View Studies Using a Murine Social Stress Model to Elucidate the Peripheral and Central Effects of Stress in the Absence and the Presence of Immune Challenge

Social Stress Induces Immunoenhancement During Allergic Airway Inflammation and Infection

Dissertation

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Brenda Faye Reader, B.A.

Integrated Biomedical Science Graduate Program

The Ohio State University

2013

Dissertation Committee:

Dr. John F. Sheridan, Advisor

Dr. Michael T. Bailey

Dr. Jonathan P. Godbout

Dr. John Walters

Brenda Faye Reader

2013

Abstract

Stress is commonly considered to be immunosuppressive, but in some

diseases states, such as asthma or infection, stress can be immunoenhancing.

This immunoenhancement has been associated with immune cell glucocorticoid

resistance that renders the cells insensitive to the anti-inflammatory effects of

glucocorticoids. A unique murine social disruption stress paradigm, SDR, can

model the stress-induced glucocorticoid resistance and exacerbation of

inflammation, which can be relevant to inflammatory diseases in humans. In the

context of SDR, stress enhances inflammation and delays resolution in an

Aspergillus fumigatus (Af) allergic airway inflammation model. In stressed and Af

challenged mice, gene expression data suggested increased inflammation (IL-1β,

TNF-α, GM-CSF) with histological data supporting that the increase was due to infiltrating inflammatory cells. Furthermore, stress and Af challenge most prominently increased granulocytes in the lung compared to controls. Bone marrow chimeras demonstrated that the increase in immune cells was bone marrow-derived, and that stress induced myeloid progenitor cell egress and trafficking to lung. Closer examination of the granulocytic population identified many as neutrophilic populations. Using the antibodies to CD16 and CD49d,

several distinct neutrophil populations were visualized including apoptotic,

mature, activated, or immature neutrophils. Stress and Af challenge significantly increased the immature neutrophil population in both the lung and blood. In the clinic, it has been shown that a rapid release of immature neutrophils from the bone marrow can occur during times of stress and immune challenge. The consequences of this state of neutrophilia on disease are still being determined, but it is known these neutrophils have a higher capacity to induce inflammation and exacerbate patient symptoms.

In a second study, we examined the consequences of Y1 receptor (Y1R),

β-adrenergic receptor (βAR), and IL-1 receptor type 1 (IL-1R1) inactivation in a murine model of periodontal inflammation and stress-exacerbated inflammation.

Previous studies show NPY, via Y1Rs, modulate NE that subsequently modulate cytokines like IL-1β via βARs. In turn, IL-1β modulates NPY and NE via IL-1R1 to precipitate inflammation. We antagonized the Y1R or βAR or used IL-1R1 knockout mice in the absence or presence of SDR. Porphyromonas gingivalis (P. gingivalis) or vehicle was injected into calvarial tissue of Y1R or βAR antagonized or IL-1R1 knockout non-stressed mice or SDR mice. After 24 hours, proinflammatory gene expression was determined. Y1R or βAR antagonist- treated P. gingivalis-infected mice had increased expression of proinflammatory cytokines compared to vehicle-treated P. gingivalis-infected mice. In non-infected animals, SDR increased proinflammatory gene expression as compared to

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control mice. In infected animals, SDR further exacerbated P. gingivalis-induced proinflammatory gene expression as compared to control animals, and this increase was abrogated by blocking Y1Rs and βARs during stress. IL-1R1 deficiency abrogated proinflammatory cytokine expression in non-stressed or stressed conditions. Altogether, the Y1R, βAR, and IL-1R1 are important mediators in inflammatory and stress-exacerbated inflammatory processes, thus elucidating potential mechanisms for the connection of stress to periodontal inflammation. Overall, stress enhances disease states such as allergic airway inflammation and periodontal inflammation through increased immune cell trafficking and through neuronal systems.

Dedication

This manuscript is dedicated to my husband Daniel Cuson and my loving and supportive family.

Acknowledgements

I would like to thank my advisor Dr. John Sheridan for his support and

encouragement both personal and professional. Without his help, this document

and my future career would not be possible. I would also like to thank the people

within the lab and within the IBMR for their expert assistance, technical support,

and comedic interludes (in alphabetical order): Ying An, Chris Burnsides, Ashley

Fenn, Jeffrey Galley, Matthew Gormley, David Hammond, Daniel McKim, Diana

Norden, Xiaoyu Liu, Carolyn Padro, Karol Ramirez Chan, Carolyn Sawicki,

Daniel Shea, Yufen Wang, and Eric Wohleb. I also would like to thank my former

undergraduate research assistants who were a joy to mentor and were a

tremendous help to my thesis work: Juan Carlo Avalon, Jack Minnillo, and Joy

Kirkpatrick. Additionally, within the IBMR and College of Dentistry I would like to

thank the faculty that graciously offered mentorship throughout my graduate

school education: Dr. Jonathan Godbout, Dr. Michael Bailey, Dr. Binnaz

Leblebicioglu, Dr. John Walters, Dr. Christine Igboin, Dr. Ronald Glaser, Dr.

Jeanette Marketon, Dr. Ning Quan, Dr. La’Tonia Stiner-Jones, Dr. David (Seung)

Jung, Dr. Nicole Powell, Dr. Andrew Tarr, and Dr. Eric Yang. A special thanks to

Dr. Randy Nelson and Dr. Leah Pyter, both of whom inspired and developed me

as a zygote of a scientist to pursue my passion for research and science. vi

Together they instilled within me a set of ethics and foundational understanding

of scientific purpose.

Many thanks to those who have supported my professional training

financially: National Institutes of Dental Craniofacial Research, The Ohio State

University College of Medicine’s Institute for Behavioral Medicine (in particular

Dr. Ronald Glaser) and the Integrated Biomedical Science Graduate program

(now known as the Biomedical Sciences Graduate Program), and The Ohio State

University College of Dentistry’s Oral Biology Program. Finally, I would like to thank my family, friends, and support system for seeing me through the good and not so good times of this endeavor, and I would especially like to thank my life coach Christine Rinehart, I could not have done it without them.

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Vita

July 21, 1978………………………Born Taegu, South Korea

2006………………………………...BA, The Ohio State University Psychology Major and Biochemistry Minor

2006-07…………………………….Graduate Research Associate, The Ohio State University College of Medicine Department of Radiology

2009-2011………………………….Graduate Research Associate, The Ohio State University, The Ohio State University College of Medicine Institute for Behavioral Medicine Research

2011-13…………………………….Graduate Research Fellow, The Ohio State University, The Ohio State University College of Medicine Institute for Behavioral Medicine Research

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Publications

Pyter LM, Reader BF, Nelson RJ. 2005. Short photoperiods impair spatial learning and alter hippocampal dendritic morphology in adult male white-footed mice (Peromyscus leucopus). Journal of Neuroscience, 25: 4521-4526.

Tarr AJ, Powell ND, Reader BF, Bhave NS, Roloson AL, Carson WE 3rd, Sheridan JF. 2012. β-adrenergic receptors mediate increases in activation and function of natural killer cells following repeated social disruption. Brain Behavior and Immunity, 26(8): 1226-1238.

Zhang Y, Guan Z, Reader B, Shawler T, Mandrekar-Colucci S, Huang K, Weil Z, Bratasz A, Wells J, Powell ND, Sheridan JF, Whitacre CC, Rabchevsky AG, Nash MS, Popovich PG. 2013. Autonomic Dysreflexia Suppresses Immune Function After Spinal Cord Injury. J Neurosci. 2013 Aug 7;33(32):12970-12981.

Powell ND, Sloan EK, Bailey MT, Reader BF, Arevalo JMG, Sheridan JF, Cole SW. Social Regulation of the Monocyte Transcriptome: Glucocorticoid Resistance and Cellular Differentiation of Ly-6chigh Monocytes. Proc Natl Acad Sci. 2013 Sep 23. [Epub ahead of print].

Field Of Study

Major Field: Integrated Biomedical Science Research Area: Psychoneuroimmunology

Table of Contents

Abstract ...... ii Dedication ...... v Acknowledgments ...... vi Vita ...... viii List of Tables ...... xi List of Figures ...... xii List of Illustrations ...... xv

Chapter 1: Introduction ...... 1

Chapter 2: Social Stress Induces Increased Immature Neutrophil Release from Bone Marrow in an Aspergillus Fumigatus-induced Allergic Airway Inflammation Model ...... 50

Chapter 3: Neuropeptide Y Y1, IL-1 Receptor Type 1, and β-Adrenergic Receptor Blockade in the Absence and Presence of Stress Differentially Modulates P. gingivalis-induced Inflammation ...... 123

Chapter 4: Discussion ...... 172

References ...... 182

List of Tables

Table 2.1: Af challenge contributed to significant increases in GFP+ cells in bone marrow, blood, and lung ...... 108

Table 2.2: Chemokine receptor expression on CD11b+ cells in bone marrow ...... 110

Table 2.3: Stress and Af challenge effects on other cell populations in the spleen and lung ...... 111

List of Figures

Figure 2.1: GFP+ bone marrow chimera and SDR protocol ...... 105

Figure 2.2: GFP+ bone marrow-chimeric mice show myeloid progenitor cell egress and trafficking to spleen and lung ...... 106

Figure 2.3: Sensitization, SDR, and Challenge Protocol ...... 107

Figure 2.4: Stress shifts granulopoiesis and monopoiesis in sensitized and sensitized challenged bone marrow ...... 109

Figure 2.5: Corticosterone increased in SDR mice 48h after Af challenge ...... 112

Figure 2.6: Stress and Af challenge effects on the percentage of monocytes in the blood, spleen, and lung ...... 113

Figure 2.7: Stress and Af challenge effects on the percentage of granulocytes in the blood, spleen, and lung ...... 114

Figure 2.8: Stress and Af challenge induces changes in gene expression in the lung ...... 115

Figure 2.9: Stress and Af challenge increased the CD16+ population in the lung ...... 116 xii

Figure 2.10: Stress shifts granulopoiesis and monopoiesis in sensitized and sensitized challenged bone marrow ...... 117

Figure 2.11: Distinct populations of granulocytes in lung ...... 118

Figure 2.12: Stress and Af challenge increased alkaline phospatase in lung tissue ...... 119

Figure 2.13: Hematoxylin and eosin staining of lung samples ...... 120

Figure 2.14: Stress and Af challenge increased CD16+ cell population in blood ...... 121

Figure 2.15: Distinct populations of granulocytes in blood ...... 122

Figure 3.1: P. gingivalis-induced proinflammatory and NPY gene expression at 24h and 72h pi in wild-type mice ...... 160

Figure 3.2: Confirmation that P. gingivalis bacteria were still viable 24h pi ...... 161

Figure 3.3: Effects of βAR antagonist propranolol, NPY Y1R antagonist BIBP3226, and a deficiency of IL-1R1 on NPY and proinflammatory gene expression ...... 162

Figure 3.4: Propranolol, but not BIBP3226 or lack of IL-1R1, blocks SDR-induced splenomegaly in uninfected and infected animals ...... 163

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Figure 3.5: Effects of SDR on NPY and proinflammatory gene expression in uninfected calvarial tissue ...... 164

Figure 3.6: NPY and proinflammatory gene expression in HCC infected calvarial tissue ...... 165

Figure 3.7: NPY and proinflammatory gene expression in HCC infected and infected calvarial tissue ...... 166

Figure 3.8: SDR enhances NPY and proinflammatory gene expression in infected calvarial tissue ...... 167

Figure 3.9: Effects of SDR on NPY and proinflammatory gene expression in infected calvarial tissue ...... 168

Figure 3.10: Effects of SDR and drug treatment on plasma IL-6 in infected animals ...... 169

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List of Illustrations

Illustration 3.1: Proposed mechanisms for Y1R, βAR, and IL-1R1 interaction during infection ...... 170

Illustration 3.2: Proposed mechanisms for Y1R, βAR, and IL-1R1 interaction during infection that is subsequent to stress ...... 171

CHAPTER 1

INTRODUCTION

1.1 The Stress Response

1.1.1 Stress and Stressors

The opportunity for the body and mind to experience stress occurs every moment that there is an opportunity to interact with stimuli. Walter Cannon, an

American physiologist, first conceptualized the notion of stress. He coined the term “flight or fight” to describe an animal response to threats, and he further described this “strong emotional state” as a part of “times of stress” (Cannon,

1915). Cannon also expounded on Claude Barnard’s idea of milieu interieur (the

environment within) to develop the concept of homeostasis (Cannon, 1932).

Hans Selye further defined stress as the “non-specific response of the body to

any demand for change” or “the rate of wear and tear on the body” (Selye, 1946).

Animal experimentation led Selye to note that persistent stressors resulted in the

diseases often seen in humans (e.g., hypertension, stroke, heart attack, ulcers)

(Selye, 1946). 1

Stress is most simply defined as the external or internal challenges,

perceived or real, which cause a body to deviate from homeostasis (Ramsey,

1982). Homeostasis is the biological process of an organism to maintain, regulate, or adapt its internal environment to external events in order to create physiological stability, balance and constancy of properties such as temperature, pH, or endocrine factors. Therefore, a stressor can be operationally defined as any threat against the maintenance of homeostasis in the organism. In humans, stressors are considered physical like lack of food or water, injury, disease, or temperature extremes, or psychological like social subordination, public speaking, loneliness, or loss of a loved one.

The response to stress involves a variety of well-characterized adaptive neuroendocrine mechanisms that precipitate various physiological and behavioral responses in an adaptive attempt to return to homeostasis. The activation and persistence of the stress response is highly variable and is dependent on factors such as personality traits, social status, and previous experiences (Kemeny and Laudenslager, 1999). In the other direction (i.e., from the periphery to the central nervous system (CNS)), an immune challenge can cause a deviation in homeostasis and can be considered a stressor. Through

NFκB transcription factor pathways, activated immune cells can release proinflammatory cytokines such as IL-1β, TNF-α, and IL-6 that can stimulate corticotrophin release hormone (CRH) secretion and activate the hypothalamic-

pituitary-adrenal (HPA) axis and sympathetic nervous system (SNS), which is

indicative of a stress response. In this way, there is bidirectional communication

between the CNS and the periphery.

1.1.2 Acute vs. Chronic Stress

Selye also described the “nonspecific response of the body to any demand”, which he termed the general adaptation syndrome. He explained the

terminology as “general because it is produced only by agents that have a

general effect upon large portions of the body… adaptive because it stimulates

defense…syndrome because its individual manifestations are coordinated and even partly dependent upon each other” (Selye, 1946). Selye further described

three stages of adaptation to stressors. He believed these stages primarily

involved the nervous and endocrine systems. The initial stage is the alarm

reaction, or the immediate reaction to the perception of a stressor, where

activation of the HPA axis and SNS cause changes in cardiovascular tone and

respiration rate to increase blood flow to muscle tissue creating the classic fight or flight dilemma. At this stage, resources may be shunted away from the immune system resulting in diminished resistance and increased susceptibility to disease. The next stage is the critical stage of adaptation or resistance, and successful completion of this stage depends on the termination of the stressful event and the manner in which the individual processes the stressor. If the stress 3

continues, physiological changes must occur in order for the body to adapt and to

reduce the effects of the stressor. The third stage is exhaustion where the stress

has persisted to the point that the body and immune system essentially collapse

and can become dysregulated.

We can term the initial stage as acute stress where the body reacts to a

stressor, and upon termination of the stressor, homeostasis can be achieved.

The second stage is a crucial period in that if the animal is unable to adapt or the

stressor persists, it will follow into the third stage. We can term the third stage, or unrelieved or persistent stress, chronic stress. This type of stress can cause the organism to be more vulnerable to mental illness, disease of bodily organs, and infectious and viral diseases. Selye called these “diseases of adaptation” and considered them “largely due to errors in our adaptive response to stress” rather than external factors such as bacteria or viruses. The errors that cause “diseases of adaptation” involve the mediators released by stressful experiences (e.g., cort, catecholamines), which can cause the body to lose its ability to regulate the inflammatory response leaving it vulnerable to disease.

To extend the concept of homeostasis to explain “errors in our adaptive response”, Bruce McEwen expounded on the concept of allostasis, which is the collection of these stress-induced systemic mediators (e.g., cort, cytokines, and hormones) that work to promote adaptation to the stressor (McEwen, 1998). It is when these responses are prolonged that they can become detrimental or

dysregulated. Allostatic load is term that describes the accumulation of these

adaptive responses and the overall effect it has on the body (McEwen, 1998).

Over time, the allostatic load can accumulate in a non-adaptive manner, and this

state can be termed allostatic overload (McEwen, 1998). At this point, the body

may succumb to the negative effects of stress such as inflammation or disease

(McEwen and Stellar, 1993).

1.1.3 Mechanism of the Stress Response

The stress response is an evolutionarily conserved mechanism that works

to restore homeostasis in the presence of challenge and enhance the chance of

an organism’s survival. As varied as the stressors may be and as individual as the response may be to a common stressor, the body has well-coordinated and

well-conserved pathways to elicit the stress response (Biondi and Picardi, 1999).

When a threat is perceived, a signaling cascade among fear/anxiety

regions is initiated in the brain, and the stress response is elicited (Eskandari et

al., 2003). Two major biological systems are activated: the HPA axis and SNS.

The activation of both of these systems leads to the release of products that can

regulate the function of the immune system. The HPA axis consists of the

paraventricular nucleus (PVN) of the hypothalamus, the anterior pituitary gland at

the base of the brain, and the adrenal glands that lie atop the kidneys. When a

stressor is detected, CRH is released from the PVN into the hypophyseal portal blood supply stimulating the production of adrenocorticotrophic hormone (ACTH) in the anterior pituitary gland. ACTH circulates via the bloodstream to the adrenal glands causing the release of glucocorticoids (GCs) such as corticosterone (cort) in mice and cortisol in humans. GCs will then feed back to negatively regulate the

HPA axis at the hypothalamic and pituitary levels. Stress also induces the release of catecholamines such as norepinephrine (NE) that are released from nerve fibers, which extend from the thoraco-lumbar spinal cord to innervate the body including primary and secondary lymphoid organs (Madden et al., 1995).

Regulation of GCs can also occur by catecholamines, cytokines, or other neuropeptides like neuropeptide Y (NPY) or arginine vasopressin (AVP).

1.1.4 Stress and Inflammation

Psychoneuroimmunology (PNI) involves the study of the bidirectional interactions between the nervous and immune systems and the relationships between stress and health. Inflammation is an important dependent variable of immune function that is a primary focus of PNI research. It is a central indicator of mental and physical disease and is a necessary biological and adaptive response to tissue injury, infection, or allergy. Stress can have a major impact on immune products such as cytokines and chemokines that are instrumental in

mobilizing appropriately activated immune cells to where they are needed to aid in the resolution of the insult.

Overall, the immune system functions to prepare for, control, and effectively clear bacteria, viruses, and allergens from the host. Cells of the innate immune system, such as macrophages and neutrophils, function as the first line of defense (Dale et al., 2008). Stress-induced release of GCs into the system normally causes immunosuppression and increased susceptibility to infections and disease severity; a prolonged GC response may lead to chronic disease

(Cohen et al., 2012). However, stress can cause a state of GC resistance in innate immune cells that works to prevent the suppression of inflammation in response to infectious pathogens in tissue. This prevention of suppression can work to eradicate the microbial organisms, but can also work to worsen tissue damage through excessive inflammation (Barnes and Adcock, 2009;Meduri and

Yates, 2004).

1.1.5 Summary

This chapter will review studies using a murine social stress model to elucidate the peripheral and central effects of stress in the absence and the presence of immune challenge. Furthermore, this introduction serves to give foundational support to the studies that will be introduced in Chapters 2 and 3.

1.2 Mouse Models of Social Stress:

1.2.1 Overview of Social Stress

Social stress can have a significant impact on the immune system affecting susceptibility to and resolution of various diseases, infections, and allergens. Numerous studies have shown that social status modulates the immunological and physiological responses to social stress. Subordinate monkeys, in response to social reorganization, had reduced body weights, higher levels of cortisol, and increased susceptibility to upper respiratory infections

(Cohen et al., 1997). In rats, confrontation with a dominant conspecific caused a significant decline in the behavior and immunity and enhanced levels of plasma corticosterone (Stefanski and Engler, 1998).

In humans, studies in social defeat involving bullying or loss of social status in the workplace have demonstrated increased incidence of depression, anxiety, loss of self-esteem, increased incidence of illness, and other negative behavioral symptoms (Marmot and Feeney, 1997). The commonality and grave impact of social stress on humans has yielded the generation of animal models of stress containing a social component.

1.2.2 Social Stress in Mice

In the wild, threats to obtaining and protecting limited resources such as

food, mates, and territory are stressors for mice. In the laboratory, social

stressors involve protecting the resources of the cage from intruding mice, and

this motive causes mice to form social hierarchies consisting of a dominant

alpha, co-dominants, and subordinates (Ginsburg and Allee, 1975). Social status

changes among these cagemates occur through aggression and acceptance of

subordination, and this often involves episodes of repeated defeat. These

hierarchies can be disrupted when another mouse vies for dominance by

challenging and defeating the dominant (Ginsburg and Allee, 1975). These

experiences are not only psychologically stressful for the mice involved, but also

entail a physical component whereby there is a risk of injury. Defeated

subordinate animals can receive bite wounds that may not be life-threatening, but can cause significant changes in the immune system, behavior, and the CNS.

The most common manner in which to replicate murine social stress in the laboratory is by using a resident-intruder paradigm where an intruder is introduced to a cage of resident mice and proceeds to defeat them repeatedly for a determined amount of time (Tamashiro et al., 2005).

1.2.3 Social Reorganization Paradigm

Social reorganization (SRO) was a novel paradigm adapted by Sheridan

and Padgett to study social stress (Padgett et al., 1998). SRO involves the

transfer of a dominant mouse from one cage of mice to another. The constant

fluctuation in social status results in disruption of the social organization within these cages and a stress response within the resident mice. SRO enhanced inflammatory and antiviral immune responses, increased immunopathology in the respiratory tract, and increased mortality of influenza-A-infected mice (Sheridan et al., 2000). This enhancement was accompanied by increased circulating levels of, normally immunosuppressive, cort leading the investigators to identify that social stress induced a state of functional GC resistance in peripheral immune cells.

1.2.4 Social Disruption Paradigm

To explore this idea further, Avitsur and Stark adapted an ethologically

relevant stress model called social disruption (SDR) from Sheridan and Padgett’s

original SRO model (Avitsur et al., 2001; Stark et al., 2001). SDR is a paradigm

of repeated social defeat involving intermale aggression and loss of social status

by the disruption of an established social hierarchy. Around the beginning of the

mouse’s active cycle (17:00), an aggressive mouse is introduced into a cage of

resident mice that have an established social hierarchy. These aggressor mice

are usually older, larger, and, due to retired breeder status, have had previous

social experience with being a sole dominant in a cage.

Within minutes of introduction, the aggressive intruder should briefly and

consistently attack the cage residents for the length of the 2h cycle. While the

aggressor is in the cage, the residents display classic behavioral signs of fear

and submissiveness. The residents have been observed to have reactions that

are dependent on social status. Previous data have shownt that the threatened

resident mouse, especially if he is a dominant or co-dominant, may choose to

fight back against his opponent possibly in an effort to reestablish dominancy

over the territory and resources or it may attempt to flee (Avitsur et al., 2007).

Because the cage is a finite space, fleeing becomes a less viable option as the

cycle number increases. Therefore, subordination is often the ultimate behavior

displayed by residents by the end of 6 cycles of SDR treatment.

These behaviors of subordination involve the resident mice huddling in a corner furthest away from the aggressor. When approached, the mice will rear or stand on their hind legs and bare their ventral body surface to the aggressor as a universal signal of subordination. SDR treatment usually consists of 6 cycles over

6 consecutive days, with a new aggressor used for each cycle. Cutaneous bite

wounds do occur as a part of repeated social defeat and seem to be necessary,

but not sufficient, for the immunological and behavioral changes to occur.

Resident animals are carefully inspected for injuries after each SDR cycle, and

mice with severe wounds (<5% in previously published studies) were removed

from the studies.

1.2.5 Paired Fighting Paradigm

In another paradigm of social stress, termed paired fighting (PF), a single

resident mouse and an aggressor mouse are placed in a neutral cage for 30 min.

The resident mouse is repeatedly defeated by the aggressor during short bouts

of fighting. The similarity between the immunological effects of SDR and PF

show the importance of the experience of repeated defeat to the development of stress-related immune outcomes such as GC resistance (Avitsur et al., 2002j).

1.2.6 Summary

Social stress paradigms in the laboratory use the natural behaviors of

mice to their advantage with the disruption of established social order and

repeated defeat by an aggressive male. Much of the data from this vein of

research has been generated using the SDR paradigm.

1.3 Peripheral Effects of Social Disruption Stress

1.3.1 Circulation

One classical effect of stress is the increase of catecholamines such as

NE and epinephrine and GCs such as cort into circulation. SDR is a significant stressor and causes significant elevations in NE and EPI and plasma cort

(Avitsur et al., 2001;Hanke et al., 2012). Habituation does not occur in this cort response in that SDR-induced levels of cort increase as the cycle number increases (Avitsur et al., 2001; Bailey et al., 2004; Engler et al., 2005; Stark et al.,

2001). Additionally, there is no break in the circadian rhythm of the SDR cort response unlike with restraint stress where cort is elevated by the stressor and remains elevated. The morning after the SDR cycle, cort levels are back to baseline (Avitsur et al., 2002). In vivo dexamethasone suppression tests indicate that SDR mice still had a GC negative feedback loop as dexamethasone suppressed cort plasma levels in SDR and controls to a similar extent (Avitsur et al., 2002).

The release of cytokines and proteins into circulation is another effect of stress. These cytokines and proteins have the ability to enhance the mobilization of immune cells through circulation and into tissue and enhance inflammation. In circulation, several proteins and cytokines are increased such as IL-6, TNF-α,

NGF, KC, MIP-2, and MCP-1 (Avitsur et al., 2001; Curry et al., 2010; Hanke et al., 2012; Wohleb et al., 2011). At least for some of these proteins, their release 13

is β-adrenergic receptor (βAR)-mediated in that pretreatment with the non-

selective βAR antagonist propranolol can abrogate increases in IL-6, TNF-α,

MCP-1 (Hanke et al., 2012; Wohleb et al., 2011). Additionally, ACTH is increased by SDR compared to HCC with the peak of ACTH after the 2nd cycle (Engler et

al., 2005). This inverse relationship of ACTH and cort levels suggested that the

negative GC feedback mechanism on the pituitary gland was intact. This

indicates that SDR did not result in a central state of GC resistance (Engler et al.,

2005).

1.3.2 Spleen

The spleen is one of the most important organs in the vertebrate animal

immune system. It functions as a filter for circulating blood and has efferent

lymphatic vessels. The structure of the spleen consists of an outer capsule, red pulp containing granulocytes, macrophages, and erythrocytes, and white pulp, the lymphocyte-rich area where antibodies are synthesized. Among many other

roles, the spleen has the function of removing senescent erythrocytes and

metabolizing hemoglobin and holding a reserve of blood. It is estimated that the

mouse spleen contains half of the body’s monocytes in the red pulp, and these

monocytes can circulate to other organs and tissues to differentiate into dendritic

cells and macrophages (Swirski et al., 2009). The spleen is also involved in the

production and maturation of B and T cells and removal of antibody covered 14

microbes. It is often considered similar in structure to a lymph node, and

enlargement, or splenomegaly, can occur in response to infection or

inflammation.

Six cycles of SDR has no significant effect on body weight, but splenomegaly, which results in a near doubling of the spleen, is a hallmark characteristic of the SDR response (Avitsur et al., 2001). The spleen not only has cycle-dependent increases in weight, but also in myeloid cells numbers specifically CD11b+ monocytes and granulocytes (Avitsur et al., 2002). CD11b is

expressed on both neutrophils and monoctyes and is a cell adhesion marker and

indicator of activation. In vitro, these monocytes have enhanced cell viability in the presence of cort and lipopolysaccharides (LPS), and enhanced IL-6

responses in the presence of cort that can persist between 10 and 30 days past

the termination of the stressor (Avitsur et al., 2002). Cort normally suppresses

proliferation, reduces survival of cultured splenocytes, and suppresses the

production of proinflammatory cytokines, but SDR splenocytes do not have these

responses and are considered GC insensitive or resistant. To test if this

phenomenon of GC resistance was global, the cell viability and cytokine

responses of stimulated peritoneal monocytes were examined. These peritoneal

monocytes produced IL-1α and IL-6 in the presence of LPS, but, in the presence

of cort, these responses were appropriately suppressed (Avitsur et al., 2002).

This phenomenon of GC resistance appears to be tissue specific and a main

reservoir of these GC resistant cells is in the spleen.

To determine the cell types that were responsible for this phenomenon of

GC resistance, B cells and macrophages were selectively depleted from cultures.

When the B cells (CD19+) were removed, the remaining cells were still GC

resistant (Stark et al., 2001). However, depletion of the macrophages (CD11b+) abolished the SDR-induced GC resistance and cytokine responses (Stark et al.,

2001). Though it is important to note that not all SDR mice develop this state of

GC resistance in the spleen. When mice are attacked by an intruder during SDR, bite wounds can be common, and the phenomenon of GC resistance has been found to be most robust in mice that were subordinate and received several bite wounds (Avitsur et al., 2007). The inflammatory response to tissue damage that occurs during SDR may be a contributor to the GC resistant state of CD11b+ cells. Alternatively, it is possible that pain associated with the bites may transmit signals to the CNS that solidify the behaviors that factor into threat appraisal as threat expression, thus exacerbating the stress response to have long-lasting biological effects on the mouse.

GC resistance presents in diseases such as asthma, infection, and depression, and it is possible that cytokines or mediators may induce GC resistance by altering the number or function of GRs (Kino et al., 2003). SDR- induced GC resistance occurs between 3 and 6 cycles of SDR and persists at

least 10 days past the termination of the stressor (Avitsur et al., 2002). Normally

when excessive GCs flood a biological system immunosuppression or anti- inflammation occurs. However, dysregulation of the GC receptor can occur at a

molecular and cellular level and this can lead to GC resistance or an insensitivity

of the GC receptor to GCs. Quan et al., (2003) examined molecular mechanisms

of GC resistance in SDR splenocytes. Because SDR splenocytes exhibit GC

resistance in vitro, it was unlikely that extracellular mechanisms such as corticosteroid-binding globulin (CBG), which inhibit GCs, had a role in GC resistance (Stark et al., 2001). Therefore, it was hypothesized that intracellular mechanisms might be responsible for the SDR-induced changes in GC receptor function. The study revealed that there were no changes in the GC receptor at the DNA or RNA level, and it was confirmed that the GC receptor had diminished function in SDR splenocytes stimulated with LPS (Quan et al., 2003). It was determined that the GC receptor in SDR splenocytes did not have the ability to suppress NFκB activity due to a failure to translocate to the nucleus (Quan et al.,

2003). This change of GC receptor function could not be detected in the receptor at the pre-translational level suggesting this change is not permanent (Quan et al., 2003). A previous study demonstrated that GC sensitivity was recovered 30 days after the termination of SDR (Avitsur et al., 2002). Overall, data support that

SDR-induced GC resistance in the presence of LPS or a second signal is due, at least in part, to the inability for the GC receptor to translocate into the nucleus and interact with NFκB.

1.3.3 Bone Marrow

The bone marrow is the flexible tissue inside bones, and, in the adult, it is

the site where all circulating blood cells are generated including immature

lymphocytes and B cells (Dorshkind, 1990). These cells originate from a common

hematopoietic stem cell that will commit to and differentiate along certain lineages (e.g., erythrocytic, granulocytic, monocytic, or lymphocytic). The proliferation and maturation of immature cells in the bone marrow are activated by colony stimulating factors such as granulocyte macrophage colony stimulating factor (GM-CSF) and macrophage colony stimulating factor (M-CSF) that are produced by stromal cells and macrophages in the bone marrow (Lieschke and

Burgess, 1992). In the bone marrow, the stromal cells (the fixed tissue cells in the medullary cavity) are organized into hemopoietic microenvironments that are composed of nutrient arteries, capillaries, and emissary veins (Dorshkind, 1990).

Influx and efflux of cells and mediators to and from the bone marrow can all affect the differentiation and release of immune cells (Dorshkind, 1990). Both activation of the HPA axis and the SNS can alter the function, timing, and migration of immune cells.

The question was raised as to where the increased number of GC resistant CD11b+ leukocytes in the SDR spleen originated. One hypothesis was

that these cells came from the vascular endothelium, because increases in 18

circulating catecholamines can result in the demargination of large numbers of monocytes from the vascular endothelium (Landmann et al., 1984). Another hypothesis was that the repeated activation of neuroendocrine systems caused the mobilization of neutrophils and monocytes from the bone marrow to the spleen. The murine spleen has low myelopoetic activity and most of the granulocytes and monocytes that circulate come from the bone marrow. Stress and severe infection has been shown to cause a rapid release of neutrophils and monocytes into circulation known as neutrophilia and monocytosis, respectively

(Powell et al., 2013; Stefanski, 2000; Stefanski and Engler, 1998)

Repeated exposure to SDR over 2, 4, or 6 cycles was associated with cell mobilization and increased myelopoiesis in bone marrow and an accumulation of neutrophils and monocytes in circulation and spleen (Engler et al., 2004). SDR treatment is associated with depletion of B cells in bone marrow and blood and increases in the spleen and T cells are reduced in spleen, circulation, and bone marrow (Engler et al., 2004). This decreased cellularity could be due to GC- induced apoptosis due to the GC sensitivity of these cells. Interestingly, bone marrow cells from home cage control (HCC) mice are GC resistant, but, after 6 cycles of SDR, these cells disappeared from the BONE MARROW and the remaining cells were GC sensitive (Engler et al., 2005). This is the complete opposite for the spleen whose cells, at the start of SDR, begin GC sensitive and become insensitive after SDR.

Quantification of myeloid progenitor cells in the bone marrow revealed an

increase in the number of immature neutrophils in SDR mice (Engler et al.,

2004). GCs are known to delay neutrophil apoptosis, and chronic GC treatment

can increase neutrophil numbers in the blood and spleen (Liles et al., 1995;

Meagher et al., 1996; Simon, 2003). The SDR-induced increase in neutrophils in

the blood and spleen are likely a combination of increased mobilization from the

bone marrow and the vascular endothelium as well as prolonged survival. The

half-life of a neutrophil is relatively short (24-48h), thus an increase in the

neutrophil population in the blood and spleen after 6 cycles of SDR could be due to extended cell survival (Fadeel et al., 1998; Webb et al., 2000). Increases in circulating endogenous GCs can increase neutrophil survival and cause accumulation of the cells. One mechanism involves the enzyme elastase, a serine protease contained in the granules of neutrophils. Elastase decreases the binding capacity of corticosteroid binding globulin (CBG) and this increases the bioavailability of GCs that can aid in the survival neutrophils.

The enhanced myelopoiesis seen in SDR may be due to combination of enhanced production of GM-CSF in the bone marrow and increased myeloid cell survival in the periphery. These colony stimulating factors likely act as

chemotactic signals for circulating myeloid cells to leave circulation in order to

enter the spleen. GM-CSF, in particular, is a potent chemoattractant, and by upregulating CD11b expression, can increase the adhesion of blood neutrophils

and monocytes to the vascular endothelium. As SDR cycles increased, GM-CSF

expression, but not M-CSF, increased in the bone marrow (Engler et al., 2005).

In the spleen, only after the 2nd cycle did GM-CSF and M-CSF increase and then

by the 6th cycle the expression decreased below HCC levels. Finally, there was a substantial increase in the proportion of immature CD11b+ cells in the 4 and 6

cycle SDR group that corresponded to the increase in GM-CSF expression

(Engler et al., 2005). In Powell et al., (2013) neutralizing GM-CSF with an

antibody or pre-treatment with propranolol inhibited SDR-induced upregulation of

bone marrow monocyte and granulocyte bone marrow progenitor cell

populations. Overall, SDR induces bone marrow immune cell GC sensitivity, increases in myeloid progenitor cells and GM-CSF, and decreases in mature

CD11b+ cells. These data point to the bone marrow as the most likely origin of

the splenic accumulation of CD11b+ cells.

1.3.4 Lung

Even in the absence of immune challenge, SDR has a significant impact

on the lung. SDR increases the number of activated and primed immune cells

that traffic to the lung, thus aiding in the creation of an inflammatory environment.

Curry et al., (2010) found that SDR induces an increase in monocytes and

neutrophils that traffic to the lung. SDR cycle-dependently enhanced the

percentage of lung cells that expressed Ly6G, a cell surface marker indicative of 21

neutrophils (Daley et al., 2008). Furthermore, SDR enhanced the percentage of

activated neutrophils (Ly6G+ and CD11b+). Additionally, myeloperoxidase

activity, a major neutrophilic lysosomal enzyme, was increased in the SDR lung

(Curry et al., 2010). IL-1β, KC, and MIP-2, but not IL-6, protein levels were locally

increased in the lungs of SDR mice (Curry et al., 2010). Furthermore, in this

study, expression of TNF-α, IL-17, which attracts neutrophils, and M-CSF, which

attracts monocytes, were unchanged in the lungs of SDR mice. In the lung, SDR

increased production of IL-1β and chemokines that recruit neutrophils and

monocytes (KC/CXCL1, MIP-2/CXCL2, and MCP-1/CCL2) (Curry et al., 2010).

SDR also induced the expression adhesion molecules that work to localize and

recruit immune cells (Curry et al., 2010). E-selectin (after 2 cycles of SDR), and

ICAM-1 (after 4 cycles of SDR) (Curry et al., 2010). Using flow cytometry, lung

endothelial cells were gated, and dual expression of P-selectin, E-selectin, or

ICAM-1 were determined (Curry et al., 2010). SDR increased the percentage of

endothelial cells expressing P-selectin and E-selectin and increased the level of

P-selectin and E-selectin expression per CD31+ cell. SDR was not found to affect

vasculature leakage, thus increased inflammation is unlikely due to compromise

of the vasculature (Curry et al., 2010).

1.3.5 Other organs

Several other peripheral organs and tissues are affected by SDR. Adrenal

hypertrophy and thymic involution are classical indicators of the stress response and can be seen after SDR (Engler et al., 2005). After cycle 4, adrenal mass increases significantly and, after cycle 2, thymus mass decreases and continues decreasing toward cycle 6 (Engler et al., 2005). The host’s indigenous microflora within the skin and the gastrointestinal tract, which are two of the largest accessory organs of the immune system, can be significantly altered by SDR.

Bailey et al., (2006) examined the effects SDR had on the translocation of microflora from cutaneous and mucosal surfaces and the gastrointestinal tract to lymph nodes, spleen and the liver. In the absence of stress, few mice have detectable levels of bacteria in their inguinal or mesenteric lymph nodes, spleen,

or liver (Bailey et al., 2006). After 6 cycles of SDR, the number of mice who had

bacteria in their lymph nodes and liver were significantly increased (Bailey et al.,

2006). It was suspected that the entry of these bacteria into the host could be

from bite wounds obtained during SDR. To explore this hypothesis, experimental

wounding and restraint stress was used. Wounding itself did not increase

bacterial translocation into the lymph nodes or liver, but the stressor in addition to

the wounding increased the number of mice whose organs were colonized

(Bailey et al., 2006). To note, the levels of bacteria found in the stressed and

colonized mice were similar to non-stressed and colonized controls (Bailey et al.,

2006). Furthermore, both restraint and SDR increased the translocation of

bacteria that were primarily Gram-negative aerobic and facultative anaerobic

from the gastrointestinal tract to the mesenteric lymph nodes, and Gram-positive

cocci (Staphylococcus aureus) from the skin to the inguinal lymph nodes (Bailey

et al., 2006). The idea that stress can precipitate the translocation of indigenous

microorganism is likely a key factor by which stressors may affect health.

1.3.6 Other Cell Types

Natural killer (NK) cells play a major role in the innate immune system as cytotoxic lymphocytes, and their role is similar to that of cytotoxic T cells in the adaptive immune system. As a first line of defense, NK cells respond to virally infected cells and tumor formation without the necessity of detection of major histocompatibility complex (MHC) allowing for a rapid response (T cells are

MHC-restricted). Tarr et al., (2012) examined the cellular distribution and phenotypes of NK cells in the spleen, lung, and blood and cytolytic activity and anti-viral cytokine production in NK cells in the spleen. Splenic CD3-/DX5+ NK cells from SDR mice were found to be of an activated phenotype immediately after SDR and 14h post SDR (Tarr et al., 2012). These cells had increased CD16 and CD69 expression, which are markers of activation, and decreased NKG2a

and Ly49a expression, which are markers of inhibition (Tarr et al.,

2012). Pretreatment of SDR mice with propranolol before each stress 24

cycle blocked these priming effects at the 14h time point. SDR had similar effects on activation and inhibitory receptors 14h post SDR in the lung, but no alterations were evident in the blood besides increased NK cells immediately following SDR

(Tarr et al., 2012). Ex vivo, SDR splenic NK cells had increased CD107a surface expression (a marker of NK function), cytolytic activity, and IFN-γ production upon co-stimulation with IgG and IL-2 (Tarr et al., 2012). Overall, social stress primes NK cells in the spleen and lung to be more proficient in their cytolytic and anti-viral/tumor effector functions and this is mediated through βAR signaling.

Dendritic cells (DCs) are a class of immune cells that work as messengers between the innate and adaptive immune system. Classical DCs function primarily as antigen presenting cells that work to regulate T cell responses

(Banchereau and Steinman, 1998). As immature cells, DCs are highly phagocytic, and as they mature they become more cytokine-producing. In mice,

DCs are rarely found in circulation and instead travel to tissue through lymphatic circulation and high endothelial venules. Plasmacytoid DCs (pDCs), located in both the bone marrow and peripheral organs, act as antigen-presenting cells and in response to viral infection can produce type I interferons (Colonna et al.,

2004;Corcoran et al., 2003).

Powell et al., (2009) found that SDR treatment activates and enhances the function of DCs. Cells that were CD11c+, a dendritic cell marker, had, increased levels of activation markers such as MHC-1, CD80, and CD44. Furthermore, ex

vivo LPS or CpG stimulation of splenic DCs enhanced TLR-dependent secretion

of TNF-α, IL-6 and IL-10, and poly(I:C) stimulation of cultures increased secretion

of TNF-α and IL-6. Finally, these CD11c+ DCs from SDR mice were also found to

be GC resistant (Powell et al., 2009).

1.3.7 IL-1R1and βAR-mediation of the SDR response

Through use of antagonists and knockout mice (KO), it has been

determined that the immunological and behavioral effects of SDR are Interleukin

1 receptor type 1 (IL-1R1)- and βAR-mediated, and functional IL-1R1 and βAR

signaling are necessary to the development of these effects. Comparable to wild-

type SDR mice, IL-1R1 knockout (KO) SDR mice do develop adrenal

hypertrophy, thymic involution, and elevated serum cort in response to SDR

(Engler et al., 2008). However, unlike wild-type SDR mice, IL-1R1 KO SDR mice

do not show splenic, blood, or BONE MARROW accumulation of CD11b+ cells and splenocytes fail to develop GC resistance. IL-1β, but not IL-1α, protein is elevated in the plasma (Engler et al., 2008). It is known that there is an increase in IL-1 after SDR with IL-1β gene expression increased in the spleen and liver and IL-1α increased in the liver (Engler et al., 2008). The lack of mobilization of immune cells in IL-1R1 KO mice may be one reason for the lack of GC resistance in IL-1R1 KO mice. Stress associated release and signaling of IL-1

likely an important component in the induction of GC resistance in SDR immune

cells.

βAR activation can mediate the actions of catecholamines and increase

the production of cytokines in many cell types. When the non-selective βAR

antagonist propranolol was administered to mice 1h before each cycle of SDR,

the SDR-induced splenomegaly and plasma increases of IL-6, TNF-α, and MCP-

1 can be prevented (Hanke et al., 2012; Wohleb et al., 2011). Pretreatment with propranolol did not alter cort levels indicating that propranolol did not affect HPA axis activation (Wohleb et al., 2011). Flow analysis from SDR propranolol- pretreated mice showed that the SDR-induced increase in the percentage of

CD11b+ splenic macrophages were decreased, and the expression of Toll like receptor (TLR) 2 and 4 and CD86 was reduced on the surface of these cells

(Hanke et al., 2012). Supernatants from 18h LPS-stimulated ex vivo cultures of splenocytes from propranolol-treated SDR mice contained less IL-6 (Hanke et al.,

2012). Propranolol pretreatment also eliminated the GC resistance of CD11b+

cells ex vivo when compared to splenocytes from SDR vehicle-treated mice

(Hanke et al., 2012). These data suggest immune activation and priming effects

of SDR are consequences of SNS activation.

1.4 Social Disruption Stress-Induced Behavior

1.4.1 Individual Differences and Behavioral and Environmental Factors

In SDR, the resident mice undergo aversive stimuli such as the repeated inescapable attacks by the aggressor causing the residents to experience long lasting behavioral changes. In the past decade, the behavior of mice undergoing

SDR has been examined before the stressor, during the stressor, and after the stressor providing data that to help understand the individual reactions to a common stressor.

Individual differences in the behavioral and immunological response to

SDR are influenced by complex interactions between the behavioral and environmental factors present before the introduction of the stressor and factors associated with the social environment during the stressor (Avitsur et al., 2007).

These individual differences are unlikely to be attributed to genetics since most studies have used inbred strains (e.g., C57BL/6), thus variability is likely due to environmental and behavioral factors (Avitsur et al., 2001). The outcomes of social stress may depend on the physiological changes associated with stimulation of neuroendocrine pathways and with behavioral variables like social status.

Prior experiences with defeat and learning to display submissive behavior upon attack are associated with subordinate social status (Ginsburg and Allee,

1975). Because of the considerable individual differences in the development of

the splenic response to SDR even in inbred mice, data suggest that social status

affects the magnitude of the splenic response to SDR. It has been determined

that these individual differences are mediated, in part, by behavioral factors such

as social hierarchy. When social status was identified prior to and after SDR,

subordinate SDR animals had increased spleen weights and splenocyte numbers

compared to dominant animals in the cohort (Avitsur et al., 2007). Furthermore,

splenocytes from SDR subordinates were less sensitive to GC-induced apoptosis

and had enhanced TNF-α and IL-6 production in response to LPS-stimulation

and cort (Avitsur et al., 2007). During attacks, defeated mice froze and reared to

expose their abdomens to the aggressor in an attempt to terminate aggressive

interactions (i.e., as a display overt submissiveness). Submissive mice are more

likely to be wounded and to have more intense wounds (Avitsur et al., 2007).

Dominant mice, at least in the first few cycles, have a more active response

(fleeing) rather than a purely submissive response (posture) and were not as likely to show an enhanced splenic response to SDR (Avitsur et al., 2001; Avitsur et al., 2007). Active responses may be more advantageous for the mouse in that it reduces the chances of a physical attack by the aggressor. Since submissiveness can be associated with an increased risk for injuries due to

attacks and fight, the development of GC resistance may be an adaptive

mechanism allowing the inflammatory component of wound healing to occur during physiologically high levels of cort and to prevent the infection of these

wounds. Social stress can cause mice to employ behavioral coping responses

that are based on current environmental conditions and previous experiences.

These situationally adaptive responses are reflected in the behavioral, endocrine, and immune changes in response to the stressor.

This relationship between social status and the immunological changes

induced by SDR are more robust in cages with stable social hierarchies (Avitsur

et al., 2007). Compared to control cages the stability over time of the dominance order in SDR cages was lower, but the frequency of status changes was not

different from controls suggesting that attacks and defeats during SDR do have a small effect on the stability of social order (Avitsur et al., 2007). Submissive behavior paralleled the increase in cycle number even as the duration of attacks were reduced (Avitsur et al., 2001). It can be concluded that there is an effect of

social status in which subordinate mice are more likely to be GC resistant

(Avitsur et al., 2001). When comparing wounded to non-wounded mice exposed

to SDR, GC insensitivity correlated with wound status, i.e., wounded mice had a higher probability of splenocyte GC insensitivity. Of note, however, is the

observation that dominant and submissive animals had similar elevated

circulating levels of cort.

Previous social experience likely contributes to the individual differences

seen in the development of GC resistance. However, group-housed mice

exhibited a higher duration of submissive behavior compared to individually-

housed mice during attacks, but not during breaks (Avitsur et al., 2003).

Individually-housed mice had higher frequencies of jumping behavior and cage

crossing compared to group-housed mice (Avitsur et al., 2003). There were no

differences in PF-induced splenomegaly in individually- or group-housed mice

suggesting that rearing conditions had no effect on splenomegaly (Avitsur et al.,

2003). Both rearing conditions resulted in GC resistance in splenocytes after

SDR (Avitsur et al., 2003). Thus, rearing conditions and previous social

experiences influenced immune and behavioral responses to SDR.

1.4.2 Necessity of Physical Contact in the SDR Response

Aggressive confrontations are composed of discrete phases: the threat of attack, the actual physical attack, and the post-attack state (Korte et al.,

1990;Martinez et al., 1998;Tornatzky and Miczek, 1994). The psychological component usually occurs in the pre- and post-attack phases, and the post- attack phase is when the body strives to achieve homeostasis. To determine if

physical defeat, or just the threat of physical attack, is sufficient for the development of GC resistance, the SDR paradigm was modified (Bailey et al.,

2004). A cage of 5 mice was exposed to 2 cycles of SDR, and then the cage was physically divided in half by wire mesh. Mice on one side of the cage were physically exposed to the aggressor for 4 additional cycles, and the remaining 3 mice on the opposite side of the partition did not physically interact with the 31

intruder. Both groups of mice had elevated plasma cort levels and displayed

submissive postures to the intruder, which are indicative of a stress response, but only the mice that had physical contact with the aggressor developed GC resistance (Bailey et al., 2004). It can be concluded that exposure to a stressful environment that causes an elevation in circulating cort is not sufficient to cause the generation of GC resistance in murine splenocytes and that this state is dependent on the physical attack component of SDR.

1.4.3 Anxiety-like behaviors

Anxiety-like behaviors are robust in mice that have undergone SDR, and

various tests have been used to examine these behaviors. Anxiety-like behavior

has been evident in the open field, novel object, and light/dark tests (Bailey et al.,

2009a; Hanke et al., 2012; Kinsey et al., 2007; Wohleb et al., 2011). Many of

these anxiety-like behaviors were present after the first cycle and persisted up to

10 days past the termination of the stress (Kinsey et al., 2007). These anxiety- like behaviors are likely mediated by the βAR and IL-1R1. When the non- selective βAR antagonist propranolol was administered before each cycle of stress or IL-1R1 deficient animals were used, the SDR-induced anxiety-like behaviors can be effectively abrogated (Wohleb et al., 2011; Hanke et al., 2012).

1.5 SDR-Induced CNS Effects

1.5.1 c-fos Immunoreactivity in the SDR Brain

Studies were designed to examine neuronal activation in response to

SDR. c-fos is an immediate early gene that is expressed when neurons fire action potentials. c-fos immunoreactivity is an indirect marker of recent neuronal activity, and visualizing the discrete brain regions in which c-fos is detected can reveal patterns of recent brain region-specific activation that are thought to be associated with behaviors and interpretation of events. In mice that underwent 1,

3, or 6 cycles of SDR, c-fos immunoreactivity was assessed in brain regions associated with threat appraisal and fear such as the prefrontal cortex (PFC), lateral septum (LS), bed nucleus of the stria terminalis (BNST), paraventricular nucleus (PVN), medial amygdala (MeA), and hippocampus (HC) (Wohleb et al.,

2011). These brain regions were specifically chosen for their roles in the neurocircuitry of threat appraisal and fear/anxiety (LeDoux, 2000). One or three cycles of SDR increased c-fos activation in the PFC, LS, BNST, PVN and MeA, and 6 cycles of SDR, increased c-fos immunoreactivity in the PFC, LS, and PVN

(Wohleb et al., 2011). Enhancement of c-fos immunoreactivity in discrete brain regions was found to be βAR-mediated in that it could be completely abrogated by pretreatment with propranolol prior to each cycle of SDR (Wohleb et al.,

2011).

Previous studies had shown that SDR-induced immune modulation was also IL-1R1-mediated (Engler et al., 2008). While SDR was not found to induce anxiety-like behavior or microglial activation in IL-1R1 KO mice, increases in brain region-specific c-fos activation were present (Wohleb et al., 2011). These data suggest that SDR-induced anxiety-like behavior and the activation of microglia is dependent on the activation of βAR and IL-1R1 (Wohleb et al., 2011).

1.5.2 Microglia and Macrophages

CNS macrophages and microglia are important in the interpretation and propagation of inflammatory signals within the bidirectional communication between the brain and the periphery. SDR increases the number of

CD11b+/CD45hi/Ly6Chi macrophages in the brain and increases the reactivity and inflammatory state of the microglia and brain macrcophages (Wohleb et al.,

2011). Specifically, inflammatory markers such as CD14, CD86, and TLR 4 were increased on microglia, and CD14 and CD86 were increased on brain macrophages after SDR (Wohleb et al., 2011). Identification of deramified microglia indicated an activated phenotype, and SDR increased the presence of these cells in the MeA, PFC, and HC (Wohleb et al., 2011). Additionally, the percentage of CD45lo cells (microglia) that were also CD14+ was increased in the brains of SDR mice, as was expression of the GC responsive genes GILZ and

FKBP51 (Wohleb et al., 2011). Ex vivo, SDR LPS-stimulated microglia were 34

found to produce higher levels of IL-6, TNF-α, and MCP-1 than control mice when obtained from SDR treated mice (Wohleb et al., 2011). All of these stress- dependent changes could be blocked by daily treatment with propranolol, thus demonstrating they are likely to be βAR-mediated.

An interesting finding was that SDR anxiety-like behavior corresponded with region specific peripheral myeloid cells recruitment to the brain during SDR

(Wohleb et al., 2013). A cycle-dependent increase in circulating monocytes that were CD11b+/SSClo/Ly6Chi, and brain macrophages that were

CD11b+/SSClo/CD45hi, also corresponded with brain region-dependent cytokine

and chemokine responses involved with myeloid cell recruitment to tissue

(Wohleb et al., 2013). To further examine the trafficking and neuroanatomical

distribution of primed, bone marrow-derived myeloid cells during SDR, two mouse models were used. The first study used LysM-GFP+ mice, and these

mice express GFP on the lysozyme M (LysM) promoter making peripheral

myeloid cells (monocytes and granulocytes) GFP+ and resident microglia GFP-

(Wohleb et al., 2013). In the second study, GFP+ bone marrow chimeric mice

were created by reconstituting wild-type bone marrow with bone marrow-derived

donor cells that ubiquitously express GFP+ (Wohleb et al., 2013). Therefore, in

this study resident microglia are GFP- and bone marrow-derived cells are GFP+.

The response to SDR was found to stimulate the recruitment of GFP+

macrophages to the perivascular space and brain parenchyma in the PFC, MeA,

and HC, which are brain regions often implicated in the stress response (Wohleb et al., 2013). Additionally, mice that were deficient in chemokine receptors that work to recruit macrophages to the brain such as CCR2 and CX3CR1 (CCR2 KO and CX3CR1 KO), did not develop anxiety-like behavior following SDR, and the

SDR-induced macrophage trafficking did not occur in bone marrow-chimeric mice

generated with CCR2 KO or CXCR1 KO donor cells (Wohleb et al., 2013).

1.5.3 Summary:

SDR activates brain regions associated with threat appraisal mechanisms.

In these regions, activated microglia and brain macrophages recruited from the

periphery contribute to neuroinflammation and correspond well with the

development, maintenance, and resolution of anxiety-like behavior. These effects

can be abrogated with the pretreatment of propranolol or by knocking out IL-1R1,

CCR2, or CX3CR1.

1.6 Disease in the Context of Social Disruption Stress

SDR has been studied extensively in the context of immune and physical

challenge. Repeated social defeat induces an array of neuroendocrine and

immunological changes with the elevation of GCs and catecholamines that are

accompanied by altered cellular and humoral immune functions. These changes 36

can affect susceptibility to infectious disease, allergic challenges and tissue repair mechanisms. Thus, a number of different infectious microbial and allergen challenges (including influenza virus, herpes simplex virus, E. coli bacteria, and

Aspergillus fumigatus extract) as well as cutaneous wounds were studied in the context of social stress.

1.6.1 Physical Injury:

In a cutaneous wounding model, two stressors, restraint and SDR were

studied for their impact on the kinetics of healing (Sheridan et al., 2004). The

nature of the stressor was critical for the rate of healing in that chronic restraint

stress, generally considered to be immunosuppressive in nature, slowed healing,

while SDR, found to be immunoenhancing in nature, was found to heal with

kinetics similar to the non-stressed home cage controls. Thus, in cutaneous

wound healing, the SDR-induced GC resistance was an adaptive mechanism

that allowed proper cell trafficking and inflammatory gene expression at the

wound site despite high levels of SDR-induced circulating GC that would normally suppress these immune functions (Sheridan et al., 2004).

1.6.2 Viral infection

Stress has been shown to increase susceptibility and severity in a number

of experimental viral infections (Biondi and Zannino, 1997). Primary infection

with herpes simplex virus type 1 (HSV-1) virus is a common infection of the

epithelial cells and the trigeminal ganglia. Primary infection results in the

development of a latent infection that recurs periodically in response to a number

of physical and psychological factors (Glaser et al., 1985). To examine the

effects of social stress on a primary HSV-1 infection, an ocular HSV-1 model was used. Following 6 cycles of SDR, BALB/C mice were ocularly infected with the

HSV-1 McKrae strain (Dong-Newsom et al., 2010). During the primary infection,

SDR induced an increase in CD11b+ cells trafficking to the trigeminal ganglia,

increased proinflammatory gene expression and decreased viral protein

expression compared to HSV-infected HCC mice (Dong-Newsom et al., 2010). In

all, SDR appears to have a beneficial effect during a primary HSV infection by

enhancing the immune response, but this may not be the case for recurrent

infections.

To examine the effects of SDR on influenza, Mays et al., (2010) chose to

use an experimental murine model of influenza A viral infection in which primary

immune responses as well as immunological memory (MEM) could be studied.

Following 6 cycles of SDR, mice were infected with an influenza A/PR/8/34 virus

and virus-specific T cell responses in the primary and secondary phases of

immunity were examined. The response to SDR resulted in enhancement of the

function and size of the resting and memory T cell pool (Mays et al., 2010).

Histology in infected SDR mice indicated increased cellular infiltration during

resting memory in the spleen and lung (Mays et al., 2010). SDR enhanced the

number of CD8+ T cells specific for the immunodominant epitope of the

A/PR/8/34 virus at 6-12 weeks post infection suggesting an enhancement of

resting memory (Mays et al., 2010). Following resolution of the primary infection,

SDR mice had enhanced delayed hypersensitivity responses, reduced IgG anti-

influenza titers, and an enhanced IFN-γ response produced by CD4+ T cells upon

viral antigen stimulation ex vivo (Mays et al., 2010).

When mice exposed to SDR during primary infection were reinfected,

termination of viral gene expression and epitope-specific CD8+ T cells in the lung

were increased compared to controls. Overall, SDR prior to influenza challenge

positively impacted cell mediated protection of the animal with an enhanced

antigen specific CD8+ T cell response that included greater clonal expansion and

cell trafficking upon reinfection. In a follow-up study, Mays et al., (2012) further

explored the impact of the enhanced immune response to an influenza viral

infection in SDR mice during the primary infection. Lungs of SDR mice

subsequently infected with A/PR8 virus had a more proinflammatory lung

environment than controls (Mays et al., 2012).

To determine the mechanism of enhanced virus-specific T cell response

following SDR, a study of dendritic cells (DCs) was undertaken. The rationale for

this study was that DCs are a primary antigen processing and presenting cell for

viral antigen. DCs present antigen to T cells that result in clonal amplification

and differentiation (Banchereau and Steinman, 1998). If SDR increased the number of DCs or enhanced their abilities to process and present antigen, then an enhanced T cell response would be expected. In Powell et al., (2009), SDR was shown to activate DCs, increase DC cytokine secretion in response to Toll- specific ligation, and render DCs GC resistant. To determine if the increase in virus-specific T cell responses following SDR were due to an SDR effect on DCs, adoptive transfer of DCs from SDR mice (uninfected) into recipient mice which were subsequently infected (24h after transfer) with A/PR8 virus were studied.

Adoptive transfer of DCs from SDR mice significantly increased the number of epitope-specific T cells, increased IFN-γ and IFN-α mRNA, and decreased influenza M1 mRNA expression (indicating reduced viral replication) in the lung during the peak primary response (9 days post-infection), compared to mice that received DCs from naïve mice (Powell et al., 2009). Data also suggest that SDR had a significant influence on the generation of immunogenic DCs and that these cells enhanced the virus-specific T cell response (Powell et al., 2011).

1.6.2 Bacteria: Endotoxin or LPS challenges

The observation that SDR stimulates the generation of myeloid cells with

enhanced resistance to GCs yielded the hypothesis that SDR mice would be

more sensitive to toxic shock as well. Quan et al., (2001) used an endotoxic

shock model to determine that SDR mice were more sensitive to the lethal

effects of LPS injection. Histology indicated that SDR mice had organ damage

due to inflammation, widespread disseminated intravascular coagulation in the

brain and lung, extensive meningitis in the brain, severe lung hemorrhage, liver

necrosis, and lymphoid hyperplasia in the spleen (Quan et al., 2001). In the

spleen and hippocampus of SDR mice, a reduction in GR gene expression was

found (Quan et al., 2001). SDR also enhanced IL-1β and TNF-α gene expression in brain, liver, lung and spleen, and enhanced IL-1α and TNF-α protein in spleen and liver (Quan et al., 2001). Because SDR mice have immune cell and tissue- specific GC resistance and SDR mice overexpress proinflammatory cytokine genes (normally regulated by cort), it is likely that GC resistance has a role in the increased sensitivity to endotoxic shock. This is a prime example of how SDR can put an organism at risk for excessive inflammation and lethality during infection.

In a model of bacteremia, Bailey et al., (2007) gave one of the first examples of a repeated social stressor that benefited the host’s resistance to bacterial infection. CD11b+ cells from SDR animals were found to have enhanced

microbiocidal activity, ex vivo and in vivo, compared to cells from HCC mice

(Bailey et al., 2007). These mechanisms involved the SDR-induced enhancement of the expression of genes associated with microbiocidal activity in phagocytes (inducible nitric oxide synthase (iNOS) and nicotinamide adenine dinucleotide phosphate (NADPH)) (Bailey et al., 2007). Further, SDR increased the antibacterial activity of splenic macrophages through a TLR dependent pathway (Bailey et al., 2007). Aggressive interactions among male mice often lead to cutaneous wounds in the social stress paradigm, and enhanced microbiocidal activity may be an adaptive strategy by the immune system to offset the risk of bacterial infection. Bailey et al., (2007) also tested the hypothesis that SDR splenic monocytes/macrophages are primed to be more physiologically active than HCC cells. SDR increased the expression of TLR 2 and 4 on the surface of splenic macrophages and increased the ability of these macrophages to kill E. coli ex vivo and in vivo (Bailey et al., 2007). When

C3H/HeJ mice were used, an inbred strain that lacks functional TLR 4, SDR failed to increase the bactericidal activity of splenic macrophages (Bailey et al.,

2007). Furthermore, SDR increases in bactericidal activity were associated with increases in macrophage gene expression for iNOS and subunits of the NADPH oxidase complex that work to generate reactive nitrogen and oxygen intermediates (Bailey et al., 2007). These increases were not seen in C3H/HeJ

SDR mice suggesting that TLR 4 receptors are important for these effects (Bailey et al., 2007). Overall, SDR increases TLR expression and enhances the

bactericidal activity of splenic macrophages by increasing pathways responsible

for reactive oxygen species and nitrogen intermediate production.

In another study, stress-induced cytokine production by peripheral inflammatory cells was further enhanced by stimulation with bacterial particles from an oral microbe Porphyromonas gingivalis (P. gingivalis) (Bailey et al.,

2009a). Those data suggested potential mechanisms through which oral inflammatory diseases and stress are connected. Ex vivo, splenocytes from SDR mice that were stimulated with P. gingivalis-derived LPS had enhanced cell viability in the presence of increasing doses of corticosterone (Bailey et al.,

2009a). Cytokine production of IL-1β and TNF-α was also enhanced in SDR splenocytes stimulated with P. gingivalis LPS in the presence of varying concentrations of cort (Bailey et al., 2009a). It was determined that stress- induced increases in spleen cell viability were dependent upon CD11b+ myeloid

cells, and that in CD11b+ cell depleted cell cultures, P. gingivalis LPS stimulation

induced IL-1β, but not TNF-α, and responses and cell viability were similar to

HCC (Bailey et al., 2009a). For CD11b+ cell enriched SDR splenocyte cultures,

IL-1β and TNF-α production and cell viability were enhanced for all

concentrations of cort (Bailey et al., 2009a). The mechanism through which SDR

enhances cytokine production is not completely understood, but it likely involves

SDR- induced increases in TLRs expression. P. gingivalis-derived LPS or the lipid A core of LPS can activate TLR 2 and stimulate TLR 4 (Darveau et al.,

2004). Macrophages from SDR spleens expressed higher levels of both TLR 2

and TLR 4 (Bailey et al., 2007), and stimulation of TLR is necessary for the

immune effects of SDR (Avitsur et al., 2003). When TLRs are ligated, activation

of signaling cascades are induced that culminate in the activation of transcription

factors, such as NFκB. TNF-α and IL-1β are under the transcriptional control of

NFκB, thus it is likely that SDR enhances TNF-α and IL-1β by increasing TLR- driven NFκB expression. NFκB levels are also higher in nuclear fractions of cells from mice exposed to SDR after stimulation with E. coli-derived LPS (Quan et al.,

2003).

To further explore the mechanisms behind the SDR-induced immunoenhancement, Allen et al., (2012) examined the role of peroxynitrite production in stressor-enhanced bacterial killing. It was known that reactive oxygen and nitrogen species were partly responsible for the enhanced bactericidal activity in CD11b+ cells from SDR mice (Bailey et al., 2009). When

SDR splenocytes were stimulated ex vivo with E. coli for 90 min, SDR splenocytes not only killed more E. coli than did HCC splenocytes, but these cells also had increased iNOS gene expression and the supernatant had increased nitrite production compared to HCC (Allen et al., 2012). Nitrite production was in part dependent upon the dose of IFN-γ in that SDR cells stimulated with the highest dose of IFN-γ produced the most nitrite, and this increase was associated with a significant increase in peroxynitrite (Allen et al., 2012). SDR

increased both superoxide anion and nitric oxide production, and these

intermediates react to form peroxynitrite needed for the stressor-induced

increase in bacterial killing. SDR cells also produced higher amounts of

peroxynitrite when stimulated with phorbol-12-myristate-13-acetate

(PMA)/LPS/IFN-γ than did HCC cells (Allen et al., 2012). The in vitro inhibition of

NADPH oxidase activity eliminated the stressor-induced peroxynitrite production

significantly reduced the stress-induced increase in bacterial killing (Allen et al.,

2012). This effect appears to be mediated by the IL-1R1 as stressor-induced

increases in splenic macrophage activity did not occur in IL-1R1 KO mice. The

KO splenocytes stimulated with E. coli did not have increased bactericidal activity, superoxide production, or production of peroxynitrite compared to SDR wild-type mice (Allen et al., 2012). In this case, IL-1 signaling is important for stressor induced immunopotentiation and inhibition of superoxide or nitric oxide production, and blocking IL-1 signaling inhibits both peroxynitrite production and killing of E. coli. Overall, these data demonstrated that peroxynitrite mediates the stressor-induced increase in bacterial killing.

In the CNS, peripheral innate immune challenge with LPS exaggerated microglia activation, increased number of inflammatory CNS macrophages, and prolonged social withdrawal in socially defeated mice (Wohleb et al., 2012). SDR or HCC mice were peripherally administered saline or LPS and activation of brain

CD11b+ cells and behavioral responses were determined (Wohleb et al., 2012).

With LPS treatment, extended sickness response occurred with exaggerated

weight loss and prolonged social withdrawal in SDR mice (Wohleb et al., 2012).

After LPS administration, SDR mice had extended weight loss, social withdrawal,

elevated plasma IL-6 levels, and increased gene expression of IL-1β, TNF-α, iNOS, and CD14 in enriched CD11b+ cells from the brain (Wohleb et al., 2012).

IL-1β RNA levels in these cells remained elevated for up to 72h after LPS

injection (Wohleb et al., 2012). Furthermore, SDR mice that were administered

LPS had increased CD14 expression on microglia, increased CD11b+/CD45hi

CNS macrophages, increased CNS inflammatory macrophages

(CD11b+/CD45hi/CCR2+), and activated microglia most evident in the

hippocampus (Wohleb et al., 2012). Anxiety-like behavior was increased by SDR,

but was not exacerbated by LPS challenge though reduced locomotor activity

and increased social withdrawal are still present in SDR mice 72h after LPS

(Wohleb et al., 2012). SDR enhanced the neuroinflammatory response and caused prolonged sickness following innate immune challenge (Wohleb et al.,

2012). Overall, immune cells, particularly CD11b+ cells, have increases in TLRs

and are more activated to kill bacteria with increased reactive oxygen and

nitrogen species. However, along with this enhancement, proinflammatory

cytokines can be drastically increased and in the case of endotoxic shock, this

state can increase the chances of lethality.

1.6.3 Allergy

To examine the effects of social stress on the respiratory system, Bailey et

al., (2009b) explored the effects of SDR on allergic airway inflammation in mice

using the extract of the allergen Aspergillus fumigatus (Af). Briefly, CD-1 mice were sensitized twice (on days 0 and 5) with Af and alum, either underwent six cycles of SDR (on days 6-11) or were left undisturbed in their cage (HCC), and on day 13 HCC and SDR mice were either administered an intranasal challenge of Af (sensitized and challenged) and PBS or left undisturbed (sensitized-only).

After 48h post challenge, mice were sacrificed. In this paradigm, SDR inhibited the resolution of allergen-induced airway inflammation and aggravated allergic airway inflammation by modifying innate immune cell production of cytokines

(Bailey et al., 2009b). This effect was mediated by altered corticosteroid action

(Bailey et al., 2009b). When a sensitized, stressed mouse was intranasally challenged with Af, increased eosinophils and lymphocytes were found in bronchoalveolar lavage fluid and respiratory function was diminished as evidence by enhanced airway responsiveness compared to sensitized and challenged

HCC mice (Bailey et al., 2009b). Despite increased serum cort levels in SDR mice, a combination of SDR and allergen challenge enhanced airway inflammation 48h after challenge (Bailey et al., 2009b). There were several cytokine/chemokine genes associated with asthmatic inflammation that were enhanced: IL-5, GM-CSF, IgG1, TNF-α, IL-6, and TARC (Bailey et al., 2009b). It

was determined that SDR inhibits the function (DNA binding) and expression of

(gene and protein levels) of GR in spleen and lung and along with the state of

GC resistance, the SDR sensitized and challenged mice had exacerbated

symptoms (Bailey et al., 2009b). Overall, SDR increases allergen-induced airway

inflammation in a mouse model of asthma and in SDR versus HCC mice

following allergen challenge.

1.7 Preface to the studies in this thesis

To further understand the SDR enhancement of inflammation during challenges, two types of studies were performed in the context of SDR: an allergic airway inflammation model and a bacterial infection model. The choice stemmed from previous data our laboratory has generated with the allergen Af and the LPS of the oral pathogen P. gingivalis. In the first study, we further characterized the state of the SDR animal, which has undergone sensitization and then challenge of an allergen. In our previous findings with the CD-1 mouse, we found that immune cell composition, cytokine and chemokine levels, and resolution of the inflammation were altered by SDR. We extend these findings to the BALB/C mouse, a strain more susceptible to T helper 2 (Th2) response

(allergy is considered a Th2-weighted imbalance), to better understand how stress can affect allergic airway inflammation. This model of Af allergic airway

inflammation with the BALB/C mouse causes a neutrophil-dominant phenotype in

the lung and presumable GC resistance due to the inflammation that occurs even

in the presence of high levels of cort. In humans, asthma patients with a severe

phenotype also display a neutrophil dominant phenotype in the lung and GC resistance, thus suggesting this model may be a relevant model to elucidate severe asthma mechanisms (Monteseirin, 2009). In the second study, we focused on the findings that in vitro P. gingivalis LPS stimulation of SDR

macrophages indicated GC resistance, increased proinflammatory cytokines, and

increased TLRs (Bailey et al., 2009a). We extend this ex vivo work into an in vivo

calvarial inflammation paradigm that models periodontal inflammation. It is a

feasible method that has been used for over a decade to study how local

inflammation with oral pathogens or LPS, can affect tissue destruction and bone

resorption characteristic of periodontal inflammation (Kesavalu et al., 2002).

Furthermore, we decided to use the whole bacteria in a live form to further

replicate the type of infection found in a living host.

CHAPTER 2

Social Stress Induces Increased Immature Neutrophil Release from Bone

Marrow in an Aspergillus Fumigatus-Induced Allergic Airway Inflammation Model

2.1 Introduction

2.1.1 Stress and Asthma

Psychological stress can modulate immune and inflammatory cell function through neuronal and hormonal pathways that link the nervous and immune systems (Dhabhar, 2002; Dhabhar et al., 2012). The stress response elicits the activation of the HPA axis and SNS causing a significant release of GCs and catecholamines in anticipation of the energy shift from homeostasis to the flight or fight response. These GCs and catecholamines can then modulate immune cell differentiation, egress, distribution, and function. This dynamic process begins in the highly adrenergically innervated bone marrow stroma where many of the innate immune cells originate. In the bone marrow, stress can have a significant impact on the type of the cells that are produced and the state of the cells when they are released into circulation en route to the tissue or organ in

need. Accumulation of these cells in organs can contribute to the enhancement

of inflammation, and this inflammation is an important characteristic of the

pathophysiological responses to asthma such as increased airway

hyperresponsiveness, constricted airflow, and delayed resolution. Interestingly,

the stress-induced increase in corticosteroid plasma levels is generally

considered immunosuppressive, yet many previous studies have shown chronic

psychosocial stress as a major factor in the exacerbation of allergic airway

inflammation (Badoux and Levy, 1994; Lehrer, 2006; Rosenkranz et al., 2005).

The 2009 statistics from the Centers for Disease Control estimated

asthma is a $56 billion a year disease. Within the last decade, the explosive

increase in the incidence and prevalence of stress-exacerbated asthma episodes

in the U.S. and the world is staggering (Akinbami et al., 2013; Asher et al., 2006).

Marginalized and minority groups and persons of low socioeconomic status, have

a disproportionate burden of both higher perceived stress and asthma (Forno

and Celedon, 2009). Many studies have documented the association of stress to

an increased frequency and severity of asthmatic episodes (Lind et al., 2013;

Van Lieshout and MacQueen, 2012; Yonas et al., 2012). For example,

longitudinal studies of stressors and asthma in Kuwaiti adults revealed that war- related exposure to stress increased the risk of asthma by two-fold (Wright et al.,

2010). Other studies show that higher perceived stress is associated with decreased asthma control (Wisnivesky et al., 2010). Furthermore, either visual or

auditory distressful experiences can cause asthma patients to have increased bronchoconstriction (Beggs and Curson, 1995; Rosenkranz et al., 2005). Also shown to exacerbate asthma are low social support, depression, social or test anxiety, or post traumatic stress disorder (Liu et al., 2002; Miller and Wood,

2013; Spitzer et al., 2011). The association of stress and exacerbation of asthmatic symptoms appears to be clear, yet the possible mechanisms must be elucidated to generate alternate treatments. Several lines of research focus on the neurocircuitry involved with these responses, while others focus on the cells and mediators that work to exacerbate inflammation (Busse, 2012; Kline and

Rose, 2014; Rosenkranz et al., 2012).

2.1.2 Role of neutrophils in allergic asthma

Asthma is often treated with inhaled corticosteroids and long-acting βAR agonists, yet there exist a large population of patients that are not responsive to these treatments (Chung, 2000). These patients are diagnosed with “therapy resistant asthma” or “severe asthma” (Robinson et al., 2003). These severe asthmatics have a neutrophil-dominant asthma that causes a shift toward the T helper (Th)1-Th17 phenotype, whereas the mild-to-moderate asthmatics tend to have an eosinophil-dominated asthma with a shift toward a Th2 phenotype

(Bogaert et al., 2011; Holgate and Polosa, 2013; Jatakanon et al., 1999; Mann and Chung, 2006). In one review, it was estimated that approximately 50% of 52

asthma cases involved eosinophilic inflammation, while a majority of the other cases involved neutrophils and the chemotactic and activating factor for neutrophils, IL-8 (Douwes et al., 2002).

Following allergen challenge in patients with severe allergic asthma, neutrophils are the first inflammatory cells to accumulate within the airways and are a major contributor to pathogenesis (Monteseirin, 2009). The role of the neutrophils in severe asthma not only involves phagocytosis and the release of enzymes and cytotoxic mediators, but also the production of other mediators such as metalloproteinases, IL-8, and elastase that contribute to asthma pathophysiology (Lee et al., 2006). Specifically, neutrophils produce IL-8 and through autocrine and paracrine mechanisms can enhance recruitment of neutrophils to inflamed tissue and to enhance and prolong the activation status and life of the neutrophil (Monteseirin, 2009). Once in inflamed tissue, neutrophils live much longer than the normal 1 to 2 days, and factors like IgE and GM-CSF can delay neutrophil apoptosis increasing the capacity of the neutrophil to contribute to inflammation and pathogenesis of asthmatic episodes (Saffar et al.,

2007). Additionally, neutrophils are equipped with the machinery such as granules and neutrophil extracellular traps (NETs) that work in concert with other cells to regulate the inflammatory response (Mocsai, 2013).

Both mouse and human data suggest that there is a relationship of the progression of severe asthma to GC resistance in these neutrophils. Many of

these neutrophils are considered activated (i.e., enhanced ability to position themselves at the vascular endothelium in order to migrate into tissue) and have been found to be insensitive to GCs (Corrigan and Loke, 2007). Mouse studies have indicated that it is at the stage of allergic sensitization that a decision is made between eosinophil- versus neutrophil-dominated asthma i.e., GC- sensitive versus GC-resistant asthma (Bogaert et al., 2011). The L-selectin molecule, CD62L, allows the initial binding of leukocytes to the endothelium of the lung in preparation for transmigration. In GC-sensitive or mild asthma, one mechanism of the anti-inflammatory action of GCs is the ability to reduce the expression of CD62L on the immune cell surface, but, in severe asthma, GCs have no effect on the expression of CD62L on circulating neutrophils (Mann and

Chung, 2006). The lack of inhibitory effect of GCs on CD62L in severe asthmatics may be one mechanism that facilitates granulocyte recruitment into sites of inflammation to continue despite therapeutic intervention. This is an interesting finding because chronic oral prednisolone therapy used for treatment of severe asthma is not always therapeutically beneficial. This treatment can exacerbate symptoms by causing the induction of blood neutrophilia attributable to GC-mediated rapid bone marrow release of neutrophils (Jilma et al., 1997).

These data yield potential mechanisms by which a flood of GCs, as it occurs in stress, can affect the gross function and egress of an immune cell.

One mechanism of GC resistance in human cells, may involve increased

expression of the alternatively-spliced variant GR-β. High levels of GR-β have been reported in neutrophils, and these can be upregulated by IL-8, an important chemotactic factor for neutrophils (Strickland et al., 2001). GM-CSF, IL-1 β and

LPS can all induce IL-8 in severe asthmatics even in the presence of therapeutic levels of GCs (Gibson et al., 2001). This highlights the ability of stress-induced increases in GCs to stimulate IL-8 and that GC resistance may play a role in allowing this to occur (Mann and Chung, 2006). Overall, in severe asthma, blood eosinophils are sensitive to suppression by GCs, while neutrophils appear to have lost their sensitivity to being suppressed by GCs and appear to be enhanced instead. This is a significant problem in the treatment of severe asthma in non-stress conditions as well as a significant problem for patients who are prone to stress-exacerbated asthmatic episodes.

2.1.3 CD49d and CD16 expression on neutrophils

In order to generate effective therapeutic interventions for patients diagnosed with severe asthma, it is important to understand the cell most likely involved in the key regulatory aspects of the immune response. It is also important to note that the contribution of the neutrophil to a disease depends on the maturation state of the cell. This idea that the maturation state of a neutrophil can have consequences for disease pathology is relatively new, and data are still 55

being compiled from human and mouse studies to fully understand the

implications of this concept. Normally, the number of circulating neutrophils in a

body is constant, but, after an immune challenge or stress, there is a rapid

release of neutrophils from the bone marrow into circulation. These neutrophils

can be at various stages of maturation with many being considered immature (or

precursor). Outside of histology, the maturation state of neutrophil can be difficult

to characterize, but there exist two surface receptors, CD16 and CD49d, that are

differentially expressed on neutrophils and can be used to elucidate states of

maturation.

For the Fc portion of IgG molecules (FcγR), neutrophils have two types of

receptors, FcRII (CD32) and FcRIII (CD16), which participate in the clearance of

circulating immune complexes (Fossati et al., 2002). When FcγRs interact with

immune complexes, responses are induced that include phagocytosis, activation

of respiratory burst, antibody-dependent cellular cytotoxicity, and secretion of

inflammatory mediators (Fossati et al., 2002). CD16 is found on macrophages,

NK cells, and neutrophils, and it is coded by two homologous genes: FcγRIIIA

(macrophages and NK cells) and FcγRIIIB (neutrophils) (Selvaraj et al., 2004).

CD16 is the most prominent receptor of the FcγRs, and it is expressed far more abundantly on the plasma membrane of neutrophils than CD32 (Selvaraj et al.,

2004).

In flow cytometry, neutrophils can be distinguished, at least partly, from eosinophils by immunostaining with an anti-CD16 antibody. Neutrophils are usually considered CD16 positive, while eosinophils are CD16 negative; however, this is not always the case (Davoine et al., 2002; Gopinath and

Nutman, 1997; Kern et al., 2000; Lukens et al., 2010; Moulding et al., 1999; Riera et al., 2003). Eosinophils can contain intracellular CD16 that can be exposed on the cell surface upon activation or stimulation with IFN-γ, thus making CD16 as a sole definitive marker less than 100% reliable (Davoine et al., 2002). For example, if one gates solely on CD16 negative cells, it would be difficult to distinguish eosinophils from apoptotic neutrophils or neutrophilic myelocytes all of which can be CD16 negative. Furthermore, solely gating on CD16 positive cells will yield activated eosinophils and a heterogenous mix of activated and immature neutrophils. However, by adding a CD49d antibody, one can better distinguish among the different populations of cells.

CD49d, or the α chain of very-late antigen-4 (VLA-4), is a member of the integrin family of cell adhesion molecules. As a receptor, CD49d binds to vascular cell adhesion molecule-1 (VCAM-1) in order to stabilize the adhesion of immune cells to endothelial cells in preparation for transmigration. CD49d is expressed on a broad variety of cells such as eosinophils and monocytes, but is low to negative on resting neutrophils (Lukens et al., 2010; Riera et al., 2003).

However, it is now known that CD49d can be expressed on neutrophils at varying

degrees with low to negative expression on immature neutrophils (especially

promyelocytes and myelocytes) and with higher expression on activated and

functional neutrophils in response to challenge (Dorward et al., 2013; Pliyev et

al., 2012). CD49d has been shown to mediate neutrophil accumulation in

inflammatory diseases including in the air space during allergic lung inflammation

(Cheung et al., 2010). Overall, by first gating granulocytes on high side scatter

(SSC), which is a measure of granularity and can help eliminate the monocyte

population, cells can then be gated on CD49d and CD16 to reveal several

distinct populations that can lend insight into the maturation state of the

neutrophil in an immune- and/or stress-challenged context.

The literature has described the expression levels of CD16 on neutrophils as being a spectrum. In particular, during the course of a respiratory syncytial virus infection, Lukens et al., (2010) identified a significant population of neutrophils that had intermediate CD16 expression that corresponded with increased disease pathogenesis. Cytospins were performed, and the granulocytes were sorted on three different populations: CD16 negative, CD16

intermediate and CD16 high. These cells were then May-Günwald Giemsa

stained and reviewed by a pathologist. The CD16 negative cells were determined

to be a population of eosinophils. The CD16 low cells were described to be a

population of apoptotic neutrophils. The CD16 high cells were determined to be a

population of mature/activated neutrophils. Finally, the CD16 intermediate

population of cells was determined to be a heterogeneous mix of myelocytes,

metamyelocytes, and banded neutrophils, which are the younger, less well

differentiated immature neutrophils that normally reside in the bone marrow.

Evidence from other studies can give us further insight into the identification of these specific populations. Neutrophil populations with low expression of CD16 can be indicative of cells with compromised neutrophilic functions due to prior activation or degranulation and/or clearance of circulating immune complexes (Meddows-Taylor et al., 1997). Neutrophils kill microorganisms either via oxidative processes, through activation of NADPH oxidase and subsequent production of toxic oxygen intermediates, or via nonoxidative means, through the release of potent antimicrobial polypeptides that reside within cytoplasmic granules (Meddows-Taylor et al., 1997). Activation of

CD16 elicits neutrophil degranulation, reduces surface expression of CD16, and suggests prior use of the nonoxidative defense mechanisms (Meddows-Taylor et al., 1997). CD49d can be helpful in further distinguishing these cells. When the cell is both CD49d positive and CD16 negative, this is indicative of a cell population of eosinophils (Lukens et al., 2010). However, when the population of cells is negative for both CD49d and CD16, this population likely consists of apoptotic neutrophils (Moulding et al., 1999; Lukens et al., 2010).

Because neutrophils are committed to an apoptotic pathway, they possess a very short half-life in circulation (6-12h) (Moulding et al., 1999). When the

neutrophils arrive at the site of inflammation they further activate and mature to perform their roles in innate immune system defense. Afterwards, removal of these neutrophils usually involves apoptosis and phagocytosis by macrophages

(Dransfield et al., 1994). Progression into an apoptotic state is characterized by the rounding and condensation of the normally characteristic multi-lobed nucleus, cell shrinkage, and the loss of functions such as chemotaxis, phagocytosis degranulation, and activation of the respiratory burst (Moulding et al., 1999). As apoptotic morphology increases, a decrease in surface expression of CD16 occurs with the help of metalloproteinases that cleave the receptor from the plasma membrane (Dransfield et al., 1994). On the other hand, CD16 is actively synthesized and expressed by mature neutrophils (CD16 high), and its expression may be upregulated by GM-CSF (Elghetany et al., 2004;Tsuda et al.,

2004). Although GM-CSF can precipitate the shedding of CD16, GM-CSF also stimulates neutrophil gene expression, protects cells from apoptosis, and maintains expression of surface CD16 by mobilization of the internal pool of

CD16 (Moulding et al., 1999).

The bone marrow is the primary site of neutrophil production and holds a reservoir of neutrophils that can be rapidly released and mobilized in response to infection or stress (Bogaert et al., 2011). Both CD49d and CD16 appear to be good indicators of immature neutrophil status with CD16 intermediate and CD49d low expression on neutrophils indicative of immature status (Lukens et al., 2010).

Immature neutrophils in circulation are not fully differentiated when released from the bone marrow, and consequently, the expression of CD16, which is normally upregulated on neutrophils at the metamyelocyte stage, is reduced (Elghetany et al., 2004). Within this immature pool of neutrophils, low CD49d expression can also be found on metamyelocytes, promyelocytes, and myelocytes, while band and segmented cells can be negative for CD49d expression (Pilyev et al., 2012;

Elghetany et. al., 2004). In circulation, this significant increase in immature neutrophils is referred to as a “left shift” or a leukemoid reaction (Orr et al., 2005).

These immature neutrophils have increased amounts of toxic granule contents such as alkaline phosphatase, and a “left shift” in a patient can be identified in the clinic by determining the alkaline phosphatase score per neutrophil.

The physiological state of neutrophilia can have profound consequences on and contributions to inflammation. Despite their immaturity, these cells can still mediate innate immune functions and are thought to have the capability of maturing (Drifte et al., 2013). A recent study of the innate immune functions of immature neutrophils revealed that these cells have classical phagocytic innate immune functions that may compromise some functions (e.g., phagocytosis and respiratory burst) in response to bacteria, but that these neutrophils are more resistant to apoptosis and capable of maturation (Drifte et al., 2013). It is thought that when these cells are able to get to the tissue they will have the ability to mature if the conditions are favorable (i.e., increased GM-CSF). Altogether, the

role of immature neutrophils in disease has not been fully elucidated, but it is

certain that the presence of these neutrophils is associated with states of

inflammation.

2.1.4 Animal models of allergic asthma

Ethical and logistical concerns can limit the ability to study of stress and

asthma in humans. In humans, asthma presents with a myriad of symptoms such as airway hyperresponsiveness, airway tissue remodeling, bronchoconstriction, and inflammation. Animal models may not be able to replicate all of the symptoms of the disease as a whole, but they can sufficiently serve to replicate

aspects of the disease that can elucidate potential therapeutic targets or clinical

interventions. In the study of allergic asthma, mouse models, in particular, are

widely available, well-characterized, and easily manipulated to focus on

mechanisms of disease parameters such as inflammation or immune cell

infiltration.

Two of the most commonly used allergens for allergic airway inflammation

models are chicken egg ovalbumin (OVA) and Aspergillus fumigatus (Af) extract.

OVA is the most commonly used allergen to elicit allergic airway inflammation in

mice, but it has been suggested that endotoxins such as LPS must be added to

the challenge adjuvant in order to get a proper Th2 response (Eisenbarth et al.,

2002). Compared to OVA, Af is considered a naturally occurring allergen and

more relevant to human disease. Af is the most common trigger for allergic airway inflammation in humans in that it is the most common fungal spore found in indoor spaces at risk for mold (Chaudhary and Marr, 2011). Spores (conidia) can remain suspended in air for long periods putting humans at risk for inhalation. For most people, Af exposure is asymptomatic, but for the immunocompromised and those at risk for asthma and allergy, Af sensitization can be symptomatic. Once the airborne conidia are inhaled, they will germinate in the lung, grow as hyphae, and cause disease (Latge, 1999). Af exposure can increase mortality in the immunocompromised, while, in others, it can increase allergic diseases such as allergic asthma. The most common protocol to induce allergic airway inflammation in the laboratory involves one or more sensitization steps where the animal is introduced, usually intraperitoneally, to the allergen and then one or more challenge steps where the allergen is introduced intranasally into the animal. These steps can span the length of 2 or 3 weeks to study acute effects or 8 or more weeks to study chronic effects.

Consideration of the type of asthma (i.e., neutrophilic vs. eosinophilic or mild vs. severe) generated by animal models depends on the choice of the strain of mice and allergen. In order to create a neutrophil-dominated phenotype, some

researchers have used C57BL/6 mice and OVA-based sensitization and

challenge paradigm (Bogaert et al., 2011). In another study, C57BL/6 and

BALB/C mice sensitized and challenged with OVA had airways that were nearly

exclusively characterized by neutrophilic infiltration that was transient and

followed later by an influx of eosinophils and lymphocytes (Taube et al., 2003).

Another study used BALB/C mice that were intraperitoneally sensitized and

intranasally challenged with OVA reached an airway eosinophils level of 80%

(Wilson et al., 2009). When these authors manipulated the OVA model by

sensitizing intranasally rather than intraperitoneally, a strong neutrophilic

response was seen in the lungs (Wilson et al., 2009). Although there are many

genetically manipulated strains of mice on the C57BL/6 background that make

this strain appealing for allergic asthma research, the BALB/C mouse is a more

popular mouse due to its tendency toward Th2-mediated immune response

(Schroder and Maurer, 2007).

In Af-based paradigms, the strain of mouse used and the protocol for sensitization and challenge can affect the immune cell profile. In BALB/C mice, over the course of a month, Hackzu et al., (2001) sensitized mice twice and

challenged mice three times with Af. In this paradigm, they were able to show

enhanced eosinophilia (Haczku et al., 2001) . Furthermore, in Bailey et al.,

(2009b), CD-1 outbred mice, sensitized twice and challenged once with Af, showed enhanced eosinophilia. Pandey et al., (2013) found enhanced neutrophil infiltration when over the course of 6 weeks BALB/C mice were sensitized once, intranasally challenged once weekly for 3 weeks, and then challenged again with

aerosolized Af (Pandey et al., 2013). Other studies with BALB/C mice and Af found neutrophils to be a dominant cell type during allergic airway inflammation

(Shevchenko et al., 2013).

Primarily at early time points following Af challenge, there appears to be an essential role for neutrophils and not alveolar macrophages (Mircescu et al.,

2009). Both cells contribute to the innate immune defense against Af, but, in selective depletion murine studies, mice depleted of neutrophils were associated with high mortality, and macrophages were considered redundant for the defense

(Mircescu et al., 2009). Alveolar macrophages are credited with controlling the conidia infection, but neutrophils work to kill hyphae once germination occurs

(Schaffer et al., 1982). Overall, neutrophils are considered the key effector cell population to defend against Af, and neutropenic patients, or patients with compromised neutrophilic function, are at a high risk for occurrence (Feldmesser,

2006). More research is still necessary to understand neutrophil-dominated asthma subphenotypes and to better understand the immunology of eosinophilic versus neutrophilic asthma types. It is important to note that selection of the appropriate model is crucial when studying the progression of neutrophil- dominated asthma and stress-exacerbated neutrophil-dominated asthma.

2.1.5 SDR and Allergic Airway Aspergillus Fumigatus (Af) Model

In this chapter, the SDR paradigm will be utilized to further explore how stress modulates the enhancement of allergic airway inflammation and the peripheral consequences of this enhancement. SDR treatment contributes to the increase of CD11b+ cells in the bone marrow, spleen, lung, and blood (Engler et al., 2005; Curry et al., 2010). In the bone marrow, SDR contributes to the decrease of the percentage of lymphocytes and erythrocytes and nearly doubles the number of monocytes and granulocytes (Engler et al., 2005). The increase of myelopoiesis results in an increased proportion of immature cells that are released from the bone marrow (Engler et al., 2005). The cycle dependent increase of these immature cells corresponds well with increases in GM-CSF expression in the bone marrow that is associated with the release (Engler et al.,

2005). It is also known that SDR increases the number of neutrophils in the blood and lung (Curry et al., 2010). Particularly in the lung, these neutrophils are likely to contribute to the pulmonary inflammation that occurs as a result of SDR (Curry et al., 2010). In Bailey et al. (2009b), Af challenge in CD-1 mice (outbred) caused eosinophilic airway inflammation and increased levels of IL-5, GM-CSF, TNF-α, and IL-6 in airways and increased airway hyperresponsiveness to methacholine.

SDR significantly enhanced this inflammatory response and delayed the resolution of the allergen challenge. Additionally, GC receptor gene and protein expression in the lungs of SDR Af sensitized and challenged mice were

significantly reduced compared to HCC. Overall, SDR treatment and subsequent

sensitization and challenge with an allergen-enhanced allergic airway

inflammation and altered GC sensitivity.

2.1.6 Overall Aim of Experiments

The major hypothesis for this research was that social stress enhances

allergic airway inflammation by shifting the balance of myelopoesis in the bone

marrow resulting in the release of immature, less well-differentiated neutrophils

and immature neutrophils in the blood that traffic to the lung. For this research,

the BALB/C strain of mouse was selected in an attempt to enhance the response

to allergic airway inflammation and to eliminate the variability that an outbred

strain might cause.

2.2 Methods

2.2.1 Animals

Male BALB/C and male BALB/C/GFP+ transgenic animals (6-8 weeks old)

and CD-1 (retired breeders) were purchased from a commercial source (BALB/C

Jackson Laboratories, Bar Harbor, ME; CD-1, Charles River Inc, Wilmington,

MA) and were allowed to acclimate to surroundings for a week prior to

experimentation. Wild-type BALB/C mice were housed 3 per cage and the

transgenic BALB/C and CD-1 mice were singly-housed. All mice were housed in an American Association for the Accreditation of Laboratory Animal Care

(AAALAC) accredited facility and were maintained under environmentally

controlled conditions on a 12:12h light:dark cycle with ad libitum access to food and water. The Institutional Animal Care and Use Committee (IACUC) of The

Ohio State University approved all experimental animals and protocols used in this study.

2.2.2 Bone marrow chimeras

Recipient mice were administered 25 mg/kg of busulfan i.p. to partially

ablate the bone marrow and allow room for engraftment for donor cells. Twenty-

four hours later, femur and tibia were harvested from GFP+ transgenic BALB/C mice. Bone marrow cells were flushed from bone with PBS, cells were strained through a 70 μM mesh filter, and washed with PBS. Cells were then counted and resuspended to 1 million cells per 100ul in PBS. Recipient mice were then intravenously injected with 1 million cells, and engraftment was allowed to occur over four weeks time. At four weeks, a steady-state number of GFP+ cells was

found in circulation (Wohleb et al., 2013). This protocol is illustrated in Figure 2.1.

2.2.3 Social disruption stress:

SDR was performed as previously described (Stark et al., 2001) with some modifications due to the use of BALB/C mice. The SDR paradigm is based on the social defeat experience of group-housed male mice in their home cage.

This social defeat was induced in the residents by daily confrontations with an intruder male aggressor mouse. The confrontations occurred at the beginning of the active phase (17:00) when an aggressor mouse was placed in the cage of the resident mice. The aggressors attacked the unfamiliar mice within the first minutes of the confrontation and continue brief, yet consistent, attacks for the length of the SDR cycle (for the BALB/C mice, the cycle was 20 minutes).

BALB/C mice are hypersensitive to stress and a reduction in exposure to the intruder was necessary to prevent morbidity. Through experimentation, it was found that a 20 min exposure to the stressor was sufficient to induce effects characteristic of SDR (increased CD11b+ cells in spleen and splenomegaly).

During these attacks, the residents either initiated the display of submissive behavior (e.g., flight, defensive upright posture, retreat, and crouch) or aggressive behavior (e.g., fighting back). In any case, the aggressor mouse won any confrontation with the residents because the aggressor was older, larger,

and, due to its retired breeder status, has had previous social experience being

the sole dominant male in a cage. If the intruder did not initiate an attack within

5–10 min, or was attacked by any of the resident mice, then a new intruder was

introduced. At the end of the SDR cycle, the intruder was removed and the

residents were left undisturbed until the following day when the paradigm was

repeated.

Home-cage control (HCC) mice were also housed in cohorts of 3-5 per

cage, but were left undisturbed in a separate room. To minimize distress

experienced by control animals, SDR was performed in a separate room. SDR

treatment consisted of 6 cycles over 6 consecutive days, and a new aggressor

was used for each cycle. All animals were carefully inspected for injuries after

each SDR cycle, and an occasional mouse with significant cutaneous wounds

(<5% in previously published studies) was removed from the study.

2.2.4 Allergic sensitization and challenge

Mice were sensitized with intraperitoneal injection of 20 µg of Aspergillus

fumigatus (Af) extract (Hollister-Stier Laboratories LLC, Spokane, WA) and 20

mg of Al(OH)3 (Imject Alum; Pierce, Rockford, IL) in PBS (100 µl) on days 0 and

5 (Bailey et al., 2009b). Mice assigned to the stress condition were exposed to

SDR on days 6–11, and HCC mice were left undisturbed. On day 13, all sensitized mice were intranasally (i.n.) challenged with10 µg of Af in PBS (30 µl) and then sacrificed by an overdose of Ketamine/Xylazine (78mg/mL ketamine and 4.4mL of Xylazine per kg in 250μL) on day 15. Cardiac blood and spleens

were harvested immediately after overdose. The following groups of mice were

used: SHCC (sensitized controls), SSDR (SDR stress, Af sensitization, and no challenge), SCHCC (no stress, Af sensitization and challenge), and SCSDR

(SDR stress, Af sensitization, and challenge). This protocol is illustrated in

Figure 2.3.

2.2.5 Flow cytometric analysis of splenocytes

Single-cell suspensions were derived from spleen, blood, and bone

marrow (1x106 cells per sample) as previously reported (Powell et al., 2013) and were incubated with1μg each of fluorescently-labeled monoclonal antibodies (or the appropriate isotype controls). Antibody labeling was performed at 4°C for 45 min. The cells were then washed twice in PBS containing 5% FBS and 0.09%

NaN3. All antibodies were obtained from BD Pharmingen (San Jose, CA),

including FITC-labeled anti-Ly6C, anti-CD11b, anti-CD11c, and anti-CD-16, PE-

labeled anti-CD31, anti-CD3, and anti-CD49d, PerCP-labeled anti-Ly6C, anti-

B220, and anti-CD4, and APC-labeled anti-CD11b, anti-CD8, anti-CCR2, anti-

CD31, anti-CXCR2. Ten thousand events were analyzed on a FACSCalibur flow

cytometer using Cell Quest and FlowJo analysis software (Tree Star Inc,

Ashland, OR), viable cells were first gated, and then leukocytes were gated based on forward versus side scatter. In some analyses, high side scatter was used to gate granulocytes from monocytes. 71

2.2.6 Hematoxylin and eosin staining of apical lobe of lung

The apical lobe of the lung was harvested, encephlated with and fixed in

10% formalin and embedded in paraffin as performed in Curry et al., (2010).

Sections (5uM) were cut, mounted on slides, and stained with hematoxylin and

eosin. Slides were imaged on a Leica DM 5000 microscope under 40X and 100X

magnification.

2.2.7 Alkaline Phosphatase Assay

The apical lobe of lungs were harvested, flash frozen in liquid nitrogen,

and stored at -80°C until processed for use in a colorimetric alkaline phosphatase

detection kit (Abcam, Cambridge MA) as per manufacturer’s protocol.

2.2.8 Corticosterone EIA

Immediately before sacrifice and within 1 min of disturbing the cage, blood for plasma was collected in heparin coated tubes by retro-orbital plexus bleed.

Blood was centrifuged at 3500 rpm for 25 min, the plasma layer carefully removed, and stored at -80°C until assayed. Corticosterone EIA (Enzo Life

Sciences Inc., Farmingdale, NY) was performed using the small volume plasma

protocol as per manufacturer’s protocol.

2.2.9 Real Time PCR

In all studies, tissues were flash frozen in liquid nitrogen, and RNA was subsequently extracted using the Trizol RNA isolation reagent (Invitrogen;

Carlsbad, CA). cDNA was obtained using a reverse transcription kit (Invitrogen;

Carlsbad, CA). RT-qPCR was performed using an ABI Prism 7000 Sequence

Detection System (Applied Biosystems; Foster City, CA) with specific primers and TaqMan probes (Applied Biosystems) for the genes of interest. All PCR experiments was conducted in triplicate, and data were analyzed by using the 2-

ΔΔCt method and normalized to 18s rRNA.

2.2.10 Statistical Analysis

Data were analyzed using Graph Pad Statistical Software (La Jolla, Ca).

Statistical significance was determined using a one or two -way ANOVA with

Dunnett’s or Tukey’s post hoc test or unpaired t test as appropriate. Grubb’s

outlier tests were performed on all data due to the high variability that can be

found with SDR samples. In all cases, the level of significance was set at an α =

0.05. Data are expressed as means +/- SEM. 73

2.3 Results

2.3.1 GFP+ bone marrow chimeras

In this chapter, we used SDR and an allergic airway inflammation model

utilizing Aspergillus fumigatus (Af) extract as an allergen for sensitization and challenge. In the first series of experiments, we explored and confirmed the identity of the cell populations that are thought to egress from bone marrow and traffic to the lung of stressed and Af sensitized and challenged mice. To do this, we used a GFP+ bone marrow-chimeric model that our laboratory adapted to

track myeloid progenitor cells from the bone marrow to target organs. Figure 2.1

shows the basic protocol used to create the GFP+ bone marrow-chimeric mice.

Recipient mice were administered busulfan (25 mg/kg i.p), a chemotherapeutic

agent, to allow space for engraftment of donor cells in recipient bone marrow

cavity. One million GFP-tagged cells from donor bone marrow were then injected

(i.v.) into recipient mice, and engraftment was allowed to proceed for 30 days.

After engraftment, the animals were subjected to SDR and other experimental

procedures.

In the first experiment, the bone marrow, lung, and spleens of HCC and

SDR GFP+ bone marrow-chimeric mice were subjected to histological and flow

cytometrical analysis. As a confirmation for engraftment, levels of GFP+ cells

were determined in the bone marrow. The HCC and SDR mice presented in this

study had similar numbers of GFP+ cells in the bone marrow confirming similar 74

engraftment (Figure 2.2A). Histological assessment of spleens of GFP+ bone

marrow-chimeric mice showed that the SDR group had larger spleens with a

higher number of GFP+ cells that densely aggregated in the marginal zones of

the germinal centers, which is a region rich in myeloid-derived cells (Figure

2.2B). Histological assessment of the lungs of GFP+ bone marrow-chimeric mice

showed an increase in GFP+ cells in SDR lungs compared to HCC (Figure 2.2B).

Flow cytometric analyses indicated a significant increase in the percentage of

GFP+/CD11b+ cells in the spleen (t(10)=4.303; p=0.0016) and lung (t(10)=2.489;

p=0.0321) that quantitatively confirmed the histological findings (Figure 2.2B).

2.3.2 GFP+ bone marrow chimeras and Af sensitization, stress, and Af

challenge

Figure 2.3 illustrates the sensitization, SDR, and challenge protocol

utilized for the rest of the experiments in this chapter. BALB/C mice were

sensitized on day 0 and 5 with an intraperitoneal injection of 20 μg of Aspergillus fumigatus (Af) extract and 20 mg of alum to enhance allergenicity. Mice assigned to the stress protocol were exposed to SDR on days 6-11, and mice that were assigned to HCC were undisturbed during these days. On day 13, mice assigned to the challenge condition (SCHCC and SCHCC) were intranasally challenged with10ug of Af allergen in PBS, and mice assigned to the sensitization only

(SHCC and SSDR) were undisturbed. Forty-eight hours later, all mice were

sacrificed by ketamine/xylazine overdose.

Using the GFP+ bone marrow chimera protocol (Figure 2.1), in conjunction

with the sensitization, SDR, and challenge protocol (Figure 2.3), we determined

the trafficking of GFP+ cells, GFP+ cells that were also CD11b+, Ly6C+, and

CD11b+/Ly6C+ cells from the bone marrow into circulation and into the lung.

Stress alone did not significantly increase percent total of GFP+ cells in the bone

marrow or blood. However, challenge and stress and challenge did increase the

percent total of GFP+ cells in the bone marrow (stress X challenge interaction;

F(3,32)=290, p<0.0001) and blood (main effects of stress and challenge;

F(3,32)=36.80, p<0.0001) of SCHCC and SCSDR mice compared to sensitized

controls (Table 2.1 A,B).

Stress alone or challenge increased the percent total GFP+ cells in the

lung (Table 2.1C; stress X challenge interaction, F(3,28)=14.53, p<0.0001 ). In the bone marrow, blood, and lung, stress alone or Af challenge contributed to increases in GFP+ cells that were also CD11b+ , Ly6C+, or CD11b+/Ly6C+(Table

2.1A-C). [(GFP+ /CD11b+: bone marrow: stress X challenge interaction,

F(3,32)=117.8, p<0.0001; blood: main effects of stress and challenge,

F(3,32)=14.50, p<0.0001; lung: stress X challenge interaction, F(3,32)=27.87, p<0.0001.) (GFP+ /Ly6C+ : bone marrow: stress X challenge interaction,

F(3,32)=16.59, p<0.0001; blood: main effects of stress and challenge,

F(3,32)=14.27, p<0.0001, lung: main effect of stress, F(3,32)=6.079, p=0.0021.)

(GFP+ CD11b +/Ly6C+ : bone marrow: main effects of stress and challenge,

F(3,32)=29.58, p<0.0001; blood: main effects of stress and challenge,

F(3,32)=29.84, p<0.0001, lung: main effects of stress and challenge

F(3,32)=5.669, p=0.0031)]. In the blood, GFP+ cells that were CD11b+/Ly6C+

were increased by stress and challenge compared to all other groups (Table

2.1B).

The bone marrow results, in particular, made us reconsider utilizing the

GFP chimera for the other experiments involving cell phenotyping. Challenge and

stress and challenge appeared to have effects on the percentage of GFP+ bone marrow cells in the bone marrow. There was more than twice the number of

GFP+ cells in the bone marrow of sensitized and challenged mice compared to

sensitized HCC or SDR bone marrow. The GFP bone marrow chimera

addressed the question as to the origin of the increases in monocyte populations,

but for the remainder of the experiments the sensitization, SDR, and challenge

protocol was utilized (Figure 2.3).

SDR is known to increase CD11b+ cells in the bone marrow, spleen, and

blood in response to SDR (Engler et al., 2004a). These data indicated that the

increase in splenic CD11b+ cells was likely due to an influx of myeloid derived

CD11b+ cells of bone marrow origin. Utilizing flow cytometry, the distribution of

monocytes, lymphocytes, granulocytes, and erythrocytes were determined in the

bone marrow, blood, and spleen of SHCC, SSDR, SCHCC, and SCSDR mice

using a panel of antibodies (FITC-conjugated anti-Ly6C and PE-conjugated anti-

CD31). Cell populations were determined by differential expression of Ly6C and

CD31: lymphoid cells Ly6C-/CD31+, erythroid cells Ly6C-/CD31-, monocytes

CD31+/Ly6Chi, and granulocytes Ly6Cint/CD31lo (Figure 2.4). Mixed progenitors

were not included in the analyses. In cell populations in the bone marrow of

sensitized mice, stress increased granulocytes (t(16)=2.577; p=0.0202), while

erythrocytes (t(16)=0.0302; p=2.378) and lymphocytes (t(16)=2.158; p=0.0465) were decreased (Figure 2.4A). In bone marrow cell populations of sensitized and challenged mice, granulocytes (t(16)=3.416; p=0.0035) were increased by stress and challenge (SCSDR) while erythrocytes (t(16)=4.323; p=0.0005) and lymphocytes (t(16)=6.395; p<0.0001) were decreased compared to control challenged (SCHCC) mice (Figure 2.4B). These results point to a population of cells, namely granulocytes that originate in the bone marrow, which was increased because of SDR in the absence and presence of challenge. Overall, stress shifted myelopoesis in sensitized and sensitized challenged bone marrow.

Next, chemokine receptor expression on CD11b+ cells was examined in

the bone marrow, blood, and lung. Stress increased the percentage of total

CD11b+ cells in the bone marrow and lung, challenge alone increased these cells

in the lung, and challenge and stress increased these cells in the bone marrow

and decreased these cells in the blood (Table 2.2; bone marrow: F(3,44)=9.111,

p<0.0001; blood: F(3,44)=3.930, p=0.0144; lung: F(3,44)=113.7, p<0.0001). In

the bone marrow, stress or challenge significantly increased CD11b+ cells that

+ + + were also CCR2 , CXCR4 , and CD31 (Table 2.2A; CCR2: F(3,44)=8.637,

p=0.0001; CXCR4: F(3,44)=6.481, p=0.001; CD31: F(3,44)=24.44, p<0.0001). In

+ + the blood, the percent of cells that were CD11b and CCR2 were decreased in

SCHCC, and the percent of cells that were CD11b+ and CD31+ were decreased

in challenged mice (Table 2.2 B; main effect of challenge, CCR2: F(3,44)=2.854,

p=0.0479; main effect of challenge CD31: F(3,44)=3.304, p<=0.0288). Stress

+ + increased the percentage of CD11b /CCR2 cells in sensitized and sensitized

and challenged lungs and stress or challenge increased percentage of

+ + CD11b /CXCR4 cells in lungs compared to SHCC (Table 2.2C; main effect of

stress, CCR2: F(3,44)=3.381, p=0.0301; main effects of stress and challenge,

CXCR4: F(3,44)=6.702, p=0.008). Challenge increased the percentage of

CD11b+/CD31+ cells in the lung compared to sensitized controls (Table 2.2C; main effect of challenge, F(3,44)=25.84, p<0.0001).

To further delineate the phenotype of immune cells that could contribute to

the SDR-induced enhancement of inflammation seen in Bailey et al., (2009b) and our model, we looked at other cell populations in the spleen and lung (Table 2.3).

In the spleen, T cells (CD3+ (F(3,44)=1.800, p=0.1611), CD3+/CD4+

(F(3,44)=0.6846, p=0.5663), and CD3+/CD8+ (F(3,44)=1.015, p=0.3953) and

plasmacytoid dendritic cells (CD11b+/CD11c+/B220+ F(3,44)=2.577, p=0.0658)

were not altered by stress or Af challenge (Table 2.3A). However, B cells were

increased (B220+; main effect of challenge (F(3,44)=3.521, p=0.0226) and

conventional dendritic cells were decreased (CD11b+/CD11c+/B220-; main effect

of challenge; F(3,44)=34.69, p<0.0001) in SCHCC spleens (Table 2.3A).

In the lung, T cells (CD3+ (F(3,44)=2.432, p=0.0777), CD3+/CD4+

(F(3,44)=0.7749, p=0.5143), and CD3+/CD8+ (F(3,44)=0.4551, p=0.7150), B

cells (B220+ (F(3,44)=1.196, p=0.3223), and conventional

(CD11b+/CD11c+/B220- F(3,44)=1.407, p=0.2534) and plasmacytoid

(CD11b+/CD11c+/B220+ F(3,44)=0.8445, p=0.4769) dendritic cells were not altered by stress or Af challenge (Table 2.3B). Overall, stress and Af challenge

did not induce significant alterations in T, B, or dendritic cells in the spleen or

lungs.

SDR and various inflammatory challenges are known to activate the HPA

axis. To effect the combined effects of SDR and allergen on the HPA axis,

corticosterone was measured from plasma collected 48h after intranasal Af

challenge of sensitized HCC and SDR mice (Figure 2.5). Plasma corticosterone

was significantly increased in SDR Af challenged mice (SCSDR; stress X

challenge interaction; F(3,44)=12.28, p<0.0001).

2.3.3 Stress and/or Af challenge effects on monocytes and granulocytes

We then examined the effects of stress and Af challenge on the innate

immune response. The percentage of CD11b+/Ly6Chi monocytes in the bone

marrow, blood, spleen, and lung was measured (Figure 2.6). Stress and Af

challenge (SSDR and SCSDR) increased the percentage of CD11b+/Ly6Chi

monocytes in the bone marrow (Figure 2.6A; stress X challenge interaction,

F(3,44)=10.35, p<0.0001). Stress and Af challenge (SSDR and SCSDR) increased CD11b+/Ly6Chi monocytes in the spleen (Figure 2.6B,C; main effects

of stress and challenge, F(3,44)=8.063, p=0.0002). Stress increased the

percentage of monocytes in both Af sensitized and Af sensitized and challenged

lung compared to controls (Figure 2.6D; main effect of stress, F(3,44)=4.330,

p=0.0093).

We then looked at the effects of stress and Af challenge on the

percentage of CD11b+/Ly6Cint granulocytes in the bone marrow, blood, spleen,

and lung (Figure 2.7A-D). Stress, Af challenge (SCHCC), and stress and challenge (SCSDR) increased granulocytes in blood (main effects of stress and challenge, F(3,44)=14.43, p<0.0001), spleen (main effects of stress and challenge, F(3,44)=8.765, p=0.0001), and lung (main effects of stress and challenge, F(3,44)=16.21, p<0.0001) compared to SHCC (Figure 2.7B-D). Af

challenge and stress increased granulocytes in SCSDR spleen and lung over all

other groups (Figure 2.7C,D). Together with the previous data, monocytes and

granulocytes appeared to be the cells mobilized in response to stress and

granulocytes appeared to be the main effector cell mobilized in response to

stress and Af challenge.

2.3.4 Gene expression in the lung

To examine the effect of increased cellular infiltration and to determine if increased inflammation was present, a portion of the lung (apical lobe) was collected for gene expression analysis (Figure 2.8). In the lung, stress (SSDR) and stress and challenge (SCSDR) induced an increase in IL-1β (Figure 2.8A; stress X challenge interaction; F(3,32)=124.4, p<0.0001), TNF-α (Figure 2.8B; stress X challenge interaction; F(3,32)=28.40, p<0.0001), and GM-CSF (Figure

2.8E; main effects of stress and challenge; F(3,32)=11.71, p<0.0001) gene expression compared to SHCC. Af challenge alone (SCHCC) increased IL-4

(Figure 2.8C; stress X challenge interaction; F(3,32)=56.53, p<0.0001) and IL-10

(Figure 2.8C; main effect of challenge; F(3,32)=10.57, p<0.0001) compared to sensitized controls. Stress and Af challenge (SCSDR) increased IL-1β, TNF-α,

IL-4, IL-10, and GM-CSF gene expression compared to all other groups.

2.3.5 Neutrophils in the lungs

Because of increased granulocytic trafficking from the circulation to the

lung, we examined the effect of SDR and Af challenge on the environment of the lung. After gating granulocytes on high side-scatter (SSC), a measure of granularity, CD16+ cell populations could be considered largely neutrophilic.

Stress alone and challenge alone increased CD16+ cells in the lung compared to

SHCC, while stress and challenge (SCSDR) increased total CD16+ cells in the

lung compared to all other groups (Figure 2.9; main effects of stress and

challenge, F(3,44)=44, p<0.0001).

Based on the dual expression of CD49d and CD16, several cell

populations could be observed in the flow cytometric analyses of the lung

homogenates. Figure 2.10A shows a chart, derived from the literature, which lists

the differential expression of these two receptors that reflect the various

neutrophil subtypes. In Figure 2.10B, a representative flow cytometric contour

map of SCSDR lung cells dual labeled for CD49d and CD16 is shown. When

gating these lung granulocytes on CD16 and CD49d, it was evident that five

distinct populations could be visualized in the lung. Using the references from

Figure 2.10A, the various subpopulations can be identified: mature neutrophils

are CD49dint-lo/CD16hi, activated neutrophils are CD49dint /CD16int, immature

neutrophils are CD49dlo-neg / CD16int-lo, eosinophils are CD49dlo /CD16lo-neg, and

apoptotic neutrophils are CD49-/CD16- (Figure 2.10C). Finally, an illustration of

these cells and their usual tissue locations are depicted in Figure 2.10D.

Af challenge (SCHCC and SCSDR) increased the percentage of cells with

CD16 high and CD49 intermediate expression (mature neutrophils) in lung

compared to sensitized controls (SHCC and SSDR) (Figure 2.11B; main effects

of stress and challenge, F(3,44)=14.24, p<0.0001). Stress (SSDR), Af challenge

(SCHCC), and Af challenge and stress (SCSDR) increased the percentage of cells with CD49d low to negative and CD16 intermediate expression (immature neutrophil) in lung compared to SHCC (Figure 2.11C; main effects of stress and challenge, F(3,44)=64.55, p<0.0001 ). Af challenge (SCHCC and SCSDR) decreased the percentage of cells with both CD16 and CD49d intermediate expression (activated neutrophils) in the lung compared to sensitized controls

(SHCC and SSDR) (Figure 2.11C; main effect of challenge, F(3,44)=20.80, p<0.0001). Stress and Af challenge decreased the percentage of cells with both

CD16 low and CD49d low expression (eosinophils) (Figure 2.11D, stress X challenge interaction F(3,44)=34.92, p<0.0001). Apoptotic neutrophils (CD16 and

CD49d negative) were not changed by stress or challenge (data not shown).

Immature neutrophils can be prematurely released from bone marrow in response to stress or infection, and these cells tend to have increased alkaline phosphatase (ALP) within their granules making them toxic during degranulation.

In humans, ALP is often measured as an indirect determination of neutrophilia or

a left shift. Stress, Af sensitization and challenge increased alkaline phosphatase

(ALP) in lung tissue (Figure 2.12; stress X challenge interaction; F(3,36)=17.91, p<0.0001).

2.3.6 Histology

Lung samples from SHCC, SSDR, SCHCC, and SCSDR mice were obtained,

stained with hemotoxylin and eosin, and examined by light microscopy. These

representative bronchia showed stress enhanced airway inflammation in the

absence of challenge and, most robustly, in the presence of challenge (Figure

2.13). In Figure 2.13B, lung sections are visualized at 40X to show both the

bronchi and the inflammatory cell infiltrate. The control mice (SHCC) appear to

have bronchi of normal appearance and a normal level of inflammatory cell

infiltration (laboratory mice are known to have baseline inflammation due to the

inhalation of particulate and fumes, e.g., urea that is present in cages). Stress

(SSDR) caused bronchi constriction with thickening of the walls and an increase

in perivascular and peribronchial inflammatory cell infiltrate. Challenge (SCHCC)

caused thickening of the bronchial walls and an increase of perivascular and

peribronchial inflammatory cell infiltrate compared to SSDR. Stress and

challenge (SCSDR) caused constriction of bronchi and thickening of the

bronchial walls and an increase of perivascular and peribronchial inflammatory

cell infiltrate compared to SHCC. These differences can be further visualized at

100X (Figure 2.13B).

2.3.7 Neutrophils in the blood

In humans, neutrophilia is diagnosed by increases in immature neutrophils

in the blood. As a confirmation of neutrophilia in stressed and Af challenged

mice, netrophillic populations were also examined in the blood. Stress, Af challenge, or stress and Af challenge increased total CD16+ cell populations in

the blood compared to SHCC (stress X challenge interaction, F(3,44)=20.75,

p<0.0001). Based on the dual expression of CD49d and CD16, three populations

of cells are evident in the blood. Circulating neutrophils do not usually go through

apoptosis or maturation outside of tissue. Immature and activated neutrophils

and eosinophils were present. Cells with CD49d low to negative and CD16

intermediate expression (immature neutrophils) were increased by stress and Af

challenge compared to SHCC (Figure 2.16B; stress X challenge interaction,

F(3,44)=33.30, p<0.0001). Cells with both CD16 and CD49d intermediate

expression (activated neutrophills) were increased by challenge compared to

sensitized controls (Figure 2.16C; main effect of challenge, F(3,44)=3.140,

p=0.0347). Stress and Af challenge (SCSDR) decreased the percent of CD49d

low to negative and CD16 low to negative cells (eosinophils) in the blood (Figure

2.16C; stress X challenge interaction, F(3,44)=19.35, p<0.0001). 86

2.4 Discussion

Following allergen challenge, neutrophils are among the first inflammatory

cells to accumulate within the airways of patients susceptible to allergic asthma

(Taube et al., 2003). In particular, severe asthmatics exhibit a neutrophil-

dominant phenotype, and this patient population tends to be non-responsive to

current treatments that often involve corticosteroids and βAR agonists (Robinson et al., 2003; Jatakanon et al., 1999). Patients with neutrophil-dominated inflammation tend to display an increased severity of disease, and both mouse and human data suggest a relationship with GC resistance (Bogaert et al., 2011;

Corrigan and Loke, 2007). There is a direct association between severe asthma and higher perceived stress, but the mechanisms by which this occurs is not clear (reviewed in Yonas et al., 2012). Previous studies combined with the data in this chapter suggest that stress induces the release of an immature myeloid cell population into circulation from the bone marrow that traffics to various organs (Engler et al., 2004; Powell et al., 2013). The data herein suggest that this population of cells is likely immature neutrophils, and these cells contribute to the enhanced inflammation and delayed resolution seen in stressed and Af- challenged mice.

2.4.1 SDR and origin of cell mobilization

SDR is known to induce the mobilization of a large population of

leukocytes that are distributed to tissue like the spleen and lung. Engler et al.,

(2004) had hypothesized and showed data in support of the concept that these

cells were recruited from the bone marrow. The data from that study showed a

strong association of SDR cycle-dependent decreases in cell populations in the

bone marrow that corresponded to increases in these cell populations in

circulation and tissues. However, the origin of these cells was not definitively

determined. Therefore, using a GFP+ bone marrow chimera paradigm, we

attempted to confirm that the splenic and lung populations of these cells were bone marrow-derived myeloid cells

This issue of the origin of the SDR-induced increase in immune cells was

addressed by histological and flow cytometric analyses of GFP+ bone marrow- chimeric mice that underwent SDR. Powell and Wohleb (Wohleb et al., 2013) developed a murine GFP+ bone marrow chimera protocol to definitively determine

if bone marrow-derived monocytes trafficked to the CNS (Figure 2.1; Wohleb et

al., 2013). To make these GFP+ bone marrow-chimeric mice, bone marrow of

C57BL/6 mice was partially ablated with busulfan, which is a cell cycle non-

specific alkylating antineoplastic agent often used in the context of

chemotherapy. Two days later, bone marrow cells from transgenic mice that

ubiquitously express GFP on all cells were adoptively transferred into recipient

mice. Four weeks after the adoptive transfer of GFP+ bone marrow, these mice

were subjected to 6 cycles of SDR treatment. In a subset of these GFP+ bone

marrow-chimeric mice (from Wohleb et al., 2013), the egress and trafficking of

myeloid cells to the spleen and lung were examined in response to SDR. Flow

cytometric analyses indicated that ~65% of the bone marrow was reconstituted

with GFP+ cells in both SDR and HCC groups suggesting equal engraftment

(Figure 2.2A). After the 6th cycle of SDR, bone marrow, spleen and lung tissues

were collected and GFP+/CD11b+ cells were analyzed. Histological analyses of

spleen and lung tissues showed high numbers of GFP+ cells in SDR compared to

HCC mice (Figure 2.2B). SDR caused a marked increase in the number

GFP+/CD11b+ cells that trafficked to the spleen and lung by flow cytometric

analysis, thus confirming the histological data (Figure 2.2C). Overall, these data

gave clear evidence that the increase of cells found in organs such as the lung

and spleen were likely bone marrow-derived.

The GFP+ bone marrow chimera protocol (Figure 2.1) was then adapted

for use in a BALB/C mouse, and the Af sensitization, SDR, and challenge

protocol (Figure 2.3) was utilized after the four week engraftment period. The

trafficking of total GFP+ cells and GFP+ cells that also expressed CD11b and

Ly6C were then determined in the circulation and the lung of Af sensitized

(SHCC, SSDR) and Af sensitized and challenged (SCHCC, SCSDR) SDR and

HCC mice (Table 2.1). Note that all the groups in this study were chimeras that

were sensitized with Af prior to SDR. As seen in the C57BL/6 mice (Figure 2.2A), stress did not affect the total GFP+ cells in the sensitized bone marrow, but Af

challenge and stress and Af challenge significantly increased the total GFP+ cells

(Table 2.1A). These results suggest that Af challenge itself had an effect on hematopoesis, and/or the release of GFP+ cells from the bone marrow. In the

blood, Af challenge increased the percentage of total GFP+ cells, while in the lung, stress increased the percentage of total GFP+ cells. In the bone marrow,

blood, and lung, stress alone or Af challenge increased GFP+ cells that were also

CD11b+, Ly6C+, or CD11b+/Ly6C+ (Table 2.1A-C). The only instance where

stress and challenge together increased the percentage of GFP+ cells that were

also CD11b+/Ly6C+ cells was in the blood (Table 2.1B). Overall, engraftment was

stable, but the response to challenge in a sensitized mouse stimulated

hematopoiesis as should be expected because of the pulmonary inflammatory

response caused by the Af challenge. Clearly, SDR had an impact on GFP+ cell

trafficking to the lungs, but Af challenge in the context of stress did not show

synergistic enhancement as were seen in previous studies and preliminary data.

The next logical step was to perform the remainder of the experiments in non-

chimeric mice using only the sensitization, SDR, and challenge protocol (Figure

2.3).

The distribution of monocytes, granulocytes, lymphocytes, and

erythrocytes was examined in the bone marrow of Af-sensitized mice that were

exposed subsequently to SDR and Af challenge. Flow cytometric analysis using a pair of monoclonal antibodies was performed to identify the major subsets of cells in the bone marrow (FITC-conjugated anti-Ly6C and PE-conjugated anti-

CD31). Differential expression of Ly6C and CD31 enabled characterization of cell populations by the following criteria: lymphoid cells Ly6C-/CD31+, erythrocytes

Ly6C-/CD31-, monocytes CD31+/Ly6Chi, and granulocytes Ly6Cint/CD31lo. Mixed progenitor cells were not considered in the analyses.

In sensitized HCC and SDR mice (SHCC and SSDR), stress decreased the percentage of erythrocytes and lymphocytes and while it increased the percentage of granulocytes (Figure 2.4A). The percentage of monocytes in the bone marrow of sensitized mice was not altered by stress alone (Figure 2.4A).

These results are similar to other studies performed in C57BL/6 mice except that

C57BL/6 had an increased percentage of monocytes as well (Engler et al.,

2004). In sensitized and challenged HCC and SDR mice (SCHCC and SCSDR), stress decreased the percentage of erythrocytes and lymphocytes and increased the percentage of granulocytes and monocytes (Figure 2.4B). These results confirm previous studies in SDR, which showed a social stress-induced bias towards myelopoiesis in the bone marrow (Engler et al., 2004; Powell et al.,

2013). Altogether, SDR alone or SDR and Af challenge shifted hematopoesis toward granulopoiesis and monopoiesis in the bone marrow, and this shift was

reflected in the myeloid cells found in the peripheral organs such as the lung and

spleen.

2.4.2 Cellular phenotypes in socially-stressed and/or challenged mice

Curry et al., (2010) found that social stress alone could increase the infiltration of activated myeloid cells into the lungs of mice. Trafficking of these myeloid cells was observed to occur despite stress-induced elevation of plasma corticosterone levels. The presence of infiltrating myeloid cells correlated with increased inflammation and the expression proinflammatory cytokines (IL-1β,

MCP-1 and MIP-2 protein and RNA). Histological assessment and increased myeloperoxidase activity confirmed the inflammatory environment in response to social stress. Furthermore, trafficking of the myeloid cells was facilitated by enhanced expression of adhesion molecules P-selectin and intracellular adhesion molecule-1 (ICAM-1), which aids myeloid cells to leave circulation and enter tissue. In Curry et al., (2010) the key cells entering the lung were identified to be neutrophils and monocytes. To extend these findings to this allergic airway inflammation model, we did an extensive characterization of the phenotypes of the cells involved in the stress and allergen challenge response and observed few changes in chemokine receptors on myeloid cells or T, B, or dendritic cells, but stress and challenge did tissue-specifically increase granulocytes and monocytes.

Chemokine receptors on myeloid cells in the bone marrow, blood, and

lung are important components of cell trafficking in allergic airway inflammation

(Rothenberg et al., 1999). CCR2 is a chemokine receptor that binds MCP-1,

MCP-3, and MCP-4, and this chemokine receptor is highly expressed on

inflammatory monocytes and neutrophils. CCR2 has a critical role in neutrophil

infiltration into the lung (Maus et al., 2003). CXCR4, with its sole ligand SDF-1, is

involved in neutrophil release and retention in the bone marrow and other tissues

(Suratt et al., 2004). CD31 (PECAM-1) binds to CD38 and is critical for

transendothelial migration of neutrophils into tissue (Chosay et al., 1998). We

focused on these receptors because the myeloid cell trafficking to the lung in

response to SDR and Af challenge appeared predominantly granulocytic. Using

flow cytometric analysis a panel of monoclonal antibodies was developed to

examine receptor expression: FITC-conjugated anti-CD11b and APC-conjugated

+ anti-CCR2, anti-CXCR4 or anti-CD31. The percent total of CD11b cells was

increased by SDR or Af challenge compared to the SHCC group and was

increased by SDR and Af challenge over all other groups in the bone marrow

(Table 2.2A). Additionally in the bone marrow, SDR or Af challenge increased the

+ + + percentage of CD11b+ cells that were CCR2 , CXCR4 , or CD31 (Table 2.2A). In

the blood, the total percentage of CD11b+ cells were significantly decreased in

+ + the SCSDR group, while the percentage of CD11b /CCR2 cells was decreased

by Af challenge as were the CD11b+/CD31+ cells (Table 2.2B). In the lung, SDR

+ + or Af challenge increased the percent total of CD11b or CD11b /CXCR4 cells, Af 93

challenge also increased the percentage of CD11b+/CD31+, while SDR alone

+ + increased CD11b /CCR2 cells (Table 2.2C). These data suggest that social

stress and Af challenge enhanced the expression of chemokine receptors on

these myeloid cells that would likely increase their capacity to home to tissue sites expressing a chemokine gradient. Additionally, Curry’s previous study showed increased myeloid cell infiltration into the lung that was attributed to increased levels of the chemokines KC, MIP-2, and MCP-1 (Curry et al., 2010).

To further characterize other myeloid cell types mobilized by SDR or

SDRs and Af challenge in this model, we quantified T, B, and dendritic cells in the spleen and lung (Table 2.3). In the spleen, the percentage of B cells was decreased in the SCHCC group, while the percentage of conventional dendritic cells (B220-/CD11b+/CD11c+) was decreased by challenge (SCHCC and

SCSDR; Table 2.3A). In the lung, there were no statistically significant

differences in other cell types (Table 2.3B). In all, it did not appear that other

myeloid cells examined were substantially increased or decreased by Af

challenge and SDR (SCSDR) in these experiments.

Granulocytes and monocytes were further examined in the bone marrow,

blood, spleen, and lung of Af sensitized, and Af sensitized and challenged SDR and HCC animals using a panel of monoclonal antibodies: FITC-conjugated anti-

Ly6C and PerCP-conjugated anti-CD11b. It is common to use markers such as

CD11b and Ly6C to immunophenotype cells by flow cytometry. CD11b is

expressed on the surface of many leukocytes including monocytes, neutrophils,

natural killer cells, granulocytes, and macrophages, and Ly6C is differentially

expressed on neutrophils, dendritic cells, and subpopulations of lymphocytes and

monocytes (Fleming et al., 1993). Functionally, CD11b and Ly6C regulate

leukocyte adhesion and migration to mediate the inflammatory response.

CD11b+/Ly6Chi cells are characterized as monocytic while CD11b+/Ly6Cint cells

are characterized as granulocytic. In the bone marrow, monocytes, but not

granulocytes, were increased by SDR and Af challenge (SCSDR; Figure 2.6A and 2.7A). In the blood, monocytes and granulocytes were increased by SDR or

Af challenge, and monocytes were further increased by SDR and Af challenge

(Figure 2.6B and 2.7B). In the spleen, monocytes and granulocytes were increased by SDR or Af challenge with a further increase of granulocytes in

SCSCR spleens compared to SSDR spleens (Figure 2.6C and 2.7C). In the lung, monocytes were increased by SDR while granulocytes were increased by SDR or Af challenge with a further increase by SDR and Af challenge (SCSDR) compared to all other groups (Figure 2.6D and 2.7D). Taken together, SDR and

Af challenge in this model had the largest effect on blood monocytes and lung granulocytes. These data confirm previous findings that SDR increased neutrophils (Ly6G+ or Gr-1+ cells) in whole lung homogenates (Curry et al., 2010;

Engler et al., 2004)

2.4.3 Neutrophils in lung and blood

Considering the data (Figure 2.7) and previous studies, it was determined that the increase in granulocytes in the lung due to SDR and Af challenge should

be further investigated and that immunophenotyping of granulocyte subsets was

warranted. In reviewing the literature, it was clear that Af-induced allergic airway

inflammation in BALB/C animals tended to be highly neutrophilic in the early

stages post challenge (Shevchenko et al., 2013; Bonnett et al., 2006).

Neutrophils are difficult to distinguish from eosinophils, but immunohistological

assessment using antibodies to specific cell surface markers makes it possible to

discriminate between the two cell types. In Curry et al., (2010), Ly6G positivity in

lung cells was used to confirm that neutrophils were increased by SDR. In order

to further phenotype neutrophil subsets, other markers were examined. Previous

studies in the literature have demonstrated that CD16 expression was indicative

of a largely functional neutrophilic population (Moulding et al., 1999). Flow

cytometric analysis using FITC-conjugated anti-CD16 in the lung showed that the

percentage of total neutrophils was increased by stress (SSDR) and by Af

challenge (SCHCC), and that this population was further increased by stress and

Af challenge (SCSDR) compared to all other groups (Figure 2.9).

After further review of the literature, other studies characterized the

various neutrophilic and eosinophilic subpopulations using the differential

expression of CD49d (VLA-4) and CD16 (Figure 2.10A). By utilizing the

monoclonal antibodies FITC-conjugated anti-CD16 and PE-conjugated anti-

CD49d, we examined the expression of these receptors in the blood and lung.

The differential expression of these receptors in the lung allowed us to

distinguish 5 distinct populations of cells (Figure 2.10B,C). These populations of

cells were illustrated in Figure 2.10D. No differences were found in apoptotic

neutrophils (CD16-/CD49d-) among any of the groups (data not shown). Af

challenge (SCHCC and SCSDR) increased the population of functionally mature

neutrophils (CD16hi/CD49int) in the lung (Figure 2.11B). Activated neutrophils

(CD16int/CD49dint) were decreased by Af challenge (SCHCC), but SDR and Af

challenge (SCSDR) significantly increased this population compared to the

SCHCC group (Figure 2.11D). These data for activated neutrophils were not

surprising, as it had been determined previously that neutrophils that home to the

lung tissue would often have an activated phenotype regardless of inflammatory or homeostatic conditions (Fortunati et al., 2009).

Eosinophils (CD16-/CD49dlo) were decreased by SDR and/or Af challenge

(Figure 2.11E). Immature neutrophils (CD16int/CD49dlo) were increased by stress

alone (SSDR), Af challenge alone (SCHCC), and SDR plus Af challenge in a

step-wise manner (Figure 2.11C). In support of an increased immature neutrophil

accumulation in SCSDR lungs, alkaline phosphatase activity was increased over

all other groups (Figure 2.12). Interestingly, Engler et al., (2004) referred to the

neutrophils induced by SDR as a largely immature population based on low

expression of GR-1. The present results confirm that observation and identity of

a subset of immature cells.

Quantitative PCR in the lung showed alterations in several genes due to

SDR and SDR and Af challenge. We assessed whether the SDR-induced increase in immature neutrophils in the lung tissue of Af-challenged mice was accompanied by increased expression of cytokines and growth factors (Figure

2.8). According to qPCR results, despite increased levels of plasma corticosterone (Figure 2.5), stressed and Af challenged mice had increases in both cytokines and growth factors, including IL-1β, TNF-α, IL-10, and GM-CSF compared to all other groups (Figure 2.8). Interestingly, IL-4 was decreased by stress and Af challenge (SCSDR), pointing to a shift away from Th2 responses to a more inflammatory microenvironment in the lung tissue. This observation is consistent with the increase in Th1 cytokines IL-1β and TNF-α. GM-CSF facilitates Th2 immune-inflammatory airway responses and is involved in the accumulation of neutrophils in the lung caused by IL-17 and TNF-α (Laan et al.,

2003). GM-CSF is also involved in the survival of neutrophils, delay of apoptosis, and the priming of neutrophil responsiveness or maturation (Moulding et al.,1999;

Kobayashi et al., 2005). An increase in IL-10 is commonly found in the lung during allergic airway inflammation and has been found to work to reduce the IL-

4 response that is consistent with our data (Justice et al., 2001). In all, the PCR

data confirm an exacerbated response to Af challenge and SDR in the SCSDR

lung.

In the blood, SDR or Af challenge increased CD16+ neutrophils (Figure

2.11). When the differential expression of CD16 and CD49d was examined, only

three distinct populations of cells could be visualized: immature neutrophils,

activated neutrophils, and eosinophils (Figure 2.16A). Apoptotic neutrophils and

mature neutrophils were not present as they were in the lung, and this is to be

expected. Upon release from the bone marrow, a neutrophil is considered

activated (i.e., ability to transmigrate into tissue), but it is not until a neutrophil

enters the tissue that it will fully mature to be functional in host immune defense.

Furthermore, apoptosis of neutrophils usually occurs in tissue rather than in

circulation. In the blood, Af challenge increased activated neutrophils (Figure

2.16C), and stress or Af challenge decreased eosinophils (Figure 2.16D). Stress

increased immature neutrophils over SHCC and SCHCC groups, while stress

and Af challenge increased immature neutrophils over all other groups (Figure

2.16B). These results support the lung neutrophil phenotype with immature neutrophils being greatly increased by SCSDR, and eosinophils decreased by

SCSDR. The only discrepancy was the increase in activated neutrophils by challenge in the blood and the decrease in activated neutrophils by challenge in the lung (Figure 2.16C and 2.15D). This may be due to the increased likelihood of activated neutrophils being in circulation and preparing to migrate into tissue.

Once the activated neutrophils enter the tissue, they may begin to increase their

CD16 and move toward a mature phenotype.

2.4.4 Neutrophil heterogeneity

Compared to lymphocytes and monocytes whose subset populations have

been thoroughly characterized and studied, neutrophils have been considered a

uniform population. However, recently there has been a strong movement in the literature to understand the functional consequences of the heterogeneity of neutrophils in circulation and tissue. No longer are neutrophils considered short- lived and terminally differentiated cells that arrive at tissue to perform their duties and undergo apoptosis, instead, neutrophils may be longer lived than previously thought and may be able to undergo recirculation even after tissue infiltration

(reviewed in Beyrau et al., 2012). Several studies have focused on targeting the release of immature neutrophils in various inflammatory diseases such as

rheumatoid arthritis, sepsis, or local infection (Okawa-Takatsuji et al., 2007; Drifte et al., 2013; Pillay et al., 2012). Particularly in neutrophil-dominant asthma phenotypes, this heterogeneity of cells may yield clues as to how stress may exacerbate asthma in treatment resistant patients.

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2.4.5 Histology

Lung samples from SHCC, SSDR, SCHCC, and SCSDR mice were obtained after 6 cycles of SDR and Af challenge, stained with hemotoxylin and eosin, and examined by light microscopy. Histology showed that control mice

(SHCC) appeared to have bronchi of normal appearance and a normal level of inflammatory cell infiltration. Stress (SSDR) caused the appearance of bronchi constriction with a thickening of the walls and an increase in perivascular and peribronchial inflammatory cell infiltrate. Challenge with Af (SCHCC) caused the appearance of a thickening of the bronchial walls and an increase of perivascular and peribronchial inflammatory cell infiltrate compared to SSDR. Stress and Af challenge (SCSDR) caused constriction of bronchi and thickening of the bronchial walls and an increase of perivascular and peribronchial inflammatory cell infiltrate compared to SHCC. Overall, visualization of lung sections confirmed previous studies and provided insight into SDR-enhancement of allergic airway inflammation.

2.4.6 Comparison of results to previous Af SDR study

In a previous study from the Sheridan lab following a protocol similar to

Figure 2.3, Bailey et al. (2009b) found that airway inflammation in CD-1 mice resolved after 48h in sensitized and Af challenged control mice, while sensitized

101

and Af challenged stressed mice had delayed resolution. In this model, Giemsa

stained cells obtained from brochoalveolar lavage fluid (BAL) were quantified,

and the key effector cells mobilized to the lung by SDR and Af challenge were

determined to be eosinophils and lymphocytes. No differences were found in

numbers of macrophages or neutrophils. SDR and Af challenged animals had

delayed clearance of these cells compared to control and Af challenged animals.

Additionally, stress and Af challenge increased hyper-responsiveness of the

airways to methacholine as a measure of impaired lung function. Challenge

increased IL-4 production in lungs while SDR and Af challenge increased IL-5,

GM-CSF, TNF-α, and IL-6 production in lungs. In this study, SDR and Af challenge increased serum cort, but the SDR alone group had nearly double the serum cort when compared to the SDR and Af challenged group.

The present study had results that differed from Bailey et al., (2009b), and this was likely due to the choice of mouse strain (CD-1 mice which are random bred) and the focus on lymphocytes and eosinophils. The data from this chapter suggest that neutrophils play a key role in the BALB/C response to Af rather than eosinophils or lymphocytes. Although all mouse strains are susceptible to Af challenge, strain differences regarding host susceptibility and immune system response do exist (Latge 1999). Furthermore, instead of bronchoalveolar lavage fluid and histology, our studies utilized whole lung homogenates, which includes cells that are within the parenchyma of the lung, and flow cytometry. Future

102

studies in the BALB/C should examine cells within the bronchoalveolar lavage fluid to determine if eosinophils are also present. PCR results between the two studies had similarities, with the exception of IL-4 being decreased in SCSDR animals instead of increased as in the Bailey et al (2009b) study. A difference existed in the circulating cort levels. In the present studies, we found that cort was only increased in the SCSDR group at 48h post-challenge (Figure 2.5). This again is likely to be due to a strain difference.

2.4.7 Conclusions:

In conclusion, the results within this chapter confirm the hypothesis that stress induces the egress of immature cells from the bone marrow and identifies that a majority of these cells are neutrophilic. Though immature, these neutrophils can egress into lung tissue, and, during allergic airway inflammation, may contribute to the enhanced inflammation and delayed resolution found by

Bailey et al., (2009b). It is important to keep in mind that the neutrophilia seen in clinical cases of allergic asthma is not just a symptom or a marker, but a factor in pathogenesis as patient tend to have more severe disease symptoms.

Furthermore, understanding that these states of neutrophilia can be exacerbated by social stress is important to understanding the development of refractory or severe asthma. For cases of neutrophilic or severe asthma that are refractory to the common course of treatment, these results suggest that further 103

understanding the maturation state of the cell type involved may be beneficial for adjusting asthma therapy. Additionally, cell-specific targeting that takes into account the cellular maturation state may have important therapeutic implications for pharmaceutical development. Finally, the results in this chapter further confirm that the SDR model is an appropriate model to study stress-exacerbation of allergic airway inflammation and that it appears to be an excellent model in which to study severe or neutrophilic asthma.

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1. GFP cells in tissue after the 30 days are considered bone marrow-derived and can be “tracked”. Busulfan (i.p.): ablate bone marrow

48h 3.

Social Disruption Stress (SDR) 2. 30 days 18h

Aggressor BM cells from GFP-tagged + 2 hours donor (i.v.): Reconstitute BM For 6 nights

Figure 2.1: GFP+ bone marrow chimera and SDR protocol. (1) Recipient mice were administered busulfan (25 mg/kg i.p), a chemotherapeutic agent, to allow room for engraftment in recipient bone marrow for donor cells. (2) One million GFP-tagged cells from donor bone marrow were injected (i.v.) into recipient mice. (3) Engraftment was allowed to occur for 30 days, and then the animals were subjected to SDR.

105

Figure 2.2: GFP+ bone marrow-chimeric mice show myeloid progenitor cell egress and trafficking to spleen and lung. (A) HCC and SDR mice represented in this study had consistent levels of GFP+ cells in the bone marrow. (B) Histology of spleens and lungs of GFP+ bone marrow-chimeric mice show that the SDR group had larger spleens with GFP+ cells densely aggregating in the marginal zones of the germinal centers and an increase in GFP+ cells in SDR lungs compared to HCC. (C) Flow cytometric analyses indicated a significant increase in the percentage of GFP+/CD11b+ cells in the spleen and lung confirming the histological findings. Data are expressed as mean ± SEM (n = 6/group). Means with different letters (a or b) are significantly different (p < 0.05) from each other.

106

A i.p. Af i.n. Af Sensitization # 1 & # 2 Challenge Sac

Days: 056 7 8 9 10 11 12 13 14 15

SDR

Day 0,5 Day 6-11 Day 13

Social Disruption Stress (SDR)

Aggressor Af extract i.p. + 2 hours Af extract i.n. Sensitization For 6 nights Challenge

B Groups Treatment SHCC Af Sensitization, HCC, and NO challenge SSDR Af Sensitization, SDR, and NO challenge SCHCC Af Sensitization, HCC, and Challenge SCSDR Af Sensitization, SDR, and Challenge

Figure 2.3: Sensitization, SDR, and challenge protocol. (A) Mice were sensitized on day 0 and 5 with 20μg of Af extract and 20mg of alum to enhance allergenicity. Mice assigned to the stress protocol were exposed to SDR on days 6-12. On day 13, mice assigned to the challenge condition were intranasally challenged with 10ug of Af allergen in PBS. Forty-eight hours later mice were sacrificed by ketamine/xylazine overdose. (B) Summary of group treatments: SHCC, SSDR, SCHCC, and SCSDR.

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Bone Marrow GFP+ Cells SHCC SSDR SCHCC SCSDR % Total GFP+ 13.2 ± 0.5a 13.8 ± 0.5a 31.9 ± 0.4b 41.0 ± 1.4c % GFP+/CD11b+ 88.1 ± 0.4a 90.5 ± 0.4b 98.5 ± 0.1c 98.3 ± 0.8c % GFP+/Ly6C+ 79.5 ± 0.5a 84.2 ± 0.3b 83.9 ± 0.6b,c 85.1 ± 0.9bc % GFP+/CD11b+/Ly6C+ 84.2 ± 0.4a 87.0 ± 0.4b 90.4 ± 0.3c 91.2 ± 1.0c B Blood GFP+ Cells SHCC SSDR SCHCC SCSDR % Total GFP+ 11.7 ± 0.7a 14.8 ± 1.0a 26.6 ± 2.1b 34.5 ± 2.5c % GFP+/CD11b+ 88.2 ± 2.4a 94.6 ± 0.8b 98.1 ± 0.7b 99.4 ± 0.2b % GFP+/Ly6C+ 81.9 ± 2.4a 89.9 ± 0.9b 90.2 ± 0.9b 94.5 ± 0.6b % GFP+/CD11b+/Ly6C+ 72.4 ± 1.8a 79.6 ± 0.7b 79.9 ± 0.9b,c 87.4 ± 0.7d C Lung GFP+ Cells SHCC SSDR SCHCC SCSDR % Total GFP+ Cells 17.5 ± 0.6a 32.4 ± 4.4b 33.9 ± 1.1b 37.9 ± 1.0b % GFP+/CD11b+ 87.9 ± 1.0a 92.0 ± 0.9b 96.0 ± 0.7c 96.6 ± 0.2c % GFP+/Ly6C+ 86.8 ± 0.5a 89.7 ± 0.8b 87.8 ± 0.5a,b 89.4 ± 0.3b a b a,b b % GFP+/CD11b+/Ly6C+ 85.4 ± 1.2 89.9 ± 0.9 87.2 ± 0.8 89.4 ± 0.4

Table 2.1: Af challenge contributed to significant increases in GFP+ cells in bone marrow, blood, and lung. Cells were first gated on GFP and then of those cells CD11b+, Ly6C+, or CD11b+/Ly6C+ cells were then selected. Stress alone did not significantly increase percent total of GFP+ cells in the bone marrow or blood, but did increase percent total GFP+ cells in the bone marrow and blood of SCHCC and SCSDR mice compared to SHCC (A,B). Stress alone or Af challenge increased the percent total GFP+ cells in the lung (C). In the bone marrow, blood, and lung, stress alone or Af challenge contributed to increases in the percentage of GFP+ cells that were also CD11b+, Ly6C+, and CD11b+/Ly6C+ (A,B,C). In the blood, increases in the percentage of GFP+ cells that were also CD11b+/Ly6C+ were increased by stress and Af challenge compared to all other groups (B). Data are expressed as mean ± SEM (n = 9/group). Means with different letters (a,b,c) are significantly different (p < 0.05) from each other.

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A Cell Populations in Sensitized BM 80 SHCC SSDR p=0.0202

60 *

p=0.0302

p=0.0465 20 * % Cells in Marrow in Bone Cells % * p=0.8126

0 Erythrocytes Granulocytes Lymphocytes Monocytes

B Cell Populations in Sensitized and Challenged BM 80 SCHCC SCSDR p=0.0012

60 *

p<0.0001

20 p=0.0035 p=0.0005 % Cells in BoneMarrow * * * 0 Erythrocytes Granulocytes Lymphocytes Monocytes

Figure 2.4: Stress shifts granulopoiesis and monopoiesis in sensitized and sensitized challenged bone marrow. Cell populations were determined by differential expression of Ly6C and CD31: lymphoid cells Ly6C-/CD31+, erythroid cells Ly6C-/CD31-, monocytes CD31+/Ly6Chi, and granulocytes Ly6Cint/CD31lo (Figure 2.4). Mixed progenitors were the only cell population not included in the analyses.(A) In cell populations in the bone marrow of sensitized mice, stress increased granulocytes while erythrocytes and lymphocytes were decreased. (B) In cell populations in the bone marrow of sensitized challenged mice granulocytes and monocytes were increased by stress and challenge while erythrocytes and lymphocytes are decreased. Data are expressed as mean ± SEM (n = 7-9/group;*p < 0.05). 109

A Chemokine Receptors on CD11b+ Cells in BM HCC SDR SCHCC SCSDR % Total CD11b+ 63.9 ± 1.7a 77.5 ± 2.3b 73.2 ± 1.5b 86.7 ± 1.6c % CD11b+/CCR2+ 14.8 ± 0.9a 28.8 ± 2.1b 24 ± 2.3b 29.1 ± 2.2b % CD11b+/CXCR4+ 5.7 ± 0.3a 20 ± 3.5b 26.3 ± 3.7b 27.2 ±2.2b % CD11b+/CD31+ 28.5 ± 1.9a 51.6 ± 5.3b 46.7 ± 3.1b 49.4 ± 4.2b

B Chemokine Receptors on CD11b+ Cells in Blood HCC SDR SCHCC SCSDR % Total CD11b+ 59.5 ± 4.6a 58.5 ± 4.5a 64.9 ± 3a 32.5 ± 12.8b % CD11b+/CCR2+ 31.5 ± 3.6a 22.5 ± 4a 14.8 ± 2.5b 20.3 ± 5.7a % CD11b+/CXCR4+ 28.7 ± 7.7 28.5 ± 2.6 21.2 ± 6.1 23.9 ± 4.1 % CD11b+/CD31+ 64.6 ± 3.5a 75.0 ± 4.1a 49.3 ± 13b 38.0 ± 11.2b C Chemokine Receptors on CD11b+ Cells in Lung SHCC SSDR SCHCC SCSDR % Total CD11b+ 36.5 ± 0.6a 49.0 ± 3.2b 74.4 ± 1.0c 75.1 ± 1.0c % CD11b+/CCR2+ 22.5 ± 0.9a 34.1 ± 5.5b 22.4 ± 1.7a 27.2 ± 1.4a,b % CD11b+/CXCR4+ 16.1 ± 0.5a 27.2 ± 2.3b 23.1 ± 2.5b 23.9 ± 1.1b a a b b % CD11b+/CD31+ 27.9 ± 1.0 36.9 ± 7.1 65.0 ± 2.0 65.1 ± 1.3 Table 2.2: Chemokine receptor expression on CD11b+ cells in bone marrow (A), blood (B), and lung (C). Chemokine receptors were immunostained with APC while CD11b was stained with FITC. First, CD11b+ cells were gated, and, of those cells, positivity for each chemokine receptor was determined. Stress increased the percent total CD11b+ cells in the bone marrow and lung (A,C). Af challenge alone increased percent total CD11b+ cells in the lung and Af challenge and stress increased percent total CD11b+ cells in bone marrow and decreased these cells in the blood (A,B). In the bone marrow, stress or Af + + + challenge significantly increased CD11b cells that were also CCR2 , CXCR4 , + + + and CD31 (A). In the blood, the percent of cells that were CD11b and CCR2 were decreased in SCHCC, and the percent of cells that were CD11b+ and CD31+ were decreased in Af challenged mice (B). Stress increased the percent + + of cells that were both CD11b and CCR2 in Af sensitized and Af sensitized and challenged lung (C). Stress or Af challenge increased percent of cells that were + + both CD11b and CXCR4 in the lung compared to SHCC (C). Af challenge increased the percent of cells that were both CD11b+ and CD31+ in the lung (C). Data are expressed as mean ± SEM (n= 9-12). Means with different letters (a,b,c) are significantly different (p < 0.05) from each other. 110

A Spleen T Cells SHCC SSDR SCHCC SCSDR % CD3+ 36.2 ± 5.2 28.6 ± 3.5 33.5 ± 4.7 23.6 ± 2.7 % CD3+/CD4+ 71.0 ± 0.3 74.3 ± 1.8 73.4 ± 2.1 72.8 ± 1.9 % CD3+/CD8+ 25.2 ± 1.5 29.8 ± 2.3 31.3 ± 3.5 29.5 ± 2.7

% B Cells in Spleen SHCC SSDR SCHCC SCSDR % B220+ Cells* 58.1 ± 4.4a 52.4 ± 2.2a 44.8 ± 2.8b 48.2 ± 2.3a

Dendritic Cells in Spleen SHCC SSDR SCHCC SCSDR % Conventional DCs** 69.6 ± 2.8a 63.2 ± 3.3a 27.1 ± 4.2b 26.3 ± 5.0b % Plasmacytoid DCs 11.5 ± 1.5 10.5 ± 2.1 6.3 ± 1.0 8.2 ± 0.9

* statistically significant difference: F(3,44)=3.521; p<0.0226; **statistically significant difference: F(3,44)=34.69; p<0.0001 B Lung T Cells SHCC SSDR SCHCC SCSDR % CD3+ 31.9 ± 5.3 22.5 ± 1.2 27.2 ± 4.2 18.7 ± 2.6 % CD3+/CD4+ 60.3 ± 7.3 66.3 ± 1.4 68.4 ± 1.4 64.9 ± 1.9 % CD3+/CD8+ 20.3 ± 6.9 24.1 ± 0.8 27.6 ± 6.1 22.0 ± 1.2

B Cells in Lung SHCC SSDR SCHCC SCSDR % B220+ Cells 31.9 ± 5.3 30.7 ± 4.3 31.8 ± 3.3 22.4 ± 3.5

Dendritic Cells in Lung SHCC SSDR SCHCC SCSDR % Conventional DCs 55.3 ± 5.9 55.1 ± 2.7 55.8 ± 4.5 65.6 ± 3.2 % Plasmacytoid DCs 35.5 ± 7.4 36.9 ± 3.7 35.9 ± 7.3 25.5 ± 3.3 Table 2.3: Stress and Af challenge effects on other cell populations in the spleen (A) and lung (B). T cells were first gated on CD3+ and then of those cells CD4+ or CD8+ cells were selected. Conventional and plasmacytoid dendritic cells (DCs) were first gated on B220- (conventional) or B220+ (plasmacytoid) and then of those cells the CD11b+/CD11c+ cells were selected. T cells and plasmacytoid dendritic cells in the spleen were not altered by stress or Af challenge. However, B cells were increased and conventional dendritic cells were decreased in SCHCC spleens. In the lung, T cells, B cells, and conventional plasmacytoid dendritic cells were not altered by stress or Af challenge. Data are expressed as mean ± SEM (n=10-12/group). Means with different letters (a or b) are significantly different (p < 0.05) from each other. 111

2000 b 1600

1200

800

400 a Corticosterone ng/mL Corticosterone a a

0 48h SHCC 48h SSDR 48h SCHCC 48h SCSDR

Figure 2.5: Corticosterone increased in SDR mice 48h after Af Challenge. Corticosterone was measured from plasma collected 48h after intranasal Af challenge. Data are expressed as mean ± SEM (n=10-12/group). Means with different letters (a,b) are significantly different (p < 0.05) from each other.

112

A B c 8 Bone Marrow 60 Blood b

6 b b 40

cells in BM a a cells in Blood hi hi

a hi 4 a

20 2 % CD11b+/Ly6C % %CD11b+/Ly6C

0 0 SHCC SSDR SCHCC SCSDR SHCC SSDR SCHCC SCSDR C D 4 Spleen 8 Lung

b,cb b b

3 6 b a b,cb cells in Lung cells in in Spleen cells a hi hi hi hi 2 4

1 a 2 % CD11b+/Ly6C % % CD11b+/Ly6C %

0 0 SHCC SSDR SCHCC SCSDR SHCC SSDR SCHCC SCSDR

Figure 2.6: Stress and Af challenge effects on the percentage of monocytes (CD11b+/Ly6Chi ) in the blood, spleen, and lung. Stress and Af sensitization and challenge (SCSDR) increased the percentage of monocytes in bone marrow (A). Stress (SSDR) or stress and Af challenge (SCSDR) increased monocytes cells in the blood and the spleen (B,C) Stress increased the percentage of monocytes in both Af sensitized and Af sensitized challenged lung compared to controls (D). Data are expressed as mean ± SEM (n=10-12/group). Means with different letters (a,b,c,d) are significantly different (p < 0.05) from each other.

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A B 80 Bone Marrow 8 Blood

a a b b 60 6 a b a cells in BM in cells cells in cells Blood int

40 int 4 a

20 2 %CD11b+/Ly6C %CD11b+/Ly6C

0 0 SHCC SSDR SCHCC SCSDR HCC SDR SCHCC SCSDR C D 25 Spleen 40 Lung c c 20 b,c 30

b 15 cells in cells SPL cells in cells Lung

int int b int int 20 b 10 a a 10

%CD11b+/Ly6C 5 %CD11b+/Ly6C

0 0 SHCC SSDR SCHCC SCSDR SHCC SSDR SCHCC SCSDR

Figure 2.7: Stress and Af challenge effects on the percentage of granulocytes (CD11b+/Ly6Cint) cells in blood, spleen, and lung. Stress increased granulocytes in (B) blood, (C) spleen, and (D) lung. Af challenge increased granulocytes in (B) blood, (C) spleen, and (D) lung compared to SHCC. Af challenge and stress increased granulocytes in SCSDR spleen and lung compared to SHCC. Data are expressed as mean ± SEM (n=10-12/group). Means with different letters (a,b,c,d) are significantly different (p < 0.05) from each other.

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A 30 c B30

β c

20 20

10 10

Fold Change in IL-1 b b in Change Fold TNF b b a a 0 0 SHCC SSDR SCHCC SCSDR SHCC SSDR SCHCCSCSDR

C 30 D60

b c

20 40

b 10 20 c Fold Change in IL-4 Fold Change in IL-10 b a a a a 0 0 SHCC SSDR SCHCCSCSDR SHCC SSDR SCHCCSCSDR

E 20

c 15

10 b b 5 Fold Change in in Change GM-CSF Fold a 0 SHCC SSDR SCHCC SCSDR Figure 2.8: Stress and Af challenge induces changes in gene expression in the lung. In the lung, stress (SSDR) induces an increase in IL-1β (A), TNF-α (B), and GM-CSF (E) gene expression compared to SHCC. Af challenge (SCHCC) increased IL-4 (C) and IL-10 (D) compared to sensitized controls. Stress and Af challenge (SCSDR) increased IL-1β (A), TNF-α (B), IL-4 (C), IL-10 (D) and GM- CSF (E) compared to all other groups. Data are expressed as mean ± SEM (n = 6-8/group). Means with different letters (a or b) are significantly different (p < 0.05) from each other. 115

29.3 % 47.0 % Sensitized

44.6 % 61.2 %

B 80 ) + c

60 b b

40 a

20 % Total Neutrophils (CD16 Total % 0 SHCC SSDR SCHCC SCSDR

Figure 2.9: Stress and Af challenge increased the CD16+ cell population in lung. After gating on high SSC to select granulocytes, CD16+ cell populations are largely neutrophilic. Stress and Af challenge (SCSDR) increases total CD16+ neutrophils in the lung compared to all other groups. Data are expressed as mean ± SEM (n= 10-12). Means with different letters (a or b) are significantly different (p < 0.05) from each other.

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A CD 49d CD16 Cell Ref intermediate high mature neutrophils Cheung et al., 2010; Tsuda et al., 2004; to low Lukens et al., 2010; Elghetany et al., 2003

intermediate intermediate activated Cheung et al., 2010; Tsuda et al., 2004; neutrophils Lukens et al., 2010

low to intermediate immature Lukens et al., 2010; Elghetany et al., negative (precursor) 2003Lukens et al., 2010 neutrophils

low negative to eosinophils Gopinath & Nutman 1997; Herman et al low 2000; Lukens et al., 2010; Kern et al., 2000 negative negative apoptotic Moulding et al., 1999; Lukens et al., 2010; neutrophils Kern et al., 2000

D myeloblast B CD16 CD49d

n. promyelocyte

Activated or

Mature Immature Marrow

Neutrophils n. myelocyte MaturingActivated

C Neutrophils Bone

Eosinophils n. metamyelocyte

n. band eosinophil neutrophil Blood

Neutrophil Apoptotic Immature Precursor Activated Neutrophils Neutrophils Tissue Mature

Figure 2.10: Neutrophil populations in lung. By first gating on high SSC (to select granulocytes), several neutrophil populations can be determined based on the dual expression of CD16 and CD49d. (A) Differential expression of these two receptors, types of cells, and references. (B) Flow cytometric density map of SCSDR lung cells dual labelled for CD49d and CD16. (C) Using the references from (A), the various populations can be identified. (E) Illustration of neutrophil populations. 117

HCC SDR A

22.0% 23.4% 38.2% 2.3% 21.5 % 2.6% Sensitized 17.1% 27.8% 3.1% 2.8%

11.3% 18.5% Sensitized 12.3 % 19.4 % 10.2% 19.6% Sand 2.2% 38.7% 2.1% 48.2% CChallenged CD49d CD16

Mature Neutrophils Immature (Precursor) 30 60 Neutrophils B C d b int int b lo c 20 40 b /CD49d /CD49d hi int a 10 20 Cells in Lung Cells in in Cells Lung % CD16 %

a a CD16 %

0 0 SHCC SSDR SCHCC SCSDR SHCC SSDR SCHCC SCSDR

Activated Neutrophils Eosinophils 30 60 a D a E int c lo a 20 40 /CD49d /CD49d lo

int b b 10 20 Cells in Lung Cells in Lung c c %CD16 CD16 %

0 0 SHCC SSDR SCHCC SCSDR SHCC SSDR SCHCC SCSDR

Figure 2.11: Distinct populations of granulocytes in lung. (A) Representative flow cytometric plots of cell distribution (SSChi/CD16/CD49d). (B)Af challenge increased the percentage of cells with CD16hi and CD49int expression (mature). (C) Stress, Af challenge, or Af challenge and stress increased the percentage of cells with CD49dlo- and CD16int expression (immature). (D)Af challenge decreased the percentage of CD16int and CD49dint cells (activated). (E) Stress and Af challenge decreased the percentage of CD16lo and CD49dlo cells (eosinophils). Data are expressed as mean ± SEM (n= 10-12). Means with different letters (a or b) are significantly different (p < 0.05) from each other.

118

0.25

0.2 b

0.15

a 0.1 a a

ALP Activity (u/mL/T)0.05

0 SHCC SSDR SCHCC SCSDR

Figure 2.12: Stress and Af challenge increased alkaline phosphatase (ALP) in lung tissue. ALP was increased in lungs of Stress and Af challenged mice (SCSDR). Immature neutrophils can be prematurely released from bone marrow with stress or infection, and these cells tend to have increased alkaline phosphatase within their granules making them toxic during degranulation. In humans, alkaline phosphatase is often measured as an indirect determination of neutrophilia or a left shift. Data are expressed as mean ± SEM (n=9-13/group). Means with different letters (a,b,c,) are significantly different (p < 0.05) from each other.

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Sensitized and A Sensitized Challenged

HCC

SDR

B SHCC SCHCC

SSDR SCSDR

Figure 2.13: Hematoxylin and eosin staining of lung samples. (A) Representative airways at 40X (B) Representative airways at 100X.

120

A HCC SDR

21.1 % 43.7 % Sensitized

32.2 % 52.8 % Sensitized and Challenged SSC CD16 B Total Neutrophils 80

b,d 60 b b

40 c

in Blood in a 20 % Total% Neutrophils

0 SHCC SSDR SCHCC SCSDR

Figure 2.14: Stress and Af challenge increase CD16+ cell population in the blood. After gating granulocytes on high SSC, CD16+ cell populations can be considered largely neutrophilic. Stress and Af challenge (SCSDR) increased the percentage of total CD16+ cells in the lung compared to SHCC and SCHCC. Data are expressed as mean ± SEM (n= 10-12). Means with with different letters (a or b) are significantly different (p < 0.05) from each other. 121

A HCC SDR

1.7 % 2.1% 3.2 % 2.2 % Sensitized

16.4 % 35.6 %

2.7% 2.5% 2.6% 1.5% Sensitized and Challenged

26.0% 48.3% CD49d

CD16

Immature Neutrophils Activated Neutrophils Eosinophils B 60 C 4 D 4 d a

lo b b lo a,b 40 b int a b /CD49d c a /CD49d

int 2 lo 2 /CD49d c int 20 a Cells in Blood Cells in in Cells Blood Cells in Blood in Cells % CD16 % CD16 % CD16

0 0 0 SHCC SSDR SCHCC SCSDR SHCC SSDR SCHCC SCSDR SHCC SSDR SCHCC SCSDR

Figure 2.15: Distinct populations of granulocytes in blood. (A) Representative flow cytometric dot plots of cell distribution (SSChi/CD16/CD49d). (B) Cells with CD49dlo- and CD16int expression (immature neutrophils) are increased by stress and Af challenge in blood compared to SHCC. (B) CD16int /CD49dint cells (activated neutrophills) are increase by Af challenge in the blood compared to sensitized controls. (D) Stress and Af challenge (SCSDR) decreases the percent of CD49dlo- and CD16lo to negative cells (eosinophils) in the blood. Data are expressed as mean ± SEM (n= 10-12). Means with different letters (a or b) are significantly different (p < 0.05) from each other. 122

CHAPTER 3

Neuropeptide Y Y1, IL-1 Receptor Type 1, and β-Adrenergic Receptor Blockade

in the Absence and Presence of Stress Differentially Modulates P. gingivalis-

Induced Inflammation

3.1 Introduction

3.1.1 Periodontal Inflammation Porphyromonas gingivalis (P. gingivalis)

Periodontal diseases are highly prevalent among humans and involve

inflammatory processes that can gradually progress to chronic inflammatory

issues (Pihlstrom et al., 2005). The host response to the formation of bacterial

plaque is an etiological factor that can have profound effects on the severity of the disease ranging from mild gingival inflammation of the soft tissues surrounding the teeth, or gingivitis, to severe tissue degradation affecting the periodontal ligament and alveolar bone leading to tooth loss, or chronic

periodontitis (Pihlstrom et al., 2005). P. gingivalis is a Gram-negative anaerobic

123

bacterium that has been closely associated with the development of chronic periodontitis (Pihlstrom et al., 2005). Accumulation of P. gingivalis plaques in the oral cavity can disrupt host-microbial homeostasis to cause tissue destruction

(Hajishengallis et al., 2011). P. gingivalis possess the ability to release virulence factors that induce tissue damage, but mostly responsible for this damage is the accumulation of proinflammatory cytokines from the immune response to the bacteria (e.g., IL-1β and TNF-α). It has been shown that blocking these cytokines can significantly reduce disease progression (Assuma et al., 1998; Kesavalu et al., 2002; Potempa et al., 2003).

Production of these cytokines is initiated when pattern recognition receptors (PRRs), such as Toll-like receptors (TLRs) 2 and 4, bind to and are activated by pathogen associated molecular patterns (PAMPs) of P. gingivalis

(Burnset et al., 2006). Specifically, lipopolysaccharide (LPS), a component of the cell walls of Gram-negative bacteria, acts as a PAMP that can initiate these actions (Darveau et al., 2004; Potempa et al., 2003; Tabeta et al., 2000; Zhou et al., 2005). For example, TLR 4 associates with MD2 and CD14 for ligation of

LPS. Upon ligation, a signaling cascade of transcription factors such as nuclear factor κB (NF-κB), activator protein 1 (AP1), and interferon regulatory factor (IRF) are activated. Transcription factors such as NF-κB can then translocate into the nucleus to initiate the production of proinflammatory cytokine genes such as

TNF-α, IL-1, and IL-6. Initially, these cytokines produced upon TLR ligation

124

enhance the immune response to eliminate pathogen and may be beneficial to

the host (Zhou et al., 2005). However, when produced in excess for a prolonged

period of time, these cytokines facilitate tissue degradation and bone resorption

characteristic of the deleterious effects of chronic periodontitis (Assuma et al.,

1998; Graves and Cochran, 2003). In particular, stress has been implicated in

the enhanced expression of these TLRs and immune cell function in a βAR and

IL-1R1-mediated manner, and stress is considered to be one mechanism by

which inflammation can be exacerbated during infection. (Bailey et al., 2007;

Engler et al., 2008; Bailey et al., 2009a; Hanke et al., 2012; Wohleb et al., 2011).

3.1.2 Stress and Periodontal Inflammation and the SDR Model

Psychological stress exacerbates many diseases including inflammatory

periodontitis, yet mechanisms that can be targeted for clinical gain are lacking

(Genco et al., 1998). Enhancement of periodontal inflammation by stress can

occur through behavioral changes (e.g., smoking, oral hygiene, dental visits), but

data show that activation of neuroendocrine systems by stress has mechanistic

roles in exacerbating periodontal inflammation (Genco et al., 1998; Peruzzo et

al., 2008). Although evidence exists that smoking enhances susceptibility via

activation of nicotinic acetylcholine, humans with higher levels of stress (e.g.,

financial strain or a lack of high-emotion coping skills) have higher levels of

periodontal disease even when data were adjusted for secondary behaviors 125

(Genco et al., 1998; Breivik et al., 2009). Thus, it may be that secondary behaviors act synergistically with the deviation of biological homeostasis caused by stress (e.g., GCs, cytokines, NPY, NE) to enhance inflammation. The selection of appropriate animal models can aid in elucidating these mechanisms.

Social disruption (SDR), an ethologically relevant murine model of social stress, is an appropriate animal model with which to study these mechanisms.

SDR shares similarities to other laboratory stressors such as HPA activation that results in elevated levels of GCs (e.g., corticosterone) and stimulation of the SNS resulting in increased catecholamines such as NE and epinephrine (Avitsur et al.,

2001; Hanke et al., 2012). However, while other laboratory stressors (e.g., prolonged, repeated restraint) are immunosuppressive, SDR enhances the immune system even in the absence of antigen (Avitsur et al., 2002), which may be more reflective of the human situation (i.e., stress-exacerbated inflammatory conditions). For example, SDR increases trafficking of primed macrophages/monocytes that contribute to enhanced antimicrobial immunity, bacterial clearance, and wound healing (Sheridan et al., 2004). Immune cells from SDR-treated mice are insensitive to GCs (Avitsur et al., 2001; Avitsur et al.,

2002; Quan et al., 2003). Furthermore, SDR has been found to induce a heightened inflammatory response to P. gingivalis (Bailey et al., 2009a).

Specifically, when stimulated with LPS derived from P. gingivalis, CD11b+ splenocytes from SDR-treated mice were found to be GC insensitive and to have

126

enhanced proinflammatory cytokine production (Bailey et al., 2009a).

Additionally, SDR increased TLR 2 and 4 expression on splenic macrophages,

and ligation of P. gingivalis LPS to these TLRs were found to be vital to

phagocyte reactivity and GC insensitivity (Bailey et al., 2009a). The mechanism

by which this occurs may lie in catecholamines, neuropeptides, and cytokine

mediators that play roles in both stress and inflammation.

3.1.3 NPY, NE, and IL-1β in stress and inflammation

Because of their roles in both inflammation and stress-exacerbated neurogenic inflammation, NPY, NE, and IL-1β have been implicated as therapeutic targets for periodontal inflammation. Pathophysiological conditions like severe infection or stress can activate the SNS to release NE and NPY to enhance IL-1β production, and these mediators serve as important communicators between the nervous and immune systems (Bedoui et al., 2003;

De la Fuente et al., 2001; Prod'homme et al., 2006). In vitro data suggest that

NE, NPY, and IL-1β that there is a regulatory relationship among these mediators that can affect biosynthesis and release (Barnea et al., 2001; Caviedes-Bucheli et al., 2008; El Karim et al., 2008; Lee and Herzog, 2009; Li et al., 2005; Lundy et al., 2009; Rosmaninho-Salgado et al., 2007; Wheway et al., 2005). Specifically, human and murine adrenal chromaffin and human astrocyte cell data suggest that IL-1β regulates NPY biosynthesis and release, and chromaffin cell data 127

indicate that NPY modulates catecholamine levels in an IL-1R1-mediated

manner (Rosmaninho-Salgado J et al., 2009;Rosmaninho-Salgado et al., 2007).

The highly selective, non-peptide NPY Y1 receptor (Y1R) antagonist BIBP3226

(R-N2-diphenylacetyl-N-4-hydroxyphenyl methyl-argininamide) has been a

powerful tool used to dissect the functional outcomes of Y1R signaling (Rudolf et

al., 1994). In chromaffin cells, immunoneutralization of NPY, or BIBP3226

treatment, inhibited the stimulatory effect of IL-1β on NE release (Rosmaninho-

Salgado et al., 2007). These elevated levels of NE can regulate inflammation through a βAR-activated NFκB pathway (Ferreira et al., 2010). Microglia stimulated with LPS or IL-1β and NPY or NPY agonist can display inhibitions in motility, phagocytosis, and nitric oxide (NO) and inducible nitric oxide synthase

(iNOS) production, and this inhibitory effect is mediated via Y1R and IL-1R1 with

BIBP3226 or IL-1ra treatment reversing these effects (Ferreira et al., 2011;

Ferreira et al., 2012). Additionally, in peripheral blood mononuclear cells

(PBMCs) and neutrophils, NPY, in the absence of antigen, can increase

monocyte activation and IL-1β secretion (Bedoui et al., 2001; Bedoui et al., 2008;

Bedoui et al., 2003). In vivo, studies with NPY Y1R knockout mice demonstrate that NPY-induced release and synthesis of NE is mediated by the Y1R (Cavadas et al., 2006). Though most of these data are from in vitro work, it is likely that the modulatory relationships between NPY, NE, and IL-1β do exist in vivo.

128

3.1.4 Norepinephrine

NE is released from the adrenal glands that lie atop the kidneys and

sympathetic nerves that innervate lymphoid organs and other tissues (Berlinger

et al., 2001). NE binds to two adrenergic receptor (AR) classes called alpha (α;

when NE is low) and beta (β; when NE is high). Several subtypes of ARs exist α1,

α2, β1, β2, and β3 with leukocytes predominantly expressing the β2AR. α1 AR

activation enhances some inflammatory processes, but appears to have little

therapeutic value (Rouppe van der Voort et al., 2000). βARs have had the most

therapeutic value with agonists being utilized to relax smooth muscle in the treatment of asthma (e.g., albuterol, salmeterol) and antagonists used in the treatment of high blood pressure and heart disease (e.g., metoprolol, atenolol, carvedilol) (Bond et al., 2007).

Stimulation of βAR activates adenylyl cyclases that catalyse the conversion of adenosine triphosphate (ATP) to 3’-5’-cyclic adenosine monophosphate (cAMP). cAMP then activates intracellular cAMP-dependent protein kinases that phosphorylate intracellular proteins to induce the physiological effects such as relaxation of smooth muscles and heart rate and force of contraction control (Elenkov et al., 2000). Additionally, cAMP can regulate gene expression and release of cytokines by binding to cAMP- responsive elements (CRE) on DNA (Montminy, 1997).

129

Reports on how NE affects cytokine production is varied and may depend

on whether the NE is derived systemically (e.g., stress) or locally (e.g., LPS or IL-

1 stimulation). Neurons and adrenal medulla are the major sources of

catecholamines, but macrophages can release NE and epinephrine after

activation with LPS or IFN-γ. In vitro, isoproterenol, a βAR agonist, increases

cytokine production from activated macrophages (Severn et al., 1992). In another

study, β2AR activation enhanced IL-1β and IL-6 production from macrophages

(Tan et al., 2007). However, in other studies, βAR binding during LPS stimulation decreases proinflammatory cytokine production. The possible role NE plays in local infection may involve macrophage autocrine actions. Studies suggest that

the release of catecholamines into the extracellular environment is rapid and that proinflammatory cytokines can be regulated by macrophage-derived catecholamines binding to α2AR eliciting an increase in inflammation or to β2AR eliciting a decrease in inflammation (Engler et al., 2004; Spengler et al., 1994).

In vivo, the existing sympathetic nervous tone of the organism may be extremely important for the fine-tuning of immediate responses of the innate immune system (Bedoui et al., 2003; Straub et al., 2006).

3.1.5 NPY

NPY is a highly conserved, widespread, and abundant 36 amino acid peptide that co-localizes and co-releases with NE upon SNS activation. Because 130

NPY does not have the ability to cross cell membranes, it binds to receptors on

target cell membranes to exert its biological effects. In the mouse, at least four

receptors are associated with NPY’s physiological effects: Y1, Y2, Y4, and Y5

(Dimitrijevic et al., 2005). Y1Rs are most densely expressed in immune cells

(e.g., T, B, and dendritic cells and macrophages), brain regions involved in the

stress response, and the oral cavity (e.g., osteoclasts, dental pulp, and crevicular

fluid ) (Eaton et al., 2010; El Karim et al., 2008; Gibbs and Hargreaves, 2008;

Lundy et al., 2009). Initially, NPY had been associated with feeding behavior and

adiposity, but current evidence points to NPY with additional roles in stress-

related disorders and the immune system (Eaton et al., 2010).

Resilience, or lack of vulnerability, to stress appears to be neuronally regulated, and this has been supported by studies highlighting regional NPY in the CNS and plasma as markers for increased resiliency to stress (Charney,

2004; Feder et al., 2009; McEwen, 2007; Morgan et al., 2000; Southwick et al.,

2004). Specifically, increased NPY mRNA expression has been measured in fear and anxiety brain regions such as the prefrontal cortex, hippocampus, hypothalamus, and amygdala of stressed animals characterized as stress resilient (Eaton et al., 2010; Krystal and Neumeister, 2009; Rutter, 2006). Models

using transgenic mice and antagonists show a role for NPY and the Y1 and Y2

receptors in mediating some aspects of the stress response and stress-related

disorders in rodents (Caberlotto and Hurd, 2013; Karlsson et al., 2008; Morales-

131

Medina et al., 2012; Gutman et al., 2008). Furthermore, NPY mRNA expression

in certain brain regions has shown an inverse correlation with trait anxiety and a

direct correlation with levels of stress-induced endogenous opioid release that

modulate the suppression of pain and stress responses (Zhou et al., 2008).

Additionally, in rodents, exogenously microinjected NPY has anxiolytic-like

effects such as inhibition and promotion of the extinction of fear conditioning and enhancement of cognition during stress (Zhou et al., 2008). In humans,

increased plasma levels of NPY have been found in Special Forces soldiers

undergoing extreme training (Morgan et al., 2000; Morgan et al., 2002). These

soldiers are deemed highly stress resilient, and the increased NPY was

associated with better performance. Overall, endogenous NPY seems to be

important for anxiety reduction and as a physiological stabilizer of neural activity

in circuits involved in the regulation of arousal and anxiety (Kask et al., 2002).

However, the exact mechanism by which NPY acts to increase stress resilience

is not yet known. Data have suggested that the various NPY receptors can have

opposing effects on the stress response and that the Y1R may have more of an

effect on the immune system than on anxiolysis (Bertocchi et al., 2011).

Overall, NPY enhances the immune system through the modulation of hormone and catecholamine secretion and interaction with endothelial and immune cells. In the periphery, NPY has roles in modulating pain, angiogenesis, vasoconstriction, tissue remodeling, leukocyte migration, lymphocyte and

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macrophage cytokine release, macrophage phagocytosis and chemotaxis, and

granulocyte production of nitric oxide (Dimitrijevic et al., 2006;Dimitrijevic et al.,

2010). The endothelium is a major site of action for NPY where it can act in an

autocrine fashion via Y1Rs (Ghersi et al., 2001; Zukowska-Grojec et al., 1998).

Furthermore, data have indicated that Y1Rs have anti-inflammatory capabilities

and are involved in the NPY modulation of pain and inflammation in caries,

pulpitis, periodontitis (Gibbs et al., 2004; Gibbs and Hargreaves, 2008; Kuphal et

al., 2008; Li et al., 2005). Overall, NPY and its Y1Rs may have important roles in

maintenance of periodontal health and the stress response by way of modulating

NE and IL-1β production, immune cell function, and subsequent neurogenic

inflammation (El Karim et al., 2009; El Karim et al., 2008; Lundy et al., 2009).

3.1.6 Aims of the study:

In the following studies, we extended the ex vivo findings that SDR exacerbates the inflammatory response to P. gingivalis to an in vivo murine calvarial inflammation model. We utilized propranolol, a non-selective βAR antagonist, and BIBP3226, a selective Y1R antagonist, and IL-1R1 knockout

(KO) mice (IL-1R1 KO) for these studies. We characterized the contribution of these receptors to NPY and proinflammatory gene expression modulation during

P. gingivalis-induced inflammation, and the contribution of these receptors to stress-induced exacerbation of NPY and proinflammatory gene expression 133

modulation during P. gingivalis-induced inflammation. We hypothesized that blockade of the βAR and Y1R would enhance NPY and proinflammatory gene expression, and deficiency of IL-1R1 would suppress NPY and proinflammatory gene expression following infection. Additionally, we expected stress to intensify inflammation especially during infection, and that blockade of these receptors during stress would attenuate the enhancement of NPY and proinflammatory cytokines. This is one of the first in vivo studies that explores the modulation of immune function and stress by the Y1R, βAR, and IL-1R1.

3.2 Methods

3.2.1 Animals

Male C57BL/6 (6-8 weeks old; housed 3/cage) and CD-1 (retired breeders; housed 1/cage) were purchased from a commercial source (Charles

River Inc, Wilmington, MA) and were allowed to acclimate to surroundings for a week prior to experimentation. All mice were housed in an American Association for the Accreditation of Laboratory Animal Care accredited facility and were maintained under environmentally controlled conditions on a 12:12-h light:dark cycle with ad libitum access to food and water. The Institutional Laboratory

Animal Care and Use Committee (IACUC) of The Ohio State University have approved all experimental animals and protocols used in this study.

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3.2.2 Bacterial and calvarial infection:

P. gingivalis strain W83 (from Drs. Eugene Leys and Christina Igboin,

Columbus, OH) was grown on Brucella blood agar plates (Anaerobe Systems;

Morgan Hill, CA) at 37°C in a chamber with an anaerobic atmosphere (85% N2,

10% H2, 5% CO2) for 48h. Anaerobic trypticase soy broth enriched with 5μg/mL

of hemin and 1μg/mL of menadione was then inoculated with bacteria and grown

in the anaerobic chamber for 24h. The bacteria were then harvested by

centrifugation at 4000 rpm for 10 min and supernatant was gently aspirated. The

pellet was resuspended in anerobic PBS and the OD at a wavelength of 600nm

was determined. It was previously established that an OD of 2.0 equaled 1011

CFUs of bacteria (Igboin et al., 2011). A low dose of Ket/Xy (7.8mg/mL ketamine

and 0.44mL of xylazine in 250μL) was injected i.p. to temporarily anesthetize and animals during calvarial injection. Freshly harvested P. gingivalis was injected subcutaneously (s.c.) into the tissues overlaying the mouse calvaria at a dose of

2x109 cells/mouse in a volume of 10uL. Control mice (vehicle) were injected with sterile PBS in the same area. Anesthetized animals were monitored according to

IACUC guidelines.

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3.2.3 Bacterial translocation and confirmation of live bacteria

To confirm no translocation of bacteria occurred systemically, various

dilutions of blood and spleen were plated to examine bacterial growth. Blood was diluted with PBS immediately after collection at 1:100, 1:1000, and 1:10,000

concentrations. The spleen was asceptically removed from animals,

homogenized in sterile PBS, and diluted with sterile PBS at 1:100, 1:1000, and

1:10,000 concentrations. Blood and spleen were spread on blood agar plates

and allowed to grow undisturbed in the anaerobic chamber for 7 days.

Additionally, to confirm that live bacteria was still present in the calvarial tissues

24 hours post infection, calvarial tissue was harvested, homogenized in PBS, and diluted to 1:100 and 1:1000 concentrations. These dilutions were spread onto blood agar plates and allowed to grow undisturbed for 5 days.

3.2.4 Pharmaceuticals:

Animals were pretreated with the drugs before experimental manipulation.

All drugs or vehicles were administered 1h before each cycle of SDR and/or

infection. Timing and frequency of the delivery of propranolol (subcutaneous;

10mg/kg); BIBP3226 (subcutaneous; 1mg/kg.), or vehicle (PBS) were based on

reported half-life and/or time to reach steady-state of the drug. Dosage of

propranolol was chosen based on previous studies in our laboratory and others

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and for its capacity to block all βARs (Hanke et al., 2012; Kohut et al., 1998;

Miura et al., 2007). BIBP3226 dosage was chosen based on previous studies

(Carlsson et al., 1998; Doods et al., 1996).

3.2.5 Social Disruption Stress:

The SDR paradigm is based on the repeated defeat of group-housed male

mice in their home cage. This social defeat is induced in the residents by daily

confrontations with an aggressive intruder male mouse. The confrontations occur

at the beginning of the active phase (17:00) when an aggressor mouse is placed

in the cage of the resident mice. The aggressor should attack the unfamiliar mice

within the first minutes of the confrontation and continue brief, yet consistent, attacks for the length of the 2h SDR cycle. During these attacks, the residents either initiate the display of submissive behavior (e.g., flight, defensive upright posture, retreat, and crouch) or aggressive behavior (e.g., retaliatory fighting). In any case, the aggressor mouse should win any confrontation with the residents because the aggressor is older, larger, and, due to its retired breeder status, has had previous social experience being the sole dominant male in a cage. If the intruder did not initiate an attack within 5–10 min, or was defeated by any of the resident mice, then a new intruder was introduced. At the end of the 2h cycle, the intruder was removed, and the residents were left undisturbed until the following day when the paradigm was repeated. SDR treatment consisted of 6 cycles over 137

6 consecutive days, and a new aggressor was used for each cycle. Home-cage

control (HCC) mice were also housed in cohorts of 3-5 per cage, but were left

undisturbed in a separate room. Sacrifice occurred the morning after the 6th cycle.

3.2.6 Real Time PCR:

In all studies, tissues were flash frozen in liquid nitrogen and RNA was extracted using the Trizol RNA isolation reagent (Invitrogen; Carlsbad, CA) according to manufacturer’s protocol. cDNA was obtained using a reverse transcription kit (Invitrogen; Carlsbad, CA). RT-qPCR was performed using an

ABI Prism 7000 Sequence Detection System (Applied Biosystems; Foster City,

CA) with specific primers and TaqMan probes (Applied Biosystems; Foster City,

CA) for the genes of interest (e.g., NPY, IL-1β, TNF-α, and IL-6). All PCR experiments were conducted in triplicate, and the data were analyzed by using the 2-ΔΔCt method and normalized to 18s rRNA.

3.2.7 IL-6 ELISA:

Blood was obtained intracardially from the mouse following euthanasia,

placed in heparinized vials, and kept on ice until centrifugation at 3500 rpm for 25

min. The plasma layer was removed from each sample and stored at -80°C until 138

assayed. The BD OptEIA IL-6 kit was used, and the protocol was performed

according to manufacturer’s instructions (BD Biosciences, San Diego, CA).

Briefly, plates were coated with 100µl of anti-mouse IL-6 monoclonal antibody

and incubated at 4°C overnight. The antibody was then blocked with PBS/10%

FBS and incubated for 1h at room temperature. Following washes with

PBS/Tween, 100µl of plasma or standard was added, and the plates were

incubated for 2h at room temperature. The plates were aspirated and washed

with PBS/Tween and 100µl of detector solution was added to each well. The

plates were incubated at room temperature for 1h before being washed.

Substrate solution (tetramethylbenzidine and hydrogen peroxide) was then

added to each well and incubated for 30 min in the dark. The reaction was

stopped by the addition of 50µl of 2N H2SO4, and an ELISA plate reader was

used to measure optical density at 450 nm with a 570 nm correction.

3.2.8 Statistical Analysis:

All data were expressed as the mean +/- standard error of mean (SEM).

All data were analyzed using Graph Pad Statistical Software (La Jolla, Ca).

Grubb’s tests were performed to detect outliers. Statistical significance was determined using one or two-way ANOVA with a Dunnett’s or Tukey’s post hoc test or unpaired t test as appropriate. In all cases, the level of significance was set at an α = 0.05.

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3.3 Results:

3.3.1 Verification of Calvarial P. gingivalis Inflammation Model

After successfully growing live cultures of P. gingivalis, we induced P.

gingivalis-mediated inflammation in mice by subcutaneously injecting live P. gingivalis or vehicle (sterile PBS) into the tissues over the calvaria (i.e., skull cap) as previously shown (Kesavalu et al., 2002).To study the kinetics of this infection, mice were sacrificed after 24h post-infection (pi) and 72h pi. These times were consistent with the times of sacrifice in the literature (Bakthavatchalu et al., 2011;

Naguib et al., 2003; Zubery et al., 1998). Spleens and blood were harvested to determine if the bacteria spread systemically or remained at the infection site.

Calvarial tissue at the injection site was excised and processed for RT-qPCR.

Spleens were homogenized in sterile PBS, and blood and spleen homogenate were diluted 1:100, 1:1000, and 1:10,000 with sterile PBS, spread onto blood agar plates, and allowed to incubate in an anaerobic chamber for one week. No bacterial colonies grew at any dilution for the spleen or the blood samples suggesting that the infection had not spread (data not shown).

Proinflammatory gene expression (IL-1β, IL-6, TNF-α), but not NPY, was significantly increased at 24h and 72h pi compared to respective control animals

(24h: NPY: t(22)=0.6126, p=0.5464; IL-1β: t(22)=4.39, p=0.0002; IL-6: t(22)=

3.71, p=0.0012; TNF-α:t(22)=4.41, p=0.0002; 72h: NPY: t(16)=1.117, p=0.5464;

IL-1β: t(16)=4.66, p=0.0002; IL-6: t(16)= 2.59, p=0.0197; TNF-α: t(16)=11.38, 140

p<0.0001; Figure 3.1 A,B). After 72h pi, mice did have a >50% reduction in

proinflammatory cytokine gene expression compared to 24h pi mice (Figure 3.1

A,B). These data suggest that after 72h pi the immune response was effectively

resolving the infection or that oxygen tension within the tissue contributed to the

eradication of the bacteria. Infected mice had slight swelling of the tissues

overlying the calvaria and surrounding the orbital region starting at ~16h (data

not shown). Swelling was visibly reduced after 72h pi (data not shown). Because

we were interested in the early innate inflammatory response to the P. gingivalis,

we decided to continue to examine the tissue at the 24h pi.

To verify that the bacteria were still viable 24h pi, infected calvarial tissue was homogenized, diluted to 1:100 and 1:1000, spread onto blood agar plates,

and allowed to incubate in an anaerobic chamber for 5 days (Figure 3.2). Many

of the colonies that grew on the plate developed the black pigmentation that is

characteristic of P. gingivalis bacteria. The number of colonies present were

affected in a dilution-dependent manner with more black pigmented colonies

being present on the 1:100 dilution plate compared to the 1:1000 dilution plate

(Figure 3.2). Non-pigmented colonies were likely to be cutaneous flora or young

colonies of P. gingivalis that had not yet developed pigmentation. The black

pigmentation develops over time from the accumulation of iron protoporphyrin

derived from the hemin in the blood agar plate (Lewis et al., 1999). The lack of

pigmentation could also be due to mutations where there is a defect in

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membrane translocation of gingipain-adhesin complexes, but these colonies can

develop pigment over time (7-14d on blood agar plates) (Chen and Kuramitsu,

1999; Yamaguchi et al., 2010).

3.3.2 Contribution of the βARs and Y1Rs to P. gingivalis infection:

Data from previous studies suggested that NPY and NE modulate proinflammatory cytokine production through the βAR, Y1R, and/or IL-1R1, but studies regarding how this might affect local inflammatory gene expression in an in vivo model had not been performed. To address this issue, wild-type mice were either pretreated with propranolol (non-selective βAR antagonist),

BIBP3226 (highly selective NPY Y1R antagonist) or vehicle (PBS) or the study was performed in IL-1R1 KO mice. All mice were then infected, and the tissue was harvested at 24h pi.

Compared to infected mice pretreated with vehicle (Inf), NPY gene expression was significantly increased in the infected tissue of propranolol- pretreated animals (Inf Prop), while it was decreased in the infected tissue of

BIBP3226 pretreated (Inf BIBP) and IL-1R1 KO (Inf KO) animals (F(3,41)=113.1, p<0.0001; Figure 3.3A). IL-1β and TNF-α gene expression were increased in both Inf Prop and Inf BIBP animals while decreased in tissue of Inf KO animals

(IL-1β: F(3,41)=33.40, p<0.0001; TNF-α: F(3,41)=66.41, p<0.0001; Figure 3.3

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B,C). IL-6 gene expression was increased in Inf Prop tissue, but not Inf BIBP or

Inf KO (F(3,41)=32.79, p<0.0001;Figure 3.3 D). Altogether, propranolol

pretreatment of infected mice significantly increased expression of NPY, IL-1β,

IL-6 and TNF-α. BIBP3226 pre-treatment of infected mice significantly decreased

NPY and IL-6 gene expression and increased IL-1β and TNF-α gene expression, and lack of IL-1R1 in infected mice abrogated the enhancement of NPY and all three proinflammatory cytokine responses.

3.3.3 Effect of SDR on Inflammation and Contribution of the βAR, Y1R,

and IL-1R1 to Stress-induced Exacerbation of Inflammation

Next, the contribution of the βAR, Y1R, and IL-1R1 to stress-induced

exacerbation of P. gingivalis-induced inflammation was examined. Wild-type

mice were administered antagonists or vehicle 1h before each cycle of SDR. IL-

1R1 KO and wild-type antagonist- or vehicle-treated mice underwent 6 cycles of

SDR or were left undisturbed (HCC). The morning after the 6th cycle, P. gingivalis or vehicle was injected into the tissues over the calvaria, and tissues were harvested 24h pi.

In previous studies of SDR, splenomegaly was a reliable indicator of the response to social stress (Avitsur et al., 2001; Stark et al., 2001), thus spleen

weights were assessed as a biomarker of the stress response (Figure 3.4).

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Uninfected HCC animals pretreated with either vehicle (HCC), propranolol (HCC

Prop), BIBP3226 (HCC BIBP), or IL-1R1 KO HCC animals (HCC KO) had spleen

weights that did not differ (F(3,35)=0.7803, p=0.5130; Figure 3.4A). Infected HCC

animals pretreated with either vehicle (HCC Inf), propranolol (HCC Inf Prop),

BIBP3226 (HCC Inf BIBP), or IL-1R1 KO HCC animals (HCC Inf KO) also had

spleen weights that did not differ (F(3,35)=0.1648, p=0.9193; Figure 3.4B).

Uninfected SDR animals pretreated with either vehicle (SDR), BIBP3226 (SDR

BIBP), or IL-1R1 KO SDR animals (SDR KO) had spleen weights that were

increased compared to propranolol pretreated (SDR Prop) or HCC animals

(F(3,63)=6.713, p=0.0001; Figure 3.4C). Similarly, infected SDR animals

pretreated with either vehicle (SDR Inf), BIBP3226 (SDR Inf BIBP), or IL-1R1 KO

animals (SDR Inf KO) had spleen weights that were increased compared to

propranolol (SDR Inf Prop) or HCC Inf animals (F(3,64)=8.590, p<0.0001; Figure

3.4D). Though we did not know what effect BIBP3226 pretreatment would have

on SDR-induced splenomegaly, previous studies had indicated that propranolol

pretreated SDR mice did not develop splenomegaly, while IL-1R1 KO SDR mice

did develop splenomegaly (Engler et al., 2011; Wohleb et al., 2011; Hanke et al.,

2012). These results are congruent with the previous studies.

In the absence of infection, vehicle pretreatment of SDR mice (SDR Uninf)

did not increase NPY or IL-6 gene expression in uninfected tissues compared to

vehicle pretreated controls (Figure 3.5 B,D; NPY: t(28)=0.4520, p=0.6547; IL-6:

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t(28)=1.453, p=0.206; Figure 3.5 A,C). SDR significantly increased IL-1β and

TNF-α in uninfected tissue compared to HCC uninfected tissue (HCC Uninf; IL-

1β: t(28)=6.331, p<0.0001; TNF-α: t(28)=3.951, p=0.0005). These data suggest

that prior to an infectious challenge, SDR induces an inflammatory environment to develop within the skin.

To determine that inflammation occurred with infection, NPY and proinflammatory gene expression in HCC Inf animals was compared to controls

(Figure 3.6). As in Figure 3.3, NPY gene expression did not increase, but IL-1β,

IL-6, and TNF-α gene expression did increase in HCC Inf tissue 24h pi (Figure

3.7A-D; NPY: t(28)=1.139, p=0.2644, IL-1β: t(28)=10, p<0.0001; IL-6: t(28)=17.99; p<0.0001; TNF-α: t(28)=34.96; p<0.0001).

Infected HCC mice that were administered propranolol (HCC Inf Prop) had increased NPY, IL-1β, IL-6, and TNF-α gene expression (NPY: F(3,50)=2.924, p=0.0428, IL-1β: F(3,50)=3.419, p=0.0242; IL-6: F(3,50)=8.834, p<0.0001; TNF-

α: F(3,50)=46.51, p<0.0001; Figure 3.6A-D). IL-1R1 deficient mice (HCC Inf KO) had decreased expression of NPY and IL-1β compared to HCC vehicle pretreated infection-only tissue (HCC Inf) similar to Figure 3.3 (Figure 3.7A,B); however, infected HCC BIBP3226-treated mice (HCC Inf BIBP) did not show a similar pattern (Figure 3.7A-D). Antagonists or vehicle were administered an hour before the SDR mice underwent stress, but not on the day of infection.

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Therefore, this effect may be due to the longer half-life of propranolol compared

to BIBP3226.

In SDR infected mice, propranolol (SDR Inf Prop) or BIBP3226 (SDR Inf

BIBP) administration before each stress cycle or IL-1R1 deficiency (SDR Inf KO)

was sufficient to completely abrogate the increased gene expression of NPY, IL-

1β, IL-6, and TNF-α compared to SDR infected mice pretreated with vehicle

(SDR Inf) (NPY: F(3,50)=26.82, p<0.0001; IL-1β: F(3,50)=55.44, p<0.0001; IL-6:

F(3,50)=122.9, p<0.0001; TNF-α: F(3,50)=12.70, p<0.0001; Figure 3.8A-D).

Another indicator of the stress response is an increase in plasma IL-6

(Wohleb et al., 2011; Hanke et al., 2012). Therefore, as an assessment of the

stress response we measured plasma of HCC and SDR infected mice (IL-1R1

KO mice were excluded due to breeding constraints) (Figure 3.9). Infection

increased IL-6 in HCC and SDR plasma, but propranolol and BIBP3226

pretreatment in SDR animals abrogated the increases (stress x treatment interaction; F(5,72)=9.005, p<0.0001).

3.4 Discussion:

3.4.1 Adapting the in vivo calvarial inflammation model

Periodontal inflammation has various outcomes in an affected host, but

left untreated, it results in tissue destruction, bone resorption, and eventual tooth 146

loss (Pihlstrom et al., 2005). These deleterious effects are known to be

exacerbated and precipitated by stress through largely unknown mechanisms

(Akcali et al., 2013). The experiments in this chapter examined putative

modulators of inflammation and provide some insight into the complex

relationship between stress and inflammation. Experiments were designed to explore the observation that NPY, NE and IL-1β have regulatory relationships among each other, and further to test the hypothesis that the βAR, Y1R, and IL-

1R1 modulate P. gingivalis-induced inflammation and stress-exacerbated inflammation. The results of the current study showed that blockade of either the

Y1R or βAR potentiated gene expression of proinflammatory cytokines during a

P. gingivalis infection, and that blockade of these receptors during stress

abrogated the stress-enhancement of NPY and proinflammatory gene expression

(Figures 3.3 and 3.9). Furthermore, IL-1R1 was necessary to stimulate

inflammation during infection and for the stress exacerbation of inflammation

(Figures 3.3 and 3.9).

Periodontal disease is often described as a polymicrobial disease, but the

Gram-negative, anaerobic, and non-motile bacteria, P. gingivalis, is a bacterial

species that can disrupt host-microbial homeostasis to cause inflammatory

disease (Hajishengallis et al., 2011). Proinflammatory cytokine production (e.g.,

TNF-α, IL-6, IL-1β) is one aspect of a P. gingivalis infection that appears to be

most devastating to the disease outcome (Kesavalu et al., 2002). For over a

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decade now, the in vivo calvarial model has been an effective laboratory model of periodontal inflammation (Kesavalu et al., 2002; Meka A et al., 2010;

Bakthavatchalu et al., 2011). The benefits of this model include the ease of

technique (i.e., injection in tissues over the mouse calvaria compared to oral

challenge), and the ease and reliability of measuring outcome variables like inflammatory cytokine profiles and bone resorption.

In these studies, local inflammation was induced by subcutaneously

injecting live P. gingivalis into the tissues over the calvaria (e.g., skullcap). After

24h, IL-1β, IL-6, and TNF-α gene expression were increased in infected animals

compared to uninfected controls (Figure 3.1A). After 72h, the pattern of gene

expression was similar, but attenuated by over 50% compared to 24h pi infected

data(Figure 3.1B). These data suggested that the height of this single infection

may be at 24h pi time point and that by 72h pi, the host is effectively resolving

the infection or the bacteria are succumbing to oxygen tension within the skin.

Interestingly, at either time point, infection alone did not increase NPY gene

expression. This observation is counter to in vitro data in which LPS stimulation

or IL-1β can induce NPY gene expression or NPY peptide production (Wheway

et al., 2007).

For the remainder of the studies, we chose to reduce our focus to the

early stages of infection or 24h pi. This time point not only marks a significant

inflammatory response in the model, but understanding this early innate immune

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response may have interesting implications for understanding periodontitis in relation to other diseases (Lazenby and Crook, 2010). Furthermore, reducing our focus allowed us to choose a simplified model, focus on the basic relationships, and to rule out some of the complexity such as bimodal actions of NPY that occurs with T cells (Wheway et al., 2007; Wheway et al. 2005).

To ensure that the 24h pi inflammatory response was due to bacterial infection, infected calvarial tissue was homogenized in sterile PBS, diluted to

1:100 and 1:1000, plated on blood agar plates optimal for P. gingivalis growth, and allowed to grow in an anaerobic chamber. After 5 days, black pigment was visualized in many of the colonies in a dilution-dependent manner confirming that the P. gingivalis from the calvarial tissue was indeed alive and able to replicate

(Figure 3.2). Also, observed on the plates were white-colored colonies. It is likely that these colonies were either young colonies of P. gingivalis that had not yet developed black pigment or colonies of other flora associated with the skin of the mouse that could withstand an anaerobic growth environment (e.g., candida).

3.4.2 βAR, Y1R, and IL-1R1 modulation of P. gingivalis-induced

inflammation in the absence of stress

In previous studies, blocking TNF-α and IL-1β stimulated by P. gingivalis enhanced anti-inflammatory cytokine production and reduced pathogenesis of

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the disease (Assuma et al., 1998; Berker et al., 2012; Chiang et al., 1999). NPY

and NE have been shown to modulate proinflammatory cytokine production

through Y1R, βARs, and IL-1R1, but studies on how this might affect local inflammation with a periodontal pathogen are limited. To study the contribution of these receptors to NPY and proinflammatory gene expression, wild-type mice were pretreated with propranolol, a non-selective βAR antagonist, BIBP3226, a selective NPY Y1R antagonist, or vehicle. These wild-type pretreated mice or IL-

1R1 KO mice were then infected with live P. gingivalis or sham infected with sterile PBS, and the infection was allowed to continue for 24h. Propranolol pretreatment of infected mice increased NPY and proinflammatory gene expression compared to infection-only tissue (Figure 3.3). This NPY increase with βAR blockade may suggest that the βAR mediated the suppression of NPY gene expression seen in infected tissue. Additionally, the proinflammatory gene expression enhancement with βAR blockade suggests that in the context of this

P. gingivalis infection βAR ligation is anti-inflammatory. These data agree with several studies where propranolol has been utilized to modulate inflammation and inflammation-related effects. For example, in a murine model of hemorrhage- induced lung injury, propranolol potentiated TNF-α and IL-1β gene expression, while the αAR antagonist phentolamine inhibited expression (Le Tulzo et al.,

1997). Additionally, in orally P. gingivalis-challenged rats, propranolol inhibited the progression of P. gingivalis-induced alveolar bone loss (Okada et al., 2010).

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In further review of the literature, data support that the type of bacteria or

bacterial product (e.g. Gram-negative or positive) affected the outcome of βAR antagonists on inflammation. For example, one study examined the role of βARs in LPS- induced (Gram-negative) and lipoteichoic acid-induced (LTA; a component of Gram-positive bacteria cell wall) lung inflammation (Giebelen et al.,

2008). Both LPS and LTA caused an inflammatory response, but propranolol administration only enhanced inflammation in LPS-administered animals (TNF-α,

IL-6, and MCP-1), demonstrating that βAR stimulation in the presence of Gram- negative bacteria was predominantly anti-inflammatory. In another study, administration of propranolol to mice challenged with LPS enhanced circulating

TNF-α concentrations (Sekut et al., 1995). In addition, complete ablation of the

SNS can have similar effects to receptor blockade. In a mouse model of sepsis, ablation of the SNS decreased dissemination of Pseudomonas aeruginosa or

Escherichia coli (E.coli) through a mechanism of increased secretion of TNF-α, improved phagocytic response of peritoneal cells, and increased influx of monocytes into the peritoneal cavity (Straub et al., 2005). In another study, chemical sympathectomy enhanced the innate immune response and decreased the specific immune response in spleen to infection with Listeria monocytogenes

(Rice et al., 2001). On the other hand, activation of SNS by experimental stress led to an increased tissue burden of Gram-negative bacteria (Cao et al., 2003).

These data suggest that although βAR antagonist administration does create an

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increased proinflammatory environment in response to Gram-negative bacteria

that it may be helpful for the eradication of the bacteria.

In vivo studies examining the Y1R and infection are largely absent, and

much of the data about inflammation and the Y1R derive from in vitro models. It is thought that NPY is largely anti-inflammatory through its Y1R, and in this study we have confirmation of NPY’s anti-inflammatory capabilities. BIBP3226 pretreatment of infected mice increased IL-1β and TNF-α expression compared to infection-only mice (Figure 3.3). NPY and the Y1R have been directly

associated with oral health. In studies of periodontitis subjects, significantly

higher levels of NPY were found in healthy periodontal sites from control subjects

compared to diseased sites from periodontitis subjects (Lundy et al., 2009). In a

rat pulpitis model, Y1R was found in capillaries and small vessels in the dental

pulp as well as in the odontoblastic layer, but not on pupal immune cells

(Rethnam et al., 2010). As disease progression increased, Y1R expression

increased on granulocytes, lymphocytes, and a decreased on blood vessels

expressing Y1R in the odontoblast layer (Rethnam et al., 2010). Previous studies

have shown that immunoneutralization of NPY or using the Y1R antagonist

BIBP3226, inhibits the stimulatory effect of IL-1β on catecholamine release.

Along with direct effects, the BIBP3226 increase in proinflammatory gene expression may be due to NPY’s role in attenuating the anti-inflammatory NE.

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Illustration 3.1 (A) diagrams the proposed mechanism by which these

effects occur. At the level of the immune cell, TLR ligation during infection leads

to an increase in IL-1β. When IL-1β binds to IL-1R1, an increase in both NPY and NE is induced. The increase in NPY induces increases in NE that through mostly αAR pathways increases IL-1β. Eventually, the locally produced NE will be elevated sufficiently to activate βAR pathways that may limit inflammation.

Blocking the activity of the βAR will prevent the ability to reduce inflammation as needed and will result in NE binding exclusively to αARs to enhance inflammation (Illustration 3.1B). Blocking the activity of the Y1R will reduce the amount of NE locally produced, but this low level of NE will still stimulate the αAR pathways to increase inflammation (Illustration 3.1C). Finally, when the IL-1R1 is unavailable, IL-1β has no mechanism in which to increase NPY or NE thus abrogating the inflammatory response (Illustration 3.1D).

3.4.3 Stress modulation of inflammation

In addition to direct host-pathogen interactions, periodontitis is

exacerbated by systemic risk factors including age, gender, secondary health

behaviors (e.g., smoking and hygiene), and diabetes mellitus (Genco et al.,

1996). Alone, stress can increase circulating and tissue cytokines, and clinical

studies have shown that stress can also exacerbate periodontal inflammation

(Elenkov and Chrousos, 2002). The results of the experiments in this chapter 153

demonstrate that in the absence of infection, SDR increased proinflammatory

gene expression in tissue (Figure 3.5) suggesting that SDR caused a baseline

proinflammatory state to occur in the skin. Since social stress in mice involves

cutaneous wounding, this may be an adaptive strategy employed by the immune

system in anticipation for future attacks and may be due to an increase of primed

and activated immune cells to the tissue. The addition of an infection challenge

after stress further enhanced inflammation (Figure 3.8), and antagonizing Y1Rs

or βARs during stress blocked this response (Figure 3.9).

Stress stimulates a large systemic increase in catecholamines affecting immune cell function and activity. For example, cutaneous wound healing of chronically stressed mice is improved through blockade of catecholamines

(Romana-Souza et al., 2010), and oral challenge with P. gingivalis in the presence of stress-induced increases in GC levels due to stress can accelerate alveolar bone loss and osteoclastic activity (Nakajima et al., 2006). Additionally, previous studies from our laboratory indicate that SDR induces the activation of stress-related brain regions, and peripheral stress effects in a βAR- and IL-1R1- mediated manner (Engler et al., 2008; Wohleb et al., 2011; Hanke et al., 2012;

Powell et al., 2013). By antagonizing βARs with propranolol or using IL-1R1 deficient mice, SDR-induced peripheral and central inflammatory effects of SDR are prevented.

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The data here extend the immunoneutralizing effects of propranolol and

IL-1R1 deficiency on SDR to a local bacterial infection. However, it was not clear that BIBP3226 pretreatment would have the same effects. The literature is absent of studies that use BIBP3226 in the context of an extended animal model of stress. Since NPY has ameliorative effects on anxiety-like behavior in control mice, we speculated that stress effects of SDR may not be reduced by

BIBP3226. However, we also considered that by blocking Y1R, the release of NE and IL-1β would be attenuated to effectively block the stress response. Together these data suggest blockade of the biological actions of the SNS and IL-1R1 during stress can have a significant impact on subsequent bacterial infection, and that βAR and Y1R blockade may differentially affect inflammatory gene expression during times of repeated social stress.

Previous data have shown that SDR, in a βAR-mediated manner, can both induce the activation of stress-related brain regions and stimulate peripheral pathways. By blocking βARs with propranolol, peripheral and central inflammatory effects of SDR including increased IL-1β production and brain region activation were abrogated (Hanke et al., 2012; Wohleb et al., 2011). The data in this study extend the immunoneutralizing effects of propranolol pretreatment of SDR to local infections. However, it was not clear that BIBP3226 pretreatment would have the same effects. Splenomegaly, as one indicator of the

SDR stress response, was present in SDR BIBP3226-treated mice (Figure 3.4).

155

Splenomegaly was also present in IL-1R1 KO animals which agrees with

previous studies (Engler et al., 2008). In Engler et al., (2008) even though

splenomegaly was present in SDR KO animals, the increase in spleen weight

was not attributed to an increase in leukocytes trafficking to the spleen, and

resident splenocytes from KO animals were not found to be GC resistant.

Interestingly, when plasma IL-6 was measured in infected animals, BIBP3226

and propranolol treatment of SDR-treated animals abrogated the increase seen

in other animals (Figure 3.10). Taken together, these data suggest that Y1Rs and

βARs are necessary for the induction of a proinflammatory state that results from

stress.

Effects of stress on infectious diseases may be mediated by the products

of the nervous and neuroendocrine systems that work to affect the function and

release of immune cells as part of host defense mechanisms. Propranolol may

modulate the function and activity of other innate immune cells such as

macrophages that can produce inflammatory cytokines. Stress stimulates a systemic increase of catecholamines, and through the activation of βARs can enhance and prolong inflammation in infected mice. Hormones such as NE increase in the bloodstream and local tissues in response to stress, and this may affect the composition or phenotype of subgingival periodontopathogens. In other studies, cutaneous wound healing of chronically stressed mice is improved through catecholamines blockade (Romana-Souza et al., 2010), and oral

156

challenge with P. gingivalis under increased GC levels due to stress can

accelerate alveolar bone loss and osteoclastic activity (Nakajima et al., 2006).

Altogether, these data suggest that the increased sympathetic activity due to

stress impacts the immune system in a negative manner. Blockade of the

biological actions of the SNS can have a significant impact on subsequent

infections. Taken together, these data suggest that βAR and Y1R blockade may differentially affect inflammatory gene expression during times of stress.

Inflammation is a double-edged sword as it is necessary to eradicate bacteria and resolve infection, but excessive inflammation may increase tissue damage leading to enhanced pathology. In the case of periodontal inflammation, the environment in which the inflammation occurs is highly dependent on preservation of the tissue structure to maintain function. Enhanced inflammation may eliminate the cause of the infection, but the tissue structure and function may be compromised. This is reflective of findings in a social influenza viral infection model in which influenza-infected exposed to SDR generated an enhanced anti-viral T cell response, but increased immunopathology in the lung enhanced disease severity (Mays et al., 2010). Therefore, it is debatable as to whether SDR-induced inflammation during a bacterial infection contributes to host defense or to increased immunopathology. Histological studies performed on the calvarial tissue in these experiments that all infected samples (HCC and

SDR) had a great deal of neutrophilic infiltration and degranulation that made

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determining differences at this time point not possible (data not shown). In

Naguib et al., (2004), histological findings were similar in that differences among

groups were hard to detect until 72h pi suggesting that future histology should be

performed at the 72h pi time point.

Illustration 3.2 diagrams the proposed mechanism of stress-induced

modulation of inflammation in the context of Y1R, βAR, and IL-1R1 blockade or

deficiency. In a manner similar to illustration 3.1, stress yields an environment

that is conducive for enhanced inflammation. Through mediators such as

systemic NE, stress can increase the priming, activation, and trafficking of

immune cells that can work to increase inflammation in tissues even in the

absence of infection. It is proposed that stress can also increase receptors and ligands for these mediators that further enhance the stress response. Therefore,

when an animal is infected subsequent to SDR exposure, inflammation can be

exacerbated compared to non-stressed infected animals. If the activity of the

Y1R, βAR, and IL-1R1 are blocked during stress, this can affect the stress

enhancement of the priming, activation, and trafficking of immune cells and likely

the upregulation of receptors for these mediators and therefore inhibit the stress-

induced enhancement of inflammation.

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3.4.4 Conclusions:

The work in this chapter sought to elucidate the relationship between

NPY, NE, and inflammation and extend previous findings to an in vivo model.

Collectively, these experiments have provided insight into the involvement of the

Y1R, βAR, and IL-1R1 in P. gingivalis-induced inflammation and stress-induced exacerbation of inflammation during infection. Stress-induced activation of the

βAR, Y1R, and IL-1R1 has the potential to play a major role in modulating the

immune system during stress and subsequent bacterial challenge. However, it is

important to note that in non-stress conditions, blocking these receptors during

inflammation can have an opposite effect. NPY and NE continue to be potential

therapeutic targets, but it is important to recognize that responses can be

different depending on the sympathetic tone of the animal. More studies will need

to be completed to understand the pathophysiological implications of Y1R and

βAR blockade on stress-exacerbated P. gingivalis-induced inflammation. Further

exploring these mechanisms will not only aid in identifying novel therapeutic

targets, but also elucidate the connection between stress and periodontitis.

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A 100 Uninf * 24h Inf 80

40 *

20 * Fold Change Over Change Over Fold Uninf 0 NPY IL-1β IL-6 TNF

B 100 Uninf 72h Inf 80

40 *

20 *

Fold Change Over Change Over Fold Uninf * 0 NPY IL-1β IL-6 TNF

Figure 3.1: P. gingivalis-induced proinflammatory and NPY gene expression at 24h and 72h pi in wild-type mice. Tissues over the calvaria of wild-type mice were injected with live P. gingivalis (Inf) or vehicle (Uninf). Infection continued for either 24hrs (A) or 72hrs (B) at which time the tissue at the site of injection was excised and processed for real-time RT-qPCR. NPY and proinflammatory (IL-1β, IL-6, and TNF-α) gene expression was then determined. Data are representative over two experiments and bars are expressed as mean fold change in gene expression over the uninfected group (Uninf) ± SEM (n=9-12;*p<0.05).

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1:100 dilution

1:1000 dilution

Figure 3.2: Confirmation that P. gingivalis bacteria were still viable 24h pi. A piece of infected calvarial tissue (24h pi) was homogenized in sterile PBS, diluted in sterile PBS at 1:100 and 1:1000 dilution, and both dilutions were spread onto blood agar plates. Plates were incubated in an anaerobic chamber for 5 days. Black pigments characteristic of P. gingivalis bacteria are observed in several colonies in a dilution-dependent manner. Other colonies (white) may or may not have been P. gingivalis and could be other bacteria associated with the skin of the mouse.

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A B 3 4 Inf Inf Inf Prop Inf Prop Inf BIBP Inf BIBP * Inf KO * 3 Inf KO 2 * 2

1 * * 1 Fold Change Over Over Change Inf Fold Fold Change Over Over Change Inf Fold * 0 0 NPY IL-1β C D 12 8 Inf Inf Inf Prop * Inf Prop Inf BIBP Inf BIBP Inf KO 6 Inf KO 8 * 4 * 4 2 Fold Change Over Over Change Inf Fold Fold Change Over Over Change Inf Fold

0 * 0 * TNF IL-6

Figure 3.3: Effects of βAR antagonist propranolol, NPY Y1 receptor antagonist BIBP3226, and a deficiency of IL-1R1 on NPY and proinflammatory gene expression in P. gingivalis-infected calvarial tissue 24h pi. NPY gene expression was increased in the infected tissue of propranolol pretreated animals (Inf Prop) while it was decreased in the infected tissue of BIBP3226 pretreated (Inf BIBP) and IL-1R1 KO (Inf KO) animals (A). IL-1β and TNF-α gene expression were increased in both Inf Prop and Inf BIBP animals while both genes were decreased in tissue of Inf KO animals (B,C). IL-6 gene expression was increased in Inf Prop tissue, but not Inf BIBP or Inf KO (D). Overall, receptor blockade appears to modulate NPY and proinflammatory gene expression in P. gingivalis- induced inflammation. Data are expressed as fold change in gene expression over the infection-only group (Inf) ± SEM (n=9-12; *p<0.05). 162

A B 120 HCC 120 HCC Prop HCC Inf HCC BIBP HCC Inf Prop 100 HCC KO 100 HCC Inf BIBP HCC Inf KO 80 80

60 60

40 40

20 20 Inf Spleen Weights(mg) Uninf Spleen Weights (mg) 0 0

C D HCC Inf 240 HCC 240 SDR Inf SDR SDR Inf Prop 200 SDR Prop 200 SDR Inf BIBP SDR BIBP SDR Inf KO SDR KO 160 * 160 * * * * 120 * 120 80 80

40 40 Inf Spleen Weights (mg) Weights Spleen Inf Uninf Spleen Spleen Uninf Weights (mg) 0 0 Figure 3.4: Propranolol, but not BIBP3226 or lack of IL-1R1, blocks SDR- induced splenomegaly in infected and uninfected animals. Spleen weights do not differ in HCC uninfected (HCC, HCC Prop, HCC BIBP, HCC KO) or HCC infected tissue (HCC Inf, HCC Inf Prop, HCC Inf BIBP, HCC Inf KO; A,B). Stress increases spleen weight in uninfected (SDR) and infected animals (SDR Inf) compared to HCC (HCC, HCC Inf; C,D). Propranolol treatment before each cycle of stress (SDR Prop, SDR Inf Prop), but not BIBP3226 treatment (SDR BIBP, SDR Inf BIBP) or lack of IL-1R1 (SDR KO, SDR Inf KO), abrogates the increase in spleen weight in uninfected or infected animals compared to HCC (HCC, HCC Inf, C,D). Bars indicate mean spleen weights in mg ± SEM (n=9-15; *p<0.05).

163

Figure 3.5: Effects SDR on NPY and proinflammatory gene expression in uninfected calvarial tissue. SDR, alone (SDR Uninf), increases IL-1β and TNF-α gene expression in uninfected tissue compared to HCC (HCC Uninf). Data are expressed as fold change in gene expression over the HCC Unif group ± SEM (n=15; *p<0.05).

164

Figure 3.6. NPY and proinflammatory gene expression in HCC uninfected and infected calvarial tissue. Infection in HCC animals increases IL-1β, TNF-α, and IL-6, but not NPY. Data are expressed as fold change in gene expression over the HCC Uninf group ± SEM (n=15; *p<0.05).

165

A 3 B HCC Inf 6 HCC Inf HCC Inf Prop HCC Inf Prop HCC Inf BIBP HCC Inf BIBP HCC Inf KO HCC Inf KO 2 4 * *

1 2

* Fold Change Over Change Over Fold HCCInf Fold Change Over Change Over HCCFold Inf * 0 0 NPY IL-1β CD 6 HCC Inf 5 HCC Inf Prop HCC Inf HCC Inf BIBP HCC Inf Prop HCC Inf KO 4 HCC Inf BIBP * HCC Inf KO 4 3

2 * 2 1 Fold Change Over Change Over Fold HCC Inf Fold Change Over Inf HCC Over Change Fold * * 0 0 TNF IL-6

Figure 3.7: NPY and proinflammatory gene expression in HCC infected calvarial tissue. HCC animals were pretreated with propranolol or BIBP3226 before each stress cycle or unstressed IL-1R1 KO mice were used. Mice were infected the morning after the last stress cycle and the infection was allowed to continue for 24h. Likely due to the long half-life of propranolol, gene expression in HCC Inf Prop tissue was similar to figure 3.3. Gene expression for the HCC Inf KO animals was also similar to figure 3.3. HCC Inf BIBP tissue did not show the same gene expression as figure 3.3 and this could be due to the short half-life of BIBP3226. Data are expressed as fold change in gene expression over the vehicle-treated HCC Inf group ± SEM (n=9-15; *p<0.05).

166

A B 3 4 HCC Inf HCC Inf SDR Inf SDR Inf *

* 3 2

1 1 Fold Change Over HCC Inf Over Change Fold Fold Change Over HCC Inf Over Change Fold

0 0 NPY IL-1β C D 4 6 HCC Inf HCC Inf * SDR Inf * SDR Inf 5 3 4

2 3

2 1 1 Fold Change Over HCC Inf Over Change Fold Fold Change Over HCC Inf Over Change Fold

0 0 IL-6 TNF

Figure 3.8: SDR enhances NPY and proinflammatory gene expression in infected calvarial tissue. Data are expressed as fold change in gene expression over the HCC infected group (SDR Inf) ± SEM (n=9-12; *p<0.05).

167

A B 2 2 SDR Inf SDR Inf SDR Inf Prop SDR Inf Prop SDR Inf BIBP SDR Inf BIBP SDR Inf KO SDR Inf KO

1 1

* * * * * * Fold Change over Change over Fold SDR Inf Fold Change over Change over Fold SDR Inf 0 0 NPY IL-1β C 2 D 2 SDR Inf SDR Inf SDR Inf Prop SDR Inf Prop SDR Inf BIBP SDR Inf BIBP SDR Inf KO SDR Inf KO

1 1

* * * Fold Change over Change over Fold SDRInf Fold Change over Change over Fold SDR Inf * * * 0 0 TNF IL-6

Figure 3.9: Effects SDR on NPY and proinflammatory gene expression in infected calvarial tissue. Propranolol (SDR Inf Prop) or BIBP3226 (SDR Inf BIBP) treatment administered before each cycle of stress or utilizing IL-1R1 KO animals abrogated the enhanced NPY and proinflammatory gene expression modulated by stress. Data are expressed as fold change in gene expression over the SDR infected group (SDR Inf) ± SEM (n=9-12; *p<0.05).

168

450 HCC Inf HCC Prop Inf 400 HCC BIBP Inf 350 SDR Inf SDR Prop Inf 300 SDR BIBP3226Inf 250 200 150 Plasma IL-6 ng/mL 100 50 * * 0

Figure 3.10: Effects SDR and drug treatment on plasma IL-6 in infected animals. Infection increased plasma IL-6 in HCC mice regardless of drug treatment and in vehicle-treated SDR mice. Propranolol or BIBP treatment abrogated the plasma IL-6 increase in stressed animals. Data are expressed as mean of plasma IL-6 concentrations in ng/mL ± SEM (n=9-15; *p<0.05).

169

Infection Propranolol + Infection

Inflammation Inflammation

IL-1β IL-1β IL-1R1 IL-1R1 AR AR X AR β AR β α α Low NE High NE NE NPY NE NPY

ABY1R Y1R BIBP‐3226 + Infection IL‐1R1 KO + Infection

Inflammation IL-1β IL-1R1

IL-1β X AR AR β IL-1R1 α AR AR β α NE NPY

NE NPY

Y1R

C Y1RX D

Illustration 3.1: Proposed mechanisms for Y1R, βAR, and IL-1R1 interaction during infection.

170

Illustration 3.2: Proposed mechanisms for Y1R, βAR, and IL-1R1 interaction during infection that is subsequent to stress.

171

CHAPTER 4

DISCUSSION

4.1 Social stress was immunoenhancing:

Over a decade of research has yielded data to support that social stress can be immunoenhancing. Much of these data have characterized the profound immunological and behavioral effects that a social stressor can have including the disruption of the homeostatic balance of the organism even in the absence of

challenge. When disease models are used subsequent to SDR,

immunoenhancement is highly evident. This can be of benefit to the host as in

the case of wound healing, bacterial clearance, or influenza, but can also be

deleterious to the host as in the case of sepsis or allergic airway inflammation

(Sheridan et al., 2004; Bailey et al., 2007; Mays et al., 2010; Quan et al., 2001;

Bailey et al., 2009a; Bailey et al., 2009b). The directionality of the response

reflects the nature of the challenge. Thus, these studies demonstrate dual nature

of inflammation, and illustrate the manner in which inflammation can function as

a double-edged sword.

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The disease models utilized in this dissertation, the calvarial model of P.

gingivalis-induced inflammation and Aspergillus fumigatus-induced allergic

airway inflammation, showed that SDR enhanced the immune response to the

challenge. Whether or not this immunoenhancement is ultimately beneficial to the

animal’s defense mechanisms is not clear as elevated immune responses can

increase pathology. This is especially apparent in the allergic airway

inflammation model where social stress was shown to exacerbate inflammation,

neutrophilic lung infiltration, and a state of GC resistance in mice. These

attributes of enhanced immunity have striking similarities to the clinical

presentation seen in severe forms of asthma. The results from the calvarial

model showed great similarities to the regulation of the mediators in vitro, but, the addition of the stress or before the infection, yielded results that gave insight into the complexities of how stress can affect the immune system.

4.2 Contribution of Y1R, βARs, and IL-1R1s to P. gingivalis-induced inflammation and stress-exacerbated P. gingivalis-induced inflammation

Over the last few years, several in vitro studies have described regulatory relationships among Y1R, βAR, and IL-1R1 and their respective ligands

(Rosmaninho-Salgado et al., 2007; Rosmaninho-Salgado et al., 2009; Ferreira et al., 2010; Ferreira et al., 2010). These receptors and ligands are involved in the inflammatory and stress responses, thus, the idea of extending the in vitro findings to an in vivo stress and disease model was a logical next step. 173

Furthermore, with these studies, we could expand on the ex vivo findings of the

SDR-induced exacerbation of the inflammatory response to P. gingivalis (Bailey et al., 2009a). Our model employed βAR and Y1R antagonists and IL-1R1 KO mice to characterize the contribution of these receptors to the modulation of NPY and proinflammatory gene expression in P. gingivalis-induced inflammation and the contribution of these receptors to stress-induced exacerbation of inflammation. We hypothesized that blockade of βAR and Y1R would enhance, and deficiency of IL-1R1 would suppress, NPY and proinflammatory gene expression following infection. Additionally, we expected stress to intensify inflammation especially during infection, and that blockade of these receptors during stress would attenuate the enhancement of NPY and proinflammatory cytokines.

In the absence of stress, antagonizing the βAR and Y1R increased proinflammatory cytokine gene expression during P. gingivalis induced inflammation. NPY gene expression was increased by antagonizing the βAR. IL-

1R1 blockade prevented increases in both NPY and proinflammatory gene

expression. At the level of the immune cell, these data allowed us to propose that

increases in IL-1β due to infection can induce an increase in both NPY and NE via the IL-1R1. The increase in NPY leads to further increases in NE that through

αAR pathways further increases IL-1β. Over time, we speculate, that the locally produced NE will be elevated sufficiently to activate βAR pathways that may limit

174

inflammation. Furthermore, we propose that blocking the activity of the βAR prevents the ability to reduce inflammation as needed and will result in NE binding exclusively to αARs to enhance inflammation. Additionally, blocking the activity of the Y1R will reduce the amount of NE locally produced, but this low level of NE will still stimulate the αAR pathways to increase inflammation. Finally, when the IL-1R1 is unavailable, IL-1β has no mechanism in which to increase

NPY or NE, thus abrogating the inflammatory response.

When an animal is infected subsequent to SDR exposure, inflammation can be exacerbated compared to non-stressed infected animals. If the Y1R, βAR, and IL-1R1 are blocked during the stress response, the NPY and proinflammatory gene expression enhancement is abrogated. Through mediators such as systemic NE, stress can increase the priming, activation, and trafficking of immune cells that can work to increase inflammation in tissues even in the absence of infection. It has been speculated that stress can also increase receptors and ligands for these mediators that may further enhance the stress response. If the activity of the Y1R, βAR, and IL-1R1 are blocked during stress, this can affect the stress enhancement of the priming, activation, and trafficking of immune cells and likely the upregulation of receptors for these mediators and therefore inhibit the stress-induced enhancement of inflammation. Overall, the stress enhancement of P. gingivalis-induced inflammation is likely due to systemic increases of stress mediators and receptors that can further enhance

175

local autocrine actions of immune cells at the site of infection. The work in this

chapter sought to elucidate the relationship between NPY, NE, and inflammation

and extend previous in vitro findings to an in vivo model. The data suggest that

NPY and NE are still viable therapeutic targets, but the differential effects of the antagonists depend on the sympathetic tone of the animal.

4.4 Immune cells enhanced by SDR are of bone marrow origin

SDR is known to induce the mobilization of a large increase of leukocytes

that are distributed to tissue like the spleen and lung. Engler et al., (2004) had

hypothesized and showed data to support that these cells were likely recruited

from the bone marrow. To definitively determine the origin of these cells, a GFP+

bone marrow chimera model was employed. After 6 cycles of SDR, it was

apparent through histology and flow cytometry that SDR mobilized bone marrow-

derived immune cells to organs such as the spleen and the lung. These data

demonstrated that the increase in myeloid cells (e.g., monocytes/macrophages

and neutrophils) in these target organs was due to stress-induced release from

the bone marrow.

4.5 Stress-exacerbated allergic airway inflammation model cell phenotypes

Bailey et al., (2009b) had described an increase of lymphocytes and eosinophils in bronchoalveolar lavage fluid in SDR Af sensitized and challenged 176

CD-1 mice. In our studies, the BALB/C strain of mouse was used in an attempt to

enhance the response to allergic airway inflammation and to reduce the

variability that may occur in an outbred strain. We were aware that using a different strain of mouse might result in some differences in response to stress and challenge. Cell distribution was examined in bone marrow, blood, and lung.

Contrary to the Bailey et al., (2009b) study, we did not find increases in B cells in any organ, and this finding may be a strain-dependent difference. In the bone marrow, we found that social stress shifted the balance of granulopoiesis and monopoiesis in the bone marrow. This finding was similar to what had been described in previous studies using the C57BL/6 (Engler et al., 2004; Powell et al., 2013). Both monocytes and granulocytes were increased by SDR, and SDR and challenge in the blood, spleen, and lung, with the most dramatic effect for challenged SDR mice occurring with the increase in granulocytes. This finding gave us cause to examine the granulocytic population more closely.

4.6 Immature neutrophils as a possible contributor to the deleterious effects of SDR on allergic airway inflammation

An essential role for neutrophils exists in the earlier time points following

Af challenge (Mircescu et al., 2009). Engler et al., (2004) had proposed and had

data in support of the concept that SDR induced the release of immature

neutrophils. This notion was based on the SDR increase in neutrophils that had a

low expression of GR-1. In our studies, two antibodies, CD16 and CD49d, were 177

used to more specifically identify subpopulations of granulocytes in the lung and

blood. After gating granulocytes on high SSC (measure of granularity), these two antibodies allowed us to distinguish populations of cells such as activated neutrophils, mature neutrophils, apoptotic neutrophils, immature neutrophils, and eosinophils. In our model, we found that stress and challenge increased a population of neutrophils in the blood and lung that was identified as a heterogeneous mixture of immature neutrophils. This finding may describe a cellular mechanism that leads to enhanced allergic airway inflammation in SDR mice. The functional contribution of these immature neutrophils to inflammation and disease has not been fully elucidated; however, it is clear that these neutrophils are associated with enhanced inflammation in the clinic and experimental laboratory (Drifte et al., 2013; Okawa-Takatsuji et al., 2007; Pillay et al., 2012; Shevchenko et al., 2013). Our data showed increased alkaline phosphatase activity in the lung of stressed and challenged mice (alkaline phosphatase is a toxic enzyme stored at an increased level in immature

neutrophilic granules). This finding may give some insight into the functional

capability of these immature cells. These neutrophils may be longer lived than

normal, and this longer life span may also contribute to the enhanced

inflammation. These data are supported by the increased granulocytes and GM-

CSF gene expression in the lung after stress and challenge. The half-life of a

neutrophil is relatively short (24-48h), thus an increase in the neutrophil

population in the spleen and lung after 6 cycles of SDR could be due, at least in

178

part, to extended cell survival (Fadeel et al., 1998; Webb et al., 2000). Increases in circulating endogenous GCs can increase neutrophil survival and cause cellular accumulation. In all, these studies yielded data that point to the importance of granulocytes, such as neutrophils in the stress response and in the response to stress and Af challenge, and these studies further suggest that immature forms of the granulocyte may contribute to enhanced airway inflammation.

4.7 Future directions

The calvarial model of a local bacterial infection and SDR has tremendous potential to contribute to our understanding of the mechanisms of stress and inflammation than might contribute to disease severity. The studies in Chapter 2 examined the gene expression of inflammatory mediators of the early phase of a single P. gingivalis infection. At this time point, examining other indicators of NE,

NPY, and IL-1 production and associated receptors could add to these data.

Immunohistochemistry would be an appropriate laboratory technique to address this issue. We speculated that some of the effects of stress on these mediators not only happen at a systemic level, but at the receptor level, and perhaps autocrine or paracrine levels as well. Immunohistochemistry could be used to elucidate the activation status of cells at the site of infection and confirm alterations in receptor expression on these cells. Ex vivo studies with CD11b+

179

cells (macrophages and neutrophils) from SDR animals, P. gingivalis bacteria or

LPS, and the antagonists and/or agonists could also confirm our hypotheses

about NFκB and cAMP. Some initial data were collected at a later time point (i.e.,

72h p.i.), and it would be interesting to expand on those data. Our studies

suggest that 72h pi may be a more appropriate time to collect tissue for histology

in order to detect differences in inflammation. This would help in elucidating the functional outcomes for the various treatments on the infection. Additionally, allowing the infection to continue for several days or weeks could allow the elucidation of the long-term contribution of these receptors to tissue healing and may reveal some of the bimodal actions of NPY (Wheway et al., 2007).

Regarding the allergic airway inflammation model, these were the first studies performed in the BALB/C mouse within our laboratory. Chapter 2 explored the origin of the SDR-induced increase in immune cells, and the phenotype of the cells that were released by stress and challenge. Only a preliminary characterization of these immature neutrophils was performed, and other studies should be done to understand how these cells contribute to the enhanced inflammation and delayed resolution. Ex vivo cell culture studies may be helpful in this regard. It must be determined if these cells are in fact insensitive to GCs, and if these cells display an enhancement of cytokine production or other indicators of neutrophil functions of host defense.

Furthermore, functional outcomes such as airway hyperresponsiveness or other

180

indicators of lung function should be explored in this strain of mouse to confirm

that they follow the same kinetics as previous studies (Bailey et al., 2009b)

4.8 Conclusions

In humans, stress can exacerbate inflammation following infection or

allergic challenge. The SDR model not only shows an inflammatory response to

stress, but it also shows immune cell and tissue-specific GC insensitivity that is

associated with many of these inflammatory diseases and conditions. Data also

support that this inflammation and mobilization of immune cells can have an

effect on indicators of mental health such as anxiety-like behaviors (Wohleb et

al., 2011; Hanke et al., 2012; Wohleb et al., 2013). This is likely relevant for the human condition as well. Thus, the SDR model provides an excellent platform in which to study the mechanisms of stress-exacerbated inflammation and GC insensitivity. The studies in this dissertation not only confirm and extend previous findings of SDR-induced immunoenhancement during infection and allergic airway inflammation, but also have provided additional cellular and soluble mediators that may make a significant contribution to the immunoenhancement.

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