Immunosenescence and Exercise-Mediated Modulation of the Innate Immune Response to Influenza Infection in Mice Shibani Naik Iowa State University

Iowa State University Capstones, Theses and Graduate Theses and Dissertations Dissertations

2013 Immunosenescence and exercise-mediated modulation of the innate immune response to Influenza infection in mice Shibani Naik Iowa State University

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Immunosenescence and exercise-mediated modulation of the innate immune response to Influenza infection in mice

Shibani Naik

A dissertation submitted to the graduate faculty

in partial fulfillment of the requirements for the degree of

DOCTOR OF PHILOSOPHY

Major: Immunobiology

Program of Study Committee: Marian Kohut, Major Professor Mark Ackermann Joan Cunnick Peter Nara Daniel Nettleton

Iowa State University Ames, Iowa 2013

TABLE OF CONTENTS

ABSTRACT iv

CHAPTER 1. GENERAL INTRODUCTION Introduction to the Dissertation 01 Literature Review: Influenza viral infection 01 Immune response to influenza infection 08 Immunosenescence 25 Exercise and the Immune System 37

CHAPTER 2. AGE IMPAIRS INNATE IMMUNE RESPONSE TO INFLUENZA INFECTION IN MICE. Abstract 40 Introduction 41 Materials and Methods 44 Results 47 Discussion 53 Figures 57 References 86

CHAPTER 3. MODERATE EXERCISE REDUCES VIRAL LOAD AND ALTERS INNATE IMMUNE RESPONSE TO INFLUENZA INFECTION IN AGED MICE. Abstract 90 Introduction 91 Materials and Methods 94 Results 99 Discussion 100 Figures 104 References 119

iii

CHAPTER 4. ACUTE EXERCISE INDUCES A STRESS RESPONSE IN LUNGS OF MICE. Abstract 124 Introduction 125 Materials and Methods 127 Results 129 Discussion 132 Figures 136 References 149

CHAPTER 5. CONCLUSIONS FOR THE DISSERTATION 152 References 156

REFERENCES FOR THE DISSERTATION 158

APPENDIX 177

ACKNOWLEDGEMENTS 186

ABSTRACT

Influenza virus is a negative sense, single stranded RNA virus that can cause severe respiratory tract infections in humans (along with other host animals such as horses, swine and poultry). Certain populations such as very young children, aged individuals, pregnant women and immunosuppressed individuals are more susceptible to influenza infections. One reason for the increased susceptibility to infection in the aged is a decreased efficacy of the seasonal influenza vaccine. As this particular section of our population continues to increase worldwide, research to improve vaccine efficacy is expanding along with efforts to identify lifestyle changes and interventions that can improve the immune response to vaccination. For these purposes, it is important to understand the mechanism by which age affects the immune response. Multiple age- related defects in T-cell or B-cell response to influenza infection have been well documented, but the impact of age on innate host defense to influenza is not well-characterized. Defects of the early innate host antiviral pathways have not been studied in depth and could impact early host defense as well as appropriate activation of adaptive immunity. The aim of the study conducted in chapter 2 was to identify age-associated alterations of innate recognition/response to influenza virus. The results identified an impairment of innate defense proteins and Toll Like Receptor signaling molecules in lungs of healthy old mice compared to young mice. The study also confirmed the presence of a chronic low level inflammation in the lungs usually systemically associated with aging. Mice infected with influenza virus elicited an impaired and possibly delayed anti-viral response to the virus.

It has been suggested that exercise can modulate the immune response to various respiratory pathogens. Physical activity may be beneficial for the immune response to pathogens v and infections in aged immune systems by decreasing morbidity and mortality. In chapter 3, we studied the potential impact of exercise on innate immune pathogen recognition and anti-viral responses. We used a model of chronic, regular moderate exercise in comparison to no exercise to assess alterations in the immune response to influenza virus infection. An exercise-associated reduction of lung viral load was observed in aged exercised-treated mice that were infected with influenza virus as compared to aged non-exercised mice. The results from this chapter indicated that early host innate defenses were altered by exercise training and may lead to the decreased viral load early during the course of influenza infection.

In chapter 4, the acute effects of a single session of exercise were studied in lungs of young mice. This was done in order to identify an effect of exercise on the activation of stress or host defense pathways given that the response of lung tissue to exercise is not well known, as compared to the effect of exercise on other tissues such as cardiac or skeletal muscle. Activation of stress response or altered cellular defense pathways and immune cell populations could affect the lung response to a pathogen such as influenza virus. In our results we discovered that acute exercise resulted in heat shock protein response as well as activation of several genes associated with regulation of inflammation. The effects of chronic exercise on the same stress response was also studied, resulting in a down-regulation of heat shock proteins, and no change in expression of genes associated with apoptosis or inflammation. Exercise training may cause a shift of CD45 positive leukocytes from the BAL into the lungs as the CD45+ population decreased in the BAL, but increased in the lung. Taken together, these changes suggest that exercise training may promote an anti-inflammatory environment in the lung. We speculate that exercise training may cause the lung tissue to adapt to stress and downregulate the heat shock response and any inflammation caused due to exercise. A shift in immune cells from BALF to lungs may explain vi our previous findings of reduced viral titer and decreased inflammation with influenza infection in exercise trained mice.

CHAPTER 1

GENERAL INTRODUCTION

Introduction to the dissertation

Organization of the Dissertation

This dissertation contains the experimental data and results obtained by the author during her Ph.D. study under the supervision of her major professor Dr. Marian L. Kohut at Iowa State

University, Immunobiology Interdepartmental Program.

The document contains manuscripts that are being prepared for submission to peer- reviewed journals. The dissertation contains a total of five chapters including a general introduction, three research papers, and a general conclusion that discusses the overall findings from the dissertation, followed by acknowledgements. The figures are provided directly following each chapter, followed by the references.

The General Introduction (Chapter I) to the dissertation begins with briefly the background information on the lifecycle of influenza A viruses and the host immune response to the virus. This is followed by the current status of knowledge and literature review on aging immunology research and exercise immunology. Chapter 2 focuses primarily on aging and the innate immune response, while chapters 3 and 4 focus on exercise immunology in the old and the young respectively. This is followed by the conclusions and summary of the findings of the dissertation, presented in chapter 5. The references that are used in the Introduction and literature review are provided, followed by the acknowledgements at the end.

Influenza virus Infection

The influenza virus is part of the Orthomyxoviridae family of viruses. These are negative sense, single stranded RNA viruses and include the thogotovirus and isavirus, along with the 2 three genera of influenza viruses, types A, B and C. Influenza A viruses are the causative agent of most severe respiratory tract infections. The symptoms of influenza viral infection may include fever, chills, cough, sore throat, runny or stuffy nose, pronounced fatigue, and less often nausea, vomiting and/or diarrhea. Some infected people may have no symptoms but may shed virus for up to a week. Severe cases of infection may require hospitalization and can be fatal, primarily because of damage caused by the immune response in the lung microenvironment.

Influenza B viruses cause the same spectrum of disease as influenza A. However, influenza B viruses do not cause pandemics, possibly because of the limited hosts (humans and seals).

Influenza C virus causes mild upper respiratory tract illness, and nearly all adults have been infected with influenza C virus (217).

Vaccines for influenza infection are available and contain two strains of Influenza A and one Influenza B strain. There are two types of influenza vaccine – the trivalent inactivated vaccine containing killed virus, and the live, attenuated intranasal influenza vaccine. Because of the high rate of mutation of the virus, the strains used in the vaccine are changed every year, based on to the World Health Organization’s prediction for the year’s prevalent strains. For example, the vaccine for the 2012-13 influenza season contain an A/California/7/2009 (H1N1)-like virus; an

A/Victoria /361/2011 (H3N2)-like virus; a B/Wisconsin /1/2010-like virus (52).

Structure of Influenza A virus

The influenza virion is a roughly spherical, enveloped virus with glycoprotein spikes embedded into the lipid membrane, known as HA (hemagglutinin) and NA (neuraminidase) in a ratio of approximately four to one. These proteins determine the subtype of influenza virus (168).

There are currently 16 known HA subtypes (56) and 9 NA subtypes. Also embedded in the lipid 3 membrane is the M2 protein, with an M2: HA ratio of one M2 channel per 10 1-10 2 HA molecules (247). Beneath the lipid membrane is a viral protein called M1, or matrix protein. The genome of the influenza A virus contains segmented, single-stranded RNA of negative polarity.

The eight RNA segments code for the viral proteins PB1, PB2, PA, HA, NA and NP proteins

(168). The interior of the virion also contains another protein called NS2 or NEP (viral nuclear export protein). The single stranded RNAs are associated with multiple monomers of nucleoprotein (NP) and a single copy of the polymerase which is a heterotrimer composed of the

PB1, PB2 and PA subunits. This whole unit is called a ribonucleoprotein (RNP) particle. Such

RNPs are independent molecular machines responsible for transcription and replication of each virus gene. The M1 protein forms a layer to separate the RNP (Ribonucleoprotein) from the viral membrane (168). This protein, which forms a shell, gives strength and rigidity to the lipid envelope and may be required for viral budding (72), though some studies have shown otherwise

(27). The M2 protein is the target of the antiviral adamantanes – amantadine and rimantadine.

The NA protein is the target of the antiviral drugs zanamivir (brand name Relenza) and oseltamivir (brand name Tamiflu) (206).

Life Cycle of influenza A virus

Influenza Virus Attachment to Cells:

Influenza viruses recognize N-acetylneuraminic (sialic) acid on the host cell surface. The

HA spikes on the surface of influenza virus recognize and bind to sialic acid moieties on the cell surface. The virus HA have a preferential specificity for either α (2,3) or α (2,6) linkages (168).

This preference is governed by amino acid sequence in the pocket region of the HA molecule

(231). In human tracheal epithelial cells, α (2,6) linkages predominate, while α (2,3) linkages are more common in duck gut epithelium. Epithelial cells of the pig trachea produce both α (2,3) and 4

α (2,6) linked sialic acids. This is believed to be the reason pigs can be infected with both avian and human influenza virus strains and serve as a ‘mixing vessel’ for the emergence of new viruses (168).

Influenza Virus Entry:

After the virion attaches to sialic-acid containing receptors at the cell surface, the virus- receptor complex is taken into cells by endocytosis, more specifically clathrin-mediated endocytic pathway. This form of entry is characterized first by the congregation of several HA proteins interacting with glycoproteins, followed by the formation of clathrin-coated pits. Some studies have also suggested other (clathrin independent) routes of entry such as caveolin- dependent and -independent endocytosis (163, 198). It is common in all modes of entry for the virus to be internalized within a vesicle that eventually uncoats and fuses with another more acidic vesicle forming an endosomal compartment (121). The pH in the endosome drops and this triggers a conformational change in the HA, exposing a fusion peptide. This peptide functions to merge the viral envelope with the endosomal membrane, thus creating an open pore for the release of viral RNPs into the cytoplasm of the host cell. Simultaneously, the M2 ion channel transports hydrogen ions from the endosome into the virus particle. This causes internal acidification of the influenza virion and disrupts internal protein-protein interactions, allowing viral RNPs to be released from the viral matrix into the cellular cytoplasm (192).

Influenza Virus Replication:

The RNPs are transported to the host cell nucleus through nuclear pores via viral proteins’ nuclear localization signals (NLSs). Influenza virus requires the use of the nuclear machinery of the host for replication to occur. Replication and transcription of viral RNA is thought to occur simultaneously within the host nucleus (91). The viral RNA dependent RNA 5 polymerase synthesizes two kinds of positive strand RNA from the viral negative sense RNA – a viral mRNA template for viral protein synthesis (using the host’s translation machinery) and a cRNA or complimentary RNA intermediate which will eventually form viral RNA for progeny viruses.

A process called cap snatching initiates the transcription process of influenza viral RNA

(175). In this process, PB2 binds to the cap of host mRNA (53, 79) and an endonuclease encoded by the PA subunit cleaves the host mRNA after the first 10 to 13 nucleotides (40). This fragment is used as a primer for transcription. Transcription is terminated when a string of 5 – 7 uridines

(U-track) are encountered and a polyadenylated (poly-A) tail is added to the viral mRNA (178).

The newly synthesized viral mRNA is exported from the nucleus into the cytosol by the M1 and

NEP proteins (32).

Replication of the viral RNA to form cRNA does not involve cap snatching or a poly-A tail addition and is a primer-independent process. Replication is carried out by the same polymerase heterotrimer and the resulting cRNA are full-length copies of the viral RNA segments, associated with NP protein. The mechanism for the regulation of replication is not yet completely understood (28).

Viral proteins are thought to be synthesized in an early phase and late phase, corresponding to two phases of mRNA synthesis (193). During the early or first phase of protein production, all eight genome segments are transcribed in equal amounts by the host cells leading to an equal level of production of all of the viral proteins encoded in those segments. During the early second phase of transcription the NS1 and NP proteins are selectively produced, followed by a late phase in which NS1 production is reduced while HA, NA and M1 proteins begin to be up-regulated. The M1 and NEP proteins are associated with translocation of vRNPs and 6 packaging of the viral components into a newly synthesized virion. Membrane bound proteins such as HA, NA and M2 are transported to the cell surface after post-translational modifications.

Influenza Virus Release:

Influenza virus utilizes lipid raft domains in the plasma membrane of infected cells as sites of virus assembly and budding. The HA and NA proteins assemble at the lipid rafts, and the difference in protein concentrations in the lipid raft induces a curvature on the outside of the host cell leading to bud formation and subsequently the release of a newly formed virion from the cell surface (185). Viral HA is cleaved into two proteins called HA1 and HA2 after the newly synthesized virions are released from cells. The protease required to cleave the HA protein is present in the human respiratory tract and restricts the replication of influenza virus to that location.

Antigenic Drift and antigenic shift

Antigenic drift is the gradual evolution of viral strains due to frequent subtle mutations involving point mutations within antibody-binding sites in the HA protein, the NA protein or both. Most of these mutations do not affect protein conformation but some mutations cause changes to the viral proteins, altering the binding to host antibodies. Consequently, infectious viruses can no longer be inhibited effectively by host antibodies raised to previously circulating strains, allowing the virus to spread more rapidly among the population.

Antigenic shift occurs when two different strains of virus infect one host animal. It is possible that when the cell is infected with both strains, the progeny virus may inherit RNA from both parent strains and would be called a reassortant. This progeny virus would display surface proteins from both strains and the resulting strain could be completely novel for some host populations, resulting in high infectivity and/or pandemics. Antigenic shift is only seen in 7 influenza A viruses, and usually results from the replacement of HA, and less frequently NA subtypes with novel ones. Because of antigenic drift and seasonal variability, it is important to monitor the circulating strain of influenza and develop vaccinations to those strains in a timely manner. Monitoring the circulating strains also helps in screening for viral reassortment due to antigenic shift (23, 225).

Immune Response to Influenza Infection

The epithelial cells of the lung act as a physical and immunological barrier to infection.

The alveolar epithelium consists of two main populations: alveolar type I (ATI) and type II

(ATII) epithelial cells. The ATI cells constitute roughly 10% of the alveolar population and are responsible for most of the gas exchange in the alveoli. The ATII population provides approximately 5% of the alveolar surface and provides protection for the alveoli and act as stem cells for ATII and ATI cells. Other cell types present are the surfactant producing Clara cells, mucus producing goblet cells, sensory neuro-epithelial cells, and basal cells that act as progenitors for other select cell types (190). The airway surface liquid interface consists of two layers, a mucus layer and a periciliary liquid layer, also sometimes referred to as “sol” layer. The mucus layer is a network of polymers that consists of high molecular weight, heavily glycosylated macromolecules, products of at least two distinct genes ( MUC5AC and MUC5B ).

The liquid layer is a low-viscosity solution in which cilia can beat rapidly and protects the epithelial cell surface from the overlying viscous mucus layer (110).The cilia of the respiratory epithelium beat in concert creating the mucociliary escalator. This system effectively moves secreted mucus containing trapped foreign particles toward the laryngopharynx, for either expectoration or swallowing to the stomach where the acidic pH helps to neutralize foreign material and micro-organisms. 8

The air liquid interface also contains many proteins, some of them anti-microbial peptides such as defensins, lactoferrin, and lysozyme. The airway epithelial cells contain certain

Pattern Recognition Receptors (PRRs) that recognize conserved sequences of pathogens, which are called Pathogen Associated Molecular Patterns (PAMPs). The main cell-associated PRRs activated by influenza infection are Toll-like Receptors (TLRs), NOD-like receptors, RIG-I and

MDA-5 (230). Some fluid-phase molecules such as collectins and pentraxins also act as PRRs associated with the respiratory system.

Defensins:

Defensins are small cationic microbicidal substances secreted into the epithelial lining fluid by neutrophils and Paneth cells ( α-defensins), or keratinocytes and epithelial cells ( β- defensins). They act as chemokines to recruit dendritic cells and T cells. There are 10 known human defensins: six α-defensins (HADs) and four β-defensins (HBDs). HADs have inflammatory properties such as inducing the release of histamine, chemokine induction through

NF-κB binding, and direct toxicity to alveolar epithelial cells. HBDs are thought to have mainly microbicidal function, although they recruit dendritic cells and memory T cells through interaction with cc chemokine receptor-6 (246).

Collectins:

Collectins, or collagen-binding lectins, are members of the C-type lectin superfamily, mainly SP-A, SP-D, and MBL. SP-A is produced by alveolar type II cells and Clara cells within the alveolar epithelium. SP-A binds to organisms that enter the pulmonary tree and either enhances their phagocytosis by alveolar macrophages or enhances their permeability. SP-A is a

Ca+2 independent γ inhibitor, binding to viral HA through the sialic acid residues present on the

SP-A molecule, blocking the receptor binding site on the virus. SP-D modulates cytokine 9 production and inflammatory responses, enhances opsonization and clearance of virus during viral infection. SP-D is a classic β inhibitor, agglutinating influenza A virus and neutralizing the virus by attaching to oligosaccharides on the viral envelope proteins (HA and NA) through its lectin domains in a Ca+2 dependent manner (132). Because of this property, the less glycosylated influenza viruses, such as the H1N1 virus used in our study (A/PR/8/34 H1N1) are less susceptible to inhibition by SP-D (84). MBL is the third major member of the pulmonary collectins, and functions by activating the complement system through C3b. MBL binds to the receptor calreticulin leading to an increase in monocyte activity, stimulation of the oxidative burst, and enhanced endothelial phagocytosis of pathogens (227).

Pentraxins:

Pentraxin 3 (PTX3), a long pentraxin, is constitutively stored in neutrophil granules and also induced in response to TNF-α and TLR agonists such as LPS. PTX3 can interact with a number of pathogens, including some strains of influenza virus, modulate the complement activity by binding C1q and can amplify the inflammatory response (151). Human and murine

PTX3 bind to influenza virus and act as a γ inhibitor, binding to viral HA through sialylated ligands on its surface. PTX3 also binds to infected cells, potentially leading to destruction before release of virions. A study has shown that absence of PTX3 aggravates infection and treatment with PTX3 reduces the viral load (181). However, it was recently reported that H1N1 influenza

A virus (including A/PR/8/34) were resistant to antiviral activity of PTX3, though it is produced and expressed upon viral infection regardless of strain resistance or susceptibility (103).

Pathogen Recognition Receptors (PRR):

RIG-I and MDA-5: 10

Retinoic acid–inducible gene I (RIG-I) is a cytoplasmic protein that was identified as participating in the recognition of virus nucleic acid inside the cell (126, 245). It recognizes the

5’ phosphorylated end of uncapped viral RNA and thus has the capability of discriminating between self and non-self RNA (93, 173). RIG-I has a helicase domain that is required for interaction with dsRNA. It contains two caspase-recruiting domains (CARD) at the N-terminus that interact with other CARD-containing adaptor proteins and are responsible for activating downstream signaling leading to IRF3 and NF- B. The C-terminal region contains a repressor domain which inhibits downstream signaling (187).

Melanoma differentiation-associated gene 5 (MDA-5; also called Helicard) is structurally related to RIG-I in that it also contains two CARD-like regions, a helicase domain, and a C- terminal region similar to the repressor domain of RIG-I. MDA-5 is also involved in viral recognition (105, 203). The CARD domains on RIG-I and MDA-5 recruit a mitochondria- associated protein called IPS-1 (also called MAVS, Cardif or VISA). This leads to activation of

NF κB, IRF3 and IRF7, and consequently inflammatory cytokines and type I IFNs (106, 107).

Toll-like Receptors:

Toll-like receptors (TLRs) comprise a family of proteins that recognize pathogen- associated molecular patterns (PAMPs) and initiates host innate immune responses. TLRs contain extracellular leucine-rich repeats that recognize and bind to their respective PAMPs, a transmembrane domain, and an intracellular domain similar to that of IL-1 receptor known as the

Toll/IL-1 receptor (TIR) domain. The intracellular domains interact with adaptor proteins and activate downstream signaling pathways. Currently, the TLR family consists of more than 13 members in mammals, each detecting different PAMPs. 10 TLRs have been identified in humans and 12 in mice. They are constitutively present on many nucleated cells and can be up-regulated 11 in response to pathogens and/or cytokines (164). TLR3, TLR7, TLR8 and TLR9 recognize viral genomic material. TLR3, TLR7 and TLR9 are mainly present on Endoplasmic Reticulum (ER) membrane and are recruited to endolysosomes upon stimulation by their ligands. TLR3 recognizes double stranded RNA in the endolysosome, TLR7 and TLR8 recognize uridine rich sequences of single stranded RNA(139), and TLR 9 senses unmethylated DNA with CpG motifs.

TLR7 and TLR9 are highly expressed on plasmacytoid dendritic cells (pDC), which produce large quantities of type I Interferons (IFN). TLR3 is expressed by conventional dendritic cells

(cDCs) and macrophages as well as non-immune cells including fibroblasts and epithelial cells.

TLR3 is localized on intracellular vesicles in cDCs, while it is localized to the cell surface as well as intracellular vesicles in fibroblasts and epithelial cells.

All TLRs (except TLR3) signal through MyD88 which activates other signaling proteins that ultimately phosphorylate an NF-κB inhibitory protein. This frees the NF-κB to translocate to the nucleus and activate expression of pro-inflammatory cytokine genes. The MyD88 pathway also activates the MAP kinase cascade, which leads to formation of transcription factor complex

AP-1 that also targets cytokine genes. TLR7 and TLR9 are selectively expressed by pDCs. They signal via the MyD88 protein and this leads to phosphorylation of IRF7, which translocates to the nucleus and activates genes encoding type I IFNs (89, 94). In cDCs, IRF1 is activated resulting in IFN-β gene expression.

TLR3 recruits an adapter protein, TRIF, and activates IRF3, and NF κB. IRF7 is also activated via the TBK1 and IKKi complex. IRF3 is involved in IFN β and IFN α4 induction.

These subtypes of interferon signal via the type I interferon receptor and activate a transcriptional complex known as ISGF3 which consists of transcriptional activators STAT1 and

STAT2, and IRF9. This pathway results in the expression of the IFN inducible genes or IFN 12 stimulated genes (ISGs) such as IRF7, Protein Kinase R and others, required for antiviral responses. TBK1 and IKKi phosphorylate IRF7 in a manner similar to IRF3, inducing type I

IFNs as well.

Type I IFN response to influenza virus:

Interferons are cytokines secreted by host cells in response to viral pathogens including influenza virus. They are mainly classified into three types - Interferon type I, II and III. Type I

IFNs bind to a specific cell surface receptor complex known as the IFN α receptor (IFNAR) that consists of IFNAR1 and IFNAR2 chains. The type I interferons present in humans are IFN α which has 13 subtypes, IFN β and IFN ω. Interferon type II, IFN γ which has 3 subtypes binds to

IFN-γ receptor (IFNGR) that consists of IFNGR1 and IFNGR2 chains. Type III Interferons were recently recognized as IFN λ (or IL28/29) and binds to IFN λ receptor(IFNLR) consisting of

IFNLR1 and IL10R2 chains (10).

As described above, PRRs activate downstream pathways that stimulate type I IFN (IFN α and IFN β) production. In response to influenza virus, type I IFNs are secreted from pDCs, alveolar macrophages, and infected epithelial cells (99) although recent studies show that ATII cells do not produce IFN α but do produce IFN β and IFN λ (233). Type I IFNs up-regulate the transcription of many IFN-inducible genes or IFN stimulated genes (ISGs). ISGs include transcription factors like IRF3 and STAT1/2 enabling an amplification loop. Other ISGs are proteins that influence protein synthesis, growth arrest, and apoptosis to create an antiviral state

(67). Type I IFNs also function to enhance dendritic cell (DC) maturation, natural killer (NK) cell activation, antibody production, and differentiation of virus-specific cytotoxic T lymphocytes (CTL). The IFN type I receptor is expressed by the infected IFN-producing cells as well as on uninfected neighboring cells, rendering an anti-viral state. The receptor activates the 13

JAK/STAT pathway which in turn induces the transcription of several ISGs, some of which are discussed below.

Mx:

The orthomyxovirus resistance gene or Mx was the first ISG found to restrict influenza virus replication (80). Mx can be induced by type I IFN α/β and type III IFN λ. Both mouse Mx1 and the human homologue MxA inhibit influenza virus replication (77, 209). MxA in humans has shown anti-viral properties against both nuclear and cytoplasmic viruses. MxA is a GTPase expressed by various cell types in peripheral tissue, for example hepatocytes, endothelial cells, peripheral blood mononuclear cells (PBMCs), pDCs and myeloid cells. MxA has a central interacting domain and a leucine zipper at the C terminal which recognizes viral nucleocapsid- like structures. It functions by oligomerizing around the ribonucleocapsids to form rings around the viral RNA and blocking viral replication (232). Most of the laboratory strains of mice lack a functional Mx1 and therefore are highly susceptible to influenza virus infection (208).

Protein Kinase R (PKR):

PKR is an IFN inducible protein kinase that becomes activated upon binding to dsRNA.

Most of the antiviral activity of PKR is due to phosphorylation of eiF2 α, which results in a general translational block, limiting viral replication (174).

Oligoadenylate synthetase (OAS):

OAS is the first component of the OAS/RNAseL antiviral system. Similar to PKR, OAS is IFN inducible but requires binding to dsRNA for activation of its enzymatic activity. Once activated, OAS generates 2 ′–5′ oligoadenylates that act as a co-factor for a latent cytoplasmic

RNAse, RNAse L. Activated RNAse L cleaves viral and cellular RNA stopping viral replication 14

(26). In addition, it has also been shown that the cleaved products of RNAse L can activate RIG-

I, and therefore serve as a positive feed-back to enhance IFN production (140).

IFN stimulated gene 15 (ISG15):

ISG15 is a 15kDa homolog of ubiquitin. While the mechanism is still unclear, it is thought that ISGylation does not cause degradation, but has an activating effect on its target proteins, such as JAK1, STAT1, RIG-I, MxA, PKR or RNase L. For example, ISG15 prevents virus mediated degradation of IRF3. It may also have extracellular functions as a cytokine to modulate the immune response (131, 248).

Viperin:

Viperin is an IFN inducible protein that localizes in the ER, where it was found to interact with and inhibit farnesyl diphosphate synthase, an enzyme required for isoprenoid biosynthesis. This inhibition leads to changes in membrane fluidity and membrane microdomains, which in turn affect the ability of influenza virus to efficiently bud from infected cells, then restricting viral replication (235).

Tetherin or BST2:

Tetherin (also known as BST2) also restricts viral budding, by retaining newly assembled virions attached to the plasma membrane (127).

IFN inducible transmembrane proteins (IFITMs):

In contrast to the budding inhibitors viperin and tetherin, IFITMs are interferon inducible genes that restrict viral entry (19), possibly through the fusion activity of the HA protein which is essential for entry (134). dsRNA specific adenosine deaminase (ADAR1): 15

ADAR1 is another ISG that has anti-viral activity. It is a site specific protein that converts the adenosine in RNA to inosine, destabilizing the dsRNA (224).

Recruitment of immune cells during influenza infection

Innate cells are recruited to the lungs in response to chemokines, and are necessary to control the early replication and spread of influenza A virus infection in the lungs. Alveolar macrophages are the primary phagocytes found in the alveoli and can be infected by influenza virus. Viral infection activates the cells and converts them into highly phagocytic cells that produce inflammatory cytokines, including IL-6 and TNF α (234). Inflammatory monocytes are recuited to the lungs via CCL2, which then differentiate into monocyte derived dendritic cells

(DC) and inflammatory macrophages. NK cells are recruited to the site of viral infection via

MIP-1α and MIP-1β and produce large amounts of cytokines such as IFNγ, TNF α, and MIP-1α.

NK cells can recognize hemagglutinin protein of the influenza virus via the NKp46 molecule

(141). They interact with influenza infected DCs via theNKG2D and NKp46 receptors (44), and this interaction along with IL12 leads to activation and increased IFN γ production of NK cells.

NK cells have potent cytotoxic activity that is dependent on IFN α/β (183). IL12-activated NK cells have the ability to activate DC by inducing maturation and via IFN α and TNF production

(69). Neutrophils will also migrate to the site of infection, may inhibit viral replication, and engulf cells opsonized with antibody or even with lectins (64, 83). Once these cells are engulfed by the neutrophil, the neutrophil may carry out a granulocytic, anti-microbial activity leading to further containment of the virus (216).

DCs play a major role in bridging the adaptive and innate immune response to influenza.

DCs are located throughout the respiratory tract and constantly survey for invading pathogens or foreign material. pDCs are recruited into the lung via the chemoattractant properties of CXCL10 16

(31) and produce massive amounts of IFN α (75), discussed in previous sections of this review.

The cDC also resides in the lung in an immature state, and will migrate into the lung environment in response to CXCL12 after infection occurs (31). Once cDCs have sensed a pathogen (via PRRs), they will uptake that antigen, process it and begin to migrate towards a draining lymph node, and simultaneously take on a mature phenotype. This mature phenotype is characterized by the increased expression of MHC-class I and II molecules, and the costimulatory molecules CD80 and CD86 which are necessary for the activation of the adaptive immune response.

The autophagy pathway

This is a highly conserved cellular pathway that is used by the cell to degrade cytosolic organelles and proteins. Macroautophagy, the most studied pathway of autophagy involves formation of an autophagosome, a double membrane structure, around cytosolic contents. The autophagosome fuses with a lysosome to form the autolysosome that degrades the targeted proteins or organelles. The primary function of this pathway is to recycle the nutrients and energy within the cell. It also prevents the accumulation of and the resulting damage caused by aggregated proteins, and is speculated to improve genetic stability and mitochondrial quality control.

Autophagy has been shown to mediate the delivery of antigens and enhance antigen presentation as demonstrated by enhancement of BCG vaccine antigen presentation by APCs.

MHC II antigen presentation was enhanced, improving Th1 mediated protection (97). It is also involved in the processing of endogenous antigens such as Epstein Barr viral antigens and selective targeting of influenza matrix protein and delivery to MHC II molecules.

Autophagosome formation occurs constitutively in pDCs and pDCs derived from Atg5-deficient 17 mice failed to produce IFN α after VSV infection (129). Autophagy may also contribute to innate immunity by reducing inflammation via decreasing necrosis and apoptosis, and inhibiting pro- inflammatory signaling via RIG-I like receptors and induction of inflammasomes (133, 186,

241). Several immune mediators such as PKR, CD40-CD40L interactions, IFN γ, TNF α, TLR4 and Th1 cells have the ability to stimulate autophagy (133). Studies have been conflicting on whether the proteins involved with autophagy are anti-viral (133, 213) or support viral replication (241).

Therefore, this process is up-regulated by infections and anti-viral responses and serves to facilitate antigen presentation and recognition by the cells and molecules of the immune response. It may also act to control some of the excessive or harmful effects of a robust response by reducing inflammation. Although the precise functions of this pathway are not yet completely understood, it is clear that it plays a role in the immune response to viral infections.

Adaptive immune response to influenza infection

The adaptive or acquired immune response consists of the humoral response (consisting mainly of antibodies) and the cell mediated response (via lymphocytes). Important characteristics of the adaptive immune response are the ability of the adaptive system to differentiate between

‘self’ and ‘non-self’, and generate a specific response to a given pathogen. The cells of the acquired immune system are T and B lymphocytes. B cells produce antibodies and play a large role in the humoral immune response, whereas T cells are involved in cell-mediated immune responses.

Extensive communication between the innate and adaptive systems is carried out with the help of cytokines that bind to cells, and via cell- cell interactions for example between DC and lymphocytes. Antigen presenting cells (APCs) such as cDC’s acquire cytosolic viral antigens 18 through the MHC I molecule, and extracellular viral antigen through phagocytosis (also called cross presentation). The extracellular antigens are presented on MHC II molecules in a process called antigen presentation. Upon stimulation with microbial products, inflammatory cytokines or CD40 ligation, DCs start to mature and migrate to the draining lymph nodes. Maturation of

DCs is associated with phenotypic changes including down-regulation of phagocytic capacity, up-regulation of costimulatory molecules, MHC and secretion of cytokines. This process transforms them into fully functional APCs capable of priming naïve T cells through presentation of antigen on MHC molecules.

The MHC I and MHC II molecules are recognized by the receptors on CD8+ T cells and

CD4+ T helper (Th) cells respectively. Recognition of antigens presented on MHC I of APCs by the T cell receptor, a second signal via costimulatory molecule CD80/86 on APCs interacting with CD28 on naïve T cells and cytokines such as IL2 are required to activate the T cell. The naïve CD8+ T cells that recognize influenza antigen and express CD28 then begin the process of clonal expansion. The effector CD8+ T cells or cytotoxic T lymphocytes (CTLs) return to the lung in a phenomenon called cellular homing, possibly via CD27 (90). They recognize influenza infected cells via their T cell receptor and kill those cells by producing IFN γ (type II IFN) and directed release of perforin and granzymes. IL-12 secreted by cDCs is essential for CTLs to produce IFN γ which activates other immune cells (for example increases phagocytic activity by macrophages) and drives activated B cells to produce highly specific anti-influenza antibody.

CTLs serve a cytotoxic function by producing perforin and granzymes specifically in response to influenza virus infected cells which express the influenza peptides and MHC I complex on their surface. The CTLs do require the help of Th cells, as reviewed next. 19

Naïve CD4+ T cells are activated in a similar way by T cell receptor ligation to antigen presented on MHC II of APCs and costimulation. However, they are not involved in cytolytic killing but play a vital role in activation of influenza-specific B cells. Until recently, it was thought that two types of effector CD4+ Th cell responses can be induced by a professional

APC, designated Th1 and Th2. However, recently many other subsets of Th cells have been discovered. Th cell subset development is dependent on the cytokines that the cell is exposed to and the transcription factors that are expressed in the cell. Each subset produces a different set of cytokines and have various functions in the body. For example, IL12(p70) and IL18 polarizes the

Th cell response towards T-bet expressing, IFN-γ and TNF secreting Th1 cells which have the ability to activate macrophages against intracellular pathogens. Similarly IL4, IL25, IL33 and thymic stromal lymphopoietin (TSLP) induce differentiation towards Th2 cells which express transcription factor GATA3 and produce mainly IL4, IL5, IL6 and IL10. Th2 cells activate B cells and mediate humoral immunity to extracellular parasites. Regulatory T cells (Tregs) are generated by stimulation with TGF-b in the absence of IL-6. More Th subsets have been discovered such as IL17-secreting Th17 cells, IL22-secreting Th22 cells, IL9-secreting Th9 cells and T follicular helper cells (Tfh) which can prime B cell antibody responses. Furthermore, studies have shown that Th cell lineages are not irreversible, but tend to be more changeable than previously believed (249). Generally, Th1 responses are more effective against intracellular pathogens such as influenza virus, while Th2 responses are more effective against extracellular bacteria, parasites including helminths and toxins. Influenza virus specific immunity relies on the activation of both CD8+ and CD4+ T cells, as CTLs are required to eliminate infected cells and

B cells stimulated by CD4+ T cells produce anti-influenza virus antibody necessary for the host to overcome this infection. 20

Naïve B cells express MHCII molecule and can present antigen. They are activated by helper T cells that respond to the same antigen and induce differentiation into antibody producing plasma cells which can produce high levels of antibody. IgA, IgG and IgM are all produced during primary infection. IgA and IgM are found predominantly in the infected mucosal tissue and IgG is prevelant in the serum. Secondary infection leads to antibody production of increased specificity, and all three antibody isotypes can be found in serum. IgM and IgG antibodies can be produced by Th cell dependent or independent routes, and are vital to the immune response against the influenza virus (128). Antibodies can neutralize viral infectivity by interfering with virion binding to receptors, blocking uptake into cells, preventing uncoating of the genomes in endosomes, or causing aggregation of virus particles.

Another characteristic of the acquired immune system is the formation of ‘memory’ T and B cells. When B cells and T cells are activated and undergo clonal expansion, some cells become memory cells. Upon interaction with a previously encountered antigen, the appropriate memory cells are selected and activated. In this manner, the second and subsequent exposures to an antigen produce a more efficient and faster immune response.

Original Antigenic Sin

The memory response also leads to a concept called ‘original antigenic sin’ described more than 50 years ago (59) that may influence immune response to influenza virus infection in young versus older populations. Influenza viruses evolve via antigenic drift, and less frequently via antigenic shift. Therefore, during the emergence of a new strain, the new virus may contain structural components from viruses that arose many years before in previous pandemics or just during the seasonal influenza cycle. For example, the 2009 H1N1 virus emerged and quickly it was shown that this new virus shared some homology with past H1N1 viruses (204). It was 21 expected that upon exposure to this variant strain, the immune system responds by activating both memory cells that recognize shared epitopes on the virus, and naïve cells that recognize novel epitopes. The concept of ‘original antigenic sin’ suggests that regardless of the novel epitopes, an individual (usually older individuals who have memory cells specific for the shared epitopes) will respond by preferentially activating memory cells. It would usually be the first influenza virus strain that they encountered in life to which they developed a dominant anti- influenza antibody response. However, this suggests that the immunity that is generated might be targeted to sub-dominant epitopes, and may ignore the dominant epitopes which would be more advantageous for the host to recognize and form immunity against (108). This is the primary problem highlighted by the concept of ‘original antigen sin’ in the aged host, and it shows the importance of development of vaccination strategies that lead to memory T and B cell responses which will target conserved structural components among influenza virus strains (157, 223).

Balancing protective immunity between T cell memory and sufficient antibody would lead to better protection in the aged host as well as the young.

Lung repair and healing

Severe influenza infection can cause considerable pathology and injury to the lungs and respiratory tract. The lungs undergo a repair and healing process enabled by localized progenitor cells as well as newly recruited circulating progenitor cells which proliferate, migrate and undergo phenotypic differentiation to reestablish epithelial integrity and function. In the airways, non-ciliated epithelial Clara cells are also capable of functioning as facultative progenitor cells following injury. At the alveolar level, the ATII cells act as progenitor cell to replenish both AT I and AT II cells. Growth factors, cytokines and matrix metalloproteinases (MMPs) are released during repair. Growth factors Hepatocyte growth factor (HGF) and keratinocyte growth factor 22

(KGF) stimulate the proliferation and migration of cells in the injured tissue (236). MMPs degrade cell-matrix interaction, enabling cell spreading and migration. Cytokines are also important in that they stimulate or decrease the migration of immune cells (macrophages, neutrophils, etc.) that are involved in the immune response as well as healing response (33).

Recently, innate lymphoid cells have been implicated in lung repair responses. These cells produce Th cell-associated cytokines but do not present T cell receptors or any other cell surface markers associated with immune cell lineages. They produce a protein called amphiregulin that may contribute to tissue repair after influenza infection (152)

Immunosenescence

The natural aging process causes a gradual decline in immunity, an increase in susceptibility to infectious diseases and greater incidence of chronic infections and diseases of inflammation in the elderly. This impairment in immunity is known as immunosenescence, and affects both the innate and the adaptive immune system. Many factors contribute to this and not all of them have been clearly elucidated. Numerous studies have shown immunosenescence in healthy aged individuals as well as in individuals in a diseased state. A significant consequence of this phenomenon is decreased vaccine efficacy in the elderly population. Thus, it is important to study immunosenescence and infections in the elderly. The next few sections will review the aging immune system and its effects on the adaptive and innate immunity to pathogenic stimulation.

Aging is associated with involution of the thymus, which begins during puberty in humans. The size of the naïve T cell pool depends on output from the thymus and not cell multiplication, so thymic involution reduces its contribution to the naïve T cell pool. The activated or memory T cell pool size can be increased through cell multiplication, so thymic 23 involution may not directly affect this. There is no significant decline in the total number of T cells in the peripheral T-cell pool, however there are considerable shifts in the ratios of both pools of cells, with an increase in the number of activated and memory T cells as well as exhausted T cells that are not as efficient in responding to stimuli as T cells from young subjects

(12). Also intrinsic defects in T cells have been suggested to contribute to skewed immune responses in aged subjects, which will be discussed later in this review. Therefore thymic involution may be a contributing factor to immunosenescence, but it is not the sole mechanism responsible for the impairments.

Inflammaging

The normal aging process causes a low grade of chronic systemic inflammation, sometimes called “inflammaging”. This was first suggested by Fagiolo et al (50) when they reported greater concentrations of inflammatory cytokines from PBMCs of aged people than young subjects. This may be caused by exposure to persistent antigens or low level of chronic infections. It is not yet clear whether this contributes to increased immunopathology in aged hosts upon infection. A production of acute phase proteins such as IL-6, TNF α and CRP in the plasma, and pro-inflammatory genes in liver, brain and other organs confirms the occurrence of inflammaging prior to infection (11, 82). The potential role of anti-inflammaging agents to promote longevity and healthy aging has also been speculated (58). Inflammaging in the lungs has been reported as well, with regard to T and B cells, T and B signaling molecules, macrophages and chemokine receptors. The increase in inflammation may link to changes in T cell signaling and/or function, though it has not been clarified yet (125).

Adaptive immunity and aging 24

Changes in the adaptive immune response with age have been well documented. Studies in this field started in the 1980s when a gradual decrease in mitogen-induced proliferative responses with increasing age was observed (156). After the initial observations, many groups have reported overall decreases in hematopoietic stem cell (HSC) tissue in the bone marrow of aged mice, along with decrease in T and B cell precursors (43). As mentioned above, thymic involution reduces the circulating naïve T cell pool. However it has been speculated that the repertoire of naïve T cells (and their T cell receptors) are more important in responding to infections rather than the number of naïve T cells, knowing that very few naïve T cells (20-200 antigen-specific T cells) are initially necessary to develop specific immunity to a particular pathogen. An age-associated dysfunction in the T cell repertoire has been reported compared to a broader repertoire available in a younger host (6, 242).

T regulatory cells (Tregs) serve an important regulatory function to the immune system upon infection, and are important in maintaining self-tolerance in the absence of infection (149,

188). Treg cells may also suppress the immune response to respiratory viral infections (177), and have been shown to suppress IFN γ production in Leishmania major infection, contributing to a chronic infectious state in elderly individuals infected with this pathogen (120). Studies have shown that Treg numbers accumulate in blood of aged human subjects and lymphoid tissue of aged mice. Increase in Tregs may contribute to recurrence of chronic infections, for example

Leishmania major (119), and suppress anti-tumor responses in aged mice. Th17 responses are also increased with age, with greater numbers of Th17 cells, and higher amounts of IL17 and IL6 produced by splenic CD4+ T cells from old mice when stimulated with anti- T cell antigen receptor antibodies (95). The presence of more Tregs is thought to utilize the IL2 that would otherwise inhibit expression of IL17, and so the increase in Tregs is also though to skew the 25 immune response towards a Th17 type (88, 95). Th17 cells have been implicated in age- associated autoimmunity (167) and Th17 cells could have a similar role in inducing the low-level chronic inflammatory condition associated with inflammaging.

A number of studies have elucidated the defects in CD8+T cell population with aging.

Naturally occurring contraction of the naïve T cell repertoire results in impaired CD8+T cell responses to known immunodominant epitopes and decline in heterosubtypic immunity (88,

242). Impaired cytotoxic killing by CD8+T cells was observed in aged mice in comparison to young mice after influenza virus infection. Aging also leads to a loss in CD28, which is the receptor for the costimulatory molecules CD80 and CD86 expressed on antigen presenting cells

(41). The reduction in CD8+ CD28+ T cells in aged hosts suggests that the intrinsic capability of these cells to respond to antigenic stimulation is at least partially impaired. T cells with memory phenotype (CD45+ RO in mice) are increased and constitute a greater portion of the T cell repertoire, leaving fewer naïve T cells to respond to novel pathogens.

Age-related defects in CD4+ T cells have also been well studied. As discussed before,

CD4+ T cells interact with APCs (mostly DCs) presenting antigens bound to MHCII molecules.

CD4+ T cell impairments with age begin with defects in cytoskeletal reorganization triggered by initial contact between TCR and peptide-bearing APC, contributing to defective activation of protein kinase-mediated signals in the first few minutes of the activation cascade (66). This defect then contributes to the well-documented reduced proliferation of CD4+ T cells from aged mice. Additionally, aged naïve CD4+ T cells have reduced ability to produce significant levels of

IL-2 upon TCR stimulation, which subsequently leads to the generation of poorly polarized Th subsets (87). As a consequence of reduced IL-2 production, CD4+ T cells from old mice may have reduced CD40L (CD154) expression, which is required in interactions between B and T 26 cells. This may lead to a poor activation of B cells and an inefficient B cell response. IL-2 is also important to induce IFN γ production by CD8+ T cells and a defect in IL2 could potentially affect the CD8+ T cell response as well. Naïve CD4+ T cells from aged subjects have also been shown to be less sensitive to IL12 and IL4 that may reduce

Th1 and Th2 or Th9 responses. They still maintain their ability to respond to TGF β and IL-23 which would induce the Th17 phenotype. A decrease in cytokine production by Th1 cells, as compared to Th2 cells, was noticed with an influenza vaccine challenge (143). Defects in CD4+

T cell functions, loss of T cell markers and co-stimulatory molecules CD40L (CD154) and CD28 in aged mice lead to defects in B cell expansion, differentiation and antibody production, affinity maturation and class switching (46, 61-63, 85, 86, 88). Upon transfer of CD4+ T cells from old

TCR transgenic hosts to young hosts, there was significantly reduced expansion and germinal center differentiation of the antigen-specific B cell population after immunization (46).

Therefore an impaired CD4+ cell population in the aged leads to a defect in the B cell response as well.

The generation of conventional B cells (or B2-B cells) from bone marrow precursors is impaired in old mice, and peripheral B cell percentages and numbers significantly decrease with age in humans. Naïve B cell numbers are reduced with age, and information on memory B cell numbers and percentages is still uncertain. Increased numbers of B cells with auto-reactive specificities and increased amounts of serum auto-antibodies have been reported in old mice. B1-

B cells may either accumulate or expand with age as a result of chronic stimulation by environmental antigens (60). The ability to make an optimal antibody response to exogenous antigens and vaccines declines with age in humans and animal models. The changes in the humoral immune response with age are both qualitative and quantitative. In particular, a 27 progressive decline in both the number and the size of germinal centers has been reported (46).

With advancing age, there is a decrease in serum concentrations of antigen-specific antibody, antibody specificity, affinity, and class switch recombination (CSR). CSR, the DNA recombination process required for the generation of switched antibodies, is initiated by activation-induced (cytidine) deaminase (AID). This enzyme causes deamination of cytidine residues in switch (S) regions, thus creating uracils, and the resulting mismatches are recognized by specific enzymes and excised, leading to DNA double strand breaks and rejoining at different regions of the chromosomes and production of different class of antibody. A decrease in expression of transcription factor E47 and AID in B cells also leads to poor class switch recombination, as demonstrated by in vitro studies which showed that the splenic B cells from old BALB/c mice were deficient in CSR and secondary Ig production (62, 63). The total number of CD19+ B cells, and mature human B cells decrease, whereas the number of late memory and exhausted memory B cells increased (61). This results in decreased antibody affinity maturation, switched memory B cells and plasmablasts upon immunization in the elderly. There are also diminished recirculating antibody-secreting plasma cells in the bone marrow (60).

Vaccinations in the elderly population

The impairment of the adaptive response results in a major problem, which is the impaired response to vaccinations in the elderly population. There are currently two types of vaccines, an injectable flu shot and a nasal spray. The flu shot consists of inactivated (killed) influenza virus, given intramuscularly and approved for use in higher doses for people 65 and older. The high dose vaccine contains 4 times the amount of antigen contained in regular flu shots (24). Current regular influenza vaccines contain 15 g of the hemagglutinin of A/H1N1,

A/H3N2, and B strains, respectively, and are administered to induce serum anti-hemagglutinin 28 antibody for prevention of subsequent infection and illness from natural influenza. The high dose vaccines were developed to meet the need for a higher efficiency vaccine for the elderly populations. The efficiency of the regular trivalent inactivated influenza vaccine responses in individuals above 65 years of age were reduced compared to young individuals (123). A large study performed in the Netherlands during the 1991-1992 influenza season reported that the effectiveness of the influenza vaccine decreased with increasing age groups (57% in people aged

60–69 years and 23% in volunteers aged ≥70 years) (74). New strategies to improve the response to vaccinations in the elderly are still being developed at present. A few recent studies used a platform that links viral epitopes to flagellin, a TLR 5 activator and this induced anti-influenza immunity in aged mice as well as aged people (130, 218). This makes it imperative to uncover the underlying mechanisms of the aging response to infections and vaccinations.

The live attenuated vaccine consists of the same three strains of live, attenuated virus and is given by an intranasal dose to people between the ages of 2 to 49 years of age (25).

Alterations in cells of the immune system.

Dendritic Cells

DCs are potent antigen-presenting cells that have the capacity to stimulate naïve T cells, and are thus called the link between adaptive and innate immunity. These cells are also affected by the aging process. DCs become more sensitive to self-antigens (e.g., human DNA) and increase activation markers (CD80 and CD86) enabling enhanced T cell activation against these self-antigens (5). An increase in basal levels of inflammatory factors like NF κB and cytokines without stimulation (thus contributing to inflammaging) and a decreased response of inflammatory cytokines such as TNF-α and IL6 to TLR stimulus demonstrates the impairment of the DC response with aging (169, 238). However there is still conflicting data on this topic and 29 reports on changes in DC numbers with age are also variable. The number of myeloid DCs

(mDCs), but not pDCs in human peripheral blood Dendritic Cells (PBDCs) declined with age in one study (37) whereas other groups noted a decline in pDCs, but not mDCs (3, 102, 197). In addition, a decrease in human Langerhans cell (LC) densities has been observed in the epidermis of the skin of aged subjects (76) and in aged mouse studies. Reduced expression of TLRs has also been suggested as a consequence of aging, demonstrated by reduced TLRs 1, 3 and 8 in cDCs and TLRs 7 and 9 in pDCs from aged individuals (102, 169). Also, defects in antigen capture by DCs, phagocytosis and pinocytosis have been suggested though this is still being investigated (2). Reduced migration of DCs to the lymph nodes and/or to the infected tissues may also contribute to age-associated immune dysfunction (4, 222). Defects in DCs can influence the adaptive immunity, especially T cell response to infections, as they are instrumental in activating these cells. This was suggested in a report where adoptive transfer of young DCs to old mice augmented the CD8+ T cell response (101).

Neutrophils and Macrophages

Neutrophils and macrophages are key components of the inflammatory response that shape immune responses and participate in the breakdown and repair of tissue. During influenza infection, they are the initial responders to be recruited to the lungs. The changes in neutrophils with age have not been completely clear so far. Neutrophils have been implicated in the pathogenesis of atherosclerosis, Alzheimer’s disease and cancer. Data on changes in number of circulating neutrophils have been inconsistent , though some data suggest an impairment in chemotaxis of human neutrophils and defects in the respiratory burst (39).

After leaving the BM and entering the blood, monocytes differentiate continuously into macrophages en route to peripheral tissues. Given the plasticity of macrophages in specific 30 tissues, it is not very surprising that age-dependent changes in macrophage function may occur in a tissue-specific manner (115). The number of macrophages in the elderly and young appears to be similar, but macrophages from aged populations have less MHC II gene expression.

Macrophages have been shown to have reduced phagocytic capability, delayed migration, impaired formation of reactive oxygen species, and formation of nitrogen intermediates important for antimicrobial activity (176). Chemokine/cytokine production and TLR expression on macrophages is also reduced with age. Some of these changes will be discussed later in this review.

NK cells

NK cells are defined by their ability to kill cancer cells and virally infected cells without prior sensitization. Two distinct populations of human NK cells can be identified based on the cell surface density of CD56. CD56bright NK cells are the primary source of NK cell-derived immune-regulatory cytokines such as IFN γ, TNF-β, granulocyte macrophage-colony-stimulating factor (GMCSF), IL10 and IL13. This subtype is rare in peripheral blood ( ∼5%) and more frequent in lymph nodes ( ∼95%). The majority of peripheral blood NK cells ( ∼95%) belong to the CD56dim NK subset, which produces low levels of NK-derived cytokines and potently mediates natural cytotoxicity. Changes in NK cell numbers are dependent on the NK subsets.

CD56 bright (cytokine producing) NK cell subset is reduced (30), whereas CD56 dim (cytotoxic) NK cells are increased with age (7, 18, 68). Increases in the expression of NK-related receptors, such as CD16, CD56, CD57, and CD94, on the T cells of elderly persons have been reported, coupled with a down-regulation of the inhibitory receptor KLRG1. This may be a compensatory adaptation, given that the overall T cell receptor diversity is decreased during aging. Changes in

NK cell cytotoxicity are still controversial. While some studies suggest a decrease, others studies 31 report no change in cytotoxicity (7, 78). In a study using ectromelia virus (murine equivalent of smallpox virus) infection in aged mice, defects in NK cell numbers and trafficking led to increased lethality and defective viral clearance. This defective migration was associated with reduced up-regulation of CD62L (also known as L-selectin), which is an adhesion molecule that allows attachment of cells to high endothelial venules. The defects in NK cells may have led to impaired CD8 T cell responses in the infected mice (51).

In summary, defects in innate cells such as DCs or NK cells of aged individuals have the potential to influence adaptive and memory responses to virus challenge and consequently effectiveness of vaccinations in the elderly.

Aging and the innate immune system

The innate system has three broad groups of receptors that alert the body to the presence of viral infections – Toll Like receptors (TLRs), RIG Like receptors (RLRs), and NOD Like receptors (NLRs). However, activation of these pathways by a specific virus may not be mutually exclusive as exemplified by influenza viral lung infection. The influenza viral infection activates TLR7 within pDCs and activates RLRs within alveolar macrophages to induce type I

IFN responses. TLR 3 and TLR 9 on myeloid and pDCs also respond to influenza viral antigens to activate type I IFN and inflammatory cytokines. The number of circulating pDCs and type I

IFN response may be reduced in healthy aged individuals (22, 102, 169, 197). Age impairs the type I IFN response to viral infections including influenza, HSV-2 or West Nile virus in human and mouse models (22, 180, 212). Aging impaired the up-regulation of IRF7, a critical transcription factor in the type I IFN signaling pathway in two studies using HSV-2 infection in murine pDCs and influenza infection in human pDCs (169, 212). Aging also compromises the

TLR responses in studies using either human PBMCs or mouse models (117, 169, 182, 228). 32

Reduced baseline TLR1 surface expression, along with a decline in TLR1/2 induced TNF α and

IL6 was observed in human PBMCs (228) while the same cytokines were decreased in mouse macrophage cultures in response to various TLR stimuli (182). The latter group also reported a decline in all TLR expression on splenic and activated macrophages. Similar data were seen in primary human DCs, with lowered levels of TLRs 1, 2 and 8 and production of TNF α, IL6 and

IL12p40in mDCs along with decreased levels of TLR7, TNF α and IFN α in pDCs, in response to

TLR stimuli (169).

However, suppression of TLRs and cytokine response is not the only means by which the immune response to viruses is impaired with age. Elevated IL-6 responses to TLR activation have also been recently documented in aging baboons (144). HSV-2 infection led to higher mortality in aged mice due to overproduction of pro-inflammatory cytokines. Also, higher levels of IL17a were produced by liver NKT cells along with more MCP-1 and neutrophil infiltration

(211). West Nile virus infection in macrophages from old subjects impaired the TLR3 response with age such that higher expression of TLR3 resulted in more cytokine response and higher mortality, as compared to young subjects in which lack of or suppression of TLR3 led to resistance to the neurological complications of this infection (117). Studies comparing influenza infection in young/adult and aged mice noted an increase in morbidity in aged mice (222), with a delay in viral clearance (16, 222), total cell infiltration and APC activation in the lungs (222).

The same study found a corresponding delay in production of neutralizing antibody, and chemokines KC, MCP1and MIP1 β. Correlating with the delay in viral load, there was a delay in adaptive responses as well, with delayed infiltration of CD8+ and CD4+ T cells into lungs of infected mice (222), impaired cytotoxic T lymphocyte (CTL) activity and a delay in epithelial 33 necrosis in the lung (16). To our knowledge, no studies have been reported on the changes in innate immune proteins such as pentraxins, MDA-5, RIG-I or α/β defensins.

Autophagy is another cellular pathway affected by age. This pathway was impaired in aged rat and mouse models (34, 42, 219) and restoration of autophagy machinery restored some of the longevity of the model organisms (186). This pathway has been implicated in pathogenesis of age-associated neurodegenerative diseases (e.g., Parkinson’s disease) and cancer, and also other liver, muscle and cardiac diseases. The contributions of autophagy to immunity have been discussed earlier, although the effect of autophagy impairment in infectious disease in the elderly has not been elucidated.

Exercise and the immune system

A growing body of research evidence supports the belief that exercise “enhances” the immune response. Physical exercise is associated with increased longevity and a lower risk of developing cardiovascular disease (CVD), diabetes, hypertension, infectious illnesses and cancer. Other physical and mental interventions such as yoga and meditation have also been explored and may improve physical and mental health (14, 184). The effect of exercise on the immune response depends on the duration and intensity of the exercise itself. In the early 1990s,

Neiman proposed the “J” curve relationship between exercise intensity and risk of upper respiratory tract infections (URTI) (160). This model suggests that none or very low intensity exercise and high intensity exercise increase the risk of URTI, while moderate intensity exercise minimizes the risk of infection. Neiman’s work showed that moderate intensity of regular exercise led to fewer reported symptoms associated with URTIs. Also ongoing research shows that acute sessions of exercise have different (possibly short term) effects on immunity as compared to chronic exercise training. 34

Acute Effects of exercise on immunity

A few studies have reported increased risk and incidences of URTIs in runners within a few weeks after a marathon race or similar endurance exercise event (162, 172), although other results have challenged this finding (49). The circulating numbers and functional capacities of leukocytes may be decreased by repeated bouts of intense exercise. A single, acute bout of increases the number of circulating memory T (CD45RO+), naïve T (CD45RA+) cells and neutrophils, pro-inflammatory cytokines such as TNFα, MIP-1 and IL1 β, anti-inflammatory cytokines like IL6, IL10, IL1ra (IL 1 receptor antagonist), and acute phase protein C reactive protein (CRP) (166). The increase in plasma IL6 can be accounted for by release from contracting muscle (210). Also, IL6 production by monocytes and IL2 or IFN γ production by T cells are inhibited after prolonged exercise, and so these are not the cause for the increase in plasma concentrations of these cytokines (71). Acute exercise temporarily increases the number of circulating NK cells, but this along with cytolytic activity (per cell) decreases after exercise.

Acute exercise also diminished the proliferative capacity and activation markers of lymphocytes and MHC II expression and antigen presenting capacity of macrophages. It has been hypothesized that lymphocytes are recruited to circulation from tissue pools such as the spleen, lymph nodes and the gastrointestinal tract during exercise (but not the lung) and are redistributed back into tissues after exercise or during prolonged and/or high intensity exercise. However, the organs or tissues that these cells are redistributed to are still not clear (170). Lymphocyte proliferation in response to T cell mitogens phytohemagglutinin and concanavalin A decreases during and immediately after exercise (159), although this may reflect the decrease in percentage or proportion of lymphocytes in tissue after recruitment to the blood. 35

Exercise activates the hypothalamic-pituitary-adrenal axis and hormonal changes occur in response to exercise. This includes increases in the plasma concentration of several hormones such as the catecholamines epinephrine (adrenaline) and norepinephrine, growth hormone, β- endorphins, testosterone, estrogen, cortisol, and prolactin, which are known to have immune- modulatory effects (118, 170). Muscle-derived IL6 appears to be at least partly responsible for the elevated secretion of cortisol during prolonged exercise, via stimulating ACTH from the anterior pituitary gland or by stimulating release of cortisol from the adrenal glands (71). T, B,

NK cells, neutrophils and macrophages express β-adrenergic receptors that are targets of catecholamines. Both cortisol and epinephrine suppress the Th1 cytokine production, whereas

IL6 directly stimulates Th2 cytokine production. So exercise also disturbs the Th1/Th2 cytokine balance, decreasing the percentage of IFN γ+ Th1 cells in circulation (122).While the decrease in

Th1 response might be harmful in case of viral URTI infections in athletes, a shift towards Th2 response might be beneficial by reducing the cellular damage and inflammation.

Chronic effects of exercise training on immunity

Studies involving long term exercise training tend to range from 8 week to 12 month exercise training interventions. Thus the outcomes are variable and dependent on the type, duration and intensity of exercise. However, some differences between trained and untrained individuals or have been consistently reported, which will be discussed in this section. As discussed before, many age-related diseases are attributed to a dysfunctional immune system.

The impact of exercise on aging immunity could serve as a simplistic, inexpensive and feasible method for designing lifestyle changes to combat immunosenescence. In this context, the effect of training on aged subjects (human or animal) is provided in this review. 36

Chronic voluntary exercise changes the age-related gene expression in the heart tissue of mice. The changes due to age in these mice were either abrogated or reduced in fold change due to exercise (20). Exercise also reversed the decline in neurogenesis and improved learning and retention in mice (229). The findings from these and other studies suggest that it is possible for exercise to alter gene expression and/or physiological function in multiple tissues. Some of the more specific effects of exercise on the innate and the adaptive immune system will be discussed in the following sections.

Effects of exercise on the innate immune system

The effects of exercise on individual cell populations are difficult to detect, and most data are obtained from in-vitro or ex-vivo studies using exercise trained subjects. This may be the cause of many discrepancies between different studies. Thus far, the research regarding changes in cell populations with exercise and aging hasmnb focused on NK cells, neutrophils and macrophages, and the TLR response has been the most well-studied innate pathway studied with exercise.

NK cell cytotoxicity, which may decrease with age, was either increased or unchanged with exercise in older individuals, and a clear consensus has not been reached (148, 161, 195,

243). Age decreases the ratio of CD56 bright: CD56dim (low cytotoxic: high cytotoxic) NK cells. The composition of NK cell subsets with exercise have not been studied extensively, although one study reported increased proportions of CD56bright NK cells in young subjects

(214). It has been suggested that the increased ratio of CD56 bright: CD56dim (low cytotoxic: high cytotoxic) NK cells may be responsible for the observed reduction in total NK cell cytotoxicity due to exercise training. 37

Fewer studies have examined how neutrophils or monocytes respond to exercise training.

Training may reduce the number of neutrophils in circulation in obese (young) women (150).

Increased phagocytosis as was observed in one study with exercise in the elderly group (243).

Since the effects of age on phagocytic properties of neutrophils are unclear, it is difficult to draw conclusions as to whether exercise “rescues” the age-associated impairments with neutrophils.

A 12 week exercise training intervention resulted in a decreased proportion of

CD14+/CD16+ monocytes in blood, although monocyte TLR4 expression was unaltered (221).

Alternatively, older women who exercised moderately had lower TLR4 expression but no change in LPS stimulated cytokine production (54, 145). A recent study found no changes in monocyte phagocytic activity in middle-aged men (191).

So far no studies involving the effects of exercise on DC activity or TLR expression have been conducted. However, exercise may shift DCs toward a more mature state, because of increases in MHCII in bone-marrow derived DCs and DC-induced leukocyte activation and IL12 production in young rats (29). A recent study involving marathon runners observed a decrease in pDCs and TLR7, and an increase in mDCs, and an increase in both pro- and anti-inflammatory cytokines immediately after the marathon (these were the acute effects of the marathon).

However, they concluded that the training level of subjects (therefore, chronic exercisers vs. non- athletes) did not affect the changes that were seen after the marathon (158).

Few groups have studied non-specific antibody levels in trained individuals. Although it was suggested that levels of secretory immunoglobulin salivary IgA (s-IgA) may be lower in athletes compared to sedentary individuals, recent studies have shown similar s-IgA levels except after periods of heavy training. There is a lack of evidence to support any increase in specific antibody response to vaccination or delayed-type hypersensitivity responses with long 38 duration training. More research is required to reveal the changes in innate immunity with exercise and how it relates to immune response during infectious diseases.

Effects of exercise on the adaptive immune system

Exercise training has been seen to affect T cells and vaccine responses in the elderly.

Although lymphocyte counts remain the same, T cell proliferation, which tends to reduce with age, increased with exercise along with naïve CD8+ T cell proportions and a reduction in exhausted T cell proportions (161, 195, 207, 243). Exercise was also able to reverse the age associated increase in memory: naïve T cell ratio in mice (239) and increase the number and percentage of T cells expressing CD28 in older subjects (194). However, exercise did not alter the T cell proliferative responses in aged individuals or change CD28 expression (21, 104).

Some studies have reported increases in IL2 and IL2 producing CD8+ T cells (17, 195).

This may explain the increase in T cell proliferation observed in some studies. Exercise may also cause a reversal of the Th2 type dominance seen in aged subjects, by enhancing type 1 cytokines in response to viral infection (112).

Exercise may reduce the age associated inflammation, and one possible mechanism that has been studied is an increase in FoxP3+ Treg cells. Although not yet studied in aged models, these cells were found to be increased with exercise in subjects with type 2 diabetes and in number and suppressive function in the mouse model of asthma (136, 244).

Moderate exercise decreases mortality in influenza infections in mice (138) and improves antibody response to HSV-1 infections in mice (116) and responses to influenza vaccine in elderly human subjects (111, 240). Human subjects who exercised at a low to moderate intensity had less mortality due to influenza or influenza associated infection, as compared to those who did not exercise (237). Mice that performed chronic moderate exercise on a treadmill have 39 reduced illness severity and less virus load in the lungs than mice that did not exercise or mice that underwent one session of acute exercise (200). Therefore exercise has the potential to ameliorate disease outcomes in several models, and further study has the capability to contribute to a healthier lifestyle for the elderly.

Exercise and response to vaccinations

Data from an increasing number of studies suggest that an exercise intervention can improve the response to influenza vaccinations in aged (111) as well as young (47, 48) human subjects. In the study conducted on aged subjects, a long term intervention with regular exercise increased antibody titers to strains used in the influenza vaccine. Studies on young adults (18 –

25 years of age) determined that a single session of exercise or mental stress could improve antibody titers in the female subjects, and the IFNγ response in the male subjects. However, a recent study suggested that moderate amount of exercise (a 45 minute brisk walk) was not capable of increasing antibody titers to vaccination in both young and old subjects, and a more robust bout of exercise is required to improve vaccine responses (135). Further studies concerning exercise and efficacy of vaccinations need to be conducted and it remains to be seen whether exercise can be suggested as an adjuvant for vaccines.

CHAPTER 2

AGE IMPAIRS INNATE IMMUNE RESPONSE TO INFLUENZA INFECTION IN MICE.

Shibani Naik 1, Mark Ackermann 2, Heng Wang 3, Dan Nettleton 3, Jack Gallup 2, Marian Kohut 1

1 Immunobiology Program, Iowa State University, Ames, Iowa 50011; 2Veterinary Pathology

Department, Iowa State University, Ames, Iowa 50011; 3 Department of Statistics, Iowa State

University, Ames, Iowa 50011

Abstract

Multiple age-related defects in T-cell or B-cell response to influenza infection have been well documented, but the impact of age on innate host defense to influenza is not well- characterized. Antiviral innate host defense mechanisms directed against influenza include the production of Type I interferon (IFN) and IFN-inducible gene expression, viral recognition involving TLR or RLR signaling cascades, expression of host defense proteins in the respiratory tract, and a recently recognized role for autophagy. Defects of the early innate host antiviral pathways could impact early host defense as well as appropriate activation of adaptive immunity.

Therefore, the aim of this study was to identify age-associated alterations of innate recognition/response to influenza virus. Aged BALB/c mice (17 months of age) and young

BALB/c mice (2 months of age) were either infected with influenza virus or remained as uninfected controls. Lungs and bronchoalveolar lavage fluid (BALF) were collected 6 hours, 12 hours and 24 hours post infection (PI), and at day 3 and day 8 PI. Uninfected aged mice exhibited increased cytokines and chemokines gene expression, illustrating the chronic inflammation associated with aging. Aging was associated with decreased PTX3, PKR, β2- 41 microglobulin, ADAR1 and few TLR signaling adaptors and constitutive monocytes in the lungs.

After infection with influenza, aged mice had lower viral load at day 1 but increased viral titer at day 3 and day 8. Subsequently, innate activation of genes such as TLR 7 and TLR 9 were decreased and activation of ISGs was delayed along with a decrease in cell infiltration of pDCs, neutrophils and inflammatory monocytes in the lungs. Our study confirmed inflammaging in aged mice, along with a depression of ISGs and possibly TLR signaling with age. Infection with influenza virus led to lower viral titer in the initial stages of infection, and lower immune activation and cell infiltration in the lungs which could lead to decreased clearance of virus.

Introduction

The elderly population, i.e. individuals above 60 years of age, constitutes approximately

18.5% of the population in the United States. This represents a 24.6% increase in this population in the last decade (Administration on Aging). The elderly are at a higher risk of infectious disease, and have higher hospitalization rates due to influenza and related respiratory diseases as compared to younger adults (220). In addition to an increased risk of infection, the response to vaccinations is also dampened in the elderly (13, 73). This decreased response to vaccination is often ascribed to the phenomenon of immunosenescence, a dysregulation of the immune response due to age. Extensive research has been conducted in an effort to uncover the causal mechanisms and the effects of aging on the immune system. Multiple changes in the adaptive immune response with advancing age have been well documented. These age related changes include an overall decrease in hematopoietic stem cell (HSC) tissue in the bone marrow of aged mice, as well as a decline in T and B cell precursors (43), naïve CD8+ cells, and CD4+ T cells

(61, 222). Decreased T cell proliferation and defects in function (61, 88) may contribute to age- associated defects in B cell expansion, differentiation and antibody production, affinity 42 maturation and class switching (46, 61-63, 85, 86, 88). An accumulation of late memory and exhausted memory B cells (43, 61-63), as well as regulatory T cell numbers may contribute to recurrence of chronic infections in the elderly (119).

However, the impact of age on innate immunity is less clear. Several studies have evaluated innate immune cell numbers and their function, but results have been variable. A decrease in Toll-like receptor (TLR) expression and cytokine production in response to TLRs has been observed with age (117, 169, 182, 228). To our knowledge, there are no reports on the effects of age on other Pathogen Recognitions Receptors (PRRs) such as Melanoma

Differentiation-Associated protein 5 (MDA-5), retinoic acid-inducible gene 1 (RIG-I) and pentraxin PTX3. These receptors have important roles in detection of influenza virus and induction of inflammatory response (105, 126, 181). Other proteins called antimicrobial peptides (AMP) present in the lung environment may act as initial defense in influenza infection.

These include mouse CRAMP, cathelicidin Related AMP (cathelicidin LL-37 in humans) and mouse Ears, eosinophil-associated ribonucleases (eosinophil-derived neurotoxin EDN/RNase 2 and eosinophil cationic protein ECP/RNase 3 in primates) (154, 226). An age-related defect in any of these host defense pathways could result in increased viral replication and/or impair the activation of appropriate dendritic cell priming of T or B cell responses.

Autophagy is a highly conserved cellular pathway that has multiple functions in cell homeostasis, and was recently recognized as playing an important role in the recognition and response to virus infection, although exact mechanisms remain to be clearly identified (129,

250) . Autophagy may contribute to a reduction in inflammation by decreasing necrosis and apoptosis, and may inhibit pro-inflammatory signaling via RIG-I like receptors and induction of inflammasomes (133, 186, 241). This pathway may influence adaptive immunity by increasing 43 the cross presentation of antigens to dendritic cells (DC) (97). Autophagy is also thought to be impaired with age, contributing to immunosenescence and possibly a dysfunctional immune response to infections (34, 42, 219). The process of autophagy was found to be impaired in aged rat and mouse models and restoration of autophagy machinery restored some of the longevity of the model organisms (186).

Aged mice infected with influenza show higher morbidity (222) and a delay in viral clearance (16, 222) with a corresponding delay in immune activation, including total cell infiltration, antibody and chemokine production, and epithelial necrosis in the lung (16). These findings may be suggestive of a decreased activation of innate immunity (and subsequently activation of adaptive immunity and CTLs) that could result in a more severe infection with influenza. However, one group reported higher inflammation during sub-lethal influenza infection and greater mortality during lethal infection than in young mice.

Studies of the innate response with age in humans have been limited to in vitro and ex vivo studies on human peripheral blood mononuclear cells (PBMCs) from geriatric populations

(22, 37, 102). Although defects of T and B cell function have been reported, particularly in response to influenza vaccination, very little has been published regarding the impact of age on innate host defense against influenza virus in humans. Based on findings from only two studies, a decrease in frequency of type I IFN producing plasmacytoid dendritic cells (pDC) and cytokine production of IFN α, IL6 and TNF α was noted in PBMCs from aged individuals in response to stimulation by influenza virus (22, 102). Such systems have the disadvantage of being isolated cell systems and may not fully represent the effects of aging on the tissue response to infection.

Therefore, the purpose of this study was to determine whether age impairs different aspects of 44 the innate host defense against influenza, and whether influenza infection leads to a different outcome in aged mice than young mice.

Materials and Methods

Animals, virus and infection

Aged BALB/c mice (male, 17 months of age, n= 6 to 10) and young BALB/c mice (male,

2 months of age, n= 6 to 10) were obtained from Charles River NIA aged mouse colony. Mice were anesthetized using aerosolized isoflurane and infected via an intranasal route with influenza virus strain A/PR/8/34 (H1N1) at doses of 163.84 HA units, 0.041 HA units and 0.02 HA units

9.5 per mouse (stock virus – HAU= 1024/0.05mL or 10^ /mLEID 50 diluted 1:6.25, 1:25,000 and

1:50,000 in sterile saline).

An experiment was conducted to ascertain the viral load post infection with influenza virus dose adjusted to lung weight and volume (which varied between young and old mice).

Therefore, old and young mice were infected with H1N1 A/PR/8/34, adjusting the viral dose to the average lung tissue weight of each group. Lung tissue weight and volume of old mice was found to be about twice that of young mice, therefore viral doses were calculated accordingly.

This was done to ensure that all mice were infected with the same amount of virus per mg tissue.

A group of old mice (Group 1 OLD, n= 8) and a group of young mice (Group 1 YOUNG, n= 8) were infected with 1:25000 dilution of influenza virus (labeled dose 1). Another group of young mice (Group 2 YOUNG, n=8) was infected with a 1:50000 dilution of influenza virus (labeled dose 2). Viral load was then measured using qRT-PCR in lungs and broncho-alveolar lavage fluid (BALF) collected at day 3 and day 8.

Non-infected controls for each group were housed separately from the infected mice.

Following infection with PR8 virus, mice were weighed every 24 hours until necropsy. All 45 animal procedures were approved by the Institutional Animal Care and Use Committee

(IACUC).

Tissue collection

Mice were euthanized by cervical dislocation at 6 hours post infection (PI), 12 hours PI, or 24 hours PI. In some experiments mice were euthanized at either 3 or 8 days PI. Lung lobes were collected and used to determine viral titers. Remaining lung tissue was collected for RNA isolation and flow cytometry. RNA was isolated using TRIzol Reagent (Invitrogen, Carlsbad,

California). Lung RNA was further purified using the RNeasy Micro Kit (QIAGEN, Valencia,

California) then frozen at -80°C until further testing was carried out by PCR. Lungs were homogenized in collagenase containing media and single-cell suspensions of lungs were obtained using a 40µm cell strainer and used for flow cytometry. Broncho-alveolar lavage fluid

(BALF) was collected by inserting a catheter attached to a syringe through an incision in the trachea, and airways were flushed three times with 1 mL of PBS. The BALF was centrifuged, cells were collected for analysis by ﬂow cytometry, and the supernatant was stored at -80 °C until subsequent analysis. qPCR and PCR Microarray

1000 ng of purified lung mRNA was analyzed for gene expression using the 96-well

Mouse Toll Like Receptor Pathway RT² Profiler™ PCR Array and Autophagy Pathway RT²

Profiler™ PCR Array (SABiosciences, Frederick, Maryland) and the protocol provided with the array. Samples were analyzed using a BioRad iCycler and corresponding MyIQ Optical System

Software Version 1.0. Customized primers were designed for IFN α/β subunits and Interferon stimulated genes (ISGs) using Primer Express software and obtained from Applied Biosystems.

GAPDH, beta actin and beta galacturonidase were used as the reference genes/housekeepers. 46

Identification of Lung Cell Populations by Flow Cytometry

Cell populations were determined in lungs and BALF from uninfected old and young mice, and from infected mice that were euthanized on day 1 PI. Live cells were gated by comparing forward scatter with side scatter and deselecting the cells with low forward and side scatter. Alveolar macrophages (Highly autofluorescent, CD11c high, CD11b low, Gr1 negative), constitutive monocytes (CD11b positive, Gr1 negative), pDCs (CD11b low, CD11c intermediate, mPDCA positive, low autofluorescence), neutrophils (CD11c negative, CD11b positive, Gr1 high, high side scatter) and inflammatory monocytes (CD11b positive, Gr1 high, CD11c negative, low side scatter) were identified in cells obtained from whole lung homogenate and

BALF. Flow cytometry was performed using a FACSCanto flow cytometer. FlowJo 7.6 software was used for gating and analysis.

Determination of viral titer

Mice were euthanized at multiple time points post-infection and viral load was assessed in the lungs. Virus titers were measured by a quantitative fluorogenic reverse transcription- polymerase chain reaction (real-time RT-PCR) using TaqMan ® chemistry. Using sequences deposited in GenBank (http://www.ncbi.nlm.nih.gov/Genbank/index.html) and Influenza

Sequence Database (http://www.flu.lanl.gov), virus-specific oligonucleotide primers and a fluorescent probe were engineered to target a highly-conserved region of SIV NP gene. The forward primer (SIVRTF: 5’- CGGACGAAAAGGCAACGA-3’) and reverse primer (SIVRTR:

5’- CTGCATTGTCTCCGAAGAAATAAG-3’) were synthesized by a commercial vendor

(Integrated DNA Technologies, Coralville, IA, USA). A TaqMan ® MGB probe with a 5’ reporter 6-carboxyfluorescein (FAM) and a 3’ non-fluorescent quencher (SIVRTP: 5’-6FAM-

CCGATCGTGCCYTC) was synthesized by Applied Biosystems (Foster City, CA, USA). To 47 conduct the assay, viral RNA was first extracted from 50 µl of lung sample, positive control

(H1N1 and H3N2 swine influenza viruses) and negative control (elution buffer) using the

Ambion ® MagMAX™ Viral RNA Isolation Kit (Applied Biosystems) and KingFisher ® 96 magnetic particle processor (Thermo Scientific, Waltham, MA, USA). Real-time RT-PCR was then carried out with the QuantiTect ® Probe RT-PCR Kit (Qiagen, Valencia, CA, USA) in a 20

µl reaction volume using 4 µl of extracted template. Primers were added at a final concentration of 0.4 µM each and the probe was at a final concentration of 0.2 µM. The PCR amplification was performed on the ABI 7900HT Sequence Detection System (Applied Biosystems, Foster

City, CA, USA) with the 384-well format. Cycling conditions were as follows: a) reverse transcription for 30 min at 50° C; b) a 15 min activation step at 95° C, and c) 40 cycles of 15 sec at 94° C and 60 sec at 60° C. A set of influenza preparations, each with a known virus titer

(EID 50 /ml), were used to generate a standard curve. Samples with threshold cycles (Ct) ≤35 were considered positive. The amount of influenza in each sample was calculated by converting the Ct value to a virus titer using the standard curve.

Statistical Analysis

Statistical analysis for lung and BAL cell populations was performed using SPSS

Statistics 17.0. A one-way ANOVA was used to compare difference between young and old mice. Viral titer data was log transformed and a one-way ANOVA again was used to compare difference between young and old mice. In order to compare body weight post-infection, a repeated measures ANOVA was used. Statistical trends were denoted by p<0.1 and significance levels for all tests were set at p<0.05. The false discovery rate was calculated as the q value for

PCR results. Statistical trends were denoted by q <0.1 and significance levels were set at q<0.05.

Results 48

Differences in viral titer in young and old mice

Old and young mice were infected with Influenza A/PR/8/34, and body weights and food intake were measured every 24 hours post infection to assess symptoms and evaluate illness severity (Figure 1). All mice infected with influenza lost weight during the course of the infection. Weight loss in old mice began at day 2 PI, whereas weight loss in young mice did not occur until day 5 PI. Overall, old mice lost more weight than young mice over 8 days of influenza infection (compare groups ‘young dose 1’ to ‘old dose 1’ in figure 1). Viral load was measured by qRT-PCR in lungs collected from mice at day 3 and day 8 after they were infected with influenza virus. The log of viral load was compared between groups (Figure 2B). Old mice had higher viral burden in lungs at both day 3 and day 8 after infection (p<0.05). To assess the effect of age on viral load early in the course of infection, mice were euthanized day 1 post influenza infection and viral load was measured. Old mice had lower viral load in BALF and lungs as compared to young mice (Figure 2A).

Body weights and viral load were measured in Group 1 OLD and Group 1 YOUNG that were infected with 1:25000 dilution of influenza virus (labeled dose 1) and Group 2 YOUNG that was infected with a 1:50000 dilution of influenza virus (labeled dose 2). Group 1 YOUNG and Group 2 YOUNG mice had similar weight loss (Figure 1B) and viral titers (Figure 3A), even though they received different virus doses. Both groups of young mice had less viral load in the lungs than old mice at both day 3 and day 8 (Viral load was then measured using qRT-PCR in lungs collected at day 3 and day 8 (Figures 3A and 3B).

Age increases expression of cytokines and chemokines associated with inflammation prior to infection, but decreases inflammatory and activation markers day 1 after infection. 49

Healthy (uninfected) aged mice showed higher expression of chemokines CCL2 (MCP-

1), CXCL10 (IP-10), cytokines IL10, IL1 β, IL6, IFN γ, CSF2 (GM-CSF) and TNF when compared with young mice (Figure 4A). This suggests that an increase in basal levels of these cytokines and chemokines may contribute to the “inflammaging” phenomenon that has been reported in aged animals. Mucin encoding gene MUC13, and Ly86 were also increased prior to infection.

A panel of activation and inflammatory markers were detected at day 1 post influenza infection. The fold change in old mice after infection was less than the fold change in young mice for many of the genes detected, such as CD80, CD86, CLEC4e, IFN γ, IL1b, MUC13,

Ly86, TNF, CCL2, IL6 and CSF3 (Figure 4B).

Influenza infection induces the expression of PRRs in young and old mice

Data in Tables 1A and 1B illustrate the impact of influenza infection on gene expression related to pattern recognition receptors (PRR’s) (Table 1A, 1B). Influenza infection in young mice induces the expression of TLRs 1-9 and associated gene MyD88. TLR3, TLR7 and TLR9 were strongly induced as early as 12 to 24 hours after infection, along with PDCD-1, MDA-5, mEAR1 and PTX3 day 1 PI. Clec4e, a recognition protein associated with bacterial infection was also increased upon infection (Table 1A).

Infection with A/PR/8/34 in old mice induced PRRs such as TLRs 1, 2, 3 and 9, MDA-5, mEAR1 and PTX3 at day 1 PI (Table 1B). Since the peak of TLR induction in young mice from our previous experiment was at day 1 PI, only that time point was studied in old mice. CRAMP,

MDA-5 and mEAR1 were detected at 12 hours and day1 PI and were induced as early as 12 hours after infection. PTX3 expression was reduced at 12 hours PI and then increased at day 1 PI in old mice. 50

When PRR expression day 1 after infection was compared between old and young mice, the expression of CRAMP, MDA-5, mEAR and PDCD-1 were similar in both groups (Figures

5A and 5B). TLR expression was studied at day 1 PI and the fold change with infection in young mice was compared with fold change induced after infection in old mice (Figure 5C). The fold change in old mice was lower than the fold change in young mice for TLR1, TLR3, TLR7, TLR8 and TLR9.

Age reduces gene expression of PRRs prior to infection.

To determine whether aging might alter the baseline expression of genes associated with viral recognition, gene expression of PRRs were measured by qPCR in mouse lung tissue from old and young mice that were not infected (Figure 5D). Expression of TLRs showed slight decreases in TLR 4 and TLR5 with age, and increases in TLR 7 and TLR 8 expression (Figure

5D), however the magnitude of change was not remarkable. Gene expression for downstream signaling proteins IRF3, TRAF6 (p<0.05) and TICAM1 (p<0.1) were lower in old mice (Figure

5D).

Influenza infection induces the expression of type I IFN and stimulated genes in young and old mice.

Table 2A and 2B depict the fold change in gene expression of type I IFN and ISGs after influenza infection. With respect to Type I interferon and interferon stimulated genes, IFN α2,

IFN α4, IFN β1 and 17 ISGs were detected in whole lungs of young mice (Table 2A). Expression was seen at early as 6 hours PI for IFN α4, IFN β1 and several ISGs. By 12 hours PI, most interferon or interferon-inducible genes were highly expressed.

After infection with influenza, ISGs were detected by qPCR in lungs of old mice at 6 hours, 12 hours and 24 hours PI (Table 2B). At 6 hours PI, CXCL10, OAS1a, OAS1b and 51

STAT2 mRNA were induced. By 12 hours PI, all ISGs that were detected were higher with infection.

Figures 6A, 6B and 6C show the induction of ISGs with infection in old and young mice compared to the respective non infected groups. Infection induces the expression of these genes to different intensities, the fold change in old mice being less than fold change with infection in young mice. This was evident for genes such as IFN α4, CXCL10, IFN β1, Mx2, Mx1, ISG15,

IFIT3 and IFN α2 (Figure 6A) at 6 hours PI. The pattern was still evident at 12 hours PI for

PTX3, CXCL10, PKR, IFN α4 and Mx2 although the gap between young and old groups was decreased (Figure 6B). At 24 hours PI, young and old mice had similar fold changes with infection (Figure 6C).

In order to compare the mRNA expression in infected old and young mice, the mRNA expression from old infected mice were compared with mRNA from young infected mice at the same time points (Figures 7A, 7B and 7C). The pattern of gene expression suggested a down- regulation of ISGs in the old mice at 6 hours PI, such as IFN α4 (q<0.1), CXCL10, IFN β1, Mx2,

Mx1, ISG15, IFIT3 and IFN α2 (Figure 7A). At 12 hours PI (Figure 7B), many genes were still down-regulated in the old mice, for example IFN β1 and PTX3 (q<0.05), CXCL10 (q<0.1), PKR,

IFN α4 and Mx2. By 24 hours PI (Figure 7C) all mRNA had returned to baseline, and OAS1a was trending an increase (q<0.1).

Age reduces gene expression of type I IFN response prior to infection.

Gene expressions of ISGs were measured by qPCR in mouse lung tissue from old and young mice that were not infected (Figure 7D). Of the genes that were detected, PTX3 and PKR mRNA were decreased by 0.58 fold in old mice compared to young mice. β2-microglobulin and 52

ADAR1 expression was reduced by 1/3 in old mice as compared to young mice, while OAS2 was increased by 1.8 fold (p<0.05, q<0.1).

Infection reduces the expression of autophagy related genes in infected young and old mice.

Genes associated with autophagy were detected at day 1 post infection. After mice were infected with influenza, both young and old mice at day 1PI down-regulated the genes involved in autophagy machinery and regulation, like Akt1, Atg, Bad, Bcl2, Ulk in infected mice when compared to the respective uninfected groups (Table 3). The changes in old mice were similar to the fold changes in young mice with infection, indicating that autophagy was similarly regulated by infection in old and young mice.

When genes associated with autophagy were detected in old and young mice prior to infection, age was not associated with a significant difference in expression of genes of the autophagy pathway in healthy mice.

Age alters the cell populations in the lungs and BALF of mice.

Cell populations were detected by flow cytometry in lung tissues as well as cells obtained from BAL from old and young mice. Total cell counts in healthy mice were not different in lungs

(Figure 8A) but in BALF old mice had higher total cell counts than young mice (Figure 8B). Cell counts of individual populations also were similar in old and young mice (Figures 8C and 8D).

The frequency of constitutive monocytes was decreased in lungs and BALF of aged mice (Figure

8E and 8F).

The same cell populations were assessed 24 hours after mice were infected with influenza

(Figures 8A- 8F). The total cell counts were reduced in BALF of infected old mice when compared to infected young mice but not in the lungs (Figures 8A and 8B). The cell counts in lungs were lower in infected old mice for pDCs, neutrophils and inflammatory monocytes, but 53 not for alveolar macrophages and constitutive monocytes which remained unchanged (Figure

8C). In the BALF, cells displayed the same pattern, with lower pDCs, inflammatory monocytes and also NK cell (Figure 8D). The percentage of inflammatory monocytes was lower in old mice in both lungs and BALF, and percentage of neutrophils and pDCs were lower in lungs of old mice (Figures 8E and 8F).

Discussion

Most studies on aging have been conducted in vitro or on specific cell types isolated from aged subjects. Our experiments were conducted on whole lung homogenates for a more comprehensive picture of how the lung tissue changes with age and how that affects the immune response to influenza infection, with the cells in their native microenvironment. We have presented a study on changes in PRRs, Type I IFN response, autophagy and cell infiltration in the lungs in healthy aged and young mice, as well as after influenza infection in aged and young mice. This enabled us to identify alterations in these pathways with age and viral infection.

Initially, the gene expression studies were performed to identify the anti-viral pathways that were induced by infection in young adult mice. The expression of anti-viral genes such as

TLRs, IFN α2, IFN α4, IFN β1 and ISGs were induced in young mice as early as 12 hours post infection. As the time course of gene expression was established, experiments were performed to determine whether age affected the expression of these genes prior to infection and at multiple time points post-infection. Prior to infection, there was no evidence of a significant difference in gene expression of PRRs such as TLRs, MDA-5, or innate proteins CRAMP, PDCD1 and mEAR1 between healthy old and young mice. A decrease in TLRs from DCs along with reduced cytokine production of IL6, TNF α and IFN α from DCs and macrophages have been reported in the literature (169, 182, 228). Though the changes in TLRs were not noticeable in our model, the 54 signaling molecules IRF3, TICAM1 and TRAF6 showed a decrease associated with age.

TICAM-1 is the functional adapter for both TLR3 and TLR4 that induces type I IFN and

MyD88-independent DC maturation. TRAF6 is a central adaptor molecule in TLR signaling that leads to the activation of NF κB, and IRF3 is an Interferon Regulatory transcription factor that leads to IFN β induction. These changes could potentially reduce the functional capacity of the

TLR pathway.

Type I IFN subunits IFN α2, IFN α4 and IFN β1 were not significantly different between old and young mice, but ADAR1, β2m, PTX3 and PKR, all of which have anti-viral properties were significantly lower in older mice. OAS2 was the only ISG to be higher in aged mice. These data suggest that while PRR expression in whole lung homogenate was not altered with age, some anti-viral gene expression may be reduced, leading to an altered immune activation status in healthy aged mice. It is interesting that though TLR signaling was down-regulated along with

IFN inducible genes, inflammatory cytokine genes were still up-regulated. This may imply that increased inflammation associated with aging is not induced by TLRs but by another pathway, for example the inflammasome.

We observed higher levels of cytokine mRNA for IL10, IL1 β, IL6, TNF and IFN γ in lungs of healthy aged mice, which may be indicative of the increase in basal levels of inflammation that are a hallmark of old age. Other studies have also noted increased cytokines such as IL6 in baboons (144) and IL12p70, IL1 β, TNF α, IL6, and IL10 in humans (8). Increased mRNA expression of chemokines CCL2 (MCP-1), CSF2 (GM-CSF) and CXCL10 (IP-10) may also contribute to “inflammaging” by attracting monocytes and dendritic cells to the lung tissue. 55

These changes in chemokines may change the trafficking of stem cell populations being attracted to the lungs.

Post influenza infection, influenza viral load was higher in lungs of old mice at days 3 and 8 PI, but lower at 24 hours PI (when given a lethal dose). We have previously reported that old mice had lower viral titers in lungs 6 hours PI and in BAL collected at 12 hours PI, as compared to young mice, and other groups have noted a delay in viral clearance in aged mice lungs but decreased viral titer in aged mice from day 2 PI (222). PRRs such as TLRs 1, 2, 3 and

9, MDA-5, mEAR1 and PTX3 were induced in old mice at day 1 PI. The increase in PRR gene expression post influenza infection was lower for old mice as compared to the increase in young mice. These include TLRs 2, 3, 6, 7, 8 and 9. Many inflammatory and activation markers such as

IL1b, TNF, CCL2, IL6, CD80/86 and Ly86 were induced to a lesser extent in the old mice. This pattern is consistent with the decrease in viral titer at day 1 post infection when compared to young mice. ISGs were induced post infection in old mice, but the activation seemed to be delayed in old mice early after infection.

The cell populations that were studied in lungs and BALF suggested that immune cells such as inflammatory monocytes and pDCs move from the BALF into the lungs as early as day 1 post influenza infection. However, we noted reduced numbers of pDCs, neutrophils and inflammatory monocytes associated with aging in both BALF and lungs of infected mice. Taking all our data into account, it is possible that in our model the decreased amount of virus in lungs at early time points after infection (6, 12 and 24 hours PI) led to lower immune activation that was observed in old mice.

Autophagy has been associated with increased antigen presentation and yet it is required for some viruses during replication, while assembling virus particle near the cell surface inside 56 the cytosol (45, 179, 202). We found that autophagy was decreased at day 1 post infection with influenza in both young and old mice in a similar fashion. This could either be a defense mechanism of the body against the virus to minimize replication, or an evasion strategy of the virus to minimize antigen presentation. More studies would have to be carried out to determine the significance of this finding, but since this is quite early in infection, the possibility exists that this may be a host defense mechanism to minimize replication. While some groups have reported decreased autophagy function with aging (34), our data did not provide any evidence of a significant difference in autophagy related genes prior to infection in old mice.

In conclusion, we observed that viral load is lower in lungs of old mice as compared to young mice, suggesting that viral uptake into cells may be impaired with age. Consequently, we noted reduced immune activation at early time points post infection (6, 12 and 24 hours post infection) along with decreased cellular infiltration into lungs associated with aging. However, higher viral load at days 3 and 8 post infection suggest that viral replication is not impaired later in infection but the immune response, perhaps because of delayed immune activation early in infection, is not able to clear the virus as efficiently as young mice. Even though healthy aging was associated with higher levels of inflammatory cytokine mRNA prior to infection, the fold change of mRNA for activation and inflammatory markers at day 1 post infection were lower in old mice. This study provides further evidence for immune impairment with aging. It highlights the importance of elucidating the mechanisms of immunosenescence in order to provide therapeutics and vaccinations that are tailored to support and augment the immune response in the elderly.

Figures for Chapter 2

Figure 1

120

100

80 t*a old dose 1 60 young dose 1 young dose 2 40 non infected old

20 Body Weight Weight Body(% of original weight) 0 Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8

Figure 1: Body weight loss over time was assessed for a time by age interaction, determined by mixed ANOVA. (t*a) signifies a significant time by age interaction; p < 0.05)

Figure 2A.

Viral load at day 1 PI 9

8 *

6 Old Inf Young Inf 5 LOG Viral LOG Titer Viral

3 BAL Lung

Figure 2B.

8 * 7.5 7 6.5 * 6 5.5 Old Inf 5 4.5 Young Inf LOG Viral LOG Titer Viral 4 3.5 3 3days p.i. 8days p.i. (Lungs) (Lungs)

Figure 2A – 2B: Viral load in lungs of young and old mice infected with influenza virus. 2A)

Viral load in BALF and lungs at day 1 post influenza infection. 2B) Viral load in lungs at day 3 and day 8 post influenza infection. Viral load was detected by quantitative PCR for influenza NP protein. * indicates a significant (p<0.05) effect of age.

Figure 3A.

Viral load in lungs at day 3 PI 7.00 * 6.00

5.00

4.00

3.00

LOG LOG Viral Titer 2.00

1.00

0.00 Old Dose 1 Young dose 1 Young dose 2

Figure 3B.

Viral load in lungs, day 8 PI 9.00 8.00 * 7.00 6.00 5.00 4.00

LOG LOG Viral Titer 3.00 2.00 1.00 0.00 Old Dose 1 Young Dose 1 Young Dose 2

Figure 3A – 3B: Viral load in lungs comparing a group of old mice and a group of young mice that were infected with 1:25000 dilution of influenza virus (labeled dose 1). Another group of young mice was infected with a 1:50000 dilution of influenza virus (labeled dose 2). 3A) Viral load in lungs of mice at day 3 post influenza infection. 3B) Viral load in lungs of mice at day 8 post influenza infection. Viral load was detected by quantitative PCR for influenza NP protein. * indicates a significant (p<0.05) effect of age, Old Dose 1> Young Dose 1 AND Dose 2.

Figure 4A.

Fold change (Old/Young), uninfected 8

+ * + + 4 + + * * * + * 2 Fold changeFold Old/Young, log 2 scale 1 Ccl2 Clec4e Csf2 Cxcl10 Ifng Il10 Il1b Il6 Muc13 Ly86 TNF

Figure 4B.

Infection in young and old mice, day 1 PI 256 128 64 32 16 Young

base) 8 Old 4 2 1 Foldc hangeFoldc Infected/Non Infected (log-2

Figure 4A – 4B: Effect of age on mRNA expression of genes associated with inflammation.

Gene expression was detected in whole lung homogenates of mice using quantitative Real Time

PCR. (4A) Whole lung homogenates were obtained from uninfected mice. Fold changes were calculated by comparing old uninfected mice to young uninfected mice. * indicates a significant effect of age (q value<0.05), + indicates trend (q value <0.1, p value <0.05). (4B) Fold changes in young mice with infection depicted alongside fold change in old mice in the same genes at day

1 post influenza infection.

Table 1A.

Fold change with infection in young mice

Gene name 12 hours PI Day 1 PI Day 2 PI Day 4 PI

Tlr1 3.107 3.8145 3.9145 4.3334 Tlr2 2.7784 4.9712 3.813 3.3425 Tlr3 3.3931 7.1697 4.1008 2.041 Tlr4 1.4872 1.9479 1.6312 1.5503 Tlr5 0.6669 0.612 0.7264 0.0731 Tlr6 2.2302 2.955 2.0569 2.4631 Tlr7 2.3882 5.5735 4.5607 3.791 Tlr8 1.5656 2.9202 2.3082 2.1586 Tlr9 3.1704 17.3156 8.464 11.5354 Myd88 2.8939 6.707 4.0549 2.7504

Clec4e 13.6785 28.1781 19.8422 16.9182 PTX3 0.998774 5.452357 CRAMP 1.801402 1.679416 PDCD1 0.800681 4.746421 MDA5 2.816064 4.657481 mEAR1 1.513176 1.71335

Table 1B.

Fold change with infection in old mice Gene name Day 1 PI Tlr1 2.1053 Tlr2 4.5083 Tlr3 3.0149 Tlr4 2.1502 Tlr5 1.0381 Tlr6 1.9392 Tlr7 1.7726 Tlr8 1.3302 Tlr9 2.7615 Myd88 5.5963 12 hours PI Day 1 PI CRAMP 2.82619 2.58433 PDCD1 1.19322 4.51479 MDA5 2.30121 7.2383 mEAR1 1.57507 1.92564 PTX3 0.5783 4.60359

Table 1A – 1B: Whole lung homogenates were tested for mRNA expression by quantitative Real

Time PCR. (1A) Fold change in gene expression of PRRs at 12 hours, day 1, day 2 and day 4 post influenza infection in young mice as detected by Real Time PCR. (1B) Fold change in gene expression of PRRs at 12 hours and day 1 post influenza infection in old mice. Fold change numbers in bold font indicate significance (p<0.05) and fold change numbers in italics indicate

(0.05< p <0.1)

Figure 5A.

Infection in young and old mice at 12 hours PI 4

2 12 hrs p.i. Young 12 hrs p.i. Old 2 scale) 2 1 CRAMP PDCD1 MDA5 mEAR1 PTX3

Fold changeFold Infected/Non Infected (log- 1/2

Figure 5B.

Infection in young and old mice at day 1 PI 8

24 hrs p.i. Young 24 hrs p.i. Old 2 scale) 2 2

1 Fold changeFold Infected/Non Infected (log- CRAMP PDCD1 MDA5 mEAR1 PTX3

Figure 5C.

Infection in young and old mice, day 1 PI 32

8 Young 4 Old 2 base) 2 2

Foldc hangeFoldc Infected/Non Infected (log- 1/2

Figure 5D.

Fold change (Old/Young), uninfected 2

* +

1 Tlr4 Tlr5 Tlr7 Tlr8 Irf3 Ticam1 Traf6

+ 1/2 * * * * Fold change Old/Young, log 2 scale log 2 Old/Young, change Fold 1/4

Figure 5A – 5D: Gene expression was detected in whole lung homogenates of mice using quantitative Real Time PCR. (5A) Fold changes in young mice with infection depicted alongside fold change in old mice in the same genes at 12 hours and (5B) at day 1 post influenza infection.

(5C) Fold changes in TLR expression at day 1 post infection for young mice are shown alongside fold change in old mice in the same genes. (5D) Whole lung homogenates from uninfected mice and were tested for mRNA expression of TLR and TLR signaling proteins. For all figures, * indicates a significant effect of age (q value<0.05), + indicates trend (q value <0.1, p value

<0.05).

Table 2A.

Fold change with infection in young mice

Gene Name 6 hours PI 12 hours PI 24 hours PI

IFNa2 0.476111 3.635415 14.13823 IFNa4 36.1449 459.4614 1310.153 IFNb1 21.34328 329.9881 648.1662 ADAR1 1.280263 1.690137 2.718423 B2m 0.633374 0.526717 1.905104 Bst2 1.30154 4.572585 15.03247 CXCL10 11.96891 174.8919 620.8668 Eifak2 1.348551 4.968878 7.037485 Gbp1 0.925914 3.256382 9.695532 Ifi204 1.024202 5.575379 18.46652 Ifit1 2.948375 12.4983 29.36407 Ifit3 1.043333 8.4088 21.55738 Irf7 1.259962 6.9105 32.27533 Isg15 2.77612 5.62452 13.62401 Mx1 2.946067 29.01084 50.04521 Mx2 5.863207 51.27771 96.01847 Oas1a 4.755872 26.1348 37.75746 Oas1b 305.975 630.5164 1366.282 Oas2 3.124878 5.057975 15.47245 Stat2 2.442435 2.463723 6.061984

Table 2B.

Fold change with infection in old mice

Gene name 6 hours PI 12 hours PI 24 hours PI

IFNa2 0.388 3.48568 21.63747 IFNa4 3.205679 109.5822 1249.392 IFNb1 6.711894 97.82017 674.8158 ADAR1 2.218431 4.332621 10.77458 B2m 1.128894 2.115414 4.76531 Bst2 0.747207 3.367762 19.75067 CXCL10 7.0675 117.7253 989.8733 Eifak2 1.736726 5.209266 17.34515 Gbp1 0.668037 2.119582 9.040797 Ifi204 0.499529 3.290918 18.12501 Ifit1 1.964075 13.90633 49.35006 Ifit3 0.727929 9.66326 39.22115 Irf7 0.512112 2.71912 18.36427 Isg15 1.372542 3.766097 10.94242 Mx1 1.202794 16.17283 53.33608 Mx2 1.534916 23.7789 73.43368 Oas1a 3.407964 20.29778 56.73787 Oas1b 130.3367 312.9894 632.9291 Oas2 1.048212 1.98686 10.39278 Stat2 1.773587 2.189771 6.19511

Table 2A – 2B: Whole lung homogenates were tested for mRNA expression by quantitative Real

Time PCR. (2A) Fold change in gene expression of Type I IFN and ISGs at 6 hours, 12 hours and 24 hours post influenza infection in young mice and (2B) in old mice are shown. Fold change numbers in italics indicate significance (p<0.05).

Figure 6A.

Infection in young and old mice, 6 hours PI 64

8 young 4 old 2

1/2 Fold changeFold Infected/Non Infected (log-2 base) 1/4

Figure 6B.

Young and old mice at 12 hours post infection 512 256 128 64 32 16 young base) 8 old 4 2 1 Fold changeFold Infected/Non Infected (log-2 Irf7

1/2 Ifit1 Ifit3 Bst2 Mx1 Mx2 B2m Oas2 Stat2 Isg15 Gbp1 Ifi204 IFNa2 IFNa4 IFNb1 Eifak2 Oas1a Oas1b ADAR1 CXCL10

Figure 6C.

Young and old mice at 24 hours post infection 2048 1024 512 256 128 64 32 young base) 16 old 8 4 2

Fold changeFold Infected/Non Infected (log-2 1 Irf7 Ifit1 Ifit3 Bst2 Mx1 Mx2 B2m Oas2 Stat2 Isg15 Gbp1 Ifi204 IFNa2 IFNa4 IFNb1 Eifak2 Oas1a Oas1b ADAR1 CXCL10

Figure 6A – 6C: Infection induces type I IFN subunits and ISGs in young and old mice to different levels. Gene expression was detected in whole lung homogenates of mice using quantitative Real Time PCR. Fold changes in young mice with infection depicted alongside fold change in old mice in the same genes at (9A) 6 hours, (9B) 12 hours and (9C) day 1 post influenza infection.

Figure 7A.

Fold change (old /young ) 6 hrs p.i . 2

1/2

1/4 +

1/8 Fold changeFold Old/ Young (log - 2 scale)

1/16

Figure 7B.

Fold change (old /young) 12 hrs p.i . 2

1/2

* 1/4 +

* 1/8 Fold changeFold Old/ young (log - 2 scale)

1/16

Figure 7C.

Fold change (Old / Young) 24hrs p.i . + 2

1/2

1/4

1/8 Fold changeFold Aged/ Young (log - 2 scale)

1/16

Figure 7D.

Fold change (Old/Young), uninfected 2 *

1 ADAR1 B2m Eifak2 Ifit1 Oas2 PTX3 + *

1/2

+ * Fold change Aged/ Young (log -(log Young Aged/ change Fold scale) 2 1/4

Figure 7A –7D: Effect of age on mRNA expression of type I IFN and ISGs in infected mouse lung homogenates. Whole lung homogenates were obtained from mice infected with influenza and tested for mRNA expression by quantitative Real Time PCR. The fold changes presented were calculated as the fold change of old mice compared to young mice at the same time point post infected. This was calculated and comparisons are presented for (10A) 6 hours, (10B) 12 hours and (10C) 24 hours post infection. * indicates a significant effect of age (q value<0.05), + indicates trend (q value <0.1, p value <0.05). (7D) Whole lung homogenates were obtained from uninfected mice and were tested for mRNA expression of ISGs. For all figures, * indicates a significant effect of age (q value<0.05), + indicates trend (q value <0.1, p value <0.05).

Table 3.

Old Gene Young Infected Infected Name Day 1 pi Day 1 PI

Akt1 0.2509 0.3705 App 0.3771 0.49 Arsa 0.2974 0.2572 Atg16l1 0.5755 1.8671 Atg3 2.2197 1.8088 Atg4d 0.3271 0.2761 Atg5 0.5416 0.8731 Atg7 0.1832 0.2486 Atg9a 0.2109 0.2585 Atg9b 0.2699 0.2114 Bad 0.3704 0.3716 Bcl2 0.3588 0.2532 Ctsb 3.1481 2.0658 Ctss 5.2006 2.6604 Eif4g1 0.3307 0.559 Fas 1.7486 1.0216 Gaa 0.5163 0.7518 Hgs 0.3575 0.4827 Hspa8 2.3287 2.1962 Htt 0.2045 0.1582 Irgm1 10.5768 3.8996 Map1lc3a 0.2896 0.409 Mapk14 0.4992 0.596 Pik3cg 0.3152 0.3181 Tgfb1 0.5292 0.5606 Trp73 0.2813 0.2752 Ulk1 0.2069 0.1949 Ulk2 0.2482 0.4258

Table 3: Fold change in mRNA expression of genes associates with autophagy pathway in young and old mice at day 1 PI. Whole lung homogenates were tested for mRNA expression by quantitative Real Time PCR. Fold change numbers in bold font indicate significance (p<0.05) and fold change numbers in italics indicate (0.05< p <0.1).

Figure 8A.

Total Live cells in Lungs 120000

100000

80000

60000 Old Infected Young Infected Old NI

Number ofcells Number 40000 Young NI

20000

0 Live cells

Figure 8B.

Total Live cells in BALF 12000

10000

8000 * Old Infected 6000 Young Infected Old NI

Number ofcells Number 4000 Young NI

2000

0 Live cells

Figure 8C

Cell counts in Lungs 14000 * 12000 Old Infected 10000

8000 * Young Infected

6000 Old NI

Number of of Numbercells 4000 Young NI 2000

0 Inflammatory Neutrophils DC pDC Constitutive Alveolar Monocytes monocytes Macrophages

Figure 8D

Cell counts in BALF 2000 * 1800 1600 1400 1200 Old Infected 1000 Young Infected 800 Old NI

Number of of Numbercells 600 * Young NI 400 200 0 Inflammatory DCs pDC Alveolar Monocytes Macrophages

Figure 8E

Frequency of cell populations in Lungs

14 *

10 *

8 Old Infected Young Infected 6 Old NI 4 Young NI Percentage ofLive Percentage ofLive cells

0 Inflammatory Neutrophils DC pDC Constitutive Alveolar Monocytes Monocytes Macrophages

Figure 8F

Frequency of cell populations in BALF 35 * 30 25 Old Infected 20 15 Young Infected 10 Old NI Young NI

Percentage Percentage of Live cells 5 0 Inflammatory DCs pDC Alveolar Monocytes Macrophages

Figure 8A – 8F: Cell populations were detected in BALF and lungs of mice using flow cytometry. Total numbers of live cells are shown in (8A) lungs and (8B) BALF of uninfected mice and infected mice at day 1 post influenza infection. (8C) shows the cell counts of inflammatory monocytes, neutrophils, DC, pDC, constitutive monocytes and alveolar macrophages in the lungs of mice and (8D) shows cell counts for inflammatory monocytes, DC, pDC and alveolar macrophages in BALF of mice. Cell frequencies were calculated as the percentage of total live cells for each population. (8E) shows the cell frequencies of inflammatory monocytes, neutrophils, DC, pDC, constitutive monocytes and alveolar macrophages in the lungs of mice and (8F) shows cell frequencies for inflammatory monocytes,

DC, pDC and alveolar macrophages in BALF of mice. Statistical significance was determined by one-way ANOVA, * indicates a significant effect of age (p value<0.05), + indicates trend (0.05< p <0.1).

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CHAPTER 3

MODERATE EXERCISE REDUCES VIRAL LOAD AND ALTERS INNATE IMMUNE

RESPONSE TO INFLUENZA INFECTION IN AGED MICE.

Shibani Naik 1, Mark Ackermann 2, Heng Wang 3, Dan Nettleton 3, Jack Gallup 2, Todd Wyatt, 4,

Marian Kohut 1

1 Program of Immunobiology, Iowa State University, Ames, Iowa 50011; 2Veterinary Pathology

Department, Iowa State University, Ames, Iowa 50011; 3 Department of Statistics, Iowa State

University, Ames, Iowa 50011; 4 Department of Internal Medicine, University of Nebraska

Medical Center, Omaha NE 68198,

Abstract

Physical activity may have a beneficial effect on the immune response to pathogens and infections in aged immune systems that exhibit immunosenescence. The potential impact of exercise on expression of pathogen recognition receptors (PRRs) and type I interferon (IFN) response, as well as cell populations in the lungs were examined in aged exercised (EX) mice compared to aged non exercised (NON-EX) mice. In previous findings, an exercise-associated reduction of lung viral load was observed in aged exercised-treated mice that were infected with influenza virus as compared to aged non-exercised mice. It is possible that early host innate defenses are altered by exercise training and result in decreased viral load. To test this hypothesis, aged BALB/c mice (17 months of age) were exercised at a moderate intensity

5d/week for 10 weeks. Twenty-four hours after the last exercise session, mice were infected with influenza A/PR/8/34 virus through an intranasal route. NON-EX old mice and young mice (2 91 months of age) were infected at the same time. Lungs and bronchoalveolar lavage fluid (BALF) were collected prior to infection and at multiple time points post-infection (PI). The mRNA for several PRR’s, interferon, and interferon-stimulated genes was detected in whole lungs using

Real Time PCR. Ciliary beat requency was measured to examine the effect of exercise on mucociliary clearance in exercised mice. Cell populations were studied in lungs and BALF by flow cytometry. In non-infected mice, exercise training resulted in greater levels of expression of TLR 6, 7 and 8, as well as β2m, a component of MHC class I molecules, and GBP1 (a Type I

IFN stimulated gene) in whole lung tissue. Lungs of exercise mice had increased numbers of the following cell populations: constitutive and inflammatory monocytes, plasmacytoid dendritic cells (pDCs) and neutrophils. In the BALF, plasmacytoide dendritic cells (pDCs ) also tended to be found in greater numbers. These effects of exercise were no longer observed 24 hours post- infection with influenza virus. There were no differences in the total number of lung cell subpopulations between exercise and non-exercise mice 24 hours after infection with influenza virus although the percent change relative to pre-infection was different. Also, viral load was decreased in the respiratory tract of EX mice. Our results suggest that exercise may alter the time course of interferon-inducible genes such that exercise mice respond more quickly (6 hrs post-infection) relative to non-exercised mice. Taken together these exercise-associated changes may contribute to an early reduction in lung viral load.

Introduction

Influenza and influenza related secondary infections cause severe disease, hospitalizations and mortality each year (35). Some groups in the population are more prone to influenza infections, for example pregnant women, young children, elderly individuals and immunocompromised patients (124, 220). Although influenza vaccination may reduce 92 hospitalization rates in the elderly (15), the response to vaccines declines in aged individuals leaving them more susceptible to infection. These factors makes the prevention of infectious diseases in the aging population more challenging (13).

Many lifestyle factors are proposed to affect risk of infection and vaccine responses in older individuals, exercise being a key intervention (14, 113, 114). Moderate exercise may slow down or even reverse the detrimental effects of age on the immune system, as demonstrated in a number of studies on humans and mouse models. Exercise reduces the mortality and morbidity in influenza or influenza associated infection in mice and humans (14, 200, 237). In aged subjects, exercise may improve the response to vaccinations (111, 113, 240). However, the mechanism by which exercise decreases morbidity and mortality in respiratory infections in the elderly remains largely unknown, and the role of early host defenses have not been elucidated.

Physical activity of moderate intensity, but not low or high intensity, decreases the risk of upper respiratory tract infections, as proposed by Nieman as the “J” curve hypothesis (155, 160).

Moderate exercise decreases mortality in influenza infections in mice (138) and improves antibody response to HSV-1 infections in mice (116) and responses to influenza vaccine in elderly human subjects (111, 240). Some data suggests that exercise may reverse some age related changes of immunity such the age-related decline in IL-2 production, and may restore the

Th1 response that is reduced with age (201). Exercise may also reduce inflammation in the elderly (also known as “inflammaging”), though this is still disputed by conflicting studies (201).

Much of the work on exercise and immunosenecence has been focused on T cells responses, and exercise may alter T cell proliferation, activation marker expression including CD28, as well as

IL2 production and Th1/Th2 balance. Limited work has examined the impact of exercise on the innate response to infections, although several studies have used other non-infectious disease 93 models to address the role of exercise in modulating innate host defense. For examples, some data suggests that exercise may alter the composition of cell subsets, particularly NK cells and monocytes (214, 221, 243). Neutrophil phagocytosis was reported to be increased with exercise in obese aged individuals (150). Exercise was reported to reduce TLR4 expression in PBMCs of elderly women in two studies (55, 146). Although these findings provide some insight into the potential impact of exercise on innate immunity, the response to a live pathogen may be more predictive of whether exercise can be effective in reducing infection severity.

In response to viral infection, innate pattern recognition receptors such as the toll like receptors (TLRs) may stimulate Type I IFN (IFN α and IFN β) production by plasmacytoid dendritic cells (pDCs), alveolar macrophages and infected epithelial cells (100). IFN α/β render an anti-viral state to the cells by inducing the transcription of several IFN stimulated genes

(ISGs) that have direct or indirect antiviral properties (36). To our knowledge, no other studies have reported the effect of regular physical activity (or chronic exercise) on pathogen recognition receptors including TLRs, or the type I IFN response to influenza virus infection. Therefore the complete effects of exercise on the different facets of the immune response remain to be defined.

Further insight into the innate system will help in revealing the interactions between the innate and adaptive responses with physical activity and designing lifestyle changes as well as possible molecular or mechanistic targets for improving the response to infections in the elderly.

The purpose of this study was to evaluate the Type I IFN response, TLR pathway and cellular composition of the lungs after exercise training, and to explore the mechanism by which exercise alters the response to influenza virus in aged mice. The innate recognition proteins were detected using quantitative Real Time PCR on lungs of physically active and inactive mice, and flow cytometry was used to detect cell composition of lungs and bronchoalveolar lavage fluid 94

(BALF) from the same mice. The effects of exercise, if any, on the immune response to influenza infection can help in designing lifestyle changes that may improve disease outcome in the elderly.

Materials and Methods

Animals and exercise procedure

Aged male BALB/c mice (17 months of age) were obtained from Charles River (aged

NIA colony) and randomly assigned to the following groups: Old, exercised (EX) and old, non- exercised (NON-EX). The mice in the EX group were exercise-trained on a treadmill for 9-10 weeks. Exercise duration was gradually increased during weeks 1 to 4; from weeks 5 to 8, mice ran 40–45 min/day; then 45 min/day for the remainder of the training period. The speed was progressed from 8 m/min during week 1 to 18 m/min by week 8. The NON-EX group did not exercise. All animal procedures were approved by the Institutional Animal Care and Use

Committee (IACUC).

Virus and Infection

Twenty-four hours after the last exercise session, mice were anesthetized using aerosolized isoflurane and infected via an intranasal route with influenza virus strain A/PR/8/34

(H1N1) at a dose of 163.84 HA units per mouse (stock virus – HAU= 1024/0.05mL or

9.5 10^ /mLEID 50 diluted 1:6.25, 1:25,000 and 1:50,000 in sterile saline). Non-infected controls for each group were housed separately from the infected mice. Mice remained in their cages and did not exercise after infection (n = 6 to 10).

Tissue collection

Mice were euthanized by cervical dislocation at 6 hours post infection (PI), 12 hours PI, and 24 hours PI Lung lobes were collected and used to determine viral load. Remaining lung 95 tissue was collected for RNA isolation and flow cytometry. Bronchoalveolar lavage fluid

200 system (BIO-RAD). RNA was isolated using TRIzol Reagent (Invitrogen, Carlsbad,

California). Lung RNA was further purified using the RNeasy Kit (QIAGEN, Valencia,

California) then frozen at -80°C until further testing was carried out by PCR. qPCR and PCR Microarray

1000 ng of purified lung mRNA was analyzed for interferon inducible gene expression using the 96-well Mouse Toll Like Receptor Pathway RT² Profiler™ PCR Array

(SABiosciences, Frederick, Maryland) and protocol provided with the array (n = 3 to 8). Samples were analyzed using the BioRad MyiQ and corresponding MyiQ Optical System Software

Version 1.0. For analysis of the interferon-stimulated genes (ISGs), customized primers were designed using Primer Express software and obtained from Applied Biosystems. GAPDH, beta actin and beta galacturonidase were used as the reference housekeeper genes (n = 6 to 10).

Identification of Lung Cell Populations by Flow Cytometry

Cell populations were determined in lungs and BALF from uninfected EX and NON-EX mice and infected mice that were euthanized on day 1 PI (n = 8 to 10). Live cells were gated by comparing forward scatter with side scatter and deselecting the cells with low forward and side scatter. Lungs were homogenized in collagenase containing media and single-cell suspensions of lungs were obtained using a 40µm cell strainer. Alveolar macrophages (Highly autofluorescent,

CD11c high, CD11b low, Gr1 negative), constitutive monocytes (CD11b positive, Gr1 negative), 96 pDCs (CD11b low, CD11c intermediate, mPDCA positive, low autofluorescence), neutrophils

(CD11c negative, CD11b positive, Gr1 high, high side scatter) and inflammatory monocytes

(CD11b positive, Gr1 high, CD11c negative, low side scatter) were identified in cells obtained from whole lung homogenate and BAL. Flow cytometry was performed using a FACSCanto flow cytometer. FlowJo 7.6 software was used for gating and analysis.

Determination of viral titer

5’- CTGCATTGTCTCCGAAGAAATAAG-3’) were synthesized by a commercial vendor

(Integrated DNA Technologies, Coralville, IA, USA). An TaqMan ® MGB probe with a 5’ reporter 6-carboxyfluorescein (FAM) and a 3’ non-fluorescent quencher (SIVRTP: 5’-6FAM-

CCGATCGTGCCYTC) was synthesized by Applied Biosystems (Foster City, CA, USA). To conduct the assay, viral RNA was first extracted from 50 µl of lung sample, positive control

(H1N1 and H3N2 swine influenza viruses) and negative control (elution buffer) using the

Ambion ® MagMAX™ Viral RNA Isolation Kit (Applied Biosystems) and KingFisher ® 96 magnetic particle processor (Thermo Scientific, Waltham, MA, USA). Real-time RT-PCR was then carried out with the QuantiTect® Probe RT-PCR Kit (Qiagen, Valencia, CA, USA) in a 20

µl reaction volume using 4 µl of extracted template. Primers were added at a final concentration 97 of 0.4 µM each and the probe was at a final concentration of 0.2 µM. The PCR amplification was performed on the ABI 7900HT Sequence Detection System (Applied Biosystems, Foster

Statistical Analysis

Statistical analysis was performed using SPSS Statistics 17.0. A one-way ANOVA was used to compare lung and BAL cell populations between young and old mice. Viral load data was log transformed prior to analysis. Statistical trends were denoted by p<0.1 and significance levels for all tests were set at p<0.05. The false discovery rate was calculated as the q value for

PCR results. Statistical trends were denoted by q <0.1 and significance levels were set at q<0.05.

Results

Exercise treatment induces expression of ISGs and TLRs

In order to determine whether exercise alone without infection may impact Type I IFN gene expression and/or expression of genes considered to be downstream of IFN, qPCR was performed on mouse lung tissue collected from EX and NON-EX mice (Table 1, Figure 1). Lung tissue was collected 24 hours after the last exercise session and the results showed that exercise increased the expression of β2m ( β2-microglobulin) and GBP1 (Guanylate Binding Protein) with a trend towards upregulation of ADAR1, PKR (Eifak2 or Protein Kinase R), BST2 and

CXCL10. Though several genes downstream of type I IFNs were upregulated, IFN α2, IFN α4, 98

IFN β1 and transcription factors IRF7 and STAT2 were either decreased (IFN α2 was reduced significantly) or remained unchanged (IFN α4 and STAT2).

Lung TLR expression was measured by PCR microarray (Figure 2). Exercise treated aged mice expressed higher amounts of TLR3 (p= 0.057), TLR6, TLR7 and TLR8 (p < 0.05).

TLR9 was also increased approximately 2 fold but not significantly (p = 0.39).

Exercise reduces influenza viral load in aged mice

In order to determine if the observed changes in gene expression may be associated with reduced viral load following intranasal challenge with influenza, EX and NON-EX mice were infected with influenza (24 hours after the last exercise session). One day post-infection viral load was measured by qRT-PCR in lungs and BALF collected from mice (Figure 3). The log of viral load was compared between groups. Exercise reduced the viral load in BALF of old mice

(p<0.05) and lungs (p=0.42)

Exercise may alter the time course of ISG expression in response to influenza infection, but does not alter TLR expression at day 1 post infection

After EX and NON-EX mice were infected with influenza virus, ISGs were detected in the lungs by qRT-PCR at 6 hours, 12 hours and 24 hours PI (Figures 4A, 4B and 4C). To evaluate the effects of exercise, gene expression in EX infected mice was compared to NON-EX infected mice at the same time point. At 6 hours PI, the pattern suggested a general upregulation of ISGs in the EX mice relative to the NON-EX mice. However, by 12 and 24 hours post- infection, the majority of genes were expressed at similar levels in EX and NON-EX mice.

TLRs gene expressions were measured only at 24 hours PI (Figure 5) using qRT-PCR. There were no significant differences in TLR expression between EX and NON-EX mice at this time point. 99

Exercise reduces the concentration of cytokines and chemokines in aged mice

Cytokine and chemokine concentrations were measured in BALF of EX and NON-EX mice 24 hours after infection with influenza virus (Table 2). We detected reduced pg/ml concentrations of IL-1b, IL-2, IL6, KC, IP10 (p<0.07), and others such as G-CSF, IL-1a, IL2,

IL10, MCP1, MIG, MIP-1a, MIP1b, MIP2, RANTES, TNF α and VEGF were also decreased with EX, though they were not significant.

Exercise does not alter mucociliary clearance in aged mice

Ciliary beat frequency (CBF) was measured in tracheas from EX and NON-EX mice to test if the mucociliary escalator is altered with exercise. Tracheas from EX and NON-EX mice were collected and stimulated with the beta-agonist isoproterenol to stimulate ciliary beat frequency in epithelial cells. Ciliary beat frequency (CBF) was quantified per minute and represented in Figure 6. Although aged mice had reduced CBF relative to young mice, EX treatment did not restore CBF.

Exercise alters cell populations in mouse lungs and BALF

The total number and frequency of multiple immune cell sub-populations were detected by flow cytometry in lung tissues as well as cells obtained from BALF from EX and NON-EX mice. Cell population number and frequency was assessed prior to infection in mice as well as at one day post-infection. Cells were collected 24 hours after the last exercise session in non- infected mice. The number of cells was increased in the BALF and lungs of non-infected EX mice compared to non-infected NON-EX mice (Figures 7A and 7B). Cell numbers were increased for alveolar macrophages, constitutive and inflammatory monocytes, dendritic cells and neutrophils in lungs of EX mice (Fig 7C). In the BALF, plasmacytoid dendritic cell (pDC) cell numbers showed a trend towards an increase with exercise (Fig 7D). The percentage of the 100 cell populations in the lungs were assessed by the frequency of immune cells in EX and NON-

EX mouse lungs and BALF (Figs 8A and 8B). Exercise led to the increase in frequency of constitutive and inflammatory monocytes, dendritic cells and neutrophils in lungs of EX mice, though this did not change in BALF of the same mice.

Infection after exercise training alters cell populations in lungs and BALF

The total number and frequency of BALF and lung cell populations was assessed 24 hours post-infection. The initial difference in total cell counts between healthy uninfected aged

EX and NON-EX mouse lungs and BALF was no longer observed post infection (Figures 7A and 7B). While cell counts for constitutive monocytes remained increased in lungs of EX mice

24 hours PI (as compared to infected NON-EX mice at 24 hours PI), none of the other cell populations in lungs or BAL were different with exercise (Figures 7C or 7D). As before, the percentages of immune cells infiltrating the lung were calculated in lung tissue as well as BALF

(Figs 8A and 8B). The frequency of constitutive monocytes was increased with exercise in the lung (p<0.05) (as compared to infected NON-EX mice at 24 hours PI). In BAL, the percentage of inflammatory monocytes was reduced, but pDC and DC percentages were higher in EX mice.

Discussion

While exhaustive or intense exercise is detrimental for the immune response and increases the risk of infection, especially upper respiratory tract infections in athletes (155), moderate exercise has shown some benefits in young subjects. Most studies have elucidated the effects of acute exercise on the immune response to pathogens. Even less is known about how chronic, moderate exercise (that can mimic an active lifestyle in older adults) changes immune response and function. Although chronic exercise has been shown to have no effect in some disease models (142), we have previously reported that exercise reduces the influenza viral titer 101 and decreases sickness severity in mice (199). The purpose of this study was to determine the effects of moderate intensity chronic exercise on innate immunity of the lungs in healthy and influenza infected aged mice.

Aging is associated with immunosenescence – an impairment of the immune response to various stimuli. Loss of TLRs and their function have been reported (54, 117, 145, 182, 228) and many cell types are reported to be reduced in numbers and function. We discovered that in our model of uninfected aged mice, exercise may improve anti-viral host defenses due to the increases in gene expression of TLRs, β2-microglobulin, BST2 and GBP1 in lungs of healthy old mice. β2m is a component of MHC-I molecule and GBP1 is IFNγ-inducible and has anti-viral properties, though the mechanism has not been elucidated yet (9, 36). However, IFN α2 was reduced. Another study also found β2m to be increased in the liver of mice that were physically active/ exercised (215).

Total cell counts in the lungs and BALF were also higher in exercise mice, including a higher percentage of monocytes (constitutive and inflammatory), neutrophils and pDCs in the lungs. The increase in the total number of cells and pDCs could explain the increase in constitutive proteins such as TLRs, β2m and BST2. TLRs and β2m (as a component of MHC-I) are present constitutively on various nucleated cells. pDCs express constitutive levels of TLR7 and TLR9, and also the antiviral protein tetherin that is encoded by the BST2 gene (which is also constitutively expressed on plasma cells and mature B cells) (127). Lower TLR4 and CD16 expressions without any change in LPS stimulated cytokine production have been reported in exercise trained human subjects (54, 145), while natural killer (NK) cell activity was increased

(147). However, these studies were carried out ex vivo with peripheral blood mononuclear cells, while our results represent whole lung tissue from treated mice. To our knowledge, there are no 102 other studies that have reported changes in immune cell infiltration in lungs with exercise in uninfected healthy aged mice.

When viral load was measured in mice day 1 post infection, exercise decreased the viral load in lungs and BALF. This is consistent with our previous studies (199) and shows that the exercise-associated decrease in viral titer occurs early in the course of infection. However, at this same time point (1 day post-infection) the gene expression of TLRs and ISGs was not different between exercise and non-exercise mice. Only OAS1a was decreased in exercise mice when compared to non-exercise infected mice. Exercised mice had lower concentrations of cytokines such as IL-1b, IL-2, IL6; KC, IP10 and other chemokines as well. The total cell counts were also similar in both groups post infection, with a slight reduction in (frequency of) inflammatory monocytes with exercise. Only the number and percentage of constitutive monocytes were increased in exercise mice. These findings may suggest that exercise training minimizes the inflammatory response to infection given that EX mice had a reduced number of inflammatory monocytes recruited to the lungs 24 hours post infection and maintained a greater number of constitutive monocytes.

When type I IFN response was measured earlier in infection, the pattern of gene expression suggested an increase in ISGs at 6 hours post infection. Interestingly, IFN α4 was decreased at 6 hours post infection in exercise mice and decreased further, along with IFN α2 and

IFN β1 at 12 hours post infection, and then returned to baseline levels at 24 hours post infection.

The pattern suggests that exercise may cause an up-regulation in the innate defense proteins even earlier than expected, possibly prior to 6 hours post infection. Others have reported reduced total cellular infiltration in lungs of influenza infected mice at days 3 and 5 post infection, decrease in

IFN γ gene expression, shift in the expression of cytokines in the lung from a Th1 to a Th2 103 response and reduction in influenza M1 protein mRNA expression (137). However, the differences between the findings can be explained by the different exercise regimes utilized by the two groups, which could have a significant effect on the response to infection.

Since there was no difference between ciliary beat frequency of exercise and non- exercise mouse tracheas, we concluded that mucociliary clearance did not influence the amount of virus entering the lungs. Higher expression of TLRs, β2-microglobulin, BST2 and GBP1 in

EX mice prior to infection and the pattern of increase in ISGs at 6 hours post infection suggests that exercise may “pre-activate” the immune system for invading pathogens, possibly with the help of danger signaling or response to exercise as a physical stressor. Another explanation could be that the increase in PRRs and anti-viral genes may be inhibiting the replication of virus during the first few cycles of replication, or infiltration of neutrophils and monocytes with exercise may be clearing some virus during the first day of infection.

In summary these findings demonstrate that regular, moderate treadmill exercise does benefit mice that are infected with influenza virus by reducing the viral load in the respiratory tract and altering the immune response to its advantage. Regular physical activity could prove to be very advantageous for older adults, more so than short bouts of exercise which may or may not have any effects on response to natural infections or vaccinations (135).

104

Figures for Chapter 3

Table 1. Names, symbols and description of genes measured via PCR.

Symbol Description Adar Adenosine deaminase, RNA-specific B2m Beta-2 microglobulin Bst2 Bone marrow stromal cell antigen 2 Cxcl10 Chemokine (C-X-C motif) ligand 10 Eif2ak2 or Eukaryotic translation initiation factor 2-alpha PKR kinase 2 Gbp1 Guanylate binding protein 1 Ifi204 Interferon activated gene 204 Ifit1 or ISG56 Interferon-induced protein with tetratricopeptide or Ifi56 repeats 1 Ifit3 or Ifi49 Interferon-induced protein with tetratricopeptide repeats 3 Ifna2 Interferon alpha 2 Ifna4 Interferon alpha 4 Ifnb1 Interferon beta 1, fibroblast Irf7 Interferon regulatory factor 7 Isg15 ISG15 ubiquitin-like modifier Mx1 Myxovirus (influenza virus) resistance 1 Mx2 Myxovirus (influenza virus) resistance 2 Oas1a 2'-5' oligoadenylate synthetase 1A

Oas1b 2'-5' oligoadenylate synthetase 1B Oas2 2'-5' oligoadenylate synthetase 2 Stat2 Signal transducer and activator of transcription 2

105

Figure 1.

Fold change in mRNA expression with exercise 8

* 4 * + 2

1/2

Fold changeFold Ex/ No (log Ex - 2 scale) 1/4

* 1/8

Figure 1: Effect of exercise on mRNA expression of ISGs. Whole lung homogenates were obtained from uninfected mice and were tested for mRNA expression by quantitative Real Time

PCR. * indicates a significant effect of exercise (q value<0.05), + indicates trend (q value <0.1, p value <0.05).

106

Figure 2

Fold change in mRNA expression with exercise 4

+ * * 2 *

1 Tlr1 Tlr2 Tlr3 Tlr4 Tlr5 Tlr6 Tlr7 Tlr8 Tlr9

0.5 Fold change Ex/ No Ex (log - Ex (log Ex/ No change Fold scale) 2

0.25

Figure 2: Effect of exercise on mRNA expression of TLR proteins. Whole lung homogenates were obtained from uninfected mice and were tested for mRNA expression by quantitative Real

Time PCR. * indicates a significant effect of exercise (q value<0.05), + indicates trend (q value

<0.1, p value <0.05).

107

Figure 3

Viral Load, Day 1PI 8 7.5 * 7 6.5 6 Old Ex Inf 5.5 Old Non Ex Inf Log viral titer viral Log 5 4.5 4 BAL Log viral titer Lung Log viral titer

Figure 3: Viral load in BALF and lungs of young and old mice day 1 after infection with influenza virus. Viral load was detected by quantitative PCR for influenza NP protein. Statistical significance was determined by one-way ANOVA, * indicates a significant (p<0.05) effect of age.

108

Figure 4A

Fold change (Old ex /Old non ex) 6 hrs PI 4

1/2 +

1/4 Fold changeFold Old Ex/ No (log ex - 2 scale)

1/8

109

Figure 4B

Fold change (Old ex / Old non ex ) 12 hrs PI 4

1/2

1/4 + Fold changeFold Old Ex/ No (log ex - 2 scale) 1/8

110

Figure 4C

Fold change (Old ex / Old non ex ) 24 hrs PI 4

1/2

1/4 * Fold change Old ex/ No ex (log -(log ex No ex/ Old change Fold scale) 2

1/8

Figure 4A – 4C: Effect of exercise on mRNA expression of type I IFN and ISGs in infected mouse lung homogenates. Whole lung homogenates were obtained from mice infected with influenza and tested for mRNA expression by quantitative Real Time PCR. The fold changes presented were calculated as the fold change of old exercise mice compared to old non exercise mice at the same time point post infected. This was calculated and comparisons are presented for

(4A) 6 hours, (4B) 12 hours and (4C) 24 hours post infection. * indicates a significant effect of exercise (q value<0.05), + indicates trend (q value <0.1, p value <0.05).

111

Figure 5

Fold change (Old ex / Old non ex ) 24 hrs PI 4

1 Tlr1 Tlr2 Tlr3 Tlr4 Tlr5 Tlr6 Tlr7 Tlr8 Tlr9

1/2 Fold change Ex/ No Ex (log -(log No Ex Ex/change Fold scale) 2

1/4

Figure 5: Effect of exercise on mRNA expression of TLRs in infected mouse lung homogenates.

Whole lung homogenates were obtained from mice infected with influenza and tested for mRNA expression at 24 hours post infection by quantitative Real Time PCR. The fold changes presented were calculated as the fold change of old exercise mice compared to old non exercise mice at the same time point post infected. * indicates a significant effect of exercise (p value<0.05), + indicates trend (0.05

112

Table 2

EX NON EX Cytokine Infected Infected p (pg/ml) (pg/ml) value G-CSF 382.183 447.957 IL-1a 97.9888 114.014 IL-1b 21.8875 29.7 + IL2 12.2675 16.28 + IL6 1288.31 2173.54 + IL10 33.1386 38.309 KC 956.043 1447.06 + IP10 745.433 1112.88 + MCP1 316.508 410.586 MIG 331.183 380.502 MIP-1a 34.6171 39.552 MIP1b 156.82 159.926 MIP2 168.912 173.764 RANTES 30.4817 34.338 TNFa 29.9533 25.012 VEGF 84.764 156.49

Table 2. Cytokines and chemokines were measured using Bioplex assay. Concentration of protein levels in BALF are presented for exercise (EX) infected and non-exercise (NON EX) infected groups at day 1 post influenza infection. + denotes significant trend effect of exercise

(0.05

113

Figure 6 Baseline

20 Stimulated with Beta Agonist

) 15 z H (

F B

C 10

5 Young Old Old + Exercise

Figure 6: Ciliary beat frequency (CBF) was calculated in the trachea of young mice, old mice and old exercise mice. The baseline CBF and CBF after stimulation with beta agonist are shown.

* indicates a significant effect of exercise (p value<0.05), + indicates trend (0.05

114

Figure 7A

Total Live cells in Lungs 160000 * 140000

120000

100000 Old Ex Infected

80000 Old Infected Old Ex NI

Number of of Numbercells 60000 Old NI

40000

20000

0 Live cells

115

Figure 7B

Total Live cells in BALF 16000

14000

12000

10000 Old Ex Infected

8000 Old Infected Old Ex NI 6000

Number ofcells Number Old NI

4000

2000

0 Live cells

116

Figure 7C

Cell counts in Lungs 16000 * 14000

12000 * Old Ex 10000 Infected Old Infected 8000 * Old Ex NI 6000 * Number of cells of Number Old NI 4000 * *

2000

0 Inflammatory Neutrophils DC pDC Constitutive Alveolar Monocytes monocytes Macrophages

117

Figure 7D

Cell counts in BALF 2000 * 1800 1600 1400

1200 Old Ex Infected 1000 Old Infected 800 Old Ex NI Number of cells of Number 600 Old NI 400 200 0 Inflammatory DCs pDC Alveolar Monocytes Macrophages

Figure 7A – 7D: Cell populations were detected in BALF and lungs of mice using flow cytometry. Total numbers of live cells are shown in (7A) lungs and (7B) BALF of uninfected mice and infected mice at day 1 post influenza infection. (7C) shows the cell counts of inflammatory monocytes, neutrophils, DC, pDC, constitutive monocytes and alveolar macrophages in the lungs of mice and (7D) shows cell counts for inflammatory monocytes, DC, pDC and alveolar macrophages in BALF of mice. Statistical significance was determined by one-way ANOVA, * indicates a significant effect of age (p value<0.05), + indicates trend (0.05< p <0.1).

118

Figure 8A

Frequency of cell populations in Lungs 14 * 12 *

8 Old Ex Infected Old Infected 6 Old Ex NI

Percentage Percentage of cells Old NI 4

0 Inflammatory Neutrophils DC pDC Constitutive Alveolar Monocytes Monocytes Macrophages

119

Figure 8B

Frequency of cell populations in BALF 20 18 16 14 12 + Old Ex Infected 10 Old Infected 8 Old Ex NI

Percentage of cells of Percentage 6 Old NI 4 2 0 Inflammatory DCs pDC Alveolar Monocytes Macrophages

Figure 8A – 8B: Cell populations were detected in BALF and lungs of mice using flow cytometry and cell frequencies were calculated as the percentage of total live cells for each population. (8A) shows the cell frequencies of inflammatory monocytes, neutrophils, DC, pDC, constitutive monocytes and alveolar macrophages in the lungs of mice and (8B) shows cell frequencies for inflammatory monocytes, DC, pDC and alveolar macrophages in BALF of mice.

Statistical significance was determined by one-way ANOVA, * indicates a significant effect of age (p value<0.05), + indicates trend (0.05< p <0.1).

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CHAPTER 4

ACUTE EXERCISE INDUCES A STRESS RESPONSE IN LUNGS OF MICE

Shibani Naik 1, Joseph Sevcik 2, Marian Kohut 1,2

1 Program of Immunobiology, Iowa State University, Ames, Iowa 50011; 2 Department of

Kinesiology, Iowa State University, Ames, Iowa 50011

Abstract

Exercise is considered to be a type of physical stress, and the effects of exercise stress on tissues such as cardiac or skeletal muscle are well documented. However, the effects of acute exercise stress on lung cellular response are not well understood. In addition to potential cellular stress, exercise via increased ventilation may expose the respiratory tract to pathogens. Although it is conceivable that pathways involved in cellular stress or pathogen recognition/response may be upregulated in the lung in response to acute exercise, the lung cellular defense pathway response to acute exercise remains largely unknown. The purpose of this experiment was to determine if exercise (acute and chronic) acts as a moderate stressor that could alter cellular defense pathways and immune cell populations in the lung. Mice were exercised for either 45,

90, or 180 minutes to compare effects of moderate and prolonged exercise. A separate group of mice exercised regularly (5 d/week, 45 min/day) for 8 weeks to determine whether regular exercise training results in adaptations in host cellular stress/defense pathways. Quantitative

PCR arrays were used to determine stress and toxicity pathways in whole lungs, and innate immune cell populations were identified in the bronchoalveolar lavage fluid and the lungs. 125

Acute exercise resulted in increased expression of heat shock proteins as well as several genes associated with regulation of inflammation. The expression of genes related to apoptosis was not generally altered with acute exercise, although Cdkn1a which may limit proliferation was increased after acute exercise. Chronic exercise training for 8 weeks resulted in a down- regulation of heat shock proteins, and did not change expression of genes associated with apoptosis or inflammation. Exercise training may cause a shift of CD45 positive immune cells from the BAL into the lungs as the CD45+ population decreased in the BAL, but increased in the lung. Also, exercise training was associated with a decreased number of inflammatory monocytes in the BAL, but an increased number of alveolar macrophages in the lung. Taken together, these changes may suggest that exercise training may promote an anti-inflammatory environment in the lung. It is possible that exercise training may cause the lung tissue to adapt to the stress and thus lead to a downregulation of heat shock proteins and control any inflammation that may be caused due to exercise. A shift in immune cells from BALF to lungs may explain our previous findings of reduced viral titer and decreased inflammation with influenza infection in exercise trained mice.

Introduction

Several forms of physical stressors may alter the immune system in several ways.

Exercise may be considered a physical stressor, along with traumatic injury, hypoxia, thermal injury and surgery (92). A single session of exercise (or acute exercise) alters the immune system in several different ways. Acute exercise leads to a mobilization of immune cells, as neutrophils, lymphocyte subsets – particularly CD8+ cells, and NK cells are increased in circulation during exercise and are either decreased or return to baseline levels shortly after exercise ceases (196). It has been hypothesized that lymphocytes are recruited to circulation from tissue pools such as the 126 spleen, lymph nodes, the gastrointestinal tract, and possibly the lung, yet are redistributed back into tissues either shortly after exercise or during prolonged and/or high intensity exercise.

However, the organs or tissues that these cells are redistributed to is not completely clear (170).

Lymphocyte proliferation in response to T cell mitogens phytohemagglutinin and concanavalin

A decreases during and immediately after exercise (159), although this may reflect the decrease in percentage or proportion of lymphocytes in tissue after recruitment to the blood. Current literature suggests that exercise induces an increase in the proinflammatory cytokines TNF-α, IL-

1β and IL-6 as well as cytokine inhibitors IL-1ra and TNF receptors (TNF-R) and the anti- inflammatory cytokine IL-10 in the serum, although these changes in cytokines are dependent upon duration and intensity of exercise (166). Also, the concentration of salivary IgA was reported to be reduced with prolonged physical activity in a number of studies. In general, the effects of exercise on immune cell responses vary with the intensity, duration and type of exercise. For example while moderate exercise improves neutrophil functions of chemotaxis, phagocytosis, and oxidative burst activity, some of these functions such as phagocytosis are not affected by extreme physical activity (165, 205).

Acute exercise leads to activation of the hypothalamic-pituitary-adrenal responses that impact the immune system (171). It increases the concentrations of a number of stress hormones in the blood, including epinephrine, norepinephrine, growth hormone, β-endorphins, testosterone, estrogen, and cortisol. The catecholamines epinephrine and norepinephrine are thought to regulate cell trafficking and recruitment into circulation during exercise for NK and

CD8+ cells. The plasma concentrations of cortisol and β-endorphins typically increase in response to prolonged and/or strenuous exercise and therefore may not play a role in immune modulation resulting from moderate duration moderate intensity exercise. 127

One session of acute eccentric exercise may increase the antibody response to vaccination, although this has not been a consistent finding and the mechanisms are not identified (47). The type, amount and duration of exercise that could be used as an “adjuvant” for vaccinations are still unclear. Previous experiments in our lab have suggested that chronic exercise training as well as a single session of acute exercise decrease lung viral load when exposure to virus occurred after the exercise session. These previous findings raise the possibility that exercise may act as a moderate stressor, potentially upregulating the ability to respond to other stressors such as infection. However, the effects of acute exercise or exercise training on lung cellular stress pathways, and/or innate host defense pathways remains unknown.

Therefore, the purpose of this experiment was to determine whether exercise (acute and chronic) induces a stress response and expression of “danger signals” in the lungs of mice. In addition, we examined whether exercise might alter the number and type of immune cell subpopulations found in either the bronchoalveolar lavage fluid (BALF) or the lung. The stress response was evaluated by detection of relevant genes associated with apoptosis, inflammation and heat shock proteins (HSP) using quantitative Real Time PCR on whole lung homogenates obtained from mice.

Materials and Methods

Animals and exercise procedure

Adult BALB/c mice (4-6 months of age) were obtained from Jackson laboratories and randomly assigned to the following groups: No exercise (0-ex), single session 45 minutes of exercise (45-ex), single session 90 minutes of exercise (90-ex), single session 180 minutes of exercise (180-ex), and chronic exercise training (EX). The mice in the EX group were exercise- 128 trained on a treadmill for 8-10 weeks. Exercise duration was gradually increased during weeks 1 to 4; from weeks 5 to 8, mice ran 40–45 min/day; then 45 min/day for the remainder of the training period. Speed progressed from 8 m/min during week 1 to 18 m/min by week 8. The

NON-EX group did not exercise. The exercise-trained mice were euthanized 24 hours after their last bout of exercise. The single session exercise groups ran on the treadmill for their group’s respective time (45 minutes, 90 minutes and 180 minutes) and were euthanized within 15 minutes post exercise. All animal procedures were approved by the Institutional Animal Care and Use Committee (IACUC).

Tissue collection

Mice were euthanized by cervical dislocation and lung lobes were collected for RNA isolation and flow cytometry. BALF was collected by inserting a catheter attached to a syringe through an incision in the trachea, and airways were flushed three times with 1 mL of PBS. The

BALF was centrifuged, cells were collected for analysis by ﬂow cytometry, and the supernatant was stored at -80 °C until subsequent analysis. RNA was isolated using TRIzol Reagent

(Invitrogen, Carlsbad, California). Lung RNA was further purified using the RNeasy Micro Kit

(QIAGEN, Valencia, California) then frozen at -80°C until further testing was carried out by

PCR. qPCR and PCR Microarray

Five hundred ng of purified lung mRNA was analyzed for stress and toxicity pathways gene expression using the 96-well Stress and Toxicity Pathway Finder RT² Profiler™ PCR Array

(SABiosciences, Frederick, Maryland) and protocol provided with the array (n= 4 to 5). Samples were analyzed using the BioRad MyiQ PCR system and Optical System Software Version 1.0. 129

GAPDH, beta actin, Hypoxanthine-Guanine Phosphoribosyltransferase and beta galacturonidase were used as the reference housekeeper genes.

Identification of Lung Cell Populations by Flow Cytometry

Cell populations were determined in BALF from 0-ex, 45-ex, 90-ex, 180 ex groups and in BALF and lungs in the EX group and 0-ex controls (n= 8 to 10). Live cells were gated by comparing forward scatter with side scatter and deselecting the cells with low forward and side scatter. Lungs were homogenized in collagenase containing media and single-cell suspensions of lungs were obtained using a 40µm cell strainer. Alveolar macrophages (Highly autofluorescent,

CD11c high, CD11b low, Gr1 negative), constitutive monocytes (CD11b positive, Gr1 negative), pDCs (CD11b low, CD11c intermediate, mPDCA positive, low autofluorescence), neutrophils

(CD11c negative, CD11b positive, Gr1 high, high side scatter), and inflammatory monocytes

(CD11b positive, Gr1 high, CD11c negative, low side scatter) were identified in cells obtained from whole lung homogenate and BAL. Expression of CD45 was used to identify cells as leukocytes or non-leukocytes. Flow cytometry was performed using a FACSCanto flow cytometer. FlowJo 7.6 software was used for gating and analysis.

Statistical Analysis

All statistical analysis was performed using SABiosciences PCR Data Analysis software and SPSS Statistics 17.0. A one-way ANOVA was used to compare gene expression and immune cell populations for differences in response to each exercise treatment. In cases in which a significant main effect of treatment was found, Fisher’s LSD post-hoc comparisons were made. Statistical trends were denoted by p <0.1 and significance levels for all tests were set at p

<0.05. 130

Results

Heat Shock Proteins were up-regulated with acute exercise and down-regulated with chronic exercise

Acute exercise led to up-regulation of heat shock protein subunits Dnaja1, Hspa1b,

Hspa5, Hspa8, Hspb1, Hspd1, Hspe1, Hsp90ab1 and Serpine1 (Table 1). Several genes including

DNAJA1 and HSPA1B peaked 45 minutes into the exercise session. In general, the results indicated that there was a progressive increase in expression as exercise duration increased

(Hspa5, Hspa8, Hspb1, Hspd1, Hspe1, Hsp90ab1). In contrast, 8 weeks of exercise training resulted in a downregulation of multiple heat shock proteins (measured 24 hours after the last exercise session) (Table 1).

Apoptosis was not induced by acute or chronic exercise

Pro-apoptotic genes coding for Caspase 1 (CASP1), Caspase 8 (CASP8), Fas Ligand

(FASL), TNF receptor (TNFRSF1A), Bcl-2-associated X protein (BAX), TNF-related apoptosis- inducing ligand (TRAIL) and TNFR1-Associated Death Domain Protein (TRADD) were either unchanged or reduced with acute exercise (Table 2). However, the anti-apoptotic gene BCL2L1 was up-regulated by greater than 2 fold after 90 minutes and sustained the increase till 180 minutes of exercise. The CDKN1A gene encodes a potent cyclin-dependent kinase inhibitor which functions as a regulator of cell cycle progression at G1. This gene is strongly up-regulated by acute exercise, up to a 5.2 fold increase by 90 minutes. With respect to eight weeks of exercise training, apoptosis genes were generally unchanged, except for a trend toward increased expression of the anti-apototic gene BCL2L1. 131

“Controlled” inflammation may be induced after acute exercise, but was not induced with chronic exercise

Genes for cytokines and chemokines associated with inflammation were detected by PCR in mouse lungs (Table 3). The most consistent changes observed across acute exercise treatments were an increase in the expression of NF κB inhibitor NFKBIA, IL-6, and MIP-1a. With 45 minutes of exercise, a trend towards a decrease in IL-1β and IL-18 was found (genes associated with inflammasome activation). With prolonged exercise (180 minutes) MIP1 α, MIP1 β, IL-1α, and IL-6 expression increased, although the NF κB inhibitor NFKBIA was also significantly increased at this time. Following eight weeks of exercise training, none of the inflammatory genes were upregulated, and CSF2 showed a significant decrease in expression.

Expression of miscellaneous genes induced by exercise

As shown in table 4, expression of EGR1 (transcriptional regulator Early Growth

Response 1), MT2 (Metallothionein) and SERPINE1 (coding for Plasminogen activator inhibitor-1) mRNA were increased after acute and chronic exercise. NOS2 (Nitric Oxide synthase, inducible) and PCNA (Proliferating Cell Nuclear Antigen) were not induced by either acute or chronic exercise. NOS2 was down-regulated at 180 minutes of exercise.

Antioxidants were not up-regulated due to exercise

There were no observed changes in superoxide dismutase coding SOD1 and SOD2 genes, or glutathione peroxidases GPX1 and GPX2 with either acute or chronic exercise (Table 5).

Acute exercise alters cell numbers in BALF of mice. 132

Cell populations were detected using flow cytometry on BALF obtained from the mice

(Figures 1A – 1C). The total number of live cells decreased after 45 minutes of exercise relative to no-exercise treatment. However, 180 minutes of exercise resulted in a greater number of cells in the BALF. With respect to specific cell populations, the number and percentage of inflammatory monocytes tended to decrease with all durations of exercise, and constitutive monocyte percentage also tended to decline at all exercise time points. The only cell population that increased after 180 minutes of exercise was the alveolar macrophage population.

Chronic exercise increased immune cell numbers in lungs, but not in BALF

Cell populations were detected in lungs and BALF of mice that were trained for chronic exercise. Regular physical activity increased the live cell population in lungs of exercising mice which were mostly CD45 positive, which is a marker used to detect most immune cells (Figure

3A). Cell numbers were higher for inflammatory monocytes, neutrophils and dendritic cells in exercise mouse lungs. Alveolar macrophages were increased in the non-exercise control mouse lungs (Figure 3B). Cell numbers in BALF were higher in the non-exercise control group, and these were explained by an increase in CD45 negative cells (Figure 4A). CD45 positive (immune cells) were not different in BALF of exercise and control groups. The individual cell populations detected were also similar in both groups (Figure 4B).

Discussion

We discovered that in our model of acute exercise, heat shock proteins were expressed immediately after a single session of exercise, and increased in proportion to duration of exercise

(45 minutes, 90 minutes and 180 minutes of exercise). Pro-apoptotic genes were not expressed, with some genes such as TRAIL being down-regulated after 90 minutes of exercise. Consistent 133 with the idea of reduced apoptosis, anti-apoptotic gene BCL2L1 was up-regulated. Cyclin- dependent kinase inhibitor 1a (CDKN1A or p21), which is induced in response to DNA damage to halt cellular proliferation (57, 81) was also highly expressed with exercise, suggesting that exercise may signal the body to reduce cell division and channel the energy to burning fuel for exercise. Inflammation, which is another possible consequence of stress, was also tested by detection of cytokine mRNA. While a few such as CSF2 (GMCSF), IL18 and lymphotoxin α were not induced with exercise, cytokine mRNA for MIP1 α and IL-6 were up-regulated after 45 minutes of exercise and MIP1 β and IL1a were up-regulated after 180 minutes of exercise.

However, induction of NF κB inhibitor (NF κBIA) indicates that anti-inflammatory factors were also being up-regulated at the same time to control excessive inflammation (as is sometimes seen when inflammation is induced). Others have also suggested that the IL-6 response to exercise may serve an anti-inflammatory role. In summary, a stress response was induced in the lung tissue of exercising mice as shown by heat shock protein expression. This stress did not induce apoptosis or extensive inflammation, but may arrest cellular proliferation of lung cells.

When the effects of chronic exercise were tested 24 hours after the last exercise session, a stress response in the lungs was not observed. Instead, there was a down-regulation of HSP mRNA, which may be an adaptation to regular exercise training. Also, no significant increases in apoptosis-inducing mRNA or pro-inflammatory cytokine mRNA were found, which is consistent with previous data from our laboratory showing that exercise trained mice had lower levels of IL-1α and IL-1β cytokine concentration in BALF.

The antioxidant enzymes that were detected by PCR in this study, superoxide dismutase and glutathione peroxidase were similar in exercise and control groups, indicating that these were not induced in response to exercise. Results showing oxidative stress and activation of 134 antioxidants due to exercise have not been consistent and may require exhaustive exercise (98).

While this may be true in muscle tissue, whether it occurs in healthy lung tissue is unknown.

After acute exercise, we also saw some changes in mRNA expression of other genes such as EGR1, MT2 and SERPINE1. EGR1 (Early Growth Response) encodes for a nuclear protein that is a transcriptional regulator, responsible for activating genes required for differentiation and mitogenesis. Studies suggest this is a cancer suppressor gene (96, 153). This is interesting because exercise has been associated with decreased risk of cancer (70) and effective in managing the side effects of cancer treatment (65). The expression of EGR1 could be a mechanism for these observed effects of exercise with respect to cancer. MT2 codes for

Metallothioneins, which have the ability to bind various heavy metals due to a high content of cysteine residues. These proteins are transcriptionally regulated by both heavy metals and glucocorticoids. It is possible that glucocorticoids (such as cortisol) (118) induced by exercise stimulated the up-regulation of MT2 and it could function in removing any particles that may have been inhaled during the exercise session. SERPINE1 encodes a member of the serine proteinase inhibitor (serpin) superfamily, which is an inhibitor of tissue plasminogen activator

(tPA) and urokinase (uPA), and hence is an inhibitor of fibrinolysis. Why this gene would be induced in response to exercise and how it would affect the lungs is unknown and could be a subject of future studies.

The source of the stress induced by exercise was not identified in these experiments.

However, we observed that exercise does not induce apoptosis or extensive inflammation, and therefore, it is not likely that apoptotic or inflammatory pathways contribute to the HSP response. Other potential sources of stress could be physical stress on the lung tissue or factors such as inhaled particles during the treadmill exercise. 135

The data on cell populations in the BALF showed a pattern of decrease at 45 minutes of exercise that gradually increased to a level equal to or higher than the control group after 180 minutes of exercise. Whether this indicates a mobilization into the blood or a shift into the lungs is not clear as we do not have data on lung cell populations. We did observe that alveolar macrophage numbers were higher at 180 minutes of exercise as compared to the controls.

Alveolar macrophages can be anti-inflammatory by releasing prostaglandins, IL-4, IL-10 and transforming growth factor-β (TGF-β) (109, 251). Although these cytokines were not tested for by PCR, alveolar macrophages may be acting to control the inflammation that was indicated by the cytokine mRNA data. Exercise training in mice increased CD45 positive immune cell numbers in the lungs, but not in BALF. Immune cells could be moving from the BAL into the lungs, increasing the inflammatory monocytes, neutrophils and dendritic cell numbers in lungs of trained mice.

In conclusion, this study discovered that a single session of exercise induces a heat shock protein response in the lung tissue of mice. Other studies have shown an HSP response in other tissues such as skeletal muscle, heart and liver during the exercise session (189). Also ours is the first study to show that HSP response is actually down-regulated in the lungs 24 hours after exercise training, indicating an adaptation of the lung tissue over time, possibly to prevent over stimulation of the stress response. We also discovered that exercise does not induce an apoptotic or antioxidant response and may induce some inflammation in the lung during and immediately after a single session of exercise. An increase in alveolar macrophages may be a part of the inflammatory response and act to control excessive inflammation in the lungs. Higher CD45 positive immune cell numbers in the lungs after exercise training could help explain the resistance to certain diseases (such as cancer) that exercise is associated with. 136

Figures for Chapter 4

Table 1.

45 mins Ex 90 mins Ex 180 mins Ex Chronic Ex Gene Fold p- Fold p- Fold p- Fold p- Name change value change value change value change value Cryab 0.991 0.959 0.810 0.022 0.778 0.012 0.665 0.000 Dnaja1 2.100 0.004 2.019 0.054 1.585 0.104 0.673 0.060 Hspa1b 4.786 0.010 3.168 0.119 1.323 0.733 0.470 0.140 Hspa1l 1.326 0.075 1.042 0.706 0.980 0.825 0.924 0.953 Hspa4 1.435 0.000 1.188 0.185 1.421 0.005 0.733 0.005 Hspa5 1.469 0.002 1.515 0.038 1.630 0.008 0.586 0.001 Hspa8 1.718 0.018 1.747 0.038 2.015 0.006 0.474 0.004 Hspb1 2.399 0.002 2.332 0.076 5.707 0.006 0.780 0.238 Hspd1 1.405 0.064 1.549 0.092 2.203 0.009 0.602 0.016 Hspe1 1.616 0.005 1.550 0.097 2.621 0.025 0.832 0.107 Hsp90ab1 1.678 0.006 1.471 0.153 2.629 0.001 0.745 0.127

Table 1: Fold change in gene expression of Heat Shock Protein subunits of four exercise groups

– 45 minutes, 90 minutes, 180 minutes and chronic exercise each compared to no-exercise controls. Whole lung homogenates were tested for mRNA expression by quantitative Real Time

PCR. Fold change numbers greater than 1.5 fold and less than 0.67 have been highlighted. Fold changes in bold font indicate significance (p<0.05) and fold change numbers in italics indicate

(0.05< p <0.1).

137

Table 2.

45 mins Ex 90 mins Ex 180 mins Ex Chronic Ex Fold p- Fold p- Fold p- Fold p- Gene Name change value change value change value change value 0.01 0.02 0.28 0.05 Casp1 0.809 0.765 0.857 1.359 1 8 9 4 0.26 0.01 0.15 0.90 Casp8 0.892 0.789 0.853 0.965 1 7 8 2 0.26 0.42 0.40 0.45 Fasl 1.304 0.653 0.819 1.191 5 1 9 5 0.09 0.41 0.84 0.08 Tnfrsf1a 0.908 0.925 0.977 0.920 1 6 8 2 0.44 0.64 0.49 0.32 Bax 1.066 0.942 0.952 0.893 3 7 5 4 0.02 0.00 0.00 0.07 Bcl2l1 1.367 2.174 2.339 1.347 5 0 0 6 0.00 0.00 0.00 0.84 Cdkn1a 3.703 5.203 4.900 1.022 0 0 0 9 Tnfsf10/TRAI 0.04 0.00 0.00 0.45 0.709 0.478 0.558 0.941 L 5 4 5 4 0.25 0.09 0.19 0.62 Tradd 0.781 0.836 0.842 0.932 6 4 6 4

Table 2: Fold change in gene expression of apoptosis associated genes of four exercise groups –

45 minutes, 90 minutes, 180 minutes and chronic exercise each compared to no-exercise controls. Whole lung homogenates were tested for mRNA expression by quantitative Real Time

PCR. Fold change numbers greater than 1.5 fold and less than 0.67 have been considered. Fold changes in bold font indicate significance (p<0.05) and fold change numbers in italics indicate

(0.05< p <0.1).

138

Table 3.

45 mins Ex 90 mins Ex 180 mins Ex Chronic Ex Gene Fold p- Fold p- Fold p- Fold p- Name change value change value change value change value Ccl3/MIP- 1.621 0.074 2.706 0.066 3.416 0.008 1.353 0.114 1a Ccl4/MIP- 1.116 0.459 1.033 0.583 1.516 0.183 0.945 0.560 1b Csf2 0.966 0.882 1.025 0.764 0.913 0.197 0.551 0.015 Cxcl10 0.765 0.621 0.622 0.167 0.859 0.544 0.779 0.374 Il18 0.753 0.074 0.970 0.698 1.194 0.102 0.981 0.961 Il1a 1.135 0.278 1.117 0.303 1.543 0.017 1.285 0.000 Il1b 0.583 0.108 0.690 0.755 0.693 0.280 1.213 0.760 Il6 1.718 0.232 1.703 0.278 2.486 0.114 0.797 0.420 Lta 0.656 0.357 0.627 0.186 1.106 0.913 1.334 0.415 Mif 0.964 0.654 0.977 0.724 0.950 0.699 1.015 0.862 Nfkb1 1.104 0.017 1.030 0.551 0.999 0.918 0.997 0.967 Nfkbia 2.148 0.000 2.240 0.000 2.288 0.000 1.208 0.026

Table 3: Fold change in gene expression of genes associated with inflammation of four exercise groups – 45 minutes, 90 minutes, 180 minutes and chronic exercise each compared to no- exercise controls. Whole lung homogenates were tested for mRNA expression by quantitative

Real Time PCR. Fold change numbers greater than 1.5 fold and less than 0.67 have been considered. Fold changes in bold font indicate significance (p<0.05) and fold change numbers in italics indicate (0.05< p <0.1).

139

Table 4.

45 mins Ex 90 mins Ex 180 mins Ex Chronic Ex Gene Fold p- Fold p- Fold p- Fold p- Name change value change value change value change value Egr1 1.632 0.191 2.363 0.008 4.599 0.001 1.611 0.167 Mt2 1.659 0.069 2.344 0.005 6.221 0.019 1.408 0.143 Nos2 1.053 0.664 0.864 0.379 0.577 0.052 1.006 0.965 Pcna 0.916 0.423 0.949 0.370 1.034 0.683 0.775 0.055 Serpine1 2.921 0.001 2.819 0.001 2.430 0.003 1.548 0.091

Table 4: Fold change in gene expression of four exercise groups – 45 minutes, 90 minutes, 180 minutes and chronic exercise each compared to no-exercise controls. Whole lung homogenates were tested for mRNA expression by quantitative Real Time PCR. Fold change numbers greater than 1.5 fold and less than 0.67 have been considered. Fold changes in bold font indicate significance (p<0.05) and fold change numbers in italics indicate (0.05< p <0.1).

140

Table 5.

45 mins Ex 90 mins Ex 180 mins Ex Chronic Ex Gene Fold p- Fold p- Fold p- Fold p- Name change value change value change value change value Sod1 1.007 0.891 1.010 0.852 1.131 0.341 0.868 0.262 Sod2 1.188 0.162 1.003 0.682 0.941 0.506 1.051 0.611 Gpx1 0.966 0.839 1.120 0.140 0.967 0.719 0.785 0.031 Gpx2 0.998 0.915 0.736 0.050 1.197 0.191 1.082 0.507

Table 5: Fold change in gene expression of antioxidants in four exercise groups – 45 minutes, 90 minutes, 180 minutes and chronic exercise each compared to no-exercise controls. Whole lung homogenates were tested for mRNA expression by quantitative Real Time PCR. Fold change numbers greater than 1.5 fold and less than 0.67 have been considered. Fold changes in bold font indicate significance (p<0.05) and fold change numbers in italics indicate (0.05< p <0.1).

141

Figure 1A.

Total Live cells in BALF 18000

16000

14000

12000 No Ex 10000 45 mins Ex 8000 90 mins Ex Number of cells of Number 6000 180 mins Ex

4000

2000

0 Live

142

Figure 1B.

Cell counts in BALF 200 180 160 140

120 No Ex 100 45 mins Ex 80 90 mins Ex Number of of Numbercells 60 180 mins Ex 40 20 0 Constitutive Inflammatory Monocytes Monocytes

143

Figure 1C.

Cell counts in BALF 3000

2500

2000 No Ex

1500 45 mins Ex 90 mins Ex Number of cells of Number 1000 180 mins Ex

500

0 Alveolar Macrophages DC

Figure 1A – 1C: Using flow cytometry, cell populations were detected in BALF of mice that underwent a single session of acute exercise. Total numbers of live cells in BALF are shown in

(1A). (1B) shows the cell counts of constitutive and inflammatory monocytes in BALF. (1C) shows the cell counts for DC and alveolar macrophages in the BALF. Statistical significance was determined by one-way ANOVA, * indicates a significant effect of age (p value<0.05), + indicates trend (0.05< p <0.1).

144

Figure 2A.

Frequency of cell populations in BALF 30

20 No Ex 15 45 mins Ex

10 90 mins Ex 180 mins Ex

Percentage Percentage of live cells 5

0 Alveolar Macrophages DC

145

Figure 2B.

Frequency of cell populations in BALF 0.9 0.8 0.7 0.6 No Ex 0.5 0.4 45 mins Ex 0.3 90 mins Ex 0.2 180 mins Ex Percentage Percentage of Live cells 0.1 0 Constitutive Inflammatory Monocytes Monocytes

Figure 2A – 2B: Cell populations were detected in BALF and lungs of mice using flow cytometry and cell frequencies were calculated as the percentage of total live cells for each population. (2A) shows the cell frequencies of alveolar macrophages and DC, (2B) shows the frequencies for constitutive and inflammatory monocytes in BALF. Statistical significance was determined by one-way ANOVA, * indicates a significant effect of age (p value<0.05), + indicates trend (0.05< p <0.1).

146

Figure 3A.

Cell count in Lungs 6000 5000 4000 3000 Ex 2000 NE Number of cells of Number 1000 0 Live CD45 - CD45+

147

Figure 3B.

Cell counts in Lungs 500 450 400 350 300 250 Ex 200 NE

Number of of Numbercells 150 100 50 0 Alveolar Inflammatory Neutrophils DC Macrophages monocytes

Figure 3A – 3B: Cell populations were detected in lungs of mice that exercised regularly for 8 weeks. (3A) Total numbers of live cells are shown in lungs and (3B) shows the cell counts of inflammatory monocytes, neutrophils, DC and alveolar macrophages in the lungs of mice.

Statistical significance was determined by one-way ANOVA, * indicates a significant effect of age (p value<0.05), + indicates trend (0.05< p <0.1).

148

Figure 4A.

Cell counts in BALF 25000

20000

15000 Ex 10000 NE Number of of Numbercells 5000

0 Live CD45+ CD45 - Alveolar Macrophages

149

Figure 4B.

Cell counts in BALF 350 300 250 200 Ex 150 NE

Number of of Numbercells 100 50 0 Inflammatory Constitutive DC Monocytes Monocytes

Figure 4A – 4B: Cell populations were detected in BALF of mice that exercised regularly for 8 weeks. (4A) Total numbers of live cells are shown in BALF and (4B) shows the cell counts of inflammatory monocytes, constitutive monocytes and DC in the BALF of mice. Statistical significance was determined by one-way ANOVA, * indicates a significant effect of age (p value<0.05), + indicates trend (0.05< p <0.1).

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152

CHAPTER 5

SUMMARY AND CONCLUSIONS FOR THE DISSERTATION

It has been well established that aging modulates immune function in animal models, including mice. The mechanisms of this immune modulation are still being investigated, although most studies indicate an increased risk and susceptibility to infection, impairment and/or delay in response to certain pathogens (1). One consequence of this phenomenon which is also called immunosenescence is the reduced response to vaccinations in the elderly, especially to influenza vaccinations (73, 78). Influenza A virus causes infection in the respiratory tract of humans (and other animals such as mice, poultry, horses and swine). Apart from weakened vaccine responses, immunosenescence causes increased risk, susceptibility and severity of infections, increasing morbidity and mortality in aged hosts (38, 73, 222). Exercise is an intervention that has been found beneficial for general well-being and also in many illnesses and infections (201).

In this dissertation, we intended to examine the effects of age on innate immunity in mouse lungs, relevant to influenza infections. More specifically, the pathways specific for pathogen recognition, anti-viral type I IFN induction and inflammation were detected along with innate cell populations such as alveolar macrophages, neutrophils and monocytes in the lungs and bronchoalveolar lavage fluid (BALF) in BALB/c mice. We then continued to examine the same pathways and cell populations in lungs, in response to exercise training in aged mice. This enabled us to study the effects of exercise on the anti-viral immunity to influenza infections in aged lungs. Our final study was conducted in order to determine the stress response in the lungs caused by regular physical activity, if any, and how it differed from the stress response elicited by a single session of exercise. 153

In chapter 2, our studies demonstrated the alterations in the innate immune system with age in the mouse respiratory tract. While systemic inflammation has been reported in other healthy aged animal systems (8, 144), we discovered that inflammaging occurred in the lungs of old mice (prior to infection or illness). Age may alter the immune status prior to infection due to a decrease in few anti-viral genes such as ADAR1, β2m, PTX3 and PKR. Even though the TLR expression may not be reduced, decreased TLR adaptor proteins may reduce signaling and these could explain the decreased functions of TLR receptors reported by other groups.

Mice were then infected with influenza virus and the same pathways were studied early in the course of the infection. We observed that viral load is lower in lungs of old mice as compared to young mice, along with reduced activation of PRRs, inflammatory cytokines (IL1b,

TNF, IL6 and CCL2) and activation markers (such as CD80/86, Ly86) and a delayed activation of type I IFN response starting from 6 hours PI till 24 hours PI (as compared to young mice infected with the same dose of virus). The data obtained from flow cytometry showed reduced cell numbers in old mice in both lungs and BALF. These data, taken together, suggested that viral uptake into cells may be impaired with age and the delayed immune activation early in infection may lead to inefficient viral clearance in old mice later in the course of infection. Even though healthy aged mice had higher levels of inflammatory cytokine mRNA prior to infection, the fold change of mRNA for activation and inflammatory markers at day 1 post infection were lower in old mice. This study provided further evidence for immune impairments with aging with respect to the pathways of antiviral response that were studied.

In chapter 3 we demonstrated the effects of exercise in aged mice on the same pathways studied in chapter 2. Healthy (uninfected) mice that regularly exercised on a treadmill for 5 days per week, for 8-10 weeks expressed higher levels of TLRs and a few ISGs such as β2- 154 microglobulin, BST2 and GBP1 in lungs and lower IFNα2. Cell numbers were also increased in lungs and BALF of exercise trained mice. This could represent more initial immune activation

(or “pre-activation”) in physically active mouse lungs.

After the mice were infected with influenza virus, viral load was measured and the same innate immune pathways were compared in exercise and non-exercise mice at day 1 PI. Regular exercise reduced the viral load in respiratory tract of mice that were regularly exercised.

Although TLRs and ISG response was similar in both groups of mice at day 1 PI, the pattern of gene expression suggested a faster activation of IFN inducible genes. Cytokine and chemokine concentrations were also reduced with exercise in the infected mice. Cell populations were also very similar in the lungs at day 1 PI, with less inflammatory and more constitutive monocytes and pDCs in the lungs of exercised infected group of mice.

To determine whether the entry of viral particles was impaired due to exercise, the ciliary beat frequency (CBF) was calculated in the trachea. There was no difference between CBF of exercise and non-exercise mice, showing that the mucociliary escalator is not altered by exercise training and would not affect the amount of virus particles entering the respiratory tract.

This study proved that regular, moderate treadmill exercise did reduce viral load in the lungs at day 1 post infection. We hypothesized that this could be due to a “pre-activation” of the immune system in response to exercise as a stressor and/or activation of danger signals in the lungs. Another explanation could be that the shift in cell populations in the physically active mice may enable clearance of virus very early in the course of infection.

To investigate our first hypothesis that regular chronic exercise elicits a stress response in the lungs of mice, we decided to determine stress response in lungs of mice that exercised on a 155 treadmill for 8 weeks and in lungs of mice that underwent a single session of moderate acute exercise of increasing duration for comparison. These results were presented in chapter 4. Genes involved in the heat shock protein response, apoptosis, inflammation, antioxidants which are induced by stress were studied in this chapter. We discovered that acute exercise led to an increase in heat shock protein response that is proportional to the duration of exercise (45 minutes, 90 minutes and 180 minutes). Inflammation with IL1a, IL6 and MIP1 α was induced in the lungs, but inhibitor of NF κB was also induced to control inflammation. Although apoptosis was not induced with acute exercise, cell proliferation might be arrested, possibly in order to shunt energy away from these cell processes. In summary, a stress response was induced in the lung tissue of exercising mice as shown by heat shock protein expression. This stress did not induce apoptosis or extensive inflammation, but may arrest cellular proliferation of lung cells.

However, when the same genes were detected 24 hours after the last exercise session in trained mice, we did not notice a stress response in the lungs. In fact heat shock proteins were down-regulated, indicating that exercise training may cause an adaptation of the lungs to prevent over-stimulation of the stress response.

When cell populations were detected in the BALF and lungs using flow cytometry, our data suggested that acute exercise caused a shift of the cells from the BALF during exercise that gradually returned to the BALF as the duration of the exercise increased to 180 minutes. Chronic exercise increased the number of immune cells in the lungs, which is consistent with data presented in chapter 3 in aged mouse lungs. We concluded that immune cells could be moving from the BAL into the lungs, increasing the inflammatory monocytes, neutrophils and dendritic cell numbers in lungs of trained mice. This alteration in cell populations due to chronic exercise 156 could lead to more viral clearance when virus is introduced into the respiratory tract, leading to lower viral load, immune activation and inflammation in the lungs of exercising mice.

In conclusion, this dissertation demonstrated immunosenescence in aging and uncovered some of the mechanisms of innate immunity that are affected by advanced age. We established that regular moderate level of exercise is beneficial to aged hosts in case of a respiratory influenza infection. Our final study identified some pathways and alterations in cellular composition in the lungs that may be responsible for this observed phenomenon.

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181

APPENDIX

SUPPLEMENTARY DATA AND FIGURES

Figure 1A

BEI-Inactive virus infection 6

5.5

4.5

3.5 log viral titer viral log 3

2.5

2 Ex Inactive Non Ex Ex Inactive Non Ex Inactive Inactive

6 hrs p.i. 24 hrs p.i.

182

Figure 1B.

Active virus infection 9

log viral titer viral log 3

0 Ex Active Non Ex Active Ex Active Non Ex Active 6 hrs p.i. 24 hrs p.i.

Figure 1A and 1B. Twenty-four hours after the last exercise session, mice were infected via an intranasal route with influenza virus strain A/PR/8/34 (H1N1) at a dose of 163.84 HA units per

9.5 mouse (stock virus – HAU= 1024/0.05mL or 10^ /mLEID 50 diluted 1:6.25 in sterile saline).

Viral load was measured in the lungs using qRT-PCR. Figure 1A: Mice were infected with virus that was inactivated using BEI. No significant difference was seen in lung viral load of exercise and non-exercise mice. Figure 1B: Mice were infected with active/live virus.

183

Figure 2A

Lung Viral titer (UV Treated Virus)

6.00

++ 5.00 ++ + 4.00 Old NON EX

Log Viral Titer Viral Log Old EX 3.00 Young

2.00 6 hrs p.i. (Lungs) 24 hrs p.i. (Lungs) + indicates trend EX OLD > YOUNG (p < 0.1) ++ indicates trend EX < NON EX (p= 0.1)

184

Figure 2B

BALF Viral Titer (UV Treated Virus)

9.00

* 8.00

7.00 ++ * 6.00 ** Old NON EX

Log Viral Titer Log 5.00 Old EX 4.00 Young

3.00 6 hrs p.i. (BAL) 24 hrs p.i. (BAL)

++ indicates trend p=0.17 EX < NON EX * indicates YOUNG EX or NON EX (p<0.05) ** indicates EX < NON EX (p<0.05)

185

Figure 2C

6 hours PI Old Old Non Young Non Exercise Ex Ex Eotaxin 43.21 43.59 22.53 GCSF 144.67 769.23 112.17 GMCSF 47.50 32.06 18.91 IFNg 25.54 2899.54 159.28 IL1a 63.63 25.10 26.94 IL1b 22.83 18.36 31.17 IL2 32.36 5.10 11.35 IL5 13.45 15.93 4.20 IL6 694.16 351.11 460.70 IL9 212.31 156.10 251.65 IL10 10.85 107.67 3.29 IL12p40 26.89 3.43 11.52 IL12p70 25.12 10.49 8.88 IL13 21.80 43.30 17.43 IL15 19.87 11.02 4.55 IP10 3693.77 4510.01 2890.14 KC 453.09 336.50 325.67 LIF 2.44 55.31 27.22 LIX 601.33 147.69 188.66 MCP1 306.05 343.64 92.49 MCSF 17.60 12.46 7.36 MIG 2321.29 16888.70 6668.52 MIP1a 36.10 82.70 113.59 MIP1b 65.62 139.39 152.51 MIP2 100.40 91.49 132.11 RANTES 21.08 27.17 26.09 TNFa 7.64 14.53 13.66 VEGF 66.94 27.61 83.35

186

Figure 2D

Figure 2A and 2B. Influenza virus strain A/PR/8/34 (H1N1) was inactivated using UV treatment

(for a duration of 45mins). Twenty-four hours after the last exercise session, mice were infected via an intranasal route with influenza virus at a dose of 163.84 HA units per mouse (stock virus – 187

9.5 HAU= 1024/0.05mL or 10^ /mLEID 50 diluted 1:6.25 in sterile saline). Viral load was measured in the lungs (Figure 2A) and BALF (Figure 2B) using qRT-PCR. Cytokines were measured in the BALF at 6 hours (Figure 2C) and 24 hours (Figure 2D) post infection.

188

Table 1A.

Fold change Gene (Old EX/Old P Value Symbol Non-EX)

Bag1 0.82 0.026814 Cyp1a1 0.32 0.094080 Cyp2c40 2.39 0.324232 Dnajb1 1.7 0.044831 Dnajb5 0.69 0.033988 Fmo1 0.7 0.044786 Hopx 0.72 0.018355 Hspa1a 4.08 0.015297 Hspa4 0.82 0.083307 Hspa8 1.31 0.075035 Hspb2 0.74 0.054431

189

Table 1B

Gene Fold change Symbol with Age P Value Bag1 0.82 0.015410 Cat 0.7 0.090966 Cct8 0.84 0.094863 Clu 1.52 0.064710 Cyp11a1 7.67 0.168919 Cyp1a1 2.13 0.148812 Cyp2f2 0.46 0.010072 Dnaja1 0.58 0.030747 Dnaja4 1.25 0.037999 Dnajb9 0.77 0.002178 Dnajc9 1.14 0.042118 Fmo1 0.73 0.020719 Gpx2 0.7 0.052363 Hspa1l 0.82 0.028888 Hspb2 0.75 0.030528 Serpinh1 0.61 0.005115 Sod3 0.58 0.007833 Xdh 2.06 0.019852

Table 1A and 1B: RNA was isolated from non-infected lungs of Old Ex, Old Non-Ex mice and

Young Non-Ex mice. PCR array for Cellular Stress Responses was used to quantify changes in mRNA expression with exercise in aged mice (Table 1A) and with age (Table 1B).

190

ACKNOWLEDGEMENTS

I would like to express my deepest appreciation and gratitude to my research advisor Dr.

Marian L. Kohut for her strong support and guidance through this process. I would like to thank her for her acceptance of myself into her lab and for her willingness and enthusiasm to mentor me through this process. The skill set I have developed while working in her lab, including basic experimental design, quality data collection, statistical analysis, and oral and written communication, have shown vast improvements because of her support and efforts. In addition, her mentorship has been paramount to the success of many of the ideas presented here. Without her, this dissertation would have been impossible to complete.

I would also like to thank my committee members, Dr. Mark Ackermann, Dr. Joan

Cunnick, Dr. Peter Nara and Dr. Daniel Nettleton for contributing to the development in this work. They encouraged me to think and perform better at every step and were always willing and accessible to help me through this task. They have provided me with guidance in theory as well as practice and I am deeply grateful that they were willing to share their knowledge in their fields of expertise and took the time to mentor me when I needed it. Their constructive criticism and encouragement improved the quality of this work immensely.

I would like to thank my lab mates Justus Hallam, Susan Hodgkins and a previous member of our lab, Kristi Warren. I am also thankful to all the undergraduate researchers for their time and efforts that have contributed in some way to this dissertation. Finally, I would like to express my gratitude to my family - my parents Lt Col. Uday Naik and Mrs Ranjana Naik, my sister Avani Naik, her husband Anurag Prakash and daughter Zoya, and last but not least my 191 husband Siddhartha Agrawal. Their countless words of encouragement, unconditional love and support helped me through the task of completing this work.