conditioning murine b cells for immunoglobulin a...

Conditioning Murine B Cells for

Immunoglobulin A Production In vitro

by

Wilford Goh

BSc Biomedical Science

This thesis is presented for the Honours degree in Biomedical Science

at Murdoch University

School of Veterinary and Biomedical Sciences

Murdoch University

Western Australia

November 2012

Conditioning Murine B Cells for Immunoglobulin A Production

ii

Declaration

I declare this thesis is my own account of my research and contains as its main

content, work which has not been previously submitted for a degree at any tertiary

educational institution.

Wilford Goh


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Abstract

The respiratory mucosa is continuously exposed to a myriad of pathogens and

allergens that are inhaled during respiration. B cells of the immune system produce

immunoglobulin A (IgA) that protects the respiratory mucosa from inhaled

pathogens and allergens. IgA is produced after naïve B cells undergo activation,

proliferation and differentiation, developing into antibody producing plasma cells.

The process that facilitates IgA production as B cells develop into plasma cells is

known as class switch recombination (CSR).

Factors favouring IgA have been determined by in vitro studies of CSR. These

established two cytokines, IL-21 and TGF-β1, to be important factors for IgA

production. Prior studies with human naïve B cells that were cultured with IL-21 and

TGF-β1, in addition to anti-IgM, anti-CD40, IL-2 and CpG, developed into

precursors of IgA producing plasma cells (plasmablasts) that possessed mucosal

homing capabilities: a process termed B cell conditioning.

The aim of this project was to establish whether the same factors were active on

murine naïve B cells in order to eventually test the in vivo therapeutic potential of B

cell conditioning. A protocol was optimised for CD19+CD27

- naïve B cell isolation

from mouse spleen and cell division, which is crucial for IgA CSR, by CFSE

labelling and flow cytometry. The number of divisions predicts the generation of IgA

mucosal homing plasmablasts in vitro. Cells were found to have undergone 5

divisions after 7 days in culture suggesting that cells had undergone a sufficient

number of divisions for CSR and IgA production. Attempts were made to quantitate

IgA production in culture supernatants, however evidence for the generation of these

cells by IgA production remains to be confirmed. The results of this project provide


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preliminary evidence that murine naïve B cells can be conditioned in vitro for IgA

production, with potential for homing to, and protection of, mucosal surfaces in vivo.


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Table of Contents

Declaration ii

Abstract iii

Index to Figures x

List of Abbreviations xii

Acknowledgements xiv

Chapter 1. Literature Review and Introduction 1

1.1 Organisation of the Respiratory Tract 2

1.2 Respiratory Mucosal Protection From Infections and Allergens 2

1.3 Physical and Chemical Protection of the Respiratory Mucosa 3

1.4 Immunological Protection of the Respiratory Mucosa 5

1.4.1 Innate Mucosal Responses 5

1.4.2 Adaptive Mucosal Immune Responses 6

1.5 Immune Sites of the Respiratory Mucosa 9

1.5.1 Inductive Sites 10

1.5.2 Effector Sites 13

1.6 Naïve B Cell Development and Maturation into Mucosal Plasma Cells 14

1.6.1 Development of Naïve B Cells 14

1.6.2 Naïve B Cell Activation 15

1.6.2.1 T Cell Independent Activation 15

1.6.2.2 T Cell Dependent Activation 16


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1.6.3 Germinal Centre Reactions Generate Plasmablasts 17

1.6.3.1 Somatic Hypermutation 18

1.6.3.2 Class Switch Recombination 18

1.6.4 Plasmablasts Migrate to Effector Sites and Terminally Differentiate

into Plasma Cells 19

1.7 IgA is Crucial for Respiratory Mucosal Immunity 20

1.7.1 Physical and Structural Properties of IgA 20

1.7.2 Secretion of Dimeric IgA onto the Respiratory Mucosa 21

1.7.3 Mechanisms of Pathogen Removal by Dimeric and Secretory IgA at

the Respiratory Mucosa 23

1.7.3.1 Immune Exclusion 23

1.7.3.2 Intraepithelial Neutralisation 24

1.7.3.3 Excretion of Immune Complexes 24

1.8 Conditioning of B cells for Immunoglobulin A Production 24

Chapter 2. Aims and Hypothesis 26

Chapter 3. Materials and Methods 28

3.1 Animal Agistment 28

3.2 Euthanasia and Tissue Collection 28

3.3 Naïve B cell Extraction and Enrichment 29

3.3.1 Preparation of Splenocyte Suspension 29

3.3.2 Enrichment of Splenocyte Suspension for Naïve B Cells 31

3.4 Naïve B Cell Labelling and In vitro Conditioning 34


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3.4.1 CFSE Labelling for Tracking Cell Division 34

3.4.2 In vitro B Cell Conditioning 34

3.4.3 Sample Collection and Storage 36

3.5 Flow Cytometric Analysis of Labelled Cells 37

3.5.1 Instrumentation and Analysis Software 37

3.5.2 Optimisation of FACS Staining by Titration 38

3.5.2.1 Fluorochrome-conjugated Monoclonal Antibodies 38

3.5.2.2 Biotin-conjugated Monoclonal Antibody 38

3.5.2.3 LIVE/DEAD Near-IR Fixable Cell Stain 39

3.5.2.4 CellTrace CFSE Cell Proliferation Stain 39

3.5.3 Staining Panels 40

3.5.3.1 Enrichment Staining 40

3.5.3.2 Proliferation Staining 41

3.5.4 Controls and Compensation 41

3.5.5 Early Cell Gating Strategy 41

3.6 IgA Enzyme-linked Immunosorbent Assay 42

3.6.1 ELISA Optimisation and Controls 42

3.6.2 Coating and Blocking of Microplates 43

3.6.3 Standard, Sample and Control Incubation 43

3.6.4 IgA Detection and Colour Development 44

3.6.5 Absorbance Measurement and Data Analysis 44

3.7 Statistical Analysis and Graphing Software 45


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Chapter 4. Results I: Experimental Optimisation 46

4.1 Titrations 46

4.1.1 Monoclonal Antibody Titres 48

4.1.2 Viability Dye Titre 51

4.1.3 CFSE Titre 53

4.2 Compensation Matrix for Enrichment and Proliferation Panels 54

4.3 ELISA Optimisation 55

4.4 LPS Titration 57

Chapter 5. Results II: Experimental Findings 60

5.1 Magnetic Depletion Yielded High Naïve B Cell Purity of ≥93% 60

5.2 Modified Separation Protocol Removed CD27+ Subpopulations to Different

Extents 63

5.3 Trends in Cell Viability Revealed Extent of Cell Proliferation 65

5.4 Comparing Cell Divisional Responses Between Different Conditions 68

5.5 Majority of Conditioned Cells Underwent 3 Rounds of Division 72

Chapter 6. Discussion 75

6.1 Magnetic Isolation for Obtaining High Naïve B Cell Purity 75

6.2 Naïve B Cell Activation 77

6.2.1 TD Activation 77

6.2.2 TI Activation 78

6.3 Cell Proliferation 78

6.4 IgA Production 82


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6.5 Immunophenotyping for Better Resolution of B Cell Populations 83

6.6 Refining CFSE Labelling for Better Determination of Cell Division 85

6.7 Future Directions 86

6.8 Conclusion 87

References 88

Appendix A: Reagent List and Preparatio 97

Appendix B: Animal Monitoring Sheet 101


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Index to Figures Figure 1.1 Mucosal surfaces of the body. .................................................................... 3

Figure 1.2 Mucociliary escalator of the respiratory tract. ............................................ 4

Figure 1.3 CD4+ T cell subsets. ................................................................................... 8

Figure 1.4 Inductive and effector site of mucosa-associated lymphoid tissue. .......... 10

Figure 1.5 Structural organisation of a lymph node. .................................................. 11

Figure 1.6 Structural organisation of the mucosa-associated lymphoid tissue. ......... 13

Figure 1.7 Structure of IgA. ....................................................................................... 21

Figure 1.8 Structure of dimeric IgA. .......................................................................... 22

Figure 1.9 Release of secretory IgA (SIgA) into the airway. ..................................... 23

Figure 3.1 Extraction procedure of splenocytes from mouse spleen. ........................ 30

Figure 3.2 Isolation of naïve B cells by magnetic depletion. ..................................... 32

Figure 3.3 Naïve B cell isolation protocol. ................................................................ 33

Figure 3.4 Cell and culture supernatant collection protocol. ..................................... 37

Figure 3.5 Early cell gating strategy. ......................................................................... 42

Figure 4.1 PE-CD19 MAb titration. ........................................................................... 48

Figure 4.2 APC-CD27 titration. ................................................................................. 50

Figure 4.3 Secondary control for APC-CD27. ........................................................... 51

Figure 4.4 Titration of viability dye. .......................................................................... 52

Figure 4.5 CFSE titration. .......................................................................................... 53

Figure 4.6 Standard curves for identical mouse IgA standards generated before and

after ELISA optimisation. .......................................................................................... 56

Figure 4.7 Cross reactivity with IgG1 and media interference. ................................. 57

Figure 4.7 LPS titration. ............................................................................................. 59

Figure 5.1 Naïve B cell purity before and after isolation. .......................................... 61


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Figure 5.2 Gating based on CD19 and CD27 FMO control. ..................................... 62

Figure 5.3 The average naïve B cell purity before and after enrichment. .................. 62

Figure 5.4 Removal of CD27+ cells after enrichment. .............................................. 64

Figure 5.5 Viability of cells cultured in different conditions for 12 days. ................. 66

Figure 5.6 Viability of cells cultured in different conditions for 7 days. ................... 67

Figure 5.7 Estimation of cell division by analysis of CFSE fluorescence intensity. . 69

Figure 5.8 Comparison of % cell divided and proliferation index for different culture

conditions at day 3. .................................................................................................... 71

Figure 5.9 Changes in the number of cell divisions for cells cultured over 12 days

and 7 days in condition 4. .......................................................................................... 74


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List of Abbreviations

2-ME 2-mercaptoethanol AID Activation-induced deaminase AMDCs Airway mucosal dendritic cells APC Allophycocyanin ANOVA Analysis of variance ARC Animal Resources Centre BCR B cell receptor BP Band pass BER Base excision repair BALT Bronchus-associated lymphoid tissue CFSE Carboxyfluorescein CCR C-C chemokine receptor CD40L CD40 ligand CSR Class switch recombination CD Cluster of differentiation CXCR CXCR4

CpG Cytosine phosphate-guanosine dinucleotide motif

CTL Cytotoxic lymphocyte DC Dendritic cells DNA Deoxyribonucleic acid DMSO Dimethylsulphoxide DPBS Dulbecco's phosphate buffered saline ELISA Enzyme-linked immunosorbent assay FMO Fluorescence minus one FACS Fluorescent activated cell sorting FAE Follicle associated epithelium FDC Follicular dendritic cells FSC Forward scatter characteristic Fab Fragment antigen-binding Fc Fragment crystallisable GIT gastrointestinal tract GC Germinal HI FBS Heat inactivated fetal bovine serum

CH Heavy chain HSC Hematopoietic stem cell HRP Horse radish peroxidase

FcαR IgA Fc receptors

Ig Immunoglobulin IL Interleukin IL-2R Interleukin-2 receptor IL-21R Interleukin-21 receptor IEL Intraepithelial lymphocytes kDa Kilo dalton LPS Lipopolysaccharide LN lymph node

http://en.wikipedia.org/wiki/CXCR4


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MHC II Major histocompatibility complex class II MZ Marginal zone M cell Microfold cell MAb Monoclonal antibody MALT Mucosal-associated lymphoid tissue NALT Nasopharynx-associated lymphoid tissue NK cells Natural killer cells Near-IR Near-infrared NFκB Nuclear factor kappa B PE Phycoerythrin PB Plasmablast pIgR Poly-immunoglobulin receptors RPMI Roswell Park Memorial Institute SC Secretory component SIgA Secretory IgA SSC Side scatter characteristic SSB Single-strand break SHM Somatic hypermutation SEM standard error of mean SA Streptavidin TD T cell dependent TI T cell independent

TFH T follicular helper cell

Treg T regulatory cell

TH T helper cell TMB Tetramethylbenzidine TLR Toll-like receptor TβR Transforming growth factor β receptor TGF-β1 Transforming growth factor β1 UNG Uracil-DNA glycosylase

VH Variable binding site of heavy chain

VL Variable binding site of light chain αtp α tail-piece


xiv

Acknowledgements

What a journey it has been. I am now ready to embark on another journey, my

holiday that is. Before this journey officially concludes, I would like to thank the

many people who have made this journey bearable. My supervisors Sarah, Phil, Deb

and John are top of the list. I have learnt so much from our interactions. They have

granted me all the freedom I could ever ask for as a honours student, thus allowing

me to enjoy the entire “show”.

Besides the official supervisors, I also have many surrogate supervisors to thank.

These people have seen the best and worst of me. We’ve had good laughs at my best,

although their ears bled and suffered at my worst. Nevertheless, I claim no part in

their loss of hearing in the future. Tracey and Michelle the flow gurus, Jenny the jack

of all trades, and Jay the wise man, have all imparted valuable skills and knowledge

to me.

Of course, there are the other surrogate supervisors who have had their fair share of

ear bleeds and migraines due to my winging. These people have been so

overwhelmingly positive and encouraging that my own pessimism (or in my defence,

just being down to earth) had to abandon me. The outcome, a confident me who can

make my own decisions (slowly getting there) and stand up for myself, which I have

been doing since I officially became bipedal. These people, in no particular order,

other than wonderous ways a sleep deprived brain works, are Mum, Ivan, Sian,

Catherine, Rebecca, Kathryn, Narelle, Chelsea, Penny, Maria, John and Susan.

Thanks guys, for being here with me on my journey.

Chapter 1. Literature Review and Introduction

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The lung is constantly exposed to a myriad of pathogens and allergens that are

inhaled during respiration. Respiratory diseases develop when these pathogens

breach the protective mechanisms of the lung and successfully establish infections

(Snelgrove et al., 2011). Acute infections of the lower respiratory tract are the

leading cause of childhood mortality and morbidity (Lim et al., 2006). These

respiratory infections are caused by viruses (e.g. influenza virus) and bacteria (e.g.

Streptococcus pneumonia and Haemphilus influenzae), which often result in the

development of bronchiolitis or pneumonia (Lim et al., 2006). Antibiotics are

commonly used as a pharmacological treatment of bacterial respiratory infections.

However, the development of multiple antibiotic resistant bacteria is on the rise. For

instance, 53.2% of S. pneumoniae strains in Asia are resistant to three of the

following antibiotics: β-lactams, macrolides, tetracyclines, phenicols, folate-pathway

inhibitors and quinolones (Lim et al., 2006). Consequently, there is a growing need

for the development of alternative forms of protection against respiratory infection.

Prophylactic vaccination, which induces immune protection by the production of

antibodies (Tamura and Kurata, 2004), is one such alternative strategy for tackling

respiratory infection.

In this paradigm, antibodies that protect against viruses and bacteria are produced by

plasma cells, an immune cell type within the body. Antibodies confer protection

against viruses and bacteria by binding physically to them, thereby preventing

contact between these pathogens and the lung, which is essential for the

establishment of antibodies (Brandtzaeg, 1992). A recent report documenting

successful generation of human antibody producing plasma cells in vitro (Dullaers et


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al., 2009) has provided support for the therapeutic application of these cells in the

treatment of the respiratory diseases. Establishing a similar protocol for generating

murine plasma cells in vitro was the overall focus of this project.

1.1 Organisation of the Respiratory Tract

The respiratory tract can be divided into two distinct regions: the conducting zone

(airway passages) and respiratory zone (lung parenchyma). The conducting airways

begins at the nasal passage and terminate at the terminal bronchioles (Pilette et al.,

2001). The primary function of the conducting airways is to condition inhaled air for

gas exchange in the parenchyma. Air passing through the conducting airways is

warmed, moistened, and filtered for foreign particulates and microbes before

entering the respiratory bronchioles, alveolar ducts, alveolar sacs and alveoli that

make up the lung parenchyma (Hyde et al., 2009). Under homeostatic conditions, the

normal function of the conducting airways and, alveolar macrophages (pathogen

engulfing immune cells) in the lung parenchyma, maintain a sterile environment

within the respiratory tract.

1.2 Respiratory Mucosal Protection From Infections and Allergens

The respiratory mucosa covers the surface of the lungs, nasal and oral cavity. At

approximately 100 m2

in adult humans, it forms the second largest mucosal surface

within the body after the gastrointestinal tract (GIT) (Figure 1.1). Given the absolute

requirement for constant gas exchange (between 1000 and 2100 litres a day) the

respiratory mucosa becomes constantly exposed to the external environment. As such,

the respiratory mucosa is a primary portal of entry for many potentially infectious

pathogens that are inhaled during respiration (Wanner et al., 1996). The risk of

infections is greatly augmented given the rich vascularization of the lungs. In order


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to facilitate unimpeded gas exchange during respiration, many blood vessels are

situated in close proximity to the external environment, becoming potential channels

for pathogen infection and dissemination (Holt et al., 2008). Aside from infections,

there is also the potential of developing allergic responses (i.e. asthma) to common

allergens (Sato and Kiyono, 2012). These risks are kept in check by physical,

chemical and immunological mechanisms along the respiratory tract. Efficient

mucosal protection requires complex interactions and coordination between these

mechanisms.

Figure 1.1 Mucosal surfaces of the body. These surfaces are in direct contact with the external

environment and are constantly exposed to foreign particles and pathogens. The sterile internal

environment of the body is shaded in blue.

1.3 Physical and Chemical Protection of the Respiratory Mucosa

The respiratory mucosa, comprised of an epithelial layer and an underlying layer of

loose connective tissue known as the lamina propria, serves as an anatomical barrier

that separates the sterile internal milieu from the external environment (Reznik,

1990). Adhesion complexes (tight junctions, adherens junctions and desmosomes)

between epithelial cells maintain epithelial integrity (Figure 1.2), thereby preventing


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paracellular (between cell) passage of foreign antigens across the mucosa (Anderson

and Van Itallie, 1995). However, the efficacy of mechanical protection decreases as

ciliated pseudostratified epithelia in the conducting airways transition into simple

squamous epithelia in the lung parenchyma to facilitate gas exchange (Tam et al.,

2011). As such, protection at the level of the lung parenchyma relies more heavily on

immunological aspects of the respiratory mucosa (Holt et al., 2008).

The mucociliary escalator is another component of physical protection. It lines the

entire surface of the trachea and parts of the bronchial tree (conducting airways) and

is comprised of a mucous layer into which beating cilia are projected from the

surface of underlying epithelial cells (Wanner et al., 1996). The mucous layer traps

inhaled pathogens and allergens while constant ciliary motion transports them away

from the lungs (Figure 1.2). This ongoing process of mucous secretion and transport

is known as mucociliary clearance and ensures the continuous removal of inhaled

pathogens and allergens, thus maintaining sterility within the airways (Kim et al.,

1997).

Figure 1.2 Mucociliary escalator of the respiratory tract. Bacteria in the airways become trapped

in the mucous layer and removed by beating cilia. Adhesion complexes hold adjacent respiratory

epithelial cells together to prevent pathogen invasion and subsequent infection.


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Various chemicals released by specific cells within the respiratory mucosa

complement the mucosal protection conferred by physical mechanisms.

Antimicrobial peptides are released into the lumen of the airways and mucous layer

by respiratory epithelial cells in response to the presence of bacteria, yeasts, fungi

and viruses. Comprised mainly of small cationic molecules, the three important

classes of antimicrobial peptides are defensins, cathelicidins and histatins. The

primary function of these peptides is to induce cell death by destabilising the

pathogen membrane (reviewed by De Smet and Contreras, 2005).

1.4 Immunological Protection of the Respiratory Mucosa

Respiratory mucosal immunity is mediated by numerous immune cell types. The

immune responses mediated by these cells ensure effective surveillance and

pathogen removal, maintaining immunological homeostasis within the lungs (Holt et

al., 2008). All immune responses generated against pathogens and allergens

encountered at the respiratory mucosa can be broadly classified into innate and

adaptive mucosal responses.

1.4.1 Innate Mucosal Responses

The primary role of innate mucosal responses is to remove common pathogens

efficiently. As such, the responses tend be less pathogen specific, but are initiated

more quickly than adaptive responses. Complement proteins, macrophages,

granulocytes (neutrophils, eosinophils and basophils), mast cells, dendritic cells

(DCs) and natural killer (NK) cells are the primary mediators of innate mucosal

responses. Respiratory epithelial cells have also been found to initiate innate mucosal

immune responses (reviewed by Parker and Prince, 2011). The primary responses,

mediated collectively by these cells include cell lysis, opsonisation, phagocytosis,


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immune cell recruitment and inflammation (Abrutyn et al., 1977; Gin et al., 1984;

Watford et al., 2000; Carroll, 2004; Bolger et al., 2007; Aleshin et al., 2012).

Resident DCs are antigen presenting cells in the respiratory mucosa, which are

known as airway mucosal DCs (AMDCs). These cells assume an additional role of

initiating adaptive immune responses. After internalising pathogens and processing

them into antigenic peptides, AMDCs migrate to regional lymph nodes within the

lungs. The peptides are then presented to T cells of the adaptive immune system,

which then proceed on to elicit various adaptive responses (Jahnsen et al., 2006). As

such, AMDCs in general are regarded as an essential link between innate and

adaptive respiratory mucosal immune responses (reviewed by Hammad and

Lambrecht, 2011).

1.4.2 Adaptive Mucosal Immune Responses

The adaptive mucosal immune system reinforces responses initiated by the innate

immune system. Although both systems are activated simultaneously upon antigen

encounter, the adaptive immune system takes a longer time to mount its specific

immune responses. These responses are initiated by antigen presentation by DCs that

have trafficked antigen to secondary lymphoid tissues such as the lymph nodes (LNs).

Macrophages, epithelial cells and other DC subsets can also initiate adaptive mucosal

responses by antigen presentation, albeit to a lesser degree compared to AMDCs.

Adaptive mucosal immune responses are mediated by B and T cells that develop

from precursor cells in the bone marrow and thymus respectively. These cells have

high pathogen specificity and are thus able to remove pathogens more effectively.

Compared to innate responses, adaptive responses take longer to initiate due to the

time required for proliferation of antigen-specific B and T cells (clonal expansion)


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following antigen presentation in secondary peripheral lymphoid tissues (reviewed

by Medzhitov, 2007).

Immune Function of Effector T Cells

Effector T cells are cells that have recognised cognate antigens presented by DCs and

undergone clonal expansion and differentiation. Most effector T cells can be

categorised into two broad classes, CD8+ and CD4+ T cells. CD4+ T cells can be

further categorised into several functional subsets based on the release of different

but overlapping cytokines (small soluble proteins secreted by cells) and/or the

expression of surface markers. The CD4+ T cell subsets include T helper (TH) 1 cells,

TH2, TH9, TH17, regulatory T (Treg) cells and T follicular helper (TFH) cells

(reviewed by Nakayamada et al., 2012) (Figure 1.3).

The CD4+ effector T cells described above control almost all of the known effector

mechanisms of the adaptive mucosal immune response (reviewed by Bennett et al.,

1998; Luckheeram et al., 2012). In contrast, CD8 effector T cells, also known as

cytotoxic T cells or cytotoxic lymphocytes (CTLs), participate directly in adaptive

mucosal responses. These cells are able to distinguish host cells that have been

infected by viruses or intracellular pathogens, removing only the infected cells by

inducing apoptosis (reviewed by Russell and Ley, 2002).


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Figure 1.3 CD4+ T cell subsets. Each subset produces a unique profile of cytokines and are

responsible for mediating a range of adaptive responses.

CD4+ T cells provide essential signals known as cytokines that influence the

response of other immune cells, thereby indirectly mediating a wide range of

adaptive mucosal responses. The adaptive responses mediated by TH1 and TH2 cells

target bacterial and parasitic infections respectively (Yap et al., 2000; Pesce et al.,

2006). While TH9 and TH17 cells enhance inflammatory responses (reviewed by

Korn et al., 2009; Wilhelm et al., 2011), Treg cells mediate responses that dampen

inflammation (reviewed by Fontenot and Rudensky, 2005). TFH cells are specialised

at mediating humoral immunity, immunity that is conferred by the function of

antibodies. This is achieved indirectly by the production of cytokines that direct

antibody production by B cells (reviewed by King et al., 2008)


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Function of Effector B Cells

Effector B cells within the respiratory mucosa are termed mucosal plasma cells,

which produce antigen specific antibodies that mediate pathogen removal from

mucosal sites (Shapiro-Shelef et al., 2003). Mucosal plasma cells can produce

antigen specific antibodies of various isotypes that include immunoglobulin (Ig) M,

IgD, IgG, IgE and IgA. These isotypes are produced and distributed in varying

abundance within the respiratory mucosa, performing distinct immune functions that

form part of the adaptive mucosal immune responses (Brüggemann et al., 1987;

Slifka et al., 1998). The antibody isotype primarily involved with the protection of

mucosal surfaces is IgA (Chen and Li, 1990). As for naive T cells described above,

naive B cells must first be activated by cognate antigen before differentiation into

antibody producing plasma cells, and this will be discussed further in Section 1.7

below.

1.5 Immune Sites of the Respiratory Mucosa

The immune system of the respiratory mucosa, like that of other mucosal surfaces,

can be divided into two distinct sites, inductive sites and effector sites (Figure 1.4).

Inductive sites are where immune responses are initiated. Effector sites located

nearby are where immune cells perform their immune effector functions (reviewed

by Kiyono and Fukuyama, 2004).


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Figure 1.4 Inductive and effector site of mucosa-associated lymphoid tissue. At inductive sites,

antigen presentation to naïve lymphocytes triggers an adaptive immune response. Migrating to nearby

effector sites via the blood circulation, activated B and T cells differentiate terminally into effector

plasma and CD4+ helper T cells respectively. Antibodies synthesised by plasma cells are secreted into

the external environment to confer mucosal protection (adapted from Kiyono and Fukuyama, 2004).

1.5.1 Inductive Sites

Inductive sites are located strategically within the respiratory mucosa such that

immune responses against infectious pathogens encountered at the mucosal surface

can be initiated promptly. The primary inductive site within the lungs is the mucosa

associated lymphoid tissue (MALT). Thoracic lymph nodes (LNs), which are located

further away from the mucosal surface than respiratory MALTs, also serve as

inductive sites (Suwatanapongched 2006). The cells and mechanisms in place at

these sites actively sample the airways for pathogens and mount efficient adaptive

mucosal responses when infectious pathogens are encountered.


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Lymph Nodes (LNs)

Thoracic LNs form the first group of inductive sites. In humans, these are comprised

of the hilar, paratracheal, tracheobronchial and intrapulmonary group of LNs that are

located along the respiratory tract (Suwatanapongched 2006). These LNs are

surrounded by a fibrous capsule and the distribution of immune cells within (Figure

1.5) is similar to that of MALTs. B cells are localised within B cell follicles present

in the cortical region of LNs. T cells and DCs are more diffusely distributed in

paracortical areas surrounding the follicles. LNs, unlike MALTs, receive an afferent

lymphatic supply and thus do not sample pathogens directly from the airways. As

such, the induction of adaptive immune responses within LNs relies on the

interactions between circulating lymphocytes and migratory DCs (reviewed by Cook

and Bottomly, 2007).

Figure 1.5 Structural organisation of a lymph node. B cells are located within the follicles, while T

cells and dendritic cells (DCs) are located in the paracortical area. (adapted from Murphy, 2012)

Mucosal Associated Lymphoid Tissue (MALT)

MALTs of the respiratory mucosa are located within the lamina propria layer and can

be anatomically divided into bronchus-associated lymphoid tissue (BALT),


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nasopharynx-associated lymphoid tissue (NALT) and Waldeyer’s pharyngeal ring.

The appearance, distribution and composition of respiratory MALTs vary

dynamically in accordance with species, age and extent of infection (reviewed by

Brandtzaeg et al., 2008).

MALTs of the lungs have highly organised microenvironments that facilitate

efficient antigen detection and the subsequent initiation of adaptive responses (Figure

1.6). Lymphoid follicles (dense and non-capsulated aggregations of immune cells)

are overlaid by specialised follicle associated epithelium (FAE). Most B cells are

located within the follicles, while T cells reside mainly in T cell zones that surround

the follicles (Korsrud and Brandtzaeg, 1980). Other immune cells such as dendritic

cells and macrophages are also present in respiratory MALTs, albeit in less

distinguishable regions (Tang et al., 1995; Lugton, 1999).

Respiratory MALTs actively sample antigens from the airways (Fujimura, 2000). For

instance in the Waldeyer’s ring, antigens are actively sampled through deep antigen-

retaining crypts that are directly exposed to the airways (Tang et al., 1995).

Specifically, thin non-secretory microfold cells (M cells) scattered across the FAE

transfer antigens directly from the airways into the underlying tissues where immune

cells are closely juxtaposed (Morin et al., 1994; Kim et al., 2011). This direct transfer

immediately exposes sampled antigens to the immune cells, allowing rapid induction

of adaptive immune responses (reviewed by Neutra, 1998).


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Figure 1.6 Structural organisation of the mucosa-associated lymphoid tissue. Microfold (M) cells

present in the follicular associated epithelium (FAE) transfer antigens directly from the airways into

underlying tissues where B cells and T cells are located nearby. Dendritic cells (DCs) at the

respiratory epithelia can sample antigens directly and transport them to lymph nodes (LNs).

1.5.2 Effector Sites

The mucosal epithelia and its underlying lamina propria form the effector sites of the

airways. Effector cells are scattered at these sites, resulting in poorly defined cellular

compartments. Plasma cells and CD4+ T cells are abundant within the lamina propria

making up the primary effector cell types mediating most of the immune responses

against pathogens (reviewed by Holt et al., 2008). CD8+ bronchial intraepithelial

lymphocytes (IELs) are interspersed among epithelial cells within the respiratory

mucosa. These cells secrete cytokines that inhibit epithelial growth and reduce viral

replication activity (Hirosako et al., 2009; Hirosako et al., 2010).


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1.6 Naïve B Cell Development and Maturation into Mucosal Plasma

Cells

Naïve B cells are derived from hematopoietic stem cells (HSCs) in the bone marrow.

Early naïve B cell development occurs within the bone marrow, while later

development into naïve B cells occurs in the spleen. Fully functional naïve B cells

emerge from the spleen after maturation and circulate throughout the body in search

of cognate antigens using specific B cell receptors (BCRs) expressed on their

surfaces. They become activated when their BCRs engage antigens and undergo

clonal expansion, differentiation and migration, developing into mucosal plasma

cells (Shikina et al., 2004; Fleire et al., 2006). These cells produce large quantities of

antibodies, especially IgA, that mediate pathogen removal at mucosal surfaces.

Mucosal plasma cells become quiescent memory B cells when the pathogens are

successfully removed, although upon repeat pathogen encounter, memory B cells

revert back into plasma cells.

1.6.1 Development of Naïve B Cells

Naïve B cell development occurs in two phases, each in a different lymphoid tissue.

The first phase occurs in the bone marrow where immature B cells develop from

dividing and differentiating HSCs (Hardy et al., 1991; Tokoyoda et al., 2004).

Commitment to B cell development in the bone marrow is marked by the expression

of B cell receptors (BCRs) on the surface of naïve B cells (Hardy et al., 1991). These

receptors, predominantly of the IgM isotype, are essential for naïve B cell function as

they are involved in pathogen recognition and binding (Fleire et al., 2006). As the

BCRs expressed on each B cell recognise a specific antigen, naïve B cells as a

population have varied antigen specificities (Hardy and Hayakawa, 2001). Immature

B cells emerging from the bone marrow migrate to the spleen where they undergo


15

the second phase of development and mature into fully functional naïve B cells

(Loder et al., 1999; Cariappa et al., 2007).

Naïve B cells are delineated by anatomical location, function and phenotypic marker

expression (Sagaert and De Wolf-Peeters, 2003). Three different subsets of naïve B

cells, B1, B2 (conventional) and marginal zone (MZ), have been identified in mice.

Similar attempts with human naïve B cells have garnered some success in the

identification of the B2 and “MZ-like” subsets but not the B1 subset (Sagaert and De

Wolf-Peeters, 2003).

1.6.2 Naïve B Cell Activation

Naïve B cells emerging from the spleen circulate to different lymphoid tissues in

search of their cognate antigens. Those that bind to their cognate antigens become

activated and undergo clonal expansion and differentiation, while those that fail to do

so either migrate to other lymphoid follicles in search of cognate antigens or undergo

apoptosis (Yi et al., 1998; Do et al., 2000). Antigen binding occurs via B cell

receptors (BCRs) and toll-like receptors (TLRs) expressed on the surface of these

cells. TLRs, unlike BCRs, are less antigen specific, binding to structures that are

conserved amongst many pathogens (Bernasconi et al., 2003). Nevertheless, antigens

that bind to either receptor, in combination with various intracellular signalling

pathways, trigger the transcription of genes that direct B cell division and

differentiation (Pone et al., 2012). Naïve B cells can be activated in two ways, with

(T cell dependent) or without (T cell independent) help from T cells.

1.6.2.1 T Cell Independent Activation

T cell independent (TI) activation occurs less frequently than T cell dependent

activation, with naïve B cells achieving full activation by antigen binding alone. TI


16

activation can be further classified into two types, Type 1 TI and Type 2 TI (Bessa

and Bachmann, 2010).

Naïve B cells that undergo Type 1 TI activation receive activation signals from both

BCRs and TLRs (Pone et al., 2012). There are 13 types of TLRs, each recognising

different groups of pathogens. TLR signalling results in the production of primary

transcription factor nuclear factor kappa B (NFκB), which initiates the transcription

of genes required for B cell proliferation and differentiation (Barton and Medzhitov,

2003). Lipopolysaccharide (LPS), a component of bacterial membranes, activates

naïve B cells via TLR4 (Kalis et al., 2003). Cytosine-phosphate-guanine (CpG)

dinucleotides, which are closely associated with pathogen DNA, activates naïve B

cells by binding to TLR9 (Pone et al., 2012).

Naïve B cells undergoing Type 2 TI rely only on extensive BCR cross-linking for

complete activation. The antigens that activate naïve B cells in this manner are often

large polysaccharides that possess multiple binding sites for efficient BCR cross-

linking, thereby providing sufficient signals for activation (Obukhanych and

Nussenzweig, 2006).

1.6.2.2 T Cell Dependent Activation

Most naïve B cells that bind antigens via their BCRs only become partially activated,

requiring co-stimulatory signals from TH for complete activation. These partially

activated B cells receive these secondary signals after presenting processed antigens,

via major histocompatibility complex class II molecules (MHC class II), to

respective TH cells (Okada et al., 2005). TH cells provide two types of co-stimulatory

signals, CD40 ligand (CD40L) and cytokines known as interleukins (ILs). CD40L

expressed on the surface of T cells bind to CD40 expressed on B cells after antigen


17

binding (Noelle et al., 1992). Interleukins, such as IL-2 and IL-4, bind to their

receptors expressed on B cells and trigger or alter intracellular signalling pathways,

directing effector B cell development (Waldmann et al., 1984; Flynn et al., 1998).

1.6.3 Germinal Centre Reactions Generate Plasmablasts

Activated B cells within specialised microenvironment of GCs undergo clonal

expansion and differentiation and, later emerge as plasmablasts (PBs) that

differentiate into long-lived plasma cells. The processes associated with clonal

expansion and differentiation within GCs are collectively referred to as GC reactions

(Klein et al., 2003; Nojima et al., 2011).

GCs contain light and dark zones that can be distinguished in relation to specific

processes associated with cell proliferation and gene modification (Allen et al., 2004).

Light zones are where B cells temporarily cease dividing and undergo selection

based on their ability to bind antigens presented by follicular dendritic cells (FDCs)

(Allen and Cyster, 2008). B cells within light zones (centrocytes) rely on signals

provided by TFH, such as IL-21 and transforming growth factor-beta 1 (TGF-β1) for

growth and further development (Bryant et al., 2007; Dullaers et al., 2009; Kerfoot et

al., 2011). Activated B cells within dark zones (centroblasts) undergo clonal

expansion (Barnett et al., 2012). Within the dark zones, centroblasts undergo two

gene modification processes that occur in association with clonal expansion. After

cycling between these two zones, which is mediated by the expression of CXCR4

and CXCR5, PBs (precursor plasma cells) emerge from the GC (Allen et al., 2004).

These cells possess BCRs of different isotypes, which are released in small amounts

as antibodies. The amount released is greatly increased when PBs terminally


18

differentiate into plasma cells following migration to immune effector sites

(Tarlinton et al., 2008).

1.6.3.1 Somatic Hypermutation

Somatic hypermutation (SHM) causes random point mutations in genes coding for

the variable binding region of BCRs, thus diversifying the antigen recognition

capability of BCRs (Zan et al., 1999; Weiser et al., 2011). SHM is initiated by the

enzyme, activation-induced deaminase (AID) (Muramatsu et al., 2000). The

expression of this enzyme is initiated during naïve B cell activation via intracellular

signalling pathways (Dedeoglu et al., 2004). AID converts cytidine in the target gene

into uracil, causing a mismatch between complementary copies of the gene (Maul et

al., 2011). Uracil is removed by the enzyme uracil-DNA glycosylase (UNG),

triggering base excision repair (BER), which creates a single-stranded break (SSB) in

the DNA (Rada et al., 2002). Resolution of the break by error-prone DNA

polymerases, which introduce bases other than cytidine, thus generates a random

point mutation (Delbos et al., 2005). Single point mutations alter the conformation of

the variable binding region of BCRs, which ultimately affects the antigen recognition

capabilities and antigen binding affinities of these receptors (Zan et al., 1999; Weiser

et al., 2011). As such, SHM diversifies the BCRs expressed on centroblasts.

1.6.3.2 Class Switch Recombination

Class switch recombination (CSR) is a gene modification process that allows BCRs

to switch from the default IgM isotype to other isotypes. Like SHM, CSR is also

initiated by the same enzymatic actions of AID described above (Muramatsu et al.,

2000). However, AID alone does not determine the isotype that will be switched to

during CSR. Additional signals received during activation, primarily in the form of


19

cytokines, are required for directing class-switching to a specific type (Reinhardt et

al., 2009).

Cytokines mediate the growth and differentiation of activated B cells into plasma

cells by binding to their respective receptors that are expressed on B cells (Kehrl et

al., 1986; Parrish-Novak et al., 2000). Two cytokines, IL-21 and TGF-β1, are

responsible for IgA class-switching and subsequent IgA production (Parrish-Novak

et al., 2000). These cytokines, which are produced by TFH cells located in the

germinal centre (Dullaers et al., 2009), bind to the respective receptors, IL-21

receptor (IL-21R) and TGF-β receptor (TβR) and provide the signals required for

growth and differentiation of activated B cells into IgA producing plasma cells

(Kehrl et al., 1986; Parrish-Novak et al., 2000).

Switching between isotypes occurs at the genetic level, where genes coding for the

heavy chain (CH) of BCRs are rearranged rather than altered, as is the case for SHM

(Xu et al., 2012). As gene deletion is involved, CSR relies on cell division for

switching between isotypes, where each round of cell division results in the

production a different isotype (Hodgkin et al., 1996; Deenick et al., 1999).

1.6.4 Plasmablasts Migrate to Effector Sites and Terminally Differentiate into

Plasma Cells

Most activated B cells emerge from GCs as PBs, which are the precursors of plasma

cells, although some emerge as memory B cells (Zotos and Tarlinton, 2012). PBs

produce antibody isotypes identical to that of BCRs expressed on their surfaces.

However, the amount of antibodies produced by PBs is comparably less than that

produced by plasma cells (Tarlinton et al., 2008). Regardless, PBs express BCRs and

thus retain the ability to bind antigens, present antigens and undergo proliferation,


20

which terminally differentiated plasma cells are no longer capable of (Chan et al.,

2009).

PBs emerging from GCs migrate (or home) to effector sites where they terminally

differentiate into plasma cells (Chan et al., 2009). Homing to the effector sites is

mediated by the expression of surface proteins that include integrins and chemokine

receptors (Warnock et al., 1998).

1.7 IgA is Crucial for Respiratory Mucosal Immunity

IgA is the predominant antibody isotype found at the respiratory mucosa and is

produced by mucosal plasma cells residing in the lamina propria. The structural and

functional features of IgA render it efficient for preventing infections and allergic

responses (Karlsson et al., 2010). As such, IgA plays a crucial role in frontline

mucosal immune defence.

1.7.1 Physical and Structural Properties of IgA

IgA monomers (160 kDa) have a distinct y-shape structure, which is attributed to the

spatial arrangement of heavy and light polypeptide chains that make up the molecule

(Silverton et al., 1977). Each monomer is comprised of two identical heavy (both α)

and two light chains (κ or λ). Disulphide bonds link each light chain with a heavy

chain and also hold the two heavy chains together (Figure 1.7). An 18 amino acid

long polypeptide known as the α tail-piece (αtp) extends from the C-terminus of each

heavy chain (Yoo et al., 1999).

Two distinct functional regions, the fragment antigen-binding (Fab) and fragment

crystallisable (Fc) regions, allow IgA molecules to perform as effector molecules

(reviewed by Kerr, 1990). Situated at the tip of each arm of the Fab region is a


21

variable antigen binding site (VL and VH) that is used for pathogen recognition and

binding. The constant heavy chain (CH) of the Fc region mediates interactions with

effector molecules and receptors specific for IgA known as FcαRs. The Fab and Fc

regions are held together by the hinge region, which confers overall structural

flexibility and facilitates pathogen binding.

Figure 1.7 Structure of IgA. IgA is comprised of two heavy chains (CH) and two light chains (CL)

that are held together by disulphide bonds. The α tail-piece (αtp) extends from the C-terminus of each

chain. IgA has two functional regions, the fragment antigen-binding (Fab) and fragment crystallisable

(Fc).

1.7.2 Secretion of Dimeric IgA onto the Respiratory Mucosa

IgA secreted at respiratory mucosal surfaces is synthesised primarily as a dimer by

mucosal plasma cells (Figure 1.8). Dimeric IgA (335 kDa) accounts for 80% of total

secreted IgA (DelaCroix et al., 1982; reviewed by Pilette et al., 2001). Trimeric and

tetrameric forms of IgA are also secreted at mucosal surfaces but in minute quantities

and are, in general, of lesser immunological significance (Vaerman et al., 1995).

Assembly of IgA dimers occurs within mucosal plasma cells, before secretion into

the airways. The process involves the tail-to-tail linking of two IgA monomers,

where a disulphide bond is formed between cysteine molecules located at the end of


22

the tail-piece (reviewed by Johansen et al., 2000). Joining chains (J chains) produced

in concomitance with dimeric IgA by mucosal plasma cells are also involved in the

dimerisation process (Halpern and Koshland, 1970). They are exclusively

incorporated into dimeric IgA, bridging only one of the two adjoining tail pieces via

disulphide bonds (Garcia-Pardo et al., 1981). The physical association between J

chains and dimeric IgA is essential for proper subsequent secretion at mucosal

surfaces (Hendrickson et al., 1996; Vaerman et al., 1998).

Figure 1.8 Structure of dimeric IgA. Two monomeric IgA are linked by their αtps to form dimeric

IgA. The joining chain (J chain) is exclusively incorporated into dimeric IgA, bridging only one of the

two adjoining αtps via disulphide bonds.

Secretion of dimeric IgA occurs via a transport process known as transcytosis, where

dimeric IgA is released into the lamina propria by mucosal plasma cells, before being

transported across the mucosal epithelium and released onto the respiratory mucosal

surface (Figure 1.9). Transmembrane poly-immunoglobulin receptors (pIgRs) on

their basolateral surface of mucosal epithelial cells bind dimeric IgA, thereby

triggering endocytosis of this IgA-receptor complex. The internalised complex is

transported in a vesicle to the apical surface and subsequently released as secretory

IgA (SIgA) by enzymatic cleavage of the pIgR. SIgA differs from dimeric IgA in

that it is attached to a secretory component (SC), the extracellular fragment

(ectodomain of pIgR) formed following enzymatic cleavage (Song et al., 1994).


23

Figure 1.9 Release of secretory IgA (SIgA) into the airway. Dimeric IgA is produced by plasma

cells situated in the lamina propria of the respiratory mucosal. Transport of dimeric IgA across the

respiratory epithelia is mediated by pIgR expressed on the basolateral surface of mucosal epithelial

cells. SIgA is released by the enzymatic cleavage of pIgR, with the extracellular fragment of pIgR

remaining attached to SIgA (adapted from Johansen et al., 2000).

1.7.3 Mechanisms of Pathogen Removal by Dimeric and Secretory IgA at the

Respiratory Mucosa

The primary immune effector function of dimeric and secretory IgA is to remove

pathogens within the internal and external environments of the respiratory tract (Yan

et al., 2002). Pathogen removal mediated by both forms of IgA occurs via three

different mechanisms: exclusion, neutralisation and secretion.

1.7.3.1 Immune Exclusion

Pathogens removal by immune exclusion with SIgA occurs within the external

environment (i.e. respiratory mucosal surface). SIgA on respiratory mucosal surfaces

binds pathogens, thus preventing pathogen-host cell interactions that are essential for

establishing infections. SIgA binds efficiently to pathogens, owing to an increase in

the number of antigen binding sites per antibody molecule following dimerisation

(Renegar et al., 1998). Pathogenic products such as toxins, which exert their effect by

interacting with host cells, are also removed by immune exclusion SIgA (Stubbe et

al., 2000).


24

1.7.3.2 Intraepithelial Neutralisation

Intraepithelial neutralisation can be regarded as the immune exclusion of pathogens

at an intracellular level. Dimeric IgA enroute to the apical surface of epithelial cells

during transcytosis binds to pathogens (especially viruses) that have penetrated the

epithelial barrier, limiting their ability to replicate within host cells and the

subsequent infection of other cells (Mazanec et al., 1992; Yan et al., 2002; Wright et

al., 2006).

1.7.3.3 Excretion of Immune Complexes

Pathogens that have managed to breach the respiratory mucosa to the level of the

lamina propria are removed by excretion. Dimeric IgA released by mucosal plasma

cells in the lamina propria bind to toxins and invading pathogens present to form

immune complexes. These immune complexes are then excreted via the same pIgR

mediated transport mechanism that secretes SIgA from mucosal epithelial surfaces,

keeping the internal environment sterile (Kaetzel et al., 1991; Yan et al., 2002).

1.8 Conditioning of B cells for Immunoglobulin A Production

The biology of many different cell types can be studied in vitro (Abbott, 2003). In

immunology, different immune cell types have been cultured under specified

conditions in vitro to replicate certain aspects of their biology in vivo. This allows the

complex biology of immune cells to be studied in detail and, with greater ease,

providing deeper insights into the functions of these cells in vivo (Miller et al., 1992;

Hartmann et al., 2000).

Class-switching is a major aspect of B cell biology that is studied in vitro, where

naïve B cells are commonly cultured in media containing various cytokines and

stimulatory signals. In light of the significant role that IgA plays in mucosal


25

protection, IgA class-switching by B cells is intensely studied (McIntyre et al., 1995;

Bryant et al., 2007; Jiang et al., 2007; Seo et al., 2009). While these studies are often

concerned with the underlying mechanisms involved, “conditioning” (a term

proposed by this project) however focuses on the application of the methods and

outcomes generated by these studies.

A recent study conducted in vitro with human B cells to determine factors involved

in IgA class-switching successfully generated mucosal homing IgA PBs (Dullaers et

al., 2009). The authors cultured naïve human B cells with anti-IgM, anti-CD40, IL-2,

CpG, IL-21 and TGF-β1 in vitro. These reagents represent the signals that naïve B

cells encounter during activation and class-switching in GCs in vivo. Anti-IgM was

used to initial activation by antigen recognition. Anti-CD40 and IL-2 was used to

provide co-stimulation that is required for TD activation of naïve B cells. CpG, on

the other hand, was used to replicate TI activation of naïve B cells (Gururajan et al.,

2007). To provide signals that direct IgA class-switching in vivo, IL-21 and TGF-β1

was used.

Culture of naïve B cells with the signals described above resulted in the generation of

mucosal homing IgA PBs. These PBs were found to express CCR10, which directs

homing to various mucosal sites. The major implication suggested by the authors was

a better understanding of the factors driving IgA mucosal responses. From a

conditioning perspective, the authors have described a methodology for which

mucosal homing plasmablasts can be generated in vitro and, possibly be used in

therapeutic applications. Another possible application would be the in vitro

generation of IgA in vast quantities, which can then be harvested and administered

for therapeutic purposes.

Chapter 2. Aims and Hypothesis

26


The successful in vitro generation of mucosal homing IgA PBs from human naïve B

cells by Dullaers et al. (2009) has revealed that IL-21 and TGF-β1, in addition to

anti-IgM, anti-CD40, IL-2 and CpG, are essential for generating strong mucosal IgA

responses (Dullaers et al., 2009). Interestingly, these mucosal homing IgA PBs were

found to express a chemokine receptor that directs non-site specific homing to

mucosal surfaces (Lazarus et al., 2003; Morteau et al., 2008). These findings have

important implications in light of mucosal vaccine design, indicating that new

vaccine candidates should aim to enhance IL-21 and TGF-β1 mediated responses in

vivo (Dullaers et al., 2009).

This project approached these findings from a different perspective, focusing more

on the therapeutic applications for these homing IgA PBs, especially with regards to

respiratory diseases. By conditioning autologous naïve B cells in vitro, the generated

mucosal homing IgA PBs can later be re-introduced in vivo to enhance antigen

specific humoral responses against pathogens and allergens at the respiratory mucosa.

With this potential clinical application as the ultimate goal, an intermediate goal

would be to assess the therapeutic potential of these cells in mouse models of

respiratory diseases. This would show proof-of-concept, a necessary and crucial step

before translation into a clinical setting.

The immediate goal of this project was to determine if the findings of Dullaers, Li et

al. (2009) could be applied to a murine model, as the effect of IgM, anti-CD40, IL-2,

CpG, IL-21 and TGF-β1 on murine naive B cells has not been reported previously.

Nevertheless, a published finding that IgA production increased when murine B cells

were cultured in vitro with IL-21 and TGF-β1 (Seo et al., 2009), provides some


27

justification for this study. As such, the specific aims of the project were focused on

demonstrating aspects that were deemed to be key indicators of successful naïve B

cell conditioning. Thus, the aims of the project were:

1. To establish a methodology for rapid purification of naïve B cells from

mouse spleen using magnetic bead isolation approaches.

2. Demonstrate in vitro proliferation of murine naïve B cells to a sufficient

extent to allow IgA class-switching following in vitro conditioning with anti-

IgM, anti-CD40, CpG, IL-2, IL-21 and TGF-β1.

3. Quantify IgA production following in vitro B cell conditioning to obtain

preliminary evidence for the successful generation of IgA PBs.

Chapter 3. Materials and Methods

28


Animals acquired and the experimental procedures performed for this project were

approved by the Murdoch University Research Ethics Office (Approval Number:

R2467/12). All reagents used were prepared according to the manufacturer’s

specifications, unless indicated otherwise. Additional details (manufacturer and

catalogue number) of the reagents are listed in Appendix A.

3.1 Animal Agistment

Pathogen-free female BALB/c mice within the age range of 8 to 12 weeks were

obtained from the Animal Resources Centre (ARC), Canning Vale, WA. Mice were

usually sacrificed immediately upon receipt for experiments. When necessary, mice

were housed for up to a maximum of 4 weeks at the Murdoch University Animal

House (Murdoch, WA) in an ambient temperature of 21°C with a 12h:12h light:dark

cycle. Food and water were available ad libitum and tissue paper was provided for

environmental enrichment. During the holding period, mice were monitored for

behavioural and physical indicators of their health status, such as self-grooming,

eating and drinking patterns, startle reflex and communal behaviour (refer to

Appendix B - Animal Monitoring Sheet).

3.2 Euthanasia and Tissue Collection

Mice were euthanised for the collection of spleens. Prior to euthanasia by cervical

dislocation, mice were anaesthetised by inhalation of 3% halothane in a gas chamber.

Charging of the gas chamber was done initially with 5% halothane and subsequently

lowered to 3% before introducing mice into the chamber.


29

Spleens from two mice were collected aseptically and pooled to minimise biological

variability between individual mice. Mouse abdomens were swabbed with 70%

ethanol (EtOH) before dissection with UV-sterilised scissors and tweezers. Collected

spleens were stored in filter sterilised fluorescent activated cell sorting (FACS)

buffer containing 5% heat inactivated fetal bovine serum in Dulbecco’s phosphate

buffered saline (5% HI FBS in DPBS) and kept on ice until use for cell extraction.

3.3 Naïve B cell Extraction and Enrichment

Magnetic depletion was used to isolate naïve B cells from the mixed population of

cells present in mouse spleens. A pure population of naïve B cells was necessary for

obtaining results that were representative of these cells.

3.3.1 Preparation of Splenocyte Suspension

Splenocytes comprising B cells were extracted from collected spleens as a cell

suspension. Each spleen was injected at opposite ends with 0.5 mL of FACS buffer

using a 3 mL syringe and a 23 gauge needle (Figure 3.1A). Cells dislodged by the

injected buffer were gently teased out through the holes made during injection

(Figure 3.1B). Clumps of cells were mechanically disaggregated by syringing with

the same needle (Figure 3.1C) and filtering through a cotton wool column (Figure

3.1D). After spinning of the initial cell suspension at 520 g for 7 min in a refrigerated

(4°C) Beckman-Coulter centrifuge, the supernatant was removed by aspiration. Red

blood cells in the pellet were lysed by resuspension in 5 mL 1X Flow Cytometry

Mouse Lyse Buffer for 10 min at room temperature. Cold FACS buffer was added in

excess to stop the lysis reaction and lysates were removed by aspiration of the

supernatant following centrifugation (same conditions as before). The resultant pellet

was resuspended in 4 mL of FACS buffer to yield a single cell suspension of


30

splenocytes. The number of viable splenocytes present in the suspension was counted

manually with an improved Neubauer haemocytometer, at a 1 in 10 dilution of the

cell suspension with 0.4% Trypan Blue staining solution. After counting ≥ 100 viable

(unstained) cells in the middle square, the final concentration of viable cells in

cells/mL was determined using the following equation:

( ⁄ )

Figure 3.1 Extraction procedure of splenocytes from mouse spleen. A) FACS buffer (DPBS with 5%

FBS) was injected into the distal ends (filled arrows) of each spleen. B) Splenocytes were teased out

of the spleen through holes made during FACS buffer injection by scraping with a bent needle

(direction indicated with a hollow arrow). C) Cell clumps were disaggregated by syringing. D) Cells

were filtered through a cotton wool column to remove fine clumps of cells.


31

3.3.2 Enrichment of Splenocyte Suspension for Naïve B Cells

The proportion of naïve B cells in splenocyte suspensions was enhanced by magnetic

depletion of other cells with the use of a commercially purchased Mouse B

Lymphocyte Enrichment Set. Modifications were made to the manufacturer’s

protocol to accommodate the removal of CD27 expressing memory B cells.

Briefly, 1 × 108 splenocytes were incubated in 500 µL of Biotin Mouse B

Lymphocyte Enrichment Cocktail and 100 µL of biotin hamster anti-mouse CD27 at

4°C for 15 min. Unbound antibodies from the cocktail were removed by a standard

wash step that involved adding excess volumes of FACS buffer, centrifugation under

conditions described above and aspiration of the supernatant. The cell pellet was

resuspended in 600 µL of streptavidin particles from the enrichment kit and

incubated at 4°C for 30 min. FACS buffer was added to a final volume of 2 mL to

yield a cell concentration of 5 x 108 cells/mL. Negative selection for naïve B cells

was performed by standing 1 mL aliquots of the cell suspension in sterile 12 x 75

mm round bottom tubes on a cell separation magnet for 8 min (Figure 3.2A). Naive

B cells present in the supernatant were collected while undesired cells (positive

selection) remained in the pellet (Figure 3.2B).

Naïve B cell recovery was optimised by resuspending the pellets, standing

suspension aliquots in tubes on the cell separation magnet for another 8 min and

collecting the supernatant. The process was repeated twice and collected supernatants

were pooled to obtain an enriched fraction, which was put on the cell separation

magnet one last time for 8 min to obtain a final suspension (twice enriched fraction).

A flow diagram of the separation procedure is illustrated in Figure 3.3.

The number of viable cells present in the twice enriched fraction was determined

using the same cell counting method described previously, but at a 1 in 5 dilution of


32

the enriched cell suspension. The purity of naïve B cells before and after enrichment

was determined by flow cytometry (Section 3.5.3).

Figure 3.2 Isolation of naïve B cells by magnetic depletion. A) Tubes containing cells that have

been incubated with streptavidin particles were placed on the cell separation magnet for 8 min. B)

Naïve B cells that were not bound by the magnetic streptavidin particles remained in the supernatant

and were collected as an enriched fraction.


33

Figure 3.3 Naïve B cell isolation protocol. Cells were washed after antibody incubation by adding excess volumes of FACS buffer, centrifuging at 1800 RPM for 7 min and

aspiration of the supernatant. After standing on the cell separation for 8 min, supernatants containing naïve B cells were collected and pellets were resuspended by repeated

pipetting with 1 mL FACS buffer.


34

3.4 Naïve B Cell Labelling and In vitro Conditioning

Isolated naïve B cells were labelled with the fluorescent dye, carboxyfluorescein

succinimidyl ester (CFSE), to allow for the tracking of cell division. These labelled

cells were then cultured in different conditioning mixtures.

3.4.1 CFSE Labelling for Tracking Cell Division

Cells from the twice enriched suspension were labelled with 5 µM CFSE

(determined by titration, Section 3.5.2) from a CellTrace CFSE Cell Proliferation Kit.

Briefly, 30 µL of 5 mM stock CFSE solution was added to 30 ml of cell suspension

(in FACS buffer) containing 3 x 107 cells. Following incubation at 37°C for 10 min,

5 volumes of cold FACS buffer was added and kept on ice for 5 min to quench the

staining. Labelled cells were washed thrice with FACS buffer to remove excess

CFSE. In preparation for conditioning, the pellet was resuspended in complete media

containing RMPI 1640 supplemented with 10% HI FBS, 50 µM 2-mercaptoethanol

(2-ME) and 2 mM L-glutamine, at a concentration of 2 x 105 cells/100 µL.

3.4.2 In vitro B Cell Conditioning

In separate experiments, CFSE labelled naïve B cells were cultured over two

different time courses: 1) 1, 3, 6, 9 and 12 days and 2) 1, 3, 5, and 7 days. The shorter

time course was used in later experiments after initial experimentation with the

longer time course revealed poor cell viability at later time points (Section 5.3).

CFSE labelled naïve B cells were conditioned with four different mixtures of

conditioning reagents, each prepared in complete media (Table 3.1). The

concentration used for each conditioning reagent was determined after consulting

published literature. Labelled cells were also cultured in complete media containing


35

1 µg/mL LPS for comparison of proliferative responses. The concentration used was

determined after a trial conditioning experiment revealed no differences in viable cell

numbers between 1 and 10 µg/mL LPS (Section 4.5). Cells maintained only in

complete media served as negative (unstimulated) controls.

Table 3.1 Constituents of the four naïve B cell conditioning mixtures.

Conditioning Reagent

Working Concentration

Literature Consulted Condition

1 2 3 4

Anti-IgM 5 µg/mL Ozaki, Spolski et al. 2004

Anti-CD40 5 µg/mL Pellegrini, Guiñazú et al. 2007

IL-2 40 U/mL Zeng, Spolski et al. 2007

Type B CpG 10 µg/mL Chu, Enghard et al. 2007

IL-21 5 ng/mL Seo, Youn et al. 2009

TGF-β1 0.2 ng/mL Seo, Youn et al. 2009

Labelled naïve B cells were cultured in 96-well tissue-culture round bottom

microplates (BD Biosciences, USA; #353077). One microplate was used for each

time point within the time course, minimising contamination risks and easing sample

collection. In total, four microplates were prepared for the shorter time course and

five for the longer time course.

Six different culture conditions were set up on each microplate. Each condition was

carried out in quadruplicates (1 well/replicate) and a final cell concentration of 2 x

105 cells/200 µL/well was used. All microplates were incubated in a humidified

37°C incubator (Shanghai Lishen Scientific Equipment Co., Ltd., China; Heal Force

HF90) containing 5% CO2 for the respective culture duration.

Naïve B cells (2 x 105 cells/100 µL/well) were incubated in anti-IgM coated wells at

37°C for 2 hr to allow for cross-linking of BCRs expressed on naïve cells and hence,

initial stimulation. Anti-IgM was coated onto the wells of microplates a day prior to

conditioning. An anti-IgM solution of 100 µL (prepared in DPBS) was delivered into


36

each well and incubated overnight at 4°C. Excess antibody was removed after

coating by flicking and microplates were blotted on dry paper towels.

The remaining reagents for each conditioning mixture were added into their

respective wells as a master mix at 100 µL/well, bringing the final volume in each

well up to 200 µL. Owing to a 1:2 dilution, the master mix for each condition was

prepared in complete media at twice the final working concentration. As IL-21 and

TGF-β1 were used at low concentrations (ng/mL), an intermediate 1 in 100 dilution

step was performed to allow for accurate micro-pipetting.

LPS and negative control wells were set up in non-coated wells after the initial 2 hr

incubation. Cells were introduced into each well at 2 x 105 cells/100 µL/well and 100

µL of 2 µg/mL LPS was added next to obtain a final working concentration of 1

µg/ml. A 100 µL volume of complete media was added to the negative control wells.

3.4.3 Sample Collection and Storage

Cells and culture supernatants were collected at each time point for all six culture

conditions. Sample collections were performed on ice to minimise protein

degradation and cell death. Contents from the respective wells for each condition

were pooled, to average the variability amongst replicates, into sterile 12 x 75 mm

round bottom tubes. Culture supernatants of 600 µL volumes were collected from

each tube after centrifuging at 520 g and 4°C for 7 min. Collected supernatants were

stored in microtubes at -20°C for subsequent IgA quantification by ELISA (Section

3.6). Cells free of culture media were retrieved by resuspending pellets in excess

FACS buffer, centrifugation as described in Section 3.3.1 and aspiration of the

supernatant. Cells were fluorescently labelled and analysed immediately by flow


37

cytometry after retrieval (Section 3.5.3). The collection procedure is depicted in

Figure 3.4.

Figure 3.4 Cell and culture supernatant collection protocol. Cells and culture supernatant from

each condition were collected at all four time points and analysed respectively by flow cytometry and

enzyme-linked immunosorbent assay (ELISA). Quadruplicate wells were pooled during collection.

Cells were stained and analysed immediately, while culture supernatants were stored at -20°C until

subsequent analysis by ELISA.

3.5 Flow Cytometric Analysis of Labelled Cells

Cells samples collected before and after enrichment, together with those collected at

various time points after conditioning, were labelled with several fluorescent markers

and analysed by flow cytometry.

3.5.1 Instrumentation and Analysis Software

Cells were analysed shortly after labelling with one of the two BD FACSCanto II

flow cytometers (BD Biosciences, USA) available at Murdoch University or the

Centre for Microscopy, Characterisation and Analysis (CMCA), University of

Western Australia. Identical excitation wavelengths and optical filters (i.e. emission

band pass (BP) filters) were used on both instruments for data acquisition (Table 3.2).

Data on the fluorescence intensity and forward and side scatter of 100,000 cells was

collected with BD FACSDiva software (BD Biosciences, USA; PC version 6.1.2).


38

The data collected was analysed using FlowJo software (Tree Star Inc., USA; PC

version 7.6.5).

Table 3.2 Excitation lasers and optical filters equipped on the BD FACSCanto II.

Instrument: BD FACSCanto II

Laser lines 488 nm (blue)

488 nm (blue)

633 nm (red)

633 nm (red)

Optical filters

585/42 BP 530/30 BP 660/20 BP 780/60 BP

Colour Yellow/Orange Green Red Far Red

3.5.2 Optimisation of FACS Staining by Titration

To determine optimal staining concentrations, all staining reagents were titrated on

splenocyte (pre-enriched) suspensions. Cells were kept on ice (≤ 4°C) at all times

during staining and flow analysis to avoid capping (redistribution and internalisation

of surface molecules), which would interfere with fluorescence intensity

measurements (Loor et al., 1972). Stained samples were stored protected from light

to prevent photobleaching.

3.5.2.1 Fluorochrome-conjugated Monoclonal Antibodies

Serial dilutions (1:100, 1:200, 1:400 and 1:800) of Phycoerythrin (PE)-CD19 MAb

were prepared in FACS buffer. Cells (1 x 106) were incubated in 100 µL of each

dilution for 20 min. Labelled cells were washed once as described in Section 3.3.1 to

remove excess antibody. Unless otherwise mentioned, all labelled cells were

resuspended in 500 µL FACS buffer after the final wash for subsequent flow analysis.

3.5.2.2 Biotin-conjugated Monoclonal Antibody

Serial dilutions of 1:100, 1:200, 1:400 and 1:800 were prepared for the biotin

conjugated CD27 MAb (Bio-CD27), while dilutions of 1:250, 1:500, 1:1000 and

1:2000 were prepared for allophycocyanin conjugated streptavidin (APC-SA). Cells


39

(1x106) were stained in two separate 20 min incubation steps, the first with dilutions

of biotin hamster anti-mouse CD27 and the second with dilutions APC-SA,

generating 16 possible staining combinations (Table 3.3). Cells were washed after

each incubation step to remove excess reagents.

Table 3.3 Titration of biotin-CD27 and APC-streptavidin. Serial dilutions were titrated in a single

experiment, using a matrix that generates 16 possible combinations between the two reagents.

1st Incubation: Bio-CD27

2nd Incubation: APC-SA

1:250 1:500 1:1000 1:2000

1:100 Tube 1 Tube 2 Tube 3 Tube 4 1:200 Tube 5 Tube 6 Tube 7 Tube 8 1:400 Tube 9 Tube 10 Tube 11 Tube 12 1:800 Tube 13 Tube 14 Tube 15 Tube 16

3.5.2.3 LIVE/DEAD Near-IR Fixable Cell Stain

A stock solution of the dye was prepared by reconstituting the lyophilised contents of

a single vial with 50 µL of anhydrous DMSO. Stock solution volumes of 0.5 µL, 1

µL and 1.5 µL were delivered into separate tubes containing 1 x 106

cells in 1 mL of

FACS buffer, half of which were rendered non-viable by snap freezing (Kandil et al.,

2005). Cells were incubated with the dye for 30 min. Excess dye remaining after

staining was removed by performing three consecutive washes.

3.5.2.4 CellTrace CFSE Cell Proliferation Stain

A 5 mM stock solution of CellTrace CFSE was prepared by dissolving the

lyophilised contents of a single vial in 18 µL of anhydrous DMSO. Cells were

labelled as described in Section 3.4.1 with either 5 µM, 10 µM, 15 µM or 25 µM

CFSE.


40

3.5.3 Staining Panels

Two staining panels, an enrichment panel and a proliferation panel, were used

respectively to determine naïve B cell purity and the proliferation of specific B cell

subpopulations (Table 3.4).

Table 3.4 Fluorescent reagents used in each staining panel and the respective emission filters

used for detection.

Panel Fluorescent Reagent Clone Emission Filter

Enrichment PE-CD19 MAb 6D5 585/42 BP

APC-CD27 MAb LG3.A10 660/20 BP LIVE/DEAD Fixable Near-IR Cell Stain - 780/60 BP

Proliferation LIVE/DEAD Fixable Near-IR Cell Stain - 780/60 BP

CellTrace CFSE Cell Proliferation - 530/30 BP

3.5.3.1 Enrichment Staining

Non-specific binding between fluorochrome-conjugated MAbs and low-affinity Fc

receptors expressed on the surface of cells was blocked to prevent increased

background staining. 2 µL Mouse BD Fc Block (purified rat anti-mouse CD16/32)

was added to 1 x 106 cells in 100 µL FACS buffer and incubated for 5 min. Cells

were washed and used immediately for staining.

In separate staining tubes, 1 x 106 cells from pre- and post-enriched suspensions were

incubated with 100 µL of a master mix containing 0.5 µg/mL PE-CD19 MAb and

2.5 µg/mL Bio-CD27 MAb for 20 min. Cells from each tube were washed and then

incubated with 100 µL of 0.8 µg/mL APC-SA for 20 min. After a second wash, cells

were resuspended in 1 mL of FACS buffer and incubated with 0.5 µL of dye solution

from the LIVE/DEAD Fixable Near-IR Dead Cell Stain Kit for 30 min. Excess dye

was removed by performing three consecutive washes.


41

3.5.3.2 Proliferation Staining

Cells were collected as described in Section 3.4, resuspended in 1 mL of FACS

buffer and incubated with 0.5 µL LIVE/DEAD Fixable Near-IR Dead Cell Stain for

30 min. Three consecutive washes were performed to remove excess dye.

3.5.4 Controls and Compensation

Unstained controls, single stained controls and fluorescence minus one (FMO)

controls relevant to each panel were analysed together with their respective panels.

Single stained controls, each containing cells stained with a different probe from the

panel, were analysed first to compensate for spillover (spectral overlap) between

detection channels. After gating on the positive and negative staining cell

populations for each stain, compensation matrices were generated by the

compensation tool BD FACSDiva and applied onto FMO controls and samples.

FMO controls, each comprised of every stain in the panel other than the one being

controlled for, were prepared and analysed to help with the determination of gating

boundaries. Three FMO controls were analysed for the enrichment panel, one for

each of the stains. None were required for the proliferation panel given the number of

stains used. Instead, undivided controls (i.e. negative controls in Section 6.4.2) were

analysed to aid with the analysis of cell division.

3.5.5 Early Cell Gating Strategy

Gates set early in the analysis were identical for both panels and used consistently for

all sample analyses. Cells were discriminated from cellular debris by gating broadly

on forward scatter (FSC) and side scatter (SSC) characteristics (Figure 3.5A).

Aggregates of cells were excluded with a doublet discriminator gate (Figure 3.5B).

Non-viable lymphocytes were excluded by gating on viable cells that stained


42

negatively with the viability dye (Figure 3.5C). Boundaries used for gating on viable

cells were determined using a FMO control for the viability dye.

Figure 3.5 Early cell gating strategy. Cellular debris, cell aggregates and dead cells were excluded

from analysis by sequential gating around cells, single cells and viable cells on bivariate dot plots of A)

forward scatter area (FSC-A) versus side scatter area (SSC-A), B) FSC-A versus forward scatter

height (FSC-H) and C) Near-IR fluorescence intensity versus SSC-A.

3.6 IgA Enzyme-linked Immunosorbent Assay

Soluble IgA in the culture supernatant was quantified by sandwich enzyme-linked

immunosorbent assay (ELISA) using a Mouse IgA Ready-SET-Go! ELISA kit.

Sandwich ELISAs work in general by using specific capture and detection antibody

pairs to form conjugates where target antigens are “sandwiched” in between.

3.6.1 ELISA Optimisation and Controls

Refinements to the manufacturer’s protocol were made to increase the absorbance

range obtained for serially diluted mouse IgA standards (Section 4.3). The incubation

temperature, except for coating and blocking, was raised from room temperature to

37°C and colour development was extended from 15 min to 30 min or 45 min.

Culture supernatants were not analysed during assay optimisation to conserve

samples and reagents.


43

Blank and negative controls were included in every assay. The former was included

to correct for background absorbance of the assay buffer used as a diluent. Wells

containing only culture media were used as negative controls. Isotype controls

containing purified mouse IgG1 MAb was included in the final round of optimisation

to test for IgA specificity.

3.6.2 Coating and Blocking of Microplates

Flat bottom 96-well high binding microplates were coated (100 µL/well) with a

1:250 dilution of purified anti-mouse IgA MAb (capture antibody) that was prepared

in a coating buffer. Plates were sealed and incubated overnight at 4°C. Unbound

capture antibodies were removed by two wash cycles on a microplate washer

(Biochrom Ltd., UK; Asys Atlantis) with sodium azide free wash buffer (1x PBS

with 0.05% Tween-20). Each wash cycle involved the addition of 400 µL wash

buffer into each well, which was allowed to soak for 1 min before removal through

aspiration. Microplates were blotted face down on dry paper towels after the last

wash cycle. Non-specific binding sites in each well were blocked by incubation with

blocking buffer (250 µL/well) at room temperature for 2 hr. Blocked plates were

washed twice afterwards.

3.6.3 Standard, Sample and Control Incubation

In duplicates (100 µL/well/replicate), negative controls, blank controls, isotype

controls, standards and culture supernatants were incubated in coated and blocked

wells at 37°C for 2 hr. A 2-fold serial dilution of the reconstituted mouse IgA

standard (50 ng/mL) with assay buffer was performed to obtain diluted standards

ranging from 0.39 to 25 ng/mL.


44

Sample culture supernatants collected after 1, 3, 6, 9 and 12 days from cells cultured

under condition 4 were analysed only in the initial assay prior to optimisation. In

anticipation of IgA production, culture supernatants collected from condition 4 (see

Table 1) of the longer experimental time course were analysed. Samples were plated

neat and at 1:2, 1:10 and 1:100 dilutions with assay buffer.

Isotype controls of purified mouse anti-bovine IgG1 (isotype IgG1), at

concentrations matching that of the mouse IgA standards, were analysed. Starting at

a 1:2000 dilution of the neat IgG1 MAb (10-50 µg/mL), separate serial 2-fold

dilutions with culture media and assay buffer were performed. The highest and

lowest possible concentration generated by serial dilution was 25 ng/mL and 0.08

ng/mL respectively.

3.6.4 IgA Detection and Colour Development

Microplates were put through four wash cycles before 100 µL of horse radish

peroxidase (HRP)-conjugated anti-mouse IgA MAb (1:250 dilution of capture

antibody prepared in assay buffer) was added to each well and incubated at 37°C for

1 hr. After another four wash cycles, 100 µL of neat tetramethylbenzidine (TMB)

substrate solution was added to each well incubated at 37°C for 30 min for colour

development. A stop solution of 1M H2SO4 at 100 µL/well was added after 30 min to

stop colour development.

3.6.5 Absorbance Measurement and Data Analysis

The absorbance of each well was measured with a plate reader (Bio-Rad, USA;

Benchmark Plus) at wavelengths of 570 nm (reference) and 450 nm (reading). Plate

artefacts that interfere with absorbance and contribute to background absorbance

were excluded by wavelength subtraction, where the absorbance at 570 nm was


45

subtracted from that at 450 nm. Data collection, manipulation (averaging of duplicate

measurements, blank correction, and wavelength subtraction) and analysis (plotting

of standard curve and determination of IgA concentration) were performed using

Microplate Manager (Bio-Rad, USA; version 5.2.1).

3.7 Statistical Analysis and Graphing Software

Numerical data for the average of triplicates are reported as the mean ± standard

error of mean (SEM). Paired t-test was used to test for significant changes after cell

enrichment. One-way analysis of variance (ANOVA) and the Bonferroni’s post-hoc

test were used to test for significant differences between culture conditions. P-values

of <0.05 were considered statistically significant. Statistical analyses and graphing

were performed using GraphPad Prism 5 (GraphPad Software Inc, USA; Mac

version 4.0b).

Chapter 4. Results I: Experimental Optimisation

46


4.1 Titrations

Before the staining reagents were used in combination for enrichment and

proliferation staining, the optimal staining concentration for each reagent was

determined by titration. This was to ensure that each staining reagent provided strong

positive signals without significant non-specific background staining, which can be

caused by non-specific binding and cellular autofluorescence.

Two criteria were used to compare the flow data collected for each titration and

determine the optimal staining concentration. First, the optimal titre had to

demonstrate minimal or no background staining, which would be evident as

comparable fluorescence intensity between the negative population for each titre and

the unstained cell population from the unstained control. Next, the optimal titre had

to provide clear distinction between the negative and positive populations, at the

lowest concentration possible.

Overlaying histograms, which displayed fluorescence intensity on the x-axis and cell

count on the y-axis, were used effectively to compare the fluorescence profiles

between dilutions and determine optimal staining titres based on the criteria

described above.

The staining reagents that were originally intended for the enrichment and

proliferation panel are indicated in Table 4.1. The original enrichment panel was

designed such that naïve B cells could be positively identified with a marker (IgD)

that was uniquely expressed by them (Sato et al., 2003; Cariappa et al., 2007), in

addition to the pan B cell marker (CD19) and memory B cell marker (CD27).


47

However, V450-IgD titrated poorly, with none meeting the criteria above. Also, as

the number of alternative fluorochromes available for IgD was limited, the marker

was excluded from the enrichment panel.

In addition to the determination of cell proliferation and viability, the markers CD38,

CD20 and CD27 were included in the original proliferation panel to allow for

immunophenotyping of the cells after conditioning. These markers were selected as

they have been successfully used to identify PBs (CD20-CD38

+) and memory cells

(CD20+CD27

+), albeit with human cells (Dullaers et al., 2009). None of the titres for

PE-CD20 met the criteria for optimal staining and hence, it was subsequently

excluded from the proliferation panel, along with Pacific-CD38 and APC-CD27. PE-

CD19 was tried, in place of the excluded markers, as an alternative for

immunophenotyping the conditioned cells. However, immense spillover from the

signal of CFSE into the detection channel of PE-CD19 negated attempts at

compensation.

Table 4.1 Original set of markers selected for the enrichment and proliferation panel.

Panel Fluorescent Reagent Clone Emission Filter

Enrichment

V450-IgD MAb 11-26c.2a 450/50 BP PE-CD19 MAb 6D5 585/42 BP


Proliferation

Pacific Blue-CD38 MAb 90 450/50 BP PE-CD20 MAb AISB12 585/42 BP


CellTrace CFSE Cell Proliferation - 530/30 BP


48

4.1.1 Monoclonal Antibody Titres

PE-CD19 MAb was used to identify cells expressing CD19, a pan-B cell marker, on

their surface (Kozmik et al., 1992). The optimal staining titre of 0.25 µg/ml (1:800

dilution) for PE-CD19 was determined from a single overlaying histogram (Figure

4.1).

Figure 4.1 PE-CD19 MAb titration. Overlay histogram of cells staining positively and negatively

for PE-CD19 MAb at dilutions of 1:100, 1:200, 1:400 and 1:800. Clear separation between the

positively (higher intensity) and negatively (lower intensity) stained populations was shown for all

dilutions. The unstained control (tinted curve) overlaps closely with the negative peaks for each

dilution, demonstrating low levels of background staining. The chosen titre was 1:800 dilution.

Bio-CD27 used during naïve B cell isolation was also used for cell staining to

maximise antibody usage. As biotin is non-fluorescent, APC-SA was used to

visualise Bio-CD27 that was bound to CD27 expressed on the surface of cells

(indirect staining), relying on the high binding affinity between biotin and

streptavidin. For convenience, the APC-SA/Bio-CD27 conjugate will be referred to

as APC-CD27. In all, 16 possible combinations between dilutions of the reagents

were tested in order to determine to the optimal staining titre for APC-CD27.


49

The respective staining titres for Bio-CD27 and APC-SA were determined by

comparing 2 sets of overlying histograms. The first set, comprised of 4 histograms,

was used to determine the optimal titre for APC-SA. Each histogram corresponded to

one of the four Bio-CD27 dilutions used and, the 4 dilutions of APC-SA that were

used with each dilution of Bio-CD27 (Table 3.3) were displayed on the respective

histogram. The best APC-SA titre for each histogram was determined after

comparing APC-SA dilutions of 1:250 and 1:500. The 1:1000 and 1:2000 dilutions

did not produce positive signals (Figure 4.2, top panel). The optimal staining

concentration for APC-SA, when used in conjunction with Bio-CD27, was

subsequently determined to be 0.8 µg/ml (1:250 dilution).

The second set was comprised of only one histogram, which displayed the four

different dilutions of CD27-Bio that was used in conjunction with the optimal titre

determined for APC-SA (Figure 4.2, bottom panel). The optimal staining

concentration for Bio-CD27, after comparing the four Bio-CD27 dilutions, was

determined to be 2.5 µg/ml (1:200 dilution).

Close alignment between negative peaks for the unstained and secondary control

(APC-SA only) showed no significant binding between the secondary staining

reagent and endogenous sources of biotin (Figure 4.3). Consequently, the gating

boundaries for APC-CD27 in subsequent analyses were determined based on CD27

FMO controls.


50

Figure 4.2 APC-CD27 titration. Staining with APC-CD27 required a two-step staining protocol

using biotin conjugated CD27 (Bio-CD27) and allophycocyanin conjugated streptavidin (APC-SA).

APC-SA dilutions produced different APC-CD27 staining intensities (top panel), when used in

conjuction with the same Bio-CD27 dilution (1:200 dilution). Bio-CD27 dilutions produced different

APC-CD27 staining intensities (bottom panel) for APC-SA. The chosen titre for Bio-CD27 and APC-

SA was 1:200 and 1:250 dilution respectively.


51

Figure 4.3 Secondary control for APC-CD27. Comprised of cells that were labelled directly with

APC-SA, the secondary control showed no significant contribution to background staining caused by

the binding of APC-SA to endogenous biotins.

4.1.2 Viability Dye Titre

LIVE/DEAD Near-IR Fixable Cell Stain, a fluorescent viability dye that reacts with

amine functional groups present on cellular proteins, was used to identify viable cells

during data collection and analysis. The dye readily permeates the disrupted

membrane of non-viable or injured cells, staining the interior as well as the exterior

of the cells to yield higher fluorescence intensity. Viable cells with intact membranes

are less permeable to the dye and stain only on the external surface, resulting in dim

fluorescence (Perfetto et al., 2006).

A high proportion of viable cells in the cells suspension resulted in a weak positive

signal (Figure 4.4, top panel). Consequently, non-viable cells were deliberately

introduced into the single stained control to improve the signal of positively staining

cells (Figure 4.4, bottom panel). Given that the concentration of the dye was not


52

provided by the manufacturer, the titres are reported as the volume used. The optimal

titre for the viability dye was determined to be 0.25 µl.

Figure 4.4 Titration of viability dye. Difference in the positive signal before (top panel) and after

(bottom panel) non-viable cells were added. The chosen titre was 0.5 µL.


53

4.1.3 CFSE Titre

CFSE was used to track cell division via the mechanism described in Section 1.9.2.

As expected, all cells stained positively with CFSE. Consequently, the optimal titre

for CFSE was chosen based on the minimum fluorescence intensity (≥103) required

for distinguishing CFSE peaks and the intensity of the signal (Hawkins et al., 2007).

A titre of 5 µM CFSE was determined to be optimal for cell labelling, as higher

concentrations produced fluorescence intensities that were too high (Figure 4.5). The

same concentration has also been used successfully by others to track B cell division

in vitro (Dullaers et al., 2009; Seo et al., 2009).

Figure 4.5 CFSE titration. Cells were stained with 5, 10, 15 and 25 µM CFSE. The optimal titre was

determined to be 5 µM as the peaks for higher concentrations were positioned too far right on the x-

axis.


54

4.2 Compensation Matrix for Enrichment and Proliferation Panels

Compensation was done to remove by subtraction, the amount of spillover between

detection channels used in each staining panel, thereby ensuring close representation

of the actual data (Roederer, 2001). The amount subtracted from each of the

detection channels was determined by FlowJo, after defining positive and negative

signals for each single stained control. The compensation values were as listed as

percentages for each matrix (Table 5). Compensation matrices for the enrichment

and proliferation panels were determined at the start (0 day) of each experiment

using single stained controls. These were subsequently applied to the respective

FMO controls and samples. In the case of the proliferation panel, the same matrix

was also applied to cells collected at later time points.

For the two staining panels used in this project, only compensation between APC-

CD27 and the viability dye was required (Table 4.2), indicating greater spillover

between APC-CD27 and the viability dye, which was expected. On the whole,

satisfactory compensation was achieved.

Table 4.2 Representative compensation matrix for the enrichment (left) and proliferation (right)

panel. Only the fluorochromes are indicated in each matrix. For convenience, the LIVE/DEAD

Fixable Near-IR Dead Cell Stain was abbreviated as LD. Compensation was required for the

enrichment panel but, not the proliferation panels.

Enrichment panel Proliferation Panel

PE LD APC

CFSE LD

PE - 0% 0%

CFSE - 0% LD 0% - 2.61%

LD 0% -

APC 0% 11.9% -


55

4.3 ELISA Optimisation

The first assay performed according to the manufacturer’s protocol yielded an

unexpectedly low absorbance range for the mouse IgA standards (Figure 4.6). As

such, the temperature during sample incubation, detection antibody incubation and

colour development was raised to 37°C in order to improve antibody binding and

enzyme activity.

Optimisation of the manufacturer’s protocol increased the absorbance range for

serially diluted mouse IgA standards (Figure 4.6), thereby improving the sensitivity

and accuracy of IgA quantification. Compared to the original protocol, the

absorbance range had increased drastically when incubations were performed at

37°C and colour development was allowed to proceed for 30 min. Extending colour

development to 45 min yielded the same absorbance range as before (data not

shown). Low background staining was maintained in spite of the modifications,

indicated by similar absorbance values for the lowest standard (0.39 ng/ml) before

and after optimisation.


56

0 5 10 15 20 250.0

0.3

0.6

0.9

1.2

Manufacturer's ProtocolOptimized Protocol

y = 0.04474 x + 0.06063

R2 = 0.9737

y = 0.01367 x + 0.01149

R2 = 0.9829

Mouse IgA Standard Concentration (ng/ml)

Ab

so

rba

nc

e(4

50

-57

0 n

m)

Figure 4.6 Standard curves for identical mouse IgA standards generated before and after

ELISA optimisation. Duplicate absorbance readings for each standard concentration were plotted as

mean ± SEM. The range of absorbance was improved when experimental conditions were optimised

by raising the incubation temperature to 37°C and extending colour development to 30 min.

To be sure that the ELISA kit was specific for mouse IgA, isotype controls of mouse

IgG1 were tested at concentrations similar to that of the standard. The isotype

controls were also prepared separately in assay buffer and complete media to test if

the media was interfering with the assay.

Cross reactivity to the mouse IgG1 isotype control was detected, demonstrating non-

specificity of the kit for mouse IgA. Higher absorbances were obtained for

approximately matching isotype control concentrations that were prepared in assay

buffer (Figure 4.7), implying binding of mouse IgG1 to the capture and detection

antibody. In stark contrast, same concentrations of the isotype control that were

prepared in complete media yielded absorbances much lower than the isotype

controls that were prepared in assay buffer and IgA standards, indicating possible

interference from the media.


57

0.39

0.78

1.56

3.13

6.25

12.5

0

25.0

0

0.0

0.5

1.0

1.5

2.0

2.5

Mouse IgA (Assay Buffer)

Mouse IgG1 (Assay Buffer)

Mouse IgG1 (Complete medium)

Antibody Concentration (ng/ml)

Ab

so

rban

ce

(45

0-5

70

nm

)

Figure 4.7 Cross reactivity with IgG1 and media interference. Absorbance of mouse IgA standards

and matching concentrations of mouse IgG1 (isotype control) prepared in either assay buffer or

complete media. Duplicate absorbance readings for each standard and isotype control concentration

and were plotted as mean ± SEM. When prepared in assay buffer, the isotype control yielded

absorbances much higher than the standards, indicating cross-reactivity. However, isotype controls

prepared in complete media yielded absorbances much lower than the standards, suggesting inference

from the culture media.

4.4 LPS Titration

As conditioning experiments have not been attempted previously, naïve B cells were

cultured with LPS, alongside the other conditioning mixtures to serve as a positive

control for cell culture techniques. This was based on the common use of LPS for

activating naïve B cells in vitro, although it is often used in conjunction with other

factors such as IL-21 and TGF-β1 (Deenick et al., 1999; Seo et al., 2009).

Prior to experiments that involved the actual conditioning of naïve B cells with

conditioning mixtures, a trial conditioning experiment was performed with 1 µg/mL


58

and 10 µg/mL LPS to determine the optimal concentration for subsequent

experiments. Due to experimental limitations, labelled naïve B cells were cultured in

either concentration for 1, 3 and 6 days only.

Following sample collection, cells were stained with the proliferation panel and

analysed by flow cytometry. Light scatter and fluorescence data collected were

displayed on bivariate pseudocolour dot plots, each dot being representative of the

light scatter characteristics or fluorescence intensity of a single cell, which was

indicated on the axes. The plots display cell frequency as a heat map, with red being

the region of highest frequency and blue being the least. Early sequential gating was

performed to remove cells from debris, cell aggregates and non-viable cells from

consideration during actual analysis.

Cell viability was determined using cell frequencies that were obtained from the last

gate drawn during early gating (Figure 4.8). It was expressed as the percentage of

cells that stained negatively with the viability dye amongst single cells:

Cell viability was used to compare between the two LPS concentrations, with an

increase in viability taken to be indicative of cell proliferation. 1 µg/mL was used in

subsequent conditioning experiments alongside the conditioning mixtures, since no

differences in cell viability were observed.


59

Figure 4.7 LPS titration. Cell viability between 1 µg/mL and 10 µg/mL LPS were similar and hence

1 µg/mL LPS was used in subsequent experiments.

Chapter 5. Results II: Experimental Findings

60


Two processing steps were necessary prior to the conditioning of naïve B cells. First,

naïve B cells of high purity were isolated by the magnetic depletion of other cell

types. Next, isolated naïve B cells were labelled with CFSE. These cells were then

conditioned in four different conditioning mixtures and LPS for either 12 or 7 days.

Cells and culture supernatants were collected at various time points during the two

incubation periods and analysed respectively for cell proliferation and IgA

production.

5.1 Magnetic Depletion Yielded High Naïve B Cell Purity of ≥93%

Cell suspensions with high naïve B cell purity were required in order to accurately

determine the conditioning outcomes, cell division and IgA quantification. Without

access to advanced flow cell sorting technology commonly used to obtain cell

populations of high purity (≥98%), naïve B cell isolation by magnetic depletion was

investigated as an alternative method.

In this project the magnetic depletion was achieved with a commercial kit that was

modified in order to additionally remove memory (CD19+CD27

+) B cells. To isolate

naïve B cells by magnetic depletion of the other cells, splenocyte suspensions were

incubated with antibodies Bio-TER119, Bio-CD43 and Bio-CD4 from the

commercial kit, and additionally Bio-CD27. Collectively, these antibodies bound

erythroid cells, plasma cells, B-1 cells, activated B cells and T cells, leaving the

naïve B cells “untouched” (Wells et al., 1994; Rice and Bucy, 1995; Kina et al.,

2000). Subsequent incubation of the suspension with SA-magnetic beads allowed

antibody bound cells to be pelleted under the influence of a magnetic field, thereby

leaving naïve B cells in the supernatant for collection. Samples of the suspensions


61

obtained before and after enrichment were stained with the enrichment panel and

analysed by flow cytometry.

Naïve (CD19+CD27

-) B cells present in suspensions were identified by the lack of

memory B cell marker (CD27) expression. As such, the pan B cell marker CD19

(Kozmik et al., 1992) became an especially important marker for identifying naïve B

cells. Although CD27 is also expressed on other immune cells and B cell subtypes

(Tesselaar et al., 2003), these were presumably removed during magnetic depletion.

On a bivariate pseudocolour dot plot of APC-CD27 (x-axis) versus PE-CD19 (y-

axis), naïve B cells (CD19+CD27

-) and memory B cells (CD19

+CD27

+) were located

respectively in the upper left and upper right quadrant (Figure 5.1). Gating

boundaries of the quadrant gates were determined using CD19 and CD27 FMO

controls (Figure 5.2). Naïve B cell purity was expressed as the percentage of

CD19+CD27

- cells amongst viable cells:

( )

Figure 5.1 Naïve B cell purity before and after isolation. Bivariate dot plots for a single

representative experiment of cells stained with PE-CD19 and APC-CD27 before and after isolation.

Naive B cells and double positive memory B cells were located respectively in the upper left and

upper right quadrants. Double negative cells were located in the lower left quadrant while CD19-

CD27+ cells were in the lower right quadrant.


62

Figure 5.2 Gating based on CD19 and CD27 FMO control. A quadrant gate was used to identify

naïve B cells (upper left quadrant) on a APC-CD27 versus PE-CD19 dot plot. Cells that stained

negatively for CD19 in the CD19 FMO control and CD27 in the CD27 FMO control were used to

determine the boundaries of the quadrant gate.

The modified enrichment protocol yielded a significant increase (1.72 ± 0.05 fold,

n=3) in the proportion of naïve B cells after enrichment (P<0.001, n=3), averaging

93.2 ± 0.7 %. The proportion of double negative cells (CD19-CD27

-) represented in

the lower left quadrant was significantly reduced after enrichment (P<0.001, n=3).

The mean naïve B cell purities (n=3) before and after enrichment are represented in

Figure 5.3.

Before After 0

20

40

60

80

100***

Naiv

e B

C

ell

Pu

rity

(%

)

Figure 5.3 The average naïve B cell purity before and after enrichment. The proportion of naïve

B (CD19+CD27-) cells after enrichment had increased significantly. Mean ± SEM, n=3. *** indicates

P<0.001


63

5.2 Modified Separation Protocol Removed CD27+ Subpopulations to

Different Extents

Bio-CD27 MAb was designed into the separation protocol to specifically remove

memory (CD19+CD27

+) B cells. This was performed as an added precaution, due to

uncertainty about the efficacy of memory B cell removal with anti-CD43 (Wells et

al., 1994). Memory B cells were not of interest as they have previously undergone

activation, cell division and class-switching in vivo, which would confound the

results obtained for conditioned naïve B cells, should they respond to the

conditioning mixture. The volume of Bio-CD27 added was derived from the titration

results for Bio-CD27 and APC-SA. When titrated at 1:100 dilution (0.50 µg/ml),

Bio-CD27 displayed a slight increase in background staining (result not shown),

which was deemed to be caused by antibody saturation. As such, 100 µl Bio-CD27

was determined to be sufficient for complete removal of CD27+ cells (including

memory B cells) contained within the splenocyte suspensions of 2 x 107cells/ml. The

total volume of streptavidin particles used was scaled up accordingly to a 1:1 ratio to

accommodate the addition of Bio-CD27. The ratio was inferred from

recommendations by the manufacturer that equal volumes of the antibody cocktail

and streptavidin particles be used.

Overall, a significant proportion of CD27+ cells were removed during the enrichment

process (P<0.001, n=3), accounting for 1.7 ± 0.3% of the enriched cell population

(Figure 5.4). The significance seemed to be attributed to the removal of CD19-CD27

+

cells rather than memory B cells (CD19+CD27

+), which remained relatively constant.

The low proportion of memory B cells suggests that these cells are unlikely to

contribute to the outcomes determined for conditioning experiments.


64

Before After0

10

20

30

40***

Pro

po

rtio

n o

f

CD

27

+ B

Cell

s (

%)

Before After0

10

20

30

40 ***

Pro

po

rtio

n o

f

CD

19

- CD

27

+ B

Cell

s (

%)

Figure 5.4 Removal of CD27+ cells after enrichment. Comparison of the proportion of all CD27+

cells (top panel) and CD19+CD27+ memory B cells (lower panel) before and after enrichment. Most

of the CD27+ cells removed during enrichment were CD19-CD27+ cells. Data are presented as mean

± SEM. *** indicates P<0.001.


65

5.3 Trends in Cell Viability Revealed Extent of Cell Proliferation

CFSE labelled naïve B cells were cultured in a total of 6 different conditions,

including LPS and complete media. Each of the 4 different conditioning mixtures

was assigned a condition number. Condition 1 contained a mixture of anti-IgM, anti-

CD40, IL-2 and CpG, which was also present in conditions 2 to 4. These reagents

were used to mimic most aspects of naïve B cell activation in vivo, such as BCR

engagement, TH cell co-stimulation, cytokine signalling and TLR engagement. IL-21

was added to condition 2, while TGF-β1 was added to condition 3. Both cytokines

are well known IgA class-switching factors (Dullaers et al., 2009; Seo et al., 2009).

Condition 4 contained both IL-21 and TGF-β1 in addition to the mixture used in

condition 1. In all, three naive B cell conditioning experiments, excluding the trial

experiment with LPS, were conducted.

Cell viability was used as an indicator of cell proliferation (Figure 4.8), thus allowing

comparisons to be drawn between culture conditions. The viability of cells cultured

under different conditions was determined at each time point. Cell samples collected

at each time point were assessed for cell viability to determine changes in

proliferative responses over time. The viability of freshly labelled cells that were put

into culture at 0 day was consistent, averaging 83.9 ± 0.7% (n=3).

The initial time course of 12 days was chosen to replicate the culture duration over

which naïve human B cells (Dullaers et al., 2009) were conditioned with the same

reagents used in this project. As expected, cell viability decreased over time for

unstimulated cells (negative control), showing that the complete media alone had no

stimulatory properties (Figure 5.5). An exception was observed when cell viability

increased sharply from 1.1% at day 9 to 26.9% at day 12. Although the anomaly


66

observed at 12 days could not be accounted for, culture contamination was ruled out

as a possible factor since the culture supernatant did not appear cloudy, which is a

cardinal sign of contamination. Observation of the collected culture supernatant

under an inverted microscope did not reveal the presence of any bacteria or fungi.

The observed decline in cell viability after 3 days in culture resulted in revision of

the culture duration to 7 days for the next two experiments, with samplings

performed on alternate days to allow the tracking of cell viability with greater fidelity.

Despite similarities in the overall trend, cell viability declined even more rapidly

after 3 days in these cultures (Figure 5.6), indicating either an increased rate in cell

death or reduced rate of proliferation. An immediate explanation could not be

provided. In hindsight, the difference could have been caused by use of different lots

of conditioning reagent, although this warrants further investigation.

0 3 6 9 120

20

40

60

80

100Condition 1

Condition 2

Condition 3

Condition 4

LPS

Negative Control

Days

%

Via

bil

ity

Figure 5.5 Viability of cells cultured in different conditions for 12 days. Cell viability for

conditions 1 to 4 and cells cultured in LPS recovered at day 3 and 6 respectively. Cell viability

eventually dropped below 20%, with day 12 from the longer time course being an exception. n=1.


67

0 3 6 9 120

20

40

60

80

100Condition 1

Condition 2

Condition 3

Condition 4

LPS

Negative Control

Days

%

Via

bil

ity

Figure 5.6 Viability of cells cultured in different conditions for 7 days. Cell viability for conditions

1 to 4 and cells cultured in LPS recovering at day 3 and 6 respectively. Cell viability eventually

dropped below 20% by day 7. n=2.

The viability of cells cultured in conditions 1 to 4 showed signs of recovery at day 3

for all three experiments, indicating cell proliferation. Nevertheless, cell viability

dropped over time to ≤20% at the end of each time course. Additional evidence for

cell proliferation was also supported by microscopic observations, with visually

detectable differences in the size of the cell masses between the conditioned cells and

cells cultured in LPS or complete media (data not shown). In addition to increasing

cell viability, yellowing of the culture media was observed at day 3 for cells cultured

with the conditioning mixtures. The colour change is often associated with increased

media acidity, caused by the accumulation of acidic by products of metabolically

active cells. As such, it appears that the proliferating cells were exhausting the media

after 3 days in culture.

Cell viability for cells conditioned with LPS plummeted in the first 3 days, before

showing signs of recovery at 6 day, albeit at much lower values compared to the

conditioning mixtures. By comparison, media exhaustion was not observed for cells


68

cultured with LPS or in complete media, suggesting that fewer cells were dividing at

a slower rate. It could also suggest that the cells were dying much sooner than

expected.

5.4 Comparing Cell Divisional Responses Between Different

Conditions

Although the cell viability trend described before provided some insight on the

extent of cell proliferation, the number of divisions could not be inferred and had to

be determined separately. This would allow division number to be examined in

relation to the amount of IgA present in culture supernatants, since class-switching is

strongly associated with cell division (Hodgkin et al., 1996).

The number of divisions undergone by viable cells cultured in each condition was

estimated by CFSE labelling of naïve B cells prior to conditioning. Cells collected

after conditioning were stained with the proliferation panel and analysed by flow

cytometry.

CFSE histograms, with CFSE intensity was plotted on the x-axis and cell count was

plotted on the y-axis, of viable cells were used to determine cell division numbers

with the Proliferation tool on FlowJo. The tool determined cell division numbers by

fitting of peaks onto the histograms. The height of the peak or rather, the area under

the peak, was indicative of the number of cells.

The position of the undivided peak was determined by fitting a single peak, since

there was no cell division, onto the CFSE histogram of the undivided control. This

peak was imposed onto the histograms of samples collected on the same day.

Starting at undivided peak for each sample histogram, peaks of sequentially halving

fluorescence intensity were fitted onto the histogram (Figure 5.7). The position of the


69

peak in relation to that of the undivided control was indicative of the number of

divisions. (Lyons and Parish, 1994).

Figure 5.7 Estimation of cell division by analysis of CFSE fluorescence intensity. CFSE profiles

of viable cells cultured under different conditions. were displayed on a histogram. Using the CFSE

profile of the undivided control (left) as a reference for the position of the undivided peak, Gaussian

peaks of sequentially halving CFSE intensity were fitted onto the profile of cells cultured under a

particular condition (right). The number of divisions was equivalent to the number of peaks fitted.

For comparison of the proliferative responses between culture conditions, two

parameters derived from the number of cell divisions were used. The first parameter

was the percentage of divided cells, which provided an estimation of the proportion

of cells that were activated by the conditioning reagents and have undergone division.

The other parameter used was the proliferation index, which averaged the total

number of divisions over the number cells that have undergone at least one division.

As such a high proliferation index suggests that the activated cells have undergone

numerous divisions.

The 3 day time point was common to all conditioning experiments, providing a

minimum sample size (n=3) on which statistical differences could be determined. As

it coincided with maximum cell viability for cells cultured in conditions 1 to 4


70

(Figure 5.6), the percentage of divided cells and proliferation index was derived

respectively for each condition, LPS and complete media. As cell proliferation was

not detected in the negative control (Section 5.3), proliferation index and percentage

of cells divided cells was assumed to be zero. ANOVA was performed on these

parameters to determine if the culture conditions were statistically different from

each other and, if indeed, the Bonferroni‘s post-hoc test was used to determine

differences between specific conditions. As the sample sizes were too small for

normality testing, cell division number and the parameters derived from it were

assumed to be normally distributed.

ANOVA revealed significant differences amongst the conditions for percentage of

cells divided cells (F(5,12) = 28.74, P<0.001) and proliferation (F(5,12) = 84.54,

P<0.001). Further testing with the Bonferroni’s post-hoc test revealed that most of

the significant differences were determined against the negative control, which was

expected (Figure 5.8).

Significant differences were observed between LPS and each of the conditioning

mixtures for the percentage of cells divided cells (P<0.001), but not proliferation

index. These results implied that LPS was causing a small proportion of naïve B cells

to divide persistently, while the conditioning mixtures caused a large proportion of

cells to undergo lesser rounds of division.

Both the percentage of cells divided cells and proliferation index did not reveal any

significant differences between any of the conditioning mixtures, indicating that IL-

21 and TGF-β1 might not have any effect on naïve B cells. As such, the proliferative

responses observed (Section 5.3) were probably induced by the combinatorial effect

of anti-IgM, anti-CD40, IL-2 and CpG.


71

Conditi

on 1

Conditi

on 2

Conditi

on 3

Conditi

on 4LPS

Neg

ativ

e Contr

ol

0

20

40

60

80

100 ******

%

Div

ided

Conditi

on 1

Conditi

on 2

Conditi

on 3

Conditi

on 4LPS

Neg

ativ

e Contr

ol

0

1

2

3***

Pro

life

rati

on

In

dex

Figure 5.8 Comparison of % cell divided and proliferation index for different culture conditions

at day 3. No significant differences were detected between conditions 1 to 4 for percentage of cells

divided cells (F(5,12) = 28.74, P<0.001) in the top panel and proliferation index (F(5,12) = 84.54,

P<0.001) in the bottom panel, indicating similar cell responses (n=3). Significant differences were

detected between LPS and each of the conditioning mixtures for percentage of cells divided cells

(P<0.001) but not for proliferation index. Data are presented as mean ± SEM. *** indicates P<0.001.


72

5.5 Majority of Conditioned Cells Underwent 3 Rounds of Division

Indications that the conditioning mixtures were not causing cells to divide

persistently prompted further investigation on cell division, since IgA class-

switching and its subsequent production is dependent on cell division (Hodgkin et al.,

1996). As such, cell division numbers for condition 4, the mixture of most interest,

were examined in relation to culture duration. This was done by comparing CFSE

histograms of the different time points, after peaks were fitted onto each histogram

for estimating cell division number (Figure 5.7).

A leftward shift (decreasing CFSE intensity) in the position of the undivided peak

was observed over time. This was caused by the slow background decay of CFSE

that does not interfere with the determination of cell division number (Hawkins et al.,

2007). The apparent increase in CFSE intensity on day 5 and 7 of the shorter time

course was most likely caused by the use of different cytometers, albeit of the same

model and identical acquisition parameters. This was due to a temporary malfunction

of the cytometer located at Murdoch University and hence, some samples had to be

analysed at CMCA, UWA.

Shown in Figure 5.9, cell division was not observed at day 1, for both the twelve and

seven day time courses, indicated by similar CFSE intensities between the undivided

control and samples collected at day 1 (data not shown). The total number of

divisions increased over time, reaching 7 divisions by day 9 during twelve day time

course and 5 divisions by day 5 during the seven day time course. A drop in number

of divisions at day 7 was observed for the latter, possibly due to rapidly declining

cell viability (Section 5.3), compounded by the low proportion of cells that have


73

undergone that many rounds of division. Cell division could not be estimated on day

12 as the number of viable cells was insufficient for analysis.

Despite the increase in number of cells dividing with time, the majority of cells

appeared only to have undergone 2 to 3 rounds of division. This was evident with the

taller peaks being centred between much shorter peaks (Figure 5.9). Culture media

exhaustion, as described earlier, could have caused the apparent arrest of cell

division beyond 3 rounds.


74

Figure 5.9 Changes in the number of cell divisions for cells cultured over 12 days and 7 days in

condition 4. Starting with 0 division at day 1, cells cultured over 12 days (left column) reached 6

divisions by day 9 while those cultured over the shorter time course reached 5 divisions by day 5. A

drop in the number of divisions was observed at day 7 for the shorter time course (right column)

Chapter 6. Discussion

75


The conditions used in this project for naïve B cell conditioning were essentially

replicating two important events that are important for plasma cell development in

vivo. The first is naïve B cell activation that occurs within the lymphoid follicles of

peripheral lymphoid tissues, where naïve B cells become activated following cognate

antigen encounter and, usually, co-stimulation by TH cells. The second event occurs

within germinal centres of lymphoid follicles, where activated B cells within the dark

zone of germinal centres undergo CSR. The purpose of CSR is to rearrange the genes

coding for the heavy chain components of BCRs expressed on centroblasts, thereby

allowing BCRs of different isotypes to be released as antibodies after they

differentiate into plasma cells. The gene rearrangement process involves the deletion

of genes and as such, requires cell division for successful switching to different

isotypes.

6.1 Magnetic Isolation for Obtaining High Naïve B Cell Purity

Cell suspensions with high naïve B cell purity were required for the conditioning

experiments conducted in this project, so as to obtain responses that were

representative of naïve B cells. This posed the first major challenge of this project,

since access to flow sorting was not readily available. Although flow sorting services

at another institution (CMCA) could be engaged, there were major concerns over the

loss of viable cells during transport (Chokeshai-u-saha et al., 2012), which would

impact the number of cells available for conditioning. Consequently, magnetic

depletion was investigated as a simpler alternative to flow sorting for the

reproducible isolation of naïve B cells with high purity.


76

A high purity of naïve B cells (≥93%) was isolated by magnetic depletion,

specifically negative selection (Section 8.1). There were significant increases in the

purity of naïve B cells (P<0.001) obtained before and after isolation. While this was

just short of the aim (≥95%), the average purity obtained was comparable to those

reported by others (90-92%) that have used the same isolation method, albeit from

different suppliers (Jiang et al., 2007; Chokeshai-u-saha et al., 2012). As such, it was

concluded that the kit was working reasonably well, even after modifications were

made to include the removal of CD27+ cells, including memory B cells.

Memory B cells were not desired as they would respond differently from naïve B

cells when conditioned (Shi et al., 2003) and thus, interfere with the responses

measured. Unexpectedly, comparisons of the changes in memory B cell numbers

after isolation revealed insignificant differences. However, a significant proportion of

CD19-CD27

+ and CD19

-CD27

- cells were removed following magnetic depletion.

The implications of these findings remain unclear but, may be related to the

separation process or antibody markers used. Furthermore, the few markers used

provided limited insight into the cell types present. Nevertheless, in light of the

overwhelming number of naïve B cells obtained post separation, the outcomes of the

conditioning experiments were not expected to be greatly affected by relatively small

numbers of memory B cells and the other two cell populations.

Although flow sorting produces higher cell purity than magnetic separation

(Chokeshai-u-saha et al., 2012), negative selection, which leaves naïve B cells

“untouched” lends an advantage to the latter method. This is due to the alteration of

BCR signalling with MAbs (CD19 and IgD) associated with the positive labelling of

naïve B cells (Pezzutto et al., 1987; Healy et al., 1997; Chen et al., 2013). This

highlights the possibility of altering conditioning outcomes as a result of flow sorting.


77

In summary, the isolation of naïve B cells by magnetic bead-based negative selection

is a safer option than flow sorting, have a lower risk of incurring mixed naïve B cell

responses.

6.2 Naïve B Cell Activation

Anti-IgM, anti-CD40, IL-2 and CpG were used in this study for the activation of

murine naïve B cells to replicate TI and TD activation of naïve B cells in vivo.

Cognate antigen recognition by naïve B cells, which is the first step in activation and

often results in the partial activation of naïve B cells, was replicated by the use of

plate bound anti-IgM. As most BCRs expressed on the surfaces of naïve B cells are

of the IgM isotype (Fleire et al., 2006), anti-IgM binds non-discriminately to these

BCRs and provides initial stimulation to a large number of naïve B cells of differing

antigen specificity. While this situation is unlikely to occur in vivo, polyclonal

activation could be ideal for conditioning as it activates naïve B cells with different

antigen specificities. This would allow magnetic separation to be used for the

selection of antigen-specific B cells (Egeland et al., 1988). Furthermore, selection

would be easier with the increase in number of antigen specific cells following

polyclonal activation.

6.2.1 TD Activation

Anti-CD40 and IL-2 were used to replicate TD activation of naïve B cells in vitro,

which would be provided in vivo by TH cells to partially activate naïve B cells. Anti-

CD40 binds to CD40 expressed on naïve B cells, mimicking engagement with

CD40L that is expressed on TH cells. This triggers expression of the transcription

factor NFκB, which in turn directs the expression of proteins that are crucial for cell

proliferation and class-switching (Dedeoglu et al., 2004). IL-2 binds to IL-2R


78

expressed on the surfaces of naïve B cells, acting as a growth factor and mimicking

co-stimulation provided by cytokines in vivo (Waldmann et al., 1984).

6.2.2 TI Activation

T cell independent activation of murine naïve B cells in vivo was replicated by the

use of CpG that engages TLR9 (Gururajan et al., 2007). These nucleotides, which are

closely associated with pathogen DNA, binds to TLR9 expressed on naïve B cells

and trigger the expression of NFκB as described for anti-CD40. As TLR9 is also

expressed on memory B cells, these cells that are present in culture could also have

responded to CpG in the culture media. However, their contribution to overall cell

proliferation would be negligible, since they were only present in small numbers

(~1%).

Cells cultured with LPS were activated differently, via TLR4. The expression level

of TLR4 on naïve B cells is approximately five times lesser than TLR9 and thus, the

stimulatory capacity of CpG would be greater than LPS (Gururajan et al., 2007).

Although the activation pathway is different from those used in the conditioning

mixtures, LPS was chosen as it is commonly used for the activation of naïve B cells

in vitro (Deenick et al., 1999; Seo et al., 2009).

6.3 Cell Proliferation

In fulfilment of the second aim, cell proliferation was successfully demonstrated with

the conditioning mixtures used in this experiment. Cell viability had increased at day

3, indicating that the proportion of viable cells was increasing and, thus proliferating.

Proliferation of the conditioned cells was also supported by the high percentage

(~80%) of cells that had divided. On average, the conditioned cells were found to


79

have undergone between 5 to 7 divisions. In view of the relationship between cell

division and class-switching, IgA production was expected in these cultures.

Although naïve cells cultured in each of the conditioning mixtures were proliferating,

no significant differences were observed between the mixtures. As anti-IgM, anti-

CD40, IL-2 and CpG were common to each mixture, a superficial interpretation of

the results would be that IL-21 and TGF-β1, when used separately or together, were

not having any effect on cell proliferation. A comprehensive interpretation of the

results would, however, require an account of the effects each individual component

has on cell proliferation and all possible interactions between them. Given that these

additional conditions were not tested, an in depth discussion on the implications of

this finding was not possible. As such, the following discussion presents published

evidence for the effect of IL-21 and TGF-β1, and highlights some of the challenges

faced with the interpretation of such data.

In vivo, activated B cells within GCs would receive IL-21 and TGF-β1 from TFH

when they migrate into the light zone following clonal expansion. These cytokines

bind to the respective receptors, IL-21 receptor (IL-21R) and TGF-β receptor (TβR),

which are expressed on the surface of B cells. The binding of these cytokines

mediates growth and differentiation of activated B cells into plasma cells (Kehrl et

al., 1986; Parrish-Novak et al., 2000). The effect IL-21 has on proliferation can be

either positive or negative, as demonstrated respectively when used in combination

with anti-CD40 or, anti-IgM and IL-4 (Parrish-Novak et al., 2000). However, these

observations could not be used to relate to the effect of IL-21 in this experiment

when both anti-CD40 and anti-IgM were used, therefore demonstrating the

complexity that is associated with attributing differences to specific components

within a set of conditioning reagents used.


80

In addition to proliferation, the importance of IL-21 in B cell differentiation was

highlighted by a study, carried out in mice deficient for IL-21R, which showed

severe defects in antibody production (Ozaki et al., 2002). Furthermore, abrogation

of IL-21 activation resulted in the inhibition of B cell activation, proliferation, and

antibody production (Bryant et al., 2007; Kuchen et al., 2007). As such, it was

unexpected that none of these reported effects of IL-21 were observed in this study.

Perhaps, the experiments performed would require optimisation, by performing dose

titrations of IL-21 in conjunction with the established concentrations of anti-IgM,

anti-CD40, IL-2 and CpG, to better appreciate the role of IL-21 in this study.

Similar to IL-21, TGF-β1 can exert stimulatory and inhibitory effects on B cell

growth and differentiation. When TGF- β1 was added at low concentrations to cells

that were activated with IL-2, B cell proliferation and antibody production were both

suppressed (Kehrl et al., 1986). However, the suppression of proliferation, but not

antibody production, was partially lifted with increased concentrations of IL-2.

Again, the study conducted by Kerhl, Roberts et al. (1986), which only examined the

effect for two of the six conditioning reagents used in this study, has highlighted the

potential complications that maybe involved in interpreting the overall cell

proliferation with respect to each component used. As suggested for IL-21, it seems

that the concentration of TGF-β1 used may need to be optimised in relation to fixed

concentrations of anti-IgM, anti-CD40, IL-2 and CpG.

One interesting observation was made when the proliferation index and percentage of

divided cells of conditioning mixtures were compared against the LPS condition,

which was meant to serve as a comparison for proliferative responses. While

significant differences in the percentage of divided cells (P<0.001) were observed

between LPS and the conditioning mixtures, none were observed for the proliferation


81

index. As proliferation index averages the total number of divisions for all dividing

cells, the results suggests that although a smaller number of cells were proliferating

later with LPS than with the conditioning mixtures, these cells were also undergoing

more divisions.

Although LPS activates naïve B cells via TLR4, it was chosen as a control for

comparing proliferative responses as it a known B cell mitogen (Andersson et al.,

1973; Coutinho et al., 1973). B cell mitogens are polyclonal activators of B cell

proliferation and hence, the proliferative responses of cells cultured with LPS would

serve as a benchmark for those observed with cells cultured in conditioning mixtures.

In this regard, the proliferation of cells, as measured by the number of divisions

undergone by cells (proliferation index) cultured in conditioning mixtures, was

markedly increased above those cultured in LPS.

In view of the significant differences seen with percentage of divided cells, the

results indicate that a mixture of anti-IgM, anti-CD40, IL-2 and CpG at least, is

capable of activating a lot more (~70%) cells than LPS. Based on the proliferation

index, it seems likely that the concentrations of IL-21 and TGF-β1 used were

insufficient to exert any of their discussed effects on the large proportion of dividing

cells, contradicting the complete absence of influence from IL-21 and TGF-β1 that

was proposed earlier based on the cell viability. This seems to provide a reasonable

account for why the majority of cells have only undergone 3 rounds of division

(Figure 5.9). By inference then, cells cultured with LPS would have to undergo more

than 2 to 3 rounds of division in order to account for the differences between the

percentage of cells divided cells and proliferation index.


82

Nevertheless, this interpretation maybe oversimplified as other differences have not

been considered. For instance, the different trend in cell viability observed between

the two time courses, the differences in time taken for cell viability to recover and,

the possible mechanistic differences that may be attributed to TLR9 and TLR4

activation of naïve B cells (Richard et al., 2008). Due to the complexity of such

systems, which is discussed in detail by Hodgkin, Chin et al. (1997), satisfactory

explanations for these differences could not be provided. However, in hindsight, dose

titrations for IL-21 and TGF-β1, as suggested before, might provide additional

insight into their respective roles in this conditioning system.

In summary, each of the conditioning mixtures has driven strong cell proliferative

responses, enabling some cells to undergo 5 to 7 divisions. These numbers provide

early evidence for IgA production, based on the relationship between division

number and class-switching.

6.4 IgA Production

IgA production could not be ascertained from this study, as the ELISA kit used

demonstrated cross-reactivity. Furthermore, cell culture media interference was

demonstrated, which would interfere with absorbance readouts. As such, this

discussion will focus on the expected outcome based on previous published findings.

IgA production has been observed after cells activated in culture have undergone 5

divisions (Deenick et al., 1999; Dullaers et al., 2009). Based on the 5 to 7 divisions

that were determined for the conditioned cells in this study, the presence of IgA in

culture supernatants would be expected. This prediction is based on the established

relationship between class-switching and cell division (Hodgkin et al., 1996), as AID

required for initiating class-switching is regulated by cell division (Rush et al., 2005).


83

Nevertheless, it is important to be aware that IgA may not be the only antibody class

that could have been produced. It seems IgG2b could also be produced, as reports

have shown that TGF-β1 induces the production of IgA and IgG2b by initiating

transcription at the switch regions of heavy chains genes that code respectively for

IgA and IgG2b (Lebman et al., 1990; Seo et al., 2009). Although the addition of IL-

21 supposedly decreases TGF-β1-induced IgG2b but not TGF-β1-induced IgA

expression (Seo et al., 2009), it would still be ideal to establish the amount of each

isotype produced by cells conditioned in this study.

Several different methods, in addition to ELISA, can be used to establish IgA

production, although ELISA is still the preferred method due to its ease and cost of

operation. One alternative would be to employ capture bead array, which involves

the capture of IgA with beads that are subsequently analysed by flow cytometry

(Elshal and McCoy, 2006). Other useful methods include the detection of IgA

surface expression by flow cytometry or immunohistochemistry (Dullaers et al.,

2009), and polymerase chain reaction (PCR) detection of germline transcripts

corresponding to IgA (Seo et al., 2009), which may also provide information about

the regulatory events surrounding IgA production. Given that culture supernatants

remain to be analysed and, the accessibility to flow cytometry, cytometric bead array

would probably be the best method.

6.5 Immunophenotyping for Better Resolution of B Cell Populations

The successful inclusion of IgD into the enrichment panel, which was unable to be

optimised in the timeframe of this project, would have aided the interpretation of

results. When used in conjunction with CD19 and CD27, IgD expressed uniquely on

human and murine naïve B cells (Sato et al., 2003) would have lent stronger support


84

to the identity of naïve B cells, as opposed to the weak inferences made in this

project by excluding CD27 expressing cells. In addition, recent evidence indicates

that the use of CD19, CD27 and IgD is not only limited to the identification of naïve

B cells.

Five different human B cell subpopulations have been identified using CD19, CD27

and IgD MAbs (Rodríguez-Bayona et al., 2010). The two populations of B cells

potentially of relevance in this study were the double negative memory B cells

(CD19+CD27

-IgD

-) and plasma cells (CD19

+CD27

++IgD

-). CD19, CD27 and IgD,

which are also expressed on mouse B cells, could have be used to distinguish

between naïve B cells and double negative memory B cells in the enriched fractions

(Klein et al., 2003). This, however, has raised doubts about the identity of

(CD19+CD27

-) naïve B cells isolated in this project and the subsequent conditioning

outcomes that were determined, which could be confounded by the responses of

negative memory B cells. Unfortunately, this question could not be adequately

addressed within the span of this project. Nevertheless, future experiments using

CD19, CD27 and IgD MAbs would potentially be able to clarify this issue and allow

for better interpretation of the results by taking the responses of different

subpopulations into consideration.

Another application for CD19, CD27 and IgD would be their incorporation into the

proliferation panel. This would circumvent the use of PE-CD20 MAb and allow for

better delineation of the B cell subpopulations as compared to the original

proliferation panel of CD20, CD38 and CD27. Regardless of panel design, the main

intention behind immunophenotyping of the conditioned cells was to determine the

relative proportion of memory B cells and plasma cells. The results obtained from


85

this new panel can improve the results of this study in two ways, each of which

would benefit this study greatly.

The first improvement would be of greater relevance to the long term goals of this

project. As the ultimate goal of this project was to direct homing IgA PBs to the

respiratory mucosa where they can boost antigen specific IgA humoral responses, the

conditioning mixture that generates a much higher proportion of PBs than memory

cells, as determined by immunophenotyping, would demonstrate greater therapeutic

potential and should be investigated in future studies.

Additionally, differences in the proportions of memory B cells and plasma cells that

were generated by the conditioning mixtures can be better analysed as effects

mediated by either IL-21, TGF-β1 or both cytokines, thereby providing some insight,

at the cellular level, into how these two factors might determine the fate of cells

emerging from GCs in vivo. As much of the molecular mechanisms involved remain

largely unknown (Zotos and Tarlinton, 2012), an additional outcome, that could be

achieved in parallel with a broader attempt to condition B cells, would be the

expansion of existing knowledge of these mechanisms, possibly by genetic studies.

The information obtained, as such, would complement conditioning studies, thereby

creating a comprehensive approach for investigating the potential of conditioning

naïve B cells in vitro for therapeutic applications.

6.6 Refining CFSE Labelling for Better Determination of Cell Division

The main problem encountered when determining cell division was poor resolution

of the CFSE histograms (Section 8.5). Unlike those shown in Figure 5.9, the peaks of

CFSE histograms published in the literature could be distinguished visually (Lyons

and Parish, 1994; Hodgkin et al., 1996), allowing easy determination of cell division


86

number. Without such distinguishable peaks, cell division number was determined in

this project by fitting peaks at sequentially halving intensities from the undivided

peak, based on the assumption that cell division leads to an equal sharing of CFSE

between daughter cells. This has been shown to be valid for several rounds of

division, however these results raise questions about the basis of poor resolution in

this study (Lyons and Parish, 1994).

Further investigations into the possible causes for poor resolution revealed uneven

staining as the most probable cause. Referring to the protocol that was published by

researchers from the laboratory that first detailed the use of CFSE labelling for

tracking lymphocyte division, even cell numbers as high as 1 x 108 were stained in a

total volume of 1 mL. Furthermore, homogeneous staining within this small staining

volume was achieved quickly within 5 min (Quah et al., 2007). Compared to the

protocol used here where the labelling of 3 x 107 cells that was done in a much larger

volume of 30 mL for 10 min in this study, homogenous staining would have been

difficult to achieve. In future, CFSE labelling with the same number of cells should

be done in a volume of 1 mL, with immediate vortexing after the addition of CFSE to

promote rapid and homogenous staining (Quah et al., 2007).

6.7 Future Directions

Undoubtedly, this study has raised several interesting questions. For one, the impact

of IL-21 and TGF-β1 on cell proliferation in relation to the other conditioning

reagents and, how it subsequently relates to IgA production requires immediate

attention. As such, simple dose titrations for each conditioning reagents may shed

light on future approaches. The next question is IgA production. Until this key piece

of information is obtained, the ultimate success of the study remains uncertain. In


87

view of the resources available, alternative commercial ELISA kits could be tested or,

flow cytometry can be used to check for surface expression of IgA on conditioned

cells. The next step after affirming IgA production would be to determine the surface

expression of homing receptors, including CCR10, which directs the homing of IgA

PBs to mucosal sites. Success with the characterisation of homing receptor

expression would then lead to studies on the migration capabilities of PBs generated

by naïve B cell conditioning, both in vivo and in vitro.

6.8 Conclusion

In this study, a modified protocol for the magnetic isolation of naïve B cells has been

established, producing naïve B cell populations of high purity that can be used to

obtain representative data from conditioning experiments. In addition, naïve B cell

activation and proliferation were successfully conditioned with a unique combination

of anti-IgM, anti-CD40, IL-2, CpG, IL-21 and TGF-β1. In conclusion, based on the

promising data generated, IgA is expected to be produced, but will need to be

confirmed. While further optimisation is required, the results of this project provide

preliminary evidence that murine naïve B cells can be conditioned in vitro for IgA

production, with potential for homing to, and protection of, mucosal surfaces in vivo.

References

88

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Appendix A: Reagent List and Preparatio

Reagent Source Catalogue Number

2-mercaptoethanol Sigma-Aldrich, St. Louis, MO M3148-100ML

Anti-mouse CD20 PE eBioscience, San Diego, CA 12-0201-80

Biotin hamster anti-mouse CD27 BD Biosciences, San Jose, CA 558753

CellTrace CFSE Cell Proliferation Kit Invitrogen, Carlsbad, CA C34554

Citric acid monohydrate Rowe Scientific, Wangara, WA CC3034

Disodium hydrogen phosphate anhydrous Merck, Kilsyth, VIC 6102490500

Dulbecco’s phosphate buffered saline Sigma-Aldrich, St. Louis, MO D8537

Ethanol absolute Merck, Kilsyth, VIC 8187609020

Fetal bovine serum Invitrogen, Carlsbad, CA 10099-141

Flow Cytometry Mouse Lyse Buffer (10x) R&D Systems, Minneapolis, MN FC003

Halothane BP Laser Animal Health, Sydney, NSW Not available

L-glutamine (200 mM solution) Invitrogen, Carlsbad, CA 25030-149

LIVE/DEAD Near-IR Fixable Cell Stain Kit Invitrogen, Carlsbad, CA L10119

LPS from E. coli serotype R515 Enzo Life Sciences, Farmingdale, NY ALX-581-007-L002

Mouse anti-bovine IgG1 AbD SeroTec, Oxford, OXON MCA627

Mouse B Lymphocyte Enrichment Set BD Biosciences, San Jose, CA 557792

Mouse IgA Ready-SET-Go! ELISA kit eBioscience, San Diego, CA 88-50450-86

Mouse IL-2 recombinant protein eBioscience, San Diego, CA 14-8021

Mouse IL-21 recombinant protein eBioscience, San Diego, CA 14-8211

Mouse transforming growth factor β1 Cell Signaling Technology, Danvers, MA 5231LC

Pacific Blue anti-mouse CD38 BioLegend, San Diego, CA 102719

PE anti-mouse CD19 BioLegend, San Diego, CA 115507

Appendix

98

PE anti-mouse CD20 eBioscience, San Diego, CA 12-0201-80

Purified anti-mouse CD40 eBioscience, San Diego, CA 14-0401

Purified anti-mouse IgM BioLegend, San Diego, CA 406502

Purified rat anti-mouse CD16/32 (Mouse BD Fc Block) BD Biosciences, San Jose, CA 553141

RPMI 1640 media, no glutamine Invitrogen, Carlsbad, CA 21870-092

Sodium chloride Sigma-Aldrich, St. Louis, MO S9888

Sodium dihydrogen orthophosphate dihydrate Thermo Fisher Scientific, Scoresby, VIC BSPSL950.500

Sodium hydroxide Thermo Fisher Scientific, Scoresby, VIC BSPS6740.500

Streptavidin APC eBioscience, San Diego, CA 17-4317-82

Sulphuric acid Thermo Fisher Scientific, Scoresby, VIC 534-2.5L GL

Trypan blue Koch-Light Laboratories, Colnbrook, BUCKS ML0553101

Tween-20 Sigma-Aldrich, St. Louis, MO 274348

Type B CpG oligonucleotide InvivoGen, San Diego, CA tlrl-1668

V450 rat anti-mouse IgD BD Biosciences, San Jose, CA 560869

Appendix

99

70% Ethanol

300 ml absolute ethanol (EtOH)

Make up to 1 L with distilled H2O

0.4% (w/v) Trypan Blue Solution

0.04 g trypan blue powder

Make up to 10 ml with distilled H2O

Filter precipitates with 0.45 µM filter

10x Phosphate Buffered Saline (PBS)

16.7 g disodium hydrogen phosphate (Na2HPO4)

5.7 g sodium dihydrogen orthophosphate (NaH2PO4)

85.0 g sodium chloride (NaCl )


ELISA Wash Buffer (1X PBS + 0.05% Tween-20)

100 ml 10X PBS

0.5 ml Tween 20


ELISA Stop Solution

27 ml concentrated H2SO4 in 450 ml of distilled water


Appendix

100

5 M Sodium Hydroxide

10.2 g sodium hydroxide (NaOH)


20 mM Citrate Buffer pH 3.0

0.4 g citric acid monohydrate

Make up to 100 ml in distilled H2O

Adjust to pH 3.0 with 5 M NaOH

Filter sterilise with 0.2 µM filter

Appendix

101

Appendix B: Animal Monitoring Sheet

Appendix

102

conditioning murine b cells for immunoglobulin a...

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