Molecular interactions between alcohol, hepatitis C virus ...€¦ · Figure 1.1 Clinical spectrum...

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Molecular interactions between alcohol, hepatitis C virus and interferon

Erin Marie McCartney B. Science (Biomedical Science) (Hons)

Discipline of Microbiology and Immunology

School of Molecular and Biomedical Science

The University of Adelaide

A dissertation submitted to The University of Adelaide

In candidature for the degree of

Doctor of Philosophy in the Faculty of Science

May 2011

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Table of Contents

List of Figures and Tables...........................................................................................x

Abstract ......................................................................................................................xv

Declaration ..............................................................................................................xviii

Acknowledgements ...................................................................................................xix

Publications Arising During PhD.............................................................................xx

Awards Received During PhD..................................................................................xx

Presentations Arising From PhD ............................................................................xxi

Materials Providers ................................................................................................xxiii

Abbreviations Used..................................................................................................xxv

Chapter 1 ......................................................................................................................1

Introduction .................................................................................................................1

1.1 Hepatitis C Virus............................................................................................................1

1.1.1 Epidemiology ...........................................................................................................1

1.1.2 Transmission ......................................................................................................................2

1.1.3 Pathogenesis .............................................................................................................2

1.1.4 Treatment..................................................................................................................4

1.1.5 The HCV genome.....................................................................................................5

1.1.6 Classification of genotypes.......................................................................................6

1.1.7 HCV proteins............................................................................................................6

1.1.8 HCV life cycle ..........................................................................................................9

1.1.9 HCV model systems ...............................................................................................10

1.1.9.1 Animal models ..............................................................................................................11

1.1.9.2 Cell culture systems ......................................................................................................11

1.1.9.3 Infectious cell culture model.........................................................................................12

1.2 Alcohol and HCV .........................................................................................................12

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1.3 Alcohol Metabolism .....................................................................................................15

1.3.1 Cytochrome P4502E1.............................................................................................16

1.4 Oxidative Stress............................................................................................................17

1.4.1 Oxidative stress and alcohol ...................................................................................17

1.4.2 Oxidative stress and HCV ......................................................................................18

1.5 ROS Induced Liver Damage .......................................................................................19

1.6 Interferon......................................................................................................................22

1.6.1 Effect of alcohol on IFN-α efficacy .......................................................................23

1.6.2 Effect of HCV and alcohol on IFN signaling .........................................................25

1.7 Cellular Factors Involved In HCV Life Cycle...........................................................27

1.7.1 STAT3 ....................................................................................................................27

1.7.2 Oxidative stress and STAT3...................................................................................29

1.8 Hypothesis and Aims ...................................................................................................29

Chapter 2 ....................................................................................................................31

Materials and Methods .............................................................................................31

2.1 General Reagents .....................................................................................................31

2.1.1 Transient transfection of plasmid DNA .................................................................31

2.1.2 Stable transfection of plasmid DNA to generate over-expressing cell lines ..........31

2.1.3 Transient transfection of StealthTM siRNA oligonucleotides .................................32

2.2 Tissue Culture Techniques..........................................................................................32

2.2.1 Tissue culture medium ...........................................................................................32

2.2.2 Maintenance of cell lines........................................................................................33

2.2.3 Cryopreservation of cultured cells..........................................................................33

2.2.4 Resuscitation of frozen cells...................................................................................34

2.2.5 Trypan blue exclusion ............................................................................................34

2.2.6 CellTiter-Blue® cell viability assay ........................................................................34

2.2.7 CellTiter 96® non-radioactive cell proliferation assay (MTT) ...............................34

2.3 Cultured Cell Lines......................................................................................................35

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2.3.1 Huh-7 ......................................................................................................................35

2.3.2 NNeoC-5B (RG).....................................................................................................35

2.3.3 NNeo3-5B (RG) .....................................................................................................36

2.3.4 HCV Genomic Replicon + CYP2E1 ......................................................................36

2.3.5 Huh-7 (EG) + CYP2E1 ..........................................................................................36

2.3.6 Huh-7.5 ...................................................................................................................36

2.3.7 Huh-7.5 + CYP2E1 ................................................................................................37

2.4 HCVcc Infectious System............................................................................................37

2.4.1 Generation of HCVcc viral stock ...........................................................................37

2.4.1.1 Preparation of HCV RNA.............................................................................................37

2.4.1.2 HCV RNA transfection.................................................................................................37

2.4.1.3 Concentration of HCV viral stocks (PEG precipitation) ..............................................38

2.4.1.4 Titration of infectious HCV ..........................................................................................38

2.4.1.5 Amplification of HCV viral stocks (‘up-scale’) ...........................................................39

2.4.2 General infection protocol for HCVcc ...................................................................40

2.5 General Molecular Biology Methods .........................................................................40

2.5.1 Synthetic oligonucleotides......................................................................................40

2.5.2 Bacterial transformation .........................................................................................41

2.5.3 Mini-preparation (small scale) of plasmid DNA....................................................41

2.5.4 Maxi-preparation (large scale) of plasmid DNA....................................................42

2.5.5 Restriction endonuclease digestion ........................................................................42

2.5.6 Agarose gel electrophoresis....................................................................................43

2.5.7 DNA ligation ..........................................................................................................43

2.5.8 Gel purification.......................................................................................................43

2.5.9 DNA sequencing ....................................................................................................44

2.5.10 Extraction of total RNA........................................................................................45

2.5.11 DNAseI treatment of RNA samples......................................................................45

2.5.12 Nucleic acid quantification...................................................................................46

2.5.13 cDNA preparation ................................................................................................46

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2.5.14 Polymerase Chain Reaction..................................................................................46

2.5.15 Real-Time Quantitative PCR................................................................................47

2.5.16 Extraction of cellular protein................................................................................47

2.5.17 Protein quantification ...........................................................................................48

2.5.18 SDS PAGE and protein transfer ...........................................................................48

2.5.19 Western blotting ...................................................................................................49

2.5.20 Dual Renilla luciferase assay................................................................................50

2.5.21 Measurement of ROS ...........................................................................................51

2.5.22 Acetaminophen assay ...........................................................................................51

2.5.23 Treatment of cells .................................................................................................52

2.5.24 Immunofluorescence microscopy.........................................................................54

2.5.24.1 HCV antigen staining..................................................................................................54

2.5.24.2 STAT3-C-fLAG staining ............................................................................................54

2.5.24.3 α-tubulin staining........................................................................................................55

2.6 Data Analysis................................................................................................................55

Chapter 3 ....................................................................................................................56

An in vitro Model System to Study the Effects of Alcohol Metabolism on HCV

Replication..................................................................................................................56

3.1 Introduction..................................................................................................................56

3.1.1 Generation of stable CYP2E1 HCV replicon cell lines..........................................57

3.1.2 Generation of stable CYP2E1 Huh-7 cell lines ......................................................58

3.1.3 CYP2E1 stable cell lines harbour replicon RNA and are permissive for HCV JFH-

1 infection ........................................................................................................................59

3.2 Characterisation of Stable CYP2E1 Cell Lines.........................................................60

3.2.1 Determination of growth rates for stable CYP2E1 cell lines .................................60

3.2.2 CYP2E1 is metabolically active in the stable cell lines .........................................61

3.2.3 Is CYP2E1 mediated metabolism of ethanol toxic to cells? ..................................61

3.3 Discussion......................................................................................................................62

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Chapter 4 ....................................................................................................................67

The Effect of Alcohol Metabolism on HCV Replication ........................................67

4.1 Introduction..................................................................................................................67

4.2 The Effect of Ethanol metabolism on HCV Replication ..........................................67

4.2.1 Ethanol metabolism by CYP2E1 increases HCV replication in replicon cells ......67

4.3 Establishing a Molecular Mechanism For the Ethanol Induced Increase in HCV

Replication ..........................................................................................................................69

4.3.1 Ethanol metabolism increases oxidative stress in HCV replicon cells...................69

4.3.2 Anti-oxidant treatment decreases HCV replication................................................70

4.3.3 Acetaldehyde does not modulate HCV replication ................................................71

4.3.4 Ethanol metabolism does not modulate HCV IRES activity..................................71

4.3.5 Exogenous H2O2 decreases HCV replication..........................................................72

4.4 The Effect of Ethanol Metabolism on HCVcc...........................................................73

4.4.1 Ethanol metabolism increases JFH-1 replication ...................................................73

4.4.2 Pre treatment with ethanol is required to increase HCV JFH-1 replication ...........73

4.4.3 Exogenous H2O2 decreases HCV JFH-1 replication...............................................74

4.4.4 NAC treatment decreases HCV JFH-1 replication.................................................75

4.5 The Oxidative Stress Sensitive Transcription Factor STAT3 .................................75

4.5.1 Rationale for investigating the involvement of STAT3 in the ethanol induced

increase in HCV replication ............................................................................................75

4.5.2 The oxidative stress sensitive transcription factor STAT3 plays a role in the

ethanol induced increase in HCV replication ..................................................................76

4.5.2.1 Ethanol metabolism increases STAT3 activation .........................................................76

4.5.2.2 Ethanol metabolism increases STAT3 promoter activity .............................................77

4.6 Discussion......................................................................................................................78

Chapter 5 ....................................................................................................................85

The Effect of Ethanol Metabolism on IFN-α Signaling .........................................85

5.1 Introduction..................................................................................................................85

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5.2 Ethanol Metabolism Decreases the Efficacy of IFN-α .............................................85

5.2.1 The effect of ethanol metabolism on the anti-viral efficacy of IFN-α ...................85

5.3 CYP2E1 Mediated Ethanol Metabolism Modulates the JAK/STAT Signaling

Cascade ...............................................................................................................................86

5.3.1 The phosphorylation status of signal transduction molecules in the JAK/STAT

signaling pathway in the presence of ethanol metabolism ..............................................86

5.3.2 Decreased STAT1-Y701 phosphorylation is dependent on CYP2E1 mediated

metabolism of ethanol .....................................................................................................88

5.3.3 The ethanol induced decrease in STAT1-Y701 phosphorylation is independent of

HCV replication...............................................................................................................88

5.4 The Effect of Ethanol Metabolism on HCVcc and IFN-α .......................................89

5.4.1 The effect of ethanol metabolism on the efficacy of IFN-α against HCVcc .........89

5.4.2 Ethanol metabolism disturbs the JAK/STAT signaling pathway in the presence of

HCV JFH-1......................................................................................................................90

5.5 Ethanol Metabolism Decreases ISRE Promoter Activity.........................................90

5.5.1 Ethanol metabolism alters ISG expression.............................................................91

5.6 Discussion......................................................................................................................92

Chapter 6 ....................................................................................................................99

The role of STAT3 in HCV replication ...................................................................99

6.1 Introduction..................................................................................................................99

6.2 HCV Replication Activates STAT3..........................................................................100

6.2.1 STAT3 is constitutively activated in HCV genomic replicon cells......................100

6.2.2 STAT3 mRNA is increased during HCV JFH-1 infection...................................100

6.2.3 HCV JFH-1 replication constitutively activates STAT3......................................101

6.2.4 HCV JFH-1 activates the STAT3 promoter .........................................................102

6.3 Characterisation of a Constitutively Active STAT3 (STAT3-C)...........................102

6.3.1 STAT3-C is functionally active............................................................................102

6.3.2 STAT3-C expression in Huh-7.5 cells .................................................................103

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6.3.3 Transient expression of STAT3-C increases HCV JFH-1 replication .................104

6.4 Characterisation of Huh-7.5 Cells Stably Expressing a Constitutively Active Form

of STAT3 (STAT3-C) ......................................................................................................104

6.4.1 Detection of STAT3-C positive clones ................................................................104

6.4.2 STAT3-C stable cell lines maintain permissiveness for JFH-1 infection ............105

6.5 The Effect of STAT3-C Expression on HCV Replication ......................................106

6.5.1 Stable expression of STAT3-C increases HCV JFH-1 replication ......................106

6.6 Can Leukemia inhibitory factor (LIF) increase HCV replication? ......................106

6.7 The Effect of STAT3 Inhibition on HCV Replication ............................................107

6.7.1 siRNA knockdown of STAT3 decreases HCV JFH-1 replication .......................107

6.7.2 Chemical Inhibition of STAT3 decreases HCV replication.................................108

6.7.2.1 AG490 and STA-21 decrease HCV replication in genomic replicon cells.................108

6.7.2.2 Chemical inhibition of STAT3 decreases HCV JFH-1 replication.............................109

6.8 Inhibition of STAT3 Prevents HCV Establishing a Productive Infection............110

6.9 STA-21 Inhibits Microtubule Polymerization.........................................................111

6.10 Discussion..................................................................................................................112

Chapter 7 ..................................................................................................................118

Conclusions and Future Directions........................................................................118

7.1 Proposed Model of Interactions Between HCV and Alcohol.................................125

Appendices ...............................................................................................................127

Appendix I. General Solutions and Buffers...................................................................127

Appendix II. Infectious HCV Constructs. .....................................................................130

Appendix III. pcDNA6/V5-His .......................................................................................131

Appendix IV. pcDNA-2E1...............................................................................................132

Appendix V. pcDNA-2E1-AS (CYP2E1 Anti-Sense)....................................................133

Appendix VI. PRL-HL ....................................................................................................134

Appendix VII. pSTAT3-Luc ...........................................................................................135

Appendix VIII. pRL-TK .................................................................................................136

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Appendix IX. pISRE-Luc................................................................................................137

Appendix X. PRc/CMV-STAT3-C .................................................................................138

Appendix XI. pRc/CMV..................................................................................................139

Appendix XII. Publications.............................................................................................140

References.................................................................................................................141

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List of Figures and Tables

Figure Number On page: Chapter 1 Figure 1.1 Clinical spectrum of HCV infection 3 Figure 1.2 Progression of HCV induced liver disease 3 Figure 1.3 HCV genome and polyprotein processing 5 Figure 1.4 Global HCV genotype distribution 6 Figure 1.5 Model of HCV entry 9 Figure 1.6 Life cycle of HCV 10 Figure 1.7 HCV model systems 11 Figure 1.8 Construction of HCV genomic replicon 11 Figure 1.9 Pathways of alcohol metabolism 15 Table 1.1 The interferon family members 22 Figure 1.10 IFN-α signal transduction 22 Figure 1.11 Potential and known host factors involved in the complete life

cycle of HCV 27 Figure 1.12 STAT3 signal transduction 28 Chapter 2 Table 2.1 Cell lines and culture conditions used in this study 33 Table 2.2 Primer sequence table 41

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Table 2.3 Antibody concentration 50 Chapter 3 Figure 3.1 Detection of CYP2E1 expression in HCV sub-genomic

replicon cell lines +/-CYP2E1 57 Figure 3.2 Detection of CYP2E1 expression in HCV genomic replicon cell

lines +/-CYP2E1 58 Figure 3.3 Characterisation of Huh-7 cells expressing CYP2E1 58 Figure 3.4 Detection of HCV antigens in CYP2E1 stable cell lines 59 Figure 3.5 Comparison of growth rates in parental replicon cells versus

replicon cells expressing CYP2E1 60 Figure 3.6 CYP2E1 is metabolically active via acetaminophen toxicity assay 61 Figure 3.7 CYP2E1 metabolism of ethanol is not toxic to replicon cells 62 Chapter 4 Figure 4.1 Ethanol modulates HCV replication in the presence of CYP2E1

mediated metabolism 68 Figure 4.2 In the absence of CYP2E1 ethanol does not modulate HCV

replication 68 Figure 4.3 The ethanol induced increase in HCV replication is

dependent on CYP2E1 mediated metabolism of ethanol 69 Figure 4.4 Metabolism of ethanol by CYP2E1 increases oxidative stress

in HCV replication cells 70 Figure 4.5 Anti-oxidants decrease HCV replication 70 Figure 4.6 Acetaldehyde does not modulate HCV replication 71

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Figure 4.7 Ethanol metabolism does not modulate HCV IRES activity 72 Figure 4.8 H2O2 decreases HCV replication 72 Figure 4.9 Ethanol metabolism increases HCV JFH-1 replication 73 Figure 4.10 Pre-treatment of ethanol is required to enhance HCV JFH-1

replication via ethanol metabolism 74 Figure 4.11 H2O2 decreases HCV JFH-1 replication 74 Figure 4.12 The anti-oxidant NAC decreases HCV JFH-1 replication 75 Figure 4.13 Ethanol metabolism increases STAT3-Y705 phosphorylation 76 Figure 4.14 Ethanol metabolism increases STAT3-S727 phosphorylation 77 Figure 4.15 Ethanol metabolism increases STAT3 promoter activity 77 Figure 4.16 Possible role of STAT3 and oxidative stress in HCV replication 82 Chapter 5 Figure 5.1 IFN-α signal transduction pathway 85 Figure 5.2 Ethanol metabolism decreases the anti-HCV efficacy of IFN-α 86 Figure 5.3 Ethanol metabolism by CYP2E1 results in decreased

STAT1 phosphorylation at tyrosine residue 701 87 Figure 5.4 STAT1-Y701 phosphorylation is decreased by ethanol

metabolism 87 Figure 5.5 The ethanol induced decrease in STAT1-Y701

phosphorylation is dependent on CYP2E1 expression 88 Figure 5.6 The ethanol induced decrease in STAT1-Y701

phosphorylation is independent of HCV replication 88

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Figure 5.7 Ethanol metabolism decreases the anti-HCV JFH-1 efficacy

of IFN-α 89 Figure 5.8 Ethanol metabolism by CYP2E1 decreases

STAT1-Y701 phosphorylation in the presence of JFH-1 90 Figure 5.9 Ethanol metabolism decreases ISRE promoter activity 91 Figure 5.10 Ethanol metabolism reduces anti-viral ISG expression 92 Figure 5.11 Alcohol metabolism decreases IFN-α efficacy via

perturbation of the JAK/STAT signaling cascade 95 Figure 5.12 Possible mechanism for the inhibition of

STAT1-Y701 phosphorylation in the presence of ethanol metabolism via SHP-2 or SOCS3 97

Chapter 6 Figure 6.1 STAT3 activation is increased in HCV genomic replicon cells 100 Figure 6.2 Signaling pathway generated from microarray data showing

STAT3 mRNA up-regulated 2-fold in JFH-1 Huh-7 cells 101 Figure 6.3 STAT3 phosphorylation is increased in the presence of HCV

JFH-1 101 Figure 6.4 STAT3 promoter activity is increased in the presence of HCV 102 Figure 6.5 The STAT3-C construct is functionally active 103 Figure 6.6 STAT3-C expression in Huh-7.5 cells 103 Figure 6.7 Expression of STAT3-C in HCV JFH-1 infected Huh-7.5 cells 104 Figure 6.8 Transient expression of STAT3-C increases HCV JFH-1

replication 104

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Figure 6.9 Characterisation of Huh-7.5 cell lines stably expressing

STAT3-C 105 Figure 6.10 STAT3-C stable cell lines are permissive for HCV JFH-1

infection 105 Figure 6.11 Stable expression of STAT3-C increases HCV JFH-1

replication 106 Figure 6.12 LIF activates STAT3 and enhances HCV JFH-1 replication 107 Figure 6.13 Knockdown of STAT3 with siRNA decreases HCV JFH-1

replication 107 Figure 6.14 Action of STAT3 inhibitors 108 Figure 6.15 Inhibition of STAT3 modestly decreases HCV replication

in genomic replicon cells 109

Figure 6.16 Inhibition of STAT3 decreases HCV JFH-1 replication 109 Figure 6.17 Inhibition of STAT3 decreases the susceptibility of Huh-7.5

cells to HCV JFH-1 infection 110 Figure 6.18 Inhibition of STAT3 decreases the susceptibility of Huh-7.5

cells to HCV JFH-1 infection 110 Figure 6.19 Model of STAT3 interaction with STMN1 111 Figure 6.20 Inhibition of STAT3 with STA-21 inhibits α-tubulin

polymerization 111 Chapter 7 Figure 7.1 Proposed model of interactions between HCV, alcohol and

hepatocytes 125

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Abstract

Hepatitis C virus (HCV) is a significant human pathogen that in many cases,

establishes a chronic life long infection of the liver, resulting in progressive liver

disease that culminates in the development of cirrhosis and hepatocellular carcinoma

(HCC). The only treatment option available for HCV infection is a combination

therapy of Interferon-α (IFN-α) and Ribavirin. However, it is only successful in a

limited number of patients. There are a number of co-factors that accelerate liver

disease in chronic hepatitis C (CHC) and one of the most significant factors is alcohol

consumption. Furthermore, alcohol consumption has been shown to reduce the

efficacy of IFN-α treatment. Despite these clinical observations, the molecular

mechanisms by which alcohol exerts these effects are unknown and remain relatively

unexplored. This is largely due to the lack of an appropriate model system to enable

studies into the interaction between the HCV life cycle, alcohol metabolism and IFN.

To overcome this limitation, we have developed an in vitro cell culture model system

that enables Huh-7 cells to metabolise alcohol (ethanol), via the enzyme cytochrome

P4502E1 (CYP2E1), while also supporting HCV replication directed from both the

HCV replicon and infectious HCV model systems. As such, this model system has

been used in this thesis to extensively investigate the interactions between alcohol

metabolism, HCV and IFN.

It is known clinically that HCV infected persons who consume alcohol, have

exacerbated liver disease and in some cases increased serum of HCV. One postulated

mechanism for this effect is that alcohol consumption increases HCV replication,

which in turn leads to increased viral burden in the liver and associated pathogenic

effects. We have shown that CYP2E1 mediated metabolism of alcohol increases HCV

RNA replication in vitro, in both the replicon and infectious HCV model systems.

Furthermore, we have demonstrated that this process is mediated via the oxidative

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stress produced by alcohol metabolism, as the anti-oxidant NAC blocked this alcohol-

induced increase in HCV RNA replication. These observations correlate with what is

noted clinically and suggest a potential mechanism whereby alcohol consumption in

chronically infected HCV individuals, leads to accelerated rates of liver disease

progression. These findings form a rationale to clinically investigate the use of anti-

oxidant therapy in CHC patients consuming alcohol.

In this thesis we present a molecular mechanism for the reduced response rates to

IFN-α therapy in HCV infected individuals consuming alcohol. Specifically we have

shown that alcohol metabolism attenuates the anti-HCV activity of IFN-α via

perturbation of the JAK/STAT signaling cascade and subsequently decreases the

expression of anti-viral ISGs, which are the effector molecules of an IFN response.

Thus alcohol metabolism seems to be able to blunt the anti-viral effects of IFN and

this has implications for anti-viral directed therapy and the innate immune response to

HCV infection in the liver.

Also arising from this thesis was the novel observation that levels of the oxidative

stress sensitive transcription factor signal transducer and activator of transcription 3

(STAT3) were increased in the context of HCV replication and alcohol metabolism.

From these observations we hypothesized that STAT3 could be a potential pro-viral

host factor. We have presented strong evidence in this thesis to suggest that STAT3 is

working at multiple levels to assist HCV replication. Firstly, we have shown that

STAT3 is activated in the presence of replicating HCV, and we believe STAT3 may

be facilitating HCV replication via the production of specific STAT3 dependent

genes. Secondly, we have presented significant data in this thesis to suggest that

STAT3 may be assisting HCV entry into hepatocytes via the control of microtubule

dynamics. These studies emphasize the need for further investigations into the role of

STAT3 in the life cycle of HCV and suggest a role for therapies directed against

STAT3 in patients with CHC, in order to limit disease progression. Furthermore, the

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ability of HCV to activate STAT3 and the oncogenic nature of STAT3 suggest that

STAT3 could be playing a mechanistic role in the development of HCC in individuals

infected with HCV.

In summary we have developed an in vitro model system to simultaneously evaluate

the impact of HCV replication, alcohol metabolism and IFN, on each other. We have

shown that alcohol metabolism increases HCV replication via an oxidative stress

related mechanism and that the anti-viral action of IFN is severely attenuated in the

presence of alcohol metabolism. Moreover, we have also identified STAT3 as a pro-

viral host factor that may exert its effect at multiple stages of the HCV life cycle.

While all of the experiments in this thesis were conducted in vitro, the knowledge

gained from this work will aid in the design of future studies to be performed when a

small animal model of HCV pathogenesis becomes available. We believe we have

significantly added to our understanding of the interplay between HCV and alcohol

metabolism and that in the long term these findings will aid in therapeutic responses

and management of patients chronically infected with HCV.

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Acknowledgements

I would like to thank my supervisor Michael Beard for the opportunity to do a PhD in

his laboratory and for his continued assistance and mentoring throughout the years.

I offer my sincerest gratitude to Karla Helbig and Nicholas Eyre for their excellent

advice, support and technical assistance during my PhD.

I am most grateful to all members of the Hepatitis C Research Laboratory both past

and present. Many of whom I count as life long friends. Specifically I would like to

acknowledge Lilijana Semendric, Evelyn Yip, Gorjana Radisic, Edmund Tse, Kate

Muller, Sumudu Narayana and Gemma Sharp. I would also like to thank the

department of Microbiology and Immunology for the opportunity to undertake a PhD.

I would like to thank my parents Kevin and Marilyn, for their continued support,

encouragement and editing of this thesis. I would also like to thank my brother

Patrick, for providing invaluable encouragement both at home and from afar at the

many locations he has been situated. Finally, I would like to thank my partner Tom,

who moved to Adelaide during the final stages of this thesis and has been the epitome

of patience. I would also like to acknowledge Tom for his graphical design

contributions to figures in this thesis.

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Publications Arising During PhD

McCartney EM, Helbig KJ, Beard MR (2011). The role of STAT3 in hepatitis C virus life cycle. (Manuscript in preparation) McCartney EM, Beard MR (2010). Impact of alcohol on hepatitis C virus replication and interferon signaling. World Journal of Gastroenterology. 2010 March 21; 16(11): 1337-1343. (see Appendix XII) McCartney EM, Semendric L, Helbig KJ, Hinze S, Jones B, Weinman S and Beard MR (2008). Alcohol metabolism increases hepatitis C virus replication and attenuates the anti-viral action of interferon. J Infect Dis. 2008 Dec 15;198(12):1766-75. (see Appendix XII) Helbig KJ, Yip E, McCartney EM, Eyre NS and Beard MR. A screening method for identifying disruptions in interferon signaling reveals HCV NS3/4a disrupts Stat-1 phosphorylation. Antiviral Res. 2008 March, 77:169-176.

Awards Received During PhD

2010 Royal Adelaide Hospital Clinical Project Grant

The role of STAT3 in the life cycle of Hepatitis C virus and hepatocellular carcinoma development - $15,000

2009 Australian Centre for Hepatitis and HIV Annual Meeting, Terrigal, ACH2 Young Investigator Travel Award for oral presentation - $5000

National award - one awarded per year for travel to international HCV meeting.

2008 Adelaide University Health Sciences Travel Fellowship - $2000 2008 School of Molecular and Biomedical Science PhD student poster award - $200 2007 Australian Centre for Hepatitis and HIV Annual Meeting, Barossa Valley,

ACH2 PhD Student Oral Presentation Award – $500 2006 13th International Meeting on Hepatitis C Virus and Related Viruses, Cairns,

Student Travel Grant - $1500

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Presentations Arising From PhD

International

McCartney EM, KJ Helbig, MR Beard. The role of STAT3 in the life cycle of HCV. 46th European Association For The Study of The Liver, Berlin, Germany, 2011. (poster presentation) McCartney EM, KJ Helbig, MR Beard. Alcohol metabolism increases HCV replication in a STAT3 dependent manner. 16th International Meeting on Hepatitis C Virus and Related Viruses, Nice, France, 2009. (poster presentation)

McCartney EM, L Semendric, KJ Helbig, MR Beard. The role of STAT3 in the alcohol induced increase in HCV replication. 15th International Meeting on Hepatitis C Virus and Related Viruses, San Antonio, USA, 2008. (poster presentation)

McCartney EM, L Semendric, KJ Helbig, MR Beard. CYP2E1 metabolism of alcohol suppresses the anti-HCV action of interferon. 13th International Meeting on Hepatitis C Virus and Related Viruses, Cairns, Australia, 2006. (oral presentation)

National

McCartney EM, KJ Helbig, MR Beard. Role of STAT3 on HCV replication. Australian Centre for Hepatitis Virology workshop, Yarra Valley, Australia, 2010. (oral presentation)

McCartney EM, L Semendric, KJ Helbig, MR Beard. Role of STAT3 and oxidative stress on HCV replication. Australian Centre for Hepatitis Virology workshop, Terrigal, Australia, 2009. (oral presentation) McCartney EM, L Semendric, KJ Helbig, MR Beard. Role of STAT3 and oxidative stress on HCV replication. Australian Centre for Hepatitis Virology workshop, Barrossa Valley, Australia, 2008. (oral presentation) McCartney EM, L Semendric, KJ Helbig, MR Beard. CYP2E1 metabolism of alcohol suppresses the anti-HCV action of interferon. Australian Centre for Hepatitis Virology workshop, Melbourne, Australia, 2007. (oral presentation)

Helbig KJ, Yip E, McCartney EM, Eyre NS, Beard MR.A high throughput method for screening disruptions in interferon signaling reveals NS3/4a disrupts Stat-1 phoshporylation. Australian Centre for Hepatitis Virology workshop, Melbourne, Australia, 2007. (oral presentation)

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McCartney EM, L Semendric, KJ Helbig, MR Beard. CYP2E1 metabolism of alcohol suppresses the anti-HCV action of interferon. Australian Centre for Hepatitis Virology and HIV virology interest group inaugural workshop, Terrigal, Australia, 2005. (oral presentation)

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Materials Providers

Abcam Cambridge, UK

Ambion Texas, USA

Amersham Pharmacia Biotech Birminghamshire, UK

Amrad Biotech Boronia, VIC, Australia

Anogen Ontario, Canada

Applied Biosystems Warrington, UK

Becton Dickson Labware New Jersey, USA

Biomol New Jersey, USA

BioRad Laboratories California, USA

Cell Signaling Massachusetts, USA

Chemicon International Massachusetts, USA

Cohu California, USA

DAKO California, USA

Dynatech Virginia, USA

GeneWorks Adelaide, SA, Australia

Invitrogen California, USA

Merck Darmstadt, Germany

Mol Bio Laboratories California, USA

Molecular Probes Oregon, USA

Nalge Nunc International Illinois, USA

Nikkon Sydney, NSW, Australia

New England Biolabs Massachusetts, USA

Oxis Oregon, USA

Olympus New York, USA

Panomics Santa Clara, USA

Perkin Elmer Massachusetts, USA

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Promega Wisconsin, USA

QIAgen Hilden, Germany

Roche Indiana, USA

Rockland Pennsylvania, USA

Schering-Plough New Jersey, USA

Schleicher and Schuell Dassel, Germany

Sigma Missouri, USA

SPSS Inc Illinois, USA

Stratagene California, USA

UVP Inc California, USA

Vector Laboratories California, USA

Vision Systems Mount Waverley, VIC, Australia

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Abbreviations Used

A adenosine

aa amino acids

bp base pairs

BSA bovine serum albumin

BVDV bovine viral diarrhoea virus

C cytosine

° C degrees Celsius

cDNA complimentary deoxyribosenucleic acid

CHC chronic hepatitis C

CMV cytomegalovirus

CYP2E1 Cytochrome P450-2E1

dATP deoxyadenosine-5’-triphosphate

dCTP deoxycytosine-5’-tripshosphate

DEPC diethyl pyrocarbonate

dGTP deoxyguanosine-5’-triphosphate

dH2O deionised water

DMEM Dulbecco’s Modified Eagle Medium with HEPES

DNA deoxyribonucleic acid

dNTP deoxyribonucleotide triphosphate

dTTP deoxythymidine-5’-triphosphate

EDTA ethylene diamine tetra acetic acid

ER endoplasmic reticulum

FCS foetal calf serum

FITC fluorescein isothiocyanate

g grams

G guanosine

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GAPDH glyceraldehyde-3-phosphate deydrogenase

HCC hepatocellular carcinoma

HCV hepatitis C virus

HRP horse radish peroxidase

IFN-α interferon alpha

IFN-γ interferon gamma

IRES internal ribosome entry site

ISRE interferon stimulated response element

JAK janus kinase

kb kilobase

kDa kilo Dalton

L-Agar LB + agar

LB Luria Bertani broth

LDL low density lipoproteins

Luc luciferase

µg micrograms

µl microlitres

µM micromolar

mA milliamps

mg milligrams

ml millilitres

mM millimolar

MCS Multiple Cloning Site

MEM Minimum Essential Medium

min minute(s)

mRNA messenger RNA

MW molecular weight

ng nanograms

nM nanomolar

xxvii

N/A not applicable

nt nucleotide

ORF open reading frame

PAGE polyacrylamide gel electrophoresis

PBS phosphate buffered saline; 0.15M NaCl, 6M K2HPO4, 2mM

KH2PO4 (pH 7)

PCR polymerase chain reaction

pg picograms

pmol picomolar

RNA ribonucleic acid

rpm revolutions per minute

RT room temperature

RT-PCR reverse transcriptase polymerase chain reaction

sd standard deviation

SDS sodium dodecyl sulfate

sec second(s)

ss single stranded

STAT signal transducer and activator of transcription

STMN1 Stathmin

T T thymidine

TAE 0.04M Tris (pH 8), 0.04M Acetic Acid, 1mM EDTA

TEMED TEMED N,N,N’,N’-tetramethylethyethylenediamine

Tris 3,3,5,5-tetramethylbenzidine

TYK2 tyrosine kinase 2

U units

xxviii

UTR untranslated region

V volts

w/v weight per volume

1

Chapter 1

Introduction

1.1 Hepatitis C Virus

1.1.1 Epidemiology

The hepatitis C virus (HCV) is one of the main aetiological factors responsible for

liver disease worldwide. Until the late 1970’s HCV was an elusive pathogen known

as ‘non A, non B’ hepatitis. However, with the identification of the HCV genome in

1989 (Choo et al. 1989), great advances have been made in characterizing the

molecular biology and pathogenesis of the virus. HCV is an enveloped virus with a

diameter of approximately 50 nm belonging to the Hepacivirus genus and the

Flaviviridae family (Farci 2002). It is estimated that there are over 170 million people

infected with HCV worldwide, with 210,000 of these infected individuals residing in

Australia (Dore et al. 2003). There are approximately 14,000 new HCV infections

diagnosed every year in Australia and 3-4 million world-wide (Shepard et al. 2005).

Of these infected individuals approximately 75% will go on to develop life long

necroinflammatory liver disease, which over decades results in serious complications

such as fibrosis, cirrhosis and hepatocellular carcinoma (Seeff et al. 1992; Poynard et

al. 1997). This progressive liver disease is thought to arise as a result of the chronic

inflammatory response directed at clearing HCV infected hepatocytes, which results

in the establishment of an environment favourable for the fibrogenic process (Guidotti

and Chisari 2006). Currently there is no effective HCV vaccine and IFN/Ribavirin

combination therapy is the only treatment option for HCV infection. However, this

treatment is only effective in 50% of individuals at best and often has severe side

effects. Over the next few years there will be progressive implementation of direct

2

acting antivirals (DAA) against HCV. DAAs such as NS3/4A protease and NS5A

polymerase inhibitors will radically change treatment strategies for CHC, however,

there will still be a significant number of individuals who will not have access to these

new therapies over the next decade (Shimakami et al. 2009; Lemon et al. 2010). As

such, HCV infection will continue to be a major cause of global morbidity and

suffering and places a significant burden on health systems.

1.1.2 Transmission

HCV is transmitted primarily through the transfer of blood and blood products. The

majority of infections pre 1992 occurred through blood transfusions and organ

transplantations. However, with the introduction of blood screening techniques in

1992 this form of transmission was virtually eradicated from the western world. The

majority of new infections now occur through intravenous (IV) drug use. This form

of transmission accounts for over 50% of new cases of HCV infection annually and

over 70% of long term IV drug users test positive for HCV antibodies (Dawson et al.

1991). HCV is less commonly transmitted via occupational exposure to blood in

needle stick injuries, tattooing and from exposure to blood or serum derived fluids in

the scenarios of an infected mother giving birth. An entirely different scenario exists

in the developing world where transmission appears to be most likely through unsafe

therapeutic injections and un-screened blood transfusions (Te and Jensen 2010).

1.1.3 Pathogenesis

HCV replication occurs primarily in hepatocytes, however, reports have been made

that other cell types harbour HCV RNA (reviewed in Dustin and Rice 2007). These

include B cells (Sung et al. 2003), dendritic cells (Pachiadakis et al. 2005), monocytes

and CD4+ and CD8+ T lymphocytes (Pham et al. 2008), however, their role in the

life cycle of HCV remains unknown and much of the data presented in these studies

remains controversial. HCV is a non-cytopathic virus and it is thought that the

3

adaptive immune response directed towards clearing HCV infected hepatocytes

mediates the majority of the liver disease associated with chronic HCV infection.

After an initial acute HCV infection there is an incubation period of 5-12 weeks and

during this time anti-HCV antibodies are generally not detected. Acute hepatitis

infections are generally asymptomatic and 20% of patients are able to clear the virus

via a vigorous immune response. The remaining 80% develop a persistent infection

that is defined as chronic hepatitis C (CHC). Over the course of 20-30 years CHC can

develop into progressive liver disease as a result of continued lymphatic infiltration

into the liver. In a large proportion of individuals this process culminates in fibrosis,

cirrhosis and in some 2% of persons, hepatocellular carcinoma (HCC) (Figure 1.1).

The immune response directed against HCV is still considered the main factor in the

development of HCV induced liver disease. There is continuous infiltration and death

of specific HCV T cells in the liver, the lysis of some but not all HCV infected

hepatocytes and the secretion of pro-inflammatory cytokines. CHC can be

characterised by an inability of the T cell response to clear the virus from the liver.

This subsequently results in continuous destruction of liver cells at a low level

(Guidotti and Chisari 2006). This process is also thought to activate hepatic stellate

cells, which are the primary source of the extracellular matrix in liver fibrosis. The

earliest change in the morphology of the HCV infected liver is the expansion of the

portal area by fibrosis, which occurs via the formation of thin collagen fibers that are

secreted from the portal tracts and separate hepatocytes. As the disease progresses

over decades, fibrous bridges form between portal areas and cirrhosis develops.

Cirrhosis is the most advanced form of liver disease, characterised by extensive

scarring that stiffens blood vessels and distorts the internal structure of the liver,

impairing its function (Figure 1.2). The pathogenic nature of HCV has resulted in it

being one of the major causes of liver disease worldwide.

Infection

Cirrhosis

Liver Failure

HCC

80%20%

20%

2%

Acute Hepatitis

Resolution Chronic Hepatitis

Figure 1.1 Clinical spectrum of HCV infection

Figure 1.2 Progression of HCV induced liver disease

Fibrosis

Time 20-30 years

Normal HCCInflammation Cirrhosis

Normal Liver Cirrhotic Liver

4

1.1.4 Treatment

The only treatment option available at this time for HCV infection is a combination

therapy of pegylated interferon-α2b (IFN-α2b) and ribavirin. IFN-α is an inducible

cytokine capable of stimulating an anti-viral response and ribavirin is a guanine

nucleotide analogue, although the exact nature of its anti-viral effect against HCV is

controversial. This combination therapy decreases viral replication, improves hepatic

inflammation and is able to improve or reverse hepatic fibrosis. Patients with

genotypes 1 are less sensitive to IFN-α treatment, with only 50% showing a sustained

virological response (SVR), which is characterised as an absence of detectable virus

24 weeks after the end of IFN treatment. However, patients with genotypes 2 and 3

respond better to IFN treatment with 80-90% of patients showing a SVR (Zeuzem et

al. 2004). On average, this combination therapy is successful in only 50% of patients

and is associated with severe side effects such as flu-like symptoms and hemolytic

anemia. Also, the long treatment regime ranging between 24 and 48 weeks makes

compliance difficult for many patients. Thus, there is a clear need for better

therapeutic treatment for HCV infection (Di Bisceglie and Hoofnagle 2002). This

need is further highlighted by the fact that many patients are simply not candidates for

therapy as individuals with a history of mental illness; continuing drug dependency

and non-compliance are excluded from treatment. In addition, and of particular

reference to this thesis, is the clinical observation that consumption of alcohol

severely impairs the therapeutic actions of IFN-α thus making alcohol consumption a

contraindication to treatment (Safdar and Schiff 2004). The exact mechanisms

whereby alcohol impairs the efficacy of IFN is unknown and will be discussed in

more detail throughout this thesis. The current price of a typical 48-week course of

interferon treatment for HCV genotype 1 infection is $25,000 USD (Shepard et al.

2005). Thus with current predictive models showing an exponential increase in HCV

induced liver disease over the next 20 years, it is imperative that more affordable and

effective treatment options are developed. Towards this end, a number of specific

HCV anti-virals are in pre-clinical trials. For example polymerase (NS5B) and

5

protease inhibitors (NS34A) have shown much promise in reducing HCV RNA levels

(Shimakami et al. 2009; Lemon et al. 2010). However, viral resistance to these

compounds is almost inevitable and while they are certainly effective they are not

affordable treatment options for the developing world.

1.1.5 The HCV genome

HCV contains a positive sense RNA genome of approximately 9,600 nucleotides that

consists of one large open reading frame (ORF) encoding for a single poplyprotein

precursor [Figure 1.3 (Moradpour et al. 2007)]. This polyprotein is cleaved both co-

and post-translationally by host and viral proteases to generate the 10 polypeptides

that represent the structural and non-structural HCV proteins.

At either end of the viral genome are untranslated regions (UTR) termed the 5’UTR

and 3’UTR. Situated in the 5’UTR (approximately 340 nucleotides) is the Internal

Ribosome Entry Site (IRES), a region of single stranded RNA with a high degree of

secondary structure. The IRES precedes the initiation codon of the HCV polyprotein

and it is essential for the binding of the host 40S ribosomal subunit to initiate

translation of the RNA genome in a cap independent manner. In addition, the 5’UTR

contains a sequence which partially overlaps with the IRES and is essential for viral

replication, it has also been speculated to be involved in the regulation of the switch

from viral translation to replication (Appel et al. 2006). The 3’UTR is situated

downstream of the HCV ORF stop codon and is highly conserved amongst HCV

genotypes. It consists of three major elements that play a role in replication - (i) a

variable region which follows the stop codon, (ii) a polyuridine tract and (iii) three

stem loop structures known as the 3’X region. Current literature suggests that the

polyuridine tract and the 3’X region are integral for negative strand RNA synthesis

(Friebe and Bartenschlager 2002).

Figure 1.3 HCV Genome and polyprotein processing (Moradpour D, Penin F, et al. 2007)

NOTE:

This figure is included in the print copy of the thesis held in the University of Adelaide Library.

6

1.1.6 Classification of genotypes

There have been 6 major HCV genotypes identified (genotype 1-6). Certain

genotypes are known to be more pathogenic and the success rate of IFN/Ribavirin

therapy is dependent on the genotype. Figure 1.4 depicts the global distribution of

HCV genotypes. As mentioned previously, genotype 1 is the predominant genotype in

the western world and infected patients show only a 50% success rate with IFN

therapy. Genotype 1 infected patients also require longer treatment periods to obtain

a SVR. In contrast, patients infected with genotypes 2 and 3 show a 80% success rate

with IFN-α treatment. Successful treatment outcomes for genotype 4 range between

55-69%. It is not well documented how genotypes 5 and 6 respond to antiviral

treatment as they are less common, however, response rates appear to be similar to

genotypes 1 and 4.

1.1.7 HCV proteins

As previously mentioned the HCV polyprotein is cleaved by host and viral proteases

to produce 10 proteins, three structural proteins (core, E1 and E2), the small

hydrophobic protein p7 and the six non-structural proteins (NS2, NS3, NS4A, NS4B,

NS5A and NS5B).

Core

The HCV core protein is located at the N-terminus of the polyprotein. The mature

core protein (22kDa) interacts with HCV RNA and forms the viral nucleocapsid in

which the HCV genome is packaged (McLauchlan et al. 2002). Core has been

demonstrated to localize to the ER and associate with cytoplasmic lipid droplets

(Rouille et al. 2006; Miyanari et al. 2007). While it would appear that the main role of

core is structural, it has been documented that core may play a pivotal role in the

pathogenesis of HCV via disturbing cellular functions (McLauchlan 2009). Core has

been shown to inhibit TNF-α mediated apoptosis and activate NF-κB mediated gene

transcription (Dansako et al. 2005). The core protein has also been sited as potentially

Figure 1.4 Global HCV genotype distribution. Genotypes 1-3 have a worldwide distribution. Types 1a and 1b are the most common, accounting for about 60% of global infections. They predominate in Northern Europe and North America, and in Southern and Eastern Europe and Japan, respectively. Type 2 is less frequently represented than type 1. Type 3 is endemic in south-east Asia and is variably distributed in different countries. Genotype 4 is principally found in the Middle East, Egypt, and central Africa. Type 5 is almost exclusively found in South Africa, and genotypes 6-11 are distributed in Asia.

1a,1b,3a

3a,6a

1a,3a

1b,2a

1b,6a1b2a

3a

5a,1b

4

4 4

1b,2b,3a

1a,1b,3a

1a,1b,2b

1,2

7

playing a role in the oncogenesis of HCC (de Lucas et al. 2005). Furthermore, core

has been shown to disrupt host immune responses via inhibition of the nuclear import

of STAT1 and subsequently decreasing the expression of the anti-viral protein MxA

(Melen et al. 2004). However, many of these studies involved the expression of core

in the absence of the other HCV proteins and thus these results should be interpreted

with caution.

Envelope glycoproteins E1/E2

The envelope glycoproteins E1/E2 are type 1 transmembrane proteins that are heavily

glycosylated (Goffard and Dubuisson 2003). They form a heterodimer and are the

major constituents of the virus particle surface (Lin et al. 1994), subsequently E1/E2

mediate the binding of the HCV virion to target cell surfaces and thus are essential for

cellular entry of HCV (Bartosch et al. 2003; Hsu et al. 2003; Wakita et al. 2005) .

P7

P7 is a small hydrophobic protein that localizes to the endoplasmic reticulum

(Haqshenas et al. 2007). Current literature suggests P7 is essential for replication,

however, the exact stage at which P7 facilitates replication is yet to be described. P7

has also been described as a viroporin; a viral cation channel that allows calcium ions

to flow from the endoplasmic reticulum into the cytoplasm (Griffin et al. 2003). It

remains to be established if P7 is incorporated into virions.

NS2

NS2 is cleaved from NS3 by a cis-acting protease that is localized within the carboxy

terminal of NS2 and the amino terminal of NS3 (Selby et al. 1994). The cellular

chaperone HSP90 interacts with NS2 and may be a co-factor necessary for cis

cleavage (Waxman et al. 2001). Recent data suggests that NS2 plays a role in viral

assembly with p7, NS2 and E2 interacting to form a functional unit, capable of

driving proteins in the vicinity of lipid droplets. As such, NS2 is thought to act as a

mediator between the structural and non-structural viral proteins during the assembly

process (Popescu et al. 2011).

8

NS3

NS3 is a multifunctional protein with the N-terminus encoding the serine protease and

C-terminus encoding the viral helicase. The serine protease function is responsible for

the proteolytic cleavage of all downstream non-structural proteins. While NS3 has

protease capabilities, NS3’s activity is greatly enhanced by its interaction with NS4A.

This interaction allows NS4A to act as a co-factor to stabilise the protease, allowing

correct alignment of the enzyme and thus enabling efficient proteolytic cleavage. The

C-terminus of NS3 acts as an ATP-dependent RNA helicase that unwinds the RNA

duplexes that form during HCV genome replication (Tai et al. 1996).

NS4A

As mentioned above, NS4A plays an important role in HCV replication as it enhances

the catalytic activity of NS3 via anchoring the NS3/4A complex to the plasma

membrane through its n-terminal transmembrane domain. The NS3/4A complex has

also been shown to inhibit the phosphorylation of IRF-3, an integral innate anti-viral

signaling molecule (Foy et al. 2003; Foy et al. 2005). This is directly mediated via

NS3/4A cleavage of IPS-1 from the mitochondrial membrane, which results in loss of

an interaction between IPS-1 and RIG-I and subsequent inhibition of IRF-3

phosphorylation, which leads to a blockage of IFN-β production (Loo et al. 2006).

This process is potentially one of the ways HCV is able to evade the innate immune

response and achieve viral persistence.

NS4B

The highly hydrophobic NS4B is a transmembrane protein thought to alter

intracellular membranes of the ER to initiate formation of a replication complex

(membranous web) in the cytoplasm, in which HCV replication takes place (Gosert et

al. 2003). NS4B has also been shown to be capable of GTP hydrolysis (Einav et al.

2004), and disruption of NS4Bs GTPase activity, results in significant reductions in

HCV replication.

9

NS5A

NS5A appears to play multiple roles in HCV replication. It is a membrane-bound

phosphoprotein that is phosphorylated at serine residues and the phosphorylation

status of NS5A appears to affect the level of HCV replication. Reductions in

hyperphosphorylation of NS5A appear to increase HCV replication significantly

(Appel et al. 2006) and it is thought that perhaps hyperphosphorylation of NS5A

might cause a switch from replication of the HCV genome to translation of viral

proteins. Serine phosphorylation of NS5A also appears to play a role in the ability of

NS5A to interact with core, which has been shown to be crucial for production of

infectious viral particles at the lipid droplet interface (Masaki et al. 2008). Currently

NS5A is thought to be vital in assisting the transfer of viral RNA to core for

packaging of infectious HCV virions (Jones and McLauchlan 2010).

NS5B

NS5B is an RNA-dependent RNA polymerase (RdRp) that is able to initiate de novo

RNA synthesis of positive and negative strand RNA (Lohmann et al. 2000). NS5B is

anchored to the ER membrane via its transmembrane domain.

1.1.8 HCV life cycle

Using cell culture models and analogous flaviviruses models, a general picture of the

HCV lifecycle has been constructed. In circulation HCV virions associate with low-

and very-low-density lipoproteins (LP) to form lipoviralparticles (VLP’s) (Nielsen et

al. 2006). HCV entry into hepatocytes is thought to occur via HCV particles

associating with low density lipoprotein receptors (LDLR) and glycoaminoglycans

(GAG), followed by the envelope glycoproteins E1/E2 interacting with a number of

receptors such as, CD81, SR-B1, claudin-1 and occludin. After binding has occurred,

the virion is internalized via receptor-medicated endocytosis into a clathrin-coated pit.

Acidification of the endosome results in release of the viral genome into the

cytoplasm [Figure 1.5 (Eyre et al. 2009)].

Figure 1.5 Model of HCV entry (Eyre et al. 2009)

10

HCV proteins are directly translated from the positive sense RNA genome, with the

large HCV polyprotein cleaved by host proteases to produce the structural proteins

(core, E1, E2 and p7) and the non-structural proteins cleaved by viral proteases to

liberate (NS2, NS3, NS4A, NS4B, NS5A and NS5B). The alteration of ER

membranes allows the formation of a membranous web that contains the replication

complex (RC). RC’s contain non-structural proteins, viral RNA and a number of

cellular factors (Gosert et al. 2003). NS5B initiates de novo synthesis of negative

strand RNA, which serves as a template for the synthesis of multiple copies of the

HCV genome. A proportion of the new HCV genomes act as templates for viral

protein translation, while some of them also associate with the core protein to form

the nucleocapsid. Recently a model of virion assembly has been described (Jones and

McLauchlan 2010). It is thought that assembly of HCV virions occurs on the

cytostolic side of the ER and complete maturation occurs in the ER lumen. It is

thought that during the early steps of assembly RC’s are recruited to the lipid droplets

via an interaction with core and NS5A and this interaction allows newly replicated

RNA to be transferred from RC’s to interact with core to allow encapsidation of the

genome. Late assembly involves the acquisition of a lipid envelope and the

incorporation of E1 and E2 (Jones and McLauchlan 2010), mature virions then exit

the cell via exocytosis (Figure 1.6).

1.1.9 HCV model systems

The study of HCV replication and pathogenesis has been severely inhibited in the past

due to the lack of a suitable small animal model and a permissive cell line in which to

propagate the virus. The only animal model available is the chimpanzee, which has

obvious financial and ethical limitations, thus limiting its use in the majority of

research laboratories. However, the development of the HCV sub-genomic replicon

system in 1999 (Lohmann et al. 1999), the genomic replicon system (Ikeda et al.

Figure 1.6 Life cycle of HCV (a) Virus binding and internalization (b) IRES-mediated translation, and polyprotein processing (c) RNA replication (d) Packaging and assembly (e) Virion maturation and (f) Virion release. (Moradpour D, Penin F, et al. 2007)

NOTE:

This figure is included in the print copy of the thesis held in the University of Adelaide Library.

11

2002) in 2002 and more recently in 2005 (Wakita et al. 2005) the development of

infectious cell culture system has lead to great advancements in HCV research.

1.1.9.1 Animal models

The chimpanzee model has played an important role in HCV research and was

instrumental in the initial characterization and cloning of the virus. In 1997 HCV

genomic transcripts were synthesized from a HCV infected individual and used to

inoculate chimpanzees. This was the first study to show that HCV was the causative

agent of hepatitis C induced liver disease (Choo et al. 1989). These chimpanzees

developed acute hepatitis and in a few cases chronic liver disease (Kolykhalov et al.

1997). Since that time the chimpanzee has played a significant role in helping us

understand HCV pathogenesis and the host response to viral infection (Boonstra et al.

2009).

1.1.9.2 Cell culture systems

The HCV replicon system consists of the human hematoma cell line (Huh-7)

autonomously replicating high levels of HCV RNA, thus providing an excellent tool

for in vitro studies of HCV replication and hepatocyte interactions (Figure 1.7A).

However, the limitation of this system is that it does not produce infectious HCV

virions. The HCV sub-genomic replicon was constructed from HCV RNA isolated

from the liver of an individual infected with HCV genotype 1a and subsequent

cloning of HCV cDNA (Lohmann et al. 1999). In contrast, the genomic replicons

were produced through the introduction of a neomycin sensitivity cassette into the 5’

end of the HCV ORF, with the HCV IRES then driving expression of neomycin

(Figure 1.8). The expression of the structural and non-structural proteins is driven by

the Encephalomyocarditis virus (EMCV) IRES. In the case of the sub-genomic

replicons the EMCV IRES drives expression of the non-structural proteins. HCV

replicon cell lines are then produced by transfection of RNA that is produced in vitro

Figure 1.7 HCV model systems (Tellinghuisen et al. 2007)

NOTE: This figure is included in the print copy of the thesis held in the University of Adelaide Library.

Characterisation

Figure 1.8 Construction of HCV genomic replicon (Ikeda et al. 2002)

NOTE: This figure is included in the print copy of the thesis held in the University of Adelaide Library.

12

from these constructs via the T7 promoter (Figure 1.8). This is followed by the

isolation of Neomycin resistant clones which are subsequently characterised, giving

rise to replicon cell lines that are capable of efficient and autonomous HCV

replication with little to no cytopathic effect on cells (Ikeda et al. 2002). While the

genomic replicon cell lines have proved to be a very valuable tool to study HCV, this

system does not produce infectious virus particles for reasons that are not readily

apparent. Hence the replicon system does not allow the full life cycle of HCV to be

studied. Significant advances have been made in our understanding of the molecular

biology of the interactions between HCV and the hepatocyte using the replicon model

system.

1.1.9.3 Infectious cell culture model

The main limitation of the replicon system (described in 1.1.9.2) was largely

overcome in 2005 with the development of the JFH-1 infectious cell culture system

(genotype 2a) (Figure 1.7B & Appendix II) (Lindenbach et al. 2005; Wakita et al.

2005; Zhong et al. 2005). HCV cDNA (JFH-1) was isolated from a patient with

fulminant hepatitis and in vitro transcription was performed to produce HCV RNA

that was subsequently transfected into Huh-7 cells. This enables the initiation of viral

replication and the production of infectious virus particles, without the need for cell

culture adapted mutations. Virus particles from cell culture derived HCV JFH-1

(HCVcc) can be passaged in vitro and are also infectious in chimpanzees (Wakita et

al. 2005). This JFH-1 system represents a major breakthrough in the field of HCV

research and allows for comprehensive studies of virus-host interactions and the

recapitulation of the full life cycle of HCV.

1.2 Alcohol and HCV

There are numerous clinical studies suggesting a strong epidemiological link between

the consumption of alcohol and an increased susceptibility to infectious diseases, with

13

HCV being no exception. The majority of alcohol metabolism takes place in

hepatocytes, which is also the primary site of HCV replication in the liver. Hence the

link between worsening HCV disease progression and alcohol consumption has

warranted significant investigation (Poynard et al. 1997; Pessione et al. 1998;

Bellentani et al. 1999; Bhattacharya and Shuhart 2003; Safdar and Schiff 2004;

Anand and Thornby 2005; Anand et al. 2006). The majority of these studies

concluded that HCV infected individuals that consume alcohol show a strong

propensity for accelerated liver disease. In fact, excessive alcohol consumption is now

a recognized co-factor in HCV related liver disease progression and persons infected

with HCV are recommended to limit their alcohol intake (Peters and Terrault 2002).

Despite this strong clinical evidence, the molecular mechanisms by which alcohol

consumption exacerbates liver disease in the setting of HCV infection, remains

unclear. Furthermore, the interactions between alcohol metabolism, HCV and the host

anti-viral immune response are also unknown. Clearly, the relationship between

alcohol and HCV is complex and the mechanisms responsible for accelerated disease

progression are most likely not related to a single factor but are the result of

alterations to hepatocyte homeostasis, production of cytokines and modification of the

immune system.

One of the first reports in the literature documenting the role of alcohol consumption

on CHC progression was published by Seeff et al, in which it was reported that two

thirds of individuals that died from end stage liver disease in a large cohort of HCV

positive patients, were chronic consumers of alcohol (Seeff et al. 1992). Poynard and

colleagues extended this study, showing that the consumption of 50g/day of alcohol

increases the rate at which fibrosis progresses in HCV infected individuals (Poynard

et al. 1997). They also identified two other independent risk factors that were

associated with increased rates of fibrosis: age greater than 40 years at time of

infection and being male. At the virological level, it has been documented that there is

a direct dose dependent correlation between increasing HCV RNA levels and

14

increasing levels of alcohol consumption (Pessione et al. 1998). The mechanism for

this increase was not established but it was postulated that the increase in HCV RNA

could be due to a direct effect of alcohol increasing viral replication or through

reduced clearance of the virus by the immune system. One of the most comprehensive

studies investigating the effect of alcohol on HCV disease progression was performed

by Corrao et al, in which they studied a large cohort of 417 patients. The most

striking finding of this study was a comparison of the associated risk factors for

developing cirrhosis between HCV infected patients that abused alcohol and those

patients that abstained. The risk factor for developing cirrhosis in patients that were

HCV positive but did not consume alcohol was 9, compared to a significantly higher

risk factor of 147 for those patients that abused alcohol (Corrao and Arico 1998).

This study adds further weight to our hypothesis that HCV and alcohol metabolism

synergistically contribute to exacerbated liver disease. There have also been a number

of studies that have documented a clear link between excessive alcohol consumption

and an increased risk of HCC development. It has been suggested that HCV infected

individuals that consume alcohol show a 100-fold increase in their risk of developing

HCC (Aizawa et al. 2000). Clearly, chronic consumption of alcohol in HCV infected

individuals is a dangerous mix, with significant clinical implications.

The mechanisms by which alcohol consumption exacerbates CHC are not well

understood. There have been a number of postulated mechanisms such as - (i) an

alcohol-induced increase in HCV RNA replication, (ii) enhancement of HCV

quasispecies complexity, leading to immune escape, (iii) modulation of the innate and

adaptive immune system and (iv) synergistic increase in reactive oxygen species

(ROS).

Clinical data indicates that there is an increase in HCV viral load in patients that

consume alcohol (Oshita et al. 1994; Pessione et al. 1998). Moreover, during chronic

alcohol consumption there is an increase in hepatocyte cell death due to deregulation

15

of inflammatory and immunoregulatory networks, hepatic iron load and fatty liver

accumulation (Nguyen and Gao 2002). Thus the combination of increased viral load

and alcohol related liver damage could potentially contribute to increased rates of

fibrosis and cirrhosis development. However, the molecular mechanisms responsible

for the accelerated rates of liver disease in CHC patients that consume alcohol are not

well understood.

There are limited in vitro investigations looking into the effects of alcohol metabolism

on HCV replication. Furthermore, there are a number of concerns with the model

system used in these studies. The HCV replicon model system utilized in these

investigations, do not appear to express any alcohol metabolizing enzymes. Thus

these studies are not investigating the direct effects of metabolised alcohol on HCV

replication (Zhang et al. 2003; Trujillo-Murillo et al. 2007). As such there is a

significant need for a better model system to be created.

1.3 Alcohol Metabolism

Alcohol is absorbed from the gastrointestinal tract and transported to the liver via

blood flow. As alcohol is a toxic drug and cannot be stored, it becomes oxidized in

the liver in order to facilitate its removal. The first step of alcohol metabolism is the

oxidation of ethanol to acetaldehyde, which is then further oxidized to acetic acid and

then finally CO2 and water via the citric acid cycle.

There are 2 main oxidative pathways of alcohol metabolism in the liver - (i) alcohol

dehydrogenase pathway (ADH) and (ii) microsomal ethanol-oxidizing system

(MEOS). These 2 pathways of alcohol metabolism are outlined in Figure 1.9. While

the majority of alcohol in the liver is metabolized by ADH, the MEOS pathway plays

a more important role in the metabolism of alcohol when consumption levels are

chronic, a situation pertinent to the many individuals chronically infected with HCV

Figure 1.9 Pathways of alcohol metabolism

16

and chronically abusing alcohol (Lieber 2004). As the model system designed in this

thesis is one of chronic alcohol consumption, the MEOS pathway forms the main

focus of this study. In both alcohol metabolizing pathways, alcohol is broken down

into the highly reactive molecule acetaldehyde and nicotinamide adenine dinucleotide

(NAD+) is reduced to NADH, which results in significant change in the ratios of

NAD/NADH. This change in the redox state of the cell is thought to be responsible

for many of the metabolic effects that alcohol induces (Lieber 1999). Acetaldehyde is

then rapidly metabolized into acetate. A by-product of alcohol metabolism is the

production of ROS that will be further discussed in the next section 1.4.

1.3.1 Cytochrome P4502E1

The enzyme responsible for converting ethanol to acetaldehyde in the MEOS pathway

is cytochrome P4502E1 (CYP2E1). The cytochrome P450 enzymes are a superfamily

of hemeproteins that metabolise a variety of xenobiotics and endogenous substrates.

CYP2E1 is expressed predominantly in hepatocytes, however, detectable levels of

CYP2E1 have been found in Kupffer cells (Robin et al. 1995). CYP2E1 expression in

hepatocytes is mainly within microsomes, which are small sphere shaped vesicles that

split off from the endoplasmic reticulum. CYP2E1 is able to metabolize other

substrates aside from alcohol such as carbon tetrachloride and acetaminophen.

It has been extensively documented that chronic alcohol consumption induces

expression of CYP2E1. Using the intragastric infusion model in rats, ethanol doses of

>65mM were shown to induce CYP2E1 transcription (Ronis et al. 1993) and

CYP2E1 levels have been shown to be increased 4-10 fold in liver biopsies of patients

that have been recently consuming alcohol (Lieber 2000). Thus alcohol is both a

substrate and an inducer of CYP2E1 and alcohol induced liver damage has been

shown to correlate with increased CYP2E1 levels (Nanji et al. 1994; Morimoto et al.

17

1995). Furthermore, CYP2E1 plays a more significant role in alcohol metabolism

when consumption levels are chronic.

1.4 Oxidative Stress

1.4.1 Oxidative stress and alcohol

ROS are defined as small highly reactive oxygen-containing molecules that cause

oxidative stress when the rate at which they are produced is greater than the rate at

which they are removed, leading to a disturbance in the pro-oxidant/anti-oxidant

balance. Metabolism of alcohol by CYP2E1 results in the production of several ROS

and while metabolism of alcohol by ADH does produce ROS, CYP2E1 mediated

metabolism of alcohol produces levels of ROS that far exceed that of ADH mediated

ROS production. Alcohol metabolism not only directly produces ROS but it also

creates an environment that is favorable for oxidative stress.

CYP2E1 mediated metabolism of alcohol stimulates the microsomal production of

ROS such as superoxide anions (O2.-), hydroxyl radicals (.OH), 1-hydroxyethyl

radicals (CH3C.HOH), lipid hydroperoxides (LOOH) and when iron levels increase

due to alcohol metabolism, ferryl radicals (FeO) are produced (Cederbaum et al.

2001).

At low concentrations ROS are actually positive mediators of the innate immune

system. However, when levels of alcohol consumption are chronic and ROS levels

increase and the various anti-oxidant mechanisms exerted by the cell are

overwhelmed, thus becoming ineffective, ROS are no longer beneficial to the liver

and contribute to liver damage. Oxidative stress can potentially lead to cellular

damage that can then play a role in a variety of pathological conditions (Caro and

Cederbaum 2004). Both chronic and acute consumption of alcohol has been shown to

increase ROS. Recently, using the intragastric feeding model, there has been strong

18

evidence to suggest that ROS play a direct role in alcohol induced liver disease as the

administration of anti-oxidants such as vitamin E, ebselen, super oxide dismutase and

GSH can prevent alcohol induced liver damage (Iimuro et al. 2000; Arteel 2003).

1.4.2 Oxidative stress and HCV

The generation of hepatic oxidative stress in CHC is now well established and most

likely a consequence of HCV protein disrupting mitochondrial and hepatocyte

organelle function, in addition to the inflammatory response directed towards HCV

infected hepatocytes. Under normal conditions, oxidative stress exists in a state of

equilibrium with cellular antioxidants that scavenge ROS and prevent cellular injury.

However, when cellular antioxidant mechanisms are overwhelmed through chronic

oxidative stress or disease processes, oxidative stress production continues

unchecked, with pathological consequences.

While clinical studies have suggested that markers of oxidative stress are increased in

CHC, it was the development of mice transgenic for the HCV core protein that clearly

demonstrated that HCV directly induces a state of oxidative stress (Moriya et al.

2001). In these studies, mice expressing either the HCV core or the complete HCV

polyprotein, developed pathologies consistent with those observed in human HCV

infection such as steatosis and HCC development (Moriya et al. 2001; Lerat et al.

2002). Prior to HCC development, the HCV core expressing mice showed a marked

increase in lipid peroxidation and activation of the antioxidant system, suggesting the

expression of HCV core is sufficient to induce oxidative stress in the mouse liver and

initiate HCC through DNA damage and the modulation of signaling cascades (Moriya

et al. 2001). It was subsequently shown in vitro, that HCV core expression results in

increased generation of ROS and expression of antioxidant enzymes (Li et al. 2002;

Okuda et al. 2002; Abdalla et al. 2005). Mechanistically, it was demonstrated that this

increase in oxidative stress was due to interactions between HCV core and

19

destabilization of the mitochondrial electron transport chain and that this was further

enhanced in the presence of alcohol (Korenaga et al. 2005; Otani et al. 2005).

In addition to the HCV core protein, the HCV nonstructural protein NS5A has also

been demonstrated to increase cellular ROS, albeit through a different mechanism to

that of the HCV core protein. HCV NS5A localizes to the ER and lipid droplets, and

is part of the HCV replication complex that is formed from altered cytoplasmic

membrane structures. It has been suggested that this change in membrane structure

results in ER stress and the unfolded protein response, leading to the release of ER

Ca2+ stores and resulting in the formation of oxidative stress (Tardif et al. 2005).

Furthermore, it has been demonstrated that oxidative stress mediated NS5A-induced

transcriptional activation can be blocked by the treatment of cells with the free radical

scavenges pyrrolidine-2,4-dicarboxylate acid and N-acetyl-cysteine (NAC) (Gong et

al. 2001). However, these studies should be interpreted with caution, as they are

reliant on ectopic over-expression of HCV proteins in the absence of the complete

repertoire of the HCV proteins and RNA replication. Furthermore, Huh-7 cells

harbouring the HCV replicon do induce a state of oxidative stress (Qadri et al. 2004;

McCartney et al. 2008). Thus it is logical to hypothesise that HCV replication and

alcohol metabolism lead to the synergistic increase in hepatic oxidative stress, which

then contributes to accelerated liver disease.

1.5 ROS Induced Liver Damage

ROS are thought to induce liver damage via a number of mechanisms – (i) lipid

peroxidation, (ii) increased collagen production, (iii) damage to mitochondria, (iv)

decreased anti-oxidant expression, (v) DNA damage and (vi) activation of

transcription factors. These mechanisms of ROS induced liver damage are outlined

below.

20

i. Lipid peroxidation and protein adducts

Also generated during alcohol metabolism are two other aldehydes: the lipid

peroxidation products, malondialdehyde (MDA) and 4-hydroxnonenal (4-HNE).

Along with acetaldehyde, they can interact with proteins and other molecules to form

adducts, which are hybrid compounds. Protein adducts can be toxic because they

result in loss of function of the protein and because they can be immunogenic. Mixed

MDA-acetaldehyde-protein adducts (MAA) have been shown to induce alterations in

Ig production, T-cell activation, cytokine and chemokine production and are thus pro-

inflammatory and pro-fibrogenic (Viitala, (Viitala et al. 2000). Lipid peroxidation is

known to be a contributing factor in alcohol induced liver disease, as it inflicts

damage on cellular membranes.

ii. Increased collagen production

Collagen synthesis by hepatic stellate cells is a significant factor in the fibrogenic

process. Investigations by Neto et al demonstrated that ROS produced by CYP2E1

are able to increase collagen production in hepatic stellate cells. This was shown via

the co-incubation of HEPG2 cells line expressing CYP2E1 (E47 cells) with hepatic

stellate cells and documenting that the ROS released by the E47 cells acted on

neighbouring stellate cells to stimulate type I collagen production (Nieto et al. 2002b;

Nieto et al. 2002a). Hence, the current consensus in the literature is that ROS

produced in hepatocytes contribute to liver disease via the stimulation of collagen

production, the consequence of which is a markedly accelerated fibrotic response.

Given that HCV replication in vitro and in vivo can induce ROS production, it is not

inconceivable to envisage that the synergistic increase in ROS from HCV and alcohol

may be a significant factor in accelerating liver disease.

iii. Mitochondrial damage and decreased ATP production

One of the major ways ROS appear to cause liver injury is by damaging

mitochondria. This damage can occur by a variety of means - i) a reduction in

mitochondrial membrane potential (Δψm), ii) opening of the mitochondrial

permeability pore, iii) reductions in adenosine triphosphate (ATP) production, which

21

can result in necrotic death of cells and iv) stimulating the release of pro-apoptotic

factors such as cytochrome c, caspase 9 and 3 that can result in apoptotic cell death

(Bailey et al. 2001). The reduction of ATP production in the presence of ROS has

been shown experimentally in E47 cells described above. E47 cells show a 40-50%

increase in the production of intracellular ROS, as assayed by the oxidation of

dichlorofluorescein diacetate and ROS induced mitochondrial damage was

demonstrated to reduce ATP levels by 30% reduction (Mari and Cederbaum 2000).

In terms of HCV induction of ROS, it has been documented that the ectopic

expression of HCV core protein increases oxidative stress via destablisation of the

mitochondrial electron transport chain, and this effect can be further enhanced in the

presence of alcohol metabolism (Korenaga et al. 2005; Otani et al. 2005).

iv. Decreased anti-oxidants

Chronic alcohol treatment has been shown to lower levels of the anti-oxidant

glutathione (GSH), which is a scavenger of ROS, particularly in hepatic

mitochondria. It is known that a decrease in GSH levels induces significant

impairment of mitochondria. It has also been suggested that decreased GSH sensitizes

hepatocytes to TNF-α induced cell death, as treatment of alcohol fed rats with S-

adenosylmethionine replenishes GSH and protects hepatocytes from the toxicity

induced by TNF-α (Bailey et al. 2001). Alcohol metabolism can therefore disturb the

balance between pro-oxidants and anti-oxidants and thus induce oxidative stress in the

cell. This increased oxidative stress can damage fats, proteins, DNA and ultimately

cause cellular injury.

v. DNA Damage

As well as being able to damage proteins and lipids, ROS are also able to damage

nucleic acids. Hydroxyl radicals have been shown to cause a large number of

pyrimidine and purine derived lesions in DNA (Dizdaroglu 1992) and in vivo and in

vitro studies have shown that ethanol induced OS can cause DNA damage (Blasiak et

al. 2000; Guo et al. 2008). This may in part account for the increased rates of HCC in

CHC patients that consume alcohol.

22

vi. ROS activation of transcription factors

ROS have the ability to act as potent second messengers and activate cellular

transcription factors. It has been documented that ROS can activate STAT3, NF-κB,

NF-AT and AP-1 (Carballo et al. 1999; Gong et al. 2001). The role of these activated

signal transduction molecules in liver pathogenesis remains unclear. However, the

importance of ROS induction of STAT3 in the context of both HCV replication and

liver pathogenesis was investigated during the course of this study and will be

discussed in greater detail in section 1.8.

1.6 Interferon

Interferons (IFNs) are a family of inducible cytokines most commonly known for

their antiviral activity, however, they are also responsible for the regulation of a

diverse number of biological functions, which can be categorised broadly under

antiviral activity, antitumor activity and immune modulation (Katze et al. 2002). All

members of the IFN family demonstrate ligand interaction with specific receptor

subunits and the activation of the JAK-STAT signaling pathway. The activation of

this pathway results in the production of hundreds to thousands of different effector

molecules that exert various biological effects, highlighting the highly pleiotropic

nature of IFNs (Der et al. 1998).

IFNs can be divided into three types based upon their structural and functional

properties (Table 1.1). The type I IFNs consist of IFN-α, IFN-β, IFN-δ, IFN-ε, IFN-

ω, IFN-κ, IFN-τ, and IFN-ζ. Type II IFNs consist solely of IFN-γ and type III IFNs

include IFN-λ1, IFN-λ2 IFN-λ3.

IFN-α and IFN-β interact with the receptor complex termed the type I IFN receptor

(IFNAR) that consists of two subunits IFNAR-1 and IFNAR-2 (Figure 1.10). The

binding of IFN α/β to their cognate receptors results in rapid autophosphorylation and

Figure 1.10 IFN-α signal transduction pathway

23

activation of receptor associated Janus activated kinases (JAKs), TYK2 and JAK1

(Silvennoinen et al. 1993). TYK2 and JAK1 phosphorylate tyrosine residues on the

cytoplasmic tail of the receptor, providing docking sites for the signal transducer and

activator of transcription (STATs). STATs are latent cytoplasmic transcription factors

that transduce signals from the cell surface to the nucleus. Once in the nucleus,

STATs are able to directly regulate gene transcription. In the case of IFN-α signal

transduction, STAT1 and STAT2 bind to the receptor and via their SH2 domains and

are phosphorylated by TYK2 and JAK1. STAT1 is then phosphorylated at tyrosine

residue 701 (Y701) and STAT2 at tyrosine residue 690 (Y690). Once phosphorylated

STAT1 and STAT2 then form active heterodimers and translocate to the nucleus

where they directly activate transcription. This process is facilitated by the formation

of the multi component transcription factor ISG factor 3 (ISGF3), which is a complex

comprised of STAT1/STAT2 and the interferon regulatory factor 9 (IRF9). Within the

nucleus, STAT1 is then further phosphorylated on a serine residue 727 (S727). This

phosphorylation event results in an increase in the transcriptional activation ability of

ISGF3. The end step of this signaling cascade is ISGF3 directly activating gene

transcription via binding to the IFN stimulated response element (ISRE), which is a

cis-acting DNA element found in the promoter of the majority of type I IFN genes.

1.6.1 Effect of alcohol on IFN-α efficacy

IFN-α2b administered to HCV patients (as part of current therapeutic regimes),

results in the binding of IFN to its cognate receptor on target cells and subsequent

activation of the JAK/STAT signaling cascade. As outlined above, the activation of

this pathway culminates in the transcriptional activation of hundreds of interferon

stimulated genes (ISGs) that produce antiviral proteins capable of limiting HCV

replication in hepatocytes and modulating the immune response. It is well established

clinically that alcohol consumption reduces the efficacy of IFN treatment, thus

making alcohol consumption a contraindication to IFN treatment (Safdar and Schiff

24

2004). There have been numerous studies confirming that alcoholics do not respond

well to IFN-α therapy. Mochida et al documented that less than 10% of alcoholic

patients respond to IFN-α therapy (Mochida et al. 1996). Furthermore, Loguercio et

al have shown a direct relationship between alcohol consumption and response to

treatment, with the numbers of patients achieving a SVR decreasing as alcohol

consumption increased (Loguercio et al. 2000). Finally, it was the study by Safdar et

al that showed that alcohol abuse decreases response to IFN treatment in HCV

patients and therefore recommended that HCV infected patients abstain from alcohol

consumption while on treatment (Safdar and Schiff 2004). These studies have

implications not only for IFN-α as part of a treatment strategy, but also for the

activity of endogenously produced type I and II IFN’s (IFNα, β and γ respectively), as

alcohol consumption will no doubt result in a weakened host response to an initial

infection.

The molecular basis that underlies the reduced anti-viral capacity of IFN-α in the

presence of alcohol metabolism remains to be established. One of the aims of this

body of work has been to correlate known clinical observations with in vitro data and

attempt to unravel the complex interactions between the hepatocyte, HCV and

alcohol. Maintaining the integrity of this pathway is vital for IFN-α to exert its anti-

viral capabilities via the production of ISGs. Previous investigations into the effects of

alcohol metabolism on the IFN signal transduction pathway remain controversial and

there appears to be a large disparity between studies performed. This could be due in

part to the myriad of different cell culture systems and treatments being used in the

various studies. As such there are many conflicting results in the literature and when

replicating HCV is incorporated into these studies, results become even more

confounding as HCV proteins have been documented to perturb JAK/STAT signaling.

25

1.6.2 Effect of HCV and alcohol on IFN signaling

There have been a number of studies reporting that certain HCV proteins are capable

of disrupting IFN signaling. The majority of these studies concluded that HCV can

decrease in STAT1 phosphorylation and implicate HCV proteins (Core and NS5A) as

the mediators of this decrease in STAT1 activation (Heim et al. 1999; Blindenbacher

et al. 2003; Melen et al. 2004; Lin et al. 2005; Osna et al. 2005; Lin et al. 2006;

McCartney et al. 2008). Also implicated is a cellular protein which plays a role in

feedback inhibition of the JAK/STAT signaling cascade, suppressor of cytokine

signaling 3 (SOCS3) has been documented as the causative molecule for the observed

decrease in STAT1 activation (Alexander 2002; Hong et al. 2002). HCV mediated

perturbation of JAK/STAT was shown by Melen et al, as this study demonstrated that

HCV core has the ability to inhibit the nuclear import of STAT1 and thus decrease

expression of the anti-viral protein MxA (Melen et al. 2004). Lin et al depicted that a

decrease in STAT1 phosphorylation was due to HCV core protein specifically

interacting with the SH-2 domain of STAT1 and thus preventing hetero- or

homodimerization (Lin et al. 2006) and also showed that HCV core could directly

target activated STAT1 for proteasomal degradation (Lin et al. 2005). Furthermore, it

has been shown HCV genomic replicon cells have decreased levels of tyrosine

phosphorylation for STAT1, STAT2 and STAT3 (Larrea et al. 2006), implying that

replicating HCV disrupts a number of key signal transduction molecules. Heim et al

have demonstrated that HCV induces the expression of protein phosphatase 2Ac

(PP2Ac), a protein that negatively regulates IFN-α signaling via inhibiting the

methylation of STAT1. Unmethylated STAT1 is bound by a protein inhibitor of

activated STAT1 (PIAS1), which renders STAT1 incapable of driving ISG expression

(Mowen et al. 2001; Duong et al. 2004; Liu et al. 2004). In terms of the initial

response to HCV infection, IFN-β production is the hepatocytes first line of defence

against a viral infection and IFN-β is also able to activate IFN-α production, through

both autocrine and paracrine activation of the JAK/STAT signaling pathway. Foy et

al demonstrated eloquently that NS3/4A disrupts IFN-β production in response to

26

virus infection, via interference with a signaling adaptor molecule IPS-1, that is part

of the RIG-I double stranded RNA signaling pathway (Foy et al. 2003; Foy et al.

2005). Collectively, these studies show that HCV has evolved mechanisms to evade

the innate immune system, something that may contribute to chronic HCV infection.

As outlined above, there are a number of studies investigating the effects of HCV on

IFN signaling, however, there are a limited number of studies investigating the

combined effects of HCV and alcohol metabolism on IFN-α signaling. Insights into

the effect of alcohol metabolism on IFN-α signaling can be gleaned from the study

conducted by Osna et al, in which the effects of alcohol metabolism by ADH and

CYP2E1 on IFN-γ signal transduction were investigated. This study documented a

decrease in STAT1 tyrosine phosphorylation in the presence of alcohol metabolism

(Osna et al. 2005). To date, the most comprehensive study looking at the effects of

alcohol and HCV on IFN signaling was conducted by Plumlee et al. This study

demonstrated that acute treatment of HCV genomic replicon cells with ethanol lead to

the inhibition of the anti-HCV effects of IFN and interestingly, caused a decrease in

STAT1 tyrosine phosphorylation but induced STAT1 serine phosphorylation

(Plumlee et al. 2005). As one of the hypothesis of this thesis is that alcohol

metabolism disrupts the JAK/STAT signaling cascade via oxidative stress, it is

worthwhile noting that oxidative stress generated via treatment of Huh-7 cells with

H2O2 treatment, causes disruption of the JAK-STAT signaling pathway, specifically

by blocking STAT1, STAT2, JAK1 and TYK2 tyrosine phosphorylation (Di Bona et

al. 2006).

While all of the aforementioned studies offer valuable insights into the effects of

alcohol metabolism and HCV replication on JAK/STAT signaling and IFN-α

efficacy, there is no definitive study that investigates the combined effects of alcohol

metabolism on HCV replication and IFN-α signaling as such, this body of work will

add significant data to this area of research.

27

1.7 Cellular Factors Involved In HCV Life Cycle

There have been numerous host cellular factors that have been identified as being

involved in HCV life cycle. One of the most well known is ApoE, a cellular protein

that is involved in lipoprotein biosynthesis. ApoE has been demonstrated to be

necessary for infectious HCV particle formation (Chang et al. 2007). In an attempt to

identify new host factors that may be important in the complete HCV life cycle, a

genome wide siRNA screen was conducted (Li et al. 2009b). Figure 1.11 depicts a

network generated from this investigation and highlighted are host proteins that are

known to interact with HCV proteins and candidate proteins identified in the screen.

Interestingly, this screen identified STAT3 as a candidate host factor in HCV

replication.

1.7.1 STAT3

STAT3 is a 79kDa protein that exists in two isoforms – STAT3α and STAT3β, where

STAT3β is a truncated form of STAT3 that acts as a dominant negative regulator of

STAT3. STAT3 is activated by all members of the IL-6 cytokine family, a number of

growth factors, oncogenes and IFNs. These include – IL-6, cardiotrophin-1 (CT-1),

leukemia inhibitory factor (LIF), epidermal growth factor (EGF), oncostatin M

(OSM) and IFN-α/β.

STAT3 was originally discovered as an acute phase response factor that is activated in

the liver by interlekin-6 (IL-6) (Kishimoto 2005). STAT3 is structurally similar to

other STAT proteins and is correspondingly activated by tyrosine phosphorylation

(Y-705) at the carboxy terminus and serine phosphorylation (S-727) within the

transactivation domain. Depending on which cytokine activates STAT3, signaling

occurs through either gp130 or related receptors and tyrosine phosphorylation is most

commonly mediated via JAK1 (Guschin et al. 1995). STAT3 then follows the normal

STAT paradigm and dimerzies, translocates to the nucleus and activates gene

Figure 1.11 Potential and known host factors involved in the complete life cycle of HCV. Network showing connections between HCV proteins, HCV-interacting host proteins and candidate proteins from the HCVcc siRNA screen. STAT3 is identified as interacting with core and NS5A and a potential candidate in the siRNA screen. (Li et al. 2009)

28

transcription via DNA binding (Figure 1.12). However, while STAT3 is structurally

similar to other members of the STAT family, it differs in that it is activated by a

wide variety of cytokines and exerts a plethora of biological responses, and most

strikingly it is the only STAT protein that when knocked out in mice, leads to

embryonic lethality (Takeda et al. 1997).

Over recent years STAT3 has been extensively studied and it has become apparent

that STAT3 has multiple and often contradictory functions. One line of thought to

explain the highly pleitropic nature of STAT3 is that distinct sets of target genes are

activated in different cell types. Hence, the cell type and the physiological state in

which STAT3 is expressed, directly effects which STAT3 dependent genes are

activated, thus enabling STAT3 to exert a complex set of responses (Bromberg et al.

1999). As such, STAT3 plays a role in a variety of biological responses such as

proliferation, differentiation and apoptosis. Examples of these varied responses

include, STAT3 dependent activation of the anti-apoptotic gene Bcl-2, that leads to

the inhibition of apoptosis and subsequent proliferation of B cells. This contrasts to

the role of STAT3 in monocytes, where it induces the contradictory biological affect

of growth arrest, via down regulation of c-myc. Furthermore, an entirely different

response is elicited in hepatocytes, as IL-6 activation of STAT3 leads to the trans

activation of genes necessary to produce proteins for the acute-phase response (Alonzi

et al. 2001a; Alonzi et al. 2001b).

Numerous investigations have implicated STAT3 in cancer. The importance of

STAT3 in malignant transformation continues to be expanded upon since the

discovery that the expression of a constitutively active form of STAT3 in fibroblasts

leads to their transformation (Bromberg et al. 1999). Numerous groups have found

that STAT3 is constitutively activated in a number of primary human tumors and

many actually cite STAT3 as oncogene in its own right. Furthermore, Yang et al

established that STAT3 plays an integral role in IFN-α/β signal transduction (Yang et

Figure 1.12 STAT3 signal transduction. The oncogenic transcription factor STAT3 is known to induce expression of many genes involved in tumor metastasis.

29

al. 1998). To this effect, there have also been a few documented investigations

depicting that STAT3 may exert anti-viral effects on HCV (Zhu et al. 2004),

however, this remains rather controversial and further studies are needed to validate

this finding.

1.7.2 Oxidative stress and STAT3

There is strong evidence in the literature that implicates OS as an activator of STAT3.

Carballo et al demonstrated that H2O2 induced OS triggered STAT3 tyrosine

phosphorylation and subsequent translocation to the nucleus (Yoshida et al. 2002). Of

particular importance for this thesis, HCV induced OS has been shown to activate

STAT3 (Waris et al. 2005) and it has been demonstrated that HCV core protein

directly interacts with and activates STAT3 by inducing tyrosine phosphorylation of

STAT3. This HCV mediated activation of STAT3 was shown to induce expression of

the STAT3 dependent genes Bcl-XL and cyclin-D1 (Yoshida et al. 2002). This study

also confirmed previous reports that constitutive STAT3 activation results in cellular

transformation and this finding may help to explain how HCV induces HCC (Yoshida

et al. 2002). However, the aforementioned studies were performed in the absence of

the complete HCV life cycle and hence future studies should include the use of the

infectious HCV cell culture system. Moreover, the results from Waris et al were

strongly suggestive of STAT3 playing a role in HCV replication, however, they did

not provide a mechanism nor was the role of STAT3 particularly well characterised.

1.8 Hypothesis and Aims

The aims of this thesis are to investigate the effect of ethanol metabolism on HCV

replication and investigate how this impacts on the anti-viral action of IFN.

Furthermore, we also plan to investigate the molecular mechanism responsible for any

effects that ethanol metabolism may have on HCV replication. Initial aims will focus

on developing an in vitro cell culture model that will be utilized to study the

30

interactions between ethanol and HCV. This will be achieved through the production

of liver derived cell lines that metabolise ethanol via re-introduced CYP2E1.

Subsequent aims will then focus on the effects of alcohol metabolism on HCV

replication and the anti-viral activity of IFN.

Hypothesis - Alcohol metabolism modulates HCV replication and decreases the

efficacy of IFN-α through the abrogation of the JAK-STAT signaling pathway.

We specifically aim to:

(1) Establish and characterize a model system that will be used to study the

interactions between HCV and ethanol metabolism.

(2) Define the molecular basis for an increase in HCV replication by ethanol

metabolism.

(3) Establish the molecular mechanism by which ethanol metabolism

attenuates the antiviral capacity of IFN-α.

(4) Investigate the role of the cellular transcription factor STAT3 in the

complete life cycle of HCV.

31

Chapter 2

Materials and Methods

2.1 General Reagents

2.1.1 Transient transfection of plasmid DNA

FuGENE 6 Transfection Reagent (Roche) was used to transfect plasmid DNA into

various cultured cell lines as per the manufacturer’s instructions. Cells were seeded in

12-well tissue culture dishes 24 hours prior to transfection at 7 × 104 cells per well

(50-70% confluency at the time of transfection). FuGENE 6 reagent and plasmid

DNA were diluted in an appropriate volume of serum free Opti-MEM according to

the manufacturer’s recommendations, generally with a DNA:FuGENE 6 ratio of 1:3.

Following a 15 minute incubation period, the transfection mixture was added in a

drop-wise fashion to cell monolayers and the dishes were gently swirled before being

returned to normal culture conditions (37 °C, 5% CO2). Assays were performed 24-

72 hours post transfection.

2.1.2 Stable transfection of plasmid DNA to generate over-expressing cell lines

To generate stably transfected cell lines overexpressing CYP2E1 and STAT3-C, HCV

replicon cells and Huh-7 cells were seeded in 10 cm2 tissue culture dishes at a density

of 3 × 105 cells per dish. Cells were transfected with vector clones of each variant

using FuGENE 6 Transfection Reagent 24 hours later. In order to select for stable

cells 24 hours post transfection, 800 µg/ml G418 sulphate (Invitrogen) was added to

STAT3-C transfected cell media and 25 µg/ml Blasticidin (Invitrogen) for the

CYP2E1 cell lines. Once antibiotic resistance was observed cells were passaged at a

low density in fresh 10 cm2 tissue culture dishes (generally diluted 1/10-1/30). When

stable colonies had formed they were harvested by trypsinisation with sterile glass

32

cloning rings. Stable clones were maintained and screened for over-expression of the

protein of interest. Positive clones were maintained under normal culture conditions

(37 °C, 5% CO2) with antibiotic selection continued.

2.1.3 Transient transfection of StealthTM siRNA oligonucleotides

StealthTM siRNA double stranded RNA oligonucleotides designed to knock down

expression of STAT3 were transfected into Huh-7.5 cells using LipofectamineTM

2000 (Invitrogen) as per the manufacturer’s instructions. [STAT3 siRNA VHS4091,

Control Lo GC 12935-500]. Briefly, 20 pmol of siRNA and 2 µl LipofectamineTM

2000 was added to 200 µl serum-free Opti-MEM and incubated for 20 minutes at

room temperature. This transfection mix was then added dropwise to each well of the

12-well plates. Scrambled control siRNA was used as a control for this assay. To

ascertain knock down of STAT3, Western blots were performed 24 hours post siRNA

transfection. For experiments with HCVcc, Huh-7.5 cells were transfected with

siRNA and then infected 24 hours later with JFH-1 (MOI=0.1) a further 24 hours post

infection total RNA was extracted.

2.2 Tissue Culture Techniques

2.2.1 Tissue culture medium

Cultured mammalian cell lines were maintained in Dulbecco’s Modified Eagle

Medium (DMEM) containing 4.5 g/L D-Glucose, 25 mM HEPES and 2 mM L-

glutamine (Gibco BRL, Invitrogen). Media was supplemented with 10% (w/v) foetal

calf serum (FCS; Trace Biosciences), 12 µg/ml penicillin (CSL), 16 µg/ml

gentamycin (Pharmacia) and other supplements as required (Table 2.1).

33

Table 2.1 Cell lines and culture conditions used in this study

2.2.2 Maintenance of cell lines

Cells were maintained in sterile 0.2 µm vented tissue culture flasks (25 cm2, 75 cm2,

or 175 cm2), tissue culture dishes (3.5 cm2, 6 cm2 or 10 cm2) or tissue culture trays (6,

12, 24, 48 or 96-well) (Falcon®, Becton Dickinson Labware). Cells were incubated

at 37 °C (5% CO2). Cells were passaged by removing the culture medium, washing

with PBS (see Appendix I) and trypsinising in a small volume of Trypsin-EDTA (see

Appendix I) for 3-5 minutes. Trysinised cells were then resuspended in culture

medium and cell counts were performed using Trypan Blue exclusion and a

haemocytometer. Cells were passaged every 2 to 3 days depending on their growth

rate.

2.2.3 Cryopreservation of cultured cells

To preserve cells in liquid nitrogen, cells (80% confluent) were trypsinised,

resuspended in culture medium and transferred to sterile 10 ml centrifuge tubes

(Techno-Plas). Cells were then centrifuged at 2,500 rpm for 5 minutes, the culture

media removed and resuspended in fresh media and transferred to sterile 1.8 ml

CryoTubeTM vials (Nunc). An equal volume of freezing mixture (80% FCS, 20%

DMSO [Sigma]) was added to each cryovial and gently mixed. Cryovials were then

transferred to a rate-controlled freezing chamber (Nalgene) containing isopropanol,

Cell Line Media Supplements

Huh-7(EG) and Huh-7.5 DMEM 10% FCS, 1% penicillin/gentamycin

NNeoC-5B(RG) DMEM 10% FCS, 1% penicillin/gentamycin, 800 µg/ml G-418

NNeoC-5B(RG)CYP2E1

DMEM 10% FCS, 1% penicillin/gentamycin, 800 µg/ml G-418, 25 µg/ml Blasticidin

Huh-7.5-STAT3-C DMEM 10% FCS, 1% penicillin/gentamycin, 800 µg/ml G-418

34

which was placed at 80 °C. A liquid nitrogen storage vessel was used for long term

storage of cryopreserved cells.

2.2.4 Resuscitation of frozen cells

Cryopreserved cells were thawed in a 37 °C water bath and then added to a flask

containing culture medium and incubated at 37 °C (5% CO2).

2.2.5 Trypan blue exclusion

Cells were counted using a Trypan Blue Exclusion. Trypsinised cells were mixed with

an equal volume of Trypan Blue (see Appendix I) and counted using a

haemocytometer. The concentration of cells was counted using the equation below :

Cell concentration (cells/ml) = cell count per grid × 2 (dilution factor) × 104

2.2.6 CellTiter-Blue® cell viability assay

Viability of cells following alcohol treatment was determined using the CellTiter-

Blue® Viability Assay (Promega). Cells were seeded at 1 × 104 onto each well of a

96-well plate in DMEM/F12 supplemented with 10% FCS and incubated overnight.

Media was then replaced with 100 µl of DMEM/F12 and treated with 100 mM

ethanol for 48 hours. At the end of treatment, 20 µl of CellTiter-Blue® reagent

(Promega) was added and cells left for 2 hours and the reading was performed at 570

nm with reference reading at 600 nm in a 96-well plate-reader.

2.2.7 CellTiter 96® non-radioactive cell proliferation assay (MTT)

The CellTiter 96® Non-Radioactive Cell Proliferation Assay is a colorimetric assay

system that measures the reduction of a tetrazolium component (MTT) into an

insoluble formazan product by viable cells, and was used in an acetaminophen

toxicity assay to determine if CYP2E1 was metabolically active. Experiments were

35

performed as per manufacturer’s instructions. Briefly, Genomic and sub-genomic

replicon cells were plated in 96-well culture plates at 2 × 104 cells per well. Cells

were then treated with 1 and 5 mM acetaminophen (Sigma Aldrich) and control cells

with media only for 48 hours. Cell viability was then performed using the CellTiter

96® Non-Radioactive Cell Proliferation Assay (MTT). 15 µl of Dye Solution was

added to each well and the plate was incubated for 1-4 hours (37 °C, 5% C02). 100 µl

of Solubilization/Stop Solution was then added to each well and a reading was

performed at 570 nm with reference reading at 600 nm in a 96-well plate-reader.

2.3 Cultured Cell Lines

2.3.1 Huh-7

The Huh-7 cell line is a human hepatocellular carcinoma cell line of epithelial origin

previously isolated from a 57 year old Japanese male (Nakabayashi et al. 1982).

2.3.2 NNeoC-5B (RG)

The NNeoC-5B (RG) cell line consists of Huh-7 cells harbouring the full HCV

genome and expressing the entire HCV polyprotein as previously described (Ikeda et

al. 2002). Under the selective pressure of G418 (800 µg/ml) this cell line

autonomously replicates HCV RNA and produces both the structural and non-

structural HCV viral proteins. However, despite this replication, infectious virions are

not produced in this system for reasons that remain unknown. This cell line was a

kind gift by Professor Stanley Lemon (University of Texas Medical Branch,

Galveston, Texas, USA). For the remainder of this thesis this cell line will be referred

to as HCV genomic replicon cells.

36

2.3.3 NNeo3-5B (RG)

Huh-7 cells harbouring the HCV sub-genomic (NNeo3-5B[RG]) that express the non-

structural HCV proteins, have been described previously (Ikeda et al. 1998). These

cell lines contain autonomously replicating HCV RNA and a neomycin cartridge to

allow for G418 selection. This cell line was kindly provided by Professor Stanley

Lemon (University of Texas Medical Branch, Galveston, Texas, USA). For the

remainder of this thesis this cell line will be referred to as HCV sub-genomic replicon

cells.

2.3.4 HCV Genomic Replicon + CYP2E1

HCV genomic replicon cells are stably transfected with the CYP2E1 gene. Under the

selective pressure of blasticidin and neomycin this stable cell line harbours the

genomic HCV replicon and metabolises alcohol via CYP2E1. For the remainder of

this thesis, this cell line will be referred to as genomic replicon + CYP2E1.

2.3.5 Huh-7 (EG) + CYP2E1

Huh-7 + CYP2E1 cells are Huh-7 cells (see 2.3.1) stably transfected with the

CYP2E1 gene. Under the selective pressure of blasticidin, this stable cell line

metabolises alcohol via CYP2E1 and is permissive for HCVcc infection. For the

remainder of this thesis, this cell line will be referred to as Huh-7 + CYP2E1.

2.3.6 Huh-7.5

Huh-7.5 cells are subgenomic replicon cells that were cured of HCV RNA by

treatment with IFN-α (Blight et al. 2002). These cells are highly permissive for

HCVcc infection and have been shown to be defective in RIG-I signaling (Sumpter et

al. 2005).

37

2.3.7 Huh-7.5 + CYP2E1

Huh-7.5 + CYP2E1 cell line consists of Huh-7.5 cells stably transfected with the

CYP2E1 gene. These cells are highly permissive for HCVcc infection and are able to

metabolise alcohol via CYP2E1.

2.4 HCVcc Infectious System

2.4.1 Generation of HCVcc viral stock

2.4.1.1 Preparation of HCV RNA

To generate a primary viral stock of JFH-1 and Jc1-myc (see Appendix II for

infectious HCV constructs), 5 µg of either pJFH-1 or pJc1-myc were digested with

the appropriate restriction enzyme at 37 °C overnight (XbaI for pJFH-1 and MluI for

pJc1-myc). RNA was then in vitro transcribed using the MEGAscript® T7 in vitro

transcription kit (Ambion), as per manufacturer’s instructions. Samples were

subsequently DNase treated with the TURBO DNase provided in the kit for 15

minutes at 37° C. RNA was then precipitated using the LiCl solution provided in the

kit. 30 µl of RNAse-free water and 30 µl of LiCl were added to samples followed by

incubation at -20 °C for at least 30 minutes. This was followed by centrifugation at

maximum speed (18,000 × g for 15 mins at 4 °C). The supernatant was then removed

carefully and the RNA pellet air dried for approximately 2 minutes. The

concentration of RNA was then measured using a spectrophotmeter and RNA

integrity checked via agarose gel electrophoresis (expected bands at ∼ 4.3 and 9.6 kb).

2.4.1.2 HCV RNA transfection

Huh-7 cells were cultured in two 175 cm2 flasks until they were near confluence.

Cells were then harvested via tyrpsinization and washed twice with 10 ml of Opti-

MEM. Cells were then resuspended in Opti-MEM at a concentration of 1 × 107

cells/ml. 0.4 ml of cells were then aliquoted per electroporation cuvette (on ice), to

38

which 10 µg of RNA was added and gently mixed. Cells were then electroporated

with a single pulse at 0.27 kV, 100 ohms and 960 µF. The cells were then

immediately plated into 175 cm2 flasks (one per electroporation) in complete culture

medium (DMEM + 10% FCS and antibiotics). Cells were then cultured for 2-10 days

post-transfection, as required, via subculture into new culture flasks when cells

reached confluence. Viral containing supernatants were collected at approximately 5

days post transfection and stored in 50 ml disposable conical tubes.

2.4.1.3 Concentration of HCV viral stocks (PEG precipitation)

The collected viral supernatants were adjusted to 40 ml with complete medium if

necessary and 10 ml of 40% (w/v) polyethylene glycol (PEG) [Sigma] was added to

give a final concentration of 8% (w/v). Tubes were then mixed well by inversion and

incubated at 4 °C overnight. Tubes were then centrifuged at 3900 × g for 30 minutes

at 4 °C. Supernatant was then removed and pellets resuspended in a small volume of

complete media (1-2ml) and samples of concentrated virus then aliquoted into screw

cap microcentrifuge tubes. Samples were then stored at -80 °C and virus titre

calculated as per section 2.1.1.4. Amplification of HCV viral stocks (‘up-scale’) was

performed as per section 2.1.1.5.

2.4.1.4 Titration of infectious HCV

To titrate infectious HCV stocks, Huh-7 cells were seeded into 96-well culture trays

at 2 × 104 cells/well. The next day, in 100 µl volumes, serial 10-fold dilutions of

virus-containing supernatants were prepared, up to 1 in 10000. The media was then

removed from near confluent Huh-7 cells in 96-well trays and replaced with 40 µl of

inoculum (in duplicate for each dilution), the cells were then cultured for 3 hours.

Inoculum was then removed and cells washed once with PBS (100 µl/well) and

replaced with 100 µl of complete media. The cells were then cultured for a further 3

days. At 3 days post infection the culture supernatant was removed and cell

39

monolayers fixed by the addition of 100 µl of ice-cold acetone:metenol (1:1) and

plates incubated at 4 °C for 15 minutes. The fixation solution was then replaced with

100 µl of PBS and HCV antigens labeled by the removal of PBS and the addition of

anti-HCV antisera (or purified antibody) diluted appropriately in PBS and containing

1% bovine serum albumin (BSA) (40 µl/well) and incubated at room temperature for

1 hour. The primary antibody was then removed and cell monolayers washed with

PBS (100 µl/well), the appropriate diluted fluorescent-conjugate of secondary

antibody was then added to cells (40 µl/well) in PBS containing 1% BSA and

incubated at 4 °C for 1 hour. The secondary antibody solution was then removed and

cell monolayers washed twice with PBS (100 µl/well). HCV positive cells were then

visualized by fluorescence microscopy using a Nikon TiE fluorescence inverted

microscope and the foci (distinct clusters) of HCV positive cells in each well (average

of duplicates) were counted. To calculate the virus titre the following formula was

used : [Titre (focus forming units [ffu/ml]) = number of foci × dilution factor × 25]

2.4.1.5 Amplification of HCV viral stocks (‘up-scale’)

The amplification of HCV viral stocks was performed via seeding Huh-7 cells 1.6 ×

106 cells / 75 cm2 flask and cultured overnight. The following day the culture medium

was replaced with 2 × 104 ffu of cell culture-propagated HCV (HCVcc) in 2-3 ml of

complete culture media and the cells returned to culture for 3 hours, after which

complete media was added to a final volume of 10 ml. The cells were then cultured

for a further 3 days. At 3 days post infection the culture supernatant was collected

and cells harvested by trypsinization and subsequently sub-cultured into 175 cm2

flask. The cells were then cultured for a further 2 to 3 days, or until visible cytopathic

effect became evident. At this point the virus containing culture supernatants were

collected and cleared of cellular debris via centrifugation (3900 × g for 5 minutes).

The cleared culture fluid could then be concentrated and titrated.

40

2.4.2 General infection protocol for HCVcc

Huh-7 cells were seeded at 8 × 104 cells per 12-well culture tray and subsequently

infected with 2 × 104 ffu/ml of JFH-1 or Jc1-myc virus in a 300 µl volume of

complete media for 3 hours. Following initial infection, the medium volume was

increased to 10 ml and the cells were left for 48 or 72 hours before being seeded for

the luciferase assay or mRNA quantification experiments, respectively. Upon

completion of the experiment, JFH-1-infected Huh-7 cells were analyzed to ensure

HCV protein expression by using indirect immunofluorescence (see section 2.5.23.1)

with the exception that cells were incubated at a 1/300 dilution of mixed sera taken

from patients chronically infected with HCV and a fluorescent isothiocyanate-

conjugated rabbit anti-human immunoglobulin G secondary antibody (Chemicon,

Temecula, CA). Cells were visualized using a Nikon TiE inverted fluorescence

microscope and all experiments were performed at least in triplicate. All cells were at

least 75% JFH-1 infected at the completion of the experiments, as determined by cell

enumeration. (Data not shown).

2.5 General Molecular Biology Methods

2.5.1 Synthetic oligonucleotides

All oligonucleotides listed in Table 2.2 were obtained from GeneWorks at

PCR/sequencing purity. Primers were received in lyphophilised form, diluted in

dH2O to 20 µM and stored at -20 °C until used. Oligonucleotide concentration was

determined using the following formula, assuming an average MW of 330 Daltons per

nucleotide: Oligonucleotide concentration (µM) = Concentration (mg/ml) × 106

Nucleotide length × nucleotide MW

41

Table 2.2 Primer sequence

Gene name Sense primer Anti-sense primer

ISG20 5’- TCGTTGCAGCCTCGTGAAC 5’- TCCCTCAGGCCGGATGA

Viperin 5’- GTGAGCAATGGAAGCCTGATC 5’- GCTGTCACAGGAGATAGCGAGAA

HCV 5’-TCTTCACGCAGAAAGCGTCTAG 5’-GGTTCCGCAGACCACTATGG

RPLPO 5’- AGATGCAGCAGATCCGCAT 5’-GGATGGCCTTGCGCA

CYP2E1 Commercially obtained (Roche) Commercially obtained (Roche)

GAPDH Commercially obtained (Clontech) Commercially obtained (Clontech)

2.5.2 Bacterial transformation

Frozen aliquots of the competent E.coli strain DH5α cells (see Appendix I) were

thawed on ice for 5 minutes prior to the addition of plasmid DNA. Once the

appropriate volume of plasmid DNA was added the tubes were gently mixed and

incubated on ice for 20 minutes. Cells were then heat shocked at 42 °C for 90

seconds followed by incubation on ice for a further 2 minutes. Luria Bertani Broth

(LB) (400 µl) was then added to the cells and they were incubated at 37 °C for 30

minutes to allow for the induction of antibiotic resistance. Cells were then plated on

L-Agar plates containing ampicillin (100 µg/ml) and incubated at 37 °C overnight. 16

hours later bacterial colonies were selected and prepared for DNA plasmid extraction.

2.5.3 Mini-preparation (small scale) of plasmid DNA

This method involves alkaline cell lysis and column purification of plasmid DNA.

LB (5 ml) cultures containing ampicillin (100 µg/ml) were inoculated with a single

transformed bacterial colony and incubated overnight with vigorous shaking at 37 °C.

Plasmid DNA was isolated from log phase cultures using the UltracleanTM 6 Minute

Mini Plasmid Prep Kit (Mol Bio Laboratories) according to the manufacturer’s

instructions.

42

2.5.4 Maxi-preparation (large scale) of plasmid DNA

LB (3 ml) cultures containing ampicillin (100 µg/ml) were inoculated with a single

transformed bacterial colony and incubated for 8 hours at 37 °C with shaking. 100 µl

of log phase culture was then transferred to LB (100 ml) containing ampicillin (100

µg/ml) and incubated overnight at 37 °C with shaking. Plasmid DNA was then

isolated using the Plasmid Maxi Kit (Qiagen) as per the manufacturer’s instructions.

Overnight cultures were centrifuged at 6,000 × g for 15 minutes at 4 °C using a JA10

or JA14 rotor in a Beckman J2-21M Induction Drive centrifuge. Cell supernatant was

discarded and the cell pellet resuspended in 10 ml Buffer P1. 10 ml Buffer P2 was

added and the mixture incubated at room temperature for 5 minutes, after which 10 ml

chilled Buffer P3 was added, tubes inverted and incubated for 20 minutes on ice.

Tubes were then centrifuged for 30 minutes at 20,000 × g at 4 °C in a JA20 rotor in a

Beckman J2-21M Induction Drive centrifuge. Meanwhile, supplied QIAGEN-tip 500

columns were equilibrated with 10 ml Buffer QT. Centrifuged supernatant was passed

through the QIAGEN-500 column, which was then washed with two 30 ml washes of

Buffer QC. Plasmid DNA was eluted from the column into a fresh collection tube

with 15 ml of Buffer QF. DNA was precipitated by adding 10.5 ml isopropanol to the

eluted plasmid mixture, gently mixing and centrifuging at 15,000 × g at 4 °C for 30

minutes. Supernatant was discarded and the resultant pellets washed with 1 ml 70%

ethanol (v/v) by centrifuging at 15,000 × g for 10 minutes at room temperature. After

removal of the ethanol wash, pellets were air dried for 5 to 10 minutes, re-dissolved in

100 µl sterile dH2O and stored at -20 °C until further use.

2.5.5 Restriction endonuclease digestion

Restriction digests were performed in a 10 µl volume, which contained 1 µg DNA

and 10 U of restriction enzymes (New England Biolabs) in the appropriated buffer.

Digests were allowed to proceed for 1 to 3 hours at 37 °C or overnight at 16 °C.

Digested DNA was then visualized on a 1% agarose gel.

43

2.5.6 Agarose gel electrophoresis

Gel electrophoresis was performed using 1-2% (w/v) agarose gels. Agarose gels were

made by dissolving DNA grade agarose (Progen Biosciences) in 1 × TAE (see

Appendix I). Gels were then cast in a BioRad Wide Mini-Sub® Cell GT tank. DNA

samples were mixed with 6 × loading dye (see Appendix I) and subsequently loaded

into wells on the agarose gel. The gel was then run at 50-100 V in 1 × TAE.

Markers were run simultaneously to estimate product size, 0.5 µg of 1 kb or 100 bp

DNA molecular weight markers (New England Biolabs). Following electrophoresis,

gels were stained in 3 × GelRedTM Nucleic Acid Gel Stain in DMSO (Biotium Inc)

for approximately 15 minutes. DNA was then visualised under ultraviolet light on a

BioRad Universal Hood II gel documentation system using Quantity One® Version

4.6 Basic software (BioRad).

2.5.7 DNA ligation

PCR amplicons of the three OPN splice variants were digested with HindIII and XbaI

to allow for directional cloning into similarly digested pRc/CMV. Ligation reactions

were performed in a 10 µl volume containing 0.4 units T4 DNA Ligase (New

England Biolabs), 1 × Ligase Buffer (New England Biolabs), and a 3:1 ratio of

amplified splice variant insert to destination vector. Reactions were allowed to

proceed at room temperature for 1 to 2 hours. Successful ligations were confirmed by

restriction digest and gel electrophoresis to identify bands of the expected size.

Correct ligation mixtures were transformed into competent DH5α cells for colony

growth and plasmid purification.

2.5.8 Gel purification

To purify electrophoresed DNA from agarose, DNA bands were excised using a

scalpel blade and stored in eppendorf tubes while being visualized under UV light.

DNA was then purified using the MinElute Gel Extraction Kit (Qiagen) as per the

44

manufacturer’s recommendations. Briefly, excised DNA bands were weighed in a

clean tube and 300 µl Buffer QG added per 100 mg gel weight. Samples were

incubated at 50 °C for approximately 10 minutes to dissolve the gel slice, after which

100 µl isopropanol was added per 100 mg gel and tubes inverted to mix. Samples

were applied to a MinElute column (placed in a supplied 2 ml collection tube) and

centrifuged at 14,000 rpm for 1 minute. Flow-through was discarded, 500 µl Buffer

QG added and tubes centrifuged again at 14,000 rpm for 1 minute. Flow-through was

again discarded and the column washed with 750 µl Buffer PE by centrifuging for 1

minute at 14,000 rpm. Final flow-through was discarded, the MinElute column placed

into a clean 1.5 ml collection tube and DNA eluted by adding 10 µl dH2O to the

column filter, incubating for 1 minute at room temperature, and centrifuging at 14,000

rpm for 1 minute. Samples were stored at -20 °C until required.

2.5.9 DNA sequencing

Gel purified PCR products and plasmid DNA were sequenced to ascertain if the

desired sequence had been obtained. Sequencing was performed in a 10 µl volume

containing 150 ng plasmid DNA or 10 ng amplicon, 0.32 pmol primer, 1 × BigDye®

Buffer (Applied Biosystems), 0.5 µl BigDye® Terminator v3.1 (Applied Biosystems)

and dH2O. Sequencing PCR conditions comprised an initial denaturation step of 94

°C for 5 minutes, followed by 25 cycles of 94 °C for 30 seconds, 50 °C for 15

seconds and 60 °C for 4 minutes. A final step of 60 °C for 7 minutes was performed,

after which reactions were prepared for sequencing by vortexing with 80 µl of 75%

(w/v) isopropanol and incubating for 15 minutes at room temperature. Samples were

centrifuged for 20 minutes at 14,000 rpm, supernatant aspirated and pellets

resuspended in a further 250 µl of 75% (w/v) isopropanol. Tubes were again vortexed

and centrifuged for 5 minutes at 14,000 rpm, supernatant removed and pellets dried at

room temperature for 15 minutes. Samples were stored at -20 °C until sequencing

could be performed on a 3730 DNA Analyser at the Molecular Pathology Sequencing

45

facility of the IMVS. Data was analysed using ChromasPro version 1.34 and

compared to known sequences using NCBI BLAST nucleotide blast search against

the human genome (http://www.ncbi.nlm.nih.gov/blast/Blast.cgi).

2.5.10 Extraction of total RNA

Total cellular RNA was extracted from cell monolayers adhered to 6 or 12-well dishes

(Falcon®, Becton Dickinson Labware) using Trizol® Reagent (Invitrogen) according

to the manufacturer’s recommendations. Cell monolayers were lysed directly in

TrizolR Reagent (500 µl per 12-well / 1 ml per 6-well culture plate). Lysates were

followed by the addition of 200 µl chloroform per 1 ml TrizolR. Tubes were then

shaken vigorously for 15 seconds and incubated again at room temperature for 2

minutes. Samples were then centrifuged at 12,000 × g for 15 minutes at 4 °C.

Following separation, the top aqueous layer was transferred to an RNAse-Free 1.5 ml

Microfuge tube (Ambion) and precipitated with isopropanol (0.5 ml per 1 ml TrizolR)

for 10 minutes at room temperature. Samples were again centrifuged for 15 minutes

at 12,000 × g at 4 °C. Supernatant was aspirated and the pellet vortexed with 1 ml

70% (v/v) ethanol and centrifuged at 7,500 × g for 10 minutes at 4 °C. After removal

of the ethanol wash, the resultant RNA pellet was air dried and resuspended in 20 µl

RNAse-free dH2O and stored at -80 °C.

2.5.11 DNAseI treatment of RNA samples

RNA samples were treated with DNAseI to remove any contaminating DNA. To each

20 µl sample 2 units RNase-free DNaseI (Ambion) and 1 × DNAseI buffer (Ambion)

were added and tubes incubated at 37 °C for 15 minutes. Following incubation, 2 µl

DNAse Inactivation Reagent (Ambion, provided with the RNAqueous-4PCR RNA

Extraction kit) was added to each sample and incubated at room temperature for 2

minutes, after which samples were centrifuged at 10,000 × g for 1 minute.

Supernatant was transferred to a fresh tube and stored at -80 °C until further use.

46

2.5.12 Nucleic acid quantification

All DNA and RNA preparations were diluted in dH20 and quantitated using the

SmartSpecTM 3000 UV spectrophotometer (BioRad Laboratories). A260nm readings

were taken and sample concentrations calculated by multiplying the absorbance

reading by the appropriate dilution factor and 50 (DNA) or 40 (RNA) as an A260nm

reading of 1 is equivalent to 50mg/ml DNA and 40mg/ml RNA.

[Nucleic Acid] = A260nm x dilution factor x (50 or 40) µg/ml

2.5.13 cDNA preparation

cDNA was prepared M-MLV reverse transcriptase (Promega). 1 µg total RNA was

combined with 1 µg random hexamer primer (GeneWorks) and diluted to a total

volume of 14 µl with dH2O. Tubes were incubated at 70 °C for 5 minutes, then on ice

for a further 5 minutes. 1 × M-MLV RT reaction buffer (Promega), 0.5 µmol dNTP

mix (0.5 µmol each dATP, dCTP, dGTP, dTTP; Promega), 40 units rRNAsin® RNase

Inhibitor (Promega), 200 units M-MLV RT, RNase H(-) Point Mutant (Promega) and

3.25 µl dH2O were added to each tube, samples mixed gently and incubated at room

temperature for 10 minutes, then 42 °C for 50 minutes. Samples were then diluted to a

final volume of 100 µl with dH2O and stored at -20 °C.

2.5.14 Polymerase Chain Reaction

All PCR reactions were performed using the MyCyclerTM Thermal Cycler (Bio-Rad)

and the high fidelity polymerase AmpliTaq Gold (Applied Biosystems). Reactions

were performed in a 50 µl volume containing 20 pmol each of forward and reverse

primer (Table 2.2), 1 × PCR Reaction Buffer (Applied Biosystems), 0.2 µmol dNTP

mix (Promega), 25 mM MgCl2 (Applied Biosystems), 1 unit AmpliTaq Gold

polymerase (Applied Biosystems) and the appropriate amount of target plasmid DNA

(typically 10-100 ng) or cDNA (5 µl of diluted synthesised cDNA). PCR reaction

47

conditions comprised initialisation at 94 °C for 10 minutes, followed by 25-40 cycles

of denaturation at 94 °C for 30 seconds, annealing at 55 °C for 30 seconds and

extension at 72 °C for 30 seconds. A final elongation step was then performed at 72

°C for 7 minutes. PCR reaction outcomes were confirmed by agarose gel

electrophoresis. All samples were simultaneously amplified with primers for GAPDH

(Table 2.2) to confirm equal loading and integrity. All PCR reactions were then

stored at 4 °C and results anlaysed via agarose gel electrophoresis.

2.5.15 Real-Time Quantitative PCR

Real-time quantitative PCR was performed to determine relative levels of HCV RNA

using the comparative CT method of SYBR® Green PCR Master Mix (Applied

Biosystems). 5 µl cDNA was combined with 10 µl SYBR® Green PCR Master Mix

and 300 nM each forward and reverse primers (Table 2.2) in duplicate. All cDNA

samples were combined with 10 µl SYBR® Green PCR Master Mix and 300 nM each

forward and reverse primers for the housekeeping gene ribosomal protein large PO

(RPLPO; Table 2.2) to normalize input cDNA levels. Reaction conditions were

controlled by an ABI PRISM 7000 Sequence Detection System (Applied Biosystems)

and comprised denaturation at 95 °C for 10 minutes followed by 40 cycles of 95 °C

for 15 seconds and 60 °C for 1 minute. A final dissociation step of 60 °C for 10

minutes followed, to facilitate melt curve analysis. Data was analysed using ABI

Prism 7000 SDS Software and the threshold was set at 0.2 for all experiments.

2.5.16 Extraction of cellular protein

Total protein was extracted from cell monolayers using RIPA buffer (see Appendix I).

Culture media was removed and cells washed in ice cold PBS. 1 µl of proteinase

inhibitor cocktail (Sigma) as added per 100 µl of RIPA buffer. 100 µl of this mixture

was then added to each well. The plates were then incubated on ice for 20 minutes

with gentle agitation every 5 minutes. The wells were then scraped and the lysates

48

collected and added to eppendorfs that were then centrifuged at 14,000 rpm for 10

minutes at 4 °C. The protein containing supernatant was then removed and stored at

-20 °C.

2.5.17 Protein quantification

The concentration of each extracted protein sample was determined using the Bio Rad

Protein Assay (Bio Rad) with purified bovine plasma γ-globulin as a standard. All

samples were diluted 1/20 with 10 µl of each sample and then added to a microtiter

plate and combined with 200 µl of Dye Reagent, the tray was incubated at room

temperature for 5 minutes. A600 values were then ascertained using an MR5000 plate

reader (Dynatech) and compared to a standard curve of known bovine plasma γ-

globulin protein concentration in order to determine sample concentrations.

2.5.18 SDS PAGE and protein transfer

SDS PAGE was performed as previously described (Laemmli 1970). A 12%

separating gel (see Appendix I) was cast in a BioRad Mini-PROTEAN® Tetra Cell gel

tank and layered with dH2O to prevent oxidation and enhance gel polymerisation.

Once set, a 5% stacking gel (see Appendix I) was layered onto the separating gel and

a comb inserted to form wells. Protein samples were prepared for electrophoresis by

boiling for 5 minutes with 1 × SDS PAGE sample buffer (see Appendix I). 50 µg

samples were then loaded onto the gel alongside 7.5 µg Precision Plus Protein®

Standards - Kaleidoscope (BioRad) and run at 100 volts for 1-2 hours in SDS-PAGE

running buffer (see Appendix I). Gels were equilibrated in cold western transfer

buffer (see Appendix I) for 5 minutes and proteins transferred to a Hybond ECL

membrane (Amersham Pharmacia Biotech) in western transfer buffer for 1-2 hours at

100 volts in a BioRad Mini Trans Blot Electrophoretic Transfer Cell.

49

2.5.19 Western blotting

Following transfer, membranes were blocked with 5% skim milk (Diploma) in 0.1%

PBS-T (see Appendix I) for 1 hour with gentle agitation. Membranes were rinsed

twice in 0.1% PBS-T and incubated in the appropriate concentration of primary

antibody diluted in 0.1% PBS-T (Table 2.3) overnight at 4 °C (see Table 2.3 for

antibody concentrations). Membranes were rinsed twice in 0.1% PBS-T and

incubated once for 15 minutes and three times for 5 minutes each in fresh changes of

0.1% PBS-T to remove any unbound primary antibody. Membranes were then

incubated in the appropriate horseradish peroxidase-conjugated secondary antibody

(Table 2.3) for 1 hour with gentle agitation and washed as described above. Protein

detection was carried out using the ECL Plus Western blotting detection reagent kit

(Amersham Pharmacia Biotech) with chemiluminescent detection as per

manufacturer’s instructions. Protein bands were visualised by exposure to Kodak

BioMax film for 30 seconds to 20 minutes depending on signal intensity.

50

Table 2.3 Antibody concentration

1 °Antibody Concentration Company

STAT1 1:1000 O/N 4°C Cell Signaling

STAT1-Y701 1:1000 O/N 4°C Cell Signaling

STAT1-S724 1:1000 O/N 4°C Cell Signaling





STAT3-S727 1:1000 O/N 4°C Cell Signaling

TYK2-Y1054/1055 1:500 O/N 4°C Cell Signaling

CYP2E1 1:1000 O/N 4°C Chemicon International

β-actin 1:10,000 O/N 4°C Sigma Aldrich

2 °Antibody

Anti-Mouse IgG

(HRP-linked)

1:20,000 1 hr @ room temp Rocklands

Anti-Rabbit IgG,

(HRP-linked)

1:1000 1 hr @ room temp Cell Signaling

2.5.20 Dual Renilla luciferase assay

The relative luciferase activity of the ISRE and STAT3 promoter elements were

measured using the Luciferase Assay System (Promega). Cells were seeded at a

density of 7 x 104 cells/well and transfected with pISRE-luc or pSTAT3-luc (800

ng/well) and pRL-TK (5ng/well) to act as a control of transfection efficiency.

Transfections were performed using FuGENE 6 transfection reagent (Roche Applied

Science) as mentioned previously. For ISRE-luc experiments, 24 hours post

transfection, the media was replaced with 2% DMEM that contained 100 mM ethanol

for the treated cells and 2% DMEM only to the control cells. After 24 hours the

media was then removed and replaced with IFN-α (at varying unit concentrations) for

51

5 hours. For STAT3-luc experiments, cells were dually transfected with pRC/CMV-

STAT3-C and also infected with 0.1 MOI JFH-1 for 48 hours following initial

transfections. Ethanol experiments were performed as previously mentioned for

ISRE-luc. At the end of each treatment time point cell lysates were collected in 80 µl

of Passive Lysis Buffer by a single freeze-thaw cycle. 20 µl of cell lysate was then

added to an optical tray and luciferase out-put measured on a Glow Max machine

(Promega).

2.5.21 Measurement of ROS

Reactive oxygen species (ROS) measurements were performed essentially as

previously described (Okuda et al. 2002). Briefly, the production of ROS was

measured by flow cytometry using the fluorogenic dye, DCF-DA (di-

chlorofluoroscein-diacetate, Molecular Probes Inc, Eugene, OR). Cells were seeded

in 60 mm2 cell culture dishes at 4 × 105 cells/dish in triplicate and incubated for 24

hours. The next day the medium was replaced with serum free medium with 0 mM

and 100 mM ethanol and 1 mM H2O2 (as a control) for each cell line and left for

another 5 hours. Lastly, medium was replaced with 1 X PBS containing 1% glucose

and DCF-DA dye was added at a final concentration 10 µM. The cells were kept in a

humidified incubator at 37 oC for 30 minutes and then harvested and resuspended in 1

x PBS supplemented with 1% FCS. DCF emission was measured at 525 ± 20 nm by

flow cytometry.

2.5.22 Acetaminophen assay

Cells were treated with acetaminophen as previously described (Jones et al. 2002).

Briefly, cells were seeded in 6-well cell culture plates at a density of 2 × 105 cells/well

and cultured for 24 hours. The following day, media was changed to FCS free

medium and treated with 1 mM or 5 mM acetaminophen (Sigma Aldrich) or left

untreated for 48 hours. Cell viability was then determined using a MTT assay.

52

2.5.23 Treatment of cells

Alcohol (ethanol): Cells were seeded in 6-well cell culture plates at a density of 2 x

105 cells/well or 12-well culture plates at a density of 7 × 104 cells/well and cultured

for 24-96 hours. The following day media was replaced with media containing

various concentrations of ethanol (10-100 mM: Sigma Aldrich). Plates were sealed to

minimize evaporation of ethanol and media-containing ethanol was replaced every 24

hours. Total RNA was isolated at 24 or 48 hours post treatment for cDNA synthesis

and semi-quantitative real-time PCR.

Interferon: Cells were seeded in 12-well plates at a density of 7 × 104 cells/well in

DMEM supplemented with 2% FCS and left at 37 °C for 24 hours before addition of

IFN-α2b (10 IU/ml : Intron A, Schering-Plough) ethanol (10-100mM : Sigma

Aldrich). Total RNA was isolated at 24 or 48 hours post treatment for cDNA

synthesis and semi-quantitative real-time PCR.

DAS: Cells were seeded in 12-well plates at 7 × 104 cells/well in DMEM

supplemented with 2% FCS and left at 37 °C for 24 hours before addition of DAS (10

mM: Sigma Aldrich) and or ethanol. Total RNA was isolated at 24 or 48 hours post

treatment for cDNA synthesis and semi-quantitative real-time PCR.

4MP: Cells were seeded in 12-well plates at a density of 7 × 104 cells/well in DMEM

supplemented with 2% FCS and left at 37 °C for 24 hours before addition of 4MP (10

mM: Sigma Aldrich) and or ethanol. Total RNA was isolated at 24 or 48 hours post


NAC: Cells were seeded in 12-well plates at a density of 7 × 104 cells/well in DMEM

supplemented with 2% FCS and left at 37 °C for 24 hours before the addition of NAC

(5-10 mM: Sigma Aldrich) and or ethanol. NAC was replaced at every 8 hour

53

interval. Total RNA was isolated at 24 or 48 hours post treatment for cDNA synthesis

and semi-quantitative real-time PCR.

LIF: Cells were seeded in 12-well plates at a density of 7 × 104 cells/well in DMEM

supplemented with 2% FCS and left at 37 °C for 24 hours before addition LIF (10

mM: Sigma Aldrich) for 24 hours prior to HCVcc infection. Total RNA was isolated

at 24 or 48 hours post treatment for cDNA synthesis and semi-quantitative real-time

PCR.

Acetaldehyde: Cells were seeded in 12-well plates at a density of 7 × 104 cells/well in

DMEM supplemented with 2% FCS and left at 37 °C for 24 hours before

acetaldehyde (100-200 µM: Sigma Aldrich) was added to the culture medium. Total

RNA was isolated at 24 hours post treatment for cDNA synthesis and semi-

quantitative real-time PCR.

H2O2: Cells were seeded in 12-well plates at a density of 7 × 104 cells/well in DMEM

supplemented with 2% FCS and left at 37 °C for 24 hours before H2O2 (50-200 mM:

Sigma Aldrich) was added to the culture medium for 1 hour. Total RNA was isolated

at 24 hours post treatment for cDNA synthesis and semi-quantitative real-time PCR.

STA-21: Cells were seeded in 12-well plates at a density of 7 × 104 cells/well in

DMEM supplemented with 2% FCS and left at 37 °C for 24 hours before fresh media

was added containing STA-21 (10 µM: Biomol) for 1 hour. Cells were then infected

with HCVcc for 3 hours, after which viral inoculum was removed, cells washed and

media containing STA-21 added. Total RNA was isolated at 24, 48 and 72 hours post


AG490: Cells were seeded in 12-well plates at a density of 7 × 104 cells/well in


54

was added containing AG490 (10 µM: Sigma Aldrich) for 1 hour. Cells were then

infected with HCVcc for 3 hours, after which viral inoculum was removed, cells

washed and media containing AG490 added. Total RNA was isolated at 24, 48 and 72

hours post treatment for cDNA synthesis and semi-quantitative real-time PCR.

S31-201: Cells were seeded in 12-well plates at a density of 7 × 104 cells/well in


was added containing S31-201 (20 µM: Sigma Aldrich) for 1 hour. Cells were then

infected with HCVcc for 3 hours, after which viral inoculum was removed, cells

washed and media containing S31-201 added. Total RNA was isolated at 24, 48 and

72 hours post treatment for cDNA synthesis and semi-quantitative real-time PCR.

2.5.24 Immunofluorescence microscopy

2.5.24.1 HCV antigen staining

Visualization of HCV antigens in HCV replicon cells and HCVcc infected Huh-7

cells was performed by indirect immunofluorescence microscopy on

acetone/methanol fixed cells essentially as described previously (Li et al. 2002) with

the exception that cells were incubated in a 1/300 dilution of de-identified HCV

positive human serum (pooled from 5 patients). HCV positive serum was inactivated

by treatment of 1% triton X-100 and heating to 60 °C prior to use. A goat anti-human

IgG Alexa 488-conjugated secondary antibody (Invitrogen) was used. Cells were

visualized using a Nikon TiE inverted fluorescence microscope.

2.5.24.2 STAT3-C-fLAG staining

Visualization of STAT3-C in Huh-7 cells was performed on acetone/methanol fixed

cells via indirect immunofluorescence microscopy using a primary FLAG antibody at

1/200 dilution. The secondary antibody used was an anti-mouse IgG Alexa 555 or

55

488-conjugated (Invitrogen). Cells were visualized using a Nikon TiE inverted

fluorescence microscope.

2.5.24.3 α-tubulin staining

Visualization of α-tubulin in Huh-7 cells was performed on acetone/methanol fixed

cells via indirect immunofluorescence microscopy using a primary α-tubulin (Sigma)

antibody at a 1/200 dilution. The secondary antibody used was an anti-mouse IgG

Alexa 555-conjugated (Invitrogen). Cells were visualized using a Nikon TiE inverted

fluorescence microscope.

2.6 Data Analysis

All data was statistically analysed by way of unpaired student t-tests using GraphPad

Prism 5.

56

Chapter 3

An in vitro Model System to Study the Effects of Alcohol Metabolism on HCV Replication

3.1 Introduction

The consumption of alcohol in persons infected with HCV is a significant clinical

problem, as alcohol consumption accelerates the progression of liver disease (Poynard

et al. 1997) and reduces the efficacy of IFN-α therapy (Safdar and Schiff 2004).

Despite these clinical findings, the mechanisms by which alcohol exacerbates liver

disease and interferes with IFN-α signaling in CHC infection remain unknown. This

lack of data can be largely attributed to the fact that the interactions between HCV

and alcohol have been difficult to investigate due to the unavailability of a suitable

model system in which to study these interactions. There have been a number of

studies investigating the pathogenic mechanisms of alcohol consumption in mice but

unfortunately mice are refractory to infection with HCV and thus the unavailability of

a small animal model for HCV research is one of the main impediments to this field

of research. While the chimpanzee model has provided invaluable insights into the

host response to a HCV infection (Boonstra et al. 2009), for obvious reasons it is not

a viable model to study the interactions between alcohol consumption and HCV

infection. The second impediment in this field of research is the fact that the in vitro

HCV model systems, namely the replicon (Lohmann et al. 1999; Ikeda et al. 2002)

and infectious cell culture (Wakita et al. 2005) systems described in section 1.1.9,

both utilize Huh-7 cell lines, which do not express the main alcohol metabolizing

enzymes CYP2E1 and ADH when cultured in vitro. Thus, while these Huh-7 cells are

able to harbour HCV replication, they are not useful for investigating the effects of

alcohol metabolism on HCV replication or the interactions between HCV host cell

factors.

57

To overcome this limitation, the aim of this chapter was to generate and characterize a

model system that will enable the dissection of the molecular interactions between

HCV, alcohol and IFN-α in hepatocytes in vitro. This chapter describes the

development of two model systems that enable investigations into the interactions

between alcohol and HCV - (i) the HCV replicon model and (ii) the infectious JFH-1

HCV cell culture (HCVcc) model. Both of these models were generated by the re-

introduction of CYP2E1 into Huh-7 cells to yield stable cell lines that are able to

effectively metabolise alcohol (ethanol) and harbour HCV replication. This approach

has been used previously to successfully investigate alcohol metabolism in the

hepatocellular carcinoma cell line HepG2 (Cederbaum et al. 2001).

3.1.1 Generation of stable CYP2E1 HCV replicon cell lines

The plasmid pcDNA-2E1 expresses CYP2E1 under the transcriptional control of a

CMV promoter (a kind gift from AI Cederbaum, Mount Sinai School of Medicine,

New York, described in Appendix IV). This plasmid construct was used to generate

Huh-7 genomic and sub-genomic replicon cell lines (kindly supplied by Stanley M

Lemon, University of North Carolina, Chapel Hill) that stably express CYP2E1. This

construct has been used by others to successfully generate stable cell lines

(Cederbaum et al. 2001; Otani et al. 2005). Briefly, these stable cell lines were

generated by transfection of genomic and sub-genomic HCV replicon cells with

pcDNA-2E1, this was followed by antibiotic selection with blasticidin. Resistant

clones were then isolated and expanded (method described in section 2.1.2). The

pcDNA-AS-2E1 plasmid (described in Appendix V) that expresses CYP2E1 in an

anti-sense orientation was used as a negative control. In order to determine which

Huh-7 clones stably expressed CYP2E1, total RNA was harvested from each clone

using Trizol®, cDNA synthesized and RT-PCR was performed to detect CYP2E1 and

GAPDH mRNA. Analysis of PCR amplicons revealed a 152 base pair specific PCR

product in approximately 50% of the selected Huh-7 sub-genomic (Fig 3.1-A) and

Figure 3.1 Detection of CYP2E1 expression in HCV sub-genomic replicon cell lines +/- CYP2E1. Multiple sub-genomic HCV replicon cell lines express CYP2E1 by (A) RT-PCR and (B) Western blotting. Note that Huh-7, the parent or anti-sense (AS) lines do not express detectable CYP2E1 message or protein.

1 2 3 4 5 6

1. Huh-72. Sub-genomic replicon3. Anti sense - Sub-genomic replicon +2E14. Sub-genomic replicon+2E1- clone 35. Sub-genomic replicon+2E1- clone 56. Sub-genomic replicon+2E1- clone 6

CYP2E1 52 kDa

β-actin 42 kDa

CYP2E1

GAPDH

B (Western Blot)

A (RT-PCR)

1 2 3 4 5 6

58

genomic replicon clones (Fig 3.2A). As expected there were no detectable levels of

CYP2E1 in the parental Huh-7 and replicon cell lines, nor was there any CYP2E1

detected in the anti-sense CYP2E1 clone. In order to ascertain if mRNA expression of

CYP2E1 translated into expression of CYP2E1 protein, total protein was harvested

from all clones and Western blots were performed using a specific antibody directed

against CYP2E1, in the combination with detection of the loading control protein β-

actin. Western blots demonstrated the detection of the 52 kDa CYP2E1 protein in

CYP2E1 positive sub-genomic replicon clones (Fig 3.1B) and genomic clones (Fig

3.2B). There was no detection of CYP2E1 protein in the parental Huh-7 and replicon

cells, or in the AS-CYP2E1 clones. Collectively these results show that we have

successfully generated both HCV genomic and sub-genomic cell lines that stably

express CYP2E1 at the mRNA and protein level.

3.1.2 Generation of stable CYP2E1 Huh-7 cell lines

The CYP2E1 HCV replicon cells generated above do not produce infectious virus

particles and thus do not provide a complete model system for the HCV life cycle.

During the course of this thesis the HCV JFH-1 cell culture system was described and

thus a decision was made to produce an infectious HCV system capable of alcohol

metabolism. To this end, a Huh-7 cell line that is permissive for HCV JFH-1

(described in Appendix II) infection (kindly provided by Professor Eric Gowans,

Basil Hetzel Institute for Medical Research, Adelaide), but does not express

detectable levels of CYP2E1 was used to generate a Huh-7 cell line stably expressing

CYP2E1. This was achieved via the same method in the aforementioned 3.1.1 section.

Briefly, following isolation and expansion of the blasticidin resistant Huh-7 CYP2E1

clones, RNA was isolated, cDNA produced and RT-PCR performed to detect

CYP2E1 mRNA as previously described. Results from these experiments yielded

three positive Huh-7 clones that demonstrated detectable levels of CYP2E1 mRNA

(Fig 3.3A). To ascertain if these three clones were similarly positive for CYP2E1

3 421 5CYP2E1 52 kDa

6

Figure 3.2 Detection of CYP2E1 expression in HCV genomic replicon cell lines +/- CYP2E1. Multiple genomic replicon cell lines express CYP2E1 by (A) RT-PCR and (B) Western blotting. Note that Huh-7, the parent or anti- sense (AS) lines do not express detectable CYP2E1 message or protein.

1. Huh-72. Genomic replicon3. Anti sense - genomic replicon +2E14. Genomic replicon+2E1- clone 25. Genomic replicon+2E1- clone 46. Genomic replicon+2E1- clone 28

β-actin 42 kDa

CYP2E1

GAPDH

B (Western Blot)

A (RT-PCR)

321 5 64

CYP2E1 52 kDa

1 2 3

Figure 3.3 Characterisation of Huh-7 cells expressing CYP2E1. Multiple Huh-7 clones express CYP2E1 by (A) RT-PCR and (B) Western blotting.

1.Huh-7 + 2E1 clone 12.Huh-7 + 2E1 clone 43.Huh-7 + 2E1 clone 5

β-actin 42 kDa

CYP2E1

GAPDH

B (Western Blot)

A (RT-PCR)

1 2 3

59

protein, total protein was harvested and Western blots specific for CYP2E1 were

performed. The result of these Western blots showed detectable levels of CYP2E1

protein in all 3 positive clones (Fig 3.3B). Parental Huh-7 cell lines did not express

CYP2E1 mRNA or protein (data not shown). Taken together, these results

demonstrate that we successfully generated Huh-7 cell lines that are permissive for

HCV JFH-1 and that stably express CYP2E1 at both the mRNA and protein level.

3.1.3 CYP2E1 stable cell lines harbour replicon RNA and are permissive for

HCV JFH-1 infection

In order to study the interactions between alcohol and HCV, we needed to ascertain if

selection of clonally derived CYP2E1 expressing HCV replicon cell lines interfered

with their ability to maintain HCV replication. Furthermore, we also needed to

determine if the Huh-7 CYP2E1 clones remained permissive for HCV JFH-1

infection following the selection process. Immunofluorescence studies (using pooled

anti-HCV serum as the primary antibody) were performed to detect the presence of

HCV antigen in both cell lines (see section 2.5.23.1 for method). HCV genomic

replicon clones deemed to be positive for CYP2E1 expression in section 3.1.1 all

showed 100% positive staining for HCV antigen via immunofluorescence, thus

indicating that these clones maintained the autonomously replicating HCV replicon

(Fig. 3.4A). Parental Huh-7 and genomic replicon cell lines were negative for HCV

antigen staining (data not shown).

The Huh-7 CYP2E1 clones were infected with HCV JFH-1 (MOI=0.1) for 72 hours

and immunofluorescence performed using pooled anti-HCV serum to detect HCV

antigen. At 72 hours post infection approximately 95% of cells were positive for

HCV antigen in all clones (Fig 3.4B), indicating that the Huh-7 clones stably express

CYP2E1 and are permissive for JFH-1 infection. Parental Huh-7 cell lines were

negative for HCV antigen expression (data not shown). These results indicate that

A B

Figure 3.4 Detection of HCV antigens in CYP2E1 stable cell lines. To investigate if stable CYP2E1 cell lines maintained HCV replication, immunofluorescence staining of HCV antigens was used for (A) genomic replicon cells expressing CYP2E1 and (B) Huh-7 cells infected with JFH-1 (MOI=0.1) for 72 hours.

Genomic Replicon (HCV antigen) JFH-1 (HCV antigen)

DAPI DAPI

60

stable CYP2E1 expression does not affect the ability of Huh-7 cells to harbour the

HCV replicon, and does not abrogate the permissiveness of Huh-7 cells for JFH-1

infection. These cell lines can now be used to study the effects of CYP2E1 mediated

alcohol metabolism on HCV biology.

3.2 Characterisation of Stable CYP2E1 Cell Lines

3.2.1 Determination of growth rates for stable CYP2E1 cell lines

HCV replication is linked to cell cycle progression (Munakata et al. 2007), thus it was

important to ascertain if the stable introduction of the CYP2E1 gene had any

deleterious effect on the growth rates of the HCV replicon and Huh-7 CYP2E1 cell

lines created in sections 3.1.1 and 3.1.2, compared to the parent Huh-7 cells.

The growth rates of genomic and sub-genomic HCV replicon cells lines expressing

CYP2E1 were measured using a trypan blue exclusion assay. Both cell lines and their

respective parental cell lines were assayed every 24 hours for a total of 96 hours. At

each 24 hour time point, cell numbers and viability were calculated using a trypan

blue exclusion assay. Figure 3.5A depicts that there was no statistical difference in

the growth rates of the HCV sub-genomic replicon cells expressing CYP2E1

compared to control cell lines. This was also the case for the HCV genomic replicon

cells, as the growth rates of the parental genomic replicon cells compared to the

genomic replicon cells expressing CYP2E1 were not statistically different (Fig 3.5B).

Taken together, these results indicate that cellular proliferation is not effected by the

introduction of the enzyme CYP2E1 into Huh-7 cells, thus indicating that there

should be no direct impact on HCV replication. These results are consistent with

findings in HepG2 cell lines, as CYP2E1 expression in these cell lines had no effect

on their growth rate (Cederbaum et al. 2001). The HCV JFH-1 permissive Huh-7 cell

lines also showed no difference in growth rates compared to the parental controls

(data not shown).

Cel

l num

ber (

x105

)

Figure 3.5 Comparison of growth rates in parental replicon cells versus replicon cells expressing CYP2E1. To investigate if the introduction of CYP2E1 into replicon cell lines affects cellular proliferation, the growth rate of replicon cell lines expressing CYP2E1 was compared to parent replicon cells (not expressing CYP2E1) using the trypan blue exclusion assay. There was no statistical difference in cell growth between sub- genomic replicon cells expressing CYP2E1 and those not (A) or genomic replicon cells expressing CYP2E1 and those not (B). Results indicate that the introduced CYP2E1 does not affect the growth rate of HCV replicon cells.

0

1

2

3

4

5

6

7

8

0 24 48 72 96

Time (hour)

Sub-genomic repliconSub-genomic replicon + 2E1

Genomic replicon

Genomic replicon + 2E1

Cel

l num

ber (×1

05)

0.0

0.5

1.0

2.0

1.5

2.5

3.0

3.5

0 24 48 72 96

Time (hour)

A

B

61

3.2.2 CYP2E1 is metabolically active in the stable cell lines

In order to establish if the introduced CYP2E1 in HCV replicon and Huh-7 cell lines

was metabolically active, a previously established N‐acetyl-p-aminophenol ([APAP]

or [acetaminophen]) toxicity assay was used (Jones et al. 2002). In addition to the

ability of CYP2E1 to metabolise ethanol, it is also able to metabolise acetaminophen

and carbon tetrachloride. In vivo, acute or cumulative overdoses of acetaminophen

can result in severe liver damage and potentially liver failure (Lee 2004). This is

facilitated by the toxic by-products produced in hepatocytes when acetaminophen is

metabolized by CYP2E1. Acetaminophen toxicity can therefore be used in vitro to

establish if the introduced CYP2E1 in the stable cell lines is metabolically active, that

is, if cell death occurs in the presence of acetaminophen, the expressed CYP2E1 is

functional. To test the enzymatic active of CYP2E1, genomic replicon CYP2E1 cells

were treated with acetaminophen (1 and 5 mM) and 48 hours later cells were

harvested and cell viability measured using the CellTiter 96® Non-Radioactive Cell

Proliferation Assay (MTT) described in section 2.2.7. Results from this experiment

showed that genomic replicon cells expressing CYP2E1 were sensitive to

acetaminophen treatment, thus significant cellular toxicity was observed in these cells

in comparison to the control genomic replicon cells that do not express CYP2E1 (Fig

3.6). These results indicate that the expressed CYP2E1 was metabolically functional

and therefore capable of metabolizing ethanol in future experiments. The Huh-7 cells

stably expressing CYP2E1 were also investigated and gave comparable results

(results not shown). These results were not surprising considering the same CYP2E1

construct has been successfully used in other alcohol studies and been shown to be

metabolically active (Cederbaum et al. 2001).

3.2.3 Is CYP2E1 mediated metabolism of ethanol toxic to cells?

It was important that the concentration of alcohol (ethanol) utilized in this model

system was within the physiological relevant range. Concentrations of ethanol used in

Genomic replicon + 2E1Genomic replicon

Figure 3.6 CYP2E1 is metabolically active via acetaminophen toxicity assay. To investigate if CYP2E1 is metabolically active, genomic replicon cells expressing CYP2E1 were treated with 1 and 5 mM acetaminophen and cell survival determined using a MTT assay. Cells expressing CYP2E1 were sensitive to acetaminophen treatment compared to control cells, indicating that the expressed CYP2E1 was metabolically functional.

Acetaminophen (mM)

0

20

40

60

80

100

120

0 1 5

Live

Cel

ls (%

)(M

TT A

ssay

)

62

published in vitro studies range from 1-200 mM (Wu and Cederbaum 2000),

however, beyond 100 mM ethanol exceeds the physiologically relevant range. This

study opted to set the maximum concentration of ethanol at 100 mM. While this is at

the upper end of the physiologically relevant range, it is still suitable for in vitro

studies and has been widely used in other published investigations. Cederbaum et al

have performed extensive investigations into CYP2E1 mediated metabolism of

ethanol in HepG2 cells at concentrations of 100 mM (Wu and Cederbaum 2000; Wu

and Cederbaum 2005). We needed to ascertain if CYP2E1 mediated metabolism of

ethanol induced toxicity in either sub-genomic or genomic replicon cells expressing

CYP2E1 or their respective parental control cell lines. To answer this question cells

were treated with 100 mM ethanol for 72 hours, with the ethanol replaced every 24

hours. At every 24 hour time point cells were harvested and cell viability was

measured using the CellTiter 96® Non-Radioactive Cell Proliferation Assay (MTT)

described in section 2.2.7. Results showed that there was no significant difference in

cell viability between the ethanol treated replicon cells that expressed CYP2E1 and

the control cells that did not. Figure 3.7 shows that there was no significant toxicity

noted in sub-genomic replicon (Fig 3.7A) or genomic replicon (Fig 3.7B) cells

expressing CYP2E1 while incubated in the presence of ethanol (100 mM). These

results indicate that CYP2E1 metabolism of ethanol is not toxic to either the sub-

genomic or genomic replicon cells. However, at concentrations greater than 150 mM

early stages of toxicity were visible under the microscope (results not shown). The

CYP2E1 Huh-7 cells permissive for JFH-1 infection that were generated at a later

stage during the course of this thesis, were not assayed for ethanol toxicity, as

treatment with 100 mM showed no toxicity at the cellular level.

3.3 Discussion

There are numerous clinical studies investigating the effects of alcohol consumption

on liver disease progression and response rates to IFN-α treatment in persons

Figure 3.7 CYP2E1 metabolism of ethanol is not toxic to replicon cells. To establish if ethanol metabolism has any toxic effects on replicon cells, HCV replicon cell lines expressing CYP2E1 were treated with or without ethanol (100 mM) every 24 hours and cell death measured using a MTT assay. No significant toxicity was noted in sub-genomic replicon (A) or genomic replicon (B) cells expressing CYP2E1 while incubated in the presence of ethanol (100 mM). Results indicate that CYP2E1 metabolism is not toxic to replicon cells.

72

Sub-genomic replicon- EtOH

Sub-genomic replicon + 2E1 + EtOH

Genomic replicon- EtOH

Genomic replicon + 2E1 + EtOH

Time (hour)

0102030405060708090

100Li

ve C

ells

(%)

(MTT

Ass

ay)

24 48

Time (hour)

0

1020

30

40

5060

70

80

90

100

Live

Cel

ls (%

)(M

TT A

ssay

)

24 48 72

A

B

72

63

chronically infected with HCV. However, there are limited in vitro studies in this

area, primarily due to a lack of appropriate model systems. Hence, the molecular

mechanisms by which alcohol consumption accelerates the disease course of CHC

and decreases the efficacy of IFN-α remain elusive. The model system generated and

characterised in this chapter signifies a significant advancement for this area of

research and provides a valuable tool to enable further investigations into the effects

of alcohol metabolism on HCV molecular biology and viral host interactions.

CYP2E1 is a member of the cytochrome P450 family of enzymes and is able to

metabolise and activate a number of substrates, including ethanol, carbon

tetrachloride, acetaminophen and N-nitrosodimethylamine (Caro and Cederbaum

2004). As discussed previously in chapter 1, there are two alcohol metabolizing

pathways (ADH and CYP2E1) (Lieber 2004). ADH mediated metabolism is generally

activated by acute alcohol consumption, however, in situations where alcohol

consumption is chronic, the majority of alcohol is metabolized via CYP2E1.

Furthermore, in comparison to ADH, CYP2E1 metabolism of alcohol produces

significantly higher levels of ROS. Moreover, alcohol induced liver damage has been

shown to correlate with increased CYP2E1 levels and the ROS species that are

produced during the catalytic cycle of CYP2E1 have been implicated as the cause of

this liver damage (Nanji et al. 1994; Morimoto et al. 1995). While other studies have

created cell lines that express either ADH or CYP2E1, the main focus of this

investigation was chronic alcohol (ethanol) treatment and the effects of ROS on HCV

and host cell interactions. Thus the model system generated in this thesis is based on

CYP2E1 mediated metabolism of ethanol. However, for future investigations it may

be helpful to include both ADH and CYP2E1 in order to have a more complete

repertoire of alcohol metabolizing enzymes, as this would allow for the investigation

of the effects of both acute and chronic ethanol treatment. Attempts were made to

produce Huh-7 cell lines expressing both ADH and CYP2E1, however, expression of

both enzymes was toxic for reasons that remain unknown. As such, this model system

64

was not pursued. The CYP2E1 expression plasmid (pcDNA-2E1) used in this study,

was the same construct used by Cederbaum et al to produce the HepG2 cell lines that

stably express CYP2E1 (E47 cells) (Mari and Cederbaum 2000). Hence, this CYP2E1

expression system has been extensively validated and characterised previously.

The model system generated in this chapter enables the use of both the HCV replicon

system and the infectious JFH-1 system. The HCV infectious model system allows for

the investigation of the effects of alcohol metabolism on the full life cycle of HCV,

something that was previously not possible. The Huh-7 cell lines stably expressing

CYP2E1 produced in this thesis are able to metabolise ethanol, as the introduced

CYP2E1 protein is capable of metabolizing acetaminophen, resulting in a cytotoxic

effect. It was also important to ascertain if the CYP2E1 mediated metabolism of

ethanol resulted in cellular toxicity. The metabolism of ethanol at the threshold

concentration of 100 mM did not induce any toxicity, thus portraying the viability of

this model to study the effects of ethanol metabolism in vitro. While 100 mM of

ethanol is high (in terms of blood alcohol levels), it is still in the physiologically

relevant range and has been used in other in vitro investigations. The expression of

CYP2E1 in the cells described in this chapter also induced no growth abnormalities,

as CYP2E1 expressing cell lines displayed comparable growth rates to their

respective parental cell lines. Moreover, the expression levels of CYP2E1 in this

system are most likely well below the levels observed in vivo. As mentioned

previously, chronic alcohol consumption induces CYP2E1 expression in the liver,

therefore in the liver of a person chronically consuming alcohol, the levels of

CYP2E1 are significantly increased and would greatly surpass the levels seen in this

model system. Most importantly, selection of stable CYP2E1 expressing clones did

not interfere with the ability of these cell lines to harbour HCV replication, as both the

genomic and sub-genomic replicon cell lines maintained high levels of HCV

replication and the Huh-7 cells displayed almost 100% of cells infected at 72 hours

post infection (MOI=0.1), which is equivalent to the standard infection rate routinely

65

seen in our laboratory. Thus the Huh-7 cell lines generated in this chapter that stably

express CYP2E1, behave as the parental cell lines.

An alternative to our Huh-7 CYP2E1 model system would be the use of primary

hepatocytes. Primary hepatocytes do express both CYP2E1 and ADH and recently it

has been published that primary hepatocytes are permissive for HCV infection

(Podevin et al.). As such, this system would be advantageous to use as it requires no

re-introduction of alcohol metabolizing enzymes and primary hepatocytes represent a

more physiologically relevant system. However, there are limitations associated with

using primary hepatocytes. They are notoriously difficult to maintain in culture and

financially their use was not an option for this study as they are expensive to purchase

and isolate. Therefore, primary hepatocytes are not a viable option for investigating

the interactions between HCV, alcohol and IFN.

There are two studies that investigated the effects of alcohol on HCV replication

using HCV replicon cells that did not appear to have detectable levels of CYP2E1 or

ADH (Zhang et al. 2003; Trujillo-Murillo et al. 2007). These studies are somewhat

controversial, as it remains to be seen how alcohol metabolism can occur in the

absence of CYP2E1 or ADH. Therefore indicating that these studies are really

investigating CYP2E1/ADH-independent effects of alcohol on HCV replication and

thus making this an incomplete model system to investigate the effects of alcohol

metabolism on the HCV life cycle. There has been some notable work done with a

hepatoma cell line stably expressing both the HCV core protein and CYP2E1. This

model has been used to show that oxidative stress is synergistically enhanced in the

presence of core and CYP2E1 mediated metabolism of ethanol. Furthermore HCV

core has been shown to induce destabilization of the mitochondrial electron transport

chain (Korenaga et al. 2005; Otani et al. 2005). This model system is useful for

studying the combined effects of CYP2E1 mediated ethanol metabolism and core

expression on hepatocyte homeostasis, however, these studies should be interpreted

66

with caution as the complete repertoire of HCV proteins and RNA replication are

absent.

In summary, we have characterised multiple Huh-7 cell lines that stably express

CYP2E1. These cell lines are able to metabolise ethanol and harbour HCV

replication. This model system enables the utilization of both current HCV models,

thus allowing for the first time, the investigation of the effects of ethanol metabolism

on the complete HCV life cycle. This model system will be used for all studies

performed in chapters 4, 5 and 6.

67

Chapter 4

The Effect of Alcohol Metabolism on HCV Replication

4.1 Introduction

It is well established that alcohol consumption contributes significantly to CHC

progression and it is likely that alcohol metabolism and HCV act synergistically to

cause this exacerbation of liver disease. Despite the strong clinical evidence

indicating that alcohol metabolism increases disease progression in chronically

infected HCV patients, the molecular mechanisms responsible for this remain to be

established. There is strong in vivo evidence to suggest that HCV replication is

increased in HCV infected patients consuming alcohol. While the pathogenesis of

alcohol exacerbated liver disease in CHC is mostly likely multifactorial, the clinical

observation of increased HCV viral load may be one mechanism (Oshita et al. 1994;

Pessione et al. 1998).

This chapter describes the use of the in vitro model system created in chapter 3, to

investigate the hypothesis that alcohol (ethanol) metabolism increases HCV

replication. The model systems used for this investigation consist of the HCV replicon

system and the infectious HCVcc model. Using these in vitro models we hope to

elucidate in part, the molecular mechanisms responsible for the increased liver disease

progression in HCV patients that consume alcohol.

4.2 The Effect of Ethanol metabolism on HCV Replication

4.2.1 Ethanol metabolism by CYP2E1 increases HCV replication in replicon cells

To investigate the effects of alcohol metabolism on HCV replication in vitro, the

HCV sub-genomic and genomic replicon cells expressing CYP2E1 were cultured in

68

the presence of varying concentrations of ethanol (0-100 mM) for a total of 72 hours,

with the ethanol replaced every 24 hours. At 72 hours post ethanol treatment total

RNA was extracted using Trizol® and RT-PCR then performed to generate cDNA,

which was subsequently used in real-time PCR to measure HCV RNA levels, with

results normalized to RPLPO levels. HCV RNA abundance was expressed as a fold

change relative to no treatment control, (i.e, no ethanol). Figure 4.1A depicts that

HCV RNA levels in sub-genomic replicon cells expressing CYP2E1 were

significantly increased in the presence of ethanol (50-100 mM), in a dose response

manner. HCV RNA levels were similarly increased in genomic replicon cells

expressing CYP2E1, however, the increase appeared to be bi-phasic and occured over

a broad range of concentrations, with HCV replication enhanced between 10-100 mM

of ethanol treatment. These results demonstrate that the treatment of both sub-

genomic and genomic replicon cells expressing CYP2E1 with ethanol significantly

enhances HCV replication, which is consistent with known clinical observations

(Pessione et al. 1998).

Next we investigated if the ethanol induced increase in HCV replication was

dependent on CYP2E1 mediated metabolism of ethanol. The parental sub-genomic

and genomic replicon cell lines that do not express any detectable levels of CYP2E1,

were cultured in the presence of ethanol (0-100 mM) for 72 hours, with the ethanol

replaced every 24 hours as described above. RNA levels were measured as described

previously. In the absence of CYP2E1 expression, the treatment of HCV replicon

cells with ethanol had no effect on HCV RNA levels. Treatment of sub-genomic (Fig

4.2A) and genomic (Fig 4.2B) replicon cells with ethanol lead to no observable

modulation of HCV replication, indicating that the effects seen in figure 4.1 were as a

direct result of CYP2E1 mediated metabolism of ethanol.

To further validate and confirm the role of CYP2E1 in the ethanol induced increase in

HCV replication, two known inhibitors of CYP2E1 were used: Diallyl sulfide (DAS)

0 10 25 50 75 100

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Figure 4.1 Ethanol modulates HCV replication in presence of CYP2E1 mediated metabolism. Sub-genomic (A) and genomic replicon (B) cells expressing CYP2E1 were treated with 0-100 mM ethanol for 72 hours, with the ethanol replaced every 24 hours. At 72 hours total RNA was extracted and real-time PCR performed to measure HCV RNA levels, RPLPO was used as a control and HCV RNA levels were expressed as a fold change relative to no treatment. In the presence of CYP2E1, ethanol treatment significantly increases HCV replication in both genomic (A) and sub-genomic replicon (B)cells expressing CYP2E1.

********p<0.01

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Figure 4.2 In the absence of CYP2E1 ethanol does not modulate HCV replication. Genomic replicon (A) and sub-genomic repliconcells (B) were treated with 0-100 mM ethanol for 72 hours, with the ethanol replaced every 24 hours. At 72 hours post treatment total RNA was extracted and real-time PCR performed to quantitate HCV RNA levels, RPLPO was used as a control and HCV RNA levels were expressed as a fold change relative to no treatment. Ethanol treatment had no effect on HCV replication in the absence of CYP2E1, indicating that un-metabolised ethanol does not modulate HCV replication.

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A Sub-genomic Replicon + 2E1 B Genomic Replicon + 2E1

69

and 4-methylpyrazole (4MP). DAS is known to inactivate CYP2E1 (Brady et al.

1991) and 4-methylpyrazole (4MP) has been demonstrated to specifically inhibit the

enzymatic ability of CYP2E1 to oxidize ethanol (Feierman and Cederbaum 1985).

Both of these inhibitors were used in combination with ethanol to investigate if the

ethanol induced increase in HCV replication is dependent on CYP2E1 mediated

metabolism of ethanol. HCV genomic replicon cells expressing CYP2E1 were treated

in the presence and absence of ethanol (100 mM) and the presence and absence of

DAS (10 mM) and 4MP (10 mM). The concentration of the inhibitors was determined

from previous studies in the literature (Song 1996; Wu and Cederbaum 1996) and was

also based on a cell viability assay, in which titrated quantities of the inhibitors were

used to investigate the toxicity of these inhibitors on Huh-7 cells (data not shown). At

24 hours post treatment, total RNA was harvested and real-time PCR used to

quantitate HCV RNA levels. RPLPO was used as a control and HCV RNA levels

were expressed as a fold change relative to no treatment. Results demonstrated that

the addition of DAS selectively blocked the ethanol induced increase in HCV

replication (Fig 4.3A). The DAS treatment of cells did not induce toxicity and the

slight observable decrease in HCV RNA levels in the cells treated with DAS alone

was not significant. The specific inhibitor of CYP2E1, 4MP (Fig 4.3B) showed a

similar blockage of the ethanol induced increase in HCV replication levels.

Collectively this data indicates that in our in vitro model, the ethanol induced increase

in HCV replication is dependent on CYP2E1 mediated metabolism of ethanol.

4.3 Establishing a Molecular Mechanism For the Ethanol Induced

Increase in HCV Replication

4.3.1 Ethanol metabolism increases oxidative stress in HCV replicon cells

Having clearly established that ethanol metabolism increases HCV replication, the

next step was to investigate potential molecular mechanisms for this effect. It is well

established that ethanol metabolism leads to increased cellular oxidative stress both in

A

B

Figure 4.3 The ethanol induced increase in HCV replication is dependent on CYP2E1 mediated metabolism of ethanol. To determine if the increase in HCV replication was specific for CYP2E1 metabolism of ethanol, genomic replicon cells expressing CYP2E1 were treated with and without ethanol (100 mM) and inhibitors of CYP2E1 (A) DAS (10 mM) and (B) 4MP (10 mM), for 24 hours. At 24 hours post treatment total RNA was harvested and real-time PCR performed to measure HCV RNA levels, RPLPO was used as a control and HCV RNA levels were expressed as a fold change relative to no treatment. Results demonstrated that CYP2E1 inhibitors DAS (A) and 4MP (B)both selectively block the increase in HCV replication induced by ethanol metabolism, indicating that the ethanol induced increase in replication is dependent on CYP2E1.

- +

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70

vivo and in vitro (Cederbaum et al. 2001), thus we sought to determine if oxidative

stress was playing a role in the ethanol induced increase in HCV replication. Firstly,

we needed to ascertain if CYP2E1 mediated metabolism of ethanol led to increased

levels of oxidative stress in HCV replicon cells. Both sub-genomic and genomic

replicon cells expressing CYP2E1 were treated with and without ethanol (100 mM)

and the cellular ROS levels were measured using the cell permeable oxidation

sensitive fluorogenic precursor DCFDA. In the sub-genomic (Fig 4.4A) and genomic

replicon cells (Fig 4.4B) treated with ethanol, there was a significant shift in the

relative fluorescence peak, indicating that an increase in the production of cellular

oxidative stress had occurred. Taken together, these results depict that CYP2E1

mediated ethanol metabolism is able to increase oxidative stress in both sub-genomic

and genomic replicon cells expressing CYP2E1.

4.3.2 Anti-oxidant treatment decreases HCV replication

It is well documented that ethanol metabolism induces a state of intracellular

oxidative stress, and this was indeed what we observed in our in vitro model system

(section 4.3.1). Furthermore, the generation of hepatic oxidative stress due to HCV

replication is well established. Thus we hypothesized that the mechanism responsible

for the increase in HCV replication in the presence of ethanol metabolism could be

the combined oxidative stress produced from ethanol metabolism and HCV

replication. To investigate this hypothesis, genomic replicon cells expressing CYP2E1

were treated with the anti-oxidant N-Acetyl-Cysteine [(NAC) 5 & 10 mM] in

combination with ethanol (100 mM). Treatment of cells with NAC (5-10 mM) was

not toxic to cells (data not shown). Cells were treated for 72 hours, with the ethanol

and NAC replaced at every 8 hour time point. At 72 hours post treatment, total RNA

was extracted using the previously described method and RNA levels quantitated. As

in previous experiments HCV RNA levels increased in the presence of ethanol, (Fig

4.5). However, this ethanol mediated increase was blocked when cells were incubated

Figure 4.4 Metabolism of ethanol by CYP2E1 increases oxidative stress in HCV replicon cells. To determine if metabolism of ethanol by CYP2E1 in HCV replicon cells results in an increase in oxidative stress we measured cellular ROS levels using the cell permeable, oxidation sensitive fluorogenic precursor DCFDA following incubation of (A) subgenomicHCV replicon cells expressing CYP2E1 and genomic replicon cells (B) with 100 mM ethanol. In the presence of ethanol there is a shift in the relative fluorescence peak indicating an increase in the production of cellular oxidative stress in both genomic and sub-genomic replicon cells expressing CYP2E1.

Relative Fluorescence

- EtOH

+EtOH

B

A


- EtOH

+EtOH

- EtOH

+EtOH


Figure 4.5 Anti-oxidants decrease HCV replication. To investigate if oxidative stress can modulate HCV replication, genomic HCV replicon cells expressing CYP2E1 and the parent replicon cell line were incubated with 5 or 10 mM of the anti-oxidant N-Acetyl-C (NAC) with or without ethanol (100 mM). At 48 hours post treatment total RNA was extracted and HCV RNA levels were quantitated by real-time PCR. In the presence of NAC the ethanol induced increase in HCV replication was blocked to approximately 50% below baseline. Similar results were seen for cells incubated in the absence of ethanol and in sub-genomic replicon cells and over multiple different lines. These results suggest that oxidative stress plays a role in HCV replication.

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in the presence of both ethanol and NAC. It was also interesting to note that the

addition of NAC (in the absence of ethanol and CYP2E1) also decreased HCV RNA

levels to approximately 50% of baseline HCV RNA levels. These results strongly

suggest that the ethanol mediated increase in HCV replication is mediated by

oxidative stress. Furthermore, the sensitivity of HCV replication to NAC in the

absence of CYP2E1 or ethanol suggests that HCV induced oxidative stress may be

advantageous to HCV replication.

4.3.3 Acetaldehyde does not modulate HCV replication

As mentioned previously in chapter 1, one of the by products of ethanol metabolism,

in addition to oxidative stress, is acetaldehyde. Thus it was important to examine if

acetaldehyde was playing a role in the ethanol induced increase in HCV replication.

This was investigated via the treatment of genomic replicon cells expressing CYP2E1

with acetaldehyde (100 & 200 µM) for 24 hours. The concentration of acetaldehyde

was based on previous studies documented in the literature (Potter et al. 2011). At 24

hours post acetaldehyde treatment total RNA was extracted and quantitated as

previously described. HCV RNA levels were expressed as a fold change relative to no

treatment. Results from these experiments documented that there was no significant

modulation of HCV RNA levels at either 100 µM or 200 µM treatment with

acetaldehyde (Fig 4.6). This data strongly suggests that acetaldehyde does not play a

role in the ethanol induced increase in HCV replication.

4.3.4 Ethanol metabolism does not modulate HCV IRES activity

The HCV IRES precedes the initiation codon of the HCV polyprotein. It is essential

for the binding of the host 40S ribosomal subunit to initiate translation of the viral

polyprotein. Therefore we wanted to investigate if ethanol metabolism could

potentiate HCV IRES activity. This could potentially increase translation of the HCV

polyprotein, resulting in an increased pool of HCV proteins that would culminate in

Figure 4.6 Acetaldehyde does not modulate HCV replication. To investigate if acetaldehyde was playing a role in the ethanol induced increase in HCV replication, genomic replicon cells expressing CYP2E1 were incubated in the presence of 100-200 μM of acetaldehyde for 24 hours. Total RNA was then extracted and real-time PCR used quantitateHCV RNA levels. RPLPO was used as a control and HCV RNA levels were expressed as a fold change relative to no treatment. These results demonstrated that acetaldehyde treatment had no observable effect on HCV replication.

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increasesed replication. A construct containing the HCV IRES linked to the luciferase

gene [pRL-HL: (Appendix VI)] was transfected into genomic replicon cells

expressing CYP2E1. These cells were then treated with 100 mM of ethanol for up to

240 minutes. Total cellular lysate was then harvested and a luciferase assay

performed, with rennilla luciferase used as a transfection control. Results were

expressed as a fold change relative to no treatment control. These experiments

demonstrated that ethanol treatment has no measurable effect on luciferase output

(Fig 4.7), suggesting that ethanol does not modulate the activity of the HCV IRES in

vitro.

4.3.5 Exogenous H2O2 decreases HCV replication

Our previous results suggest that oxidative stress potentiates HCV replication. Thus

we deemed it necessary to determine if exogenously applied oxidative stress could

similarly modulate HCV replication. This was investigated via H2O2 treatment of

genomic replicon cells expressing CYP2E1. Briefly genomic replicon cells expressing

CYP2E1 were treated with H2O2 (50-200 mM) for 24 hours and HCV RNA levels

quantitated as previously described. Results from these experiments demonstrated that

treatment of genomic replicon cells expressing CYP2E1 with H2O2 significantly

decreased HCV replication by approximately 50% at all concentrations of H2O2 (Fig

4.8). These results were unexpected, as we had previously observed a decrease in

HCV RNA levels using anti-oxidants. Therefore, exogenous oxidative stress induced

the opposite effect to the endogenous oxidative stress produced from alcohol

metabolism. This will be discussed further in section 4.6 of this chapter.

Figure 4.7 Ethanol metabolism does not modulate HCV IRES activity. To investigate if ethanol metabolism was able to modulate HCV IRES activity, genomic replicon cells expressing CYP2E1 were transiently transfected with pRL-HL for 24 hours and then incubated in the presence of ethanol (100 mM) for 30-240 minutes. Total cellular lysate was extracted and a lucifrease assay performed to measure HCV IRES lucifrease activity. Renilla luciferase was used as a transfection control and results were expressed as a fold change relative to no treatment control. These results indicated that ethanol metabolism does not modulate IRES luciferase output, suggesting that this is not the mechanism by which ethanol modulates HCV replication.

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Figure 4.8 H2O2 decreases HCV replication. To investigate if exogenous oxidative stress could modulate HCV replication, H2O2 (50-200 mM) was applied for 1 hour to genomic replicon cells expressing CYP2E1. 24 hours post H2O2 treatment total RNA was extracted and real-time PCR used to quantitate HCV RNA levels, RPLPO was used as a control and HCV RNA levels were expressed as a fold change relative to no treatment. Exogenous H2O2 significantly decreased HCV replication in genomic replicon cells.

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4.4 The Effect of Ethanol Metabolism on HCVcc

4.4.1 Ethanol metabolism increases JFH-1 replication

When this thesis commenced the infectious HCVcc had only just been described. As

such, it took some time before it was available for use in our laboratory and further

time was required for optimization. Thus all of the first ethanol experiments were

performed using the HCV replicon model system. Using this system we were able to

show that ethanol metabolism by CYP2E1 significantly increases HCV replication.

We then sought to investigate the effects of ethanol metabolism on the complete life

cycle of HCV through the use of the infectious HCV JFH-1 system. To investigate

this, Huh-7 cells permissive for HCV infection and expressing CYP2E1 (these cells

were characterised in chapter 3) were pre-treated with ethanol (0-100 mM) for 24

hours, followed by infection with JFH-1 (MOI=0.1) for 3 hours. The ethanol was

replaced at every 24 hour time point. After 72 hours of ethanol treatment (Fig 4.9A),

and at each 24 hour interval (Fig 4.9B), total RNA was extracted using Trizol® and

RT-PCR performed to generate cDNA, which was subsequently used in real-time

PCR to measure HCV RNA levels, with results normalized to RPLPO levels. HCV

RNA levels were expressed as a fold change relative to no treatment control. Results

clearly demonstrated that ethanol metabolism significantly increases HCV replication

at concentrations of ethanol ranging from 10-100 mM (Fig 4.9A). The peak of this

increase in HCV RNA occurred at approximately 72 and 96 hours post ethanol

treatment (Fig 4.9B). These results indicate that ethanol metabolism via CYP2E1

significantly enhances HCV (JFH-1) replication in the context of the complete HCV

life cycle.

4.4.2 Pre treatment with ethanol is required to increase HCV JFH-1 replication

To investigate if the ethanol induced increase in JFH-1 replication could be observed

when ethanol was added post JFH-1 infection, Huh-7 cells expressing CYP2E1 were

treated with ethanol (10 and 50 mM) pre and post JFH-1 infection. The ethanol was

replaced every 24 hours and at 72 hours post infection, total RNA was harvested and

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Figure 4.9 Ethanol metabolism increases JFH-1 replication. To investigate if ethanol metabolism modulates JFH-1 replication, Huh-7 cells expressing CYP2E1 were pre-treated with ethanol (0-100 mM) for 24 hours followed by infection with JFH-1 for 96 hours (MOI=0.1). Ethanol was replaced at every 24 hour time point and at 96 hours post infection (A) and at every 24 hour time point (B) total RNA was extracted and real-time PCR used quantitate HCV RNA levels, RPLPO was used as a control and HCV RNA levels were expressed as a fold change relative to no treatment. Results demonstrated that JFH-1 replication was significantly increased at all concentrations of ethanol (A) and this increase occurred between 72-96 hours post infection (B).

Control

EtOH (mM)

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74

measured as previously described. HCV RNA levels were expressed as a fold change

relative to no treatment control. Figure 4.10A showed that ethanol pre-treatment of

Huh-7 cells results in an increase in JFH-1 replication, which was comparable to

previous findings in figure 4.4. However, ethanol post treatment did not modulate

JFH-1 replication (Fig 4.10B). These results show that in order to facilitate ethanol

induced enhancement of JFH-1 replication, pre-treatment of cells with ethanol is

required. These results suggest that priming the cell prior to infection with JFH-1 is

required for the increase in HCV replication.

4.4.3 Exogenous H2O2 decreases HCV JFH-1 replication

Our previous results in section 4.3.5 showed that exogenously applied H2O2 induced a

significant decrease in HCV replication in HCV genomic replicon cells expressing

CYP2E1. Thus we wanted to determine the effect of H2O2 treatment on the infectious

HCV JFH-1 system. This was investigated via H2O2 treatment of Huh-7 cells

expressing CYP2E1, in which a HCV JFH-1 infection had been established. Briefly,

Huh-7 cells expressing CYP2E1 were infected with JFH-1 (MOI=0.1) for 72 hours.

This time point was chosen to ensure greater than 90% of cells were positive for HCV

infection. At 72 hours post infection, cells were treated with H2O2 (50-200 mM) for

24 hours, followed by HCV RNA quantitation as previously described. Results from

these experiments demonstrated that treatment of JFH-1 infected Huh-7 cells with

H2O2 (200 mM) decreased replication by more than approximately 50%. Furthermore,

treatment with H2O2 (100 mM) decreased HCV RNA levels even more markedly, to

around 40% (Fig 4.11). These results demonstrated that the exogenous induction of

oxidative stress via H2O2 treatment significantly decreased HCV JFH-1 replication, in

a similar manner to that observed with the HCV genomic replicon system (see section

4.3.5). These findings will be discussed in greater detail in section 4.6.

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Figure 4.10 Pre-treatment of ethanol is required to enhance JFH-1 replication via ethanol metabolism. Huh-7 cells expressing CYP2E1 were pre-treated with ethanol (10-50 mM) (A) or treated with ethanol post JFH-1 infection (B). The ethanol was maintained for a further 72 hours and replaced at every 24 hour time point. At 72 hours post infection total RNA was harvested and real-time PCR performed to quantitate HCV RNA levels, RPLPO was used as a control and HCV RNA levels were expressed as a fold change relative to no treatment. Pre-treatment with ethanol is necessary to increase in JFH-1 replication via CYP2E1 mediated metabolism of ethanol (A), as treatment post JFH-1 infection, does not modulate JFH-1 RNA levels (B).

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Figure 4.11 H2O2 decreases HCV JFH-1 replication. To investigate if exogenous oxidative H2O2 could modulate HCV JFH-1 replication, Huh-7 cells expressing CYP2E1 were infected with JFH-1 (MOI=0.1) for 72 hours. At 72 hours post infection, H2O2 (10-200 mM) was applied for 1 hour. At 24 hours post H2O2 treatment total RNA was extracted and real-time PCR used to quantitate HCV RNA levels, RPLPO was used as a control and HCV RNA levels were expressed as a fold change relative to no treatment. Exogenous H2O2 significantly decreased HCV JFH-1 replication.

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4.4.4 NAC treatment decreases HCV JFH-1 replication

To ascertain if NAC treatment can similarly modulate HCV replication in the context

of the complete HCV life cycle, Huh-7 cells were infected with JFH-1 (MOI=0.1) for

3 hours, followed by removal of virus innoculant and replacement with media

containing NAC (5 mM). At 24 hours post treatment, total RNA was extracted and

HCV RNA levels quantitated as previously described. Results demonstrated that the

addition of NAC significantly reduced HCV RNA levels to less than 50% of the

control cells (Fig 4.12). This suggests that oxidative stress is important for the full life

cycle of HCV replication. Collectively, results from this section and the previous

section (4.3.2) indicate that oxidative stress may play a pivotal role in the ethanol

induced increase in HCV replication and are also indicative of HCV using oxidative

stress to its replicative advantage.

4.5 The Oxidative Stress Sensitive Transcription Factor STAT3

4.5.1 Rationale for investigating the involvement of STAT3 in the ethanol

induced increase in HCV replication

As discussed in chapter 1, the transcription factor STAT3 has been documented to be

sensitive to the oxidative stress produced during HCV replication (Waris et al. 2005).

This observation lead us to hypothesize that STAT3 activation may be significantly

enhanced in the presence of alcohol metabolism and HCV replication, through a

synergistic increase in oxidative stress. This increase in STAT3 activation could

potentially allow STAT3 to induce transcription of STAT3 dependent genes that

could subsequently create a cellular environment that is favourable for HCV

replication.

*

0.0

0.5

1.0

1.5

*P=0.04

0 10

Fold

Cha

nge

in H

CV

Rep

licat

ion

(Nor

mal

ised

to R

PLP

O)

NAC (10 mM)

Figure 4.12 The anti-oxidant NAC decreases HCV JFH-1 replication. To investigate if oxidative stress can modulate JFH-1 replication, Huh-7 cells were infected with JFH-1 for 3 hours, followed by treatment with NAC (10 mM). Total RNA was extracted 24 hours later and real-time PCR used quantitate HCV RNA levels, RPLPO was used as a control and HCV RNA levels were expressed as a fold change relative to no treatment. In the presence of NAC JFH-1 replication was reduced by approximately 50%, indicating that oxidative stress plays a role in the enhancement of HCV replication for the infectious JFH-1 clone.

76

4.5.2 The oxidative stress sensitive transcription factor STAT3 plays a role in the

ethanol induced increase in HCV replication

4.5.2.1 Ethanol metabolism increases STAT3 activation

It has been shown previously that the transcription factor STAT3 is sensitive to

oxidative stress. Thus we hypothesized that the oxidative stress produced by ethanol

metabolism could lead to enhanced STAT3 activation, specifically by increasing

STAT3 phosphorylation. Enhanced STAT3 gene transcription could potentially be

one of the mechanisms by which ethanol metabolism increases in HCV replication.

To investigate this hypothesis, the activation status of STAT3 was measured in the

presence of ethanol metabolism and IFN-α treatment. The inclusion of IFN-α

treatment to these experiments was due to the fact that IFN-α is a potent activator of

STAT3 and we were attempting to mimic conditions that would be found in vivo in

the liver of a HCV infected patient consuming alcohol, as IFN-α is produced

endogenously during a viral infection. These experiments were performed using

genomic replicon cells expressing CYP2E1. Cells were treated with ethanol (100

mM) for 24 hours, followed by an IFN-α (150 IU/ml) time course for up to 300

minutes. Total protein was then extracted and Western blots specific for STAT3-

Y705 and STAT3-S727 phosphorylation were performed. Phosphorylation at Y705 is

necessary for STAT3 to form homo and heterodimers and translocate into the nucleus.

Phosphorylation at S727 increases the transcriptional activation ability of STAT3

once inside the nucleus. Levels of β-actin were also detected to control how much

protein was loaded into each well. Results from at least 3 independent experiments

showed that STAT3-Y705 phosphorylation was significantly increased in the

presence of ethanol metabolism, most predominantly at 20, 30 and 60 minutes post

IFN-α treatment (Fig 4.13A) and was confirmed quantitatively by densitometry

analysis (Fig 4.13B). Phosphorylation at this residue should result in increased

translocation to the nucleus of STAT3 dimers. We also investigated if STAT3-S727

phosphorylation was similarly increased in the presence of ethanol metabolism.

Figure 4.13 Ethanol metabolism increases STAT3-Y705 phosphorylation. To determine if ethanol metabolism affects the activation of STAT3, genomic replicon cells expressing CYP2E1 were cultured in the presence and absence of ethanol (100 mM) and treated with IFN-α (150 IU/ml) over a 300 minute time course. Total cell lysates were then recovered and immunoblots probed with specific STAT3-Y705 and β-actin specific antibodies. Results from 3 independent Western blot experiments showed a significant increase in STAT3-Y705 phosphorylation levels at all time points in the cells treated with ethanol (A). Densitometry analysis of these Western blots showed that the increase in phosphorylation was most noticeable at 20, 30, 60 minutes post IFN-α treatment (B).

STAT3-Y705 79 kDa

β-actin 42 kDa

A

B

0 10 20 IFN-α Time (mins) 30 60 300

- EtOH

0 10 20 30 60 300

+ EtOH

0

5

10

15

20

25

0 10 20 30 60 300

EtOH (100 mM)

Control

STA

T3-Y

705

/ β-a

ctin

(arb

itrar

y va

lue)

IFN-α Time (mins)

Densitometry Analysis (NIH Image)

77

Again, HCV genomic replicon cells expressing CYP2E1 were used and experimental

conditions were the same as previously mentioned, however, this time immunoblots

were carried out specifically for STAT3-S727. Results from at least three independent

experiments portrayed that STAT3-S727 phosphorylation levels were sustained for a

more prolonged time period in the presence of ethanol metabolism. Densitometry

analysis showed that the increase in phosphorylation was most marked at 20, 30 and

60 minutes post IFN-α treatment (Fig 4.14 A&B). Taken together, these results

strongly suggest that ethanol metabolism enhances STAT3 phosphorylation at Y705

and S727 residues, which are both integral in enabling STAT3 to be transcriptionally

active. Thus it is possible that in the presence of ethanol metabolism, increased

STAT3 activation could lead to an increase in the expression of STAT3 dependent

genes that could in turn facilitate and enhance HCV replication.

4.5.2.2 Ethanol metabolism increases STAT3 promoter activity

To investigate if the ethanol induced increase in STAT3 phosphorylation translated to

a functional increase in STAT3 transcriptional activity, a STAT3 luciferase construct

[(pSTAT3-Luc):Appendix VII] was used to measure the activity of the STAT3

promoter elements in the presence of ethanol metabolism. Genomic replicon cells

expressing CYP2E1 were transfected with pSTAT3-luc and cultured in the presence

of ethanol for a further 48 hours. Total cellular lystate was then recovered and a

luciferase assay performed to measure STAT3 luciferase output. Results were

normalized to Renilla luciferase and were expressed as a fold change relative to no

ethanol control. These results depict that ethanol metabolism significantly increases

STAT3 directed luciferase output (Fig 4.15), thus suggesting that there is increased

activated STAT3 translocating into the nucleus and binding the STAT3 promoter

elements in the presence of ethanol metabolism. Collectively, section 4.5 documents

that the transcription factor STAT3 could be playing a role in the ethanol induced

increase in HCV replication, as increased activation of STAT3 and increased STAT3

Figure 4.14 Ethanol metabolism increases STAT3-S727 phosphorylation. To determine if ethanol metabolism affects the activation of STAT3, genomic replicon cells expressing CYP2E1 were cultured in the presence and absence of ethanol (100 mM) and treated with IFN-α (150 IU/ml) over a 300 minute time course. Total cell lysateswere then recovered and immunoblots probed with specific STAT3-S727 and β-actin antibodies. Results from 3 independent Western blot experiments showed a significant increase in STAT3-S727 phosphorylation levels at most time points in the cells treated with ethanol (A). Densitometry analysis showed that the increase in phosphorylationoccurred at 20 minutes and was followed by prolonged phosphorylation at 30 and 60 minutes post IFN-α treatment (B).

β-actin 42 kDa

STAT3-S727 79 kDa

B

A

0 10 20 IFN-α Time (mins) 30 60 300

- EtOH

0 10 20 30 60 300

+ EtOH

00 10 20 30 60 300

IFN-α Time (mins)

STA

T3-S

727

/ β-a

ctin

(arb

itrar

y va

lue)

EtOH (100 mM)

Control

5

10

15

20

25

35

40

30


Figure 4.15 Ethanol metabolism increases STAT3 promoter activity. To investigate if ethanol metabolism was able to increase the transcriptional activation ability of STAT3, genomic replicon cells expressing CYP2E1 were transfected pSTAT3-Luc and cultured in the presence of ethanol (0-100 mM) for 48 hours. Total cellular lysate was then harvested and a luciferase assay performed to measure STAT3 luciferase output. Results were expressed as a fold change relative to no treatment control and were normalised to renilla luciferase to control for transfection efficiency. STAT3 luciferase output was significantly enhanced in the presence of ethanol metabolism, suggesting that ethanol metabolism increases the transcriptional activation ability of STAT3.

∗

0

1

2

3

4

5

Rel

ativ

eFo

ld C

hang

e in

STA

T3-L

ucifr

ease

Out

put

(Nor

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ised

to R

enill

a)

*p=0.030

EtOH (mM)

100

78

promoter activity was observed in the presence of ethanol metabolism. Furthermore, it

is feasible that in the presence of ethanol metabolism, STAT3 is activated. This would

then have the down stream effect of STAT3 dependent gene transcription and we

hypothesise that specific STAT3 target genes could create an environment favorable

for enhanced HCV replication. The role of STAT3 in the complete life cycle of HCV

is further explored in chapter 6.

4.6 Discussion

As previously outlined there is significant clinical evidence suggesting that alcohol

consumption exacerbates disease progression in CHC (Seeff et al. 1992; Poynard et

al. 1997; Pessione et al. 1998). The exact molecular mechanisms for this remain

unclear, however, there have been a number of postulated mechanisms, such as - (i)

alcohol-induced increase in HCV RNA replication, (ii) enhancement of HCV quasi-

species complexity, (iii) modulation of the immune system and (iv) synergistic

increases in ROS. This chapter has used an in vitro model system to provide strong

evidence that an alcohol (ethanol) induced increase in HCV RNA may be one of the

contributing factors responsible for the increased rates of CHC progression in persons

that consume alcohol.

Using both the sub-genomic and genomic HCV replicon cell lines that stably express

CYP2E1, we showed that physiological concentrations of ethanol (0-100 mM)

significantly enhanced HCV RNA levels (Fig 4.1A&B). This ethanol induced

increase was shown to be dependent on CYP2E1, as ethanol treatment of the parental

replicon cell lines (Fig 4.2A&B) that do not express any detectable levels of CYP2E1,

showed no observable modulation of HCV RNA levels. Furthermore, we also

observed that treatment of JFH-1 infected Huh-7 cells (that express CYP2E1) also

resulted in a significant increase in HCV RNA levels (Fig 4.9A). This increase in

RNA peaked between 72 and 96 hours post ethanol treatment (Fig 4.9B). This

79

investigation also revealed that pre-treatment with ethanol prior to infection with JFH-

1 was necessary for the ethanol induced increase in JFH-1 replication to occur (Fig

4.10). These results could be in part explained by the fact that HCV may use oxidative

stress for its replicative advantage and thus an established state of oxidative stress,

that is achieved by pre-treatment with ethanol, is necessary to enhance HCV

replication. Treatment of genomic replicon cells expressing CYP2E1 with ethanol and

specific CYP2E1 inhibitors, DAS (Fig 4.3A) and 4MP (Fig 4.3B) lead to the

abrogation of the ethanol induced increase in HCV replication, further documenting

that the ethanol induced increase in HCV replication was dependent on CYP2E1

mediated metabolism of ethanol. Collectively, these results suggest that CYP2E1

mediated metabolism of ethanol results in an increase in HCV replication in vitro, and

these results are consistent with the clinical observations previously described.

There are conflicting reports in the literature surrounding the role of ethanol

metabolism on HCV replication in vitro, which most likely reflects the different

model systems used in the various laboratories. The model system used in this chapter

consists of Huh-7 cell lines stably expressing CYP2E1, however, there have been

reports of observable increases in HCV RNA levels in HCV replicon cell lines that do

not express detectable levels of CYP2E1 (Zhang et al. 2003; Trujillo-Murillo et al.

2007). This is in direct contrast to results from this thesis and can be explained in part

by the possibility that Huh-7 cells may differ between laboratories. It is possible that

some Huh-7 cells may express low basal levels of CYP2E1 or ADH, however, the

previously mentioned studies did not investigate this. Secondly, there are considerable

variations in experimental design that could explain the differences. For example, the

study of (Plumlee et al. 2005) used experimental conditions that mimic acute

exposure to ethanol, in which the ethanol was added for 30 minutes, whereas, this

thesis is modeled on chronic exposure to ethanol and thus ethanol treatment was

maintained for days. Furthermore, in opposition to results in this chapter, published

investigations using acute ethanol exposure have demonstrated that acute ethanol

80

treatment may actually inhibit HCV replication (Choi et al. 2004; Choi et al. 2006),

however, no mechanism for this decrease in HCV RNA levels was postulated in these

studies. These results may be rationalised by the fact that acute exposure of cells to

ethanol results in a rapid increase in cellular ROS, resulting in an oxidative burst that

could act to limit HCV replication. This theory would also help to explain why

exogenous treatment of both genomic replicon cells and JFH-1 infected Huh-7 cells

expressing CYP2E1, resulted in a significant decrease in HCV RNA levels by

approximately 50% (Fig 4.8 & 4.12). It is possible that acute ethanol and H2O2

treatment, could have inhibitory effects on HCV replication, because these treatments

would stimulate an acute rise in ROS and a burst of oxidative stress. Adding further

weight to this theory is the fact that we observed a bi-phasic effect of ethanol

metabolism on HCV replication, which can be seen clearly in figure 4.1. These results

indicate that perhaps moderate levels of oxidative stress, induced by physiologically

relevant concentrations of ethanol in our chronic ethanol model, stimulate HCV

replication, whereas more pronounced levels of oxidative stress, that would occur

during acute treatment with ethanol and with exogenous H2O2 treatment, act to

suppress HCV replication.

Having firmly established an interaction between ethanol metabolism and HCV

replication, we then focused on determining a potential molecular mechanism for this

effect. Throughout this study oxidative stress emerged as a potential mediator of the

ethanol induced increase in HCV RNA levels. The reasoning for this being that we

demonstrated that ethanol metabolism via CYP2E1 increased cellular oxidative stress

levels in Huh-7 cells (Fig 4.4). Furthermore, it has been documented that HCV

replication induces oxidative stress and HCV core and NS5A proteins have been

implicated as the mediators of this oxidative stress production. Specifically, the

localization of NS5A to the ER and lipid droplets during HCV replication, is thought

to induce changes in membrane structures that results in ER stress and the unfolded

protein response, which ultimately leads to the release of ER Ca2+ stores and the

81

production of oxidative stress (Korenaga et al. 2005). As HCV is able to induce

oxidative stress, it seems feasible that the oxidative stress produced by ethanol

metabolism could be one of the mechanisms by which ethanol metabolism mediates

the increase in HCV replication. This hypothesis was investigated via the treatment of

HCV genomic replicon cells expressing CYP2E1 with the anti-oxidant NAC. NAC

treatment blocked the ethanol induced increase in HCV replication (Fig 4.5), which

strongly suggests that oxidative stress is playing a pivotal role in the ethanol induced

increase in HCV replication. Moreover, the addition of NAC alone decreased HCV

replication by approximately 50%, in both HCV replicon cell lines and Huh-7 cells

infected with JFH-1 (Fig. 4.12), indicating that HCV uses oxidative stress for its

replicative advantage. In order to rule out other possible mechanisms we investigated

if acetaldehyde, one of the main metabolites of ethanol, was responsible for the

ethanol induced increase in HCV replication. However, the addition of acetaldehyde

to HCV genomic replicon cells expressing CYP2E1, caused no modulation of HCV

RNA levels (Fig 4.6). We also investigated if ethanol was having a direct effect on

translation of the HCV polyprotein via enhancement of HCV IRES activity (Fig 4.7).

Theoretically an increase in IRES activity could lead to an increase in the levels of

HCV non-structural proteins available to initiate HCV replication, however, results

from these experiments demonstrated that ethanol does not modulate HCV IRES

activity, at least in vitro.

Taken together, our results and previously published findings indicate that HCV

replication induces oxidative stress and it is not inconceivable to envisage that HCV

utilizes oxidative stress for its replicative advantage. Thus, the results presented in

this chapter suggest that the enhancement of HCV replication in the presence of

ethanol metabolism is as a result of the synergistic production of oxidative stress from

ethanol metabolism and HCV replication itself. Obviously, this is just one potential

mechanism and in the HCV infected liver the interactions between alcohol

metabolism and HCV that lead to accelerated disease progression will be a complex

82

and multi-factorial process. However, deciphering just one of these mechanisms could

aid in the development of improved treatment options for CHC patients who consume

alcohol and form a rationale for anti-oxidant therapy.

Oxidative stress is known to be a potent second messenger for the activation of a

number of transcription factors, namely NF-κB, NF-AT, AP-1 and STAT3 (Carballo

et al. 1999; Gong et al. 2001). Hence, it is plausible that the oxidative stress generated

by HCV replication and ethanol metabolism could induce the activation of these

transcription factors. This activation could then result in the transcription of certain

genes, which could in turn enhance HCV replication. We hypothesized that the

oxidative stress sensitive transcription factor STAT3 could be playing a role in this

enhancement of HCV replication in the presence of ethanol metabolism, as the

oxidative stress produced by HCV replication has been shown previously to increase

the activation of STAT3 (Waris et al. 2005). This chapter documents that ethanol

metabolism increases STAT3 phosphorylation at the critical tyrosine 705 and serine

727 residues (Fig 4.13 & 4.14). This increased tyrosine phosphorylation could

theoretically increase STAT3 dimer formation and nuclear translocation.

Furthermore, increased S-727 phosphorylation could enhance the transcriptional

activation ability of STAT3. In line with the observation that STAT3 activation is

increased in the presence of ethanol metabolism, we also observed a modest increase

in STAT3 promoter activity when cells were cultured in the presence of ethanol (Fig

4.15). This increase in promoter activity could potentially lead to an increase in the

transcription of STAT3 dependent genes, which in turn may have various cellular

functions that could enhance HCV replication. Figure 4.16 shows a potential model

for the role of STAT3 and oxidative stress in the ethanol induced increase in HCV

replication.

Nuclear translocation of STAT3 results in the up-regulation of a wide and often

contradictory set of cellular responses. STAT3 has been shown to up-regulate genes

Figure 4.16 Possible role of STAT3 and oxidative stress in HCV replication. Ethanol metabolism via CYP2E1 leads to the production of oxidative stress. This oxidative stress may increase activation of STAT3, via increased Y705 and S727 phosphorylation. The resultant effect of this increased phosphorylation would be the enhancement of the transcriptional activation ability of STAT3, leading to increased expression of STAT3 dependent genes. This change in gene transcription could lead to the generation of a cellular environment favourable for HCV replication. HCV replication itself also induces oxidative stress and as such, could act synergistically with the oxidative stress produced by ethanol metabolism to increase STAT3 activation.

83

involved in cell cycle progression (Barre et al. 2005; Leslie et al. 2006), cell survival

(Bromberg et al. 1999; Catlett-Falcone et al. 1999; Kiuchi et al. 1999; Shirogane et

al. 1999; Ivanov et al. 2001) and metastasis (Dechow et al. 2004). Specifically, HCV

core protein has been shown to activate STAT3 and induce Bcl-Xl and Cyclin-D1

gene expression (Yoshida et al. 2002), which can lead to increased cell growth. It is

possible to envisage that in the presence of ethanol metabolism and HCV, the

activation of STAT3 via oxidative stress could lead to the cellular transcription of

genes that generate an environment that is favourable for enhanced HCV replication.

Clearly these results are preliminary and future work will be required to ascertain the

specific STAT3 dependent genes that are expressed during ethanol metabolism and an

active HCV infection, before the role of STAT3 in the ethanol induced increase in

HCV replication can be clearly defined.

As mentioned previously, HCV infected individuals that consume alcohol show

accelerated rates of CHC progression and an increased propensity for HCC

development. This chapter has demonstrated that STAT3 activation is increased in

the presence of ethanol metabolism and HCV replication. As STAT3 has been

classified as an oncogene, due to its ability to up-regulate the oncogenic protein as c-

Myc (Barre et al. 2005) and induce cellular transformation (Bromberg et al. 1999), it

is conceivable that STAT3 could be playing an integral role in the development of

HCC in HCV infected persons that consume alcohol. Thus the therapeutic inhibition

of STAT3 could represent a beneficial treatment option for end stage CHC patients

that are at risk of developing HCC.

This chapter has demonstrated that CYP2E1 mediated metabolism of ethanol

increases HCV replication and we have provided strong evidence that this increase is

mediated by the oxidative stress produced during ethanol metabolism. Furthermore,

the oxidative stress sensitive transcription STAT3 has emerged as a potential

84

candidate for facilitating the ethanol induced increase in HCV replication. The role of

STAT3 in the complete life cycle of HCV will be discussed further in chapter 6.

85

Chapter 5

The Effect of Ethanol Metabolism on IFN-α Signaling

5.1 Introduction

The consumption of alcohol in HCV infected individuals leads to reduced anti-viral

efficacy of IFN therapy (Safdar and Schiff 2004). As such, alcohol consumption is a

contraindication for therapy. The molecular mechanisms responsible for the low

response rates to IFN-α in HCV patients who consume alcohol are unknown. The

ability of IFN-α to exert an anti-HCV effect is largely dependent on the maintenance

of the JAK/STAT signaling cascade and the subsequent down stream activation of

anti-viral ISGs that are the mediators of an anti-viral response. Furthermore, optimal

activation of the IFN response is essential in shaping the adaptive immune response.

This chapter utilizes the in vitro model system described in chapter 3, to investigate

the anti-HCV activity of IFN-α in the presence of alcohol (ethanol) metabolism.

Specifically, we investigated components of the JAK/STAT signaling pathway and

known antiviral effectors in the presence of ethanol metabolism (Fig 5.1). The

dissection of possible mechanisms through which alcohol reduces the anti-HCV

activity of IFN-α, will hopefully provide a basis for further clinical investigations into

better treatment options for HCV patients who consume alcohol.

5.2 Ethanol Metabolism Decreases the Efficacy of IFN-α

5.2.1 The effect of ethanol metabolism on the anti-viral efficacy of IFN-α

To investigate if ethanol metabolism can modulate the anti-HCV efficacy of IFN-α in

vitro, genomic replicon cells expressing CYP2E1 were treated with and without 100

mM ethanol and 10 IU/ml IFN-α for 24 hours. At 24 hours post treatment total RNA

recovered using Trizol® and HCV RNA quantitated by real-time PCR. HCV RNA

Figure 5.1 IFN-α signal transduction pathway

86

levels were normalised to the control protein RPLPO and were expressed as fold

change relative to no treatment. Results demonstrated that when cells were cultured

in the presence of ethanol for 24 hours there was a modest increase in HCV RNA

levels (Fig 5.2), which was consistent with previous experiments described in chapter

4. As expected, treatment of genomic replicon cells with IFN-α decreased HCV RNA

levels by approximately 50%, however, when IFN-α was added to cells in

combination with ethanol, the anti-HCV activity of IFN-α was completely abrogated

(Fig 5.2). These results indicate that CYP2E1 mediated metabolism of ethanol

abrogates the anti-HCV activity of IFN-α in vitro.

5.3 CYP2E1 Mediated Ethanol Metabolism Modulates the

JAK/STAT Signaling Cascade

5.3.1 The phosphorylation status of signal transduction molecules in the

JAK/STAT signaling pathway in the presence of ethanol metabolism

The antiviral effects of IFN-α are largely dependent on maintaining the integrity of

the JAK/STAT signaling cascade. The activation of this pathway culminates in the

expression of hundreds of genes, many of which have antiviral and immunoregulatory

functions. We hypothesize that ethanol metabolism may abrogate activation of the

JAK/STAT signaling pathway. To test this hypothesis we firstly investigated the

phosphorylation status of STAT1, STAT2 and TKY2 in the presence of ethanol. HCV

genomic replicon cells expressing CYP2E1 were cultured in the presence and absence

of ethanol (100 mM) for 24 hours. IFN-α (150 IU/ml) was then added to cells for a

time course of up to 300 minutes. Total cell lysates were then extracted and Western

blots performed with antibodies specific for STAT1-Y701, STAT1-S727, STAT2-

Y690, TYK2-Y1054/1055 and also the non-phosphorylated forms of STAT1 and

STAT2. To determine the amount of protein loaded into each well, levels of β-actin

were also determined for each Western blot. Results shown are for 3 independent

experiments. Western blots experiments detected no observable difference between

Figure 5.2 Ethanol metabolism decreases the anti HCV efficacy of IFN-.HCV genomic replicon cells expressing CYP2E1 were incubated in the presence of IFN-α (10 IU/ml) with or without ethanol (100 mM) and total RNA recovered and HCV RNA quantitated by real-time PCR at 24 hours post IFN-α treatment. HCV RNA levels were normalised to the control protein RPLPO and were expressed as fold change relative to no treatment. Results demonstrated that ethanol metabolism significantly reduces the anti-HCV activity of IFN-α against the genomic replicon.

* P=0.0143

Control

EtOH (100 mM)

IFN-α (Units/ml)

10 10

Fold

Cha

nge

in H

CV

Rep

licat

ion

(Nor

mal

ised

to R

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O)

*

0.0

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2.0

87

the cells treated with ethanol in phosphorylation levels of STAT2-Y690 or total

STAT2 protein levels (Fig 5.3). There was also no difference noted in the levels of

phosphorylation of TKY2 at tyrosine residues 1054/1055 in the presence of ethanol

metabolism. STAT1 protein levels remained constant following ethanol treatment and

phosphorylation of STAT1 at S727 also remained unaffected by ethanol metabolism.

However, phosphorylation of STAT1-Y701 was significantly decreased in the

presence of ethanol metabolism. Figure 5.4A demonstrates that in the un-treated cells,

phosphorylation of STAT1-Y701 was detectable at 10 minutes post IFN-α treatment,

peaked at around 20 minutes post treatment and was still detectable at low levels at

300 minutes post treatment. On comparison, the level of phosphorylation in the

ethanol treated cells is markedly different. STAT1 tyrosine phosphorylation was

barely detectable at 10 and 20 minutes post IFN-α treatment and almost undetectable

at 30, 60 and 300 minutes post treatment. Densitometry analysis of these Western

blots graphically represents the marked difference in phosphorylation levels in the

ethanol treated cells (Fig 5.4B). Repeated attempts were made to investigate the

phosphorylation levels of JAK1 in the presence of ethanol metabolism. However,

attempts to optimize JAK1 Western blots were unsuccessful during the course of this

thesis. Results in this section demonstrated that ethanol metabolism modulates the

JAK/STAT signaling cascade by specifically decreasing the phosphorylation of

STAT1 at the critical Y701 residue. These results provide a possible molecular

mechanism for the decreased efficacy of IFN-α in the presence of ethanol

metabolism, as a decrease in STAT1-Y701 phosphorylation would potentially

decrease STAT1 dimerization and translocation into the nucleus, which would

translate into defective IFN signaling and an abrogated anti-viral response.

β-actin

STAT2-Y690

STAT1

0 10 20 IFN-α Time (mins)

STAT2

30 60 300

- EtOH + EtOH

β-actin

STAT1-S727

STAT1-Y701

Figure 5.3 Ethanol metabolism by CYP2E1 results in decreased STAT1 phosphorylation at tyrosine residue 701. HCV genomic replicon cells expressing CYP2E1 were incubated in the presence or absence of ethanol (100 mM) and stimulated with IFN-α (150 IU/ml) for a time course of up to 300 min. Total cell lysates were recovered and immunoblots were probed with various phospho specific STAT antibodies. β-actin was used as a loading control. Note the significant decrease in STAT1 tyrosine 701 phosphorylation following ethanol treatment. Phosphorylation at other STAT1 or STAT2 or TYK2 residues and total STAT protein levels were not affected by ethanol metabolism. These Western blots are representative of at least 3 independent experiments.

-actin

TYK2-Y-1054/1055

- EtOH

30 15 0

+ EtOH

IFN-α Time (mins)

0 10 20 30 60 300

30 15 0

STA

T1-Y

701/-

actin

(Arb

itrar

y V

alue

)

0 10 20 30 60 3000

5

10

20

30

40

50

ControlEtOH (100 mM)

IFN-α Time (mins)

Figure 5.4 STAT1-Y701 phosphorylation is decreased by ethanol metabolism. HCV genomic replicon cells expressing CYP2E1 were pre-treated with and without ethanol (100 mM) for 24 hours followed by IFN-(150 IU/ml) for up to 300 minutes and total cellular lysate recovered and immunoblot specific for STAT1-Y701. (A) Ethanol decreases STAT1-Y701 phosphorylation which is confirmed by densitometry analysis (B). STAT1-Y701 phosphorylation is decreased at all time points.

0 10 20 IFN-α Time (mins) 30 60 300

- EtOH

0 10 20 30 60 300

+ EtOH

β-actin

STAT1-Y701

A

B

88

5.3.2 Decreased STAT1-Y701 phosphorylation is dependent on CYP2E1

mediated metabolism of ethanol

To investigate if the decrease in STAT1-Y701 phosphorylation was dependent on

CYP2E1 metabolism of ethanol, HCV genomic replicon cells were cultured in the

presence or absence of ethanol and treated with IFN-α (150 U/ml) to induce STAT1-

Y701 phosphorylation, as per section 5.3.1. After the IFN-α time course total cellular

lysates were recovered and Western blots specific for STAT1-Y701 and β-actin were

conducted. Results indicated that there was no significant difference between the

phosphorylation levels of STAT1-Y701 in the presence of ethanol treatment (Fig 5.5).

These experiments strongly suggest that the ethanol induced decrease in STAT1-

Y701 phosphorylation is dependent on CYP2E1 mediated metabolism of alcohol.

5.3.3 The ethanol induced decrease in STAT1-Y701 phosphorylation is

independent of HCV replication

There have been numerous investigations into the effects of HCV protein expression

and replication on the JAK/STAT signaling pathway (reviewed in section 1.6).

Therefore we sought to investigate if the ethanol induced decrease in STAT1-Y701

phosphorylation was, in part, due to HCV replication. To test this, Huh-7 cells

expressing CYP2E1 were treated with and without ethanol (100 mM) for 24 hours,

followed by an IFN-α (150 IU/ml) time course of up to 60 minutes. Total cellular

lysates were recovered and Western blots specific for STAT1-Y701 were performed,

with β-actin used as a loading control. Results showed that there was a clear

difference in the phosphorlyation levels between the ethanol treated cells and those

not treated (Fig 5.6). Detectable levels of STAT1-Y701 phosphorylation were

observed at 60, 30 and 20 minutes post IFN-α treatment, however, there was almost

no discernable STAT1-Y701 phosphorylation seen in the ethanol treated cells at any

time point of IFN-α treatment. These results suggest that replicating HCV is not

Figure 5.5 The ethanol induced decrease in STAT1-Y701 phosphorylation is dependent on CYP2E1 expression. To investigate if the decrease in STAT1-Y701 phosphorylation was dependent on CYP2E1 metabolism of ethanol, genomic replicon cells were incubated in the presence or absence of ethanol (100 mM) for 24 hours and then stimulated with IFN-α (150 IU/ml) for a time course of up to 300 minutes. Total cell lysates were recovered and immunoblots were probed with STAT1-Y701 specific antibody. β-actin was used as a loading control. Western blots showed no significant modulation of STAT1-Y701 phosphorylation, indicating that the decrease in phosphorylation is dependent on CYP2E1 metabolism of ethanol.

STA

T1-Y

701/-

actin

(Arb

itrar

y V

alue

)

0 10 20 30 60 300

IFN-α Time (mins)

Control

EtOH (100 mM)

A

B

0 10 20 30 60 300- + EtOH

STAT1-Y701

β-actin

EtOHIFN-α Time (mins) 0 10 20 30 60 300

0

5

10

15

20

25

- EtOH + EtOH

60 30 20 0IFN-α (minutes)

STAT1-Y701

β-actin

60 30 20 0

Figure 5.6 The ethanol induced decrease in STAT1-Y701 phosphorylation is independent of HCV replication. To investigate if the decrease in STAT1-Y701 phosphorylation was affected by the presence of replicating HCV, Huh-7 cells (not expressing HCV) expressing CYP2E1 were incubated in the presence or absence of ethanol (100 mM) for 24 hours and then stimulated with IFN-α (150 IU/ml) for a time course of up to 60 minutes. Total cell lysates were recovered and immunoblotswere probed with STAT1-Y701 specific antibody. β-actin was used as a loading control. Western blots analysis demonstrates asignificant decrease in STAT1-Y701 phosphorylation levels in the presence of ethanol, indicating that the decrease in phosphorylation is independent of HCV replication.

STA

T1-Y

701/-

actin

(Arb

itrar

y V

alue

)

60 30 20 0

IFN-α Time (mins)


A

B

0

10

20

30

40

50

89

contributing to the decrease in STAT1-Y701 phosphorylation, and the effects seen are

due to CYP2E1 mediated metabolism of ethanol.

5.4 The Effect of Ethanol Metabolism on HCVcc and IFN-α

5.4.1 The effect of ethanol metabolism on the efficacy of IFN-α against HCVcc

As mentioned previously, the work for this thesis began when the infectious HCV

JFH-1 system was not available, thus the majority of the investigations into the effect

of ethanol metabolism on HCV were performed using the HCV replicon system.

However, once the infectious HCVcc system was optimized in our laboratory we then

sought to establish if our observations noted in section 5.3, held true in the context of

the complete HCV life cycle. These experiments were performed with Huh-7 cells

that are permissive for HCV (JFH-1) infection and express CYP2E1. Cells were pre

treated with ethanol (100 mM) for 24 hours, followed by infection with JFH-1

(MOI=0.1) for 3 hours and replacement of the media that contained ethanol. The

infection was allowed to proceed for a further 24 hours, with the media, then replaced

and 10 IU/ml IFN-α added in combination with ethanol. Total RNA was then

extracted using Trizol® and HCV RNA quantitated by real-time PCR. HCV RNA

levels were normalised to the control protein RPLPO and were expressed as fold

change relative to no treatment. Results showed that in the presence of ethanol alone,

HCV RNA levels were slightly increased, as we have noted previously (Fig 5.7). As

expected the treatment of cells with IFN-α in the absence of ethanol, significantly

reduced HCV RNA levels by approximately 85%. However, when IFN-α was added

in combination with ethanol treatment, the antiviral activity of IFN-α was

significantly impaired (Fig 5.7). Collectively, these experiments demonstrate that the

anti-HCV activity of IFN-α against both the HCV genomic replicon and HCVcc, is

abrogated in the presence of CYP2E1 mediated ethanol metabolism in vitro. These

observations correlate with the clinical documentation of reduced response rates to

Figure 5.7 Ethanol metabolism decreases the anti-HCV JFH-1 efficacy of IFN-. Huh-7 cells expressing CYP2E1 were infected with JFH-1 (MOI=0.1) and incubated in the presence of IFN-α (10 IU/ml), with or without ethanol (100 mM). Total RNA was recovered and HCV RNA quantitated by real-time PCR at 24 hours post IFN-α treatment. HCV RNA levels were normalised to the control protein RPLPO and were expressed as fold change relative to no treatment. Results demonstrate that ethanol metabolism significantly reduces the anti-HCV activity of IFN-α against JFH-1.

IFN- (Units/ml)

10

*** *** P=0.0003

10

Control

EtOH (100 mM)

0.0

0.5

1.0

1.5

2.0Fo

ld C

hang

e in

HC

V R

eplic

atio

n(N

orm

alis

edto

RP

LPO

)

90

IFN-α in patients consuming alcohol and suggest that this effect is mediated at the

level of IFN controlling HCV infection in hepatocytes.

5.4.2 Ethanol metabolism disturbs the JAK/STAT signaling pathway in the

presence of HCV JFH-1

To establish if the aforementioned decrease of STAT1-Y701 phosphorylation in HCV

genomic replicon cells (Fig 5.4) held true in presence of the full life cycle of HCV,

Huh-7 cells expressing CYP2E1 were pre treated with ethanol (100 mM) prior to

infection with JFH-1. The ethanol was replaced every 24 hours and at 48 hours post

infection cells were stimulated with IFN-α (150 IU/ml) for 10, 30 and 60 minutes.

Total cellular lysates were recovered and Western blots performed with an antibody

specific for STAT1-Y701. In the presence of ethanol there was a substantial

difference in the levels of STAT1-Y701 phosphorylation. There was a significant

decrease in the levels of STAT1-Y701 phosphorylation at all time points (Fig

5.8A&B). These results are consistent with the HCV replicon data and suggest that

ethanol metabolism decreases STAT-Y701 phosphorylation in the presence of HCV

JFH-1. This was not entirely unexpected given that the ethanol decrease in STAT1-

Y701 phosphorylation was shown to be independent of HCV replication (see section

5.3.3)

5.5 Ethanol Metabolism Decreases ISRE Promoter Activity

To determine if the ethanol induced decrease in STAT1-Y701 phosphorylation

translates to a functional decrease in ISGF3 activation of the ISRE promoter element,

an ISRE-luciferase reporter system was used [(pISRE-Luc): Appendix IX]. HCV

genomic replicon cells expressing CYP2E1 were transiently transfeted with pISRE-

Luc and a Renilla lucfierase construct (pRL-TK), which was used to control for

transfection efficiency. Following transfection, cells were treated with and without

Figure 5.8 Ethanol metabolism by CYP2E1 decreases STAT1-Y701 phosphorylation in the presence of HCV JFH-1. To investigate if the decrease in STAT1-Y701 phosphorylation levels observed in genomic replicon cells could also be seen in the presence of JFH-1, Huh-7 cells expressing CYP2E1 were infected with JFH-1 (MOI=0.1) for 72 hours followed by incubation in the presence orabsence of ethanol (100 mM) for 24 hours. Cells were then stimulated with IFN-α (150 IU/ml) for a time course of up to 60 minutes. Total cell lysates were recovered and immunoblots probed with a STAT1-Y701 specific antibody. β-actin was used as a loading control. Western blot data demonstrated a significant decrease in STAT1-Y701 (A) phosphorylation in the presence of ethanol metabolism and replicating JFH-1, which was confirmed by denistometry analysis (B).

STA

T1-Y

701/-

actin

(Arb

itrar

y V

alue

)

0 60 30 10

IFN-α Time (mins)


A

B

- EtOH + EtOH

STAT1-Y701

β-actin

60 30 10 0 IFN-α Time (mins) 60 30 10 0

0

10

20

30

40

50

91

ethanol (100 mM) for 24 hours and subsequently treated with IFN-α (10 & 150

IU/ml) for 5 hours. After 5 hours treatment total cellular lysates were harvested and a

luciferase assay used to measure total ISRE directed luciferase output. Results were

normalized to Renilla luciferase and expressed as a fold change relative to IFN-α

stimulation. Results from these experiments showed that stimulation of cells with 10

IU/ml IFN-α induced a significant fold change in ISRE-luciferase out-put (≈35 fold),

in the absence of ethanol. However, cells treated with ethanol induced a significantly

lower fold change with IFN-α treatment with (≈15 fold) (Fig 5.9). A more marked

inhibition of ISRE-luciferase output was observed when cells were treated with 150

IU/ml IFN-α. The relative fold change in ISRE-luciferase output was ≈130, which

was substantially different to the fold change of 40 observed in the cells treated with

ethanol and IFN-α. These results demonstrate that CYP2E1 mediated metabolism of

ethanol significantly reduces ISRE-luciferase output, indicating that ethanol

metabolism is able to functionally decrease the activity of the ISRE promoter element.

These findings are in accordance with the decreased STAT1-Y701 phosphorylation

levels observed in the previous section.

5.5.1 Ethanol metabolism alters ISG expression

The above results suggest that metabolism of ethanol reduces signaling through the

JAK/STAT pathway and is also capable of decreasing ISRE promoter activity. To

determine if this inhibitory action of ethanol metabolism results in a consequential

downstream decrease in ISG expression, we investigated ISG expression in Huh-7

cells metabolizing ethanol. Huh-7 cells expressing CYP2E1 were pre treated with

ethanol (100 mM) for 24 hours before they were infected with HCV JFH-1 for 3

hours. The ethanol was then replaced and 24 hours later 10 IU/ml IFN-α was added to

cells for 8 hours. At the end of this 8 hour IFN-α treatment, total RNA was extracted

by the previously described method. mRNA levels of the anti-viral ISGs viperin and

ISG20 were then quantitated by real-time PCR. RNA levels were normalised to the

10U 150U

IFN- (IU units/ml)

Fold

Cha

nge

in IS

RE-

Luc

Out

put

(Nor

mla

ised

to R

enill

a)

*P<0.05

Control

EtOH (100 mM)

Figure 5.9 Ethanol metabolism decreases ISRE promoter activity. To investigate if ethanol metabolism can affect downstream signaling of the JAK-STAT pathway, pISRE-Luc was transiently expressed in genomic replicon cells expressing CYP2E1. Cells were treated with and without 100 mM ethanol for 24 hours after which 10-150 IU/ml of IFN-α was added for 5 hours. Total cellular lysate was then extracted and a luciferase assay used to measure ISRE directed luciferase output. Renilla luciferase was used as a transfection control and results were expressed as a fold change compared to no treatment control. Ethanol metabolism significantly reduced IFN-α induced ISRE-luciferase output, indicating that ethanol metabolism is capable of reducing ISRE promoter activity.

0

50

100

150

92

control protein RPLPO and were expressed as fold change relative to the no

treatment. As expected, results showed that IFN-α treatment for 8 hours induced the

production of viperin and ISG20 mRNA. However, when IFN-α was added in

combination with ethanol, viperin mRNA levels were reduced by approximately 50%

(Fig 5.10A) and ISG20 mRNA levels were reduced by approximately 60% (Fig

5.10B). These results indicate that ethanol metabolism is capable of suppressing anti-

viral ISG expression. Collectively, results from this chapter document a potential

molecular mechanism for the reduced anti-HCV efficacy of IFN-α in the presence of

ethanol metabolism.

5.6 Discussion

As mentioned previously it has been observed clinically that the consumption of

alcohol in HCV infected people decreases the efficacy of IFN-α treatment, therefore

making alcohol consumption a contraindication for IFN-α therapy (Mochida et al.

1996; Loguercio et al. 2000; Safdar and Schiff 2004). The molecular basis underlying

the reduced anti-viral capacity of IFN-α in the presence of alcohol metabolism

remains to be established, however, results from this chapter indicate that alcohol

(ethanol) metabolism directly inhibits the action of IFN-α at the level of the

JAK/STAT signaling pathway.

This chapter utilized the model system developed in chapter 3 to investigate the effect

of ethanol metabolism on the anti-HCV capacity of IFN-α in vitro. We show for the

first time that the anti-HCV action of IFN-α is significantly abrogated in cells

harbouring HCV (either replicon or JFH-1) and metabolizing ethanol (Fig 5.1 & 5.7).

These results correlate with the aforementioned clinical findings and add further

weight in support of HCV infected persons abstaining from alcohol while undergoing

IFN-α therapy.

*P=0.015

*

Fold

Cha

nge

in V

iper

inm

RN

A(N

orm

alis

edto

RP

LPO

)

EtOH (100 mM)

IFN-α (10 IU/ml))

-- - +

+ - ++

***

***P=0.0005Fold

Cha

nge

in IS

G20

mR

NA

(Nor

mal

ised

to R

PLP

O)

EtOH (100 mM)

IFN-α (10 IU/ml)

-- - +

+ - ++

Figure 5.10 Ethanol metabolism reduces anti-viral ISG expression. To investigate if ethanol metabolism can reduce anti-viral ISG expression, Huh-7 cells expressing CYP2E1 were infected with JFH-1 and treated with and without ethanol (100 mM) and IFN-α (10 IU/ml). After 8 hours of IFN-α treatment total RNA was recovered and ISG20 and Viperin mRNA quantitated by real-time PCR. RNA levels were normalised to the control protein RPLPO and were expressed as fold change relative to no treatment. Ethanol metabolism significantly reduced the mRNA expression of the anti-viral proteins (A) Viperin and (B) ISG20, indicating that ethanol metabolism can interfere with an anti-viral response.

B

A

0

6

4

2

8

0

15

10

5

20

93

The ability of IFN-α to exert an anti-HCV effect in infected and un-infected

bystander cells, is facilitated by IFN-α activation of the JAK/STAT signaling

pathway and subsequent activation of the signal transduction molecules integral to

this pathway (Fig 5.1). This signaling event precedes the transcriptional activation of

the ISRE promoter element, which in turn leads to the production of hundreds of

different ISGs, many of which are anti-viral proteins capable of exerting an anti-HCV

effect. Therefore, following our observation that ethanol metabolism abrogates the

anti-HCV action of IFN-α, we wished to determine if the molecular basis for this

inhibition was due to perturbation of JAK/STAT signaling pathways. This was

achieved through the investigation of the phosphorylation status of the signal

transduction molecules integral to the JAK/STAT signaling pathway in the presence

of ethanol metabolism. In cells harbouring HCV replication and metabolizing ethanol

we found no abrogation of the phosphorylation status of the key signal transduction

molecules STAT2 (Y690) and TYK2 (Y1054/1055) (Fig 5.3). However, investigation

of STAT1 revealed that while phosphorylation at the serine 727 residue remained

unaffected by ethanol metabolism, levels of STAT1 tyrosine phosphorylation (Y701)

were significantly decreased in the presence of ethanol metabolism (Fig 5.3 & 4).

Furthermore, the decrease was specific for CYP2E1 dependent ethanol metabolism,

as in the absence of CYP2E1, we observed no decrease in STAT1 tyrosine

phosphorylation (Fig 5.5).

A notable investigation conducted by Osna et al documented the effects of

ADH/CYP2E1 mediated ethanol metabolism on IFN-γ signal transduction. While

IFN-γ signals through a different receptor complex to IFN-α, STAT1 tyrosine

phosphorylation is still necessary to induce activation of the JAK/STAT signaling

cascade, thus valuable insights can be gleaned from this investigation. This study

documented a decrease in STAT1-Y701 phosphorylation (Osna et al. 2005), which is

analogous to the results described within this chapter. Collectively, results from Osna

et al and this thesis suggest that ethanol metabolism can effectively dampen the IFN

94

signaling cascade for both IFN-α and IFN-γ. The exact molecular mechanism for this

effect remains unknown, although the oxidative stress produced by ethanol

metabolism emerges as a plausible candidate. It has been documented that exogenous

oxidative stress generated by the treatment of Huh-7 cells with H2O2 disrupts the

JAK/STAT signaling pathway by blocking STAT1, STAT2, JAK1 and TYK2

tyrosine phosphorylation (Di Bona et al. 2006). However, it is difficult to compare

oxidative stress generated by H2O2 and ethanol metabolism as the degree of oxidative

stress generated by H2O2 would be significantly different to that generated by ethanol

metabolism and the sub-cellular distribution of oxidative stress would also differ

between the two (Forman 2007). This investigation by Bona et al, does, however,

intimate that oxidative stress could be the mediator of the perturbation in JAK/STAT

signaling observed with ethanol metabolism.

Results from this chapter provide a possible molecular mechanism for the abrogation

of the anti-HCV action of IFN-α in the presence of ethanol metabolism. Namely,

decreased phosphorylation of STAT1 at Y701 residue would potentially lead to

reduced hetro-dimer formation and translocation into the nucleus. However, it was

important to determine if this decrease in STAT1-Y701 phosphorylation resulted in a

functional abrogation of IFN-α signaling. This was investigated using an ISRE

luciferase construct, which enabled ISRE promoter activity to be measured in the

presence of IFN-α treatment and ethanol metabolism. Results from these experiments

clearly demonstrated a marked decrease in ISRE promoter activity in the presence of

ethanol metabolism and IFN-α (Fig 5.9). The resultant effect of diminished ISRE

promoter activity would most likely be reduced downstream ISG expression. Hence,

it was logical to establish if ethanol metabolism was capable of altering ISG

expression, specifically anti-viral ISG’s, ISG20 and viperin. Both ISG20 (Jiang et al.

2008) and viperin (Helbig et al. 2005) have been shown previously to be anti-viral

against HCV and are significantly induced following IFN stimulation. Results clearly

95

showed that mRNA levels of ISG20 and viperin (Fig 5.10) were notably reduced in

the presence of ethanol metabolism, which correlates with our previous analysis.

A comprehensive investigation into the effects of ethanol metabolism on HCV and

IFN-α stimulation was conducted by Plumee et al, however, this study was modeled

on acute treatment of cells with ethanol (Plumlee et al. 2005), in which HCV replicon

cells were treated with a single dose of ethanol (100 mM). This study showed that in

the context of acute ethanol exposure, the anti-HCV effects of IFN were abrogated

and in concordance with this chapter, they also observed a decrease in STAT1-Y701

phosphorylation. However, in contrast to the results described in this thesis, they

showed that acute ethanol metabolism resulted in phosphorylation of STAT1-S727

and that this event corresponded with a decrease in HCV replication. Furthermore,

their effects were independent of ethanol metabolism by ADH and/or CYP2E1. Thus,

the variance between our study and their observations most likely reflects differences

between acute and chronic alcohol exposure.

Taken together, the results discussed in this chapter provide a possible molecular

mechanism for the reduced efficacy of IFN-α in patients consuming alcohol. This

chapter has demonstrated in vitro that ethanol metabolism decreases STAT1 tyrosine

phosphorylation, which translates to diminished ISRE promoter activity and

subsequently dampens anti-viral ISG output (Fig 5.11). For this study we only

investigated the expression of two ISGs and future experiments should include a

larger panel of ISGs. Clearly this is just one mechanism, and in the HCV infected

individual the factors at play in the alcohol induced suppression of IFN signaling are

multi-factorial and complex. For example, there has been some recent evidence

indicating that the high non-compliance rate of alcoholics adhering to treatment

programs could account for the reduced response rates of alcoholic patients in the

literature (Anand et al. 2006).

Figure 5.11 Alcohol metabolism decreases IFN-α efficacy via perturbation of the JAK/STAT signaling cascade.

96

While this thesis has demonstrated that ethanol metabolism perturbs JAK/STAT

signaling, further investigations are required to ascertain the precise molecular

mechanism for the observed decrease in STAT1-Y701 phosphorylation. We

hypothesise that ethanol metabolism may modulate various components of the innate

immune system such as the suppressor of cytokine signaling 3 (SOCS3). SOCS3 has

been demonstrated to inhibit IFN-α induced STAT1 tyrosine phosphorylation and

nuclear translocation, through inhibition of JAKs (Fujimoto and Naka 2003; Liu et al.

2004). There are a number of findings in the literature that have led us to propose

SOCS3 as a likely candidate for mediating the decrease in STAT1-Y701

phosphorylation that had been described in this chapter. Firstly, activated STAT3

(which could occur in the setting of HCV or ethanol metabolism) has been shown to

induce SOCS3 (Norkina et al. 2008) and Hong et al used a ConA model of mouse

hepatitis to also show that activated STAT3 plays an important role in inducing

SOCS3 (Hong et al. 2002). Secondly, HCV core has been shown to induce SOCS3

expression (Bode et al. 2003) and Szabo et al have shown that acute ethanol treatment

increases SOCS3 expression in monocytes (Norkina et al. 2008). While only

theoretical at this point, we believe there is significant evidence suggesting that

SOCS3 could be activated synergistically by ethanol metabolism and HCV to

abrogate JAK/STAT signaling specifically by reducing STAT1-Y701

phosphorylation, which would consequently decrease the anti-viral capacity of IFN-α.

Another possible candidate for directly mediating the decrease in STAT1-Y701

phosphorylation is Src homology region 2 domain-containing phosphatase 2 (SHP-2).

SHP-2 is a SH2 domain-containing tyrosine phosphatase that has been demonstrated

to decrease STAT activation, via catalyzing the tyrosine dephosphorylation of JAK

(You et al. 1999; Qu 2000; Wu et al. 2002). Due to a study by Holgado-Madruga et al

demonstrating that SHP-2 can be activated by oxidative stress, SHP-2 has arisen as a

potential candidate along with SOCS3 (Holgado-Madruga and Wong 2003). Other

strong evidence in support of SHP-2 and SOCS3 playing a functional role in the

97

decrease in STAT1-Y701 phosphorylation is the observation that alcohol

consumption causes the release of the pro-inflammatory cytokine TNF-α (Hoek and

Pastorino 2002) and TNF-α has been shown to induce expression of both SOCS3 and

SHP2 expression in the liver in vivo (Hong et al. 2001). Clearly, further work is

required to ascertain if either SOCS3 or SHP-2 mediates the decrease in STAT1-

Y701 phosphorylation. However, a proposed theoretical model for the role of SOCS3

and SHP2 in the ethanol induced decrease in STAT1-Y701 phosphorylation is

described in figure 5.12.

The results described in this thesis were all performed in vitro, and it is likely that in

vivo, the ability of ethanol metabolism to inhibit other components of the cellular

innate immune response would play an equally important role in clearance of HCV.

It has been documented that acute ethanol administration to mice results in

suppression of TLR-3 signaling (Pruett et al. 2004). As the TLR-3 and RIG-I

pathways recognize viral RNA, they are the hepatocytes first line of defence against

HCV infection, thus it is easy to envisage that the host would be highly susceptible to

chronic HCV infection if these two pathways were to be inhibited by alcohol

consumption. As such, investigation into the effects of ethanol metabolism on IFN

signaling in this chapter have important ramifications for not only exogenous IFN

applied during treatment, but also for endogenous IFN that is produced in host cells

upon infection with HCV in an attempt to clear the virus. It is feasible to envisage that

HCV infected individuals consuming alcohol may have a dampened endogenous

innate immune response to HCV infection. This may contribute to increased levels of

HCV replication and exacerbation of liver disease, not to mention the deleterious

effects of chronic alcohol consumption on the liver. In effect, HCV and alcohol

represents the ‘perfect storm’ in terms of liver disease.

Clearly, the factors at play in alcohol-induced suppression of IFN function in the

background of HCV replication are complex. However, the system described in this

SHP2

STAT3Activation

Pro-inflammatory cytokines (TNF-α)

HCVinduced CHC

SOCS3

Reduced Anti-HCV Activity of

IFN-α

ALCOHOLMetabolism

12

4 3

6

5

7

Inhibition of STAT1-Y701

Figure 5.12 Possible mechanism for the inhibition of STAT1-Y701 phosphorylation in the presence of alcohol metabolism via SHP-2 or SOCS3. Alcohol metabolism and HCV replication synergistically increase STAT3 activation (1) and production of TNF-α (2). STAT3 induces the activation of SOCS3 (3) in combination with HCV (4). TNF-α production leads to the activation of SHP2 and SOCS3 (5). Both SOCS3 and SHP2 inhibit STAT1-Y701 phosphorylation (6), which ultimately leads to reduced anti-viral activity of IFN-α (7).

98

chapter provides a model for further in depth dissection of innate immune response

and IFN signaling cascades in response to alcohol and HCV.

99

Chapter 6

The role of STAT3 in HCV replication

6.1 Introduction

STAT3 is a transcription factor that is activated by a wide variety of cytokines and

while STAT3 certainly plays a role in normal cell signaling processes that culminate

in biological responses such as proliferation, differentiation and apoptosis, STAT3

has also been shown to play a direct role in the oncogenic process (Bromberg et al.

1999; Bromberg and Darnell 2000). As such STAT3 has been demonstrated to be

constitutively active in a large number of human tumors (Bowman et al. 2000). Two

main investigations have documented direct interactions between STAT3 and HCV.

Yoshida and colleagues showed that STAT3 directly interacts with and is also

activated by the HCV core protein when expressed ectopically (Yoshida et al. 2002).

Furthermore, Waris and colleagues documented that HCV replication, in the context

of the HCV sub-genomic replicon, constitutively activates STAT3 via oxidative stress

related mechanisms (Waris et al. 2005). However, the molecular means through

which STAT3 enhances HCV replication remain to be established. Moreover, the

role of STAT3 in the complete HCV life cycle has not been investigated.

In previous chapters of this thesis we have shown that ethanol metabolism increases

HCV replication in an oxidative stress dependent manner and that ethanol metabolism

induces a concomitant activation of STAT3 in the presence of IFN-α. Given this

observation and previous findings in the literature, we deemed it necessary to

investigate the impact of STAT3 activation on the HCV life cycle. We surmised that

the ability of HCV to activate the oncogene STAT3, might be beneficial to the virus,

with the long term consequence being the development of HCC. Hence the aim of this

chapter was to further investigate the interactions between HCV and STAT3 and to

100

expand upon previous findings in the literature, in the hope of elucidating the

molecular interactions between HCV and STAT3.

6.2 HCV Replication Activates STAT3

6.2.1 STAT3 is constitutively activated in HCV genomic replicon cells

It has been shown previously by Waris et al, that STAT3 is constitutively active in

Huh-7 cells that harbour HCV replication in the form of a HCV genomic replicon,

thus we needed to confirm these observations and establish if this effect was

observable in our replicon system. To achieve this, total protein from HCV genomic

replicon cells and the parental Huh-7 cell line were used in Western blots

experiments, with antibodies specific for STAT3-Y705, STAT3 and β-actin (as a

loading control). In the presence of HCV replication, levels of STAT3-Y705

phosphorylation were significantly increased in comparison to the parental Huh-7 cell

line (Fig 6.1A). This result was confirmed via densitometry analysis of the Western

blots (Fig 6.1B). There was nominal detection of STAT3-Y705 phosphorylation in

the control Huh-7 line. This was not surprising considering that Huh-7 cells are a

HCC derived cell line and STAT3 has been shown to be constitutively active in a

number of tumor derived cell lines. Levels of total STAT3 were comparable in both

cell lines indicating that HCV replication did not significantly impact on basal STAT3

expression. These results of increased phosphorylation of STAT3-Y705 in HCV

genomic replicon cells were consistent with the findings by Waris et al.

6.2.2 STAT3 mRNA is increased during HCV JFH-1 infection

While the HCV replicon system is an excellent model system, it is limited by the fact

that infectious virions are not produced and thus the complete life cycle of HCV

replication is not recapitulated in vitro. We therefore wished to investigate if in the

context of HCVcc, we could observe an increase in STAT3 activation. Initially, we

Figure 6.1 STAT3 activation is increased HCV genomic replicon cells.To investigate if STAT3 activation is increased in the presence of HCV replication, total protein was harvested from genomic replicon cells and Huh-7 cells and immunoblots probed with antibodies specific for of STAT3-Y705, STAT3 and β-actin. (A) Phosphorylation of STAT3 at residue Y705 was significantly increased in genomic replicon cells, compared to the control Huh-7 cell line. (B) Densitometry analysis of these Western blots graphically depicts the marked increase in STAT3- Y705 phosphorylation levles in the presence of replicating HCV. STAT3 levels remained constant in both cell lines and β-actin was used as a loading control.

89 kDa

42 kDa

89 kDa

β-actin

STAT3-Y705

STAT3

A

B

20

0

40

60

80

Genomicreplicon

Control(Huh-7)

STA

T3-Y

705

/ β-a

ctin

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itrar

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Control(Huh-7)

101

analysed microarray data in which the transcriptome of JFH-1 infected Huh-7 cells

was compared to uninfected Huh-7 cells. These experiments were performed as part

of a separate project. Microarray analysis (Affymetrix HU133A plus 2.0, 47K

transcripts; entire human genome) was performed in consultation with Dr Mark Van

der Hoek (Adelaide Microarray Facility, SA Pathology) and Partek and Ingenuity

software programs were used to generate a comparison of gene expression profiles

between the JFH-1 infected cells and the control Huh-7 cells. This array data revealed

that HCV JFH-1 replication induced a 2-fold increase in STAT3 mRNA abundance.

Furthermore, Partek Pathway analysis revealed that associated STAT3 transcriptional

target genes, such as VEGF, were also increased in expression (Fig 6.2). These results

indicate that HCV JFH-1 replication can increase the expression of STAT3 at the

mRNA level.

6.2.3 HCV JFH-1 replication constitutively activates STAT3

The activation status of STAT3 in the presence of the infectious JFH-1 system has not

been previously investigated. To determine if STAT3 is activated in the presence of

the complete HCV life cycle, Huh-7.5 cells were infected with JFH-1 (MOI=0.1) for

72 hours (approximately 90% of cells infected at this time point), following which

total protein was extracted and Western blots performed using antibodies specific for

STAT3-Y705, STAT3 and β-actin. Consistent with our replicon data, results showed

detection of significantly increased levels of STAT3-Y705 phosphorylation in the

presence of HCV JFH-1 replication (Fig 6.3A). However, there was minimal

detection of phosphorylation in the control Huh-7 cells. This may be due to a different

Huh-7.5 clone being used for JFH-1 infection studies. Densitometry analysis of these

Western blots graphically depicts the marked increase in STAT3-Y705

phosphorylation in the presence of HCV JFH-1 (Fig 6.3B). This is the first

demonstration that STAT3 is activated in the presence of HCVcc.

Figure 6.2 Signaling pathway generated from microarray data showing STAT3 mRNA up-regulated 2-fold in JFH-1 infected Huh-7 cells. Microarray data (HU133A plus 2.0, 47K transcripts; entire human genome) was generated from Huh-7 cells infected with JFH-1 for 96 hours. Data was analysed using Partek and Ingenuity software programs to generate a comparison of gene expression profiles between the JFH-1 infected cells and the control Huh-7 cells and to draw a STAT3 signaling map. STAT3 mRNA levels were up- regulated 2- fold in JFH-1 infected Huh-7 cells in comparison to uninfected control Huh-7 cells.

A

Figure 6.3 STAT3 activation is increased in the presence of HCV JFH-1. To investigate if STAT3 activation is increased in the presence of JFH-1, Huh-7.5 cells were infected with JFH-1 (MOI=0.1) and total protein harvested 72 hours post infection. Immunoblots were probed with antibodies specific for STAT3- Y705, STAT3 and β-actin. (A) Phosphorylation of STAT3 at the critical residue Y-705 was strikingly increased in Huh-7.5 cells infected with JFH-1 compared to control cell line Huh-7.5. (B) Densitometry analysis of these Western blots clearly depicts the marked increase in STAT3-Y705 phosphorylation levels in the presence of JFH-1. Indicating that replicating HCV increases STAT3 activation. STAT3 levels remained constant in both cell lines and β-actin was used as a loading control.

42 kDaβ-actin

STAT3-Y705

STAT3

89 kDa

89 kDa

B

20

0

4060

80

HCVcc(JFH-1)

Control(Huh-7)

STA

T3-Y

705

/ β-a

ctin

(arb

itrar

y va

lue)


100

HCVcc(JFH-1)

Control(Huh-7.5)

102

6.2.4 HCV JFH-1 activates the STAT3 promoter

We showed in the previous section that HCV (both genomic replicon and JFH-1)

replication leads to activation of STAT3, thus we sought to determine if this increase

in STAT3 activation correlated in downstream activation of the STAT3

transcriptional promoter. To investigate this, Huh-7.5 cells and HCV genomic

replicon cells were transiently transfected with a plasmid containing STAT3

responsive DNA element driving luciferase [(pSTAT3-luc): Appendix VII].

Transfection of Huh-7.5 cells with p-STAT3-Luc was followed by infection with

JFH-1 (MOI=0.1). At 48 hours post infection total cellular lysate was harvested and a

luciferase assay performed to measure STAT3 directed luciferase output. To control

for transfection efficiency, cells were also transfected with a plasmid expressing

Renilla luciferase [(pRL-TK): Appendix VIII)]. Results were expressed as a fold

change relative to the non-infected control cells. Figure 6.4A&B depict that while

only a modest increase, JFH-1 and HCV genomic replicon replication significantly

enhances STAT3 luciferase output. These results indicate that HCV enhances STAT3

binding to the STAT3 promoter elements and thus potentially causing an increase in

STAT3 dependent gene transcription.

6.3 Characterisation of a Constitutively Active STAT3 (STAT3-C)

6.3.1 STAT3-C is functionally active

There are a number of lines of evidence that suggest STAT3 may play a role in HCV

RNA replication, namely – (i) the work described in Chapter 5 implicating STAT3 as

a mediator of the ethanol induced increase in HCV replication, (ii) STAT3 is an OS

sensitive transcription factor and (iii) the activation of STAT3 by replicating HCV

(shown in this thesis and by Waris et al). However, the work to date is observational

and little has been done to investigate the molecular interaction between STAT3 and

the HCV life cycle. To investigate this further, we used a constitutively active STAT3

molecule (STAT3-C) [Appendix X. (PRc/CMV-STAT3-C)], which was a kind gift

*P=<0.05

Figure 6.4 STAT3 promoter activity is increased in the presence of HCV. To investigate STAT3 promoter activity in the presence of replicating HCV, genomic replicon cells and Huh-7 cells were transfected with pSTAT3-luc and the Huh-7 cells were subsequently infected with JFH-1 for 48 hours (MOI=0.1). Total cellular lysate was extracted and luciferase assay performed to measure the STAT3 luciferase output in the presence of replicating HCV. Results were expressed as a fold change relative to un-infected control Huh-7 and Huh-7 cells and were normalised to renilla luciferase. In both JFH-1 infected Huh-7 cells (A) and genomic replicon cells (B) there was a significant increase in STAT3 luciferase output, indicating that replicating HCV enhances STAT3 promoter activity.

Control(Huh-7)

HCVcc(JFH-1)

2

3

4

5

6

*

Control(Huh-7)

GenomicReplicon

0

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ativ

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AT3

-Luc

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ivity

(Nor

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enill

a)

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AT3

-Luc

Act

ivity

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a)

*

A

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*P=0.017

103

from Dr Jacqueline Bromberg (Rockerfeller University, New York). This construct

has been extensively characterised (Bromberg et al. 1999). STAT3-C is a

constitutively active form of STAT3 in which 2 cysteine residues inserted into the C-

terminal loop of STAT3 allow for the formation of di-sulph hydryl bonds between

STAT3 monomers. This results in the formation of active STAT3 heterodimers that

do not require phosphorylation in order to be active and translocate into the nucleus

(Fig 6.5A). The aim of this section was to characterize STAT3-C expression in Huh-

7 cells and to ascertain if the expression of constitutively active STAT3 has any effect

on HCV replication. To establish if STAT3-C is functionally active in our hands,

Huh-7.5 cells were transiently transfected with pRc/CMV-STAT3-C and pSTAT3-

Luc. At 48 hours post transfection total cellular lysates were harvested and a

luciferase assay performed to measure STAT3 directed luciferase output. Renilla

luciferase was used to control for transfection efficiency and results were expressed as

a fold change relative to empty plasmid negative control [Appendix XI. (pRc/CMV)].

STAT3-C expression was able to significantly induce STAT3 luciferase output (Fig

6.5B), indicating that the expressed STAT3-C is functionally active and able to bind

to STAT3 promoter elements, and thus is capable of driving STAT3 dependent gene

expression in vitro.

6.3.2 STAT3-C expression in Huh-7.5 cells

To investigate STAT3-C expression, Huh-7.5 cells were transiently transfected with

pRc/CMV-STAT3-C for 48 hours. Immunofluorescence was then performed to detect

STAT3-C cellular localization. Approximately 30% of cells expressed STAT3-C

using this transient system (Fig 6.6A). STAT3-C showed strong nuclear expression

(Fig 6.6A&B). We then sought to investigate STAT3-C expression in the context of

JFH-1. Briefly, Huh-7.5 cells were transiently transfected with pRc/CMV-STAT3-C,

followed by infection with JFH-1 (MOI=0.1) for 48 hours. Immunofluorescence was

then performed to detect STAT3-C cellular localization and HCV antigen expression.

Figure 6.5 The STAT3-C construct is functionally active. To investigate if the STAT3-C plasmid (A) is functionally active and able to drive STAT3 dependent gene transcription, Huh-7.5 cells were transfected with pRc/CMV-STAT3-C and the control empty pRc/CMV plasmid in combination with pSTAT3-Luc. At 48 hours post transfection total cellular lysate was harvested and a luciferase assay performed to measure STAT3 luciferase output. Results were expressed as a fold change relative to control and renilla luciferase was used to control for transfection efficiency. (B) Transient STAT3-C expression was able to induce STAT3- luciferase output, thus indicating that the STAT3-C plasmid is functionally active in our system.

STAT3 C-Terminal Loop655

676

GYKIMDATNLVSPLVYLYPDI

Constitutively Active STAT3

C C

**P=0.0049

**

Rel

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-Luc

Act

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(Nor

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ised

to R

enill

a)

Control STAT3-C

8

6

4

2

0

B

A

Figure 6.6 STAT3-C expression in Huh-7.5 cells. To investigate the localisation of STAT3-C, Huh-7.5 cells were transfected with pRc/CMV-STAT3-C. At 48 hours post transfection cells were fixed and STAT3-C detected using a FLAG antibody. (A) Approximately 30% of cells expressed STAT3-C. Strong nuclear expression of STAT3-C was detected (B&C).

A

C

B

104

Consistent with activated states of STAT3, STAT3-C was detected in the cytoplasm

and nucleus of Huh-7.5 cells (Fig 6.7) and STAT3-C showed high levels of nuclear

expression in JFH-1 infected Huh-7.5 cells. These results indicate that STAT3-C

expression is viable in the presence of JFH-1 infection and STAT3-C localizes to the

cytoplasm and nucleus.

6.3.3 Transient expression of STAT3-C increases HCV JFH-1 replication

To establish if transient expression of STAT3-C effected HCV replication, Huh-7.5

cells were transiently transfected with pRc/CMV-STAT3-C and an empty vector

negative control (pRc/CMV). At 48 hours post transfection, cells were infected with

JFH-1 (MOI=0.1) and at 24 hours post infection total RNA was extracted and HCV

RNA levels quantitated by real-time PCR. RNA levels were normalised to the control

protein RPLPO and were expressed as fold change relative to the empty vector

negative control. Results clearly demonstrate that the transient expression of STAT3-

C significantly enhances HCV replication by two-fold (Fig 6.8), adding further weight

to our hypothesis that STAT3 plays a pivotal role in HCV replication. While we

observed an increase in HCV replication using this transient expression system, the

transfection efficiency in Huh-7.5 was approximately 20%, and thus the effect of

STAT3-C may only target a small population of HCV infected Huh-7.5 cells. Thus in

order to overcome this limitation, we opted to create a cell line that stably expresses

STAT3-C, which is described in the following section.

6.4 Characterisation of Huh-7.5 Cells Stably Expressing a

Constitutively Active Form of STAT3 (STAT3-C)

6.4.1 Detection of STAT3-C positive clones

Having established the functionality of STAT3-C in a nascent expression system we

next generated Huh-7.5 cell lines that stably express STAT3-C. This was done to

Figure 6.7 Expression of STAT3-C in HCV JFH-1 infected Huh- 7.5 cells. To investigate the transient expression of STAT3-C in the presence of JFH-1, Huh-7.5 cells were transfected with pRc/CMV‐

STAT3-C followed by infection with JFH-1 (MOI=0.1) for 48 hours. Immunofluoresence studies demonstrated that STAT3-C localised to the nucleus (red) in JFH-1 infected cells JFH-1 (green).

Control STAT3-C0.0

0.5

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**P=0.0027

**

Figure 6.8 Transient expression of STAT3-C increases HCV JFH-1 replication. To investigate if transient STAT3-C expression modulates HCV replication, Huh-7.5 cells were transiently transfected with pRc/CMV-STAT3-C for 48 hours, followed by infection with JFH-1 (MOI=0.1). At 48 hours post infection total RNA was extracted and HCV RNA levels quantitated by real-time PCR. RNA levels were normalised to the control protein RPLPO and were expressed as fold change relative to control. Results demonstrate that transient expression of STAT3-C significantly enhances HCV RNA levels.

105

overcome the 20-30% transfection efficiency observed above and to ensure all Huh-

7.5 cells express STAT3-C. This was done via the method described in section 2.1.2.

Briefly, Huh-7.5 cells were transfected with pRc/CMV-STAT3-C and treated with

neomycin to select for clones of cells in which the STAT3-C plasmid had integrated

into the genomic DNA. To confirm expression of STAT3-C in the seven expanded

clones, total protein was extracted from each cell line and Western blot performed

with antibodies specific for FLAG (STAT3-C is flag tagged) and β-actin (Fig 6.9).

Four clones (2, 3, 4 & 6) were positive for STAT3-C with variable expression. Two

clones (1 & 5) were negative for STAT3-C while clone 7 showed minimal expression

levels. These STAT3-C positive clones showed no abnormalities in cell morphology

or growth characteristics compared to the parent cell line. Attempts were made to

visualize the cellular localization of STAT3-C in the stably derived cell lines, as we

had done in the transient expression system. However, we could not detect STAT3-C

in any of the stable lines which mostly reflects significantly lower expression in these

cells compared to the transient assay.

6.4.2 STAT3-C stable cell lines maintain permissiveness for JFH-1 infection

In order to utilise these clonally derived Huh-7.5 cell lines stably expressing STAT3-

C we needed to ascertain if these cell lines maintained their permissiveness for HCV

JFH-1 infection. Thus the STAT3-C clones were infected with HCV JFH-1

(MOI=0.1), and at 72 hours post infection immunofluorescence was performed using

pooled human anti-HCV serum to detect HCV antigens. Clones numbered 1-7 and the

empty plasmid negative control cell line showed positive staining for HCV antigens

(Fig 6.10). All clones were approximately 90% infected, indicating that the clonally

derived nature of these stable cells does not negatively interfere with JFH-1 infection.

These results indicate that the Huh-7.5 cells stably expressing STAT3-C are

permissive for JFH-1 infection.

Figure 6.9 Characterisation of Huh-7.5 cell lines stably expressing STAT3-C. To detect expression of STAT3-C in neomycin resistant STAT3-C cell lines, total protein was extracted from each cell line and immunobloted with antibodies specific for FLAG and β-actin. Results indicated that STAT3-C clone 4 had the highest levels of STAT3-C expression, clones 2 and 3 expressed moderate levels, while clones 6 and 7 expressed low levels of STAT3-C. The empty vector control cell line expressed no detectable STAT3-C (clone 1).

1 2 3 4 5 6 7

STAT3-C Clones

FLAG

β-actin 42 kDa

89 kDa

STAT3-C (Clone 1)

STAT3-C (Clone 2)

STAT3-C (Clone 3)

STAT3-C (Clone 4)

STAT3-C (Clone 5)

STAT3-C (Clone 6)

STAT3-C (Clone 7)

pRc-CMV-Control

Figure 6.10 STAT3-C stable cell lines are permissive for HCV JFH-1 infection. To determine if STAT3-C clones maintained their permissiveness for JFH-1 infection following selection with neomycin, all cell lines were infected with JFH-1 (MOI=0.1) for 48 hours, followed by immunofluorescence staining of HCV antigens using pooled human anti- HCV serum. All STAT3-C stable cell lines were positive for HCV antigen, indicating that STAT3-C stable lines are permissive for JFH-1 infection.

106

6.5 The Effect of STAT3-C Expression on HCV Replication

6.5.1 Stable expression of STAT3-C increases HCV JFH-1 replication

In section 6.3.3 we demonstrated that transient expression of pRc/CMV-STAT3-C

lead to enhanced HCV replication. We then sought to ascertain the effect of stably

expressed pRc/CMV-STAT3-C on HCV replication, using the cells that were

characterised in section 6.4. Briefly, STAT3-C Huh-7.5 stable cell lines were infected

with HCV JFH-1 (MO I= 0.1) for 24 hours and total RNA extracted HCV RNA

quantitated by real-time PCR. RNA levels were normalised to the control protein

RPLPO and were expressed as fold change relative to control. Four different clones

were chosen: two that were negative for STAT3-C via immuno blot (clones 1&5) and

one that was positive for STAT3-C (clone 4) and the parent plasmid control line (see

Fig 6.9). Results demonstrated that HCV replication was significantly enhanced in

only STAT3-C clone 4, which was the clone that demonstrated the highest levels of

STAT3-C expression via Western blot analysis (Fig 6.11). On comparison in clones

(1 & 5) that showed no detectable levels of STAT3-C expression, we did not observe

any modulation of HCV RNA levels. As expected the empty plasmid negative control

cell line displayed no marked increase in HCV replication. Collectively figures 6.8

and 6.11 document that the expression of a constitutively active form of STAT3

markedly enhances HCV replication in both a transient and stable system, suggesting

that STAT3 may play an integral role in HCV replication.

6.6 Can Leukemia inhibitory factor (LIF) increase HCV replication?

Having established that the exogenous expression of a constitutively active form of

STAT3 can increase HCV replication, we next wished to determine if endogenous

activation of STAT3 could show a similar effect. STAT3 can be activated by all

members of the IL-6 type cytokine family and a number of growth factors and IFNs,

these include – IL-6, leukemia inhibitory factor (LIF), cardiotrophin-1 (CT-1),

epidermal growth factor (EGF), oncostatin M (OSM) and IFN-α/β. To further

Figure 6.11 Stable expression of STAT3-C increases HCV JFH-1 replication. To investigate if stable STAT3-C expression modulates HCV replication, STAT3-C stable cell lines were infected with JFH-1 (MOI = 0.1) for 24 hours, total RNA extracted and HCV RNA quantitated by real-time PCR. RNA levels were normalised to the control protein RPLPO and results were expressed as fold change relative to control. HCV replication was significantly enhanced in STAT3-C clone 4, while there was no modulation of HCV RNA levels in the control cell line or clones 1 and 5, which were negative for STAT3-C expression.

***

***P=0.0005

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STAT3-C - - + -

2.5

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0

107

elucidate the role of STAT3 in HCV replication, we investigated if LIF induced

activation of STAT3 lead to enhanced HCV replication. Firstly, to establish if LIF

activates STAT3 in our system, Huh-7.5 cells were treated with LIF (10 µM) for up to

60 minutes and total protein extracted and a Western blot performed using antibodies

specific for STAT3-Y705 and β-actin. Figure 6.12A clearly demonstrates that LIF

treatment induces STAT3-Y705 phosphorylation optimally at 60 minutes post

treatment. In order to establish if LIF treatment modulates HCV replication, Huh-7.5

cells were infected with JFH-1 (MOI=0.1) and treated with LIF (10 mM) for 48 hours

post infection. Total RNA was then extracted and HCV RNA levels quantitated by

real-time PCR. RNA levels were normalised to the control protein RPLPO and results

were expressed as fold change relative to control. LIF stimulation of Huh-7.5 cells

infected JFH-1 significantly enhances HCV replication by approximately two-fold.

This observation provides further evidence that STAT3 plays a role in HCV

replication. However, we cannot discount other cellular effects that LIF may be

inducing, that could also impact on HCV replication.

6.7 The Effect of STAT3 Inhibition on HCV Replication

6.7.1 siRNA knockdown of STAT3 decreases HCV JFH-1 replication

Collectively our previous experiments have shown that activation of STAT3 results in

enhanced HCV replication. To extend these observations, a converse set of STAT3

inhibition experiments were performed. The first method used to inhibit STAT3 was

a siRNA knockdown approach (for method see section 2.1.3). To validate this

approach STAT3 siRNA (Invitrogen) and a control siRNA were transfected into Huh-

7 cells. 24 hours later, total protein was harvested and a Western blot performed using

antibodies directed against STAT3 and β-actin. While a near complete knockdown is

desirable using a siRNA approach, we were only able to reduce STAT3 expression by

approximately 50%, as shown in Figure 6.13A. To determine the effect of STAT3

siRNA knockdown on HCV replication, Huh-7.5 cells were transfected with STAT3

Figure 6.12 LIF activates STAT3 and enhances HCV JFH-1 replication. To determine if LIF can enhance HCV replication via activation of STAT3, Huh-7.5 cells were treated with LIF (10 mM) for a time course of 0-60 minutes. Total protein was then extracted and immunoblots probed with antibodies specific for STAT3-Y705 and β-actin. (A) LIF induced STAT3- Y705 phosphorylation at 10, 30 and 60 minutes post treatment. To investigate if LIF can enhance HCV replication, Huh-7.5 cells were infected with JFH-1 (MOI=0.1) and treated with LIF (10 mM) for 48 hours post infection. Total RNA was then extracted and HCV RNA levels quantitated by Real-time PCR. RNA levels were normalised to the control protein RPLPO and were expressed as fold change relative to control. (B) LIF markedly enhanced HCV RNA levels, possibly through LIF induced activation of STAT3.

Fold

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*P=0.0283

β-actin

STAT3-Y705

LIF (10 mM) Time (minutes) 0 10 30 60

A

B

0 10

LIF (mM)

4

3

2

1

0

*

Figure 6.13 Knockdown of STAT3 with siRNA decreases HCV JFH-1 replication. To ascertain if siRNA knockdown of STAT3 modulates HCV replication, Huh-7.5 cells were transfected with STAT3 siRNA and a control scrambled siRNA. 24 hours post transfection cells were infected with JFH-1 (MOI=0.1). At 24 hours post infection total RNA was extracted and HCV RNA levels quantitated by real-time PCR. RNA levels were normalised to the control protein RPLPO and were expressed as fold change relative to control. (A) Western blot showing approximately 50% reduction in STAT3 protein levels following transfection with STAT3 siRNA. (B) The knockdown of STAT3 with siRNA decreased HCV RNA levels by approximately 40%, indicating that STAT3 plays a role in HCV replication.

0.0

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Control siRNA

STAT3 siRNA

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STAT3

β-actin

controlcontrolsiRNA

STAT3siRNA

A

B

42 kDa

89 kDa

**

108

siRNA and a control scrambled siRNA, and 24 hours later cells were infected with

HCV JFH-1 (MOI=0.1). At 24 hours post infection total RNA was extracted and

HCV RNA levels quantitated by real-time PCR. RNA levels were normalised to the

control protein RPLPO and were expressed as fold change relative to control. The

knockdown of STAT3 with siRNA significantly decreased HCV RNA levels by

approximately 40%. In combination with our STAT3 constitutive expression studies,

these results strongly suggest that STAT3 plays an important role in HCV replication.

6.7.2 Chemical Inhibition of STAT3 decreases HCV replication

There are a number of commercial STAT3 inhibitors available - AG490 (Sigma) is a

JAK-2 protein tyrosine kinase (PTK) inhibitor; as STAT3 is phosphorylated by JAK-

2, AG490 inhibits Y705 phosphorylation of STAT3. As such, AG490 acts as an

indirect inhibitor of STAT3 dimerization. STA-21 (Biomol) is a novel selective small

molecule inhibitor of STAT3, which binds to the SH-2 domain of STAT3 and

specifically prevents dimerization of STAT3 and DNA binding (Song et al. 2005).

S31-201 (NSC74859) (Sigma) is a cell-permeable inhibitor of STAT3 that targets the

STAT3-SH2 domain and blocks STAT3 dependent transcription (Siddiquee et al.

2007). Figure 6.14 outlines the STAT3 signaling cascade and demonstrates the

specific points where these inhibitors act.

6.7.2.1 AG490 and STA-21 decrease HCV replication in genomic replicon cells

The effects of AG490 and STA-21 mediated inhibition of STAT3 on HCV replication

were first investigated in the HCV genomic replicon cell line. Briefly, genomic

replicon cells were treated with STA-21 (10 µM) and AG490 (40 µM) for 24 hours,

total RNA was extracted and at 24 hours post treatment and HCV RNA levels were

quantitated by real-time PCR as previously outlined. Results demonstrated that STA-

21 treatment of genomic replicon cells did not appear to markedly modulate HCV

RNA levels. However, AG490 treatment did modestly decrease HCV RNA levels by

S31-201/STA-21

AG490

Figure 6.14 Action of STAT3 inhibitors. STA-21 and S31-201 bind to the SH-2 domain of STAT3 to prevent dimerization. AG490 inhibits JAK mediated tyrosine phosphorylation of STAT3.

109

approximately 35% (Fig 6.15). The modest decrease in HCV replication with the

indirect STAT3 inhibitor (AG490), may be due to off target effects of this compound.

Given that the direct acting STAT3 inhibitor (STA-21) had no effect on the HCV

replicon, it is possible that STAT3 activation is not involved in HCV RNA replication

per se, but is perhaps more likely to be involved in either HCV entry or assembly.

6.7.2.2 Chemical inhibition of STAT3 decreases HCV JFH-1 replication

We next sought to determine the effect of STAT3 inhibition with AG490, STA-21

and a newly acquired inhibitor S31-201 (Sigma), on HCV replication, in the context

of the complete HCV life cycle. Briefly, Huh-7.5 cells were pre treated with STA-21

(10 µM), AG490 (10 µM) and S31-201 (20 µM) for 1 hour, followed by infection

with JFH-1 (MOI=0.1). At 24 hours post infection, total RNA was extracted and HCV

RNA levels quantitated by real-time PCR. RNA levels were normalised to the control

protein RPLPO and results were expressed as fold change relative to the no treatment

control. In contrast to HCV replicon cells, treatment of HCV JFH-1 infected Huh-7.5

cells with STA-21, AG490 and S31-201 significantly decreased HCV replication by

approximately 70% (Fig 6.16). Treatment of cells with AG490, STA-21 and S31-201

did not affect growth rates of Huh-7.5 cells and no toxicity was observed (results not

shown). As the effects seen with the infectious HCVcc system were dramatically

increased on comparison to the results observed in the genomic replicon system, it is

possible that STAT3 is playing a role in assisting HCV entry, assembly or egress.

Collectively, results from section 6.7 show that inhibition of STAT3 leads to

significant deceases in HCV replication levels, thus suggesting that STAT3 may be

playing an integral role in the HCV life cycle.

*

Figure 6.15 Inhibition of STAT3 modestly decreases HCV replication in genomic replicon cells. To determine if inhibition of STAT3 modulates HCV replication, genomic replicon cells were treated with STA-21 (10μM) and AG490 (10μM) for 24 hours. After 24 hours of treatment total RNA was extracted and HCV RNA levels quantitated by real-time PCR. RNA levels were normalised to the control protein RPLPO and were expressed as fold change relative to control. Treatment of cells with STA-21 modestly decreased HCV replication, whereas AG490 treatment significantly decreased HCV RNA levels by approximately 35%.

AG490(10 μM)

Control0

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***P=0.0003

*P=0.0454

A

B

C

Figure 6.16 Inhibition of STAT3 decreases HCV JFH-1 replication. To determine if inhibition of STAT3 modulates JFH-1 replication, Huh-7.5 cells were pre treated with (A) S31-201 (20 μM), (B) AG490 (10 μM) and (C) STA-21(10 μM) for 1 hour followed by infection with JFH-1 (MOI=0.1). At 24 hours post infection, total RNA was extracted and HCV RNA levels quantitated by real-time PCR. RNA levels were normalised to the control protein RPLPO and were expressed as fold change relative to control. Treatment with these STAT3 inhibitors significantly decreased HCV replication by approximately 70%. Results indicate that STAT3 plays a pivotal role in the life cycle of HCV.

**

***

*

110

6.8 Inhibition of STAT3 Prevents HCV Establishing a Productive

Infection

The above section demonstrated that inhibition of STAT3 significantly decreased

HCV (JFH-1) replication, however, given the modest effect of these compounds on

the HCV replicon system, it is possible that STAT3 is working during early stages of

HCV infection. Thus to investigate if STAT3 plays a role in facilitating HCV

establishing a productive infection, Huh-7.5 cells were treated with each of the

STAT3 inhibitors and an infectivity assay used to measure entry of the virus into

cells. Briefly, Huh-7.5 cells were pre treated with STA-21 (10 µM), AG490 (10 µM)

and S31-201 (20 µM) for 1 hour and then infected with a defined MOI of HCV JFH-1

and the number of HCV positive foci were determined by an immunofluorescence

assay. At 72 hours post infection cells were stained for HCV antigen using pooled

human anti-HCV serum (Fig 6.17) and the number of ffu/ml enumerated (Fig 6.18).

In cells treated with STA-21 there was a massive reduction in infected foci (0.15 x

106), compared to 1.2 x 106 ffu/ml for the control treated cells (Fig 6.18A). These

results strongly suggest that STA-21 may abrogate HCV entry into cells. AG490

treatment similarly decreased the number of foci from 1.3 x 106 ffu/ml for the control

cells to 0.043 x 106 ffu/ml, demonstrating that AG490 is also capable of inhibiting

HCV entry (Fig 6.18B). S31-201 treatment also reduced the number of foci from 7.6

x 105 ffu/ml for the control treated cells, to 0.068 x 105 ffu/ml (Fig 6.18C). These

results provide impressive evidence for STAT3 playing a vital role in HCV

establishing a productive infection. Given that STAT3 is a transcription factor, we

first hypothesized that STAT3 was not playing a direct role in facilitating HCV, but

rather it was the expression of STAT3 dependent genes that led to facilitation of HCV

entry into cells. However, after extensive literature searches, we formed the

hypothesis that STAT3 may be assisting HCV entry into hepatocytes via the control

of microtubule dynamics. This will be discussed in more detail below.

STA-21 (10μM) ControlA

B

C

Figure 6.17 Inhibition of STAT3 decreases the susceptibility of Huh-7.5 cells to HCV JFH-1 infection. To investigate if the inhibition of STAT3 effects HCV infectivity, Huh-7.5 cells were pre treated with STA-21 (10 μM), AG490 (10 μM) and S31-201 (20 μM) for 1 hour, followed by JFH-1 infection. At 72 hours post infection cells were stained for HCV antigen using pooled human anti-HCV serum. (A) STA-21, (B) AG490 and (C) S31-201 treatment significantly decreased HCV infectivity. These results suggest that STAT3 may play a role in assisting HCV entry into hepatocytes.

AG490 (10μM) Control

S31-201 (20μM) Control

FFU

/ml (×1

06)

Control(DMSO)

STA-21(10 μM)

FFU

/ml (×1

06)

Control(EtOH)

AG490(10 μM)

* * *

Figure 6.18 Inhibition of STAT3 decreases the susceptibility of Huh-7.5 cells to HCV JFH-1 infection. To investigate if the inhibition of STAT3 effects HCV infectivity, Huh-7.5 cells were pre treated with STA-21 (10 μM), AG490 (10 μM) and S31-201 (20 μM) for 1 hour, followed by infections with JFH-1 for 3 hours. At 72 hours post infection cells were stained for HCV antigen using pooled human anti-HCV serum and focus forming units (ffu/ml) calculated. (A) STA-21, (B) AG490 and (C) S31-201 treatment significantly decreased HCV infectivity. These results suggest that STAT3 may play a role in HCV establishing a productive infection.

FFU

/ml (×1

05)

Control(DMSO)

S31-201(20 μM)

***P<0.0001

***P<0.0001

***P<0.0001

***

***

***

0

0.5

1.0

1.5

0

0.5

1.0

1.5

0

2

6

4

8

10

111

6.9 STA-21 Inhibits Microtubule Polymerization

It has been recently described that STAT3 is able to positively regulate microtubule

dynamics via a direct interaction with (Stathmin) STMN1 (Ng et al. 2006; Verma et

al. 2009). This interaction is depicted in Figure 6.19, whereby phosphorylated STAT3

binds to STMN1 and inhibits the ability of STMN1 to depolymerize tubulin, resulting

in the maintenance of microtubule integrity. Interestingly, it has been documented that

in order to initiate a productive infection, HCV utilizes microtubules for entry into

Huh-7 cells (Roohvand et al. 2009). Roohvand et al documented that treatment of

hepatocytes with a known microtubule inhibitor (vinblastin) causes inhibition of entry

and possibly post-entry steps. Under vinblastic treatment they observed significant

decreases in HCV entry using the HCV pseudo particle (HCVpp) system and also saw

decreased intracellular RNA levels. However, this effect was only observed when

cells were pre-treated with vinblastin, indicating that it is most likely an entry

mediated effect. Current literature suggests that microtubule inhibitors do not have a

direct effect on HCV RNA replication, as treatment of HCV replicon cells and Huh-7

cells with an established JFH-1 infection, induces no modulation of HCV RNA levels.

Roohvand et al have suggested that both an intact and dynamic microtubule network

is required to establish a productive HCV infection. Thus, given these recent findings

in the literature, we hypothesized that STAT3 may be assisting HCV entry or post-

entry steps, via the induction of α-tubulin polymerization, which would culminate in

enhanced microtubule activity. We sought to determine if treatment of Huh-7.5 cells

with the STAT3 inhibitor STA-21 resulted in a decrease in microtubule

polymerization. Briefly, Huh-7 cells were treated with STA-21 (10 µm) for 2 hours,

followed by immunofluorescence staining for α-tubulin, the main constituent of

microtubules. Nocodazole, a known microtubule depolymerizing agent, was used as a

positve control and results were compared to the DMSO vehicle control treated cells.

Figure 6.20 clearly depicts that in the presence of STA-21, there is no microtubule

polymerization, as there is minimal α-tubulin staining. This drastically differs to the

morphology of the microtubules in the control (DMSO) treated cells, which show

Cytokine

HCV Entry

Figure 6.19 Model of STAT3 interaction with STMN1. STAT3 is able to positively regulate microtubule dynamics via a direct interaction with STMN1, a known tubulin depolymerizing protein.

HCV

Figure 6.20 Inhibition of STAT3 with STA-21 inhibits α-tubulin polymerization. To investigate if the inhibition of STAT3 effects microtubule polymerization Huh-7.5 cells were treated with STA-21 (20 μM) for 2 hours and then immunofluoresence performed for α-tubulin. (A)(200x magnification) Control (DMSO) cells showed strong α-tubulin staining and intact microtubules. Nocodazole treatment drastically reduced α-tubulin staining indicating microtubules were depolymerized. (B) (600x magnification) STA-21 treatment showed comparable staining with the known microtubule depolymerization Nocodazole, indicating that STAT-21 treatment causes tubulin depolymerization.

Control

Control STA-21

STA-21 Nocodazole

A

B

112

strong α-tubulin staining and long spindle like microtubule formation. The STA-21

treated cells appear to have the same staining pattern as the nocodazole treated cells.

These results indicate that STA-21 does indeed appear to inhibit α-tubulin

polymerization, potentially indicating that inhibition of STAT3 with STA-21 causes

decreased HCV entry, via control of microtubule activity. Clearly, further

investigations are required to establish if STMN1 is the mediator of this effect.

Furthermore, as STAT3 exerts a diverse set of responses, it has the potential to be

playing a role in multiple stages of the HCV life cycle. Further clarification of the role

of STAT3 in HCV entry and egress is necessary to ascertain the precise molecular

mechanism(s) by which STAT3 contributes to the life cycle of HCV.

6.10 Discussion

STAT3 is sensitive to oxidative stress and there have been a number of investigations

showing an association between STAT3 and HCV. Chapter 4 of this study has

demonstrated that ethanol metabolism can induce STAT3 activation, most likely

through the oxidative stress produced during ethanol metabolism. It has also been

identified that HCV replication can induce oxidative stress, and as such the oxidative

stress sensitive transcription factor STAT3 can be activated during HCV replication

(Waris et al. 2005). Furthermore, STAT3 has been shown to directly interact with the

HCV core protein (Yoshida et al. 2002). Clearly, experimental evidence associates

STAT3 with HCV and implicates STAT3 in the life cycle of the virus. The aim of this

chapter was to further clarify the role of STAT3 using the HCV infectious model

system and to attempt to establish at the molecular level, a role for STAT3 in the

HCV life cycle.

Firstly, this study has shown that STAT3 mRNA levels are increased by two-fold in

the presence of JFH-1 infection (Fig 6.2). However, in terms of STAT3, increased

mRNA levels does not necessarily correlate with increased effector function; as in

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order for STAT3 to become activated, it requires phosphorylation at the critical Y705

residue. Phosphorylation at this residue renders STAT3 capable of dimerization and

enables subsequent translocation into the nucleus. Once in the nucleus, STAT3 can

then drive STAT3 dependent gene expression. The next logical step for this project

was to establish if STAT3 activation was increased in the presence of HCV

replication. Figure 6.1 confirms previous findings by Waris et al and demonstrates

that STAT3-Y705 phosphorylation is significantly increased in genomic replicon

cells. However, it is unknown if HCVcc affects STAT3 activation. We have now

demonstrated for the first time, that STAT3-Y705 phosphorylation levels are

markedly increased in the presence of JFH-1, thus indicating that STAT3 is

constitutively activated by HCV replication (Fig 6.3). Moreover, to establish if this

increased activation of STAT3 lead to an increase in DNA binding of STAT3, a

STAT3 luciferase assay was employed. Results demonstrated that STAT3 dependent

DNA binding was notably increased in the presence of replicating HCV (Fig 6.4).

Collectively, these results indicate that HCV replication can induce STAT3

activation, which would potentially lead to increased STAT3 dependent gene

expression. STAT3 has been shown to exert a wide variety of biological responses.

The pathological and physiological state of the cell type that STAT3 is expressed in,

directly affects the type of STAT3 dependent genes that are activated. Hence, it is

possible that oxidative stress produced by HCV replication leads to activation of

STAT3, resulting in the expression of a distinct set of target genes in infected

hepatocytes.

There are a number of candidate STAT3 dependent genes that could potentially play a

role in HCV replication. Constitutive activation of STAT3 has been shown to induce

VEGF expression (Niu et al. 2002) and HCV has been shown to induce VEGF

expression and secretion (Nasimuzzaman et al. 2007). VEGF is most likely not

playing a role in the in vitro investigations performed in this study, as the cells used in

this model system are un-polarised. However, it has been shown that HCV induced

114

VEGF expression can cause reduced hepatoma tight junction integrity and re-

organization of occludin (Mee et al.), which is one of the receptors necessary for

HCV entry. Thus, it is possible that in vivo, HCV induction of VEGF (by STAT3),

leads to the promotion of HCV entry into hepatocytes, via re-organization of

occludin. Clearly, this cannot be the only factor at play and further investigations into

other STAT3 dependent genes will be necessary to fully elucidate the role of STAT3

in the life cycle of HCV.

To firmly establish a role for STAT3 in HCV replication a constitutively active form

of STAT3 was used (STAT3-C). This construct has been extensively characterised by

Bromberg et al, and we demonstrated that STAT3-C is functional in our system and

displays normal cellular localization (Fig 6.6 & 6.7). The STAT3-C construct was

used in transient expression assays and a stable expression model. Both transient (Fig

6.8) and stable (Fig 6.11) expression of STAT3-C significantly enhanced JFH-1

replication. We hypothesise that activation of STAT3 by JFH-1 may lead to the

transcription of specific STAT3 dependent genes, which could potentially lead to the

production of proteins that may create an environment favourable for HCV

replication, or the proteins may directly enhance replication itself. However, further

microarray investigations will be required to ascertain a distinct STAT3 dependent

gene profile in HCV infected hepatocytes.

As mentioned previously STAT3 is activated by a number of cytokines and growth

factors, one of them being LIF. Figure 6.12 demonstrates that LIF treatment of JFH-1

infected Huh-7.5 cells significantly enhances HCV replication, presumably through

LIF induced STAT3 activation. One possible mechanism for the LIF induced increase

in HCV RNA could be the interactions between the molecular chaperone heat shock

protein 90 (HSP90), STAT3 and LIF (Setati et al.). HSP90 is a molecular chaperone

that plays a key role in the conformational maturation of many cellular proteins. It has

been documented that LIF promotes an association between HSP90 and STAT3,

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resulting in HSP90 chaperoning phosphorylated STAT3 into nucleus, thus preventing

degradation of STAT3. Hence, it is possible that activation of STAT3 by LIF may

lead to enhanced HCV replication via increased STAT3 dependent gene expression,

which is facilitated via an association between HSP90 and STAT3. Furthermore

HSP90 has been shown to play a role in HCV replication via stablization of the HCV

non-structural protein NS3 (Ujino et al. 2009).

To firmly establish STAT3 as a pro-viral host factor we next investigated if the

inhibition of STAT3 conversely decreased HCV RNA levels. Figure 6.13 depicts that

siRNA knockdown of STAT3 results in a 50% reduction of JFH-1 RNA levels.

Furthermore, when known inhibitors of STAT3: STA-21, AG490 and S31-201 were

used to treat JFH-1 infected cells, marked decreases in HCV replication were

observed (Fig 6.16). STA-21, AG490 and S31-201 reduced HCV replication by

approximately 70%. This substantial decrease in JFH-1 replication by STAT3

inhibition, was not seen in the HCV genomic replicon system. Treatment of genomic

replicon cells with STA-21 only modestly decreased HCV replication by 10%,

however, a slightly more significant decrease was seen with AG490 treatment

decreasing replication by approximately 35% (Fig 6.15). In support of this finding,

Waris et al showed a similar decrease in HCV replication with AG490 in replicon

cells (Waris et al. 2005).

The fact that STAT3 inhibition reduced HCV replication in the HCVcc system to

such a large degree, while conversely only causing moderate decreases in the genomic

replicon system, could be indicative of STAT3 playing a role in HCV entry or

assembly; as the HCV genomic replicon cells do not replicate the full life cycle of the

virus and no infectious virus particles are produced. As such, this possibility was

investigated and figure 5.16 demonstrates the effect of the STAT3 inhibitors on HCV

entry via an infectivity assay. STA-21 pre-treatment of Huh-7.5 cells causes

significant reductions in the susceptibility of these cells to JFH-1 infection, as shown

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by the substantial decrease in numbers of HCV positive foci in the STA-21 treated

cells (Fig 6.18A). AG490 and S31-201 treatment had a similar inhibitory effect on

infectivity (Fig 6.16B&C). Collectively, these results strongly suggest that STAT3 is

playing an integral role in the life cycle of HCV, possibly by facilitating entry of the

virus into cells.

Recently it has come to light that HCV utilizes microtubules to initiate a productive

infection and for entry into cells (Roohvand et al. 2009). Pertinent to this thesis are

the recent studies that cite STAT3 as having functional involvement in controlling

microtubule dynamics, via an interaction with STMN1. STMN1 is a microtubule

depolymerizing protein that has been demonstrated to be an integral regulator of the

microtubule cytoskeleton and has also been shown to be expressed highly in a large

number of human malignancies, including HCC (Belmont and Mitchison 1996;

Marklund et al. 1996; Wong et al. 2008). STAT3 has been shown to bind to and

attenuate the microtubule destabilizing protein STMN1. Therefore, once

phosphorylated STAT3 has bound to STMN1, the ability of STMN1 to depolymerize

tubulin is inhibited. As such, STAT3 directly facilitates polymerization of tubulin and

microtubule activity (Ng et al. 2006; Verma et al. 2009). While none of these

investigations were performed in hepatocytes, we hypothesize that activated STAT3

could be playing a role in assisting HCV entry via controlling microtubule dynamics.

We therefore investigated microtubule morphology in the presence of a STAT3

inhibitor. Due to time restraints, only STA-21 was utilized for these experiments.

Immunofluoresence studies showed that STA-21 treatment drastically reduced α-

tubulin staining, in a manner similar to the known microtubule depolymerizing agent

nocodazole (Fig 6.20). While preliminary, these results support our hypothesis that

STAT3 may be an important mediator of HCV entry, via the control of microtubule

dynamics. Figure 6.19 portrays a proposed model for STAT3 mediated control of

microtubules, leading to HCV entry. Obviously further investigations are required to

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confirm this hypothesis, but it does provide a potential molecular role for STAT3 in

the life cycle of HCV.

Collectively, the results from this chapter demonstrate convincingly that STAT3 plays

a pivotal role in the life cycle of HCV. STAT3 was found to be activated in genomic

replicon cells and JFH-1 infected cells, which corresponded to a downstream increase

in STAT3 binding to DNA promoter elements in the presence of HCV. Furthermore,

the expression of a constitutively active form of STAT3 lead to the enhancement of

HCV replication. Whereas, the converse inhibition of STAT3 with siRNA and

specific inhibitors, drastically decreased HCV replication. We believe STAT3 to be a

pro-viral host factor and propose that STAT3 could be facilitating entry via positive

regulation of microtubule activity.

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Chapter 7

Conclusions and Future Directions

HCV has emerged as a significant human pathogen worldwide and is now the most

common cause of liver disease in many countries (Dore et al. 2003). More than 70%

of individuals infected with HCV will go on to develop a chronic infection, which

over the course of 20-30 years can result in progressive liver disease and loss of

functioning hepatocyte mass (Thomas et al. 2000; Harris et al. 2002). A proportion of

chronically infected individuals will develop cirrhosis and eventually HCC (Seeff et

al. 1992; Poynard et al. 1997). While a number of factors contribute to disease

progression, alcohol consumption is one of the most significant co-factors leading to

exacerbation of liver disease (Corrao and Arico 1998; Safdar and Schiff 2004).

Alcohol consumption has been linked to increased rates of fibrosis, cirrhosis and HCC

and as such, persons infected with HCV are recommended to limit their alcohol intake

(Peters and Terrault 2002). Alcohol consumption has also been documented to

drastically reduce the anti-HCV efficacy of IFN-α treatment and as a result alcohol

consumption is a contraindication for IFN-α therapy (Mochida et al. 1996; Loguercio

et al. 2000; Safdar and Schiff 2004). Despite this strong epidemiological evidence, the

molecular mechanisms by which alcohol consumption exacerbates CHC development

and decreases the efficacy of IFN-α remain unresolved. Clearly, the relationship

between alcohol and HCV is complex and the mechanisms responsible for these

effects of alcohol are most likely not related to a single factor, but are a result of

alterations to hepatocyte homeostasis, production of cytokines and modulation of the

immune system. Alcohol is one of the most widely used toxic substances in the world

and while the effects of alcohol on the liver have been extensively studied (Szabo and

Bala 2010), the relationship and interaction between HCV and alcohol at the

molecular level remains largely unexplored. The reasons for this significant lack of

119

information are two-fold. Firstly, there is no small animal model available for the

study of HCV pathogenesis, thus the mouse/rat models that are often used for alcohol

related studies are not applicable. Secondly, the current hepatocyte derived Huh-7 cell

culture models used to study HCV lack the ability to metabolise alcohol, as they lose

expression of the alcohol metabolizing enzymes CYP2E1 and ADH. Thus the aim of

this thesis was to generate a cell culture model system that could be utilized to

thoroughly investigate the effects of alcohol metabolism on HCV replication and the

anti-viral effects of IFN.

In the context of HCV infection and alcohol consumption, the factors that lead to

increased rates of liver disease are complex, however, a common thread emerged

from this thesis: this being the combined production of oxidative stress generated by

alcohol metabolism and HCV replication. Hence a logical conclusion from these

observations is that HCV replication and alcohol metabolism act synergistically to

accelerate disease progression via oxidative stress mediated mechanisms. We have

demonstrated that alcohol (ethanol) metabolism (via CYP2E1) increases HCV

replication in our in vitro model system and furthermore the oxidative stress produced

via alcohol metabolism and HCV replication itself, act synergistically to enhance

HCV replication (chapter 4). These in vitro findings correlate with the known clinical

observation of increased HCV viral loads in infected individuals consuming alcohol

(Oshita et al. 1994; Pessione et al. 1998). Paradoxically, current literature suggests

that elevated serum HCV RNA levels in patients do not necessarily correlate with

accelerated disease progression (Zeuzem et al. 1996). However, this clinical

observation needs to be interpreted with caution, as serum HCV RNA levels do not

reflect intrahepatic HCV RNA levels. Thus further studies should be performed to

ascertain if there is a correlation between intrahepatic HCV RNA levels and disease

course (Gervais et al. 2001). Despite the fact that there is no correlation between

increased serum HCV RNA levels and accelerated disease progression, it is possible

that an increase in HCV viral load due to alcohol metabolism could, over time, act to

120

synergistically increase cellular oxidative stress levels, which are known to contribute

significantly to liver disease. Oxidative stress has been shown to accelerate liver

damage via a number of mechanisms – (i) lipid peroxidation, (ii) increased collagen

production, (iii) damage to mitochondria, (iv) decreased anti-oxidant expression, (v)

DNA damage and (vi) activation of transcription factors. Clearly, in HCV infected

individuals, the alcohol mediated exacerbation of liver disease will not be attributed to

just one mechanism such as increased HCV RNA levels, as we have shown in this

thesis. It will most certainly be a complicated and synergistic process and further

studies are required to dissect the mechanisms responsible. These questions will only

be answered once a small animal model of HCV infection is established. Such a

model would allow for investigation into the interactions between HCV and alcohol

metabolism in vivo. However, the fact that we have shown oxidative stress to be

increased in cells replicating HCV and metabolizing alcohol provides a rational basis

for the investigation of anti-oxidant therapy in CHC patients consuming alcohol.

Our observation of increased HCV replication in the context of alcohol metabolism

raises the question as to the molecular mechanism responsible for this effect. A

number of observations have lead to our hypothesis that the cellular transcription

factor STAT3 may be involved. Oxidative stress is a known activator of STAT3 and

consistent with this, is our observation that STAT3 phosphorylation is increased in the

context of alcohol metabolism. As work for this thesis progressed, it became

increasingly clear that STAT3 was not only potentially playing a role in the alcohol

induced increase in HCV replication, but emerged as an integral host player in the life

cycle of HCV. A series of experiments using specific inhibitors of STAT3, siRNA

directed knockdown of STAT3 and the expression of a constitutively active form of

STAT3 confirmed our hypothesis. We have shown that STAT3 plays a pivotal role in

the life cycle of HCV and identify STAT3 as a pro-viral host factor. This thesis

confirms and significantly extends the work of Waris et al, who showed that STAT3

was activated in Huh-7 cells harbouring the HCV replicon (Waris et al. 2005). The

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obvious question of how STAT3 may be acting to increase HCV replication remains

to be answered. Our observation that specific STAT3 inhibitors markedly decrease

HCV infectivity using the HCVcc system suggest that STAT3 may be acting during

early stages of the HCV life cycle, such as entry or assembly/egress. Time restraints

precluded us from defining a precise role for STAT3 in HCV entry and clearly future

work is needed to clarify the exact points of entry that STAT3 may be assisting HCV.

Preliminary HCVpp experiments failed to definitively clarify the role of STAT3 in

entry and further optimization of this system will be required in the future. It will also

be important to definitively ascertain the role of STAT3 in the HCV RNA replication

process.

The question of how a transcription factor could augment HCV entry then arises. Current

evidence suggests that HCV utilizes the cellular microtubule network for entry

(Roohvand et al. 2009) and it is possible that STAT3 could facilitate HCV entry via the

control of microtubule dynamics. This hypothesis is based on current findings in the

literature, in which STAT3 has functional involvement in microtubule dynamics. STAT3

has been documented to bind to and attenuate the microtubule destabilizing protein

STMN1. Once STAT3 has bound to STMN1, it inhibits the ability of STMN1 to

depolymerize tubulin (Ng et al. 2006; Verma et al. 2009). As such, STAT3 facilitates

polymerization of tubulin and positively regulates microtubule activity, thus potentially

enhancing HCV entry. Our preliminary findings support this hypothesis, as we have

shown that the specific STAT3 inhibitor (STA-21) causes tubulin depolymerization in

hepatocytes (chapter 6). Future directions arising from this project are to characterize the

interaction between STAT3 and STMN1 in the context of HCV replication.

As STAT3 has been shown to exert such a broad range of biological effects, it is possible

that STAT3 works at multiple levels to facilitate the establishment of a productive

infection. STAT3 is also a known transcriptional activator of VEGF (Nasimuzzaman et

al. 2007), a protein capable of promoting HCV entry into hepatocytes in vivo (Mee et

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al.). Thus it is conceivable that enhanced STAT3 activation may result in increased HCV

entry into hepatocytes via a variety of mechanisms. We also hypothesise that a distinct

set of STAT3 dependent genes are expressed in HCV infected hepatoctyes, which can in

turn lead to the production of proteins that could create a cellular environment that is

favourable for HCV replication. Future investigations will try to establish specific

STAT3 dependent genes that are expressed during HCV infection of Huh-7 cells. This

could be achieved through the use of HCV infected STAT3-C expressing cells and

microarray analysis. This would allow for the delineation of specific STAT3-C

dependent genes that are activated during HCV infection. STAT3 dependent genes

discovered in vitro could then be investigated in the HCV infected liver. Clearly, as

STAT3 exerts such a diverse set of responses, it has the potential to be playing a role in

multiple stages in the life cycle of HCV. Further clarification of the role of STAT3 in

HCV entry and egress is necessary to ascertain the precise molecular mechanism(s) by

which STAT3 contributes to the life cycle of HCV.

The activation of STAT3 by HCV has far reaching clinical implications. STAT3 is

defined as an oncogene and as such, STAT3 is highly pertinent in the cancer field,

where its biological effects are intensely researched. Due to its oncogenic nature there

have been a number of studies investigating a potential role for STAT3 in HCC

development. During the course of this thesis, this area of research has intensified and

Lin et al have shown that inhibition of STAT3 with NSC 74859 (S31-201), results in

HCC tumor regression in mice (Lin et al. 2009). Furthermore, Li et al documented

that RANi knockdown of STAT3 causes suppression of HCC tumor growth in nude

mice (Li et al. 2009a). The molecular mechanisms responsible for HCC development

are not entirely clear, however, a number of mechanisms have been postulated and

include the oncogenic potential of HCV (Liang and Heller 2004). It is possible that

HCV mediates HCC development by inducing the continual turnover of hepatocytes

and through the chronic production of oxidative stress in the liver. Both of these

events have the potential to cause genomic instability, which could potentiate HCC

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development. The results of this thesis demonstrate that STAT3 is phosphorylated as

a direct result of HCV replication (chapter 6) and therefore, as STAT3 is an

oncogene, it is highly likely to be playing a role in the development of HCC. Per year,

HCC arises in approximately 2% of HCV patients with cirrhosis. This causes

significant morbidity and mortality and requires treatment such as loco-regional

therapies and liver transplantation. Sorafenib is an approved medical therapy for

disseminated HCC but only extends median survival by approximately 3 months.

Clearly there is a need for better HCC therapies. Patients with cirrhosis are also less

likely to respond to IFN-α treatment and show a lower overall rate of SVR, compared

to non-cirrhotic patients. This is due to a number of reasons, including the need for

dose reduction in cirrhotic patients due to the fact they have higher rates of

complications such as neutropaenia and thrombocytopaenia. As such, better treatment

options for HCV infected patients with cirrhosis and HCC are urgently required. The

findings of this thesis form a basis for further clinical investigations into the use of

therapeutic strategies directed against STAT3. Anti-STAT3 therapies could

potentially be used in combination with current treatment options for CHC patients,

specifically at end stage liver disease courses in order to prevent HCC development.

One of the contraindications of IFN-α/ribavirin combination therapy is alcohol

consumption. This thesis has demonstrated that alcohol metabolism attenuates the

anti-HCV activity of IFN-α via disturbance of the JAK/STAT signaling cascade and

by specifically decreasing STAT1-Y701 phosphorylation in vitro (chapter 5). This

perturbation in JAK/STAT signaling can ultimately lead to decreased expression of

ISGs, which are the effector molecules of an IFN response. We have shown

specifically that levels of the anti-HCV ISGs viperin and ISG20 (chapter 5) are

significantly reduced in expression in Huh-7 cells metabolizing alcohol. Time

restraints allowed us to investigate only two ISGs, however, it seems likely that

expression of other ISGs will be attenuated in the presence of alcohol. These

observations are important not only for the identification of a molecular mechanism

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responsible for reduced IFN efficacy in HCV infected persons consuming alcohol, but

these results also suggest that alcohol may suppress the action of the endogenous anti-

viral IFN pathways. This finding could also be important for understanding the

pathogenesis of CHC in persons who consume alcohol. While, reduced ISG

expression may be the mechanism responsible for reduced IFN-α efficacy in HCV

infected patients consuming alcohol, it is clear that the deleterious effect of alcohol on

the liver is a complicated process and cannot be attributed to one single mechanism.

Other potential mechanisms include the reduction of viral-specific cytotoxic T-

lymphocytes and attenuated activity of natural killer activity (NK) cells. Moreover,

alcohol has been shown to modulate and activate antigen presenting cells and induce

the over production of pro-inflammatory cytokines (Szabo 1999; Encke and Wands

2000). Furthermore, the toxic metabolites produced during alcohol metabolism impact

on hepatocyte homeostasis and in combination with HCV infection, may induce

hepatocyte death, which can contribute to liver disease progression. The ability of

alcohol metabolism to inhibit other components of the cellular innate immune

response has been relatively unexplored and potentially may play a very important

role in clearance of HCV in vivo. It has been documented that acute alcohol

administration to mice results in suppression of TLR-3 signaling (Pruett et al. 2004).

As the TLR-3 and RIG-I pathways recognize viral RNA early following infection,

they are the hepatocytes first line of defense against HCV infection. Thus it is not

inconceivable to envisage that the host would be highly susceptible to chronic HCV

infection, if these two pathways were to be inhibited by alcohol consumption. Hence,

even in those patients not undergoing IFN-α therapy, the ability of their own innate

immune response to combat a HCV infection via an IFN response will be severely

compromised if they are consuming alcohol. Further studies are clearly required to

investigate the interactions between alcohol metabolism and the innate immune

recognition of HCV and other pathogens.

125

All of the studies performed in this body of work are in vitro, and while they add

significant data to this area of research, ultimately we await the development of a

small animal model, such as the mouse, in which to study HCV, as this will greatly

advance our understanding of the interaction between alcohol, HCV and the host.

7.1 Proposed Model of Interactions Between HCV and Alcohol

The in vitro findings of this thesis indicate that alcohol metabolism is able to decrease

the efficacy of IFN-α and increase HCV replication. In the chronically infected HCV

individual, who consumes alcohol, it is most definitely a combination of factors that

contribute to an increase in liver disease progression. Figure 7.1 depicts our model for

the accelerated rates of disease progression in CHC patients that consume alcohol,

focusing on the synergistic effects of the combined oxidative stress that is produced

by HCV replication and alcohol metabolism. This model shows that there is increased

HCV replication and perturbation of endogenous and exogenous IFN-α signaling, in

combination with increased chemokine and cytokine expression leading to increased

inflammation. The transcription factor STAT3 is activated by HCV and alcohol

metabolism, and can contribute to liver disease progression by increasing HCV RNA

levels and potentially enhancing HCV entry into hepatocytes. Also documented is the

activation of hepatic stellate cells by oxidative stress, leading to increased production

of collagen and thus accelerating rates of fibrosis and cirrhosis. Finally, oxidative

stress can induce DNA damage and STAT3 activation, both of which can potentially

promote HCC development.

In summary, we have developed an in vitro cell culture model to evaluate the

interactions between alcohol metabolism and HCV. Specifically we have shown that

metabolism of alcohol by CYP2E1 results in the enhancement of HCV replication and

this is mediated by oxidative stress. Furthermore, we have demonstrated that alcohol

can impair the anti-HCV action of IFN-α through abrogation of the JAK/STAT

AlcoholCYP2E1

CYP2E1

Inhibition of IFNSignaling

HCV Replication

Oxidative StressROS

HCVCore

NS5A

HCV replication

Oxidative StressROS

Activation Transcription factors

(STAT3)

Chemokine & Cytokine Expression

Oxidative StressROS

HCV Entry/Replication

?

STAT3Activation

Figure 7.1 Proposed model of interactions between HCV, alcohol and hepatocytes

126

signaling pathway. These in vitro observations are particularly important, because

they are consistent with the known clinical effects that alcohol consumption exerts in

HCV infected persons undergoing IFN therapy. The protective effect of the anti-

oxidant NAC on reducing HCV replication levels implies a potential therapeutic role

for anti-oxidant supplementation to augment standard interferon based antiviral

therapies. In addition, these studies also emphasize the need for further investigations

into the role of STAT3 in the life cycle of HCV and highlight a role for therapies

directed against STAT3 in CHC patients, in order to limit disease progression and

potentially prevent HCC development. Further dissection of the interactions between

alcohol, HCV and the hepatocyte using this model system will aid in our

understanding of CHC in the setting of alcohol consumption. Hopefully this insight

will aid in the design of future investigations to be performed in a small animal model

of HCV pathogenesis.

127

Appendices

Appendix I. General Solutions and Buffers

The following solutions were obtained from the Central Services Unit, School of

Molecular Life Sciences, University of Adelaide.

Competent Cells

The genotype of DH5a strain used in this thesis was :

F’/endA1 hsdR17 (rk- mk

+) supE44 thi-1 recA1 gyrA (Nalr) relA1 Δ (laczYA –

argF)u169 (m80lacZΔM15)

EDTA

FCS

L-Agar + ampicillin plates

Luria Broth

PBS

SDS

SSC

TAE

Tris

128

Solution Components

RIPA Buffer 1% NP-40

5% sodium deoxycholate

0.1% SDS in PBS

Cell Lysis Buffer 1M Tris [pH 7.5]

0.5M EDTA

4M NaCl

0.5% NP-40

5X Stop Buffer 10% SDS

1M Tris [pH 7.5]

0.5mM EDTA

10X TAE Loading Buffer 60% sucrose

1% Sarkosyl

1X TAE

0.1% bromophenol blue

0.1% xylene cyanol

12% Separating Gel 12% acrylamide (Sigma)

0.4M Tris (pH 8.8)

0.1% SDS

0.1% ammonium persulfate (Sigma)

0.025% TEMED (Sigma)

5% Stacking Gel 5% acrylamide (Sigma)

0.13M Tris (pH 6.8)

0.1% SDS

0.1% ammonium persulfate (Sigma)

0.1% TEMED (Sigma)

129

SDS PAGE Running Buffer 2.9% Trisma Base

14.14% glycine

1% SDS

2X Laemmli Buffer 4% SDS

16% glycerol

0.02% bromophenol blue

10% β-mercaptoethanol

0.1M Tris (pH 6.8)

SDS PAGE Transfer Buffer 0.3% Tris Base

1.44% glycine

20% methanol

130

Appendix II. Infectious HCV Constructs.

Full length JFH1 construct (GT2a) and J6CF (GT2a). The chimeric Jc1 construct

consisting of the structural proteins and NS2 of the J6CF clone with the non-structural

proteins of JFH1.

131

Appendix III. pcDNA6/V5-His

132

Appendix IV. pcDNA-2E1

133

Appendix V. pcDNA-2E1-AS (CYP2E1 Anti-Sense)

134

Appendix VI. PRL-HL

(Gift from Professor Stanley Lemon)

NOTE: This appendix is included in the print copy of the thesis held in the University of Adelaide Library.

135

Appendix VII. pSTAT3-Luc

(Panomics)


136

Appendix VIII. pRL-TK

(Invitrogen)


137

Appendix IX. pISRE-Luc

138

Appendix X. PRc/CMV-STAT3-C

(Gift from Professor JF Bromberg)


139

Appendix XI. pRc/CMV

(Invitrogen)


140

Appendix XII. Publications

McCartney, E.M., Semendric, L., Helbig, K.J., Hinze, S., Jones, B., Weinman, S.A. and Beard, M.R. (2008) Alcohol Metabolism Increases the Replication of Hepatitis C Virus and Attenuates the Antiviral Action of Interferon. The Journal of Infectious Diseases, v.198 (12), pp. 1766-1775, December 2008

NOTE: This publication is included in the print copy of the thesis

held in the University of Adelaide Library.

It is also available online to authorised users at:

http://dx.doi.org/10.1086/593216

1337 March 21, 2010|Volume 16|Issue 11|WJG|www.wjgnet.com

Erin M McCartney, Michael R Beard, Centre for Cancer Biol-ogy, Hanson Centre, Adelaide, South Australia, 5000, Australia; School of Molecular and Biomedical Science, University of Adelaide, Adelaide, South Australia, 5000, AustraliaAuthor contributions: McCartney EM and Beard MR con-tributed equally to this work.Correspondence to: Michael R Beard, PhD, School of Molecular and Biomedical Science, University of Adelaide, Adelaide, South Australia, 5000, Australia. [email protected]: +61-8-83035522 Fax: +61-8-83037532Received: December 12, 2009 Revised: February 2, 2010Accepted: February 9, 2010Published online: March 21, 2010

AbstractHepatitis C virus (HCV) is one of the main etiological factors responsible for liver disease worldwide. It has been estimated that there are over 170 million people infected with HCV worldwide. Of these infected indi-viduals, approximately 75% will go on to develop a life long necroinflammatory liver disease, which over decades, can result in serious complications, such as cirrhosis and hepatocellular carcinoma. Currently there is no effective vaccine and whilst antiviral therapies have been improved, they are still only effective in ap-proximately 50% of individuals. HCV infection stands as a major cause of global morbidity and suffering, and places a significant burden on health systems. The second highest cause of liver disease in the western world is alcoholic liver disease. Frequently, HCV in-fected individuals consume alcohol, and the combined effect of HCV and alcohol consumption is deleterious for both liver disease and response to treatment. This review discusses the impact of alcohol metabolism on HCV replication and the negative impact on interferon (IFN)- treatment, with a particular focus on how al-cohol and HCV act synergistically to increase oxidative

stress, ultimately leading to exacerbated liver disease and a reduction in the efficacy of IFN- treatment. A better understanding of the complicated mechanisms at play in hepatocytes infected with HCV and metabo-lizing alcohol will hopefully provide better treatment options for chronic hepatitis C individuals that consume alcohol.

© 2010 Baishideng. All rights reserved.

Key words: Alcohol metabolism; Hepatitis C virus; Re-active oxygen species; Interferon signaling

Peer reviewer: Dr. Claudia Zwingmann, PhD, Professor, Department of Medicine, University of Montreal, Centre de Recherche, 264 Rene-Levesque Est, Montreal, QC, H2X 1P1, Canada

McCartney EM, Beard MR. Impact of alcohol on hepatitis C virus replication and interferon signaling. World J Gastroenterol 2010; 16(11): 1337-1343 Available from: URL: http://www.wjg-net.com/1007-9327/full/v16/i11/1337.htm DOI: http://dx.doi.org/10.3748/wjg.v16.i11.1337

INTRODUCTIONHepatitis C virus (HCV) has emerged as a significant hu-man pathogen worldwide and is now the most common cause of significant liver disease in many countries[1]. Although the disease is typically not severe in the acute phase, more than 70% of infected individuals develop a persistent infection that, over the course of 2-3 de-cades, can result in progressive hepatic fibrosis and loss of functioning hepatocyte mass[2,3]. A proportion of infected individuals will develop cirrhosis and eventu-ally hepatocellular carcinoma (HCC)[4,5]. This progressive liver disease is thought to arise as a result of the chronic inflammatory response to clear HCV infected hepato-

TOPIC HIGHLIGHT

World J Gastroenterol 2010 March 21; 16(11): 1337-1343 ISSN 1007-9327 (print)

© 2010 Baishideng. All rights reserved.

Online Submissions: http://www.wjgnet.com/1007-9327office

[email protected]:10.3748/wjg.v16.i11.1337

Impact of alcohol on hepatitis C virus replication and interferon signaling

Erin M McCartney, Michael R Beard

Natalia A Osna, MD, PhD, Series Editor

cytes, resulting in an environment that is favorable for the fibrogenic process[6].

There are numerous clinical studies that suggest a strong epidemiological link between the consumption of alcohol and accelerated liver disease in HCV infected individuals[7-9]. The majority of alcohol metabolism takes place in hepatocytes, which is also the primary site of HCV replication, and thus it is logical that interactions between the two will occur, both at the clinical and mo-lecular level. The majority of studies have concluded that HCV infected individuals that consume alcohol show a strong propensity for accelerated liver disease, and that alcohol metabolism and concurrent HCV infec-tion act synergistically to facilitate this rapid disease pro-gression[7-11]. In fact, excessive alcohol consumption is now a recognized co-factor in liver disease progression, and persons infected with HCV are recommended to limit their alcohol intake[12]. Despite strong epidemiologi-cal evidence, the molecular mechanisms by which alco-hol consumption exacerbates chronic hepatitis C (CHC) remain unclear. Furthermore, the interactions between alcohol metabolism, HCV, and the host antiviral immune response are also unknown. Clearly, the relationship be-tween alcohol and HCV is complex, and the mechanisms responsible for accelerated disease progression are most likely not related to a single factor, but are the result of alterations to hepatocyte homeostasis, production of cy-tokines, and modification of the immune system.

This review will focus on the role that alcohol me-tabolism has on HCV RNA replication and discuss the potential molecular mechanisms responsible, with a par-ticular focus on oxidative stress. The effect of alcohol on interferon (IFN)- action and its modulation of signal transduction pathways will also be discussed.

ALCOHOL CONSUMPTION ACCELERATES HCV RELATED LIVER DISEASEOne of the first reports documenting the role of alco-hol consumption on CHC progression was published by Seeff et al[5], in which they reported that two thirds of HCV positive patients that died from end stage liver disease were chronic consumers of alcohol. Poynard et al[4] extended this study, showing that the consumption of 50 g/d of alcohol increased the rate at which fibrosis progresses in HCV infected individuals. They also iden-tified three independent risk factors that were associated with increased rates of fibrosis: age greater than 40 years at time of infection, being male, and consuming more than 50 g of alcohol per day. At the virological level, Pessione et al[8] found a direct dose dependent correla-tion between increasing HCV RNA levels and increas-ing levels of alcohol consumption. The mechanism for this increase was not established, but it was postulated that the increase in HCV RNA could be due to a direct effect of alcohol increasing viral replication or through reduced clearance of the virus by the immune system. One of the most comprehensive studies investigating

the effect of alcohol on HCV disease progression was performed by Corrao et al[9], in which they studied a large cohort of 417 patients. The most striking finding of this study was a comparison of the associated risk factors for developing cirrhosis between HCV infected patients that abused alcohol and those that abstained. The risk factor for developing cirrhosis in patients that were HCV positive but did not consume alcohol was 9, compared to a significantly higher risk factor of 147 for those patients that abused alcohol. This study added further weight to the hypothesis that HCV and alcohol metabolism synergistically contribute to exacerbated liver disease.

There have been a number of studies that have doc-umented a clear link between excess alcohol consump-tion and an increased risk of HCC development. It has been suggested that HCV infected individuals that con-sume alcohol show a 100-fold increase in their risk of developing HCC[13-18]. Clearly, chronic consumption of alcohol in HCV infected individuals is a dangerous mix, with significant clinical implications.

ALCOHOL AND HCV INDUCE OXIDATIVE STRESS Reactive oxygen species (ROS) are defined as small highly reactive oxygen-containing molecules that cause oxidative stress when the rate at which they are pro-duced is greater than the rate at which they are removed, leading to a disturbance in the pro-oxidant/anti-oxidant balance. Cytochrome P450-2E1 (CYP2E1) metabolism of alcohol stimulates the microsomal production of ROS, such as superoxide anions (O2

.-), hydroxyl radicals (OH-), 1-hydroxyethyl radicals (CH3C.HOH), lipid hy-droperoxides (LOOH), and (when iron levels increase due to alcohol metabolism) the production of ferryl radicals[19]. Oxidative stress can potentially lead to cellu-lar damage that can play a role in a variety of pathologi-cal conditions[20]. The generation of hepatic oxidative stress in CHC is now well established, and most likely a consequence of HCV proteins disrupting mitochondrial and hepatocyte organelle function, in addition to the inflammatory response directed towards HCV infected hepatocytes. Under normal conditions, oxidative stress exists in a state of equilibrium with cellular antioxidants that scavenge ROS and prevent cellular injury. However, when cellular antioxidant mechanisms are overwhelmed through chronic oxidative stress or disease processes, oxidative stress production continues unchecked, with pathological consequences. This chronic exposure of the liver to oxidative stress in CHC has significant clini-cal implications, as it is well documented that oxidative stress is a mediator of hepatic inflammation, fibrosis, and the development of HCC[21].

One of the most significant mediators of oxida-tive stress in the liver is the metabolism of alcohol by the enzyme CYP2E1. Metabolism of alcohol can also occur via the other main alcohol metabolizing enzyme


McCartney EM et al . Alcohol metabolism and HCV replication

alcohol dehydrogenase (ADH). Whilst ADH-mediated metabolism of alcohol does produce ROS, CYP2E1-mediated metabolism of alcohol produces levels of ROS that greatly exceed that of the ROS produced by ADH. Alcohol metabolism not only directly produces ROS, but it also creates an environment that is favorable for oxidative stress. It is becoming increasingly clear that oxidative stress plays a prominent role in the pathogen-esis of alcohol-induced liver disease[22] and CHC[21]. It is therefore not difficult to envisage the potentially explo-sive situation where oxidative stress produced by HCV and alcohol leads to a synergistic exacerbation of liver disease.

HCV INFECTION INDUCES A STATE OF OXIDATIVE STRESSWhile clinical studies have suggested that markers of oxidative stress are increased in CHC, it was the devel-opment of mice transgenic for the HCV core protein that clearly demonstrated that HCV directly induces a state of oxidative stress[23]. Mice expressing either the HCV core or the complete HCV polyprotein developed pathologies consistent with those observed in human HCV infection[23,24], such as steatosis and development of HCC. Prior to HCC development, the HCV core-expressing mice showed a marked increase in lipid peroxidation and activation of the anti-oxidant system, suggesting that the expression of HCV core is sufficient to induce oxidative stress in the mouse liver and initiate HCC through DNA damage and modulation of signal-ing cascades[23]. It was subsequently shown in vitro that HCV core expression results in increased generation of ROS and expression of antioxidant enzymes[25-27]. Mech-anistically, it was shown that this increase in oxidative stress was due to interactions between HCV core and destabilisation of the mitochondrial electron transport chain and that this was further enhanced in the presence of alcohol[28,29].

In addition to the core protein, the HCV nonstruc-tural protein non-structural 5A (NS5A) has also been demonstrated to increase cellular ROS, albeit through a different mechanism to that of the HCV core. HCV NS5A localizes to the endoplasmic reticulum (ER) and lipid droplets, and is part of the HCV replication com-plex that results in the formation of altered cytoplasmic membrane structures, known as the membranous web. It has been postulated that this change in the membrane structure results in ER stress and the unfolded protein response, leading to the release of ER Ca2+ stores and resulting in the formation of oxidative stress[30]. Expres-sion of ectopic NS5A results in oxidative stress, and NS5A-induced transcriptional activation can be blocked by the treatment of cells with the free radical scavenges pyrrolidine-2,4-dicarboxylate acid and N-acetyl-cysteine (NAC)[31], suggesting that NS5A induces a state of oxida-tive stress in the cells. However, these studies should be interrupted with caution, as they are reliant on ectopic

over-expression of HCV proteins in the absence of the complete repertoire of HCV proteins and RNA replica-tion. However, Huh-7 cells harboring the HCV replicon do induce a state of oxidative stress[32,33]. Thus, it is logical to hypothesize that HCV replication and alcohol me-tabolism lead to a synergistic increase in hepatic oxidative stress that contributes to accelerated liver disease.

ALCOHOL MODULATES HCV REPLICATIONAs previously outlined, there is clinical evidence to sug-gest that alcohol metabolism increases HCV replication and modulates the host response to HCV[4,7,8]. While the exact molecular mechanisms are unclear, there have been a number of postulated mechanisms, such as (1) an al-cohol-induced increase in HCV RNA replication; (2) en-hancement of HCV quasispecies complexity; (3) modu-lation of the immune system; and (4) synergistic increase in ROS. However, pinpointing the precise mechanism of how alcohol and HCV interact in the laboratory has been hampered by the lack of a small animal model of HCV pathogenesis and, until recently, the inability to culture the virus. However, the recent development of a fully permissive cell culture system for HCV has been a significant advancement for the study of HCV biol-ogy[34]. This is further compounded by the fact that he-patocyte-derived cell lines (including the Huh-7 cell line that is permissive for HCV replication) do not express the alcohol metabolizing enzymes ADH and CYP2E1 in culture. However, numerous studies have been con-ducted using non-CYP2E1/ADH hepatocyte derived cell lines to determine the impact of alcohol on HCV replication, often with conflicting conclusions. To over-come this limitation, hepatocyte derived cell lines have been engineered to express CYP2E1[19], including Huh-7 cell lines that support HCV replication and metabolize alcohol[32]. These cells provide a useful tool to study the molecular interactions between alcohol metabolism and HCV.

There are conflicting reports surrounding the role of alcohol metabolism on HCV replication in vitro, which most likely reflects the different model systems used in different laboratories. Using HCV replicon cell lines that constitutively express CYP2E1 (replicon cells constitutively replicate HCV RNA under the control of an antibiotic selection marker, but do not produce in-fection virus particles), it was shown that physiological concentrations of alcohol (0-100 mmol/L) resulted in a CYP2E1-dependent increase in HCV RNA levels, 72 h following alcohol stimulation[32]. This alcohol-induced increase in replication was blocked in the presence of the anti-oxidant NAC, strongly suggesting that oxidative stress plays a central role in this alcohol-induced effect. Furthermore, consistent with the data suggesting that HCV induces a state of oxidative stress alone, NAC reduced HCV replication by 50% in both HCV repli-con cell lines and Huh-7 cells infected with HCV cell



culture derived virus (JFH-1) (Beard MR, personal com-munication). Therefore, it is conceivable that HCV uses oxidative stress to its replicative advantage. Moreover, when the infectious HCV JFH-1 virus was used to infect CYP2E1 expressing Huh-7 cells, treatment with alcohol also resulted in a significant increase in HCV (JFH-1) replication (Beard MR, personal communication). Col-lectively, these results suggest that CYP2E1-mediated metabolism of alcohol results in an increase of HCV replication, at least in vitro, and are consistent with the clinical observations described earlier. In contrast, CY-P2E1-independent, alcohol-induced increases in HCV replication have been reported using the HCV replicon system[35,36]. Conversely, it was shown that a single dose of acute ethanol exposure inhibits HCV replication[37]. There are several methodological issues that explain these apparent discrepancies. Firstly, Huh-7 cells are dif-ferent between laboratories and it is possible that low basal levels of CYP2E1/ADH exist. Secondly, there are significant differences in these studies in regards to ex-perimental design that could account for the differences noted. For example, significant differences may occur depending on whether experimental conditions mimic acute or chronic exposure to ethanol. Acute alcohol me-tabolism results in a rapid increase in cellular ROS and it is possible that this burst of oxidative stress can inhibit replication[38,39]. This correlates with unpublished find-ings in our laboratory, where the treatment of HCV rep-licon cells and HCVcc (JFH-1) infected Huh-7 cells with H202, to induce an acute burst of oxidative stress, results in a decrease in HCV replication, although chronic expo-sure to alcohol increases HCV replication. We have also shown in our laboratory that there is a bi-phasic effect of alcohol metabolism on HCV replication, suggesting that perhaps moderate levels of oxidative stress stimulate replication whereas more pronounced levels of oxidative stress could repress replication[32].

The molecular mechanism whereby ROS modulates HCV replication is unknown. However, ROS have the ability to act as potent second messengers and activate cellular transcription factors, such as STAT3, nuclear fac-tor B, NF-AT, and AP-1[31,40]. Interestingly, it has been reported that ROS induced by HCV replication in vitro can activate the transcription factor STAT3, which can, in turn, lead to the stimulation of STAT3-dependent genes that are capable of creating a cellular environment favourable for HCV replication[41]. Our laboratory has also shown this HCV/ROS increase in STAT3 activation. Expression of a constitutively active STAT3 molecule increases HCV replication, while conversely, specific inhibitors of STAT3 (AG490 and STA-21) cause significant decreases in repli-cation (Beard MR, unpublished results). Clearly, the role of STAT3 and STAT3-dependent gene expression war-rants further investigation.

However, not all studies implicate ROS in the in-crease in HCV replication following alcohol stimulation. Seronello et al[42] suggested that metabolism of alcohol modulates host lipid metabolism, thus, potentiating

HCV replication. Obviously, the interactions between HCV and alcohol metabolism is a complex and multi-factorial process (Figure 1), and further investigations are required to ascertain the role of the alcohol-induced modulation of HCV replication.

EFFICACY OF IFN- IN THE PRESENCE OF ALCOHOL METABOLISMIFN-2b/Ribavirin combination therapy is the cur-rent and only treatment strategy for CHC. Whilst the exact mode of IFN- action is not well understood, IFN- therapy is thought to result in the induction of interferon-stimulated genes (ISGs), many of which have antiviral activity. The binding of IFN to its cellular recep-tor results in rapid autophosphorylation and activation of receptor-associated Janus activated kinases (JAKs), TYK2 and JAK1, and activation of the JAK/STAT signal-ing cascade[43]. TYK2 and JAK1 phosphorylate tyrosine residues on the cytoplasmic tail of the receptor, this pro-vides docking sites for the signal transducer and activator of transcription (STATs), which are latent cytoplasmic transcription factors that transduce signals from the cell surface to the nucleus, where they directly regulate tran-scription. STAT1 is phosphorylated at tyrosine residue 701 (Y-701) and STAT2 at tyrosine residue 690 (Y-690). Once phosphorylated, STAT1 and STAT2 then form ac-tive heterodimers and translocate to the nucleus where they directly activate transcription via the multi compo-nent transcription factor ISG factor 3, which binds to the interferon-stimulated response element (ISRE), a cis-acting DNA element found in the promoters of the ma-jority of type Ⅰ IFN genes. Within the nucleus, STAT-1 is further phosphorylated on serine residue 727, resulting in an increase in the transcriptional activation ability of this complex. The end step of this signaling cascade cul-


Alcohol

CYP2E1CYP2E1

HCVcoreNS5A

HCV replication

Activation of OSsensitive

transcription factorsSTAT3, AP-1, NF-B

Chemokine/cytokineexpression

Oxidative stressROS

Oxidative stressROS

Oxidative stressROS

Activation of hepaticstellate cells

↑Fibrosis/cirrhosis

OS induced DNA damage

↑HCC

↑Inflammation

Inhibition of IFNsignaling HCV replication

Figure 1 Proposed model of hepatitis C virus (HCV)/alcohol interactions

in hepatocytes. Metabolism of alcohol by cytochrome P450-2E1 (CYP2E1) and HCV replication leads to a synergistic induction of oxidative stress in the cell. Oxidative stress inhibits interferon (IFN)- signalling and also leads to increased rates of inflammation, cirrhosis, and hepatocellular carcinoma (HCC). NS5A: Non-structural 5A; NF-B: Nuclear factor B; ROS: Reactive oxygen species.


minates in the transcriptional activation of hundreds of ISGs. These produce anti-viral proteins capable of limit-ing HCV replication in hepatocytes and modulating the immune response (Figure 2). As mentioned previously, it is a well established clinical observation that alcohol consumption reduces the efficacy of IFN treatment[7]. The molecular basis that underlies the reduced anti-viral capacity of IFN- in the presence of alcohol metabolism remains to be established; however, evidence suggests that alcohol might directly inhibit the actions of IFN- in patients at the signaling level.

In combination with the effect of alcohol on HCV replication and accelerated disease progression, alcohol metabolism also decreases the efficacy of IFN-. Pa-tients who consume alcohol do not respond effectively to IFN- therapy and for this reason alcohol consump-tion is contraindicated during IFN- treatment. There have been numerous studies confirming that alcoholics do not respond well to IFN- therapy. Mochida et al[44] showed that less than 10% of alcoholic patients re-sponded to IFN- therapy. Loguercio et al[45] showed a direct relationship between alcohol consumption and response to treatment, with the numbers of patients achieving a sustained virological response decreasing as alcohol consumption increased. Safdar et al[7] recently published their findings that alcohol abuse decreases response to IFN treatment in HCV patients and there-

fore, it is recommended that HCV infected patients ab-stain from alcohol consumption whilst on treatment. A number of studies have shown that alcohol metabolism directly interferes with IFN signaling, indicating that the consumption of alcohol could directly inhibit IFN- treatment in patients. However, there has been some recent evidence indicating that the high non-compliance rate of alcoholics adhering to treatment programs could account for the reduced response rates of alcoholic pa-tients in the literature[46]. Whilst this is certainly a contrib-uting factor, it does not detract from the strong in vitro data showing that alcohol has a direct inhibitory effect on IFN- signaling. These studies have implications not only for IFN- treatment, but also for the activity of endogenously produced type Ⅰ and Ⅱ IFN’s (IFN-, , and , respectively) that might result in a weakened host response to HCV infection.

ALCOHOL AND IFN- SIGNALINGThere are a number of reports investigating the effects of HCV on IFN- signaling, suggesting that HCV negatively impacts on IFN- signaling[47-51]; however, there are a limited number of studies investigating the combined effects of HCV and alcohol metabolism on IFN- signaling. Insights into the effect of alcohol metabolism on IFN- signaling can be gleaned from the study conducted by Osna et al[52], in which the ef-fects of alcohol metabolism by ADH and CYP2E1 on IFN- signal transduction were investigated. This study documented a decrease in STAT1 tyrosine phosphoryla-tion in the presence of alcohol metabolism, suggesting that alcohol can effectively dampen the IFN signaling cascade. The most comprehensive study investigating the effects of alcohol and HCV replication on IFN signaling was conducted by Plumlee et al[37]. This study showed that acute treatment of HCV genomic replicon cells with ethanol lead to the inhibition of the anti-HCV effects of IFN and interestingly, caused a decrease in STAT1 tyrosine phosphorylation, but induced STAT1 serine phosphorylation. This study also showed induc-tion of ISRE promoter activity in the presence of alcohol, which is somewhat contradictory to their find-ing that IFN signaling was abrogated. It has also been documented that the oxidative stress generated via the treatment of Huh-7 cells with H202, disrupted the JAK-STAT signaling pathway specifically, by blocking STAT1, STAT2, JAK1, and TYK2 tyrosine phosphorylation[53]. More recently it has been shown that alcohol metabo-lism decreases the efficacy of IFN- in vitro in genomic replicon cells that express CYP2E1[32]. In this study, alcohol metabolism preferentially inhibited STAT1 tyro-sine phosphorylation at residue 701 (Y701), the critical residue required for STAT1 heterodimerisation with STAT2[32]. These findings suggest that a decrease in STAT1-Y701 phosphorylation due to alcohol metabo-lism would decrease downstream ISG expression and, in part, explain the reduced efficacy of IFN- in HCV positive patients that consume alcohol. Consistent with


Alcohol inhibits Y701

JAK1

STAT1

STAT1STAT2

STAT2

TYK2

p p

ISGF3

IRF-9

S727

ISG expression

IRF-9

ISRE

Y701

Anti-viralImmunomodulatoryGrowthdifferentiation

Y690

INFA

R1

INFA

R2

STAT2 STAT1

IFN-

Alcohol decreases ISRE activity Alcohol reducesISG output

Figure 2 IFN- signal transduction. Binding of IFN- to its cognate receptor on the cell surface results in activation of the Janus activated kinase (JAK)/STAT signaling pathway culminating in the production of interferon-stimulated genes (ISGs), many of which have anti-viral properties that act to limit HCV infection. Alcohol inhibits Y701, decreases interferon-stimulated response element (ISRE) activity, and subsequently dampens the ISG response.


this finding, a decrease in ISRE activity in the presence of alcohol metabolism was also observe[32] and a number of anti-viral ISGs have been shown to be downregulated by alcohol metabolism (Beard MR, unpublished find-ings). Collectively, these studies suggest that alcohol can specifically inhibit IFN- at the molecular level.

Clearly, the factors at play in the alcohol-induced suppression of IFN signaling in the background of HCV replication are multifactorial and complicated in an infected patient. It is also possible that alcohol can inhibit other components of the cellular innate immune response, such as components of the cellular recognition of viral pathogen-associated molecular patterns, and by activation of the toll-like-receptor-3 and the retinoic acid-induced gene-1 pathways. Another possibility is that alco-hol might modulate SOCS-1 and -3, which are part of a negative feedback loop that acts to suppress IFN-signal-ing. It has been shown using a concanavalin-A model of hepatitis in mice that activated STAT3 plays an important role in inducing SOCS-3[54]. Interestingly, as outlined previously, we have been able to demonstrate that both alcohol metabolism and HCV replication are capable of activating STAT3, and it appears that this increase is due to oxidative stress.

CONCLUSIONIn summary, it is well established clinically that chronic al-cohol consumption in the setting of CHC is a dangerous combination leading to exacerbated liver disease. While the factors that lead to increased liver disease are com-plex, it seems that a common thread throughout many investigations is the generation of oxidative stress by both alcohol metabolism and HCV replication. Thus, it is a logical conclusion that HCV and alcohol metabolism act synergistically to accelerate disease progression via oxidative stress. In an attempt to understand these pro-cesses we have developed a model to portray these inter-actions (Figure 1). Evidence suggests that this oxidative stress synergy impacts on HCV replication and the anti-viral action of IFN-, although we are waiting for the development of a small animal model to confirm these in vitro observations. Defining the molecular mechanisms and complex interactions between HCV and alcohol will further our understanding of the pathogenic role alcohol plays in CHC development and hopefully lead to novel therapeutic strategies and patient management.

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S- Editor Tian L L- Editor Stewart GJ E- Editor Zheng XM


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Molecular interactions between alcohol, hepatitis C virus ...€¦ · Figure 1.1 Clinical spectrum...

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