CLARIFICATION OF THE ROLE OF HOST DNA AS A MEDIATOR OF

VACCINE ADJUVANT ACTIVITY

by

LAURA EVELYN NOGES

B.S., University of Richmond, 2009

A thesis submitted to the

Faculty of the Graduate School of the

University of Colorado in partial fulfillment

of the requirements for the degree of

Doctor of Philosophy

Immunology Program

2015

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This thesis for the Doctor of Philosophy degree by

Laura Evelyn Noges

has been approved for the

Immunology Program

by

Roberta Pelanda, Chair

Holger Eltzschig

Rachel Friedman

Peter Henson

Claudia Jakubzick

Philippa Marrack, Advisor

Date 08/14/2015

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Noges, Laura Evelyn (Ph.D., Immunology)

Clarification of the Role of Host DNA as a Mediator of Vaccine Adjuvant Activity

Thesis directed by Professor Philippa Marrack.

ABSTRACT

Aluminum salt (alum) adjuvants are widely used in human vaccination

because they are safe and effective at generating antibody-mediated protective

immunity. Though it is well known that alum induces T helper 2 responses and

antigen-specific IgG1 and IgE antibody production in mice, the mechanism by

which alum elicits these effects is poorly understood. Recently, others and our

group reported that alum immunization results in the release of host DNA, which

mediates adjuvant activity by acting as an endogenous immunostimulatory

signal. These conclusions were based, in part, on experiments that combined

alum vaccines with DNase I enzymes to study loss-of-function scenarios.

Curiously, DNase only inhibited CD4 T cell priming and antibody responses to

alum; CD8 T cell activation was not affected. As such, further clarification was

needed regarding the role of host DNA in alum adjuvant activity.

Here I employed a mouse model system and injectable DNase treatments

to study the role of host DNA in mediating immune responses to intramuscular

alum vaccines. To ensure that my studies pertained solely to the effects of host

DNA within alum biology, I performed comprehensive analysis of relevant DNase

reagents that had been used for alum studies in previous publications.

Unfortunately, my data indicated that commercial DNase reagents are prone to

iv  

contain impurities and contaminants including digestive proteases. When alum

studies were repeated using pure DNase, I found that alum-associated DNA is

actually dispensable in the generation of effective cellular and humoral immune

responses by alum vaccines. Furthermore, when proteases were co-injected

with alum vaccines, the effects on immune responses mimicked those observed

following co-injection with impure DNase reagents.

In conclusion, we suggest that host DNA is not a major contributor to the

adjuvant effect of alum when vaccines are administered to the muscle and that

contaminated reagents may have misled interpretations of past experiments

involving DNase reagents. This correction of the literature may help improve

future studies to elucidate the mechanism of aluminum salts as vaccine

adjuvants, an endeavor that remains paramount to understanding why alum

vaccines have successfully protected hundreds of millions of people from

disease and how they may be improved for future vaccination strategies.

The form and content of this abstract are approved. I recommend its publication.

Approved: Philippa Marrack

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I dedicate this dissertation to the incredible mentors I’ve had throughout my

education. I hope this work will contribute to the integrity, persistence, and

betterment of science for our world.

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ACKNOWLEDGEMENTS

I am deeply indebted to many people who provided advice, support, and

encouragement throughout my graduate career. Above all, I want to thank Jan

and Paul Noges, Joel Crandall, Bailey Gross, Nicole Desch, Bryan Wee, Raul

Torres, and Janice White for always being there when I needed them.

I would like to thank past and present members of my thesis committee,

Roberta Pelanda, Holger Eltzschig, Rachel Friedman, Laurent Gapin, Dirk

Homann, Peter Henson, and Claudia Jakubzick, for their guidance, input, and

encouragement throughout my thesis project.

I thank all of the current and past members of the Kappler/Marrack lab for

scientific discussion, experimental advice, and technical help. Specifically, I want

to thank Janice White for her generous benchside help and practical advice on all

problems science and otherwise, Fran Crawford for her careful explanations of

protein chemistry and her camaraderie in fighting ‘I got mine,’ and Megan

MacLeod for her patience in explaining science and techniques, willingness to

contribute ideas to my projects, and lightning fast email responses from the other

side of the world. My officemates Matt Phillips and Harsha Krovi provided me

with moral support, scientific insight, and countless jokes – thank you both.

Finally, I will thank my doctorate advisor, Dr. Pippa Marrack. Pippa

nurtured me from an infantile graduate student to an independent, conscientious,

and confident scientist. Through the highs and lows of bench science, graduate

school, and life, Pippa has dedicated her time and energy to guide my

development as a young woman and scientist.

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TABLE OF CONTENTS

CHAPTER

I. INTRODUCTION 1

Natural Protective Immune Responses 2

Primary immune responses (overview) 3

Initiation 3

Contraction and establishment of immune memory 4

Optimizing immune responses 4

Pathogen detection by antigen presenting cells 5

Immunization 6

History of immunizations 7

Immunity 7

Variolation 7

Vaccination 8

Immunization 8

Adjuvants 8

Types of immunizations 9

Live attenuated 9

Inactivated 11

Subunit 11

Adjuvants used in subunit vaccines 12

Aluminum Salts as Vaccine Adjuvants 13

Discovery and use in vaccines 13

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Mechanism of action 13

Generation of protective antibodies 15

Innate immune cell activation 19

Stimulating T cell responses 23

Alum’s cytotoxicity and host DNA as an induced self adjuvant 25

Immunogenicity of Heat Aggregated Proteins 27

II. MATERIALS AND METHODS 29

Mice 29

Reagents, Antigens, Tetramers, and Antibodies 29

Reagents 29

Model antigens 30

Tetramers 31

Antibodies 31

DNases 32

Preparation of Soluble or Aggregated Protein Antigens (Chapter V) 34

Soluble protein 34

Aggregated protein 34

Assessing Protein Conformation and Aggregation (Chapter V) 34

Size exclusion chromatography 34

Micro-flow imaging 35

Infrared spectroscopy 35

Measuring surface hydrophobicity 35

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Immunizations 36

Assessment of Antigen-Specific T Cell Priming 36

Antigen Presenting Cell Analyses 37

RNA Sequencing: Cell Preparation and Analysis 39

Antibody Detection by ELISA 42

Assessing DNase Reagent Purity 42

SDS-PAGE 42

Protease activity assay 43

Mass spectrometry 43

DNase Activity Assay 44

Antigen Destruction Assay 45

Generation of 3NP311-2 CD4 T Cell Hybridomas 45

Statistical Analyses 46

III. HOST DNA IS DISPENSIBLE IN ALUM RESPONSES 47

Introduction 47

Results 49

Creating model antigens: OVA-NP and mutant nucleoprotein 49

Roche DNase I grade II does not affect adaptive immune responses to epitopes within intact protein antigens 50

Primary T cell responses 50

Primary antibody responses and secondary CD4 T cell responses 51

Commercial DNase I reagents are contaminated with active proteases 55

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Proteases are predominantly responsible for the effects of contaminated DNases on CD4 T cell responses to alum 60

DNase enzymatic activity does not impair T cell responses to alum 64

STING may be dispensable in alum vaccine responses 67

Discussion 69

IV. EFFECTS OF ALUM ON ANTIGEN PRESENTING CELLS 71

Introduction 71

Results 74

Technical considerations when using fluorescent antigens 74

Choice of fluorophore for antigen tracking affects detection of antigen-loaded cell subsets 74

Artifacts of flow cytometry: possible B cell + iMono doublets 76

Alum adjuvant effect on antigen-loaded APCs 76

RNA sequencing identifies alum-induced inflammatory pathways 79

Discussion 85

V. SINGLE DOSES OF HEAT AGGREGATED PROTEINS ARE NOT IMMUNOGENIC 88

Introduction 88

Results 89

Characterizing protein antigens: soluble versus heat aggregated OVA 89

Soluble ovalbumin must be filtered and can be stored for at least two weeks at 4°C 89

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Heat aggregation of ovalbumin at concentrations >1 mg/ml alters its surface hydrophobicity, conformation, and structure 90

Heat aggregated proteins do not prime T cells 93

Discussion 96

VI. DISCUSSION AND FUTURE DIRECTIONS 99

Alum’s Mechanism: A Working Model + Unanswered Questions 100

Step 1: Damage and inflammation at the site of injection 101

Step 2: Activation of antigen presenting cells 104

Step 3: Priming adaptive immune cells 106

Step 4: Resolution and boosting 107

Beyond the Model: Additional Unresolved Questions 108

T cell responses to alum 108

B cells as alum/antigen presenters 112

Adjuvant Action of Host DNA 113

Reproducibility in Science and Implications of DNase Contamination 116

The Future of Vaccines 117

Future Directions 119

Concluding Remarks 121

REFERENCES 122

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LIST OF TABLES

TABLE

1.1: Common vaccines in the United States 10

1.2: Vaccines that contain aluminum salt adjuvants 14

1.3: Effector functions and alum induction of human and mouse antibody isotypes 18

2.1: Tetramers used for flow cytometry 31

2.2: Antibodies used for flow cytometry 31

2.3: DNase reagents used in Chapter III 33

2.4: Sorted cell populations submitted for RNA sequencing 40

4.1: APC subset phenotypes 77

4.2: Functional gene clusters that have altered expression in response to alum 85

6.1: Signaling pathways that involve Tbk1 and Irf3 114

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LIST OF FIGURES

FIGURE

1.1: Primary immune response schematic 5

1.2: Human vaccine adjuvants 12

1.3: Efficacy of vaccines in the United States 15

1.4: Conventional dendritic cell and monocyte differentiation in mice 22

1.5: CD11b+ cDCs and iMonos are the predominant APC subsets that respond to intramuscular alum injections 23

2.1: Antigen-specific CD4 and CD8 T cell gating strategy 38

2.2: Gating scheme for antigen-loaded APC sorting prior to RNA sequencing 40

3.1: MutNP and NP stimulate equivalent alum immune responses 50

3.2: Added BSA has no effect on the magnitude of NP311-325-specific CD4 T cell responses to alum immunization 52

3.3: DNase treatment does not affect CD4 T cell responses to intact proteins 53

3.4: DNase treatment does not impair secondary CD4 T cell responses 52

3.5: Commercial DNases are contaminated with active proteases 57

3.6: Roche recombinant DNase has no protease activity 59

3.7: Contaminating proteases rapidly destroy NP311-325 peptide on OVA-NP but not within NP 59

3.8: Worthington DNase, wtDNase, and mutDNase are all pure and appropriately active or inactive 61

3.9: Proteases impair CD4 T cell responses to alum + OVA-NP 62

3.10: Trypsin and chymotrypsin cleavage sites in NP311-325 and SIINFEKL peptides 64

3.11 MutDNase is inactive up to 1 mg/ml concentration 65

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3.12 DNase activity does not impair T cell responses to alum + OVA-NP 66

3.13: STING is dispensable in adaptive immune responses to alum 68

4.1: Choice of fluorescent marker affects the detection of antigen-bearing cells by flow cytometry 75

4.2: Alum increases numbers of antigen-loaded APCs, but does not affect loaded cell type of degree of antigen uptake 78

4.3: Inflammatory monocytes capture the most alum-adsorbed antigen per cell 81

4.4: Antigen arrives to dLNs rapidly via iMonos, but later time points reveal more antigen-bearing migDCs (DCs) 82

4.5: Alum induces vast changes in gene expression profiles within exposed APC subsets 84

5.1: Resuspended lyophilized OVA is predominantly monomeric after filtration and ultracentrifugation 89

5.2: Filtering is required to rid resuspended OVA of particulates 91

5.3: Heating OVA alters its structural conformation 92

5.4: Heat treatment alters the secondary structure of OVA 93

5.5: Single doses of heat aggregated proteins are not immunogenic when administered i.p. or s.c. 95

6.1: Working model of alum’s mechanism 102

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LIST OF ABBREVIATIONS

A488 Alexa Fluor 488 A647 Alexa Fluor 647 ADCC Antibody-dependent cellular cytotoxicity Alum Aluminum hydroxide ANS 1-Anilinonaphthalene-8-sulfonic acid APC Professional antigen presenting cell BCR B cell antigen receptor BSA Bovine serum albumin CD Circular dichroism CDC Complement-dependent cytotoxicity cDC Conventional dendritic cell CLR C-type lectin receptor CTL Cytotoxic T lymphocyte CTM Complete Tumor Medium DAMP Damage/danger-associated molecular pattern DAVID Database for annotation, visualization, and integrated discovery DC Dendritic cell dLN Draining lymph node ELISA Enzyme-linked immunosorbent assay FPLC Fast protein liquid chromatography FTIR Fourier transfer infrared spectroscopy g Gravitational-force (acceleration) HMGB1 High mobility group box 1 proteins HPLC High performance liquid chromatography iDC Inflammatory monocyte-derived dendritic cell ICAM1 Intercellular adhesion molecule 1 Ig Immunoglobulin IL Interleukin iMono Inflammatory monocyte (monocyte-derived dendritic cell) IR Infrared spectroscopy Irf3 Interferon regulatory transcription factor 3 LFA1 Lymphocyte function-associated antigen 1 LN Lymph node LPS Lipopolysaccharide MFI Mean fluorescence intensity MHC Major histocompatibility complex migDC Migratory dendritic cell MSU Monosodium urate NLR NOD-like receptor NOD Nucleotide-binding oligomerization domain NP Influenza A virus nucleoprotein NP311-325 NP peptide (QVYSLIRPNENPAHK) NP366-374 NP peptide (ASNENMETM) OVA Chicken ovalbumin

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OVA-NP Chicken ovalbumin with covalently conjugated NP311-325 peptide PAMP Pathogen-associated molecular pattern pMHCI Peptide-loaded major histocompatibility complex class I pMHCII Peptide-loaded major histocompatibility complex class II PRR Pattern recognition receptor resDC Lymphoid resident dendritic cell RIG-I Retinoic acid-inducible gene I RLR RIG-I-like receptor STING Stimulator of interferon genes Tbk1 Tumor necrosis activating factor-associated NFκB activator

(TANK)-binding kinase 1 TCR T cell antigen receptor TH Helper T lymphocyte TH1 Type 1 helper T lymphocyte TH2 Type 2 helper T lymphocyte TLR Toll-like receptor

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CHAPTER I

INTRODUCTION

“Nothing in biology makes sense except in the light of evolution.”

–Theodosius Dobzhansky

This statement is the title of a 1973 essay by Ukrainian-born Theodosius

Dobzhansky1. The piece brazenly criticized anti-evolution creationism and

implored readers to come to their senses and accept the intellectually satisfying

and even inspiring phenomenon of evolution. With ample biological examples

and logic, Dobzhansky argued that evolution plays a central and unifying role in

the science of biology. This statement resonates deeply with me so I’ve begun

my dissertation with an explanation of how I mentally approach biology and my

research projects in light of evolution.

Dobzhansky’s outlook applies directly to the field of immunology: evolution

drove the development of host immune systems over a multimillion-year-old arms

race between pathogens and hosts. Though some of the most primitive

components of immune systems date back to the origin of multicellularity, the

adaptive arm of the immune system appeared within vertebrates some 450

million years ago2. The purpose of an organism’s immune system is to react to

infection by mounting biological responses that both resolve the primary infection

and establish protective immunological memory that prevents future reinfection

with the same pathogen. This body system evolved in response to endless

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infection and parasitism of multicellular hosts by microbes, viruses, and

parasites. Therefore, the immune system is functionally diverse and able to

make refined responses to limitless types of infectious organisms. As the battle

between pathogens and hosts rages on, human beings have developed an

ingenious technological edge: vaccination.

This dissertation includes several research projects having to do with how

vaccines work. The first two studies examine how aluminum salt adjuvants

stimulate protective immune responses. Chapter III focuses on alum induction

of adaptive immune responses while Chapter IV focuses on alum activation of

innate immune cells. Last, the immunogenicity of a separate vaccine platform is

explored in Chapter V: heat aggregated proteins.

Natural Protective Immune Responses

Before discussing vaccinations in great detail, I must first introduce the

natural mechanisms of protective immune responses. The mammalian immune

system is comprised of both innate and adaptive immune mechanisms. As can

be expected, there are also immune mechanisms that seem to have qualities of

both innate and adaptive immunity, such as memory natural killer cells3,4. As a

rule, innate immune components detect and respond to pathogens in a general

manner and do not confer antigen-specific protective immunity to the host.

Adaptive immunity, however, involves a system of highly specialized cells that

respond in an antigen-specific manner. Moreover, after an initial response to a

  3  

given pathogen, immunological memory is created and subsequent encounters

with the same pathogen are met with greatly enhanced immune responses that

generally prevent symptomatic disease. This memory is the basis of acquired

protective immunity and it is the central goal of vaccination.

Primary immune responses (overview)

Initiation. The initiation of an immune response to an infection requires

collaboration between innate immune cells and T lymphocytes of the adaptive

immune system. The activation of T cells depends on their interactions with

professional antigen presenting cells (APCs), which are specialized innate

immune cells that are directly activated by the pathogens that they engulf or

otherwise encounter5. Upon traveling to lymphoid organs such as lymph nodes,

APCs process and present pathogens to T cells via peptide-loaded major

histocompatibility complex proteins (MHC) on their cell surfaces5. Activated T

cells proliferate, mobilize, and orchestrate specific immune responses that are

tailored to optimally protect the body from various types of infections.

Specifically, T cells activate other immune cells and also become cytotoxic

themselves in order to kill off infected cells within the body. Among the immune

cells activated by T cells, antibody-producing B lymphocytes are one of the most

important subsets. B cells are capable of producing a variety of isotypes of

antibody molecules, each of which are designed to protect against different

infections5. For example, IgA antibodies protect against mucosal pathogens.

The bottom line is that innate and adaptive immune cells are capable of

  4  

chemically detecting the qualities of an offending pathogen and work together to

mount the most effective immune counterattack to combat the infection.

Contraction and establishment of immune memory. At the end of an

immune response, the majority of activated T and B cells undergo apoptosis.

However, a small percentage remain alive because they have differentiated into

memory cells that stay primed and ready to respond rapidly if the host is ever re-

exposed to the same pathogen6,7. Mimicking natural responses, vaccines must

be able to prime antigen-specific T and B cells so that some of them remain in

the body as long lived memory cells.

Optimizing immune responses. Moreover, the best vaccines aim to initiate

the proper type of immune response that will best protect against a particular

pathogen. Naturally, the body has ways to distinguish between different types of

pathogens and respond accordingly. The different ways in which the immune

system can respond to antigen often revolve around the characteristics of the

pathogen (intra/extra-cellular, viral/bacterial/parasitic, etc) that are detected by

APCs and communicated to either or both of the major classes of T cells: helper

CD4 T cells (TH) and cytotoxic CD8 T cells (CTL) (Fig. 1.1). The qualities of

subsequent immune responses depend on this pathogen recognition by innate

immune cells. For example, detection of a viral infection results in CTL killing of

infected cells and antibody neutralization of extracellular virions (Fig. 1.1).

Alternatively, some bacterial or parasitic infections require CD4 T cells to secrete

cytokines that activate particular groups of innate immune cells (Fig. 1.1).

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Figure 1.1. Primary immune response schematic, reprinted from McKee et al., BMC Biology, 2010 (Fig. 1)8.

The next section will focus on the ways in which APCs detect different

pathogenic features upon infection, since vaccines endeavor to imitate this

process.

Pathogen detection by antigen presenting cells

APCs must distinguish between different kinds of pathogens in order to

mount the proper immune response for each type of threat. Innate immune cells

can achieve this by recognizing generally conserved pathogen-associated

molecular patterns (PAMPs) on microorganisms5. PAMPs include molecules

derived from bacterial cell walls, viral RNA genetic codes, CpG-rich DNA, and

other common features of microbes. In turn, innate immune cells express pattern

recognition receptors (PRRs) that specifically detect types of microbial patterns5.

Toll-like receptors (TLRs), nucleotide-binding domain and leucine-rich-repeat-

containing family (NLRs), retinoic acid-inducible gene I (RIG-I)-like receptors

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(RLRs), and C-type lectin receptors (CLRs) are among the best known PRRs9,10.

TLR9, for example, is expressed within cell endosomes and detects CpG-rich

DNA.

Host cell recognition of PAMPs at the site of infection promotes the

recruitment of innate immune cells, including APCs. Signals from PAMP-

activated cells as well as direct PAMP recognition activates APCs, leading to

increased antigen uptake, expression of activation-associated cell surface

molecules, and secretion of soluble chemical mediators that promote T cell

activation5. Together, these effects influence the magnitude and quality of T and

B cell responses, which subsequently affect the generation of memory

lymphocytes that are produced. PRR activation of innate immune cells is a

critical first step toward effective immune responses because it serves to warn

surrounding cells of an infection (reducing collateral damage), activates adaptive

immune cells, and guides the type of immune response that develops.

Immunization

Immunization is a process by which an individual is protected against a

disease through vaccination. Vaccination (interchangeably called immunization)

refers to the controlled introduction of all or a piece of pathogen for the purpose

of generating enhanced immunity to subsequent encounters with the pathogen.

The discovery and use of immunization to protect against particularly deadly

infectious diseases is regarded as the single most influential biomedical

  7  

advancement to date11. The goal of immunization is to generate long-lived

protective immunity against specific pathogens without causing sickness in order

to protect an individual against future infection. This protective immunity is

achieved by stimulating adaptive immune responses that are directed against

pathogenic antigens.

History of immunizations

Immunity: The concept of immunity has existed since ancient times. For

example, the first European mention of immunity was recorded by Thucydides in

Athens in 430 BC. He describes that only those who had recovered from the

plague could nurse the sick because they could not contract the disease a

second time. Allegedly, in gratitude for their tending to the sick, nurses were

exempt from paying municipal taxes: they were immunis.

Variolation: As the notion of acquired immunity was observed and

accepted, a variety of societies around the world began manipulating this

phenomenon. The most widely known early attempts to induce active immunity

were aimed at containing the deadly disease smallpox. Both in China by 1000

AD and Europe within the 15th century, the practice of variolation, also called

inoculation, became common: scratching the skin or inhaling powdered material

derived from smallpox lesions to induce a mild case of smallpox disease12,13. If

variolated subjects recovered from their illness, they would be protected from

future, more deadly cases of the smallpox infection.

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Vaccination: A much safer form of smallpox immunization was reported in

1798 by Edward Jenner12. Jenner deliberately infected a young boy with pus

from the lesions of a cowpox-infected milkmaid. Once the boy recovered from

the cowpox infection, Jenner then challenged his acquired immunity to smallpox

by infecting him with smallpox. The boy suffered no symptoms or disease and

was thus declared immune. Jenner termed this cowpox inoculation procedure

‘vaccination’ as ‘vacca’ is the Latin term for cow. Now, the terms vaccination and

immunization are used interchangeably.

Immunization: As the science of immunology developed and infectious

diseases were better understood in the years following Jenner’s discovery,

scientists began formulating additional vaccines. By 1885, a rabies vaccine had

been devised by two French scientists, Louis Pasteur and Emile Roux, that

employed attenuated rabies virus as an immunogen14. Within the twentieth

century, a variety of successful vaccines were developed as scientists found

ways to produce safe immunogens for vaccination15,16. Many disease-causing

microorganisms were inactivated or attenuated toward this end. Additionally,

toxins from bacteria such as diphtheria and tetanus were inactivated into ‘toxoids’

that were effective immunogens.

Adjuvants: Underlying each successful vaccine was a common theme: a

safe and effective adjuvant must accompany target antigens in order to mount

robust immune responses. An adjuvant is any biochemical substance, organic or

inorganic, that augments immune responses in a way that promotes

immunological memory. Early vaccines employed natural adjuvants that were

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provided by pathogens themselves: bacterial or viral components. These

methods are still used today. The acknowledgement of adjuvants as necessary

components within vaccines was one of the driving forces behind the

development of subunit vaccines, vaccines that deliver only part of an agent

rather than the whole entity. In the early 1920s, Gaston Ramon discovered that

addition of extra substances to antigenic vaccines could enhance immune

responses17. Soon thereafter, Alexander Glenny utilized an inorganic adjuvant to

promote immune responses that would open up a new realm of possibilities for

vaccine development: aluminum salts18.

Types of immunizations

Currently, three main categories of vaccines are used in humans: live

attenuated vaccines composed of a virus or bacterium that is similar but less

pathogenic than the wild form; inactivated vaccines that are heat-killed or

otherwise chemically inactivated forms of the wild pathogen; and subunit

vaccines that are a combination of components of a pathogen (such as surface

proteins) and biochemical immunostimulants called adjuvants. Table 1.1 lists by

type common vaccines given in the United States.

Live attenuated: Vaccines may contain live but weakened, or attenuated,

microbes that are able to replicate within the body but are no longer virulent.

Immune responses to these agents are broad enough to cross-react with the

more dangerous strains that cause disease. Attenuation of viruses or bacteria is

often achieved by culturing under conditions that promote the loss of virulence

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Table 1.1. Common vaccines in the United States, adapted from historyofvaccines.org using Plotkin et al. Vaccines, 200816

Vaccine type Vaccines of this type on U.S. Recommended Childhood (ages 0-6) Immunization Schedule

Live, attenuated

Measles, mumps, rubella (MMR combined vaccine) Varicella (chickenpox) Influenza (nasal spray) Rotavirus

Inactivated/Killed Polio (IPV) Hepatitis A

Toxoid (inactivated toxin) Diphtheria, tetanus (part of DTaP combined immunization)

Subunit/conjugate

Hepatitis B Influenza (injection) Haemophilus influenza type b (Hib) Pertussis (part of DTaP combined immunization) Pneumococcal Meningococcal

Vaccine type Other available vaccines

Live, attenuated Zoster (shingles) Yellow fever

Inactivated/Killed Rabies

Subunit/conjugate Human papillomavirus (HPV)

factors. Attenuated vaccines typically provoke durable immunological responses

because the live microorganism is able to replicate and thus stimulate the

immune system in the same manner as the natural infection. For this reason,

they are preferred for healthy adults. However, a live vaccine format may be

unsafe for use in immunocompromised individuals that cannot mount proper

immune responses against even attenuated microorganisms. Furthermore, there

is always the possibility that an attenuated pathogen may mutate and revert to a

virulent form that causes disease. For example, the Sabin live attenuated oral

poliovirus vaccine is capable of reverting to a neurovirulent form that causes

vaccine-associated paralytic poliomyelitis and the emergence of vaccine-derived

poliovirus strains19–21. Most live attenuated vaccines contain attenuated viruses,

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such as measles, mumps, rubella, yellow fever, or poliovirus (Sabin version).

However, there are a few bacterial attenuated vaccines, including those for

typhoid fever, Yersinia pestis, and tuberculosis.

Inactivated: Alternatively, vaccines may contain viruses or bacteria that

are entirely inactivated or otherwise ‘dead.’ Pathogenic microbes may be killed

by chemicals, heat, or radiation. Inactivated vaccines are more stable and safer

than live vaccines because dead microbes have no possibility of mutating back to

their disease-causing state. However, most inactivated vaccines struggle to

stimulate strong immune responses compared to live vaccines and individuals

may require multiple booster shots until protective immunity is built.

Subunit: Instead of vaccinating with the entire microbe, subunit vaccines

include only the antigens that best stimulate the immune system. These

vaccines generally contain one or several protein antigens along with an adjuvant

that stimulates the immune system. The antigens are selected because they are

common antibody targets and/or they stimulate strong T cell responses. These

proteins are either harvested from the microbes themselves or they are

manufactured via recombinant DNA technology. A limited number of vaccine

adjuvants have been approved for human use. By far, aluminum-containing salts

such as aluminum hydroxide (alum) are the most widely used adjuvants in

human subunit vaccines11. Though alum has been used successfully in human

vaccinations for over 80 years, its mechanism of action as an immunological

adjuvant remains unclear.

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Adjuvants used in subunit vaccines

Adjuvants promote immune responses by recruiting APCs to the

vaccination site, increasing antigen uptake by APCs, and/or by activating APCs

to produce immunostimulatory cytokines that affect T cells and other immune

cells. Figure 1.2 summarizes adjuvants that are currently in use or being tested

for use in human vaccines. The class of adjuvant that boasts the longest

historical use in human vaccines is aluminum salts, referred to as alum. To

create an alum subunit vaccine, proteins sourced from a given pathogen are

adsorbed onto alum crystals, creating a slurry suspension that is injected

intramuscularly. Despite its long-standing and widespread use in human

vaccines, it is still not clear exactly how alum adjuvants work. The following

section is devoted to reviewing alum as an adjuvant, including proposed

mechanisms by which it stimulates immune responses.

Figure 1.2. Human vaccine adjuvants, adapted from Rappuoli et al., Nat Rev Immunol, 201122.

  13  

Aluminum Salts as Vaccine Adjuvants

Discovery and use in vaccines

In 1926, Alexander T. Glenny and colleagues reported that superior

antibody responses resulted from soluble protein immunizations if the protein

antigen was first precipitated onto insoluble particles of aluminum potassium

sulfate (potash alum)18. This was the first study to indicate that aluminum salts

have adjuvant properties. Following this discovery, aluminum salts were used in

vaccine preparations with tetanus and diphtheria toxoids to protect against C.

tetani and C. diphtheria, respectively. Today, various alum species are used in a

variety of safe and effective human vaccines worldwide (Table 1.2) that have

saved millions of lives, as illustrated in an infographic of vaccine efficacy within

the United States23 (Fig. 1.3).

Mechanism of action

Glenny proposed that aluminum salts were effective adjuvants because

they created antigen depots within the body and that, upon injection, alum

particles slowly released antigen over a long period of time. He reasoned that

this slow antigen release would promote prolonged and effective stimulation of

the immune system25, an effect referred to as the ‘depot effect.’ This explanation

was accepted as dogma for more than 60 years as there was little academic

interest in exploring the mechanism of alum adjuvant effect. In the past few

decades, however, interest in alum adjuvants has reignited and many research

  14  

Table 1.2. Vaccines that contain aluminum salt adjuvants. Information was sourced from the CDC24. Bolded vaccines contain aluminum hydroxide.

Vaccine Aluminum Salt Adjuvant Anthrax (Biothrax) Aluminum hydroxide Diphtheria, Tetanus, Acellular Pertussis

DT (Sanofi) DTaP (Daptacel) DTaP (Infanrix) DTaP-IPV (Kinrix) DTaP-HepB-IPV (Pediarix) DTaP-IPV/Hib (Pentacel) Td (Decavac) Td (Tenivac) Td (Mass Biologics) Tdap (Adacel) Tdap (Boostrix)

Aluminum potassium sulfate Aluminum phosphate Aluminum hydroxide Aluminum hydroxide Aluminum hydroxide, aluminum phosphate Aluminum phosphate Aluminum potassium sulfate Aluminum phosphate Aluminum phosphate Aluminum phosphate Aluminum hydroxide

Hib (PedvaxHIB) Aluminum hydroxphosphate sulfate Hib/Hep B (Comvax) Aluminum potassium sulfate, aluminum

hydroxyphosphate sulfate Hepatitis A

Hep A (Havrix) Hep A (Vaqta)

Aluminum hydroxide Amorphous aluminum hydroxyphosphate sulfate

Hepatitis B Hep B (Engerix-B) Hep B (Recombivax)

Aluminum hydroxide Aluminum sulfate, amorphous aluminum hydroxyphosphate sulfate

Hep A/Hep B (Twinrix) Aluminum phosphate, aluminum hydroxide Human Papillomavirus

HPV (Cerverix) HPV (Gardasil)

Aluminum hydroxide Amorphous aluminum hydroxyphosphate sulfate

Japanese Encephalitis (Ixiaro) Aluminum hydroxide Meningococcal (MenB – Bexsero) Aluminum hydroxide Pneumococcal (PCV13 – Prevnar 13) Aluminum phosphate

  15  

Figure 1.3. Efficacy of vaccines in the United States, adapted from an infographic created by Leon Farrant, based on a study by Roush et al., JAMA, 200723.

efforts have been directed at understanding the precise adjuvant actions of these

compounds. Alum’s mechanism of action remains largely mysterious as a

surprising number of immune pathways have been implicated as necessary and

later dismissed as dispensable, including the depot effect26,27.

Generation of protective antibodies: As it is their essential use, alum

adjuvants are well known to generate long-lived protective antibody responses

against their adsorbed antigens. Antibodies act by rapidly binding to pathogens

(or pathogenic products such as toxins) within the serum, mucosa, and other

tissues. Upon binding, antibodies may neutralize pathogens, opsonize them for

Alum%

  16  

future destruction, and/or activate complement cascades that directly kill the

bound pathogen. Antibody responses are considered protective when they are

present in high enough concentrations to effectively neutralize threatening

pathogens before they cause damage or disease in the host.

As an effective adjuvant, alum stimulates the activation and differentiation

of B cells into long-lived plasma cells that home to bone marrow and continue

secreting antibodies for months to years, maintaining a stable serum titer of

protective antigen-specific antibodies28–30. However, alum vaccines generally do

not induce antibody responses quite as robust as those generated by live

attenuated vaccines. For example, the alum-containing tetanus vaccine must be

re-administered every 10 to 15 years to ensure protection because the induced

tetanus toxoid-specific plasma cells eventually die off within vaccinees31.

The discoveries that class-switched antibody production depends on T cell

help32 and that different infections induce different TH cell subsets with disparate

functions33 led to an effort to determine which TH subsets are induced by alum

adjuvants. Alum was found to preferentially induce TH2 responses34 that direct

activated B cells to secrete TH2-associated antibody isotypes IgG1 and IgE in

mice. In humans and rhesus macaques, alum also induces potent IgG1-

dominated antibody responses, with smaller inductions of IgG3 and sometimes a

little bit of IgG4 isotypes35–41. However, mouse IgG1 and human IgG1 are

dissimilar in function, so inferences regarding alum-induced human antibody

responses from mouse studies must be done with great care.

  17  

At this point, I will discuss some of the issues that arise when mouse

research is translated into human biology when studying antibody isotypes within

protective immunity. In mammals, there are five classes of antibodies (IgM, IgD,

IgG, IgE, and IgA) with distinct structures, biological functions, and distributions

throughout the body. In humans there are four subclasses of IgG: IgG1, IgG2,

IgG3, and IgG4. IgG subclass nomenclature is independent among species so

murine IgG subclasses do not correspond to human. However, within a given

species, there is always a variety of antibody isotypes and subclasses that have

different functional abilities to fix complement or bind Fc receptors. For example,

human IgG1 and IgG3 excel at mediating antibody-dependent cellular cytotoxicity

(ADCC) and complement-dependent cytotoxicity (CDC) effector functions.

Accordingly, vaccines generally aim to induce these IgG subclasses to

confer immunity against most viral and bacterial pathogens. The ADCC and

CDC capabilities of human and mouse IgG subclasses are compared in Table

1.3. Alarmingly, alum predominantly induces antibodies with different functions

in humans (strong ADCC and CDC abilities) and mice (poor ADCC and CDC

abilities) (Table 1.3). This disparity suggests that mouse models are limited in

their ability to mirror alum responses in humans and should therefore be used

cautiously.

  18  

Table 1.3. Effector functions and alum induction of human and mouse antibody isotypes, adapted from Invivogen42 with added alum induction.

Species Isotype ADCC CDC Alum induction

Human

IgM - +++ unknown

IgG1 +++ +++ +++ 35–40,43

IgG2 +/- + +/- 37,38,40

IgG3 +++ ++++ ++ 38,40

IgG4 +/- - + 36–38,40

IgA1&2 ++ +/- unknown

IgE - - + 44,45

Mouse

IgM - +++ ++ 46–48

IgG1 - +/- +++ 34,47,49–51

IgG2a/c +++ +++ +/- 34,47,50,51

IgG2b +++ +++ - 34,47,50,51

IgG3 +++ + unknown

IgA ++ +/- unknown

IgE - - ++ 47,49,50

IgE function = mast and other cell degranulation. ADCC, antibody-dependent cellular cytotoxicity; CDC, complement-dependent cytotoxicity

Furthermore, while it is clear that alum induces classic type 2 responses in

mice, this may not actually be the case in humans. Though type 2 responses

vary among humans, TH2 responses generally induce IL-4, which promotes B

cell class switching to IgE and IgG4 isotypes. Conversely, human TH1 responses

employ IFNγ to promote IgG1 and IgG3 antibodies52–54. Therefore, I suggest that

alum induction of IgG1 antibodies in humans actually indicates TH1 immunity.

Clearly this is a disparity that remains in the literature since most reports still

insist that alum is a TH2 adjuvant in both mice and humans.

  19  

Regardless of the confusion surrounding which type of immune response

alum induces, the plain truth remains that alum is an effective and safe vaccine

adjuvant. One possible reason for its efficacy as a hepatitis B vaccine is that it

induces the same IgG subclasses as hepatitis B virus. Naturally, both chronic

and acute infections with hepatitis B virus induce mostly IgG1 antibody

responses, with contributions from IgG3 and IgG4 and little to no IgG238–40,55.

Therefore, it is fortunate that alum stimulates IgG1 antibodies in humans.

Innate immune cell activation: Antigen presenting cells (APCs) are central

to adaptive immune defenses – they bridge the gap between innate and adaptive

immunity by acquiring foreign antigens and presenting them to T lymphocytes.

They are also pivotal in initiating immune responses to alum vaccines. Aluminum

salts are known to generally activate APCs in vivo: promoting antigen uptake and

presentation, increasing surface expression of activation molecules, and

encouraging migration to lymphoid organs 56–61. However, alum only variably

induces these effects in vitro, as there have been conflicting reports of effect and

no effect of alum on APC maturation in vitro62,63. Additionally, the mechanism(s)

by which alum achieves APC activation is still unclear.

Though many natural adjuvants such as PAMPs stimulate TLRs, studies

in the literature agree that alum does not activate APCs via TLR signaling, since

MyD88 and TRIF signaling molecules are dispensable in alum responses

(reviewed in 56). Alum stimulates inflammasome activation within APCs, though

there is disagreement about whether or not this pathway is required for alum

adjuvant activity47,59,64–68. Furthermore, it is unclear whether inflammasome

  20  

activation by alum is direct or indirect. Both models agree that phagocytosis by

innate cells is required. In the direct activation model, phagocytic cells would

directly engage and engulf alum particles, leading to lysosomal damage, followed

by the release of stimulatory endosomal contents into the cytosol64,69. There is

no identified surface receptor that is specific for alum particles, though alum may

be detected by lipid sorting, similar to the detection of uric acid-derived

monosodium urate (MSU) crystals70,71. Alternatively, alum could indirectly

stimulate inflammasome activation by acting as a cytotoxin that causes the

release of endogenous DAMPs (including uric acid) from dying cells59. Uric acid

and resulting MSU crystals are known to activate the inflammasome pathway.

The cytotoxicity of alum will be discussed further in its own section.

In summary, all identified immunostimulatory actions of alum have been

deemed nonessential for the adjuvant activity of alum, except for the recently

identified innate mechanism of APC activation following lipid sorting upon

interaction of the plasma membrane with alum crystals. Alum is likely detected

by this innate mechanism that causes broad downstream inflammation.

Subsequent general inflammation seems to employ redundant pathways; it is

affected little by the loss of any one mechanism, making reductionist alum

research attempts difficult.

Many cells can act as antigen presenters, but the most efficient APCs are

conventional dendritic cells (cDCs), inflammatory monocytes (iMonos),

macrophages, and B cells. Though phenotypically and functionally very similar

(discussed in detail in the next sections), cDCs and iMonos differentiate from

  21  

different progenitor cells72,73 (Fig. 1.4). In the context of intramuscular injection,

alum-adsorbed antigen is acquired and presented to T cells by a variety of APC

subsets, the most prominent being the CD11b+ subset of cDCs and

iMonos58,59,61.

Though there are many specialized subsets of dendritic cells, conventional

DCs (cDCs) can be grouped into two general categories: 1) lymphoid tissue

resident DCs (resDCs) that live within secondary lymphoid tissues and 2) tissue-

resident DCs that reside in the parenchyma of nonlymphoid tissues and, upon

taking up antigen, migrate to draining lymph nodes (dLNs), where they are called

migratory DCs (migDCs). In the dLNs, migDCs excel in activating antigen-

specific naive T cells. cDCs express CD11c and MHC class II (MHC II)

molecules and can be categorized as CD8α+ or CD11b+ cDCs, a dichotomy that

accounts for phenotypic, developmental, and functional attributes74–76. Tissue

(muscle) resident CD11b+ cDCs are activated by i.m. alum vaccination. They are

the most numerous APC subset to take up alum-adsorbed antigen and migrate to

dLNs to present antigen to T cells (illustrated in Fig. 1.5, pink). Upon migration to

dLNs, they can be identified as CD11b+ migDCs by their very high MHC II

expression.

Monocytes exist in two subsets (Ly6Chigh classical blood monocytes and

Ly6Clow non-classical monocytes73,77) that mainly circulate within the blood,

though they have been found within various tissues during steady state as well.

In inflammatory conditions such as those caused by intramuscular alum

immunization, classical blood monocytes extravasate into tissues and locally

  22  

Figure 1.4. Conventional dendritic cell and monocyte differentiation in mice. Adapted from Geissmann et al. Science 2010 (Fig. 2)72 and Guilliams et al. Nat Rev Immunol 2014 (Fig. 2)73. Abbreviations: BATF3, basic leucine zipper transcriptional factor ATF-like 3; cDC1, classical type 1 DC; cDC2, classical type 2 DC; CDP, common DC precursor; cMop, common monocyte progenitor; FLT3, FMS-like tyrosine kinase 3; HSC, haematopoietic stem cell; IRF4, interferon-regulatory factor 4; LP, lymphoid precursor; MDP, monocyte, macrophage, and DC precursors; MP, myeloid precursor; PDC, plasmacytoid DC.

develop into CD11b+ CD11c− MHCII+ macrophages and CD11b+ CD11c+ MHCII+

inflammatory monocytes (iMonos). iMonos have also been called inflammatory

DCs or monocyte-derived DCs. Though iMonos and CD11b+ cDCs express

many of the same surface activation markers (namely CD11c, MHC II, and

CD11b), iMonos can be distinguished from CD11b+ cDCs by their expression of

CD64, the high affinity IgG receptor FcγRI61. Alum-containing immunizations

stimulate the recruitment and differentiation of classical blood monocytes into

CD64+ iMonos at the site of injection59 (illustrated in Fig. 1.5, yellow).

cMoP

?

Monocyte-derived cells

iMono

FLT3 ligand

CD11b+

CD8α+

  23  

Figure 1.5. CD11b+ cDCs and iMonos are the predominant APC subsets that respond to intramuscular alum injections. Adapted from Langlet et al. J Immunol 2012 (Fig. 3)61

Chapter IV contains a study that aimed to identify molecular signaling

pathways that are induced by alum adjuvant. The hypothesis was that i.m.

injection of alum plus antigen would significantly upregulate inflammatory

signaling pathways within APCs that migrated to dLNs (compared to APCs that

had only seen soluble protein antigen). To achieve this, RNA sequence profiles

were obtained from alum-responding APC subsets in order to gain insight on the

molecular pathways stimulated by alum.

Stimulating T cell responses: Alum adjuvants provoke strong TH2 immune

responses in mice34,78–80 but may struggle to build protective immunity against

CD11b+ cDC (in muscle) CD11b+ migDC (in LN) iMono

  24  

pathogens that require TH1 and cell-mediated immunity for clearance. TH2

responses are thought to have evolved to protect against multi-cellular parasites

and, now in many Western countries, drive allergies and atopic illnesses81.

Notably, alum responses can be skewed toward TH1 when alum is combined with

a toll-like receptor (TLR) 4 agonist such as monophosphoryl lipid A (MPL) as in

the Adjuvant System 04 (AS04) created by GlaxoSmithKline Biologicals82.

Though still up for debate, alum induction of TH2 responses has been attributed

to inflammasome activation62,65,83, early IL-4-producing eosinophil

recruitment46,48,50,59,84, and production of several other TH2-inducing cytokines

(IL-25, IL-1β, IL-6, and prostaglandin E2)68,78,85–87.

Furthermore, alum induces robust TFH differentiation in mice80,88, which

may explain why it is so effective at generating antibody responses since TFH are

critical helpers in B cell germinal centers89. Alum has also been reported to

induce TH17 responses in addition to TH2. In fact, one study found that IL-1

signaling promoted alum induction of TH17 cells and claimed that TH2 cells were

dispensable while TH17 cells were required for protective immunity against

pertussis51.

Alum is widely recognized as a poor inducer of CTL responses90. One

study even suggested that alum skews immune responses away from producing

CTLs since such strong antibody responses are initiated91. However, antigen-

specific CD8 T cells can be detected, though in small numbers, after alum

immunization92,93.

  25  

To summarize, alum induces robust TH2 responses in mice that

orchestrate long-lived antibody production; this is the basis for alum-induced

immune protection. Alum also induces protective antibody responses in humans,

though the ‘type’ of immune response may not be strictly TH2. A significant

contribution of TH17 responses has been suggested51, but needs to be verified by

other groups. Studies to verify alum’s effect on T cell differentiation in humans

are lacking, though our lab is working to remedy this gap in knowledge.

Alum’s cytotoxicity and host DNA as an induced self adjuvant: It has long

been known that alum crystals exert some level of cytotoxicity when injected as

vaccine adjuvants94. They are known to cause cell death at the site of injection47

and dying cells can release molecules that act as endogenous danger signals or

DAMPs that may activate innate immune cells95,96. Our group previously

reported that alum particles become entrapped by host chromatin upon i.m.

injection26, the site of administration for most human vaccines. Since this finding,

another group and we have suggested that DNA released by host cells at the site

of injection contributes to alum’s adjuvant activity47,49.

In 2011, Marichal et al. reported that host DNA is required for IgG1 and

IgE induction by alum vaccination47. Host DNA’s mechanism for promoting IgG1

remains a mystery, but IgE depended on stimulation of DNA-sensing pathways

involving [Tumor necrosis activating factor-associated NFκB activator (TANK)]-

binding kinase 1 (Tbk1) and interferon regulatory transcription factor 3 (Irf3).

DNA sensing led to increased local production of IL-12p80 and activation of

inflammatory DCs and monocytes that promoted downstream adaptive immune

  26  

responses. In 2013, our lab further contributed to the theory that DNA mediates

alum activity by reporting that alum-associated host DNA augments CD4 T cell

priming by enhancing MHC II antigen presentation by APCs and prolonging DC/T

cell interactions in draining LNs49. These effects were dependent on stimulator of

interferon genes (STING), a molecule upstream of Tbk1 and Irf3 in an

intracellular DNA-sensing pathway. Together, these studies defined an important

role for host DNA as an inducible, endogenous adjuvant that mediates alum

activity.

I began the main project of my thesis research with the goal of further

investigating the role of host DNA as a mediator of alum responses. Upon close

inspection, I noticed that the model systems and approaches used in the two

aforementioned studies had some caveats. First, they employed transgenic CD4

T cell adoptive transfer experiments that can be flawed in their ability to reflect

endogenous, wild-type biology. Second, both groups combined alum vaccines

with DNase I enzymes purchased from Roche Diagnostics Corporation to

examine loss-of-function scenarios that lacked extracellular host DNA as a

stimulus; there could be off-target effects of injected DNase enzymes. Third,

both groups curiously made no mention of DNA’s effects on CD8 T cell

responses, though it is not surprising that they focused on CD4 T cell responses

given alum’s preferential priming of TH2 cells. These caveats, especially the use

of DNase I as a vaccine treatment, will be discussed in great detail in Chapter III

as they turned out to be significant oversights in this field.

  27  

Chapters III and IV contain studies that aimed to better define the role of

host DNA in alum biology. Chapter III focuses on determining how DNA

stimulates T cell responses. In the early stages of this study, some of the results

from the Marichal et al. and McKee et al. papers were unrepeatable.

Consequently, my objective shifted from extending the research to reconciling

the disparities. It turns out that DNA is actually not necessary for alum

responses to certain antigens. Chapter IV examines the effect of alum on innate

immune cells, as mentioned above, though the study was originally launched to

explore the effects of host DNA on APCs.

Immunogenicity of Heat Aggregated Proteins

Chapter V contains data from my first few years of graduate study that

was spent focusing on the adjuvant activity of aggregated proteins. This

scientific topic is particularly relevant in clinical settings because many

therapeutic proteins that are administered to patients are partially aggregated

due to production or storage conditions.

Protein aggregation can cause a variety of diseases and conditions such

as Alzheimer’s disease, systemic amyloidoses, inappropriate neutralization of

administered therapeutic proteins, and even allergies97–100. Inappropriate

aggregation of endogenous proteins is usually prevented by complex cellular

quality control mechanisms such as heat shock protein chaperones during

  28  

protein folding as well as the unfolded protein response101. It is widely

recognized that protein aggregates are immunogenic and can induce specific

adaptive immune responses98–100,102–105. Most endogenous protein aggregates

are formed by hydrophobic interactions between damaged or misfolded proteins

that expose regions of their hydrophobic cores106–109. It is not clear how foreign

or endogenous protein aggregates are recognized as harmful entities by the

immune system. This project aimed to determine how protein aggregates

activate innate immune sensors and induce adaptive immune responses.

Given the wide, albeit vague, body of literature (explained further in the

Introduction to Chapter V) that suggests aggregated proteins are

immunogenic, I hypothesized that heat denatured protein aggregates are more

immunogenic than soluble proteins because dendritic cells can more efficiently

present them to prime specific T cell responses. Much of this project was left

unfinished as Pippa and I refocused my efforts on the alum project (Chapters III

and IV). In fact, after developing several reagents with which to test my

hypothesis, I only succeeded in testing the effect of aggregated proteins on T cell

responses before this project was moved to the back burner. Our long-term goal

was to understand how T cell responses to protein aggregates could be

manipulated for therapeutic purposes. Promoting immune responses to specific

protein epitopes would be instrumental in the effective treatment of viral diseases

and cancer, while suppressing immunity will mitigate unwanted immunity against

harmless protein antigens.

  29  

CHAPTER II

MATERIALS AND METHODS

Mice

C57BL/6.J mice were purchased from The Jackson Laboratory at 5 weeks

of age. STING-deficient mice were generated and provided by John Cambier at

National Jewish Health (NJH). STING-deficient mice had their genotypes

reconfirmed by PCR at the time of sacrifice. In all experiments, C57BL/6.J mice

were used unless specifically indicated otherwise. All mice were age matched

and between 6-18 weeks of age at the time of first immunization. Animals were

housed and maintained in the Biological Resource Center within NJH in

accordance with the research guidelines of the NJH Institutional Animal Care and

Use Committee.

Reagents, Antigens, Tetramers, and Antibodies

Reagents

Alhydrogel® aluminum hydroxide (Brenntag) was purchased from

Accurate Chemical. The following reagents were purchased from Sigma-Aldrich:

BSA (A8806), TPCK Trypsin (T-1426), a-Chymotrypsin (C-4129), and LPS (from

E. coli). The Kedl lab provided Poly(I:C) (GE Healthcare) and anti-CD40

antibody (FGK-45, BioXcell). Complete Tumor Medium (CTM) was created by

  30  

adding 10% FBS and KM tumor cocktail (containing nutrients and antibiotics) to

Minimal Essential Medium for suspension cultures (GibcoTM).

Model antigens

Chicken ovalbumin (OVA) was purchased from Sigma-Aldrich (grade VII,

A7641). Fluorescent antigens were either purchased from InvitrogenTM

Molecular Probes® (OVA-A488, OVA-A647, OVA-FITC) or conjugated in-house

using life technologiesTM molecular probes® conjugation kits (OVA-A647, OVA-

A488, NP-A647, NP-A488).

OVA-NP was generated using Imject Maleimide-Activated Ovalbumin Kit

(Pierce Biotechnology) and cysteine-linked influenza A nucleoprotein peptide

NP311-325 (QVYSLIRPNENPAHKGGGC) purchased from CHI Scientific.

PR8 influenza A nucleoprotein (NP) was produced as previously

described92. Briefly, Hi-5 insect cells were infected with a baculovirus expression

vector containing Influenza A nucleoprotein (PR8) with a 6-Histadine tag. After 3

days, infected cells were lysed, treated with DNase and RNase, and NP was

purified by nickel column (Ni++-NTA-Agarose beads, Qiagen) and, in some cases,

size exclusion chromatography using “Aurora,” a HiLoadTM 26/60 SuperdexTM

200 prep grade column (GE Healthcare). Mutant NP (mutNP), containing five

arginine residues mutated to alanines at positions 74, 75, 174, 175, and 221, was

cloned and produced in the same manner using a baculovirus expression vector.

  31  

Tetramers

Tetramers (listed in Table 2.1) were either obtained from the NIH Tetramer

Core Facility or produced in-house as described previously 110.

Table 2.1. Tetramers used for flow cytometry.

Tetramer Peptide Fluorophore Working Conc. Source

IAb/NP311-325 QVYSLIRPNENPAHK PE, APC 14 µg/ml NIH Tetramer Core

IAb/OVA323-339 ‘DO register’ ISQAVHAAHAEINEAGR PE 20 µg/ml KM lab

Db/NP366-374 ASNENMETM APC 14 µg/ml NIH Tetramer Core

Kb/OVA257-264 SIINFEKL APC 0.5-2 µg/ml KM lab

Antibodies

Antibodies (listed in Table 2.2) were either purchased from vendors or

purified from B cell hybridoma supernatants in our laboratory, as indicated.

Table 2.2. Antibodies used for flow cytometry.

Antibody Clone Fluorophore Working Dilution Source

T cell analyses B220 RA3-6B2 eFluor450 1:500 eBioscience Bcl-6 7D1 PE 1:200 BioLegend CD4 RM4-5 APC-e780 1:400 eBioscience

CD8a 53-6.7 PE-Cy7 1:800 eBioscience

CD44 IM7 PerCP-Cy5.5 1:400 eBioscience

CXCR5 2G8 Biotin, SA-PE-Cy7 1:100, 1:1000 BD Pharmingen

F4/80 BM8 eFluor450 1:200 eBioscience MHC II Y3P Pacific Blue 1:800 KM lab PD-1 J43 FITC 1:200 eBioscience  

  32  

Table 2.2. Antibodies used for flow cytometry.

Antibody Clone Fluorophore Working Dilution Source

Antigen presenting cell analyses

B220 RA3-6B2 FITC, PE, PE-Cy7, PerCP-Cy5.5

1:100-500 BD Pharmingen, eBioscience

CD11c N418 PE-Cy7 1:400 eBioscience

CD11b M1/70 APC-A750, PerCP-Cy5.5, PB

1:400-500 BioLegend, eBioscience,

CD64 X54-5/7.1.1 PE 1:100-200 BD Pharmingen

Ly6C HK1.4 eFluor450, PerCP-Cy5.5 1:200 eBioscience

MHC II (IA/IE) M5/114.15.2 FITC, APC,

APC-Cy7 1:500-1000 eBioscience

DNases

DNase preparations were either purchased or produced in-house, as

indicated in Table 2.3. To produce wtDNase and mutDNase, plasmids

containing wild-type or mutated (R111A, D212A, H252A) bovine DNase I

nucleotide sequences with 6x Histidine tags that were optimized for Homo

sapiens translation were ordered from Integrated DNA Technologies, Inc. Janice

White digested and ligated these genes into the CMVR-VRC01-L plasmid (NIH

AIDS Reagent Program) in place of the immunoglobulin genes it came with,

using Sal1 and BamH1 cut sites. Plasmids were transformed into XL1-Blue E.

coli (Agilent) and selected on kanamycin agar plates. Colonies were picked,

Minipreps were made, and plasmids were sequenced using the following

  33  

primers: 6187 DNase fwd, 6188 DNase rev, 2844 CMV fwd. Suitable plasmids

were: p2127-2 = wtDNase; p2128-1 = mutDNase.

Transfection of FreeStyleTM 293-F cells (Life Technologies, derived from

293 human embryonic kidney cells) with these plasmids was outsourced to Lori

Sherman at the UCCC Protein Production Core Facility. She followed a standard

PEI transfection protocol, using 750 µg plasmid DNA per liter of cells.

Supernatants were collected 6 days after transfection, bound to Ni-NTA

agarose (QIAGEN), washed, and eluted with an increasing gradient of imidazole

elution buffer. DNase-containing fractions were grouped, buffer exchanged to

PBS by Amicon Ultra® centrifugal filtration, flash frozen, and stored at -20°C.

Table 2.3. DNase reagents used in Chapter III Alias within Thesis Product Name Vendor Source

Catalog Number

Lot(s) used

Roche DNaseGII DNase I, grade II Roche bovine pancreas 10104159001 10172600, 13814800

Roche Recomb DNase DNase I recombinant Roche

from bovine pancreas, expressed in Pichia pastoris grade I

04 536 282 001 10392800

Sigma DNase Deoxyribonuclease I, from bovine pancreas

Sigma-Aldrich bovine pancreas D4513-1VL 040M7012,

070M7008V

Worth DNase Deoxyribonuclease I, Ribonuclease & Protease Free

Worthington Biochemical Corporation

bovine pancreas LS006334 52N13773

wtDNase -------- -------- WT DNase I from bovine pancreas + 6xHis tag, expressed in 293F cells

-------- --------

mutDNase -------- -------- mutant DNase I (R111A, D212A, H252A) from bovine pancreas + 6xHis tag, expressed in 293F cells

-------- --------

  34  

Preparation of Soluble or Aggregated Protein Antigens (Chapter V)

Soluble protein

OVA (Sigma-Aldrich, grade VII, lot 066K7020) or NP was filtered through

a 0.22 µm polyethersulfone membrane (Millex® or Thermo Scientific) and, if

indicated, ultracentrifuged at 200,000 x g for 2 hours (OptimaTM L-100 XP

ultracentrifuge, Beckman Coulter). Only the top portion of a sample was

collected after ultracentrifugation. Protein preparations were stored at 4°C.

Aggregated protein

OVA or NP (at indicated concentration in PBS) was filtered (0.22 µm) and

then heated at 80°C for 10 min or 96-98°C for 5-10 min, as indicated.

Alternatively, NP was cross-linked with gluteraldehyde (0.5%) for 2 hours, then

buffer exchanged to PBS.

Assessing Protein Conformation and Aggregation (Chapter V)

Size exclusion chromatography

Monomers and aggregates were distinguished within soluble OVA

preparations by size exclusion chromatography on “Fiona,” a SuperdexTM 200

10/300 GL column (GE Healthcare). Fran Crawford oversaw this procedure.

  35  

Micro-flow imaging

Particulates between 1-1000 µm in size were counted (per ml) for various

soluble OVA preparations. Samples were prepared at 5 mg/ml in PBS and

analyzed by micro-flow imaging (MFITM DPA 4100, ProteinSimple®) at 0.1

ml/minute flow rate.

Infrared spectroscopy

Soluble OVA preparations were assessed for secondary structure by mid-

infrared Fourier transform infrared spectroscopy (FTIR). Soluble and heat

aggregated OVA samples were prepared at 20 mg/ml in PBS and analyzed using

an MB-series FTIR spectrometer (ABB Bomem Inc). Amide I region spectra

were corrected and second-derivatives were compared between samples using

BGRAMSTM software (Galactic Industries).

Measuring surface hydrophobicity

OVA samples were diluted to 0.1 mg/ml in PBS and 1-anilinonaphthalene-

8-sulfonic acid (ANS) was added to a final concentration of 20 µM. ANS is a

fluorescent stain that binds to hydrophobic regions on proteins. Upon binding to

hydrophobic surfaces, ANS fluorescence was detected using a FeliX32TM

spectrofluorometer (Photon Technology International). Samples were

maintained at 23°C, excited at 350 nm, and scanned for emission between 400-

500 nm.

  36  

Immunizations

Mice were anesthetized with 2.5% (vol/vol) isoflurane and injected i.m. in

each calf muscle with a total vol of 50µl per calf, unless another immunization

route is indicated. For T cell studies, all vaccines consisted of 10 µg protein

antigen (OVA, OVA-NP, NP, or mutNP) that was fully adsorbed to 200 µg alum

(or combined with other adjuvants, as indicated) and suspended in endotoxin-

free PBS (Cellgro). For APC studies, vaccines contained dose of antigen

between 5-20 µg of OVA-A647, OVA-A488, OVA-FITC, NP-A647, or NP-A488.

When indicated, additional reagents (BSA, various DNases, trypsin, and/or

chymotrypsin) were added as treatments to vaccines immediately before

injection. The endotoxin content of each vaccine component was <1

EU/injection, as measured by Limulus Amoebocyte Lysate Assay (Lonza).

Assessment of Antigen-Specific T Cell Priming

Popliteal LNs were harvested into ice-cold balanced salt solution and

disrupted through nylon mesh to create single cell suspensions. Cells were

counted using a Z1 Coulter® Particle Counter (Beckman Coulter) and then

stained with tetramers (Table 2.1) for 2 hours at 37°C (25 µl volume in CTM +

heat inactivated normal mouse serum and 2.4G2 blocking antibody). Antibodies

for CD4, CD44, CD8a, B220, MHC II, and F4/80 were added and the cells were

further incubated for at least 30 min on ice or at 4°C. Cells were washed and

  37  

analyzed on a CyAnTM ADP Analyzer (Beckman Coulter) flow cytometer using

Summit Software (DakoCytomation) and then FlowJo software (TreeStar).

IAb/peptide tetramer-positive cells were defined after gating on live,

singlet, CD4+ CD44hi cells that were negative for CD8a, B220, MHC II, and

F4/80 (Fig. 2.1). Kb/peptide or Db/peptide tetramer-positive cells were similarly

defined, but were gated on CD8a+ and CD4– (Fig. 2.1). Total numbers of

tetramer+ cells per organ were calculated by multiplying the percentage of

tetramer+ cells within the FlowJo live gate by the total cells counted per organ by

Coulter® Counter.

Antigen Presenting Cell Analyses

Draining LNs (dLNs) were harvested from mice 6-72 hours (as indicated)

after immunization into ice cold Collagenase D solution: HBSS (without calcium

or magnesium, GibcoTM) + Collagenase D (2.5 mg/ml, Roche) + 1% FCS that

was pretreated with 0.02 mM EDTA + 100 µg/ml DNase I (Roche, DNaseGII).

dLNs were minced with two 25G needles, incubated 37°C for 30 min, then placed

on ice and collagenase digestion was stopped with EDTA addition to 10-50 mM.

Digested tissues were mechanically disrupted by vigorous Pasteur pipetting,

filtered (100µm), washed, and then stained with antibodies (listed in Table 2.2)

for 45-60 min while on ice or at 4°C. Cells were washed and analyzed on a

CyAnTM ADP Analyzer (Beckman Coulter) flow cytometer using Summit Software

(DakoCytomation). Data were analyzed using FlowJo software (TreeStar).

  38  

Live

CD

4+ d

ump-

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CD

8-

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D44

+ te

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CD

8+ d

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Figu

re 2

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Ant

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ting

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(CD

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, B22

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HC

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0-, a

nd s

ingl

ets

by p

ulse

wid

th.

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en-s

peci

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cel

ls w

ere

iden

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44+

tetra

mer

+ (IA

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Kb o

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8).

Tota

l tet

ram

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cell

num

bers

per

org

an w

ere

calc

ulat

ed b

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ultip

lyin

g th

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rcen

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of t

etra

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the

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gate

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low

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  39  

RNA Sequencing: Cell Preparation and Analysis

Mice were immunized with 10 µg OVA-A647 ± 200 µg alum + 1 mg BSA

or Roche DNaseGII. Popliteal dLNs were harvested 24 hours after

immunization, grouped from 10-20 mice per treatment group, and processed and

stained as described above for antigen presenting cells. Samples were

resuspended in sorting diluent (1X PBS + 1 mM EDTA + 1% FCS + 25 mM

HEPES pH 7.0) and antigen-loaded A647+ cells were sorted into B220+ (B cell),

CD11chigh (DC), or CD11bhigh (iMono) populations (Fig. 2.2 and Table 2.4),

collected in CTM. Samples were sorted using a MoFloTM XDP-70 (Beckman

Coulter) high speed cell sorter by Alistaire (Lester) Acosta at the University of

Colorado Cancer Center Flow Cytometry Shared Resource (Anschutz Medical

Campus location). Sorted cells were washed once with PBS, spun, resuspended

in QIAzol Lysis Reagent (QIAGEN), flash frozen with dry ice, and stored at -80°C

before shipment on dry ice to Expression Analysis, Inc. (Durham, NC) for RNA

sequencing analysis.

Expression Analysis, Inc., performed RNA sequencing on these sorted cell

populations. RSEM expression counts were normalized within samples by upper

quartile (75th percentile) normalization to 1000:

Normalized count genei samplex =

expression count genei x 1000 75th percentile (samplex)

Normalized gene expression was compared between treatment groups (antigen

± alum + BSA or DNase) within given cell populations (B cell, iMono, or DC) by

  40  

Figure 2.2. Gating scheme for antigen-loaded APC sorting prior to RNA sequencing. All cells were gated on live, A647+ singlet events. iMonos, DCs, and B cells were gated as shown and as described in Table 2.4. Sorting gate boundaries were intentionally conservative. Table 2.4. Sorted cell populations submitted for RNA sequencing.

Population name Population phenotype Number of sorted cells submitted

B cells B220+ CD11c- CD11b-

OVA-A647: 119,300 OVA-A647+alum+BSA: 88,200 OVA-A647+alum+DNase: 117,100

iMonos CD11bhigh CD11cint

OVA-A647: 54,100 OVA-A647+alum+BSA: 88,200 OVA-A647+alum+DNase: 116,900

DCs CD11chigh CD11bint-high

OVA-A647: 27,100 OVA-A647+alum+BSA: 23,700 OVA-A647+alum+DNase: 37,400

live%

MHC%class%II%

CD11b%

CD11c%

FSC%(Height)%

SSC%(Height)%

APC subsets

OVA-A647+ singlets

B cells

SSC%(Height)%

OVA

:A647%

CD11b%

B220%

SSC%(Width)%

B cells

iMonos

DCs

  41  

calculating fold-change differences. Fold-change of normalized gene expression

between experimental groups was calculated by dividing one group’s gene

expression value by another’s. To avoid mathematical issues, if a gene’s

normalized expression value was equal to 0, its value was changed to 1 for fold-

change calculations because 1 represented a low value within the normalized

gene expression counts. There were few normalized counts that were positive

values less than 1. Also, for each fold-change comparison between groups, if

the numerator value was zero for a given gene, that gene was excluded from the

analysis. Fold-change calculations were performed in excel, but the general

equation is described here in an example to calculate genes that alum treatment

increased, compared to antigen alone:

Fold-change  (antigen+alum+BSA

antigen)  =

Norm. expression (genei (antigen+alum+BSA), if not = 0)Norm. expression (genei (antigen), if = 0, then change to = 1)

Sonia Leach at National Jewish Health generated a heat map of gene

cluster expression within each of the alum-treated or untreated APC subsets.

Relative expression values of genes were clustered by heat map with respect to

respective mean expression for each gene across all samples. Thus warmer

colors (red) indicate expression higher than the gene's mean across all samples

while cooler colors (blue) indicate expression lower than the gene's mean.

Genes with greater than 2-fold-change difference in their expression

between treatments were identified for each cell population and analyzed by

Database for Annotation, Visualization, and Integrated Discovery (DAVID) v6.7

bioinformatics resources web program (NIAID, NIH). Analyses included Kegg

  42  

Pathways, Swiss-Prot and Protein Information Resource Keywords, and Gene

Ontologies of cellular components, molecular functions, and biological

processes. Functional gene clusters were analyzed if the DAVID program

calculated their enrichment score to be ≥1.

Antibody Detection by ELISA

For OVA-, mutNP-, and NP-specific IgG1 detection, we incubated serially-

diluted sera from immunized mice on 96-well Immulon plates (Thermo Scientific)

coated with OVA (grade VII, Sigma-Aldrich) at 100 µg/ml or mutNP or NP at 10

µg/ml. We detected bound IgG1 using alkaline phosphatase-conjugated anti-

mouse IgG1 antibodies (BD Pharmingen) followed by incubation with p-

nitrophenyl phosphate and measurement by spectrophotometry. To determine

relative units, we used positive control serum samples from B6 mice that

contained OVA-specific or NP-specific antibodies.

Assessing DNase Reagent Purity

SDS-PAGE

Samples (>8mg/ml) were reduced, heat denatured, and applied to a SDS

PhastGelTM Homogenous 12.5% polyacrylamide gel (GE Healthcare) as

recommended by the manufacturer. Low Molecular Weight standards (GE

  43  

Healthcare) were applied alongside the samples. Gels were stained with

Coomassie® Brilliant Blue G-250 (Bio-Rad).

Protease activity assay

Pierce Protease Assay Kit (Thermo Scientific) was used according to the

manufacturer’s instructions. TPCK trypsin standard was serially diluted by 5-fold

while samples were serially diluted by 2-fold.

Mass spectrometry

Samples were prepared in PBS and reduced, denatured, alkylated, and

digested overnight at 37°C with Trypsin Gold (Promega). Peptides within

samples were chromatographically resolved on-line using a C18 column and

1260 series high performance liquid chromatography (HPLC, Agilent

Technologies) and analyzed using a 6550 LCMS QTOF mass spectrometer

(Agilent Technologies, Palo Alto, CA) in the National Jewish Health Proteomics

Facility. Raw data was extracted and searched using the Spectrum Mill search

engine (Rev B.04.00.127, Agilent Technologies, Palo Alto, CA). “Peak picking” is

performed within SpectrumMill with the following parameters: signal-to-noise set

at 15, maximum charge state of 4 was allowed (z=4), and the program was

directed to find a precursor charge state. During searching the following

parameters were applied: searched the SwissProt Bovine database,

carbamidomethylation as a fixed modification, oxidized methionine and

deamidated asparagine as variable modifications, collected spectra were

  44  

compared to tryptic peptides in the database, maximum of 2 missed cleavages,

precursor mass tolerance +/- 20 PPM, product mass tolerance +/- 50 PPM, and

maximum ambiguous precursor charge = 3. Data were evaluated and protein

identifications were considered significant if the following confidence thresholds

were met: minimum of 3 peptides per protein, protein score > 10, individual

peptide scores of at least 6, and Scored Percent Intensity (SPI) of at least 60%.

The SPI provides an indication of the percent of the total ion intensity that

matches the peptide’s MS/MS spectrum. Standards were run at the beginning of

each day of analyses for quality control purposes.

DNase Activity Assay

DNase reagents were serially diluted in 96-well round bottomed tissue

culture plates and exposed to 800 ng genomic mouse DNA within PBS + 25 mM

MgCl2 and 5 mM CaCl2 for 30 min at 37°C. Enzymatic activity was stopped by

heat denaturation at 95°C for 5 min and samples were immediately placed on ice

and assessed for double-stranded DNA content using a Qubit® dsDNA Broad

Range Assay Kit. Alternatively, samples were ran on a 5% agarose gel (50V, 50

min) alongside untreated DNA (800 ng) and HyperLadderTM V (25bp, Bioline)

molecular weight marker for determination of size of DNA fragments. DNA

fragments were visualized by staining the gel with ethidium bromide and imaging

under ultraviolet light.

  45  

Antigen Destruction Assay

Protein antigens (OVA-NP or NP) were prepared at 200 µg/ml in PBS + 25

mM MgCl2 and exposed to treatments for 0, 1, or 21 hours at 37°C. To mimic

vaccine preparations, treatments were as follows: BSA (20 mg/ml), Roche

DNaseGII (20 mg/ml), trypsin (200 µg/ml), or chymotrypsin (200 µg/ml). OVA-NP

or NP mixtures were then added in duplicate to tissue culture wells containing

Chb-2.4.4 antigen-presenting B cells and ‘3NP311-2’ NP311-325-specific T cell

hybridomas. Cells were incubated for 24 hours at 37°C then supernatant were

tested for IL-2 by sandwich ELISA. Supernatants were serially diluted on 96-well

Immulon plates (Thermo Scientific) coated with anti- IL-2 (eBioscience). Bound

IL-2 was detected with biotin-conjugated anti-IL-2 (eBioscience) followed by

HRP-conjugated streptavidin (Jackson Immunoresearch) and subsequent

incubation with 1-step Ultra TMB substrate (Thermo Scientific) and 2M H2SO4

stopping solution. Plates were measured by spectrophotometry.

Generation of 3NP311-2 NP311-325-specific CD4 T Cell Hybridomas

Female C57BL/6 mice were immunized i.m. with 10 µg OVA-NP + 200 µg

alum. Draining LNs were harvested on day 7 and stimulated for 4 days in vitro

with 100 µg/ml NP311-325 peptide (CHI Scientific) in Click’s medium + 1% normal

mouse serum. Antigen-specific T cell blasts were grown for 3 more days in CTM

+ IL-2 and then fused to BW5147α-β- (AKR thymoma) cells and cultured in CTM

  46  

with HAT (hypoxanthine-aminopterin-thymidine) added after 1 day. Colonies of

hybrids were picked and grown up in CTM. The colonies were not cloned

because they were mathematically clonal from fusion. Hybrids (including

3NP311-2) were tested for their ability to respond (IL-2 secretion) to the following

proteins/peptides presented by Chb cells: OVA (no response), OVA-NP (positive

response), and NP311-325 peptide (positive response).

Statistical Analyses

All statistical analyses were conducted using GraphPad Prism software.

All statistics shown were generated using two-tailed pairwise Student’s t tests

unless otherwise specified. Asterisks (*) were used to indicate significant

differences observed when comparing indicated groups: * p < 0.05; ** p < 0.01;

*** p < 0.001. Comparisons that were not significant were marked ‘ns’, in which

p ≥ 0.05.

  47  

CHAPTER III

HOST DNA IS DISPENSABLE IN ALUM RESPONSES1

Introduction

For over 80 years, insoluble aluminum salts (alum) have been safely used

in subunit vaccines to generate protective immunity in hundreds of millions of

people. Alum, in a variety of forms, is a component of many commonly

administered vaccines (listed in Table 1.2 and Fig. 1.3 of Chapter I). Despite its

extensive and continuous use, the mechanism by which alum promotes effective

immune responses eludes complete understanding. In mouse models of

vaccination, alum is widely known to induce T helper 2 (TH2) responses and

subsequent production of IgG1 and IgE antigen-specific antibodies (reviewed in

56). However, the immune mechanisms triggered by alum to cause these effects

are controversial or still unknown.

Our lab has previously reported that alum particles become entrapped by

host chromatin upon intramuscular injection26. Since reporting this finding,

another group and we have shown that DNA released by host cells at the site of

injection can mediate adaptive immune responses to alum vaccines47,49. In these

studies, it was concluded that alum-associated DNA acted as an endogenous

immunostimulatory signal that triggered activation of the DNA-sensing pathway

involving Stimulator of Interferon Genes (STING) within innate immune cells such

                                                                                                                         1  This chapter is under review for publication in The Journal of Immunology.  

  48  

as inflammatory monocyte-derived dendritic cells (iDCs). Activated iDCs then

facilitated CD4 T cell priming and subsequent IgG1 and IgE antibody responses.

These studies were based, in part, on transgenic CD4 T cell adoptive transfer

experiments as well as loss-of-function experiments that combined alum

vaccines with DNase I enzymes purchased from Roche Diagnostics Corporation.

Notably, there were no reported effects of DNA on alum-induced CD8 T cell

responses. These reports defined a possible role for host DNA in alum biology

that needed further clarification.

The objective of this study was to reconcile the differences observed

between the effects of alum-associated DNA on CD4 versus CD8 T cell

responses to alum vaccines. I began by scrutinizing the quality of commonly

used DNase I reagents that were used to study deficiencies within alum-induced

T cell responses mounted in the absence of host DNA stimuli. Here I report that

DNase treatment impairs T cell responses to alum due to activity of

contaminating proteases within DNase reagents and not DNase enzyme activity.

Furthermore, I observed normal immune responses to alum in mice deficient in

the DNA-sensing molecule STING. We conclude that DNA and DNA-sensing

molecules are not major contributors to adaptive immune responses mounted

against alum vaccines administered to the muscle.

  49  

Results

Creating model antigens: OVA-NP and mutant nucleoprotein

Others and we recently proposed that co-injected DNase I treatment

impairs primary CD4 T cell priming following immunization with alum adjuvant

because endogenous DNA danger signals are eliminated47,49. To elucidate the

mechanisms behind this phenomenon as it pertains to single doses of

intramuscularly administered human vaccines that contain alum, we analyzed T

cell responses in mice to intramuscular (i.m.) vaccinations containing alum, with

and without DNase treatment, and two model antigens: chicken ovalbumin (OVA)

and influenza A nucleoprotein (NP). OVA is well known to generate robust CD8

T cell responses in C57BL/6 mice to its immunodominant CD8 epitope:

SIINFEKL. However, OVA-specific CD4 T cell responses are inconsistent

among individual C57BL/6 mice, so we instead created an altered OVA antigen

(OVA-NP) that consists of the NP311-325 peptide (an immunodominant epitope of

influenza A nucleoprotein in mice expressing IAb MHC class II molecules)

chemically conjugated to OVA protein. CD4 T cells in C57BL/6 mice respond

consistently to NP311-325 and their response is easily detectable with IAb tetramers

5-9 days after immunization92,111.

Since influenza NP binds influenza RNA, it was possible that NP-bound

RNA could act as a confounding adjuvant within alum + NP vaccines. To ensure

that NP antigen was adjuvant-free, we produced a mutant version of NP (mutNP)

that cannot bind RNA112. The five alanine mutations within mutNP and its

  50  

consequent inability to bind RNA do not affect the generation of T cell or antibody

responses to this antigen alone or adsorbed to alum (Fig. 3.1). As such, both

antigens (NP and mutNP) were used within this study and were considered

interchangeable.

Figure 3.1. MutNP and NP stimulate equivalent alum immune responses. Mice were immunized with mutNP or NP ± alum. (A) Antigen-specific CD4 and CD8 T cells were quantified on d9 after immunization with tetramers and antibodies as described in Chapter II. Data were combined from 2 independent experiments with n = 3. (B) Serum samples were taken on d14 and tested for anti-mutNP or anti-NP IgG1 antibodies by ELISA. Data is representative of 2 independent experiments with n = 6. RU, relative units.

Roche DNase I grade II does not affect adaptive immune responses to epitopes within intact protein antigens

Primary T cell responses. Mice were immunized i.m. with OVA-NP that

was adsorbed to Alhydrogel® aluminum hydroxide (alum) adjuvant and injected

in the presence or absence of Roche DNase I grade II (Roche DNaseGII)

enzyme isolated by Roche from bovine pancreas. To control for the addition of

  51  

Roche DNaseGII, which could potentially compete with OVA-NP either as a

foreign antigen or for binding to alum, we added BSA instead of DNase to the

immunizations administered to control mice. The addition of BSA to the alum

vaccines did not significantly affect antigen-specific responses (Fig. 3.2).

Antigen-specific T cell responses were quantified in immunized mice 7 days after

injection. Co-injection of Roche DNaseGII with alum + OVA-NP resulted in a 4-

fold reduction in numbers of NP311-325-specific CD4 T cells in draining popliteal

lymph nodes (Fig. 3.3A). However, Roche DNaseGII did not affect SIINFEKL-

specific CD8 T cell responses (Fig. 3.3B). Unexpectedly, when intact

nucleoprotein (NP) was used as an alum vaccine antigen, we found that CD4

and CD8 T cell responses were unaffected by Roche DNaseGII (Fig 3.3C-D).

Primary antibody responses and secondary CD4 T cell responses. Unlike

past reports on this subject 47,49, IgG1 responses to alum + OVA or mutNP were

resistant to Roche DNaseGII treatment (Fig 3.3E-F). Since alum vaccines are

used to generate protective memory responses, I determined if Roche DNaseGII

treatment altered the effectiveness of alum vaccines to generate protective

immunity by evaluating secondary recall responses upon challenge. Mice were

primed with OVA-NP + alum ± Roche DNaseGII and then later challenged with

mutNP + alum. The change of antigen from OVA-NP to mutNP removed the

effects of anti-OVA-NP neutralizing antibodies from the challenge environment

while retaining the NP311-325 epitope for CD4 T cells. Secondary CD4 T cell

responses were assessed on day 5 after challenge. Roche DNaseGII treatment

of the priming immunization did not affect secondary CD4 T cell responses (Fig.

  52  

3.4). This indicated that the reduced total numbers of CD4 T cells in the primary

response (reported in Fig. 3.3A) were not impaired from becoming memory cells

capable of mounting robust secondary responses upon challenge.

Figure 3.2. Added BSA has no effect on the magnitude of NP311-325-specific CD4 T cell responses to alum immunization. Mice were immunized with OVA-NP ± alum ± 1 mg BSA or Roche DNaseGII. Antigen-specific CD4 T cells were quantified on d7 after immunization with tetramer and antibodies as described in Chapter II. Data is representative of 2 independent experiments each with n = 3 or 5. Error bars show means ± SEM for each group. Statistical differences were determined using an unpaired Student’s t test; ns indicates p > 0.05.

Figure 3.4. DNase treatment does not impair secondary CD4 T cell responses. Mice were challenged with 10 µg mutNP + 200 µg Alhydrogel® alum at least 25 weeks after primary immunization with OVA-NP ± alum ± Roche DNaseGII or BSA. Cells from dLNs were analyzed 5 days after challenge immunization, as described in Chapter II. Data are cumulative of two independent experiments each with n = 4. Error bars show means ± SEM for each group. Statistical differences were determined using an unpaired Student’s t test; ns indicates p > 0.05.

1

10

ns**

Tota

l num

ber o

fIA

b -N

P T

et+

CD

4 T

cells

x10

-3

Priming immunization:

All groups challenged with mutNP + alum

Treatment − − BSA Roche DNaseGII

Alum − − + + OVA-NP311 − + + +

  53  

Figure 3.3. DNase treatment does not affect CD4 T cell responses to intact proteins

  54  

Figure 3.3. DNase treatment does not affect CD4 T cell responses to intact proteins. Mice were immunized with the indicated combinations of antigen ± adjuvant ± 1 mg of Roche DNaseGII or BSA. (A-D,G) Antigen-specific CD4 and CD8 T cells were quantified on d7 after immunization with tetramer and antibodies as described in Chapter II. (E,F) Serum samples were taken 21 d after immunization and tested for the presence of anti-OVA or anti-mutNP IgG1 antibodies by ELISA. RU, relative units. Data in: (A-D) were combined from 4-10 independent experiments each with n = 3-4, (E,F) were combined from two independent experiments each with n = 5-8, and (G) were combined from 2-3 independent experiments each with n = 3-4. Error bars show means ± SEM for each group. Statistical differences were determined using an unpaired Student’s t test; *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001; ns indicates p > 0.05.

  55  

To examine these disparities further, I tested the effects of Roche

DNaseGII on CD4 T cell responses to two other common vaccine adjuvants:

lipopolysaccharide (LPS) and combined anti-CD40 + poly(I:C). Roche DNaseGII

treatment reduced CD4 T cell responses to OVA-NP combined with either of

these adjuvants (Fig. 3.3E). These were surprising results because neither of

these adjuvants is thought to act via host DNA. My findings suggested that the

Roche DNaseGII preparation might be affecting the immune response in some

unforeseen way.

Commercial DNase I reagents are contaminated with active proteases

To determine if other commercial DNase products had the same effects as

Roche DNaseGII did on alum-induced immune responses, we tested two other

DNase preparations: Sigma-Aldrich DNase I (Sigma DNase, from bovine

pancreas) and Roche DNase I recombinant (Roche Recomb DNase, from Pichia

pastoris). DNase treatments were administered as 2000 Kunitz units per mouse

based on vendor-reported Kunitz units of activity.

These three DNases had different effects on CD4 T cell responses to

alum + OVA-NP (Fig. 3.5A). Sigma DNase had the same effect as Roche

DNaseGII: leading to a more than 4-fold reduction in response. Roche Recomb

DNase, on the other hand, did not significantly impair CD4 T cell responses.

This DNase was recombinantly produced in yeast, however, and is probably

glycosylated with high mannose sugars since it contains two possible N-linked

glycosylation sites. High mannose sugars are known to have adjuvant properties

  56  

that stimulate T cell responses in mice113,114. Therefore we cannot tell whether

the Roche Recomb DNase simply had no effect on CD4 T cell priming or

possessed confounding adjuvant properties.

My first step in investigating why the DNases had variable effects on alum

T cell priming was to analyze the protein content of each DNase preparation by

SDS-PAGE. The smear of bands that appear in both the Roche DNaseGII and

Sigma DNase lanes indicated that these products are highly impure (Fig. 3.5B).

The lane containing Roche Recomb DNase, on the other hand, had only two

heterogeneous bands at the estimated weight for glycosylated DNase: 31-34

kDa115. In agreement with the gel analyses, mass spectrometry revealed that

Roche DNaseGII and Sigma DNase preparations contained trypsin,

chymotrypsin and other contaminants in addition to DNase while Roche Recomb

DNase mainly contained DNase (Fig. 3.5C). It must be noted that the peptides

found in these samples could not distinguish between chymotrypsinogen and

chymotrypsin. Regardless, chymotrypsinogen is activated by trypsin cleavage

followed by trans-proteolysis and, since trypsin was also present in the

contaminated preps, we assume that the samples contain active chymotrypsin.

I used a broad protease activity assay to confirm that the proteases found

within Roche DNaseGII and Sigma DNase were indeed proteolytically active

(Fig. 3.5D). As expected, Roche Recomb DNase had no protease activity (Fig.

3.6). Next, I created an in vitro assay (Fig. 3.7A) to determine if these active

proteases could destroy the NP311-325 antigenic epitope when it was either

conjugated to OVA or present within intact NP. OVA-NP or NP antigens were

  57  

Figure 3.5. Commercial DNases are contaminated with active proteases. (A) Mice were immunized with OVA-NP ± alum ± 2000 Kunitz units DNase I reagent from indicated sources. Antigen-specific CD4 T cells were quantified on d7 as before. Data in (A) were combined from 2-3 independent experiments each with n = 3-4. Error bars show means ± SEM. Statistical differences are with respect to the positive control group (treated with OVA-NP + alum + BSA) and were determined using an unpaired t test; ***p ≤ 0.001; ns indicates p > 0.05. (B) SDS-PAGE was performed on the indicated DNAse preparations. Gels were stained with Coomassie® Brilliant Blue dye. (C) DNase products were analyzed by mass spectrometry, as described in Chapter II. Spectra were compared to SwissProt databases to identify protein contents within samples (tan: DNase I, red: protease). Database matches (+) were listed when a sample contained at least 3 distinct peptides from the protein. (D) DNase samples were assessed for protease activity at indicated concentrations using the Pierce Protease Assay Kit. The dotted line indicates the lowest level of detection. Per mg of protein, Roche DNaseGII and Sig-DNase contained protease activities equal to approximately 10 µg and 1 µg trypsin, respectively. Data are representative of (C) 1 or (B,D) 2 independent experiments.

  58  

incubated for 0, 1, or 21 hours with or without Roche DNaseGII or control BSA.

The antigen mixtures were then fed to antigen-presenting Chb-2.4.4 cells, which

bear IAb, and ‘3NP311-2’ T cell hybridomas specific for IAb/NP311-325. Production

of IL-2 within 24 hours indicated the presence of intact NP311-325 peptide ligand.

The Roche DNaseGII preparation rapidly destroyed NP311-325 when it was

conjugated to OVA (Fig. 3.7B) but not when it was contained in its natural

context, intact NP protein (Fig. 3.7C). Notably, Roche DNaseGII destroyed the

epitope even at the 0 h time point, meaning that the DNase was mixed with OVA-

NP and immediately added to the cell culture. One possible explanation for this

result is that Roche DNase GII preparation destroyed the epitope within the very

short amount of time between when they were combined and when the

combination was fed to cells in culture. Alternatively, perhaps the cell culture

medium (containing 10% FBS) did not fully quench the protease activity within

the Roche DNaseGII preparation, allowing for continued antigen cleavage during

the 24 hours in cell culture. These observations suggest that NP311-325-specific

CD4 T cell impairment by Roche DNaseGII was due to rapid antigen destruction

by contaminating proteases rather than any DNase effect on alum biology.    

In conclusion, none of these three commercial DNase reagents (Roche

DNaseGII, Roche Recomb DNase, and Sigma DNase) can be used as

unequivocal measurements of the effects of DNase enzyme either because they

contain contaminating proteases or they include high mannose glycosylations

that act as confounding adjuvants. As such, careful examination of DNase

reagents should be done prior to their use in certain experiments.

 

  59  

Figure 3.6. Roche recombinant DNase has no protease activity. Roche DNases were assessed for protease activity at indicated concentrations using Pierce Protease Assay Kit. Dotted line indicates lowest level of detection. This assay was only performed once with one sample per reagent due to limited supply of lot 10392800 of Roche Recomb DNase.

Figure 3.7. Contaminating proteases rapidly destroy NP311-325 peptide on OVA-NP but not within NP. (A) Illustration of the experimental design. (B,C) OVA-NP or NP antigen was treated with or without Roche DNaseGII or BSA for 0, 1, or 21 h at 37°C and then added (in duplicate) to cell culture wells containing Chb-2.4.4 cells + ‘3NP311-2’ NP311-325-specific T cell hybridomas. Supernatant was assessed for IL-2 by ELISA 24 hours after adding antigen. Data are grouped from 2 independent experiments.

an#gen&±&Roche&DNaseGII&

37°C%0,%1,%or%21%hours%

Added&to&cells&Chb&(an#gen&presenters)&+&BNP>2&T&cell&hybridomas&

(responders)&

37°C%24%hours%

IL>2&ELISA&

A

  60  

Proteases are predominantly responsible for the effects of contaminated DNases on CD4 T cell responses to alum

Upon extending my search for a commercially available mammalian-

produced and protease-free DNase I, I found that Worthington Protease- and

Ribonuclease-Free DNase I (Worth DNase, from bovine pancreas) is

satisfactorily pure as established by SDS-PAGE (Fig. 3.8C), mass spectrometry

(Fig. 3.8F), and protease activity (Fig. 3.8E). As with the other commercial

DNases from before, I compared the effects of Worth DNase and Roche

DNaseGII on the vaccine adjuvant activity of alum. For this comparison,

however, I did not administer the DNases based on vendor-reported Kunitz units

of activity. Instead, I measured their enzymatic activities myself by measuring

their abilities to cleave mouse genomic DNA within 30 minutes at 37°C. I found

that while Worth DNase and Roche DNaseGII were nearly equivalent in DNase

activity on a per milligram of protein basis (823 µg Worth = 1 mg Roche) (Fig.

3.8B), the activity in vendor-reported Kunitz units per milligram was surprisingly

different: 8000 Worthington Kunitz units were equal to 2263 Roche Kunitz units.

When co-injected with alum + OVA-NP, Worth DNase only marginally impaired

the CD4 T cell response by 1.6-fold, whereas Roche DNaseGII reduced the CD4

T cell response 5-fold as before (Fig 3.9A). Worth DNase did not affect CD8 T

cell responses (Fig. 3.9B).

My previous experiment established that each milligram of Roche

DNaseGII was contaminated with proteases that have cumulative activities

equivalent to either 10 µg trypsin or chymotrypsin (Fig. 3.5D). To determine if

this contamination was sufficient to reduce CD4 T cell responses, alum vaccines

  61  

   

Figu

re 3

.8.

Wor

thin

gton

DN

ase,

wtD

Nas

e, a

nd m

utD

Nas

e ar

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ly a

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e or

inac

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(A

,B) R

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sted

for t

heir

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ase

enzy

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ic a

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ity b

y m

easu

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litie

s to

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mou

se

geno

mic

DN

A w

ithin

30

min

utes

at 3

7°C

at i

ndic

ated

con

cent

ratio

ns.

DN

ase

prep

arat

ions

wer

e an

alyz

ed b

y (C

) SD

S-P

AG

E or

(D) m

ass

spec

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etry

as

desc

ribed

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. Sp

ectra

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e co

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taba

ses

to id

entif

y pr

otei

n co

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(tan

: DN

ase

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atab

ase

mat

ches

(+) w

ere

liste

d w

hen

a sa

mpl

e co

ntai

ned

at le

ast 3

dis

tinct

pep

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from

the

prot

ein.

(E,F

) Rea

gent

s w

ere

asse

ssed

for p

rote

ase

activ

ity

at in

dica

ted

conc

entra

tions

usi

ng P

ierc

e Pr

otea

se A

ssay

Kit.

Dot

ted

line

indi

cate

s lo

wes

t lev

el o

f det

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n. D

ata

are

repr

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2 in

depe

nden

t exp

erim

ents

eac

h w

ith o

ne s

ampl

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r rea

gent

.  

  62  

Figure 3.9. Proteases impair CD4 T cell responses to alum + OVA-NP. (A,B) Mice were immunized with OVA-NP ± alum ± 1 mg BSA or indicated DNase I (dosed to equal the DNase activity of 1 mg Roche DNaseGII) ± 10 µg trypsin or chymotrypsin. Antigen-specific CD4 (A) and CD8 (B) T cells were quantified on d7 after immunization with tetramers and antibodies as described in Chapter II. Data in (A,B) were combined from 2-3 independent experiments depending on the group, each with n = 4. Error bars show means ± SEM for each group. Statistical differences were determined using an unpaired Student’s t test; *p ≤ 0.05; ***p ≤ 0.001; ns indicates p > 0.05. (C,D) OVA-NP or NP antigen was treated with trypsin or chymotrypsin for 0, 1, or 21 h at 37°C and added (in duplicate) to Chb-2.4.4 cells + ‘3NP311-2’ NP311-325-specific T cell hybridomas. Supernatant was assessed for IL-2 by ELISA 24 h after adding antigen. Data are representative of 2 independent experiments.

  63  

were given with 10 µg trypsin or chymotrypsin, with or without Worth DNase. I

found that both of these proteases could independently reduce NP311-325-specific

CD4 T cell responses whether or not the Worth DNase was also present (Fig.

3.9A). Notably, chymotrypsin was the more potent treatment. None of the

preparations affected CD8 T cell responses (Fig 3.9B).

In vitro antigen-destruction studies confirmed that trypsin treatment was

less efficient than chymotrypsin at destroying the NP311-325 epitope within OVA-

NP (Fig. 3.9C). Chymotrypsin could destroy the NP311-325 epitope by cleaving

after Y313, a putative anchor residue for binding the peptide to IAb, and/or after

L315 (Fig. 3.10). It is unclear whether or not trypsin can destroy the epitope by

cleaving after R317 because the relevant bond may or may not be protected by

the following proline residue116,117. Trypsin cleavage would, however, completely

sever NP311-325 peptides from OVA molecules by cleaving on the C-terminal side

of the K325 (Fig. 3.10). This would result in disassociated, but nonetheless

intact, peptide antigen that could potentially be loaded into MHC II. Interestingly,

the NP311-325 epitope within intact NP protein was protected from protease

cleavage for at least one hour at 37°C (Fig. 3.9D). Theoretically, the CD8-

stimulating SIINFEKL epitope from OVA could be attacked by either trypsin or

chymotrypsin (Fig. 3.10). However, CD8 T cell responses to SIINFEKL within

intact OVA were not impaired by protease treatments (Fig. 3.9B). Therefore, the

SIINFEKL peptide within intact OVA must be resistant to protease cleavage

within the timeframe and biological environment of i.m. vaccinations.

  64  

  Figure 3.10. Trypsin and chymotrypsin cleavage sites in NP311-325 and SIINFEKL peptides.

Taken together, my data offer an explanation for how impure Roche

DNaseGII and Sigma DNase affect CD4 T cell priming by alum: contaminating

proteases destroy or remove the CD4 epitope of interest. We observed only a

slight inhibitory effect of protease-free Worth DNase treatment within alum

vaccines on CD4 T cell responses, suggesting that DNase itself might indeed

have a small effect on alum-containing vaccines.

DNase enzymatic activity does not impair T cell responses to alum

To test if this DNase effect was due to the protein’s enzymatic activity, I

produced enzymatically active (wtDNase) and inactive (mutDNase) recombinant

bovine DNase I proteins using an HEK293 mammalian expression system with

help from Lori Sherman at the UCCC Protein Production Core. MutDNase

differed from wtDNase by three substitutions: R111A, D212A, and H252A118. I

confirmed that the wtDNase enzymatic activity per milligram protein was

QVYSLIRPNENPAHK-GGGC-OVA

Underlined = known or predicted IAb or Kb binding sites

?

flexible'linker'with'cysteine'NP3115325'pep9de'

Trypsin cleavage sites

Chymotrypsin cleavage sites

primary'amine'groups'(lysine'residues)'on'OVA'

OVA-SI INFEKL-OVA

  65  

equivalent to that of Roche DNaseGII (Fig. 3.8A) and that the mutDNase had no

enzymatic activity at 100 µg/ml (Fig. 3.8A) and 1 mg/ml (Fig. 3.11). As before, I

assessed the purity of these homemade DNases by SDS-PAGE (Fig. 3.8C),

mass spectrometry (Fig. 3.8D), and protease activity (Fig. 3.8E). The

mammalian-expressed recombinant wtDNase and mutDNase both had higher

molecular weights than bovine pancreas-sourced DNases (Fig. 3.8C). We

hypothesize that this difference is caused by variations in protein glycosylation

patterns used by different mammalian cell lines119: HEK293 may glycosylate

proteins differently than primary bovine pancreas cells.

Figure 3.11. MutDNase is inactive up to 1 mg/ml concentration. DNases were assessed for enzymatic activity on 800 ng of mouse genomic DNA within 30 minutes at 37°C at indicated concentrations (2-fold dilutions from 1 mg/ml). Data are representative of 3 independent experiments each with single replicates.  

  66  

Co-injection of wtDNase or mutDNase with alum vaccines yielded the

same numbers of antigen-specific CD4 or CD8 T cells (Fig. 3.12). Curiously, both

the control mutDNase and the active wtDNase treatments reduced CD4 T cell

responses by approximately 2-fold when compared with responses induced in

the absence of added protein or with added BSA. This dampening effect was

generally consistent between wtDNase, mutDNase, and Worth DNase, though

there were a few experiments in which Worth DNase did not significantly reduce

CD4 T cell priming (not shown). We hypothesize that the small effect of DNase

may be caused not by enzymatic activity, but by some biochemical property of

the DNase proteins, such as altered competition with the model antigen for

adherence to alum. Regardless of this issue, the comparison of T cell responses

in mutDNase- and wtDNase-treated mice indicates that DNase enzymatic activity

does not affect T cell responses to alum plus antigen.

Figure 3.12. DNase activity does not impair T cell responses to alum + OVA-NP. Mice were immunized with OVA-NP ± alum ± 1 mg indicated treatment. Antigen-specific CD4 (A) and CD8 (B) T cells were quantified on d7 as described in Chapter II. Data were combined from 2-4 independent experiments each with n = 4-5. Error bars show means ± SEM for each group. Statistical differences were determined using an unpaired Student’s t test; ***p ≤ 0.001; ns indicates p > 0.05.  

  67  

STING may be dispensable in alum vaccine responses

In another approach to measure the effects of host DNA on alum’s

adjuvant activity, I evaluated the role of STING, a cytoplasmic DNA-sensing

molecule, on alum vaccination. Previous experiments had suggested that

defects in the STING signaling pathway reduced alum’s ability to prime CD4 T

cell responses to OVA or the 3K peptide47,49. Host DNA is thought to attach to

and travel with alum crystals as they gain entrance into cytosolic spaces by

damaging and ultimately rupturing lysosomes, a phenomenon reported by

Hornung et al. in 200864. Cytoplasmic host DNA would then activate the

intracellular DNA-sensing pathway involving STING, Tbk1, and Irf3, resulting in

inflammatory responses such as type I interferon production and NFκB

activation64,120–122.

I repeated the alum vaccination experiments with STING-deficient mice.

Contrary to previous reports47,49, I found that both CD4 and CD8 T cells in

STING-deficient mice respond normally to the OVA-NP plus alum vaccine (Fig.

3.13A-B). Alum is known to induce substantial T follicular helper (TFH)

differentiation within CD4 cells80,88,123–125, an effect that is assumed to be critical

for the generation of protective antibodies by alum vaccines. Since both quantity

and quality of responding T cells contributes to alum’s effectiveness as an

adjuvant, I tested STING’s effect on T cell TFH differentiation. I found that alum-

primed CD4 T cells in STING-deficient mice differentiate into TFH cells at the

same frequency as those in WT mice (Fig. 3.13C). Lastly, I confirmed that IgG1

responses to alum are also STING-independent (Fig. 3.13D), as others have

  68  

reported. Overall, these findings suggest that the STING signaling pathway is

dispensable for adaptive immune responses to certain antigens, such as OVA-

NP, when delivered with alum.

Figure 3.13. STING is dispensable in adaptive immune responses to alum. WT or STING-deficient mice were immunized with OVA-NP + 1 mg BSA ± alum. Antigen-specific CD4 (A) and CD8 (B) T cells were quantified on d7 as described in Chapter II. (D) Antigen-specific CD4 T cells were assessed for frequency of TFH phenotype (PD1+ Bcl6+), compared to TFH frequency observed in CD44high CD4 T cells within PBS control mice. Data were combined from 5 (A) or 2 (B,C) independent experiments each with n = 3-4. (D) Serum samples were taken on d21 after immunization and tested for the presence of anti-OVA IgG1 antibodies by ELISA. RU, relative units. Data are from 1 experiment, n = 6. Error bars show means ± SEM for each group. Statistical differences were determined using an unpaired Student’s t test; ns indicates p > 0.05.

D C

  69  

Discussion

Findings in this study contrast those reported in previous publications that

examine the role for DNA and DNA-sensing molecules in alum biology. Though

extracellular host DNA is known to be an inflammatory danger-associated

molecular pattern, we found that it is dispensable in the generation of cellular and

humoral immune responses following i.m. alum immunization. Given the

conflicting results now published on the subject, the role of host DNA and the

STING pathway in alum-induced T cell activation remains unclear, similar to

alum’s relationships with several other inflammatory pathways.

The release of host DNA by alum is attributed to the massive cell death

observed at the site of i.m. injection47. The immune system recognizes necrotic

cell death by detecting the release of intracellular contents and rapidly mobilizing

an ensuing inflammatory response. The intracellular contents such as genomic

dsDNA, heat-shock proteins, uric acid, and high mobility group box 1 (HMGB1)

proteins act as endogenous adjuvants that have been called damage-associated

molecular patterns (DAMPs) (reviewed in 95). Our data suggest that alum

responses do not depend on DAMP signaling from host DNA, even though

genomic dsDNA has been shown to have adjuvant activity126. However, alum-

induced cell death releases a variety of DAMPs in addition to dsDNA. We

previously showed that alum nodules contain host chromatin26 which, in addition

to nucleic acid, contains DAMPs such as HMGB1. We show that host DNA is not

required for alum responses, but perhaps alum is releasing DAMPs that stimulate

the immune system redundantly even if one particular stimulus is absent.

  70  

Alum is known to induce many inflammatory pathways including the

creation of an antigen depot within the body27,127,128, activation of APCs

(reviewed in 56), inflammasome activation64–67, and release of endogenous

danger signals such as uric acid and host DNA26,47,59. Many of these pathways

have been implicated in or dismissed as contributors to alum’s adjuvant activities,

depending on the vaccine scenario. It is likely that the biochemical properties of

antigens, antigen dose, immunization schedule, and differences in precursor T

cell frequencies for given epitopes all affect which types of immunostimulatory

pathways triggered by alum vaccines ultimately contribute to the immune

response129–133. In this case, since the C57BL/6 murine CD4 T cell response to

NP311-325 within the OVA-NP antigen is quite robust, perhaps alum no longer

requires the STING pathway to be operative to mount a sufficient immune

response. Alternatively, responses to OVA (without NP peptide) and alum need

stronger instigation in the form of STING pathway activation.

In conclusion, we suggest that DNA may not play a prominent role in

mediating adaptive immune responses to alum and that contaminated reagents

may have led to incorrect interpretations of past experiments involving DNase

reagents. The correction of the literature that is presented here may help improve

future studies to elucidate the mechanism of aluminum salts as vaccine

adjuvants, an endeavor that remains paramount to understanding why alum

vaccines have successfully protected hundreds of millions of people from

disease and how they may be improved for future vaccination strategies.

  71  

CHAPTER IV

EFFECTS OF ALUM ON ANTIGEN PRESENTING CELLS

Introduction

The experiments in Chapter III demonstrated that Roche DNaseGII is

contaminated with active proteases that destroy the CD4 epitope on OVA-NP.

This discovery altered the interpretations of all Roche DNaseGII experiments

conducted before the contamination was discovered (years of work). This caveat

nullified many experiments because they are uninterpretable; these experiments

were excluded from this thesis. However, some were still of some use if the

following argument is acceptable. Since some of the peptide epitopes

(SIINFEKL and NP311-325) within intact proteins (OVA and NP, respectively) were

resistant to protease digestion within the relevant conditions of i.m. vaccination,

this means that alum vaccines administered with Roche DNaseGII indeed

delivered alum + antigen, as intended. Only analyses of CD4 T cell responses to

conjugated peptides (NP311-325) were compromised due to possible protease

destruction of their protease-susceptible epitope. Therefore, if we focused on

immune responses other than NP311-325-specific CD4 T cells, experiments using

Roche DNaseGII can still be cautiously interpreted regarding the effects of

DNase enzymic activity on immune responses to alum vaccines. This chapter

focuses on antigen presenting cell activation by alum and the effect of DNase

treatment on this process.

  72  

Antigen presenting cells (APCs) are instrumental in the initiation of

adaptive immune responses. They educate lymphocytes differently depending

on the type of foreign threat that is detected, ultimately guiding different adaptive

immune responses. For this reason, it is imperative to understand which APCs

react to aluminum salt (alum) adjuvants in order to understand how alum works

to generate protective immune responses.

CD11b+ conventional dendritic cells (cDCs) and inflammatory monocytes

(iMonos) have been implicated as the primary APC subsets that facilitate

immune responses to intramuscularly administered alum plus antigen58–61.

CD11b+ cDCs were found to be the most numerous alum antigen presenters

because they migrate easily from the muscular injection site to the dLN61. At the

same time, while only a small fraction of iMonos migrate from the muscle to the

draining lymph nodes (dLNs), iMonos were found to be more potent to induce

IFNγ-producing T cells on a per cell basis61.

Though these APC subsets have been identified, it is still unclear how

alum activates these cells within the muscle, since a variety of suggested

inflammatory pathways have been found to be dispensable for alum responses

(discussed in Chapter III). A specific receptor for which alum is a ligand has not

been identified. However several groups have proposed that alum is detected by

APCs through strong interactions between alum crystals and APC plasma

membranes. This can occur in two ways. Flach et al. reported that alum crystals

directly interact with dendritic cell plasma membranes and subsequent lipid

sorting, abortive phagocytosis, and antigen uptake may be responsible for DC

  73  

activation64,71,134. Alternatively, Kool et al. found that, when injected i.p., alum

increases levels of uric acid in the intraperitoneal space, which was important for

iMono migration to dLNs59. Uric acid forms monosodium urate (MSU) crystals

when released into extracellular spaces, and MSU crystals have been shown to

interact strongly with cholesterol and other lipids on the plasma membrane,

resulting in dendritic cell activation70.

In this study, I aimed to identify molecular stimuli and signaling pathways

that are induced by alum adjuvant within antigen-loaded APC subsets. My

approach was to use fluorescent antigen to identify and sort antigen-bearing

APCs 24 hours after i.m. immunization with antigen alone or antigen plus alum.

The RNA within these APC subsets were then sequenced and compared to gain

insight regarding the molecular pathways that are activated by alum. I found

that, curiously, alum does not seem to affect the types or ratios of APCs loaded

with antigen when compared to APCs that took up soluble antigen alone.

However, there were substantial up and down regulations of inflammation-

associated mRNA sequences among alum-treated and -untreated APCs.

Overall, alum appears to act as an inflammatory stimulus through a variety of

pathways, resulting in wide scale immune activation.

  74  

Results

Technical considerations when using fluorescent antigens

Choice of fluorophore for antigen tracking affects detection of antigen-

loaded cell subsets. The first step to achieve the goals of this project was to sort

antigen-loaded APCs from dLNs of alum-immunized mice. To make sure the

reports in the literature were repeatable in my hands, I began by immunizing

mice with fluorescent antigen ± alum and analyzing antigen-bearing cells by flow

cytometry. Through the course of this study, I used every combination of OVA or

NP protein antigen conjugated to FITC, Alexa Fluor 488 (A488), or Alexa Fluor

647 (A647).

It is important to note that choice of fluorophore for antigen-tracking

experiments seems to greatly affect the distribution of cell populations that

appear to be antigen+ and the relative brightness of fluorescent antigen within

antigen-bearing cells (Fig. 4.1). OVA-FITC was difficult to rely upon because it

was very dim within antigen-bearing cells when analyzed by flow cytometry (Fig.

4.1, top) and there is often high background within the FL1 FITC channel (488

nm excitation, emission: 530 nm) due to cellular autofluorescence of flavin

nucleotides, which are excited by and emit similar wavelengths of light

(excitation: 430-500 nm, emission: 530-550 nm). OVA- or NP-A488 was very

bright, but similar high background issues were a concern. OVA- and NP-A647

seemed to be the most reliable reagents because loaded cells were quite bright

(shifted up to three decades) and there was minimal background. The most

  75  

concerning analytical difference observed when using different fluorophores was

that B cells were (with A488 and A647) or were not (with FITC) appearing to

make up a substantial population of antigen-loaded cells in dLN 24 hours after

alum immunization (Fig. 4.1). B cells (B220+) make up the majority of the

CD11b- population in the right-most panels. As discussed in the next sections, B

cells are generally loaded with low amounts of antigen, compared to DCs or

iMonos. Since FITC was quite dim as a fluorescent marker, it is possible that

minimally-loaded B cells were registering as FITC- instead of FITClow.

Figure 4.1. Choice of fluorescent marker affects the detection of antigen-bearing cells by flow cytometry. Cells from dLNs were analyzed by flow cytometry 24 hours after mice were immunized i.m. with PBS or 5-20 µg OVA or NP that was conjugated to indicated fluorophores (FITC, A488, or A647) ± 200 µg alum ± 1 mg BSA. After gating on live cell singlet events, MHC II+ fluorophore+ cells were selected and plotted by CD11b and MHC II to distinguish general APC subsets: DCs (CD11b+ MHC IIhigh), iMonos (CD11b+), and B cells (CD11b-). Data are representative of at least 2 independent experiments per fluorescent marker, n = 2-3.

0 101 102 103

0

101

102

103

16 alum ova647 BSA.fcs…OVA647

<FL 1 Log>: FITC-MHCII

<FL

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g>: P

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D11

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56

32.8

0 101 102 103

<FL 8 Log>: APC-MHCII

0

101

102

103

<FL

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g>: F

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0.11

0 101 102 103

<FL 8 Log>: APC-MHCII

0

101

102

103

<FL

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g>: F

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A

0.16

0 101 102 103

<FL 8 Log>: APC-MHCII

0

101

102

103

<FL

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g>: F

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-OV

A

0.23

PBS Antigen Antigen

+ alum ± BSA

0 101 102 103

<FL 8 Log>: APC-MHCII

0

101

102

103

<FL

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g>: F

ITC

-OV

A48

8

1.28

0 101 102 103

<FL 8 Log>: APC-MHCII

0

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<FL

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g>: F

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6.34

0 101 102 103

<FL 8 Log>: APC-MHCII

0

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<FL

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-OV

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0 101 102 103

<FL 1 Log>: FITC-MHCII

0

101

102

103

<FL

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g>: A

PC

-ova

647

1.2

0 101 102 103

<FL 1 Log>: FITC-MHC II

0

101

102

103

<FL

8 Lo

g>: A

PC

-NP

647

0.93

0 101 102 103

<FL 1 Log>: FITC-MHC II

0

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102

103

<FL

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PC

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647

0.084

MHC$class$II$

An,g

en/Fluor$

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0 101 102 103

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0

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102

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<FL

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D11

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73.4

0 101 102 103

0

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5 4C OVA488alum.fcs…NP488+

<FL 8 Log>: APC-MHCII

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CD11b$

Antigen+ subsets

  76  

Artifacts of flow cytometry: possible B cell + iMono doublets. Another

technical difficulty was that often up to 40% of iMonos (identified as described in

Table 4.1) stained positive for B220, the CD45R isoform that exists on B cell

surfaces. This substantial proportion of B220+ iMonos has never been reported,

so I am hesitant to believe they are biologically real cells. Instead, they are likely

B cell/iMono doublets, especially because they are loaded with an intermediate

amount of fluorescent antigen compared to iMonos (higher) and B cells (lower)

(Fig. 4.2C). Doublets were excluded to the greatest extent possible without

sacrificing singlet events (as shown in Fig. 4.3A), but perhaps the small size of

coupled B cells + iMonos was within this singlet gate. This exemplifies a

limitation of using flow cytometry to analyze heterogeneous cell populations.

Bearing in mind the technical caveats described in this section, Figures

4.2 and 4.3 are generally representative of all the APC experiments performed

with either OVA or NP antigen, conjugated to A488, A647, or FITC (10

independent experiments).

Alum adjuvant effect on antigen-loaded APCs

Previous reports have established that peak numbers of antigen-loaded

APCs appear in dLNs 24 hours after i.m. alum vaccination60,61. Using flow

cytometry, I identified APC subsets within dLN of mice that were injected with

PBS or OVA-A647 ± alum ± BSA. APC subsets can vary in nomenclature

throughout the literature, so the phenotypes and corresponding APC subset

names that are used within this section are listed in Table 4.1.

  77  

Table 4.1. APC subset phenotypes. Name within thesis Aliases in the literature Phenotype

B cells B lymphocytes B220+ MHC II+ CD11c- CD11b- Conventional dendritic cells (DCs or cDCs) Classical DCs CD11c+ MHC II+ (CD8a+ or CD11b+)

Lymphoid-resident dendritic cells (resDCs)

Lymphoid tissue (LT-) DCs CD11c+ MHC II+

Migratory dendritic cells (migDCs) CD11c+ MHC IIhi (CD8a+ or CD11b+)

Blood monocytes Classical blood monocytes = Ly6Chigh

CD11b+ CD11cio-int MHC II+ CD64+ Ly6Chi

Inflammatory monocytes (iMonos)

Monocyte-derived dendritic cells (moDCs), inflammatory DCs (iDCs)

CD11b+ CD11cio-int CD64+ Ly6Clo

Other, doublets (B cell + iMono)

Likely unreal (flow cytometry doublets) B220+ CD11bint

Though increases in total numbers of loaded APCs did not reach

statistical significance, there is a trend that suggests that both alum and high

antigen dose (provided by the addition of 1 mg BSA) promote antigen take up by

APCs and their migration to dLNs (Fig. 4.2A). Roche DNaseGII treatment further

trended toward an increase in the total numbers of antigen+ cells in dLN at 24

hours, perhaps because alum/chromatin nodules detain cells due to their

trapping nature. Unexpectedly, neither alum nor alum + Roche DNaseGII

treatment affected the relative proportions of antigen-loaded B cells, iMonos,

migDCs (Fig. 4.2B). In all groups, CD11b+ iMonos contained the highest amount

of fluorescent OVA within dLN 24 hours after i.m. immunization (Fig. 4.2C).

  78  

Figure 4.2. Alum increases numbers of antigen-loaded APCs, but does not affect loaded cell type or degree of antigen uptake. Cells from dLNs were analyzed by flow cytometry 24 hours after mice were immunized i.m. with 10 µg OVA-A647 ± 200 µg alum ± 1 mg BSA or Roche DNaseGII, as described in Chapter II. Panels show (A) total number of OVA-A647+ cells, (B) relative proportions of antigen-loaded APCs by cell phenotype, and (C) MFI of OVA-A647 within indicated cell subsets. Data are representative of 2 independent experiments, n = 3. Error bars show means ± SEM for each group. Inflammatory monocytes take up the most antigen upon intramuscular injection

Similarly, when using NP-A647 fluorescent antigen, I found that iMonos

contained the most antigen on a per cell basis (Fig. 4.3C-D) and that both B cells

and iMonos were the most numerous antigen-loaded subsets within the dLN at

24 hours (Fig. 4.3E). It should be noted that Fig. 4.3E is comprised of cumulative

data from three independent experiments in which it varied whether B cells or

iMonos were the largest antigen-bearing population. Given the NP-A647+ gate

position, it is possible that antigen non-bearing B cells were wrongly included

# Ag+ cells

PBS

OVA647

OVA647 +

alum

OVA647 +

alum

+ BSA

OVA647 +

alum

+ DNas

e

0

100

200

300

400

Tota

l num

ber o

fO

VA-A

647+

cel

lsin

dLN

x10

-3

B220+%36%%

CD11b+%22%%

CD11b+%B220+%17%%

CD11c+%6%%

other%19%%

OVA8A647%

B220+%38%%

CD11b+%23%%

CD11b+%B220+%15%%

CD11c+%7%%

other%17%%

OVA8A647%+%alum%+%BSA%

Treatment:% −% −% −% BSA$ Roche$DNaseGII$

Adjuvant:% −% −% alum$ alum$ alum$

OVA8A647:% −% +$ +$ +$ +$

B220+%CD11b+%CD11b+%B220+%CD11chi%Total%anIgen+%cells%

OVA6A647$

A B

C

B220+%37%%

CD11b+%25%%

CD11b+%B220+%12%%

CD11c+%8%%

other%18%%

OVA8A647%+%alum%+%Roche%DNaseGII%

OVA6647$ OVA6647$+$alum$+$BSA$ OVA6647$+$alum$+$Roche$DNaseGII$

  79  

even though the gate was set comfortably above background fluorescence within

PBS treated samples (not shown).

Though OVA-FITC was dim for identifying fluorescent antigen ex vivo, this

reagent was used for a time course to identify when and which antigen-loaded

APC subsets appeared in the dLN after i.m. alum injection. This experiment

suggests that iMonos are the cells that rapidly (within 6 hours after injection)

acquire antigen and traffic to the dLN, while migDCs are slower to appear in

dLNs (Fig. 4.4). An important caveat is that my experimental approach did not

allow me to distinguish between cells that took up antigen at the site of injection

and brought it to the dLN from cells that may have acquired the antigen while in

the dLN. As time progressed after vaccination, there were fewer antigen-loaded

iMonos and more loaded migDCs within dLNs (Fig. 4.4). It is possible that

antigen is being passed off among APC subsets within the dLN or that DCs are

slower to migrate from the site of injection to dLNs than iMonos.

RNA sequencing identifies alum-induced inflammatory pathways

I next sought to identify inflammatory pathways affected by alum in an

unbiased and broad manner by using RNA sequencing to examine changes in

gene expression after alum injection. Groups of mice (n = 10-20) were

immunized i.m. with fluorescent antigen (OVA-A647) either alone or adsorbed to

alum. Antigen-loaded APCs (iMonos, DCs, and B cells) were sorted 24 hours

after injection and their mRNA was sent to Expression Analysis, Inc., for RNA

sequencing. One drawback of this study was that samples were sent without

  80  

Figure 4.3. Inflammatory monocytes capture the most alum-adsorbed antigen per cell.

live%

SS%(Lin)%

NP-A647+ singlets A

MHC%class%II%

NP4A6

47%

NP4A647%

%%of%M

ax%

B

C

D

B cells

Mono-cytes

cDCs migDCs other

E

Mono-cytes

Ungatedsample monos.fcsEvent Count: 3003939

0 10K 20K 30KFS Lin: FS

0

10K

20K

30K

SS

Lin

: SS

79.4

livesample monos.fcsEvent Count: 2384056

0 100 200 300 400 500Pulse Width: Pulse Width

0

10K

20K

30K

FS L

in: F

S

97.5

singlesample monos.fcsEvent Count: 2324169

0 101 102 103

<FL 1 Log>: FITC-MHC II

0

101

102

103

<FL

8 Lo

g>: A

PC

-NP

647

2.67

NP647+sample monos.fcsEvent Count: 62106

0 101 102 103

<FL 9 Log>: APC-Cy7-CD11b

0

101

102

103

<FL

5 Lo

g>: P

E-C

y7-C

D11

c

53.3

11.7

18.5

11.6

NP647+sample monos.fcsEvent Count: 62106

0 101 102 103

<FL 1 Log>: FITC-MHC II

0

101

102

103

<FL

5 Lo

g>: P

E-C

y7-C

D11

c

7.69

imonossample monos.fcsEvent Count: 11509

0 101 102 103

<FL 2 Log>: PE-CD64

0

101

102

103

<FL

6 Lo

g>: P

B-L

y6C

50.2

41.1

MHC%class%II%

NP4AF

647%

Pulse%Width%FS%(Lin)%

FS%(Lin)%

CD11c%

CD11c%

Ly6C

CD11b% CD64 MHC%class%II%

migratory%DCs%all%monocytes%

cDCs%(mig%and%res)%other%

B%cells%blood%

monocytes%

B cells

cDCs migDCs other

major APC subsets blood monocytes migratory DCs

# of NP647 higher ag gate

B cells

other

cDCs

iMon

o (all

)

blood

mon

o

migDCs

0

20000

40000

60000

Tota

l num

ber o

fA

647+

cel

ls

MFI of NP647 higher ag gate

B cells

other

cDCs

iMon

o (all

)

blood

mon

o

migDCs

0

50

100

150

200

250

MFI

of A

647

  81  

Figure 4.3. Inflammatory monocytes capture the most alum-adsorbed antigen per cell. Mice were immunized i.m. with PBS or 200 µg alum + 5-20 µg NP-A647 ± 1 mg BSA. Popliteal dLNs were harvested 24 hours after immunization, grouped into one sample (n = 3), and analyzed as described in Chapter II. (A) Gating scheme to identify antigen-loaded (A647+) cell subsets: B cells (blue), conventional DCs (cDCs), migratory DCs (migDCs), inflammatory monocytes, blood monocytes, and ‘other’ cells that displayed an indeterminate phenotype. All subsets were gated on live cells, singlet events, and MHC II+ A647+. A647+ gate was set based on PBS control mice. Subsets were then compared to the cumulative population of A647+ cells (grey) and analyzed for their (B) MHCII x A647 phenotype and (C) A647 fluorescence intensity by % of max. (D) Mean fluorescence intensity (MFI) of A647 per APC subset. (E) Total number of A647+ cells per APC subset. Data are representative (A-C) or cumulative (D-E) of 3 independent experiments. Error bars show means ± SEM for each group.

  82  

Figure 4.4. Antigen arrives to dLNs rapidly via iMonos, but later time points reveal more antigen-bearing migDCs (DCs). Cells from dLNs were analyzed by flow cytometry at indicated time points after mice were immunized i.m. with 5 µg OVA-FITC ± 200 µg alum, as described in Chapter II. Data are from only one experiment with n = 3. Error bars show means ± SEM for each group. replicates, due to relative cost. Since each sample contained pooled mRNA from

10-20 individual mice, we hoped that these pooled samples would serve as an

accurate representation of reality. However, since this study was conducted

without RNA sequencing replicates, the following analyses and conclusions must

be judged cautiously.

With help from Sonia Leach at National Jewish Health, I generated a heat

map of gene cluster expression within each of the alum-treated or untreated APC

subsets. Distinct gene expression profiles were evident after heat map cluster

analysis (Fig. 4.5A), with more than 3000 genes differentially expressed within

each APC subset (Fig. 4.5B). Differentially expressed gene lists were analyzed

by Database for Annotation, Visualization, and Integrated Discovery (DAVID)

v6.7 bioinformatics resources web program using the following databases: Kegg

Pathways, Swiss-Prot and Protein Information Resource Keywords, and Gene

Ontologies of cellular components, molecular functions, and biological

OVA-FITC+ loaded cells following immunization

0 6 12 18 24 30 36 42 480

2

4

6

8 iMonos (+alum)

DCs (+alum)

B cells (+alum)

iMonos (-alum)

DCs (-alum)

B cells (-alum)

Hours post-immunization

Tota

l num

ber o

fO

VA-F

ITC

+ ce

llsin

dLN

x10

-3

  83  

processes. Functional annotation gene clusters were counted if the DAVID

program calculated their enrichment score to be ≥1 and quantified by APC

subset (Fig. 4.5C).

Though there were too many gene clusters to analyze fully within the

scope of this thesis, I have summarized the functional theme of each cluster that

had a DAVID enrichment score above 5 (highly significant) in Table 4.2.

Enrichment scores rank the biological significance of gene clusters based on

overall modified p-values (EASE scores) of all genes within the cluster. As could

be expected, alum treatment both up-regulated and down-regulated RNA

associated with a broad category labeled: protein changes, cell signaling, and

secreted proteins. This cluster is so broad that little can be interpreted without

analyzing specific genes. Similarly, cell adhesion genes were both up regulated

and down regulated across the board, indicating that closer inspection of the

specific genes in this functional cluster is needed to identify distinct biological

effects. The iMono gene profiles indicate a pan-inflammatory effect of alum, as

alum-treated gene expression is increased in clusters associated with the

immune response, inflammatory response, and lysosomes. Curiously, genes

implicated in sugar and carbohydrate binding were down regulated in iMonos, but

up regulated in B cells at this time point. Lastly, two clusters were preferentially

down regulated in alum-treated iMonos and DCs: cytokine and cytokine

receptors and extracellular matrix proteins. These alum effects can be followed

up by analyzing the regulation of specific genes within these functional groups.

  84  

Figure 4.5. Alum induces vast changes in gene expression profiles within exposed APC subsets. As described in detail in Chapter II, mice (n = 10-20) were immunized with 10µg OVA-647 ± 200 µg alum + 1 mg BSA. Antigen-loaded APCs were sorted 24 hours after injection and sent to Expression Analysis, Inc., for RNA sequencing. RSEM normalized gene expression profiles were compared between antigen- and antigen + alum-treated cells for the three chosen APC subsets by (A) heat map cluster analysis, (B) quantification of genes that changed more than 2-fold in expression, and (C) quantification of functional annotation gene clusters identified by the DAVID program, based off of genes represented in (B). (A) The heat map colorbar represents the relative expression value of a gene with respect to the gene's mean expression across all samples. Thus warmer colors (red) indicate expression higher than the gene's mean across all samples while cooler colors (blue) indicate expression lower than the gene's mean.

Ag_B220

alumBSA_B220

alumBSA_C

D11b_hi

Ag_CD11b_hi

Ag_CD11c_hi

alumBSA_C

D11c_hi

−2

−1

0

1

2

B"cells""""""""B"cells """"iMonos"""""iMonos"""""""""DCs """"""DCs"""""

An#gen&only& &&&&&&&&&&&&Alum&+&an#gen&

Genes

CD11b hi iMonosCD11c hi DCs B cells

-4000

-2000

0

2000

4000 Up-regulated

CD11bhi

iMonosCD11chi

DCsB cells

15731144

1732

Num

ber o

f Gen

esw

ith A

ltere

d E

xpre

ssio

n

CD11b hi iMonosCD11c hi DCs B cells

-4000

-2000

0

2000

4000

4150

1989 1651

Down-regulated

CD11b hi iMonosCD11c hi DCs B cells

-100

-50

0

50

100

86

6143

Down-regulated

Functional AnnotationGene Clusters

CD11b hi iMonosCD11c hi DCs B cells

-100

-50

0

50

100Up-regulated

CD11bhi

iMonosCD11chi

DCsB cells

6042

62

Num

ber o

f Clu

ster

sId

entif

ied

by D

AV

ID

A

B C

  85  

Overall, the functional gene clustering analysis helps to confirm that alum

has many effects on APCs, but lacks the specificity to identify distinct immuno-

stimulatory pathways that are affected. Furthermore, replicate data are needed

before thorough analysis of this RNA sequencing experiment is warranted.

Table 4.2. Functional gene clusters that have altered expression in response to alum

iMonos DCs B cells Increased Expression After Alum Treatment

• Protein changes, signaling proteins

• Immune response • Inflammatory defense response • Cell surface proteins • Lysosome • Positive regulation of immune

response

• Protein changes, secreted proteins, signaling proteins

• Cell adhesion

• Protein changes, signaling proteins

• Secreted protein signals • Cell surface proteins • Extracellular matrix • Cell adhesion • Angiogenesis • Plasma membrane • Sugar binding • Carbohydrate binding • Inflammatory response

Decreased Expression After Alum Treatment • Protein changes, signaling

proteins • Secreted proteins • Cell surface markers • Cell adhesion • Sugar binding • Extracellular matrix • Cytokine & cytokine receptors • Cell-cell signaling • Carbohydrate binding

• Protein changes, signaling proteins, secreted protein signals

• Extracellular matrix • Cell surface proteins • Cell adhesion • Cytokine & cytokine receptor • Synapse

• Protein changes, signaling proteins, secreted protein signals

• Extracellular matrix • Cell junction & synapse • Bone development • Cell adhesion

*Clusters are arranged in descending order of DAVID enrichment score; only clusters with enrichment scores ≥ 5 are listed.

Discussion

The data in this chapter suggest that intramuscularly injected alum does

not greatly alter how the mouse immune system takes up foreign antigen and

shuttles it to dLNs. Compared to soluble protein alone, it was unexpected that

alum adjuvant does not more significantly skew the APCs subsets that acquire

  86  

antigen. This suggests that the APC subsets others59–61 and I have identified to

respond to i.m. alum injection may simply specialize in patrolling skeletal

musculature and, consequently, pick up all forms of injected antigen regardless

of whether or not alum is present. However, it is clear from the RNA sequencing

data that alum has immunostimulatory effects on all involved APC subsets.

This study is a valuable extension to another report that focused solely on

APCs within steady state and alum-treated skeletal muscle, along with their

migratory counterparts in dLNs61. My study added the condition of soluble

protein injected without alum, which elicited the same antigen-loaded APC

subsets within dLNs as did alum-adsorbed antigen. Furthermore, my use of

fluorescent antigen enabled the quantification of antigen acquisition by distinct

APC subsets. I determined that antigen is most concentrated in iMonos, followed

by CD11b+ DCs, and lastly B cells. This may explain why previous reports have

found that iMonos are the most efficient subset at priming IFNγ-producing T

cells61.

However, there is a notable difference between the other studies and

mine. Concerning the relative frequencies of migratory APCs involved in

detecting intramuscular vaccine antigens, I found a large proportion of iMonos

and B cells to be fluorescent antigen-loaded in the dLNs while other authors

emphasized a large role for CD11b+ migDCs60,61. Some of this discrepancy is

due to variable nomenclature for DC-like APCs that either does or does not

distinguish between monocyte-derived and DC-derived CD11b+ CD11c+ cells.

Furthermore, reports that did not observe much iMono migration to dLNs used

  87  

small volume injections (15 µl) whereas my injections were larger per muscle (50

µl). This difference may not be trivial as the increased volume of liquid draining

from the muscle may influence the appearance of different APC subsets in the

dLNs. Lastly, my data are the first to raise the possibility that antigen-loaded B

cells may constitute a substantial population of APCs within the dLNs after alum

injection. Alternatively, perhaps B cells are antigen-loaded merely because they

must present linked antigen to TFH cells in order to receive help within germinal

centers. It is still unclear where B cells acquire this antigen, though it is likely

acquired within the dLN because few B cells are found in steady state skeletal

muscle. Antigen-loaded B cells may have been previously overlooked and/or

discounted due to their low antigen load and consequent difficult nature to detect

by fluorescent antigen tracking. B cell APCs may be an important factor in alum

biology because they have been reported to promote type 2 immune

responses135,136, as is elicited by alum. Additionally, B cells may have a

tolerogenic role when stimulated through TLR9 by DNA complexes associated

with dexamethasone-treated apoptotic cells137.

In conclusion, this study confirms other reports that iMonos and CD11b+

DCs are important alum/antigen APCs and also suggests a new role for B cells

as alum-induced APCs. Furthermore, the preliminary RNA sequencing data also

suggest that alum may affect a variety of immunostimulatory pathways within

APCs. However, these findings must be repeated before they can be relied

upon.

  88  

CHAPTER V

SINGLE DOSES OF HEAT AGGREGATED PROTEINS

ARE NOT IMMUNOGENIC

Introduction

Many diseases and conditions stem from inappropriate adaptive immune

responses mounted against protein aggregates99,103–105,138. Surprisingly, T cell

responses to aggregates are not well characterized, though one study suggested

that heat aggregated proteins specifically elicit CTL responses91. Furthermore, it

has been previously reported that heat denatured OVA enhances production of

OVA-specific TH1-dependent IgG2a class-switched antibodies104. Others also

showed that pathogen-sized particulate proteins are typically more TH1-

stimulating than soluble proteins139,140. These scattered reports within the

literature needed clarification by a direct study on the effect of aggregated

proteins on T cell responses.

Consequently, the objective of this study was to determine the magnitude

and functionality of primary T cell responses to heat aggregated proteins.

Though this project was discontinued, my preliminary data are presented in this

chapter and they suggest that heat aggregated proteins do not stimulate T cell

responses in mice. This inability of protein aggregates to induce cellular immune

responses after one immunization raises concern about their value as vaccine

components.

  89  

Results

Characterizing protein antigens: soluble versus heat aggregated OVA

Soluble ovalbumin must be filtered and can be stored for at least two

weeks at 4°C. Soluble, monomeric OVA protein is a critical negative control in all

experiments within this project. I first determined if ultracentrifugation after

filtering was required to ensure that resuspended OVA was monomeric. After

lyophilized OVA was resuspended in PBS, samples were either filtered through a

0.22 µm membrane or filtered and ultracentrifuged at 200,000 x g for 2 hours in

an attempt to pellet any existing protein aggregates. Freshly prepared samples

or samples that had been stored for 15 days at 4°C were assessed for protein

size by size exclusion chromatography and particle size by micro-flow imaging.

Size exclusion chromatography revealed that ultracentrifugation was not required

to ensure that resuspended OVA is predominantly monomeric (Fig. 5.1).

Figure 5.1. Resuspended lyophilized OVA is predominantly monomeric after filtration and ultracentrifugation. OVA (13 mg/ml in PBS) was only filtered (0.22 µm) or filtered and ultracentrifuged at 200,000 x g for 2 hrs. Fresh samples and samples that had been stored for 15 days at 4°C were separated by size exclusion chromatography.  

  90  

However, ultracentrifugation seemed to rid the OVA samples of a small portion of

degraded protein that was less than 45 kDa in size. When compared to

unfiltered OVA (Fig 5.2A), filtered OVA (Fig. 5.2B) contained very few particles,

as assessed by micro-flow imaging. Furthermore, filtered OVA can be stored at

4°C for at least 15 days without protein aggregation or particle accumulation (Fig.

5.1 and 5.2B). These results indicate that “soluble OVA” (native and monomeric)

could be prepared by resuspending the lyophilized OVA in PBS, filtering, and

storing at 4°C until use.

Heat aggregation of ovalbumin at concentrations >1 mg/ml alters its

surface hydrophobicity, conformation, and structure. To generate aggregated

OVA antigen, I first turned to heat denaturation because this is the simplest

approach. Alternative approaches included urea denaturation, chemical

conjugation, or gluteraldehyde crosslinking. To confirm that heating OVA

produced denatured protein aggregates, I compared the secondary and tertiary

structures, surface hydrophobicity, and tryptophan fluorescence of soluble OVA

and heat aggregated OVA. Hydrophobicity has been proposed as an

immunogenic factor of unfolded or otherwise denatured proteins141. Heating

OVA at either 1 mg/ml or 10 mg/ml in PBS resulted in increased surface

hydrophobicity of the proteins, as measured by 8-anilinonaphthalene-1-sulfonate

(ANS) fluorescence staining and spectrofluorometry (Fig. 5.3A). Tryptophan

peak fluorescence, an indication of protein conformation, was increasingly

altered (blue-shifted) as OVA was heated at higher concentrations (1 mg/ml

versus 10 mg/ml) (Fig. 5.3B,C). Infrared (IR) spectroscopy was used to assess

  91  

A

B

Figure 5.2. Filtering is required to rid resuspended OVA of particulates. OVA preparations (5 mg/ml in PBS) were either filtered (0.22 µm) or not and then analyzed for particle concentration by micro-flow imaging. (A) The y-axis is increased to accommodate the particle concentrations found in fresh and stored (15 days) unfiltered OVA samples (bolded in legend). With this scale, the filtered samples are essentially undetectable. (B) The y-axis is reduced and only filtered OVA samples (fresh and old) are shown.

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  92  

Figure 5.3. Heating OVA alters its structural conformation. (A) ANS staining for soluble or heated (80°C for 10 min at either 1 mg/ml or 10 mg/ml in PBS) OVA preparations. Samples were excited at 350 nm and fluorescence emission was scanned between 400-500 nm by spectrofluorometry. (B) Tryptophan fluorescence spectra of soluble or heated OVA samples. (C) First derivative plot of data from (B), illustrating the position of the fluorescence peaks (where y = 0). Analytical data were collected from one experiment with one sample per treatment with help from the Carpenter Lab (University of Colorado).

protein secondary structure within soluble and heated OVA samples. Results

show that soluble OVA contains both alpha helical and beta sheet structures

while heated OVA only retains cross-linked beta sheets (Fig. 5.4). In conclusion,

my data clearly indicate that heat treatment alters the surface hydrophobicity,

conformation, and structure of OVA protein, things that are intuitively known by

all who have ever boiled an egg.

400 410 420 430 440 450 460 470 480 490 5000

5000

10000

15000

20000

25000

30000

35000

40000

native OVAOVA heated at 10mg/mlOVA heated at 1mg/ml

ANS staining, 23°C

nm

AN

S fl

uore

scen

ce s

igna

l

300 310 320 330 340 350 360 370 380 390 4000

10000

20000

30000

40000

50000

60000 native OVAOVA heated at 10mg/mlOVA heated at 1mg/ml

nm

Trp

fluor

esce

nce

310 320 330 340 350 360 370 380 390 400

-1500

-1250

-1000

-750

-500

-250

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500

750

1000

1250

1500

1750

2000

2250 native OVAOVA heated at 10mg/mlOVA heated at 1mg/ml

nmFirs

t der

ivat

ive

A

B C

  93  

Figure 5.4. Heat treatment alters the secondary structure of OVA. Comparisons of the second-derivative mid-range infrared absorption spectra of soluble (blue) or heated (red) OVA preparations. Labels indicate the secondary structures (alpha helices and beta sheets) that characteristically signal at the denoted ranges of frequency (cm-1). Analytical data were collected from one experiment with one sample per treatment with help from the Carpenter Lab (University of Colorado). Heat aggregated proteins do not prime T cells

To test whether or not heat aggregated proteins were more immunogenic

than soluble proteins, I quantified antigen-specific T cell responses in mice that

were immunized with soluble or aggregated OVA or NP proteins delivered by a

variety of routes. Analytical assays regarding the precise structural changes

provoked by heat treatment (Figs 5.1-3) were only performed on OVA protein

and were not repeated with NP because NP is significantly more precious

(supply and price) than OVA. Neither heat aggregated OVA (injected i.p.) nor

heat aggregated NP (injected s.c. or i.d.) increased CD4 or CD8 T cell priming

when compared to soluble OVA or NP protein (Fig. 5.5). Gluteraldehyde cross-

linking of NP resulted in trends of higher T cell priming, but the effects were not

significant given the power of this experiment (Fig. 5.5B).

1650-1658 α helices

1640-1620 β sheets 1620

β turns or X-linked β sheets

1690- 1670 β turns

Soluble'OVA'Heated'OVA!

  94  

PBSOVA +

alum

solub

le OVA

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  95  

Figure 5.5. Single doses of heat aggregated proteins are not immunogenic when administered i.p. or s.c. (A) Experimental design. Mice were immunized via the indicated route with indicated doses of soluble OVA or NP, heat aggregated OVA or NP (red), gluteraldehyde aggregated NP (red), or Alhydrogel® alum + soluble OVA or NP. OVA was heated at 96°C for 5 min at 50 mg/ml in PBS. NP (1 mg/ml in PBS) was aggregated by heat (98°C for 10 min) or gluteraldehyde treatment (0.5% for 2 hrs, then buffer exchanged to PBS). (B) OVA-or NP-specific CD4 and CD8 T cells were quantified on d8 or d9 after immunization with tetramers and antibodies as described in Chapter II. Data are from experiments that were only conducted once each, n = 3. Error bars show means ± SEM for each group. Statistical differences were determined using an unpaired Student’s t test; ns indicates p > 0.05.

  96  

Discussion

The current literature contains largely correlative accounts of antigen-

specific immunity to protein aggregates that have been reported since the 1960s

when David Dresser first reported that aggregated proteins can be immunogenic

142–144,102,104,100. Few direct studies to illuminate the immunological

consequences of protein aggregate introduction into the body have been

published. To the best of my knowledge, there is only one published study from

1997 that directly reported the ability of heat denatured proteins to prime CTL

responses when injected intraperitoneally into mice91. However, their

experimental approach was limited due to the techniques and reagents available

at that time. Furthermore, their data contradict other more recent reports in that

they show that heated protein aggregates stimulate little to no antibody

responses91, unlike reports of anti-therapeutic protein responses in human

patients97,99,145. My study set out to provide clarity about how protein aggregates

become immunogenic.

Unlike the aforementioned study91, the data presented in this chapter

suggest that heat aggregated proteins are not immunogenic for T cells when

given in a single dose. However, the limited experimental conditions in this study

were unable to fully test the hypothesis that aggregated proteins can be

immunogenic. Single dose exposures to aggregated proteins may not be

sufficient to prime immune responses, though single doses seemed to be

sufficient for one group of researchers to elicit antigen-specific CTLs in 199791,

  97  

perhaps due to reagent contaminants. The discrepancy here may also be due to

a difference in assay sensitivity used for each study. Perhaps re-stimulated ex

vivo CTL ability to carry out specific lysis is more sensitive than MHC tetramer

identification of antigen-specific T cells within directly ex vivo.

It is possible that aggregated proteins, such as those that form within vials

of therapeutic proteins97, only become immunogenic when administered routinely

over a long period of time. Chronic exposure of aggregated antigen may be

essential for the stimulation of adaptive immune responses. It is difficult to draw

conclusions from these preliminary data because this study is incomplete.

It is well established that particles containing repetitive arrangements of

antigens have their own adjuvant activity that is capable of stimulating innate

immunity. This observation has led to the design of vaccines that employ virus-

like particles or virosomes to deliver antigens as well as the use of protein

aggregation in some vaccines138,141,146,147. While VLPs and virosomes seem to

stimulate immunity by mimicking the physical characteristics of pathogens, it is

unclear how simple native or denatured protein aggregates stimulate innate

immune sensors. Since T cell responses rely upon stimulation by APCs, an

important part of this study would be to determine how aggregates are detected

by and activate APCs.

To extend this study, I would recommend augmenting the delivery routes

and immunization schedules used to administer protein aggregates. Most

endogenous protein aggregates are formed by hydrophobic interactions between

damaged or misfolded proteins that expose regions of their hydrophobic

  98  

cores106–109. However, aggregates composed of predominantly native proteins

can also be immunogenic148–150. One study directly compared native and

denatured aggregates and found that native aggregated are more immunogenic

than their denatured counterparts151. This suggests that the nativity of the

proteins affects the immunogenic mechanism of aggregate species. In both

cases, it is not clear how foreign, endogenous, native, or denatured protein

aggregates stimulate our innate immune cells.

Understanding how aggregates activate the innate immune system and

induce adaptive responses will greatly improve our understanding of protein

immunogenicity. This insight will aid clinical progress toward the deliberate

manipulation of immune responses to protein aggregates, namely those mounted

against protein therapeutics or even destructive anti-protein autoimmune

responses such as Alzheimer’s disease. Targeting immunostimulatory pathways

that are triggered by offending protein aggregates could be used to treat protein

aggregate-associated conditions and diseases. At the same time, understanding

the primary features of aggregate immunogenicity will encourage more deliberate

use or avoidance of protein aggregates as vaccine components. Specific

exploitation of the immunogenic or tolerogenic strengths of denatured or native

protein aggregates could lead to the generation of aggregate-based vaccines

that are easily stored and transported due to their stability. Potent vaccines with

these qualities would greatly improve global public health.

  99  

CHAPTER VI

DISCUSSION AND FUTURE DIRECTIONS

Aluminum salt adjuvants have greatly impacted global health by providing

protective immunity against deadly diseases to hundreds of millions of

people11,23. Since its adjuvant effect was first discovered in 1926, it has been

unclear how alum achieves such effective immunostimulation. Recently, it was

proposed that alum works by causing a release of host DNA that acts as an

endogenous adjuvant26,47,49. My thesis work contributes to the growing body of

knowledge about alum mechanism by providing an alternative opinion: DNA is

dispensable in alum responses.

The study in Chapter III exhaustively demonstrated that host DNA does

not play a prominent role in mediating adaptive immune responses to alum,

contradicting the aforementioned literature. Furthermore, this study highlighted

the importance of thoroughly evaluating the purity of commercial DNase reagents

prior to use, as active protease contaminants can have off target effects. Here I

will discuss how this study affects both the working model for how alum functions

as a vaccine adjuvant and other fields of research, as well as touch on issues of

reproducibility in published science.

Data presented in Chapter IV confirmed published reports that iMonos

and CD11b+ DCs are important alum-reactive APCs and also suggested a new

role for B cells as a substantial population of alum-induced APCs. These data

  100  

will be incorporated to the current working model of alum adjuvant action and I

will briefly discuss the importance of B cells as antigen presenters.

Last, the experiments and discussion presented in Chapter V emphasized

how very little is known about the immunogenic mechanisms triggered by protein

aggregates. More research is warranted to clarify this subject, as it is highly

relevant to the clinical use of protein therapeutics in human patients. This study

is incomplete and was appropriately discussed at the end of Chapter V, so I will

not mention it further in this section.

Alum’s Mechanism: A Working Model + Unanswered Questions

My work presented in Chapter III serves to correct the literature about

DNA’s role in mediating alum adjuvant action: i.e. it is not required for immune

responses to alum vaccines. It is important to note that these data do not

discount the fact that alum stimulates the extracellular release of host chromatin,

which in turn stimulates several inflammatory pathways. (The subject of DNA as

an inducible endogenous adjuvant will be discussed in the next section).

However, since I’ve demonstrated that DNA-sensing is not the key to alum’s

success as an adjuvant, the question remains: how does alum work? There is a

trend within the alum field that inflammatory pathways will be proposed as

responsible for alum’s adjuvant effect, only to be dismissed shortly thereafter

when other labs do not find them essential. I think there is a reason for this: alum

triggers many redundant inflammatory pathways, each of which may be

  101  

individually dispensable. In this section I will integrate my findings with what is

known from current publications to generate a working model for how alum

functions as an adjuvant, illustrated in Fig. 6.1. Furthermore, I will emphasize the

gaps in the literature where questions about alum’s mechanism remain

unanswered.

Step 1: Damage and inflammation at the site of injection

In the literature, all signs point to the fact that alum crystals cause

substantial inflammatory damage at the site of injection. Since its discovery,

alum vaccines are known to form “nodules” at the site of injection25. Thorough

examinations of these nodules revealed that they contain dead or dying cells,

damage-associated factors such as host chromatin, and a myriad of

inflammatory innate cells26,47,128. Abundant cell death has been documented at

the site of alum injection, owing to alum’s cytotoxic properties47,94. Dying cells

release their intracellular contents, including uric acid, chromatin, and heat shock

proteins, that can act as immunostimulatory damage-associated molecular

patterns (DAMPs)59,95,96,126,152,153. In fact, one group suggested that alum elicits

increased heat shock protein 70 in DCs154, suggesting that alum causes stress

signaling in innate immune cells. The profile of innate cells that are recruited to

alum nodules is extensive, including eosinophils, mast cells, neutrophils,

macrophages, inflammatory monocytes, NK cells, and dendritic cells among

others26,68. Adding to the chromatin content of alum nodules, neutrophils also

  102  

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  103  

Figure 6.1. Working model of alum’s mechanism. Step 1: Alum causes inflammation at the site of injection, causing release of DAMPs and recruitment of inflammatory innate immune cells. Step 2: Alum crystals themselves and/or induced DAMPs cause activation and antigen uptake by APCs, predominantly iMonos and CD11b+ DCs. Step3: Activated APCs migrate to dLNs and prime CD4 and CD8 T cells via pMHCII/TCR and pMHCI/TCR interactions, respectively. APC/CD4 T cell interactions are stabilized by ICAM1/LFA1 molecules. Cytokine signals (IL-4, IL-25, etc.) promote TH2 differentiation of CD4 T cells. TFH2 cells aid B cells in class switch recombination to IgG1 and IgG3 in humans (IgG1 and IgE in mice) and differentiation into long lived plasma cells. Memory T cells are also formed through unclear mechanisms. Step 4: Protective memory is generated after a series of 3 alum immunizations or is maintained through the administration of booster shots throughout life. DC, dendritic cell; iMono, inflammatory monocyte; HMGB1, high mobility group box 1; MSU, monosodium urate; IL, interleukin; pMHC, peptide-loaded MHC; PGE2, prostaglandin E2; ICAM1, intercellular adhesion molecule 1; LFA1, lymphocyte function-associated antigen 1; IFNγ, interferon gamma.

  104  

release neutrophil extracellular traps containing granule proteins and, of course,

chromatin26,155, though neutrophils are not required for alum nodule formation26.

Several types of recruited innate immune cells (especially mast cells and

macrophages) secrete inflammatory IL-1β and IL-18 due to inflammasome

activation68. Though not required for alum responses, the inflammasome has

been proposed to be activated by alum in a number of ways, all of which

probably occur in vivo. These pathways include detection of alum crystals

themselves or damage-induced uric acid crystals59, lysosomal rupture by

engulfed alum crystals and subsequent release of cathepsin B protein into the

cytosol64, and even host DNA sensing156. In addition to inflammasome-

associated molecules that are secreted by a number of innate immune cell

subsets, eosinophils rapidly produce IL-4 and mast cells produce IL-5 at the site

of alum injection50,68 and macrophages produce prostaglandin E286,87.

Cumulatively, these inflammatory signals seem to promote the development of

type 2 immune responses in mice.

Step 2: Activation of antigen presenting cells

The most important consequence of the damage and inflammation caused

by alum is the activation of professional antigen presenting cells. As discussed

and demonstrated in Chapter IV, conventional dendritic cells (cDCs) and

inflammatory monocytes (iMonos) are the most prominent players in alum

antigen presentation to T cells. Activation of these and other subsets is critical

  105  

for the initiation of adaptive immune responses and generation of protective

immune memory.

There seems to be disagreement about whether or not alum crystals are

phagocytosed by immune cells. One group used macrophage cell lines to show

that alum can be engulfed and caused lysosomal destabilization that leads to

inflammasome activation64. Conversely, another group found that alum does not

enter cells; it instead delivers soluble antigen across the plasma membrane71. In

this latter study, Flach et al. reported that alum directly engages lipids in the

plasma membrane of dendritic cells, leading to lipid sorting that initiates abortive

phagocytosis through spleen tyrosine kinase (Syk) and phosphoinositide 3-

kinase (PI3K) signaling71 as well as DC activation. Furthermore, they claimed

the inflammasome is not required for this lipid sorting-mediated DC activation.

Both of these studies used in vitro models to make these discoveries. It is

unknown how the in vivo cell milieu affects these processes, but I am inclined to

think that different immune cell subsets deal with alum differently: engulfing the

crystals or not. Since the route by which APCs take up particulate antigen (pino-,

endo-, or phago-cytosis) affects their ability to present or cross-present antigen to

T cells157, alum uptake or lack thereof by APCs likely affects how and which T

cells the APCs prime in dLNs. Flow cytometry studies, such as mine, that use

fluorescent antigen with alum cannot distinguish whether a cell has internalized

the antigen/alum or has it on its cell surface. Immunohistochemistry must be

done to parse this difference out.

  106  

Regardless of whether or not alum is engulfed by APCs, alum

vaccinations cause widespread APC activation at the site of injection. Several

studies agree that detection of alum leads to increased antigen uptake, DC

maturation and upregulation of associated cell surface molecules, migration to

draining lymph nodes, and increased peptide presentation on MHC II57–60,62,83,158.

In conclusion, it seems likely that alum triggers a number of redundant

inflammation pathways that all contribute to broad type 2-biased APC activation.

Step 3: Priming adaptive immune cells

Upon activation, APCs migrate to draining lymph nodes to initiate adaptive

immune responses against the offending threat. Antigen-loaded APCs prime

CD4 T cell responses through pMHC II/TCR interactions. These APC/T cell

interactions are stable, mediated by co-stimulatory and adhesion molecules such

as intracellular adhesion molecule-1 (ICAM-1) and lymphocyte function-

associated antigen-1 (LFA-1)49,71. Additionally, primed CD4 T cells receive

chemical signals (such as IL-4 and IL-25) from alum-activated APCs that bias

them toward TH2 and TFH2 differentiation in mice78,79. To prime CD8 T cells,

APCs must cross-present antigen. It is not clear which APCs are responsible for

CD8 T cell priming, though I hypothesize that cells which took up alum crystals

and suffered from lysosomal rupture would be best at presenting antigen on

MHC I because antigen has leaked into their cytosols and thus could be easily

loaded onto MHC I molecules. Primed CD8 T cells differentiate into IFNγ-

producing CTLs79,93. Importantly, alum-primed APCs promote strong enough T

  107  

cell activation in both CD4 and CD8 T effector subsets to generate protective

memory T cell populations in mice92,125,159 and humans160, though the process by

which memory cell differentiation occurs remains unclear.

Germinal center B cells must acquire and present antigen to TFH cells to

receive ‘help’, so these antigen-bearing cells contribute to (but don’t fully explain)

the large number of antigen-positive B cells in dLNs after alum vaccination

(Chapter IV). It is unknown when, where, or how B cells encounter alum-

adsorbed antigen, nor did my experiments determine if B cells had indeed

engulfed the fluorescent antigen. Activated TFH cells use their upregulated

CXCR5 receptor to migrate into B cell zone germinal centers to aid antigen-

specific B cells with class switching to IgG1 and IgE isotypes (in mice)56 or IgG1

and IgG3 (in humans)40. To the best of my knowledge, the degree of IgE

induction by alum vaccines in humans has not been formally reported. Alum-

activated B cells differentiate into long-lived plasma cells that home to bone

marrow (or alum nodules128) and continue secreting antibodies for months to

years. This maintains a stable serum titer of antigen-specific antibodies that

protect the individual from future infection by pathogens that contain the vaccine

antigens28–30.

Step 4: Resolution and boosting

The nodules that form upon alum injection are long-lived; they can be

recovered from injected animals more than 7 weeks following immunization and

still contain antigen and immunogenic properties at that point127. However, alum

  108  

nodules are not required for the establishment of an alternative antigen depot,

but this is less well understood26,27. A recent study by Tamburini et al. proposed

that viral or vaccine-elicited inflammation can lead to ‘antigen archiving’ by

lymphatic endothelial cells: these cells capture and harbor antigens involved in

robust immune responses161. Lymphatic endothelial cell-mediated antigen

archiving may provide an explanation for how alum forms an antigen depot aside

from the nodules it forms.

Though alum stimulates effective antibody responses, these responses

are generally not as robust as those generated by live attenuated vaccines or

infections themselves. The long-lived antigen-specific plasma cells eventually

die off, so people require booster shots (every 10 to 15 years in the case of the

tetanus vaccine31) or a priming series of three vaccinations (as with the hepatitis

B vaccine24). Even with this drawback, alum vaccines have revolutionized public

health by providing an adaptable platform with which to provide people with

prophylactic protective immunity against a variety of deadly diseases11,23.

Beyond the Model: Additional Unresolved Questions

T cell responses to alum

It is clear that mice mount TH2 responses to alum, but the evidence for

TH2-bias in humans is much less convincing162. There is a paucity of studies on

human T cell responses to alum, but the few available suggest responses driven

by mixed populations of TH1, TH2, and possibly other CD4 effector subtypes.

  109  

Infants immunized with alum + Bordatella pertussis antigens generated mixed

TH1/TH2 cytokine profiles upon restimulation of peripheral blood mononuclear

cells44. Furthermore, alum is often used as an adjuvant in allergen preparations

for desensitization of patients with allergies163. A possible explanation for the

effectiveness of this treatment is that alum shifts immune responses away from

TH2 responses and induces IgE-blocking IgG antibodies and regulatory T cells164.

The issue of mouse immunology failing to reflect human immunology is not new

or particularly surprising. However, it must be emphasized and dealt with

carefully within the field of alum research because, at this point, the literature is

too far skewed toward mouse-only studies. It is difficult to evaluate the projected

success or failure of alum with new pathogenic antigens (for vaccines for

emerging diseases, per se) when too little is known about human T cell

responses to this adjuvant. After all, CD4 T cells are critical players in the

development of immune responses.

My experimental approach in Chapter III focused mainly on CD4 and CD8

T cell priming, with little attention paid to effector T cell functionality. It was

recently proposed that TH17 cells are responsible for the effectiveness of alum

vaccines in mice51,165, while TH2 cells are irrelevant. Although I phenotyped

responding CD4 T cells for TFH characteristics in WT and STING-deficient mice

immunized with alum, I did not look for TH17 cells. Mostly, my studies to evaluate

DNA’s role in mediating CD4 T cell priming by alum vaccines leaned heavily on

total numbers of primed CD4 T cells. In future studies, human peripheral blood

  110  

mononuclear cells should be examined for antigen-specific TH phenotype and

functionality shortly after alum vaccine administrations.

To further complicate matters, one study reported that the particular

antigen adsorbed to alum can alter which TH immune response is mounted in

humans. When humans subjects were immunized with Keyhole Limpet

Hemocyanin (KLH) plus alum, they mounted TH2-biased responses involving IL-

4, -5, -13, and -10 as well as induction of IgG4 antibodies166. However, people

who had received alum vaccinations with tetanus toxoid mounted TH1 responses

indicated by high IFNγ production and little to no IL-13 production in tetanus

toxoid-stimulated peripheral blood mononuclear cells166. This antigen effect

strongly suggests that alum research should be conducted with biomedically

relevant antigens rather than model antigens like chicken ovalbumin. It is

important to discern how alum acts when it has particular pathogenic antigens

adsorbed to it, such as hepatitis B surface antigen, tetanus toxoid, inactivated

hepatitis A virus, human papillomavirus L1 protein, etc. Lastly, this issue leads to

another question: How well do the characteristics of alum responses correlate to

the natural responses elicited by the pathogens against which alum vaccines

protect? A comprehensive study on this question would contribute greatly to our

understanding on alum efficacy. In conclusion, there are discrepancies between

how alum acts in mice versus humans and the body of alum literature is lacking

when it comes to human studies and characterizations of CD4 T cell responses.

It is important to patch these gaps in knowledge to understand why alum is an

effective human vaccine adjuvant.

  111  

Alum is widely thought to struggle with induction of CD8 CTL

responses162. One group proposed that the robust antibody responses elicited

by alum actually prevent strong CTL priming91. Very little is known about the

quality, homing, or memory induction of CD8 T cells by alum in humans. Our lab

previously reported that, in mice, alum can induce CD8 memory T cells that can

protect against influenza challenge93. However, alum-activated CD8 T cells

produce IFNγ but fail to differentiate into CTLs68,79,93. IFNγ secretion, and not

CTL activity, has been identified as an important aspect of immune responses

against select pathogens, such as Mycobacterium tuberculosis167. Perhaps alum

could stimulate effective CD8 T cells for protection against these sorts of

diseases. Importantly, our group is beginning a study to quantify and examine

antigen-specific CD8 T cells in peripheral blood samples from people who have

previously received the alum-containing hepatitis B vaccine series. This will be

the first study to evaluate CD8 T cell memory responses to an alum vaccine in

human beings. If possible, we will also analyze primary CD8 T cell responses in

recently-vaccinated subjects. In summary, there is a large gap in our knowledge

about the qualities of CD8 T cells stimulated by alum vaccines. Though alum is

recognized for its ability to generate antibody-mediated protection against a

variety of antigens, its ability to stimulate protective CD8 T cell responses may be

underestimated. Using this well-tolerated vaccine adjuvant in new vaccines that

protect against intracellular pathogens (that require CD8 T cell responses) could

be a powerful tool to better global health.

  112  

B cells as alum/antigen presenters

In Chapter IV, I observed that a large population of B cells was antigen-

loaded within dLN 24 hours after alum immunization. In addition to dendritic cells

and macrophages, antigen-specific B cells are also considered professional

APCs. There is disagreement about whether or not B cells are important in

and/or capable of primary T cell priming168,169. B cells very efficiently present

specific antigens to TFH CD4 T cells in order to obtain help for the production of

high-affinity antibodies. B cells can also present nonspecific antigens derived

from endogenous and pinocytosed proteins, but the outcome is T cell

tolerance169–171. Furthermore, B cells as APCs have been reported to promote

type 2 immune responses because they produce IL-4 in response to IL-12-

producing DCs136. Alum has been documented to induce local IL-12p80 cytokine

concentration when injected intraperitoneally47 in mice, suggesting that IL-12-

induced B cell production of IL-4 could contribute to TH2 skewing in alum

responses. Alternatively, if they secrete IL-4 in an autocrine manner, this IL-4

production could purely be used to promote self-stimulation within an

inflammatory setting since IL-4 is an anti-apoptotic B cell survival and

differentiation factor89,172–174. More studies are required to discern the role of

antigen-loaded B cells in alum immunogenicity.

  113  

Adjuvant Action of Host DNA

Data in Chapter III indicate that host DNA does not play a major role in

mediating the adjuvant activity of alum in mice. Amy McKee and I both used

STING-deficient animals to test STING’s importance to alum responses as its

main known function is to mediate intracellular DNA-sensing pathways. Using

OVA-3K as a model antigen, she found that STING was necessary for 3K-

specific CD4 T cell responses49, but did not affect CD8 responses (unpublished

data). Using OVA-NP as a model antigen, I found that STING was dispensable

for both NP311-325-specific CD4 and SIINFEKL-specific CD8 T cell responses.

Beside genetic drift within STING-deficient and C57BL/6 animals, this

discrepancy can only be accounted for by the difference in CD4 T cell epitope

used (conjugated to OVA). Since the C57BL/6 murine CD4 T cell response to

NP311-325 within the OVA-NP antigen is quite robust, perhaps alum no longer

requires the STING pathway to be operative to mount a sufficient immune

response. Alternatively, responses to OVA (without NP peptide) or 3K peptide

and alum need stronger instigation in the form of STING pathway activation.

While I found that STING-deficient animals respond normally to alum

vaccines, Marichal et al. reported that IgE responses to alum depend on Tbk1

and Irf3 signaling47, two molecules that are downstream of STING upon

intracellular DNA-sensing. If we assume that alum requires DNA to trigger this

pathway for immunostimulatory effects, my data directly contradict those reported

by Marichal and colleagues. However, STING (and host DNA) may be

  114  

dispensable while Tbk1 and Irf3 signaling are still required because these two

molecules are involved in more pathways than just STING-associated DNA

sensing. Tbk1 and Irf3 are implicated in a variety of known intracellular signaling

pathways175 (listed in Table 6.1) and, of course, may be activated by yet

unidentified mechanisms. For these reasons, it is still possible that Tbk1 and Irf3

are required for efficient IgE induction upon alum immunization.

Table 6.1. Signaling pathways that involve Tbk1 and Irf3175.

PRR PRR full name Known ligands

Molecule that interacts with Tbk1

TLR3 Toll-like receptor 3 dsRNA TRIF (TIR-domain-containing adapter-inducing interferon-β)

TLR4 Toll-like receptor 4 LPS, gp96176 TRIF RIG-I Retinoic acid-inducible gene 1 dsRNA RIG-I

MDA5 Melanoma differentiation-associated protein 5 dsRNA MDA5

DAI DNA-dependent activator of IFN-regulatory factors dsDNA DAI

NODs (1 and 2)

Nucleotide-binding oligomerization domain containing proteins (1 and 2)

Peptidoglycan RIPK2 (Receptor-interacting serine-threonine kinase 2)

Even though I report that DNA is non-essential for alum responses, I do

not discount that host DNA can still contribute to alum responses via STING

activation and (likely) other mechanisms. As I discussed in my working model of

alum activity, alum is capable of triggering many inflammatory pathways, most of

which have been shown to be dispensable for alum’s overall effect as an

adjuvant. This redundancy may explain why inflammatory detection of chromatin

release by dying cells and neutrophils is not required for alum responses. DNA

has been shown to be immunostimulatory for a variety of cells in a variety of

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settings95,96,126,177. In fact, mammals have evolved to express a large number of

dsDNA sensing molecules, implying that dsDNA sensing is an important cellular

function178. As an added adjuvant, genomic DNA was shown to activate iMonos,

promote antigen-specific T cell proliferation, and induce IgG1 and IgE antibody

production47. Self DNA can be transported into cells such as plasmacytoid DCs

and monocytes, leading to production of type I IFNs via the STING/Tbk1/Irf3

pathway179. DNA can also activate the inflammasome in an ASC- (apoptosis-

associated speck-like protein containing a caspase activation and recruitment

[CARD] domain) and caspase-1-dependent, but not NLRP3-dependent,

manner156. Furthermore, one study reported that T cells can directly sense

genomic DNA, which is released from dead cells, and promotes the induction of

TH2 differentiation180. This DNA sensing was independent of known nucleic acid

sensors, including TLRs, RLRs, inflammasomes, and STING-dependent sensors.

It is clear that host DNA can indeed stimulate immune responses, but my findings

show that it is not essential for alum responses.

Another way to infer if host DNA plays a role in immune responses is to

examine pathogenic virulence factors for proteins that interact with DNA. Indeed,

Streptococcus pneumoniae escapes from neutrophil extracellular traps

(comprised of a DNA backbone with embedded antimicrobial peptides and

enzymes181) by expressing its own DNase called Sda1182,183. Thus the Sda1

bacterial virulence factor specifically counteracts NETs, implying that NETs

impede infection by this bacterial pathogen. It is important to note that NETs

contain host chromatin, not just host DNA, and chromatin-associated proteins

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such as HMGB1 are also known to be inflammatory DAMPs95. In conclusion,

release of chromatin as a danger signal from dying cells and within NETs is an

important innate mechanism of immune activation.

Reproducibility in Science and Implications of DNase Contamination

It is no secret that reproducibility (or lack thereof) is a considerable issue

in scientific research184. Our discovery that bovine-sourced commercial DNase

reagents can be contaminated with active proteases (Chapter III) has far-

reaching implications, the first of which is that reported quality assessments of

commercial products may be faulty (i.e. Sigma reported zero protease activity,

though the product contained substantial activity). Though unreproducible

studies are caused by a variety of factors, both innocent and fraudulent, the use

of reagents that have contaminants with off target effects is one possible cause

of this problem. I hope my example can serve as a warning to other researchers

that reagents must be thoroughly analyzed for quality and purity before use.

More importantly, unsuspected protease contamination within the

commonly used Roche DNaseGII and Sigma DNase products has potentially

affected a substantial number of experiments in the last decade or more. Use of

contaminated DNases in any procedure that aims to purify or retain proteins

while degrading DNA would have potentially digested the proteins of interest. At-

risk procedures include chromatin immunoprecipitation, recombinant protein

purification, tissue digestion for isolation of antigen presenting cells, preparation

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of cell samples for flow cytometric analysis, and unknown numbers of other

procedures. In fact, I used Roche DNaseGII in the purification of recombinant

NP and mutNP, used in Chapters III-V, which raises uncertainty about both

proteins’ intactness when used as vaccine model antigens. Of course, the

experimental conditions during which DNase is used would affect the kinetics of

protease digestion of proteins within samples. However, many protocols allow

DNase digestion to occur for approximately 30 minutes either at room

temperature or 37°C. I demonstrated that this is ample time for active proteases

to cause off target damage (Chapter III).

In conclusion, protease contamination within DNase reagents may have

unintentionally altered the results or interpretations of published scientific studies,

particularly those that are not repeatable. This contamination was present within

at least two lots of a very commonly used commercial product, Roche DNaseGII,

and therefore this discovery could have widespread effects on laboratory

protocols across the nation.

The Future of Vaccines

Finally, I want to briefly share my thoughts on the future of vaccines. Alum

has been reported to cause substantial injury to muscle fibers, necrosis,

microabscesses, and histopathological lesions within injected muscle

tissue94,185,186. Additionally, I already mentioned that antigen-containing alum

nodules remain at the site of injection for at least 7 weeks after immunization127.

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Are these aspects of alum immunization acceptable? Arguably, damaged

muscle and lingering alum nodules are a relatively small price to pay for

protection against deadly infections such as pertussis, tetanus, or diphtheria or

cancer-causing viruses like HPV16, but is there a better way? Furthermore, it

has been known for quite some time that intradermal administration of vaccines

is generally more effective than intramuscular injection187. Perhaps we should

consider tailoring our standard routes of administration to encourage the highest

efficacy possible for each vaccine? Additionally, different routes of administration

and components within vaccines may be desirable for patients of different age

groups, immune status, or genetic backgrounds. In the past few decades, there

has been a flurry of progress toward the intelligent design of vaccines,

specifically regarding the deliberate selection of antigens and adjuvants for

effective subunit vaccines. For example, simultaneous stimulation of several

TLRs188 and/or targeted activation of specific dendritic cell subsets to achieve

desired immune outcomes189 can drastically affect immune responses to

vaccines.

Lastly, returning to the subject of alum as a versatile vaccine adjuvant,

additional adjuvants (such as TLR4-stimulating LPS derivatives) have been

added to alum to enhance immune responses82,93. Additionally, altered forms of

antigen have been adsorbed to alum, which can also alter the ensuing immune

responses. For example, if mildly heat denatured allergens are adsorbed to alum

instead of soluble protein allergens, IgE-binding epitopes are largely destroyed

but IgG2a antibody responses are augmented, which helps skew allergic

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responses away from TH2104. This and other studies indicate that either antigen

properties and/or whole particle size affects immune responses190–192. In

summary, there are many known and unknown factors that play into the efficacy

of human vaccines. In my opinion, we should leverage what we know to

generate the most effective vaccines against the most diseases possible, without

getting bogged down in precedent, paperwork, or politics. We have yet to design

effective prophylactic vaccines against HIV or malaria and therapeutic vaccines

against many cancers, but I believe these goals will soon be in reach.

Future Directions

My thesis concludes that DNA plays only a minor role in alum biology,

contrary to two recent publications. Thus, the future of this investigation is no

longer concerned with DNA and alum. Interesting but incomplete studies

presented in this thesis should be followed up. As described in Chapter IV, RNA

sequencing of alum-treated or untreated APCs should be repeated in order to

more confidently identify genes that have altered expression after alum

exposure. Once genes are identified, experiments are needed to validate that

RNA expression alterations correlate with differences in protein expression.

Finally, the importance of these proteins in alum sensing and inflammation may

be verified by performing loss-of-function and phenotype rescue experiments.

This extension of Chapter IV studies could prove useful in validating or

discovering new inflammatory pathways stimulated by alum. Particularly, this

  120  

approach may validate the lipid sorting57 and lysosomal destabilization49 theories

of alum recognition by APCs. However, there is a large, if incongruent, body of

literature that focuses on how alum stimulates innate immune cells in mice.

Instead of studying alum stimulation of mouse APCs further, there is a great

need for better characterization of T cell and antibody responses to alum in

humans.

Given the expertise of the Kappler/Marrack lab in T cell biology, I propose

that this project move toward better characterizing human T cell responses to

alum vaccines. A reasonable next study would be to examine primary and

memory CD4 and CD8 T cell populations in peripheral blood of alum-vaccinated

human subjects. Quantification of antigen-specific T cells is warranted, though

this requires the creation of human peptide/HLA tetramers that can recognize T

cells specific for alum-adsorbed antigens of interest. Obtaining or designing

these reagents is no small feat. Ideally, functional tests on human T cells would

also be conducted to determine which cytokines they secrete and thus infer

which type(s) of immune response they facilitate. This would help settle the

issue of whether or not alum induces TH2 responses in humans. If possible,

several (or all) currently licensed and used alum vaccines should be examined to

determine if alum behaves similarly or differently based on the type of protein

antigen(s) used and presence of other vaccine components. Information from

such a study should provide definitive information about the adjuvant mechanism

of alum in humans, possibly improving vaccine practices.

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Concluding Remarks

Alum is a critical component in subunit vaccines that have greatly helped

mankind avoid illness and death from a variety of infectious diseases. Though it

is widely used, alum’s mechanism of action is still mysterious in some ways. My

thesis project contributes to alum research by questioning the theory that DNA

mediates alum activity. I found that DNA is not essential to this process. My

work serves to correct the literature and hopefully redirect other labs’ research

efforts on this subject. This knowledge will improve future studies to elucidate

the mechanism of aluminum salts in future vaccination strategies. Additionally, I

have revealed an important contamination issue within current DNase reagents,

a discovery that has broad implications for scientific protocols in many fields of

research. I hope my thesis work contributes to biomedical literature in a way that

assists other researchers in their goals.

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