NF-kappaB in Neuroinflammation - Research Explorer

NF-kappaB in Neuroinflammation

A Thesis submitted to The University of Manchester for the degree of Doctor of

Philosophy in Systems Biology, in the Faculty of Life Sciences.

2014

Nisha Patel


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Contents

Contents ................................................................................................................................. 2

List of Figures ...................................................................................................................... 10

List of Tables........................................................................................................................ 14

List of Abbreviations............................................................................................................ 15

Abstract ................................................................................................................................ 18

Declaration ........................................................................................................................... 19

Copyright Statement ............................................................................................................ 19

Acknowledgements .............................................................................................................. 20

1. Introduction ...................................................................................................................... 21

1.1. General Considerations ............................................................................................. 22

1.1.1. Neuroinflammation ............................................................................................ 22

1.1.2. Microglia ............................................................................................................ 23

1.1.3. Neural Progenitor Cells ...................................................................................... 25

1.1.4. Microglial and Neural Progenitor Cell Interactions ........................................... 26

1.2. The Nuclear Factor KappaB (NF-κB) Signalling Pathway....................................... 27

1.2.1. Overview of NF-κB Signalling .......................................................................... 27

1.2.2. Overview of the Structure and Function of NF-κB Pathway Components ........ 29

1.2.2.1. Rel Proteins ................................................................................................. 29

1.2.2.2. Inhibitor KappaB (IκB) Proteins ................................................................. 30

1.2.2.2.1. IκBα and IκBε in NF-κB Activation .................................................... 31

1.2.2.3. Inhibitor KappaB Kinase (IKK) Complex .................................................. 32

1.2.2.3.1. IKK Complex Components and Formation ......................................... 32

1.2.2.3.2. IKK Complex Activation ..................................................................... 33

1.2.3. Canonical Activation of NF-κB Pathway .......................................................... 34

1.2.3.1. TNFα Structure ........................................................................................... 34


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1.2.3.2. TNFR Structure and Function ..................................................................... 35

1.2.3.3. TNFR1 Signalling ....................................................................................... 36

1.2.3.3.1. Induction of Apoptosis ......................................................................... 37

1.2.3.4. TNFR2 Signalling ....................................................................................... 38

1.2.4. NF-κB Dynamics and Function ......................................................................... 39

1.2.5. Regulation of NF-κB Transcriptional Activity .................................................. 41

1.2.5.1. Atypical IκB Proteins .................................................................................. 41

1.2.5.1.1. B-cell Lymphoma-3 (Bcl-3) ................................................................. 41

1.2.5.1.2. IκBζ ...................................................................................................... 42

1.2.5.1.3. IκBδ ...................................................................................................... 42

1.2.5.2. IKKα and IKKβ ........................................................................................... 43

1.2.5.3. Other Factors influencing NF-κB Transcription. ........................................ 43

1.2.6. Termination of the NF-κB Response ................................................................. 44

1.2.6.1. TNFα-induced Protein 3 (A20) ................................................................... 44

1.2.6.2. Cylindromatosis (CYLD) ............................................................................ 45

1.3. NF-κB in the Central Nervous System (CNS) .......................................................... 46

1.3.1 Overview of NF-κB Components in the CNS .................................................... 46

1.3.2. NF-κB Function in the CNS ............................................................................... 47

1.3.3. NF-κB Activation in Microglia and Neural Progenitor Cells ............................ 49

1.4. Thesis Aims ............................................................................................................... 50

2. Materials and Methods ..................................................................................................... 52

2.1. Materials .................................................................................................................... 53

2.1.1. Reagents ............................................................................................................. 53

2.1.2. Vectors ............................................................................................................... 53

2.1.2.1 Luciferase Construct .................................................................................... 53

2.1.2.2 Fluorescent Fusion p65 Constructs .............................................................. 53


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2.2. Methods ..................................................................................................................... 54

2.2.1. Propagation of Vectors ....................................................................................... 54

2.2.2. Cell Culture ........................................................................................................ 54

2.2.2.1. Cell Lines and Culture Maintenance ........................................................... 54

2.2.2.2. Long-term Storage of Cell Lines ................................................................ 55

2.2.2.3. Thawing Cells from Frozen Stocks ............................................................. 55

2.2.2.4. Cell Enumeration ........................................................................................ 55

2.2.2.5. Plating Cells for Experiments ..................................................................... 55

2.2.2.5.1. Plating Cells for Live Cell and Endpoint Luminometry ...................... 56

2.2.2.5.2. Plating Cells for Cell Viability and Apoptosis Assays with Inhibitor

Treatment ............................................................................................................. 57

2.2.3. Treatment of Cells with TNFα ........................................................................... 57

2.2.4. Transfections and Transductions ....................................................................... 57

2.2.4.1. Plasmid Transfections ................................................................................. 57

2.2.4.2. BAC Transfections ...................................................................................... 57

2.2.4.3. Lentiviral Transductions ............................................................................. 57

2.2.5. Luminometry ...................................................................................................... 58

2.2.5.1. Live Cell Luminometry ............................................................................... 58

2.2.5.2. Endpoint Luminometry ............................................................................... 58

2.2.6. Live Cell Imaging .............................................................................................. 58

2.2.6.1. Analysis of Live Cell Imaging Experiments ............................................... 59

2.2.7. Western Blotting ................................................................................................ 59

2.2.7.1. Sample Preparation ..................................................................................... 59

2.2.7.2. Preparation of Gels for SDS Polyacrylamide Gel Electrophoresis (PAGE)

.................................................................................................................................. 59

2.2.7.3. Protein Separation by SDS-PAGE .............................................................. 60

2.2.7.4. Transfer of Protein to Nitrocellulose Membrane ........................................ 60


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2.2.7.5. Immunostaining of Nitrocellulose Membrane ............................................ 60

2.2.7.6. Relative Quantification of Proteins ............................................................. 61

2.2.8. Cell Viability ...................................................................................................... 61

2.2.8.1. Analysis of Cell Viability Data ................................................................... 62

2.2.9. Apoptosis Assays ............................................................................................... 62

2.2.9.1. Analysis of Apoptosis Data ......................................................................... 63

2.2.10. Flow Cytometry ............................................................................................... 63

2.2.10.1. Sample Preparation and TNFR1-Labelling ............................................... 63

2.2.10.2. Flow Cytometry Data Analysis ................................................................. 63

2.2.11. Enzyme-linked Immunosorbent Assay (ELISA) ............................................. 64

2.2.12. NanoString ....................................................................................................... 65

2.2.12.1. Sample Preparation ................................................................................... 65

2.2.12.2. NanoString Measurements ........................................................................ 65

2.2.12.3. NanoString Data Analysis ......................................................................... 65

2.2.13. Quantitative-Polymerase Chain Reaction (Q-PCR) ......................................... 66

2.2.13.1. Sample Preparation ................................................................................... 66

2.2.13.2. Q-PCR Analysis ........................................................................................ 66

2.2.13.3. Analysis of Q-PCR Results ....................................................................... 67

3. Establishing and Characterising a Model System for the Study of NF-κB in C17.2 and

BV.2 Cells ............................................................................................................................ 69

3.1. General Introduction ................................................................................................. 70

3.2. Results ....................................................................................................................... 71

3.2.1. Analysis of NF-κB Function and Dynamics in a Neural Progenitor Cell Line . 71

3.2.1.1. Creating C17.2 Reporter Cell Lines for Observation of p65 Dynamics ..... 71

3.2.1.2. Single-cell p65 Dynamics in C17.2 Reporter Cell Lines ............................ 71

3.2.1.3. Population-level NF-κB Activation in C17.2 Cell Lines ............................ 76


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3.2.1.3.1. Analysis of NF-κB Transcriptional Activity in the Differentially

Transfected C17.2 cells ........................................................................................ 76

3.2.1.3.2. TNFα-induced IκBα Degradation Profiles in C17.2 Cell Lines .......... 79

3.2.1.3.3. NF-κB-dependent Gene Expression Changes in TNFα Stimulated Cells

.............................................................................................................................. 83

3.2.1.3.4. Basal p65 and IκBα Expression in C17.2 Cell Lines ........................... 86

3.2.2. Investigating NF-κB Dynamics in the BV.2 Cell Line ...................................... 88

3.2.2.1. Creating BV.2 Reporter Cell Lines for Observation of p65 Dynamics ...... 88

3.2.2.2. Single-cell p65 Dynamics ........................................................................... 89

3.2.2.3. Population-level NF-κB Activation in BV.2 Cell Lines ............................. 90

3.2.2.3.1. TNFα-induced IκBα Degradation Profiles in BV.2 Cell Lines ............ 90

3.2.2.3.2. NF-κB-dependent Gene Expression Changes in TNFα Stimulated

BV.2 Cell Lines .................................................................................................... 92

3.2.2.3.3. Basal p65 and IκBα Expression in BV.2 Cell Lines ............................ 94

3.3. Discussion ................................................................................................................. 95

3.3.1. NF-κB Activation in C17.2 Cells ....................................................................... 95

3.3.1.1. Single-Cell p65 Dynamics in C17.2 Cells .................................................. 96

3.3.1.2. NF-κB-dependent Gene Expression ............................................................ 96

3.3.2. NF-κB Activation and p65 Dynamics in p65-BAC Stable C17.2 Clones ......... 97

3.3.3. NF-κB Activation in BV.2 (UT) Cells ............................................................... 98

3.3.3.1. IκBα Degradation in BV.2 (UT) Cells ........................................................ 98

3.3.3.2. NF-κB-dependent Gene Expression ............................................................ 98

3.3.4. Discussion of Problems with using Lentivirally Transduced Cell Lines ........... 99

3.3.4.1. General Problems with p65 Overexpression ............................................... 99

3.3.4.2. Choice of C17.2 (lenti) as a Model System and Potential Problems ........ 100

3.3.4.3. Choice of BV.2 (lenti) as a Model System and Potential Problems ......... 101


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4. NF-κB Activation and Dynamics in C17.2 and BV.2 Cells in Mono-cultures and Co-

cultures ............................................................................................................................... 103

4.1. General Introduction ............................................................................................... 104

4.2. Results ..................................................................................................................... 104

4.2.1. NF-κB Dynamics and Activation in C17.2 Cells ............................................. 104

4.2.1.1. Single-cell p65 Dynamics in Mono-cultures and 1:1 Co-cultures ............ 104

4.2.1.2. NF-κB Activation in Co-cultured Wild-type C17.2 Cells ........................ 107

4.2.2. Single-cell p65 Dynamics in BV.2 Cells, in Mono-cultures and 1:1 Co-cultures

.................................................................................................................................... 116

4.2.3. TNFα availability in Mono- and Co-cultures. .................................................. 121

4.2.4. TNFR1 Expression in Unstimulated and TNFα-stimulated C17.2 cells, in

Mono-cultures and Co-cultures. ................................................................................. 122

4.3 Discussion ................................................................................................................ 126

4.3.1. NF-κB in Mono-cultured and Co-cultured C17.2 ............................................ 127

4.3.1.1. TNFα-induced Single-cell p65 Dynamics in C17.2, in Mono-cultures and

1:1 BV.2 Co-cultures ............................................................................................. 127

4.3.1.2. Population-level NF-luc Induction in C17.2, in Mono-cultures and Co-

cultures ................................................................................................................... 127

4.3.2. Single-cell p65 Dynamics in Mono-cultured and Co-cultured BV.2 ............... 129

5. Analysis of Co-culture- and TNFα-induced Gene Expression Changes........................ 130

5.1 General Introduction ................................................................................................ 131

5.2 Results ...................................................................................................................... 132

5.2.1. Gene Expression in Untreated C17.2 and BV.2 Mono-cultures ...................... 133

5.2.2. TNFα-induced Changes in Gene Expression at 230 min Post-TNFα-Stimulation

.................................................................................................................................... 134

5.2.3. TNFα and Co-culture-induced Gene Expression Changes at 230 min Post-

TNFα Stimulation ...................................................................................................... 136

5.2.4. Co-culture-induced Gene Expression Changes, 28 h after Co-culturing ......... 138


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5.2.5. TNFα-induced Changes in Gene Expression at 24 h Post-TNFα-Stimulation 138

5.2.6. TNFα and Co-culture-induced Gene Expression Changes at 24 h Post-TNFα-

Stimulation ................................................................................................................. 140

5.2.7. Co-culture-induced Gene Expression Changes, 48 h after Co-culturing ......... 142

5.3 Discussion ................................................................................................................ 143

5.3.1. Potential NF-κB-mediated Interactions between C17.2 and BV.2 .................. 144

5.3.2. Future Experiments .......................................................................................... 146

6. Effects of TNFα and NF-κB Activity on Neural Progenitor Cells and Microglia ......... 148


6.2. Results ..................................................................................................................... 150

6.2.1. Effects of TNFα on Cell Viability and Apoptosis............................................ 150

6.2.2. Effects of C17.2- BV.2 Interactions on 1:1 Co-culture Viability and Apoptosis

.................................................................................................................................... 155

6.2.3. Pyrollidine Dithiocarbamate-induced NF-κB Inhibition ................................. 159

6.2.4. Effects of NF-κB Inhibition on Untreated and TNFα-treated Mono-cultures and

1:1 Co-cultures ........................................................................................................... 161

6.2.5. Effects of C17.2-BV.2 Interactions on Cell Viability in 1:1 Co-cultures ........ 165

6.3 Discussion ................................................................................................................ 169

6.3.1. Effects of TNFα on C17.2 and BV.2 Mono-cultures ....................................... 170

6.3.2. Effects of NF-κB Inhibition on C17.2 and BV.2 Mono-culture and 1:1 Co-

culture Viability ......................................................................................................... 172

6.3.3. C17.2-BV.2 Interactions in 1:1 Co-cultures .................................................... 173

7. Discussion ...................................................................................................................... 176


7.2. NF-κB Activation and p65 Dynamics in C17.2 cells .............................................. 178

7.3. NF-κB Dynamics to Cell Survival .......................................................................... 180

7.3.1. BV.2 Prevents TNFα-induced C17.2 Apoptosis .............................................. 180


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7.3.2. NF-κB Inhibition in Mono-cultures Induces C17.2 Apoptosis and Increases

Viability ..................................................................................................................... 183

7.3.3. TNFα-induced BV.2 p65 Dynamics ................................................................ 184

7.4. Future Experiments ................................................................................................. 186

7.5. Concluding Remarks ............................................................................................... 188

References .......................................................................................................................... 190

Word Count: 51,094


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List of Figures

1.1: An overview of the TNFα-induced canonical NF-κB activation pathway…………...28

1.2: The structure and composition of NF-κB family members. ………………………….29

1.3: The structure and composition of key IκB family members………………………….31

1.4: The structure and composition of the main IKK complex constituents……………....33

2.1: TNFR1-phycoerythrin and eGFP fluorescence of lentivirus transduced C17.2 and

BV.2 mono-cultures and 1:1 co-cultures……………………………………………..……64

3.1: Expression of p65 fluorescent fusion proteins in C17.2 cells……………………...…72

3.2: TNFα-induced p65 localisation in C17.2 cells transfected or transduced with different

p65 constructs……………………………………………………………………...………72

3.3: Quantification of nuclear p65 fluorescence in different C17.2 cell populations after

TNFα stimulation………………………………………………………………………….74

3.4: TNFα-induced p65 nuclear translocation profiles obtained from C17.2 cell

populations…………………………………………………………………….…………..75

3.5: Dose-dependent NF-κB activation in differentially transfected / transduced C17.2

cells………………………………………………………………………………..……….77

3.6: Comparison of NF-luc induction, after TNFα stimulation, in C17.2 cell

populations……………………….………………………………………………………..78

3.7: Comparison of basal luminescence of NF-luc transfected C17.2 cell

populations……………………………………………………………...………………....78

3.8: Western blot analysis of IκBα levels in wild type C17.2 cells after TNFα

stimulation………………………………………………………..………………………..80

3.9: Western blot analysis of IκBα levels in lentivirus transduced C17.2 cells after TNFα

stimulation…………………………………………………………………………………81

3.10: Western blot analysis of IκBα levels in BAC clone A cells after TNFα

stimulation………………………………………………………………………………....82

3.11: Western blot analysis of IκBα levels in BAC clone 5 cells after TNFα

stimulation…………………………………………………………………………………83

3.12: NF-κB-dependent gene expression changes in C17.2 cell populations after TNFα

stimulation…………………………………………………………..……………………..84

3.13: Basal expression of NF-κB-dependent genes in C17.2 cell populations……………86


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3.14: Comparison of p65 protein levels in C17.2 cell populations………………………..87

3.15: Comparison of IκBα protein levels in unstimulated C17.2 cell populations………..88

3.16: Expression of p65-eGFP in lentivirus transduced BV.2 cells…………………….....89

3.17: TNFα-induced p65 translocation in lentivirus transduced BV.2 cells………………89

3.18: Analysis of p65 dynamics in single BV.2 (lenti) cells following TNFα

stimulation…………………………………………………………………………………90

3.19: Western blot analysis of IκBα levels in wild type BV.2 cells after TNFα

stimulation…………………………………………………………………………...…..91

3.20: Western blot analysis of IκBα levels in lentivirus-transduced BV.2 cells after TNFα

stimulation…………………………………………………………………………………92

3.21: NF-κB-dependent gene expression changes in wild type vs lentivirus transduced

BV.2 cells following TNFα stimulation…………………………………..……………….93

3.22: Basal expression of NF-κB-dependent genes in BV.2 cell populations………….…94

3.23: Western blot analysis of p65 levels in the wild type BV.2 cells and BV.2 (lenti)

cells……………………………………………………………………………………..….94

3.24: Western blot analysis of IκBα levels in the wild type BV.2 cells and BV.2 (lenti)

cells……………………………………………………………………………………...…95

4.1: Expression of p65-eGFP in C17.2 (lenti) cells, in mono-culture and 1:1 co-culture

(with BV.2 cells)……………………………………………………………………...….104

4.2: Quantification of nuclear p65 fluorescence in C17.2 (lenti) cells, after TNFα

stimulation, in mono-cultures and 1:1 co-cultures (with BV.2 cells)…………………....105

4.3: Average peak timing and amplitude of the first p65 nuclear translocation, after TNFα

stimulation, in C17.2 (lenti) cells…………………………………………………….…..106

4.4: TNFα-induced p65 nuclear translocation profiles obtained from C17.2 (lenti) cells in

mono-cultures and 1:1 co-cultures (BV.2 cells)………………………………………….107

4.5: TNFα stimulated NF-luc induction in C17.2 cells, in mono-cultures and co-cultures

(with BV.2 cells)………………………………………………………………………....109

4.6: TNFα stimulated NF-luc induction in C17.2 cells, in mono-cultures and 1:4 co-

cultures (with SK-N-AS cells)………………………………………………………..….110

4.7: TNFα stimulated NF-luc induction in C17.2 cells, in mono-cultures and 1:4 co-

cultures (with RAW264.7 cells)………………………………………………….………110


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4.8: Basal luminescence of NF-luc plasmid-transfected C17.2 cells, in different culture

conditions…………………………………………………………………………….…..112

4.9: Background luminescence from BV.2 cells………………………………………....113

4.10: Unstimulated and TNFα stimulated NF-luc induction in mono-cultured C17.2 cells,

with and without transwells………………………………………………………………114

4.11: Unstimulated and TNFα stimulated NF-luc induction in C17.2 cells in mono-cultures

and 1:4 transwell co-cultures (with BV.2 cells)……………………………………..…...115

4.12: Unstimulated and TNFα stimulated NF-luc induction in C17.2 cells in mono-cultures

and 1:8 transwell co-cultures (with BV.2 cells)……………………………………..…...115

4.13: Basal luminescence in NF-luc plasmid transfected C17.2 cells, in different culture

conditions………………………………………………………………………….……..116

4.14: Expression of p65-eGFP in BV.2 (lenti) cells, in mono-culture and 1:1 co-culture

(with C17.2 cells)……………………………………………………………………...…117

4.15: Quantification of nuclear p65 fluorescence in BV.2 (lenti) cells, after TNFα

stimulation, in mono-cultures and 1:1 co-cultures (with C17.2 cells)……………...……118

4.16: Average peak to peak timing of p65 nuclear translocations in mono-cultured and co-

cultured BV.2 (lenti) cells, after TNFα stimulation…………………………………..….119

4.17: Average peak timing and amplitude of the first p65 nuclear translocation, after TNFα

stimulation, in BV.2 (lenti) cells, in mono-cultures and 1:1 co-cultures (with C17.2

cells)……………………………………………………………………………...………120

4.18: TNFα-induced p65 nuclear translocation profiles obtained from BV.2 (lenti) cells in

mono-cultures and 1:1 co-cultures (with C17.2 cells)…………………………….……..121

4.19: Relative TNFα concentration in mono- and co-cultures, after 2ng/ml TNFα

stimulation…………………………………………………………………………..……122

4.20: TNFR1-associated fluorescence in unstimulated and TNFα-stimulated wild type

C17.2 cells and C17.2 (lenti) cells……………………………………………………….123

4.21: TNFR1-associated fluorescence in unstimulated and TNFα-stimulated C17.2 (lenti)

cells……………………………………………………………………………………….125

5.1: A comparison of gene expression in unstimulated C17.2 and BV.2 mono-

cultures……………………………………………………………………………...……134

5.2: Genes upregulated/downregulated, at 230 min post-20ng/ml TNFα-stimulation, in

C17.2 and BV.2 mono-cultures and 1:1 co-cultures……………………………………..135


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5.3: Genes upregulated/downregulated, at 230 min post-20ng/ml TNFα-stimulation, in

transwell co-cultures and 1:1 contact-permissive co-cultures……………………………137

5.4: Genes upregulated/downregulated, at 24h post-20ng/ml TNFα-stimulation, in C17.2

and BV.2 mono-cultures and 1:1 co-cultures…………………………………………….139

5.5: Genes upregulated/downregulated, at 24h post-20ng/ml TNFα-stimulation, in

transwell co-cultures and 1:1 contact-permissive co-cultures………………...………….141

6.1: C17.2 viability and apoptosis levels, after 20ng/ml TNFα stimulation…………..…152

6.2: BV.2 viability and apoptosis levels, after 20ng/ml TNFα stimulation……………...153

6.3: Viability and apoptosis levels in 1:1 co-cultures (C17.2: BV.2), after 20ng/ml TNFα

stimulation……………………………………………………………………………..…154

6.4: Expected versus actual viability in unstimulated 1:1 co-cultures (C17.2:

BV.2)………………………………………………………………………………….….156

6.5: Expected versus actual viability in TNFα-stimulated 1:1 co-cultures (C17.2:

BV.2)…………………………………………………………………………………..…157

6.6: Expected versus actual apoptosis in unstimulated and TNFα-stimulated 1:1 co-cultures

(C17.2: BV.2)………………………………………………………………………...…..158

6.7: IκBα levels in PDTC-treated cells, after TNFα stimulation………………………....160

6.8: TNFα-stimulated NF-luc induction in PDTC- and non-PDTC treated C17.2 cells....161

6.9: C17.2 cell viability after 30 min pre-treatment with water or 0.1mM PDTC and either

no stimulation or 20ng/ml TNFα stimulation…………………………………………….162

6.10: BV.2 cell viability after 30 min pre-treatment with water or 0.1mM PDTC and either

no stimulation or 20ng/ml TNFα stimulation………………………………………...…..163

6.11: Viability of 1:1 co-cultures (C17.2: BV.2), after 30 min pre-treatment with water or

0.1mM PDTC and either no stimulation or 20ng/ml TNFα stimulation…………………164

6.12: Expected versus actual viability in 1:1 co-cultures (C17.2:BV.2), after either a 30

min treatment with water or 0.1mM PDTC……...……………………………..….…….166

6.13: Expected versus actual viability in 1:1 co-cultures (C17.2: BV.2) treated for 30 min

with either water or 0.1mM PDTC and 20ng/ml TNFα……………..………………...…167

6.14: Apoptosis levels in water- or PDTC-treated C17.2 cells…………………………..168

6.15: Apoptosis levels in water- or PDTC-treated BV.2 cells………………………...…169


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List of Tables

2.1: Cell numbers, dishes, cell growth area and media volume used in

experiments……………………………………………………………………………......56

2.2: Cell numbers, cell growth area and media volume in luminometry

experiments…………………………………………………………………………….….56

2.3: Primary and secondary antibodies used in Western blots………………………….…61

2.4: Calculations conducted to assess co-culture-mediated viability changes………….…62

2.5.1: Examples of the two different comparisons conducted with NanoString results:

Analysis of TNFα-induced gene expression…………………………………………...….66

2.5.2: Examples of the two different comparisons conducted with NanoString results:

Analysis of cell-contact-independent co-culture interactions…………………………..…66

2.6: Primers used for Q-PCR……………………………………………………………....67

2.7: Cycling parameters for Q-PCR……………………………………………………….67

5.1: Genes that were differentially expressed between mono-cultures and transwell co-

cultures…………………………………………………………………..……………….142

5.2: A collated list of NF-κB-dependent genes that were differentially regulated, at

different time points, by TNFα or co-culture interactions in: C17.2 or BV.2 mono-cultures,

transwell co-cultures or 1:1 contact-permissive co-cultures…………………...……...…143


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List of Abbreviations

A20 Tumor necrosis factor alpha-induced protein 3

A Adenine

AD Alzheimer’s disease

ARD Ankyrin repeat domain

BAC Bacterial artificial chromosome

Bcl-3 B-cell lymphoma-3

BDNF Brain-derived neurotrophic factor

BSA Bovine serum albumin

C Cytosine

CAP-Gly Cytoskeleton-associated proteins-glycine rich

CBP CREB-binding protein

cDNA Complementary deoxyribonucleic acid

c-IAP Cellular inhibitor of apoptosis protein

CNS Central nervous system

COX-2 Cyclooxygenase-2

CREB cAMP response element-binding protein

CYLD Cylindromatosis

DD Death domain

DMEM Dulbecco’s modified eagle’s medium

DNA Deoxyribonucleic acid

DsRedXP Discosoma sp. red fluorescent protein

EAE Experimental allergic encephalomyelitis

eGFP Enhanced green fluorescent protein

ELISA Enzyme-linked immunosorbent assay

EMSA Electrophoretic mobility shift assay

ERK Extracellular signal-regulated kinases

FADD Fas-associated via death domain protein

FBS Foetal bovine serum

FLIP FLICE-like inhibitor protein

G Guanine

Hsp Heat shock protein

IFN-γ Interferon gamma


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IκB Inhibitor kappaB

IKK Inhibitor kappaB kinase

IL-1β Interleukin-1 beta

Itch Itchy E3 ubiquitin protein ligase

JNK c-Jun N-terminal kinases

LPS Lipopolysaccharide

MAPKAPK2 Mitogen activation protein kinase-activated protein kinase 2

MCP-1/CCL2 Monocyte chemoattractant protein-1

mRNA Messenger ribonucleic acid

mTNFα Transmembrane tumor necrosis factor alpha

MTS 3-(4,5-dimethyl-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-

sulfophenyl)-2H-tetrazolium

NEAA Non-essential amino acids

NEMO Nuclear-factor kappaB essential modulator

NF-κB Nuclear-factor kappaB

NGF Nerve growth factor

NLS Nuclear localisation sequence

NPC Neural progenitor cell

NSC Neural stem cell

PBS Phosphate buffered saline

PDTC Pyrrolidine dithiocarbamate

PE Phycoerythrin

PEST Proline-, glutamic acid-, serine-, threonine-rich

PK Protein kinase

Q-PCR Quantitative-polymerase chain reaction

RHD Rel homology domain

RING Really interesting new gene

RIP Receptor-interacting protein

RT-PCR Reverse transcription-polymerase chain reaction

SODD Silencer of death domains

STAT6 Signal transducer and activator of transcription-6

T Thymine

TACE Tumor necrosis factor alpha converting enzyme


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TAD Transcription activation domain

Tax1BP1 Tax 1 binding protein 1

TGF-β Transforming growth factor-beta

TNFα Tumor necrosis factor alpha

TNFR Tumor necrosis factor receptor

TRADD Tumor necrosis factor receptor type 1-associated death

domain

TRAF Tumor necrosis factor receptor-associated factor

UT Untransfected

VEGF Vascular endothelial growth factor


18

Abstract NF-kappaB in Neuroinflammation

Nisha Patel

A Thesis submitted to The University of Manchester for the degree of Doctor of

Philosophy in Systems Biology (2014)

The NF-κB stress signalling system has an important role in the control of

inflammation, being both stimulated by cytokines and itself regulating cytokine gene

expression. NF-κB dynamics have previously been studied in a variety of different cell

lines and primary cells. It has been shown, using live-cell microscopy, that NF-κB proteins

show complex oscillatory dynamics between the nucleus and cytoplasm at the single-cell

level. These dynamics are thought to control gene expression responses.

A key aim of the work described in this thesis was to understand the functional NF-

κB-mediated paracrine interactions that occur between different cell types to control tissue-

level inflammatory responses. This project aimed to investigate cytokine-mediated

interactions between neural progenitor cells (NPCs) and microglia following Tumour

Necrosis Factor alpha (TNFα) stimulation. Specifically, the interactions between the C17.2

NPC line and the BV.2 microglial cell line were used as a model system. Understanding

the interactions between these cell types might be physiologically important for providing

an insight into the regulation of neuroinflammation. A further goal was to establish a

better understanding of how single-cell NF-κB dynamics could be related to differential

gene expression and cell survival.

Initially, different methods for expressing labelled RelA/p65 (p65) in C17.2 and

BV.2 cells were investigated. TNFα-induced NF-κB activation and p65 dynamics were

measured in cells that had been transfected or transduced with a range of p65 constructs

(plasmid, bacterial artificial chromosome or lentiviral vectors) to express fluorescent p65

fusion proteins. This study resulted in the selection of lentivirally transduced cells,

expressing p65-eGFP, as the most appropriate model system for the observation of p65

dynamics in these cells. C17.2 and BV.2 p65 dynamics and C17.2 NF-κB transcriptional

activity were measured in mono-cultures and co-cultures. These data indicated that BV.2

cells mediated inhibition of TNFα-induced NF-κB activity and p65 nuclear translocations

in the C17.2 NPCs. Preliminary evidence for C17.2 regulation of BV.2 p65 dynamics was

also found. However, this project mainly focussed on modulation of the C17.2 cell

responses, since it was considered that these were likely to be particularly important in the

control of neuroinflammation.

Gene expression was measured in untreated and TNFα-stimulated mono-cultures, co-

cultures and transwell co-cultures, in order to assess the functional effects of any

intercellular interactions. These studies were also designed to assess the outcome of TNFα

treatment and co-culture interactions on cell viability and apoptosis. In addition to this, an

NF-κB inhibitor was used to evaluate the NF-κB contribution to changes in cell viability

and apoptosis. These results implicated a role for TNFα in C17.2 apoptosis and suggested

that the presence of BV.2 cells could prevent this cell fate. Interestingly, NF-κB inhibition

was also shown to induce C17.2 apoptosis and increased overall viability. This may

suggest promotion of cell proliferation.

Together, these data provide functional evidence for TNFα-induced, co-culture- and

NF-κB-mediated interactions between these cell types at the molecular, genetic and

cellular level. These interactions had a significant effect on the extent of cell survival in

response to TNFα. This observation is relevant to the study of neurodegenerative disease,

where high TNFα concentrations are known to mediate tissue damage and NPCs have been

shown to provide a therapeutic benefit.


19

Declaration

No portion of the work referred to in the thesis has been submitted in support of an

application for another degree or qualification of this or any other university or other

institute of learning.

Copyright Statement

i. The author of this thesis (including any appendices and/or schedules to this thesis)

owns certain copyright or related rights in it (the “Copyright”) and s/he has given

The University of Manchester certain rights to use such Copyright, including for

administrative purposes.

ii. Copies of this thesis, either in full or in extracts and whether in hard or electronic

copy, may be made only in accordance with the Copyright, Designs and Patents

Act 1988 (as amended) and regulations issued under it or, where appropriate, in

accordance with licensing agreements which the University has from time to time.

This page must form part of any such copies made.

iii. The ownership of certain Copyright, patents, designs, trade marks and other

intellectual property (the “Intellectual Property”) and any reproductions of

copyright works in the thesis, for example graphs and tables (“Reproductions”),

which may be described in this thesis, may not be owned by the author and may be

owned by third parties. Such Intellectual Property and Reproductions cannot and

must not be made available for use without the prior written permission of the

owner(s) of the relevant Intellectual Property and/or Reproductions.

iv. Further information on the conditions under which disclosure, publication and

commercialisation of this thesis, the Copyright and any Intellectual Property and/or

Reproductions described in it may take place is available in the University IP

Policy (see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=487), in any

relevant Thesis restriction declarations deposited in the University Library, The

University Library’s regulations (see

http://www.manchester.ac.uk/library/aboutus/regulations) and in The University’s

policy on Presentation of Theses.


20

Acknowledgements

Firstly, I would like to thank my supervisors, Prof. M White and Dr. P Paszek, for their

help and guidance throughout the course of my PhD.

Also, many thanks go to all members of the Prof. White lab group. Special thanks to Polly

Downton for performing a miracle when I needed it, Kathryn Roberts for proofreading (at

a remarkable speed) and Angela Pisco for dedicating hours to helping me with formatting

(and offering me a bed). Also, thank you to James Bagnall for advice (and harassment) in

the lab throughout the years, to Anne McNamara with help troubleshooting (and for

showing me funny youtube clips), Connie Lam for helping me with just about everything

in the lab (and for listening to me rant) and Dr. Adamson for letting me steal his fine art-

work (and the awkward/funny conversations).

I am also grateful to every other member of the group for making the lab and office area a

great place to work in. Outside of work, thank you to James Bagnall (again), James Boyd,

Will Rowe and Nick Jones for the chuckles and drinks (although, I am not sure the latter

has done my liver any good).

I would like to thank my supervisors (again), Prof. M White and Dr. P Paszek, for getting

me through this. Special thanks, and eternal gratitude, go to Dr. D Spiller for support

throughout, but mainly for pushing me through the final stages- I needed the extra push.

On a personal note, thank you to Miquette Hall for making me laugh when I felt like I was

going crazy and Steph Baldwin for being an awesome lab buddy.

Finally, I would like to thank my parents and sister for their continual unconditional love

and support, for listening to me complain and giving me hugs when I need them: this really

would not have been possible without any of you.


21

1. Introduction


22

1.1. General Considerations

Even the most simple of biological processes involves a large number of biomolecules,

interactions and emergent properties, with an inherent element of stochasticity. It is

commonly accepted that understanding individual components in isolation is not sufficient

for understanding biological phenomena: the whole is greater than the sum of its parts.

The challenge of transcending multiple areas of research has been taken up by systems

biology. The principle behind this field is the integration of data from multiple levels, e.g.

from genes to cells, to achieve a more complete understanding of biological systems.

Neuroinflammation is an exemplar of a complex, disease-related biological process in

which there is a gap between molecular knowledge and tissue-level understanding. This

process is orchestrated by a wide range of cells, proteins and biomolecules, creating an

intricate network of interactions that determine cell fate in neurodegenerative disease. One

way to begin to detangle the web is to traverse the various areas/levels of the network,

starting with a central node.

1.1.1. Neuroinflammation

Neuroinflammation is a multi-stage defence process launched by the central nervous

system (CNS) in response to injury/infection. This process is designed to protect host

tissue by destroying noxious stimuli, such as bacterial toxins, and promoting damage repair

(Nikbin et al, 2011).

Neuroinflammation involves interactions between a range of different cell types, including

astrocytes, neurons, microglia and neural progenitor cells. Inflammatory stimuli trigger cell

signalling pathways, leading to the activation of transcription factors, such as nuclear-

factor kappaB (NF-κB). Activated NF‐κB regulates the expression of many pro- and anti‐

inflammatory cytokines and chemokines such as tumor necrosis factor α (TNFα; Shakhov

et al, 1990), interleukin‐1 (IL‐1; Mori and Prager, 1996) and monocyte chemotactic

protein‐1 (MCP‐1, also known as chemokine ligand 2; CCL2; Ueda et al, 1997).

Gene expression is modified in a cell-type- and stimulus-specific manner. Cytokines and

chemokines, secreted by stimulated cells, create a dynamic cocktail that perpetuates or

terminates the inflammatory response, by activating a series of signalling pathways in

receptive cells (Nikbin et al, 2011; Ramesh et al, 2013). Many of these factors also activate

or repress NF-κB signalling (Pahl, 1999; Gilmore and Herscovitch, 2006). The integration


23

of these signals determines the fate of cells in inflamed tissue. Due to its intimate

relationship with inflammatory factors, NF-κB is a central regulator of inflammatory

outcome (Tak and Firestein, 2001).

Neuroinflammation is a major cause of tissue damage sustained in neurodegenerative

diseases (Richardson et al, 2005; Klegaris et al, 2007; Frank-Cannon et al, 2009).

Prolonged (chronic) inflammation has previously been associated with disease, whereas

the acute (transient) inflammatory response was thought to be beneficial (Nikbin et al,

2011).

More recently, Wynn et al (2004) described chronic inflammation as a consequence of

dysfunctional microglial activity. In fact, microglia are involved in many CNS diseases

(Perry et al, 2010), most notably Alzheimers disease (AD; Bader et al, 1994) and

experimental allergic encephalomyelitis (EAE; an animal model of stroke; Banati et al,

1995; Bauer et al,1995).

Due to their ability to regulate inflammation and differentiate to replace damaged cells,

neural progenitor cells have emerged as a promising mode of therapy in neurodegenerative

diseases (Martino and Pluchino, 2006). Microglial-neural progenitor cell interactions are

particularly important governors of neuroinflammatory outcome: neural progenitor cells

can promote microglial proliferation and activation (Mosher et al, 2012; Forstreuter et al,

2002; Deierborg et al, 2010) and, in turn, microglia can induce neural progenitor cell

apoptosis, thereby preventing tissue regeneration (Guadagno et al, 2013; Liu et al, 2014).

The following sections will focus on the role of these cells, and their interactions, in

neuroinflammation.

1.1.2. Microglia

Microglia are CNS-specific macrophages that comprise 10-15% of all CNS cells and are

strategically localized in the most vulnerable areas of the nervous system (Abbott et al,

1986; Larner et al, 1995). Microglia are unique in that, as well as providing mechanical

and structural support, they are the first line of defence against invading pathogens and the

main resident mediators of the neuroinflammatory response (Saijo and Glass, 2011;

Colton, 2009; Nakajima and Kohsaka, 2001).

Quiscent (non‐activated) microglia are guardians of the CNS, actively extending and

retracting their processes, patrolling for foreign antigens or apoptotic cells. Upon


24

encountering an inflammatory stimulus, these cells undergo a morphological and

functional transformation; a process referred to as activation. The changes that microglial

cells undergo allow them to perform a range of functions including phagocytosis of dead

cells/bacteria and promotion of immune cell migration and activation (Saijo and Glass,

2011; Boche et al, 2013; Colton, 2009). Aarum et al (2003) reported that microglia can

also promote migration and neuronal differentiation of murine neural precursor cells,

suggesting that microglia can play a vital role in regeneration.

Microglial activation state and its functional consequences are determined by the

environmental milieu (Saijo and Glass, 2011; Colton, 2009). There are two well described

activation states for microglia- M1 (classical) and M2 (often subdivided into alternative

and acquired deactivation). Microglial exposure to interferon-γ (IFNγ) triggers the release

of cytokines that exaggerate the initial response and lead to classical activation of

microglia (via paracrine/autocrine feedback). Classical activation is characterized by

phagocytic ability and microglial‐release of proinflammatory cytokines, including TNFα,

cyclooxygenase‐2 (COX‐2) and IL-1β (Colton, 2009; Saijo and Glass, 2011). Microglial-

derived proinflammatory agents amplify the inflammatory response by triggering the

activation of other microglial cells and astrocytes (Saijo and Glass, 2011; Suzumura,

2008).

Classical activation is the first stage of the inflammatory response. The second stage of the

response is described as regenerative and requires a termination of the classically‐activated

phenotype (Nakajima and Kohsaka, 2001). This can involve regulatory proteins that are

induced by the initial inflammatory stimulus or constitutively expressed by immune cells.

NF-κB inhibition can also resolve the proinflammatory phenotype (Nakajima and

Kohsaka, 2001; Colton, 2009).

Classically‐activated microglia are a major source of TNFα in inflamed tissue, as well as

neurotoxic reactive oxygen species and excitotoxins (Mattson and Camandola, 2001). In

AD, TNFα appears to be responsible for much of the amyloid‐β‐induced neuronal

degeneration (Cartier et al, 2005). Microglial-derived TNFα has also been implicated in

neural progenitor cell apoptosis (Guadagno et al, 2013).

Alternatively, microglial cells can be switched into a different activation state by other

stimuli, produced by the classically activated response. Alternative activation is reportedly

induced by exposure to IL-4 or IL-13. This state is defined by the production of anti-


25

inflammatory cytokines and factors that are intended to promote tissue repair, such as

components of the extracellular matrix (Saijo and Glass, 2011; Colton, 2009). The

transcription factor, signal transducer and activator of transcription-6 (STAT6), has been

implicated in the switch from classical- to alternative-activation (Nguyen and Benveniste,

2000).

A third, less studied, activation state has also been proposed; acquired deactivation is

mainly induced by the anti‐inflammatory agents IL‐10 and transforming growth factor-beta

(TGF-β). These microglial cells are specialised to resolve inflammation by uptake of

apoptotic cells and immunosuppression (Colton, 2009).

In practice, microglial activation state is not discrete and exists on a continuum comprising

classical and alternative activation (Perry et al, 2010; Colton, 2009). Mechanistically, more

work is required to fully understand microglial activation and deactivation. It is not known

whether microglial cells within a given population can exist in different activation states

(Colton, 2009).

In summary, microglial activation status is an important determinant of neural progenitor

cell survival and, therefore, neuroinflammatory outcome.

1.1.3. Neural Progenitor Cells

Neural progenitor cells (NPCs) are heterogeneous, multipotent and mitotic cells that

differentiate into neural cells during neurogenesis, in developing and adult organisms

(Gage, 2000). They are generally believed to reside in only two distinct regions of the adult

CNS; the subventricular zone in the lateral ventricles and the subgranular zone of the

hippocampus (Gage, 2000; Ivanova et al, 2002; Doetsch, 2003).

It is worth making a point about the nomenclature used in the field of stem cell biology:

many researchers use the term ‘neural progenitor cells’ interchangeably with ‘neural stem

cells’. Various definitions of stem and progenitor cells have been proposed, in an effort to

distinguish between the two (Seaberg and van der Kooy, 2003). However, a commonly-

accepted definition has yet to be established, hence, when referring to studies, the term

used here reflects the term used by the authors of the study.

In recent years, exogenous NPCs have emerged as a potential candidate for treatment of a

range of pathological conditions associated with neuroinflammation, such as stroke (Daadi

et al, 2008), Parkinson’s disease (Richardson et al, 2005) and AD (Abdel‐Salam, 2011).


26

The exogenous application of NPCs has demonstrated non‐tumorigenic properties, long‐

term survival and therapeutic benefits in disease (Temple, 2001). Studies have shown that

engrafted NPCs migrate into areas of brain injury (Ivanova, 2002; Doetsch,2003; Merkle et

al, 2004) and can differentiate into a range of neural cells including neurons, astrocytes and

oligodendrocytes (Park et al, 2006).

Microglial cells are one of the major drivers of NPC migration into sites of

neuroinflammation (Aarum et al, 2003). As well as differentiating to replace damaged

neurons, exogenous NPCs have been shown to exert immune functions and reportedly

create a neuroprotective inflammatory phenotype (Martino and Pluchino, 2006). In order to

do this, they must navigate the potentially toxic neuroinflammatory microenvironment. As

the main producers of many proinflammatory factors, activated microglia present the

biggest threat to survival of NPCs (Pellegatta et al, 2006).

1.1.4. Microglial and Neural Progenitor Cell Interactions

The activation state of microglia contributes to their effect on NPCs. Non-activated

microglia have been shown to promote NPC proliferation in vitro (Liu et al, 2013a),

whereas culture media from classically activated microglia can cause NPC apoptosis

(Guadagno et al, 2013). This latter result was dependent on microglial-derived TNFα, NF-

κB activation and downstream Puma expression in NPCs. In another study, culture media

from activated microglia reportedly induced proliferation and differentiation of NPCs

(Deierborg et al, 2010). This may reflect differences in cell types or microglial activation

state: Guadagno et al used lipopolysaccharide (LPS) to activate murine microglia, whereas

Deierborg et al used rat microglia that had been activated by a brain injury.

Reciprocally, NPCs can promote microglial proliferation (Liu et al, 2013a) and regulate

activation and chemotaxis (Mosher et al, 2012). Microglial proliferation in this latter study

was mediated by NPC-derived vascular endothelial growth factor (VEGF); this factor was

previously shown to induce microglial chemotaxis and proliferation (Forstreuter et al,

2002). Interestingly, VEGF expression is regulated by NF-κB (Chilov et al, 1997). NF-κB

activity has yet to be thoroughly investigated in neural cells. The following chapter

explores what is currently known about NF-κB, much of which is derived from non-neural

cells.


27

1.2. The Nuclear Factor KappaB (NF-κB) Signalling Pathway

1.2.1. Overview of NF-κB Signalling

Nuclear‐Factor kappaB (NF-κB; also known as Rel) is a family of five proteins,

evolutionarily conserved from Cnidaria to humans, which form dimeric eukaryotic

transcription factors (Chen and Ghosh, 1999). Almost thirty years ago, NF-κB was

discovered as a transcriptional regulator of immunoglobulin light chain genes in B-

lymphocytes (Singh et al, 1986). We now know that NF-κB is ubiquitously expressed

(Bonizzi and Karin, 2004) and can be activated by a range of factors, e.g. cytokines, viral

infection and DNA damage (Brasier, 2006; Gilmore, 2006; Hayden and Ghosh, 2008). As

a regulator of hundreds of genes, NF-κB is a central player in many processes such as

inflammation, proliferation and apoptosis (Hayden and Ghosh, 2008; Ghosh and Karin,

2002; Bonizzi and Karin, 2004; Gilmore, 2006).

Depending on the stimulus, NF-κB activation can occur via three different pathways: the

well-known canonical or non-canonical pathways or the most recently discovered atypical

pathway. Each pathway is distinguished by the complement of NF-κB dimers and

signalling molecules that are involved (Hoffmann and Baltimore, 2006; Gilmore, 2006).

The most prevalent NF-κB dimer, p65:p50, is part of the canonical pathway (Hoffmann

and Baltimore, 2006; Hayden and Ghosh, 2008).

Canonical signals converge on a multi-protein kinase complex called inhibitor kappaB

kinase (IKK). Downstream of the IKK complex are inactive NF-κB dimers, bound to

cytoplasmic inhibitor kappaB (IκB) proteins: this interaction prevents NF-κB nuclear

entry. The canonical NF-κB network has to undergo a complex series of events in order to

produce transcriptionally activated NF-κB dimers (Hayden and Ghosh, 2008; Gilmore,

2006; Perkins, 2006).

Ligands for the canonical pathway, such as TNFα, trigger the activation of IKK complexes

which facilitate degradation of NF-κB-bound IκB proteins. NF-κB is then free to

translocate into the nucleus, bind to specific sites on DNA, and modify gene expression

(Hoffmann et al, 2002; Ashall et al, 2009). IκB genes are transcriptionally‐upregulated and

newly‐synthesised IκB proteins chaperone NF‐κB out of the nucleus and back into the

cytoplasm (Hayden and Ghosh, 2008). Due to the pattern of degradation and later

resynthesis of IκB proteins, NFκB can move (oscillate) in and out of the nucleus


28

repeatedly in response to a single stimulus (Nelson et al, 2004; Ashall et al, 2009; Turner et

al, 2010). The dynamics of NF-κB are described in more detail in section 1.2.4.

With a focus on the canonical pathway, the following sections detail different aspects of

the NF-κB network, beginning with NF-κB, IκB and IKK complex proteins (see Figure

1.1). This will be followed by a section on TNFα-induced NF-κB activation, NF-κB

dynamics and the regulation of NF-κB transcriptional activity and response.

F ig u r e 1 .1 . A n o v e r v ie w o f th e T N F - in d u c e d c a n o n ic a l N F -B a c t iv a t io n p a t h w a y .

T h is sc h e m a tic s h o w s th e m a in p ro te in s in v o lv e d in T N F - in d u c e d c a n o n ic a l a c t iv a tio n . T N F R

b in d in g to T N F in d u c e s th e a c t iv a t io n o f IK K , v ia d o w n s tr e a m s ig n a lin g m o le c u le s . A c tiv a te d

IK K th e n p h o s p h o ry la te s (p ) IB p ro te in s , s u c h a s IB , th e re b y le a d in g to th e ir u b iq u it in a t io n

(u b ) a n d d e g ra d a tio n . T h is r e le a s e s N F -B a n d a l lo w s i t to t r a n s lo c a te in to th e n u c le u s , w h e re i t

u p re g u la te s th e e x p re s s io n o f IB g e n e s , a s w e ll a s o th e r ta rg e t g e n e s . N e w ly - s y n th e s is e d IB

p ro te in s b in d to a n d e x p o r t n u c le a r N F -B , c re a tin g a n e g a tiv e f e e d b a c k lo o p . C y c le s o f IB

d e g ra d a tio n a n d r e s y n th e s is c a n le a d to m u ltip le N F -B n u c le a r t r a n s lo c a tio n s (o s c i l la t io n s ) .

A d a p te d f ro m D r . A . A d a m so n .


29

1.2.2. Overview of the Structure and Function of NF-κB Pathway Components

1.2.2.1. Rel Proteins

In mammals, the NF-κB family is composed of five proteins: p65 (also known as RelA),

Rel B, c-Rel, p50 and p52, encoded by RELA, RELB, REL, NFKB1 and NFKB2 genes,

respectively (Gilmore, 2006; Hayden and Ghosh, 2008; see Figure 1.2).This family of

proteins is defined by an N-terminal Rel Homology Domain (RHD). This domain enables

dimerization and allows NF-κB dimers to interact with IκB proteins. When NF-κB is

activated, a nuclear localization sequence (NLS) within the RHD permits NF-κB nuclear

entry (Gilmore, 2006; Hayden and Ghosh, 2008).

F ig u r e 1 .2 . T h e s tr u c tu r e a n d c o m p o s it io n o f N F -B fa m ily m e m b e r s .

T h e a b o v e s c h e m a t ic s h o w s th e s t ru c tu re o f N F -B fa m ily m e m b e rs , w ith

a n n o ta tio n s d e n o tin g th e m a in c o n s ti tu e n t d o m a in s o f e a c h p ro te in .

A l te rn a tiv e n a m e s fo r th e p ro te in s a re s h o w n in b ra c k e ts . (A b b re v ia t io n s :

A N K , a n k y r in re p e a t d o m a in ; D D , d e a th d o m a in ; G R R , g ly c in e -r ic h re g io n ;

L Z , le u z in e -z ip p e r; R H D , R e l h o m o lo g y d o m a in ; T A D , tra n s a c t iv a tio n

d o m a in ) . S c h e m a t ic ta k e n f ro m G h o s h a n d H a y d e n , 2 0 0 8 .

NF-κB proteins can be divided into two groups based on their transcriptional capacity. The

p65, c-Rel and Rel B proteins contain transcription activation domains (TADs), which

confer transcriptional ability to the NF-κB dimers that these proteins form. The p65:p50

heterodimer is the most prevalent and transcriptionally active NF-κB dimer (Gilmore,

2006; Hayden and Ghosh, 2008). As p50 and p52 lack TADs, they must form dimers with

TAD-containing proteins in order to gain transcriptional ability (Hayden and Ghosh,

2008).

Almost all variations of NF-κB homo- and hetero-dimers have been identified (Philips et

al, 1996; Liou et al, 1994, Lee et al, 1995; Molitor et al, 1990) with the exception of RelB

which only binds to p52 and p50 (Ryseck et al, 1992; Ryseck et al, 1995). Unlike other


30

dimers, RelB-containing dimers are constitutively active in B cells and inducible in other

cell types investigated (Dobrzanski et al, 1995; Olashaw, 1996).

In unstimulated cells, most NF-κB dimers are cytoplasmic; the exceptions to this are p50

and p52 homodimers, which are readily found in the nucleus. As non-TAD-containing

dimers, p50 and p52 homodimers can repress gene transcription by binding to DNA and

preventing DNA access to TAD-containing dimers (Zhong et al, 2002; Hayden and Ghosh,

2008; Ghosh et al, 1998).

Nuclear NF-κB binds to κB sites on gene promoter and enhancer sequences. The consensus

sequence of κB sites is highly variable: 5’-GGGRN(Y)YYCC-3’ where R= adenine (A) or

guanine (G); Y= cytosine (C) or thymine (T) and N= A, G, C or T (Hoffmann and

Baltimore, 2006). NF-κB dimer composition determines κB site specificity. For example,

p65 homodimers have an affinity for the 5’TTTCC’3 sequence in regions of low GC

content: through this interaction p65 homodimers are primarily responsible for NF-κB-

dependent IL-8 upregulation (Kunsch and Rosen, 1993). On the other hand, p50

homodimers preferentially bind to GC rich areas, such as the 5’GGGGATTCCC’3 κB site

on the major histocompatibility class I gene (Kunsch et al, 1992; Kieran et al, 1990;

Grimm and Baeuerle, 1993). The κB site specificity of NF-κB dimers contributes to

differential gene regulation: this area of NF-κB activity has yet to be thoroughly

investigated. Chromatin immuno-precipitation sequencing data may soon shed more light

on this area of NF-κB gene regulation.

1.2.2.2. Inhibitor KappaB (IκB) Proteins

The IκB protein family includes IκBα, IκBβ, IκBδ, IκBε, IκBζ and Bcl-3 (Hayden and

Ghosh 2008; Ghosh and Karin, 2002; see Figure 1.3). The role of these proteins in NF-κB

activity is largely dependent upon their structure: they all contain central multiple ankyrin

repeat domains (ARD), which allow 1:1 association with NF-κB dimers (Hayden and

Ghosh, 2008). Cytoplasmic IκBα, IκBδ, IκBε and IκBζ bind to and mask the NF-κB NLS,

thereby preventing NF-κB nuclear entry (Beg et al, 1992; Henkel et al, 1992; Zabel et al,

1993). IκBα and IκBβ also have a C-terminal acidic and threonine rich sequence, PEST,

which is involved in IκB protein stabilisation (Beauparlant et al, 1996) and disrupting NF-

κB-DNA binding (Ernst et al, 1995). Bcl-3 uniquely possesses a TAD, enabling it to

endow target NF-κB dimers with transcriptional activity (Bours et al, 1993; Fujita et al,

1993).


31

IκB proteins have different preferences for NF-κB binding partners. For example, Bcl-3

and IκBδ only associate with p50 and p52 homodimers (Nolan et al, 1993) and RelB:p52

heterodimers (Dobrzanski et al, 1995), respectively. IκBγ is less specific and binds to c-

Rel-containing dimers, p65:p50 and p50 homodimers (Inoue et al, 1992). These

associations allow most IκB proteins to function in canonical and non-canonical pathways.

IκBα, which preferentially binds to the p65:p50 heterodimer, functions primarily as part of

the canonical pathway (Hayden and Ghosh, 2008).

F ig u r e 1 .3 . T h e s tr u c tu r e a n d c o m p o s it io n o f k e y IB fa m ily m e m b e r s .

T h e a b o v e s c h e m a t ic s h o w s th e s t ru c tu re o f th e m a jo r IB fa m ily m e m b e rs ,

w i th a n n o ta tio n s d e n o t in g th e m a in c o n s ti tu e n t d o m a in s o f e a c h p ro te in .


P E S T , p ro lin e - , g lu ta m ic a c id - , s e r in e - a n d th re o n in e -r ic h ; T A D ,

tra n s a c tiv a tio n d o m a in ) . S c h e m a t ic ta k e n f ro m G h o s h a n d H a y d e n , 2 0 0 8 .

IB (IB N S )

IκB proteins are referred to as typical or atypical, and differ according to their cellular

localisation, expression and function (Hayden and Ghosh, 2008). Due to their nuclear

localisation, the atypical proteins- Bcl-3, IκBδ and IκBζ- function mainly as regulators of

differential κB-driven transcription (Bours et al, 1993; Fujita et al, 1993; Dobrzanski et al,

1995). The focus in the remainder of this section will be two of the major regulators of the

canonical p65:p50 activation response: IκBα and IκBε (Hayden and Ghosh, 2008).

1.2.2.2.1. IκBα and IκBε in NF-κB Activation

TNFα-stimulation leads to the rapid IKK-mediated degradation of cytoplasmic IκBα and

IκBε, thereby releasing NF-κB for nuclear entry (Hayden and Ghosh, 2008; Perkins, 2006).

IκBα phosphorylation at serine 32 and serine 36 is required, but not sufficient, for IκBα

degradation. Phosphorylation makes IκBα a target for ubiquitination, primarily at lysine 21

and lysine 22, which promotes degradation by the 26S proteasome (Whiteside and Israël,


32

1997). IκBε is thought to be degraded in a similar ubiquitin-dependent manner (Whiteside

and Israël, 1997).

Both IκBα and IκBε genes are NF-κB-dependent; their upregulation after NF-κB activation

provides a negative feedback loop that is vital in controlling NF-κB response duration

(Hayden and Ghosh, 2008). The IκBα gene is an early target of NF-κB, enabling rapid

restoration of IκBα protein levels after TNFα stimulation (Moss et al, 2012; Ashall et al,

2009; Hoffmann et al, 2002). Newly-synthesised IκBα translocates into the nucleus,

dissociates DNA-NF-κB binding and chaperones NF-κB out of the nucleus and back into

the cytoplasm (Hoffmann et al, 2002). The temporal profile of IκBα degradation and

resynthesis makes it an effective inhibitor of the early NF-κB response. IκBε degradation

and resynthesis profile is slower than that of IκBα, allowing inhibition of later stages of the

NF-κB response (Whiteside and Israël, 1997). Together, IκBα and IκBε are vital regulators

of the duration of NF-κB activation (Hayden and Ghosh, 2008; Hoffmann et al, 2002;

Paszek et al, 2010).

1.2.2.3. Inhibitor KappaB Kinase (IKK) Complex

1.2.2.3.1. IKK Complex Components and Formation

Canonical NF-κB activation signals converge on the multi-unit inhibitor kappaB kinase

(IKK) complex (700-900kDa): NF-κB activation is dependent on the kinase activity of this

complex (Sun and Ley, 2008). IKK kinase activity is derived from its IKK components,

IKKα and IKKβ. These proteins share 50% sequence homology: their N-terminal protein

kinase and C-terminal leucine zipper and helix-loop-helix domains are required for protein

interactions (Zandi et al, 1997; Hayden and Ghosh, 2008; Li and Lin, 2008).

IKK complex formation and activation is dependent on a non-catalytic regulatory protein

called NEMO (NF-κB essential modulator; 48kDa; May et al, 2000; Tegethoff et al, 2000;

Li and Verma, 2002). The N-terminal of NEMO binds to the C-terminal hexapeptide

NEMO-binding domain (NBD) of IKK subunits (Scheidereit, 2006; Chen, 2012;

Laplantine et al, 2009).

The core IKK complex is believed to be composed of two IKKα:IKKβ dimers and a

tetrameric NEMO unit (Hayden and Ghosh, 2008; Hacker and Karin, 2006; see Figure

1.4). There is evidence of other IKK components, around the core complex. A homodimer

of a kinase chaperone, heat shock protein 90 (Hsp90), is constitutively associated with the

IKK complex. Recruitment of Hsp90 to IKK, mediated by Cdc37, is vital in TNFα-induced


33

IKK activation (Chen et al, 2002). ELKS, a DNA-binding protein, was more recently

proposed to act as a regulatory subunit of IKK, although its role in IKK formation and

activation has yet to be elucidated (Ducut Sigala et al, 2004).

F ig u r e 1 .4 . T h e s tr u c tu r e a n d c o m p o s it io n o f th e m a in I K K c o m p le x

c o n s t i tu e n ts .

T h e a b o v e s c h e m a t ic s h o w s th e s tru c tu re o f th e m a in IK K c o m p le x

c o m p o n e n ts , w i th a n n o ta tio n s d e n o tin g th e ir c o n s ti tu e n t d o m a in s .


C C , c o ile d -c o il ; H L H , h e lix - lo o p -h e lix ; L Z , le u z in e -z ip p e r; N B D ,

N F -B -e s s e n tia l-m o d u la to r-b in d in g d o m a in ) . S c h e m a tic ta k e n fro m G h o s h

a n d H a y d e n , 2 0 0 8 .

1.2.2.3.2. IKK Complex Activation

IKK kinase activity requires non-degradative ubiquitination and also phosphorylation of

two T loop serines of at least one of the IKK subunits: either serine 176 and serine 180 or

serine 177 and serine 181 of IKKα and IKKβ, respectively (Mercurio et al, 1997; Delhase

et al, 1999; Johnson et al, 1996). These modifications lead to conformational changes and

IKK complex activation (Delhase et al, 1999; Johnson et al, 1996).

The exact mechanisms behind IKK complex activation require further investigation.

However, evidence from various studies indicates transautophosphorylation as an

important driver of IKK activation. The C-terminal of NEMO plays an important role in

this process by binding IKK dimers and keeping them in close proximity (Rothwarf and

Karin, 1999).

Components of the TNF receptor-1 (TNFR1)-signalosome, upstream of IKK, may play a

role in TNFα-induced IKK activation. TNFR-associated factor-1 (TRAF1) recruits IKK

into the TNFR1-signalosome, after which receptor-interacting protein kinase (RIP)

oligomerization acts as a platform for IKK oligomerisation (Inohara et al, 2000; Devin et

al, 2000). This final event is vital in IKK activation, possibly due to its promotion of

proximity-induced phosphorylation events.


34

Once activated, the IKK complex phosphorylates downstream IκB proteins, initiating the

first step in their degradation via the 26S proteasome (Chen et al 1996; Whiteside and

Israël, 1997). IκBα, particularly NF-κB-bound IκBα, is a major target for activated IKKα

and IKKβ. IKKβ phosphorylates IκBα more efficiently than IKKα: it accounts for nearly

all of IκBα degradation observed after TNFα stimulation (Hacker and Karin, 2006; Hayden

and Ghosh, 2008; Hayden and Ghosh, 2004).

Moreover, it is widely reported that IKKβ kinase activity is required and sufficient for

canonical NF-κB activation. However, studies on IKK-deficient mice suggest that both

IKKα and IKKβ are non-redundant and differentially effect TNFα-induced NF-κB

activation (Takeda et al, 1999; Hu et al, 1999; Li et al, 1999). It has been found that protein

phosphatase 2A treatment inactivates IKK, possibly by removing vital T loop serine-

associated phosphate groups (DiDonato et al, 1997). The exact mechanisms behind the

termination of IKK activation are largely unknown.

1.2.3. Canonical Activation of NF-κB Pathway

Activation of the canonical pathway can be induced by a range of ligands, including TNFα

and IL-1. Ligand-receptor interactions on the cell surface trigger the recruitment of

intracellular adaptor proteins such as TNFR-associated death domain protein (TRADD)

and RIP (Hayden and Ghosh, 2008; Perkins 2006). The resulting intracellular complex

recruits and activates IKK. IKK activity is vital for NF-κB activation via the canonical

pathway: it phosphorylates IκB proteins, thereby facilitating their degradation and NF-κB

release for nuclear entry (Hoffmann et al, 2002; Hayden and Ghosh, 2008). The following

section details the TNFα-induced canonical signalling pathway, from ligand to signalling

outcome (i.e. cell survival versus apoptosis).

1.2.3.1. TNFα Structure

TNFα is a member of a large cytokine family, the TNF ligand family, which also includes

Fas, CD40 ligand and lymphotoxin α. TNFα was initially discovered almost fourty years

ago as an antitumor agent, capable of inducing apoptosis in tumour cells. It was found to

exert therapeutic effect, when combined with chemotherapeutics, in cases of cancer

(Carswell et al, 1975; Williamson et al, 1983). Since its initial discovery, the pleotropic

nature of TNFα has been revealed: it is an important player in the inflammatory process,


35

cell proliferation and apoptosis (Montgomery and Bowers, 2012; Bernardino et al, 2008;

Guadagno et al, 2013; Widera et al, 2006a).

TNFα is synthesised as a monomeric transmembrane protein that requires

homotrimerization to become biologically active (Kriegler et al, 1988; Tang et al, 1996).

The soluble homotrimers are proteolytically cleaved by TNFα converting enzyme (TACE)

to produce two forms of TNFα: soluble 51kDa trimeric TNFα and membrane-anchored

17kDa TNFα protomer (Black et al, 1997). The transmembrane TNFα (mTNFα) has a

structure that is typical of members of the TNF ligand family: two anti-parallel beta-

pleated sheets with antiparallel beta strands form what is known as a ‘jelly-roll’ structure

(Bazan, 1993).

TNFα upregulation is a common feature of neuroinflammatory diseases, most notably AD

(Montgomery and Bowers, 2012; Cartier et al, 2005). CNS-specific overexpression of

TNFα in mice can lead to astrogliosis, microgliosis and demyelination (Probert et al,

1995). However, TNFα can also be beneficial: the duality of its effects has been attributed

to cell-type specificity and TNF receptor engagement (Probert et al, 1995; Fontaine et al,

2002; Kontoyiannis et al, 1999).

1.2.3.2. TNFR Structure and Function

TNFα exerts its effects via TNFR1 (also known as CD120a; p55 or p60) and TNFR2 (also

known as CD120b; p75 or p80; Tartaglia and Goeddel, 1992). Although both soluble

TNFα and mTNFα can interact with TNFR1 and TNFR2, soluble TNFα has a higher

affinity for TNFR1 than mTNFα (Grell et al, 1995; Grell et al, 1998). Due to the stability

of the TNFR1-TNFα complex, soluble TNFα is thought to primarily signal through

TNFR1 (Thoma et al, 1990; Brockhaus et al, 1990) and, conversely, mTNFα preferentially

signals through TNFR2 (Eissner et al, 2004; Grell et al, 1995).

Receptor-ligand preferences have been implicated in dual TNFα functionality: TNFR1 and

TNFR2 signalling is generally associated with cell damage and cell survival, respectively

(Fontaine et al, 2002; Shen et al, 1997; Yang et al, 2002). However, this idea is too

simplistic: TNFR2 triggering alone in the CNS can induce cell death (Bigda et al, 1994;

Grell et al, 1993; Medvedev et al, 1994). Also, TNFR2 signalling can augment TNFR1-

induced apoptosis and cooperation between these receptors reportedly enhances

cytotoxicity (Declerc et al, 1998; Vandanabeele et al, 1995; Grell et al, 1999).


36

The extracellular domain of both receptors contains four cysteine rich repeats that are

arranged into elongated shapes, to enable interactions with the lateral grooves of soluble

TNFα trimers (Naismith and Sprang, 1998; Banner et al, 1993). Difference in structure is a

contributory factor in TNFR1 and TNFR2 signalling outcome. The cytoplasmic portion of

TNFR1 contains a death domain (DD), which is essential for the induction of an apoptotic

signal (Micheau and Tschopp, 2003; Thorburn, 2004). In contrast, TNFR2 does not contain

a DD, but can induce apoptosis by activating the TNFR1 signalling pathway, as TNFR1

has a region which is responsive to TNFR2 activation (Declercq et al, 1998; Vandanabeele

et al, 1995).

Like TNFα, TNFR2 undergoes proteolytic cleavage by TACE to release its extracellular

domain (Solomon et al, 1999). This domain can bind to soluble TNFα in the extracellular

space, thereby reducing TNFα action on cells (Kraft et al, 2009). TNFR1 also undergoes a

similar cleavage process; the protease responsible has not yet been identified (Wajant et al,

2003).

TNFR1 is constitutively expressed in most cells, whereas TNFR2 is primarily expressed in

immune cells (Wajant et al, 2003). Differential expression of TNFRs may contribute to

cell-type specific TNFα effects.

1.2.3.3. TNFR1 Signalling

The formation of TNFR1 trimers is thought to be essential for initiating the response to

TNFα (Wajant et al, 2003). This can occur spontaneously in unstimulated cells, as a result

of homophilic interactions between receptors, driven by distal cysteine rich domains. Pre-

ligand-binding assembly domains prevent this auto-activation and maintain the receptors in

an inactive state (Chan et al, 2000).

The death domain of TNFR1 is particularly prone to self-aggregation; a process which is

prevented by the binding of silencer of death domain (SODD) protein. SODD dissociates

from TNFR1 upon its interaction with TNFα (Jiang et al, 1999). Tyrosine residues, present

in the intracellular domain of TNFR1, facilitate rapid internalisation of TNFR1 after

binding to TNFα (Kraft et al, 2009; Schutze et al, 1999). This process seems to be required

for transduction of the apoptotic signal (Kraft et al, 2009; Hsu et al, 1996a) and also the

stimulation of c-Jun N-terminal kinase (JNK) pathways (Wajant et al, 2003). Activation of

NF-κB and other pathways, such as extracellular signal-regulated kinases (ERK), is

thought to occur independently of receptor internalisation (Wajant et al, 2003).


37

Within minutes of internalisation, the TNFR1-TNFα complex recruits TRADD which, in

turn, initiates a cascade of adaptor protein recruitment (Hsu et al, 1996a). This recruitment

cascade is mediated by homophilic interactions between the DDs of adaptor proteins

(Schulze-Osthoff et al, 1998). TRADD acts as a platform for recruitment of Fas-associated

protein with death domain (FADD): this event is involved in the transduction of apoptotic

signals (Hsu et al.1996b; Juo et al, 1998; Yeh et al, 1998). RIP is also recruited to the

TNFR1-complex (Hsu et al, 1996a). Wajant et al (2003) speculated that RIP is involved in

the stabilization of this complex, via its interactions with TRAF2 (Hsu et al, 1996a).

TRAF 2 polyubiquitinates RIP1 and facilitates the recruitment of IKK to the signalosome,

via its Really Interesting New Gene (RING) domain (Inohara et al, 2000; Hayden and

Ghosh 2008). Oligomerized TRAF proteins alone are sufficient for recruitment of the IKK

complex into the signalosome, whereas RIP1 is a requirement for IKK activation (Devin et

al, 2000): RIP1 and 2 oligomerization may provide a platform for IKK complex

oligomerization (Inohara et al, 2000).

However, the composition of the signalosome is highly complex and dynamic: over time,

members of the signalosome dissociate to form a second complex with other proteins. The

balance between the initial and second complex can determine whether or not apoptosis is

induced by TNFR1-signalling (Micheau and Tschopp, 2003; Micheau et al, 2001).

1.2.3.3.1. Induction of Apoptosis

Molecular studies have shed light on how elements of the TNFR1 activation pathway can

determine how cells respond to TNFα i.e. survival versus apoptosis (Micheau and

Tschopp, 2003; Micheau et al, 2001).

Micheau and Tschopp (2003) proposed that TNFR1-induced apoptosis requires the

formation of two signalling complexes: the balance between these complexes determines

signalling outcome. They utilised wild-type HT1080 cells, modified to express an un-

degradable form of IκBα: these cells were susceptible to TNFα-induced apoptosis. Wild

type HT1080 cells were resistant to TNFα-induced apoptosis. In this study, the

composition of the TNFR1 signalling complex was analysed in apoptosis-susceptible and

apoptosis-resistant cells.

The plasma-membrane bound complex I, formed rapidly after TNFR1 internalisation, was

composed of TRADD, RIP proteins, TRAF2 and cellular inhibitor of apoptosis protein-1


38

(c-IAP1). This complex signalled to activate NF-κB, via the recruitment and activation of

IKK.

Over time, complex I progressively dissociated and adaptor proteins, which included

TRADD, RIP1 and TRAF2, formed a second complex (complex II), along with caspase-8,

caspase-10 and FADD. Association of these factors became more pronounced over time,

reaching a peak at the onset of apoptosis.

It was found that NF-κB activity, initiated by complex I, could prevent complex II-driven

apoptosis, by upregulating the expression of anti-apoptotic factors such as TRAF and c-

IAP. Caspases-3 and -7 were tagged for proteasomal degradation by the C-terminal RING

domain of c-IAP1 and 2 proteins. The NF-κB-dependent caspase-8 inhibitor, FLICE-like

inhibitory protein (FLIP) was vital in the prevention of apoptosis: overexpression of FLIP

in apoptosis-susceptible cells prevented TNFR1-induced apoptosis (Micheau and Tschopp,

2003; Micheau et al, 2001). Other studies have shown that NF-κB activity regulates the

expression of other anti-apoptotic factors, such as immediate early response gene-1L and

X-linked inhibitor of apoptosis (Stehlik et al, 1998; Wu et al, 1998). Together, these results

highlight the importance of analysing molecular-level data, as well as downstream gene

expression, to understand signalling outcomes.

1.2.3.4. TNFR2 Signalling

The TNFR2 signalling pathway is less well understood than TNFR1 signalling. As TNFR2

lacks a DD, its ability to promote apoptosis is reliant on activating TNFR1 signalling:

TNFR2 can mediate TNFR1-dependent apoptosis in one of three ways (Wajant et al,

2003). The first involves competitive binding for TRAF2-associated anti-apoptotic

proteins, c-IAP1 and 2. TRAF2 affinity for TNFR1 and TNFR2 is comparable (Fotin-

Mleczek et al, 2002). Therefore, TNFR2 activation and subsequent recruitment of TRAF2

decreases TRAF2 availability for TNFR1 signalling. Reduction in TRAF2 recruitment can

cause apoptosis, possibly via the resulting decrease in c-IAP recruitment to the TNFR1-

signalling complex (Weiss et al, 1997; Weiss et al 1998; Duckett and Thompson, 1997; Li

et al, 2002; Chan and Lenardo, 2000; Brown et al, 2002; Fotin-Mleczek et al, 2002).

Consistent with this idea, TNFR2 stimulation is associated with TNFR1-mediated caspase-

8 activation and, thereby, apoptosis (Chan and Lenardo, 2000; Brown et al, 2002; Fotin-

Mleczek et al, 2002).


39

The second method by which TNFR2 could induce TNFR1-driven apoptosis is by

promoting c-IAP1-initiated degradation of TRAF2 (Wajant et al, 2003). The consequent

TRAF2 depletion would enhance competition between TNFR1 and TNFR2 for recruitment

of remaining TRAF2 (Wajant et al, 2003).

Finally, TNFR2-stimulation can promote TNFR2 cleavage to produce mTNFα. This can,

in turn, directly activate TNFR1 and, thereby contribute to apoptosis (Grell et al, 1995;

Grell et al, 1998).

1.2.4. NF-κB Dynamics and Function

Hoffmann et al (2002) used a mathematical model to predict that the NF-κB system could

produce oscillations in certain circumstances. Treating with a 15-minute pulse of TNFα

appeared to produce a more transient NF-κB response in MEFs (mouse embryonic

fibroblasts). Apparent oscillatory behaviour during continual TNFα treatment was

observed using electromobility shift assays (EMSA) for nuclear NF-κB in cells where

IκBβ and IκBε were knocked out. Interestingly, Hoffmann et al (2002) reported that

different TNFα treatments produced different downstream NF-κB-dependent expression

profiles of MCP-1/CCL2 and IP-10/CXCL10 genes.

When NF-κB dynamics were observed for the first time in single-cells (Nelson et al, 2004),

cell-type specific NF-κB oscillations were observed, in response to continual TNFα

treatment. This was achieved using SK-N-AS (human neuroblastoma) and HeLa (human

cervical cancer) cells expressing fluorescent protein-tagged p65 and time lapse

microscopy. SK-N-AS cells displayed sustained oscillations for over 20 hours, whereas

HeLa cells displayed more transient oscillations, the amplitudes of which dampened over

time. Moreover, the oscillatory NF-κB response between cells was highly heterogeneous

and asynchronous.

Since these pioneering studies, others have reported TNFα-induced NF-κB oscillations

with an average period of around 100 minutes, in a range of cell-types (Ashall et al, 2009;

Turner et al, 2010; Paszek et al, 2010; Tay et al, 2010; Sung et al, 2009). Mathematical

models have been created to recapitulate the NF-κB dynamics observed. Hypotheses

initially generated from mathematical models, and subsequently investigated in the

laboratory, have provided vital insights to regulation of NF-κB activation and dynamics

(Hoffmann et al, 2002; Ashall et al, 2009; Paszek et al, 2010). This includes models which


40

proposed that cell-cell heterogeneity is controlled by temporal differences in IκBα and

IκBε transcription profiles (Ashall et al, 2009; Paszek et al, 2010).

Heterogeneous NF-κB response within cell populations, and thereby differential gene

regulation, has highlighted the importance of studying NF-κB on the single-cell level.

Turner et al (2010) revealed that, in SK-N-AS cells, NF-κB heterogeneity increases as

TNFα dose decreases. In the inflammatory environment, NF-κB heterogeneity may be a

way of preventing the production of toxic levels of cytokines and protecting healthy cells

from damage. Cell synchrony in vivo might offer an explanation for the damage caused by

inflammation in disease states (Paszek et al, 2010).

Arguably the most important insight from single-cell observation, is on the role of NF-κB

dynamics in determining downstream gene expression profile. In vivo, cells in areas of

inflammation may release TNFα in a pulsatile manner (Covert et al, 2005; Werner et al,

2005). Ashall et al (2009) studied the effects of pulsatile TNFα-stimulation on NF-κB

dynamics in SK-N-AS cells. They found that the amplitude of successive NF-κB nuclear

translocations was dependent on the time between TNFα pulses, as a result of IKK

activation kinetics. Pulse TNFα treatment at 60 minute- or 100 minute- intervals, led to

successively lower NF-κB nuclear translocation amplitudes: this was not observed in cells

that were stimulated with 200-minute TNFα pulses. Ashall et al (2009) went on to show

differential NF-κB-dependent gene expression in response to different pulsatile treatments.

These results strongly suggested that aspects of NF-κB dynamics, such as amplitude of

nuclear translocations, could be key to determining gene expression.The amplitude of NF-

κB nuclear translocations has more recently been highlighted as a vital determinant of

TNFα-induced IL-8, A20 and IκBα mRNA production (Lee et al, 2014).

It has been proposed that the purpose of NF-κB oscillations is to allow continual sensing of

an evolving inflammatory environment. NF-κB post-translational modifications over

successive nuclear: cytoplasmic translocations may contribute to differential gene

regulation and, thereby, allow cells to produce a highly specialised response to

inflammatory stimuli (Perkins, 2006; Vermeulen et al, 2002; Saccani et al, 2003). More

investigation is required to further delineate the relationship between various aspects of

NF-κB dynamics and gene expression.


41

1.2.5. Regulation of NF-κB Transcriptional Activity

Nuclear NF-κB binds to κB sites on the promoter or enhancer sequences of NF-κB target

genes (Hoffmann et al, 2006). However, the presence of nuclear NF-κB alone is not

sufficient to induce gene expression: full transactivation of p65 requires a series of post-

translational modifications. Phosphorylation of serine residues, mediated by protein kinase

A (PKA), is required for most of the transcriptional responses that are driven by p65 (Chen

and Green, 2004). Also, phosphorylation of serine 529 is a requirement for

transcriptionally-activating p65: this can be done by casein kinase II after TNFα-

stimulation (Wang and Baldwin, 1998; Wang et al, 2000). Acetylation of p65 has also been

shown to increase transcriptional activity: p65 acetylation leads to higher induction of NF-

κB-dependent genes (Chen and Greene, 2004).

NF-κB preference for κB binding sites is conferred by the N-terminus of immunoglobulin-

like domains within the RHD (Hayden and Ghosh, 2008). Hence, one source of

transcriptional selectivity is NF-κB dimer composition (see section 1.2.2.1). Three other

mechanisms which affect the NF-κB transcriptional response are:

1) Post-translation modifications to NF-κB dimers;

2) Recruitment of co-activators and co-repressors of gene transcription and;

3) NF-κB dynamics (see section 1.2.4)

It should be noted that there are many other mechanisms by which NF-κB transcriptional

activity is modulated: the above mechanisms were selected here as they have been well

studied, in comparison to other mechanisms.

The first two mechanisms above can be intrinsically linked; post-translational

modifications determine later recruitment of transcriptional co-factors. Atypical IκB and

IKK proteins modify NF-κB-dependent gene expression, via these mechanisms. NF-κB

regulation by these proteins, and other important factors are outlined in the following

sections.

1.2.5.1. Atypical IκB Proteins

1.2.5.1.1. B-cell Lymphoma-3 (Bcl-3)

Bcl-3 was originally identified as a proto-oncogene in chronic B-lymphocyte leukaemia

(Ohno et al, 1990). Of all the atypical IκB proteins, only Bcl-3 contains a TAD and is

localized to the nucleus of cells (Nolan et al, 1993; Hayden and Ghosh, 2008). Bcl-3 can


42

bind to DNA-bound p50 and p52 homodimers and either stabilize the DNA-homodimer

complex to repress transcription or trigger the release of homodimers, thereby allowing

NF-κB access to κB sites (Hayden and Ghosh, 2008). Stabilisation of DNA-bound

repressive complexes mediated by Bcl-3 has been implicated in LPS tolerance (Wessells et

al, 2004; Carmody et al, 2007; Ghosh and Hayden, 2008). As this interaction is dependent

on the nuclear localisation of Bcl-3, it is mediated by Bcl-3 phosphorylation and

ubiquitination (Nolan et al, 1993; Caamano et al, 1996; Bundy and McKeithan, 1997).

Cylindromatosis (CYLD) can negatively regulate the activity of Bcl-3 by inhibiting its

ubiquitination and thereby preventing nuclear entry (Massoumi et al, 2006).

Phosphorylated Bcl-3 can endow target p50 and p52 homodimers with transcriptional

activity (Nolan et al, 1993; Caamano et al, 1996; Bundy and McKeithan, 1997). Rocha et

al (2003) showed that reduction in Bcl-3 expression, caused by p53 activation, allows p52

homodimers to repress Cyclin D1 expression by binding to κB sites on the promoter region

of the gene. Cyclin D1 has been shown to mediate NF-κB-dependent proliferation of NPCs

(Widera et al, 2006a).

1.2.5.1.2. IκBζ

IκBζ expression can be induced by NF-κB signalling in a ligand-specific manner

(Yamazaki et al, 2005). Although it lacks a well-defined TAD, IκBζ is more homologous

to Bcl-3 than other IκB proteins (Hayden and Ghosh, 2008). Like Bcl-3, IκBζ binding to

p50 homodimers may confer transcriptional activity (Yamamoto et al, 2004).

The loss of IκBζ has been reported to result in the loss of expression of a subset of NF-κB

target genes (Yamamoto et al, 2004). Of these, IκBζ has a particularly profound effect on

IL-6 expression: induction of IL-6 is abrogated in IκBζ -deficient mice. IκBζ binds to p50

homodimers located on κB sites within the IL-6 promoter: it is thought that this interaction

is vital for IL-6 expression (Yamamoto et al, 2004).

1.2.5.1.3. IκBδ

IκBδ was initially identified in T-cells undergoing negative selection (Fiorini et al, 2002).

The exact role of IκBδ in regulating NF-κB transcriptional activity is largely unknown.

IκBδ preferentially binds to p50 and its overexpression has an inhibitory effect on NF-κB

reporter gene expression; together, this suggests that IκBδ may promote the formation of

repressive NF-κB-DNA complexes (Fiorini et al, 2002).


43

1.2.5.2. IKKα and IKKβ

IKKα has a dual function in NF-κB transcriptional activity, as it is able to promote and

inhibit the expression of NF-κB target genes (Scheidereit, 2006; Chen and Greene, 2004;

Hayden and Ghosh, 2008). IKKα-deficient macrophages express higher levels of NF-κB

target pro-inflammatory genes than wild-type cells (Li et al, 2005). On the other hand,

IKKα-mediated phosphorylation events can promote chromatin opening and, thereby,

facilitate the binding of NF-κB to κB sites (Hoberg et al, 2004). Phosphorylation of SMRT

complexes induces the release of histone deacetylase 3 from these complexes which can, in

turn, increase NF-κB transcriptional activity by increasing p65 acetylation. This effect

requires the removal of a histone acetyltransferase complex (Hoberg et al, 2006; Chen and

Greene, 2004).

IKKα can also facilitate p65 binding to the transcriptional co-activator CREB-binding

protein (CBP), by CBP phosphorylation at serine 1382 and serine 1386 (Huang et al,

2007).

1.2.5.3. Other Factors influencing NF-κB Transcription.

One of the first kinases implicated as a regulator of p65 transcriptional activity was protein

kinase C zeta (PKCζ). PKCζ-driven phosphorylation of p65 at serine 311 is required for

CBP recruitment to transcriptionally active p65-containing NF-κB dimers (Zhong et al,

1998; Duran et al, 2003).

Another kinase, MAP kinase-activated protein kinase 2 (MAPKAPK2), regulates p65

phosphorylation via its target substrate, Hsp27 (Gorska et al, 2007). MAPKAPK2-deficient

mice display lower induction of NF-κB-dependent pro-inflammatory cytokines, compared

to wild-type mice. Deficiencies in MAPKAPK2 or Hsp27 cause an increase in p65

phosphorylation at serine 276: this finding is associated with increases in IκBα

transcription and earlier p65 nuclear exit (Gorska et al, 2007).

MAPKAPK2 is also involved in p38-mediated regulation of NF-κB dependent transcripts.

The p38-MAPKAPK2 pathway promotes translation of TNFα mRNA, produced

downstream of NF-κB activation (Kontoyiannis, et al, 1999; Neininger et al, 2002). Also,

p38-mediated phosphorylation of histone 3 at serine 10 can increase p65 binding to

IL12p40 and IL-6 promoters (Saccani et al, 2002).


44

As well as phosphorylation, ubiquitination regulates NF-κB transcriptional activity

(Tanaka et al, 2007). PDZ and LIM domain protein 2 (PDLIM2), a nuclear ligase,

ubiquitinates p65 and transports it to nuclear compartments called PML nuclear bodies.

This promotes degradation of p65-containing NF-κB dimers and, thereby, transcriptional

silencing (Ghosh and Hayden, 2008; Tanaka et al, 2007).

1.2.6. Termination of the NF-κB Response

IκBα and IκBε are vital in the inhibition of NF-κB during the early stages of NF-κB

activation: these proteins bind to and export nuclear NF-κB dimers (Hayden and Ghosh,

2008; Perkins 2006). Other proteins, such as A20 and CYLD, exert their action on NF-κB

at later stages of the NF-κB response and thereby determine the persistence of NF-κB

activation (Lee et al, 2000; Brummelkamp et al, 2003). Some mechanisms of this

inhibition will be outlined here.

1.2.6.1. TNFα-induced Protein 3 (A20)

Discovered in 1990, the zinc finger protein TNFα-induced protein 3 (A20) is an ubiquitin-

editing enzyme (Opipari et al, 1990; Jaattela et al, 1996; He and Ting, 2002). A20-deficient

MEFs display prolonged TNFα-induced NF-κB activation and NF-κB-DNA binding (Lee

et al, 2000). Deficiency of A20 in mice causes severe inflammation and premature death,

highlighting A20 as an important factor in the resolution of inflammation (Lee et al, 2000).

Unlike IκB proteins, A20 does not directly interact with NF-κB, but instead targets

components of the IKK complex. A20 targets include IKKα and IKKβ (Zhang et al, 2000),

as well as upstream molecules, TNFR1, RIP1 and TRAF6 (Song et al, 1996; Heyninck et

al, 1999; Heyninck and Beyaert, 1999).

A20 directly modifies RIP1 via its ubiquitin-editing domains: an N-terminal ovarian

tumour deubiquitinating domain and 7 carboxyterminal zinc finger domains (Wertz et al,

2004; Shembade et al, 2008). These domains each have different targets: the N-terminal

domain preferentially deubiquitinates K63-linked ubiquitin chains from RIP1, whereas the

C-terminal domain catalyzes the polyubiquitination of K48 on RIP1. This process of site-

specific ubiquitination and deubiquitination triggers the proteasomal degradation of RIP1

(Wertz et al, 2004; Shembade et al, 2008).

A20 interactions with the proteins Tax1 binding protein 1 (Tax1BP1), Ring finger protein

11 and Itchy E3 ubiquitin protein ligase (Itch) are required to terminate TNFα-induced NF-


45

κB activation (Shembade et al, 2007; Shembade et al, 2008; Shembade et al, 2009).

Deficiencies in Tax1BP1 and Itch lead to a prolonged TNFα-induced NF-κB response: as

observed in A20-deficient MEFs. In these Tax1BP1-deficient and Itch-deficient MEFs,

enriched K63-linked ubiquitination of TRAF6 and RIP1 was observed, respectively (Iha et

al, 2008; Shembade et al, 2007).

The mechanisms behind the formation of the A20 ubiquitin-editing complex are yet

unknown. IKKα-mediated phosphorylation of serine residues on Tax1BP1 induces

formation of the A20 complex, by unknown mechanisms (Shembade et al, 2011). In turn,

A20 can promote the phosphorylation of IKKα and IKKβ within the IKK complex (Zhang

et al, 2000). Phosphorylated IKKβ can undergo autophosphorylation, resulting in

decreased kinase activity (Delhase et al, 1999): it has been speculated that A20 can

stabilise inactive, phosphorylated IKKβ (Wajant et al, 2003). Together, this creates a

closed loop: IKKα-drives activation of the A20 complex which, in turn, feeds back to

deactivate IKKα, as well as IKKβ. From this, it has been postulated that assembly of the

A20 complex may be dependent on signalling from activated receptors, such as TNFR1

(Pujari et al, 2013).

1.2.6.2. Cylindromatosis (CYLD)

Cylindromatosis (CYLD) is an evolutionarily conserved deubiquitinating enzyme that was

originally identified in tumour development (Bignell et al, 2000). The C-terminal of CYLD

contains three cytoskeleton-associated proteins-glycine (CAP-Gly) motifs and a domain

which comprises the catalytic pocket-forming active histidine and cysteine residues

(Courtois, 2008).

The first evidence of CYLD involvement in NF-κB inhibition stemmed from a shRNA

screening study (Brummelkamp et al, 2003). CYLD-targeting shRNA could prolong

TNFα-induced NF-κB activation in HeLa cells. NF-κB activation was also inhibited by

CYLD overexpression in IL-1 and TNFα-stimulated cells (Kovalenko et al, 2003;

Brummelkamp et al, 2003; Trompouki et al, 2003).

Since its discovery as an NF-κB regulator, it has been found that CYLD is unable to

deubiquitinate IκB proteins so, like A20, targets IKK components or molecules upstream

of IKK (Courtois, 2008). CYLD overexpression leads to deubiquination of TRAF proteins,

NEMO, RIP1 and TAK1 (Kovalenko et al, 2003; Brummelkamp et al, 2003; Trompouki et

al, 2003; Yoshida et al, 2005; Wright et al, 2007); conversely, CYLD knockdown results in


46

increased ubiquitination of these proteins (Zhang et al, 2006; Reiley et al, 2007; Wright et

al, 2007; Reiley et al, 2005; Jin et al, 2008). Together, this suggests that CYLD

constitutively prevents IKK activation and, thereby, NF-κB activation.

As yet, all the mechanisms by which CYLD inhibits NF-κB are not fully understood. It has

been suggested that CYLD can exert its effects via physical interaction with target

molecules: the N-terminal proline-rich area of NEMO directly associates with a CYLD

CAP-Gly motif (Kovalenko et al, 2003; Trompouki et al, 2003; Saito et al, 2004). It has

been speculated that this association may allow CYLD to interact with NEMO-bound RIP1

and TRAF2 (Kovalenko et al, 2003). However, it appears CYLD target specificity is

heavily regulated by its association with adaptor proteins (Courtois, 2008). The adaptor

protein p62 mediates interactions between CYLD and TRAF6 (Jin et al, 2008; Wooten et

al, 2008). The consequences of these interactions require further investigation.

Interestingly, CYLD mRNA expression was reduced in TNFα-treated, IKKα-, IKKβ- and

NEMO-knockout MEFs (Jono et al, 2004). These findings suggest that, similar to A20,

CYLD expression may be regulated by NF-κB activation. As well as this, there is evidence

to suggest that CYLD activation is driven by NEMO-mediated phosphorylation events

(Reiley et al, 2005). Although the outcome of these phosphorylation events is unknown, it

appears that stimulus-induced NEMO activation may initiate CYLD negative feedback.

The studies discussed here suggest that CYLD has multiple roles in preventing IKK

activation.

1.3. NF-κB in the Central Nervous System (CNS)

Much of what is known about NF-κB has been derived from non-neural cells. Here, the

role of NF-κB in the CNS is outlined, with a particular focus on the central mediators of

neuroinflammation; microglia and NPCs.

1.3.1 Overview of NF-κB Components in the CNS

NF‐κB pathway components are present throughout the nervous system. As in non-neural

cells, the most ubiquitously expressed are RelA, p50 and IκBα- although NF‐κB

expression levels are cell‐type specific (O'Neill and Kaltschmidt, 1997). Dimers of

p65:p50 have been found in astrocytes (Sparacio et al, 1992), neurons (Kaltschmidt et al,


47

1993; Schmidt-Ullrich et al, 1996), microglia (Nakajima and Kohsaka, 1998) and neural

stem cells (Denis-Donini et al, 2005).

The NF-κB pathway has a CNS-specific NF‐κB subunit, called neuronal κB factor

(Moerman, 1999), and a set of CNS‐specific stimuli which includes nerve growth factor

(NGF; Carter et al, 1996), brain-derived neurotrophic factor (BDNF; Gavalda et al, 2009)

and amyloid precursor protein (Barger and Mattson, 1996). In turn, NF-κB regulates the

expression of nervous system-specific factors, including BDNF (Kairisalo et al, 2009; Saha

et al, 2006), and NGF (Heese et al, 2006).

1.3.2. NF-κB Function in the CNS

Most NF-κB knockouts are embryonic lethal due to defects unrelated to the nervous

system; this provides a limited time window for observing the role of NF-κB in the

developing CNS (Beg et al, 1995). Transient NF-κB activation is observed during

development in the spinal cord and certain brain areas (Schmidt-Ullrich et al, 1996). RelB

knockout mice show no CNS developmental defects (Weih et al, 1995), but RelA, p50 and

c-Rel have been implicated in CNS development, mainly through experiments with

knockout mice (Middleton et al, 2000; Nickols et al, 2003; Pizzi et al, 2002; Köntgen et al,

1995). RelA knockout mice display reduced neuronal survival in response to ciliary

neurotrophic factor (Middleton et al, 2000) and p50 knockout mice develop normally, but

later show increased age-related degeneration and apoptosis (Grumont et al, 1998; Lu et al,

2006). Another study showed that p50 knockout mice exhibit greater tissue damage after

excitotoxic stimulation, suggesting that p50-containing dimers can serve a neuroprotective

function (Yu et al, 1999). Also, survival of neurons in c-Rel knockout mice is severely

impaired.

In the adult CNS, NF-κB is important in synaptic plasticity, learning and memory

formation (Kaltschmidt et al, 2006a). Knockout of c-Rel impairs memory formation, by

impairing synaptic-plasticity (Ahn et al, 2008). Also, NF-κB inhibition in hippocampal

neurons diminishes neurite extension and branching, thereby impairing the formation of

memory-associated neuronal connections (Sanchez-Ponce et al, 2011). TNFR1 and p65

double knockout mice have a reduced capacity for spatial memory formation (Meffert et al,

2003) and short term memory formation is impaired in p50 knockout mice (Denis-Donini

et al, 2008). Together, these observations implicate the canonical NF-κB activation

pathway in memory formation. The mechanisms by which NF-κB regulates memory


48

formation are unclear, although they are thought to involve PKA expression and, thereby,

CREB activity (Kaltschmidt et al, 2006).

This has important implications when considering inhibition of NF-κB as a therapeutic in

neuroinflammation: interfering with NF-κB activity could have detrimental effects on

normal brain function.

NF‐κB activity in the nervous system is also vital in the vaccination process. Vaccination

is the term used to describe a phenomenon in which a subtoxic dose of an inflammatory

substance can be protective against a later toxic dose of that substance. In the case of

amyloid-β, this vaccination process is dependent on NF‐κB activation (Kaltschmidt et al,

1999; Kaltschmidt et al, 2002). This suggests that NF-κB activity may have a pivotal role

in determining cell fate in AD.

NF-κB activation corresponds to apoptosis and disease onset in mouse models of AD (Niu

et al, 2010). Also, NF‐κB can induce the expression of amyloid precursor protein, the

amyloid-β precursor (Grilli et al, 1996), as well as being activated by it (Pahl, 1999). This

positive feedback motif might result in NF-κB-driven runaway inflammation, perpetuating

the proinflammatory environment and, consequently, tissue damage. It could be speculated

that the same feedback motif may also be created by TNFα in neurodegenerative diseases,

such as AD (Niu et al, 2010; Cartier et al, 2005).

As in non-neural cells, NF-κB is a major controller of cell survival, via its regulation of

pro- and anti-apoptotic factors, which include Bcl-2, Bax and c-IAPs (Tamatani et al,

1999; Baud and Karin, 2001; Shou et al, 2002). NF-κB-dependent expression of Cyclin D1

is associated with apoptosis of cortical and striatal neurons (Liang et al, 2007). In contrast,

NF‐κB inhibition in neurons reportedly increases their vulnerability to toxins like amyloid‐

β. Prostrate apoptosis response-4 (a protein implicated in AD) also causes neuron death,

partly via NF‐κB inhibition (Guo et al, 1998; Mattson and Camandola, 2001).

Interestingly, NF‐κB levels are reportedly elevated in the forebrains of AD patients,

particularly around senile plaques (Kaltschmidt et al, 1997; Kaltschmidt et al, 1999).

Moreover, microglial NF-κB inhibition prevents amyloid β-induced cell death (Chen et al,

2005). This highlights the importance of studying NF-κB at the single-cell level,

particularly when studying mixed cell populations.

Mattson and Camandola (2001) proposed that, as observed in non-neural cells, stimuli

induce different NF-κB-dependent gene expression profiles, according to cell type and


49

receptor engagement in the nervous system. They speculated that TNFR2 signalling in

neurons causes the upregulation of anti-apoptotic genes, whereas TNFR1 activation in

microglia promotes the production of toxic agents. This idea is supported by studies that

report TNFα-induced neuronal toxicity only in the presence of glial cells (Mir et al, 2008;

Taylor et al, 2005; Tolosa et al, 2011). Microglial-specific inhibition of NF-κB has been

suggested as a form of therapy for AD (Chen et al, 2005).

In summary, NF‐κB activity is central in a network that determines cell survival in

neuroinflammation. A better understanding of the complex profiles of cell-type specific

NF-κB activation and downstream gene expression will help to design therapies that can

manipulate the neuroinflammatory process. The next sections will outline current

knowledge on NF-κB activation in vital cellular components of the neuroinflammatory

network: microglia and NPCs.

1.3.3. NF-κB Activation in Microglia and Neural Progenitor Cells

NF‐κB activation in microglia is essential for their exertion of neuroprotective properties:

microglial NFκB activation results in clearance of amyloid‐β deposits in animal models of

AD (Li and Schmidt, 1997; Herber et al, 2007). In rat microglia, LPS exposure also causes

an NF‐κB‐dependent increase in NGF release (Heese et al, 1998). These observations

suggest that microglial NF-κB is involved in both phagocytosis and neuroprotection.

Microglial NF‐κB activation plays a multidimensional role in neuroinflammation; NF‐κB‐

dependent gene expression is implicated in classical and alternative activation, as well as

acquired deactivation (Colton, 2009).

Microglia control the fate of NPCs through the release of NF‐κB‐dependent factors such as

nitric oxide (NO), COX‐2 and TNFα (Das and Basu, 2008). Microglial-derived TNFα

induces apoptosis of NPCs, via NPC NF-κB activation (Guadagno et al, 2013).

Interestingly, non-activated microglia reportedly promote NPC proliferation (Liu et al,

2013a), whereas activated microglia induce NPC apoptosis (Guadagno et al, 2013; Liu et

al, 2014; Liu et al, 2013b). In turn, NPCs promote activation and proliferation of microglia

(Forstreuter et al, 2002; Mosher et al, 2012; Liu et al, 2013a).

The therapeutic effect of NPCs, observed in many disease states, is dependent on NPC

migration into sites of injury, proliferation and survival (Martino and Pluchino, 2006). In


50

particular, NF-κB-mediated proliferation and apoptosis have been well studied in NPCs

(Widera et al, 2006a; Widera et al, 2006b; Piotrowska et al, 2006; Guadagno et al, 2013).

Although most insults in the CNS lead to NPC proliferation (Parent, 2003), opposing

effects have also been observed. Proliferation of NPCs from the subventricular zone is

promoted by NF-κB activity: this effect is mediated by the downstream expression of NF‐

κB‐dependent genes, c-myc and Cyclin D1 (Widera et al, 2006a). It is generally believed

that TNFR1 activation suppresses NPC proliferation, whereas TNFR2 promotes NPC

proliferation and survival (Das and Basu, 2008). We can conjecture that differences in

single‐cell NF-κB dynamics may be central to determining NPC fate.

To date, NF-κB activation in microglia and NPCs has been measured using population-

level biochemical assays including EMSA and p65 Western blots; single-cell observations

have been made via p65 immunostaining in fixed cells (Sheppard et al, 2011; Widera et al,

2006a; Piotrowska et al, 2006). Due to its dynamic and pleotropic nature, simply

measuring NF-κB activation status is not an accurate indicator of downstream effects: NF-

κB activation has been reported in classical and alternative activation of microglia (Colton,

2009), as well as proliferation and apoptosis of NPCs (Widera et al, 2006a; Widera et al,

2006b). In order to understand the consequences of NF-κB activation, it has to be studied

in greater depth, from observing single-cell dynamics to measuring downstream gene

expression, and consequent cell fate decisions.

1.4. Thesis Aims

The studies outlined in this chapter provide evidence for vital NF-κB mediated interactions

between microglia and NPCs: these interactions have yet to be thoroughly investigated.

TNFα, a potent NF-κB activator, is upregulated in many disease states, most notably AD.

Single-cell NF-κB dynamics contributes to gene expression and, thereby, cell

survival/apoptosis: these life/death decisions govern neuroinflammatory outcome.

Given the importance of microglia and NPCs in these neuroinflammatory states, the main

aim of this thesis was to investigate NF-κB-mediated interactions between these cells, the

downstream gene expression profiles and the consequent effects on microglial and NPC

fate. TNFα stimulation could be used to mimic neuroinflammatory conditions in vivo:

these results would inform on the role of NF-κB in neuroinflammation. As TNFα is a


51

potent activator of the canonical NF-κB pathway, the p65:p50 heterodimer was the primary

focus of this project.


52

2. Materials and Methods


53

2.1. Materials

2.1.1. Reagents

Standard laboratory chemicals were obtained from Sigma-Aldrich (USA) or Fisher

Scientific (UK), unless otherwise stated. Tissue culture media, trypsin, non-essential amino

acids (NEAA), bovine serum albumin (BSA) and phosphate buffered saline (PBS) were

purchased from Sigma-Aldrich. Foetal bovine serum (FBS) was purchased from Life

Technologies (USA). Murine recombinant TNFα was obtained from Merck Millipore

(Germany). D-luciferin was obtained from Biosynth AG (Switzerland). Primers for

quantitative polymerase chain reactions (Q-PCR) were obtained from Sigma-Aldrich. All

dishes, plates, transwells and flasks used in experiments were obtained from Corning

(USA), with the exception of microscopy dishes, which were obtained from Greiner Bio-

One (Germany).

2.1.2. Vectors

2.1.2.1 Luciferase Construct

The NF-κB-responsive luciferase construct (NF-luc) contains five κB site repeats upstream

of the TATA box controlling the expression of a firefly luciferase gene (Stratagene, USA).

2.1.2.2 Fluorescent Fusion p65 Constructs

In the course of this project, a fluorescent fusion p65 plasmid, bacterial artificial

chromosome (BAC) and lentiviral construct have been used. These constructs were made

by members of the laboratory group and validated in HeLa, SK-N-AS and mouse

embryonic fibroblast cells (Nelson et al, 2004 and unpublished data). The p65 reporter

plasmid expresses p65 fused at the C-terminus to Discosoma sp.-Red-Express (DsRedXP)

under the control of the CMV promoter. The p65 BAC reporter construct contains a 108 kb

fragment of the human genome encompassing the p65 locus, modified to express p65 fused

at the C-terminus to DsRedXP. The lentiviral reporter plasmid expresses p65 fused at the

C-terminus to enhanced green fluorescent protein (eGFP) under the control of the ubiquitin

ligase C promoter.


54

2.2. Methods

2.2.1. Propagation of Vectors

Plasmid DNA was purified using the GenElute plasmid miniprep kit (Sigma-Aldrich) or

the PureLink HiPure plasmid maxiprep kit (Life Technologies), according to the

manufacturer’s instructions. BAC DNA was purified using the NucleoBond BAC 100 kit

(Macherey-Nagel, Germany), according to the manufacturer’s instructions. Purified DNA

was the kind gift of members of the White laboratory group.

2.2.2. Cell Culture

2.2.2.1. Cell Lines and Culture Maintenance

Murine microglia and neural progenitor cell lines, C17.2 and BV.2, were selected for use

in this investigation due to their reported roles in neuroinflammatory processes.

C17.2 is a multipotent murine neural progenitor cell line that has demonstrated therapeutic

potential in many disease models (Teng et al, 2002; Park et al, 2002; Ourednik et al, 2002).

These cells are non-tumourigenic and capable of differentiation into a variety of neural cell

types, including neurons, glia and oligodendrocytes (Ryder et al, 1990).

BV.2 cells express many properties of primary microglial cells, including changes in

activation status, physical characteristics, ion channel expression and relationship with

astrocytes. In response to LPS, they display anti-microbial activity, phagocytic behaviour

and proteomic changes that are comparable to primary microglia (Bocchini et al, 1992;

Blasi et al 1990; Henn et al, 2009). Also, classically-activated microglial cells can activate

nearby astrocytes; an action which is reproduced by BV.2 cells in culture (Henn et al,

2009).

C17.2 and BV.2 cell lines were cultured in Dulbecco’s Modified Eagle’s Medium

(DMEM) supplemented with 10% (v/v) FBS and maintained at 37°C and 5% CO2 in a

humidified New Brunswick Galaxy 170S incubator (Eppendorf, Germany). Cells were

split at a ratio of 1:10, every 2-3 days. Cell cultures were discarded upon reaching passage

30.

RAW267.4 cells, a murine peripheral macrophagic cell line, were maintained in the same

conditions as C17.2 and BV.2 cells. SK-N-AS cells, a human neuroblastoma cell line, were


55

cultured in Minimal Essential Medium (MEM) supplemented with 10% (v/v) FBS and 1%

(v/v) NEAA.

2.2.2.2. Long-term Storage of Cell Lines

Cell stocks were diluted to 2x106 cells per ml in DMEM containing 10% (v/v) FBS

solution and 10% (v/v) dimethyl sulfoxide. This cell mixture was aliquoted into cryovials

(1 ml/vial) and stored at -80°C overnight, before transfer to liquid nitrogen storage.

2.2.2.3. Thawing Cells from Frozen Stocks

To grow new cell cultures, cryovials were removed from liquid nitrogen storage, defrosted

at 37°C in a water bath for one minute and poured into 9 ml of warm DMEM containing

10% (v/v) FCS. This solution was then centrifuged at 160 x g for 5 minutes in an

Eppendorf 5804 centrifuge (Eppendorf). The supernatant was removed and the cell pellet

was resuspended in fresh, warm culture medium. Cells were transferred into a sterile tissue

culture flask and placed at 37°C in a 5% CO2 incubator.

2.2.2.4. Cell Enumeration

Cell counts were determined using either a Bio-Rad TC10 cell counter (Bio-Rad, USA) or

a Coulter Z2 Counter (Beckman Coulter, USA), according to the manufacturer’s

instructions.

2.2.2.5. Plating Cells for Experiments

For most experiments, cells were plated directly into the final experimental dish/plate (see

sections 2.2.2.5.1. and 2.2.2.5.2 for exceptions). Table 2.1 shows the dishes and the cell

densities used for different types of experiments. With the exception of NanoString

experiments, all experiments were performed in triplicate.


56

Table 2.1: Cell numbers, dishes, cell growth area and media volume used in

experiments.

Experiment

Conducted

Total Number

of Cells Dish/Plate

Growth

Area

Media

Volume

Live Cell

Imaging 5x10

4 cells

35 mm Greiner glass

bottomed dishes 8.7 cm

2

3 ml

Western blot 5x105 cells 60 mm dishes 21 cm

2 3 ml

Cell Viability

Assays

(without

PDTC)

1000 and 3000

cells per well 96-well plate 0.32 cm

2 100 µl

Apoptosis

Assays

(without

PDTC)

1000 and 3000

cells per well 96-well plate 0.32 cm

2 100 µl

Flow

Cytometry 1x10

6 cells 60 mm dishes 21 cm

2 3 ml

ELISA 2x106 cells 60 mm dishes 21 cm

2 3 ml

NanoString 1x105

cells 60 mm dishes 21 cm2 3 ml

Q-PCR 5x105

cells 60 mm dishes 21 cm2 3 ml

Transwell

Experiments/

Flow

Cytometry/

Nanostring

See specific

experiments

for cell number

Target cell type was seeded

in a 6-well plate. Non-target

cell type was seeded in

transwell inserts, which

were placed in the wells.

Well

surface

area=

8.96 cm2

Transwel

l insert

area =

4.7 cm2

4 ml

2.2.2.5.1. Plating Cells for Live Cell and Endpoint Luminometry

C17.2 cells were trypsinised and 5x105 cells were seeded in a 100 mm dish. The following

day, cells were transfected with the NF-luc construct (see section 2.2.4.1). Approximately

24 hours after transfection, C17.2 cells were trypsinised and seeded in a 24-well plate,

according to details in Table 2.2. For co-culture luminometry, untransfected BV.2/SK-N-

AS/RAW267.4 cells were seeded directly into the 24-well plate with transfected C17.2

cells at an appropriate ratio.

Table 2.2: Cell numbers, cell growth area and media volume in luminometry

experiments

Cell Type Total Number of Cells (Per

Well) Growth Area Media Volume

C17.2 2x104 1.9 cm

2

1 ml per well BV.2,

SK-N-AS or

RAW267.4

Ratio of 1:2= 4x104 cells

Ratio of 1:4= 8x104 cells

Ratio of 1:8=1.6x106 cells

1.9 cm2


57

2.2.2.5.2. Plating Cells for Cell Viability and Apoptosis Assays with Inhibitor

Treatment

Pyrollidine dithiocarbamate (PDTC) is an NF-κB inhibitor. For experiments with PDTC

treatment, 5x105 cells were initially plated in a 60 mm dish. The day after plating, cells

were incubated with 0.1 mM PDTC for 30 minutes at 37°C. Cells were then washed with

PBS, to remove PDTC, and seeded into 96-well plates, according to details in Table 2.1,

for viability and apoptosis readings.

2.2.3. Treatment of Cells with TNFα

Murine recombinant TNFα (10 µg) was resuspended in 1 ml PBS containing 0.1% (w/v)

BSA to make a working stock solution with a concentration of 10 ng/µl. Aliquots were

stored at -80°C until use. Unless otherwise stated, 20ng/ml TNFα was used to stimulate

cells in experiments.

2.2.4. Transfections and Transductions

2.2.4.1. Plasmid Transfections

Cells were transfected with the p65 plasmid using ExGen 500 (Thermo Fisher Scientific,

USA) at a reagent: DNA ratio of 1: 8 (e.g. 1 µg DNA to 8 µl ExGen 500). Cells were

incubated with the transfection mixture for at least 24 hours before imaging or splitting

cells for experiments.

2.2.4.2. BAC Transfections

Cells were transfected with the p65 BAC using ExGen 500 (Thermo Fisher Scientific,

USA) at a reagent: DNA ratio of 1: 10. Cells were grown in selection medium (DMEM

supplemented with 10% (v/v) FCS and 1400 µg/ml zeocin (Thermo Fisher Scientific,

USA) until they were suitable for ring cloning. Cells were cultured in selection medium for

approximately 2 months to ensure the production of BAC-stable populations. BAC-stable

clones were labelled with letters or numbers e.g. clone A, clone 3, clone 5.

2.2.4.3. Lentiviral Transductions

Lentivirus was prepared for transduction of C17.2 and BV.2 cells by J. Bagnall (University

of Manchester). HEK293T cells were transfected with third generation packaging vectors

and a lentivirus-compatible p65-eGFP vector. Virus was then harvested and subsequently


58

concentrated by ultracentrifugation. Concentrated virus was used to transduce C17.2 and

BV.2 cells.

2.2.5. Luminometry

2.2.5.1. Live Cell Luminometry

Cells were transfected with NF-luc and/or seeded according to section 2.2.2.5.1.

Approximately 24 hours after seeding in 24-well luminometry plates, D-luciferin was

added to each well to a final concentration of 1 mM and left to incubate for at least 3 hours.

Cells were then stimulated with different doses of TNFα (control cells were left

unstimulated), a breathable membrane was used to seal the plate and it was placed in a

FLUOstar Omega microplate reader running Omega software v3.00 (BMG Labtech,

Germany). Luminescence readings were taken every 15 minutes for at least 5 hours per

experiment, using an integration time of 18 seconds. Experiments were performed in

triplicate, with three technical replicates per plate. Data was exported from MARS Data

Analysis software v2.40 (BMG Labtech). One-way ANOVAs were performed to assess

significant differences in NF-luc induction between culture conditions.

2.2.5.2. Endpoint Luminometry

Cells were transfected with NF-luc and/or seeded according to section 2.2.2.5.1. C17.2

mono-cultures and C17.2 co-cultures (with BV.2 cells seeded in transwell inserts) were

investigated. Approximately 24 hours after seeding, some cells were left unstimulated and

others were stimulated with different doses of TNFα. At an appropriate time point after

treatment, cells were washed with PBS and lysed in 200 μl luminometry lysis buffer

(0.025% (w/v) dithiothreitol, 1% (w/v) BSA, 25 mM Tris PO3 pH 7.75, 1% (v/v) Triton X-

100, 15% (v/v) glycerol, 0.1 mM EDTA, 8 mM MgCl2). Plates were shaken at room

temperature for 15 minutes. For analysis, ATP was added to each sample to a final

concentration of 1 mM and 80 μl duplicate samples were transferred to a 96-well

luminometry plate. Experiments were performed in triplicate. Unpaired t-tests were used

to assess significant differences.

2.2.6. Live Cell Imaging

Cells were imaged using a LSM 5 Exciter Axiovert microscope (Zeiss, Germany), with a

20X objective. During these experiments, cells were maintained in a humidified chamber,


59

at 37°C and 5% CO2. An argon ion 488 nm laser was used to excite eGFP and the emitted

light was detected using a bandpass filter of 505-530 nm. A green helium ion 543 nm laser

was used to excite DsRedXP; emission was detected using a 560 nm long-pass filter.

Data acquisition was performed at a resolution of 512 x 512 pixels, using LSM software

AIM (version 4.1; Zeiss). Acquisition was started after selection of 10 to 12 spatial

locations per imaging dish. Time taken to image cells across all locations did not exceed 7

minutes in any experiment. Unstimulated cells were imaged for at least 2 hours before

TNFα was added to the dish.

All microscopy experiments were performed in triplicate, with the exception of co-cultured

lentivirus transduced BV.2 cells: only one microscopy experiment was performed with this

co-culture.

2.2.6.1. Analysis of Live Cell Imaging Experiments

Cell Tracker software (Perkins, 2007) was used to obtain fluorescence intensity readings

for cell nuclei. Pre-stimulatory nuclear intensities were averaged for each cell; post-

stimulatory nuclear fluorescence was normalised to these mean values. These values were

then interpolated to allow data from replicate experiments to be collated and plotted

together.

2.2.7. Western Blotting

2.2.7.1. Sample Preparation

Cells were plated according to section 2.2.2.5. The day after plating, cells were stimulated

with TNFα (section 2.2.3.). At the appropriate timepoint after treatment, cells were washed

with cold PBS and lysed by the addition of 200 μl lysis buffer (1% (w/v) sodium dodecyl

sulphate (SDS), 10% (v/v) glycerol, 10% (v/v) β-mercaptoethanol, 40 mM tris HCl pH 6.8,

0.001% (w/v) bromophenol blue). Cell lysates were stored at -20°C until use. Experiments

were performed in triplicate. Unstimulated protein samples were used in Western blots for

measuring p65 and IκBα protein levels across cell lines: one Western blot was performed

per cell line.

2.2.7.2. Preparation of Gels for SDS Polyacrylamide Gel Electrophoresis (PAGE)

Gels for SDS-PAGE were cast using the Mini-Protean 3 system (Bio-Rad). After set-up of

the casting apparatus, the resolving gel (10% acrylamide, 125 mM Tris HCl pH 6.8, 0.1%


60

(w/v) SDS, 0.064% (w/v) ammonium persulphate (APS), 0.064% (v/v) N,N,N’,N’-

tetramethylethylenediamine (TEMED)) was poured between the glass plates and left to

solidify. The resolving gel was topped with stacking gel (4% acrylamide, 375 mM Tris

HCl pH 8.8, 0.1% (w/v) SDS, 0.06% (w/v) APS, 0.12% (v/v) TEMED) and wells made by

insertion of a comb into the unset gel. Once set, gels were used immediately for protein

separation by SDS-PAGE.

2.2.7.3. Protein Separation by SDS-PAGE

Gels were loaded into a Mini-Protean gel tank and connected to a PowerPac Basic power

supply unit (both Bio-Rad). The tank was filled with SDS running buffer (25 mM Tris, 192

mM glycine, 3.4 mM SDS). Protein samples were heated at 100°C for 10 minutes prior to

loading onto the gel. ColorPlus prestained protein ladder (New England Biolabs, USA) and

horseradish peroxidase (HRP)-linked protein ladder (Cell Signalling Technology, USA)

were loaded for identification of protein size. Protein samples were separated at 100 volts

for 20 minutes, and then at 160 volts for 30 to 90 minutes, until markers appeared

sufficiently separated.

2.2.7.4. Transfer of Protein to Nitrocellulose Membrane

Proteins were transferred from the SDS-PAGE gel to BA83 Protran nitrocellulose

membrane (GE Healthcare, UK) using a Mini Trans-Blot Cell (Bio-Rad). Transfer was

made by wet blotting at 300 mA in chilled transfer buffer (20% methanol, 25 mM Tris, 200

mM glycine), for approximately 1-2 hours.

2.2.7.5. Immunostaining of Nitrocellulose Membrane

Nitrocellulose membranes were incubated in blocking buffer (5% (w/v) skimmed milk

powder, 20 mM Tris HCl pH 7.8, 140 mM NaCl, 0.1% (v/v) Tween 20) for 1 hour and

then incubated with the primary antibody in blocking buffer at 4°C overnight (see Table

2.3 for antibodies used). Cyclophilin A (CycA) and α-tubulin antibodies were used as

loading controls.


61

Table 2.3: Primary and secondary antibodies used in Western blots

Antibody target Manufacturer Type of Antibody Working Dilution

α-tubulin Cell Signaling Primary 1:1000

IκBα Cell Signaling Primary 1:1000

Cyclophilin A Cell Signaling Primary 1:1000

p65 Cell Signaling Primary 1:1000

Anti-HRP Cell Signaling Secondary 1:2000

Anti-rabbit IgG (HRP-

conjugated) Cell Signaling Secondary 1:2000

Membranes were washed three times for five minutes with wash buffer (20 mM Tris HCl

pH 7.8, 140 mM NaCl, 0.1% (v/v) Tween 20). After washing, membranes were incubated

with the secondary antibody in blocking buffer at room temperature for one hour.

Membranes were washed three times for five minutes with wash buffer, and then incubated

with enhanced chemiluminescent substrate (ECL; Thermo Fisher Scientific) for

approximately five minutes. The membrane was washed and photographic films (Kodak

BioMax MR film, Sigma-Aldrich) were exposed to membranes for varying amounts of

time (depending on the strength of the light signal). Exposed films were developed in an

automated processor.

2.2.7.6. Relative Quantification of Proteins

In order to quantify changes in IκBα levels after TNFα stimulation, densitometry readings

were taken using AQM Version 6 software. To account for differences in protein

concentration or loading between samples, all IκBα levels were normalised using CycA or

α-tubulin bands. IκBα values were then normalised to pre-stimulatory IκBα.

2.2.8. Cell Viability

Cells were plated according to methods described in sections 2.2.2.5. (without PDTC

treatment) and 2.2.2.5.2 (with PDTC treatment). Cells were either plated in normal

medium or medium containing 20ng/ml TNFα. The CellTiter 96® Aqueous Non-

Radioactive Cell Proliferation Kit (Promega, USA) was used to determine cell viability.

This kit utilises a tetrazolium compound (3-(4,5-dimethylthiazol-2-yl)-5-(3-

carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium; MTS). MTS is reduced to a

soluble formazan product by live cells; absorbance of formazan can be measured at 490 nm

as a measure of viable cells. Cells in the 96-well plate were incubated for 3 hours with


62

MTS mix, made according to manufacturer’s instructions. Absorbance was then measured

at 490 nm at an appropriate time point (24, 48 or 72 hours) after treatment, using a

FLUOstar Omega microplate reader. Experiments were performed in triplicate, with three

technical replicates per plate.

2.2.8.1. Analysis of Cell Viability Data

Negative control values were subtracted from cell viability values to eliminate background

signal. Data was collated across replicate experiments and tested for significant

differences, against unstimulated culture readings, using Mann-Whitney U tests. Data was

also analysed for co-culture mediated viability changes. In order to do this, expected co-

culture mean and standard deviation values were calculated from mono-culture data (as

shown in Table 2.4). These values were then tested for significance differences (compared

to actual co-culture data), using z-tests. The same analysis was conducted for TNFα-

treated, PDTC-treated and PDTC + TNFα-treated cultures.

Table 2.4: Calculations conducted to assess co-culture-mediated viability changes.

Expected co-culture means and standard deviations were tested against actual co-culture

data, using z-tests.

Average

Basal

C17.2

S.D.

Basal

C17.2

Average

Basal

BV.2

S.D.

Basal

BV.2

Expected

Average

Co-culture

Expected

Standard

Deviation

Average or

Standard

Deviation

(S.D.)

of Viability

Readings

1.25 0.29 2.1 0.12 =1.25+2.1

=3.46

=(√((0.29)^2+(0

.12)^2))

=0.31

2.2.9. Apoptosis Assays

As with cell viability assays, cells (both untreated and PDTC-treated) were plated in

normal medium or medium containing 20 ng/ml TNFα, according to methods and cell

density described in sections 2.2.2.5. and 2.2.2.5.2. The Caspase-Glo® 3/7 Kit (Promega)

was used to determine apoptosis rates in different conditions. A proluminescent caspase3/7

substrate and luciferase mix was made according to manufacturer’s instructions. The

substrate is cleaved by caspase3/7 to create aminoluciferin, which produces a luminescent

signal in the presence of luciferase. Cells were incubated for 1 hour with the substrate mix.

Luminescence was then measured at the appropriate timepoint (24, 48 or 72 hours) using a


63

FLUOstar Omega microplate reader, and an integration time of 0.1 seconds. Experiments

were performed in triplicate, with two technical replicates per plate.

2.2.9.1. Analysis of Apoptosis Data

Apoptosis data was analysed according to the methods described in section 2.2.8.1 and

Table 2.4.

2.2.10. Flow Cytometry

2.2.10.1. Sample Preparation and TNFR1-Labelling

The day after plating (as described in Table 2.1), cells were either left unstimulated or

treated with 20ng/ml TNFα. Two hours after treatment, cells were washed with PBS,

trypsinised and counted. For each sample, 1x106 cells were incubated with 2 µg/ml

phycoerythrin (PE) conjugated- TNFR1 antibody mix (BioLegend, UK) in the dark for 45

minutes. Cells were washed with PBS, to ensure removal of the antibody mix, and

resuspended in 500 µl PBS for analysis. Experiments were performed in triplicate. Each

sample was analyzed in a BD FACS Calibur machine (Becton Dickinson, USA), using a

488 nm laser to excite eGFP and PE. Fluorescence from eGFP and PE were detected using

514-545nm and 564-601nm filters, respectively. Mono-culture experiments were

conducted with lentivirus-transduced C17.2 cells (expressing p65-eGFP) and untransfected

C17.2 and BV.2 cells. Co-culture experiments were performed with lentivirus transduced

C17.2 cells and untransfected BV.2 cells, to enable separation of cell types during data

analysis (see sections 2.2.4.2 and 2.2.10.2.).

2.2.10.2. Flow Cytometry Data Analysis

Mean fluorescence intensities of cell populations were obtained using FlowJo software

version 7.6.5. Mann Whitney U tests were used to assess differences in TNFR1 expression

between groups. For the analysis of TNFR1-expression on co-cultured cells, eGFP

expression was used to differentiate between lentivirus transduced C17.2 cells (expressing

eGFP) and untransfected BV.2 cells. Figure 2.1 shows how cell populations were separated

along PE and eGFP expression axes.


64

B V .2

C 1 7 .2 ( le n ti)

1 :1 C o -c u ltu re

A B

C D

F ig u r e 2 .1 . T N F R 1 -p h y c o e r y th r in a n d e G F P f lu o r e s c e n c e o f le n tiv ir u s

tr a n s d u c e d C 1 7 .2 a n d B V .2 m o n o -c u ltu r e s a n d 1 :1 c o -c u ltu r e s .

L e n t iv i ru s t ra n s d u c e d C 1 7 .2 m o n o -c u l tu re s , u n t ra n s fe c te d B V .2

m o n o -c u ltu re s a n d 1 :1 c o -c u l tu re s w e re la b e lle d w i th T N F R 1 -p h y c o e ry th r in

a n t ib o d y . P h y c o e ry th r in a n d e G F P f lu o re s c e n c e w a s m e a s u re d in : (A )

u n tra n s fe c te d B V .2 m o n o -c u l tu re s ; (B ) le n t iv iru s t ra n s d u c e d C 1 7 .2

m o n o -c u l tu re s ; (C ) 1 :1 c o -c u ltu re s . (D ) S u p e rim p o s it io n o f f lu o re s c e n c e in

m o n o -c u ltu re s a n d 1 :1 c o -c u ltu re s , s h o w in g s e p a ra tio n o f c e ll p o p u la tio n s ,

a c c o rd in g to e G F P f lu o re s c e n c e le v e ls .

2.2.11. Enzyme-linked Immunosorbent Assay (ELISA)

The day after seeding (see Table 2.1), cells were treated with 2ng/ml TNFα, after which

100 µl culture medium was removed at the appropriate time points (i.e. before treatment, 2

hours, 4 hours and 6 hours after TNFα-treatment). Experiments were performed in

triplicate. Samples were frozen at -80˚C, until use in an ELISA. Mouse TNFα was

quantified using the BD OptEIA mouse TNFα ELISA set (Becton Dickinson), according to

the manufacturer’s instructions. Duplicate readings were taken for each sample.


65

Differences between culture conditions were assessed using Kruskal-Wallis ANOVA tests.

Data across replicates was collated, averaged and normalised to time 0 values for display.

2.2.12. NanoString


Cells were plated as described in section 2.2.2.5. RNA was extracted from mono-cultures

and 1:1 co-cultures (from a mixture of C17.2 and BV.2 cells). In addition, extracts were

taken from cells in transwell co-cultures. For example, RNA was extracted from C17.2

cells that had been cultured with BV.2 cells seeded in transwell inserts; these cultures were

referred to as ‘C17.2 transwell co-culture’. Likewise, BV.2 cells that had been cultured

with C17.2 cells in transwells were labelled ‘BV.2 transwell co-culture’. Experiments were

performed in duplicate or triplicate.

One day after plating, cells were either left untreated or stimulated with 20ng/ml TNFα.

RNA was extracted from cells 230 minutes or 24 hours after treatment, using the High

Pure RNA Isolation Kit (Roche, UK) according to the manufacturer’s instructions. RNA

samples were quantified using a NanoDrop ND1000 spectrophotometer (Thermo Fisher

Scientific).

2.2.12.2. NanoString Measurements

The quality of each undiluted RNA sample was determined using a 2200 TapeStation

system (Agilent Technologies, USA). Prepared RNA samples were submitted for analysis

by the Genomic Technologies Core Facility of the Faculty of Life Sciences, University of

Manchester. Samples were assayed using the nCounter Mouse Inflammation Kit v1

(NanoString Technologies, USA), which contains a CodeSet of capture and reporter probes

for 185 genes, including cytokines, chemokines, inflammatory receptors and transcription

factors. For each sample, 125ng RNA was used per CodeSet hybridisation reaction.

2.2.12.3. NanoString Data Analysis

NanoString results were analysed using nSolver analysis software v1.1 (NanoString

Technologies). All results were normalised to the level of house-keeping genes and

positive controls incorporated into the CodeSet. Negative control values were subtracted

from the resulting data. Biological replicates were averaged and averages across different

groups were compared. Genes that exhibited fold differences in expression that were

greater than or equal to two were considered to be differentially regulated.


66

Two different comparisons between conditions and treatments were made: Tables 2.5.1

and 2.5.2 show an example of each. Analyses in Tables 2.5.1- 2.5.2 were conducted with

unstimulated and TNFα-treated cultures.

Tables 2.5.1 to 2.5.2: Examples of the two different comparisons conducted with

NanoString results

Table 2.5.1 Basal

C17.2 cells

24 hour TNFα-treated

C17.2 cells

Fold Change in

Expression

1) Analysis of TNFα-

induced gene

expression

300 900 (= 900/300)

=3

2.2.13. Quantitative-Polymerase Chain Reaction (Q-PCR)


Cells were stimulated with 20ng/ml TNFα and RNA was extracted at time 0, 15 minutes,

30 minutes, 1 hour, 2 hours, 4 hours, 6 hours and 8 hours post-stimulation. Experiments

were performed in triplicate. RNA was extracted using the High Pure RNA Isolation kit

(Roche, Switzerland), according to the manufacturer’s instructions. RNA samples were

quantified using a NanoDrop ND1000 spectrophotometer (Thermo Fisher Scientific).

Samples were converted to complementary DNA (cDNA) using the SuperScript VILO

cDNA Synthesis Kit (Life Technologies), according to the manufacturer’s instructions.

Amplification steps were performed in a C1000 thermal cycler (Bio-Rad), using 1 μg RNA

as starting material. The resulting cDNA samples were diluted 1 in 20 with RNase-free,

DEPC-treated water and stored at -20°C.

2.2.13.2. Q-PCR Analysis

cDNA samples were analysed by Q-PCR to assess relative expression levels of IκBα, IκBε,

TNFα and A20 genes. Primer sequences are shown in Table 2.6. These primers have been

validated by members of the laboratory, using murine cell lines.

Table 2.5.2 Basal C17.2

cells

Basal C17.2 cells (seeded

with transwell BV.2 cells)

Fold Change in

Expression

2) Analysis of cell-

contact-independent

co-culture interactions

500 250

(= 250/500)

= 0.5


67

Table 2.6: Primers used for Q-PCR

Target NCBI

Accession ID

Primer sequence (5’ to 3’) Product

length Left Right

IκBα NM_010907 GTGTAGCAGTCTTG

ACGCAG

CATCAGCACCCAAA

GTCACC 150 bp

IκBε NM_008690 CAGCCGAATTCTGC

AGGATC

GCAATGTGGCAATG

TGGAGA 158 bp

TNFα NM_013693 TGAGGTCAATCTGC

CCAAGT

TGGACCCTGAGCCA

TAATCC 208 bp

A20 NM_009397 TCTTCCTTCGTCAC

AGCCAT

CCAGTCCTAGCACG

CATTTC 175 bp

CycA NM_008907 CTGGACCAAACACA

AACGGT

TGCCCGCAAGTCAA

AAGAAA 208 bp

Each reaction was performed in one well of an opaque 96-well plate, with 1 μl of cDNA,

10 μl SYBR-Green Master Mix (Roche), 1.5 μl each of forward and reverse primers (final

concentration 0.25 μM each) and 6 μl of DEPC-treated water. Each reaction was

performed with three technical replicates per plate. Plates were covered with sealing foil,

spun briefly, and then analysed in a LightCycler 480 machine (Roche). Cycling parameters

are described in Table 2.7.

Table 2.7: Cycling parameters for Q-PCR

Cycles Target

temperature Time

Ramp

speed

Acquisition

mode

Initial

denaturation 1 95˚C 5 minutes 4.4 ˚C/s None

Amplification 45 95˚C 10 s 4.4 ˚C/s

Once per cycle 60˚C 30 s 2.2 ˚C/s

Melt curve 1

95˚C 5 s 4.4 ˚C/s

Ten per ˚C 65˚C 1 minute 2.2 ˚C/s

97˚C 0.06 ˚C/s

Cooling 1 40˚C 10 s 1.5 ˚C/s None

2.2.13.3. Analysis of Q-PCR Results

Q-PCR data was analysed using LightCycler 480 software release 1.5.0. Samples were

annotated according to treatment, time points and primer content (reference versus target

gene). Relative gene expression levels were then calculated using the automated relative

quantification method in the LightCycler 480 software. Gene expression data was

normalised to the reference gene CycA, then expressed relative to time 0. These values

were calculated for each cell population and Kruskal-Wallis ANOVA tests were performed


68

on the resulting dataset to assess significant differences in gene expression. This analysis

was performed on unstimulated expression levels of IκBα, IκBε, A20 and TNFα in

untransfected cells, lentivirally transduced cells, clone A, clone 3 and clone 5.


69

3. Establishing and Characterising a

Model System for the Study of NF-

κB in C17.2 and BV.2 Cells


70

3.1. General Introduction

The initial aim in this project was to investigate NF-κB dynamics and activation (i.e. p65

translocation and a surrogate for NF-κB activation) in individual neural progenitor cells in

response to stimulation. NF-κB single cell dynamics had never previously been studied in

this cell type and therefore it was important to observe the response of these cells to

stimulation. The C17.2 cell line was chosen for this purpose as these cells have been

widely used as a model system for neural progenitor cell function (Bakshi et al, 2006; Lu

et al, 2003). Relevant published data revealed strong nuclear p65 presence in murine stem

cells with p65 immunostaining, 30 min after TNFα stimulation (Widera et al, 2006a).

The most obvious way to study p65 dynamics in these cells was to make stable cell lines.

Initially, it was thought that the optimal construct to use would be a human BAC

expressing p65-DsRedXP fusion protein, as it includes the endogenous promoter and

regulatory sequences for the p65 gene. This means that the fusion protein would be

expressed at a similar level to an endogenous p65 allele. However, obtaining stable clones

containing the integrated BAC required a lengthy process of culture from single cells, ring

cloning and subsequent expansion. Also available were plasmid vectors, expressing p65-

DsRedXP, and a lentivirus construct that could be used to transduce cells so they would

produce p65-eGFP. The plasmid could be used for transient transfection of neural

progenitor cells to observe the dynamics of p65 fusion proteins. The particular advantage

of the lentivirus was that it could be used to rapidly produce a population of cells stably

expressing the fusion protein, without the requirement for extensive cell cloning.

Since the main aim of the work in this thesis was to investigate neural progenitor cell –

microglial cross-talk in the control of neuroinflammation (see Chapter 1), it was also

important to choose an appropriate microglial cell line. To this end, the BV.2 cell line was

chosen as it accurately reproduces key characteristics of primary microglial cells (Henn et

al, 2009). Similar to the work with C17.2, it was important to develop a BV.2 cell

population expressing p65 fusion protein that could be used to investigate NF-κB dynamics

in these cells. No such study had previously been performed, although some population-

level biochemical studies of the NF-κB pathway had been performed in BV.2 cells

(Sheppard et al, 2011; Magni et al, 2012; Wang et al, 2011).

In conclusion, this chapter describes the single-cell imaging of p65, population-level NF-

κB activation and gene expression analyses of BAC stable clonal, plasmid-transfected and


71

lentivirus-transduced cells, derived from C17.2 and BV.2, in order to develop model cell

systems suitable for use in the remainder of the project.

3.2. Results

3.2.1. Analysis of NF-κB Function and Dynamics in a Neural Progenitor Cell Line

3.2.1.1. Creating C17.2 Reporter Cell Lines for Observation of p65 Dynamics

The C17.2 neural progenitor cell line was chosen as a model system for studying NF-κB

function. As discussed above, the first aim was to express a p65 fluorescent fusion protein

in C17.2 cells, to allow observation of p65 dynamics within individual living cells. In order

to observe p65 in the C17.2 cell line, plasmid and Bacterial Artificial Chromosome (BAC)

constructs, encoding p65-DsRedXP, and a lentiviral construct, expressing p65-eGFP, was

used.

Wild-type C17.2 cells were transiently transfected with the p65-DsRedXP plasmid and a

lentiviral transduction was performed to create cells expressing p65-eGFP. C17.2 cells

were also stably-transfected with the p65-BAC. One transfection was performed and

resulting BAC positive cells were ring cloned to isolate a set of six p65-DsRedXP

expressing clones: three of which were chosen for further investigation, due to their display

of a growth rate that was comparable to wild-type C17.2 cells. These cell lines are referred

to as BAC stable clones A, 3 and 5, the lentivirus transduced cells are called C17.2 (lenti),

plasmid-transfected cells are called ‘C17.2 (transient)’ and untransfected cells are labelled

with the suffix ‘(UT)’.

Transfection/transduction of these constructs into cells successfully led to the expression of

fluorescent-p65, which was observable under a confocal microscope (Figure 3.1). The next

step was to determine which cell line(s) best represented characteristics of wild-type C17.2

cells. To do this, reporter cell lines were characterised and compared to wild-type C17.2

cells, using a variety of different methods.

3.2.1.2. Single-cell p65 Dynamics in C17.2 Reporter Cell Lines

In order to observe and compare p65 dynamics between the differently transfected cell

populations, confocal microscopy was used to take time-lapse images of cells from 0 to

400 min after 20ng/ml TNFα stimulation.


72

F ig u r e 3 .1 . E x p r e s s io n o f p 6 5 f lu o r e s c e n t fu s io n p r o te in s in C 1 7 .2 c e l ls .

C 1 7 .2 c e l ls w e re t ra n s fe c te d o r t ra n s d u c e d w i th d if fe re n t p 6 5 - f lu o re s c e n t p ro te in c o n s t ru c ts .

C o n fo c a l m ic ro s c o p y im a g e s w e re ta k e n o f (A ) L e n tiv iru s tra n s d u c e d c e l ls . (B ) T ra n s ie n tly

(p la s m id ) tra n s fe c te d c e l ls . (C ) B A C s ta b le c lo n e 3 . (D ) B A C s ta b le c lo n e 5 a n d ; (E ) B A C

s ta b le c lo n e A . S c a le b a r = 5 0 µ m

A B C D E

Figure 3.2 displays microscopy images showing the localization of fluorescent p65 in

representative cells at different times after TNFα stimulation. The BAC clonal lines were

found to respond in a similar manner to each other and, therefore, one representative clonal

cell line is displayed in Figure 3.2.

F ig u r e 3 .2 . T N F - in d u c e d p 6 5 lo c a l is a t io n in C 1 7 .2 c e l ls tr a n s fe c te d o r

tr a n s d u c e d w ith d if fe r e n t p 6 5 c o n s tr u c ts .

C e lls w e re s t im u la te d w i th 2 0 n g /m l T N F a t t im e 0 a n d v is u a l is e d b y c o n fo c a l

m ic ro s c o p y a t th e d if fe re n t t im e p o in ts a f te r T N F s t im u la tio n . (A ) L en tiv iru s

tra n s d u c e d c e l ls . (B ) T ra n s ie n t ly - tra n s fe c te d c e lls . (C ) B A C c lo n e 5 . S c a le b a r =

5 0 µ m .

A

B

C

C17.2 (lenti) cells appeared to respond with stronger p65 nuclear movements than the BAC

clones and the transiently transfected cells. There also appeared to be a greater proportion

of responsive cells in the C17.2 (lenti) culture than the other cell populations. In order to


73

quantify these apparent differences, nuclear p65 fluorescence intensity was analysed using

Cell Tracker software (Perkins, 2007). Nuclear fluorescence intensity, post-TNFα

stimulation, was normalised to the mean pre-stimulation nuclear fluorescence. The total

number of cells analysed for the plasmid transfected, lentiviral transduced and BAC clones

3, 5 and A was 22, 32, 22, 66 and 47, respectively. Except for some clone 5 cells, all cell

data obtained is displayed in Figure 3.3: representative clone 5 cells were selected to avoid

presenting too much information in one graph.

All of the C17.2 (lenti) cells exhibited a clear, rapid nuclear p65-eGFP movement (>7 fold

increase in nuclear p65), in response to TNFα. On average, the initial peak of nuclear p65

occupancy occurred 20 min after stimulation and many cells displayed subsequent nuclear

p65 movements - as signified by the average p65 nuclear fluorescence being sustained at a

higher level (>2 fold), for over 200 min. BAC clones 5, A and the plasmid-transfected

C17.2 cells exhibited smaller changes in nuclear p65 and delayed peaks in nuclear p65

translocation (Figure 3.3F). Their responses were also more transient; average nuclear p65

fluorescence returned to pre-stimulatory levels within 200 min of TNFα treatment. In

contrast to this, the BAC clone 3 cells were largely unresponsive, displaying no

change/very low amplitude changes in nuclear p65, after TNFα stimulation.

To further characterize the differences in p65 response observed across reporter cell lines,

the single-cell data displayed in Figure 3.3 was clustered using a k-means algorithm.

Initially, clustering was conducted using different cluster numbers (results not shown). It

was concluded that a cluster number of 4 was the most suitable for representing the p65

dynamic profiles observed in cells. This algorithm stratified cells into 4 different p65

response categories (Figure 3.4A-D). Figures 3.4E and 3.4F show the distribution of

different cell lines across categories of p65 response.

Categorisation of cells by the k-means algorithm reflected differences in amplitude and

persistence of p65 response to TNFα. Cluster A accommodated cells that did not exhibit

any clear nuclear p65 translocations (95% of clone 3 cells were associated with this

category, see Figure 3.4E). Cells that displayed small nuclear p65 movements were sorted

into cluster B: this included over 50% of C17.2 (transient), clone 5 and clone A cells. The

cells that displayed higher amplitude p65 movements were classified into clusters C or D,

depending on whether they exhibited a single nuclear p65 translocation only (cluster D) or

a more persistent response (cluster C).


74

0 100 200 300 4000

2

4

6

8

10

12

14

16

Nu

cle

ar

p6

5 F

luore

scen

ce

In

ten

sity

Time (Minutes)

0 100 200 300 4000

2

4

6

8

10

12

14

16

Nu

cle

ar

p6

5 F

luo

resce

nce I

nte

nsity

Time (Minutes)

0 100 200 300 4000

1

2

3

4

5

6

Nu

cle

ar

p6

5 F

luore

sce

nce

In

ten

sity

Time (Minutes)

0 100 200 300 4000

2

4

6

8

10

12

14

16

Nu

cle

ar

p65

Flu

ore

sce

nce

In

ten

sity

Time (Minutes)

0 100 200 300 4000

2

4

6

8

10

Nu

cle

ar

p6

5 F

luore

scen

ce

In

ten

sity

Time (Minutes)

Initial Peak

Amplitude

Initial Peak Timing

(Minutes)

C17.2 (transient) 2.76 40

C17.2 (lenti) 7.57 20

Clone 3 N/A N/A

Clone 5 1.47 35

Clone A 1.63 35

A B

C D

E

F ig u r e 3 .3 . Q u a n t i f ic a t io n o f n u c le a r p 6 5 f lu o r e s c e n c e in d i ffe r e n t C 1 7 .2 c e ll p o p u la t io n s

a fter T N F s t im u la t io n .

N u c le a r p 6 5 f lu o re s c e n c e o f c e lls w a s re c o rd e d b e tw e e n 0 a n d 4 0 0 m in a f te r T N F s tim u la tio n .

R e a d in g s w e re n o rm a lis e d to m e a n p re -s t im u la tro ry n u c le a r p 6 5 f lu o re s c e n c e . E a c h g ra p h s h o w s

d a ta fro m o n e e x p e r im e n t; e a c h l in e re p re s e n ts a n a ly s is o f a s in g le c e ll a n d th e th ic k b la c k l in e s

s h o w th e a v e ra g e o f a l l o f th e c e l ls . (A ) T ra n s ie n t ly - t ra n s fe c te d c e lls . (B ) L e n t iv iru s t ra n s d u c e d

c e lls . (C ) B A C c lo n e 3 . (D ) B A C c lo n e 5 . (E ) B A C c lo n e A . (F ) A v e ra g e in i t ia l n u c le a r p 6 5 p e a k

a m p li tu d e s a n d t im in g s . G ra p h s A - E d is p la y d a ta fo r 2 2 , 3 2 , 2 2 , 5 5 a n d 4 7 c e lls re s p e c t iv e ly .

F


75

To further investigate differences between the cell lines, data in Figure 3.4E was used to

determine the distribution of cells across low and high amplitude cluster groups (Figure

3.4F). Over 92% of all BAC clonal cells fitted into the low amplitude response group. This

group was also comprised of 68% of C17.2 (transient) cells. In contrast, over 90% of

C17.2 (lenti) cells were placed in the high amplitude category, which was composed of

clusters C and D.

0 100 200 300 4000

1

2

3

4

5

6

7

8

9

10

0 100 200 300 4000

1

2

3

4

5

6

7

8

9

10

0 100 200 300 4000

1

2

3

4

5

6

7

8

9

10

0 100 200 300 4000

1

2

3

4

5

6

7

8

9

10A B C D

F ig u r e 3 .4 . T N F - in d u c e d p 6 5 n u c le a r tr a n s lo c a t io n p r o f ile s o b ta in e d fr o m C 1 7 .2 c e ll

p o p u la tio n s .

N u cle a r p 6 5 flu o re sce n c e rea d in g s w e re rec o rd ed b e tw e en 0 an d 4 0 0 m in u tes a fte r T N F

s tim u la tio n . R ead in g s w e re n o rm a lised to m ean p re -s tim u la to ry n u c lea r p 6 5 flu o rescen ce . T h is

d a ta w as c lu s te red w ith a M atla b k -m ean s a lg o rith m . (A )-(D ) M ea n n u c le a r p 6 5 flu o re scen ce o f

c e lls in ea ch o f th e 4 c lu s te rs id en tif ied b y th e a lg o rith . (E ) T h e d is tr ib u tio n o f ce lls ac ro ss

c lu s te rs A -D . (F ) P e rce n ta g e o f c e lls in lo w a n d h ig h a m p litu d e re sp o n se c lu s te rs . T h e to ta l

n u m b er o f c e lls an a ly sed fo r tran s ien tly -tra n sfec ted , le n tiv iru s tran sd u c ed a n d B A C s tab le

c lo n e s 3 , 5 a n d A w a s 2 2 , 3 2 , 2 2 , 6 6 a n d 4 7 , re sp e c tiv e ly .

Pla

sm

id

Len

tivir

al p

65

B.A

.C. C

lon

e 3

B.A

.C. C

lon

e 5

B.A

.C. C

lon

e A

0

2 0

4 0

6 0

8 0

1 0 0

% o

f C

ell

Po

pu

lati

on

A B C D

Pla

sm

id

Len

tivir

al p

65

B.A

.C. C

lon

e 3

B.A

.C. C

lon

e 5

B.A

.C. C

lon

e A

0

2 0

4 0

6 0

8 0

1 0 0

% o

f C

ell

Po

pu

lati

on

L o w A m p litu d e

R e s p o n s e (A & B )

H ig h A m p litu d e

R e s p o n s e (C & D )

E F

T im e a fte r S t im u la tio n (M in u te s )

Fo

ld C

ha

ng

e i

n N

uc

lea

r p

65

Flu

ore

sc

en

ce


76

3.2.1.3. Population-level NF-κB Activation in C17.2 Cell Lines

Having established differences in TNFα-induced p65 dynamics, the next aim was to

investigate population-level NF-κB activation in the different C17.2 cell populations,

beginning with NF-κB-regulated transcriptional response. It was decided to exclude clone

3 from these experiments due to the lack of a visible p65 response.

3.2.1.3.1. Analysis of NF-κB Transcriptional Activity in the Differentially Transfected

C17.2 cells

A useful method for studying transcription responses to NF-κB activation is to measure

luciferase production from the NF-luc reporter plasmid. This contains a minimal promoter

with 5 copies of a consensus NF-κB response motif. To measure NF-luc induction, the

cells were transiently transfected with an NF-luc plasmid and stimulated with different

doses of TNFα. Luminescence readings were taken every 15 min, from 0 to 5 h after TNFα

stimulation. The results of these experiments can be seen in Figure 3.5.

Experiments were performed in triplicate for each cell population; one experiment for each

was extended to take luminescence readings for 12 h after TNFα stimulation. This allowed

the determination of the time of peak luciferase expression. No further increases in

luciferase expression were seen later than 5 h post-stimulation. Therefore, only data up to 5

h is displayed here.

In the wild type C17.2 cells, doses under 100pg/ml did not induce NF-luc, as signified by

the results of a one-way ANOVA. Peak NF-luc induction was observed after 1ng/ml TNFα

stimulation. Peak induction occurred at 3 h and 4-5 h after stimulation with 100pg/ml

TNFα and doses ≥1ng/ml TNFα, respectively. The C17.2 (lenti) cells exhibited a similar

temporal and dose-dependent response, except that they showed lower peak amplitudes. In

the BAC clone 5 cells, the peak activation levels exhibited were reduced at all doses. Clone

A cells were even less responsive: only doses of ≥10ng/ml TNFα gave significant NF-luc

upregulation. The significance of the observed differences between the cells was

investigated further. Peak NF-luc induction levels, after stimulation with 100pg/ml and ≥

1ng/ml TNFα, were calculated and results are displayed in Figure 3.6. Kruskal-Wallis

ANOVA test results indicated that the peak induction level of atleast one cell population

was significantly different to that of the other cell populations (p-value<0.05): Kruskal-

Wallis ANOVA tests do not inform on exactly which groups within a dataset are

significantly different.


77

0 1 2 3 4 5

0

1

2

3

4

5

6

T im e a fte r S t im u la t io n (H o u rs )

Fo

ld C

ha

ng

e i

n L

uc

ife

ra

se

Ex

pre

ss

ion

C o n tro l

1 0 p g /m l

5 0 p g /m l

1 0 0 p g /m l *

1 n g /m l * *

1 0 n g /m l * *

2 0 n g /m l * *

5 0 n g /m l * *

0 1 2 3 4 5

0

1

2

3

4


Fo

ld C

ha

ng

e i

n L

uc

ife

ra

se

Ex

pre

ss

ion

C o n tro l

1 0 p g /m l

5 0 p g /m l

1 0 0 p g /m l * *

1 n g /m l * *

1 0 n g /m l * *

2 0 n g /m l * *

5 0 n g /m l * *

0 1 2 3 4 5

0

1

2

3


Fo

ld C

ha

ng

e i

n L

uc

ife

ra

se

Ex

pre

ss

ion

C o n tro l

1 0 p g /m l

5 0 p g /m l

1 0 0 p g /m l

1 n g /m l

1 0 n g /m l * *

2 0 n g /m l * *

5 0 n g /m l * *

0 1 2 3 4 5

0

1

2

3


Fo

ld C

ha

ng

e i

n L

uc

ife

ra

se

Ex

pre

ss

ion

C o n tro l

1 0 p g /m l

5 0 p g /m l

1 0 0 p g /m l * *

1 n g /m l * *

1 0 n g /m l * *

2 0 n g /m l * *

5 0 n g /m l * *

A B

DC

F ig u r e 3 .5 . D o s e -d e p e n d e n t N F -B a c t iv a tio n in d i f fe r e n t ia l ly tr a n s fe c te d / tr a n s d u c e d C 1 7 .2

c e l ls .

(A ) W T C 1 7 .2 c e l ls . (B ) L e n t iv iru s tra n s d u c e d c e l ls . (C ) B A C c lo n e A . (D ) B A C c lo n e 5 . E a c h c e l l

p o p u la tio n w a s tra n s fe c te d w ith th e N F - lu c p la s m id a n d s t im u la te d w ith v a ry in g d o s e s o f T N F .

L u m in e s c e n c e w a s m e a s u re d e v e ry 1 5 m in f ro m 0 to 3 0 0 m in a f te r T N F s t im u la tio n . A ll e x p e rim en ts

w e re p e r fo rm e d in t r ip lic a te . B a rs re p re s e n t ±S .D . a n d a s te r is k s re p re s e n t s ig n if ic a n t o n e w a y A N O V A

te s t re s u lts (* = p -v a lu e 0 .0 5 , * * = p -v a lu e 0 .0 1 , v e rs u s c o r re s p o n d in g u n s tim u la te d g ro u p ) .

Overall, the C17.2 (lenti) cells best displayed the key features of NF-luc induction that

were observed in wild-type cells. The BAC clones, on the other hand, displayed dampened

NF-luc induction profiles. There were a number of possible explanations for this

observation. These include the possibility that basal NF-κB activity was higher in the

clones than in the wild-type cells.

Experiments were performed with each cell line individually, making comparison of basal

luminescence data problematic. Assuming similar transfection efficiency across the cells,

basal luminescence can be taken as a measure of basal NF-κB activity. To this end, a

comparison was conducted of basal luminescence values from wild-type C17.2, clone A

and clone 5 cells (see Figure 3.7).


78

100p

g/m

l

1n

g/m

l

10n

g/m

l

20n

g/m

l

50n

g/m

l

0

1

2

3

4

5

6

7

8

T N F D o s e

Me

an

Fo

ld C

ha

ng

e

in L

um

ine

sc

en

ce

C 1 7 .2 (W T )

C 1 7 .2 ( le n t i )

C lo n e A

C lo n e 5

*

*

**

*

F ig u r e 3 .6 . C o m p a r is o n o f N F - lu c in d u c tio n , a fte r T N F s t im u la t io n , in C 1 7 .2 c e l l p o p u la t io n s .

E a c h c e ll p o p u la tio n w a s tra n s fe c te d w ith th e N F -lu c p la s m id a n d s t im u la te d w i th v a ry in g d o s e s o f

T N F . L u c ife r in w a s a d d e d to th e c e l ls a n d lu m in e s c e n c e w a s m e a s u re d e v e ry 1 5 m in f ro m 0 to 3 0 0

m in a f te r T N F s t im u la tio n . E x p e rim e n ts w e re p e rfo rm e d in tr ip lic a te , w ith th re e b io lo g ic a l re p lic a te s p e r

e x p e rim e n t. M e a n m a x im u m fo ld c h a n g e in lu m in e s c e n c e w a s c a lc u la te d 3 h o u rs a f te r 1 0 0 p g /m l

s tim u la t io n a n d 5 h o u rs a f te r s t im u la tio n w i th h ig h e r d o s e s . B a rs re p re s e n t S .D . a n d a s te r is k s re p re s e n t

s ig n if ic an t K ru s k a l-W a llis A N O V A te s t re su lts (* = p -v a lu e 0 .0 5 ) .

C17.2

(W

T)

Clo

ne A

Clo

ne 5

0 .0

0 .5

1 .0

1 .5

2 .0

Re

lati

ve

Lu

min

es

ce

nc

e C 1 7 .2 (w ild -ty p e )

C lo n e A

C lo n e 5

*

F ig u r e 3 .7 . C o m p a r is o n o f b a s a l lu m in e s c e n c e o f N F - lu c tr a n s fe c te d C 1 7 .2 c e ll p o p u la t io n s .

B a s a l lu m in e s c e n c e o f d if fe re n t N F -lu c -tra n s fe c te d c e l l p o p u la tio n s w a s m e a s u re d . E x p e r im e n ts

w e re p e r fo rm e d in tr ip lic a te w ith th re e te c h n ic a l re p lic a te s p e r e x p e r im e n t . D a ta w a s a v e ra g e d a n d

n o rm a lis e d to th e C 1 7 .2 (w i ld - ty p e ) a v e ra g e , fo r d is p la y . B a rs re p re s e n t S .D . a n d a s te r is k s

re p re s e n t s ig n if ic a n t M a n n W h itn e y U te s t re s u lts (* = p -v a lu e 0 .0 5 ) .

The basal luminescence values from clone A and clone 5 cells were lower than that of

wild-type C17.2 cells. Mann Whitney U test results suggested that the difference between

clone 5 and wild-type C17.2 cells was significant (p-value<0.05). No transfection control


79

was included in these experiments and so it is not possible to make strong conclusions

from this comparison.

3.2.1.3.2. TNFα-induced IκBα Degradation Profiles in C17.2 Cell Lines

The degradation and resynthesis of IκB proteins, such as IκBα, allows the shuttling of NF-

κB between the nucleus and cytoplasm. Without IκBα degradation, NF-κB is generally

believed to be retained in the cytoplasm (reviewed by Hoffmann et al, 2006). For this

reason, it was important to characterize the TNFα-induced IκBα degradation and

resynthesis profiles in wild-type cells and C17.2 reporter cell lines.

To achieve this goal, protein extracts were taken from cells at 15 min intervals, from 0 to

120 min, after 20ng/ml TNFα stimulation. These experiments were performed in triplicate.

Figure 3.8 shows the TNFα-induced IκBα degradation profile obtained from wild-type

C17.2 cells.

Within 15 min, there was ≥85% decrease in IκBα, which was then rapidly resynthesized

between 30 and 45 min. In two out of three replicates, IκBα levels were comparable to

their pre-stimulatory state within 2 h of TNFα treatment. C17.2 (lenti) cells showed a

similar temporal IκBα degradation and resynthesis profile (Figure 3.9).

Once again, the profiles from clone A and clone 5 were distinct from wild-type and C17.2

(lenti) cells, but were similar to each other (see Figures 3.10 and 3.11). With the exception

of one replicate from each dataset, the clonal cells maintained stable IκBα levels after

TNFα stimulation. It was noted that, additional IκBα bands were observed in the Western

blots; these bands were not obtained with extracts from the wild type or C17.2 (lenti) cells.


80

0 5 0 1 0 0 1 5 0

0 .0

0 .5

1 .0

1 .5

T im e a fte r T N F S tim u la t io n (M in u te s )

No

rm

ali

se

d I

B-

Le

ve

ls R e p lic a te 1

R e p lic a te 2

R e p lic a te 3

A

B

F ig u r e 3 .8 W e s te r n b lo t a n a ly s is o f IB le v e ls in w i ld ty p e C 1 7 .2 c e l ls


P ro te in e x tra c ts w e re ta k e n f ro m C 1 7 .2 c e lls a t 1 5 m in in te rv a ls f ro m 0 to

1 2 0 m in a f te r s t im u la t io n w ith 2 0 n g /m l T N F . W e s te rn b lo ts fo r IB w e re

p e r fo rm e d w i th th e p ro te in e x tra c ts . E x p e rim e n ts w e re p e r fo rm e d in

tr ip lic a te . (A ) R e p re s e n ta tiv e W e s te rn b lo t . (B ) D e n s ito m e try a n a ly s is o f

tr ip lic a te e x p e rim e n ts (B la c k l in e = b lo t s h o w n in A ).


81

0 5 0 1 0 0 1 5 0

0 .0

0 .5

1 .0

1 .5

2 .0


No

rm

ali

se

d I

B-

Le

ve

ls R e p lic a te 1

R e p lic a te 2

R e p lic a te 3

A

B

F ig u r e 3 .9 W e s te r n b lo t a n a ly s is o f IB le v e ls in le n t iv ir u s tr a n s d u c e d

C 1 7 .2 c e l ls a f te r T N F s t im u la t io n .

P ro te in e x t ra c ts w e re ta k e n f ro m le n tiv i ru s t ra n s d u c e d C 1 7 .2 c e l ls a t 1 5 m in

in te rv a ls f ro m 0 to 1 2 0 m in a f te r s t im u la tio n w ith 2 0 n g /m l T N F . W e s te rn

b lo ts fo r IB w e re p e rfo rm e d w i th th e p ro te in e x t ra c ts . E x p e r im e n ts w e re

p e rfo rm e d in t r ip l ic a te . (A ) R e p re s e n ta tiv e W e s te rn b lo t . (B ) D e n s ito m e try

a n a ly s is o f tr ip lic a te e x p e rim e n ts (B lu e l in e = b lo t s h o w n in A ).


82

0 5 0 1 0 0 1 5 0

0 .0

0 .5

1 .0

1 .5

2 .0

2 .5

3 .0


No

rm

ali

se

d I

B-

Le

ve

ls R e p lic a te 1

R e p lic a te 2

R e p lic a te 3

A

B

F ig u r e 3 .1 0 W e s te r n b lo t a n a ly s is o f IB le v e ls in B A C c lo n e A c e l l s


P ro te in e x tra c ts w e re ta k e n fro m B A C c lo n e A c e l ls a t 1 5 m in in te rv a ls

fro m 0 to 1 2 0 m in a f te r s t im u la t io n w i th 2 0 n g /m l T N F . W e s te rn b lo ts fo r

IB w e re p e r fo rm e d w i th th e p ro te in e x tra c ts . E x p e r im e n ts w e re


a n a ly s is o f tr ip lic a te e x p e rim e n ts (B lu e l in e = b lo t s h o w n in A ).

- tu b u lin

A d d it io n a l I B - b a n d s

I B -


83

0 5 0 1 0 0 1 5 0

0 .0

0 .5

1 .0

1 .5

2 .0

2 .5


No

rm

ali

se

d I

B-

Le

ve

ls R e p lic a te 1

R e p lic a te 2

R e p lic a te 3

A

B

F ig u r e 3 .1 1 W e s te r n b lo t a n a ly s is o f IB le v e ls in B A C c lo n e 5 c e l l s


P ro te in e x tra c ts w e re ta k e n fro m B A C c lo n e 5 c e lls a t 1 5 m in in te rv a ls f ro m

0 to 1 2 0 m in a f te r s t im u la t io n w ith 2 0 n g /m l T N F . W e s te rn b lo ts fo r IB

w e re p e rfo rm e d w i th th e p ro te in e x tra c ts . E x p e r im e n ts w e re p e r fo rm e d in



- tu b u lin

A d d it io n a l I B - b a n d s

I B -

3.2.1.3.3. NF-κB-dependent Gene Expression Changes in TNFα Stimulated Cells

Experiments discussed so far have explored p65 localization and NF-κB activation. In

these experiments, C17.2 (lenti) cells provided an accurate representation of wild-type

cells. The next aim was to further investigate whether NF-κB target gene transcriptional

activity in the fluorescent cell lines was similar to that in wild-type cells.

RNA was extracted from cells at 0, 15, 30, 60, 120, 240, 360 and 480 min after 20ng/ml

TNFα stimulation. RT-PCR was conducted to produce cDNA and Q-PCR was performed

with primers for prototypical NF-κB-dependent genes: IκBα, IκBε, A20 and TNFα. Q-PCR

results are displayed as fold changes in mRNA expression in Figure 3.12.


84

0 1 2 3 4 5 6 7 8 9

0

1 0

2 0

3 0

4 0

5 0

T im e a fte r T N F S t im u la t io n (H o u rs )

Fo

ld C

ha

ng

e i

n m

RN

A

0 1 2 3 4 5 6 7 8 9

0

1 0

2 0

3 0

4 0


Fo

ld C

ha

ng

e i

n m

RN

A

0 1 2 3 4 5 6 7 8 9

0

1 0

2 0

3 0

4 0


Fo

ld C

ha

ng

e i

n m

RN

A

0 1 2 3 4 5 6 7 8 9

0

5 0

1 0 0

1 5 0


Fo

ld C

ha

ng

e i

n m

RN

A

0 1 2 3 4 5 6 7 8 9

0

5

1 0

1 5


Fo

ld C

ha

ng

e i

n m

RN

A

0 1 2 3 4 5 6 7 8 9

0

1 0 0

2 0 0

3 0 0

4 0 0


Fo

ld C

ha

ng

e i

n m

RN

A

I B - T N F I B - A 2 0

A B

C D

E F

F ig u r e 3 .1 2 . N F -B -d e p e n d e n t g e n e e x p r e s s io n c h a n g e s in C 1 7 .2 c e ll p o p u la t io n s a f te r

T N F s t im u la t io n .

R e la t iv e g e n e e x p re s s io n w a s m e a s u re d b y R T -P C R a n d Q -P C R in : (A ) C 1 7 .2 w i ld - ty p e

c e lls . (B ) C lo n e A c e l ls . (C ) & (D ) C lo n e 5 c e lls . (E ) & (F ) L e n t iv iru s tra n s d u c e d C 1 7 .2

c e lls . E x p e r im e n ts w e re c o n d u c te d in tr ip lic a te w ith th re e te c h n ic a l re p lic a te s p e r

e x p e rim e n t. G ra p h s s h o w th e a v e ra g e c h a n g e in g e n e e x p re s s io n S .D .

All cell lines showed induction of the target NF-κB genes. Given that TNFα treated clones

showed little to no nuclear p65 translocations, NF-κB-dependent gene expression changes

were unexpected. Expression of the target genes IκBα and IκBε are believed to be critical

in determining NF-κB subcellular localisation: therefore, the ideal C17.2 reporter cell line


85

would display the same temporal profile and fold changes as those observed in wild-type

C17.2 cells (Figure 3.12A). In wild-type cells, IκBα, A20 and TNFα mRNA levels peaked

1 h post-TNFα stimulation and then dropped to a plateau after 4 h. IκBε expression peaked

at 2 h post-stimulation and fell to a plateau after 6 h. The relative increase in expression

was similar between IκBα, IκBε and TNFα (8.5- 10 fold), whereas A20 was higher (26

fold).

The timing of expression of IκBα and A20 in clone A cells was similar to that of the wild-

type cells (Figure 3.12B). Peak IκBε expression occurred 2 h post-stimulation, which was

consistent with results from wild-type C17.2. However, unlike wild-type cells, IκBε

expression showed a greater increase (19 fold) and the levels of expression remained

elevated, even at 8 h post-stimulation. TNFα expression also remained elevated for longer

than observed in wild-type cells.

The expression profiles obtained from clone A were similar to that of clone 5 (see Figures

3.12B- D), with the exception of the TNFα gene expression profile. Similar to wild-type

cells, TNFα expression in clone 5 peaked at 1 hour post-stimulation. However, the

upregulation of TNFα expression was higher than observed in wild-type cells (69 fold).

The relative activation of IκBα and IκBε gene expression in the C17.2 (lenti) cells was

comparable to that seen in wild-type cells. However, as with clone 5 cells, the C17.2 (lenti)

cells displayed a larger activation of TNFα expression (187 fold). Also in contrast to the

wild-type C17.2 results, A20 expression in these cells exhibited an apparent oscillatory

profile, peaking at 1 h and 4 h post-TNFα stimulation.

This data suggested differences in the gene expression activation profiles, in response to

TNFα, between the different cell populations. It is important to note that these were

examined in terms of relative fold activation, following TNFα stimulation. One important

factor in considering this data is whether there were differences in basal expression of NF-

κB-dependent genes, across C17.2 cell populations. To elucidate differences in basal gene

expression, average CT values of the target gene were subtracted by the average CT values

of the control gene (see Chapter 2 for methods). These calculations were conducted using

data obtained from three Q-PCRs per cell line. A Kruskal-Wallis ANOVA was performed

using the values obtained and the datasets were averaged for display (Figure 3.13).


86

1 2 3 4

0

5

1 0

1 5

2 0

2 5

IB - IB - A 2 0 T N F

Ge

ne

CT

-C

yc

AC

T

C 1 7 .2 (U T )

C 1 7 .2 ( le n t i)

C lo n e A

C lo n e 5

**

F ig u r e 3 .1 3 . B a s a l e x p r e s s io n o f N F -B -d e p e n d e n t g e n e s in C 1 7 .2 c e l l

p o p u la t io n s .

G e n e e x p re s s io n w a s m e a s u re d b y R T -P C R a n d Q -P C R f ro m w ild ty p e

C 1 7 .2 , c lo n e A , c lo n e 5 a n d th e le n tiv iru s t ra n s d u c e d C 1 7 .2 c e l ls . A v e ra g e

C T v a lu e s o f th e g e n e o f in te re s t w e re s u b tra c te d b y th e a v e ra g e C T v a lu e s

fo r C y c A . E a c h e x p e r im e n t w a s p e r fo rm e d in t r ip lic a te . G ra p h s re p re s e n t

a v e ra g e o f c o l la te d d a ta , b a rs re p re s e n t S .D a n d a s te r is k s re p re s e n t

s ig n if ic an t K ru s k a l-W a llis A N O V A te s t re su lts (* = p -v a lu e 0 .0 5 ) .

The Kruskal-Wallis ANOVA results indicated differences in the basal expression of IκBα

and A20; at least one cell line had a significantly different expression level to the other cell

lines (p-value<0.05). The biggest differences observed were between wild-type and C17.2

(lenti) and clone A.

So far, the work described in this chapter has suggested differences between the differently

labelled C17.2 cell populations in terms of: TNFα-induced p65 dynamics, NF-κB reporter

gene activation, IκBα degradation and NF-κB-dependent gene expression changes. Many

of these factors might be influenced by the levels of p65 and negative feedback proteins

(e.g. IκBα, IκBε and A20) in the cells. Therefore the next aim was to quantify and compare

p65 and IκBα levels in the C17.2 cell populations.

3.2.1.3.4. Basal p65 and IκBα Expression in C17.2 Cell Lines

The next aim was to measure the levels of p65 and IκBα protein in the different cell

populations by Western blotting. Western blots for p65 are shown in Figures 3.14A and B.

In all of the cell populations, a band that corresponded to endogenous p65 was observed.

As expected the C17.2 (lenti) cells showed a single higher molecular weight band that

corresponded to p65-fluorescent fusion proteins. However, multiple intermediate

molecular weight bands were seen in the BAC clones. Clone 5 also had an even higher

molecular weight band. It was not possible to obtain control α-tubulin bands for the


87

Western blot conducted with C17.2 (lenti) cells (Figure 3.14A), therefore it is difficult to

draw any conclusions on the relative levels of p65 across C17.2 cell populations.

A B

F ig u r e 3 .1 4 . C o m p a r is o n o f p 6 5 p r o te in le v e ls in C 1 7 .2 c e l l p o p u la t io n s .

W e s te rn b lo ts w e re p e r fo rm e d w ith a p 6 5 a n t ib o d y , u s in g p ro te in s e x tra c ts

fro m : (A ) w ild ty p e C 1 7 .2 a n d le n t iv i ru s tra n s d u c e d c e lls a n d ; (B ) w ild ty p e

C 1 7 .2 a n d B A C c lo n e s .

IκBα levels were analysed by Western blotting and this is shown in Figure 3.15. As

observed with p65, multiple unexplained (lower molecular weight) bands were bound by

the IκBα antibody in the BAC clone cells. Again, it is difficult to make conclusions based

on these results: more p65 and IκBα Western blots should be conducted in the future to

fully characterise these cell lines.

From the results outlined in this chapter, it would seem that the C17.2 (lenti) cells

represented the most appropriate model system for study of NF-κB dynamics in C17.2

cells. In contrast to the BAC clone cells, they had similar levels of TNFα-stimulated NF-

luc induction and IκBα degradation to wild-type C17.2. The data obtained from single cell

imaging of fluorescently-tagged p65 dynamics in the C17.2 (lenti) and C17.2 (transient)

cells was more consistent with data from the literature than the results from BAC clonal

cells (Widera et al, 2006a). Transiently-transfected cells were excluded for use as a model

system, due to the inherent variability and time-consuming nature of transfections.


88

F ig u r e 3 .1 5 . C o m p a r is o n o f IB p r o te in le v e ls in

u n s t im u la te d C 1 7 .2 c e ll p o p u la t io n s .

P ro te in e x tra c ts f ro m u n s tim u la te d c e lls w e re a n a ly s e d

b y W e s te rn b lo tt in g w ith IB a n d - tu b u lin a n tib o d ie s .

3.2.2. Investigating NF-κB Dynamics in the BV.2 Cell Line

Population-level data on TNFα-induced NF-κB activation has previously been reported in

the BV.2 cell line (Sheppard et al, 2011). In this study free (activated) NF-κB levels were

measured using ELISA. Peak NF-κB activation was observed at 25 min post-10ng/ml

TNFα stimulation. To date, there has been no description in the literature of the time-lapse

analysis of p65 dynamics in single living BV.2 cells.

3.2.2.1. Creating BV.2 Reporter Cell Lines for Observation of p65 Dynamics

BV.2 cells are difficult to transfect and therefore the production of stable cell lines using

transfections was not possible. (Many unsuccessful attempts were made to transfect the

cells with the p65 plasmid; results not shown). Lentiviral transduction was therefore

employed to produce a BV.2 (lenti) cell line expressing p65-eGFP (Figure 3.16).


89

F ig u r e 3 .1 6 . E x p r e s s io n o f p 6 5 -e G F P in le n tiv ir u s tr a n s d u c e d B V .2 c e lls .

B V .2 c e lls w e re t ra n s d u c e d w i th a p 6 5 -e G F P c o n s tru c t . C o n fo c a l m ic ro s c o p y

im a g e s w e re ta k e n o f le n tiv iru s tra n s d u c e d c e lls . S c a le b a r= 5 0 µ m .

3.2.2.2. Single-cell p65 Dynamics

To investigate NF-κB response, BV.2 (lenti) cells were stimulated with 20ng/ml TNFα and

the dynamics of p65-eGFP localization were observed with a confocal microscope (see

Figure 3.17 for images and Figure 3.18 for Cell Tracker quantification). The cells exhibited

a heterogeneous and asynchronous NF-κB response with multiple p65-eGFP oscillations

being observed in single cells. On average, the initial peak in nuclear p65 fluorescence

occurred at 30 min post-TNFα stimulation. This was consistent with results reported by

Sheppard et al (2011).

F ig u r e 3 .1 7 . T N F - in d u c e d p 6 5 tr a n s lo c a t io n in le n t iv ir u s tr a n s d u c e d B V .2 c e l ls .

C e lls w e re s t im u la te d w i th 2 0 n g /m l T N F a t t im e 0 a n d v is u a lis e d b y c o n fo c a l m ic ro s c o p y

a t th e d i ffe re n t t im e p o in ts a f te r T N F s t im u la tio n . S c a le b a r = 2 0 µ m .


90

0 100 200 300 400

0

1

2

3

4

5

6

Nucle

ar p

65 F

luore

scence

Inte

nsity

Time after Stimulation (Minutes)

F ig u r e 3 .1 8 . A n a ly s is o f p 6 5 d y n a m ic s in s in g le B V .2 ( le n t i ) c e l ls fo llo w in g T N F s t im u la t io n .

L e n tiv i ru s tra n s d u c e d B V .2 c e l ls w e re s t im u la te d w ith 2 0 n g /m l T N F a n d o b s e rv e d b y c o n fo c a l

m ic ro s c o p y . N u c le a r f lu o re s e n c e fro m s in g le c e lls w a s a n a ly s e d u s in g C e llT ra c k e r . P o s t- s t im u la tio n

n u c le a r f lu o re s e n c e w a s n o rm a l is e d to m e a n p re -s t im u la t io n n u c le a r f lu o re s c e n c e . T h e d a ta s h o w n is f ro m

o n e re p re s e n ta tiv e e x p e r im e n t. C o lo u re d l in e s s h o w 1 0 re p re s e n ta tiv e s in g le c e lls a n d th e b la c k l in e

re p re s e n ts th e m e a n o f a l l 2 1 c e lls w h ic h w e re a n a ly s e d in th e e x p e rim e n t .

3.2.2.3. Population-level NF-κB Activation in BV.2 Cell Lines

The next step in the characterisation of the BV.2 (lenti) cells was to compare the NF-κB

response in these cells to that of wild-type BV.2 cells. This involved analysis of IκBα

levels over time and gene expression analysis at the cell population level.

3.2.2.3.1. TNFα-induced IκBα Degradation Profiles in BV.2 Cell Lines

Western blot analysis of IκBα levels before and after TNFα stimulation were performed in

triplicate with the wild type and BV.2 (lenti) cells. IκBα bands were quantified using

densitometry and normalised to α-tubulin bands and pre-stimulation IκBα levels (Figures

3.19 and 3.20).


91

0 5 0 1 0 0 1 5 0

0

1

2

3

4

5

6

7

8


No

rm

ali

se

d I

B-

Le

ve

ls R e p lic a te 1

R e p lic a te 2

R e p lic a te 3

A

B

F ig u r e 3 .1 9 W e s te r n b lo t a n a ly s is o f I B le v e ls in w i ld ty p e B V .2 c e l ls


P ro te in e x tra c ts w e re ta k e n fro m B V .2 c e l ls a t 1 5 m in in te rv a ls f ro m 0 to

1 2 0 m in a f te r s t im u la t io n w ith 2 0 n g /m l T N F . W e s te rn b lo ts fo r I B w e re

p e rfo rm e d w ith th e p ro te in e x t ra c ts . E x p e rim e n ts w e re p e rfo rm e d in



Both cell lines displayed a >60% decrease in IκBα within 15 min post-TNFα stimulation.

IκBα returned to, and was maintained at, pre-stimulatory levels within 60 min post

stimulation (with the exception of replicate 2 in Figure 3.19). It was noted that the wild

type cells might show a slower recovery in IκBα levels as indicated by the level of newly-

synthesized IκBα observed at 30 min. (In 2 out of 3 replicates, IκBα was ≥ 48% and <3%

of the pre-stimulatory level in BV.2 (lenti) and BV.2 (UT) cells, respectively.) This

difference in timing might be reflected by differences in NF-κB transcriptional activity

between the cell populations.


92

0 5 0 1 0 0 1 5 0

0 .0

0 .5

1 .0

1 .5

2 .0


No

rm

ali

se

d I

B-

Le

ve

ls R e p lic a te 1

R e p lic a te 2

R e p lic a te 3

A

B

F ig u r e 3 .2 0 W e s te r n b lo t a n a ly s is o f IB le v e ls in le n tiv ir u s -tr a n s d u c e d

B V .2 c e lls a fte r T N F s t im u la t io n .

P ro te in e x t ra c ts w e re ta k e n fro m le n tiv i ru s - tra n s d u c e d B V .2 c e lls a t 1 5 m in

in te rv a ls f ro m 0 to 1 2 0 m in a f te r s t im u la tio n w ith 2 0 n g /m l T N F . W e s te rn

b lo ts fo r IB w e re p e r fo rm e d w ith th e p ro te in e x t ra c ts .E x p e rim e n ts w e re


a n a ly s is o f tr ip lic a te e x p e rim e n ts (B la c k l in e = b lo t s h o w n in A ).

3.2.2.3.2. NF-κB-dependent Gene Expression Changes in TNFα Stimulated BV.2 Cell

Lines

To observe transcriptional NF-κB activity in BV.2 cell lines, NF-κB-dependent gene

expression changes were measured over a timecourse after TNFα stimulation (Figure

3.21).


93

0 1 2 3 4 5 6 7 8 9

0

1 0

2 0

3 0


Fo

ld C

ha

ng

e i

n m

RN

A

0 1 2 3 4 5 6 7 8 9

0

1 0

2 0

3 0

4 0


Fo

ld C

ha

ng

e i

n m

RN

A

IB -

T N F

IB -

A 20

A B

F ig u r e 3 .2 1 . N F - B -d e p e n d e n t g e n e e x p r e ss io n c h a n g e s in w ild ty p e v s le n t iv ir u s

tr a n sd u c e d B V .2 c e lls fo llo w in g T N F s t im u la t io n .

G e n e e x p re ss io n o f k n o w n N F - B ta rg e t g e n e s w a s m e a su re d b y Q -P C R a t 0 , 1 5 , 3 0 , 6 0 ,

1 2 0 , 2 4 0 3 6 0 a n d 4 8 0 m in a f te r s t im u la tio n w ith 2 0 n g /m l T N F . G ra p h s sh o w

T N F - in d u c e d g e n e e x p re s s io n c h a n g e s in (A ) w ild - ty p e B V .2 c e lls a n d ; (B )

le n tiv iru s - tra n sd u c e d B V .2 c e lls . E x p e r im e n ts w e re c o n d u c te d in tr ip lic a te w ith th re e

te c h n ic a l re p lic a te s . B a rs re p re se n t S .D .

The different cell populations showed similar expression profiles for A20 and TNFα, with

similar timing and amplitude of peak changes. The IκBα expression profile of the BV.2

(lenti) cells had a similar temporal profile to the wild type cells, but had a lower maximum

fold induction (4 fold versus 10 fold).

The IκBε gene expression profiles between the two cell populations were noticeably

different. In the BV.2 (lenti) cells, this gene showed an oscillatory expression profile

peaking at 2 and 6 h post-stimulation whereas, in wild-type cells, expression peaked at 1 h

post-stimulation. IκBε expression in the wild-type cells stayed elevated throughout the

remainder of the time course.

Basal expression of NF-κB-dependent genes was compared across BV.2 cell lines (results

are shown in Figure 3.22). The results of Mann Whitney U tests indicated that there were

no significant differences in basal gene expression between the cell populations. Therefore,

basal gene expression levels do not play a role in the gene expression differences seen in

Figure 3.21.


94

1 2 3 4

0

5

1 0

1 5

2 0

2 5

Ge

ne

CT

-C

yc

AC

T

B V .2 (U T )

B V .2 ( le n t i)

IB - IB - A 2 0 T N F

F ig u r e 3 .2 2 . B a s a l e x p r e s s io n o f N F -B -d e p e n d e n t g e n e s in

B V .2 c e l l p o p u la t io n s .

B a s a l e x p re s s io n o f N F -B -d e p e n d e n t g e n e s w a s m e a s u re d in

w ild - ty p e a n d le n tiv iru s tra n s d u c e d B V .2 c e l ls . A v e ra g e C T

v a lu e s o f th e in te re s t g e n e w e re s u b tra c te d b y th e a v e ra g e C T

v a lu e s o f C y c A . C o lu m n s re p re s e n t a v e ra g e s o f c o lla te d d a ta a n d

b a rs re p re s e n t S .D . M a n n W h itn e y U te s t re s u l ts in d ic a te n o

s ig n if ic a n t d iffe re n c e s b e tw e e n th e c e ll p o p u la tio n s .

To complete characterisation of the BV.2 cell lines, p65 and IκBα levels were measured in

these cell lines.

3.2.2.3.3. Basal p65 and IκBα Expression in BV.2 Cell Lines

Western blots were conducted to analyse the levels of p65 and IκBα in the wild-type and

BV.2 (lenti) cells (see Figures 3.23 and 3.24).

F ig u r e 3 .2 3 . W e s te r n b lo t a n a ly s is o f p 6 5 le v e ls in

th e w i ld - ty p e B V .2 c e l ls a n d B V .2 ( le n t i ) c e l ls .

P ro te in e x tra c ts f ro m u n s t im u la te d B V .2 c e lls a n d

le n t iv iru s tra n s d u c e d B V .2 c e lls w e re a n a ly s e d b y

W e s te rn b lo t t in g w i th a p 6 5 a n tib o d y .


95

F ig u r e 3 .2 4 . W e s te r n b lo t a n a ly s is o f I B le v e ls in

th e w i ld - ty p e B V .2 c e l ls a n d B V .2 ( le n t i ) c e l ls .

P ro te in e x tra c ts f ro m u n s t im u la te d B V .2 c e lls a n d

le n tiv iru s tra n s d u c e d B V .2 c e lls w e re a n a ly s e d b y

W e s te rn b lo tt in g w ith IB a n d - tu b u lin a n tib o d ie s .

Levels of endogenous p65 appeared to be comparable between the cell lines. Total p65

expression (endogenous plus p65-eGFP fusion protein) in the BV.2 (lenti) cells appeared

to be higher than in the wild type BV.2 cells. Western blot analysis of IκBα levels showed

similar results: BV.2 (lenti) cells appeared to express more IκBα than wild-type cells.

However, these Western blots did not contain control α-tubulin bands, which preclude

comparison of p65 and IκBα levels across cell populations.

3.3. Discussion

Analysis of TNFα-induced NF-κB activation has previously been reported at the cell

population level in neural progenitor/stem cells (Widera et al, 2006a) and microglia

(Sheppard et al, 2011). These studies might have missed some important characteristics of

the NF-κB response in cells, as they did not make single-cell level observations. To this

end, the first goal of the work described in this chapter was to create neural progenitor and

microglial cell lines, which could be readily used for p65 observation within individual

living cells. The next goal was to systematically characterise NF-κB activation, in wild-

type and reporter cell lines, to determine the best model system for use in future

experiments. The major findings of this characterisation procedure will be described in the

following sections.

3.3.1. NF-κB Activation in C17.2 Cells

NF-κB activation was measured using a consensus NF-κB-luciferase reporter. Overall the

response was similar to that reported for other cell types (Cheong et al, 2006; Khabar et al,

1995; Turner et al, 2010).


96

The lowest TNFα dose required to achieve maximal induction of the NF-luc reporter was

between 100pg/ml and 1ng/ml (Figure 3.5). Peak induction occurred at 5 h post-

stimulation with doses ≥1ng/ml TNFα; 1 h later than previously observed in SK-N-AS

cells (Turner et al, 2010). Conversely, with doses ≤100pg/ml, peak NF-luc induction was

observed earlier in C17.2 compared to SK-N-AS cells (3 h versus 6 h post-stimulation).

This latter result cannot be explained by higher basal TNFR expression in C17.2 cells, as

these cells were less sensitive to lower doses of TNFα than SK-N-AS cells: the lowest

TNFα dose that led to NF-luc induction was 100pg/ml in C17.2, versus 10pg/ml in SK-N-

AS cells (Turner et al, 2010).

3.3.1.1. Single-Cell p65 Dynamics in C17.2 Cells

Nuclear localisation of p65 in C17.2 cells, 30 min after TNFα stimulation, has previously

been reported in fixed cells, via p65 immunostaining (Widera et al, 2006a). Results from

transiently-transfected and C17.2 (lenti) cells were consistent with this observation.

In previous studies of p65 dynamics, cells that were highly overexpressing p65 were

eliminated from the analysis (Nelson et al, 2004; Ashall et al, 2009; Turner et al, 2010).

Here, all C17.2 (transient) cells were included in the analysis: the consequent variations in

p65 overexpression may explain the differences between C17.2 (transient) and C17.2

(lenti) cells: lower amplitude p65 nuclear translocations were observed in transiently-

transfected cells, compared to C17.2 (lenti) cells (Figure 3.3).

To minimise perturbation of the NF-κB response, it is important to only analyse transfected

cells which express relatively low levels of the fusion protein. Combined with low

transfection efficiency, this cell selection procedure reduces the amount of data that can be

acquired from each transfection/microscopy experiment. Stable transfection with the p65

plasmid was not possible as it would have required geneticin selection, an antibiotic to

which all C17.2 cells are immune. Moreover, lentiviral transductions usually result in

integration of low copy number of genes across cells in a population, making them more

reliable as reporter systems. For this reason, C17.2 (lenti) cells were selected as the best

model system for representing untransfected C17.2 cells in future experiments.

3.3.1.2. NF-κB-dependent Gene Expression

Strong induction of NF-κB-dependent genes was observed after TNFα-stimulation (Figure

3.12). Consistent with data from other cell lines, IκBε induction in C17.2 cells was delayed

compared to IκBα. A forty-five minute delay, observed in MEFs, is thought to be optimum


97

for maximising asynchronicity of NF-κB response between cells (Ashall et al, 2009;

Paszek et al, 2010) The delay in C17.2 cells cannot be established to the same degree of

accuracy from timepoints observed here, but expression profiles of IκBα and IκBε were

similar to that observed in MEFs (Paszek et al; 2010). This would suggest that the NF-κB

response in C17.2 cells is asynchronous, as reported with other cell lines (Nelson et al,

2004; Ashall et al, 2009; Paszek et al, 2010).

IκBε expression is important for the termination of the NF-κB response (Hoffmann et al,

2002). Unlike IκBα, the IκBε profile in C17.2 cells was similar to that observed in SK-N-

AS (Ashall et al, 2009). This might suggest a similar duration of NF-κB response. Also, a

peak in TNFα gene expression observed here at 1 h may have contributed to a later

resurgence of NF-κB activation in C17.2 cells; TNFα-induced upregulation of TNFα could

create a feed forward loop (Covert et al; 2005).

3.3.2. NF-κB Activation and p65 Dynamics in p65-BAC Stable C17.2 Clones

TNFα invoked a strong activation of NF-κB in wild-type C17.2, as measured by NF-κB-

dependent increases in luciferase expression (see Figure 3.5). However, TNFα stimulation

of clones A and 5 induced very low levels of NF-κB activation and did not mirror the dose-

dependent profile generated by wild-type cells. IκBα levels in clones reflected this

observation: levels were maintained for up to 2 h post-20ng/ml TNFα stimulation.

Single-cell data with the BAC clones was consistent with the population-level results:

clones A and 5 exhibited very small to no p65 nuclear translocations, compared to C17.2

(lenti) and transiently transfected cells (Figure 3.3). Although low TNFα-induced NF-κB

activation was observed in these cells, strong induction of NF-κB-dependent gene

expression was observed after 20ng/ml TNFα stimulation (Figure 3.12). These differences

may have been caused by the single cell cloning process.

Ryder et al (1990) suggested that significant changes in culture conditions, such as cell-cell

contact and composition of culture media, could incline C17.2 cells towards a more

neuronal phenotype. This suggests that BAC clonal cells were more differentiated than

wild-type C17.2 cells. Support for this idea comes from a study by Listwak et al (2013).

They obtained similar, seemingly contradictory, TNFα-induced NF-κB activation results

from murine cortical neurons. In this study, IκBα level, NF-κB-dependant gene expression

and nuclear p65 was measured after 100ng/ml TNFα stimulation. Very little to no nuclear


98

p65 presence was reported at 30 minutes and IκBα levels were maintained up to 1 hour

post-stimulation. However, NF-κB-dependant gene expression changes were observed.

Mixed brain and microglial cell cultures were also investigated in this study; these cells all

displayed strong TNFα-induced nuclear p65 and IκBα degradation. Together with the

results of this study, the present study suggests that during the process of cloning, the p65-

BAC stable cells may have adopted a more neuronal phenotype.

3.3.3. NF-κB Activation in BV.2 (UT) Cells

NF-κB activation has previously been reported in BV.2 cells, in response to TNFα using

population-level assays (Sheppard et al, 2011). Peaks in nuclear p65 were reported at 25

min and 105 min after 10ng/ml TNFα stimulation. Here, average nuclear p65 peaks were

observed around 30 and 105 min after TNFα stimulation: this provides support for the use

of BV.2 (lenti) as a representative for p65 in untransfected BV.2 cells (Figure 3.18).

3.3.3.1. IκBα Degradation in BV.2 (UT) Cells

In the BV.2 cultures, over 60% of IκBα was degraded within 15 min of TNFα stimulation

(Figure 3.19), which was comparable to that observed in other cell types (e.g. 70% in

HepG2 cells (Moss et al, 2012) and ≥85% in C17.2 cells). Pre-stimulatory levels of IκBα

were reached within 60 min of TNFα treatment, compared to 65 +/- 8% of the pre-

stimulatory level after 137 +/- 5 min in HepG2s (Moss et al, 2012). Assuming similar basal

nuclear p65 presence in these cells, variations in IκBα degradation could manifest in

different amplitudes of p65 nuclear translocation.

3.3.3.2. NF-κB-dependent Gene Expression

TNFα-induced changes in NF-κB-dependant gene expression were measured in BV.2 cells

(Figure 3.21). Peak IκBα induction was lower in BV.2 cells than SK-N-AS (~10 fold

versus >20 fold; Ashall et al, 2009). This may reflect smaller TNFα-induced changes in

nuclear p65. The timings of IκBα gene induction were similar between these cells; that

might be mirrored in the timings of the initial nuclear p65 translocations. Unlike in SK-N-

AS cells, IκBα upregulation decreases between 1-2 h. SK-N-AS cells exhibit sustained

nuclear p65 oscillations in response to TNFα, which allows IκBα gene expression to

remain upregulated for >7 h (Ashall et al, 2009). Differences in the upregulation of IκBα

expression indicate a more transient NF-κB response in BV.2 cells.


99

IκBε gene induction in BV.2 was comparable to SK-N-AS cells in terms of peak induction

and timings. Interestingly, IκBε peak induction occurred simultaneously to IκBα. Delayed

induction of the IκBε gene in relation to IκBα is believed to be responsible for

asynchronous NF-κB responses between cells in a population (Ashall et al, 2009; Paszek et

al, 2010). The lack of a delay in BV.2 cells may manifest in more synchronous NF-κB

dynamics in microglial populations. However, Sheppard et al (2011) produced a

mathematical model to reproduce population level data on p65 response in BV.2 cells and

they found that parameters relating to IκBε had little to no effect on NF-κB activity.

3.3.4. Discussion of Problems with using Lentivirally Transduced Cell Lines

NF-κB activation data from C17.2 and BV.2 reporter cell lines was compared to data from

the respective wild-type cell line. It was concluded that lentivirally transduced cell lines

were the best model systems for further use. However, there are potential problems with

using these lentivirally transduced cell lines that will be addressed here. These problems

include those that are specific to a cell line and lentiviral transductions, as well as generic

issues regarding the use of fusion proteins.

3.3.4.1. General Problems with p65 Overexpression

Many studies have used EMSA, bioluminescence and Western blots to observe population-

level NF-κB activation (Sheppard et al, 2011; Magni et al, 2012). Single-cell p65

localisation is commonly observed in fixed cells using immunostaining (Widera et al,

2006a). These methods do not offer any insights into single-cell p65 dynamics: an

important determinant of gene expression (Ashall et al, 2009; Lee et al, 2014). From this, it

can be conjectured that single-cell dynamics are vital determinants of cell fate. In order to

visualise p65 in living cells, many studies have taken advantage of constructs that enable

cells to express fluorescently-tagged p65 (Nelson et al, 2004; Ashall et al, 2009; Turner et

al, 2010). These studies have revealed many aspects of NF-κB activation that were not

detected on a population-level, including asynchronicity and heterogeneity of p65 response

within cell populations.

An unavoidable consequence of genetically modifying cells is increasing p65 levels. It has

been argued that overexpression of p65 within cells alters NF-κB localisation (Scott et al,

1993; Beg et al,1992; Zabel et al, 1993). This argument is countered with the observation

that physiological levels of fluorescent p65 were expressed in modified cell lines (Ashall et


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al, 2009). Also, it has been shown that the NF-κB system is subject to autoregulation by

p65-induced upregulation of IκBα (Scott et al, 1993; Brown et al, 1993; Sun et al, 1993).

Although literature suggests that moderate levels of p65 overexpression do not affect NF-

κB dynamics, this topic is discussed in more depth in relation to C17.2 and BV.2 reporter

cell lines

3.3.4.2. Choice of C17.2 (lenti) as a Model System and Potential Problems

From the data collected in the characterisation of C17.2 cell lines, it was concluded that the

C17.2 (lenti) cell line was the best model system for observation of p65 dynamics. This

was based on a few key characteristics. Firstly, TNFα-stimulated NF-luc induction in

C17.2 (lenti) showed a time- and dose-dependent profile similar to that observed in wild-

type cells (Figure 3.5). Secondly, the IκBα degradation profile in C17.2 (lenti) cells

strongly resembled that reported in wild-type cells, whereas clonal cells did not exhibit

TNFα-induced IκBα-degradation (Figure 3.8-3.11). Finally, TNFα-induced p65

translocations were observed in C17.2 (lenti) cells; this is consistent with the limited data

available on p65 localisation in NPCs (Figure 3.3). Again, BAC clonal cells responded

very differently, exhibiting little to no nuclear p65 translocations.

Although the C17.2 (lenti) cell line was selected as the best model system for use, some

differences were observed between the wild-type and C17.2 (lenti) cells: these differences,

and their potential consequences, will be discussed here.

A major concern when working with progenitor/stem cells is ensuring that they remain in

an undifferentiated state. Blits et al (2005) reported no change in NPC expression of stem,

glial and neuronal cell markers after lentiviral transduction with different constructs. Some

studies have employed transduction to overexpress transcription factors and, thereby,

induce differentiation (Maire et al, 2009; Falk et al, 2002; Stock 2010). There is currently

no data to suggest that NF-κB expression can be used to differentiate cells in the same

manner.

NF-κB-driven gene expression, as measured by NF-luc, was lower in C17.2 (lenti) than

wild-type cells after stimulation with doses ≥100pg/ml TNFα (Figure 3.5). However, the

same dose- and time-dependent profile was preserved: this was not the case with the BAC

clones investigated.


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Two out of three replicates from wild-type C17.2 cells exhibited complete degradation of

IκBα within 15 minutes following TNFα treatment (Figure 3.8). However, IκBα

degradation in the C17.2 (lenti) was incomplete (Figure 3.9). When combined with the

above observations made on activation of the luciferase reporter, these results might

suggest smaller amplitude NF-κB nuclear translocations in the C17.2 (lenti) cells.

IκBα in the C17.2 (lenti) cells returned to pre-stimulatory levels within 45 min post- TNFα

treatment, compared to 60 min in wild-type C17.2 (Figures 3.8 and 3.9). Also, rapid

reduction in IκBα level was observed in C17.2 (lenti) at 105 min after TNFα stimulation:

this was not observed in wild-type cells. These results are surprising and no evidence of

increased NF-κB activity was seen in the luciferase reporter assay experiments conducted

with the C17.2 (lenti) cells (Figure 3.5).

Finally, the expression of key NF-κB-dependent genes, IκBα, IκBε and A20, was observed

in wild-type and C17.2 (lenti) cells: overall, the cells displayed similar expression profiles.

C17.2 (lenti) cells exhibited the same delay in IκBε gene induction, compared to IκBα, as

observed in wild-type C17.2 cells and non-neural cell lines (Paszek et al, 2010). However,

TNFα gene induction was markedly stronger in C17.2 (lenti) cells, compared to wild-type

C17.2: peak fold induction was >180 at 1 h post-TNFα stimulation (versus ~9 fold in wild-

type cells). TNFα can contribute to a feed-forward loop and could lead to later, secondary

NF-κB activation in cells (Covert et al, 2005). This may have contributed to IκBα

degradation observed at 105 min post-TNFα stimulation (Figure 3.9).

3.3.4.3. Choice of BV.2 (lenti) as a Model System and Potential Problems

To ensure that the lentiviral transduction procedure did not change the activation status of

BV.2 cells, TNFα expression can be compared between BV.2 (UT) and BV.2 (lenti):

TNFα expression is commonly used as an indicator of BV.2 activation status (Kobayashi et

al, 2013; Liu et al, 2013b). There was no difference in the basal expression of TNFα

between wild-type and BV.2 (lenti) cells (Figure 3.21). Moreover, the same was true for

IκBα, IκBε and A20 gene expression. This indicates that transduction did not alter the

activation status of microglia or basal NF-κB transcriptional activity.

However, TNFα-induced IκBα gene induction was weaker in BV.2 (lenti) cells compared

to wild-type cells. This was not reflected in the resynthesis of IκBα: 30 min post-TNF-α

stimulation, IκBα levels were ≥48% of pre-stimulatory levels in BV.2 (lenti) cells,

compared to 20% on average in wild-type cells (Figures 3.19 and 3.20). It is difficult to


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draw any definitive conclusions from this, but differences in IκBα resynthesis time may

affect NF-κB nuclear export times. IκBα degradation and the time taken to restore IκBα to

pre-stimulatory levels were similar between the cell populations.

Activation of IκBε was higher in BV.2 (lenti) cells than BV.2 (UT). Sheppard et al (2010)

have previously suggested that the effects of IκBε on TNFα-induced NF-κB activity are

negligible. However, this conclusion originated from a mathematical model (the Ashall et

al (2009) model) that was adapted to fit population-level data. Population-level data has

previously failed to provide insights on the various mechanisms for fine-tuning NF-κB

activity and dynamics, whereas single-cell data has filled this niche (Nelson et al, 2004;

Ashall et al, 2009; Turner et al, 2010; Paszek et al, 2010). For this reason, it must be noted

that differences in IκBε levels may cause premature termination of NF-κB activity in BV.2

(lenti), compared to wild-type BV.2.

Cells have an ability to compensate for small increases in p65, either through an inherent

availability of excess, or an induced upregulation of IκBα (Scott et al, 1993; Brown et al,

1993; Sun et al, 1993). However, large increases in p65 can disrupt normal NF-κB activity

and localisation (Beg et al, 1992; Zabel et al, 1993). Preliminary Western blots showed that

p65 expression in BV.2 (lenti) cells was comparable to endogenous p65 expression in the

wild-type cells. Also, IκBα levels in BV.2 (lenti) cells appeared to be upregulated (Figures

3.23 and 3.24). As observed in cells that overexpress p65, this may be a compensatory

method to minimise perturbation to the NF-κB network (Scott et al, 1993).


103

4. NF-κB Activation and Dynamics

in C17.2 and BV.2 Cells in Mono-

cultures and Co-cultures


104


Having established lentivirally transduced cell lines, C17.2 (lenti) and BV.2 (lenti), as

suitable model systems for the study of NF-κB in C17.2 and BV.2 cells, the project could

progress onto the next stage: investigation of NF-κB -mediated interactions between cells.

This chapter details NF-κB activation profiles in mono-cultures and 1:1 co-cultures, after

TNFα-stimulation.

4.2. Results

4.2.1. NF-κB Dynamics and Activation in C17.2 Cells

4.2.1.1. Single-cell p65 Dynamics in Mono-cultures and 1:1 Co-cultures

C17.2 cells were seeded in mono-cultures or 1:1 co-cultures with BV.2 in glass-bottom

dishes. Figures 4.1A and B show C17.2 (lenti) cells in mono-culture and co-culture,

respectively. Dishes were put on a confocal microscope, cells were stimulated with

20ng/ml TNFα and time-lapse images were taken from 0 to 300 min after stimulation.

Microscopy experiments were performed in triplicate.

F ig u r e 4 .1 . E x p r e s s io n o f p 6 5 -e G F P in C 1 7 .2 ( le n t i) c e l ls , in

m o n o -c u ltu r e a n d 1 :1 c o -c u ltu r e (w ith B V .2 c e l ls ) .

C 1 7 .2 c e l ls w e re t ra n s d u c e d w i th a p 6 5 -e G F P c o n s t ru c t .

C o n fo c a l m ic ro s c o p y im a g e s w e re ta k e n o f le n tiv iru s tra n s d u c e d

c e lls in : (A ) M o n o -c u ltu re s a n d (B ) 1 :1 C o -c u ltu re s , w ith

b rig h tf ie ld to a l lo w o b s e rv a tio n o f u n tra n s fe c te d B V .2 c e lls

( in d ic a te d b y b la c k a rro w s ) . S c a le b a r= 5 0 µ m .

A B

Nuclear p65 was quantified, using CellTracker software (Perkins, 2007). A complete cell

tracking time line was impossible for cells that moved out of the field of view, moved out

of focus, died or divided during the course of the experiment. Post-TNFα stimulation data


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was normalised to mean pre-stimulation nuclear p65 levels to show fold changes in nuclear

p65 (Figures 4.2A and B). Data is displayed as heat maps in Figures 4.2C and D. Higher

nuclear p65 fold changes are represented by darker colours in these heat maps.

A B

C D

0 5 0 1 0 0 1 50 2 0 0 2 5 0 3 00 0 5 0 1 0 0 1 50 2 0 0 2 5 0 3 00

T im e a fte r S tim u la tio n (M in u te s ) T im e a fte r S tim u la tio n (M in u te s )

M o n o -c u lt u r e C o -c u ltu r e

F ig u r e 4 .2 . Q u a n t if ic a t io n o f n u c le a r p 6 5 f lu o r e s c e n c e in C 1 7 .2 ( le n t i ) c e l ls , a f te r T N F

s t im u la t io n , in m o n o -c u ltu r e s a n d 1 :1 c o -c u ltu r e s (w ith B V .2 c e l ls ) .

N u c le a r p 6 5 f lu o re s c e n c e w a s re c o rd e d b e tw e e n 0 a n d 3 0 0 m in a f te r T N F s tim u la tio n .

R e a d in g s w e re n o rm a lis e d to m e a n p re -s t im u la tio n n u c le a r p 6 5 f lu o re s c e n c e . (A ) a n d (B ) S in g le

c e l l t ra c e s fo r 6 3 m o n o -c u ltu re d c e lls a n d 5 6 c o -c u ltu re d c e lls , re s p e c tiv e ly . T h ic k b la c k l in e s

s h o w th e a v e ra g e o f a l l o f th e c e l ls in e a c h p o p u la t io n . (C ) a n d (D ) H e a t m a p s re p re s e n tin g fo ld

c h a n g e s in n u c le a r p 6 5 f lu o re s c e n c e in m o n o -c u ltu re d a n d c o -c u l tu re d c e lls , re s p e c tiv e ly . E a c h

ro w d is p la y s d a ta fro m a s in g le -c e ll : d a rk e r c o lo u rs re p re s e n t h ig h e r a m p litu d e c h a n g e s in

n u c le a r p 6 5 f lu o re s c e n c e . S in g le -c e ll d a ta w a s c o lla te d f ro m m ic ro s c o p y e x p e rim e n ts

p e rfo rm e d in tr ip lic a te .

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All cells in mono-culture displayed a clear initial p65 nuclear translocation (as reported

previously in Chapter 3). Some cells displayed a more sustained nuclear p65 presence,


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after the initial p65 translocation. In contrast, C17.2 (lenti) cells in co-culture displayed an

initial translocation, of lower amplitude, and no subsequent translocations.

Timing and amplitude of initial nuclear p65 translocations were quantified for each cell in

mono-culture and co-culture. Unpaired t-tests were conducted and averaged data is

displayed in Figure 4.3. On average, the amplitude of the initial p65 translocation was

significantly lower in co-cultured C17.2 (lenti) cells than mono-cultured cells (p-

value≤0.01; Figure 4.3B). There was no significant difference in the initial nuclear p65

peak timing between culture conditions (Figure 4.3A).

M o n o -c u ltu re C o -c u ltu re

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F ig u r e 4 .3 . A v e r a g e p e a k t im in g a n d a m p li tu d e o f th e f ir s t p 6 5 n u c le a r

tr a n s lo c a tio n , a fte r T N F s t im u la t io n , in C 1 7 .2 ( le n t i ) c e l ls .

N u c le a r p 6 5 f lu o re s c e n c e re a d in g s w e re ta k e n f ro m 0 to 3 0 0 m in a f te r T N F

s t im u la tio n in le n tiv iru s tra n s d u c e d C 1 7 .2 c e lls , in m o n o -c u ltu re s a n d 1 :1 c o -c u ltu re s

(w ith B V .2 c e lls ) . N u c le a r p 6 5 f lu o re s c e n c e w a s q u a n tif ie d . (A ) a n d (B ) A v e ra g e p e a k

tim in g a n d a m p litu d e o f in it ia l p 6 5 n u c le a r tra n s lo c a tio n s in 6 3 m o n o -c u ltu re d c e lls a n d

5 6 c o -c u l tu re d c e lls , re s p e c tiv e ly . B a rs re p re s e n t S .D .

To further characterize the dynamic profiles seen in Figure 4.2, single-cell data was

clustered using a k-means algorithm and a cluster number of 4. Different cluster numbers

were investigated initially (results not shown): clustering into 4 groups produced results

that best represented the heterogeneity of the p65 response. The k-means algorithm sorted

cells into 4 different p65 response categories (Figure 4.4A-D). Figures 4.4E and 4.4F show

the distribution of cells across p65 response categories.

Cells were sorted into clusters according to two different aspects of p65 response,

predominantly: 1) amplitude of initial nuclear p65 translocation and 2) response duration.

Amplitude of nuclear p65 translocation decreases going from Figure 4.4A through to 4.4D.

Clusters A and B accommodated cells that displayed sustained nuclear p65 occupancy: on

average, nuclear p65 returned to pre-stimulatory levels at ≥150 min after TNFα-


107

stimulation. Only cells that were tracked for at least 300 min were included in this analysis

(47 and 45 mono-cultured and co-cultured C17.2 (lenti) cells, respectively).

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F ig u r e 4 .4 . T N F - in d u c e d p 6 5 n u c le a r tr a n s lo c a t io n p r o f i le s o b ta in e d fr o m C 1 7 .2

(le n ti ) c e l ls in m o n o -c u ltu r e s a n d 1 :1 c o -c u ltu r e s (w ith B V .2 c e l ls ) .

N u c le a r p 6 5 f lu o re s c e n c e re a d in g s w e re re c o rd e d b e tw e e n 0 a n d 3 0 0 m in a f te r T N F

s t im u la tio n . R e a d in g s w e re n o rm a lis e d to m e a n p re -s t im u la to ry n u c le a r p 6 5 f lu o re s c e n c e .

T h is d a ta w a s c lu s te re d w ith a M a tla b k -m e a n s a lg o ri th m . (A )- (D ) M e a n n u c le a r p 6 5

flu o re s c e n c e o f c e lls in e a c h o f th e 4 c lu s te rs id e n ti f ie d b y th e a lg o ri th . (E ) T h e d is tr ib u t io n

o f c e lls a c ro s s c lu s te rs A -D . T h e to ta l n u m b e r o f c e l ls a n a ly s e d f ro m m o n o -c u l tu re s a n d

c o -c u l tu re s w a s 6 3 a n d 5 6 , re s p e c t iv e ly .

4.2.1.2. NF-κB Activation in Co-cultured Wild-type C17.2 Cells

C17.2 (lenti) cells that were co-cultured with BV.2 displayed smaller and fewer p65

nuclear translocations in response to TNFα, compared to mono-cultured cells. In an effort


108

to exaggerate co-culture effects and measure transcriptional output from the NF-κB

system, live cell luminometry was utilised (see Chapter 2 for methods).

Wild-type C17.2 cells were transiently transfected with an NF-luc plasmid then seeded in

24-well plates as mono-cultures or with BV.2 cells. Cultures were stimulated with different

doses of TNFα and luminescence measurements were taken every 15 min from 0 to 5 h

after stimulation. Experiments were performed in triplicate, with three technical replicates

per plate. Data from mono-cultures and co-cultures was normalized to the corresponding

unstimulated group. Figure 4.5 shows averaged data and the results of a one-way ANOVA,

comparing NF-κB response across mono- and co-culture groups.

The first set of experiments were conducted using 1:2 (C17.2:BV.2) co-cultures and doses

≤20ng/ml TNFα (1ng/ml, 10ng/ml and 20ng/ml; Figure 4.5A). Under these conditions, NF-

luc induction in co-cultured C17.2 cells was comparable to that in mono-cultures.

Continuing with the effort to enhance co-culture effects on C17.2 NF-κB response, higher

C17.2:BV.2 co-culture ratios were investigated (1:4 and 1:8; Figures 4.5B and C,

respectively) and TNFα dose was lowered (500pg/ml, 1ng/ml or 10ng/ml TNFα). One-way

ANOVA test results showed that peak C17.2 NF-luc induction was significantly lower in

1:4 co-cultures than in mono-cultures, at all doses investigated (p-value≤0.01; Figure

4.5B). Interestingly, this effect is not seen in 1:8 co-cultures.

To eliminate the possibility of confluency-dependent changes in NF-luc induction,

luminometry experiments were conducted using 1:4 co-cultures with SK-N-AS (human

neuroblastoma) cells instead of BV.2 (Figure 4.6). SK-N-AS cells were selected for use as

they are neural cells that, unlike BV.2 cells, are not part of the immune system. NF-luc

induction in these co-cultured C17.2 cells was comparable to that in mono-cultured C17.2.

Therefore, the effects displayed in Figure 4.5B were BV.2-specific.

In order to investigate whether the ability to inhibit C17.2 NF-luc induction was unique to

BV.2 or common to macrophages, luminometry experiments were conducted using a

murine peripheral macrophage cell line, RAW 264.7 (Figure 4.7). Significantly lower NF-

luc induction was observed in co-cultured C17.2 compared to mono-cultured cells (p-

value≤0.01), thus both BV.2 and RAW 264.7 inhibited TNFα-stimulated NF-luc induction

in C17.2.


109

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B a s a l C 1 7 .2

C 1 7 .2 + 1 n g /m l

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C 1 7 .2 + 1 0 n g /m l





F ig u r e 4 .5 . T N F -s t im u la te d N F - lu c in d u c t io n in C 1 7 .2 c e l ls , in m o n o -c u ltu r e s a n d

c o -c u ltu r e s (w ith B V .2 c e l ls ) .

C e lls w e re tra n s fe c te d w ith th e N F -lu c p la s m id , a n d s t im u la te d w i th v a ry in g d o s e s o f T N F .

L u m in e s c e n c e w a s m e a s u re d e v e ry 1 5 m in f ro m 0 to 3 0 0 m in a f te r T N F s t im u la t io n . E a c h

g ra p h re p re s e n ts N F -lu c in d u c t io n in m o n o -c u ltu re d c e lls a n d : (A ) 1 :2 c o -c u ltu re d c e lls , (B )

1 :4 c o -c u ltu re d c e lls a n d (C ) 1 :8 c o -c u ltu re d c e lls . A ll e x p e rim e n ts w e re p e rfo rm e d in

tr ip lic a te . B a rs re p re s e n t ±S .D . a n d a s te r is k s re p re s e n t s ig n if ic a n t o n e w a y A N O V A te s t

re s u l ts (* * = p -v a lu e 0 .0 1 , v e rs u s c o r re s p o n d in g m o n o -c u l tu re g ro u p ) .

A

B

C


110

F ig u r e 4 .6 . T N F -s t im u la te d N F - lu c in d u c t io n in C 1 7 .2 c e l ls , in

m o n o -c u ltu r e s a n d 1 :4 c o -c u ltu r e s (w ith S K -N -A S c e lls ) .

C 1 7 .2 c e l ls w e re tra n s fe c te d w i th a n N F - lu c p la s m id , th e n s e e d e d in

m o n o -c u ltu re s a n d 1 :4 c o -c u l tu re s w ith S K -N -A S c e lls . L u m in e s c e n c e

w a s m e a s u re d e v e ry 1 5 m in f ro m 0 to 3 0 0 m in a f te r T N F s tim u la tio n .

A ll e x p e r im e n ts w e re p e rfo rm e d in tr ip lic a te . B a rs re p re s e n t ± S .D . a n d

a s te r is k s re p re s e n t s ig n if ic a n t o n e -w a y A N O V A te s t re s u lts

(* * = p -v a lu e 0 .0 1 , v e rs u s c o r re s p o n d in g m o n o -c u l tu re g ro u p ) .

0 1 2 3 4 5

0

2

4

6

8

1 0

1 2

1 4

1 6


Fo

ld C

ha

ng

e i

n L

uc

ife

ra

se

Ex

pre

ss

ion

B a s a l C 1 7 .2

C 1 7 .2 + 5 0 0 p g /m l

C 1 7 .2 + 1 n g /m l

C 1 7 .2 + 1 0 n g /m l

C o n tro l C o -c u ltu re




0 1 2 3 4 5

0

2

4

6

8

1 0

1 2

1 4

1 6

1 8

2 0

2 2


Fo

ld C

ha

ng

e i

n L

uc

ife

ra

se

Ex

pre

ss

ion

B a s a l C 1 7 .2

C 1 7 .2 + 5 0 0 p g /m l

C 1 7 .2 + 1 n g /m l

C 1 7 .2 + 1 0 n g /m l





F ig u r e 4 .7 . T N F -s t im u la te d N F - lu c in d u c t io n in C 1 7 .2 c e l ls , in

m o n o -c u ltu r e s a n d 1 :4 c o -c u ltu r e s (w ith R A W 2 6 4 .7 c e lls ) .


m o n o -c u ltu re s a n d 1 :4 c o -c u ltu re s w i th R A W 2 6 4 .7 c e lls . L u m in e s c e n c e

w a s m e a s u re d e v e ry 1 5 m in f ro m 0 to 3 0 0 m in a f te r T N F s tim u la tio n .

A ll e x p e r im e n ts w e re p e rfo rm e d in tr ip lic a te . B a rs re p re s e n t ± S .D . a n d

a s te r is k s re p re s e n t s ig n if ic a n t o n e -w a y A N O V A te s t re s u lts

(* * = p -v a lu e 0 .0 1 , v e rs u s c o r re s p o n d in g m o n o -c u l tu re g ro u p ) .


111

Due to the method of analysing luminometry data, co-culture effects displayed in Figures

4.5-4.7 may have been a result of differences in basal NF-luc expression. After normalising

luminescence data to the unstimulated control, TNFα-induced fold changes in luciferase

expression were calculated relative to unstimulated luciferase expression levels. For

example, if after normalisation, basal and 5 hours post-TNFα stimulated luminescence was

300 and 1500 then the fold change would have been 5 (i.e. 1500/300). This means that a

high fold change would be obtained with a low basal luminescence and vice versa: higher

basal luciferase expression may have contributed to the lower fold changes in NF-luc

induction in co-cultures (versus mono-cultures).

To investigate this possibility, basal luminescence values across culture conditions were

compared. Each co-culture ratio was investigated in parallel with mono-cultures, so basal

luminescence of co-cultures could be compared directly to corresponding mono-cultures.

However, each co-culture ratio was investigated independently, in separate experimental

plates, therefore, basal luminescence of different co-cultures could be not be compared

directly e.g. basal luminescence of 1:2 co-cultures cannot be compared to that of 1:4 co-

cultures. Basal luminescence values from mono-cultures and co-cultures were evaluated

for significant differences using unpaired t-tests. Values were then averaged, and

normalised to the corresponding mono-culture average, for display in Figure 4.8.

No difference in basal luminescence was detected between mono-cultures and SK-N-AS

co-cultures (Figure 4.8B). In contrast, average basal luminescence was significantly higher

in RAW 264.7 (p-value≤0.01; Figure 4.8C), 1:4 BV.2 (p-value≤0.05), and 1:8 BV.2 co-

cultures (p-value≤0.01; Figure 4.8A), compared to mono-cultures. Basal luminescence

values from untransfected BV.2 cells were measured to ensure that the observed

differences in luminescence could not be attributed to increasing background from cells.

The background luminescence from BV.2 remained the same across increasing cell

densities (moving from left to right in Figure 4.9). This indicates that BV.2, as well as

RAW267.4, increased basal NF-luc expression in co-cultured C17.2.


112

M o n o -c u ltu re 1 :4 C o -c u ltu re

0 .0

0 .5

1 .0

1 .5

Re

lati

ve

Lu

min

es

ce

nc

e

Mo

no

-cu

ltu

re

1:2

Co

-cu

ltu

re

Mo

no

-cu

ltu

re

1:4

Co

-cu

ltu

re

Mo

no

-cu

ltu

re

1:8

Co

-cu

ltu

re

0

1

2

3

4

5

Re

lati

ve

Lu

min

es

ce

nc

e*

**

M o n o -c u ltu re 1 :4 C o -c u ltu re

0

2

4

6

8

1 0

Re

lati

ve

Lu

min

es

ce

nc

e

**

F ig u r e 4 .8 . B a s a l lu m in e s c e n c e o f N F - lu c p la s m id -tr a n s fe c te d C 1 7 .2 c e lls , in

d if fe r e n t c u ltu r e c o n d it io n s .

B a s a l lu m in e s c e n c e re a d in g s fro m N F -lu c -t ra n s fe c te d C 1 7 .2 c e lls in m o n o -c u ltu re s a n d

c o -c u ltu re s w e re c o lla te d fro m lu m in o m e try d a ta d is p la y e d in F ig u re s 4 .5 -4 .7 . C h a rts

(A )- (C ) re p re s e n t d a ta fro m B V .2 , S K -N -A S a n d R A W 2 6 7 .4 c o -c u l tu re s , re s p e c t iv e ly .

A v e ra g e s a re d is p la y e d , n o rm a l is e d to c o r re s p o n d in g m o n o -c u l tu re g ro u p . B a rs

re p re s e n t ± S .D . a n d a s te r is k s re p re s e n t s ig n if ic a n t u n p a ire d t- te s t re s u lts

(* = p -v a lu e 0 .0 5 , * * = p -v a lu e 0 .0 1 , v e rs u s c o r re s p o n d in g m o n o -c u l tu re g ro u p ) .

A B

C

Having established that co-culture of BV.2 cells increased basal luminescence but

significantly reduced TNFα-induced NF-luc induction in C17.2 cells, luminometry

experiments were conducted to ascertain whether or not these effects were cell-contact

dependent. In these experiments, transwell membranes were used to prevent contact

between BV.2 and C17.2 in co-cultures, whilst allowing the passage of secreted

biomolecules. To avoid the possibility of transwell interference with luminescence

detection, endpoint luminometry was used in preference to live cell luminometry.


113

20,0

00

40,0

00

80,0

00

160,0

00

0 .0

0 .5

1 .0

1 .5

2 .0

N u m b e r o f M ic ro g lia l C e lls /W e ll

No

rm

ali

ze

d L

um

ine

sc

en

ce

F ig u r e 4 .9 . B a c k g r o u n d lu m in e s c e n c e fr o m B V .2 c e l ls .

B a c k g ro u n d lu m in e s c e n c e re a d in g s w e re m e a s u re d f ro m in c re a s in g

n u m b e rs o f u n tra n s fe c te d B V .2 c e lls . E x p e rim e n ts w e re p e r fo rm e d in

tr ip lic a te . A v e ra g e s d is p la y e d a b o v e a re n o rm a lis e d to lu m in e s c e n c e

fro m 2 0 ,0 0 0 B V .2 c e lls . B a rs re p re s e n t ± S .D . U n p a ire d t - te s ts w e re

p e rfo rm e d o n th is d a ta s e t: n o s ig n if ic a n t d iffe re n c e s w e re h ig h lig h te d .

First, control experiments were performed to observe any effects that transwells might

exert on TNFα-induced NF-luc induction in C17.2. Cells were transfected with an NF-luc

plasmid and seeded in mono-cultures either with or without empty transwells. These cells

were then stimulated with 500pg/ml, 1ng/ml or 10ng/ml TNFα and lysed 5 h later.

Luminescence readings were taken from these lysates. Experiments were performed in

triplicate with three technical replicates per plate. Data was collated from replicates,

averaged and normalised to the corresponding unstimulated mono-culture (Figure 4.10A).

Also, basal luminescence readings were normalised to readings from mono-cultures

without transwells (Figure 4.10B).

As conducted earlier with data in Figures 4.5-4.7 (see Figure 4.8), unpaired t-tests were

used to compare basal NF-luc expression and TNFα-induced NF-luc induction in C17.2

cells seeded with and without transwells. For example, basal luminescence of unstimulated

mono-cultures without transwells was compared to that of unstimulated mono-cultures

with transwells. This same analysis was performed with TNFα-stimulated mono-cultures

with and without transwells; each TNFα-treated culture was compared to the

corresponding unstimulated culture. Results showed that transwells did not affect basal

NF-luc expression or NF-luc induction after TNFα-stimulation. Having established this,

the same luminometry protocol was used to investigate the effects of BV.2 cells on NF-luc


114

induction in C17.2 cells, in transwell co-cultures. BV.2 cells were seeded in transwell

inserts, separated from C17.2, at co-culture ratios of 1:4 and 1:8 (C17.2:BV.2).

1 2 3 40

2 0

4 0

6 0

8 0

1 0 0

T N F - D o s e

Fo

ld C

ha

ng

e i

n L

um

ine

sc

en

ce

B a s a l 5 0 0 p g /m l 1 n g /m l 1 0 n g /m lM o n o -c u ltu re T ra n s w e ll

M o n o -c u ltu re

0 .0

0 .5

1 .0

1 .5R

ela

tiv

e L

um

ine

sc

en

ce

M o n o -c u ltu reT ra n s w e ll

M o n o -c u ltu re

F ig u r e 4 .1 0 . U n s t im u la te d a n d T N F -s t im u la te d N F - lu c in d u c t io n in

m o n o -c u ltu r e d C 1 7 .2 c e l ls , w ith a n d w ith o u t tr a n s w e l ls .

C 1 7 .2 c e lls w e re tra n s fe c te d w i th a n N F -lu c p la s m id , th e n s e e d e d in m o n o -c u ltu re s

w ith o r w ith o u t e m p ty tra n s w e lls . C e lls w e re ly s e d fo r lu m in e s c e n c e re a d in g s 5 h

a f te r T N F -s t im u la tio n . A ll e x p e rim en ts w e re p e rfo rm e d in tr ip lic a te . (A ) B a s a l

lu m in e s c e n c e in tra n s w e ll c u ltu re s , n o rm a lis e d to lu m in e s c e n c e in m o n o -c u ltu re s

w i th o u t tra n s w e l ls (B ) T N F - in d u c e d fo ld c h a n g e s in lu m in e s c e n c e , n o rm a lis e d to

c o r re s p o n d in g u n s tim u la te d c u ltu re s . B a rs re p re s e n t ± S .D . U n p a ire d t - te s ts w e re

p e r fo rm e d o n d a ta : th e re w e re n o s ig n if ic a n t d if fe re n c e s fo u n d b e tw e e n

m o n o -c u ltu re s w ith a n d w i th o u t t ra n s w e lls .

A B

Results for 1:4 transwell co-cultures can be seen in Figure 4.11. TNFα-stimulated NF-luc

induction and basal NF-luc expression were compared across culture conditions using

unpaired t-tests (Figures 4.11A and B, respectively). NF-luc induction was significantly

lower in transwell co-cultures after stimulation with ≥1ng/ml TNFα (p-value≤0.05).

Stimulating transwell co-cultured C17.2 with 1ng/ml and 10ng/ml TNFα resulted in 42%

and 39% lower NF-luc induction, respectively (compared to mono-cultured C17.2). No

differences were observed in basal luminescence across culture conditions. Therefore,

increased basal NF-luc expression in co-cultured C17.2 (previously observed in Figure 4.8)

was dependent on physical contact with BV.2.

In contrast to results from 1:4 transwell co-cultures, NF-luc induction in NPCs in 1:8

transwell co-cultures was not significantly different to that of NPCs in mono-culture.

(Figure 4.12B). This suggests that TNFα-treated BV.2 cells are producing an NF-κB

activating agent that, in high ratio co-cultures, can counteract the NF-κB inhibition

observed in 1:4 co-cultures.


115

1 2 3 4

0

1

2

3

4

5

6

7

8

9

1 0

T N F - D o s e

Fo

ld C

ha

ng

e i

n L

um

ine

sc

en

ce

B a s a l 5 0 0 p g /m l 1 n g /m l 1 0 n g /m l

*

*

M o n o -c u ltu re T ra n s w e ll


0

1

2

3

Re

lati

ve

Lu

min

es

ce

nc

e

M o n o - c u l t u r e T r a n s w e ll 1 : 4 C o - c u ltu r e

A B

F ig u r e 4 .1 1 . U n s t im u la te d a n d T N F -s t im u la te d N F -lu c in d u c t io n in C 1 7 .2

c e l ls in m o n o -c u ltu r e s a n d 1 :4 tr a n s w e l l c o -c u ltu r e s (w ith B V .2 c e lls ) .


m o n o -c u ltu re s o r 1 :4 c o -c u ltu re s (w ith B V .2 c e lls in tra n s w e ll in s e r ts ) . C e lls

w e re ly s e d fo r lu m in e s c e n c e re a d in g s 5 h a f te r T N F -s tim u la tio n . A ll

e x p e r im e n ts w e re p e rfo rm e d in tr ip lic a te . (A ) B a s a l lu m in e s c e n c e in c u ltu re s ,

n o rm a l is e d to lu m in e s c e n c e in m o n o -c u ltu re s (B ) T N F - in d u c e d fo ld c h a n g e s in

lu m in e s c e n c e , n o rm a lis e d to c o r re s p o n d in g u n s tim u la te d c u l tu re s . B a rs re p re s e n t

± S .D . a n d a s te r is k s re p re s e n t s ig n if ic a n t u n p a ire d t - te s ts re s u lts

(* = p -v a lu e 0 .0 5 ) .

1 2 3 4

0

1 0

2 0

3 0

4 0

Fo

ld C

ha

ng

e i

n L

um

ine

sc

en

ce

B a s a l 5 0 0 p g /m l 1 n g /m l 1 0 n g /m l

T N F - D o s e

M o n o -c u ltu re T ra n s w e ll


0

1

2

3

Re

lati

ve

Lu

min

es

ce

nc

e

M o n o - c u l t u r e T r a n s w e ll 1 : 8 C o - c u ltu r e

A B

F ig u r e 4 .1 2 . U n s t im u la te d a n d T N F -s t im u la te d N F -lu c in d u c t io n in C 1 7 .2

c e l ls in m o n o -c u ltu r e s a n d 1 :8 tr a n s w e l l c o -c u ltu r e s (w ith B V .2 c e lls ) .


m o n o -c u l tu re s o r 1 :8 c o -c u ltu re s (w ith B V .2 c e l ls in tra n s w e ll in s e r ts ) . C e lls w e re

ly s e d fo r lu m in e s c e n c e re a d in g s 5 h a f te r T N F -s tim u la tio n . A ll ex p e rim en ts

w e re p e rfo rm e d in t r ip lic a te . (A ) B a s a l lu m in e s c e n c e in c u ltu re s , n o rm a lis e d to

lu m in e s c e n c e in m o n o -c u ltu re s (B ) T N F - in d u c e d fo ld c h a n g e s in lu m in e s c e n c e ,

n o rm a lis e d to c o rre s p o n d in g u n s t im u la te d c u ltu re s . U n p a ire d t- te s ts w e re

p e r fo rm e d o n d a ta : th e re w e re n o s ig n if ic a n t d if fe re n c e s fo u n d b e tw e e n

m o n o -c u l tu re s a n d c o -c u ltu re s .

In order to compare the effects of transwells, BV.2 cell-contact and increasing BV.2 cell

numbers, NF-luc transfected C17.2 were seeded in different conditions, in the same 24-

well plate. Some co-cultures were made using transwells to prevent C17.2-BV.2 cell

contact ('transwell co-culture' groups). Other co-cultures were seeded to enable contact

between cells ('w/empty transwell'). Cells were left overnight then lysed for basal


116

luminescence readings. Experiments were performed in triplicate. Luminescence data from

the ‘mono-culture with empty transwell’ groups was compared to that from all other

groups, using unpaired t-tests. All data was averaged and normalised to the ‘mono-culture

w/empty transwell’ group (Figure 4.13).

The results of unpaired t-tests were consistent with observations made previously: 1)

transwells did not induce basal NF-luc expression and; 2) C17.2 in contact-permissive co-

cultures exhibited higher basal luminescence than cells in mono-culture (p-value≤0.01)

and; 3) precluding contact between BV.2 and C17.2 cells prevented basal NF-luc induction

in C17.2.

In summary, BV.2 and RAW267.4 cells inhibited TNFα-stimulated NF-luc induction in

co-cultured C17.2 (in contact-permissive 1:4 co-cultures). On a single-cell level, nuclear

p65 translocations were inhibited in C17.2 (lenti) by BV.2 (in 1:1 co-cultures). The

directionality of co-culture effects was studied by observation of p65 dynamics in co-

cultured BV.2 cells.

4.2.2. Single-cell p65 Dynamics in BV.2 Cells, in Mono-cultures and 1:1 Co-cultures

BV.2 cells inhibited TNFα-induced p65 dynamics and NF-luc induction in C17.2 cells.

The mutuality of this effect was studied by characterising p65 dynamics in mono-cultured

and co-cultured BV.2 (lenti) cells. Cells were seeded in mono-cultures or 1:1 co-cultures,

Mo

no

-cu

ltu

re w

/o t

ran

sw

ell

Mo

no

-cu

ltu

re w

/ em

pty

tra

nsw

ell

1:2

Co

-cu

ltu

re w

/ em

pty

tra

nsw

ell

1:2

Tra

nsw

ell c

o-c

ult

ure

1:4

Co

-cu

ltu

re w

/ em

pty

tra

nsw

ell

1:4

Tra

nsw

ell c

o-c

ult

ure

1:8

Co

-cu

ltu

re w

/ em

pty

tra

nsw

ell

1:8

Tra

nsw

ell c

o-c

ult

ure

0

1

2

3

4

No

rm

ali

ze

d L

um

ine

sc

en

ce M o n o -c u ltu re w /o tra n s w e ll

M o n o -c u ltu re w / e m p ty tra n s w e ll

1 :2 C o -c u ltu re w / e m p ty tra n s w e ll

1 :2 T ra n s w e ll c o -c u ltu re





**

****

F ig u r e 4 .1 3 . B a s a l lu m in e s c e n c e in N F - lu c p la s m id tr a n s fe c te d C 1 7 .2 c e lls , in

d if fe r e n t c u ltu r e c o n d it io n s .

C 1 7 .2 c e lls w e re tra n s fe c te d w i th a n N F -lu c p la s m id , th e n s e e d e d in m o n o -c u ltu re s

a n d 1 :2 , 1 :4 o r 1 :8 B V .2 c o -c u ltu re s , w i th o r w ith o u t tra n s w e lls . C o -c u l tu re s w e re

m a d e to e i th e r p e rm it C 1 7 .2 -B V .2 c o n ta c t ( 'w /e m p ty tra n s w e ll ' g ro u p s ) o r to p re v e n t

c o n ta c t ( 't r a n s w e ll c o -c u l tu re ' g ro u p s ) . U n s tim u la te d lu m in e s c e n c e w a s m e a s u re d fro m

th e d if fe re n t c u ltu re s . A l l e x p e rim e n ts w e re p e rfo rm e d in tr ip lic a te .B a rs re p re s e n t

S .D . a n d a s te r is k s re p re s e n t s ig n if ic a n t u n p a ire d t - te s t re s u lts (* * = p -v a lu e 0 .0 1 ,

v e rs u s 'm o n o -c u l tu re w /e m p ty t ra n s w e l l ' g ro u p ) .


117

with C17.2 (UT) cells, in glass-bottom dishes (Figure 4.14A). Time lapse images were

taken from 0 to 400 min after TNFα-stimulation. Microscopy experiments were performed

in triplicate with mono-cultures. One co-culture microscopy experiment was performed

and analysed for discussion here.

F ig u r e 4 .1 4 . E x p r e s s io n o f p 6 5 -e G F P in B V .2 ( le n t i ) c e l ls , in

m o n o -c u ltu r e a n d 1 :1 c o -c u ltu r e (w ith C 1 7 .2 c e l ls ) .

B V .2 c e lls w e re t ra n s d u c e d w i th a p 6 5 -e G F P c o n s tru c t . C o n fo c a l m ic ro s c o p y

im a g e s w e re ta k e n o f le n tiv iru s t ra n s d u c e d c e lls in : (A ) M o n o -c u ltu re s a n d (B )

1 :1 C o -c u ltu re s (w ith C 1 7 .2 c e lls ) . (C ) B rig h tf ie ld im a g e o f c e lls c a p tu re d in

im a g e B to a l lo w o b s e rv a tio n o f u n tra n s fe c te d C 1 7 .2 c e lls ( in d ic a te d b y b la c k

a rro w s ) . S c a le b a r= 5 0 µ m .

A B C

Nuclear p65 fluorescence was quantified, using CellTracker software (Perkins, 2007).

Post-stimulation nuclear p65 fluorescence was normalised to mean pre-stimulation nuclear

p65 for each individual cell analysed (Figures 4.15A and B).This data is displayed as heat

maps in Figures 4.15C and D. Higher nuclear p65 fold changes are represented by darker

colours in these heat maps.

All BV.2 (lenti) cells exhibited at least one nuclear p65 translocation in response to TNFα,

in mono-cultures and co-cultures, respectively. Unlike C17.2 (lenti), many BV.2 (lenti)

cells displayed subsequent strong nuclear p65 translocations, with some degree of

regularity. These oscillatory dynamics have previously been reported in many different cell

lines (Nelson et al, 2004; Ashall et al, 2009; Turner et al, 2010). Peak to peak timing of

nuclear p65 translocations was calculated for every cell that displayed oscillations (i.e. ≥2

nuclear p65 translocations). These values were averaged for each cell to give a mean

oscillation period, represented by the blue dots in Figure 4.16. Mean values were averaged

and standard deviations were calculated: this data is represented by the black horizontal

and vertical lines in Figure 4.16, respectively.


118

0 5 0 1 0 0 1 5 0 2 00 2 5 0 3 0 0 3 5 0 4 00

T im e a fte r S tim u la tio n (M in u te s )

0 5 0 1 0 0 1 5 0 20 0 2 5 0 3 0 0 3 5 0 4 00

T im e a fte r S tim u la tio n (M in u te s )

A B

C D

M o n o -c u lt u r e C o -c u ltu r e

F ig u r e 4 .1 5 . Q u a n tif ic a t io n o f n u c le a r p 6 5 f lu o r e sc e n c e in B V .2 ( le n t i) c e lls ,

a f te r T N F s t im u la t io n , in m o n o -c u ltu r e s a n d 1 :1 c o -c u ltu r e s (w ith C 1 7 .2

c e l ls ) .

N u c le a r p 6 5 f lu o re sc e n c e w a s re c o rd e d b e tw e e n 0 a n d 4 0 0 m in a f te r T N F

s tim u la tio n . R e a d in g s w e re n o rm a lise d to m e a n p re -s t im u la tio n n u c le a r p 6 5

f lu o re sc e n c e . (A ) a n d (B ) S in g le c e ll t ra c e s fo r 5 7 m o n o -c u ltu re d c e lls a n d 2 0

c o -c u ltu re d c e lls , re sp e c tiv e ly . T h ic k b la c k l in e s sh o w th e a v e ra g e o f a l l o f th e

c e lls in e a c h p o p u la tio n . (C ) a n d (D ) H e a t m a p s re p re se n tin g fo ld c h a n g e s in

n u c le a r p 6 5 f lu o re sc e n c e in m o n o -c u ltu re d a n d c o -c u ltu re d c e lls , re sp e c tiv e ly .

E a c h ro w d isp la y s d a ta f ro m a s in g le -c e ll : d a rk e r c o lo u rs re p re se n t h ig h e r

a m p litu d e c h a n g e s in n u c le a r p 6 5 f lu o re sc e n c e . M o n o -c u ltu re d a ta w a s c o lla te d

fro m m ic ro sc o p y e x p e r im e n ts p e r fo rm e d in tr ip lic a te ; c o -c u ltu re d a ta w a s o b ta in e d

fro m o n e m ic ro sc o p y e x p e rim e n t.

0 100 200 300 4000

1

2

3

4

5

6

Nu

cle

ar

p65

Flu

ore

sce

nce

In

tensity

T ime after Stimulation (Minutes)0 100 200 300 400

0

1

2

3

4

5

6

Nu

cle

ar

p6

5 F

luore

scen

ce I

nte

nsity

T ime after Stimulation (Minutes)

The mean period for cells in mono-culture and co-culture was evaluated for significant

differences using an unpaired t-test, the results of which can be seen in Figure 4.16. The

average period of oscillations in co-cultured cells was 63 min, which was significantly

faster than the period observed in mono-cultured BV.2 (lenti) cells (108 min; p-

value≤0.01).


119

F ig u r e 4 .1 6 . A v e r a g e p e a k to p e a k t im in g o f p 6 5 n u c le a r

tr a n s lo c a t io n s in m o n o -c u ltu r e d a n d c o -c u ltu r e d B V .2 ( le n t i )

c e lls , a fte r T N F s t im u la t io n .

N u c le a r p 6 5 f lu o re s c e n c e re a d in g s w e re ta k e n fro m 0 to 4 0 0 m in

a f te r T N F s t im u la tio n in B V .2 ( le n ti) c e lls , in m o n o -c u ltu re s a n d

1 :1 c o -c u ltu re s (w ith C 1 7 .2 c e lls ) . F lu o re s c e n c e re a d in g s w e re u s e d

to c a lc u la te p e a k to p e a k t im in g o f p 6 5 n u c le a r tra n s lo c a tio n s in

c e lls . A v e ra g e p e a k to p e a k t im in g (p e r io d ) o f e a c h c e ll i s

re p re s e n te d b y a b lu e d o t . 5 3 m o n o -c u ltu re d a n d 2 0 c o -c u ltu re d

B V .2 c e lls a re re p re s e n te d h e re . A v e ra g e s a n d s ta n d a rd d e v ia t io n s

a re re p re s e n te d b y th e b la c k h o r iz o n ta l a n d v e rt ic a l b a rs ,

re s p e c tiv e ly . A s te r is k s s ig n ify th e re s u l ts o f a M a n n W h itn e y U te s t

(* * = p -v a lu e 0 .0 1 ) .


0

1 0 0

2 0 0

3 0 0

4 0 0

Av

era

ge

Os

cil

lati

on

Pe

rio

d

(Min

ute

s)

**

Peak timings and amplitudes of initial nuclear p65 translocations were quantified, unpaired

t-tests were conducted and data was averaged for display in Figure 4.17. Initial nuclear p65

translocation peaks occurred significantly earlier in co-cultured BV.2, compared to mono-

cultured cells (p-value≤0.05). No difference was found in the average amplitude of this

response between different cultures.

Single-cell data was clustered using a k-means algorithm and a cluster number of 2: this

cluster number was selected, out of a variety of cluster numbers tested (results not shown),

as it best represented the p65 dynamic profiles obtained here. Some cells were excluded

from this analysis, as it was not possible to track them for 400 min: the analysis was

conducted with 32 and 13 mono-cultured and co-cultured cells, respectively. Dynamic

profiles of nuclear p65 generated are displayed in Figures 4.18A and B. Figure 4.18C

represents the distribution of mono-cultured and co-cultured BV.2, across clusters A and

B.

All of the cells analysed exhibited p65 oscillations. Cells that displayed lower amplitude

oscillations, with a noticeable dampening of amplitude over time, were stratified into

cluster B; the remaining cells, in cluster A, exhibited only a slight dampening over time.


120

92% of co-cultured BV.2 (lenti) cells were sorted into cluster B, compared to 41% of

mono-cultured cells.


0

1 0

2 0

3 0

4 0

5 0

6 0

Tim

e (

Min

ute

s)

*


0

1

2

3

4

5

Fo

ld C

ha

ng

e i

n N

uc

lea

r

p6

5 F

luo

re

sc

en

ce

A B

F ig u r e 4 .1 7 . A v e r a g e p e a k t im in g a n d a m p litu d e o f th e f ir s t p 6 5 n u c le a r tr a n s lo c a tio n ,

a fter T N F s t im u la t io n , in B V .2 ( le n t i ) c e l ls , in m o n o -c u ltu r e s a n d 1 :1 c o -c u ltu r e s (w ith

C 1 7 .2 c e l ls ) .

N u c le a r p 6 5 f lu o re s c e n c e re a d in g s w e re ta k e n f ro m 0 to 4 0 0 m in a f te r T N F s t im u la tio n in

B V .2 ( le n ti) c e lls , in m o n o -c u ltu re s a n d 1 :1 c o -c u ltu re s (w i th C 1 7 .2 c e l ls ) . N u c le a r p 6 5

flu o re s c e n c e w a s q u a n t if ie d . (A ) a n d (B ) P e a k t im in g a n d a m p l itu d e o f in it ia l p 6 5 n u c le a r

tra n s lo c a tio n s in 5 7 m o n o -c u ltu re d c e lls a n d 2 0 c o -c u ltu re d c e lls , re s p e c tiv e ly . B a rs re p re s e n t

S .D .

In conclusion, BV.2 cells inhibited TNFα-stimulated NF-luc induction and p65 nuclear

translocations in C17.2. Conversely, TNFα-induced BV.2 p65 dynamics were altered by

C17.2: later initial peak timings and faster oscillations were observed in co-cultured BV.2,

compared to mono-cultured cells. The observations on BV.2 cells originated from only one

co-culture microscopy experiment, whereas results on C17.2 involved collation of data

from triplicate experiments. For these reasons, NF-κB in C17.2 became the primary focus

of further experiments.

To elucidate the mechanisms that may have been involved in BV.2 effects on C17.2 NF-

κB, the TNFα signalling pathway was targeted for further investigation.


121

0 100 200 300 4000

0.5

1

1.5

2

2.5

3

0 100 200 300 4000

0.5

1

1.5

2

2.5

3


0

2 0

4 0

6 0

8 0

1 0 0

% o

f C

ell

Po

pu

lati

on

A B


Fo

ld C

ha

ng

e i

n N

uc

lea

r p

65

Flu

ore

sc

en

ce

A B

C

F ig u r e 4 .1 8 . T N F - in d u c e d p 6 5 n u c le a r tr a n s lo c a t io n p r o f ile s o b ta in e d fr o m B V .2 ( le n t i )

c e lls in m o n o -c u ltu r e s a n d 1 :1 c o -c u ltu r e s (w ith C 1 7 .2 c e l ls ) .

N u c le a r p 6 5 f lu o re s c e n c e re a d in g s w e re re c o rd e d b e tw e e n 0 a n d 4 0 0 m in a f te r T N F s tim u la tio n

in B V .2 ( le n ti) c e lls . R e a d in g s w e re n o rm a lis e d to m e a n p re -s t im u la to ry n u c le a r p 6 5 f lu o re s c e n c e .

T h is d a ta w a s c lu s te re d w i th a M a t la b k -m e a n s a lg o r i th m . (A )- (B ) M e a n n u c le a r p 6 5 f lu o re s c e n c e

o f c e lls in th e 2 c lu s te rs id e n tif ie d b y th e a lg o ri th . (C ) T h e d is t r ib u tio n o f c e lls a c ro s s c lu s te rs A &

B . M o n o -c u ltu re d a ta w a s c o lla te d fro m m ic ro s c o p y e x p e r im e n ts p e rfo rm e d in tr ip lic a te .

C o -c u l tu re d a ta w a s o b ta in e d fro m o n e m ic ro s c o p y e x p e rim e n t .T h e to ta l n u m b e r o f c e lls a n a ly s e d

fro m m o n o -c u l tu re s a n d c o -c u l tu re s w a s 3 2 a n d 1 3 , re s p e c tiv e ly .

4.2.3. TNFα availability in Mono- and Co-cultures.

TNFα-stimulated NF-luc induction in C17.2 was inhibited by BV.2. On a single-cell level,

average TNFα-induced p65 nuclear translocations were of lower amplitude in co-cultured

C17.2 than in mono-cultured cells. Simple explanations for differences in p65 dynamics

would be: lower TNFα availability in co-cultures and lower TNFR expression in co-

cultured C17.2, compared to mono-cultured C17.2. First, TNFα availability in mono-

cultures and co-cultures was investigated, using TNFα ELISA.

C17.2 (UT) and BV.2 (UT) mono-cultures and 1:1 co-cultures were stimulated with

2ng/ml TNFα: this dose was selected based on sensitivity of the subsequent ELISA that

was conducted. Media from cultures was extracted at 0, 2, 4 and 6 h after stimulation.

Experiments were performed in triplicate and one ELISA was used to determine TNFα

concentration in all extracts simultaneously. This data was averaged and normalised to

concentration at time 0. Results are displayed in Figure 4.19.


122

0 2 4 6

0 .0

0 .5

1 .0

1 .5

T im e a f te r T N F S t im u la t io n (H o u r s )

Re

lati

ve

TN

F

Co

nc

en

tra

tio

n

C 1 7 .2 (U T )

B V .2 (U T )

1 :1 C o -c u ltu r e

F ig u r e 4 .1 9 . R e la tiv e T N F c o n c e n tr a t io n in m o n o - a n d

c o -c u ltu r e s , a fte r 2 n g /m l T N F - s t im u la t io n .

C 1 7 .2 a n d B V .2 m o n o -c u ltu re s a n d 1 :1 c o -c u l tu re s w e re s t im u la te d

w ith 2 n g /m l T N F . M e d ia f ro m th e s e c u l tu re s w a s e x t ra c te d a t 0 , 2 , 4

a n d 6 h o u rs a f te r T N F s t im u la tio n . E x p e rim e n ts w e re p e rfo rm e d in

tr ip lic a te . T N F c o n c e n tra tio n in e x t ra c ts w a s d e te rm in e d u s in g

E L IS A . A v e ra g e d a ta is d is p la y e d , n o rm a lis e d to T N F c o n c e n tra tio n

a t t im e 0 . B a rs re p re s e n t ± S .D . K ru s k a l-W a llis A N O V A te s ts w e re

p e rfo rm e d o n th is d a ta : n o s ig n if ic a n t d i ffe re n c e s w e re fo u n d b e tw e e n

c u ltu re c o n d it io n s .

Kruskal-Wallis ANOVA was used to test for significant differences in relative TNFα

concentrations at different time points, across culture conditions: no significant differences

were found. This suggests that TNFα availability was not responsible for the differences in

p65 response observed in co-cultured C17.2 (compared to mono-cultured C17.2).

Following on from this, TNFR expression was studied in mono-cultured and co-cultured

C17.2.

4.2.4. TNFR1 Expression in Unstimulated and TNFα-stimulated C17.2 cells, in Mono-

cultures and Co-cultures.

Having ruled out TNFα availability as a causative factor in C17.2 NF-κB inhibition, TNFR

expression became the next candidate for investigation. There are two receptors for TNFα:

TNFR1 and TNFR2, also known as p55 and p75, respectively (Smith et al, 1994). TNFR1

and TNFR2 expression has been reported on NPC and microglial cell lines (Cacci et al,

2005). The response to soluble TNFα is predominantly driven by TNFR1 interaction (Grell

et al, 1998). Therefore, focus was placed on analysis of TNFR1 expression in C17.2.

TNFR1 expression was measured with the use of a phycoerythrin-associated anti-TNFR1

antibody. After antibody labelling, fluorescence from phycoerythrin excitation was


123

measured via flow cytometry (see Chapter 2). All experiments were performed in

triplicate: each replicate involved collecting fluorescence measurements from 10,000 cells.

TNFR1 expression was measured in unstimulated and 20ng/ml TNFα-stimulated wild-type

C17.2 and C17.2 (lenti) cells, 2 h after stimulation. At this time point, little to no nuclear

p65 was detected in co-cultured C17.2 (lenti) cells, whereas some cells in mono-culture

were still exhibiting nuclear p65 translocations (see Figure 4.2). Mean TNFR1-associated

fluorescence was calculated and compared across C17.2 cell lines (Figure 4.20). Mean

fluorescence was also normalised to corresponding unstimulated fluorescence to represent

TNFα-induced changes in TNFR1 expression (Figure 4.21). Mann Whitney U tests were

performed to determine statistical significance. Representative flow cytometry profiles are

shown alongside each individual comparison.

TN

F- U

T

TN

F- Lent i

0

5

1 0

1 5

Me

an

Flu

ore

sc

en

ce

U T L e n t i

Basal- U

T

Basal- L

ent i

0

5

1 0

1 5

2 0

2 5

Me

an

Flu

ore

sc

en

ce

U T L e n t i

B a s a l T N F

0

5 0

1 0 0

1 5 0

Pe

rc

en

ta

ge

of M

ea

n F

luo

re

se

nc

e

B a s a l T N F

0

5 0

1 0 0

1 5 0

Pe

rc

en

ta

ge

of M

ea

n F

luo

re

se

nc

eA : B a s a l

F lu o r e s c e n c e

C : T N F -S t im u la te d


E : C 1 7 .2 (U T )


G : C 1 7 .2 (L e n t i )


F ig u r e 4 .2 0 . T N F R 1 -a s s o c ia te d f lu o r e s c e n c e in u n s tim u la te d a n d T N F -s t im u la te d w ild -ty p e

C 1 7 .2 c e l ls a n d C 1 7 .2 ( le n t i ) c e l ls .

T N F R 1 e x p re s s io n w a s m e a s u re d in w i ld - ty p e C 1 7 .2 a n d C 1 7 .2 ( le n t i) c e l ls , u s in g a n a n ti-T N F R 1

a n tib o d y . L a b e ll in g w a s c o n d u c te d in u n s tim u la te d a n d 2 0 n g /m l T N F -s t im u la te d c u ltu re s (2 h

a f te r s t im u la tio n ) . F lo w c y to m e try w a s u s e d to m e a s u re T N F R 1 -a s s o c ia te d f lu o re s c e n c e ; a l l

e x p e r im e n ts w e re p e rfo rm e d in tr ip l ic a te . (A ) a n d (B ) M e a n f lu o re s c e n c e o f c e lls in u n s t im u la te d

c u l tu re s a n d re p re s e n ta t iv e f lo w c y to m e try p ro f i le , re s p e c t iv e ly . (C ) a n d (D ) M e a n f lu o re s c e n c e o f

c e lls in T N F - t re a te d c u l tu re s a n d re p re s e n ta t iv e f lo w c y to m e try p ro f i le , re s p e c t iv e ly . (E ) a n d (F )

T N F - in d u c e d c h a n g e s in f lu o re s c e n c e in w i ld - ty p e C 1 7 .2 c e lls a n d re p re s e n ta t iv e f lo w c y to m e try

p ro fi le , re s p e c tiv e ly . (G ) a n d (H ) T N F - in d u c e d c h a n g e s in f lu o re s c e n c e in C 1 7 .2 ( le n ti ) c e lls a n d

re p re s e n ta tiv e f lo w c y to m e try p ro f i le , re s p e c tiv e ly . B a rs re p re s e n t ± S .D . M a n n W h itn e y U te s ts

w e re p e r fo rm e d o n th is d a ta : n o s ig n if ic a n t d if fe re n c e s w e re fo u n d .

B D

F H


124

Figures 4.20A and C show mean fluorescence in unstimulated and TNFα-stimulated C17.2

cell lines, respectively. Statistical analysis showed that differences in fluorescence were

not significant, suggesting comparable TNFR1 expression between C17.2 cell lines, in

unstimulated and TNFα-stimulated conditions. TNFα-induced changes in mean

fluorescence in wild-type C17.2 and C17.2 (lenti) cells are displayed in Figures 4.20E and

4.20G, respectively. No significant differences were detected within cell lines

(unstimulated versus TNFα-stimulated TNFR1 expression). These results supported use of

the C17.2 (lenti) cell line as representative of TNFR1 expression in wild-type C17.2. This

was important for co-culture experiments: C17.2 (lenti) could be separated from

untransfected BV.2 cells, according to eGFP fluorescence.

Figure 4.21 displays the mean fluorescence of unstimulated and TNFα-treated C17.2 (lenti)

cells in mono- and co-cultures. No difference was observed in TNFR1-associated

fluorescence between mono-cultured and co-cultured C17.2 (lenti) cells in unstimulated

and TNFα-treated conditions (Figures 4.21A and C, respectively). A key question was

whether these cells displayed greater decreases in TNFR1 expression in co-culture,

compared to mono-cultures. On average, mono-cultured C17.2 (lenti) cells exhibited a

17% decrease in TNFR1-associated fluorescence, after 2h TNFα-stimulation (Figure 4.20):

this was similar to the decrease exhibited by co-cultured C17.2 (lenti) cells (15%; see

Figure 4.21). These results strongly suggest that variations in TNFR1 expression levels are

not a causative factor in the differences in C17.2 p65 response, across culture conditions

(seen in Figure 4.2).


125

B a s a l T N F

0

5 0

1 0 0

1 5 0

Pe

rc

en

tag

e o

f M

ea

n F

luo

re

se

nc

e

Basal-

Len

t i

Basal

0

5

1 0

1 5

2 0

2 5

Me

an

Flu

ore

sc

en

ce


TN

F-

Len

t i

TN

F

0

5

1 0

1 5

2 0

Me

an

Flu

ore

sc

en

ce


A : C 1 7 .2 ( le n t i ) : U n s t im u la te d F lu o r e s c e n c e

C : C 1 7 .2 ( le n t i ) : T N F -S t im u la t e d F lu o r e s c e n c e

E : F lu o r e s c e n c e o f C 1 7 .2 ( le n t i ) in C o - c u ltu r e

F ig u r e 4 .2 1 . T N F R 1 -a s s o c ia te d f lu o r e s c e n c e in u n s tim u la te d a n d T N F -s t im u la te d C 1 7 .2

(le n t i ) c e lls .

T N F R 1 e x p re s s io n w a s m e a s u re d in C 1 7 .2 ( le n ti ) c e l ls , in m o n o -c u ltu re s a n d 1 :1 c o -c u l tu re s (w ith

B V .2 c e lls ) , u s in g a n a n ti-T N F R 1 a n tib o d y . L a b e ll in g w a s c o n d u c te d in u n s tim u la te d a n d 2 0 n g /m l

T N F -s t im u la te d c u ltu re s (2 h a f te r s t im u la tio n ) . F lo w c y to m e try w a s u s e d to m e a s u re

T N F R 1 -a s s o c ia te d f lu o re s c e n c e ; a l l e x p e rim e n ts w e re p e rfo rm e d in tr ip lic a te . (A ) a n d (B ) M e a n

flu o re s c e n c e o f c e l ls in u n s tim u la te d c e lls a n d re p re s e n ta tiv e f lo w c y to m e try p ro fi le , re s p e c tiv e ly .

(C ) a n d (D ) M e a n f lu o re s c e n c e o f c e l ls in T N F - tre a te d c u l tu re s a n d re p re s e n ta tiv e f lo w

c y to m e try p ro f i le , re s p e c t iv e ly . (E ) a n d (F ) T N F - in d u c e d c h a n g e s in f lu o re s c e n c e in c o -c u ltu re d

C 1 7 .2 c e l ls a n d re p re s e n ta t iv e f lo w c y to m e try p ro fi le , re s p e c t iv e ly . B a rs re p re s e n t ± S .D . M a n n

W h itn e y U te s ts w e re p e rfo rm e d o n th is d a ta : n o s ig n if ic a n t d i ffe re n c e s w e re fo u n d .

B

D

F


126

4.3 Discussion

Most studies on NF-κB activation and p65 dynamics have been conducted in non-neural

cell lines (Nelson et al, 2004; Ashall et al, 2009; Turner et al, 2010; Paszek et al, 2010) and

paracrine effects on p65 dynamics have yet to be investigated in mixed cell cultures.

Together, NPCs and microglia are vital governors of neuroinflammatory outcome: NPCs

regulate microglial proliferation and activation (Forstreuter et al, 2002; Mosher et al, 2012)

and, in turn, microglia regulate NPC survival, proliferation and differentiation (Liu et al,

2014; Liu et al, 2013a; Liu et al, 2013b; Guadagno et al, 2013). Other studies have shown

that NF-κB activation can determine NSC fate (Widera et al, 2006a; Widera et al, 2006b;

Piotrowska et al, 2006), as well as microglial activation status (Saijo and Glass, 2011;

Colton, 2009). Taken together, these observations provide a strong argument for the study

of NF-κB in NPCs and microglia, in mono-cultures and co-cultures.

Here, for the first time, p65 dynamics in the neural progenitor and microglial cell lines,

C17.2 and BV.2 respectively, have been characterised in mono-cultures and co-cultures.

To complement this data, transcriptional output of NF-κB in C17.2 was measured and

compared across culture conditions. The major findings of this investigation are as follows:

1) Mono-cultured and co-cultured C17.2 mostly displayed single nuclear p65

translocations, in response to TNFα;

2) BV.2 inhibited TNFα-induced p65 nuclear translocations in C17.2 (in 1:1 co-cultures);

3) BV.2 and RAW267.4 both inhibited TNFα-stimulated NF-luc induction in 1:4 co-

cultured C17.2: the effect of BV.2 cells was independent of cell-contact;

4) Basal NF-luc expression was induced by BV.2 cells in C17.2, in a cell-contact-

dependent manner (in 1:4 and 1:8 BV.2 co-cultures);

5) Mono-cultured and co-cultured BV.2 exhibited oscillatory p65 dynamics, in response to

TNFα.

6) Co-cultured BV.2 displayed later initial nuclear p65 peaks and faster oscillatory p65

dynamics, compared to mono-cultured cells (in 1:1 co-cultures).

The dynamics of p65 in C17.2 and BV.2 cultures will be compared to previous

observations in other cell lines. Co-culture findings will be used to formulate new

hypotheses on the mechanisms of paracrine interactions between C17.2 and BV.2 and,

thereby, NPCs and microglia.


127

4.3.1. NF-κB in Mono-cultured and Co-cultured C17.2

4.3.1.1. TNFα-induced Single-cell p65 Dynamics in C17.2, in Mono-cultures and 1:1

BV.2 Co-cultures

In contrast to most cell lines, which show oscillatory p65 dynamics in response to TNFα,

C17.2 cells displayed a single nuclear translocation of p65 (Ashall et al, 2009; Turner et al,

2010). Some of these cells exhibited sustained and fluctuating nuclear p65 presence. Co-

cultured C17.2 exhibited, on average, lower amplitude initial p65 nuclear translocations

and a more transient nuclear p65 presence (Figures 4.2-4.3).

TNFα availability was initially investigated as a possible explanation for the differences

observed across co-cultures conditions: TNFα ELISA results showed no difference in

TNFα availability between mono-cultures and co-cultures (see Figure 4.19). Next, TNFα-

stimulated TNFR1 expression was measured in mono-cultured and co-cultured C17.2:

TNFR1 signalling dominantly drives the response to soluble TNFα (Grell et al, 1998).

TNFR1 expression analysis concluded with no significant differences being observed

across culture conditions (see Figures 4.20-4.21).

An important point to note is that differences in TNFR1 expression in a few C17.2 cells

may have been masked in the population-level analysis conducted here. To improve on this

analysis, future experiments should focus on TNFR1 expression in 1:4 co-cultured C17.2,

where differences in TNFR1 may be more pronounced. Alternatively, TNFR1 expression

could be observed on a single-cell level, ideally in live cells so that TNFR1 expression can

be directly correlated with p65 dynamics. The potential involvement of other factors, such

as TNFR2 and non-TNFα related signals, is discussed in the following section.

4.3.1.2. Population-level NF-luc Induction in C17.2, in Mono-cultures and Co-cultures

To investigate differences observed in the single-cell C17.2 p65 response to TNFα, NF-luc

induction was characterised in co-cultured C17.2. NF-luc transfected C17.2 cells were

cultured with BV.2 in 1:2, 1:4 and 1:8 (C17.2:BV.2) co-cultures. It was thought that

increasing the co-culture ratio would enhance the inhibition of TNFα-induced p65 nuclear

translocations in C17.2. This inhibition would be represented by decreases in C17.2 NF-luc

induction. C17.2 in 1:4 BV.2 co-cultures displayed lower peak NF-luc induction levels,

compared to mono-cultured cells. C17.2 in 1:4 RAW267.4 co-cultures also displayed the

same dampened induction levels, indicating that inhibition of C17.2 NF-luc induction is a

trait that is shared by BV.2 and RAW267.4.


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Interestingly, BV.2 did not exert an inhibitory effect on C17.2 NF-luc induction in 1:2 or

1:8 (C17.2:BV.2) co-cultures. Basal C17.2 NF-luc expression was higher in 1:4 BV.2, 1:8

BV.2 and 1:4 RAW267.4 co-cultures: this effect was cell-contact dependent in BV.2 co-

cultures. On the other hand, inhibition of TNFα-stimulated NF-luc induction was

independent of cell-contact. Co-culture effects will now be discussed in two parts: 1) cell-

contact-dependent factors which may be involved in basal NF-luc induction and; 2) soluble

factors that may contribute to inhibition of TNFα-driven NF-luc induction and nuclear p65

translocations.

TNFR1 expression was ruled out as a player in co-culture effects; this leaves the possibility

of TNFR2 involvement in cell-contact dependent effects. Compared to TNFR1, TNFR2

has a low affinity for soluble TNFα. Instead, TNFR2 is preferentially activated by the

transmembrane form of TNFα (mTNFα; Grell et al, 1998), which is expressed on

microglia (Zhou et al, 2010). Cell-contact dependent increases in basal NF-luc expression

may have been due to interactions between C17.2 TNFR2 and BV.2 mTNFα. This would

be an interesting area to study in the future, as mTNFα can also act as a receptor and

reverse signal to cells (Xin et al, 2006).

Paracrine or cell contact-dependent interactions between microglia and NPCs are largely

unknown. However, Liu et al (2013) found a role for CD200 in mediating NPC-microglial

interactions. CD200 is a cell-surface ligand, expressed throughout the cerebellum, the same

area from which the C17.2 cell line originates (Ryder et al, 1990). The receptor for CD200

(CD200R) is expressed on microglia (Liu et al, 2013a) and can signal to induce IL-4 and

IL-10 expression (Gorczynski, 2001), as well as inhibit classical activation of microglia

(Broderick et al, 2002). CD200 and CD200R expression is reportedly upregulated in co-

cultured NPCs and microglia, respectively (Liu et al, 2013a).

As CD200 expression is NF-κB-dependent (Pahl, 1999), it could be hypothesised that

C17.2 expression of CD200, induced by TNFα, interacts with CD200R on BV.2 cells in

co-culture. This may cause the induction of IL-4 and/or IL-10 expression, which feeds

back into the C17.2 NF-κB signalling pathway and inhibits p65 nuclear translocations.

However, this explanation does not account for inhibition of C17.2 NF-luc induction, seen

in transwell co-cultures (Figure 4.11); considering the network complexity, it is likely that

multiple different mechanisms are converging to produce the co-culture effects observed.


129

4.3.2. Single-cell p65 Dynamics in Mono-cultured and Co-cultured BV.2

Consistent with observations in other cell lines, 93% and 100% of mono-cultured and co-

cultured BV.2 cells, respectively, exhibited oscillatory p65 dynamics in response to TNFα.

Co-cultured BV.2 displayed faster oscillations on average (63 min versus 108 min

observed in mono-cultured BV.2).

Reverse signalling is largely uninvestigated in microglia, but it may be play a role in the

effects of C17.2 on BV.2 p65 dynamics. Reverse signalling has been shown to influence

the expression of important inflammatory genes, such as IL-2, IL-6, IL-10 and TNFα (Xin

et al, 2006). It is thought that TNFR1 may be cleaved in response to TNFα stimulation to

produce soluble TNFR1 (Wajant et al, 2003). Activation of mTNFα, using soluble TNFR1,

enhances later soluble-TNFα driven IκBα degradation in a human lymphocytic cell line

(Xin et al, 2006). Using this data, it could be hypothesised that C17.2-derived soluble

TNFR1 abrogates the influence of inhibitory agents in the culture media and modifies

BV.2 NF-κB activity. The effects of C17.2-BV.2 contact can be investigated in future

experiments with the use of NF-luc transduced BV.2 cells.


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5. Analysis of Co-culture- and

TNFα-induced Gene Expression

Changes


131

5.1 General Introduction

The main aim of this work was to better understand the role of neural progenitor cell-

microglial cross-talk in neuroinflammation. On the molecular level, NF-κB-mediated

interactions were observed in C17.2 and BV.2 reporter cell lines, after TNFα stimulation in

1:1 co-cultures. Notably, co-cultured C17.2 cells displayed dampened κB-driven

transcription activity and lower amplitude nuclear p65 translocations, compared to mono-

cultured cells. Also, there was preliminary evidence of C17.2-driven changes in TNFα-

induced BV.2 p65 dynamics.

Having established co-culture effects on TNFα-induced NF-κB dynamics, the next goal of

this work was to investigate downstream TNFα-induced changes in gene expression

profiles. This work was conducted with a particular focus on associating differential NF-

κB dynamics with distinct gene expression profiles. In order to simultaneously quantify the

expression of hundreds of immune genes, NanoStringTechnology was utilised (Geiss et al,

2008). This involves a multiplexed probe library that contains two-sequence specific

probes for each target RNA molecule: a capture probe and a reporter probe. The capture

probes also contains a common sequence bound to an affinity tag e.g. biotin, and the

reporter probe is coupled to a colour-coded tag. Probe hybridization to target RNA

sequences results in a tripartite structure, which can be purified using the affinity tag in the

capture probe and the appropriate capture reagent e.g. streptavidin. Colour-coded tags on

the capture probe enable identification and absolute quantification of target RNA

sequences (Geiss et al, 2008).

The nCounter Mouse Inflammation Kit v1 was selected to assess mRNA expression of 185

inflammatory genes, including transcription factors, chemokines and pro- and anti-

inflammatory cytokines.

RNA from untreated and TNFα-stimulated cultures could be analyzed to see how gene

expression in mono-cultures and 1:1 co-cultures was affected by TNFα. Transwell inserts

would create a physical barrier between cell types, in order to observe the effects of

paracrine factors on gene expression changes. Comparison of mono-cultures with transwell

co-cultures would potentially identify gene expression changes driven by C17.2-BV.2

interactions.

This chapter describes gene expression changes at two different time points after TNFα-

stimulation: 230 min and 24 h. The 24 h time point was selected for analysis to observe


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long-term effects of TNFα stimulation on gene expression. The 230 min time point was

selected for two reasons. Firstly, previous and current members of the Prof. White

laboratory group have constructed a comprehensive microarray database of TNFα-induced

gene expression in SK-N-AS cells, using a range of time points (unpublished data): this

data shows that the 230 min time point is optimum for observing TNFα-induced gene

expression changes in early, middle and late responding genes (Dr. W. Rowe, personal

communication).

Secondly, the suitability of this time point was established by results shown in Chapter 4:

p65 localisation within mono-cultured C17.2 was different to that of co-cultured C17.2,

after TNFα-stimulation (Figure 4.2). More specifically, TNFα-induced p65 dynamics were

inhibited, between 0 and 230 min after stimulation, in co-cultured C17.2 (compared to

mono-cultured C17.2). Moreover, some C17.2 cells in mono-cultures exhibited nuclear

p65 localisation at 230 min post-stimulation, whereas nuclear p65 in co-cultured C17.2 had

returned to pre-stimulation levels before this time point. These findings strongly suggested

that different NF-κB-dependent gene expression profiles would be obtained from mono-

cultured and co-cultured C17.2 cells at 230 min post-TNFα stimulation.

In summary, this chapter contains a preliminary analysis of TNFα- and co-culture-induced

gene expression changes, in C17.2 and BV.2 mono-cultures and 1:1 co-cultures, with and

without transwells; NF-κB-dependent genes are the focus of this analysis.

5.2 Results

Cells were seeded in mono-cultures and 1:1 co-cultures, with and without transwells i.e.

BV.2 cells were seeded with transwell inserts containing C17.2 cells and, conversely,

C17.2 cells were seeded with transwells containing BV.2: these cultures are referred to as

‘BV.2 transwell co-cultures’ and ‘C17.2 transwell co-cultures’, respectively. These

transwell co-cultures prevented contact between C17.2 and BV.2, but allowed paracrine

communication via permeable transwell membranes. Contact between C17.2 and BV.2

was permitted in 1:1 co-cultures that were seeded without transwells.

The day after seeding, these cultures were left untreated or stimulated with 20ng/ml TNFα.

At the appropriate time point (i.e. 230 min or 24 h after stimulation), RNA was extracted

from all cultures: in transwell co-cultures, RNA was extracted from the cell type that was


133

seeded directly into wells (and not the cell type seeded into transwells). Each experiment

was performed in duplicate or triplicate.

For each condition, 125ng of extracted RNA was analysed for mRNA expression level

using NanoString Technology. Gene expression was normalised to internal house-keeping

genes and positive controls. The resulting expression levels were corrected by subtracting

negative controls, after which data across replicates was averaged. All data presented in

this chapter was derived from these average values.

It should be noted that some genes were not highly expressed so subtraction by negative

control values resulted in gene expression values below one. These values were all

corrected to one, in order to enable ease of analysis.

5.2.1. Gene Expression in Untreated C17.2 and BV.2 Mono-cultures

Throughout this chapter, fold differences are calculated between different sets of averages:

statistical analysis was not conducted, due to the low number of replicates. A fold

threshold of 2 was selected as a filter to account for natural variability in gene expression

and, thereby, avoid false positive results.

For example, say C17.2 average expression of gene A was 2 in unstimulated mono-

cultures and 10, after 230 min TNFα-stimulation. This would equate to a fold change of 5

(i.e. 10/2); therefore, gene A would be of interest here. However, differences in gene

expression levels between C17.2 and BV.2 may mask upregulation of gene A in co-culture.

Following the previous example, if BV.2 average expression of gene A was 2000, then

unstimulated 1:1 co-culture gene A expression would be 1001 (i.e. (2000 + 2)/2). In these

co-cultures, a 5-fold upregulation of gene A in C17.2 cells would lead to an average co-

culture expression of 1006 (i.e. 1001 + (1*5)): this would equate to a fold change of 1.005,

leading to gene A being discounted as a gene of interest.

To ensure awareness of potential false negatives in this analysis, a comparison of

expression levels was performed between C17.2 and BV.2 in unstimulated mono-cultures.

The average expression levels of genes were plotted, with C17.2 expression level along the

x-axis and BV.2 expression level along the y-axis (Figure 5.1).

Figure 5.1 shows differences in gene expression between C17.2 and BV.2, which may

result in false negative results. More specifically, some genes that were highly expressed in


134

BV.2 mono-cultures were expressed at low levels in C17.2 cultures. This disadvantage is

noted here and improvement on future techniques is discussed later.

F ig u r e 5 .1 . A c o m p a r is o n o f g e n e e x p r e s s io n in u n s t im u la te d

C 1 7 .2 a n d B V .2 m o n o -c u ltu r e s .

R N A w a s e x t ra c te d f ro m u n s tim u la te d C 1 7 .2 a n d B V .2 c e l ls .

S a m p le s w e re a n a ly s e d fo r th e m R N A le v e l o f 1 8 5 g e n e s .

E x p e rim e n ts w e re p e r fo rm e d in d u p lic a te o r tr ip lic a te a n d a v e ra g e

m R N A le v e ls a re d is p la y e d h e re (o n a lo g a ri th m ic s c a le ) . E a c h

g e n e is re p re s e n te d b y a s in g le p o in t .

100

101

102

103

104

105

106

100

101

102

103

104

105

106

mR

NA

coun

t in

BV

.2

mRNA count in C17.2

5.2.2. TNFα-induced Changes in Gene Expression at 230 min Post-TNFα-Stimulation

A major goal of this chapter was to observe changes in gene expression, induced by 230

min TNFα-stimulation, in C17.2 and BV.2 mono-cultures and 1:1 co-cultures. To do this,

fold differences in average expression of each gene was calculated between untreated

cultures and TNFα-treated cultures: TNFα-induced upregulation of a gene would result in a

positive fold change, whereas downregulation would produce a negative fold change. A

fold threshold of two was selected to filter out any false positive results. Genes that

exhibited a fold change ≥2 or ≤-2 are displayed in Figure 5.2A, and the corresponding fold

changes are displayed in Figure 5.2B.


135

C 1 q b

C s f1

Il2 3 r

R ip k 2

C d 4 0

Il1a

Il1b

T n f

C x c l1 0

T lr2

B V .2C 1 7 .2

C o -c u ltu r e

F ig u r e 5 .2 . G e n e s u p r e g u la te d /d o w n r e g u la te d , a t 2 3 0 m in p o s t -2 0 n g /m l

T N F -s t im u la t io n , in C 1 7 .2 a n d B V .2 m o n o -c u ltu r e s a n d 1 :1 c o -c u ltu r e s .

R N A w a s e x t ra c te d f ro m C 1 7 .2 a n d B V .2 m o n o -c u ltu re s a n d 1 :1 c o -c u l tu re s , a t

2 3 0 m in p o s t-2 0 n g /m l T N F s t im u la tio n . E a c h e x p e rim e n t w a s p e rfo rm e d in

d u p lic a te o r tr ip lic a te a n d m R N A le v e ls w e re d e te c te d u s in g N a n o S tr in g

te c h n o lo g y . F o ld d i ffe re n c e s in m R N A e x p re s s io n b e tw e e n u n s tim u la te d a n d

T N F -s t im u la te d c u l tu re s w a s c a lc u la te d . (A ) G e n e s in d u c e d b y a fo ld c h a n g e

o f 2 o r -2 (g e n e s in b lu e a n d re d w e re d o w n re g u la te d a n d u p re g u la te d ,

re s p e c tiv e ly ) . (B ) F o ld c h a n g e s o f m R N A le v e ls o f g e n e s in A .

C17.2 BV.2 Co-culture

C1qb -4.1

Ccl2 6.9 2.8

Ccl5 70.0 18.8

Ccl7 4.7 2.5

Cd40 3.3 3.8

Csf1 2.3

Cxcl1 8.1 3.8

Cxcl10 47.5 17.4 12.3

Il1a 2.0 2.6

Il1b 2.1 3.8

Il23r -2.3

Ripk2 2.2

Tlr2 4.1 2.7 3.1

Tnf 2.3 2.6

B

A

C c l2

C c l5

C c l7

C x c l1


136

Figure 5.2A shows that C1qb, Csf1, Il23r and Ripk2 genes were differentially regulated by

TNFα in C17.2 mono-cultures and not in 1:1 co-cultures. Moreover, Ripk2 is an NF-κB-

dependent signalling molecule in the canonical NF-κB activation pathway (Matsuda et al,

2003; Devin et al, 2000). Together, this suggests that Ripk2 upregulation may be

dependent on aspects of p65 dynamics that were only observed in mono-cultured C17.2

cells. Alternatively, given the low fold change (2.2), it is likely that C17.2 upregulation of

Ripk2 was masked in 1:1 co-cultures.

BV.2 cells upregulated the expression of pro-inflammatory factors and, notably, NF-κB

activators (e.g. Cd40, Il1a, Il1b and Tnf; Pahl, 1999). All genes that were differentially

regulated by TNFα in co-cultures were also similarly altered in one or both mono-cultures

e.g. Ccl5 was upregulated in 1:1 co-cultures and also C17.2 mono-cultures, suggesting that

Ccl5 upregulation in co-cultures can be attributed to C17.2 cells.

5.2.3. TNFα and Co-culture-induced Gene Expression Changes at 230 min Post-TNFα

Stimulation

Having established TNFα-dependent gene expression changes, the combined effects of

TNFα and paracrine interactions were investigated using transwell co-cultures. C17.2 and

BV.2 cells were seeded with BV.2 and C17.2 cells in transwell inserts, respectively (at a

1:1 ratio). RNA was extracted, 230 min after TNFα-stimulation, from one cell population

in these transwell co-cultures i.e. RNA from C17.2 cells in transwell co-cultures is referred

to as ‘C17.2 transwell co-cultures’. Average fold changes in gene expression were

calculated between untreated and TNFα-treated transwell co-cultures: results are displayed

in Figure 5.3, along with genes that were differentially regulated by TNFα in contact-

permissive 1:1 co-cultures.

Comparison of Figures 5.2 and 5.3 shows evidence of TNFα- and co-culture-dependent

gene expression changes. For example, Ccl17 is upregulated in TNFα-treated C17.2

transwell co-cultures but not in C17.2 mono-cultures. Therefore, Ccl17 upregulation is

dependent on TNFα-induced paracrine interactions with BV.2.

Interestingly, TNFα-induced Il1a upregulation was seen in BV.2 mono-cultures, but not in

BV.2 transwell co-cultures: this suggests that C17.2 can mediate inhibition of BV.2 pro-

inflammatory gene expression (discussed later in this chapter).


137

C c l1 7

C s f1

Il2 3 r

M a p 2 k 6

R ip k 2

Il15

Il8 rb

Il1a

T n f

C d 4 0

Il1b

C c l2

C c l5

C c l7

C x c l1

C x c l1 0

T lr2

B V .2

T r a n s w e ll

C 1 7 .2

T r a n s w e ll

C o -c u ltu r e

A


Ccl17 29.9

Ccl2 7.2 2.8

Ccl5 89.6 18.8

Ccl7 4.0 2.5

Cd40 2.6 3.8

Csf1 2.3

Cxcl1 7.1 3.8

Cxcl10 28.8 86.3 12.3

Il15 -2.1

Il1a 2.6

Il1b 2.3 3.8

Il23r -3.0

Il8rb -2.7

Map2k6 -1.9

Ripk2 2.3

Tlr2 3.8 3.2 3.1

Tnf 2.3 2.6

B

F ig u r e 5 .3 . G e n e s u p r e g u la te d /d o w n r e g u la te d a t 2 3 0 m in p o s t-2 0 n g /m l

T N F -s t im u la t io n , in tr a n s w e l l c o -c u ltu r e s a n d 1 :1 c o n ta c t-p e r m is s iv e

c o -c u ltu r e s .

C 1 7 .2 a n d B V .2 c e l ls w e re s e e d e d w i th tra n s w e ll in s e r ts c o n ta in in g B V .2 a n d

C 1 7 .2 c e lls , re s p e c tiv e ly . C e lls w e re a ls o s e e d e d in 1 :1 c o n ta c t-p e rm is s iv e

c o -c u l tu re s . C u ltu re s w e re s t im u la te d w ith 2 0 n g /m l T N F a n d R N A w a s e x t ra c te d

2 3 0 m in a f te r s t im u la tio n . E a c h e x p e rim e n t w a s p e rfo rm e d in d u p lic a te a n d

m R N A le v e ls w e re d e te c te d u s in g N a n o S tr in g te c h n o lo g y . F o ld d iffe re n c e s in

m R N A e x p re s s io n b e tw e e n u n s tim u la te d a n d T N F -s t im u la te d c u ltu re s w a s

c a lc u la te d . (A ) G e n e s in d u c e d b y a fo ld c h a n g e o f 2 o r -2 (g e n e s in b lu e a n d

re d w e re d o w n re g u la te d a n d u p re g u la te d , re s p e c tiv e ly ) . (B ) F o ld c h a n g e s o f

m R N A le v e ls o f g e n e s in A .


138

5.2.4. Co-culture-induced Gene Expression Changes, 28 h after Co-culturing

The previous analysis performed highlighted gene expression changes that were dependent

on TNFα and co-culture-interactions (at 230 min post-TNFα-stimulation, which was

approximately 28 h after seeding cultures). To investigate gene expression changes that

were induced as a result of co-culturing cells, fold differences in gene expression were

calculated between untreated mono-cultures and corresponding transwell co-cultures. For

example, untreated gene expression in C17.2 mono-cultures was compared to that of

untreated C17.2 transwell co-cultures: this would highlight genes that were differentially

regulated by paracrine interactions with BV.2. Accordingly, the same analysis was

conducted with untreated BV.2 mono-cultures and transwell co-cultures.

This analysis highlighted 3 genes that were differentially regulated by paracrine

interactions between C17.2 and BV.2: C1qb, Il15 and Tlr3. C1qb was inhibited by 39.6

fold in untreated C17.2 transwell co-cultures, compared to untreated C17.2 mono-cultures.

In untreated BV.2 transwell co-cultures, Il15 was upregulated and Tlr3 was inhibited,

compared to the corresponding mono-cultures. It should be noted that the fold changes of

Il15 and Tlr3 expression were close to the 2-fold threshold set for filtering out false

positives: these results are therefore less reliable than the results obtained on C1qb.

5.2.5. TNFα-induced Changes in Gene Expression at 24 h Post-TNFα-Stimulation

To assess long-term effects of TNFα treatment on cells, RNA samples were extracted after

24 h 20ng/ml TNFα-stimulation. As with gene expression data from 230 min RNA

samples, TNFα-induced gene expression changes were analysed: average gene expression

in untreated cultures was compared to that of the corresponding TNFα-stimulated cultures.

Again, genes that exhibited a fold change ≥2 or ≤-2 are displayed in Figure 5.4A, and the

corresponding fold changes are displayed in Figure 5.4B.

The gene set displayed in Figure 5.4 is dominated by chemokines, such as Ccl2, Ccl5 and

Ccl7, as well as NF-κB dependent genes and NF-κB activators e.g. Nos2, Il1a, Il1b and

Tnf (Pahl, 1999).

Il1a, Il1b and Tnf were upregulated in BV.2 mono-cultures, and not in C17.2 mono-

cultures, which suggests that BV.2 were also responsible for the upregulation of these

genes in 1:1 co-cultures. Moreover, upregulation of Il1a, Il1b and Tnf genes was observed

in the same culture conditions at 230 min post-TNFα stimulation (see Figure 5.2A): this is


139

consistent with the role of microglia in propagating neuroinflammatory signals (Nakajima

and Kohsaka, 2001; Henn et al, 2009).

F o s

M yc

R a p g e f2

Il23a

Il8 rb

N o s 2

Il1a

Il1b

T n f

C c l2

C c l7

C x c l1

C 1 s

C 3

C c l5

C d 4 0

C x c l1 0

T lr2

B V .2C 1 7 .2

C o -c u ltu r e


C1s 2.5 49.3 2.5

C3 40.4 5.4 5.3

Ccl2 4.5 2.8

Ccl5 453.6 14.9 10.0

Ccl7 3.4 2.3

Cd40 11.5 2.9 2.6

Cxcl1 4.0 4.7

Cxcl10 10.3 8.7 5.1

Fos -2.1

Il1a 8.0 4.3

Il1b 5.8 3.8

Il23a 2.0

Il8rb -2.4

Myc 2.7

Nos2 4.0

Rapgef2 2.0

Tlr2 2.8 3.0 3.0

Tnf 2.2 2.4

B

A

F ig u r e 5 .4 . G e n e s u p r e g u la te d /d o w n r e g u la te d , a t 2 4 h p o s t -2 0 n g /m l

T N F -s t im u la t io n , in C 1 7 .2 a n d B V .2 m o n o -c u ltu r e s a n d 1 :1 c o -c u ltu r e s .

R N A w a s e x t ra c te d f ro m C 1 7 .2 a n d B V .2 m o n o -c u ltu re s a n d 1 :1 c o -c u l tu re s , a t

2 4 h p o s t -2 0 n g /m l T N F s t im u la tio n . E a c h e x p e rim e n t w a s p e rfo rm e d in

d u p lic a te o r tr ip lic a te a n d m R N A le v e ls w e re d e te c te d u s in g N a n o S tr in g

te c h n o lo g y . F o ld d i ffe re n c e s in m R N A e x p re s s io n b e tw e e n u n s tim u la te d a n d

T N F -s t im u la te d c u l tu re s w a s c a lc u la te d . (A ) G e n e s in d u c e d b y a fo ld c h a n g e

o f 2 o r -2 (g e n e s in b lu e a n d re d w e re d o w n re g u la te d a n d u p re g u la te d ,

re s p e c tiv e ly ) . (B ) F o ld c h a n g e s o f m R N A le v e ls o f g e n e s in A .


140

More genes were differentially regulated by TNFα in BV.2 mono-cultures and 1:1 co-

cultures at 24 h- than at 230 min-post-TNFα stimulation (compare Figures 5.2A and 5.4A).

Together, this suggests that TNFα-stimulation has a persistent and ongoing effect on BV.2

gene expression. In contrast, the same number of genes were differentially regulated in

C17.2 mono-cultures at both time points.

Another similarity between results from 230 min and 24 h post TNFα-stimulation was in

the regulation of Ccl5: this gene was more strongly upregulated than other genes at both

time points, primarily by C17.2 cells. Ccl5 is an NF-κB dependent gene, involved in

attracting immune cells to sites of inflammation (Wickremasinghe et al, 2004).

5.2.6. TNFα and Co-culture-induced Gene Expression Changes at 24 h Post-TNFα-

Stimulation

Analysis of TNFα- and co-culture- induced gene expression changes were conducted using

C17.2 transwell, BV.2 transwell and 1:1 contact-permissive co-cultures: fold changes in

gene expression were calculated between untreated cultures and corresponding TNFα-

stimulated cultures. Genes that exhibited a fold change ≥2 or ≤-2, after 24 h TNFα-

treatment, are displayed in Figure 5.5A, and the corresponding fold changes are displayed

in Figure 5.5B.

C17.2 transwell co-cultures and mono-cultures both downregulated Fos expression after

TNFα-stimulation (Figures 5.4A and 5.5A), whereas Il15 and Tlr1 were differentially

regulated only in C17.2 transwell co-cultures. Cd40 upregulation, observed in C17.2

mono-cultures, was prevented in C17.2 transwell co-cultures. Together, this provides

strong evidence for TNFα- and paracrine interaction-dependent changes in C17.2 gene

expression.

BV.2 cells also displayed co-culture- and TNFα-induced changes in gene expression: Nos2

was upregulated in BV.2 transwell co-cultures, and not in mono-cultured cells, after TNFα-

stimulation. Therefore, C17.2- BV.2 interactions are bidirectional and result in differential

gene regulation by both cell types, after TNFα-stimulation.


141

F o s

Il15

T lr1

C c l2 4

Il23a

C 1 s

C d 4 0

Il1a

Il1b

N o s 2

T n f

Il8 rb

C c l2

C c l5

C c l7

C x c l1

C 3

C x c l1 0

T lr2

B V .2

T r a n s w e ll

C 1 7 .2

T r a n s w e ll

C o -c u ltu r e


C1s 60.1 2.5

C3 45.2 5.3 5.3

Ccl2 5.8 2.8

Ccl24 -2.1

Ccl5 104.9 10.0

Ccl7 4.4 2.3

Cd40 2.3 2.6

Cxcl1 5.9 4.7

Cxcl10 12.4 9.1 5.1

Fos -2.3

Il15 2.5

Il1a 5.5 4.3

Il1b 4.5 3.8

Il23a 2.0

Il8rb -2.2 -2.4

Nos2 3.3 4.0

Tlr1 -2.3

Tlr2 2.5 3.5 3.0

Tnf 2.5 2.4

B

A

F ig u r e 5 .5 . G e n e s u p r e g u la te d /d o w n r e g u la te d a t 2 4 h p o s t-2 0 n g /m l

T N F -s t im u la t io n , in tr a n s w e l l c o -c u ltu r e s a n d 1 :1 c o n ta c t-p e r m is s iv e

c o -c u ltu r e s .

C 1 7 .2 a n d B V .2 c e lls w e re s e e d e d w ith tra n s w e ll in s e r ts c o n ta in in g B V .2 a n d C 1 7 .2

c e lls , re s p e c tiv e ly . C e lls w e re a ls o s e e d e d in 1 :1 c o n ta c t -p e rm is s iv e c o -c u ltu re s .

C u ltu re s w e re s t im u la te d w ith 2 0 n g /m l T N F a n d R N A w a s e x t ra c te d 2 4 h a f te r

s t im u la tio n . E a c h e x p e rim e n t w a s p e rfo rm e d in d u p lic a te a n d m R N A le v e ls w e re

d e te c te d u s in g N a n o S tr in g te c h n o lo g y . F o ld d iffe re n c e s in m R N A e x p re s s io n b e tw e e n

u n s tim u la te d a n d T N F -s t im u la te d c u ltu re s w a s c a lc u la te d . (A ) G e n e s in d u c e d b y a

fo ld c h a n g e o f 2 o r -2 (g e n e s in b lu e a n d re d w e re d o w n re g u la te d a n d

u p re g u la te d , re s p e c t iv e ly ) . (B ) F o ld c h a n g e s o f m R N A le v e ls o f g e n e s in A .


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5.2.7. Co-culture-induced Gene Expression Changes, 48 h after Co-culturing

Previous analysis performed highlighted differences in gene expression between untreated

mono-cultures and the corresponding untreated transwell cultures. This analysis was

conducted on RNA samples extracted from cells which had been growing in transwell co-

cultures for approximately 28 h. Here, we look at RNA samples that were extracted

approximately 48 h after co-cultures were seeded.

Fold differences were calculated between average gene expression in untreated mono-

cultures and the corresponding untreated transwell co-cultures e.g. gene expression in

untreated C17.2 mono-cultures was compared to that of untreated C17.2 transwell co-

cultures. The same analysis was conducted for BV.2 mono-cultures and transwell co-

cultures (results are shown in Table 5.1).

Table 5.1: Genes that were differentially expressed between mono-cultures and

transwell co-cultures. Fold differences in gene expression were calculated between

untreated C17.2/BV.2 mono-cultures and the corresponding transwell co-cultures (after

co-culturing for 48 h).

C17.2 BV.2

C3 -2.6

Ccr1 3.9

Creb1 -2.3

Fos 2.6

Hras1 -34.5

Il1b 3.2

Il1r1 7.5

Il8rb 2.3

Myc 2.4

Nos2 7.3 36.3

Ppp1r12b -2.3

Fos expression was higher in C17.2 transwell co-cultures than C17.2 mono-cultures. Fos

upregulation has been related to increases in Cyclin D1, D2 and D3, resulting in NPC

proliferation (Adepoju et al, 2014). Also, Myc was upregulated in BV.2 transwell cultures:

the transcription factor, Myc, is responsible for controlling the expression of proliferation

genes (Bretones et al, 2014). This suggests that paracrine interactions between C17.2 and

BV.2 may mediate changes in the proliferation profile of these cells.

In summary, many inflammatory genes were differentially regulated according to

treatment, time, and co-culture interactions between C17.2 and BV.2 cells. In particular,


143

many NF-κB dependent genes and activators were highlighted by the analysis conducted

here: these include Tnf, Il1a, Il1b, Ccl5 and Nos 2 (Pahl, 1999). To assess NF-κB

contribution to gene regulation in these analyses, Table 5.2 was compiled to show a list of

the NF-κB-dependent genes that were differentially regulated (seen in Figures 5.2-5.5).

Table 5.2: A collated list of NF-κB-dependent genes that were differentially

regulated, at different time points, by TNFα or co-culture interactions in: C17.2 or

BV.2 mono-cultures, transwell co-cultures or 1:1 contact-permissive co-cultures

(seen in Figures 5.2-5.5). (Reference: http://www.bu.edu/NF-κB/gene-resources/target-

genes/, visited on 24/09/14).

Gene Time point

C3 24 h

Ccl2 230 min and 24 h

Ccl5 230 min and 24 h

Ccl17 230 min

Cxcl1 230 min and 24 h

Cxcl10 230 min and 24 h

Cd40 230 min and 24 h

Csf1 230 min

Fos 24 h

Il1a 230 min and 24 h

Il1b 230 min and 24 h

Il15 230 min and 24 h

Il23a 24 h

Myc 24 h

Nos 24 h

Ripk2 230 min

Tlr-2 230 min and 24 h

Tnf 230 min and 24 h

As can be seen in Table 5.2, many NF-κB-dependent genes were differentially regulated at

230 min and 24 h after TNFα-stimulation (Figures 5.2-5.5), as well as in untreated

transwell co-cultures (compared to mono-cultures; Table 5.1). Together, these results

suggest that NF-κB plays an important role in TNFα- and co-culture induced gene

expression changes in C17.2 and BV.2: these results require further investigation in the

future.

5.3 Discussion

In this chapter, NanoString technology was used to analyse the expression of 185

inflammatory genes in different C17.2 and BV.2 cultures. As this was a preliminary


144

screening, findings will be discussed only briefly. The goal of this discussion will be to

generate hypotheses on NF-κB-mediated interactions in co-cultures and, via a critique of

the methods used in this chapter, design future experiments to test new hypotheses.

5.3.1. Potential NF-κB-mediated Interactions between C17.2 and BV.2

Analysis of gene expression highlighted differential gene regulation by TNFα in C17.2 and

BV.2 mono-cultures and 1:1 co-cultures, as well as transwell co-cultures. BV.2 cells

consistently upregulated the expression of proinflammatory cytokines. This finding is

supported by data in the literature which reports microglial upregulation of pro-

inflammatory cytokines, in response to inflammatory stimuli (Guadagno et al, 2013;

Colton, 2009; Saijo and Glass, 2011).

More specifically, BV.2 consistently upregulated the expression of NF-κB-dependent pro-

inflammatory cytokines, Il1a, Il1b and Tnf, after TNFα treatment (Pahl, 1999). These

genes can be used as markers for microglial classical activation (Colton, 1999; Saijo and

Glass, 2011). Interestingly, C17.2 cells in transwell inserts prevented BV.2 upregulation of

Il1a at 230 min post-TNFα-stimulation; this effect was not reproduced in contact-

permissive 1:1 co-cultures (see Figures 5.2 and 5.3). Together, this suggests cell-contact-

dependent or juxtacrine regulation of IL-1 expression in BV.2.

Upstream of IL-1 expression, these results could relate to differences in BV.2 p65

dynamics (reported in Chapter 4; Figure 4.15). TNFα stimulation induced p65 oscillations

in both mono-cultured and co-cultured BV.2 cells, however, the average period of these

oscillations differed between culture conditions (108 min versus 63 min, respectively). As

Il1a expression is a marker of classical activation, this suggests that differential p65

dynamics determines microglial activation status. From this, it could be hypothesised that

C17.2 inhibits BV.2 activation by modulating BV.2 p65 dynamics. This hypothesis

contradicts findings that report NPC-driven microglial classical activation (Mosher et al,

2012).

However, microglial activation status is not discrete and, therefore, the use of one or two

markers of activation is not sufficient for determining microglial behaviour. Moreover,

Nos2 expression was upregulated after 24 h TNFα-stimulation in BV.2 transwells, and not

in BV.2 mono-cultures. This finding suggests that C17.2 promote BV.2 classical

activation. These seemingly contradictory findings draw attention to one of the advantages


145

of NanoString Technology: the simultaneously quantification of hundreds of mRNA

molecules. Use of this technology in the future will shed more light on the spectrum of

microglial activation status and, therefore, their effects in neuroinflammatory tissue.

As well as C17.2 effects on BV.2, NanoString analysis conducted in this chapter provided

evidence of bidirectional paracrine interactions. An example of this was differential

regulation of Cd40 in C17.2 cultures: Cd40 was upregulated in C17.2 mono-cultures (11.5

fold), after 24 h TNFα-stimulation. This upregulation was prevented by BV.2 cells in

C17.2 transwell co-cultures. As Cd40 is an NF-κB activator (Hayden and Ghosh, 2004;

Bonizzi and Karin, 2004), these results may relate to differences in C17.2 p65 dynamics

that were reported in Chapter 4 (Figure 4.2). In response to TNFα-stimulation, p65 in

mono-cultured C17.2 displayed a rapid, high amplitude nuclear translocation, followed by

some irregular nuclear movements. Co-cultured C17.2, on the other hand, displayed an

inhibited p65 response to TNFα-stimulation. It could be conjectured that differential p65

dynamics led to the differences observed in Cd40 expression. However, single-cell

dynamics were observed from 0-300min after TNFα-stimulation and the effects reported

here were measured some time later, at 24 h post-stimulation. Also, microscopy

experiments were conducted with co-cultures that were seeded approximately 24 h before

stimulation, whereas the results obtained on Cd40 expression were derived from C17.2

cells that had been co-cultured with BV.2 for 48 h: data outlined in this chapter provides

evidence for time-dependent co-culture interactions. Moreover, C17.2-BV.2 cell-contact

was enabled in microscopy experiments and not in the transwell co-cultures described

here.

In summary, NanoString data outlined in this chapter has provided preliminary evidence

for TNFα- and co-culture-mediated interactions between C17.2 and BV.2 cells, albeit

inconclusive. More importantly, there is preliminary evidence to suggest that co-culture-

induced p65 dynamics (reported in Chapter 4), can contribute to differential gene

regulation in C17.2 and BV.2 cells.

The following section will critique the experimental design described in this chapter and

discuss more thorough experiments to be performed in the future.


146

5.3.2. Future Experiments

As well as measuring TNFα-induced gene expression, the goal of this chapter was to

observe differential gene expression that may be associated with differential p65 dynamics

in mono-cultures and co-cultures (described in Chapter 4). One of the main findings

described in Chapter 4 was the inhibition of C17.2 p65 dynamics in 1:1 contact-permissive

co-cultures, after TNFα-stimulation. Certain aspects of NF-κB dynamics can determine

downstream gene expression: IL-8, A20 and IκBα gene expression in single cells is

regulated by the amplitude of p65 nuclear translocations (Lee et al, 2014). Also, pulsatile

TNFα stimulation has been used to force p65 nuclear translocations, thereby modulating

NF-κB-dependent gene expression (Ashall et al, 2009). Therefore, it was hypothesised that

the differences in p65 dynamics observed in C17.2 cells might correspond to different NF-

κB-dependent gene expression profiles.

In order to investigate this thoroughly in the future, RNA extracts should be taken from co-

cultures that reproduce the conditions of the microscopy experiments performed (see

Chapter 4). This entails seeding cells at the same density, and co-culturing cells for the

same amount of time, before stimulating with TNFα. Most importantly though, 1:1

contact-permissive co-cultures should be used: transcriptional activity of NF-κB in C17.2

cells was higher in untreated contact-permissive co-cultures than in transwell co-cultures.

Differences in NF-κB activity may affect TNFα-induced gene expression changes.

A major disadvantage of the NanoString technology is the inability to separate different

cell populations in co-cultures, therefore this type of population-level analysis masks cell-

cell heterogeneity. Instead, gene expression observations on a single-cell level would allow

cell types to be distinguished in co-culture and also enable direct association of p65

dynamics with gene expression. A disadvantage to this method is that the expression of

only a few genes can be observed in parallel in single-cell experiments. Lee et al (2014)

observed TNFα expression only in fixed cells, which would not capture the dynamic nature

of single-cell gene expression.

Recently, a microfluidics procedure has been developed to obtain high-throughput data on

the expression of up to 96 genes and, in parallel, single-cell p65 dynamics (Kellogg et al,

2014). Multiple time points can be used with this technique to obtain more dynamic gene

expression data. This technique is not suited to allow direct correlation of single-cell p65

dynamics with gene expression but it might be informative in certain culture conditions.


147

Luminometry results in Chapter 4 (Figure 4.5) showed that BV.2 inhibition of κB-driven

transcription in C17.2 cells can be enhanced by increasing co-culture ratio i.e. 1:4 (C17.2:

BV.2), instead of the 1:1 co-cultures utilised in microscopy experiments. By enhancing co-

culture effects, NF-κB-dependent differential gene expression may be observable on a

population-level, therefore, 1:4 co-culture experiments could be conducted with

microfluidics in the future.


148

6. Effects of TNFα and NF-κB

Activity on Neural Progenitor Cells

and Microglia


149


Results in Chapter 4 detailed NF-κB-mediated interactions between C17.2 and BV.2.

Specifically, BV.2 cells inhibited TNFα-induced p65 nuclear translocations in C17.2 (lenti)

cells, in 1:1 co-cultures (C17.2:BV.2). On a population-level, in 1:4 co-cultures

(C17.2:BV.2), C17.2 cells displayed increased, and inhibited, basal and TNFα-induced

NF-κB transcriptional activity, respectively. Endpoint luminometry experiments with

transwells showed that basal NF-luc induction was dependent on physical contact between

C17.2 and BV.2 cells; TNFα-induced NF-luc inhibition occurred independent to this

contact.

Having established these differences in NF-κB activation and dynamics, gene expression

changes downstream of TNFα were investigated (Chapter 5). Expression of inflammatory

genes was measured in C17.2 (UT) and BV.2 (UT) mono-cultures and 1:1 co-cultures,

with and without transwells. The goal was to observe differential gene regulation that may

be a consequence of changes in TNFα-induced NF-κB dynamics. Without the use of an

NF-κB inhibitor in these experiments, it is difficult to attribute any gene expression

changes directly with NF-κB. However, evidence of NF-κB-mediated differential gene

regulation was reported: the expression of many NF-κB-dependent genes was altered in

C17.2 and BV.2 cells in different culture conditions (see Table 5.2).

Here, the outcome of differential NF-κB dynamics and TNFα-induced gene expression is

investigated in the context of cell fate decisions. The effects of TNFα on cell viability and

apoptosis is established with the use of MTS and caspase-3/7-associated assays,

respectively. To complement data detailed in previous chapters, assays were conducted

with mono-cultures and 1:1 co-cultures, and combined with the use of pyrrolidine

dithiocarbamate (PDTC; an NF-κB inhibitor).

In brief, the goals of this chapter are to assess TNFα effects on C17.2 and BV.2 mono-

cultures and 1:1 co-cultures, and investigate the role that NF-κB activity plays in exerting

these effects.


150

6.2. Results

6.2.1. Effects of TNFα on Cell Viability and Apoptosis

In order to observe potential TNFα-induced changes in cell viability, MTS assays were

performed with C17.2 and BV.2 cultures. These assays utilised a tetrazolium compound,

MTS (3-(4, 5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-

tetrazolium), which is reduced (depending on the cellular metabolic activity, due to

NAD(P)H flux) by cells into a formazan product. The absorbance of formazan, measured

at 490nm, is proportional to the number of living cells in culture. Experiments were

conducted using mono-cultures and 1:1 co-cultures, seeded at two different cell densities

(1000 or 3000 cells per cell-type). So, for example, lower cell density mono-cultures were

composed of either 1000 C17.2 or 1000 BV.2: co-cultures were composed of 1000 C17.2

and 1000 BV.2 cells. Apoptosis assays were conducted separately using caspase3/7-

associated luminescence reactions. These assays were carried out at the aforementioned

cell densities for comparability between datasets. For both viability and apoptosis assays,

cells were seeded in 100µl of either normal medium or 20ng/ml TNFα-medium.

Readings for viability/apoptosis were taken 24, 48 and 72 h after seeding. All experiments

were performed in triplicate on 96-well plates, with two and three technical replicates per

plate for viability and apoptosis assays, respectively. Viability graphs display averaged

data collated from the replicates. There was a large difference between the lowest and

highest apoptosis readings obtained; therefore, apoptosis data was normalised to data from

unstimulated groups at each time point.

Figures 6.1, 6.2 and 6.3 show the results of viability and apoptosis assays in C17.2 mono-

cultures, BV.2 mono-cultures and 1:1 co-cultures, respectively. Mann Whitney U tests

were performed on data to evaluate changes in viability/apoptosis. Significantly lower cell

viability was observed in all TNFα-treated C17.2 cultures, except at 72 h in the higher cell

density cultures (p-value≤0.05; Figures 6.1A and B). Accordingly, significant TNFα-

induced increases in apoptosis were seen at the same time points (p-value≤0.05; Figures

6.1C and D).

Viability and apoptosis readings were normalised to readings obtained at 24 h to measure

growth or apoptosis rates between 24 h and 72 h (Figures 6.1E and F). Culture growth and

apoptosis rates were assessed for significant differences using Kruskal-Wallis ANOVA


151

tests. This enabled discrimination between long-term effects of early TNFα-induced

apoptosis and ongoing apoptosis induction. Analysis revealed that between 24 and 72 h,

there were no significant differences in culture growth or apoptosis rates between

unstimulated and TNFα-treated groups. This suggests that later decreases in viability were

a long-term effect of apoptosis at 24 h and not an ongoing TNFα effect on cell viability.

However, more rapid increases in apoptosis levels were observed in TNFα-stimulated

groups, at both cell densities between 48 and 72 h (see Figures 6.1E and F; compare blue

and grey lines). Together, this suggests the possibility of TNFα-induced increases in

apoptosis between 48 and 72 h. Increases in proliferation rate could account for increases

in apoptosis, resulting in a culture that exhibits growth rates that are identical to

unstimulated cultures.

In contrast to C17.2 cultures, TNFα-induced decreases in BV.2 viability were observed

only at 72 h, at the higher cell density (p-value≤0.01; Figures 6.2A and B). Levels of

apoptosis in BV.2 cultures were unaffected by TNFα. This suggests that the significant

difference in viability may have been due to a confluency-dependent saturation of the MTS

signal or a difference in culture growth rate, between 48 and 72 h. No differences in

growth rates were highlighted by statistical analysis, although there is a marked reduction

between 48 and 72 h in TNFα-stimulated cultures (compare black and red lines in Figure

6.2F). These observations are mirrored in the viability and apoptosis results for co-cultures:

TNFα caused a decrease in viability at 72 h (p-value≤0.05; Figures 6.3B) that could be

attributed to a decrease in growth rate between 48 and 72 h (Figure 6.3F) or saturation of

the MTS signal.

Both cell types displayed cell density-dependent changes in growth rate between 24-48 h

and 48-72h. Comparison of C17.2 and BV.2 growth rates (seen in Figures 6.1E-F and

Figures 6.2E-F, respectively) revealed that BV.2 cultures grow at a faster rate than C17.2

cultures. In lower density unstimulated cultures, between 24 and 72 h, cell number in

C17.2 and BV.2 cultures increased by a fold change of 4.5 and 10.7, respectively. In high

density cultures, these fold changes were 3.1 and 7.8, respectively. Therefore, BV.2

population growth occurred at >2 times the rate of C17.2 culture growth, independent of

cell density.


152

24

48

72

0 .0

0 .5

1 .0

1 .5

2 .0

2 .5

T im e a fte r S tim u la tio n (H o u rs )

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49

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1

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7

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T N F

**

**

**

1 0 0 0 C 1 7 .2 c e lls / w e l l 3 0 0 0 C 1 7 .2 c e lls / w e l l

A B

C D

F ig u r e 6 .1 . C 1 7 .2 v ia b ility a n d a p o p to s is le v e ls , a f te r 2 0 n g /m l T N F s t im u la tio n .

C 1 7 .2 ce lls w ere seeded , a t tw o d ifferen t ce ll den sities , in 9 6 -w e ll p la te s in e ithe r n o rm a l m ed ium

('U n s tim u la ted ' g ro u p ) o r m ed iu m + 2 0 n g /m l T N F ( 'T N F ' g ro u p ). V iab ility /ap o p to s is

m easu rem en ts w ere tak en 24 , 48 an d 7 2 h a fte r p la ting : (A ) V iab ility read in gs in ce lls seeded a t

1 00 0 ce lls /w e ll; (B ) V iab ility read ings in ce lls seeded a t 30 00 ce lls /w ell; (C ) A po p tos is read in gs in

c e lls seed ed a t 1 0 0 0 ce lls /w e ll; (D ) A p o p to s is read in g s in ce lls seed e d a t 3 0 0 0 ce lls /w e ll; (E )

M e asu rem e n ts in A & C , n o rm a lise d to c o rre sp o n d in g 2 4 h re a d in g s a n d (F ) M ea su re m en ts in B &

D , n o rm a lis e d to c o rre sp o n d in g 2 4 h re a d in g s . G ra p h s E a n d F re p re se n t T N F - in d u c e d e ffe c ts

th a t o c cu rred b e tw e e n 2 4 a n d 7 2 h ; e a ch lin e is c o lo u r-m a tch ed w ith th e sa m e c o n d itio n in g ra p h s

A & C a n d g ra p h s B & D , re sp e c tiv e ly (v ia b il ity re a d in g s an d a p o p to s is rea d in g s a re p lo tte d o n

th e le ft and rig h t y -ax is , respec tiv e ly ). E xp erim en ts w ere p e rfo rm ed in tr ip lica te . A v erag ed d a ta is

d isp la y e d , b a rs re p re se n t S .D . a n d a s te risk s rep re se n t s ig n ific an t M an n W h itn ey U te s t re su lts

(*= p-value0 .0 5 , * * = p -v a lue0 .0 1 ). K ru sk a l-W allis A N O V A te s ts w ere p e rfo rm ed o n d a ta in

g ra p h s E a n d F : n o s ig n ifica n t d iffe re n c es w e re fo u n d .

2 4 4 8 7 2

0

1

2

3

4

5

6

0

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1 0

1 5

2 0

2 5

3 0

3 5

4 0


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U /S A p o p to s is T N F A p o p to s isU /S V iab ility T N F V iab ility

V ia b ilit y

A p o p to s is

C o l la t e d

D a t a


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24

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T N F

1 0 0 0 B V .2 c e lls / w e l l 3 0 0 0 B V .2 c e lls / w e l l

A B

C D

2 4 4 8 7 2

0

5

1 0

1 5

2 0

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/Ap

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2 4 4 8 7 2

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V ia b ilit y

A p o p to s is

C o l la t e d

D a t a

F ig u r e 6 .2 . B V .2 v ia b ility a n d a p o p to s is le v e ls , a f te r 2 0 n g /m l T N F s t im u la tio n .

B V .2 ce lls w ere seeded , a t tw o d ifferen t ce ll d en sities , in 96 -w e ll p la te s in e ithe r n o rm a l m ed ium

('U n s tim u la ted ' g ro u p ) o r m ed iu m + 2 0 n g /m l T N F ( 'T N F ' g ro u p ). V ia b ility /a p o p to s is m easu re m en ts

w ere taken 24 , 48 and 7 2 h afte r p la ting : (A ) V iab ility read ing s in ce lls seeded a t 1 000 ce lls/w e ll; (B )

V iab ility read in gs in c e lls seed ed a t 3 00 0 ce lls /w e ll; (C ) A p op to s is read in g s in ce lls seed ed a t 1 0 00

c e lls /w e ll; (D ) A p o p to s is rea d in g s in ce lls seed ed a t 30 0 0 ce lls /w e ll; (E ) M easu rem en ts in A & C ,

n o rm a lise d to c o rre sp o n d in g 2 4 h rea d in g s a n d (F ) M ea su re m e n ts in B & D , n o rm a lised to

c o rre sp o n d in g 2 4 h rea d in g s (v iab ility re a d in g s an d a p o p to s is re ad in g s a re p lo tted o n th e le ft a n d rig h t

y -a x is , re sp e c tiv e ly ) . G ra p h s E a n d F re p re se n t T N F - in d u c e d e ffe c ts th a t o c c u rre d b e tw e e n 2 4 a n d

7 2 h ; e a ch lin e is co lo u r-m a tc h ed w ith th e sa m e c o n d itio n in g ra p h s A & C a n d g ra p h s B & D ,

re sp ec tiv e ly . E x p erim e n ts w ere p e rfo rm e d in tr ip lic a te . A v e rag e d d a ta is d isp lay ed , b a rs re p resen t

S .D . an d a s te risk s rep resen t s ig n ifican t M an n W h itn e y U te s t re su lts (* * = p -v a lu e0 .01). K ruskal-W allis

A N O V A tes ts w e re p e rfo rm e d o n d a ta in g ra p h s E an d F : n o s ig n ifica n t d iffe ren c es w e re fo u n d .


154

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T N F

*

24

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0

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T N F

1 0 0 0 C 1 7 .2 a n d B V .2 c e lls / w e l l 3 0 0 0 C 1 7 .2 a n d B V .2 c e lls / w e l l

A B

C D

2 4 4 8 7 2

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/Ap

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2 4 4 8 7 2

0

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bil

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lativ

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po

pto

sis

E F


V ia b ilit y

A p o p to s is

C o l la t e d

D a t a

F ig u r e 6 .3 . V ia b ility a n d a p o p to s is le v e ls in 1 :1 c o -c u ltu r e s (C 1 7 .2 : B V .2 ) , a f te r 2 0 n g /m l

T N F s t im u la tio n .

C 1 7 .2 an d B V .2 ce lls w ere seeded , a t tw o d iffe ren t ce ll d ens itie s , in 9 6 -w e ll p la te s in e ith e r n o rm al

m ed iu m ( 'U n stim u la ted ' g ro u p ) o r m ed iu m + 20 n g /m l T N F ( 'T N F ' g ro u p ). V iab ility /ap o p to s is

m easu rem en ts w ere tak en 24 , 48 an d 7 2 h afte r p la ting : (A ) V iab ility read in gs in ce lls seeded a t 10 00

ce lls /w ell; (B ) V iab ility read ings in ce lls seed ed a t 30 00 ce lls /w e ll; (C ) A pop to s is read ing s in ce lls

seed ed a t 1 0 0 0 ce lls /w e ll; (D ) A p o p to s is read in g s in ce lls seed ed a t 3 0 0 0 ce lls /w e ll; (E )

M e asu rem e n ts in A & C , n o rm a lise d to c o rre sp o n d in g 2 4 h re a d in g s a n d (F ) M ea su re m en ts in B &

D , n o rm a lise d to co rre sp o n d in g 2 4 h re ad in g s (v ia b ili ty re a d in g s an d ap o p to s is rea d in g s a re p lo tted

o n th e le ft an d rig h t y -ax is , re sp e c tiv e ly ). G ra p h s E a n d F re p rese n t T N F - in d u ce d e ffe c ts th a t

o c cu rre d b e tw e en 2 4 an d 7 2 h ; e a ch lin e is c o lo u r-m a tch ed w ith th e sa m e c o n d itio n in g ra p h s A & C

a n d g rap h s B & D , re sp ec tiv e ly . E x p erim en ts w ere p e rfo rm e d in tr ip lic a te . A v erag e d d a ta is

d isp la y e d , b a rs re p re se n t S .D . a n d a s te risk s rep re se n t s ig n ific an t M an n W h itn ey U te s t re su lts

(*= p-value0 .0 5 ). K ru sk a l-W a llis A N O V A te s ts w e re p e rfo rm e d o n d a ta in g ra p h s E a n d F : n o

s ig n ifican t d iffe ren ces w ere fo u n d .


155

6.2.2. Effects of C17.2- BV.2 Interactions on 1:1 Co-culture Viability and Apoptosis

Using the data displayed in Figures 6.1- 6.3, co-culture-induced changes in cell viability

and apoptosis were investigated. Mono-culture viability and apoptosis results were used to

calculate expected co-culture results; these are the results that would be obtained if

viability and apoptosis in co-cultures was unaffected by C17.2-BV.2 interactions. An

example of the calculations conducted is in Table 2.4, Chapter 2. Analysis was conducted

separately for unstimulated and TNFα-treated cultures. The expected results obtained were

compared to the actual results observed, which can be seen in Figure 6.3. Although,

previous analysis of viability/apoptosis data has utilised non-parametric statistical tests,

parametric z-tests were selected for use here.

The parametric z-test assumes a normal distribution, which cannot be reliably assigned to a

dataset composed of 3 replicate values, as was the case here. However, the non-parametric

alternative to the z-test was a chi-squared test which required discrete data. Therefore, it

was decided to proceed with use of the z-test, whilst acknowledging the risk of obtaining

false positives. To identify any false positive results, the magnitude of any significant

differences will be taken into account.

As a guideline, significant differences in Figures 6.1-6.3 were revisited: significance was

assigned with high confidence in these figures, due to use of the non-parametric Mann

Whitney U test. A difference of 24% was the smallest that was assigned statistical

significance (see 24 h time point in Figure 6.1B). This difference will be used to evaluate

the validity of significance assigned by z-tests in Figures 6.4-6.6.

Viability was significantly lower than expected in unstimulated higher density co-cultures

at 72 h (14% lower than expected; p-value≤0.01; Figure 6.4B). This result mirrors

observations in BV.2 cultures (see Figure 6.2). Assuming that there are little or no co-

culture-associated changes in C17.2 or BV.2 growth rate, co-culture readings would be

dominated by BV.2 cells. Expected and actual co-culture readings displayed similar

growth profiles between 24 and 72 h (Figure 6.4C and D). Taking this into consideration, it

is possible that the significance assigned in this dataset is a consequence of confluency-

dependent saturation of MTS signal. The assay used in this study is reportedly a reliable

indicator of viability for cultures of up to 2.5x105 cells: the possibility of saturation is

noted here and discussed later in this chapter (see section 6.3).


156

No significant differences were reported between expected and actual TNFα-induced co-

culture viability and growth rates (Figures 6.5C and D).

2 4 4 8 7 2

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49

0n

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E x p e c te d

U n s tim u la te d

A ctu a l

U n s tim u la te d


A B

C D

F ig u r e 6 .4 . E x p e c te d v e r su s a c tu a l v ia b ility in u n st im u la te d 1 :1 c o -c u ltu r e s

(C 1 7 .2 :B V .2 ) .

M on o -cu ltu re v iab ility re su lts (d isp lay ed in F ig u res 6 .1 A -B an d 6 .2A -B ) w ere u sed to ca lcu la te

ex p ec ted v iab ility in un s tim u la ted co -cu ltu res . (A ) and (B ) E x pec ted & ac tu a l v iab ility in

1 00 0cells /w e ll/ce ll-ty pe and 300 0cells /w e ll/ce ll-ty pe cu ltu res , re spec tive ly . Z -te s ts w ere used

to d e te rm ine w he the r ac tua l co -cu ltu re v iab ility re su lts w ere s ign ifican tly d iffe ren t to exp ec ted

resu lts . V iab ility read in g s in A an d B w ere n o rm a lised to 2 4 h m easu rem en ts , to rep rese n t

c u ltu re g ro w th b e tw e en 2 4 an d 7 2 h : th is n o rm a lised d a ta is d isp lay e d in (C ) an d (D ),

re sp e c tiv e ly . A v e ra g e s a re d isp la y e d , b a rs re p re se n t S .D . an d a s te risk s re p re sen t s ig n ifica n t

z -te s t re su lts (** = p -v a lue0 .0 1 ).

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E x p e c te d

U n s tim u la te d

A ctu a l

U n s tim u la te d

* *

U n s t im u la te d

Expected apoptosis was calculated and compared to actual apoptosis results, in basal and

TNFα-treated co-cultures (Figure 6.6A-D). The rate of apoptosis between 24 and 72 h was

similar across groups; a high degree of overlap can be seen in Figure 6.6E-F. However, z-

tests highlighted higher than expected apoptosis levels at 48 h in all conditions, except for

lower density unstimulated cultures (p-value≤0.01; Figure 6.6B-D). Average increases of

105%, 49% and 61% were observed in TNFα-stimulated lower cell density (Figure 6.6C),

unstimulated higher cell density (Figure 6.6B) and TNFα-stimulated higher cell density

(Figure 6.6D) cultures, respectively. These findings were not reflected by changes in co-

culture viability (see Figures 6.4 and 6.5), suggesting that increases in proliferation rate

may have accounted for increases in apoptosis.


157

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E x p e c te d T N F

A c tu a l T N F


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C D

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A c tu a l T N F

T N F T r e a t e d

F ig u r e 6 .5 . E x p e c te d v e r s u s a c tu a l v ia b ility in T N F -s t im u la te d 1 :1 c o -c u ltu r e s (C 1 7 .2 :B V .2 ).

M o n o -c u ltu re v iab ility re su lts (d isp lay ed in F ig u re s 6 .1 A -B an d 6 .2 A -B ) w ere u sed to c a lcu la te ex p ec ted

viability in T N F -s tim u la ted co -cu ltu res . (A ) an d (B ) E x pec ted & ac tu a l v iab ility in

1 00 0ce lls /w ell/ce ll-type and 3 00 0cells /w e ll/ce ll- ty pe cu ltu res , re spec tive ly . Z -te s ts w ere used to de term ine

w hethe r ac tu a l co -cu ltu re v iab ility re su lts w ere sign ifican tly d iffe ren t to ex pec ted re su lts . V iab ility read ings

in A a n d B w e re n o rm a lise d to 2 4 h m e asu rem e n ts , to rep re se n t cu ltu re g ro w th b e tw ee n 2 4 an d 7 2 h : th is

n o rm a lised d a ta is d isp lay ed in (C ) a n d (D ), re sp e c tiv e ly . A v e ra g e s a re d isp la y e d an d b a rs rep re se n t

S .D . N o s ig n ific an t d iffe re n ce w as fo u n d b e tw e en e x p ec ted a n d a c tu a l co -cu ltu re v iab ility .

In summary, co-culture interactions may have increased apoptosis and proliferation rate of

cells. Increases in apoptosis appeared to be counteracted by increases in proliferation, thus

co-culture interactions did not affect overall viability of cell populations.

TNFα triggered apoptosis in C17.2 mono-cultures, but not in 1:1 co-cultures. This suggests

the possibility of BV.2 inhibition of TNFα-induced C17.2 apoptosis, which could be linked

to differences in NF-κB dynamics that were discussed in Chapter 4 (refer to Figure 4.2).

An alternative possibility is that, since BV.2 growth rate was higher than that of C17.2

cells, co-culture readings were dominated by BV.2 cells and, thereby, apoptosis of C17.2

was masked (this is debated in section 6.3).

Having established the effects of TNFα and co-culture interactions on viability and

apoptosis, the next goal was to investigate NF-κB contribution to these effects.


158

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A B

C D

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A c tu a l


* *

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T N F T r e a t e d

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E x p e c te d


A c tu a l



A c tu a l T N F

T im e (H o u rs )

E FC o lla t e d

D a t a

F ig u r e 6 .6 . E x p e c te d v e r s u s a c tu a l a p o p to s is in u n s t im u la te d a n d T N F -s tim u la te d 1 :1 c o -c u ltu r e s

(C 1 7 .2 :B V .2 ) .

M o n o -c u ltu re a p o p to s is re su lts (d isp la y ed in F ig u re s 6 .1 C -D an d 6 .2 C -D ) w e re u sed to ca lcu la te ex p e c ted

a p o p to s is in u n s tim u la te d a n d T N F -s tim u la te d c o -c u ltu re s . (A ) a n d (B ) E x p e c te d & a c tu a l a p o p to s is in

1 000ce lls /w ell/ce ll-typ e an d 3 000cells /w ell/ce ll- typ e unstim u la ted cu ltu res , respective ly . (C ) and (D )

E x p e c te d & ac tu a l ap o p to s is in lo w er c e ll d e n s ity a n d h ig h e r c e ll d en sity T N F -s tim u la ted cu ltu res,

re s p e c tiv e ly . Z - te s ts w e re u s e d to c o m p a re e x p e c te d a n d a c tu a l c o -c u ltu re a p o p to s is re su lts . A p o p to s is

rea d in g s in A & C , an d B & D , w e re n o rm a lised to 2 4 h re a d in g s , to re p re sen t c u ltu re g ro w th b e tw ee n 2 4

a n d 7 2 h : th is n o rm a lise d d a ta is d isp la y ed in (E ) a n d (F ), re sp e c tiv e ly . G ra p h s E a n d F re p re se n t

c o -cu ltu re -in d u c e d e ffec ts th a t o c cu rred b e tw e en 2 4 a n d 7 2 h ; ea ch lin e is co lo u r-m a tc h e d w ith th e sa m e

c o n d itio n in g ra p h s A & C a n d g ra p h s B & D , re s p e c tiv e ly . A v e ra g e s a re d isp la y e d a n d b a rs re p re se n t

S .D . M a n n W h itn ey U te s ts w e re p e rfo rm e d : n o s ig n ific an t d iffe ren ce w as fo u n d b e tw ee n ex p e c te d an d

actua l co -cu ltu re v iab ility .


159

6.2.3. Pyrollidine Dithiocarbamate-induced NF-κB Inhibition

In order to investigate NF-κB contribution to changes in viability and apoptosis,

pyrollidine dithiocarbamate (PDTC) was identified as a candidate to inhibit NF-κB

activation. PDTC inhibits IκB phosphorylation and, thereby, p65 nuclear translocation and

NF-κB DNA-binding activity (Zhang et al, 2011). It has previously been used on neural

stem cells to show that NF-κB activation is necessary for TNFα-induced increases in

apoptosis and proliferation (Widera et al, 2006a).

To test PDTC efficacy, C17.2 and BV.2 cells were pre-treated with 0.1mM PDTC for 30

min, then PDTC was washed away and cells were stimulated with 20ng/ml TNFα. Protein

extracts were taken at 15 min intervals from 0 to 120 min post-TNFα stimulation. Western

blots were conducted with these extracts: IκBα levels were used as a measure of NF-κB

activation. IκBα levels were quantified using densitometry and normalised to pre-

stimulation level, for display in Figure 6.7.

Strong TNFα-induced IκBα degradation (without PDTC treatment) was observed in these

cell lines and described in Chapter 3 (refer to Figures 3.8 and 3.19). Here, IκBα in both cell

lines was maintained at pre-stimulation levels for 2 h after TNFα stimulation (Figure 6.7).

This suggests that TNFα-induced NF-κB activation was strongly inhibited and/or delayed

by pre-treatment with PDTC.

To investigate the duration of PDTC-dependent NF-κB inhibition, NF-luc induction was

measured in luminometry experiments. C17.2 cells were transfected with an NF-luc

plasmid and seeded as mono-cultures and 1:1 co-cultures with BV.2 cells. Cultures were

pre-treated for 30 min with water or 0.1mM PDTC, then washed and stimulated with

20ng/ml TNFα, as before. Luminescence measurements were taken at 15 min intervals

from 0 to 15 h after TNFα stimulation. Results from TNFα-treated conditions were

normalised to the corresponding unstimulated controls (Figure 6.8).

One-way ANOVA tests were performed to assess significant differences between groups.

Significant increases in NF-luc induction was observed in all TNFα-treated groups,

compared to unstimulated controls (these significant differences are not represent in Figure

6.8). Figure 6.8 displays significant differences in NF-luc induction, between water +

TNFα groups and PDTC + TNFα groups.


160

A . C 1 7 .2 B . B V .2

0 2 0 4 0 6 0 8 0 1 0 0 1 2 0

0 .0

0 .5

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1 .5


No

rm

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d I

B-

Le

ve

l

C 1 7 .2 B V .2

C

F ig u r e 6 .7 . I B le v e ls in P D T C -tr e a te d c e lls , a fte r T N F s t im u la tio n .

C 1 7 .2 an d B V .2 ce lls w ere p re trea te d fo r 3 0 m in w ith 0 .1 m M P D T C . C e lls w e re th en

w ash ed an d s tim u la ted w ith 20 n g /m l T N F an d p ro te in ex trac ts w e re ta k en a t 1 5 m in

in te rv a ls , fro m 0 to 1 2 0 m in , a fte r s tim u la tio n . (A ) a n d (B ) W es te rn b lo ts fo r I B w ith

p ro te in e x trac ts fro m C 1 7 .2 a n d B V .2 ce lls , re sp ec tiv e ly . (C ) D en sito m e try an a ly s is o f

W es te rn b lo ts : I B lev e ls w ere no rm a lised to co rre sp o n d in g p re -s tim u la tio n lev e l.

Figures 6.8A-B show that NF-luc induction was inhibited in PDTC + TNFα treated C17.2

cells, compared to water + TNFα treated cells, in mono-cultures and co-cultures (p-

value≤0.01). Slower increases in luciferase expression were observed in PDTC-treated

cultures; curves representing non-PDTC-treated groups show a steeper increase in

luciferase expression after TNFα stimulation.

Each luminometry experiment was conducted with mono-cultures and co-cultures, seeded

with the same batch of NF-luc-transfected C17.2 cells. This made the results from mono-

cultures and co-cultures comparable. Significant differences between these groups can be

seen in Figure 6.8C. No difference in NF-luc induction was observed between PDTC +

TNFα-treated mono-cultures and co-cultures.

In summary, pre-treatment with 0.1mM PDTC inhibited, not prevented, TNFα-induced

NF-κB activation in C17.2 cells. IκBα level after TNFα-stimulation indicated that PDTC

also strongly inhibited/prevented NF-κB activation in BV.2 cells. For these reasons, PDTC

was deemed suitable for use to assess NF-κB contribution to TNFα-induced changes in cell

viability and apoptosis.


161

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 150

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T ime after Treatment (Hours)

A . M o n o -c u ltu re B . 1 :1 C o -c u ltu re

F ig u r e 6 .8 . T N F -s t im u la te d N F -lu c in d u c t io n in P D T C - a n d n o n -P D T C tr e a te d C 1 7 .2

c e l ls .

C e lls w ere tran s fec ted w ith an N F -lu c p la sm id an d see d ed in to m o n o -c u ltu re s (A ) o r 1 :1

c o -c u ltu res w ith B V .2 (B ). T h ese cu ltu res w e re th e n p re -trea ted fo r 3 0 m in u tes w ith e ith e r w a te r o r

0 .1 m M P D T C , b e fo re b e in g w ash ed an d e ith e r le ft u n s tim u la ted o r s tim u la ted w ith 20 n g /m l T N F .

L u m in e sce n ce rea d in g s w ere tak en ev e ry 1 5 m in fro m 0 to 1 5 h a fte r T N F s tim ula tion .

E x p e rim e n ts w ere p e rfo rm ed in tr ip lic a te s . (C ) D a ta fro m g rap h s A a n d B , d isp lay e d w ith o u t S .D .

b a rs , fo r c o m p a riso n b e tw e e n d a ta s e ts . G ra p h s re p re s e n t a v e ra g e s f ro m c o lla te d d a ta , b a rs

re p resen t ± S .D . an d a s te risk s re p resen t s ig n ifica n t o n e -w a y A N O V A tes t re su lts . A ll d o u b le

a s te risk s rep resen t p -v a lu e0 .0 1 (* * is v e rs u s 'W a te r + T N F a ' g ro u p in (A ) a n d (B ), ** is v e rsu s

'C o -c u ltu re : W a te r + T N F a ' g ro u p a n d ** is v e rs u s 'C o -c u ltu re : P D T C + T N F a ' g ro u p in (C )).

C . C o lla te d D a ta

0 1 2 3 4 5 6 7 8 9 10 11 12 1314150

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Time after Treatment (Hours)

Mono-culture: Water + TNFa ** **

Mono-culture: PDTC + TNFa **

Co-culture: Water + TNFa

Co-culture: PDTC + TNFa

6.2.4. Effects of NF-κB Inhibition on Untreated and TNFα-treated Mono-cultures and

1:1 Co-cultures

Previously outlined data described TNFα-induced changes in cell viability and apoptosis in

mono-cultures and co-cultures (Figures 6.1-6.3). To learn more about the role that NF-κB

played in these changes, viability readings were taken from water/0.1mM PDTC-pretreated

cells that were washed and then left unstimulated or stimulated with 20ng/ml TNFα. These

experiments were conducted at two different cell densities with C17.2 and BV.2 mono-

cultures (Figures 6.9 and 6.10, respectively), as well as 1:1 co-cultures (Figure 6.11).

Experiments were performed in triplicate, with three technical replicates per assay. One-


162

way ANOVA tests were performed to evaluate differences between groups and data was

averaged for display. Kruskal-Wallis ANOVA tests were used to assess differences in

growth rates across culture conditions.

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**

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W a te r

P D T C

P D T C + T N F

W a te r + T N F

1 0 0 0 C 1 7 .2 c e lls / w e l l 3 0 0 0 C 1 7 .2 c e lls / w e l l

A B

2 4 4 8 7 2

0

1

2

3

4

5


Re

lati

ve

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at

49

0n

m

2 4 4 8 7 2

0

1

2

3

4

5


Re

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Ab

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ce

at

49

0n

m

W a te r

P D T C

P D T C + T N F -

W a te r + T N F -

C D

F ig u r e 6 .9 . C 1 7 .2 c e ll v ia b ility a fte r 3 0 m in p r e -tr e a tm e n t w ith w a te r o r 0 .1 m M P D T C

a n d e ith e r n o s t im u la tio n o r 2 0 n g /m l T N F s t im u la tio n .

W ate r- o r P D T C -p re trea te d C 1 7 .2 ce lls w ere w ash ed an d se ed e d in a 9 6 -w e ll p la te in n o rm a l

m ed iu m o r m ed iu m + 2 0n g /m l T N F . V iab ility m easu rem en ts w ere tak en 2 4 , 4 8 an d 7 2 h a fte r

p la ting: (A ) V iab ility readings in ce lls seeded a t 1000 ce lls /w ell; (B ) V iability read ings in ce lls

se ed e d a t 3 0 0 0 ce lls /w e ll; (C ) M e asu rem e n ts in A , n o rm a lise d to c o rre sp o n d in g 2 4 h rea d in g s

a n d (D ) M e a su re m e n ts in B , n o rm a lise d to c o rre sp o n d in g 2 4 h re ad in g s . G ra p h s C a n d D

re p re sen t trea tm e n t-in d u c e d e ffe c ts th a t o c cu rre d b e tw e en 2 4 an d 7 2 h ; ea c h lin e is

c o lo u r-m a tc h ed w ith th e sa m e c o n d itio n in g rap h A an d g rap h B , re sp ec tiv e ly . E x p erim en ts w e re

p e rfo rm e d in tr ip lic a te . A v e ra g e d d a ta is d isp la y e d , b a rs re p re sen t S .D . a n d a s te risk s re p re se n t

s ig n ifican t o ne -w ay A N O V A tes t re su lts (* * = p-va lue0 .01 ). K rusk a l-W allis A N O V A tes ts w ere

p e rfo rm e d o n d a ta in g ra p h s C an d D : n o s ig n if ica n t d iffe re n c e s w e re fo u n d .

PDTC-treated C17.2 cultures were significantly more viable than TNFα-treated cultures at

the lower cell density (p-value≤0.01; Figure 6.9A). Moreover, it should be noted that

PDTC and PDTC + TNFα-treated cultures were consistently more viable than water and

water + TNFα-treated groups, although these results were not highlighted by statistical

analysis. The growth rate of cultures between 24 and 72 h was comparable, indicating that

early TNFα-induced decreases in viability (at 24 h) are responsible for the viability

differences observed at later time points: this is consistent with the conclusions drawn from

the previous set of viability experiments (see Figure 6.1).


163

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*

*

**

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0n

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W a te r

P D T C

P D T C + T N F

W a te r + T N F **

**

****

*

**

1 0 0 0 B V .2 c e lls / w e l l 3 0 0 0 B V .2 c e lls / w e l l

A B

2 4 4 8 7 2

0

1

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2 4 4 8 7 2

0

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Re

lati

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Ab

so

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ce

at

49

0n

m

W a te r

P D T C

P D T C + T N F -

W a te r + T N F -

C D

F ig u r e 6 .1 0 . B V .2 c e ll v ia b ility a fte r 3 0 m in p r e -tr e a tm e n t w ith w a te r o r 0 .1 m M

P D T C a n d e ith e r n o s t im u la t io n o r 2 0 n g /m l T N F s t im u la tio n .

W ate r- o r P D T C -p re tre a ted B V .2 c e lls w ere w ash ed a n d seed e d in a 9 6 -w e ll p la te in n o rm a l

m ed ium o r m ed iu m + 20n g /m l T N F . V iab ility m easu rem en ts w ere taken 24 , 48 an d 7 2 h

a fter p la ting : (A ) V iability read ings in ce lls seeded a t 1000 ce lls/w ell; (B ) V iab ility read ings in

c e lls se ed e d a t 3 0 0 0 c e lls /w e ll; (C ) M easu rem e n ts in A , n o rm a lised to co rre sp o n d in g 2 4 h

rea d in g s an d (D ) M e a su rem e n ts in B , n o rm a lise d to c o rre sp o n d in g 2 4 h rea d in g s . G ra p h s C

a n d D re p re se n t tre a tm en t-in d u c e d e ffec ts th a t o c cu rred b e tw ee n 2 4 an d 7 2 h ; e a ch lin e is

c o lo u r-m a tch e d w ith th e sa m e c o n d itio n in g ra p h A an d g rap h B , re sp e c tiv e ly . E x p erim en ts

w e re p e rfo rm e d in tr ip lica te . A v era g ed d a ta is d isp la y ed , b a rs rep re sen t S .D . a n d a s te r isk s

rep resen t s ig n ifican t o n e -w ay A N O V A tes t re su lts (*= p -v a lue0 .0 5 ,* *= p-va lue0 .0 1 ).

K ru sk a l-W a llis A N O V A te s ts w ere p e rfo rm ed o n d a ta in g rap h s C an d D : n o s ig n ifican t

d iffe re n ce s w e re fo u n d .

Earlier analysis of viability data from unstimulated and TNFα-stimulated C17.2 cultures

highlighted significant differences between the two groups (see Figures 6.1A-B): this was

not observed in Figure 6.9. This discrepancy may be due to the use of different statistical

tests; the non-parametric Mann Whitney U test is more apt for analysis of small datasets

than the one-way ANOVA. The one-way ANOVA was employed here due to the large

number of groups in this analysis. Although, not assigned statistical significance, TNFα-

treated cultures were consistently less viable than water-treated cultures.

Unlike C17.2 observations, one way ANOVA of BV.2 viability results highlighted many

significant differences (p-value≤0.05; Figures 6.10A-B). As previously observed in Figure


164

6.2, MTS signal appears saturated in higher density cultures at 48 and 72 h: this is seen in

Figure 6.10D as a plateau in growth rate. For clarity, focus will be placed on two consistent

findings across culture conditions. Firstly, PDTC + TNFα treated groups were more viable

than TNFα-treated cultures, at both cell densities. This difference was assigned

significance in higher cell density cultures only. Secondly, viability of PDTC-treated

cultures was significantly higher than that of TNFα-stimulated cultures at 72 h, across cell

densities, and at 48 h in higher cell density cultures only.

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W a te r

P D T C

P D T C + T N F

W a te r + T N F

**

**

**

****

**


A B

2 4 4 8 7 2

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Re

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W a te r

P D T C

P D T C + T N F -

W a te r + T N F -

*

C D

F ig u r e 6 .1 1 . V ia b ility o f 1 :1 c o -c u ltu r e s (C 1 7 .2 :B V .2 ) , a fte r 3 0 m in p r e -tr e a tm e n t w ith

w a te r o r 0 .1 m M P D T C a n d e ith e r n o s t im u la t io n o r 2 0 n g /m l T N F s t im u la tio n .

W a ter- o r P D T C -p re trea ted 1 :1 c o -cu ltu res w ere w a sh ed a n d se ed e d in a 9 6 -w e ll p la te in

n orm al m ed iu m o r m ed iu m + 20 ng /m l T N F . V iab ility m easu rem en ts w ere taken 2 4 , 48 and

72 h afte r p la ting : (A ) V iab ility readings in ce lls seeded a t 1000 ce lls/w e ll; (B ) V iab ility

read ing s in ce lls seed ed a t 3 0 00 ce lls /w e ll; (C ) M easu rem en ts in A , no rm a lised to

c o rre sp o n d in g 2 4 h re a d in g s a n d (D ) M ea su re m en ts in B , n o rm a lise d to c o rre sp o n d in g 2 4 h

re a d in g s . G ra p h s C a n d D re p re se n t tre a tm e n t-in d u c e d e ffe c ts th a t o c c u rre d b e tw e e n 2 4 a n d

7 2 h ; e ac h lin e is co lo u r-m a tc h ed w ith th e sam e co n d itio n in g ra p h A an d g rap h B ,

re sp e c tiv e ly . E x p erim en ts w e re p e rfo rm ed in trip lic a te . A v erag ed d a ta is d isp la y ed an d b a rs

re p resen t S .D . O n e -w ay A N O V A a n d K ru sk a l-W allis A N O V A tes ts w ere p e rfo rm e d o n

d a ta in A & B an d C & D , re sp e c tiv e ly . A s te risk s re p re se n t s ig n ific a n t d iffe re n c es

(*= p-value0 .0 5 , * * = p -v a lue0 .0 1 ).

As with C17.2, growth rates of different culture conditions were comparable. Therefore,

significant differences observed at 72 h, at higher cell densities, was most likely due to the

effects of PDTC observed at 24 h.


165

Overall, PDTC-treatment was found to promote viability of both C17.2 and BV.2 mono-

cultures. Next, the effects of PDTC were investigated in 1:1 co-cultures (Figure 6.11). As

with BV.2 data, one-way ANOVA tests highlighted many significant differences between

culture conditions (p-value≤0.05). One consistent finding mirrors observations made in

C17.2 and BV.2 mono-cultures: PDTC-treated cultures were significantly more viable than

TNFα-treated cultures at 48 and 72 h at both cell densities. Differences at 72 h may be the

effect of significant differences in growth rate observed between 24 and 48 h (compare

blue and red lines in Figures 6.11C and D) or MTS signal saturation, as previously noted in

BV.2 cultures (Figures 6.2 and 6.10). The significant difference in growth rates cannot be

assigned to any particular groups: Kruskal-Wallis ANOVA results only reveal that at least

one group is significantly different to the others. Considering the plateau in growth rate

between 48 and 72 h in high cell density cultures, MTS saturated signals could be masking

the effects of PDTC treatment at later time points. Hence, results from low cell density

cultures are likely to be more reflective of treatment-induced changes in viability at later

time points.

6.2.5. Effects of C17.2-BV.2 Interactions on Cell Viability in 1:1 Co-cultures

In order to establish whether C17.2- BV.2 interactions contributed to co-culture viability

results obtained, expected co-culture results were calculated from mono-culture data (see

Table 2.4 in Chapter 2 for methods). These calculations were performed separately for

water only, water + TNFα, PDTC only and PDTC + TNFα-treated groups. Z-tests were

used to determine significant differences between expected results and actual co-culture

results obtained (which are displayed in Figure 6.11). As mentioned earlier in this chapter,

ideally the non-parametric Chi-squared test would have been used but, due to the

continuous nature of this dataset, this was not possible. Therefore, caution will be

exercised in the interpretation of significance assigned by z-tests.

Water-treated co-culture viability results were lower than expected at 24 h in lower cell

density cultures (p-value≤0.01; Figure 6.12A). This is inconsistent with results shown in

Figure 6.4. The effects of saturation could be seen in higher cell density co-cultures:

significance assigned at 72 h can be attributed to this (p-value≤0.01).

PDTC-treated co-culture viability was lower at the same time points and cell densities as

observed in unstimulated co-cultures (p-value≤0.01; Figure 6.12A). Again, significance


166

assigned at 72 h, in lower cell density cultures, and at 48 h and 72 h in higher cell density

cultures is most likely an artefact of confluency-dependent saturation of absorbance.


F ig u r e 6 .1 2 . E x p e c te d v e r s u s a c tu a l v ia b il ity in w a te r o r 0 .1 m M P D T C -

tr e a te d 1 :1 c o -c u ltu r e s (C 1 7 .2 :B V .2 ) .

M o n o -c u ltu re v ia b il i ty re s u lts (d is p la y e d in F ig u re s 6 .9 A -B a n d 6 .1 0 A -B ) w e re

u s e d to c a lc u la te e x p e c te d v ia b il i ty in w a te r t re a te d c o -c u l tu re s . (A ) a n d (B )

E x p ec te d & ac tu a l v iab il ity in 1 0 0 0 ce lls /w e ll /c e ll- ty p e a n d 3 0 0 0 ce lls /w e ll/c e ll- ty p e

c o -c u l tu re s , re s p e c t iv e ly . Z -te s ts w e re u s e d to d e te rm in e w h e th e r a c tu a l

c o -c u ltu re v ia b ili ty re su lts w e re s ig n ific a n tly d iffe re n t to e x p e c te d re su lts . V ia b il i ty

re a d in g s in A a n d B w e re n o rm a lis e d to 2 4 h m e a s u re m e n ts , to re p re s e n t c u ltu re

g ro w th b e tw e e n 2 4 a n d 7 2 h : th is n o rm a lis e d d a ta i s d is p la y e d in (C ) a n d (D ) ,

re s p e c tiv e ly . A v e ra g e s a re d is p la y e d , b a rs re p re s e n t S .D . a n d a s te r is k s re p re s e n t

s ig n if ic a n t z - te s t re s u lts (* * = p -v a lu e 0 .0 1 ) .

A B

C D

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* ** *

* *

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2 0

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m

E x p e c te d : W a te r

A c tu a l: W a te r

E x p e c te d : P D T C

A c tu a l: P D T C

* *

* * * *

2 4 4 8 7 2

0

2

4

6

8

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0

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E x p e c te d : W a te r

A c tu a l: W a te r

E x p e c te d : P D T C

A c tu a l: P D T C

Growth of cultures that contained BV.2 cells consistently plateaued after reaching

absorbance readings around 10-15 arbitrary units, independent of treatment and initial cell

density (see Figures 6.2, 6.3, 6.10 and 6.11). The plateau effect may be due to confluency-

dependent changes in culture growth rate or saturation of the MTS signal.

Consistent with previous observations, growth of water + TNFα-stimulated cultures

plateaued at higher cell densities (Figure 6.13C-D), hence lower cell density results will be

the focus here. Viability of water + TNFα-treated co-cultures was significantly lower than


167

expected, at 48 h after TNFα-stimulation (p-value≤0.05; Figure 6.13). This observation is

inconsistent with data in Figure 6.5, where no difference was found between expected and

actual co-culture viability. However, it should be noted that the difference observed here is

small and that this dataset is not entirely suited to statistical analysis with z-tests.

24

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*

*

* *

* *

* *

2 4 4 8 7 2

0

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E x p e c te d : P D T C + T N F

A c tu a l: P D T C + T N F

E x p e c te d : T N F

A c tu a l: T N F

2 4 4 8 7 2

0

2

4

6

H o u rs

Re

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24

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0

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Ab

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m

E x p e c te d : P D T C + T N F

A c tu a l: P D T C + T N F

E x p e c te d : T N F

A c tu a l: T N F * *

* *

* *

* * * *


F ig u r e 6 .1 3 . E x p e c te d v e r s u s a c tu a l v ia b i l ity in 1 :1 c o -c u ltu r e s (C 1 7 .2 :B V .2 ) ,

a f te r e ith e r a 3 0 m in p r e - tr e a tm e n t w ith w a te r o r 0 .1 m M P D T C a n d 2 0 n g /m l

T N F .

M o n o -c u ltu re v ia b il i ty re s u lts (d is p la y e d in F ig u re s 6 .9 A -B a n d 6 .1 0 A -B ) w e re

u s e d to c a lc u la te e x p e c te d v ia b il i ty in w a te r t re a te d c o -c u l tu re s . (A ) a n d (B )

E x p ec te d & ac tu a l v iab il ity in 1 0 0 0 ce lls /w e ll /c e ll- ty p e a n d 3 0 0 0 ce lls /w e ll/c e ll- ty p e

c o -c u l tu re s , re s p e c t iv e ly . Z -te s ts w e re u s e d to d e te rm in e w h e th e r a c tu a l

c o -c u ltu re v ia b ili ty re su lts w e re s ig n ific a n tly d iffe re n t to e x p e c te d re su lts . V ia b il i ty

re a d in g s in A a n d B w e re n o rm a lis e d to 2 4 h m e a s u re m e n ts , to re p re s e n t c u ltu re

g ro w th b e tw e e n 2 4 a n d 7 2 h : th is n o rm a lis e d d a ta i s d is p la y e d in (C ) a n d (D ) ,

re s p e c tiv e ly . A v e ra g e s a re d is p la y e d , b a rs re p re s e n t S .D . a n d a s te r is k s re p re s e n t

s ig n if ic a n t z - te s t re s u lts (* * = p -v a lu e 0 .0 1 ) .

A B

C D

TNFα stimulation, preceded by PDTC-treatment, led to significantly lower co-culture

viability, across time points (p-value≤0.01; Figure 6.13). Considering potential effects of

saturation, credence will be paid to results at earlier time points i.e. 24 h and 48 h in low

cell density cultures and 24 h in high cell density cultures. Expected and actual co-culture

growth curves were similar between 24 h and 72 h, which suggest that earlier changes in


168

viability (at 24 h) were propagated over time. Therefore, it can be concluded that co-

culture viability was lower than expected at 24 h after PDTC + TNFα treatment.

Overall, PDTC treatment increased viability of C17.2 and BV.2 cells in mono-cultures and

1:1 co-cultures, compared to TNFα-treated cells. Due to time constraints, it was not

possible to study the effects of PDTC on proliferation and apoptosis rates. Instead,

preliminary apoptosis assays were conducted to observe any PDTC-induced effects that

may have contributed to results outlined in this chapter.

C17.2 and BV.2 cells were treated for 30 min with either 0.1mM PDTC or water, then

washed and seeded in 96-well plates in mono-cultures at two different cell densities (1000

and 3000 cells per well). Apoptosis readings were measured 24 h after treatment.

Experiments were performed in triplicate, with three technical replicates per plate, and

Mann Whitney U tests were conducted on collated datasets. Averaged data is displayed in

Figures 6.14 and 6.15.

U n s tim u la te d P D T C -tre a te d

0

1

2

3

4

5

Re

lati

ve

Lu

min

es

ce

nc

e

1 0 0 0 c e l ls /w e ll

3 0 0 0 c e l ls /w e ll

**

**

F ig u r e 6 .1 4 . A p o p to s is le v e ls in w a te r - o r P D T C -tr e a te d C 1 7 .2

c e l ls .

C 1 7 .2 c e l ls w e re w a s h e d a n d s e e d e d a t tw o d if fe re n t c e l l d e n s it ie s ,

a f te r 3 0 m in t re a tm e n t w i th e i th e r w a te r ( 'U n s tim u la te d ') o r 0 .1 m M

P D T C ( 'P D T C -tre a te d ') . A p o p to s is le v e ls w e re m e a s u re d 2 4 h a f te r

tre a tm e n t . E x p e r im e n ts w e re p e r fo rm e d in t r ip lic a te . A v e ra g e d d a ta

is d is p la y e d , b a rs re p re s e n t S .D . a n d a s te r is k s re p re s e n t

s ig n if ic a n t M a n n W h itn e y U te s t re s u lts (* * = p -v a lu e 0 .0 1 ) .

PDTC-treated C17.2 mono-cultures were more apoptotic than control cultures, at both cell

densities investigated (p-value≤0.01; Figure 6.14). No change in BV.2 apoptosis rate was

observed after PDTC-treatment (Figure 6.15). Increased viability in PDTC-treated cultures

(versus TNFα-treated cultures; seen in Figures 6.9- 6.11) must have been due to increased

proliferation of both C17.2 and BV.2 cells. The results outlined here strongly suggest that


169

NF-κB inhibition increased viability and proliferation of C17.2 and BV.2 cells and also

increased apoptosis in C17.2 cells only.

U n s tim u la te d P D T C -tre a te d

0

1

2

3

4

Re

lati

ve

Lu

min

es

ce

nc

e

1 0 0 0 c e l ls /w e ll

3 0 0 0 c e l ls /w e ll

F ig u r e 6 .1 5 . A p o p to s is le v e ls in w a te r - o r P D T C -tr e a te d B V .2

c e l ls .

B V .2 c e l ls w e re w a s h e d a n d s e e d e d a t tw o d iffe re n t c e l l d e n s i t ie s ,

a f te r 3 0 m in t re a tm e n t w i th e i th e r w a te r ( 'U n s tim u la te d ') o r 0 .1 m M

P D T C ( 'P D T C -tre a te d ') . A p o p to s is le v e ls w e re m e a s u re d 2 4 h a f te r

tre a tm e n t. E x p e rim e n ts w e re p e rfo rm e d in t r ip lic a te . A v e ra g e d d a ta i s

d is p la y e d , a n d b a rs re p re s e n t S .D . M a n n W h itn e y U te s t re s u l ts

in d ic a te n o s ig n if ic a n t d iffe re n c e b e tw e e n a p o p to s is le v e ls in

u n s t im u la te d a n d P D T C -tre a te d g ro u p s .

6.3 Discussion

Numerous studies have been reported on the effects of TNFα on NPCs/NSCs (Ben-hur et

al, 2003; Wong et al, 2004; Widera et al, 2006a; Widera et al, 2006b; Wang et al, 2014).

The findings from these studies are somewhat contradictory: TNFα was found to inhibit

proliferation and promote proliferation of NPCs by separate studies (Wong et al, 2004;

Widera et al, 2006a). In general, TNFα effects on apoptosis are more consistent: findings

show that TNFα can promote apoptosis (Wang et al, 2014; Widera et al, 2006a).

The effects of TNFα on NPCs are reported to be dose-dependent: Bernardino et al (2008)

reported NPC proliferation in response to 1ng/ml TNFα and apoptosis after stimulation

with doses of ≥10ng/ml TNFα. The outcome of TNFα treatment can also be determined by

TNFR engagement by TNFα: TNFR1 and TNFR2 interactions are generally associated

with apoptosis and cell survival, respectively (MacEwan, 2002), although this picture is

too simplistic and TNFR2 signaling can contribute to apoptosis (Wajant et al, 2003).

TNFR1 is thought to be the major NF-κB activating TNFR in NPCs (Kolesnick and Golde,


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1994) and TNFR1 signaling inhibits proliferation of NPCs (Iosif et al, 2006), implying that

NF-κB activity may be a negative regulator of proliferation.

Many factors converge to determine the outcome of TNFα stimulation: this complexity

may explain the seemingly contradictory observations of TNFα effects on NPCs. In

contrast to NPCs, there is a deficiency in studies on the effects of TNFα on microglia. It

has been reported that TNFα leads to an increase in viability of microglial cultures (Kuno

et al, 2005).

None of the studies mentioned above were conducted with the cell lines used in this study.

Here, with the use of MTS and caspase3/7 assays, viability and apoptosis was investigated

in C17.2 and BV.2 mono-cultures, as well as 1:1 co-cultures, after 20ng/ml TNFα

stimulation. NF-κB contribution to TNFα effects was also studied with the use of PDTC

(an NF-κB inhibitor). The main findings of this investigation are as follows:

1) TNFα induced apoptosis and decreased cell viability in C17.2 mono-cultures: this effect

was prevented by BV.2 cells in 1:1 co-cultures;

2) TNFα did not affect BV.2 viability or apoptosis rates;

3) NF-κB inhibition caused apoptosis in C17.2 cultures and increased viability in C17.2

and BV.2 mono-cultures and 1:1 co-cultures.

TNFα-induced changes in cell survival will be considered in relation to observations made

in other microglial and NPC lines. The goal of this discussion is to formulate hypotheses

that may explain the above findings.

6.3.1. Effects of TNFα on C17.2 and BV.2 Mono-cultures

TNFα treatment decreased the viability of C17.2 mono-cultures. This effect was at least

partially mediated by increased caspase3/7-dependent apoptosis: proliferation rates cannot

be ruled out as a contributory factor. As many studies report on simultaneous TNFα-

induced changes in proliferation and apoptosis; future proliferation assays would provide a

more thorough understanding of TNFα effects on this cell line. TNFα reportedly increased

proliferation and apoptosis in NSCs via an NF-κB-dependent mechanism (Widera et al,

2006a). From this, it was predicted that inhibition of NF-κB activation, dominantly via

TNFR1, would prevent TNFα-induced apoptosis in C17.2 mono-cultures.


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Contrary to observations on C17.2 cultures, 20ng/ml TNFα had no effect on BV.2 viability

or apoptosis levels, up to 72 h post-treatment: this contradicts observations from the Kuno

et al study (2005) where an increase in cell viability was reported after TNFα treatment.

However, this increase was measured at 6 days after treatment- later than the observations

made here.

The decrease in cell viability detected at 72 h in higher cell density BV.2 cultures was most

likely due to saturation of the MTS signal, caused by high cell confluency (see Figure 6.2).

Strong evidence of saturation was observed with some consistency in other results on

BV.2-containing cultures. This was a surprising observation, as it has been reported that

the MTS assay employed here is a reliable indicator of cell viability for a population of up

to 2.5x105 cells (manual by kit supplier, see Chapter 2). The same problem with saturation

was not observed with C17.2 cultures: this reflects the differences in proliferation rate of

these cell lines. BV.2 cell proliferation rate was atleast 2-fold higher than C17.2

proliferation rate.

Due to the problems associated with a saturated MTS signal, the results from lower cell

densities will be the primary focus for discussion here, as they are more reliable markers of

changes in viability.

Co-culture viability results reflected observations made in BV.2 mono-cultures, rather than

the decreases in viability and increases in apoptosis measured in C17.2 mono-cultures.

This suggests that BV.2 cells can prevent TNFα-induced NPC apoptosis. However, since

BV.2 growth rates were higher than those of C17.2, the viability readings from co-cultures

will be dominated by BV.2 cell fate. As BV.2 viability does not decrease in response to

TNFα, BV.2 cell viability may have been masking C17.2 apoptosis.

Although BV.2 cells may have dominated co-culture readings, there are two important

factors that should be considered here: 1) it is unknown whether C17.2-BV.2 interactions

influenced the growth rate of these cells and; 2) assuming no co-culture-related changes in

growth rate of either cell line, C17.2 cells would have composed approximately one-third

of co-cultures. Elaborating on the first point, it is possible that increased growth rate of one

cell line would have been counteracted by a decrease in growth rate of the other cell line,

so that no change was observed in overall culture viability. On the second point, assuming

that C17.2 cells continue to proliferate as usual in co-cultures, it is unlikely that C17.2

numbers were too small to allow detection of apoptosis. This is particularly true for later


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time points, when small differences caused by early C17.2 apoptosis would have been

propagated to create lower viability readings (compared to unstimulated co-cultures).

Microglial-derived TNFα can induce NPC apoptosis in an NF-κB-dependent manner

(Guadagno et al, 2013). BV.2-mediated prevention of TNFα-induced C17.2 apoptosis may

be related to inhibition of p65 nuclear translocations (reported in co-cultured C17.2 cells in

Chapter 4; see Figure 4.2). This idea will be discussed further in Chapter 7.

6.3.2. Effects of NF-κB Inhibition on C17.2 and BV.2 Mono-culture and 1:1 Co-

culture Viability

From data described in this chapter, it was predicted that NF-κB inhibition would block

TNFα-dependent decreases in C17.2 mono-culture viability. The results of MTS assays

performed with TNFα and PDTC (an NF-κB inhibitor) supported this idea. With the

exception of one data point (in Figure 6.10A), all groups pre-treated with PDTC gave a

stronger MTS signal than the corresponding untreated or TNFα-stimulated groups. Some

of the differences in viability were not statistically significant.

An important factor to consider was the efficacy of NF-κB inhibition by PDTC. PDTC pre-

treatment delayed and partially inhibited TNFα-induced NF-κB activation, as measured by

NF-luc activity in C17.2 cells and by Western blots for IκBα degradation in both cell types

(see Figures 6.7-6.8). Complete inhibition of NF-κB may have led to more pronounced,

statistically significant, differences between PDTC and non-PDTC treated groups.

However, even partial inhibition led to an observable effect on C17.2 viability: consistency

across the dataset provides a convincing argument for a PDTC-dependent increase in cell

viability. Future experiments with other NF-κB inhibitors could be used to further

investigate NF-κB-mediated effects of TNFα.

Widera et al, (2006a) used a combination of NF-κB inhibitors, including PDTC and a super

repressor IκB construct. They reported that TNFα-induced NF-κB activation increased

both proliferation and, to a lesser degree, apoptosis in NSCs. The differences between their

observations and those made here might be explained by methodology. They used NSCs

isolated from the subventricular zone of adult rats and 10ng/ml TNFα, whereas murine

cells and 20ng/ml TNFα was used here. Low and high doses of TNFα have been associated

with cell survival and apoptosis, respectively (Bernardino et al, 2008): this may also

contribute to differences between published results and those seen here. Another


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contributory factor could be TNFR2 expression levels. TNFR2 is expressed on NPCs and

has a high affinity for mTNFα, a form of TNFα that is expressed on the membranes of

microglial cells (Zhou et al, 2010). Signalling through TNFR2 may be responsible for

prevention of TNFα-induced C17.2 apoptosis, observed in co-cultures (see Figure 6.3),

although TNFR2 signaling can also enhance TNFR1-driven apoptosis (Wajant et al, 2003).

TNFR1 versus TNFR2 signaling, and downstream NF-κB dynamics, may be an interesting

avenue of investigation in the future.

From the results seen in Figures 6.9-6.11, it was hypothesised that PDTC-treatment might

increase culture viability by decreasing apoptosis or increasing proliferation rate. To

address these possibilities, preliminary apoptosis assays were conducted on PDTC-treated

C17.2 and BV.2 mono-cultures (see Figures 6.16-6.17). Surprisingly, these results showed

that PDTC increased C17.2 apoptosis and had no effect on BV.2 apoptosis rates (at 24 h

post-treatment). Combined with the viability results obtained from PDTC-treated cultures,

this strongly suggests that PDTC treatment increases proliferation of cells, which accounts

for increased apoptosis, and results in increased culture viability. (This is discussed further

in Chapter 7).

6.3.3. C17.2-BV.2 Interactions in 1:1 Co-cultures

Previous studies have reported changes in co-culture viability and apoptosis that occur as a

result of interactions between microglia and NPCs (Guadagno et al, 2013; Mosher et al,

2012; Liu et al, 2013a; Liu et al, 2014; Deierborg et al, 2010). Many of these involved the

exchange of culture media, thereby showing that soluble microglial or neural progenitor

cell-derived factors drive the effects observed (Guadagno et al, 2013; Deierborg et al,

2010). These factors include NPC-derived VEGF: this factor was shown to promote

microglial proliferation in co-cultures (Mosher et al, 2012) and its expression is regulated

by NF-κB (Chilov et al, 1997).

Mosher et al (2012) observed NPC and microglial response in separate cultures, thereby

preventing cell-contact. However, microglia are densely populated in neurogenic niches in

vivo and ideally located to have physical contact with NPCs (Mosher et al, 2012). Also,

results in Chapter 4 show that basal NF-κB activity in C17.2 is increased by physical

contact with BV.2 (Figure 4.13). Together, this suggests that contact-permissive co-

cultures are the ideal model systems to use for accurate representation of NPC-microglial

interactions in vivo.


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It has been reported that microglia promote NPC proliferation and induce apoptosis

(Guadagno et al, 2013; Liu et al, 2013b; Liu et al, 2014). Microglial effects on NPCs are

determined by activation status: ‘resting’ and classically activated microglia have been

found to increase and decrease NPC number, respectively (Cacci et al, 2005). Moreover,

NPC apoptosis was induced by microglial-derived TNFα (Guadagno et al, 2013; Liu et al,

2013b). In turn, NPCs increase proliferation and promote activation of microglia (Mosher

et al, 2012; Forstreuter et al, 2002). It should be noted that co-culture ratios used in these

studies were unclear and may play an important role in determining the outcome of co-

culture interactions.

Here, seemingly contradictory findings were observed in co-culture. The second set of

viability experiments conducted resulted in lower than expected co-culture viability, at 24

h, in unstimulated co-cultures (see Figure 6.12A). Also, lower co-culture viability was

observed in TNFα-treated co-cultures, at 48 h and 72 h (see Figure 6.13A and B). Co-

culture-induced decreases in cell viability were small, compared to TNFα-induced changes

(see Figure 6.1-6.3).

No significant differences between expected and actual co-culture viability were observed

from the first analysis conducted (see Figures 6.4 and 6.5), although unstimulated co-

culture viability was consistently lower than expected. Together, this suggests that

interactions between C17.2 and BV.2 cells could lead to an overall decrease in cell

viability. These decreases were observed in PDTC + TNFα and water + TNFα treated

groups, indicating that co-culture interactions appear to be treatment-dependent (see

Figures 6.14-6.15). The requirement for TNFα in these effects suggests that BV.2

activation state, and co-culture specific NF-κB activity, may be involved in determining

co-culture viability. Results from literature suggest that decreases in co-culture viability

may be due to C17.2 apoptosis, driven by microglial-derived factors. These factors could

include microglial-TNFα, previously reported to induce NPC apoptosis (Guadagno et al,

2013).

In summary, TNFα and PDTC treatment exerted different effects on C17.2 and BV.2

viability and apoptosis, strongly implicating NF-κB activity in the determination of cell

fate. Some of the results in this chapter were difficult to interpret as a time 0 reading was

not taken in viability and apoptosis assays: this time point should be included in future

experiments. Also, MTS signal saturation was observed in some high cell density BV.2-

containing cultures: this made some results unreliable. Results from lower cell density


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cultures provided reliable readings for viability and apoptosis here, but, in future, it would

be informative to calibrate cell number against MTS signal in BV.2 cultures.


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7. Discussion


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This project aimed to investigate NF-κB-mediated interactions between C17.2 and BV.2

cells in TNFα-treated cultures, as a model system for neural progenitor cell-microglial

interactions in neuroinflammation. The ultimate goal was to get a better understanding of

how single-cell NF-κB dynamics, can be related to differential gene expression and

thereby, cell survival.

Although many studies report on NF-κB on a population-level, single-cell level analysis

was selected as the better method for studying NF-κB, as this level of analysis has

provided valuable insight into the NF-κB system that have eluded population-level studies.

Arguably, one of the most important insights is the observation that specific aspects of NF-

κB dynamics within individual cells, such as amplitude and frequency of nuclear

translocations (Lee et al, 2014 and Ashall et al, 2009, respectively), determine downstream

gene expression profiles.

Initially, different methods of p65 observation in C17.2 and BV.2 cells were investigated

(Chapter 3). The investigation then progressed onto analysis of C17.2 and BV.2 p65

dynamics and C17.2 NF-κB transcriptional activity, in mono-cultures and co-cultures

(Chapter 4). Moving down the TNFα signalling network, mRNA expression was measured

in TNFα-stimulated mono-cultures and co-cultures: this analysis showed TNFα- and co-

culture-induced modulation of gene expression (Chapter 5). Finally, the outcome of TNFα

treatment and co-culture interactions on cell viability and apoptosis, with and without an

NF-κB inhibitor, was measured (Chapter 6).

Lentivirally transduced cells, expressing p65-eGFP, as the best model systems for

observation of p65 dynamics. Results showed BV.2-mediated inhibition of TNFα-induced

NF-κB activity and p65 nuclear translocations in C17.2 cells. Preliminary evidence for

C17.2 regulation of BV.2 p65 dynamics was also found; more emphasis has been placed

on observations made in C17.2 as a more complete analysis was conducted with these

cells.

Viability and apoptosis results showed that TNFα induced C17.2 apoptosis and suggested

BV.2-mediatedprevention of this TNFα-stimulated apoptosis. Interestingly, NF-κB

inhibition was also shown to induce C17.2 apoptosis and increase overall viability, which

may suggest promotion of cell proliferation.


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These data provided strong evidence for TNFα-induced, co-culture- and NF-κB-mediated

interactions between C17.2 and BV.2 cells occurring at the molecular, genetic and cellular

levels. These interactions were vital in determining the cell survival in response to TNFα,

an observation which is relevant to the study of neurodegenerative disease, where high

TNFα concentrations are known to mediate tissue damage (Cartier et al, 2005) and NPCs

have been shown to provide a therapeutic benefit (Park et al, 2002; Park et al, 2006; Teng

et al, 2002).

The results obtained from Chapters 3-6 will be discussed together here, in the context of

relevant literature, taking into consideration the advantages and problems with techniques

used in this thesis. This chapter will be concluded with some suggestions for relevant

future experiments.

7.2. NF-κB Activation and p65 Dynamics in C17.2 cells

The C17.2 cell line was selected as a model system to represent NPCs. These murine cells

display key defining characteristics of NPCs, including multipotency and high proliferative

capacity (Ryder et al, 1990). A trait that is more unique to C17.2 cells are their ability to

exert therapeutic effects when transplanted into disease models (Teng et al, 2002; Park et

al, 2002; Ourednik et al, 2002), via long-term immune regulation, as well as differentiation

to regenerate neuronal circuity (Snyder et al, 1992; Park et al, 2006). For these reasons, the

C17.2 cell line is considered to be a good model system for NPCs and also a useful tool for

studying beneficial immune regulation.

Although C17.2 cells are commonly referred to as NPCs, researchers have argued that

these cells are more ‘stem-like’. There is no common agreement on the definition of neural

progenitor cells and neural stem cells and consequently the two terms have been used

interchangeably in the literature (Seaberg and van der Kooy, 2003). For this reason,

literature on NPCs and neural stem cells (NSCs) has been referenced throughout this

thesis: it is recognised that C17.2 cells may share characteristics of both, depending on the

definitions adopted, as well as displaying their own unique features.

Despite their importance in regulating inflammation, studies that have observed NF-κB

activity in C17.2 cells have been few in number. Those that have reported on TNFα-

induced NF-κB activity in NPCs/NSCs have commonly done so via p65 immunostaining

methods. Using these methods, increased nuclear p65 presence in stimulated NSCs has


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been observed, 30 min after TNFα stimulation, compared to unstimulated cells (Widera et

al, 2006a).

Here, NF-κB activation was measured in C17.2 cells: NF-luc plasmid-transfected cells

were stimulated with TNFα doses of 10pg/ml up to 50ng/ml TNFα (Figure 3.5A). Peak

NF-luc induction was reached at ~3 h and 5 h after stimulation with doses ≤100pg/ml

TNFα and ≥1ng/ml TNFα, respectively. Turner et al (2010) reported peak NF-luc

induction times of 6 h with 10pg/ml and 4 h with 100pg/ml and 10ng/ml TNFα in SK-N-

AS cells. NF-luc induction with 10pg/ml TNFα was not observed in C17.2, suggesting that

these cells are less sensitive to low dose TNFα compared to SK-N-AS cells.

NF-luc induction is a good reporter for NF-κB activation over a period of hours. However,

due to the stability of luciferase, it cannot provide high temporal resolution data. To get

more information on the temporal profile of NF-κB activation, IκBα levels were measured

after 20ng/ml TNFα stimulation. Western blots showed almost complete degradation and

resynthesis of IκBα within 15 min and 60 min of TNFα stimulation, respectively (Figure

3.8). In HepG2 cells, ~70% of IκBα is degraded in response to 10ng/ml TNFα and newly

synthesised IκBα levels peak at 65 +/- 8% of the pre-stimulatory level after 137 +/- 5

minutes (Moss et al, 2012). IκBα degradation in C17.2 cells appears to be comparable to

that seen in HepG2 cells. However, return to pre-stimulation IκBα levels occurs more

rapidly in C17.2 cells than HepG2 cells. Use of a higher TNFα dose on C17.2 cells

(20ng/ml versus 10ng/ml) might explain the difference observed in IκBα resynthesis times:

Moss et al (2012) found that increasing TNFα dose increased IκBα resynthesis kinetics. An

alternative explanation is that C17.2 cells basally express lower levels of IκBα than HepG2

cells.

Having established NF-κB activation in C17.2 cells in response to TNFα, corresponding

p65 dynamics were observed using C17.2 (lenti) cells (expressing p65-eGFP; Figure

3.1A). In mono-cultures, these cells exhibited high amplitude initial nuclear p65

translocations, which peaked on average at 26 min after TNFα stimulation (Figures 4.2A

and 4.3A). In contrast to observations in other cell lines, few cells displayed subsequent

p65 nuclear translocations (Ashall et al, 2009; Turner et al, 2010; Paszek et al, 2010).

C17.2 cells were also stably-transfected with a p65-BAC to create clonal cell populations

expressing p65-DsRedXP: these clonal cell lines were evaluated as a model system for

studying NF-κB in the C17.2 cell line. Observation of single-cell p65 dynamics in these


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cells after TNFα stimulation revealed very little nuclear movement of NF-κB, as oppose to

the lentivirally-transduced C17.2 cells. Consistent with single-cell data, clonal cells

displayed dampened NF-luc induction, as well as maintenance of IκBα levels, after TNFα

stimulation. These results are similar to those obtained from murine cortical neuronal cells

in mixed cell cultures: neuronal cells display sustained levels of IκBα and little nuclear

movement of NF-κB, after TNFα stimulation (Listwak et al, 2013). This suggests that the

C17.2 p65-BAC stable cells endured a process of neuronal differentiation during the

cloning procedure: for this reason, work with these cells was discontinued.

Following mono-culture experiments, C17.2 (lenti) cells were seeded in 1:1 co-cultures

with untransfected BV.2 cells, in order to observe co-culture effects on C17.2 p65

dynamics. The following sections detail the results of co-culture microscopy experiments,

along with co-culture-induced changes in C17.2 viability.

7.3. NF-κB Dynamics to Cell Survival

7.3.1. BV.2 Prevents TNFα-induced C17.2 Apoptosis

Confocal microscopy experiments were performed with C17.2 (lenti) cells that were co-

cultured with BV.2 cells (at a ratio of 1:1; Figure 4.1). After TNFα-stimulation, co-cultured

C17.2 (lenti) cells exhibited a single phase of p65 nuclear translocation (Figure 4.2A). On

average, these translocations were of lower amplitude than those observed in mono-

cultured C17.2 (lenti) cells (3.3 versus 4.8 fold change in average nuclear NF-κB; Figures

4.2-4.3). Moreover, p65 nuclear translocations were not observed after the initial phase of

translocation in co-cultured C17.2 (lenti) cells, whereas mono-cultured cells displayed

lower amplitude subsequent p65 nuclear movements (Figure 4.2).

Higher amplitude p65 nuclear translocations in individual C17.2 cells after TNFα

treatment (Figure 4.2), were associated with increased apoptosis and decreased cell

viability 24h post-stimulation (Figure 6.1). Conversely, lower amplitude p65 responses in

co-cultured C17.2 cells (Figure 4.2) corresponded to levels of viability and apoptosis that

were similar to unstimulated controls (Figure 6.3).

In summary, co-cultured C17.2 (lenti) p65 dynamics may be functionally associated with

prevention of TNFα-induced apoptosis (Figures 4.2, 6.1 and 6.3). Direct links have yet to

be made between single-cell NF-κB dynamics and cell fate. However, population-level


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studies may elucidate the potential mechanism of cell fate regulation by NF-κB. Previous

studies conducted to observe differences in NF-κB localisation in TNFα-susceptible and

TNFα-resistant cell lines are particularly relevant and will be compared to data obtained in

this project.

Park et al (1996) modified the TNFα-resistant HepG2 cell line to create a cell line that was

sensitive to TNFα-induced apoptosis (HepG2 2.15). These cells were stimulated with

TNFα, nuclear NF-κB was measured (using EMSA) and downstream gene expression was

observed. The TNFα-induced NF-κB response in HepG2 cells resulted in gradual up-

regulation in the expression of NF-κB-dependent anti-apoptotic genes, Bcl-Xl and FLIP

between 0-120 min after TNFα-stimulation: downregulation of these genes was observed

in Hep 2.15 over the same time frame (Park et al, 1996). Expression of these genes was

associated with survival in HepG2 cells and apoptosis in HepG2 2.15, in response to

TNFα. In turn, cell fate was associated with differences in nuclear NF-κB: lower amplitude

changes in nuclear NF-κB were reported in HepG2 2.15, compared to HepG2 (~1.5 versus

~5; relative to pre-stimulation nuclear NF-κB). These differences in amplitude were

mirrored by mono-cultured and co-cultured C17.2 (lenti) cells: higher amplitude changes

in nuclear p65 were observed, after TNFα stimulation, in mono-cultured C17.2 (lenti),

compared to co-cultured cells.

Together, these data suggest that lower amplitude NF-κB nuclear translocations lead to

down-regulation of NF-κB-dependent anti-apoptotic factors, leading to apoptosis. NF-κB

activity also regulates the expression of many TNFR1-signalosome components that play a

role in apoptosis, including caspases, TRAFs and c-IAPs (Micheau and Tschopp, 2003;

Micheau et al, 2001). Future experiments in this area should focus on measurement of NF-

κB-dependent gene expression, with a focus on apoptotic and anti-apoptotic genes, at

different time points. Determining whether the C17.2 (lenti) p65 dynamics observed, and

the prevention of C17.2 apoptosis in co-culture, is dependent on C17.2-BV.2 cell contact

would also shed light on the molecular mechanisms involved in NF-κB-dependent cell

survival decisions. Analysis of microscopy experiments conducted here showed that some

C17.2 cells make physical contact with BV.2 in co-cultures. Interestingly, cell-contact

dependent increases in NF-luc expression were observed in 1:1 co-culture luminometry

experiments (Figure 4.13). The nature of this physical contact was not investigated (Figure

4.1). Previous literature has reported that NPCs and microglia can communicate via cell

surface receptor and ligand interactions, although focus has been placed on NPC ligand-


182

microglial receptor interactions (Liu et al, 2013a; Wang et al, 2007). These ligand-receptor

molecules include CD200 and its receptor CD200R, both of which are upregulated by

NPCs and microglia, respectively, in co-cultures (Liu et al, 2013). CD200 is an NF-κB-

dependent and TNFα-responsive gene, suggesting the possibility of its upregulation in

mono-culture studies conducted here. As yet, there are no studies reporting NF-κB

activation in response to CD200-CD200R interactions, however, there are reports that this

interaction prevents tissue-damaging activation of macrophages (Nathan and Muller,

2001). This is consistent with the idea that microglia increase NPC survival in co-culture

after TNFα stimulation (Figure 6.3).

Also, there is evidence to suggest that TGF-β may play a role in NPC-microglia crosstalk:

higher levels of TGF-β2 were found in co-cultures, compared to NPC and microglial

mono-cultures (Liu et al, 2013). Furthermore, the proportion of TGF-β1 expressing NPCs

was larger in co-cultures than in NPC mono-cultures (Liu et al, 2013). TGF-β1 has been

reported to decrease NF-κB activity, by upregulating IκBα expression, in unstimulated

immature B cells (Arsura et al, 1996). This offers another possible mechanism for the

inhibition of NF-κB in NPCs in co-culture after TNFα stimulation: microglia may be

promoting NPC expression of TGF-β1 which acts in an autocrine manner to inhibit NF-κB

nuclear translocation. Although, it should be noted that NanoString analysis conducted

showed that TGF-β1 was not upregulated in co-cultures after TNFα stimulation (Figures

5.2-5.5).

In summary, there are a few candidates offered by current literature as to how microglial

cells can modulate NF-κB activity in NPCs but, as yet, there are no thorough and

conclusive studies on this subject. It seems likely that the outcome of NPC-microglia

interactions is determined by the balance between cell-contact dependent mechanisms (e.g.

CD200-CD200R interactions) and cell-contact-independent mechanisms (e.g. secreted

molecules such as TGF). Transwell experiments showed elevated basal NF-κB activity in

co-cultured NPCs: this effect was dependent on contact between NPCs and microglia

(Figure 4.13). NanoString data showed that NPCs upregulate the expression of chemokines

such as Ccl2, Ccl5 and Ccl7, in response to TNFα (Figures 5.2-5.5), suggesting that in the

neuroinflammatory environment they can attract microglia and alter the balance between

cell-contact dependent and cell-contact-independent actions on NF-κB activity. This may

lead to differences in downstream cell fate i.e. cell survival vs. apoptosis. The ability to

attract microglia would also affect the neural progenitor:microglial cell ratio. As such,


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there is a deficiency in quantitative data on NPCs and microglia in vivo, but the results

displayed in this thesis (Figures 4.2, 4.5 and 4.8) highlight the importance of considering

cell ratios in vivo in healthy tissue, as well as inflamed tissue. This area should be

investigated in the future, in relation to findings reported here.

7.3.2. NF-κB Inhibition in Mono-cultures Induces C17.2 Apoptosis and Increases

Viability

Viability assays conducted with the use of PDTC (an NF-κB inhibitor) revealed that NF-

κB activity has a pleotropic role in C17.2. C17.2 mono-cultures and 1:1 co-cultures with

BV.2 cells were pre-treated with PDTC or water for 30 min, before stimulation with TNFα.

The viability readings from both PDTC- and PDTC + TNFα-treated cultures were

consistently higher than those from water + TNFα treated cultures (Figure 6.9). These

observations were consistent with data on p65 dynamics and corresponding viability and

apoptosis results (Figures 4.2 and 6.1). Surprisingly, preliminary apoptosis assays showed

that PDTC treatment increased apoptosis in C17.2 mono-cultures (Figure 6.14). Together,

these results strongly suggest that NF-κB inhibition in C17.2 mono-cultures induces

apoptosis and, markedly increases proliferation, to lead to an overall increase in culture

viability (Figures 6.9 and 6.16). In contrast with this observation, microglia may prevent

NPC apoptosis in 1:1 co-cultures: this result was associated with microglial-driven NF-κB

inhibition in NPCs, after TNFα stimulation. These contradictory findings can be explained

in a number of different ways, one of which involves interpretation of the viability results

obtained in this thesis (Figures 6.1-6.3 and 6.9). BV.2 cell growth was more rapid than

C17.2 growth in mono-cultures (see Figures 6.1 and 6.2) and viability results obtained

from BV.2 mono-cultures were similar to those obtained from 1:1 co-cultures (see Figure

6.3): these observations suggest that BV.2 cells dominated the 1:1 co-cultures and

therefore the lower apoptosis levels observed in these cultures may have been due to very

small C17.2 cell numbers.

Alternatively, the temporal profile of NF-κB inhibition after TNFα may contribute to the

differential effects in 1:1 co-cultures and PDTC-treated C17.2 mono-cultures. Western blot

analysis and NF-luc induction data from PDTC-treated C17.2 cultures show that PDTC

treatment may prevent early NF-κB activation (<1 h post-stimulation), whereas single-cell

analysis shows that microglial cells prevent later NF-κB activation (≥2 h post-stimulation)

and only dampen initial NF-κB nuclear translocations.


184

Previous analyses of NF-κB activity have been described using NSCs pretreated with

PDTC. These studies contradict the observations made here: basal and TNFα-induced NF-

κB activity promoted NSC proliferation (Widera et al, 2006a; Piotrowska et al, 2006).

These results may emphasise the importance of studying NF-κB dynamics at the single-cell

level, in order to understand cell fate decisions. Here, the population-level effects of PDTC

pre-treatment on TNFα-induced NF-κB activation was measured using Western blot

analysis of IκBα protein levels. There was no evidence of NF-κB activation in C17.2 cells

up to 2 h post-TNFα stimulation (Figure 6.7). However, luminometry experiments

conducted with NF-luc plasmid transfected cells showed delayed NF-luc induction in

PDTC + TNFα treated cells, compared to control TNFα-simulated cultures (Figure 6.8).

In summary, NF-κB inhibition was shown to induce apoptosis, but was also associated

with the prevention of apoptosis in co-cultured C17.2 cells (see Figures 6.3 and 6.16).

This duality in functional effect highlights the need for observations of NF-κB dynamics at

the single cell level. A key experiment for the future would be the observation of TNFα-

induced p65 dynamics in cells that have been pre-treated with PDTC. Comparing this data

with co-cultured C17.2 (lenti) p65 dynamics would inform on the relationship between p65

dynamic profiles and cell fate. Single-cell observations on the expression of NF-κB-

dependent apoptotic and anti-apoptotic factors would also greatly enhance progress in this

field of research. Particularly interesting results might arise from apoptosis assays with

PDTC-treated 1:1 co-cultures. The apoptotic effect of TNFα on C17.2 cells was negated by

BV.2 cells in 1:1 co-cultures (Figures 6.1 and 6.3). One could hypothesise that BV.2 cells

might prevent PDTC-induced apoptosis (Figure 6.14), possibly by altering p65 response in

C17.2 cells.

7.3.3. TNFα-induced BV.2 p65 Dynamics

The BV.2 cell line shows many properties of primary microglial cells. Classically-

activated BV.2 display anti-microbial activity, phagocytic behaviour and proteomic

changes which are comparable to primary microglia (Bocchini et al, 1992; Blasi et al 1990;

Henn et al, 2009). Also, classically-activated BV.2 cells can activate nearby astrocytes; an

action which is also performed by primary microglia (Henn et al, 2009). For these reasons,

BV.2 was selected as a suitable cell line representing microglia for studies of NPC-

microglial interactions. Data acquired on BV.2 cells will be discussed in relation to current

data available on primary microglia and other microglial cell lines.


185

The single-cell p65 dynamics of BV.2 cells have been described for the first time in the

present study. One previous study has reported population-level analysis of activated NF-

κB levels in 10ng/ml-TNFα stimulated BV.2 (Sheppard et al, 2010). This analysis reported

that NF-κB activation reached a peak at 25 min and 105 min post-TNFα stimulation. Here,

average peaks in nuclear p65 were observed at 30 min and 105 min after TNFα

stimulation. These data provide support for the use of BV.2 (lenti) to represent wild-type

BV.2 p65 dynamics.

On the single-cell level, BV.2 (lenti) exhibited p65 oscillations in response to TNFα, in

both mono-cultures and co-cultures. The average period of these oscillations was 108 min

and 63 min, respectively (Figures 4.15-4.16). Interestingly, the average timing of initial

peaks in nuclear p65 was earlier in co-cultures, compared to mono-cultures (22 min

compared to 30 min; Figure 4.17). In contrast to C17.2, these differences in p65 dynamics

were not correlated with differences in cell survival: BV.2 mono-cultures and co-cultures

displayed no changes in viability or apoptosis in response to TNFα (see Figures 6.10-6.11).

This shows that NF-κB regulation of cell fate is cell-type specific between these cell lines.

TNFα is known to induce p65 oscillations, with periods of around 100 min, in non-neural

cell lines (Ashall et al, 2009; Turner et al, 2010; Paszek et al, 2010). The faster oscillations

seen in BV.2 (lenti) co-culture (63 min; see Figures 4.15-4.16) have interesting

implications for C17.2 regulation of BV.2 activation status, as NF-κB activity had been

implicated in microglial activation (Colton, 2009; Saijo and Glass, 2011; Liu et al, 2013b).

However, co-culture data observing p65 in BV.2 (lenti) cells was only obtained from a

single microscopy experiment. More replicates would be required before any conclusions

could be reached on the C17.2 regulation of BV.2 p65 dynamics. Factors that might

influence oscillation period and p65 peak timings will be discussed briefly next, before

progressing on to a plan for future experiments.

Sheppard et al (2010) modified a mathematical model, which was published by Ashall et al

(2009), to reproduce TNFα-induced changes in population level NF-κB activation in BV.2.

They concluded that NF-κB activation timing was strongly influenced by IKK-dependent

degradation of IκBα and, thereby, factors that regulate IKK activation. This could suggest

that the expression of the TNFR1-signalosome components or A20-mediated inhibition of

IKK activation might be involved in the delay in nuclear p65 peak timing observed in co-

cultured BV.2 (lenti) cells.


186

The parameters that influence NF-κB oscillation period have been investigated using

mathematical models, many of which incorporated single-cell data on non-neural cell lines.

Nelson et al (2004) conducted sensitivity analysis of the parameters in a mathematical

model created by Hoffmann et al (2002). It was found that two parameters were

particularly important in determining oscillation dynamics: IKK deactivation rate and the

rate of IκBα nuclear import. Decreasing the rate of IKK deactivation and increasing the

rate of IκBα nuclear import could shorten the period. The Hoffmann et al (2002)

mathematical model was based on results from IκB protein-deficient cells, so caution

should be exercised when applying this model to BV.2, although Sung et al (2009)

highlighted the same parameters from their mathematical model which was based on

MEFs.

7.4. Future Experiments

Results obtained in this thesis provide evidence for: the role of differential NF-κB

dynamics in regulating C17.2 cell fate and; BV.2 regulation of C17.2 cell fate, possibly

through modulation of the C17.2 NF-κB response. However, associations between the two

were indirect and there were issues with the experimental design and techniques used.

These will be discussed here and used to suggest improved future experiments to advance

the data described in this thesis.

One issue with the apoptosis and viability assays conducted here was the lack of a time 0

reading (Figures 6.1-6.3 and 6.9-6.11). In retrospect, initial apoptosis/viability of the cells

should have been measured when they were seeded in the experimental dish. This would

have provided extra data on culture growth between 0 and 24 h. Also, any changes in co-

culture apoptosis/viability over this time period would have been captured. In theory, co-

culture-induced changes in viability or apoptosis may have occurred, independent to

TNFα-treatment, between 0 and 24 h. Since, viability/apoptosis readings from TNFα-

stimulated cultures were compared to readings from unstimulated cultures, differences

caused by co-culturing cells would have been masked. Time 0 readings in future

experiments will highlight any cell fate-determining co-culture interactions.

Another problem with viability results was saturation of the MTS signal in higher cell

density cultures. This was observed at 48 h and 72 h time points in experiments with BV.2

cells, either in mono-cultures or co-cultures (Figures 6.2, 6.3, 6.10 and 6.11). These results

were unexpected, as the manual for the viability kit (obtained from the supplier; see


187

Chapter 2), claimed that the procedure was suitable for use with up to 2.5x105 cells per

well. As 3000 BV.2 cells per well were seeded for the assays conducted in the present

study, it is unlikely that cell numbers exceeded 2.5x105 cells per well, even considering the

rapid proliferation rate of BV.2 cells. This highlights the importance of calibrating BV.2

cell number against MTS absorbance readings, to ensure that signal saturation is not a

problem in future viability experiments.

As well as viability and apoptosis assays, proliferation assays are required to investigate

some results obtained with PDTC. NF-κB inhibition by PDTC-treatment led to increases in

viability across all culture conditions (Figure 6.10-6.11), but most notably, in C17.2 mono-

cultures (Figures 6.9). Surprisingly, PDTC treatment also increased C17.2 apoptosis,

measured at 24 h post-treatment (Figure 6.14). This suggests that NF-κB activity inhibits

C17.2 proliferation.

Also, in future experiments co-culture ratios should be optimised to maximise co-culture

effects, making them easily detectable. Live-cell luminometry experiments in this project

have set a foundation for this work. These experiments were performed using NF-luc

plasmid-transfected C17.2 cells, seeded in different co-culture ratios (Figure 4.5). BV.2

inhibition of TNFα-induced NF-κB transcriptional activity was not observed in 1:2

(C17.2:BV.2) co-cultures, but this effect was observed in 1:4 co-cultures. Also, lower

TNFα doses (500pg/ml, 1ng/ml and 10ng/ml) were used in these experiments, to enhance

co-culture-induced decreases in NF-κB transcriptional activity (compared to 20ng/ml

TNFα in microscopy experiments). Considering these results, microscopy experiments in

future could use high ratio co-cultures (1:4) and lower TNFα doses: this could enhance co-

culture effects on C17.2 viability/apoptosis. Combining these experiments with NF-κB

inhibitors would allow assessment of NF-κB contribution to C17.2 cell fate.

Endpoint luminometry experiments with transwells showed that C17.2 NF-luc inhibition

by BV.2 occurred independently of cell contact (Figure 4.11). From this result, it was

concluded that BV.2 inhibition of TNFα-induced NF-luc expression was due to soluble

autocrine/paracrine factors in co-cultures. Multiplex ELISA assays in future would help to

determine potential candidates for mediating C17.2-BV.2 communication and modulating

NF-κB dynamics. These experiments could be combined with single-cell imaging of

fluorescent protein tagged-Annexin V labelling (Moulding et al, 2000) and p65 dynamics,

thereby enabling NF-κB dynamics to be correlated with cytokine secretions and cell

survival/apoptosis.


188

In parallel to the above experiment, a recently developed microfluidics procedure could be

used to measure the expression of up to 96 genes, in one sample, after TNFα stimulation

(Kellogg et al, 2014). This analysis would not be conducted on live cells, but with the

selection of a few key time points, it would complement the results from Annexin-V

experiments. The NanoString assay conducted during the course of this project (Chapter 5)

was focussed on the expression of inflammatory factors. It might be more informative to

focus on the expression of apoptotic and anti-apoptotic factors in future experiments.

An important goal of future microscopy experiments should be the simultaneous

observation of NF-κB dynamics in co-cultured BV.2 (lenti) and C17.2 (lenti) cells. This

would halve the number of microscopy experiments required for full datasets and,

therefore, save time. Since both of the lentivirally transduced cell lines expressed p65-

eGFP, it was not possible to confidently distinguish between them in co-cultures.

Therefore, co-culture microscopy experiments detailed in this thesis were conducted with

one p65-labelled cell-type and another untransfected cell population (e.g. BV.2 (lenti) +

untransfected C17.2; Figures 4.1 and 4.14). This was due to the limited availability of other

fluorescently-tagged p65 constructs, a problem which has since been remedied in the

laboratory. Now, with a whole range of p65 constructs available, BV.2 or C17.2 cells can

be lentivirally transduced with a non-eGFP construct which would enable them to be

observed simultaneously.

Much of the focus in this chapter has been on C17.2 p65 dynamics. This is due to the

preliminary nature of the data obtained on BV.2 (lenti) p65 dynamics. More specifically,

BV.2 (lenti) cells displayed faster oscillations in co-culture, than in mono-cultures, but

these results were obtained from only a single microscopy experiment (Figure 4.15-4.16).

Further co-culture experiments should be conducted with BV.2 (lenti) to either discount or

confirm the preliminary findings reported here.

7.5. Concluding Remarks

In summary, the results detailed in this thesis have provided a solid foundation for

establishing NF-κB-mediated interactions between C17.2 and BV.2 cells. Evidence of

these interactions was found at the molecular, genetic and cellular level. Combining data

from these different levels of analysis has led to new hypotheses on NF-κB dynamics in

these cells: 1) differential NF-κB dynamics in C17.2 is involved in cell fate decisions and;


189

2) BV.2 cells inhibit TNFα-induced C17.2 p65 dynamics, via paracrine factors, and

thereby influence C17.2 fate.

The findings described are the first of their kind: paracrine interactions in the field of NF-

κB dynamics are largely uninvestigated. These findings highlight the importance of

studying NPC-microglial interactions. These results are particularly important given the

role that these cells play in the neuroinflammatory process and, thereby, in diseases such as

Alzheimer’s disease. Future experiments using confocal microscopy techniques,

microfluidic Q-PCR, multiplex ELISA and single-cell apoptosis imaging will help to test

the hypotheses proposed above and advance the field of NF-κB-mediated paracrine

interactions.

A long term objective would be to understand these interactions and their dynamics in

primary NPC and microglia. Our lab now has p65-DsRed and IκBα-eGFP-expressing

transgenic mouse lines that are proving to be useful tools for studies of NF-κB dynamics in

a range of cells and tissues. Therefore, in the future, it may be possible to use the mouse

lines to move onto studying neuroinflammatory interactions in primary cells. In addition,

the transgenic mouse lines may allow in vivo physiological studies of the role of NF-κB in

neuroinflammation.


190

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