Investigation into the role of novel interferon
lambdas in the treatment of viral disease,primarily hepatitis C
Thesis submitted for the degree of

DOCTOR OF PHILOSOPHY
atImperial College London
Rhiannon May Lowe2012
Academic supervisor: Professor Mark R. Thursz
Industrial supervisor: Dr Peter MorleyHepatology Section
School of Medicine
Imperial College London
St Mary’s Campus
Norfolk Place
Paddington
London, W2 1PG

Page 1 of 183

Abstract
Interferon lambdas (IFNλs), termed IFN-λ1, IFN-λ2 and IFN-λ3, or IL-29, IL-28A
and IL-28B are a recently identified family of cytokines with antiviral activity. IL28A/B and IL-29 bind to a novel heterodimeric receptor complex formed
between IL-28 receptor (IL-28R) and IL-10 receptor (IL-10R2). Type I IFNs areused therapeutically in the treatment of chronic hepatitis B and C; however only
~30% of patients with hepatitis B virus will be successfully treated and only
~60% of patients with chronic HCV. New interventions are therefore required toaddress this unmet medical need and this thesis aimed to evaluate the potential
use of IFNλs in treating viral infection.
A range of in vitro antiviral assays were developed to determine which viruses
were inhibited by IFNλs. Results showed IL-28A and IL-29 have antiviral effects
with HCV 1a and 1b replicons and HBV. No antiviral effect was demonstrated
against dengue, RSV or HIV. Gene expression stimulated by IFNλ wascompared with IFNα; and the effects of IFNλ against HCV were investigated.
The types of genes induced, and the kinetics of gene induction were similar
between the type I and type III IFNs in the HCV replicon cell line. With theparental cell line, the interferon signalling pathway was the most greatly affectedby IFNα, IL-28A and IL-29, but IL-29 strongly regulated the antigen presenting
pathway compared with IFNα. IL-28R distribution was determined to investigate
the tissue and cellular distribution of IFNλ responsive cells. IL-28R was
expressed in epithelial tissues, lymphoid tissue, spleen, liver, kidney andthymus, with majority of IL-28R expression on macrophages and dendritic cells.
The differences between type I and type III IFNs need to be further investigated
but these differences identified provide a rationale for exploring the use of type
III IFNs as an alternative to IFNα in the treatment of viral diseases.

Statement of Originality
All work is my own unless acknowledged and all else is appropriately
referenced.

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Acknowledgements
To Professor Mark Thursz and Dr Peter Morley for being there for me at every
step of the PhD. I want to thank Mark for never giving up on me and always
believing that I could do it, he gave me initial advice when SB and Glaxo were
merging to hang in and apply to do a part time PhD with Imperial and thenGlaxoSmithKline. Dr Peter Morley was happy to give me help at the beginningof the PhD despite the fact I was working in Safety Assessment (SA) and myday job role is quite different from the PhD interest, he agreed kindly to be myjoint industrial supervisor with Dr Chantelle Ward when Dr Chris Clarke (SA) left
GSK.
Dr Chris Clarke who was my initial GSK supervisor in 2005 and Dr Chantelle
Ward (made redundant Dec 2008) were industrial supervisors for the early partof the PhD. I want to thank them for their guidance whilst at GlaxoSmithKline
and their continued input and moral support in the years when they had left
GSK. Thank you to Dr Susanne Knapp and Dr Paul Langford, mentors at
Imperial College.
Viral assay support was given by Virology CEDD GSK (HCV, HIV, Semliki
Forest virus), Professor Graham Fosters lab at QEQM (Dengue, RSV) and Dr
Mike McGarvey’s lab Imperial College (St Mary’s Campus) (HBV) – I think fate
was telling me to stick with HCV as some RSV experiments were lost due to afire in Graham Foster’s office whilst I was working there and HBV work had to
be cut short in part due to the July 2005 London bomb explosions.
Gene Expression work was performed with help from Fiona Kelly and Laurie
Scott, Discovery Technology Group, GSK. Affymetrix analysis help wasprovided by Nikol Simecek, GSK, Ingenuity and GeneGo support lines.
IL-28R distribution experiments were supported by my dear friends andcolleagues Sylvia Fung and Martin Vidgeon-Hart, this work was presented at
the European Histology Forum 2010 and won best new speaker award. IHC
slides were peer reviewed by Dr Chris Clarke and Dr Rob Goldin (Imperial),
John Bowles (GSK) helped with image capture, Ian Roman (GSK) with FLOW
analysis and inflammatory cell microarray screen was taken from GSK work by

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Adele Gibson, Michelle Bartholomew, Richard Priest, Dilniya Fattah, William
Wixted, Janet Smith, Susan Boyce and Laurie Scott.
Mouse bone marrow assay work was done in collaboration with David Brott,Astrazeneca and human bone marrow assay work in collaboration with Dr Aisha
Sauer and Nicola Carriglio (Professor Alessandro Aiuti’s lab).
A massive thank you to my line managers at GSK; Dr Joel Parry, Dr Jon Lyon
and Dr John Haselden for supporting me in the part time PhD, allowing me 20%
of work time to do the PhD and providing funding for the PhD.
To my family, husband Dan and especially to my children William (6) and Isabel(2), two reasons for the part time PhD taking a little longer than anticipated.

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Contents
Abstract ......................................................................................................................... 2
Statement of Originality .............................................................................................. 2
Acknowledgements ....................................................................................................... 3Contents ........................................................................................................................ 5
Table of Figures ............................................................................................................ 9
List of Tables .............................................................................................................. 12
Abbreviations used ..................................................................................................... 13
1. General Introduction ............................................................................................. 16
1.1 Introduction to interferons and the discovery of type III interferons .............. 16
1.2 Antiviral properties of interferon lambdas ...................................................... 19
1.3 IL-28 receptor and signalling........................................................................... 26
1.4 Transcriptomic analysis gene activation profiles and signalling pathways of
IL-28A and IL-29 .................................................................................................. 30
1.5 Alternative therapies for HCV and IFN lambda as a therapy .......................... 31
1.6 Introduction summary...................................................................................... 33
1.7 Hypothesis ....................................................................................................... 34
1.8 Thesis Aims ..................................................................................................... 34
2. Materials and methods .......................................................................................... 35
2.1 Investigation of the antiviral activity of IL-28A and IL-29 using antiviral andinterferon sensitive gene model assays .................................................................. 35
2.1.1 Hepatitis C comparison of antiviral activity of IFNα, IFNβ, IFNγ, IL-28A andIL-29 ................................................................................................................... 35
2.1.2 Determination of IC50 values for four luciferase HCV replicon clones .... 37
2.1.3 IL-28A, IL-29 and IFNα synergy .............................................................. 38
2.1.4 IFN sensitive gene models 6-16 and ISG56 .............................................. 38
2.1.5 Hepatitis B (HBV) ..................................................................................... 40
2.1.6 Real-Time PCR assay overview ................................................................... 41
2.1.6.1 Sybr Green 1 dye .................................................................................... 42
2.1.6.2 Fluorogenic 5’ nuclease assay (TaqMan®) ............................................. 42
2.1.6.3 Primer and probe design ......................................................................... 43
2.1.6.4 PCR reagents .......................................................................................... 43
2.1.6.5 PCR cycling parameters ......................................................................... 44
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2.1.6.6 Data Analysis .......................................................................................... 44
2.1.7 Human immunodeficiency virus (HIV) ..................................................... 45
2.1.8 Dengue fever virus ..................................................................................... 48
2.1.9 Respiratory Syncytial Virus (RSV) ........................................................... 51
2.2 Transcriptome analysis in HCV replicon cells treated with type I and type III
IFNs ....................................................................................................................... 53
2.2.1 Determination of IC50 values for 4 replicon clones ................................... 53
2.2.2 Cell culture and treatment .......................................................................... 53
2.2.3 Isolation of RNA........................................................................................ 53
2.2.4 Quantitative QPCR pre-screen .................................................................. 54
2.2.5 Affymetrix GeneChips® Expression analysis ............................................ 54
2.2.6 Preparation and Quality Control of cRNA Targets for Hybridisation to
GeneChips® ........................................................................................................ 57
2.3 Distribution of type III interferon receptor in a panel of mouse and humantissues –genomic analysis ...................................................................................... 66
2.3.1 TaqMan® quantative PCR for IL-28R RNA detection in mouse .............. 66
2.3.2 Gene Logic human tissue microarray screen ............................................. 66
2.3.3 Human inflammatory cell microarray screen ............................................ 66
2.3.4 Isolation & treatment of cells for human inflammatory cell microarray screen............................................................................................................................ 67
2.3.5 Human tissues and whole blood ................................................................ 68
2.4 Distribution of type III interferon receptor in a panel of mouse and humantissues, protein expression analysis ....................................................................... 68
2.4.1 Immunohistochemistry overview .............................................................. 68
2.4.2 Immunohistochemical staining - IL-28R single stain in mouse and human69
2.4.3 Immunohistochemical staining- IL-28R dual stain in mouse .................... 70
2.4.4 Toluidine blue histochemical stain in mouse ............................................ 72
2.4.5 Flow Cytometric Analysis for tissue IL-28R determination ..................... 73
2.5 Bone marrow assays ........................................................................................ 73

3.

2.5.1 Murine bone marrow in vitro assay ........................................................... 73
2.5.2 Human bone marrow ................................................................................. 74
2.5.2.3 Human tissues and whole blood ............................................................. 75
Investigation of the antiviral activity of IL-28A and IL-29 using antiviral andinterferon sensitive gene model assays ............................................................ 76
3.1 Introduction...................................................................................................... 76
3.1.1 Hepatitis C comparison of antiviral activity of IFNα, IFNβ, IFNγ andinterferon lambdas IL-28A and IL-29 in two replicon assays ............................ 78
3.1.2 Determination of IC50 values for luciferase HCV replicon clones ............ 81
3.1.3 IL-29 and IFNα synergy ............................................................................ 83
3.1.4 IFN sensitive gene models 6-16 and ISG56 .............................................. 83
3.1.5 Hepatitis B (HBV) ..................................................................................... 85
3.1.6 Human immunodeficiency virus (HIV) ..................................................... 86
3.1.7 Dengue Fever Virus assay ......................................................................... 88
3.1.8 Respiratory Syncytial Virus (RSV) ........................................................... 88
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3.1.9 Discussion .................................................................................................. 89
4. Transcriptome analysis in parent HuH7 cells and HCV replicon cells treated with
type I and type III IFNs ................................................................................... 93
4.1 Introduction...................................................................................................... 93
4.2 Determination of 10 x IC50 for most IFN sensitive replicon cell line ............. 95
4.3 TaqMan® analysis ............................................................................................ 95
4.4 Parent HuH7 .................................................................................................... 97
4.4.1 Parent HuH7 versus HCV replicon ........................................................... 97
4.4.2 Parent HuH7 signature genes................................................................... 102
4.4.3 Parent HuH7 pathway analysis IPA ........................................................ 103
4.4.4 Parent HuH7 unique IL-29 gene analysis ................................................ 109
4.4.5 Parent HuH7 pathway analysis GeneGo.................................................. 111
4.4.6 Additional unique gene changes –cytokine induction, TLR and MAPK
signalling........................................................................................................... 113
4.4.7 Parent HuH7 kinetics ............................................................................... 113
4.5 HCV replicon ................................................................................................. 114
4.5.1 Comparison of parental data with replicon data to investigate the effects of
HCV on IL-28A, IL-29 and IFNα gene modulation ......................................... 114
4.5.2 HCV replicon signature genes ................................................................. 115
4.5.3 HCV replicon kinetics ............................................................................. 116
4.6 Discussion ...................................................................................................... 120
5. IL-28R distribution using genomic analysis ...................................................... 124
5.1 Introduction.................................................................................................... 124
5.2 IL-28R gene expression in mouse tissue ....................................................... 124
5.3 Gene Logic human tissue microarray screen ................................................. 127
5.4 Inflammatory cell microarray screen ............................................................. 131
5.5 Discussion ...................................................................................................... 133
6. Distribution of IL-28R, protein expression........................................................ 135
6.1 Introduction.................................................................................................... 135
6.2 Immunohistochemistry for IL-28R protein expression in murine lymphoid andepithelial tissues ................................................................................................... 135
6.3 Toluidine blue histochemical stain in mouse showed mast cells express IL28R....................................................................................................................... 143
6.4 Dual staining- IL-28R and macrophage markers........................................... 144
6.5 IL-28R protein expression in normal and diseased human tissues ................ 145
6.6 Discussion ...................................................................................................... 149
7. Bone marrow ........................................................................................................ 152
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7.1 Introduction.................................................................................................... 152
7.2 Mouse cells .................................................................................................... 154
7.3 Human cells - IL-28R gene expression in comparison with IFNAR inhematopoietic stem cells and lymphoid lineages................................................. 155
7.4 Colony forming capacity and proliferation of human CD34+ cells in vitro . 155
7.5 Bone marrow cell discussion ......................................................................... 157
General Discussion ................................................................................................... 159
8.1 Antiviral properties of interferon lambdas .................................................... 159
8.2 Gene Expression ............................................................................................ 160
8.3 IL-28R distribution ........................................................................................ 161
8.4 Bone marrow experiments ............................................................................. 163
8.5 IFNλs as a therapy ......................................................................................... 163
8.6 Future work .................................................................................................... 166
8.7 Conclusions ................................................................................................... 166
Appendix I ................................................................................................................ 169
Appendix II Suppliers .............................................................................................. 169
Appendix III Publications ....................................................................................... 171

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Table of Figures
Figure 1.1:
genes

A phylogenetic alignment of the class II cytokine family
17

Figure 1.2:

Graphical representations of IFNα, IL-28A and IL-29 ....... 20

Figure 1.3:

Organization of Flaviviridae genome HCV ........................ 21

Figure 1.4:

Hypothetical HCV replication cycle .................................... 23

Figure 1.5: Geographical representation of HCV prevalence.................. 24
Figure 1.6: IL-10Rβ is a promiscuous cytokine receptor ........................ 28
Figure 1.7: Type III IFN receptor signalling compared to type I and II .... 29
Figure 2.1: HCV replicon structure ............................................................ 35
Figure 2.2: HCV luciferase replicon clones structure .............................. 38
Figure 2.3: ISG56-luciferase reporter ........................................................ 40
Figure 2.4: TaqMan® Real-time PCR process ........................................... 43
Figure 2.5: TaqMan® Real-time PCR amplification plot ........................... 45
Figure 2.6: MT-4 cells uninfected and infected with HXB2 ...................... 47
Figure 2.7: Schematic showing plasmid pDENΔCprME-PAC2A ............. 48
Figure 2.8: Standard eukaryotic gene expression assay ........................ 56
Figure 2.9: Representative RNA 6000 Nano Labchip cRNA Quality
Assessment Images ............................................................................ 61
Figure 2.10: Avidin-Biotin Complex (ABC) method ................................. 69
Figure 2.11: Structure of toluidine blue .................................................... 72
Figure 3.1: IC50 plots for IFNα, IFNβ, IFNγ, IL-28A and IL-29 ................... 80
Figure 3.2: IC50 plots for HCV replicon assays 1a3II and 1b2.5 .............. 82
Figure 3.3: Antiviral effects of IL-28A and IL-29 with HBV ...................... 85
Figure 3.4: Antiviral effects of IL-28A and IL-29 against HIV virus HXB287
Figure 3.5: Dengue virus replicon ............................................................. 88
Figure 4.1: TaqMan® expression of IFITI, MX1, OAS1 and G1P3 ............ 96
Figure 4.2: Venn diagrams ......................................................................... 98
Figure 4.3: PCA plot –PC1 Vs 2 by time point ........................................ 100
Figure 4.4: PCA plot –PC2 Vs 3 by cell type ........................................... 101
Figure 4.5 A: Parent HuH7 cell line pathway analysis at 4 hours for IFNα104

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Figure 4.5 B: Parent HuH7 cell line pathway analysis at 4 hours for IL28A

105

Figure 4.5 C: Parent HuH7 cell line pathway analysis at 4 hours for IL-29106
Figure 4.6 A: Parent HuH7 cell line pathway analysis at 8 hours for IFNα107
Figure 4.6 B: Parent HuH7 cell line pathway analysis at 8 hours for IL-29108
Figure 4.7: A top pathway - antigen presentation pathway determinedby Ingenuity for genes unique to IL-29 at 8 hours .......................... 110
Figure 4.8: Top pathway interferon signalling determined by GeneGo forgenes unique to IL-29 at 24 hours. ................................................... 112
Figure 4.9: Cluster analysis plot .............................................................. 117
Figure 4.10: Heat map ............................................................................... 118
Figure 4.11: Trend plots ........................................................................... 119
Figure 5.1: TaqMan® IL-28R...................................................................... 126
Figure 5.2 A: Gene Logic graph showing IFNAR1 expression in a rangeof human cell types and tissues....................................................... 128
Figure 5.2 B: Gene Logic graph showing IL-28R expression in a rangeof human cell types and tissues ....................................................... 129
Figure 5.2 C: Gene Logic graph showing IL-10RB expression in a rangeof human cell types and tissues ....................................................... 130
Figure 5.3: GSK Inflammatory cell screen showing IL-28R gene
expression .......................................................................................... 132
Figure 6.1: Flow cytometry showing IL-28R expression in mouse spleen136
Figure 6.2 A and B: IL-28R distribution in mouse spleen using
Immunohistochemistry ..................................................................... 139
Figure 6.2 C and D: IL-28R distribution in mouse thymus andmesenteric lymph node using Immunohistochemistry .................. 140
Figure 6.2 E and F: IL-28R distribution in mouse liver using
Immunohistochemistry ..................................................................... 141
Figure 6.2 G and H: IL-28R distribution in mouse colon using
Immunohistochemistry ..................................................................... 142
Figure 6.3: IL-28R distribution in mast cells ........................................... 143
Figure 6.4: Dual staining .......................................................................... 144
Figure 6.5 A and B: Human diseased liver and IL-28R expression using
Immunohistochemistry ..................................................................... 146
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Figure 6.5 C and D: Human diseased liver and IL-28R expression using
Immunohistochemistry ..................................................................... 147
Figure 6.5 E and F: Human ileum and synovium and IL-28R expression
using Immunohistochemistry ........................................................... 148
Figure 7.1: Mouse bone marrow data ...................................................... 154
Figure 7.2: Human IFNαR1 and IL-28R expression ................................ 155
Figure 7.3: Colony forming cell (CFC) assay .......................................... 156
Figure 7.4: CD34+ cells’ viability after proliferation ............................... 157

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List of Tables
Table 2.1: Hepatitis B virus probe and primer sequences ...................... 41
Table 2.2: Dengue virus probe and primer sequences ............................ 51
Table 2.3 Probe and primer sequences for RSV ...................................... 52
Table 2.4: Reagents and Volumes for Hybridisation Cocktail Preparation62
Table 2.5: GeneChip® hybridisation quality control metrics ................... 63
Table 3.1 IC50 values for IL-29, IL-28A, IFNα, IFNβ and IFNγ ................... 79
Table 3.2: IC50 values for IL-28A, IL-29 and IFNα in HCV replicon clones83
Table 3.3: EC50 values for IFNs in ISG models ......................................... 84
Table 3.4: Subsection of Table 4.7 to highlight G1P3 expression .......... 84
Table 4.1: IC50 values in ng/mL of IL-28A, IL-29 and IFNα in HCV
replicons 95
Table 4.2: Table to show top 20 expressed genes in parent HuH7 cells102
Table 4.3: Antigen presenting genes IL-29 versus IFNα. ....................... 109
Table 4.4: Pathway analysis for HuH7 cell line GeneGo ........................ 111
Table 4.5 Data subset: to illustrate kinetics in parent HuH7 cells ........ 113
Table 4.6: Comparison of replicon versus parent HuH7 cells............... 114
Table 4.7: Sensitivity of parent HuH7 cell line versus replicon ............ 115
Table 4.8: A selection of top 20 expressed genes in the replicon cells115
Table 6.1: Location of IL-28R protein expression in mouse tissues .... 138

Page 12 of 183

Abbreviations used%-

Percent<-

Less than>-Greater than±-

Plus or minus?

-

Less than or equal to?

-

Greater than or equal to~-Approximately± s.d.

-

Plus or minus standard deviation°C-

Degrees Celsiusµg-

MicrogramµL-

Microlitre(s)µM-

Micromolar

A-

AdenineANOVA-

Analysis of varianceC-

Cytosine

CALR-

Calreticulin

CD (34)-Cluster of differentiation

cDNA

-

Complementary DNA

CH3-

Methyl group

CLIP

-

Class II-associated invariant chain peptide

CNX-

CalnexincRNA-

Complementary RNA

Ct-

Cycle threshold

Da-

DaltonDDX58-

DEAD (Asp-Glu-Ala-Asp) box polypeptide 58 (also RIG-I)

DMSO

-

DimethylsulphoxideDNA-

Deoxyribonucleotide acid

DTT-

Dithiothreitol

dUTP

-

Deoxyuridine Triphosphate

e.g.

-

For example

EC50

-

Effective concentration 50 percent

EDTA

-

Ethylenediaminetetraacetic acid

EGF-

Epidermal growth factor

Page 13 of 183

ELF2

-

E74-like factor 2

EPSTI1-

Epithelial stromal interaction 1g-Gram(s)G-

Guanine

G1P3-

Interferon, alpha-inducible protein 6

GM-CSF-

Granulocyte macrophage colony-stimulating factor

GPCR

-

G protein coupled receptors

GSK-

GlaxoSmithKline

HCI-

Hydrochloric Acid

HETE

-

5-Hydroxyeicosatetraenoic acid

HLA (A)-

Human leukocyte antigen

HPETE

-

Arachidonic acid 5-hydroperoxide

IFI (6)-

Interferon, alpha-inducible protein

IFIH1

-

Interferon induced with helicase C domain 1

IFIT1

-

Interferon-induced protein with tetratricopeptide repeats 1

IFITM(1)-Interferon induced transmembrane protein 1

Ig (G)-

Immunoglobulin

IGF-1

-

Insulin-like growth factor 1

IMS-

Industrial methylated spirit

IPA-

Ingenuity pathways analysis

ISGF3G-Interferon regulatory factor 9

IU-

International Unit

LPS-

Lipopolysaccharide

M

-

Molar

MAPK

-

Mitogen-activated protein kinasemg-

Milligram(s)mL-Millilitre(s)mM-Millimolar

mRNA

-

Messenger RNA

nM-

Nanomolar

Oligo(s)-Oligonucleotide(s)OPD-O-phenylenediamine

PARP9

-

Poly (ADP-ribose) polymerase family, member 9

PBMC

-

Peripheral blood mononuclear cell

PCR-

Polymerase chain reaction

Page 14 of 183

PEG

-

Polyethylene glycolpg-

PicogrampH-

Potential Hydrogen

PLSCR1-

Phospholipid scramblase 1

RNA-

Ribonucleotide acidrpm-

Revolutions per minute

RT-QPCR-

Real-time quantitative PCR

SUMO-1-

Small Ubiquitin-like Modifier

SUPT16H -Suppressor of Ty 16 homologT-

ThymineTGF-

Tumor growth factor

Th1-

T helper cell

TNF-

Tumor necrosis factor

TRAF

-

TNF receptor-associated factor

T-Reg

-

Regulatory T cell

VEGF

-

Vascular endothelial growth factor

Page 15 of 183

Chapter 1

Chapter 1
1. General Introduction
1.1 Introduction to interferons and the discovery of type III
interferons
Type I interferons (IFNs) have been considered the gold standard for antiviralprotection since their discovery over 50 years ago1. Interferons (IFNs) aredefined by their ability to induce resistance to viral infection. However the recent
discovery of type III interferons may add a new dimension to conventional
treatment regimes.
Interferon lambdas (IFNλs) are newly identified cytokines jointly discovered in
2002/32,3 termed IFN-λ1, IFN-λ2 and IFN-λ32 or interleukin (IL) IL-29, IL-28A, IL28B respectively3. These cytokines are the first novel IFN family (IFN type III)
defined in more than 20 years4. Initial studies showed that interferon lambdas
had antiviral properties in vitro with encephalomyocarditis virus (EMCV)3,
stimulated interferon sensitive genes (ISGs)2,3 and both groups described thatthe activity of the interferon lambdas is achieved through a novel receptor
interferon-lambda receptor 1 (IFN-λR1)2 also known as interleukin-28 receptor(IL-28R)3.
Interferon lambdas share similar expression patterns with type I IFNs andtrigger common signal transduction cascades and sets of stimulated genes.
Both type I and type III IFNs share many biological activities, including theability to induce an antiviral state in cells. IFNs protect cells from virus infection,
directly by inducing ISGs such as 2’, 5’-oligoadenylate synthetase 1 (2’, 5’-OAS)
and myxovirus resistance-A (MxA) and intracellular proteins5 and, indirectly, by
inducing major histocompatibility complex (MHC) class I antigen expression on
and activation of antigen-presenting cells, stimulating dendritic cell maturation
and activating macrophages and natural killer cells6.
There are three families of interferons: type I interferons, like interferon alphafamily (IFNαs) and interferon beta (IFNβ), which show potent antiviral activity;
type II interferon like interferon gamma (IFNγ), which shows weak antiviral
activity but is a strong activator of cellular immune responses; and now type III
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Chapter 1
interferons with novel IFNλs. In humans, the type I IFN family comprises at least
13 nonallelic IFNα genes, IFNβ, IFNω, IFNκ and the limitin gene7; type II is IFNγ
and the novel type III interferons IL-28A, IL-28B and IL-29. IL-28A, IL-28B and
IL-29 are weakly related to type I IFNs at the amino acid level but have agenetic structure more similar to IL-10. IL-28A and IL-28B share 96% aminoacid identity and IL-29 shows 81% homology to IL-283. Genes for all threemembers of the IFNλ family are found on chromosome 19 (q13.13 region)3,
whereas the genes for all type I IFNs are clustered on human chromosome 9 8,9.
The gene for IFNγ is located on chromosome 1210. Type I IFN genes lackintrons, but the coding regions of the IFNλ genes are interrupted by 4 introns,
and the positions of the introns with respect to the protein reading frames areconserved for the IFNλ genes and for genes encoding IL-10-related cytokines11.
Even though the amino acid identity of type III IFNs is lower than even the most
distant members of the type I IFN family, and the fact that they are clustered on
different chromosomes, the conserved cysteine pattern and amphipathic profile 3of the IFNλs suggest they belong to the helical cytokine family and appear to bean evolutionary link between IL-10 and type I IFNs.

Figure 1.1: A phylogenetic alignment of the class II cytokine family genes
Figure taken from Donnelly et al12 Alignment of the human interferon-λ (IFN-λ) genes
with either (A) the human type I IFN genes or (B) the human interleukin-10 (IL-10)related cytokines was used to generate a phylogenetic tree for the class II cytokine
genes.

IFN-λ genes are clustered together on human chromosome 19 (19q13.13
region) or murine chromosome 7 (7A3 region). There are three functional IFN-λgenes in the human genome IFN-λ1 (IL-29), IFN-λ2 (IL-28A) and IFN-λ3 (IL28B) and 1 pseudogene IFN-λ4ψ, whereas there are only 2 functional IFN-λPage 17 of 183

Chapter 1
coding genes in the murine genome: IFN-λ2 (IL-28A) and IFN-λ3 (IL-29), mIFNλ1Ψ and mIFN-λ4Ψ genes are pseudogenes. Studies have shown that the
mutated mIFN-λ1 gene does not encode a functional IFN-λ1 protein13. The highdegree of homology between the IFN-λ genes suggesting that the genes
evolved from a common predecessor, IFN-λ3 (IL-28B) gene is almost identicalto the IFN-λ2 (IL28A) gene not only in the coding region but also in the
upstream and downstream flanking sequences. The promoters of the IFN-λ2
and IFN-λ3 genes are very similar and share several common elements with the
IFN-λ1 promoter, suggesting that all 3 genes are likely to be regulated in asimilar manner14,15.
Type I and type III IFN genes have similar expression patterns, this is likely tobe due to common regulatory elements in the promoters of the type I and type
III IFN genes. Promoters of IFN-λ genes have predicted binding sites fortranscription factors: AP1 (dimeric factor containing members of the JUN, FOS,ATF and MAF protein families), nuclear factor κB (NF-κB) and interferon
regulatory factors (IRFs), crucial for the induction of type I and type III IFN
expression14,15. IFN-λ1 is controlled by either IRF3 or IRF7, but importantly IFNλ2/3 like IFNα genes are more dependent on IRF7 15. IRF3 is ubiquitously
expressed in cells and upon direct viral activation upregulates IFN-λ1 and IFNβ
representing early response genes. IFN-λ2/3 gene expression is mainly
controlled by IRF7, thus resembling those of IFNα genes with delayed kinetics
conforming to a positive feed-back mechanism. The regulation of type III IFNs
may differ in mice, however, since there is no functional IFN-λ1 gene in themurine genome13. Co-expression of type I and type III IFNs in response todiverse viruses and various TLR agonists has been shown by multiple cell types
but plasmacytoid dendritic cells (pDCs) constitutively express IRF7, enablingthese cells to rapidly produce high levels of type I and type III IFNs upon
stimulation16. Differences in type I and type III IFN expression have beenreported, including IFN-λs were shown to be the main IFN type produced byboth murine and human airway epithelial cells in response to various respiratory
viruses17,18, a model is proposed for IFN-λ1 gene regulation, in which IRF and
NF-κB activate gene expression independently via spatially separated promoter
elements19 showing type III IFNs can be induced through IRFs or NF-κB unlike
IFNα which needs multiple transcription factors. Though IFN-λ is typically

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Chapter 1
activated by viral infections, showing that it is an important part of the innate
immune response, activation of TLR-4 by bacterial LPS has been shown to
induce IFN-λ in DCs16,19 highlighting a role of IFN-λ in the modulation of theimmune response. Interferon lambdas also have a role in antiviral immunity
through modulation of both the maturation and differentiation of immune cells.
Differentiation of monocytes into dendritic cells leads to upregulation of IL28R and an increased ability to express IFN-λ20,21,22,23. When DCs are thenexposed to IFN-λ, increased maturation and migration capacity are induced 22.
Interferon lambda influences the effects of DCs on interactions with T cells. DCs
treated with IFN-λ preferentially expand regulatory T cells, which negatively
regulate the immune response, and promote self-tolerance20,22. IFN-λ appears
to be primarily focused on biasing T cell differentiation against Th2 development
and Th2 cytokine secretion but also modulating Th1 cells 24,25,26,27,28although
this role is not fully clear. Interferon lambdas are an important part of the innate
immune response and have a role in the modulation of the adaptive immune
response.

1.2 Antiviral properties of interferon lambdas
Like IFNα, IL-28A and IL-29 have antiviral properties and potentially could be
used as or incorporated into another therapeutic approach to treating viraldisease. Initial studies by Sheppard et al in 2003 showed that IL-28A and IL-29
induced antiviral effects in response to encephalomyocarditis virus (EMCV) andstimulated interferon sensitive genes in vitro (Figure 1.2)3.
As IFNλs had been shown to have antiviral properties it was an aim of thisthesis to investigate the antiviral properties of IFNλs in vitro against a panel ofviruses

includinghepatitis

C(HCV),

hepatitis

B(HBV),

human

immunodeficiency virus (HIV), dengue fever and respiratory syncytial virus(RSV), with a primary focus on HCV.

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Chapter 1A

B

Figure 1.2: Graphical representations of IFNα, IL-28A and IL-29
EMCV assay A and interferon sensitive gene induction with ISG B
A Antiviral activity of IL-28A and IL-29. IL-28A, IL-29 and IFNα2a (IFNα) were added at varying concentrations to HepG2 cells before EMCV
infection and dye-uptake was measured. Mean s.d. A570 values, which were directly proportional to antiviral activity, are shown (n = 3).
B IL-28A and IL-29 signal through the IFN-stimulated response element (ISRE). HepG2 cells were transfected with an ISRE reporter plasmid andluciferase activity was analysed after treatment with varying concentrations of IL-28A, IL-29 or IFNα2a. Fold activation was determined by dividing
the relative light units (RLU) of each experimental sample by the RLU of media alone. Mean s.d. data are shown (n = 2). Figure taken from
Sheppard3.

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Chapter 1
Hepatitis C (HCV) has a positive-sense single stranded RNA genome and isclassified as a flavivirus. The hepatitis C virus particle consists of a core ofgenetic material (RNA), surrounded by an icosahedral protective shell ofprotein, and further encased in a lipid (fatty) envelope of cellular origin. Twoviral envelope glycoproteins, E1 and E2, are embedded in the lipid envelope29.
The HCV genome is 9600 nucleotides and comprises of two non-coding regionsin 5' and 3' flanking a large reading frame which codes for a polyprotein of 3000
amino acids; this polyprotein is further cleaved into structural (C, El, E2) andnon- structural (NS1, NS2, NS3, NS4, NS5) proteins. The positive RNA acts asa cap-independent messenger; the transcription is mediated by the NS5 RNApolymerase. After the maturation step, the virion is liberated by budding throughthe cytoplasmic membrane.

Figure 1.3: Organization of Flaviviridae genome HCV
Figure adapted30to show organization of Flaviviridae genome, HCV showing structuralproteins made by the hepatitis C virus include Core protein, E1 and E2; nonstructuralproteins include NS2, NS3, NS4, NS4A, NS4B, NS5, NS5A, and NS5B.

The structurural proteins made by HCV are further described below. Core
protein is a highly basic, RNA-binding protein, proteins of various sizes (17 to
23 kDa) are described but the 21-kDa core protein (P21) appeared to be thepredominant form31. The core protein contains three distinct predicted domains:an N-terminal hydrophilic domain of 120 aa (domain D1), principally involved in
RNA binding and nuclear localization, a C-terminal hydrophobic domain of
about 50 aa (domain D2), responsible for core protein association withendoplasmic reticulum (ER) membranes, and the last 20 or so aa that serve asa signal peptide for the downstream envelope protein E1 32. Envelope proteins
E1 and E2 are highly glycosylated and have a key role in cell entry, the p7
protein, a 63 amino acid membrane spanning protein which locates itself in theendoplasmic reticulum, is dispensable for viral genome replication but plays acritical role in virus morphogenesis33. NS2 protein is a 21-23 kDa
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Chapter 1transmembrane protein with protease activity, NS2 is a short-lived protein thatloses its protease activity after self-cleavage from NS3 and is degraded by theproteasome34. NS3 is 67 kDa protein whose N-terminal has serine proteaseactivity and whose C-terminal has NTPase/helicase activity. NS4A is a cofactorof NS3 protease activity. NS3-4A also bears additional properties through its
interaction with host cell pathways and proteins that may be important in the
lifecycle and pathogenesis of infection, NS3-NS4A protease is a popular viraltargets for anti-HCV therapeutics35. NS4B is a small (27 kDa) hydrophobic
integral membrane protein with 4 transmembrane domains. It is located within
the endoplasmic reticulum and plays an important role for recruitment of otherviral proteins36. NS5A is a hydrophilic phosphoprotein which plays an importantrole in viral replication, modulation of cell signaling pathways and the interferon
response. The NS5B protein (65 kDa) is the viral RNA dependent RNA
polymerase. Until recently when the complete replication of hepatitis C virus incell culture was demonstrated37, the lack of a robust tissue culture system for
HCV meant that HCV was studied using a replicon system38, where the effectsof IFNs on HCV replication in vitro can be studied39. Replication of HCV
involves several steps. The virus replicates mainly in the hepatocytes of theliver, where each infected cell produces approximately 10 virions per day40 and
NS5B produces mutations at rate 10-4 per nucleotide41, this key in using current
direct acting antivirals (DAA) in the treatment of HCV, the risk of rapid
development of resistance, without the use of cotreatment of IFN. Entry into
host cells occur through interactions between virions and cell-surface molecules
CD81, LDL receptor, SR-BI, DC-SIGN, Claudin-1, and Occludin42. HCV uses
portions of the intracellular machinery to replicate43. The HCV genome istranslated to produce a 3000aa protein, which is processed by viral and cellular
proteases to produce three structural and seven nonstructural (NS) proteins.
The NS proteins then recruit the viral genome into an RNA replication complex.
RNA replication takes places via the viral RNA-dependent RNA polymerase
NS5B, which produces a negative strand RNA intermediate. The negative
strand RNA then serves as a template for the production of new positive strand
viral genomes. Nascent genomes can then be translated, further replicated or
packaged within new virus particles. New virus particles are thought to bud into
the secretory pathway and are released at the cell surface.
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Figure 1.4: Hypothetical HCV replication cycle
This figure is taken from Bartenschlager et al., 200430. HCV particles bind to the hostcells via a specific interaction between the HCV envelope glycoproteins and a yet
unknown cellular receptor. After the viral genome is liberated from the nucleocapsid
and translated at the rough ER, NS4B induces the formation of membranous vesicles(referred to as the membranous web; EM in the lower right). These membranes aresupposed to serve as scaffolds for the viral replication complex. After genome
amplification and HCV protein expression, progeny virions are assembled. Newly
produced virus particles may leave the host cell by the constitutive secretory pathway.
The upper right panel of the figure shows a schematic representation of an HCV
particle. The middle panel shows a model for the synthesis of negative-stranded (−)
and positive stranded (+) progeny RNA via a double-stranded replicative form (RF) anda replicative intermediate (RI).

HCV is sensitive to IFNα, IFNβ and IFNγ44 but at the time this project was
initiated (August 2004) there was not any published data on the role of type III
interferons in HCV. Pegylated IFNα in combination with ribavirin is the current
standard of care for the treatment of patients chronically infected with HCV; it
results in a sustained virological response (defined as clearance of circulating
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Chapter 1
HCV RNA at 6 months post-treatment) in ~50% of HCV patients45. However,combination therapy remains less effective against infections caused by HCV
genotype 1 which constitute ~75% of all HCV infections in the developed world.
IFNα therapy is administered intravenously and has side effects such as flu-like
symptoms, anorexia, depression, haemolytic anaemia and myelosuppressionthat can be severe and sometimes dose limiting. Approximately 500 million
people worldwide are living with either hepatitis B or hepatitis C 46. This
represents 1 in 12 people, and was the basis for the 2008 ‘World Hepatitis Day
Am I Number 12?’ campaign. HCV affects ~ 170 million people worldwide, witha seroprevalence in the United States and Japan of ~2%, and in Western
Europe of 1-1.9%47 (Figure 1.5). HCV infection can lead to liver fibrosis,
cirrhosis and liver cancer14.

Figure 1.5: Geographical representation of HCV prevalence
Percentage of the population infected with HCV globally. Figure from Shepard 200548

The HCV genome exhibits a high degree of variability, especially in the E2/NS1,
El, NS3 and NS5b regions, resulting in at least 6 genotypes of HCV numberedfrom 1 to 6 in Simmonds' classification49 and over 100 subtypes. Genotype 1,
1a and 1b accounts for 60% of all HCV cases in USA and Europe and in Japan
73% is 1b. Geneotype 2 is 8% in Europe; Genotype 3 is 60% in India and 58%
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in Iran. Genotype 4 has been associated with 20% of chronic infections
worldwide and is the genotype in 7% of Northern Europe HCV cases and 24%
of Southern Europe, Genotype 4a makes up 90% of HCV cases in Egypt, Egypt
has 13% of its population diagnosed with HCV. Genotype 5 is in 40% of the
HCV cases in South Africa and genotype 6 is a diverse genotype now including
genotypes originally classes as 7,8, and 11, it is the genotype in 30% of HCVcases in Asia and 20% in China. Genotype is clinically important in determining
potential response to therapy, for example genotypes 1 and 4 are lessresponsive to interferon-based treatment than are the other genotypes (2, 3, 5
and 6)49.
Hepatitis B, which is caused by the hepatitis B virus (HBV), affects 350 million
people worldwide and is responsible for one million deaths each year. HBV
infection, like HCV, can lead to liver fibrosis, cirrhosis and liver cancer. Hepatitis
B is the primary cause of liver cancer (60-80%), (WHO 2006). HBV is part of thehepadnaviridae (hepatitis DNA viruses) family. Hepatitis B is typically treatedwith interferon alpha (IFNα) which results in ~30% seroconversion, or
nucleoside reverse transcriptase inhibitors (NRTIs) such as adefovir, entecavir,
lamivudine, telbivudine, and tenofovir. Lamivudine, a nucleoside analogue,
results in ~40% seroconversion, compared with 5% seroconversion with notreatment. As with HCV, there is a need for new treatments with increased
efficacy. The effect of HBV and IFNα has been studied in vivo50. IFNλs havebeen shown to reduce levels of HCV mRNA in the HCV replicon system andreduce expression of HBV DNA in murine cells51.
Human immunodeficiency virus (HIV) is an RNA reverse transcribing virus, partof the retroviridae family of viruses. Approximately 40 million people worldwide
are living with HIV (WHO statistics 2005). HIV infection leads to the loss of CD4
cells, which can result in immunosuppression (Acquired immune deficiency
syndrome (AIDS)). There are currently a variety of treatments for HIV: IFNα, cellfusion inhibitors, reverse transcriptase inhibitors and protease inhibitors.
Treatment options are often limited due to cross resistance. Overall prevalenceof HIV drug resistance is on the increase52, so alternative therapies are still
being developed for the treatment of HIV.

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Dengue fever is a major threat to public health in many tropical and subtropicalcountries. There are an estimated 50 million infections per year (WHO 2006).
Dengue is a flavivirus which circulates as four major serotypes and is passed onfrom an infected mosquito bite. Dengue haemorrhagic fever and dengue shock
syndrome are the more severe manifestations of dengue infection and primarily
occur on re-infection with a virus of differing serotype to the initial infection.
IFNα in the dengue replicon system has been shown to have no antiviral effectand that dengue virus specifically inhibits IFNα signalling by the down-regulationof signal transducers and activators of transcription protein (STAT) STAT2
expression53, however the effects on dengue with IFNλs remain to be
determined.
Respiratory syncytial virus (RSV) is a single stranded RNA paramyxovirus,
which is the same family as para-influenza, measles and rubella. RSV infection
is recognised as the leading cause, of bronchiolitis and pneumonia in infants
and young children54. RSV is highly contagious and in immunocompromised
patients can lead to persistent infection. Treatment options are currently limited
to monoclonal antibody based therapy and supportive care; ribavirin has beenused historically.
Type III interferons have also been implicated as having antiviral properties in arange of viruses: DNA viruses; poxvirus55, murine cytomegalovirus (CMV)56,56,
hepatitis B virus57,51,58 and herpes simplex virus 1 and 259, the single stranded(ss) (+) RNA viruses EMCV60,3, West Nile virus57 and hepatitis C virus57,61,62,51,
as well as the ss (−) RNA viruses influenza-A virus63 and vesicular stomatitis
virus,62. IL-28A and IL-29 has also been shown to modulate anti-viral proteins
like 2′5′-oligoadenylate synthetase2,3, MxA protein, and IFN-inducible double
stranded (ds) RNA-activated protein kinase, and multiple interferon sensitive
genes (ISGs)56,57,2,64,62,65.

1.3 IL-28 receptor and signalling
IFNα and IFNβ (type I IFNs) bind to a specific and distinct heterodimeric
receptor composed of IFNARα and IFNARβ. Binding of IFNα or IFNβ to their
receptor leads to the activation of two receptor-associated tyrosine kinases,
Janus kinase (Jak)1 and tyrosine kinase (Tyk)2; this is followed by tyrosine
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phosphorylation of the Signal Transducers and Activators of Transcription(STAT)1 and STAT2 proteins. Phosphorylated STAT1 and STAT2 combine with
IFN-regulatory factor 9 (IRF-9) to form the trimeric IFN-stimulated gene factor-3(ISGF-3) complex, which, upon translocation to the nucleus, binds to the cis
element IFN-stimulated response element (ISRE), upstream of IFN-inducible
genes, and modulates their transcription66,67.
Type I, II and III IFNs are class II cytokine receptor ligands (CRF2) which also
include interleukin 10 (IL-10) and IL-10 related proteins11.The activity of the type
III IFNs is achieved through a heterodimeric receptor complex which, is formed
between IL-28A receptor (IL-28R) and IL-10 receptor (IL-10R2). The
promiscuous IL-10R2 is also part of the IL-10 and IL-22 receptor complex and is
involved in signal transduction for IL-10 and IL-22 (Figure 1.6). Other key
ligands have now been shown to include IL-28A, IL-28B and IL-292,3.
IFNλs were initially shown to activate both STAT1 and STAT2 and thedownstream signalling pathways including interferon sensitive gene complex
ISGF3 and ISRE, similar to those activated by IFNα and IFNβ2. IFNλs like IFNαand IFNβ have been shown to activate STAT3, 4 and 568. Some of IFNα andIFNβimmunomodulatory

functionsaremediated

via

STAT469.

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Chapter 1

Figure 1.6: IL-10Rβ is a promiscuous cytokine receptor
Figure 1.6 adapted from Dumoutier, Sheppard, Kotenko and Xie

2,3,70,71

shows that part of this heterodimeric receptor is the promiscuous interleukin 10

receptor beta (IL-10Rβ) which has a role in cytokine binding with not only the IFNλs but IL-10 and IL-22. However the downstream signalling cascadeshows that IFNλs cause STAT1 and 2 activation. This signalling pathway shares similarities with the IFNAR receptor.

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Despite signalling through distinct receptor complexes, type I and type III IFNs
trigger similar signalling pathways (Figure 1.7), leading to the activation of atranscriptional complex designated ISGF3 which is a unique and crucial
mediator of type I and type III IFN-induced biological activities. ISGF3 binds to
the ISRE in the promoters of ISGs leading to gene transcription.

Figure 1.7: Type III IFN receptor signalling compared to type I and II
Type I, II and III IFN receptor binding leads to activation of STAT, the translocation of
STAT into the nucleus activates either interferon-stimulated genes (ISG) with apromoter interferon-stimulated response element (ISRE) or γ-activated sequence(GAS). Adapted Vilcek, J. Nat Immunol4.

As well as the Jak-STAT pathway type I and type III IFNs can also induce
signalling through mitogen-activated protein kinase (MAPK) cascades: stressactivated protein kinase/c-Jun N-terminal kinase (SAPK/JNK); extracellularsignal-regulated kinase (ERK)-1/2; and mitogen-activated protein kinase p38
56,65

.

The heterodimeric receptor IFNAR1/2 for IFN-α and IFN-β is present on all
nucleated cells72. IL-10R2 is ubiquitously expressed73, whereas initial RNA
expression data showed IL-28R is limited to specific tissues and cell types2. ILPage 29 of 183

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28R has been shown to be present in intestinal epithelial cells, MCA205, afibrosarcoma cell line56 and type III IFN expression has been shown inmonocyte–derived dendritic cells (MDDC)74,75,76, plasmacytoid dendritic cells(pDC)74,76 and human primary macrophages where induction of type III IFNs
required pre-treatment with IFNα74,75,76. Other studies showed in vivo
experiments highlighting primary targets of type III IFNs are epithelial cells of
the respiratory, gastro-intestinal and reproductive tracts59,77,78. IL-28R is
predominantly expressed in epithelial cells and specific subsets of immune
cells77,79,78,80.

1.4 Transcriptomic analysis gene activation profiles andsignalling pathways of IL-28A and IL-29
Transcriptional (mRNA) expression patterns have been shown for IFNα, β and
γ81, and for IL-29 in a HCV replicon cell line61 and Raji cells65. Zhou65
investigated gene expression at an early time point, 4 hours, with 200 IU of
IFNα and 10ng/mL of IL-29 in triplicate on Affymetrix gene chips. 27 uniquegenes with greater than a two fold change were seen with IL-29 compared with
313 IFNα induced genes. Significance Analysis of Microarrays analysis (SAM)(Stanford University) showed that only 10 genes were unique to IFNα, themajority of genes were also present in the IFNλ dataset but due to IFNλ signal
being weaker they did not reach the 2 fold cut off. IFNλ was shown to induce
ISGs, none of which were determined to be unique to IFNλ. Marcello61 also
used Affymetrix microarray analysis, but used 5ng/mL IFNα and 10ng/mL of IL29 in an HCV replicon system at looked at 3, 12 and 24 hour time points.
Marcello showed in a dataset of 66 genes (being induced at least 2 fold in either
IFNα or IL-29 at one or more time points); that IFNα and IL-29 induce most of
the same genes (with no unique genes being expressed with IFNλ) but that overtime the majority of IFNλ genes continue to increase by 24 hours whereas
expression of IFNα genes are mainly decreased by 24 hours. Doyle57 also
reported that IL-29 stimulates nearly identical patterns of gene expression as
IFNα as analysed by microarray. Microarray analysis as documented in thisthesis was initiated prior to the publication of microarray studies describedabove57,61,65. There is still a need to fully identify the antiviral effects and modes

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Chapter 1of action of type III interferons by pathway expression analysis. Microarray
analysis described in this thesis additionally investigated IL-28A versus IFNα
and work was carried out in a HCV HuH7 parent cell line.
Induction of similar sets of ISGs enables Interferon lambdas and IFNα to induce
similar biological activities and functions primarily inducing an antiviral state incells.

1.5 Alternative therapies for HCV and IFN lambda as a therapy
Chronic infection with hepatitis C virus affects 1:12 or approximately 3% of theworld’s population and causes approximately 350,000 deaths annually 46.
Pegylated interferonα (IFNα) in combination with the nucleoside analogueribavirin is the current standard of care for the treatment of patients chronicallyinfected with hepatitis C (HCV). Combination therapy results in a sustained
virological response (defined as clearance of circulating HCV RNA at six
months post-treatment) of only ~50% of patients with HCV genotype 1
infection82. IFNα therapy is administered parenterally and has side effects suchas flu-like symptoms, anorexia, depression83 and myelosuppression84 that canbe severe and often dose limiting85. In recent years, a number of new drugs
against HCV have emerged. Direct-acting antivirals (DAAs) are specificallydesigned to inhibit viral targets, and host-targeted antivirals block host factorsthat are important for the viral lifecyle. Alternative interferons could be effective
antiviral agents, without the side effects of IFNα.
Direct-acting antivirals, NS3/4A protease inhibitors inhibit viral protease NS3/4A
is required for the cleavage of downstream, nonstructural proteins, including the
NS5A protein and the NS5B RNA-dependent RNA polymerase (RdRp). In May
2011, NS3/4A protease inhibitors, telaprevir and boceprevir, were approved by
the US Food and Drug Administration for the treatment of patients with chronic
genotype 1 HCV infection. With the current DAAs there is rapid resistance due
to rapid mutations of HCV40,41,86,87. The current DAAs are administered withpeginterferon-alfa-2a and ribavirin to prevent resistance to the DAAs. Bothtelaprevir and boceprevir highly improve rates of SVR of HCV infected patients
but there are limitations, designed to target genotype 1 HCV they havedifferential efficiency across the genotypes88,89,90, they are also limited by side
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effects, rash (Telaprevir) and anaemia and pharmcokinetic properties meaningthat they have to be taken with fatty meals every 8 hours.
RdRp inhibitors inhibit the active site of polymerase activity, Preliminary resultsfrom Phase II trials reported rates of EVR >80% among patients with HCV
genotype 1 or 4 infection who received mericitabine in combination with SOC
PEG-IFN and RBV47; no viral rebound or resistance mutations were observed
by week 1291. These inhibitors could be used without IFN. miR-122 inhibitors
inhibit miR-122 which is a host liver-specific microRNA required for HCV
replication. Miravirsen is in Phase IIa trials; and significantly reduces viral load
after 8 weeks of therapy without significant adverse effects 92 but there areconcerns with microRNAs with off target effects. Host factor cyclophilins areimportant for viral replication, Alisporivir is in advanced clinical trials, it inhibits
viral replication by disrupting the interaction between cyclophilin A andNS5A93,94. Alisporivir combined with PEG-IFN and RBV, led to an SVR in 76%
of HCV genotype 1 infection patients compared to 55% with SOC94.
Zymogenetics licensed lambda interferons to Novo-Nordisk and now BristolMyers Squibb for viral infections including HCV. A pegylated form of IFN-λ1 (IL29) is currently in clinical trials for the treatment of chronic HCV infection andinitial reports shows less severe side effects than pegylated IFNα, phase 1b
dose-escalation study, PEG−IFN-λ1 inhibited HCV without significant systemic
toxicity and phase 2b data showed that the highest doses of PEG−IFN-λ1,
when combined with RBV, produced a complete EVR in 30% of patients with
HCV genotype 1 infection, compared with 28% of the patients who received the
SOC95,96. Clinical development: A recent press release from Bristol-Myers
Squibb (19 April 2012) showed that peginterferon lambda-1a (Lambda) plus
ribavirin achieved sustained virologic response rates 24 weeks post-treatment(SVR24) that were comparable to peginterferon alpha-2a plus ribavirin in phase
IIb EMERGE clinical trial in 118 treatment-naïve patients chronically infectedwith genotype 2 or (HCV). There may be a role for IL-28B treatment in the
future, four Genome Wide Association studies have highlighted the significanceof IL-28B within the innate immune response to HCV 97,98,99,100. Two protective
SNPs were shown to be associated with a SVR to IFNα/Ribavirin in patientswith HCV genotype 1. These were the T allele of rs8099917 and the C allele

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Chapter 1of rs12979860 located 8 kilo bases (kb) and 3 kb respectively upstream of the
IL-28B gene. In a study of rapid viral response (RVR) (undetectable HCV
RNA at 4 weeks) rates in patients with HCV Genotype 1 and 4, of the RVRs
100% of carriers of the protective rs12979860 C allele, and 64% of non-RVR
individuals expressed the non-protective genotype T allele of rs8099917101.
The potential broad roles of IFN-λs in immune function may also mean they playa future role in autoimmunity and cancer therapy. Type III IFNs like type I IFNs,
may potentially be used for the treatment of other inflammatory or autoimmune
diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus(SLE)102, or multiple sclerosis (MS)103. IFN-λs have been shown to have potent
antitumor activities in murine models of cancer104,105,106, highlighting potential asanti-cancer therapy.

1.6 Introduction summary
The biological significance of IFNλs remains to be fully determined. This thesisshows the investigation of antiviral activity of IFNλs, the similarities anddifferences between the type I and type III IFNs determined by microarray
analysis, and the distribution of IL-28R and the significance of limited
distribution in bone marrow assays.

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1.7 Hypothesis“Current treatment of antiviral diseases with type I IFNs can be inadequate. As
IFNλs have antiviral activity and use a different receptor and signallingtransduction pathways to IFNα, IFNλ therapy could be useful in the
management of viral infections.”

1.8 Thesis Aims
1.

Investigation of the antiviral activity of IL-28A and IL-29 on a panel ofviruses in vitro and their effects on IFN sensitive gene models.

2.

Transcriptomic analysis to determine gene activation profiles andsignalling pathways of IL-28A and IL-29.

3.

Investigation of IL-28R tissue expression in a panel of mouse and humantissues.

4.

Further investigations to support hypothesis that IFNλ therapy could be analternative to IFNα.

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Chapter 2

Chapter 2
2. Materials and methods
2.1 Investigation of the antiviral activity of IL-28A and IL-29
using antiviral and interferon sensitive gene model assays
2.1.1 Hepatitis C comparison of antiviral activity of IFNα, IFNβ, IFNγ, IL28A and IL-29
The antiviral effects of interferon lambdas were investigated in a HCV repliconmodel which comprises of a HuH7 hepatoma derived cell line stably transfectedwith an autonomously replicating subgenomic HCV RNA 38. Established stable
replicon assays for HCV genotypes 1a and 1b were used; constructs are shown(Figure 2.1). Later work used clones of HCV genotype 1b with an integral
luciferase; the structure is shown (Figure 2.2) and method is described (Section
2.1.2).

Figure 2.1: HCV replicon structure
HCV replicon RNA in HuH7 hepatoma cells, replicons of HCV genotypes 1a (top) and1b (bottom). Non structural viral (NS) proteins are expressed 5 prime (‘) and 3’
nontranslated regions (NTR), neo is the neomycin phosphotransferase gene used with
G418 to select cells containing the replicon, NS2- envelope protein not present in the
1a replicon, NS3 serine protease, NS4A and 4B cofactors of NS3, NS5A interaction
with cellular proteins and NS5B RNA dependant RNA polymerase.

HuH7 cells containing either genotype 1a107 or 1b38 replicons were cultured in:
Dulbecco's Modified Eagle Medium (DMEM) without sodium pyruvate,
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Chapter 2
4500mg/L Glucose and Pyridoxine hydrochloride (HCl), supplemented with 10%
foetal bovine serum, 1% penicillin, 100μg/mL streptomycin, 2mM L-glutamine(left), 1% non-essential amino acids and 500μg/mL G418 (Geneticin) (additionof G418 selects cells with replicon) (all reagents from Invitrogen). 96-well flatbottomed microtitre plate (Nunc) containing 3 x 104 cells per well wereincubated with compounds as detailed below in a humidified incubator at 37°C
and 5% CO2 for 72 hours.
Serial dilutions of IFNα, IFNβ, IFNγ (PBL biomedical laboratories) IL-28A andIL-29 (R&Dsystems) were made up in culture medium as described above
without the addition of G418. IFNα2a was used in all experiments and called
IFNα. IFNα, IFNβ dilutions were optimised to 1000, 500, 250, 125, 63, 32, 16, 8,
4, 2 international units (IU)/mL, IFNγ 2000 to 4 IU/mL, IL-28A 200ng/mL to
4ng/mL and IL-29 1000ng/mL to 2ng/mL. Controls were included on each plate,these were: no primary antibody controls, cell control wells without the additionof compound and in house proprietary assay controls were included as anegative control and positive controls respectively. IFNα, IFNβ, IFNγ, IL-28A
and IL-29 were run in duplicate at each dilution on the plate and each plate wasrun in triplicate over 3 separate occasions to allow for variability of cell passage.
An Enzyme-linked immunosorbent assay (ELISA) was performed on the plates
to detect NS5A protein using murine anti-HCV NS5A primary antibody. Medium
was aspirated followed by a PBS wash and aspirate; the cells were then fixedfor 5 minutes in methanol (MeOH): acetone (1:1). The fixative was removed andfurther washed in PBS. This was followed by a blocking step with 2% skimmed
milk in PBS plus 0.05% tween 20 at 37oC for 1 hour. Blocking buffer was
removed and primary antibody, 50µL of murine anti-HCV NS5A (Virostat) was
diluted to 0.5µg/mL in blocking buffer and added to the plate, with the exceptionof no primary antibody wells (blocking buffer only) then incubated at 37oC for 2
hours. Primary antibody was removed and plates were washed three times withwash buffer, PBS plus 0.05% tween 20. 50µL of horseradish peroxidaseconjugated secondary antibody, rabbit anti-mouse immunoglobulin G (IgG)(Dako) was diluted 1:1000 in blocking buffer and incubated for 1 hour at 37 oC.
Secondary antibody was then removed and plates were washed five times withwash buffer. The next step was to allow a colour to develop by incubating thePage 36 of 183

Chapter 2plates for 30 minutes with 50µL OPD/peroxidase substrate in urea buffer. The
colour reaction was stopped with the addition of 25µL of 2 molar (M) sulphuric
acid. Absorbance was then measured at 490 nanometers (nm). Cells were also
stained with 5% carbol fuchsin to visually assess cytotoxicity.
2.1.2 Determination of IC50 values for four luciferase HCV replicon clones
Values for 10 x IC50 concentrations in the replicon cell lines were determined tonormalise for the antiviral activities of proteins IFNα, IL-28A and IL-29. Fourluciferase replicon cell lines were compared for sensitivity with IFNα, IL-28A andIL-29 these were: 1a1_19, 1a3II, 1b 2.2, 1b2.5, and the most sensitive selected
to carry through into transcriptomics analysis (Section 2.2.1).
HuH7 HCV luciferase replicon cells were routinely maintained in DMEM,
4500mg/L Glucose and Pyridoxine HCl supplemented with 10% foetal bovine
serum, 100IU/mL penicillin, 100µg/mL streptomycin, 2mM L-glutamine, 1% nonessential amino acids and 500µg/mL Geneticin. (All reagents from Invitrogen).
The assay media conditions were as above minus Geneticin. 1 x 106 cells perwell of each of the HuH7 HCV luciferase replicon cells were cultured in 96-wellplates at 37°C. Dilutions of IFNα, IL-28A and IL-29 were made up in triplicate.
For each luciferase cell line, 5 x 104 confluent cells in a 50µL volume per well
were added to compound made up to 50µL with medium. The plates wereincubated for 18 hours at 37oC. Supernatent was removed and 25µL of SteadyGlo (Promega) was added per well and the plate was left in the dark for 15
minutes before reading chemiluminescence at 450nm. The half maximal
inhibitory concentration (IC50) was defined as the concentration of eachtreatment which reduced luciferase signal by 50% compared with untreatedcells.

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Figure 2.2: HCV luciferase replicon clones structure
Clones 1a1_19, 1a3II and 1b 2.2, 1b2.5 were provided by Thomas Zurcher GSK, allclones had a 5’ lucifease unit (luc-ubiq). Neo is the neomycin phosphotransferase geneused with G418 to select cells containing the replicon, NS2- envelope protein notpresent in the 1a replicon, NS3 serine protease, NS4A and 4B cofactors of NS3, NS5A
interaction with cellular proteins and NS5B RNA dependant RNA polymerase.

2.1.3 IL-28A, IL-29 and IFNα synergy
1b replicon cell line assay as described (Section 2.1.1) was used as results
showed (Section 3.1.1) that the 1b cell line was most sensitive to interferons
tested. Serial dilutions of IL-28A 200ng/mL to 4ng/mL and IL-29 1000ng/mL to 2
ng/mL were made up in culture medium alone and then in addition with
0.09ng/mL of IFNα (IC50 concentration as determined in experiments performed(Section 2.1.1)). To determine antiviral activity in the HCV 1b replicon cell line of
IFNα at 0.09ng/mL this was also run separately on its own as a control. Controls
were included on each plate, these were: no primary antibody controls, cell
control wells without the addition of compound and in house proprietary assay
controls were included as a negative control and positive controls respectively.
IL-28A and IL-29 were run in duplicate at each dilution on the plate and eachplate was run in triplicate over at 2, 4, 6, 8, 16 and 24 hours.
2.1.4 IFN sensitive gene models 6-16 and ISG56
To investigate type III interferon modulation of interferon sensitive genes (ISGs),
two ISG assays were used: interferon sensitive gene 56 (ISG56) and interferon
inducible gene 6-16 (G1P3).

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ISG56 alternatively named interferon-induced protein with tetratricopeptide
repeats 1 (IFIT1), a 293 cell line (a continuous line of transformed humanembryonic kidney cells) with ISG56 promoter construct was used. ISG56 is themost highly induced IFN sensitive gene (30-100 fold induction), the assay isrobust over several logs of IFN concentration and response is dependent on
intact receptor and signal transduction pathways. 293 cells were cultured in
DMEM + 4500mg/mL glucose, 20mM L-Glutamine, Pyruvate (Sigma-Aldrich),
10% foetal calf serum, 100 IU/mL penicillin, 100μg/mL streptomycin and500μg/mL G418. 5 x 104 cells were cultured for 18 hours with serial dilutions of
IFNα, IFNβ and IFNγ, 1000, 500, 250, 125, 63, 32, 16, 8, 4, 2 IU/mL and serial
dilutions for IL-28A ranging from 200ng/mL to 4ng/mL and IL-29 from
1000ng/mL to 2ng/mL. Untreated cell and virus controls were also included.
IFNs were run in duplicate and the experiment was performed in duplicate.
Supernatants were removed and 25μL of Steady-Glo, (Promega) was added
per well and the plate was left in the dark for 15 minutes at room temperature
before optical density (OD) measurement at 405nm.

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Figure 2.3: ISG56-luciferase reporter
The ISG56-luciferase reporter assay is used to show binding to Toll-like receptor 3(TLR3), inducing antiviral response resulting in ISG56 induction and involving TANKbinding kinase 1(TBK-1), interferon regulatory factor 3 (IRF3) leading to modulation of
ISG56.

Interferon, alpha-inducible protein 6 (6-16) alias IFI6; 6-16; FAM14C; G1P3; IFI6-16; IFI616 an interferon sensitive gene model was also used to investigate
type III interferon activity, this cell line was maintained at GSK. Humanglioblastoma T98G cells were transfected with a plasmid containing a genecoding for soluble alkaline phosphatase under control of an interferon-inducible
promoter. The assay was set up as described above for ISG56.
2.1.5 Hepatitis B (HBV)
Antiviral effects of IL-28A and IL-29 compared with IFNα were investigated inhuman hepatocellular carcinoma HepG2 (2.2.15) cell line stably transfected with
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HBV subtype ayr maintained at the Department of Medicine, Imperial College.
HepG2 cells were cultured at 37°C in a humidified 5% CO2 atmosphere in
Minimum Essential Medium Eagle media (MEME) supplemented with 10%
foetal calf serum, and 50µg/mL kanamycin. Cells were subcultured once a week
by detaching the cells with pancreatin (0.5mg/mL) followed by change of
medium on the following day. 8 well plates containing 5 x 104 cells per well wereincubated with IFNs in a humidified incubator at 37°C and 5% CO 2 for 1 week.
Concentrations of IFNs used were: 100, 1000 IU/mL for IFNα, 200, 2000ng/mL
for IL-28A, 100, 1000ng/mL for IL-29 and untreated. Total DNA was extracted
from each well using a Wizard® Genomic DNA Purification kit according to
manufacturer’s instructions.
(http://www.promega.com/~/media/Files/Resources/Protocols/Technical%20Ma
nuals/0/Wizard%20Genomic%20DNA%20Purification%20Kit%20Protocol.pdf.)
Antiviral activity was detected using quantitative real-time polymerase chain
reaction (PCR) (TaqMan®) primers (Proligo) and probes (Applied Biosystems).
This was performed in the presence of the house-keeping gene glyceraldehyde
3-phosphate dehydrogenase (GAPDH) and all amplifications were performed inquadruplicate.
Table 2.1: Hepatitis B virus probe and primer sequences
HBV1

Sequence

Forward primer

5’GGACGGAAACTGCACTTGTATTC-3’

Reverse primer

5’GACTGAGGCCCACTCCCATAG-3’

Probe FAM/ TAMRA

5’ CCATCATCCTGGGCTTTCGCAAGATT-3’

TaqMan® probes consist of a fluorophore (e.g. 6-carboxyfluorescein, (FAM)) covalently
attached to the 5’-end of the oligonucleotide probe and a quencher (e.g.
tetramethylrhodamine, (TAMRA)) at the 3’-end.

2.1.6 Real-Time PCR assay overview
TaqMan® (Applied Biosystems) is the trademark name of the PCR-based,
fluorogenic 5'-nuclease assay, which allows for the real-time quantitation of
DNA/RNA, allelic discrimination and pathogen detection. This can include
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SybrGreen and fluorogenic probes (TaqMan®). Most PCR included in the thesis
is covered by these two assays and run on Applied Biosystems 7900 PCR
machines, the other PCR assay described in this thesis also uses SybrGreendye but run on a different proprietary PCR machine Corbett Life Science RotorGene real-time PCR machine (Corbett Life Science).
2.1.6.1 Sybr Green 1 dye
Sybr Green 1 dye: binds to the minor groove of DNA and is fluorescent whenbound. As the PCR progresses through the cycles and more PCR product isaccumulated so more dye binds resulting in an increase in fluorescence. Byplotting fluorescence against cycle number an amplification plot is produced
which provides a more accurate picture of the PCR rather than measuring end
product. To ensure the specificity of the primers, dissociation curve analysis iscarried out on the PCR’d samples. This collects the fluorescence levels
associated with the melting point of the PCR product already produced and it
allows detection of non-specific priming and primers dimers in the template freesample.
2.1.6.2 Fluorogenic 5’ nuclease assay (TaqMan®)
The fluorogenic 5' nuclease assay uses a fluorogenic probe to enable thedetection of a specific PCR product as it accumulates during PCR. The reporterdye is incorporated on the 5' end and the quencher on the 3' end of the probe.
When the probe is intact, the proximity of the reporter dye to the quencher dye
results in suppression of the reporter fluorescence. During PCR, if the target ofinterest is present, the probe specifically anneals between the forward andreverse primer sites. The 5´–3´ nucleolytic activity of the AmpliTaq Gold DNA
Polymerase cleaves the probe between the reporter and the quencher only if
the probe hybridises to the target. The probe fragments are then displaced fromthe target, and polymerisation of the strand continues. The increase influorescence signal is detected only if the target sequence is complementary to
the probe and is amplified during PCR. Because of these requirements, any
non-specific amplification is not detected.

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Figure 2.4: TaqMan® Real-time PCR process
Real time PCR process probe containing R-reporter and Q- quencher, anneals totarget sequence, during the extension phase the reporter is detached and can bemeasure at every cycle of the PCR. Taken from http://ukgwrdweb1.ggr.co.uk/TaqMan

2.1.6.3 Primer and probe design
Primer sequence and where applicable probe sequences were designed using
NCBI entrez nucleotide website:
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Nucleotide
Primers and probe are designed to the gene of interest using Applied
Biosystems Primer Express software. This software has some of the necessary
requirements for acceptable probes and primers built in. The exception to thiswas IL-28R assay was on demand assay predesigned (Applied Biosystems).
2.1.6.4 PCR reagents
DNA or Total RNA was prepared from the tissue or cells being investigated andnormally added at 50ng concentration. Copy number relative changes or a
genomic standard curve was prepared for the species being investigated. This
allowed quantification of gene copy number. Primers were diluted to a working
concentration of 10M, and probe to 5M. Universal PCR Master Mix (Applied
Biosystems) was added at 2 x concentration, it contains the AmpliTaq Gold
DNA polymerase, AmpErase® Uracil N-glycosylase (UNG), deoxynucleotide
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triphosphates (dNTPs), Passive reference ROX, and optimised buffer
components. AmpErase UNG is present in the mix as it can prevent thereamplification of carryover PCR products by removing any uracil incorporated
into single or double stranded DNA. ROX is a passive reference dye present in
the master mix and allows for the normalisation of amplification across wells
due to master mix variability.
Multiplexing allowed normalisation of the gene of interest to an endogenous
control whose levels are assumed not to change with treatment, reducing thewell to well template variability within the data, e.g. GAPDH, b-actin, 18S
ribosomal RNA.
2.1.6.5 PCR cycling parameters
PCR cycling parameters unless stated were 40 cycles of:
50oC for 2 minutes
95oC for 10 minutes
95oC for 15 seconds
60oC for 1 minute
For Sybr Green Dissociation Curve analysis one cycle is added at the end of
run.
95oC for 15 seconds
60oC for 20 seconds
95oC for 15 seconds
2.1.6.6 Data Analysis
Key parameter for data analysis is the Threshold cycle (Ct): this is the cycle atwhich the amplification of the gene is in the exponential phase. The baseline
was set to ensure that signal is not discarded as noise. The standard curve waschecked to ensure reproducibility and satisfactory linear regression. No
Template Control (NTC) wells were viewed to assess cross contamination. The
starting copy number of the gene in each sample was calculated from thestandard curve by the software, and then exported into Excel (Microsoft), forfurther data analysis including normalisation to endogenous control if
applicable.

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Figure 2.5: TaqMan® Real-time PCR amplification plot
Adapted from TaqMan® data plot 7900 Applied Biosystems.

2.1.7 Human immunodeficiency virus (HIV)An established method was adapted at GSK to look at antiviral effects of IFNα,
IFNβ, IFNγ, IL-28A and IL-29. The assay used MT4 T lymphocyte derived cells
infected with HIV virus HXB2. MT4 cells were split 1:4 two days before required
using phenol red indicator media (RPMI) plus 10% Hyclone foetal bovine serum
and Penicillin/streptomycin/L-Glutamine (100units/mL,100µg/mL and 2mM
respectively). Cells were used at a concentration of 8 x 105 per mL and 2.4 x
106 cells were used per infection. Cells were harvested by spinning at 400g for
5 minutes at room temperature and re-suspended in RPMI medium without
phenol red indicator containing the supplements as above.
MT4 cells were infected with HIV virus HXB2 at a concentration of 100 x 50%
Tissue Culture Infectious Dose (TCID50) per million cells for one hour. IFNs
were then added to the cells. Serial dilutions of IFNα were optimised to 400,
200,100, 50, 25, 12, 6, 3, 1.5 IU/mL, IFNβ were optimised to 3200, 1600, 800,
400, 200, 100, 50, 25, 12 IU/mL and serial dilutions were made for IFNγ ranging
from 25600 to 2 IU/mL, for IL-28A from 7.68mg/mL to 4ng/mL and for IL-29 fromPage 45 of 183

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1mg/mL to 2ng/mL. IFNs were run in quadruplicate on the plate and each plate
was run in triplicate over different days. Non infected cells were used as a cell
control and virally infected cells with media in place of drug were run as a virus
control. The cells were incubated for 120 hours and then treated with Dimethyl
thiazolyl diphenyl tetrazolium salt (MTT). Plates were read between 540-590nm
and the IC50 for IFNs calculated.
Category 3 lab training was required in order to work with HIV virus in the GSK
Stevenage labs; and was completed before work using HIV was initiated.

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Figure 2.6: MT-4 cells uninfected and infected with HXB2
An example of MT-4 cells uninfected and infected with HXB2;
A shows normal MT-4 cells in suspension, single cells and common clumping,
B shows HXB2 infected cells, the cells circled show one cell full of HXB2 virus and the outline of a burst cell.

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2.1.8 Dengue fever virus
A cell line stably expressing dengue virus replicon established in Professor
Graham Foster’s laboratory at Queen Mary's School of Medicine and Dentistry
was used to test the antiviral properties of type III interferons. K562 (humanchronic myeloid leukaemia) cell line stably expressing the dengue virus replicon
ΔCprME-PAC2A was used.

Figure 2.7: Schematic showing plasmid pDENΔCprME-PAC2A
Dengue virus type 2 infectious clone cDNA (in plasmid pDVWS601)108 containing asingle open reading frame carrying three structural genes (C, core; prM, premembrane;
E, envelope), seven nonstructural (NS) genes, and flanking 5' and 3' untranslated
regions (UTR).

2.1.8.1 Cell Culture
Cells stably expressing dengue virus replicon RNA were generated bytransfection with ΔCprME-PAC2A RNA and then propagation in RPMI
containing 10% foetal bovine serum (FBS) and 3μg of puromycin (SigmaAldrich) per mL. Cells were removed from puromycin selection and checked for
replicon expression before use by indirect immunofluorescence of the dengue
virus NS1 protein with a specific monoclonal antibody (5H5.4)109. K562 cells
without replicon were continuously maintained in the same medium without
puromycin53. K562.ΔCprME-PAC2A cells were grown in the presence of 0, 100,
1,000 IU/mL for IFNα, IFNβ and IFNγ, 0, 200, 2000ng/mL, 0, 100, 1000ng/mL
for IL-28A and IL-29 respectively for 24 hours.
2.1.8.2 Total RNA extraction
Total RNA extraction from suspension cell cultures was carried out using the SV
Total RNA Isolation System (Promega). Samples were centrifuged for 5 minutes
and culture media was removed. Cell pellets were washed with 1mL of sterile
PBS and centrifuged for a further 5 minutes. The PBS was removed and 150µL
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SV Lysis Buffer added to each tube. The lysates were transferred into
RNase/DNase free 1.5mL Eppendorf tubes. Genomic DNA was sheared bypassing the lysates through a 19-gauge blunt-ended needle four times andplaced on ice. Lysates were stored at -80ºC until required for total RNA
extraction.
2.1.8.3 Total RNA extraction using the SV Columns
Lysates were thawed and 350µL transferred to a fresh RNase/DNase free
1.5mL Eppendorf. 700 µL of SV Dilution Buffer was added, mixed by inversion,and the mixture incubated at 70oC for 3 minutes. Following centrifugation at
12,000 x g for 10 minutes, the supernatant was transferred to a sterile 1.5mL
Eppendorf containing 400µL of 95% v/v ethanol (Sigma-Aldrich). This mixture
was loaded onto two SV RNA Isolation Tube Assemblies which were
centrifuged at 14,000 x g for 1 minute. Liquid in the collection tubes was
discarded, 600µL of SV RNA Wash Solution applied to each column and the SV
RNA Isolation Tube Assemblies centrifuged at 14,000 x g for 1 minute. The
collection tubes were emptied and 50µL of SV DNase Incubation Mix (preparedfrom 50µL of SV Yellow Core Buffer, 5µL of SV 0.09M MgCl2 and 5µL of SV
DNase I enzyme) applied to the surface of each column membrane. SV RNA
Isolation Tube Assemblies were incubated at room temperature for 15 minutes
to allow DNA digestion to proceed, after which 200µL of SV DNase Stop
Solution was added to each column. SV RNA Isolation Tube Assemblies were
centrifuged at 14,000 x g for 1 minute, 600µL of SV RNA Wash Solution applied
to each column and then centrifuged again at 14,000 x g for 1 minute. Liquid in
the collection tubes was discarded and a final wash carried out by applying
300µL of SV RNA Wash Solution to each column and centrifuging the SV RNA
Isolation Tube Assemblies at 14,000 x g for 2 minutes (to eliminate ethanol
carry-over).
The column within each SV RNA Isolation Tube Assembly was transferred to a
fresh 1.5mL RNase/DNase free Eppendorf tube and 100µL of SV Nuclease
Free Water applied to the membrane. Columns were incubated at room
temperature for 1 minute and the total RNA eluted by centrifuging thecolumn/tube assemblies at 14,000 x g for 1 minute. The columns were

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discarded and eluted total RNA from replicate columns pooled prior to storage
at -80oC until required.
2.1.8.4 Total RNA Quantification and Quality Control
The concentration, yield and purity of each total RNA sample was determinedusing ultraviolet (UV) spectrophotometry. The integrity of each total RNA
sample was determined by agarose gel electrophoresis.
2.1.8.5 Quantification Using UV Spectrophotometry
Spectramax 190 UV Microtitre Plate Reader (Molecular Devices) was used formeasuring UV absorbance of total RNA samples. The absorbance of each total
RNA sample (at an appropriate dilution in Molecular Grade Water) at 260nm(peak nucleic acid absorbance) and 280nm (peak protein absorbance) was
measured and the A260/A280 ratio determined to indicate the level of protein
contamination. Total RNA samples with an A260/A280 ratio of 1.8 to 2.1 wereconsidered of acceptable quality. The total RNA concentration was derived
using the following formula:
RNA concentration in µg/µL = ((A260 x 40*) x dilution factor)/1000*Where 40 = the RNA extinction coefficient
2.1.8.6 Quality determination using agarose gel electrophoresis
A 1% weight/volume agarose gel was prepared by melting 1g of Molecular
Biology Grade Agarose (Sigma-Aldrich) in 100mL of 1 x Tris-borate
Ethylenediaminetetraacetic acid (EDTA) (TBE) buffer (45mM tris-borate, 2mM
EDTA) (Sigma-Aldrich). The melted gel was allowed to cool to approximately
60ºC before adding 5µL of 10mg/mL ethidium bromide solution (Sigma-Aldrich)(final concentration of 0.5µg/mL). The gel was mixed gently by swirling, poured
onto a gel tray (containing two gel combs) and allowed to set for 30 minutes atroom temperature. The set gel was transferred to an electrophoresis tank (LifeTechnologies) and submerged in 1 x TBE buffer.
Total RNA samples were prepared by mixing 5µL of each total RNA sample
with 1µL of 6 x Gel Loading Buffer (Sigma-Aldrich) and placed on wet ice until
required. Samples were loaded into wells within the gel and electrophoresis
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carried out for 30-45 minutes at 100 volts. To visualise total RNA staining, thegel was visualised using the GeneGenius Bioimager gel documentation system(Syngene) and the presence of intact discrete 18S and 28S ribosomal RNA(rRNA) bands indicated that the total RNA was of acceptable quality. If therRNA bands were not present, or appeared degraded, the total RNA wasdiscarded and a fresh isolation carried out.
2.1.8.7 QPCR
Extracted RNAs were treated with RQ1 RNase-free DNase (Promega) todegrade both double stranded and single-stranded DNA, and reverse
transcribed with Moloney murine leukemia virus (M-MLV) reverse transcriptase(RT) (Promega) using random decamer primers. PCR reactions were performed
and analysed on a Rotorgene instrument (Corbett Life Science) by the use ofcustom primers and a fluorescent probe specific for dengue virus NS1 andhousekeeping gene GAPDH was analysed in the same samples by the use of
specific primers and QuantiTect SYBR green (QIAGEN).
Table 2.2: Dengue virus probe and primer sequences
Sequences
Gene

Dengue virus NS1

GAPDH

Forward primer

Reverse primer

Probe /equivalent(5’-3’)(5’-3’)(5’-3’)CTGAAGTGTGGCAGTCTTCAAAGCTAGCTTCACACAGACAACGTGCACGGGATTGCTATCCAACATGGACAGA

ACAGTCCATGCCATCA

GCCTGCTTCACCACCTT

CTGCC

CTTG

QuantiTect SYBR green

Table 2.2 shows probe and primer sequences used for RT-PCR analysis to detect
dengue virus NS1 and housekeeping gene GAPDH.

2.1.9 Respiratory Syncytial Virus (RSV)
A tissue culture model of chronic viral infection using an RSV virus infectedtransformed human B cell line established in Professor Graham Foster’slaboratory at Queen Mary's School of Medicine and Dentistry, was used to test
the antiviral properties of type III interferons.

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2.1.9.1 RSV cell culture
Transformed B cells (106 in 10 mL RPMI medium) were incubated with 2 x 108
viral particles for a total of 14 days leaving the cells undisturbed. Chronic
infection was assessed by direct cell staining and by quantitative PCR. Afterincubation for 14 days, greater than 90% of the cells expressed RSV antigens.
Viral RNA was detected in the supernatant. The cells were maintained in culture
for 16 weeks and passaged every two weeks (cells split 1:3 and the media
exchanged). Cells in six well plates at 0.5 x 106 cells per well were treated with
IFNα, IFNβ and IFNγ at 1000 IU/mL, IL-28A at 2µg/mL, IL-29 at 1µg/mL anduntreated to assess the effects of antiviral treatment. Plates were incubated at
two time points: 48 hours and 96 hours.
Total RNA was extracted and quantified as described (Section 2.1.8.2 – 6) andreversed transcribed using M-MLV RT (Promega). A quantitative PCR reaction
was performed and analysed by Rotorgene (Corbett Life Science) using primers
designed to the WSX1 RSV virus. The values obtained for RSV concentration
were normalised against GAPDH.
Table 2.3 Probe and primer sequences for RSV
Sequences
Gene

Forward primer

Reverse primer(5’-3’)(5’-3’)RSVGATATGCCTATAACAAATGATCAG

GATACTGATCCTGCATTGTCACGAPDHACAGTCCATGCCATCACTGCC

GCCTGCTTCACCACCTTCTTG

Table 2.3 shows probe and primer sequences used for RT-PCR analysis to detect RSV
and housekeeping gene GAPDH.

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2.2 Transcriptome analysis in HCV replicon cells treated with
type I and type III IFNs
2.2.1 Determination of IC50 values for 4 replicon clones
Values for 10 x IC50 concentrations in the replicon cell lines were determined tonormalise for the antiviral activities of proteins IFNα, IL-28A and IL-29. Fourluciferase replicon cell lines were compared for sensitivity with IFNα, IL-28A andIL-29 these were: 1a1_19, 1a3II, 1b 2.2, 1b2.5, and the most sensitive selected
to carry through into transcriptomics analysis. Dilutions of IFNα, IL-28A and IL29 were made up in triplicate. For each luciferase cell line, 5 x 104 confluent
cells in a 50µL volume per well were added to compound made up to 50µL withmedium. The plates were incubated for 18 hours at 37 oC. Supernatent wasremoved and 25µL of Steady-Glo (Promega) was added per well and the plate
was left in the dark for 15 minutes before reading chemiluminescence at
450nm. The IC50 was defined as the concentration of each treatment which
reduced luciferase signal by 50% compared with untreated cells.
2.2.2 Cell culture and treatment
Parental HuH7 and HuH7 HCV 1a3II luciferase replicon cells were routinely
maintained in DMEM, 4500mg/L Glucose and Pyridoxine HCl supplemented
with 10% foetal bovine serum, 100IU/mL penicillin, 100µg/mL streptomycin,
2mM L-glutamine, 1% non-essential amino acids and 500µg/mL Geneticin. (Allreagents from Invitrogen). The assay media conditions were as above minus
Geneticin. 1 x 106 cells per well of parental HuH7 and HuH7 HCV 1a3II
luciferase replicon cells were cultured in 6-well plates at 37°C. Four treatments
were used: untreated, 10 x IC50 for IFNα, IL-28A and IL-29 at time points of 4, 8,
16 and 24 hours. Each condition was performed in triplicate. Values for 10 x
IC50 concentrations in the replicon cell lines were determined to normalise forthe antiviral activities of proteins IFNα, IL-28A and IL-29.
2.2.3 Isolation of RNA
Culture media was removed and monolayers were washed with 1mL of sterile
PBS. The PBS was removed and 1mL TRIzol® Reagent (Invitrogen) 4°C added
to each well. Cells were scraped with a sterile tissue culture scraper, the lysates
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were collected in RNAse/DNAse free 1.5mL Eppendorf tubes. Genomic DNA
was sheared by passing the lysates through a 19-gauge blunt-ended needle
four times and placed on ice. Lysates were stored at -80ºC until required for
total RNA extraction. Total RNA was isolated the SV Total RNA Isolation
System (Promega) and stored at -80°C until required (description of method
section 2.1.8.2).
All RNA samples were analysed by the Agilent Bioanalyzer 2100 Lab-On-AChip Nano 6000 chip (Section 2.2.6.6) to determine the integrity and by UV
spectrometer; OD A260 and A280 for accurate RNA concentration determination.
2.2.4 Quantitative QPCR pre-screen
Real-time PCR was performed on the RNAs isolated above and data analysed
to assess the suitability of the time points and concentrations of the IFNs in theassay before running the samples of full genome Affymetrix chips. Applied
Biosystems assay on demand were used for interferon sensitive genes:
Interferon-induced GTP-binding protein (IFIT1), myxovirus (influenza virus)
resistance 1 (MX1), 2'-5'-oligoadenylate synthetase 1 (OAS1) and an interferon
inducible gene 6-16 (G1P3). Five micrograms of each RNA sample was reverse
transcribed to cDNA using SuperScript II first strand cDNA synthesis (LifeTechnologies). The relative levels of target transcripts were measured using an
ABI PRISM 7900 Sequence Detector System (Applied Biosystems). Serial
dilutions of human genomic DNA (Novagen) were used to generate a standard
curve for quantitation. GAPDH and b-actin were used as housekeeping genes
to normalise the data. Real-time data was collected and analysed using
Sequence Detection System (SDS) software Version 2.0 (Applied Biosystems).
2.2.5 Affymetrix GeneChips® Expression analysis
Affymetrix analysis was carried out using RNA from PBS, IL-28A, IL-29 andIFNα treated samples in both replicon and parental HuH7 cells at time points of
8,16 and 24 hours with each in triplicate (72 chips in total). Analysis of 12
additional chips was performed at the 4 hour time point in parental cells only
due to lack of RNA in the 4 hour time point in the replicon cells, making a totalof 84 chips in the experiment.

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The samples were hybridised to the Human Genome HG-U133plus2 GeneChip(Affymetrix). This array enables the analysis of the expression levels of over
47,000 transcripts and variants including 38,500 well characterised genes.
Further information on the Human Genome HG-U133plus2 GeneChip isavailable at: (http://www.affymetrix.com/products/arrays/specific/hgu133.affx).
Briefly the standard expression GeneChips® possess 22 different 25mer oligo
probes (termed a ‘probe set’) for each gene represented, which are distributed
at locations remote to each other. The probe sets are 3’-biased and designed togive the optimal balance between sensitivity and specificity for the target gene.
To evaluate any potential for non-specific hybridisation, each ‘perfect match’(PM) probe feature has an adjacent paired ‘mismatch’ (MM) probe feature. The
MM probe differs in sequence from the PM probe by a single nucleotide, locatedin the centre of the 25mer. The MM features serve as controls that allow thesubtraction of non-specific hybridisation signals (non-specific hybridisation for
the PM and MM features should be roughly equivalent) from the PM signal toderive the true signal for a particular gene.

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Figure 2.8: Standard eukaryotic gene expression assay
Labelled cRNA targets derived from mRNA of an experimental sample are hybridised
to nucleic acid probes attached to the quartz wafer chip. By monitoring the amount oflabel associated with each DNA location, it is possible to infer the relative abundance ofeach RNA species represented (Affymetrix image library - http://affymetrix.com).

Reverse transcription, second-strand synthesis, and probe generation wereaccomplished by standard Affymetrix protocols full details can be found at:(http://www.affymetrix.com/support/technical/manual/expression_manual.affx)
and are described briefly below.
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2.2.6 Preparation and Quality Control of cRNA Targets for Hybridisation to
GeneChips®
2.2.6.1 Preparation Double-Stranded cDNA
Double-stranded cDNA (ds cDNA) was prepared from total RNA using the OneCycle cDNA Synthesis Kit (900431, Affymetrix).
The following was added to a 0.75mL RNase/DNase free Eppendorf tube:
2µL of T7-(dT)24 primer (100pmol/µL), 5µg of total RNA in 9µL of
Nuclease Free Water.

The tubes were then centrifuged briefly and incubated at 70C for 10 minutes toallow total RNA denaturation and primer hybridisation. The tubes were cooled to
4C and the following added to each reaction:

4µL of 5 x First Strand cDNA Buffer, 2µL 0.1M DTT, 1µL 10mM dNTP
mix and 2µL Superscript II RT (200U/µL)

The tubes were centrifuged briefly and incubated at 42C for 1 hour (to allow
first strand synthesis to proceed). The tubes were cooled to 4C and thefollowing added to each reaction:
91µL of nuclease free water, 30µL of 5 x Second Strand cDNA Buffer,
3µL 10mM dNTP mix, 1µL of E. coli DNA ligase (10U/µL), 4µL of E. coli
DNA polymerase (10U/µL) and 1µL of E. coli RNase H (2U/µL)

The tubes were centrifuged briefly and incubated at 16C for 2 hours (to allow
second strand synthesis to proceed). Two microlitres of T4 DNA polymerase
was added to each reaction, the tubes centrifuged briefly and incubated at 16C
for 15 minutes. To stop the reaction, 10µL 0.5M EDTA (Fluka) was added toeach tube and the contents mixed well.
2.2.6.2 ds cDNA cleanup
ds cDNA was cleaned-up using the ds cDNA Cleanup Kit (Affymetrix). 600μl of
Binding Buffer was added to each ds cDNA sample, mixed thoroughly andapplied to a ds cDNA Spin Column Assembly. The Assemblies were centrifuged
at 14,000 x g for 1 minute and the flow through discarded. The columns were
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Chapter 2transferred to a fresh 2mL collection tube, 750µL of cDNA Wash Buffer added
and the tube assemblies centrifuged at 14,000 x g for 1 minute. The flow
through was discarded and the tube assemblies centrifuged at 14,000 x g for 5
minutes with the caps open (to completely dry the columns). The columns weretransferred to a 1.5mL Collection Tube and 25µL of cDNA Elution Buffer applied
to the membrane. The columns were centrifuged at 14,000 x g for 1 minute andthe purified ds cDNA stored at -20C until required for the in vitro transcription(IVT) reaction.
2.2.6.3 IVT reaction
Biotinylated complementary RNA (cRNA) targets were generated from ds cDNA
using the IVT Labelling Kit (Affymetrix). The following were added to a 0.75mL
RNase/DNase free Eppendorf tube:
20µL of ds cDNA sample, 4µL of 10 x IVT Labelling Buffer, 12µL of IVTLabelling NTP Mix and 4µL of IVT Labelling Enzyme Mix.

The tubes were centrifuged briefly and incubated at 37C for 16 hours to allow
IVT to proceed. The cRNA was either stored at -20ºC until required, or
subjected to cRNA Cleanup.
2.2.6.4 cRNA Cleanup
Biotinylated-cRNA was cleaned-up using the cRNA Cleanup Kit (Affymetrix). To
each cRNA sample, 55µL of Nuclease Free Water and 5µL of 3M Sodium
Acetate (Fluka) were added. 350L of cRNA Binding Buffer and 250µL 100%
ethanol were added to each cRNA sample, mixed thoroughly and applied to acRNA Spin Column Assembly. The assemblies were centrifuged at 14,000 x g
for 15 seconds. The flow through was reapplied to the columns and assemblies
centrifuged again at 14,000 x g for 15 seconds. The columns were transferred
to a fresh 2mL collection tube, 500µL of cRNA Wash Buffer added and the tube
assemblies centrifuged at 14,000 x g for 15 seconds and the flow throughdiscarded. This step was repeated, followed by a final centrifugation at 14,000 x
g for 1 minute. The columns were transferred to a 1.5mL Collection Tube and50µL of Nuclease Free Water applied to the membrane. The columns wereincubated at room temperature for 1 minute and centrifuged at 14,000 x g for 1
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minute to elute the cRNA. The purified cRNA was stored at -20C until required
for the quantification and fragmentation.
2.2.6.5 Quantification of IVT Products and Fragmentation
UV spectrophotometry was used to determine the cRNA concentration andyield. For cRNA samples where sufficient yield and concentration had beenachieved, fragmentation was carried out using the Fragmentation Buffer as
supplied with the cRNA Cleanup Kit. An appropriate dilution of each cRNAsample in Nuclease Free Water was prepared. The absorbance at A260 and A280
was measured and the adjusted cRNA yield calculated using the following
formula:Adjusted cRNA yield (µg) = A – (B x C)
Where:
A = Total yield of cRNA according to A260 result (µg).
B = Starting amount of total RNA used in cDNA reaction (µg).
C = Fraction of cDNA used in IVT reaction.
For example: Start with 5µg of total RNA, use 80% (or 4µg) in the IVT,
and the cRNA yield is 45µg. The calculation would therefore be:
45 - (5 x 0.8) = 41µg
To determine the adjusted concentration, the adjusted yield (in µg) is divided by
the total volume (µL). A volume of each cRNA sample containing 15µg (basedon the adjusted concentration) was transferred to a 0.75mL RNase/DNase free
Eppendorf tube. 0.25µL of Fragmentation Buffer was added for each 1µL ofcRNA and the tube incubated at 94C for 35 minutes and then cooled to 4C for
5 minutes using a DNA Engine Tetrad PCR machine (Bio-Rad). FragmentedcRNA samples were stored at -20C until required. To determine whether cRNAfragmentation was successful, the size of cRNA and fragmented cRNA samples
were assessed using the RNA 6000 Nano Labchip Kit (Agilent).
2.2.6.6 Gel preparation and RNA 6000 Nano Labchip Priming
RNA 6000 Nano Gel Matrix was prepared by placing 550µL into a Spin Filterand centrifuging at 1,500 x g for 10 minutes at room temperature. On the day ofuse, a 65µL aliquot of filtered RNA 6000 Nano Gel Matrix was transferred to a
RNase free Eppendorf tube and 1µL of RNA Nano 6000 Dye Concentrate
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added (Gel-Dye Matrix). The Gel-Dye Matrix was mixed by vortexing andcentrifuged at 13,000 x g for 10 minutes at room temperature. A RNA 6000
Nano Labchip was placed on the Priming Station (Agilent) and 9µL of Gel-Dye
Matrix carefully pipetted into the ‘priming well’. The plunger of the Priming
Station was positioned at the 1mL graduation and the manifold closed firmly
over the Labchip. The plunger was firmly depressed until it was held by the clip
and priming allowed to proceed for 30 seconds, after which the clip was
released. The plunger allowed to recoil for 5 seconds and then pulled back to
the 1mL graduation. The Priming Station was opened, the Labchip removed
and 9µL of Gel-Dye Matrix carefully pipetted into each of the three ‘gel’ wells.
Labchip priming was completed by adding 5µL of RNA 6000 Nano Marker
Buffer to wells 1-12 and the ‘ladder’ well.
2.2.6.7 Sample Preparation, Loading and Running the Labchip
Frozen cRNA and fragmented cRNA samples were thawed and diluted 1/10
with Molecular Biology Grade Water. Two microlitres of RNA Nano 6000 Ladderand each diluted cRNA/fragmented cRNA sample was transferred to a 0.75mL
RNase free Eppendorf tube and heat denatured at 70ºC for 2 minutes. The
tubes were immediately chilled on ice and the contents centrifuged to thebottom at 14,000 x g. One microlitre of heat denatured sample was added toeach sample well; the same volume of heat denatured RNA Nano 6000 Ladder
was added to the ‘ladder’ well. The RNA Nano 6000 Labchip was placed on the
Labchip Vortexer (IKA) and vortexed for 1 minute at 2,400 rpm. The loaded
Labchip was placed into the 2100 Bioanalyzer (Agilent). The ‘Nano 6000 Assay’protocol was selected within 2100 Expert Software version B.02.02 (Agilent)and electrophoresis commenced. Once the electrophoresis was complete theresults file was saved and the size profiles of each cRNA and respective
fragmented cRNA sample inspected visually.

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Figure 2.9: Representative RNA 6000 Nano Labchip cRNA Quality
Assessment Images
A Gel View and B Electropherogram View L = RNA 6000 Nano Marker Ladder. 1-6 =cRNA samples. 7-12 = fragmented cRNA samples.

2.2.6.8

Hybridisation of cRNA Targets to Affymetrix GeneChips® andScanning

Fragmented cRNA targets were hybridised to GeneChips® using the GeneChip®
Hybridisation, Wash and Stain Kit (Affymetrix). All reagents were used as
supplied. The required number of GeneChips® were allowed to equilibrate toroom temperature for a minimum of 1 hour. The GeneChip® was filled with
250µl Pre-Hybridisation Buffer. GeneChips® were placed in a rotisserie rack andincubated at 45C for a minimum of 10 minutes with rotation (~60rpm) in a
GeneChip® Incubator (Affymetrix).
While pre-hybridisation proceeded, hybridisation cocktails were prepared.
Reagents (Table 2.4) were added to a 1.5mL RNase/DNase free Eppendorf
tube. The hybridisation cocktails were incubated at 99ºC for 5 minutes followed
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by 45ºC for 5 minutes using a DNA Engine Tetrad PCR machine (Bio-Rad).
Tubes were centrifuged at 14,000 x g for 10 minutes to remove particulates andstored at room temperature just prior to hybridisation.
Table 2.4: Reagents and Volumes for Hybridisation Cocktail Preparation
Reagent

Human Genome HG-

Final Concentration

U133plus2 GeneChip®
Fragmented cRNA

15µg

0.05µg/µL

Control Oligo B2

5µL

50pM

20 x Hyb Controls

15µL

1.5, 5, 25 and 100pM spikes

DMSO

30µL

2 x Hyb Mix

150µL

Nuclease Free
Water

1x

Up to 300µL

GeneChips® were removed from the incubator and the Pre-Hybridisation Buffer
removed. 200µL hybridisation cocktail was applied to the GeneChip®.
GeneChips® were placed in a rotisserie rack and incubated at 45C for 16 hours
with rotation (~60rpm) in a GeneChip® Incubator (Affymetrix).
2.2.6.9 Washing and Staining of Affymetrix GeneChips®
GeneChips® were removed from the incubator and the hybridisation cocktail
removed. The GeneChip® was filled with 250µL Wash Buffer A.
GeneChip®

For each

to be stained, 600µL of Staining Cocktail 1, 600µL of Staining

Cocktail 2 and 800µL of Array Holder Buffer were dispensed into 1.5mL
Eppendorf tubes on the fluidic station. The Experimental details and barcode foreach GeneChip® were entered in Experiment Manager within Affymetrix
Microarray Suite (MAS). To commence staining and washing, GeneChips® were
loaded into cassette holders on the appropriate Fluidics Station 450. When thewash protocol was completed, the GeneChip® was removed for scanning.

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2.2.6.10 Scanning of Affymetrix GeneChips®, Primary Analysis andQuality Assessment
To scan the GeneChips®, Scanner Control within MAS was opened and the‘autoloader’ function selected. Stained GeneChips were loaded onto the
autoloader of a GeneChip® Scanner 3000 (Affymetrix) and scanning
commenced by clicking ‘start scan’ within Scanner Control. The GeneChips ®
were automatically scanned, producing a .dat file. GeneChip ® .dat files thatwere of acceptable visual quality were analysed using the ‘batch analysis
function’ within GeneChipA® operating software (GCOS) to generate .chp, .celand .rpt files. Hybridisation quality was assessed by reviewing the metrics
generated within the .rpt file and the quality assessed according to thethresholds (Table 2.5).
Table 2.5: GeneChip® hybridisation quality control metrics
Quality Indicator

MetricDescription

Background values

Average Background

Values range 20-100 intensity units

Background values

Raw Q value

Overall indication electrical noise

BioB (1.5pM final)Hybridisation controls

BioC (5pM final)
BioD (25pM final)
Cre (100pM final)Internal control genes

Beta-actin
GAPDH

Prokaryotic gene spikes. BioB equates to
1:100,000 copies and is at the limit of
assay sensitivity. BioB should be called‘present’ in 50% of arrays. BioC, D and
Cre should always be called present.
Used to assess input RNA quality. Ratio
3’:5’ ratio should be <3 for at least one
gene.
The number of probe sets called ‘present’

Percent present%P

expressed as a percentage of the total®

probe sets on the GeneChip .
Scaling andnormalisation factors

SF

Indicates the factor used to normalise thearray to the Target Intensity Signal.

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2.2.6.11 Downstream Analysis of Transcriptomic Data
To undertake comparison analyses of different treatment conditions, thenormalised .chp file for GeneChips® of acceptable quality (as defined in Table
2.5) were imported into Rosetta Resolver® Version 6.0 (Merck Sharpe Dohme).
Rosetta Resolver® is an integrated microarray data repository system thatenables the storage, annotation and statistical analysis of GeneChip ®
experiments110. Upon import of .chp files Rosetta Resolver® associates
individual probe set intensities with gene annotations. To analyse the data,
Rosetta Resolver® uses a proprietary error model that is specific to the
GeneChip® type being analysed111. The concept of the error model is to accountfor experimental error without the need to perform large numbers of replicate
experiments. The error model is an empirical intensity-based method for
obtaining a conservative estimate of the signal variability within a small replicate
data set. To determine the average signal, and whether a particular probe set issignificantly expressed above background (absolute analysis), Rosetta
Resolver® computes the average PM minus MM value for the each probe pair.
As part of this analysis the error model is used to define the variability of eachprobe set intensity. Significance of expression is determined by comparing the
average signal of each probe set to the average signal of negative controls
within the GeneChip®. Probe sets where the error-normalised difference insignal is significantly different are called as present (or significantly expressed).
To undertake comparative analysis between control (‘baseline’) and treatment(‘test’), replicate arrays are defined for any number of groups and the‘RatioBuild’ function used. The RatioBuild function automatically performs
comparisons between all pairs of baseline and test groups and produces aconsensus result for ratio of change (relative to baseline) and significance ofchange. During the course of this analysis, a global normalisation is applied to
all replicate GeneChips® and ratio of change computed from the group mean
intensity for each probe set. To determine the significance of change, the errorof the ratio of change is computed by combining the modelled error of individual
probe sets and the variability of the actual replicates signals. With increasing
numbers of experimental replicates, the relative contribution that the modelled
error makes to the analysis decreases. The analysed data can then be exported
by using the ‘TrendSet’ function within Rosetta Resolver®. The user defines all
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Chapter 2comparisons within the data set and selects thresholds for ratio of change andsignificance (P-value). An arbitrary threshold can also be set for the number ofcomparisons in which the ratio of change and significance thresholds must be
met. This data can then be exported to Excel or as tab-delimited files fordownstream data analysis.
The complexity of the data generated by microarray experiments necessitates
the use of bioinformatics tools to aid interpretation and help confer biologicalmeaning. To this end, transcriptional data exported from Rosetta Resolver ® wasanalysed using biological theme analysis tools. This provides a high level
overview of the functional classes of genes and pathways significantly
overrepresented within a data set.
Two alternative methods, GeneGo MetaCore™ pathways analysis software(http://www.genego.com/metacore.php) and Ingenuity Pathway Analysis (IPA)(Ingenuity Inc.) (Version 2.1), were used.
IPA segregates groups of genes within the query set into networks defined by
known interactions amassed from the literature112. In addition, biological themes
are conferred to the networks by again utilising a modified version of the Fisher
exact. IPA uses proprietary ‘function terms’ to assign overrepresented gene
categories within the gene list. IPA (and GeneGo) are able to identify canonicalpathways that are significantly regulated within the data113. Ingenuity Pathway
Analysis Base (IPKB) has a knowledge base of ~1.4 million findings.
Expression data sets containing gene identifiers (Entrez Gene ID) and theircorresponding expression values with a cut off p-value of 95% or higher andfold changes were uploaded into IPKB or GeneGo. The genes identified as
differentially expressed were included in the analysis and utilised to search forbiological networks.

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2.3 Distribution of type III interferon receptor in a panel ofmouse and human tissues –genomic analysis
2.3.1 TaqMan® quantative PCR for IL-28R RNA detection in mouse
Total cellular RNA was extracted using the SV RNA Isolation kit (Promega),(Section 2.1.8.2-6). Using the Bioanalyser RNA 6000 Nano Chip (Agilent), theintegrity of the RNA samples was assessed. 1µg of total RNA was reverse
transcribed (RT) using the Superscript™ First-Strand Synthesis System for
Reverse Transcription RT-PCR (Invitrogen). Three tissue replicates of 10ng/µL
cDNA per tissue were pooled and then used in triplicate for TaqMan® analysis.
IL-28R specific RNA levels were quantified using an ABI Prism 7900 sequence
detector (Applied Biosystems). RT-PCR was performed using mastermix (1x)and IL-28R assay on demand, Mm00558035_m1 (Applied Biosystems): 18S
ribosomal RNA used as the endogenous control in a multiplex reaction, RT
reactions were incubated for 30 minutes at 50oC followed by the activation of
Taq polymerase at 95oC for five minutes. After cooling for two minutes, 40
cycles of PCR were performed with cycling conditions of 15 seconds at 95 oC,
40 seconds at 50oC and 30 seconds at 72oC. A relative standard curve using
known standards of genomic human DNA was run in parallel and real-time
amplification signals were analysed using SDS software (version 1.71 Applied
Biosystems).
2.3.2 Gene Logic human tissue microarray screen
The BioExpress Human Atlas Suite (Gene Logic Inc), comprising of 2695
normal human samples belonging to 101 tissue types profiled 114 using human
U133A & B chips (Affymetrix)115,114,116 was used to look at gene expression of
IL-28R, IL-10R and IFNAR1.
2.3.3 Human inflammatory cell microarray screen
A GSK proprietary panel of mRNA from human primary cells was used toinvestigate IL-28R expression using microarray technology, developed by GSK.
The panel included peripheral blood mononuclear cells (PBMCs), plasmacytoid
dendritic cells (pDC), myeloid dendritic cells (mDC), alveolar macrophages,
macrophages, mast cells, B cells, CD4+ T cells and CD8+ T cells, (unstimulated
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and stimulated). The Affymetrix human HG-U133-Plus 2 chips were used to
profile expression data on mRNA extracted from these cells, IL-28R (TIG45563)
data is shown from this screen.
2.3.4 Isolation & treatment of cells for human inflammatory cell microarray
screenpDC and mDCs (>95%), CD4+ T cells, CD8+ T cells and CD4+ CD25+
regulatory T cells were isolated from PBMCs (three donors); separated using
Accuspin Histopaque-1077 columns (Sigma-Aldrich) and purified using
magnetically labelled beads (Miltenyi Biotec). pDCs and mDCs weremagnetically labelled with BDCA-4 and BDCA-1 microbeads respectively.
Untouched CD4+ T cells were prepared by magnetic depletion of other cells
within PBMC using antibodies to CD8, CD11b, CD16, CD19, CD36, CD56. In asecond step naїve CD4+ T cells were isolated from CD4+ T cells by depletion of
CD45RO+ T cells (>90% CD4+ CD45RA+ T cells). Isolated CD8+ T cells are
depleted of CD8+CD56+cells. Non-CD8+ T cells are indirectly magneticallylabelled by using a cocktail of biotin-conjugated antibodies (CD4, CD15, CD16,
CD19, CD34, CD36, CD56, CD123, TCR γ/δ, and CD235a), and the CD8+ T
Cell MicroBead cocktail. Isolation of highly pure CD8+ T cells was achieved bydepletion of magnetically labelled cells. CD4+CD25+ regulatory T cells wereisolated by indirectly magnetically labelling non-CD4+ cells (by using a cocktail
of biotin-conjugated antibodies against CD8, CD14, CD16, CD19, CD36, CD56,
CD123, TCR γ/δ, and CD235a (glycophorin A)). In a second step CD4+CD25+
regulatory T cells are directly labelled with CD25 MicroBeads and isolated bypositive selection from CD4+ T cells. Primary tonsillar B cells from three donors(>98%) were isolated by negative selection, non-B cells were labelled (CD2,
CD14, CD16, CD36, CD43, CD235a). Macrophages derived from monocytes
were prepared from PBMCs (three donors), separated using Accuspin
Histopaque-1077 columns and purified using positive selection CD14 beads.
Cells were resuspended in RPMI, 10% foetal calf serum, penicillin/streptomycin+L-glutamine and 100ng/mL Macrophage colony-stimulating factor (M-CSF) andincubated for four days to differentiate into macrophages. Mast cells were
derived from cord blood mononuclear cells (AllCells), cells were cultured in
Iscove’s modified Dulbecco’s medium (Invitrogen), supplemented with 5% foetal
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Chapter 2bovine serum, 1% penicillin/streptomycin, human stem cell factor (100ng/mL),
human IL-6 (50ng/mL) and IL-10 (10ng/mL) for 14 weeks.
Cells were treated with a wide range of inflammatory stimuli. pDCs and mDCs
were untreated. B cells were unstimulated or stimulated with CD40 ligand or
anti B cell receptor (anti-IgM) co-stimulation assay at four time points; 0, 24, 48
and 72 hours. Macrophages were cultured with vehicle alone, TNF (10ng/mL),
LPS (10ng/mL), immune complex (IgG coated beads) and cytomix (TNF
(10ng/mL), LPS (10ng/mL) and IFNγ (10ng/mL)) for 2, 6 and 24 hours. T cells
treatments were CD4+ and CD8+ cells resting; 1, 6 and 24 hours post antiCD3/CD28. Mast cells were primed for 6 days with human IL-4 (10ng/mL) andhuman myeloma IgE, lambda (1µg/mL) / human myeloma IgE, kappa (1µg/mL),
cells were triggered for 1 hour with anti-IgE (1.5µg/mL), control with notriggering.
2.3.5 Human tissues and whole blood
Human tissue and whole blood samples were collected from anonymised
donors. Ethics committee approval was provided and all patients gave informed
consent.

2.4 Distribution of type III interferon receptor in a panel ofmouse and human tissues, protein expression analysis
2.4.1 Immunohistochemistry overview
Immunohistochemistry (IHC) is a powerful investigative tool used to detectpresence and location of antigens (e.g. proteins) in cells of a tissue (histo)
section using antibodies specific for the antigen of choice. Antigen : antibody
interactionisvisualisedusing chromogenic detection;

where

enzymeconjugated antibody cleaves substrate resulting in coloured product at locationof target protein, or fluorescent detection using fluorophore conjugation to
specific

antibody.

In

optimising

IHC

protocols,

severalstagesneedconsideration and optimisation; these include antigen retrieval, blocking,primary antibody choice and incubation temperature and time, direct labelling or
indirect labelling, choice of secondary antibody and detection method enzyme,
substrate. Dual staining where multiple primary antibodies are used needs
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further consideration, care needs to be taken to ensure compatibility of methods
so both primary antibodies can be visualised.

Figure 2.10: Avidin-Biotin Complex (ABC) method
Diagram representation of immunohistochemistry using ABC method - adapted from
Dako IHC Staining methods Fifth Edition.

2.4.2 Immunohistochemical staining - IL-28R single stain in mouse andhuman
IL-28R protein expression in a selected panel of mouse and human tissues wasdetermined by immunohistochemistry. Optimal staining parameters for IL-28R
were initially worked up in mouse spleen using two IL-28R antibodies(Capralogics and Abcam). Frozen tissues were evaluated first and then adapted
for use in paraffin fixed tissues (formalin fixed for human). Experiments were
designed to determine the optimal dilutions that yielded specific positive
immunohistochemical staining with minimal non-specific background staining.
The following conditions were optimised: dilution range of 4µg/mL to 0.4µg/mL,+/- antigen retrieval, +/- additional avidin/biotin blocking steps, +/- copper
sulphate to enhance staining. Preliminary experiments to optimise rat IL-28R
antibody (Capralogics) in mouse spleen showed non-specific staining so only
IL-28R antibody (Abcam) was evaluated further. Immunohistochemistry method
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was developed using IL-28R goat anti-mouse polyclonal antibody (Abcam)(amino acid residues corresponding to 44-72 of N-terminus of mouse CRF-2-12(IL-28R) protein: LPGLGSPPNVT YFVTYQSYIK TGWRPVEH. Tissue sections
were de-waxed in xylene (Sigma-Aldrich) for 5 minutes and rehydrated inindustrial methylated sprit (IMS) (Sigma-Aldrich) to distilled water, 2 x 5
minutes. Antigen retrieval was carried out using a low pH buffer; slides weremicrowaved (Antigen retrieval programme, Milestone Mega TT microwave(Analytix)) in

1500mL of

dilutedantigenunmasking solution(VectorLaboratories). Slides were washed in water and mounted into sequenza
cassettes and slide racks (Thermo Shandon), then rinsed in TBS* buffer for 5
minutes. Peroxidases were blocked with peroxidase blocking solution (Dako) toblock endogenous peroxidises for 10 minutes. Non-specific binding of protein
was blocked using normal rabbit serum (Dako) (diluted 1:5 TBS) for 10 minutes,
followed by a rinse in TBS for 5 minutes and then avidin and biotin blocks(Vector) (4 drops per mL of TBS) for 15 minutes with a TBS wash in between.
Slides were incubated with IL-28R antibody at 0.8µg/mL diluted in TBS for 1
hour at room temperature followed by a 5 minute TBS wash. Slides wereincubated for 30 minutes with biotinylated rabbit anti-goat secondary antibody(Dako) at 13µg/mL TBS and then washed with TBS for 5 minutes. Slides weredeveloped using streptavidin horseradish peroxidise (HRP) and 3, 3‐
diaminobenzidine tetrahydrochloride (DAB) (Dako). Staining was enhanced
using 4% Copper Sulphate (Sigma-Aldrich) (diluted in distilled water) for 5
minutes, washed in TBS for 5 minutes and then counterstained in Mayers
haematoxylin (Sigma-Aldrich) for 5 minutes. Slides were ‘blued’ in running tap
water and taken through IMS and xylene washed before being cover slippedusing Entellen® mounting medium (Merck Sharpe and Dohme). A negative
control goat IgG and a negative control (no antibody) for assessing thebiological system were performed for every tissue.
* TBS Tris Buffered Solution 50mM Tris, 0.15M NaCl, pH 7.4. (Dako).
2.4.3 Immunohistochemical staining- IL-28R dual stain in mouse
IL-28R dual staining in mouse tissues was additionally performed with mouseand rat monoclonal antibodies for macrophage identification; 1) Mac387(ab22506 Abcam) which recognises the L1 or Calprotectin molecule expressed
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by granulocytes, monocytes and by tissue macrophages and 2) F4/80 (ab6640
Abcam) which is expressed on a wide range of mature tissue macrophages
including Kupffer cells, Langerhans and macrophages located in cords andmarginal zone of the spleen. Macrophages are white blood cells derived frommonocytes. Macrophages have a phagocytic role, secrete cytokines and are
involved in antigen processing and presentation to other cells. OX-62a dendritic
cell antibody (ab36444 Abcam) and CD79a b cell marker antibody (Dako 7050)
were also used during the optimisation of dual staining protocol but not carriedthrough as the methods for antigen retrieval for OX-62 and IL-28R antibodies
were not compatible. All antibodies above were optimised as a single assay andthen evaluated for compatibility as a dual assay with IL-28R.
IL-28R dual staining in mouse tissues was performed with 5µg/mL Mac387(Abcam) and 10μg/mL F4/80 (Abcam), mouse and rat monoclonal antibodies for
macrophage identification.
Tissue sections were de-waxed in xylene for 5 minutes and rehydrated inindustrial methylated spirit (IMS) to distilled water, 2 x 5 minutes. Antigen
retrieval was carried out using a low pH buffer; slides were microwaved(Antigen retrieval programme, Milestone Mega TT microwave (Analytix,)) in
1500mL of diluted (1:10 TBS) antigen unmasking solution (Vector). Slides were
washed in water and mounted into sequenza cassettes and slide racks (Thermo
Shandon), then rinsed in TBS buffer for 5 minutes. Peroxidases were blockedwith peroxidase blocking solution (Dako) to block endogenous peroxidises for
10 minutes. Non-specific binding of protein was blocked using normal rabbit
serum (Dako) (diluted 1:5 TBS) for 10 minutes, followed by a rinse in TBS for 5
minutes and then avidin and biotin blocks (Vector) (4 drops per mL of TBS) for
15 minutes with a TBS wash in between. Slides were incubated with IL-28R
antibody at 0.8µg/mL diluted in TBS for 1 hour at room temperature followed by
a 5 minute TBS wash. Slides were incubated for 30 minutes with biotinylated
rabbit anti-goat secondary antibody (Dako) at 13µg/mL TBS and then washedwith TBS for 5 minutes. Slides were developed using streptavidin horseradish
peroxidase (HRP) and 3, 3‐diaminobenzidine tetrahydrochloride (DAB) (Dako).
Staining was enhanced using 4% Copper Sulphate (Sigma-Aldrich) (diluted in
distilled water) for 5 minutes.
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Sections were incubated for 1 hour with the primary antibody MAC387 (5µg/µL
Mouse tissue 1µg/µL Human tissue) or F4/80 10µg/mL at room temperature.
Slides were incubated for 30 minutes with biotinylated rabbit anti-rat secondary
antibody (Dako) at 13µg/mL. The sections were then developed using either
VECTASTAIN® ABC-Alkaline Phosphatase (AP) reagent and Vector Red(Vector Laboratories) for MAC387 or HRP followed by VECTASTAIN ® ABCVery Intense Purple® (VIP) (Vector Laboratories) F4/80, and counter-stainedwith either haematoxylin (Sigma-Aldrich) or methyl green (Vector Laboratories).
Slides were taken through IMS and xylene washed before being cover slippedusing mount with glycergel mounting medium (Dako).

A matched isotype

control goat IgG for IL-28R comparison and rat IgG2b for MAC387/F4/80
comparison and a negative control (no antibody) for assessing the biologicalsystem were performed for every tissue.
2.4.4 Toluidine blue histochemical stain in mouse
To identify mast cells toluidine blue was used on a section of mouse uterus andcompared to serial sections stained with IL-28R antibody and a goat IgG isotype
matched control. Mast cells are connective tissue cells with cytoplasm filled with
granules comprising predominantly of histamine and heparin. Tissues
containing glycosaminoglycans (GAGs) e.g. heparin GAGs, can be stained withbasic (cationic) dye, toludine blue. This results in mast cells displaying apurple/violet ‘metachromatic’ colour and blue background staining. Toluidine
blue dye structure is shown below.

Figure 2.11: Structure of toluidine blue
5µm paraffin sections were dewaxed using xylene and rehydrated in IMS andthen distilled water. A toluidine blue working solution was made fresh (1gtoluidine blue and 100ml 70% alcohol, mixed 1:10 with a 1% sodium chloride
solution (0.5g sodium chloride and 50mL distilled water pH adjusted to 2-2.5
using glacial acetic acid) (all reagents Sigma-Aldrich). Sections were stained in
toluidine blue working solution for 3 minutes. Washed 3 times in distilled water
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and then dehydrated quickly in 95% ethanol and then 100% ethanol. The
sections were then cleared in xylene and cover slipped using Entellen®
mounting medium (Merck, Sharp and Dohme).
2.4.5 Flow Cytometric Analysis for tissue IL-28R determination
Mouse tissues: spleen, liver, heart, brain, kidney were homogenised using
Covaris focused acoustic system (Kbioscience). IL-28R antibody (Abcam) was
biotinylated with an ImmunoProbe Biotinylation kit (Sigma-Aldrich) according to
manufacturer’s instructions:
http://www.sigmaaldrich.com/etc/medialib/docs/Sigma/Bulletin/bk101bul.Par.00
01.File.tmp/bk101bul.pdf
Biotinylated IL-28R was then added to streptavadin phycoerythrin conjugate(R&D systems) and then incubated with tissue homogenate (~5 x 106/mL) for 15
minutes at room temperature. Goat IgG antibody was used as a negative
control. Cell pellets were suspended in CellWash (Becton Dickinson),centrifuged at 2100rpm for 3 minutes, supernatant decanted and this process
was repeated until visibly clear of red blood cells. Labelled cells were analysed
on a FACSCalibur flow cytometer (Becton Dickinson). A homogeneous
population of cells was gated and analysed using FlowJo Version 4.5.4 software(Tree Star).

2.5 Bone marrow assays
2.5.1 Murine bone marrow in vitro assay
This work was carried out in collaboration with David Brott, AstraZeneca, US allcell work was completed at AstraZeneca, US. Methods were adapted fromthose described by Brott & Pognan (2009)117, briefly:
Cell lines & Cultures: M1 cell line (ATCC TIB-192) derived from Mus muscululs
spontaneous myeloid leukemia with the cell type being myeloblast was used toevaluate myelotoxicity potential. M1 cells were maintained by splitting cultures
twice a week to 1-2 x 105 cells/mL in RPMI-1640 (Sigma Aldrich) and 10%
foetal bovine serum (Sigma Aldrich).
The HCD57 epo-dependent erythroleukemia cell line was kindly provided by Dr.
Spiveck at Johns Hopkins University. HCD57 cells were maintained by splitting
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cultures twice a week to 2-5 x 105 cells/mL in Iscove’s Modified Dulbecco’s
Medium containing 30% foetal bovine serum, L-glutamine (Sigma Aldrich),
10pg/mL mouse recombinant erythropoietin (R&D Systems) and 20µM betamercaptoethanol (Qiagen).
Assay: M1 and HCD57 cells were seeded at 5,000 cell per well in 50µL
media. Compounds were dissolved and diluted in appropriate media with 50µL
added to the appropriate wells. Mouse IFNα (R&D systems (PBL)) and mouse
IL-28A and IL-28B (R&D systems). IFNα, IL-28A and IL-28B were run in
triplicate and over duplicate plates, serial dilutions were prepared 0.002, 0.004,
0.008, 0.16, 0.031, 0.063, 0.125, 0.25, 0.5, 1 and 2µM. Assays were cultured at
37oC and 5% CO2 for approximately 72 hours. After adding 100µL of CellTiter
Glo (Promega) to each well, relative luminescence was determined and IC 50
calculated.
2.5.2 Human bone marrow
2.5.2.1 Gene expression
CD34+ hematopoietic cell samples were obtained from five human umbilicalcords (purity >60%) and three bone marrow donors (Lonza, purity >95%) CD3+

T-cells,

CD19+

B-cells,

CD11c+

DCs

and

CD14+

monocytes/macrophage cells were purified from peripheral blood from four
normal donors using magnetic beads protocols for separation (Miltenyi Biotec,
purity >80%). Cells were analysed for IFNAR1 (Hs01066118_m1 FAM labelled
assay on demand (Applied biosystems)) and IL-28R (Hs00417120_m1 FAM
labelled assay on demand (Applied biosystems)), IL-10RB (Hs00175123_m1
FAM labelled assay on demand (Applied biosystems)) gene expression using
TaqMan® using b-actin house keeper gene (Hs00417120_m1 VIC labelled
assay on demand (Applied biosystems)).
2.5.2.2 Human bone marrow CD34+ cell assays
A colony forming cell (CFC) assay was used to determine the ability ofhematopoietic progenitor bone marrow CD34+ cells to proliferate anddifferentiate into erythroid or myeloid colonies after two weeks in amethylcellulose-based semi-solid media (StemCell Technologies) in response
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to cytokine stimulation. 0, 0.03125, 0.0625, 0.125µM of IFNα (Sigma-Aldrich),
IL-28A (R&D), IL-28B (R&D) and IL-29 (R&D) were added in duplicate. Colony
forming unit burst forming unit-erythroid (CFU-BFU), CFU-granulocyte,
macrophage (CFU-GM) and CFU-granulocyte, erythrocyte, macrophage,megakaryocyte (GEMM) colonies formed were enumerated and characterised
according to their unique morphology.

For proliferation assays, 50,000 CD34+ cells (Lonza) were plated in 200 µL/wellofculture medium: DMEM,

Penicillin/streptomycin,

10%

L-Glutamine

Hyclone foetal bovine serum and(100units/mL,

100µg/mL

and2mM

respectively). Cells were stimulated with TPO (100ng/mL, Preprotech), IL-3
(60ng/mL, Preprotech), SCF (100ng/mL, Preprotech), Flt3 ligand (300ng/mL,
Preprotech) and incubated with serial dilutions of 0.03125, 0.0625, 0.125µM of
IFNα (Sigma-Aldrich), IL-28A (R&D), IL-28B (R&D) and IL-29 (R&D) in triplicate
for 72 hours. After three days of culture 40µL of Cell Titer 96 aqueous solution(Promega) was added to each well to measure the number of viable cells after
proliferation. After 2 hours of incubation at 37oC- the absorbance wasmeasured at 490nm on a 680 microplate reader (BioRad). Stimulated samples
exposed to IFN-α or IFNuntreated controls.
2.5.2.3 Human tissues and whole blood
Human tissue and whole blood samples were collected from anonymised
donors. Ethics committee approval was provided and all patients gave informed
consent. San Raffaele Telethon Institute for Gene Therapy Biologic, specimensfrom umbilical cord blood and peripheral blood of healthy donors were collected
for research purpose and used on informed consent in agreement with the rules
defined by approved protocols TIGET01 and TIGET PERIBLOOD.

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Chapter 3
3. Investigation of the antiviral activity of IL-28A

and IL-29 using antiviral andsensitive gene model assays

interferon

3.1 Introduction
At the time of this work being undertaken IL-29 and IL-28A had been shown tohave antiviral properties in an EMCV model3 and sensitivity was shown withinterferon sensitive gene assays2,3, but other antiviral activity against a virus or
using a model/replicon had not been published.
The aim of this chapter was to evaluate the in vitro antiviral activity of IL-28A
and IL-29 across a range of viruses spanning a cross section of viruses from allseven classes classified using Baltimore classification118 compararing theirantiviral properties with each other and with IFNα primarily. IL-28B was nottested in these assays as at the time it was not commercially available and wasdeemed to be similar to IL-28A (96% amino acid identity).
This Chapter looked aty the antiviral activity of IL-28A and IL-29 in the viruses
below, class II and III were not covered:
I: dsDNA viruses: Papillomaviridae – Human Papillomarvirus HPV-16 andHPV31
II: ssDNA viruses (+)sense DNA (e.g. Parvoviruses)
III: dsRNA viruses (e.g. Reoviruses)
IV: (+)ssRNA viruses (+)sense RNA: Flaviviridae - Dengue and Hepatitis C,
Togaviridae –Semliki Forest virus)
V: (−)ssRNA viruses (−)sense RNA: Paramyxoviridae - Respiratory Syncyticalvirus.
VI: ssRNA-RT viruses (+)sense RNA: Retroviridae - Human Immunodeficiency
virus
VII: dsDNA-RT viruses: Hepadnaviridae - Hepatitis B

Effects of IL-28A and IL-29 were also investigated in IFN sensitive gene models
IFIT6-16 and ISG-56.
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IFNλs were tested in a wide range of viral cell assays and models in order toelicit interferon lambdas antiviral properties. IFNα was used as a comparison in
all assays with IFNα and IFNγ being additional comparisons in the; 1a and 1b
HCV replicon assays, HIV, dengue fever replicon assay, RSV assay and ISG
assays. Positive sense RNA virus HCV (flavivirus) using replicon models were
tested as a priority: as type I interferons have antiviral properties it was likelythat interferon lambdas may also have been shown to reduce levels of HCVmRNA in the HCV replicon system. Human liver cells HuH7 containing either
genotype 1a or 1b HCV replicons were tested in an ELISA assay, and later
experiments were performed using two genotype 1a and two genotype 1b
replicon luciferase clones in a common parent HuH7 cell (developed by Thomas
Zurcher, GSK). HCV is responsive to IFNα, IFNβ and IFNγ119 but at the time
this project was initiated (August 2004) there was no published work to show
the role of type III interferons in HCV.
Pegylated IFNα, in combination with ribavirin, is the current standard of care forthe treatment of patients chronically infected with HCV; it results in a sustained
virological response (defined as clearance of circulating HCV RNA at 6 months
post-treatment) in ~50% of patients10. However, combination therapy remains
less effective against infections caused by HCV genotype 1 which constitute~75% of all HCV infections in the developed world 10. New interventions are
therefore required to address this unmet medical need and the discovery ofinterferon lambdas presents the opportunity to explore their roles in antiviraltherapy.
Dengue was tested as a virus in the same family as HCV, flavivirus, this assay,
like the hepatitis C assay, used a replicon model. A further range of viruses
were investigated: DNA virus HBV (Hepadnaviridae), negative sense RNA virus
Respiratory Synctial Virus (RSV) and the RNA transcribing virus Human
Immunodeficiency Virus (HIV) (Retroviridae) to give a broad spectrum ofdifferent families of viruses. Other viruses: Influenza and Human papillomavirus
HPV-16, HPV-31, Semliki Forest virus were considered and even work
instigated but are not reported here.
Additional work in this chapter: IFNα and IL-28A, IL-29 were evaluated together
in a HCV 1a replicon assay over a time course of 2, 4 ,6, 8, 16 and 24 hours, inPage 77 of 183

Chapter 3order to determine any synergistic effects of the type I interferons with type III
interferons.
Effects of IL-28A and IL-29 were also investigated in IFN sensitive gene models
IFIT6-16 and ISG-56 to see if interferon lambdas had a role in regulation ofinterferon sensitive genes. ISG56 is the most highly induced IFN sensitive gene(30-100 fold induction), and is stimulated by both IFNα and IFNβ, but not IFNγ,IFIT6-16 is also induced by type I IFNs but the role of IFNλ modulation was
unknown.
3.1.1 Hepatitis C comparison of antiviral activity of IFNα, IFNβ, IFNγ andinterferon lambdas IL-28A and IL-29 in two replicon assays
HuH7 cells containing either genotype 1a or 1b HCV replicons were stainedwith 5% carbol fuchsin to visually assess cytotoxicity. Cytotoxicity based on cell
shape was not seen with any of the interferons tested at any concentration.
The half maximal inhibitory concentration (IC50) values for all interferons were
determined as the concentration of each treatment which showed 50% inhibitionof the NS5A ELISA signal in HCV 1a and 1b replicon cell lines compared withuntreated cells. IC50 values were determined for positive control, IFNα, IFNβ,
IFNγ, IL-28A and IL-29. % inhibition values were determined according to thefollowing formula:% Inhibition = 100 - [100x (mean concentration – mean cell control) /(mean cell control – mean no primary antibody control)]IC50 values for replicon assays of genotype 1b were determined; IFNα 18
IU/mL, IFNβ 50 IU/mL, IFNγ 54 IU/mL, IL-28A 160ng/mL and IL-29 11ng/mL.
IC50 values for genotype 1a replicon assays were as follows; IFNα 86 IU/mL,
IFNβ 89 IU/mL, IFNγ 148 IU/mL, IL-28A 201ng/mL and IL-29 19ng/mL.
For comparison purposes IU/mL values for IFNα, IFNβ and IFNγ wereconverted to pg/mL using the following formula:[1 x 109 ÷ (Lot specific activity)] x (Lot Concentration (IU/mL) = pg/mL)
IC50 values for IFNα, IFNβ, IFNγ, IL-28A and IL-29 all in ng/mL units are shown
below (Table 3.1) and determined from IC50 plots (Figure 3.1).

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Table 3.1 IC50 values for IL-29, IL-28A, IFNα, IFNβ and IFNγ
IL-29

IL-28A

IFNα

IFNβ

IFNγ

Mean (SD)

Mean (SD)

Mean (SD)

Mean (SD)

Mean (SD)1a

20 (1.6)

202 (20.1)

0.4 (0.03)

7.3 (0.8)

7.2 (0.6)

1b

11 (2.0)161 (9.4)

0.09 (0.01)

5 (0.4)6 (0.7)

Table 3.1 shows IC50 values in ng/mL determined in two HCV replicon cell lines 1a and1b for: IL-29, IL-28A, IFNα, IFNβ and IFNγ.

The results show that all IFNs had some potency against the HCV 1a and 1b
replicons in vitro. IL-29 was shown to be ~10 x more potent than IL-28A against
both replicons, IL-29 was shown to be in the same level of magnitude withpotency in both cell lines comparable to IFNβ and IFNγ. IFNα was shown toapproximately 100 times more potent than IL-29 and ~1000 times more potent
than IL-28A.

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Chapter 3

80

100

100

60

80

80

% Inhibition

60

80

60
60

60

40

40

40

40

20

0

R esponse20

R espo nse

Re sponse

Resp onse

Re sponse

20

40
20

20

0

0

0

0
1

1

10

ng/ml

10

2

3

1

10

10

1

10

2

3

-2

10

10

10

ng/ml

ng/ml

1A IL-29

1A IL-28a

-1

-1

10

1

1

1

2

10

10

ng /ml101

ng /ml101

Parameter

Value

S td. Error

Parameter

Value

Std. Error

Parameter

Value

Std. Error

Paramet er

Value

St d. Error

Paramet er

Value

St d. Error

Y Range
IC 50
Slope f actor
Background72.3747
19.6611-0.8052-2.26968.31504.22210.14296.1411

Y Range
IC 50
Slope fact or
Background73.6689202.5431-0.70638.485426.0123160.6297
0.32465.3282

Y Range
IC 50
Slope f actor
Background115.7064
0.4059-0.6176-8.9939

18.21250.11250.1312
6.9869Y Range
IC 50
Slope fact or
Background84.8527
7.3808-1.4704
2.5626

6. 2139
1. 2735
0. 3382
4. 2614

Y Range
IC 50
Slope fact or
Background90.0274
7.2444-0.8950-2.9928

9. 4522
1. 3305
0. 1647
4. 0231

100

100

100

% Inhibition

80

80

Data set #1

Data set #1

Data set #1

102

1A IFNg

1A IFNb

1A IFNa

10 -1

3

80

80

60

60

40

40

80

60

60

60

40

0

20
1

1

10

2

ng/ml

10

1B IL-29

20

10

1

2

ng/ml

3

10

10

10-2

10-1

ng/ml

1

20

0

10 -1

1

ng /ml101

1B IFNb

1B IFNa

1B IL-28a

20

0

0

3

10

R espo nse

20

Respo nse

Resp onse

Resp onse

Re sponse

40

40

102

10-1

1

ng /ml101

102

1B IFNg

Parameter

Value

Std. Error

Parameter

Value

S td. Error

Paramet er

V alueStd. E rror

Paramet er

Value

St d. Error

Paramet er

Value

St d. Error

YRangeIC 50
Slope factor
Background68.8590
10.9084-1.1275
22.7300

4.81651.50420.13464.1603

YRangeIC 50
Slope factor
Background77.6823161.4851-1.8299-1.36769.510729.4477
0.58304.0982

Y Range
IC 50
Slope fact or
Background118. 5865
0. 0867-0. 5816-18. 3320

58.77510.08780.374442.2925

Y Range
IC 50
Slope fact or
Background77.33134.8282-0.9544
8.122710.9885
1.18030.25175.8714

Y Range
IC 50
Slope fact or
Background88.0165
6.0006-0.9650-4.3322

12.21311.24390.2422
6.8914

Figure 3.1: IC50 plots for IFNα, IFNβ, IFNγ, IL-28A and IL-29
Figure 3.1 shows IC50 plots for IFNα, IFNβ, IFNγ, IL-28A and IL-29 in HCV replicon cell assays 1a and 1b, values in ng/mL (Graffit V5).

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3.1.2 Determination of IC50 values for luciferase HCV replicon clones
Four luciferase HCV replicon clones 1a1_19, 1a3II and 1b 2.2, 1b2.5 were
tested for their antiviral sensitivity to IL-28A and IL-29 compared to IFNα. Thesecells were all developed in the same parental HuH7 cell line. Log dose plots areshown (Figure 3.2) for clones 1a3II and 1b2.5 showing good curve fits for IL-29
and IFNα and due to solubility issues the best fit for IL-28A is shown (Figure
3.2).

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A

HCV replicon 1a 3II
20000

IL-28A (ng/ml)
IL-29 (ng/ml)
IFN alpha (IU/ml)

Luciferase

15000
10000
5000
0
-1

0

1

2

3

4

Log doseB

HCV replicon 1b 2.5
10000

IL-28A (ng/ml)
IL-29 (ng/ml)
IFN alpha (IU/ml)

Luciferase

8000
6000
4000
2000
0
-1

0

1

2

3

4

Log dose

Figure 3.2: IC50 plots for HCV replicon assays 1a3II and 1b2.5
Figure 3.2: IC50 plots are shown for luciferase assays: A 1a3II and B 1b2.5 for IL-28A,
IL-29 ng/mL and IFNα IU/mL (PRISM).

All four HCV replicon clone assays 1a1_19, 1a3II and 1b 2.2, 1b2.5 wereassessed and the IC50 values in ng/mL with IL-28A, IL-29 and IFNα shown(Table 3.2).
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Table 3.2: IC50 values for IL-28A, IL-29 and IFNα in HCV replicon clones
IL-28A IC50 (ng/mL)

IL-29 IC50 (ng/mL)

IFNα IC50 (ng/mL)

Mean (SD)

Mean (SD)

Mean (SD)1a 1_1946.6 (2.9)

0.7 (0.08)

0.005 (0.0002)

1a3II

21.8 (5.6)

0.55 (0.03)

0.003 (0.0001)

1b 2.2118 (16.5)

2.7 (0.17)

0.004 (0.0002)

1b2.5

227 (19.9)

4.6 (0.31)

0.01 (0.003)

Clone

Mean IC50 values for IL-28A, IL-29 and IFNα are shown for HCV replicon clones
1a1_19, 1a3II and 1b 2.2, 1b2.5 in ng/mL.

Replicon clone 1a3II was most sensitive to all tested interferons having thelowest IC50 value for IL-28A, IL-29 and IFNα. IC50 values for replicon clone 1a3II
were used for later gene expression work (Section 4.2).
3.1.3 IL-29 and IFNα synergy
IFNα and IL-28A, IL-29 were evaluated together in a HCV 1b replicon assay
over a time course of 2, 4 ,6, 8 16 and 24 hours, in order to determine any
synergistic effects of the type I interferons with type III interferons. Serial
dilutions of IL-28A 200ng/mL to 4ng/mL and IL-29 1000ng/mL to 2 ng/mL were
tested with and without 0.09ng/mL of IFNα (IC50 concentration as determined inexperiments performed (Section 2.1.1). To confirm baseline expression of IFNα
at 0.09ng/ml this was also run separately. Results showed an additive effectonly, not a synergistic effect. This was seen across all doses with IL-28A and IL29 at all tested time points.
3.1.4 IFN sensitive gene models 6-16 and ISG56
To investigate type III interferon modulation of interferon sensitive genes (ISGs),
two ISG assays were used; interferon sensitive gene 56 (ISG56) and interferon
inducible gene 6-16 (G1P3).

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Half maximal effective concentration (EC50), representing the concentration of acompound where 50% of its maximal effect is observed, were determined forboth ISG models.
Table 3.3: EC50 values for IFNs in ISG models
IFN

ISG56 EC50

6-16 EC50

Mean (SD)

Mean (SD)

IL-28A439ng/mL (34.7)>2.0µg/mL

IL-29

115ng/mL (18.4)>1.0µg/mL

IFNα

50 IU/mL (3.2)

48 IU/mL (4.6)(0.16ng/mL)(0.15ng/mL)

IFNβ

121 IU/mL (14.3)

120 IU/mL (0.89)

IFNγ

350 IU/mL (22.0)

500 IU/mL (35.7)

In the Interferon sensitive assays, sensitivity was shown in the ISG56 assay to
IL-28A and IL-29 but not in the 6-16 interferon sensitive gene model. Theseexperiments suggested different modes of action for IL-28A and IL-29
compared with IFNα, however Affymetrix gene expression data suggested that
there was expression of the IFIT6-16, alias G1P3 with IFNα, IL-28A and IL-29
treatment at 8, 16 and 24 hour time points.
Data below is taken from replicon data (Section 4.5.2, Table 4.8).
Table 3.4: Subsection of Table 4.7 to highlight G1P3 expression
Symbol

G1P3

IFNα

IL-29

IL-28A

8h

16h

24h

8h

16h

24h

8h

16h

24h

3.2

82.1

42.1

6.7

100

96.5

4.5

100

43

This suggests that whilst the 6-16 cell model is not sensitive to type III IFNs,
there is gene expression of 6-16 shown with Affymetrix and TaqMan®
technology.

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3.1.5 Hepatitis B (HBV)
Antiviral effects of IL-28A and IL-29 compared with IFNα were investigated inhuman hepatocellular carcinoma HepG2.2.15 cell line stably transfected with
HBV subtype ayr. Concentrations of IFNs tested were: IFNα: 100, 1,000 ng/mL,
IL-28A: 200, 2000 ng/mL and IL-29: 100, 1000 ng/mL, compared to untreated.
Preliminary results shown (Figure 3.3) indicated that both IL-29 and IL-28A
have antiviral properties in the HepG2 (2.2.15) cells stably transfected with HBV
subtype ayr. These results show that IFNα has a greater antiviral effect of IL-29
on HBV compared to IL-28A. Initial data shows IL-29 having a greater antiviraleffect on HBV than IL-28A. A publication by Robek51 superseded further workon HBV.

80000
70000

HBV copy
number

60000
50000
40000
30000
20000
10000
0

Concentration
Figure 3.3: Antiviral effects of IL-28A and IL-29 with HBV
Antiviral effects of IL-28A and IL-29 compared with IFNα were investigated in humanhepatocellular carcinoma HepG2.2.15 cell line stably transfected with HBV subtype ayr.
IL-28A and IL-29 tested at low and high doses (200, 2000 and 100, 1000 ng/ml
respectively) and compared with IFNα low and high dose dose (100, 1000 IU/ml). Copy
number was determined from the mean of the 4 replicate samples using the following
equation: 10-1(Ct-40)/3.5 where 10-1 is the inverse log, Ct is cycle threshold, 40 is
number of total cycles and 3.5 is PCR efficiency.

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3.1.6 Human immunodeficiency virus (HIV)IFNα, IFNβ, IFNγ have been shown to have antiviral properties against HIV120,
and are used as positive controls and as comparisons to investigate the antiviraleffects of IL-28A and IL-29 with HIV.
Data (Figure 3.4) shows: a strong antiviral effect of IFNα and IFNβ on HIV, IFNγ
has a weak antiviral effect and IL-28A and IL-29 have no antiviral effects evenat very high concentrations. IC50 values were determined as: IFNα 2.8 IU/mL,
IFNβ 43.2 IU/mL and IFNγ 140 IU/mL. There were no effects even at a highdose of 7.68mg/mL for IL-28A and 1mg/mL for IL-29; interestingly no toxicity
was observed at these doses. In this cell system, type III lambdas do not seemto have an antiviral effect even at very high doses.

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Chapter 3

HIV HXB2
IFN alpha
IFN beta
IFN gamma
IL-28A
IL-29% viability

100

50

0
0.1

1

10

100

1000 10000 100000

Drug (nM)
Figure 3.4: Antiviral effects of IL-28A and IL-29 against HIV virus HXB2
The antiviral effects of IFNα, IFNβ, IFNγ, IL-28A and IL-29 in and MT4 cell line infected with HIV virus HXB2. The graph shows % viability of MT4
cells against log dose concentration of IFNα, IFNβ, IFNγ, IL-28A and IL-29. (PRISM).

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3.1.7 Dengue Fever Virus assay
K562 myeloid/erythroid (human chronic myeloid leukaemia) cell line stably
expressing the dengue virus replicon ΔCprME-PAC2A was used to test theantiviral properties of type III interferons, compared to IFNα, IFNβ and IFNγ.
100, 1,000 IU/mL of IFNα, IFNβ and IFNγ, 200, 2000ng/mL of IL-28A and 100,
1000ng/mL of IL-29 were tested against dengue virus replicon with an
incubation of 24 hours. Results show for all IFNs at all concentrations that
dengue virus RNA levels do not significantly vary from that of untreated cells,
results shown (Figure 3.5).

Figure 3.5: Dengue virus replicon
Dengue RNA levels were measured by quantitative PCR and normalised to GAPDHmRNA levels; the data demonstrated no significant difference between untreatedsample (negative control) and IFNα, IFNβ, IFNγ, IL-28A and IL-29 treatment, indicatingthat Interferon lambdas IL-29 and IL-28A do not have antiviral effects in a dengue
replicon system.

3.1.8 Respiratory Syncytial Virus (RSV)
Transformed B cells infected with RSV WSX1 viral particles were treated with
IFNα, IFNβ and IFNγ at 1000 IU/mL, IL-28A at 2µg/mL, IL-29 at 1µg/mL anduntreated to assess the effects of antiviral treatment. Cells were incubated at
two time points: 48 hours and 96 hours.
No test samples differed significantly from control, suggesting that IFNs have noeffect on the RSV WSX1 model. The negative results above may also be

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explained by RSV RNA being very sensitive to manipulation and the cell model
being quite difficult to maintain stable RSV levels.
3.1.9 Discussion
It has been shown that type I IFNs (IFNα, IFNβ, IFNЄ, IFNκ and IFNω inhumans) are modulators of antiviral defence by many groups121,122,123, Type II
IFN, IFNγ is also an important mediator of antiviral defence but not as its
primary function which is stimulation of the immune responses 124,125. The role oftype III interferons, IL-28A, IL-28B and IL-29 in antiviral disease is still not fully
known.
HCV- in vitro assays show that IL-28A and IL-29 have a direct antiviral effectagainst HCV in the HCV genotype 1a and 1b replicon systems (ELISA).
Despite having similar molecular weights (IFNα 19.5kDa, IL-29 21.9kDa and IL28A 20.8kDa) IFNα was shown to be ~100 fold more potent against HCV
replicons 1a and 1b than IL-29 and 1000 fold more potent than IL-28A,
suggesting that IFNα is more potent against HCV than type III IFNs. IFNβ andIFNγ showed similar potency to IL-29 in both 1a and 1b replicon assays and IL29 was shown to be ~10 times more potent in both assays than IL-28A.
Replicon 1b assay was more sensitive to all IFNs tested; IFNα, IFNβ, IFNγ, IL29 and IL-28A.
With an alternative luciferase replicon assay model for HCV 1a replicon clones,
1a 1_19, 1a3II and 1b replicon clones 1b 2.2 and 1b2.5, similar results wereshown with comparison of IFNα to IL-28A and IL-29 as with the HCV genotype
1a and 1b replicon systems (ELISA). IFNα was shown to be ~100 fold morepotent than IL-29 (1000 fold in 1b 2.2) and over 1000 fold more potent than IL28A. IFNα showed similar IC50 values in all the four replicon assays but IL-28A
and IL-29 were ~10 times more potent against the 1a replicons than the 1b
replicons which may show a difference in mode of antiviral action against the
HCV sequence. Replicon clone 1a3II was shown to be most sensitive to IFNα,IL-28A and IL-29 and chosen for further investigation of pathway analysis (genechip experiments). Robek51 demonstrated that IL-29 and IL-28A inhibits
replication of subgenomic and full-length HCV replicons in HuH7 cells and thiswas also shown later by Doyle57 and Marcello61.

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Due to IL-28A and IL-29 using a different receptor (IL-28R rather than IFNR1),
IL-28A and IL-29 were tested in the HCV 1b replicon assay to determine any
synergistic effects of the type I and type III interferons together. Results
described only showed an additive effect not a synergistic effect, this wasobserved at all time points 2, 4, 6, 8, 16 and 24 hours. An additive effect though
could show that IL-29 when used with IFNα could be good as a dual therapy as
opposed to IFNα alone as the results demonstrate greater potency against HCVwith both IFNa and IL-29 together. These results were confirmed by Marcello et
al in 2006, his group also saw an additive effect not a synergistic effect of IL2961.
Two interferon sensitive gene assays ISG56 and 6-16 were tested with IL-29
and IL-28A and compared to IFNα, IFNβ and IFNγ. In the ISG56 assay (Human
Embryonic Kidney 293 cells (HEK cells)) IL-28A and IL-29 were shown to be~1000 times less potent for activation of the ISG promoter in this model thanIFNα and interestingly significantly less sensitive at modulation of ISG56 thanIFNβ and IFNγ. In the HCV replicon assays IL-29 showed similar antiviralprotective effects as IFNβ and IFNγ. IL-28A has been shown to have ~10 times
less antiviral effect in the replicon assays than IL-29 but in the ISG56 assay, IL29 and IL-28A showed EC50 values in the same magnitude. In the interferon
sensitive assays, sensitivity was shown in the ISG56 assay with IL-28A and IL29 but not in the 6-16 assay. It was initially thought the ISG experiments
described above suggest different modes of action for IL-28A and IL-29
compared with IFNα, but results later (Chapters 5 and 6) showed IL-28R had
limited receptor distribution, and difference seen in reporter activity might bedue to restricted receptor expression. Interferon lambdas have also been shownto induce expression of 2’5-OAS2 and MxA126 by other groups Kotenko et al and
Brand et al.
All cells described in Chapter 3 were tested by TaqMan® for presence of IL-28R
gene, Human T98G cells (glioblastoma multiforma tumor cells) (6-16 assay
cells) did not show signal for IL-28R.
Initial data in a human HepG2 cell line stably transfected with HBV subtype ayr
showed that both IL-29 and IL-28A had antiviral effects against HBV but
significantly lower in antiviral activity than IFNα. The antiviral effect of IL-28A
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compared to IL-29 was significantly lower. HBV data was consistent with datafrom Robek51, where IL-29 was shown to inhibit HBV replication in a murine
model (HBV-Met cells). However, a later study suggested that the antiviral
activity of type III IFNs against HBV may be limited in human cells; Kotenko et
al found limited antiviral properties with IL-29 in human hepatoma cells stablytransfected with HBV subtype adwR9127.
No antiviral effects were observed with IL-28A or IL-29 in HIV, RSV assays oragainst the dengue replicon system. The presence of IL-28 receptor gene
expression was confirmed by TaqMan® real-time PCR in these systems,
implying that the specific type III receptor could be present, so an obvious lackof receptor is unlikely to be the reason for the lack antiviral response in thesesystems. There was no cytotoxicity observed with the type III IFNs in the HIV
assays at concentrations of IL-28A and IL-29 up to 7.68mg/mL and 1mg/mL
respectively. This initially was of great interest as IL-28A and IL-29 not having
any antiviral activity against HIV in vitro could have indicated that the lambdas
were functionally different to IFNα. To date limited studies have described theeffects of IFN-λ on HIV-1 replication and disparate results were reported, theeffect of interferon lambdas remains controversial. Hou et al demonstrated
inhibition of HIV-1 replication in macrophages by IL-29 and IL-28A128, with Liu et
al showing that IL-29 inhibition of HIV in macrophages is via the JAK-STAT
pathway129. Another study showed pretreatment of uninfected PBMCs or CD4+
T-cell lines with IFN-λ improved the expression of HIV-1 receptor and coreceptors that increase viral binding and replication130 and in July 2012 Tian etal demonstrated IL-28A and IL-29 treatment induced an antiviral state incultured primary T-cells, suppressing HIV-1 integration whereas in vivo IL-29
showed limited in vivo repression of viral production in CD4+ T cells131.
It is possible to speculate that the IFN signal transduction pathway with type I, II
and III IFNs is blocked in the dengue virus replicon system. Jones et al showedthat IFNα in the same dengue replicon system had no antiviral effect and that
dengue virus specifically inhibits IFNα signalling by the down-regulation of
STAT2 expression53. Whilst HCV is very sensitive to the antiviral cascade
induced by IFNα, in contrast, the related viruses West Nile virus (WNV) andPage 91 of 183

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Japanese encephalitis virus are resistant to IFNα therapy. WNV has beenshown to block the IFN signal transduction pathway132.
Results from the RSV assay showed no differences between IFNα, IL-28A, IL29 compared with negative control, suggesting that IFNs have no effect on the
RSV WSX1 model. The negative results above may also be explained by RSV
RNA being very sensitive to manipulation and the cell model being quite difficult
to maintain stable RSV levels. There are also reports to show that RSV inhibits
IFNα signalling, IFNγ production and type III interferon expression 133.
The antiviral effects in other viral systems have been demonstrated for the
IFNλs both in vitro and in vivo: IL-28A and IL-29 in an in vivo poxvirus infection
model55, IL-29 reduced influenza A titre in vitro134, IL-28A and IL-29 in an in vitro
murine CMV system56, IL-29 had antiviral effects against herpes simplex virus(HSV-1) in vitro comparable to that of IFNα135, IFNλs have antiviral effects invivo and not in vitro with HSV-2136 highlighting the possibility that the majority ofIFNλs antiviral effects against HSV may involve immune modulation. Taken
together, these studies supported the value of studying IL-28A and IL-29 as apossible therapeutic approach to viral disease. Whilst there have been several
studies looking at the antiviral properties of IFNλs in RNA viruses there is a gap
in research on the effects of IFNλs with DNA viruses.

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Chapter 4
4. Transcriptome analysis in parent HuH7 cells

and HCV replicon cells treated with type I andtype III IFNs
4.1 Introduction
Type III interferons (IFNs) are a newly identified class of cytokines with antiviral
activity(1,2). It is not yet clear how the function of these cytokines differs from thetype I IFNs. This chapter therefore sets out to investigate how the pattern ofgene induction by type III IFNs (IL-28A and IL-29) differs from that of type I andwhether type III IFNs might have a superior therapeutic profile. IFNs protect
cells from viral infection, directly by inducing interferon sensitive genes (ISGs)
such as 2’, 5’-oligoadenylate synthetase 1 (2’, 5’-OAS) and myxovirus
resistance-A (MxA) and intracellular genes and, indirectly, by inducing major
histocompatibility complex (MHC) class I antigen expression on and activationof antigen-presenting cells, by stimulating dendritic cell maturation andactivating macrophages and natural killer cells.
IFNλs were initially shown to activate both STAT1 and STAT2 and thedownstream signalling pathways including interferon sensitive gene complex
ISGF3 and ISRE13 , similar to those activated by IFNα and IFNβ. However themechanisms of IFNλs still need to be fully elucidated.
The objectives of this chapter were to:1) identify which genes are regulated by type III IFNs
2) to see how this profile differs from type I IFNs and3) to see the effect of IFNs on human hepatoma cell line HuH7 HCV repliconcells compared with parental HuH7 cells.
By comparing the transcriptional levels of genes in tissues or cells from ‘control’and ‘test’ states, it is possible to gain insight into the mechanisms and pathways
underlying the comparative phenotypes observed. There are a multitude oftechniques available to researchers to undertake these types of transcriptional
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investigation, although they can be broadly defined as ‘open systems’ and‘closed systems’. Open transcriptional systems have the advantage of not
requiring any prior sequence knowledge of the genes under investigation,
examplesare:‘fragment‘subtractive/competitive

display’hybridisation’(FD)137,‘tag

techniques.

In

sequencing’
general,

the

and
main

disadvantage associated with open transcriptional systems is their relatively low
throughput, both in terms of numbers of gene modulations that can be positively
identified and the number of transcriptional comparisons that can be made.
Closed transcriptional systems include an equally diverse array of techniques,
although the shared attribute is the requirement for prior sequence knowledgeof the gene(s) under investigation. Closed systems include techniques that are
only amenable to investigating the transcriptional levels of single (e.g. Northernblots and the ribonuclease protection assay) or small subsets of genes (e.g.
real-time quantitative PCR (RT-QPCR)). At the other end of the spectrum, they
include those capable of simultaneously measuring the expression levels of
thousands of genes, i.e. Affymetrix GeneChips® microarrays, leading to thedevelopment of ‘transcriptomics’, broadly defined as the rapid and quantitative
comparison of large-scale mRNA expression profiles in biological systems.
Combined with the huge advances in genome sequencing and gene annotation
made in recent years, they have led to the advantages of ‘open’ transcriptional
systems becoming more or less obsolete. As genome sequencing of anincreasing number of model species is completed, it is becoming practicable touse microarrays to measure transcription at a virtually genome-wide scale. This
has enabled the generation of huge volumes of data, faster than ever before.
Data (Section 3.1.2) showed that the HCV replicon system would be a suitablemodel for transcriptomic analysis of the IL-28A and IL-29 as the replicon cellline showed sensitivity to IL-28A and IL-29. To determine gene activation
profiles and the signalling pathways of IL-28A and IL-29 transciptomic andpathway analysis were performed using Affymetrix GeneChips® analysis andpathway analysis.

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4.2 Determination of 10 x IC50 for most IFN sensitive repliconcell line
Results of the four replicon cell lines were compared and IC 50 values
determined (Section 3.1.2, Table 3.2),1a3II results highlighted below (Table 4.1)
Table 4.1: IC50 values in ng/mL of IL-28A, IL-29 and IFNα in HCV replicons
Clone

IL-28A IC50 (ng/mL)

IL-29 IC50 (ng/mL)

IFNα IC50 (ng/mL)

1a1_19

46.6

0.7

0.005

1a3II

21.8

0.55

0.003

1b2.2

118

2.7

0.004

1b2.5

227

4.6

0.01

HCV replicon clone 1a3II was most sensitive to interferons having the lowest
IC50 value with IL-28A, IL-29 and IFNα. 10 x the IC50 level was calculated as:
218ng/mL, 6ng/mL and 0.03ng/mL for IL-28A, IL-29 and IFNα respectively.
These 10 x IC50 values were used to treat parent HuH7 cells and HuH7 HCV
1a3II luciferase replicon cells for use in transcriptome analysis.

4.3 TaqMan® analysis
Real-time PCR was performed on the RNAs isolated from HuH7 cells and HuH7
HCV 1a3II luciferase replicon cells treated with 10 x IC50 values of IL-29, IL-28A
and IFNα at 4, 8, 16 and 24 hour time points The data was analysed to assess
the suitability of the time points and concentrations of the IFNs in the assay
before running the samples of full genome Affymetrix chips.
TaqMan® analysis showed IFIT1 expression in all IL-29, IL-28A and IFNα
samples showing that all RNAs were suitable for further Affymetrix genechip ®
analysis.
TaqMan® analysis showed greatest gene expression change with IFIT1, MX1,
OAS1 and G1P3 at the 8, 16 and 24 hour time points (Figure 4.1).

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10,000,000

Taqman prescreen G1P3 expression

5,000,0000

800,000

TaqMan Prescreen OAS1 expression

600,000
400,000
200,000
0

TaqMan prescreen MX1 expression
4,000,000

2,000,000

0

TaqMan Prescreen IFIT expression
2,000,000
1,500,000
1,000,000
500,000
4h IL28A Replicon
4h IL29 Replicon
4h IFNa replicon
4h IL28A HuH7
4h IL29 HuH7
4h IFNa HuH7
8h IL28A Replicon
8h IL29 Replicon
8h IFNa Replicon
8h IL28A HuH7
8h IL29 HuH7
8h IFNa HuH7
16h IL28A Replicon
16h IL29 Replicon
16h IFNa Replicon
16h IL28A HuH7
16h IL29 HuH7
16h IFNa HuH7
24h IL28A Replicon
24h IL29 Replicon
24h IFNa Replicon
24h IL28A HuH7
24h IL29 HuH7
24h IFNa HuH70

Figure 4.1: TaqMan® expression of IFITI, MX1, OAS1 and G1P3
TaqMan® expression of IFITI, MX1, OAS1 and G1P3 compared with house keeping
genes b-actin and GAPDH in parent HuH7 and HuH7 HCV replicon cells treated with
10 x IC50 values of IFNα, IL-28A and IL-29 at 4, 8, 16 and 24 hour time points.
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4.4 Parent HuH7
Individual data and pathway analysis was undertaken for all treatments andtime points. Data was analysed to a set criteria: in Rosetta Resolver (2.2.6.11),
an ANOVA was generated for each compound versus PBS control, the genes
were filtered to include genes with fold change >1.5 and >minus 1.5, and genes
were included if their p-value was <0.05 (>95%). Lists were generated based on
the above criteria of upregulated and downregulated genes for IL-28A, IL-29
and IFNα at each time point. Lists were also generated of genes that werecommon and unique between IL-28A, IL-29 and IFNα in both HuH7 parent cells
and HuH7 HCV replicon cells. Gene lists were then put into Ingenuity and
GeneGo for pathway analysis.
4.4.1 Parent HuH7 versus HCV replicon
The Affymetrix dataset (P-value >95% Fold change -1.5< and >1.5) isrepresented numerically in a series of Venn diagrams (Figure 4.2), showing
gene numbers common and unique to IFNα, IL-28A and IL-29 at all time points
in both the parent HuH7 and HCV replicon datasets.

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Chapter 4

8 hours

16 Hours

24 Hours

RepliconParentFigure 4.2: Venn diagrams
The number of genes expressed by IL-28A, IL-29 and IFNα across the 8, 16 and 24 hour time points from both replicon and parental datasets
are represented in Venn diagrams. (P-value >95%, fold change -1.5< and >1.5)
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Chapter 4
Results from the data presented as Venn diagrams (Figure 4.2) show at the 8hour time point show a 90, 92 and 56% reduction in gene expression for genes
unique to IFNα IL-28A and IL-29 respectively in replicon compared to parent
line. Similar reductions in gene expression are also seen at the 16 hour and 24
hour time points. The Venn diagrams showed a trend between parent andreplicon datasets of more genes being unique to an individual interferon thanthere were genes in common between the interferons.
Principal component analysis (PCA) is a mathematical procedure that uses anorthogonal transformation to convert a set of observations of possibly correlated
variables into a set of values of linearly uncorrelated variables called principal
components. The first principal component (PCA1) shows the largest possible
variance e.g. accounts for as much of the variability in the data as possible, thiswill be followed by PCA2 and so on. PCA1 is shown (Figure 4.3) and illustrates
that time accounts for the biggest variable in the data, followed by cell typereplicon versus parent in PCA2 plot (Figure 4.4). PCA1 plot shows 4 hour and16 hour clustering together and 8 hour data being separate for replicon andparent cell lines. PCA2 shows replicon cells separating from normal parent
HuH7cells.

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Chapter 4

GP1546 intensity for PCA.M3 (PCA-X)
t[Comp. 1]/t[Comp. 2]
Colored according to classes in M3

4hour
8hour
16 hour

20
IL28A16h-1HIL294h-3H
IFNa2a4h-1H

10

t[2]

PBS8h-2H
IL298h-1H
IFNa2a8h-3HPBS8h-1H
PBS8h-3H

IFNa2a16h-2H
IL28A16h-3H
IL28A16h-2HIL2916h-2HIL2916h-3HIL2916h-1HIFNa2a4h-2H
PBS16h-3H
IFNa2a16h-1HPBS4h-3H
IFNa2a16h-3H
PBS16h-2H
IL28A4h-1H
IL28A4h-2H
PBS16h-1H
IL28A4h-3HPBS4h-2H
IL294h-1HIL294h-2HIL2916h-3RIL2916h-1RIFNa2a16h-3RIFNa2a4h-3HPBS4h-1H
PBS16h-2R
IL28A16h-3RIFNa2a16h-1RIL2916h-2RIFNa2a16h-2R
IL28A16h-1R
PBS16h-1R
PBS16h-3R
IL28A16h-2R

0IL28A8h-1H
IL28A8h-2HIL298h-2H
IFNa2a8h-2H
IL28A8h-3HIFNa2a8h-1H
PBS8h-3R
IL298h-2R
IL28A8h-1R
IL28A8h-2R
PBS8h-1R
IL298h-1R
IFNa2a8h-3RIFNa2a8h-1RIFNa2a8h-2RIL298h-3R
PBS8h-2R
IL28A8h-3R

-10

-20
-20

-10

0

10

20

t[1]
R2X[1] = 0.283455

R2X[2] = 0.18434

Ellipse: Hotelling T2 (0.95)
SIMCA-P+ 11 - 08/05/2006 11:53:29

Figure 4.3: PCA plot –PC1 Vs 2 by time point
The first principal component (PCA1) shows the largest possible variance time accounts for the biggest variable in the data, PCA1
plot shows 4 hour and 16 hour clustering together and 8 hour data being separate for replicon and parent cell lines.

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GP1546 intensity for PCA.M5 (PCA-X)
t[Comp. 2]/t[Comp. 3]
Colored according to classes in M5

10

IFNa2a8h-1H
PBS16h-1H
PBS16h-3H
IL28A8h-3HIL2916h-1HIFNa2a8h-2HIFNa2a16h-3HIFNa2a16h-1H
IL28A8h-2HIL298h-2H
PBS16h-2H
IL28A8h-1HIL2916h-3HIL294h-2H
IL28A4h-3HPBS4h-1H
IL28A4h-1HPBS4h-3H
IFNa2a4h-2HIL294h-1H
IL28A4h-2HIFNa2a4h-3HPBS4h-2H

t[3]

5

0
IL298h-1R
IFNa2a8h-1RIFNa2a8h-3R
IL28A8h-3RIFNa2a8h-2RIL298h-2R
PBS8h-1R
PBS8h-2R
PBS8h-3R
IL298h-3R
IL28A8h-2R
IL28A8h-1R-5IFNa2a16h-2R
PBS16h-1R
IL2916h-2RIL2916h-3R
IL28A16h-2R
PBS16h-3R
IL2916h-1RIFNa2a16h-1R
IL28A16h-1R
IL28A16h-3R
PBS16h-2R
IFNa2a16h-3R

Replicon
Normal cells

IL2916h-2HIFNa2a16h-2H
IL28A16h-3H
IL28A16h-2HIL298h-1H
IL28A16h-1HIFNa2a8h-3HPBS8h-3H
PBS8h-1H PBS8h-2HIFNa2a4h-1H-10IL294h-3H

-20

-10

0

10

20

t[2]
R2X[2] = 0.18434

R2X[3] = 0.0725509

Ellipse: Hotelling T2 (0.95)
SIMCA-P+ 11 - 08/05/2006 13:02:37

Figure 4.4: PCA plot –PC2 Vs 3 by cell type
PCA2 shows replicon cells separating from normal parent HuH7cells.

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4.4.2 Parent HuH7 signature genes
The top 20 expressed genes in the parent cell line with IFNα, IL-28A and IL-29
treatments at 4, 8, 16 and 24 hour time points in relation to IL-29 expression 8
and 24 hour time points are shown below (Table 4.2).
Table 4.2: Table to show top 20 expressed genes in parent HuH7 cells
Symbol

IFNα

IL-29

IL-28A

4h

8h

16h

24h

4h

8h

16h

24h

4h

8h

16h

24h

G1P3

100

79

74

74

100

100

100

100

84

52

69

48

IFI6

-

79

-

74

-

100

-

100

-

52

-

48

IFIT1

16

6.6

3.9

7.1

100

100

100

100

14

7.2

4.6

3.4

MX1

8.8

2.9

2.9

2

66

51

53

46

7.7

5.2

2.7

1.9

IFITM3

11

12

6.3

10

26

38

18

40

8.5

7.9

6

5.6

IFIH1

-

-

-

5.2

34

-

30

30

3.9

5

-

3.4

IFITM1

15

16

3.6

6.9

67

82

22

25

15

9.2

3.8

4.5

ISG15

-

5

-

5.4

-

18

-

20

-

3.3

-

2.4

OAS1

4.7

-

2.6

-

49

14

38

19

6.1

-

3.1

-

ISGF3G

6.6

7.7

3.6

6.1

14

17

12

16

6.2

7.4

3.9

3.1

SUPT16H

-

49

-

-

29

12

-

-

70

3.1

-

STAT1

3.4

14

2

11

28

12

-

2.7

11

2.1

-

IFI27

-

-

-

-

12

-

14

9.7

-

-

-

-

IFITM2

4.5

2.8

2.6

3.9

9.3

8.1

7.2

9.4

3.5

2.3

2.9

2.6

OAS3

2

1.7

-

-

14

8.4

14

8.6

2.1

-

-

-

PARP9

2.3

-

1.9

2.1

7.3

2.3

8.7

5.8

2.3

-

2

-

PLSCR1

2.5

2.8

1.6

-

8.7

8.6

8.4

5.5

2.4

2.6

1.6

-

DDX58

3.4

-

-

-

20

5.1

14

5

-

-

-

-

IFI35

2.6

-

2.8

2.1

5.7

2.7

9.3

5

2.4

-

2.8

1.8

EPSTI1

2.4

-

-

-

11

5.6

7.2

4.7

2.5

-

-

-

7.6
2.2

Table 4.2 shows the top 20 expressed genes in the parent cell line with IFNα, IL-28A
and IL-29 treatments at 4, 8, 16 and 24 hour time points in relation to IL-29 expression
at 8 and 24 hour time points. Genes are >1.5 fold up or down with one or more

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treatments. Values represent fold activation compared with PBS treatment. Genes
highlighted in yellow are also present in the replicon table (Table 4.8).
(-) = <1.5 fold induction.

There are highly expressed interferon stimulated genes (ISG) common to IFNαand IFNλs both in the replicon and the parent HuH7 cell lines, these include
G1P3, IFI6, IFIT, IFITM1, MX1, IFITM3, STAT1, ISG15, ISGF3G and OAS1 asshown in Table 4.8. The only top 20 gene determined by IL-29 at the 24 hour
time point to not be represented in the entire replicon dataset (genes expressed> or < 1.5 fold change) was SUPT16H which plays a role in generaltranscription, it has positive and negative effects on gene expression. Required
for the appropriate synthesis during heat shock and continued expression of
cyclin genes that determine the passage through start during cell cycle control it
may act as an acidic activator.
4.4.3 Parent HuH7 pathway analysis IPA
To demonstrate the mechanisms of IFNλs, pathway analysis was performed
using Ingenuity and GeneGo pathway analysis tools. The top 7 pathways
determined by Ingenuity pathway analyses scoring for IFNα, IL-28A and IL-29 atthe 4 hours and IFNα and IL-29 at 8 hours are shown in Figures 4.5 and 4.6
respectively. For type I and type III IFNs at 4 hours, interferon signalling is themost strongly induced pathway determined by Ingenuity Pathway Analysis,complement coagulation pathway is the second most strongly induced pathway
for IL-28A, and protein ubiquitination pathway is the second most strongly
induced pathway for both IFNα and IL-29. After this, IL-29 induces immune
modulation pathways such as antigen presentation pathway and complement
and coagulation cascades predominantly, in contrast to IFNα that predominantly
regulated cell signalling pathways. At 8 hours interferon signalling is the top
pathway for IL-29 followed by antigen presentation and complement coagulation
pathways, for IFNα there are gene expression changes in multiple signalling
pathways:integrin,

IGF-1,Jak/Stat,

SAPK/JNK

signalling

pathways.

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Chapter 4A

Figure 4.5 A: Parent HuH7 cell line pathway analysis at 4 hours for IFNαUsing IPA for the Parent HuH7 cell line at the 4 hour time point, showing the top seven pathways for: A IFNα. Pathway analysis using IPA for theparent cell line at the 4 hour time point graphical representation of the top seven pathways for IFNα showing up and down regulated genes
associated to the pathways IPA gives a score shown by the trend line and –log scale determined by expression level and number of genes
expressed in pathway/total number of genes within pathway. Percentage is number of genes modulated in pathway; red represents up regulated
genes and green represents down regulated genes.
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Chapter 4

B

Figure 4.5 B: Parent HuH7 cell line pathway analysis at 4 hours for IL-28A
Using IPA for the Parent HuH7 cell line at the 4 hour time point, showing the top seven pathways for: B IL-28A. Pathway analysis using IPA forthe parent cell line at the 4 hour time point graphical representation of the top seven pathways for IL-28A showing up and down regulated genes
associated to the pathways IPA gives a score shown by the trend line and –log scale determined by expression level and number of genes
expressed in pathway/total number of genes within pathway. Percentage is number of genes modulated in pathway; red represents up regulated
genes and green represents down regulated genes.
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Chapter 4C

Figure 4.5 C: Parent HuH7 cell line pathway analysis at 4 hours for IL-29
Using IPA for the Parent HuH7 cell line at the 4 hour time point, showing the top seven pathways for: C IL-29. Pathway analysis using IPA for theparent cell line at the 4 hour time point graphical representation of the top seven pathways for IL-29 showing up and down regulated genes
associated to the pathways IPA gives a score shown by the trend line and –log scale determined by expression level and number of genes
expressed in pathway/total number of genes within pathway. Percentage is number of genes modulated in pathway; red represents up regulated
genes and green represents down regulated genes.
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Chapter 4AA
Figure 4.6 A: Parent HuH7 cell line pathway analysis at 8 hours for IFNαUsing IPA for the Parent HuH7 cell line at the 8 hour time point, showing the top seven pathways for: A IFNα. Pathway analysis using IPA for theparent cell line at the 8 hour time point graphical representation of the top seven pathways for IFNα showing up and down regulated genes
associated to the pathways IPA gives a score shown by the trend line and –log scale determined by expression level and number of genes
expressed in pathway/total number of genes within pathway. Percentage is number of genes modulated in pathway; red represents up regulated
genes and green represents down regulated genes.
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Chapter 4

B``

Figure 4.6 B: Parent HuH7 cell line pathway analysis at 8 hours for IL-29
Using IPA for the Parent HuH7 cell line at the 8 hour time point, showing the top seven pathways for: B IL-29. Pathway analysis using IPA for theparent cell line at the 8 hour time point graphical representation of the top seven pathways for IL-29 showing up and down regulated genes
associated to the pathways IPA gives a score shown by the trend line and –log scale determined by expression level and number of genes
expressed in pathway/total number of genes within pathway. Percentage is number of genes modulated in pathway; red represents up regulated
genes and green represents down regulated genes.
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Chapter 4

4.4.4 Parent HuH7 unique IL-29 gene analysis
Genes unique for IFNα belong to predominately signalling pathways; Jak/Stat,
EGF, IGF-1, IL-2, GM-CSF, FGFF, IL-4 and IL-6. These unique genes for IFNα
include: PIK3CB, PIK3R1, SOS2, SOCS2, MAP3K1. Genes unique to IL-28A
belong to IGF-1, EGF, TGF, VEGF, IL-2, IL-6 and IL-4 signalling pathways. IL29 unique genes belong to interferon signalling as the top pathway but are
followed by antigen presentation and complement and coagulation cascades;
unique genes at the 8 hour time point include HLA-A, HLA-B, HLA-C, HLA-F,
HLA-G, PLG, CFB and SERPINE1. Antigen presenting gene expression with
IFNα and IL-29 treatments are shown (Table 4.3). Antigen presenting genes areshown to be expressed at earlier time points in cells treated with IL-29
compared to cells treated with IFNα.(Table 4.3)
Table 4.3: Antigen presenting genes IL-29 versus IFNα.

Symbol

IFNα

IL29

4h

8h

16h

24h

4h

8h

16h

24h

HLA-A

-

-

-

-

1.5

1.5

1.6

-

HLA-B

-

-

-

1.9

2.6

2.9

2.9

2.9

HLA-C

-

-

-

1.6

2.5

2.4

3.2

2.6

HLA-DRA

-

-

-

-

-

3.6

-

-

HLA-DRB4

-

-

-

-

-

-

-

3.2

HLA-E

-

-

-

-

2.6

1.6

3.9

2.3

HLA-F

-

-

-

-

-

1.6

-

-

HLA-G

-

-

-

-

1.5

2.7

1.6

-

PSMB8

-

-

-

-

-

3.2

-

-

TAP1

-

-

-

2.8

-

2.7

3.3

4.5

(-) = <1.5 fold induction

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Chapter 4

Figure 4.7: A top pathway - antigen presentation pathway determined by Ingenuity for genes unique to IL-29 at 8 hours
Antigen processing is a biological process that prepares antigens for presentation to T lymphocytes. This process involves two distinct pathways forprocessing of antigens from an organism's own (self) proteins or intracellular pathogens (e.g. viruses), or from phagocytosed pathogens (e.g. bacteria);
subsequent presentation of these antigens on class I or class II MHC molecules is dependent on which pathway is used. Both MHC class I and II are
required to bind antigen before they are stably expressed on a cell surface. Red correspondes to up regulation of gene.
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Chapter 4

An Ingenuity pathway map for a top pathway antigen presentation pathway isshown (Figure 4.7) determined by genes unique to IL-29 at 8 hours. Other
pathway analysis tools were used including GeneGo, data shown below(Section 4.4.5).
4.4.5 Parent HuH7 pathway analysis GeneGo
The top 10 pathways with genes uniquely regulated by IL-29 at 24 hours areshown in Table 4.4. Genes unique to IL-29 treatment at 24 hours induce IFNα,
IFNβ and IFNγ pathways, so any gene changes with IL-29 at 24 hours may be
due to secondary mechanisms, e.g. feedback from genes expressed at earlytime points. These pathways are also shown in a GeneGo pathway map (Figure
4.8).
Table 4.4: Pathway analysis for HuH7 cell line GeneGo
Genego Map - Unique genes to IL-29 at 24 hours

p-Value

Genes ↓

Genes ↑

RhoA regulation pathway (extension, GEFs/GAPs)

0.000267

6

34

IL9 signaling pathway

0.001799

5

33

Propionate metabolism p.2

0.01824

3

21

Mitochondrial ketone bodies biosynthesis and metabolism

0.02321

2

9

HETE and HPETE diosynthesis and metabolism

0.02636

4

42

IFN gamma signaling pathway

0.02765

5

63

Gs-a Specific GPCRs (in brain)

0.04279

3

29

Putative SUMO-1 pathway

0.04279

329

Ascorbate metabolism

0.04535

5

72

IFN alpha/beta signaling pathway

0.04662

3

30

Pathway analysis for genes unique to IL-29 at the 24 hours shows the top 10 pathwaysfor IL-29 determined by GeneGo.

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Chapter 4

Figure 4.8: Top pathway interferon signalling determined by GeneGo for genes unique to IL-29 at 24 hours.
This figure is a schematic produced in GeneGo, bars with one represent IL-29 upregulation, the higher the red in the bar –the higher the gene
expression e.g. 2-5A synthetase is highly upregulated by IL-29 and not up-regulated significantly (≥ 1.5 fold) at this time point by IFNα.

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Chapter 4
4.4.6 Additional unique gene changes –cytokine induction, TLR and MAPK
signalling
There are differences in cytokine induction between the types of interferons: IL24 is down regulated by type III IFNs, IL-27 is up regulated by type I IFN. IL-27R
is up regulated by type I IFN and down regulated by IL-29.
TLR7 signalling genes unique to IL-28A in the parent cell line at the 8 hour time
point are: TLR7, TRAF4, TRAF5 and IRAK1BP1 (-2.9, 1.9, -1.9 and 1.7 foldchange respectively) and at the 24 hour time point IRF7 and TRAF31P3 wereexpressed (-3.2 and -2.9).
There are notable differences between the IFNs with MAPK signalling
regulation in the parent cell line IFNα induces a far greater number of the MAPK
genes than IL-29. For IFNα, 9 genes are expressed at the 8 hour time point and
16 genes are expressed at the 24 hour time point, for IL-29 this is 3 and 2
genes respectively. IL-28A has more similarities with IFNα with the regard to
expression of MAPK genes with expression of 15 MAPK genes at the 8 hour
time point but only 4 genes at the 24 hour time point.
4.4.7 Parent HuH7 kinetics
Table 4.5 shows the kinetics of expression in a selection of genes in the parent
cell line 8, 16 and 24 hours after treatment with IFNα, IL-28A and IL-29
treatments. The IFNs shown similar trends to each other over the time points
e.g. IFI6 was shown to be expressed with IFNα, IL-29 and IL-28A at 8 hours
and 24 hours but not at 4 and 16 hour time points.
Table 4.5 Data subset: to illustrate kinetics in parent HuH7 cells
Symbol

IFNα

IL-29

IL-28A

4h

8h

16h

24h

4h

8h

16h

24h

4h

8h

16h

24h

100

79.3

74.2

74

100

100

100

100

84.3

51.7

68.7

48.2

-

74

-

100

-

100

-

51.7

-

48.2

10.1

26.4

37.9

17.6

40.4

5.4

-

18.4

-

19.7

48.8

13.6

38.2

18.8

6.1

-

3.1

-

11

28.2

11.8

-

2.7

10.9

2.1

-

G1P3
IFI6

-

79.3

IFITM3

11.4

11.8

ISG15

-

5

OAS1

4.7

-

STAT1

3.4

13.5

6.3
2.6
2

-2.2

8.5

7.9

-

3.3

6

5.6

-

2.4

(-) = <1.5 fold induction.

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Chapter 4

4.5 HCV replicon
4.5.1 Comparison of parental data with replicon data to investigate theeffects of HCV on IL-28A, IL-29 and IFNα gene modulation

RNA from time point 4 hours with the replicon cells was not of sufficient quality
to use in Affymetrix genechip® analysis.
HCV replicon inhibited gene induction by both type I and type III IFNs; this isseen at 8, 16 and 24 hour time points in the Venn diagrams (Figure 4.2), where
there is a substantial decrease in the numbers of genes expressed in thereplicon system from those expressed in the parent system. Parent HuH7 cells
are more sensitive to interferons IFNα, IL-28A and IL-29 compared to thereplicon cells. Gene expression is generally higher in the parent cells than thereplicon cells, as shown for IF16 in Table 4.7. This is also highlighted in the
Venn diagrams (Figure 4.2). Gene expression detail is shown below (Tables 4.6
and 4.7).
Table 4.6: Comparison of replicon versus parent HuH7 cells
RepliconParentRepliconParentSymbol

IFNα

IFNα

IL-29

IL-29

G1P3

3.2

79.3

6.7

100

IFIT1

20

6.6

29.8

100

IFI6

-

79.3

9.8

100

MX1

2.3

2.9

3.4

53.1

ISGF3G

15

7.7

18.3

12.1

IFIH1

6

-

6.6

30

IFITM3

-

11.8

4

17.6

ISG15

2.6

5

3.1

-

IFITM1

-

16.1

-

22.2

Comparison of replicon cells versus parent HuH7 cells at 8 hours with IFNα and IL-29

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Chapter 4
Table 4.7: Sensitivity of parent HuH7 cell line versus replicon
IF16 fold change

8hr IFNα

8hr IL-29

24hr IFNα

24hr IL-29

Parent

79

>100

73

>100

Replicon

0

9.7

52

41.9

4.5.2 HCV replicon signature genes
The top 20 expressed genes in the replicon cell line with IFNα, IL-28A and IL-29
treatments at 8, 16 and 24 hour time points in relation to IL-29 expression at 24hour time point are shown below (Table 4.8).
Table 4.8: A selection of top 20 expressed genes in the replicon cells
Symbol

IFNα

IL-29

IL-28A

8h

16h

24h

8h

16h

24h

8h

16h

24h

IFIT1

21

21

100

30

100

100

13

78

64

G1P3

3.2

82

42

6.7

100

97

4.5

100

43

IFI6

-

-

52

9.8

100

42

-

54

20

MX1

2.3

2.3

30

3.4

18

35

-

12

17

ISGF3G

15

15

22

18

14

21

15

12

16

IFIH1

6

6

23

6.6

23

15

4.4

13

9.5

IFITM3

-

-

7.6

4

4.9

12

3

3.5

4

ISG15

2.6

2.6

11

3.1

14

9.9

-

7.4

5.4

IFITM1

-

-

7.1

-

9.9

8.7

-

5.6

4.3

ADAMTS13

-

-

-

-

-

7.7

-

-

6.7

OAS1

3.2

3.2

5.3

6.2

10

7.4

3.8

5.4

4.1

DDX58

3.4

3.4

7.9

3.7

11

6.5

-

4.8

3.6

PRIC285

2.2

-

6.8

3.1

5.1

6.4

3.1

3.4

3

OAS3

3.4

3.4

8

5.1

6.4

5.3

-

-

2.8

PARP9

-

-

4.9

2.9

-

4.9

-

-

3

STAT1

3.2

3.2

5.4

3.5

5.2

4.8

-

3.2

3.3

PLSCR1

-

-

4.2

-

4.6

4.2

-

-

2.9

PML

-

-

-

-

-

4

-

-

-

IFI27

-

-

-

-

-

3.5

-

-

-

IFITM2

-

-

-

-

-

3.3

-

-

-

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Chapter 4

Table 4.8 shows a selection of top 20 expressed genes in the replicon cell line with
IFNα, IL-28A and IL-29 treatments at 8, 16 and 24 hour time points in relation to IL-29
expression at the 24 hour time point. Genes are >1.5 fold activation with one or moretreatments compared with PBS treatment. 100 represents 100 fold change or greater,
Genes highlighted in yellow are also present in the parent table. (-) = <1.5 foldinduction.

The only top 20 gene determined by IL-29 at the 24 hour time point to not be
represented in the entire replicon dataset (genes expressed > or < 1.5 foldchange) was ADAMTS13 which prevents thrombosis through abnormal clotting.
There are highly expressed interferon stimulated genes (ISG) common to IFNαand IFNλs both in the replicon and the parent HuH7 cell lines, these include
G1P3, IFI6, IFIT, IFITM1, MX1, IFITM3, STAT1, ISG15, ISGF3G and OAS1.
4.5.3 HCV replicon kinetics
To compare gene expression trends in the replicon cells treated with IFNα, IL28A and IL-29 at 8, 16 and 24 hours, several types of data analysis was
performed on the replicon data set. Cluster analysis was generated using
Rosetta Resolver of all replicon fold change data greater than 2 fold up or down
regulated and > 99% confidence; a total of 881 genes. The data clustered bygroups of genes which share similar properties is shown in Figure 4.9.
The up regulated data from the entire replicon data set where a gene is above 2
fold change in relation to PBS control in a minimum of one time point, based on
their fold regulation in response to IFNα at 8 hours. Data is represented visually
in more detail as a Heat Map (Figure 4.10) and in further detail for MX1, IFIT1
and ISGF3G genes in trend plots (Figure 4.11).

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Chapter 4

8 hours

16 hours

24 hours

IL-28 IL-29 IFNαIL-28 IL-29 IFNαIL-28 IL-29 IFNα

Figure 4.9: Cluster analysis plot
Cluster analysis of 640 genes regulated significantly (p<0.01) regulated ±1.5-fold with either IFNα, IL-29 or IL-28A at 8, 16 and 24 hours.
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Chapter 4

Figure 4.10: Heat map
A visual summary of the replicon gene data. In the heat map, genes are sorted in decreasing order based on their fold regulation in response to
IFNα at 8 hours. The heat map represents the entire up regulated data set for any one gene whose expression was above 2 fold compared with
PBS treatment with one or more IFNs at one or more time points, p-value <0.5. To show low induction values, the maximum heat intensity (red)was set to a 20 fold induction value.

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Chapter 4

PBS

IL-28

IL-29

MX1

IFNα

P r o f ile C h a r t

600

500

400

300

200

100

0

PBS

IL-28

IL-29

IFIT1

IFNα

P r o f ile C h a r t

1600

1400

1200

1000

800

600

400

200

0

PBS

IL-28

IL-29

IFNα

ISGF3GP r o f ile C h a r t

1000

800

600

400

200

0

Figure 4.11: Trend plots
Trend plots were used as an effective, efficient oversight screening tool to visualise
control (PBS) versus treatments IL-28A, IL-29 and IFNα over 3 timepoints 8 hour (bluebox), 16 hour (orange box) and 24 hour (green box). Trend plots for three genes Mx1,
IFIT1 and ISGF3G are shown.

Trend plots and trend analysis show that IFNα and IL-28A and IL-29 show thesame trends, e.g. for Mx1 (MxA) there is low expression with IL-28A, IL-29 andPage 119 of 183

Chapter 4
IFNα at 8 hours, this peaks at 16 hours and levels off at 24 hours for all IFNs
tested (IL-28A, IL-29 and IFNα).

4.6 Discussion
There are many similarities in both gene modulation between type I and type III
IFNs. When looking at the genes that are expressed most highly in both theparent HuH7 and the replicon systems IFNλs and IFNα show largely
overlapping sets of interferon stimulated genes (ISGs). Although antiviralmechanisms of type I and III differ, they may actually involve similar ISG
responses. The individual gene expression results from the replicon data set
shown here showed good concordance with data published by Marcello et al 61,
with 45/66 differentially regulated genes as a response to IFNα and 49/66 as a
response to IL-29. Zhou et al, Doyle et al and Marcello et al have all shown
similar sets of ISGs being expressed by type I and type III IFNs65,57,61.
Genes common to both the replicon and parent gene expression werehighlighted (in Tables 4.2 and 4.8). The majority of interferon stimulated genes(ISG) stimulated in the replicon cell line by IFNα, IL-28A and IL-29 are also
stimulated in the parental cell line; these ISGs include: G1P3, IFIT1-5, ISG15
and ISGF3G.
Despite this there are more differences in the pattern of expressed genes
between the IFNλs and IFNα than genes expressed in common as shown in the
Venn diagrams (Figure 4.2). The Venn diagrams showed a trend between
parent and replicon datasets of there being more genes being unique to anindividual interferon than genes in common between the interferons. This isdifferent to the findings of other groups 61,65. The unique genes shown in the
Venn diagrams are generally expressed at low levels.
For the majority of genes in both the replicon and the parent datasets, thekinetics of gene expression was the same for type I and type III IFNs, which ishighlighted in subset of data (Table 4.5) GIP3, IF16, IFITM3, ISG15, OAS1,STAT1. The table shows that gene modulation with IFNα, IL-28A and IL-29
shows similar patterns over the time courses even being expressed at sometime points and not at all in other time points as shown with IFI6, and ISG15.

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Chapter 4
The Marcello study61 showed in the replicon system that the majority of type III
stimulated genes continue to increase at 24 hours and with IFNα the samegenes tend to decrease by the 24 hour time point. In contrast the data shown
here demonstrates that the kinetics of the type I and III IFNs show similar
patterns of gene expression. HCV replicon inhibited gene induction by both type
I and type III IFNs; this is seen at 8, 16 and 24 hour time points, where there isa substantial decrease in the numbers of genes expressed in the repliconsystem from those expressed in the parent system. There are also multiple
genes for which the expression levels are lower in the replicon data than that ofthe parent. The NS3/4A protease encoded by HCV has been shown to cleave
the adaptor in the RIG-I-like receptor (RIG-I) pathway IPS1 thus disrupting thesignalling to type I IFN138; this data indicates that signalling to type III IFN is also
disrupted. Downstream genes from RIG-I are affected in the replicon system
including MAPK genes which show lower abundance in number in the repliconsystem than in the parent system.
Pathway analysis was carried out for the replicon dataset but due to limited
gene numbers in the replicon dataset more focus was placed on the larger
parental cell line dataset. At the earliest time point 4 hours, for type I and type III
IFNs interferon signalling is the most strongly induced pathway determined by
Ingenuity Pathway Analysis, complement coagulation pathway is the second
most strongly induced pathway for IL-28A, and protein ubiquitination pathway is
the second most strongly induced pathway for both IFNα and IL-29. At 8 hours
after interferon signalling pathway, IL-29 induces immune modulation pathways
such as antigen presentation pathway and complement and coagulationcascades predominantly, compared with IFNα mostly regulating cell signalling
pathways. Interferon signalling was not represented in the top 7 pathways by
IFNα at 8 hours potentially showing that IFNα is less specific in its signalling
pathways than IL-29.
The antigen presenting pathway regulated in the parent cell line showed gene
expression of MHC class I antigens to be up regulated with IFNa and IL-29, but
IL-29 up regulated MHC class expression at much earlier time points (4,8,16
hours and 24 hours) than IFNα (24 hours). MHC class I antigen expression wasshown to be up-regulated following type I or type III IFN addition2. Up regulation

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Chapter 4of MHC class I expression may lead to increased recognition of virus-infected
cells by the immune system.
Genes unique for IFNα belong to predominately signalling pathways; Jak/Stat,
EGF, IGF-1, IL-2, GM-CSF, FGFF, IL-4 and IL-6. These unique genes for IFNα
include: PIK3CB, PIK3R1, SOS2, SOCS2, MAP3K1. Genes unique to IL-28A
also belong to IGF-1, EGF, TGF, VEGF, IL-2, IL-6 and IL-4 signalling pathways.
IL-29 unique genes belong to interferon signalling as the top pathway but
interestingly are followed by antigen presentation and complement andcoagulation cascades; unique genes at the 8 hour time point include HLA-A,
HLA-B, HLA-C, HLA-F, HLA-G, PLG, CFB and SERPINE1.
Genes unique to IL-29 treatment at 24 hours induce IFNα, IFNβ and IFNγ
pathways, so any gene changes with IL-29 at 24 hours may be due tosecondary mechanisms, e.g. feedback from genes expressed at early time
points. 2-5A synthetase is of note being significantly (≥ 1.5 fold) expressed by
IL-29 but not IFNα at 24 hours, this gene encodes a member of the 2-5A
synthetase family, essential proteins involved in the innate immune response toviral infection.
Gene expression analysis here suggests that IFNλs and IFNα have primarily
complementary functions, signalling through common pathways enabling IFNλs
and IFNα to induce similar biological activities in particular antiviral resistancemediated by very similar sets of interferon sensitive genes, this has also beenshown by other groups65,57,61. The kinetics of IL-29 response has been shown todiffer from IFNα by Marcello with gene expression data 139 also demonstrating in
Huh-7 hepatocellular carcinoma cells, that IFN-λ induces STAT-1 and STAT-2
more rapidly than IFNα64,139 this is also seen in HaCaT keratinocytes63 thesestudies have also shown although the subsequent transcriptional response isslightly delayed, the increase in ISG expression induced by IFNλ is stronger andmore prolonged than the response activated by IFNα64,139. There are several
studies although Jak/STAT signaling mediates the primary functions of IFNλ,other pathways are also activated by the receptor including ERK-1/2, mitogenactivated protein kinase (MAPK) and Akt in intestinal epithelial and colorectal
cancer-derived cell lines126, activation of MAPKs was also observed in Raji cells
following treatment with IFNλ65. These results indicate that IFNλ can induce

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multiple signaling pathways that may contribute to its activity as an antiviral andimmunomodulatory cytokine and complement the findings here.
Where this research differs from that published is that IL-29 is more specific in
its modulation and by modulating alternative pathways such as the antigen
presentation and processing pathways at early time points may prove to be auseful therapeutic option for the management of chronic viral infection such as
HCV. IL-28R is not as widely expressed as the type I IFN receptor which could
mean a more specific target. IL-28R was shown to be found primarily on antigen
presenting cells (Chapters 5 & 6). Coupled with IL-29 modulating the antigen
presenting pathway at earlier time points than IFNα could prove to have asuperior therapeutic profile to IFNα.

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Chapter 5

Chapters 5 & 6
5. IL-28R distribution using genomic analysis
5.1 Introduction
The aim of this chapter was to study the expression of IL-28 receptor (IL-28R) ina panel of tissues and cells in order to identify type III IFN targeted tissues andcells. Tissues and cells containing IL-28R were identified using real-time PCR
and gene expression data for IL-28R was analysed.
IFNα and IFNβ (type I IFNs) bind to a heterodimeric receptor comprising analpha component (IFNAR1) and a beta component (IFNAR2). Although theactivities of type III IFNs are similar to type I IFNs, IFNλ signalling is achieved
through a specific and distinct heterodimeric receptor complex which is formed
between IL-28A receptor (IL-28R / IFN-λR1) and IL-10 receptor (IL-10R2)2,3.
Similarly to type I IFNs, binding of type III IFNs to their receptor leads to theactivation of the Jak:STAT pathway. This is upstream of IFN-inducible genes
and modulates their transcription.
The heterodimeric receptor IFNAR1/2 for IFNα and IFNβ is present on all
nucleated cells72. IL-10R2 is ubiquitously expressed73, whereas initial RNA
expression data showed that IL-28R is limited to specific tissues and cell types3.
It is the aim of this chapter to conduct a comprehensive exploration of IL-28R
distribution using gene expression techniques in both human and murine
tissues and immunohistochemical techniques in both human and murine tissues
are described in chapter 6.

5.2 IL-28R gene expression in mouse tissue
IL-28R gene expression was studied in a panel of mouse tissues using real-time
PCR (Figure 5.1). IL-28R was shown to be expressed predominantly inepithelial tissue, lymph nodes and spleen, as was seen with the protein
expression of IL-28R. High expression; greater than 1,000,000 copies per 50ng
of cDNA was seen in mandibular and messenteric lymph nodes and gut tissues
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Chapter 5(stomach, duodenum, jejunum, ileum and colon). Expression was also detectedin epididymis, spleen, thyroids, kidney, lung, pancreas, prostate, oesophagus,
ovaries, peripheral nerve and pituitary gland. Tissues with minimal expression
were: liver, bone marrow, adrenals, heart, seminal vesicles and cerebellum.
Tissues (not recorded in Figure 5.1) with no detectable expression were: aorta,
bladder, eyes, harderian gland, skeletal muscle, skin and spinal cord.

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Figure 5.1: TaqMan® IL-28R
Quantative RT-PCR analysis of IL-28R expression in a range of mouse tissues, shown as magnitude of fluorescence signal ΔRn and measured
in copy numbers, 3 samples for each tissue were pooled prior to PCR analysis.

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5.3 Gene Logic human tissue microarray screen
Using data from the Gene Logic human tissue microarray database, gene
expression of IL-28R (TIG45563), IL-10RB (TIG1871) and IFNAR1 (TIG1823)
were compared across a panel of human tissues (Figure 5.2 A-C). This data
showed that while IL-10R and IFNAR mRNAs were ubiquitously expressed
across tissues (with the exception of brain IL-10RB and skeletal muscle IFNAR1
shown in red), several tissues were negative for IL-28R (left and right ventricles,
blood, cervix, exo/endo cervix, brain, thymus, bone, ovary, testis, placenta,
uterus, bladder, adipose, aorta and vein shown in red). Gene Logic data for IL28R in human tissues showed gene expression primarily in epithelial tissue,
lymph nodes and spleen,). Tissues expressing IL-28R (shown in blue): small
intestine, ileum, jejunum, pancreas, thyroid, lymph node, gallbladder, colon,
rectum, liver, prostate, seminal vesicle, cecum, lung, skin, kidney, spleen,
stomach, skeletal muscle, bronchus, breast, heart, oesophagus, adrenal gland,
fallopian tube.

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A – Gene Logic Normal Pathology: 225669_at(HG-U133_Plus_2): TIG1823(IFNAR1)

Figure 5.2 A: Gene Logic graph showing IFNAR1 expression in a range of human cell types and tissues
Affymetrix data retrieved from a database of human gene expression data across a range of human cell types and tissues using the bioinformatics
tool Gene Logic. Tissues highlighted in blue show significant expression and tissue highlighted in red insignificant expression.

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Chapter 5

B – Gene Logic Normal Pathology: 244261_at(HG-U133_Plus_2): TIG45563(IL-28R)

Figure 5.2 B: Gene Logic graph showing IL-28R expression in a range of human cell types and tissues
Affymetrix data retrieved from a database of human gene expression data across a range of human cell types and tissues using the bioinformatics
tool Gene Logic. Tissues highlighted in blue show significant expression and tissue highlighted in red insignificant expression.

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C – Gene Logic Normal Pathology: 209575_at(HG-U133_Plus_2): TIG1871(IL-10RB)

Figure 5.2 C: Gene Logic graph showing IL-10RB expression in a range of human cell types and tissues
Affymetrix data retrieved from a database of human gene expression data across a range of human cell types and tissues using the bioinformatics
tool Gene Logic. Tissues highlighted in blue show significant expression and tissue highlighted in red insignificant expression.

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5.4 Inflammatory cell microarray screen
In order to investigate the expression of IL-28R in immune and inflammatory
cells in more detail we looked at mRNA extracted from a panel of human cells(Figure 5.3). The graph demonstrates the distribution of IL-28R on a panel ofcells both with and without a variety of inflammatory stimuli. The data reveal that
IL-28R is highly expressed on stimulated and untreated B cells and alveolar
macrophages. In non-alveolar macrophages only those stimulated for 24 hours
with immune complex (IgG coated beads) showed significant IL-28R
expression. Unstimulated pDCs have a higher level of IL-28R expression thanunstimulated mDCs. Stimulated and resting CD8+ T cells show low levels of IL28R expression. Similarly resting PBMCs express IL-28R at low levels while
CD4+ T cells and mast cells do not significantly express IL-28R.

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Figure 5.3: GSK Inflammatory cell screen showing IL-28R gene expression
Inflammatory cell screen: B cells were unstimulated or stimulated with CD40 ligand or anti B cell receptor (anti-IgM) co-stimulation assay at fourtime points; 0, 24, 48 and 72 hours. Macrophages were cultured with vehicle alone, TNF (10ng/mL), LPS (10ng/mL), immune complex (IgG coatedbeads) and cytomix (TNF (10ng/mL), LPS (10ng/mL) and IFNγ (10ng/mL) for 2, 6 and 24 hours. T cells treatments were CD4+ and CD8+ cells
resting; 1, 6 and 24 hours post anti-CD3/CD28. Mast cells were cultured with human stem cell factor (100ng/mL), human IL-6 (50ng/mL) and IL-10(10ng/mL), then primed for 6 days with human IL-4 (10ng/mL), human myeloma IgE, lambda (1µg/mL) and human myeloma IgE, kappa (1µg/mL).
Cells were triggered for 1 hour with anti-IgE (1.5µg/mL), control with no triggering. pDCs and mDCs; no treatment. Numbers in brackets indicate
number of replicates.

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5.5 Discussion
IL-28R gene expression was shown in a panel of mouse tissues using real-time
PCR (Figure 5.1). High levels of IL-28R gene expression were seen in
mandibular and messenteric lymph nodes and gut tissues (stomach,
duodenum, jejunum, ileum and colon). Expression was also detected in
epididymis, spleen, thyroid, kidney, lung, pancreas, prostate, oesophagus,
ovaries, peripheral nerve and pituitary gland. Tissues with minimal expression
were: liver, bone marrow, adrenals, heart, seminal vesicles and cerebellum.
Tissues with no detectable expression were: aorta, bladder, eyes, harderian
gland, skeletal muscle, skin and spinal cord.
The distribution of IL-28R, IFNAR1 and IL-10RB expression in human tissues
was shown by mRNA expression profiles in the Affymetrix datasets.
Whilst type I IFN receptor and IL-10RB are expressed on virtually all cell types,
type III IFN receptor expression exhibits more restricted cellular distribution.
Type III IFN receptor is expressed primarily in epithelial tissue, lymph nodes
and spleen, tissues expressing IL-28R in detail were: small intestine, ileum,jejunum, pancreas, thyroid, lymph node, gallbladder, colon, rectum, liver,prostate, seminal vesicle, cecum, lung, skin, kidney, spleen, stomach, skeletal
muscle, bronchus, breast, heart, oesophagus, adrenal gland, fallopian tube.
Patterns of IL-28R gene expression in mouse tissues (summarised in Figure5.1) were compared with those found in human tissues (illustrated in Figure 5.2
B). In both human and mouse high levels of IL-28R was expressed in lymph
nodes, spleen and gut epithelial tissues, low levels of IL-28R were seen in brain
and bone marrow, a notable difference in IL-28R expression between humanand mouse was in liver where the levels in human were a lot higher than inmouse (mouse expression levels of IL-28R were low). This was also shown in
Chapter 6 where compared with human liver, mouse liver was found to havevery restricted IL-28R staining (mainly in Kupffer-like cells). The tissues above
are complex in nature and contain a wide variety of cell types –some of thesewere investigated further in an inflammatory cell microarray screen (Figure 5.3)
and immunohistochemistry was carried out on various tissues (Chapter 6) to try
and identify specific cell types which express the IL-28R.

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An inflammatory cell microarray screen was used to investigate the expressionof IL-28R in human immune and inflammatory cells. Data from this screen
showed that IL-28R is highly expressed on stimulated and untreated B cells andalveolar macrophages. In non-alveolar macrophages only those stimulated for
24 hours with immune complex (IgG coated beads) showed significant IL-28R
expression. Unstimulated pDCs have a higher level of IL-28R expression thanunstimulated mDCs. Stimulated and resting CD8+ T cells show low levels of IL28R expression. Similarly resting PBMCs express IL-28R at low levels while
CD4+ T cells and mast cells do not significantly express IL-28R140. While type I
IFN receptors are expressed on virtually all cell types, results described aboveshow that type III IFN receptor expression exhibits a more restricted cellular
distribution.

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6. Distribution of IL-28R, protein expression
6.1 Introduction
The aim of this chapter was to study the expression of IL-28 receptor (IL-28R) ina panel of mouse/human tissues and cells in order to identify type III IFN
targeted tissues and cells. Tissues and cells containing IL-28R were identified
using immunohistochemistry (IHC), dual staining IHC methods and FLOW.
The heterodimeric receptor IFNAR1/2 for IFNα and IFNβ is present on all
nucleated cells72. IL-10R2 is ubiquitously expressed73, whereas initial RNA
expression data showed IL-28R is limited to specific tissues and cell types3. IL28R has been shown to be present in intestinal epithelial cells 56,6,141, MCA205,
a fibrosarcoma cell line142 and type III IFN expression has been shown inmonocyte–derived dendritic cells (MDDC)74,75,76, plasmacytoid dendritic cells(pDC)74,76 and human primary macrophages where induction of type III IFNs
required pre-treatment with IFNα74,75,76.

6.2 Immunohistochemistry for IL-28R protein expression inmurine lymphoid and epithelial tissues
Positive IL-28R expression in mouse tissues (summarised in Table 6.1 andillustrated in Figure 6.2 A-H). Tissue type was confirmed /scored by peer review
from two pathologists Dr Rob Goldin and Dr Chris Clarke. IL-28R was found to
be widely expressed in epithelial tissues such as stomach, small and large
intestine where baso-lateral staining of the epithelial cells and strongly staining
individual cells was found in the lamina propria. In lymphoid tissue and spleen
approximately 30% of cells visibly expressed IL-28R. This was confirmed byflow cytometry analysis on mouse spleen showing that ~60% of spleen cells
stained positively for the IL-28R (Figure 6.1).

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Figure 6.1: Flow cytometry showing IL-28R expression in mouse spleen
Analysis of a murine spleen sample using IL-28R antibody by flow cytometry. A shows
normal scatter plot for treated cells, B shows normal scatter plot for control. SS = side
scatter and FS = forward scatter. C shows positive cells beyond negative point asshown in D. D = negative. (F = negative cells, G = positive cells) FL2 log shows PE-IL28R.

In the spleen IL-28R positive cells were distributed throughout the red and white
pulp but predominately in the red pulp, where antigen-presenting andphagocytic cells such as dendritic cells and macrophages are concentrated. In
lymph nodes IL-28R expression was shown throughout the cortex and medullawith notable presence in the sub-capsular sinus. The sub-capsular sinus area isthe receiving area for afferent (incoming) lymph and is populated by 'activated'
dendritic cells from stimulated regional tissues. In the mouse liver, scattered
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Chapter 6
non-parenchymal cells lining the hepatic sinusoids express IL-28R; these arelikely to be Kupffer cells or stellate cells.
The following mouse tissues showed no observable IL-28R protein expression:
adrenal gland, bladder, brain, eyes, harderian gland, heart, lungs, peripheral
nerve, pituitary, prostate, seminal vesicles, skeletal muscle, skin, salivary
glands, pancreas, spinal cord, testis, tongue and trachea.

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Table 6.1: Location of IL-28R protein expression in mouse tissues
TissuePositive staining*

Likely Cell type

Likely background stain**

StomachOccasional interstitial cell ‘endocrine’ granular cells in basal area

macrophage

Glandular epithelial cells

DuodenumOccasional cell in lamina propria

macrophage-

ThymusScattered cells throughout cortex and medulla

dendritic cell/ macrophage

Gall bladderOccasional cell in subepithelial lamina propria

Liver

Occasional small cells with oval nuclei, sinusoidal spaces

Kupffer cell-

Epididymis

Occasional small interstitial cell

macrophageepithelium

KidneyRare interstitial cell in cortex

macrophage-

UterusOccasional cell with positive cytoplasmic granules and small non-granlular

mast cells-

dendritic cell/ macrophage--cells – subepithelial and myometrium
SpleenScattered cells throughout red pulp and white pulp/PALS

Large & small intestine

Occasional cell in lamina propria

Peyer’s patches

Occasional cell

dendritic cell/ macrophage

Blood

Occasional cell

dendritic cell/ macrophage--* Typically represented by sharply-defined, intense cytoplasmic/membrane staining. ** Typically represented by pale ‘wash’ effect

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Chapter 6

Figure 6.2 A and B: IL-28R distribution in mouse spleen using Immunohistochemistry
IHC specific staining of IL-28R is represented by sharply-defined, intense cytoplasmic/membrane staining in a selection of mouse tissues.
A Spleen goat IgG negative control. B Spleen showing scattered positive cells throughout the marginal zone.

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Chapter 6

Figure 6.2 C and D: IL-28R distribution in mouse thymus and mesenteric lymph node using Immunohistochemistry
IHC specific staining of IL-28R is represented by sharply-defined, intense cytoplasmic/membrane staining in a selection of mouse tissues.
C Thymus: scattered cells throughout cortex D Mesenteric lymph node.

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Chapter 6

Figure 6.2 E and F: IL-28R distribution in mouse liver using Immunohistochemistry
IHC specific staining of IL-28R is represented by sharply-defined, intense cytoplasmic/membrane staining in a selection of mouse tissues.
E Liver goat IgG negative control. F Liver: occasional small cells stained.

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Chapter 6

Figure 6.2 G and H: IL-28R distribution in mouse colon using Immunohistochemistry
IHC specific staining of IL-28R is represented by sharply-defined, intense cytoplasmic/membrane staining in a selection of mouse tissues.
G Colon: goat IgG negative control. H Colon: cells stained at base of crypt and non-specific staining of the brush border.

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Chapter 6

6.3 Toluidine blue histochemical stain in mouse showed mast cells express IL-28R
In the uterus, IL-28R staining was found in cells with granular cytoplasm which stained positively for the mast cell stain toluidine blue
on serial sections.

Figure 6.3: IL-28R distribution in mast cells
Mouse uterus A IL-28R staining in granular cells these were confirmed to be mast cells with a serial section stained with toludine blue B.

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Chapter 6

6.4 Dual staining- IL-28R and macrophage markers
The distribution of IL-28R staining in mouse tissues suggested expression of the IL-28R in macrophages and dendritic cells. Mouse
monoclonal antibodies Mac 384 and F4/80 were used for macrophage identification. Dual staining (illustrated in Fig. 6.4) revealed thata sub-population of macrophages/DCs express IL-28R in normal mouse spleen but with a different pattern of staining in lymph node.

Figure 6.4: Dual staining
IL-28R and macrophage markers A mouse spleen stained with Mac 387 and IL-28R B mouse lymph node stained with F4/80 and IL-28R. Red
stained, Mac 387+ macrophages are predominantly in the marginal zone and cords. Cells demonstrating IL-28R staining (brown cytoplasmic) were
distributed throughout the red pulp. A subset of IL-28R positive cells stain with Mac 387 indicating IL-28R distribution on phagoctic cells; dendritic
cells and macrophages. However, in lymph node B F4/80-positive macrophages, stained with Very Intense Purple appear to be a separate
population of cells from those which stained (brown) for IL-28R.
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6.5 IL-28R protein expression in normal and diseased humantissues
Human IL-28R protein expression was determined in a selection of relevant
normal tissues and diseased tissues (Figure 6.5 A-F). In normal liver
parenchyma, cells expressing IL-28R are relatively sparse and presumed to be
Kupffer cells and some macrophages. In contrast, the number of IL-28R
expressing cells in hepatitis C infected liver are increased, particularly aroundinflammatory infiltrates and portal areas. In addition to the inflammatory cells
there appears to be low level expression of IL-28R in some hepatocytes. In fatty
liver IL-28R staining was seen mainly at the edge of the cell membranes and insinusoidal cells presumed to be Kupffer cells and macrophages. In a section ofwell differentiated hepatocellular carcinoma, IL-28R expression was observed inlarge pleomorphic cells of uncertain origin which may be mega macrophages. In
ileal sections most of the positive IL-28R staining was within the lamina propria,
expressed by lymphocytes. There was some IL-28R expression in cells close to
the bottom of the crypt near the paneth cells. Some staining also occurred in theenterocytes but goblet cells were not involved. In sections of synovial tissue
taken from patients with rheumatoid arthritis there was increased cellularity due
to an influx of inflammatory cells. IL-28R staining is taken up by some of thespindle shaped/fibroblast like synovial cells and some macrophages.
Patterns of IL-28R expression in mouse tissues (summarised in Table 6.1 andillustrated in Figure 6.2 A-H) were compared with those found in human tissues(illustrated in Figure 6.5 A-F). Human tissues showed a similar pattern ofstaining for IL-28R in uterus, ileum and lymph nodes with predominantly
macrophages/DCs staining. Compared with human liver, mouse liver was foundto have very restricted IL-28R staining (mainly in Kupffer-like cells), while inhuman cells staining of the hepatocytes as well as macrophages/DCs wasseen. This was further enhanced in diseased tissue where there was anincreased expression of IL-28R in hepatitis, fatty liver and liver tumor tissues incomparison with normal liver.

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Chapter 6A

B

Figure 6.5 A and B: Human diseased liver and IL-28R expression using Immunohistochemistry
IHC specific staining of IL-28R in a selection of human tissues, A Normal liver showing IL-28R expression on mixed population of cells including
hepatocytes. B Hepatitis C infected liver.

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Chapter 6C

D

Figure 6.5 C and D: Human diseased liver and IL-28R expression using Immunohistochemistry
IHC specific staining of IL-28R in a selection of human tissues. C Fatty liver (macrovesicular steatosis). D Hepatocellular carcinoma.

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Chapter 6

E

F

Figure 6.5 E and F: Human ileum and synovium and IL-28R expression using Immunohistochemistry
IHC specific staining of IL-28R in a selection of human tissues, E Normal ileum. F Synovium - rheumatoid arthritis.

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Chapter 6

6.6 Discussion
While type I IFN receptors are expressed on virtually all cell types, results(Chapter 5 and 6) show that type III IFN receptor expression exhibits a more
restricted cellular distribution. Gene array data confirms that the IL-10RB
component of the receptor is ubiquitously expressed but the IL-28R component
is not. As both components are required for IFNλ signalling the distribution of
the IL-28R is likely to determine which cells or tissues respond to this class ofinterferon.
In the panel of murine tissues, immunohistochemical analysis shows that IL28R is expressed at highest levels by cells in lymph nodes and spleen. There ismoderate cellular staining in the epithelial tissue of the gastrointestinal tract andlow numbers of cells expressing IL-28R in the epididymis, uterus, thymus andkidney. Flow cytometric analysis revealed that ~60% of splenic and lymph nodecells expressed IL-28R. The pattern of staining in these tissues, particularly thestaining of cells in the sub-capsular regions of lymph nodes suggested that
antigen presenting cells express IL-28R at high density. Dual staining with Mac
387 and F4/80 illustrate that some but not all tissue macrophages express IL28R at high density. Interestingly, mast cells also appear to express IL-28R athigh density. The immunohistochemical findings are effectively replicated in the
IL-28R gene expression data (Figure 5.1). The distribution of IL-28R expression
in mouse tissues was confirmed by TaqMan® PCR.
In human tissues we first analysed the distribution of IL-28R using microarray
screens which showed a broadly similar tissue expression pattern to the mouse.
One major exception was a much greater expression in the human liver than in
the mouse. Hepatocytes were seen to express IL-28R in human tissue but notin murine tissue. A low level of IL-28R expression in mouse liver has also beenreported by other investigators78.
Although IL-28R is highly expressed by macrophages, DC and lymphocytes,
neither human nor murine bone marrow was found to express the IFNλreceptor.

This

may

have

importantconsequences

if

IFNλ

is

used

therapeutically. Up to 20% of patients treated for chronic HCV infection with
IFNα have to reduce the dose due to the consequences of bone marrow
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suppression. From our data it appears unlikely that IFNλ would have any
significant impact on bone marrow cells and therefore neutropenia andthrombocytopaenia are less likely to occur.
Analysis of IL-28R mRNA in resting and activated inflammatory cells suggeststhat the IL-28R is responsive to inflammatory stimuli in some cell types. To
some extent this is also seen in the comparison of IL-28R expression in normal
and diseased liver tissue where there is a significant increase in the number of
IL-28R expressing cells in non-alcoholic hepatitis and chronic HCV infection.
However, in these tissues it is difficult to determine whether increased IL-28R
expression is due to IL-28R induction or recruitment of IL-28R-expressing
inflammatory cells into the diseased tissue.
In summary we have demonstrated that the distribution of the IL-28R is
restricted in comparison to the IFNα receptor. Differences in receptor
expression may result in a different profile of therapeutic effects and a reductionof adverse events if patients are treated with IFNλ.
IL-28R was found to be expressed in many mouse tissues including epithelial
tissues such as stomach, and small and large intestine where there is basolateral staining of the epithelial cells and in addition, strongly staining individual
cells were found in the lamina propria. In the liver, scattered non-hepatocyte
cells lining the hepatic sinusoids appear to express IL-28R. These may be
Kupffer cells or stellate cells. In lymphoid tissue and spleen approximately 5%of cells expressed the IL-28R strongly. In the spleen these were distributed
throughout the red and white pulp. In lymph nodes these were scatteredthroughout the cortex and medulla. There was a notable presence of cells in
subcapsular sinus, this is an area of a lymph node that is the receiving area for
afferent (incoming) lymph and hence tends to be populated by 'activated'
dendritic cells from stimulated regional tissues. The distribution of staining
suggested expression of the IL-28R in macrophages and dendritic cells could
be confirmed by staining for these cells on serial sections and/or by flow
cytometry analysis of these cell types. In the uterus, staining was found in cellswith granular cytoplasm which stained positively for the mast cell stain toluidine
blue on serial sections. The distribution of IL-28R expression in human tissues
was shown by TaqMan® PCR and correlated directly with mRNA expression
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Chapter 6
profiles in the Affymetrix datasets. Gene expression analysis showed additional
tissues likely to be expressing IL-28R including lung, heart and thyroid.
Whilst type I IFN receptors are expressed on virtually all cell types (IFNαR1Gene Logic data), type III IFN receptor expression exhibits more restricted
cellular distribution. Type III IFN receptor is expressed in epithelial tissue, lymph
nodes and spleen. Macrophages and/or dendritic cells appear to express thereceptor at high levels. Preliminary evidence shows IL-28R is predominately
expressed on antigen presenting cells. If confirmed this suggests thattherapeutic manipulation of these cells may be achieved by use of IFNλ without
affecting a wide range of cell types as seen with IFNα. However none of thetissues in these experiments were stimulated or infected: IL-28R might be
inducible in other cell types and tissues that are stimulated or infected.

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Chapter 8

Chapter 7
7. Bone marrow
7.1 Introduction
Although IFN-α is a potent antiviral agent, the broad expression of the type I IFN
receptor results in responses in many organs apart from the target tissue,
leading to serious complications include the development of neutropenia andlymphopenia resulting from IFNAR1 expression in hematopoietic cells 84,
depression resulting from CNS effects83, and constitutional symptoms (fevers,
chills, myalgias). Lymphopenia, is the condition of having an abnormally low
level of lymphocytes in the blood and neutropenia is characterised by anabnormally low number of neutrophils, neutrophils account for 50-70% of
circulating white blood cells and act as the primary defence against infection,
destroying bacteria. Patients with neutropenia are more susceptible to bacterial
infections which can lead to sepsis without treatment and often results indiscontinuation of IFNα treatment.
Although IL-28R is highly expressed by macrophages, DC and lymphocytes,
neither human nor murine bone marrow was found to express the IFNλ receptor(Data from Chapter 5 and 6). The limitation of type III IFN receptor expression
suggests that some side effects may be avoided by type III IFN administration.
This may have important consequences if IFNλ is used therapeutically. Up to
20% of patients treated for chronic HCV infection with IFNα have to reduce thedose due to the consequences of bone marrow suppression. From data in
Chapters 5 & 6 it appears unlikely that IFNλ would have any significant impact
on bone marrow cells, this chapter set out to investigate this further.
Initially Professor Myrtle Y Gordon’s group and Dr Hayley Cordingley's groups
at Imperial College, London were contacted for a collaboration to look atinterferon lambdas in human bone marrow assays, the groups at Imperial wereno longer doing these assays and could not reinstate. Commercial options werealso considered but could not be funded by GSK. Through various contacts
within GSK it was found that Astra Zeneca were doing bone marrow assays
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using mouse cell lines, this was a good starting point to investigate theproperties of IL-28A and IL-28B.
Work in collaboration with David Brott, Astra Zeneca was done to look at IFNs
in murine myeloid and erythroleukemia cell lines. IL-28A and IL-28B were tested
in myeloid M1 and HCD57 erythroleukemia murine cell lines and compared to
IFNα. M1 mouse cells were used to look at differentiation into M1 macrophagelike cells (promoting a Th1 response –innate immune system) and HCD57, anerythroleukemia cell line derived from a mouse infected at birth with Friend
murine leukemia virus, the cells proliferate in response to Epo to erythrocytes(red blood cells).
IL-29 is not expressed in mice so only IL-28A and IL-28B were tested in themouse cell lines.
The mouse bone marrow data was very limited but data showed that it wasworth pursuing collaboration with a group that did bone marrow research inhumans. Human bone marrow work was performed in collaboration with
Alessandro Aiutis lab, University of Rome using a gene therapy connection.
Initially IL-28R gene expression in comparison with IFNAR was evaluated inhematopoietic stem cells and lymphoid lineages (Bone marrow derived CD34+
and

CD3+

T-cells,

CD19+

B-cells,

CD11c+

DCs

and

CD14+

monocytes/macrophage cells were purified from peripheral blood) to determine
IL-28R distribution. To determine if in vitro there was a myelosuppressive effectof IFNα or interferon lambdas IL-29, IL-28A and IL-28B, human CD34+ cells
were tested in colony forming cell (CFC) assays and using a CD34+
proliferation assay showed the viability of CD34+ cells in the presence ofinterferon lambdas and IFNα.
IL-28B was evaluated in the experiments above as it is commercially available(not the case when work was undertaken in Chapter 3 and 4) and of key
interest as 3 independent genome-wide association studies have identified
single nucleotide polymorphisms in the IL-28B gene region to be associatedwith response of patients with chronic hepatitis C to pegylated IFN-α
treatment143,100,144, showing a role for IL-28B unique to that of IL-29 or IL-28A.

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7.2 Mouse cells
The myeloid M1 cell line did not respond appropriately so only data from the
HCD57 epo-dependent erythroleukemia cell line assay is shown below.
The concentration that decreased the cell number by 50% (IC 50) was calculated
for IFNα, IL-28A and IL-28B from the data shown in Figure 7.1 and used todetermine whether a compound was a bone marrow toxicant. A compound wasdeemed positive if it had an IC50 <1µM.

Figure 7.1: Mouse bone marrow data
The values in the graph are percent of control (100 means same relative luminescence[cell number] as in the control well; 50 means 50% less relative luminescence [cellnumber] compared to the control well). From these values (triplicate wells for eachconcentration) the IC50 was calculated, IFNα is 0.04µM and IL-28A and IL-28B >2µM.

In the HCD57 epo-dependent erythroleukemia cell line assay the IC50 for IFNα
is 0.04µM or 40nM. IL-28A and IL-28B have IC50 values of >2µM (highest
concentration tested due to solubility). This data shows that IFNα has an IC50
value of <1µM which shows that it is classed as a bone marrow toxicant in the

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HCD57 erythroleukemia cell line assay. IL-28A and IL-28B was not associatedwith any toxicity at 2µM. IL-29 was not tested as it is not expressed in mouse.

7.3 Human cells - IL-28R gene expression in comparison with
IFNAR in hematopoietic stem cells and lymphoid lineages
The expression of IFNAR1 and IL-28R were tested on purified CD34+, CD3+,
CD19+, CD14+ and CD11c+ purified from healthy donors. The expression
levels for the IFNAR1 were higher than the expression of IL-28R, with CD34+,
CD3+, CD14+ and CD11c+ cells but not with CD19+ cells where receptor
expression for IL-28R and IFNAR1 were shown to be similar. IL-28R expression
was detected in very low levels in peripheral myeloid cells CD11c+ but notdetected in CD14+ cells or bone marrow derived CD34+ cells, Figure 7.2. Highlevels of IL-10R2 expression were detected in all cell types (data not shown).

0
0
0
0.05

B
M
C
D
3
4
+

G
e

P
UCB
CD34+

Figure 7.2: Human IFNαR1 and IL-28R expression
Quantitative RT-PCR analysis of IL-28R and IFNAR1 expression in humanhematopoietic stem cells and peripheral lymphoid lineages. Umbilical cord (UCB) andbone marrow (BM) CD34+ cells, peripheral blood (PB) CD3+, CD19+, CD11c+ andCD14+ cells. Gene expression data calculated as ΔCt in comparison with b-actin
housekeeping control, concentration in µM.

7.4 Colony forming capacity and proliferation of human CD34+
cells in vitro
To assess a possible myelosuppressive effect of IFNα or interferon lambdas,
human CD34+ cells were tested in colony forming cell (CFC) assays. As shownin Figure 5B, IL-29, IL-28A and IL-28B did not inhibit the capacity of BM CD34+
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Chapter 8cells to form erythroid or myeloid colonies (BFU, GM and GEMM) with theconcentrations tested. In comparison the capacity of the plated cells to
proliferate and form colonies is significantly reduced by the presence of all three

IL-28B

IFNα concentrations tested, Figure 7.3.

I
L
2
8
A

0

IL-28B

C
IL-29

B

6
0

2
0

0

I
F
N
-

Number of coloies [GM]Figure 7.3: Colony forming cell (CFC) assay
1000 BM CD34+ cells/ well after 14 days in methylcellulose with 0.03125, 0.0625 and0.125µM IL-29, IL-28A, IL-28B and IFNα stimulation. (A) BFU colonies= burst-forming
unit erythroid= erythroid progenitor cells. (B) GM colonies= granulocyte, monocyte =Page 156 of 183

Chapter 8
precursor for monoblasts and myeloblasts. (C) GEMM colonies= granulocyte,
erythrocyte, monocyte, megakaryocyte= multipotential progenitor cells.

In addition the CD34+ proliferation assay showed the viability of CD34+ cells
after cytokine stimulation is lower for IFNα compared to the interferon lambdas(Figure 7.4), this comparible to the results seen for the mouse bone marrow
data, Figure 7.1.

untreated

IFN-α

IL-29

Figure 7.4: CD34+ cells’ viability after proliferation
50,000 bone marrow CD34+ cells/ well after cytokine stimulation (with TPO, SCF, Flt3,
IL-3) and proliferation for 3 days in the presence of 0.03125, 0.0625 and 0.125µM
IFNα, IL-29, IL-28A and IL-28B.

7.5 Bone marrow cell discussion
In the murine HCD57 erythroleukemia cell line assay data showed that IFNα
has an IC50 value of <1µM which shows that it is classed as a bone marrow
toxicant in the HCD57 erythroleukemia cell line assay and IL-28A and IL-28B
show no toxicity at 2µM. IL-29 is not expressed in the mouse so work to look at
IL-29 was done in a human CD34+ assay.
Results for the IFNαR1 and IL-28R gene expression on purified CD34+, CD3+,
CD19+, CD14+ and CD11c+ cells show the expression levels for the IFNR1 ishigher in most cell types than IL-28R, including CD34+. Most importantly, IL28R expression was not detected in peripheral myeloid cells.

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Chapter 8
In vivo exposure to IFNα acting through IFNαR1 is therefore likely to have agreater effect on immune cell development and function as compared to thethree interferon lambdas IL-29, IL-28A and IL-28B. The IL-28R is not only
expressed at lower levels as compared to IFNαR1, but its expression iscompletely absent in peripheral blood myeloid cells (CD14+, CD11c+). Thisdifferential expression could contribute to a greater myeloablative action of IFNα
as compared to lambdas in vivo.
Consistently, the capacity of BM CD34+ cells to proliferate and form colonies
was severely not compromised by the presence of IFN lambdas IL-29, IL-28A
and IL-28B. But in vitro exposure to IFNα lowered the viability of CD34+ cells
after cytokine stimulation and completely abolished their colony forming
capacity. These findings are consistent with the findings that both human andmurine bone marrow only expressed IFNAR but not the IL-28 receptor, thereby
indicating an increased sensitivity of bone marrow haematopoietic stem cells to
IFNα. It can be hypothesised that IFN-α exerts an inflammatory effect also on
hematopoietic stem cells, thereby altering their quiescence state. Changes intheir cellular turnover and increased proliferation are likely to lead to an
exhaustion of their differentiation capacity. This effect might well underlie their
abolished colony formation capacity in vitro and cause a myeloablative effectafter treatment with IFNα. The conserved viability and colony forming capacity
in the presence of interferon lambdas on the other hand indicates that thisunwanted side effect could be prevented by administration of the interferon
lambdas. Although the IL-28R was found expressed by macrophages, DC andlymphocytes in the peripheral blood, its expression was lower than the IFNAR in
all cell types and comparable in B cells.

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Chapter 8

Chapter 8General Discussion
8.1 Antiviral properties of interferon lambdas
Interferon lambdas show a clear role in antiviral response, with EMCV, vesicularstomatitis virus, herpes simplex virus 1, influenza A virus, cytomegalovirus,
HIV,

HBV,

and

HCV

are

all

sensitive

totheantiviral

effectsofIFNλ136,145,57,127,2,58,51,3,146,65. Data here shows in vitro assays show that IL-28A
and IL-29 have an antiviral effect against HCV in the HCV genotype 1a and 1b
replicon systems. IFNα was shown to have ~100 times greater antiviral activity
than IL-29, and IL-29 had ~10 times greater antiviral effect in the HCV 1a and1b replicon system than IL-28A. Robek demonstrated that IL-29 and IL-28A
inhibit replication of subgenomic and full-length HCV replicons in HuH7 cells.
IFNα and type III interferons were tested in the HCV 1b replicon assay todetermine any synergistic effects of the type I and type III interferons together:results showed an additive effect not a synergistic effect, also seen with IL-29
and IFNα by Marcello et al 61. An additive effect though could show that IL-29
when used with IFNα could be good as a dual therapy as opposed to IFNα
alone. In the interferon sensitive assay, sensitivity was shown in the ISG56
assay with IL-28A and IL-29: interferon lambdas have also been shown to
induce expression of 2’5-OAS2 and MxA126. Initial data in a human HepG2 cellline stably transfected with HBV subtype ayr showed that both IL-29 and IL-28A
had antiviral effects against HBV but significantly lower in antiviral activity thanIFNα. IL-29 was shown to inhibit HBV replication in a murine model Robek51. No
antiviral effects were observed with IL-28A or IL-29 in the HIV, RSV assays or in
the dengue replicon system, Therefore, the inability of IFNλ to inhibit theseviruses may be due to the cell line having limited IL-28R distribution or theirinherent insensitivity to the antiviral effects of IFNs in general, rather than aspecific shortcoming of the IFNλ response.

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Chapter 8

8.2 Gene Expression
There are many similarities in gene modulation by type I and type III IFNs.
When looking at the genes that are expressed most highly in both the parent
HuH7 and the replicon systems IFNλs and IFNα show largely overlapping setsof interferon stimulated genes (ISGs). Although antiviral mechanisms of type I
and III differ, they may actually involve similar ISG responses. Other groups
have shown similar sets of ISGs being expressed by type I and type III
IFNs65,57,61. Our data was different to these groups in that IL-28A was also
tested in HuH7 and the replicon systems, and that parent HuH7 cells were usedin gene expression analysis. Marcello and Zhou used HCV replicon cells andDoyle used HepG2 cells for microarray analysis and all groups compared IL-29
with IFNα.
The majority of interferon stimulated genes (ISG) stimulated in the replicon cellline by IFNα, IL-28A and IL-29 are also stimulated in the parental cell line. For
the majority of genes in both the replicon and the parent datasets, the kinetics
of gene expression was the same for type I and type III IFNs. Marcello61
showed in the replicon system that the majority of type III stimulated genes
continue to increase at 24 hours and with IFNα the same genes tend to
decrease by the 24 hour time point. In contrast the data shown here
demonstrates that the kinetics of the type I and III IFNs show similar patterns ofgene expression. HCV appears to influence IFNλ induced gene expression
similar to IFNα induced gene expression. HCV replicon inhibited gene induction
by both type I and type III IFNs; this may be due to the NS3/4A protease
encoded by HCV cleaving the adaptor in the RIG-I-like receptor (RIG-I) pathway
IPS1 thus disrupting the signalling to type I IFN138; this data indicates thatsignalling to type III IFN is also disrupted. Downstream genes from RIG-I are
affected in the replicon system including MAPK genes which show lower
abundance in number in the replicon system than in the parent system.
Pathway analysis showed in the parent HuH7 cells at the earliest time point
tested, 4 hours, for type I and type III IFNs interferon signalling is the moststrongly induced pathway. At 8 hours after interferon signalling pathway, IL-29
induces immune modulation pathways such as antigen presentation pathway

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Chapter 8
and complement and coagulation cascades predominantly, compared with IFNα
mostly regulating cell signalling pathways. Interferon signalling was not
represented in the top 7 pathways by IFNα at 8 hours potentially showing that
IFNα is less specific in its signalling pathways than IL-29. This gene expression
analysis suggests that IFNλs and IFNα have primarily complementary functions
but where IL-29, by modulating alternative pathways such as the antigen
presentation and processing pathways at an early time point, may prove to be auseful therapeutic option for the management of chronic viral infection such as
HCV.

8.3 IL-28R distribution
While type I IFN receptors are expressed on virtually all cell types, results showthat type III IFN receptor expression exhibits a more restricted cellular
distribution. This is also reported by other groups showing not all cell types
respond to interferon lambdas including fibroblasts and endothelial cells13.
In the panel of murine tissues, immunohistochemical analysis shows that IL28R is expressed at highest levels by cells in lymph nodes and spleen andepithelial tissue of the gastrointestinal tract. Type III interferons have beenshown to be the main interferon giving antiviral protection of intestinal epithelial
cells against GI viruses identifying a critical role of IFN-λ in the epithelial
antiviral host defense147 and possibly maintenance of GI tract homeostasis,
linking this role to high level of IL-28R expression in gut tissue. A high level of
IL-28R on intestinal epithelial cells has been shown to be of importance.
Antiviral protection of intestinal epithelial cells against gastrointestinal viruses
mainly relies on the type III antiviral system147. This study showed mice lacking
functional IL-28R had impaired control of oral rotavirus infection, which infects
intestinal epithelial cells. Additionally it was demonstrated that systemic
administration of IL-29 not IFNα, induced an antiviral state in these cells
resulting in suppression of rotavirus replication. The immunohistochemical
findings were confirmed in the IL-28R gene expression data. The uniquefunctional tissue-specificity of IFN-λs is due to the cell type-restricted pattern of
IFN-λR1 expression it was shown here the unique of staining in these tissues,particularly the staining of cells in the sub-capsular regions of lymph nodes
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Chapter 8
suggested that antigen presenting cells express IL-28R at high density. Dualstaining with Mac 387 and F4/80 illustrated that some but not all tissue
macrophages express IL-28R at high density. Literature also shows that unlike
IFNα IFN-λR1 is primarily expressed in epithelial cells and specific subsets ofimmune cells59,57,13,148,77,79,78,80,23. In human tissues the distribution of IL-28R
using microarray screens showed a broadly similar tissue expression pattern tothe mouse. One major exception was a much greater expression in the humanliver than in the mouse. Hepatocytes were seen to express IL-28R in humantissue but not in murine tissue, this may account for the IFN-λ antiviral systemappearing to play minimal if any role in the protection of mice against
hepatotropic viruses148.
IHC data didn’t not show IL-28R in lung but stimulated alveolar macrophages
showed high gene expression of IL-28R, type III IFN system is shown to havean important role in asthma and respiratory viral infections149,140.
Neither human nor murine bone marrow was found to express the IFNλreceptor in significant levels. This may have important consequences if IFNλ isused therapeutically. Up to 20% of patients treated for chronic HCV infection
with IFNα have to reduce the dose due to the consequences of bone marrow
suppression. It appears unlikely that IFNλ would have any significant impact onbone marrow cells and therefore bone marrow suppression is less likely.
In summary the distribution of the IL-28R is restricted in comparison to the IFNα
receptor. IFN-λs have a specialized role in diseases of epithelial tissue, and in
the treatment of viral infections of these and other responsive tissues. Limited
IL-28R may explain the findings that IFN-λ independently of IFNα cannot
provide full protection against systemic virus infections; these viruses infectcells that are not responsive to type III IFNs. Restriction of IL-28R receptor
expression may result in a different profile of therapeutic effects and fewer or
milder adverse events if patients are treated with IFNλ rather than IFNα.

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Chapter 8

8.4 Bone marrow experiments
In a murine HCD57 erythroleukemia cell line assay, IFNα was classed as abone marrow toxicant while IL-28A and IL-28B were shown to not cause
toxicity. In a murine HCD57 erythroleukemia cell line assay, IFNα was classed
as a bone marrow toxicant while IL-28A and IL-28B were shown to not cause
toxicity. Consistently, the capacity of BM CD34+ cells to proliferate and formcolonies was not compromised by the presence of IFN lambdas IL-29, IL-28A
and IL-28B. But in vitro exposure to IFNα lowered the viability of CD34+ cells
after cytokine stimulation and completely abolished their colony forming
capacity. These findings are consistent with the finding that both human andmurine bone marrow only expressed IFNAR but not the IFN-λ receptor, thereby
indicating an increased sensitivity of bone marrow haematopoietic stem cells to
IFNα. The conserved viability and colony forming capacity in the presence ofinterferon lambdas, indicates that this unwanted side effect could be prevented
by administration of the latter. Although the IL-28R was found expressed bymacrophages, DC and lymphocytes in the peripheral blood, its expression was
lower than the IFNAR in all cell types and comparable in B cells. These findings
might therefore have important consequences if IFNλ is used therapeutically.
Up to 20% of patients treated with IFN-α for chronic HCV infection have to
reduce the dose due to the consequences of bone marrow suppression. Fromdata in Chapter 7 it appears unlikely that IFNλ would have any significant
impactonbonemarrowcells

andtherefore

neutropaenia

andthrombocytopaenia are less likely to occur. In support of this hypothesis phase1b data from Zymogenetics showed that repeated dosing with PEG-IFN-λ waswell tolerated with minimal constitutional symptoms and in contrast to theeffects of type I interferons, there were no significant decreases from baseline
values in neutrophil or platelet counts96,150,116.

8.5 IFNλs as a therapy
Type III interferons have been implicated as having antiviral properties in arange of viruses: DNA viruses; poxvirus55, murine cytomegalovirus (CMV)56,56,
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Chapter 8
hepatitis B virus57,51,58 and herpes simplex virus 1 and 259, the single stranded(ss) (+) RNA viruses EMCV60,3, west nile virus57 and hepatitis C virus57,61,62,51,
as well as the ss (−) RNA viruses influenza-A virus63 and vesicular stomatitis
virus,62. Chronic infection with hepatitis C virus causes approximately 350,000
deaths annually46. Pegylated interferonα (IFNα) in combination with thenucleoside analogue ribavirin is the current standard of care for the treatment ofpatients chronically infected with hepatitis C (HCV). There is a role for Interferon
lambdas in the treatment of HCV, data described here showed IL-29 and IL-28A
have an antiviral effect against HCV in the HCV genotype 1a and 1b repliconsystems. An additive effect of IFNα and IL-29 or IL-28A treatment could showthat IFN lambdas when used with IFNα could be good as a dual therapy as
opposed to IFNα alone.
The data presented shows that by modulating alternative pathways such as theantigen presentation and processing pathways at an early time point and having
a limited receptor distribution it may prove to be a superior therapeutic option forthe management of HCV chronic viral infection, causing fewer and/or milder
adverse events. Up to 20% of patients treated for chronic HCV infection with
IFNα have to reduce the dose due to the consequences of bone marrow
suppression, this data shows IFNλ does not have a significant impact on bonemarrow cells and therefore neutropaenia and thrombocytopaenia are less likely
to occur. In support of this hypothesis, phase 1b data from Zymogenetics
showed repeated dosing with PEG-IFNλ was well tolerated with minimal
constitutional symptoms and in contrast to effects of type I interferons, there
were no significant decreases from baseline values in neutrophil or platelet
counts96,116. Latest data from Bristol Myers Squibb Co. showed peginterferon
lambda achieved SVR24 rates comparable to peginterferon alpha with fewer
flu-like and musculoskeletal symptoms in phase IIb study in treatment-naïve
genotype 2 or 3 hepatitis C patients.
There is a potential role for IL-29 instead of IFNα in the treatment regime withdirect-acting antivirals (DAAs), NS3/4A protease inhibitors, telaprevir andboceprevir. With the current DAAs there is rapid resistance due to rapid
mutations of

HCV40,41,86,87.

The

current DAAs areadministeredwithpeginterferon-alfa-2a and ribavirin to prevent resistance to the DAAs. BothPage 164 of 183

Chapter 8
telaprevir and boceprevir highly improve rates of SVR of HCV infected patients
but there are limitations, designed to target genotype 1 HCV they havedifferential efficancy across the genotypes88,89,90, they are also limited by side
effects, rash (Telaprevir) and anaemia, replacement of IFNα with IL-29 could
reduce side effects caused by IFNα and may reduce side effects attributed to
the DAA as this may be exasperated by IFNα. Other HCV therapies are
currently being evaluated using co treatment of IFNα , these include RdRp
inhibitors which inhibit the active site of polymerase activity, preliminary resultsfrom Phase II trials reported rates of EVR >80% among patients with HCV
genotype 1 or 4 infection who received mericitabine in combination with SOC
PEG-IFN and RBV47; may not need the co-administration of IFNs and hostfactor cyclophilins, Alisporivir is in advanced clinical trials, it inhibits viral
replication by disrupting the interaction between cyclophilin A and NS5A 93,94.
Alisporivir combined with PEG-IFN and RBV, led to an SVR in 76% of HCV
genotype 1 infection patients compared to 55% with SOC94. There may be arole for Interferon lambdas to replace IFNα as a co treatment but the aim withthese therapies is to have an interferon free regime.
A pegylated form of IFN-λ1 (IL-29) is currently in clinical trials for the treatmentof chronic HCV infection and initial reports shows less severe side effects thanpegylated IFNα and similar antiviral activity95,96. Caution would be needed if
administrating interferon lambda with HCV/HIV co infection as the role of IFNλs
is still unclear, whilst IL-29 and IL-28A are reported to inhibit HIV-1 replication in
macrophages151 pretreatment of uninfected PBMCs or CD4+ T-cell lines with
IFN-λ improved the expression of HIV-1 receptor and co-receptors that increase
viral binding and replication130.
There may be a role for IL-28B treatment in the future, four Genome Wide
Association studies have highlighted the significance of IL-28B within the innate
immune response to HCV97,98,99,100. Two protective SNPs were shown to be
associated with a SVR to IFNα/Ribavirin in patients with HCV genotype 1. In a
study of rapid viral response (RVR) rates in patients with HCV Genotype 1 and
4, of the RVRs 100% of carriers of the protective rs12979860 C allele, and 64%
of non-RVR individuals expressed the non-protective genotype T allele of
rs8099917101.

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Chapter 8
The potential broad roles of IFN-λs in immune function may also mean they playa future role in autoimmunity and cancer therapy. Type III IFNs like type I IFNs,
may potentially be used for the treatment of other inflammatory or autoimmune
diseases such as rheumatoid arthritis (RA), systemic lupus erythematosus(SLE)102, or multiple sclerosis (MS)103, IFN-λ therapy may represent a novel
approach to prevention and/or treatment of respiratory virus-triggered asthma
exacerbations149,140. IFN-λs have been shown to have potent antitumor activities
in murine models of cancer104,105,106, highlighting potential as anti-cancer
therapy.

8.6 Future work
Further experiments could be designed looking at the effects of interferon
lambdas on antigen presenting cells, as experiments above have suggested
that the interferon lambdas not only modulate alternative pathways such as theantigen presentation and processing pathways at an early time point comparedwith IFNα but their receptor IL-28R is also found primarily on antigen presenting
cells. Maturation of dendritic cells (DCs) (generated from buffy coats) can beinvestigated by applying a fixed dose of antigen to DCs, treating the DCs with
IFNλ, IFNα and no interferon and looking at T-cell responses. The current,
immunomodulatory activities of IFNλs are still not defined and studies to dateshow opposing functions e.g. DC-mediated stimulation of either T-reg
proliferation22 or towards Th1 differentiation140. There is value in continuing tolook at the properties of IL-28A and IL-28B as well as IL-29 and look at theirbroader roles in immune function including autoimmunity and cancer therapy.

8.7 Conclusions
Interferon lambdas (IFNλs), termed IFN-λ1, IFN-λ2 and IFN-λ3, or IL-29, IL-28A
and IL-28B are a recently identified family of cytokines with antiviral activity.
Type I IFNs are used therapeutically in the treatment of chronic hepatitis B andC; however only ~30% of patients with hepatitis B virus will be successfully
treated and only ~60% of patients with chronic HCV. New interventions are
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Chapter 8
therefore required to address this unmet medical need and this thesis aimed toevaluate the potential use of IFNλs in treating viral infection.
A range of in vitro antiviral assays were developed to determine which viruses
were inhibited by IFNλs. Results showed IL-28A and IL-29 have antiviral effects
with HCV 1a and 1b replicons and HBV. No antiviral effect was demonstrated
against dengue, RSV or HIV. Gene expression stimulated by IFNλ wascompared with IFNα; and the effects of IFNλ against HCV were investigated.
The types of genes induced, and the kinetics of gene induction were similar
between the type I and type III IFNs in the HCV replicon cell line. With theparental cell line, the interferon signalling pathway was the most greatly affectedby IFNα, IL-28A and IL-29, but IL-29 strongly regulated the antigen presenting
pathway compared with IFNα. IL-28R distribution was determined to investigate
the tissue and cellular distribution of IFNλ responsive cells. IL-28R was
expressed in epithelial tissues, lymphoid tissue, spleen, liver, kidney andthymus, with majority of IL-28R expression on macrophages and dendritic cells.
In mouse HCD57 erythroleukemia cell line assay, IFNα was classed as a bonemarrow toxicant and IL-28A and IL-28B were shown to not cause toxicity.
Human BM CD34+ cells ability to proliferate and form colonies was notcompromised by the presence of IFN lambdas IL-29, IL-28A and IL-28B whilst
IFNα completely abolished their colony forming capacity. Human and murinebone marrow only expressed IFNAR but not the IL-28 receptor, thereby
indicating an increased sensitivity of bone marrow haematopoietic stem cells to
IFNα. The conserved viability and colony forming capacity in the presence ofinterferon lambdas, indicates that this unwanted side effect could be prevented
by administration of the latter.
These findings might therefore have important consequences if IFNλ is usedtherapeutically. Up to 20% of patients treated with IFNα for chronic HCV
infection have to reduce the dose due to the consequences of bone marrow
suppression. From our data it appears unlikely that IFNλ would have any
significant impact on bone marrow cells and therefore neutropenia andthrombocytopenia are less likely to occur. In support of this hypothesis phase1b data from Zymogenetics showed that repeated dosing with PEG-IFN-λ waswell tolerated with minimal constitutional symptoms and in contrast to the
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Chapter 8
effects of type I interferons, there were no significant decreases from baseline
values in neutrophil or platelet counts53, 63.

In summary differences in receptor expression and gene expression compared
to IFNα may result in a different profile of therapeutic effects and adverse
events if patients are treated with IFN-λ.

Page 168 of 183

Appendix I
A data CD containing Affymetrix gene chip raw data is enclosed.

Appendix II Suppliers
Below are listed the names and contact details of most suppliers or materials
and reagents used in this study.
Abcam

www.abcam.com

Affymetrix

www.affymetrix.com

Agilent

www.agilent.com

AllCells

www.allcells.com

Analytix

www.analytix.co.uk

Applied Biosystems

www.appliedbiosystems.com

Becton Dickinson

www.bdbiosciences.com

Bio-Radwww.bio-rad.com

Capralogics

www.capralogics.net

Corbett Life Science

www.corbettlifescience.com

Dako

www.dako.com

Eppendorf

www.eppendorf.co.uk

Fluka

www.sigmaaldrich.com/Fluka

Gene Logic Inc.

www.genelogic.com

Gibco

www.invitrogen.com

IKA

www.ika.com

Ingenuity Inc.

www.ingenuity-inc.org

Invitrogenwww.invitrogen.com

Kbioscience

www.kbioscience.co.uk

Life Technologies

www.lifetechnologies.com

Lonza

www.lonza.com/research

Merck, Sharpe and Dohme

www.msd-uk.com

Miltenyi Biotec

www.miltenyibiotec.com

Molecular devices

www.moleculardevices.com

Novagenwww.merckmillipore.com/novagen

Nunc

www.nuncbrand.com

PBL

www.interferonsource.com

Proligowww.sigmaaldrich.com

Page 169 of 183

Promega

www.promega.com

Qiagenwww.qiagen.com

R&D systems

www.rndsystems.com

Sigma-Aldrich

www.Sigma-Aldrich.com

Syngenewww.syngene.com

Thermo Shandon

www.thermoscientific.com

Tree Star

www.treestar.com

Vector Labratories

www.vectorlabs.com

Virostatwww.virostat-inc.com

Page 170 of 183

Appendix III Publications
TALKS:
Rhiannon Lowe Talk entitled ‘Use of IHC to show distribution of IL-28R’. 9th European
Histopathology Forum (19-21st April 2010) - Stratford on Avon. Awarded best new
speaker award.
PUBLICATIONS:
Jaimini Mistry, Rhiannon Lowe, Christian Weise, Mikala Skydsgaard and Zuhal
Dincer.Morphometric assessment of minipig skin thickness in relation to age, sex andanatomical location using a computerised system. 8th European Histopathology Forum(20th - 22nd April 2009) - Stratford on Avon
Coelho A-M, Lowe R.M. (May 2008) Analysing the phenotype and function ofregulatory T cells (EuroSciCon meeting) meeting report. Immunology News, 2008 15.2,
pp. 33-36.
Lowe R Toll-like receptors - Investigating innate immunity & infection meeting report.
Nov 2007 Immunology News.
Lowe R; Morley P; Simecek N; Scott L; Thursz M. (Aug 2007). Microarray comparisonof type I and type III interferons: Superior therapeutic profile for IL-29? J INTERFCYTOK RES. 27:733-733.
Lowe R; Morley P; Scott L; Simecek N; Thursz M. (Aug 2007). HCV replicon inhibits
gene induction by type III interferons. J INTERF CYTOK RES. 27:732-733.
Lowe RM; Fung SSL; Clarke CJ; Thursz MR. (Aug 2007). Distribution of the type III
interferon receptor. J INTERF CYTOK RES. 27:732-732.
Claire J. Weekes, Gino Brunori, Tracy M. Walker, Rhiannon M. Lowe, Angela T.
White, Joel D. Parry. Mitochondrial toxcitiy of nucleoside analogoues and theapplication of real-time PCR. Int Cong Drug Therapy HIV 2004 Nov 14-18;7:Abstract
No. P185
W Wu*, S E Wildsmith, A J Winkley, R Yallop, F J Elcock, P J Bugelski.
Chemometric strategies for normalisation of gene expression data. Analytica
Chimica Acta Mar 2001.
SE Wildsmith, R Yallop, P Bugelski, G Morgan. EP1101114B-Method of Protein
Analysis. Patent filed July 1999, Granted in Europe July 2005.
M Thursz, R Yallop, R Goldin, C Trepo, HC Thomas. Influence of MHC class II
genotype on outcome of infection with hepatitis C virus. Lancet. 354(9196): 2119-24,
1999 Dec 18-25.

Page 171 of 183

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