabetes and

obesity is evidenced by a report showing that triglyceride emulsion in a non-diabetic

people who had first-degree relatives with T2D showed decrease in insulin secretion

but not in others (Kashyap, Belfort et al. 2003). This showed that genetic differences

become obvious only in the presence of elevated fat.

Introduction

33

Figure 9: Pathways and related complications of type 2 diabetes (Nolan, Dammet al. 2011) .

Additionally several mechanisms such as: tissue inflammation, lipotoxicity (caused by

ectopic lipid accumulation or elevated free fatty acids (FFA), glucotoxicity (caused by

sustained hyperglycemia), oxidative stress (caused by FFA or glucose) and

endoplasmic reticulum stress (ER) have been shown to impair insulin secretion,

induce pancreatic β-cell dysfunction and insulin resistance in type 2 Diabetes (Wilcox

2005) (Donath and Shoelson 2011; Samuel and Shulman 2012).

Introduction

34

1.4.3 Factors controlling β-cell mass and T2D

Several studies points to the reduction of β-cell mass in T2D although there is a

continuous ongoing debate about this controversy and it is also unclear whether T2D

occurs as a result of reduced β-cell mass or it developed as a consequence of

sustained hyperglycemia (Ashcroft and Rorsman 2012). It was also evidenced that

reduced number of β-cell rather than impaired β-cell function are the major

contributors of T2D (Butler, Janson et al. 2003). β-cell mass is also influenced by

long term insulin secretion and certain growth hormones prolactin, placental lactogen

and GLP1 increases β-cell proliferation in addition to glucose stimulated insulin

secretion and insulin gene expression (Nielsen, Galsgaard et al. 2001; MacDonald,

El-Kholy et al. 2002). Importantly on the other hand β-cell hyperplasia in insulin

resistance states driven by liver-derived systemic factors has also been reported (El

Ouaamari, Kawamori et al. 2013). Furthermore the role of betatrophin hormone,

which is primarily expressed in liver and fat induces a dramatic increase in β-cell

proliferation, β-cell expansion and improves glycemic control in mouse models of

insulin resistance (Yi, Park et al. 2013). It is uncertain that how much β-cell mass is

needed for the proper glycemic control nevertheless it was suggested that 40% of β-

cell mass is sufficient for normal glucose homeostasis and it is supported by the

notion that removal of almost half of pancreas has only a small effect on glucose

tolerance (Menge, Tannapfel et al. 2008). This suggests that although β-cell mass

plays some important role in T2D but this is not the only, or even the most pivotal,

factor in T2D (Ashcroft and Rorsman 2012).

1.4.4 Molecular mechanism of Insulin resistance

Disruption of insulin signaling, at different levels of insulin signalling pathways are the

major characteristic of insulin resistance states (Kwon and Pessin 2013). Insulin

resistance at the molecular level can be acquired by either decreased or increased

degradation or decreased transcriptional activities of critical components of insulin

signalling cascade e.g IRS1, IRS2 (Bar, Harrison et al. 1979; Shimomura, Matsuda et

al. 2000; Zhande, Mitchell et al. 2002). It was reported previously that increased

stimulation of SREBP1-c could inhibit transcription of IRS-2 levels (Ide, Shimano et

Introduction

35

al. 2004) suggesting that interaction between signalling components regulate one

another. Serine phosphorylation of insulin receptor and IRS proteins by ERK, PKB

and the oxidative stress kinases JNK and IKKβ can impair their tyrosine kinase (Liu,

Paz et al. 2001) (Gao, Hwang et al. 2002; Hirosumi, Tuncman et al. 2002) activity

and futher association with 14-3-3 proteins cause the removal from the insulin

signalling pathways (Craparo, Freund et al. 1997). Several inhibitory proteins can

interact with components of insulin signalling cascade to produce insulin resistance

such as several inflammatory cytokines induce the suppressors of cytokine signalling

proteins (SOCS) which binds to insulin receptor and attenuate insulin signalling

pathway (Emanuelli, Peraldi et al. 2000; Rui, Yuan et al. 2002) (Figure 10).

Additionally insulin resistance can be due to increase in amount and activities of

phosphotyrosine phosphatases enzymes that normally reverse insulin action e.g

PIP3 phosphatases, PTEN and SHIP (Nakashima, Sharma et al. 2000; Clement,

Krause et al. 2001). Finally the phenotype of insulin resistance depends on the exact

components of affected insulin signalling pathway and the exact tissues in which the

components of insulin signalling are affected (Biddinger and Kahn 2006).

Figure 10: Molecular events that can result in insulin resistance (Biddinger andKahn 2006)

Introduction

36

1.4.5 Genetics of Type 2 Diabetes mellitus (T2DM)

Genome wide association (GWAS) and linkage studies have discovered more than

60 genes correlated with increased risk of type2 diabetes mellitus (Morris, Voight et

al. 2012) (Bonnefond, Froguel et al. 2010; McCarthy 2010; Taneera, Lang et al.

2012). Several studies have shown that many of these genes are important for β-cell

function, β-cell development, regulation of β-cell mass and some are associated with

hepatic glucose production, insulin resistance and predisposition to obesity such as

FTO (fat mass and obesity-related gene). Although it is uncertain how these genes

predispose to full blown diabetes (Bonnefond, Froguel et al. 2010; McCarthy 2010).

The important diabetes suscebtible gene identified is TCF7L2 a transcription factor

(T-cell factor 7 like-2) involved in WNT signalling. It has been shown that the risk

allele for TCF7L2 was associated with altered insulin secretion and improved hepatic

glucose production rate (Lyssenko, Lupi et al. 2007; McCarthy, Rorsman et al. 2013).

Other genes involved in impaired β-cell function include (KCNJ11, TCF7L2, WFS1,

HNF1B, SLC30A8, CDKAL1, IGF2BP2, CDKN2A, CDKN2B, NOTCH2, CAMK1D,

THADA, KCNQ1, MTNR1B, GCKR, GCK, PROX1, SLC2A2, G6PC2, GLIS3,

ADRA2A, and GIPR) and some important genes involved in impaired insulin

senstivity include (PPARG, IRS1, IGF1, FTO, and KLF14) (Nolan, Damm et al. 2011)

(Figure 11).

Introduction

37

Figure 11: Genetic risk factors associated with type 2 diabetes (McCarthy 2010)

1.4.6 Animal models of type 2 diabetes

Several invivo genetic models are greatly useful as they provide new awareness into

the functions of human diseases. Obesity, insulin resistance and type 2 diabetes can

be induced by various diet/nutritional, chemical, surgical agents and knockout or

transgenic approaches (Table 4) (Chatzigeorgiou, Halapas et al. 2009) . The most

characteristic examples of T2DM model include db/db, ob/ob and Zucker fatty rat

(ZFR). The diabetic models db/db and ob/ob mice develop obesity due to autosomal

recessive mutations in leptin and leptin receptors genes that finally leads to diabetes.

While Zucker fatty rats (ZFR) phenotype is associated with hypothalamic defect in

leptin receptor signalling, and particular inbreeding of zucker fatty rat for

hyperglycemia gave birth to zucker diabetic rats (ZDF). Of these models the ob/ob

mouse and zucker fatty rat (ZFR) is characterized by mild to moderate

hyperglycemia, hyperinsulinemia, hyperphagia, obesity and insulin resistance. These

mice do not develop diabetes because of compensatory action of `sturdy´ pancreatic

β-cells capable of maintaining lifelong insulin secreting capacity (Durham and Truett

2006; Srinivasan and Ramarao 2007; Chatzigeorgiou, Halapas et al. 2009). On the

other hand zucker diabetic fatty rats (ZDF) and db/db mouse have pancreatic β-cells

Introduction

38

which are `labile or brittle´ enabling only for a short-term hyperinsulin secretion for

obesity.

Eventually as a result of other environmental and genetic predisposition factors it

induces pressure on pancreatic β-cells for insulin secretion and which ultimaltely

leads to apoptosis, degranulation and overt hyperglycemia. At this stage, the animals

lose their accumulated fat, suffer from ketosis and require lifelong insulin therapy.

This ZDF rat and db/db mouse resemble nearly to type 2 diabetes of humans

(Srinivasan and Ramarao 2007).

Table 4: Animal models of type 2 diabetes (T2D) (Srinivasan and Ramarao2007)

Model category Type 2 diabetic modelsObese Non obese

Spontaneous or geneticallyderived diabetic animals

ob/ob mousedb/db mouseKK mouseKK/Ay mouseNZO mouseNONcNZO10 mouseTSOD mouseM16 mouse

ZDF ratSHR/N-cp ratJCR/LA-cp ratOLETF ratObese rhesus monkey

Cohen diabetic ratGK ratTorri rat Non obese C57BL/6(Akita) mutant mouse

ALS/Lt mouse

II. Diet/nutrition induced diabeticanimals

Sand ratC57/BL 6J mouseSpiny mouse

III. Chemically induced diabeticanimals

GTG treated obese mice

IV. surgical diabetic animals VMH lesioned dietary obesediabetic rat

Introduction

39

V. Transgenic/knock-outdiabetic animals

β3 receptor knockout mouseUncoupling protein (UCP1)knock-out mouse

Low dose ALX or STZ adultrats, mice, etc.Neonatal STZ rat

Par t ia l pancreatectomizedanimals e.g. dog, primate, pig &rats

Transgenic or knockout miceinvolving genes of insulin andinsul in receptor and i tscomponents of downstreaminsulin signalling e.g.

IRS-1, IRS-2, GLUT-4, PTP-1Band othersPPAR-C tissue specific knockoutMouse

Glucokinase or GLUT 2 geneknockout mice

Human islet amyloid

1.5 Metformin

1.5.1 Metformin as an anti-hyperglycemic agent

The most widely recommended drug to treat hyperglycemia in patients with type 2

diabetes is Metformin (1,1-dimethylbiguanide), a derivative of biguanide. According to

the guidelines of American Diabetes Association and European Association of the

Study of Diabetes, Metformin is used as the first line of oral therapy (Adler, Shaw et

al. 2009; Nathan, Buse et al. 2009). Additionally Metformin is also used for treating

several other diseases e.g as cancer preventive drug (Marchesini, Brizi et al. 2001;

Evans, Donnelly et al. 2005; Ben Sahra, Le Marchand-Brustel et al. 2010), in cases

with fatty liver diseases (Nair, Diehl et al. 2004), in pregnancy during gestational

diabetes (Rowan, Hague et al. 2008; Balani, Hyer et al. 2009), and to reduce

macrovascular and microvascular complication in T2D (Hurst and Lee 2003). In

cases with type 2 diabetes metformin is recently being prescribed to at least 120

million people worldwide and the antihyperglycemic effect of metformin works by

lowering the blood glucose concentrations without causing overt hypoglycemia

(Viollet, Guigas et al. 2012). It was shown that metformin is the best insulin sensitizer

in cases of insulin resistance where metformin reduces the fasting plasma insulin

Introduction

40

levels. Metformin improves insulin sensitivity through positive effects on activation of

insulin signalling by increased tyrosine kinase activity and increased insulin receptor

expression (Gunton, Delhanty et al. 2003). It has been shown from animal models

and clinical studies that metformin reduces hepatic glucose production principally by

inhibiting hepatic gluconeogenesis (Cusi, Consoli et al. 1996; Hundal, Krssak et al.

2000; Natali and Ferrannini 2006). Metformin-induced attenuation of hepatic glucose

production is mediated by changes in enzymatic activities and decreased uptake of

gluconeogenic substrates to liver. It is shown in high-fat diet insulin resistant rats that

metformin lowers hepatic gluconeoenesis by inhibiting the activity of glucose-6-

phosphatase (G6pc) (Argaud, Roth et al. 1993; Radziuk, Zhang et al. 1997; Mithieux,

Guignot et al. 2002).

1.5.2 Mechanism of Metformin action

The exact and precise mechanism of hepatic metformin action is a matter of debate

and still unknown. The explanation of such a mechanism is pivotal issue as it may

unveil new targets for the treatment of type 2 diabetes. Metformin at the physiological

pH exist as organic cation acts as a hydrophilic base and can only pass through the

plasma membrane by passive diffusion (Detaille, Guigas et al. 2002; Viollet, Guigas

et al. 2012). The cationic transporters, which are involved in the intracellular

internalization of metformin, are (OCTs). OCT1 transport metformin to the liver and

OCT2 transports metformin to the kidney (Graham, Punt et al. ; Shu, Sheardown et

al. 2007). Metformin is mostly acculmulated in the liver than in any other tissues

(Wilcock and Bailey 1994). The molecular targets and mechanism of Metformin

action was difficult to achieve for several years. It has been shown that multiple

actions of Metformin are associated with activation of AMPK (AMP-activated protein

kinase) (Zhou, Myers et al. 2001). AMPK is serine/threonine protein kinase, which is

phylogenetically conserved among eukaryotes. Under stress condition activation of

AMPK protect the cellular functions. AMPK exists as heterodimeric complexes

comprising a catalytic-α subunit, two regulatory subunits β and γ (Corton, Gillespie et

al. 1994; Viollet, Guigas et al. 2012) (Hardie, Scott et al. 2003; Kahn, Alquier et al.

2005). AMPK is activated under cellular stress conditions, an increased cellular

AMP/ATP ratio or when ATP is depleted (Hardie, Scott et al. 2003; Carling 2004;

Hardie 2004; Viollet, Guigas et al. 2012). AMP promotes the AMPK activation, by

Introduction

41

stimulating phosphorylation at a critical threonine residue (Thr172) of the kinase

domain at catalytic-α subunit. AMPK is activated by upstream kinases such as

serine/threonine kinase 11 (STK11/LKB1) identified as tumor suppressor (Viollet,

Guigas et al. 2009). When AMPK is activated it turn off the anabolic pathways and

triggers the catabolic pathways as a result production of glucose, lipid synthesis and

protein synthesis are inhibited and utilization of glucose and oxidation of fatty acid get

started.

Of notice it was shown that metformin does not directly activate AMPK, the primary

target for metformin are the mitochondria where metformin blocks mitochondrial

respiratory chain at the complex 1, resulting in lower oxidation of NADH, decreased

pumping of protons across the inner mitochondrial membrane leading to lowering of

proton gradient that results in reduced proton-driven synthesis of ATP (Viollet,

Guigas et al. 2012) (Figure 10). Inhibitory effect of metformin through blocking

mitochondrial respiratory chain complex 1 was shown in isolated hepatocytes and

perfused livers from rodents (El-Mir, Nogueira et al. 2000; Owen, Doran et al. 2000).

It was also shown in human primary hepatocytes that metformin firstly targets

complex 1 of mitochondrial respiratory chain resulting in decreased cellular energy

status that activates AMPK (Stephenne, Foretz et al. 2011).

Introduction

42

Figure 12: Metformin target mitochondrial respiratory-chain complex 1 (Viollet,Guigas et al. 2012). Metformin has a positive charge and can pass across the cell membrane by

passive diffusion and internalized with in the hepatocytes with the help of OCT1 transporters in the

liver. Once the drug is with in the liver mitochondria are the primary targets. Metformin selectively

inhibits the complex-1 of the respiratory chain without affecting the other complexes this causes a

decrease in oxidation of NADH, consumption of oxygen rate and resulting in decreasing proton

gradient across the mitochondrial membranes and subsequently it results in lowering proton-driven

synthesis of ATP.

Importance of AMPK activation in antidiabetic effect by metformin was firstly

supported from the study showing that mice lacking hepatic LKB1 were unable to

lower the blood glucose and this also showed that metformin require LKB1 in the liver

to reduce the levels of blood glucose (Shaw, Lamia et al. 2005). Importantly it was

evidenced that LKB1/AMPK signalling regulates phosphorylation and cytoplasmic

translocation of CREB-regulated transcriptional coactivator 2 (CRTC2 also reffered to

as TORC2) (Shaw, Lamia et al. 2005). CREB is critical regulator of hepatic

gluconeogenic programme in mice (Koo, Flechner et al. 2005). TORC2 interact with

CREB to regulate the expression of PGC-1α and gluconeogenic target genes

phosphoenolpyruvatecarboxykinase (PEPCK) and glucose-6-phosphatase (G6Pase).

Introduction

43

AMPK or AMPK related kinases are involved in the phosphorylation of CRTC2 that

results in degradation of complex and hence inhibiting the gluconeogenic programme

(Koo, Flechner et al. 2005; Shaw, Lamia et al. 2005) (Figure 11).

Furthermore metformin induced activation of AMPK results in the upregulation of an

orphan nuclear receptor small heterodimer partner (SHP), which works as a

transcriptional repressor (Kim, Park et al. 2008). SHP represses the transcriptional

activities of FoxO1, hepatocyte nuclear factor 4-α and a number of nuclear receptors

that are involved in regulation of gluconeogenesis (Lu, Makishima et al. 2000; Lee

and Moore 2002; Kim, Kim et al. 2004; Yamagata, Daitoku et al. 2004). In addition

SHP inhibits hepatic gluconeogenic gene expression through interaction with CREB-

CBP complex and CRTC2 (Lee, Seo et al. 2010). Furthermore metformin induced

inhibition of gluconeogenesis is also supported by the role of Krüpple-like factor 15

(KLF15). Krüpple-like factor 15 is highly expressed in the liver and plays an important

role in the regulation of gluconeogenesis in the liver. Previously it was shown that

KLF15 is up-regulated in diabetic mice with increased expression of PEPCK gene in

the liver (Teshigawara, Ogawa et al. 2005; Gray, Wang et al. 2007). Metformin

suppresses the KLF15 gene expression and induces proteosomal degradation by

promoting its ubiquitination (Takashima, Ogawa et al. 2010).

Interestingly it was further showed by recent reports stating that AMPK and LKB1

activities are dispensable for inhibition of gluconeogenesis by metformin (Foretz,

Hebrard et al. 2010). Indeed metformin inhibits the process of gluconeogenesis

independent of AMPK activation through decrease in hepatic energy status (Miller

and Birnbaum 2010). This decrease in energy status by blocking mitochondrial

respiratory chain complex 1 leads to acute inhibition of gluconeogenesis through

allosteric regulation of key enzymes such fructose-1, 6-biphosphatase independent

of gluconeogenic gene expression (Miller and Birnbaum 2010).

Metformin also play a beneficial role in improving the disorders of lipid metabolism. It

was shown previously in leptin deficient ob/ob mice that metformin improves fatty

liver disease (Lin, Yang et al. 2000; Cool, Zinker et al. 2006). Metformin has also

been proved useful in patients suffering from alcoholic steatohepatitis (Marchesini,

Brizi et al. 2001; Nair, Diehl et al. 2004; Raso, Esposito et al. 2009). Metformin-

induced activation of AMPK inactivates acetyle CoA carboxylase (ACC) by

phosphorylation and activates fatty acid oxidation. ACC is the rate-limiting enzyme for

the production of malonyl-CoA, which is important precursor for the synthesis of fatty

Introduction

44

acids and an important inhibitor for mitochondrial fatty acid oxidation (Zhou, Myers et

al. 2001). In addition metformin-induced activation of AMPK inhibits fatty acid

synthesis through regulating sterol regulatory element-binding protein-1c (SREBP1)

gene expression and thereby inhibiting lipogenesis (Li, Xu et al. 2011).

In summary metformin plays an important role in inhibition of gluconeogenic gene

programme via both AMPK-dependent and AMPK-independent mechanism through

controlling several critical regulatory points (Figure 11) (Viollet, Guigas et al. 2012).

Figure 13: Mechanism of metformin action in controlling hepaticgluconeogenesis (Viollet, Guigas et al. 2012). Metformin attenuate the process of

gluconeogenesis either AMPK-dependent or AMPK-independent signalling pathways through

controlling several critical regulatory points.

Introduction

45

1.6 Aims of study

The interplay between different FoxO family members sharing the conserved DNA

binding domain is far from being understood and this may account for the paradoxical

findings described above (Biddinger and Kahn 2006). Importantly, in addition to

FoxO1, FoxO3 is also significanly expressed in the liver, its contribution to metabolic

regulation has however not been thoroughly analysed. Interestingly FoxO3

genotypes are associated with insulin sensitivity phenotypes and longevity in humans

suggesting that FoxO3 is critical for metabolic control (Willcox, Donlon et al. 2008;

Flachsbart, Caliebe et al. 2009; Pawlikowska, Hu et al. 2009). The relative

contribution of individual FoxO proteins has not been addressed the reason behind

this might be experimental approaches (most of which are loss of function studies),

cell type specific functions and the context-and kinetic-specific stimulation, which

might affect the biological outcome of the FoxO signalling system. Therefore a

refined study using a conditional gain-of-functional model should be capable to unveil

the functions of FoxO3 in the liver under physiological conditions. This would also

help to estimate the usefulness of FoxO3 inhibitors in diabetes therapy. To achieve

this goal, firstly this study was designed to establish a mouse model that allows for

conditional regulation, activation of FoxO3 activity specifically in liver-cells. Further,

The morphological, functional, and biochemical consequences of transgene

expression should be investigated. Specifically the following questions will be

addressed in detail:

1. Does liver-specific expression of constitutively active FoxO3 (LAP-tTA x (tetO)7-

FOXO3CA) interfere with metabolic liver functions?

2. What are the consequences of expression of FoxO3CA in regulation of hepatic

glucose and lipid homeostasis?

Material and Methods

46

2 Materials an Methods

2.1 Mice

We crossed mice expressing the tetracycline-responsive transactivator (tTA) under

the control of the rat liver activator protein (LAP) promoter (Sunami, Leithauser et al.

2012) with mice bearing a constitutively active human FOXO3 allele (FOXO3CA)

(Schmidt-Strassburger, Schips et al. 2011; Schips, Wietelmann et al. 2011) under the

control of a tTA-regulated promoter. Studies were performed on a C57BL/6xNMRI

mixed background. FOXO3CAHep mice contain a bidirectional promoter, which

mediates simultaneous expression of FOXO3 and luciferase that was used for in vivo

imaging analysis and in vitro luciferase assays as described (Schmidt-Strassburger,

Schips et al. 2011; Schips, Wietelmann et al. 2011; Sunami, Leithauser et al. 2012).

Mice were kept in a specific pathogen-free (SPF) animal facility at University of Ulm.

Experiments were approved by the state of Baden-Württemberg in Germany.

2.1.1 Doxycycline administration

To avoid embryonic activation of FOXO3CA, all mice received 0.1g/L doxycycline in

1% sucrose in drinking water during pregnancy untill mice were born. Afterwards, the

doxycycline (DOX) (MP Biomedicals Eschwege) was withdrawn to activate the

FOXO3CA expression and the mice were analysed at 4-weeks of age. To avoid the

developmental defects and lethality at the earlier time point of FOXO3CA activation

the animals received Doxycycline 0.1g/L Doxycycline in 1% sucrose in drinking water

untill the newborn animals reached 5-weeks of age and the Doxycycline was

withdrawn after 5-weeks to activate the expression of FOXO3CA and the animals

were analysed at the age of 7-weeks or at 9-weeks.

2.1.2 Metformin administration

Metformin (1,1-Dimetylbiguanide hydrochloride, D150959, Sigma-Aldrich) was orally

administered in drinking water (1.65 g/l). Schedule of metformin administration is

shown in the (Figure 34). For the analysis at the age of 7-weeks, metformin

administration was performed for the last 3 days untill the animals become 7-weeks.

Material and Methods

47

For the analysis at the age of 9-weeks metformin was administered for three weeks

untill the animals become 9-weeks of age. For each experiment mice were fasted for

6 hours prior to the analysis. During 6 hours fasting period mice drink the normal

drinking water.

2.2 Genotyping

2.2.1 Isolation of genomic DNA

Extraction of genomic DNA was made from the tail tips of mice. Tails were incubated

over night at 56°C for digestion with the DNA lysis buffer (733 µl TNES-buffer with 17

µl proteinase K (20 µg/ µl)). Afterwards, 250µl of 6M NaCl was used and

centrifugation was done at 13000 rpm for 10 min at room temperature. The

supernatent was transferred to a fresh eppendorf tube. Genomic DNA was

precipitated by supplying equal volume of isopropanol to the pellet followed by

centrifugation at 13000 rpm for 10 min. DNA pellet was washed with 500 µl of 70%

ethanol, dried for 10 min. Dried DNA was dissolved in 250 µl sterile ampuwa water.

2.2.2 Polymerase chain reaction (PCR)

The transgenes tTA and FOXO3CA were detected by PCR with specific pair of

primers and applying the following recipe,

Reaction mix:

DNA sample: 2 µl

dNTPs 2mM: 3 µl

5x GoTaq buffer: 6 µl

primers 10 µM: 1µl

water: 16.8 µl

Taq 5000 U/ml: 0.2 µl

Primers sequences:

tTA 5´ gctaggtgtagagcagcctacattg

tTA 3´ gtccagatcgaaatcgtctagcgcg

FOXO3-P17 catggagtctgcggccgtctcc

FOXO3-P48 ggtacccggggatcctctagtcag

Material and Methods

48

PCR programmes

2.3 In Vivo Bioluminescence imaging

To determine liver-specific transgene expression, mice were anesthetized by

continous inhalation of 2% vol/vol isoflurane.and injected intraperitoneally with 25 mM

Luciferin (Synchem OHG) (150µg/g body weight). Bioluminescence was monitored 1

minute after injection by the IVIS imaging system Xenogen IVIS 200 System (Caliper

Life Sciences, Hopkinton, MA, USA) as previously described (Schmidt-Strassburger,

Schips et al. 2011; Schips, Wietelmann et al. 2011; Sunami, Leithauser et al. 2012).

2.4 Metabolic studies

2.4.1 Glucose Tolerance Test (GTT) and Insulin Tolerance Test (ITT)

Glucose Tolerance Test (GTT) and Insulin Tolerance Test (ITT) were performed in 7-

week-old animals. For GTT, animals were fasted for 6 hours during fasting animals

were provided with drinking water, After 6 hour fasting the blood glucose was

measured from the tail vein and then injected with glucose (0.75 g / kg body weight)

intraperitoneally (i.p.). Tail vein blood was collected and blood glucose values were

measured with glucometer (One Touch Ultra II, Life Scan) at the indicated time points

PCR LAP.tTA (tetO)7.FOXO3CA

Start 94°C /3 min 94°C /3 min

Cycles 33 cycles 33 cycles

Annealing

Synthesis

Denaturation

94°C /45 sec

62°C /45 sec

72°C /1 min 20 sec

94°C /45 sec

62°C/ 45 sec

72°C /1 min 20 sec

End 72°C 2 min 72°C 2 min

Material and Methods

49

after every 30 minutes for two hours.

For Insulin tolerance test (ITT), the animals were not fasted they were in the random-

fed state and then injected intraperitoneally (i.p.) with insulin (0.75 U / kg body

weight, Actrapid Penfill Novo Nordisk). Blood glucose levels were measured from tail

vein at the indicated time points after every 15 minutes for 1 hour.

2.4.2 Animal studies

Mice were sacrificed via CO2 inhalation, and blood was collected from vena cava

inferior. After brief centrifugation, serum was collected and used for measurement of

alanine and aspartate aminotranferase levels (ALT and AST) as well as bilirubin,

triglycerides, cholesterol, alkaline phosphatase (ALP), were measured by

(Reflotron,Roche). Albumin, pseudocholinesterase, urea, and creatinine levels were

measured by (Technical University of Munich). Blood glucose measurement was

performed immediately after a collection of tail vein blood with glucometer (One

Touch Ultra II, Life Scan).

2.4.3 Enzyme-linked immunosorbent assay (ELISA)

All the ELISA were performed in serum from 6 hour fasted animals with following kits

Kits Catalog number/ Company

Insulin (90080) from Crystal Chem

glycogen (K648-100) from BioVision

β-hydroxybutyrate / ketone bodies (700190) from Cayman chemicals

All the ELISA were performed according to the manufacturers instruction.

2.5 Protein biochemistry

2.5.1 Protein extraction with Dignam C buffer

Material and Methods

50

Mice were sacrificed by the way of CO2 inhalation; tissues were collected for protein

and RNA isolation and rapidly snap frozen in liquid nitrogen. For preparing the

protein extract for SDS-PAGE the liver tissues were incubated in 3-5 volumes of

Dignam C buffer additionally supplemented with 1mM DTT, Roche complete mini

protease inhibitor (1 tablet/10 ml) and finely grinded with the help of tissue lyser

(Tissue lyser Retch, Qiagen, Germany). Afterwards the crude extract was centrifuged

(13000rpm for 30min at 4 °C) and the pellet was discarded. Finally the protein

concentration in the supernatant was determined by a Bradford assay.

2.5.2 Protein concentration measurement by Bradford method

2 µl of protein extracts made with Dignam C buffer was mixed with 100 µl of 150 mM

NaCl and 900 µl of Bradford reagent and vortexed briefly. Optical density of formed

protein/coomassie-brilliantblue complex was measured in photometer at wavelengths

of 595 nm. Protein concentration in extracts was estimated according standard curve

with known concentrations of bovine serum albumin. Protein extracts were shock-

freezed in liquid nitrogen and stored at -80°C.

2.5.3 In vitro Luciferase reporter gene activity measurement

For the exact determination of transgene expression in protein extracts, luciferase

reporter gene activity was measured with the luminometer Lumat LB9507 (Berthold,

Bad Wildbad). For in vitro luciferase assay, 5 µl of protein extract were incubated with

50 µl of luciferase buffer (20 mM Tris, 1.07mM magnesium carbonate, 2.7 mM

magnesium sulfate, 0.1 mM dimethyl sulfoxide (DMSO), 60 mM dithiothreitol (DTT),

1.06mM adenosine triphosphate (ATP), 0.54 mM coenzymeA (CoA), 1 mM luciferin)

and light emission (RLU) was measured over 15 seconds. From mean values of two

measurements the background activity (Dignam C) was subtracted and the obtained

values were normalized to the amount of protein (RLU/ µg).

2.5.4 Western blotting

For SDS-PAGE 20-50 µg of protein were diluted with the Dignam C buffer to a

specific volume and incubated with the appropriate amount of 4x-Laemmli loading

Material and Methods

51

buffer + 5 % β-mercaptoethanol, freshly added for 10 min at 95 °C.

The protein samples were separated on polyacrylamide gels with a 5 %

polyacrylamide stacking gel (with 0.5 M Tris-HCl pH 6.8, 20 % SDS, APS 10%) and a

resolving gel with 8,10,12.5,15 % polyacrylamide depending on the size of the

proteins to detect (with 1.5 M Tris/HCl pH 8.8, 20% SDS, APS 10%). The gels were

run with the electrophoresis system (CBS Scientific Company, California) in a

Tris/glycine/SDS running buffer (25 mM Tris, 192 mM glycine, 0.1% SDS). With the

Trans-Blot-Cell system (CBS Scientific Company, California) the proteins were

transferred to a nitrocellulose membrane (0.45 µm pore size, Whatman), which was

activated with methanol and washed in the blotting buffer (25 mM Tris, 192 mM

glycine, 0.025 % SDS, 20 % methanol).

The membranes are then washed three times with TBS/Tween (0.1 %). Unspecific

protein binding was blocked by incubation with 5 % dry milk powder in TBS/Tween

(0.1 %) for 1 h at RT followed by incubation with primary antibodies (in blocking

solution) overnight at 4° C. After three washes with TBS/Tween the membranes were

incubated with the HRP-coupled secondary antibody (1:5000 in blocking solution) for

1 h at RT. After additional three washes chemiluminescence signals were developed

with ECL (Super Signal West Dura Extended Duration Substrate Thermoscientific)

and detected with X-ray films.

Similarly β-tubulin was detected on the same membrane as a control for equal

loading. The membrane was sometimes reprobed with several antibodies. If old

bands might mask the new bands to detect, the membrane was stripped by

incubation with 0.2 M NaOH for 5 min, followed by thorough washing and new

blocking. The weterns are performed with the following antibodies listed in (Table 5).

Material and Methods

52

Table 5: Antibodies used for immunostaining and immunoblotting

Antigen source Company Cat.no WB dil IF dil IHC dil

FOXO3/FKHRL Rb Santacruz sc-11351 1:1000 1:100 1:100

AKT Rb Cellsignalling 9272 1:1000

T-308phospho-AKT Rb Cellsignalling 4056 1:1000

S-473 phospho-AKT Rb Cell signalling 9271 1:1000

AMPK Rb Cell signalling 2603 1:1000

T172 phospho-AMPK Rb Cell signalling 2535 1:1000

β-Tubulin Abcam Ab6046 1:5000

K8/18 (Ku, Toivola

et al. 2004)

8592 1:100

Insulin Rb Cellsignalling 4590 1:100 1:100

Cd45 Rb Abcam 10558 1:200

Abbreviations: IB Immunoblot, IF immunofluorescence, dil. dilution, Rb rabbit, IHC

2.6 RNA Analysis

2.6.1 RNA extraction and cDNA synthesis

RNA was extracted from liver samples kept in RNAlater (Qiagen) by RNAeasy Mini

Kit (Qiagen), following the manufacturers instruction. Then the RNA was dissolved in

50 µl of DEPC water and the concentration of RNA was measured with the Nanodrop

1000 spectrophotometer (Thermo Scientific). For purity control the ratio of absorption

at 260/280 nm and 260/230 nm was measured. Complementary DNA was generated

from 2 µg of RNA using MMLV reverse transcriptase (Promega) using the

manufacturers instruction. Quantitative real-time PCR was carried out using qPCR

master mix and corresponding universal probe library on Roche LC480 light cycler

system (Roche). Primers are listed in (Table 6). PCRs were performed in triplicates

according to the manufacturer's instructions, with HPRT used as a reference for

relative quantification. Data were corrected for primer efficiency, which was

determined by serial dilution of cDNA.

Material and Methods

53

Table 6 : List of primers used in real time PCR analysis.

Transcript Probe (UPL) L primer R primer

FoxO3 11 cttcaaggataagggcgaca cgactatgcagtgacaggttg

G6PC 19 Tctgtcccggatctaccttg gaaagtttcagccacagcaa

Pdk4 22 Cgcttagtgaacactccttcg cttctgggctcttctcatgg

Pepck1 49 ggagtacccattgagggtatcat gctgagggcttcatagacaag

Igfbp1 66 Ttcagctcccagcatgaag gggctctcagaaagctcatc

Igfbp2 62 gcgggtacctgtgaaaagag cctcagagtggtcgtcatca

Lepr 50 gcacaaggactgaatttccaa ctgatttcttctgaaatgggttc

Pygl 12 Ccagagtgctctaccccaat ccaccacaaagtactcctgtttc

Cpt1α 70 Gactccgctcgctcattc tctgccatcttgagtggtga

Echs 79 Cgggtgagtctctgagtgc ccagagtgctctaccccaat

Acaca 50 Gcctccgtcagctcagatac tttactaggtgcaagccagacat

FAS 19 Gctgctgttggaagtcagc agtgttcgttcctcggagtg

SREBP1 74 ttcctcagactgtaggcaaatct agcctcagtttacccactcct

Acot11 10 Ccatcgtgaataacgccttt ggtacgcctccacacaca

Acss 63 aaatgtgttccaggatacaatgg atcagatatgggctcattttcc

Apom 78 cccagacatgaaaacagacct gagggtgtggtgaccgatt

Aqp7 84 Ggctccagccagaagtca gggccattgtggagttgt

Gckr 53 Gcttcaatccggtgagca tctcctgcatcttctgcatc

Pklr 79 acttagcaaagtctgctttaagtgg tggcacgtctcaggtatcc

Pdk3 7 aagcagatcgagcgctactc ttcacatgcattatcccttcc

Cpt-1b 92 gagtgactggtgggaagaatatg gctgcttgcacatttgtgtt

Fabp5 46 acggctttgaggagtacatga ctcggttttgaccgtgatg

Material and Methods

54

2.6.2 Gene expression analysis

Microarray analyses were performed using 200 ng total RNA as starting material and

5.5 µg ssDNA per hybridization (GeneChip Fluidics Station 450; Affymetrix, Santa

Clara, CA). The total RNAs were amplified and labeled following the Whole

Transcript (WT) Sense Target Labeling Assay (http://www.affymetrix.com). Labeled

ssDNA was hybridized to Mouse Gene 1.0 ST Affymetrix GeneChip arrays

(Affymetrix, Santa Clara, CA). The chips were scanned with an Affymetrix GeneChip

Scanner 3000 and subsequent images were analyzed using Affymetrix® Expression

Console™ Software (Affymetrix).

A transcriptome analyses was performed using BRB-ArrayTools

(http://linus.nci.nih.gov/BRB-ArrayTools.html). Raw feature data were normalized and

log2 intensity expression summary values for each probe set were calculated using

robust multiarray average (RMA, Irizarry et al., 2003).

Filtering: Genes showing minimal variation across the set of arrays were excluded

from the analysis. Genes whose expression differed by at least 1.5 fold from the

median in at least 20% of the arrays were retained.

Class Comparison: We identified genes that were differentially expressed among the

two classes using a 2 sample t-test. Genes were considered statistically significant if

their P value was less than 0.05 and displayed a fold change between the two groups

of at least 1.5 fold.

We used the multivariate permutation test to provide 90% confidence that the false

discovery rate was less than 10%. To identify the most affected biological processes,

as defined by Gene Ontology annotation, we used the GoMINER analysis tool

(Zeeberg et al., 2003) with minor modification. Complete microarray data are

available at Gene Expression Omnibus (GEO accession number: GSE44977

2.7 Histology

2.7.1 Liver tissue preparation

Livers removed from sacrificed animals were weighed and divided into several pieces

that were fixed in 10% formaldehyde for histological/immunohistochemical analysis,

Material and Methods

55

snap frozen in liquid nitrogen for immunofluorescence staining. Livers were

dehydrated in increasing concentration of ethanol and embedded in paraffin

according to standard histological procedures. From the paraffin blocks horizontal

sections with a thickness of 2 µm were cut with a microtome and mounted on slides

(3-1 sections per slide).

For cryosections, the fresh liver tissue was immediately frozen on a plastic cassette

that was cooled on liquid nitrogen with the help of tissue tek. The frozen tissue was

cut with a cryotome (leica) into 4 µm thick sections (1-2 sections per slide) and stored

at –20 °C.

2.7.2 Immunofluorescence staining of paraffin embedded sections

Before staining paraffin sections were incubated for at least 20 minutes then after

incubation deparaffinized with 3x xylene, and rehydrated with ethanol (2x 100 %,

1x90 %, 1x70 %, water), for at least 5 min per bath. Then the slides were boiled for

antigen retrieval for 15-20 min in a pressure cooker in preheated citric acid buffer (10

mM, pH 6.0, with 0.05 % Tween 20).

After cooling for at least 30 min at RT the slides were incubated for 30 min with 0.5 %

Triton X-100 in PBS for full permeabilization. Then the slides were washed three

times for at least 5 min with PBS. For each slide, liver sections were surrounded with

a PAP- pen to create two independent staining compartments per slide.

To prevent unspecific antibody binding, sections were incubated for 1 h at RT with

blocking solution containing 5 % BSA in PBS in a dark humidified chamber. After

removal of the blocking solution the sections were incubated with the primary

antibodies in blocking solution, usually overnight at 4 °C. After three washes with

1xPBS the slides were incubated with the fluorescently labeled secondary antibodies

(dilution 1:500, labeled with Alexa Fluor 488 (green) or 568/594 (red)) in blocking

solution for 1 h at RT, with DAPI (250 ng/ml) for nuclear counterstaining. After two

additional washes with PBS (in dark), the slide were shortly washed with water and

mounted with a coverglass with mowiol as aqueous mounting medium. TUNEL

staining was performed with an in situ TUNEL cell death detection kit (Roche)

following the manufacturer's instructions. Immunofluorescence staining for Insulin on

pancreas sections was done with the same method as described above.

Alexa Fluor-coupled secondary antibodies for immunofluorescence (goat anti-rabbit

Material and Methods

56

A488/A568, donkey anti-rabbit A594, goat anti-mouse A488/A568, donkey anti-

mouse A594, donkey anti-goat A488, goat anti-rat A488) were obtained from Life

Technologies (Molecular Probes, Paisley, UK) and used in a dilution of 1:500.

2.7.3 Immunofluorescence image aquisition and processing

To avoid bleaching of the fluorescent dyes, the slides were stored in the darkness

and analysed within a few days. Images were taken with the Zeiss Axiovert 200M,

with filters for DAPI, FITC/Alexa Fluor 488, DsRed and Texas Red/Alexa Fluor

568/594. All directly compared images were taken at the same session with the Zeiss

Axiovision-software (version 4.8) with the same settings that were separately

adjusted for each channel. After export to jpg files the final adjustment of total

brightness (equally for all directly compared images) and the cutting of relevant

image parts was performed with Adobe Photoshop.

2.7.4 Quantification of TUNEL staining, Cd45 and Insulin staining

For the quantification of Tunel positive cells and Cd45 positive cells, all the images

were taken at the same settings. Images were obtained using Leica CTR5500

microscope. Cell count was performed manually using ImageJ64 software.

The quantification of insulin staining for pancreatic sections was done with Image J64

software. All the images were taken in the same settings. The settings were made in

the software to calculate the total area (including endocrine as well exocrine), size of

islets and number of the islets the results were plotted by calculating the percentage

of endocrine area.

2.7.5 Immunohistochemical staining of paraffin embedded sections

Before staininng paraffin sections were incubated for atleast 20 minutes then after

incubation deparaffinized with 3x xylene, and rehydrated with ethanol (2x 100 %,

1x90 %, 1x80%, 1x70 %, water), for at least 5 min per bath. Then the slides were

boiled for antigen retrieval for 15-20 min in a microwave in preheated citric acid buffer

(10 mM, pH 6.0, with 0.05 % Tween 20). After cooling for at least 30 min at room

temperature the slides were incubated with primary antibody for 1 hour at RT. The

Material and Methods

57

primary antibody was made in blocking solution (0.1% BSA in PBS). The slides were

then washed 3x in PBS for at least 5 minutes. After washing the slides were

incubated with secondary antibody (Dako/Jackson Immunoresearch) for 1hour. The

slides were washed 3x in PBS and after washing the slides were incubated and

finally developed with two drops of AEC (Dako) on each liver section for 20 minutes.

After 20 minutes incubation the slides were again washed in PBS two times and then

immediately transferred in hematoxylin for 10 sec. The slides were then washed for

10 miutes in water bath with continous supply of water. After washing the slides were

mounted with mowiol and left for air-drying at room temperature.

For k8/k18 staining the sections were blocked with 10% goat serum with 1 %BSA

prior to incubation with primary antibody. After incubation with secondary antibody

slides were developed with permanent red dye systems (Dako). The other procedure

is the same as described above. For Immunohistochemistry secondary antibodies

were purchased from Dako/Jackson Immunoresearch and they were applied 50ml on

everysection of slide.

2.7.6 PAS staining for Glycogen

For PAS (Periodic acid Schiffs) staining for glycogen content the sections were

deparaffinized with 3x xylene, and rehydrated with ethanol (2x 100 %, 1x90 %,

1x80%, 1x70 %, water), for at least 5 min per bath. The slides were incubated in

0.5% periodic acid for 5 minutes. The slides were then washed in distilled water two

times for 3 minutes. The slides were then incubated with Schiff´s reagent and

provided high power in the microwave for 45-60 seconds until the colour was

changed to deep magenta. The slides were then washed in the running tap water for

5 minutes. The slides were counterstained in hematoxylin for 3 minutes. Washed in

running tap water and rehydrated with graded ethanol. The slides were mounted with

entellan and left for air-drying. All the pictures for Immunohistochemical staining and

Hematoxyline staining were taken with (Leica CTR5500) microscope.

2.8 Statistical analyses

Data are shown as means ±SD. Statistical significance was determined using a two-

tailed student t-test P<0.05 was considered significant.

Material and Methods

58

2.9 Reagents and Materials

2.9.1 General chemicals

General chemicals (inorganic chemicals, solvents, standard organic salts, acids)

were purchased from Applichem (Darmstadt), Roth (Karlsruhe), Merck (Darmstadt)

and Sigma (Taufkirchen).

Item Company

Acetic acid (glacial) Merck, Germany

Acetic acid Fluka, Switzerland

Acrylamide solution 40% AppliChem, Germany

Agarose Ultrapure, Electrophoresis Grade Gibco BRL , USA

APS Sigma-Aldrich, Germany

b- Mercaptoethanol AppliChem, Germany

Bromphenolblue Carl Bittmann, Switzerland

BSA (Albumin Fraction V) AppliChem, Germany

Calcium chloride Sigma-Aldrich, Germany

Di- sodium-hydrogen phosphate Sigma-Aldrich, Germany

DTT AppliChem, Germany

EDTA– dihydrate AppliChem, Germany

Ethanol (absolute) Sigma-Aldrich, Germany

Glycerol AppliChem, Germany

Glycine AppliChem, Germany

HEPES Gibco BRL , USA

Hydrochloric acid 37% Sigma-Aldrich, Germany

Hydrogen peroxide AppliChem, Germany

Isopropanol Merck, Germany

Methanol Merck, Germany

Magnesium chloride Sigma-Aldrich, Germany

Non-fat dried milk AppliChem, Germany

Potassium chloride Carl Roth GmbH , Germany

Material and Methods

59

Potassium dihydrogen phosphate Merck, Germany

SDS AppliChem, Germany

Sodium chloride AppliChem, Germany

Sodium dihydrogen phosphate Sigma-Aldrich, Germany

Sodium hydroxide, pellets AppliChem, Germany

Sodium orthovanadate Sigma-Aldrich, Germany

TEMED AppliChem, Germany

Tris (ultrapure) AppliChem, Germany

Tween 20 AppliChem, Germany

Urea AppliChem, Germany

2.9.2 Buffers and solutions

TNES-buffer50 mM Tris-HCl (stock 1M pH 7.5)

0.1M EDTA (stock 0.5 M, pH 8.0)

0.1M NaCl

1 % SDS

Proteinase K (Applichem, Darmstadt) 0.45 µg/ µl)

PBS (10x) pH 7.3 87.65 g/l NaCl

2 g/l KCl

11.7 g/l Na2HPO4

2.4 g/l NaH2PO4

TBS(10x) pH 7.624.2 g/l Tris

80g/l NaCl

TBE (10x)121.1 g/l Tris

61.8 g/l hydroboric acid

7.4 g/l EDTA

Material and Methods

60

Dignam C buffer20 mM Hepes (pH 7.9)

25 % glycerol

0.42 M NaCl

1.5 mM MgCl20.2 mM EDTA

1 mM PMSF

1 mM DTT, 1 tablet/10 ml complete mini protease inhibitor (Roche,

Mannheim)

RIPA buffer50 mM Tris-HCl (stock 1M pH 7.4)

150 mM NaCl

1 % Triton X-100

0.5 % sodium desoxycholate

0.1 % SDS

1 mM PMSF, 1 tablet/10 ml complete mini protease inhibitor (Roche,

Mannheim)

Luciferin buffer (for luciferase assay)20 mM Tricin

1.07 mM magnesiumcarbonatehydroxyde

2.67 mM magnesiumsulfate

0.1 mM EDTA

33.3 mM DTT

0.27 mM Coenzyme A

0.47 mM luciferin

0.53 mM ATP

4x Laemmli loading buffer125 mM Tris-HCl (pH 6.8)

20 % SDS

25 % glycerol

bromphenol blue for coloring

Material and Methods

61

(+ 5 % β-mercaptoethanol)

2.9.3 Protein biochemistry materials

5x Bradford reagent (Biorad, München)

PageRuler prestained protein ladder (Fermentas, St. Leon-Rot)

MagicMarkXP Western Protein Standard (Invitrogen, Life Technologies,

Paisley, UK)

Protease inhibitor , Complete-Mini (Roche Diagnostics, Germany)

PVDF membrane Milipore, USA

Whatman paper Invitrogen, USA

2.9.4 Histology and microscopy materials

Cresyl violet (Merck, Darmstadt)

DAPI (Merck, Darmstadt)

Entellan (Merck, Darmstadt)

Mowiol (Merck, Darmstadt)

Paraformaldehyde/PFA (Sigma, Taufkirchen)

PAP-Pen (Sigma, Taufkirchen)

Peel-A-Way disposable embedding molds (Polysciences, Warrington, PA,

USA) Microscopy slides “Superfrost Ultra Plus” (Menzel,

Braunschweig)

Coverglasses 24x50 mm (VWR, Ulm)

2.9.5 Molecular biology materials

1kb plus DNA ladder (Invitrogen, Life Technologies, Paisley, UK)

Agarose Ultrapure, Electrophoresis Grade (Invitrogen, Life Technologies, Paisley,

UK)

Ethidium bromide (Applichem, Taufkirchen)

Taq Poymerase and 5x Green GoTaq Reaction buffer (Promega, Mannheim)

dNTPs (Genaxxon, Ulm)

PCR tubes 0.2 ml (Brand, Wertheim)

Material and Methods

62

Lightcycler 480 Multiwell Plate 96 (Roche, Mannheim)

2.9.6 General laboratory materials

Reaction tubes 1.5/2 ml (Eppendorf, Wesseling-Berzdorf)

15/50 ml High-Clarity Polypropylen Conical Tubes (BD Falcon, San Diego, CA, USA)

5 ml Polystyrene Round Bottom tubes GLKL (Greiner Bio-One, Frickenhausen)

Pipette tips 1-1000 ml (Hightech lab, Warsaw, Poland and Axygen, Union City, CA,

USA)

1/2/5/10/25 ml glass pipettes (Brand, Wertheim)

1ml Sub-Q syringes (BD, Franklin Lakes, NJ, USA)

3 Laboratoryequipment

3.1 General laboratory equipment

Pipettes 0.1-2 µl

2-20 µl

20-200 µl

200-1000 µl (Abimed, Gilson, Brand)

Pipette controller Pipetus (Hirschmann, Eberstadt)

Surgical forcipes and scissors (FST, Heidelberg)

Biofuge Pico 17 (Thermo Scientific, Waltham, MA, USA)

Megafuge 1.0R (Thermo Scientific, Waltham, MA, USA)

Digital Heat Block (VWR, Ulm)

Centrifuge (max.13.000 rpm) / Biofuge A (Heraeus, Germany)

Dryer T5050E (Heraeus, Germany)

Freezer (Liebherr, Germany)

Deep freezer -80°C, Class N / HFU 586 (Heraeus, Germany)

Block thermostat / TCR 100 (Roth AG, Germany)

pH-meter Calimatic 761 (Knick, Berlin)

ice-machine automatic / AF10 (Scotsman, Italy)

Light microscope (Leica, Germany)

Lightcycler 480 (Roche, Germany)

Material and Methods

63

Nanodrop (Peqlab, Germany)

Magnetic stirrer / RCT-BE (Kika Labortechnik, Germany)

Scale Scaltec (Scaltec, Heiligenstadt)

Scale BP-210-S (Sartorius, Göttingen)

Spectrophotometer Genesys 10S UV/VIS (Thermo Scientific, Waltham, MA, USA)

Steam sterilizer H+P (Labortechnick, Germany)

Thermocycler Primus 96 plus (MWG, Ebersberg)

Gel documentation Genosmart (VWR, Ulm)

Vortex Genie-2 / G-560E (Scientific Industries, USA)

Cell culture incubator Hera-Safe (Thermo Scientific, Waltham, MA, USA)

Laminar flow sterile bank (Thermo Scientific, Waltham, MA, USA)

Shaker Polymax 1040 (Heidolph, Schwabach)

Waterbath (B.Braun, Germany)

Power supplies for electrophoresis Desatronic 500/400 (Desaga, Heidelberg)

Agarose gel equipment was constructed by the scientific workshop facilities of Ulm

University

3.2 Histology and microscopy equipment

Microtome Microm HM355S (Thermo Scientific, Waltham, MA, USA)

Cryotome CM1900 (Leica, Wetzlar)

Vibratome VT1200S (Leica, Wetzlar)

Leica CTR 5500 microscope (5x,10x,20,40x)

Microscope Axiovert 200M (Zeiss, Oberkochen):

b/w camera AxioCam MRm

objectives Plan-Apochromat 2.5x, 5x, 10x, 20x, 40x, 63x

UV-lamp X-Cite 120 EXFO (Lumen dynamics, Mississauga, Canada)

Excitation/emission filters for DAPI, FITC/Alexa Fluor 488, DsRed/PE and

Texasred/Alexa Fluor 568/594 (AHF Analysentechnik)

Stereomicroscope SteREO Discovery.V20 (Zeiss, Oberkochen):

RGB camera AxioCam MRc

Objective Achromat S 0.63x

Material and Methods

64

3.3 Software

Microsoft Office X

Adobe Photoshop CS2 V9.0

Adobe Illustrator CS2 V12.0.0

ImageJ64 1.41

Zeiss Axiovision 4.8

Results

65

3 Results

3.1 Generation of transgenic mice with inducible liver-specific expression ofconstitutively active FOXO3

The role of FoxO1 in regulation of hepatic glucose production has been showed

previously in several mouse models (Matsumoto, Han et al. 2006; Zhang, Patil et al.

2006; Matsumoto, Pocai et al. 2007; Lin and Accili 2012). However the interplay

between different FoxO family members sharing the conserved DNA binding domain

is far from being understood. Importantly in addition to FoxO1, FoxO3 is also

significantly expressed in the liver its contribution to metabolic regulation has

however not been thoroughly analysed. Interestingly previous studies have shown

the role of FoxO3 in insulin sensitivity phenotypes and longevity in humans

suggesting that FoxO3 is critical for metabolic control (Willcox, Donlon et al. 2008;

Flachsbart, Caliebe et al. 2009; Pawlikowska, Hu et al. 2009). Therefore the present

study was designed to investigate consequences of FOXO3 function in vivo. For this

purpose, a transgenic mouse model was generated that allows expression of a

mutant (constitutively active) FOXO3 allele specifically in the liver with an inducible

transgene expression system to conditionally modulate FOXO3 activity in

hepatocytes.

3.1.1 Tetracycline regulated expression of a constitutively active FOXO3 alleledriven by the LAP promotor

To activate FoxO3 signaling in the liver a constitutively active allele of FoxO3

(FOXO3-CA) was used in which the three AKT phosphorylation sites (T32, S253,

S315) are mutated to alanine residues keeping the FOXO3 in an activated

confirmation (Schmidt-Strassburger, Schips et al. 2011; Schips, Wietelmann et al.

2011) (Figure 14). We crossed transgenic mice expessing tetracycline-regulated

transactivator (tTA) under the control of LAP promotor which is highly specific for the

liver (Sunami, Leithauser et al. 2012) with mice carrying the FoxO3CA allelle and a

luciferase reporter gene controlled by a bidirectional promotor (luciferase-(tetO)7-

FOXO3-CA) (Figure 15). Tetracyclin transactivator (tTA) binds to tet-operator

elements (tetO)7 and drives the transcription of both the luciferase reporter gene and

the FOXO3-CA transgene. The tTA binding can be blocked by doxycycline (Dox),

Results

66

thereby shutting off transgene expression (Lavon, Goldberg et al. 2000; Sunami,

Leithauser et al. 2012)

Figure 14. Mutated FOXO3 structure in which three AKT phosporylation sitesT32, S253, S315 are mutated to alanine residues.

Figure 15: Tetracycline regulated (“tet-off”) expression system for the liverspecific expression of FOXO3-CA and a luciferase reporter gene.

Animal obtained from breedings (LAP.tTA x (tetO) 7.FOXO3-CA) which contain both

the transgenes are called double transgenic (FoxO3CAHep mice) should express

FOXO3CA in a doxycycline-regulated manner, whereas single transgenic or wild type

littermates should not express FOXO3CA and could be used as controls (Control).

3.2 Perinatal induction of FOXO3CA results in lethal phenotype

3.2.1 liver-specific expression of FOXO3CA

In order to avoid consequences of FoxO3CA expression during embryogenesis,

pregnant mothers were kept under doxycycline in the drinking water to repress

FoxO3 expression. With this setting, FoxO3CAHep were born at the expected

Mendelian ratio. In a first set of experiments doxycycline was removed immediately

after birth and the mice were anlaysed at the age of 4-weeks (Figure16A).

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67

Macroscopically the FoxO3CAHep mice at this age appeared very sick, they were

much smaller then their wildtype littermates, and some mice had already died before

the age of 4-weeks (52.94%alive and 47.04 dead) (Figure16B). In vivo luciferase

imaging was performed to determine the specificity of transgene expression by

injection of luciferin (150µg/g body weight) as an indirect measurement of transgene

expression. In vivo imaging confirmed the strongest activity clearly in the liver of

double transgenic animals (Figure 16C).

Transgene expression was further analysed in different organs from FoxO3CAHep

mice by ex vivo luciferase measurement. High luciferase activity was detected only in

the livers of 4-week-old FOXO3CA mice and other peripheral tissues had

nondetectable luciferase activities (Figure 16D). Hepatic expression of FoxO3CA

transgene was further confirmed by immunoblot analysis using antibodies against

FOXO3 and β-Tubulin. The results showed strong expression of FOXO3 band only in

FoxO3CAHep animals and was undetected in liver from control animals (Figure 16E)

Furthermore FoxO3CAHep mice showed a pronounced decrease in liver size and liver

weight even more than the body weight (Figure 16F) and the reduced liver weight to

body weight ratio (LW/BW) was due to reduction in liver size (Figure 16G).

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68

Figure 16: FoxO3CAHep mice exhibit a robust, liver-specific transgeneexpressionA. Schedule of Doxycycline treatment. Doxycyline was administered untill birth. After

birth DOX administration is ceased and the animals were analysed at 4-weeks of

age.

B. Macroscopic appearence of FoxO3CAHep mice as compared to their littermate

controls.

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69

C. In vivo assessment of transgene expression. Control and double transgenic

(FoxO3CAHep) mice were analysed for luciferase expression using an IVIS system.

The FoxO3CAHep mice were kept with doxycycline (DOX) until birth then DOX

treatment was ceased. Luciferase activity was imaged at the age of 4- weeks.

D.Transgene expression was analysed in different organs from FoxO3CAHep mice by

ex vivo luciferase measurement. High luciferase activity was detected in livers of 4-

week-old mice. Extrahepatic tissues displayed only negligible luciferase activities

(RLU: relative light unit).

E. Western blot analysis of whole liver extracts from 4-week-old control and

FoxO3CAHep mice using antibodies against FOXO3 and β-Tubulin. The latter was

used as a loading control.

F. Liver from FoxO3CAHep mice and control animals. The livers from transgenic

animals were much smaller then their littermate controls.

G. Liver weight, bodyweight and liver weight/body weight ratio from 4-week-old mice

are shown (n=7, data are represented as mean +/-SD).

3.2.2 FOXO3CA activation affects size and structure of hepatocytes andinduces liverdysfunction and metabolic abnormalities

In order to obtain a more detailed insight into the liver structure and morphology,

histological sections stained with hematoxylin and eosin were analysed in detail.

FoxO3CAHep mice showed much smaller hepatocytes as compared to control

animals. Immunohistochemical staining performed with FOXO3 antibody showed the

strong nuclear expression of FOXO3CA in these smaller hepatocytes (Figure 17

A,B).

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70

Figure 17: Expression of liver-specific FoxO3CA leads to morphologicalalterations.

A: Paraffin sections stained with hematoxylin and eosin; scale bar: 100 µm.

B: Paraffin sections stained with an antibody specific for FOXO3CA (Brown). Scale

bar: 100µm.

We then analysed the FoxO3CAHep mice with respect to markers of liver damage

serum levels of the liver enzymes alanine aminotranferase (ALT) and aspartate

amino transferase (AST) were elevated in FoxO3CAHep mice (Figure 18A, B). At the

same time, bilirubin levels were increased in FoxO3CAHep mice as compared to

control 4-week-old animals (Figure 18C). These changes in ALT, AST, and bilirubin

reflect a significant extent of liver damage. Furthermore FoxO3CAHep mice have a

moderate reduction in triglyceride (TG) and cholesterol levels (Figure 18D-E) as

reported before due to defective insulin action in the liver (Michael, Kulkarni et al.

2000; Zhang, Patil et al. 2006). Interestingly, FoxO3CAHep mice showed reduction of

blood glucose levels as compared to control animals and were severely

Results

71

hypoglycemic (63.75 ± 4.9 mg/dl vs. 139 ± 11.6 mg/dl, FoxO3CAHep vs. Control,

respectively) (Figure 18F). This could be due to dual role of FoxO transcription

factors in controlling hepatic insulin sensitivity (Matsumoto, Han et al. 2006) or might

be due to some other reasons discussed later.

Figure 18: Expressio of FoxO3CA induces hepatocyte damage and alteredmetabolic parametersA. Alanine aminotransferase (ALT) and B. aspartate aminotransferase (AST) C.bilirubin, D. Serum triglycerides E. Serum Cholesterol F. Blood glucose levels in the

4-week-old control and FoxO3CAHep mice (n=7, data are represented as mean +/-

SD).

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72

3.2.3 Expression of FOXO3CA in younger animals induces autophagy

As in a previous study it has already been shown (Schips, Wietelmann et al. 2011)

that the consequences of constitutive activation of FOXO3 in cardiomyocytes induces

reversible cardiac atrophy and autophagy, we reasoned whether in this mouse model

constitutive activation of FoxO3CA in the liver might induce the upregulation of genes

involved in autophagy because the animals at 4-weeks of age were extremely

atrophic. We therefore performed RTqPCR for autophagy-associated genes (Atg1,

Atg12, Atg5). The results showed a moderate upregulation for cell autophagy

associated genes investigated namely Atg1, Atg5, Atg12 (Figure 19).

In summary FoxO3 activation just after birth results in smaller animals with

hypoglycemic phenotype, additionally hepatocyte damage and altered metabolic

parameters was observed. Furthermore FoxO3CAHep mice at the age of 4-weeks

showed moderate upregulation of autophagy associated genes and this may explain

smaller size of hepatocytes and smaller size of liver. Autophagy is the catabolic

process of lysosomal degradation and self-destruction. In FoxO3CAHep mice at the

age of 4-weeks catabolic pathways such as autophagy was activated that might

result in hypoglycemic phenotype or due to some other unknown reasons and also

several other parameters were not listed due to severity of phenotype. The results

from 4-week-old animals prompted us to analyse FoxO3CA activation in adult

animals.

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73

Figure 19: FoxO3CAHep shows elevation of various autophagy-associatedgenes.Expression of several autophagy-associated genes determined by RTqPCR. Bars

represent the ratio of gene expression relative to Hprt (n=7).

3.3 FOXO3CA activation in adult animals

3.3.1 Expression pattern of FOXO3CA transgene

In order to analyze FoxO3 function in mature livers, transgene expression was

suppressed until 5-weeks of age by administration of doxycycline (DOX) in the

drinking water. After removal of doxycyline/ induction of transgene expression mice

were analysed at two different time points at the age of 7-weeks (after two weeks of

FOXO3CA activation) and at the age of 9-weeks (after four weeks of FOXO3CA

activation) (Figure 20A). In order to check for the specificity of transgene expression

in vivo imaging was performed both for Control and FoxO3CAHep mice at the age of

7-weeks and at the age of 9-weeks. In vivo imaging again showed strong expression

of the transgene only in the liver specifically in double transgenic FoxO3CAHep mice

(Figure 20B). Importantly, these mice appeared normal. In vitro luciferase assays

were also performed in both 7-week-old and 9-week-old animals. The results

revealed that expression of the transgene reporter luciferase was restricted to the

liver of FoxO3CAHep mice. Extrahepatic tissues displayed only negligible luciferase

activities (Figure 20C).

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74

Figure 20: FoxO3CAHep mice reveal a robust, liver-specific transgeneexpression at the age of 7-weeks and 9-weeks.A. Schedule of doxycycline treatment. DOX administration was started from birth

untill 5-weeks of age then DOX administration is ceased and the animals were

analysed at 7-weeks and at 9-weeks after 2-weeks and 4-weeks of FOXO3CA

activation.

B. In vivo assessment of transgene expression. Control and double transgenic

(FoxO3CAHep) mice were analysed for luciferase expression using an IVIS system.

Luciferase activity was imaged at the age of 7-weeks and at the age of 9-weeks.

C. Transgene expression was analysed in different organs from FoxO3CAHep mice by

ex vivo luciferase measurement. High luciferase activity was detected in livers of both

7-week-old and 9-week-old mice. Extrahepatic tissues displayed only negligible

luciferase activities (RLU: relative light unit).

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75

In addition, FoxO3 transgene expression was confirmed at the protein level by

performing western blot of whole liver extracts from 7-week-old and 9-week-old mice

with antibodies specifically recognizing FoxO3 protein and β-Tubulin as a loading

control. The results from western blotting showed strong expression of FoxO3 protein

only in FoxO3CAHep mice both at 7-week and 9-week but not in control animals

(Figure 21A). We also checked the hepatic expression of FOXO3CA gene at the

transcriptional level via real time RT-PCR. The results showed FOXO3CA gene was

upregulated in FoxO3CAHep mice both at the age of 7-weeks and 9-weeks. Results

are normalized to expression of hypoxanthine-guanine phosphoribosyl transferase

gene (Hprt). (Figure 21B).

Figure 21: Detection of FoxO3CA transgene at the protein and transcriptionallevel in 7-week and 9-week-old mice.A. Western blot analysis of whole liver extracts from 7-week-old and 9-week control

and FoxO3CAHep mice using antibodies against FOXO3 and β-Tubulin. The latter

was used as a loading control.

B. Hepatic expression of FOXO3CA was determined via real time RT-PCR. Results

are normalized to expression of hypoxanthine-guanine phosphoribosyl transferase

gene (Hprt).

3.3.2 Expression of FOXO3CA in adult animals is not associated with growthdefect

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76

As already mentioned, mice with hepatic activation of FOXO3CA at birth resulted in

growth defect. Accordingly we considered enlisting weight parameters in control and

FoxO3CAHep animals at the age of 7-weeks and 9-weeks. We observed that

activation of FoxO3 for 2-weeks and 4-weeks did not result in any obvious growth

defect as the body weight, liver weight and liver weight/ body weight ratios were

normal and the animal appeared active and normal (Figure 22 A,B).

Figure 22: Normal body weight and liver weight characteristics of FoxO3CAHep

mice at the age of 7-week and 9-weeks.A. Body weight, liver weight and liver weight/body weight ratio from 7-week-old mice

are shown (n=7, data are represented as mean +/-SD).

B. Body weight, liver weight and liver weight/body weight ratio from 9-week-old mice

are shown (n=7, data are represented as mean +/-SD).

3.3.3 FOXO3CA activation results in altered hepatic morphology

Active FOXO3 should accumulate in the nucleus and activate FOXO3-dependent

gene expression. We determined FOXO3 expression and localization by

immunohistochemical analysis both in 7-week-old and 9-week-old animals and we

found that FOXO3CA indeed localized in the nucleus. Interestingly, FOXO3CA

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77

expression affected cell morphology, as FoxO3CAHep hepatocytes were much smaller

than wildtype controls already seen at 4-weeks (Figure 17). To confirm that all these

smaller cells are hepatocytes, Keratin 8/18 staining was performed as hepatocyte

marker. The staining displayed all the smaller cells as hepatocytes (Figure 23 A, B).

Figure 23: Expression of FoxO3CA induces hepatocyte atrophy in FoxO3CAHep

mice at the age of 7-weeks and 9-weeks.A. Representative H&E-staining from control and FoxO3CAHep mouse livers (A and

B, bar: 100 µm).

B. Expression of FOXO3 was determined by immunohistochemical staining with

FOXO3 antibody. Strong nuclear staining of FOXO3 is seen in livers from

FoxO3CAHep mice, Keratin 8/18 staining was performed for hepatocyte staining.

3.3.4 FOXO3CA activation induces moderate hepatocyte damage

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78

To examine liver functionality after two weeks of FOXO3CA activation the markers for

liver damage and liver dysfunction were assessed from the serum of 7-week-old

control and FoxO3CAHep mice after 6 hour of fasting. The transgenic animals showed

mildly elevated serum alanine aminotransferase (ALT) and aspartate

aminotransferase (AST) levels indicating moderate hepatocyte damage (Figure 24A).

Elevated serum bilirubin levels could indicate hepatocyte dysfunction (Figure 24B).

However, serum albumin and pseudocholinesterase levels, widely accepted

hepatocyte function markers, were not changed (Figure 24C). Alkaline phosphatase

levels were elevated in FoxO3CAHep mice suggesting that hepatocyte function is still

intact, but biliary tract function is impaired (Figure 24D).

Figure 24: FoxO3CAHep show elevated markers of hepatocyte damage andhepatocyte dysfunction.A. Alanine aminotransferase (ALT) and aspartate aminotransferase (AST) B. Bilirubin

C. albumin, pseudocholinesterase, and alkaline phosphatase (ALP) D. levels in the 7-

week-old control and FoxO3CAHep mice (n=7, data are represented as mean +/-SD).

Increased liver enzyme levels would be a consequence of hepatocyte death. Indeed

FOXO3CA expression in murine forebrain had resulted in massive apoptosis of

neuronal progenitors (Schmidt-Strassburger et al., 2012). In order to check for

apoptosis in FoxO3CAHep mice TUNEL assays were performed the staining and

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79

TUNEL quantification revealed not significant increased levels of apoptosis in

FoxO3CAHep mice (Figure 25A). We used TAK1-LPCKO liver as positive control as it

was previously reported that TAK1 deficiency mediates hepatocyte cell death

(Bettermann, Vucur et al. 2010). We also performed CD45 staining for inflamation the

results from staining and quantification of CD45 positive cells showed no signs of

inflammation in FoxO3CAHep mice (Figure 25B). We used IKK2CA liver as positive

control for inflammation because it has been shown that over-expression of IKK2

cause liver fibrosis through macrophage-mediated chronic inflamation (Sunami,

Leithauser et al. 2012). Taken together, hepatic FOXO3 expression led to mild

hepatocyte damage independent of inflammation or apoptosis, but hepatocyte

function is largely intact.

Figure 25: Expression of constitutively active FoxO3 does not induce stronginflammation and apoptosis.A. Immunofluorescence TUNEL staining for 7-week-old control and FOXO3CAHep

mice. Liver-specific deletion of TAK1 (Map3k7) mouse liver (Bettermann, Vucur et al.

2010) served as a positive control (bar: 100 µm).

B. Immunohistochemical stainings against CD45 for 7-week-old control and

FOXO3CAHep mice were shown. Liver from over-expression of IKK2 mutant

(Sunami, Leithauser et al. 2012) served as a positive control (bar: 100 µm).

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80

3.3.5 Hepatocellular FOXO3 activation induces metabolic abnormalities

After two weeks of transgene activation, FoxO3CAHep mice displayed markedly

elevated fasting blood glucose levels compared to control animals (282.4 ± 22.8

mg/dl vs. 128 ± 4.8 mg/dl, FOXO3CAHep vs. Control, respectively) (Figure 26A).

Elevated blood glucose levels could be a consequence of increased

gluconeogenesis. Consistently, increased hepatic expression of several genes

involved in gluconeogenesis, namely glucose 6 phosphatase (G6pc),

phosphoenolpyruvate carboxykinase (Pepck), and pyruvate dehydrogenase kinase

isoenzyme 4 (Pdk4), was observed (Figure 26B). Furthermore in order to examine

whether hyperglycemic FoxO3CAHep animals were able to tolerate a glucose load

through glucosetolerance test. Glucose tolerance test (GTT) was performed as

mentioned in materials and methods. The results from intraperitoneal glucose

tolerance test performed on FoxO3CAHep mice demonstrated impaired glucose

tolerance (Figure 26C). In order to analyze whether glucose intolerance might be a

consequence of insufficient insulin production, we measured serum insulin levels.

Interestingly, FOXO3CAHep mice showed significantly higher insulin levels (10.01 ±

1.56 ng/ml vs. 1.50 ± 0.82 ng/ml, FoxO3CAHep vs. Control, respectively) (Figure 26D).

In order to further confirm that FoxO3CAHep mice are able to lower glucose in

response to injected insulin insulin tolerance test (ITT) was performed as mentioned

in materials and methods. The results of insulin tolerance test demonstrated that

exogenously administered insulin failed to lower blood glucose level in FOXO3CAHep

mice (Figure 26E) and further showed that FOXO3CAHep mice was extremely

resistant to injected insulin. These data suggest that hepatic FOXO3 affects glucose

homeostasis by regulating gluconeogenesis-associated enzymes and it impairs

hepatic insulin signalling.

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81

Figure 26: Overexpression of FoxO3CA induces hyperglycemia,hyperinsulinemia and impaired glucose tolerance as well as insulin sensitivity.A. Serum glucose levels from 7-week-old control and FoxO3CAHep mice after 6 hours

fasting (A- E: n=7, data are represented as mean +/-SD).

B. Up-regulation of gluconeogenesis-associated genes in FoxO3CAHep livers. Results

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from quantitative real-time PCR experiments are shown. Bars represent the ratio of

the expression of the highlighted genes relative to the hypoxanthine-guanine

phosphoribosyltransferase gene (Hprt).

C. Glucose tolerance test. Blood glucose levels from control and FoxO3CAHep were

measured at the indicated time points after glucose injection. Mice were fasted for 6

hours before performing experiments (*** P<0.001).

D. Serum insulin level from control and FoxO3CAHep mice after 6 hours fasting.

E. Insulin tolerance test. Blood glucose levels control and FoxO3CAHep were

measured after insulin injection (*** P<0.001). Mice were fed ad libitum before

performing the experiments.

3.3.6 Activation of catabolic pathways by expression of constitutively activeFOXO3

FOXO3 transcription factors are involved in regulation of metabolic homeostasis

therefore the observed hyperglycemic metabolic phenotype could be explained by

up-regulation of FOXO3 metabolic target genes. To unveil FOXO3-induced

transcriptional network, we performed microarray analyses using livers from 7-week-

old control (n=4) and FoxO3CAHep (n=4) 6 hours, fasted mice. This analysis revealed

560 up-regulated genes and 421 down-regulated genes in FoxO3CAHep mice

compared to control animals (Appendix Table 1). The data confirmed an increase in

the mRNA levels for several gluconeogenesis-associated enzymes such as pyruvate

dehyrogenase kinase (Pdk4, Pdk3) were upregulated. Pdk4 inhibits pyruvate

dehydrogenase by phosphorylation providing pyruvate as gluconeogenic substrates

(Wei, Tao et al. 2011). A known regulator of glucose and lipid metabolism

peroxisome proliferator activated receptor-γ coactivator-1α (Pparγc1α) was

upregulated. Subsets of genes involved in regulation of glucose homeostasis for

providing energy during the process of starvation were upregulated (Table 7).

Consistently the glycolytic genes such as glucokinase and pyruvate kinase (Gck,

Pklr), were downregulated hepatic glucokinase is an important enzyme linking

glucose and lipid metabolism by catalysing the conversion of glucose to glucose-6-

phosphate, which is an important precursor in support of lipogenesis. In addition, we

observed significant alterations in expression levels of genes involved in lipid

metabolism and other metabolic pathways (Table 8). Consistently due to enhanced

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activation of lipid catabolic pathways in FoxO3CAHep mice we have observed up-

regulation of genes involved in lipid transport and trafficking several fatty acid binding

proteins (fabp5, fabp7), apolipoprotein M (Apom), phospholipid transporting ATPase

(Atp11) was upregulated. Genes involved in fatty acid synthesis were down-regulated

ATP citrate lyase (Acly), ATP citrate lyase provide a sole fuel for cytoplasmic acetyl-

CoA, fatty acid synthase Fasn, acetylCoA carboxylase (Acc) acetyl-CoA carboxylase-

α which convert acetyl-CoA to malonylCoA which serve as a substrate for

lipogenesis, acetyl-CoA synthase (Acsm1). In line with this genes involved in fatty

acid oxidation were up-regulated carnitine palmitoyltransferase (cpt1b), enoyl-CoA

hydratase/3-hydroxy acyl Coenzyme A dehydrogenase (ehhadh), acetyl-CoA

acetyltransferase (Acot2), acety-CoA dehydrogenase (Acad12). This suggests that

FOXO3 activates catabolic pathways to provide substrates and energy for

gluconeogenesis.

Table 7: Genes involved in glucose metabolismClassification of the main genes that were differentially expressed betweencontrol mice and FoxO3CAHep mice. Relevant up-regulated genes were

categorized into several ontologies. Data are expressed as the mean-fold difference

in gene expression in FoxO3CAHep mouse livers relative to control mouse liver

samples.

Function Gene Symbol Gene name

Fold-changeTransgenic(n=4) vsControl(n=4)

Lepr leptin receptor 29.41Pdk4 pyruvate dehydrogenase kinase, isoenzyme 4 15.38Igfbp1 insulin-l ke growth factor binding protein 1 10.99Akr1b7 aldo-keto reductase family 1, member B7 7.14Igfbp2 insulin-l ke growth factor binding protein 2 4.35

Glucose Irs2 insulin receptor substrate 2 3.23Metabolism Me2 malic enzyme 2, NAD(+)-dependent, mitochondrial 2.38

Hmox1 heme oxygenase (decycling) 1 2.38Leprot leptin receptor overlapping transcript 2.38Aqp7 aquaporin 7 2.08Pgm3 phosphoglucomutase3 2.22Akr1b8 aldo-keto reductase family 1, member B10 gucose metabolism 1.96Pdp1 pyruvate dehydrogenase phosphatase catalytic subunit GM 1.92Pparγc1α peroxisome proliferative activated receptor, gamma, coactivator 1 alpha 1.92Igf1r insulin-l ke growth factor-1 receptor 1.92Gys2 glycogen synthase 2 1.85Pdk3 pyruvate dehydrogenase kinase isoenzyme 3 GM 1.63Pgd phosphogluconate dehydrogenase 1.61Aldh3b1 aldehyde dehydrogenase 3 family, member B1 1.59Pklr Glycolysis (Pyruvate kinase liver) 0.51Igf1 insulin-l ke growth factor 1 0.49Gckr Glucokinase regulatory protein 0.45Gck glucokinase 0.23

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Table 8: Genes involved in lipid metabolism

Function Gene Symbol Gene name

Fold-changeTransgenic (n=4) vsControl(n=4)

Lipid Metabolism Acmsd amino carboxymuconate semialdehyde decarboxylase 4.17Acot2 acyl-CoA thioesterase 2 4.17Acad12 acyl-Coenzyme A dehydrogenase family, member 12 2.7Cpt1b Carnitine palmitoyltransferase 1b,muscle 2.56Smpd3 Sphingomyelinphosphodieasterase 3 2.43Ehhadh enoyl-Coenzyme A, hydratase/3-hydroxyacyl Coenzyme A dehydrogenase 2.33Ugcg UDP-glucose ceramide glucosyltransferase 2.04Apom apolipoprotein M 2Lipo1 lipase, member O1 2Cerk ceramide kinase 2Pld4 phospholipase D family, member 4 1.89B3galnt1 UDP-GalNAc:betaGlcNAc beta 1,3-galactosaminyltransferase, polypeptide 1 1.82

Galnt7UDP-N-acetyl-alpha-D-galactosamine: polypeptide N-acetylgalactosaminyltransferase 7 1.82

Acsl4 acyl-CoA synthetase long-chain family member 4 1.82Atp11a Phospholipid transporting ATPase 1.78Fabp7 fatty acid binding protein 7 1.78Gltp Glycolipid transfer protein 1.72Pla2g12a phospholipase A2, group XIIA 1.54Fabp5 fatty acid binding protein 5, epidermal 1.53Acsm1 acyl-CoA synthetase medium-chain family member 1 0.66Ldlr low density lipoprotein receptor 0.66Acot11 Acyle-CoA thioesterase11 0.58Acss3 AcetyleCoA synthetase, short chain family member 3 0.36Fasn Fatty Acid synthase 0.42Acacα AcetyleCoA carboxylase alpha 0.55Acly ATP citrate lyase 0.58

The normal action of insulin in the liver is to inhibit glycogenolysis and

gluconeogenesis (Jitrapakdee 2012). It is reported peviously in type 2 diabetic

conditions that 90% of impaired hepatic glucose production occurs by

gluconeogenesis and the rest is supported by glycogenolysis (DeFronzo, Bonadonna

et al. 1992). Therefore in order to further confirm the activation of catabolic pathways

including glycogenolysis liver glycogen content was examined histochemically by

PAS (Periodic Acid Schiffs) staining for liver glycogen. Indeed, FoxO3CAHep mice

have significantly reduced glycogen as compared to control animals. Furthermore the

results from biochemical analysis revealed reduced glycogen in FoxO3CAHep mice as

compared to control animals. Accordingly, glycogen phosphorylase (an enzyme

involved in conversion of glycogen to glucose during glycogenolysis) mRNA

expression levels are up-regulated in FoxO3CAHep mice as compared to control

animals (Figure 27).

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Figure 27: Increased glycogenolysis in FoxO3CAHep mice.

A.Representative PAS (Periodic Acid Schiffs) stainings from control and FoxO3CAHep

mice (bar: 100 µm).

B. Quantification of hepatic glycogen content.

C . Up-regulation of a glycogen phosphorylase gene (Pygl) in the livers from

FoxO3CAHep mice. Results from RTqPCR experiments are shown. Bars represent

the ratio of the expression relative to Hprt.

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In addition, serum triglyceride and cholesterol levels were measured from serum of 6

hour fasted FoxO3CAHep and control mice. The results showed fewer triglycerides

and cholesterol in FoxO3CAHep mice compared to control animals (Figure 28A), and

consistently again mRNA expression of lipid anabolic enzymes namely acetyl-CoA

carboxylase (Acc), sterol regulatory element-binding protein 1c (Srebp1), and fatty

acid synthase (Fasn) were reduced (Figure 28B). This might be due to reduced effect

of insulin in the liver to stimulate lipogenesis together with enhanced insulin activity in

extrahepatic tissues to inhibit lipolysis as reported before in liver-specific insulin

receptor knockout mice (Michael, Kulkarni et al. 2000).

Figure 28: FoxO3CAHep mice display decreased lipogenesis.A. Serum triglyceride and cholesterol levels from control and FoxO3CAHep mice.

B. Expression of lipid synthesis-associated genes determined by RTqPCR. Bars

represent the ratio of gene expression relative to Hprt.

In contrast, expression of mRNA levels for lipid catabolic enzymes like carnitine

palmitoyltransferase 1a (Cpt1a) and enoyl-CoA hydratase (Echs1), were upregulated

(Figure 29A). Consistently, serum ketone bodies (β-Hydroxybutyrate), markers for

excessive lipid β-oxidation, were elevated in FoxO3CAHep mice (Figure 29B).

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Figure 29: Enhanced lipid catabolic pathways in FoxO3CAHep.A. Hepatic mRNA levels for genes involved in lipid catabolic pathway (β-oxidation)

were measured in control and FoxO3CAHep mice. Bars represent the ratio relative to

Hprt.

B. Serum ketone bodies from control and FoxO3CAHep mice.

We also measured serum urea as end product of protein catabolism but observed no

significant difference compared to controls. In addition, serum creatinine levels as

marker of kidney function were not elevated, indicating that the process of protein

catabolism was not significantly activated in FoxO3CAHep mice (Figure 30A).

Figure 30: FoxO3CAHep shows no symptoms of protein catabolism.A. Levels of serum urea as end product during protein catabolism and creatinine as

marker of kidney function from 7-week-old mice are shown (n=7, data are

represented as mean +/-SD).

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Taken together, activation of hepatic FOXO3 induces catabolic pathways including

glycogenolysis, and β-oxidation of fatty acids, to presumably provide metabolites and

energy required for excessive glucose production.

3.3.7 Continuous expression of constitutively active FOXO3 in the liver inducesloss of gluconeogenic potential

For assessing the disease progression, FOXO3CAHep mice were kept for another 2

weeks. By 9 weeks of age, to our surprise, FOXO3CAHep mice showed fasting

hypoglycemia (70.42 ± 8.3 mg/dl vs. 127.8 ± 4.8 mg/dl, FoxO3CAHep vs. Control,

respectively) rather than hyperglycemia (Figure 31A). This could be due to high

insulin production by pancreatic langerhans β-cells. Indeed, serum insulin level in 9-

week-old FoxO3CAHep mice showed significantly higher insulin levels (8.37 ± 1.63

mg/dl vs. 0.71 ± 0.64 mg/dl, FoxO3CAHep vs. Control, respectively) (Figure 31B).

Figure 31: Expression of FoxO3CA at 9-week results in hypoglycemia andhyperinsulinemia.A. Serum glucose levels from 9-week-old control and FoxO3CAHep mice after 6 hours

fasting (A-B: n=7, data are represented as mean +/-SD).

B. Serum insulin level from control and FoxO3CAHep mice after 6 hours fasting.

However, this is in contrast with our previous finding that high insulin levels in 7-

week-old FoxO3CAHep mice showed fasting hyperglycemia and whereas at 9-weeks

of age the transgenic mice have fasting hypoglycemia. One reason could be that in

FoxO3CAHep mice gluconeogenesis in the liver for glucose production is less active.

To test our hypothesis, as depicted above expression levels of several genes

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involved in promoting gluconeogenesis were analysed. This revealed that the mRNA

expression of gluconeogenesis-associated genes was reduced/ normalized in 9-

week-old FoxO3CAHep mice compared to 7-week-old mice Figure 26b (Figure 32).

Hepatocytes are major place for insulin clearance and another possibility for fasting

hypoglycemia is that, hepatocytes in liver failure probably are getting not able to

clean up insulin properly as reported previously in liver-specific insulin receptor

knockout mice (Michael, Kulkarni et al. 2000).

Figure 32: FoxO3CAH e p mice at the age of 9-weeks shows normalgluconeogenesis.A. Up-regulation of gluconeogenesis-associated genes in FoxO3CAHep livers in 7-

week-old mice. Results from quantitative real-time PCR experiments are shown. Bars

represent the ratio of the expression of the highlighted genes relative to the

hypoxanthine-guanine phosphoribosyltransferase gene (Hprt).

B. Gluconeogenesis-associated genes in FoxO3CAHep livers in 9-week-old mice.

Results from quantitative real-time PCR experiments are shown. Bars represent the

ratio of the expression of the highlighted genes relative to the hypoxanthine-guanine

phosphoribosyltransferase gene (Hprt).

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3.3.8 FOXO3CA activation in the liver induces subordinate pancreatichyperplasia

We characterized further the hyperglycemic phenotype at the age of 7-week and

hypoglycemic phenotype at the age of 9-week concerning pancreatic morphology

since the pancreas is the major site of insulin secretion and several mouse models

points to pancreatic hyperplasia in insulin-resistant states (Michael, Kulkarni et al.

2000; El Ouaamari, Kawamori et al. 2013). Interestingly we detected enlarged

pancreatic langerhans islets in 9-week-old FoxO3CAHep mice as compared to control

animals however pancreatic islets were normal structured in 7-week-old animals

(Figure 33A). Insulin immunostaining demonstrated the prescence of enlarged β-cell-

rich islets, which stained strongly for insulin (Figure 33B). Furthermore we quantified

the endocrine area that was significantly more in 9-week-old animals then in 7-week

animals (Figure 33C). Taken together, continuous activation of FoxO3 signalling

leads to initial fasting hyperglycemia and subordinate fasting hypoglycemia, might be

due to less insulin clearance capacity in the liver and more insulin production

capacity in pancreas. However, several other unknown reasons might explain

pancreatic hyperplasia as reported recently the role of liver-derived systemic factors

and critical role of betatrophin hormone inducing pancreatic hyperplasia and

improving glucose tolerance (El Ouaamari, Kawamori et al. 2013; Yi, Park et al.

2013).

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Figure 33: Pancreatic hyperplasia and increased insulin content in FoxO3CAHep

mice at the age of 9-weeks.A. Representative H&E-staining from control and FoxO3CAHep mouse Pancreas, 9-

week-old mouse has enlarged pancreatic Islets (bar: 100 µm).

B. Immunoflourescence staining for Insulin 9-week-old mouse has larger area for

producing insulin (bar: 100 µm).

C. Quantification of endocrine area from both 9-week-old and 7-week-old mouse

(n=50, data are represented as mean +/-SD).

3.4 Metformin normalizes FOXO3-induced distorted glucose and insulinmetabolism

Metformin (1,1-dimethylbiguanide hydrochloride) is a hypoglycemic agent and one of

the most widely used therapeutics for type 2 diabetes (Stumvoll et al., 1995). The

principal function of metformin is in part to reduce hepatic glucose production and to

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improve peripheral insulin sensitivity (Stumvoll et al., 1995). Although multiple

hepatocyte pathways affected by metformin have been identified, the precise

mechanism of metformin action still remains elusive. We wanted to determine,

whether metformin administration attenuates FOXO3-induced distorted glucose

homeostasis. We therefore administered metformin for the last 3 days until the

animals become 7 weeks old (Figure 34A), or to see long-term effect of Metformin,

we administered Metformin for 3 weeks (from 6 weeks to 9 weeks old) (Figure 34 B).

Metformin was administered with a concentration of 1.65g/L in normal drinking water

bottles and the quantity of metformin water used was checked and refilled everyday.

Figure 34: Schematic representation for the administration of Metformin

A. Animals were treated with metformin for 3 days before 7-weeks and the animals

were analysed at the age of 7-weeks.

B. Animals were treated with metformin for 3 weeks before 9-weeks and the animals

were analysed at the age of 9-weeks.

We analysed whether 3-days and 3-weeks of metformin treatment affects FOXO3-

induced dysregulation of glucose homeostasis. We first analysed potential effects of

metformin treatment on transgene activity, In vitro Luciferase assays were performed

both after 3-days of metformin treatment and 3-weeks of metformin treatment. The

results showed that luciferase activity was unaffeted in the livers of FoxO3CAHep mice

and extrahepatic tissues displayed negligible luciferase activities (Figure 35A-B).

Furthermore at the molecular level FOXO3 protein expression was also intact in

livers from FoxO3CAHep mice. This showed that metformin treatment has no effect on

transgene activity or FoxO3 protein expression both after 3-days and 3-weeks of

metformin administration (Figure 35C-D).

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Figure 35: FoxO3CA transgene expression is intact after administration ofmetformin. Metformin treatment has no influence on transgene expression inFoxO3CAHep.A. Transgene expression was analysed in different organs from FoxO3CAHep mice by

ex vivo luciferase measurement after administration of metformin. Luciferase activity

was intact in livers of 7-week-old as well as in 9-week-old mice (RLU: relative light

unit).

B. Western blot analysis of whole liver extracts from control 3days metformin-treated

left and 3-weeks metformin-treated right and FoxO3CAHep mice using antibodies

against FOXO3 and β-Tubulin. The latter was used as a loading control.

Several studies have shown a critical role of metformin in attenuating

gluconeogenesis by lowering hepatic glucose production (Hundal, Krssak et al. 2000;

Natali and Ferrannini 2006). Interestingly, already after 3 days of metformin treatment

FoxO3CAHep mice showed normalization in fasting blood glucose level (Figure 36A).

We asked whether this was due to normalization in gluconeogenesis and indeed

found that several glucogeogenesis-associated genes which were up-regulated in 7-

week-old FoxO3CAHep mice were normalized after short-term Metformin treatment

(Figure 36B).

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Figure 36: Metformin administration rapidly normalizes FoxO3-induceddistorted glucose level and sustained gluconeogenesis.A. Serum glucose levels from control and FoxO3CAHep mice, either without metformin

treatment (-Met) or treated for 3 days (+Met3D) (A-B: n=7 data are represented as

mean +/- SD).

B. Hepatic mRNA levels for genes involved in gluconeogenesis were measured in

control and FoxO3CAHep mice by RTqPCR. Bars represent the ratio of gene to Hprt

expression.

Furthermore, at the age of 9 weeks, we observed no hypoglycemic phenotype in

FoxO3CAHep mice after 3-weeks of metformin treatment (Figure 37A). In addition,

elevated insulin levels in the both 7-week- and 9-week-old FoxO3CAHep mice, as well

as enlarged endocrine area at the age of 9 weeks, were also all normalized (Figure

37 B-C). Consistently Threonine-308 and Serine-493 positions of AKT were no more

phosphorylated after metformin treatment in FoxO3CAHep mice (Figure 38). Taken

together, Metformin administration normalizes FOXO3-induced defective glucose and

insulin metabolism.

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Figure 37: Metformin treatment normalizes glucose, insulin and pancreatichyperplasia.A. Normalization of blood glucose after 3-weeks metformin treatment (+)Met3W (n=7

data are represented as mean +/- SD) all the animals were fasted for 6.hours before

analysis.

B. Normalization of serum Insulin after 3 weeks metformin treatment (+)Met3W (n=7

data are represented as mean +/- SD) all the animals were fasted for 6.hours before

analysis.

C. Normal histology of pancreatic islets form FoxO3CAHep mice after 3-weeks

meformin treatment (+) Metformin3W lower panel as compared to pancreatic

hyperplasia without metformin treatment at 9-weeks (-) Metformin upper panel.

In order to find out mechanism for metformin action it has been shown previously in

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in vivo mouse model with adenosine mono-phosphate (AMP)-activated protein kinase

(AMPK)-defeciency shows no influence on metformin-dependent reduction in blood

glucose levels (Foretz, Hebrard et al. 2010), although Metformin has been suggested

to perform anti-diabetic effect via activation of adenosine mono-phosphate (AMP)-

activated protein kinase (AMPK) (Zhou, Myers et al. 2001). However, it has

previously shown that AMPK phosphorylation of FOXO proteins results in activation

and nuclear accumulation (Greer, Oskoui et al. 2007). In that respect, metformin

would rather worsen than improve the pathology. We nevertheless analyzed state of

AMPK activation as measured by Western blot analysis with antibody recognizing

AMPKα harboring phosphorylated Threonine-172. Activation of FOXO3 resulted in

significant reduction of AMPK phosphorylation (Figure 38). Metformin in our system

did not measurably affect AMPK phosphorylation, suggesting that persistant FOXO3

activation may somehow control AMPK activity and might erace potential metformin-

driven beneficial activation. Taken together, metformin administration normalizes

FOXO3-induced defective glucose and insulin metabolism potentially independent of

AMPK.

Figure 38: Metformin normalizes FoxO3CA driven distorted glucose, lipid,insulin metabolism independent of AMPK activation.Hepatic expression of AKT and phopsho-AKT (threonine-308, T308 and serine 473,

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S473), AMPKα as well as phospho-AMPKα (threonine-172, T172) was analyzed by

Western blotting. β-Tubulin was used as a loading control.

3.5. FOXO3-induced activation of global catabolism, hepatocyte atrophy, orhepatocyte damage were reversed after Metformin administration

As described before, expression of FoxO3CA led to hepatic damage as well as

hepatocyte atrophy. If glucose metabolism is normalized in FoxO3CAHep mice after

Metformin administration, hepatocytes do not have to undergo autophagy. This

suggested the hypothesis that metformin treatment in FoxO3CAHep mice could induce

histological normalization and normal ALT and AST levels. As expected, there was

no FOXO3-induced elevation of ALT and AST levels in serum after Metformin

administration (Figure 39 A-B).

Figure 39: Metformin treatment results in normalization of hepatocytic damage.A. ALT B. AST levels in mice with 3-days metformin treatment and 3-weeks

metformin treatment the values are compared with mice without any metformin

treatment (n=7 data are represented as mean +/- SD) all the animals were fasted for

6 hours before analysis.

Furthermore, we examined liver histology to ascertain that metformin treatment has

no influence on hepatocyte structure as well as on nuclear localization of FOXO3 and

as we assumed the results displayed that there was no FOXO3 activation-driven

hepatocyte atrophy as previously observed without any metformin treatment in both

7-week- and 9-week-old animals. After Metformin treatment there were no smaller

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cells, and livers have the homogenous structure and morphology with strong FoxO3

expression (Figure 40).

Figure 40: Metformin treatment has no influence on FoxO3CA nuclearexpression and normalizes hepatocyte atrophy.A. Representative H&E-staining from control and FoxO3CAHep mice livers (A, B the

upper panel, bar: 100 µm). Normalization of liver histology after 3-days and 3-weeks

of metformin treatment.

B. Expression of FOXO3 was determined by immunohistochemical staining (A, B the

lower panel, bar: 100 µm) with FOXO3 antibody. Strong nuclear staining of FOXO3 is

seen in livers from FoxO3CAHep mice, Normalization of liver histology after 3days and

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3-weeks of metformin treatment.

Normalization in glucose homeostasis after Metformin administration could normalize

general metabolism. To check whether Metformin administration also normalized

mRNA expression not only for gluconeogenesis-associated genes, but also for global

metabolic system, microarray analyses were performed using mRNA of livers from 6

hours fasted, 7-week-old mice without and with metformin treatment for 72 hours.

The results of microarray analysis from 7-week-old animals with 3-days metformin

treatment were compared with the 7-week-old microarray data without any metformin

treatment. We found that 560 genes up-regulated and 421 genes down-regulated in

FoxO3CAHep mice were normalized after metformin treatment (Appendix Table 2).

The data confirmed the normalization of expression levels for genes both in glucose

metabolism, as well as lipid metabolism by metformin as shown in heatmap (Figure

41A) all those genes involved in gluconeogenesis such as Pdk4 which were

upregulated without any metformin treatment were downregulated with metformin

treatment. In contrast the glycolytic genes Gck and pklr, which were downregulated

without any metformin treatment were normalized with metformin treatment. Similarly

genes involved in lipid transport (fabp7, fabp5, Apom) and lipid β-oxidation (Cpt1b,

Acot12), which were upregulated without any metformin treatment, were normalized

with metformin treatment and as expected the genes involved in lipid synthesis

pathways (Acot, Acss), which were downregulated without metformin treatment were

now normalized after metformin treatment (Figure 41A). All those genes were further

confirmed by RTqPCR by using specific primers and the results were shown in log2

bardiagram (Figure 41B). We therefore conclude that metformin immediately targets

FOXO3 activity. However the mechanism how metformin targets FoxO3 still needs

further investigation.

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Figure 41A: Metformin administration reverses global catabolism induced byFoxO3CA activation.A. Heat-map summary of relative changes in gene expression. The left lane indicates

fold change in FoxO3CAHep mouse liver compared with those of controls. The right

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lane indicates fold change after administration of metformin in FoxO3CAHep mice

compared with FoxO3CAHep mice without metformin.

Figure 41B: Relative up-regulated and down-regulated gene with and withoutmetformin adminstration.B. From the Affymetrix data, several genes involved in glucose and lipid metabolisms

were analysed by RTqPCR. Bars represent the ratio of gene to Hprt and data are

shown in log2 bar diagram.

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4 Discussion

Type 2 diabetes mellitus and insulin resistance occur as a consequence of

uncontrolled gluconeogenesis that is failed to be suppressed by insulin (Rizza 2010).

It is a major worldwide health care problem affecting the quality of life. The

physiological processes contributing to insulin resistance in type 2 diabetes remain

enigmatic (Pajvani, Shawber et al. 2011). Therefore, there is a continuous need to

identify molecular events responsible for type 2 diabetes and insulin resistance and

this could help to discover new targets for the improvement of antidiabetic drugs.

One of the main signalling pathways involved in the insulin-dependent regulation of

hepatic glucose production is Irs/PI3-K/Akt/FoxO pathway. It has been shown that the

subcellular localization of FoxO transcription factors is controlled by insulin through

Akt-dependent phosphorylation (Nakae, Kitamura et al. 2001; Dong, Copps et al.

2008). The molecular mechanisms that integrate impaired insulin effects to

unconstrained gluconeogenesis in type 2 diabetic subjects remains ill defined.

Although it had been suggested that FoxO1 is the major executer for regulation of

insulin signaling-mediated glucose homeostasis (Gross, van den Heuvel et al. 2008;

van der Vos and Coffer 2011) as FoxO1 has been repeatedly described in regulation

of hepatic glucose production in the liver (Matsumoto, Han et al. 2006; Zhang, Patil et

al. 2006; Matsumoto, Pocai et al. 2007; Zhang, Li et al. 2012). It has been reported in

insulin-resistant mice that reducing or antagonizing hepatic FoxO1 activity markedly

improves insulin sensitivity and glucose tolerance (Altomonte, Richter et al. 2003;

Puigserver, Rhee et al. 2003; Matsumoto, Han et al. 2006; Samuel, Choi et al. 2006;

Matsumoto, Pocai et al. 2007; Dong, Copps et al. 2008). In addition to FoxO1, FoxO3

is also significantly expressed in the liver, its contribution to metabolic regulation has

however not been thoroughly analysed.

In this study we established and analysed a novel gain-of-function model of hepatic

FOXO3 where the constitutively active FOXO3CA transgene is expressed under the

control of the LAP promoter system that is specifically active in hepatocytes (LAP-tTA

x luciferase-(tetO) 7-FOXO3CA). This mouse model offers a defined genetic system to

gain a better understanding for the role of hepatic FOXO3 in regulating glucose

homeostasis and lipid metabolism. Previously it was found that FOXO3 genotypes

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are associated with insulin sensitivity phenotypes and longevity in human, mice and

invertebrates demonstrating that FOXO3 is critical for metabolic control (Willcox,

Donlon et al. 2008; Flachsbart, Caliebe et al. 2009; Pawlikowska, Hu et al. 2009).

Moreover recently various loss-of-function approaches of FoxO1, FoxO3, FoxO4 in

liver have addressed the role of FoxO3 in lipid metabolism (Estall 2012) but the role

of liver-specific gain-of-function of FOXO3 in the context of modulating glucose and

lipid metabolism in a cell type and context dependent manner was not addressed

untill now.

In this study we could demonstrate that constitutively active FoxO3 in the liver

critically affects glucose homeostasis and lipid metabolism. Expression of FoxO3CA

after birth resulted in perinatal lethality of 47% of FoxO3CAHep mice just within 4-

weeks of FoxO3 activation, whereas the rest of 52% FoxO3CAHep mice survived but

showed a smaller and severe hypoglycemic phenotype associated with moderate

upregulation of autophagy associated genes. Interestingly expression of FoxO3CA in

adult animals was sufficient to induce hyperglycemia in FoxO3CAHep mice at the age

of 7-weeks through regulation of gluconeogenesis-associated genes and alteration of

gene expression in glucose and lipid metabolism. Furthermore, we observed

elevated insulin levels as well as impaired glucose tolerance followed by insulin

sensitivity and activation of catabolic pathways including glycogenolysis and lipid

catabolic pathways in the liver. However the disease progression at the age of 9-

weeks in FoxO3CAHep mice was associated with hypoglycemia, hyperinsulinemia and

pancreatic hyperplasia. Strikingly, the anti-diabetic drug metformin completely

normalized glucose, insulin as well as lipid metabolism in FoxO3CAHep mice.

An important role of insulin signalling in regulating glucose homeostasis and systemic

growth has been shown previously in various experimental paradigms (Accili, Drago

et al. 1996; Dong, Park et al. 2006). FoxO transcription factors are the potential

mediators of hepatic gucose production downstream of insulin signalling and

deregulated during insulin resistance conditions (Eijkelenboom and Burgering 2013).

In our mouse model FoxO3CA expression just after birth result in perinatal lethality of

FoxO3CAHep mice with in 4-weeks of FoxO3 activation. The rest of FoxO3CAHep

animal analysed were severely smaller, sick and showed hypoglycemic phenotype. It

was previously reported that liver-specific deletion of Irs1/Irs2 results in

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hyperglycemia, hyperinsulinemia and smaller mice. In this mouse model it was

further evidenced that hepatic deletion of FoxO1 in triple knockout mice (TKO)

reverses the phenotype. This study pointed to the role of FoxO1 in directly regulating

the genes involved in glucose metabolism and indirectly inhibiting growth hormone

regulated genes (Dong, Copps et al. 2008). Additionally the smaller size of liver was

reported in liver-specific insulin receptor knockout (LIRKO)(Michael, Kulkarni et al.

2000) mice and in liver-specific deletion of catalytic subunit of PI3K (p110α) L-

p110α KO mice (Sopasakis, Liu et al. 2010) and was associated with defects in

growth signalling pathways. It is still not known whether FoxO1 and FoxO3 share

similar target genes or upregulate specific genes. In our mouse model it might be

possible that growth-signalling pathways were suppressed due to overactivation of

FoxO3 but this needs further investigation.

However it has been recently reported that expression of FoxO3CA in

cardiomyocytes resulted in a small heart phenotype and this was associated with

cardiomyocyte atrophy and activation of autophagy (Schips et al., 2011). In line with

this finding we also observed moderate upregulation of autophagy-associated genes

(e.g Atg5, Atg12, Atg1) in FoxO3CAHep mice. Additionaly hepatocytes were much

smaller and appeared atrophic in FoxO3CAHep mice. As autophagy is a lysosomal

degradation and self-destruction process, we could assume that the hypoglycemic

phenotype in FoxO3CAHep mice at the age of 4-weeks might be due to activation of

catabolic pathways like autophagy. Due to the severity of the phenotype at the age of

4-weeks in FoxO3CAHep mice most of the parameters could not be investigated and

this prompted us to analyse the animals at adult age.

When FoxO3CAHep mice were analysed at the age of 7-weeks, we observed a

hyperglycemic phenotype due to enhanced gluconeogenesis. This was followed by

hyperinsulinemia, impaired glucose and insulin tolerance, consistent with studies

showing constitutive activation of FoxO1 in the liver (Nakae, Biggs et al. 2002; Qu,

Altomonte et al. 2006; Zhang, Patil et al. 2006). However, our data suggest that the

interplay between different FoxO family members could be critical for the fine-tuning

of glucose metabolism. Previous work demonstrated that expression of a gain-of-

function allele of FoxO1 (FoxO1ADA) in the mouse liver paradoxically induced

hypoglycemia and increased insulin sensitivity through its increased ability to

Discussion

105

phosphorylate Akt in Trb3 (tribbles homologue 3)-dependent or independent manner

(Matsumoto, Han et al. 2006). In addition, deletion of FoxO1 in hepatocytes did not

alter the expression of gluconeogenic enzymes during fasting or after feeding (Lu,

Wan et al. 2012). Finally, additional members of the FoxO family might be involved in

regulating liver glucose homeostasis as hepatic activation of FoxO6 also induces

hyperglycemia in mice (Kim, Perdomo et al. 2011; Kim, Zhang et al. 2013). The

discrepencies observed in these studies with respect to insulin sensitivity might be

due to variation in experimental animal models, level and duration of overexpression,

as well as time of evaluation with respect to feeding versus fasting. Alternatively,

these data might be difficult to understand because different mutated forms of FoxO

may behave differently in unexpected ways. In contrast to these studies synergistic

contributions of FOXO transcription factors was also evidenced (Haeusler, Kaestner

et al. 2010) (Estall 2012; Zhang, Li et al. 2012) (Xiong, Tao et al. 2013) although

peviously no glucose metabolic defects have been outlined in either FoxO3-/- or

FoxO4-/- mice (Hosaka, Biggs et al. 2004). It had been shown that liver-specific

deletion of FoxO1, FoxO3, FoxO4 causes more profound fasting hypoglycemia,

improved insulin sensitivity and enhanced glucose tolerance with reduced plasma

insulin levels and this study presented an important role of FoxO1 for regulating

glucose metabolism and FoxO3 regulating lipid metabolism. However, the authors

claim whether it is achieved in a synergistic or coordinated pattern is still far from

being understood and remains largely open and the relative contributions of

individual FoxO transcription factors was not described. Accordingly, the FoxO3CAHep

mouse model is advantageous and a unique model for studying the metabolic

disease pathogenesis with respect to tissue specific gain-of function of FOXO3 in the

liver.

Our mice show substantial hyperinsulinemia. The normal action of insulin in the liver

involves an inactivation of FoxO transcription factors. However, this pathway is

blunted in our mouse model. Therefore, the hyperglycemic phenotype predominates.

Our data suggest that FoxO3 in hepatocytes could be the central effector

downstream of the insulin receptor/PI3K/Akt axis. This conclusion is supported by the

fact that the FoxO3CAHep mice among the FoxO gain-of-function studies show the

phenotype closest related to the mouse model of hepatic insulin receptor deficiency.

Both the studies are consistent in terms of FoxO3CAHep and liver-specific insulin

Discussion

106

receptor knock out mice (LIRKO) producing hyperglycemia due to increased hepatic

glucose production and increased expression of gluconeogenic target genes G6pc,

Pepck followed by marked hyperinsulinemia, impaired glucose and insulin tolerance.

These effects in LIRKO mice could arise due to deficiency of hepatic insulin signalling

resulting in insulin resistance and diabetes. In our mouse model our phenotype of

FoxO3CAHep mice also mimics several insulin resistance phenotypes such as liver-

specific deletion of Irs1 and Irs2 (DKO-mice) (Dong, Copps et al. 2008), liver-specific

deletion of Akt1 and Akt2 (DLKO) mice (Lu, Wan et al. 2012), and liver-specific

deletion of catalytic subunit of PI3K (p110α) L-p110α KO mice (Sopasakis, Liu et al.

2010) develop hyperglycemia due to unbridled gluconeogenesis, hyperinsulinemia

followed by impaired glucose and impaired insulin tolerance. All these studies points

to defective insulin signalling culminating in insulin resistance and type 2 diabetes.

The metabolic system reacts to environmental conditions by storing or utilizing

nutrients. For example lack of metabolites in the glucose metabolic pathway will

stimulate catabolic pathways like gluconeogenesis, glycogenolysis or lipid β-oxidation

(Sun, Miller et al. 2012). Consistently, in our study we observed that continuous

glucose production by FoxO3CA expression in FoxO3CAHep mice led to inhibition of

lipid synthesis and to activation of glycogenolysis and lipid catabolic pathways. We

saw an inhibition of the fatty acid synthesis pathway and activation of lipid β-oxidation

most likely in order to provide energy and metabolites for gluconeogenesis.

A previous study with over-expression of FoxO1 (FoxO1ADA) in the liver observed

improved insulin sensitivity, lipid accumulation and steatosis in the liver, with reduced

fatty acid oxidation which is quite distinct from our model. The lipid catabolic pathway

was actually inhibited in mice with FoxO1 over-expression (Matsumoto, Han et al.

2006). In this study the increase in insulin sensitivity and lipid accumulation (Aoyama,

Peters et al. 1998) was associated with increase FoxO1 activity to suppress

pseudokinase tribble 3 (Trb3). Trb3 is a modulator of Akt activity and it has been

shown that Trb3 when it binds to Akt and prevents insulin-induced phosphorylation of

Akt (Du, Herzig et al. 2003). The suppression of Trb3 was not dependent on FoxO1

but FoxO1 may interact with the PPARγ coactivator 1α (Pgc1α) a well-known

modulator of Trb3. However, the importance of (Pgc1α) has been previously reported

in disorders of lipid metabolism in the liver in several mouse models (Leone,

Discussion

107

Weinheimer et al. 1999; Hashimoto, Cook et al. 2000). In our mouse model, we

obeserved an increase in lipid and glucose catabolic pathway a possible explanation

might be that critical regulators of glucose and lipid metabolism such as Pgc1α (Li,

Monks et al. 2007) are differently affected in FoxO1 and FoxO3 gain-of-function

models. In line with this using a similar gain-of function model Qu et al. (Qu,

Altomonte et al. 2006) have observed enhanced lipogenesis and liver steatosis due

to increased FoxO1 activity resulted in upregulation of Pgc-1α, fatty acid synthase

and acetyl CoA carboxylase expression. The inconsistency oberved with respect to

improved insulin sensitivity and increased lipogenesis can be due to variation in

experimental animal models and experimental settings. However there are only few

gene expression studies comparing target genes of different FoxO members

(Eijkelenboom and Burgering 2013), and further investigation of specific gene

regulation by individual FoxO members also in the context of lipid metabolism is

required.

We have seen a moderate reduction in triglycerides and cholesterol levels in

FoxO3CAHep mice. In line with this (Zhang, Patil et al. 2006), liver-specific FoxO1

activation has resulted in decreased triglycerides in transgenic mice which were due

to decreased expression of genes involved in glycolysis and lipid synthesis resulting

in reduced triglyceride concentrations in transgenic mice (Zhang, Patil et al. 2006). In

our mouse model in FoxO3CAHep mice we also have observed downregulation of

genes involved in glycolysis, such as glucokinase and pyruvate kinase are

downregulated as well as lipid synthesis genes ascertained by microarray analysis

and quantitative PCR studies. Consistently, the reduced triglycerides in liver-specific

Irs1/ Irs2 knockout mice are associated with decreased SREBP-1c expression (Dong,

Copps et al. 2008). Furthermore the decreased triglycerides in liver-specific deletion

of catalytic subunit of PI3K (p110α) L-p110α KO mice (Sopasakis, Liu et al. 2010)

are also linked to decreased lipogenic gene expression. Another possibility for

reduced triglycerides in FoxO3CAHep mice might be due to a decreased effect of

insulin in the liver to promote triglyceride synthesis coupled with suppression of

extrahepatic lipolysis due to high insulin levels in FoxO3CAHep mice as reported

previously in LIRKO mice (Michael, Kulkarni et al. 2000).

Discussion

108

Additionally, expression of FoxO3CA in the liver led to loss of glycogen storage in

FoxO3CAHep mice, a phenotype also observed in insulin resistant LIRKO mice

(Michael, Kulkarni et al. 2000), liver-specific Irs1/ Irs2 knockout mice (Dong, Copps et

al. 2008) and in liver-specific FoxO1 gain-of-function mice (Qu, Altomonte et al.

2006). The normal action of insulin in the liver is to suppress glycogenolysis and

gluconeogenesis. Loss of glycogen in these studies is associated with impaired

insulin signalling during insulin resistant states. However, it has also been reported in

subjects of type 2 diabetes that the increase in hepatic glucose production occurs by

enhanced gluconeogenesis and enhanced glycogenolysis (DeFronzo, Bonadonna et

al. 1992). Consistently, in our mouse model we have observed an increase in mRNA-

level of glycogen phosphorylase an important enzyme for glycogenolysis showing

that both gluconeogenesis and glycogenolysis are activated to produce more glucose

production in FoxO3CAHep mice as reported recently in diabetic db/db mouse liver

(Zhang, Xu et al. 2013).

Our gene expression profile ascertained by microarray analysis in FoxO3CAHep mice

showed a global metabolic profile with the regulation of several genes involved in

glucose and lipid metabolism. The most upregulated gene was leptin receptor (Lepr).

It has been shown in the liver that proper insulin signalling plays a critical role in

expression and clearence of leptin receptor as well as fine-tuning of leptin action and

leptin homeostasis. The upregulation of Lepr during insulin resistance states was

reported by (Cohen, Kokkotou et al. 2007) in liver-specific insulin receptor knockout

mice LIRKO mice (Michael, Kulkarni et al. 2000). Additionally the increase in leptin

receptor expression was also reported in liver-specific deletion of the catalytic subunit

of PI3K (p110α) L-p110α KO mice (Sopasakis, Liu et al. 2010) and was due to insulin

resistance phenotype. Consistently, in our mouse model we can postulate that

increased expression of Lepr is correlated with insulin resistance in FoxO3CAHep

mice.

In diabetes, the increased rate of hepatic gluconeogenesis has been shown

previously (DeFronzo, Bonadonna et al. 1992; Pilkis and Granner 1992; Samuel and

Shulman 2012). Consistent with the previous reports, genes involved in promoting

hepatic gluconeogenesis such as pyruvate dehydrogenase kinase-4 (Pdk4) were

upregulated and glycolytic genes such as Glucokinase (Gck), and pyruvate kinase

Discussion

109

liver (Pklr) were downregulated as reported before in liver-specific gain-of-function of

FoxO1 and in type 2 diabetic stated in human liver (Pilkis and Granner 1992; Zhang,

Patil et al. 2006). Interestingly genes providing substrates for gluconeogenesis are

increased such as aquaporin7 as shown previously (Zhang, Patil et al. 2006).

Consistently due to enhanced activation of lipid catabolic pathways in FoxO3CAHep

mice we have observed upregulation of genes involved in lipid transport and

trafficking (fabp5, fabp7, Apom, Atp11) and genes involved in fatty acid oxidation

(cpt1b, ehhadh, Acot2, Acad12). Conversly genes involved in fatty acid synthesis

were downregulated (Acly, Fasn, Acc, Acsm1). Moreover our microarray analyses

reveal that the livers from FoxO3CAHep mice are accelerated towards uncontrolled

gluconeogenesis by inhibiting the lipid synthesis pathway and activation of lipid β-

oxidation. Interestingly, our gene expression profiles are very similar to microarray

analysis of recently reported 9-week-old type 2 diabetic db/db mouse liver (Zhang, Xu

et al. 2013).

Interestingly, when we evaluated the disease progression by analysing the

FoxO3CAHep mice at the age of 9-weeks, surprisingly FoxO3CAHep mice showed

fasting hypoglycemia and higher insulin levels. These findings were in contrast to our

previous findings where FoxO3CAHep mice showed fasting hyperglycemia at the age

of 7-weeks. What could be the reason for this unanticipated hypoglycemic response?

It could be due to high insulin secretion from pancreatic β-cells as the insulin levels

were elevated in FoxO3CAHep mice at the age of 9-weeks. Similarly, it was previously

reported in liver-specific LIRKO mouse model that LIRKO mice showed progressive

decline in blood glucose at 6 months of age, LIRKO mice showed fasting

hypoglycemia that resembles the hypoglycemic phenotype of FoxO3CAHep mice at

the age of 9 weeks. The hypoglycemic effect could be due to the development of

acquired liver failure or plausibly imitating the reduced sufficiency of livers for

gluconeogenesis. When FoxO3CAHep mice were analysed for gluconeogenesis they

showed reduced effect of gluconeogenesis. Additionally, another possibility for

fasting hypoglycemia is that it might arise due to less insulin clearence capacity in the

liver as observed in LIRKO mice. Hepatocytes are the major place for insulin

clearence and hepatocytes in liver failure probably are not able to clean up insulin

properly. Furthermore it was reported in human patients that any excess of

endogenous or exogenous insulin could cause hypoglycemia in diabetes (Cryer,

Discussion

110

Davis et al. 2003; De Leon and Stanley 2013).

Strikingly in our mouse model we have demonstrated pancreatic hyperplasia at the

age of 9-weeks in FoxO3CAHep mice and this finding is similar to pancreatic

hyperplasia of insulin-resistant LIRKO mouse model (Michael, Kulkarni et al. 2000). It

could arise as a compensatory mechanism in response to increased insulin levels

and impaired insulin clearence. However, the mechanisms controlling proliferation,

expansion of β-cells and its adaptation to insulin resistance are incompletely defined

although it was evidenced that massive bulk of new β-cells in both rodent and

humans develop by simple self-duplication of preexisting β-cells (Dor, Brown et al.

2004; Teta, Rankin et al. 2007; Meier, Butler et al. 2008). It is known that pancreatic

β-cells preserve the potential to raise their replication rate in reply to physiological

challenges, including hyperglycemia (Alonso, Yokoe et al. 2007), pancreatic injury

(Nir, Melton et al. 2007; Cano, Rulifson et al. 2008) insulin resistance (Bruning,

Winnay et al. 1997; Pick, Clark et al. 1998; Michael, Kulkarni et al. 2000; Kulkarni,

Jhala et al. 2004) and gestation (Parsons, Brelje et al. 1992; Rieck, White et al.

2009). It has been reported that circulating and systemic factors can influence β-cell

mass and replication. Importantly glucose infusion in mice induces β-cell replication

showing glucose itself is a β-cell mitogen (Bonner-Weir, Deery et al. 1989; Bernard,

Thibault et al. 1998; Alonso, Yokoe et al. 2007). In addition to the factors described

above several hormones including prolactin, placental lactogen, insulin, glucagons-

like peptide 1, and glucose-dependent insulinotropic polypeptide also play a critical

role in regulation of β-cell mass (Parsons, Brelje et al. 1992; Bernard, Thibault et al.

1998; Paris, Bernard-Kargar et al. 2003; Drucker 2006; Sachdeva and Stoffers 2009).

The role of circulating islet cell growth factor during insulin resistance condition

independent of obesity and glucose has also been shown in transplanted mice (Flier,

Kulkarni et al. 2001).

Specifically how the liver signals pancreatic β-cells to proliferate is unknown, but

recently using LIRKO mouse model it was demonstrated that non-cell-autonomous,

nonneural, humoral factors causes pancreatic hyperplasia (El Ouaamari, Kawamori

et al. 2013). This study showed that the liver-derived systemic factors trigger human

and mouse β-cell proliferation and further showed that the liver serves as a source for

Discussion

111

β-cell growth factors in response to insulin resistance. In line with this study recently

betatrophin a hormone that controls pancreatic β-cell proliferation and β-cell mass

expansion in insulin resistant mouse model was identified (Yi, Park et al. 2013). This

study critically showed the role of betatrophin produced in mouse liver inducing β-cell

proliferation, β-cell mass expansion and improving glucose tolerance and further

pointing to the therapeutic importance of betatrophin during insulin resistance

conditions. Similarly constitutive activation of mitogen- activated protein kinase / ERK

kinase (MEK-1) in the mouse liver induces pancreatic β-cell replication and enhances

glucose tolerance showing that the increase in hyperinsulinemia and compensatory

pancreatic β-cell mass is multifactorial and requires the central nervous system

(CNS) presenting an inter-organ communication system controlling pancreatic β-cell

proliferation (Imai, Katagiri et al. 2008). Recently the role of hepatocyte growth factor

(HGF) in determining increase in islet cell mass along with hyperinsulinemia in

mouse models of insulin-resistance was reported (Araujo, Oliveira et al. 2012).

However in our mouse model it might be that glucose and insulin itself are potential

candidates for the observed pancreatic hyperplasia as reported before (Bonner-Weir,

Deery et al. 1989; Assmann, Hinault et al. 2009; Assmann, Ueki et al. 2009).

However, we cannot exclude the possibility of liver-derived unknown factors inducing

β-cell hyperplasia or betatrophin like hormone contribution augmenting β-cell

hyperplasia in FoxO3CAHep mice at the age of 9 weeks. Importantly the expression of

betatrophin was not affected in our gene expression analyses. Therefore further

investigation is needed to identify specific β-cell growth factor. Indeed our mouse

model may serve as a tool for identifying yet unknown liver-derived factors/ hormones

augmenting β-cell hyperplasia in insulin resistance states.

Since decades, several types of anti-diabetic drugs have been generated. Among

those, biguanides including phenformin and metformin function by inhibition of

glucose production (Stumvoll, 1995). Especially metformin is currently the most

prescribed drug for type 2 diabetes. In our mouse model metformin administration

completely normalizes glucose level with marked decrease in expression of

gluconeogenic target genes in FoxO3CAHep mice. It has been reported that metformin

primarily functions to decrease hepatic glucose production by attenuating hepatic

gluconeogenesis both in diabetic mouse models (Mithieux, Guignot et al. 2002;

Discussion

112

Shaw, Lamia et al. 2005; Kim, Park et al. 2008; He, Sabet et al. 2009; Hou, Venier et

al. 2010; Tahara, Matsuyama-Yokono et al. 2011) and in humans with type 2

diabetes (Davidson and Peters 1997; Hundal, Krssak et al. 2000; Natali and

Ferrannini 2006). Additionally metformin administration in our mouse model

normalizes insulin levels in FoxO3CAHep mice both at the age of 7-week as well as at

9-weeks. Metformin is the best insulin sensitizer during insulin resistance conditions

and it improves insulin sensitivity due to its positive effects on insulin receptor

tyrosine kinase activity in streptozotosin-induced diabetic rats (Rossetti, DeFronzo et

al. 1990) and it increases the activation of insulin receptor specifically insulin receptor

substrate 2 (Irs2) activation in human liver (Gunton, Delhanty et al. 2003). In our

mouse model we have seen downregulation of Irs2 in gene expression analysis after

metformin treatment and actually the normalization of insulin levels in our mouse

model is associated with normalization of glucose levels after metformin treatment as

evidenced in several studies (Hou, Venier et al. 2010; Martin-Montalvo, Mercken et

al. 2013). We have also seen the normalization of pancreatic islet morphology in

FoxO3CAHep mice at the age of 9-weeks, as it has been already known that

metformin has no immediate effect on the function of pancreatic beta cells. Fasting

and feeding insulin levels are frequently reduced after metformin treatment in patients

and in mice with diabetes showing the normal compensatory response of the

pancreas to enhanced insulin sensitivity (Klip and Leiter 1990; Rossetti, DeFronzo et

al. 1990; DeFronzo, Barzilai et al. 1991; Johnson, Webster et al. 1993; Stumvoll,

Nurjhan et al. 1995; Cusi, Consoli et al. 1996). From these studies it can be inferred

that in our mouse model the normalization of pancreatic islets after metfromin

treatment in FoxO3CAHep mice at the age of 9-weeks is associated with normal

insulin levels and improved insulin sensitivity.

Despite the wide acceptance of metformin as first-line therapy, the molecular

mechanisms of action remain incompletely understood. It was suggested that

metformin reduces glucose levels via activating adenosine mono-phosphate (AMP)-

activated protein kinase (AMPK) and its upstream kinase serine/threonine kinase 11

(STK11) also known as liver kinase B1 (LKB1) both in vivo and in vitro (Zhou, Myers

et al. 2001; Shaw, Lamia et al. 2005; Kim, Park et al. 2008; Lee, Seo et al. 2010).

Interestingly, in vivo mouse models with liver-specific AMPK-deficient mice

(AMPKα1α2-/-) and liver-specific LKB1-deficient mice (Lkb1-KO) show no

Discussion

113

influence on metformin-dependent reduction in blood glucose levels (Foretz, Hebrard

et al. 2010). We also assume that metformin effects in our model were AMPK-

independent. We did not see significant changes of amount and phosphorylation of

AMPK in FoxO3CAHep mice. Furthermore, as AMPK is known to activate FoxO family

members metformin-induced activation of AMPK should actually result in

phosphorylation and activation of FoxO3 (Greer, Oskoui et al. 2007). Therefore it

could be reasonable that AMPK activity is suppressed by active FoxO3. This could

explain why independent of metformin treatment FoxO3CAHep mice displayed lower

AMPK activity. A recent study suggested that metformin suppresses hepatic

glucagon signaling by decreasing production of cyclic AMP and PKA activity in an

AMPK-dependent manner (Miller, Chu et al. 2013). PKA signaling activates the

transcription factor CREB that regulates target gene expression for glucose and lipid

metabolism together with CREB-binding protein (CBP). In addition, metformin was

shown to inactivate CBP by phosphorylation (He, Sabet et al. 2009). Given that CBP

is a general transcription co-regulator, this axis of metformin action might affect

FoxO3-dependent transcription. However, direct effects of metformin on FoxO3

activity are more likely, as modulation of CBP should result in a much more

generalized alteration of gene expression.

Additionally, it has also been reported that metformin-induced activation of AMPK

lowers hepatic gluconeogenesis in livers from B6-Lepob/ob mice through modulation of

orphan nuclear receptor small heterodimer partner (SHP) (Kim, Park et al. 2008). The

role of SHP in repressing the transcriptional activities of hepatic nuclear factor 4-

α (HNF4α), FoxO1 and a variety of nuclear receptors that regulate the gluconeogenic

programme has been reported (Lee and Moore 2002; Kim, Kim et al. 2004;

Yamagata, Daitoku et al. 2004). SHP also interacts with the CREB-CBP complex and

CRTC2 to attenuate gluconeogenic gene expresssion (Lee, Seo et al. 2010). In our

mouse model it is possible that SHP might interact with FoxO3 or other

transcriptional regulators to lower gluconeogenesis. Nevertheless we performed

various experiments to assess the level of SHP activation but we have not found any

striking results one plausibility could be an unknown exciting mechanism to attenuate

distorted glucose and lipid metabolism in FoxO3CAHep mice after metformin treatment

and this mechanism is on the way of further exploration.

Discussion

114

We observed complete normalization in lipid metabolism, as well as hepatocyte

morphology after metformin administration in FoxO3CAHep mice. Metformin-mediated

re-normalization of lipid metabolism is probably a consequence of normalization in

glucose metabolism. Previously it was shown that metformin reverses fatty liver

disease in leptin-deficient ob/ob mice (Lin et al., 2000) and in rat fatty liver induced by

high fat feeding (Gao, Lu et al. 2005; Zhang, Zhang et al. 2006), suggesting that

metformin is beneficial in improving lipid metabolism. In line with this it has also been

recently reported that metformin reduces the fat content of the liver in obese

overweight women (Sanchez-Munoz, Salas-Romero et al. 2013). The gene

expression analysis after metformin treatment in FoxO3CAHep mice showed complete

normalization of all the genes involved in lipid and glucose metabolism. The possible

explanations for normalization of genes after metformin treatment in FoxO3CAHep

mice are correlated with normalization of glucose metabolism. Given that our model

depends on the expression of a transcription factor that was rendered non-

responsive to insulin signalling suggests that this terminal step is crucially targeted by

metformin. In summary, our study provides new insights into the role of FoxO3 in

glucose and lipid metabolism. Furthermore, our data suggest that FoxO3 could be an

immediate target of metformin action.

Conclusions

In the present study we demonstrate that constitutive activation of FoxO3 results in

impaired glucose and lipid metabolism in transgenic mice. FoxO3 activation resulted

in impaired glucose tolerance due to upregulation of gluconeogenic target genes

followed by hyperinsulinemia and impaired insulin sensitivity. Moreover expression of

constitutively active FoxO3 results in activation of catabolic pathways including

glycogenolysis and lipid catabolic pathways in the liver. On the other hand FoxO3

inhibits lipid synthesis pathways. Consistently our gene expression analysis has

identified several genes important for regulation of glucose and lipid catabolic

pathways as reported in type 2 diabetes conditions. However the disease

progression in transgenic mice resulted in hypoglycemia might be as a consequence

of beginning of liver failure, hyperinsulinemia and pancreatic hyperplasia. Strikingly

the administration of metformin rapidly and completely normalizes glucose, insulin as

Discussion

115

well as lipid metabolism in mice expressing constitutively active FoxO3 (Figure 42).

Our findings identify FoxO3 as a critical metabolic regulator and a potential hepatic

target of metformin. Taken together the results obtained from constitutive activation

of FoxO3 in the liver imply that dysbalanced FoxO3 activity in the liver augments

insulin resistance and type 2 diabetes. Therefore tight regulation of FoxO3 activity

would be very crucial and agents controlling hepatic FoxO3 system may represent

therapeutic tools to prevent type 2 diabetes.

Figure 42: Effects of liver-specific FoxO3 activation in FoxO3CAHep mice.Expression of constitutively active FoxO3 leads to hyperglycemia due to up-regulation of

gluconeogenic target genes followed by impaired glucose and insulin tolerance and furthermore

resulted in activation of catabolic pathways including enhanced glycogenolysis and decresed lipid

synthesis. The disease progression in transgenic mice resulted in hypoglycemia, hyperinsulinemia and

pancreatic hyperplasia. The administration of metformin for 3 days and 3 weeks completely normalizes

the distorted glucose and lipid metabolism in FoxO3CAHep mice.

References

116

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Declaration

154

DeclarationI hereby confirm that I have made the work independently and without using any

sources or aids other than those stated. In each individual case, I have clearly

identified the source of the passages that are taken word for word or paraphrased

from other works.

Ulm,

Sarah Gul

Acknowledgement

155

AcknowledgementI would like to thank Prof. Dr. Thomas Wirth for giving me the opportunity to work on

this project under his supervision, for his keen interest, and fruitful discussions on this

project and his great support even in personal matters.

I would like to express my gratitude to Dr. Yoshiaki Sunami for his supervision, skilful

guidance, practical help, for his informative discussions and speacial thanks for

preparing the manuscript and arranging further cooperations on this project.

I am also thankful to Dr. Pavel Strnad for his informative discussions and suggestions

on this project.

I would like to express my gratitude to Prof. Dr. Bernhard Böhm for his interest, nice

suggestions and informative discussions on this project.

I am thankful to Dr. Karl Lenhard Rudolph for his keen interest and useful

discussions on this project.

It’s a pleasure to thank Dr. Frank Leithaüser and other staff members of Pathology

department for analysing and processing the histology from the animals related to

this project.

I am also thankful to Dr. Karl-Heinz Holzmann for the help with gene expression

microarray experiments.

I am also thankful to Melanie Gerstlauer and Nina Ushmorov for the excellent

technical assistance.

I do appreciate Dr. Katja Fiedler for her kind help in various issues in the lab. I am

also very thankful to the former and present members of the Institute of Physiological

Chemistry for their help and special thanks to Hansgeorg Glöckler for his help in

computer issues.

I am thankful to my friends Ayesha Maqbool, Heba Hamed Salem, Gandhari Maity for

being cooperative and helpful in various issues.

My heartfelt gratitude is reserved for my beloved parents and my in-laws for allowing

me to complete this educational carrier and for their continuous support, great care

and encouragement through out my studies. Lastly, but perhaps most importantly I

am thankful to my caring and loving husband Dr. Muazzam Ali Khan Khattak for his

great support, his patience and his encouragement during this time. A very special

thanks to my little son Mohammad Zaween a nice companion during the last year of

Acknowledgement

156

my P. hD studies. I do appreciate all those who remembered me in their prayers.

Curriculum Vitae

157

Curriculum Vitae

Personal Information

Name: Sarah Gul

Date of Birth: 28-08-1982

Place of Birth: Peshawar-Pakistan

Nationality: Pakistani

Gender: Female

Address: Institute of Physiological Chemistry

Albert-Einstein-Allee 11

D-89081

Ulm, Germany

Telephone: +49 (0) 731 (500) 33834

+49 (0) 731 (500) 23263

Email: sarah.gul@uni-ulm.de

Qualification:08/2009 – to date PhD Student at Institute of Physiological Chemistry,

University of Ulm. Member of the International Graduate

School in Molecular Medicine Ulm, Germany.

Supervisor: Prof. Dr. Thomas Wirth

Thesis: “Functional analysis of hepatic FOXO3 signalling

in glucose and lipid metabolism ”

2004 – 2006 Master of Philosophy (M. Phil)

(Molecular biology/Biochemistry)

Quaid-e-Azam University (QAU)

Islamabad, Pakistan

Thesis: "Iron-Regulated Outer Membrane Protein Profiles

of Pasteurella multocida”. Research done under Vaccine

Quality control section in National Veterinary Laboratories

Curriculum Vitae

158

(NVL) National agricultural research centre (NARC)

Islamabad, Pakistan

2002 – 2004 Master of Science (M. Sc)

(Molecular biology/Biochemistry)

Quaid-e-Azam University (QAU)

Islamabad, Pakistan

2000 – 2002 Bachelor of Science (B. Sc)

Botany/Zoology /Chemistry

Punjab University, Pakistan

1998 – 2000 Higher Secondary School (HSSC) (F. Sc)

Biology/Physics/Chemistry

PAF Intermediate college, Rawalpindi, Pakistan

1996 – 1998 Matriculation (Secondary School)

Biology/Physics/Chemistry

PAF Intermediate college, Rawalpindi, Pakistan

Publications:

S Gul, KH Holzmann, F Leithäuser, H Maier, M Vogel, T Luedde, B Boehm, P

Strnad, Y Sunami, T Wirth. Metformin reverses FOXO3-induced hyperactivation of

hepatic gluconeogenesis and catabolic pathways (Submitted).

Y Sunami, F Leithäuser, S Gul, K Fiedler, N Güldiken, S Espenlaub, KH Holzmann,

N Hipp, A Sindrilaru, T Luedde, B Baumann, S Wissel, F Kreppel, M Schneider, KS

Kochanek, S Kochanek, P Strnad, and T Wirth. Hepatic activation of IKK/NFκB

signaling induces liver fibrosis via macrophage-mediated chronic inflammation.

Hepatology. 2012 Sep;56(3):1117-28. doi: 10.1002/hep.25711. Epub 2012 Jul 10.

Posters:

S Gul , KH Holzmann , F Leithäuser, H Maier , B Böhm, P Strnad, Y Sunami, T

Wirth. FOXO3 regulates hepatic glucose production.

Poster presented by Dr. Yoshiaki Sunami in Zeitschrift für Gastroenterologie meeting,

Curriculum Vitae

159

Hannover, Germany, January 2013

S Gul , KH Holzmann , F Leithäuser, H Maier , B Böhm, P Strnad, Y Sunami, T

Wirth. FOXO3 regulates hepatic glucose production.

Poster presented by Dr. Yoshiaki Sunami in Europeon association for the study of

liver diseases EASL, Amsterdam. The Netherlands, April 2013

S Gul, KH Holzmann, F Leithäuser, H Maier, M Vogel, T Luedde, B Böhm, P Strnad,

Y Sunami, T Wirth. Metformin reverses FOXO3-induced hyperactivation of hepatic

gluconeogenesis and catabolic pathways.

Poster presented by Dr. Yoshiaki Sunami in European association for the study of

diabetes in 49th EASD virtual meeting. Barcelona, Spain September 2013

S Gul , KH Holzmann , F Leithäuser, H Maier , B Böhm, P Strnad, Y Sunami, T

Wirth. Hepatic activation of FOXO3 induces initial hyperglycemia and subordinate

hypoglycemia and pancreatic β-cell proliferation.

Poster presented in Europeon association for the study of liver diseases EASL

Barcelona, Spain April 2012

S Gul , KH Holzmann , F Leithäuser, H Maier , B Böhm, P Strnad, Y Sunami, T

Wirth. Activation of FoxO3a in the liver induces hypoglycemia and metabolic

dysfunction.

Poster presented in American Association for the study of Liver diseases AASLD San

Francisco, California, USA November 2011

S Gul , F Leithäuser, H Maier , P Strnad, Y Sunami, T Wirth. Activation of FoxO3a in

the liver induces hypoglycemia and metabolic dysfunction.

Poster presented in DGVS spring conference Complications of liver diseases, Berlin,

Germany May 2011

S Gul , F Leithäuser, H Maier , P Strnad, Y Sunami, T Wirth. Characterization of

FOXO3a function in the liver.

Poster presented in Retreat, Signalling pathways in development and regeneration,

Günzberg, Germany June 2010

Curriculum Vitae

160

Meeting/Conferences:

04/2012: Europeon association for the study of liver diseases (EASL)

Barcelona, Spain

11/ 2011: American Association for the study of Liver diseases (AASLD)

Sanfrancisco, California, USA

05/2011: DGVS spring conference 2011 Complications of liver diseases

Berlin, Germany