ENHANCEMENT OF RECOMBINANT ADENOVIRUS VECTOR
VACCINE EFFICACY BY INNATE IMMUNE MODULATION
By
Dionisia Marie Quiroga

A DISSERTATION
Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of
Cell and Molecular Biology – Doctor of Philosophy
2014

ABSTRACT
ENHANCEMENT OF RECOMBINANT ADENOVIRUS VECTOR
VACCINE EFFICACY BY INNATE IMMUNE MODULATION
By
Dionisia Marie Quiroga
In the field of vaccine development, there is a clear need for novel, effective platforms
and adjuvants that can elicit robust, multifaceted adaptive immune responses to antigenic targets.
Unfortunately, many methods investigated thus far are either too toxic or too weak to induce a
substantial response against difficult targets, such as tumor-associated antigens (TAAs) or
antigens from highly-mutagenic pathogens. In this dissertation, we explore the use of
recombinant adenovirus serotype 5 (rAd5) platforms as vaccine vectors and the ability of innate
immunostimulants to act as concurrently-administered adjuvants.
First, we investigated how different variations of rAd5 vectors may promote altered
innate immune signaling, and downstream, improved transgene memory responses. rAd5 vectors
are strong vaccine candidates due to their intrinsic immunogenicity and potent transgene
expression, however, widespread pre-existing Ad5 immunity has been considered a
developmental barrier to the use of traditional, first-generation (Ad5[E1-]) vectors. Recently
published studies have revealed that additionally E2b-deleted rAd5 (Ad5[E1-,E2b-]) vectors
circumvent anti-Ad5 immunity to induce stronger transgene-specific memory responses than
Ad5[E1-] vectors, yet it is unknown why these vector differences exist. Therefore, we decided to
compare Ad5[E1-] and Ad5[E1-,E2b-] vector-induced innate immune responses by using human
peripheral mononuclear cell (hPBMC) samples from multiple donors. We found that Ad5[E1,E2b-] vectors trigger higher levels of pro-inflammatory cytokine secretion and Th1-dominant
gene expression; yet lowered amounts of Ad viral-derived gene expression, independent of the

donors' pre-existing anti-Ad5 adaptive responses. These results suggest that Ad5[E1-,E2b-], in
contrast to Ad5[E1-], vaccines do not promote activities that suppress innate immune signaling,
revealing a novel way they may produce superior efficacy and safety profiles, regardless of
previous Ad5 immunity.
Next, we investigated if and how a recombinant profilin-like immunostimulant derived
from the Eimeria tenella protozoan (rEA) may promote innate immunity during rAd5-mediated
vaccination. Upon finding that rEA could trigger activation of multiple types of hematopoietic
immune cells in a MyD88-dependent, but TRIF-inhibitory, manner; we created a rAd5 vector
expressing rEA to test its ability to enhance CMI responses against co-injected vaccine targets.
rEA is an attractive vaccine candidate due to previous clinical investigations showing it to be a
safe, immunogenic agent with the ability to trigger Th1-predominant responses in vivo.
Subsequently, we investigated if an rEA-expressing rAd5 (rAd5-rEA) could promote and/or alter
cytotoxic memory responses towards CEA, a colorectal cancer-related TAA. We found that the
addition of rAd5-rEA to an Ad-based CEA vaccine (rAd5-CEA) induced a dose-dependent
increase in the potency of anti-CEA T cell and B cell responses, elevated the number of CMIand IgG-recognized CEA-specific epitopes, and enhanced in vivo CEA-targeted cell killing,
suggesting that co-injection of rAd5-rEA with a TAA-directed vaccine can substantially boost
and broaden the TAA-specific memory response.
Finally, we briefly discuss the use of an rAd5 expressing endoplasmic reticulum
aminopeptidase 1 (ERAP1) and how different polymorphisms of this gene may promote innate
immune and cellular stress signaling. Overall, these dissertation findings address how best the
features of rAd5-based vectors can be utilized as vaccine models and how modulation of innate
immunity can be used to direct and foster vaccine-promoting long-term memory responses.

Copyright by
DIONISIA MARIE QUIROGA
2014

I dedicate my dissertation to my friends and family,
who have supported me whole-hearted throughout my
graduate school process and will continue to support me afterwards.
For every phone call, every meal, every hug, and every smile,
I can’t thank you enough.

v

ACKNOWLEDGEMENTS

To my mentor, Dr. Andy Amalfitano – It is clear that you serve as a model for what
D.O./Ph.D students can hope one day become: a successful, intelligent physician scientist who
has made tremendous strides in their area of research while still taking the time to provide
compassionate treatment to his patients. Of all the hats you wear, you were still able to provide
me with the mentorship and education I needed to excel in my studies. You taught me not only
how to conduct medical research well, but also how to think outside of the box and be a more
independent thinker. And while you have been a more than kind and generous mentor; you did
not hesitate to gradually push me to do more than what I even thought I was capable of. Without
this motivation, I doubt I would be able to come out of this program with as many skills and
experiences as I have now; and I am eternally grateful for all of them you’ve equipped me with.
Thank you for believing in me every step of the way; my hope is that one day, I will be able to
pass on these same gifts to another young researcher like you did for me.
To my guidance committee members, Dr. Walter Esselman, Dr. J. Justin McCormick, Dr.
Richard Schwartz, and Dr. Kefei Yu – Thank you so much for your helpful comments and
suggestions. You helped me to think constructively and analytically, while also providing input
into how best to proceed with my experiments, funding opportunities, and future career goals.
To my colleague, Dr. Yasser Aldhamen – Your insight, advice, and day-to-day assistance
were invaluable tools to me during the entirety of my graduate experience. As you’ve progressed
over the years from graduate student, to post-doctoral scientist, to professor; you’ve allowed me
to advance in my skills as a researcher as well. I was so fortunate to have your guidance; it was
truly like having a second mentor.

vi

To my labmates, past and current, including Dr. Fadel Alyaqoub, Dr. Daniel Appledorn,
Dr. Charles Aylsworth, Dr. Joyce Liu, Aaron McBride, Yuliya Pepelyayeva, Cristiane Pereira,
David Rastall, Sarah Godbehere Roosa, Dr. Nathan Schuldt, Dr. Sergey Seregin, and Dr. Tyler
Voss – You have made coming to work every day a pleasure and were more than kind in giving
me your assistance and advice throughout the years. I look forward to keeping in touch with
everyone, both through your research work and personally.
To our undergraduate assistants, past and current, including Marissa Bauters,
Christopher Blum, Matthew Bujold, Brandi Burke, Christopher Busuito, John David, Dr.
William DePas, Laura Harding, Megan Hoban, Kristen Kenny, William Nance, Doug Peters,
Ashley Raedy, and Jennifer Zehnder – I thank you for your many hours of work that allow for
the lab functions and experiments to run smoothly. I have enjoyed watching you progress from
freshman to graduate/professional students yourself and I’m happy to have had the chance to be
a part of that process.
To the MSU ULAR and Research Technology Support Facility staff, especially Dr. Louis
King in flow cytometry and Dr. Jeff Landgraf and Colleen Curry in genomics – I am so grateful
for your aid in learning and working with the technologies and facilities necessary for me to
complete my dissertation research.
To my graduate program director Dr. Susan Conrad and program manager Becky
Mansel – Thank you for giving me the opportunity to conduct my graduate studies in such a
supportive and friendly environment. Additionally, your assistance with all the logistics that go
into completing a Ph.D was priceless to me.
To the MSU D.O./Ph.D program personnel, past and current, including Dr. Justin
McCormick, Dr. Veronica Maher, and Bethany Heinlen – I cannot thank you enough for

vii

allowing me to join this exceptional program. You have helped me through every step and every
stumble I made along the way, and always with compassion, resolve, and encouragement. Thank
you for keeping me on track, both then and now.
To my fellow D.O./Ph.D students, especially Steven Proper, Joseph Prinsen, Darin
Quach, and Paul Beach – Thank you so much for all your great, honest advice as we went
through this process together. I am so grateful for the friendship and good times I got to have
with you during our years here.
To Mrs. Lois Rood, and in memory of Suzan Jean Snyder – I thank you for your support
and scholarship to assist me in my graduate and medical studies into the field of oncology. I hope
that I can contribute back to the field of cancer research and patient care in a way that would
honor the memory of your daughter who lost her battle with cancer.
To the McNair/SROP program staff and scholars, especially Dr. Nettavia Curry – I have
you to thank for first introducing me to the research world as an undergraduate student and
helping me to begin development of the skills I would need to pursue a Ph.D and career as a
scientist.
To my lovely friends, especially Lola Alvarez, Ruby Carrillo, Allie Holschbach, and
Jessica Jean – Whatever day or time it was, I could always count on you to be a lending hand, a
study buddy, or a dance partner with me. You are overly generous and patient with me and I’m
so proud and happy to have you all in my life.
To my aunts, uncles, cousins, half-siblings, and other extended family members – Since
day one, you’ve always encouraged me to follow my passions. Also, thank you for teaching me
about the importance of learning about one’s culture, telling a good joke, reading great books,
and drinking excellent wine.

viii

To my little brother, Michael – Thank you so much for assisting me in the editing and
design of some of the dissertation figures. More importantly, thank you for being the steadythinking and collected sibling in our family. You’re an intelligent, caring, and witty person that I
am so lucky to call my friend and my brother.
To my mom, Lenore – You have always supported me through thick and thin; always
putting the needs of your family and others before yourself . Once I got into college, you may not
have been able to help me with my homework anymore, but you took the time to help me with
every other difficulty I approached, whether it was fixing up things around the house, giving me
a place to stay when I had none, making big financial decisions, or planning my next move. You
are were and are a shining example to me of what a strong, smart, and caring woman should be
like.
To my dad, Pablo – Since I was a little girl, you’ve always been my hero; my first and
best inspiration to pursue medicine and graduate school. You never tried to push or persuade me
into the medical profession; all you needed to do is show me by example what a great physician
could do. I can only hope that after getting both my medical degree and my Ph.D, I could
possibly be even half the doctor you are.
Thank you all for your generosity; I couldn’t have done this without you!

ix

TABLE OF CONTENTS

LIST OF TABLES ....................................................................................................................... xiii
LIST OF FIGURES ..................................................................................................................... xiv
KEY TO ABBREVIATIONS ...................................................................................................... xvi
Chapter 1: Introduction ............................................................................................................... 1
1.1
Innate immunity .................................................................................................................. 2
1.1.1 Definition and overview ......................................................................................... 2
1.1.2 Toll-like receptors and Toll-like receptor agonists ................................................. 5
1.1.3 Anti-viral innate immunity ..................................................................................... 6
1.2
Adaptive immunity ............................................................................................................. 8
1.2.1 T cell-based adaptive immunity .............................................................................. 8
1.2.2 B cell-based adaptive immunity.............................................................................. 9
1.2.3 Effects of TLR signaling on adaptive memory response ...................................... 10
1.3
Vaccine adjuvants ............................................................................................................. 12
1.3.1 Definition and overview ....................................................................................... 12
1.3.2 Currently utilized adjuvants in human vaccines ................................................... 12
1.3.3 TLR agonist adjuvants .......................................................................................... 13
1.4
Recombinant adenoviruses ............................................................................................... 15
1.4.1 Adenovirus biology and structure ......................................................................... 15
1.4.2 Synthesis and utilization of rAd for vaccine vectors ............................................ 17
1.4.3 Innate immune recognition of rAd ........................................................................ 19
1.4.4 Pre-existing immunity against rAd vaccine vectors ............................................. 21
Chapter 2: Decreased vector gene expression from second-generation, E2b-deleted Ad5
vaccines paradoxically intensifies pro-inflammatory immune responses.............................. 23
2.1
Introduction ....................................................................................................................... 24
2.2
Methods............................................................................................................................. 27
2.2.1 Microarray analysis ............................................................................................... 27
2.2.2 Recombinant adenovirus vector construction ....................................................... 27
2.2.3 Cell isolation, culture, and adenovirus infection .................................................. 28
2.2.4 ELISA analysis ..................................................................................................... 28
2.2.5 Cell staining and flow cytometry .......................................................................... 29
2.2.6 RNA extraction, cDNA synthesis, and quantitative RT-PCR .............................. 29
2.2.7 Statistical analysis ................................................................................................. 32
2.3
Results ............................................................................................................................... 33
2.3.1 Hepatocyte microarray analysis following first- or second-generation rAd
infection ................................................................................................................ 33
2.3.2 Ad5[E1-,E2b-] vectors induce an increased pro-inflammatory cytokine response
upon hPBMC infection ......................................................................................... 48

x

2.3.3

Ad5-induced pro-inflammatory cytokine responses are not correlated to preexisting Ad5 immunity in human blood samples ............................................... 556
2.3.4 Ad5[E1-,E2b-] infection produces dampened Ad gene expression ...................... 61
2.3.5 Ad5[E1-] and Ad5[E1-,E2b-] vectors induce distinct innate immune gene
expression profiles ................................................................................................ 68
2.4
Discussion ......................................................................................................................... 70
Acknowledgements ....................................................................................................................... 74
Chapter 3: Utilization of a recombinant adenovirus vector expressing an Eimeria antigenderived TLR agonist as a vaccine adjuvant. ............................................................................. 75
3.1
Introduction ....................................................................................................................... 76
3.2
Methods............................................................................................................................. 78
3.2.1 Animal care and procedures.................................................................................. 78
3.2.2 Recombinant adenovirus vector construction ....................................................... 78
3.2.3 Splenocyte processing ........................................................................................... 79
3.2.4 Cell staining and flow cytometry .......................................................................... 79
3.2.5 Cytokine and chemokine analysis ......................................................................... 80
3.2.6 Enzyme-linked immunosorbent spot (ELISpot) assay analysis............................ 80
3.2.7 Statistical analysis ................................................................................................. 81
3.3
Results ............................................................................................................................... 82
3.3.1 Regulation of rEA-induced dendritic cell responses by TLR adaptor proteins
... …………………………………………………………………………………82
3.3.2 Regulation of rEA-induced natural killer cell responses by TLR adaptor
proteins………………………………………………………………………..….88
3.3.3 Murine cytokine response to intramuscular or intraperitoneal rEA protein
injections ............................................................................................................... 93
3.3.4 An rEA-expressing recombinant Ad5 vector enhances co-expressed transgenespecific immunity.................................................................................................. 97
3.3.5 Addition of rAd5-rEA improves CMI against a co-injected rAd-expressed
transgene ............................................................................................................. 102
3.4
Discussion ....................................................................................................................... 104
Acknowledgements ..................................................................................................................... 106
Chapter 4: Strengthened tumor antigen immune recognition by inclusion of a recombinant
Eimeria antigen in therapeutic cancer vaccination ................................................................ 108
4.1
Introduction ..................................................................................................................... 109
4.2
Methods........................................................................................................................... 111
4.2.1 Recombinant adenovirus vector construction ..................................................... 111
4.2.2 Animal care and procedures................................................................................ 111
4.2.3 ELISpot assay analysis ....................................................................................... 111
4.2.4 Cell staining and flow cytometry ........................................................................ 112
4.2.5 In vivo cytotoxic T lymphocyte (CTL) assay ..................................................... 112
4.2.6 Anti-CEA and anti-Ad ELISA analysis .............................................................. 113
4.2.7 Statistical analysis ............................................................................................... 114
4.3
Results ............................................................................................................................. 115

xi

4.3.1

Increased rAd5-CEA transgene-specific CMI responses induced in the presence
of rAd5-rEA ........................................................................................................ 115
4.3.2 Improved cytotoxic T cell responses against CEA following high-dose rAd5-CEA
+ rAd5-rEA co-administration ............................................................................ 117
4.3.3 Dose-dependent increase in anti-CEA IgG production following rAd5-CEA +
rAd5-rEA co-administration ............................................................................... 120
4.3.4 rAd5-CEA + rAd5-rEA co-injection enhances breadth of T cell-recognized CEA
peptide epitopes .................................................................................................. 122
4.3.5 rAd5-CEA + rAd5-rEA co-injection enhances diversity of anti-CEA IgG
antibody-identified CEA peptide epitopes .......................................................... 130
4.3.6 Enhanced in vivo CEA-targeted CTL killing following rAd5-CEA + rAd5-rEA
co-administration ................................................................................................ 134
4.4
Discussion ....................................................................................................................... 137
Acknowledgments....................................................................................................................... 142
Chapter 5: Recombinant adenoviruses expressing antigen-trimming protein ERAP1 trigger
a robust innate immune response. ........................................................................................... 143
5.1
Introduction ..................................................................................................................... 144
5.2
Methods........................................................................................................................... 146
5.2.1 Cell transfection and culture ............................................................................... 146
5.2.2 Recombinant adenovirus construction and cell infection ................................... 147
5.2.3 RNA extraction, cDNA synthesis, and quantitative RT-PCR ............................ 147
5.2.4 Protein isolation and western blotting................................................................. 149
5.2.5 In vitro phagocytosis assay ................................................................................. 149
5.2.6 Statistical analysis ............................................................................................... 150
5.3
Results ............................................................................................................................. 151
5.3.1 ERAP-1 expression following transfection of HeLa-Kb-B27/47 cells............... 151
5.3.2 Ad-ERAPlow and Ad-ERAPhigh activation of AS-related gene immune
responses ............................................................................................................. 156
5.3.3 Phagocytosis activity of RAW macrophages following Ad-ERAP stimulation..159
5.4
Discussion ....................................................................................................................... 163
Acknowledgments....................................................................................................................... 166
Chapter 6: Summary and future directions ........................................................................... 167
BIBLIOGRAPHY ....................................................................................................................... 176

xii

LIST OF TABLES

Table 1

Quantitative RT-PCR primers for rAd5[E1-,E2b-] studies……………………...31

Table 2

Ontological categorization of genes differentially and significantly expressed
following in vivo Ad5[E1-] or Ad5[E1-,E2b-] infection………………………...40

Table 3

Individual hPBMC sample cytokine inductions…………………………………52

Table 4

CEA peptide epitope sequences and assigned numbering………………...……123

Table 5

Quantitative RT-PCR primers for ERAP1 studies……………………………...148

xiii

LIST OF FIGURES

Figure 1

rAd5 genome and recombinant rAd5 platforms…………………………………16

Figure 2

Functional analysis of murine hepatocytes following in vivo Ad5[E1-] and
Ad5[E1-,E2b-] infection ………………………………………………………...35

Figure 3

Ad5[E1-,E2b-] infection induces increased hPBMC pro-inflammatory cytokine
secretion……………………………………………………………………….…50

Figure 4

Quantity of Ad5[E1-,E2b-]-induced hPBMC pro-inflammatory cytokine secretion
is not correlated to pre-existing anti-Ad5 immunity……………………………..57

Figure 5

Ratio of Ad5[E1-,E2b-] to Ad5[E1-] induced cytokine production is not
correlated to pre-existing anti-Ad5 immunity……………………………………60

Figure 6

Ad5[E1-,E2b-] infection produces dampened Ad gene expression……………...63

Figure 7

Ad5[E1-] and Ad5[E1-,E2b-] viral genome quantification following human
PBMC infection………………………………………………………………….67

Figure 8

Ad5 vectors promote distinct innate immune gene expression patterns dependent
on vector generation……………………………...………………………………69

Figure 9

rEA-mediated dendritic cell activation is differentially regulated by MyD88 and
TRIF……………………………………………………………………..……….83

Figure 10

rEA-mediated dendritic cell activation is differentially regulated by MyD88 and
TRIF (histogram plots)…………………………………………………....……..85

Figure 11

rEA-mediated dendritic cell activation is differentially regulated by MyD88 and
TRIF (MFI)…………………………………………………………..……..…....87

Figure 12

rEA-mediated NK cell activation is differentially regulated by MyD88 and
TRIF.......................................................................................................................90

Figure 13

rEA-mediated NK cell activation is differentially regulated by MyD88 and TRIF
(histogram plots)………………………………………………………..……..…92

Figure 14

rEA protein promotes cytokine and chemokine induction mainly independent of
injection route…………………………………………………………..………..95

Figure 15

rAd5-rEA construction……………………………………………………..…….99

xiv

Figure 16

Improved cell-mediated immunity towards co-expressed transgene following
rAd5-rEA vaccination…………………………………………..…………........101

Figure 17

rAd5-rEA induces heightened HIV Gag-specific CMI responses………..….....103

Figure 18

Strong CEA-specific cell-mediated immunity produced by rAd5-CEA and rAd5rEA co-vaccination……………………………………………………………..116

Figure 19

High-dose rAd5-CEA and rAd5-rEA administration induces a robust, CEAspecific CD8+ cytotoxic T cell response…………………………………….…119

Figure 20

Anti-CEA IgG production is potently induced by rAd5-CEA and rAd5-rEA coinjection…………………………………………………………………………121

Figure 21

rAd5-CEA and rAd5-rEA co-vaccination induces CMI against multiple unique
CEA peptide epitopes………………………………………………………..…126

Figure 22

Addition of rAd5-rEA to an rAd5-CEA vaccine regimen induces CMI against
multiple CEA peptide regions…………………………………………………..129

Figure 23

rAd5-CEA and rAd5-rEA co-injection induces creation of IgG antibodies against
a diverse area of CEA peptide regions………………………………………….131

Figure 24

High anti-CEA IgG binding affinity following rAd5-CEA and rAd5-rEA coinjection…………………………………………………………………………133

Figure 25

rAd5-CEA and rAd5-rEA co-injection induces significant CEA-specific in vivo
cytolytic T cell killing activity……………………………………………….…135

Figure 26

ERAP1 expression following HeLa-Kb-B27/47 transfection…………………..152

Figure 27

Expression of AS-related genes in ERAP1-transfected HeLa-Kb-B27/47
cells………………………………………………………………..……………155

Figure 28

Ad-ERAPlow and Ad-ERAPhigh induce AS-related gene expression………...158

Figure 29

Ad-ERAP stimulates RAW macrophage phagocytosis activation……………..162

xv

KEY TO ABBREVIATIONS

μL

microliter(s)

μM

micromolar

Ad

adenovirus

Ad5[E1-]

first-generation recombinant adenovirus

Ad5[E1-,E2b-]

E2b-deleted, second-generation recombinant adenovirus

Ad5[E1-,E4-]

E4-deleted, second-generation recombinant adenovirus

ADCC

antibody-dependent cell-mediated cytotoxicity

ANOVA

analysis of variance

APC

antigen presenting cell

AS

ankylosing spondylitis

AS03

adjuvant system 03

AS04

adjuvant system 04

ATP

adenosine triphosphate

BCG

Bacillus Calmette–Guérin

BCR

B cell receptor

BH FDR MTC

Benjamini-Hochberg false discover rate multiple test correction

BiP

binding immunoglobulin protein

bp

base pair(s)

CA-125

cancer antigen 125

CAR

coxsackievirus and adenovirus receptor

CD

cluster of differentiation

xvi

CD40L

cluster of differentiation 40 ligand

cDNA

complementary deoxyribonucleic acid

CEA

carcinoembryonic antigen

CFSE

carboxyfluorescein succinimidyl ester

CLR

C-type lectin receptor

CMI

cell-mediated immunity

CMV

cytomegalovirus

CNS

central nervous system

CpG

cytosine – phosphate – guanine

CTL

cytotoxic T lymphocyte

CXCL10

C-X-C motif chemokine 10

DC

dendritic cell

DKO

double knockout

DNA

deoxyribonucleic acid

dpi

day(s) post-injection

dsDNA

double-stranded deoxynucleic acid

dsRNA

double-stranded deoxynucleic acid

EASE

Expression Analysis Systematic Explorer

ELISA

enzyme-linked immunosorbent assay

ELISpot

enzyme-linked immunospot

EMCV

encephalomyocarditis virus

ER

endoplasmic reticulum

ERAP1

endoplasmic reticulum aminopeptidase 1

xvii

FACS

fluorescence-activated cell sorting

FBS

fetal bovine serum

Fc

fragment crystallizable

FDA

Food and Drug Administration

GAPDH

glyceraldehyde 3-phosphate dehydrogenase

GBP2

interferon-induced guanylate-binding protein 2

G-CSF

granulocyte colony-stimulating factor

GFP

green fluorescent protein

GI

gastrointestinal

GM-CSF

granulocyte-macrophage colony-stimulating factor

GO

gene ontology

HBV

hepatitis B virus

HCV

hepatitis C virus

HD-Ad5

helper-dependent adenovirus serotype 5

HEK293

human embryonic kidney 293

HIV

human immunodeficiency virus

HLA

human leukocyte antigen

hPBMC

human peripheral blood mononuclear cell

hpi

hour(s) post-injection

hpt

hour(s) post-transfection

HPV

human papillomavirus

HRP

horseradish peroxidase

HSV

herpes simplex virus

xviii

ICS

intracellular staining

IFIT

interferon-induced protein with tetratricopeptide repeats 1

IFN

interferon

Ig

immunoglobulin

IκB

nuclear factor of kappa light polypeptide gene enhancer in B cells
inhibitor

IKK-β

inhibitor of nuclear factor kappa-B kinase subunit beta

IL

interleukin

IM

intramuscular(ly)

IP

intraperitoneal(ly)

IPA

Ingenuity Pathway Analysis

IRAK

interleukin-1 receptor-associated kinase

IRF

interferon regulatory factor

ITR

inverted terminal repeat

IV

intravenous(ly)

kb

kilobase(s)

kDa

kilodalton(s)

KO

knockout

LPS

lipopolysaccharide

LRR

leucine-rich repeat

LTA

lipoteichoic acid

MALP-2

macrophage-activating lipopeptide 2

MAP3K7

mitogen-activated protein kinase kinase kinase 7

xix

MAPK

mitogen-activated protein kinase

MAVS

mitochondrial antiviral-signaling protein

MDa

megadalton(s)

MDA5

melanoma differentiation-associated protein 5

MFI

mean fluroescence intensity

mg

milligram(s)

MHC

major histocompatibility complex

miRNA

micro ribonucleic acid

mL

milliliter(s)

MLP

major late promoter

MPL

monophosphoryl lipid A

MyD88

myeloid differentiation primary response gene 88

NALP3

nucleotide binding oligomerization domain-like receptor-like
receptor family, pyrin domain containing 3

NCBI

National Center for Biotechnology Information

NFκB

nuclear factor kappa B

ng

nanogram(s)

NK

natural killer

NKT

natural killer T

NLR

nucleotide binding oligomerization domain-like receptor

OD

optical density

ODN

oligodeoxynucleotide(s)

OTC

ornithine transcarbamylase

PAMP

pattern-associated molecular pattern

xx

PBS

phosphate buffer saline

PCR

polymerase chain reaction

PKR

protein kinase ribonucleic acid-activated

PMA

phorbol myristate acetate

Pol

DNA polymerase

poly(I:C)

polyinosinic:polycytidylic acid

PRR

pattern recognition receptor

PSF

penicillin-streptomycin-fungizone

PTP

precursor terminal protein

rAd

recombinant adenovirus

rAd5

recombinant adenovirus, serotype 5

RANTES

regulated on activation, normal T cell expressed and secreted

RBC

red blood cell

rEA

recombinant Eimeria antigen

RFP

red fluorescent protein

RIG-I

retinoic acid-inducible gene I

RIPK1

receptor-interacting serine/threonine-protein kinase 1

RLR

retinoic acid-inducible gene-I-like receptor

RNA

ribonucleic acid

RNAi

ribonucleic acid interference

RT-PCR

reverse transcription polymerase chain reaction

SFC

spot-forming cells

ssRNA

single-stranded ribonucleic acid

xxi

TBK1

tumor necrosis factor receptor-associated factor family memberassociated nuclear factor kappa B activator-binding kinase 1

TCR

T cell receptor

Th

T helper

TIR

Toll/interleukin-1 receptor

TIRAP

Toll-interleukin 1 receptor domain containing adaptor protein

TLR

Toll-like receptor

TMB

tetramethylbenzidine

TNF

tumor necrosis factor alpha

TRAF

tumor necrosis factor receptor associated factor

TRAM

Toll/interleukin-1 receptor -domain-containing adapter-inducing
interferon-β-related adaptor molecule

Treg

Regulatory T cell

TRIF

Toll/interleukin-1 receptor -domain-containing adapter-inducing
interferon-β

UPR

unfolded protein response

U.S.

United States

UV

ultraviolet

VARNA

viral-associated ribonucleic acid

viperin

virus inhibitory protein, endoplasmic reticulum-associated,
interferon-inducible

vp

viral particle(s)

VSV

vesicular stomatitis virus

wpi

week(s) post-infection

XBP1s

X-box binding protein 1s

xxii

Chapter 1: Introduction

1

1.1

Innate immunity

1.1.1 Definition and overview
In all mammalian organisms, innate immunity serves as the first-line defense against
invading pathogens. The initially encountered components of this system include basic physical
barriers by epithelial cells, constitutive expression of peptide antibiotics, and phagocytosismediated killing by neutrophils (1). This response progresses to cell-mediated promotion of
inflammatory signals and processing of microbial antigens so as to recruit downstream adaptive
responses (2,3). As opposed to adaptive immunity, elements of the innate immune system are
intrinsic to the organism’s germline DNA and are ubiquitous across all cells within that lineage
(2). While this limits the diversity of molecules that the innate immune response can detect, its
molecules mainly recognize microbially-conserved components called pathogen-associated
molecular patterns (PAMPs) (3,4). Importantly, PAMPs remain recognizable even across species
or when minor genetic variations are present. For example, retinoic acid-inducible gene-I-like
receptors (RLRs) detect viral dsRNA from many different viruses and in a manner that is
dependent on the dsRNA’s length, but not sequence (3). Human cells contain a considerable
amount of PAMP-recognizing surface, endosomal, and cytoplasmic pattern recognition receptors
(PRRs), including C-type lectin receptors (CLRs), nucleotide binding oligomerization domainlike receptors (NLRs), RLRs, and Toll-like receptors (TLRs) (2,3); the latter of which will be
detailed in the next section.
While activation of PRRs trigger a general pro-inflammatory signaling cascade, they can
also lead to unique effects depending upon the specific PRR, the cell type that is expressing it,
and the immune environment that surrounds it (5). The human cells that express PRRs are
mainly derived from a hematopoietic lineage, including monocytes, macrophages, dendritic cells

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(DCs), natural killer (NK) cells, B cells, and some T cells; however, PRRs can also be found on
non-immune cells, such as epithelial and endothelial cells (2,6). Macrophages, DCs, and a small
subset of B cells are considered professional antigen-presenting cells (APCs), meaning they are
particularly effective at internalizing microbial pathogens (typically through receptor-mediated
endocytosis or phagocytosis), processing them into small antigenic peptides, and displaying them
extracellularly on class II MHC molecules (7).
Tissue macrophages are blood monocyte-derived cells that both act as professional APCs
as well as phagocytes. While neutrophils may be the most predominant phagocytic cells in the
human body and are typically considered “first-responder” immune cells, macrophages are able
to differentiate into specialized phagocyte forms (e.g. Kupffer cells in the liver, osteoclasts in the
bone, alveolar macrophages in the lungs, microglial cells in the central nervous system (CNS)),
become activated to kill vacuolated pathogens, and present antigens to T cells (3,8).
Macrophages can also be activated by the binding of cytokines, chemokines, or PAMPs to the
appropriate PRRs (e.g. mannose receptor binding triggers phagocytosis; TLR or cytokine
receptor triggering activates inflammation, antigen presentation, and co-stimulatory molecule
expression) (8). These cells can also release their own cytokines and chemokines, which help to
alert other macrophages and innate immune cells to become activated and migrate towards the
site of infection.
The other major professional APC that humans possess are DCs. These cells possess
many of the same traits as macrophages, but their function is more specific to the effective
display of antigenic epitopes; often being seen as the “bridge” between the initial innate response
and the developing adaptive immune response (9). Immature/migratory DCs are present in many
parts of the human body, for example, in local lymph nodes, as Langerhans cells in the skin, and

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as Peyer’s patch colonic DCs in the gastrointestinal (GI) system (9–11). When activated by PRR
stimulation, DCs also express cytokine molecules like macrophages, but do not destroy engulfed
microbes. Instead, DCs quickly migrate to lymph nodes or other areas of high T cell
concentrations to initiate the required signals to form an eventual adaptive immune response
(9,12).
NK cells serve as another subset of immune cells that contribute to the innate immune
response. While recent studies have found them to have properties of adaptive immune
lymphocytes as well (13,14), the main function of NK cells are to specifically browse their
environment for cells that either lack surface class I MHC molecules or display other
danger/immune activation signals that would suggest the cell was infected or possibly
tumorigenic (15,16). When NK cells identify dysfunctional cells, they come into close contact
with them and release α-defensins, perforin, and other granzymes, thereby triggering the targeted
cell to undergo cytolytic granule-mediated apoptosis (15,16). While other lymphocytes are
slower to act and can only identify a single antigen epitope per cell, NK cells are able to quickly
kill infected or abnormal cells that may have otherwise been able to evade T and B cell
recognition due to lack of antigen presentation (17).
Phenotypically similar to NK cells and T cells, natural killer T (NKT) cells are also
contributors towards the overall innate immune schema. As the existence of these as an
independent lymphocyte group is still moderately new (18), their exact mechanisms and purpose
are not completely clear. However, it has been found that NKT cells are able to secrete large
amounts of pro-inflammatory cytokines (e.g. GM-CSF, IFNγ, IL-2, TNFα) upon activation (19).
These cells have also been found to assist in maturation of DCs when working in concert with
certain TLR agonists (20).

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1.1.2 Toll-like receptors and Toll-like receptor agonists
TLRs were named as such due to their homology with the Drosophila fly species’ Toll
protein, which was found to be an anti-microbial agent (21,22). All TLR molecules share
sequence homology in that they are composed of a cytosolic Toll/IL-1R (TIR) domain and
several lumenal or extracellular leucine-rich repeat (LRR) domains. TLRs are unique receptors
in that they can recognize both nucleic acids and proteins. For example, TLR1, TLR2, and TLR6
are activated by binding to lipopeptides, LTA, peptidoglycans, porins, mannans, and zymosan.
TLR4 is also able to recognize mannans, but is best characterized as responding to Gramnegative bacteria LPS and viral envelope proteins (6,21,23). TLR5 is more restricted, and is
mainly cited as recognizing bacterial flagellins (24). While these aforementioned TLRs are
positioned within the plasma membrane and mostly recognize protein structures; TLR3, TLR7,
TLR8, and TLR9 are embedded in endosomes and are mainly activated by foreign forms of
nucleic acids (e.g. unmethylated CpG dinucleotides, ssRNA, dsRNA) (25,26).
To transmit signals to the nucleus following ligand binding, TLRs form homodimers or,
in some cases, heterodimers to other TLR molecules (e.g. TLR2 with TLR1 or TLR6 (27,28)).
Conformational protein changes upon dimerization then allow for recruitment of one or more
cytosolic adaptor proteins. All human TLRs, with the exception of TLR3, utilize the adaptor
protein MyD88 for signal transduction (5). MyD88 works to recruit IRAK kinases, which in
turn phosphorylates TRAF6; subsequently leading to the polyubiquitination of itself and
MAP3K7. This action allows for IKK-β, then IκB, to be phosphorylated; freeing NFκB to
migrate to the nucleus and activate pro-inflammatory gene signaling (29,30).
TLR3 and TLR4 use a TRIF-dependent pathway to initiate NFκB signaling; this involves
TRIF activating RIPK1, thereby inducing polyubiquitination of itself and MAP3K7, and from

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there on, proceeding in the same manner as the MyD88-dependent signaling cascade. TRIF also
can form a complex with TBK1 which can phosphorylate IRF3 and allow it to travel to the
nucleus and induce IRF3-mediated type I IFN production and signaling (6,23). TIRAP and
TRAM are also used in conjunction with TLRs and other adaptor proteins to signal NFκB and
IRF3, as well as multiple MAPK systems (23).
1.1.3 Anti-viral innate immunity
During virus infection, innate mechanisms are triggered by many unique components of
these microbes. For example, TLR2 is able to recognize extracellular glycoproteins produced by
CMV and HSV (31,32). TLR4, another plasma membrane-bound PRR originally believed to
only recognize bacterial motifs, has also been found to recognize viral proteins from such
microbes as VSV and Ebola virus (33,34). When viruses are taken into cells via endosomal
transport, they are exposed to several endosomal TLRs (35). Endosome-bound TLR3 is able to
detect dsRNA, therefore, is able to be triggered by dsRNA from viral genomes or secondary
dsRNA-like structures (25,30). TLR7/TLR8 also contribute to endosomal virus recognition in
that they are directly activated by viral-derived ssRNA (36). Moreover, TLR9 binds to and is
activated by unmethylated CpG sequences, which are rare in typical human cell systems, but
much more common in viruses and bacterial organisms (37,38).
Cytosolic PRRs, such as RLRs, also contribute greatly to the initial immune response to
viral infection (39). RIG-I binds and reacts to viral short dsRNA and 5’ triphosphate ssRNA,
which are produced by such microbes as the influenza virus, hepatitis C virus (HCV), and
Newcastle disease virus (40,41). Alternatively, MDA5 uses long dsRNA as a ligand; this
structure is often derived from such pathogens as the West Nile virus and encephalomyocarditis
virus (EMCV) (42,43).

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Despite the plethora of anti-viral mechanisms in place, it is important to recognize that
they are not fool-proof, as many viruses have evolved to evade innate immune detection and
response (44). Human CMV protein products are able to keep MHC I from being expressed on
the cell surface so as to avoid T cell recognition (45). Similar MHC I inhibitory viral defense
phenomena have also been described with infection by HIV and adenoviruses (46,47). While NK
cells typically would identify these class I MHC-lacking cells as damaged and cause them to
undergo cytolysis, the some viruses are also able to block this action by producing class I MHC
molecule homologs to trick the NK cells into seeing the virus-infected cell as normal (48).
Viruses are also able to create cytokine receptor homologs or directly bind to and inhibit
cytokine and cytokine receptors which are important for the anti-viral response, including such
targets as TNF receptors (49,50), IFNs (51,52), and chemokine receptors (53,54).
Anti-viral innate immune responses also work sequentially to affect adaptive memory
responses in positive and/or negative ways. For example, in a HIV vaccine study, TLR3
stimulation was found to decrease cytotoxic lymphocyte (CTL) responses against the HIV
protein Gag, while application of a TLR4 agonist boosted CD8+ T cell function (55). These
innate immune responses are important to consider during the utilization of viral-based
therapeutic delivery methods (56) and will be further addressed in the subsequent sections.

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1.2

Adaptive immunity

1.2.1 T cell-based adaptive immunity
T cells represent one of the two major cells involved in the adaptive memory response.
Naïve versions of these cells are residents of the spleen and lymph nodes, where they can
frequently interact with antigenic peptides being presented on MHC molecules by APCs (57).
When combined with the expression of co-stimulatory factors, T cell receptors (TCRs) can react
to non-self antigens in a multitude of ways. Each T cell contains only one specific type of TCR;
therefore, during T cell activation, it replicates by clonal expansion to respond with greater
numbers to the specific antigen recognized (58). For CD4 receptor-expressing T helper (Th)
cells, recognition of foreign antigens presented by class II MHC molecules leads to an extensive
production of cytokines that recruit other T cells, B cells, and APCs (58). These CD4+ T cells
can also be stimulated to differentiate into different Th subtypes, allowing them to respond in a
manner that is specific to the type of immune response required to act against the pathogenic
threat (59). Alternatively, CD8-expressing CTLs identify antigens presented by class I MHC
molecules, and upon recognition of foreign antigen epitopes alongside the appropriate costimulatory signals, are activated to kill the MHC-antigen complex-bearing cell by release of
cytotoxins or Fas-Fas ligand binding-mediated apoptosis, a process known as cell-mediated
immunity (CMI) (60).
The final prominent group of T cells present in the human body are called regulatory T
cells (Tregs). These cells use similar antigen recognition techniques as Th cells and CTLs, but
function so to suppress antigenic reactivity and promote antigen immune tolerance instead (61).
Treg dysfunctions can lead to the development of autoimmune diseases as they act as a major
protectant against self-antigen immunogenicity (62). On the other hand, they have also been

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implicated in perpetuating immunological tolerance towards tumor cells due to their phenotypic
similarities with normal, healthy cells (63,64).
1.2.2 B cell-based adaptive immunity
B cells are another adaptive immune cell that possesses unique cellular receptors for
specific antigenic epitopes and can induce robust responses against identified foreign antigens
(65,66). As opposed to T cells, B cell receptors (BCRs) have the ability to recognize protein and
non-protein antigens, like those that are membrane-bound or repetitive (66,67). Following
exposure to an antigen, naïve B cells undergo clonal expansion and differentiation into effector
plasma cells, which secrete antibodies containing the identical epitope binding receptor pattern
as the cell’s original BCRs (68). Initially, B cells can perpetuate a “primary response”, during
which it produces low strength, variable IgM antibodies (67). During the “secondary response”, a
later and larger wave of antibodies is produced, including higher-affinity IgG antibodies and
sometimes specialized antibody classes (e.g. IgA, IgE) (69).
Besides microbial antibody binding, B cells can also interact with CD4+ Th cells in
lymphoid follicles and present antigens to them via class II MHC complex (70). This union
allows for Th cell activation, leading to the secretion of cytokines and surface expression of the
co-stimulatory molecule CD40L. In turn, CD40 molecules and cytokine receptors on the B cell
surface can engage CD40L and cytokine proteins, respectively, allowing them to be subsequently
activated themselves (71). Moreover, antibodies secreted from B cells can assist in NK cell
killing. Following IgG antibody binding to a surface antigen, NK cells are able to recognize their
exposed Fc regions and attach to them with their own Fcγ receptors. This antibody-dependent
cell-mediated cytotoxicity (ADCC) interaction allows for NK cells to be activated and kill
antibody-bound cells that may have evaded cytolytic killing otherwise (16,72).

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1.2.3 Effects of TLR signaling on adaptive memory response
For there to be a strong and useful adaptive memory response mounted against an
antigenic target, it is vital that a robust innate immune response be created upon initial antigen
encounter. Cellular TLR activation has been linked in multiple cell and pathogen models as
being an important promoter of pro-inflammatory cytokine expression, thereby activating other
immune cells, steering CD4+ Th cells away from an anergic state, and even reprogramming
Tregs into Th cells (73). Moreover, animals deficient in MyD88 TLR adaptor protein have been
found to have blunted Th cell differentiation abilities and absent Th cell-dependent IgG antibody
responses (74).
The functions of CD8+ T cells are also dependent upon innate immune function. In TLR2
knockout (KO) mice, memory CD8+ T cells were found to be completely absent while other
types of CD8+ T cells were also dysfunctional in that they were unable to resolve a Listeria
monocytogenes infection (75). Alternatively, TLR2 stimulation in wild-type animals was found
to promote the expression of granzymes from activated CTLs (76). Signaling through TLRs is
also required in situations where the reversal of Treg-induced CD8+ T cell tolerance towards a
specific antigen is desired (77).
NK cells have been found to be important mediators of the adaptive memory response as
well. When these cells induce cell-mediated killing of infected targets, NK cells are able to
induce CD4+ T cell activation in a MyD88- and TRIF-dependent fashion (78). NK cells also use
this pathway and IFN cytokine signaling to stimulate humoral and CD8+ T cell memory
responses, making them an important component in several facets of adaptive immunity (78,79).
Additionally, NKT-dependent activation of DCs has been shown to specifically prime these cells
for a more robust anti-antigen CD4+ and CD8+ T cell response (80,81).

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Finally, TLRs present on DCs have a vital role in determining how T cells they interact
with will differentiate and activate (82,83). TLR9 stimulation within certain DC subsets increase
their expression of pro-migratory cytokines that propel them to the lymph nodes and allow for
increased rates of T cell maturation (84). Both TLR9-deficient and MyD88-deficient mice have
been found to have virtually non-existent levels of DC proliferation and maturation, meaning
they are unable to enact any meaningful antigen presentation to T cells (36).

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1.3

Vaccine adjuvants

1.3.1 Definition and overview
Vaccines provide prophylactic and/or therapeutic protection against specific pathogens or
cell types by inducing a memory response against one or more pathogen-derived antigens that
the vaccine provides or expresses. It is common that introduction of a target antigen/pathogen
alone is not sufficient to induce protective/therapeutic immunity, therefore, vaccine adjuvants
must be added so as to boost the strength, speed, and breadth of immunologic memory response
that the host will eventually mount against the desired antigen(s) (85,86).
1.3.2 Currently utilized adjuvants in human vaccines
Vaccine adjuvants can be composed of a wide variety of substances, including salts,
proteins, oils, virosomes, and nucleic acids (87). Despite the considerably great amount of time
that has been spent studying a wide spectrum of these compounds, there are only two specific
adjuvants approved by the U.S. FDA for use in the general human population (86). The first, and
by far most popular, adjuvant licensed for use is alum, which is composed of aluminum salts
(88). Many vaccines contain some form of alum, including those for the prevention of diphtheria,
tetanus, pertussis, and hepatitis A (89). The mechanism by which alum functions is believed to
be TLR-independent, involving the NALP3 inflammasome instead to potentiate IL-1β
production, DC activation, and upregulated pathogen internalization by DC and B cells (90,91).
However, using alum as an adjuvant is not a perfect fit for all vaccine regimens as it mainly
promotes humoral and Th2-dominant responses, both adaptive pathways that favor B cell over T
cell activation (89). Alternatively, a strong T cell-mediated Th1 response would be needed to
boost therapeutic cancer vaccines, as these typically require robust CTL killing activities over
development of neutralizing antibodies to be effective (92).

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AS04 is another approved adjuvant and is made up of both monophosphoryl lipid A
(MPL) and either aluminum hydroxide or aluminum phosphate (87). It can be found both in
vaccines against human papillomavirus (HPV) and in newer versions of the hepatitis B virus
(HBV) vaccines, which have actually been shown to be more immunogenic than alum-adjuvant
HBV vaccine preparations (93–95). In comparison to alum alone, AS04 has been found to
increase both humoral and Th1 responses against co-administered antigens; this is most likely
due to MPL being a TLR4 agonist, thereby, it can substantially activate NFκB and MAPK
pathway signaling (95,96).
Technically, the influenza vaccine adjuvant AS03 (a combination of squalene, DL-αtocopherol, and polysorbate 80) could be counted as a third U.S. FDA-approved adjuvant (97).
However, due to some safety concerns, including the possibility that it may induce severe
anaphylactic reactions and acute narcoleptic symptoms upon administration, this adjuvant and
vaccine formulation are not commercially available and are only stockpiled by the U.S.
government for cases in which public health crises may validate it’s use (98,99).
1.3.3 TLR agonist adjuvants
As the TLR4 agonist-containing AS04 and other similar adjuvants have shown great
promise in the past couple decades, there has been much interest in developing other adjuvants
that trigger TLR signaling, perhaps in an even more robust manner. As established earlier, TLRs
help to bridge innate and adaptive responses in a multitude of ways, including assisting in the
maturation/activation/migration of APCs, elevating pro-inflammatory cytokine secretion,
inducing lymphocyte differentiation into more specialized memory cells, and combating antigen
tolerance signals (20,73–84,100). Besides MPL, other examples of TLR agonist adjuvants that
have been previously studied include MALP-2 (TLR2 and TLR6 agonist), poly(I:C) (TLR3

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agonist), flagellin (TLR5 agonist), imidazoquinolins (TLR7/8 agonists), and CgG ODN (TLR9
agonist) (101–106), resulting in different levels of efficacy. It should be stated that while many
of these components have the potential to activate strong anti-antigen immune responses, some
produce such an excessive amount of TLR stimulation that it may cause significant side effects.
One example of such a reaction was seen in human trials utilizing the tuberculosis vaccine and
TLR agonist, BCG, which triggered acute pneumonitis and hepatitis in some participants (107–
109). Consequently, it is important that the actions of an adjuvant be balanced precisely to allow
for beneficial immune stimulation without toxicity.

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1.4

Recombinant adenoviruses

1.4.1 Adenovirus biology and structure
Human adenoviruses (Ads) are a non-enveloped dsDNA viral species which belong to the
Mastadenovirus genus and Adenoviridae family (110). Currently, there are over 50 identified
human Ad serotypes, each belonging to one of six subgroups (A, B, C, D, E) (110). Each possess
an outer icosahedral capsid structure that measures about 90 nm in length with a weight of
approximately 150 MDa (111,112). The capsid structure includes seven proteins (II, III, IIIa, IV,
VI, VIII, and IX) and is predominantly made up of hexon and penton formations (113). Some
penton complexes are also attached to fiber homotrimers that project externally from the virus;
these serve as viral binding knobs which can attach to host cell coxsackievirus and adenovirus
receptors (CARs), thereby allowing Ad to be internalized (112,114). Internally, the Ad core is
made up of four proteins (V, VII, X, terminal 5’ DNA-linked protein) and the viral genome
(113). The Ad genome is approximately 36 kb long, which includes the early (E1a, E1b, E2a,
E2b, E3, and E4), late (L1, L2, L3, L4, and L5), and other smaller transcriptional units (IVa2,
IX, VAI, and VAII) (Figure 1) (110,115,116). Additionally, Ads also contain a major late
promoter (MLP) sequence that assists in enhancing late (as well as early) Ad gene transcription
and 100-140 bp inverted terminal repeat (ITR) elements that flank the genomic ends (110,115–
118).

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Figure 1

rAd5 genome and recombinant rAd5 platforms

The top figure represents the wild-type adenovirus serotype 5 genome. The genome
extends for approximately 36 kb and is divided into the early (E1A, E1B, E2A, E2B, E3, and E4)
and late (L1, L2, L3, L4, and L5) transcription units. pIX, IVa2, VAI, and VAII are transcribed
during this process as well. ITRs and MLP are also pictured. Below this genome schematic are
bars highlighting the areas in which different generations of rAd5 vectors are modified from the
original Ad5 genome, as indicated by Δ marked transcription units. Areas of transgene insertion
are also indicated.

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Viral replication occurs at a rapid rate; with a typical 24 hour life cycle yielding
approximately 10,000 viral particles (vp) per infected cell (116). While some human Ad species
are symptomatically benign, many are able to induce mild respiratory disease, conjunctivitis,
pharyngitis, and/or gastroenteritis (119). Occasional cases of severe Ad-induced acute respiratory
disease have also been described, although outbreaks seem to be confined in areas where living
conditions are crowded, such as in military barracks (119,120).
1.4.2 Synthesis and utilization of rAd for vaccine vectors
Recombinant adenoviruses (rAds), particularly serotype 5, are currently one of the most
studied therapeutic viral vectors and possess many attractive attributes for clinical use. For
example, as wild-type adenoviruses typically include mild cold-like symptoms and are then
processed to rAds to make them replication incompetent, these resulting vectors typically
produce only minor side effects when used as vaccine platforms (e.g. erythema at injection site)
(121). rAd5 vectors have particularly well-characterized genomes, allowing for researchers to
design transgene-expressing Ad-based vectors simply and easily. Once the rAd5 construct is
synthesized, growing the virus to a substantial amount and concentration is quick and effective,
allowing for the accumulation of a potent dosage that can easily be scaled up or down, dependent
on the desired utilization. rAds also do not integrate their own genome into that of the host cell;
effectively eliminating the risk of vector-induced mutagenesis and oncogenesis that is present
with other viral vectors (e.g. retroviruses) (122,123). rAd5 vectors can be utilized to infect both
dividing and non-dividing cells; allowing them to have a large infection tropism as they are able
to enter cells via the largely ubiquitous CAR and α-integrin binding, as well as other host cell
receptors (124–126). Moreover, rAds5 vectors possess intrinsic immunogenicity that improve

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adaptive memory responses when they are used as vaccine platforms; this characteristic will be
further discussed in the following section (127).
To date, there have been many recombinant constructs created from the Ad5 genome
backbone (Figure 1). The most prolifically used rAd5 platform is surely the first-generation rAd5
vector (Ad5[E1-]), which contains E1 and E3 deletions. The E1 transcription region encodes for
a trans-acting transcriptional regulatory factor needed for efficient transcriptional activation and
viral replication. In addition, E1 encodes for multiple proteins that can work to suppress
apoptosis, inhibit IFN signaling, and block cellular p53 signaling; allowing for virus to persist
and defer recognition (121,128). The E3 region also contains several genes which translate into
inhibitors that work against class I MHC molecule mobilization and other host anti-viral
responses, however, E3 is not required for viral replication and is mainly removed from rAds to
allow for a larger transgene insertion area (116,121). Deletion of both of these regions allows for
a total transgene insertion size of about 8 kb and can be easily grown when introduced to
HEK293 cells (115,116,129). Unfortunately, Ad5[E1-] vectors do not persist for long periods of
time in vivo and of all of the rAd5 vector options, produces the highest amount of inflammatory
side effects (130–132).
Second-generation rAd5 vectors contain E1 and E3 transcriptional unit deletions too, but
also have additional genomic areas removed, such as E2b or E4. Vectors with the additional E4
deletion (Ad5[E1-,E4-]) lack genes that promote viral gene expression and replication, as well as
lytic function signals (133). These vectors have been found to induce slightly lower levels of
inflammation, but have profound issues in maintaining transgene expression (134,135). In
contrast, second-generation, E2b-deleted vectors (Ad5[E1-,E2b-]) lack the genes that encode for
viral DNA polymerase (Pol) as well as a precursor terminal protein (PTP) region which acts as a

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primer for viral DNA replication (136,137). While no more difficult to reproduce than Ad5[E1-]
vectors (requiring instead a modified HEK-293-based cell line that also expresses the Ad5 E2b
genes in trans), Ad5[E1-,E2b-] vectors have been found to induce less toxicity and persist for
long periods of time within various tissues of immune-competent animals (116,131,138).
A “third” generation of rAd5 vector also exists which are referred to as gutted or helperdependent rAd5, as they lack any Ad-specific genes and require trans-complementation from a
first-generation Ad5 vector to propagate (139,140). As can be expected, these vectors have the
largest transgene cloning capacity possible for a rAd-based system (about 37 kb). The functional
benefits and disadvantages of using each rAd generation will be further compared in the last
section below.
1.4.3 Innate immune recognition of rAd
Using rAd5 vectors as a vaccine platform carries the added benefit of introducing
intrinsically immunogenic virus-derived components that can act as an innate immune boosting
mechanism, further enhancing adaptive transgene memory responses. rAd5 is able to trigger
activation of multiple TLRs by MyD88-dependent signaling (141); these include positively
regulating TLR2, TLR6, and TLR9, and negatively regulating TLR4 (142,143). As described
above, TLR innate triggering is very much linked to the development of strong vaccine
responses, therefore, rAd exposure stimulates these PRRs to promote increased DC maturation
(144). In addition to TLRs, our laboratory has provided evidence to suggest that rAds also signal
through RLR pathways, as the knockdown of MAVS adaptor protein results in loss of NFκB
signaling and downstream pro-inflammatory cytokine expression (145). Furthermore, rAd5
vectors are activators of the complement system (146), which, in turn, is intimately linked to the
development of antibodies against Ad5 (147).

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Most innate immunity directed towards rAd5 vectors is known to be against its outer,
exposed protein components, such as the hexon, penton, and fiber proteins (148). rAd5 nucleic
acid products have been historically considered less important in the early, inflammatory
response as UV-inactivated rAds are still able to promote production of cytokines, including IL6, IL-10, and RANTES (149,150). That being said, adenoviral DNA has been implicated in
triggering innate immune responses as well, only more predominantly through the NALP3
inflammasome pathway (151). Additionally, rAd viral-associated RNAs (VARNAs) have been
found to stimulate a later innate immune response upon intracellular expression, specifically, by
binding to and activating RIG-I, resulting in the upregulation of type I IFN production and
signaling (152,153). Moreover, VARNAs can suppress cellular RNA interference (RNAi)
machinery and act as competitive inhibitors of the dsRNA-activated protein kinase PKR, thereby
causing NFκB pathway inhibition (154–157).
While there have been a multitude of studies that have shown rAd5-induced innate
immune responses can help to promote the development of adaptive memory responses (148), it
must also be recognized that excessive early immune stimulation can lead to substantial toxicity
and clinical side effects. In one infamous case, an 18-year old man enrolled in a gene therapy
trial was intravenously (IV) administered high doses of an Ad5[E1-,E4-] vector for the treatment
of ornithine transcarbamylase (OTC) deficiency. Within 18 hours after administration, the man
developed thrombocytopenia and multi-organ failure, leading to his death four days later (132).
This response was found to be induced by a cytokine storm reaction during which his plasma IL6 and IL-10 levels were profoundly elevated (132). Since its occurrence, this misfortune has
served as a precaution to those who study the use of any viral vector and how the immune
response to them may provoke beneficial or harmful reactions (158).

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1.4.4 Pre-existing immunity against rAd vaccine vectors
Due to their multitude of benefits, rAd5 vectors are consistently ranked among the most
utilized forms of viral delivery. These vectors are also intrinsically strong immunostimulants, as
was discussed in the previous section, and therefore provide a substantial boost to the immune
response towards their transgenes. On the other hand, the immunogenicity of these vectors can
swing both ways. Epidemiologically, the majority of the human population has had exposure to
naturally-existent adenoviruses within their adolescent years of life, thus carry measurable titers
of anti-adenovirus antibodies (159–161). As with innate immunity, strong neutralizing antibodies
and anti-Ad specific T cells directed against wild-type and recombinant Ads are more exclusive
to external capsid proteins (162–164), while lower strength adaptive responses can be developed
against other adenovirus components as well (165,166). These responses are thought to be the
main reason for the Merck STEP HIV trial failure, during which the testing of this HIV vaccine
was prematurely halted due to the observation that individuals with high anti-Ad5 titers prior to
vaccine administration were more likely to contract HIV than those administered a placebo
vaccine (167,168). Consequently, this ineffectual attempt has given researchers much hesitation
towards future utilization of unmodified, first-generation rAd vectors in populations at high-risk
for HIV infection (169).
A number of methods to evade pre-existing immunity against Ad vectors have been
developed and attempted, including lower viral particle dose regimens (170,171), modification of
Ad capsid proteins (163,172), and use of alterative Ad serotypes that do not typically infect
humans (e.g. chimpanzee-endogenous Ads) (173,174). While some of these methods may help in
avoiding anti-Ad5 immune neutralization, unfortunately, they also appear to blunt the adaptive
memory response towards the encoded transgene, which is adversative to the properties of a

21

good vaccine (175–178). Another investigated technique to combat this issue has been the
inclusion of additional early Ad gene deletions within the typical Ad5[E1-] vectors. As was
mentioned above, these “later-generation” rAds have been developed as a means to reduce
responsivity to overly excessive anti-viral immune responses generated by first-generation
vectors. We and other research groups have found that the additionally-deleted rAd5 vectors
prevent “leaky” expression of Ad5-specific proteins and promote longer durations of transgene
expression compared to that which first-generation, Ad5[E1-] vectors induce (179–182). Most
importantly, later-generation rAd5 vectors, such as Ad5[E1-,E2b-], are able to produce superior
transgene-specific adaptive immunity following vaccination of Ad-immune mice, non-human
primates, and humans (181,183–186). These platforms present novel and interesting ways to
induce potent adaptive immunity against evasive pathogen-derived and TAA targets.

22

Chapter 2: Decreased vector gene expression from second-generation, E2b-deleted Ad5
vaccines paradoxically intensifies pro-inflammatory immune responses

This chapter is the edited version of a research article under review for publication; submitted
August 20th, 2014.

Authors: Quiroga D, Aldhamen YA, Godbehere S, Harding L, Amalfitano A

23

2.1

Introduction
Recombinant vaccine platforms derived from adenoviruses, particularly Ad5, are some of

the best studied and characterized of the viral vector-based vaccines. Ad5-based vaccines have
several benefits for use in humans, including broad human cell tropism, relative ease of
development, and low incidence of adverse side effects (116). Multiple studies have
demonstrated the tremendous ability of Ad5 vaccines to create robust, transgene-specific CMI
against antigens derived from pathogens such as HIV (185,187–190), malaria (191–193),
tuberculosis (194,195), as well as many tumor-associated antigens (181,184,186,196). Although
the benefits of these vaccines are numerous, there has been some hesitation towards their
practical use due to the high prevalence of pre-existing Ad5 immunity in the human population
(160,197,198). Several tactics to evade pre-existing immunity towards Ad5 have been attempted,
including alternative delivery methods (199,200), modification of viral surface proteins (163),
and use of alternative Ad serotypes (176,193,201), each with varying levels of success.
Another proposed strategy to combat this issue is to delete additional genes from the Adbased vectors. Traditional, or “first-generation” recombinant Ads are engineered to lack E1 and
E3 gene regions (Ad5[E1-]), which substantially inhibits, but does not completely eliminate,
viral replication and protein translation (182). Alternatively, second-generation recombinant Ads
have a further deletion of the E2b gene region (Ad5[E1-,E2b-]), which normally encodes for the
Ad5 Pol and PTP genes. In studies comparing these two generations of Ads, Ad5[E1-,E2b-]
vaccines have been found to promote decreased expression of viral proteins, persist longer in
vivo, and induce less viral-associated toxicity following in vivo administration (131,138,181).
Furthermore, multiple murine, non-human primate, and human studies have shown that the antiAd5 pre-existing immunity that inhibits Ad5[E1-] efficacy can be circumvented through use of

24

Ad5[E1-,E2b-] platforms, allowing for induction of a robust immune response against the
vaccine transgene target (181,183–186).
Currently, the rationale for the responsive differences between these Ad5 vectors is not
clear. For example, it has been consistently acknowledged that the large majority of immunity
developed following Ad5 virus exposure is directed against Ad5 capsid proteins (e.g. hexon)
(162,163), which are products of Ad5 late transcription units and, therefore, identical across both
Ad5[E1-] and Ad5[E1-,E2b-] vaccines. While it has been reported that some human CD8+ T
cells can recognize Ad5 E2b gene-derived epitopes, they are not as immunodominant as many
other Ad5 capsid-based epitopes (166,202). It has also been observed that Ad5[E1-] viruses
produce “leaky” expression of virus-derived proteins, while E2b-deleted vaccines do not
(180,182). Consequently, it has been hypothesized that viral protein production from Ad5[E1-]
vaccines accelerate anti-Ad5 memory responses towards the recombinant Ad-infected cells,
thereby shortening transgene expression time and decreasing therapeutic efficacy. While this
process may contribute partially to the in vivo differences between Ad5[E1-] and Ad5[E1-,E2b-]
vaccines during long term infection, there is little evidence to suggest that this is the most
influential factor responsible for their differential performances.
Another possibility to consider is that the two Ad vector generations may produce
divergent inductions of the innate immune response. Previous microarray studies have shown
that Ad5[E1-] infection instigates a unique hepatocellular gene expression pattern as compared to
fully-deleted Ad5 vaccines, which lack any viral genome-derived gene expression. Interestingly,
the differences in immune-related gene expression peaked at six hours post-infection (hpi) and
were greatly diminished by 72 hpi, suggesting that vaccine differences may be most profound
during early innate stages of viral recognition (203). Acknowledging that additional viral gene

25

deletions within recombinant Ad5 vaccines can change the initial immune reactions towards
them, we wished to compare the early immune responses that Ad5[E1-] and Ad5[E1-,E2b-]
infection could induce. In this investigation, we initially examined previously gathered
microarray data to compare murine liver gene expression following Ad5[E1-] or Ad5[E1-,E2b-]
administration to delineate functional transcriptome differences. Additionally, we measured early
amounts of cytokine secretion from multiple, independent samples of human peripheral blood
mononuclear cells (hPBMCs) following Ad5[E1-] or Ad5[E1-,E2b-] infection and tested if such
responses were independent of previous anti-Ad5 immunity. Finally, hPBMC expression of viral
and innate immune genes was quantified following Ad5[E1-] or Ad[E1-,E2b-] treatment. Our
studies revealed there to be significant differences between the innate responses to Ad5[E1-] and
Ad5[E1-,E2b-] vector treatment both within in vivo murine and in vitro human studies.
Furthermore, these findings suggest that the improved therapeutic value of Ad5[E1-,E2b-] over
first-generation rAd5 vectors may be, in part, due to the alternative biological manners by which
they modulate the innate immune response.

26

2.2

Methods

2.2.1 Microarray analysis
Liver RNA microarray data from mice injected with Ad5[E1-] or Ad5[E1,E2b-] vectors
was previously collected and preliminary findings were published (141). This data was submitted
to NCBI’s Gene Omnibus Express as accession number GSE3739. Data was normalized using
Genespring 6.2 software using Lowness normalization, with microarray values below 0.01 set to
0.01, as previously described (141). Novel analysis of this data was conducted using Expression
Analysis Systematic Explorer (EASE v2.0) using developer’s standard protocols (204) with all
gene ontology (GO) groups listed representing significant differences (p<0.05 with one-way
ANOVA using a Benjamini-Hochberg false discover rate multiple test correction (BH FDR
MTC)) between Ad5[E1-] and Ad5[E1-,E2b-] injected mice at a set time-point post-injection.
Microarray data was also analyzed using QIAGEN’s Ingenuity Pathway Analysis software
(IPA®, QIAGEN Redwood City, www.qiagen.com/ingenuity). Both EASE and IPA analysis
used a variant of a one-tailed Fisher’s exact test, also called an “EASE score”, at a threshold of
p<0.05 to denote significance between groups.
2.2.2 Recombinant adenovirus vector construction
Transgene-lacking recombinant Ad5 vectors Ad5[E1-] (205) and Ad5[E1-,E2b-] (182)
were built and propagated as previously described, using a pAdEasy-based system
(182,205,206). Viral particle titers were determined by spectrophotometry. Ad5 gene region
deletions were confirmed by PCR, as previously described (182). HD-Ad5 (FDAdhGAA) (207)
was kindly provided by Dr. Philip Ng (Baylor College of Medicine). All viral vectors were tested
and validated as having <0.01 EU (per injection dose) bacterial endotoxin contamination, as
previously described (208).

27

2.2.3 Cell isolation, culture, and adenovirus infection
Sera and hPBMCs were obtained from de-identified blood samples (Stanford Blood
Bank, Palo Alto, CA) using Ficoll-Paque PLUS gradient (GE Healthcare Life Sciences,
Piscataway, NJ), as described in manufacturer’s protocol. In experiments where sera was not
required, de-identified buffy coats were used as a source of hPBMCs (Stanford Blood Bank) and
were isolated in the same manner. hPBMCs were plated at 5x106 cells/well in 6-well plates and
incubated in RPMI media supplemented with 2% fetal bovine serum (FBS), 1x PSF, 5 ng/mL IL12, and 10 ng/mL IL-18. HEK293 cells were seeded at 3.5x105 cells/well in 6-well plates in
DMEM media supplemented with 10% FBS and 1x PSF. Ad5 vectors were administered in a
volume of 50μL/well phosphate buffer saline (PBS), with mock treatment being PBS alone.
2.2.4 ELISA analysis
Anti-Ad5 ELISAs were performed on sera as previously described (147). Briefly, 5x108
vp/well Ad5[E1-] was plated in a high-binding 96-well flat-bottom plate and incubated overnight
at 4⁰C. Plates were rinsed with washing buffer (PBS containing 0.05% Tween) and incubated
with blocking buffer (PBS containing 3% bovine serum albumin) for an hour at room
temperature. Sera was diluted in PBS (1:200), plated, and incubated at room temperature for an
hour. Wells were rinsed with washing buffer, coated with a horseradish peroxidase (HRP)
conjugated rabbit anti-mouse antibody (Bio-Rad, Hercules, CA), and developed with
tetramethylbenzidine (TMB) (Sigma-Aldrich, St. Louis, MO). The development reaction was
halted by adding 1N phosphoric acid to wells. Plates were analyzed using an automatic
microplate reader at 450nm absorbance.
Cell media was collected and used to perform human IL-1β, IL-6, and TNFα ELISAs, as
per manufacturer’s protocol (BD Biosciences, San Diego, CA). The protocol was basically

28

identical to that of the anti-Ad5 ELISA, with the exception that the plates were initially coated
with an anti-IL-1β, anti-IL-6, or anti-TNFα capture antibody overnight and that the HRPconjugated antibodies used were also specific to the cytokine being measured. Sample
concentrations of each cytokine were determined by normalization to a recombinant human IL1β, IL-6, or TNFα dose curve developed concurrently with experimental samples.
2.2.5 Cell staining and flow cytometry
Fluorescent intracellular staining (ICS) was performed as described previously (189).
Briefly, 1.5x106 hPBMCs were stimulated with 1x1010 vp UV-inactivated Ad5[E1-] for 30
minutes at 37⁰C. Cells were stained with Alexa Fluor488-CD3, Alexa Fluor700-CD8a, and
CD16/32 Fc-block antibodies (BD Biosciences), fixed using 2% formaldehyde (Polysciences,
Warrington, PA), permeabilized with 0.2% saponin (Sigma-Aldrich), and stained with PE-IFNγ
(BD Biosciences) and violet fluorescent reactive dye for dead cell exclusion (Invitrogen,
Carlsbad, CA). Fluorescence-activated cell sorting (FACS) buffer (PBS containing 2% FBS and
sodium azide) was used to wash and resuspend cells between and after each treatment. Cell
analysis was performed using an LSRII flow cytometer (BD Biosciences) with FlowJo software
(Tree Star, San Carlos, CA).
2.2.6 RNA extraction, cDNA synthesis, and quantitative RT-PCR
Cellular RNA and DNA was extracted using TRIzol reagent (Life Technologies, Grand
Island, NY), as detailed in manufacturer’s manual. cDNA was synthesized by reverse
transcription using SuperScript III First-Strand Synthesis SuperMix (Life Technologies) as per
manufacturer’s instructions. Quantitative RT-PCR was performed and analyzed using SYBR
Green PCR Mastermix (Life Technologies) on an ABI 7900HT Fast Real-Time PCR System
(Life Technologies) as previously described (189,209). Primers used to detect expression of viral

29

and

human

genes

were

designed

using

the

online

PrimerBank

database

(http://pga.mgh.harvard.edu/primerbank) (Table 1). To measure relative gene expression,
GAPDH and the comparative Ct method were used for all samples. Induction of gene expression
was calculated as the relative change from the level of mock-treated cell transcripts to the level
of rAd-treated cell transcripts.

30

Table 1

Quantitative RT-PCR primers for rAd5[E1-,E2b-] studies

Primers were designed using PrimerBank online software. Primer sequences are written 5’ to 3’.

31

2.2.7 Statistical analysis
The associations between cytokine production and anti-Ad5 IgG titers or anti-Ad5 CD8+
T cells were tested with the Pearson correlation coefficient. Statistical significance of all other
data was determined using one-way ANOVAs with Newman-Keuls post-hoc corrections, unless
otherwise stated (e.g. microarray data). Graphs in this chapter are presented as mean ± standard
error. Statistical analyses were performed using GraphPad Prism (GraphPad Software, La Jolla,
CA).

32

2.3

Results

2.3.1 Hepatocyte microarray analysis following first- or second-generation rAd infection
Our group has previously published microarray studies examining murine hepatocyte
rAd5 infection-induced transcriptome modifications, specifically, those observed when utilizing
different generations of rAd vectors, analyzing several post-infection RNA collection timepoints, and utilizing C57BL/6-derived mouse strains (141). Briefly, adult C57BL/6 mice were IV
injected through the retro-orbital sinus with 200μL PBS as a mock treatment, or a 200μL PBS
suspension containing 1.5x1011 vp Ad5[E1-] or Ad5[E1-,E2b-]. Upon initial analysis, our results
found the greatest divergence in rAd infection-triggered hepatocyte gene expression during early
post-infection time-points (141). We observed that in vivo murine Ad5[E1-] infection
significantly induced multiple gene groups to a greater extent than mock-treated animals at the 6
hpi time-point, including groups for innate immune signaling, RNA regulatory mechanisms, and
apoptosis-related pathways. As compared to mock-treated animals, these same gene groups that
Ad5[E1-] injection altered the expression of were also the same groups significantly induced by
Ad5[E1-,E2b-]-treated mice (141).
To determine which biological functions and/or diseases may be triggered by murine
Ad5[E1-] or Ad5[E1-,E2b-] infection at a later time point, we analyzed the 3 days post-infection
(dpi) time-point hepatocyte microarray data using IPA software, with mock-treated mouse data
serving as the comparative baseline. Analysis revealed there to be many processes significantly
activated by rAd5 infection, including many cellular biological functions (e.g. growth,
proliferation, death, survival), immune cell trafficking, inflammation, humoral immunity, and
cell-to-cell signaling (Figure 2). Also, the significant processes identified were very similar
between Ad5[E1-]- and Ad5[E1-,E2b-]-injected mice, with there being only three out of fifteen

33

groups that Ad5[E1-], but not Ad5[E1,E2b-], administration triggered significantly over mock
treatment (lymphoid tissue structure and development, hematopoiesis, and cell signaling). It
should also be noted that the groups most significantly associated with Ad5[E1-] infection over
mock treatment were the same as when Ad5[E1-,E2b-] and mock gene groups were compared.

34

Figure 2

Functional analysis of murine hepatocytes following in vivo Ad5[E1-] and Ad5[E1-,E2b-] infection

35

Figure 2 (cont’d)

36

Figure 2 (cont’d)

37

Figure 2 (cont’d)
Previously gathered microarray data comparing mock-infected, Ad5[E1-]-infected, and
Ad5[E1-,E2b-]-infected murine hepatocyte RNA was used for further analysis (GSE3739) (141).
Biological functions induced by rAd5 infection as compared to mock infection were determined
using Ingenuity Pathway Analysis software, with murine gene groups supplied by the included
Knowledge Base database. Functional categories significantly upregulated by rAd5 treatment are
listed on the y-axis. Significantly upregulated gene groups were determined by a variant righttailed Fischer’s exact test, as displayed on the x-axis as the negative log of the resulting p-value.
The cutoff for significance is displayed as the dashed vertical line (p<0.05). Functional
categories are listed most to least significant, according to Ad5[E1-] values.

38

While we did observe gene expression differences between Ad5[E1-] and Ad5[E1-,E2b-]
treated samples, they remained ~96% homologous at 6 hpi and only became more homologous at
the 3 dpi and 3 weeks post-injection (wpi) time points. To evaluate if these gene expression
differences were not simply arbitrary findings, we normalized and analyzed this microarray data
(GSE3739) by using EASE software to determine if these gene expression differences between
Ad5[E1-] and Ad5[E1-,E2b-] treated mice were significantly clustered in recognized ontological
categories. We found there to be many significant gene ontological differences between Ad5[E1]- and Ad5[E1-,E2b-]-infected mouse hepatocytes at 6 hpi and 3 dpi (22 and 20 groups,
respectively), but no GO group differences at 3 wpi (Table 2).

39

Table 2

Ontological categorization of genes differentially and significantly expressed following in vivo Ad5[E1-] or

Ad5[E1-,E2b-] infection

40

Table 2 (cont’d)

41

Table 2 (cont’d)

42

Table 2 (cont’d)

43

Table 2 (cont’d)

44

Table 2 (cont’d)

45

Table 2 (cont’d)

46

Table 2 (cont’d)
Previously gathered microarray data comparing Ad5[E1-]- and Ad5[E1-,E2b-]-infected
murine hepatocyte RNA was used for further analysis (GSE3739) (141). Significantly different
GO groups were determined by a p<0.05 using one-way ANOVAs with a BH FDR MTC
utilizing EASE software.

47

At 6 hpi, the GO groups most upregulated in murine hepatocytes following Ad5[E1-]
infection, as compared to Ad5[E1-,E2b-] infection, were the immune and defense response
groups. Interestingly, several of these individual genes are also important regulators of IFNinducible responses (e.g. CXCL10, IRF2, GBP2). Additionally, Ad5[E1-] infection significantly
upregulated genes in GO groups involved with cell growth/maintenance, guanine-based
nucleotide/nucleoside interactions, exonuclease activity, and catalase activity. Upregulated GO
groups in the 6 hpi Ad5[E1-,E2b-]-treated samples as compared to the Ad5[E1-,E2b-]-treated
samples include protein modification and adenine-based nucleotide/nucleoside interaction.
Interestingly, all GO groups significantly promoted at 6 hpi by Ad5[E1-] infection over
Ad5[E1-,E2b-] were not found to be significantly upregulated at 3 dpi; with the majority of
upregulated GO groups conversely being related to cell death/apoptosis. GO groups upregulated
by Ad5[E1-,E2b-] infection over Ad5[E1-] infection were more conserved, with nucleotide
binding, phosphorylation, ATP binding, and adenyl nucleotide binding all being significantly
greater at both 6 hpi and 3 dpi time points. Moreover, GO groups for phosphate/phosphorus
metabolism, phosphorylation, and protein metabolism were also significantly upregulated by
Ad5[E1-,E2b-] over Ad5[E1-] treated murine hepatocytes. These multifactorial analyses signify
that differences between Ad5[E1-] and Ad5[E1-,E2b-] infection-induced gene expression appear
to occur early after infection, with Ad5[E1-] infection over-expressed GO groups being
substantially different from 6 hpi to 3 dpi.
2.3.2 Ad5[E1-,E2b-] vectors induce an increased pro-inflammatory cytokine response
upon hPBMC infection
Next, we wished to examine the early functional differences between Ad5[E1-] and
Ad5[E1-,E2b-] infection. As some of the microarray findings pointed towards altered induction

48

of innate immune functions by cells exposed to the two different rAd5 vectors, we decided to test
if exposure to Ad5[E1-] or Ad5[E1-,E2b-] vectors may induce altered levels of early innate
immune cytokine secretion in humans. To allow for a more individualized and clinically relevant
model, we obtained and utilized 17 unique, de-identified human blood samples. Upon receiving
the samples, hPBMCs were isolated via Ficoll-Paque gradient, plated, and mock infected or
infected with Ad5[E1-] or Ad5[E1-,E2b-] vectors. At 72 hpi, media was collected and used for
ELISA measurement of IL-1β, TNFα, and IL-6. These particular pro-inflammatory cytokines
were selected for quantification due to their significant production by hPBMCs following Ad
infection and association with improved antigen-specific T cell expansion (150,210).
Interestingly, mean statistical comparison of all samples revealed that Ad5[E1-,E2b-] exposure
induced a greater amount of IL-1β (p<0.05) and TNFα (p<0.001) secretion than Ad5[E1-]
treatment of the hPBMCs (Figure 3A). Furthermore, Ad5[E1-] treatment of hPBMCs did not
appear to induce significantly higher levels of IL-1β or TNFα than mock-treated cells.
Individually, the majority of hPBMC samples produced significantly higher IL-1β and TNFα
levels when treated with Ad5[E1-,E2b-] as compared to Ad5[E1-], and none of the samples
produced greater cytokine induction with Ad5[E1-] over Ad5[E1-,E2b-] infection (Table 3).
There was no observed difference between Ad5[E1-]- and Ad5[E1-,E2b-]-induced secretion of
IL-6 from hPBMCs, however, both triggered higher levels of IL-6 production than mock
infection. Overall, these findings suggest that Ad5[E1-,E2b] infection drives a stronger proinflammatory response than Ad5[E1-], though both viruses can provoke significant hPBMC
cytokine induction.

49

Figure 3

Ad5[E1-,E2b-] infection induces increased hPBMC pro-inflammatory cytokine secretion

50

Figure 3 (cont’d)
hPBMCs and sera were isolated from 17 human blood samples by Ficoll-Paque PLUS
gradient separation. Cells were plated at 5x106 cells/well in 6-well plates with RPMI media
supplemented with 2% FBS, 1x PSF, 5 ng/mL IL-12, and 10 ng/mL IL-18 and either mock
infected, or infected with 10,000 vp/cell Ad5[E1-] or Ad5[E1-,E2b-]. (A) At 72 hpi, cell media
was collected and used to perform human IL-1β, TNFα, and IL-6 ELISAs to measure the amount
of hPBMC cytokine secretion. Bars denote mean ± standard error. *, ** denote significant
differences between that group and mock-treated samples (p<0.05, p<0.01 respectively). #, ###
denote significant differences between Ad treatments (p<0.05, p<0.001 respectively). (B) Sera
samples were used to measure pre-existing anti-Ad5 IgG by ELISA. The obtained (450nm) OD
values were plotted against respective cytokine concentration values produced when hPBMCs
from the same blood sample were infected with Ad5[E1-]. Correlation analysis between
variables was performed by Pearson correlation coefficient test. (C) 1.5x106 hPBMCs per sample
were stimulated with UV-inactivated Ad5[E1-]. Total percentages of IFNγ-producing CD3+,
CD8+ hPBMCs were determined by ICS and flow cytometry analysis. The obtained percentages
were plotted against respective cytokine concentrations produced when hPBMCs from the same
blood sample were infected with Ad5[E1-]. Correlation analysis between variables was
performed by Pearson correlation coefficient test.

51

Table 3

Individual hPBMC sample cytokine inductions

52

Table 3 (cont’d)

53

Table 3 (cont’d)

54

Table 3 (cont’d)
hPBMCs were isolated from 17 human blood samples by Ficoll-Paque PLUS gradient
separation. Cells were plated at 5x106 cells/well in 6-well plates in RPMI media supplemented
with 2% FBS, 1x PSF, 5 ng/mL IL-12, and 10 ng/mL IL-18 and either mock infected, or infected
with 10,000 vp/cell Ad5[E1-] or Ad5[E1-,E2b-]. For each sample, each treatment was repeated
in triplicates. At 72 hpi, cell media was collected and used to perform human IL-1β, TNFα, and
IL-6 ELISAs to measure the amount of hPBMC cytokine secretion. Values represent mean ±
standard error. *, **, *** denote significant differences between that group and mock-treated
samples (p<0.05, p<0.01, p<0.001 respectively). †, ††, ††† denote significant differences
between Ad treatments (p<0.05, p<0.01, p<0.001 respectively).

55

2.3.3 Ad5-induced pro-inflammatory cytokine responses are not correlated to pre-existing
Ad5 immunity in human blood samples
One of the biggest apprehensions to Ad5 vaccine use has been the concern over naturallyoccurring, pre-existing Ad5 immunity in the general human population. Previous studies have
shown that the presence of anti-Ad5 IgG antibodies or CMI can prevent development of
transgene immunity following vaccination with Ad5[E1-] transgene-expressing vectors (165),
yet this effect does not seem to be problematic during the use of Ad5[E1-,E2b-] vaccines
(181,184–186,190,196).
To investigate if Ad5[E1-] or Ad5[E1-,E2b-] infection-induced cytokine expression
correlated to pre-existing anti-Ad5 IgG antibody levels, serum was collected from the previously
specified human blood samples prior to hPBMC isolation. Anti-Ad5 IgG ELISA was performed
and obtained values were plotted against the same subject’s hPBMC IL-1β, TNFα, and IL-6
secreted cytokine levels following Ad5[E1-] or Ad5[E1-,E2b-] infection. Correlation analysis
revealed no association between pre-existing anti-Ad5 IgG levels and IL-1β, TNFα, or IL-6
secretion amounts, either with Ad5[E1-] (Figure 3B) or Ad5[E1-,E2b-] (Figure 4A) treatment.

56

Figure 4

Quantity of Ad5[E1-,E2b-]-induced hPBMC pro-inflammatory cytokine secretion is not correlated to pre-

existing anti-Ad5 immunity

57

Figure 4 (cont’d)
hPBMCs and sera were isolated from 17 human blood samples by Ficoll-Paque PLUS
gradient separation. (A) Sera samples were used to measure pre-existing anti-Ad5 IgG by
ELISA. The obtained (450nm) OD values were plotted against respective cytokine concentration
values produced when hPBMCs from the same blood sample were infected with Ad5[E1-,E2b-],
as seen in Figure 3. Correlation analysis between variables was performed by Pearson correlation
coefficient test. (B) 1.5x106 hPBMCs per sample were stimulated with UV-inactivated Ad5[E1-].
Total percentages of IFNγ-producing CD3+, CD8+ hPBMCs were determined by ICS and flow
cytometry analysis. The obtained percentages were plotted against respective cytokine
concentrations produced when hPBMCs from the same blood sample were infected with
Ad5[E1-,E2b-], as seen in Figure 3. Correlation analysis between variables was performed by
Pearson correlation coefficient test.

58

Additionally, we wished to examine if pre-existing anti-Ad5 CMI could be correlated to
Ad5[E1-] or Ad5[E1-,E2b-]-induced cytokine production, as CD8+ T lymphocytes have also
been found to be an integral part of anti-Ad5 immunity (165). To do this, hPBMCs were
stimulated with UV-inactivated Ad5[E1-] and analyzed by flow cytometry for quantification of
IFNγ-expressing CD3+, CD8+ T cells, as previously described (189). CD3+, CD8+ cells which
expressed intracellular IFNγ were considered anti-Ad5-specific CD8+ T cells and the percent of
these cells were plotted against the samples’ respective IL-1β, TNFα, and IL-6 cytokine
concentration amounts. Similar to the humoral response, correlation analysis revealed no
association between percent of anti-Ad5-specific CD8+ T cells and any of the measured cytokine
secretion amounts induced by Ad5[E1-] (Figure 3C) or Ad5[E1-,E2b-] (Figure 4B) infection.
Several studies have shown that in instances where there are high levels of anti-Ad5 preexisting immunity, Ad5[E1-,E2b-] vaccines are able to induce much greater transgene-specific
immunity than Ad5[E1-] vaccines (181,190,196). Consequently, we considered the possibility
that the difference in Ad5[E1-,E2b-] over Ad5[E1-] vector pro-inflammatory cytokine induction
may be correlated with the level of pre-existing anti-Ad5 antibodies and/or T cells. To examine
these relationships, correlation analyses were completed as mentioned above, with the exception
that the obtained values for anti-Ad5 immunity were plotted against a ratio of each subject’s
Ad5[E1-,E2b-] to Ad5[E1-]-induced cytokine secretion. These analyses revealed that amounts of
neither pre-existing anti-Ad5 IgG antibodies (Figure 5A) nor anti-Ad5 CD8+ T cells (Figure 5B)
were correlated to cytokine expression ratios. Overall, these results suggest that while proinflammatory cytokine induction differs between Ad5[E1-] and Ad5[E1-,E2b-] vectors, this
response seems to occur independent of pre-existing anti-Ad5 humoral or cellular immunity.

59

Figure 5

Ratio of Ad5[E1-,E2b-] to Ad5[E1-] induced cytokine production is not correlated to pre-existing

anti-Ad5 immunity

60

Figure 5 (cont’d)
Using data described in Figure 3, ratios of cytokine secretion from Ad5[E1-,E2b-]-treated
to Ad5[E1-]-treated hPBMCs derived from the same blood sample were calculated. Previously
obtained pre-existing anti-Ad5 IgG OD values (A) and percentages of Ad5-specific CD8+ T
cells (B) were plotted against these respective ratios produced from the same blood sample.
Correlation analysis between variables was performed by Pearson correlation coefficient test.

61

2.3.4 Ad5[E1-,E2b-] infection produces dampened Ad gene expression
Next, we wished to determine if lack of E2b gene function was the specific factor causing
Ad5-induced cytokine production differences between Ad5[E1-] and Ad5[E1-,E2b-] vectors. To
do this, we infected HEK293 cells with equivalent doses of Ad5[E1-], Ad5[E1-,E2b-], or HDAd5 (207) (a helper-dependent adenovirus; gutted for all viral genes) vectors. HEK293 cells
constitutively produce the Ad5 E1 protein (129), allowing for Ad5[E1-], but not Ad5[E1,E2b-]
or HD-Ad5, vectors to be replication-competent. Subsequently, we found that HEK293 cells
expressed significantly greater amounts of E4, VAI, VAII, and hexon RNA when infected with
Ad5[E1-] as compared to Ad5[E1-,E2b-] (p<0.001) (Figure 6A). These differences were so
robust that they statistically rendered Ad5[E1-,E2b-] viral gene transcript levels not different
from mock or HD-Ad5 infected cells, with the exception of early gene E4 (p<0.001). Neither
mock nor HD-Ad5 showed any notable Ad gene expression within HEK293 cells.

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Figure 6

Ad5[E1-,E2b-] infection produces dampened Ad gene expression

63

Figure 6 (cont’d)

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Figure 6 (cont’d)
(A) HEK293 cells were plated at 3.5x106 cells/well in 6-well plates with DMEM media
supplemented with 10% FBS and 1x PSF and either mock infected, or infected with 200 vp/cell
Ad5[E1-], Ad5[E1-,E2b-], or HD-Ad5. RNA was collected at 24 hpi for RT-PCR quantification
of Ad gene expression. (B) hPBMCs were plated at 5x106 cells/well in 6-well plates with RPMI
media supplemented with 2% FBS, 1x PSF, 5 ng/mL IL-12, and 10 ng/mL IL-18 and either
mock infected or infected with 10,000 vp/cell Ad5[E1-], Ad5[E1-,E2b-], or HD-Ad5. RNA was
collected at 6 hpi for RT-PCR quantification of Ad gene expression. Bars denote mean ±
standard error. *, **, *** denote significant differences between that group and mock-treated
samples (p<0.05, p<0.01, p<0.001, respectively). #, ##, ### denote significant differences
between Ad treatments (p<0.05, p<0.01, p<0.001, respectively).

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To determine if these viral gene expression differences would also be seen following
infection of hPBMCs (which do not express the Ad5 E1 gene), these cells were plated and mock
infected or infected with equivalent doses of Ad5[E1-], Ad5[E1-,E2b-], or HD-Ad. RNA
collected from these samples revealed that hPBMC Ad5[E1-,E2b-] infection induced less E4
(p<0.001), hexon (p<0.01), VAI (p<0.01), and VAII (p<0.05) gene transcription than Ad5[E1-]
treatment (Figure 6B). Again, the amount of gene expression induced by Ad5[E1-] vectors
statistically skewed the analysis, resulting in expression levels from Ad5[E1-,E2b-]-treated
hPBMCs to appear no different than the control-treated hPBMCs; with the exception of VAI
(p<0.05 for mock, p<0.01 for HD-Ad5). Mock and HD-Ad5 infected hPBMCs yielded no
expression of any Ad-specific genes in comparison to Ad5[E1-] and Ad5[E1-,E2b-]-infected
samples. These dissimilarities in Ad5 gene expression are in agreement with past studies which
show that Ad5[E1-,E2b-] infection produces substantially less “leaky” Ad5 protein expression
than Ad5[E1-] vectors (180,182), suggesting that regulation of this expression likely occurs at
the transcriptional level.
To further verify that these Ad gene expression variations were not due to unequal
amounts of Ad5 viral particles being introduced and/or entering the hPBMCs, sample DNA and
RNA were collected simultaneously and relative viral genome quantification was conducted by
quantitative PCR measurement of Ad5 hexon gene DNA, as described previously (209).
Comparison of viral DNA from Ad5[E1-] and Ad5[E1-,E2b-]-treated cells revealed no
differences in the amount of viral genomes present in either group (Figure 7).

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Figure 7

Ad5[E1-] and Ad5[E1-,E2b-] viral genome quantification following human

PBMC infection
hPBMCs were plated at 5x106 cells/well in 6-well plates with RPMI media supplemented
with 2% FBS, 1x PSF, 5 ng/mL IL-12, and 10 ng/mL IL-18 and either mock infected or infected
with 10,000 vp/cell Ad5[E1-] or Ad5[E1-,E2b-]. At 6 hpi, DNA was collected simultaneously
and from the same samples as RNA using TRIzol gradient separation. DNA was used to detect
the presence of Ad5 genomes using quantitative RT-PCR with Ad5 hexon primers.

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2.3.5 Ad5[E1-] and Ad5[E1-,E2b-] vectors induce distinct innate immune gene expression
profiles
To examine the induction of human immunity-related genes by different Ad5 vector
platforms, hPBMCs were either mock infected, or infected with Ad5[E1-], Ad5[E1-,E2b-], or
HD-Ad5 vectors at equivalent doses. RNA was isolated from infected hPBMC samples and used
to measure expression of early innate immune response genes. Interestingly, exposure to the
Ad5[E1-,E2b-] vector induced significantly more IFIT1 and IL-12β gene expression than the
Ad5[E1-] vector (p<0.001, p<0.01 respectively) (Figure 8). IFIT1 and IL-12β expression
triggered by Ad5[E1-,E2b-] infection was also significantly greater than that triggered by HDAd5 (p<0.05, p<0.001 respectively) or mock (p<0.001) infection. Conversely, Ad5[E1-] did not
induce significantly higher amounts of IFIT1 or IL-12β gene expression than the other treatment
groups; actually inducing statistically lower quantities of IFIT1 than the HD-Ad5 control vector
(p<0.01). Infection of hPBMCs with Ad5[E1-,E2b-] also promoted greater RIG-I gene
expression than noted in mock-infected cells (p<0.05), although no other differences between
treatment groups were found to be statistically significant. Alternatively, cells infected with
Ad5[E1-] and HD-Ad5 did produce significantly higher levels of IFNβ gene expression than
mock (p<0.01, p<0.05 respectively) and, while not statistically notable, averaged greater
amounts of IFNβ expression than cells treated with the Ad5[E1-,E2b-] vector.

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Figure 8

Ad5 vectors promote distinct innate immune gene expression patterns

dependent on vector generation
hPBMCs were plated at 5x106 cells/well in 6-well plates with RPMI media supplemented
with 2% FBS, 1x PSF, 5 ng/mL IL-12, and 10 ng/mL IL-18 and either mock infected or infected
with 10,000 vp/cell Ad5[E1-], Ad5[E1-,E2b-], or HD-Ad5. RNA was collected at 6 hpi for RTPCR quantification of Ad gene expression. Bars denote mean ± standard error. *, **, *** denote
significant differences between that group and mock-treated samples (p<0.05, p<0.01, p<0.001
respectively). #, ##, ### denote significant differences between Ad treatments (p<0.05, p<0.01,
p<0.001 respectively).

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2.4

Discussion
Recombinant adenovirus vectors are promising, highly characterized platforms on which

to create vaccines. First-generation rAd5 vectors possess the ability to promote strong
immunologic responses against their expressed transgenes, but these same properties also trigger
host anti-viral responses which can lead to increased toxicity, limited persistence, and decreased
efficacy in the face of pre-existing anti-Ad immunity (131,132,138,167,180). Alternatively,
second-generation rAds, possessing additional viral gene deletions, have been found to negate
these detrimental effects. Back-to-back comparisons of traditional Ad5[E1-] vectors to E2bdeleted, Ad5[E1,E2b-] vectors have shown that the latter produces virtually no hepatotoxicity
after IV administration (138), persists and expresses transgenes for longer durations than
Ad5[E1-] vectors (131,180), and remains efficacious in hosts with substantial pre-existing antiAd5 immunity (181,183–186). Up until know, it has been largely assumed that the rationale for
these rAd5 differences is that Ad5[E1-,E2b-] vectors do not produce substantial amounts of viral
proteins upon infection, thereby more adeptly evading host anti-viral responses (180,182). While
this may serve as a contributor towards these divergent responses, multiple rAd5 studies have
shown that anti-Ad5 immunity alone is not predictive of a rAd5-based vaccine’s efficacy
(186,194,211).
To investigate what other biological mechanisms may be causing the split in Ad5[E1-]
versus Ad5[E1-,E2b-] responses, we analyzed our group’s previously gathered and published
hepatocyte RNA microarray data of mice that were injected with either Ad5[E1-] or Ad5[E1,E2b-] vectors. Our previously published manuscript revealed that the most hepatocyte
transcriptome changes between mock and rAd5-treated mice occurred at the earliest time-point
studied (6 hpi), so at that time we focused on the ontological differences that occurred between

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these specific treatment groups (141). In our current studies, we analyzed the gene ontology
groups that were expressed at a higher level at 3 dpi by Ad5[E1-] and Ad5[E1-,E2b-] injection as
compared to mock. We found that several gene groups were expressed differentially, and that
essentially all of the groups significantly overexpressed by Ad5[E1-]-injected mice were also
overexpressed by mice administered Ad5[E1-,E2b-], when compared to mock-treated animals.
However, when comparing the rAd5 groups head-to-head, we were still able to identify notable
ontological differences, particularly at 6 hpi. While Ad5[E1-] administration seemed to promote
a more global response at the 6 hpi time-point, these effects appeared to burn out quickly, so that
the majority of overexpressed groups were absent at 3 dpi, as compared to Ad5[E1-,E2b-]
injection. Instead, 3 dpi hepatocyte samples revealed that Ad5[E1-] treatment caused
overexpression of

gene groups focused on cell death/apoptosis responses, as compared to

Ad5[E1-,E2b-] vectors. These results are experimentally consistent with past findings that
Ad5[E1-] vectors induce more liver toxicity and inflammation than Ad5[E1-,E2b-] vectors (138).
In contrast, several GO groups significantly upregulated by Ad5[E1-,E2b-] over Ad5[E1-]
infection were conserved at both 6 hpi and 3 dpi time-points, which may be due to Ad5[E1-,E2b] vectors’ ability to persist beyond that which is seen with Ad5[E1-] vectors (131,180).
While these microarray findings confirmed that there are substantial gene expression
differences that Ad5[E1-] and Ad5[E1-,E2b-] promote, we understood these findings alone were
not enough to confirm how these vaccine platforms may perform divergently in clinical models.
Thus, the experimental model we chose to functionally compare Ad5[E1-] and Ad5[E1-,E2b-]
effects were human PBMCs. As we chose to harvest the hPBMCs from multiple human blood
samples, this not only improved the statistical power of our findings, but also allowed for a more
diverse population to be tested.

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Gene expression analysis of hPBMCs following rAd5 treatment lead us to find that
Ad5[E1-,E2b-] infection promoted induction of genes that are strongly tied with Th1 and NFκB
pathway activation, while Ad5[E1-] triggered higher amounts of type I interferon signaling,
which may be a reason for Ad5[E1-,E2b-]’s superior vaccine efficacy and longer viral
persistence in vivo. For example, it is known that NFκB activation and IL-12 expression
enhances DC activation, promotes CD4+ T cell Th1 differentiation, and boosts IgG antibody
production; all beneficial immune actions during the development of a substantial vaccination
response (144,83). Our hPBMC cytokine secretion results also fall in-line with this trend;
whereas, the pro-inflammatory cytokines more potently induced by Ad5[E1-,E2b-] than Ad[E1-]
vectors, IL-1β and TNFα, are also important instigators of antigen-dependent CD4+ T cell clonal
expansion (210). Alternatively, it has been found that increased IFNβ production following viral
vaccine administration can inhibit mucosal phagocyte IL-12 responses, thereby decreasing
efficiency of vaccine-induced phagocyte killing and class II MHC expression (195). These
results further corroborate with previous microarray comparisons between Ad5[E1-] and HDAd5, showing there to be many significant interferon-mediated gene expression differences
between these vectors at early post-infection times (203).
The mechanism by which Ad5[E1-,E2b-] vectors produce this beneficial immune
response requires further investigation, although the observed decreases in vector-derived gene
expression when compared to Ad5[E1-] vectors may be a pivotal factor. For example, two of
these differentially expressed viral genes were VAI and VAII, the Ad5 VARNA genes. Ad
VARNAs have been characterized as potent dsRNA activators of type I interferon expression
(152), yet also act as NFκB signaling inhibitors (212,213). Moreover, Ad VARNAs interact with
RNAi-related enzymes to inhibit endogenous RNAi activities while simultaneously promoting

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VARNA-derived siRNA and miRNA synthesis (154,214,215); production of which have been
shown to impact many aspects of cell biology, including anti-viral immune function (216,217).
Products from other rAd5 genes have also been shown to directly affect human cellular signaling
pathways; for example, hexon protein has been described as interacting with dynein-dependent
transport and the coagulation cascade (218,219). The decreased expression of Ad gene products
by Ad5[E1-,E2b-] vaccines may minimize these types of effects, some of which (e.g. NFκB
inhibition) are known to be directly detrimental to the development of transgene-specific
immunity (83).
The other postulation that can be reached from these results is that Ad5[E1-] vaccines
may be elaborating Ad-derived immune evasion strategies. This is further supported by the fact
that Ad5[E1-] hPBMC infection not only induced a smaller pro-inflammatory, Th1 response than
Ad5[E1-,E2b-] infection, but also produced significantly less IFIT1 expression than a fullydeleted Ad5-based vector which lacks any Ad gene expression (Figure 8).
In summary, Ad5[E1-]- and Ad5[E1-,E2b-]-based vaccines were found to each induce
unique, early innate responses along with differences in viral-derived gene expression during
hPBMC infection. These findings help to shed light on the immune balancing act that
recombinant virus vectors face when being used for vaccination; triggering innate immunity can
promote transgene-specific memory responses and vaccine efficacy, yet it can also activate antiviral responses and predispose them to pre-existing anti-vector immune responses that diminish
vaccine efficacy. While adaptive immune responses caused by previous Ad5 exposure may still
contribute to the lower efficacy of Ad5[E1-] as compared to Ad5[E1-,E2b-] vaccines, these
results suggest that this is unlikely to be the only factor and that early adenoviral biological
activities may also play a role in these differences. Better understanding of the immune

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responses towards innovative recombinant Ad vectors, such as the Ad5[E1-,E2b-] platform, may
allow for further optimization of safe and effective virus-based vaccines.

Acknowledgements
A.A. was supported by the Michigan State University Osteopathic Heritage Foundation.

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Chapter 3: Utilization of a recombinant adenovirus vector expressing an Eimeria antigenderived TLR agonist as a vaccine adjuvant.

Portions of this chapter are derived from the previously published research articles:

Appledorn DM, Aldhamen YA, DePas W, Seregin SS, Liu C-JJ, Schuldt N, Quach D, Quiroga
D, Godbehere S, Zlatkin I, Kim S, McCormick JJ, Amalfitano A. A new adenovirus based
vaccine vector expressing an Eimeria tenella derived TLR agonist improves cellular immune
responses to an antigenic target. PloS One. 2010; 5(3):e9579.
Quiroga D – contributed towards experiments using ELISpot assays for measurement of
splenocyte transgene response in mice injected with recombinant adenovirus vectors

Seregin SS, Aldhamen YA, Appledorn DM, Aylsworth CF, Godbehere S, Liu C-JJ, Quiroga D,
Amalfitano A. TRIF is a critical negative regulator of TLR agonist mediated activation of
dendritic cells in vivo. PloS One. 2011; 6(7):e22064.
Quiroga D – contributed towards experiments using ICS analysis of DC and NK cells treated
with rEA

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3.1

Introduction
Vaccination protocols often call for not only an antigenic component, but also for an

adjuvant to promote long-term immunity and memory towards the specific antigen. In turn,
substances that are agonists of the TLR system have been connected to the development of many
consequential adaptive immune responses (220,221). When the appropriate PAMP binds to a
TLR, it triggers downstream activation of NFκB and other signaling pathways, which in turn
promotes the upregulation of many pro-inflammatory genes and increase of surface MHC and
co-stimulatory molecule expression (23). Clinical trials have been conducted using a variety of
TLR agonists as adjuvant agents (222), but finding a compound which is both potent and safe
has proven to be a difficult task.
One promising TLR agonist candidate to use as an adjuvant immunostimulant is the 19
kDa protein, recombinant Eimeria antigen (rEA) (223). rEA was originally isolated following
examination of the bovine-derived gut protozoa, Eimeria tenella; an organism found to be
critically involved in the creation of a tumor-free, Th1-skewed environment (223). Introduction
of this protein into animal models has resulted in improved survival rates following Toxoplasma
gondii, flaviviruses, and phleboviruses challenges (224–227). rEA has also been tested for use as
a therapeutic anti-tumor treatment, with studies confirming rEA’s ability to stimulate DC IL-12
release as well as lower circulating levels of the TAA, CA-125, in patients that were carrying
CA-125 expressing tumors (223,228). Importantly, administration of sizable rEA protein
concentrations resulted in no discernable animal or human patient side effects (223,228).
As rEA shares a high amount of homology with T. gondii profilin-like protein and
induces similar DC activation patterns, it has been assumed that rEA also induces its proinflammatory, anti-microbial, and anti-tumor effects at least in part through the mouse TLR11

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pathway (229). However, this cannot be the route by which humans recognize rEA as the human
TLR11 gene contains stop codons, thereby keeping it from encoding a functional protein (230).
In this chapter, we wished to ascertain if rEA protein could be signaling through human
TLR or TLR-related pathways by determining if its immunogenic effects are dependent upon
TLR adaptor proteins, MyD88 and TRIF, and the immune cells it is exposed to (231). As
previously characterized TLR agonists have been shown to be potent adjuvants (93,220,222), we
also evaluated rEA’s ability to improve CMI and CTL functions against targeted antigens when
it is being expressed by a rAd vector (187). Together, these findings assist in the understanding
and characterization of a novel TLR ligand and potential vaccine adjuvant.

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3.2

Methods

3.2.1 Animal care and procedures
All animal procedures were conducted under the approval of Michigan State University’s
Institutional Animal Care and Use Committee. Eight-week old male Balb/c and wild-type (WT)
C57BL/6 mice were purchased from The Jackson Laboratory (Bar Harbor, ME). MyD88-KO
and TRIF-KO mice were generously provided by Dr. Shizuo Akira. MyD88/TRIF-DKO mice
were bred at Michigan State University. All knock-out mice were bred on a C57BL/6
background. For intraperitoneal (IP) injections, mice were administered 100μL PBS (pH 7.4)
dilutions of purified rEA protein (NCBI Accession: AY745810), as previously described (187).
For IV injections, mice were administered 200μL PBS dilutions of rAd5 virus or rEA protein via
retro-orbital sinus. For intramuscular (IM) injections, mice were administered 20μL PBS
dilutions of rAd5 virus or 50 μL PBS dilutions of rEA protein within the tibialis anterior muscle
of the right hindlimb.
3.2.2 Recombinant adenovirus vector construction
The rEA gene open reading frame was inserted directly upstream of a GFP cassette
within a CMV-driven pShuttle cassette, creating the pAdTrack-rEA shuttle. pAdTrack-rEA was
linearized and recombined within BJ 5183 cells with the pAdEasy1 Ad5 vector, as previously
described (205). The resulting pAd5-rEA plasmid was linearized with PacI restriction enzyme,
transfected into HEK293 cells for vector replication, and purified using cesium gradient
separation, as previously described (205,206). During these processes, direct sequencing and
restriction enzyme mapped were used to verify correct plasmid sequences.
rAd5-GFP was built and propagated using the pAdEasy1 Ad5 system, as previously
described (205). rAd5-GFP was used as a control vector as it was previously confirmed to have

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no significant impact on measurable adaptive immune responses to co-administered antigens
(191).
All vectors underwent direct sequencing to verify correct transgene insertion and were
found to be replication-incompetent via E1 gene region deletion by PCR, as previously described
(232). Viral particle titers were determined by spectrophotometry. All viral vectors were tested
and validated as having <0.01 EU (per injection dose) bacterial endotoxin contamination, as
previously described (208).
To verify that in vitro transduction efficiencies of rAd5-GFP and rAd5-rEA vectors were
equivalent, HEK293 cells were infected with 1x1010 vp/mL and percentages of GFP-positive
cells were compared (and found to be similar at 24 hpi) by FACS analysis using an LSRII flow
cytometer and FlowJo software (Tree Star) (187).
3.2.3 Splenocyte processing
Splenocytes were obtained and processed as previously described (142). Briefly, mouse
spleens were homogenized through physical disruption by passage through a 40 μm sieve.
Splenocytes were treated with red blood cell (RBC) lysis buffer, then washed and resuspended in
RPMI media supplemented with 10% FBS and 1x PSF (penicillin, streptomycin, and fungizone).
3.2.4 Cell staining and flow cytometry
Prepared splenocytes were measured for DC and NK cell activation and maturation
markers, as previously described (172). For DC staining, 1x106 splenocytes per sample were
treated with 4 mg/mL PECy7-Cd11c, APC-CD80, Pacific Blue-CD86, and PerCpCy5.5CD3/CD19/NK1.1 (dump channel) (BD Biosciences) on ice for 30 minutes, then washed with
FACS buffer and sorted using an LSRII flow cytometer and FlowJo software.

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For intracellular NK cell staining, 2x106 splenocytes per sample were treated with 1
μg/mL Brefeldin A (suspended in DMEM supplemented with 10% FBS and 1x PSF) for 4 hours
at 37⁰C. Splenocytes were washed twice with FACS buffer, incubated with rat anti-mouse
CD16/CD32 Fcγ block (BD Biosciences) for 15 minutes, and stained with 8 mg/mL APC-CD3
and PE-Cy7-NK1.1 (BD Biosciences) for 30 minutes on ice. Following fluorescent antibody
staining, splenocytes were washed with FACS buffer, fixed on ice with a 20 minute treatment of
2% formaldehyde (Polysciences), permeabilized at room temperature for 20 minutes with 0.5%
saponin (Sigma-Aldrich), and intracellularly-stained on ice for two hours with 8 mg/mL FITCIFNγ. Finally, cells were washed with FACS buffer and sorted using an LSRII flow cytometer
and FlowJo software.
3.2.5 Cytokine and chemokine analysis
Plasma cytokine and chemokine concentrations were measured via 23-plex mouse
multiplex-based assay as indicated by the manufacturer’s instructions (Bio-Rad) by use of a
Luminex 100 machine (Luminex, Austin, TX), as previously described (232).
3.2.6 Enzyme-linked immunosorbent spot (ELISpot) assay analysis
ELISpot assay analyses were performed using a Ready-Set-GO! ELISpot mouse IFNγ kit
(eBioscience, San Diego, CA), as previously described (233). In brief, splenocytes (5x106
cells/well) from individual mice were incubated on capture antibody pre-treated plates with 4
mg/mL GFP (DTLVNRIEL), LacZ (DAPIYTNV), or Gag (AMQMLKETI) peptides (Genscript,
Piscataway, NJ). Staining of plates was performed as described in manufacturer’s protocol. Plate
well photography and spot-forming cell (SFC) quantification was performed by an automated
ELISpot reader (Cellular Technology, Cleveland, OH).

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3.2.7 Statistical analysis
Flow cytometry data was analyzed using two-tailed homoscedastic Student’s t-tests to
compare differences between mock- and rEA-treated mice in each individual knockout group, as
well as between WT mice and other knockout groups following mock or rEA treatment. All
other experiments where statistical significance was determined was analyzed using a one-way
ANOVA with a Newman-Keuls post-hoc correction. Graphs in this chapter are presented as
mean ± standard error. Statistical analyses were performed using GraphPad Prism (GraphPad
Software).

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3.3

Results

3.3.1 Regulation of rEA-induced dendritic cell responses by TLR adaptor proteins
In characterizing the type of innate immune response that rEA stimulation would induce,
we wished to test if the presence of MyD88 and/or TRIF adaptor proteins would affect its
immunostimulatory activities. To do this, we IP injected C57BL/6-background WT, MyD88-KO,
TRIF-KO, and MyD88/TRIF-DKO mice with mock (PBS alone) or 100ng purified rEA protein.
Previous studies have shown that rEA can induce DC activation by 6 hpi (187), therefore, mice
were sacrificed for splenocytes at this time for flow cytometry analysis of DCs (CD3-, CD11c+,
CD19- splenocytes), which were analyzed for expression of DC activation markers CD80 and
CD86. In WT and TRIF-KO mice, we found that the percentage of DCs expressing CD80 and
CD86 were higher following rEA treatment than with mock (p<0.01) (Figure 9, 10).
Interestingly, rEA-treated TRIF-KO mice had a greater percent of activated DCs than rEAtreated WT mice (p<0.001). Alternatively, rEA treatment of MyD88-KO and MyD88/TRIFDKO mice did not result in a significant increase in the amount of CD80- or CD86-expressing
DCs as compared to mock-treated animals.

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Figure 9

rEA-mediated dendritic cell activation is differentially regulated by MyD88 and TRIF

83

Figure 9 (cont’d)
C57BL/6 WT (n = 3-4), MyD88-KO (n = 3), TRIF-KO (n = 3-4), and MyD88/TRIFDKO (n = 4) mice were mock injected or injected with 100 ng rEA protein. At 6 hpi, splenocytes
were harvested, stained with fluorescent antibodies, and sorted by flow cytometry. Independent
groups of WT mice were used for each knockout genotype comparison. Bars denote mean ±
standard error. ** denotes a significant difference from mock-treated animals (p<0.01).

84

Figure 10

rEA-mediated dendritic cell activation is differentially regulated by MyD88

and TRIF (histogram plots)
Representative histograms of rEA-treated DC samples detailed in Figure 9.

85

The concentration of CD80 and CD86 surface expression per cell also followed this
trend, with WT and TRIF-KO mice both possessing a significant increase in the proportion of
activated DCs upon rEA administration as opposed to mock treated (Figure 11). rEA-treated
TRIF-KO mice also produced significantly greater amounts of CD86 expression per cell than
rEA-treated WT mice (p<0.001). Again, MyD88-KO and MyD88/TRIF-DKO mice did not have
this induction of DC maturation following rEA treatment, with rEA-treated MyD88-KO mice
producing significantly lower amounts of CD80 and CD86 expression per cell than rEA-treated
WT mice (p<0.01).

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Figure 11

rEA-mediated dendritic cell activation is differentially regulated by MyD88 and TRIF (MFI)

87

Figure 11 (cont’d)
C57BL/6 WT (n = 3-4), MyD88-KO (n = 3), TRIF-KO (n = 3-4), and MyD88/TRIFDKO (n = 4) mice were mock injected or injected with 100 ng rEA protein. At 6 hpi, splenocytes
were harvested, stained with fluorescent antibodies, and sorted by flow cytometry. Independent
groups of WT mice were used for each knockout genotype comparison. Mean fluorescent
intensity (MFI) values are displayed and are representative of the indicated marker concentration
per cell. Bars denote mean ± standard error. ** denotes a significant difference from mocktreated animals (p<0.01 respectively).

88

3.3.2 Regulation of rEA-induced natural killer cell responses by TLR adaptor proteins
Finding such striking differences in rEA-stimulated mouse DC activation, depending
upon the presence of certain TLR adaptor proteins, prompted further investigation into the
function of other immune cells such as NK cells. To study rEA protein effects, C57BL/6background WT, MyD88-KO, TRIF-KO, and MyD88/TRIF-DKO mice were IP injected with
mock (PBS alone) or 100ng purified rEA protein. We have previously shown that rEA can
promote significant NK cell activation at 6 hpi (187), therefore, mice were sacrificed at the this
time-point for splenocyte-based flow cytometry analysis of NK cells (CD3-, NK1.1+ splenocytes)
which were activated to express intracellular IFNγ. Similar to our DC results, WT and TRIF-KO
mice produced a higher percentage of NK cells expressing IFNγ after rEA treatment than with
mock treatment (p<0.01) (Figure 12, 13), whereas MyD88-KO and MyD88/TRIF-DKO mice
showed no rEA-triggered increases in NK cell activation.

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Figure 12

rEA-mediated NK cell activation is differentially regulated by MyD88 and TRIF

90

Figure 12 (cont’d)
C57BL/6 WT (n = 3-4), MyD88-KO (n = 3), TRIF-KO (n = 3-4), and MyD88/TRIFDKO (n = 4) mice were mock injected or injected with 100 ng rEA protein. At 6 hpi, splenocytes
were harvested, stained with fluorescent antibodies, and sorted by flow cytometry. Independent
groups of WT mice were used for each knockout genotype comparison. MFI values displayed
are representative of the concentration of the indicated marker per cell. Bars denote mean ±
standard error. ** denotes a significant difference from mock-treated animals (p<0.01).

91

Figure 13

rEA-mediated NK cell activation is differentially regulated by MyD88 and TRIF (histogram plots)

Representative histograms of rEA-treated DC samples detailed in Figure 12.

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In WT and TRIF-KO mice, NK cell IFNγ MFI values were also increased following rEA
treatment, but were left unchanged in MyD88-KO and MyD88/TRIF-DKO mice (p<0.01)
(Figure 12). It should also be noted that the amount by which NK cell activation was increased
following rEA protein treatment was elevated in WT mice (from 1% to 20-30% IFNγ-expressing
NK cells), but even higher levels were noted in TRIF-KO mice following rEA administration
(from 1% to >40% IFNγ-expressing NK cells). Conversely, MyD88 and MyD88/TRIF-DKO
mice did not demonstrate an increase in the IFNγ MFI values of NK cells following rEA
exposures.
3.3.3 Murine cytokine response to intramuscular or intraperitoneal rEA protein
injections
Since its original synthesis, rEA’s adjuvant properties have been studied in mice via IP
injection, in part to be synonymous with tumor injection sites but also to take advantage of the
robust immune responses that can be triggered through this route (187,223). However, if rEA is
to be used for vaccine applications, IM administration would serve as a more convenient and
consistent inoculation route. To measure if the innate immune responses triggered by IP-injected
rEA protein differs from IM-injected rEA protein, C57BL/6 mice were injected with IP or IM
with a total of 100 ng rEA protein. In previous IP studies, rEA injections were delivered in a 100
μL volume. Unfortunately, 100 μL injections could not be physically or ethically IM injected
into a single, unilateral site on one of the animal’s tibialis anterior muscles, therefore, we split
this volume into two 50 μL injections that were administered bilaterally. Mice were sacrificed for
serum collection at 6 hpi and analyzed for serum cytokine and chemokine concentrations by
multiplex assay. Of the 23 cytokines and chemokines measured by this assay, all but one (IL-10)
were expressed at similar levels, independent of the rEA protein administration route (Figure

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14). In general, we found that rEA injection, by either route, induced a broad spectrum of
cytokine and chemokine production, including IL-2, IL-4, IL-10, IL-17, eotaxin, IFN-γ,
RANTES, and TNFα, consistent with previous in vivo rEA findings (187,223).

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Figure 14

rEA protein promotes cytokine and chemokine induction mainly independent of injection route

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Figure 14 (cont’d)

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Figure 14 (cont’d)
C57BL/6 mice (n = 2) were mock injected, or injected with 100 ng rEA protein IM or IP.
At 6 hpi, serum was collected and measured for cytokine and chemokine concentrations by
multiplex assay. *, ** denotes a significant difference from mock-treated animals (p<0.05,
p<0.01, respectively). # denotes a significant difference between IM- and IP-route injected
animals (p<0.05).

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3.3.4 An rEA-expressing recombinant Ad5 vector enhances co-expressed transgenespecific immunity
After verifying rEA protein’s immunostimulatory characteristics, we wished to study
how administration of rEA would affect the development of vaccine-based immunity. To do this,
we wished to constitutively express rEA by utilization of an rEA-expressing rAd5 vector (rAd5rEA) (Figure 15). In addition to expressing the rEA gene, we built rAd5-rEA to also express
green fluorescent protein (GFP) as a way to measure how it may induce immunity to a coexpressed transgene. This also allowed us to directly compare rAd5-rEA’s immunogenic effects
to rAd5-GFP; a useful control vector which has been found to have little effect on the promotion
of long-term memory responses when introduced alongside antigens of interest (191).

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Figure 15

rAd5-rEA construction

The open reading frame of the human rEA gene was inserted into a CMV expression
cassette which also contained an upstream GFP expression cassette, resulting in the creation of
pAdTrack-rEA. The plasmid was then linearized by PmeI restriction enzyme processing and
recombined with pAdEasyI Ad5 (an Ad5 genomic backbone lacking E1 and E3 genes) inside of
BJ 5183 cells. The resulting pAd5-rEA was linearized by PacI restriction enzyme processing
and transfected into HEK293 cells, where the vector was able to replicate to large titers. rAd5rEA purification was conducted using cesium gradient separation and directly sequenced to
confirm transgene rEA’s presence. This figure is an amended version of our previously published
version, courtesy of Dr. Schuldt (191).

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We studied the adjuvant effects of rAd5-rEA by IV (Figure 16A) or IM (Figure 16B)
injecting C57BL/6 mice with mock, 1x1010 vp rAd5-GFP, or 1x1010 vp rAd5-rEA. Mice were
sacrificed at 7 dpi for collection of splenocytes to use for ELISpot detection of GFP-specific
CMI responses. We found that both rAd5-GFP and rAd5-rEA treated mice were able to induce a
significant response against GFP (p<0.01), while also lacking a response towards the nonspecific LacZ peptide; showing that mouse CMI following vaccination was specific to the
introduced transgene. Most importantly, the quantity of GFP-directed immunity was significantly
greater in mice administered rAd5-rEA than rAd5-GFP (p<0.01), showing that rEA expression
promotes transgene immunity. This difference was approximately four-fold higher in IV-injected
animals and two-fold higher in IM-injected animals, however, the total quantities of GFPresponsive splenocytes in IV and IM rAd5-rEA treated mice were found to be mainly equivalent.

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Figure 16

Improved cell-mediated immunity towards co-expressed transgene following

rAd5-rEA vaccination
C57BL/6 mice (n = 2-3) were IV (A) or IM (B) injected with 1x1010 vp rAd5-GFP or
rAd5-rEA and were sacrificed for splenocyte collection at seven (A) or fourteen (B) days postinjection and examined by IFN-γ ELISpot to count peptide-specific SPCs. Bars denote mean ±
standard error. ## denotes a significant difference from naïve animals (p<0.01). ** denotes a
significant difference between rAd5-GFP and rAd5-rEA treated animals (p<0.01)

Naïve
rAd5-GFP
rAd5-rEA

Naïve
rAd5-GFP
rAd5-rEA

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3.3.5 Addition of rAd5-rEA improves CMI against a co-injected rAd-expressed transgene
For an adjuvant to be useful, it must be able to promote a vigorous response against a
pathogenic antigen. To investigate the adjuvant properties rAd5-rEA can contribute for increased
pathogen-specific peptide recognition, we injected Balb/c mice with 1x106 or 1x108 total vp of an
equivalent combination of a rAd vector expressing the HIV-specific Gag gene (rAd5-Gag) and
either rAd5-GFP or rAd5-rEA. Splenocytes were collected at 14 dpi, stimulated with one of two
HIV Gag epitopes (#304769 or AMQMLKETI), and analyzed by IFN-γ ELISpot. We found that
the 1x106 vp dose treatment of rAd5-Gag + rAd5-rEA induced significantly greater amounts of
Gag-specific immunity towards both epitopes over 1x106 vp of rAd5-Gag + rAd5-GFP (p<0.001)
(Figure 17). Also, CMI against the AMQMLKETI epitope was significantly higher in animals
treated with 1x108 vp rAd5-Gag + rAd5-rEA than with 1x108 vp rAd5-Gag + rAd5-GFP
(p<0.05).

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Figure 17

rAd5-rEA induces heightened HIV Gag-specific CMI responses

Balb/c mice (n = 3) were IM injected with 1x106 or 1x108 total vp of an equivalent
combination of rAd5-Gag and rAd5-GFP or rAd5-Gag and rAd5-rEA. At 14 hpi, splenocytes
were harvested and examined by IFN-γ ELISpot to measure Gag-specific immunity against two
Gag-derived epitopes (#304769 and AMQMLKETI). Bars denote mean ± standard error. *, ***
denote a significant difference between treatment groups (p<0.05, p<0.001, respectively).

rAd5-Gag + rAd5-GFP
rAd5-Gag + rAd5-rEA

rAd5-Gag + rAd5-GFP
rAd5-Gag + rAd5-rEA

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3.4

Discussion
Multiple past studies have shown how TLR stimulation can serve as an important factor

in the development of long-term adaptive immune responses (86,220,234). With this in mind, we
chose to investigate the properties of a novel TLR agonist, rEA. Previous investigations have
validated that rEA is both safe to administer as well as adept at inducing innate immune and antitumor effects in humans (223,228), however, the exact pathways by which rEA exerts these
actions is unclear. Therefore, we chose to test how mice that lacked TLR adaptor protein
expression (MyD88 and/or TRIF) would respond to rEA protein stimulation. We found that both
DCs and NK cells from WT and TRIF-KO mice were strongly activated following rEA treatment
and that mice lacking TRIF sometimes experienced even greater levels of rEA-dependent
activation than WT animals. On the other hand, rEA-induced activation of DC and NK cells was
completely ablated in MyD88-KO and MyD88/TRIF-DKO mice. These findings indicate that
rEA requires MyD88 to trigger activation of important innate immune components, while TRIF
acts as a negative regulator of this response.
Other experiments completed by our group also revealed that monocytes, NKT, T, and B
cells were activated by MyD88 and inhibited by TRIF in the same manner (231). These studies
also included measurement of cytokines and chemokines following rEA treatment, which
showed that the pro-inflammatory response induced in WT mice (expression of IL-2, IL-6, IL12, G-CSF, and IFNγ) was even more pronounced in TRIF-KO mice and was diminished in
MyD88-KO and MyD88/TRIF-DKO mice (231), further confirming rEA’s mechanism of
immune activation. These systematic findings are important in validating the hypothesis that rEA
is a TLR agonist; this conjecture was based on rEA’s high level of protein sequence homology
with the TLR11 agonist Toxoplasma gondii profilin (224,225,229). As with rEA, profilin-TLR11

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signaling and promotion of DC IL-12 production has been identified as MyD88 dependent (229).
Past studies have also shown that the transition of TLR signaling to strong adaptive responses
requires the presence of MyD88 (235), whereas TRIF has yet to be described in this fashion. It is
additionally notable that the removal of TRIF allows for a more immunogenic effect following
rEA administration. In future studies, inhibition of TRIF may be a useful tool in triggering innate
immunity by other PAMPs as well.
So to transition rEA into the clinical vaccine delivery field, it would be helpful to prove
that rEA can be effective by multiple routes, including intramuscularly. In general, we found that
administration of rEA protein by IP or IM route did not change its potency or pattern of cytokine
signaling. With this in mind, we built an rEA- and GFP-expressing rAd vector (rAd5-rEA) to see
if we could develop a way to deliver rEA more constitutively and immunogenically than rEA
protein alone. Our group’s previous studies explored the differential cytokine responses that rEA
protein, rAd5-GFP, rAd5-GFP with rEA protein, and rAd5-rEA treatments created upon in vivo
injection. We found that rAd5-rEA injection promotes pro-inflammatory cytokine production at
significantly greater levels than any of the other aforementioned treatments (187). Additionally,
these studies found that DC, NK, and NKT cells are also more readily activated by rAd5-rEA
than rAd5-GFP vector injection (187).
To test if rAd5-rEA immunostimulatory effects could translate into potent adjuvant
activities, we measured CMI towards rAd5-rEA’s co-expressed transgene, GFP, and a transgene
expressed by a co-injected rAd5 vector, HIV Gag. In both instances, rAd5-rEA increased the
amount of transgene-specific immunity over rAd5-GFP control vector treatment. Such boosting
of Gag-directed immunity is of particular interest as studies of HIV long-term progenitors
(patients that retain healthy immune function and T cell counts even without anti-HIV therapies)

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have shown them to consistently possess strong anti-Gag CTL responses (236). Analysis of the
failed rAd5 Merck HIV STEP clinical trial revealed that vaccine recipients who had strong
inductions of TLR-specific signaling and Th1-dominant gene expression pathways were also
more likely to mount substantial anti-HIV CTL responses (237).
Additionally, it should also be noted that these studies were conducted in two different
strains of mice, C57BL/6 and Balb/c. It has been established that C57BL/6 mice have an
intrinsically Th1-skewed immune responses while Balb/c mice favor Th2-skewed immune
processes (238,239); consequently demonstrating that we can develop sizeable transgene
memory responses in both immunologically diverse in vivo mouse models. These findings also
support the possibility of effective clinical translation with the hope that the inherent genetic
differences between individual humans may not impact the efficacy of rEA-based treatments.
In summation, these studies identified that rEA’s effects on portions of the innate
immune response are MyD88-dependent and TRIF-inhibited. Also, by creating an rEAexpressing rAd5 vector, we showed that administration of rAd5-rEA has the capability to induce
large amounts of cytokines and to promote transgene-specific immunity when administered
concurrently with a transgene-expressing vector. We believe the next appropriate studies to test
rAd5-rEA efficacy would be to further characterize the adaptive immunity that it fosters and
examine if this response would allow for a multi-faceted immune induction against a vaccine
antigenic target of interest.

Acknowledgements

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We wish to thank the personnel in Michigan State University’s laboratory animal support
facilities for their assistance in the humane care of animals utilized in this work. A.A. was
supported by the Michigan State University Osteopathic Heritage Foundation.

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Chapter 4: Strengthened tumor antigen immune recognition by inclusion of a recombinant
Eimeria antigen in therapeutic cancer vaccination

This chapter is the edited version of a research article under review for publication; originally
submitted June 25th, 2014 and currently undergoing revisions.

Authors: Quiroga D, Aldhamen YA, Appledorn DM, Godbehere S, Amalfitano A

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4.1

Introduction
Immune responses against cancerous cells are often absent as a result of systemic T cell-

mediated tolerance against them and their respective tumor-associated antigens (TAA). To
mount a substantial immune response against malignancies, successful immunotherapy trials
have shown that a therapeutic vaccine must be able to initiate and propagate a strong, TAAspecific cytotoxic immune response (240). Carcinoembryonic antigen (CEA) has been identified
as a particularly promising TAA target due to its ubiquitous overexpression in colorectal and
other carcinomas, as well as its relatively high level of immunogenicity (241). Various methods
have been employed to use CEA as a vaccine transgene, with several resulting in induction of
CEA-targeted CTL responses and anti-CEA antibody production (242–245). Recently, a phase
I/II clinical trial in which colorectal cancer patients, who had failed an average of three prior
chemotherapeutic regimens, were administered adenovirus vectors expressing an enhanced,
modified version of CEA (rAd5-CEA) (186,196). This CEA-expressing adenovirus vector
multiplied anti-CEA CMI responses several fold over patient pre-vaccination baseline. In
addition, patient survival rates at one year were found to be greater than those previously
reported in demographically similar colorectal cancer patient populations (246) and were most
improved in the treatment group given the highest dose of rAd5-CEA.
As this and many other cancer immunotherapy trials have revealed, there is a substantial
positive correlation between the amount of TAA-directed CMI produced and rates of patient
survival. It has also been recognized that even immunotherapy-naïve patient tumor
microenvironments often contain TAA-presenting cells, yet they do not readily activate a CTL
response against the antigen when present (247,248). Therefore, in addition to a TAA

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vaccination, successful treatment may also require an adjuvant to promote long-term immunity
and memory towards the cancer cells.
Several adjuvants have been shown to improve both the degree and breadth of antigen
specific cellular immune responses, particularly those that trigger TLR- and other PRR-mediated
innate immune responses (77,88,220,221,249). Recombinant Eimeria antigen (rEA) is a notable
activator of TLR and non-TLR innate immune signaling pathways. rEA was initially identified
within the Eimeria tenella protozoan as an inducer of high IL-12 levels in the bovine intestine,
an effect that promoted an overall anti-tumorigenic environment (223). Injection of the rEA
protein has since been shown to prolong survival of tumor-carrying mice and induce a safe,
cytokine-dependent decrease in the CA-125 tumor marker within advanced malignancy patients
(223,228). In previous studies, we have created an rEA-expressing rAd vector (rAd5-rEA) and
shown that in vivo delivery of this agent can promote a Th1-skewed, pro-inflammatory response
greater than rEA protein or a non-specific rAd, as measured by heightened cytokine responses
(e.g. IFNγ, TNFα, IL-12(p70)), activation of innate immune cells (e.g. NK, NKT, DC), and
greater transgene memory responses against a co-injected HIV derived (HIV-Gag) antigen (187).
Moreover, we have found that rEA can directly promote human NK effector cell activation and
stimulate human peripheral blood mononuclear cell (PBMC) cytolytic tumor cell killing (250).
Based on these findings, we wished to investigate if co-administration of rAd5-CEA and rAd5rEA could further improve anti-CEA immunity. Additionally, we explored the spectrum,
quantity, and relationship of T and B cell-facilitated adaptive immune responses that rAd5-rEA
introduces to a vaccine regimen targeting a human-relevant TAA.

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4.2

Methods

4.2.1 Recombinant adenovirus vector construction
Recombinant Ad5 vectors rAd5-CEA (196), rAd5-rEA (187), and rAd5-GFP (205) were
built and propagated as previously described. rAd5-GFP was used as a control vector as it was
previously confirmed to have no significant impact on measurable adaptive immune responses to
co-administered antigens (191). The cDNA sequence of human CAP1(6D)-modified CEA was
produced and generously supplied from Duke University (251). Vectors underwent
recombination and viral propagation as previously described (206). All vectors underwent direct
sequencing to verify correct transgene insertion and were found to be replication-incompetent via
E1 gene region deletion by PCR, as previously described (232). Viral particle titers were
determined by spectrophotometry and SDS-polyacrylamide gel electrophoresis following silver
stain or western blotting.
4.2.2 Animal care and procedures
All animal procedures were conducted under the approval of Michigan State University’s
Institutional Animal Care and Use Committee. Eight-week old male C57BL/6 mice were
purchased from The Jackson Laboratory and injected IM into the tibialis anterior of the right
hindlimb with 20μL phosphate-buffered saline solution (PBS, pH 7.4) containing a total of 1x108
to 1x1010 vp, including rAd5-CEA and an equivalent vp dose of either rAd5-GFP or rAd5-rEA.
Splenocytes and blood plasma were obtained and processed as previously described (142).
4.2.3 ELISpot assay analysis
ELISpot assay analyses were performed using Ready-Set-GO! ELISpot mouse IFNγ and
IL-2 kits (eBioscience), as previously described (233). In brief, splenocytes (5 x 106 cells/well)
from individual mice were incubated on capture antibody pre-treated plates with individual CEA

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peptides or a CEA peptide pool. Individual CEA peptides were 15 aa in size and covered the
CEA498-676 sequence with a CAP1(6D) modification in 10aa overlaps using a PepTrack peptide
library (JPT Peptide Technologies, Berlin, Germany). The CEA peptide pool of CAP1(6D)modified CEA sequence peptides was a generous gift from Dr. Michael Morse at Duke Medical
Center (186). Staining of plates was performed as described in manufacturer’s protocol. Plate
well photography and SFC quantification was performed by an automated ELISpot reader
(Cellular Technology).
4.2.4 Cell staining and flow cytometry
Fluorescent ICS was performed as previously described (189). In brief, 2 x 106
splenocytes were stained with APC-Cy7-CD3, Alexa Fluor700-CD8a, and CD16/32 Fc-block
antibodies, fixed using 2% formaldehyde (Polysciences), permeabilized using 0.2% saponin
(Sigma-Aldrich), stained for intracellular cytokines using APC-granzyme B, FITC-IFNγ, PEperforin, PE-Cy7-TNFα (BD Biosciences), and PerCpCy5.5-IL-2 (BioLegend, San Diego, CA),
and stained for dead cell exclusion using violet fluorescent reactive dye (Invitrogen). Cells were
analyzed with a LSRII flow cytometer (BD Biosciences) using FlowJo software (Tree Star).
4.2.5 In vivo cytotoxic T lymphocyte (CTL) assay
In vivo CTL analysis was performed similarly to previously described studies (233).
Briefly, mice were vaccinated with 5 x 109 vp rAd5-CEA and 5 x 109 vp of either rAd5-GFP or
rAd5-rEA. At 21dpi, syngeneic splenocytes were pulsed with a CEA-specific peptide pool or the
irrelevant HIV Gag peptide, AMQ (AMQMLKETI), for 1 hour at 37⁰C. Carboxyfluorescein
succinimidyl ester (CFSE) was used to stain CEA-pulsed splenocytes at a 10μM concentration
(CFSEHigh) and AMQ-pulsed splenocytes at a 1μM concentration (CFSELow). Immunized and
naïve mice were injected in the left retro-orbital sinus with equal amounts of CEA- and AMQ-

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pulsed splenocytes at a total volume of 8x106 cells. Twenty-four hours following splenocyte
infusion, mice were sacrificed for splenocyte collection, washing, and FACS analysis by LSRII
flow cytometer. FlowJo software was utilized to quantify amounts of CFSE-stained splenocytes.
The percentage of specific CEA-pulsed splenocyte killing was determined using the following
equation: % specific killing = 1 – ((% CFSEHigh /% CFSELow)immunized/(% CFSEHigh /%
CFSELow)naive).
4.2.6 Anti-CEA and anti-Ad ELISA analysis
ELISAs were performed as previously described (147). Briefly, 5 x 108 vp of a null Ad5
vector, 0.2 μg CEA peptide pool, or 0.2 μg individual CEA peptide epitopes were plated per well
in a high-binding 96-well flat-bottom plate. Following overnight 4⁰C incubation, plates were
rinsed with washing buffer (PBS containing 0.05% Tween) and incubated with blocking buffer
(PBS containing 3% bovine serum albumin) for an hour at room temperature. Plasma was plated
following 1:1600 dilution (or pooled and diluted 1:10 for measurement of individual CEA
epitope IgG binding) in blocking buffer and incubated for an hour at room temperature. Wells
were subsequently rinsed with washing buffer and coated with an HRP-conjugated rabbit antimouse antibody (Bio-Rad) diluted 1:4000 in washing buffer. TMB substrate (Sigma-Aldrich)
was added to each well to initiate the spectrophotometric reaction, which was stopped with 1N
phosphoric acid. Plates were analyzed using an automatic microplate reader at 450nm
absorbance.
For anti-CEA IgG antibody avidity binding ELISAs, assays were performed as
previously described (252). Briefly, 0.2 μg CEA peptide pool was plated per well in a highbinding 96-well flat-bottom plate. Following overnight 4⁰C incubation, plates were rinsed with
washing buffer and incubated with blocking buffer for an hour at room temperature. Serum was

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diluted 1:20, plated in duplicates, and incubated for one hour at room temperature. Wells were
subsequently rinsed with washing buffer and incubated with either PBS or PBS containing 8M
urea at 37⁰C for 10 minutes. Following another wash, wells were coated with an HRPconjugated rabbit anti-mouse antibody (Bio-Rad) diluted 1:4000 in washing buffer. TMB
substrate (Sigma-Aldrich) was added to each well to initiate the spectrophotometric reaction,
which was stopped with 1N phosphoric acid. Plates were analyzed using an automatic microplate
reader at 450nm absorbance. Individual samples’ anti-CEA IgG binding avidity ratios were
calculated as: OD450[urea-treated sample] / OD450[untreated sample].
4.2.7 Statistical analysis
Statistical analysis comparing in vivo CTL CEA-specific killing between Ad treatment
groups was performed using a Student’s t-test. The association between percent CEA-specific in
vivo CTL killing and anti-CEA IgG titers within individual animals was tested with the Pearson
correlation coefficient. All other experiment data where statistical significance was determined
were analyzed using a one-way ANOVA with a Newman-Keuls post-hoc correction. Graphs in
this chapter are presented as mean ± standard error. Statistical analyses were performed using
GraphPad Prism (GraphPad Software).

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4.3

Results

4.3.1 Increased rAd5-CEA transgene-specific CMI responses induced in the presence of
rAd5-rEA
We and others have verified that rAd5-CEA vaccination of murine and human subjects
induces significant CEA-specific CMI (186,196,233). To examine if the addition of rAd5-rEA to
a TAA-expressing vaccine would further promote anti-TAA CMI responses, we treated mice
with rAd5-CEA and an equivalent dose of either rAd5-rEA or a GFP-expressing control
adenovirus vector (rAd5-GFP). Mice were injected with a total viral dose of either 1x108, 1x109,
or 1x1010 vp per mouse. Splenocytes were harvested at 14 days post-injection, processed, and
analyzed for anti-CEA specific CMI by IFNγ and IL-2 ELISpot assays. Our data revealed the
amount of CEA-specific, IFNγ-secreting splenocytes to be greater in mice injected with the
rAd5-CEA + rAd5-rEA combination rather than those given rAd5-CEA + rAd5-GFP (Figure
18A). Specifically, both the 1x109 and 1x1010 vp rAd5-CEA + rAd5-rEA groups yielded
statistically more IFNγ-secreting splenocytes than the 1x108 and 1x109 vp rAd5-CEA + rAd5GFP treated groups (p<0.01). IL-2 ELISpot analysis also revealed a significantly greater CEAspecific CMI response when comparing the 1x109 vp dose of rAd5-CEA + rAd5-rEA with the
1x108 (p<0.01) and 1x109 vp (p<0.05) rAd5-CEA + rAd5-GFP treated animals, as well as the
1x108 vp dose of rAd5-CEA + rAd5-rEA treated animals (p<0.05), showing a positive
relationship between dose and rAd5-rEA-promoted CEA-specific CMI (Figure 18B).
Interestingly, the 1x1010 vp dose showed no difference in the amount of cells secreting IL-2 in
response to CEA stimulation. These findings indicate that co-injection of rAd5-rEA with rAd5CEA improves anti-CEA CMI in a mainly dose-dependent manner.

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Figure 18

Strong CEA-specific cell-mediated immunity produced by rAd5-CEA and rAd5-rEA co-vaccination

C57BL/6 mice (n = 2–3) were IM injected with rAd5-CEA and either rAd5-GFP or rAd5-rEA at equal viral particles per
vector, totaling 1x108, 1x109, or 1x1010 vp. Splenocytes were collected from vaccinated and naïve mice at fourteen days post-injection
and examined by IFN-γ (A) and IL-2 (B) ELISpot to count SPCs. Bars denote mean ± standard error. Solid and dashed lines denote a
significant difference between treatment groups (p<0.05, p<0.01 respectively).

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4.3.2 Improved cytotoxic T cell responses against CEA following high-dose rAd5-CEA +
rAd5-rEA co-administration
During the process of tumor cell killing, effector memory CD8+ T cells produce cytolytic
and inflammatory cytokines in response to specific tumor-derived antigens (253,254). To
quantify the amount of CEA-specific cytokine producing CD8+ T cells, splenocytes were
collected from naïve or vaccinated mice administered rAd5-CEA combined with an equal dose
of either rAd5-rEA or rAd5-GFP. Splenocytes were stimulated ex vivo with either a CEA peptide
pool or non-specific HIV-Gag peptide. Splenocytes were analyzed by multicolor flow cytometry
after subsequent fluorescent antibody extracellular staining against CD3 and CD8 and ICS
against IFNγ, TNFα, IL-2, and perforin.
Upon CEA stimulation, 1x1010 vp rAd5-CEA + rAd5-rEA co-injection induced a
significantly higher frequency of IFNγ-expressing CD8+ T cells than those given rAd5-CEA and
rAd5-GFP at all treatment doses, rAd5-CEA + rAd5-rEA at the 1x108 vp dose, and naïve mice
(p<0.05) (Figure 19A). The highest dose of rAd5-CEA + rAd5-rEA also produced a higher
frequency of TNFα-producing CD8+ T cells than 1x108 vp and 1x109 vp rAd5-CEA + rAd5GFP injected and naive mice (p<0.05) (Figure 19B). Quantity of intracellular perforin production
within CD8+ T cells after CEA stimulation was significantly larger following 1x1010 vp rAd5CEA + rAd5-rEA administration in comparison to all other treatment groups (p<0.05 for 1x108
vp and 1x1010 vp rAd5-CEA + rAd5-GFP; p<0.01 for all other groups) (Figure 19C).
Intracellular IL-2 within CD8+ T cells was also measured, but no significant differences were
found between any treatment groups (data not shown). Stimulation with the irrelevant HIV-Gag
peptides did not produce significantly different amounts of cytokine-producing CD8+ T cells
between treatment groups (data not shown). These results suggest that the combination of rAd5-

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CEA + rAd5-rEA at a 1x1010 vp dose induces substantially more CEA-triggered activation of
cytotoxic CD8+ T lymphocytes.

118

Figure 19

High-dose rAd5-CEA and rAd5-rEA administration induces a robust, CEA-

specific CD8+ cytotoxic T cell response
C57BL/6 mice (n = 3) were IM injected with combination of rAd5-CEA and either rAd5GFP or rAd5-rEA at equal viral particles per vector, totaling 1x108, 1x109, or 1x1010 vp.
Splenocytes were collected from vaccinated and naïve mice at fourteen days post-injection,
permeabilized, and stained for CD8+ T cell IFNγ (A), TNFα (B), and perforin (C) expression.
Bars denote mean ± standard error. *, ** denote significant differences between that group and
naïve animals (p<0.05, p<0.01 respectively). Solid and dashed lines denote a significant
difference between treatment groups (p<0.05, p<0.01 respectively).

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4.3.3 Dose-dependent increase in anti-CEA IgG production following rAd5-CEA + rAd5rEA co-administration
In addition to TAA-directed CMI, the generation of TAA-specific IgG antibodies is also
an important aspect of effective cancer immunotherapy through participation in antibodydependent cell-mediated cytotoxicity (251). Curiously, in our clinical trial using solely rAd5CEA, we did not find notable changes in patient serum anti-CEA IgG following vaccination
(186). To measure if the co-administration of rAd5-CEA + rAd5-rEA would induce greater antiCEA IgG titers than rAd5-CEA + rAd5-GFP, mice were co-injected with either combination at a
total viral dose of 1x108, 1x109, or 1x1010 vp. Serum was collected at 14 days post-injection and
used to perform an anti-CEA IgG ELISA. We observed that at the 1x1010 vp dose, mice treated
with rAd5-CEA + rAd5-rEA had significantly greater anti-CEA IgG titers than all other rAd5CEA-treated mice (p<0.05) (Figure 20A). Serum was also used to measure anti-Ad5 IgG titers to
evaluate if vaccinated mice developed an antibody response against the vector itself. As seen
with anti-CEA IgG, 1x1010 vp rAd5-CEA + rAd5-rEA induced a significantly greater titer of
anti-Ad5 IgG than any of the other vaccine-treated mice (p<0.01 for 1x1010 vp rAd5-CEA +
rAd5-GFP and 1x109 vp rAd5-CEA + rAd5-rEA; p<0.001 for all other treatments) (Figure 20B),
suggesting that rEA overexpression enhances B cell responses to all antigenic targets, including
Ad-derived antigens. Moreover, the mice in the 1x109 vp rAd5-CEA + rAd5-rEA had higher
amounts of anti-Ad5 IgG than both groups of 1x108 vp dosed mice (p<0.05). This data suggests
that high doses of rAd5-CEA + rAd5-rEA successfully induce substantial anti-CEA IgG
production, while also producing greater levels of antibodies against the Ad5 vector.

120

Figure 20

Anti-CEA IgG production is potently induced by rAd5-CEA and rAd5-rEA co-injection

C57BL/6 mice (n = 2–3) were IM injected with rAd5-CEA and either rAd5-GFP or rAd5-rEA at equal viral particles per
vector, totaling 108, 109, or 1010 vp. Serum was collected at fourteen days post-injection, diluted at a 1:1600 ratio, and measured for
IgG antibody levels against CEA (A) and Ad5 (B) by ELISA with 450nm OD. Bars denote mean ± standard error. Solid, dashed, and
dotted lines denote a significant difference between treatment groups (p<0.05, p<0.01, p<0.001 respectively).

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4.3.4 rAd5-CEA + rAd5-rEA co-injection enhances breadth of T cell-recognized CEA
peptide epitopes
While it is important to have a strong memory response against a TAA, worth is also
placed on the creation of an epitope-diverse response (255,256). Vaccine-induced recognition of
a greater number of immunogenic antigen epitopes can possibly allow for superior protection in
cases where some epitopes may be bypassed via tumor survival methods and intrinsic HLA
haplotype differences (255,256). We have previously shown that the addition of rAd5-rEA to an
HIV antigen-expressing Ad vaccine increased the breadth and quality of response against HIV
antigen epitopes (187); therefore, we wished to investigate if rAd5-rEA could also improve the
antigen epitope recognition of CEA.
To measure the range of CEA immunogenic areas following vaccination, we collected
splenocytes isolated from mice injected with 1x1010 total vp of either rAd5-CEA + rAd5-rEA or
rAd5-CEA + rAd5-GFP. Splenocytes were stimulated ex vivo with individual, 15 aa-long CEA
peptides that encompassed the entirety of one of CEA protein’s repeating domains in N- to Cterminal 10aa overlaps and were numbered subsequently in that order (Table 4).

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Table 4

CEA peptide epitope sequences and assigned numbering

The location of the epitopes’ amino acid sequence within the CEA protein
(NP_004354.3) is indicated as counted from N- to C-terminus.

Peptide

Peptide

Location in CEA protein sequence

number1

AELPKPSISSNN
sequence

498-512

2

PSISSNNSKPVE
SKP

503-517

3

NNSKPVEDKD
DKD

508-522

4

VEDKDAVAFTC
AVAFT

513-527

5

AVAFTCEPEAQ
EPEA

518-532

6

CEPEAQNTTYL
NTTY

523-537

7

QNTTYLWWVN
WWVN

528-542

8

LWWVNGQSLP
GQSLP

533-547

9

GQSLPVSPRLQ
VSPRL

538-552

10

VSPRLQLSNGN
LSNG

543-557

11

QLSNGNRTLTL
RTLT

548-562

12

NRTLTLFNVTR
FNVT

553-567

13

LFNVTRNDARA
NDAR

558-572

14

RNDARAYVCGI
YVCG

563-577

15

AYVCGIQNSVS
QNSV

568-582

ANRS

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Table 4 (cont’d)

Peptide

Peptide

Location in CEA protein sequence

16
number

IQNSVSANRSD
sequence

573-587

17

SANRSDPVTLD
PVTL

578-592

18

DPVTLDVLYGP
VLYG

583-597

19

DVLYGPDTPIIS
DTPI

588-602

20

PDTPIISPPDSSY
PPD

593-607

21

ISPPDSSYLSGA
LS

598-612

22

SSYLSGADLNL
DLN

603-617

23

GADLNLSCHSA
SCHS

608-622

24

LSCHSASNPSP
SNPS

613-627

25

ASNPSPQYSWR
QYSW

618-632

26

PQYSWRINGIP
INGI

623-637

27

RINGIPQQHTQ
QQHT

628-642

28

PQQHTQVLFIA
VLFI

633-647

29

QVLFIAKITPNN
KITP

638-652

30

AKITPNNNGTY
NGT

643-657

31

NNNGTYACFVS
ACFV

648-662

32

YACFVSNLATG
NLAT

653-667

33

SNLATGRNNSI
RNNS

658-672

34

TGRNNSIVKSIT
VKSI

662-676

VSA

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Using an IFNγ ELISpot to measure CMI, we found several areas of epitope recognition
following rAd5-CEA + rAd5-rEA vaccination (Figure 21), as it produced significantly higher
levels of IFNγ-producing cells than naïve (p<0.05 for peptides #8, 24, 25; p<0.01 for peptide
#31) and rAd5-CEA + rAd5-GFP vaccinated (p<0.05 for peptides #24 and 25; p<0.01 for
peptide #8; p<0.001 for peptide #31) mice following splenocyte stimulation with four distinct
peptide epitopes.

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Figure 21

rAd5-CEA and rAd5-rEA co-vaccination induces CMI against multiple unique CEA peptide epitopes

126

Figure 21 (cont’d)
C57BL/6 mice (n = 9) were IM injected with 5x109 vp of rAd5-CEA and 5x109 vp of
either rAd5-GFP or rAd5-rEA. Splenocytes from vaccinated and naïve (n = 5) mice were
collected at fourteen days post-injection and examined by IFN-γ ELISpot where splenocytes
were divided and stimulated by a single CEA-derived peptide epitope per well (see Table 4 for
sequences). ELISpot analysis was completed by quantification of SFCs. CEA peptides that
induced greater amounts of SFCs in rAd5-CEA-treated animals than naïve animals are shown.
Bars denote mean ± standard error. *, ** denote significant difference from naïve group (p<0.05,
p<0.01 respectively). #, ##, ### denote significant difference from rAd5-CEA + rAd5-GFP
treatment group (p<0.05, p<0.01, p<0.001 respectively).

127

Independent of the particular CEA epitope, rAd5-CEA + rAd5-GFP was unable to
produce significantly higher amounts of IFNγ-producing cells than the other treatment groups
and, for all treatment groups, most CEA epitopes produced SFC counts close to baseline (Figure
22). These results suggest that rAd5-rEA co-administration with rAd5-CEA allows for a diverse
subset of CEA epitopes to be recognized by an adaptive CMI response.

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Figure 22

Addition of rAd5-rEA to an rAd5-CEA vaccine regimen induces CMI against multiple CEA peptide regions

C57BL/6 mice (n = 9) were IM injected with 5x109 vp of rAd5-CEA and 5x109 vp of either rAd5-GFP or rAd5-rEA.
Splenocytes were collected at fourteen days post-injection and examined by IFN-γ ELISpot where splenocytes were divided and
stimulated by a single CEA-derived peptide epitope per well (see Table 4 for sequences). ELISpot analysis was completed by
quantification of SFCs. Bars denote mean ± standard error.

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4.3.5 rAd5-CEA + rAd5-rEA co-injection enhances diversity of anti-CEA IgG antibodyidentified CEA peptide epitopes
While researchers have identified several T cell receptor-recognized CEA epitopes (257–
259), there are presently none conclusively verified to be recognized by B cell-based receptors.
In addition, previous vaccine prototypes targeting CEA have often been unable to induce
measurable amounts of anti-CEA IgG antibodies within patients’ blood serum (186,260). We
wished to see if the supplementation of rAd5-rEA to a rAd5-CEA injection would allow for a
more varied and detectable repertoire of CEA-binding IgG antibodies. To measure anti-CEA IgG
diversity, we collected serum isolated from mice that had been injected with 1x1010 total vp of
either rAd5-CEA + rAd5-rEA or rAd5-CEA + rAd5-GFP. Serum was pooled within treatment
groups and plated on wells that were coated with the aforementioned individual 15mer CEA
peptides (Table 4). In identifying values above the baseline optical density (OD) of 0.2
(measured value in wells without serum plated), ELISA analysis revealed that both rAd5-CEA +
rAd5-rEA and rAd5-CEA + rAd5-GFP treatments induced epitope recognition by anti-CEA IgG
(Figure 23), while naïve mice did not. However, in observing the number of CEA peptide
epitopes recognized by rAd5-CEA-vaccinated mouse serum IgG, there were clearly more unique
epitopes bound by immunoglobulins derived from mice given rAd5-rEA as compared to rAd5GFP (28 and 2, respectively). Furthermore, in the instances where rAd5-CEA + rAd5-GFP
vaccination did produce a significant amount of epitope-specific anti-CEA IgG, rAd5-CEA +
rAd5-rEA vaccination always produced a substantially higher IgG titer against those same
epitopes.

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Figure 23

rAd5-CEA and rAd5-rEA co-injection induces creation of IgG antibodies against a diverse area of CEA peptide

regions
C57BL/6 mice (n = 7) were IM injected with 5x109 vp rAd5-CEA and 5x109 vp rAd5-GFP or rAd5-rEA. Serum from
vaccinated and naïve (n = 5) mice was collected at 21 days post-injection. Serum dilutions (1:10) were pooled by treatment group and
plated on wells containing a single CEA-derived peptide epitope per well (see Table 4 for sequences). IgG levels against individual
CEA epitopes were measured by ELISA at 450nm OD. The inset graph demonstrates the amount of epitopes in each treatment group
that produced an OD value greater than 0.2, as this was the baseline OD measured in wells without serum plated.

131

To test if the addition of rAd5-rEA to the rAd5-CEA vaccine was inducing creation of
high affinity anti-CEA IgG antibodies, we next performed a urea-binding affinity ELISA using
the same serum samples mentioned above. Assay results revealed that the anti-CEA IgG binding
ability was high in both rAd5 treatment groups (Figure 24). Overall, these findings serve as a
novel instance where adjuvant treatment alongside a CEA-targeted vaccine increased the breadth
of durable anti-CEA B cell responses.

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Figure 24

High anti-CEA IgG binding affinity following rAd5-CEA and rAd5-rEA co-injection

C57BL/6 mice (n = 7) were IM injected with 5x109 vp rAd5-CEA and 5x109 vp rAd5-GFP or rAd5-rEA. Serum from
vaccinated and naïve (n = 5) mice was collected at 21 days post-injection. Serum dilutions (1:20) were plated on wells that had been
previously incubated with a CEA peptide pool. Following serum incubation, wells were briefly incubated with either PBS (untreated)
or an 8M urea PBS solution (urea-treated). (A) IgG levels against individual CEA epitopes were measured by ELISA at 450nm OD.
Bars denote mean ± standard error. * denotes significant difference between treatment group and naïve animals (p<0.05). #, ## denote
significant difference between rAd5 treatment groups (p<0.05, p<0.01, respectively). (B) Avidity binding ratios were individually
calculated and plotted as equaling (OD450[urea-treated sample] / OD450[untreated sample]).

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4.3.6 Enhanced in vivo CEA-targeted CTL killing following rAd5-CEA + rAd5-rEA coadministration
It is important to verify that the components of a multi-faceted, robust memory response
can be amplified against a TAA, but these constituents must also be functionally tested to
validate their practical anti-tumorigenic actions. To measure the amount of CEA-specific cell
killing that could be produced after use of an adjuvant such as rEA, mice vaccinated twenty-one
days prior with rAd5-CEA + rAd5-rEA or rAd5-CEA + rAd5-GFP, and Ad-naïve mice, were
injected with equal amounts of CEA- or AMQ-pulsed syngeneic splenocytes, which had been
labeled with high and low amounts of CFSE, respectively. Twenty-four hours following adoptive
transfer of peptide-loaded, CFSE-labeled splenocytes, mice were sacrificed and splenocytes were
prepared for measurement of the remaining CEA- (CFSEHigh) and AMQ- (CFSELow) pulsed cells.
Flow cytometry analysis revealed that the ratios of CEA:AMQ cells were no different between
naïve (Figure 25A) and rAd5-CEA + rAd5-GFP (Figure 25B) co-injected mice. In contrast,
splenocytes derived from rAd5-CEA + rAd5-rEA treated animals possessed a notably smaller
ratio of CEA:AMQ cells (Figure 25C), indicating more potent in vivo CEA-specific CTL
activity. Calculation of the percentage of specific CEA cell killing revealed that all animals
treated with rAd5-CEA + rAd5-rEA sustained some measurable level of specific cytotoxic
lymphocyte killing, while none of the rAd5-CEA + rAd5-GFP co-injected animals could
(p<0.001) (Figure 25D).

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Figure 25

rAd5-CEA and rAd5-rEA co-injection induces significant CEA-specific in vivo cytolytic T cell killing activity

135

Figure 25 (cont’d)
C57BL/6 mice (n = 7) were IM injected with 5x109 vp rAd5-CEA and 5x109 vp rAd5GFP or rAd5-rEA. At 21 days post-injection, syngeneic splenocytes were pulsed with CEAspecific peptides or AMQ and labeled with CFSEHigh (10μM) or CFSELow (1μM), respectively.
Immunized and naïve (n = 5) mice were injected with equal amounts of CEA- and AMQ-pulsed
splenocytes and, twenty-four hours following, mouse splenocytes were collected, washed, and
analyzed via FACS. Population percentages of low-CFSE AMQ-pulsed splenocytes and highCFSE CEA-pulsed splenocytes were compared in naïve (A), rAd5-CEA + rAd5-GFP (B), and
rAd5-CEA + rAd5-rEA (C) treatment groups. (D) Percentages of CEA-specific CTL killing was
compared

between

vaccine

groups

by

calculating

%

specific

killing

=

1

–

((%CEA/%AMQ)immunized/(%CEA/%AMQ)naive. (E) At the time of sacrifice, serum was collected
from these mice, diluted (1:100), and used to perform an anti-CEA ELISA to measure anti-CEA
IgG levels. The obtained (450nm) OD values from rAd5-CEA + rAd5-rEA were plotted against
respective percentages of CEA-specific CTL killing from each individual animal. The line
represents a calculated best-fit linear regression between variables.

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To investigate if the extent of the anti-CEA T cell and B cell responses may be
correlated, serum was collected at the same time as splenocyte collection and used to measure
anti-CEA IgG by ELISA. Since rAd5-CEA + rAd5-GFP treatment produced no assessable CEAspecific killing, we only compared the killing percentages of rAd5-CEA + rAd5-rEA treated
animals to their respective anti-CEA IgG titers. Linear regression analysis revealed a significant,
positive linear correlation (p = 0.0148; r = 0.8523) between the percent of CEA-specific killing
and anti-CEA IgG titers (Figure 25E). These findings suggest not only that the formulation of
rAd5-CEA vaccine with rAd5-rEA allows for measurable, functional CEA-specific cell killing,
but also that these actions correspond directly with levels of IgG antibodies against CEA.
4.4

Discussion
Creating a strong enough memory response against an often immune-tolerated TAA has

been a persistent issue of the cancer immunotherapy field since its inception (261). Alternatively,
researchers have observed that immunogenic treatments that are too aggressive can induce severe
systemic side effects, as was seen in the development of an inflammatory colitis following highdose autologous T cell transfer (254). Recombinant adenoviral delivery of tumor-associated
antigens has become a popular immunotherapy method, leading to the exploration of many
antigenic vaccine targets within numerous human clinical trials. This class of vectors serves as a
desirable option due to their ability to efficiently and exceptionally promote T cell memory
responses against expressed antigens, which is largely due to rAds’ ability to trigger
multidimensional innate immune responses (142,148,220). Recently, we have reported that the
use of an adenovirus vector encoding the gene CEA (rAd5-CEA) can be safely administered to
human subjects and may prolong survival of patients with advanced, chemotherapy-resistant
colorectal cancers by inducing potent anti-CEA-specific T cell immunity (186). In this current

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study, we wished to investigate if the efficaciousness of this same vaccine could be further
improved with the supplementation of a vector expressing the TLR agonist and anti-tumorigenic
protein, rEA. The adjuvant properties and human safety profile of rEA have been previously
established

(187,223,228),

therefore,

we

felt

that

the

characterization

of

rEA’s

immunomodulatory effects on a TAA-based vaccine were warranted.
Our first round of experiments included dosage studies so that the optimal therapeutic
viral dose could be estimated. The amount of total viral particles used ranged from 1x108 to
1x1010, which has been found to be appropriate for IM murine vaccination protocols in the past
(187,189,196). Generally, we found that increasing doses of rAd5-CEA + rAd5-rEA resulted in a
greater amount of CEA immune recognition, including stronger CMI (as quantified by the
amount of IFNγ- and IL-2-secreting splenocytes), greater amounts of CD8+ cytotoxic T cell
activation, and higher anti-CEA IgG titers. Considering these results, all future experiments were
performed at the 1x1010 vp dose. While the optimal amount of rAd5-rEA is greater than what we
had previously used to improve immunity against the HIV Gag protein (187), it is possible that
CEA is less immunogenic than HIV Gag or, that immunization against human CEA, which
shares significant homology to mouse CEACAM family proteins (262), may require a larger
treatment dose to induce the antigen-directed immune responses towards a protein sequence that
is similar one or more of the animal’s own intrinsic non-foreign, “self” proteins.
The amount of anti-Ad IgG was also measured among the vaccinated animals, finding
that the rAd5-CEA(6D) + rAd5-rEA combination also induced increased amounts of vectordirected antibodies within the animal’s serum. This is a notable finding due to the ongoing
concern of pre-existing Ad5 immunity negatively affecting vaccination outcomes, which was
most strikingly established following the early termination of the Merck HIV STEP trial (168).

138

While this issue cannot be ignored, it has been shown multiple times since that anti-Ad immunity
does not directly correlate with vaccine inefficacy, particularly in cases using modified versions
of Ad5 (186,194,211). Our rAd5-CEA(6D) vector is a second-generation, E2b-deleted virus and
has been verified, both in murine and human subjects, to induce anti-CEA immunity despite the
presence of Ad5 neutralizing antibodies (186,196). Moreover, the amount of anti-CEA CMI and
survival time of rAd5-CEA(6D)-vaccinated patients were found to have no association with the
serum titers of pre- or post-vaccination anti-Ad5 neutralizing antibodies (186); thus ameliorating
some concern over whether or not a paired rAd5-CEA(6D) + rAd5-rEA treatment would be
unsuccessful due to previous Ad5 exposure.
It has been observed that T cells from both healthy and tumor-burdened patients can
respond to a wide range of CEA derived antigens; it is a major therapeutic goal that vaccination
against CEA may break down immunologic tolerance to these antigens (253,263). Vaccine trials
where a single CEA epitope was targeted have reported having to exclude many patients who did
not meet HLA-matching criteria (264), limiting the vaccine’s treatable population. Alternatively,
a strong, multiregional repertoire of antigen epitopes could allow for a greater incidence of
efficacy across different HLA backgrounds and against multiple variants of CEA-expressing
malignancies (255,256). We tested if the adjuvant activities of rAd5-rEA could not only increase
the response to individual CEA-derived antigens, but also broaden this type of response to
greater numbers of CEA-derived antigens when paired with the rAd5-CEA vaccine. We found
that inclusion of an rEA-expressing vector along with a CEA-targeting vaccine induced
substantial CMI against several distinct CEA-derived peptides, including four documented
epitopes previously shown to be directly recognized by three distinct HLA haplotypes (257–
259). Interestingly, these haplotypes include class I and II HLAs, suggesting that rAd5-CEA +

139

rAd5-rEA co-vaccination may have the potential to activate not only CEA-directed CD8+ T
cells, but also effector CD4+ T cells, the numbers of which have been found to be strongly and
positively correlated with improved clinical outcomes of advanced malignancy patients (265).
However, verification of these notions will require further study in a humanized murine model or
human subjects.
While the importance of anti-TAA IgG development has been well established (241),
many CEA-targeting vaccine prototypes have been found to be unable to induce anti-CEA IgG
production above pre-treatment levels (186,260). In our work, while rAd5-CEA vaccination
alone was a weak inducer of anti-CEA humoral immunity (186), the combination of rAd5-CEA
with rAd5-rEA was able to create a significant amount of circulating serum anti-CEA IgG to
several peptide epitopes of CEA. According to the Immune Epitope Database and Analysis
Resource (www.iedb.org), there are over 100 confirmed immune epitopes derived from human
CEA protein, but as of yet none have been confirmed by B cell response assay, making further
investigation into the humoral promotion that rAd5-CEA + rAd5-rEA could provide even more
important.
Furthermore, rAd5-CEA + rAd5-rEA vaccinated animals also showed markedly higher
levels of CEA-specific killing, with the amount of CEA-specific in vivo CTL killing in rAd5CEA + rAd5-rEA vaccinated animals being positively correlated with the amount of anti-CEA
IgG detected in their serum. This suggests that induction of humoral and/or cell-mediated
adaptive immune responses against TAAs such as CEA are not mutually exclusive, and can be
promoted alongside each other using potent adjuvants such as rEA.
The molecular mechanisms by which innate immune modulators, such as rEA, assist in
the development of a strong immunological memory response are still in the process of being

140

understood (86). Many of the identified characteristics that make an adjuvant effective have been
detected in rEA, such as promotion of NK cell activation, increased amounts of DC
activation/maturation, induction of pro-inflammatory cytokines (e.g. IL-12(p70), TNFα), and an
overall robust Th1-skewing response (187,223,231,250). rEA also promotes relatively unique
agonist signaling mechanics in that it uses the TLR adapter protein MyD88 as a positive
regulator, and yet another TLR adapter, TRIF, as a negative regulator (231). While there have
been previous concerns regarding rEA’s immunogenicity as a profilin-like protein to be limited
to mammals that express functional TLR11/12, clinical trials and ex vivo human studies have
assuaged much of this concern, revealing there to be many TLR11/12-independent mechanisms
by which rEA triggers human immunity (223,228,250). Moreover, it has been recently confirmed
that human PBMC recognition of profilin is instead dependent on TLR5 (266); thereby
suggesting rEA may be recognized by this PRR as well. We have also shown that rEA can
directly activate human NK cells (250), a critical subtype of innate immune cells that perform
anti-tumor immune activities (17). Furthermore, rEA has been verified as safe to administer to
human patients, even those who may have advanced malignancies with compromised immune
systems (223,228); an attribute that is lacking for many other innate immune agonists (267).
With the knowledge that rEA is a robust innate stimulator, we explored the scope of
adaptive immunity that it could affect. While we have previously shown rAd5-rEA to promote
transgene immunity against the HIV Gag protein (187), this is the first time that co-injection of it
with a TAA-expressing Ad has been shown to have similar benefits. Furthermore, the
importance of gut microbiota (of which rEA is derived) and innate activation has been shown to
be essential in the response to several chemotherapy treatments (268,269), suggesting the use of
rAd5-CEA + rAd5-rEA alongside these medications may provide a substantially better clinical

141

outcome without making the treatment regimen more physically rigorous for the patient. As
phase II trials have already shown significant preliminary success with the use of rAd5-CEA in
advanced colorectal cancer patients, it is exceedingly relevant that an adjuvant which would
enhance anti-tumor effect to an even greater extent be considered. All in all, rAd5-rEA has the
possibility of serving as a conduit to a much larger and more diverse immune response against
CEA and a multitude of other TAA-expressing malignancies.

Acknowledgments
We wish to thank the personnel in Michigan State University’s laboratory animal support
facilities for their assistance in the humane care of animals utilized in this work. A.A. was
supported by the Michigan State University Osteopathic Heritage Foundation.

142

Chapter 5: Recombinant adenoviruses expressing antigen-trimming protein ERAP1 trigger
a robust innate immune response.

Portions of this chapter are derived from the previously published research articles:

Seregin SS, Rastall DP, Evnouchidou I, Aylsworth CF, Quiroga D, Kamal RP, GodbehereRoosa S, Blum CF, York IA, Stratikos E, Amalfitano A. Endoplasmic reticulum
aminopeptidases-1 alleles associated with increased risk of ankylosing spondylitis reduce HLAB27 mediated presentation of multiple antigens. Autoimmunity. 2013; 46(8):497-508.
Quiroga D – contributed towards HeLa cell transfection experiments and the measurement of
ERAP1 expression following transfection

143

5.1

Introduction
Endoplasmic reticulum aminopeptidase 1 (ERAP1) protein was first characterized for its

ability to trim and process antigens, thereby preparing them for MHC molecule loading (270).
Recently, it has also been implicated as the second-most pathologically-associated gene of the
autoimmune disease, ankylosing spondylitis (AS), a condition which causes inflamed, painful
vertebral joints and often disability (271). Approximately 0.5% of Americans will suffer from
this disease in their lifetime, yet the current treatment options available to patients are limited
and mainly palliative (271). Moreover, the pathogenesis of this disease is not well defined. It is
known that over 90% of AS patients are HLA-B27-positive, with twin studies showing there to
be approximately a 75% monozygotic to 27% dizygotic concordance rate (272). However, less
than 5% of the HLA-B27 positive population ever develops AS, which suggests that other genes
must be implicated in its development as well (272,273).
Genome-wide association studies (GWAS) have been able to link certain ERAP1
polymorphisms to the decreased likelihood of an HLA-B27-positive individual developing AS,
while other ERAP1 polymorphisms increased the likelihood of developing AS (271,274). The
exact functional mechanism of how these genes may bias an individual towards or away from
developing AS is unknown, although HLA-B27’s predisposition to misfold and allow for peptide
aggregation, particularly when ERAP1 is absent; suggesting that the endoplasmic reticulum
(ER)-based cellular stress reaction, known as the unfolded protein response (UPR), and/or other
inflammatory responses may be to blame (275–277).
ERAP1 has also been implicated in the pathogenesis of other diseases, such as
hypertension, inflammatory bowel disease, and psoriasis (278–280). Besides antigen processing,
ERAP1 is known to directly promote TNFα and IL-6 receptor shedding, therefore,

144

overexpression of ERAP1 may alter pro-inflammatory innate responses (281,282). Moreover,
TLR and/or LPS and IFNγ stimulation of murine macrophage RAW264.7 cells has been found to
promote ERAP1 extracellular secretion (283,284). Exposure of RAW264.7 cells to this secreted
form of ERAP1 was also shown to promote cellular phagocytosis activity, further supporting the
hypothesis that ERAP1 may have functional significance in the innate immune response (283).
In these studies, we wished to investigate the effects that the presence of low-AS risk and
high-AS risk ERAP1 alleles may have on UPR and pro-inflammatory signaling. To do this, we
constructed a HLA-B27 restricted HeLa cell model to examine intrinsic differences overexpression of low- or high-AS risk ERAP1 allele may induce upon UPR gene expression. We
also created rAd vectors to express the low- and high-AS risk ERAP1 alleles to study how UPR
and pro-inflammatory genes may react to ERAP1 overexpression. Finally, we tested the function
of macrophages exposed to ERAP1-expressing rAds in vivo and how low- or high-AS risk
ERAP1 expression may alter their in vitro phagocytosis activity. Our findings suggest ERAP1
overexpression does promote UPR-related gene expression and that high-risk ERAP1 expression
may induce a greater level of pro-inflammatory innate immune signaling; further implicating
ERAP1 with AS pathogenesis and innate immune signaling.

145

5.2

Methods

5.2.1 Cell transfection and culture
pTracer-CMV-RFP plasmids encoding either low- or high-AS risk human ERAP1 alleles
were created using a QuikChange II XL Site-Directed Mutagenesis kit (Stratagene, La Jolla, CA)
as per manufacturer’s instructions and as previously described (270,276). The high-AS risk
ERAP1 allele is the HeLa-endogenous sequence, with the low-AS risk ERAP1 allele differs from
it at five amino acid positions: M349V, K528R, D575N, R725Q, and Q730E. All of these
polymorphisms were previously identified in GWASs to be significantly associated with the
increased risk of AS diagnosis (285,286).
HeLa-Kb-B27/47 cells were cultured at 3x105 cell/well on 6 well plates in high-glucose
DMEM media (Life Technologies) supplemented with 10% FBS, 100 μg/mL Geneticin (Life
Technologies), 100 μg/mL Zeocin (Invivogen), and 500 μg/mL Hygromycin (Life
Technologies). HeLa-Kb-B27/47 cells were transfected with 1 μg low AS-risk (ERAP1_low) or
high-AS risk (ERAP1_high) ERAP1-containing plasmids using the HeLA-specific TransIT
HeLaMonster transfection kit (Mirus Bio LLC, Madison, WI). Transfection efficiency was
typically observed by flow cytometry as 5-10% RFP-positive cells (287). RNA and protein
samples were collected at 24 hours post-transfection (hpt).
THP-1 monocytes were cultured in DMEM media (Life Technologies) supplemented
with 10% FBS and 1x PSF. Monocytes were differentiated to macrophages by application of 1
μg/mL phorbol myristate acetate (PMA) for twelve hours, after which media was changed and
macrophages were left PMA-free for twelve hours prior to treatment. RAW264.7 macrophages
were cultured in RPMI 1640 (Life Technologies) containing 10% FBS.

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5.2.2 Recombinant adenovirus construction and cell infection
ERAP1_low and ERAP1_high gene open reading frames were inserted within CMVdriven pShuttle cassettes, then linearized, recombined, and propagated within BJ 5183 cells
using a pAdEasy system, as previously described (182,205,206). The resulting Ad5-ERAPlow
and Ad5-ERAPhigh vector titers were quantified by spectrophotometry. Ad5 gene region
deletions were confirmed by PCR, as previously described (182). All viral vectors were tested
and validated as having <0.01 EU (per injection dose) bacterial endotoxin contamination, as
previously described (208).
5.2.3 RNA extraction, cDNA synthesis, and quantitative RT-PCR
Cellular RNA was extracted using TRIzol reagent (Life Technologies), as detailed in
manufacturer’s manual. cDNA was synthesized by reverse transcription using SuperScript III
First-Strand Synthesis SuperMix (Life Technologies) as per manufacturer’s instructions.
Quantitative RT-PCR was performed and analyzed using SYBR Green PCR Mastermix (Life
Technologies) on an ABI 7900HT Fast Real-Time PCR System (Life Technologies) as
previously described (189,209). Primers used to detect cellular gene expression were designed
using the online PrimerBank database (http://pga.mgh.harvard.edu/primerbank) (Table 5). To
measure relative gene expression, GAPDH and the comparative Ct method were used for all
samples. Induction of gene expression was calculated as the relative change from the level of
mock-treated cell transcripts to the level of rAd-treated cell transcripts.

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Table 5

Quantitative RT-PCR primers for ERAP1 studies

Primers were designed using PrimerBank online software. Primer sequences are written
5’ to 3’.

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5.2.4 Protein isolation and western blotting
HeLa-Kb-B27/47 cells were mock transfected or transfected with pTracer-CMV-RFP,
pTracer-CMV-RFP-ERAP1_Low, or pTracer-CMV-RFP-ERAP1_High. Protein was harvested
using lysis buffer (20mM Tris-HCl, pH 7.4, 1mM EDTA, 150mM NaCl, 1% Triton X-100, 1x
protease inhibitor) at 24 hpt. Protein was isolated by centrifugation and quantified by BCA, as
previously described (231).
Equal amounts of protein were run and separated electrophoretically using 7%
polyacrylamide gels. Protein bands on the gels were transferred onto nitrocellulose membranes,
then probed using a mouse anti-human tubulin monoclonal primary antibody (Sigma-Aldrich)
and a polyclonal rabbit-anti-hERAP1 (Proteintech, Chicago, IL). Following incubation with
primary antibodies, IRDYE800-conjugated goat anti-mouse IgG (Rockland) and Alexa Fluor
680-conjugated goat anti-rabbit IgG (Invitrogen) were used as detection secondary antibodies.
Membranes were scanned for protein bands using a LI-COR Odyssey scanner and software (LICOR Biosciences, Lincoln, NE). Fluorescence of the samples’ tubulin bands were used to
normalize ERAP1 protein levels.
5.2.5 In vitro phagocytosis assay
Measurement of in vitro phagocytosis activity was completed using a phagocytosis assay
kit (FITC) (Cayman Chemical, Ann Arbor, MI). Briefly, RAW264.7 macrophages were cultured
at 3x104 cells/well and were either mock infected or infected with 20,000 vp/cell control rAd5,
Ad-ERAPlow, or Ad-ERAPhigh. At 48 hpi, cells were washed with PBS and given fresh cell
media containing 2.5 μL FITC-labeled bead stock per 1 mL media. 18 hours following bead
application, cells were harvested, washed, and resuspended in FACS buffer. The quantity and

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intensity of FITC-positive cells was measured by FACS analysis using an LSRII flow cytometer
and FlowJo software (Tree Star).
5.2.6 Statistical analysis
Statistical significance all other data was determined using one-way ANOVAs with
Newman-Keuls post-hoc corrections, unless otherwise stated. Graphs in this chapter are
presented as mean ± standard error. Statistical analyses were performed using GraphPad Prism
(GraphPad Software).

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5.3

Results

5.3.1 ERAP-1 expression following transfection of HeLa-Kb-B27/47 cells
We utilized a previously described HeLa cell model (HeLa-Kb-B27/47) to stably express
human HLA-B27, murine H-2Kb, and a TAP1 blocker (herpesvirus protein ICP47) to allow only
for peptides that possess a specific ER-localization sequence to be substrates for ERAP1-based
HLA-B27 antigen loading (276,287–290). To test the function of this system, we transfected
HeLa-Kb-B27/47 cells with RFP (control plasmid), ERAP1_Low (low-AS risk ERAP1 allele),
or ERAP1_High (high-AS risk ERAP1 allele) plasmids or performed a mock transfection on
them. Following collection of RNA and protein samples at 24 hpt, we found there to be no
significant differences in the amount of ERAP1 gene (Figure 26A) or protein expression (Figure
26B,C) following ERAP1_Low or ERAP1_High plasmid transfection. Both ERAP1 plasmids
expressed approximately 700 times the ERAP1 RNA and 4 times the ERAP1 protein
concentration as the endogenous HeLa-Kb-B27/47 ERAP1 amounts. This indicates that it is
unlikely that ERAP1_Low or ERAP1_High alleles create more or less ERAP1 production or
persistence at the transcriptional and translational levels. RFP, our control plasmid, failed to
produce a significantly greater amount of ERAP1 RNA or protein than mock, indicating that the
transfection process alone was not inducing significant amounts of ERAP1 expression.

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Figure 26

ERAP1 expression following HeLa-Kb-B27/47 transfection

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Figure 26 (cont’d)
HeLa-Kb-B27/47 cells were mock transfected or transfected with plasmids expressing
RFP, ERAP1_Low, or ERAP1_High alleles. RNA and protein were harvested from samples at
24 hpt. (A) ERAP1 mRNA levels were measured using RT-PCR quantification. (B,C) ERAP1
protein concentrations were measured by Western blot. Bars denote mean ± standard error. *
denotes a significant difference between that group and mock-transfected cells (p<0.05).

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We used this model to test if low- and high-AS risk ERAP1 alleles express different
levels of genes previously identified as overexpressed by AS patients in GWAS studies. To test
this, HeLa-Kb-B27/47 cells were mock transfected or transfected RFP, ERAP1_Low, or
ERAP1_high plasmids, then harvested at 24 hpt to measure expression of other AS and UPRrelated genes. The genes we chose to test were the ones most strongly related to genes
differentially expressed in mammalian models of HLA-B27-induced spondyloarthropathies,
particularly after IFNγ-triggered UPR activation; these include viperin, CHOP, HLA-B, and
IRF1 (291–293). We found that introduction of the RFP plasmid into HeLa-Kb-B27/47 cells
resulted in significant inductions of viperin (p<0.05), CHOP (p<0.01), HLA-B (p<0.001), and
IRF1 (p<0.01) over mock transfection (Figure 27). However, ERAP1_Low and ERAP1_High
allele plasmid-transfected cells did not produce significantly different gene expression patterns
from each other or from the control RFP plasmid-transfected cells; possibly suggesting that it
may be possible the transfection procedure alone could induce these genes and mask any effects
that the ERAP1 plasmids may have induced.

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Figure 27

Expression of AS-related genes in ERAP1-transfected HeLa-Kb-B27/47 cells

HeLa-Kb-B27/47 cells were mock transfected or transfected with plasmids expressing
RFP, ERAP1_Low, or ERAP1_High alleles. RNA was harvested from samples at 24 hpt and
analyzed by RT-PCR quantification for gene expression. *, **, *** denotes a significant
difference between that group and mock-transfected cells (p<0.05, p<0.01, p<0.001,
respectively).

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5.3.2 Ad-ERAPlow and Ad-ERAPhigh activation of AS-related gene immune responses
Considering the results we found with our HeLa-Kb-B27/47 system, we decided to test if
ERAP1_low and ERAP1_high could promote altered responses in another cell system. We
selected to use macrophage-differentiated THP-1 cells as a model to study in vitro ERAP1_Low
and ERAP1_High differences as these cells are functionally more similar to in vivo human
professional APCs. We also wished to allow for a longer-term and constitutive expression of the
ERAP1 genes, therefore, we constructed rAd5[E1-] vectors expressing the low- and high-AS risk
ERAP1 alleles (Ad-ERAPlow and Ad-ERAPhigh, respectively), as previously described
(172,205,206,209).
To test if low- and high-risk ERAP1 alleles could induce the expression of other ASrelated genes when introduced by rAd5 vectors, we mock infected or infected THP-1
macrophages for 24 hours with a control rAd5 vector, Ad-ERAPlow, or Ad-ERAPhigh. Gene
expression of the viperin, CHOP, HLA-B, and IRF1 UPR-related genes, two additional UPRrelated genes (BiP and XBP1s), and IFIT1 and IFIT2 innate immune and UPR components, was
measured as conducted previously (293–295,292). Compared to mock and control rAd5-treated
cells, gene expression in Ad-ERAPhigh treated cells were able to induce significantly greater
amounts of viperin (p<0.001, p<0.01, respectively) , BiP (p<0.01), CHOP (p<0.01), HLA-B
(p<0.05 with mock-treated cells), IFIT1 (p<0.001), IFIT2 (p<0.001), IRF1 (p<0.001), and
XBP1s (p<0.05) (Figure 28). Ad-ERAPlow treated cells were also able to induce several ASrelated gene expression over mock and control rAd5-treated cells, including viperin (p<0.01),
BiP (p<0.01), CHOP (p<0.05, p<0.01, respectively), IFIT1 (p<0.001), IFIT2 (p<0.001), and
IRF1 (p<0.001). It was also noted that the control rAd5 infection induced significantly greater

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amounts of viperin (p<0.01), IFIT1 (p<0.01), IFIT2 (p<0.001), and IRF1 (p<0.01) gene
expression than mock treatment, which is consistent with previous rAd5 studies (141,148).

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Figure 28

Ad-ERAPlow and Ad-ERAPhigh induce AS-related gene expression

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Figure 28 (cont’d)
THP-1 macrophages were mock infected or infected with a control rAd5 vector, AdERAPlow, or Ad-ERAPhigh at 20,000 vp/cell. At 24 hpi, RNA was isolated for RT-PCR
quantification of Ad gene expression. Bars denote mean ± standard error. *, **, *** denote
significant differences between that group and mock-treated samples (p<0.05, p<0.01, p<0.001
respectively). #, ##, ### denote significant differences between Ad treatments (p<0.05, p<0.01,
p<0.001 respectively).

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5.3.3 Phagocytosis activity of RAW macrophages following Ad-ERAP stimulation
Following the confirmation that Ad-ERAPlow and Ad-ERAPhigh vectors were able to
promote production of genes which are upregulated in association with AS diagnosis, we wished
to test if these vectors could also promote functional in vitro differences in macrophages.
Previous studies have shown that exogenously-introduced ERAP1 protein can stimulate murine
RAW264.7 macrophage phagocytosis activity (283). Therefore, we wished to test if endogenous
introduction of low- and high-AS risk ERAP1 alleles via rAd5 would also induce phagocytosis
actions in a macrophage cell line. RAW264.7 cells were either mock infected or infected with a
control rAd5, Ad-ERAPlow, or Ad-ERAPhigh. The day after infection, FITC-labeled beads were
applied to each sample. Following bead incubation, macrophages were collected and washed to
measure the amount of cells that had internalized FITC-labeled beads and the amount of beads
engulfed per cell. We found that bead application alone induced about a 28% rate of
phagocytosis and that application of an rAd5 vector to these cells increased this rate to ~ 37%,
while also increasing the amount of beads each cell was able to engulf, as measured by MFI
(p<0.001) (Figure 29). Moreover, it was observed that a greater percentage of RAW264.7
macrophages treated with Ad-ERAPlow or Ad-ERAPhigh vectors, as opposed to mock
treatment, were activated to phagocytose the FITC-labeled beads upon application (p<0.001).
Ad-ERAPlow or Ad-ERAPhigh treated cells also phagocytosed a larger average amount of beads
per cell (p<0.001). In comparing the amount of phagocytically-active macrophages and the
concentration in which they engulf FITC-labeled beads, we found that Ad-ERAPhigh treatment
resulted in significantly greater phagocytosis activity than Ad-ERAPlow (p<0.05, p<0.01,
respectively).

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These studies were also attempted using the THP-1 cell line, but due to PMA stimulation
required to differentiate THP-1 monocytes to macrophages, these cells were immunologically
activated prior to infection. This effect was so strong that even the mock-treated cells were
stimulated so to allow for close to 100% of the applied FITC-beads to be engulfed (data not
shown).

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Figure 29

Ad-ERAPlow and Ad-ERAPhigh stimulate RAW macrophage phagocytosis

activation

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Figure 29 (cont’d)
RAW264.7 macrophages (n=3) were mock infected or infected with 20,000 vp/cell
control rAd5, Ad-ERAPlow, or Ad-ERAPhigh, then treated with FITC-labeled beads. At 18
hours post-bead application, cells were harvested to measure the quantity (percent of FITC+
cells) and intensity (MFI) of FITC-positive cells using FACS analysis. Bars denote mean ±
standard error. *** denotes significant differences between that group and samples not treated
with beads (p<0.001). ^^^ denotes significant differences between that group and the mock
treatment group (p<0.001). #, ##, ### denote significant differences between Ad treatments
(p<0.05, p<0.01, p<0.001 respectively).

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5.4

Discussion
Originally characterized as only a processor of MHC-antigen loading, human ERAP1 has

been implicated in a variety of processes, from cytokine receptor shedding to anti-viral miRNA
degradation (281,282,296). It seems that many of its disease-related roles are double-sided, in
that ERAP1 can either increase or decrease the risk of pathogenesis; dependent upon the ERAP1
polymorphism that an individual carries (272,274,297,298). Recently, our group has also found
that ERAP1 is able to skew the selection of which epitopes will be immunodominant in APC
presentation and can alter the balance of which type of memory T cell response will be
developed (299). Although ERAP1 clearly demonstrates association with polymorphismdependent immune alterations, the mechanism by which it acts on these systems is currently
unknown.
In this chapter, we used an HLA-B27-expressing HeLa cell model to test the expression
of ERAP1 low- and high-AS risk variants following their introduction by plasmid transfection.
We found that this method was able to induce about a 500-1000 fold induction of ERAP1 mRNA
expression and about a 3-4 fold induction of ERAP1 protein expression, independent of which
ERAP1 variant plasmid was used. These similarities reveal that it is unlikely that the differences
between low- and high-AS risk ERAP1 alleles due to differences in the protein’s naturallyoccurring transcriptional or translational levels, but instead are caused by altered ERAP1
functions. Our group also conducted further experiments with the HeLa-Kb-B27/47 cell system
in which low- and high-AS risk ERAP1 plasmids were co-transfected with selected peptide
epitopes; revealing that the high-AS risk ERAP1 variant degrades HLA-B27-specific epitopes at
a greater rate, is less efficient at loading those epitopes onto HLA-B27 molecules, and, overall,
decreases HLA-B27 surface expression of to a greater extent than the low-risk ERAP1 variant

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(287). The idea that high AS-risk ERAP1 alleles may have an increased rate of peptide
processing to blame for functional differences between the variants is supported by previous
preliminary studies that have suggested low-AS risk ERAP1 polymorphisms possess decelerated
peptidase activity rates (274).
The UPR is an important cellular stress response, induced by accumulation of
dysfunctionally-folded proteins in the ER lumen, that allows for cellularly-resuscitative measures
to take place and clear compartmental aggregates before proceeding towards apoptosis signaling
(300). It is believed that neurological diseases characterized by over-accumulation of
harmful/misfolded protein products (e.g. Alzheimer’s disease, Parkinson’s disease) could be
linked to UPR inhibition (301,302), however, excessive UPR signaling may also be to blame in
the inflammatory pathogenesis of other diseases, including spondyloarthropathies like AS
(293,303,304).
In studying the UPR in our HeLa-Kb-B27/47 cell system, we were able to see inductions
of multiple UPR genes upon ERAP1_Low and ERAP1_High plasmid transfection. However, as
these genes were also upregulated upon RFP control plasmid transfection, it was realized that
due to the nature of the transfection procedure and/or the efficacy of this cell model, there may
have been other ways to more opportunistically study the ERAP1-UPR interactions.
Additionally, we recognized the importance of measuring low- and high-AS risk ERAP1 effects
in a non-HLA-B27-dependent environment and, also, in an APC model so that the cells in which
ERAP1’s antigen processing activities are most utilized may be examined (270,281,288).
While several UPR-related genes were found to be upregulated by rAd expression of
ERAP1, production of the high-AS risk allele allowed for a more robust induction of those UPR
genes that have also been implicated in interferon-inducible innate immunity. Interestingly, Ad-

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ERAPhigh treatment also increased the amount and breadth of in vivo macrophage activation as
compared to Ad-ERAPlow treatment, although both did induce high levels of phagocytosis from
baseline and the mean difference in the amount of cells that phagocytosed FITC-labeled beads
between the two treatment groups was only about 2.5%. Whether this amount of variance is
noteworthy, or if larger discrepancy may be observed in a human macrophage line or in vivo
animal model, would require further validation.
Like other gene products activated during innate immunity, ERAP1 expression is
triggered by exposure to TLR agonists and pro-inflammatory cytokines (270,283,284). The
understanding of ERAP1 as more than just a step along the antigen processing and loading path
is still developing, and from our results, it seems likely that these “non-traditional” roles may
play a larger part in how ERAP1 protects or predisposes an individual from/to specific, ERAP1
linked diseases.

Acknowledgments
We wish to thank the personnel in Michigan State University’s laboratory animal support
facilities for their assistance in the humane care of animals utilized in this work. A.A. was
supported by the Michigan State University Osteopathic Heritage Foundation.

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Chapter 6: Summary and future directions

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The modern development of vaccines cannot be undertaken without thorough
consideration of each human immune response component and how vaccine formulations may
manipulate them. From the initial physical barriers that microbes must pass to enter the human
body, to epitope-specific adaptive targeting of pathogenic antigens; the interplay of each cell
type, signaling pathway, and cytokine expressed combine to result in a complex immune system
activation milieu. Thus, vaccine researchers are employed with the task of developing vaccine
components that direct an individual towards the types of immune responses thought to be
needed for an effective immune response against antigens present in harmful microbes and/or
tumor cells (305). In this dissertation, we discussed the immunogenic properties that both
recombinant adenovirus vaccine vectors and TLR agonist-based adjuvants possessed, while also
introducing novel methods and mechanics by which these constituents may be effectivity
utilized.
In Chapter 2, we compared the biological and innate immune characteristics of firstgeneration Ad5[E1-] and second-generation Ad5[E1-,E2b-] vectors. These rAd5 vectors only
differ by an additional deletion of the E2b transcriptional region; a sequence that encodes the
necessary genes for Ad5 DNA polymerase and PTP synthesis. This small modification within the
Ad5[E1-,E2b-] platform has been shown to result in several advantageous vaccine properties as
compared to Ad5[E1-] vectors; including lower hepatotoxicity, longer in vivo persistence, and
decreased expression of viral proteins (131,138,181,182). Perhaps most desirable, Ad5[E1-,E2b] vector activities are not as easily disabled by pre-existing anti-Ad5 immune responses as
Ad5[E1-] vectors are; a phenomena often thought as being due to the “leaky” Ad5[E1-] viral
protein expression that doesn’t substantially exist with Ad5[E1-,E2b-] vectors (181,183–186).

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Looking back on these previous studies, Ad5[E1-] and Ad5[E1-,E2b-] vectors have
mainly been compared for their divergences in adaptive immune responses. Alternatively, we
wished to compare the early, innate responses induced by Ad5[E1-] and Ad5[E1-, E2b-]. Prior to
experimentation, we analyzed previously published mouse liver RNA microarray data to
determine if there were differences between animals given Ad5[E1-] or Ad5[E1-, E2b-] vectors
and at which time-point after infection did they occur. While the large majority of the Ad5[E1-]
and Ad5[E1-,E2b-] vector-induced transcriptomes were similar, there were several significant
gene groups induced at a higher amount than the other vector. We found that most Ad5[E1-] and
Ad5[E1-,E2b-] vector differences occurred within the first day of infection and mainly
disappeared by 3 dpi, suggesting that the dissimilarities between rAds are more likely to be based
upon an early, innate responses.
To test this hypothesis, we gathered blood samples from 17 independent human donors.
Utilizing a large number of blood samples not only increased our sample size, but also allowed
us to obtain serum and T cells from individuals with varied amounts of anti-Ad5 antibodies and
CTLs; therefore, these adaptive components could be compared side-to-side with the innate
hPBMC products. In measuring the cytokines secreted from these blood donor samples after they
were infected with mock, Ad5[E1-], or Ad5[E1-,E2b-] vectors, we found a surprisingly unified
pro-inflammatory cytokine signaling pattern. For IL-1β and TNFα expression, Ad5[E1-,E2b-]
vector infection served as a significantly greater stimulant than Ad5[E1-]. When these cytokine
responses were plotted against the same donor’s anti-Ad5 IgG titer and anti-Ad5 CD8+ CTL
levels, we found no association between the amount of pre-existing Ad5 immunity and the
measured cytokine responses measured after rAd5 infection (by either Ad5[E1-] or Ad5[E1,E2b-] vectors). These data strongly argue that the functional differences between Ad5[E1-] and

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Ad5[E1-, E2b-] are not completely attributed to adaptive anti-Ad5 responses, but also to more
intrinsic innate response differences between the vectors.
We further compared these first- and second-generation rAd vectors by measuring levels
of Ad-specific gene expression and found that the Ad5[E1-] vectors produced tremendously
greater amounts of both early and late Ad5 gene products than Ad5[E1-, E2b-] did. Interestingly,
innate immune gene induction triggered by Ad5[E1-, E2b-] vector treatment was generally
higher than Ad5[E1-] vector-treated cells. Moreover, cells infected with Ad5[E1-] vectors
produced such blunted expression of the pro-inflammatory IFIT1 gene that the levels were
significantly lower than that which was produced by cells infected with an rAd5 vector lacking
any Ad genes (HD-Ad5). With this in mind, it appears that Ad5[E1-] vector infection may even
promote inhibition of certain innate immune responses.
. Future studies to characterize these potential inhibitory signals and how they can be
modulated to create an immunogenic, but safe, viral platform would serve as important tools to
more thoroughly understand how a beneficial vaccine response can be mounted. In upcoming
investigations, determining the mechanism by which Ad5[E1-] and Ad5[E1-,E2b-] vectors
differentially trigger innate immunity should be a prioritized goal. The methods and problemsolving approach by which such a task could be completed are diverse. For example, a more
extensive immune gene and cytokine expression profile could be obtained further comparing
Ad5[E1-] and Ad5[E1-,E2b-] infected hPBMCs; this may help to indicate which specific
pathways are being utilized differently between vectors. Experiments could also be conducted to
investigate if greater expression of certain Ad5 genes (e.g. VARNA, hexon) by Ad5[E1-] over
Ad5[E1-,E2b-] may be leading to the early, pro-inflammatory dissimilarities.

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In Chapter 3, we examined the characteristics a novel Eimeria tenella-derived TLR
agonist, rEA, which has the ability to activate and mature many innate immune cells when
delivered exogenously as a purified protein. From this work, we were able to conclude that
TRIF-KO can promote rEA-stimulatory activities to a greater extent than even WT mice,
suggesting that TRIF acts as a sort of inhibitor against rEA immunostimulatory effects.
Alternatively, MyD88-KO and MyD88/TRIF-DKO animals completely lacked any rEAmediated innate stimulation, suggesting that MyD88 is essential for rEA early signaling. These
findings support the current hypothesis that rEA is highly homologous to the TLR11 agonist,
profilin; not only in protein sequence, but also in immune-induced responses (229). Similar to
other TLR ligands, profilin-like protein recognition by TLR11 had previously been found to be a
significant, MyD88-dependent process by which the innate and CMI could be stimulated (306).
Since the publication of the Chapter 3 results, it has been found that while humans do not
produce functional TLR11 (230), profilin proteins can be recognized by and trigger activation of
human TLR5 (266). As rEA shares significant homology to profilin and other profilin-like
proteins (223,229), this seems likely to be the MyD88-dependent pathway in which it promotes
pro-inflammatory signals. Moreover, other researchers have found that TLR11 can be activated
by the introduction of flagellin, which has traditionally been viewed as a TLR5 agonist (307).
While TLR5 and TLR11 both signal through the MyD88 adaptor protein, TLR5 has been
identified as a plasma membrane-bound receptor, while TLR11 is believed to reside mainly in
endolysosomal compartments within the endoplasmic reticulum (308). Whether rEA actually is a
human TLR5 ligand and if detection of rEA extracellularly versus within endolysosomal
compartments may alter the type of immunity it produces are questions that would be beneficial
to answer in future pre-clinical studies. For example, our group has also published findings in

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which mice were injected with either rEA protein or the rAd5-rEA vector. Both groups were
found to have significant inductions of many pro-inflammatory cytokines, however, rAd5-rEA
vectors produced a much more significant quantity of response and stimulation (187). This may
be due to the fact that vectors can promote a more robust production of its transgene and/or that,
by being immunogenic itself, a transgene-expressing rAd5 may be expected to be more proinflammatory (148,171). However, it is also possible that, due to endosomal TLR11 positioning
(308), internalized rAd5-rEA vectors have better access to this PRR than extracellularlyintroduced rEA protein. Whether these differences in TLR cellular locations may or may not be a
factor in rEA-triggered immunity, it is, nevertheless, important to consider during future TLR
agonist studies.
We also worked to create an rEA-expressing rAd5 vector, which was found to promote
co-injected transgene memory responses of such pathogens as the HIV Gag protein. In Chapter
4, rAd5-rEA was used alongside a therapeutic colorectal cancer vaccine that is currently in phase
IIb clinical trials, rAd5-CEA (186). As CEA is a highly sensitive marker for colorectal cancer, is
overexpressed in many other carcinomas, and possesses some natural immunogenicity, it has
become one of immunotherapy researchers’ favorite TAA targets (241). While rAd5-CEA trials
have shown promising inductions of anti-CEA CMI, as well as increased survival rates in the
patients given higher doses of this vector (186), we believe this response could be heightened
even more with the introduction of the adjuvant, rEA. Throughout our studies, murine injection
of rAd5-CEA + rAd5-rEA was compared in a variety of ways to the control vaccine protocol,
rAd5-CEA + rAd5-GFP. Both rAd5 vaccine combinations induced dose-dependent increases in
the amount of CEA-specific CMI, CTL, and IgG production, but the rAd5-CEA + rAd5-rEA

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treatment provided the most superior amounts of each of these factors when utilized at the
highest dose (1 x1010 vp total).
After establishing a greater intensity of anti-CEA cell-mediated and humoral adaptive
immune responses following rAd5-CEA + rAd5-rEA vaccination, we characterized the diversity
of the response. We found that rAd5-CEA + rAd5-rEA vaccination of mice promoted
recognition of several CEA epitopes, whereas rAd5-CEA + rAd5-GFP produce a more narrow
scope of antigenic epitopes, as seen with both CEA-directed CMI and CEA-neutralizing IgG
antibodies. Finally, an in vivo CTL killing assay was also used to verify that rAd5-CEA + rAd5rEA vaccination effects could translate to functional recognition and killing of TAA-expressing
cells.
Considering these encouraging results, the next pre-clinical step to take this vaccineadjuvant combination treatment would be to an animal tumor model. Past rAd5-CEA studies
have utilized a C57BL/6 murine-derived colon adenocarcinoma cell line that has been modified
to express human CEA on its surface (MC38-cea2) to test its anti-tumor vaccine efficacy (196),
so this would serve as an appropriate model to conduct such an experiment for rAd5-CEA +
rAd5-rEA vaccination studies as well. Additionally, it may be advantageous to use human CEAtransgenic mice so to more accurately replicate the spatiotemporal pattern in which colorectal
cancer patients typically express CEA and other TAAs (309,310).
When developing new adjuvants and vaccine models for cancer immunotherapy, it is also
important to consider the potential side effects of excessive immune stimulation or induced
autoimmune reactions. While current rAd5-CEA clinical trial participants have not complained
or presented with serious side effects, there have been cancer immunotherapy trials in the past in
which severe autoimmune patient reactions have occurred, with one testing a CEA-specific

173

adoptive T cell transfer treatment that lead to an acute, autoimmune colitis (109,254). In future
studies, this vaccination protocol and others should be monitored within in vivo models for signs
of such exorbitant and toxic autoimmune effects.
In Chapter 5, we briefly examined the implications of low- and high-AS risk ERAP1
alleles and how the small polymorphic differences between them may lead to altered UPR and/or
innate immune responses by infecting cell cultures with ERAP1-expressing vectors specific to
each allele. Within Ad-ERAPhigh vector-infected macrophage lines, we were able to measure
significant upregulation of genes associated with both pro-inflammatory and unfolded protein
responses over that seen in macrophages administered the Ad-ERAPlow vector. Also, AdERAPhigh vector infection promoted significantly greater levels of macrophage phagocytosis
activity, further implicating that the high-AS risk allele may induce a stronger innate immune
response than other ERAP1 polymorphisms. Our group is currently conducting extensive
research using human ERAP1 transgenic mice and other applicable models that will be useful for
the characterization of ERAP1’s novel immunologic roles. Additional clinically-relevant
experiments that could be conducted to study AS-related ERAP1 alleles are ones in which blood
and tissue samples are obtained from symptomatic AS patients and compared for innate immune
and UPR-related gene and protein expression differences, as compared to samples from persons
without AS.
In summation, this dissertation includes several promising studies and results for the
fields of vaccinology and cancer immunotherapy. We showed that first-generation rAd5 vectors,
which have received considerable criticism in the past for some of their detrimental side effects
and inefficacies, can be re-engineering into E2b-deleted second-generation rAd5 vectors that
break past many of these barriers. We also extensively studied the properties of TLR agonist

174

rEA, both alone and alongside a cancer vaccine platform. Lastly, we touched on some of the
work we completed regarding the antigen-processing ERAP1 protein and how it may modulate
cellular stress and innate immune pathways. All together, these studies highlight many of the
methods by which innate immunity directly and indirectly plays a role in the synthesis of a
valuable, robust memory vaccine response.

175

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