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Dissecting macrophage responses to Salmonella Typhimurium infection Rosenberger, Carrie Melissa 2004

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DISSECTING MACROPHAGE RESPONSES TO SALMONELLA TYPHIMURIUM INFECTION Carrie Melissa Rosenberger B. Arts Sci. (Honours), McMaster University, 1996 A THESIS SUBMITTED IN PARTIAL F U L F I L L M E N T OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE F A C U L T Y OF G R A D U A T E STUDIES Department of Microbiology and Immunology and the Biotechnology Laboratory We accept this thesis as conformed to the required standard THE UNIVERISITY OF BRITISH C O L U M B I A January 2004 © Carrie Melissa Rosenberger, 2004 11 Abstract. Salmonella Typhimurium infection of murine macrophages provides a robust model for studying host-pathogen interactions at a molecular level. Gene array hybridization studies identified changes in the expression of numerous genes not previously recognized to be involved in macrophage response to infection. A n overlapping spectrum of genes was expressed in response to virulent S. Typhimurium and purified S. Typhimurium lipopolysaccharide, reinforcing the major role of this bacterial component in stimulating the early response of macrophages to bacterial infection. The infected macrophage gene expression profile was further altered by priming with interferon-y, indicating that host cell responses depend on the activation state of the cell. These studies identified upregulated expression of MEK1 kinase in macrophages infected by S. Typhimurium, which correlated with increased MEK1 kinase activity during infection. As this kinase plays a key role in regulating macrophage signal transduction and antimicrobial activities, the functional role of MEK1 in Salmonella-infected macrophages was characterized. Inhibiting M E K kinase activity significantly increased intracellular bacterial numbers. In addition, while macrophages exert stress on intracellular Salmonella and impair bacterial cell division to result in long filamentous bacteria, there was a significant decrease in the number of filamentous Salmonella when MEK1 kinase activity was impaired. This filamentous bacterial morphology was also dependent on the production of reactive oxygen intermediates, which function in parallel to M E K signaling. Experiments were performed to characterize the macrophage effector mechanism(s) responsible for impairing the replication of this intracellular pathogen and the consequent bacterial filamentation. Antimicrobial peptides play an important role in the defense against extracellular infections, but the expression of cationic peptides within macrophages as an antibacterial effector mechanism against intracellular pathogens has not been demonstrated. Ill Macrophages indeed express the antimicrobial peptide C R A M P , and this expression was increased following infection and was dependent on the macrophage's production of reactive oxygen intermediates. Studies using CRAMP-deficient mice or synthetic C R A M P peptide determined that C R A M P impairs Salmonella cell division in vivo and in vitro, resulting in long filamentous bacteria. This impaired bacterial cell division was also dependent on intracellular elastase-like serine protease activity, which can proteolytically activate antimicrobial peptides. A peptide-sensitive Salmonella mutant showed enhanced survival within macrophages derived from CRAMP-deficient mice, indicating that Salmonella can sense and respond to cationic peptides in the intracellular environment. Together, these results show that intracellular ROIs and proteases regulate macrophage C R A M P expression and activity to impair the replication of an intracellular bacterial pathogen. In summary, profiling of macrophage gene expression led to characterization of host signal transduction pathways necessary for impairing bacterial replication and the elucidation of novel antibacterial effector mechanisms. These data begin to address the complexity of interactions between macrophage signaling and effector mechanisms triggered by bacterial infection. iv Table of Contents Page Abstract ii Table of Contents iv List of Tables viii List of Figures ix List of Abbreviations x Acknowledgements xii Chapter 1 Introduction 1.1 Preface 1 1.2 Macrophages 1 1.2.1 Macrophage Biology 1.2.2 Pathogen recognition: modulins and pattern recognition receptors 2 1.2.3 Macrophage signaling 3 1.2.4 Antimicrobial capacities 4 1.3 Salmonella Typhimurium 1.3.1 Salmonellosis 5 1.3.2 Mechanisms of virulence 5 1.3.3 Salmonella interactions with host cells 8 1.4 Macrophage-S'tf/mo«e//a Interactions 1.4.1 Role of macrophages in the murine typhoid model 9 1.4.2 Role in innate immune responses to S. Typhimurium 10 1.4.3 Role in adaptive immune responses to S. Typhimurium 12 1.4.4 Macrophage subversion by S. Typhimurium 13 1.5 Transcriptional profiling of infected macrophages 15 1.6 Summary of thesis 16 1.7 Literature cited 18 Chapter 2 Salmonella Typhimurium and lipopolysaccharide stimulation induce similar changes in macrophage gene expression. 2.1 Preface 30 2.2 Summary 30 2.3 Introduction 31 2.4 Experimental Procedures 34 2.5 Establishment of array hybridization conditions 38 V Table of Contents Chapter 2 2.6 Effect of S. Typhimurium on R A W 264.7 gene expression 39 2.7 Effect of IFN-y on gene expression by infected macrophages 48 2.8 Contribution of LPS signaling 49 2.9 Confirmation of array data using northern blots and ELISAs 51 2.10 Discussion 54 2.11 Literature cited 63 Chapter 3 Effect of SPI2-secreted virulence factors on macrophage gene expression. 3.1 Objective 69 3.2 Introduction 69 3.3 Experimental Procedures 71 3.4 Contribution of SPI 2 secretion to macrophage gene expression 73 3.5 Contribution of SspHl and SspH2 to macrophage gene expression 79 3.6 Preliminary confirmation 83 3.7 Discussion 83 3.8 Literature cited 85 Chapter 4 Macrophages inhibit Salmonella Typhimurium replication through M E K / E R K kinase and phagocyte N A D P H oxidase activities. 4.1 Preface 86 4.2 Summary 86 4.3 Introduction 87 4.4 Experimental Procedures 90 4.5 IFN-y priming of R A W 264.7 cells restricts S. Typhimurium growth 95 4.6 Macrophages induce bacterial filamentation at 24 h post-infection 95 4.7 Salmonella induces MEK1 kinase mRNA and activity 97 4.8 Increased MEK1 activity correlates with bacterial filamentation 103 4.9 MEK1 activity controls intracellular bacterial numbers 107 4.10 Phagocyte N A D P H oxidase also mediates bacterial filamentation 107 4.11 M E K and phox activities at later times mediate bacterial filamentation 109 4.12 M E K and phox activities function in parallel to mediate filamentation 111 4.13 Discussion 116 4.14 Literature cited 122 vi Table of Contents Chapter 5 Interplay between antimicrobial effectors: A macrophage antimicrobial peptide impairs intracellular Salmonella replication. 5.1 Preface 126 5.2 . Summary 126 5.3 Introduction 127 5.4 Experimental Procedures 128 5.5 Oxidase-dependent impairment of bacterial cell division 133 5.6 Intracellular protease activity mediates impaired Salmonella cell division 135 5.7 Macrophages express the cathelicidin C R A M P 142 5.8 C R A M P mediates filamentation in vitro 144 5.9 Salmonella minimizes filamentation using PhoP/Q 146 5.10 C R A M P and proteases cooperate to impair Salmonella cell division in vitro and within macrophages 148 5.11 Role of vacuolar acidification 151 5.12 Discussion 153 5.13 Literature cited 157 Chapter 6 General discussion and perspectives 6.1 Lessons learned about pathogenesis using gene arrays 161 6.2 How do macrophages integrate signals from bacterial pathogens? 163 6.3 Why does Salmonella respond to intracellular signals with filamentation? 164 6.4 Interplay between macrophage signaling and antimicrobial responses 165 6.5 Literature cited 168 Appendix A Gene array data sets A . 1 Hybridization intensities in R A W 264.7 cells infected with S. Typhimurium or stimulated with LPS 170 A . 2 Hybridization intensities in IFN-y-primed R A W 264.7 cells infected with S. Typhimurium 189 Appendix B: SifA permits replication of S. Typhimurium within macrophages. B. l Preface 202 B.2 Introduction 202 B.3 Experimental Procedures 203 B.4 Results and Discussion 204 B.5 Literature Cited 207 vii Table of Contents Appendix C Phagocyte sabotage: Disruption of macrophage signaling by bacterial pathogens. 209 Appendix D Using gene array technology to determine host responses to Salmonella. 222 Appendix E Contributions of others. 231 Appendix F Publications arising from graduate work. 232 Vlll List of Tables Table 2.1 Table 2.2 Table 3.1 Table 3.2 Table 3.3 Table 3.4 Table 3.5 Table 3.6 Table A . l Table A.2 Hybridization intensities of genes used for data normalization. Effect of IFN-y activation on gene expression by S. Typhimurium-infected R A W 264.7 macrophages. Genes more highly induced in IFN-y primed R A W 264.7 cells infected with wt bacteria relative to an AssaR SPI2 type III secretion mutant: 8 h. Genes more highly induced in IFN-y primed R A W 264.7 cells infected with an AssaR SPI2 type III secretion mutant relative to wt bacteria: 8 h. Page 41 50 75 76 Genes more highly induced in IFN-y primed R A W 264.7 cells infected with wt bacteria relative to an AssaR SPI2 type III secretion mutant: 24 h. 77 Genes more highly induced in IFN-y primed R A W 264.7 cells infected with an AssaR SPI2 type III secretion mutant relative to wt bacteria: 24 h. 78 Genes more highly induced in R A W 264.7 cells infected with wt bacteria relative to an AsspHlAsspH2 virulence factor mutant. 80 Genes more highly induced in R A W 264.7 cells infected with an AsspHl AsspH2 virulence factor mutant relative to wt bacteria. 82 Hybridization intensities in R A W 264.7 cells infected with S. Typhimurium or stimulated with LPS. 170 Hybridization intensities in IFN-y-primed R A W 264.7 cells infected with S. Typhimurium. 189 ix List of Figures Fig. Title p. 2.1 Differential gene expression by macrophages upon S. Typhimurium infection or L P S 40 stimulation as measured by gene arrays. 2.2 R A W 264.7 macrophage gene expression induced by S. Typhimurium and L P S . 43 2.3 R A W 264.7 macrophage gene expression inhibited by S. Typhimurium. 46 2.4 Confirmation and quantification of genes differentially expressed upon S. Typhimurium 53 infection and L P S stimulation using Northern blots. 3.1 Array hybridization images comparing R A W 264.7 cells infected for 24 h with various S. 74 Typhimurium strains. 3.2 Northern blot analysis of type III secretion-dependent increase in M E K 1 gene expression. 84 4.1 Priming of R A W 264.7 cells with IFN-y inhibits S. Typhimurium replication. 96 4.2 Filamentous bacteria reside in an endosomal compartment and can be extruded from the 98 macrophage. 4.3 Primary macrophages cause filamentation of Salmonella. 99 4.4 S. Typhimurium infection increases M E K 1 m R N A and protein in IFN-y-primed R A W 101 264.7 cells. 4.5 S. Typhimurium infection increases M E K 1 protein and activity. 104 4.6 M E K 1 and phox activity correlates with bacterial filamentation. 105 4.7 M E K 1 activity controls Salmonella Typhimurium replication. 108 4.8 M E K kinase and phox activities at later times mediate bacterial filamentation. 110 4.9 ROIs do not mediate filamentation by modulating E R K phosphorylation. 112 4.10 M E K kinase does not mediate filamentation by increasing intracellular ROIs. 114 4.11 Working model for signaling in R A W 264.7 cells mediating filamentation of Salmonella. 120 5.1 Filamentation is dependent on M E K kinase signaling and oxidants in bone marrow-derived 134 macrophages. 5.2 Filamentation independent of SPI1- and SPI2-dependent virulence factors. 136 5.3 Serine protease inhibitors decrease bacterial filamentation in bone marrow-derived 137 macrophages. 5.4 Localization, regulation, and substrate of macrophage protease activity. 140 5.5 Macrophages express the antimicrobial cathelicidin C R A M P . 143 5.6 C R A M P mediates Salmonella filamentation in vitro and in vivo. 145 5.7 Salmonella minimizes filamentation using a PhoP/Q-dependent mechanism. 147 5.8 Cooperativity between C R A M P and protease effectors. 149 5.9 Role of vacuolar acidification in bacterial filamentation. 152 5.10 Interplay between multiple antimicrobial effectors impairs S. Typhimurium cell division. 154 B . l SifA mediates survival/replication of S. Typhimurium within macrophages. 206 List of Abbreviations x AEBSF 4-(2-Aminoethyl) benzenesulphonyl fluoride A T C C American Type Culture Collection. B M D M bone marrow-derived macrophage(s) C F U colony forming unit(s) CR complement receptor C R A M P cathelicidin-related antimicrobial peptide DIC Differential interference contrast microscopy D M E M Dulbecco's modified Eagle medium DMSO dimethylsulphoxide D - N M M A NG-D-monomethyl arginine DP-1 DRTF polypeptide-1 DPI diphenyleneiodonium E R K extracellular signal-regulated kinase EST expressed sequence tag FACS fluorescence activated cell sorting FBS fetal bovine serum GFP green fluorescent protein h hour Hox homeobox transcription factor ICE interleukin 1 converting enzyme IFN-y interferon-y 1-KB inhibitory Kappa B IL interleukin iNOS inducible nitric oxide synthase L A M P lysosome-associated membrane protein L B Luria-Bertani broth L - N M M A NG-L-monomethyl arginine LPS lipopolysaccharide MIP macrophage inflammatory protein MOI multiplicity of infection xi List of Abbreviations N F - K B nuclear factor Kappa B PCR polymerase chain reaction Phox phagocyte N A D P H oxidase ROI reactive oxygen intermediate RNI reactive nitrogen intermediate s c v Salmonella-containing vacuole SD standard deviation S E M standard error of the mean Sif Salmonella-induced filament SPI2 Salmonella pathogenicity island 2 TGF-p tumor growth factor-(3 TLR Toll-like receptor wt wild type X l l Acknowledgements I am grateful to so many people who made this work possible. Working with the many past and present members of the Salmonella group and the Finlay lab has been a fantastic experience. Their ideas, support, and encouragement are all reflected in these pages. Thank you to Brett, for giving me the freedom to find my own path in the lab. And thanks to Gwen, for always making time, and helping to make jumping through the hoops of graduate school feel manageable. I, and this work, benefited from ongoing discussions with my valuable collaborators Monisha Scott, Mike Gold, Bob Hancock, Ferric Fang, David Speert, Andy Pollard, and Rich Gallo. My committee members, Rachel Fernandez, Rick Stokes, and Alice Mui have never failed in their support and advice. Thank you to everyone in the U B C Biolmaging Facility and the B R C Multi-User Flow Cytometry Facility for advice on experiments, Fern Ness for graphic design of the models, and Fiona Brinkman for creating the web site for the array data. This work was performed in the Department of Microbiology and Immunology and Biotechnology Laboratory. I appreciate the support of the Natural Sciences and Engineering Research Council, the Canadian Institutes for Health Research, the Michael Smith Foundation for Health Research, and the William and Dorothy Gilbert Scholarship in Biomedical Sciences over the course of my studies. And my deepest appreciation to Richard, my parents, family, and friends, who provided vital perspective and encouragement over the years and share in my enthusiasm for research. 1 Chapter 1 Introduction. 1.1 Preface. Portions of this chapter have been adapted from previously published work: Carrie M . Rosenberger and B. Brett Finlay. 2003. Pathogen sabotage: Disruption of signaling by bacterial pathogens. Nature Reviews Molecular Cell Biology. 4: 385-396. Carrie M . Rosenberger, Andrew J. Pollard, and B. Brett Finlay. 2001. Gene array technology to determine host responses to Salmonella. Microbes and Infection. 3:1353-1360. 1.2 Macrophages. 1.2.1 Macrophage Biology. Mononuclear phagocytes develop from a myeloid lineage in the bone marrow that differentiate into long-lived resident tissue macrophages. There is plasticity in macrophage development, as they can arise from a mobile pool of infiltrating monocytes or from proliferation of resident macrophages (1). These ubiquitous cells play important roles in normal homeostatic and immunological processes. Metchnikoff identified the central importance of macrophages in response to infectious agents. He wrote that "the vital manifestation of the phagocytes, irritability, mobility, and voracity, constitutes an essential factor in ridding the animal of micro-organisms, because the true bacteriocidal ferment is contained within the phagocytes", thereby proposing the now widely accepted theory of cellular immunity (2). It has been recognized for a century that macrophages are not a homogeneous population of cells. Resident macrophage populations in the spleen, lung (alveolar macrophages), liver (Kupffer cells), and skin (Langerhans cells) differ from each other and from macrophages recruited during inflammation or infection. Heterogeneity also exists within each population of macrophage, due to the milieu of cytokines, foreign antigens, and other cell types present in different microenvironments (3, 4). Macrophages can respond to cues of danger such as inflammatory cytokines (i.e. interferon (IFN)-y) or bacterial components by altering their 2 phenotype and becoming "activated". Such macrophage activation by IFN-y is necessary for clearance of a variety of pathogens. Macrophage activation is a complex and multi-stage process that results in the so-called "angry macrophage", possessing increased speed and magnitude of responses to pathogens (5-7). Therefore macrophage phenotype can dramatically influence the response to pathogens. It can also influence data interpretation and comparisons between experiments. 1.2.2 Pathogen recognition: Modulins and pattern recognition receptors. In contrast to many other cell lineages, unstimulated macrophages constitutively express unique receptor repertoires to rapidly detect bacteria and trigger cell signaling, and inflammatory stimuli such as cytokines can further enhance receptor expression and downstream responses. These receptors include pattern recognition receptors, which recognize conserved microbial chemical structures, and receptors that bind host molecules, which opsonize microbes and thereby transmit a danger signal. • Examples of these receptors include: complement receptors, which bind microbes coated with host serum complement proteins and microbial sugars; Fc receptors, which bind antibody-opsonized microbes; lectins such as the mannose receptor, which bind microbial sugars; scavenger receptors, which bind microbial lipoproteins, and Toll-like receptors, which bind diverse bacterial products (8). Pattern recognition receptors can also interact with each other to increase the repertoire of recognized ligands and maximize responsiveness (9-12). Many of these receptors can mediate phagocytic internalization of microbes as well as initiate signal transduction (13). Cytosolic surveillance systems also exist. NODI (nucleotide-binding oligomerization domain) mediates response to cytosolic bacterial peptidoglycan diaminopimelic acid (iE-DAP) (14). Cytosolic Listeria initiates p38 mitogen-activated protein kinase (MAPK) signaling and subsequent transcription of interferon-^ (IFN-(3) and IL-8 independently of TLRs (15). 3 Macrophages can recognize conserved bacterial products, termed modulins, such as lipopolysaccharide (LPS), porins, fimbrial proteins, flagella, bacterial D N A containing methylated CpG motifs, lipoproteins, glycoproteins, lipoarabinomannan, and peptidoglycan ( 1 6 ) . LPS, the cause of endotoxic septic shock, is likely the most heavily studied modulin. Historically referred to as endotoxin, LPS is an essential and highly conserved component of the cell wall of Gram-negative bacteria comprised of a bioactive lipid A moiety, which is inserted into the membrane, and an antigenicly variable polysaccharide, which is exposed on the bacterial surface. Purified LPS is a potent immunostimulatory molecule that is recognized by T L R 4, which initiates rapid changes in both macrophage signaling pathways and gene expression. LPS alters the expression of a variety of genes including transcription factors, cytokines, chemokines, receptors, and cationic antimicrobial peptides (see ( 1 7 - 1 9 ) for a thorough review of macrophage recognition of LPS). However, the relative contribution of LPS in the context of the many other modulins expressed by Gram-negative bacteria is unclear. 1.2.3 Macrophage Signaling Macrophages integrate information received from pattern recognition receptors, phagocytosis, and cytokines and tune signal transduction cascades to create the appropriate response to the microbial threat. LPS alone induces signaling that includes serine kinases such as MEK7ERK and p38 M A P kinases, tyrosine kinases such as lyn and hck, heterotrimeric G proteins, PI-3 kinase, protein kinase B (PKB), GTPases such as Rac, phospholipase C (PLC), ceramide, arachidonic acid metabolites, reactive oxygen and nitrogen intermediates (ROI and RNI), and N F - K B translocation (8, 20). Other modulins use distinct TLRs to trigger overlapping and unique downstream signaling pathways. The magnitude and kinetics of signaling is tightly controlled by inhibitory molecules and phosphatases to prevent damage to the host caused by unregulated inflammatory signaling. Signaling also culminates in activation of transcription 4 factors such as nuclear factor K B , AP-1, and signal transducer and activator of transcription (STAT) proteins, leading to cytokine and chemokine gene expression (19). 1.2.4 Antimicrobial capacities Signaling coordinates macrophage killing mechanisms by activation and recruitment of antibacterial effectors to the phagolysosome. Macrophages have a high rate of phagocytosis and pinocytosis and are constantly sampling their environment (see (13) for a review of phagocytosis). Internalized microbes are trafficked through increasingly hostile compartments in the phagolysosal network, and can be degraded with combinations of ROI, RNI, acidification, nutrient limitation, lysozyme, hydrolases, and proteases (5). Macrophages express the necessary antigen processing pathways and co-stimulatory molecules to initiate class I- and class II-restricted antigen presentation, to alert the adaptive immune response to the location and identity of an infectious agent. Macrophage signaling also culminates in the activation of transcription factors, leading to expression and release of a plethora of cytokines and chemokines (21). Cytokines can have autocrine as well as paracrine effects on cell types in addition to macrophages. These soluble mediators regulate inflammation and response to infection by stimulating fever, production of compounds such as acute phase proteins and mannose-binding protein, altering vascular permeability, recruitment of immune cells, and regulating cellular activation states. Macrophages are therefore crucial generalists within the immune system, as other cell types possess more specialized or potent repertoires of capacities but lack in breadth. Macrophages occupy a central role in immune responses to pathogens, as an ideally-situated population capable of expansion, activation, and coordination of both innate and adaptive immune responses. As such, macrophages are often targeted by bacterial pathogens that benefit from interfering with immune responses (see Appendix C, (22, 23) for a more comprehensive discussion). 5 1.3 Salmonella Typhimurium. 1.3.1 Salmonellosis. The species Salmonella enterica is a Gram negative bacteria and contains nearly 2 000 serotypes, a few of which cause significant disease in humans (24, 25). Salmonella enterica serovars Enteritidis and Typhimurium are common causes of food and water-borne gastroenteritis (26), usually a self-limiting disease characterized by diarrhea in North America but leading to dehydration,, malnutrition, and death in populations with poor health status. 5*. Typhimurium can also cause a systemic disease in humans similar to typhoid, notably in immunocompromised individuals such as patients with AIDS or malaria. Salmonella Choleraesuis causes a less frequent invasive disease. Salmonella enterica serovars Typhi and Paratyphi are the causative agents of typhoid fever, a systemic disease characterized by fever and intestinal perforation and hemorrhage, responsible for an estimated 16 million cases worldwide each year (27). S. Typhi is highly adapted to humans and no animal model exists. However, Salmonella Typhimurium infection of mice provides a well-characterized analogous disease useful to study the pathogenesis of human typhoid fever (28). In this model, orally ingested bacteria penetrate the intestinal mucosa, primarily using M cells (29, 30). 5*. Typhimurium is disseminated systemically by CD18-positive lymphocyte vehicles, migrating via the lymph nodes to the spleen and liver, where they reside intracellularly within macrophages to cause systemic disease (31-33). 1.3.2 Mechanisms of virulence. S. Typhimurium is genetically similar to E. coli and therefore genetically tractable, making it an excellent candidate for understanding the molecular basis for its ability to cause disease. Salmonella has acquired a number of genetic elements that have allowed them to 6 become enteric and systemic pathogens. The genome of S. Typhimurium contains five identified pathogenicity gene islands (SPI), clusters of virulence genes acquired by horizontal gene transfer and with a GC content distinct from the rest of the genome. These pathogenicity islands are common attributes of bacterial pathogens and encode virulence factors together with machinery for their regulation and secretion. SPI 1 and SPI 2 each encode a multi-subunit type III secretion system (TTSS), with homology to the TTSS of Shigella and enteropathogenic E. coli, respectively, which deliver virulence proteins directly from the bacteria to the host cell cytosol (reviewed in (34) and (35)). Secretion by the SPI 1-encoded TTSS mediates host cell cytoskeletal rearrangements and bacterial invasion. Expression of SPI 1-encoded genes is downregulated in the intracellular environment, and SPI 1-secretion mutants are attenuated in the intestinal phase of disease but show normal virulence i f injected into mice, suggesting that SPI 1 gene expression does not play an essential role in the systemic phase of disease. SPI 2 has been shown to be essential for survival and replication within macrophages, which is necessary to cause systemic disease (36, 37). SPI 2 encodes a TTSS, at least 7 putative virulence proteins, and a two-component regulatory system to control SPI 2 gene expression (38). Mutants with a deletion in an apparatus component, such as SsaR or SsaV, cannot secrete virulence proteins and fail to replicate within macrophages (36, 39). Virulence proteins encoded outside of these identified islands can also be regulated and secreted in a SPI 2-restricted manner, for example SspH2, SifA, PipB, and SlrP (40-43). S. Typhimurium also contains the pSLT virulence plasmid that encodes a number of potential virulence proteins and serves to increase the growth rate within mice (44). The two-component regulatory system PhoP/Q regulates gene expression required for systemic infection, resistance to antimicrobial peptides, interference with antigen presentation, and avoidance of phagolysosome fusion (45, 46). SPI 2 secretion is essential for intramacrophage replication, perhaps due to the modifications of endosomal trafficking induced by secreted virulence proteins. S. Typhimurium 7 rapidly uncouples itself from the normal endocytic maturation and avoids lysosomal degradation by creating a unique intracellular compartment, the Salmonella-containing vacuole (SCV) (reviewed in (47)). Upon entering macrophages, the SCV transiently interacts with normal early endosomal compartments (expressing the markers EEA1, Rab5, and transferrin receptor) as well as endoplasmic reticulum (expressing glucose-6 phosphatase). The SCV retains the GTPase Rab5, excludes Rab7, and matures into a modified late endosomal/lysosomal compartment (expressing the markers LAMP1 and L A M P 2 and cathepsin L (in some macrophages) but with little L B P A , cathepsin D, and mannose-6-phosphate receptor) (46-52). This compartment forms within an hour of infection and is characterized by delayed acidification to pH 4-5, enrichment of cholesterol, uncoupling from fluid-phase endocytosis, and is surrounded by a meshwork of polymerized G-actin (31, 53-56). Creation of this replication-competent SCV is dependent upon SPI 2-mediated secretion, and the contribution of particular secreted proteins has been uncovered. The S. Typhimurium proteins SseF, SseG, SseJ, and SifA play roles in aggregation of endosomal membranes or membrane integrity, and SpiC/SsaB is proposed to inhibit the fusion of SCV membranes with lysosomes (57-61). SpvB, encoded on the virulence plasmid, Ssel/SrfH, and SspH2 may be involved in actin remodeling around the SCV, which is proposed to limit the accessibility of the SCV and block interactions with lysosomal compartments (62-65). SPI 2 secretion also impairs acquisition of the phagocyte oxidase (phox) and inducible nitric oxide synthase (iNOS), responsible for the oxidative and nitrosative bursts, respectively, via an unknown mechanism (66-68). S. Typhimurium likely alters aspects of macrophage biology in addition to endosomal trafficking, and effects of these bacterial proteins on other cellular processes or gene transcription have yet to be identified. The recent elucidation of the genomic sequence of S. Typhimurium will also undoubtedly identify new secreted virulence factors. 8 1.3.3 Salmonella interactions with host cells S. Typhimurium can invade most cell types and replicate within epithelial, melanoma, and macrophage cell lines. In contrast, there is a striking decrease in intracellular C F U within the first few hours in macrophages isolated from mice (elicited and resident peritoneal, splenic, and bone marrow-derived), followed by a relatively static number of intracellular C F U (69). Studies using a temperature-sensitive plasmid have revealed that this apparent static population size belies a dynamic process, resulting from bacterial attrition and proliferation, and showed that SPI 2 plays a more important role in facilitating bacterial replication than protecting bacteria from killing (37). 5*. Typhimurium does not replicate well within fibroblasts or neutrophils, either because these cells restrict the bacteria's ability to grow or because it could be advantageous for the bacteria to limit their replication within particular cell types (70-72). S. Typhimurium resides within dendritic cells, and there are contradictory reports of whether dendritic cells permit bacterial replication (73-77). Regulation of bacterial virulence factor expression and secretion are cell type-specific, perhaps reflecting the unique arsenals required to combat distinct obstacles to infection. SCV trafficking differs based on macrophage activation state and between cell types (47), although a comparison of SCV in different tissue macrophages has not been published. As well, Salmonella has differing requirements for its SCV: this vacuolar niche is essential within macrophages as the cytosol does not permit replication while the SCV is dispensable within epithelial cells, where cytosolic bacteria replicate faster than their vacuolar counterparts (60, 78). S. Typhimurium has also been found inside hepatocytes (79) and neutrophils (80) in the murine typhoid model, but macrophages in the liver and spleen appear to be the preferred site for bacterial replication (81, 82). Ex vivo infection of macrophages may not adequately model the tissue microenvironments during systemic infection, because a discrepancy exists between the bacterial replication observed within splenic and hepatic macrophages in infected mice and the ability of macrophages infected ex vivo to limit bacterial replication (69). 9 1.4.1 Role of macrophages in the murine typhoid model. Because their intramacrophage niche helps to shield Salmonella from killing by components of the innate and humoral immune defenses, the responses of infected macrophages should serve a central role in determining the disease outcome. Prior activation of macrophages by interferon (IFN)-y dramatically influences macrophage gene expression and capacity to coordinate immune responses. IFN-y, produced by natural killer cells and T lymphocytes 2-3 days after S. Typhimurium infection, is essential for clearance of S. Typhimurium infection in mice (83-85). Therefore, naive macrophages initially encounter S. Typhimurium while IFN-y activated macrophages may play a larger role at later stages of infection. Since most studies of macropha.ge-Salmonella interactions use cultured or isolated macrophages, a study using liposomes to selectively deplete tissue macrophages provides important insights into their role in the murine typhoid model (81). The presence of macrophages correlated with tissue pathology and mortality following S. Typhimurium infection, with macrophage-depleted mice surviving a normally lethal dose of S. Typhimurium. Macrophages were shown to be important effectors during infection of vaccinated mice, but were not required during the initial vaccination to establish cellular or humoral immunity. The authors speculate that exaggerated macrophage responses to bacterial factors such as LPS may mediate the pathology associated with S. Typhimurium in naive mice while the actions of IFN-y activated macrophages may be important in mediating bacterial clearance in immune mice (81). Macrophage phenotype is affected by activation state, cytokine exposure, tissue distribution, interactions with other cells, the mechanism of bacterial entry, and other factors, all of which cannot be fully reproduced in vitro. Therefore, in vivo studies are essential for understanding their physiological role during S. Typhimurium infection 10 1.4.2 Role of macrophages in innate immune responses to Salmonella. The innate immune system permits a general rapid response to an infectious agent. Macrophages normally reside beneath mucosal surfaces and in tissues and lymphoid organs, making them well-situated to rapidly detect S. Typhimurium. This initial recognition is important in determining disease pathogenesis. Mice deficient in T L R 4, which are therefore unresponsive to LPS, are protected from lethal septic shock but are more susceptible to S. Typhimurium infection (86-88). Recognition of bacteria can also lead to phagocytosis. Macrophages can phagocytose S. Typhimurium opsonized with complement, using CR1 and CR3 complement receptors, or bacteria opsonized with specific antibody in mice that have previously been exposed to S. Typhimurium, using Fc receptors (89). The contribution of phagocytosis relative to active bacterial invasion of macrophages is unclear, as it is not currently known whether S. Typhimurium is invasive during systemic infection. The composition of its intracellular compartment and short-term survival is not affected by the mechanism of bacterial entry (90, 91). Internalization of other pathogens using the CR1 complement receptor avoids activating the oxidative burst, but it is not known how macrophage signaling and trafficking events are altered by the receptors engaged during Salmonella uptake (92). Different macrophage signaling events are likely to occur depending on the complement of receptors used for internalization of the bacteria, but this has not been addressed experimentally as the receptors used by S. Typhimurium to invade macrophages are not known. Studies using mice deficient in various effector mechanisms have revealed their role during 5". Typhimurium infection. Two enzymes that are crucial for the macrophage's microbicidal activity are the phagocyte N A D P H oxidase and inducible nitric oxide synthase (reviewed in (93)). These enzymes catalyse the oxidative burst: synthesis of antibacterial reactive oxygen and nitrogen intermediates that include superoxide, nitric oxide and peroxynitrite. These reactive species can damage bacterial nucleic acids and proteins, and 11 recombination-impaired S. Typhimurium mutants, which cannot repair the damage caused by these compounds, are more sensitive to killing by macrophages in vitro and are attenuated in mice (94, 95)). Phox-deficient mice, which cannot produce an oxidative burst, have impaired ability to control early bacterial replication, and this has been shown to be mediated by macrophages. iNOS-deficient mice, which cannot produce a nitrosative burst, have impaired ability to control later bacterial replication. Macrophages from these mice kill bacteria normally within the first few hours of infection using an oxidative mechanism, but require iNOS to control intracellular bacterial numbers after 24 h (96, 97). Infection of mice deficient in both phox and iNOS indicates that antibacterial activity exists against S. Typhimurium independent of these two effector mechanisms (98). Innate immune responses also include antimicrobial peptides, cationic peptides such as cathelicidins and defensins which can bind LPS, damage bacterial membranes, and alter macrophage gene expression (99). The contribution of cationic peptides to macrophages' antimicrobial capabilities has yet to be determined. TNFR1-deficient mice, which lack the receptor to respond to the proinflammatory cytokine TNF-a, are also impaired in their ability to limit bacterial replication through perturbation of phox trafficking (100). In addition to TNF-a, the cytokines I L - l a , IL-12, IL-15, IL-18, and IFN-y are all produced by macrophages and are important in host clearance of S. Typhimurium (reviewed in (101)). IFN-y is a potent cytokine produced by N K cells, T cells, and macrophages. In S. Typhimurium infection, high levels are produced by the lymphoid cells of the intestinal Peyer's patches, and this appears to be required for priming macrophage responses and inhibiting bacterial growth (84, 85, 102). Host genetics can also dictate susceptibility to S. Typhimurium infection. Most studies examining host responses to S. Typhimurium use susceptible mice, such as B A L B / c , or cells derived from these mice, such as R A W 264.7 cells. These mice possess a point mutation in the Nrampl gene (natural resistance-associated macrophage protein 1; renamed Slcl l a l , also known 12 as Ity/Bcg/Lsh), which blocks expression of a functional protein (see (103, 104) for reviews of Nrampl). Susceptible mice succumb to a low dose of S. Typhimurium due to uncontrolled bacterial replication, while resistant mice can clear the same infection using innate immune mechanisms. Nrampl"1" resistant mice show increased IFN-y production, phagosomal pH, and oxidative burst. Nrampl is a divalent cation transporter, although the mechanism underlying its important role in host defense is not clear. While Nrampl"7" mice and cells are used by the majority of Salmonella researchers, these experimental systems do not fully model human Salmonellosis since most humans express a functional Nrampl protein. 1.4.3 Role of macrophages in adaptive immune responses to Salmonella. While N R A M P + resistant mice can clear infection with a low dose of S. Typhimurium using innate immune defenses, N R A M P " mice require both humoral and cellular arms of acquired immunity to counter S. Typhimurium infection (105, 106). For bacterial pathogens that breach the pre-existing innate immune defenses, an adaptive or acquired immune response is necessary for clearance of the infection. This later phase of the immune response is mediated by T and B lymphocytes and offers several advantages to innate immunity: remarkable specificity and immunological memory. Macrophage recognition of bacterial pathogens controls adaptive immune responses. Macrophages shape these later responses through cytokine production and antigen presentation, to activate cytotoxic CD8 + T cells to kil l infected cells or CD4 + T cells to interact with B cells to facilitate antibody production. Infected macrophages interact with CD4 + T cells to promote release of IFN-y and other cytokines that favour a T H I response, which is most effective for controlling infection by intracellular bacteria. Dendritic cells also have a fundamental role in initiating adaptive immune responses to bacterial pathogens (reviewed in (107)). Both dendritic cells and macrophages can identify bacteria using pattern-recognition 13 receptors, phagocytose bacteria and process antigen for presentation, but dendritic cells have the added capacity to migrate more readily to lymph nodes and activate naive T cells. Macrophages are capable of antigen presentation when infected by S. Typhimurium. Peptides from bacterial flagellar protein as well as ovalbumin, expressed by engineered bacteria, are presented by surface MHCII on infected macrophages along with the necessary costimulatory molecules to initiate a CD4 T cell response (108, 109). Macrophages that are killed by S. Typhimurium through apoptosis are taken up by dendritic cells and bacterial antigens are cross-presented to T cells (110). Classic adoptive transfer experiments showed that both CD4 + and CD8 + T cell responses as well as humoral responses are important in clearance of S. Typhimurium (106, 111, 112). 1.4.4 Macrophage subversion by S. Typhimurium. Macrophages are both sentinels and the first line of defense against infection, and S. Typhimurium possess numerous mechanisms for subverting macrophage functions. This is essential for pathogenesis, as S. Typhimurium mutants that cannot replicate within macrophages are avirulent in mice (113). As described earlier (section 1.3.2), Salmonella uses SPI 2 TTSS-secreted virulence proteins to perturb intracellular trafficking of the SCV. The SCV does not acquire the full complement of cathepsins and lysosomal hydrolases used by lysosomes to degrade bacteria. While the SCV does acquire the v-ATPase proton pump, S. Typhimurium is acid tolerant and can replicate at low pH, and bacterial survival is not improved if acidification is blocked (114, 115). In fact, secretion of a virulence protein by the SPI 2 TTSS requires acidification (116). S. Typhimurium can protect itself from reactive oxygen intermediates by two mechanisms, First, S. Typhimurium express superoxide dismutase to resist oxidative damage (117, 118). Second, bacterial SPI 2-secreted virulence proteins prevent assembly of active phox and iNOS enzymes on the SCV membrane, and thereby minimize damage from 14 reactive intermediates (66-68). S. Typhimurium express a number of genes that mediate resistance to antimicrobial peptides. Bacteria with loss of function mutations in the PhoP/PhoQ two component regulatory system, the sap A operon, and the mig-14 gene, are all more susceptible to antimicrobial peptides (119-122). S. Typhimurium can kil l macrophages, although the physiological relevance of each of two possible killing pathways is unclear (see (123, 124) for reviews of this controversial topic). Depending on the growth phase of the bacteria (which alters virulence factor expression), mechanism of entry, and bacterial load, macrophages die by rapid apoptosis (within 30 min) dependent on caspase 1, or a slower apoptosis (after 24 h; also referred to as necrosis) that is independent of caspase 1 (125-129). S. Typhimurium express a virulence protein called SipB, which is expressed under SPI 1-inducing conditions and activates the caspase 1/interleukin 1-converting enzyme (ICE), resulting in both macrophage death and release of the proinflammatory cytokine IL-16(130). Studies using caspase 1-deficient mice show that bacterial activation of caspase 1 and IL-1 [3 release facilitates pathogen spread to systemic sites and is detrimental to the host (131). Macrophage apoptosis has been observed in vivo within infected liver, but the pathway of cell death and whether it is coupled with inflammation is not known (132). Kill ing macrophages, the apparent primary reservoir of S. Typhimurium within mice, would be a disadvantage i f it happened too rapidly or i f bacteria lack a means of escaping dying cells. It would however be advantageous to eliminate macrophages, thereby interfering with a coordinated immune response requiring cytokine production or antigen presentation. S. Typhimurium uses a two-component gene expression regulatory system, PhoP/PhoQ, to decrease antigen presentation by infected macrophages, although the mechanism is not known (108). In addition, the pSLT virulence plasmid impairs recruitment of yb T cells within infected mice 15 (133). S. Typhimurium therefore uses a variety of mechanisms to interfere with macrophages, and this provides an excellent model for dissecting the interplay between host and pathogen. 1.5 Transcriptional profiling of infected macrophages. Large scale expression profiling is a tool for ascribing biological function to the rapidly increasing amount of available genomic sequence data. Gene expression arrays are available in a variety of formats and have been used to probe the biology of many cell types (see (134, 135) for overviews of the technology and its applications). In brief, the mRNA abundance for thousands of genes can be measured within cells by hybridizing a labeled probe synthesized from mRNA to cDNAs or oligonucleotides arrayed on a solid support and measuring the hybridization intensity for each gene. D N A arrays are a powerful tool for expanding our current understanding of host-pathogen relationships for a variety of reasons (136). A proven strength of this experimental approach has been the ability to study the expression of hundreds or thousands of genes efficiently and simultaneously without biasing conclusions drawn from studying a small subset of genes presumed to be involved in a particular process. This permits an unprecedented broad and objective view of mRNA levels within infected cells, which wil l only expand with the increasing availability of completed genomic sequences from many hosts and pathogens. This high-throughput approach allows analysis of changes in the expression of a large number of genes under uniform experimental conditions, including infectious dose and cell passage number. Gene arrays permit comparison of expression profiles obtained from multiple stages of infection or different host cell types, from stimulation with purified microbial products, or from infection with bacterial virulence factor mutants. This technique also measures changes in individual genes in the context of how the expression of other members of the gene family, their receptors, ligands, or transcriptional activators are altered. By identifying patterns of gene expression that would not be evident from studying each gene in isolation by conventional 16 methods, this technology will allow a more comprehensive understanding of host responses to bacterial infection. 1.6 Summary of thesis. One way to dissect the complexity of host-pathogen interactions is by using a global expression profiling approach offered by gene array technology, as detailed in Appendix D. Chapter 2 describes array hybridization experiments examining the expression of hundreds of genes in Salmonella-infected macrophages. This approach identified changes in the expression of genes not previously recognized to be involved in host response to infection. The relative contributions of a host factor (the cytokine IFN-y). and a bacterial surface component (lipopolysaccharide) in mediating the altered gene expression profile was also addressed. Chapter 3 summarizes the results of array hybridization experiments aimed at determining the contribution of SPI 2-secreted virulence factors in altering macrophage gene expression. Appendix B shows that a SPI 2-secreted virulence factor can facilitate bacterial replication within macrophages. These studies identified upregulated expression of M E K 1 kinase in macrophages infected by S. Typhimurium. As this kinase plays a key role in regulating macrophage signal transduction and antimicrobial activities, the functional role of M E K 1 in Salmonella-infected macrophages was characterized. As described in Chapter 4, upregulated MEK1 gene and protein expression was measured in Salmonella-infected macrophages, and this correlated with increased M E K 1 kinase activity in these cells. Inhibiting M E K kinase activity significantly increased intracellular bacterial numbers. In addition, while macrophages exert stress on intracellular Salmonella and impair bacterial cell division to result in long filamentous bacteria, there was a significant decrease in the number of filamentous Salmonella when MEK1 kinase activity was impaired. This filamentous morphology was also dependent on the production of reactive oxygen intermediates (ROI), which function in parallel to M E K signaling. 17 Chapter 5 details experiments undertaken to characterize the macrophage effector mechanism(s) responsible for impairing the replication of this intracellular pathogen and the consequent bacterial filamentation. Antimicrobial peptides have established an important role in the defense against extracellular infections, but the expression of cationic peptides within macrophages as an antibacterial effector mechanism against intracellular pathogens has not been demonstrated. Macrophages indeed express the antimicrobial peptide C R A M P , and this expression was increased following S. Typhimurium infection and was dependent on the macrophage's production of reactive oxygen intermediates. Using CRAMP-deficient mice or synthetic C R A M P peptide, we found that C R A M P impairs Salmonella cell division in vivo and in vitro, resulting in long filamentous bacteria. This impaired bacterial cell division was also dependent on intracellular elastase-like serine protease activity, which can proteolytically activate antimicrobial peptides. A peptide-sensitive Salmonella mutant showed enhanced survival within macrophages derived from CRAMP-deficient mice, indicating that Salmonella can sense and respond to cationic peptides in the intracellular environment. Together, these results show that intracellular ROIs and proteases regulate macrophage C R A M P expression and activity to impair the replication of an intracellular bacterial pathogen. 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Induction of gamma/delta T cells in murine salmonellosis by an avirulent but not by a virulent strain of Salmonella choleraesuis. J Exp Med 176:363. 134. Lockhart, D. J., and E. A . Winzeler. 2000. Genomics, gene expression and D N A arrays. Nature 405:827. 135. Eisen, M . B. , and P. O. Brown. 1999. D N A arrays for analysis of gene expression. Methods Enzymol 303:179. 136. Cummings, C. A. , and D. A . Relman. 2000. Using D N A microarrays to study host-microbe interactions. Emerg Infect Dis 6:513. 30 Chapter 2 Salmonella Typhimurium Infection and Lipopolysaccharide Induce Similar Changes in Macrophage Gene Expression 2.1 Preface. This chapter was previously published in part as: Carrie M . Rosenberger, Monisha G. Scott, Michael R. Gold, Robert E.W. Hancock, and B. Brett Finlay. 2000. Salmonella Typhimurium Infection and Lipopolysaccharide Induce Similar Changes in Macrophage Gene Expression. The Journal of Immunology. 164: 5894-5904. 2.2 Summary. Changes in macrophage phenotype induced during infection result from the recognition of bacterial products as well as the action of bacterial virulence factors. We used the unprecedented opportunity provided by gene arrays to simultaneously study the expression of hundreds of genes during Salmonella Typhimurium infection of macrophages and to assess the contribution of the bacterial virulence factor, lipopolysaccharide, in initiating the host responses to Salmonella. We found that S. Typhimurium infection caused significant changes in the expression of numerous genes encoding chemokines, cell surface receptors, signaling molecules, and transcriptional activators at four hours post-infection of the R A W 264.7 murine macrophage cell line. Our results revealed changes in the expression of several genes which had not been previously implicated in host responses to S. Typhimurium infection, as well as changes in the expression of several genes previously shown to be regulated by 5*. Typhimurium infection. A n overlapping spectrum of genes was expressed in response to virulent S. Typhimurium and purified S. Typhimurium lipopolysaccharide, reinforcing the major role of this surface molecule in stimulating the early response of macrophages to bacterial infection. The gene expression profile was further altered by activation with interferon-y, indicating that host cell responses depend on the activation state of the cell. 31 2.3 Introduction. Salmonella species are the causative agents of typhoid fever and diarrheal diseases in humans, responsible for an estimated 16 million cases of systemic typhoid fever worldwide each year (1). Salmonella Typhimurium infection of mice provides a well characterized model for the pathogenesis of human typhoid fever. Orally-ingested bacteria penetrate the intestinal mucosa and migrate via the lymph nodes to the spleen and liver to cause systemic disease (2, 3). During bacterial infection, macrophages serve as professional phagocytes and key effectors of the innate and adaptive immune responses. S. Typhimurium capitalizes on the macrophage's phagocytic nature, and has been shown by confocal microscopy to reside intracellularly within macrophages, where it replicates within specialized vacuoles (4). As this intracellular niche helps to shield Salmonella from host-mediated killing by components of the innate and humoral immune responses, the antimicrobial actions of infected macrophages serve a central role in determining the outcome of disease (5). In the in vivo mouse model of human typhoid fever, interferon-y (IFN-y) is released by natural killer and T cells two to three days following S. Typhimurium infection. IFN-y is a potent stimulator of macrophage gene expression and is necessary for clearance of S. Typhimurium and other intracellular bacteria (6-8). A variety of studies, including the use of gene arrays, have supplied a wealth of data regarding differential gene expression in response to IFN-y stimulation (9, 10). These pleiotropic effects on gene expression translate into alterations in receptor expression, antigen presentation, phagocytosis, cell proliferation, metabolism, and the antimicrobial oxidative and nitric oxide burst (11, 12). While IFN-y is thought to prime the macrophage to respond more rapidly and effectively against invading pathogens, the spectrum of genes whose expression is altered during bacterial infection in unprimed versus IFN-y-primed cells has not been extensively analyzed. Investigating how IFN-y activation alters the ability of 32 S. Typhimurium to affect macrophage gene expression may lead to the identification of genes that contribute to IFN-y's critical role during S. Typhimurium infection. Macrophages have evolved the ability to recognize bacterial products and to rapidly initiate an immune response to clear the microbe. A n innate pattern of macrophage response is triggered by conserved bacterial products such as: LPS, porins and other outer membrane proteins, flmbrial proteins, flagella, lipoproteins, glycoproteins, and peptidoglycan (13). These bacterial components, termed modulins, signal through CD 14 or other pattern recognition receptors to modulate overlapping as well as unique host cell gene expression. These signals help to initiate the innate and specific immune responses to clear the bacterial infection (14, 15). The bacterial surface component lipopolysaccharide (LPS) is a potent immunostimulatory molecule that initiates both rapid changes in macrophage signaling pathways and adaptive changes in macrophage gene expression. LPS alters the expression of a variety of genes including transcription factors, cytokines, chemokines, receptors, and cationic antimicrobial peptides (16-19). Other structural components of Salmonella such as porins and flagella induce cytokine gene expression independently of LPS (20-22). To promote their survival, bacterial pathogens such as S. Typhimurium secrete specialized protein effectors that induce alterations in the responses of host cells (23). These effectors specifically affect host cell functions such as cytoskeletal architecture, vesicle trafficking, cell signaling, and apoptosis in order to create a more hospitable intracellular niche (24-28). Most studies to date have shown how bacterial effectors modify existing host proteins rather than examining how host gene transcription is affected. One way to analyze both the complex interactions between host and pathogen as well as the priming effects of IFN-y is with a general approach such as gene arrays. Gene array technology has recently been used for a more global view of differential gene expression in such . . . 33 fields as inflammatory diseases (29), tumor biology (30), human cytomegalovirus infection (31), superantigen stimulation of T cells (32), S. cerevisiae metabolism (33), and genetic variability of Mycobacterium tuberculosis (34, 35). The array chosen for this study contained 588 cDNAs for genes involved in a wide range of cellular processes and were not restricted to those with characterized roles in defense against infection. One proven strength of this experimental approach has been the ability to study the expression of hundreds of genes simultaneously without biasing conclusions drawn from a subset of genes presumed to be involved in a particular process. We capitalized on gene array technology to obtain, for the first time, a more comprehensive picture of how macrophage gene expression is altered during infection by a pathogenic bacterium. Differential host cell gene expression was examined in an in vitro model of S. Typhimurium infection using the R A W 264.7 murine macrophage cell line, a common model for the intracellular growth of S. Typhimurium. Gene arrays were used to test two hypotheses: (1) that most of the gene expression changes in macrophages infected by S. Typhimurium can be induced by LPS, the major constituent of S. Typhimurium outer membranes, and (2) that the priming of macrophages by IFN-y alters the spectrum of genes induced by S. Typhimurium infection. We found that S. Typhimurium infection altered the expression of a large number of genes in R A W 264.7 cells and that an individual virulence factor, LPS, could itself cause many of the same changes in host gene expression. The gene expression profile following infection was altered by priming with IFN-y, revealing how host cell activation state alters macrophage responses to bacterial infection at the molecular level. 34 2.4 Experimental Procedures. Bacterial and cell culture strains and growth conditions. The Salmonella Typhimurium strain SL1344 was obtained from the American Type Culture Collection (ATCC; Manassas, V A ) , cultured in Luria-Bertani (LB) broth, and grown for 6-20 passages. For infections, highly-invasive bacterial cultures were prepared by diluting an overnight culture 1:34 in L B broth and subculturing aerobically with shaking for 3 h at 37°C. The murine macrophage cell line R A W 264.7 (ATCC) was maintained in Dulbucco's modified Eagle medium ( D M E M , Gibco B R L , Burlington, ON) supplemented with 10% fetal calf serum (FBS; Gibco) without antibiotics at 37°C in 5% CO2. Where indicated, the cells were cultured with 200 U/ml IFN-y (Genzyme) for 24 hours prior to infection. Infection Conditions. For immunofluorescence studies and bacterial colony counts, 24 well plates were seeded with 2.5x105 R A W 264.7 cells per well. Bacteria were diluted in culture medium to give a nominal multiplicity of infection (MOI) of approximately 20. Invasion was allowed to proceed for 10 min in a 37°C, CO2 incubator. Cells were washed two times with PBS to remove extracellular bacteria and then incubated in D M E M + 10% FBS containing 100 pg/ml gentamicin (Sigma, St. Louis, MO) to kill any remaining extracellular bacteria and prevent re-infection. After 2 h, the gentamicin concentration was lowered to 10 pg/ml. Colony counts and immunofluorescence were subsequently performed in parallel to compare the variability in the actual number of intracellular bacteria per cell with the average number per cell for the population, as determined by colony counts. To determine invasion efficiency, samples of cells were washed twice with PBS to remove gentamicin and lysed with 1% Triton X-100/0.1% SDS in PBS at 2 h post-infection. Numbers of intracellular bacteria were calculated by colony counts. At various times post-infection, immunofluorescence was performed as previously described 35 (36) using a rabbit polyclonal anti-LPS antibody diluted 1:200 (S. Typhimurium O antigen group B Factors 1,4,5,12; Difco Laboratories Inc., Detroit MI) and Alexa 488-conjugated mouse anti-rabbit secondary antibody diluted 1:400 (Molecular Probes, Eugene OR). Cells were counted within randomly selected fields. Consistently, cells were infected by an average of 1-3 bacteria per cell as assessed by standard plate counts and immunofluorescence studies. RNA Isolation. R A W 264.7 macrophage cells were seeded at 5.6x106 cells in 20 ml media per 150 mm diameter tissue culture dishes and cultured overnight. R A W 264.7 macrophages were infected with S. Typhimurium at an MOI of 20 or stimulated with 100 ng/ml S. Typhimurium LPS (Sigma) for 4 h. After stimulation, the culture medium was removed for measurement of cytokine production. The cells were washed once with DEPC-treated PBS and scraped to detach the cells from the dish. R N A was then isolated using Trizol according to the manufacturer's directions (Gibco). The R N A pellet was resuspended in RNase-free water containing RNase inhibitor (Ambion, Austin, TX). Contaminating genomic D N A was removed using DNasel (Clontech, Palo Alto, CA) in the presence of 50 U RNase inhibitor for 1 hour at 37°C. The reaction was stopped by adding 1/10 volume lOx termination mix (0.1M E D T A [pH 8.0], 1 mg/ml glycogen) and extracted twice with phenol:chloroform:isoamyl alcohol (25:24:1) and once with chloroform. The R N A was then precipitated with 2.5 volumes 100% ethanol and 1/10 volume sodium acetate pH 5.2, resuspended in RNase-free water with RNase inhibitor, and stored at -70°C in aliquots to minimize freeze-thaw cycles. Thirty micrograms of total RNA, as determined by OD260 reading, was routinely, isolated from one 150 mm dish of cells. The quality of the R N A was assessed by gel electrophoresis and ethidium bromide staining. The absence of genomic contamination was confirmed by using the isolated R N A as a template for PCR amplification using |3-actin-specific primers (5 ' -GTCCCTGTATGCCTCTGGTC-3 ' and 5'-36 G A T G T C A C G C A C G A T TTCC-3') in the absence of reverse transcriptase. The absence of an amplicon after 35 cycles was checked by agarose gel electrophoresis and ethidium bromide staining. Mouse cDNA Expression Arrays. Atlas™ Mouse cDNA Expression Arrays I (#7741-1; Clontech) consist of a matched set of positively charged membranes containing duplicate spots of 588 mouse partial cDNAs. Information on the genes represented on these arrays and hybridization protocols can be found on the manufacturer's website: www.clontech.com. Briefly, 32P-radiolabeled first strand cDNA probes were prepared from 2-5 pg of total R N A from each cell population using M M L V reverse transcriptase and pooled primers specific for the 588 genes. 3 2P-labeled cDNA probe was separated from unincorporated nucleotides using the provided ChromaSpin columns and probe activity was measured using a scintillation counter. The arrays were prehybridized for one hour with ExpressHyb containing 100 pg/ml heat-denatured herring sperm D N A (Sigma) to block non-specific hybridization. The filters were then incubated with 5x106 cpm of denatured cDNA probes in 5 ml of hybridization solution in hybridization bottles. Hybridization was performed overnight at 71 °C in a hybridization oven and bottles were rotated at 5 rpm. The filters were then extensively washed at low and high stringency conditions in hybridization bottles at a rotation speed of 15 rpm, exposed to a phosphoimager screen (Molecular Dynamics, Sunnyvale, CA) for 3 to 5 d at 4°C, and the resulting hybridization signals measured using a PSI Phosphoimager (Molecular Dynamics). Image Analysis. Atlaslmage 1.0 (Clontech) and Excel 5.0 (Microsoft) software were used to quantify and compare the hybridization signals. The intensities for each spot were corrected for background levels and normalized for differences in probe labeling using the average values for genes 37 observed to vary little between our stimulation conditions: (3-actin, ubiquitin, glyceraldehyde-3-phosphate dehydrogenase (GAPDH), calcium binding protein CAB45, and ribosomal protein S29 (37). Spots with an intensity lower than 300 under all conditions, as calculated by Atlas Image, exhibited higher variability and a low signal to noise ratio and were therefore not included in the analysis. Genes included in all tables were selected by the following criteria: the mean hybridization intensity values for genes were altered by more than 2-fold upon S. Typhimurium infection; the averaged data was representative of the individual data sets; duplicate spots on the array gave similar hybridization signals; and the specific hybridization signal was not confounded by background hybridization. Intensity values of zero were replaced by the arbitrary value of 20 to permit ratio calculation. Northern Blots. cDNA was prepared from total R N A purified from R A W 264.7 cells using oligo dT and SuperScriptll reverse transcriptase (Gibco). The following primer pairs were designed to amplify portions of the indicated cDNAs to produce templates for probe synthesis: DP-1 5 ' -TCCAATGGGTCTCAGTACAGC-3 ' , 5 ' -TGTCATTGTCACTGGTGTGG-3' ; IL- ip 5*-TCCAGGATGAGGACATGAGC-3 ' , 5 ' -CTTGTGCTCTGCTTGTGAGG-3' ; Cyclin D l 5 ' -CAGCTTAATGTGCCCTCTCC-3 ' , 5 ' -GGTAATGCCATCATGGTTCC-3 '3 ' ; Tristetraprolin 5 ' -GGACTCGTCATTGCTGTGG-3' , 5 ' -CAATGGCTTTGGCTATTTGC-3' ; CD14 5 ' -CTGATCTCAGCCCTCTGTCC-3 ' , 5 ' -CAGGAGGATGCAAATGTTCC-3 ' ; G A P D H 5 ' -AGAACATCATCCCTGCATCC-3 ' , 5 ' -CTGGGATGGAAATTGTGAGG-3 ' . Antisense cDNA probes were prepared by PCR using 50 ng of the appropriate PCR product template, the 3' oligo, and modified nucleotides to facilitate repeated stripping of blots (Strip-EZ PCR, Ambion). These single-stranded PCR products were column purified (Qiagen, Mississauga, ON) and labeled with biotin using psoralen-biotin (Ambion) and cross-linking with 38 365 nm ultraviolet light. Northern blots were performed with the NorthernMax-Gly kit (Ambion) which uses glyoxal/dimethylsulfoxide to denature the R N A as an alternative to formaldehyde. R N A was transferred to a positively-charged membrane (Ambion) and crosslinked with long-wave ultraviolet light and baked at 80° C for 30 min. Labeled probe (3 ng in 10 ml UltraHyb or ZipHyb, Ambion) was used for hybridization at 71°C. The BrightStar nonisotopic detection kit (Ambion) was used for probe detection according to the manufacturer's protocols. Northern blots were analyzed using an Alphalmager system (Alpha Innotech Co, San Leandro, CA). Cytokine Assays. The concentration of TNF-a , IL-1B, and M l P - l a in culture supernatents from R A W 264.7 cells was determined by ELISA (R&D Systems, Minneapolis, M N , USA). 2.5 Establishment of array hybridization conditions. Gene array technology was used to examine differential gene expression in the R A W 264.7 murine macrophage cell line following S. Typhimurium infection. The arrays chosen for this study contained 588 murine cDNAs encoding proteins with a wide range of functions and included several gene families whose role during macrophage responses to infection have not been characterized. Cells were infected with S. Typhimurium SL1344 for 10 min, after which time cells were washed and treated with gentamicin to kil l any remaining extracellular bacteria and prevent re-infection. The short invasion time permitted a synchronous wave of bacterial invasion to induce a coordinated change in gene expression that could be measured 4 h post-infection. Total R N A was isolated from R A W 264.7 cells that were unstimulated or stimulated with virulent S. Typhimurium or 100 ng/ml purified S. Typhimurium LPS. Figure 2.1 shows images of identical arrays hybridized with 32P-labeled cDNA probes prepared from R A W 264.7 39 macrophages that were either left unstimulated, infected with S. Typhimurium, or stimulated with purified S. Typhimurium LPS. To permit comparison between multiple array experiments, the data sets were normalized to each other using the average expression level of 5 genes. Table 2.1 compares the hybridization intensities of these 5 genes and shows that their expression levels under different experimental conditions deviated by not more than 0.7-1.4 fold, indicating valid data normalization. To determine the reproducibility of the gene arrays, we compared the hybridization intensities of 2 identical array membranes hybridized with probes synthesized from 2 separate R N A preparations of unstimulated R A W 264.7 cells. Less than 5% of genes expressed by unstimulated cells varied by more than 2-fold between the two hybridization experiments (data not shown). 2.6 Effect of S.Typhimurium Infection on RAW 264.7 Macrophage Gene Expression. Our application of gene array technology provided a cross-section of the diversity of genes whose expression is altered at a given time point after S. Typhimurium infection. Due to the extensive amount of data accumulated from the gene array experiments, the data sets for all 588 genes are provided on our web pages (http://www.cmdr.ubc.ca/S,a/OTong//flarrav) and in Appendix A . At 4 h post-infection with S. Typhimurium, the expression levels for 40 of the 588 genes represented on the array were altered in R A W 264.7 macrophages by 4-fold or greater from their uninfected level (Figure 2.2). When a cut-off of 2-fold induction or inhibition was applied to the data, 77 genes showed changes in expression. Figure 2.2 shows the mean hybridization intensity values for genes, encoding a broad spectrum of proteins, that were induced by more than 4-fold upon S. Typhimurium infection. Many of these upregulated genes encode effectors with well-characterized proinflammatory or direct antimicrobial properties. For 40 A. Figure 2.1 Differential gene expression by macrophages upon 5. Typhimurium infection or L P S stimulation as measured by gene arrays. R A W 264.7 cells were (A) unstimulated, (B) infected with S. Typhimurium, or (C) stimulated with 100 ng/ml S. Typhimurium LPS. Total R N A was isolated after 4 h and used to prepare a 32P-labeled first strand cDNA probe using reverse transcriptase and pooled primers specific for the 588 genes arrayed on the membranes. Probes were hybridized to gene arrays containing duplicate spots of partial cDNAs representing a wide range of genes and the hybridization intensities were collected using a phosphoimager. The two pairs of cDNA spots identified by boxes correspond to MIP-1 a and p\ The five circled pairs of cDNA spots identify the genes used for data normalization: ubiquitin, G A P D H , (3-actin, Cab45 calcium binding protein, and ribosomal protein S29 (left to right). These data are representative of n=3 (infected or LPS-stimulated) and n=2 (unstimulated). 41 Average intensity for duplicate array spots Ratio relative to unstimulated cells Unstimulated S. Typhimurium LPS S. Typhimurium LPS Gene Mean Range Mean SD Mean SD ubiquitin 15698 683 14718 3098 15970 3027 1.2 0.8 0.9 1.0 0.8 1.2 GAPDH 5102 893 5264 867 5162 956 0.9 1.2 1.0 0.9 1.2 0.9 beta-actin 9732 848 12580 1378 11874 '714 1.2 1.2 1.4 1.2 1.2 1.3 Cab45 1446 11 1317 60 1133 62 0.9 0.9 1.0 0.8 0.8 0.7 ribosomal S29 12582 109 11272 572 11377 532 0.9 0.9 0.9 0.9 0.9 0.9 Table 2.1 Hybridization intensities of genes used for data normalization. The average hybridization signals for duplicate cDNA spots of ubiquitin, G A P D H , p-actin, Cab45 calcium binding protein, and ribosomal protein S29 were calculated and corrected for background. The mean hybridization intensity and the associated range (for unstimulated cells, n=2) or SD (S. Typhimurium-infected or LPS-stimulated, n=3) are shown as well as the ratio for each gene relative to unstimulated cells. The values for these five genes were normalized to each other to account for differences in probe labeling efficiency between experiments. Table 2.1 contains the mean hybridization intensities of these five genes after normalization for the 8 hybridization experiments summarized in Fig. 2.2 and Fig. 2.3. The appropriate normalization coefficient was then used to normalize the entire data sets in order to make possible direct comparison between them. 42 example, iNOS, the enzyme responsible for producing the potent antibacterial molecule nitric oxide, was strongly induced upon S. Typhimurium infection (38). Highly elevated expression levels were also observed for the chemokines MlP-lct , MIP-lp\ (39) and MIP-2ct (40) which selectively recruit other effector cells to infection sites (41). The expression of IL-1(3, which contributes to the proinflammatory and acute phase responses, was also upregulated (42). S. Typhimurium infection also elevated the expression of receptors that allow macrophages to communicate with other cells of the immune system. Expression of the gene encoding the receptor for the pro-inflammatory cytokine tumor necrosis factor (TNF)-ct was upregulated, as was CD40. CD40 binds to a ligand on T lymphocytes and this interaction induces the production of many inflammatory mediators, primes T cells (43), and augments survival of mice infected with Salmonella dublin (44). A subset of the induced genes shown in Figure 2.2 may serve to control or inhibit the inflammatory response. Tristetraprolin was highly induced upon S. Typhimurium infection and can decrease TNF -a synthesis by decreasing mRNA stability (45). Elevated transcription of the I -KBa and I - K B | 3 inhibitory subunits of N F - K B was also observed and these proteins are known to downregulate the transcriptional program initiated by the translocation of N F - K B to the nucleus (46). Elevated expression of the anti-inflammatory cytokines tumor growth factor (TGF)P-l and 2 was also observed. TGF|3 can have potent effects on macrophage activities and administration of recombinant TGF|3 has been shown to protect mice from a lethal dose of S. Typhimurium (47). Elevated mRNA levels for signaling molecules that are involved in cell death or the response to IFN-y were also observed. These include the apoptosis-associated genes ICE protease (caspase 1), TNF receptor 1, Fas, TDAG51, and TRAIL, and the IFN-y-induced interferon regulatory factor 1. Some of the 5". Typhimurium-upregulated genes also encode proteins involved in macrophage migration. For example, I C A M -1 is required for vascular extravasation during migration to sites of infection, and urokinase 43 Figure 2.2 RAW 264.7 gene expression induced by S. Typhimurium and LPS. Gene arrays were hybridized using cDNA probes prepared from unstimulated R A W 264.7 cells or from cells 4 h after S. Typhimurium infection or S. Typhimurium LPS stimulation. A. List of genes with mRNA levels elevated by at least 4-fold. The mean hybridization signal for each gene was calculated from 2 to 3 data sets obtained from hybridization experiments using probes prepared from independent batches of R N A . The fold increase in hybridization signal upon S. Typhimurium infection or LPS stimulation was calculated relative to the value for unstimulated cells. B. Graphical representation. Graphs of the mean hybridization signals for a subset of induced genes in unstimulated cells ( • ) and following bacterial infection ( • ) or LPS stimulation ( fl). Error bars represent the standard deviation from the mean of three intensity values for infected and LPS stimulated cells and the range of two intensity values for unstimulated cells. Due to the extensive amount of data accumulated from the gene array experiments, we have made the complete data sets for all 588 genes available in Appendix A and on our web pages fhttp://www.cmdr.ubc.ca/5,Q//wong//aarrayy Accession Grid Hybridization Intensity Fold Induction Protein/Gene Number Position Unstimulated S. typhimurium LPS 5. typhimurium LPS X06381 F3d 20 1512 1394 76 70 LIF M57422 B4k 20 1475 1135 74 57 tristetraprolin (TTP) M20157 D2i 20 1372 1446 . 69 72 Egr-1 L28095 F7a 20 1219 860 61 43 ICE M83312 E l f 20 1128 1419 56 71 CD 40 M83649 C3f 20 965 1388 48 69 Fas 1 receptor M35590 F3f 188 8963 8865 48 47 " iVTTP 1 .beta M15131 . F4k 20 823 1491 41 75 IL-1 beta M87039 C3m 20 698 646 35 32 iNOS X53798 F3g 20 697 802 35 40 MTP 2 alpha X14432 F4d 20 516 386 26 19 thrombomodulin X72307 F2e 20 498 140 25 7.0 HGF X72711 C5e 20 448 636 22 32 replication factor C L38847 F2f 20 420 137 21 6.9 HTK ligand X99063 B7n 20 419 314 21 16 Zyxin X12531 F3e 489 10124 9147 21 19 VHP 1 alpha U01036 D2d 20 367 423 18 21 NF-E2 X57413 F4g 20 348 420 17 21 TGF beta 2 U03856 E6f 20 344 236 17 •12 CD45-AP X65453 C2n 20 340 279 17 14 CD40 ligand X53779 E3j 20 333 279 17 14 androgen receptor X56848 F i d 20 309 178 15 8.9 BMP 4 M23384 B2e 20 308 376 15 19 Glucose transporter 1 U44088 C5a 20 302 274 15 14 TDAG51 L36435 Die 20 288 406 14 20 b-ZIP (kr) X07414 C6d 20 272 307 14 15 ERCC-1 X52264 E7i 20 258 363 13 18 ICAM-1 X15842 A2m 20 256 395 13 20 c-rel M59378 C5d 580 5315 5566 9.2 9.6 TNF receptor 1 M21065 B7k 120 961 958 8.0 8.0 IRF1 X62700 B3i 121 776 1045 6.4 8.6 uPARl U19799 B3n 143 575 723 4.0 5.1 I-kappa B beta U37522 C5c 151 596 908 3.9 6.0 TRAIL U36760 D l f 20 77 444 3.9 22 BF-1 B. ure 2.2 R A W 264.7 gene expression induced by S. Typhimurium and LPS . 45 receptor participates in extracellular matrix remodeling (48). Dystroglycan 1 promotes extracellular matrix formation, and its transcriptional down-regulation (Figure 2.3) may cooperate with the upregulated genes encoding various proteases to remodel the extracellular matrix and promote tissue infiltration by macrophages (49, 50). The pattern of altered gene expression caused by S. Typhimurium infection is reminiscent of the anti-proliferative and pro-differentiating transcriptional program that occurs during myeloid development (53). A number of genes with well-characterized roles in macrophage differentiation were upregulated by S. Typhimurium infection (Figure 2.2). For example, leukemia inhibitory factor (LIF) was upregulated. LIF is secreted by macrophages in response to LPS and promotes myeloid differentiation (51). A number of transcription factors were also regulated by S. Typhimurium infection. Expression of Egr-1, NF-E2, IRF-1, and c-rel was upreguated while expression of Ski, B-myb, Fli-1, and c-Fes was down-regulated by more than 2-fold (Figure 2.3). Egr-1 controls both monocyte development and appears necessary for maintenance of macrophage differentiation, as the expression of many cytokines and receptors important during infection are regulated by egr-1 activity (52). B-myb is a negative regulator of macrophage terminal differentiation and its down-regulation by bacterial products promotes macrophage development. These transcription factors all regulate macrophage differentiation and their coordinated expression in response to bacterial products may serve to promote development of the macrophage's antibacterial abilities (53, 54). Expression of these transcription factors during macrophage maturation is usually coupled with an inhibition of cell proliferation. The expression level of many genes controlling cell cycle Gi to S phase transition were downregulated. Modest decreases in the mRNA levels of cyclin D l and its partner cyclin dependent kinase (cdk) 4 were measured. This kinase complex phosphorylates the retinoblastoma gene product, causing it to dissociate from the DP-1 :E2F heterodimer, which then translocates to the nucleus, and initiates cell cycle progression. 46 Figure 2.3 RAW 264.7 gene expression inhibited by S. Typhimurium and LPS . A. Hybridization intensities. List of the mean hybridization intensity values for R A W 264.7 macrophage mRNA levels that were repressed by at least 2-fold after S. Typhimurium infection or LPS stimulation for 4 h. The average hybridization intensities were calculated from two to three independent data sets obtained from hybridization experiments using probes prepared from independent batches of RNA. B. Graphical representation. Graphs of the mean hybridization signals and standard deviation for a subset of repressed genes in unstimulated cells ( • ) and following bacterial infection ( • ) or LPS stimulation (0 ). Error bars represent the standard deviation from the mean of three intensity values for infected and LPS stimulated cells and the range of two intensity values for unstimulated cells. Due to the extensive amount of data accumulated from the gene array experiments, we have made the data sets for all 588 genes available in Appendix A and on our web pages (http://www.cmdr.ubc.ca/5a/moA7e//aarrav). 47 Accession Grid Hybridization Intensity Fold Inhibition Protein/Gene Number Position Unstimulated S. typhimurium LPS S. typhimurium LPS X75888 A6i 388 89 85 4.4 4.6 cyclin E L13968 D7k 509 272 171 1.9 3.0 Y Y 1 Y00864 A4c 501 149 173 3.4 2.9 c-Kit D30743 A7h 349 61 121 5.7 2.9 Weel U43512 E6m 794 233 298 3.4 2.7 dystroglycan 1 X59421 A3b 798 377 327 2.1 2.4 Fli-1 U14173 A4g 725 211 304 3.4 2.4 Ski D17384 C51 349 115 149 3.0 2.3 D N A pol alpha X70472 A 2 f 614 207 277 3.0 2.2 B-myb X02389 F7f 194 192 89 1.0 2.2 uPA Z47766 A6j 391 132 181 3.0 2.2 cyclin F D83698 C4b 651 425 319 1.5 2.0 death protein-5 U58533 D2m 323 61 161 5.3 2.0 Erf L34169 F4e 393 707 197 0.6 2.0 thrombopoietin X53068 C7b 343 203 175 1.7 2.0 P C N A U24160 B7i 430 171 229 2.5 1.9 Dvl2 XI2616 A41 569 278 305 2.0 1.9 c-Fes M83336 B3c 459 241 255 1.9 1.8 IL-6 receptor beta X64361 B7f 584 253 331 2.3 1.8 Vav X68932 A4b 4455 2225 2531 2.0 1.8 c-Fms X03919 A3h 2225 1478 1367 1.5 1.6 N-myc V00727 A2h 930 399 590 2.3 1.6 c-Fos S78355 A 6 f 1489 921 955 1.6 1.6 cyclin D l X72310 D2g 1709 1093 1153 1.6 1.5 DP-1 B. Dystroglycan 1 Erf B-myb Cyclin E DP-1 Figure 2.3 R A W 264.7 gene expression repressed by 5. Typhimurium and LPS . 48 The array results also revealed down-regulation of DRTF polypeptide-1 (DP-1) and cyclin E, as well as upregulated expression of various retinoblastoma-related genes (data not shown), all known to block entry into S phase (55). 2.7 Effect of IFN-y Activation on Gene Expression by Infected Macrophages. IFN-y primes macrophages for enhanced microbicidal responses to bacterial infection. The established importance of IFN-y production during S. Typhimurium infection invites a molecular examination of how the macrophage's gene expression profile following S. Typhimurium infection is affected by prior IFN-y activation. To this end, gene arrays were hybridized with cDNA probes prepared from uninfected and S. Typhimurium-infected R A W 264.7 macrophages, with or without prior IFN-y activation. Table 2.2 presents genes that were differentially expressed by IFN-y activated and unactivated macrophages 4 h after S. Typhimurium infection. We found that IFN-y treatment altered the expression of a number of genes and importantly, that it modulated the ability of S. Typhimurium to alter R A W 264.7 macrophage gene expression. IFN-y often upregulated gene expression in uninfected cells, such as BST-1, MIG monokine, and M l P - l a . For some genes, this expression level was further enhanced by S. Typhimurium infection. Examples include iNOS, I - K B ( 3 , N F - K B p65, JunB, JunD, TDAG51, tristetraprolin, and TNF-a . For other genes, such as MIG, IFN-y upregulated their expression but bacterial products did not significantly increase expression levels above the IFN-y-stimulated level. Prior IFN-y stimulation resulted in gene expression upon infection, such as the transcription factors Cdx2 and Brn3.2, which was not observed at the same time point in infected cells not primed by IFN-y. For other genes, IFN-y treatment upregulated mRNA levels in uninfected cells which was repressed following S. Typhimurium infection. The interferon 49 inducible protein 1 is an example of this pattern of gene expression that may provide negative feedback. The most striking trend was an increase in the steady state mRNA levels encoding transcription factors such as tristetraprolin, three members of the Jun family (Jun-B, Jun-D, and c-Jun), Fos B , 1 - K B O . and I - K B ( 3 , C-EBP, Stat 5a, and elk-1. Of note was an induction in the expression of the homeobox (Hox) family transcription factors. Expression of the Hox-4.2, caudal type homeobox 2, and Brn 3.2 P O U transcription factors was upregulated by S. Typhimurium infection of IFN-y-treated macrophages to a greater extent than in unprimed macrophages. Homeobox genes play critical roles during development and the homeobox genes Hox-B3, Hox-B4, and Hox-B7 have been implicated in orchestrating various stages of myeloid differentiation (53, 56). This is the first data, to our knowledge, suggesting that other homeobox genes may play a role in macrophage responses stimulated by bacterial products. 2.8 Contribution of LPS Signaling to S. Typhimurium-induced Changes in Gene Expression. LPS is a potent inducer of macrophage inflammatory functions (13, 17). Since S. Typhimurium is a Gram-negative bacteria with an outer membrane rich in LPS, our hypothesis was that many of the effects of S. Typhimurium on macrophage gene expression are due to its LPS. Gene arrays were used to identify the relative contribution of the bacterial component, LPS, to the overall pattern of macrophage gene expression observed during S. Typhimurium infection. This analysis revealed that the gene expression profiles overlapped considerably (Figures 2.2 and 2.3). In most cases, 100 ng/ml LPS caused equivalent or greater increases in steady-state mRNA levels than S. Typhimurium infection. The 100 ng/ml dose of purified LPS used was probably greater than the amount of LPS encountered by macrophages during a 10 min 50 Hybridization Intensity Ratio Accession Grid -IFN +IFN Uninfected Infected Number Position Uninfected Infected Uninfected Infected +IFN/-IFN +IFN/-IFN Protein/gene X12531 F3e 489 10124 3637 10454 7.4 1.0 MIP-1 alpha M57422 B4k 20 1475 1262 3699 63 2.5 tristetraprolin U19799 B3n 143 575 1622 3155 11 5.5 I-kappa B beta U44088 C5a 20 302 970 2410 49 8.0 TDAG51 M34815 F l m 20 56 2374 1885 119 33 MIG U09419 D6g 20 167 1394 1804 70 11 RIP 15 M87039 C3m 20 698 733 1705 37 2.4 iNOS J05205 A3g 20 231 621 1362 31 5.9 jun-D D31788 B2h 20 20 1598 1219 80 61 BST-1 M61909 B4a 20 20 659 1125 33 56 NF-kappa B p65 J03236 A3f 20 171 273 1055 14 6.2 Jun-B X57796 C5b 121 265 654 1049 5.4 4.0 TNF 55 M60778 B3e 20 107 786 1002 39 9.3 LFA1-alpha D17571 C4a 183 167 392 967 2.1 5.8 NADPH-cytochrome P450 X52264 E7i 20 258 537 808 27 3.1 ICAM-1 M86671 F4n 20 167 641 741 32 4.4 IL-12(p40) beta chain X67083 C3a 20 25 245 702 12 28 Chop10 J03770 D4e 20 166 20 599 1.0 3.6 Hox-4.2 S69336 B3b 223 240 399 568 1.8 2.4 IFN-gamma Receptor 2 M37897 F41 170 • 323 431 546 2.5 1.7 IL-10 U19119 D4k 272 1141 876 534 3.2 0.5 IFN inducible protein 1 M20157 D2i 20 1372 230 495 11 0.4 Egr-1 S68377 D l h 20 59 20 465 1.0 7.8 Brn-3.2 M26391 A i m 20 106 267 444 13 4.2 Rb; ppl05 X87257 A3a 123 176 302 433 2.5 2.5 Elk-1 X61800 D l k 20 57 21 425 1.1 7.5 C / E B P S74520 D i m 20 21 20 367 1.0 18 Cdx2 X72310 D2g 1709 1093 534 340 0.3 0.3 DP-1 U17698 D l a 20 215 71 338 3.5 1.6 ablphilin-1 L12120 E3a 20 106 117 323 5.9 3.1 IL-10 receptor X14897 A3c 20 77 263 312 13 4.1 Fos-B J04103 D3b 20 75 106 ' 278 5.3 3.7 Ets-2 M37163 D l l 20 29 20 267 1.0 9.1 Cdxl Table 2.2 Effect of IFN-y priming on RAW 264.7 macrophage gene expression. List of genes differentially expressed due to prior activation with IFN-y by R A W 264.7 macrophages 4 h following S. Typhimurium infection. The mean hybridization intensities were calculated from two array hybridization experiments using R N A samples from IFN-y-activated R A W 264.7 cells and compared to the hybridization intensities obtained from cells not primed with IFN-y. Ratios of gene expression for uninfected and infected cells were calculated by dividing the hybridization intensity for IFN-y primed cells by the intensity for unprimed cells. The complete data set is available in Appendix A , Table A.2. 51 invasion by S. Typhimurium, but due to the chemical nature of LPS, it is not possible to accurately quantify the amount of LPS present during Salmonella infection. This high dose was used to maximize LPS-dependent responses and effect expression changes in genes that have a higher threshold for responding to LPS. Therefore, of special interest are genes, such as tristetraprolin, that this semi-quantitative technique suggests are preferentially induced by Salmonella invasion in comparison to LPS stimulation. 2.9 Confirmation of Array Data using Northern Blots and ELISAs. Despite its reproducibility, gene array analysis is only semi-quantitative. Therefore, northern blots were used to confirm and more accurately measure the regulation of genes identified in our gene array analysis to be regulated by S. Typhimurium infection or LPS stimulation. mRNA levels for both CD 14, a receptor for LPS, and IL-1(3, a pro-inflammatory cytokine, were upregulated while cyclin D l levels were decreased in R A W 264.7 cells by S. Typhimurium and purified LPS from northern blot analysis, confirming previously published data (data not shown). TLR4, which is required for macrophage response to LPS, was not included on the array and therefore its expression was not examined in parallel with CD 14. Northern blots were also used to confirm the induction or repression of candidate genes identified using array technology where there was little precedence in the literature. We analyzed mRNA levels of DP-1 and tristetraprolin relative to G A P D H in R A W 264.7 macrophages at 1 h, 4 h, and 6 h following S. Typhimurium infection or LPS stimulation. DP-1 binds to members of the E2F gene family to form a heterodimeric transcription factor that can regulate cell cycle progression (57, 58). Expression of DP-1 is necessary for progression from G l to S phase, as shown by studies with dominant negative mutants (59). To date, two DP genes 52 and five E2F genes have been identified, and heterodimer subunit composition determines specificity for different E2F D N A binding sites (60). Regulated expression of DP-1 may therefore coordinate expression of a subset of genes involved in entry into S phase. According to the two array hybridization results, both S. Typhimurium and LPS stimulation decreased DP-1 expression by 40% in unprimed macrophages. We confirmed this data by northern blot analysis, in that DP-1 expression decreased at 6 h following infection or LPS stimulation (Figure 2.4a). To our knowledge, this is the first report of repressed DP-1 mRNA levels in a macrophage-like cell line during bacterial infection. A n important finding is that a decrease in macrophage gene expression as small as 40% can be detected by array hybridization and confirmed and quantified by northern blot analysis. The expression of tristetraprolin was greatly upregulated by both Salmonella infection and LPS, according to the array data sets. Tristetraprolin, encoded by the gene zfp-36, has been hypothesized to be a transcription factor due to its zinc finger motif and its ability to translocate to the nucleus (61). Tristetraprolin regulates mRNA stability as studies with knockout mice show that tristetraprolin lowers TNF-a protein levels by binding to the AU-rich elements in T N F - a mRNA and destabilizing it.(62). Tristetraprolin is encoded by an early response gene that is rapidly induced by mitogens (63) and LPS (45). In northern blot experiments, we found that expression of tristetraprolin was increased as early as 1 h post-stimulation by virulent S. Typhimurium or by LPS (data not shown) and then decreased to a lower level at 4 h and 6 h (Figure 2.4b). The apparent increase in tristetraprolin mRNA levels was smaller when quantified by northern blot analysis compared to the array data, suggesting that the array technique accurately detects trends in altered gene expression but can overestimate ratios. This could be explained by the inability of the semi-quantitative array technique to accurately quantify low levels of gene expression, for example in unstimulated cells. Quantification of the northern 53 1 5 A. DP-1 B. Tristetraprolin C. GAPDH 4h 6h AH W,«*i JHI #40 <Mt§ u s LPS U S LPS 4h 6h . U S LPS U S LPS 4h 6h mi* <,,,** u s LPS u S LPS 0.5 < 2 4 h; Hours 6 h 4 h Hours 6 h Figure 2.4 Confirmation and quantification of genes differentially expressed upon S. Typhimurium infection and LPS stimulation using northern blots. R A W 264.7 cells were infected with S. Typhimurium at an MOI of 20:1 or stimulated with 100 ng/ml 5. Typhimurium LPS and compared to unstimulated cells. Total RNA was isolated from macrophages after 4 h and 6 h. R N A was separated by denaturing gel electrophoresis, immobilized on a positively-charged membrane, and probed sequentially with biotinylated single-stranded cDNA probes specific for (A) DP-1, (B) tristetraprolin, and (C) GAPDH. The hybridization intensities were quantified using a densitometer and normalized to G A P D H expression. Graphs depict the mean fold change ± SD (or range for n=2) subsequent to bacterial infection (Q ) or LPS stimulation 0 ) relative to unstimulated cells (• ) at each time point for the northern blot shown. Tristetraprolin: 4 h, n=5; 6 h, n=2. DP-1: 4 h, n=3; 6 h, n=2. These data confirm results from three separate array hybridizations. 54 blotting results revealed that cells infected by 5*. Typhimurium exhibited a higher level of tristetraprolin mRNA compared to cells stimulated by 100 ng/ml LPS. This confirmed the array data which suggested that infection by 1-3 bacteria per macrophage induced a 30% higher level of tristetraprolin mRNA than following stimulation by LPS. To confirm that changes in mRNA levels detected by the array hybridizations translated into similar changes in protein abundance for a subset of genes, growth media was collected from the cells used for R N A isolation and tested for proinflammatory cytokine levels by ELISA. Candidates were selected based on our criteria for significance (hybridization intensity >300 and 4-fold induction or repression of expression). In culture supernatants from cells infected with S. Typhimurium or stimulated with LPS, levels of M l P - l a (both conditions resulted in 6.3-8.8 ng/ml) and TNF-a (infection: 1.3-2.0 ng/ml, LPS: 2.8-3.4 ng/ml) were elevated at 4 h, while levels of interleukin 1(3 were elevated at 24 h (0.3-0.5 ng/ml) when compared to unstimulated cells. For each ELISA, pro-inflammatory cytokine concentrations in culture supernatants of cells stimulated by S. Typhimurium or LPS were similar, supporting our array data. By array analysis, iNOS expression was induced by S. Typhimurium infection and LPS stimulation. Elevated levels of nitrate in the culture supernatants were detected at 24 h (data not shown), indicating increased iNOS activity and confirming that elevated iNOS expression translated into increased nitric oxide production. 2.10 Discussion. Significant progress has been made towards understanding how pathogenic bacteria promote their survival within the host through the regulated expression of bacterial virulence genes. Much less is known about how the host responds to these pathogens in order to shape the 55 outcome of a potentially fatal liaison with pathogenic microbes. This is the first report to capitalize on gene array technology to profile how the expression of hundreds of macrophage genes are altered by a virulent bacterium. Gene array technology is a powerful tool that can be used to expand our current understanding of this relationship for a number of reasons. First, this technique permits one to study simultaneous changes in expression of a large number of genes under uniform experimental conditions, including infectious dose and cell passage number. While the selection of genes for inclusion on the array introduces some bias, the wide range of gene families allows rapid identification of genes previously not known to be involved in the host response to pathogens. In this study, we identified genes that have never been directly implicated in macrophage responses to S. Typhimurium infection and identified novel gene targets of LPS signaling. These include dystroglycan, which is involved in extracellular matrix formation, and DP-1, which regulates cell cycle progression. Second, gene arrays permit comparison of expression profiles obtained from multiple stages of infection, from stimulation with purified microbial products, or from infection with bacterial virulence factor mutants. Our comparison of macrophage gene expression altered by bacterial infection to stimulation with purified LPS suggests that LPS serves a principal role in altering host gene expression during S. Typhimurium infection. Third, gene arrays measure changes in individual genes in the context of how the expression of other members of the gene family, their receptors, ligands, or transcriptional activators are altered. This allows a more comprehensive understanding of host responses to bacterial infection by identifying patterns of gene expression that would not be evident from studying each gene in isolation. Indeed, this approach enabled us to detect the induction of families of transcription factors in IFN-y-activated macrophages following S. Typhimurium infection. 56 We were able to identify novel macrophage gene targets of IFN-y activation or S. Typhimurium infection by looking at fewer than 600 genes. The genes presented in this study likely underestimate the total number of affected genes due to limitations of accurately quantifying very low levels of gene expression. This suggests that gene array filters (used in this study) can complement the use of gene chip technology (capable of analyzing the expression of thousands of genes) since different cross-sections of the genome can be studied in each case. The use of commercially-available filter-based gene arrays is an accessible approach to generate testable hypotheses of how hosts respond to pathogens. These arrays have the advantage of containing characterized genes for which reagents such as antibodies, mutant cell lines, and knock-out mice may be available for hypothesis testing. A n even more comprehensive view of host response could be obtained by extending this approach to using gene microarrays incorporating thousands of genes. For this to be successful, improved bioinformatics resources are needed as well as a conceptual shift in the way we analyze and publish large amounts of data. The findings of many studies similarly rest on our assumption that changes in steady state mRNA levels often correlate with meaningful changes in protein levels. While increased protein levels have been measured for some of the genes found to be differentially expressed in this study, others are bound to be regulated at the level of protein synthesis, post-translational modification, or intracellular localization. This also highlights the need for high-throughput strategies to confirm changes in genes of interest at the level of transcription, translation, and protein localization in order to pursue the biological relevance of array data. Our gene array results suggest that the macrophage's transcriptional program undergoes a massive overhaul during bacterial infection and highlight the myriad of ways in which macrophages attempt to control and clear Salmonella infection. The majority of differentially expressed genes were upregulated upon S. Typhimurium infection, and several of these are 57 known to play well characterized roles during bacterial infection. In general, we observed a strong proinflammatory response which may be tempered by upregulated expression of TGF-|3, IL-10, and tristetraprolin, all of which have demonstrated anti-inflammatory properties. This suggests that there may be a balance between pro-inflammatory responses and negative feedback regulation during S. Typhimurium infection (42). Stimulation by LPS enhances the macrophage's ability to interact with other cells through the coordinated expression of various receptors, such as CD40 and ICAM-1 (44). Extracellular matrix remodeling, through alterations in the expression of various proteases, protease inhibitors, and dystroglycan may promote macrophage entry into infected tissues (48). Differentially expressed genes identified using the arrays were not limited to genes with characterized proinflammatory or antibacterial properties, since 5*. Typhimurium had numerous effects on the cell cycle regulator and transcription factor gene families within macrophages. With myeloid cells, LPS has anti-mitotic effects by downregulating the expression of cyclins and cyclin-dependent kinases and by influencing levels of positive and negative transcriptional activators (55). Northern blots for cyclin D l and the transcription factor DP-1 revealed that the expression of both are decreased to an equivalent extent by LPS and S. Typhimurium. This suggests that Salmonella infection may affect the cell cycle via LPS signaling. Our data supports a re-prioritizing of host gene expression away from normal physiology towards establishing an antibacterial state. While S. Typhimurium initially invade naive unactivated murine macrophages in vivo, macrophages are more likely to be stimulated by IFN-y during later stages of S. Typhimurium infection (7). IFN-y-activated macrophages display enhanced microbicidal activities upon bacterial infection, due to changes in the expression of genes such as iNOS and MIP chemokines (64). However, the spectrum of host responses affected by IFN-y priming is not fully understood at the molecular level. We analyzed the expression patterns of hundreds of genes to gain a more 5 8 comprehensive understanding of how priming by I F N - y alters macrophage gene expression, and hence responses, to S. Typhimurium infection. We identified a variety of gene expression patterns in IFN-y-primed R A W 2 6 4 . 7 macrophages, which included upregulated gene expression in uninfected cells, synergistic effects between I F N - y and S. Typhimurium infection, and elevated expression of genes following infection of IFN-y-primed cells that was not seen following infection of unprimed cells. I F N - y signaling has been shown to increase the amount of N F - K B in the macrophage cytoplasm that, upon L P S stimulation, translocates to the nucleus more rapidly and effectively than without prior priming by I F N - y ( 6 4 , 6 5 ) . This model of priming by I F N - y may explain the differential response to S. Typhimurium mediated by I F N - y , by altering the kinetics of gene activation, so that genes are elevated at our 4 h experimental window. Alternatively, I F N - y may supply a necessary first signal so that a second stimulus provided by the bacteria triggers gene expression which is not possible in unactivated cells. Either mechanism could make IFN-y-primed macrophages more sensitive to stimulation by bacterial products and permit a more rapid and effective antimicrobial response against invading S. Typhimurium. To our knowledge, this is the first report of the application of gene arrays to the study of macrophage biology by profiling how R A W 2 6 4 . 7 macrophages respond to various stimuli, such as I F N - y and L P S . While unprimed R A W 2 6 4 . 7 cells continue to undergo cell division, resident tissue macrophages exhibit a limited capacity for division under normal conditions. Maturation of myeloid cells into terminally differentiated macrophages involves an arrest in proliferation and the differential expression of many transcription factors ( 5 4 ) , some of which were identified using the arrays. Both L P S and I F N - y exert anti-mitotic effects while promoting development of the antimicrobial properties of myeloid cells. Many of the cell cycle regulatory and transcription factor genes expressed by R A W 2 6 4 . 7 cells in response to L P S stimulation have previously been 59 reported using primary macrophages (18, 45, 46, 53, 66-70). This suggests that R A W 264.7 cells may provide an adequate model for identifying genes involved in macrophage responses to infection, which can then be further characterized using primary macrophages. The most striking class of gene induction in IFN-y activated cells 4 h after S. Typhimurium infection was a group of more than 15 transcription factors. In infected unactivated cells, many of these transcriptional activators, namely of the homeodomain class, were not induced above our detection level. Homeobox transcription factors play crucial roles during developmental patterning (71). A previous report has connected the processes of developmental patterning and macrophage differentiation by implicating the expression of the homeobox transcription factor Hox-2.4 (Hox-B8) in the terminal differentiation of a hematopoietic cell line along the macrophage lineage (56). This differentiation required expression of Egr-1, that was upregulated upon infection of IFN-y activated R A W 264.7 macrophages in this study. Since IFN-y activation results in differentiation of monocytes into macrophages, it is possible that expression of homeobox transcription factors upon infection of R A W 264.7 macrophages, identified in this study, may promote further maturation of the cell's antibacterial phenotype. Alternatively, these transcription factors may serve an as yet uncharacterized role during macrophage response to S. Typhimurium infection We hypothesized that LPS, a structural component of all Gram-negative bacteria and the most well-characterized modulin, should play a principal role in stimulating the early innate response of macrophages to bacterial infection. To test this hypothesis, we compared changes in host gene expression caused by virulent S. Typhimurium and purified & Typhimurium LPS to investigate the relative contribution of this virulence factor. LPS exerts its effects through its lipid A moiety, which is buried in the cell wall of live bacteria. During our infection model, cells would be stimulated by the lipid A of LPS shed by live bacteria, extracellular bacteria killed by 60 antibiotics, or intracellular bacteria killed by macrophages. There was a remarkable degree of overlap between genes induced by virulent S. Typhimurium and purified S. Typhimurium LPS. The 100 ng/ml dose of LPS was likely much higher than the amount of free LPS that stimulated the cells during infection and caused equivalent or higher alterations in gene expression when compared to bacterial infection. The overlap in the macrophage expression data following stimulation with virulent S. Typhimurium or purified S. Typhimurium LPS suggests that there is redundancy in host response to bacteria. Gene expression regulated by LPS stimulation has also been shown to be altered by other bacterial components. The ability of both 5*. Typhimurium LPS and flagellar proteins to trigger TNF-a and IL-16 release by macrophages (20, 22) supports the concept that different bacterial inputs can initiate a conserved program of macrophage responses. The remarkable overlap in macrophage gene expression induced by S. Typhimurium or purified S. Typhimurium LPS suggests that Salmonella specifically affects a relatively small subset of macrophage processes to secure their survival rather than completely dampening the inflammatory response. A number of host proteins and signaling cascades have been identified that are modified by specific bacterial virulence effectors. For example, the S. Typhimurium virulence factor SopE upregulates IL-8 production by epithelial cells (25) and SipB binds and activates caspase 1 (ICE) protease to promote macrophage apoptosis (24). The majority of these studies have used epithelial cells and have measured how S. Typhimurium invasion and virulence factor expression specifically alter host protein abundance or activity. Our results in macrophages, at the level of altered gene expression, invites a comparative study in epithelial cells to identify similarities and differences in gene expression profiles between these two infection models. Appendix D compares gene array studies of host cell responses to various bacterial pathogens and reveals conserved gene expression changes. Since S. Typhimurium 61 resides within macrophages to cause systemic disease, bacterial factors independent of LPS likely specifically modulate macrophage phenotype at the levels of gene expression, protein abundance, and protein activity in order to secure this intracellular niche. We identified some genes induced to a higher extent by S. Typhimurium infection compared to LPS stimulation and have confirmed this higher level of expression for tristetraprolin. While the differential increase in expression was small, it may be significant that another bacterial factor can produce a higher induction in gene expression compared to a relatively large dose of LPS. This raises the intriguing possibility that another virulence factor upregulates tristetraprolin mRNA levels in macrophages. Our ability to confirm array data for differential tristetraprolin expression suggests that other differentially expressed genes identified by array hybridization may. be altered by additional bacterial virulence factors acting synergistically or antagonistically with the effects of LPS. Experiments using killed bacteria or macrophages from LPS-hyporesponsive mice will more accurately quantify the contribution of LPS-independent factors in altering host gene expression. Array technology is also ideally suited to the study of host gene expression in response to characterized Salmonella mutants to address the contribution of other specific bacterial virulence factors in modulating host gene expression. This application of array technology will provide insight into how pathogenic bacteria use some of their many virulence effectors to specifically alter host cell biology and secure their niche. Array technology is highly applicable to studying numerous host-pathogen interactions. Comparison of array data from host cells infected with a variety of pathogenic bacteria will likely reveal how specific virulence factors trigger a unique pattern of host gene expression in response to the particular pathogen. Comparison of these data sets with those obtained from LPS and other structural components will likely reveal an overall conserved host gene expression profile that serves as a common signature of infection. 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Our hypothesis is that macrophage gene expression is altered in response to S. Typhimurium SPI 2-secreted virulence factors. Since S. Typhimurium can only survive and replicate within macrophages i f the SPI 2-encoded type III secretion apparatus is intact, a reasonable assumption is that secreted virulence factors could alter macrophage function at the level of gene expression or macrophages could recognize these foreign proteins and alter their gene expression accordingly. Gene array hybridization will be used to compare gene expression in macrophages infected by wild-type S. Typhimurium to cells infected by various bacterial mutants deficient in secretion of SPI 2 effectors to analyze whether these secreted proteins alter macrophage gene expression. 3.2 Introduction. The experiments described in Chapter 2 showed that gene array hybridization can indeed be used to profile macrophage responses to bacterial infection. In addition, these data reveal that array technology is also well-suited for a hypothesis-driven approach, and can be used to assess the relative contributions of different host and bacterial factors during infection. A variety of signals are integrated before a macrophage alters its phenotype and responds to infection. While the data presented in Chapter 2 supports the ability of purified LPS to recapitulate the macrophage's early transcriptional responses to S. Typhimurium, other signals such as phagocytosis, active bacterial invasion, intracellular survival and replication, other modulins, and bacterial virulence factors could each alter macrophage gene expression in distinct ways. The availability of bacterial mutants that are highly similar to wild type bacteria but lack the expression of individual virulence genes provides a well-controlled system for identifying the 70 possible roles of these proteins in mediating host transcriptional changes during infection. As described in Chapter 1, bacterial pathogens such as S. Typhimurium secrete specialized protein effectors directly into the host cell through a multisubunit type III secretion apparatus. Expression of the type III secretion apparatus encoded on SPI 2 is essential for survival and replication within macrophages and necessary for systemic disease, and mutants with a deletion in an apparatus component such as SsaR, or a virulence protein such as SifA, are highly attenuated (see Appendix B for analysis of the role of SifA in intramacrophage replication). S. Typhimurium's type Ill-secreted effectors specifically affect host cell functions such as cytoskeletal architecture, vesicle trafficking, and cell signaling, in order to invade and survive within host cells (1). When these studies were undertaken, the possible effects of SPI 2-secreted virulence factors on macrophage gene expression had not been examined. Macrophage transcriptional responses to the AssaR mutant will identify which host genes are altered in response to all of the virulence proteins secreted by the SPI 2-encoded secretion apparatus. For a more detailed view of the interplay between host and bacterial gene expression, it is important to identify the contribution of individual bacterial proteins in altering the expression of specific host genes. SspHl and SspH2 are encoded outside of the SPI 2 pathogenicity island and contain secretion signals that direct their secretion by the SPI 2 type III secretion apparatus, and SspH2 was one of the first virulence proteins shown to be secreted in macrophages using this apparatus (2). SspHl and SspH2 are intriguing candidates for altering host gene expression as they contain leucine rich repeats and homology to Yersinia's YopM, which translocates to the nucleus in host cells (2). SspHl has since been shown to have a nuclear localization within host cells and can partially block N F - K B signaling (3). Elucidating a host response to these factors would aid in our understanding of their function during infection and expand our knowledge of the interplay between host and pathogen gene expression. 71 As a long-term survival strategy, S. Typhimurium likely alters macrophage gene transcription to maintain a hospitable intracellular niche and prevent immune clearance of infected cells. We have previously shown that macrophages respond to S. Typhimurium LPS with dramatic changes in gene expression, some of which should mediate bacterial clearance (Chapter 2, (4)). The failure of these macrophage responses to a conserved bacterial structure to halt the infection suggests that virulent S. Typhimurium undermines an effective response, and thereby causes disease. Since S. Typhimurium can only survive and replicate within macrophages if the SPI 2-encoded type III secretion apparatus is intact, secreted virulence factors are strong candidates for altering macrophage function. Profiling macrophage gene expression changes triggered by bacterial SPI 2 virulence factor mutants as compared to a wild type infection should provide clues to effector functions as well as provide a possible mechanism to explain why macrophage responses are ineffective in controlling S. Typhimurium infection. 3.3 Experimental Proceedures. Bacterial and cell culture strains and growth conditions. The Salmonella Typhimurium strain SL1344 was obtained from the A T C C (Manassas, V A ) and SL1344 AssaR has been previously described (see Appendix B). The bacterial strains cs401 (14028s Str* wild type) and 14028s AsspHlAsspH2 were provided by Dr. Ed Miao and Dr. Sam Miller (University of Washington, Seattle, WA). For macrophage infections, stationary phase cultures were prepared by inoculating 10 ml L B in a 125 ml flask and culturing overnight with shaking at 37°C. The murine macrophage cell line R A W 264.7 (TIB-72, A T C C ) was maintained in D M E M (Invitrogen, Burlington, ON) supplemented with 10% heat-inactivated FBS (Invitrogen) without antibiotics at 37°C in 5% CO2 and cultured for less than 20 passages. R A W 264.7 cells 72 were cultured with 200 U/ml (20 ng/ml) IFN-y (Genzyme) for 24 hours where indicated prior to infection. Bone marrow was isolated from the femurs of B A L B / c mice (Jackson Laboratories, Bar.Harbor, ME), cultured for 7 days without antibiotics in D M E M supplemented with 20% heat-inactivated FBS, 2 m M L-glutamine, 1 m M sodium pyruvate, and 30% L-cell conditioned media as a source of M-CSF at 37°C in 5% C 0 2 . Infection Conditions. Macrophages were seeded at a density of 2.5xl0 5 cells/well of a 24 well plate (for C F U experiments) or 5.6xl0 6 cells/150 mm diameter round tissue culture dish (for RNA isolation). Bacteria were opsonized with 10% normal human serum containing active complement for 20 min at 37°C prior to infection. Bacteria were diluted in warm culture medium to give a MOI of approximately 20, and infection was allowed to proceed for 20 min in a 37°C, C 0 2 incubator. Cells were washed two times with PBS to remove extracellular bacteria and then incubated in D M E M + 10% FBS containing 100 ^g/ml gentamicin (Sigma, St. Louis, MO) to kill any remaining extracellular bacteria and prevent re-infection. After 2 h, the gentamicin concentration was lowered to 10 /^g/ml. Immunofluorescence and C F U counts were subsequently performed in parallel to compare the variability in the actual number of intracellular bacteria per cell with the average number per cell for the population, respectively. To determine invasion efficiency, samples of cells were washed twice with PBS to remove gentamicin and lysed with 1% Triton X-100/0.1% SDS in PBS at 2 h post-infection. Numbers of intracellular bacteria were calculated by colony counts. Consistently, macrophages were infected by an average of 1-3 bacteria per cell as assessed by standard plate counts and immunofluorescence studies, and no significant differences were observed in invasion efficiency or intracellular numbers at 8 h or 24 h post-infection between wild type and mutant bacteria. 73 RNA isolation, gene array hybridization, data analysis, and northern blotting. Total R N A was isolated from 1.2xl07 cells per condition for gene array hybridization. Refer to Chapter 2, experimental procedures (2.4) for complete methods. Results. 3 . 4 Comparing macrophage gene expression following infection by wild type S. Typhimurium or the AssaR S P I 2 secretion mutant. For these studies, a macrophage-like cell line, R A W 264.7 was primed by IFN-y for 24 h and then infected for 4 h, 8 h, or 24 h with equal numbers of either wild type or a AssaR mutant S. Typhimurium strain SL1344. The AssaR mutant has a deletion in a structural component of the SPI 2-encoded type III secretion apparatus and cannot replicate within macrophages, presumably because it cannot form a functional secretion apparatus through which to secrete essential protein effectors. Intracellular bacterial numbers between the replication-competent wild type and the replication-incompetent AssaR mutant are similar at 8 h and 24 h when R A W 264.7 cells are IFN-y primed. Bacteria used for the infections were grown to stationary phase to increase the induction of SPI 2 genes (2, 5). Figure 3.1 contains two array hybridization results using probes prepared from cells infected for 24 h. Quantification of the hybridization signals revealed that while the expression of most genes are similar after infection by the mutant or wild type strain, a small number of genes are differentially expressed at 8 h and/or 24 h after infection but not at 4 h. Genes that were more highly induced in cells infected by wild type bacteria relative to the AssaR secretion mutant at 8 h are listed in Table 3.1 and differentially expressed genes after 24 h are listed in Table 3.3. Genes that have lower expression in cells infected by wild type bacteria compared to cells infected with the AssaR mutant, are listed in Table 3.2 (8 h post-infection) and Table 3.4 74 A. wild type B. ssaR C. wild type D. sspH1sspH2 Figure 3.1 Array hybridization images comparing R A W 264.7 cells infected for 24 h with various S. Typhimurium strains. Cells were infected with: A . wild type SL1344, B. AssaR SPI2 type III secretion mutant SL1344, C. wild type 14028s, D. AsspHlAsspH2 virulence factor mutant 14028s. 75 Table 3.1 Genes more highly induced in IFN-y primed R A W 264.7 cells infected with wild type bacteria relative to an AssaR SPI2 type III secretion mutant: 8 h. A cut-off of 2-fold was applied to the data. n=\. Intensity Intensity Ratio Array wt ssaR wt/ssaR Position Protein/gene 413 20 20.7 E5m catenin alpha 304 46 6.6 A5d Lfc proto-oncogene 365 87 4.2 F1d BMP4; bone morphogenetic protein 4 595 143 4.2 B5b Hck tyrosine-protein kinase 584 168 3.5 B6i Rsk; ribosomal protein S6 kinase 490 146 3.4 D4n Lbx 1 transcription factor 344 125 2.8 E3a interleukin-10 receptor 531 206 2.6 B3b IFNgR2 762 316 2.4 B4f Stat5a; mammary gland factor 527 219 2.4 E1e CD4 receptor 723 303 2.4 E5g GABA-A transporter 4 916 394 2.3 B6g PKC-delta; protein kinase C delta type 473 206 2.3 D5c myocyte nuclear factor (MNF) 2757 1211 2.3 B6a MAPKK1 (MKK1) 664 313 2.1 C5f A P endonuclease 862 412 2.1 A5c H-ras proto-oncogene 1709 832 2.1 E3c interleukin-2 receptor gamma chain 3147 1562 2.0 C3f Fas I receptor; Fas antigen 616 307 2.0 F6f A C E ; angiotensin-converting enzyme 1892 946 2.0 B3e LFA1-alpha 442 224 2.0 B7b Rab-2 ras-related protein 76 Table 3.2 Genes more highly induced in IFN-y primed RAW 264.7 cells infected with an AssaR SPI2 type III secretion mutant relative to wild type bacteria: 8 h. A cut-off of 2-fold was applied to the data. n=l. tensity Intensity Ratio Array wt ssaR wt/ssaR Position Protein/gene 20 367 0.1 D1j CACCC Box- binding protein BKLF 20 343 0.1 D1i butyrate response factor 1 20 305 0.1 D1h Brn-3.2 POL) transcription factor 20 303 0.1 D1k C/EBP transcription factor 20 299 0.1 C1a caspase-11 82 316 0.3 C7m XPAC 136 515 0.3 C3a Chop10 148 544 0.3 B3k retinoic acid receptor beta-2 140 428 0.3 C7a MSH2 DNA mismatch repair protein 139 396 0.4 B3j VEGFR2 119 315 0.4 B1h HMG1-related signal binding protein 114 296 0.4 C7i ShcC adaptor; She-related; brain-specific 229 542 0.4 B5k Jnk stress-activated protein kinase (SAPK) 120 281 0.4 B4i transcription factor A10 335 771 0.4 A1f ezrin 156 351 0.4 C3j gadd45 138 292 0.5 F7j serine protease inhibitor 2 202 426 0.5 A6c cyclin B1 197 413 0.5 D4I IRF2, interferon regulatory factor 2 150 313 0.5 F4i uromodulin 223 463 0.5 A2n Ear-2, v-erbA related proto-oncogene 152 307 0.5 C1b Caspase-3 167 334 0.5 A4j VEGFR1 283 558 0.5 F1m MIG, gamma interferon induced monokine 265 520 0.5 D2m Erf; Ets-related transcription factor 301 568 0.5 D4i ikaros DNA binding protein 395 743 0.5 A3n casein kinase II (alpha subunit) 184 342 0.5 C1k BID; apoptotic death agonist 167 305 0.5 F7m TIMP-2 77 Table 3.3 Genes more highly induced in IFN-y primed R A W 264.7 cells infected with wild type bacteria relative to an AssaR SPI2 type III secretion mutant: 24 h. A cut-off of 2-fold was applied to the data. n=\. Intensity Intensity Ratio Array wt ssaR wt/ssaR Position Protein/gene 342 20 17.1 C6f ERCC5 excision repair protein 492 44 11.2 B i n oxidative stress-induced protein mRNA 569 70 8.1 C6i MHR23A; Rad23 UV excision repair protein homolog 426 88 4.8 C7c photolyase/blue-light receptor homolog 472 131 3.6 D2g DP-1 321 97 3.3 E3c interleukin-2 receptor gamma chain 752 239 3.1 C6e ERCC3 DNA repair helicase 1234 401 3.1 C6c DNAse I 1732 610 2.8 B4g Stat6 437 154 2.8 E6f CD45 associated protein (LSM-1) 356 131 2.7 C4f PD-1 possible cell death inducer 688 259 2.7 E7i intercellular adhesion molecule-1 3431 1404 2.4 C6j MHR23B; Rad23 UV excision repair protein homolog 837 351 2.4 A3n casein kinase II (alpha subunit) 539 235 2.3 B6g PKC-delta; protein kinase C delta type 778 352 2.2 A7m prothymosin alpha 603 273 2.2 F2m IGFBP-5, insulin-like growth factor binding protein-5 685 312 2.2 C4a NADPH-cytochrome P450 reductase 752 343 2.2 G13 myosin I 936 436 2.1 C4e p55cdc; cell division control protein 20 1388 647 2.1 F6i cathepsin H 467 221 2.1 B4I Cas; Crk-associated substrate 673 320 2.1 E7g integrin beta 470 225 2.1 . F7f urokinase type plasminogen activator 2656 1274 2.1 E6i CD22 antigen 3581 1737 2.1 F6j cathepsin L 823 401 2-1 C6b. DNA-poJymerase delta catalytic subunit 4106 2056 2.0 C5c TRAIL; TNF-related apoptosis inducing ligand 747 375 2.0 F4I interleukin 10 418 210 2.0 F6a kinesin like protein KIF 3B 1255 632 2.0 E2e GM-CSF receptor 78 Table 3.4 Genes more highly induced in IFN-y primed RAW 264.7 cells infected with an AssaR SPI2 type III secretion mutant relative to wild type bacteria: 24 h. A cut-off of 2-fold was applied to the data. n=\. Intensity Intensity Ratio Array wt ssaR wt/ssaR Position Protein/gene 20 410 0.0 F5k epidermal keratin 20 303 0.1 D7i TEF-1, transcriptional enhancer factor 1 31 335 0.1 D3h glial cells missing gene homolog 37 303 0.1 F1a b-FGF, basic fibroblast growth factor 54 340 0.2 C5j DNA ligase I 142 476 0.3 C1k BID; apoptotic death agonist 581 1658 0.4 A7e p21/Cip1/Waf1; cdk-inhibitor protein 1 223 632 0.4 A7c p18ink4; cdk4 and cdk6 inhibitor 119 314 0.4 F5j cytoskeletal epidermal keratin 1730 4401 0.4 A7d p19ink4; cdk4 and cdk6 inhibitor 198 476 0.4 A4f Ret proto-oncogene 209 493 0.4 F7m TIMP-2 tissue inhibitor of metalloproteinases-2 145 320 0.5 C5i ATP-dependent DNA helicase II 80-kDa subunit 1062 2331 0.5 A1j p107; RBL1 2430 5296 0.5 C1f Bak apoptosis regulator; Bcl-2 family member 590 1236 0.5 B4c RXR-beta cis-11-retinoic acid receptor 2186 4496 0.5 C1g Bax, Bcl-2 heterodimerization partner 182 372 0.5 F7b mast cell protease (MMCP) - 4 669 1364 0.5 C3d DAD-1; defender against cell death 1 188 383 0.5 E3d interleukin-3 receptor 1185 2413 0.5 A3g jun-D; c-jun-related transcription factor 344 693 0.5 B4j transcription factor TF II D 877 1746 0.5 A5f She transforming adaptor protein 3019 5936 0.5 D5m split hand/foot gene 443 856 0.5 F7n TIMP-3 tissue inhibitor of metalloproteinases-3 312 601 0.5 D5I PAX-8 (paired box protein PAX 8) 389 745 0.5 A1k p130; Rb2 595 1129 0.5 A2n Ear-2; v-erbA related proto-oncogene 21437 40115 0.5 F3f macrophage inflamatory protein 1 beta 240 448 0.5 D2d erythroid transcription factor NF-E2 79 (24 h post-infection). These genes are candidates for being repressed by type III secretion. Few of the differentially expressed genes are conserved between the 8 h and 24 h data sets. 3.5 Comparing macrophage gene expression following infection by wild type S. Typhimurium or the AsspHlsspH2 SPI2 secreted virulence factor mutant. Using a similar strategy as with the AssaR mutant, gene array hybridization was employed to compare changes in macrophage gene expression induced by wild-type S. Typhimurium with infection by a AsspHl AsspH2 non-polar deletion mutant. sspH2 is present in all Salmonella species examined to date, while sspHl is present only in the S. Typhimurium strain 14028s (2), the background strain of the mutants provided by our collaborator. These experiments use R A W 264.7 macrophages not primed with IFN-y to compare host responses to wild type and AsspHlAsspH2 mutant S. Typhimurium 14028s, since SspHl and SspH2 have previously been characterized in naive macrophages and the AsspHlAsspH2 mutant does not have a replication defect, resulting in a similar bacterial load within unactivated cells after 24 h. While the kinetics of SspHl and SspH2 activity is not known, they can be detected within the macrophage cytosol after 6 h (2), and therefore the 24 h time point is reasonable for this initial study. R N A was isolated from unactivated R A W 264.7 macrophages infected by equal numbers of wild type or AsspHl AsspH2 mutants after 24 h. Figure 3.1 contains array hybridization images from this experiment. Genes that were more highly induced in cells infected by wild type bacteria relative to the AsspHl AsspH2 mutant at 24 h are listed in Table 3.5. Genes that are more lowly expressed in cells infected by wild type bacteria compared to cells infected with the AsspHlAsspH2 mutant are listed in Table 3.6. Few of the same differentially expressed genes are observed in cells infected by AsspHl AsspH2 and AssaR, although the macrophage activation state differs between these two experiments. 80 Table 3.5 Genes more highly induced in RAW 264.7 cells infected with wild type bacteria relative to AsspHlAsspH2 virulence factor mutant: 24 h. A cut-off of 2-fold was applied to the data. n=l. Intensity Intensity Ratio ' Array WTcs401 sspH1/2 wt/sspH12 Position Protein/gene 543 21 25.9 C1b Caspase-3 410 20 20.5 B7a Gem; induced, immediate early protein 354 20 17.7 B6c MAPKK4 (JNKK1; S E K 1 ; MKK4) 804 105 7.7 E1c bone morphogenetic protein receptor 452 66 6.8 A7a Cdk7; cyclin-dependent kinase 7 1362 279 4.9 E1j granulocyte CSF-receptor 936 203 4.6 C4m STAM; signal transducing adaptor molecule 398 95 4.2 D7m zinc finger transcription factor RU49 1493 362 4.1 E1n ERBB-3 receptor 679 173 3.9 E2I interferon alpha-beta receptor 2793 776 3.6 A6a cyclin A (G2/M-specific) 1292 365 3.5 C3a Chop10 4804 1396 3.4 E7c integrin alpha 5 (CD51) 1748 515 3.4 D7k YY1 (UCRBP) transcriptional factor 3559 1087 3.3 B3b IFNgR2 3152 970 3.2 F4j vascular endothelial growth factor (VEGF) 604 188 3.2 E1I D-factor/LIF receptor 1594 508 3.1 D7i transcriptional enhancer factor 1 (TEF-1) 2138 694 3.1 D4k interferon inducible protein 1 4189 1373 3.1 F4k interleukin 1 beta 2612 872 3.0 C4I SPI3; serine proteinase inhibitor 8037 2684 3.0 F7i plasminogen activator inhibitor-2 1607 546 2.9 C2b glutathione S-transferase Mu 1 4014 1380 2.9 A6d cyclin B2 (G2/M-specific) 12118 4180 2.9 E1k monotype chemoattractant protein 3 1583 548 2.9 A7I myeloblastin; serine protease 16885 5852 2.9 D7j YB1 DNA binding protein 5531 1939 2.9 A6c cyclin B1 (G2/M-specific) 1463 513 2.9 B5a Fyn proto-oncogene; Src family member 458 162 2.8 B6n G13; guanine nucleotide regulatory protein 1845 657 2.8 D3d G A binding protein beta-2 chain 5372 1924 2.8 E6n glutamate receptor channel subunit gamma 699 257 2.7 D7n zinc finger X-chromosomal protein (ZFX) 1091 402 2.7 D6j transcription factor BARX1 30702 11329 2.7 F6j cathepsin L 2543 952 2.7 B5b Hck tyrosine-protein kinase 81 Intensity Intensity Ratio Array WTcs401 sspH1/2 wt/sspH12 Position Protein/gene 4813 1809 2.7 D7h transcription factor UBF 3474 1309 2.7 A1n TSG101 tumor susceptibility protein 2445 932 2.6 C4j RIP cell death protein 701 270 2.6 E1b orphan receptor 709 284 2.5 F5k epidermal keratin (1 human) 2728 1094 2.5 A7n Tob antiproliferative factor 316 127 2.5 B6e PKC-alpha; protein kinase C alpha type 574 232 2.5 B6h PKC-theta; protein kinase C theta type 3716 1507 2.5 B3c interleukin-6 receptor beta chain 7641 3121 2.4 B7c Rac1 murine homolog 1062 434 2.4 A6I cyclin G2 (G2/M-specific) 1451 606 ' 2.4 C6m MmRad51; E coli RecA homolog 5818 2456 2.4 B7b Rab-2 ras-related protein 7164 3040 2.4 D2g DP-1 658 280 2.4 C3n interleukin-1 receptor 891 387 2.3 E2j snoN; ski-related oncogene 406 177 2.3 A6g cyclin D2 (G1/S-specific) 1357 595 2.3 B6b MAPKK3 (MKK3, MEK3) 4892 2162 2.3 D5g NF-kappa B binding subunit (TFDB5) 20787 9335 2.2 F6d vimentin 1689 762 2.2 E7d integrin alpha 6 3166 1439 2.2 B3h transferrin receptor protein (p90, CD71) 4233 1977 2.1 C7b PCNA; proliferating cell nuclear antigen 1798 844 2.1 D1a ablphilin-1 (abi-1); similar to HOXD3 4605 2180 2.1 D2k E G F R kinase substrate E P S 8 1977 938 2.1 E7b integrin alpha 4 693 329 2.1 C1c caspase-7 3014 1439 2.1 C5h ATP-dependent DNA helicase II 70 kDa 866 415 2.1 B7h cortactin 669 321 2.1 A7h Wee1/p87; cdc2 tyrosine 15-kinase 3651 1753 2.1 D3m HMG-14 non histone chromosomal protein 2887 1387 2.1 F6k collagenase type IV 821 403 2.0 E2k TGF-beta receptor type 1 2256 1115 2.0 C3h FLIP-L; apoptosis inhibitor 3949 1962 2.0 D6n transcription factor L R G - 21 652 324 2.0 C1I glutathione peroxidase; selenoprotein 9789 4926 2.0 E6e CD44 antigen 1137 573 2.0 D6m LIM-1 transcription factor 20422 10392 2.0 F3g MIP2a lpha 4516 2309 2.0 C3e FAF1; apoptosis activator 3996 2046 2.0 A1e EB1 APC-binding protein 82 Table 3.6 Genes more highly induced in RAW 264.7 cells infected with AsspHlAsspH2 virulence factor mutant relative to wild type bacteria: 24 h. A cut-off of 2-fold was applied to the data. n=l. Intensity Intensity Ratio Array wtcs401 sspH1/2 wt/sspH12 Position Protein/gene 20 616 0.0 E1i endothelin b receptor (Ednrb) 20 482 0.0 A2d ZO-1 20 395 0.1 F1n glial cell line-derived neurotrophic factor 20 388 0.1 B1f Osp94 osmotic stress protein; APG-1 20 337 0.1 C7m X P A C 48 615 0.1 A7i Cdc25 phosphatase 82 727 0.1 C7f Rad50; DNA repair protein 49 327 0.1 C5m DNA topoisomerase I (Top I) 105 570 0.2 E1h corticotropin releasing factor receptor 118 472 0.3 D4a homeobox protein 2.1 (Hox-2.1) 151 505 0.3 C7g RAG-1 ; V(D)J recombination activating protein 219 610 0.4 F7I serine protease inhibitor homolog J6 353 965 0.4 C2f adenosine A1M receptor 140 368 0.4 B7I P T P R G ; protein-tyrosine phosphatase gamma 395 994 0.4 C3g Fasl; Fas antigen ligand 222 552 0.4 D4g homeobox protein 8 (Hox-8) 329 817 0.4 F7b mast cell protease (MMCP) - 4 152 345 0.4 D3a Ets-related protein P E A 3 169 383 0.4 A1b B R C A 608 1336 0.5 A1c BRCA2 446 979 0.5 E4f 5-hydroxytryptamine (serotonin) receptor 1b 283 610 0.5 C7a MSH2 DNA mismatch repair protein 317 678 0.5 D7c transcription factor RelB 395 839 0.5 F3b keratinocyte growth factor FGF-7 218 461 0.5 C7h RAG-2; V(D)J recombination activating protein 325 682 0.5 A i d DCC; netrin receptor 168 345 0.5 A5n Tiam-1 invasion inducing protein 1102 2210 0.5 F2a granulocyte colony- stimulating factor (G-CSF) 201 397 0.5 A5h lnt-3 proto-oncogene; NOTCH4 239 462 0.5 A4e platelet-derived growth factor alpha-receptor 590 1131 0.5 D2b engrailed protein (En-1) homolog 256 485 0.5 F1h Cek 7 receptor protein tyrosine kinase ligand 426 806 0.5 A2e A-myb proto-oncogene 272 506 0.5 F2k insulin-like growth factor binding protein-3 576 1069 0.5 F2n insulin-like growth factor-2 (somatomedin A) 1009 1853 0.5 A5i preproglucagon 610 1113 0.5 C2g adenosine A2M2 receptor 83 3.6 Preliminary confirmation. Genes with altered expression in a type Ill-secretion-dependent and SspHlSspH2-dependent manner, along with a hybridization intensity of >300 and a 2-fold difference in gene expression, were selected for further confirmation. Based on this criteria, northern blots were performed for M E K 1 expression, which gave 2.3-fold and 1.9-fold higher expression following 8 h infection by wild type S. Typhimurium by array hybridization, when compared to the ASsaR and ASspHlSspH2 mutants, respectively. The image in Figure 3.2 shows a similar increase in M E K 1 levels (n=2). However, in two subsequent experiments, these differences in M E K 1 expression levels between wild type and mutant-infected cells were not observed, perhaps because such small changes in gene expression are difficult to measure reproducibly using this technique. Due to time constraints, these results have not been confirmed in replicate array experiments or by other techniques. However, the increase in MEK1 expression levels following infection by wild type S. Typhimurium relative to uninfected cells was subsequently shown to be significant and its characterization forms the basis for Chapter 4. 3.7 Discussion and future directions. There has since been one publication addressing macrophage gene expression in response to a S. Typhimurium virulence factor. Detweiller et al. have profiled gene expression in P M A -stimulated THP-1 human macrophage-like cells following infection by wild type or a PhoP n u" mutant (6). Using a 22 000 cDNA array, they observed that expression of only 0.3% of these cDNAs differed between the two infections. To pursue our preliminary results, R N A has been isolated from bone marrow-derived macrophages infected for 8 h or 24 h with wild type or AssaR S. Typhimurium. Experiments are 84 MEK1 G A P D H Wt A wt A 8 h 24 h Figure 3.2 Northern blot analysis of type III secretion-dependent increase in MEK1 gene expression. RNA was isolated from R A W 264.7 cells infected with wild type (wt) or ASspHlASspH2 (A) S. Typhimurium or uninfected (-) after 8 h and 24 h. Northern blots were hybridized with a MEKT-specific probe and then stripped and re-probed using a GAPDH-specific probe. This is representative of 2 independent experiments. 85 planned to use more advanced glass slide arrays containing >10 000 cDNAs. These experiments should provide a more relevant model than R A W 264.7 cells for studying macrophage gene expression, and provide more robust data for detecting differential expression of a potentially small number of genes. 3.8 Literature cited. 1. Waterman, S. R., and D. W. Holden. 2003. Functions and effectors of the Salmonella pathogenicity island 2 type III secretion system. Cell Microbiol 5:501. 2. Miao, E. A. , C. A . Scherer, R. M . Tsolis, R. A . Kingsley, L . G. Adams, A . J. Baumler, and S. I. Miller. 1999. Salmonella typhimurium leucine-rich repeat proteins are targeted to the SPI1 and SPI2 type III secretion systems. Mol Microbiol 34:850. 3. Haraga, A. , and S. I. Miller. 2003. A Salmonella enterica serovar typhimurium translocated leucine-rich repeat effector protein inhibits NF-kappa B-dependent gene expression. Infect Immun 71:4052. 4. Rosenberger, C. M . , M . G. Scott, M . R. Gold, R. E. Hancock, and B. B. Finlay. 2000. Salmonella typhimurium infection and lipopolysaccharide stimulation induce similar changes in macrophage gene expression. J Immunol 164:5894. 5. Beuzon, C. R., G. Banks, J. Deiwick, M . Hensel, and D. W. Holden. 1999. pH-dependent secretion of SseB, a product of the SPI-2 type III secretion system of Salmonella typhimurium. Mol Microbiol 33:806. 6. Detweiler, C. S., D. B. Cunanan, and S. Falkow. 2001. Host microarray analysis reveals a role for the Salmonella response regulator phoP in human macrophage cell death. Proc Natl Acad Sci USA 98:5850. 86 Chapter 4 Macrophages Inhibit Salmonella Typhimurium Replication through MEK/ERK Kinase and Phagocyte NADPH Oxidase Activities. 4.1 Preface. This chapter was previously published in part as: Carrie M . Rosenberger and B . Brett Finlay. 2002. Macrophages Inhibit Salmonella Typhimurium Replication through M E K / E R K Kinase and Phagocyte N A D P H Oxidase Activities. Journal of Biological Chemistry. 277:18753-18762. 4.2 Summary. Host responses during the later stages of Salmonella-macrophage interactions are critical to controlling infection but have not been well characterized. After 24 h of infection, nearly half of interferon-y primed murine R A W 264.7 macrophage-like cells infected by Salmonella Typhimurium contained filamentous bacteria. Bacterial filamentation indicates a defect in completing replication and has been previously observed in bacteria responding to a variety of stresses. To understand whether macrophage gene expression was responsible for this effect on S. Typhimurium replication, we used gene arrays to profile IFN-y primed R A W 264.7 cell gene expression following infection. We observed an increase in M E K 1 kinase mRNA at 8 h, an increase in M E K protein at 24 h, and measured phosphorylation of M E K ' s downstream target kinases, ERK1/2, throughout the 24 h infection period. Treatment of cells with M E K kinase inhibitors significantly reduced numbers of filamentous bacteria observed within macrophages after 24 h and increased the number of intracellular CFU. Phagocyte N A D P H oxidase inhibitors and antioxidants also significantly reduced bacterial filamentation. Either M E K kinase or phagocyte oxidase inhibitors could be added 4-8 h after infection and still significantly decrease bacterial filamentation. Oxidase activity appears to mediate bacterial filamentation in parallel to M E K kinase signaling, while inducible nitric oxide synthase inhibitors had no significant effect on bacterial morphology. In summary, S. Typhimurium infection of interferon-y primed 87 macrophages triggers a M E K kinase cascade at later infection times and both M E K kinase and phagocyte N A D P H oxidase activity impair bacterial replication. These two signaling pathways mediate a host bacteriostatic pathway and may play an important role in innate host defense against intracellular pathogens. 4.3 Introduction. Macrophages serve a central role in host defense against pathogenic microbes by nature of their ability to rapidly recognize bacterial components, phagocytose pathogens, and activate an arsenal of antimicrobial effectors to contain and eliminate the microbe. A macrophage's repertoire of antimicrobial effectors includes the phagocyte N A D P H oxidase (phox), inducible nitric oxide synthase (iNOS), cationic antimicrobial peptides, and an endosomal system designed to restrict nutrients and traffic phagocytosed microbes to degradative lysosomes. Phox is a multisubunit complex that can be assembled on intracellular membranes, such as the phagosomal membrane, and the plasma membrane. Phox activity produces superoxide that can lead to the generation of other toxic reactive oxygen intermediates (ROI) such as hydrogen peroxide, and combine with nitric oxide to generate peroxynitrite, all of which can directly cause oxidative damage to bacteria (1). Macrophages activate many signaling pathways following recognition of bacterial components, although the relative contribution of each pathway to the induction of antibacterial effectors is not fully understood. For example, macrophages activate M E K / E R K kinase signaling in response to bacterial infection (2). M E K is a M A P kinase kinase that is activated by phosphorylation following Salmonella enterica serovar Typhimurium infection of macrophages in a Raf-dependent or -independent manner (3). Upon activation, M E K phosphorylates the downstream kinase E R K (extracellular signal-regulated kinase), which then dimerizes and translocates to the nucleus where it activates transcription factors such as Elk-1 to modify gene expression (4). M E K / E R K signaling is involved in the activation of oxidative and 88 nitrosative bursts, endosomal trafficking, and increased macrophage differentiation and therefore is a strong candidate for being involved in the augmentation of macrophage defenses against intracellular pathogens (5). In the murine model of human typhoid fever, S. Typhimurium resides intracellularly within macrophages (6) in a specialized vacuole and macrophages appear to be a preferred site for bacterial replication (7). Because this intramacrophage niche helps to shield Salmonella from killing by components of the innate and humoral immune defenses, the responses of infected macrophages are thought to serve a central role in determining disease outcome (7). The interplay between host resistance factors and bacterial virulence factors are critical to determining the outcome of infection. On the host side, macrophages serve to limit the course of infection by destroying intracellular S. Typhimurium or restricting bacterial replication by modifying its intracellular environment. Macrophages limit the availability of cations and nutrients required by Salmonella within its intracellular vacuole (8). Both phox and iNOS are required for effective host resistance against S. Typhimurium in the murine typhoid model (9-11). Cytokines secreted during infection, including IFN-y (12), are essential for host defense against Salmonella infection. IFN-y primed macrophages may be important in mediating bacterial clearance in immune mice (7) and IFN-y stimulation upregulates the expression of many of these antimicrobial effectors and impairs replication of S. Typhimurium within macrophages (12). On the bacterial side, while S. Typhimurium initiate a pro-inflammatory response by macrophages, some bacteria are able to secure an intracellular niche within a distinct endosomal compartment where replication occurs 4-8 h after infection. Bacterial virulence protein mutants that cannot replicate within macrophages are strongly attenuated for systemic disease within the murine typhoid model, reinforcing the importance of Salmonella-macrophage interactions (13, 14). 89 Distinct antibacterial activities have been observed in macrophages at different times during infection (10). The responses of macrophages to intracellular S. Typhimurium at later times post-infection are likely critical in mediating the outcome of infection but have not been well characterized, with most of the work centered upon the first few hours of infection. We demonstrate here that IFN-y primed R A W 264.7 macrophage-like cells are capable of restricting the bacterial replication that is permitted by naive R A W 264.7 cells. To identify host factors mediating this control of bacterial replication, we have used gene arrays to examine the transcriptional responses of IFN-y primed R A W 264.7 cells to intracellular S. Typhimurium at 8 h post-infection. We identified upregulated MEK1 kinase mRNA levels, which were confirmed at the levels of RNA, protein, and kinase activity. M E K activity correlated with inhibition of bacterial replication and induction of bacterial filamentation, an indicator of bacterial stress. M E K kinase and phox activities can impact each other and we observed that phox inhibitors mimicked the effect of M E K inhibitors in reducing bacterial filamentation. M E K kinase or oxidase inhibitors added later during infection could significantly decrease bacterial filamentation, suggesting that M E K and phox activities at later times are primarily responsible for mediating bacterial filamentation. While phox activity can positively regulate as well as be regulated itself by M E K kinase activity, our results suggest that M E K and phox activities function in parallel to mediate bacterial filamentation. In summary, we provide evidence that S. Typhimurium infection of IFN-y primed macrophages triggers a M E K kinase cascade and ROI production at later infection times, and that both M E K kinase and phox activities impair bacterial replication, which is reflected by filamentation. 90 4.4 Experimental Procedures Growth Conditions of Bacterial and Macrophage Cells. The Salmonella enterica serovar Typhimurium strain SL1344 (ATCC, Manassas, V A ) was grown in L B broth. The plasmid p A T l 13-GFP (kindly provided by Dr. J.L. Gaillard, Paris, France) was introduced into SL1344 by electroporation (kindly provided by Dr. L . Knodler, University of British Columbia, Vancouver, Canada). The S. Typhimurium strain cs401 (14028S StrR) was kindly provided by Dr. S. Miller (University of Washington, Seattle, WA). For macrophage infections, 10 ml L B in a 125 ml flask was inoculated from a frozen glycerol stock and cultured overnight with shaking at 37°C to stationary phase. The murine macrophage cell lines R A W 264.7 (TIB-72) and J774.1 (ATCC) were maintained in D M E M (Gibco B R L , Burlington, ON) supplemented with 10% heat-inactivated FBS (Gibco) without antibiotics at 37°C in 5% CO2. Cultures were used between passage numbers 6-20. For the bacterial colony forming unit (CFU) enumeration experiments described in Figure 4.1, R A W 264.7 cells were either unprimed or cultured with 20 U/ml (2 ng/ml) IFN-y (R&D Systems, Minneapolis, MN) for 20-24 h prior to infection. For all subsequent experiments, cells were primed with IFN-y prior to infection. Resident peritoneal macrophages were harvested from B A L B / c mice by peritoneal lavage using 5 ml cold RPMI medium containing 10% heat-inactivated FBS. Lavage cells were seeded at 1 x 106 per cover slip in 24 well plates, and non-adherent cells removed by washing after 6 h. Splenic macrophages were harvested from B A L B / c mice by enzymatically dissociating isolated spleens using Liberase, as directed by the manufacturer (Roche) at 37°C for 1 h, passing cells through a fine wire mesh, and pelleting cells by centrifugation at 1 000 rpm for 5 min. Cells were resuspended in D M E M + 10% heat-inactivated FBS + 2 mM L-glutamine, seeded 1 x 107 cells in the wells of 24 well plates containing glass cover slips, and washed after 16 h to remove 91 non-adherent cells. Spleens were isolated from mice infected with GFP-5. Typhimurium, frozen in OCT compound (Miles, Inc., Elkhart, IL), and 10 pm cryosections were cut (Histology, University of British Columbia). Mice were sacrificed by cervical dislocation and all procedures were approved by the Committee on Animal Care at the University of British Columbia. Infection Conditions. For immunofluorescence and C F U experiments, IFN-y primed R A W 264.7 cells ( l x l 0 5 cells/well) were seeded in 24 well plates. Bacteria were diluted in culture medium to give a MOI of approximately 100, bacteria were centrifuged onto the monolayer at 1000 rpm for 10 minutes to synchronize infection, and the infection was allowed to proceed for 20 min in a 37°C, 5% C O 2 incubator. Cells were washed 3 times with phosphate buffered saline (PBS) to remove extracellular bacteria and then incubated in D M E M + 10% FBS containing 100 pg/ml gentamicin (Sigma, Oakville, Ont) to kil l any remaining extracellular bacteria and prevent re-infection. After 2 h, the gentamicin concentration was lowered to 10 pg/ml and maintained throughout the assay. Intracellular survival/replication of S. Typhimurium SL1344 was determined using the gentamicin-resistance assay, as described in Chapter 3 (15). Under these infection conditions, macrophages contained an average of 1 bacterium per cell after 2 h as assessed by standard plate counts, which permitted analysis of macrophages after 24 h. Imm unofluorescence. IFN-y primed R A W 264.7 cells ( lx lO 5 cells/well) were seeded on 12 mm-diameter glass coverslips in 24 well plates. Following infection with S. Typhimurium for 24 h, fixation was performed with 2.5% paraformaldehyde for 10 min at 37°C. Fixed cells were washed 3 times with PBS and blocked in PBS containing 10% normal goat serum for 10 min. Extracellular bacteria were labeled by sequentially overlaying coverslips with a rabbit polyclonal primary antibody to S. Typhimurium LPS (Difco, Detroit, MI) at 1:200 and an Alexa 568-conjugated 92 mouse anti-rabbit secondary antibody (Molecular Probes, Eugene, OR) at 1:400 in PBS + 10% normal goat serum for 20 min. Coverslips were mounted onto glass sides using Mowiol (Aldrich Chemical Co., Milwalkee, WI). To quantify cells containing filamentous bacteria, only intracellular S. Typhimurium were counted (not labeled by the extracellularly applied LPS-specific antibody). Bacteria were scored as "filamentous" when they were >3x longer than a typical bacterium (approximately >5 pm). Three populations were scored: the number of infected cells containing predominantly filamentous bacteria, the number of infected cells where >50% of intracellular bacteria were of normal size, and the number of infected cells containing bacteria that were all of normal size. Significance was determined by calculating P values using an unpaired 2-tailed t test. The level of TUNEL-positive (Boehringer Mannheim, Laval, Que) apoptotic cells was less than 10% for all conditions. RNA Isolation and Northern Blotting. At various times post-infection, IFN-y primed R A W 264.7 cells were washed once with PBS and scraped to detach the cells from the dish. R N A was then isolated using Trizol according to the manufacturer's directions (Gibco). R N A was extracted twice with phenol:chloroform:isoamyl alcohol (25:24:1) and once with chloroform. The R N A was then precipitated with 2.5 volumes 100% ethanol and 1/10 volume sodium acetate pH 5.2, resuspended in RNase-free water containing RNase inhibitor (Ambion, Austin, TX), and stored at -70°C. R N A quality was assessed by gel electrophoresis and staining with ethidium bromide. Northern blots were prepared as previously described, using 5-10 pg of total R N A per lane (16). To prepare templates for probe synthesis, cDNA was prepared from total R N A purified from R A W 264.7 cells using oligo dT and SuperScriptll reverse transcriptase (Gibco). The following primer pairs were designed to amplify portions of the indicated macrophage genes: MEK1 5'-G T T G C T T T C A G G C C T C T C C - 3 ' , 5 ' - A G T G A T G G G C T C T G C T T A G G -3'; G A P D H 5'-93 A G A A C A T C A T C C C T G C A T C C - 3 ' , 5 ' -CTGGGATGGAAATTGTGAGG-3 ' . Antisense c D N A probes were prepared by PCR using 50 ng of the appropriate PCR product template, the reverse 3' oligo, and modified nucleotides to facilitate repeated stripping of blots (Strip-EZ PCR, Ambion). These single-stranded PCR products were column purified (Qiagen, Mississauga, ON) and labeled with biotin using psoralen-biotin (Ambion) and cross-linking with 365 nm ultraviolet light. Overnight hybridization at 42°C was with labeled probe in UltraHyb (Ambion). The BrightStar nonisotopic detection kit (Ambion) was used for probe detection according to the manufacturer's protocols. Northern blots were quantified by densitometry using an Alphalmager system (Alpha Innotech Co, San Leandro, CA). Preparation of protein extracts and Western blots. IFN-y primed R A W 264.7 cells (5xl0 5/well) were seeded in 6 well tissue culture plates and incubated overnight. At various times post-infection, cells were collected into 100 pi boiling 5x SDS-PAGE loading buffer. Total protein lysates were resolved on a 12% acrylamide SDS-P A G E gel, electrotransferred to nitrocellulose membrane, and blocked with 5% skim milk in tris-buffered saline (TBS)-0.1% (v/v) Tween-20. Antibodies were used at the following concentrations: rabbit ant i -MEKl 1:1000 (New England Biolabs, Beverly, M A ) , rabbit anti-phosphorylated M E K 1 1:1000 (New England Biolabs; kindly provided by Dr. B . Ellis, University of British Columbia), rabbit anti-ERK 1:2000 (New England Biolabs, Beverly, M A ) , monoclonal phosphospecific anti-p44/p42 (ERK1/2) 1:2000 (New England Biolabs), and monoclonal anti-actin (ICN, Montreal, Que) 1:15000. Blots were incubated with primary antibodies overnight at 4°C, followed by HRP-conjugated secondary antibodies for 1 h at RT and detected by enhanced chemiluminescence (Amersham Pharmacia Biotech, Baie d'Urfe, Que). Western blots were quantified by densitometry using ImageQuant software (Molecular Dynamics, Sunnyvale, CA). 94 Chemical Inhibitors of MEK kinase, NADPH oxidase, and iNOS. IFN-y primed R A W 264.7 cells were pretreated with inhibitors for 30 min prior to infection at the following concentrations: 50 p M PD 98059 (Calbiochem), 50 p M U 0126 (Promega, Madison, WI), 4 p M diphenyleneiodonium (DPI; Sigma), 250 p M acetovanillone (apocynin; Aldrich), 1 m M ascorbic acid (Sigma), 30 m M N-acetyl cysteine (Sigma), 2 m M N -L-monomethyl arginine ( L - N M M A , Molecular Probes) or 2 m M NG-D-monomethyl arginine (D-NMMA, Molecular Probes). Fresh inhibitors were added immediately after infection, at 2 h, and 6-8 h post-infection to ensure potency. Control cells were treated with equivalent volumes of dimethylsulfoxide (DMSO) per mL of media. To remove inhibitors from pretreated cells, monolayers were washed 3 times with PBS at 8 h post-infection and then cultured for 16 h in D M E M containing 10% FBS and 10 pg/ml gentamicin. Quantification of intracellular ROIs and extracellular nitrite. Intracellular ROIs were quantified by a luminol-enhanced chemiluminescence assay as described previously (17, 18). Briefly, 1 x 106 IFN-y primed R A W 264.7 cells were seeded per well in 6-well tissue culture plates and primed with IFN-y for 24 h. Cells were pretreated with inhibitors or DMSO in media and infected as described above. After 6 h or 24 h of infection, cells were washed once with PBS, scraped into 200 pL of substrate warmed to 37°C (PBS containing 10%> heat-inactivated FBS, 5 x 10"5 M luminol (5-amino-2,3-dihydro-l,4-phthalazinedione, Sigma) as an indicator of ROIs, and 50 U/ml superoxide dismutase (Sigma) and 2 000 U/ml catalase (Sigma) to remove extracellular ROIs). Duplicate samples of 100 pL each were transferred to a clear-bottomed white 96-well plate and chemiluminescence (light) units were quantified for 20 min using a T E C A N spectrophotometer/luminometer (Mannedorf, Switzerland) and the light units detected per minute over this time period were calculated. 95 Nitrite concentration in extracellular media of infected cells after 24 h was measured using a Griess reagent kit (Molecular Probes) according to the manufacturer's instructions. 4.5 IFN-y priming of RAW 264.7 cells restricts S. Typhimurium growth. IFN-y is essential for clearance of S. Typhimurium within the murine typhoid model, and we have previously shown that IFN-y has pleiotropic effects on macrophage transcriptional responses at early times to S. Typhimurium infection (16). To establish a model for investigating macrophage responses that are effective in restricting S. Typhimurium replication, we assessed the effect of IFN-y on the ability of R A W 264.7 macrophage-like cells to control intracellular numbers of S. Typhimurium. As shown in Figure 4.1a, the number of intracellular S. Typhimurium increased 6-fold over a 22.5 h period in R A W 264.7 cells. These cells permit S. Typhimurium replication after 4-8 h, although bacterial avoidance of macrophage-mediated killing could partially contribute to the increase. In contrast, intracellular bacterial numbers did not increase in R A W 264.7 cells primed with IFN-y over this same period (Figure 4.1a). We hypothesized that IFN-y primed R A W 264.7 cells provide a more relevant model for studying macrophage responses that are effective in limiting S. Typhimurium infection, as host factors should be maximally expressed in IFN-y primed R A W 264.7 cells that restrict intracellular bacterial numbers. This choice of model was strengthened by the observation that both naive primary murine macrophages and IFN-y primed R A W 264.7 cells restrict the intracellular load of S. Typhimurium (19). 4.6 Macrophages induce bacterial filamentation at 24 h post-infection. IFN-y priming of macrophages restricts intracellular S. Typhimurium replication but the precise mechanisms for this control are unclear (20). To better understand the interactions 96 Figure 4.1 Priming of R A W 264.7 cells with IFN-y inhibits S. Typhimurium replication. A . Naive or IFN-y primed R A W 264.7 cells were infected with S. Typhimurium and the number of intracellular bacteria per well after infection for 1.5 h (white bars) and 24 h (filled bars) was determined by gentamicin resistance assay and C F U counts. The mean ± SD for 3 experiments is shown, with 2 samples plated in duplicate per condition for each experiment. * P<0.001. B. Many intramacrophage S. Typhimurium are filamentous after 24 h. IFN-y primed R A W 264.7 cells were infected with S. Typhimurium expressing GFP and visualized by fluorescence microscopy after 8 h and 24 h. After 8 h, bacteria were of typical size and no bacteria adopted a filamentous morphology (GFP panel) within infected cells (phase contrast panel). After 24 h, 47 ± 12% of infected cells (phase contrast panel) contained one or more bacteria with a filamentous morphology (GFP panel), indicating impaired bacterial replication. C. Macrophages cause bacterial filamentation independent of IFN-y signaling. Naive or IFN-y primed R A W 264.7 cells were infected with S. Typhimurium + GFP and the number of infected cells containing filamentous bacteria were counted. The mean ± SD is shown, n=3. 97 between macrophages and S. Typhimurium, IFN-y primed R A W 264.7 cells were infected with S. Typhimurium expressing green fluorescent protein (GFP) and examined by fluorescence microscopy. While intracellular bacteria exhibited normal morphology after 8 h of infection, 47 ± 12 % of infected cells contained filamentous bacteria that were >3x the length of a typical bacterium after 24 h (Figure 4.1b). Filamentous bacteria were observed using another S. Typhimurium strain (14028s), indicating that filamentation is shared by more than one strain of S. Typhimurium (data not shown). These filamentous bacteria reside in an endosomal compartment similar to bacteria of normal length, as indicated by an enrichment of the late endosomal glycoprotein, LAMP1 (Figure 4.2a). Some filamentous bacteria were accessible to an extracellularly applied antibody (Figure 4.2b) and were present in the media of cells infected for 24 h (data not shown), suggesting that some bacteria were being extruded by or escaping from infected cells or released from dying cells. Bone marrow-derived macrophages (BMDM), isolated splenic and resident peritoneal macrophages^ and macrophages within infected mouse spleen were all capable of causing bacterial stress and filamentation (Figure 4.3). By scanning electron microscopy, filamentous bacteria had partial or absent septa, suggesting a defect in completion of cell division, an indicator of bacterial stress (Figure 4.3g) (21, 22). 4.7 Salmonella induces M E K 1 kinase m R N A and activity. To examine whether macrophage gene expression was responsible for this effect on bacterial replication at later infection times, we used gene array analysis to profile the transcriptional responses of IFN-y primed R A W 264.7 cells macrophages to intracellular S. Typhimurium after infection for 4 h, 8 h, and 24 h. Hybridization of cDNA arrays indicated that M E K 1 kinase (MKK1) mRNA levels were elevated in IFN-y primed R A W 264.7 cells at 8 h post-infection (Figure 3.2 and Table 3.1) but not significantly different after 4 h (Appendix A.2). 9 8 Figure 4.2 Filamentous bacteria reside in an endosomal compartment and can be released from the macrophage. IFN-y primed R A W 264.7 cells were infected with S. Typhimurium + GFP for 24 h. Cells were permeabilized and stained with an antibody specific for the endosomal marker LAMP1 (A), or stained with an antibody specific for Salmonella LPS without permeabilization (B) to detect extracellular portions of filamentous bacteria. These images are representative of 3 independent experiments. Figure 4.3 Primary macrophages cause filamentation of intracellular Salmonella. Cells were infected in vitro (24 h) or in vivo (3 d) with S. Typhimurium expressing G F P and processed for microscopy. A . Bone marrow derived macrophage. B . Splenic macrophage infected in vitro. C . Peritoneal macrophage infected in vitro. D. J774.1 macrophage-like cell line. E . 10 p m section of infected murine spleen. F . Cel l isolated from dissociated infected murine spleen. G . S E M of infected B M D M . H. Filamentous S. Typhimurium bacterium released from infected B M D M , stained with D A P I to show chromosomes. Scale bar denotes 10 um in A - F and H , and 5 urn (250 nm inset) in G . 100 This observed modest increase (2.3 fold) in MEK1 mRNA after 8 h of S. Typhimurium infection was confirmed by northern blot analysis. As seen in Figure 4.4a, MEK1 mRNA was transiently upregulated at 8 h and 18 h post-infection, was not observed prior to 8 h, and reduced to the baseline level measured in uninfected cells at 24 h (n=3). The increase in MEK1 mRNA 8 h after infection ranged from 1.2-2.5 fold relative to uninfected cells in each of 8 experiments (Figure 4.4b). We observed similar kinetics in the increase in MEK1 mRNA abundance in cells stimulated with 1 pg/ml S. Typhimurium lipopolysaccharide for 8 h or 24 h (data not shown). This increase in MEK1 mRNA after infection for 8 h was abrogated when cells were treated with the M E K kinase inhibitor U 0126 prior to infection, suggesting that transcriptional upregulation of MEK1 is mediated by prior kinase activity (Figure 4.4a and quantification in Figure 4.4c). While activation of M E K / E R K kinase cascades has previously been shown to occur within 1 h of S. Typhimurium infection or LPS stimulation (2), M E K kinase activity at much later times of infection or its transcriptional regulation following infection has not previously been reported. The observed elevation of M E K 1 mRNA level in S. Typhimurium infected IFN-y primed R A W 264.7 cells relative to uninfected cells was followed by increased MEK1 protein abundance at 24 h, as determined by western blot analysis (Figure 4.4d). A modest increase in MEK1 protein of 1.5 ± 0.2 fold was detected at 24 h post-infection when normalized to actin protein and relative to uninfected cells («=4). This is of a comparable magnitude to the induction of M E K mRNA at 8 h post-infection. At the times when increases in M E K mRNA and protein abundance were measured, M E K protein was phosphorylated, an essential step in activation of M E K kinase. M E K phosphorylation was maximal at 1 h but remained sustained at a modest level in infected cells throughout 24 h, as seen in longer exposures of Western blots (Figure 4.4d and data not shown). M E K activity could be detected throughout the infection period, as measured by Western blot analysis of phosphorylation of its downstream targets, the ERK1/2 101 Figure 4.4 S. Typhimurium infection increases MEK1 mRNA and protein in IFN^y primed RAW 264.7 cells. A. Northern blot analysis of MEK1. R N A was isolated from S. Typhimurium-infected or mock-infected IFN-y primed R A W 264.7 cells at 1 h, 2 h, 4 h, 6 h, 8 h, 18 h or 24 h following infection. The label 8 h + U 0126 denotes R N A isolated from cells that were pretreated with the M E K kinase inhibitor U 0126 and infected for 8 h. Northern blots were hybridized with a MEKl-specific probe and then stripped and re-probed using a GAPDH-specific probe. A representative experiment is shown (n=3). B. Quantification of northern blot analysis. Northern blot hybridization signals for MEK1 at 8 h, 18 h, and 24 h in uninfected (white bars) or infected cells (grey bars), or at 8 h in infected cells pretreated with U 0126 (black bar), were quantified by densitometry and normalized to the hybridization signals for G A P D H and to the level in uninfected cells at each time point. mRNA levels for G A P D H in uninfected cells at 8 h, 18 h, and 24 h were equivalent. The mean ± SD for the following number of independent experiments is shown: 8 h n=8, 18 h n=3, 24 h «=8. * denotes PO.01. C. Effect of kinase inhibitor on MEK1 expression. The increase in M E K 1 expression following infection for 8 h (grey bar) relative to uninfected cells (white bar) was abrogated in infected cells pretreated with the M E K inhibitor U 0126 (black bar). Northern blot hybridization signals were quantified as in B. n=3, * denotes P<0.01. D. Western blot analysis of MEK1. Protein lysates were prepared from S. Typhimurium-infected (+) or mock-treated (-) IFN-y primed R A W 264.7 cells at 1 h, 2 h, 4 h, 6 h, 8 h, or 24 h following infection and separated by SDS-PAGE electrophoresis. Western blots were probed with antibodies specific for total M E K 1 , phosphorylated M E K 1 , and total ERK1/2, to confirm equal loading of samples. A representative experiment is shown (n=3). 102 uninfected S. Typhimurium MEK1 * M nit t^o G A P D H « m ~ hour 1 8 24 1 2 4 6 8 18 24 8 B < z 2.0 1.5 E I 1.0 < G g 0 . 5 LU ^ 0 . 0 D MEK1 P-MEK1 m +U0126 2.0 f , . 5 X Q Q_ 1.0 < o 5 0.5 LU 0.0 8h 18 h 24 h time post-infection 8 h time post-infection + ERK1 ERK2 hour 8 24 Figure 4.4 S. Typhimurium infection increases M E K 1 mRNA and protein in IFN-y primed R A W 264.7 cells. 103 kinases. As seen in Figure 4.5a-c, phosphorylation of ERK1/2 was maximal within 1 h following stimulation but phosphorylation remained elevated throughout the 24 h period examined when compared to uninfected cells (quantification of ERK2 phosphorylation is shown in Figure 4.5d). MEK1 abundance and activity were similar in IFN-y primed R A W 264.7 cells infected by S. Typhimurium or stimulated with 1 pg/ml purified S. Typhimurium LPS over 24 h. Therefore, upregulated MEK1 mRNA, protein, and activity in IFN-y primed R A W 264.7 cells during a 24 h infection by S. Typhimurium can be triggered, at least in part, by bacterial LPS. 4.8 Increased M E K 1 activity correlates with bacterial filamentation. Since both M E K kinase activity and bacterial filamentation were observed at 24 h post-infection and M E K / E R K kinases are strong candidates for augmenting macrophage defenses against intracellular pathogens, we investigated if there was a connection between induction of M E K kinase signaling and bacterial filamentation. IFN-y primed R A W 264.7 cells were pretreated with the M E K inhibitor PD 98059 or D M S O as a control and infected with S. Typhimurium expressing GFP. Remarkably, M E K inhibition by PD 98059 caused a 76 ± 10% reduction in the number of cells containing predominantly filamentous bacteria (representative immunofluorescence shown in Figure 4.6a and quantification in Figure 4.6b). Similar results were obtained using U 0126, another M E K inhibitor but with a different mode of action (Figure 4.6b and data not shown) (23). Both inhibitors were functional in greatly reducing M E K activity under our experimental conditions, as determined by Western blot analysis of ERK1/2 phosphorylation (Figure 4.9 and data not shown). This suggests that MEK-dependent control of intracellular bacterial proliferation is mediated through impairment of bacterial cell division, resulting in filamentation. 104 Uninfected P-ERK1 P-ERK2 ERK1 ERK2 B + S. Typhimurium P-ERK1 P-ERK2 ERK1 ERK2 + LPS P-ERK1 P-ERK2 - i ERK1 ERK2 0.5 1 2 4 6 8 24 hours post-infection 1 2 4 6 hours post-infection 24 -IFN +IFN Figure 4.5 S. Typhimurium infection increases M E K 1 protein and activity. A - C . Western blots. Protein lysates were prepared from IFN-y primed R A W 264.7 cells that were mock-treated (A), infected with S. Typhimurium (B), or stimulated with 1 pg/ml S. Typhimurium LPS (C) at various times between 0.5 h and 24 h and separated by SDS-PAGE electrophoresis. Western blots were sequentially probed with antibodies specific for phosphorylated ERK1/2, to measure MEK1 activity, and total ERK1/2, to confirm equal loading of samples. These data are representative of 4 independent experiments. D. Quantification of western blot. The quantity of phosphorylated ERK2 was quantified by densitometry for uninfected (white bars), S. Typhimurium-infected (black bars), and purified S. Typhimurium LPS-stimulated cells (grey bars) and normalized to the level of total ERK2 protein. The mean and standard error of the mean (SEM) is shown (n=4). The values obtained from each independent experiments were normalized to the quantity of phospho-ERK2/total ERK2 in infected cells at 1 h to facilitate comparison between experiments. * denotes p=s0.01. E . Quantification of western blot. Salmonella infection increases E R K phosphorylation at 1 h post-infection in both naive and IFN-y primed R A W 264.7 cells. Densitometry was performed as in D. The mean ± SD is shown (n=3). 105 Figure 4.6 M E K 1 and NADPH oxidase activity correlate with bacterial filamentation. A. Fluorescence microscopy. IFN-y primed R A W 264.7 cells were seeded on glass coverslips, pretreated with either chemical inhibitors or DMSO (control) and infected with S. Typhimurium expressing GFP. After 24 h, the monolayers were fixed and the coverslips incubated with anti-Salmonella LPS antibody and a red fluorophore-conjugated secondary antibody to label extracellular bacteria. A l l bacteria shown were intracellular. The effect of various inhibitors on bacterial filamentation was assessed relative to infected cells mock-treated with DMSO. Decreased bacterial filamentation was observed in cells treated with PD 98059 to inhibit M E K kinase activity. Decreased bacterial filamentation was also observed in cells treated with DPI to inhibit ROIs. No significant inhibition of bacterial filamentation was observed in cells treated with L - N M M A to inhibit iNOS. Similar results for each inhibitor were observed in ^3 independent experiments. B. Quantification of decrease in bacterial filamentation by MEK kinase inhibitors. Cells were pretreated with each inhibitor and infected cells containing intracellular S. Typhimurium that were not labeled by the extracellularly applied LPS-specific antibody were counted. The mean percentage of cells containing predominantly filamentous bacteria ± SD is shown relative to the percentage of DMSO-treated cells, which was set to 100% (36 ± 8% of infected DMSO-treated cells contained predominantly filamentous bacteria). Pretreatment with the M E K kinase inhibitors PD 98059 or U 0126 or the oxidase inhibitors and antioxidants DPI, acetovanillone, or N-acetyl-L-cysteine significantly decreased the number of cells containing predominantly filamentous bacteria relative to D M S O treated cells (* denotes P<0.01). No significant inhibition of bacterial filamentation was observed in cells treated with L - N M M A to inhibit iNOS relative to cells treated with DMSO or the inactive enantiomer D - N M M A (P=0.05 and P=0.85 respectively). For each experiment, 100-250 infected cells were counted per condition. The number of independent experiments for each condition were as follows: DMSO n=\0, PD 98059 n=9, U 0126 n=4, DPI n=5, N-acetyl cysteine n=3, acetovanillone n=3, L - N M M A n=4, D-N M M A n=3. 106 Figure 4 . 6 M E K 1 and N A D P H oxidase activity correlate with bacterial filamentation. 107 4.9 MEK1 activity controls intracellular bacterial numbers. To confirm the morphological impairment of bacterial replication revealed by fluorescence microscopy using an independent assay, we counted the number of CFUs isolated from infected cells treated with DMSO or M E K inhibitor PD 98059 after 24 h. When M E K activity was inhibited in IFN-Y-primed R A W 264.7 cells, we observed a significant (3-fold) increase in the number of intracellular S. Typhimurium that could form colonies on solid media (Figure 4.7). Similar results were obtained using the M E K inhibitor U 0126 (data not shown), further supporting our observation that control of intracellular bacterial numbers results from increased M E K activity. Neither M E K inhibitor altered internalization of bacteria, as the number of intracellular C F U at 3 h post-infection was comparable between inhibitor-treated and untreated cells (Figure 4.7). Both M E K inhibitors were active, reducing ERK1/2 phosphorylation to the basal levels observed by western blotting in uninfected cells (Figure 4.9 and data not shown). It is not known whether filamentous bacteria form colonies on solid media (LB agar plates), therefore it is possible that the MEK-dependent impairment of bacterial cell division within R A W 264.7 cells and the MEK-dependent inhibition of the number of bacteria able to replicate outside of a host cell are distinct events. ^ 4.10 Phagocyte NADPH oxidase also mediates bacterial filamentation. We proceeded to investigate a mechanism to explain the effect of M E K kinase activity on impairing bacterial replication. The antibacterial effectors phox and iNOS were strong candidates for mediating bacterial stress and inducing filamentation. Both reactive oxygen and nitrogen species can inhibit S. Typhimurium survival in macrophages in vivo (9, 10). ROIs produced by phox can positively regulate M E K kinase activity and phox and iNOS can be activated by M E K / E R K signaling (24-29). The iNOS inhibitors L - N M M A and L - N A M E had no 108 2.0 n Figure 4.7 M E K 1 activity controls S. Typhimurium replication. IFN-y primed R A W 264.7 cells were pretreated with PD 98059 (MEK inhibitor, filled bars) or DMSO (control, white bars) and then infected with S. Typhimurium. Extracellular bacteria were removed after 30 min by washing and remaining bacteria were killed using gentamicin. At 3 h and 24 h following infection, monolayers were lysed with detergent and intracellular bacteria enumerated by plating dilutions on solid media. The mean ± SD is shown. These data consist of 5 independent experiments with 3 wells plated in triplicate per experiment; * denotes P<0.001. 109 significant effect on bacterial morphology when compared to inactive D - N M M A or DMSO, respectively (Figure 4.6 and data not shown). In addition, L - N M M A did not have a synergistic effect when applied with various antioxidants, although L - N M M A was functional in decreasing iNOS activity and the corresponding concentration of extracellular nitrate by the Griess assay (data not shown). By contrast, numerous N A D P H oxidase inhibitors and antioxidants had a similar effect to the M E K inhibitors in reducing bacterial filamentation in IFN-y primed R A W 264.7 cells (representative immunofluorescence shown in Figure 4.6a and quantification in Figure 4.6b). The inhibitor DPI, which lowers ROI levels and increases intracellular levels of the antioxidant glutathione, reduced the number of cells containing predominantly filamentous bacteria by 97 ± 5%. Because DPI also inhibits iNOS activity, we used a variety of other chemical inhibitors of oxidative burst to confirm the involvement of oxidase activity in mediating bacterial filamentation. The antioxidant N-acetyl-L-cysteine and the phox flavoprotein inhibitor acetovanillone reduced the number of these filamentous bacteria-containing cells by 86 ± 12%, and 53 ± 13%, respectively. 4.11 M E K kinase and phox activities at later times mediate bacterial filamentation. As seen in Figure 4.5, phosphorylation of ERK1/2 are maximal within 1 h of infection but remain elevated for 24 h. To determine whether this sustained activity plays a role in mediating bacterial filamentation, distinct from the early maximal kinase activation, the M E K inhibitor U 0126 was added to infected IFN-y primed R A W 264.7 cells 1 h, 2 h, 4 h, 6 h, or 8 h post-infection and compared to cells treated with inhibitors prior to infection. Interestingly, U0126 significantly reduced the number of cells containing predominantly filamentous bacteria relative to DMSO when added up to 8 h after infection rather than pre-infection (Figure 4.8a). Similar results were observed when the antioxidant DPI was added post-infection. As shown in 110 A 30% Figure 4.8 M E K kinase and phox activities at later times mediate bacterial filamentation. A . The M E K inhibitor U 0126 was added to infected IFN-y primed R A W 264.7 cells 1 h, 2 h, 4 h, 6 h, or 8 h post-infection and compared to cells treated with inhibitors prior to infection (0 h) or treated with DMSO. Some cells were treated with U 0126 for the first 8 h of infection and then washed to remove the inhibitor for the remaining 16 h of infection (8 h chase). B. Cells were treated as in A , except that the antioxidant DPI was used. For both A and B, the percentage of cells containing predominantly filamentous bacteria after infection for 24 h was counted. The mean ± SD are representative of 3 independent experiments, with >100 cells counted per condition per experiment; * denotes P<0.01. I l l Figure 4.8b, DPI added up to 4 h post-infection was as potent in decreasing bacterial filamentation as cells pretreated with inhibitors. Inhibition of bacterial filamentation was also observed in cells treated with the M E K inhibitor PD 98059 or antioxidant N-acetylcysteine 6 h post-infection (data not shown). Furthermore, cells treated with U 0126 or DPI for the first 8 h of the infection and then removed by washing exhibited a similar degree of bacterial filamentation to cells not treated with either inhibitor (Figure 4.8a-b). Taken together, these data suggest that later M E K kinase and phox activities are primarily responsible for mediating bacterial filamentation and can be dissociated from the rapid M E K and phox activities following S. Typhimurium infection, which are maximal at 1 h. 4.12 M E K kinase and phox activities appear to function in parallel to mediate bacterial filamentation. Phox activity produces ROIs that can enhance M E K kinase activity (25, 26). To assess whether the oxidase induces bacterial filamentation by increasing M E K kinase activity, we treated IFN-y primed R A W 264.7 cells with DPI prior to and during S. Typhimurium infection and measured E R K phosphorylation relative to untreated cells. Antioxidant treatment did not reduce M E K kinase activity, as detected by phosphorylation of the downstream E R K kinases at 8 h (data not shown) or 24 h (Figure 4.9 and data not shown). In addition, DPI did not attenuate the increase in total M E K kinase protein after 24 h of infection relative to uninfected cells (data not shown). In contrast, the M E K kinase inhibitors PD 98059 and U 0126 substantially reduced E R K phosphorylation (Figure 4.9 and data not shown). These data suggest that phox activity does not augment M E K kinase activity either prior or subsequent to the induction of bacterial filamentation within R A W 264.7 cells. 112 P-ERK1 P-ERK2 ERK1 E R K 2 B DMSO D M S O PD98059 DPI + S. Typhimurium CM 4 X. CL - 3 S o cc LU Q .1 I I I DMSO DMSO PD98059 DPI + S. Typhimurium Figure4.9 N A D P H oxidase does not mediate filamentation by modulating E R K phosphorylation. A . Western blot. Protein lysates were prepared from IFN-y primed R A W 264.7 cells pretreated with DMSO or various inhibitors that were either S. Typhimurium-infected or mock-treated for 24 h and then separated by SDS-PAGE electrophoresis. Western blots were probed with antibodies specific for phosphorylated E R K 1/2 as an indicator of MEK1 activity and total ERK1/2 to confirm equal loading of samples. B . Quantification of western blots. The level of phosphorylated ERK2 was quantified by densitometry and normalized to the level of total ERK2. The mean ± SD are representative of 4 independent experiments; * denotes P<0.01. 113 To assess whether M E K kinase activity mediates bacterial filamentation by positively regulating oxidase activity (24, 29), we measured the effect of various inhibitors on intracellular ROIs in infected cells. A luminol-based chemiluminescence assay detected elevated levels of intracellular ROIs within IFN-y primed R A W 264.7 cells after 6 h of infection by S. Typhimurium, relative to uninfected cells. DPI and N-acetyl-L-cysteine were effective in significantly decreasing the products of phox activity (Figure 4.10a). However, treatment with the M E K kinase inhibitors U 0126 or PD 98059 did not significantly reduce intracellular ROIs (Figure 4.10b and data not shown). Elevated ROIs were measured within infected cells at 24 h, when bacterial filamentation is observed, which were similarly reduced by antioxidants and unchanged by inhibition of M E K kinase activity (Figure 4.10c). These data suggest that M E K kinase activity does not alter oxidase activity and intracellular ROIs either prior to or during the presence of filamentous bacteria. 114 Figure 4.10 M E K kinase does not mediate filamentation by increasing intracellular ROIs. A . Chemical inhibitors decrease intracellular ROIs. IFN-y primed R A W 264.7 cells (1 x 106 cells) were pretreated with inhibitors or D M S O (n=5) and harvested 6 h post-infection. Intracellular ROIs were detected using a luminol chemiluminescence assay. Chemiluminescence (light) units were quantified every min for 20 min and the mean light units detected per minute over this time period ± SD is shown. Infection caused a significant increase in intracellular ROIs (n=5) which was decreased by the inhibitors diphenylene iodonium (DPI, n=5), and N-acetyl cysteine (NAC, n=3). The inhibitor acetovanillone (AV, n=4) had a modest effect while ascorbic acid (AA, n=3) had no effect on decreasing intracellular ROIs. * denotes P<0.01 relative to uninfected cells. B. Intracellular ROIs 6 h post-infection. Measurement of intracellular ROIs was performed as described in A . Infection caused a significant increase in intracellular ROIs compared to uninfected cells, which was not significantly altered by treatment with the M E K inhibitor U 0126. The oxidase inhibitor DPI significantly reduced intracellular ROIs within infected cells when compared to DMSO-treated infected cells. The mean ± SD is shown and represents duplicate samples from at least 3 independent experiments; * denotes P<0.01. C. Intracellular ROIs 24 h post-infection. Cells were harvested 24 h after infection and ROIs detected as described in A. 115 DMSO DMSO NAC + S. Typhimurium DMSO DMSO U0126 100 <D 80 (J § 60 w o .£ 40 20 + S. Typhimurium 24 h * I DMSO DMSO DPI U0126 + S. Typhimurium Figure 4.10 M E K kinase does not mediate filamentation by increasing intracellular ROIs. 116 4.13 Discussion. In the murine model of human typhoid fever, Salmonella Typhimurium establish a niche within macrophages where they can replicate and cause a systemic disease. Disease is mediated by a dynamic interplay between host responses to bacterial components and bacterial virulence mechanisms that are triggered upon entry into the host environment. We previously used gene arrays to profile the responses of the R A W 264.7 murine macrophage cell line to S. Typhimurium at 4 h post-infection and demonstrated that most of the macrophages' early transcriptional responses to S. Typhimurium could be triggered by purified S. Typhimurium LPS and altered by priming with IFN-y (16). IFN-y priming of macrophages restricts intracellular S. Typhimurium replication but the precise mechanisms for this control, including a role for M E K / E R K signaling, are unclear (20). We therefore examined macrophage signaling upon infection with S. Typhimurium to probe the host's efforts to limit intracellular bacterial replication and survival. To this end, we used gene array analysis to examine the transcriptional responses of IFN-y primed R A W 264.7 macrophages to intracellular S. Typhimurium at later times (8 h) post-infection. At this time point, bacteria have initiated virulence factor expression specific to the intracellular environment and are beginning to replicate within naive R A W 264.7 cells (30). We observed that MEK1 kinase mRNA levels were transiently elevated in IFN-y primed R A W 264.7 macrophage cells at 8 h post-infection, which was confirmed by northern blot analysis and followed by elevated M E K 1 protein levels at 24 h post-infection. Our observation that inhibition of M E K activity abrogated the increase in M E K mRNA levels 8 h after infection supports a connection between early kinase activity and subsequent transcriptional upregulation. However, the delayed inhibitor addition experiments shown in Figure 4.8 suggest that it is rather the later sustained kinase activity that mediates bacterial filamentation. This prolonged activation of M E K kinase activity observed throughout the 24 h infection period by 117 phosphorylation of ERK1/2 may result from continued shedding of LPS by intracellular bacteria (31). Alternatively, a feedback mechanism of enhancement of M E K activity has been previously observed, both directly by M E K 1 activity, and indirectly, by ROI signaling that can be modulated by M E K activity (25). While the rapid activation of M E K kinase following LPS stimulation is downregulated by specific phosphatases, increased transcription of M E K kinase at later infection time points could contribute to the prolonged levels of M E K activity. The importance of M E K kinase signaling in effective host response to bacteria is highlighted by the evolution of a MEK-specific phosphatase that is required by Yersinia to colonize host cells. In macrophages, signals transmitted through M E K / E R K kinases are known to induce cell proliferation, differentiation, and the expression of proinflammatory genes such as TNF-a (5). M E K can exert its pleiotropic effects on cells by two general mechanisms. First, M E K / E R K signaling has a large number of downstream targets including multiple transcription factors, phox and iNOS, while a functional proteomics study recently identified an additional 20 previously unrecognized M E K / E R K effectors (32). Second, the kinetics of M E K activity impacts the functional effect on the cell. For example, M-CSF causes maximal induction of E R K activity in macrophages after 5 min, leading to cell proliferation. In contrast, LPS stimulation induces maximal E R K activity after 15 min, arresting proliferation and promoting macrophage activation (33, 34). In addition to the previously reported early activation of M E K / E R K cascades, in this study we have shown that Salmonella also induce M E K kinase activation at later time points of infection. We have demonstrated that M E K inhibitors can be added 8 h after infection and still inhibit bacterial filamentation. In addition, chemical inhibition of M E K kinase signaling for only the first 8 h of infection results in the same extent of bacterial filamentation after 24 h as cells with functional M E K kinase activity throughout the entire infection. Together, this suggests that the sustained M E K activity at later time points plays a 118 more important role in stressing intracellular bacterial replication than the early induction of M E K activity that peaks at 1 h. Interestingly, inhibition of M E K signaling has the opposite effect in epithelial cells infected by influenza virus (35). In this infection model, intact M E K signaling is necessary for viral replication as it controls nuclear export of viral ribonucleoproteins and the M E K inhibitor U 0126 impaired viral production. M E K inhibitors added at 4 h after infection still substantially inhibited replication, providing another example of the dissociation of early E R K activation from later signaling events. M E K signaling appears to be playing a distinct role in macrophages infected by S. Typhimurium. Our results emphasize the importance of studying host responses to S. Typhimurium infection at times following the initial interactions between bacteria and macrophage since distinct host responses can occur at different times during the infection. Bacteria respond to stresses such as oxidative stress (8), nutrient stress (36), D N A damage (22), and some antibiotics (21, 37) by arresting D N A replication and/or cell division. Filamentous uropathogenic E. coli have been observed during infection of bladder epithelial cells (38). Filamentation or arrest of bacterial septation has been observed in S. Typhimurium infection of other cell lines. Mouse and rat fibroblast cell lines, which do not permit replication of S. Typhimurium, interfere with bacterial cell division and result in filamentation (39). Recently, Martinez-Lorenzo et al. observed non-septate S. Typhimurium in a variety of human cancerous skin-related cell lines and primary melanocytes that also do not permit bacterial replication. These bacteria were exocytosed, non-invasive, and it was suggested that filamentation may facilitate antigen presentation, but neither the host nor bacterial cell signaling responsible for this effect on the bacteria was described (40). We also observed in macrophages that filamentous bacteria were non-invasive (data not shown). Furthermore, we observed that a reduction in the number of filamentous bacteria following treatment with M E K kinase inhibitors correlated with an increased intracellular load of viable bacteria. Therefore, M E K kinase and 119 phox activity contribute to the macrophage's ability to contain intracellular bacterial numbers by interrupting S. Typhimurium replication, which impairs the infectious cycle. This is one of the first examples of a candidate gene identified by array hybridization for which a functional consequence for host response to infection has been characterized. Bacteria within the Salmonella-containing vacuole are subject to numerous stresses, including oxidative and nitrosative chemistry and limitation of necessary cations and nutrients (8).. The relative contribution of other host stressors found within the Salmonella-containing vacuole on bacterial replication remains to be determined. In our model, infection of IFN-y primed macrophages by S. Typhimurium triggers both M E K kinase signaling and N A D P H oxidase activity that can each limit bacterial replication. This effect is manifested at later time points and is distinct from the rapid M E K activation and oxidative burst triggered in macrophages by LPS and phagocytosis. Assembly of the N A D P H oxidase enzyme complex can be regulated by M E K kinase activity, since the inhibitor PD 98059 attenuates superoxide production within neutrophils (18). Conversely, ROIs can induce M E K kinase activity (25). Our results suggest that M E K kinase and N A D P H oxidase likely function in parallel to mediate bacterial filamentation, as inhibition of neither M E K or oxidase activity attenuated activity of the other (Figure 4.11). To further test for an interaction between M E K and phox in mediating bacterial filamentation, we measured filamentation in cells treated with suboptimal concentrations of both U 0126 and DPI to determine whether there was synergy between M E K and phox activities. In preliminary experiments, two different suboptimal concentrations of U 0126 and DPI resulted in a higher percentage of IFN-y primed R A W 264.7 cells containing predominantly filamentous bacteria than when cells were treated with both inhibitors simultaneously. Further investigation is required to characterize how MEK-dependent 120 1 Figure 4.11 Working model for signaling in RAW 264.7 cells mediating filamentation of S. Typhimurium. R A W 264.7 cells infected by S. Typhimurium or stimulated by purified LPS activate both M E K kinase activity, resulting in phosphorylation of the E R K 1/2 kinases, and phox activity, resulting in increased intracellular ROIs. M E K kinase and phox appear to function in parallel to inhibit bacterial replication and induce bacterial filamentation, an indicator of bacterial stress. 121 signaling and phox-dependent ROIs impair bacterial replication and induce filamentous morphology. In addition to their direct antibacterial properties, ROIs can also act as signaling molecules and are potent stimulators of many signal transduction cascades in macrophages (41, 42). Phox is required for effective host resistance against S. Typhimurium in the murine typhoid model (10). Early in infection, virulent S. Typhimurium actively secretes one or more virulence proteins that block assembly of a functional multi-subunit phox enzyme on the membrane of the Salmonella-containing vacuole to avoid direct oxidative damage. (43). However, we show that at later infection times, phox activity correlates with bacterial filamentation, an indicator of cell stress. Therefore, while S. Typhimurium alters its gene expression upon entering a macrophage to protect itself from direct oxidative damage, the macrophage continues to produce ROIs that may exert antibacterial effects later in infection by an indirect mechanism, perhaps by altering the cellular redox state and subsequent cell signaling. A recent study by Ehrt et. al. (44) provides evidence to support this concept. Using gene array expression profiling of macrophages from normal and phox-deficient mice, they observed that 484 differentially expressed genes following Mycobacterium tuberculosis infection and/or IFN-y stimulation were phox-dependent. 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Reprogramming of the Macrophage Transcriptome in Response to Interferon- gamma and Mycobacterium tuberculosis. Signaling roles of nitric oxide synthase-2 and phagocyte oxidase. J Exp Med 194:1123. 126 Chapter 5 Interplay between antimicrobial effectors: A macrophage antimicrobial peptide impairs intracellular Salmonella replication. 5.1 Preface. This chapter was previously published in part as: C M . Rosenberger, R.L. Gallo, and B.B. Finlay. Interplay between antibacterial effectors: A macrophage antimicrobial peptide impairs intracellular Salmonella replication. 2004. Proceedings of the National Academy of Sciences. 101(8): 2422-2427. 5.2 Summary. Antimicrobial peptides have an established and important role in the defense against extracellular infections, but the expression of cationic peptides within macrophages as an antibacterial effector mechanism against intracellular pathogens has not been demonstrated. Expression of the murine cathelicidin C R A M P in macrophages was increased following infection by the intracellular pathogen Salmonella Typhimurium, and this increase required reactive oxygen intermediates (ROIs). Using CRAMP-deficient mice or synthetic C R A M P peptide, we found that C R A M P impairs Salmonella cell division in vivo and in vitro, resulting in long filamentous bacteria. This impaired bacterial cell division was also dependent on intracellular elastase-like serine protease activity both within macrophages and in a cell-free in vitro system, either by a direct mechanism or by proteolytic activation of the cathelicidin. A peptide-sensitive Salmonella mutant showed enhanced survival within macrophages derived from CRAMP-deficient mice, indicating that Salmonella can sense and respond to cationic peptides in the intracellular environment. While cationic peptides have been hypothesized to have activity against pathogens within macrophages, this work provides experimental evidence that the macrophage's antimicrobial arsenal includes cathelicidins. These results show intracellular ROIs and proteases regulate macrophage C R A M P expression and activity to impair 127 the replication of an intracellular bacterial pathogen, and highlights cooperativity between macrophage antibacterial effectors. 5.3 Introduction. Macrophages comprise an essential part of the innate immune response to bacterial infections (1). Since macrophages are highly phagocytic and are actively targeted by pathogenic bacteria, they must have effective mechanisms for either killing bacteria or controlling their replication to avoid becoming a reservoir of infection. Salmonella Typhimurium is a bacterial pathogen that resides within murine splenic and liver macrophages (2, 3), causing systemic disease in susceptible mice resembling typhoid fever in humans. This pathogen counters macrophage antibacterial effectors with acid tolerance and perturbation of endosomal trafficking, to avoid oxidative and nitrosative damage and phagolysosomal degradation (4, 5). We have observed that macrophages impair cell division of intracellular S. Typhimurium, resulting in the formation of filamentous bacteria with arrested septation (6). This morphology indicates a bacterial stress response and has been observed in bacteria responding to damage from low doses of antibiotics, starvation, and reactive oxygen and nitrogen species (7-9). We have previously shown that macrophages use a phagocyte oxidase (phox)-dependent and iNOS-independent mechanism to impair Salmonella cell division (6). Since S. Typhimurium diverts the phagocyte oxidase to minimize direct damage by ROI (4), we hypothesized that these ROIs impair bacterial cell division by regulating a previously uncharacterized antimicrobial effector mechanism(s). Macrophages possess a variety of intracellular proteases, some of which are secreted while others show activity within a phagolysosomal compartment. Studies using knock-out mice have shown that the proteases neutrophil elastase and cathepsin G have important antibacterial activities within neutrophils (10, 11), but a role for macrophage proteases during bacterial infection has not been reported. In addition to a direct microbicidal role (12), proteases with 128 elastase-like specificities proteolytically activate members of the cathelicidin family of cationic peptides, which are synthesized as inactive pro-proteins (13, 14). Mice express cathelicidin-related antimicrobial peptide (CRAMP), a cationic alpha-helical peptide with antimicrobial activity against Gram-positive and Gram-negative bacteria in vitro (13). While C R A M P expression by keratinocytes mediates control of bacterial skin infection by Group A Streptococcus (15), expression in macrophages has not been examined. S. Typhimurium possess a variety of mechanisms to resist damage by cationic antimicrobial peptides in vitro. For example, members of the PhoP/Q regulon are thought to modify LPS structure to reduce sensitivity to peptides (16), and PhoP n u" mutants, which are more susceptible to peptides in vitro (17), exhibit decreased virulence in mice (18). Since macrophages provide an intracellular niche for S. Typhimurium within secondary lymphoid organs, it is of interest to determine i f murine macrophages use cationic peptides such as C R A M P to control Salmonella replication. These studies examined whether macrophages utilize proteases and cationic peptides to limit replication of an intracellular bacterial pathogen. 5.4 Experimental Procedures. Growth Conditions of Bacterial and Macrophage Cells The Salmonella Typhimurium strain SL1344 was obtained form A T C C (Manassas, V A ) and 14028s was obtained from the Salmonella Genetic Stock Center (Calgary, AB) . 14028s Pho24 phoP c o n s t i t u t i v e mutant (kindly provided by F. Heffron, Oregon Health and Science University, OR), 14028s phoP::TnlO MS7953s PhoP n u" mutant (kindly provided by S. Miller, University of Washington, WA), and SL1344 phoP::TnlO (kindly provided by L . Knodler, Rocky Mountain Laboratories, MT) and strains expressing pFPV25.1-GFP (plasmid kindly provided by S. Meresse, Marseille, France and S. Falkow, Standford University, CA) were cultured as previously described (6). 129 R A W 264.7 macrophage-like cells (ATCC) were mycoplasma-free, cultured in D M E M + 10% FBS and used between passages 6-20. Bone marrow was isolated from the femurs of B A L B / c (Nramp_/", from which R A W 264.7 cells were derived; Jackson Laboratories, Bar Harbor, ME), 129sv (Nramp+ / +), or Cnlp"A CRAMP-deficient mice in the 129sv background (15), cultured for 7 days in non-tissue culture-treated petri dishes without antibiotics in D M E M (HyClone, Utah) supplemented with 20% heat-inactivated FBS (Invitrogen, Burlington, ON), 2 m M L-glutamine, 1 m M sodium pyruvate, and 30% L-cell conditioned media as a source of M -CSF at 37°C in 5% C02. Macrophages were frozen in 90% FBS + 10% DMSO and stored in liquid nitrogen. B M D M treated with chemical inhibitors were examined for cell death by propidium iodide, 7-AAD, and TUNEL staining (Boehringer Mannheim) and death was <10%. Mice were sacrificed by cervical dislocation and all procedures were approved by the Committee on Animal Care at the University of British Columbia. Reagents Macrophages were treated with inhibitors after infection at the following concentrations: 4 p M diphenyleneiodonium (DPI; Sigma, Oakville, ON), 250 u M acetovanillone (apocynin; Aldrich, Milwaukee, WI), 30 m M N-acetyl cysteine (Sigma), 10 m M ascorbic acid (Sigma), 100 p M AEBSF (4-(2-Aminoethyl) benzenesulphonyl fluoride; Calbiochem, La Jolla, CA) , 25 p M elastatinal (Calbiochem), 100 p M MeOSuc-Ala-Ala-Pro-Ala-CMK (human neutrophil elastase inhibitor; Calbiochem), 100 p M MeOSuc-Ala-Ala-Pro-Val-CMK (human leukocyte elastase inhibitor; Calbiochem), 1 p M bafilomycin A l (Sigma), 10 m M ammonium chloride (Sigma), 50 p M monensin. The complete mini EDTA-free protease inhibitor cocktail was used according to the manufacturer's instructions (Roche, Laval, Que). Control cells were treated with equivalent volumes of D M S O per mL of media. Human neutrophil elastase was purchased from Calbiochem. C R A M P peptide, corresponding to the mature C-terminal 34 aa peptide, was 130 synthesized according to published methods by the Protein Services Laboratory at The University of British Columbia. C R A M P was dissolved in water at 5 mg/ml stored at -80 °C in individual aliquots. Infection Conditions For immunofluorescence and C F U experiments, bone marrow-derived macrophages (BMDM) were seeded in 24 well plates ( lx lO 5 cells/well) 24 h prior to experiments and infected with S. Typhimurium for 20 min as previously described [chapter 3, (6)]. Monolayers were washed with PBS and incubated in media containing 100 pg/ml gentamicin (Sigma) for 2 h to ki l l any remaining extracellular bacteria, and then maintained with 10 pg/ml gentamicin. Intracellular survival/replication of S. Typhimurium was determined using the gentamicin-resistance assay, as previously described (6). For C F U enumerations, wells were washed 3x with PBS, lysed with PBS containing 1% Triton-X-100, 0.1% SDS, and serial dilutions were plated on L B agar. Immunofluorescence B M D M were seeded on 12 mm-diameter glass cover slips in 24 well plates 24 h prior to infection. Following infection with S. Typhimurium expressing GFP for 24 h, cells were fixed with 2.5% paraformaldehyde, mounted in Mowiol (Aldrich), and examined using a Zeiss Axioskop epifluorescence microscope. Immunofluorescence staining was performed as previously described [chapter 3,(6)] using rabbit anti-5. Typhimurium LPS Ab at 1:200 (Difco, Detroit, MI) without permeabilization to detect extracellular bacteria,. or using polyclonal rabbit anti-CRAMP Ab at 1:150 (19) in the presence of 0.2% saponin. A n Alexa 568-conjugated mouse anti-rabbit secondary Ab was used at 1:200-1:400 dilution (Molecular Probes, Eugene, OR). To quantify cells containing filamentous bacteria, only intracellular S. Typhimurium were 131 counted (not labeled by the extracellular LPS-specific Ab). Bacteria were scored as "filamentous" when they were >3x longer than a typical bacterium (approximately >5 urn). To assess protease activity, B M D M were incubated with 10 u M CBZ-Ala-Ala-Ala-Ala-rhodamine 110 (Calbiochem) for the last 2 h of infection. Confocal analysis was performed using a Zeiss Axiovert S100 TV microscope attached to a Bio-Rad Radiance Plus confocal microscope (63x objective). Images were acquired using Lasersharp software (Bio-Rad, Mississauga, ON) and sections of 0.1 pm thickness were assembled into flat projections using NIH Image and imported into Adobe Photoshop. To stain D N A , cells were incubated with 1 pg/ml diamidino-2-phenylindole (DAPI; Sigma), 30 p M SYTO 9 (Molecular Probes) or 30 p M propidium iodide (Molecular Probes) in PBS for 10 min protected from light, and washed with PBS before mounting. Scanning electron microscopy Cells on glass cover slips were washed gently with PBS, fixed with 2.5% gluteraldehyde in 0.1 M cacodylate buffer pH 7.4 for 30 min at 37°C. Cells were washed for 30 min in 0.1 M cacodylate buffer containing 1% tannic acid, treated with 1% osmium tetraoxide in 0.1 M cacodylate buffer, and dehydrated in a series of ethanol washes. After critical point drying, samples were coated with gold, mounted on aluminum stubs, stored under desiccation, and viewed on a Nikon scanning electron microscope. Zymogram for Protease Activity B M D M (lxlO 6 ) were lysed into 100 pi boiling Laemeli sample buffer and 30 pi of total protein was resolved on a 12% acrylamide SDS-PAGE gel containing 0.5 mg/mL MeOSuc-Ala-Ala-Pro-Val-pNA (Colorimetric elastase substrate I, Calbiochem). Proteins in the gel were renatured overnight at 37 °C in 20 m M sodium phosphate buffer pH 8.0 containing 0.1% Triton-132 X-100 and 10 m M MgCb. Gels were subsequently stained with Coomassie Blue R250 to visualize total proteins and molecular weights were calculated using Alphalmager software (Alpha Innotech, San Leandro, CA). Flow Cytometry Staining buffer consisted of PBS+2% FBS+5 m M EDTA+0.1% sodium azide+0.2% saponin. B M D M were stained sequentially with rabbit anti-CRAMP Ab (1:150) and goat anti-rabbit PE secondary Ab (1:200) for 30 min each on ice. Cells were stained for viability after infection by measuring exclusion of 7-AAD (20 pg/ml; BD Biosciences, San Jose, CA). Flow cytometry was performed using a FACSCaliber (BD Biosciences) with CellQuest software and 10 000 events were counted per sample. In vitro Filamentation Assay Stationary phase bacteria were diluted 1:40 in N-minimal media pH 7-4 or pH 5.8 containing 0.1% Casamino acids, 0.3% v/v glycerol, and 8 p M MgCl2, and concentrations of synthetic active C R A M P peptide or macrophage lysates as indicated. Cultures were incubated overnight at -37°C with shaking and examined by microscopy. To quantify the extent of bacterial filamentation, cultures were prepared as above in 96 well micro titer plates and the culture OD at 560 nm was measured every 20 min for 16 h using a Spectrafluor Plus spectrophotometer ( T E C A N , Austria) and data evaluated using Magellan Software (TECAN). To prepare macrophage lysates, R A W 264.7 cells were lysed using a teflon dounce homogenizer, centrifuged at 500 rpm for 12 min to remove nuclei and unbroken cells, the post-nuclear supernatant freeze-thawed 3 times on methanol-dry ice, sonicated, and centrifuged at 14 000 rpm for 12 min to remove debris (20). Protein concentration was quantified by Bradford assay (BioRad). 133 Statistics Significance was determined by calculating P values using an unpaired 2-tailed t test. P values <0.01 were considered significant. 5.5 Macrophages Impair.Salmonella Cell Division Using an Oxidase-Dependent Mechanism. When primary macrophages are infected with S. Typhimurium, there is a decrease in the number of viable intracellular bacteria within the first few hours of infection, and then the size of this surviving population remains relatively stable over the next 20 h (21, 22). Many of these surviving bacteria exhibited impaired cell division and were unable to complete septation, resulting in filamentous bacteria after 24 h. We previously described, using R A W 264.7 murine macrophage-like cells, that macrophage impairment of bacterial cell division is dependent on ROI and M E K kinase signaling and independent of RNI (6). This phenotype was also observed in B M D M (Figure 5.1 and data not shown). A significant decrease in the number of filamentous bacteria occurred in cells treated with diphenylene iodonium (DPI), a chemical inhibitor of ROIs (Figure 5.1, DPI panel). A similar inhibition of bacterial filamentation was observed using two other antioxidants, N-acetyl cysteine and acetovanillone (data not shown). In addition, M E K kinase inhibitors significantly inhibited the ability of B M D M to impair bacterial cell division. While the mechanism for M E K kinase-mediated impairment of Salmonella cell division remains to be elucidated, ROI are strong candidates for directly stressing bacteria and impairing cell division. However, S. Typhimurium delivers proteins into infected macrophages, using a secretion apparatus encoded on the Salmonella pathogenicity island 2 (SPI2), which inhibit functional assembly of phox on the Salmonella-containing vacuole (SCV) (4). Bacterial A. DMSO U0126 DPI G F P Phase Contrast B. < * 'i v.-0% Cells with Filamentous Bacteria 20% 40% 60% 80% 100% D M S O PD 98059 H * DPI 1 * Figure 5.1 Filamentation is dependent on M E K kinase signaling and oxidants in B M D M . B M D M were pretreated with M E K kinase inhibitor (U0126 or PD 98059) or antioxidant (DPI), infected with S. Typhimurium + GFP for 24 h, and processed for microscopy. A . Fluorescence microscopy. Fewer bacteria are filamentous in cells treated with M E K kinase inhibitor or antioxidant relative to mock-treated cells (DMSO). B. Quantification. The percentage of infected macrophages containing filamentous bacteria were quantified in at least 100 infected cells per experiment. The mean percentage of infected DMSO-treated cells containing filamentous bacteria ± SD (24 ± 5%, n=6) was normalized to 100%. * denotes pO.Ol , m»4. 135 filamentation within macrophages was not dependent on SPI2, since no significant difference in the number of cells containing filamentous bacteria was observed when cells were infected with wild type bacteria, which avoid co-localization with phox, or a SPI2 secretion mutant, which does not divert phox (Figure 5.2). In addition, while inhibiting M E K kinase increases the number of wild type C F U within macrophages, it did not repair the replication defect of a SPI2 secretion mutant. Since S. Typhimurium avoids close association with phox, and ROIs must be produced near their target to be most effective, we hypothesized that the stressor was not direct oxidative damage but rather an effector regulated by ROIs. 5.6 Intracellular Protease Activity Mediates Impaired Salmonella Cell Division. Neutrophil elastase and cathepsin G activity are regulated by ROIs within early neutrophil phagosomes, and these proteases are important for killing phagocytosed Gram-negative bacteria (11). We investigated whether protease activity could be the ROI-regulated effector mechanism that causes bacterial filamentation within macrophages. We treated R A W 264.7 cells with a proprietary mixture of protease inhibitors (Roche) and observed a significant decrease in the number of infected cells containing filamentous bacteria (Figure 5.3a). To determine the pharmacologic characteristics of the protease activity or activities correlating with impaired bacterial cell division, cells were treated with individual specific inhibitors. Macrophages treated with the protease inhibitors pepstatin (aspartic proteases), T L C K (trypsin-like serine proteases), TPCK (chymotrypsin-like serine proteases), leupeptin (cysteine proteases), or aprotinin (serine proteases) contained filamentous bacteria and were indistinguishable from mock-treated cells (data not shown), although the permeability or uptake of these inhibitors was not determined. In contrast, a significant decrease in the number 136 • DMSO • PD 98059 B. w t ssaR 1.5 CD O I 1 o CO CE 0.5 • DMSO • PD98059 T , T w t r, . • , ~. • ssaR Bacterial Strain Figure 5.2 Filamentation is independent of SPI2-dependent virulence factor secretion. A. No significant difference was observed in the number of infected IFN-y primed R A W 264.7 cells containing filamentous bacteria when infected with wild type S. Typhimuirum (wt) or mutants deficient for SPI2-secretion (AssaR). A significant reduction in the number of cells containing filamentous bacteria was observed in cells treated with PD 98059 to inhibit M E K kinase activity relative to DMSO-treated cells, which was independent of functional SPI2 secretion (p<0.01). Mean ± SD is shown for 3 independent experiments (>100 cells counted per experiment). * denotes p<0.01. B. IFN-y primed R A W 264.7 cells were pretreated with PD 98059 or DMSO and infected with S. Typhimurium. Extracellular bacteria were removed after 30 min by washing and remaining bacteria were killed using gentamicin. At 3 h and 24 h following infection, monolayers were lysed with detergent and intracellular bacteria enumerated by plating serial dilutions on solid media. Treatment of cells with M E K kinase inhibitor significantly increased the number of intracellular wt bacteria after 24 h but did not alter the number of bacteria internalized (data not shown). The replication defect of the SPI2 secretion mutant (AssaR) was not repaired by M E K kinase inhibition. The number of intracellular bacteria was divided by the number of macrophages seeded in each well. The mean ± SD of 5 independent experiments performed in duplicate is shown. * denotes p<0.01. 137 Figure 5.3 Serine protease inhibitors decrease bacterial filamentation in macrophages. A . Quantification of Fluorescence. R A W 264.7 cells were pretreated with inhibitors, infected with S. Typhimurium expressing GFP for 24 h, and examined by fluorescence microscopy. The mean percentage of infected DMSO-treated cells containing filamentous bacteria ± SD (33 ± 7%, n=7) was normalized to 100%. There was a decrease in the number of filamentous bacteria in cells treated with a protease inhibitor cocktail or an inhibitor specific for serine proteases (AEBSF). * denotes p O . O l , n=3-7. B. Fluorescence Microscopy. B M D M were treated as in A and then examined by fluorescence microscopy. Mock-treated cells (DMSO) contained filamentous bacteria (GFP DMSO panel). There was a decrease in the number of filamentous bacteria in cells treated with chemical inhibitors of serine proteases (AEBSF) or a more specific elastase-like serine protease inhibitor (MeOSuc-AAPA-CMK). n;>4. C. Quantification. Cells were treated with an inhibitor of serine proteases (AEBSF) or a more specific elastase-like serine protease inhibitor (elastatinal, MeOSuc-AAPV-CMK, or MeOSuc-A A P A - C M K ) and the percentage of infected macrophages containing filamentous bacteria were quantified in at least 100 infected cells per experiment. The mean percentage of infected DMSO-treated cells containing filamentous bacteria ± SD (24 ± 5%, n=6) was normalized to 100%. * denotes p O . O l , na4. 138 0% Cells with Filamentous Bacteria 20% 40% 60% 80% DMSO Inhibitor Cocktail A E B S F H * B. DMSO AEBSF MeOSuc-AAPA-CMK G F P Phase Contrast / 1 * > . . . . c. 0% Cells with Filamentous Bacteria 20% 40% 60% 80% DMSO A E B S F Elastatinal MeOSuc-AAPV-CMK MeOSuc-AAPA-CMK 100% 100% I Figure 5.3 Serine protease inhibitors decrease bacterial filamentation in macrophages. 139 of R A W 264.7 cells containing filamentous bacteria was observed following treatment with the broad serine protease inhibitor AEBSF. These results were confirmed in B M D M (Figure 5.3b and 5.3c). By treating cells with more specific inhibitors of serine proteases (elastatinal, MeOSuc-AAPA-CMK, or MeOSuc-AAPV-CMK), it was determined that the protease activity correlating with filamentation exhibited elastase-like serine protease activity. As macrophages can both store and secrete proteases, we examined the location of this protease activity relative to Salmonella-containing vacuoles. B M D M infected with S. Typhimurium were examined 8 h post-infection, which is immediately prior to the onset of filamentation and when we hypothesized a putative effector mechanism would be active in impairing bacterial cell division. Cells were incubated with a cell permeable elastase substrate CBZ-Ala-Ala-Ala-Ala-rhodaminel 10 that fluoresces upon cleavage. Figure 5.4 shows that infected B M D M contain a protease activity capable of cleaving this substrate in a vesicular distribution with a perinuclear location similar to intracellular Salmonella. This fluorescence pattern was also observed in uninfected cells (Figure 5.4) and cells infected for 24 h, which contain filamentous bacteria (data not shown). Macrophages treated with the serine protease inhibitor A E B S F , which contain less filamentous bacteria (Figure 5.3), exhibit significantly decreased substrate proteolysis when the fluorescence of cleaved substrate was quantified by flow cytometry (Figure 5.4b). Treatment with the antioxidants DPI, N-acetylcysteine or acetovanillone did not significantly reduce the substrate cleavage (Figure 5.4b), which is different from the regulation of neutrophil elastase by ROIs within neutrophil phagosomes (11). Treatment with the M E K kinase inhibitor U0126 did not significantly decrease substrate fluorescence, suggesting that M E K signaling does not regulate protease activity. 140 Figure 5.4 Localization, regulation, and substrate of macrophage protease activity. A . Confocal microscopy. Macrophages were either infected with S. Typhimurium for 8 h or left uninfected, and then incubated with the cell permeable elastase substrate CBZ-AAAA-R110 for the last 2 h. .Cleavage of the protease substrate yields fluorescence at 488 nm, which is observed in a punctate perinuclear pattern (green). Intracellular S. Typhimurium was detected using an antibody specific for S. Typhimurium LPS (red). White arrows in the overlay panel indicate overlap of elastase activity with intracellular bacteria (yellow). n=4. B. Flow cytometry. Elastase activity is not blocked by antioxidants. Cells were pretreated with the serine protease inhibitors A E B S F or M e o S u c - A A P V - C M K (EII), the antioxidant diphenylene iodonium (DPI), N-acetyl cysteine (NAC), or acetovanillone (AV), or the M E K inhibitor U0126 or DMSO (control) and infected with S. Typhimurium for 8 h. Cells were incubated with the cell permeable elastase substrate CBZ-AAAA-R110 for the last 2 h and the fluorescence of the cleaved substrate was quantified by flow cytometry. The mean ± SD of the flow cytometry histogram for each infected population was compared to the fluorescence observed in uninfected cells (set to 100%). * denotes p<0.01 relative to infected DMSO-treated cells, «s:3. C. Zymogram. B M D M express multiple elastase-like protease activities. Macrophage lysates were separated by SDS-PAGE in a gel containing the colorimetric elastase-like serine protease substrate MeOSuc-Ala-Ala-Pro-Val-pNA. Proteins were renatured and white bands indicate protease activity, and the gel was subsequently stained with Coomassie blue to visualize total proteins. * indicates the molecular weight of neutrophil elastase. n=3. 142 To begin to characterize the protease(s), total cell proteins were resolved in a gel containing MeOSuc-Ala-Ala-Pro-Val-pNA, a substrate of elastase-like proteases that yields a white precipitate when cleaved. As seen in Figure 5.4c, B M D M contain multiple elastase-like protease activities that are capable of cleaving this substrate. Major bands have an apparent molecular weight of 105 kDa, 32 kDa, and 11 kDa, with minor bands of 55 kDa, 41 kDa, 13 kDa, and 8 kDa. The mobility of these proteases is different from neutrophil elastase (indicated by * in Figure 5.4c). Similar activities were observed in Salmonella-infected B M D M and R A W 264.7 cells (data not shown). 5.7 Macrophages Express the Cathelicidin C R A M P . Mechanisms by which proteolytic activity could cause this bacterial replication defect include directly damaging bacteria or by activating cationic antimicrobial peptides (23). We tested the hypothesis that a cathelicidin mediates Salmonella filamentation within macrophages, since a synthetic active peptide of indolicidin, a bovine cathelicidin, has been reported to induce bacterial filamentation in vitro (24). Mice produce a single cathelicidin named C R A M P (cathlicidin-related antimicrobial peptide). When activated by proteolytic cleavage, the peptide has microbicidal activity against S. Typhimurium (19), although its expression or biological function in macrophages has not been assessed. Using confocal microscopy and an antibody specific for both the inactive pro-protein and proteolytically active C R A M P peptide, B M D M (Figure 5.5a) and splenic macrophages infected in vivo or in vitro (data not shown) expressed C R A M P in a punctate pattern, with more intense staining in the perinuclear region. A similar pattern was observed in uninfected macrophages and was not observed in unpermeabilized cells, indicating that C R A M P is intracellular (data not shown). S. Typhimurium resides in a similar perinuclear location, with some overlap with C R A M P (Figure 5.5a, merge). Flow cytometry confirmed that C R A M P is expressed by uninfected macrophages (Figure 5.5b, yellow filled 143 C R A M P G F P - Salmonella B. Merge Merge + DIC if' Jj M \ mm • m ffl 1 2 0 a c c a tn DO CD o It 60 c GS c * 30 10' 10' 10' log CRAMP-PE Fluorescence DMSO D M S C NAC U0126 + S. Typhimurium Figure 5.5 Macrophages express the antimicrobial cathelicidin C R A M P . A . Confocal immunofluorescence. Macrophages were infected with S. Typhimurium expressing GFP (green) for 24 h and processed for immunofluorescence using a C R A M P -specific antibody (red). The C R A M P and GFP panels are flat projections of 50 optical sections and the overlay panel is composed of single confocal sections. Scale bar=5 mm. n=4. B. Flow cytometry. C R A M P expression in macrophages is upregulated by S. Typhimurium infection and modulated by ROIs. Macrophages were infected and processed as described in A , and then analyzed by flow cytometry. C R A M P expression was detected in uninfected macrophages (yellow filled curve) when compared to cells incubated with secondary antibody alone (grey dotted line). C R A M P expression was elevated in S. Typhimurium-infected macrophages (red line) and infected cells treated with the M E K inhibitor U0126 (green line), and was decreased in infected cells treated with the antioxidant N-acetylcysteine (blue line). A representative experiment is shown. C. Quantification of flow cytometry. The histogram mean±SD is shown. * denotes p<0.01 relative to uninfected cells. n=A. N A C , N-acetylcysteine. 144 curve) when compared to cells incubated with secondary antibody alone (Figure 5.5b, grey dotted line) or unpermeabilized cells (data not shown). C R A M P expression was significantly increased in macrophages following Salmonella infection (Figure 5.5b, red line) and this increase was unaffected by a M E K inhibitor (Figure 5.5b, blue line), indicating that C R A M P expression is not upregulated in a MEK-dependent manner. In contrast, the upregulation of C R A M P expression in infected B M D M was abrogated in cells pretreated with the antioxidants N-acetyl cysteine (Figure 5.5b, green line, and quantified in Figure 5.5c) or acetovanillone (data not shown). Therefore, while ROIs do not alter this macrophage serine protease activity (Figure 5.4b), they increase the abundance of a potential protease substrate, C R A M P . 5.8 CRAMP Mediates Bacterial Filamentation in vitro. A n in vitro assay was developed to determine i f chemically synthesized active C R A M P peptide can impair S. Typhimurium cell division similar to the stressed bacterial morphology (filamentation) within macrophages. As shown in Figure 5.6a, 6 p M C R A M P induced filamentous bacteria with arrested septum formation at pH 7.4. This was also observed at the predicted pH of the SCV, pH 5, although a much higher concentration of peptide relative to pH 7.4 was required to induce filamentation. To quantify this increase in bacterial length, wild type 5*. Typhimurium was cultured with increasing concentrations of C R A M P peptide. An increase in culture OD was observed between 3 p M to 10 p M (Figure 5.6b), which correlated with increasing bacterial length while C F U remained constant (data not shown). Filamentous bacteria of increasing length were observed at higher C R A M P concentrations (Figure 5.6a) but this also had a partial bacteriostatic effect, resulting in decreasing culture OD (Figure 5.6b) and C F U (data not shown). A concentration of 24 p M C R A M P was bacteriostatic, resulting in cultures that were not turbid and containing small round bacteria (Figure 5.6a). The majority of filamentous 145 Control 6 uM CRAMP 12 uM CRAMP 24 uM CRAMP pH 7.4 pH 5.0 i m p 4 » • •' ' \ , • : - ,. • / « • \ Control 75 uM CRAMP 100 uM CRAMP 200 uM AEBSF ; £ .-, . • • • . • i B. 2 4 6 8 10 12 14 16 Time (hours) Figure 5.6 C R A M P mediates Salmonella filamentation in vitro. A . Fluorescence microscopy of bacteria in vitro. 5. Typhimurium + GFP was incubated overnight in a minimal media at pH 7.4 or 5.0 containing various concentrations of synthetic active C R A M P peptide and examined by microscopy. Incubation of bacteria with AEBSF in minimal media pH 7.4 had no effect on bacterial growth or morphology. n=5. B. Quantification of filamentation. Bacteria were cultured as in A in the presence of increasing concentrations of C R A M P (pM) for 16 h and the extent of bacterial filamentation and growth arrest quantified every 20 min by optical density at 560 nm. Data are representative of n=4. 146 bacteria were viable (exclusion of propidium iodide) and many were motile (microscopic analysis; data not shown). Bacteria incubated in minimal media pH 7.4 in the presence of the chemical inhibitors used in this study were not impaired in growth or cell division (Figure 5.6a and data not shown). We have observed that filamentous S. Typhimurium, induced by incubation with synthetic C R A M P in vitro, are phagocytosed by macrophages and are rapidly killed (data not shown), suggesting that induction of filamentation interrupts the infectious cycle. 5.9 Salmonella Minimizes Filamentation Using a PhoP/Q-dependent Mechanism. Since the PhoP/Q two component regulatory system mediates resistance to other cationic antimicrobial peptides in vitro, PhoP mutants were exposed to C R A M P in vitro. As shown in Figure 5.7a, a PhoP n u 1 1 mutant, which is more sensitive to damage from other antimicrobial peptides, exhibited filamentation and the corresponding increase in optical density when cultured with 3-5 p M C R A M P . Moreover, it was highly susceptible to lower C R A M P concentrations compared to wild type S. Typhimurium, preventing an increase in culture turbidity, and yielding small round bacteria at C R A M P concentrations of 10 p M or higher (Figure 5.7b). In contrast, a PhoP c constitutive active mutant, which can modify its LPS structure and decrease its sensitivity to antimicrobial peptides in vitro (17), was able to withstand a concentration of C R A M P that is bacteriostatic for wild type S. Typhimurium (Figure 5.7a). Normal bacterial cell division and morphology of the PhoP c mutant was observed at concentrations up to 20 p M , after which C R A M P demonstrated a bacteriostatic effect (Figure 5.7b). Paralleling what was observed in vitro, many wild-type bacteria are filamentous within B M D M , while PhoP mutants are not 147 Wild type P h o P N u " P h o P c 0 uM - s - - 5- S>_ • CRAMP+ 24 h • CRAMP- 24 h wt PhoPC PtioPNull AroA SsaR SUA Figure 5.7 Salmonella minimizes filamentation using a PhoP/Q-dependent mechanism. A. Quantification of filamentation. PhoP"u" and PhoP c mutants have increased and decreased susceptibility to C R A M P , respectively. SL1344 wild type, 14028s PhoP c, and 14028s PhoP""11 bacteria were cultured in a minimal media in the presence of increasing concentrations of C R A M P for 16 h and the extent of bacterial filamentation and growth arrest quantified by optical density at 560 nm. ODs6onm at 16 h were normalized to the absorbance of bacteria cultured in parallel without C R A M P (100%). Data are representative of n=4. B. Fluorescence microscopy of bacteria in vitro and in vivo. PhoP mediates resistance to filamentation in vitro and in vivo. In the top panel, S. Typhimurium SL1344 wild type, 14028s PhoP c, and 14028s PhoP""11 were cultured in the presence of increasing concentrations of C R A M P in vitro as described in A and illustrative individual filamentous bacteria were photographed. In the bottom panels, B M D M were infected for 24 h with bacteria expressing GFP and infected cells were examined by microscopy. Scale bar=l mm for in vitro images and 2 mm for infected macrophage images. C. Quantification of bacterial CFU. Significant increase in the number of PhoPn u" bacteria at 24 h in CRAMP" macrophages. B M D M derived from CRAMP+ and CRAMP" mice were infected with the following strains of S. Typhimurium: wt 14028, wild type 14028; PhoPC, 14028 PhoP constitutively active mutant; PhoPNull, 14028 PhoP-deficient mutant; wt SL1344, wild type SL1344; AroA, SL1344 AaroA auxotroph; SsaR, SL1344 AssaR SPI2 type III secretion mutant; SifA, SL1344 AsifA virulence factor mutant. The mean ± SEM of three independent experiments performed in duplicate is shown. * denotes pO.Ol , «=6. 148 (Figure 5.7b, macrophage panels). Results were independent of bacterial strain background (data not shown). Since PhoP-regulated gene expression can protect S. Typhimurium from C R A M P in vitro, we investigated whether PhoP regulates resistance to the concentration of C R A M P contained within macrophages. B M D M from Cnlp"A CRAMP-deficient and congenic wild type mice were infected with S. Typhimurium and the numbers of C F U were enumerated at 30 min and 24 h post-infection. The presence of C R A M P did not affect the number of bacteria that were internalized by macrophages (data not shown). No difference in the number of bacteria able to grow on solid media was observed when wild type S. Typhimurium or the peptide-resistant PhoP c mutant were harvested from CRAMP" and C R A M P + macrophages after 24 h (Figure 5.7c). However, a significant increase in the intracellular C F U in CRAMP" macrophages was observed when cells were infected with the S. Typhimurium PhoP n u" mutant (Figure 5.7c). This mutant was more susceptible to impaired cell division and filamentation following in vitro incubation with C R A M P (Figure 5.7a and 5.7b). Similar results were observed using wild type and PhoP n u" mutants in an SL 1344 background (data not shown, p<0.01, n=6). In contrast, there was no difference in the number of intracellular C F U within C R A M P + or CRAMP" macrophages infected with the peptide-resistant PhoP c mutant (Fig. 4d). As well, three other bacterial mutants attenuated for intramacrophage replication, the auxotroph AaroA and the virulence factor mutants AssaR, and AsifA, are unaffected by the presence of C R A M P (Fig. 4d and data not shown) Therefore, S. Typhimurium resists the bacteriostatic activities of C R A M P by a PhoP-dependent mechanism. ' B. 100% 80% I 60% -I E 3 40% i u 1 20% -I 0% CRAMP+ CRAMP-Figure 5.8 C R A M P + C R A M P -Cooperation between CRAMP and Protease Effectors. C R A M P + + A E B S F C R A M P -+ A E B S F A . Confocal microscopy. Bacteria + GFP were incubated for 16 h in a minimal media pH 5.8 with combinations of macrophage lysate (0.5 mg/ml protein), C R A M P (100 pM), and AEBSF (500 pM). Representative flat projections of 20 0.2 pm sections are shown. n=3. B. Fluorescence microscopy. C R A M P expression correlates with bacterial filamentation in vivo. B M D M derived from C R A M P + and CRAMP" mice, with or without treatment with the serine protease inhibitor AEBSF , were infected with wild type S. Typhimurium + GFP and examined 24 h after infection. The mean percentage of infected cells containing filamentous bacteria ± SD is shown relative to the number observed in C R A M P + cells (14 ± 6%, n=5 normalized to 100%). * denotes p<0.01 relative to CRAMP+ cells, ** denotes significance relative to both C R A M P + and CRAMP" B M D M . «=4-5. Inset: Fluorescence microscopy of C R A M P T or CRAMP" B M D M infected for 24 h with S. Typhimurium + GFP. 150 5.10 CRAMP and Proteases Cooperate to Impair Salmonella Cell Division in vitro and in vivo. To assess whether macrophage proteases could act in combination with C R A M P and directly impair bacterial cell division, macrophage lysates were incubated with S. Typhimurium in vitro (Figure 5.8a). Macrophage lysate impaired bacterial cell division in a dose-dependent manner, with filamentation observed in cultures containing 0.5 mg/mL protein lysate, with decreasing activity as concentrations were lowered and bacteriostatic effects at higher concentrations. Activity of the lysate was observed when proteins were isolated at pH 5.8 but filamentation was not observed i f the lysate pH was shifted to pH 7.4 during incubation with bacteria (n=3, data not shown). Higher concentrations of C R A M P were required to induce filamentation at this lower pH, as was observed earlier (Figure 5.8). Filamentation was more dramatic when bacteria were incubated with a combination of lysate and C R A M P , even at a concentration of C R A M P that alone induced little filamentation. Filamentation was abrogated by addition of the serine protease inhibitor AEBSF (Figure 5.8a), although this inhibitor alone had no effect on bacterial morphology (Figure 5.6). To determine i f C R A M P is required to impair bacterial cell division within macrophages, B M D M were derived from Cnlp + / +and Cnlp_/"mice (15) and the bacterial morphology within infected cells examined after 24 h. As shown in Figure 5.8b, CRAMP-deficient macrophages were significantly impaired in their ability to cause filamentation of intracellular S. Typhimurium relative to cells expressing C R A M P . Since some filamentation was still observed in the absence of C R A M P , B M D M with or without C R A M P were treated with the serine protease inhibitor AEBSF prior to infection. The number of macrophages containing filamentous bacteria was reduced to a similar extent in CRAMP"1" cells treated with protease inhibitor and CRAMP" cells with intact protease activity, both of which were less than wild-type cells. CRAMP" 151 macrophages treated with AEBSF were further impaired in their ability to interrupt bacterial cell division, indicating that protease activity also mediates filamentation independently of C R A M P activation. 5.11 Role of vacuolar acidification. Neutrophil elastase activity within neutrophil phagosomes is regulated by ROIs and cations such as K + and FT/. As this macrophage protease activity was not decreased by antioxidants (Figure 5.4), experiments were undertaken to determine whether cations are involved in bacterial filamentation within the Salmonella-containing vacuole. As seen in Figure 5.9a, cells treated with the v-ATPase inhibitor bafilomycin, which blocks vacuolar acidification, contained less filamentous bacteria than cells with normal vacuolar acidification. This decrease in filamentation occurred when cells were treated with bafilomycin prior to infection or at 2 h or 8 h post-infection. This suggests that the decrease in filamentation was not a symptom-of bacteria that are deficient in early acid-induced bacterial gene expression that could be necessary for replication. Similar results were obtained in cells treated two other inhibitors of vacuolar acidification, 10 m M ammonium chloride added 8 h post-infection or 20 m M monensin added 1 h or 7 h post-infection. A decrease in bacterial filamentation was not observed in cells pretreated with valinomycin, which disrupts K + gradients (data not shown). To assess whether there is a connection between vacuolar acidification and protease activity, infected macrophages were treated with bafilomycin and incubated with the cell-permeable elastase substrate CBZ-AAAA-Rhodaminel 10 as in Figure 5.4. Bafilomycin (Figure 5.9b, thick line) decreased protease activity relative to cells with normal vATP-ase function (filled curve). In contrast, treating cells with valinomycin did not decrease protease activity (dotted line), which is in contrast to what has been observed in neutrophils. Quantification is shown in Figure 5.9c. To determine whether there is any connection between normal vacuolar 152 Figure 5.9 Role of vacuolar acidification in bacterial filamentation. A . Immunofluorescence. B M D M were infected with S. Typhimurium + GFP, treated with 1 p M bafilomycin or an equivalent volume of DMSO, and fixed 24 h post-infection. n=4. B. Flow cytometry. B M D M were treated with DMSO (control, filled curve), 1 uM bafilomycin (thick line), or valinomycin (dotted line) and infected with S. Typhimurium for 8 h. Cells were incubated with the cell permeable elastase substrate CBZ-AAAA-R110 for the last 2 h and the fluorescence of the cleaved substrate was quantified by flow cytometry. Representative of n=3. C. Quantification of flow cytometry. Cells were treated as described in B and the mean of the histogram ± SD is shown. * denotes P<0.01 relative to infected DMSO-treated cells, n=3. D. Flow cytometry. C R A M P expression was determined using a CRAMP-specific antibody and a PE-conjugated secondary Ab. B M D M were treated with DMSO and left uninfected (dotted line) or infected for 24 h with S. Typhimurium (thin line). Infected macrophages were also treated with 1 p M bafilomycin (thick line). Data are representative of n=3. 153 acidification and C R A M P expression, C R A M P expression was measured by flow cytometry. As seen in Figure 5.9d, there was an increase in C R A M P expression following S. Typhimurium infection (thin line) relative to uninfected B M D M (dotted line). Treatment of cells with bafilomycin did not decrease C R A M P expression in infected cells (thick line). 5.12 Discussion. We have elucidated a previously unknown macrophage effector mechanism for controlling the replication of a pathogenic bacterium. Our results show that S. Typhimurium infection of macrophages increases intracellular ROIs which upregulate the expression of the cationic antimicrobial protein C R A M P (Figure 5.10). ROIs are known to alter gene expression in macrophages, and the upregulation of C R A M P following infection could occur transcriptionally, as C R A M P contains N F - K B , NF-IL6, AP4, and C/EBP transcription factor binding sites upstream of the transcriptional start site, or translationally (13). A serine protease activity within macrophages impairs bacterial cell division by both proteolytic release of active C R A M P peptide and by a direct mechanism. However, the possibility that the filamentation-inducing property of the macrophage lysate is due to activation of native C R A M P within the lysate cannot be excluded. Experiments to fractionate the macrophage lysate based on size is one strategy to address this possibility. Activity could be monitored by in vitro incubation with bacteria, and the protease and C R A M P content could be assayed by zymogram and western blotting, respectively. Preliminary experiments to fractionate the lysate using size-exclusion chromatography or centrifugation columns with defined molecular weight cut-offs were not successful in isolating a fraction that retained activity (data not shown). Elastase-like proteases can be antimicrobial through enzymatic (12) or non-enzymatic (25) activities. The cooperation observed between macrophage elastase-like proteases and C R A M P within macrophages, and the 154 Salmonella Figure 5.10 Macrophages use ROIs, serine protease, and C R A M P antimicrobial peptide to impair cell division of 5. Typhimurium. Model. S. Typhimurium infection of macrophages induces ROIs, which increase expression of the cathelicidin C R A M P . This antimicrobial peptide is activated by an intracellular protease, and both C R A M P and protease activity impair bacterial cell division, resulting in filamentous bacteria. 155 potential cooperation in a cell-free system, is similar to- synergy between lysozyme and defensins (26). Cationic peptides play a central role in control of microbial infection, and deficiency of the human homologue of C R A M P , LL-37, may lead to susceptibility to chronic skin and oral infections (27). High concentrations of antimicrobial peptides are stored by neutrophils and are expressed at lower levels by other granulocytes, mast cells, keratinocytes, and epithelial cells (23). While these antimicrobial peptides can be released, activated by extracellular proteases, and serve important roles in killing of extracellular pathogens, their regulation within phagocytes and activity against intracellular pathogens or phagocytosed bacteria is not well understood. Ectopic expression of foreign peptides has suggested that peptides can be important mediators of innate immune control of bacterial pathogens: human LL-37 augments mouse lung defense against Pseudomonas aeruginosa (28), human defensin 5 in the intestine makes mice more resistant to oral challenge with S. Typhimurium (29), and human defensin expression in macrophages controls replication of pathogens such as Mycobacterium tuberculosis and Histoplasma capsulatum (30, 31). Here we show expression, activation, and activity of an endogenous cationic peptide within macrophages, an important target cell of many significant intracellular pathogens. The residual filamentation observed in Cnlp"7" macrophages may suggest a contribution by other antimicrobial peptides. Salmonella resistance to cationic peptides in vitro has been well described, and many bacterial mutants unable to resist peptides in vitro show attenuated virulence within mice (32-37). However, none of the peptides used in these in vitro studies have been shown to be expressed by murine macrophages, which provide an in vivo niche for S. Typhimurium. PhoP/Q is a two component regulatory system that mediates pleiotropic changes in S. Typhimurium gene expression (16). PhoP n u" mutants are highly susceptible to growth inhibition by peptides in vitro, caused by an inability to mediate LPS modifications that protect bacteria from membrane 156 damage from peptides (17, 38). Here we show that 5*. Typhimurium is exposed to a cationic peptide within the endosomal compartment of macrophages. The ability of PhoP mutants to resist filamentation in macrophages as well as at higher in vitro concentrations of C R A M P suggests that the kinetics or levels of PhoP expression by wild type bacteria within macrophages is not sufficient to resist CRAMP-mediated septation arrest. Indeed, there is a net increase in the phosphorylation of PhoP (and therefore activity) in PhoP c mutants relative to wild type bacteria, with phosphorylation absent in the PhoP n u" mutant (39). The increased C F U of PhoP n u" mutants within CRAMP-deficient macrophages provides direct evidence that the PhoP regulon protects S. Typhimurium from cationic peptides within host cells! Perhaps the best-characterized antimicrobial effector is the oxidative burst. It has been shown in neutrophils that the influx of ROIs and cations such as K + and H* into the phagosome cooperate to activate the serine proteases neutrophil elastase and cathepsin G, and that protease activity is responsible for impaired bacterial survival (11). Neutrophil elastase can proteolytically cleave virulence proteins secreted by S. Typhimurium (40). However, mature macrophages do not express neutrophil elastase (41). We detected macrophage serine protease activities demonstrating activity and inhibitor sensitivity similar to elastases. This activity is regulated in a manner distinct from elastase in neutrophils, as it is not sensitive to inhibitors of ROIs and potassium channels although it is sensitive to a v-ATPase inhibitor. Rather, we show that an antibacterial effector regulated by ROIs within macrophages is the expression of C R A M P . Therefore, both macrophages and neutrophils possess indirect mechanisms of oxidase-dependent impairment of bacterial replication. In summary, these data indicate that ROIs and intracellular proteases can impair cell division of a bacterial pathogen within macrophages through complementary yet independent mechanisms, by regulating expression and activity of an antimicrobial peptide. 157 5.13 Literature Cited 1. Rosenberger, C. M . , and B. B. Finlay. 2003. Phagocyte sabotage: disruption of macrophage signalling by bacterial pathogens. 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Transcriptional regulation of Salmonella virulence: a PhoQ periplasmic domain mutation results in increased net phosphotransfer to PhoP. J Bacteriol 178:6369. 40. Weinrauch, Y. , D. Drujan, S. D. Shapiro, J. Weiss, and A . Zychlinsky. 2002. Neutrophil elastase targets virulence factors of enterobacteria. Nature 417:91. 41. Takahashi, H. , T. Nukiwa, P. Basset, and R. G. Crystal. 1988. Myelomonocytic cell lineage expression of the neutrophil elastase gene. JBiol Chem 263:2543. 161 Chapter 6 General discussion and perspectives. 6.1 Lessons learned about Salmonella pathogenesis using gene arrays. Gene arrays have become a popular tool to profile host cell responses to bacterial, viral, and parasitic pathogens. Appendix D provides a summary and comparison of the first array studies of host responses to bacterial pathogens. Eckmann et al. published an expression profiling study of epithelial cell responses to S. Dublin infection, shortly after the experiments described in Chapter 2 were completed (1). Appendix D (Table II) show that both mouse macrophages and human colonic epithelial cells upregulate expression of the proinflammatory cytokine leukemia inhibitory factor (LIF) and the chemokine MIP-2a. However, these studies used different arrays containing different subsets of genes and the epithelial response data set is not publicly available, making direct comparisons between host response to S. Typhimurium in the human gastroenteritis and murine typhoid models difficult. Detweiler et al. has reported array profiling of PMA-differentiated U937 human macrophage-like cells infected by wild type S. Typhimurium or a PhoP n u" mutant (2). They identified 6 genes involved in cell death or cell cycle that were more highly expressed in wild type-infected macrophages compared to those infected by PhoP n u", and no genes that were impaired by PhoP expression, and confirmed a role for PhoP in macrophage death. Interestingly, they observed that only 0.3% of the 22 571 cDNAs on their arrays were differentially expressed in response to bacterial PhoP gene expression. This may suggest a technical reason underlying why differentially expressed genes were not observed in response to SPI2-secreted virulence factors as described in Chapter 3, as those studies used arrays containing 588 genes. The availability of S. Typhimurium arrays wil l make possible simultaneous analysis of the effect of a macrophage signal transduction cascade on both host and pathogen gene expression. There have been a few limitations of many array studies of host responses to pathogens. First, complete data sets are not always available or there is insufficient information on data 162 analysis, which prevents comparisons between studies. As well, differences in infection conditions make direct comparisons difficult. Second, all studies to date rely on infection of host cells in vitro. As discussed in Chapter 1, macrophages are a heterogeneous population and their phenotype is modulated by the net balance of cytokines and interactions with other cell types that occur within infected tissues. Therefore, infection of macrophages in vitro only provides a model for studying possible responses of macrophages in vivo. Third, array studies, including the work described in this thesis, have so far led to little hypothesis generation and functional analysis of unpredicted changes in host gene expression. Dozens of reviews have been written extolling the unprecedented opportunities offered by expression profiling. Saddled with a reductionist heritage, many scientists are not inclined to use arrays maximally as it is more expedient to confirm array results that fit with our current understanding of infectious disease (i.e. upregulation of a cytokine) rather than a potentially novel player in host responses to infection (i.e. induction of an uncharacterized ORF with no homology). We identified novel changes in a variety of genes, and confirmed increased tristetraprolin mRNA and decreased DP-1 mRNA using more quantitative techniques. However, we chose to functionally characterize the role of the well-described M E K 1 kinase, for which antibodies and chemical inhibitors are available, rather than characterize a more enigmatic gene array result, and this approach led to the identification of a novel role of macrophage signaling in limiting S. Typhimurium replication. With the current availability of more advanced bioinformatics tools, a reductionist approach to array data can be replaced with a systems biology approach. A greater focus on the thousands of uncharacterized open reading frames identified in genome sequencing projects will likely identify truly novel host responses to pathogens. 6.2 How do macrophages integrate signals from bacterial pathogens? Two array studies have provided a wealth of information on the transcriptional responses of macrophages to bacteria and their components and complement the data presented here. Nau 163 and colleagues undertook a large-scale array study of human blood monocyte responses to a diverse set of bacteria (E. coli, enteropathogenic E. coli, S. Typhi, S. Typhimurium, S. aureus, L. monocytogenes, M. tuberculosis, and BCG) and their, components (LPS, lipoteichoic acid, muramyl dipeptide, heat shock proteins, f-met-leu-phe, protein A and mannose) and compared the responses to phagocytosis of latex beads (3). Their data reveal that macrophages initiate a core activation programme in response to these stimuli that is temporally conserved. Of the 6 800 genes examined, 15% were altered in response to one or more stimuli and 3% were altered in response to every stimuli. This core expression profile was then built upon by specific responses to particular classes of bacteria or structures. Boldrick et al. analyzed the responses of these same cells to a variety of doses of live and heat-killed bacteria (B. pertussis, E. coli, and S. aureus clinical isolates), LPS, or the non-specific activators ionomycin and phorbol 12-myristate 13-acetate (4). They also detected common induction and repression clusters, and many of the upregulated genes were regulated by N F - K B and serve proinflammatory functions. Above this common infection signature, they also identified numerous genes that were specifically regulated by B. pertussis virulence factors. While the signaling from pattern recognition receptors converge to produce many of these conserved responses to infection, the mechanisms for generating pathogen-specific responses have not been fully elucidated (5). Data in Chapters 2 and 4 suggest that LPS is a powerful stimulus, and results in the majority of gene expression and M E K kinase signaling that we have observed in S. Typhimurium-infected macrophages. However, adding purified LPS to macrophages does not recapitulate the dose, kinetics, or intracellular localization of LPS shed by live and killed bacteria within infected cells. Our results therefore indicate that a high dose of purified LPS is capable of stimulating the observed changes in gene and protein expression and kinase activity. A recent study has examined the physiological role of LPS signaling in macrophage responses to S. Typhimurium, by adding a lipid A antagonist to S. Typhimurium-infected R A W 264.7 cells or 164 by infecting TLR4-deficient B M D M (6). They show that macrophage production of nitric oxide and TNF-a in response to S. Typhimurium is dependent on LPS-TLR4 signaling. Their data indicate that infection with whole bacteria stimulates a more delayed activation of kinase activity compared with purified LPS stimulation. Early N F - K B activation (30 min) and prolonged activation of p38 and JNK kinase activity (90 min) could not be blocked by the LPS antagonist, suggesting that other components of the bacteria or the infection process are responsible for this signaling. We demonstrate in Chapter 4 that M E K activity and ROIs measured at later post-infection time points mediated bacterial filamentation, and thereby serve a unique function relative to the rapid activation of M E K and oxidative burst immediately following infection. Temporal regulation of signaling likely combines with activation and spatial regulation as mechanisms for tuning the appropriate macrophage responses from a given bacterial input. 6.3 Why does Salmonella respond to intracellular signals with filamentation? It is unknown whether Salmonella is unique in responding to the macrophage vacuolar environment with filamentation. We have observed that non-pathogenic E. coli is not filamentous within mouse macrophages, and this could be due either to the bacteria's inability to resist macrophage antimicrobial effectors or because it traffics to a more bactericidal lysosomal compartment. Since the experiments in Chapter 4 were performed, a MEK-dependent mechanism of control of Mycobacterium avium growth within murine macrophages has been described (7, 8). Since Mycobacteria alter phagosomal trafficking to occupy an intracellular niche distinct from the SCV, it would be interesting to investigate whether antimicrobial peptides and proteases play any role in controlling mycobacterial infection and whether this or any other bacterial pathogens adopt a filamentous morphology similar to Salmonella. Since most filamentous Salmonella are alive within macrophages, it is not obvious whether this phenotype offers an advantage to either host or pathogen. Growth within liver macrophages in vivo results from transmission of bacteria between cells and the establishment of 165 new infectious foci, rather than large numbers of replicating bacteria contained within each phagocyte (9). This important role for transmission rather than intracellular replication is not modeled by our in vitro system. However, since we observe that filamentous Salmonella induced by C R A M P in vitro did not survive well when internalized by macrophages, it is tempting to speculate that filamentation could interrupt transmission of infection in vivo. S. Typhimurium is known to respond to the intracellular environment with the induction of a stress regulon (10) as well as damage repair mechanisms (11-13). Erikkson et al. have published an elegant first study of S. Typhimurium gene expression within a macrophage cell line using gene arrays (14). They observed changes in a variety of bacterial stress response genes, suggesting that although there is a net increase in the number of bacteria within macrophage-like cell lines, the population is still subject to a variety of stressors. It could therefore be speculated that S. Typhimurium responds to stresses within the SCV by modulating its gene expression, which impairs cell division. Analysis of their publicly available data set reveals increased expression of genes with possible roles in bacterial cell division and filamentation (sulA, fic, cedA) after 4 h, 8 h, and 12 h of infection. Heat shock genes (i.e. yegD), SOS response genes ilexA, ydjM), and genes involved in response to stresses such as D N A damage (recA, dinF, yebG) are also induced in macrophages, along with a strong upregulation of ydgE and ydgF expression, predicted membrane transporters of cations and cationic drugs. Salmonella transcriptional responses to the particular stress of a sublethal concentration of cationic peptides have been examined using bacterial gene arrays (15). Under this in vitro condition, S. Typhimurium alters its gene expression in a PhoP-dependent manner to become more resistant to different structural classes of antimicrobial peptides. Sublethal concentrations of cationic peptides also increases bacterial resistance to oxidative stress, suggesting that exposure to antimicrobial peptides triggers S. Typhimurium resistance mechanisms to counteract both oxidative and non-oxidative innate immune effectors within host cells. While bacterial 166 mechanisms to avoid and repair damage likely play an important role, it is also possible that the particular combination of stressors within the macrophage SCV is ineffectual in completely halting bacterial replication or killing bacteria, resulting in this impaired cell division phenotype. 6.4 Interplay between macrophage signaling and antimicrobial responses. Different complements of effectors may explain some of the differences observed between cell types. R A W 264.7 cells induced more bacterial filamentation than B M D M and other primary macrophages. As R A W 264.7 cells are more permissive for S. Typhimurium replication, it is possible that this increased bacterial replication simply leads to longer and more numerous filamentous bacteria. SCV differ between macrophages, and SCV within R A W 264.7 cells exclude the lysosomal hydrolases cathepsin D and cathepsin L while SCV within B M D M contain cathepsin L. It is therefore possible that SCV within B M D M are more bacteriostatic or bactericidal compared to R A W 264.7 cells due to the levels of proteases, antimicrobial peptides, cations, nutrients, and oxidants. These differences could result from inherent differences between cell types or differences in the state of activation in vitro. Much has been speculated on the direct antimicrobial role of Nrampl as a cation transporter, particularly of its possible transport of iron, and it can also alter vacuolar pH (16). It would be interesting to know i f it Nrampl serves to regulate other antimicrobial activities such as antimicrobial peptide expression or protease activity, as has been shown with ROIs. This net balance of effectors within the SCV can also benefit pathogen survival. While most pathogens avoid endosomal acidification, Salmonella permits it. It has been proposed that low pH is used as a cue for SPI2-encoded type III virulence factor secretion. Allowing acidification could also benefit this pathogen as our data indicate that C R A M P is less active in acidic conditions, as has been observed with other cationic peptides. While influx of H + may regulate neutrophil elastase within neutrophils (17, 18), activity of this neutral serine protease is significantly impaired at the pH of the SCV. It may therefore be the impaired activity of some 167 antimicrobial effectors within the macrophage SCV that result in bacterial filamentation instead of bacterial killing. Different cell types show unique regulation and expression of antimicrobial effectors. Current evidence suggests that neutrophils have the broadest repertoire of antimicrobial capabilities, with a high oxidative burst potential and containing large stores of proteases and antimicrobial peptides. Neutrophils can also rapidly kill S. Typhimurium in vitro. It would be interesting to examine the role of C R A M P in impairing Salmonella growth within neutrophils. The roles of antimicrobial peptides within other granulocytes and dendritic cells during Salmonella infection remain to be examined. As well, since ectopic expression of a defensin within the intestine can mediate protection from 5. Typhimurium infection (19), it would be interesting to evaluate whether endogenous C R A M P within the small intestine plays a role during enteric salmonellosis, and whether myeloid or epithelial cells are the source (20). Traditionally, the physiological roles of antimicrobial effectors have been elucidated by studying the course of infections in cohorts of humans that are naturally deficient or mice that are engineered to be deficient in a single functional protein. While this has been a successful strategy to identify host proteins with major, non-redundant roles during infection, it tends to overlook the interplay that occurs between these effectors. Looking at individual antimicrobial players in isolation does not allow us to understand the intracellular environment experienced by a given pathogen. Such information is essential for a better understanding of bacterial virulence. For example, the natural cues to which many bacterial two-component regulatory systems respond or that regulate type III secretion are currently unclear. The ability of bacterial pathogens to perturb macrophage signaling and avoid or resist macrophage effectors, as discussed in Appendix C, adds an extra layer of complexity to this host-pathogen interaction. This thesis work begins to address the signals used by macrophages to facilitate innate immune response to a pathogen, and the interplay between macrophage effector mechanisms that restricts bacterial cell division. 168 6.5 Literature cited. 1. Eckmann, L. , J. R. Smith, M . P. Housley, M . B. Dwinell, and M . F. Kagnoff. 2000. Analysis by high density cDNA arrays of altered gene expression in human intestinal epithelial cells in response to infection with the invasive enteric bacteria Salmonella. J Biol Chem 275:14084. 2. Detweiler, C. S., D. B. Cunanan, and S. Falkow. 2001. Host microarray analysis reveals a role for the Salmonella response regulator phoP in human macrophage cell death. Proc Natl Acad Sci USA 98:5850. 3. Nau, G. J., J. F. Richmond, A . Schlesinger, E. G. Jennings, E. S. Lander, and R. A . Young. 2002. Human macrophage activation programs induced by bacterial pathogens. Proc Natl Acad Sci USA 99:1503. 4. Boldrick, J. C , A. A . Alizadeh, M . Diehn, S. Dudoit, C. L . Liu, C. E. Belcher, D. Botstein, L . M . Staudt, P. O. Brown, and D. A . Relman. 2002. Stereotyped and specific gene expression programs in human innate immune responses to bacteria. Proc Natl Acad Sci USA 99:972. 5. Sabroe, I., R. C. Read, M . K. Whyte, D. H . Dockrell, S. N . Vogel, and S. K. Dower. 2003. Toll-like receptors in health and disease: complex questions remain. J Immunol 171:1630. 6. Royle, M . C , S. Totemeyer, L . C. Alldridge, D. J. Maskell, and C. E. Bryant. 2003. Stimulation of Toll-Like Receptor 4 by Lipopolysaccharide During Cellular Invasion by Live Salmonella typhimurium Is a Critical But Not Exclusive Event Leading to Macrophage Responses. J Immunol 170:5445. 7. Tse, H . M . , S. I. Josephy, E. D. Chan, D. Fouts, and A . M . Cooper. 2002. Activation of the mitogen-activated protein kinase signaling pathway is instrumental in determining the ability of Mycobacterium avium to grow in murine macrophages. J Immunol 168:825. 8. Schorey, J. S., and A . M . Cooper. 2003. Macrophage signalling upon mycobacterial infection: the M A P kinases lead the way. Cell Microbiol 5:133. 9. Sheppard, M . , C. Webb, F. Heath, V . Mallows, R. Emilianus, D. Maskell, and P. Mastroeni. 2003. Dynamics of bacterial growth and distribution within the liver during Salmonella infection. Cell Microbiol 5:593. 10. Buchmeier, N . A. , and F. Heffron. 1990. Induction of Salmonella stress proteins upon infection of macrophages. Science 248:730. 169 11. Buchmeier, N . A. , C. J. Lipps, M . Y . So, and F. Heffron. 1993. Recombination-deficient mutants of Salmonella typhimurium are avirulent and sensitive to the oxidative burst of macrophages. Mol Microbiol 7:933. 12. Schapiro, J. M . , S. J. Libby, and F. C. Fang. 2003. Inhibition of bacterial D N A replication by zinc mobilization during nitrosative stress. Proc Natl Acad Sci U SA 100:8496. 13. Fang, F. C. 1997. Perspectives series: host/pathogen interactions. Mechanisms of nitric oxide-related antimicrobial activity. J Clin Invest 99:2818. 14. Eriksson, S., S. Lucchini, A . Thompson, M . Rhen, and J. Hinton. 2003. Unravelling the biology of macrophage infection by gene expression profiling of intracellular Salmonella enterica. Mol Microbiol 47:103. 15. Bader, M . W., W. W. Navarre, W. Shiau, H. Nikaido, J. G. Frye, M . McClelland, F. C. Fang, and S. I. Miller. 2003. Regulation of Salmonella typhimurium virulence gene expression by cationic antimicrobial peptides. Mol Microbiol 50:219. 16. Forbes, J. R., and P. Gros. 2001. Divalent-metal transport by N R A M P proteins at the interface of host-pathogen interactions. Trends Microbiol 9:397. 17. Harrison, R. E., N . Touret, and S. Grinstein. 2002. Microbial killing: oxidants, proteases and ions. Curr Biol 12:R357. 18. Jankowski, A. , and S. Grinstein. 2002. Modulation of the cytosolic and phagosomal pH by the N A D P H oxidase. Antioxid Redox Signal 4:61. 19. Salzman, N . H. , D. Ghosh, K. M . Huttner, Y . Paterson, and C. L . Bevins. 2003. Protection against enteric salmonellosis in transgenic mice expressing a human intestinal defensin. Nature 422:522. 20. Gallo, R. L. , K . J. Kim, M . Bernfield, C. A . Kozak, M . Zanetti, L . Merluzzi, and R. Gennaro. 1997. Identification of C R A M P , a cathelin-related antimicrobial peptide expressed in the embryonic and adult mouse. J Biol Chem 272:13088. Appendix A . l Hybridization intensities in R A W 264.7 cells infected with S. Typhimurium or stimulated with LPS . Unactivated R A W 264.7 cells were unstimulated (Unstim.; n=2), infected with S. Typhimurium («=3), or treated with LPS («=3) for 4 h. The mean ± SD is shown along with the ratio relative to the mean hybridization signal in unstimulated cells for each individual experiment. A , B, C refer to independent experiments. Code refers to the position of cDNA spots on the array. Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium LPS Gene/Protein Name Number A + B mean SD mean SD A B C A B C M88127 A l a 20 102 41 159 59 7.5 3.8 4.1 4.7 8.6 10.5 A P C (adenomatous polyposis coli protein) U31625 A l b 20 40 53 99 45 5.1 0.0 1.0 2.4 6.2 6.3 B R C A 1 ; breast/ovarian cancer susceptibility locus U65594 A l e 167 122 93 202 70 1.1 0.1 1.0 1.5 1.4 0.7 B R C A 2 ; breast cancer susceptibility locus 2 X85788 A i d 20 46 63 156 70 5.9 0.0 1.0 4.3 11.3 7.8 D C C ; netrin receptor; Ig gene superfamily U51196 A l e 563 412 161 675 311 0.5 0.6 1.1 0.8 1.8 0.9 E B 1 APC-binding protein X60671 A l f 543 788 468 777 157 1.1 0.8 2.4 1.7 1.2 1.4 ezrin; v i l l in 2; NF-2 (merlin) related U58992 A l g 20 86 63 145 84 5.1 0.8 7.0 5.1 12.1 4.6 M a d r l ; mSmadl; (bsp-1) X58876 A l h 20 189 71 322 162 9.3 6.0 13.1 9.8 25.2 13.3 Mdm2; p53-regulating protein L27105 A l i 20 172 101 314 84 12.5 2.9 10.5 17.2 19.0 11.0 N F 2 ; merlin (moesin-ezrin-radixin-like protein); U27177 A l j 20 210 82 350 232 10.4 6.5 14.6 11.4 30.9 10.2 p i07 ; R B L 1 ; retinoblastoma gene product-related U36799 A l k 20 47 47 339 315 2.4 0.0 4.7 7.4 35.2 8.4 p i30 ; retinoblastoma gene product-related protein KOI700 A l l 20 101 7 243 210 5.3 5.2 4.7 4.0 24.0 8.5 p53; tumor suppressor; DNA-binding protein M26391 A i m 20 106 49 156 102 2.5 6.9 6.6 4.2 13.7 5.7 Rb; ppl05; retinoblastoma susceptibility-assoc. U52945 A l n 164 185 63 157 90 1.0 1.6 0.9 1.5 0.4 0.9 TSG101 tumor susceptibility protein U54705 A 2 a 20 98 63 141 59 8.5 3.7 2.6 10.0 4.1 7.0 tumor suppressor maspin U12570 A2b 20 45 61 83 41 5.8 0.0 1.0 4.4 2.0 6.1 V H L ; V o n Hippel-Lindau tumor suppresso M55512 A2c 20 17 16 49 35 1.6 0.0 1.0 2.2 0.9 4.3 W T 1 ; Wilms tumor protein; tumor suppressor D14340 A 2 d 20 16 15 54 45 1.5 0.0 1.0 3.9 0.2 4.2 ZO-1 ; tight junction protein X82327 A2e 20 36 47 94 64 4.5 0.0 1.0 6.0 1.1 7.1 A-myb proto-oncogene; myb-related protein A X70472 A 2 f 614 207 59 277 70 0.3 0.2 0.4 0.4 0.6 0.4 B-myb proto-oncogene; myb-related protein B X51983 A 2 g 147 170 55 197 43 1.4 0.7 1.4 1.7 1.1 1.2 c-ErbA oncogene; thyroid hormone receptor. V00727 A2h 930 399 75 590 23 0.5 0.3 0.5 0.6 0.6 0.7 c-Fos proto-oncogene; transcription factor AP-1 J04115 A 2 i 426 650 262 465 103 1.2 1.1 2.2 1.3 0.8 1.1 c-Jun proto-oncogene; transcription factor AP-1 X83974 A2j 3050 4553 1654 3498 536 1.1 1.2 2.1 1.2 1.0 1.3 R N A polymerase I termination factor TTF-1 M l 6449 A 2 k 181 410 204 404 76 2.0 1.3 3.5 2.6 1.8 2.3 c-myb proto-oncogene protein X01023 A21 710 1439 628 2116 663 3.0 1.4 1.7 2.1 2.9 3.9 c-myc proto-oncogene protein 170 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium LPS Gene/Protein Name Number A+B mean S D mean SD A B C A B C XI5842 A 2 m 20 256 27 395 84 13.1 14.0 11.4 15.6 23.9 19.8 c-rel proto-oncogene X76654 A 2 n 20 166 48 146 47 9.9 9.5 5.6 10.0 5.7 6.2 Ear-2; v-erbA related proto-oncogene X87257 A 3 a 123 176 73 193 33 2.1 1.2 1.0 1.4 1.4 1.9 Elk-1 ets-related proto-oncogene X59421 A3b 798 377 123 327 22 0.6 0.3 0.5 0.4 0.4 0.4 Fli-1 ets-related proto-oncogene X14897 A 3 c 20 77 52 72 11 6.7 3.2 1.6 4.1 3.1 3.6 Fos-B; c-fos-related protein fos B X83971 A 3 d 20 155 103 140 62 12.9 2.6 7.8 10.3 4.1 6.6 Fra-2 (fos-related antigen 2) S65038 A3e 20 67 88 85 62 8.4 0.0 1.8 6.5 0.7 5.6 G l i oncogene; zinc finger transcription factor J03236 A 3 f 20 171 174 179 61 18.1 l . l 6.5 10.1 5.5 11.3 Jun-B; c-jun-related transcription factor J05205 A 3 g 20 231 150 248 74 14.9 3.0 16.8 14.4 8.1 14.6 jun-D; c-jun-related transcription factor XI3945 A 3 h 20 67 76 49 49 7.5 0.0 2.6 4.9 0.0 2.5 L-myc proto-oncogene protein Z32815 A 3 i 423 366 166 289 151 0.9 0.4 1.2 1.1 0.4 0.5 Net; ets related transcription factor X03919 A3j 2225 1478 287 1367 160 0.8 0.5 0.7 0.7 0.5 0.6 N-myc proto-oncogene protein M13071 A 3 k 490 420 191 535 213 1.3 0.6 0.7 1.6 0.8 0.8 A - R a f proto-oncogene M64429 A31 1135 853 430 900 249 1.2 0.7 0.4 1.0 0.8 0.6 B-Raf proto-oncogene D13759 A 3 m 20 171 36 129 59 7.6 10.6 7.5 9.9 4.4 5.1 Cot proto-oncogene U51866 A 3 n 672 635 67 574 78 0.8 1.0 1.0 0.8 0.8 1.0 casein kinase II (alpha subunit) M l 3945 A 4 a 573 1145 247 1213 257 2.2 1.5 2.3 2.1 1.7 2.6 Pim-1 proto-oncogene X68932 A4b 4455 2225 493 2531 174 0.6 0.4 0.6 0.6 0.5 0.6 c-Fms proto-oncogene; M - C S F - 1 receptor Y00864 A 4 c 501 149 45 173 74 0.4 0.3 0.2 0.5 0.2 0.3 c-Kit proto-oncogene; mast cell growth factor Y00671 A 4 d 20 72 68 50 50 7.5 0.9 2.5 5.4 1.0 1.1 Met proto-oncogene M84607 A4e 20 23 24 51 18 2.4 0.0 1.0 3.2 1.5 3.0 platelet-derived growth factor alpha-receptor X67812 A 4 f 20 15 13 65 28 1.3 0.0 1.0 4.6 3.4 1.8 Ret proto-oncogene U14173 A 4 g 725 211 155 304 76 0.4 0.0 0.4 0.5 0.3 0.5 Ski proto-oncogene U18342 A 4 h 20 17 22 35 40 0.5 0.0 2.1 4.1 0.8 0.4 Sky proto-oncogene (Tyro3; Rse; Dtk) S67051 A 4 i 20 51 50 68 22 5.0 0.0 2.7 4.7 2.7 2.8 Tie-2 proto-oncogene L07297 A4j 179 335 128 533 48 2.7 1.6 1.3 2.8 3.3 2.8 vascular endothelial growth factor receptor 1 LI 0656 A 4 k 20 115 83 53 41 10.1 5.5 1.8 4.1 0.3 3.7 c-Abl proto-oncogene X12616 A41 569 278 20 305 58 0.5 0.5 0.5 0.6 0.4 0.5 c-Fes proto-oncogene X52191 A 4 m 20 116 109 76 78 3.8 12.0 1.7 3.6 0.0 7.8 c-Fgr proto-oncogene M17031 A 4 n 20 243 51 280 106 11.9 14.9 9.8 11.6 10.4 20.1 c-Src proto-oncogene M l 2056 A 5 a 20 179 79 213 38 13.4 7.8 5.7 12.9 9.4 9.7 lymphocyte-specific tyrosine-protein kinase L C K X57111 A5b 383 190 44 325 158 0.6 0.5 0.4 0.5 1.3 0.8 c-Cbl proto-oncogene (adaptor protein) 171 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A+B mean SD mean SD A B C A B C Z50013 A5c 20 219 62 192 74 14.5 9.8 8.7 13.2 10.0 5.8 H-ras proto-oncogene; transforming G-protein U28495 A 5 d 126 171 97 222 108 2.0 1.6 0.5 0.8 2.5 1.9 Lfc proto-oncogene XI3664 A5e 283 307 71 375 256 1.2 1.3 0.8 0.6 2.4 1.0 N-ras proto-oncogene; transforming G-protein U15784 A 5 f 176 157 18 257 48 0.8 0.8 1.0 1.1 1.6 1.6 She transforming adaptor protein X05010 A 5 g 20 43 46 97 53 4.8 0.5 1.3 6.6 1.8 6.1 CSF-1 ; M - C S F ; colony stimulating factor-1 M80456 A 5 h 20 24 26 24 29 2.6 0.0 1.0 2.9 0.0 0.8 Int-3 proto-oncogene; N O T C H 4 Z46845 A 5 i 20 27 31 30 49 3.1 0.0 1.0 4.3 0.0 0.2 preproglucagon D17584 A5j 191 141 165 208 274 1.7 0.0 0.5 2.7 0.3 0.2 beta-protachykinin a Z22649 A 5 k 20 42 21 49 68 3.1 2.2 1.0 6.3 0.0 1.0 c -Mpl ; thrombopoietin receptor X67735 A51 20 105 82 197 243 10.0 3.5 2.3 23.9 2.5 3.1 Mas proto-oncogene (G-protein coupled receptor) X81580 A 5 m 20 55 32 45 42 4.2 3.1 1.0 4.5 2.0 0.3 IGFBP-2; insulin-like binding protein 2 U05245 A 5 n 20 23 20 47 50 2.2 0.3 1.0 5.0 0.0 2.1 Tiam-1 invasion inducing protein Z26580 A 6 a 189 149 96 253 129 0.7 1.3 0.3 0.9 2.1 1.0 cyclin A (G2/M-specific) X84311 A6b 20 66 49 88 2 5.9 3.1 1.0 4.4 4.5 4.3 cyclin A1 (G2/M-specific) X64713 A6c 704 555 281 751 519 0.4 0.8 1.2 0.3 1.7 1.2 cyclin B1 (G2/M-specific) X66032 A 6 d 511 370 96 302 73 0.9 0.7 0.5 0.4 0.7 0.7 cyclin B2 (G2/M-specific) U62638 A6e 20 95 49 94 18 7.6 3.3 3.4 4.1 5.7 4.3 cyclin C (Gl-specific) S78355 A 6 f 1489 921 169 955 237 0.5 0.7 0.6 0.5 0.8 0.6 cyclin D l (Gl/S-specific) M83749 A 6 g 20 38 35 55 31 3.5 0.0 2.3 4.2 1.1 2.9 cyclin D2 (Gl/S-specific) U43844 A 6 h 165 80 104 113 168 1.2 0.0 0.3 1.9 0.0 0.2 cyclin D3 (Gl/S-specific) X75888 A 6 i 388 89 67 85 59 0.3 0.0 0.4 0.4 0.1 0.2 cyclin E (Gl/S-specific) Z47766 A6j 391 132 121 181 126 0.7 0.2 0.1 0.8 0.3 0.3 cyclin F (S/G2/M-specific) Z37110 A 6 k 153 188 34 189 50 1.3 1.4 1.0 1.1 1.6 1.0 cyclin G (G2/M-specific) U95826 A61 20 159 60 172 123 11.4 5.7 6.8 15.7 4.3 5.8 cyclin G2 (G2/M-specific) L01640 A 6 m 481 335 58 326 40 0.6 0.8 0.7 0.8 0.6 0.6 Cdk4; cyclin-dependent kinase 4 D29678 A 6 n 20 227 75 205 74 15.3 11.1 7.8 14.1 6.7 9.9 Cdk5; cyclin-dependent kinase 5 U l 1822 A 7 a 20 60 37 115 55 4.6 3.4 1.0 2.8 8.2 6.3 Cdk7; M O 15; cyclin-dependent kinase 7 M58633 A7b 20 53 45 81 28 5.2 1.8 1.0 2.9 3.7 5.6 p58/GTA; galactosyltransferase-associated kinase U19596 A7c 126 77 51 147 94 0.9 0.7 0.2 0.8 2.0 0.6 pl8ink4; cdk4 and cdk6 inhibitor U19597 A 7 d 161 172 136 170 23 2.0 0.3 0.9 0.9 1.1 1.2 pl9ink4; cdk4 and cdk6 inhibitor U09507 A7e 20 220 129 313 137 18.5 7.2 7.4 14.8 9.3 22.9 p21 /Cip l /Waf l ; cdk-inhibitor protein 1 U10440 A 7 f 20 77 48 65 58 6.6 2.4 2.5 5.7 0.0 4.1 p27kipl ; G l cyclin-Cdk protein kinase inhibitor 172 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A+B mean SD mean SD A B C A B C U20553 A 7 g 20 36 46 27 47 4.4 0.0 1.0 4.1 0.0 0.0 p57kip2; cdk-inhibitor kip2 D30743 A 7 h 349 61 58 121 30 0.3 0.0 0.2 0.4 0.3 0.3 Weel/p87; cdc2 tyrosine 15-kinase X59868 A 7 i 20 32 39 8 13 3.8 0.0 1.0 1.2 0.0 0.0 Cdc25 phosphatase U27323 A7j 391 170 76 246 80 0.7 0.3 0.3 0.5 0.5 0.9 Cdc25a; c d c 2 5 M l ; M P I l S93521 A 7 k 20 91 71 32 55 8.6 1.8 3.4 4.8 0.0 0.0 Cdc25b; cdc25M2; MPI2 U43525 A71 527 450 106 295 34 1.0 0.6 0.9 0.6 0.5 0.5 myeloblastin; serine protease X56135 A 7 m 5605 4646 650 4598 383 0.7 0.8 1.0 0.9 0.7 0.8 prothymosin alpha D78382 A 7 n 958 556 32 789 605 0.6 0.6 0.6 1.6 0.4 0.5 Tob antiproliferative factor U03560 B l a 20 9 10 83 7 0.4 0.0 1.0 4.1 4.5 3.8 HSP27; heat shock 27-kDa protein 1 X53584 B i b 506 322 91 468 218 0.5 0.6 0.8 0.5 1.3 0.9 HSP60 (heat shock 60-kDa protein 1); chaperonin M36829 B l c 2214 1999 516 2276 458 1.1 0.9 0.7 0.8 1.2 1.1 HSP84 (heat shock 84-kDa protein) M36830 B i d 2731 2373 324 2700 636 1.0 0.8 0.9 0.8 1.2 1.0 HSP86; heat shock 86-kDa protein L16953 B l e 407 355 123 435 25 1.1 0.5 1.0 1.1 1.1 1.0 M T J 1 ; DnaJ-like heat-shock protein D49482 B l f 20 105 77 136 84 9.7 3.3 2.8 11.2 6.4 2.8 Osp94 osmotic stress protein; hsp70-related M l 4757 B i g 138 175 125 284 48 2.1 0.3 1.4 2.0 1.8 2.4 M D R 1 ; P-glycoprotein; multidrug resistance S50213 B l h 707 381 69 479 107 0.6 0.4 0.6 0.5 0.8 0.7 H M G 1 -related V D J recombination binding protein U58987 B l i 170 139 24 211 32 1.0 0.8 0.7 1.1 1.4 1.2 M m M r e l l a putative endo/exonuclease X78445 B l j 20 25 27 15 8 2.7 0.0 1.0 1.1 0.9 0.3 C 3 H cytochrome P450; C y p l b l J05186 B l k 905 517 77 667 127 0.6 0.5 0.6 0.6 0.8 0.8 ERp72 endoplasmic reticulum stress protein U41751 B l l 488 308 46 378 59 0.7 0.5 0.7 0.7 0.7 0.9 etoposide induced p53 responsive (EI24) m R N A D78645 B l m 1015 1116 506 1242 446 1.6 0.6 1.2 1.6 0.7 1.4 glucose regulated protein, 78 kDa; Grp78 U40930 B i n 20 199 92 262 63 10.6 14.2 5.1 16.4 12.8 10.1 oxidative stress-induced protein m R N A M10021 B2a 20 84 93 162 154 9.6 1.5 1.6 16.7 5.8 1.8 P-1-450; dioxin-inducible cytochrome P450 U34920 B2b 20 23 24 48 42 2.4 0.0 1.0 3.6 3.6 0.0 ATP-binding casette 8; A B C 8 U20372 B2c 20 56 29 124 54 4.4 1.6 2.5 4.5 9.4 4.8 C C H B 3 ; calcium channel (voltage-gated) U34259 B2d 193 138 58 400 244 1.1 0.5 0.6 1.3 3.5 1.4 Golgi 4-transmembrane spanning transporter M23384 B2e 20 308 33 376 73 17.2 14.1 14.9 17.7 15.9 22.9 Glucose transporter-1, erythrocyte; Glu t l L36179 B 2 f 20 33 40 32 36 3.9 0.0 1.1 3.6 1.2 0.0 voltage-gated sodium channel L25606 B2g 20 168 202 123 58 2.8 2.4 20.1 8.8 3.1 6.6 B7-2; T lymphocyte activation antigen CD86 D31788 B2h 20 8 10 42 24 0.3 0.0 1.0 0.7 2.9 2.6 BST-1 ; lymphocyte differentiation antigen CD38 U29678 B 2 i 20 7 12 47 30 0.0 0.0 1.0 1.3 4.1 1.8 C - C C K R - 1 ; C C R - 1 ; MIP-lalpha-R; R A N T E S - R L03529 B2j 20 33 41 17 2 3.9 0.0 1.0 0.9 1.0 0.8 Cf2r; coagulation factor II (thrombin) receptor 173 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A+B mean SD mean SD A B C A B C L25890 B2k 20 21 21 20 34 2.1 0.0 1.0 3.0 0.0 0.0 Eph3 (Nuk) tyrosine-protein kinase receptor M68513 B21 20 44 37 47 33 4.4 1.3 1.0 2.7 0.6 3.8 E t k l (Mek4; H E K ) tyrosine kinase receptor U43205 B 2 m 20 15 13 61 26 1.1 0.0 1.3 2.8 2.0 4.5 Frizzled-3; Drosophila tissue polarity gene Z49086 B2n 20 20 20 13 19 2.0 0.0 1.0 0.2 0.0 1.8 Hek2 murine homolog; Mdk5 Z49085 B3a 20 46 56 69 35 5.4 0.0 1.6 5.5 2.3 2.6 Htk; Mdk2 mouse developmental kinase S69336 B3b 223 240 62 290 89 0.8 1.2 1.3 1.7 1.4 0.9 IFNgR2; interferon-gamma receptor beta chain M83336 B3c 459 241 53 255 3 0.5 0.4 0.7 0.6 0.5 0.6 interleukin-6 receptor beta chain D87747 B3d 20 28 26 83 29 0.5 0.9 2.9 4.0 5.7 2.7 L C R - 1 ; C X C R - 4 ; C X C chemokine receptor 4 M60778 B3e 20 107 35 287 157 6.4 3.4 6.4 8.2 11.6 23.2 L F A 1 -alpha; integrin alpha L D13458 B 3 f 20 111 33 129 39 7.2 3.9 5.5 7.3 7.9 4.2 prostaglandin E2 receptor EP4 subtype X80764 B3g 20 26 23 94 50 1.7 0.0 2.2 4.9 7.2 2.1 Tie-1 tyrosine-protein kinase receptor X57349 B3h 234 389 28 632 348 1.7 1.7 1.5 1.7 4.4 1.9 transferrin receptor protein (p90, CD71) X62700 B 3 i 121 776 268 1045 518 5.4 4.9 9.0 5.8 6.6 13.6 u P A R l ; C D 8 7 X70842 B3j 20 52 55 96 15 0.3 1.9 5.7 5.5 5.0 4.0 V E G F R 2 ; K D R / f l k l S56660 B3k 20 15 14 40 41 0.9 0.0 1.4 0.0 2.0 4.1 retinoic acid receptor beta-2 (beta2-RAR) S76657 B31 20 95 46 261 113 2.5 7.0 4.8 7.7 18.9 12.6 C R E - B P 1 ; c A M P response binding protein 1 U36277 B 3 m 402 1050 72 1239 378 2.8 2.5 2.5 2.1 3.1 4.0 I-kB (I-kappa B) alpha chain U19799 B3n 143 575 163 723 240 4.7 4.6 2.7 3.1 6.0 6.0 I-kB (I-kappa B) beta M61909 B4a 20 18 32 86 26 0.0 0.0 2.8 2.8 4.8 5.3 N F - k B p65; NF-kappa-B p65 subunit U33626 B4b 20 114 30 145 49 6.7 4.0 6.4 8.5 8.9 4.4 Pml; leukemia-associated P M L gene X66224 B4c 175 255 112 293 88 0.8 1.6 2.0 1.4 2.3 1.3 RXR-beta cis-11-retinoic acid receptor U06924 B4d 858 2063 437 2223 403 2.0 2.3 3.0 2.1 3.1 2.5 Statl U06922 B4e 188 365 72 441 167 2.2 1.5 2.1 3.1 2.6 1.4 Stat3; acute phase response factor (APRF) Z48538 B 4 f 20 149 42 261 111 6.2 9.9 6.3 11.0 19.4 8.8 Stat5a; mammary gland factor L47650 B4g 975 507 105 740 256 0.4 0.6 0.6 0.5 1.0 0.7 Stat6; IL-4 Stat; S T A 6 U51907 B4h 239 298 62 483 239 1.0 1.3 1.5 1.4 3.2 1.5 T A N K ; I -TRAF; N F - k B activator L21027 B 4 i 20 190 33 173 36 10.0 7.7 10.9 8.5 7.0 10.5 transcription factor A10 DO 1034 B4j 124 199 40 281 75 1.3 1.6 1.9 1.7 2.9 2.2 transcription factor TF II D M57422 B4k 20 1475 292 1135 89 56.9 81.6 82.8 51.7 60.1 58.5 tristetraprolin U48853 B41 20 84 20 87 24 3.1 4.9 4.7 5.1 5.1 2.9 Cas; Crk-associated substrate; F A K substrate S72408 B 4 m 128 190 105 234 50 0.7 1.5 2.3 1.4 2.2 1.9 Crk adaptor protein U05247 B4n 199 271 47 221 32 1.2 1.6 1.2 1.1 1.3 0.9 Csk; c-Src-kinase and negative regulator 174 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name umber A+B mean SD mean SD A B C A B C U70324 B5a 20 85 46 102 79 3.8 6.8 2.3 4.2 9.5 1.8 Fyn proto-oncogene; Src family member Y00487 B5b 20 140 80 181 15 3.8 5.8 11.5 9.2 9.7 8.2 Hck tyrosine-protein kinase U29056 B5c 20 109 62 124 81 3.4 4.0 9.0 8.2 8.9 1.5 S L A P ; src-like adapter protein U25685 B5d 20 117 43 251 85 5.4 4.0 8.3 8.8 11.7 17.2 Syk tyrosine-protein kinase D84372 B5e 20 98 23 97 68 4.0 6.2 4.5 3.2 8.8 2.6 Syp; SH-PTP2 X58995 B 5 f 20 10 10 1 2 0.5 0.0 1.0 0.0 0.2 0.0 C a m K I V ; calmodulin-dependent protein kinase M20473 B5g 20 7 12 2 3 0.0 0.0 1.0 0.0 0.3 0.0 cAMP-dependent protein kinase M61177 B5h 165 168 55 141 66 0.6 1.2 1.2 0.6 1.3 0.6 extracellular signal-regulated kinase 1 (ERK1) ; U28423 B 5 i 2222 1369 394 1516 227 0.7 0.4 0.7 0.8 0.6 0.7 inhibitor of the RNA-activated protein kinase L33768 B5j 168 173 59 305 133 0.8 0.9 1.4 2.7 1.5 1.2 Jak3 tyrosine-protein kinase; Janus kinase 3 L35236 B5k 20 31 29 10 9 0.0 2.8 1.9 0.6 0.9 0.0 Jnk stress-activated protein kinase ( S A P K ) U15159 B51 20 14 25 10 17 0.0 0.0 2.2 0.0 1.5 0.0 L I M K ; L I M serine/threonine kinase U10871 B 5 m 542 427 121 416 114 0.5 0.8 1.0 0.6 1.0 0.7 M A P K ; M A P kinase; p38 X76850 B5n 194 549 80 621 181 2.4 3.2 3.0 2.4 4.2 3.0 M A P K A P K - 2 ; M A P K A P kinase 2 L02526 B6a 722 937 574 1020 467 0.4 1.7 1.8 0.7 2.0 1.5 M A P K K 1 ; M A P kinase kinase 3; M E K 1 U43187 B6b 20 89 20 119 83 3.6 4.3 5.5 5.6 10.3 2.0 M A P K K 3 ; M A P kinase kinase 3; M K K 3 , M E K 3 U18310 B6c 20 82 38 69 63 2.0 4.7 5.7 4.1 6.3 0.0 M A P K K 4 ; M A P kinase kinase 4; J N K K 1 ; S E K 1 ; X97052 B 6 d 20 33 31 24 30 3.1 0.0 1.9 0.7 2.9 0.0 M A P K K 6 ; M A P kinase kinase 6; M K K 6 M25811 B6e 20 18 18 6 10 1.8 0.0 1.0 0.0 0.9 0.0 PKC-alpha; protein kinase C alpha type X53532 B 6 f 20 21 18 31 53 1.6 0.0 1.6 4.7 0.1 0.0 PKC-beta; protein kinase C beta-II type M69042 B 6 g 536 624 71 820 394 1.3 1.1 1.1 0.8 1.6 2.3 PKC-delta; protein kinase C delta type DL1091 B 6 h 20 23 22 18 4 0.1 1.2 2.2 0.9 0.7 1.1 PKC-theta; protein kinase C theta type M28489 B 6 i 20 88 76 122 25 0.0 6.6 6.6 4.7 6.6 7.0 Rsk; ribosomal protein S6 kinase U03279 B6j 152 123 26 205 69 1.0 0.8 0.7 1.2 1.9 1.0 P I 3 - K p l l 0 M60651 B6k 147 54 48 126 118 0.0 0.4 0.7 0.3 1.8 0.5 PI3-Kp85 U43144 B61 20 7 12 14 24 0.0 0.0 1.0 0.0 2.1 0.0 P L C beta; phospholipase C beta 3 X95346 B 6 m 20 31 13 0 0 1.4 2.3 1.0 0.0 0.0 0.0 P L C gamma; phospholipase C gamma M63660 B6n 20 41 19 27 33 2.4 2.8 1.0 0.9 3.2 0.0 G-alpha-13 guanine nucleotide regulatory protein U10551 B7a 155 54 48 199 154 0.0 0.5 0.6 0.6 2.4 0.8 Gem; induced, immediate early protein X95403 B7b 839 543 213 686 554 0.4 0.9 0.7 0.3 1.6 0.6 Rab-2 ras-related protein X57277 B7c 20 80 35 48 66 4.2 2.2 5.7 1.0 6.2 0.0 R a c l murine homolog M21019 B7d 20 31 32 10 17 1.6 0.0 3.2 0.0 1.5 0.0 R-ras protein 175 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A+B mean SD mean SD A B C A B C U34960 B7e 127 81 82 107 34 0.0 0.6 1.3 0.7 1.1 0.6 transducin beta-2 subunit X64361 B 7 f 584 253 130 331 123 0.3 0.3 0.7 0.7 0.7 0.3 Vav; G D P - G T P exchange factor; proto-oncogene U57311 B7g 2783 1640 138 1713 299 0.6 0.5 0.6 0.5 0.7 0.6 14-3-3 protein eta U03184 B7h 195 120 40 138 46 0.7 0.4 0.8 1.0 0.6 0.6 cortactin; protein tyrosine kinase substrate U24160 B 7 i 430 171 119 229 71 0.2 0.2 0.7 0.4 0.7 0.5 Dvl2; dishevelled-2 tissue polarity protein U20238 B7j 20 50 58 91 18 0.0 1.8 5.7 4.4 5.5 3.8 GapIII; GTPase-activating protein M21065 B7k 120 961 309 958 142 5.7 7.6 10.8 6.6 8.5 8.8 IRF1; interferon regulatory factor 1 L09562 B71 20 42 39 76 73 0.0 3.9 2.4 7.5 3.8 0.2 P T P R G ; protein-tyrosine phosphatase gamma U92456 B 7 m 20 51 28 43 42 1.0 3.2 3.6 4.2 2.3 0.0 W B P 6 ; p S K - S R P K l X99063 B7n 20 419 68 314 45 17.1 22.4 23.4 17.4 13.1 16.6 Zyxin; L I M domain protein U59463 C l a 20 81 62 74 47 7.6 1.6 3.1 6.1 1.4 3.8 caspase-11; ICH-3 cysteine protease D28492 C l b 20 72 87 64 14 8.4 0.0 2.4 3.9 2.5 3.2 Caspase-3; Nedd2 cysteine protease U67321 C l c 20 68 64 170 61 7.1 1.7 1.5 11.8 8.0 5.8 caspase-7; Lice2; I C E - L A P 3 cysteine protease L37296 C l d 20 60 34 92 90 2.8 1.5 4.8 2.6 9.8 1.4 Bad; heterodimeric partner for B c l - X L and Bcl-2 U17162 C l e 1339 838 231 975 454 0.5 0.8 0.6 0.5 1.1 0.6 B A G - 1 ; bcl-2 binding protein Y13231 C l f 565 591 85 499 63 1.1 1.2 0.9 0.9 1.0 0.8 Bak apoptosis regulator; Bcl-2 family member L22472 cig 814 527 158 660 125 0.8 0.4 0.8 0.8 1.0 0.7 Bax; Bcl-2 heterodimerization partner M l 6506 C l h 174 125 123 177 219 1.5 0.2 0.5 2.5 0.4 0.2 Bcl-2; B cell lymphoma protein 2 U59746 C l i 20 16 14 24 27 1.4 0.0 1.1 2.7 0.0 1.0 B c l - W apoptosis regulator; Bcl-2 family member L35049 C l j 20 50 50 53 77 5.4 1.1 1.0 7.1 0.3 0.6 B c l - x L apoptosis regulator (bcl-x long) U75506 C l k 20 94 110 98 73 11.1 1.8 1.3 8.6 4.7 1.3 BID; apoptotic death agonist U13705 C l l 20 36 47 71 54 4.5 0.0 1.0 5.8 4.3 0.6 glutathione peroxidase (plasma protein) X76341 C l m 1198 542 143 802 274 0.4 0.3 0.6 0.6 0.9 0.5 glutathione reductase J03958 C l n 20 30 36 70 60 3.5 0.0 1.0 6.8 1.0 2.6 glutathione S-transferase A J03752 C2a 20 50 39 61 44 2.9 0.4 4.3 5.6 2.1 1.4 glutathione S-transferase (microsomal) J04696 C2b 131 140 24 155 50 0.9 1.2 1.2 1.6 1.0 0.9 glutathione S-transferase M u 1 X98055 C2c 20 80 71 73 76 6.7 0.0 5.4 7.6 3.4 0.0 gluthathione S-transferase (theta type I) D30687 C2d 20 136 38 91 32 6.9 4.9 8.7 3.8 6.4 3.5 G S T P i 1; glutathione S-transferase P i 1 U19463 C2e 242 275 159 246 162 1.7 0.4 1.3 1.7 0.9 0.4 A20 zinc finger protein; apoptosis inhibitor U05671 C 2 f 20 119 64 125 37 7.2 2.3 8.4 7.9 6.7 4.2 adenosine A I M receptor U05672 C2g 20 65 57 68 49 4.5 0.0 5.3 3.8 5.7 0.8 adenosine A 2 M 2 receptor L20331 C2h 20 269 78 289 145 9.8 13.1 17.6 19.2 18.0 6.1 adenosine A3 receptor 176 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A+B mean SD mean SD A B C A B C U49112 C 2 i 20 101 27 126 97 5.9 5.8 3.5 3.5 11.9 3.5 A L G - 2 ; calcium binding protein M30903 C2j 20 85 37 69 92 6.1 4.4 2.4 8.7 1.6 0.1 Blk ; B lymphocyte kinase; Src family member M94335 C2k 1486 1134 251 954 150 0.7 1.0 0.7 0.6 0.8 0.6 c-Akt proto-oncogene; Rac-alpha; protein kinase B L24495 C21 20 81 22 82 28 4.8 4.6 2.8 5.7 3.0 3.8 CD27; lymphocyte-specific N G F receptor family U25416 C 2 m 20 63 28 38 8 4.8 2.2 2.6 2.3 1.5 2.0 C D 30L receptor; lymphocyte activation antigen X65453 C2n 20 340 219 279 205 29.6 11.6 9.8 25.4 11.0 5.5 C D 4 0 L ; CD40 ligand X67083 C3a 20 25 26 121 15 2.6 0.0 1.1 7.0 5.5 5.8 Chop 10; murine homolog of Gaddl53 L08235 C3b 133 75 55 93 36 0.3 0.4 1.0 0.6 1.0 0.5 clusterin; complement lysis inhibitor U21050 C3c 247 288 24 296 40 1.1 1.1 1.3 1.2 1.3 1.0 C R A F 1 ; TNF/CD40 receptor-associated factor U83628 C3d 179 237 63 286 38 1.5 0.9 1.6 1.8 1.6 1.4 D A D - 1 ; defender against cell death 1 U39643 C3e 574 448 158 441 91 0.8 0.5 1.1 0.8 0.9 0.6 F A F 1 ; Fas-associated protein factor M83649 C 3 f 20 965 329 1388 544 66.7 34.9 43.3 38.1 83.0 87.1 Fas 1 receptor; Fas antigen (Apo-1 antigen) U06948 C3g 20 116 34 154 13 6.8 3.9 6.8 7.2 7.6 8.4 Fasl; Fas antigen ligand U97076 C3h 188 489 190 776 213 3.6 1.6 2.5 3.1 3.9 5.3 F L I P - L ; FLICE- l ike inhibitory protein U04807 C 3 i 20 68 18 73 37 4.5 2.8 3.0 1.6 4.7 4.8 fms-related tyrosine kinase 3 Flt3/Flk2 ligand L28177 C3j 20 94 91 134 65 10.0 2.2 1.9 8.9 3.0 8.2 gadd45; growth arrest/DNA-damage inducible U04710 C3k 467 462 191 461 93 1.5 0.7 0.8 1.2 0.8 0.9 insulin-like growth factor receptor II ( IGFRII) U00182 C31 20 61 46 87 63 4.6 0.4 4.2 8.0 2.8 2.3 insulin-like growth factor I receptor alpha subunit M87039 C 3 m 20 698 175 646 116 39.6 24.8 40.3 38.9 30.4 27.7 nitric oxide synthase, inducible ( iNOS) M20658 C3n 20 53 43 97 41 4.1 0.2 3.7 6.2 2.5 6.0 interleukin-1 receptor D17571 C4a 183 167 59 223 18 1.0 0.6 1.2 1.3 1.3 1.1 NADPH-cytochrome P450 reductase D83698 C4b 651 425 57 319 192 0.6 0.7 0.7 0.7 0.2 0.6 neuronal death protein X68193 C4c 4872 4234 322 3702 160 0.9 0.8 0.9 0.7 0.8 0.8 Nm23-M2; nucleoside diphosphate kinase B J04113 C4d 289 668 141 359 515 2.6 1.7 2.6 3.3 0.4 0.0 Nur77 early response protein U05341 C4e 1194 841 169 762 95 0.6 0.7 0.9 0.6 0.7 0.6 p55cdc; cell division control protein 20 X67914 C 4 f 582 2160 1143 1780 252 2.0 3.3 5.9 3.2 2.6 3.4 PD-1 possible cell death inducer D83966 C4g 20 107 103 130 129 0.5 4.9 10.8 14.0 3.2 2.4 protein tyrosine phosphatase U57324 C4h 20 81 27 128 32 5.4 2.7 4.1 8.0 6.5 4.8 PS-2; homolog of the Alzheimer's disease gene Z27088 C 4 i 20 62 18 69 39 3.4 2.1 3.9 5.1 4.0 1.3 relaxin U25995 C4j 784 434 49 558 147 0.5 0.5 0.6 0.7 0.9 0.5 RIP cell death protein; Fas/APO-1 (CD95) U16805 C4k 20 41 44 19 23 4.4 0.1 1.7 2.3 0.6 0.1 Sik; Src-related intestinal kinase U25844 C41 20 88 42 115 102 2.0 5.7 5.5 2.3 11.7 3.3 S P B ; serpin; serine proteinase inhibitor 177 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name umber A + B mean S D mean SD A B C A B C U43900 C4m 20 56 18 84 57 3.4 1.8 3.3 2.8 7.5 2.3 S T A M ; signal transducing adaptor molecule Z12604 C4n 20 25 33 29 40 0.2 0.4 3.2 3.8 0.0 0.6 stromelysin-3; matrix metalloproteinase-11 U44088 C5a 20 302 68 274 128 13.9 19.0 12.5 12.2 8.2 20.8 T D A G 5 1 ; couples T C R signaling to Fas X57796 C5b 121 265 23 288 124 2.2 2.4 2.0 1.9 3.6 1.7 T N F 55; tumor necrosis factor 1 (55 kDa) U37522 C5c 151 596 225 908 16 2.5 3.9 5.4 5.9 6.0 6.1 T R A I L ; TNF-related apoptosis inducing ligand M59378 C5d 580 5315 1715 5566 2160 12.2 6.3 9.0 8.0 7.0 13.9 tumor necrosis factor receptor 1 (TNFR-1) X72711 C5e 20 448 178 636 159 30.6 13.0 23.7 31.3 24.2 40.0 activator -1 1404<Da subunit; replication factor U12273 C 5 f 20 213 95 187 160 14.2 5.3 12.5 18.5 6.3 3.4 A P endonuclease (Apex) U43678 C5g 20 90 54 127 37 5.2 1.5 6.8 8.0 4.4 6.7 Atm; ataxia telangiectasia murine homolog M38700 C5h 465 243 53 293 43 0.6 0.4 0.5 0.6 0.7 0.6 ATP-dependent D N A helicase II 70 kDa subunit; X66323 C 5 i 20 69 12 56 14 4.0 2.8 3.7 2.1 2.8 3.5 ATP-dependent D N A helicase II 80-kDa subunit; U04674 C5j 20 77 30 104 37 4.4 2.2 5.1 4.5 7.3 3.9 D N A ligase I U66058 C5k 20 133 27 115 54 6.3 8.2 5.6 3.1 8.4 5.9 D N A ligase III D17384 C51 349 115 70 149 31 0.5 0.1 0.4 0.5 0.4 0.4 D N A polymerase alpha catalytic subunit (p 180) D10061 C5m 20 158 62 172 104 9.3 4.4 10.1 4.5 14.5 6.9 D N A topoisomerase I (Top I) D12513 C5n 219 190 68 199 151 0.6 1.2 0.9 0.5 1.7 0.6 D N A topoisomerase II (Top II) X96618 C6a 885 466 24 522 165 0.5 0.5 0.5 0.6 0.4 0.8 P A 6 stromal protein; R A G 1 gene activator Z21848 C6b 352 208 118 200 51 0.9 0.3 0.6 0.7 0.5 0.5 DNA-polymerase delta catalytic subunit U00478 C6c 20 147 83 181 24 10.6 2.7 8.9 9.4 10.1 7.7 D N A s e I X07414 C6d 20 272 128 307 101 20.7 8.3 11.9 20.4 15.4 10.2 E R C C - 1 ; D N A excision repair protein S71186 C6e 20 119 88 179 44 6.4 1.3 10.1 9.6 10.7 6.5 E R C C 3 D N A repair helicase; DNA-repair protein D16306 C 6 f 148 197 56 272 62 1.4 0.9 1.6 1.8 2.3 1.4 E R C C 5 excision repair protein; DNA-repair U42190 C6g 20 77 62 142 51 5.9 0.3 5.4 4.4 9.4 7.6 G T B P ; G/T-mismatch binding protein; M S H 6 D49429 C6h 20 174 51 226 57 11.5 6.4 8.2 12.6 13.3 8.0 HR21spA; protein involved in D N A repair X92410 C 6 i 574 374 109 469 194 0.8 0.4 0.8 0.7 1.2 0.6 M H R 2 3 A ; Rad23 U V excision repair protein X92411 C6j 2651 2349 196 2472 227 0.9 0.8 0.9 0.8 1.0 1.0 M H R 2 3 B ; Rad23 U V excision repair protein U59883 C6k 144 182 30 159 33 1.5 1.1 1.2 0.9 1.0 1.4 M L H 1 D N A mismatch repair protein D64107 C61 263 165 190 247 288 1.4 0.0 0.4 2.2 0.5 0.2 M m L i m l 5 ; RecA-like gene; D M C 1 homolog D13473 C6m 20 62 27 50 33 3.1 1.8 4.5 2.8 4.0 0.8 MmRad51; RecA homolog Z32767 C6n 20 163 126 117 92 15.3 5.9 3.3 10.2 6.3 1.0 MmRad52; yeast D N A repair Rad52 homolog U21011 C7a 128 81 38 142 73 0.9 0.3 0.7 0.5 1.5 1.4 M S H 2 D N A mismatch repair protein X53068 C7b 343 203 28 175 51 0.7 0.6 0.5 0.7 0.5 0.4 P C N A ; proliferating cell nuclear antigen 178 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A+B mean SD mean SD A B C A B C AB000777 C7c 20 69 64 72 28 6.4 0.0 4.0 2.1 4.0 4.8 photolyase/blue-light receptor homolog U28724 C7d 122 91 98 86 38 1.7 0.1 0.4 0.5 1.1 0.6 PMS2 D N A mismatch repair protein U02098 C7e 20 117 42 62 36 8.3 5.2 4.2 1.3 3.2 4.9 pur-alpha transcriptional activator U66887 C 7 f 326 133 104 192 32 0.7 0.1 0.4 0.5 0.7 0.6 Rad50; D N A repair protein M29475 C7g 20 39 34 71 23 3.3 0.0 2.6 4.8 3.4 2.5 R A G - 1 ; V(D)J recombination activating protein M64796 C7h 20 52 46 88 57 3.3 0.0 4.5 7.7 3.3 2.3 R A G - 2 ; V(D)J recombination activating protein U46854 C 7 i 20 77 44 117 50 3.6 1.8 6.2 6.6 7.9 3.0 ShcC adaptor; She-related; brain-specific X81464 C7j 687 442 15 537 114 0.6 0.7 0.6 0.6 1.0 0.7 translin; recombination hotspot binding protein X96859 C7k 20 115 66 118 49 4.1 3.7 9.6 4.4 8.7 4.6 ubiquitin-conjugating enzyme X99018 C71 20 51 71 42 29 6.6 0.0 1.1 3.8 1.5 1.1 U n g l ; uraci l-DNA glycosylase X74351 C7m 20 60 51 23 20 6.0 1.6 1.4 1.9 1.6 0.0 X P A C ; xeroderma pigmentosum group A U02887 C7n 20 66 42 25 17 3.8 5.2 1.0 2.0 1.6 0.3 X R C C 1 DNA-repair protein, affecting ligation U17698 D l a 20 215 104 285 100 13.4 14.2 4.8 11.3 20.0 11.4 ablphilin-1 (abi-1); similar to H O X D 3 M94087 D l b 20 15 13 140 141 1.3 0.0 1.0 4.9 14.9 1.2 activating transcription factor 4 (mATF4) L12721 D i e 20 46 64 170 194 6.0 0.0 1.0 3.7 19.7 2.1 adipocyte differentiation-associated protein D26046 D i d 20 33 36 308 278 3.6 0.0 1.4 10.0 31.2 5.0 A T motif-binding factor A T B F 1 L36435 D i e 20 288 76 406 357 17.3 10.1 15.9 15.9 40.0 5.1 basic domain/leucine zipper transcription factor U36760 D l f 20 77 60 444 487 7.4 2.0 2.3 9.3 50.3 7.0 brain factor 1 (Hfhbfl) S53744 D i g 20 23 20 118 103 1.6 0.0 1.9 8.2 0.0 9.5 brain specific transcription factor N U R R - 1 S68377 D l h 20 59 59 414 339 6.4 1.2 1.4 9.2 40.2 12.8 Brn-3.2 P O U transcription factor M58566 D l i 20 41 54 615 535 5.1 0.0 1.0 6.5 59.5 26.3 butyrate response factor 1 U36340 D l j 20 22 19 610 532 1.6 0.0 1.7 5.6 58.5 27.3 C A C C C Box- binding protein B K L F X61800 D l k 20 57 58 191 125 6.1 0.5 1.9 6.8 5.2 16.7 C C A A T - binding transcription factor {CI E B P ) M37163 D l l 20 29 35 203 126 3.4 0.0 1.0 6.5 17.4 6.5 caudal type homeobox 1 (Cdx l ) S74520 D i m 20 21 21 248 141 2.1 0.0 1.0 9.6 20.5 7.2 caudal type homeobox 2 (Cdx2) U42554 D i n 20 30 15 296 72 2.4 1.1 1.0 16.9 17.0 10.7 Sim transcription factor L12147 D2a 20 92 67 46 80 8.5 3.1 2.4 7.0 0.0 0.0 early B cell factor (EBF) LI2703 D2b 20 51 72 52 91 6.7 0.0 1.0 7.9 0.0 0.0 engrailed protein (En-1) homolog LI2705 D2c 20 32 40 45 52 3.9 0.0 1.0 5.3 1.2 0.4 engrailed protein (En-2) homolog U01036 D2d 20 367 42 423 111 18.9 16.1 20.1 27.2 16.2 20.1 erythroid transcription factor N F - E 2 U05252 D2e 20 36 39 96 74 3.9 0.0 1.6 8.7 4.4 1.3 DNA-binding protein S A T B 1 L10075 D 2 f 20 89 79 170 51 7.6 0.0 5.8 10.2 9.8 5.6 DNA-binding protein S M B P 2 179 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A+B mean SD mean SD A B C A B c X72310 D2g 1709 1093 230 1153 9 0.7 0.5 0.7 0.7 0.7 0.7 DP-1 (DRTF-polipeptide 1) transcription factor X86925 D2h 20 157 73 262 74 12.1 5.5 6.0 16.4 13.9 9.1 E2F-5 transcription factor M20157 D 2 i 20 1372 770 1446 325 110.8 59.8 35.3 53.5 81.9 81.5 Egr-1 Zn-finger regulatory protein U19617 D2j 340 315 64 460 99 1.1 0.7 1.0 1.0 1.6 1.4 Elf-1 (Ets family transcription factor) L21671 D2k 585 342 201 385 191 0.4 0.4 1.0 0.9 0.8 0.3 epidermal growth factor receptor kinase substrate M22115 D21 20 88 47 155 34 7.1 3.6 2.6 7.7 6.1 9.5 E R A - 1 protein (ERA-1-993) U58533 D2m 323 61 34 161 63 0.3 0.2 0.1 0.4 0.4 0.7 Erf; Ets-related transcription factor M97200 D2n 20 25 24 104 62 2.4 0.0 1.4 6.3 1.7 7.6 erythroid kruppel-like transcription factor X63190 D3a 20 34 40 31 49 3.9 0.0 1.3 4.4 0.0 0.3 Ets-related protein P E A 3 J04103 D3b 20 75 108 129 136 10.0 0.0 1.3 14.0 0.8 4.7 Ets-2 transcription factor Z36885 D3c 20 62 38 175 85 5.3 2.3 1.7 13.1 8.6 4.6 Ets-related protein Sap 1A M74517 D3d 20 178 27 265 36 10.0 7.4 9.4 14.7 13.9 11.2 G A binding protein beta-2 chain M98339 D3e 20 37 48 45 77 4.6 0.0 1.0 6.7 0.0 0.1 G A T A binding transcription factor ( G A T A - 4 ) X55123 D 3 f 20 55 71 117 169 6.8 0.0 1.5 15.6 0.5 1.4 G A T A - 3 transcription factor L39770 D3g 20 63 56 64 72 5.3 0.0 4.2 7.4 1.2 1.1 G b x 2 U59876 D3h 20 58 58 76 35 6.3 1.4 1.0 3.6 2.2 5.7 glial cells missing gene homolog ( m G C M l ) U20344 D 3 i 20 114 75 129 65 9.9 2.6 4.6 10.2 4.2 5.0 Gut-specific Kruppel-like factor G K L F X61754 D3j 20 138 49 218 20 9.3 4.4 7.2 11.4 11.6 9.7 heat shock transcription factor 2 (HSF 2) L35949 D3k 20 73 85 241 152 8.5 0.6 1.9 5.9 20.5 9.7 hepatocyte nuclear factor 3; forkhead homolog 8 D49474 D31 20 67 56 271 75 6.6 1.5 2.1 13.8 17.2 9.7 H M G - b o x transcription factor from testis X53476 D3m 994 555 184 925 494 0.5 0.8 0.4 0.6 1.5 0.7 H M G - 1 4 non histone chromosomal protein M17192 D3n 20 40 47 118 56 4.6 0.0 1.4 4.7 4.0 9.1 homeobox protein 1.1 (Hox-1.1) M26283 D4a 20 134 84 157 48 10.5 2.2 7.5 10.1 5.3 8.1 homeobox protein 2.1 (Hox-2.1) X13721 D4b 20 44 59 57 82 5.6 0.0 1.0 7.6 0.6 0.4 homeobox protein 2.4 (Hox-2.4) M34857 D4c 20 26 30 159 212 3.0 0.0 1.0 20.0 0.0 3.9 homeobox protein 2.5 (Hox-2.5) X07439 D4d 20 49 69 72 118 6.4 0.0 1.0 10.4 0.0 0.5 homeobox protein 3.1 (Hox-3.1) J03770 D4e 20 166 183 122 181 18.8 2.0 4.1 16.5 0.6 1.1 homeobox protein 4.2 (Hox-4.2) X14759 D 4 f 20 25 28 71 51 2.8 0.0 1.0 6.4 1.3 3.0 homeobox protein 7.1 (Hox-7.1) X59252 D4g 20 38 35 48 29 3.5 0.0 2.2 3.1 0.8 3.3 homeobox protein 8 (Hox-8) X73573 D4h 20 103 44 124 71 4.9 3.1 7.5 10.3 4.7 3.6 homeobox protein H O X D - 3 L03547 D 4 i 156 442 85 419 9 2.3 2.8 3.4 2.6 2.7 2.7 ikaros D N A binding protein U62522 D4j 20 199 109 209 193 15.9 8.8 5.3 19.0 0.0 12.3 Sp4 zinc finger transcription factor 180 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A+B mean S D mean SD A B C A B C U19119 D4k 272 1141 792 2176 1524 3.5 7.4 1.7 4.4 14.5 5.1 interferon inducible protein 1 J03168 D41 442 614 53 802 153 1.5 1.3 1.4 1.8 2.2 1.5 interferon regulatory factor 2 (IRF 2) U25096 D4m 207 333 76 338 35 1.7 1.2 2.0 1.8 1.7 1.4 Kruppel-like factor L K L F X90829 D4n 20 146 127 184 82 11.8 0.0 10.2 10.8 4.6 12.3 Lbx 1 transcription factor U63386 D5a 20 21 21 57 70 2.1 0.0 1.0 6.8 0.0 1.8 Mph-1 transcriptional repressor for hox genes X71327 D5b 20 44 59 77 48 5.6 0.0 1.0 6.6 2.2 2.8 MRE-binding transcription factor L26507 D5c 122 88 83 118 27 1.5 0.5 0.2 1.2 0.8 0.8 myocyte nuclear factor ( M N F ) X56182 D5d 20 16 15 57 74 1.5 0.0 1.0 7.0 0.0 1.5 myogenic factor 5 U29086 D5e 20 42 56 71 74 5.3 0.0 1.0 7.8 1.5 1.3 neuronal helix-loop-helix protein N E X - 1 D90176 D 5 f 20 48 36 67 39 4.4 1.8 1.0 5.2 3.6 1.3 N F - 1 B protein (transcription factor) M57999 D5g 172 399 60 637 249 2.4 2.6 1.9 2.0 4.5 4.5 NF-kappa B binding subunit (TFDB5) U20532 D5h 1852 1133 260 1482 252 0.8 0.5 0.6 0.9 0.9 0.6 nuclear factor related to P45 N F - E 2 U53228 D5i 141 125 73 152 84 1.1 0.3 1.3 1.8 0.8 0.7 nuclear hormone receptor ROR-alpha-1 M96823 D5j 20 61 52 117 27 5.8 0.6 2.9 5.7 4.6 7.3 nucleobindin M34381 D5k 20 43 36 121 44 3.1 0.1 3.3 5.1 8.6 4.5 octamer binding transcription factor (Oct 3) X57487 D51 234 198 37 335 56 0.8 0.7 1.0 1.7 1.5 1.2 P A X - 8 (paired box protein P A X 8) U41626 D5m 1930 1688 262 1936 577 0.7 0.9 1.0 0.7 1.3 1.0 split hand/foot gene X94125 D5n 457 412 252 355 118 1.2 0.3 1.2 1.0 0.5 0.8 SRY-box containing gene 3 (Sox3) M97013 D6a 20 54 76 82 89 7.1 0.0 1.0 8.8 0.0 3.5 P A X - 5 (B cell specific transcription factor) X63963 D6b 20 44 60 46 59 5.6 0.0 1.0 5.7 0.0 1.3 P A X - 6 (paired box protein) U43788 D6c 20 23 24 26 45 2.4 0.0 1.0 3.9 0.0 0.0 P O U domain (class 2) associated factor 1 D50621 D6d 20 52 73 110 107 6.8 0.0 1.0 11.7 2.4 2.5 PSD-95/SAP90A M35523 D6e 20 31 24 69 52 3.0 0.8 1.0 5.5 0.6 4.3 retinoic acid binding protein II, (CRABP-I I ) M84819 D 6 f 20 36 46 31 30 4.4 0.0 1.0 3.0 0.0 1.7 retinoic acid receptor (RXR-gamma) U09419 D6g 20 167 93 230 54 13.8 5.8 5.6 14.4 9.0 11.2 retinoid X receptor interacting protein (RIP 15) M31042 D6h 1413 1307 597 1411 383 1.4 0.7 0.6 1.3 1.0 0.8 T-lymphocyte activated protein X61753 D6i 422 411 190 327 21 1.5 0.6 0.8 0.8 0.8 0.7 transcription factor 1 for heat shock gene Y07960 D6j 20 144 94 174 67 9.8 1.8 10.1 12.6 6.5 7.0 transcription factor B A R X 1 U53925 D6k 414 228 186 277 23 1.0 0.1 0.5 0.7 0.6 0.6 transcription factor C 1 U51037 D61 806 549 146 648 54 0.8 0.5 0.8 0.9 0.8 0.8 transcription factor C T C F (11 zinc fingers ) Z27410 D6m 20 121 97 117 26 10.7 1.0 6.5 7.4 4.9 5.4 transcription factor L I M - 1 U19118 D6n 20 220 65 148 84 11.2 7.7 14.2 11.2 2.9 8.0 transcription factor L R G - 21 181 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name umber A+B mean SD mean SD A B C A B C U02079 D7a 20 89 130 87 90 12.0 0.0 1.5 9.1 0.2 3.8 transcription factor N F A T 1, isoform alpha X70298 D7b 20 49 69 89 146 6.4 0.0 1.0 12.9 0.0 0.5 SRY-box containing gene 4 M83380 D7c 20 51 72 97 98 6.7 0.0 1.0 9.8 0.0 4.7 transcription factor Re lB D00926 D7d 20 97 109 73 82 10.8 0.0 3.8 8.2 0.3 2.5 transcription factor S -II X91753 D7e 673 473 33 632 98 0.7 0.7 0.7 1.1 0.9 0.8 transcription factor SEF2 X56959 D 7 f 20 22 24 38 46 2.4 0.0 1.0 4.5 0.0 1.2 transcription factor SP1P D17407 D7g 20 62 90 48 59 8.3 0.0 1.0 5.7 0.0 1.5 transcription factor SP2 X60831 D7h 310 178 74 246 109 0.8 0.3 0.6 1.2 0.5 0.7 transcription factor U B F S74227 D 7 i 368 258 91 304 68 0.7 0.5 0.9 1.0 0.8 0.7 transcriptional enhancer factor 1 (TEF-1) X57621 D7j 3770 2817 565 3116 90 0.9 0.6 0.8 0.8 0.8 0.8 Y B 1 D N A binding protein L13968 D7k 509 272 145 171 138 0.7 0.2 0.7 0.0 0.5 0.5 Y Y 1 ( U C R B P ) transcriptional factor U47104 D71 20 27 32 40 69 3.1 0.0 1.0 6.0 0.0 0.0 zinc finger Kruppel type Zfp 92 U41671 D7m 20 31 38 7 12 3.7 0.0 1.0 0.0 0.0 1.1 zinc finger transcription factor RU49 M32309 D7n 20 37 37 29 48 3.7 0.0 1.9 4.2 0.0 0.2 zinc finger X-chromosomal protein ( Z F X ) Z31663 E l a 20 103 105 115 37 11.2 2.2 2.1 6.8 6.9 3.7 activin type I receptor U11688 E l b 20 7 12 24 41 0.0 0.0 1.0 3.6 0.0 0.0 orphan receptor D16250 E l c 162 98 39 174 59 0.8 0.6 0.3 0.8 1.5 0.9 bone morphogenetic protein receptor U56819 E l d 20 46 25 94 37 1.4 1.9 3.7 4.2 6.8 3.1 C - C chemokine receptor ( M C P - 1 R A ) X04836 E l e 20 82 52 142 64 7.1 2.8 2.4 3.7 7.6 10.0 C D 4 receptor (T cell activation antigen) M83312 E l f 20 1128 370 1419 535 77.7 44.4 47.2 49.0 63.1 100.7 C D 40L receptor (TNF receptor family) L05630 E l g 792 648 29 816 149 0.9 0.8 0.8 1.1 0.8 1.1 C 5 A receptor X72305 E l h 20 21 21 19 27 2.1 0.0 1.0 0.4 0.0 2.5 corticotropin releasing factor receptor U32329 E l i 20 7 13 3 5 0.0 0.0 1.1 0.5 0.0 0.0 endothelin b receptor (Ednrb) M58288 E l j 20 20 21 15 25 2.1 0.0 1.0 2.2 0.0 0.1 granulocyte colony - stimulatings factor receptor S71251 E l k 20 182 89 200 143 14.2 7.1 6.0 17.4 9.5 3.1 monotype chemoattractant protein 3 D26177 E l l 20 24 26 26 45 2.6 0.0 1.0 3.9 0.0 0.0 D-factor/LIF receptor L47239 E l m 20 15 13 10 18 1.3 0.0 1.0 1.6 0.0 0.0 E R B B - 2 receptor; c-neu; H E R 2 tyrosine kinase L47240 E l n 20 29 35 19 33 3.4 0.0 1.0 2.9 0.0 0.0 E R B B - 3 receptor J04843 E2a 20 44 54 49 64 5.3 0.3 1.0 6.1 0.0 1.2 erythropoietin receptor X59927 E2b 20 23 12 6 10 1.9 0.7 1.0 0.0 0.9 0.0 fibroblast growth factor receptor 4 M28998 E2c 20 21 22 37 22 0.0 2.2 1.0 3.1 1.2 1.2 fibroblast growth factor receptor basic (b F G F - R ) D17292 E2d 20 184 39 266 32 10.0 10.7 7.0 11.5 14.4 14.1 G-protein-coupled receptor 182 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name umber A+B mean SD mean SD A B C A B C M85078 E2e 2228 1937 733 2229 170 1.2 0.9 0.5 1.0 1.1 0.9 G M - C S F receptor M98547 E2f 157 268 47 297 63 1.9 1.4 1.8 1.7 1.6 2.3 growth factor receptor U29173 E2g 194 261 123 261 72 2.1 l . l 0.9 1.7 1.0 1.3 lymphotoxin receptor ( T N F R family) Z11974 E2h 20 57 79 80 115 7.4 0.2 1.0 10.6 1.3 0.1 macrophage mannose receptor X04367 E2i 20 16 14 9 14 1.4 0.0 1.0 0.1 1.3 0.0 pre-platelet-derived growth factor receptor U36203 E2j 148 280 49 271 68 1.5 1.9 2.2 1.5 1.6 2.4 snoN; ski-related oncogene D25540 E2k 20 48 46 48 54 5.1 1.1 1.0 5.3 1.9 0.0 TGF-beta receptor type 1 M89641 E21 20 20 18 42 11 1.5 0.0 1.6 1.5 2.4 2.5 interferon alpha-beta receptor M28233 E2m 20 60 85 40 19 7.9 0.0 1.1 2.8 2.3 0.9 interferon-gamma receptor X59769 E2n 20 12 11 9 16 0.9 0.0 1.0 1.4 0.0 0.0 interleukin-1 receptor type II L12120 E3a 20 106 4 148 78 5.5 5.3 5.1 9.0 3.0 10.2 interleukin-10 receptor M81832 E3b 20 33 41 115 86 0.0 4.0 1.0 0.9 8.8 7.7 somatostatin receptor 2 L20048 E3c 499 544 158 1011 543 0.9 1.5 1.0 0.8 3.0 2.3 interleukin-2 receptor gamma chain M29855 E3d 20 136 53 89 26 4.1 9.4 7.0 5.2 3.0 5.3 interleukin-3 receptor M27959 E3e 20 145 15 125 42 6.4 7.8 7.6 8.6 4.7 5.5 interleukin-4 receptor D90205 E3f 20 83 39 38 25 2.0 4.8 5.7 3.2 0.8 1.7 interleukin-5 receptor M29697 E3g 20 37 38 48 59 0.6 4.0 1.0 5.7 0.0 1.5 interleukin-7 receptor D17630 E3h 20 9 10 4 4 0.4 0.0 1.0 0.0 0.4 0.2 interleukin-8 receptor M84746 E3i 20 13 11 18 22 0.9 0.0 1.0 2.2 0.6 0.0 interleukin-9 receptor X53779 E3j 20 333 159 279 147 25.8 11.7 12.5 21.7 13.3 7.0 androgen receptor U18542 E3k 20 7 11 7 10 0.1 0.0 1.0 1.0 0.2 0.0 calcitonin receptor lb M38651 E31 20 34 30 34 46 2.9 0.0 2.2 4.3 0.8 0.0 estrogen receptor X13358 E3m 20 171 5 251 68 8.9 8.5 8.4 11.6 16.3 9.7 glucocorticoid receptor form A M33324 E3n 20 7 12 2 3 0.0 0.0 1.0 0.3 0.0 0.0 growth hormone receptor J05149 E4a 20 43 7 87 29 1.9 2.5 2.1 2.8 4.6 5.7 insulin receptor L24563 E4b 20 39 52 0 0 0.0 4.9 1.0 0.0 0.0 0.0 insulin receptor substrate-1 (IRS-1) M22959 E4c 20 80 105 21 18 0.9 10.1 1.0 0.3 0.8 2.1 prolactin receptor P R L R 2 Z19521 E4d 20 281 99 183 78 11.1 19.8 11.3 10.1 4.9 12.5 low density lipoprotein receptor S49542 E4e 20 109 155 19 32 0.0 14.3 2.0 0.0 0.0 2.8 5-hydroxytryptamine receptor Zl1597 E4f 20 98 96 19 24 3.5 10.3 1.0 2.4 0.2 0.3 5-hydroxytryptamine (serotonin) receptor l b X72230 E4g 20 47 58 26 29 0.4 5.7 1.0 0.0 1.1 2.8 5-hydroxytryptamine (serotonin) receptor l c Z14224 E4h 20 33 8 73 45 2.1 1.4 1.5 1.7 6.1 3.2 5-hydroxytryptamine (serotonin) receptor le beta 183 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A+B mean SD mean SD A B c A B C Z15119 E4i 20 12 10 15 16 0.8 0.0 1.0 1.6 0.0 0.7 5-hydroxytryptamine (serotonin) receptor 2c X72395 E4j 20 7 12 2 3 0.0 0.0 1.0 0.0 0.3 0.0 5-hydroxytryptamine (serotonin) receptor 3 Z23107 E4k 20 18 31 3 5 0.0 0.0 2.7 0.0 0.4 0.0 5-hydroxytryptamine (serotonin) receptor 7 K02582 E41 20 12 21 9 16 0.0 0.0 1.8 1.4 0.0 0.0 acetylcholine receptor delta submit L I 0084 E 4 m 20 46 56 18 22 5.4 0.0 1.5 0.6 2.1 0.0 adrenergic receptor beta 1 U17985 E4n 20 22 34 36 27 0.3 0.0 3.1 3.1 2.1 0.4 cannabinoid receptor 1 (brain) U21681 E5a 20 28 33 7 13 3.3 0.0 1.0 1.1 0.0 0.0 cannabinoid receptor 2 (macrophage, CB2) U19880 E5b 20 28 32 6 11 0.1 3.2 1.0 1.0 0.0 0.0 dopamine receptor 4 U46923 E5c 20 49 64 0 0 0.0 6.1 1.3 0.0 0.0 0.0 G-protein coupled receptor M86566 E5d 20 101 153 27 25 0.0 13.9 1.3 1.6 2.5 0.0 G A B A - A receptor alpha-1 subunit M92378 E5e 20 116 140 96 11 1.4 13.9 2.2 5.4 4.9 4.3 G A B A - A transporter 1 L04663 E 5 f 20 87 106 23 23 0.0 10.3 2.9 0.0 2.3 1.2 G A B A - A transporter 3 L04662 E5g 20 163 79 215 119 3.6 10.0 10.9 7.9 17.6 6.8 G A B A - A transporter 4 X57497 E5h 122 276 124 296 140 3.4 2.0 1.4 2.5 3.5 1.2 glutamate receptor, ionotropic A M P A 1 D10217 E 5 i 20 96 71 172 87 7.1 0.8 6.7 4.5 13.2 8.1 glutamate receptor, ionotropic D10651 E5j 20 42 36 143 74 3.2 0.0 3.1 11.4 5.1 4.9 glutamate receptor, ionotropic N M D A 2 B M14537 E5k 20 7 12 0 0 0.0 0.0 1.0 0.0 0.0 0.0 nicotinic acetylcholine receptor X91144 E51 20 32 47 127 18 0.3 0.3 4.4 7.4 6.1 5.6 P-selectin (glycoprotein ligand-1) D25281 E 5 m 20 49 69 48 2 0.4 0.6 6.4 2.4 2.5 2.4 catenin alpha X14951 E5n 592 1010 349 975 342 1.1 1.9 2.2 1.0 2.0 2.0 C D 18 antigen beta subunit (LFA-1) M l 8934 E6a 20 15 13 0 0 0.0 1.2 1.0 0.0 0.0 0.0 CD2 antigen M34563 E6b 20 58 51 19 16 0.0 5.0 3.7 1.9 0.7 0.3 CD28 (receptor for B71) M33158 E6c 20 102 160 34 29 0.0 14.4 1.0 3.1 0.2 1.9 CD3 antigen, delta polypeptide L06039 E6d 20 318 225 367 265 7.3 28.6 11.8 33.6 11.5 10.0 CD31; platelet endothelial cell adhesion molecule M27129 E6e 1345 2090 962 2610 544 2.3 0.9 1.5 2.1 1.5 2.3 CD44 antigen U03856 E 6 f 20 344 62 236 49 14.7 20.7 16.2 11.8 9.4 14.3 CD45 associated protein (CD 45-ap, L S M - 1 ) D10329 E6g 570 810 300 901 537 0.8 1.6 1.8 0.5 2.0 2.2 CD7 antigen M34510 E6h 5970 8776 1690 9420 1949 1.8 1.2 11.4 1.3 1.6 1.9 C D 14 antigen L16928 E 6 i 761 734 282 644 782 0.6 1.0 1.3 0.6 0.0 2.0 CD22 antigen X07640 E6j 494 612 502 851 136 2.3 0.2 1.2 1.6 1.5 2.0 cell surface glycoprotein M A C - 1 alpha subunit X05719 E6k 20 76 110 111 54 10.1 0.0 1.3 8.5 4.8 3.3 C T L A - 4 (immunoglobin superfamily member) L33779 E61 20 28 30 43 45 3.0 0.0 1.3 4.5 2.0 0.0 desmocollin 2 184 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A+B mean SD mean SD A B C A B C U43512 E6m 794 233 120 298 60 0.3 0.1 0.4 0.4 0.5 0.3 dystroglycan 1 X04648 E6n 20 143 64 175 36 7.6 3.8 10.1 10.8 7.5 7.9 glutamate receptor channel subunit gamma X75427 E7a 20 66 37 37 18 5.3 3.0 1.6 1.3 2.9 1.3 integrin alpha 2 (CD49b) X53176 E7b 1292 634 297 791 104 0.6 0.2 0.7 0.6 0.6 0.7 integrin alpha 4 U14135 E7c 685 744 179 1002 242 1.3 0.8 1.1 1.1 1.6 1.7 integrin alpha 5 (CD51) X69902 E7d 20 63 67 118 37 2.8 0.0 6.7 5.7 4.2 7.8 integrin alpha 6 L23423 E7e 20 89 48 82 25 5.3 1.8 6.4 4.2 2.8 5.3 integrin alpha 7 X58384 E7f 20 202 181 97 24 1.7 19.7 9.0 6.2 4.6 3.8 dipeptidyl peptidase IV Y00769 E7g 733 798 104 831 87 1.2 1.0 1.0 1.0 1.1 1.3 integrin beta M95633 E7h 151 416 168 248 220 3.7 3.1 1.5 2.8 2.1 0.0 integrin beta 7 subunit X52264 E 7 i 20 258 125 363 164 20.0 8.0 10.9 11.6 15.6 27.3 intercellular adhesion molecule-1 J02870 E7j 238 485 223 505 64 2.0 1.1 3.0 1.8 2.4 2.1 lamimin receptor 1 M31131 E7k 20 53 49 50 68 4.9 0.0 3.2 6.4 0.0 1.1 neuronal-cadherin (N-cadherin) XI4943 E71 20 52 47 33 34 4.6 0.0 3.2 3.4 1.5 0.0 neuronal cell surface protein F3 M84487 E7m 20 23 32 1 1 0.5 0.0 3.0 0.1 0.0 0.0 vascular cell adhesion protein 1 D13867 E7n 20 8 14 11 17 0.0 0.0 1.3 1.6 0.1 0.0 V L A - 3 alpha subunit D12482 F l a 20 46 53 18 25 5.2 0.0 1.8 2.4 0.0 0.4 basic fibroblast growth factor (b- FGF) L24755 F i b 20 37 14 25 36 1.4 2.7 1.6 3.3 0.5 0.0 bone morphogenetic protein 1 L25602 F l c 20 207 213 76 121 7.2 22.2 1.6 10.8 0.7 0.0 bone morphogenetic protein 2 (BMP-2) X56848 F i d 20 309 82 178 137 13.9 20.1 12.3 16.4 2.9 7.5 bone morphogenetic protein 4 (BMP-4) X56906 F i e 20 140 30 104 31 8.1 5.3 7.6 6.9 3.8 4.9 bone morphogenetic protein 7 (BMP-7) M97017 F l f 20 116 34 100 55 4.6 7.8 5.1 8.0 2.7 4.3 bone morphogenetic protein 8a (BMP-8a) U12983 F i g 20 108 34 71 84 7.1 3.8 5.4 8.2 0.1 2.3 Cek 5 receptor protein tyrosine kinase ligand U14752 F l h 20 60 46 77 100 5.5 0.9 2.7 9.7 0.8 1.2 Cek 7 receptor protein tyrosine kinase ligand M93428 F l i 20 21 22 44 46 2.2 0.0 1.0 4.8 0.5 1.4 endothelial ligand for L-selectin ( G L Y C A M 1) J00380 F l j 20 19 19 34 43 1.9 0.0 1.0 4.1 0.0 1.0 epidermal growth factor (EGF) D38258 F l k 20 58 72 57 51 7.0 0.0 1.8 5.8 1.6 1.2 fibroblast growth factor 9 Z29532 F l l 20 101 116 120 151 11.7 1.0 2.5 14.7 1.6 1.7 follistatin M34815 F l m 20 56 81 72 66 7.5 0.0 1.0 7.3 2.5 1.0 gamma interferon induced monokine (MIG) D49921 F i n 20 52 69 31 40 6.6 0.3 1.0 3.8 0.0 0.8 glial cell line-derived neurotrophic factor M l 3926 F2a 20 47 55 42 31 5.4 0.0 1.6 3.2 0.4 2.7 granulocyte colony- stimulating factor (G-CSF) M62301 F2b 20 101 91 23 20 1.6 10.2 3.4 0.6 0.6 2.3 growth/ diffferentiation factor 1 (GDF-1) 185 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium LPS Gene/Protein Name umber A+B mean SD mean SD A B C A B C X77113 F2c 20 86 86 44 13 0.0 8.6 4.3 1.5 2.4 2.7 growth/ diffferentiation factor 2 (GDF-2) L07264 F2d 20 245 218 167 58 15.8 0.0 21.0 8.8 11.0 5.3 heparin-binding EGF- l ike growth factor X72307 F2e 20 498 119 140 239 31.6 23.2 20.0 20.8 0.2 0.0 hepatocyte growth factor ; hepapoitein L38847 F 2 f 20 420 127 137 237 25.6 23.7 13.8 20.6 0.0 0.0 hepatoma transmembrane kinase ligand X69618 F2g 20 202 83 166 64 13.8 5.6 11.0 10.9 9.3 4.7 inhibin alpha subunit X69619 F2h 240 186 129 228 241 1.3 0.2 0.8 2.1 0.4 0.4 inhibin beta A subunit (TGF beta family) X81584 F 2 i 20 78 70 102 22 6.9 0.0 4.9 6.3 4.1 5.0 insulin-like growth factor binding protein -6 X81579 F2j 20 49 52 24 21 5.2 0.0 2.2 1.6 2.0 0.0 insulin-like growth factor binding protein-1 X81581 F2k 20 56 51 57 27 4.9 0.0 3.6 3.9 3.4 1.3 insulin-like growth factor binding protein-3 X81582 F21 396 232 60 240 49 0.5 0.5 0.8 0.5 0.6 0.7 insulin-like growth factor binding protein-4 X81583 F2m 188 116 66 179 52 1.0 0.4 0.5 1.0 1.2 0.7 insulin-like growth factor binding protein-5 M14951 F2n 20 36 37 73 3 3.7 0.0 1.8 3.7 3.5 3.8 insulin-like growth factor-2 (somatomedin A ) X04480 F3a 572 411 115 671 317 0.9 0.6 0.7 0.8 0.9 1.8 insulin-like growth factor-IA Z22703 F3b 20 75 66 52 32 6.3 0.0 5.0 2.1 1.3 4.4 keratinocyte growth factor FGF-7 M30642 F3c 20 179 159 241 86 11.9 0.0 15.1 7.7 12.2 16.3 K-fibroblast growth factor X06381 F3d 20 1512 549 1394 681 44.0 90.7 92.2 82.7 31.1 95.3 leukemia inhibitory factor (LIF) X12531 F3e 489 10124 574 9147 2228 21.8 19.4 20.9 17.6 14.8 23.7 macrophage inflamatory protein (MIP) M35590 F 3 f 188 8963 345 8865 2432 47.9 49.4 45.7 44.2 36.0 61.3 macrophage inflamatory protein 1 beta (Act 2) X53798 F3g 20 697 610 802 1076 47.8 0.0 56.8 19.1 0.0 101.2 macrophage inflamatory protein 2 alpha U60530 F3h 193 306 88 339 84 1.6 1.1 2.0 1.3 1.9 2.1 M a d related protein 2 ( M A D R 2 ) U44725 F 3 i 20 72 13 54 10 3.9 2.9 4.1 3.0 3.1 2.2 mast cell factor X83106 F3j 20 228 19 180 34 12.5 10.7 11.0 10.8 8.9 7.4 mothers against DPP protein M l 1434 F3k 20 95 46 91 16 6.9 2.3 5.1 5.5 4.3 3.9 nerve growth factor alpha (alpha-NGF) KOI 759 F31 660 630 138 450 159 0.9 0.8 1.2 0.9 0.5 0.7 nerve growth factor beta (beta-NGF) M l 4220 F3m 5403 4463 937 4696 159 1.0 0.7 0.8 0.9 0.8 0.9 neuroleukin D31942 F3n 480 335 78 429 64 0.8 0.5 0.8 0.8 0.8 1.0 oncostatin M U22516 F4a 20 53 46 23 14 3.9 0.0 4.0 1.6 1.5 0.4 placental ribonuclease inhibitor; angiogenin M29464 F4b 20 72 74 41 27 7.4 0.0 3.4 3.6 1.0 1.6 platelet- derived growth factor (A chain) U32330 F4c 20 120 30 67 39 5.4 4.9 7.8 1.6 3.0 5.4 prepro-endothelin-3 XI4432 F4d 20 516 382 386 145 33.2 4.1 40.2 26.2 20.1 11.7 thrombomodulin L34169 F4e 393 707 612 197 171 2.7 0.0 2.7 0.7 0.8 0.0 thrombopoietin M13177 F4f 2305 3559 514 3323 421 1.5 1.4 1.8 1.5 1.2 1.6 transforming growth factor beta 186 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium LPS Gene/Protein Name Number A+B mean S D mean SD A B c A B C X57413 F4g 20 348 301 420 364 26.5 0.0 25.7 31.5 0.0 31.6 transforming growth factor beta 2 M16819 F4h 20 145 35 116 43 9.2 5.8 6.8 6.1 3.6 7.8 tumor necrosis factor beta (TNF-beta) L33406 F4i 20 80 60 27 9 6.6 0.7 4.8 1.0 1.9 1.1 uromodulin M95200 F4j 20 153 83 134 85 7.2 3.8 12.1 2.6 6.5 11.1 vascular endothelial growth factor ( V E G F ) M15131 F4k 20 823 300 1491 962 38.3 27.8 57.4 19.0 103.5 101.1 interleukin 1 beta M37897 F41 170 323 35 279 65 1.7 2.1 1.9 2.0 1.7 1.2 interleukin 10 U03421 F4m 513 395 172 361 90 1.1 0.5 0.7 0.9 0.6 0.6 interleukin 11; adipogenesis inhibitory factor M86671 F4n 20 167 73 100 26 8.0 5.0 12.2 3.6 6.1 5.4 interleukin 12 (p40) beta chain U14332 F5a 20 180 36 261 154 7.8 11.1 8.2 7.0 21.7 10.6 interleukin 15 M25892 F5b 20 64 50 41 39 0.5 3.7 5.4 2.3 3.9 0.0 interleukin 4 X51975 F5c 472 414 302 425 99 1.4 0.2 1.0 1.1 0.8 0.7 interleukin 6 (B cell differentiation factor) X07962 F5d 20 268 47 114 45 11.2 13.1 15.9 3.2 7.2 6.8 interleukin 7 M76601 F5e 20 242 6 160 18 12.4 11.8 12.2 7.6 7.4 9.1 alpha cardiac myosin heavy chain X63615 F5f 20 197 180 217 18 17.6 0.0 11.9 11.7 9.9 11.1 C a m K II; calmodulin-dependent protein kinase U37720 F5g 20 199 86 151 44 8.3 14.9 6.8 5.5 9.9 7.3 C D C 4 2 GTP-binding protein; G 2 5 K M13806 F5h 20 143 65 94 32 10.9 4.8 5.9 6.4 3.2 4.6 cytoskeletal epidermal keratin (14 human) M11686 F5 i 20 73 65 27 29 6.3 0.0 4.7 1.2 0.0 2.9 cytoskeletal epidermal keratin (18 human) M28698 F5j 20 86 57 45 16 7.6 2.2 3.2 3.0 1.4 2.5 cytoskeletal epidermal keratin (19 human) M10937 F5k 20 93 17 54 37 5.5 3.8 4.8 0.8 4.5 2.9 epidermal keratin (1 human) M19436 F51 20 129 103 27 28 12.1 1.9 5.5 0.2 2.9 0.9 fetal myosin alkali light chain D29951 F5m 20 150 53 98 5 10.1 4.8 7.7 4.7 5.2 4.9 kinesin family protein K I F 1 A X61435 F5n 138 267 56 142 75 2.1 1.5 2.2 0.7 0.7 1.7 kinesin heavy chain D26077 F6a 163 369 22 430 95 2.4 2.2 2.2 2.6 3.2 2.1 kinesin like protein K I F 3B U04443 F6b 800 613 212 748 73 0.7 0.6 1.1 1.0 0.9 0.9 non-muscle myosin light chain 3 Y14019 F6c 20 246 215 203 79 9.6 3.2 24.2 9.5 14.4 6.5 Rab-3b ras-related protein X51438 F6d 2702 3224 1014 2252 667 1.1 0.9 1.6 0.8 0.6 1.1 vimentin U49739 F6e 20 270 254 281 50 15.2 0.0 25.3 11.2 15.7 15.3 unconventional myosin V I J04946 F6f 20 147 137 144 31 8.6 0.0 13.5 9.0 6.1 6.5 angiotensin-converting enzyme ( A C E ) M14222 F6g 980 1248 132 1166 170 1.1 1.4 1.3 1.0 1.2 1.3 cathepsin B X53337 F6h 1429 1953 412 1729 562 1.5 1.0 1.6 1.2 0.8 1.6 cathepsin D U06119 F6i 20 195 71 197 44 13.1 6.0 10.2 9.0 8.3 12.4 cathepsin H X06086 F6j 659 997 308 808 251 1.5 1.1 2.0 1.2 0.9 1.6 cathepsin L 187 Ratio Relative to Unstimulated Cells Accession Code Unstim. S. Typhimurium L P S S. Typhimurium L P S Gene/Protein Name Number A + B mean SD mean SD A B C A B C M84324 F6k 20 161 125 72 37 15.1 3.2 5.9 4.5 1.5 4.8 collagenase type IV X12822 F61 20 106 107 8 13 10.7 0.0 5.2 1.2 0.0 0.0 cytotoxic cell protease 2 (BIO) M12302 F6m 20 131 151 83 66 15.1 0.6 4.0 3.1 1.5 7.8 cytotoxic T lymphocyte-specific serine protease X72795 F6n 20 182 73 127 53 12.9 5.7 8.8 5.5 4.2 9.3 gelatinase B L28095 F7a 20 1219 447 860 264 86.1 53.4 43.3 28.4 54.1 46.5 interleukin-converting enzyme (ICE) M55617 F7b 20 158 44 100 67 9.8 8.5 5.5 8.4 5.1 1.6 mast cell protease ( M M C P ) - 4 X83536 F7c 20 265 117 120 120 14.6 18.4 6.9 4.3 1.1 12.7 membrane-type matrix matalloproteinase X70296 F7d 20 195 51 99 38 12.4 7.4 9.5 7.1 4.2 3.6 protease nexin 1 (PN-1) J03520 F7e 20 175 60 59 38 11.4 9.3 5.5 3.1 1.0 4.8 tissue plasminogen activator X02389 F 7 f 194 192 135 89 30 0.5 1.8 0.7 0.5 0.3 0.6 urokinase type plasminogen activator M75716 F7g 20 142 96 23 13 9.4 10.4 1.6 1.8 0.5 1.1 alpha-1 protease inhibitor 2 M33960 F7h 20 237 105 130 20 17.8 10.2 7.6 6.3 5.7 7.6 plasminogen activator inhibitor XI6490 F7i 20 183 125 128 69 16.3 6.6 4.6 4.2 10.4 4.7 plasminogen activator inhibitor-2 M64086 F7j 20 114 76 27 46 9.6 2.0 5.6 4.0 0.0 0.0 serine protease inhibitor 2 (spi-2) X69832 F7k 20 126 176 16 27 16.4 0.3 2.3 2.4 0.0 0.1 serine protease inhibitor 2.4 J05609 F71 20 123 137 38 44 13.6 0.0 4.9 4.3 0.0 1.4 serine protease inhibitor homolog J6 X62622 F7m 20 155 158 47 28 16.7 1.9 4.7 1.6 1.6 4.0 TIMP-2 tissue inhibitor of metalloproteinases-2 LI9622 F7n 197 193 60 160 68 1.3 0.7 1.0 0.5 0.7 1.2 TIMP-3 tissue inhibitor of metalloproteinases-3 X51703 G05 15698 14718 3098 15970 3027 1.2 0.8 0.9 1.0 0.8 1.2 ubiquitin D78647 G06 2156 1462 493 1855 262 0.4 0.9 0.7 0.8 1.0 0.8 phospholipase A2 J00423 G07 624 299 100 530 216 0.3 0.6 0.5 0.6 1.2 0.7 hypoxantine-guanine phosphoribosyltransferase M32599 G12 5102 5264 867 5162 956 0.9 1.2 1.0 0.9 1.2 0.9 glyceraldehyde-3-phosphate dehydrogenase L00923 G13 536 308 125 240 148 0.4 0.8 0.5 0.4 0.7 0.2 myosin I M l 0624 G14 699 1850 650 1487 314 1.7 2.7 3.5 1.7 2.6 2.1 murine ornithine decarboxylase X03672 G19 9782 12580 1378 11874 714 1.2 1.2 1.4 1.2 1.2 1.3 beta-actin U45977 G20 1446 1317 60 1133 62 0.9 0.9 1.0 0.8 0.8 0.7 Ca2+ binding protein, Cab45 L31609 G21 12582 11272 572 11377 532 0.9 0.9 0.9 0.9 0.9 0.9 ribosomal protein S29 188 189 Appendix A.2 Hybridization intensities in IFN-y-primed RAW 264.7 cells infected with S. Typhimurium. R A W 264.7 cells were primed with IFN-y for 24 h and then left uninfected (Uninfect.; n=2), or infected with S. Typhimurium (n=2), The hybridization intensity in infected cells for each experiment is listed as well as the ratio relative to the mean hybridization signal in uninfected cells. A and B refer to independent experiments. Code refers to the position of c D N A spots on the array. Hybridization Intensity Ratio Accession Code Uninfect. Infected +/- bacteria Number A+B A B A B Protein/Gene Name M88127 A l a 216 666 965 3.1 4.5 A P C (adenomatous polyposis coli protein) U31625 A l b 209 564 581 2.7 2.8 BRCA1; breast/ovarian cancer susceptibility locus U65594 A l e 327 766 586 2.3 1.8 BRCA2; breast cancer susceptibility locus 2 X85788 A i d 135 361 166 2.7 1.2 DCC; netrin receptor; Ig gene superfamily U51196 A l e 110 541 310 4.9 2.8 EB1 APC-binding protein X60671 A l f 278 608 336 2.2 1.2 ezrin; villin 2; NF-2 (merlin) related U58992 A l g 129 531 73 4.1 0.6 Madrl ; mSmadl; (bsp-1) X58876 A l h 180 500 343 2.8 1.9 Mdm2; p53-regulating protein L27105 A l i 88 717 178 8.1 2.0 NF2; merlin (moesin-ezrin-radixin-like protein); U27177 A l j 137 778 286 5.7 2.1 pi07; RBL1; retinoblastoma gene product-related U36799 A l k 246 562 638 2.3 2.6 pl30; retinoblastoma gene product-related protein KOI 700 A l l 1719 1242 2810 0.7 1.6 p53; tumor suppressor; DNA-binding protein M26391 A i m 267 383 505 1.4 1.9 Rb; ppl05; retinoblastoma susceptibility-assoc. U52945 A l n 262 296 325 1.1 1.2 TSG101 tumor susceptibility protein U54705 A2a 191 581 342 3.0 1.8 tumor suppressor maspin U12570 A2b 129 319 238 2.5 1.8 V H L ; Von Hippel-Lindau tumor suppresso M55512 A2c 196 391 62 2.0 0.3 WT1; Wilms tumor protein; tumor suppressor D14340 A2d 100 138 20 1.4 0.2 ZO-1; tight junction protein X82327 A2e 20 222 20 11,1 1.0 A-myb proto-oncogene; myb-related protein A X70472 A2f 860 432 273 0.5 0.3 B-myb proto-oncogene; myb-related protein B X51983 A2g 420 353 209 0.8 0.5 c-ErbA oncogene; thyroid hormone receptor. V00727 . A2h 178 378 57 2.1 0.3 c-Fos proto-oncogene; transcription factor AP-1 J04115 A2i 457 916 483 2.0 1.1 c-Jun proto-oncogene; transcription factor AP-1 X83974 A2j 1943 1125 2285 0.6 1.2 R N A polymerase I termination factor TTF-1 M l 6449 A2k 135 286 193 2.1 1.4 c-myb proto-oncogene protein X01023 A21 405 344 583 0.8 1.4 c-myc proto-oncogene protein XI5842 A2m 84 288 121 3.4 1.4 c-rel proto-oncogene X76654 A2n 256 226 106 0.9 0.4 Ear-2; v-erbA related proto-oncogene X87257 A3a 302 624 242 2.1 0.8 Elk-1 ets-related proto-oncogene X59421 A3b 386 476 125 1.2 0.3 Fli-1 ets-related proto-oncogene X14897 A3c 263 623 20 2.4 0.1 Fos-B; c-fos-related protein fos B X83971 A3d 561 558 364 1.0 0.6 Fra-2 (fos-related antigen 2) S65038 A3e 163 365 55 2.2 0.3 Gl i oncogene; zinc finger transcription factor J03236 A3f 273 1324 785 4.8 2.9 Jun-B; c-jun-related transcription factor J05205 A3g 621 1626 1098 2.6 1.8 jun-D; c-jun-related transcription factor X13945 A3h 139 400 13 2.9 0.1 L-myc proto-oncogene protein Z32815 A3i 672 715 461 1.1 0.7 Net; ets related transcription factor X03919 A3j 1923 1254 1392 0.7 0.7 N-myc proto-oncogene protein M13071 A3k 352 596 277 1.7 0.8 A-Raf proto-oncogene M64429 A31 105 304 20 2.9 0.2 B-Raf proto-oncogene D13759 A3m 394 508 181 1.3 0.5 Cot proto-oncogene Hybridization Intensity Ratio 190 Accession Code Uninfect. Infected +/- bacteria Number A+B A B A B Protein/Gene Name U51866 A3n 131 229 80 1.7 0.6 casein kinase II (alpha subunit) M13945 A4a 1276 1814 1795 1.4 1.4 Pim-1 proto-oncogene X68932 A4b 2885 2938 2728 1.0 0.9 c-Fms proto-oncogene; M-CSF-1 receptor Y00864 A4c 779 1574 34 2.0 0.0 c-Kit proto-oncogene; mast cell growth factor Y00671 A4d 103 241 20 2.3 0.2 Met proto-oncogene M84607 A4e 121 173 20 1.4 0.2 platelet-derived growth factor alpha-receptor X67812 A4f 131 192 38 1.5 0.3 Ret proto-oncogene U14173 A4g 1096 649 '537 0.6 0.5 Ski proto-oncogene U18342 A4h 123 162 20 1.3 0.2 Sky proto-oncogene (Tyro3; Rse; Dtk) S67051 A4i 738 270 20 0.4 0.0 Tie-2 proto-oncogene L07297 A4j 1493 1098 1235 0.7 0.8 vascular endothelial growth factor receptor 1 L10656 A4k 273 440 20 1.6 0.1 c-Abl proto-oncogene X12616 A41 562 319 71 0.6 0.1 c-Fes proto-oncogene X52191 A4m 36 199 20 5.6 0.6 c-Fgr proto-oncogene M17031 A4n 40 463 165 11.5 4.1 c-Src proto-oncogene M12056 A5a 238 805 134 3.4 0.6 lymphocyte-specific tyrosine-protein kinase L C K X57111 A5b 294 331 91 1.1 0.3 c-Cbl proto-oncogene (adaptor protein) Z50013 A5c 199 376 93 1.9 0.5 H-ras proto-oncogene; transforming G-protein U28495 A5d 290 444 147 1.5 0.5 Lfc proto-oncogene X13664 A5e 855 855 796 1.0 0.9 N-ras proto-oncogene; transforming G-protein U15784 A5f 320 143 109 0.4 0.3 She transforming adaptor protein X05010 A5g 145 103 165 0.7 1.1 CSF-1; M-CSF; colony stimulating factor-1 M80456 A5h 138 244 20 1.8 0.1 Int-3 proto-oncogene; NOTCH4 Z46845 A5i 120 205 20 1.7 0.2 preproglucagon D17584 A5j 197 74 20 0.4 o.i beta-protachykinin a Z22649 A5k 162 77 20 0.5 0.1 c-Mpl; thrombopoietin receptor X67735 A51 88 253 20 2.9 0.2 Mas proto-oncogene (G-protein coupled receptor) X81580 A5m 46 74 20 1.6 0.4 IGFBP-2; insulin-like binding protein 2 U05245 A5n 51 318 20 6.2 0.4 Tiam-1 invasion inducing protein Z26580 A6a 263 556 20 2.1 0.1 cyclin A (G2/M-specific) X84311 A6b 315 556 20 1.8 0.1 cyclin A l (G2/M-specific) X64713 A6c 819 353 20 0.4 0.0 cyclin BI (G2/M-specific) X66032 A6d 345 268 20 0.8 0.1 cyclin B2 (G2/M-specific) U62638 A6e 158 121 20 0.8 0.1 cyclin C (Gl-specific) S78355 A6f 1572 652 620 0.4 0.4 cyclin D l (Gl/S-specific) M83749 A6g 490 510 88 1.0 0.2 cyclin D2 (Gl/S-specific) U43844 A6h 303 484 91 1.6 0.3 cyclin D3 (Gl/S-specific) X75888 A6i 682 265 20 0.4 0.0 cyclin E (Gl/S-specific) Z47766 A6j 993 233 233 0.2 0.2 cyclin F (S/G2/M-specific) Z37110 A6k 380 189 20 0.5 0.1 cyclin G (G2/M-specific) U95826 A61 131 116 20 0.9 0.2 cyclin G2 (G2/M-specific) L01640 A6m 466 372 205 0.8 0.4 Cdk4; cyclin-dependent kinase 4 D29678 A6n 168 203 20 1.2 0.1 Cdk5; cyclin-dependent kinase 5 U11822 A7a 199 480 50 2.4 0.2 Cdk7; M015; cyclin-dependent kinase 7 M58633 A7b 281 257 20 0.9 0.1 p58/GTA; galactosyltransferase-associated kinase U19596 A7c 1255 956 533 0.8 0.4 pl8ink4; cdk4 and cdk6 inhibitor U19597 A7d 267 20 20 0.1 0.1 pl9ink4; cdk4 and cdk6 inhibitor U09507 A7e 236 779 288 3.3 1.2 p21/CiplAVafl; cdk-inhibitor protein 1 U10440 A7f 126 290 20 2.3 0.2 p27kipl; G l cyclin-Cdk protein kinase inhibitor Hybridization Intensity Ratio 191 Accession Code Uninfect. Infected +/- bacteria Number A+B A B A B Protein/Gene Name U20553 A7g 59 20 20 0.3 0.3 D30743 A7h 161 160 20 1.0 0.1 X59868 A7i 110 62 20 0.6 0.2 U27323 A7j 186 20 20 0.1 0.1 S93521 A7k 40 82 20 2.1 0.5 U43525 A71 315 136 93 0.4 0.3 X56135 A7m 2610 2121 2229 0.8 0.9 D78382 A7n 332 95 88 0.3 0.3 U03560 B l a 152 573 42 3.8 0.3 X53584 B i b 440 681 440 1.5 1.0 M36829 B l c 3753 4373 3921 1.2 1.0 M36830 B i d 714 657 617 0.9 0.9 L16953 B l e 132 180 20 1.4 0.2 D49482 B l f 20 95 20 4.8 1.0 M14757 B i g 100 20 20 0.2 0.2 S50213 B l h 258 20 13 0.1 0.1 U58987 B l i 297 424 121 1.4 0.4 X78445 B l j 479 579 472 1.2 1.0 J05186 B l k 633 653 744 1.0 1.2 U41751 B l l 512 461 314 0.9 0.6 D78645 B l m 898 858 1238 1.0 1.4 U40930 B i n 149 725 939 4.9 6.3 M l 0021 B2a 134 478 20 3.6 0.2 U34920 B2b 149 282 69 1.9 0.5 U20372 B2c 222 20 20 0.1 0.1 U34259 B2d 429 183 479 0.4 1.1 M23384 B2e 308 344 667 1.1 2.2 L36179 B2f 20 20 20 1.0 1.0 L25606 B2g 149 20 55 0.1 0.4 D31788 B2h 1598 857 1581 0.5 1.0 U29678 B2i 978 1542 1432 1.6 1.5 L03529 B2j 5526 10623 10838 1.9 2.0 L25890 B2k 804 1088 1463 1.4 1.8 M68513 B21 125 79 20 0.6 0.2 U43205 B2m, 41 121 131 3.0 3.2 Z49086 B2n 20 20 20 1.0 1.0 Z49085 B3a 112 " 688 65 6.1 0.6 S69336 B3b 399 593 543 1.5 1.4 M83336 B3c 88 246 20 2.8 0.2 D87747 B3d 343 708 347 '2.1 1.0 M60778 B3e 786 1098 906 1.4 1.2 D13458 B3f 150 22 20 0.1 0.1 X80764 B3g 49 20 20 0.4 0.4 X57349 B3h 54 20 20 0.4 0.4 X62700 B3i 347 3.83' 567 1.1 1.6 X70842 B3j 242 688 529 2.8 2.2 S56660 B3k 137 183 340 1.3 2.5 S76657 B31 158 104 212 0.7 1.3 U36277 B3m 413 922 1203 2.2 2.9 p57kip2; cdk-inhibitor kip2 Weel/p87; cdc2 tyrosine 154dnase Cdc25 phosphatase Cdc25a; cdc25Ml ;MPI l Cdc25b; cdc25M2; MPI2 myeloblastin; serine protease prothymosin alpha Tob antiproliferative factor HSP27; heat shock 27-kDa protein 1 HSP60 (heat shock 60-kDa protein 1); chaperonin HSP84 (heat shock 84-kDa protein) HSP86; heat shock 86-kDa protein MTJ1; DnaJ-like heat-shock protein Osp94 osmotic stress protein; hsp70-related MDR1; P-glycoprotein; multidrug resistance HMGl-related-VDJ recombination binding protein MmMrel l a putative endo/exonuclease C3H cytochrome P450; Cyp lb l ERp72 endoplasmic reticulum stress protein etoposide induced p53 responsive (EI24) mRNA glucose regulated protein, 78 kDa; Grp78 oxidative stress-induced protein mRNA P-l-450; dioxin-inducible cytochrome P450 ATP-binding casette 8; ABC8 CCHB3; calcium channel (voltage-gated) Golgi 4-transmembrane spanning transporter Glucose transporter-1, erythrocyte; Glutl voltage-gated sodium channel B7-2; T lymphocyte activation antigen CD86 BST-1; lymphocyte differentiation antigen CD38 C-C CKR-1 ; CCR-1; MIP-lalpha-R; RANTES-R Cf2r; coagulation factor II (thrombin) receptor Eph3 (Nuk) tyrosine-protein kinase receptor Etkl (Mek4; HEK) tyrosine kinase receptor Frizzled-3; Drosophila tissue polarity gene Hek2 murine homolog; Mdk5 Htk; Mdk2 mouse developmental kinase IFNgR2; interferon-gamma receptor beta chain interleukin-6 receptor beta chain LCR-1; CXCR-4; C X C chemokine receptor 4 LFAl-alpha; integrin alpha L prostaglandin E2 receptor EP4 subtype Tie-1 tyrosine-protein kinase receptor transferrin receptor protein (p90, CD71) u P A R l ; C D 8 7 VEGFR2; KDR/f lk l retinoic acid receptor beta-2 (beta2-RAR) CRE-BP1; cAMP response binding protein 1 I-kB (I-kappa B) alpha chain Hybridization Intensity Ratio 192 Accession Code Uninfect. Infected +/- bacteria Number A+B A B A B Protein/Gene Name U19799 B3n 1622 2914 3396 1.8 2.1 I-kB (I-kappa B) beta M61909 B4a 659 1318 933 2.0 1.4 NF-kB p65; NF-kappa-B p65 subunit U33626 B4b 308 659 233 2.1 0.8 Pml; leukemia-associated P M L gene X66224 B4c 278 283 131 1.0 0.5 RXR-beta cis-11-retinoic acid receptor U06924 B4d 1043 609 843 0.6 0.8 Statl U06922 B4e 293 341 267 1.2 0.9 Stat3; acute phase response factor (APRF) Z48538 B4f 96 367 369 3.8 3.8 Stat5a; mammary gland factor L47650 B4g 1366 873 1009 0.6 0.7 Stat6; IL-4 Stat; STA6 U51907 B4h 169 158 20 0.9 0.1 T A N K ; I-TRAF; NF-kB activator L21027 B4i 224 206 20 0.9 0.1 transcription factor A10 DO1034 B4j 304 324 398 1.1 1.3 transcription factor TF IID M57422 B4k 1262 3833 3564 3.0 2.8 tristetraprolin U48853 B41 543 183 325 0.3 0.6 Cas; Crk-associated substrate; F A K substrate S72408 B4m 598 191 84 0.3 0.1 Crk adaptor protein U05247 B4n 148 348 167 2.4 1.1 Csk; c-Src-kinase and negative regulator U70324 B5a 251 456 395 1.8 1.6 Fyn proto-oncogene; Src family member Y00487 B5b 1175 1485 1696 1.3 1.4 Hck tyrosine-protein kinase U29056 B5c 259 214 290 0.8 1.1 SLAP; src-like adapter protein U25685 B5d 290 335 674 1.2 2.3 Syk tyrosine-protein kinase D84372 B5e 414 62 538 0.1 1.3 Syp; SH-PTP2 X58995 B5f 52 20 212 0.4 4.1 CamK IV; calmodulin-dependent protein kinase M20473 B5g 60 20 53 0.3 0.9 cAMP-dependent protein kinase M61177 B5h 374 56 306 0.2 0.8 extracellular signal-regulated kinase 1 (ERK1); U28423 B5i 915 693 818 0.8 0.9 inhibitor of the RNA-activated protein kinase L33768 B5j 262 89 95 0.3 0.4 Jak3 tyrosine-protein kinase; Janus kinase 3 L35236 B5k 24 109 28 4.5 1.1 Jnk stress-activated protein kinase (SAPK) U15159 B51 255 368 325 1.4 1.3 L I M K ; L I M serine/threonine kinase U10871 B5m 353 201 68 0.6 0.2 M A P K ; M A P kinase; p38 X76850 B5n 352 418 466 1.2 1.3 M A P K A P K - 2 ; M A P K A P kinase 2 L02526 B6a 647 527 454 0.8 0.7 M A P K K 1 ; M A P kinase kinase 3; MEK1 U43187 B6b 289 294 146 1.0 0.5 M A P K K 3 ; M A P kinase kinase 3; M K K 3 , MEK3 U18310 B6c 362 36 441 0.1 1.2 M A P K K 4 ; M A P kinase kinase 4; JNKK1; SEK1; X97052 B6d 150 110 205 0.7 1.4 M A P K K 6 ; M A P kinase kinase 6; M K K 6 M25811 B6e 69 94 246 1.4 3.6 PKC-alpha; protein kinase C alpha type X53532 B6f 33 97 20 2.9 0.6 PKC-beta; protein kinase C beta-II type M69042 B6g 461 532 478 1.2 1.0 PKC-delta; protein kinase C delta type D l 1091 B6h 1292 2330 1339 1.8 1.0 PKC-theta; protein kinase C theta type M28489 B6i 210 109 20 0.5 0.1 Rsk; ribosomal protein S6 kinase U03279 B6j 70 60 20 0.9 0.3 PI3-Kpl lO M60651 B6k 88 103 20 1.2 0.2 PI3-K p85 U43144 B61 100 34 16 0.3 0.2 PLC beta; phospholipase C beta 3 X95346 B6m 24 20 20 0.8 0.8 PLC gamma; phospholipase C gamma M63660 B6n 21 115 20 5.4 0.9 G-alpha-13 guanine nucleotide regulatory protein U10551 B7a 216 177 337 0.8 1.6 Gem; induced, immediate early protein X95403 B7b 771 265 928 0.3 1.2 Rab-2 ras-related protein X57277 B7c 549 294 585 0.5 1.1 Racl murine homolog M21019 B7d 203 248 459 1.2 2.3 R-ras protein U34960 B7e 288 209 480 0.7 1.7 transducin beta-2 subunit X64361 B7f 811 373 772 0.5 1.0 Vav; GDP-GTP exchange factor; proto-oncogene Hybridization Intensity Ratio 193 Accession Code Uninfect. Infected +/- bacteria Number A+B A B A B Protein/Gene Name U57311 B7g 2591 1323 2039 0.5 0.8 14-3-3 protein eta U03184 B7h 416 20 73 0.0 0.2 cortactin; protein tyrosine kinase substrate U24160 B7i 263 20 67 0.1 0.3 Dvl2; dishevelled-2 tissue polarity protein U20238 B7j 160 20 28 0.1 0.2 GapIII; GTPase-activating protein M21065 B7k 1178 801 909 0.7 0.8 IRF1; interferon regulatory factor 1 L09562 B71 191 20 20 0.1 0.1 PTPRG; protein-tyrosine phosphatase gamma U92456 B7m 196 20 251 0.1 1.3 WBP6; pSK-SRPKl X99063 B7n 1001 1036 1603 1.0 1.6 Zyxin; L I M domain protein U59463 C l a 148 367 31 2.5 0.2 caspase-11; ICH-3 cysteine protease D28492 C l b 144 250 76 1.7 0.5 Caspase-3; Nedd2 cysteine protease U67321 C l c 242 135 200 0.6 0.8 caspase-7; Lice2; ICE-LAP3 cysteine protease L37296 C l d 288 32 310 0.1 1.1 Bad; heterodimeric partner for B c l - X L and Bcl-2 U17162 C l e 1210 623 781 0.5 0.6 BAG-1 ; bcl-2 binding protein Y13231 C l f 2383 1406 2378 0.6 1.0 Bak apoptosis regulator; Bcl-2 family member L22472 c i g 1399 998 1750 0.7 1.3 Bax; Bcl-2 heterodimerization partner M16506 C l h 265 112 91 0.4 0.3 Bcl-2; B cell lymphoma protein 2 U59746 C l i 66 20 28 0.3 0.4 Bcl-W apoptosis regulator; Bcl-2 family member L35049 c i j 410 292 812 0.7 2.0 Bcl-xL apoptosis regulator (bcl-x long) U75506 C l k 161 20 137 0.1 0.8 BID; apoptotic death agonist U13705 C l l 56 17 24 0.3 0.4 glutathione peroxidase (plasma protein) X76341 C l m 739 162 467 0.2 0.6 glutathione reductase J03958 C l n 61 20 315 0.3 5.1 glutathione S-transferase A J03752 C2a 166 890 119 5.4 0.7 glutathione S-transferase (microsomal) J04696 C2b 153 887 62 5.8 0.4 glutathione S-transferase Mu 1 X98055 C2c 91 440 20 4.8 0.2 gluthathione S-transferase (thetatypel) D30687 C2d 148 463 91 3.1 0.6 GST Pi 1; glutathione S-transferase Pi 1 U19463 C2e 163 20 20 0.1 0.1 A20 zinc finger protein; apoptosis inhibitor U05671 C2f 185 20 20 0.1 0.1 adenosine A I M receptor U05672 C2g 158 69 20 0.4 0.1 adenosine A2M2 receptor L20331 C2h 36 98 20 2.8 0.6 adenosine A3 receptor U49112 C2i 233 20 76 0.1 0.3 ALG-2 ; calcium binding protein M30903 C2j 253 65 277 0.3 1.1 Blk; B lymphocyte kinase; Src family member M94335 C2k 1944 820 1510 0.4 0.8 c-Akt proto-oncogene; Rac-alpha; protein kinase B L24495 C21 354 189 402 0.5 1.1 CD27; lymphocyte-specific NGF receptor family U25416 C2m 98 36 201 0.4 2.1 CD 30L receptor; lymphocyte activation antigen X65453 C2n 69 89 20 1.3 0.3 CD40L; CD40 ligand X67083 C3a 245 1221 183 5.0 0.7 Chop 10; murine homolog of Gaddl53 L08235 C3b 200 628 86 3.1 0.4 clusterin; complement lysis inhibitor U21050 C3c 330 434 38 1.3 0.1 CRAF1; TNF/CD40 receptor-associated factor U83628 C3d 441 1003 1115 2.3 2.5 DAD-1; defender against cell death 1 U39643 C3e 47 41 128 0.9 2.7 FAF1; Fas-associated protein factor M83649 C3f 50 20 20 0.4 0.4 Fas 1 receptor; Fas antigen (Apo-1 antigen) U06948 C3g 20 60 20 3.0 1.0 Fasl; Fas antigen ligand U97076 C3h 250 265 423 1.1 1.7 FLIP-L; FLICE-like inhibitory protein U04807 C3i 189 154 218 0.8 1.2 fms-related tyrosine kinase 3 Flt3/Flk2 ligand L28177 C3j 39 200 106 5.1 2.7 gadd45; growth arrest/DNA-damage inducible U04710 C3k 166 59 216 0.4 1.3 insulin-like growth factor receptor II (IGFRII) U00182 C31 183 265 308 1.5 1.7 insulin-like growth factor I receptor alpha subunit M87039 C3m 733 1658 1752 2.3 2.4 nitric oxide synthase, inducible (iNOS) Hybridization Intensity Ratio 194 Accession Code Uninfect Infected +/- bacteria Number A+B A B A B Protein/Gene Name M20658 C3n 474 294 440 0.6 0.9 interleukin-1 receptor D17571 C4a 392 1208 725 3.1 1.8 NADPH-cytochrome P450 reductase D83698 C4b 341 1025 280 3.0 0.8 neuronal death protein X68193 C4c 1736 1576 1918 0.9 1.1 Nm23-M2; nucleoside diphosphate kinase B J04113 C4d 515 265 476 0.5 0.9 Nur77 early response protein U05341 C4e 330 192 554 0.6 1.7 p55cdc; cell division control protein 20 X67914 C4f 657 700 1420 1.1 2.2 PD-1 possible cell death inducer D83966 C4g 156 62 407 0.4 2.6 protein tyrosine phosphatase U57324 C4h 297 151 499 0.5 1.7 PS-2; homolog of the Alzheimer's disease gene Z27088 C4i 174 60 129 0.3 0.7 ..relaxin U25995 C4j 271 141 218 0.5 0.8 RIP cell death protein; Fas/APO-1 (CD95) U16805 C4k 94 183 20 2.0 0.2 Sik; Src-related intestinal kinase U25844 C41 595 205 467 0.3 0.8 SPB; serpin; serine proteinase inhibitor U43900 C4m 141 20 .152 0.1 1.1 S T A M ; signal transducing adaptor molecule Z12604 C4n 87 109 191 1.3 2.2 stromelysin-3; matrix metalloproteinase-11 U44088 C5a 970 2649 2172 2.7 2.2 TDAG51; couples TCR signaling to Fas X57796 C5b 654 1215 884 1.9 1.4 TNF 55; tumor necrosis factor 1 (55 kDa) U37522 C5c 411 443 363 1.1 0.9 TRAIL; TNF-related apoptosis inducing ligand M59378 C5d 777 1738 2936 2.2 3.8 tumor necrosis factor receptor 1 (TNFR-1) X72711 C5e 271 195 531 0.7 2.0 activator -1 140-kDa subunit; replication factor U12273 C5f 145 20 161 0.1 1.1 A P endonuclease (Apex) U43678 C5g 100 144 356 1.4 3.6 Atm; ataxia telangiectasia murine homolog M38700 C5h 477 183 678 0.4 1.4 ATP-dependent D N A helicase II70 kDa subunit; X66323 C5i 213 44 591 0.2 2.8 ATP-dependent D N A helicase II 80-kDa subunit; U04674 C5j 209 256 444 1.2 2.1 D N A ligase I U66058 C5k 193 194 202 1.0 1.0 D N A ligase III D17384 C51 115 98 150 0.9 1.3 D N A polymerase alpha catalytic subunit (pi80) D10061 C5m 297 20 336 0.1 1.1 D N A topoisomerase I (Top I) D12513 C5n 84 20 507 0.2 6.0 D N A topoisomerase II (Top II) X96618 C6a 2040 2059 2451 1.0 1.2 PA6 stromal protein; RAG1 gene activator Z21848 C6b 768 884 507 1.2 0.7 DNA-polymerase delta catalytic subunit U00478 C6c 269 212 288 0.8 1.1 DNAse I X07414 C6d 284 496 589 1.7 2.1 ERCC-1; D N A excision repair protein S71186 C6e 240 28 228 0.1 1.0 ERCC3 D N A repair helicase; DNA-repair protein D16306 C6f 115 68 76 0.6 0.7 ERCC5 excision repair protein; DNA-repair U42190 C6g 211 332 351 1.6 1.7 GTBP; G/T-mismatch binding protein; MSH6 D49429 C6h 1180 1335 1981 1.1 1.7 HR21spA; protein involved in D N A repair X92410 C6i 462 341 1204 0.7 2.6 MHR23A; Rad23 U V excision repair protein X92411 C6j 3233 1450 3329 0.4 1.0 MHR23B; Rad23 U V excision repair protein U59883 C6k 503 273 680 0.5 1.4 MLH1 D N A mismatch repair protein D64107 C61 131 108 340 0.8 2.6 MmLiml5; RecA-like gene; DMC1 homolog D13473 C6m 96 63 449 0.7 4.7 MmRad51; RecA homolog Z32767 C6n 55 233 366 4.2 6.6 MmRad52; yeast D N A repair Rad52 homolog U21011 C7a 333 702 548 2.1 1.6 MSH2 D N A mismatch repair protein X53068 C7b 634 527 752 0.8 1.2 PCNA; proliferating cell nuclear antigen AB000777 C7c 367 493 242 1.3 0.7 photolyase/blue-light receptor homolog U28724 C7d 228 224 154 1.0 0.7 PMS2 D N A mismatch repair protein U02098 C7e 232 374 215 1.6 0.9 pur-alpha transcriptional activator U66887 C7f 205 138 334 0.7 1.6 Rad50; D N A repair protein Hybridization Intensity Ratio 195 Accession Code Uninfect. Infected +/- bacteria Number A+B A B A B Protein/Gene Name M29475 C7g 137 238 450 1.7 3.3 RAG-1; V(D)J recombination activating protein M64796 C7h 170 104 416 0.6 2.4 RAG-2; V(D)J recombination activating protein U46854 C7i 156 192 707 1.2 4.5 ShcC adaptor; She-related; brain-specific X81464 C7j 383 447 1106 1.2 2.9 translin; recombination hotspot binding protein X96859 C7k 516 378 1272 0.7 2.5 ubiquitin-conjugating enzyme X99018 C71 176 259 1114 1.5 6.3 Ungl ; uracil-DNA glycosylase X74351 C7m 92 62 860 0.7 9.3 X P A C ; xeroderma pigmentosum group A U02887 C7n 100 100 534 1.0 5.4 XRCC1 DNA-repair protein, affecting ligation U17698 D l a 71 324 351 4.6 5.0 ablphilin-1 (abi-1); similar to HOXD3 M94087 D l b 249 199 878 0.8 3.5 activating transcription factor 4 (mATF4) L12721 Die 24 329 162 13.8 6.8 adipocyte differentiation-associated protein D26046 D i d 216 453 98 2.1 0.5 A T motif-binding factor ATBF1 L36435 Die 151 394 132 2.6 0.9 basic domain/leucine zipper transcription factor U36760 D l f 42 268 75 6.3 1.8 brain factor 1 (Hfhbfl) S53744 D i g 96 374 157 3.9 1.6 brain specific transcription factor NURR-1 S68377 D l h 20 618 312 30.9 15.6 Brn-3.2 POU transcription factor M58566 D l i 165 840 636 5.1 3.9 butyrate response factor 1 U36340 Dl j 28 447 328 16.1 11.8 C A C C C Box- binding protein B K L F X61800 D l k 21 420 430 19.9 20.3 C C A A T - binding transcription factor (C/ EBP) M37163 D l l 20 277 257 13.9 12.8 caudal type homeobox 1 (Cdxl) S74520 D i m 20 400 333 20.0 16.7 caudal type homeobox 2 (Cdx2) U42554 D i n 52 517 560 9.9 10.7 Sim transcription factor L12147 D2a 20 86 20 4.3 1.0 early B cell factor (EBF) L12703 D2b 20 235 136 11.7 6.8 engrailed protein (En-1) homolog LI2705 D2c 20 71 124 3.6 6.2 engrailed protein (En-2) homolog U01036 D2d 59 20 20 0.3 0.3 erythroid transcription factor NF-E2 U05252 D2e 20 118 20 5.9 1.0 DNA-binding protein SATB1 L10075 D2f 65 339 20 5.2 0.3 DNA-binding protein SMBP2 X72310 D2g 534 268 411 0.5 0.8 DP-1 (DRTF-polipeptide 1) transcription factor X86925 D2h 88 185 137 2.1 1.6 E2F-5 transcription factor M20157 D2i 230 338 652 1.5 2.8 Egr-1 Zn-finger regulatory protein U19617 D2j 20 131 298 6.6 14.9 Elf-1 (Ets family transcription factor) L21671 D2k 164 59 110 0.4 0.7 epidermal growth factor receptor kinase substrate M22115 D21 53 145 195 2.7 3.7 ERA-1 protein (ERA-1-993) U58533 D2m 127 20 224 0.2 1.8 Erf; Ets-related transcription factor M97200 D2n 70 275 149 3.9 2.1 erythroid kruppel-like transcription factor X63190 D3a 20 350 20 17.5 1.0 Ets-related protein PEA 3 J04103 D3b 1.06 248 308 2.4 2.9 Ets-2 transcription factor Z36885 D3c 36 253 , 20 7.0 0.6 Ets-related protein Sap 1A M74517 D3d 20 89 20 4.5 1.0 G A binding protein beta-2 chain M98339 D3e 56 253 27 4.5 0.5 G A T A binding transcription factor (GATA-4) X55123 D3f 60 329 20 5.5 0.3 GATA-3 transcription factor L39770 D3g 20 279 20 13.9 1.0 Gbx2 U59876 D3h 20 65 20 3.2 1.0 glial cells missing gene homolog (mGCMl) U20344 D3i 20 291 29 14.6 1.5 Gut-specific Kruppel-like factor G K L F X61754 D3j 20 268 20 13.4 1.0 heat shock transcription factor 2 (HSF 2) L35949 D3k 161 116 80 0.7 0.5 hepatocyte nuclear factor 3; forkhead homolog 8 D49474 D31 119 44 178 0.4 1.5 HMG-box transcription factor from testis X53476 D3m 465 247 587 0.5 1.3 HMG-14 non histone chromosomal protein Hybridization Intensity Ratio 196 Accession Code Uninfect Infected +/- bacteria Number A+B A B A B Protein/Gene Name M17192 D3n 581 166 211 0.3 0.4 homeobox protein 1.1 (Hox-1.1) M26283 D4a 125 314 34 2.5 0.3 homeobox protein 2.1 (Hox-2.1) X13721 D4b 51 92 20 1.8 0.4 homeobox protein 2.4 (Hox-2.4) M34857 D4c 14 51 20 3.7 1.4 homeobox protein 2.5 (Hox-2.5) X07439 D4d 20 186 606 9.3 30.3 homeobox protein 3.1 (Hox-3.1) J03770 D4e 20 209 989 10.5 49.4 homeobox protein 4.2 (Hox-4.2) X14759 D4f 20 89 20 4.5 1.0 homeobox protein 7.1 (Hox-7.1) X59252 D4g 20 188 20 9.4 1.0 homeobox protein 8 (Hox-8) X73573 D4h 20 54 20 2.7 1.0 homeobox protein HOXD-3 L03547 D4i 112 227 51 2.0 0.5 ikaros D N A binding protein U62522 D4j 38 82 20 2.2 0.5 Sp4 zinc finger transcription factor U19119 D4k 876 387 682 0.4 0.8 interferon inducible protein 1 J03168 D41 447 494 473 1.1 1.1 interferon regulatory factor 2 (IRF 2) U25096 D4m 348 154 242 0.4 0.7 Kruppel-like factor L K L F X90829 D4n 254 308 121 1.2 0.5 Lbx 1 transcription factor U63386 D5a 30 139 20 4.6 0.7 Mph-1 transcriptional repressor for hox genes X71327 D5b 20 200 20 10.0 1.0 MRE-binding transcription factor L26507 D5c : 117 256 84 2.2 0.7' myocyte nuclear factor (MNF) X56182 D5d 20 73 303 3.6 15.1 myogenic factor 5 U29086 D5e 46 116 360 2.6 7.9 neuronal helix-loop-helix protein NEX-1 D90176 D5f 16 240 20 15.1 1.3 NF-1B protein (transcription factor) M57999 D5g 93 547 106 5.9 1.1 NF-kappa B binding subunit (TFDB5) U20532 D5h 735 649 277 0.9 0.4 nuclear factor related to P45 NF-E2 U53228 D5i 643 614 191 1.0 0.3 nuclear hormone receptor ROR-alpha-1 M96823 D5j 75 388 20 5.2 0.3 nucleobindin M34381 D5k 36 387 27 10.7 0.7 octamer binding transcription factor (Oct 3) X57487 D51 411 549 260 1.3 0.6 PAX-8 (paired box protein P A X 8) U41626 D5m 2398 1148 2204 0.5 0.9 split hand/foot gene X94125 D5n 692 804 599 1.2 0.9 SRY-box containing gene 3 (Sox3) M97013 D6a 56 20 20 0.4 0.4 PAX-5 (B cell specific transcription factor) X63963 D6b 54 51 20 1.0 0.4 PAX-6 (paired box protein) U43788 D6c 100 179 20 1.8 0.2 POU domain (class 2) associated factor 1 D50621 D6d 17 135 20 7.8 1.2 PSD-95/SAP90A M35523 D6e 103 214 20 2.1 0.2 retinoic acid binding protein II, (CRABP-II) M84819 D6f 71 255 49 3.6 0.7 retinoic acid receptor (RXR-gamma) U09419 D6g 1394 2213 1395 1.6 1.0 retinoid X receptor interacting protein (RIP 15) M31042 D6h 362 832 317 2.3 0.9 T-lymphocyte activated protein X61753 D6i 2090 4572 1623 2.2 0.8 transcription factor 1 for heat shock gene Y07960 D6j 543 670 207 1.2 0.4 transcription factor B A R X 1 U53925 D6k 772 731 783 0.9 1.0 transcription factor C 1 U51037 D61 170 160 20 0.9 0.1 transcription factor CTCF (11 zinc fingers) Z27410 D6m 443 308 83 0.7 0.2 transcription factor LIM-1 U19118 D6n 222 160 227 0.7 1.0 transcription factor L R G - 21 U02079 D7a 163 216 36 1.3 0.2 transcription factor N F A T 1, isoform alpha X70298 D7b 44 352 20 8.0 0.5 SRY-box containing gene 4 M83380 D7c 20 20 20 1.0 1.0 transcription factor RelB D00926 D7d 20 86 20 4.3 1.0 transcription factor S -II X91753 D7e 120 159 20 1.3 0.2 transcription factor SEF2 X56959 D7f 20 41 20 2.0 1.0 transcription factor SP1P Hybridization Intensity Ratio 197 Accession Code Uninfect Infected +/- bacteria Number A+B A B A B Protein/Gene Name D17407 D7g 20 327 20 164 1.0 transcription factor SP2 X60831 D7h 114 470 54 4.1 0.5 transcription factor UBF S74227 D7i 503 1332 413 2.6 0.8 transcriptional enhancer factor 1 (TEF-1) X57621 D7j 3918 4567 3511 1.2 0.9 YB1 D N A binding protein L13968 D7k 691 285 800 0.4 1.2 Y Y 1 (UCRBP) transcriptional factor U47104 D71 63 20 20 0.3 0.3 zinc finger Kruppel type Zfp 92 U41671 D7m 45 215 20 4.8 0.4 zinc finger transcription factor RU49 M32309 D7n 20 20 20 1.0 1.0 zinc finger X-chromosomal protein (ZFX) Z31663 E l a 50 44 20 0.9 0.4 activin type I receptor U11688 E l b 20 20 20 1.0 1.0 orphan receptor D16250 E l c 20 62 20 3.1 1.0 bone morphogenetic protein receptor U56819 E l d 20 20 20 1.0 1.0 C-C chemokine receptor (MCP-1RA) X04836 E le 35 240 187 6.8 5.4 CD 4 receptor (T cell activation antigen) M83312 E l f 461 817 1070 1.8 2.3 CD 40L receptor (TNF receptor family) L05630 E l g 49 623 298 12.8 6.1 C5A receptor X72305 E l h 44 183 20 4.1 0.5 corticotropin releasing factor receptor U32329 E l i 95 203 20 2.1 0.2 endothelin b receptor (Ednrb) M58288 E l j 77 276 33 3.6 0.4 granulocyte colony - stimulatings factor receptor S71251 E l k 22 48 20 2.1 0.9 monotype chemoattractant protein 3 D26177 E l l 20 20 20 1.0 1.0 D-factor/LIF receptor L47239 E l m 27 62 20 2.3 0.7 ERBB-2 receptor; c-neu; HER2 tyrosine kinase L47240 E l n 20 30 20 1.5 1.0 ERBB-3 receptor J04843 E2a 77 201 187 2.6 2.4 erythropoietin receptor X59927 E2b 20 20 20 1.0 1.0 fibroblast growth factor receptor 4 M28998 E2c 20 20 20 1.0 1.0 fibroblast growth factor receptor basic (b FGF-R) D17292 E2d 50 240 20 4.8 0.4 G-protein-coupled receptor M85078 E2e 1304 2158 2024 1.7 1.6 GM-CSF receptor M98547 E2f 289 200 411 0.7 1.4 growth factor receptor U29173 E2g 362 89 557 0.2 1.5 lymphotoxin receptor (TNFR family) Z11974 E2h 20 151 262 7.6 13.1 macrophage mannose receptor X04367 E2i 20 130 123 6.5 6.1 pre-platelet-derived growth factor receptor U36203 E2j 20 20 75 1.0 3.8 snoN; ski-related oncogene D25540 E2k 20 20 169 1.0 8.4 TGF-beta receptor type 1 M89641 E21 20 20 20 1.0 1.0 interferon alpha-beta receptor M28233 E2m 20 20 20 1.0 1.0 interferon-gamma receptor X59769 E2n 20 20 20 1.0 1.0 interleukin-1 receptor type II L12120 E3a 117 378 268 3.2 2.3 interleukin-10 receptor M81832 E3b 59 13 102 0.2 1.7 somatostatin receptor 2 L20048 E3c 1389 1051 1541 0.8 1.1 interleukin-2 receptor gamma chain M29855 E3d 159 199 146 1.2 0.9 interleukin-3 receptor M27959 E3e 20 92 20 4.6 1.0 interleukin-4 receptor D90205 E3f 20 20 62 1.0 3.1 interleukin-5 receptor M29697 E3g 20 296 418 14.8 20.9 interleukin-7 receptor D17630 E3h 20 372 178 18.6 8.9 interleukin-8 receptor M84746 E3i 20 20 102 1.0 5.1 interleukin-9 receptor X53779 E3j 20 100 220 5.0 11.0 androgen receptor U18542 E3k 20 20 637 1.0 31.8 calcitonin receptor lb M38651 E31 20 20 231 1.0 11.6 estrogen receptor X13358 E3m 20 133 20 6.7 1.0 glucocorticoid receptor form A Hybridization Intensity Ratio 198 Accession Code Uninfect. Infected +/- bacteria Number A+B A B A B Protein/Gene Name M33324 E3n 20 20 20 1.0 1.0 growth hormone receptor J05149 E4a 20 20 20 1.0 1.0 insulin receptor L24563 E4b 20 20 58 1.0 2.9 insulin receptor substrate-1 (IRS-1) M22959 E4c 20 20 20 1.0 1.0 prolactin receptor PRLR2 Z19521 E4d 20 88 117 4.4 5.8 low density lipoprotein receptor S49542 E4e 20 44 20 2.2 1.0 5-hydroxytryptamine receptor Z11597 E4f 20 20 20 1.0 1.0 5-hydroxytryptamine (serotonin) receptor lb X72230 E4g 20 20 176 1.0 8.8 5-hydroxytryptamine (serotonin) receptor l c Z14224 E4h 20 20 286 1.0 14.3 5-hydroxytryptamine (serotonin) receptor le beta Z15119 E4i 20 20 354 1.0 17.7 5-hydroxytryptamine (serotonin) receptor 2c X72395 E4j 20 20 391 1.0 19.5 5-hydroxytryptamine (serotonin) receptor 3 Z23107 E4k 20 2Q 424 1.0 21.2 ; 5-hydroxytryptamine (serotonin) receptor 7 K02582 E41 20 20 251 1.0 12.5 acetylcholine receptor delta submit LI0084 E4m 25 20 285 0.8 11.4 adrenergic receptor beta 1 U17985 E4n 43 268 211 6.2 4.9 cannabinoid receptor 1 (brain) U21681 E5a 20 147 20 7.3 1.0 cannabinoid receptor 2 (macrophage, CB2) U19880 E5b 20" 20 20 1.0 1.0 dopamine receptor 4 U46923 E5c 20 20 20 1.0 1.0 G-protein coupled receptor M86566 E5d 20 83 20 4.2 1.0 G A B A - A receptor alpha-1 subunit M92378 E5e 73 67 20 0.9 0.3 G A B A - A transporter 1 L04663 E5f 57 136 20 2.4 0.3 G A B A - A transporter 3 L04662 E5g 471 394 757 0.8 1.6 G A B A - A transporter 4 X57497 E5h 803 892 1234 1.1 1.5 glutamate receptor, ionotropic A M P A 1 D10217 E5i 315 282 814 0.9 2.6 glutamate receptor, ionotropic D10651 E5j 109 20 630 0.2 5.8 glutamate receptor, ionotropic N M D A 2 B M14537 E5k 45 20 626 0.4 13.9 nicotinic acetylcholine receptor X91144 E51 407 205 602 0.5 1.5 P-selectin (glycoprotein ligand-1) D25281 E5m 170 233 603 1.4 3.5 catenin alpha X14951 E5n 1125 1375 1357 1.2 1.2 CD 18 antigen beta subunit (LFA-1) M l 8934 E6a 20 240 20 12.0 1.0 CD2 antigen M34563 E6b 42 125 20 3.0 0.5 CD28 (receptor for B71) M33158 E6c 43 186 20 4.3 0.5 CD3 antigen, delta polypeptide L06039 E6d 502 244 288 0.5 0.6 CD31; platelet endothelial cell adhesion molecule M27129 E6e 2340 2979 3860 1.3 1.6 CD44 antigen U03856 E6f 583 424 609 0.7 1.0 CD45 associated protein (CD 45-ap, LSM-1) D10329 E6g 2042 2354 2186 1.2 1.1 CD7 antigen M34510 E6h 9350 12877 11360 1.4 1.2 CD 14 antigen LI 6928 E6i 1791 1325 2771 0.7 1.5 CD22 antigen X07640 E6j 248 205 1014 0.8 4.1 cell surface glycoprotein MAC-1 alpha subunit X05719 E6k 64 20 744 0.3 11.6 CTLA-4 (immunoglobin superfamily member) L33779 E61 63 94 558 1.5 8.8 desmocollin 2 U43512 E6m 317 154 567 0.5 1.8 dystroglycan 1 X04648 E6n 448 511 781 1.1 1.7 glutamate receptor channel subunit gamma X75427 E7a 635 20 20 0.0 0.0 integrin alpha 2 (CD49b) X53176 E7b 133 44 90 0.3 0.7 integrin alpha 4 U14135 E7c 394 116 482 0.3 1.2 integrin alpha. 5 (CD51) X69902 E7d 545 420 440 0.8 0.8 integrin alpha 6 L23423 E7e 100 20 84 0.2 0.8 integrin alpha 7 X58384 E7f 85 20 71 0.2 0.8 dipeptidyl peptidase IV Hybridization Intensity Ratio 199 Accession Code Uninfect. Infected +/- bacteria Number A+B A B A B Protein/Gene Name Y00769 E7g 449 354 709 0.8 1.6 integrin beta M95633 E7h 689 719 1180 1.0 1.7 integrin beta 7 subunit X52264 E7i 537 546 1070 1.0 2.0 intercellular adhesion molecule-1 J02870 E7j 1173 1089 2078 0.9 1.8 lamimin receptor 1 M31131 E7k 126 20 627 0.2 5.0 neuronal-cadherin (N-cadherin) XI4943 E71 63 20 809 0.3 12.8 neuronal cell surface protein F3 M84487 E7m 59 20 765 0.3 13.0 vascular cell adhesion protein 1 D13867 E7n 151 20 704 0.1 4.7 V L A - 3 alpha subunit D12482 F l a 20 20 20 1.0 1.0 basic fibroblast growth factor (b- FGF) L24755 F ib 45 20 20 0.4 0.4 bone morphogenetic protein 1 L25602 F l c 209 20 20 0.1 0.1 bone morphogenetic protein 2 (BMP-2) X56848 F i d 387 48 262 0.1 0.7 bone morphogenetic protein 4 (BMP-4) X56906 Fie 119 478 452 4.0 3.8 bon