Examining Host and Microbial Determinants of Pseudomonas aeruginosa and Staphylococcus aureus Induced Delayed Wound Healing

DISSERTATION

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

By

Sarah Buckler Chaney

Graduate Program in Veterinary Biosciences

The Ohio State University

2017

Dissertation Committee:

Daniel Wozniak, Advisor

Paul Stromberg

Sashwati Roy

Luanne Hall-Stoodley

Copyrighted by

Sarah Buckler Chaney

2017

ABSTRACT

Any breakdown of epidermal barrier function leaves the host susceptible to infection. The innate immune system is tasked with the ability to clear these infections and provide an environment that can progress through the remaining stages of wound healing. There is a growing population of both immune competent and immunocompromised individuals that develop non-healing soft tissue injuries. Consistent identification of opportunistic pathogens Pseudomonas aeruginosa and Staphylococcus aureus in chronic wounds has focused our attention on these bacterial species.

Specifically, these opportunistic pathogens often exist as sessile, aggregated communities within these wounds and are profoundly resistant to exogenous and host derived antimicrobials. Therefore, we hypothesized that P. aeruginosa and S. aureus are able to subvert the innate immune system leading to persistent inflammation and delayed wound healing.

The first part of this thesis investigates the host response to P. aeruginosa and S. aureus in a chronic porcine burn wound model. Previous work in our lab, established this model in collaboration with Drs. Shahwati Roy and Chandan Sen and other members of the Ohio State University’s Comprehensive Wound Center. In the establishment of this wound it was apparent that although epidermal wound healing was achieved after poly- microbial infection, there remained incompetence of the barrier function. Mono-species ii infections with P. aeruginosa and S. aureus or co-infections with both of these species had previously not been conducted in a chronic wound model using a clinically relevant species. We discovered that bacterial infection results in a host response unique to the infective bacterial species and additive pathologic effects were expressed when present together. Specifically, we were able to identify mono-species infection induced responses by the epidermis that recapitulate defining features of chronic wounds in humans.

Ultimately, this work generated a standardized histopathology grading rubric to evaluate changes in the host incited by experimental conditions such as infection or treatments.

In the second portion of this thesis, we investigated the hypothesis that human neutrophils could generate a bacterial specific response to P. aeruginosa or S. aureus in vitro. We further speculated that the mode of bacterial growth (i.e. biofilm or planktonic) would influence the neutrophil response. We showed that P. aeruginosa incites a robust pro-inflammatory response. In contrast, S. aureus blunted the neutrophil cytokine response. These bacterial specific responses were largely independent of the mode of bacterial growth. There were minor differences in immune regulatory cytokines and macrophage and lymphocyte chemoattractants between biofilm and planktonic grown P. aeruginosa.

Lastly, genetic determinants of fitness in P. aeruginosa were investigated using the chronic porcine wound model, transposon mutant library and deep sequencing technologies. We hypothesized that P. aeruginosa would employ a unique set of genes

iii when establishing chronic infection. We identified transposon mutants in several acute virulence factors that displayed enhanced growth in the wound. Coversely, most genes identified to be important in establishing chronic wound infection were hypothetical, involved in small molecule acquisition or environmental adaptation.

This thesis address the importance of bacterial infection in chronic wound development and the role of bacteria in subverting host immune responses. These studies demonstrate that the clinical outcome of delayed wound healing by either P. aeruginosa or S. aureus is dependent on mechanisms unique to either species. Co-infections with both bacterial species produces unique effects on the host (synergism). These studies implicate the need for bacterial specific interventions.

iv

ACKNOWLEDGMENTS

To the pigs that I have had the honor of working with and that have sacrificed their lives to the advancement of this scientific endeavor.

v

VITA

2004...... B.A., cum laude, Biological Chemistry,

Florida Atlantic University

2004-2006 ...... Research and Development Chemist,

CrossMatch Technologies

2010...... D.V.M., cum laude, University of Florida

2010-2015 ...... Veterinary Anatomic Pathology Residency,

The Ohio State University

2015...... Diplomate American College of Veterinary

Pathology (Anatomic)

2011 to present ...... Graduate Research Associate, Department

of Veterinary Bioscience, The Ohio State

University

PUBLICATIONS

S. Roy, H. Elgharably, M. Sinha, K. Ganesh, S. Chaney, E. Mann, C. Miller, S. Khanna, V. Bergdall, H. Powell, C. Cook, G. Gordillo, D. Wozniak, and C. Sen Mixed-species Biofilm Compromises Burn Wound Healing by Disrupting Epidermal Barrier Function. 2014, J. Pathol., 233(4):331-43. vi

S. Harshman, M. Hoover, C. Huang, O. Branson, S. Chaney, C. Cheney, T. Rosol, C. Shapiro, K. Huebner, V. Wysocki, M. Freitas. 2013. Histone H1 Phosphorylation in Breast Cancer. 2014, J. Proteome Res., 13(5):2453-67

FIELDS OF STUDY

Major Field: Veterinary Biosciences

vii

TABLE OF CONTENTS

ABSTRACT ...... ii

ACKNOWLEDGMENTS ...... v

VITA ...... vi

TABLE OF CONTENTS ...... viii

LIST OF TABLES ...... xi

LIST OF FIGURES ...... xii

CHAPTER 1: INTRODUCTION ...... 1

CHAPTER 2: HISTOPATHOLOGICAL COMPARISONS OF STAPHYLOCOCCUS

AUREUS AND PSEUDOMONAS AERUGINOSA EXPERIMENTAL INFECTED

PORCINE BURN WOUNDS ...... 22

2.1 ABSTRACT ...... 22

2.2 INTRODUCTION ...... 23

2.3 MATERIALS AND METHODS ...... 24

2.4 RESULTS ...... 27

2.5 DISCUSSION ...... 31

viii

2.6 ACKNOWLEDGEMENTS ...... 35

CHAPTER 3: THE IMMUNOMODULATORY ROLE OF PSEUDOMONAS

AERUGINOSA AND STAPHYLOCOCCUS AUREUS ON NEUTROPHIL CYTOKINE

RESPONSES ...... 45

3.1 ABSTRACT ...... 45

3.2 INTRODUCTION ...... 46

3.3 MATERIALS AND METHODS ...... 50

3.4 RESULTS AND DISCUSSION ...... 54

3.5 CONCLUSIONS ...... 64

CHAPTER 4. DETERMINANTS OF PSEUDOMONAS AERUGINOSA FITNESS IN

THE CHRONIC WOUND ...... 74

4.1 ABSTRACT ...... 74

4.2 INTRODUCTION ...... 75

4.3 MATERIALS AND METHODS ...... 78

4.4 RESULTS AND DISCUSSION ...... 81

4.5 CONCLUSIONS ...... 92

CHAPTER 5. DISCUSSION ...... 98

REFERENCES ...... 107

APPENDIX A: TN-SEQ DATA: DECREASED ABUNDANCE ...... 136

ix

APPENDIX B: TN-SEQ: INCREASED ABUNDANCE ...... 141

x

LIST OF TABLES

Table 1. Microscopic Evaluation Scheme of Healing Burn Wounds...... 36

Table 2. Microscopic Evaluation Scheme of Acute Inflammation...... 37

Table 3. Cytokine production from human peripheral blood derived neutrophils exposed to biofilm and planktonic grown P. aeruginosa and S. aureus...... 66

Table 4. Essential Genes of P. aeruginosa, PAO1, in the Porcine Burn Wound ...... 96

Table 5. Positively Selected Genes of P. aeruginosa, PAO1, in the Burn Wound ...... 97

xi

LIST OF FIGURES

Figure 1. Tissue Divisions for Microscopic Evaluation...... 38

Figure 2. Scoring of Inflammation in Infected Chronic Wounds...... 39

Figure 3. Inflammation of the Infected Chronic Wound...... 40

Figure 4. Quantification of Dermal Responses to Chronic Wound Infection...... 41

Figure 5. Dermal Responses to Infection in Chronic Burn Wounds...... 42

Figure 6. Quantification of Epidermal Responses to Chronic Wound Infection...... 43

Figure 7. Epithelial Responses of Infected Chronic Wounds...... 44

Figure 8. Bacterial Growth Kinetics in Roswell Park Memorial Institute Media...... 69

Figure 9. Pro-Inflammatory Cytokines Produced By Wound Pathogen Exposed

Neutrophils...... 70

Figure 10. Th1/Th2 Inducing Cytokines Produced By Wound Pathogen Exposed

Neutrophils...... 71

Figure 11. Bacterial Induced Neutrophil Cytotoxicity...... 72

Figure 12. IL-16 Production by Bacterial Stimulated Neutrophils...... 73

Figure 13. Bacterial Burden of Porcine Wounds with Bacterial Transposon Library

Infections...... 94

Figure 14. Healing Porcine Burn Wounds Infected with P. aeruginosa Transposon

Mutant Library ...... 95 xii

CHAPTER 1: INTRODUCTION

Chronic wounds are a public health concern with a heavy socioeconomic burden.

Individuals with significant co-morbidities (i.e. diabetes or obesity), prolonged immobility (i.e. bed bound patients) or advanced age are prone to the development of a chronic wound (Sen et al, 2009). However, surgical intervention from both medically necessary and elective procedures, battlefield trauma and burn patients are also susceptible to the development of chronic wounds (Menke et al, 2007). Therefore, the ever-increasing age, obesity and trauma-related wounds incurred by the global population coincides with an increase in the incidence of chronic wound development. This means that immune competent and immune compromised individuals are both at risk for the development of a chronic wound after soft tissue injury. Moreover, complications of chronic wounds may be severe and include, infection, sepsis, amputation and death

(Menke et al, 2007). These wounds can last months or years requiring frequent medical attention in both the hospital and community care setting. The purpose of this dissertation is to address gaps in our understanding of chronic wound development.

The prevalence of chronic wounds has been estimated to be 1-2% of the population in developed countries (Sen et al, 2009). That amounts to an estimated 6.5 million people with a chronic wound in the United States alone at any given time

(Lindholm and Searle, 2016). Of those afflicted with chronic wounds, ~15% have not 1 reached clinical resolution after one year (Lindholm and Searle, 2016). Estimating the total annual expenditure on wound care is challenging since numerous facilities and health care professionals are involved in this process. Current reports attribute ~3% of all health care expenditures to wound management (Lindholm and Searle, 2016). Even though these estimates are reported per underlying co-morbidity (i.e. pressure ulcer or diabetic foot ulcer) it is clear that total annual chronic wound care costs, irrespective of the underlying cause, is well over several billion US dollars per year (Sen et al, 2009;

Lindholm and Searle, 2016; Posnett et al, 2009). This is not surprising given that a staggering 27-50% of all hospitalized patients are in need of wound management (Posnett et al, 2009).

A primary clinical concern is identifying the factors that contribute to developing a chronic wound in order to design appropriate treatments and preventatives. Since it appears that nearly any soft tissue injury even in immune competent individuals has the potential to develop into a chronic wound an underlying etiology that unifies these complex clinical presentations is clinically desirable. Chronic wounds have an increased susceptibility to microbial colonization inherent to the long-standing loss of epidermal barrier function (Gallo and Hooper, 2012). Burn wounds have a compounded propensity to infection due to the loss of local tissue perfusion, resident immune cells and glandular secretions responsible for innate immune defenses (Plichta et al, 2014). Given the exposure of the epidermal surface to the environment, it should be of no surprise that a multitude of organisms are identified within chronic wounds over the course of healing.

In fact, using culture-dependent and –independent methods (i.e. 16s and shotgun

2 sequencing) wounds are found to be poly-microbial microenvironments containing numerous bacterial taxa (Rhoads et al, 2012; Dowd et al, 2008; Scali and Kunimoto,

2013; Sprockett et al, 2015; Hodkinson and Grice, 2015).

These findings have lead to controversy regarding the significance of bacteria in delaying wound healing (Bowler et al, 2001). There are some that believe microbial density [bacterial load/gram of tissue] is critical to determining the significance of bacterial presence and its contributions to infection and delayed wound healing (Robson et al, 1970; Raahave et al, 1986). A problem with this theory is the limitation of culture- dependent methods and samples, which often consist of superficial swabs (Hodkinson and Grice, 2015). Also the infective dose of some bacteria has not been clearly established; therefore, the role some microbes play in delaying wound healing is not clearly established (Kallstrom 2014; Grice and Segre, 2012).

Despite this argument, the well known pathogens Acinetobacter sp., Klebsiella sp., Aeromonas sp., Staphylococcus aureus and Pseudomonas aeruginosa are consistently identified within chronic wounds regardless of the inciting soft tissue injury

(Akers et al, 2014; Grice and Segre, 2012; Gjødsbøl et al, 2006). Thus, others have reasoned that it is the identification of a specific pathogen that determines its significance in contributing to chronic wound development (Danielsen et al, 1998; Madsen et al,

1996). Moreover, bacterial populations establish non-random mono-species niches within these wounds (Burmolle et al, 2010; Fazli et al, 2009). Specifically, S. aureus remains within the superficial wound while P. aeruginosa is present deeper in the wound bed

(Fazli et al, 2009). The presence of P. aeruginosa specifically has been linked to chronic

3 wounds that were larger than those that did not contain this bacterium and wound healing was more severely delayed (Madsen et al, 1996; Halbert et al, 1992; Gjødsbøl et al,

2006). Therefore, the role that specific pathogens play in altering the progression of wound healing to result in delayed closure is not clear and is still debated. A major focus of this dissertation is to identify mechanisms by which P. aeruginosa or S. aureus contribute to the development of a chronic wound.

P. aeruginosa is a Gram-negative bacilli capable of surviving in the natural environment (i.e. soil, water, plants) and in animals (i.e. human and veterinary species)

(Gellatly and Hancock, 2013). Infections with P. aeruginosa include keratitis, urinary tract infections, chronic wound infection, sepsis, and cystic fibrosis- or ventilator- associated pneumonia (Gellatly and Hancock, 2013). Acute infections follow a quick time course (hours to days) with local tissue invasion and systemic spread causing cytotoxicity and tissue damage (Coggan and Wolfgang, 2012). This rapid-onset cellular and tissue damage brings a threat of acute death. Chronic infections are characterized as localized infections with minimal cytotoxicity and morbidity is associated with persistent inflammation.

Staphylococcus aureus is Gram-positive coccus, also capable of producing a broad spectrum of diseases including those of both acute and chronic duration (Lowy,

1998). This opportunistic pathogen has adapted to the widespread use of antibiotics with the emergence of a methicillin-resistant strain (MRSA) associated with hospital-acquired infections (nosocomial) and increasingly with community-acquired infections (Otto,

2013). A significant proportion of the general population are carriers of this pathogen

4 making this a common and difficult infection to prevent (Wertheim et al, 2005; Foster,

2009). S. aureus strain USA300 has become one of the leading causes of community acquired infections (Thurlow et al, 2012). USA300 continues to show a hypervirulent phenotype in animal studies compared to most other MRSA strains (Li et al, 2009; Li et al, 2010; Montgomery et al, 2008). Human infections with USA300 primarily present in the skin although invasive disease such as bacteremia, pneumonia, osteomyelitis, endocarditis and necrotizing fasciitis are also sequalae to colonization and infection with this isolate (Talan et al, 2011; Seybold et al, 2006; Haque et al, 2007; Miller et al, 2005).

The preponderance of community-acquired infections that occur with this isolate highlights the ability of this pathogen to infect immune competent hosts. The success of the widely prevalent USA300 strain has been attributed to newly acquired genes, altered regulation of genes and mutations in core genes that all lead to enhanced virulence

(Thurlow et al, 2012).

While there have been numerous scientific advances in our understanding of the mechanisms of acute virulence in P. aeruginosa and S. aureus, there has been less success in defining the mechanisms by which these pathogens delay wound healing.

Validating in vitro work requires use of clinically relevant animal models that are able to faithfully recapitulate human disease. Unfortunately our understanding of human disease has been somewhat hindered until recently by the reticence to sample chronic wounds for microscopic analysis, in fear of hindering the already tenuous wound healing

(Panuncialman et al, 2010). However, a hyper-proliferative wound edge, marked inflammation and delayed re-epithelialization have been established as defining

5 microscopic characteristics (Golinko et al, 2009; Stojadinovic et al, 2013). Most animal models of chornic wounds fail to capture these features (Pastar et al, 2014). The remarkable nature of immune competent animals to successfully resolve soft tissue injury regardless of infection status has meant that animal models uncomplicated by co- morbidity can only sustain wounds for upwards of 2 weeks (Ganesh et al, 2015).In contrast, chronic wounds in humans can persist for months to years. Therefore, currently available animal models fail to reproduce key features and the complexity of human disease (Nunan et al, 2014; Pastar et al, 2014).

Nevertheless, small animal models are the mainstay of most wound healing studies to date. Due to the ease of handling, availability, cost, tools/molecular techniques available and familiarity to most researchers, rodent and lagamorph models are more commonly employed in wound healing research (Sullivan et al, 2001). These models include: rabbit ear ischemia, rat magnet ischemia-reperfusion, diabetic mouse, non- diabetic mouse incisional and burn wounds (Ganesh et al, 2015; Nunan et al, 2014).

However, there are marked differences between human and small animal skin anatomy and wound healing mechanisms. The most striking differences between small animals and humans include a dense hair coat, thin epidermis and dermis as well as healing by contraction (Sullivan et al, 2001). The pig has been increasingly used as a preclinical animal model for pharmaceutical research, valued for its marked similarity to human anatomy, physiology and immunity (Swindle et al, 2012; Sullivan et al, 2001). The recent use of porcine models in wound healing has included partial thickness excisional wounds and pig flap ischemia. With collaboration between the Dan Wozniak laboratory and

6 researchers at The Ohio State University’s Comprehensive Wound Care Center and

Center for Regenerative Medicine, namely, Shashwati Roy and Chandan Sen, a novel porcine chronic burn wound model was developed (Roy et al, 2014). The advantages of this model include: pig as a clinically relevant animal to model human disease, easy visualization of the wound for repetitive, non-invasive assessment, long-term multi- sample experiments conducted on a single animal. Porcine skin is the most similar to human skin regarding anatomy, physiology and immunology of any laboratory animal

(Sullivan et al, 2001).

Using the porcine wound model, we set out to investigate the host response to infections with P. aeruginosa, S. aureus or both bacterial species (Chapter 2). Although there have been numerous studies, in several iterations, of wound healing in small animal models using P. aeruginosa and S. aureus there remains a gap in our understanding of the host response to persistent bacterial infection and novel targets for therapeutic target.

Many of the studies conducted in small animal and porcine studies have narrowly focused on achieving re-epithelialization as a criterion for evaluating competent healing.

Resolution of cutaneous soft tissue skin injury by any insult requires prompt and coordinated cellular mechanisms aimed at regaining homeostasis. Classical wound healing occurs in phases and include: inflammation, tissue regeneration/proliferation and remodeling. Each of these phases are geared towards wound healing and are a result of very complex, tightly regulated and well-orchestrated processes (Schultz et al, 2011).

Thus, evaluation of a single wound parameter (epithelilization) is an oversimplification of

7 this complex process and it has been previously demonstrated that epidermal continuity does not necessarily achieve proper wound closure (Roy et al, 2014).

Since the focus of this dissertation is understanding and evaluating disruptions of normal wound healing, a brief overview of this process will be given here. Immediately after soft tissue injury, to control blood and fluid loss, hemostasis is accomplished by the deposition of fibrin and activated platelets (platelet plug). The network of fibrin also serves as a scaffold on which infiltrating cells can migrate into the site of tissue injury.

Neutrophils and subsequently macrophages respond to the tissue injury and migrate into the injured site, coordinating downstream cellular and molecular events. These white blood cells are also involved in removing cellular and necrotic tissue debris, thereby preparing the wound site for newly synthesized extracellular products and infiltrating cells. The formation of new tissue (regeneration) is characterized by the proliferation and migration of numerous cell types into the wound including fibroblasts and endothelial cells. An important feature of this phase is the deposition of collagen and other extracellular matrix components to form “granulation tissue”. Granulation tissue provides a platform on which keratinocytes can migrate to close the defect and re-establish an epithelial barrier. Re-epithelialization requires the proliferation and migration of surviving keratinocytes at the periphery of the wound and attachment to the underlying dermis. The structural integrity of this newly formed skin does not resemble that of normal skin and can remain susceptible to re-injury or trauma for extended periods of time after the initial insult. Return of structural integrity requires long-term remodeling of the dermal matrix with increasing organization and deposition of collagen fibrils.

8

Numerous cell types, including the anatomic site-specific constituents, hemostatic and inflammatory cells, and tissue matrix producing cells are critical for proper wound healing. Cross talk and integrated orchestrated cellular processes between these cells are involved in achieving proper wound healing (Schultz et al, 2011). Therefore, wound- healing studies should seek to evaluate all these components. Currently, wound healing research conducted in animals lacks a standardized method of evaluation using light microscopy to evaluate these parameters. Thus, comparisons between infections, treatments and published reports is challenging. We address this current gap in methodologies by establishing a broadly applicable, systematic rubric for histologic analysis of wounds in Chapter 2. By comparing acute wounds with healing and non- healing wounds in humans, there have been significant advances in understanding the disrupted or dysregulated cellular process that may account for delayed healing.

Chronic wounds are prone to repeat tissue injury and bacterial infection, which can perpetuate the influx of immune cells, pro-inflammatory cytokines and elevated levels of proteases (Frykberg and Banks, 2015). Proteases are important for tissue breakdown but require tight control to avoid excessive tissue degradation or molecules associated with wound healing. Protease inhibitors are balanced in acute wounds but in chronic, non-healing wounds tissue proteases exceed inhibitor concentrations (Lobmann et al, 2002; Liu et al, 2008; Muller et al, 2008). This imbalance between protease and inhibitor leads to degradation of growth factors, receptors and extracellular matrices

(McCarty and Pervical, 2013; Lazaro et al, 2016; Shah et al, 2012). Immune cells that infiltrate wounds are capable of producing reactive oxygen species that are potent

9 antimicrobials but can also cause secondary collateral tissue damage (McDaniel et al,

2013; Babior, 1994). This oxidant stress perpetuates the influx of inflammatory cells and protease excretion leading ultimately to delayed wound healing (Budzyń et al, 2011;

Schreml et al, 2010; Dhall et al, 2014). Oxidant damage in the chronic wound can also cause DNA damage and cell cycle arrest resulting in a premature expression of a normal process of cellular aging termed senescence (Telgenhoss and Shroot, 2005). The decreased replicative and stimulatory capacity of these pre-maturely aged cells in the wound environment delays wound healing (Stanley and Osler, 2001; Stephens et al,

2003; Telgenhoss and Shroot, 2005). Similar local disruptive effects on keratinocyte proliferation and differentiation have been noted in chronic wounds (Stojadinovic et al,

2008). Searching for a biomarker of non-healing chronic wounds has also revealed that these wounds have excessively high concentrations of cytokines (Shah et al, 2012; Gohel et al, 2008; Trengove et al, 2000; Beidler et al, 2009). The exact reason for these molecular and cellular deficiencies is the focus of intensive scientific investigation. Of note though is the central role the neutrophil has in secreting tissue destructive compounds that are poorly regulated in the chronic wound environment (Wilgus et al,

2013).

Specifically neutrophils are crucial to successful wound healing and serve to provide protection from infection, limit exuberant neutrophil/pro-inflammatory responses and help initiate the signal to switch from pro-inflammatory to anti-inflammatory cellular processes (Nathan, 2006). Neutrophils phagocytize bacteria, which are killed by granule contents such as proteases and antimicrobial proteins including cationic antimicrobial

10 peptides and metal chelator proteins or NADPH generated reactive oxygen species

(Amulic et al, 2012; Kolaczkowska and Kubes, 2013). People with inherent neutrophil defects are particularly prone to infection and display delayed wound healing (Nathan,

2006). The finding that uncomplicated wound closure is inhibited by excessive neutrophil responses highlights the need for the proper control and function of this cell in the wound

(Dovi et al, 2004; Martin et al, 2003). The consistent identification of robust neutrophilic inflammation in wounds that fail to heal begs the question: What is the stimulus for intense neutrophilic inflammation?

P. aeruginosa and S. aureus exist within the chronic wound as sessile, aggregates embedded in a extracellular matrix (Fazli et al, 2009; Krketerp-Moller et al, 2008). These aggregates are referred to as biofilms. In contrast, bacteria can otherwise live as free- swimming, single cells (planktonic). In the natural environment the biofilm lifestyle is protective against adverse conditions (Hall-Stoodley et al, 2004). In a host the biofilm lifestyle confers a unique recalcitrance to host derived and exogenous antimicrobials and immune clearance mechanisms (Hirschfeld, 2014). Astoundingly, the growth of bacteria as a biofilm can impart 10-1000 times more resistance to antimicrobials than the same bacteria grown under planktonic conditions (Mah and O’Toole, 2001; Stewart and

Costerton, 2003). Bacterial biofilms are also capable of resisting neutrophil clearance or have mechanisms of reducing recognition by the immune system. P. aeruginosa biofilms produce a potent cytotoxic compound, rhamnolipid, capable of inducing rapid death of adjacent neutrophils (Jensen et al, 2007). S. aureus produces the pore-forming toxins

Panton-Valentine leukocidin and leukocidin A/B, which are capable of inducing

11 neutrophil cell lysis (DuMont and Torres, 2014). Surface appendages of P. aeruginosa are lost in biofilm formation, thereby reducing immune cell recognition (Sadikot et al,

2005; Feldman et al, 1998). Therefore, we speculate that bacterial biofilms possess unique mechanisms to subvert the host immune response within soft tissues leading to persistent inflammation and contributing to delayed wound healing.

Histologically, it is clear that neutrophils are capable of migrating to the site of bacterial biofilms in the chronic wound setting (Fazli et al, 2011; Hurlow et al, 2016).

Laboratory grown biofilms of P. aeruginosa and S. aureus are both phagocytized readily by healthy human, peripheral blood derived neutrophils (Leid et al, 2002; Günther et al,

2009; Jesaitis et al, 2003; Hanke et al, 2013; Thurlow et al, 2011). However there is not a consensus about the bacterial biofilm or neutrophil fate after this interaction. Both P. aeruginosa and S. aureus have within their repertoire of virulence factors, mechanisms capable of neutrophil cytolysis (Jensen et al, 2007; Kobayashi et al, 2010; Dumont and

Torres, 2014). However, in vivo and in vitro data indicate that this interaction is much more complex. Jesaitis et al (2003) found that upon interactions with P. aeruginosa biofilms, neutrophils maintained the ability to degranulate and produce reactive oxygen species, although at a reduced level. The bacterial biofilm fate was not a focus of this study but biofilm bacteria were clearly apparent in the phagolysosome of these cells

(Jesaitis et al, 2003). Jesaitis et al (2003) also reported that while neutrophils were capable of infiltrating and phagocytizing P. aueringosa biofilms they retained a rounded morphology indicative of a non-motile state. In a mouse skin infection model though neutrophils were responsible for carrying phagocytosed bacteria to draining lymph nodes

12

(Hampton et al, 2015). Neutrophils at the site of S. aureus skin infections are capable of migrating to draining lymph nodes with S. aureus particles, and S. aureus is capable of survival within neutrophils (Hampton and Chtanova, 2016; Gresham et al, 2000). Thus, viable neutrophils are capable of leaving the site of infection after interactions with either

P. aeruginosa or S. aureus. Also, neutrophils exiting the site of infection with P. aeruginosa or S. aureus were later identified within draining lymph nodes and influenced adaptive immune responses (Hampton and Chtanova, 2016).

Although neutrophils are important in bacterial clearance they are also gaining recognition as modulators of local and adaptive immune responses (Leliefeld et al, 2015).

One mechanism by which this is accomplished is through the generation of cytokines

(Mantovani et al, 2011). Bacteria are able to augment neutrophil cytokine secretions to promote bacterial persistence (Wilson et al, 1998). Fewer studies have assayed the neutrophil cytokine response to infection with either P. aeruginosa or S. aureus. Due to differences in the species assayed or use of whole cell or secreted bacterial products

(conditioned media) direct consensus between studies has been challenging to ascertain.

These in vitro results also poorly correlate to animal studies, which have demonstrated a difference in cytokine production at the wound site, dependent on the infective bacteria

(Seth et al, 2009 a and b; Pastar et al, 2013). However, these experiments assay the global wound response. Since, neutrophils are the first line of defense at the site of tissue damage and infection we sought to investigate the immunomodulatory role of the neutrophil-bacterial interaction. Using a multi-plex enzyme-linked immunosorbent assay

(ELISA) we assayed the secreted cytokine responses of neutrophils to planktonic and

13 biofilm grown P. aeruginosa or S. aureus. We hypothesize that the neutrophil response would be dependent on the bacterial species and method of bacterial growth (i.e. planktonic versus biofilm). These studies aimed to address the current lack of understanding in how this host-microbe interaction could influence the local host response (Chapter 3).

Although understanding the host response to infection may lead to improved healing outcomes with improved interventions to bolster the host response there remains a critical need for preventing bacterial colonization and infection. The mechanisms deployed by invading bacteria to establish chronic infection are not clearly understood but could potentially be exploited as novel anti-microbial agents. P. aeruginosa is able to persist in extremely diverse, environmental conditions and produce clinical diseases of varied outcome (i.e. acute and chronic disease presentations). Surprisingly though, the genomes of clinical and environmental isolates of P. aeruginosa are highly conserved

(Wolfgang et al, 2003). The virulence factors that P. aeruginosa uses to infect the mammalian host are thought to be derived from those that are used to survive in the environment (Hilbi et al, 2007). Just as biofilm formation contributes to environmental resistance, biofilms are proposed to confer a persistent phenotype within the human host.

In fact, P. aeruginosa biofilm formation results in the differential regulation of 73 genes when compared to planktonic grown P. aeruginosa (Whitely et al, 2001). Therefore, we hypothesized that P. aeruginosa employs specific mechanisms to persist within the chronic wound. In Chapter 4, we use the porcine wound model and a P. aeruginosa

14 transposon mutant library with deep-sequencing technologies for an unbiased whole genome study of P. aeruginosa fitness determinants in the wound.

Most information about the virulence of P. aeruginosa has been derived from the study of pulmonary infections; chronic pneumonia that develops after acute infection episodes in cystic fibrosis patients (Sousa and Pereira, 2014). Clinical isolates from cystic fibrosis patients revealed that there is a marked phenotypic switch between early infecting bacteria and those isolated much later in a patient’s life (Sousa and Pereira,

2014). Chronic infection isolates are less inflammatory and less cytotoxic with changes in expression of flagellum and pili (adherence and motility appendages), type 3 secreted toxin, lipopolysaccharide alteration, alginate production and loss of lasR quorum sensing

(Cullen and McClean, 2015). Acute infection isolates retain the expression of these acute virulence factors (Coggan and Wolfgang, 2012). Thus, the expression of P. aeruginosa virulence factors is considered host specific and may very well also be dependent on the anatomic location of infection (Dubern et al, 2015). What follows is a brief review of P. aeruginosa virulence factors that are relevant to the later chapters presented in this dissertation:

Flagella and type IV pili: P. aeruginosa is a motile bacteria, facilitated by surface appendages flagella and pili. Flagellum is a single, polar rod that provides swimming motility in fluids and participates in chemotaxis (Sampedro et al, 2015; Alhazmi, 2015).

Pili are rod-like appendages with a role in twitching motility, a surface associated motility requiring adhesion and extension/retraction action of the pilus that pulls the bacterium along a solid surface (Burrows, 2012). Both bacterial appendages facilitate

15 surface adherence to epithelial cells and can initiate host immune responses important for acute virulence (Feldman et al, 1998; Kang et al, 1997). These appendages have been shown to be important to the establishment of biofilm formation and in particular the 3D structure characteristic of in vitro biofilms (Klausen et al, 2003; O’Toole and Kolter,

1998). Chronic pneumonia isolates from cystic fibrosis patients exhibit variable expression of motility and attachment mediated phenotypes conferred by these appendages (Deligianni et al, 2010; Mahenthiralingam et al, 1994).

Type 3 Secretion System: Type 3 secretion systems (T3SS) act like a hypodermic needle to inject toxins directly into host cells (Hauser, 2009). Toxins identified in P. aeruginosa to be secreted by T3SS include: ExoY, ExoS, ExoT and ExoU. ExoS and

ExoT act to alter actin cytoskeletal rearrangement (Barbieri and Sun, 2004). ExoU alters plasma membrane integrity through phospholipase activity. ExoY has minor roles in cytotoxicity (Cowell, 2005). The cytotoxic effects of these injected toxins are critical to acute infections and increases in patient mortality (Hauser et al, 2002). Down regulation of T3SSs are features of chronic infection and biofilm formation (Hogardt and

Heesemann, 2010).

Proteases: Several proteases are excreted by P. aeruginosa during acute infections and are responsible for inflicting tissue damage. Elastases, LasA (stapholysin) and LasB (elastase), are regulated by the quorum sensing systems and secreted via type 2 secretion systems into the extracellular environment (Gellatly and Hancock, 2013). These elastases can degrade opsonins, thereby preventing phagocytosis and mutations in this lasB attenuates virulence (Kuang et al, 2011).

16

Lipopolysaccharide (LPS): This outer membrane glycolipid serves several roles including antigenicity, initiating immune responses and exclusion of molecules from the environment (King et al, 2009). LPS is composed of a membrane bound anchor composed of a lipid and polysaccharide (lipid A), core polysaccharide, and an outermost variable region (O-antigen). The lipid A component binds to host cell receptors for the activation of pro-inflammatory cytokines and inflammation in the host (Akira et al,

2006). Laboratory grown P. aeruginosa display a different lipid A modification profile that is comparable to isolates from acute infection (Gellatly and Hancock, 2013).

Conversely, chronic cystic fibrosis pneumonia isolates display lipid A modifications that increase the isolates ability to induce a pro-inflammatory response and also correlates to increased severity of pulmonary disease (Ernst et al, 2007).

Iron Acquisition: Bacteria requires iron for growth. Hosts tightly regulate iron by binding iron to proteins. P. aeruginosa possesses mechanisms to acquire iron. Iron chelating molecules include siderophores (pyochelin and pyoverdine) and ferrisiderophores. The pirating of siderophores from co-habitating species can be utilized in poly-microbial environments (xenosiderophres). P. aeruginosa is also able to uptake host hemoproteins and reduce iron within the extracellular environment by phenazine compounds.

Pyoveridine is essential to acute infection in both burn wound and pulmonary infection rodent models (Cornelis and Dingemans, 2013). Similarly, mutations in ferrisiderophore uptake render P. aeruginosa avirulent (Takase et al, 2000). Pyoveridine also acts to signal the production of virulence factors, namely a protease and exotoxin A (Lamont et al,

2002).

17

Quorum sensing and Biofilm formation: Cell-to-cell communication between bacteria is referred to as quorum sensing, which is dependent on sensing population density and coordinating gene expression amongst the resident bacterial population (Lee and Zhang, 2014; Coggan and Wolfgang, 2012). Quorum sensing depends on self- produced diffusible small molecules (autoinducers), which accumulate locally within a niche as the population density increases or diffusion rates decrease (Lee and Zhang,

2014). At a saturation point, the secreted signaling molecules will interact with a receptor to activate gene expression. These community-associated regulators are important to cell survival, virulence regulation and biofilm formation (Lee and Zhang, 2014). Some cystic fibrosis isolates have been found to have mutations in some of the quorum sensing systems which conferred advantages to survival in chronic infection through reduction of virulence factor production and tolerance to amino acid limitation (D'Argenio et al,

2007).

Biofilms form after initial attachment, local proliferation and maturation and finally these cells are able to disperse, leaving the site of initial biofilm formation. Initial attachment requires surface adherence mediated by type IV pili, flagella and quorum sensing signals (Coggans and Wolfgang, 2012). Bacteria will then multiply to form microcolonies and express polysaccharides, encasing themselves in host and microbe derived proteins and extracellular DNA (Mann and Wozniak, 2012; Limoli et al, 2015).

P. aeruginosa produces several polysaccharides, including: Pel, Psl and alginate.

Although this is a simplified distillation of the factors important to biofilm formation the

18 remainder of this brief review will focus on the regulatory pathways important for the transition between planktonic and biofilm lifestyles:

cAMP/Vfr Signaling: A second messenger signaling molecule adenosine 3’-5’- cyclic monophosphate (cAMP) mediates acute virulence factor gene expression in planktonic bacteria through binding and activation of transcriptional regulator, Vfr

(Wolfgang et al, 2003). cAMP is produced by adenylate cyclases, the most productive of which is CyaB and is degraded by phosphodiesterase CpdA (Coggans and Wolfgang,

2012). CyaB is controlled by a chemotaxis-like chemosensory system (Chp) (Fulcher et al, 2010). The transcriptional regulator Vfr positively regulates over 200 virulence genes including type IV pilus, type 3- and type 2- secretion systems, numerous extracellular toxins and enzymes and quorum sensing systems (Suh et al, 2002; Wolfgang et al,

2003b). Vfr negatively regulates flagellar genes (Dasgupta et al, 2002). Mutations in cyaB or vfr attenuate P. aeruginosa virulence in an acute pneumonia model (Smith et al,

2004).

c-di-GMP Signaling: Another second messenger signaling molecule bis-(3’-5’)- cyclic dimeric guanosine monophosphate (c-di-GMP), controls the expression of the biofilm phenotype. Increases in c-di-GMP induce adhesins and exopolysaccharide (Pel and Psl) synthesis which are important for establishing biofilms (Coggans and Wolfgang,

2012). During chronic infection of cystic fibrosis patients, P. aeruginosa develops hyper- biofilm forming mutants that over express c-di-GMP (Drenkard and Ausubel, 2002).

These mutants are referred to as rugose small colony variants (RSCV). Biofilms generated by RSCVs have enhanced antibiotic resistance when compared to the isolate

19 from which they originated (Drenkard and Ausubel, 2002). This phenotype also displays decreased acute virulence factor expression (Almblad et al, 2015). The RSCV phenotype is believed to be selected for in the chronic infection of cystic fibrosis patient airways

(Smith et al, 2006; Starkey et al, 2009). Thus, c-di-GMP regulates biofilm formation, which may be important for persistent infection.

While the planktonic-biofilm dichotomy is linked to acute and chronic infection outcomes, respectively, it is important to note that these second messengers are expressed in a continuum (Valentini and Filloux, 2016). In the human host it is considered likely that the expression of ability to transition between both phenotypes is likely important to the establishment of infection (Furukawa et al, 2006).

It is clear that P. aeruginosa has a large and diverse arsenal of virulence factors that play an important role in pathogenicity. Most of these virulence factors have been validated in small animal acute infections models. Assaying isolates from chronic pulmonary infections in cystic fibrosis patients has indicated that several acute virulence factors may be selected against in the chronic infection setting (Cullen and McClean,

2015). However, chronic infection determinants are harder to investigate given the limited availability of chronic infection models. The aim of the transposon sequencing study presented here is to determine genetic determinants of P. aeruginosa fitness in establishing chronic infection in a clinically relevant animal model.

The overall goal of the work presented in this dissertation is to gain a better understanding of both host and microbial contributions to delayed wound healing. While significant advances have been made to define mechanisms by which P. aeruginosa and

20

S. aureus can subvert host immune cells and the dysfunction unique to chronic wound healing, gaps in our knowledge remain. We proposed to identify P. aeruginosa and S. aureus specific mechanisms of immune cell dysfunction that contribute to delayed wound healing to address these gaps. Chapter 2 presents work aimed at standardizing microscopic evaluation of the porcine host response to infection and correlating these findings to known human pathologies in the chronic wound. We also present the host specific responses unique to the infecting bacterial species. Chapter 3 presents work aimed at testing the hypothesis that biofilms of these bacterial species are capable of altering the neutrophil secreted cytokine response. Lastly, we focus on P. aeruginosa specific genetic determinants of fitness in the chronic wound. In Chapter 4, using transposon-sequencing of a mutant library in P. aeruginosa we approach this question with an un-biased whole genome query. The body of work presented here provides a better understanding of the unique mechanisms that differentiate P. aeruginosa and S. aureus in the chronic wound and subvert of host-immune cell responses. Although these factors result in similar outcomes clinically (delayed wound healing), the findings presented here highlight the need for species-specific approaches to designing antimicrobials or enhancing host immune responses.

21

CHAPTER 2: HISTOPATHOLOGICAL COMPARISONS OF STAPHYLOCOCCUS AUREUS AND PSEUDOMONAS AERUGINOSA EXPERIMENTAL INFECTED PORCINE BURN WOUNDS

2.1 ABSTRACT

Chronic skin wounds are a significant human health concern and are often complicated by infection with Pseudomonas aeruginosa and Staphylococcus aureus, particularly methicillin resistant S. aureus (MRSA). Translating the knowledge gained from extensive study of virulence mechanisms and pathogenesis of these bacterial species to new treatment modalities has been lacking in part due to a paucity of animal models able to recapitulate human disease. Our groups recently described a novel porcine chronic burn wound model for the study of bacterial infection; however, the histopathology of infection has yet to be described. The objective of this study is to describe the histopathology of this model using important human chronic wound bacterial isolates.

Porcine full-thickness burn wounds topically inoculated with P. aeruginosa strain PAO1,

MRSA S. aureus strain USA300 or both bacteria were used to define and quantify histopathologic lesions. The development of a systemic, well-defined rubric for analysis allowed for semi-quantitative evaluation of differences between infection groups.

Differences, including epithelial migration and proliferation, stromal necrosis, fluid accumulation and intensity and character of the innate and adaptive inflammatory cell responses were identified temporally between infection groups. Mono-species infected 22 wounds developed a hyper-proliferative wound edge. Co-infected wounds at day 35 had the largest wound sizes, increased amounts of neutrophilic inflammation, immaturity of the wound bed, and retention of necrotic tissue. Infection, regardless of species, inhibited wound contracture at all time points evaluated. Most importantly, this model recapitulated key features of chronic human wounds. Thus, this model will allow researchers to study novel treatment modalities in a biologically relevant animal model while monitoring both host and bacterial responses.

2.2 INTRODUCTION

Chronic wounds are a major health care concern worldwide with millions of people affected each year and annual treatment expenditure estimated to be several billion dollars (Lindholm and Searle, 2016). The increasing incidence of obesity, diabetes, nosocomial post-operative surgical infections, combat-related wound infections, and growing elderly population make wound care a significant public health concern.

Due to the multifactorial contributing factors and complexities of this microenvironment

(ie. ischemia, infection status, co-morbidities, immune status), developing an all- encompassing model is not realistic. However, to address and understand wound healing, numerous animal models of chronic wound healing have been developed (Ganesh et al,

2015). Bacterial persistence is considered a significant contributor to delayed healing with an astounding 60% of all chronic wounds show evidence of chronic bacterial infection. Staphylococcus aureus and Pseudomonas aeruginosa account for the most

23 common human wound bacterial isolates regardless of the initiating cause of soft tissue injury (Rhoads et al, 2012).

While the term chronic wound encompasses a broad range of disease and clinical presentations, the histopathology of human chronic wounds has some common microscopic features; the most detailed of which are a proliferative wound edge with hyperkeratosis and variably fibrotic wound bed with neutrophilic inflammation (Golinko et al, 2009). In contrast, the histopathology of animal models of chronic wounds are poorly characterized, which makes drawing parallels between human and model systems difficult. Also, a lack of consistent criteria to evaluate host healing and response to infection makes comparison between animal models challenging and experimentation redundant. We aimed to detail the histopathology of the host response to various bacterial infections using common human bacterial isolates in our newly described animal model.

The rubric developed here provides a means to evaluate future comparisons between treatment groups and infection types. Correlation to human pathology is also discussed.

2.3 MATERIALS AND METHODS

Animals. The Ohio State University’s Institutional Laboratory Animal Case and Use

Committee (protocol 2012A00000041-R1) approved all experiments. Female Yorkshire pigs weighing between 70 to 80 pounds were used in this study (n=11).

Bacterial Isolates. Pseudomonas aeruginosa strain PAO1 was obtained from the

Mathew Parsek Laboratory (Stover et al, 2000) and a spontaneous rifampicin mutation

24 was generated from overnight culture on tryptic soy agar (TSA) with 100μg/mL rifampicin. Staphylococcus aureus strain USA300 was obtained from the Network on

Antimicrobial Resistance in Staphylococcus aureus (NARSA, BEI Resources Repository,

NAID, NIH, Manassas, VA) and was grown on TSA plates or broth media.

Porcine Burn Wound Model. Porcine infections were carried out as previously described (Roy et al, 2014). A total of 108 CFU of P. aeruginosa (n=2, PA), S. aureus

(n=3, SA) or both bacteria (n=2, CO) in 250uL of PBS (1x) was inoculated into the wounds topically 3 days post full-thickness burning. Control wounds (CT, n=4) were topically mock inoculated with 1X PBS. Full-thickness, excisional wound biopsies

(oriented in the sagittal plane) were removed at days 7, 14 and 35 post-bacterial inoculation (PI) and placed in 10% neutral buffered formalin for >72 hours. Normal/non- burned skin (~1cm) from each side of the wound was included in the biopsy. Skin samples were adhered to wooden tongue depressors to maintain skin shape prior to fixation.

Tissue Processing and Imaging. Porcine tissues were paraffin embedded, sectioned

(5μm) and stained with hematoxylin and eosin (H&E). The slides were scanned with

Aperio Slide Scanner, Scan Scope XT, up to 40x resolution and viewed, analyzed and measured using ImageScope Software (Leica Biosystems, Buffalo Grove, IL).

25

Histopathology Evaluation. A systematic review of histologic lesions between infection groups followed a detailed rubric developed for various skin healing parameters as outlined in Table1 and Table 2, adapted from Meyers et al (1961). Refer to Figure 1 for depictions of the tissue divisions and locations of measurements. Tissue evaluation was undertaken using routine H&E staining and detailed descriptions on identification of each of the graded parameters is outside the scope of this paper.

The percent surface area occupied in each segment by immature granulation tissue or mature fibrosis, necrosis, blood, edema or fibrin and histiocytic/granulomatous inflammation or mineral was estimated as detailed in Table 1. A minimum of 10% of the lesion was required to be present in the section evaluated to reach a grade 1. Epithelial responses were measured as detailed in Figure 1B. The epithelial gap was measured across the exposed (lacking epithelium) wound surface as the distance between the tips of the migrating epithelium. Polymorphonuclear inflammation was evaluated using the parameters outlined in Table 2.

Statistics. Statistical analysis was performed with GraphPad Prism version 5.0b

(GraphPad, La Jolla, CA) and all graphical data is presented as a mean with standard deviation. Comparisons between infection groups were made with two-way ANOVA and

Bonferroni post-testing. Significance was set to p values <0.05.

26

2.4 RESULTS

Clinically, all pigs remained healthy and asymptomatic for systemic infection during the duration of the study. Key microscopic findings between experimental groups over the course of infection are presented here.

Inflammation. The early inflammatory response in infected wounds is primarily neutrophilic with fewer numbers of macrophages, eosinophils, or lymphocytes and plasma cells. Peak inflammation in all infected wounds occurred at day 14 post- inoculation (PI). Inflammation remained primarily neutrophilic at day 35 PI, focused at the superficial half of the wound and became increasingly more histiocytic deeper within the wound bed. In each group, neutrophils were largely absent beyond the level of the mid-dermis (follicular units) when measured in comparison to the adjacent, non-burned skin.

Neutrophils were present in all animals at day 7 PI and all toher inflammatory cell types were present in lesser numbers (i.e. eosinophils, macrophages, lymphocytes and plasma cells (Figure 2C)). The SA and CO groups contained mostly individualized neutrophils within the superficial wound bed with scattered areas of degenerate neutrophils (suppuration) at the wound surface while PA and CT wounds were coated with suppurative inflammation. Neutrophilic inflammation resolved over time in CT wounds with decreasing amounts at days 14 and 35 PI, corresponding to wound healing.

Abscess formation was only identified in PA wounds (Figure 3C) at day 14 PI.

Neutrophilic inflammation peaked in all infected groups at day 14 PI and coincided with a peak in histiocytic or granulomatous inflammation (Figure 2). Neutrophilic

27 inflammation in mono-infected groups was minimal by day 35 PI, corresponding to decreasing wound sizes. CO wounds had thick suppurative exudate at day 35 PI (Figure

2).

In all groups, including CT, macrophages and multinucleated giant cells were focused on large clear vacuoles, interpreted as free lipids released in the burning process.

Although differences in the number of macrophages or histiocytes were not appreciated between any of the experimental groups (including CT wounds) qualitative differences between these groups were apparent (Figure 2). Two morphologic subsets were noted: 1) foamy macrophages with cytoplasmic small caliber distinct clear vacuoles (Figure 3A), and 2) macrophages with amphophilic homogenous cytosol and multinucleated giant cells (Figure 3B). The latter phenotype frequently was focused on extracellular mineral, which was also deposited on collagen bundles with minimal associated inflammation

(Figure 2B). Mineral was primarily a feature of infected wound groups, versus CT wounds, and more prominent in SA infections. Although macrophage phenotypes described above were not graded separately, there was a trend towards lipid-laden macrophages in PA wounds and multinucleated giant cells predominating in SA wounds.

CO wounds contained a mixture of these phenotypes.

Eosinophils were not identified in CT wounds and were uniquely present in mono-species infected wounds (i.e. PA and SA wounds). Individualized eosinophils were present within SA wounds at day 35 PI, throughout all depths of the wound bed.

Lymphoplasmacytic nodules (Figure 3D) and foci of macrophages or multinucleated giant cells were also infiltrated by eosinophils of day 35 PI SA wounds. In contrast, PA

28 day 7 wounds contained eosinophils primarily clustered at the superficial wound bed adjacent to the re-epithelialized edge. Far fewer eosinophils were present within PA wounds at any other time point. Degranulation of these cells was not a feature in any of the wounds.

Lymphoplasmacytic inflammation was most prominent at day 35 PI (Figure 2C) in the infected wounds but not a prominent feature of CT wounds. This inflammation was highest in PA wounds compared to any other infected wound at day 35 PI. In all instances the lymphocytes and plasma cells formed discrete nodules but lacked germinal center formation and rarely the center of these lymphoid aggregates contained a sclerotic mass of collagen (Figure 2A).

Dermal Healing CT wounds exhibited prompt infiltration of the wound with granulation tissue, which remodeled to mature collagen concomitant with a decrease of the dermal wound size (contraction) over time. Contracture was taken as the total length of the wound bed measured from the dermis between the interface between normal dermal collagen and wound bed on either side (Figure 1A). Infected wounds retained necrotic tissue and were slower to infiltrate with granulation tissue at days 7 and 14 PI

(Figure 4). Wound contracture was larger in all infected wounds compared to CT wounds

(Figure 5B). CO wounds had elevated amounts of necrotic tissue at all time points when compared to all other groups.

Extracellular fluid is considered a function of dermal healing due the dependence of this feature on the presence of vascular components such as capillaries (blood supply) and lymphatics (drainage). Neovascularization/Vasculogenesis is dependent on a

29 supporting ground structure such as granulation tissue and collagen. Extracellular fluid was most consistently characterized in all wounds by perivascular or dissecting clear spaces with and without a slight pink tincture (i.e. protein). Extracellular fluid accumulations in infection groups remained comparable to CT wounds except for early

PA infections. PA wounds at day 7 PI showed large dissecting accumulations of protein rich edema with fibrinous exudate (Figure 5A).

Epithelial Response. Mono-infected wounds were largest and most significantly larger than CT wounds at days 7 and 14 PI (Figure 7A). By day 35 PI, CO wounds were the only infection group with significantly delayed wound healing. Normal skin thickness was measured in histologic sections in all pigs in this cohort at the most distant point from the wound and was calculated to range between ~30-50m which is in accordance with previous reports (Summerfield et al, 2014). SA and PA wounds maintained thicker wound edges over the course of infection when compared to CT and CO wounds (Figure

6). The average thickness across the epithelial tongue reached ~100µm and 150µm for

SA and PA infections (2x and 3x normal), respectively, as early as 7 days PI. PA wounds had the thickest epithelium of all the infection groups at days 7 and 14 PI reaching

~200µm (>4x normal). SA wounds edges were thickest at day 35 PI with the average thickness of the re-epithelialized segment calculated to be over 100µm and the thickest measurement at >350µm. Re-epithelialized segments of CT and CO wounds averaged

~70µm and between 72µm and 106µm, respectively (Figure 7B and 7C). Re- epithelialized sections in mono-infected wounds contained minimal amounts of compact

30 ortho- and parakeratotic hyperkeratosis and moderate to marked rete-peg formation

(Figure 6). These features were not considered separately in the evaluation of the tissue.

2.5 DISCUSSION

To the best of our knowledge this is the first detailed evaluation of the histopathology of infected, healing burn wounds in any pig model to date. Differences in wound healing parameters were demonstrated over the course of the chronic infection between different infective bacterial strains. Importantly, as will be discussed below, there are features of these wounds that recapitulate key features of human burn wounds regardless of inciting cause or co-morbidities, which have not been previously described in any animal model (Pastar et al, 2014 and Golinko et al, 2009).

Inflammation. No other animal model has been able to re-capitulate long-term (>30days) wound inflammation without significant host-comorbidity (i.e. diabetes) making this animal model an excellent system by which to study long-term effects of chronic neutrophilic inflammation on wound healing (Ganesh et al, 2015 and Metcalf et al, 2016 and Nunan et al, 2014).

While macrophage quantities were not discernably different, these cells exhibited differing phenotypes dependent on infective bacterial species. The significance of this observation is not clear. We speculate that the predominance of vacuolated macrophages in PA wounds and mineral associated and multinucleated giant cells in SA wounds may correlate to an altered activation state or physiologic demand as in vitro manipulation of

31 macrophage activation states alters cell morphologies (McWhorter et al, 2013 and

Gordon S, 2003).

The increased numbers of eosinophils in mono-species infected wounds, early in

PA infected wounds and late in SA infected wounds, is peculiar. Evidence of these cell types being identified in human chronic wounds is lacking but the importance of this cell type in wound healing and in the recovery from S. aureus and P. aeruginosa infection has been documented (Lee et al, 2010, Rodriguez-Fernandez et al, 2013, Linch et al, 2009,

Song et al, 1993). Further studies are needed to understand the significance of these findings.

Dermal Healing. As wounds heal, the removal of necrotic tissue is considered a pivotal event to aide in the clearance of inflammatory cytokines, nidi for bacterial infection, granulation tissue formation and epithelial migration. Retention of necrotic tissue is associated with delayed wound healing and chronic wound formation (Schultz et al,

2003). Since there is standardization of the initial amount of necrotic tissue inflicted in this animal model, increased amounts are proposed to be retained via the following mechanisms: altered immune cell responses (i.e. phagocytosis), delayed neovascularization (i.e. delivery of inflammatory cells, nutrients and oxygen) or lack of appropriate microenvironment for fibroblast maturity and differentiation. In this study,

CO wounds, compared with mono-infected or CT wounds displayed a greater amount of retained necrotic tissue and stromal immaturity and may have contributed to delayed re- epithelialization.

32

While specific mechanisms were not in the scope of this report, there is evidence to support that the bacteria used here are specifically able to alter stromal components and inflammatory cells and their responses. Human stromal cells are susceptible to soluble factors of both S. aureus and P. aeruginosa biofilms, decreasing cell differentiation, viability, migration and angiogenesis (Ward et al, 2015). The inhibition of stromal cells is anticipated to affect wound-healing parameters such as is present in this study (i.e. contraction, necrotic tissue accumulation, hemorrhage, and edema). It is clear by the total dermal wound size in each of the infection groups that the microenvironment did not allow for the same degree of contracture as seen in control wounds (Rose and

Chan, 2016; Darby et al, 2014). The degree of extracellular accumulation, unique to early

PA wounds may be of particular import to burn wound patients that are susceptible to hypovolemic shock (Tiwari, 2012). Further study is required in this area but this model may prove to be physiologically relevant to human chronic wounds and therefore increase the ability to study this unique microenvironment.

Epithelial Response. One of the key parameters defining chronic human wounds is a hyper-proliferative wound edge with hyperkeratosis (Golinko et al, 2009). This feature is rarely reported in current chronic skin wound animal models with more emphasis placed on re-epithelialization. Re-epithelialized sections of the wounds in this study displayed minimal amounts of compact hyperkeratosis, which was not equivocal to human chronic wound descriptions (Golinko et al, 2009). Using mono-infections with either SA or PA, the re-epithelialized wound edge reached 2-3x or nearly up to 4x normal skin thickness, respectively, within 7 days PI and this was maintained until at least day 14 PI. At no

33 point in the course of healing did CT wounds average a thickness above 2x normal.

Therefore, it appears that SA and PA have a dramatic effect on keratinocyte proliferation rates as well as an impedance to the migration of the keratinocytes as evidenced by delayed wound closure in the mono-infected groups at day 7 and 14 PI. Given our previous use of this model and determination of biofilm mode of growth of PA in that model we speculate that this response may be due to the specific biofilm mode of growth of these bacterial species (Roy et al, 2014).

Extracellular products from biofilms of S. aureus and P. aeruginosa have a significant effect on epithelial proliferation and migration in vitro (Marano et al, 2015). It is speculated that a similar mechanism may be produced in these porcine infections.

Marano et. al. (2015) identified that human epidermal keratinocytes were highly susceptible to cytolytic properties of the conditioned biofilm media of both bacterial species while at reduced concentrations there was inhibition of migration and proliferation. Others have identified S. aureus and P. aeruginosa specific factors that may enhance epithelial proliferation (Preciado et al, 2005 and Haugwitz et al, 2006).

Therefore, the effects seen here may not be specific to a bacterial mode of growth.

Surprisingly, the hyperproliferative wound edge was not present in CO wounds.

This may be a dose dependent phenomena however we consider this less likely given that the delay in re-epithelialization was of a similar magnitude at days 7 and 14 PI and even more pronounced at day 35 PI when compared to mono-infected wounds. Therefore, the effect of both of these bacteria together appears to reduce epithelial proliferation and migration.

34

The detailed evaluation of these wounds has shown great similarity to key features of the chronic human wounds, regardless of inciting cause. Importantly, the effects of bacterial infection on host responses were widespread (i.e. epidermal, dermal and inflammatory) and when conducting animal experiments for evaluation of treatment modalities and bacterial effects all parameters should be evaluated. The information gained from these studies will aide in evaluating the effect of interventions for both bacterial and host responses.

2.6 ACKNOWLEDGEMENTS

All animal work would not be possible without the aide and expertise of Jennifer

Dickerson. The Comparative Pathology & Mouse Phenotyping Shared Resource of The

Ohio State University, which is supported in part through an NCI Cancer Center Support

Grant P30 CA016058, performed Immunohistochemisty. Public Health Services grants

NR013898 and AI097511 (DJW) supported this work.

35

Grade 0 Grade 1 Grade 2 Grade 3 Grade 4 Inflammation Neutrophils* Mild Moderate Marked Severe Eosinophils* Mild Moderate Marked Severe Lymphocytes & Plasma 0 to 5 6 to 10 11 to 15 16 to 20 >21 Cells Organized Units Histiocytes/MNGC°/Mineral <10% 10 to 25% up to 50% up to 75% >80% Dermal Response Blood/Edema <10% 10 to 25% up to 50% up to 75% >80% Necrosis, stromal <10% 10 to 25% up to 50% up to 75% >80% Granulation Tissue <10% 10 to 25% up to 50% up to 75% >80% Characterized by fibroblasts and increased density of small caliber capillaries Mature Dermis <10% 10 to 25% up to 50% up to 75% >80% Characterized by mature, dense collagen and fibrocytes Dermal Wound Bed Measure Length Epithelial Response Epithelial Proliferation >3x or 2.5x 2x 1.5x ≤Normal healed thickness wound Epithelial Gap <40% Open Up to 40% Up to 60% Up to 80% >100% Table 1. Microscopic Evaluation Scheme of Healing Burn Wounds.

°Multinucleated Giant Cells, *Details provided in Table 2

36

Neutrophil Severity Grade 0 Scattered individual cells may be present in the wound but primarily intravascular/marginating or widely spaced within the wound Grade 1 Viable/non-degenerate neutrophils as individual cells within the wound. If suppuration is present it does not coat the surface or span the length of the segment being graded Grade 2 Variably thick suppurative inflammation that spans the length of the segment Grade 3 Dense consistent thickness of suppurative inflammation that spans the length of the segment and neutrophils present within the wound bed below are in small clusters or individual Grade 4 Large pools of suppurative exudate over the length of the segment with large numbers present in the underlying wound bed, mostly present in clusters. Abscess formation. Eosinophil Severity Scored based on the number of foci of clustered eosinophils or numerous individual cells, when viewed at 10x. Grade 0 Less than 10 foci Grade 1 11-20 foci Grade 2 21 to 30 foci Grade 3 31 to 40 foci Grade 4 >40 foci Table 2. Microscopic Evaluation Scheme of Acute Inflammation.

37

Figure 1. Tissue Divisions for Microscopic Evaluation. A) The total wound bed length (black ruler) was divided into 6 equidistant segments (oriented superficial to deep, grey dashed lines). The bounds of the wound bed are defined by the interface of normal dermal collagen and thermally injured tissue (black stars). Each segment (1-6) was evaluated using the scheme in Tables 1 and 2. The scores from each segment were averaged for a final wound score, per parameter. B) The epithelium covering the wound bed (epithelial tongue) was measured from the base (far left white arrow, #1) to the tip (grey arrow). Epithelial thicknesses were measured at 3 points from each side of the wound: #1) base (far left white arrow) #2) mid-point (middle white arrow) #3) epithelial tip (far right white arrow). Measurements were taken in areas in which there was a discrete stratum corneum formed (magenta line) but thickness measurements only included the stratum basale (dark purple) and stratum spinosum (light pink).

38

Figure 2. Scoring of Inflammation in Infected Chronic Wounds.

A) Pseudomonas infected wounds at 35 days post-infection (PI) contained organized lymphoplasmacytic nodules (arrows) within the dermal wound bed. Occasionally these nodules contained a central core of dense hylanized collagen (#). B) Staphylococcus infected wounds contained collagen bundles with mineral deposition (arrowheads) with minimal amounts of associated inflammation (multinucleated giant cell, arrow) at day 14 PI. C) Using the grading scheme outlined Table 1, the individual wound histology parameters were scored and averaged from 6 segments evenly distributed across the wound. Inflammatory parameters were scored 0-4 as outlined in Table 1 and Table 2. For the graph above, C: x-axis represents time points day 7, 14 and 35 post-infection; SA=Staphylococcus, PA=Pseudomonas, CO=Co-infected wounds and CT=Control wounds. The mean scores are graphed here with standard deviation error bars and statistical significance measured by 2-way ANOVA, p<0.05.

39

Figure 3. Inflammation of the Infected Chronic Wound.

Granulomatous and histiocytic inflammation did not vary in quantity over the course of infection but tended to accumulate around large clear vacuoles (free lipid, star, A and B, scale bar = 60μm). Pseudomonas infected wounds (PA) at day 14 post-infection (PI) contained foamy macrophages with small, discrete clear vacuoles filling the cell cytoplasm (arrows, A). Granulomatous inflammation of Staphylococcus infected wounds (SA) at day 14 PI centered on extracellular mineral (arrows, B, scale bar = 80μm ) with multinucleated giant cells (arrowheads, B). Abscesses only formed in PA wounds at day 14 PI (bounded by arrows, C, scale bar = 2mm). Eosinophils were present as individualized scattered cells in SA wounds at day 35 PI (clear arrows, D, scale bar = 50μm) or within organized lymphoplasmacytic nodules (*).

40

Figure 4. Quantification of Dermal Responses to Chronic Wound Infection.

Using the grading scheme outlined Table 1, the individual wound histology parameters were scored and averaged from 6 segments evenly distributed across the wound. Dermal response parameters were scored 0-4 as outlined in Table 1. For the graph above: x-axis represents time points day 7, 14 and 35 post-infection; SA=Staphylococcus, PA=Pseudomonas, CO=Co-infected wounds and CT=Control wounds. The mean scores are graphed here with standard deviation error bars and statistical significance measured by 2-way ANOVA, p<0.05.

41

Figure 5. Dermal Responses to Infection in Chronic Burn Wounds.

A) Pseudomonas infected wounds at day 7 post-inoculation (PA) contained marked amounts of proteinaceous edema (*) filling necrotic areas and cuffed by moderate amounts of hemorrhage (+). B) Infection, regardless of bacterial strain (red = Staphylococcus infected, green = PA, brown = Co-infected), delayed the contraction of the dermal wound bed compared to control wounds (black line). Graphed are mean measurements with standard deviation, statistical significance is considered at p<0.05 using 2-way ANOVA. x-axis represents time points day 7, 14 and 35 post-infection.

42

Figure 6. Quantification of Epidermal Responses to Chronic Wound Infection.

Using the epithelial measurements detailed in Figure 1 and Table 1, epithelial responses were analyzed by determining the wound size/epithelial defect with the size of the burning instrument indicated by the horizontal dashed line (A), the thickest point measured out of the 3 described in Figure 1 within the new epithelial tongues (B) and the average thickness across the epithelial tongue as measured by 3 separate, defined points (C). For all the graphs above: x-axis represents time points day 7, 14 and 35 post- infection; SA=Staphylococcus, PA=Pseudomonas, CO=Co-infected wounds and CT=Control wounds. The mean scores are graphed here with standard deviation error bars and statistical significance measured by 2-way ANOVA, p<0.05.

43

Figure 7. Epithelial Responses of Infected Chronic Wounds.

The re-epithelialized section of skin (wound edge) covering mono-infected wounds, Staphylococcus (SA) and Pseudomonas (PA) infected wounds (rows 1 and 2), were hyper-proliferative compared to co-infected and control wounds (CO, row 3 and CT row 4, respectively) at all time points (columns 1, 2, 3 are days 7, 14 and 35 post-infection (PI), respectively). Proliferation was accompanied by rete-peg formation (arrows) and mild hyperkeratosis (*). Scale bars = 100μm.

44

CHAPTER 3: THE IMMUNOMODULATORY ROLE OF PSEUDOMONAS AERUGINOSA AND STAPHYLOCOCCUS AUREUS ON NEUTROPHIL CYTOKINE RESPONSES

3.1 ABSTRACT

P. aeruginosa and S. aureus are both common inhabitants of chronic wounds. The ability of these bacterial species to persist within the host despite a robust inflammatory response and aggressive wound care continues to confound the scientific and medical community. The persistence of these bacteria has been, in part, attributed to their ability to subvert the host immune response. Bacterial biofilms of both S. aureus and P. aeruginosa can be phagocytized by human neutrophils in vitro. Thus a route that is subsequent to phagocytosis; such as resistance to intracellular killing mechanisms or the induction of cytokine responses must augment the effectiveness of the abundant neutrophil inflammation in chronic wounds. In a recent review of the host response to infection using a chronic porcine wound model, S. aureus and P. aeruginosa induced different immune responses over the course of infection. At early time points (day 7) P. aeruginosa infected wounds contained more neutrophils than S. aureus wounds.

Neutrophils are considered a first responder to tissue damage and infection as well as increasingly recognized as modulatory cells to acute and adaptive immune response.

These findings led us to postulate that early interactions between the neutrophil and bacterial species may influence the host microenvironment and ultimately wound healing. 45

Specifically, we hypothesized that there would be differences in the neutrophil secreted cytokine profile when stimulated with S. aureus or P. aeruginosa. We also hypothesized that neutrophil responses would be dependent on the mode of bacterial growth (i.e. biofilm vs. planktonic). Neutrophils exposed to P. aeruginosa induced a robust pro- inflammatory response, independent of the mode of bacterial growth. Conversely, S. aureus, independent of the mode of growth, incited scant neutrophil cytokine excretion.

The differences in neutrophil responses, dependent on bacterial species, may contribute to chronic wound responses that differ between infections with S. aureus and P. aeruginosa.

3.2 INTRODUCTION

While chronic wounds are a major human health concern, the medical and scientific communities lack a complete understanding of the cause of delayed cutaneous healing in both healthy and immune compromised individuals (Sen et al, 2009). Chronic wounds are characterized by imbalanced and elevated proteases, reactive oxygen species and increased pro-inflammatory cytokines (Frykberg and Banks, 2015). These tissue destructive and pro-inflammatory substances can largely be attributed to infiltrating neutrophils (Amulic, et al, 2012; Wilgus et al, 2013; McDaniel et al, 2013). Stalling the normal progression of wound healing in a pro-inflammatory state leads to marked tissue destruction generating a self-perpetuating cycle of destruction and inflammation

(MacLeod and Mansbridge, 2016). The consistent identification of microcolonies of bacteria embedded in non-healing wounds has lead to the hypothesis that the persistence

46 of these bacterial communities incites long-standing inflammation (Bjarnsholt et al, 2007;

Gompelman et al, 2016).

Aggregated, sessile bacterial communities are called biofilms. In contrast, growth of single cells is called planktonic growth. These differing bacterial growth conditions or

“lifestyles” correlate to vastly different responses to host-derived and exogenous antimicrobials and transcriptional profiles (Davies, 2013; Phillips and Schultz, 2012;

Waite et al, 2005; Waite et al, 2006; Resch et al, 2005; Beenken et al, 2004; Resch et al,

2006). Motility and invasiveness, qualities of planktonic growth, are considered responsible for acute infections, are more susceptible to antimicrobials and produce cytolysis (Pollitt et al, 2015; Coggan and Wolfgang, 2012; Sousa and Pereira, 2014). In contrast, biofilms are associated with persistent, long-standing infections that resist antimicrobials and phagocytic clearance (Furukawa et al, 2006). Therefore, the identification of these microbes in chronic wounds is believed to be the focus of intense, unresolved inflammation. Although chronic wounds are generally considered poly- microbial environments, consistent identification of Staphylococcus aureus and

Pseudomonas aeruginosa in cutaneous soft tissue wounds, regardless of the inciting cause, has focused scientific attention on these bacterial species (Serra et al, 2015). S. aureus and P. aeruginosa are each capable of infecting a broad range of organ systems.

Each species is also capable of producing vastly different clinical outcomes, including rapid disease progression and ultimate death or long-standing persistent infections, such as the chronic wound.

47

Virulence factors and immune evasion mechanisms unique to each bacterial species have been identified largely via in vitro studies (Liu, 2009; Archer et al, 2011;

Graves et al, 2010; Alhede et al, 2014). In the laboratory, neutrophils are capable of phagocytosing biofilm grown S. aureus and P. aeruginosa (Leid et al, 2002; Günther et al, 2009; Jesaitis et al, 2003; Hanke et al, 2013; Thurlow et al, 2011). Perplexingly though, there has been little success in understanding how clearance remains to be achieved (Hanke et al, 2013). Neutrophil reactive oxygen species generation is reduced or delayed upon interaction with P. aeruginosa (Jensen et al, 1990; Jesaitis et al, 2003).

S. aureus is capable of persisting within the neutrophil after phagocytosis (Gresham et al,

2000; Hanke et al, 2013). Additionally, macrophages in S. aureus infection display a reparative response (alternative activation), proposed to be ineffective at immune clearance of this organism and responsible for persistence (Thurlow et al, 2011; Hanke et al, 2013). The role of alveolar macrophages in pulmonary infections with P. aeruginosa remains controversial (Morissette et al, 1996; Fujimoto et al, 2002; Ojielo et al, 2003;

Cheung et al, 2000). Therefore, there remains a gap in our understanding of how bacterial biofilms persist in the host given a potent immune response at the site of infection.

Neutrophils are considered the first responder to bacterial infections and responsible for much of the tissue damage contributing to chronicity of these wounds.

These cells are capable of accumulation in massive numbers at the site of infection in chronic wounds and producing various types of cytokines (Cassatella, 1999; Tecchio et al, 2014). Recognition of the role of this cell in shaping the innate and adaptive immune response is growing (Kolaczkowska and Kubes, 2013; Mantovani et al, 2011; Silva,

48

2010; Jaillon et al, 2013). Therefore, the ability of bacteria to alter the effectiveness and response of this cell could have important consequences to the mammalian host. Studies have shown a difference in the number of neutrophils present in wounds dependent on the infective bacteria. More robust neutrophil inflammation is present in wounds with P. aeruginosa infection (Fazli et al, 2009, Fazli et al, 2011, Hanke and Kielian, 2012).

Previous work in our porcine burn wound model confirms this finding and also reveals a difference in the immune response to this bacterium at later time points (Chapter 2). In the porcine wound, S. aureus wounds contain high numbers of eosinophils and fewer aggregates of lymphocytes and plasma cells in comparison to P. aeruginosa (Chapter 2).

Therefore, the interaction of neutrophils and bacterial biofilms in the wound environment may be an important predictor of the host response to infection.

Neutrophils are capable of influencing a microenvironment through cytokine and growth factor production (Mantovani et al, 2011). The ability of these cells to migrate from infected skin wounds to local lymphoid tissue also serves to influence adaptive immune responses (de Oliveira et al, 2016; Hampton et al, 2015; Hampton and Chtanova,

2016). Querying cytokine responses to P. aeruginosa or S. aureus in both in vitro and in vivo studies have produced incongruous results (Seth et al, 2012a; Seth et al, 2012b,

Pastar et al, 2013; Cooper et al, 1994; Sousse et al, 2011; Hessle et al, 2005; Sadowska et al, 2013; Secor et al, 2011; Nguyen et al, 2013). In some animal models there is a reduction in the overall levels of cytokines produced by S. aureus infection compared with P. aeruginosa while other studies saw no difference. This is may be due to differences in species, cell types or bacterial products (i.e. whole cell or conditioned

49 media) or growth conditions. Gram-negative sepsis in humans is correlated with higher pro-inflammatory cytokine production than Gram-positive induced sepsis (Surbatovic et al, 2015; Raynor et al, 2012; Xu et al, 2013). This is consistent with some studies that have directly compared wound infections with S. aureus versus P. aeruginosa (Seth et al,

2012a; Seth et al, 2012b; Sousse et al, 2011; Chekabab et al, 2015). These findings may eventually prove useful biomarkers for guiding treatment or determining prognosis in chronic wounds (Lindley et al, 2016). We are particularity interested in the potential difference in neutrophil responses to these bacterial species and the influence these differences may have on shaping the outcome of infection in the chronic setting (Hanke et al, 2013; Wilson, et al, 1998; Greenlee-Wacker et al, 2014; Ciornei et al, 2010). Here we present the cytokine responses of healthy peripheral blood neutrophils to S. aureus and P. aeruginosa under planktonic and biofilm growth conditions. It was hypothesized that the secreted neutrophil response to each of these bacterial species would differ in the types of cytokines produced and also depend on the mode of growth of these bacteria (i.e. biofilm versus planktonic).

3.3 MATERIALS AND METHODS

Bacterial strains Pseudomonas aeruginosa strain PAO1 (PA) was maintained on

Pseudomonas Isolation Agar (PIA). Staphylococcus aureus strain USA300 (SA) obtained from the Network on Antimicrobial Resistance in Staphylococcus aureus (NARSA, BEI

Resources Repository, Manassas, VA) and was grown on tryptic soy agar (TSA) plates.

50

Bacterial Growth Conditions Single colonies from overnight plate cultures were suspended in 5mL of 1x Roswell Park Memorial Institute Media with L-glutamine and phenol red (RPMI 1640, Corning, Manassas, VA). With constant agitation (200rpm), bacteria were grown at 37°C overnight. Biofilms were established using overnight cultures diluted 1:1 (volume) with fresh RPMI media and immediately inoculated into 24 well cell culture plates (300μL). Biofilms were grown for 4 days in a stationary humidified chamber at 37°C. Fresh media changes (300μL) were performed every 24 hours after careful removal of spent media. Planktonic cultures used for neutrophil experiments were generated by overnight cultures of a single colony, diluted 1:5

(volume) with fresh RPMI media and incubated at 37°C under constant agitation

(200rpm) until reaching an optical density at 600nm of ~0.1.

Bacterial and Biofilm Enumeration Overnight and mid-log phase planktonic growth curves were constructed using absorbance readings and serial dilution plating (in 1x PBS) for colony forming unit (CFU) determination. Biofilms (4 days) were manually disrupted by scraping, sonication and tituration with a small caliber needle. Biofilm bacterial suspension CFUs were enumerated by serial dilution in 1x PBS and plating overnight.

Intact biofilms were stained with 0.1% crystal violet in ethanol for 10min at room temperature. Biofilms were gently rinsed with 1xPBS and crystal violet was re- solubilized in ethanol. Absorbance was measured at 540nm.

51

Neutrophil Isolation All human subject experiments were approved by The Ohio State

University’s Institutional Review Board (IRB protocol # 2009H0314). Peripheral blood was obtained from healthy human donors. Hepranized blood was laid over a Ficoll-

Paque media density cushion and centrifuged at 400xg to separate and remove plasma, excess ficoll, peripheral blood monocytes and lymphocytes (buffy coat). The remaining erythrocyte-rich pellet was suspended in normal saline at a volume 1:1 ratio. Erythrocyte sedimentation depletion was performed with 1.5% dextran at 4°C for ~20min. The resultant supernatant was centrifuged at 550xg for 10min at 4°C. The neutrophil pellet was exposed to hypotonic saline to lyse remaining erythrocytes and isotonicity was restored with the addition of 1.8% NaCl. Neutrophils were suspended in RPMI with 1% autologous human donor serum. Human serum was collected from autologous donors by coagulation of non-heparinized peripheral blood at room temperature for 1 hr than and additional coagulation at 4°C for 1 hour. Final separation was achieved by centrifugation for 40 min at 404xg and filter sterilization. Serum was stored at -80°C for less than 3 months prior to use.

Neutrophil-Bacterial Exposure Biofilms and equivalent colony-forming unit planktonic bacteria were opsonized in 20% autologous serum in RPMI for 30min at 37°C. Bacteria was washed 3x in fresh RPMI. Neutrophils were exposed to bacteria at an MOI of 10:1

(bacteria to neutrophil) in 1% autologous serum in RPMI. Planktonic replicates were placed in poly-L-lysine coated 24-well cell culture dishes. Bacteria-neutrophil interactions were kept stationary at 37°C with 5% CO2 after brief centrifugation at 404xg.

52

Negative controls consisted of neutrophils kept at the same conditions and media but lacking bacteria. Supernatants were retrieved from unchallenged neutrophils wells at 4, 8 and 12 hours after establishment of neutrophil-bacterial interactions. Supernatants were centrifuged at 4°C through 0.22 µm filters and cell-free supernatants stored at -80°C.

Neutrophil-Cytotoxicity Assay Cell-free supernatant were immediately analyzed for lactate dehydrogenase (LDH) concentration using CytoTox96 Non-Radioactive

Cytoxicity Assay per manufacturer instructions (Promega, Madison, WI). In brief, 50μL of experimental supernatants including blank media and neutrophil control media were transferred to a fresh 96-well plate. Samples were mixed with 50μL of reconstituted

Substrate Mix and incubated, protected from light, for 30 minutes. Stop Solution (50μL) was added to each well and absorbance was recorded at 490nm.

Cytokine Determinations Cell free supernatants were analyzed for select cytokines using

Meso Scale Diagnostics (Rockville, Maryland) V-PLEX human kits (Pro-Inflammatory,

Cytokine and Chemokine). Assays were performed by the Analytical and Development

Lab at The Ohio State University per manufacturers specifications.

Statistics Statistical analysis was performed with GraphPad Prism version 5.0b

(GraphPad, La Jolla, CA). Data is presented as the mean of five independent experiments with duplicates and standard deviation. Comparisons between infection groups were

53 made with two-way ANOVA and Bonferroni post-testing. Bacterial culture methodologies were assessed using student t-test. Significance was set to p values <0.05.

3.4 RESULTS AND DISCUSSION

There have been several reports of S. aureus or P. aeruginosa induced cytokines using different cell lines or animal models, each with differing methodologies making direct comparison difficult (Seth et al, 2012a; Seth et al, 2012b; Pastar et al, 2013; Sousse et al,

2011; Hessle et al, 2005; Sadowska et al, 2013; Secor et al, 2011; Nguyen et al, 2013).

Most studies have been conducted using bacterial cultures or cell-free supernatants generated in rich bacterial growth media (i.e. tryptic soy broth or Luria broth media) and rodent derived or immortalized cell lines. Fewer reports have been published using primary human cells. In vitro bacterial culture in various growth media has been explored and significant changes in virulence factors, biofilm and motility expression has been reported (Oogai et al, 2011; Penttinen et al; 2016; Blair et al, 2013; Sridhar and Steele-

Mortimer, 2016). The effect of bacterial growth media on eukaryotic cells is less well defined.

Preliminary experiments performed in preparation of these experiments identified that Luria broth or tryptic soy broth media alone induced high levels of IL-8 production from naïve, human peripheral blood derived neutrophils. A major constituent of bacterial growth media is tryptone, which supplies nitrogen, energy and carbon to growing bacteria from cleaved protein. This same material has been used in animal models to incite sterile peritonitis (Knudsen et al, 2004;Knudsen et al, 2014). Therefore, bacterial growth

54 conditions were established in RPMI media, a cell culture media that supports a wide range of cell types. Similar methods have been employed by other groups using macrophages due to observed morphology differences consistent with apoptosis of unstimulated cells from media exposure alone (Thurlow et al, 2011). Biofilm formation of both bacterial species was delayed in RPMI and biofilms similar to those grown in rich media (i.e. tryptic soy broth or Luria broth media) were identified at day 4. Bacterial culture density in RPMI was quantified by colony forming unit (CFU) determination and crystal violet assay for planktonic and biofilm growth methods, respectively (Figure 8).

Biofilms of P. aeruginosa and S. aureus had equivalent CFU and crystal violet determined biomass, with no statistically significant differences (Figure 8). Therefore, 4- day-old biofilms grown in RPMI were selected for comparison to mid-log phase, RPMI- grown, planktonic bacteria of equivalent bacterial number.

Important to the translation of in vitro assays to clinically relevant data is the use of an appropriate host/animal model. There are important differences between human and rodent immune responses (Mestas and Hughes, 2004; Sullivan et al, 2001). These differences may account for the poor correlation of mouse model responses to human diseases they are designed to recapitulate (Seok et al, 2013). Ciornei et al (2010) compared the cytokine responses of primary human macrophages and mouse macrophages to planktonic and biofilm grown P. aeruginosa and S. aureus. In this study, mouse macrophages did not replicate the results obtained from human macrophages

(Ciornei et al, 2010). Similarly, Dubern et al (2015) found that P. aeruginosa virulence was highly dependent on the disease model used. There was little agreement between

55 commonly used model systems (Drosophila melanogaster, Caenorhabditis elegans, mouse and human cell lines) when searching for a multi-host virulence factor (Dubern et al, 2015). Therefore, bacterial pathogenicity may be host specific and in vitro experiments should utilize relevant model systems.

In the present study, it was hypothesized that neutrophil interactions with different bacterial species will alter the types and intensity of cytokines expressed into the extracellular milieu. These responses were speculated to change based on the mode of growth of these bacteria. The most significant differences were seen between bacterial species (i.e. S. aureus vs. P. aeruginosa) and not the mode of bacterial growth (i.e. planktonic vs. biofilm). Specifically, P. aeruginosa exposed neutrophils produced significantly more cytokines types than S. aureus exposed neutrophils. The mode of bacterial growth accounted for minimal differences in the types and quantities of neutrophil cytokines elicited. There was scant cytokine production by S. aureus exposed neutrophils under either bacterial growth condition. Table 3 presents each of the cytokines assayed at 4, 8 and 12 hours post-interaction. Differences are proposed to be due to cell envelope/wall constituents (i.e. Gram-negative vs. Gram-positive bacteria) or the amount of cytotoxicity induced by each bacterial species.

Pro-inflammatory cytokines [interleukin-1 α/β (IL-1), Tumor necrosis factor α

(TNF-a), IL-6, and IL-8] were all increased above controls after 8 and 12 hours of interaction with P. aeruginosa biofilms and planktonic cells (Figure 9). Only IL-8 was increased in S. aureus conditions compared to control neutrophil conditions (Figure 9).

Anti-inflammatory cytokine IL-10 was only expressed by P. aeruginosa exposed

56 neutrophils (Figure 10). Planktonic grown P. aeruginosa conditions resulted in increases at 12 hours whereas biofilms resulted in only increases at 8 hours, returning to insignificant levels at 12 hours. The difference in pro-inflammatory cytokine expression induced by P. aeruginosa or S. aureus may contribute to the difference in neutrophil infiltration of chronic wounds infected with either of these bacterial species. P. aeruginosa infection resulted in increased numbers of neutrophils in porcine burn wounds and human chronic wounds compared to those infected with S. aureus (Chapter

2, Hanke and Kielian, 2012; Fazli, et al, 2011).Morever, murine models of S. aureus foreign body infections also show low numbers of neutrophils present at the site of infection (Thurlow et al 2011; Hanke and Kielian, 2012). Of note, the expression of anti- inflammatory cytokine, IL-10 was unique to P. aeruginosa conditions and was most profoundly expressed by planktonic grown P. aeruginosa. This may indicate that under planktonic P. aeruginosa conditions, neutrophils are able to balance pro- and anti- inflammatory responses or prevent a hyper-inflammatory response. We conclude that S. aureus interactions with neutrophils appear minimally stimulatory and not anti- inflammatory.

Immune responses have been categorized by the cytokines produced by CD4+ T- helper cells (i.e. Th1 v Th2). The Th1 T-cell phenotype produces cytokines that perpetuate a pro-inflammatory response and increase intracellular bacterial killing (Kidd,

2003). The Th2 T-cell phenotype produces cytokine that are associated with anti- inflammatory, repair or allergy (Kidd, 2003).Murine models of bacterial infections have shown that the inability to produce a proper Th1 response can lead to bacterial

57 persistence (Wilson et al, 1998; Bogdan et al, 1993). Thus, this dichotomous relationship has become an attractive way to evaluate the competency of the host response to infection. However, it should be made clear that the expression of a predominantly Th1 response does not always equate to adequate host clearance (Hume et al, 2005).

Generating a Th1 or Th2 phenotype is dependent on antigen presentation and the extracellular cytokine milieu present at the time of antigen presentation. Thus, the neutrophil response at the site of infection and production of cytokines may help shape these immune responses (Kumar and Sharma, 2010). Cytokines that help CD4+ T-cells adopt a Th1 phenotype include interferon-gamma (IFN-g) and IL-12 (p70). The Th2 phenotype is supported in the presence of IL-4 and IL-10. The Th1/Th2 paradigm has also been linked to the modulation of macrophage responses. Classically activated macrophages (M1) exhibit pro-inflammatory properties and alternatively activated macrophages (M2) express anti-inflammatory or reparative properties (Martinez and

Gordon, 2014). Th1 expressed cytokines are involved in priming/activating M1 macrophages and Th2 expressed cytokines are involved in the activation of the M2 phenotype. Although this is a simplified view of this complex process, these cytokines are often assayed to understand disease processes.

P. aeruginosa exposed neutrophils expressed cytokines of both Th1 and Th2 categories (Figure 10). Interestingly, P. aeruginosa biofilms did not elicit IFN-g (Figure

10) or IL-13 (Table 3) expression from neutrophils, which are Th1 and Th2 cytokines, respectively. Although the significance of these differences is not clear, it is important to recognize that IFN-g is a potent inducer of the bactericidal effects of macrophages and

58 has important immune regulatory roles (Beekhuizen and van de Gevel, 2007; Shtrichman and Samuel, 2001). Similarly, IL-13 is important in the induction of a Th2 response and in limiting neutrophil mediated tissue damage in other infection studies (Seki et al, 2012).

Therefore, the lack of expression of these cytokines by neutrophils exposed to P. aeruginosa biofilms may indicate that bactericidal efforts may not be effective or properly regulated.

S. aureus exposed neutrophils failed to express cytokines from either Th1 or Th2 category (Figure 10). The lack of these cytokine responses from S. aureus may indicate that neutrophils do not likely contribute to the M2 macrophage phenotype that is proposed to permit chronic infection in mouse models (Greenlee-Wacker et al, 2014;

Thurlow et al, 2011; Hanke et al, 2013).The mechanism by which S. aureus augments local and systemic immune responses is intensively studied. In a mouse model of cutaneous S. aureus infection, α-hemolysin production can kill perivascular macrophages, inhibiting the influx of neutrophils to the site of infection (Abtinet al,

2014). When neutrophils are able to reach the site of infection, S. aureus can persist within the neutrophil cytosol (Gresham et al, 2000). Regression from the site of S. aureus infections to draining lymph nodes can also result in substantial influence of adaptive immune responses (de Oliveira et al, 2016; Kamenyeva et al, 2015; Hampton et al, 2015). Therefore, the lack of significant cytokine production by S. aureus exposed neutrophils may be a specific mechanism by which S. aureus alters neutrophil responses.

By limiting local immune cell influx and exuberant pro-inflammatory responses these cells may more readily migrate to distant sites and influence adaptive immune responses.

59

Planktonic P. aeruginosa exposed neutrophils uniquely expressed macrophage inflammatory protein-1 α and β (MIP-1α and MIP-1β) which were not present under any other conditions tested (P. aeruginosa biofilm or either S. aureus condition) (Table 3).

MIP-1 α and β are important chemo-attractants for inflammatory cells such as lymphocytes (B and T) and modulate acute phase cytokine production (O’Grady et al,

1999). P. aeruginosa biofilms uniquely elicited expression of IP-10 and GM-CSF from neutrophils (Table 3). GM-CSF is important to the chemoattraction and survival of neutrophils at the site of infection (Shi et al, 2006). IP-10 is expressed in inflammatory diseases in humans and is important to the recruitment of T-cells to the site of inflammation (Dufour et al, 2002). Thus, biofilm conditions appear to lack the stimulation of some regulatory and immune modulatory cytokines and chemokines, concomitant with production of immune stimulatory products. This may indicate that unbridled inflammation is important to the pathogenesis of P. aeruginosa biofilm infections, such as the prolonged and intense neutrophil infiltration with lack of resolution.

Neutrophil viability was determined by lactate dehydrogenase (LDH) measurement (Figure 11). Neutrophil cell death increased over time regardless of bacterial species or growth conditions. Growth conditions did not influence neutrophil cell death, as biofilm and planktonic modes of growth of each species were not statistically different at any time point. S. aureus exposed neutrophils, regardless of growth condition, exhibited higher cytotoxicity than P. aeruginosa exposed neutrophils.

At 4 hours post-inoculation, there was no difference in cell death between neutrophils

60 exposed to P. aeruginosa biofilms and controls (autologous uninfected neutrophils). Cell death increased markedly at 8 hours post-infection in S. aureus exposed neutrophils and remained constant at 12 hours. Cytotoxicity of P. aeruginosa exposed neutrophils at 8 and 12 hours were less than 80%. Neutrophil concentrations at 12 hours decreased to

6x105 neutrophils/mL and 7.5 x105 neutrophils/mL for S. aureus and P. aeruginosa conditions, respectively, a concentration at which cytokines should still be produced at detectable levels.

The presence of LDH indicates that cells are undergoing loss of cell membrane integrity such as necrosis or long-term unresolved apoptosis (secondary necrosis).

Secondary necrosis would be anticipated in an assay lacking a clearance mechanism for apoptotic cells (i.e. macrophages). The lack of detection of cytokine levels, even at 4 hours, in S. aureus conditions makes the theory of complete cell membrane disintegration, i.e. oncotic necrosis, of these cells less likely since pre-stored or other inflammatory markers are not detected. Thus, the marked difference in number of cytokines produced between these two bacterial species is considered reflective of a bacterial-driven process and not loss of neutrophil viability (Wilson et al, 1998). The concomitant release of proteolytic enzymes and degradation of secreted factors cannot be ruled out. However, we aimed to identify the cytokines that would remain within a host and influence the microenvironment. Thus it is anticipated that in vivo, neutrophils are not likely to contribute significantly to cytokine production in S. aureus infected wounds.

These findings are consistent with some in vivo models in which S. aureus infections produced less cytokines than P. aeruginosa infections (Hume et al, 2005; Seth et al,

61

2012a, Seth et al, 2012b, Sousse et al, 2011). However there are other conditions in which this phenotype is less clear (Pastar et al, 2013; Hessle et al, 2005; Sadowska et al,

2013).

Of the cytokines that were elevated in S. aureus exposed neutrophils, interleukin-

16 (IL-16) was the most distinct. The levels of IL-16 detected here may be indicative of apoptosis, as IL-16 release was unable to be induced in human neutrophils by other common stimulatory methods (i.e. microbial substances and pro-inflammatory cytokines) and was contingent upon caspase-3 activation (Roth et al, 2015). Consistent with LDH detection, IL-16 levels are significantly higher in both planktonic and biofilm S. aureus exposed neutrophils compared to either P. aeruginosa exposed neutrophil groups; although, IL-16 production in P. aeruginosa exposed neutrophils also mirrors LDH production (Figure 12). It is speculated that the release of IL-16 in secondary necrosis of neutrophils may serve as a danger signal of inefficient apoptotic neutrophil clearance

(Roth et al, 2016). However, the chemoattractant potential of IL-16 for cell types such as monocytes, T-lymphocytes and eosinophils may account for other changes identified in the porcine burn wounds infected with S. aureus as presented in Chapter 2 (Cruikshank and Kornfeld, 2000). In S. aureus infected porcine burn wounds eosinophils were present at later time points (Chapter 2). Elevated IL-16 production and eosinophil influx is characteristic of atopic dermatitis, a disease in which S. aureus infection is purported to play a significant role in the pathogenesis (Leung, 2003; Frezzolini et al, 2002; Baviera et al, 2015). Although IL-16 levels are elevated in P. aeruginosa exposed neutrophils above control neutrophils, secretion is significantly less than the S. aureus group and

62 eosinophils were only identified in P. aeruginosa infected wounds at day 7 post-infection and not day 14 or 35 post-infection.

The marked increase in cytokines from neutrophils exposed to P. aeruginosa in comparison to S. aureus exposed neutrophils may be due to inherent differences in cell wall components. Gram-negative bacteria uniquely express lipopolysaccharide (LPS) while gram-positive bacteria express lipoteichoic acid (LTA). These cell wall components are regarded as important immunostimulatory components. Gram-negative bacteria stimulate significantly more pro-inflammatory cytokines than Gram-positive bacteria in septic human patients (Surbatovic et al, 2015; Raynor et al, 2012; Xu et al,

2013). Human monocytes exposed to biofilm or planktonic grown P. aeruginosa identified enhanced pro-inflammatory cytokine production from biofilms compared with planktonic exposed cells (Ciornei et al, 2010). This heightened response was attributed to biofilm specific modification of the lipid A and polysaccharide components of P. aeruginosa’s LPS (Ciornei et al, 2010). The modifications of LPS in clinical isolates of

P. aeruginosa from cystic fibrosis patients with chronic disease have been shown to contribute to increased survival in murine pulmonary infections (Ernst et al, 2007;

Chalabaev et al, 2014; Cigana et al, 2011; Cigana et al, 2009). Gram-positive bacteria similarly are capable of modifying surface structures to evade the immune system

(Foster, 2005). S. aureus strains lacking surface modification are susceptible to neutrophil killing and have attenuated virulence in animal models (Collins et al, 2002). It is also accepted that LPS and LTA independent mechanisms may be responsible for these differences. An LPS deficient mutant of Gram-negative bacteria Neisseria gonorrhoeae

63 was still capable of inducing a pro-inflammatory response without LPS expression in human monocytes (Uronen et al, 2000). In Gram-positive bacteria, Streptococcus pneumoniae autolysis (programmed cell death) is important in subverting pro- inflammatory responses in human peripheral mononuclear cells (Martner et al, 2009).

There was a nearly complete lack of monocyte stimulation to produce TNF, IFN-g and

IL-12 by S. pnuemoniae dependent on the ability to undergo autolysis (Martner et al,

2009). In S. aureus there is also a link between LTA expression and autolysis activity

(Fedtke et al, 2007). The loss of LTA expression in S. aureus also resulted in the reduction of autolysis (Fedtke et al, 2007).

3.5 CONCLUSIONS

Presented here is the unique finding that although clinically, chronic wound infections with S. aureus and P. aeruginosa are generally considered to be nearly indistinguishable by gross assessment and histology there is a marked difference in the stimulus incited by interactions with neutrophils. Determining the immunopathology that is unique to each of these bacterial infections may help in identifying biomarkers for early diagnosis and guiding treatment strategies. The lack of a significant S. aureus-induced neutrophil response correlates well with clinical and experimental findings of reduced neutrophil burden in these wounds and experimental attenuation of wound cytokine responses. Since others have identified that neutrophils are important to the clearance of S. aureus skin infections, this dampening of neutrophil inflammation appears to be a bacterial specific mechanism. Contrarily, P. aeruginosa incites a strong pro-inflammatory response with

64 reduced neutrophil cytotoxicity. Under biofilm growth conditions P. aeruginosa may augment neutrophil responses by promoting the local neutrophil survival while dampening responses that make this pro-inflammatory response effective (i.e. IFN-g).

These findings require further scientific investigation.

65

Control S. aureus P. aeruginosa Analyte Time (Neutrophils (hours) Only) Biofilm Planktonic Biofilm Planktonic 4 0.16 ± 0.09 0.15 ± 0.07 0.29 ± 0.09 0.43 ± 0.39 0.28 ± 0.12 GM-CSF 8 0.20 ± 0.13 0.38 ± 0.36 0.24 ± 0.12 1.93 ± 1.28*** 0.77 ± 0.56 12 0.19 ± 0.13 0.42 ± 0.21 0.25 ± 0.07 2.30 ± 1.45*** 0.80 ± 0.53 4 7.17 ± 2.30 69.45 ± 35.70** 45.76 ± 27.61 15.87 ± 8.43 18.17 ± 8.68 IL-16 8 9.45 ± 4.42 226.19 ± 20.53*** 191.10 ± 57.74*** 83.38 ± 8.81*** 85.67 ± 26.51*** 12 14.61 ± 5.32 278.95 ± 42.08*** 245.41 ± 35.04*** 99.25 ± 27.33*** 111.70 ± 25.39*** 4 0.04 ± 0.05 0.64 ± 0.61 0.53 ± 0.39 0.33 ± 0.42 1.09 ± 0.81 IL-1alpha 8 0.34 ± 0.64 1.68 ± 0.73 1.23 ± 0.25 6.94 ± 2.12 12.67 ± 8.64*** 12 0.10 ± 0.19 3.37 ± 2.08 2.07 ± 0.14 11.68 ± 3.25** 20.46 ± 14.75*** 4 0.36 ± 0.11 2.26 ± 1.17 2.07 ± 0.79 4.13 ± 4.21 5.15 ± 6.49 IP-10 8 0.45 ± 0.24 3.95 ± 2.88 2.53 ± 1.05 19.12 ± 26.69 12.89 ± 22.76 12 0.65 ± 0.40 4.52 ± 2.55 3.09 ± 1.60 29.43 ± 44.32* 16.14 ± 29.31 66 4 2.28 ± 0.75 282.55 ± 321.30 382.23 ± 433.02 370.56 ± 381.08 977.52 ± 1033.45 MIP-1alpha 8 3.82 ± 2.52 501.50 ± 603.86 885.37 ± 987.43 1163.50 ± 1230.41 1592.85 ± 1501.82* 12 7.23 ± 7.22 642.26 ± 697.50 1174.28 ± 1311.53 1361.76 ± 1538.95 1630.42 ± 1553.96* Continued

Table 3. Cytokine production from human peripheral blood derived neutrophils exposed to biofilm and planktonic grown P. aeruginosa and S. aureus.

aLevels were determined by multiplex ELISA from cell free supernatants acquired from peripheral blood derived neutrophils exposed to live bacteria grown as biofilm or planktonic culture. All values are presented are means (pg/mL) ± SD for five independent experiments/human blood donors. Statistical significance indicated as compared to controls by 2-way ANOVA with Bonferroni post-hoc testing and significance set to p<0.05. * Indicates statistical significance compared to control.

66 Table 3, Continued

4 5.37 ± 5.70 44.48 ± 48.40 42.81 ± 30.97 248.61 ± 439.08 385.01 ± 446.57 MIP-1beta 8 10.27 ± 13.87 48.78 ± 16.21 52.89 ± 32.90 441.32 ± 445.58 556.50 ± 401.78* 12 14.53 ± 21.85 103.22 ± 91.59 75.39 ± 38.86 432.34 ± 424.82 542.84 ± 396.02* 4 3.41 ± 1.35 54.94 ± 6.68*** 42.29 ± 11.42*** 38.23 ± 7.00*** 41.56 ± 13.61*** VEGF 8 3.97 ± 1.46 66.79 ± 6.00*** 61.11 ± 15.79*** 55.20 ± 5.98*** 61.40 ± 11.50*** 12 4.82 ± 1.48 70.42 ± 7.20*** 72.69 ± 12.97*** 65.26 ± 4.19*** 71.05 ± 10.47*** 4 1.50 ± 0.28 1.13 ± 0.15 1.28 ± 0.17 1.30 ± 0.15 1.60 ± 0.14 IFN-g 8 1.39 ± 0.67 1.55 ± 0.25 1.62 ± 0.17 2.20 ± 0.57 3.08 ± 1.18** 12 1.58 ± 0.95 1.21 ± 1.04 1.62 ± 0.22 2.46 ± 0.93 3.56 ± 1.73*** 4 0.07 ± 0.05 0.16 ± 0.04 0.26 ± 0.13 0.24 ± 0.08 0.41 ± 0.14 IL-10 8 0.05 ± 0.03 0.27 ± 0.18 0.28 ± 0.11 1.28 ± 1.05* 0.86 ± 0.27 12 0.06 ± 0.03 0.62 ± 0.42 0.35 ± 0.08 1.03 ± 0.47 2.58 ± 2.02*** 67 4 0.08 ± 0.07 0.09 ± 0.06 0.27 ± 0.09 0.15 ± 0.06 0.20 ± 0.09 IL-12p70 8 0.06 ± 0.02 0.17 ± 0.04 0.28 ± 0.04 0.30 ± 0.12* 0.48 ± 0.32*** 12 0.09 ± 0.04 0.26 ± 0.14 0.25 ± 0.06 0.36 ± 0.13* 0.57 ± 0.30*** 4 0.71 ± 0.66 1.08 ± 0.66 1.62 ± 1.18 2.40 ± 2.25 2.15 ± 1.10 IL-13 8 0.64 ± 0.63 1.13 ± 0.40 1.49 ± 0.78 2.52 ± 1.36 3.43 ± 1.09* 12 0.67 ± 0.63 2.27 ± 1.61 2.24 ± 0.90 2.70 ± 1.36 5.07 ± 3.56*** 4 0.23 ± 0.05 6.25 ± 2.98 9.29 ± 3.43 14.05 ± 15.44 45.99 ± 31.97 IL-1 beta 8 0.18 ± 0.07 16.72 ± 6.61 14.80 ± 5.79 88.91 ± 28.00*** 181.95 ± 71.75*** 12 0.19 ± 0.06 28.42 ± 12.39 20.10 ± 11.14 110.80 ± 35.43*** 200.05 ± 94.27*** 4 0.03 ± 0.03 0.08 ± 0.05 0.44 ± 0.33 0.15 ± 0.05 0.17 ± 0.07 IL-2 8 0.03 ± 0.03 0.18 ± 0.06 0.26 ± 0.05 0.96 ± 1.08 0.74 ± 0.50 12 0.02 ± 0.05 1.25 ± 1.28 0.71 ± 0.54 1.41 ± 0.91* 2.43 ± 2.48*** 4 0.03 ± 0.02 0.04 ± 0.01 0.06 ± 0.02 0.03 ± 0.01 0.04 ± 0.01 IL-4 8 0.02 ± 0.01 0.05 ± 0.01 0.07 ± 0.02 0.09 ± 0.04** 0.11 ± 0.06*** 12 0.03 ± 0.01 0.07 ± 0.03 0.07 ± 0.02 0.08 ± 0.02* 0.13 ± 0.07*** Continued

67 Table 3, continued (2)

4 0.12 ± 0.04 0.51 ± 0.30 0.47 ± 0.17 2.44 ± 2.18 2.98 ± 2.62 IL-6 8 0.14 ± 0.07 0.95 ± 0.87 0.61 ± 0.32 12.78 ± 5.66*** 10.40 ± 8.97** 12 0.19 ± 0.10 1.99 ± 1.36 0.61 ± 0.53 15.41 ± 9.38*** 12.05 ± 10.02*** 4 2.28 ± 0.50 295.15 ± 88.83 417.36 ± 122.46 565.89 ± 280.16* 1401.25 ± 360.24*** IL-8 8 4.89 ± 1.49 463.44 ± 224.82 870.31 ± 331.67*** 1679.04 ± 580.95*** 2056.97 ± 331.71*** 12 9.73 ± 3.03 890.35 ± 283.78*** 1141.02 ± 384.18*** 1797.22 ± 560.23*** 2186.69 ± 302.07*** 4 0.48 ± 0.32 7.73 ± 5.18 9.52 ± 5.43 30.23 ± 17.97* 37.64 ± 17.81** TNF-alpha 8 0.57 ± 0.47 6.68 ± 3.25 9.51 ± 4.22 45.61 ± 17.86*** 53.45 ± 36.39*** 12 0.62 ± 0.52 10.32 ± 6.50 12.29 ± 7.29 45.62 ± 14.48*** 59.47 ± 38.78*** 68

68 NOT STATISTICALLY SIGNIFICANTLY DIFFERENT

Crystal Violet Assay on 4 day biofilms in RPMI, generated without nutation and NO CO2. Measured absorbance, SD P4< 0.day05 biofilms with no nutation and no CO2 in RPMI student t-test disrupted and serial dilutions plated

NOT STATISTICALLY SIGNIFICANTLY DIFFERENT

Overnight Cultures were started from bacteria on a plate (1 colony struck out) as a swab from the plate. Grown overnight at 37C 200rpm Biomass of Biofilms Viable Bacteria in Biofilms Start at T0: 1mL of overnight culuture into 4mL of8 fresh culture (5 replicates) 2.0 10 Take only 1 and plate in triplicate at every time point the CFU

1.5 m e l

Big Difference in OD readings in RPMI but overnighi t CFU does not indicate a difference c f n o i a between the 2 bacteria. Huge difference in opacity appreciated grossly. B

b 7

r 1.0 / 10

o U s F b CFU on TSA plates with serial dilutions in 1x PBS A C 0.5

0.0 106 PAO1 USA300 PAO1 USA300 A. B.

Planktonic Growth Curve

109

8

L 10 m

/

U F

C 107 USA300 PAO1 106 0 1 2 3 4 5 6 7 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 ht 8 9 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 ig rn e v o Time (hours) C.

Figure 8. Bacterial Growth Kinetics in Roswell Park Memorial Institute Media.

S. aureus, USA300, and P. aeruginosa, PAO1, grown for 4 days in Roswell Park Memorial Institute (RPMI) media under static conditions (biofilms) were not statistically different when assayed by crystal violet absorbance (biomass, A) or viable bacteria (colony forming unit (CFU), B). Graphs display mean with standard deviation and statistical analysis performed by student t-test and p-value <0.05. Planktonic growth of both bacterial strains in RPMI (overnight or during mid-log phase, C) was not statistically different; graph depicts a single experiment, representative of n=5 individual experiments. Comparisons were made between 4-day biofilms of each species and mid- log phase planktonic grown bacteria prepared to equivalent bacterial concentrations as established biofilm CFUs.

69

Figure 9. Pro-Inflammatory Cytokines Produced By Wound Pathogen Exposed Neutrophils.

Cytokines responsible for promoting inflammation by inducing a systemic response such as fever and hyperemia and neutrophil activation include: IL-6 (A), TNF-alpha (C) and IL-1 (D). P. aeruginosa induces significantly higher amounts of all pro-inflammatory cytokines compared to S. aureus, independent of the method of bacterial growth (i.e. planktonic or biofilm). Neutrophils are attracted to the sites of infection by IL-8 (B). All bacteria induced high levels of IL-8 from neutrophils compared to controls (unstimulated autologous neutrophils). P. aeruginosa induced higher production of IL-8 than S. aureus, when comparing respective bacterial growth conditions. PA+PL = planktonic P. aeruginosa; PA+BF = biofilm P. aeruginosa; SA+PL = planktonic S. aureus; SA+BF = biofilm S. aureus. Means of five independent experiments are graphed with standard deviations and statistical significance indicated as compared to controls by 2-way ANOVA with Bonferroni post-hoc testing and significance set to p<0.05. * Indicates statistical significance compared to control. # Indicates statistical significance between indicated conditions. + Indicates statistical significance between indicated conditions. All measurements were taken after 12-hours of bacterial-neutrophil interactions.

70

Figure 10. Th1/Th2 Inducing Cytokines Produced By Wound Pathogen Exposed Neutrophils.

Th1 stimulatory cytokines IFN-g (A) and IL-12p70 (C) were produced most significantly by neutrophils exposed to planktonic P. aeruginosa compared to neutrophils exposed to biofilm grown P. aeruginosa. Th2 stimulating cytokines IL-4 (B) and IL-10 (D) were also produced at highest levels by neutrophils exposed to planktonic grown P. aeruginosa than from biofilm grown P. aeruginosa. Planktonic and biofilm grown S. aureus induced insignificant amounts of any of these cytokines from neutrophils compared to controls (unstimulated autologous neutrophils). PA+PL = planktonic P. aeruginosa; PA+BF = biofilm P. aeruginosa; SA+PL = planktonic S. aureus; SA+BF = biofilm S. aureus. Means of five independent experiments are graphed with standard deviations and statistical significance indicated as compared to controls by 2-way ANOVA with Bonferroni post-hoc testing and significance set to p<0.05. * Indicates statistical significance compared to control. # Indicates statistical significance between indicated conditions. All measurements were taken after 12-hours of bacterial-neutrophil interactions. 71

Figure 11. Bacterial Induced Neutrophil Cytotoxicity.

Neutrophils were exposed to S. aureus or P. aeruginosa grown as planktonic bacteria or biofilms and lactate dehydrogenase was measured from cell-free supernatants. Presented here is the amount of lactate dehydrogenase per condition as a percentage of max lysis by Triton-X. Controls included neutrophils in media alone. ). PA+PL = planktonic P. aeruginosa; PA+BF = biofilm P. aeruginosa; SA+PL = planktonic S. aureus; SA+BF = biofilm S. aureus. Means are graphed with standard deviations and statistical significance indicated as compared to controls by 2-way ANOVA with Bonferroni post-hoc testing and significance set to p<0.05.

72

Figure 12. IL-16 Production by Bacterial Stimulated Neutrophils.

Independent of the mode of bacterial growth (i.e. biofilm (BF) or planktonic (PL)) S. aureus (SA) bacteria induce higher levels of IL-16 than P. aeruginosa (PA) bacteria at 8 and 12 hours post-exposure. Graphic representation of mean IL-16 production from five independent experiments as measured by ELISA in pg/mL. Means are graphed with standard deviations and statistical significance indicated as compared to controls by 2- way ANOVA with Bonferroni post-hoc testing and significance set to p<0.05. PA+PL = planktonic P. aeruginosa; PA+BF = biofilm P. aeruginosa; SA+PL = planktonic S. aureus; SA+BF = biofilm S. aureus. * Indicates statistical significance compared to control. # Indicates statistical significance between indicated conditions.

73

CHAPTER 4. DETERMINANTS OF PSEUDOMONAS AERUGINOSA FITNESS IN THE CHRONIC WOUND

4.1 ABSTRACT

Pseudomonas aeruginosa is capable of infecting a broad host range with drastically different outcomes including acute, high-mortality infections and chronic infections lasting months to years and. The ability of this organism to persist within highly variable environments both outside and within a mammalian host is accomplished by the same genetic composition with little variation between clinical and environmental isolates. To determine the genetic contributions to successful infection of a chronic wound by P. aeruginosa strain PAO1, we employed high-throughput sequencing of a transposon mutant library in a porcine burn wound model. There were restricted numbers of transposon mutants displaying decreased fitness in the wound. Of the 33 genes identified as important for fitness in the porcine burn wound, 25 were annotated as hypothetical or with only putative function. There is a clear requirement for micronutrient acquisition, flagella associated motility, outer membrane proteins/small molecule transport systems and extracellular sigma factor transcriptional regulators. Surprisingly, transposon mutants with insertions in acute virulence factors and type IVa pili were positively selected for in the burn wound. These findings indicate that the burn wound is a distinct niche in which P. aeruginosa is required to rapidly adapt. However, P.

74 aeruginosa may not be exposed to the same host defenses as those present in the acute wound or pulmonary infections early in the course of establishing infection.

4.2 INTRODUCTION

Chronic wounds are a significant public health burden with broad social and economic impacts (Sen et al, 2009). The opportunistic pathogen, P. aeruginosa, is commonly identified within chronic wounds, regardless of inciting cause of skin or soft tissue injury. The ability of this pathogen to successfully colonize and infect a wound requires coordinated bacterial responses while responding to host interactions. At each stage of colonization and infection, a pathogen must rapidly respond and adapt to the ever-changing environment. This demand persists even when localized in chronic infection as the host attempts to heal and change from acute to adaptive immune responses. This response is genetically encoded and determines the overall fitness of the pathogen. Since, Pseudomonas aeruginosa has evolved outside of a human host there has been little modification of its genetic makeup to account for it’s increasing prevalence as an opportunistic pathogen (Wolfgang et al, 2003b). With increasing age, obesity and trauma related injuries sustained by the human population there comes an increased risk of secondary opportunistic infection by P. aeruginosa.

Current treatment methods of chronic wounds including tissue debridement and antimicrobial therapy are not consistently successful at resolving persistent infection by

P. aeruginosa. Therefore, a better understanding of the mechanism(s) by which P. aeruginosa establishes infection in the host may inform development of better treatment

75 and prevention measures. We aimed to identify P. aeruginosa genes important for colonization and persistence in the porcine burn wound model. Genome wide transposon insertion mutagenesis fitness profiling was used to investigate the genetic requirements of

P. aeruginosa persistence in a porcine burn wound model. High-throughput screening of gene essentiality is possible by use of a verified, near full-genome saturation, random transposon insertion mutant library of P. aeruginosa strain PAO1. The input transposon mutant pool is altered under the selection pressure of the chronic wound. Sequencing

(Tn-seq) and comparison of input and output pools of mutants will elucidate fitness determinants important to chronic wound infection.

In vitro and mixed screenings (in vitro and in vivo methods) have been used to identify conditional requirements for P. aeruginosa or screen for unique virulence factors

(Turner et al, 2015; Lee et al 2015). Previous studies using similar methods in infection models of various species and body systems have been conducted but are limited in number. Using a murine intestinal colonization and neutropenia induced sepsis model,

Skurnik et al (2013a) identified the requirement for host infection of P. aeruginosa strain

PA14. A large proportion of known virulence factors were identified as being essential, including: type 6 secretion systems, iron acquisition systems (pyochelin, pyocyanin, pyoveradin), rhamnolipid, lipopolysaccharide (LPS). Additionally, the acquisition of nutrients, ion pumps and respiration were essential to intestinal colonization (Skurnik et al, 2013a). Surprisingly this group found the loss of type IVa pili enhanced intestinal colonization but hindered systemic spread.

76

Follow up to these studies identified a fitness advantage to oprD transposon mutants in colonizing the murine gastrointestinal tract and disseminating to the spleen

(Skurnik et al, 2013b). The oprD mutation also exhibited carbapenem resistance (Skurnik et al 2013b). The authors hypothesize that the development of antibiotic resistance to carbapenem may therefore lead to enhanced virulence in the host. Further transposon sequencing studies using a library of P. aeruginosa strain PA14 and murine pulmonary infections were designed to test this hypothesis (Roux et al, 2015). Transposon mutations in genes conferring antibiotic resistance were selected for in pulmonary infections, indicating a fitness advantage to this phenotype (Roux et al, 2015).

Turner et al (2014) investigated the metabolic requirements of P. aeruginosa strain PAO1 using both a acute and chronic murine wound models. Transcriptional expression of a gene during infection poorly correlated to the fitness of the gene in the wound. This assessment held true for all but genes associated with metabolism (Turner et al, 2014). Correlating transcriptional expression and TN-seq data from both selective media in vitro and in vivo conditions, long-chain fatty acids were identified as a major carbon source in wounds. P. aeruginosa must also synthesize purines and amino acids in wounds of any duration (Turner, et al, 2014). Motility genes including type IV pili and chemotactic flagella were required for fitness in acute wounds. However, fitness in chronic wounds only required type IV pili motility. Despite this work, there remains an incomplete understanding of the bacterial processes that govern chronic wound pathogenesis. Here, we sought to employ a clinically relevant animal model with one of

77 the longest reported infection intervals (i.e. 35 days) to determine the genetic determinants of fitness in P. aeruginosa (Roy et al, 2014).

4.3 MATERIALS AND METHODS

Bacterial Transposon Library The Marvin Whiteley laboratory (University of Texas) supplied Pseudomonas aeruginosa strains PAO1 and PA14 transposon insertion libraries, which were originally generated by the Colin Manoil laboratory (University of

Washington) (Gallagher et al, 2011; Jacobs et al, 2003). Individual aliquots contained

250μL of cells in half strength rich media brain heart infusion media (BHI) and 25% glycerol. PAO1 contained 2 x 1010 colony forming units (CFU)/mL [5 x109 total CFU] and PA14 aliquots contained 1.16 x 1010 CFU/mL [2.9 x 109 total CFU]. Aliquots were thawed on ice and washed three times with 1x phosphate buffered saline (PBS) and then re-suspended to 108CFU/250μL.

Porcine Burn Wound Inoculations The Ohio State University’s Institutional Laboratory

Animal Case and Use Committee (protocol #: 2012A00000041-R1) approved all experiments. Female Yorkshire pigs weighing between 70 to 80 pounds were used in this study (n=5).

Porcine infections were carried out as previously described (Roy et al, 2014). A total of 108 CFU of P. aeruginosa, PAO1 transposon library (n=3, PAO1) and PA14 (n=2,

PA14) in 250μL of PBS (1x) was inoculated into the wounds topically 3 days post full- thickness burning. Full-thickness, excisional wound biopsies (oriented in the sagittal

78 plane) were removed at 3, 14, and 28 days post-bacterial inoculation (PI) and placed in

10% neutral buffered formalin (NBF) for >72 hours. Normal/non-burned skin (~1cm) from each side of the wound was included in the biopsy. Skin samples were adhered to wooden tongue depressors to maintain skin shape prior to fixation. Punch biopsies (8mm) were also collected from the wound bed and further bisected for CFU determination and

DNA-isolation. CFU samples were immediately placed on ice, weighed and homogenized in 1mL PBS (1X). Serial dilutions of the homogenate were plated on PIA plates and incubated overnight at 37°C. DNA-isolation samples were immediately placed in ~1.5mL of RNA-later at room temperature for 24 hours then transferred to long-term storage at -80°C.

DNA Isolation Bacterial DNA isolation from porcine tissues were carried out by the

Marvin Whiteley laboratory at the University of Texas at Austin. These methods have been previously described (Turner et al, 2014). Porcine tissue was homogenized by bead beating with pre-loaded Lysing Matrix B (MP Biomedicals) [Mini-Beadbeater (Biospec)] in 1mL of Goodman buffer A (100 mM NaCl, 100 mM Tris-HCl at pH 8, 10 mM EDTA at pH 8, 3.33% SDS, 0.1% sodium deoxycholate). Samples were stored on ice between homogenization intervals. Proteinase K was added to each sample prior to additional homogenization.

Samples from the same wound were pooled and extraction was performed at 4°C with phenol:chloroform:isoamyl alcohol (25:24:1) at pH 8. The aqueous phase was retrieved and precipitated with isopropanol (3M Na-acetate (pH5), 100% isopropanol) at -20°C.

79

The sample was centrifuged and the resultant pellet washed in 1mL 75% ethanol and air dried before reconstituting in water.

RNAse (5μL, 10mg/mL) and sodium chloride (5μL, 5M) was added to each sample for 1 hour at 37°C. The aqueous phase was collected from an extraction with

500μL phenol:chloroform:isoamyl alcohol (25:24:1) at pH8 and ethanol precipitated.

Ethanol precipitation was performed with 3M sodium acetate and cold 100% ethanol at -

20°C. The resultant centrifuged pellet was washed with 75% ethanol and allowed to air dry before reconstituting in water.

Transposon-Sequencing Library Preparation Tn-seq sequencing libraries were prepared as previously described by the Marvin Whiteley laboratory at the University of

Texas at Austin (Goodman et al, 2009; Turner et al, 2014). Sheared DNA fragments were used as template in a linear PCR reaction with a biotinylated primer and linear amplification. Biotinylated PCR products were bound to Streptavidin-coupled Dynabeads

(Invitrogen) and second strands were synthesized as previously described (Goodman et al, 2011 and Turner et al, 2014). Resultant double-stranded DNA was eluted and sequenced by Illumina sequencing. Sequencing of the libraries was performed at the

Genome Sequencing and Analysis Facility at the University of Texas at Austin on a

HiSeq 2000 (Illumina).

Transposon-Sequencing Bioinformatics Analysis Bioinformatics analysis was performed at the University of Texas at Austin, through the Marvin Whiteley laboratory

80 as previously described and presented here in brief (Turner et al, 2014). Transposon sequence reads were mapped and tallied. Differential abundance of the mutants was determined using a Unix, Perl, and R pipeline. Reads containing a transposon end sequence were identified using fqgrep. The transposon-associated sequences were removed and remaining sequences mapped to the P. aeruginosa PAO1 genome. A total of the individual insertions sites and number of reads from each insertion was corrected for amplification bias and smoothed to account for genomic position-dependent effects on apparent abundance. Data was normalized using DESeq.

4.4 RESULTS AND DISCUSSION

Porcine Infections All pigs infected with the PA14 transposon mutant library (n=4) remained clinically healthy for the duration of the experiment. Of the 4 pigs infected with

PAO1 transposon mutant library, 2/4 remained clinically healthy throughout the duration of infection (28 days). A single PAO1 infected pig (AI 01) was euthanized due to signs of systemic illness and disseminated infection including fever (temperature of 107°F) and left forelimb lameness with joint swelling on day 16 post-infection. Gross post-mortem evaluation revealed fibrino-suppurative arthritis of the left carpus. Bacterial cultures were submitted to the Ohio State University College of Veterinary Medicine Clinical

Microbiology Department and were positive for Trueperella pyogenes. A single PAO1 infected animal (AI 02) died abruptly on study from an abdominal hernia of the left flank with small intestinal strangulation. The animal was weighed the morning prior to acute 81 demise with animal technicians reporting uneventful monitoring leading up to finding the animal the following morning. Gross post-mortem revealed ~2 feet of small intestines within the subcutaneous tissues of the left flank through an irregular defect in the abdominal body wall musculature, surrounded by hemorrhage. There were no gross lesions to indicate that this animal had developed a systemic infection or bacterial dissemination due to the wound infliction or infection with transposon library. The premature death of two animals infected with the PAO1 transposon library was unrelated to the inoculation with these bacteria and were a result of secondary infection and possible trauma, respectively.

Wound Parameters Punch biopsy samples of wounds collected on days 3, 14 and 28 post-inoculation (PI) showed decreasing bacterial burdens (Figure 13), which corresponded with wound healing (Figure 14). The cultured biomass of both the PAO1 and PA14 groups remained above 105 CFU/gram of tissue at days 3 and 14 post- inoculation (PI). PA14 infected wounds were significantly smaller in size compared to

PAO1 infected wounds at day 28 PI (Figure 14). The reduced open surface area of the wounds on day 28 post-infection of PA14 infected wounds resulted in only 3 samples being collected per wound versus 5 samples from PAO1 infected wounds.

The similar bacterial burden between these strains yet striking difference in wound healing may be a function of differences in virulence in the porcine wound model or ability to produce chronic infection. Although PA14 is considered more virulent than the PAO1 strain, most infection studies have been carried out in animal models of acute

82 infection (Mikkelsen et al, 2011; Lee et al, 2006). The virulence of PA14 has been attributed to the presence of two pathogenicity islands encoding virulence genes of the type III secretion system or a two-component system controlling chaperone-usher fimbriae (He et al, 2004). These pathogenicity islands are not present in the PAO1 genome (Lee et al, 2006; He et al, 2004). Additionally, the PA14 strain possesses a mutation in the ladS gene leading to attenuated biofilm formation and increased T3SS production (Mikkelsen et al, 2011). These genetic differences between the strains used in this study may account for the difference in rate of wound healing at day 28 PI. Similarly, in a rodent chronic lung infection model, PA14 displayed reduced biomass and reduced competitive index in competition with PAO1 (Kukavica-Ibrulj et al, 2008).

Determinants of PAO1 fitness in the porcine burn wound Due to the lower bacterial yield, PAO1 samples collected at day 14 and 28 PI and all PA14 samples were not used in this analysis. A library of P. aeruginosa, PAO1, transposon mutants was recovered from 3 day old porcine full-thickness burn wound and mutant abundance was profiled by transposon sequencing (Tn-seq) at day 3 PI. A minimum of a 2-fold change in abundance was required for inclusion in this analysis. A total of 141 genes were identified to contribute to fitness (i.e. had reduced abundance) in the porcine chronic wound with a statistical significance of p <0.01, which narrowed to 33 genes with p

<0.05 (Appendix A, Table 6). All genes exhibiting reduced fitness were grouped by functional genomic class provided by PseudoCAP (www.pseudomonas.com). Of the 141 genes, 68 were annotated as hypothetical or putative proteins (68/141=~45%). Given that

83 these exhibit reduced fitness in a chronic wound infection and a subset are not mapped by

KEGG Orthology to various cellular processes, they may warrant further investigation to assign biologic function. Insertions in genes with known/mapped functions primarily belonged to the “Transcriptional Regulator”, “Membrane Proteins” or “Transport of

Small Molecules” functional classes with 13, 19 and 21 genes, respectively.

Of the annotated genes in these categories, many are related to the response to extracellular environment. Within the “Transcriptional Regulators” functional class

(Table 4), three extracytoplasmic function (ECF) sigma factors were identified to be important to wound infection. ECF sigma factors are a part of cell-surface signaling systems that result in a coordinated transcriptional response to extracellular stimuli

(Potvin et al, 2008). Therefore, examining the responses to which P. aeruginosa requires adaptation/response may provide insights into the wound microenvironment and help drive interventions that can be exploited through wound care treatment. The ECF sigma factor vreI, identified in this transposon mutant screen, regulates the transcription of

PUMA3 regulated virulence factors under inorganic phosphate limited conditions sensed by the PhoR-PhoB two-component system (Quesada et al, 2016; Santos-Beneit, 2015;

Faure et al, 2013). Although PUMA3 regulated virulence genes are poorly characterized, they include the type II secretion system (Hxp) and its substrate low-molecular weight mass alkaline phosphatase A (LapA) (Faure et al, 2013). In a zebra fish embryo infection model, PUMA3 regulated genes significantly contributed to virulence and mortality

(Llamas et al, 2009). Adaptation to phosphate limiting environments may therefore be crucial to P. aeruginosa infection of the wound (Lamarche et al, 2008).

84

The transcriptional regulator betI, also identified in this screen, is a choline- responsive transcriptional repressor. With increasing cytosolic concentrations of choline, a water-soluble B vitamin, betI repression is lifted and choline oxidase is functional.

Choline is catabolized to glycine betaine which can either be further processed for energy production or accumulate for osmoprotection (Dingemans et al, 2016). Osmoprotection may be important in the biofilm mode of growth in which there is proposed to be local accumulation of excreted solutes and cell debris causing a hyperosmotic environment

(Dingemands et al, 2016). The use of choline as an energy source may be critical in the wound environment (Wargo, 2013).

External stressors, such as oxidative stress, detergents or excess extracellular pollutants are responded to by P. aeruginosa with mechanisms that also facilitate antibiotic resistance (Poole, 2012 a and b). EsrC is a negative regulator (repressor) of mexCD-oprJ, an antibiotic efflux system and identified in this transposon mutant screen in the porcine wound (Purssell et al, 2015). The transcriptional regulator, esrC, is responsive to envelope stress and is proposed to limit the over-expression of MexCD-

OprJ (Purssell et al, 2015). Perturbing, via envelope stress, a mutant in a second repressor to the mexCD-oprJ system there was a build up of fatty acids which has been proposed to indicate a role in membrane adaptability (Stickland et al, 2010). These findings indicate that when establishing a burn wound infection, adaptations to external pressures are pivotal to the success of P. aeruginosa as a pathogen.

Outer-membrane proteins (OMPs) are complex structures with roles in numerous cell functions important to the response and adaptation to a changing environment. OMPs

85 can serve the bacteria to allow transport across the cell membrane, membrane structural integrity and adhesion or response to other cells (Wexler, 2002). OMPs that serve as transport channels in the outer membrane are referred to as porins or permeases (Galdiero et al, 2003). In the context of host-pathogen interactions, OMPs and porins can facilitate the attachment and invasion of the host epithelial and immune cells and augment their responses to infection (i.e. cytokines) (Galdiero et al, 2012). At least 5/21 of the “Small molecule transporters” are annotated to be outer membrane proteins or porins (Table 4).

The citations provided in this table refer to the demonstrated role in pathogenicity of these OMPs/porins.

Another 9 of the 21 annotated “Small Molecule Transporters” are involved in nutrient acquisition including iron, amino acids, magnesium and nitrogen (Table 4). The acquisition of micronutrients may be important to the pathogenesis of P. aeruginosa when interacting with mammalian hosts (Weir et al, 2008). Iron regulated virulence determinants of P. aeruginosa are heavily studied (Cornelis and Dingemans, 2013). The main iron acquisition compounds produced by P. aeruginosa are pyoverdine and pyochelin, which are considered important to acute virulence. Interestingly these iron acquisition systems were not identified to affect fitness in the porcine burn wound.

Alternatively though the unique iron acquisition systems including iron-regulated extracellular heme-binding protein (hasAp) and a xenosiderophore (fvbA) were identified to have a role in fitness in the burn wound. These findings likely point to the source of iron availability in the iron rich wound environment (i.e. hemoglobin rich) (Yeoh-

Ellerton and Stacey, 2003). The additional importance of magnesium and nitrogen

86 transport in fitness in the wound may be an important avenue for future investigation on the role in virulence (Weir, et al, 2008).

Surprisingly, transposon insertion into 616 individual genes resulted in positive- selection, defined as ≥ 2-fold increase in mutant abundance of the bacterial population in the wound (Appendix B, Table 7). Of these genes ~41% were categorized as hypothetical or putative genes using functional genomic classification provided by PseudoCAP

(www.pseudomonas.com). The functional classes, “Membrane Proteins”, “Small

Molecule Transport” and “Amino Acid Transport” are the groups that contain the most genes. We considered the identification of nutrient transport systems and metabolic pathways to be less significant when identified in higher proportion in the wound due to the redundancy of these systems and the limitations inherent to transposon-sequencing assays. One limitation that cannot be overcome in this assay is the ability for bacteria to share freely available resources present with the wound environment. Thus, genes annotated to be involved in metabolic pathways that displayed increased growth will not be discussed further.

Transposon-insertions into type IVa pili related genes were positively selected for in the porcine burn wound (Table 5). The genes spanned regulatory (two component system pilS-pilR), biogenesis, and structural components. Individual mutants are anticipated to either completely lack type IVa pili or become hyperpiliated and non- functional. This finding is unexpected given the well-documented necessity of pili in establishing acute infection, systemic dissemination and biofilm formation (Tang et al,

1995; Comolli et al, 1999; Hahn, 1997; O’Toole and Kolter, 1998). It is hypothesized that

87 selection for these individual mutants may be multifactorial, including: conservation of energy expenditure from production of this structure or dampening of immune recognition from reduced pathogen associated molecular patterns (PAMPs) recognition.

These hypotheses don’t account for the mutants that are hyper-piliated but non- functional. Therefore, it is accepted here that there may be a yet to be recognized immune evasion function of pili, independent of adhesion or motility. This has been demonstrated in piliated but non-functional mutants, which were able to resist phagocytosis from innate immune cells at equivalent rates as wild-type (Tan et al, 2014). However, a non-piliated mutant is efficiently opsonized and fails to establish infection in a rodent lung infection model (Tan et al, 2014).

Our findings are consistent with studies carried out by Skurnik et al (2013a) in which transposon insertions in pilus genes were positively selected for in a rodent model of cecal colonization. In the Skurnik et al (2013a) experiments, the transposon library was fed orally and colonized an intact mucosal surface (cecal lumen). This is in contrast to our studies present here where the bacteria were topically inoculated onto the burned surface, which lacks intact epithelium. These differences would indicate that functional pili are not required for colonization of the murine gastrointestinal mucosal epithelium or attachment to burn eschar of the porcine burn wounds. Other surface binding lectins may be more important, such as LecB, which was shown to be crucial for P. aeruingosa pig burn wound infection in this study and in a murine mouse infection (Chemani et al,

2009). The pili mutants identified in Skurnik’s (2013a) study, however, failed to spread

88 systemically when neutropenia was induced indicating that pili are still required for systemic dissemination.

Our results, regarding the necessity of type IV pili, are in direct contrast to the studies carried out by Turner et al (2014) in which pili were identified to be important for both acute and chronic skin infections. Using the same PAO1 transposon library as utilized in the present study, Turner et al injected bacteria into the subcutis of cutaneous burn wounds of mice. This is an acute infection model resulting in death within 48 hours.

The chronic wound model used by the Turner et. al. (2014) group topically inoculated excisional wounds in mice, which results in chronic (~8 days) wounds. Therefore, the difference between these two studies may be due to differences in the species used

(mouse versus pig), method of wounding or bacterial inoculation. Animal model species could play a significant role in the outcome of infection and importance of virulence factors in establishing and maintaining infection. In a screen of P. aeruginosa virulence factors using multiple species (i.e. Caenorhabditis elegans, Drosophila melanogaster, human and mouse), virulence was found to be host specific (Dubern et al, 2015). In the

Turner et al (2014) studies the acute infections result in septicemic death and it is anticipated as indicated by the Skurnik et al (2013a) study and others that pili may be required for systemic dissemination. Systemic infection is not a feature of the porcine chronic wound model employed here (Roy et al, 2014). The chronic wound models used by the Turner et al (2014) group and ourselves differ in the method of establishing the initial wound. The porcine model uses a 3rd degree burn wound that sterilizes the wound site and due to vascular coagulation within the wound site, delays cellular infiltration into

89 the center of the wound. The murine model uses an excisional wound that maintains vascular perfusion and tissue viability at the site of bacterial inoculation. Therefore, the wound sites are different with regards to the cellular defense mechanisms encountered, oxygen tension and nutrient availability at the time of establishing infection. These findings warrant more detailed investigation into the role of type IVa pili in P. aeruginosa induced chronic disease and call into question the effectiveness of therapies that are designed to target this bacterial appendage.

Indicated by the above results, there may be a unique demand placed on P. aeruginosa when encountering the burn wound. The lack of an intact barrier function, the relative sterility of the acute burn wound and protected niches within the wound from innate immune cells early in the course of injury characterize the wounds in this model.

Therefore, it is not surprising that several virulence factors were identified within the positively selected pool of transposon mutants. Virulence factors are considered to be essential for epithelial barrier break down and local tissue invasion, innate immune evasion and the acquisition of host-limited nutrients such as iron. Of the myriad genes involved in acute virulence, cyclic AMP is recognized as the an important mediator of their expression (Coggan and Wolfgang, 2012). Cylcic AMP is generated by adenylate cyclases (AC). Three intracellular AC enzymes exist in P. aeruginosa of which CyaB is the most productive and essential for host infection (Wolfgang et al, 2003a; Smith et al,

2004). cAMP binds to and regulates the activity of the transcription factor, vfr, virulence factor regulator which regulates the expression of numerous virulence factor genes

(Wolfgang et al 2003a; Suh et al, 2002).

90

Multiple genes associated with the cAMP/vfr signaling pathway were positively selected for in the porcine chronic wound. A fitness benefit was conferred to mutants with insertions in the cyaB and vfr genes. In acute infections models, cyaB and vfr have attenuated virulence (Smith et al, 2004). cAMP/vfr regulated genes include type IV pili, type III and type II secretion systems and toxins (Coggan and Wolfgang, 2012). Using the KEGG Orthology pathway mapping function (Table 5), a surprising number of genes mapped to these categories. The positive selection for numerous type IV pili genes has already been discussed. Flagellar-related genes were more prone to contain both positively and negatively selected genes attributed to transposon insertion in the burn wound. While flagella are considered essential to host infection and biofilm formation they are also highly immunogenic (Feldman et al, 1998; Sadikot et al, 2005). The loss of flagella in mature biofilms is considered pivotal to immune evasion in pulmonary infections in cystic fibrosis (Wolfgang et al, 2004). However, there is evidence to indicate that the swimming motility conferred by functional flagella is the stimulus for immune recognition by a yet to be determined mechanism (Amiel et al, 2010). Bacteria possessing flagella that display various degrees of motility dysfunction are still capable of immune cell evasion (Lovewell et al, 2011). This may account for the fitness advantage conferred by the transposon disruption of some flagella associated genes and the loss of fitness by others. These findings suggest that some commonly studied acute virulence factors may not be essential to establishing infection in the porcine burn wound. This is suspected to be due to the breakdown of host defenses that occur in the process of soft tissue injury

(discussed earlier). Without an epithelial barrier and a nutrient rich necrotic wound bed,

91 acute virulence factors required for nutrient acquisition and cytolysis may not be essential to establishing infection in a burn wound.

The results presented here represent a single time point. We suspect that focusing on a single time point may limit the overall interpretation of these findings. Although it is anticipated that innate immune effectors are present at 3 days PI, chronic wounds develop complex adaptive and chronic inflammation that is not present at day 3 PI. Thus, the interval in which type IV pili may be essential to establishing infection could have lapsed by prior to sampling (i.e. days 1-2 post-inoculation). Similarly the mixed necessity of flagellar genes may indicate that there is a transition towards or lapsed requirement for fitness at the time point investigated here. Additional analysis of later or earlier time points may help address the evolution of genetic determinants of fitness.

4.5 CONCLUSIONS

P. aeruginosa is highly adaptable bacteria, capable of inhabiting a wide range of environmental and host niches. The virulence of P.aeruginosa is proposed to have derived from its success at adapting to environmental pressures encountered in dry, soil, plant and moist habitats (Hilbi et al, 2007). To establish mammalian disease, P. aeruginosa is considered to establish itself when host defenses are weakened (i.e. opportunistic conditions) and not de novo or as a primary pathogen. This may explain why environmental and clinical isolates share virulence mechanisms, these mechanisms are pre-existing from adaptation of environmental conditions (Wolfgang et al, 2003b).

The studies undertaken here offer a unique insight into the essentiality of the P. 92 aeruginosa genome for burn wound infection. The pig is a highly relevant animal model by which to study human disease and immune responses (Meurens et al, 2012). It is proposed that studies carried out in this animal may be more likely to predict clinically relevant targets for intervention in host-pathogen interactions. Differences in the local skin anatomy, physiology and systemic immune responses in this host compared to the more commonly utilized murine models may account for differences in the genes indicated as being essential for fitness.

The remarkable capacity of this organism to be responsible for vastly different clinical outcomes (acute and chronic disease) is a testament to the inherent adaptability of this organism’s genome. The positive selection of transposon mutants in well-studied acute virulence factors (cAMP/vfr system) may not be surprising given the unique environment that the burn wound presents. With most of the host barrier functions being weakened or delayed it may allow sufficient time for P. aeruginosa to establish infection such as biofilm growth. Under the conditions employed here, we have identified that micronutrient acquisition may influence host adaptation and virulence. Therefore, in the treatment of chronic wounds and developing preventative interventions targeting acute virulence factors and pili may not produce resolution or prevention of colonization in the burn wound.

93

Bacterial Burden from Burn Wound *** 1010 109 e 8 Inoculating Dose u 10 s

s 7 i

t 10

f 6

o 10 5 m 10 a

r 4

g 10 / 3 U 10 F 2 C 10 PA14 1 10 PAO1 100 Day 3 Day 14 Day 28 Days post infection

Figure 13. Bacterial Burden of Porcine Wounds with Bacterial Transposon Library Infections.

Porcine third-degree burn wounds were topically inoculated with a transposon library of either P. aeruginosa strain PAO1 or PA14. Over the course of infection (days 3, 14 and 28 post inoculation), random punch biopsy samples were taken for colony forming unit (CFU) determination per gram of tissue. The graph represents a scatter plot with median (horizontal bar) calculation of individual biopsies taken from n=3 pigs for PAO1 infections (red/inverted triangles) at day 3 PI and n=2 for days 14 and 28 PI and n=2 pigs for all times points of PA14 infected pigs (black/upright triangles). The dashed horizontal line indicates the inoculating dose of 108 bacteria per wound. Statistical analysis performed using a 2-way ANOVA and Bonferroni post-test with statistical significance set to a p-value <0.05.

94

Figure 14. Healing Porcine Burn Wounds Infected with P. aeruginosa Transposon Mutant Library

Porcine 3rd degree burn wounds (2” square) were topically inoculated with either P. aeruginosa strain transposon library, PAO1 or PA14. Wound healing was monitored by visual measurements of epithelial defect at days 3, 14 and 28 post-inoculation (PI). Representative images are presented from 3 days PI from PAO1 and PA14 (panel A and B, respectively) and 28 days PI (panels C and D, respectively). PA14 infected wounds at day 28 PI (panel D) were markedly reduced in size in comparison to the open PAO1 infected wounds at day 28 (panel C). Scale bar (1cm) for all images is present in panel A.

95

Transcriptional Regulators Faure et al, 2013; PA0675 vrel ECF sigma factor Llama et al, 2009 PA1363 ECF sigma factor Llamas et al, 2014 PA4896 ECF subfamily Llamas et al, 2014 Dingemands et al, 2016; Wargo, PA5374 betI Transcriptional regulator 2013 PA3571 mmsR Transcriptional regulator Steele et al, 1992 PA4596 esrC Transcriptional regulator Purssell et al, 2015 Transport of small molecules/Membrane Proteins PA0427 oprM Outer membrane efflux pump Hirakata et al, 2002 PA4208 opmD Outer membrane protein precursor Aendekerk et al, 2005 PA1025 opdD Probable porin, amino acid transport Tamber et al, 2006 PA2700 opdB Proline porin, amino acid transport Tamber et al, 2006 PhoP/Q and low Mg2+ inducible outer Bell et al, 1991; Edrington et al, PA1178 oprH membrane protein H1 precursor 2011 PA5268 corA Magnesium/cobalt transport protein Groisman et al, 2013 PA1339 aatP D-amino acid transport Sanchez et al, 2013 PA2041 Amino acid permease PA3407 HasAp Heme acquisition protein Létoffé et al, 1998 PA4156 fvbA Siderophore transport Elias et al, 2011 Chen and Beatti, 2007; Malek et PA3891 opuCA OpuC ABC transporter al, 2011 PA5287 amtB Ammonium transporter Vermeiren et al, 2002 PA5288 glnK Nitrogen regulatory protein Alvarez-Ortega et al, 2010 Quorum Sensing PA0427 oprM multidrug ABC transporter PA3361 lecB fucose-binding lectin, PAIIL PA3250 Hypothetical protein PA1002 phnB anthranilate synthase component II Flagellar System PA3349 chemotaxis protein PA0180 cttP chemotactic transducer for trichloroethylene PA4954 motA flagellar motor proteins PA3350 flgA flagellar body P-ring biosynthesis protein PA1080 flgE flagellar hook protein PA1441 hypothetical protein Type VI secretion system PA0093 tse6 effector, protein secretion in type 6 secretion PA1510 tle4 phospholipase, bacterial immunity

Table 4. Essential Genes of P. aeruginosa, PAO1, in the Porcine Burn Wound

96

Table 5. Positively Selected Genes of P. aeruginosa, PAO1, in the Burn Wound

97

CHAPTER 5. DISCUSSION

Chronic wounds have devastating social and economic impact (Sen et al, 2009;

Lindholm and Searle, 2016). Sequelae from delayed wound healing include amputation, septicemia and death (Lindholm and Searle, 2016; Sen et al, 2009). There have been significant scientific advances in our understanding of chronic wound pathogenesis, which have been translated to bedside treatments (Frykberg and Banks, 2015). However, there remain millions of people with chronic wounds that can persist for over a year from a myriad of inciting soft tissue injuries (Lindholm and Searle, 2016). Inherent to the loss of epidermal barrier function, chronic wounds readily permit bacterial colonization and infection. Culture-dependent and –independent methods confirm that the chronic wound is a poly-microbial environment (Kirkup, 2015). However, the most commonly identified bacterial species are the opportunistic pathogens Staphylococcus aureus and

Pseudomonas aeruginosa. Within the wound these bacteria are largely present as mono- species biofilms (Burmølle et al, 2010). This sessile aggregated lifestyle confers a profound recalcitrance to endogenous and exogenous host anti-microbials making treatment almost impossible. Identifying a reliable and effective, broadly applicable bacterial biofilm preventative or anti-biofilm treatments have been limited. Since the

98 population of people susceptible to developing chronic wounds is not diminishing it remains imperative to identify novel methods of combatting biofilm infections.

Modeling this complex system in a clinically relevant animal model for the purpose of investigating bacterial contributions to delayed wound healing and novel treatments is challenging. It has become clear that developing a single animal model to recapitulate the numerous conditions under which chronic wounds can develop is not a realistic goal (Nunan et al, 2014). However, small animal models, uncomplicated by significant co-morbidities, maintain wounds for only ~2 weeks (Ganesh et al, 2015).

Therefore, the interface that develops between the biofilm, inflammation and extracellular matrix over months is minimally reflected in these models. Meanwhile, porcine wound models have proven more successful, with wounds lasting ~ 2months

(Ganesh et al, 2015; Nunan et al, 2014). The similarities in anatomy, physiology and immune responses between humans and pigs make these models ideal (Sullivan et al,

2001).

Wound healing studies have largely focused on the endpoint of re-establishing a contiguous epidermal barrier. However, the process of wound healing is a complicated biologic function requiring numerous well-orchestrated cellular processes with cross-talk between epidermal and dermal cellular components as well as the immune system

(Schultz et al, 2011). The focus on epidermal continuity alone does not equate to effective wound closure. Roy et al (2014) established that gross or histologic evidence of a re-epithelialized surface does not equate to adequate wound closure. Rigorous evaluation of all components contributing to soft tissue healing provides a more complete

99 understanding of the effects of treatments or infection on the host and potential targets for intervention or causes of treatment failures.

To this point, in studies presented here (Chapter 2), re-epithelialization rates did not differ in the porcine burn wound when infected with either S. aureus or P. aeruginosa. However, there were significant differences between these infections when evaluating the immune response and vascular competency of the neovascularized wound bed (i.e. granulation tissue). Specifically, P. aeruginosa infected wounds exuded copious amounts of fluid compared to un-infected wounds or S. aureus infected wounds. Since extensive burn wounds are complicated by increased vascular permeability the presence of P. aeruginosa may exacerbate this phemoenon and hasten the development of hypovolemic shock in these patients (Tiwari, 2012). P. aeruginosa infected wounds contain more neutrophils at early time points and more robust lymphocyte and plasma cell infiltration into the chronic wound than S. aureus infection. S. aureus wounds were infiltrated by high numbers of eosinophils in late stages of infection. Eosinophils may prove to be a component of effective S. aureus clearance or indicative of the maladaptive immune responses incited by this pathogen in the skin (Lee et al, 2010; Rodriguez-

Fernandez et al, 2013; Thurlow et al, 2011; Hanke and Keilin, 2009). Further investigations are required to understand the impact of these differences in host immune responses to infection with S. aureus or P. aeruginosa on wound healing. However, it is clear that in the chronic wound the host response can be augmented in a bacterial dependent manner.

100

Uniquely, in the studies we present here, mono-species infections re-capitulate the hyper-proliferative wound edge defining human chronic wounds (Pastar et al, 2014;

Golinko et al, 2009; Stojadinovic et al, 2013). This may be due the protracted time-course we are able to achieve or a unique response to burning and bacterial infection that is not incited in existing excisional porcine models (Pastar et al, 2014; Ganesh et al, 2015).

However this hyper-proliferative phenotype expressed by either microbe alone is lost in co-infection. Synergism of these bacterial species in the porcine chronic wound is evident by the marked delay in wound healing with blunted proliferation and migration of the wound edge in co-infected wounds. These findings are in agreement with the porcine partial thickness excisional wound model study by Pastar, et al (2013) where co-infected wounds healed at a slower rate than mono-infected wounds. Similar studies have found that unique to the wound environment S. aureus and P. aeruginosa may enhance virulence (DeLeon et al, 2014). While the relationship between these bacteria ranges from mutualistic to parasitic, the impact in the chronic wound has been difficult to dissect

(Nguyen and Oglesby-Sherrouse, 2016; DeLeon et al, 2014). There is a need for future studies to correlate the microscopic pathology, microbiology and outcomes of human chronic wounds (Thomson, 2011). These studies have been limited in the past due to an apprehension to remove excisional biopsies from chronically injured skin. However, these procedures hinder wound healing (Panuncialman et al, 2010) and there is a recently recognized utility in analyzing debrided tissue samples (Golinko et al, 2009; Stojadinovic et al, 2013). Such studies will help us interpret the relevance of animal model studies and the role of bacterial infection on host responses. Importantly, the rubric established in this

101 study provides a systematic approach to microscopic evaluation of wounds to identify differences in the host response to infection or treatment modalities. By establishing a consistent evaluation schematic that can be adopted for any wound type, intervention or infection, we can reduce experimental redundancy and permit direct comparisons between published studies.

Chronic wounds remain in a pro-inflammatory state that negatively impacts the progression of wound healing by exuberant production of unbalanced proteolytic substances and stimulatory cytokines (Frykberg and Banks, 2015). The recalcitrance of bacterial biofilms to host clearance mechanisms is thought to incite protracted and unresolving inflammation. Neutrophils are the first responder to tissue damage and infection, containing potent antimicrobials that are otherwise able to clear the planktonic counterparts of bacterial biofilms. In the laboratory, neutrophils are capable of phagocytizing biofilms of S. aureus and P. aeruginosa (Leid et al, 2002; Günther et al,

2009; Jesaitis et al, 2003; Hanke et al, 2013; Thurlow et al, 2011). However, there remains a black box around how this could still result in defective clearance by the coordinated efforts of a competent immune system. In this vane, there are numerous studies on the contributions of individual virulence factors unique to each bacterial species to evading the host immune system.

Neutrophils are the first responders to S. aureus and P. aeruginosa infections in the porcine burn wound, albeit in differing amounts. This cell influences many of the cellular components within the immediate vicinity and adaptive immune responses.

Neutrophils produce a large and diverse number of pro-inflammatory cytokines when

102 exposed to P. aeruginosa independent of biofilm formation. Intriguingly though, biofilms of P. aeruginosa induce GM-CSF production and not IFN-gamma production. GM-CSF plays a critical role in enhancing the survival and local concentration of inflammatory cells like neutrophils and macrophages. The lack of INF-gamma may indicate that the resultant inflammation at the site of biofilm infections with P. aeruginosa may be poorly stimulated to perform anti-microbial functions. Previous work in small animal models of

P. aeruginosa infection has tested the role of IFN-gamma in achieving bacterial clearance with incongruous results (Nieuwenhuis et al, 2002; Johansen et al, 1996; Murphey et al,

2004; Schultz et al, 2001; Hazlett et al, 2002). However, in cystic fibrosis patients lower levels of IFN-gamma correlated with chronic P. aeruginosa infection (Moser et al, 2000).

In this same study, higher levels of IFN-gamma correlated with better lung function

(Moser et al, 2000). Therefore, the neutrophil may contribute to priming the wound environment towards P. aeruginosa survival by inhibiting effective immune clearance.

In stark contrast, S. aureus exposed neutrophils incited minimal cytokine responses from the neutrophil compared to control, unstimulated neutrophils. This is surprising given the high degree of cell death with loss of cell membrane integrity

(detected by lactate dehydrogenase release). It is speculated that this blunted immune response may be an S. aureus specific mechanism of immune evasion. Although, S. aureus is capable of producing marked cytolysis of numerous cell types and this expression of virulence contributes to abscess formation in the host; S. aureus infection did not result in abscess formation in the pig wound (Kobayashi et al, 2015). Cell death may not be a predominant feature of S. aureus virulence in the porcine wound. In other

103 infections models S. aureus was capable of surviving within neutrophils or displayed less apoptosis compared to neutrophils draining from the infection site (Gresham et al, 2000,

Hampton et al, 2015). The ability of neutrophils to leave the site of S. aureus skin infection and interact with lymphocytes in draining lymph nodes augments local adaptive immune responses (Hampton et al, 2015; Kamenyeva et al, 2015). Therefore, although it has been speculated that neutrophils may be less important to chronic wound infections with S aureus, since they are present in lower numbers, they may play a crucial role in blunting immune responses driven by interactions with neutrophils (Thurlow et al, 2011;

Hanke and Kielian, 2012, Hanke et al, 2013). In support of this hypothesis, Greenlee-

Wacker et al (2014) identified the inhibition of macrophage efferocytosis function dependent on the induction of necroptosis in neutrophils that have phagocytized S. aureus. Necroptosis is a programmed cell death pathway that can attenuate pro- inflammatory signals (Kearney et al, 2015). Further study is required to investigate the relevance of this mechanism in the chronic wound setting.

There has been great advancement in our understanding of bacterial virulence factors that contribute to acute infection. However, the significance of these virulence factors to chronic disease has been less clear. The availability of deep sequencing technologies and our clinically relevant, chronic wound model has allowed us to take a relatively unbiased approach to addressing this question. By surveying the fitness of a P. aeruginosa transposon mutant library within the porcine chronic wound it became clear that the wound may represent a unique environment to which P. aeruginosa must adapt.

Strikingly, using strict statistical criteria, only 33 genes were identified to contribute to

104 fitness in the porcine burn wound. A large proportion of these were hypothetical.

Assigning function to these may help us understand bacterial adaptation to the wound.

Intriguingly, the type IV pilus of P. aeruginosa, a major virulence determinant in acute infection of the lung and septicemia, was not required for fitness in the porcine wound. The pilus is considered essential for attachment to an epithelial surface and provides motility for invasion/dissemination. Therefore, it is not surprising that it was not identified as crucial for infection in the chronic wound. The burn wound lacks an epithelial surface and consists of necrotic tissue. Also, chronic infections are characterized by the lack of dissemination. Similarly, acute virulence factors are aimed at breaking down host barrier functions and inciting tissue lysis to allow for colonization, invasion and dissemination. Therefore the acute virulence factors regulated by the

Vfr/CyaB regulon may not be essential to establishing infection in the burn wound due to a similar rationale. These findings have important implication for antimicrobial drug development.

Targeting acute virulence factors or the type IV pilus may not serve to prevent colonization or infection in the chronic wound context. Although they may be directed at preventing the sequelae of dissemination and sepsis once infection has been established

(Wagner et al, 2016). Since we identified small molecule sensing or ion acquisition systems as essential in the chronic wound these may be better targets for inhibiting the establishment of infection. This may help explain the success that has been afforded wound healing when using chelators such as ethylenediaminetetraacetic acid (EDTA)

(Finnegan and Pervical, 2015). Chelation contributes to inhibition of biofilm formation

105 and potentiates antibiotic effectiveness by inducing biofilm dispersion in several bacterial species (Finnegan and Percival, 2015; Banin et al, 2006). Although when using clinical isolates of P. aeruginosa in vitro, biofilm formation was inconsistently inhibited (Zenga et al, 2012). The lack of metabolic pathways being present in the list of genes required for fitness may indicate that the wound is nutrient rich and P. aeruginosa is highly adaptable to maximize the use of these nutrients. Lessons gleaned from attempts to target bacterial central metabolism has indicated that there is marked redundancy in these pathways; which may heighten the difficulty in finding novel targets (Murima et al, 2014).

The work presented here demonstrates that P. aeruginosa and S. aureus are each capable of altering the host response to infection in unique ways, ultimately resulting in delayed wound healing. Intriguingly, mutations in known virulence factors of P. aeruginosa did not hinder this versatile pathogen from establishing chronic infection in the porcine wound environment. The outcomes of innate immune interaction are drastically different and depend more significantly on pathogen and not biofilm formation. In the chronic wound the contribution of infective bacterial species affects more than just the immune system with perturbations of epithelialization and vascular integrity. The foundation laid out by this work will help support future experiments geared to identifying novel treatment strategies.

106

REFERENCES

Abtin, A., Jain, R., Mitchell, A.J., Roediger, B., Brzoska, A.J., Tikoo, S., Cheng, Q., Ng, L.G., Cavanagh, L.L., von Andrian, U.H., Hickey, M.J., Firth, N., Weninger, W., 2014. Perivascular macrophages mediate neutrophil recruitment during bacterial skin infection. Nat Immunol. 15(1):45-53.

Aendekerk, S., Diggle, S.P., Song, Z., Høiby, N., Cornelis, P., Williams, P., Cámara, M., 2005. The MexGHI-OpmD multidrug efflux pump controls growth, antibiotic susceptibility and virulence in Pseudomonas aeruginosa via 4-quinolone-dependent cell- to-cell communication. Microbiology. 151(Pt 4):1113-25.

Akers, K.S., Mende, K., Cheatle, K.A., Zera, W.C., Yu, X., Beckius, M.L., Aggarwal, D., Li, P., Sanchez, C.J., Wenke, J.C., Weintrob, A.C., Tribble, D.R., Murray, C.K., 2014. Infectious Disease Clinical Research Program Trauma Infectious Disease Outcomes Study Group. Biofilms and persistent wound infections in United States military trauma patients: a case-control analysis. BMC Infect Dis. 8;14:190.

Akira, S., Uematsu, S., Takeuchi, O., 2006. Pathogen recognition and innate immunity. Cell. 124(4):783-801.

Alhede, M., Bjarnsholt, T., Givskov, M., Alhede, M., 2014. Pseudomonas aeruginosa biofilms: mechanisms of immune evasion. Adv Appl Microbiol. 86:1-40.

Almblad, H., Harrison, J.J., Rybtke, M., Groizeleau, J., Givskov, M., Parsek, M.R., Tolker-Nielsen, T., 2015. The Cyclic AMP-Vfr Signaling Pathway in Pseudomonas aeruginosa Is Inhibited by Cyclic Di-GMP. J Bacteriol. 197(13):2190-200.

Alvarez-Ortega, C., Wiegand, I., Olivares, J., Hancock, R.E., Martínez, J.L., 2010. Genetic determinants involved in the susceptibility of Pseudomonas aeruginosa to beta- lactam antibiotics. Antimicrob Agents Chemother. 54(10):4159-67.

Alhazmi, A., 2015. Pseudomonas aeruginosa—Pathogenesis and Pathogenic Mechanisms. Int J Biology. 7(2): 44-67.

Amiel, E., Lovewell, R.R., O'Toole, G.A., Hogan, D.A., Berwin, B., 2010. Pseudomonas aeruginosa evasion of phagocytosis is mediated by loss of swimming motility and is independent of flagellum expression. Infect Immun. 78(7):2937-45. 107

Amulic, B., Cazalet, C., Hayes, G.L., Metzler, K.D., Zychlinsky, A., 2012. Neutrophil function: from mechanisms to disease. Annu Rev Immunol. 30:459-89.

Archer, N.K., Mazaitis, M.J., Costerton, J.W., Leid, J.G., Powers, M.E., Shirtliff, M.E., 2011. Staphylococcus aureus biofilms: Properties, regulation and roles in human disease. Virulence. 2(5):445-459.

Babior, B.M., 1994 Activation of the respiratory burst oxidase. Environ Health Perspect. 1994. 102 Suppl 10:53-6.

Banin, E., Brady, K.M., Greenberg, E.P., 2006. Chelator-Induced Dispersal and Killing of Pseudomonas aeruginosa Cells in a Biofilm. Applied and Environmental Microbiology. 72(3):2064-2069.

Barbieri, J. T., Sun, J., 2004. Pseudomonas aeruginosa ExoS and ExoT. Rev Physiol Biochem Pharmacol 152:79-92.

Baviera, G., Maiello, N. and Galli, E., 2015. Staphylococcus aureus and atopic dermatitis: which came first, the chicken or the egg?. European Medical Journal.

Beekhuizen, H., van de Gevel, J.S., 2007. Gamma interferon confers resistance to infection with Staphylococcus aureus in human vascular endothelial cells by cooperative proinflammatory and enhanced intrinsic antibacterial activities. Infect Immun. 75(12):5615-26.

Beenken, K.E., Dunman, P.M., McAleese, F., Macapagal, D., Murphy, E., Projan, S.J., Blevins, J.S., Smeltzer, M.S., 2004. Global gene expression in Staphylococcus aureus biofilms. J Bacteriol. 186(14):4665-84.

Beidler, S.K., Douillet, C.D., Berndt, D.F., Keagy, B.A., Rich, P.B., Marston, W.A., 2009. Inflammatory cytokine levels in chronic venous insufficiency ulcer tissue before and after compression therapy. J Vasc Surg. 49(4):1013-20.

Bielecki, P., Glik, J., Kawecki, M., Martins dos Santos, V.A., 2008. Towards understanding Pseudomonas aeruginosa burn wound infections by profiling gene expression. Biotechnol Lett. 30(5):777-90.

Bell, A., Bains, M., Hancock, R.E., 1991. Pseudomonas aeruginosa outer membrane protein OprH: expression from the cloned gene and function in EDTA and gentamicin resistance. Journal of Bacteriology. 173(21):6657-6664.

108

Bjarnsholt, T., Kirketerp-Møller, K., Jensen, P.Ø., Madsen, K.G., Phipps, R., Krogfelt, K., Høiby, N., Givskov, M., 2008. Why chronic wounds will not heal: a novel hypothesis. Wound Repair Regen. 16(1):2-10.

Blair, J.M.A., Richmond, G.E., Bailey, A.M., Ivens, A., Piddock, L.J.V., 2013. Choice of Bacterial Growth Medium Alters the Transcriptome and Phenotype of Salmonella enterica Serovar Typhimurium. PLoS ONE 8(5): e63912.

Bogdan, C., Gessner, A., Röllinghoff, M., 1993.Cytokines in leishmaniasis: a complex network of stimulatory and inhibitory interactions. Immunobiology. 189:356–396.

Bowler, P.G., Duerden, B.I., Armstrong, D.G., 2001. Wound Microbiology and Associated Approaches to Wound Management. Clinical Microbiology Reviews. 14(2):244-269.

Brett, D., 2008. A Review of Collagen and Collagen-based Wound Dressings. Wounds. 20(12):347-56.

Budzyń, M., Iskra, M., Krasiński, Z., Dzieciuchowicz, Ł., Kasprzak, M., Gryszczyńska, B., 2011. Serum iron concentration and plasma oxidant-antioxidant balance in patients with chronic venous insufficency. Med Sci Monit. 17(12):CR719-27.

Burmølle, M., Thomsen, T.R., Fazli, M., Dige, I., Christensen, L., Homøe, P., Tvede, M., Nyvad, B., Tolker-Nielsen, T., Givskov, M., Moser, C., Kirketerp-Møller, K., Johansen, H.K., Høiby, N., Jensen, P.Ø., Sørensen, S.J., Bjarnsholt, T., 2010. Biofilms in chronic infections – a matter of opportunity - monospecies biofilms in multispecies infections. FEMS Immunol Med Microbiol. 59(3):324-36.

Burrows, L.L., 2012. Pseudomonas aeruginosa twitching motility: type IV pili in action. Annu Rev Microbiol. 66:493-520.

Cassatella, M.A., 1999. Neutrophil-derived proteins: selling cytokines by the pound. Adv Immunol. 73:369-509.

Chalabaev, S., Chauhan, A., Novikov, A., Iyer, P., Szczesny, M., Beloin, C., Caroff, M., Ghigo, J.M., 2014. Biofilms formed by gram-negative bacteria undergo increased lipid a palmitoylation, enhancing in vivo survival. MBio. 5(4). pii: e01116-14.

Chekabab, S.M., Silverman, R.J., Lafayette, S.L., Luo, Y., Rousseau, S., Nguyen, D., 2015. Staphylococcus aureus Inhibits IL-8 Responses Induced by Pseudomonas aeruginosa in Airway Epithelial Cells. PLoS One. 10:e0137753.

109

Chemani, C., Imberty, A., de Bentzmann, S., Pierre, M., Wimmerová, M., Guery, B.P., Faure, K., 2009. Role of LecA and LecB lectins in Pseudomonas aeruginosa-induced lung injury and effect of carbohydrate ligands. Infect Immun. 77(5):2065-75.

Chen, C., Beattie, G.A., 2007. Characterization of the osmoprotectant transporter OpuC from Pseudomonas syringae and demonstration that cystathionine-beta-synthase domains are required for its osmoregulatory function. J Bacteriol. 189(19):6901-12.

Cheung, D.O., Halsey, K., Speert, D.P., 2000. Role of pulmonary alveolar macrophages in defense of the lung against Pseudomonas aeruginosa. Infect Immun. 68(8):4585-92.

Cigana, C., Curcurù, L., Leone, M.R., Ieranò, T., Lorè, N.I., Bianconi, I., Silipo, A., Cozzolino, F., Lanzetta, R., Molinaro, A., Bernardini, M.L., Bragonzi, A., 2009. Pseudomonas aeruginosa exploits lipid A and muropeptides modification as a strategy to lower innate immunity during cystic fibrosis lung infection. PLoS One. 4(12):e8439.

Cigana, C., Lorè, N.I., Bernardini, M.L., Bragonzi, A., 2011. Dampening Host Sensing and Avoiding Recognition in Pseudomonas aeruginosa Pneumonia. J Biomed Biotechnol. 2011:852513.

Ciornei, C.D., Novikov, A., Beloin, C., Fitting, C., Caroff, M., Ghigo, J.M., Cavaillon, J.M., Adib-Conquy, M., 2010. Biofilm-forming Pseudomonas aeruginosa bacteria undergo lipopolysaccharide structural modifications and induce enhanced inflammatory cytokine response in human monocytes. Innate Immun.16, 288-301.

Coggan, K.A., Wolfgang, M.C., 2012. Global regulatory pathways and cross-talk control Pseudomonas aeruginosa environmental lifestyle and virulence phenotype. Curr Issues Mol Biol. 14(2):47-70.

Cooper, D.M., Yu, E.Z., Hennessey, P., Ko, F., Robson, M.C., 1994. Determination of endogenous cytokines in chronic wounds. Ann Surg. 219(6):688-91; discussion 691-2.

Comolli, J.C., Hauser, A.R., Waite, L., Whitchurch, C.B., Mattick, J.S., Engel, J.N., 1999. Pseudomonas aeruginosa gene products PilT and PilU are required for cytotoxicity in vitro and virulence in a mouse model of acute pneumonia. Infect Immun. 67(7):3625- 30.

Cornelis, P., Dingemans, J., 2013. Pseudomonas aeruginosa adapts its iron uptake strategies in function of the type of infections. Front Cell Infect Microbiol. 3:75.

Cowell, B.A., Evans, D.J., Fleiszig, S.M., 2005. Actin cytoskeleton disruption by ExoY and its effects on Pseudomonas aeruginosa invasion. FEMS Microbiol. Lett. 250, 71-76. Cruikshank, W.W., Kornfeld, H., Center, D.M., 2000. Interleukin-16. J Leukoc Biol. 67(6):757-66. 110

Cullen, L., McClean, S., 2015. Bacterial Adaptation during Chronic Respiratory Infections. Kowalski ML, ed. Pathogens. 4(1):66-89.

D'Argenio, D.A., Wu, M., Hoffman, L.R., Kulasekara, H.D., Deziel, E., Smith, E.E., Nguyen, H., Ernst, R.K., Larson Freeman, T.J., Spencer, D.H., 2007. Growth phenotypes of Pseudomonas aeruginosa lasr mutants adapted to the airways of cystic fibrosis patients. Mol. Microbiol. 64, 512–533.

Danielsen, L., Balslev, E., Döring, G., Høiby, N., Madsen, S.M., Agren, M., Thomsen, H.K., Fos, H.H., Westh, H., 1998. Ulcer bed infection. Report of a case of enlarging venous leg ulcer colonized by Pseudomonas aeruginosa. APMIS. 106(7):721-6.

Darby, I.A., Laverdet, B., Bonté, F., Desmoulière, A., 2014. Fibroblasts and myofibroblasts in wound healing. Clin Cosmet Investig Dermatol. 7, 301-311.

Dasgupta, N., Ferrell, E.P., Kanack, K.J., West, S.E., and Ramphal, R., 2002. fleQ, the gene encoding the major flagellar regulator of Pseudomonas aeruginosa, is σ70 dependent and is downregulated by Vfr, a homolog of Escherichia coli cyclic AMP receptor protein. J. Bacteriol. 184, 5240-5250.

Davies, D., 2003. Understanding biofilm resistance to antibacterial agents. Nat Rev Drug Discov. 2(2):114-22.

Dawson, H., 2011. A comparative assessment of the pig, mouse, and human genomes: structural and functional analysis of genes involved in immunity and inflammation. In The Minipig in Biomedical Research (McAnulty, P.A., ed.), CRC Press, Taylor & Francis Group, pp. 321–341 de Oliveira, S., Rosowski, E.E., Huttenlocher, A., 2016. Neutrophil migration in infection and wound repair: going forward in reverse. Nat Rev Immunol. 16(6):378-91.

DeLeon, S., Clinton, A., Fowler, H., Everett, J., Horswill, A.R., Rumbaugh, K.P., 2014. Synergistic interactions of Pseudomonas aeruginosa and Staphylococcus aureus in an in vitro wound model. Infect Immun. 82(11):4718-28.

Deligianni, E., Pattison, S., Berrar, D., Ternan, N.G., Haylock, R.W., Moore, J.E., Elborn, S.J., Dooley, J.S., 2010. Pseudomonas aeruginosa cystic fibrosis isolates of similar RAPD genotype exhibit diversity in biofilm forming ability in vitro. BMC Microbiol. 10:38.

Dhall, S., Do, D.C., Garcia, M., Kim, J., Mirebrahim, S.H., Lyubovitsky, J., Lonardi, S., Nothnagel, E.A., Schiller, N., Martins-Green, M., 2014. Generating and reversing chronic 111 wounds in diabetic mice by manipulating wound redox parameters. J Diabetes Res. 2014:562625.

Dingemans, J., Monsieurs, P., Yu, S.H., Crabbé, A., Förstner, K.U., Malfroot, A., Cornelis, P., Van Houdt, R., 2016. Effect of Shear Stress on Pseudomonas aeruginosa Isolated from the Cystic Fibrosis Lung. MBio. 7(4). pii: e00813-16.

Dovi, J.V., Szpaderska, A.M., DiPietro L.A., 2004. Neutrophil function in the healing wound: adding insult to injury? Thromb Haemost. 92(2):275-80.

Dowd, S.E., Sun, Y., Secor, P.R., Rhoads, D.D., Wolcott, B.M., James, G.A., Wolcott, R.D., 2008. Survey of bacterial diversity in chronic wounds using pyrosequencing, DGGE, and full ribosome shotgun sequencing. BMC Microbiol.8:43.

Drenkard, E., Ausubel, F.M., 2002. Pseudomonas biofilm formation and antibiotic resistance are linked to phenotypic variation. Nature. 416(6882):740-3.

Dubern, J.F., Cigana, C., De Simone, M., Lazenby, J., Juhas, M., Schwager, S., Bianconi, I., Döring, G., Eberl, L., Williams, P., Bragonzi, A., Cámara, M., 2015. Integrated whole- genome screening for Pseudomonas aeruginosa virulence genes using multiple disease models reveals that pathogenicity is host specific. Environ Microbiol. 17(11):4379-93

Dufour, J.H., Dziejman, M., Liu, M.T., Leung, J.H., Lane, T.E., Luster, A.D., 2002. IFN- gamma-inducible protein 10 (IP-10; CXCL10)-deficient mice reveal a role for IP-10 in effector T cell generation and trafficking. J Immunol. 168(7):3195-204.

DuMont, A.L., Torres, V.J., 2014. Cell targeting by the Staphylococcus aureus pore- forming toxins: it's not just about lipids. Trends Microbiol. 22(1):21-7.

DuMont, A.L., Torres, V.J., 2014. Cell targeting by the Staphylococcus aureus pore- forming toxins: it's not just about lipids. Trends Microbiol. 22(1):21-7.

Edrington, T.C., Kintz, E., Goldberg, J.B., Tamm, L.K., 2011. Structural Basis for the Interaction of Lipopolysaccharide with Outer Membrane Protein H (OprH) from Pseudomonas aeruginosa. The Journal of Biological Chemistry. 286(45):39211-39223.

Elias, S., Degtyar, E., Banin, E., 2011. FvbA is required for vibriobactin utilization in Pseudomonas aeruginosa. Microbiology. 2011 Jul;157(Pt 7):2172-80.

Ernst, R.K., Moskowitz, S.M., Emerson, J.C., Kraig, G.M., Adams, K.N., Harvey, M.D., Ramsey, B., Speert, D.P., Burns, J.L., Miller, S.I., 2007. Unique lipid a modifications in Pseudomonas aeruginosa isolated from the airways of patients with cystic fibrosis. J Infect Dis. 196(7):1088-92.

112

Ernst, R.K., Moskowitz, S.M., Emerson, J.C., et al., 2007. Unique Lipid A Modifications in Pseudomonas aeruginosa Isolated from the Airways of Patients with Cystic Fibrosis. The Journal of infectious diseases. 196(7):1088-1092.

Fairbairn, L., Kapetanovic, R., Sester, D.P., Hume, D.A., 2011. The mononuclear phagocyte system of the pig as a model for understanding human innate immunity and disease. J Leukoc Biol. 89(6):855-71.

Faure, L.M., Llamas, M.A., Bastiaansen, K.C., de Bentzmann, S., Bigot, S., 2013. Phosphate starvation relayed by PhoB activates the expression of the Pseudomonas aeruginosa σvreI ECF factor and its target genes. Microbiology. 159(Pt 7):1315-27.

Fazli, M., Bjarnsholt, T., Kirketerp-Møller, K., Jørgensen, A., Andersen, C.B., Givskov, M., Tolker-Nielsen, T., 2011. Quantitative analysis of the cellular inflammatory response against biofilm bacteria in chronic wounds. Wound Repair Regen. 19(3):387-91.

Fazli, M., Bjarnsholt, T., Kirketerp-Møller, K., Jørgensen, B., Andersen, A.S., Krogfelt, K.A., Givskov, M., Tolker-Nielsen, T., 2009. Nonrandom distribution of Pseudomonas aeruginosa and Staphylococcus aureus in chronic wounds. J Clin Microbiol. 47(12):4084-9.

Fedtke, I., Mader, D., Kohler, T., et al. 2007. A Staphylococcus aureus ypfP mutant with strongly reduced lipoteichoic acid (LTA) content: LTA governs bacterial surface properties and autolysin activity. Molecular Microbiology. 65(4):1078-1091.

Feldman, M., Bryan, R., Rajan, S., Scheffler, L., Brunnert, S., Tang, H., Prince, A., 1998. Role of flagella in pathogenesis of Pseudomonas aeruginosa pulmonary infection. Infect Immun. 66(1):43-51.

Finnegan, S., Percival, S.L., 2015. EDTA: An Antimicrobial and Antibiofilm Agent for Use in Wound Care. Advances in Wound Care. 4(7):415-421.

Foster, T.J., 2005. Immune evasion by staphylococci. Nat Rev Microbiol. 3(12):948-58.

Foster, T.J., 2009. Colonization and infection of the human host by staphylococci: adhesion, survival and immune evasion. Vet Dermatol. 20(5-6):456-70.

Frezzolini, A., Paradisi, M., Zaffiro, A., Provini, A., Cadoni, S., Ruffelli, M., De Pità, O., 2002. Circulating interleukin 16 (IL-16) in children with atopic/eczema dermatitis syndrome (AEDS): a novel serological marker of disease activity. Allergy. 57(9):815-20.

Frykberg, R.G., Banks, J., 2015. Challenges in the Treatment of Chronic Wounds. Adv Wound Care (New Rochelle). 4(9):560-582.

113

Fujimoto, J., Wiener-Kronish, J.P., Hashimoto, S., Sawa, T., 2002. Effects of Cl2MDP- encapsulating liposomes in a murine model of Pseudomonas aeruginosa-induced sepsis. J Liposome Res. 12(3):239-57.

Fulcher, N.B., Holliday, P.M., Klem, E., Cann, M.J., Wolfgang, M.C., 2010. The Pseudomonas aeruginosa Chp Chemosensory System Regulates Intracellular cAMP Levels by Modulating Adenylate Cyclase Activity. Molecular microbiology. 76(4):889- 904.

Furukawa, S., Kuchma, S.L., O’Toole, G.A., 2006. Keeping Their Options Open: Acute versus Persistent Infections. Journal of Bacteriology. 188(4):1211-1217.

Galdiero, M., Vitiello, M., Galdiero, S., 2003. Eukaryotic cell signaling and transcriptional activation induced by bacterial porins. FEMS Microbiol Lett. 226(1):57- 64.

Galdiero, S., Falanga, A., Cantisani, M., Tarallo, R., Della Pepa, M.E., D'Oriano, V., Galdiero, M., 2012. Microbe-host interactions: structure and role of Gram-negative bacterial porins. Curr Protein Pept Sci. 13(8):843-54.

Gallagher, L.A., Shendure, J., Manoil, C., 2011. Genome-scale identification of resistance functions in Pseudomonas aeruginosa using Tn-seq. mBio 2: e00315-00310.

Gallo, R.L., Hooper, L.V., 2012. Epithelial antimicrobial defence of the skin and intestine. Nat Rev Immunol. 2012 Jun 25;12(7):503-16.

Ganesh, K., Sinha, M., Mathew-Steiner, S.S., Das, A., Roy, S., Sen, C.K., 2015. Chronic Wound Biofilm Model. Adv Wound Care (New Rochelle). 4, 382-388.

Gellatly, S.L., Hancock, R.E., 2013. Pseudomonas aeruginosa: new insights into pathogenesis and host defenses. Pathog Dis. 67(3):159-73.

Gjødsbøl, K., Christensen, J.J., Karlsmark, T., Jørgensen, B., Klein, B.M., Krogfelt, K.A., 2006. Multiple bacterial species reside in chronic wounds: a longitudinal study. Int Wound J. 3(3):225-31.

Gohel, M.S., Windhaber, R.A., Tarlton, J.F., Whyman, M.R., Poskitt, K.R., 2008. The relationship between cytokine concentrations and wound healing in chronic venous ulceration. J Vasc Surg. 48(5):1272-7.

Golinko, M.S., Joffe, R., de Vinck, D., Chandrasekaran, E., Stojadinovic, O., Barrientos, S., Vukelic, S., Tomic-Canic, M., Brem, H., 2009. Surgical pathology to describe the clinical margin of debridement of chronic wounds using a wound electronic medical record. J Am Coll Surg. 209, 254-260.e1. 114

Gompelman, M., van Asten, S.A., Peters, E.J., 2016. Update on the Role of Infection and Biofilms in Wound Healing: Pathophysiology and Treatment. Plast Reconstr Surg. 138(3 Suppl):61S-70S.

Goodman, A.L., McNulty, N.P., Zhao, Y., Leip, D., Mitra, R.D., et al., 2009. Identifying genetic determinants needed to establish a human gut symbiont in its habitat. Cell Host Microbe 6: 279–289.

Goodman, A.L., Wu, M., Gordon, J.I., 2011. Identifying microbial fitness determinants by insertion sequencing using genome-wide transposon mutant libraries. Nat Protoc. 17;6(12):1969-80.

Gordon, S., 2003. Alternative activation of macrophages. Nat Rev Immunol. 3, 23-35.

Graves, S.F., Kobayashi, S.D., DeLeo, F.R., 2010. Community-associated methicillin- resistant Staphylococcus aureus immune evasion and virulence. J Mol Med (Berl). 88(2):109-14.

Greenlee-Wacker, M.C., Rigby, K.M., Kobayashi, S.D., Porter, A.R., DeLeo, F.R., Nauseef, W.M., 2014. Phagocytosis of Staphylococcus aureus by human neutrophils prevents macrophage efferocytosis and induces programmed necrosis. J Immunol. 192(10):4709-17.

Gresham, H.D., Lowrance, J.H., Caver, T.E., Wilson, B.S., Cheung, A.L., Lindberg, F.P., 2000. Survival of Staphylococcus aureus inside neutrophils contributes to infection. J Immunol. 164(7):3713-22.

Grice, E.A., Segre, J.A., 2012. Interaction of the microbiome with the innate immune response in chronic wounds. Adv Exp Med Biol. 946:55-68.

Groisman, E.A., Hollands, K., Kriner, M.A., Lee, E.J., Park, S.Y., Pontes, M.H., 2013. Bacterial Mg2+homeostasis, transport, and virulence. Annu Rev Genet.47:625-46.

Günther, F., Wabnitz, G.H., Stroh, P., Prior, B., Obst, U., Samstag, Y., Wagner, C., Hänsch, G.M., 2009. Host defence against Staphylococcus aureus biofilms infection: phagocytosis of biofilms by polymorphonuclear neutrophils (PMN). Mol Immunol. 46(8- 9):1805-13.

Hahn, H.P., 1997. The type-4 pilus is the major virulence-associated adhesin of Pseudomonas aeruginosa--a review. Gene. 192(1):99-108.

Halbert, A.R., Stacey, M.C., Rohr, J.B., Jopp-McKay, A., 1992. The effect of bacterial colonization on venous ulcer healing. Australas J Dermatol. 33(2):75-80. 115

Hall-Stoodley, L., Costerton, J.W., Stoodley, P., 2004. Bacterial biofilms: from the natural environment to infectious diseases. Nat Rev Microbiol. 2(2):95-108.

Hampton, H.R., Chtanova T., 2016. The lymph node neutrophil. Semin Immunol. 28(2):129-36.

Hampton, H.R., Bailey J., Tomura M., Brink R., Chtanova T., 2015. Microbe-dependent lymphatic migration of neutrophils modulates lymphocyte proliferation in lymph nodes. Nat Commun. 6:7139.

Hanke, M.L., Heim C.E., Angle A., Sanderson S.D., Kielian T., 2013. Targeting macrophage activation for the prevention and treatment of Staphylococcus aureus biofilm infections. J Immunol. 190(5):2159-68.

Hanke, M.L., Kielian T., 2012. Deciphering mechanisms of staphylococcal biofilm evasion of host immunity. Front Cell Infect Microbiol. 2:62.

Haque, N.Z., Davis, S.L., Manierski, C.L., Vager, D., Donabedian, S.M., Perri, M.B., Sabbagh, R., Cheema, F., Zervos, M.J., 2007. Infective endocarditis caused by USA300 methicillin-resistant Staphylococcus aureus. Int J Antimicrob Agents. 30(1):72-7.

Haugwitz, U., Bobkiewicz, W., Han., S.R., Beckmann, E., Veerachato, G., Shaid, S., Biehl, S., Dersch, K., Bhakdi, S., Husmann, M., 2006. Pore-forming Staphylococcus aureus alpha-toxin triggers epidermal growth factor receptor-dependent proliferation. Cell Microbiol. 8, 1591-15600.

Hauser, A.R., 2009. The type III secretion system of Pseudomonas aeruginosa: infection by injection. Nat Rev Microbiol. 7(9):654-65.

Hauser, A.R., Cobb, E., Bodi, M., Mariscal, D., Vallés, J., Engel, J.N., Rello, J., 2002. Type III protein secretion is associated with poor clinical outcomes in patients with ventilator-associated pneumonia caused by Pseudomonas aeruginosa. Crit Care Med. 30(3):521-8.

Hazlett, L.D., Rudner, X.L., McClellan, S.A., Barrett, R.P., Lighvani, S., 2002. Role of IL-12 and IFN-gamma in Pseudomonas aeruginosa corneal infection. Invest Ophthalmol Vis Sci. 43(2):419-24.

He, J., Baldini, R.L., Déziel, E., Saucier, M., Zhang, Q., Liberati, N.T., Lee, D., Urbach, J., Goodman, H.M., Rahme, L.G., 2004. The broad host range pathogen Pseudomonas aeruginosa strain PA14 carries two pathogenicity islands harboring plant and animal virulence genes. Proc Natl Acad Sci U S A. 101(8):2530-5.

116

Heinrich, W., Lange, P.M., Stirtz, T., Iancu, C., Heidemann, E., 1971. Isolation and characterization of the large cyanogen bromide peptides from the alpha1- and alpha2- chains of pig skin collagen. FEBS Lett. 16(1):63-67.

Hessle, C.C., Andersson, B., Wold, A.E., 2005. Gram-positive and Gram-negative bacteria elicit different patterns of pro-inflammatory cytokines in human monocytes. Cytokine. 30(6):311-8.

Hilbi, H., Weber, S.S., Ragaz, C., Nyfeler, Y., Urwyler, S., 2007. Environmental predators as models for bacterial pathogenesis. Environ Microbiol. 9(3):563-75.

Hirakata, Y., Srikumar, R., Poole, K., Gotoh, N., Suematsu, T., Kohno, S., Kamihira, S., Hancock, R.E., Speert, D.P., 2002. Multidrug efflux systems play an important role in the invasiveness of Pseudomonas aeruginosa. J Exp Med. 196(1):109-18.

Hirschfeld, J., 2014. Dynamic interactions of neutrophils and biofilms. Journal of Oral Microbiology. 6:10.3402/jom.v6.26102.

Hodkinson, B.P., Grice, E.A., 2015. Next-Generation Sequencing: A Review of Technologies and Tools for Wound Microbiome Research. Adv Wound Care (New Rochelle). 4(1):50-58.

Hogardt, M., Heesemann, J., 2010. Adaptation of Pseudomonas aeruginosa during persistence in the cystic fibrosis lung. Int J Med Microbiol. 300(8):557-62.

Hume, E.B., Cole, N., Khan, S., Garthwaite, L.L., Aliwarga, Y., Schubert, T.L., Willcox, M.D., 2005. A Staphylococcus aureus mouse keratitis topical infection model: cytokine balance in different strains of mice. Immunol Cell Biol. 83(3):294-300.

Hurlow, J., Blanz, E., Gaddy, J.A., 2016. Clinical investigation of biofilm in non-healing wounds by high resolution microscopy techniques. J Wound Care. 25 Suppl 9:S11-22.

Jacobs, M.A., Alwood, A., Thaipisuttikul, I., Spencer, D., Haugen, E., et al., 2003. Comprehensive transposon mutant library of Pseudomonas aeruginosa. Proc Natl Acad Sci U S A 100: 14339-14344.

Jaillon, S., Galdiero, M.R., Del Prete, D., Cassatella, M.A., Garlanda, C., Mantovani, A., 2013. Neutrophils in innate and adaptive immunity. Semin Immunopathol. 35(4):377-94.

Jensen, E.T., Kharazmi, A., Lam, K., Costerton, J.W., Høiby, N., 1990. Human polymorphonuclear leukocyte response to Pseudomonas aeruginosa grown in biofilms. Infect Immun. 58(7):2383-5.

117

Jensen, P.Ø., Bjarnsholt, T., Phipps, R., Rasmussen, T.B., Calum, H., Christoffersen, L., Moser, C., Williams, P., Pressler, T., Givskov, M., Høiby, N., 2007. Rapid necrotic killing of polymorphonuclear leukocytes is caused by quorum-sensing-controlled production of rhamnolipid by Pseudomonas aeruginosa. Microbiology. 153(Pt 5):1329- 38.

Jesaitis, A.J., Franklin, M.J., Berglund, D., Sasaki, M., Lord, C.I., Bleazard, J.B., Duffy, J.E., Beyenal, H., Lewandowski, Z., 2003. Compromised host defense on Pseudomonas aeruginosa biofilms: characterization of neutrophil and biofilm interactions. J Immunol. 171(8):4329-39.

Johansen, H.K., Hougen, H.P., Rygaard, J., Høiby, N., 1996. Interferon-gamma (IFN- gamma) treatment decreases the inflammatory response in chronic Pseudomonas aeruginosa pneumonia in rats. Clin Exp Immunol. 103(2):212-8.

Kallstrom, G., 2014. Are quantitative bacterial wound cultures useful? J Clin Microbiol. 52(8):2753-6.

Kamenyeva, O., Boularan, C., Kabat, J., Cheung, G.Y., Cicala, C., Yeh, A.J., Chan, J.L., Periasamy, S., Otto, M., Kehrl, J.H., 2015. Neutrophil recruitment to lymph nodes limits local humoral response to Staphylococcus aureus. PLoS Pathog. 11(4):e1004827.

Kang, P.J., Hauser, A.R., Apodaca, G., Fleiszig, S.M., Wiener-Kronish, J., Mostov, K., Engel, J.N., 1997. Identification of Pseudomonas aeruginosa genes required for epithelial cell injury. Mol Microbiol. 24(6):1249-62.

Kearney, C.J., Cullen, S.P., Tynan, G.A., et al., 2015. Necroptosis suppresses inflammation via termination of TNF- or LPS-induced cytokine and chemokine production. Cell Death and Differentiation. 22(8):1313-1327.

Kidd, P., 2003. Th1/Th2 balance: the hypothesis, its limitations, and implications for health and disease. Altern Med Rev. 8(3):223-46.

King, J.D., Kocincova, D., Westman, E.L., Lam, J.S., 2009 Lipopoly- saccharide biosynthesis in Pseudomonas aeruginosa. Innate Immun 15: 261–312.

Kirketerp-Møller, K., Jensen, P.Ø., Fazli, M., Madsen, K.G., Pedersen, J., Moser, C., Tolker-Nielsen, T., Høiby, N., Givskov, M., Bjarnsholt, T., 2008. Distribution, organization, and ecology of bacteria in chronic wounds. J Clin Microbiol. 46(8):2717- 22.

Kirkup, B.C. Jr., 2015. Bacterial Strain Diversity Within Wounds. Adv Wound Care (New Rochelle). 4(1):12-23.

118

Klausen, M., Heydorn, A., Ragas, P., Lambertsen, L., Aaes-Jørgensen, A., Molin, S., Tolker-Nielsen, T., 2003. Biofilm formation by Pseudomonas aeruginosa wild type, flagella and type IV pili mutants. Mol Microbiol. 48(6):1511-24.

Knudsen, E., Benestad, H.B., Seierstad, T., Iversen, P.O., 2004. Macrophages in spleen and liver direct the migration pattern of rat neutrophils during inflammation. Eur J Haematol. 73(2):109-22.

Knudsen, E., Carlsen, H., Bøyum, A., Benestad, H.B., Iversen, P.O., 2014. No major role for the transcription factor NF-κB in bone marrow function during peritonitis in the mouse. Int J Hematol. 100(2):111-8.

Kobayashi, S.D., Malachowa, N., DeLeo, F.R., 2015. Pathogenesis of Staphylococcus aureus abscesses. Am J Pathol. 185(6):1518-27.

Kobayashi, S.D., Braughton, K.R., Palazzolo-Ballance, A.M., Kennedy, A.D., Sampaio, E., Kristosturyan, E., Whitney, A.R., Sturdevant, D.E., Dorward, D.W., Holland, S.M., Kreiswirth, B.N., Musser, J.M., DeLeo, F.R., 2010. Rapid neutrophil destruction following phagocytosis of Staphylococcus aureus. J Innate Immun. 2(6):560-75.

Kolaczkowska, E., Kubes, P., 2013. Neutrophil recruitment and function in health and inflammation. Nat Rev Immunol. 13(3):159-75.

Kuang, Z., Hao, Y., Walling, B.E., Jeffries, J.L., Ohman, D.E., Lau, G.W., 2011. Pseudomonas aeruginosa elastase provides an escape from phagocytosis by degrading the pulmonary surfactant pro- tein-A. PLoS ONE 6: e27091.

Kukavica-Ibrulj, I., Bragonzi, A., Paroni, M., Winstanley, C., Sanschagrin, F., O'Toole, G.A., Levesque, R.C., 2008. In vivo growth of Pseudomonas aeruginosa strains PAO1 and PA14 and the hypervirulent strain LESB58 in a rat model of chronic lung infection. J Bacteriol. 190(8):2804-13.

Kumar, V., Sharma, A., 2010. Neutrophils: Cinderella of innate immune system. Int Immunopharmacol. 10(11):1325-34.

Lamarche, M.G., Wanner, B.L., Crépin, S., Harel, J., 2008. The phosphate regulon and bacterial virulence: a regulatory network connecting phosphate homeostasis and pathogenesis. FEMS Microbiol Rev. 32(3):461-73.

Lamont, I.L., Beare, P.A., Ochsner, U., Vasil, A.I., Vasil, M.L., 2002. Siderophore- mediated signaling regulates virulence factor production in Pseudomonas aeruginosa. Proc Natl Acad Sci U S A. 99(10):7072-7.

119

Lazaro, J.L., Izzo, V., Meaume, S., Davies, A.H., Lobmann, R., Uccioli, L., 2016. Elevated levels of matrix metalloproteinases and chronic wound healing: an updated review of clinical evidence. J Wound Care. 25(5):277-87.

Lee, D.G., Urbach, J.M., Wu, G., Liberati, N.T., Feinbaum, R.L., Miyata, S., Diggins, L.T., He, J., Saucier, M., Déziel, E., Friedman, L., Li, L., Grills, G., Montgomery, K., Kucherlapati, R., Rahme, L.G., Ausubel, F.M., 2006. Genomic analysis reveals that Pseudomonas aeruginosa virulence is combinatorial. Genome Biol. 7(10):R90.

Lee, J.J., Jacobsen, E.A., McGarry, M.P., Schleimer, R.P., Lee, N.A., 2010. Eosinophils in health and disease: the LIAR hypothesis. Clin Exp Allergy. 40, 563-575.

Lee, J., Zhang, L., 2015. The hierarchy quorum sensing network in Pseudomonas aeruginosa. Protein & Cell. 6(1):26-41.

Lee, S.A., Gallagher, L.A., Thongdee, M., Staudinger, B.J., Lippman, S., Singh, P.K., Manoil, C., 2015. General and condition-specific essential functions of Pseudomonas aeruginosa. Proc Natl Acad Sci U S A. 112(16):5189-94.

Lehrer, R.I., Lu, W., 2012. α-Defensins in human innate immunity. Immunol Rev. 245(1):84-112.

Leid, J.G., Shirtliff, M.E., Costerton, J.W., Stoodley, P., 2002. Human leukocytes adhere to, penetrate, and respond to Staphylococcus aureus biofilms. Infect Immun. 70(11):6339-45.

Leliefeld, P.H., Koenderman, L., Pillay, J., 2015. How Neutrophils Shape Adaptive Immune Responses. Front Immunol. 6:471.

Létoffé, S., Redeker, V., Wandersman, C., 1998. Isolation and characterization of an extracellular haem-binding protein from Pseudomonas aeruginosa that shares function and sequence similarities with the Serratia marcescens HasA haemophore. Mol Microbiol. 28(6):1223-34.

Leung, D.Y., 2003. Infection in atopic dermatitis. Curr Opin Pediatr. 15(4):399-404.

Li, M., Diep, B.A., Villaruz, A.E., Braughton, K.R., Jiang, X., DeLeo, F.R., Chambers, H.F., Lu, Y., Otto, M., 2009. Evolution of virulence in epidemic community-associated methicillin-resistant Staphylococcus aureus. Proc Natl Acad Sci U S A. 106(14):5883-8.

Li, M., Cheung, G.Y., Hu, J., Wang, D., Joo, H.S., Deleo, F.R., Otto, M., 2010. Comparative analysis of virulence and toxin expression of global community-associated methicillin-resistant Staphylococcus aureus strains. J Infect Dis. 202(12):1866-76.

120

Limoli, D.H., Jones, C.J., Wozniak, D.J., 2015. Bacterial Extracellular Polysaccharides in Biofilm Formation and Function. Microbiology spectrum. 3(3):10.

Linch., S.N., Kelly., A.M., Danielson., E.T., Pero., R., Lee., J.J., Gold., J.A., 2009. Mouse eosinophils possess potent antibacterial properties in vivo. Infect Immun. 77, 4976-4982.

Lindholm, C. and Searle, R., 2016. Wound management for the 21st century: combining effectiveness and efficiency. Int Wound J. 13 Suppl 2:5-15.

Lindley, L.E., Stojadinovic, O., Pastar, I., Tomic-Canic, M., 2016. Biology and Biomarkers for Wound Healing. Plast Reconstr Surg. 2016 Sep;138(3 Suppl):18S-28S.

Liu, G.Y., 2009. Molecular Pathogenesis of Staphylococcus aureus Infection. Pediatric research. 65(5 Pt 2):71R-77R.

Liu, Y., Min, D., Bolton, T., Nubé, V., Twigg, S.M., Yue, D.K., McLennan, S.V., 2009. Increased matrix metalloproteinase-9 predicts poor wound healing in diabetic foot ulcers. Diabetes Care. 32(1):117-9.

Llamas, M.A., van der Sar, A., Chu, B.C., Sparrius, M., Vogel, H.J., Bitter, W., 2009. A Novel extracytoplasmic function (ECF) sigma factor regulates virulence in Pseudomonas aeruginosa. PLoS Pathog. 5(9):e1000572.

Llamas, M.A., Imperi, F., Visca, P., Lamont, I.L., 2014. Cell-surface signaling in Pseudomonas: stress responses, iron transport, and pathogenicity. FEMS Microbiol Rev. 38(4):569-97.

Lobmann, R., Ambrosch, A., Schultz, G., Waldmann, K., Schiweck, S., Lehnert, H., 2002. Expression of matrix-metalloproteinases and their inhibitors in the wounds of diabetic and non-diabetic patients. Diabetologia. 45(7):1011-6.

Lovewell, R.R., Collins, R.M., Acker, J.L., O'Toole, G.A., Wargo, M.J., Berwin, B., 2011. Step-wise loss of bacterial flagellar torsion confers progressive phagocytic evasion. PLoS Pathog. 7(9):e1002253.

Lowy, F.D., 1998. Staphylococcus aureus infections. N Engl J Med. 339(8):520-32.

MacLeod, A.S., Mansbridge, J.N., 2016. The Innate Immune System in Acute and Chronic Wounds. Advances in Wound Care. 5(2):65-78.

Madsen, S.M., Westh, H., Danielsen, L., Rosdahl, V.T., 1996. Bacterial colonization and healing of venous leg ulcers. APMIS. 104(12):895-9.

121

Mah, T.F., O'Toole, G.A., 2001. Mechanisms of biofilm resistance to antimicrobial agents. Trends Microbiol. 9(1):34-9.

Malek, A.A., Chen, C., Wargo, M.J., Beattie, G.A., Hogan, D.A., 2011. Roles of three transporters, CbcXWV, BetT1, and BetT3, in Pseudomonas aeruginosa choline uptake for catabolism. J Bacteriol. 193(12):3033-41.

Mahenthiralingam, E., Campbell, M.E., Speert, D.P., 1994. Nonmotility and phagocytic resistance of Pseudomonas aeruginosa isolates from chronically colonized patients with cystic fibrosis. Infect Immun. 62(2):596-605.

Mann, E.E., Wozniak, D.J., 2012. Pseudomonas biofilm matrix composition and niche biology. FEMS Microbiol Rev. 36(4):893-916.

Mantovani, A., Cassatella, M.A., Costantini, C., Jaillon, S., 2011. Neutrophils in the activation and regulation of innate and adaptive immunity. Nat Rev Immunol. 11(8):519- 31.

Marano, J.R., Wallace, J.H., Wijeratne, D., Fear, W.M., Wong, S.H., O'Handley, R., 2015. Secreted biofilm factors adversely affect cellular wound healing responses in vitro. Sci Rep. 5., 13296.

Martin, P., D'Souza, D., Martin, J., Grose, R., Cooper, L., Maki, R., McKercher, S.R., 2003. Wound healing in the PU.1 null mouse--tissue repair is not dependent on inflammatory cells. Curr Biol. 13(13):1122-8.

Martinez, F.O., Gordon, S., 2014. The M1 and M2 paradigm of macrophage activation: time for reassessment. F1000Prime Reports. 6:13.

Martner, A., Skovbjerg, S., Paton, J.C., Wold, A.E., 2009. Streptococcus pneumoniae autolysis prevents phagocytosis and production of phagocyte-activating cytokines. Infect Immun. 77(9):3826-37.

McCarty, S.M., Percival, S.L., 2013. Proteases and Delayed Wound Healing. Adv Wound Care (New Rochelle). 2(8):438-447.

McDaniel, J.C., Roy, S., Wilgus, T.A., 2013. Neutrophil activity in chronic venous leg ulcers--a target for therapy? Wound Repair Regen. 21(3):339-51.

McWhorter, F.Y., Wang, T., Nguyen, P., Chung, T., Liu, W.F., 2013. Modulation of macrophage phenotype by cell shape. Proc Natl Acad Sci U S A. 110, 17253-17258.

Menke, N.B., Ward, K.R., Witten, T.M., Bonchev, D.G., Diegelmann, R.F., 2007. Impaired wound healing. Clin Dermatol. 25(1):19-25. 122

Mestas, J., Hughes, C.C., 2004. Of mice and not men: differences between mouse and human immunology. J Immunol. 172(5):2731-8.

Metcalf, D., Bowler, P. and Parsons, D., 2016. Wound Biofilm and Therapeutic Strategies. In: Dhanasekaran, D. and Thajuddin, N., editors. Microbial Biofilms- Importance and Applications. Rijeka: InTech, 271-298.

Meurens, F., Summerfield, A., Nauwynck, H., Saif, L., Gerdts, V., 2012. The pig: a model for human infectious diseases. Trends Microbiol. 20(1):50-7.

Mikkelsen, H., McMullan, R., Filloux, A., 2011. The Pseudomonas aeruginosa reference strain PA14 displays increased virulence due to a mutation in ladS. PLoS One. 6(12):e29113.

Miller, L.S. and Cho, J.S., 2011. Immunity against Staphylococcus aureus cutaneous infections. Nat Rev Immunol. 11, 505-518.

Miller, L.G., Perdreau-Remington, F., Rieg, G., Mehdi, S., Perlroth, J., Bayer, A.S., Tang, A.W., Phung, T.O., Spellberg, B., 2005. Necrotizing fasciitis caused by community-associated methicillin-resistant Staphylococcus aureus in Los Angeles. N Engl J Med. 352(14):1445-53.

Mölne, L., Verdrengh, M., Tarkowski, A., 2000. Role of neutrophil leukocytes in cutaneous infection caused by Staphylococcus aureus. Infect Immun. 68, 6162-6167.

Montagna, W., Yun, J.S., 1964. The Skin of the Domestic Pig. J Invest Dermatol. 42:11- 21.

Montgomery, C.P., Boyle-Vavra, S., Adem, P.V., Lee, J.C., Husain, A.N., Clasen, J., Daum, R.S., 2008. Comparison of virulence in community-associated methicillin- resistant Staphylococcus aureus pulsotypes USA300 and USA400 in a rat model of pneumonia. J Infect Dis. 198(4):561-70.

Morissette, C., Francoeur, C., Darmond-Zwaig, C., Gervais, F., 1996. Lung phagocyte bactericidal function in strains of mice resistant and susceptible to Pseudomonas aeruginosa. Infect Immun. 64(12):4984-92.

Moser, C., Kjaergaard, S., Pressler, T., Kharazmi, A., Koch, C., Høiby, N., 2000. The immune response to chronic Pseudomonas aeruginosa lung infection in cystic fibrosis patients is predominantly of the Th2 type. APMIS. 108(5):329-35.

123

Muller, M., Trocme, C., Lardy, B., Morel, F., Halimi, S., Benhamou, P.Y., 2008. Matrix metalloproteinases and diabetic foot ulcers: the ratio of MMP-1 to TIMP-1 is a predictor of wound healing. Diabet Med.25(4):419-26.

Murima, P., McKinney, J.D., Pethe, K. 2014. Targeting bacterial central metabolism for drug development. Chem Biol. 21(11):1423-32.

Murphey, E.D., Herndon, D.N., Sherwood, E.R., 2004. Gamma interferon does not enhance clearance of Pseudomonas aeruginosa but does amplify a proinflammatory response in a murine model of postseptic immunosuppression. Infect Immun. 72(12):6892-901.

Myers, A.H., Postlethwait, R.W., Smith, A.G., 1961. Histologic Grading of the Experimental Healing Wound. Arch Surg. 83, 771-774.

Nathan, C., 2006. Neutrophils and immunity: challenges and opportunities. Nat Rev Immunol. 6(3):173-82.

Nguyen, K.T., Seth, A.K., Hong, S.J., Geringer, M.R., Xie, P., Leung, K.P., Mustoe, T.A., Galiano, R.D., 2013. Deficient cytokine expression and neutrophil oxidative burst contribute to impaired cutaneous wound healing in diabetic, biofilm-containing chronic wounds. Wound Repair Regen. 21(6):833-41.

Nguyen, A.T., Oglesby-Sherrouse, A.G., 2016. Interactions between Pseudomonas aeruginosa and Staphylococcus aureus during co-cultivations and polymicrobial infections. Appl Microbiol Biotechnol. 100(14):6141-8.

Nicolaides, N., Fu, H.C., Rice, G.R., 1968. The skin surface lipids of man compared with those of eighteen species of animals. J Invest Dermatol. 51(2):83-9.

Nieuwenhuis, E.E., Matsumoto, T., Exley, M., Schleipman, R.A., Glickman, J., Bailey, D.T., Corazza, N., Colgan, S.P., Onderdonk, A.B., Blumberg, R.S., 2002. CD1d- dependent macrophage-mediated clearance of Pseudomonas aeruginosa from lung. Nat Med. 8(6):588-93.

Nunan, R., Harding, K.G., Martin, P., 2014. Clinical challenges of chronic wounds: searching for an optimal animal model to recapitulate their complexity. Dis Model Mech. 7, 1205-1213.

O'Grady, N.P., Tropea, M., Preas, H.L. 2nd, Reda, D., Vandivier, R.W., Banks, S.M., Suffredini, A.F., 1999. Detection of macrophage inflammatory protein (MIP)-1alpha and MIP-1beta during experimental endotoxemia and human sepsis. J Infect Dis. 179(1):136- 41.

124

O'Toole, G.A., Kolter, R., 1998. Flagellar and twitching motility are necessary for Pseudomonas aeruginosa biofilm development. Mol Microbiol. 30(2):295-304.

Ojielo, C.I., Cooke, K., Mancuso, P., Standiford, T.J., Olkiewicz, K.M., Clouthier, S., Corrion, L., Ballinger, M.N., Toews, G.B., Paine, R. 3rd, Moore, B.B., 2003. Defective phagocytosis and clearance of Pseudomonas aeruginosa in the lung following bone marrow transplantation. J Immunol. 171(8):4416-24.

Oogai, Y., Matsuo, M., Hashimoto, M., Kato, F., Sugai, M., Komatsuzawa, H., 2011. Expression of Virulence Factors by Staphylococcus aureus Grown in Serum. Applied and Environmental Microbiology. 77(22):8097-8105.

Otto, M., 2013. Staphylococcal infections: mechanisms of biofilm maturation and detachment as critical determinants of pathogenicity. Annu Rev Med. 64: 175-188.

Panuncialman, J., Hammerman, S., Carson, P., Falanga, V., 2010. Wound edge biopsy sites in chronic wounds heal rapidly and do not result in delayed overall healing of the wound. Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society. 18(1):21-25.

Pastar, I., Stojadinovic, O., Yin, N.C., Ramirez, H., Nusbaum, A.G., Sawaya, A., Patel, S.B., Khalid, L., Isseroff, R.R., Tomic-Canic, M., 2014. Epithelialization in Wound Healing: A Comprehensive Review. Adv Wound Care (New Rochelle). 3, 445-464.

Pastar, I., Nusbaum, A.G., Gil, J., et al., 2013. Interactions of Methicillin Resistant Staphylococcus aureus USA300 and Pseudomonas aeruginosa in Polymicrobial Wound Infection. Otto M., ed. PLoS ONE. 8(2):e56846.

Penttinen, R., Kinnula, H., Lipponen, A., Bamford, J.K., Sundberg, L.R., 2016. High Nutrient Concentration Can Induce Virulence Factor Expression and Cause Higher Virulence in an Environmentally Transmitted Pathogen. Microb Ecol. 72(4):955-964.

Phillips, P.L., Schultz, G.S., 2012. Molecular Mechanisms of Biofilm Infection: Biofilm Virulence Factors. Advances in Wound Care. 1(3):109-114.

Plichta, J.K., Droho, S., Curtis, B.J., Patel, P., Gamelli, R.L., Radek, K.A., 2014. Local Burn Injury Impairs Epithelial Permeability and Antimicrobial Peptide Barrier Function in Distal Unburned Skin*. Critical care medicine. 42(6):e420-e431.

Pollitt E.J., Crusz S.A., Diggle S.P., 2015. Staphylococcus aureus forms spreading dendrites that have characteristics of active motility. Sci Rep. 5:17698.

Poole, K., 2012. Stress responses as determinants of antimicrobial resistance in Gram- negative bacteria. Trends Microbiol. 20(5):227-34. 125

Poole, K., 2012. Bacterial stress responses as determinants of antimicrobial resistance. J Antimicrob Chemother. 67(9):2069-89.

Posnett, J., Gottrup, F., Lundgren, H., Saal, G., 2009. The resource impact of wounds on health-care providers in Europe. J Wound Care. 18(4):154-161.

Potvin, E., Sanschagrin F., Levesque R.C., 2008. Sigma factors in Pseudomonas aeruginosa. FEMS Microbiol Rev. 32(1):38-55.

Preciado, D., Caicedo, E., Jhanjee, R., Silver, R., Harris, G., Juhn, S.K., Choo, D.I., Ondrey, F., 2005. Pseudomonas aeruginosa lipopolysaccharide induction of keratinocyte proliferation, NF-kappa B., and cyclin D1 is inhibited by indomethacin. J Immunol. 174, 2964-2973.

Purssell, A., Fruci, M., Mikalauskas, A., Gilmour, C., Poole, K., 2015. EsrC, an envelope stress-regulated repressor of the mexCD-oprJ multidrug efflux operon in Pseudomonas aeruginosa. Environ Microbiol. 17(1):186-98.

Quesada, J.M., Otero-Asman, J.R., Bastiaansen, K.C., Civantos, C., Llamas, M.A., 2016. The Activity of the Pseudomonas aeruginosa Virulence Regulator σ(VreI) Is Modulated by the Anti-σ Factor VreR and the Transcription Factor PhoB. Front Microbiol. 7:1159.

Raahave, D., Friis-Møller, A., Bjerre-Jepsen, K., Thiis-Knudsen, J., Rasmussen, L.B., 1986. The infective dose of aerobic and anaerobic bacteria in postoperative wound sepsis. Arch Surg. 121(8):924-9.

Raynor, L.L., Saucerman, J.J., Akinola, M.O., Lake, D.E., Moorman, J.R., Fairchild, K.D., 2012. Cytokine screening identifies NICU patients with Gram-negative bacteremia. Pediatr Res. 71(3):261-6.

Resch, A., Leicht, S., Saric, M., Pásztor, L., Jakob, A., Götz, F., Nordheim, A., 2006. Comparative proteome analysis of Staphylococcus aureus biofilm and planktonic cells and correlation with transcriptome profiling. Proteomics. 6(6):1867-77. Erratum in: Proteomics. 6(7):2327.

Resch, A., Rosenstein, R., Nerz, C., Götz, F., 2005. Differential gene expression profiling of Staphylococcus aureus cultivated under biofilm and planktonic conditions. Appl Environ Microbiol. 71(5):2663-76.

Rhoads, D.D., Cox, S.B., Rees, E.J., Sun, Y., Wolcott, R.D., 2012. Clinical identification of bacteria in human chronic wound infections: culturing vs. 16S ribosomal DNA sequencing. BMC Infect Dis.12., 321.

126

Rittié, L., Sachs, D.L., Orringer, J.S., Voorhees, J.J., Fisher, G.J., 2013. Eccrine sweat glands are major contributors to reepithelialization of human wounds. Am J Pathol. 182(1):163-71.

Robson, M.C., Shaw, R.C., Heggers, J.P., 1970. Th recolsure of postoperative incisional abscesses based on bacterial quantification of the wound. Ann. Surg. 171: 279-282.

Rodriguez-Fernandez, A., Andaluz-Ojeda, D., Almansa, R., Justel, M., Eiros, J.M., Ortiz de Lejarazu, R., 2013. Eosinophil as a protective cell in S. aureus ventilator-associated pneumonia. Mediators Inflamm. 152943.

Rose, L.F. and Chan, R.K., 2016. The Burn Wound Microenvironment. Adv Wound Care (New Rochelle). 5, 106-118.

Roth, S., Agthe, M., Eickhoff, S., Möller, S., Karsten, C.M., Borregaard, N., Solbach, W., Laskay, T., 2015. Secondary necrotic neutrophils release interleukin-16C and macrophage migration inhibitory factor from stores in the cytosol. Cell Death Discov. 1.

Roth, S., Solbach, W., Laskay, T., 2016. IL-16 and MIF: messengers beyond neutrophil cell death. Cell Death Dis. e2049.

Roux, D., Danilchanka, O., Guillard, T., Cattoir, V., Aschard, H., Fu, Y., Angoulvant, F., Messika, J., Ricard, J.D., Mekalanos, J.J., Lory, S., Pier, G.B., Skurnik, D., 2015. Fitness cost of antibiotic susceptibility during bacterial infection. Sci Transl Med. 7(297):297ra114.

Roy, S., Elgharably, H., Sinha, M., Ganesh, K., Chaney, S., Mann, E., Miller, C., Khanna, S., Bergdall, V.K., Powell, H.M., Cook, C.H., Gordillo, G.M., Wozniak, D.J., Sen, C.K., 2014. Mixed-species biofilm compromises wound healing by disrupting epidermal barrier function. J Pathol. 233, 331-343.

Sadikot, R.T., Blackwell, T.S., Christman, J.W., Prince, A.S., 2005. Pathogen-host interactions in Pseudomonas aeruginosa pneumonia. Am J Respir Crit Care Med. 171(11):1209-23.

Sadowska, B., Więckowska-Szakiel, M., Paszkiewicz, M., Różalska, B., 2013. The immunomodulatory activity of Staphylococcus aureus products derived from biofilm and planktonic cultures. Arch Immunol Ther Exp (Warsz). 61, 413-420.

Sampedro, I., Parales, R.E., Krell, T., Hill, J.E., 2015. Pseudomonas chemotaxis. FEMS Microbiol Rev. 39(1):17-46.

127

Sanchez, Z., Tani, A., Kimbara, K., 2013. Extensive reduction of cell viability and enhanced matrix production in Pseudomonas aeruginosa PAO1 flow biofilms treated with a D-amino acid mixture. Appl Environ Microbiol. 79(4):1396-9.

Santos-Beneit, F., 2015. The Pho regulon: a huge regulatory network in bacteria. Front Microbiol. 6:402.

Scali, C., Kunimoto, B., 2013. An update on chronic wounds and the role of biofilms. J Cutan Med Surg. 17(6):371-6.

Schreml, S., Szeimies, R.M., Prantl, L., Karrer, S., Landthaler, M., Babilas, P., 2010. Oxygen in acute and chronic wound healing. Br J Dermatol. 163(2):257-68.

Schultz, G.S., Sibbald, R.G., Falanga, V., Ayello, E.A., Dowsett, C., Harding, K., Romanelli, M., Stacey, M.C., Teot, L., Vanscheidt, W., 2003. Wound bed preparation: a systematic approach to wound management. Wound Repair Regen. 11 Suppl 1:S1-28.

Schultz, M.J., Rijneveld, A.W., Speelman, P., van Deventer, S.J., van der Poll, T., 2001. Endogenous interferon-gamma impairs bacterial clearance from lungs during Pseudomonas aeruginosa pneumonia. Eur Cytokine Netw. 12(1):39-44.

Schultz, G.S., Davidson, J.M., Kirsner, R.S., Bornstein, P., Herman, I.M., 2011. Dynamic Reciprocity in the Wound Microenvironment. Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society. 19(2):134-148.

Seaton, M., Hocking, A., Gibran, N.S., 2015. Porcine models of cutaneous wound healing. ILAR J. 56(1):127-38.

Secor, P.R., James, G.A., Fleckman, P., Olerud, J.E., McInnerney, K., Stewart, P.S., 2011. Staphylococcus aureus Biofilm and Planktonic cultures differentially impact gene expression, mapk phosphorylation, and cytokine production in human keratinocytes. BMC Microbiol. 11:143.

Seki, T., Kumagai, T., Kwansa-Bentum, B., et al., 2012. Interleukin-4 (IL-4) and IL-13 Suppress Excessive Neutrophil Infiltration and Hepatocyte Damage during Acute Murine Schistosomiasis Japonica. Urban JF, ed. Infection and Immunity. 80(1):159-168.

Sen, C.K., Gordillo, G.M., Roy, S., Kirsner, R., Lambert, L., Hunt, T.K., Gottrup, F., Gurtner, G.C., Longaker, M.T., 2009. Human skin wounds: a major and snowballing threat to public health and the economy. Wound Repair Regen. 17(6):763-71.

Seok, J., Warren, H.S., Cuenca, A.G., Mindrinos, M.N., Baker, H.V., Xu, W., Richards, D.R., McDonald-Smith, G.P., Gao, H., Hennessy, L., Finnerty, C.C., López, C.M., 128

Honari, S., Moore, E.E., Minei, J.P., Cuschieri, J., Bankey, P.E., Johnson, J.L., Sperry, J., Nathens, A.B., Billiar, T.R., West, M.A., Jeschke, M.G., Klein, M.B., Gamelli, R.L., Gibran, N.S., Brownstein, B.H., Miller-Graziano, C., Calvano, S.E., Mason, P.H., Cobb, J.P., Rahme, L.G., Lowry, S.F., Maier, R.V., Moldawer, L.L., Herndon, D.N., Davis, R.W., Xiao, W., Tompkins, R.G., 2013. Inflammation and Host Response to Injury, Large Scale Collaborative Research Program. Genomic responses in mouse models poorly mimic human inflammatory diseases. Proc Natl Acad Sci U S A. 110(9):3507-12.

Serra, R., Grande, R., Butrico, L., Rossi, A., Settimio, U.F., Caroleo, B., Amato, B., Gallelli, L., de Franciscis, S., 2015. Chronic wound infections: the role of Pseudomonas aeruginosa and Staphylococcus aureus. Expert Rev Anti Infect Ther. 13(5):605-13.

Seth, A.K., Geringer, M.R., Galiano, R.D., Leung, K.P., Mustoe, T.A., Hong, S.J., 2012a. Quantitative comparison and analysis of species-specific wound biofilm virulence using an in vivo, rabbit-ear model. J Am Coll Surg. 215, 388-399.

Seth, A.K., Geringer, M.R., Hong, S.J., Leung, K.P., Galiano, R.D., Mustoe, T.A., 2012b. Comparative analysis of single-species and polybacterial wound biofilms using a quantitative., in vivo., rabbit ear model. PLoS One. 7(8):e42897.

Seybold, U., Kourbatova, E.V., Johnson, J.G., Halvosa, S.J., Wang, Y.F., King, M.D., Ray, S.M., Blumberg, H.M., 2006. Emergence of community-associated methicillin- resistant Staphylococcus aureus USA300 genotype as a major cause of health care- associated blood stream infections. Clin Infect Dis. 42(5):647-56. PubMed

Shah, J.M., Omar, E., Pai, D.R., Sood, S., 2012. Cellular events and biomarkers of wound healing. Indian J Plast Surg. 45(2):220-8.

Shi, Y., Liu, C.H., Roberts, A.I., Das, J., Xu, G., Ren, G., Zhang, Y., Zhang, L., Yuan, Z.R., Tan, H.S., Das, G., Devadas, S., 2006. Granulocyte-macrophage colony-stimulating factor (GM-CSF) and T-cell responses: what we do and don't know. Cell Res. 16(2):126- 33.

Shtrichman, R., Samuel, C.E., 2001. The role of gamma interferon in antimicrobial immunity. Curr Opin Microbiol. 4(3):251-9.

Silva, M.T., 2010. Neutrophils and macrophages work in concert as inducers and effectors of adaptive immunity against extracellular and intracellular microbial pathogens. J Leukoc Biol. 87(5):805-13.

Skurnik, D., Roux, D., Aschard, H., Cattoir, V., Yoder-Himes, D., Lory, S., Pier, G.B., 2013a. A comprehensive analysis of in vitro and in vivo genetic fitness of Pseudomonas aeruginosa using high-throughput sequencing of transposon libraries. PLoS Pathog. 9(9):e1003582. 129

Skurnik, D., Roux, D., Cattoir, V., Danilchanka, O., Lu, X., Yoder-Himes, D.R., Han, K., Guillard, T., Jiang, D., Gaultier, C., Guerin, F., Aschard, H., Leclercq, R., Mekalanos, J.J., Lory, S., Pier, G.B., 2013b. Enhanced in vivo fitness of carbapenem-resistant oprD mutants of Pseudomonas aeruginosa revealed through high-throughput sequencing. Proc Natl Acad Sci U S A. 110(51):20747-52.

Smith, E.E., Buckley, D.G., Wu, Z., Saenphimmachak, C., Hoffman, L.R., D’Argenio, D.A., et al., 2006. Genetic adap- tation by Pseudomonas aeruginosa to the airways of cystic fibrosis patients. Proc Natl Acad Sci USA 103: 8487– 8492. Smith, R.S., Wolfgang, M.C., Lory, S., 2004. An adenylate cyclase-controlled signaling network regulates Pseudomonas aeruginosa virulence in a mouse model of acute pneumonia. Infect Immun. 72(3):1677-84.

Song, B.Z., Donoff, R.B., Tsuji, T., Todd, R., Gallagher, G.T., Wong, D.T., 1993. Identification of rabbit eosinophils and heterophils in cutaneous healing wounds. Histochem J. 25, 762-771.

Sousa, A.M., Pereira, M.O., 2014. Pseudomonas aeruginosa Diversification during Infection Development in Cystic Fibrosis Lungs—A Review. Pathogens. 3(3):680-703.

Sousse, L.E., Jonkam, C.C., Traber, D.L., Hawkins, H.K., Rehberg, S.W., Traber, L.D., Herndon, D.N., Enkhbaatar, P., 2011. Pseudomonas aeruginosa is associated with increased lung cytokines and asymmetric dimethylarginine compared with methicillin- resistant Staphylococcus aureus. Shock. 36(5):466-70.

Sprockett, D.D., Ammons, C.G., Tuttle, M.S., 2015. Use of 16S rRNA sequencing and quantitative PCR to correlate venous leg ulcer bacterial bioburden dynamics with wound expansion, antibiotic therapy, and healing. Wound Repair Regen. 23(5):765-71.

Sridhar, S., Steele-Mortimer, O., 2016. Inherent Variability of Growth Media Impacts the Ability of Salmonella Typhimurium to Interact with Host Cells. PLoS One. 9;11(6):e0157043.

Stanley, A., Osler, T., 2001. Senescence and the healing rates of venous ulcers. J Vasc Surg. 33(6):1206-11.

Starkey, M., Hickman, J.H., Ma, L., Zhang, N., De Long, S., Hinz, A., Palacios, S., Manoil, C., Kirisits, M.J., Starner, T.D., Wozniak, D.J., Harwood, C.S., Parsek, M.R., 2009. Pseudomonas aeruginosa rugose small-colony variants have adaptations that likely promote persistence in the cystic fibrosis lung. J Bacteriol. 191(11):3492-503.

Steele, M.I., Lorenz, D., Hatter, K., Park, A., Sokatch, J.R., 1992. Characterization of the mmsAB operon of Pseudomonas aeruginosa PAO encoding methylmalonate- 130 semialdehyde dehydrogenase and 3-hydroxyisobutyrate dehydrogenase. J Biol Chem. 267(19):13585-92.

Stephens, P., Cook, H., Hilton, J., Jones, C.J., Haughton, M.F., Wyllie, F.S., Skinner, J.W., Harding, K.G., Kipling, D., Thomas, D.W., 2003. An analysis of replicative senescence in dermal fibroblasts derived from chronic leg wounds predicts that telomerase therapy would fail to reverse their disease-specific cellular and proteolytic phenotype. Exp Cell Res. 283(1):22-35.

Stewart, P.S., Costerton, J.W., 2001. Antibiotic resistance of bacteria in biofilms. Lancet. 358(9276):135-8.

Stickland, H.G., Davenport, P.W., Lilley, K.S., Griffin, J.L., Welch, M., 2010. Mutation of nfxB causes global changes in the physiology and metabolism of Pseudomonas aeruginosa. J Proteome Res. 9(6):2957-67.

Stojadinovic, O., Landon, J.N., Gordon, K.A., et al., 2013. Quality Assessment of Tissue Specimens for Studies of Diabetic Foot Ulcers. Experimental dermatology. 22(3):216- 218.

Stojadinovic, O., Pastar, I., Vukelic, S., Mahoney, M.G., Brennan, D., Krzyzanowska, A., Golinko, M., Brem, H., Tomic-Canic, M., 2008. Deregulation of keratinocyte differentiation and activation: a hallmark of venous ulcers. J Cell Mol Med. 12(6B):2675- 90.

Stover, C.K., Pham, X.Q., Erwin, A.L., Mizoguchi, S.D., Warrener, P., Hickey, M.J., Brinkman, F.S., et. al., 2000. Complete genome sequence of Pseudomonas aeruginosa PAO1, an opportunistic pathogen. Nature. 406, 959-964.

Suh, S.J., Runyen-Janecky, L.J., Maleniak, T.C., Hager, P., MacGregor, C.H., Zielinski- Mozny, N.A., Phibbs, P.V. Jr., West, S.E., 2002. Effect of vfr mutation on global gene expression and catabolite repression control of Pseudomonas aeruginosa. Microbiology. 148(Pt 5):1561-9.

Sullivan, T.P., Eaglstein, W.H., Davis, S.C., Mertz, P., 2001. The pig as a model for human wound healing. Wound Repair Regen. 9(2):66-76.

Summerfield, A., Meurens, F., Ricklin, M.E., 2014. The immunology of the porcine skin and its value as a model for human skin. Mol Immunol. 66, 14-21.

Surbatovic, M., Popovic, N., Vojvodic, D., Milosevic, I., Acimovic, G., Stojicic, M., Veljovic, M., Jevdjic, J., Djordjevic, D., Radakovic, S., 2015. Cytokine profile in severe Gram-positive and Gram-negative abdominal sepsis. Sci Rep. 5:11355.

131

Swindle, M.M., Makin, A., Herron, A.J., Clubb, F.J. Jr., Frazier, K.S., 2012. Swine as models in biomedical research and toxicology testing. Vet Pathol. 49(2):344-56.

Takase, H., Nitanai, H., Hoshino, K., Otani, T., 2000. Requirement of the Pseudomonas aeruginosa tonB gene for high-affinity iron acquisition and infection. Infect Immun. 68(8):4498-504.

Talan, D.A., Krishnadasan, A., Gorwitz, R.J., Fosheim, G.E., Limbago, B., Albrecht, V., Moran, G.J.; EMERGEncy ID Net Study Group. Comparison of Staphylococcus aureus from skin and soft-tissue infections in US emergency department patients, 2004 and 2008. Clin Infect Dis. 53(2):144-9.

Tamber, S., Ochs, M.M., Hancock, R.E.W., 2006. Role of the Novel OprD Family of Porins in Nutrient Uptake in Pseudomonas aeruginosa. Journal of Bacteriology. 188(1):45-54.

Tan, R.M., Kuang, Z., Hao, Y., Lau, G.W., 2014. Type IV pilus of Pseudomonas aeruginosa confers resistance to antimicrobial activities of the pulmonary surfactant protein-A. J Innate Immun. 6(2):227-39.

Tang, H., Kays, M., Prince, A., 1995. Role of Pseudomonas aeruginosa pili in acute pulmonary infection. Infect Immun. 63(4):1278-85.

Tecchio, C., Micheletti, A., Cassatella, M.A., 2014. Neutrophil-derived cytokines: facts beyond expression. Front Immunol. 5:508.

Telgenhoff, D., Shroot, B., 2005. Cellular senescence mechanisms in chronic wound healing. Cell Death Differ. 12(7):695-8.

Thomson, C.H., 2016. Biofilms: do they affect wound healing? Int Wound J 2011; 8:63– 67

Wagner S., Sommer R., Hinsberger S., Lu C., Hartmann RW., Empting M., Titz A. Novel Strategies for the Treatment of Pseudomonas aeruginosa Infections. J Med Chem. 59(13):5929-69.

Thurlow, L.R., Hanke, M.L., Fritz, T., Angle, A., Aldrich, A., Williams, S.H., Engebretsen, I.L., Bayles, K.W., Horswill, A.R., Kielian, T., 2011. Staphylococcus aureus biofilms prevent macrophage phagocytosis and attenuate inflammation in vivo. J Immunol. 186, 6585-6596.

Thurlow, L.R., Joshi, G.S., Richardson, A.R., 2012. Virulence strategies of the dominant USA300 lineage of community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA). FEMS Immunol Med Microbiol. 65(1):5-22. 132

Tiwari, V.K., 2012. Burn wound: How it differs from other wounds? Indian J Plast Surg. 45, 364-373.

Tkaczyk, C., Hamilton, M. M., Datta, V., Yang, X. P., Hilliard, J. J., Stephens, G. L., Sellman, B. R., 2013. Staphylococcus aureus Alpha Toxin Suppresses Effective Innate and Adaptive Immune Responses in a Murine Dermonecrosis Model. PLoS ONE. 8., e75103.

Trengove, N.J., Bielefeldt-Ohmann, H., Stacey, M.C., 2000. Mitogenic activity and cytokine levels in non-healing and healing chronic leg ulcers. Wound Repair Regen. 8(1):13-25.

Turner, K.H., Everett, J., Trivedi, U., Rumbaugh, K.P., Whiteley, M., 2014. Requirements for Pseudomonas aeruginosa acute burn and chronic surgical wound infection. PLoS Genet. 10(7):e1004518.

Turner, K.H., Wessel, A.K., Palmer, G.C., Murray, J.L., Whiteley, M., 2015. Essential genome of Pseudomonas aeruginosa in cystic fibrosis sputum. Proc Natl Acad Sci U S A. 112(13):4110-5.

Uronen, H., Williams, A.J., Dixon, G., Andersen, S.R., Van Der Ley, P., Van Deuren, M., Callard, R.E., Klein, N., 2000. Gram-negative bacteria induce proinflammatory cytokine production by monocytes in the absence of lipopolysaccharide (LPS). Clin Exp Immunol. 122(3):312-5.

Valentini, M., Filloux, A., 2016. Biofilms and Cyclic di-GMP (c-di-GMP) Signaling: Lessons from Pseudomonas aeruginosa and Other Bacteria. J Biol Chem. 291(24):12547-55.

Vermeiren, H., Keijers, V., Vanderleyden, J., 2002. Isolation and sequence analysis of the GlnKamtB1amtB2 gene cluster, encoding a PII homologue and two putative ammonium transporters, from Pseudomonas stutzeri A15. DNA Seq. 13(1):67-74.

Waite, R.D., Papakonstantinopoulou, A., Littler, E., Curtis, M.A., 2005. Transcriptome analysis of Pseudomonas aeruginosa growth: comparison of gene expression in planktonic cultures and developing and mature biofilms. J Bacteriol. 187(18):6571-6.

Waite, R.D., Paccanaro, A., Papakonstantinopoulou, A., Hurst, J.M., Saqi, M., Littler, E., Curtis, M.A., 2006. Clustering of Pseudomonas aeruginosa transcriptomes from planktonic cultures., developing and mature biofilms reveals distinct expression profiles. BMC Genomics. 7:162.

133

Ward, C.L., Sanchez, C.J. Jr., Pollot, B.E., Romano, D.R., Hardy, S.K., Becerra, S.C., Rathbone, C.R., Wenke, J.C., 2015. Soluble factors from biofilms of wound pathogens modulate human bone marrow-derived stromal cell differentiation, migration., angiogenesis., and cytokine secretion. BMC Microbiol. 15:75.

Wargo, M.J., 2013. Homeostasis and catabolism of choline and glycine betaine: lessons from Pseudomonas aeruginosa. Appl Environ Microbiol. 79(7):2112-20.

Weir, T.L., Stull, V.J., Badri, D., Trunck, L.A., Schweizer, H.P., Vivanco, J., 2008. Global gene expression profiles suggest an important role for nutrient acquisition in early pathogenesis in a plant model of Pseudomonas aeruginosa infection. App Ωl Environ Microbiol. 74(18):5784-91.

Wertheim, H.F., Melles, D.C., Vos, M.C., van Leeuwen, W., van Belkum, A., Verbrugh, H.A., Nouwen, J.L., 2005. The role of nasal carriage in Staphylococcus aureus infections. Lancet Infect Dis. 5(12):751-62.

Wexler, H.M., 2002. Outer-membrane pore-forming proteins in gram-negative anaerobic bacteria. Clin Infect Dis. 35(Suppl 1):S65-71.

Whiteley, M., Bangera, M. G., Bumgarner, R., Parsek, M., Teitzel, G., Lory, S., Greenberg, E. P., 2001. Gene expression in Pseudomonas aeruginosa biofilms. Nature, 413(October), 860–864. Wilgus, T.A., Roy, S., McDaniel, J.C., 2013. Neutrophils and Wound Repair: Positive Actions and Negative Reactions. Advances in Wound Care. 2(7):379-388.

Wilson, M., Seymour, R., Henderson B., 1998. Bacterial perturbation of cytokine networks. Infect Immun. 66(6):2401-9.

Wolfgang, M.C., Jyot, J., Goodman, A.L., Ramphal, R., Lory, S., 2004. Pseudomonas aeruginosa regulates flagellin expression as part of a global response to airway fluid from cystic fibrosis patients. Proc Natl Acad Sci U S A. 101(17):6664-8.

Wolfgang, M.C., Lee, V.T., Gilmore, M.E., Lory, S., 2003a. Coordinate regulation of bacterial virulence genes by a novel adenylate cyclase-dependent signaling pathway. Dev Cell. 4(2):253-63.

Wolfgang, M.C., Kulasekara, B.R., Liang, X., Boyd, D., Wu, K., Yang, Q., Miyada, C.G., Lory, S., 2003b. Conservation of genome content and virulence determinants among clinical and environmental isolates of Pseudomonas aeruginosa. Proc Natl Acad Sci U S A. 100(14):8484-9.

Wollina, U., Berger, U., Mahrle, G., 1991. Immunohistochemistry of porcine skin. Acta Histochem. 90(1):87-91. 134

Xu, X.J., Tang, Y.M., Liao, C., Song, H., Yang, S.L., Xu, W.Q., Shi, S.W., Zhao, N., 2013. Inflammatory cytokine measurement quickly discriminates gram-negative from gram-positive bacteremia in pediatric hematology/oncology patients with septic shock. Intensive Care Med. 39(2):319-26.

Yeoh-Ellerton, S., Stacey, M.C., 2003. Iron and 8-isoprostane levels in acute and chronic wounds. J Invest Dermatol. 121(4):918-25.

Zenga, J., Gagnon, P.M., Vogel, J., Chole, R.A., 2012. Biofilm Formation by Otopathogenic Strains of P. aeruginosa is not Consistently Inhibited by EDTA. Otology & neurotology 33(6):1007-1012.

135

APPENDIX A: TN-SEQ DATA: DECREASED ABUNDANCE

136

Locus ID Abundance p-value Gene Predicted Function (COG CATEGORY) PA0093 -2.20 0.0755 tse6 Involved in protein secretion in type 6 secretion PA0097 -2.61 0.0927 conserved hypothetical protein PAO105 -1.88 0.0857 coxB Cytochrome C oxidase activity PAO151 -2.07 0.0772 Probable TonB-dependent receptor, cell surface chemotactic transducer for trichloroethylene [positive PAO180 -1.90 0.0689 cttP chemotaxis, CttP PA0205 -2.21 0.0719 Probable permease of ABC transporter PA0255* -2.44 0.0413 conserved hypothetical protein PA0257 -2.08 0.0842 conserved hypothetical protein PA0286 -1.79 0.0730 desA delta-9 fatty acid desaturase PA0360* -2.45 0.0225 conserved hypothetical protein PA0374* -2.40 0.0486 ftsE cell division protein major intrinsic multiple antibiotic resistance outer PA0427 -2.33 0.0624 oprM membrane efflux pump PA0430 -2.45 0.0873 metF 5,10-methylenetetrahydrofolate reductase PA0457.1 -2.17 0.0689 conserved hypothetical membrane protein PA0497 -2.27 0.0579 conserved hypothetical protein PA0498 -1.89 0.0812 conserved hypothetical protein PA0561 -2.14 0.0820 hypothetical protein PA0587 -1.83 0.0979 conserved hypothetical protein PA0620 -1.76 0.0873 probable bacteriophage protein PA0621* -2.87 0.0178 probable bacteriophage protein PA0628 -2.03 0.1000 conserved hypothetical protein PA0653 -2.02 0.0956 conserved hypothetical protein PA0675 -1.89 0.0920 vrel ECF sigma factor PA0715 -2.42 0.0629 hypothetical protein PA0737* -2.57 0.0313 hypothetical protein PA0825 -2.15 0.0811 hypothetical protein PA0935 -1.72 0.0893 mazG mazG - purine metabolism hypothetical protein - DNA binding and transposase PA0983* -3.06 0.0127 activity hypothetical protein - DNA binding and transposase PA0986 -2.64 0.0567 activity PA1002 -2.05 0.0937 phnB anthranilate synthase component II PA1025* -2.28 0.0438 opdD probable porin PA1080* -2.64 0.0232 flgE flagellar hook protein PA1143 -2.03 0.0992 hypothetical protein

137

Locus ID Abundance p-value Gene Predicted Function (COG CATEGORY) PhoP/Q and low Mg2+ inducible outer membrane PA1178 -2.24 0.0915 oprH protein H1 precursor PA1240 -2.16 0.0977 probable enoyl-CoA hydratase/isomerase PA1339 -2.19 0.0664 aatP D-amino acid transport PA1363 -2.20 0.0664 ECF sigma factor PA1368 -2.02 0.0955 hypothetical protein PA1386 -2.11 0.0563 probable ATP-binding component of ABC transporter PA1388 -2.08 0.0932 hypothetical protein probable periplasmic spermidine/putrescine-binding PA1410 -1.79 0.0910 protein PA1411* -2.41 0.0224 hypothetical protein PA1441* -2.63 0.0389 FliK putative flagellar hook-length control protein FliK PA1510 -1.91 0.0918 tle4 tle4 - intracellular protein transport and hydrolase PA1595 -2.10 0.0869 hypothetical protein PA1602 -2.21 0.0634 probable oxidoreductase PA1710 -2.33 0.0942 ExsC ExsC, exoenzyme S synthesis protein C precursor PA1836 -2.04 0.0983 probable transcriptional regulator PA1864 -2.32 0.0573 probable transcriptional regulator PA2015 -2.03 0.0930 liuA putative isovaleryl-CoA dehydrogenase PA2041* -2.83 0.0227 Amino acid permease probable binding protein component of ABC PA2058* -2.70 0.0457 transporter PA2102 -2.45 0.0803 hypothetical protein PA2220 -2.34 0.0672 oprR probable transcriptional regulator PA2221 -2.06 0.0928 conserved hypothetical protein PA2546* -2.77 0.0326 probable ring-cleaving dioxygenase PA2568 -2.30 0.0613 hypothetical protein PA2580 -1.80 0.0890 mdaB conserved hypothetical protein, oxidative stress PA2616 -2.40 0.0585 trxB1 thioredoxin reductase 1 PA2618* -2.46 0.0449 hypothetical protein PA2650 -2.23 0.0819 ybaJ conserved hypothetical protein (metabolism) conserved hypothetical protein (liopoprotein PA2695 -1.99 0.0992 yaiW attachment site) PA2700 -2.09 0.0950 opdB proline porin PA2746 -2.14 0.0791 hypothetical protein PA2759 -1.99 0.0601 hypothetical protein PA2777 -2.17 0.0875 yfdC conserved hypothetical protein (transporter activity) PA2794 -2.19 0.0695 pseudaminidase PA2830 -2.17 0.0757 htpX heat shock protein

138

Locus ID Abundance p-value Gene Predicted Function (COG CATEGORY) PA2864 -2.32 0.0666 conserved hypothetical protein PA2878 -2.28 0.0600 hypothetical protein PA2899 -2.02 0.0965 probable transcriptional regulator PA2901* -2.50 0.0397 hypothetical protein PA3012* -3.00 0.0179 hypothetical protein PA3066 -1.95 0.0642 hypothetical protein PA3079 -2.12 0.0914 hypothetical protein PA3177 -1.94 0.0591 hypothetical protein PA3180 -1.82 0.0861 hypothetical protein PA3196 -1.68 0.0909 hypothetical protein PA3238 -1.88 0.0755 hypothetical protein PA3250 -2.47 0.0533 hypothetical protein PA3281 -2.26 0.0674 hypothetical protein PA3295* -2.32 0.0313 probable HIT family protein PA3349 -2.18 0.0711 flgM probable chemotaxis protein PA3350* -2.10 0.0370 hypothetical protein PA3361 -2.24 0.0721 lecB fucose-binding lectin PA-IIL PA3368 -2.07 0.0931 probable acetyltransferase PA3390 -2.31 0.0586 hypothetical protein PA3407 -2.46 0.0676 HasAp heme acquisition protein HasAp PA3438* -2.51 0.0341 folE1 GTP cyclohydrolase I precursor conserved hypothetical protein (transmembrane PA3468 -1.79 0.0880 ybdG transport) PA3473 -1.74 0.0924 hypothetical protein probable Resistance-Nodulation-Cell Division (RND) PA3522 -2.12 0.0915 efflux transporter PA3571 -2.00 0.0990 mmsR transcriptional regulator MmsR PA3680 -2.18 0.0781 yhiQ conserved hypothetical protein PA3714* -2.54 0.0336 probable two-component response regulator PA3740 -2.23 0.0683 hypothetical protein probable major facilitator superfamily (MFS) PA3749* -2.94 0.0149 yhjE transporter PA3759* -2.62 0.0265 probable aminotransferase PA3795 -2.05 0.0652 probable oxidoreductase PA3855* -2.31 0.0242 hypothetical protein PA3891 -2.30 0.0705 opuCA OpuC ABC transporter, ATP-binding protein, OpuCA PA3962 -2.10 0.0801 hypothetical protein PA3967* -2.47 0.0449 hypothetical protein PA3970 -2.10 0.0688 amn AMP nucleosidase

139

Locus ID Abundance p-value Gene Predicted Function (COG CATEGORY) PA4006 -2.30 0.0592 nadD nicotinic acid mononucleotide adenylyltransferase PA4040 -2.08 0.0925 hypothetical protein PA4090 -2.14 0.0819 hypothetical protein PA4156 -1.78 0.0921 fvbA fvbA siderophore transport PA4208* -2.37 0.0419 opmD probable outer membrane protein precursor PA4294 -2.04 0.0899 hypothetical protein PA4312 -2.21 0.0729 conserved hypothetical protein PA4324* -2.44 0.0497 hypothetical protein PA4503 -2.13 0.0757 dppB probable permease of ABC transporter PA4540 -1.93 0.0951 lepB hypothetical protein (polypeptide transport) PA4564 -2.26 0.0597 creA conserved hypothetical protein PA4581* -2.15 0.0460 RtcR transcriptional regulator RtcR PA4596 -2.18 0.0725 esrC esrC, DNA binding, regulation of transcription PA4641 -2.92 0.0610 hypothetical protein PA4694* -2.43 0.0357 ilvC ketol-acid reductoisomerase PA4695 -2.23 0.0651 ilvH acetolactate synthase isozyme III small subunit PA4831* -2.41 0.0484 probable transcriptional regulator PA4869 -1.89 0.0916 hypothetical protein PA4896* -2.72 0.0322 probable sigma-70 factor, ECF subfamily PA4939 -2.36 0.0563 hisX conserved hypothetical protein PA4954* -2.25 0.0479 motA Chemotaxis protein PA4973 -1.96 0.0829 ThiC thiamin biosynthesis protein ThiC PA5066 -2.05 0.0986 hisI phosphoribosyl-AMP cyclohydrolase PA5147 -2.17 0.0885 micA A / G specific adenine glycosylase PA5150 -2.27 0.0611 probable short-chain dehydrogenase PA5225 -2.00 0.0997 hypothetical protein PA5227.1 -2.01 0.0952 ssrS 6S RNA PA5268 -2.03 0.0640 corA magnesium/cobalt transport protein PA5273* -2.58 0.0386 hypothetical protein PA5287 -1.99 0.0631 AmtB ammonium transporter AmtB PA5288 -2.63 0.0645 glnK nitrogen regulatory protein P-II 2 PA5298 -2.43 0.0631 xpt xanthine phosphoribosyltransferase PA5310 -2.03 0.0718 ymdC conserved hypothetical protein PA5374 -2.24 0.0688 betI transcriptional regulator BetI PA5401 -2.25 0.0695 hypothetical protein PA5480* -2.84 0.0407 hypothetical protein hypothetical protein part of dsbA operon PA5488 -2.07 0.0732 thiol:disulfide interchange protein DsbA

140

APPENDIX B: TN-SEQ: INCREASED ABUNDANCE

141

Gene ID Abundance Gene/Function PA5483 2.09 algB PA3804 3.14 hypothetical protein PA3961 3.25 probable ATP-dependent helicase PA4009 3.33 hypothetical protein PA3706 3.35 probable protein methyltransferase PA5428 3.38 probable transcriptional regulator PA5547 3.38 conserved hypothetical protein PA1868 3.40 meatbolic/phosphatase PA5538 3.41 N-acetylmuramoyl-L-alanine amidase PA5541 3.42 dihydroorotase PA4914 3.42 probable transcriptional regulator PA4591 3.42 hypothetical protein PA0243 3.42 probable transcriptional regulator PA5445 3.44 probable coenzyme A transferase PA4798 3.46 hypothetical protein PA5030 3.50 probable major facilitator superfamily (MFS) transporter PA3672 3.52 probable ATP-binding component of ABC transporter PA4187 3.56 probable major facilitator superfamily (MFS) transporter PA3596 3.56 probable methylated-DNA--protein-cysteine methyltransferase PA5356 3.57 transcriptional regulator GlcC PA4136 3.57 probable major facilitator superfamily (MFS) transporter Resistance-Nodulation-Cell Division (RND) multidrug efflux membrane fusion PA4374 3.58 protein MexV PA4446 3.59 algW protein PA2882 3.60 probable two-component sensor PA4702 3.61 hypothetical protein PA3949 3.62 hypothetical protein PA4880 3.63 probable bacterioferritin PA2399 3.66 pyoverdine synthetase D PA3025 3.69 probable FAD-dependent glycerol-3-phosphate dehydrogenase PA0335 3.70 hypothetical protein PA2688 3.70 Ferric enterobactin receptor, outer membrane protein PfeA precursor PA4872 3.70 hypothetical protein PA2592 3.71 probable periplasmic spermidine/putrescine-binding protein PA2075 3.71 hypothetical protein PA0794 3.72 probable aconitate hydratase

142

Gene ID Abundance Gene/Function PA4588 3.73 glutamate dehydrogenase PA4985 3.73 Uncharacterized protein PA3717 3.74 probable peptidyl-prolyl cis-trans isomerase, FkbP-type PA1682 3.75 probable MFS metabolite transporter PA1018 3.75 hypothetical protein PA3937 3.76 probable ATP-binding component of ABC taurine transporter PA3875 3.76 respiratory nitrate reductase alpha chain PA2230 3.76 hypothetical protein PA4688 3.77 iron (III)-transport system permease HitB PA4667 3.77 hypothetical protein PA3392 3.79 nitrous-oxide reductase precursor PA5459 3.80 putative methyltransferase PA5218 3.81 probable transcriptional regulator PA0088 3.81 TssF1 PA2276 3.82 probable transcriptional regulator PA4589 3.83 probable outer membrane protein precursor PA3901 3.84 Fe(III) dicitrate transport protein FecA PA1846 3.84 cis/trans isomerase PA0479 3.85 probable transcriptional regulatorLysR PA2443 3.85 L-serine dehydratase PA5090 3.86 VgrG5 PA5262 3.86 FimS PA3509 3.87 probable hydrolase PA5077 3.88 OpgH PA4226 3.90 dihydroaeruginoic acid synthetase PA4839 3.90 arginine decarboxylase (ADC)/speA PA4650 3.93 Pilin subunit CupE3 PA5100 3.93 urocanase PA3659 3.95 probable aminotransferase PA0251 3.96 hypothetical protein PA0600 3.96 two-component sensor, AgtS PA3603 3.97 diacylglycerol kinase PA3871 3.98 probable peptidyl-prolyl cis-trans isomerase, PpiC-type PA5286 3.98 conserved hypothetical protein PA3710 3.99 probable GMC-type oxidoreductase PA0484 3.99 conserved hypothetical protein PA3588 4.00 probable porin PA3785 4.02 conserved hypothetical protein

143

Gene ID Abundance Gene/Function PA1526 4.03 probable transcriptional regulator PA0623 4.04 probable bacteriophage protein PA4075 4.05 hypothetical protein PA5375 4.05 BetT1 PA1376 4.05 aceK: isocitrate dehydrogenase kinase/phosphatase PA3556 4.05 inner membrane L-Ara4N transferase ArnT PA4772 4.05 probable ferredoxin PA2652 4.05 methyl-accepting chemotaxis protein PA0095 4.06 conserved hypothetical protein PA2724 4.06 hypothetical protein PA2873 4.07 transglutaminase protein A, TgpA PA4365 4.07 probable transporter PA3979 4.07 hypothetical protein PA1150 4.07 pyocin S2 PA4821 4.08 probable transporter PA3739 4.08 probable sodium/hydrogen antiporter PA2532 4.08 tpx: thiol peroxidase PA1933 4.10 probable hydroxylase large subunit PA4816 4.10 hypothetical protein PA0345 4.11 hypothetical protein PA2042 4.11 probable transporter (membrane subunit) PA0293 4.13 aguB: N-carbamoylputrescine amidohydrolase PA5207 4.13 probable phosphate transporter PA0450 4.15 probable phosphate transporter PA0824 4.15 hypothetical protein PA5026 4.16 hypothetical protein PA3930 4.16 cioA: cyanide insensitive terminal oxidase PA5361 4.16 two-component sensor PhoR PA4660 4.16 phr: deoxyribodipyrimidine photolyase PA4356 4.17 xenB: xenobiotic reductase PA4995 4.20 probable acyl-CoA dehydrogenase PA0887 4.21 acetyl-coenzyme A synthetase PA4504 4.22 probable permease of ABC transporter PA4124 4.22 hpcB: homoprotocatechuate 2,3-dioxygenase PA5251 4.22 hypothetical protein PA2792 4.22 hypothetical protein PAO132 4.23 bauA: Beta-alanine:pyruvate transaminase PA0081 4.24 Fha1

144

Gene ID Abundance Gene/Function PA3597 4.24 probable amino acid permease PA4131 4.25 probable iron-sulfur protein PA0267 4.26 hypothetical protein PA3421 4.27 conserved hypothetical protein PA4808 4.28 L-seryl-tRNA(ser) selenium transferase PA3258 4.28 hypothetical protein PA3008 4.29 hypothetical protein PA0917 4.29 kup: potassium uptake protein Kup PA4088 4.30 probable aminotransferase PA3716 4.32 hypothetical protein PA0777 4.33 hypothetical protein PA3972 4.33 probable acyl-CoA dehydrogenase PA5413 4.34 ltaA: low specificity l-threonine aldolase PA4548 4.34 probable D-amino acid oxidase PA2393 4.34 putative dipeptidase PA3301 4.36 hypothetical protein PA0829 4.36 probable hydrolase PA2699 4.37 hypothetical protein PA3393 4.37 NosD protein PA2635 4.38 hypothetical protein PA5368 4.38 pstC: membrane protein component of ABC phosphate transporter PA1014 4.38 1,2-glucosyltransferase WapB PA2418 4.39 hypothetical protein PAO136 4.39 probable ATP-binding component of ABC transporter PA3760 4.40 N-Acetyl-D-Glucosamine phosphotransferase system transporter PA0290 4.40 hypothetical protein PA3077 4.41 cprR PA0642 4.41 hypothetical protein PA2370 4.43 HsiH3 PA2933 4.43 probable major facilitator superfamily (MFS) transporter PA0860 4.43 probable ATP-binding/permease fusion ABC transporter PA0699 4.43 probable peptidyl-prolyl cis-trans isomerase, PpiC-type, PA4993 4.43 hypothetical protein PA4918 4.44 hypothetical protein PA0936 4.44 lpx02: lipopolysaccharide biosynthetic protein LpxO2 PA4402 4.45 argJ: glutamate N-acetyltransferase PA3947 4.45 RocR PA3280 4.47 OprO: Pyrophosphate-specific outer membrane porin OprO precursor

145

Gene ID Abundance Gene/Function PA4786 4.48 probable short-chain dehydrogenase PA1975 4.48 hypothetical protein PA4541 4.48 lepA: Pseudomonas aeruginosa-derived large extracellular protease, LepA PA1092 4.50 fliC: flagellin type B PA4539 4.50 hypothetical protein PA0337 4.50 ptsP; phosphoenolpyruvate-protein phosphotransferase PtsP PA1207 4.53 kefb: glutathione-regulated potassium-efflux system protein KefB PA4026 4.53 probable acetyltransferase PA0586 4.56 conserved hypothetical protein PAO166 4.56 probable transporter PA3236 4.57 BetX PA3127 4.58 hypothetical protein PA2672 4.59 probable type II secretion system protein PA2506 4.61 hypothetical protein PA5382 4.62 probable transcriptional regulator PA1181 4.62 conserved hypothetical protein PA4946 4.63 mutL: DNA mismatch repair protein MutL PA5159 4.65 multidrug resistance protein PA1082 4.66 flgG: flagellar basal-body rod protein FlgG PA4023 4.67 probable transport protein PA1306 4.72 probable HIT family protein PA5105 4.74 hutC: histidine utilization repressor HutC PA0820 4.74 hypothetical protein PA1734 4.74 hypothetical protein PA1194 4.74 probable amino acid permease PA4646 4.75 uracil phosphoribosyltransferase PA3889 4.76 OpuC ABC transporter, periplasmic substrate-binding protein, OpuCC PA3599 4.76 probable transcriptional regulator PA2032 4.76 probable transcriptional regulator PA4519 4.77 speC: ornithine decarboxylase PA1007 4.77 conserved hypothetical protein PA0924 4.77 hypothetical protein PA1818 4.77 lysine-specific pyridoxal 5'-phosphate-dependent carboxylase, LdcA PA2677 4.77 probable type II secretion protein PA3934 4.78 conserved hypothetical protein PA2632 4.78 hypothetical protein PA3114 4.78 truA: tRNA-pseudouridine synthase I PA2865 4.79 probable glycosylase

146

Gene ID Abundance Gene/Function PA4467 4.79 hypothetical protein PA0641 4.79 probable bacteriophage protein PA0987 4.80 conserved hypothetical protein PA1740 4.80 hypothetical protein PA0451 4.80 conserved hypothetical protein PA0841 4.81 hypothetical protein PA5472 4.81 hypothetical protein PA1163 4.81 NdvB PA5399 4.81 DgcB, Dimethylglycine catabolism PA3504 4.81 probable aldehyde dehydrogenase PA2555 4.82 probable AMP-binding enzyme PA2943 4.82 phospho-2-dehydro-3-deoxyheptonate aldolase PA4976 4.83 Arginine:Pyruvate Transaminas, AruH PA3981 4.83 conserved hypothetical protein PA1124 4.83 dgt: deoxyguanosinetriphosphate triphosphohydrolase PA4683 4.83 hypothetical protein PA4074 4.83 probable transcriptional regulator PA5184 4.83 hypothetical protein PA1101 4.84 fliF: Flagella M-ring outer membrane protein precursor PA0823 4.84 hypothetical protein PA0308 4.84 hypothetical protein PA4516 4.86 hypothetical protein PA4982 4.86 probable two-component sensor PA0544 4.87 hypothetical protein PA4497 4.90 probable binding protein component of ABC transporter PA2556 4.90 probable transcriptional regulator PA5325 4.90 SphA: sphingosine PA0530 4.90 probable class III pyridoxal phosphate-dependent aminotransferase PA3070 4.94 conserved hypothetical protein PA3108 4.95 purF: amidophosphoribosyltransferase PA0889 4.96 arginine/ornithine transport protein AotQ PA0622 4.96 probable bacteriophage protein PA3228 4.97 probable ATP-binding/permease fusion ABC transporter PA5383 4.97 conserved hypothetical protein PA4048 4.98 hypothetical protein PA2526 4.98 muxC PA5168 4.98 DctQ PA1186 4.99 hypothetical protein

147

Gene ID Abundance Gene/Function PA4339 5.01 probable phospholipase PA5059 5.01 probable transcriptional regulator PA5021 5.02 probable sodium/hydrogen antiporter PA1412 5.02 hypothetical protein PA1046 5.03 hypothetical protein PA1001 5.04 phnA: anthranilate synthase component I PA4699 5.04 hypothetical protein PA1436 5.05 probable Resistance-Nodulation-Cell Division (RND) efflux transporter PA5188 5.05 probable 3-hydroxyacyl-CoA dehydrogenase PA1544 5.05 transcriptional regulator Anr PA2160 5.06 probable glycosyl hydrolase PA0269 5.07 conserved hypothetical protein PA2925 5.07 histidine transport system permease HisM PA3125 5.07 hypothetical protein PA0331 5.07 ilvA1: threonine dehydratase, biosynthetic PA5080 5.09 prolyl aminopeptidase PA3495 5.09 nth: endonuclease III PA2835 5.09 probable major facilitator superfamily (MFS) transporter PA1126 5.10 hypothetical protein PA5148 5.11 conserved hypothetical protein PA5532 5.11 hypothetical protein PA3858 5.11 probable amino acid-binding protein PA0571 5.12 hypothetical protein PA0761 5.13 nadB: L-aspartate oxidase PA0069 5.13 conserved hypothetical protein PA1243 5.13 probable sensor/response regulator hybrid PA1166 5.13 hypothetical protein PA3708 5.14 wspA: probable chemotaxis transducer PA1231 5.14 conserved hypothetical protein PA1504 5.14 probable transcriptional regulator PA3894 5.14 probable outer membrane protein precursor probable Resistance-Nodulation-Cell Division (RND) efflux membrane fusion PA3523 5.15 protein precursor PA4207 5.15 mexI: probable Resistance-Nodulation-Cell Division (RND) efflux transporter PA0686 5.15 HxcR: type 2 secretion system T2SS PA2701 5.16 probable major facilitator superfamily (MFS) transporter PA2449 5.16 transcriptional regulator PAO176 5.18 aerotaxis transducer Aer2

148

Gene ID Abundance Gene/Function PA1030 5.19 hypothetical protein PA5294 5.19 putative multidrug efflux pump PA0865 5.20 hpd4-hydroxyphenylpyruvate dioxygenase PA3195 5.21 gapA: glyceraldehyde 3-phosphate dehydrogenase PA1993 5.21 probable major facilitator superfamily (MFS) transporter PA3391 5.21 regulatory protein NosR PA2748 5.22 probable methionine aminopeptidase PA2588 5.22 probable transcriptional regulator PA0563 5.23 conserved hypothetical protein PA1663 5.23 sfa2: Protein secretion/export apparatus PA1624 5.23 hypothetical protein PA0056 5.23 probable transcriptional regulator PA0321 5.24 probable acetylpolyamine aminohydrolase PA2949 5.26 probable lipase PA3059 5.26 PelF PA1851 5.27 hypothetical protein PA1964 5.27 probable ATP-binding component of ABC transporter PA0277 5.27 conserved hypothetical protein PA1060 5.27 hypothetical protein PA2761 5.28 hypothetical protein PA2719 5.28 hypothetical protein PA4825 5.30 mgtA: Mg(2+) transport ATPase, P-type 2 PA0852 5.30 cbpD: chitin-binding protein CbpD precursor PA4217 5.31 phzS: flavin-containing monooxygenase PA2392 5.31 pvdP PA4039 5.32 hypothetical protein PAO103 5.32 probable sulfate transporter PA0045 5.32 hypothetical protein PA2697 5.33 hypothetical protein PA3505 5.33 hypothetical protein PA0933 5.34 ygcA: probable RNA methyltransferase triC: Resistance-Nodulation-Cell Division (RND) triclosan efflux transporter, PAO158 5.34 TriC PA0221 5.34 probable aminotransferase PA3355 5.34 hypothetical protein PA0920 5.35 hypothetical protein PA3078 5.36 CprS PA4574 5.36 conserved hypothetical protein

149

Gene ID Abundance Gene/Function PA0849 5.36 thioredoxin reductase 2 PA3405 5.37 hasE: metalloprotease secretion protein PA5238 5.37 probable O-antigen acetylase PA3118 5.37 leuB: 3-isopropylmalate dehydrogenase PA0996 5.37 PqsA PA1601 5.37 probable aldehyde dehydrogenase PA1647 5.37 probable sulfate transporter PA2228 5.38 hypothetical protein PA0916 5.39 conserved hypothetical protein PA3536 5.39 hypothetical protein PA3235 5.40 conserved hypothetical protein PA5470 5.40 probable peptide chain release factor PA2442 5.41 gcvT2: glycine cleavage system protein T2 PA3283 5.41 conserved hypothetical protein PA0537 5.41 conserved hypothetical protein PA4201 5.42 ddlA: D-alanine-D-alanine ligase A PA1172 5.42 napC: cytochrome c-type protein NapC PA3087 5.42 hypothetical protein PA5258 5.43 hypothetical protein PA3553 5.44 arnC PA0718 5.44 hypothetical protein of bacteriophage Pf1 PA0840 5.44 probable oxidoreductase PA5151 5.45 hypothetical protein PA1327 5.45 probable protease PA2720 5.47 hypothetical protein PA4116 5.48 bphO: heme oxygenase, BphO PA1611 5.49 hybrid sensor kinase PA3208 5.49 conserved hypothetical protein PA2382 5.50 lldA: L-lactate dehydrogenase PA3344 5.50 recQ: ATP-dependent DNA helicase RecQ PA0020 5.51 tsaP: T4P secretin-associated protein TsaP PA3888 5.51 opuCD: OpuC ABC transporter, permease protein, OpuCD PA3054 5.52 hypothetical protein PA0412 5.53 pilK: methyltransferase PilK PA1125 5.54 probable cobalamin biosynthetic protein PA3081 5.56 conserved hypothetical protein PA4525 5.56 pilA: type 4 fimbrial precursor PilA PA0044 5.57 exoT: exoenzyme T

150

Gene ID Abundance Gene/Function PA0566 5.58 hypothetical protein PA0727 5.58 hypothetical protein from bacteriophage Pf1 PA1930 5.59 probable chemotaxis transducer PA3513 5.59 hypothetical protein PA3000 5.59 aroP1: aromatic amino acid transport protein AroP1 PA2776 5.60 pauB3: FAD-dependent oxidoreductase PA3095 5.61 xcpZ: general secretion pathway protein M PA4224 5.62 pchG: pyochelin biosynthetic protein PchG PA1760 5.63 probable transcriptional regulator PAO192 5.63 probable TonB-dependent receptor PA1524 5.65 xdhA: xanthine dehydrogenase PA0695 5.67 hypothetical protein PA5311 5.67 probable major facilitator superfamily (MFS) transporter PA4904 5.67 vanA: vanillate O-demethylase oxygenase subunit PA3912 5.68 conserved hypothetical protein PA3631 5.69 conserved hypothetical protein PA0550 5.69 conserved hypothetical protein PA0886 5.69 probable C4-dicarboxylate transporter PA1865 5.69 hypothetical protein PAO186 5.71 probable binding protein component of ABC transporter PA2444 5.71 glyA2: serine hydroxymethyltransferase PA2897 5.71 probable transcriptional regulator PA0745 5.71 probable enoyl-CoA hydratase/isomerase PA5324 5.72 sphR: Sphingosine-responsive Regulator, SphR PA2727 5.72 hypothetical protein PA3252 5.73 probable permease of ABC transporter PA3409 5.74 hasS PA0957 5.74 hypothetical protein PA3046 5.75 conserved hypothetical protein PA5482 5.75 hypothetical protein PA4851 5.75 hypothetical protein PA3797 5.76 conserved hypothetical protein PA3340 5.76 hypothetical protein PA1069 5.76 hypothetical protein PA5261 5.76 alginate biosynthesis regulatory protein AlgR PA2915 5.77 hypothetical protein PAO194 5.77 hypothetical protein PA4626 5.77 hprA: glycerate dehydrogenase

151

Gene ID Abundance Gene/Function PA3590 5.78 probable hydroxyacyl-CoA dehydrogenase PA4282 5.83 probable exonuclease PA2710 5.84 hypothetical protein PAO108 5.84 coIII: cytochrome c oxidase, subunit III PA3157 5.85 probable acetyltransferase PA3101 5.85 xcpT: general secretion pathway protein G PA3226 5.85 probable hydrolase PA3492 5.87 conserved hypothetical protein PA2807 5.88 hypothetical protein PA0735 5.88 hypothetical protein PA1335 5.89 aauR PA1209 5.90 hypothetical protein PA1337 5.90 ansB: glutaminase-asparaginase PA0893 5.90 argR: transcriptional regulator ArgR PA3060 5.92 pelE PA0510 5.93 nirE PA0352 5.93 probable transporter PA4219 5.93 ampO PA0897 5.93 aruG: arginine/ornithine succinyltransferase AII subunit PA0351 5.95 conserved hypothetical protein PA3358 5.95 hypothetical protein PA0669 5.95 probable DNA polymerase alpha chain PA0810 5.96 probable haloacid dehalogenase PA3980 5.98 conserved hypothetical protein PA1017 5.98 pauA: pimeloyl-CoA synthetase PA2801 5.99 hypothetical protein PA0625 6.00 hypothetical protein PA4898 6.00 opdK: histidine porin OpdK PA5104 6.00 conserved hypothetical protein PA3430 6.00 probable aldolase PA2771 6.00 conserved hypothetical protein PA0585 6.00 hypothetical protein PA2542 6.01 conserved hypothetical protein PAO100 6.01 hypothetical protein PA3425 6.02 hypothetical protein PA2762 6.02 hypothetical protein PA0706 6.03 cat: chloramphenicol acetyltransferase PA5056 6.05 phaC1: poly(3-hydroxyalkanoic acid) synthase 1

152

Gene ID Abundance Gene/Function triB: Resistance-Nodulation-Cell Division (RND) triclosan efflux membrane PAO157 6.05 fusion protein, TriB PA2251 6.05 hypothetical protein PA4959 6.05 fimX PA4444 6.06 mltB1: soluble and membrane-bound lytic transglycosylases PA3418 6.06 ldh: leucine dehydrogenase PA2941 6.07 hypothetical protein PA2583 6.09 probable sensor/response regulator hybrid PA4687 6.09 hitA: ferric iron-binding periplasmic protein HitA PA0448 6.09 probable transcriptional regulator PA2687 6.10 pfeS: two-component sensor PfeS PA1331 6.10 conserved hypothetical protein PA4915 6.10 probable chemotaxis transducer PA4341 6.10 probable transcriptional regulator PA2265 6.11 gluconate dehydrogenase PA1421 6.11 gbuA: guanidinobutyrase PA0355 6.11 pfpI: protease PfpI PA2662 6.11 conserved hypothetical protein PAO195.1 6.12 PNTAB: putative NAD(P) transhydrogenase, subunit alpha part 2 PA2708 6.12 hypothetical protein PA1157 6.12 probable two-component response regulator PA4578 6.13 hypothetical protein PA3193 6.13 GLK: glucokinase PA0222 6.14 hypothetical protein PA5210 6.15 probable secretion pathway ATPase PA3805 6.15 pilF: type 4 fimbrial biogenesis protein PilF PA1754 6.16 cysB: transcriptional regulator CysB PA2773 6.16 hypothetical protein nrdG: class III (anaerobic) ribonucleoside-triphosphate reductase activating PA1919 6.17 protein, 'activase', NrdG PA1606 6.19 hypothetical protein PA3532 6.19 hypothetical protein PA1997 6.21 probable AMP-binding enzyme PA1686 6.21 alkA: DNA-3-methyladenine glycosidase II PA0993 6.21 cupC2 PA3781 6.21 probable transporter PA4527 6.22 pilC: PA0652 6.22 vfr: transcriptional regulator Vfr

153

Gene ID Abundance Gene/Function PA1219 6.23 hypothetical protein PA1745 6.25 hypothetical protein PA0408 6.27 pilG: twitching motility protein PilG PA0719 6.28 hypothetical protein of bacteriophage Pf1 PA1541 6.28 probable drug efflux transporter PA2224 6.30 hypothetical protein PA3332 6.30 conserved hypothetical protein PA3942 6.30 tesB: acyl-CoA thioesterase II PA4818 6.32 conserved hypothetical protein PA0749 6.33 hypothetical protein PA2665 6.33 fhpR: Transcriptional activator of P. aeruginosa flavohemoglobin, FhpR PA3027 6.35 probable transcriptional regulator PA1139 6.36 hypothetical protein PA1521 6.36 probable guanine deaminase PA0558 6.36 conserved hypothetical protein PA3516 6.36 probable lyase PA3116 6.37 probable aspartate-semialdehyde dehydrogenase PA3364 6.38 amiC: aliphatic amidase expression-regulating protein PA0950 6.39 probable arsenate reductase PA1876 6.39 probable ATP-binding/permease fusion ABC transporter PA3217 6.41 cyaB PA0395 6.41 pilT: twitching motility protein PilT PA0452 6.42 probable stomatin-like protein PA1823 6.42 nudC PA3319 6.43 plcN: non-hemolytic phospholipase C precursor PA1044 6.44 hypothetical protein PA1498 6.44 pykF: pyruvate kinase I PA2858 6.46 conserved hypothetical protein PA1717 6.47 pscD: type III export protein PscD PA2529 6.47 hypothetical protein PA2537 6.47 probable acyltransferase PA1700 6.48 pcr2 PA2561 6.48 ctpH: chemotaxis, adaptation and protection PA1939 6.49 hypothetical protein PA0090 6.52 clpV1 PAO187 6.53 hypothetical protein PA2385 6.53 pvdQ: 3-oxo-C12-homoserine lactone acylase PvdQ PA1112.1 6.54

154

Gene ID Abundance Gene/Function PA3009 6.55 hypothetical protein PA1091 6.56 fgtA: flagellar glycosyl transferase, FgtA PA1070 6.57 braG: branched-chain amino acid transport protein BraG PA1731 6.57 conserved hypothetical protein PA1831 6.58 hypothetical protein PA1987 6.58 pyrroloquinoline quinone biosynthesis protein C PA2670 6.59 hypothetical protein PA3052 6.60 hypothetical protein PA5165 6.63 dctB PA4873 6.65 probable heat-shock protein PA1304 6.67 probable oligopeptidase PA4556 6.67 pilE: type 4 fimbrial biogenesis protein PilE PA1819 6.67 probable amino acid permease PA5075 6.68 probable permease of ABC transporter PA3224 6.68 hypothetical protein PA0679 6.68 hxcP PA1187 6.68 probable acyl-CoA dehydrogenase PA4546 6.71 pilS: two-component sensor PilS PA4550 6.72 fimU: type 4 fimbrial biogenesis protein FimU PA2357 6.72 msuE: NADH-dependent FMN reductase MsuE PA2078 6.73 (7S,10S)-hydroperoxide diol synthase PA2781 6.75 hypothetical protein PA0046 6.75 hypothetical protein PA4547 6.75 pilR: two-component response regulator PilR PAO168 6.77 conserved hypothetical protein PA0808 6.77 hypothetical protein PA1693 6.78 pscR: translocation protein in type III secretion PA2661 6.80 hypothetical protein PA2955 6.81 hypothetical protein PA2772 6.81 hypothetical protein PA4642 6.82 hypothetical protein PA2505 6.82 opdT: tyrosine porin OpdT PA1307 6.82 conserved hypothetical protein PA3679 6.83 hypothetical protein PA1357 6.83 conserved hypothetical protein PA1252 6.84 probable L-malate dehydrogenase PA1239 6.84 hypothetical protein PA0052 6.85 hypothetical protein

155

Gene ID Abundance Gene/Function PA1757 6.86 thrH: homoserine kinase PA1326 6.86 ilvA2: threonine dehydratase, biosynthetic PA0534 6.86 FAD-dependent oxidoreductase PA1567 6.87 conserved hypothetical protein PA2539 6.87 conserved hypothetical protein PA2753 6.88 hypothetical protein PA1813 6.88 probable hydroxyacylglutathione hydrolase PA1957 6.90 hypothetical protein PA4552 6.91 pilW: type 4 fimbrial biogenesis protein PilW PA2419 6.91 probable hydrolase PA1203 6.93 hypothetical protein PA1414 6.94 hypothetical protein PA1626 6.94 probable major facilitator superfamily (MFS) transporter PA5043 6.95 pilN: type 4 fimbrial biogenesis protein PilN PA2073 6.96 probable transporter (membrane subunit) PA1934 6.96 hypothetical protein PA1493 6.96 cysP; sulfate-binding protein of ABC transporter PA0734 6.97 hypothetical protein PA2152 6.97 probable trehalose synthase PA5041 6.99 pilP; type 4 fimbrial biogenesis protein PilP PA1711 6.99 exsE PA4734 6.99 hypothetical protein PA4528 7.00 pilD: type 4 prepilin peptidase PilD PA1935 7.00 hypothetical protein PA2475 7.00 probable cytochrome P450 PA4551 7.01 pilV: type 4 fimbrial biogenesis protein PilV PA1146 7.02 probable iron-containing alcohol dehydrogenase PA1373 7.03 fabF2: 3-oxoacyl-acyl carrier protein synthase II PA2343 7.03 mtlY: xylulose kinase PA5347 7.04 hypothetical protein PA5309 7.05 pauB4: FAD-dependent oxidoreductase PA1484 7.07 probable transcriptional regulator PA1249 7.08 aprA: alkaline metalloproteinase precursor PA2051 7.08 probable transmembrane sensor PA0396 7.10 pilU: twitching motility protein PilU PA1869 7.10 probable acyl carrier protein PA0410 7.10 pilI: twitching motility protein PilI PA2940 7.11 probable acyl-CoA thiolase

156

Gene ID Abundance Gene/Function PA1000 7.11 pqsE: Quinolone signal response protein PA3561 7.17 fruK: 1-phosphofructokinase PA1019 7.17 mucK: cis,cis-muconate transporter MucK PA5042 7.17 pilO: type 4 fimbrial biogenesis protein PilO PA1204 7.18 NAD(P)H quinone oxidoreductase PA1136 7.18 probable transcriptional regulator PA0411 7.19 pilJ: twitching motility protein PilJ PA4553 7.19 pilX: type 4 fimbrial biogenesis protein PilX PA2301 7.19 hypothetical protein PA3096 7.20 xcpY: general secretion pathway protein L PA2698 7.22 probable hydrolase PA2569 7.23 hypothetical protein PA1457 7.23 cheZ: chemotaxis protein CheZ PA3731 7.27 conserved hypothetical protein PA2180 7.27 hypothetical protein PA1134 7.32 hypothetical protein PA4554 7.33 pilY1: type 4 fimbrial biogenesis protein PilY1 PA1982 7.33 exaA: quinoprotein ethanol dehydrogenase PA1520 7.34 probable transcriptional regulator PA2002 7.36 conserved hypothetical protein PA2338 7.36 probable binding protein component of ABC maltose/mannitol transporter PA0349 7.37 hypothetical protein PA1147 7.41 probable amino acid permease PA1573 7.43 conserved hypothetical protein PA2347 7.46 hypothetical protein PA1822 7.50 fimL: hypothetical protein PA1188 7.52 hypothetical protein PA5040 7.52 pilQ: Type 4 fimbrial biogenesis outer membrane protein PilQ precursor PA1491 7.53 probable transporter PA2579 7.54 kynA: L-Tryptophan:oxygen 2,3-oxidoreductase (decyclizing) KynA PA0804 7.55 probable oxidoreductase PA1264 7.57 probable transcriptional regulator PA5044 7.66 pilM: type 4 fimbrial biogenesis protein PilM PA2270 7.70 probable transcriptional regulator PA2543 7.71 conserved hypothetical protein PA4526 7.75 pilB: type 4 fimbrial biogenesis protein PilB PA1599 7.78 probable transcriptional regulator PA2960 7.78 pilZ: type 4 fimbrial biogenesis protein PilZ

157

Gene ID Abundance Gene/Function PA2072 7.78 conserved hypothetical protein PA5081 7.79 hypothetical protein PA2497 7.99 probable transcriptional regulator PA2356 8.06 msuD: methanesulfonate sulfonatase MsuD PA3419 8.13 hypothetical protein PA2081 8.14 kynB: kynurenine formamidase, KynB PA2054 8.16 cynR: transcriptional regulator CynR PA0413 8.50 chpA: component of chemotactic signal transduction system PA5249 8.65 hypothetical protein PA3115 8.82 fimV: Motility protein FimV PA1817 9.00 hypothetical protein PA2561 6.48 ctpH PA1939 6.49 hypothetical protein PA0090 6.52 clpV1 PAO187 6.53 hypothetical protein PA2385 6.53 pvdQ: 3-oxo-C12-homoserine lactone acylase PvdQ PA1112.1 6.54 PA3009 6.55 hypothetical protein PA1091 6.56 fgtA: flagellar glycosyl transferase, FgtA PA1070 6.57 braG: branched-chain amino acid transport protein BraG PA1731 6.57 conserved hypothetical protein PA1831 6.58 hypothetical protein PA1987 6.58 pqqC: pyrroloquinoline quinone biosynthesis protein C PA2670 6.59 hypothetical protein PA3052 6.60 hypothetical protein PA5165 6.63 dctB: PA4873 6.65 probable heat-shock protein PA1304 6.67 probable oligopeptidase PA4556 6.67 pilE: type 4 fimbrial biogenesis protein PilE PA1819 6.67 probable amino acid permease PA5075 6.68 probable permease of ABC transporter PA3224 6.68 hypothetical protein PA0679 6.68 hxcP: PA1187 6.68 probable acyl-CoA dehydrogenase PA4546 6.71 pilS: two-component sensor PilS PA4550 6.72 fimU: type 4 fimbrial biogenesis protein FimU PA2357 6.72 msuE: NADH-dependent FMN reductase MsuE PA2078 6.73 (7S,10S)-hydroperoxide diol synthase

158

Gene ID Abundance Gene/Function PA2781 6.75 hypothetical protein PA0046 6.75 hypothetical protein PA4547 6.75 pilR: two-component response regulator PilR PAO168 6.77 conserved hypothetical protein PA0808 6.77 hypothetical protein PA1693 6.78 pscR: translocation protein in type III secretion PA2661 6.80 hypothetical protein PA2955 6.81 hypothetical protein PA2772 6.81 hypothetical protein PA4642 6.82 hypothetical protein PA2505 6.82 opdT: tyrosine porin OpdT PA1307 6.82 conserved hypothetical protein PA3679 6.83 hypothetical protein PA1357 6.83 conserved hypothetical protein PA1252 6.84 probable L-malate dehydrogenase PA1239 6.84 hypothetical protein PA0052 6.85 hypothetical protein PA1757 6.86 thrH: homoserine kinase PA1326 6.86 ilvA2: threonine dehydratase, biosynthetic PA0534 6.86 pauB1: FAD-dependent oxidoreductase PA1567 6.87 conserved hypothetical protein PA2539 6.87 conserved hypothetical protein PA2753 6.88 hypothetical protein PA1813 6.88 probable hydroxyacylglutathione hydrolase PA1957 6.90 hypothetical protein PA4552 6.91 pilW: type 4 fimbrial biogenesis protein PilW PA2419 6.91 probable hydrolase PA1203 6.93 hypothetical protein PA1414 6.94 hypothetical protein PA1626 6.94 probable major facilitator superfamily (MFS) transporter PA5043 6.95 pilN: type 4 fimbrial biogenesis protein PilN PA2073 6.96 probable transporter (membrane subunit) PA1934 6.96 hypothetical protein PA1493 6.96 cysP: sulfate-binding protein of ABC transporter PA0734 6.97 hypothetical protein PA2152 6.97 probable trehalose synthase PA5041 6.99 pilP: type 4 fimbrial biogenesis protein PilP PA1711 6.99 ExsE

159

Gene ID Abundance Gene/Function PA4734 6.99 hypothetical protein PA4528 7.00 pilD: type 4 prepilin peptidase PilD PA1935 7.00 hypothetical protein PA2475 7.00 probable cytochrome P450 PA4551 7.01 pilV: type 4 fimbrial biogenesis protein PilV PA1146 7.02 probable iron-containing alcohol dehydrogenase PA1373 7.03 fabF2: 3-oxoacyl-acyl carrier protein synthase II PA2343 7.03 mtlY: xylulose kinase PA5347 7.04 hypothetical protein PA5309 7.05 pauB4: FAD-dependent oxidoreductase PA1484 7.07 probable transcriptional regulator PA1249 7.08 aprA: alkaline metalloproteinase precursor PA2051 7.08 probable transmembrane sensor PA0396 7.10 pilU: twitching motility protein PilU PA1869 7.10 probable acyl carrier protein PA0410 7.10 pilI: twitching motility protein PilI PA2940 7.11 probable acyl-CoA thiolase PA1000 7.11 pqsE: Quinolone signal response protein PA3561 7.17 fruK: 1-phosphofructokinase PA1019 7.17 mucK: cis,cis-muconate transporter MucK PA5042 7.17 pilO: type 4 fimbrial biogenesis protein PilO PA1204 7.18 NAD(P)H quinone oxidoreductase PA1136 7.18 probable transcriptional regulator PA0411 7.19 pilJ: twitching motility protein PilJ PA4553 7.19 pilX: type 4 fimbrial biogenesis protein PilX PA2301 7.19 hypothetical protein PA3096 7.20 xcpY: general secretion pathway protein L PA2698 7.22 probable hydrolase PA2569 7.23 hypothetical protein PA1457 7.23 cheZ: chemotaxis protein CheZ PA3731 7.27 conserved hypothetical protein PA2180 7.27 hypothetical protein PA1134 7.32 hypothetical protein PA4554 7.33 pilY1: type 4 fimbrial biogenesis protein PilY1 PA1982 7.33 exaA: quinoprotein ethanol dehydrogenase PA1520 7.34 probable transcriptional regulator PA2002 7.36 conserved hypothetical protein PA2338 7.36 probable binding protein component of ABC maltose/mannitol transporter

160

Gene ID Abundance Gene/Function PA0349 7.37 hypothetical protein PA1147 7.41 probable amino acid permease PA1573 7.43 conserved hypothetical protein PA2347 7.46 hypothetical protein PA1822 7.50 fimL: hypothetical protein PA1188 7.52 hypothetical protein PA5040 7.52 pilQ: Type 4 fimbrial biogenesis outer membrane protein PilQ precursor PA1491 7.53 probable transporter PA2579 7.54 kynA: L-Tryptophan:oxygen 2,3-oxidoreductase (decyclizing) KynA PA0804 7.55 probable oxidoreductase PA1264 7.57 probable transcriptional regulator PA5044 7.66 pilM: type 4 fimbrial biogenesis protein PilM PA2270 7.70 probable transcriptional regulator PA2543 7.71 conserved hypothetical protein PA4526 7.75 pilB: type 4 fimbrial biogenesis protein PilB PA1599 7.78 probable transcriptional regulator PA2960 7.78 pilZ: type 4 fimbrial biogenesis protein PilZ PA2072 7.78 conserved hypothetical protein PA5081 7.79 hypothetical protein PA2497 7.99 probable transcriptional regulator PA2356 8.06 msuD: methanesulfonate sulfonatase MsuD PA3419 8.13 hypothetical protein PA2081 8.14 kynB: kynurenine formamidase, KynB PA2054 8.16 cynR: transcriptional regulator CynR PA0413 8.50 chpA: component of chemotactic signal transduction system PA5249 8.65 hypothetical protein PA3115 8.82 fimV: Motility protein FimV PA1817 9.00 hypothetical protein PA3724 5.36 elastase LasB PA1391 5.58 probable glycosyl transferase PA0997 5.00 PqsB PA4343 5.18 probable major facilitator superfamily (MFS) transporter

161