A Role for Stat-1 in Regulating Interleukin 10 Production Following Lps Challenge

Home , Inflammatory cytokine, Interferon type II, STAT protein

A ROLE FOR STAT-1 IN REGULATING INTERLEUKIN 10 PRODUCTION FOLLOWING LPS CHALLENGE

DISSERTATION

Presented in Partial Fulfillment of the Requirements for

the Degree Doctor of Philosophy in the

Graduate School of The Ohio State University

Jeffrey Bryan VanDeusen, B.A.

* * * * *

The Ohio State University

2004

Dissertation Committee: Approved by Clay Marsh, MD

Christoph Plass, PhD ______Michael A. Caligiuri, MD Denis Guttridge, PhD Adviser Department of Molecular Virology, Immunology, and Molecular Genetics

ABSTRACT

There have been substantial advances in understanding the events that regulate gene expression at the cellular and molecular level, however, there has been limited progress integrating this information to understand how biological systems function in vivo. Complementary DNA and protein microarray technologies in combination with sophisticated bioinformatics may eventually provide important insight into how biologic systems work in vivo. We hypothesized that assessments of such events in vivo would provide new insights into the immune response that could not be predicted or discovered ex vivo. Here, we describe the use of quantitative real time RT-PCR to serially quantify expression of a variety of pro- and anti-inflammatory cytokine genes in a number of individual tissues before, during, and after challenge with lipopolysaccharide (LPS). The data provide new insight into the heterogeneity of cytokine gene expression from organ to organ following infectious insult in vivo, as well as a greater understanding of cytokine regulation. For example, the anti- inflammatory cytokine interleukin-10 (IL-10) is thought to down-regulate the effects of the pro-inflammatory cytokine interferon gamma (IFN-γ) on monocyte activation following lipopolysaccharide (LPS) stimulation. However, the often-postulated reciprocal regulation of IL-10 gene expression by IFN-γ has not been studied in vivo.

ii Here we serially quantify the expression of IL-10 before, during, and after an in vivo challenge with LPS or a gram-negative organism. In our system, we demonstrate that the regulation of IL-10 gene expression has at least two phases. The early induction occurs independent of the signal transducer and activator of transcription 1 (STAT-1), while a delayed active repression of IL-10 gene expression is critically dependent on

STAT-1, most or all of which is independent of IFN-γ. Consistent with this, STAT-1 is absent from the IL-10 promoter during the early induction of the cytokine, but is bound to the IL-10 promoter in the delayed repression of the cytokine. Thus, STAT-1 binding to the IL-10 promoter is likely directly associated with STAT-1-mediated repression of

IL-10 gene repression during infectious challenge with gram-negative organisms in vivo. This study provides new insights into the regulation of IL-10 following in vivo challenge with a gram-negative organism.

iii

What are the words to describe the feeling of watching a sunset over the ocean, the death of a loved one, or the warm sun on your face after a long winter? The English language, always so descriptive, fails utterly to portray these moments in all our lives.

The words seem a dim reflection when held up to the events that inspire them.

What are the words for graduate school? Some of them are hard work, inspiration,

exhaustion, and elation. But they are pale.

Dedicated to my loving family and friends

In loving memory of Evelyn, my first girlfriend

ACKNOWLEDGMENTS

I wish to thank first and foremost my adviser, Michael Caligiuri, for his patience, guidance, enthusiasm and support during the last 6 years. His time and energy have helped shape my view of life and science.

I also wish to thank Martin Guimond, whose arrival in the laboratory was a catalyst of change for my work. His technical expertise and discussions made much of my work possible.

I thank my first student mentor in the lab, Todd Fehniger, for his help in teaching me how to be a graduate student in those early critical years.

I thank Donna Bucci and Tamra Brooks for years of tireless work on my behalf.

I thank my friends and collaborators Sameek Roychowdhury, Brian Becknell, Megan

Cooper, Aharon Freud, and Bradley Blaser for their help and advice. I also would like to thank the many people whom are too numerous to mention whom have come through

Dr. Caligiuri’s lab and helped me in my studies.

Most importantly, I thank my family and Amanda for their love and support.

This work was made possible by grants CA-68458, CA-65670, and P30CA-16058 from the National Institutes of Health.

VITA

July 15, 1975...... Born Columbus, Ohio

1997...... B.A. Biology Summa Cum Laude Wittenberg University

1997-2004...... M.D./Ph.D. Candidate Fellow, Medical Scientist Program The Ohio State University, College of Medicine

AWARDS AND FELLOWSHIPS 1993 Wittenberg University Honors Scholar. 1995 Outstanding Biology Student of the Year, Wittenberg University. 1996 Wittenberg University Presidential Scholar. 1996 Phi Beta Kappa. 1997 Summa Cum Laude. 1997-2004 Medical Scientist Program Fellow, The Ohio State University, College of Medicine 2000 First Place, Poster Presentation, Landacre Day Medical Student Research Forum, The Ohio State University. 2000 First Place, Poster Abstract, Medical Scientist Student Organization Research Day Conference Award, The Ohio State University.

PUBLICATIONS

1. Fehniger TA, Shah MH, Turner MJ, VanDeusen JB, Whitman SP, Cooper MA, Suzuki K, Wechser M, Goodsaid F, Caligiuri MA. Differential cytokine and chemokine gene expression by human NK cells following activation with IL-18 or IL-15 in combination with IL-12: implications for the innate immune response. J Immunol 1999; 162(8):4511- 20.

2. Fehniger TA, Bluman EM, Porter MM, Mrozek E, Cooper MA, VanDeusen JB, Fankel SR, Stock W, Caligiuri MA. Potential mechanisms of human natural killer cell expansion in vivo during low dose IL-2 therapy. J Clin Invest. 2000; 106(1):117-24.

3. Fehniger TA, Suzuki K, Ponnappan A, VanDeusen JB, Cooper MA, Florea SM, Freud AG, Robinson ML, Durbin J, and Caligiuri MA. Fatal leukemia in interleukin 15 transgenic mice follows early expansions in natural killer and memory phenotype CD8+ T Cells. J Exp Med 2001; 193(2): 219-232.

vi 4. Fehniger TA, Suzuki K, VanDeusen JB, Cooper MA, Freud AG, and Caligiuri MA: Fatal leukemia in interleukin-15 transgenic mice. Blood Cells Mol Dis 2001; 27(1):223-230.

5. Tong HH, Chen Y, James M, VanDeusen JB, Welling DB, DeMaria TF: Expression of cytokine and chemokine genes by human middle ear epithelial cells induced by formalin-killed Haemophilus influenzae or its lipooligosaccharide htrB and rfaD mutants. Infect Immun. 2001 Jun;69(6):3678-84.

6. Cooper MA, Bush JE, Fehniger TA, VanDeusen JB, Waite RE, Liu Y, Aguila HL, Caligiuri MA: In vivo evidence for a dependence on interleukin 15 for survival of natural killer cells. Blood. 2002 Nov 15;100(10):3633-8.

7. Nguyen KB, Salazar-Mather TP, Dalod MY, VanDeusen JB, Wei XQ, Liew FY, Caligiuri MA, Biron CA: Coordinated and distinct roles for IFN-alphabeta, IL-12, and IL-15 regulation of NK cell responses to viral infection. J Immunol. 2002 Oct 15;169(8):4279- 87.

8. VanDeusen JB, Caligiuri MA: New developments in anti-tumor efficacy and malignant transformation of human natural killer cells. Curr Opin Hematol. 2003 Jan; 10(1):55- 59.

9. Farag SS, VanDeusen JB, Fehniger TA, Caligiuri MA: Biology and clinical impact of human natural killer cells. Int J Hematol. 2003 Jul; 78(1):7-17.

FIELDS OF STUDY

Major Field: Molecular Virology, Immunology, and Medical Genetics Concentration in immunology

vii

TABLE OF CONTENTS

Page Abstract...... ii

Dedication...... iv

Acknowledgments...... v

Vita...... vi

List of Figures...... ix

1. Introduction...... 1

Materials and Methods...... 17 Results...... 22 Discussion...... 33

2. Literature Cited ...... 54

viii

LIST OF FIGURES

Figure Page

1 LPS elicited cytokine production ...... 14

2 The LPS signaling pathway ...... 15

3 Interferon signaling...... 16

4 Spleen cytokine production post LPS...... 39

5 Liver cytokine production post LPS ...... 40

6 Lung cytokine production post LPS ...... 41

7 Kidney cytokine production post LPS ...... 42

8 White blood cell cytokine production post LPS ...... 43

9 Peritoneal cavity cell cytokine production post LPS ...... 44

10 IL-10 production in WT and STAT-1-/- animals...... 46

11 IL-10 production in IFN deficient animals ...... 48

12 In vivo source of IL-10 post LPS ...... 50

13 STAT-1 activation and association with IL-10...... 52

14 In vitro IL-10 production in WT and STAT-1-/- bone marrow ...... 53

INTRODUCTION

Inflammation is at the heart of infection, autoimmunity, and cancer.

Appropriate responses to environmental insults, such as a bacterial infection, are critical to the survival of the host organism. Sepsis, a condition in which a patient has a systemic response to a bacterium or fungal infection, results in a cascade of events that is often devastating. Sepsis most often occurs in the intensive care unit of hospitals, but can arise for a variety of reasons. In 2000 alone, there were a reported 659,935 cases of sepsis in the United States. The patient care for this condition, requiring extensive medical treatment and long term recovery, is an average $50,000 per person (17 billion dollars annually), and patient mortality resulting mostly from organ failure ranges between 20-50% (Martin et al., 2003).

This cascade of events is initiated through of a series of high affinity receptors designed to detect the presence of a bacterial invasion. These function to activate the innate, or non-specific immune response, which begins the process of containing and eliminating the bacterial challenge. The gram-negative bacterial cell wall component, lipopolysaccharide (LPS), is a surface endotoxin that is shed from bacteria and triggers the production of a myriad of immunoregulatory proteins called cytokines that participate in eliminating the bacterial insult (Aderem and Underhill, 1999) (Fig. 1).

During the early host response to a gram-negative infection, LPS associates with a 60kd

1 serum protein called lipid binding protein (LBP) and this complex subsequently associates with CD14, a 50kd glycoprotein surface receptor constitutively expressed primarily by macrophages and monocytes, two cellular components of the innate immune system (Schumann et al., 1990; Tobias et al., 1995) (Fig. 2). Once bound to

CD14, the LPS/CD14 complex associates with a separate membrane bound receptor

TLR4, a member of a family of specialized pattern recognition receptors called the Toll- like receptors (TLR), so named for their homology to the Drosophila Toll proteins

(Medzhitov et al., 1997; Wright et al., 1990).

The Toll family of pattern recognition receptors includes ten members to date, all of which recognize pathogen-associated motifs such as CpG DNA (TLR9) and bacterial lipopeptides (TLR2). Once engaged, TLR4 associates with another membrane associated protein MD2, first discovered when experiments transfecting TLR4 alone into cell lines failed to induce LPS responsiveness (Shimazu et al., 1999). The engagement of the Toll4/MD2 complex results in activation of MyD88, an intracellular protein that binds to the Toll/IL-1 receptor (TIR) domain of Toll4 (Kawai et al., 1999;

Takeuchi et al., 2000). MyD88 subsequently recruits interleukin (IL)-1 receptor associated kinase (IRAK)-1, 4, and tumor necrosis factor receptor-associated factor

(TRAF)-6 (Cao et al., 1996a; Cao et al., 1996b; Hacker, 2000). Ultimately, this complex results in the activation of the NF-kB and MAP kinase transcription factors that stimulate production of cytokines and other immune response proteins (Sen and

Baltimore, 1986; Weinstein et al., 1992).

Until recently, it was also unclear how specificity for the various TLR receptors was achieved due to the seemingly common signaling pathways used by all family 2 members. However, adaptor proteins known as TIR domain-containing adaptor protein

(TIRAP) and TIR domain-containing adaptor inducing IFN-β (TRIF) have been identified that specifically associate with different TLR/MyD88 receptors (Horng et al.,

2001; Yamamoto et al., 2003). Experiments with TIRAP knockout macrophages demonstrating delayed/reduced activation following LPS stimulation suggests that

TIRAP associated with MyD88 and helps mediate signaling through TLR4. However, these knockouts still responded partially to LPS stimulation, suggesting that TIRAP is not essential to LPS signaling and may act as a signal enhancer (Horng et al., 2002).

Toll4 also appears to activate its own signal repressor. It has recently been shown that TLR4 activates a novel family of cytoplasmic proteins termed Toll- interacting protein, or Tollip (Burns et al., 2000). Activation of Tollip appears to negatively regulate TLR4 signaling through its association with IRAK-1, excluding it from activating TRAF and other downstream signal mediators (Zhang and Ghosh,

2002). More work will be needed to elucidate the full role of this inhibitory pathway and TLR4 signaling.

In response to TLR4/MD2 stimulation by LPS, host macrophages and other components of the innate and antigen-specific immune system synthesize and secrete pro-inflammatory cytokines such as tumor necrosis factor alpha (TNF-α), IL-12, and

IL-1 (van der Poll and van Deventer, 1999). These cytokines or monokines bind to constitutively expressed receptors on other innate immune effector cells, such as natural killer (NK) cells, and stimulate the secretion of additional pro-inflammatory cytokines like interferon (IFN)-γ that further drive pro-inflammatory cytokine production before

3 the induction of adaptive immunity (Trinchieri, 1989) (Fig. 1). This early IFN-γ production by NK cells is requisite for the further activation of monocytes, macrophages, and other innate immune cells to clear the host of invading pathogens, as evidenced by the susceptibility of mice lacking IFN-γ to mycobacterial infections

(Jouanguy et al., 1999). However, the importance of tightly regulating this inflammatory response to bacterial challenge is clear, as too little or too much monocyte/macrophage activation can result in death for the host (van der Poll and van

Deventer, 1999).

There are two subgroups of interferon, type II (IFN-γ) and type I (IFN-α/β).

While IFN-γ and IFN-β are single proteins, IFN-α represents multiple subtypes that are a result of alternative splicing and multiple genes on human chromosome 9 (Pestka et al., 1987). The receptor for IFN-γ consists of two separate protein chains, IFN-γ receptor 1 (IFNGR1) and IFNGR2, expressed nearly ubiquitously (Bach et al., 1997).

Upon ligation of IFN-γ to its receptor, two family members of the Janus kinases (JAK1 and JAK2) associate with the receptor chains, become phosphorylated, and recruit signal transducer and activator of transcription (STAT)-1 through SRC homology 2

(SH2) domains (Silvennoinen et al., 1993) (Fig. 3). The STAT family of proteins consists of seven family members, all of whom contain several important functional domains including the SH2 domains, a DNA binding domain, a carboxy terminal transactivation domain, and an amino terminal activation domain (Horvath et al., 1995;

Shuai et al., 1994). Each of these domains plays an important role in the regulation of

STAT activation and its activity as a transcription factor.

4 Once associated with JAK1 and JAK2, STAT-1 becomes phosphorylated on a single tyrosine residue (701) in its amino terminal region and forms a homodimer with another phosphorylated STAT-1 protein (Shuai et al., 1993). These homodimers translocate to the nucleus, where they bind recognition sequences referred to as GAS sequences (IFN-γ-activated site) and activate transcription largely by means of recruitment of co-activators such as CBP/p300 through the c-terminal transactivation domain (Khan et al., 1993; Qureshi et al., 1996). The critical importance of STAT-1 to

IFN-γ signaling is demonstrated by STAT-1 knockout (STAT-1-/-) mice that lack activation of IFN-γ target genes and thus have increased susceptibility to viral infections such as mouse hepatitis virus (MHV) (Durbin et al., 1996).

Type I interferon (IFN-α/β) signaling is more complex than that of IFN-γ. All of these proteins bind to their heterodimeric receptor, IFN-α receptor 1 (IFNAR1) and

IFNAR2 (Mogensen et al., 1999). Binding of IFN-α/β results in amino terminal tyrosine phosphorylation of both STAT-1 and STAT-2. These proteins form subsequently a heterodimer, and additionally will associate with a third protein, either p48 or IRF9, to form a transcription factor complex known as ISGF3 (Kimura et al.,

1996). ISGF3 translocates to the nucleus where it binds recognition sites known as interferon-stimulated response elements (ISRE). Early binding of ISGF3 to key gene

ISRE upregulates anti-viral response genes, as evidenced by mice lacking IFN-β that are significantly more susceptible to Vaccinia viral infection (Deonarain et al., 2000).

While critical for anti-viral responses, the role that IFN-α/β plays in microbial defense

is less well understood than IFN-γ and is yet to be fully recognized. Initial studies with

5 IFN-α/β receptor knockout animals show similar susceptibility to bacterial infection,

however, deficient animals had a lower bacterial load in liver and spleen suggesting

INF-α/β delays clearance of these organisms (van den Broek et al., 1995).

Regulation of the Jak/STAT signaling cascade is essential to modulating

cytokine responses and thus coordinating the host defense to pathogen insult. Indicative

of their central role in immunity, several mechanisms exist to control Jak/STAT

activity. In the earliest steps in this signal cascade, the Jak proteins are targeted by the

suppressor of cytokine signaling (SOCS) family of proteins. These proteins consist of

eight family members, all of which contain SH2 domains and a carboxy terminal

domain called a SOCS box (Yasukawa et al., 2000). The SOCS proteins are

upregulated by cytokine stimulation, and function by either associating with Jak

proteins and excluding them from STAT activation (i.e. SOCS1 and SOCS3), or by

directly associating with the activated receptor (i.e. SOCS3), blocking Jak recruitment

(Sasaki et al., 1999; Yasukawa et al., 1999; Yoshimura et al., 1995). In addition to

physically blocking Jak activation, SOCS may also help target these proteins for

degradation. SOCS1 specifically is required for the ubiquination of Jak2, and co-

expression of SOCS1 with Jak2 increases the degradation of Jak2 (Kamizono et al.,

2001).

Globally, the critical importance of these proteins in cytokine regulation has

been confirmed in animals with targeted deletions of the SOCS proteins. Mice with a

germline deletion of SOCS1 die soon after birth, however, crossing SOCS1-/- mice with

IFN-γ-/- animals largely rescues the lethal phenotype, demonstrating that these animals

6 likely die due to dysregulation of IFN-γ production (Alexander et al., 1999; Bullen et

al., 2001; Starr et al., 1998). In addition to SOCS1, a conditional SOCS3-/- animal in which SOCS3 has been deleted from macrophages demonstrates that SOCS3 is important for abrogating IL-6 mediated STAT3 activation in macrophages (Yasukawa et al., 2003).

In addition to the Jak family, the STAT proteins are also highly regulated by

post-transcriptional modifications and associations with other proteins. Although

tyrosine phosphorylation of STAT-1 may be critical to its activation and dimerization,

STAT-1 is also regulated by serine phosphorylation of residue 727 (Varinou et al.,

2003; Wen et al., 1995). This phosphorylation appears to increase transcriptional

activity of STAT-1 target genes, and may be mediated by protein kinases such as

extracellular signal-regulated protein kinase (ERK) or calcium/calmodulin-dependent

kinase II (CAMK2) (Li et al., 2004; Nair et al., 2002). STAT-1 can also be methylated

on N-terminal Arginine 31 by protein arginine methyltransferase 1 (PRMT1), which

associates with the IFN-α/β receptor (Mowen et al., 2001). The methylation of STAT-1

increases DNA binding activity of STAT-1, potentially by preventing interaction with

an inhibitor of STAT-1 called PIAS1 (Mowen et al., 2001).

The PIAS family of proteins consists of four related proteins: PIAS1, PIAS3,

PIASX, and PIASY(Shuai, 2000). Some of the PIAS proteins exhibit alternative

splicing that generates isoforms. PIAS3 has a splice variant that includes 39 additional

amino acids (PIAS3β), and PIASXα and β differ in their amino terminal regions

(Moilanen et al., 1999; Wible et al., 2002). Despite splice variants and differences in

7 some domains, all of these proteins share homology in their central region called the

RING-finger-like-zinc-binding domain (RLD). The PIAS proteins also have an amino

terminal domain called scaffold attachment factor A/B, acinus and PIAS, or SAP

domain (Aravind and Koonin, 2000). This is believed to be an anchoring domain for

the PIAS proteins to chromatin to affect local gene expression.

PIAS proteins inhibit the Jak/STAT pathway by directly associating with

activated STAT proteins following stimulation (Chung et al., 1997). PIAS1 and PIASY

have both been shown to interact with activated STAT-1, however, this interaction does

not occur in the absence of stimulation as PIAS proteins only bind to STAT dimers

(Liao et al., 2000; Liu et al., 1998). The influence of PIAS proteins exert on STAT

mediated gene activation varies. For example, PIAS1 inhibits STAT-1 transcription by

interrupting STAT-1 DNA binding (Liu et al., 1998). However, PIASY inhibits STAT-

1 mediated gene activation without affecting DNA binding (Liu et al., 2001), but

PIASY has been found to interact with histone deacetylase (HDAC)1 (see chromatin

remodeling chapter 1.8), suggesting a mechanism by which the PIAS proteins may alter

STAT mediated gene activation by recruiting co-repressor molecules(Long et al., 2003).

Further studies are needed to fully understand all the roles that PIAS proteins play in this and other pathways where they are operative.

While IFN-γ is the prototypic monocyte/macrophage activating factor, IL-10 has been identified as a key component in down-regulating the pro-inflammatory cytokine cascade that ensues following exposure to bacterial products such as LPS (de Waal

Malefyt et al., 1991; Ertel et al., 1996; Fiorentino et al., 1991). IL-10 was first

identified as a protein capable of inhibiting the production of pro-inflammatory 8 cytokines and called cytokine synthesis inhibitory factor (Fiorentino et al., 1989). In

vitro, IL-10 is produced by monocytes and macrophages following exposure to LPS (de

Waal Malefyt et al., 1991), and its mechanism of action includes down-regulating the production of pro-inflammatory cytokines such as IFN-γ, as well as repressing IFN-γ

mediated (STAT)-1 activation through induction of the SOCS family of proteins (Ito et

al., 1999). The importance of IL-10 in controlling pro-inflammatory cytokine release is

evidenced by studies demonstrating increased mortality among mice with neutralized or

deficient IL-10 following LPS (Emmanuilidis et al., 2001; Howard et al., 1993;

Marchant et al., 1994; Rennick et al., 1997).

While the role of IL-10 in controlling pro-inflammatory host responses is well

established, little is known about how the production of this critical anti-inflammatory cytokine is regulated. The successful host response to invading pathogens is a careful balance, and while an excessive pro-inflammatory response has negative consequences for the host, overabundant IL-10 can compromise inflammation designed to clear invading pathogens (Sewnath et al., 2001). Thus, several investigators have begun to examine the transcriptional regulation of IL-10. In vitro, two transcription factors designated SP1 and SP3 have been implicated as important for the regulation of IL-10, suggesting that IL-10 mRNA may be constitutively produced under the influence of

SP1/SP3 transcriptional elements and largely regulated by post-transcriptional control mechanisms such as 3’ mRNA instability sequences present in the IL-10 mRNA transcript (Brightbill et al., 2000; Powell et al., 2000; Tone et al., 2000). In addition to these observations, further regulation of IL-10 was suggested by in vitro work that observed decreases in IL-10 production following removal of a putative STAT-3 9 binding site at position -120 in the IL-10 promoter (Benkhart et al., 2000).

However, effects on transcription mediated by cis-acting elements in the promoter elements of a gene are often limited to a specific cell type, developmental stage, or physiologic stimulus. A demonstration of this principle is work in which

Takeda et al. created knockout mice selectively lacking STAT-3 in the neutrophil and macrophage compartment. In contrast to earlier in vitro work examining the positive role for STAT-3 and IL-10 transcription in vitro, these cell-specific STAT-3-/- mice dramatically overproduced IL-10 in response to LPS in vivo (Takeda et al., 1999).

These seemingly paradoxical results outlining the role for STAT-3 in the regulation of

IL-10 highlight the importance of in vivo experiments in understanding the role that transcription factors play in the complex regulation of IL-10. In addition to the work with SP1/3 and STAT-3, previous in vitro work has also identified IFN as a likely candidate for regulating IL-10 production. For example, pretreatment of peripheral blood cells in vitro with IFN-γ suppresses IL-10 production in response to LPS in a dose dependent fashion (Chomarat et al., 1993).

In addition to the STATs and their role as transcription factors, newly discovered mechanisms of gene regulation include epigenetic modifications that affect

DNA accessibility. In eukaryotic cells, DNA is directly organized around scaffolding proteins called histones, and further arranged into higher order structures by other proteins that compact the DNA into chromatin. Histones are organized into octamers comprised of two H3 and H4 proteins, and two H2A/H2B dimmers (Luger et al., 1997).

Each histone is a globular basic protein with a charged amino terminal tail that “sticks out” from the histone/DNA complex. Alterations to these amino terminal tails plays a 10 central role in the association of transcription factors to DNA by either “opening” or

“closing” of the DNA/histone superstructure (Cheung et al., 2000). Modification of histone tails includes methylation, phosphorylation, or acetylation. As an example, histone acetylation of key residues such as lysine generally promotes gene expression by spacing histones, and thus is believed to increase the availability of DNA to transcription factor proteins by relaxing the DNA superstructure (Roth et al., 2001).

The regulation of these modifications is complex, and involves a growing class of

proteins that form large complexes that may mediate multiple modifications.

One class of proteins that mediate these reversible alterations to DNA are the

histone acetyltransferases (HAT), which as their name implies add acetyl groups to

histones, and the histone deacetylases (HDAC) which remove them. Experiments using

chemical inhibitors of HATs and HDACs such as trichostatin A (TSA) demonstrate that

these proteins carry out acetylation activity, and that their role in acetylation is important in gene regulation (Chambers et al., 2003). Recently, a link between these proteins and JAK/STATs has been established. In 2002, it was demonstrated that

STAT2 could recruit HAT proteins through its transactivation domain (Paulson et al.,

2002). In addition, work examining the role of HDAC1 and IFN regulated gene expression also demonstrates that STAT1/STAT2/IRF9 associates with HDAC1, and that HDAC1 functions to upregulate IFN mediated gene expression through deacetylation of histone H4 (Nusinzon and Horvath, 2003). It is traditionally believed that HDAC proteins suppress gene expression through deacetylation; however, the opposite appears to occur in this relationship. These paradoxes highlight the need to further understand how this complex regulation is occurring, and what other proteins,

11 such as PIAS, may be present in the regulatory complex being recruited by the STAT

proteins.

The relatively recent advances in genomic discovery tools, such as complementary DNA microarray chips, have provided the ability to simultaneously analyze thousands of gene transcripts. These techniques will likely soon lead to a deeper understanding of the regulation of gene expression at the cellular level, yet several obstacles will have to be overcome before such tools will provide insight into how biologic systems function in vivo (Brown and Botstein, 1999; Duggan et al., 1999).

The optimal statistical methodology for analysis of the abundant data is not yet resolved. Advances in bioinformatics promises to provide powerful tools to complement the microarray technology, but a complete solution to this bottleneck will likely take years (Reichhardt, 1999). The sheer number of genes and the need to perform sequentially times assays using this very expensive technology render this approach impractical for most laboratories to assess biologic systems in vivo at this time.

In contrast, quantitative real-time PCR is a relatively inexpensive, targeted technique by which transcript may be accurately quantified. In an effort to further understand, at the tissue specific level, the production of key immunoregulatory cytokines following in vivo LPS challenge we have serially quantified a number of these factors by real-time PCR in wild type animals. In addition to these experiments, we examine the resultant production of IL-10, crucial to regulating this cycle of activation. In an effort to further understand the role that IFN-α/β/γ signaling may have in the regulation of IL-10 resulting from LPS or stimulation via a gram-negative 12 organism in vivo, we have challenged, in addition to WT animals, STAT-1-/-, IFN-γ-/-, and IFN-α/β/γ neutralized mice with a sub-lethal dose of LPS and serially measured production of IL-10 transcript and protein by quantitative real-time RT PCR. We demonstrate, for the first time, that IL-10 has at least two phases of regulation following this in vivo infectious challenge; the first is induction of IL-10 gene expression within several hours of LPS challenge that is independent of both STAT-1 and IFN-γ. The

second phase is an active repression of IL-10 gene expression that is critically

dependent on STAT-1, yet most or all of which is independent of IFN-γ. Additionally,

we demonstrate that the STAT-1 regulation of IL-10 is tissue specific, and is an in vivo

only phenomenon, highlighting the need for such studies when analyzing complex

cytokine networks.

Monokines IL-1 IL-12 TNF-α LPS +

Inhibitory Pathway - IL-10

Type 2 cells, B cells Macrophage NK +

IFN-γ

Figure 1: LPS elicited cytokine production. In response to LPS, monocytes/macrophages release type 1 pro-inflammatory cytokines that activate NK cells and stimulate release of IFN-γ. IFN-γ provides positive feed-back on monocytes/macrophages, stimulating the release of additional pro-inflammatory cytokines. This pro-inflammatory cycle is negatively regulated in part by type 2 cytokines such as IL-10, which is produced by monocytes/macrophages as well as CD4+ type 2 cells.

Figure 2: The LPS signaling pathway. LPS signals through a complex signaling cascade that is initiated by its association with lipid binding protein (LBP), which in turn associates with CD14 and TLR4/MD2. MyD88 and TIRAP adaptor proteins consequently activate TRAF6, ultimately resulting in NF-kB activation and inflammatory cytokine gene transcription.

15 Figure 3: Interferon Signaling. In response to stimuli such as IFN-γ, STAT-1 becomes phosphorylated at tyrosine residue 701 (tyr701) and forms an active homodimer with another phosphorylated STAT protein. In the case of IFN-α/β, STAT-2 also becomes phosphorylated forms a heterodimer with STAT-1. These STAT-1/STAT-2 heterodimers further complex with IRF-9. Subsequent to dimerization, STAT complexes translocate to the nucleus where they bind recognition sequences and influence gene transcription.

16 MATERIALS AND METHODS

In vivo challenge with LPS

C57BL/6 WT and IFN-γ-/- mice were purchased from The Jackson Laboratory

(Bar Harbor, ME). C57BL/6 STAT-1-/- mice were provided by J. Durbin (Durbin et al.,

1996). All mice used were between 8-12 weeks of age, and experiments were conducted in accordance with institutional guidelines for animal care and use. Mice were administered 50µg LPS or PBS (Difco, Detroit, MI) by tail vein injection. Five mice at each time point (pre-LPS, 5 minutes, 15 minutes, 30 minutes, 1 hour, 3 hours,

16 hours, 24 hours, and 72 hours), had blood obtained by retro-orbital access, followed by RBC lysis, centrifugation and snap freeze in liquid nitrogen for RNA extraction.

Peritoneal cavity cells were harvested by peritoneal lavage with ice cold PBS, centrifuged, and snap frozen. Tissues indicated (liver, lung, spleen, kidney) were harvested, snap frozen, and pulverized for RNA extraction.

In vivo neutralization of IFN-α/β

For indicated experiments, IFN-γ-/- mice were administered 1x104 units of polyclonal anti-IFN-α/β (PBL Biomedical Laboratories) by I.P. injection 16 hours prior

to LPS challenge following the manufacturer's recommendations. Effective

neutralization of IFN-α/β was determined by RT-PCR on whole spleen RNA for

ISG54, a gene specific for IFN-α/β stimulation (Der et al., 1998). Primers for ISG54

were as follows in the 5’-3’ direction: F-ATGAAGCGTCAAGACAAGGC,

R-CATTCTTGATCCAGGAAGTGG. Standard PCR was performed with Taq

polymerase and buffer (PE Applied Biosystems, Foster City, CA) for 30 cycles at 95oC:

17 30 seconds, 62oC 1 minute, and 72oC 1 minute. RT-PCR in tissues from LPS-treated animals injected I.P. with a control antiserum revealed abundant ISG54 gene expression at 16 hours. No expression was observed in tissues of mice treated with LPS and I.P injection of anti-IFNα/β, indicating complete neutralization (data not shown).

E. coli infections

WT and STAT-1-/- mice were intravenously injected with either PBS or 108 WT

E. coli K-12 (strain MG1655 obtained from the E. coli Genetic Stock Center). Three mice per group at 16 hours post infection mice were sacrificed and serum was collected for IL-10 analysis.

Measurement of cytokine transcripts and protein

Reverse transcription of total RNA and real-time RT-PCR reactions were performed as previously described (Fehniger et al., 1999). Data were analyzed for threshold cycle number (CT) using Sequence Detector version 1.6 software (PE Applied

Biosystems, Foster City, CA). A normalized threshold cycle (NCT) was calculated for each sample by subtracting the internal 18s ribosomal RNA CT (VIC Dye) from the target cytokine CT (Joe Dye) (FAM CT – Joe CT = NCT). All data were compared to the time zero (pre-LPS) normalized threshold cycle T0NCT and a relative fold increase above baseline was calculated: (2^(NCT - T0NCT) = fold increase over baseline transcript expression.

The following real-time primer-probe sequences for cytokine transcripts were used: sequences are written in the 5’-3’ direction, and probes were labeled 5’ FAM,

3’TAMRA: IL-10 primers F-TTTGAATTCCCTGGGTGAGAA,

R-ACAGGGGAGAAATCGATGACA, and probe 18 TGAAGACCCTCAGGATGCGGCTG. TNF-α primers

F-CTGTCTACTGAACTTCGGGGTGAT, R-GGTCTGGGCCATAGAACTGATG, and probe ATGAGAAGTTCCCAAATGGCCTCCCTC. IL-12 primers

F-AGCTAACCATCTCCTGGTTTGC, R-CCACCTCTACAACATAAACGTCTTTC, and probe TGCTGGTGTCTCCACTCATGGCCA. IFN-γ primers

F-AGCAACAGCAAGGCGAAAA, R-CTGGACCTGTGGGTTGTTGA, and probe

CCTCAAACTTGGCAATACTCATGAATGCATCC. IL-15 primers

F-TCATATTGACACCACTTTATACACTGACA,

R-GCAATTCCAGGAGAAAGCAGTT, and probe CTTTCATCCCAGTTGCAAAGTTACTGCAATG.

Blood mononuclear cells were FACS sorted using anti-CD11b PE and anti-DX5 APC (BD Pharmingen, San Diego, CA). In situ RT-PCR was then performed on these cells as previously described (Nuovo et al., 1999), using the same primer sequences for IL-10 as shown above. Serum and in vitro supernatant IL-10 protein concentrations were analyzed by ELISA according to the manufacturer's instructions

(Endogen, Woburn, MA). ELISA sensitivity is ≥ 37pg/ml.

In vitro challenge with LPS

Whole bone marrow preparations were RBC lysed and plated into 6 well flat bottom plates at 2x10^6 cells/well in RPMI 1640 supplemented with 10% fetal calf serum, sodium pyruvate, non-essential amino acids, L-glutamine, and antibiotics/antimycotics (Gibco BRL). LPS was added to a concentration of 10µg/mL and supernatants were harvested at time points indicated.

19 Western blot and Active Motif ELISA

Protein lysates were prepared from whole blood leukocytes at indicated times

following in vivo LPS stimulation. Cells were washed once with PBS and lysed with

lysis buffer plus protease inhibitors supplied in the STAT Active MOTIF Kit (Active

Motif, Carlsbad, CA). Proteins were separated by 4-15% PAGE on a Biorad minigel

apparatus (Biorad, Hercules, CA) and transferred to nitrocellulose. Blots were probed with polyclonal anti-Phospho STAT-1 and reprobed with polyclonal anti-STAT1 (Cell

Signaling Technology, Beverly, MA). Blots were imaged with anti-rabbit HRP, ECL plus, and ECL Hyperfilm (Amersham Biosciences, Piscataway, NJ). Active motif

STAT ELISA was carried out according to the manufacturer's instructions with 10ug whole blood protein per well.

Chromatin immunoprecipitation assays

Anti-STAT1 ChIP assay was performed using the ChIP assay kit (Upstate

Biotechnology, Waltham, MA). Briefly, whole RBC lysed blood cells were crosslinked with formaldehyde for 15 minutes followed by addition of 0.125M glycine for 5 minutes to terminate the crosslinking process. Pelleted cells were washed with PBS and sonicated to produce DNA fragments 200-500bp in size. STAT-1-DNA complexes were immunoprecipitated by using anti-STAT-1 antibody (Cell Signaling Technology,

Beverly, MA). Precipitated DNA was amplified using primers encompasing a 147bp segment of the 5' flanking sequence of the IL-10 gene approximately 350bp upstream from the transcription start site. Primers were as follows in the 5'-3' direction:

F-CTCTCGGGGTTTCCTTTGGGTAA,

20 R-ATAATGACGTGGATAAATGGGCTATTCC. PCR with taq platinum (Invitrogen,

Carlsbad, CA) was performed under the following cycling conditions: 95oC 30 seconds,

55oC 30 seconds, 72oC 30 seconds. Products were separated by 2% agarose gel electrophoresis and visualized with ethidium bromide stain.

Statistical analysis

For the real-time PCR analysis, a two-way ANOVA (time, group, and time*group effects) model was fit to the data from blood. Multiple comparisons were performed to test for differences between WT, STAT-1-/-, and IFN-γ-/-mice at different time points. For serum IL-10 data, a one-way analysis of variance model was fit to the data. Multiple comparisons were performed to test for differences between the four groups (Dean and Voss). In each instance, the overall significance level was set to 0.05.

21 RESULTS

Real-time mapping of cytokine transcripts following LPS challenge

Quantitative real-time RT-PCR is a sensitive and accurate method for quantifying cytokine transcript (Fehniger et al., 1999). Our laboratory had initially investigated IFN-γ and its relationship to LPS toxicity (Fehniger et al., 2000), and so we

wished to determine the potential utility and analytical power of the quantitative real-

time RT-PCR technique in further determining the molecular events that occur during

bacterial sepsis in vivo. We thus used quantitative real-time RT-PCR to measure

changes in cytokine mRNA transcripts in wild type (wt, C57/BL6J) mice in response to

LPS challenge. Following IV injection with LPS (50µg), tissues (lung, liver, spleen,

kidney, white blood cells, and peritoneal cavity cells) were harvested, snap frozen in

liquid nitrogen, and total RNA was extracted and reverse transcribed for real-time PCR

analysis. Mean changes in transcript expression (5 mice/time point) above baseline

values (set as expression at time 0) were calculated and plotted to create a unique real-

time picture of in vivo cytokine expression changes at the organ level in response to

LPS

Strikingly, a vast heterogeneity of cytokine gene expression was observed

between tissues following LPS (Fig. 4-9). An early increase in pro-inflammatory

cytokine transcript (TNF-α and IL-12) in the spleen was followed at three hours post

challenge by a surge in IL-10 transcript in the spleen and white blood cells. Meanwhile,

pro-inflammatory transcript changes in liver and kidney (IL-12 and TNF-α) were much

more striking comparatively. In contrast, lung tissues showed a relatively short burst of

22 transcript activity followed by a decrease in cytokine gene expression for all 5

transcripts measured one hour after administration of LPS. Peritoneal cells (PEC) had

an early increase in IL-12 gene expression that was 3500 times higher, respectively,

than that measured before LPS administration one hour earlier. This was followed by a

24-fold increase in IFN-γ in these cells. Thus, each tissue has a distinct cytokine profile

following its encounter with LPS, which likely reflects quantitative and/or qualitative

differences in the cell types present in each specific tissue.

However, perhaps the most striking contrast observed was that measured

between white blood cells and PEC cells where the stromal and parenchymal elements

of organs likely have little or no role. In response to LPS, at three hours we observed

200-fold increase in monocyte-derived IL-10 predominated in peripheral WBCs, with

negligible change in the monocyte derived IL-12, while at nearly the same time (one

hour), a 1000-fold increase of IL-10 in PECs was dwarfed by a 3500-fold increase in

IL-12 (Fig. 8-9). Thus, despite the fact that both of these cytokines are largely produced

by cells of the monocyte lineage, the state of monocyte differentiation, their numbers

and location, as well as their degree of exposure to LPS all likely influence this heterogeneity of cytokine responsiveness to LPS. It should be noted that comparable profiles were obtained in these tissues when LPS was administered via the IV route as shown here, or the intraperitoneal (IP) route (data not shown).

Inherent in the striking heterogeneity of cytokine expression observed in each organ is the likelihood that serum protein does not reflect local cytokine expression.

Following LPS challenge, serum IL-10 protein levels in wt mice peaked at 1 hour, and returned to pre-challenge levels by 3 hours despite abundant transcript present in spleen 23 and liver at 3 hours. Additionally, serum TNF-α protein in wt mice peaked at 1 hour, while TNF-α transcript in the liver remained markedly elevated through 3 hours. This confirms that peak cytokine expression in each tissue did not necessarily correlate with

the protein measurements in serum even if an expected time-lapse between transcription

and translation is allowed for.

IL-10 Cytokine Expression in Wild type, STAT-1-/-, and IFN-γ-/- mice following

LPS challenge

In order to better understand the putative role of IFN-γ and STAT-1 signaling molecules in the control of IL-10 gene expression following LPS challenge in vivo we repeated the quantitative assessment in parallel with mice possessing a targeted disruption of the STAT-1 or IFN-γ genes. We observed that STAT-1-/- mice exhibit a significant dysregulation of IL-10 expression 12-24 hours after LPS administration without significant changes in the pro-inflammatory cytokine gene transcript profile.

However, the shift in this gene expression profile in the STAT-1-/- mice was organ specific, achieving statistically significant differences from the wt mouse profile in the lung, liver, and peripheral white blood cells, but not in the spleen or kidney. Graphical depictions of IL-10 expression in spleen, lung, and liver highlight that IL-10 expression was much greater and persists significantly longer in the lung (p<0.0001) and the liver

(p=0.0035) of STAT-1-/- mice compared to wt mice, however, there was no significant difference in IL-10 expression in the spleen or kidney (p>0.05). These results illustrate the in vivo role STAT-1 has in the regulation of IL-10 in response to LPS and

demonstrates that this effect is organ specific. The exact mechanism behind this tissue-

specific immune regulation is unclear. However, compartmental differences in immune 24 cytokines have been previously observed in the Biron laboratory when investigating

liver requirements for IL-18 during viral infection (Pien et al., 2000).

IL-10 has been shown in numerous reports to protect against lethal side cytokine

effects in model systems of bacterial shock by down-regulating pro-inflammatory

cytokine expression and release (Cusumano et al., 1996; Florquin et al., 1994; Marchant

et al., 1994; Rongione et al., 2000). Analysis of WBC IL-10 (Fig. 10A) shows that

IL-10 has at least two phases to its expression in WBCs following in vivo LPS.

Initially, there is an induction of IL-10 transcript by 1-3 hours in both WT and

STAT-1-/- mice without significant difference, indicating that this expression is STAT-1

independent in WT mice. However, 16 hours after in vivo LPS challenge, there is a

massive induction of IL-10 gene expression in the WBCs of STAT-1-/- mice when compared to WT mice (p<0.0001). This indicates that a second, delayed phase of IL-10 gene expression is actively repressed in a manner that is critically dependent on

STAT-1 mediated signaling in WT mice. Serum IL-10 protein concentration measured in STAT-1-/- and WT mice showed no significant difference at 1 or 3 hours. Serum

IL-10 protein concentration in WT animals remained low at 16 and 24 hours

(< 421 ± 43 pg/ml), while STAT-1-/- mice exhibited a second peak in serum IL-10 at 16 hours post LPS (16,270 ± 3,900 pg/ml), and measurable levels persisted for greater than

24 hours (6700 ± 2900 pg/ml) (Fig. 10B). Thus, the massive induction of IL-10 gene transcript noted at 16 hours in WBC of STAT-1-/- mice was also reflected at the protein level in serum with a 40-fold difference between STAT-1-/- and WT mice (p<0.0001),

This confirms the critical role that STAT-1 has in actively mediating repression of

IL-10 gene expression 16-24 hours after in vivo LPS challenge in WBC of WT mice.

25 In order to determine if STAT-1-/- mice also overproduce IL-10 in response to in vivo challenge with a live infection, we injected WT and STAT-1-/- mice with E. coli

K-12 and measured serum IL-10 protein. At 16 hours post infection, STAT-1-/- mice overproduced IL-10 protein (3601 ± 584 pg/ml) when compared to WT animals

(1140 ± 380 pg/ml, p < 0.05), confirming LPS challenge observations as relevant in an infectious setting.

IL-10 expression in IFN-α/β/γ deficient animals

In vitro studies suggest an important role for IFN-γ in the negative regulation of

IL-10 (Chomarat et al., 1993; Donnelly et al., 1995). IFN-γ is produced in response to

LPS in vivo and signals through STAT-1 (Chomarat et al., 1993; Donnelly et al., 1995;

Shuai et al., 1993). In order to determine if IFN-γ was involved in the STAT-1 mediated repression of IL-10 that we observed in vivo, we analyzed data from IFN-γ-/- mice challenged with LPS. Interestingly, there was no significant difference in WBC

IL-10 gene transcript between IFN-γ-/- and WT mice (Fig. 11A). At 16 hours post LPS challenge, serum IL-10 protein was only modestly elevated following LPS challenge in

IFN-γ-/- mice (2,330 ± 590 pg/ml) in contrast to STAT-1-/- mice (16,270 ± 3,900 pg/ml)

(Fig. 11B). Collectively, these data show, for the first time, that most or all of the

STAT-1 mediated active repression of delayed IL-10 gene expression seen in response to an in vivo challenge of LPS or E. coli in WT mice is independent of IFN-γ.

In addition to IFN-γ, type 1 IFN-α/β are produced in response to LPS in vivo

(Pluznik et al., 1989). IFN-β, in particular, has been demonstrated to phosphorylate

STAT-1 following LPS challenge in vitro (Toshchakov et al., 2002). To determine if 26 type 1 IFN-α/β signaling was responsible for STAT-1 mediated repression of IL-10

production at 16 hours post LPS in vivo, IFN-γ-/- mice were pretreated with antiserum known to completely neutralize IFN-α/β (see methods), and subsequently challenged with LPS (Fig. 11B). These mice had a significantly higher concentration of serum

IL-10 protein at 16 hours when compared to IFN γ-/- mice, indicating that type 1

IFN-α/β is in part responsible for the STAT-1 mediated repression of IL-10. However,

the mice produced significantly less serum IL-10 protein compared to STAT-1-/- mice, suggesting that the STAT-1 mediated repression of IL-10 gene expression is in part independent of IFN-α/β/γ signaling (p<0.0001 for the multiple comparison across groups).

Identification of the in vivo cellular source of IL-10 in STAT-1-/- mice

WBC from WT and STAT-1-/- mice show dramatic differences in IL-10 gene transcript 16 hours after in vivo LPS challenge (Fig. 10A). We used in situ RT-PCR on

cells sorted from fresh blood to determine which cell type(s) were responsible for the

observed difference. We sorted CD11bbright+DX5- cells from other blood mononuclear cells 16 hours after LPS challenge. CD11bbright+DX5- (monocytes) appear entirely responsible for the observed increases in blood IL-10 transcript, both in WT at 1 hour

(not shown) and STAT-1-/- mice at 16 hours (Fig. 12A, B).

Surprisingly, when we examined the liver tissues in which we observed IL-10 overproduction, we found that it was the blood monocytes, and not tissue macrophages, that appeared to be the source of IL-10 transcript (Fig. 12). This is in contrast to other in vivo studies suggesting a strong putative role for liver tissue macrophages (kupfer

27 cells) in IL-10 production following systemic bacterial exposure from cecal ligation and

puncture (Emmanuilidis et al., 2001). In addition to these seemingly conflicting results,

we also observed that while there were significant measurable increases in IL-10

transcript in spleen cells following LPS challenge, there was no significant differences

in the levels of IL-10 transcript between STAT-1-/- and WT spleen (Fig. 4). The virtually identical production of IL-10 in wild type and STAT-1-/- spleen following LPS challenge are in complete contrast with IL-10 production in white blood cells, as well as the systemic levels of cytokine in these mice. To identify which cell type may be making IL-10 in the spleen, we thus further performed in situ RT-PCR data from WT and STAT-1-/- spleen that indicated macrophages were the primary source of IL-10 in this tissue (data not shown). These unexpected results suggest that splenic macrophage

IL-10, while present, does not contribute significantly to systemic levels of IL-10 during a system infectious challenge, and that it is the blood monocytes which are the major source of this anti-inflammatory cytokine.

Assessment for an indirect mechanism by which STAT-1 mediates repression of

IL-10.

Our data showed that in vivo analysis of IL-10 gene expression following LPS stimulation demonstrated a role for STAT-1 in actively repressing systemic IL-10 protein production, and that this repression was occurring in blood monocytes. In first considering how STAT-1, an activator of transcription, could be repressing IL-10 gene expression in vivo, we made an assumption that this mechanism must be indirect, i.e.,

STAT-1 must activate a repressor that in turn silences IL-10 gene expression. We therefore first assessed two well-known mechanisms that could potentially be operative

28 under such circumstances:

SOCS and PIAS, as discussed in the introduction, are upregulated by

JAK/STAT pathway as well as NFkB, which is activated by LPS. These proteins

function as a feedback shutoff of cytokine signaling and are largely regulated

transcriptionally. Animals with deletions in these proteins generally fail to terminate

cytokine activation or production. We thus hypothesized that SOCS1 and or PIAS1,

both of which may interact with STAT1, may be differentially transcribed between WT

and STAT-1-/- animals and account for the prolonged production of IL-10 in response to

LPS challenge. We thus performed real-time PCR with primer probe sets for SOCS1 and PIAS1 on white blood cell cDNA from our original experiments; however, there were no significant differences in the transcript levels between WT and STAT-1-/- animals.

In addition to the activation of repressor proteins that feed-back to regulate cytokine production, it has been recently described that naïve T-cells can rapidly alter the methylation status of CpG motifs within their 5’ flanking sequence (demethylation), and that this change confers an increase in the transcription rate of IL-2 in memory cells

(Bruniquel and Schwartz, 2003). We thus hypothesized that in blood monocytes,

STAT-1 may be mediating changes (methylation) to CpG dinucleotides in the 5’ flanking sequence that resulted in a repression of IL-10 production. To test this hypothesis, we purified DNA from CD11b+ blood monocytes from WT and STAT-1-/- animals post LPS challenge and performed bisulfite sequencing to determine the methylation status of all but 2 CpG motifs within the first 1kb of the IL-10 transcription start site. Our results indicated that there were no differences in the methylation of IL-

29 10 CpG dinucleotides in WT and STAT-1-/- blood monocytes.

STAT-1 activation and physical association with the IL-10 gene

Without evidence for an indirect mechanism, we next considered that STAT-1 could mediate repression of IL-10 directly, i.e., with direct binding to the IL-10 promoter itself. We first examined STAT-1 phosphorylation by western blot in whole peripheral blood cells following in vivo LPS stimulation at 0, 1, and 16 hours. Fig. 13A shows that at both 1 and 16 hours, STAT-1 is tyrosine phosphorylated. We next assayed STAT-1 binding activity in lysates from these same animals using a STAT-1

ELISA. A strong positive signal was found in lysates from 1 and 16 hours, but not at 0 hours (data not shown), demonstrating that STAT-1 was phosphorylated and able to bind its DNA recognition sequence at these times following in vivo LPS stimulation.

Finally, we determined if STAT-1 was physically associating with the 5' flanking sequence of the IL-10 gene following in vivo LPS stimulation. Analysis of the

IL-10 5' flanking sequence for STAT consensus binding elements identified two closely spaced target sequences at -376 and -456. Primers encompassing this region of the

IL-10 5' flanking sequence were used to amplify STAT1 immunoprecipitated ChIP lysates. Our results demonstrate that STAT-1 associates with the IL-10 5' flanking region at 16 hours post LPS stimulation, but not at 1 hour or at rest (Fig 13B). These data provide indirect evidence that the STAT-1 mediated repression involves the direct recruitment of STAT-1 to the regulatory region of IL-10.

STAT-1 is known to recruit an abundance of co-activators to its binding elements, but little is known about recruitment of co-repressors. Data in other systems show that gene activation and gene silencing as induced by transcription factors can

30 result from a balance between recruitment of both co-activators and co-repressors by a

transcription factor (Milne et al., 2002; Nakamura et al., 2002; Sif et al., 2001).

Therefore we investigated the mechanism by which STAT-1 might accomplish this

repression by assessing for one co-repressor that is known to associate with STAT

proteins, HDAC1 (Nusinzon and Horvath, 2003), and by assessing for another well

characterized co-repressor not-previously known to associate with STAT-1, Brg1. We

thus performed ChIP analysis of blood cell lysates from WT and STAT-1-/- animals 16 hours post LPS challenge. Our results indicate that HDAC1 is present at very low levels in both STAT-1 and WT animals on the IL-10 promoter following LPS challenge, suggesting that histone deacetylation is not responsible for changes to IL-10 production. Further ChIP analysis of histone 3 lysine 9 acetylation, a known target for

HDAC1, demonstrated that histone 3 is acetylated in both groups of animals. In addition, Brg1 ChIP analysis suggests that Brg1 is not associated with the IL-10 promoter following LPS challenge.

In vitro regulation of IL-10 production With the inability to determine the exact mechanism by which STAT-1 mediated IL-10 gene repression in vivo, and an estimate that innumerable co-repressors could be associating with STAT-1 at the IL-10 promoter, we explored several in vitro model systems by which to further explore mechanism in a more efficient manner. We first needed to prove that our in vivo observation of STAT-1 mediated repression of

IL-10 could be reproduced in vitro. We therefore isolated WT and STAT-1-/- thioglycolate activated peritoneal macrophages, bone marrow derived macrophages, spleen cell macrophages, and fresh bone marrow cells. We stimulated these cultures in

31 the presence of 10µg LPS and determined IL-10 production at both the protein and

RNA level using identical time points as those studied in vivo. Figure 14 is an

experiment representative of each of these in vitro systems, demonstrating IL-10

production by WT and STAT-1-/- bone marrow cells. In contrast to in vivo stimulated animals, in all in vitro experiments, LPS-stimulated WT cells produced more IL-10 compared to STAT-1-/- cells. These data support our original hypothesis that in some instances, such as has been seen in this study, observations regarding gene regulation made in vitro do not necessarily provide any insight as to how such regulation is accomplished in vivo.

DISCUSSION

In the present study, we utilized quantitative real-time RT-PCR as a tool to study the WT cytokine response following infectious challenge in vivo. We assessed both pro- and anti-inflammatory cytokines in several organs following LPS challenge to better understand the degree of heterogeneity between their expression in different tissues in vivo. Our results indicate that in vivo, there are significant differences between tissues in both the timing and the magnitude of cytokine gene expression levels, as well as differences between tissue cytokine gene expression and serum protein levels. In turn, this implies that the morbidity and mortality which results from cytokine induced shock is likely secondary to a diverse series of organ-specific injuries mediated by a variety of cytokines, rather than any one or two cytokines that can be measured systemically in serum. The data lends insight into why the systemic administration of one or two cytokine antagonists to patients with shock has been met with limited success (Lauw et al., 2000).

We focused our investigation on the in vivo regulation of IL-10, an anti- inflammatory cytokine thought to regulate IFN-γ production and signaling following exposure to LPS (Ito et al., 1999; Marchant et al., 1994; Rennick et al., 1997). In WT and STAT-1-/- mice, we demonstrate that IL-10 gene transcript and protein production following LPS peaks within 1 hour and subsides within 3 hours, completely independent of STAT-1 signaling. However, at later time-points, STAT-1 becomes 33 critical for the normal repression of IL-10 in vivo, in that STAT-1-/- mice produce massive amounts of IL-10 gene transcript and protein in response to both LPS and live

E. coli challenge which is not seen in WT mice. In contrast to earlier in vitro studies

(Chomarat et al., 1993; Donnelly et al., 1995), this STAT-1 mediated repression of

IL-10 gene expression appears to occur with little or no dependence on IFN-γ, reinforcing the importance of studying such cytokine networks in vivo.

In vivo, we see monocytes, which are macrophage precursors, as the predominant source of massive IL-10 production in response to LPS or E. coli challenge in STAT-1-/- mice. In situ RT-PCR histology sections of liver demonstrate IL-10 production by blood monocytes, but surprisingly not by tissue kupfer cell macrophages, at 16 hours post LPS in both STAT-1-/- and WT animals (Fig. 13). There is also no significant difference in whole spleen IL-10 transcript between WT and STAT-1 knockout mice post LPS challenge, perhaps reflective of the paucity of monocytes in this tissue compared to the monocyte rich blood. It is likely that as the blood monocytes mature and become tissue macrophages that their regulation of IL-10 production is altered, as is observed in other lineages such as T-cells whose capacity to

produce cytokine changes as a result of differentiation (Ansel et al., 2003). These

changes are likely due to the milieu of transcription factors acquired and lost during

differentiation, as highlighted by experiments with cell cloning (Shi et al., 2003), as

well as epigenetic alterations that occur in cells as they mature (Ansel et al., 2003).

The true mechanism of this seemingly compartmental and differentiation

dependent regulation is unclear, but may be reflective of the different cellular

environments found in each organ and their interaction with each other. Our in vitro 34 experiments demonstrating less IL-10 produced by STAT-1 knockout tissue, a completely opposite effect than in vivo, highlights the critical importance of the tissue milieu in the normal regulation of cytokine production. Dr. Cristine Biron's laboratory has also reported the observation that the liver and spleen have differential requirements for IL-18 in an in vivo model of MCMV infection [Pien, 2000 #125]. Interestingly, it is the spleen in their infectious model that appears to be most influential in serum levels of

IFN-γ, whereas our experiments indicate that the lung and liver are critical contributors to serum IL-10. These results may mean that cytokine regulation in a systemic response to immune challenge results from a complex web of regulatory signals originating from multiple organs.

In an effort to further delineate which cytokines may contribute to the late

STAT-1-mediated repression of IL-10 in WT animals following LPS challenge, we

examined IL-10 production in IFN-γ-/- without and with neutralization of type 1

IFN-α/β. We demonstrate, for the first time, that most or all of the late STAT-1

mediated repression of IL-10 gene expression is independent of IFN-γ and that

significant yet partial repression of IL-10 results from type 1 IFN-α/β. Thus, additional

factors that signal via STAT-1 must participate in this repression, likely in coordination

with IFN-α/β.

One potential mechanism by which STAT-1 might normally mediate the

repression of IL-10 in monocytes could be via direct binding to the IL-10 promoter

either alone or in combination with other transcription factors that are activated upon

exposure to LPS. Work demonstrating a cooperative effect of STAT-1 and NF-kappa B

35 on iNOS regulation highlights this concept (Ganster et al., 2001). The

heterodimerization of STAT-1 with STAT-3 to mediate in vivo repression of IL-10

expression appears unlikely, as mice that lack STAT-3 in myeloid cells have

constitutive STAT-1 activation and are highly susceptible LPS-induced endotoxin

shock (Takeda et al., 1999), while our STAT-1-/- mice were very well protected compared to controls (not shown). An additional possibility is that STAT-1 is inhibiting IL-10 expression following LPS through the recruitment of additional repressor proteins. The growing body of work demonstrating the importance of chromatin remodeling in STAT mediated gene expression suggests that these proteins may have a role in IL-10 regulation by STAT1. Recent work demonstrating that

STAT-1 associates with HDAC1, and that addition of HDAC inhibitors augments

STAT-1 mediated gene expression strongly suggests this possibility (Nusinzon and

Horvath, 2003), however, our work suggests that HDAC1, at least, is not responsible for the repression of IL-10. Additional work to identify if transcriptional repressors may be recruited to the IL-10 promoter will be needed to clarify this hypothesis.

In addition to the in vivo work presented in this manuscript, we have extensively compared in vitro IL-10 production in response to LPS between WT and STAT-1-/- bone marrow derived macrophages, fresh bone marrow, thioglycolate derived macrophages, and splenic macrophages. At both the message and protein level,

STAT-1-/- cells consistently produced significantly less IL-10 compared to WT cells in response to LPS. The reason for the decreased production of IL-10 observed in

STAT-1-/- cells, when there is an overproduction in vivo, is unclear, but may be a result of the maturation/activation state of IL-10 producing cells in vitro as outlined above.

36 Additionally, there are likely inflammatory proteins and cell/cell contact present in vivo

that are not present in vitro which contribute to IL-10 regulation. These discrepancies

between our in vivo and in vitro observations highlight the importance of examining

cytokine regulation in vivo, at the tissue specific level.

In summary, our experimental approach for sequentially quantifying IL-10 gene expression in vivo following LPS or E. coli challenge using mice deficient in STAT-1 and IFN-α/β/γ has led to the novel discovery that the regulation of IL-10 following this challenge is at least biphasic. There is a STAT-1 independent induction of gene expression that occurs early, followed by a delayed STAT-1 dependent repression of gene expression, most or all of which is independent of IFN-γ. Further work is required to determine how this "activator of transcription" actually mediates repression of IL-10 gene expression. To our knowledge, this distinct pattern of IL-10 gene regulation has not been predicted by any previously published in vitro study, suggesting that assessment of cytokine networks might best occur by directed profiling of gene expression in vivo.

Figures 4-9. Quantitative real-time RT-PCR analysis of multiple tissue transcript

following LPS challenge in WT, STAT-1-/-, and IFN-γ-/- mice. 5 mice per group were injected with 50µg of LPS and sacrificed at indicated time points. Tissues were harvested for total RNA extraction followed by reverse transcription and real-time

RT-PCR for indicated cytokines. Fold increase in cytokine transcript was calculated from baseline expression set at time 0 (pre-LPS).

38 Figure 4: Spleen cytokine production post LPS

39 Figure 5: Liver cytokine production post LPS

40 Figure 6: Lung cytokine production post LPS

41 Figure 7: Kidney cytokine production post LPS

42 Figure 8: White blood cell cytokine production post LPS

43 Figure 9: Peritoneal cavity cell cytokine production post LPS

Figure 10. A. Quantitative real-time RT-PCR analysis of WBC IL-10 gene transcript

following LPS challenge in STAT-1-/- and WT mice. Mice were injected with 50µg of

LPS and 5 mice/group were sacrificed at each indicated time point. WBCs were harvested for total RNA extraction followed by reverse transcription and real-time PCR.

Fold increase in cytokine transcript was calculated from baseline expression set at time 0 (pre-LPS). At 16 and 24 hours, IL-10 gene transcript is significantly higher in

STAT-1-/- mice WBC compared to WT mice WBC (p< 0.0001). B. Comparison of

serum IL-10 protein concentration in STAT-1-/- and WT mice following LPS challenge.

Early serum IL-10 protein concentration peaks at 1 hour and subsides at 3 hours in both

WT and STAT-1-/- mice. At 16 hours, STAT-1-/- mice have a substantially higher serum IL-10 protein concentration that remains elevated above baseline for an extended period (>24 hours) of time compared to WT controls (* p< 0.0001). Results represent the average of 5 mice per group ± standard deviation.

45 Figure 10: IL-10 production in WT and STAT-1-/- animals

A STAT-1-/-

750 Wild Type

600

Transcript 450

300

150

0 Fold Change in IL-10

7 days 0 hour 1 hour 3 days 3 hours 16 hours 24 hours B

20000

15000

10000

5000 Serum IL-10 (pg/mL)

0 01 3 16 24

Time Post LPS (Hours)

Figure 11. A. Quantitative real-time RT-PCR analysis of WBC IL-10 gene transcript

following LPS challenge in WT, IFN-γ-/-, and STAT-1-/- mice. Mice were injected with

50µg of LPS and 5 mice/group were sacrificed at each indicated time point. Real-time

RT-PCR was used to determine fold increase over baseline in WBC IL-10 gene transcript. There was no significant difference in WBC IL-10 gene expression between

WT, IFN-γ-/-, and STAT-1-/- mice from time 0 (pre LPS) to 3 hours following LPS challenge. At 16 and 24 hours, there was no difference in IL-10 gene expression between WT and IFN-γ-/- mice, while STAT-1-/- mice had a substantially higher IL-10 gene expression compared to WT and IFN-γ-/- mice at 16 and 24 hours (p< 0.0001). B.

Comparison of serum IL-10 protein concentration in WT, IFN-γ-/-, IFN-γ-/- mice administered anti-IFN-α/β antiserum, and STAT-1-/- mice at 16 hours post LPS challenge. IFN-γ-/- mice show modest production of IL-10 16 hours after challenge with

LPS in vivo, while the additional neutralization of IFN-α/β in IFN-γ-/- mice substantially increased IL-10 production following LPS (p<0.0001 compared with IFN-γ-/- mice).

However, this complete neutralization of IFN-α/β/γ only partially increased IL-10 production compared to STAT-1-/- mice (p<0.0001), suggesting the STAT-1 mediated repression of IL-10 is in part independent of IFN-α/β/γ signaling.

47 Figure 11: IL-10 production in IFN deficient animals

A 700

STAT-1-/- pt 600 ri

sc Wild

n 500 a IFN-γ-/- Tr

0 400

300 in IL-1 ge

n 200 a h C 100 d l o F 0 3 days 7 days 0 hour 3 hours 24 hours 16 hours Time Post LPS B 25000

20000

(pg/mL) 15000

10000 Serum IL-10 5000

0 - - / b - -/ −/− γ γ α/ - IFN- IFN- STAT-1 Wild type Anti-IFN

Figure 12. In situ RT-PCR analysis of STAT-1-/- WBC IL-10 gene expression following LPS challenge. WBC from STAT-1-/- mice were obtained 16 hours after LPS challenge, sorted by flow cytometry using a mononuclear gate, monocyte (CD11b) and

NK cell (DX5) markers, and analyzed for IL-10 mRNA by in situ RT-PCR. CD11b- and CD11blow cells that were both positive and negative for DX5 (A) showed no IL-10 mRNA expression, while CD11bbright+DX5- cells (B) all expressed IL-10. These data are representative of 2 experiments and demonstrate that circulating blood monocytes are responsible for IL-10 gene expression in WBC following in vivo LPS challenge.

Liver sections from both WT and STAT-1-/- mice at 16 hours post LPS (C) demonstrated that IL-10 producing cells were restricted to cells in the vasculature, and not the tissue macrophages, or Kupfer cells.

49 Figure 12: In vivo source of IL-10 post LPS

CD11b

DX5

-/- low/negative -/- bright A: STAT-1 CD11b Cells B: STAT-1 CD11b Cells At 16 Hours Post LPS At 16 Hours Post LPS

-/- C: STAT-1 Liver Post LPS

IL-10

Figure 13. STAT-1 activation following in vivo LPS challenge. A. WT and STAT-1-/-

mice (STAT-1 as a negative control) were injected with 50ug of LPS and RBC lysed

WBC were obtained pre-LPS, 1, and 16 hours after LPS challenge. WBC were lysed for

whole protein and assayed for STAT-1 tyrosine phosphorylation by PAGE/western blot

analysis. STAT-1 is unphosphorylated in pre-LPS WBC of WT mice, but is activated

by 1 hour and remains phosphorylated at 16 hours post LPS challenge. B. WT and

STAT-1-/- were injected with 50ug of LPS and sacrificed at 16 hours post LPS challenge. RBC lysed WBC were subjected to formalin crosslinking and ChIP analysis with anti-STAT-1. ChIP analysis demonstrates that STAT-1 is associated with the

IL-10 5' flanking sequence at 16 hours post LPS challenge, but not at 1 hour or pre-LPS.

51 Figure 13: STAT-1 activation and association with IL-10

P-STAT1 Total STAT1

γ -/-

STAT-1 EL4 + IFN WT 0 hours WT 1 hours

WT 16 hours B

- s / - urs NA

D hour ic DNA 0 put STAT-1 In WT 1 hour Input DNA

WT WT 16 ho enom G

1400

1200 Wild Type STAT-1 KO 1000 (pg/mL)

800

entration 600

400 -10 Conc L I 200

0 16 hours 24 hours 48 hours Time post LPS challenge

Figure 14. Bone marrow IL-10 production during in vitro LPS challenge. WT and STAT-1-/- whole bone marrow was isolated and stimulated with 10µg/mL LPS. At times indicated, culture supernatant was harvested and assayed for IL-10 concentration by ELISA. At each time-point, WT bone marrow produced significantly higher amounts of IL-10 compared to STAT-1-/- bone marrow.

LITERATURE CITED

Aderem, A., and Underhill, D. M. (1999). Mechanisms of phagocytosis in macrophages. Annu Rev Immunol 17, 593-623.

Alexander, W. S., Starr, R., Fenner, J. E., Scott, C. L., Handman, E., Sprigg, N. S., Corbin, J. E., Cornish, A. L., Darwiche, R., Owczarek, C. M., et al. (1999). SOCS1 is a critical inhibitor of interferon gamma signaling and prevents the potentially fatal neonatal actions of this cytokine. Cell 98, 597-608.

Ansel, K. M., Lee, D. U., and Rao, A. (2003). An epigenetic view of helper T cell differentiation. Nat Immunol 4, 616-623.

Aravind, L., and Koonin, E. V. (2000). SAP - a putative DNA-binding motif involved in chromosomal organization. Trends Biochem Sci 25, 112-114.

Bach, E. A., Aguet, M., and Schreiber, R. D. (1997). The IFN gamma receptor: a paradigm for cytokine receptor signaling. Annu Rev Immunol 15, 563-591.

Benkhart, E. M., Siedlar, M., Wedel, A., Werner, T., and Ziegler-Heitbrock, H. W. (2000). Role of Stat3 in lipopolysaccharide-induced IL-10 gene expression. J Immunol 165, 1612-1617.

Brightbill, H. D., Plevy, S. E., Modlin, R. L., and Smale, S. T. (2000). A prominent role for Sp1 during lipopolysaccharide-mediated induction of the IL-10 promoter in macrophages. J Immunol 164, 1940-1951.

Brown, P. O., and Botstein, D. (1999). Exploring the new world of the genome with DNA microarrays. Nat Genet 21, 33-37.

54 Bruniquel, D., and Schwartz, R. H. (2003). Selective, stable demethylation of the interleukin-2 gene enhances transcription by an active process. Nat Immunol 4, 235- 240.

Bullen, D. V., Darwiche, R., Metcalf, D., Handman, E., and Alexander, W. S. (2001). Neutralization of interferon-gamma in neonatal SOCS1-/- mice prevents fatty degeneration of the liver but not subsequent fatal inflammatory disease. Immunology 104, 92-98.

Burns, K., Clatworthy, J., Martin, L., Martinon, F., Plumpton, C., Maschera, B., Lewis, A., Ray, K., Tschopp, J., and Volpe, F. (2000). Tollip, a new component of the IL-1RI pathway, links IRAK to the IL-1 receptor. Nat Cell Biol 2, 346-351.

Cao, Z., Henzel, W. J., and Gao, X. (1996a). IRAK: a kinase associated with the interleukin-1 receptor. Science 271, 1128-1131.

Cao, Z., Xiong, J., Takeuchi, M., Kurama, T., and Goeddel, D. V. (1996b). TRAF6 is a signal transducer for interleukin-1. Nature 383, 443-446.

Chambers, A. E., Banerjee, S., Chaplin, T., Dunne, J., Debernardi, S., Joel, S. P., and Young, B. D. (2003). Histone acetylation-mediated regulation of genes in leukaemic cells. Eur J Cancer 39, 1165-1175.

Cheung, P., Allis, C. D., and Sassone-Corsi, P. (2000). Signaling to chromatin through histone modifications. Cell 103, 263-271.

Chomarat, P., Rissoan, M. C., Banchereau, J., and Miossec, P. (1993). Interferon gamma inhibits interleukin 10 production by monocytes. J Exp Med 177, 523-527.

Chung, C. D., Liao, J., Liu, B., Rao, X., Jay, P., Berta, P., and Shuai, K. (1997). Specific inhibition of Stat3 signal transduction by PIAS3. Science 278, 1803-1805.

Cusumano, V., Genovese, F., Mancuso, G., Carbone, M., Fera, M. T., and Teti, G. (1996). Interleukin-10 protects neonatal mice from lethal group B streptococcal infection. Infect Immun 64, 2850-2852.

55 de Waal Malefyt, R., Abrams, J., Bennett, B., Figdor, C. G., and de Vries, J. E. (1991). Interleukin 10(IL-10) inhibits cytokine synthesis by human monocytes: an autoregulatory role of IL-10 produced by monocytes. J Exp Med 174, 1209-1220.

Dean, A., and Voss, D. (1999). Design and analysis of experiments (New York, Springer).

Deonarain, R., Alcami, A., Alexiou, M., Dallman, M. J., Gewert, D. R., and Porter, A. C. (2000). Impaired antiviral response and alpha/beta interferon induction in mice lacking beta interferon. J Virol 74, 3404-3409.

Der, S. D., Zhou, A., Williams, B. R. G., and Silverman, R. H. (1998). Identification of genes differentially regulated by interferon alpha , beta , or gamma using oligonucleotide arrays. PNAS 95, 15623-15628.

Donnelly, R. P., Freeman, S. L., and Hayes, M. P. (1995). Inhibition of IL-10 expression by IFN-gamma up-regulates transcription of TNF-alpha in human monocytes. J Immunol 155, 1420-1427.

Duggan, D. J., Bittner, M., Chen, Y., Meltzer, P., and Trent, J. M. (1999). Expression profiling using cDNA microarrays. Nat Genet 21, 10-14.

Durbin, J. E., Hackenmiller, R., Simon, M. C., and Levy, D. E. (1996). Targeted disruption of the mouse Stat1 gene results in compromised innate immunity to viral disease. Cell 84, 443-450.

Emmanuilidis, K., Weighardt, H., Maier, S., Gerauer, K., Fleischmann, T., Zheng, X. X., Hancock, W. W., Holzmann, B., and Heidecke, C. D. (2001). Critical role of Kupffer cell-derived IL-10 for host defense in septic peritonitis. J Immunol 167, 3919- 3927.

Ertel, W., Keel, M., Steckholzer, U., Ungethum, U., and Trentz, O. (1996). Interleukin- 10 attenuates the release of proinflammatory cytokines but depresses splenocyte functions in murine endotoxemia. Arch Surg 131, 51-56.

56 Fehniger, T. A., Shah, M. H., Turner, M. J., VanDeusen, J. B., Whitman, S. P., Cooper, M. A., Suzuki, K., Wechser, M., Goodsaid, F., and Caligiuri, M. A. (1999). Differential cytokine and chemokine gene expression by human NK cells following activation with IL-18 or IL-15 in combination with IL-12: implications for the innate immune response. J Immunol 162, 4511-4520.

Fehniger, T. A., Yu, H., Cooper, M. A., Suzuki, K., Shah, M. H., and Caligiuri, M. A. (2000). Cutting edge: IL-15 costimulates the generalized Shwartzman reaction and innate immune IFN-gamma production in vivo. J Immunol 164, 1643-1647.

Fiorentino, D. F., Bond, M. W., and Mosmann, T. R. (1989). Two types of mouse T helper cell. IV. Th2 clones secrete a factor that inhibits cytokine production by Th1 clones. J Exp Med 170, 2081-2095.

Fiorentino, D. F., Zlotnik, A., Mosmann, T. R., Howard, M., and O'Garra, A. (1991). IL-10 inhibits cytokine production by activated macrophages. J Immunol 147, 3815- 3822.

Florquin, S., Amraoui, Z., Abramowicz, D., and Goldman, M. (1994). Systemic release and protective role of IL-10 in staphylococcal enterotoxin B-induced shock in mice. J Immunol 153, 2618-2623.

Ganster, R. W., Taylor, B. S., Shao, L., and Geller, D. A. (2001). Complex regulation of human inducible nitric oxide synthase gene transcription by Stat 1 and NF-kappa B. Proc Natl Acad Sci U S A 98, 8638-8643.

Hacker, H. (2000). Signal transduction pathways activated by CpG-DNA. Curr Top Microbiol Immunol 247, 77-92.

Horng, T., Barton, G. M., Flavell, R. A., and Medzhitov, R. (2002). The adaptor molecule TIRAP provides signalling specificity for Toll-like receptors. Nature 420, 329-333.

Horng, T., Barton, G. M., and Medzhitov, R. (2001). TIRAP: an adapter molecule in the Toll signaling pathway. Nat Immunol 2, 835-841.

Horvath, C. M., Wen, Z., and Darnell, J. E., Jr. (1995). A STAT protein domain that determines DNA sequence recognition suggests a novel DNA-binding domain. Genes Dev 9, 984-994. 57 Howard, M., Muchamuel, T., Andrade, S., and Menon, S. (1993). Interleukin 10 protects mice from lethal endotoxemia. J Exp Med 177, 1205-1208.

Ito, S., Ansari, P., Sakatsume, M., Dickensheets, H., Vazquez, N., Donnelly, R. P., Larner, A. C., and Finbloom, D. S. (1999). Interleukin-10 inhibits expression of both interferon alpha- and interferon gamma- induced genes by suppressing tyrosine phosphorylation of STAT1. Blood 93, 1456-1463.

Jouanguy, E., Doffinger, R., Dupuis, S., Pallier, A., Altare, F., and Casanova, J. L. (1999). IL-12 and IFN-gamma in host defense against mycobacteria and salmonella in mice and men. Curr Opin Immunol 11, 346-351.

Kamizono, S., Hanada, T., Yasukawa, H., Minoguchi, S., Kato, R., Minoguchi, M., Hattori, K., Hatakeyama, S., Yada, M., Morita, S., et al. (2001). The SOCS Box of SOCS-1 Accelerates Ubiquitin-dependent Proteolysis of TEL-JAK2. J Biol Chem 276, 12530-12538.

Kawai, T., Adachi, O., Ogawa, T., Takeda, K., and Akira, S. (1999). Unresponsiveness of MyD88-deficient mice to endotoxin. Immunity 11, 115-122.

Khan, K. D., Shuai, K., Lindwall, G., Maher, S. E., Darnell, J. E., Jr., and Bothwell, A. L. (1993). Induction of the Ly-6A/E gene by interferon alpha/beta and gamma requires a DNA element to which a tyrosine-phosphorylated 91-kDa protein binds. Proc Natl Acad Sci U S A 90, 6806-6810.

Kimura, T., Kadokawa, Y., Harada, H., Matsumoto, M., Sato, M., Kashiwazaki, Y., Tarutani, M., Tan, R. S., Takasugi, T., Matsuyama, T., et al. (1996). Essential and non- redundant roles of p48 (ISGF3 gamma) and IRF-1 in both type I and type II interferon responses, as revealed by gene targeting studies. Genes Cells 1, 115-124.

Lauw, F. N., Pajkrt, D., Hack, C. E., Kurimoto, M., van Deventer, S. J., and van Der Poll, T. (2000). Proinflammatory Effects of IL-10 During Human Endotoxemia. J Immunol 165, 2783-2789.

Li, Y., Sassano, A., Majchrzak, B., Deb, D. K., Levy, D. E., Gaestel, M., Nebreda, A. R., Fish, E. N., and Platanias, L. C. (2004). Role of p38alpha Map kinase in Type I interferon signaling. J Biol Chem 279, 970-979.

58 Liao, J., Fu, Y., and Shuai, K. (2000). Distinct roles of the NH2- and COOH-terminal domains of the protein inhibitor of activated signal transducer and activator of transcription (STAT) 1 (PIAS1) in cytokine-induced PIAS1-Stat1 interaction. Proc Natl Acad Sci U S A 97, 5267-5272.

Liu, B., Gross, M., ten Hoeve, J., and Shuai, K. (2001). A transcriptional corepressor of Stat1 with an essential LXXLL signature motif. Proc Natl Acad Sci U S A 98, 3203- 3207.

Liu, B., Liao, J., Rao, X., Kushner, S. A., Chung, C. D., Chang, D. D., and Shuai, K. (1998). Inhibition of Stat1-mediated gene activation by PIAS1. Proc Natl Acad Sci U S A 95, 10626-10631.

Long, J., Matsuura, I., He, D., Wang, G., Shuai, K., and Liu, F. (2003). Repression of Smad transcriptional activity by PIASy, an inhibitor of activated STAT. Proc Natl Acad Sci U S A 100, 9791-9796.

Luger, K., Mader, A. W., Richmond, R. K., Sargent, D. F., and Richmond, T. J. (1997). Crystal structure of the nucleosome core particle at 2.8 A resolution. Nature 389, 251- 260.

Marchant, A., Bruyns, C., Vandenabeele, P., Ducarme, M., Gerard, C., Delvaux, A., De Groote, D., Abramowicz, D., Velu, T., and Goldman, M. (1994). Interleukin-10 controls interferon-gamma and tumor necrosis factor production during experimental endotoxemia. Eur J Immunol 24, 1167-1171.

Martin, G. S., Mannino, D. M., Eaton, S., and Moss, M. (2003). The epidemiology of sepsis in the United States from 1979 through 2000. N Engl J Med 348, 1546-1554.

Medzhitov, R., Preston-Hurlburt, P., and Janeway, C. A., Jr. (1997). A human homologue of the Drosophila Toll protein signals activation of adaptive immunity. Nature 388, 394-397.

Milne, T. A., Briggs, S. D., Brock, H. W., Martin, M. E., Gibbs, D., Allis, C. D., and Hess, J. L. (2002). MLL targets SET domain methyltransferase activity to Hox gene promoters. Mol Cell 10, 1107-1117.

59 Mogensen, K. E., Lewerenz, M., Reboul, J., Lutfalla, G., and Uze, G. (1999). The type I interferon receptor: structure, function, and evolution of a family business. J Interferon Cytokine Res 19, 1069-1098.

Moilanen, A. M., Karvonen, U., Poukka, H., Yan, W., Toppari, J., Janne, O. A., and Palvimo, J. J. (1999). A testis-specific androgen receptor coregulator that belongs to a novel family of nuclear proteins. J Biol Chem 274, 3700-3704.

Mowen, K. A., Tang, J., Zhu, W., Schurter, B. T., Shuai, K., Herschman, H. R., and David, M. (2001). Arginine methylation of STAT1 modulates IFNalpha/beta-induced transcription. Cell 104, 731-741.

Nair, J. S., DaFonseca, C. J., Tjernberg, A., Sun, W., Darnell, J. E., Jr., Chait, B. T., and Zhang, J. J. (2002). Requirement of Ca2+ and CaMKII for Stat1 Ser-727 phosphorylation in response to IFN-gamma. Proc Natl Acad Sci U S A 99, 5971-5976.

Nakamura, T., Mori, T., Tada, S., Krajewski, W., Rozovskaia, T., Wassell, R., Dubois, G., Mazo, A., Croce, C. M., and Canaani, E. (2002). ALL-1 is a histone methyltransferase that assembles a supercomplex of proteins involved in transcriptional regulation. Mol Cell 10, 1119-1128.

Nuovo, G. J., Plaia, T. W., Belinsky, S. A., Baylin, S. B., and Herman, J. G. (1999). In situ detection of the hypermethylation-induced inactivation of the p16 gene as an early event in oncogenesis. Proc Natl Acad Sci U S A 96, 12754-12759.

Nusinzon, I., and Horvath, C. M. (2003). Interferon-stimulated transcription and innate antiviral immunity require deacetylase activity and histone deacetylase 1. Proc Natl Acad Sci U S A 100, 14742-14747. Epub 12003 Nov 14725.

Paulson, M., Press, C., Smith, E., Tanese, N., and Levy, D. E. (2002). IFN-Stimulated transcription through a TBP-free acetyltransferase complex escapes viral shutoff. Nat Cell Biol 4, 140-147.

Pestka, S., Langer, J. A., Zoon, K. C., and Samuel, C. E. (1987). Interferons and their actions. Annu Rev Biochem 56, 727-777.

Pien, G. C., Satoskar, A. R., Takeda, K., Akira, S., and Biron, C. A. (2000). Cutting edge: selective IL-18 requirements for induction of compartmental IFN-gamma responses during viral infection [In Process Citation]. J Immunol 165, 4787-4791. 60 Pluznik, D. H., Frappier, N., and Nordan, R. P. (1989). Interleukin 6 (interferon beta 2) and interferon alpha/beta present in postendotoxin serum induce differentiation of murine M1 myeloid leukemia cells. Exp Hematol 17, 1063-1066.

Powell, M. J., Thompson, S. A., Tone, Y., Waldmann, H., and Tone, M. (2000). Posttranscriptional regulation of IL-10 gene expression through sequences in the 3'- untranslated region. J Immunol 165, 292-296.

Qureshi, S. A., Leung, S., Kerr, I. M., Stark, G. R., and Darnell, J. E., Jr. (1996). Function of Stat2 protein in transcriptional activation by alpha interferon. Mol Cell Biol 16, 288-293.

Reichhardt, T. (1999). It's sink or swim as a tidal wave of data approaches [news] [see comments]. Nature 399, 517-520.

Rennick, D. M., Fort, M. M., and Davidson, N. J. (1997). Studies with IL-10-/- mice: an overview. J Leukoc Biol 61, 389-396.

Rongione, A. J., Kusske, A. M., Kwan, K., Ashley, S. W., Reber, H. A., and McFadden, D. W. (2000). Interleukin-10 protects against lethality of intra-abdominal infection and sepsis. J Gastrointest Surg 4, 70-76.

Roth, S. Y., Denu, J. M., and Allis, C. D. (2001). Histone acetyltransferases. Annu Rev Biochem 70, 81-120.

Sasaki, A., Yasukawa, H., Suzuki, A., Kamizono, S., Syoda, T., Kinjyo, I., Sasaki, M., Johnston, J. A., and Yoshimura, A. (1999). Cytokine-inducible SH2 protein-3 (CIS3/SOCS3) inhibits Janus tyrosine kinase by binding through the N-terminal kinase inhibitory region as well as SH2 domain. Genes Cells 4, 339-351.

Schumann, R. R., Leong, S. R., Flaggs, G. W., Gray, P. W., Wright, S. D., Mathison, J. C., Tobias, P. S., and Ulevitch, R. J. (1990). Structure and function of lipopolysaccharide binding protein. Science 249, 1429-1431.

Sen, R., and Baltimore, D. (1986). Inducibility of kappa immunoglobulin enhancer- binding protein Nf-kappa B by a posttranslational mechanism. Cell 47, 921-928.

61 Sewnath, M. E., Olszyna, D. P., Birjmohun, R., ten Kate, F. J. W., Gouma, D. J., and van der Poll, T. (2001). IL-10-deficient mice demonstrate multiple organ failure and increased mortality during escherichia coli peritonitis despite an accelerated bacterial clearance. J Immunol 166, 6323-6331.

Shi, W., Zakhartchenko, V., and Wolf, E. (2003). Epigenetic reprogramming in mammalian nuclear transfer. Differentiation 71, 91-113.

Shimazu, R., Akashi, S., Ogata, H., Nagai, Y., Fukudome, K., Miyake, K., and Kimoto, M. (1999). MD-2, a Molecule that Confers Lipopolysaccharide Responsiveness on Toll- like Receptor 4 J Exp Med 189, 1777-1782.

Shuai, K. (2000). Modulation of STAT signaling by STAT-interacting proteins. Oncogene 19, 2638-2644.

Shuai, K., Horvath, C. M., Huang, L. H., Qureshi, S. A., Cowburn, D., and Darnell, J. E., Jr. (1994). Interferon activation of the transcription factor Stat91 involves dimerization through SH2-phosphotyrosyl peptide interactions. Cell 76, 821-828.

Shuai, K., Stark, G. R., Kerr, I. M., and Darnell, J. E., Jr. (1993). A single phosphotyrosine residue of Stat91 required for gene activation by interferon-gamma. Science 261, 1744-1746.

Sif, S., Saurin, A. J., Imbalzano, A. N., and Kingston, R. E. (2001). Purification and characterization of mSin3A-containing Brg1 and hBrm chromatin remodeling complexes. Genes Dev 15, 603-618.

Silvennoinen, O., Ihle, J. N., Schlessinger, J., and Levy, D. E. (1993). Interferon- induced nuclear signalling by Jak protein tyrosine kinases. Nature 366, 583-585.

Starr, R., Metcalf, D., Elefanty, A. G., Brysha, M., Willson, T. A., Nicola, N. A., Hilton, D. J., and Alexander, W. S. (1998). Liver degeneration and lymphoid deficiencies in mice lacking suppressor of cytokine signaling-1. Proc Natl Acad Sci U S A 95, 14395-14399.

Takeda, K., Clausen, B. E., Kaisho, T., Tsujimura, T., Terada, N., Forster, I., and Akira, S. (1999). Enhanced Th1 activity and development of chronic enterocolitis in mice devoid of Stat3 in macrophages and neutrophils. Immunity 10, 39-49.

62 Takeuchi, O., Takeda, K., Hoshino, K., Adachi, O., Ogawa, T., and Akira, S. (2000). Cellular responses to bacterial cell wall components are mediated through MyD88- dependent signaling cascades. Int Immunol 12, 113-117.

Tobias, P. S., Soldau, K., Gegner, J. A., Mintz, D., and Ulevitch, R. J. (1995). Lipopolysaccharide Binding Protein-mediated Complexation of Lipopolysaccharide with Soluble CD14. J Biol Chem 270, 10482-10488.

Tone, M., Powell, M. J., Tone, Y., Thompson, S. A., and Waldmann, H. (2000). IL-10 gene expression is controlled by the transcription factors Sp1 and Sp3. J Immunol 165, 286-291.

Toshchakov, V., Jones, B. W., Perera, P. Y., Thomas, K., Cody, M. J., Zhang, S., Williams, B. R., Major, J., Hamilton, T. A., Fenton, M. J., and Vogel, S. N. (2002). TLR4, but not TLR2, mediates IFN-beta-induced STAT1alpha/beta-dependent gene expression in macrophages. Nat Immunol 3, 392-398.

Trinchieri, G. (1989). Biology of natural killer cells. Adv Immunol 47, 187-376. van den Broek, M. F., Muller, U., Huang, S., Zinkernagel, R. M., and Aguet, M. (1995). Immune defence in mice lacking type I and/or type II interferon receptors. Immunol Rev 148, 5-18. van der Poll, T., and van Deventer, S. J. (1999). Cytokines and anticytokines in the pathogenesis of sepsis. Infect Dis Clin North Am 13, 413-426, ix.

Varinou, L., Ramsauer, K., Karaghiosoff, M., Kolbe, T., Pfeffer, K., Muller, M., and Decker, T. (2003). Phosphorylation of the Stat1 transactivation domain is required for full-fledged IFN-gamma-dependent innate immunity. Immunity 19, 793-802.

Weinstein, S., Sanghera, J., Lemke, K., DeFranco, A., and Pelech, S. (1992). Bacterial lipopolysaccharide induces tyrosine phosphorylation and activation of mitogen- activated protein kinases in macrophages. J Biol Chem 267, 14955-14962.

Wen, Z., Zhong, Z., and Darnell, J. E., Jr. (1995). Maximal activation of transcription by Stat1 and Stat3 requires both tyrosine and serine phosphorylation. Cell 82, 241-250.

63 Wible, B. A., Wang, L., Kuryshev, Y. A., Basu, A., Haldar, S., and Brown, A. M. (2002). Increased K+ efflux and apoptosis induced by the potassium channel modulatory protein KChAP/PIAS3beta in prostate cancer cells. J Biol Chem 277, 17852-17862.

Wright, S. D., Ramos, R. A., Tobias, P. S., Ulevitch, R. J., and Mathison, J. C. (1990). CD14, a receptor for complexes of lipopolysaccharide (LPS) and LPS binding protein. Science 249, 1431-1433.

Yamamoto, M., Sato, S., Hemmi, H., Hoshino, K., Kaisho, T., Sanjo, H., Takeuchi, O., Sugiyama, M., Okabe, M., Takeda, K., and Akira, S. (2003). Role of adaptor TRIF in the MyD88-independent toll-like receptor signaling pathway. Science 301, 640-643.

Yasukawa, H., Misawa, H., Sakamoto, H., Masuhara, M., Sasaki, A., Wakioka, T., Ohtsuka, S., Imaizumi, T., Matsuda, T., Ihle, J. N., and Yoshimura, A. (1999). The JAK-binding protein JAB inhibits Janus tyrosine kinase activity through binding in the activation loop. Embo J 18, 1309-1320.

Yasukawa, H., Ohishi, M., Mori, H., Murakami, M., Chinen, T., Aki, D., Hanada, T., Takeda, K., Akira, S., Hoshijima, M., et al. (2003). IL-6 induces an anti-inflammatory response in the absence of SOCS3 in macrophages. Nat Immunol 4, 551-556.

Yasukawa, H., Sasaki, A., and Yoshimura, A. (2000). Negative regulation of cytokine signaling pathways. Annu Rev Immunol 18, 143-164.

Yoshimura, A., Ohkubo, T., Kiguchi, T., Jenkins, N. A., Gilbert, D. J., Copeland, N. G., Hara, T., and Miyajima, A. (1995). A novel cytokine-inducible gene CIS encodes an SH2-containing protein that binds to tyrosine-phosphorylated interleukin 3 and erythropoietin receptors. Embo J 14, 2816-2826.

Zhang, G., and Ghosh, S. (2002). Negative regulation of toll-like receptor-mediated signaling by Tollip. J Biol Chem 277, 7059-7065.