The Pennsylvania State University

The Graduate School

College of Agricultural Sciences

GENOMIC AND IMMUNOLOGICAL APPROACHES TO CONTROL GRAM-

NEGATIVE INTRAMAMMARY INFECTIONS IN DAIRY CATTLE

A Thesis in

Animal Science

by

Annapoorani Chockalingam

© 2006 Annapoorani Chockalingam

Submitted in Partial Fulfillment of the Requirements for the Degree of

Doctor of Philosophy

May 2006

The thesis of Annapoorani Chockalingam was reviewed and approved* by the following:

Cindy E. McKinney Assistant Professor of Transgenic Biology Thesis Advisor Co-Chair of Committee

Douglas D. Bannerman Research Scientist, BFGL-ANRI, BARC, USDA-ARS Co-Chair of Committee

Guy F. Barbato Associate Professor of Poultry Science

Kenneth M. Weiss Evan Pugh Professor of Anthropology and Genetics

Eric T. Harvill Assistant Professor of Veterinary Science

Robert F. Paulson Associate Professor of Veterinary Science

Terry D. Etherton Distinguished Professor of Animal Nutrition Head of the Department of Dairy and Animal Science

*Signatures are on file in the Graduate School

iii ABSTRACT

The incidence of mastitis due to Gram-negative bacteria continues to impact the dairy industry due to the ubiquitous nature of the pathogens. Gram-negative bacteria account for nearly 40% of clinical mastitis cases resulting in an estimated loss to the U.S. dairy industry of $800 million per year. The research presented here focuses on host- mediated genetic and immunological factors involved in Gram-negative bacteria induced mastitis during the early phases of disease onset. Array analysis of mammary gland gene expression in a global context in response to E. coli is currently unavailable. A mouse mastitis model was used to study the transcriptional response in the mammary gland. This study identified potential candidate genes for susceptibility to bovine mastitis. We identified bactericidal/permeability increasing protein (BPI) as a potential candidate gene for susceptibility to Gram-negative infections. Ten single nucleotide polymorphisms

(SNPs) were identified within the BPI gene sequence encoding for the N-terminal region of the mature protein that exhibits bactericidal and LPS-neutralizing activity. A polymorphism located at +61 (G/A) resulted in a non-synonymous amino acid substitution from glycine to serine. No significant association was found between the identified SNP-marker allele and their haplotypes with SCS for a sample size of eighty- five Holstein dairy bulls.

Current therapeutic and prophylactic measures have marginal efficacy against mastitis. The potency of human and bovine BPI-derived synthetic peptides was evaluated for its bactericidal and LPS-neutralizing activity in biological fluids from the bovine. In this study, a 24 amino acid (aa) sequence synthetic peptide of human (hBPIpep) and

iv bovine BPI (bBPIpep) corresponding to domains 90-99 and 148-161 of both human and bovine mature BPI protein was found to exhibit 100% LPS-neutralizing activity at 100

µg/mL concentration. Complete bactericidal activity against E. coli was demonstrated in broth, serum and whey. However, only bacterial inhibitory activity was recorded in milk at the highest concentration tested (2 mg/mL). In the presence of EDTA (16mM concentration), a chelator of divalent cations, the hBPIpep exhibited complete bactericidal

activity at the lowest concentration tested (10µg/mL). The other two bovine BPI peptides

corresponding to amino acid 65-99 (bBPIpep-II) and 142-169 (bBPIpep-III) did not have any

bactericidal activity. However, bBPIpep-III exhibited LPS-neutralizing activity equivalent

to polymixin-B (concentration ≥ 30 µg/mL). The human and bovine BPI peptides were

tested for their minimum inhibitory concentration (MIC) and minimum bactericidal

concentration (MBC) against clinical isolates of major Gram-negative mastitis pathogens.

The innate immune response to Pseudomonas aeruginosa was studied to determine

whether the induction pattern to different Gram-negative bacteria is conserved in bovine

mammary gland immunity. We show that the cytokine pattern induced by P. aeruginosa

and E. coli are conserved with respect to systemic and local innate immune responses.

v TABLE OF CONTENTS

LIST OF FIGURES ...... vii

LIST OF TABLES...... ix

ACKNOWLEDGMENTS ...... xii

Chapter 1 INTRODUCTION...... 1

REFERENCES ...... 22

Chapter 2 A MICROARRAY SCREEN FOR IDENTIFICATION OF POTENTIAL CANDIDATE GENES FOR GRAM-NEGATIVE INTRAMAMMARY PATHOGENESIS IN A MOUSE MASTITIS MODEL ...... 32

REFERENCES ...... 50

Chapter 3 SINGLE NUCLEOTIDE POLYMORPHISMS AND HAPLOTYPES WITHIN THE BOVINE BACTERICIDAL/PERMEABILITY-INCREASING PROTEIN: A CANDIDATE GENE FOR MASTITIS ...... 52

REFERENCES ...... 68

Chapter 4 EFFICACY OF HUMAN BACTERICIDAL/PERMEABILITY- INCREASING PROTEIN DERIVED PEPTIDE AGAINST MAJOR GRAM- NEGATIVE MASTITIS PATHOGENS ...... 72

REFERENCES ...... 93

Chapter 5 EFFICACY OF BOVINE BACTERICIDAL/PERMEABILITY- INCREASING PROTEIN DERIVED PEPTIDE AGAINST MAJOR GRAM- NEGATIVE MASTITIS PATHOGENS ...... 97

REFERENCES ...... 120

vi

Chapter 6 THE BOVINE INNATE IMMUNE RESPONSE DURING EXPERIMENTALLY INDUCED Pseudomonas aeruginosa AND Escherichia coli MASTITIS ...... 125

REFERENCES ...... 157

Chapter 7 SUMMARY AND FUTURE DIRECTIONS ...... 163

APPENDIX ...... 167

vii LIST OF FIGURES

Chapter 1 Figures:

Figure 1: Schematic representation of bovine mammary gland. 3

Figure 2A: Cross section of cow udder from an uninfected quarter. 5

Figure 2B: Cross section of cow udder 72 hour post-infection with E. coli. 5

Chapter 2 Figures:

Figure 1: Cross section of murine mammary gland (A) Saline Infused (B & C) E. coli treated. 40

Figure 2A: Density plot: Perfect match and mismatch probes for 22,690 genes. 42

Figure 2B: Box plot: Perfect match and mismatch probes for 22,690 genes. 42

Figure 3: Differentially expressed genes of unknown function co-expressed with genes of known function with gene node correlation r = 0.92. 46

Chapter 3 Figures:

Figure 1: Chromatogram of bBPI gene Exon 1 sequenced with reverse primer. 59

Figure 2A: SignalP prediction of signal peptide sequence for glycine at position +21. 62

Figure 2B: SignalP prediction of signal peptide sequence for serine at position +21. 62

Chapter 4 Figures:

Figure 1: Bactericidal activity of human BPI synthetic peptide hBPIpep in milk in the presence of EDTA. 84

Figure 2: Percent inhibition of purified LPS by human BPI derived synthetic peptide. 86

Chapter 5 Figures:

Figure1: Percent inhibition of purified LPS by bovine BPI derived synthetic peptides. 112

viii

Chapter 6 Figures:

Figure 1: Bacterial growth of P. aeruginosa and E. coli following experimental challenge. 136

Figure 2: Effect of P. aeruginosa intramammary infection on systemic response. 138

Figure 3: Effect of bacterial infection on milk somatic cell counts (SCC). 140

Figure 4: Effect of intramammary bacterial infection on mammary vascular permeability. 141

Figure 5: Effect of intramammary infection on complement activation and pro- inflammatory cytokine levels in milk. 143

Figure 6: Effect of intramammary infection with E. coli on TNF-α and IL-8 levels in milk. 145

Figure 7: Effect of P. aeruginosa infection on anti-inflammatory cytokine levels in milk. 147

Figure 8: Effect of E. coli infection on anti-inflammatory cytokine levels in milk. 148

Figure 9: Intramammary challenge with P. aeruginosa increases milk levels of sCD14 and LBP. 149

ix LIST OF TABLES

Chapter 1 Tables:

Table 1. Quantitative trait loci for mastitis and somatic cell score (SCC). 9

Table 2. Major cytokines: their sources and functions. 12

Table 3. List of antibiotics approved for mastitis treatment in dairy cattle. 20

Chapter 2 Tables:

Table 1.List of differentially expressed genes between uninfected and E. coli infected mammary tissue classified on their molecular function in the disease process. 43

Table 2. Validation of differentially expressed immune related candidate genes for mastitis by Q-PCR 45

Chapter 3 Tables:

Table 1. Forward and reverse primer sequence and product size for the five exons of bovine BPI gene. 57

Table 2. Single nucleotide polymorphisms identified within the bovine BPI gene. 59

Table 3. Estimated bBPI haplotype frequencies for SNPs for BPI gene in Holstein dairy breed. 60

Chapter 4 Tables:

Table 1. Antimicrobial activity of hBPIpep synthetic peptide. 82

Table 2. MIC and MBC values of hBPIpep against clinical isolates of major Gram- negative mastitis pathogens. 85

Chapter 5 Tables:

Table 1. Antimicrobial activity of bBPIpep-I synthetic peptide. 107

Table 2. Antimicrobial activity of bBPIpep-II synthetic peptide. 108

Table 3. Antimicrobial activity of bBPIpep-III synthetic peptide. 109

x

Table 4. MIC and MBC values of bBPIpeps against clinical isolates of major Gram- negative mastitis pathogens. 111

xi

I dedicate this study to the loving memory of my brother and the dairy cows that are noble species on earth.

Any intelligent fool can make things bigger, more complex, and more violent. It takes a touch of genius-- and a lot of courage-- to move in the opposite directions. - Albert Einstein

xii

ACKNOWLEDGMENTS

I would like to thank my Co-advisors Cindy McKinney and Douglas Bannerman.

I am indebted to Dr. McKinney for her advice, support and encouragement throughout my graduate study. She was thoughtful and I emulated her ability to think and write as a scientist. I am thankful to Dr. Bannerman for his guidance, time and advice regarding my doctoral program. He made a profound influence on my approach to scientific research. I feel privileged to have worked under him; he has immense passion for research. I also thank my former advisor Dr. Vallejo for his guidance during my time at Penn State.

Thank also to the committee members Drs. Weiss, Barbato, Harvill and Paulson for their time and advice. I am also very grateful to Terry Etherton for his support and efforts on my behalf during my research period at USDA. As a recipient of 2005 NMPF schloraship, I acknowledge National Milk Producers Federation scholarship committee.

I would also like to thank the staff of the PSU’s Department of Dairy and Animal

Science, in particular Pat, Carol, Sylvia and LuAnn for their time, friendship and help. I acknowledge Bill, Jen and Manuella who are my colleagues and friends.

Most importantly I would like to thank my family for their support, in particular my father who had instilled philosophical values in me and guided in shaping my career and personality.

1

CHAPTER 1

INTRODUCTION

MASTITIS

Mastitis is an inflammation of the mammary gland, the predominant causative

organisms being Gram-positive and Gram-negative bacteria, and mycoplasma species

(spp). Based on the mode of transmission of the etiological agent, mastitis can be further sub-classified as either contagious or environmental mastitis. The major pathogens that

cause contagious mastitis include Streptococcus agalactiae, Staphylococcus aureus and

Mycoplasma spp (Fox and Gay, 1993). The major environmental mastitis pathogens

include coliforms, Streptococcal spp. other than Streptococcus agalactiae and

Pseudomonas spp. (Smith and Hogan, 1993). The most common Gram-negative

pathogens include Escherichia coli, Klebsiella pneumoniae and Pseudomonas spp. These

pathogens cause a wide array of clinical signs from peracute to asymptomatic in dairy

cows. Clinical signs for mastitis include fever, udder edema, changes in milk composition

and reduced milk production. Based on these clinical signs, mastitis is broadly classified

as clinical or subclinical mastitis (Schalm et al., 1971).

Gram-negative bacteria are responsible for an estimated 40% of clinical mastitis

cases (Erskine et al., 1991; Ziv, 1992) with 25% of these cases resulting in death or

culling of the dairy cows (Erskine et al., 1991). Mastitis caused by contagious organisms,

in particular, Streptococcus agalactiae, has been reduced by improved management

practices, yet economic losses from clinical mastitis caused by environmental pathogens

will continue because of the ubiquitous nature of the pathogens (National Mastitis

2

Council (NMC), 1999). E. coli-induced mastitis results in severe clinical signs in dairy cows and the incidence is common in herds with low bulk milk somatic cell count (SCC)

(Bradley and Green, 2001).

Mastitis is highly prevalent in U.S. dairy herds and the estimated economic loss to the U.S. dairy industry alone is over $2 billion per annum (NMC, 1999). Based on retrospective studies the cost for each case of clinical mastitis is estimated to be $100 to

$200 per cow (Hoblet et al., 1991; Wilson et al., 1997). Mastitis is an important factor

(second only to fertility problems) affecting the decision to retain or to cull dairy cows.

Several studies were conducted to evaluate the economic loss associated with mastitis.

The economic losses are mainly due to reduced milk quality, reduced milk production,

replacement costs and veterinary costs (Fetrow et al., 1991; Gill et al., 1990; Lehenbauer et al., 1998; Shim et al., 2004). As the current management practices and therapeutic

measures remain relatively ineffective in reducing the economic losses due to Gram-

negative pathogens, understanding the genetic and immunological aspects of the inflammatory response of the mammary gland would aid in developing measures that could combat mastitis caused by Gram-negative bacteria.

MAMMARY GLAND

The bovine mammary gland (udder) grossly consists of four glands, commonly referred to as quarters. A schematic representation of a longitudinal cross section of bovine udder is shown in Figure 1. The glands are separated from one another by

connective tissue and median suspensory ligaments. Each gland has a single teat that

opens to the exterior through the streak canal through which the mammary secretions are

drained. The teat canal is lined with skin-like epidermis known as keratin that acts as the

3

main physical barrier against pathogens that can invade the mammary gland (Nickerson,

1989). The cavity within the teat seen above the teat canal is the teat cistern and is continuous with the gland cistern of the mammary gland (Turner, 1952).

Fig 1: Schematic representation of bovine mammary gland (Adapted from Dept of Anatomy, University of Bristol).

The secretory tissue and associated connective tissue constitute the interior of the

mammary gland. Secretory tissue in the udder is organized into lobes, each of which is subdivided into lobules. Each lobule contains 150-200 microscopic alveoli. Each alveolus

is a sac-like structure lined with a single layer of secretory epithelial cells, where milk is

4

synthesized and then secreted. The epithelial lining of the alveolus is surrounded by myoepithelial cells. In response to the release of oxytocin a hormone from the pituitary gland, myoepithelial cells by their contractile nature assist in ejection of milk from each alveolus into the mammary duct (Lefcourt and Akers, 1983). Outside the myoepithelial cells, the alveolus is surrounded with connective tissue, which consists of fibroblasts, adipocytes, capillaries and extracellular matrix components (Berry et al., 2003). Milk synthesized in alveoli is drained to the gland cistern through tubular structures known as ducts. The cellular component of milk is referred to as somatic cells and the total number of these cells is represented as the somatic cell count (SCC). In an uninfected gland, macrophages are the predominant cell type in the SCC followed by epithelial cells, lymphocytes and polymorphonuclear neutrophils (PMN’s) (Concha et al., 1986; Miller et al., 1990, 1991). In an infected gland the PMNs are the major cell type (Leitner et al.,

2000). After the keratinized physical barrier, these phagocytic cells (i.e., PMN and macrophages) residing in the mammary gland represent the second line of defense against infection (Paape et al., 2002). A cross section of bovine udder from uninfected (Fig. 2A) and 72 hour post-E. coli infected glands (Fig. 2B) are shown.

Mammogenesis, lactogenesis and galactopoiesis are tightly regulated by a wide variety of endocrine hormones in a complex way (Schalm et al., 1971). The mammary gland continually undergoes changes in its structure and function under hormonal regulation (Tucker, 2000; Vangroenweghe et al., 2005). These physiological changes in the mammary gland predispose cows to intramammary infections. Several studies have shown that the incidence of mastitis due to E. coli is highest during the period of

5

involution which corresponds to a resting state (Oliver and Mitchell, 1983; Green et al.,

2005). Additionally, herds with low milk SCC are more susceptible to coliform infection

Fig. 2A: Cross section of cow udder from an uninfected quarter. The single layer of epithelial cells lining the alveolus is shown by arrow heads. Courtesy: Dr. Tony Capuco, BFGL, USDA

Fig. 2B: Cross section of cow udder 72 hour post-infection with E. coli. Arrows indicate infiltration of neutrophils in the alveolar lumen. Courtesy: Dr. Tony Capuco, BFGL, USDA

6

(Erskine et al., 1988; Bradely & Green, 2001). The pathogenicity of E. coli-induced mastitis is more severe during the periparturient period (Erskine et al., 1988; Shuster et al., 1996) and mainly determined by host factors (Burvenich et al., 2003).

The use of cows as an experimental animal model to study mastitis is not cost effective; therefore, Chandler (1970) developed a laboratory mouse model to study bovine mastitis. The mouse mammary gland is similar to the bovine as each mammary gland in mouse is anatomically and functionally distinct from the adjacent gland.

However, there are five pairs of mammary gland in the mouse and they are located in the thoracic and inguinal region. Several studies (Anderson and Craven, 1984; Garcia et al.,

1996; Brouillette et al., 2003) support the use of a mouse model to study inflammatory responses to intramammary pathogens.

GENETICS OF MASTITIS

Variability in genetic susceptibility to mastitis in dairy cattle has been known for more than 50 years (Lush, 1950). Several independent studies have reported a moderate association between the major histocompatability (MHC) region and mastitis (Mallard et al., 1995; Kelm et al., 1997). However, genes other than MHC loci also contribute to mastitis susceptibility, and in this regard, genes regulating the mammary gland and their immunity may be important (Seykora and McDaniel, 1985; Rogers et al., 1998; Lassen et al., 2003; Youngerman et al., 2004). Together, these studies emphasize the polygenic nature of mastitis susceptibility (Fries and Ruvinsky, 1999). The inheritance component of mastitis has been established in several studies of various cattle breeds and ranges from 0.02 to 0.10 (Weller et al., 1992; Lund et al., 1999). Nash et al. (2000) reported estimates from 0.03 to 0.25 which are relatively high compared to other studies. The

7

heritability for SCC is higher than clinical mastitis (Emanuelson et al., 1988) with reasonably high genetic correlation between mastitis and SCC (Coffey et al., 1986;

Emanuelson et al., 1988). In many countries, SCC has been included in breeding programs, as it is a good indicator of udder health. However, direct selection of sires for daughters with improved resistance to intramammary pathogens is currently unavailable in the breeding program of dairy cattle in the U.S..

Several cattle reference families have been used for the construction of genetic linkage maps including, the International Bovine Reference Panel (IBRP) families

(Barendse et al., 1997); the USDA Meat Animal Research Center (MARC) mapping herd

(Bishop et al., 1994; Kappes et al., 1997); a large collection of U.S. Holstein families

(Georges et al., 1995); the Illinois Reference Resource Families (Ma et al., 1996); and the

Angleton Research Herd (Yeh et al., 1996). The cattle genome is between 2500 and 3000 centi Morgan (cM) located on 30 pairs of chromosomes (Fries, 1993; Kappes et al., 1997;

Fries and Ruvinsky, 1999). Second generation bovine genetic maps have resulted in more than 1600 microsatellite markers located in all regions of the bovine genome providing an average marker density of 3.0 centi Morgan (cM) (Georges et al., 1995; Ma et al.,

1996; Barendse et al., 1997; Kappes et al., 1997). Recently, a high resolution genetic map for cattle was developed consisting of 3960 markers spanning 3160 cM with an average map interval of 1.4 cM (Ihara et al., 2004). This comprehensive genetic map will allow fine mapping of chromosomal regions harboring candidate genes for inherited polygenic traits such as milk yield, protein and fat content, mastitis and other diseases.

Several genome scans to identify quantitative trait loci (QTL) for udder health have been conducted in dairy cattle. All of these studies used grand-daughter designs

8

(GDD) with sparse marker density. Most of them analyzed QTL for SCC and very few have analyzed for mastitis and udder type traits. A summary of reported putative QTL for

SCC and mastitis is presented in Table 1. These markers are located in different chromosomal regions and many reported QTL were not confirmed, suggesting that the variation could be altered by the allelic frequencies in the founder population studied or they might be false positives. However, instances of QTL having a major effect on quantitative traits have been discovered. Examples in livestock include double-muscling

in cattle (Kambadur et al., 1997), milk-fat percentage in dairy cattle (Grisart et al., 2002)

and Booroola in sheep (Mulsant et al., 2001). Hence, with the current high-throughput

molecular tools and rapid expansion of bovine genomic databases, a functional genomic

approach would aid in fine mapping of QTL regions and identification of candidate genes

for increased susceptibility to mastitis or traits related to mastitis. Current antimicrobial

therapeutics and prophylactic measures have marginal efficacy against mastitis caused by

environmental pathogens. Therefore, an alternate approach to reduce incidence of

environmental mastitis among dairy cattle could be by integration of breeding program

for mastitis resistance through marker assisted selection (MAS) with the current

prophylactic measures.

9

Table1: Quantitative trait loci for mastitis and somatic cell score (SCC).

Chromosome Trait Closest Marker (position cM) Significance References 1 SCC ? (59) *** Schulman et al., 2004 3 SCC BMC5227 (171) * Schrooten et al., 2000 SCC ? (109) *** Schulman et al., 2004 CM BR4502 * Klungland et al., 2001 4 SCC RM188-TGLA116 (0-46) *** Zhang et al., 1998 CM BM6458-BMS1974 * Klungland et al., 2001 5 SCC BM315 ** Heyen et al., 1999 6 CM FBN12 *** Klungland et al., 2001 7 SCC BMS1979 ** Heyen et al., 1999 SCC BM6117 (61) * Van Tassel et al., 2000 8 SCC TGLA13, INRA 122 * Klungland et al., 2001 9 SCC BMS1967 (125) * Boichard et al., 2003 10 SCC DICK20 (86) ** Boichard et al., 2003 11 SCC ? (68) *** Schulman et al., 2004 13 SCC TGLA381-AGLA232 (78-140) Zhang et al., 1998 14 SCC ILSTS11-BM302 (0-65) *** Zhang et al., 1998 CM ? (25) *** Schulman et al., 2004 CM BM6425 * Klungland et al., 2001 Udder-SCC BM302 ** Ashwell et al., 1998 15 SCC BMS2684 (88) *** Boichard et al., 2003 18 SCC BM7109-ILSTS002 (70) * Shrooten et al., 2000 SCC ? (111) *** Schulman et al., 2004 CM ? (111) *** Schulman et al., 2004 SCC -117 *** Kuhn et al., 2003 21 SCC ETH131 ** Heyen et al., 1999 SCC ? (51) *** Schulman et al., 2004 SCC TGLA122 (90) * Boichard et al., 2003 22 SCC BM3628-CSSM26 * Heyen et al., 1999 23 MGTG7 * Heyen et al., 1999 RM33 (19) * Boichard et al., 2003 Udder-SCC 513-BM1258 ** Ashwell et al., 1998 24 SCC ? (28) *** Schulman et al., 2004 Holmberg and 25 CM ILSSTS102-RM404 * Andersson-Eklund, 2004 26 SCC TGLA429-BM804 (71-82) *** Zhang et al., 1998 27 SCC ? (1) *** Schulman et al., 2004 CM BM1857, INRA27 * Klungland et al., 2001 29 SCC ? (16) *** Schulman et al., 2004 *** represents genome wide significance, ** and * represents significance at chromosomal level for value of P < 0.05 and 0.01.

10

INNATE IMMUNITY

The host’s defense mechanism against an invading pathogen is mediated by a combination of innate and adaptive immunity. The innate immune response is a non- clonal system of pathogen recognition and is mediated by germline-encoded receptors conserved through evolution. The identification of Toll-like receptors (TLR) and their signaling pathways led to a better understanding of host innate immune response to invading pathogens (Medzhitov and Janeway, 2000; Akira et al., 2001). The innate immune system represents the first line of defense in the host (Hoffman et al., 1999) and is operative during the earliest stages of infection. The recognition of conserved structural motifs on microbes, called pathogen associated molecular patterns (PAMPs), is mediated by pattern-recognition receptors (PRRs) in the host through mechanisms that are not well defined. Through PAMP recognition by the PRRs system, the innate immune system detects the presence of infection and recognizes the type of infection such as Gram- negative or Gram-positive bacteria, viral agents and other parasites (Medzhitov and

Janeway, 2000). Upon recognition of microbial pathogens, TLR activates the innate immune response through the NFκB-dependent expression of antimicrobial peptides

(Lemaitre et al., 1996), including pro-inflammatory cytokines and co-stimulatory molecules (Medzhitov et al., 1997). They also mediate phagocytosis (Takeuchi et al.,

2000) and maturation of dendritic cells that are highly efficient antigen-presenting cells

(APC) (Medzhtitov et al., 1997; Visintin et al., 2001). In response to intramammary pathogens, mammary epithelial cells and macrophages secrete pro-inflammatory cytokines and chemo-attractants to recruit circulating neutrophils to the site of infection.

11

The major effector of the mammary defense mechanism against most mastitis pathogens is mediated by neutrophils through phagocytosis and respiratory burst mechanisms (Burvenich et al., 1994; Burton and Erskine, 2003). The initial innate

immune response that occurs early in infection is critical for localization of infection as well as activation of adaptive immunity which becomes active normally 4-5 days later in the host defense mechanism. An increase in the expression of TLR2 and TLR4 genes was

noticed at the mRNA level in the bovine mammary gland in response to intramammary

pathogens (Goldammer et al., 2004). The innate immune response to intramammary

E. coli and S. aureus experimental challenge has been well studied in cows for major pro- inflammatory cytokines and acute phase proteins (Riollet et al., 2000 & 2001; Bannerman et al., 2004a). These studies clearly demonstrate that the innate immune response varies among intramammary pathogens. A comprehensive list of cyokines, growth-factors, interferons, and colony stimulating factors, their major source and their biological function are given in Table 2. Although much is known about the innate immune response to E. coli, less is known about the response to other Gram-negative mastitis pathogens. Elucidation of the innate immune response to Pseudomonas aeruginosa, a major Gram-negative mastitis pathogen, would help in better understanding the mammary gland’s innate defense mechanism against various pathogens.

Acquired or adaptive immunity evolved more recently as it is found only in the subphylum vertebrata and is mediated by B-cell antibody production. Antibody diversity is mediated via somatic rearrangement of receptor genes, producing a diverse repertoire of B- and T-cell receptors with random specificities to combat invading pathogens.

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Table 2: Major cytokines: their sources and functions.

CYTOKINE CELLULAR SOURCE BIOLOGICAL FUNCTION CHROMO- SOME NUMBER (BOVINE) INTERLEUKINS IL-1α and β Macrophages, epithelial cells, Induction of fever, and inflammation, 11 fibrobalsts acute phase protein synthesis, activation of T-cell and macrophage IL-1Ra Monocytes, macrophages, neutrophils, As a natural antagonist of IL-1 function 13 and hepatocytes IL-6 T-cells, macrophages and endothelial Acute phase response, T-and B-cells 4 cells growth and differentiation IL-8 Macrophages, endothelial and epithelial Chemoattractant for neutrophils 6 cells IL-10 Macrophage, T-cells Potent suppressant of macrophage 16 function and cytokine production, promotes B cell proliferation and antibody production IL-12 B-cells, macrophages Activates natural killer (NK) cells, 7 induces CD4 T-cell differentiation to TH1- like cells. INTERFERONS IFN-γ T-cells, NK cells, macrophages? Induction of anti-viral activity, Ig class 5 switching, macrophage activation IFN-α Leukocytes Antiviral, increased MHC class I 8 molecule expression IFN-β Fibroblats Antiviral, increased MHC class I 8 molecule expression GROWTH FACTORS TGF- α Epithelial cells, fibroblasts, monocytes, Promotes IL-8 production, mediates unknown macrophages wound healing TGF- β Chondrocytes, macrophages and T-cells Anti-inflammatory, promotes wound unknown healing, induces IgA secretion, and inhibits monocytes/macrophages class II expression. TUMOR NECROSIS FACTORS TNF- α Macrophages, NK-cells, T-cells Local inflammation, endothelial 23 activation, acute phase response TNF- β T- and B-cells Tumor cytotoxicity, endothelial 23 activation

13

Recognition of pathogens by PRRs induces expression of costimulatory molecules in APCs. Upon recognition of antigen presented by APC cells along with costimulatory molecules, naïve TH (T helper) cells are activated and differentiate to form

TH1 (type 1) and TH2 (type 2) cells. The differentiation of TH cells is determined by the

dendritic subsets and is influenced by the conditional cytokines or maturation stimulus

and inflammatory mediators present at the site of infection (Mazzoni and Segal, 2004).

TH1 cells primarily mediate cell-mediated immunity and inflammation, and secrete their

own interferon-γ and interleukin-12 (IL-12) while, TH2 cells promote antibody mediated

immunity and produce interleukin 4 (IL-4), IL-5, IL-10 and IL-13. IL-12 and IL-4 act as positive feedback mediators promoting naïve TH cells to enter the TH1 or TH2 pathway,

respectively (Medzhitov and Janeway, 1997; Akira et al., 2001). The success of

neutrophil mediated defense mechanisms in the mammary gland largely depends upon

the level of immunoglobulin, isotype G2 (IgG2) in milk and is primarily induced by a TH1 response (Burton and Erskine, 2003). Antibody mediated protection against S. aureus and

E. coli induced mastitis generally is not effective to date. Therefore, a thorough study of cytokine responses to major Gram-negative pathogens is important to strike a TH balance or tailor adaptive immunity to type 1 (TH1) polarization. The cytokines important for

mammary gland immunity in response to Gram-negative infections are described below.

PRO-INFLAMMATORY CYTOKINES

Tumor Necrosis Factor-alpha (TNF-α)

TNF-α (also called cachectin), like IL-1, is a major immune response modifying cytokine produced primarily by activated macrophages and T-cells. It was first isolated in an attempt to demonstrate factors that caused tumor cell necrosis (Carswell et al., 1975).

14

The 705 bp mRNA encodes a TNF-α protein of 233 aa in bovine (Cludts et al., 1993).

The action of TNF-α is mediated by a receptor-bound mechanism located on the cell surface; the 55 kDa TNF-receptor 1 (TNFR1) and 75 kDa TNF-receptor 2 (TNFR2)

(Taraglia and Goeddel, 1992). TNF-α is the key cytokine mediated in the host innate response to lipopolysaccharide (LPS) or Gram-negative bacteria that induces expression

of other molecules and interleukins (Tracey and Cerami, 1994). TNF-α along with IL-1β

is known to initiate the acute phase response (Koj, 1998) and to activate neutrophils in a

process preventing apoptotic death (Oehler et al., 1998). Infusion of recombinant bovine

TNF-α in the mammary gland is found to inhibit synthesis of milk, alter the blood-

mammary gland barrier and has a marginal effect on the generalized inflammatory

response (Watanabe et al., 2000).

Interleukin -1 (IL-1)

IL-1 and its related members are primarily pro-inflammatory cytokines. The two

IL-1 peptides are IL-1α and IL-1β and have pleiotropic roles in inflammation and

immune response (March et al., 1985). IL-1 factor was first identified as a pyrogenic

factor produced by activated peritoneal exudate cells (Heyman and Beeson, 1949). Later

two different lines of research identified it as a leukocyte endogenous mediator

(Kampschmidt, 1984) and lymphocyte activating factor (Gery et al., 1971). The mature

bovine IL-1α and IL-1β proteins are 150 and 153 aa with molecular weights of 17.2 and

17.7 kDa, respectively (Maliszewski et al., 1988). Receptor mediated function of IL-1

was first demonstrated by Dower et al. (1985) on a T-lymphoma cell line. IL-1 is a potent

inducer of fever, acute phase proteins and IL-6. It also recruits neutrophils to the site of

infection by upregulation of adhesion molecules (Dinarello, 1996). IL-1α and IL-1β have

15

been detected in mammary epithelial cells from uninfected cows using reverse transcriptase- polymerase chain reaction (Okada et al., 1997). In E. coli, increases in IL-1

level were noticed in association with an influx of neutrophils (Riollet et al., 2000;

Bannerman et al., 2004a).

Interleukin-8 (IL-8)

IL-8 (CXCL8) is a member of the chemokine family that exhibits potent

chemotactic activity for neutrophils and is produced by activated monocytes,

macrophages, endothelial cells and T-lymphocytes (Matsushima and Oppenheim, 1989).

In the bovine, the mRNA sequence for IL-8 corresponds to 643 bp encoding for a mature

protein of 101 aa with a molecular weight of 7.8 kDa (Morsey et al., 1996). IL-8 exhibits

its biological activity on neutrophils by CXCR1 and/or CXCR2; the latter are members of

the seven-transmembrane domain G-protein coupled receptor family (Holmes et al.,

1991; Gao et al., 1993). IL-8 brings about migration of neutrophils to the site of infection,

delays apoptosis of neutrophils and enhances their killing ability by granule release and

respiratory burst activity (Harada et al., 1994; Jones et al., 1996; Kettritz et al., 1998;

Chertov et al., 2000).

Interleukin-12 (IL-12)

IL-12 is produced by monocytes, macrophages, and neutrophils. It is a potent

stimulator of natural killer (NK) cells and mediates differentiation of the TH1 subset of

T-helper cells. Incubation of resting or activated peripheral blood lymphocytes (PBL)

with IL-12 results in induction of interferon-γ (IFN- γ). It acts as a link between innate and adaptive immunity (Chan et al., 1991 & 1992; Trinchieri, 1993). IL-12 is an unusual cytokine composed of two subunits (p35 and p40) that are co-expressed to yield bioactive

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IL-12 in humans (Wolf et al., 1991). Similarly, bovine IL-12 is a heterodimer composed of two subunits (p35 and p40) that are co-expressed to form p70 (Zarlenga et al., 1995;

Takehara et al., 2000).

Interferon-γ (IFN- γ)

IFN-γ is a type-II interferon and was first reported by Wheelock (1965) as an antiviral factor in uninfected human leukocytes. IFN-γ is mainly secreted by TH1 cells

and NK cells and contributes to both innate and cell mediated immunity (Trinchieri, 1993

& 1997). The bovine IFN-γ is composed of 143 aa and has been shown to be expressed

in normal mammary gland (Cerretti et al., 1986; Alluwaimi, 2000). IFN-γ can either

activate or inhibit apoptosis of neutrophils. Neutrophil cultures, when treated with IFN-γ

or granulocyte macrophage colony stimulating factor (GM-CSF), express CD83, a cell

surface marker that is similar to dendritic cells (Iking-Konert et al, 2001). IFN-γ also

activates cytotoxic T cells and inhibits proliferation of TH2 cells that mediate cellular immune response (Akira et al., 2001).

ANTI-INFLAMMATORY CYTOKINES

Interleukin-10 (IL-10)

IL-10 secreted by TH2 cells is one of the most potent anti-inflammatory cytokines in the immune system. It was first identified as cytokine synthesis inhibitory factor as it inhibited the production of IFN-γ and IL-2 by TH1 cells (Fiorentino et al., 1989). The

bovine IL-10 gene encodes a protein of 178 aa (Hash et al., 1994). IL-10 is a potent

deactivator of pro-inflammatory cytokines synthesized by macrophages/ monocytes

(Clarke et al., 1998; Gerard et al., 1993). As an anti-inflammatory cytokine, it inhibits

nuclear factor κB (NF-κB) nuclear translocation following LPS stimulation. It also

17

inhibits surface expression of CD14, an LPS recognition and signaling molecule (Opal et al., 1998).

Transforming Growth Factor (TGF-β)

TGF-β belongs to a superfamily that has more than 25 distinct dimeric proteins that share a common structure (Kingsley, 1994). There are three isoforms of TGF-β

(designated TGF- β1-3) in mammalian species. However, in bovine milk, only two

isoforms (TGF-β1 and TGF-β2) have been reported (McCartney-Francis et al., 1998;

Ginjala and Pakkanen, 1998). TGF-β has an effect on cell proliferation and differentiation

(Letterio and Roberts, 1997). In vitro, it inhibits growth of ectodermally derived cells

(Roberts and Sporn, 1992) and alveolar type II cell proliferation (Jetten et al., 1986) and it induces squamous cell differentiation of bronchial epithelial cells (Norgaard et al.,

1994). It also regulates mammary gland development and function. It includes ductal

growth and patterning, alveolar development and its functional differentiation (Daniel et

al., 2001). TGF-β has both pro- and anti-inflammatory properties, but its major role is

down-regulation of the inflammatory response (Ashcroft, 1999). Its function as a

suppressor or activator depends largely on the presence of other cytokines that modulate

the cellular response to TGF- β and also on the activation state of the cell (Kingsley,

1994). TGF- β brings about resolution and wound repair in an active site of

inflammation. The anti-inflammatory properties of TGF-β are characterized by its ability

to inhibit production of pro-inflammatory cytokines and IFN-γ production. TGF-β1

suppresses the proliferation and differentiation of T and B cells (Letterio and Roberts,

1997).

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ANTIMICROBIAL AGENTS AND CURRENT THERAPIES IN MASTITIS

The U.S. Food and Drug Administration’s (FDA) definition of antimicrobial is an agent that kills bacteria or suppresses their multiplication or growth. This includes antibiotics and synthetic agents. The discovery of penicillin by Alexander Fleming in the

1929 was a major revolution for modern therapeutic medicine. Several antimicrobial classes are approved for use in food animals for the treatment of mastitis including β- lactams (e.g., penicillins, cephalosporins, ampicillin), tetracycline, macrolides (e.g., erythromycin), linocosamides (e.g., pirlimycin), and novobiocin (CLSI, 2002; Mitchell et al., 1998). A comprehensive list of antimicrobials approved for mastitis treatment in lactating and dry cows is presented in Table 3. The incidence of mastitis due to Gram- negative bacteria remains high due to the ubiquitous nature of these bacteria (Smith and

Hogan, 1993) and the current lack of effective therapeutic antimicrobials, preventive vaccines and other prophylactic measures. Some bacteria develop resistance by horizontal transfer of genetic material (McDermott et al., 2003). Bacteria like

Providencia stuartii have a natural resistance mechanism to antimicrobial agents like tetracylines (Mateu and Martin, 2001). Serratia marcescens, an important nosocomial agent and one of the major Gram-negative mastitis pathogens (Bannerman et al., 2004b) exhibits resistance mechanisms to multiple drugs by their efflux pump mechanisms

(Berlanga et al., 2000).

As an alternative to traditional antibiotic therapies, many naturally occurring endogenous products have been tested for their bactericidal activity including lactoferrin

(Sanchez and Watts, 1999), myeloperoxidase (Cooray and Bjorck, 1995), and β-defensin

(Cullor et al., 1991). However, their bactericidal activity in milk is limited or ineffective.

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Endotoxin, also known as LPS, an integral component of the cell wall of all

Gram-negative bacteria, activates host’s innate immune response and induces production

of proinflammatory cytokines. However, excessive or prolonged inflammatory responses

are detrimental to the host’s mammary secretory tissue and result in apoptosis of

mammary epithelial cells (Long et al., 2001). Therefore, there is strong interest in

developing antimicrobials that have both bactericidal and LPS-neutralizing activity.

Bactericidal/Permeability-Increasing protein (BPI) is a 50-60 kDa protein expressed in

PMN (Weiss et al., 1978). Human BPI exhibits both LPS-neutralization activity (Marra et

al., 1992) and bactericidal activity against Gram-negative bacteria (Weiss et al., 1982).

No study has yet reported on bovine BPI and its bactericidal activity. The biological

activity of human BPI has not been evaluated in bovine milk or serum.

SPECIFIC AIM

Several genome-wide scans and association studies suggest that genetic

variability among cows is one of the contributory factors for mastitis susceptibility. Also,

genetic variability may influence the host’s innate immune response to major

intramammary pathogens, including E. coli and P. aeruginosa. The innate immune

response to P. aeruginosa remains ill-defined. Current antimicrobial therapies are sub-

optimal in treating these infections, consequently, development of more efficacious

therapies is essential to combat the rapidly evolving array of intramammary pathogens. I

hypothesized that: (i) allelic variations in specific genes alter the genetic susceptibility to

mastitis. To evaluate this hypothesis, gene expression studies were conducted in an

experimental mouse model of mastitis to identify candidate genes that may underlie

genetic risk factors for mastitis caused by E. coli. The expectation is that potential

20

Table 3: List of antibiotics approved for mastitis treatment in dairy cattle.

Class Antimicrobial Trade Indications Spectrum of Withdrawl period agents name activity (at labeled doses)

Milk Slaughter (hours) (days) β-Lactams Penicillin-G Go-Dry Dry cows broad spectrum 72 14 (procaine) Masti-clear Lactating cows 60 3

Amoxicillin Amoxi- lactating broad spectrum 60 12 trihydrate Mast cows Cloxacillin Dari-Clox Lactating Staphylococcal 48 10 (sodium) cows spp Dri-Clox Dry cows Staphylococcal do not use 30 days spp prior to calving Cephapirin Cefa-Dri Dry cows narrow 72 hours 42 benzathine spectrum after (first calving generation cephalosporins) Cephapirin Cefa-Lak Lactating narrow 96 4 sodium (first cows spectrum generation cephalosporins) Ceftiofur Hcl spectramast Lactating Coagulase 72 none LC cows negative Staphylococcus spp, S.dysgalactiae, E. coli Macrolides Erythromycin Gallimycin- Lactating S.aureus, 36 14 36 cows S. agalactiae, S. dysgalactiae, S.uberis Lincosamides Pirlimycin Hcl Pirsue Lactating staph spp, Strep 36 9 cows spp. Miscellaneous Novobiocin 17900- Lactating Some Gram + 72 10 Forte cows cocci Drygard Dry cows 72 hours 30 after calving Hetacillin Hetacin K Lactating S.agalactiae, 72 10 potassium cows S.dysgalactiae, S.aureus, E. coli

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candidate genes that could act as biomarkers for mastitis susceptibility may be identified.

(ii) BPI is a candidate gene for mastitis susceptibility, any allelic variation in the functional domain of BPI could alter the functionality of the protein. To evaluate this hypothesis, single nucleotide polymorphism (SNP) discovery was undertaken in the coding region of the functional domains that are known to have bactericidal and LPS neutralizing activity. An association study was carried out between the identified SNP marker alleles and daughter yield deviation for milk SCC, the phenotypic trait for bovine mastitis. (iii) Bovine-BPI-derived synthetic peptides are potential anti-inflammatory and antimicrobial agents against Gram-negative intramammmary pathogens. To evaluate this hypothesis, the bactericidal and LPS neutralizing activity of human- and bovine-BPI- derived synthetic peptides were tested in vitro against various Gram-negative mastitis pathogens. It is expected that potential SNPs or haplotypes associated with SCC phenotype may be identified within the BPI N-terminal region. An evaluation of the BPI peptides for their biological activity in milk and serum against the Gram-negative mastitis pathogens would aid in development of an endogenous protein as a new therapeutic

agent. (iv) The bovine innate immune response to the Gram-negative mastitis pathogens

is conserved. To evaluate this hypothesis using the cow as an experimental animal model,

the innate immune response for Pseudomonas aeruginosa was studied for various pro-

inflammatory and anti-inflammatory cytokine responses. It is expected that the

mechanism of host-pathogen interaction could be elucidated and would aid in

development of cytokines and their receptors as new therapeutic agents or

immunomodulators. The following chapters outline in detail my studies to investigate

these four hypotheses.

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CHAPTER 2

A MICROARRAY SCREEN FOR IDENTIFICATION OF POTENTIAL

CANDIDATE GENES FOR GRAM-NEGATIVE INTRAMAMMARY

PATHOGENESIS IN A MOUSE MASTITIS MODEL

INTRODUCTION

Mastitis is an inflammatory disease of the mammary gland caused by bacteria and

40% of clinical mastitis cases affecting the U.S. dairy industry are caused by Gram- negative bacteria (Erskine et al., 1991). Mastitis is a multifactorial inflammatory disease where genetic and environmental factors play a role in host susceptibility (Shook, 1989).

In the U.S. dairy industry mastitis related traits such as somatic cell score (SCS, a logarithmic score of somatic cell count), and udder and teat characteristics (related to

primary defense of the mammary gland) are phenotypic factors included in the breeding

programs. Successful quantitative trait loci (QTL) mapping is limited due to low

heritability of mastitis related traits and their moderate level of correlation with mastitis

(Pighetti, 2006). Genetic selection for mastitis, based on records from clinical cases of

bovine mastitis is being practiced in Scandinavian countries (Heringstad et al., 1999). In the U.S., genetic selection for udder health based on clinical mastitis (CM) is unavailable

because records of clinical cases in field conditions are unavailable. In addition, clinical

mastitis represents only one form of the disease, subclinical mastitis is probably more

prevalent than CM, and requires culturing of milk samples to determine the presence of

bacteria (Pighetti, 2006).

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In the past decade, many genome-wide scan studies have identified a number of

QTL regions for the SCS trait related to mastitis on all bovine chromosomes. However,

QTL positions that are repeatedly confirmed in two or more studies emphasize the potential of the mapped region for markers related to mastitis resistance or susceptibility.

Genome scan studies in Scandinavian countries have mapped QTL directly for clinical mastitis based on clinical records for mastitis and additional udder health information.

These studies, identified three QTL on bovine chromosomes 6, 14, and 18, and two putative QTL were also mapped on chromosomes 9 and 11 (Klungland et al., 2001;

Schulman et al., 2004; Holmberg and Anderson-Eklund, 2004). Putative QTL for SCC were identified on chromosome 3, 14 and 18 (Zhang et al., 1998; Schrooten et al., 2000).

The main objective of QTL mapping is to identify coding sequences or marker alleles localized in the QTL region that are causative for the observed phenotype under study

(Collins, 1995). Identification of putative candidate genes and genetic variability in the form of single nucleotide polymorphism (SNPs) within them would help in determining the genetic variation to susceptibility for complex diseases including mastitis (Pighetti,

2006).

Microarray based gene expression studies are a powerful tool that allows investigations based on the level and pattern of expression of thousands of genes simultaneously (Lockhart and Winzeler, 2000). Prior studies have used differential display or real-time PCR based molecular techniques for identification of functional candidate genes for mastitis resistance (Madsen et al., 2002; Schwerin et al., 2003;

Schmitz et al., 2004). One study has reported altered gene expression using a cDNA microarray technique to capture cDNA representing unique bovine leukocyte genes.

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Analysis of transcriptional gene activity on a global level has not yet been applied to

bovine mastitis.

Several studies support the use of a mouse model to study bovine-mammary-

gland mediated inflammatory responses to bacterial pathogens (Anderson and Craven,

1983; Garcia et al., 1996; Brouillette et al., 2003). A combination of a mouse

experimental mastitis model and cDNA microarrays is a powerful technique to study the

biological pathways involved in the host inflammatory response to E. coli-induced

mastitis. In this chapter, we report potential candidate genes for mastitis susceptibility

determined using microarray analysis.

MATERIALS AND METHODS

Mouse Model of E. coli induced Mammary Inflammation

Experimental mice were maintained and used according to guidelines approved

by the Pennsylvania State University Institutional Animal Care and Use Committee.

Timed pregnant mice (13 days pregnant) of inbred strains Balb/cJ, C57/BL6J, and

C3H/HeJ were purchased (Jackson Laboratory, Maine). The E. coli strain P4 was

provided by Dr. Max Paape (USDA, Beltsville, MD), and strain 487 was provided by Dr.

Lorraine Sordillo (MSU, East Lansing, MI). These bacterial strains were originally

isolated from cows with clinical mastitis. A day before the intramammary challenge with

E. coli, 10 mL of tryptic soy broth (TSB) (Becton-Dickinson Diagnostics systems, Inc.)

were inoculated with E. coli bacteria and incubated for 18h at 37°C shaking. The next

day bacteria were centrifuged at 2500 x g for 10 min at 4°C. The resulting pellet was

washed three times with sterile PBS. After the final wash, the bacterial pellet was

resuspended in 10 mL PBS and the bacterial concentration was determined by reading its

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optical density at OD 610 nm. The stock solution was adjusted to obtain a bacterial concentration of 108 CFU/mL. For the intramammary challenge, serial dilutions were made to a concentration of 30 CFU/50µl. Prior to intramammary challenge with E. coli, the mice were anesthetized with a mixture of ketamine (100 mg/mL) and xylazine

(20mg/mL) at a dose of 1mg and 0.2 mg respectively per 10 gm body weight. For the gene expression profiling experiment, Balb/cJ inbred mice at their 5th to 8th day post

partum were challenged with E. coli strain 487. The 4th right mammary gland was infused

with E. coli (36-42 CFU/50µl) and the contralateral gland was infused with 50µl of

sterile PBS. The number of CFU infused was empirically confirmed by spreading 50 µl

of the bacterial inoculum onto a blood agar plate. The plate was subsequently incubated

overnight at 37 ºC and enumerated the next day.

Tissue Sampling and RNA isolation

The saline- and E. coli-challenged mammary glands were excised aseptically at

24 and 48 hrs post-injection. Briefly, a midline incision was made and the skin was

separated from the peritoneum to expose the mammary gland. The mammary tissue was

traced from the teat end and excised by blunt dissection. The tissue samples were stored

in RNA Later (Ambion, TX) until further processing for RNA extraction. For total RNA isolation, the tissue samples were homogenized using a tissue homogenizer (Omni

International, VA) and total RNA was isolated using a lipid tissue midi kit (Qiagen, CA).

Aliquots of the total RNA were stored at -81°C. A small representative portion of mammary tissues from each sample was sent to the Animal Diagnostic Laboratory (ADL,

Pennsylvania State University, University Park, PA) for bacteriological culture and

confirmation. The occurrence of an inflammatory response in the mammary gland was

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confirmed by histological examination using Shandon Varistain Gemini H&E protocol in the Electron Microscopy Facility (EMF) at Pennsylvania State University (University

Park, PA).

Microarray Hybridization

Unless otherwise indicated, the protocols of the reagents’ manufacturers were strictly followed. The following reagents were used for the cDNA synthesis: Genechip

T7-oligo dT promoter kit (Affymetrix, CA), Superscript II (Invitrogen, Life

Technologies, CA), E. coli DNA ligase (Invitrogen, Life Technologies, CA), E. coli

DNA polymerase (Invitrogen, Life Technologies, CA), E. coli RnaseII (Invitrogen, Life

Technologies, CA), T4 DNA polymerase (Invitrogen, Life Technologies, CA), 5X

second strand buffer (Invitrogen, Life Technologies, CA), 10mM dNTP (Invitrogen, Life

Technologies, CA), and Genechip sample cleanup module (Affymetrix, CA). The Enzo

RNA transcript labeling kit (Affymetrix, CA) was used for the Biotin labeling of cRNA.

The GeneChip® Mouse Expression Set 430A (Affymetrix, CA) was used for the

gene expression analysis. This array included 22,690 well-characterized mouse genes.

Eleven pairs of oligonucleotide probes were used to measure the level of transcription of each sequence represented on the array. The genes GAPDH, β-Actin, transferrin receptor and pyruvate carboxylase were included in the arrays as housekeeping/control genes.

The target (biotin-labeled cRNA) was prepared and fragmented in accordance with instructions in the GeneChip® Mouse Expression Set 430A expression analysis technical

manual (Affymetrix, CA). The fragmented cRNA target was hybridized to the probe array (GeneChip® Mouse Expression Set 430A) in the Microarray Core Facility at

Pennsylvania State University (University Park, PA). One tissue sample or population of

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mRNAs (from infected or uninfected mammary tissue) was hybridized to one GeneChip®

array using the Affymetrix System (Affymetrix, CA) and a Microfluidcs Agilent System

(Agilent Technologies, CA). Then the signal expression per spot within arrays was

measured using a GenePix 4000A scanner (Axon Instruments, CA). The signal

expression raw data for each of the 8 arrays were stored in electronic files (*.CEL files)

in our laboratory database. Following publication of the result, the raw data will be

available in the PSU’s Department of Dairy and Animal Science web page.

Experimental Design

The gene expression profiling study was conducted using a split-plot design. We measured levels of gene expression in uninfected (saline) and infected (E. coli) mammary

gland tissues (treatment= 2, in sub-plots) at 24 and 48 hrs time point (time= 2, in main-

plots). In comparison with designs where each treatment is tested in a different inbred

mouse, this study design is expected to minimize the effects of inter-mouse variation and

thereby increase the accuracy of the treatment effect measured. The expression profiling

study was restricted to two biological replicates considering the cost factor.

Array Quality Control and Data Pre-processing

Data pre-processing and statistical analysis were carried out by Dr. Roger Vallejo.

For the quality assessment of the gene expression data, statistical and graphical functions

from the R package version 1.9.0 for UNIX operating system were used to generate

density, box and scatter plots for the whole dataset and combination of arrays (Ihaka and

Gentleman, 1996). The quality of the microarray data was assessed by visual inspection

of these plots for data outliers and other attributes suggestive of arrays with poor data quality. Then the raw expression data were pre-processed using functions from the R

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package version 1.9.0 for UNIX operating system (Ihaka and Gentleman, 1996). A data background correction was performed using the robust multichip average (RMA) procedure, which included a log2 transformation of the perfect match signal expression, quantile data normalization and a median Polish summary method. After running these functions in the raw expression data, a score was obtained for each of the 22,690 genes.

This dataset was used for further statistical analysis described below.

Statistical Data Analysis

The statistical analysis of the expression “score” dataset was performed using the

R package version 1.9.0 for UNIX operating system (Ihaka and Gentleman, 1996).

Linear mixed effect-Analysis of variance (LME-ANOVA) was performed using this statistical model,

yijk = ai + tj + (at)ij + mk/tj + eijk

Where,

yijk is the gene expression score for the i-th treatment, j-th time, and k-th mouse,

ai is the fixed treatment effect with i = 1, 2; where 1= saline and 2= E. coli,

tj is the fixed time effect with j = 1, 2; where 1= 24 hr and 2= 48 hr,

(at)ij is the interaction effect due to the interaction of treatment with time,

mk/tj is the random effect of the k-th mouse nested in the j-th time, and

eijk is the residual error effect.

To run the LME-ANOVA, a script was written in R language using functions available in

the R package version 1.9.0 (Ihaka and Gentleman, 1996).

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Validation of Differentially Expressed Genes by Quantitative Real Time RT-PCR

From the genes declared as differentially expressed using statistical analysis, a set of genes were validated using quantitative real-time PCR (Q-PCR). Q-PCR was performed using Gene Expression Taqman® Assays-on-Demand reagents (Applied

Biosystems, CA). We measured the relative quantity of mRNA in E. coli and saline treated mammary gland at either 24 h r or 48 hr post-injections as indicated in the column

“time tested” in Table 2. We determined the relative quantity of mRNA in E. coli and saline treated mammary tissue using the Comparative Ct Method (Applied Biosystems,

CA). The mouse GAPDH gene was used as an endogenous control to determine the baseline expression level. The expression level of each validated gene was measured via

Q-PCR using three technical replications.

RESULTS

Intramammary Infection in Mouse Mastitis Model

Initially, three inbred strains of mice were infected with two strains of E. coli that were originally isolated from clinical mastitis cases. The inflammatory responses were observed in the mammary gland of all the three strains of mice for the two E. coli isolates. This was done to confirm that the subsequent inflammatory response to E. coli- induced mastitis was neither due to genetic variation among the inbred mice strains nor due to variation in bacterial strain (data not shown). The establishment of an inflammatory response in the mammary gland in response to E. coli strain 487 was confirmed by gross and histological changes between the infected (E. coli) and uninfected (saline) glands (Fig. 1). Total RNA samples were extracted from the tissues that were found to be positive for E. coli intramammary infection.

40

A:Control (Saline)

B: Treated (E. coli)

C: Treated (E. coli)

Fig. 1: Cross section of murine mammary gland (A) Saline infused (B & C) E. coli treated Infiltration of neutrophils ( ) and loss of alveoli structure ( ) in the E. coli infected mammary glands are shown by arrows (B & C).

41

Differentially Expressed Genes in Mammary Gland in Response to E. coli.

Data from each raw expression array were normalized for any obscuring variation caused by hybridization, labeling, and other errors caused inadvertently during the hybridization process. The eight arrays were normalized using the RMA procedure in the

R package. The quality of the arrays was found to be good; the density plot (Fig. 2A) and

box plot (Fig. 2B) of the log ratio of all eight arrays were found to have a similar

distribution with a single peak and median of approximately 8 as shown in Figure 2. The

genes involved in the pathogenesis of mastitis, primarily the inflammatory and innate

immune response genes invoked by E. coli in the mammary gland were identified by

comparison of expression profiles between (1) effect of treatment and (2) effect of

treatment and time. Of the 22,690 genes evaluated from the array set, 1575 genes were

determined as differentially expressed genes that had a P-value ≤ 0.034 for treatment

effect and treatment and time effect. The list of gene group that are significantly

expressed based on linear mixed-effect-analysis of variance is provided in Table 1 and

the complete list of differentially expressed genes are given in appendix A. A

representative set of 19 of the differentially expressed genes based on statistical analysis

were further validated by Q-PCR. The genes included in this sample had a t-test P-value

≤ α empirical threshold P-value, a fold-signal expression ≥1.1 or ≤0.9 (raw expression

data E. coli/saline), or based on biological relevance for immune/inflammatory response.

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Fig. 2A: Density plot: Perfect match and mismatch probes for 22,690 genes. The log ratio of eight arrays have a single peak at value of 8 and similar spread indicating similar distribution of signal intensity. 24h 48h

Fig. 2B: Box plot: Perfect match and mismatch probes for 22, 690 genes. Median of box plot for all eight arrays is around value of eight with similar spread indicting the signal intensities are similar among the arrays. The log-intensity is shown on y-axis.

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Table 1: List of differentially expressed genes between uninfected and E. coli infected mammary tissue classified on their molecular function in the disease process.

Number of Differentially Expressed Gene Group Genes Acute-phase response 6 Angiogenesis 10 Apoptosis and anti-apoptosis 32 Apoptosis pathway 5 Antigen presentation, exogenous antigen 2 B-cell differentiation and activation 4 Bone morphogenetic protein signaling pathwway 4 Calcium transport and calcium ion homeostasis 15 Carrier activity 11 Cell events 133 Cell surface receptor linked signal transduction 10 Chemokine activity 9 Chemotaxis 9 Chloride transport 5 Complement activation 6 Cytokine activity 28 Cytokine and chemokine mediated signaling pathway 1 DNA repair 16 Electron transport activity 30 Endocytosis 5 Epidermal differentiation 1 Frizzled signaling pathway 3 G-protein coupled receptor protein signaling pathway 35 GTP binding 30 Heat shock protein activity 5 Hyaluronic acid binding 2 Humoral immune response 1 I-kappa B phosphorylation 1 Immune response 26 Inflammatory response 17 Inflammatory response pathway 9 Insulin receptor signaling pathway 3 Integrin-mediated signaling pathway 4 Intracellular signaling cascade 39 Inositol/phosphatidylinositol kinase/phosphatase activity 5 Interleukin receptor activity 11 JAK-STAT, JNK, MAPK, MAPKKK cascade 10 Leukotriene biosynthesis-metabolism 1 MAPK activation 8 mRNA processing and splicing 12 NIK-I-KappaB/NF-KappaB cascade 2

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Table 1: Contd Oxidoreductase activity 52 Oxygen transport 2 Phagocytosis 1 Protein tyrosine/serine/threonine kinase/phosphatase activity 48 Proteolysis and peptidolysis 35 Oxidative stress 14 Rho protein signal transduction 3 RNA processing and splicing 4 Scavenger receptor activity 2 Signal transduction 77 TGF beta receptor/ signaling pathway 8 Transcription factor activity related 108 Translation factors 8 Transmembrane receptor prtein tyrosine phosphatase signal pathway 3 tRNA processing and splicing 2 Tumor necrosis factor receptor binding/activity 4 Ubiquitin-dependent protein catabolism and ubiquitin cycle 13 Wnt receptor/signaling pathway 16

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Table 2: Validation of differentially expressed immune related candidate genes for mastitis by Q-PCR Pa Pa Fold- Fold- Timed Fold- Vali- Gene Selection Criteriac treat treat*time 24hb 48hb tested QPCRe dationf Daf1 0.0094 0.0022 1.1 1.3 Anova, up regulated at 48h 48h 1.0 ±0.05 no Mtpn 0.0723 0.0014 1.0 1.4 Anova, up regulated at 48h 48h 0.9 ±0.40 ? Icos 0.4124 0.0058 1.0 0.8 Anova, down regulated at 48h 48h 0.9 ±0.06 no Cd2 0.0066 0.0021 1.1 0.9 Anova, down regulated at 48h 48h 0.9 ±0.06 no Tccr 0.0099 0.1487 0.9 0.9 Anova, down reg. at 24h & 48h 48h 1.1 ±0.28 ? Epgn 0.0272 0.0071 0.9 0.7 Anova, down regulated at 48h 48h 1.2 ±0.07 ? Klf15 0.0090 0.0096 0.8 1.1 Anova, down regulated at 24h 24h 0.6 ±0.05 yes Tlr4 0.0343 0.2163 1.1 1.1 Anova, up regul. at 24h and 48h 24h 1.6 ±0.03 yes Ncf1 0.3698 0.9802 1.1 1.1 Dis. biol., up regul. at 24h & 48h 24h 2.2 ±0.05 yes Cybb 0.0170 0.9215 1.2 1.2 Anova, up regul. at 24h and 48h 24h 2.5 ±0.08 yes Myd88 0.0008 0.0007 1.2 0.9 Anova, up regulated at 24h 24h 0.9 ±0.06 ? Fbln5 0.0006 0.0008 1.2 1.0 Anova, up regulated at 24h 24h 1.9 ±0.13 yes Ikbkb 0.0074 0.0250 1.2 1.0 Anova, up regulated at 24h 24h 1.4 ±0.06 no Icam1 0.0022 0.0057 1.5 1.1 Anova, up regulated at 24h 24h 3 ±0.21 yes Il1b 0.0322 0.0779 1.7 1.1 Anova, up regulated at 24h 24h 6.2 ±0.32 yes Cspg2 0.0028 0.0064 1.9 1.0 Anova, up regulated at 24h 24h 2.8 ±0.07 yes Il6 0.0240 0.0366 1.9 0.9 Anova, up regulated at 24h 24h 7.6 ±1.9 yes Socs3 0.0031 0.0086 2.1 1.1 Anova, up regulated at 24h 24h 2.2 ±0.17 yes Cxcl2 0.0031 0.0054 6.2 0.9 Anova, up regulated at 24h 24h 10.9 ±0.67 yes a P-value for t-test from LME-ANOVA of gene expression score. bFold of gene expression (E. coli/saline) based on raw expression score from microarray data. cGenes selected for gene validation had any of these attributes: P-value ≤0.0347, fold expression ≥1.1 or ≤0.9, or disease biology (inflammatory/immunity response) relevance. dQuantitative real-time PCR (Q-PCR) was performed using RNA isolated frommammary tissues (E. coli and saline treated) sampled at either 24 hr or 48 hr post injection. eRelative quantity of mRNA measured using Q-PCR and the comparative Ct method (Applied Biosystems, CA). fA gene was considered as validated if it had a Fold-qpcr ≥1.5 or ≤0.8; genes with “?” indicates that the Fold-qpcr result was in disagreement with the fold gene expression observed in the microarray study. From the differentially expressed genes declared in the microarray study, approximately 57.9% of these genes were validated as differentially expressed genes using Q-PCR.

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Hierarchical Cluster Analysis

Hierarchical cluster analysis was performed using expression scores (log2 transformed, background corrected and normalized data) for the genes that were declared as differentially expressed using results from the LME-ANOVA. Cluster analysis was performed using the computer program Gene Cluster version 3.0 and applying the options for Euclidean distance and centroid linkage (Eisen et al., 2002) (Fig. 3). The clustering of gene expression data groups genes of similar function. The co-expression of genes of known function with poorly characterized or novel genes provides clues to the function of novel genes (Eisen et al., 1998). Clusters of genes with node correlation r ≥0.92 were used as input for putative function to identify the function of differentially co-expressed genes whose functions are unknown.

Fig. 3: Differentially expressed genes of unknown function co-expressed with genes of known function with gene node correlation r=0.92 Colors red, green and black indicate genes upregulated, downregulated and neutral in expression level between E. coli and saline treated mammary tissues.

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DISCUSSION

This microarray analysis demonstrates the feasibility of studying differential expression of many genes involved in the biological pathways associated with the intramammary defense mechanism responding to Gram-negative bacteria. The current study compared the mRNA expression pattern in E. coli infected and saline control mammary glands from mice. Several studies illustrate the power of gene expression profiling in the identification of susceptibility genes for complex diseases. For example, a combination of QTL analysis in conjunction with microarray analysis led to the identification of the gene encoding complement factor 5 (C5) as a susceptibility locus for experimentally induced allergic asthma (Karp et al., 2000). Similarly, it may be possible

to identify the underlying cause of susceptibility to complex diseases like mastitis in

bovine species.

In this exploratory study 22,690 mouse genes were evaluated, 1575 were declared

as differentially expressed genes based on a LME-ANOVA statistical test. A significant number of differentially expressed genes were involved in inflammation, innate immune response and/or apoptotic pathways as shown in Table 1. Based on differentially expressed gene patterns, our data add new insights into the biological pathways involved in the intramammary gland defense mechanism to Gram-negative bacteria. The results of previous studies on LPS-associated gene expression in mammary epithelial cells are in agreement with the present findings. Cytokines play key roles in the host innate immune response to mastitis pathogens (Bannerman et al., 2004). Similar to our results, induction of interleukin-6 (IL-6) and CXCL5 chemokine that are potent chemoattractants for neutrophils were found by Pareek et al. (2005) to be differentially expressed in LPS-

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challenged mammary cells. As reported by Schwerin et al. (2003) genes related to acute phase response like serum amyloid A (SAA3) and inflammatory marker related genes were found to be differentially expressed in the mouse model of mastitis. This suggests that certain pathways of the host defense mechanism are conserved between mouse and bovine species.

The differentially expressed genes that are statistically significant and validated by Q-PCR can be used for identification of putative candidate genes for mastitis based on mouse-bovine comparative mapping and positional information on QTL’s for mastitis- related traits. The release of the bovine genome sequence will accelerate the identification of candidate genes for mastitis susceptibility. Further, identification of single nucleotide polymorphisms within the candidate genes and development of haplotypes will aid in developing more informative markers that could be used in the

selection breeding program. However, the limiting factor of this study is that the

differentially expressed genes do not significantly represent the genes that are induced in the mammary epithelial cells as the RNA was extracted from whole mammary gland that includes other cell type. Also, the study should be repeated with a larger sample size to confirm the reported findings.

Based on the differential expression data in the reported array analysis and on

biological relevance to the disease process, neutrophil cytosolic factor 1 (NCF-1) also

known as p47-pHOX was identified as a candidate gene for mastitis susceptibility. In

neutrophils, NCF-1 plays an important role in oxygen-dependent intracellular phagocytosis exhibited by neutrophils. NCF-1 is one among the five glycoprotein

subunits of the NADPH oxidase complex that contributes to cellular superoxide

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production (Shao et al., 2003; Vilhardt et al., 2004). In humans, a dinucleotide deletion of

GT in exon 2 of the p47-pHOX gene results in autosomal recessive chronic granulomatous disease (CGD) (Noack et al., 2001). CGD is an immunodeficiency disease where the neutrophil’s phagocytic activity is impaired due to its inability to produce reactive oxygen species (Heyworth et al., 2003). Patients with CGD show increased susceptibility to severe bacterial and fungal function (Heyworth et al., 2003). The

primary defense mechanism of the bovine mammary gland is mediated by neutrophils

(Paape et al., 2003). NCF-1 could be a candidate gene for mastitis since it does have a

role in one of the first defense mechanism mediated by phagocytotic cells. Identification

of SNP’s within the coding region of NCF-1 was undertaken. Based on a case-control

association study, a SNP was identified that caused a non-synonymous substitution in the

coding region of the NCF-1 gene associated with the clinical mastitis trait (Dr. Vallejo,

unpublished data). A dysfunction in the activity of bovine neutrophils like in CGD

disease, could be a predisposing factor for mastitis susceptibility.

Complex traits like mastitis result from multiple interacting genes located

throughout the genome. Micrarray based gene expression profiles aids in simultaneously

scanning marker loci that could play a causative role in disease susceptibility. This

exploratory study strongly suggests that positional and functional candidate gene

approaches would be a powerful tool for identification and cloning of candidate genes

with underlying QTL effects related to bovine mastitis.

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Anderson, J.C., and Craven, N. 1984. Recruitment of neutrophils by an encapsulated coagulase-negative strain of Staphylococcus simulans in the mammary gland of the mouse. J Leukoc Biol 36:633-645. Bannerman, D.D., Paape, M.J., Lee, J.W., Zhao, X., Hope, J.C., and Rainard, P. 2004. Escherichia coli and Staphylococcus aureus elicit differential innate immune responses following intramammary infection. Clin Diagn Lab Immunol 11:463- 472. Brouillette, E., Talbot, B.G., and Malouin, F. 2003. The fibronectin-binding proteins of Staphylococcus aureus may promote mammary gland colonization in a lactating mouse model of mastitis. Infect Immun 71:2292-2295. Collins, F.S. 1995. Positional cloning moves from perditional to traditional. Nat Genet 9:347-350. Eisen, M.B., Spellman, P.T., Brown, P.O., and Botstein, D. 1998. Cluster analysis and display of genome-wide expression patterns. Proc Natl Acad Sci U S A 95:14863- 14868. Erskine, R.J., Tyler, J.W., Riddell, M.G., Jr., and Wilson, R.C. 1991. Theory, use, and realities of efficacy and food safety of antimicrobial treatment of acute coliform mastitis. J Am Vet Med Assoc 198:980-984. Garcia, V., Gomez, M., Iglesias, M., Sanjuan, N., Gherardi, M., Cerquetti, M.C., and Sordelli, D. 1996. Intramammary immunization with live-attenuated Staphylococcus aureus: microbiological and immunological studies in a mouse mastitis model. FEMS Immunol Med Microbiol 14:45-51. Heringstad, B., Klemetsdal, G., and Ruane, J. 1999. Clinical mastitis in Norwegian cattle: frequency, variance components, and genetic correlation with protein yield. J Dairy Sci 82:1325-1330. Heyworth, P.G., Cross, A.R., and Curnutte, J.T. 2003. Chronic granulomatous disease. Curr Opin Immunol 15:578-584. Holmberg, M., and Andersson-Eklund, L. 2004. Quantitative trait loci affecting health traits in Swedish dairy cattle. J Dairy Sci 87:2653-2659. Ihaka, R., and Gentleman, R. 1996. R: A language for data Analysis and Graphics. . J. Comput. Graph. Statistics. 5:299-314. Karp, C.L., Grupe, A., Schadt, E., Ewart, S.L., Keane-Moore, M., Cuomo, P.J., Kohl, J., Wahl, L., Kuperman, D., Germer, S., et al. 2000. Identification of complement factor 5 as a susceptibility locus for experimental allergic asthma. Nat Immunol 1:221-226. Klungland, H., Sabry, A., Heringstad, B., Olsen, H.G., Gomez-Raya, L., Vage, D.I., Olsaker, I., Odegard, J., Klemetsdal, G., Schulman, N., et al. 2001. Quantitative trait loci affecting clinical mastitis and somatic cell count in dairy cattle. Mamm Genome 12:837-842. Lockhart, D.J., and Winzeler, E.A. 2000. Genomics, gene expression and DNA arrays. Nature 405:827-836. Madsen, S.A., Weber, P.S., and Burton, J.L. 2002. Altered expression of cellular genes in neutrophils of periparturient dairy cows. Vet Immunol Immunopathol 86:159-175.

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Noack, D., Rae, J., Cross, A.R., Ellis, B.A., Newburger, P.E., Curnutte, J.T., and Heyworth, P.G. 2001. Autosomal recessive chronic granulomatous disease caused by defects in NCF-1, the gene encoding the phagocyte p47-phox: mutations not arising in the NCF-1 pseudogenes. Blood 97:305-311. Paape, M.J., Bannerman, D.D., Zhao, X., and Lee, J.W. 2003. The bovine neutrophil: Structure and function in blood and milk. Vet Res 34:597-627. Pareek, R., Wellnitz, O., Van Dorp, R., Burton, J., and Kerr, D. 2005. Immunorelevant gene expression in LPS-challenged bovine mammary epithelial cells. J Appl Genet 46:171-177. Pighetti, G.M. 2006. Selecting for disease resistance: fact or fiction? In NMC Annual Meeting Proceedings. Florida. 97-102. Schmitz, S., Pfaffl, M.W., Meyer, H.H., and Bruckmaier, R.M. 2004. Short-term changes of mRNA expression of various inflammatory factors and milk proteins in mammary tissue during LPS-induced mastitis. Domest Anim Endocrinol 26:111- 126. Schrooten, C., Bovenhuis, H., Coppieters, W., and Van Arendonk, J.A. 2000. Whole genome scan to detect quantitative trait loci for conformation and functional traits in dairy cattle. J Dairy Sci 83:795-806. Schulman, N.F., Viitala, S.M., de Koning, D.J., Virta, J., Maki-Tanila, A., and Vilkki, J.H. 2004. Quantitative trait Loci for health traits in Finnish Ayrshire cattle. J Dairy Sci 87:443-449. Schwerin, M., Czernek-Schafer, D., Goldammer, T., Kata, S.R., Womack, J.E., Pareek, R., Pareek, C., Walawski, K., and Brunner, R.M. 2003. Application of disease- associated differentially expressed genes--mining for functional candidate genes for mastitis resistance in cattle. Genet Sel Evol 35 Suppl 1:S19-34. Shao, D., Segal, A.W., and Dekker, L.V. 2003. Lipid rafts determine efficiency of NADPH oxidase activation in neutrophils. FEBS Lett 550:101-106. Shook, G.E. 1989. Selection for disease resistance. J Dairy Sci 72:1349-1362. Vilhardt, F., and van Deurs, B. 2004. The phagocyte NADPH oxidase depends on cholesterol-enriched membrane microdomains for assembly. Embo J 23:739-748. Zhang, Q., Boichard, D., Hoeschele, I., Ernst, C., Eggen, A., Murkve, B., Pfister- Genskow, M., Witte, L.A., Grignola, F.E., Uimari, P., et al. 1998. Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred pedigree. Genetics 149:1959-1973.

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CHAPTER 3

SINGLE NUCLEOTIDE POLYMORPHISMS AND HAPLOTYPES WITHIN

THE BOVINE BACTERICIDAL/PERMEABILITY-INCREASING PROTEIN:

A CANDIDATE GENE FOR MASTITIS

INTRODUCTION

In current breeding programs, dairy cows are selected for production traits such as milk yield, which is negatively correlated with mastitis resistance (Shook, 1989).

Therefore, recent research has focused on association studies between mastitis-related traits and genetic variation in immune-related genes that modulate the pathophysiological impacts on the mammary gland during disease (Kelm et al., 1997). Other studies have reported genetic variation in immunocompetence of the neutrophil functions that influence host resistance mechanisms to mastitis (Kehrli et al., 1991; Youngerman et al.,

2004). Identification of informative markers that establish the genetic basis for variation in susceptibility to mastitis would aid in its utilization in the marker assisted selection program of dairy cows (Pighetti, 2006).

Mastitis is an inflammatory disease where innate immunity provides the first line of defense against infection (Bannerman et al., 2004). Recognition of molecular pathogens by the innate immune system is mediated through a limited number of monoclonal, germline-encoded receptors conserved through evolution. Further, activation of antigen-specific adaptive immunity is mediated through signals induced by the innate immune system (Medzhitov and Janeway, 2000; Akira et al., 2001). TLR-4 (Toll-like

Receptor) mediated signal transduction in response to LPS (Lipopolysaccharide), a

53

glycolipid that is specific to the cell wall of Gram-negative bacteria is the best studied.

LBP (Lipopolysaccharide binding protein) and CD14 are the two molecules of the innate immune system that contribute to host recognition of pathogen (Wright et al., 1990;

Schumann and Latz, 2000).

Bactericidal Permeability Increasing (BPI) protein binds and neutralizes LPS and

kills Gram-negative bacteria (Marra et al., 1993; Elsbach et al., 1979). BPI acts as a

regulatory molecule by down-regulating the host immune pro-inflammatory response to

LPS (Marra et al., 1993). The N-terminal region of BPI is known to exhibit LPS-

neutralization and antibacterial activity (Ooi et al., 1991). Recombinant BPI protein

(rBPI) and synthetic peptides derived from the functional domain of BPI are shown to

have antibacterial and LPS-neutralizing activity both in vitro and in vivo (Elsbach and

Weiss, 1998; Jiang et al., 2004). The bovine BPI mature protein is 456 aa in size that is mapped to bovine chromosome bTA13. This region encompasses a putative QTL

(quantitative trait locus) for milk SCS (somatic cell score), a trait correlated with mastitis

(Zhang et al., 1998).

In humans, genetic variation in the genes of the innate immune system has an important role in susceptibility to a variety of inflammatory diseases including asthma

(Umetsu and Dekruyff, 1999), systemic lupus erythematosus (Gibson et al., 2001) and atherosclerosis (Ross, 1999). Genetic variation in the human BPI gene has been studied for association with Crohn’s disease and Gram-negative sepsis (Hubacek et al., 2001;

Klein et al., 2005). An extended-twin study in humans has shown that heritability estimates for genes of innate immunity like IL-1ra, IL-6, IL-10, TNF-α, and IL-1β varies between 53% and 86 % (de Craen et al., 2005). Nearly 25% of dairy cows showing

54

clinical mastitis due to Gram-negative bacteria either die or are culled due to development of bacteremia and sepsis. BPI protein demonstrates bactericidal activity against Gram-negative bacteria and consequently is a gene with a potential role in innate immunity. Lazarus et al. (2002) studied genetic variation in human innate immunity genes, including BPI in various ethnic groups. They found abundant variation in the gene that may effect susceptibility to human inflammatory response based diseases. In this study, we hypothesize that genetic variation in bovine BPI encoding for the functional N- terminal region of mature protein alters the susceptibility of the cow to Gram-negative intramammary infection and sepsis. Single nucleotide polymorphisms (SNPs) within the

BPI gene were identified and tested for association with SCS that is correlated with mastitis susceptibility.

MATERIALS AND METHODS

Resource Population and Recorded Phenotypic Trait

Genomic DNA (isolated from semen) from ninety-six sires from the Beltsville

Agricultural Research Centre (BARC) Dairy Cattle Panel ver. 1.0 (Tad Sonstegard, personnel communication) served as the animal resource to identify SNPs within the BPI

candidate gene for mastitis. The panel included elite sires from Holstein (n=85), Jersey

(n=7), Brown Swiss (n=2) and Guernsey (n=1) breeds used extensively in the current

artificial insemination breeding program of U.S. dairy cattle. The daughter yield

deviation for SCC was the phenotypic trait used for the association study. The sire data

was provided by the Animal Improvement Programs Laboratory of USDA-ARS for the

association studies.

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PCR Amplification of BPI Exons

The genomic sequence of bovine BPI (bBPI) was retrieved from the Genebank database by blast search against the bBPI cDNA sequence (Genebank Accession no,

NM173895). Forward and reverse primers were designed (Primer3 output program,

Whitehead Institute, MA) for first five exons from the bovine genomic DNA for the BPI locus (Trace Archive # 38220112 for exon 1 and Btau_1.0: Scaffold135164 for exon 2 through 5) to amplify the genomic region encoding for the N-terminus of the BPI protein.

The primers were designed to include the sequences corresponding to exon/intron splice junctions. The primer sequence and the amplicon size for the five exons are given in

Table 1. Each PCR reaction was carried out in a volume of 11 µl containing 1 µl of

genomic DNA (10 µg/ µl), 0.05 µl of 100 µM of forward and reverse primer, 9 µl of

1.1x thermo-start PCR master mix (cat no AB-0938-25, Abgene, UK) and 0.9 µl of

nuclease free water. PCR cycling conditions consisted of an initial denaturing step at 94

ºC for 15 min, followed by 30 cycles of a denaturation at 94 ºC for 1 min, annealing at

63 ºC for 30 sec (65 ºC for exon IV and V) and extension at 72 ºC for 1 min. A final

extension step at 72 ºC for 5 min was incorporated prior to a final hold at 4 ºC. After each

PCR reaction, the amplicons were verified for their size by electrophoresis on a 1%

agarose gel run at 60V for 40 min.

Characterization of SNPs by Direct DNA Sequencing

The amplicons were purified using a Montage PCR96 clean-up kit (Cat #

MANU03050, multiscreen PCR, Millipore, MA) following the manufacturer’s instructions and reconstituted in 50µl of nuclease free water. The concentration was determined in an ND-1000 spectrophotometer. The concentration of template DNA for

56

BigDye terminator cycle sequencing ready reaction was determined based on the amplicon size (15-30 ng for product range from 300bp to 600bp). The appropriate

volume of template was vacuum dried and the sequencing reaction was executed in a

total volume of 5 µl. The reaction consisted of 2 µl of either forward or reverse primer

(1.6 pM/ µl), 1.8 µl of 5x buffer, 0.2 µl of BD enzyme V.1.1 (Part no. 4303152 Applied

Biosystems, CA) and 1 µl of nuclease-free water. The sequencing reaction condition

consisted of initial denaturation at 96 ºC for 1 min, followed by 25 cycles of a denaturing

step at 96 ºC for 10 sec, 50 ºC for 5 sec, 60 ºC for 4 min. Following the cycling, a final

extension at 60 ºC for 1 sec was done prior to a final hold at 4 ºC. The products were then

purified by ethanol precipitation. Briefly, the 96 well plates were given a quick spin and

20 µl of 70% isopropanol were added to each well to precipitate the dye-labeled PCR products. The plates were spun at 2160 g for 15 min and the supernatant was removed

followed by a quick spin. The precipitated amplified products were washed with 20 µl of

70% ethanol. Following removal of ethanol, the sequencing reaction products were

reconstituted in deinonized formamide and sequenced by an ABI 3730 DNA Analyzer at

the Bovine Functional Genomics Laboratory, USDA-ARS Beltsville, MD. For identification of SNPs the sequence data were analyzed using Chromas 2.31

(Technelysium, Australia) and Lasergene 5 (DNASTAR, WI). Identification of the signal peptide sequence for BPI gene was carried by using the signalP 3.0 server (Technical

University of Denmark, DK).

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Table 1: Forward and reverse primer sequence and product size for the five exons of bovine BPI gene.

Amplicon bBPI exon bBPI PRIMER (bp) Ex1F:CTCGAGGTTTTGGCAGCTCT 1 Ex1R: GCCCAGCTTCTTGCTCTGTA 300 Ex2F: ATCGGGACATTGACAAGAGC 2 Ex2R: TAAGGGCTTGGCACAGAGTT 481 Ex3F:GGCCAGGATCACACAAAAGT 3 Ex3R:AAAAATTCGGCATGCTTGAG 312 Ex4F:AGAGGCTGAGGCAGTGGATA 4 Ex4R:GCAGGAGATGTGGGTTCAAT 621 Ex5F:AAGCAGAGGACACAGGAGGA 5 Ex5R:GCTGTAGGGGACTGCTGAAG 586

Statistical Analysis

Analysis of the data for association between the marker (SNP haplotype or SNP allele) and the phenotypic trait (SCS) was performed (Dr.Van Tassell, USDA-ARS) using a mixed linear model that included random animal effect and a fixed genotypic effect. Variance component estimates and solutions to the mixed model equations were

obtained by multiple trait derivative-free restricted maximum likelihood (MTDFREML;

Boldman et al., 1995).

The mixed linear model used for variance component and effect estimation was

h DYDi,j=µ i +∑ p j,k β i,k + e i,j , k1=

Where DYDi,j is the Daughter Yield Deviation (DYD) for trait i and bull j, µi is

the mean of trait i, pj,k is the allele or haplotype at SNP locus or haplotype k, βi,k is the regression that estimates ai,k, half the difference between the two homozygotes, for trait i,

and ei,j is a random residual. It should be noted that ai also corresponds to the average

effect of an allele substitution in the absence of a dominance effect. Because DYD are a

58

function of additive genetic effects, the dominance deviation is assumed to be null, and

then aˆ i was the estimate of the substitution effect. Using the standard distribution of

MTDFREML, the residuals are assumed to be independently and identically distributed.

RESULTS

Identification of SNPs within bovine BPI gene

A total of six SNPs (Table 2) were identified within the bovine BPI (bBPI)

mRNA sequence corresponding to the N-terminal region of the mature protein (first five

exons). Three SNPs were located within exon I [+61 (G/A), +93 (T/C), +126 (C/T)], two

SNPs were within exon II [+162 (A/G), +168 (A/G)] and one SNP was within exon IV of

bBPI at positions [+446 (C/T)]. These were identified relative to the available mRNA

sequence from the start codon (Genebank accession no. NM173895). A “C/T” polymorphism was identified at four intronic loci, one each within intron I and III, and two within intron II, relative to the available genomic sequence (Btau 1.0:

Scaffold135164). BlastX (Biology workbench V3.2) analysis of the corresponding amino acid sequence revealed a non-synonymous substitution at +61 (G/A) (Fig. 1) resulting in change of glycine to serine at the amino acid residue 21 (G21S), which lies within the 26 amino acid putative signal peptide for the BPI gene (Leong and Camerato, 1990). The five other polymorphisms that occurred within the introns and exons resulted in synonymous substitutions. The analysis was restricted to the Holstein breed because the sample numbers for the other three breeds were significantly low.

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Table 2: Single nucleotide polymorphisms identified within the bovine BPI gene.

SNP No. Position Substitution Type of Mutation 1 Exon I +61 G→A Non-synonymous (G to S) 2 Exon I +93 T→C Synonymous 3 Exon I +126 C→T Synonymous 4 Intron I C→T 5 Exon II +162 G→A Synonymous 6 Exon II +168 G→A Synonymous 7 Intron II C→T 8 Intron II C→T 9 Intron III C→T 10 Exon IV +446 C→T Synonymous

Fig 1: Chromatogram of bBPI gene exon I sequenced with reverse primer. Arrow points to mutation in exon I causing amino acid substitution from glycine to serine (G21S).

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Determination of haplotype frequencies

The eight polymorphisms identified within the genomic region corresponding to the N-terminal region of mature bBPI protein were considered for haplotype analysis using Phase program (Dr. Lakshmi Kumar, USDA). Markers at +162 and +168 in exon 2 were excluded from haplotype analysis as they weren’t informative. A total of fifteen haplotypes were predicted from eight markers using the Phase program (Table 3). Among these 90% of total expressed haplotypes were from three haplotypes in the order of

ACCCTTTT (#5), GTCCTCTT (#7), and ACTTCCCC (#2). The first eight haplotypes

(Table 3) that are more frequent in the population were studied for association using

MTDFREML. No association (t =2) was found between the haplotypes or single marker allele at +61 and the phenotype (SCS daughter yield deviation).

Table 3: Estimated bBPI haplotype frequencies for SNPs for BPI gene in Holstein dairy breed. Haplotype Haplotype frequency Number Haplotype (n=85) 1 A-C-T-C-C-C-C-C 0.0060 (± 0.0019) 2 * A-C-T-T-C-C-C-C 0.2200 (±0.0020) 3 A-C-C-C-C-C-C-C 0.0030 (±0.0029) 4 A-C-C-C-T-T-T-C 0.0020 (±0.0030) 5 * A-C-C-C-T-T-T-T 0.3400 (±0.0033) 6 G-T-C-C-C-C-C-C 0.0700 (±0.0029) 7 * G-T-C-C-T-C-T-T 0.3200 (±0.0043) 8 G-T-C-C-T-T-T-T 0.0050 (±0.0031) 9 A-C-T-T-T-C-T-T 0.0001 (±0.0008) 10 A-C-C-C-T-C-C-C 0.0004 (±0.0016) 11 A-C-C-C-T-C-T-T 0.0002 (±0.0011) 12 A-C-C-C-T-T-C-C 0.0020 (±0.002) 13 G-T-C-C-C-T-C-C 0.0010 (±0.0027) 14 G-T-C-C-T-C-C-T 0.0001 (±0.0008) 15 G-T-C-C-T-C-T-C 0.0030 (±0.0029) The standard errors are given in parentheses. * indicates the three haplotypes that represent 90% frequency of the total haplotypes expressed in the population.

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Characterization of Functionality for the Identified SNPs

Prediction of signal peptide

Analysis of the corresponding amino acid sequence from bBPI exon I suggested that amino acid residues 1 through 26 code for a signal peptide sequence. The most likely cleavage site is located between amino acid position 26 and 27. This is in agreement with the putative signal peptide sequence reported by Leong and Camerato (1990). The data also indicated that the maximum score (S-score) for the corresponding amino acid which is part of a signal peptide shifted from position 20 (Lysine) to position 21 (Serine) when glycine at position +21 was mutated to serine (Fig. 2 A&B).

Significance of C/T Polymorphism within Exon I 3' Splice Site

Comparison of DNA sequence of Exon I with the cDNA sequence of bBPI

predicted that the C/T polymorphism at +126 lies within the splice site at 3' end of exon I.

Analysis of the corresponding sequence (Exon I/ Intron I) of bBPI gene using

bioinformatics workbench (Alternative Splicing Workbench, European Bioinformatics

Institute) predicted that the C/T polymorphism at this position resulted in the loss of a

binding site for SR (Serine/Arginine) protein; SR 9GB, with a high motif score value of

7.592. The binding site for SR 9GB is shown in bold, the polymorphic site is indicted by

an arrow, and the sequence from exon I and intron I are shown in capital and small

letters, respectively. The C/T polymorphism also concurrently introduces a motif for an

exonic silencer sequrnce TGGT in the mutant.

Normal GGGCCTGGACTACGgtaact

Mutant GGGCCTGGACTATGgtaact

62

Fig. 2A: SignalP prediction of signal peptide sequence for glycine at position +21. The maximum S-score value of 0.977 was at position 20. The most likely cleavage site for signal peptidase enzyme lies between position 26 and 27: VTT-TN. Arrow indicates the signal peptide cleavage site.

Fig. 2B: SignalP prediction of signal peptide sequence for serine at position +21. The maximum S-score value of 0.978 was at position 21. The most likely cleavage site for signal peptidase enzyme lies between position 26 and 27: VTT-TN. Arrow indicates the signal peptide cleavage site.

63

DISCUSSION

Traditional selection methods for udder traits, SCS, milking speed, etc., have improved mastitis resistance among dairy cows, but their application is limited due to low

heritability and moderate correlation with the mastitis trait (Pighetti, 2006). Haplotypes

are groups of alleles of SNPs along the chromosome that are rarely separated by

recombination and inherited as a unit (Crawford and Nickerson, 2005). Haplotype

mapping can be utilized for fine mapping of disease genes of unknown loci. In the

present study a direct candidate gene approach was taken to identify SNPs within bBPI

and evaluating them for possible association of marker alleles with mastitis related traits.

The bBPI gene was found to be highly polymorphic. Six polymorphisms were found in

the five exons encoding for the N-terminal region of mature BPI protein. An additional

four polymorphisms were found in the introns (Table 2). Two SNPs identified within

exon 2 (+ 93 and + 126) were excluded from haplotype analysis as they were not

informative. The polymorphism (G/A) at +61 relative to the available mRNA sequence

from the start codon resulted in an amino acid change from glycine to serine, resulting in

a missense mutation in the leader peptide sequence of BPI gene. Missense and nonsense

mutations are likely to affect the protein function and are frequently associated with

single gene disorders (Botstein and Risch, 2003).

Selection of dairy cows for mastitis resistance is currently not feasible in the U.S.

dairy industry due to lack of records of clinical mastitis occurrences. This is a limiting

factor in determining direct association between genetic markers and clinical mastitis.

SCS has been included in the selection process against mastitis as low SCS is associated

with a low incidence of mastitis (Shutz, 1994; Shook and Schutz, 1994). SCS and clinical

64

mastitis are positively correlated ranging from 0.3- 0.7 (Rupp and Boichard, 1999). A study by Nash et al. (2002) has shown that low SCS is associated with less severity and less clinical episodes of mastitis from environmental organisms. The study was conducted with the data recorded for first lactation in dairy cows. In the present study, no association was found between the haplotypes or marker allele at +61 position and SCS,

which serves as indicator of mastitis. Lack of significant association between the marker

and phenotype could be due to small sample size. Hence, we propose to genotype for the

marker allele at +61 position in a sample size of 2300 belonging to four half-sib families.

Also, it would be more appropriate to test for association in case-control samples for

mastitis, with a clinical record of microbial causative agents. It is reported that a direct

record of clinical mastitis along with SCS is effective in identifying genetic variation for

mastitis susceptibility (Odegard and Klemetsdal, 2003).

The leader peptide sequence is important in intracellular trafficking and export of

proteins to their final destination both in prokaryotic and eukaryotic systems (Hardy and

Randall, 1989; Kjeldsen et al., 1999). Studies in E. coli and bacteriophage M13 have

shown that the amino acids at -6, -3 and -1 are part of an essential recognition cleavage

site for the leader peptidase. In procoat mutants of phage M13 with a single amino acid

substitution at -6 (Pro to Ser), the proteins were not processed to the mature form (Kuhn

and Wickner, 1985). Using simulated molecular evolution techniques (SME) and in vivo

studies, it has been established that the amino acid at position is predominant as a

recognition site for the cleavage peptidase (Laforet and Kendall, 1991; Schneider and

Wrede, 1994). Comparison of prokaryotic leader and eukaryotic leader sequences shows

that the α-helical hydrophobic core of the leader sequence of many pre-proteins is

65

terminated at residues -6 to -4 by a strong helix-breaking residue such as proline or

glycine (glycine is an ideal residue at -6 position) (Perlman and Havorson, 1983;

Schneider and Wrede, 1994). In the present study, the bBPI mutation from Gly to Ser is

found at -6 position to that of the cleavage site (VTT-TN) a indicated by arrow (Fig 2 A

& B). Hence, this mutation could significantly affect the processing of mature bBPI

protein. In vitro protein expression for the two genotypes (AA/GG) at this polymorphic

site would confirm the significant functional role of the mutation in trafficking and

processing of BPI protein.

A mutation in leader sequence of interleukin 10 (IL-10) has been associated with

Crohn's Disease in human subjects. A Gly15Arg substitution in IL-10 caused decreased

IL-10 secretion thereby reducing its anti-inflammatory effect as observed in Crohn’s

disease (van der Linde et al., 2003). Similarly, the mutation Gly21Ser identified here in

bBPI may cause reduced and/or lack of BPI secretion. This could enhance the pro-

inflammatory response in the mammary gland. The binding of bBPI with LPS results in

down regulation of the pro-inflammatory response in the host (Marra et al., 1993). It is

possible that there exists a natural selection in the bovine species for this mutation; as a

mechanism to arrest the bacterial growth by eliciting an exaggerated pro-inflammatory response.

Based on the existing literature, this is the first study to repot the Gly21Ser substitution in the leader sequence of a protein in eukaryotes, however several studies have reported Gly→Ser substitutions within mature proteins and their association with human diseases. A single pair substitution at amino acid 284 in CD18 protein results in

Gly→Ser and is associated with leukocyte adhesion deficiency type 1 of moderate

66

severity (Back et al., 1993). Substitution of Gly→Ser at aa 883 in pro alpha 1 chain of type I procollagen introduces a change on the triple helix N-terminal end in individuals

with osteogenesis imperfecta type IV (Lightfoot et al., 1994). Additional reports showing

a Gly→Ser substitution and its association with disease include (1) platelet-type von

Willebrand disease due to G233S in platelet glycoprotein Ibalpha (Matsubara et al.,

2003), (2) 21-hydroxylase deficiency in Brazilian population due to G424S mutation in

CYP21 gene [cytochrome P450] (Billerbeck etal., 1999), (3) association of G204S mutation in myophosphorylase gene with McArdle’s disease (Rubio et al., 1999), and (4) association of G344S mutation in lecithin: cholesterol acetyltransferase (LCAT) gene with LCAT deficiency (Moriyama et al., 1995).

SNPs that occur in regions other than exons are of importance and cause variation in susceptibility to disease in humans. These functional SNPs include polymorphisms in promoter region (Lin et al., 2003), introns (Tokuhiro et al., 2003), and splice sites

(Betticher et al., 1995). Interestingly, the C/T polymorphism in bBPI lies within the 3' splice site of exon 1 at -2 position with respect to splice site (“-“indicate nucleotide position upstream of exon/intron boundary). SR 9GB proteins are involved in regulation and selection of splice sites for alternate splicing in eukaryotic mRNA (Black, 2005). The binding site for SR 9GB in the bBPI sequence is GGACTACG/GT. The C/T polymorphism also concurrently introduces a “TGGT” motif for Exonic Silencer

Sequence ESS in the mutant. This motif has been identified as transcriptional regulator in bovine papillomavirus type 1 (Zheng et al., 2000). It is unknown whether C/T polymorphism at this position causes alteration in splice site and variation in the

67

transcript of the bBPI gene. Therefore, further analysis of transcripts from homozygous cows would determine if there is any alteration in splice site.

In the present study, SNPs were identified within the bBPI gene encoding for the

N-terminal region of bBPI protein. However, no significant association was found

between the haplotypes and single marker allele with the phenotype for mastitis disease

susceptibility. This could be due to small sample size or population stratification. We

propose to genotype the SNPs that could be functional (+61 and +126) in a larger sample

size for association studies. Also, further association studies need to be tested in case-

control samples for mastitis with phenotypic data for causative pathogens, score for

severity of disease and development of sepsis in addition to SCS.

68

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Marra, M.N., Thornton, M.B., Snable, J.L., Leong, S., Lane, J., Wilde, C.G., and Scott, R.W. 1993. Regulation of the response to bacterial lipopolysaccharide by endogenous and exogenous lipopolysaccharide binding proteins. Blood Purif 11:134-140. Matsubara, Y., Murata, M., Sugita, K., and Ikeda, Y. 2003. Identification of a novel point mutation in platelet glycoprotein Ibalpha, Gly to Ser at residue 233, in a Japanese family with platelet-type von Willebrand disease. J Thromb Haemost 1:2198- 2205. Medzhitov, R., and Janeway, C., Jr. 2000. The Toll receptor family and microbial recognition. Trends Microbiol 8:452-456. Moriyama, K., Sasaki, J., Arakawa, F., Takami, N., Maeda, E., Matsunaga, A., Takada, Y., Midorikawa, K., Yanase, T., Yoshino, G., et al. 1995. Two novel point mutations in the lecithin:cholesterol acyltransferase (LCAT) gene resulting in LCAT deficiency: LCAT (G873 deletion) and LCAT (Gly344-->Ser). J Lipid Res 36:2329-2343. Nash, D.L., Rogers, G.W., Cooper, J.B., Hargrove, G.L., and Keown, J.F. 2002. Relationships among severity and duration of clinical mastitis and sire transmitting abilities for somatic cell score, udder type traits, productive life, and protein yield. J Dairy Sci 85:1273-1284. Odegard, J., Klemetsdal, G., and Heringstad, B. 2003. Genetic improvement of mastitis resistance: validation of somatic cell score and clinical mastitis as selection criteria. J Dairy Sci 86:4129-4136. Ooi, C.E., Weiss, J., Doerfler, M.E., and Elsbach, P. 1991. Endotoxin-neutralizing properties of the 25 kDa N-terminal fragment and a newly isolated 30 kDa C- terminal fragment of the 55-60 kDa bactericidal/permeability-increasing protein of human neutrophils. J Exp Med 174:649-655. Perlman, D., and Halvorson, H.O. 1983. A putative signal peptidase recognition site and sequence in eukaryotic and prokaryotic signal peptides. J Mol Biol 167:391-409. Pighetti, G.M. 2006. Selection for disease resistance: Fact or Fiction? NMC Annual Meeting Proceedings:97-102. Ross, R. 1999. Atherosclerosis--an inflammatory disease. N Engl J Med 340:115-126. Rubio, J.C., Martin, M.A., Garcia, A., Campos, Y., Cabello, A., Culebras, J.M., and Arenas, J. 1999. McArdle's disease associated with homozygosity for the missense mutation Gly204Ser of the myophosphorylase gene in a Spanish patient. Neuromuscul Disord 9:174-175. Rupp, R., and Boichard, D. 1999. Genetic parameters for clinical mastitis, somatic cell score, production, udder type traits, and milking ease in first lactation Holsteins. J Dairy Sci 82:2198-2204. Schneider, G., and Wrede, P. 1994. The rational design of amino acid sequences by artificial neural networks and simulated molecular evolution: de novo design of an idealized leader peptidase cleavage site. Biophys J 66:335-344. Schumann, R.R., and Latz, E. 2000. Lipopolysaccharide-binding protein. Chem Immunol 74:42-60. Schutz, M.M. 1994. Genetic evaluation of somatic cell scores for United States dairy cattle. J Dairy Sci 77:2113-2129.

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Shook, G.E. 1989. Selection for disease resistance. J Dairy Sci 72:1349-1362. Shook, G.E., and Schutz, M.M. 1994. Selection on somatic cell score to improve resistance to mastitis in the United States. J Dairy Sci 77:648-658. Tokuhiro, S., Yamada, R., Chang, X., Suzuki, A., Kochi, Y., Sawada, T., Suzuki, M., Nagasaki, M., Ohtsuki, M., Ono, M., et al. 2003. An intronic SNP in a RUNX1 binding site of SLC22A4, encoding an organic cation transporter, is associated with rheumatoid arthritis. Nat Genet 35:341-348. Umetsu, D.T., and DeKruyff, R.H. 1999. Interleukin-10: The missing link in asthma regulation? Am J Respir Cell Mol Biol 21:562-563. van der Linde, K., Boor, P.P., Sandkuijl, L.A., Meijssen, M.A., Savelkoul, H.F., Wilson, J.H., and de Rooij, F.W. 2003. A Gly15Arg mutation in the interleukin-10 gene reduces secretion of interleukin-10 in Crohn disease. Scand J Gastroenterol 38:611-617. 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. Youngerman, S.M., Saxton, A.M., Oliver, S.P., and Pighetti, G.M. 2004. Association of CXCR2 polymorphisms with subclinical and clinical mastitis in dairy cattle. J Dairy Sci 87:2442-2448. Zhang, Q., Boichard, D., Hoeschele, I., Ernst, C., Eggen, A., Murkve, B., Pfister- Genskow, M., Witte, L.A., Grignola, F.E., Uimari, P., et al. 1998. Mapping quantitative trait loci for milk production and health of dairy cattle in a large outbred pedigree. Genetics 149:1959-1973. Zheng, Z.M., Reid, E.S., and Baker, C.C. 2000. Utilization of the bovine papillomavirus type 1 late-stage-specific nucleotide 3605 3' splice site is modulated by a novel exonic bipartite regulator but not by an intronic purine-rich element. J Virol 74:10612-10622.

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CHAPTER 4

EFFICACY OF HUMAN BACTERICIDAL/PERMEABILITY-INCREASING

PROTEIN DERIVED PEPTIDE AGAINST MAJOR GRAM-NEGATIVE

MASTITIS PATHOGENS

INTRODUCTION

Bovine mastitis is a disease of economic importance affecting the dairy industry.

The annual economic loss due to mastitis is estimated to be approximately $2 billion in

the U.S. (NMC, 1999) and $35 billion worldwide (Wellenberg et al., 2002). It is

primarily caused by bacterial infections of the mammary gland (Schalm et al., 1971).

About 40% of the annual clinical cases of mastitis are due to Gram-negative bacteria

(Erskine et al., 1991; Ziv, 1992) and 25% of these cases result in death or culling

(Erskine et al., 1991). The most common Gram-negative intramammary pathogens are

the coliforms, which include E. coli, Klebsiella spp., and Enterobacter spp., and non-

coliforms such as Serratia marcescens and Pseudomonas aeruginosa (NMC, 1999).

Nearly one-third of the clinical cases of mastitis are of unknown etiology. This could be

due to undetectable concentrations of common Gram-negative pathogens like E. coli in

the mammary gland (Wellenberg et al., 2002).

Endotoxin or lipopolysaccharide (LPS) is an integral component of the outer

leaflet of the outer cell wall of all Gram-negative bacteria and is a potent activator of the

host innate immune response. LPS is composed of polysaccharides and phospholipids

and consists of three subunits: (1) Lipid A, the lipid moiety, is the bioactive portion of the

LPS; (2) The core region; and (3) the O-specific region. The latter two subunits are

73

polysaccharides. The core region consists of hexoses, hexamines and heptose that act as a bridge between the other two subunits. The O-specific region is the most variable region.

It confers strain specificity and elicits a specific immune response (Rietschel et al., 1991,

1993, 1994; Beutler and Rietschel, 2003). LPS is a potent mediator of the host’s innate immune response. Exposure of phagocytic (PMN, macrophages) and endothelial cells to

LPS both in vitro and in vivo results in onset of pro-inflammatory substances like histamines, prostanoids, and oxygen radicals, which when over produced, are deleterious to the host (Janosi et al., 1998). Another report suggests that endotoxin-associated mastitis is a predominant factor affecting reproductive performance in dairy cattle

(Moore et al., 1991). Therefore, development of antimicrobials targeting the lipid A moiety of LPS could be used as a potential antibacterial and anti-inflammatory agent

(Tyler et al., 1990; Wyckoff et al., 1998).

Lipid A is evolutionarily conserved and is essential for the functional barrier of the outer membrane of Gram-negative bacteria. Mutants with reduced lipid A content are more sensitive to antimicrobial agents than wild type strains (Vaara, 1993; Rietschel et al., 1994). The emergence of antibiotic resistant bacteria and the excessive inflammation mediated by the lipid A moiety released from lysed bacteria pose a major clinical problem during Gram-negative infection. Unfortunately, antibiotics that are effective against Gram-negative bacteria can exacerbate LPS release. Therefore, development of antimicrobials targeting the lipid A moiety of LPS could have great potential in reducing the deleterious outcome of Gram-negative infections (Wyckoff et al., 1998).

Until recently, the identity of the transmembrane receptor responsible for transducing LPS signaling was unknown. A spontaneous mutation occurring in C3H/HeJ

74

mice caused an aberration in LPS-mediated signaling and suggested the existence of single receptor for LPS (Watson and Riblet, 1974 & 1975). Positional cloning identified a point mutation in the cytoplasmic domain of Toll-like receptor 4 (TLR-4). The hyporesponsiveness of TLR-4 knock-out mice to LPS confirmed TLR-4 as the receptor

for LPS (Poltorak et al., 1998; Hoshino et al., 1999). TLR induction in mastitis was

reported in one study where a relative increase in TLR-4 mRNA expression was observed

in the bovine mammary gland in response to bacterial infection (Goldammer et al., 2004).

Interaction of LPS and TLR-4 and related accessory molecules results in cellular

activation and induction of proinflammatory cytokines like interleukin (IL)-1β, IL-8 and

tumor necrosis factor (TNF)-α. These are the key components activating the host innate

response against invading pathogens (Akira et al., 2001). Increases in the level of these

proinflammatory cytokines have been detected in the milk of cows challenged with LPS

or experimentally infected with Gram-negative intramammary pathogens (Bannerman et

al., 2003, 2004 a,b,c & 2005). LPS-mediated induction of these cytokines and other

inflammatory mediators is essential for the recruitment of neutrophils that form the first

line of host defense against the invading pathogens (Paape et al., 2000). LPS is not only

responsible for activating host defense mechanisms, but is also a mediator of septic shock

that could be life threatening (Morrison and Ryan, 1987). In mastitis, LPS-mediated

prolonged and/or excessive inflammatory response elicits an acute phase response in

cows and damages host mammary tissue. The acute response results in reduced milk

production, leukocyte-induced tissue injury and systemic shock that are often fatal to

cows (Sordillo and Peel, 1992; Hirvonen et al., 1999; Paape et al., 2000; Hoeben et al.,

2000; Hogan and Smith, 2003).

75

Bactericidal/permeability-increasing protein (BPI) was identified in humans as a

55 kDa cationic protein expressed in the azurophilic granules of PMN and mediates

oxygen-independent bacterial killing. It specifically kills Gram-negative bacteria (Weiss

et al., 1975; Elsbach et al., 1979; Lehrer et al., 1988). BPI constitutes nearly 0.5 percent

of the total protein contained in human neutrophils (Elsbach and Weiss, 1985). Hiki et al.

(1999) evaluated the concentration of BPI protein in plasma during an abdominal surgery

in 40 patients. The concentration of BPI ranged from 0-25 ng/mL in the patients. No

significant differences were noticed in the concentration level of BPI during the operative

process. Opal et al. (1994) studied concentration of BPI and LBP in biological fluids like

closed space abscesses, peritoneal fluid in patients suffering from peritonitis and non

infected fluids. The BPI concentrations were higher in infected fluids (2221 ng/mL) than

non-infected fluids (60 ng/mL). Also, the BPI concentration was higher in abscess fluids

infected with Gram-negative organisms (2042 ng/mL) than the Gram-positive organisms

(260 ng/mL). The concentration of BPI was directly correlated with the white blood cell

counts in the biological fluids tested.

Studies have shown that BPI has LPS-neutralizing activity. An in vitro study has

shown that BPI completely inhibits up-regulation of surface expression of complement

receptors (CR) on neutrophils when stimulated with both rough and smooth strains of

LPS. BPI-neutralizing activity on LPS is highly specific, as the CR expression was

uninhibited in activated neutrophils when stimulated with formylated peptide or TNF

(Marra et al., 1990).

The structure of full length BPI was resolved by X-ray crystallography and was

shown to have an unusual “boomerang” structure, unlike other soluble proteins that are

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nearly globular. It has two domains (N- and C-terminal) with similar folding structures, yet dissimilar in their aa sequences that are connected by a proline rich linker (Beamer et al., 1999). The 25-kDa N-terminal region of BPI contains the functional domains that are required by the holo-protein for its antibacterial and LPS binding and neutralizing activity

(Ooi et al., 1991; Gazzano-Santoro et al., 1992). N-terminal fragments of BPI cleaved by chemical and proteolytic methods were assayed for bactericidal activity. No bactericidal activity was evident for chemical or proteolytic cleaved N-terminal fragments of BPI

(Little et al., 1994). Further, 47 different 15-mer overlapping synthetic peptides were synthesized for the N-terminal fragment of BPI and only one peptide, corresponding to the amino acid region 85-99, was found to have a bactericidal effect against the E. coli J5 strain (Little et al., 1994). Based on the above study, three functional domains were identified within the amino acid regions 17-45, 65-99, and 142-169 that are capable of interacting with LPS (Little et al., 1994). In another study, addition of cysteine to the amino terminus of a peptide corresponding to amino acid residues 90 to 99 increased its bactericidal activity by 10 fold (Gray and Haseman, 1994). Wasiluk et al. (2004) showed that the cationic and hydrophobic amino acid residues within the synthetic peptide are critical for its bactericidal and LPS-neutralizing activity. Endotoxin neutralizing activity for the domain corresponding to amino acids 142-169 was studied both in vitro and in vivo and showed that BPI amino acid sequence 148-161 had a potent endotoxin neutralizing activity (Jiang et al., 2004). Thus, a human BPI-derived synthetic peptide that contains sequences with both bactericidal and LPS-neutralization activity may be a powerful therapeutic agent for the treatment of both Gram-negative mastitis and the development of septic shock that often ensues.

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BPI-derived synthetic peptides have not been tested for bactericidal activity or inhibitory activity against Gram-negative bacterial strains that cause mastitis. Whether such peptides are efficacious in biological fluids such as milk and blood is also unknown.

The objective of the current study was to evaluate the efficacy of a human BPI synthetic peptide (hBPIpep) for its antibacterial and LPS-neutralizing activity. In this study, a 24

amino acid synthetic peptide corresponding to amino acid sequences 90-99 and 148-161

of the human BPI mature protein was tested for its bactericidal activity against major

Gram-negative mastitis pathogens and for its LPS-neutralizing activity.

MATERIALS AND METHODS

Biological Fluid & Broth Preparation

Milk and blood samples were collected from eight clinically healthy (antibiotic

free) quarters of midlactating, first lactation Holstein cows. Animals were selected on the

basis of milk somatic cell counts (SCC) of <150,000 and the absence of detectable

bacterial growth from aseptic milk samples collected on three different days. For the

preparation of whey, milk samples were centrifuged at 44,000 x g at 4 ºC for 30 min, and the fat layer was removed with a spatula. The skim milk was transferred into a sterile tube and centrifuged for another 30 min as described above. The translucent supernatant

was aseptically transferred into a new sterile tube. Milk and whey samples were

pasteurized by heating at 63 ºC for 30 min. For the preparation of serum, tail vein blood

samples were collected in vacutainers containing gel and clot activator for serum separation (Becton Dickinson Corp., Franklin Lakes, NJ), spun at 1500 x g for 15 min

and the clear serum aseptically transferred into sterile tubes. The serum samples were

heat inactivated at 56 ºC for 30 min. An aliquot of all biological samples was plated on

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blood agar plates and samples that were free of detectable bacterial growth were stored at

-20 ºC. Brain heart infusion broth (BHI) and cation-adjusted-Muller-Hinton broth

(CAMHB) (Becton Dickinson Diagnostic Systems, Inc., Sparks, MD) were used as growth media for the in vitro bactericidal assay and antimicrobial susceptibility test, respectively.

Bacteria

E. coli strain P4 (a gift of A. J. Bramley, Institute for Animal Health, Compton

Laboratory, Newbury, England), originally isolated from a clinical case of mastitis, was

used for the in vitro determination of the bactericidal activity of the hBPIpep in various

biological fluids. Six isolates each of E. coli, K. pneumonia, S. marcescens and P.

aeruginosa, four isolates of Enterobacter cloacae and one isolate of Enterobacter

aerogenes, all of which were isolated from clinical cases of bovine mastitis (gift of Y.

Schukken, Cornell University, Ithaca, NY), were used for the antimicrobial susceptibility

test. E. coli ATCC 25922 and S. aureus ATCC 29213 (Gift of Dr. Bob Walker, FDA,

Laurel, MD) were used as reference strains for the antimicrobial susceptibility test. All

strains were maintained on blood agar plates.

Antimicrobial Synthetic hBPIpep

The synthetic peptide hBPIpep (KWKAQKRFLKKSKVGWLIQLFHKK)

corresponding to amino acid residues 90-99 and 148-161 of mature human BPI protein

and control peptide SHLT-1 (MCHWAGGASNTGDARGDVFGKQAG) were

commercially synthesized (Genemed Synthesis, Inc., South San Francisco, CA). The peptides were reconstituted in citrate buffered saline (CBS) [20mM sodium citrate,

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150mM sodium chloride, 0.1% poloxamer, and 0.002% polysorbate 80, pH 5.0, (Sigma

Chemical Co., St. Louis, Mo)] to a final concentration of 10 mg/mL and were stored at

-20 ºC until use. The synthetic peptides were tested for the presence of endotoxin by the limulus amebocyte lysate (LAL) test according to the manufacturer’s instructions

(Cambrex Bio Science Walkersville, Inc., Walkersville, MD). Tetracyline and

polymyxin-B (Sigma Chemical Co.) were reconstituted in endotoxin free water (Cambrex

Bio Science Walkersville, Inc. Walkersville, MD) and aliquots were stored at -20 ºC and

used as positive controls for the minimum inhibitory concentration (MIC) and LAL

assays respectively. All antimicrobial peptide aliquots were dissolved at two-fold higher

concentration than the highest concentration assayed and were thawed only once.

Microbial Growth Assays

Overnight bacterial cultures were diluted 1:1000 in BHI and incubated shaking at

37 ºC for 2 hours. Bacteria in log phase were diluted 1:10 in BHI to obtain a final concentration of 1 x 106 CFU/mL. The bacterial inoculum (0.01 mL) was added to a 1.5

mL sterile microcentrifuge tube containing 0.04 mL of milk, serum or whey. An aliquot

(0.05 mL) of BPI peptide, control peptide, or CBS alone was added to each tube. The

samples were then shaken @ 100 rpm for 6 hours at 37 ºC. The sample mixtures were

subsequently serially diluted and plated on MacConkey agar plates. The plates were

incubated overnight at 37 ºC and the next day the colonies were enumerated.

Antimicrobial Susceptibility Test to Determine MIC and MBC Values

To determine the spectrum of activity of hBPIpep against major Gram-negative

pathogens, the MIC and MBC (minimal bactericidal concentration) values were

determined against selected clinical isolates of bovine mastitis by the microdilution

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method, according to the Clinical Laboratory Standards Institute guidelines (CLSI, 2002).

To ensure the quality of the assay, each test was run with reference strains as recommended by CLSI. The quality control (QC) range of MIC values for tetracycline was within the acceptable range. Briefly, 100 µL of the highest concentration of the

antimicrobial was serially diluted in a 96-well plate. The transmittance of bacterial

inoculum was adjusted to 0.5 Mcfarland (108 CFU/mL) using a colorimeter. A 100-fold

dilution of 108 CFU/mL was made and 50 µL of the bacterial inoculum was added to each

well. The plates were incubated for 16-20 h at 35ºC with ambient air circulation and no

shaking. After incubation the plates were read to determine the MIC range using a

magnifying glass plate reader. MBC range was determined by plating 0.01 mL from clear

wells and counting the number of CFU.

LPS Neutralization Assay

The ability of the hBPIpep to neutralize LPS was determined using the LAL assay.

The hBPIpep or polymixin-B (PMB) were incubated with 1 ng of LPS in a 500 µl reaction

volume of endotoxin free water shaking @100 rpm for 30 min @ 37 ºC. Following

incubation, the amount of free endotoxin was determined according to the manufacturer’s

instructions. Briefly, 50 µl of the above mixture was placed in a microtiter plate (Costar).

The reaction was initiated by the addition of an equal volume of amoebocyte lysate.

Following incubation @ 37 ºC for 15 min, 100 µl of chromogenic substrate was added

and the plate incubated for 5-10 min @ 37 ºC. The reaction was stopped by the addition

of 50 µl of acetic acid and the absorbance was measured at 405 nm using a microplate

reader (Biotec Instruments, Inc., Winooski, VT). The amount of non-bound LPS was

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extrapolated from a standard curve and the percent inhibition calculated. The assay was replicated twice and for each replicate the measurement was performed in quadruplicate.

Statistical methods

A paired t test was used to determine statistical significance between experimental

and control groups. A P value of < 0.05 was considered significant (Prism version 4.0

for Windows; GraphPad Software Inc., San Diego, CA).

RESULTS

Growth inhibition of E. coli P4 by hBPIpep in whole milk, serum, whey and broth

The hBPIpep peptide was synthesized based on the published amino acid sequence

for the two domains (amino acid residues 90-99 and 148-161) (Gray and Haseman, 1994;

Jiang et al., 2004). It was also compared with the amino acid sequence deduced from the

human cDNA sequence available in the public genome database (Accession #

BC040955). The efficacy of the peptide to inhibit the growth of E. coli strain P4 in

various biological fluids, including milk, whey, serum and broth was assayed (Table 1).

The peptide exhibited complete bactericidal activity in broth and serum at 10 µg/mL and at 100 µg/mL in whey. The peptide inhibited bacterial growth in whey and broth at 10 and 1 µg/mL, respectively. In whole milk, the peptide exhibited a growth inhibitory effect at 100 µg/mL; however, the peptide had no bactericidal activity in milk at any concentration tested. In contrast, a control peptide displayed no significant bactericidal or inhibitory effect in milk and broth at the highest concentration tested for the hBPIpep.

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Tab1e 1: Antimicrobial activity of hBPIpep synthetic peptide. a a * SAMPLE Conc of Conc of hBPIpep Control N P value

SHLT1/mL hBPI/mL (CFU Log10) (CFU Log10) Mean SE Mean SE Milk 2mg 6.09 0.22 8.91 0.07 7 P<0.0001

1mg 6.67 0.042 8.54 0.16 8 P<0.0001

100µg 7.60 0.18 8.36 0.15 8 P=0.0007

10 µg 8.95 0.09 8.96 0.08 8 P=0.4504

1 mg 8.86 0.04 8.68 0.11 4 P=0.1490

Whey 1 mg 0 0 8.83 0.05 8 P<0.0001

100 µg 0 0 8.83 0.05 8 P<0.0001

10 µg 4.85 0.20 8.15 0.10 8 P<0.0001

1 µg 8.05 0.26 8.81 0.08 8 P=0.0025

0.1 µg 8.71 0.21 8.81 0.08 8 P=0.2397

Serum 100 µg 0 0 8.22 0.17 8 P<0.0001 (HI) 10 µg 0 0 8.20 0.05 8 P<0.0001

1 µg 7.90 0.14 8.20 0.05 8 P=0.0511

0.1 µg 8.17 0.03 8.20 0.05 8 P=0.2133

0.01 µg 8.21 0.04 8.17 0.04 8 P=0.0773

Broth 100 µg 0 0 8.90 0.02 5 P<0.0001

10 µg 0 0 8.90 0.02 5 P<0.0001

1 µg 3.56 0.97 8.90 0.02 5 P=0.0027

0.1 µg 8.68 0.04 8.90 0.02 5 P=0.0030

0.01 µg 8.85 0.03 8.88 0.02 5 P=0.2700

100 µg 8.81 0.03 8.91 0.01 4 P=0.0214

10 µg 8.66 0.12 8.73 0.10 4 P=0.1021 The bactericidal and growth inhibition activity of human BPI protein derived synthetic peptide and control a peptide SHLT-1 was tested against E. coli P4 strain in milk, whey, serum and broth Values shown are the means ± standard error of the replicates for total number of colony forming units of E. coli bacteria enumerated the next day. * number of replicates for each experimental value.

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Enhanced antibacterial activity of hBPIpep in whole milk in the presence of EDTA

Ethylenediaminetetraacetate (EDTA) is a metal chelator that binds divalent

cations. To determine if EDTA could enhance the growth inhibitory effect of hBPIpep in

milk, varying concentrations of hBPIpep were assayed in the presence of increasing EDTA

concentrations. In the presence of 16mM EDTA, hBPIpep peptide had complete

bactericidal activity at 10 µg/mL. EDTA also significantly inhibited E. coli bacterial growth at this concentration (Fig. 1). At 8mM EDTA concentration, the peptide significantly inhibited bacterial growth at 1mg/mL with a 5 fold difference relative to the

control. To determine whether EDTA itself had any bactericidal effect, it was tested at

16mM concentration in BHI broth. The mean log values of bacterial count for the EDTA

treated and control were 7.106 ± 0.300 and 8.679 ± 0.042 (n=6, P = 0.001), while in milk

the value was 4.496 ± 0.291 CFU/mL (Fig. 1).

MIC and MBC values of hBPIpep against major Gram-negative mastitis pathogens

To determine its spectrum of activity hBPIpep was tested against various isolates

of major Gram-negative mastitis pathogen by the microdilution susceptibility assay.

Each test was performed in triplicate by repeating the assay on three different days. On

each individual test day, samples were run in duplicate. The average difference in MIC

and MBC values for hBPIpep against the mastitis pathogens were only 1-2 fold, whereas

the difference in these values for tetracycline was much higher (Table 2). All isolates of

Serratia spp. were found to be resistant to hBPIpep as the MIC and MBC values were

greater than 512 µg/mL and they were also found to be less susceptible to tetracycline as the MBC values were higher. Two isolates of Enterobacter spp. which were resistant to

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tetracycline (MIC > 128 µg/mL), were found to be susceptible to hBPIpep (MIC = 32-64

µg/mL).

EDTA vs CFU/ ml

10

9

8

7

6 1mg 100ug 5 10ug

4 0ug

3 CFU / mL ( Log 10 )

2

1

0 024816

EDTAEDTA(mM) (mM)

Fig. 1: Bactericidal activity of human BPI synthetic peptide hBPIpep in milk in the presence of EDTA.

At various concentration of EDTA the antibacterial activity of hBPI against E. coli (CFU/mL log10) was tested in milk.

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Table 2: Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) values of hBPIpep against isolates of major Gram-negatve mastitis pathogens.

Microorganism Isolates hBPIpep (n=6) Tetracycline (n=2) MIC MBC MIC MBC Escherichia coli CI #1 16 32 2 64-128 CI#2 16-32 16-32 2 >128 CI#3 32 32-64 2 >128 CI#4 32-64 32-64 2 >128 CI#5 32-64 32-128 2 64-128 Ci#6 32-64 64-128 1-2 >128 Klebsiella spp CI #1 32-64 32-64 64-128 128 CI#2 32-64 32-64 128 128 CI#3 64-128 64-128 2 128 CI#4 64-128 64-128 64-128 128 CI#5 32-64 32-64 2 128 Ci#6 32-64 32-64 1-16 128 Pseudomonas spp CI #1 64-128 64-128 16 >128 CI#2 64-128 64-128 8-16 >128 CI#3 64-128 64-128 64 128 CI#4 64-128 64-256 16-32 >128 CI#5 128-256 128-256 32 >128 CI#6 64-128 64-128 16-32 >128

Serratia spp CI #1 >512 >512 32-64 >128 CI#2 >512 >512 64 >128 CI#3 >512 >512 64 >128 CI#4 >512 >512 64 >128 CI#5 >512 >512 64 >128 CI#6 >512 >512 64 >128 Enterobacter spp CI #1 64 64 >128 >128 CI#2 32-64 32-64 2-4 >128 CI#3 64-128 64-128 128 128 CI#4 32-64 32-128 >128 >128 CI#5 32-64 32-128 4-16 >128

E. coli ATCC 25922 BPI (n=30) 32-64 32-64 0.5-1 32-128

S. aureus ATCC 29213 BPI (n=30) 128-256 128-256 <0.25-1 128->128 Tetracycline was used as positive control. E. coli ATCC 25922 and S. aureus ATCC 29213 were the two reference strains used as recommended by CLSI.

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LPS neutralizing activity of hBPIpep

To determine whether hBPIpep was able to neutralize LPS, increasing

concentrations of BPI were incubated with LPS and the resulting mixture assayed with

the LAL assay (Fig. 2). At a concentration ≥ 30 µg/mL the LPS-neutralizing activity of

hBPIpep was equivalent to PMB, which was used as a positive control. However, no LPS

binding activity was detected for the control peptide.

LPS 1ng/mL 100 hBPIpep PMB 75 Co.Pep

50

%inhibition 25

0 0 25 50 75 100 125 Antimicrobials (µg/mL)

Fig. 2: Percent inhibition of purified Lipopolysaccharide (LPS) by human BPI derived synthetic peptide. Polymixin B (PMB) and SHLT-I control peptide (Co.Pep) were the positive and negative control. The standard error bars were two small to be seen in the figure. LPS was used @ 1ng/mL in LAL assay.

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DISCUSSION

In the present study, a 24-mer synthetic peptide of human BPI was evaluated in vitro for its: (1) antibacterial property in bovine biological fluids including whole milk, whey and serum; (2) antibacterial activity against clinical mastitis isolates of E. coli, K. pneumonia, S. marcescens and P. aeruginosa, and Enterobacter spp. and (3) LPS- neutralization using the LAL assay. The hBPI domain corresponding to amino acid residues 85-99 has the highest bactericidal activity, whereas the domains for LPS- neutralizing activity lie within residues 73-99 and 140-170 (Little et al., 1994). A synthetic hBPI peptide corresponding to amino acid residues 90-99 had bactericidal activity against a wide array of bacterial organisms including Pseudomonas cepacia and

Staphylococcus aureus which were resistant to killing by the BPI holoprotein. In contrast, this peptide had no LPS-neutralizing activity when tested at 4.5 x 10-4 M (600 µg/mL)

(Gray and Haseman, 1994). Both in vitro and in vivo studies have shown that synthetic

peptides derived from a functional domain of BPI corresponding to amino acid residues

148-161, represented as BNEP had anti-endotoxin activity (Jiang et al., 2004). The

current study, examines the hypothesis that a single synthetic human peptide composed

of two functionally distinct BPI domains (BPI residues 90-99 and 148-161) is efficacious

for both antibacterial and LPS-neutralizing activity. The results provide evidence, for the

first time, that a human-BPI-derived short synthetic peptide corresponding to an

endogenous protein, possesses potent LPS neutralizing and antimicrobial agent against

Gram-negative mastitis pathogens.

Bactericidal activity for hBPIpep against E. coli was observed in broth, bovine serum and whey. At 10 µg/mL the hBPIpep exhibited bactericidal activity in broth and

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serum, and at a higher concentration (100 µg/mL) in whey. A significant inhibitory effect on bacterial growth was observed in broth at 1 µg/mL between the treatment (3.56

± 0.96) and control (8.90 ± 0.02) and a 3 log fold difference was observed between the hBPIpep (10 µg/mL) and control whey samples (Table 1). Bactericidal activity was

previously reported for a 15-mer peptide (85-99 aa) against E. coli J5 bacteria grown in

tryptic soy agar where the activity was determined by a radial diffusion assay (Little et

al., 1994). Gray and Haseman (1994) reported that a peptide corresponding to amino

acids 90-99 and related peptides, exhibited bactericidal activity against P. aeruginosa (5

x 106 CFU). The peptide (90-99) had a bactericidal effect against P. aeruginosa at a

concentration of 20 µg/mL and also exhibited killing ability against S. aureus. However, at 3 x 10-5 M concentration, only 31 % of 5x 10-6 E. coli organisms were killed by the

peptide. In contrast, the present study demonstrated that the hBPIpep had bactericidal effect against E. coli strain P4 (5x 104) at 10 µg/mL. This enhanced antimicrobial activity

of hBPIpep could be due to the additional amino acid sequence corresponding to 148-161

residues, as a similar enhancement in bactericidal activity was observed when the amino

acid sequence was elongated at the amino and carboxyl end of the 90-99 peptide (Gray and Haseman, 1994). In their study, it was also observed that addition of cysteine at the

N-terminal end (C# 90-99) enhanced the bactericidal activity of the peptide (90-99). The

C# 90-99 peptide exhibited a bactericidal effect against P. aeruginosa at the concentration of 2.1µg/mL and the same effect at 10-times higher concentration against rough strain E. coli B and P. cepacia. It also exhibited killing ability against S. aureus at

a 20 fold higher concentration than that required for killing P. aeruginosa. Any variation

in the biological activity between the two studies could be due to variation in growth

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medium, growth conditions and differences in the strain used in the study. Although there are no previous reports on the biological activity of hBPIpep tested in bovine serum or

whey, the concentration required to kill the E. coli bacteria in broth is comparable to that

of serum and 10 fold lower than whey.

In milk, the hBPIpep peptide exhibited significant growth inhibition against E. coli

P4 strain at ≥ 1mg/mL concentration (Table 1). Muller-Hinton broth has been recommended by the clinical laboratory standard institute (CLSI) in the NCCLS document M2 for the susceptibility testing of commonly isolated, rapidly replicating pathogens. One reason for this recommendation is due to the broth’s reproducibility and low content of tetracycline inhibitor. It has also been shown that a change in concentration of divalent cations like Ca++ and Mg ++ in the Muller-Hinton broth, could

alter the MICs of aminoaglycosides for P. aeruginosa and MICs of tetracycline for all

bacteria from those values obtained in Muller-Hinton agar. In the presence of high

concentrations of magnesium sulphate, vancomycin failed to lyse E. coli bacteria and the

effect was unaltered against S. aureus (Russell, 1967). Addition of the chelating agent

EDTA enhanced the effect of sublethal concentrations of vancocmycin against E. coli,

however, it had no beneficial action against the inhibitory effect of vancomycin with S.

aureus. This observation strongly suggests that the enhanced effect of EDTA on the

antibacterial effect of vancomycin is due to removal of cations that are bound to the outer

wall of bacteria thereby increasing the permeability of the antibiotic (Russell, 1967).

Therefore, we hypothesized that divalent cations like Ca++ and Mg ++ that are present in

milk could have a major inhibitory action against the hBPIpep bactericidal activity in milk.

The free calcium ion concentration in bovine milk is estimated to be in the range of 2-3.2

90

mM (Silanikove et al., 2003). To test our hypothesis, the hBPIpep was tested against E.

coli strain P4 with varying concentrations of EDTA. The antibacterial effect of hBPIpep against E. coli in milk was enhanced in the presence of EDTA at 16mM concentration

(4.68 mg). The peptide exhibited complete inhibitory effect on the bacterial growth at 10

µg/mL concentration. EDTA by itself had a significant inhibitory effect on E. coli growth in milk but not in broth. It has been reported that EDTA at concentrations from

250-1000 ppm (250-1000 µg/mL) had no significant inhibitory effect in BHI broth against E. coli MacDonald 92, originally isolated from a clinical case of mastitis (Chew et al., 1985). The inhibitory effect in milk could result from an EDTA-mediated increased permeability of the outer membrane of E. coli wherein the antimicrobial substances that are present in the milk had easy access to the bacterial cell wall. Also, potentially there

++ would be enhanced antibacterial activity of hBPIpep in mastitis milk as the Ca level

decreases in milk from mastitis cows (Schalm et al., 1971).

An interesting finding from our data is that the differences in MIC and MBC

values were very narrow for various isolates tested when compared with that of

tetracycline. The hBPIpep exhibited bactericidal effect against isolates tested for the

major Gram-negative mastitis pathogens, however, all isolates of Serratia spp. were

found to be resistant. The resistance mechanism is also observed against BPI holoprotein

(Weiss et al., 1975). Two possible explanations for its mode of resistance are: (i) efflux

mechanisms exhibited against drugs (Berlenga et al., 2000) or (ii) decreased permeability

to antimicrobials (Hechler et al., 1989). Further experiments with EDTA would

determine whether decreased permeability is a major resistance mechanism exhibited by

Serratia spp. against antimicrobial agent hBPIpep.

91

The LAL assay is a highly sensitive assay to detect the presence of free LPS in trace amounts and is accepted as a standard assay to determine the LPS-neutralizing activity of any molecule. The hBPIpep inhibited the LPS-induced LAL reaction.

Therefore, the LPS-neutralizing activity of domain (148-161) is retained in this hybrid

peptide. Our results are comparable with the published report for BNEP peptide (148-

161), where it was shown that the BNEP (32 µg/mL) inhibited more than 1 ng/mL of LPS activity and was less potent than PMB. In contrast, our data show that hBPIpep was equally competent to that of PMB from 30 µg/mL and at higher concentrations.

Administration of an anti-inflammatory agent by the systemic route for treatment of infectious disease has been contraindicated due to adverse side effects and could hinder the rate of clearance of infectious agents. It was reported that use of an anti- inflammatory agent in a goat model of intramammary infection did not adversely affect the bacterial clearance from the infected gland (Anderson et al., 1991).

LPS is a potent mediator of the host’s innate immune response and in vivo and in vitro exposure of phagocytic (PMN, macrophages) and endothelial cells to LPS result in onset of pro-inflammatory substances, histamines, prostanoids and oxygen radicals, which, when over-produced are deleterious to the host (Janosi et al., 1998). Another report suggests that endotoxin-associated mastitis is a predominant factor affecting reproductive performance in dairy cattle (Moore et al., 1991). Therefore, development of antimicrobials and, more specifically antimicrobials targeting the lipid A moiety of LPS could be a potential antibacterial and anti-inflammatory agent (Tyler et al., 1990;

Wyckoff et al., 1998). One such potential agent is BPI, an endogenous protein expressed in primary granules of PMN that has been well studied in humans for its antibacterial and

92

endotoxin binding activity. The present data establishes human-BPI- derived synthetic peptide as a potential antimicrobial and anti-inflammatory agent against Gram-negative mastitis pathogens. Many other functions have been reported for BPI and BPI-derived peptides including their role in phagocytosis-mediated killing of E. coli (Nishimura et al.,

2001); their prevention of endotoxin mediated shock through inhibition of TNF-α

synthesis by macrophages (Dankesreiter et al., 2000) and their protection of endotoxin-

induced damage to vascular endothelial cells by inhibition of proinflammatory cytokine

synthesis (Arditi et al., 1994). However, more in vivo study needs to be conducted to

study the protective role of hBPIpep in the pathophysiological processes of the bovine

mammary gland.

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Dankesreiter, S., Hoess, A., Schneider-Mergener, J., Wagner, H., and Miethke, T. 2000. Synthetic endotoxin-binding peptides block endotoxin-triggered TNF-alpha production by macrophages in vitro and in vivo and prevent endotoxin-mediated toxic shock. J Immunol 164:4804-4811. Elsbach, P., and Weiss, J. 1985. Oxygen-dependent and oxygen-independent mechanisms of microbicidal activity of neutrophils. Immunol Lett 11:159-163. Elsbach, P., Weiss, J., Franson, R.C., Beckerdite-Quagliata, S., Schneider, A., and Harris, L. 1979. Separation and purification of a potent bactericidal/permeability- increasing protein and a closely associated phospholipase A2 from rabbit polymorphonuclear leukocytes. Observations on their relationship. J Biol Chem 254:11000-11009. Erskine, R.J., Tyler, J.W., Riddell, M.G., Jr., and Wilson, R.C. 1991. Theory, use, and realities of efficacy and food safety of antimicrobial treatment of acute coliform mastitis. J Am Vet Med Assoc 198:980-984. Gazzano-Santoro, H., Parent, J.B., Grinna, L., Horwitz, A., Parsons, T., Theofan, G., Elsbach, P., Weiss, J., and Conlon, P.J. 1992. High-affinity binding of the bactericidal/permeability-increasing protein and a recombinant amino-terminal fragment to the lipid A region of lipopolysaccharide. Infect Immun 60:4754-4761. Goldammer, T., Zerbe, H., Molenaar, A., Schuberth, H.J., Brunner, R.M., Kata, S.R., and Seyfert, H.M. 2004. Mastitis increases mammary mRNA abundance of beta- defensin 5, toll-like-receptor 2 (TLR2), and TLR4 but not TLR9 in cattle. Clin Diagn Lab Immunol 11:174-185. Gray, B.H., and Haseman, J.R. 1994. Bactericidal activity of synthetic peptides based on the structure of the 55-kilodalton bactericidal protein from human neutrophils. Infect Immun 62:2732-2739. Hechler, U., van den Weghe, M., Martin, H.H., and Frere, J.M. 1989. Overproduced beta- lactamase and the outer-membrane barrier as resistance factors in Serratia marcescens highly resistant to beta-lactamase-stable beta-lactam antibiotics. J Gen Microbiol 135:1275-1290. Hiki, N., Berger, D., Dentener, M.A., Mimura, Y., Buurman, W.A., Prigl, C., Seidelmann, M., Tsuji, E., Kaminishi, M., and Beger, H.G. 1999. Changes in endotoxin-binding proteins during major elective surgery: important role for soluble CD14 in regulation of biological activity of systemic endotoxin. Clin Diagn Lab Immunol 6:844-850. Hirvonen, J., Eklund, K., Teppo, A.M., Huszenicza, G., Kulcsar, M., Saloniemi, H., and Pyorala, S. 1999. Acute phase response in dairy cows with experimentally induced Escherichia coli mastitis. Acta Vet Scand 40:35-46. Hoeben, D., Burvenich, C., Trevisi, E., Bertoni, G., Hamann, J., Bruckmaier, R.M., and Blum, J.W. 2000. Role of endotoxin and TNF-alpha in the pathogenesis of experimentally induced coliform mastitis in periparturient cows. J Dairy Res 67:503-514. Hogan, J., and Larry Smith, K. 2003. Coliform mastitis. Vet Res 34:507-519. Hoshino, K., Takeuchi, O., Kawai, T., Sanjo, H., Ogawa, T., Takeda, Y., Takeda, K., and Akira, S. 1999. Cutting edge: Toll-like receptor 4 (TLR4)-deficient mice are hyporesponsive to lipopolysaccharide: evidence for TLR4 as the LPS gene

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product. J Immunol 162:3749-3752. Janosi, S., Huszenicza, G., Kulcsar, M., and Korodi, P. 1998. Endocrine and reproductive consequences of certain endotoxin-mediated diseases in farm mammals: a review. Acta Vet Hung 46:71-84. Jiang, Z., Hong, Z., Guo, W., Xiaoyun, G., Gengfa, L., Yongning, L., and Guangxia, X. 2004. A synthetic peptide derived from bactericidal/permeability-increasing protein neutralizes endotoxin in vitro and in vivo. Int Immunopharmacol 4:527- 537. Lehrer, R.I., Ganz, T., and Selsted, M.E. 1988. Oxygen-independent bactericidal systems. Mechanisms and disorders. Hematol Oncol Clin North Am 2:159-169. Little, R.G., Kelner, D.N., Lim, E., Burke, D.J., and Conlon, P.J. 1994. Functional domains of recombinant bactericidal/permeability increasing protein (rBPI23). J Biol Chem 269:1865-1872. Marra, M.N., Wilde, C.G., Griffith, J.E., Snable, J.L., and Scott, R.W. 1990. Bactericidal/permeability-increasing protein has endotoxin-neutralizing activity. J Immunol 144:662-666. Moore, D.A., Cullor, J.S., BonDurant, R.H., and Sischo, W.M. 1991. Preliminary field evidence for the association of clinical mastitis with altered interestrus intervals in dairy cattle. Theriogenology 36:257-265. Morrison, D.C., and Ryan, J.L. 1987. Endotoxins and disease mechanisms. Annu Rev Med 38:417-432. National Mastitis Council. 1999. Current concepts of bovine mastitis, 4th ed. The National Mastitis council, Inc., Madison, Wis. Nishimura, H., Gogami, A., Miyagawa, Y., Nanbo, A., Murakami, Y., Baba, T., and Nagasawa, S. 2001. Bactericidal/permeability-increasing protein promotes complement activation for neutrophil-mediated phagocytosis on bacterial surface. Immunology 103:519-525. Ooi, C.E., Weiss, J., Doerfler, M.E., and Elsbach, P. 1991. Endotoxin-neutralizing properties of the 25 kDa N-terminal fragment and a newly isolated 30 kDa C- terminal fragment of the 55-60 kDa bactericidal/permeability-increasing protein of human neutrophils. J Exp Med 174:649-655. Opal, S.M., Palardy, J.E., Marra, M.N., Fisher Jr, C.J., McKelligon, BM., and Scott, R.W. 1994. Relative concentrations of endotoxin-binding proteins in body fluids during infection. The Lancet 344: 429-431. Paape, M.J., Shafer-Weaver, K., Capuco, A.V., Van Oostveldt, K., and Burvenich, C. 2000. Immune surveillance of mammary tissue by phagocytic cells. Adv Exp Med Biol 480:259-277. Poltorak, A., He, X., Smirnova, I., Liu, M.Y., Van Huffel, C., Du, X., Birdwell, D., Alejos, E., Silva, M., Galanos, C., et al. 1998. Defective LPS signaling in C3H/HeJ and C57BL/10ScCr mice: mutations in Tlr4 gene. Science 282:2085- 2088. Rietschel, E.T., Kirikae, T., Schade, F.U., Mamat, U., Schmidt, G., Loppnow, H., Ulmer, A.J., Zahringer, U., Seydel, U., Di Padova, F., et al. 1994. Bacterial endotoxin: molecular relationships of structure to activity and function. Faseb J 8:217-225.

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Rietschel, E.T., Kirikae, T., Schade, F.U., Ulmer, A.J., Holst, O., Brade, H., Schmidt, G., Mamat, U., Grimmecke, H.D., Kusumoto, S., et al. 1993. The chemical structure of bacterial endotoxin in relation to bioactivity. Immunobiology 187:169-190. Rietschel, E.T., Seydel, U., Zahringer, U., Schade, U.F., Brade, L., Loppnow, H., Feist, W., Wang, M.H., Ulmer, A.J., Flad, H.D., et al. 1991. Bacterial endotoxin: molecular relationships between structure and activity. Infect Dis Clin North Am 5:753-779. Russell, A.D. 1967. Effect of magnesium ions and ethylenediamine tetra-acetic acid on the activity of vancomycin against Escherichia coli and Staphylococcus aureus. J Appl Bacteriol 30:395-401. Schalm, O.W., Carroll, E.J., and Jain, N.C. 1971. Bovine Mastitis. Lea & Febiger. Philadelphia. 360 pp. Silanikove, N., Shapiro, F., and Shamay, A. 2003. Use of an ion-selective electrode to determine free Ca ion concentration in the milk of various mammals. J Dairy Res 70:241-243. Sordillo, L.M., and Peel, J.E. 1992. Effect of interferon-gamma on the production of tumor necrosis factor during acute Escherichia coli mastitis. J Dairy Sci 75:2119- 2125. Tyler, J.W., Cullor, J.S., Spier, S.J., and Smith, B.P. 1990. Immunity targeting common core antigens of gram-negative bacteria. J Vet Intern Med 4:17-25. Vaara, M. 1993. Antibiotic-supersusceptible mutants of Escherichia coli and Salmonella typhimurium. Antimicrob Agents Chemother 37:2255-2260. Wasiluk, K.R., Leslie, D.B., Vietzen, P.S., Mayo, K.H., and Dunn, D.L. 2004. Structure/function studies of an endotoxin-neutralizing peptide derived from bactericidal/permeability-increasing protein. Surgery 136:253-260. Watson, J., and Riblet, R. 1974. Genetic control of responses to bacterial lipopolysaccharides in mice. I. Evidence for a single gene that influences mitogenic and immunogenic respones to lipopolysaccharides. J Exp Med 140:1147-1161. Watson, J., and Riblet, R. 1975. Genetic control of responses to bacterial lipopolysaccharides in mice. II. A gene that influences a membrane component involved in the activation of bone marrow-derived lymphocytes by lipipolysaccharides. J Immunol 114:1462-1468. Weiss, J., Franson, R.C., Beckerdite, S., Schmeidler, K., and Elsbach, P. 1975. Partial and purification of a rabbit granulocyte factor that increases permeability of Escherichia coli. J Clin Invest 55:33-42. Wellenberg, G.J., van der Poel, W.H., and Van Oirschot, J.T. 2002. Viral infections and bovine mastitis: a review. Vet Microbiol 88:27-45. Wyckoff, T.J., Raetz, C.R., and Jackman, J.E. 1998. Antibacterial and anti-inflammatory agents that target endotoxin. Trends Microbiol 6:154-159. Ziv, G. 1992. Treatment of peracute and acute mastitis. Vet Clin North Am Food Anim Pract 8:1-15.

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CHAPTER 5

EFFICACY OF BOVINE BACTERICIDAL/PERMEABILITY-INCREASING

PROTEIN DERIVED PEPTIDE AGAINST MAJOR GRAM-NEGATIVE

MASTITIS PATHOGENS

INTRODUCTION

Gram-negative bacteria are the causative agents for nearly 40% of clinical mastitis affecting the U.S. dairy industry. Approximately 25% of these clinical cases are

replaced in herds through early culling and death of animals (Eberhart, 1984; Erskine et

al., 1991). The incidence of clinical mastitis due to Gram-negative pathogens is reported

to occur more frequently in herds with low bulk milk somatic cell count (SCC) (Barkema

et al., 1998). Since the dairy industry is striving to meet National Mastitis Council

guidelines (NMC) for bulk milk SCC, the incidence of mastitis due to Gram-negative

bacteria is expected to increase. Approximately 65% of clinical cases are caused by

environmental pathogens and coliforms are the major causative agent (Hillerton et al.,

1995; Erskine et al., 1991). Escherichia coli, Klebsiella spp. and Enterbacter spp., are the

common coliform mastitis pathogens with infection from E. coli being the most common

due to its presence in the cow’s environment (Eberhart, 1977; Smith et al., 1985;

Makovec and Ruegg, 2003). Species of Serratia, Pseudomonas, and Proteus are the other

common Gram-negative bacteria isolated from acute clinical cases of mastitis (Hogan

and Smith, 2003). Implementation of a five-point mastitis control plan for dairy herd

management has reduced the incidence of contagious mastitis but has not been effective

in preventing environmental mastitis. Several studies have shown that the incidence of

coliform mastitis is high during the dry period rather than during lactation (Eberhart,

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1979; Oliver and Mitchell, 1983; Smith et al., 1985; Dingwell et al., 2004). Mastitis associated death is high in adult dairy cows and approximately 10% of coliform mastitis results in the peracute form of mastitis with systemic signs resulting from endotoxemia

(Wang et al., 2002).

Mastitis continues to a have major economic impact on the dairy industry, accounting for 38% of the total direct costs of the common production diseases.

Estimated loss due to coliform mastitis is $800 million in the U.S. alone (Kossaibati and

Esslemont, 1997). In addition to economic loss, a few studies have shown that mastitis

due to Gram-negative pathogens has an impact on reproductive performance of dairy

cows. Clinical mastitis due to Gram-negative bacteria affects the reproductive

performance of dairy cows by altering the estrus cycle and decreasing luteal phase length

(Moore et al., 1991). Endotoxin released from Gram-negative bacteria may induce luteolysis that may influence the conception rate and early embryonic survival by release of pro- inflammatory cytokines and the luteolytic hormone prostaglandin F2α (PG F2α)

(Cullor, 1990; Moore and O’Connor, 1993). Schrick et al. (2001) have reported that the number of artificial insemination services per conception were high in cows with clinical mastitis compared to uninfected cows or cows diagnosed with subclinical mastitis.

While studies on mastitis have focused more on its economic impact, it also has a significant impact on the environment. In a case study of dairy herds, environmental issues like acidification, eutrophication and global warming were the major categories that were found to be significantly influenced by mastitis incidence (Hospido and

Sonesson, 2005). Antibiotic treatment, administered by the intramammary route, is the primary method of treatment and prophylaxsis for mastitis in dairy cows (Berghash et al.,

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1983). This raises environmental concern as the use of antibiotics increase the risk of

developing antibiotic resistant bacteria. Extralabel and injudicious use of antibiotics for

treating mastitis in dairy cows and other bacterial diseases in food- producing animals is a

major cause for the emergence of antibiotic resistance and antibiotic residual effect in

animal products. These have significant impacts on public health (Smith et al., 2005;

Piddock, 1996; Sawant et al., 2005). In Europe, a ban on the use of growth-promoting

antibiotics like bacitracin, spiramycin, virginiamycin in food animals, has concomitantly

increased the use of therapeutic antibiotics like tetracycline, aminoglycosides,

lincosamides, etc. that are commonly used in human medicine. This may impact human

health as the incidence of resistance is more likely to occur in Salmonellae,

Campylobacters and zoonotic strains of E. coli (Casewell et al., 2003). Non-therapeutic use of antibiotics in farm animals and the emergence of antimicrobial resistance in animal populations require evaluation for its associated risk to human health (Bailar 3rd and

Travers, 2002; Shea, 2004; Phillips et al., 2004). The Food and Drug Administration

(FDA) has reviewed the development of antimicrobial resistance due to use and misuse of antibiotics in food animals. It issued guidelines for judicious use of antimicrobials for dairy cattle veterinarians. One of the recommendations is to consider other therapeutic options prior to use of antimicrobials (www.fda.gov/cvm/documents/judiciary.pdf). In

2003, the FDA issued guidelines for drug manufacturers asking for a risk assessment process to ensure that the antimicrobial drugs used in food-producing animals would not create a potential risk of emergence of antimicrobial resistant bacteria that are likely to lead to human health problems.

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Prophylactic measures like teat dipping prior to and after milking, dry cow antibiotic therapy and vaccination are unable to reduce the incidence of mastitis due to

Gram-negative environmental pathogens. Intramammary infusion of antibiotics is the common method of treatment for mastitis (Nair et al., 2005). The current antibiotic methods remain suboptimal in curing mastitis (Erskine et al., 1991; Ziv, 1992). The economic loss is high due to the prolonged milk withdrawal period caused by the residual effect of antibiotics in milk, in addition to decreased milk production (Daley and Hayes,

1992; Erskine, 1996). Gram-negative intramammary infection is responsible for a significant number of cows with coliform mastitis developing bacteremia resulting in release of lipopolysaccharide (LPS) directly into the circulation producing systemic endotoxemia (Wenz et al., 2001). The emergence of antibiotic resistance bacteria has become a major threat to public health (Jacoby, 1996) and necessitates development of alternative antimicrobials that have bactericidal and LPS neutralization activity with very few side effects. Synthetic congeners corresponding to functional domains of naturally occurring endogenous antimicrobial proteins will be good candidates for non-antibiotic antimicrobials.

Bactericidal/permeability-increasing protein (BPI) is a 55 kDa cationic protein expressed from the primary granules of human neutrophils. Its activity is highly specific against Gram-negative bacteria (Weiss et al., 1975; Elsbach et al., 1979). BPI constitutes nearly 0.5 percent of the total protein contained in human neutrophils (Elsbach and

Weiss, 1985). The 23-kDa N-terminal region of BPI contains the functional domains that confer antibacterial, LPS-binding and neutralizing activity to the holo-protein (Ooi et al.,

1991; Gazzano-Santoro et al., 1992). The recombinant form of BPI protein and its

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peptides are found to possess antifungal activity (Gavit and Better, 2000), attenuate LPS- induced vascular reactivity and hyercoagulability (Yamashita, 1997; Ciornei et al., 2002), ameliorates acute lung injury in endoxemic pigs (Vandermeer, et al., 1994), and are antiangiogenic (Van der Schaft et al., 2002). They possess anti-inflammatory activity

through inhibition of sCD14-mediated LPS signal transduction (Huang et al., 1994), and

also show heparin binding activity (Little et al., 1994). Three functional domains were

identified within the N-terminal region of human BPI corresponding to amino acid

regions 17-45, 65-99, and 142-169 that are capable of interacting with LPS (Little et al.,

1994). In another study, the addition of cysteine to the amino terminus of a BPI peptide

corresponding to amino acid residues 90-99 increased its bactericidal activity by 10 fold

(Gray and Haseman, 1994). Endotoxin-neutralizing activity for the domain

corresponding to amino acids 142-169 was studied both in vitro and in vivo model. The

sequence corresponding to amino acids 148-161 had a potent endotoxin-neutralizing

activity (Jiang et al., 2004). The cDNA sequence corresponding to mature bovine BPI

protein is found to be moderately conserved at the nucleotide (75%) and amino acid

(63%) level with human BPI (Leong and Camerato, 1990). In contrast to human BPI,

studies on bovine BPI are very limited. Bovine-BPI- derived synthetic peptides (bBPIpeps) have not been tested for their bactericidal activity or inhibitory activity against Gram- negative bacterial strains that cause mastitis. Whether such peptides are efficacious in biological fluids such as milk and blood is also unknown. The objective of the current study is to evaluate the efficacy of bBPIpeps for their antibacterial and LPS-neutralizing

activity. In this study we determined (1) the bactericidal activity of three bovine

synthetic peptides; bBPIpep-I (24 aa), bBPIpep-II (35 aa), and bBPIpep-III (28 aa) against E.

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coIi; (2) the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) values for the peptides against strains of major Gram-negative

mastitis pathogens; and (3) the LPS neutralizing activity of each bBPIpeps.

MATERIALS AND METHOD

Biological Fluid & Broth Preparation

Milk and blood samples were collected from eight clinically healthy (antibiotic free) quarters of midlactating, first lactation Holstein cows. Animals were selected on the basis of milk somatic cell counts (SCC) of <150,000 and the absence of detectable bacterial growth from aspetic milk samples collected on three different days. For the preparation of whey, milk samples were centrifuged at 44,000 x g at 4 ºC for 30 min, and the fat layer was removed with a spatula. The skim milk was transferred into a sterile tube and centrifuged for another 30 min as described above. The translucent supernatant was aseptically transferred into a new sterile tube. Milk and whey samples were pasteurized by heating at 63 ºC for 30 min. For the preparation of serum, tail vein blood samples were collected in vacutainers containing gel and clot activator for serum separation (Becton Dickinson Corp., Franklin Lakes, NJ), spun at 1500 x g for 15 min and the clear serum aseptically transferred into sterile tubes. The serum samples were heat inactivated at 56 ºC for 30 min. An aliquot of all biological samples was plated on blood agar plates and samples that were free of detectable bacterial growth were stored at

-20 ºC. Brain heart infusion broth (BHI) and cation-adjusted-Muller-Hinton broth

(CAMHB) (Becton Dickinson Diagnostic Systems, Inc., Sparks, MD) were used as growth media for the in vitro bactericidal assay and antimicrobial susceptibility test, respectively.

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Bacteria

E. coli strain P4 (a gift of A. J. BramLey, Institute for Animal Health, Compton

Laboratory, Newbury, England), originally isolated from a clinical case of mastitis, was

used for the in vitro determination of the bactericidal activity of the synthetic b.BPIpep peptide in various biological fluids. Six isolates each of E. coli, K. pneumonia, S. marcescens and P. aeruginosa, four isolates of Enterobacter cloacae and one isolate of

Enterobacter aerogenes, all of which were isolated from clinical cases of bovine mastitis

(gift of Y. Schukken, Cornell University, Ithaca, NY), were used for the antimicrobial susceptibility test. E. coli ATCC 25922 and S. aureus ATCC 29213 (Gift of Dr. Bob

Walker, FDA, Laurel, MD) were used as reference strains for the antimicrobial susceptibility test. All strains were maintained on blood agar plates.

Antimicrobial Synthetic bBPIpeps

The bovine synthetic peptides; bBPIpep-I (KWKAQKRFLKKSKVGWLIQLFHKK), 24 aa), bBPIpep-II (NSQIRPLPDKGLDLSIRDASIKIRGKWKARKNFIK, 35 aa), and bBPIpep-III

(VRIHISGSSLGWLIQLFRKRIESLLQKS, 28 aa) and control peptide SHLT-1

(MCHWAGGASNTGDARGDVFGKQAG, 24 aa) were commercially synthesized (Genemed

Synthesis, Inc., South San Francisco, CA). The bBPIpep-II and bBPIpep-III correspond to

amino acid residues 65-99 and 142-169 respectively of mature bovine BPI protein. The bBPIpep-I is a fusion peptide corresponding to amino acid residues 90-99 and 148-161 of mature bovine BPI protein. The peptides were reconstituted in citrate buffered saline

(CBS) [20mM sodium citrate, 150mM sodium chloride, 0.1% poloxamer, and 0.002% polysorbate 80, pH 5.0, (Sigma Chemical Co., St. Louis, Mo] to a final concentration of

10 mg/mL and were stored at -20ºC until use. The synthetic bBPIpeps were tested for the

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presence of endotoxin by the limulus amoebocyte lysate (LAL) test according to the manufacturer’s instructions (Cambrex Bio Science Walkersville, Inc., Walkersville, MD).

Tetracyline and polymyxin-B (Sigma Chemical Co.) were reconstituted in endotoxin free water (Cambrex Bio Science Walkersville, Inc. Walkersville, MD) and aliquots were stored at -20 ºC and used as positive controls for the MIC and LAL assays respectively.

All bBPI antimicrobial peptide aliquots were dissolved at two fold higher concentration than the highest concentration assayed and were thawed only once.

Microbial Growth Assays

Overnight bacterial cultures were diluted 1:1000 in BHI and incubated shaking at

37 ºC for 2 hours. Bacteria in log phase were diluted 1:10 in BHI to obtain a final concentration of 1 x 106 CFU/mL. The bacterial inoculum (0.01 mL) was added to a 1.5

mL sterile microcentrifuge containing 0.04 mL of milk, serum or whey. An aliquot (0.05

mL) of either BPI peptide, or control peptide, or CBS alone was added to each tube. The

samples were then shaken @ 100 rpm for 6 hours at 37 ºC. The sample mixtures were

subsequently serially diluted and plated on MacConkey agar plates. The plates were

incubated overnight at 37 ºC and the next day the colonies were enumerated.

Antimicrobial Susceptibility Test to Determine MIC and MBC Values

To determine the spectrum of activity of the three bBPIpeps against major Gram-

negative pathogens, the MIC and MBC values were determined against selected clinical

isolates of bovine mastitis by the microdilution method, according to the Clinical

Laboratory Standards Institute guidelines (CLSI, 2002). To ensure the quality of the

assay, each test was run with reference strains as recommended by CLSI. The quality

control (QC) range of MIC values for tetracycline was within the acceptable range.

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Briefly, 100 µL of the highest concentration of the antimicrobial was serially diluted in a

96 well plate. The transmittance of bacterial inoculum was adjusted to 0.5 Mcfarland (108

CFU/mL) using a colorimeter. A 100-fold dilution of 108 CFU/mL was made and 50 µL

of the bacterial inoculum was added to each well. The plates were incubated for 16-20 h

at 35ºC with ambient air circulation and no shaking. After incubation the plates were read

to determine the MIC range using a magnifying glass plate reader. MBC range was

determined by plating 0.01 mL from clear wells and counting the number of CFU.

LPS Neutralization Assay

The ability of the bBPIpeps to neutralize LPS was determined using the LAL assay.

The bBPIpeps or polymixin-B (PMB) were incubated with 1 ng of LPS in a 500 µl reaction volume of endotoxin free water shaking @100 rpm for 30 min @ 37 ºC.

Following incubation, the amount of free endotoxin was determined according to the

manufacturer’s instructions. Briefly, 50 µl of the above mixture was placed in a

microtiter plate (Costar). The reaction was initiated by the addition of an equal volume

of amoebocyte lysate. Following incubation @ 37 ºC for 15 min, 100 µl of chromogenic

substrate was added and the plate incubated for 5-10 min @ 37 ºC. The reaction was

stopped by the addition of 50 µl of acetic acid and the absorbance was measured at 405

nm using a microplate reader (Biotec Instruments, Inc., Winooski, VT). The amount of

non-bound LPS was extrapolated from a standard curve and the percent inhibition

calculated. The assay was replicated twice and for each replicate the measurement was

performed in quadruplicate.

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Statistical methods

A paired t test was used to determine statistical significance between experimental and control groups. A P value of < 0.05 was considered significant (Prism version 4.0 for Windows; GraphPad Software Inc., San Diego, CA).

RESULTS

Growth inhibition of E. coli P4 by bBPIpeps in whole milk, serum, whey and broth

The three bBPIpeps: bBPIpep-I (aa 90-99 and 148-161, fusion peptide); bBPIpep-II (aa

65-99); and bBPIpep-III (aa 142-169) were synthesized based on the amino acid sequence

corresponding to the two domains in the human BPI (amino acids 65-99 and 148-169)

(Gray and Haseman, 1994; Jiang et al., 2004). The efficacy of the three peptides to

inhibit the growth of E. coli strain P4 in various biological fluids, including milk, whey,

serum and broth were assayed. The bBPIpep-I (Table 1) exhibited complete bactericidal

activity in serum and whey at 10 µg/mL and at 1 µg/mL in broth. Significant bacterial

growth inhibitory effect was detected for bBPIpep-I in whey 1 µg/mL (P=0.009). In whole

milk, the peptide exhibited a growth inhibitory effect at 200 µg/mL and higher. However,

the peptide had no bactericidal activity in milk at any concentration tested. The control

peptide displayed no significant bactericidal or inhibitory effect in milk and broth at the

highest concentration tested for the bBPIpep (i.e., 2 mg/mL, data not shown). The bBPIpep-

II exhibited no bactericidal or growth inhibitory effect against E. coli strain P4 in milk, serum and broth. However, in whey a growth inhibitory effect was noticed at 100 µg/mL concentration (Table 2). The bBPIpep-III was found to have bactericidal activity against E. coli strain P4 when tested in broth at 100 µg/mL concentration. Significant growth inhibitory effect (a log difference) was found between the treatment and control in milk,

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whey and serum at the highest concentration tested (Table 3). Control peptide SHLT-1 had no bactericidal activity.

Table 1: Antimicrobial activity of bBPIpep-I synthetic peptide.

Controla a Conc of Conc of bBPIpep-I (CFU Log10) * Sample N SHLT-1 bBPIpep (CFU Log10) (No bBPIpep-I ) P value Mean SE Mean SE BROTH 4 10µg 0 0 8.98 0.24 P<0.0001 4 1 µg 0 0 8.98 0.24 P<0.0001 4 0.1 µg 8.79 0.30 8.98 0.24 P=0.0691 4 0.01 µg 8.91 0.16 8.95 0.20 P=0.4518 4 100 µg 8.81 0.03 8.91 0.01 P=0.0214 4 10 µg 8.66 0.13 8.73 0.10 P=0.1021 SERUM 8 100 µg 0 0 8.40 0.05 P<0.0001 8 10 µg 0 0 8.40 0.05 P<0.0001 8 1 µg 8.15 0.06 8.40 0.05 P=0.0001 8 0.1 µg 8.25 0.03 8.40 0.05 P=0.0044 8 0.01 µg 8.30 0.05 8.40 0.05 P=0.0771 MILK 8 2 mg 6.55 0.27 8.69 0.05 P<0.0001 8 200 µg 7.89 0.12 8.69 0.05 P<0.0001 8 20 µg 8.65 0.08 8.69 0.05 P=0.2447 4 1 mg 8.86 0.04 8.68 0.11 P=0.149 WHEY 8 100 µg 0 0 8.27 0.05 P<0.0001 8 10 µg 0 0 8.27 0.05 P<0.0001 8 1 µg 7.97 0.04 8.27 0.05 P=0.0009 8 0.1 µg 8.17 0.03 8.27 0.05 P=0.0898

The bactericidal and growth inhibition activity of bovine BPI protein derived synthetic peptide bBPIpep-I and control peptide SHLT-1was tested against E. coli P4 strain, a clinical mastitis isolate, in milk, whey, serum and broth. a Values shown are the means ± standard error of the replicates for total number of colony forming units of E. coli bacteria enumerated the next day. * Number of replicates for each experimental value.

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Table 2: Antimicrobial activity of bBPIpep-II synthetic peptide.

Conc Controla a of bBPIpep-II (CFU Log10) * Sample N bBPIpep (CFU Log10) (No bBPIpep-II) P value Mean SE Mean SE BROTH 4 100ug 8.70 0.03 8.93 0.02 P=0.0003 4 10ug 8.80 0.02 8.93 0.02 P=0.0065 4 1ug 8.87 0.04 8.93 0.02 P=0.0768 4 0.1ug 8.84 0.05 8.97 0.05 P=0.0854

SERUM 8 100ug 8.07 0.05 8.40 0.05 P=0.0005 8 10ug 8.23 0.03 8.40 0.05 P=0.0008 8 1ug 8.28 0.04 8.40 0.05 P=0.0135 8 0.1ug 8.27 0.03 8.40 0.05 P=0.0089

MILK 8 2mg 8.06 0.12 8.69 0.05 P=0.0002 8 200ug 8.54 0.10 8.69 0.05 P=0.0429 8 20ug 8.69 0.06 8.69 0.05 P=0.4979

WHEY 8 100ug 7.36 0.30 8.28 0.24 P=0.0096 8 10ug 8.16 0.16 8.28 0.24 P=0.3157 8 1ug 8.26 0.18 8.28 0.24 P=0.4699 8 0.1ug 8.47 0.14 8.20 0.20 P=0.0521

The bactericidal and growth inhibition activity of bovine BPI protein derived synthetic peptide bBPIpep-II was tested against E. coli P4 strain, a clinical mastitis isolate, in milk, whey, serum and broth. a Values shown are the means ± standard error of the replicates for total number of colony forming units of E. coli bacteria enumerated the next day . * Number of replicates for each experimental value.

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Table 3: Antimicrobial activity of bBPIpep-III synthetic peptide.

Controla a Conc bBPIpep-III (CFU Log10) * Sample N of BPI (CFU Log10) (No bBPIpep-II P value Mean SE Mean SE BROTH 4 100ug 0 0 8.69 0.06 P<0.0001 4 10ug 7.51 0.04 8.69 0.06 P<0.0001 4 1ug 8.56 0.02 8.69 0.06 P=0.0837 4 0.1ug 8.73 0.07 8.69 0.06 P=0.3000

SERUM 8 100ug 7.96 0.07 8.40 0.05 P=0.0007 8 10ug 8.29 0.04 8.40 0.05 P=0.0695 8 1ug 8.38 0.03 8.40 0.05 P=0.3622 8 0.1ug 8.42 0.05 8.40 0.05 P=0.3948

MILK 8 2 mg 7.99 0.07 8.69 0.05 P<0.0001 8 200ug 8.55 0.07 8.69 0.05 P=0.0759 8 20ug 8.67 0.03 8.69 0.05 P=0.3751

WHEY 8 100ug 7.45 0.21 8.32 0.23 P=0.0014 8 10ug 8.10 0.20 8.28 0.24 P=0.2321 8 1ug 8.44 0.14 8.28 0.24 P=0.1515 8 0.1ug 8.29 0.18 8.20 0.20 P=0.7260

The bactericidal and growth inhibition activity of bovine BPI protein derived synthetic peptide bBPIpep-III Was tested against E. coli P4 strain, a clinical mastitis isolate, in milk, whey, serum and broth. a Values shown are the means ± standard error of the replicates for total number of colony forming units of E. coli bacteria enumerated the next day . * Number of replicates for each experimental value.

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MIC and MBC values of bBPIpeps against major Gram-negative mastitis pathogens

To determine the spectrum of antimicrobial activity, the three bBPIpeps were tested

against various isolates of major Gram-negative mastitis pathogen by the microdilution

susceptibility assay. Each test was performed in triplicate by repeating the assay on three

different days. On each individual test day, samples were run in duplicate. Of the three

bovine synthetic peptides, the bBPIpep-I was found to have lower MIC and MBC values

for selected isolates of Gram-negative mastitis pathogens (Table 4). Consistent with the

in vitro assay, the MIC and MBC values for bBPI pep-II were greater than the highest

concentration (>256 µg/mL) tested and the bBPI pep-III exhibited inhibitory and

bactericidal activity against isolates of E. coli in the concentration range of 126-256

µg/mL. The average difference in MIC and MBC values for bBPIpep-I against the mastitis

pathogens were only 1-2 fold, whereas the difference in these values for tetracycline was

much higher as the MBC values were greater than 128 µg/mL (Table 4). All isolates of

S. marcescens were found to be resistant to the three bBPIpeps as the MIC and MBC

values were greater than 512 µg/mL and they were also found to be less susceptible to

tetracycline as the MBC values was higher. The MIC values were much lower for

bBPIpep-I (MIC = 32-64 µg/mL) when compared with tetracycline (MIC > 128 µg/mL)

against one isolate of Klebsiella spp. and three isolates of Enterobacter spp.

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Table 4: Minimum Inhibitory Concentration (MIC) and Minimun Bactericidal Concentration (MBC) values of bBPIpeps against clinical isolates of major Gram-negative mastitis pathogens.

Microorganism Isolates bBPIpep-I(n=3) bBPIpep-II(n=3) bBPIpep-III (n=3) Tetra (n=1) MIC MBC MIC MBC MIC MBC MIC MBC Escherichia coli CI #1 16 16-32 >256 >256 256 256 4 128 CI#2 32-64 32-64 >256 >256 256 256 4 >128 CI#3 32-64 32-64 >256 >256 128-256 128-256 4 >128 CI#4 32-64 64 >256 >256 128-256 128-256 4 >128 CI#5 64 64 >256 >256 256 256 4 128

Ci#6 16-64 32-64 >256 >256 128-256 128-256 1 >128 Klebsiella spp. CI #1 32-64 32-64 >256 >256 >256 >256 64 >128 CI#2 32-64 32-64 >256 >256 >256 >256 128 >128 CI#3 32-64 32-64 >256 >256 >256 >256 1 >128 CI#4 32-64 32-64 >256 >256 256 256 64 >128 CI#5 32-64 32-64 >256 >256 >256 >256 16 >128 Ci#6 64 64 >256 >256 >256 >256 0.5 128 Pseudomonas spp. CI #1 128 128 >256 >256 >256 >256 32 >128 CI#2 128 128 >256 >256 >256 >256 16 >128 CI#3 64 64 >256 >256 >256 >256 32 128 CI#4 128 128 >256 >256 >256 >256 16 >128 CI#5 128 128 >256 >256 >256 >256 32 >128 CI#6 128 128 >256 >256 >256 >256 16 >128 Serratia spp. CI #1 >512 >512 >512 >512 >512 >512 32 >128 CI#2 >512 >512 >512 >512 >512 >512 64 >128 CI#3 >512 >512 >512 >512 >512 >512 64 >128 CI#4 >512 >512 >512 >512 >512 >512 64 >128 CI#5 >512 >512 >512 >512 >512 >512 64 >128 CI#6 >512 >512 >512 >512 >512 >512 64 >128 Enterobacter spp. CI #1 32 64 >256 >256 >256 >256 128 >128 CI#2 32 32-64 >256 >256 256 256 4 >128 CI#3 64 64 >256 >256 >256 >256 128 >128 256- 256- CI#4 64 64 >256 >256 >256 >256 4 >128 256- CI#5 64 64 >256 >256 >256 >256 128 >128 0.5- 64 E. coli ATCC 25922 32-64 64 >256 >256 128-256 128-256 16 64- 128- S. aureus ATCC 29213 64 128 >256 >256 128-256 128-256 <0.25 >128

Tetracyline was used as positive control. E. coli ATCC 25922 and S. aureus ATCC 29213 were the two reference strains used as recommended by CLSI. Values reported are µg/mL. CI: Clinical isolates.

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LPS neutralizing activity of bBPIpeps

To determine whether bBPIpeps were able to neutralize LPS, increasing

concentrations were incubated with LPS and the resulting mixture assayed with the LAL

assay (Fig 1). At a concentration ≥ 30 µg/mL the LPS-neutralizing activity of bBPIpep-III was equivalent to PMB, which was used as a positive control. At concentration 100

µg/mL the percentage inhibition of bBPIpep-I was equivalent to PMB and bBPIpep-III. At the maximum concentration tested (100 µg/mL) bBPIpepII was less efficient (>50%) when

compared to other peptides. However, no LPS binding activity was detected for the

control peptide.

LPS 1 ng/mL 100 bBPIpep-I bBPIpep-II 75 bBPIpep-III PMB 50 Co.Pep

%inhibition 25

0 0 25 50 75 100 125 Antimicrobials (µg/mL)

Fig. 1: Percent inhibition of purified LPS by bovine BPI derived synthetic peptides. Antimicrobial at various concentrations were tested against LPS (concentration 1ng/mL). The standard error bars are too small to be seen in the figure. Polymixin B (PMB) and SHLT-1 control peptide (Co. pep) were the positive and negative controls.

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DISCUSSION

The in vitro study (chapter 4) indicated that a human BPI derived synthetic peptide containing amino acid sequences from two functional domains (90-99 and 148-

161 aa) exhibited both antimicrobial and LPS-neutralizing activity. Studies have shown

that the three functional domains (Do) of human BPI corresponding to amino acid

regions 17-45 (Do.I), 65-99 (Do.II), and 142-169 (Do.III) have LPS-neutralizing activity

and bactericidal activity. In vitro and in vivo studies (Jiang et al., 2004) have shown that a synthetic peptide derived from human BPI corresponding to aa 148-161 had LPS- neutralizing activity. The bactericidal effect could be identified specifically within 85-99 aa of the functional human BPI protein. In another study, the peptide corresponding to

90-99 aa sequence of mature human BPI demonstrated a 10 fold increase in bactericidal activity but it lacked LPS-neutralizing activity (Little et al., 1994; Gray and Haseman,

1994). It was demonstrated that hBPIpep with aa sequences from two functional domains

of BPI N-terminal protein exhibited both LPS-neutralizing and antibacterial activity,

here the study is extended to characterize the biological activity of the peptides derived

from bovine BPI functional domains that correspond to human BPI domains.

In the present study, where the objective is to develop data perhaps leading to a

potential new therapeutic agent for treatment of mastitis, three bovine BPI synthetic

peptides corresponding to the human functional domains (bBPIpep-I, bBPIpep-II, and

bBPIpep-III) were tested: (1) in vitro for their antimicrobial activity against E. coli, a

common causative organism of coliform mastitis, in bovine biological fluids including

milk, serum and whey; (2) the MIC and MBC values were determined for the three

peptides against clinical mastitis isolates of E. coli, K. pneumonia, S. marcescens and P.

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aeruginosa, and Enterobacter spp.; and (3) LPS-neutralizing activity was determined by the LAL assay.

Our data show that the bovine-BPI-derived synthetic peptide bBPIpep-I exhibits

bactericidal activity in broth, bovine serum and whey (Table 1) as did the human BPI

analog. The bBPIpep-I exhibited bactericidal activity in broth (1 µg/ mL) and whey (10 µg/

mL) at lower concentration when compared with the human-BPI-derived synthetic

peptide (10 µg/ mL in broth and 100 µg/ mL in whey). The bBPIpep-I concentration

required for bactericidal activity in serum was similar for that in broth. The current study

is the first to evaluate the therapeutic potential of bovine-derived-synthetic peptides

hence, there are no direct data for comparison from the literature. However, the

bactericidal activity of bBPIpep-I against E. coli P4 is significantly higher than reported for

human-BPI-derived: peptide 90-99 (Gray and Haseman, 1994); peptide 85-99 (Little et

al., 1994). This enhanced antimicrobial activity of bBPIpep could be due to additional

amino acid sequence corresponding to 148-161 residues, as a similar enhancement in bactericidal activity was observed when the amino acid sequence was elongated at the amino and carboxyl end of the peptide (90-99) (Gray and Haseman, 1994). In their

study, it was also observed that addition of cysteine at the N-terminal end (C# 90-99)

enhanced the bactericidal activity of the peptide (90-99). Also, it has been reported that

the C# 90-99 peptide exhibited a bactericidal effect against P. aeruginosa at the

concentration of 2.1 µg/mL and at 10-times higher concentration against rough strain

E. coli B and P. cepacia. In milk, the bBPIpep-I peptide exhibited significant growth

inhibition against E. coli P4 strain at ≥ 1 mg/mL concentration (Table 1). Absence of

bactericidal activity in milk could be attributed to the presence of divalent cations like

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Ca++ and Mg ++. The presence of the divalent cations may compete with BPI peptides for its binding site on the outer wall of Gram-negative bacteria, as a similar inhibitory effect of divalent cations on vancomycin has been reported (Russell, 1967). Since there is no

significant difference in bacterial growth number between the control samples for milk

and broth, the lack of bactericidal effect in milk could be attributed to the constituents in

milk, such as the high level of cations in ionic and bound form (Silanikove et al., 2003).

++ Also, the bBPIpeps can be expected to be more efficacious as the milk Ca levels are

lower in mastitis milk (Schalm et al., 1971). The lack of bactericidal activity of bBPIpep-II

(aa 65-99) in broth (Table 2), bovine serum and whey and bBPIpep-III in bovine serum and

whey (Table 3) at the highest concentration tested could be attributed to the peptide size.

The data is consistently similar to that reported by Gray and Haseman (1994) for corresponding human BPI amino acid sequences.

To determine the spectrum of activity of the bovine BPI synthetic peptides, the

MIC and MBC values were determined by the microdilution method (Table 4). Among

the three peptides tested, bBPIpep-I was found to have antibacterial activity, the results are

comparable to an in vitro study conducted in our laboratory for hBPIpep, as this is also the

first study to determine the MIC and MBC values for bBPIpeps. Unlike tetracycline, the

MIC and MBC values for a given isolate were narrow (1-2 fold difference). Therefore,

the mechanism required for killing and inhibiting the growth of the bacteria could be

similiar. Among the isolates tested, isolates of E. coli were found to be highly susceptible

(with low MIC and MBC values) compared to Serratia spp. A study by Weiss et al.

(1975) reported that Serratia spp. exhibited antimicrobial resistance against BPI holoprotein. In the humans, Serratia marcescens is known to cause various infections due

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to a resistance mechanism against a broad spectrum of antibiotics like ceftazidime (Hidri et al., 2005), beta-lactam and aminoglycoside (Goldstein et al., 1983), and other antimicrobials (Kumar and Worobec, 2005). Two possible explanations for its mode of resistance could be: (i) efflux mechanisms exhibited against antimicrobials (Berlenga et al., 2000); or (ii) decreased permeability to antimicrobials due to an alteration in inner and outer membrane permeability (Lannigan and Bryan, 1985; Hashizume et al., 1993;

Hechler et al., 1989). Further experimental studies are needed to determine the exact mode of the resistance mechanism against BPI-derived-synthetic peptide. For example, treatment with EDTA, a metal chelator, would determine whether decreased permeability is a major resistance mechanism exhibited by Serratia spp. against antimicrobial agent bBPIpeps.

The emergence of such antibiotic resistance bacteria depends on selective

antibiotic pressure the bacteria are being exposed to in their environment. A classic

example of selective pressure is the use of antibiotics in food animals at sub-therapeutic

levels as growth promoters or as prophylaxis which seems to have created a large source

of resistance genes mediated by horizontal transfer from commensal organisms in the gut of the animals to pathogens like Salmonella enterica, E. coli, etc., (Gebreyes and Altier,

2002; Witte, 2000). Similiarly, a classic example of emergence of antibiotic resistance in

lactating cows due to the use of antibiotics, is intramammary infection caused by

Staphylococcus aureus (Berghash et al., 1983; Teuber, 2001). Current antibiotics used for

veterinary therapeutics belong to essentially the same classes of antibiotics used in human

therapeutics. Hence, development of antibiotic resistance in farm animals for these

antibiotics could be a major public health problem if transmitted (horizontal transfer via

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plasmid) to organisms that are pathogenic to humans. The development of synthetic

peptides that are derived from natural endogenous antimicrobial proteins when used as an

alternative to antibiotics will reduce such threats to public health. As shown here, bovine-

BPI-derived synthetic peptides could be one such alternative against Gram-negative

pathogens, as it is not commonly used in human treatment. Therefore, if a resistance

mechanism develops against BPI it will still pose less threat to public health.

We have shown by in vitro assays that the bBPIpeps are potential LPS-binding

agents. As determined by LAL assay, a highly sensitive assay to detect the presence of

free LPS in trace amounts, the bBPIpeps inhibited the LPS-induced LAL reaction at

varying degrees. The percent inhibitions of LPS by bBPIpeps are comparable with the published report (Jiang et al., 2004) for BNEP peptide (148-161) and the result for hBPIpep in our laboratory. At 30 µg/mL and higher concentration bBPIpeps-III was as potent

as PMB which was used as positive control. At 100 µg/mL bBPIpep-I was equally

competent to that of PMB while bBPIpep-II exhibited less than 50 percent activity. The

control peptide (SHLT-1) exhibited no LPS-neutralizing activity. The present data

demonstrates bBPIpeps LPS-neutralizing activity strongly establishes bBPIpep-I and

bBPIpep-II as anti-inflammatory agents against Gram-negative mastitis pathogens. As the

current therapeutic measures remain suboptimal, a significant percentage of cows with

acute coliform mastitis develop a systemic response due to endotoxemia. It is well

established that LPS is a potent mediator of systemic inflammatory response and affects

the reproductive performance in dairy cattle (Moore et al., 1991; Janosi et al., 1998).

Drugs alternatives to antibiotics that have anti-inflammatory properties and potency to

increase permeability should be considered as therapeutics to treat dairy cows for

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intramammary infection especially when there is evidence of systemic involvement

(Black, 1977; Gruet et al., 2001). Current antibiotics used in mastitis therapy do not bind or neutralize the LPS molecule; therefore, development of antimicrobials targeting the lipid A moiety of LPS could be a potential antibacterial and anti-inflammatory agent

(Tyler et al., 1990; Wyckoff et al., 1998). One such potential agent is BPI, an endogenous antimicrobial expressed in primary granules of neutrophils. Human BPI has been well studied for its antibacterial activity and its synthetic peptides could block LPS-mediated inflammatory responses by binding to the lipid moiety of LPS (Elsbach et al., 1979; Jiang et al., 2004). The therapeutic efficacy of 23 kDa recombinant N-terminal fragment of BPI has been evaluated against Gram-negative pneumonia in mice (Kelly et al., 1993), and in children with meningococcal sepsis (Giroir et al., 1997). Similiar to the above studies the therapeutic efficacy of bBPIpeps has to be evaluated for its efficacy in vivo. Alexander et

al. (2004) have demonstrated that in vivo gene transfer of human BPI protected mice

against endotoxemia. Such BPI trangene-based therapeutic method in bovines could relatively result in high sustainable level of BPI concentration in biological fluids. Such model could be developed and evaluated to treat bovine mastitis caused by Gram- negative bacteria. In vivo gene-transfer could be cost-effective to meet out the high

therapeutic dose required to treat mastitis. Expression of mouse BPI is mediated through

TLR4-TRIF-dependent pathway and secretion of BPI is delayed (Eckert et al., 2006).

This is probably to ensure that the host immune system is first activiated by LPS. Similiar

study in bovine would help in understanding the underlying mechanism of death due to endotoxemia caused by Gram-negative mastitis. Variation of BPI protein expression has been found in various cell lines of intestinal epithelial cells (Canny et al., 2006).

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However, the expression of BPI in bovine mammary epithelial cells or milk has not been reported in literature. Study on regulation of BPI expression in mammary gland during

various stages of lactation will provide insight into the mastitis susceptibility to E. coli during different stages of lactation. The present data demonstrate that bovine-BPI-derived synthetic peptides may act as a potential antimicrobial and anti-inflammatory agents against Gram-negative intramammary infections and associated systemic complications.

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Hidri, N., Barnaud, G., Decre, D., Cerceau, C., Lalande, V., Petit, J.C., Labia, R., and Arlet, G. 2005. Resistance to ceftazidime is associated with a S220Y substitution in the omega loop of the AmpC beta-lactamase of a Serratia marcescens clinical isolate. J Antimicrob Chemother 55:496-499. Hillerton, J.E., Bramley, A.J., Staker, R.T., and McKinnon, C.H. 1995. Patterns of intramammary infection and clinical mastitis over a 5 year period in a closely monitored herd applying mastitis control measures. J Dairy Res 62:39-50. Hogan, J., and Larry Smith, K. 2003. Coliform mastitis. Vet Res 34:507-519. Hospido, A., and Sonesson, U. 2005. The environmental impact of mastitis: a case study of dairy herds. Sci Total Environ 343:71-82. Huang, K., Conlon, P.J., and Fishwild, D.M. 1994. A recombinant amino-terminal fragment of bactericidal/permeability increasing protein (rBPI23) inhibits soluble CD14-mediated lipopolysaccharide-induced endothelial adherence for human neutrophils. Shock 1:81-86. Jacoby, G.A. 1996. Antimicrobial-resistant pathogens in the 1990s. Annu Rev Med 47:169-179. Janosi, S., Huszenicza, G., Kulcsar, M., and Korodi, P. 1998. Endocrine and reproductive consequences of certain endotoxin-mediated diseases in farm mammals: a review. Acta Vet Hung 46:71-84. Jiang, Z., Hong, Z., Guo, W., Xiaoyun, G., Gengfa, L., Yongning, L., and Guangxia, X. 2004. A synthetic peptide derived from bactericidal/permeability-increasing protein neutralizes endotoxin in vitro and in vivo. Int Immunopharmacol 4:527- 537. Kelly, C.J., Cech, A.C., Argenteanu, M., Gallagher, H., Shou, J., Minnard, E., and Daly, J.M. 1993. Role of bactericidal permeability-increasing protein in the treatment of gram-negative pneumonia. Surgery 114:140-146. Kossaibati, M.A., and Esslemont, R.J. 1997. The costs of production diseases in dairy herds in England. Vet J 154:41-51. Kumar, A., and Worobec, E.A. 2005. Cloning, sequencing, and characterization of the SdeAB multidrug efflux pump of Serratia marcescens. Antimicrob Agents Chemother 49:1495-1501. Lannigan, R., and Bryan, L.E. 1985. Decreased susceptibility of Serratia marcescens to chlorhexidine related to the inner membrane. J Antimicrob Chemother 15:559- 565. Leong, S.R., and Camerato, T. 1990. Nucleotide sequence of the bovine bactericidal permeability increasing protein (BPI). Nucleic Acids Res 18:3052. Little, R.G., Kelner, D.N., Lim, E., Burke, D.J., and Conlon, P.J. 1994. Functional domains of recombinant bactericidal/permeability increasing protein (rBPI23). J Biol Chem 269:1865-1872. Makovec, J.A., and Ruegg, P.L. 2003. Results of milk samples submitted for microbiological examination in Wisconsin from 1994 to 2001. J Dairy Sci 86:3466-3472. Moore, D.A., Cullor, J.S., BonDurant, R.H., and Sischo, W.M. 1991. Preliminary field evidence for the association of clinical mastitis with altered interestrus intervals in dairy cattle. Theriogenology 36:257-265.

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Moore, D.A., and O'Connor, M.L. 1993. Coliform Mastitis: its possible effects on reproduction in dairy cattle. Pages 162-166 in Proc. 32nd Annu. Meet. Natl. Mastitis Counc., Kansas City, Mo. Natl. Mastitis Counc., Inc. Arlington, VA. Nair, M.K., Joy, J., Vasudevan, P., Hinckley, L., Hoagland, T.A., and Venkitanarayanan, K.S. 2005. Antibacterial effect of caprylic acid and monocaprylin on major bacterial mastitis pathogens. J Dairy Sci 88:3488-3495. Oliver, S.P., and Mitchell, B.A. 1983. Susceptibility of bovine mammary gland to infections during the dry period. J Dairy Sci 66:1162-1166. Ooi, C.E., Weiss, J., Doerfler, M.E., and Elsbach, P. 1991. Endotoxin-neutralizing properties of the 25 kDa N-terminal fragment and a newly isolated 30 kDa C- terminal fragment of the 55-60 kDa bactericidal/permeability-increasing protein of human neutrophils. J Exp Med 174:649-655. Phillips, I., Casewell, M., Cox, T., De Groot, B., Friis, C., Jones, R., Nightingale, C., Preston, R., and Waddell, J. 2004. Does the use of antibiotics in food animals pose a risk to human health? A critical review of published data. J Antimicrob Chemother 53:28-52. Piddock, L.J. 1996. Does the use of antimicrobial agents in veterinary medicine and animal husbandry select antibiotic-resistant bacteria that infect man and compromise antimicrobial chemotherapy? J Antimicrob Chemother 38:1-3. Russell, A.D. 1967. Effect of magnesium ions and ethylenediamine tetra-acetic acid on the activity of vancomycin against Escherichia coli and Staphylococcus aureus. J Appl Bacteriol 30:395-401. Sawant, A.A., Sordillo, L.M., and Jayarao, B.M. 2005. A survey on antibiotic usage in dairy herds in Pennsylvania. J Dairy Sci 88:2991-2999. Schrick, F.N., Hockett, M.E., Saxton, A.M., Lewis, M.J., Dowlen, H.H., and Oliver, S.P. 2001. Influence of subclinical mastitis during early lactation on reproductive parameters. J Dairy Sci 84:1407-1412. Shea, K.M. 2004. Nontherapeutic use of antimicrobial agents in animal agriculture: implications for pediatrics. Pediatrics 114:862-868. Silanikove, N., Shapiro, F., and Shamay, A. 2003. Use of an ion-selective electrode to determine free Ca ion concentration in the milk of various mammals. J Dairy Res 70:241-243. Smith, G.W., Gehring, R., Craigmill, A.L., Webb, A.I., and Riviere, J.E. 2005. Extralabel intramammary use of drugs in dairy cattle. J Am Vet Med Assoc 226:1994-1996. Smith, K.L., Todhunter, D.A., and Schoenberger, P.S. 1985. Environmental mastitis: cause, prevalence, prevention. J Dairy Sci 68:1531-1553. Teuber, M. 2001. Veterinary use and antibiotic resistance. Curr Opin Microbiol 4:493- 499. Tyler, J.W., Cullor, J.S., Spier, S.J., and Smith, B.P. 1990. Immunity targeting common core antigens of gram-negative bacteria. J Vet Intern Med 4:17-25. Vandermeer, T.J., Menconi, M.J., O'Sullivan, B.P., Larkin, V.A., Wang, H., Kradin, R.L., and Fink, M.P. 1994. Bactericidal/permeability-increasing protein ameliorates acute lung injury in porcine endotoxemia. J Appl Physiol 76:2006- 2014.

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CHAPTER 6

THE BOVINE INNATE IMMUNE RESPONSE DURING EXPERIMENTALLY-

INDUCED Pseudomonas aeruginosa and Escherichia coli MASTITIS

INTRODUCTION

Mastitis caused by Gram-negative bacteria from the environment continues to be

a major challenge to the U.S. dairy industry despite implementation of several control

strategies (Jackson and Bramley, 1983; Erskine et al., 1991). Escherichia coli, normal

inhabitants of the gastrointestinal tract of cattle, account for the majority of clinical

mastitis cases caused by environmental organisms (Barekma et al., 1998; Hogan and

Smith, 2003). The pathogenicity of a particular E. coli strain is mainly determined by its virulence factors such as adhesions, invasins, toxins and capsules. E. coli isolated from

mastitis milk and feces of cows with mastitis were compared with respect to biochemical properties and virulence factors to the E. coli isolates from fecal samples of healthy cows.

There were no potential biochemical markers or virulence genes specific for isolates that induced mastitis. E. coli could be potential opportunistic pathogens from the environment and are, therefore, the most common cause of fatal mastitis due to their ubiquitous nature

(Nemeth et al., 1994; Wenz et al., 2001).

Pseudomonas aeruginosa, one of the three most prevalent Gram-negative bacteria found in the cow’s environment is frequently cultured from bovine milk samples obtained from clinical mastitis cases (Ziv et al., 1971; Howell, 1972; Wilson et al., 1997; Barkema et al., 1998). The ubiquitous nature of P. aeruginosa in the environment makes it an ideal opportunistic pathogen for intramammary infection (Lyczak et al., 2000; Packer, 1977).

Intramammary infection with P. aeruginosa is characterized by an acute localized

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inflammation that later develops into chronic mastitis (Howell, 1972; Packer, 1977).

Development of systemic signs in Pseudomonas mastitis is not uncommon and fatal episodes of gangrenous mastitis with systemic complications are reported in dairy cows

(Howell, 1972; Packer, 1977; Crossman and Hutchinson, 1995; Power, 2003). Herd

outbreaks of clinical mastitis due to P. aeruginosa are reported and caused by a variety of

factors, including contaminated dry-cow therapy (Anderson et al., 1979; Nicholls et al.,

1981; Osborne et al., 1981), teat wipes (Daly et al., 1999; Power, 2003), and the wash-

water system used for washing udders (Curtis, 1969; Kirk and Bartlett, 1984; Erskine et

al., 1987). The pathogenicity of P. aeruginosa depends upon a variety of virulence

factors, including synthesis of different forms of lipopolysaccharide based on target site

(Goldberg and Pler, 1996), presence of pili and flagella (Van Delden and Iglewski, 1998;

Lyczak et al., 2000), secretion of toxins like exotoxin A and elastase (Ijiri et al., 1994;

Jenkins et al., 2004) and formation of polysaccharide-rich structures known as biofilm

(Van Delden and Iglewski, 1998).

Lipopolysaccharide (LPS), an essential component of the outer membrane of

Gram-negative bacteria initiates proinflammatory responses in the infected mammary

gland. These sometimes lead to septic shock and multiple organ failure (Glauser et al.,

1994; Bannerman et al., 2003; Schmitz et al., 2004; Lehtolainen et al., 2004). The innate

recognition of pathogen-associated molecular patterns (PAMPs) and activation of

proinflammatory responses is mediated through evolutionarily conserved pattern

recognition receptors known as toll-like receptors (TLRs). They form critical components

of the host innate defense mechanisms (Hoffman et al., 1999; Akira et al., 2001). TLR-4

detects the presence of Gram-negative bacteria in conjunction with membrane-associated

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CD14 (mCD14) (Chow et al., 1999). LPS-binding protein (LBP), though not a true pattern recognition receptor, aids in recognition of LPS by forming LBP-LPS complex and transferring it to CD14 (Ulevitch and Tobias, 1995).

A key component of the host innate immune response, upon recognition of the pathogen, is activation of proinflammatory cytokines that act as intracellular signal molecules mediating the process of inflammation and immune responses (Dinarello,

1996; Koj, 1996; Goodridge and Harnett, 2005). Following LPS recognition, there is complement activation and induction of pro-inflammatory cytokines such as TNF-α and

IL-1β that play important roles in both local and systemic inflammatory responses

(Dinarello, 1996; Thijs, et al., 1996). IL-1β induces expression of vascular-cell adhesion molecules (VCAM-1) on endothelial cells that facilitate neutrophil migration (Dinarello,

1996; Burne et al., 2001). Neutrophil trafficking to the site of infection is further mediated by induction of CXCL8/IL-8, which, in combination with C5a (a complement factor), are potent chemoattractants for neutrophils (Harada et al., 1994). IL-12 is also an

important cytokine because of its effect on the production of other immunoregulatory

cytokines, particularly IFN-γ, an activator of macrophages, neutrophils and nature killer

cells. (Trinchieri 1997; Hazlett et al., 2002). Further, resolution of inflammation is

mediated by up-regulation of anti-inflammatory cytokines like IL-10, and cytokines

belonging to the TGF superfamily (Letterio and Roberts, 1998; Ashcroft, 1999).

The incidence of bovine mastitis caused by E. coli and P. aeruginosa will

continue unabated due to the ubiquitous nature of the two organisms. Quantitation of

cytokines in clinical mastitis cases caused by Gram-negative bacteria will provide insight

into the immune responses occurring in the mammary gland. The cytokine response to P.

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aeruginosa was analyzed to determine if the cytokine induction pattern to different

Gram-negative bacteria is conserved in bovine mammary gland immunity. Though the immune response to E. coli mastitis has been well studied, little is known about its induction of other cytokines, including TGF-α, TGF-β1 and TGF-β2. In the present study,

the expression level of TGF-α, TGF-β1 and TGF-β2 were characterized in response to E. coli-induced bovine mastitis.

MATERIALS AND METHODS

Cows

Healthy mid-lactating cows were selected (n = 12 for E. coli and n = 10 for

P. aeruginosa) on the basis of milk SCC (somatic cell count) of <250,000 cells/mL and

the absence of detectable bacteria growth from three daily consecutive aseptic milk

samples plated on blood agar plates. The use and care of all animals in this study was

approved by the Beltsville Agricutural Research Center’s Animal Care and Use

Committee.

Intramammary challenge with bacteria

Prior to intramammary challenge, 10 mL of brain heart infusion broth (Becton-

Dickinson Diagnostic Systems, Inc, Sparks, MD) were inoculated with E. coli strain P4

and a strain of P. aeruginosa (gift of Dr. W.D. Schultze, USDA-ARS Beltsville

Agricultural Research Center, Beltsville, MD). Both the strains were originally isolated

from clinical mastitis cases. Following a 6 h incubation at 37ºC, 1 mL of the culture was

transferred to an aerating flask containing 99 mL of tryptic soy broth and incubated

overnight at 37 ºC. After incubation, the flasks were placed in an ice water bath and

mixed by swirling. A 1 mL aliquot from the flask was serially diluted in PBS and 0.1 mL

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of the resulting dilutions spread on trypticase soy agar plates containing 5% bovine blood and 0.1% esculin (Becton-Dickinson Diagnostic Systems, Inc, Sparks, MD). The plates were incubated overnight at 37 ºC while the aerating flasks containing the stock cultures were maintained at 4 ºC. After determining the concentration (CFU/mL) of stock cultures, the stock culture was diluted in PBS to yield a final estimated concentration of

100 and 35 CFU/mL for P. aeruginosa and E. coli respectively.

Immediately following the morning milking, the contralateral quarters of each animal were infused with either 2 mL of bacterial innoculum or PBS alone. To determine the actual number of bacteria infused, serial dilutions of the challenge innoculum were plated and incubated overnight. The number of bacteria infused into each quarter was determined to be 115 and 72 CFU for P. aeruginosa and E. coli, respectively. Throughout the study, aseptic milk samples were collected from control and infected quarters and plated on blood agar plates. Colonies displaying characteristics similar to those of P. aeruginosa and E. coli and that contained Gram-negative, oxidase-positive rods were considered positive for P. aeruginosa and E. coli. Confirmatory identification was performed by the Maryland Department of Agriculture Animal Health Section

Laboratory (College Park, MD).

Determination of milk somatic cell and circulating differential white blood cell counts

To quantitate somatic cells, milk samples were heated to 60 ºC and subsequently

maintained at 40ºC until counted on an automated cell counter (Fossomotic model 90,

Foss Food Technology, Hillerod, Denmark). For the determination of circulating differential white blood cell counts, tail vein blood samples were collected in Vacutainer® glass tubes containing K3 EDTA (Becton-Dickinson Corp, Franklin, Lakes, NJ), inverted

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x10, placed on a rocker for 15 min, and analyzed using a HEMAVET® 3700 automated

multi-species hematology system (CDC Technologies, Inc., Oxford, CT).

Whey and plasma preparation

For the preparation of whey, milk samples were centrifuged at 44,000 x g at 4 ºC

for 30 min and the fat layer removed with a spatula. The skimmed milk was decanted into

a clean tube and centrifuged again for 30 min as above and the translucent supernatant

and stored -70 °C. For the preparation of plasma, tail vein blood samples were collected

as above, inverted x10, centrifuged at 1500 x g for 15 min, and the clear plasma

supernatant collected and stored in aliquots at -70 ºC.

Enzyme linked immunosorbent assays (ELISA’s)

ELISA for Bovine Serum Albumin (BSA)

Milk BSA levels were assayed using a commercially available kit (Bethyl

Laboratories, Inc., Montgomery, TX) according to the manufacturer’s instructions with

only slight modification. Briefly, flat-bottom 96-well plates (Nalge Nunc International,

Rochester, N.Y.) were coated overnight at 4°C with 10µg/mL of sheep anti-bovine BSA

antibody diluted in 0.05 M sodium carbonate, pH 9.6. The plates were washed x4 with

0.05% Tween 20 diluted in 50mM Tris-buffered saline (TBS), pH 8.0, and subsequently

blocked with 2% fish skin gelatin (Sigma Chemical Co.) for 1 h at room temperature.

Plates were washed, and 100 µl of diluted whey samples (1:15,000) was added to each

well. Plates were incubated for 1 h at room temperature and subsequently washed as

described above. Sheep-anti-BSA conjugated to horseradish peroxidase (HRP) was diluted 1:60,000 in Tris-buffered saline (TBS) wash buffer containing 2% gelatin, and

100 µl of this solution was added to each well. Plates were incubated for 1 h at room

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temperature, washed as above, and 100 µl of 3,3´,5, 5´-tetramethylbenzidine (TMB) substrate solution (Kirkegaard and Perry laboratories Inc., Gaithersburg, MD.) added to each well. The reaction was stopped by the addition of 100 µl of 2 M H2SO4. and the absorbance read at 450 nm on a microplate reader (BioTec Instruments, Inc., Winooski,

VT). A background correction reading at 565 nm was subtracted from the 450-nm absorbance readings. The concentration of BSA was calculated by extrapolating from a standard curve run concurrent with the samples.

ELISA for TNF-α and IL-1β

Flat-bottom 96-well plates were coated overnight at 4°C with 100 µl of 0.05 M sodium carbonate, pH 9.6, containing either mouse anti-recombinant bovine TNF-α antibody (diluted 1:1,000) (Paape et al., 2002) or mouse anti-ovine IL-1β (5 µg/mL) antibody (Serotec, Inc., Raleigh, NC). The plates were washed four times with 0.05%

Tween 20 diluted in 50mM TBS, pH 8.0 and subsequently blocked with 2% fish skin gelatin (Sigma Chemical Co. St. Louis, Mo) for 1 h at room temperature. The plates were washed, and 100 µl of diluted whey samples of 1:5 and 1:1 were added to the anti- TNF-

α and anti-IL-1β coated plates, respectively. The plates were incubated for 1.5 h at room temperature and subsequently washed as described above. Rabbit anti-recombinant bovine TNF-α polyclonal serum or rabbit anti-recombinant ovine IL-1β polyclonal serum (Serotec, Inc., Raleigh, NC) was diluted 1:5,000 or 1:500, respectively, in TBS wash buffer containing 2% gelatin, and 100 µl was added to each well. The plates were incubated for 1 h at room temperature and washed. Secondary goat anti-rabbit immunoglobulin G (IgG) conjugated to HRP was diluted 1:5,000 (TNF- α) or 1:10,000

(IL-1β) in TBS wash buffer containing 2% gelatin, and 100 µl was added to each well of

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the respective plates. Following a 1-h incubation, the plates were washed, and 100 µl of

TMB substrate solution was added to each well. The reaction was stopped by the addition of 100 µl of 2 M H2 SO4, and the absorbance was read at 450 nm. The values for TNF- α and IL-1β were calculated from a standard curve run concurrent with the assay.

ELISA for sCD14

Milk sCD14 from whey samples (1:10 diluted) were measured by a sandwich

ELISA as described for BSA. Mouse anti-bovine CD14 monoclonal antibody (CAM36A clone; VMRD, Inc., Pullman, WA) at concentration 5 µg/mL was used as the capture antibody. Mouse anti-bovine CD14 antibody (MM61A clone; VMRD,Inc.) was conjugated to HRP using a commercially available kit (Pierce Chemical Co., Rockford,

IL) and used as the detection antibody (diluted 1:150). Recombinant bovine sCD14 was used to generate a standard curve for the assay.

ELISA for IL-10 and IL-12

Concentrations of IL-10 and IL-12 were determined as previously described with slight modifications (Hope et al., 2002; Kwong et al., 2002). Flat-bottom 96-well plates were coated overnight at 4°C with mouse anti-bovine IL-10 (CC-318) or IL-12 (CC-301) antibody diluted to 4 µg/mL in 0.05 M sodium carbonate pH 9.6. The plates were washed and subsequently blocked with 2% fish skin gelatin for 1 h at room temperature. The plates were washed, and 100 µl of diluted (1:5) or undiluted whey samples was added to the anti-IL-10 or anti-IL-12 coated plates, respectively. Following a 1 h incubation at room temperature, the plates were washed, and 100 µl of either biotin-conjugated mouse anti-bovine IL-10 (CC-320) or IL-12 (CC-326) antibody diluted to 1 or 8 µg/mL, respectively, was added to the respective plates. The plates were incubated for 1 h at

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room temperature and washed. HRP-conjugated streptavidin (Sigma Chemical Co.) was diluted 1:500 in TBS wash buffer containing 2 % gelatin, and 100 µl of this solution was added to each well. The plates were incubated for 1 h at room temperature and washed, and TMB substrate solution was added to each well. The reaction was stopped by the addition of 100 µl of 2 M H2SO4, and the absorbance was read at 450 nm and 565 nm.

Supernatants derived from COS-7 cells transfected with either IL-10 or IL-12 encoding plasmids and previously assayed for biological activity were used to generate standard curves.

ELISA for C5a

Measurement of complement factor 5a (C5a) in milk was performed by sandwich

ELISA using anti-bovine C5a monoclonal antibody for antigen capture and rabbit anti- bovine C5a antiserum for detection. Flat-bottom 96-well plates were coated overnight at

4°C with goat anti-mouse IgG (Jackson immunoresearch Laboratories, Inc., West Grove,

Pa) diluted to 5 µg/mL in 0.05 M sodium carbonate, pH 9.6. The plates were washed, and

100 µl of anti-C5a monoclonal antibody/well diluted 1:5,000 in 0.05 % Tween-20-TBS

containing 0.1% gelatin and 1mM EDTA was added to each well. Following a 1-h

incubation at 37°C, the plates were washed, and 100 µl of whey diluted 1:10 in 0.05%

Tween 20-TBS containing 0.1% gelatin and 1 mM EDTA was added to each well. The

plates were incubated for 1.5 h at room temperature and washed, and 100 µl of rabbit

anti-bovine C5a/C5 diluted 1:2,500 in 0.05% Tween 20-TBS containing 0.1% gelatin was

added to each well. The plates were incubated for 30 min at 37°C and washed, and 100 µl

of goat anti-rabbit IgG conjugated to HRP (1:5,000 dilution in 0.05% Tween 20-TBS containing 0.1% gelatin) was added to each well. Following a 30-min incubation at 37°C,

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the plates were washed, and 100 µl of TMB substrate solution was added to each well.

The reaction was stopped by the addition of 100 µl of 2 M H2SO4, and the absorbance

was read at 450-nm absorbance readings. Purified C5adesArg was used to generate a

standard curve for the assay.

ELISA for IL-8, LBP, IFN-γ, SAA (Serum Amyloid A)

Milk IL-8 levels were determined from undiluted whey samples assayed with a

commercially available human IL-8 ELISA kit that cross-reacts with bovine IL-8 (R&D

Systems, Inc., Minneapolis, MN). Milk and plasma LBP were diluted 1:400 and 1:1,500

respectively and the levels were determined with a commercially available LBP ELISA

kit that cross-reacts with bovine LBP (Cell Sciences, Inc., Norwood, MA). Milk IFN-γ

was measured from undiluted whey samples using a commercially available kit

(Biosource International, Inc., Camarillo, Calif.) according to the manufacturer’s

instructions. Recombinant bovine IFN-γ (Serotec, Inc., Raleigh, NC.) was used to

generate a standard curve for the assay. SAA was determined with a commercially

available kit (Tri-Delta Diagnostics, Inc., Morris Plains, NJ)

ELISA for TGF-α, TGF-β1 and TGF-β2

Milk TGF-α, TGF-β1 and TGF-β2 were measured using commercially available

kits (R&D Systems, Inc., Minneapolis, MN). Undiluted whey samples were activated

with an equal volume of an aqueous solution containing 2.5 N acetic acid and 10 M urea

for 10 min. The reaction was then neutralized by the addition of a half volume of an

aqueous solution containing 2.7 N sodium hydroxide and 1 M HEPES and the final

reactants diluted four-fold with the supplied diluent. Samples assayed for TGF-β2 were

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first diluted (1:13) in deionized water and subsequently activated according to the manufacturer’s instructions.

Statistical methods

Repeated measures ANOVA was performed using the PROC Mixed model (SAS

8.2: SAS Institute, Cary, NC) to compare the mean responses between the experimental groups and the control groups (time 0 for Pseudomonad). For statistical analysis of milk

SCC, data were transformed to log10 values. A P-value of < 0.05 was considered significant.

RESULTS

Enumeration of bacterial growth from infected quarters

Aseptic milk samples were collected from quarters infused with saline or bacteria at varying time points following infusion. Milk samples were serially diluted and 0.01 mL was plated and colonies were enumerated. Within 16 h and up to 40 h following challenge, viable P. aeruginosa were recovered from all ten challenged quarters and six of the ten quarters remained infected through the end of the study. Maximal number of P. aeruginosa (3.94 ± 0.43 log10 CFU/mL) was recovered from milk samples within 16 h of

infusion, after which they declined until 40 h and then remained relatively constant

through the end of the study (Fig. 1A). From E. coli infused quarters, maximal number of

bacteria (4.10 ± 0.34 log10 CFU/mL) were recovered at 40 h post-infusion (Fig. 1B).

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A 5 P. aeruginosa

4

CFU/mL) 3 10

2

1 Bacteria (log 0 0 8 4 8 2 6 7 1 16 2 40 4 7 9 14 2 hours days

Time Following Infusion

B 5 E. coli

4

CFU/mL) 3 10

2

1 Bacteria (logBacteria 0 0 8 6 2 8 1 24 32 40 48 7 96 6 120 1 Time Following Infusion (h)

Fig.1. Bacterial growth of P. aeruginosa and E. coli following experimental challenge. Sterile milk samples were collected from all infused quarters and plated. Mean ± SE of log10 CFU/mL of P.aeruginosa and E. coli is shown (A) and (B) respectively.

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Intramammary infection elicits acute phase systemic response

To determine whether P. aeruginosa intramammary infection could elicit a

systemic response, changes in body temperature, acute phase protein synthesis and differential white blood cell counts were assayed. Elevated body temperatures were first observed 12 h post-infection, reached a peak of 39.43 ± 0.26 °C at 24h and returned to baseline levels by 32 h (Fig. 2A). In response to E. coli infection, elevated rectal

temperatures were initially detected 8 h after challenge and reached a peak (40.59 ± 0.34

ºC) eight hours later after which they returned to baseline (time 0) levels (Fig. 2B).

The systemic response to P. aeruginosa infection was further characterized by the

induction of acute phase synthesis of SAA and LBP (Fig. 2C). Circulating levels of LBP

and SAA increased within 24 and 32 h of infection, respectively, and reached maximal

levels 48h. Within 7 and 14 days respectively, plasma concentration of SAA and LBP

returned to pre-challenge levels. Changes in circulating levels of SAA and LBP strongly

correlated with one another (r = 0.90). In addition to elevations in body temperature and

the induction of acute phase protein synthesis, intramammary infection with P.

aeruginosa elicited a transient decrease in circulating levels of neutrophils and

lymphocytes, the most predominant white blood cells, within 24 h (Fig. 2D).

138

A B P. aeruginosa E. coli 40.0 Rectal Temperature 41.0 * Rectal Temperature C) C) o ** o 40.5 39.5 40.0 * 39.0 39.5 * * 39.0 * 38.5 38.5 Rectal Temperature ( Rectal Temperature ( 38.0 38.0 0 8 6 7 1 24 32 40 48 72 96 14 21 0 8 16 24 32 40 48 72 96 20 68 1 1 hours days Time Following Infusion (h) Time Following Infusion D C P. aeruginosa P. aeruginosa

600 * SAA 120 6 Neutrophils Lymphocytes 500 LBP 100 5

# L) µ g/mL) g/mL) 400 # # * 80 4 µ µ

* # # cells/

3 # 300 60 3 # # 200 * 40 2 # * * 100 20 1 WBC's (10 WBC's Plasma LBP ( Plasma SAA ( Plasma SAA

0 0 0 0 8 6 7 4 1 24 32 40 48 72 96 1 21 0 8 16 24 32 40 48 72 96 7 14 21 hours days hours days

Time Following Infusion Time Following Infusion

Fig. 2. Effect of P. aeruginosa intramammary infection on systemic response. Changes in rectal temperature to P. aeruginosa and E. coli (A&B), induction of acute phase synthesis of SAA and LBP (C), circulating leukocyte populations (D). Mean ± SE rectal temperature is reported in °C (A). (*) significantly increased compared to time 0 (P<0.05). Plasma assayed for SAA and LBP by ELISA (C). Mean ± SE levels of plasma SAA and LBP are reported in µg/mL. (*,#) significantly increased SAA and LBP levels, respectively, compared to time 0 (P<0.05). Differential neutrophil and lymphocyte counts were determined in whole blood obtained in parallel as above (D). Mean ± SE cell counts are reported in thousands/µl. (*, #) significantly decreased circulating neutrophils or lymphocytes, respectively, compared to time 0 (P <0.05).

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Intramammary infection with P. aeruginosa and E. coli elicits a localized

inflammatory response as characterized by elevated milk SCC

Increases in milk SCC were evident within 12 and 16 h for P. aeruginosa and E.

coli infected quarters, respectively, following infusion and remained elevated throughout

the study (Fig. 3 A & B). Maximal elevations in milk SCC were observed for P.

aeruginosa and E. coli 32 h post-infusion and reached a level of 62.92 x 106 ± 6.39 x 106

and 46.79 x 106 ± 6.65 x 106 cells/mL, respectively. In contrast, the milk SCC remained

unchanged in the saline infused quarters throughout the study.

Increased vascular permeability during intramammary infection with P. aeruginosa and E. coli

Milk BSA levels were assayed to determine whether intramammary infection with

P. aeruginosa and E. coli causes increased vascular permeability. Milk from quarters infected with P. aeruginosa demonstrated an acute increase in levels of BSA within 20 h of infection that remain elevated for an additional two weeks (Fig. 4A). An increase in milk BSA from E. coli infected quarters was detected within 16 h post-infusion (Fig. 4B).

Peak levels of BSA were observed within 32 h of challenge and reached a concentration of 524.94 ± 30.27 µg/mL.

140

A 70 * * P. aeruginosa 60 Saline 50

40

cells/mL) 30 6 * 20 * (10 10 * * * Milk Somatic Cell Count Cell Somatic Milk * * 0 *** 0 8 6 0 8 2 6 7 1 24 32 4 4 7 9 14 21 hours days

Time Following Infusion

B

60 Saline * E. coli 50 * * 40 * 30 cells/mL)

6 * 20 (10 * 10 * * * Milk Somatic Cell Count Cell Somatic Milk 0

0 8 16 24 32 40 48 72 96 20 1 168 Time Following Infusion (h)

Fig. 3. Effect of bacterial infection on milk somatic cell counts (SCC). SCC were determined from milk samples obtained immediately prior to and for various time points from quarters infected either with saline or P. aeruginosa (A) or E. coli (B). Mean ± SE milk SCC are reported in millions/mL. (*) represents significantly increased in bacterial infected quarters relative to time 0 (P <0.05) by repeated measures ANOVA.

141

A P. aeruginosa 600 Milk BSA * * 500 * 400 * g/mL) * µ * 300 * *

200 *

Milk BSA ( BSA Milk 100

0 0 8 6 0 8 2 7 1 24 32 4 4 7 96 14 21 hours days

Time Following Infusion

B Milk BSA 1400 Saline * E. coli 1200 *** 1000

g/mL) * µ 800 600 * * 400 *

Milk BSA ( BSA Milk * 200

0 0 8 6 4 2 8 0 1 2 3 40 4 72 96 2 1 168 Time Following Infusion (h)

Fig. 4. Effect of intramammary bacterial infection on mammary vascular permeability. Milk BSA levels were measured by ELISA immediately prior to and for various time points following intramammary infusion of P.aeruginosa (A) and E. coli (B). Mean ± SE BSA levels are reported in µg/mL. (*) represents significantly increased compared to time 0 (P < 0.05) by repeated measures ANOVA.

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Changes in milk complement activation and pro-inflammatory cytokine levels in response to P. aeruginosa intramammmary infection

Increased milk levels of the chemoattractants C5a and IL-8 were observed within

20 h of infection (Fig. 5A). Elevated levels of C5a were sustained for an additional 52 h, whereas those of IL-8 returned to baseline levels within 12 h of the initial increase.

Maximal levels of IL-8 (90.47 ± 46.61 pg/mL) and C5a (17.64 ± 3.58 ng/mL) were observed in the milk quarters within 20 and 32 h, respectively. Increased levels of IFN-γ and IL-12 were detected in milk within 24 and 32 h post-infection (Fig. 5B). IL-12 levels reached the maximum within 32h post infection (73.91 ± 21.96 biological units/mL) and remain elevated until 40 h after challenge. In contrast, maximal levels of IFN-γ (284.01 ±

67.13 pg/mL) were not observed until 72 h post-infection.

Initial elevations in the milk concentrations of the pro-inflammatory cytokines IL-

1β and TNF-α were observed at 20 and 24 h post-infection, respectively (Fig. 5C). Milk

TNF-α levels reached a peak of 11.77 ± 3.72 ng/mL and returned to baseline levels within 72 h of challenge. Maximal levels of IL-1β (0.55 ± 0.09 ng/mL), which were significantly elevated relative to pre-challenge (time 0) levels, were observed 32 h post- infection and remain elevated for up to 1 week. Increases in TGF-α were found within 20 h of infection and sustained for ≥ 2 weeks (Fig. 5D). Changes in milk TGF- α levels correlated with those of IL-1β (r = 0.6204), but not TNF- α (r = 0.3393). Increases in

milk TGF- α in response to E. coli were found within 16 h of and sustained until 72 h of

infection (Fig. 5E).

143

P. aeruginosa A P. aeruginosa 25 150 B 100 # # C5a * IL-12 350 # IL-8 # IFN-γ 20 * 125 80 300 * 100 * 250 15 60 200 (pg/mL) * γ 75 # 10 40 # # # 150

50 IL-12 Milk # # # 100

Milk C5a (ng/mL) 5 20 Milk IL-8 (pg/mL) IL-8 Milk

25 IFN- Milk ** units/mL) (biological * 50 0 0 0 0

0 8 16 24 32 40 48 72 96 7 14 21 0 8 16 24 32 40 48 72 96 7 14 21 hours days hours days

Time Following Infusion Time Following Infusion

C P. aeruginosa D P. aeruginosa 16 * TNF-α 1.4 350 TGF-α IL-1β 1.2 300 * 12 * * 1.0 250 *

(ng/mL) * (pg/mL) 0.8 (ng/mL) 200 α

α *

β * 8 # * * # 0.6 150 # # # # 0.4 4 100 # Milk IL-1 Milk Milk TNF- Milk * 0.2 TGF- Milk 50 0 * * 0.0 0 0 8 4 2 0 2 6 7 4 1 16 2 3 4 48 7 9 1 2 0 8 16 24 32 40 48 72 96 7 14 21 hours days hours days

Time Following Infusion Time Following Infusion E E. coli

600 * Saline E. coli 500 * * 400 ** (pg/mL) α 300 *

200

100 Milk TGF- Milk

0 0 8 6 4 0 8 2 6 8 1 2 32 4 4 7 9 120 16 Time Following Infusion (h)

Fig. 5. Effect of intramammary infection on complement activation and pro-inflammatory cytokine levels in milk. Milk samples collected for various time points were analyzed by ELISA for the following: C5a and IL-8 (A); IL-12 and IFN-γ (B); TNF-α and IL-1β (C) and TGF-α (D) and for P. aeruginosa, and TGF-α for E. coli (E). (*) represents significantly increased levels of C5a, TNF-α, TGF-α, or IL-12 relative to time 0 levels (P<0.05). (#) represents significantly increased levels of IL-8, IL-1β, or IFN-γ relative to time 0 levels (P<0.05). Mean ± SE of C5a and TNF-α levels are reported in ng/mL. Mean ± SE of TGF-α and IFN-γ levels are reported in pg/mL. Mean ± SE of IL-12 levels are reported in biological units/mL.

144

Changes in pro-inflammmatory cytokine IL-8 and TNF-α levels in response to E. coli intramammary infection

Intramammary infection with E. coli induced an increase in concentrations of IL-8 and TNF-α in milk within 16 h of challenge, and elevated levels of milk IL-8 (Fig. 6A) and TNF-α (Fig. 6B) persisted through 24 and 40 h, respectively (Fig. 6). Maximal level

of IL-8 (395.9 ± 82.9 pg/mL) and TNF-α (16.86 ± 3.94 ng/mL) were observed 16 h after

bacterial infusion. There were no changes in the milk levels of either cytokine in saline

treated quarters.

Changes in anti-inflammatory cytokine levels during the intramammary infection

To determine whether the pro-inflammatory response elicited by intramammary

infection with P. aeruginosa was accompanied by a compensatory anti-inflammatory

response, milk levels of IL-10 were assayed by ELISA (Fig. 7). TGF-β1 and TGF-β2,

the two isoforms of TGF-β were assayed by ELISA in response to P. aeruginosa (Fig. 7)

and E. coli (Fig. 8). Milk IL-10 levels initially increased within 24 h of infection, peaked

8 h later, and returned to pre-challenge (time 0) levels within 48 h of the initial increase

(Fig. 7A). Increases in milk TGF- β1 were first detected 40 h post-challenge and

remained elevated for >2 days (Fig. 7B). In contrast, elevated levels of milk TGF- β2

were observed within 8 h of challenge and, with the exception of the 24 h time point,

were sustained throughout the study. Peak levels of TGF- β1 and TGF- β2 were observed

48 and 96 h after infection, respectively, reaching concentrations of 8.40 ± 1.27 ng/mL

and 75.68 ± 13.68 ng/mL. Relative to time 0, increased TGF- β1 (Fig. 8A) and TGF- β2

(Fig. 8B) levels were detected in milk from E. coli infected quarters within 32 h and the

levels of both cytokines remained elevated throughout the study.

145

A 500 * Saline E. coli 400

300

200 *

100 Milk IL-8 (pg/mL) IL-8 Milk

0 0 8 6 4 2 0 8 2 1 2 3 4 4 7 96 20 68 1 1 Time Following Infusion (h)

B 21 * Saline 18 E. coli

15

(ng/mL) 12 * α 9 * 6 *

Milk TNF- Milk 3

0 0 8 6 0 8 16 24 32 40 48 72 9 2 6 1 1 Time Following Infusion (h)

Fig. 6. Effect of intramammary infection with E. coli on TNF-α and IL-8 levels in milk.Concentrations of IL-8 (A) and TNF-α (B) in milk for various time points in response to E. coli were determined by ELISA. (*) represents significantly increased IL-8 and TNF-α levels in E. coli infected quarters compared to those in pre-infused (time 0) quarters (P< 0.05). Mean ± SE IL-8 and TNF-α levels are reported in pg/mL and ng/mL respectively.

146

Maximal concentrations of TGF-β1 (13.27 ± 1.94 ng/mL) and TGF-β2 (72.99 ± 16.09

ng/mL) were detected in milk 48 and 96 h post-infection, respectively. With the

exception of the 48 h time point, TGF- β1 levels in milk from saline infused quarters

remained unchanged from the time 0 concentrations (Fig. 8A). At 48 h, a slight but

significant transient increase in milk TGF-β1 was detected in saline control quarters,

however, this level was significantly less than that detected in E. coli-infused quarters at

the same time point. Similarly, transient increases in milk TGF- β2 concentrations were detected in quarters infused with saline at 32 and 40 h (Fig. 8B).

Induction of milk sCD14 and LBP during P. aeruginosa intramammary infection:

Changes in the accessory molecules sCD14 and LBP, which facilitate host recognition and neutralization of LPS, were assayed by ELISA (Fig. 9). Relative to pre- challenged (time 0) quarters, increased levels of sCD14 and LBP in milk were detected within 20 and 32h of infection, respectively. Maximal concentrations of sCD14 (16.10 ±

3.54 µg/ mL) and LBP (30.32 ± 2.40 µg/mL) in milk were measured 40h after challenge. sCD14 concentrations returned to pre-challenge levels by day 7, while the LBP levels remained elevated beyond day 21. Changes in LBP concentrations in milk strongly correlated (r = 0.9566) with those in plasma (Fig. 2C).

147

A

P. aeruginosa 800 IL-10 700 * 600 500 400 * 300 Milk IL-10 Milk 200 * (biological units/mL) (biological 100 * 0 0 8 0 7 4 1 16 24 32 4 48 72 96 1 2 hours days

Time Following Infusion

B P. aeruginosa

TGF-β1 TGF-β2 10 100 * * # # 8 # 80 # # 6 60 2 (ng/mL) 1 (ng/mL) # # # # β β # * 4 * 40

2 20 Milk TGF- Milk Milk TGF- Milk 0 0 0 8 4 0 6 7 4 1 16 2 32 4 48 72 9 1 2 hours days

Time Following Infusion

Fig. 7. Effect of P. aeruginosa infection on anti-inflammatory cytokine levels in milk. Concentrations of IL-10 (A), TGF-β1 (B) and TGF-β2 (B) in milk for various time points in response to P. aeruginosa were determined by ELISA. Mean ± SE IL-10 levels are reported in biological units/mL. Mean ± SE TGF-β1 and TGF-β2 levels are reported in ng/mL. (*) represents significantly increased IL-10 or TGF- β1 levels compared to those in pre-infused (time 0) quarters (P< 0.05). (#) represents significantly increased TGF- β2 levels compared to levels in pre-infused (time 0) quarters (P<0.05).

148

A

16 ** Saline 14 E. coli 12 * * 10 * * * 1 (ng/mL)

β 8 # 6 4

Milk TGF- Milk 2 0 0 8 16 24 32 40 48 72 96 120 168 Time Following Infusion (h)

B 90 * Saline * E. coli 75 * * * 60 * 2 (ng/mL)

β 45 *

30 # #

15 Milk TGF- Milk 0 0 8 16 24 32 40 48 72 96 120 168 Time Following Infusion (h)

Fig. 8. Effect of E. coli infection on anti-inflammatory cytokine levels in milk. Concentrations of TGF-β1 (A) and TGF-β2 (B) in milk for various time points in response to E. coli were determined by ELISA. Mean ± SE TGF-β1 and TGF-β2 levels are reported in ng/mL. (*) represents significantly increased TGF- β1 and TGF- β2 levels in E. coli infected quarters compared to those in pre- infused (time 0) quarters (P< 0.05). (#) represents significantly increased TGF- β1 and TGF- β2 levels in saline infected quarters compared to levels in pre-infused (time 0) quarters (P<0.05).

149

P. aeruginosa # 20 sCD14 35 * LBP 30 16 25 g/mL) g/mL) µ

12 µ # # 20 * # # 8 15 # # # # 10 4 # * * Milk LBP ( LBP Milk

Milk sCD14 ( sCD14 Milk * 5

0 0 0 8 6 7 1 24 32 40 48 72 96 14 21 hours days

Time Following Infusion

Fig. 9. Intramammary challenge with P. aeruginosa increases milk levels of sCD14 and LBP. Levels of sCD14 and LBP in milk obtained from P. aeruginosa infected quarters were quantified by ELISA. Mean ± SE sCD14 and LBP levels are reported in µg/mL. (*, #) represents significantly increased levels of sCD14 or LBP, respectively, compared to levels in pre-infused (time 0) quarters (P < 0.05).

150

DISCUSSION

The establishment of intramammary infection after contamination of the teat end is determined by the virulence factors of the pathogenic organisms and the nature of the host immune response to the pathogens (Burvenich et al., 2003). Once the pathogen has breached the physical barriers in the mammary gland, the innate immune response represents the major defense mechanism of the host against the invading pathogen

(Hoffmann et al., 1999). Although many aspects of innate immunity are evolutionarily conserved like recognition of PAMPs (pathogen associated molecular patterns) through

PRRs (Pattern-Recognition Receptors), the nature of the host response to different bacterial pathogens is often variable (Hoffmann et al., 1999; Uthaisangsook et al., 2002).

Studies on innate immune responses to intramammary infection with E. coli and

Staphylococcus aureus have shown that they are distinct in several aspects including: (1) the degree of febrile response; (2) the types of cytokines that are upregulated; and (3) the ability to activate milk complement (Riollet et al., 2000; Bannerman et al., 2004).

Cytokines are significant in clearing bacteria following infection. Most of our understanding of the innate immune response to intramammary Gram-negative infections has been limited to studies with E. coli. The present study was designed to examine the innate immune response against another major Gram-negative intramammary pathogen,

P. aeruginosa. In addition, the expression of cytokines belonging to TGF superfamily both in E. coli and P. aeruginosa that are known to moderate inflammatory responses and modulate the ensuing resolution of inflammation were investigated.

Recognition of a foreign pathogen through conserved PAMP motifs by the host through PRRs is a critical component of the host innate response (Medzhitov and

151

Janeway, 2000). sCD14 facilitates recognition of Gram-negative bacteria by binding to

LPS, an integral component of the outer wall of all Gram-negative bacteria, including

E. coli and P. aeruginosa. The importance of CD14 in the LPS-TLR signal transduction is well understood, as several studies have reported that the ability of the host to fight

Gram-negative bacterial infections is impaired when levels of sCD14 are diminished (Le

Roy et al., 2001; Wenneras et al., 2001; Yang et al., 2002). In the present study, we demonstrated that intramammary infection with P. aeruginosa results in an increase in levels of sCD14 in milk (Fig. 9). The temporal changes in sCD14 levels were similar to those of E. coli intramammary infection and maximal levels of sCD14 were observed in both studies 40 h after initial infection (Bannerman et al., 2004). Maximal levels of sCD14 were slightly higher following E. coli challenge (Bannerman et al., 2004); however, elevated levels of sCD14 were sustained for a longer duration following P. aeruginosa infection (Fig. 9). Earlier studies have reported that the increased level of sCD14 in milk during the mammary inflammatory response did not result from extravasation from the vascular compartment but rather from shedding of neutrophil mCD14 (membrane bound CD14) (Lee et al., 2003 a, b). Consistent with this hypothesis, increases in milk sCD14 correlated with increases in milk SCC (r = 0.7204), that are primarily composed of neutrophils during acute mastitis (Saad and Ostensson, 1990).

Also, mammary epithelial cells have been shown to upregulate sCD14, thus providing another potential source of milk sCD14 (Labeta et al., 2000; Vidal et al., 2001).

LBP is an acute phase protein that is primarily synthesized in the liver in response to bacterial infection. LBP is an accessory molecule that facilitates binding of LPS to sCD14 and this complex is in turn recognized by TLR-4, a membrane bound receptor

152

(Tobias et al., 1999; Schumann and Latz, 2000). Increased levels of plasma LBP were detected following P. aeruginosa challenge. The temporal changes in the expression pattern were similar to that of SAA, another liver derived acute phase protein (Fig. 2C).

Change in levels of LBP in milk (Fig. 9) strongly correlated with the levels in plasma and with increases in mammary vascular permeability as evidenced by increased milk BSA levels (Fig. 4). Therefore, the increased level of milk LBP is due to extravasation of circulating LBP resulting from increased vascular permeability. It is also possible for there to be a local source of LBP in the mammary gland, since IL-1β and TNF-α, which

are elevated in the mammary gland following P. aeruginosa infection, have been demonstrated to upregulate the production of LBP in the epithelial cells of lung and intestine (Vreugdenhil et al., 1999; Dentener et al., 2000).

Upon recognition of the pathogenic microorganisms, the host immune system response is mediated by activation of intracellular signal transduction that culminates in

the upregulation of chemokines and cytokines. The cytokines in turn contribute to

trafficking of neutrophils to the site of infection. The milk levels of two pro-inflammatory

cytokines TNF-α and IL-1β were elevated following P. aeruginosa infection (Fig. 5C).

Studies have shown that both the cytokines, along with cytokines like IL-6 and IFN-γ, are

known to activate neutrophils and inhibit apoptotic death, in addition to neutrophil

recruitment to the site of infection (Pober, 1987; Wang et al., 2003; Mcloughlin et al.,

2004; Cowburn et al., 2004). Also, both the cytokines have been reported to contribute to

the induction of several aspects of systemic acute response, including onset of fever,

changes in vascular permeability, and hepatic synthesis of acute phase proteins (Koj,

1996; Suffredini et al., 1999). Correspondingly, initial increases in TNF-α and IL-1β

153

within 24 h of P. aeruginosa infection either preceded or were temporally coincident with maximal increases in rectal temperature (Fig. 2A), circulating levels of the acute phase proteins, LBP and SAA (Fig. 2C), and mammary gland vascular permeability (Fig. 4).

Peak increases in TNF-α level following P. aeruginosa and E. coli challenge and IL-1β level following P. aeruginosa were comparable to those observed following E. coli infection (Bannerman et al., 2004).

Neutrophil recruitment to the site of infection is further mediated by the chemoattractants IL-8 and the complement cleavage product C5a (Collins et al., 1991).

Increases in milk TNF-α, IL-1β, IL-8 and C5a following P. aeruginosa infection (Fig. 5

A&B) preceded maximal increases in milk SCC (Fig. 3A), that are primarily composed

of neutrophils during the acute phase of intramammmary infection (Saad and Ostensson,

1990). The brief, transient increases in activated complement following P. aeruginosa

challenge are similar to those previously reported following E. coli infection (Lee et al.,

2003a, b; Bannerman et al., 2004).

The increases in milk levels of TNF-α, IL-1β, and IL-8 could be attributed either entirely or in part to local production by mammary epithelial cells and macrophages

(Politis et al., 1991; Riollet et al., 2001; Alluwaimi et al., 2003). However, increases in

C5a levels are more likely due to the influx of serum components into the mammary gland as the levels of complement in milk were found to be relatively low in healthy glands (Rainard and Poutrel, 1995). In the present study, initial detection and subsequent increases in milk concentrations of C5a (Fig. 5A) paralleled increases in milk levels of

BSA (Fig. 4A) and changes in concentrations of both C5a and BSA correlated with one another (r = 0.84). Increased milk BSA levels are due to increased mammary vascular

154

permeability, therefore, increased milk C5a is from activation of serum-derived influx of complement into the mammary gland.

TGF-α expressed in various cell types like epithelial cells and macrophages is known to regulate growth and development, in addition to resolution of wound healing and maintenance of homeostasis (Kumar et al., 1995). TGF-α has also been shown to promote inflammation by upregulating the production of prostaglandins and by synergistically enhancing the effects of IL-1β and TNF-α (Bry, 1993; Unemori et al.,

1994; Subauste and Proud, 2001). Increased milk levels of TGF-α were observed within

24 h of P. aeruginosa infection and 16 h of E. coli infection (Fig. 5D & E), however, in contrast to other proinflammatory cytokines including, IL-8, IL-1β and TNF-α, TGF-α levels remain elevated for a longer period of time and did not return to baseline levels until more than 2 weeks and 1 week after challenge with P. aeruginosa and E. coli respectively. The sustained level of TGF-α for a longer period might reflect its role in the wound-healing process. The present finding is consistent with the only other published report to study the effects of mastitis on TGF-α, wherein the levels were measured at the mRNA level from the mammary tissue and not at the protein level as reported here

(Sheffield, 1997).

IL-12 and IFN-γ contribute to both the innate and adaptive immune responses by activating neutrophils and promoting a Th1-type immune response (Trinchieri, 1997).

Neutrophils, when cultured in the presence of IFN-γ, are shown to express CD83, a dendritic cell marker, on their surface (Iking-Konert et al., 2002). Peak levels of both cytokines were observed 32 h after infusion of P. aeruginosa (Fig. 5B) and the temporal changes in these cytokines were similar to that reported against E. coli induced mastitis

155

(Bannerman et al., 2004). Initial increases in IFN-γ closely paralleled those of IL-12 and are consistent with studies demonstrating that each of these cytokines could upregulate production of the other (Collins et al., 1998; Munder et al., 1998; Ma 2001).

Prolonged or excessive inflammatory responses can have a deleterious effect on the epithelial cells of mammary gland resulting in loss of milk production (Paape et al.,

2003). Resolution of the inflammation is mediated by the down regulation of proinflammatory cytokine production by anti-inflammatory cytokine IL-10 and members of the TGF-β family (Ayoub and Yang, 1997; Conti et al., 2003). To counter the pro- inflammatory response elicited in response to intramammary infection with P. aeruginosa and E. coli, increases in levels of anti-inflammatory cytokines, IL-10, TGF-β1

and TGF-β2 were observed within 40 h of infection (Fig. 7 and Fig. 8). The temporal

change in IL-10 expression was similar to that previously observed during E. coli

intramammary infection (Bannerman et al., 2004). The present study establishes

increased TGF-β1 and TGF-β2 expression levels following P. aeruginosa (Fig. 7), and E.

coli (Fig. 8) infection. To date, the present report is the first to study the effects of mastitis on milk TGF-β1 and TGF-β2 levels. The TGF-β1 and TGF-β2 expression level in

response to E. coli is consistent with other reported expression levels of TGF in rats following systemic infection with E. coli (Ahmad et al., 1997). The pre-challenge (time

0) milk TGF-β1 and TGF-β2 of 2.03 ± 0.44 ng/mL and 28.65 ± 6.31 ng/mL (Fig. 8), respectively were comparable with other studies measured in milk samples from healthy quarters (Ginjala and Pakkanen, 1998). The increased levels of TGF- β1 are consistent

with reports of elevated TGF- β1 in other tissues infected by this bacterium (Kernacki et

al., 1998; Rumbaugh et al., 2001). Increased levels of TGF- β have further been reported

156

in response to Streptococcal infections (Ling et al., 2003) and during the course of septic shock induced by other bacterial pathogens (Marie et al., 1996).

To our knowledge, the present study is the first to characterize the cytokine response to intramammary infection with P. aeruginosa and represents a comprehensive investigation of the innate immune response to intramammary infection caused by any mastitis-causing pathogen. It is also the first study to investigate the effects of mastitis caused by P. aeruginosa and E. coli on milk TGF-β1 and TGF-β2. This comprehensive

study elucidates the existence of similarity between P. aeruginosa and E. coli with

respect to both systemic and local innate immune responses. This similarity is most likely

due to the conserved presence of recognition motifs: LPS found on both species of Gram-

negative bacteria. Cytokines are the natural regulators of the host defense mechanism

against invading pathogenic microorganisms. Further investigations will need to focus on

how the complex interplay of pro and anti-inflammatory responses contributes to the

success or failure of the mammary gland to eliminate the infection.

The economic impact of the disease to the dairy industry has led several basic

research efforts and development of several categories of therapeutic and prophylactic

agents to treat mastitis. The present study and several others (Sordillo et al., 1991;

Shuster et al., 1993; Riollet et al., 2000) have shown the important role of cytokines in host defense and pathophysiological process of the mammary gland in response to Gram- negative bacteria. Therefore, understanding the pro- and anti-inflammatory cytokine profiles generated against the two major Gram-negative mastitis pathogens will aid in further focus on the application of these cytokines for the treatment of bovine mastitis as immunomodulators after careful evaluation for any side effects.

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CHAPTER 7

SUMMARY AND FUTURE DIRECTIONS

SUMMARY

In the dairy industry, current breeding programs focus on selection for milk

production traits. Mastitis will continue to have a major economic impact due to its

negative correlation with production traits. Although the heritability for mastitis trait is

low there exists a clear genetic component to this inflammatory disease. The host’s

immune status plays pivotal role in the pathophysiology of the disease in response to

intramammary pathogens. Dairy cattle are continuously exposed to Gram-negative

bacteria due to the ubiquitous nature of these pathogens in the environment. Therefore, an

integrated genomic and immunological approach to study mastitis is essential and will

generate new insights into understanding the underlying molecular mechanisms of the

disease process. Current therapeutic and prophylactic measures have marginal efficacy in

preventing and treating mastitis and this necessitates the development of new therapeutic

agents for Gram-negative intramammary infections.

The analysis of gene expression, in a global context, using microarray technology

in a mouse mastitis model is a promising tool for data mining of transcriptional activities

that may help to untangle the biological pathways active in the pathogenesis of this

disease. This approach may also identify potential candidate genes for susceptibility to

bovine mastitis. In the present exploratory approach a mouse mastitis model (Chapter 2)

was developed that can identify genes involved in the host immune response to mammary

infection. Compared to the outbred bovine population, the use of a model developed in a

highly inbred population generates more robust data due to low experimental noise from

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genetic variation and environmental effects. However, cluster analysis of differentially co-expressed genes in the mammary gland of the two species in response to endotoxin

from Gram-negative bacteria and comparison of the two would help in identifying the

signal transduction pathway involved in an exaggerated inflammatory response to

endotoxin in bovine species.

An alternative method to quantitative-trait-loci (QTL) mapping in identification

of genes for complex disease would be development of the following: (1) dense single

nucleotide polymorphism (SNP) based markers; and (2) haplotypes derived from the SNP

polymorphisms that are highly informative for the disease trait. Such an informative

“hapmap” could be used in candidate-gene-association studies. There is increasing

awareness for the role of genes for innate immunity in the pathogenesis of mastitis.

Bactericidal/permeability increasing protein (BPI), a candidate innate immune gene, was

analyzed for SNP discovery. However, no significant association was found between the

SNP-marker allele and haplotypes derived from the SNP polymorphisms to the mastitis

related phenotype. The small sample size analyzed and the lack of case-control samples

could be impeding factors in our association study (Chapter 3).

Increased antibiotic resistance in food-producing animals and associated potential

risk to public health has prompted FDA to form regulations for the judicious use of

antibiotics in agriculture. BPI-derived-peptides are potential antimicrobial and anti-

inflammatory agents that could be used in the treatment of Gram-negative intramammary

infections. As shown in this study (Chapter 4 & 5), BPI possesses LPS-neutralizing

activity, and thereby, has potency as a drug for treatment of systemic sepsis. Therefore, it

is anticipated that LPS-induced pathological changes in the parenchymatous mammary

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tissue will be very minimal due to the anti-inflammatory effect of BPI, however, this remains to be evaluated in vivo.

Cytokines are the key immune mediators in numerous inflammatory diseases including mastitis. In this study (Chapter 6), the data confers that cytokine expression is conserved in the bovine mammary gland in response to the Gram-negative bacteria E. coli and P. aeruginosa. However, further comprehensive studies are needed to determine the complex interplay between the pro- and anti-inflammatory cytokines towards elimination of the pathogen. These studies may provide evidence for cytokines as therapeutic agents; if so they could act as potential alternatives to current antibiotic therapies. In contrast to IL-6 response against E. coli (Chapter II), P. aeruginosa failed to induce expression of IL-6 in bovine (unreported data). IL-6 is involved in many diseases and it induces B-cells to produce immunoglobulins. The lack of IL-6 induction in the bovine mammary gland could be an immune-evasive mechanism exhibited by P.

aeruginosa towards establishment of chronic infection. Another question is whether the

presence of IL-6 alters the severity of the disease. As noted in the experimental study, the

mammary gland failed to clear the organism over 21 days which could be due to a failure

in adaptive immunity. Therefore, IL-6 might be considered as a treatment for P.

aeruginosa mastitis with regard to rate of clearance of bacteria from the mammary gland.

FUTURE DIRECTIONS

Short-term goals

The mouse mastitis model based microarray data provide insights into the

molecular pathogenesis of mastitis and the genes that are differentially expressed in

response to E. coli. Potential candidate genes for mastitis were identified based on the

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microarray gene expression study. Clustering algorithms will be used to study the inherent expression patterns that are hidden and thereby identify possible biological pathways involved in the disease process. Further, SNPs were identified within neutrophil cytosol factor1 (NCF1) and the identified SNP polymorphism was genotyped in case-control samples for clinical mastitis (CM). Preliminary studies indicate a possible association between the marker allele and the CM phenotype. Further, the goal is to type a large sample size and test for association. A SNP identified within the BPI gene (+61 position) will be typed in 2300 samples belonging to four sire families for possible association with SCS trait. Further, in vitro assays will test the glycine to serine aa change for functionality of the mutation. BPI-derived synthetic peptide (bBPIpep-I) will

also be tested in vitro for any toxic effect using a mammary epithelial cell culture system.

Additionally, BPI-derived synthetic peptide will be tested in vivo against Gram-negative

bacteria like Klebsiella spp. and E. coli.

Long-term goals

Due to differences, bovine vs. murine in mammary gland response to LPS I

postulate that the inflammatory response may lead to the activation of similar, but not

necessarily identical transcriptional regulators of inflammation-associated gene expression. This will be explored by using superarrays for distinct signal transduction pathways which may produce insights into the exaggerated inflammatory response of

bovine mammary gland to LPS. With industrial collaboration, BPI-derived peptide will

be evaluated for its pharmaco-kinetics and pharmaceutical formulation for intramammary

therapy. Also, a slow-release biopolymer of BPI peptide will be formulated and evaluated

for its efficacy for dry-cow therapy as an alternative to antibiotics.

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APPENDIX

List of differentially expressed genes between uninfected and infected (E. coli) mammary tissue classified based on their on molecular function in the biological process of the disease. See chapter 2 for details of analysis. P P Fold Fold Affy Probeset ID Gene Symbol Gene Description treatment treat*time 24h 48h Acute-phase response(6) 1450297_at Il6 Interleukin 6 0.024003 0.036553 1.9 0.9 1420438_at Orm2 Orosomucoid 2 0.026788 0.085527 1.3 1.1 Regenerating islet-derived 3 1449495_at Reg3a 0.013617 0.062088 0.9 1.0 alpha 1450788_at Saa1 Serum amyloid A 1 0.001836 0.010380 1.6 1.2 1419075_s_at Saa2 Serum amyloid A 2 0.007718 0.031219 2.1 1.3 Serine (or cysteine) 1420553_x_at Serpina1a proteinase inhibitor, clade A, 0.012783 0.008787 1.0 1.0 member 1a Angiogenesis(10) 1450008_a_at Catnb catenin beta 0.029806 0.167067 1.1 1.1 corticotropin releasing 1450462_at Crhr2 0.023775 0.056579 0.9 1.0 hormone receptor 2 connective tissue growth 1416953_at Ctgf 0.001810 0.004427 1.7 1.1 factor 1423136_at Fgf1 fibroblast growth factor 1 0.029586 0.048242 0.9 0.9 1438953_at Figf c-fos induced growth factor 0.102041 0.015950 0.9 1.2 heart and neural crest 1422221_at Hand2 derivatives expressed 0.517266 0.016217 1.0 0.9 transcript 2 MAD homolog 5 1421047_at Madh5 0.032424 0.038553 0.9 1.0 (Drosophila) mitogen activated protein 1451927_a_at Mapk14 0.001970 0.001970 1.1 1.3 kinase 14 phosphatidic acid 1.1 1.1 1448908_at Ppap2b phosphatase type 2B 0.016429 0.275237 1421811_at Thbs1 thrombospondin 1 0.016508 0.116533 1.6 1.3 Apoptosis and anti-apoptosis(32) RIKEN cDNA 2010107K23 1422498_at 2010107K23Rik 0.079986 0.025589 1.0 1.0 gene ataxia telangiectasia mutated 1421205_at Atm 0.024916 0.008726 0.9 1.1 homolog (human) beta-amyloid binding protein 1426254_at Bbp 0.022221 0.003950 0.9 1.2 precursor 1420888_at Bcl2l Bcl2-like 0.172063 0.028947 1.0 1.0 BCL2-like 13 (apoptosis 1424406_at Bcl2l13 0.026806 0.118438 0.9 1.0 facilitator) baculoviral IAP repeat- 1425223_at Birc2 0.030677 0.025760 0.9 1.1 containing 2 baculoviral IAP repeat- 1437533_at Birc4 0.011033 0.982665 1.2 1.2 containing 4 BCL2/adenovirus E1B 1416923_a_at Bnip3l 19kDa-interacting protein 3- 0.417321 0.033893 1.0 1.2 like 1418981_at Casp12 caspase 12 0.009171 0.034761 1.1 1.0 1424552_at Casp8 caspase 8 0.026036 0.065375 1.1 1.0 death associated protein 1427358_a_at Dapk1 0.007840 0.004753 0.9 1.1 kinase 1 death effector domain- 1434995_s_at Dedd 0.799420 0.002645 1.0 1.2 containing 1424592_a_at Dnase1 deoxyribonuclease I 0.022307 0.035101 0.9 1.0

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1418242_at Faf1 Fas-associated factor 1 0.084423 0.013263 1.0 1.1 1434832_at Foxo3 forkhead box O3 0.974317 0.031271 1.0 1.2 1460671_at Gpx1 glutathione peroxidase 1 0.076771 0.031586 0.9 1.1 glycogen synthase kinase 3 Gsk3b beta 0.139723 0.020217 0.9 1.2 1421483_at Lhx4 LIM homeobox protein 4 0.031835 0.069812 0.9 0.8 microphthalmia-associated 1422025_at Mitf 0.168041 0.004611 1.0 0.9 transcription factor nucleolar protein 3 (apoptosis 1451503_at Nol3 repressor with CARD 0.016986 0.050559 0.8 1.0 domain) pleiomorphic adenoma gene- 1417519_at Plagl2 0.026526 0.013241 1.2 0.9 like 2 polymerase (DNA directed), 1425371_at Polb beta 0.004997 0.004672 0.9 1.1 phosphatase and tensin 1422553_at Pten 0.944585 0.034101 1.0 1.4 homolog 1455938_x_at Rad21 RAD21 homolog (S. pombe) 0.014211 0.008797 0.9 1.1 receptor (TNFRSF)- 1450173_at Ripk2 interacting serine-threonine 0.004239 0.002788 1.1 1.0 kinase 2 serum/glucocorticoid 1416041_at Sgk 0.010725 0.181970 1.2 1.2 regulated kinase serine/threonine kinase 17b 1450997_at Stk17b 0.101693 0.003629 1.0 1.1 (apoptosis-inducing) 1424641_a_at Thoc1 THO complex 1 0.479803 0.008237 1.0 1.3 tumor necrosis factor receptor 1422740_at Tnfrsf21 0.008459 0.021600 1.1 1.0 superfamily, member 21 tumor necrosis factor (ligand) 1420412_at Tnfsf10 0.086384 0.026974 1.1 0.9 superfamily, member 10 TNFRSF1A-associated via 1452622_a_at Tradd 0.120990 0.032328 0.9 1.2 death domain transformation related protein 1416926_at Trp53inp1 0.182414 0.033879 0.9 1.3 53 inducible nuclear protein 1 Apoptosis pathway(5) ADP-ribosyltransferase (NAD+; poly (ADP-ribose) 1422502_at Adprt1 polymerase) 1 0.038495 0.011376 0.9 1.1 1420888_at Bcl2l Bcl2-like 0.172063 0.028947 1.0 1.0 1424552_at Casp8 caspase 8 0.026036 0.065375 1.1 1.0 mitogen activated protein 1448342_at Mapk10 kinase 10 0.021170 0.621306 0.9 0.9 tumor necrosis factor (ligand) 1420412_at Tnfsf10 superfamily, member 10 0.086384 0.026974 1.1 0.9 Antigen presentation, exogenous antigen(2) Histocompatibility 2, class II, 1422527_at H2-DMa locus DMa 0.081721 0.025803 0.9 1.1 Tnf receptor-associated factor 1421376_at Traf6 6 0.009769 0.008403 1.1 1.0 Autophagy(1) Golgi associated PDZ and 1421191_s_at Gopc coiled-coil motif containing 0.008672 0.006598 1.1 0.9 B-cell differentiation and activation(4) 1422003_at Blr1 Burkitt lymphoma receptor 1 0.012633 0.109817 1.0 1.0 1450262_at Bsf3 B-cell stimulating factor 3 0.023794 0.110925 1.0 1.0 Phosphatidylinositol 3-kinase, regulatory subunit, 1451737_at Pik3r1 polypeptide 1 0.010515 0.002568 1.1 1.2 Recombination activating 1450680_at Rag1 gene 1 0.085458 0.016844 1.1 0.9

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Bone morphogenetic protein signaling pathway(4) 1450759_at Bmp6 bone morphogenetic protein 6 0.011121 0.073183 0.8 0.9 MAD homolog 5 1421047_at Madh5 (Drosophila) 0.032424 0.038553 0.9 1.0 1421245_at Sost sclerostin 0.855159 0.018631 1.0 0.8 1423176_at Tob1 transducer of ErbB-2.1 0.140039 0.018048 0.9 1.2 Cation transport and calcium ion homeostasis(15) ATPase, Na+/K+ transporting, alpha 2 1427465_at Atp1a2 polypeptide 0.004173 0.045776 0.9 0.9 ATPase, Ca++ transporting, 1427250_at Atp2a2 cardiac muscle, slow twitch 2 0.005716 0.079482 1.2 1.1 calcium channel, voltage- dependent, P/Q type, alpha 1450510_a_at Cacna1a 1A subunit 0.005024 0.002749 1.1 0.9 calcium channel, voltage- dependent, L type, alpha 1D 1428051_a_at Cacna1d subunit 0.003359 0.003497 1.0 0.9 potassium voltage gated channel, Shaw-related 1423559_at Kcnc1 subfamily, member 1 0.523855 0.017342 1.0 0.8 potassium voltage-gated channel, Shal-related family, 1450773_at Kcnd2 member 2 0.027486 0.184978 0.9 1.0 potassium voltage-gated channel, subfamily H (eag- 1449544_a_at Kcnh2 related), member 2 0.335358 0.006533 1.0 0.7 potassium channel, subfamily 1421852_at Kcnk5 K, member 5 0.050287 0.028702 0.9 1.1 1456575_at Ndn necdin 0.128676 0.001074 1.0 0.7 Polycystic kidney dis and REJ (sperm recept egg jelly, 1422244_at PkDarej s. urchin homol)-like 0.041258 0.006225 1.1 0.8 sodium channel, voltage- gated, type XI, alpha 1420784_at Scn11a polypeptide 0.015129 0.834045 0.9 0.9 1417560_at Sfxn1 sideroflexin 1 0.052310 0.025582 0.9 1.1 transient receptor potential cation channel, subfamily C, 1417577_at Trpc3 member 3 0.290331 0.002886 1.0 0.9 transient receptor potential cation channel, subfamily M, 1421617_at Trpm8 member 8 0.000859 0.001541 0.9 1.0 transient receptor potential cation channel, subfamily V, 1419615_at Trpv6 member 6 0.008474 0.024502 0.9 0.8 Carrier activity(11) RIKEN cDNA 1110014C03 1454688_x_at 1110014C03Rik gene 0.307588 0.024409 1.0 1.3 RIKEN cDNA 1110032D12 1436452_x_at 1110032D12Rik gene 0.218849 0.032419 0.9 1.2 RIKEN cDNA 3930401E15 1419917_s_at 3930401E15Rik gene 0.055425 0.019402 0.9 1.2 1427440_a_at Alb1 albumin 1 0.202368 0.021707 1.1 0.8 1426547_at Gc group specific component 0.001034 0.001471 0.9 1.0 1423738_at Oxa1l oxidase assembly 1-like 0.012698 0.034953 0.9 1.0 solute carrier family 16 (monocarboxylic acid 1418445_at Slc16a2 transporters), member 2 0.030264 0.040973 1.2 1.0 1425415_a_at Slc1a1 solute carrier family 1, 0.023156 0.033203 1.2 1.0

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member 1 solute carrier family 20, 1438824_at Slc20a1 member 1 0.029730 0.007973 1.0 1.2 solute carrier family 22 (organic cation transporter)- 1422897_at Slc22al2 like 2 0.846029 0.023624 1.0 0.9 solute carrier family 34 (sodium phosphate), member 1453962_at Slc34a1 1 0.023373 0.082566 0.9 1.0 Cell events: adhesion, cell-matrix adhesion, cell-cell signaling, communication, cycle, differentiation, growth and maintenance, migration, proliferation(133) RIKEN cDNA 9430022F06 1427601_at 9430022F06Rik gene 0.019366 0.033348 1.1 1.0 ARP3 actin-related protein 3 1434968_a_at Actr3 homolog (yeast) 0.086614 0.028416 1.0 1.2 1450695_at Ahr aryl-hydrocarbon receptor 0.011523 0.034319 0.9 1.0 1422184_a_at Ak1 adenylate kinase 1 0.015983 0.005277 0.9 0.8 armadillo repeat gene deleted in velo-cardio-facial 1450856_at Arvcf syndrome 0.407811 0.008346 1.0 0.8 ataxia telangiectasia mutated 1421205_at Atm homolog (human) 0.024916 0.008726 0.9 1.1 Bardet-Biedl syndrome 2 1424478_at Bbs2 homolog (human) 0.010672 0.009146 0.9 1.1 1433964_s_at BC032204 cDNA sequence BC032204 0.012236 0.042421 1.2 1.1 bone morphogenetic protein 1450210_at Bmp15 15 0.005381 0.661588 0.9 0.9 1450759_at Bmp6 bone morphogenetic protein 6 0.011121 0.073183 0.8 0.9 1450262_at Bsf3 B-cell stimulating factor 3 0.023794 0.110925 1.0 1.0 B-cell translocation gene 1, 1426083_a_at Btg1 anti-proliferative 0.001214 0.042270 0.4 1.3 1455571_x_at Calm1 calmodulin 1 0.199082 0.015133 1.0 1.3 1422414_a_at Calm3 calmodulin 3 0.001914 0.074259 1.1 1.2 1437275_at Catna1 catenin alpha 1 0.721282 0.031169 1.0 0.9 1450008_a_at Catnb catenin beta 0.029806 0.167067 1.1 1.1 1417861_at Ccnc cyclin C 0.011213 0.007187 0.9 1.1 1416492_at Ccne1 cyclin E1 0.026329 0.714129 1.0 1.0 1460609_at Ccne2 cyclin E2 0.031157 0.063629 0.9 0.9 1448334_a_at Ccni cyclin I 0.252075 0.016142 1.0 1.3 1427089_at Ccnt2 Cyclin T2 0.038672 0.016666 1.1 1.3 chemokine (C-C motif) 1419609_at Ccr1 receptor 1 0.014560 0.052440 1.6 1.1 1418770_at Cd2 CD2 antigen 0.006564 0.002068 1.1 0.9 1423760_at Cd44 CD44 antigen 0.030655 0.576548 1.5 1.4 cell division cycle 2 homolog 1448314_at Cdc2a A (S. pombe) 0.142416 0.031199 1.0 0.9 1418602_at Cdh15 cadherin 15 0.014533 0.130227 0.9 1.0 1421741_at Cdk8 cyclin-dependent kinase 8 0.031569 0.023811 0.9 1.1 CEA-related cell adhesion 1427630_x_at Ceacam1 molecule 1 0.134222 0.020374 1.0 1.1 carbohydrate (chondroitin 1453393_a_at Chst4 6/keratan) sulfotransferase 4 0.017307 0.102860 0.9 0.9 CDC28 protein kinase 1417457_at Cks2 regulatory subunit 2 0.266295 0.007943 1.0 1.1 C-type (Ca depend, carbohyd recog domain) lectin, 1419627_s_at Clecsf10 superfam memb 10 0.031358 0.042620 1.5 0.9 1421108_at Cml2 camello-like 2 0.024547 0.597755 0.9 0.9 procollagen, type XVI, alpha 1427986_a_at Col16a1 1 0.145601 0.032510 1.0 0.9

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1423669_at Col1a1 procollagen, type I, alpha 1 0.033101 0.101588 1.1 1.2 1427883_a_at Col3a1 procollagen, type III, alpha 1 0.021391 0.093160 1.3 1.1 1426348_at Col4a1 procollagen, type IV, alpha 1 0.054546 0.013212 1.1 0.9 cartilage oligomeric matrix 1419527_at Comp protein 0.014634 0.002917 1.1 0.8 chondroitin sulfate 1427256_at Cspg2 proteoglycan 2 0.002834 0.006402 1.9 1.0 connective tissue growth 1416953_at Ctgf factor 0.001810 0.004427 1.7 1.1 1422795_at Cul3 cullin 3 0.798299 0.032709 1.0 0.9 1426060_at Cul4a cullin 4A 0.027264 0.011809 0.9 1.2 1417453_at Cul4b cullin 4B 0.993692 0.032199 1.0 1.2 chemokine (C-X-C motif) 1419209_at Cxcl1 ligand 1 0.024938 0.053037 3.7 1.1 DNA segment, Chr 7, 1451160_s_at D7Ertd458e ERATO Doi 458, expressed 0.122596 0.029877 1.0 0.9 1422166_at Dcl1 C-type lectin 1 0.025818 0.597403 0.9 0.9 1419204_at Dll1 Delta-like 1 (Drosophila) 0.039397 0.019689 1.1 0.9 1449236_at Dll3 delta-like 3 (Drosophila) 0.007054 0.000827 1.0 0.8 1421827_at Dll4 delta-like 4 (Drosophila) 0.001767 0.231282 0.9 0.9 1449740_s_at Dsg2 desmoglein 2 0.245134 0.000558 1.0 1.2 1450119_at Dst dystonin 0.024555 0.079732 0.9 1.0 1427462_at E2f3 E2F transcription factor 3 0.036173 0.008973 1.1 0.9 1451925_at Eda ectodysplasin-A 0.004713 0.045651 0.9 0.9 ELAV (embryo lethal, abnorm vision, Drosoph)-like 1435871_at Elavl3 3 (Hu antigen C) 0.031071 0.007837 1.0 0.8 ELK1, member of ETS 1421896_at Elk1 oncogene family 0.007876 0.026651 0.9 1.0 E26 avian leukemia oncogene 1452163_at Ets1 1, 5' domain 0.033304 0.136406 1.4 1.1 E26 avian leukemia oncogene 1416268_at Ets2 2, 3' domain 0.018971 0.508112 1.2 1.1 1421339_at Extl3 exostoses (multiple)-like 3 0.782662 0.032622 0.0 1.0 1416164_at Fbln5 fibulin 5 0.000579 0.000771 1.2 1.0 1423136_at Fgf1 fibroblast growth factor 1 0.029586 0.048242 0.9 0.9 1438953_at Figf c-fos induced growth factor 0.102041 0.015950 0.9 1.2 1423100_at Fos FBJ osteosarcoma oncogene 0.002222 0.003066 1.7 0.9 1434832_at Foxo3 forkhead box O3 0.974317 0.031271 0.0 1.0 1448494_at Gas1 growth arrest specific 1 0.002439 0.004523 0.9 1.0 growth differentiation factor 1416900_s_at Gdf1 1 0.007946 0.013712 0.2 1.1 gap junction membrane 1416715_at Gjb3 channel protein beta 3 0.011150 0.025146 0.9 0.8 gap junction membrane 1448397_at Gjb6 channel protein beta 6 0.027546 0.755229 0.9 0.9 guanine nucleotide binding 1448031_at Gnao protein, alpha o 0.016473 0.125914 0.9 0.9 glycoprotein 1448303_at Gpnmb (transmembrane) nmb 0.008258 0.050730 1.3 1.1 gastrin releasing peptide 1421470_at Grpr receptor 0.027103 0.066657 0.9 1.0 glycogen synthase kinase 3 1451020_at Gsk3b beta 0.139723 0.020217 0.9 1.2 histocompatibility 2, complement component 1417314_at H2-Bf factor B 0.032363 0.184445 1.8 1.3 1433843_at Hs1bp3 HS1 binding protein 3 0.068865 0.004363 1.0 0.9 intercellular adhesion 1424067_at Icam1 molecule 0.002194 0.005712 1.5 1.1

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intercellular adhesion 1448862_at Icam2 molecule 2 0.036136 0.022460 1.1 0.9 1449399_a_at Il1b interleukin 1 beta 0.032167 0.077854 1.7 1.1 1421997_s_at Itga3 integrin alpha 3 0.010405 0.010786 1.1 1.0 1422445_at Itga6 integrin alpha 6 0.016780 0.046438 1.1 1.0 1426873_s_at Jup junction plakoglobin 0.062778 0.026359 0.9 1.1 killer cell lectin-like receptor, 1420789_at Klra5 subfamily A, member 5 0.002233 0.034998 0.9 0.9 killer cell lectin-like receptor, 1426171_x_at Klra7 subfamily A, member 7 0.009971 0.169209 0.9 0.8 killer cell lectin-like receptor, 1426136_x_at Klra8 subfamily A, member 8 0.454839 0.016542 1.0 0.8 1423885_at Lamc1 laminin, gamma 1 0.043456 0.027875 1.1 0.9 1423075_at Lman2 lectin, mannose-binding 2 0.066971 0.031999 1.1 0.9 Avian musculoaponeurotic fibrosarc (v-maf) AS42 1447945_at Maf oncogene homolog 0.006369 0.025319 0.9 1.0 v-maf musculoaponeurotic fibrosarc oncogene fam, prot 1418616_at Mafk K (avian) 0.103455 0.023217 0.0 1.0 mitogen activated protein 1425393_a_at Map2k7 kinase kinase 7 0.024330 0.557126 0.9 0.9 mitogen activated protein 1419208_at Map3k8 kinase kinase kinase 8 0.013991 0.035152 1.6 1.1 mitogen-activated protein 1419169_at Mapk6 kinase 6 0.024646 0.096238 1.1 1.0 mitogen activated protein 1420931_at Mapk8 kinase 8 0.005626 0.268061 0.9 0.9 1420713_a_at Mdfi MyoD family inhibitor 0.015444 0.022573 0.9 1.0 1417331_a_at Mina myc induced nuclear antigen 0.034199 0.124843 1.3 1.1 microphthalmia-associated 1422025_at Mitf transcription factor 0.168041 0.004611 1.0 0.9 Myeloid/lymphoid lineage- leukem transloc to 6 homolog 1425360_at Mllt6 (Drosophila) 0.002025 0.024373 0.9 0.9 1432177_a_at Mnat1 menage a trois 1 0.089550 0.021772 0.9 1.2 1450775_at Mos Moloney sarcoma oncogene 0.648076 0.025322 1.0 0.8 1416988_at Msh2 mutS homolog 2 (E. coli) 0.003842 0.006071 1.1 1.0 1422734_a_at Myb myeloblastosis oncogene 0.005910 0.111287 1.0 0.9 N-myc downstream regulated 1417664_a_at Ndr3 3 0.004460 0.003213 1.2 0.9 NIMA (never in mitosis gene 1424094_at Nek9 a)-related expressed kinase 9 0.026088 0.065800 1.1 1.0 1450836_at Neurog1 Neurogenin 1 0.026416 0.152350 0.9 0.9 Nuclear factor kappa light chain gene enhanc in B-cells 1420088_at Nfkbia inhibitor, alpha 0.003563 0.017297 1.3 1.1 1451338_at Nisch Nischarin 0.036809 0.004510 0.9 1.2 neuroblastoma myc-related 1425923_at Nmyc1 oncogene 1 0.008077 0.136353 0.9 0.9 nephrosis 1 homolog, nephrin 1422142_at Nphs1 (human) 0.057846 0.005102 1.0 0.8 par-6 (partitioning defective 1423174_a_at Pard6b 6) homolog beta (C. elegans) 0.000660 0.007321 1.2 1.1 par-6 partitioning defective 6 1420851_at Pard6g homolog gamma (C. elegans) 0.003331 0.026196 0.9 0.9 1425563_s_at Pcdh10 protocadherin 10 0.022971 0.974192 0.8 0.8 1450270_at Pcdhb11 protocadherin beta 11 0.017413 0.302915 0.9 0.9 1450263_at Pcdhb5 protocadherin beta 5 0.006075 0.123734 1.0 1.0 1435458_at Pim1 proviral integration site 1 0.032479 0.045328 0.2 1.2

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Prot-kinase, interf-induc ds RNA depend inhibr, represr 1426482_at Prkrir of (P58 represr) 0.019652 0.016947 1.0 1.0 Phosphatase and tensin 1422553_at Pten homolog 0.944585 0.034101 1.0 1.4 1455938_x_at Rad21 RAD21 homolog (S. pombe) 0.014211 0.008797 0.9 1.1 1426476_at Rasa1 RAS p21 protein activator 1 0.070484 0.001046 0.0 1.0 1437767_s_at Rbl2 retinoblastoma-like 2 0.001676 0.001420 0.9 1.1 regenerating islet-derived 3 1449495_at Reg3a alpha 0.013617 0.062088 0.9 1.0 Src family associated 1418895_at Scap2 phosphoprotein 2 0.008466 0.008868 1.1 1.0 1420558_at Selp selectin, platelet 0.005809 0.049080 1.4 1.2 1449105_at Sh2d2a SH2 domain protein 2A 0.000139 0.001151 0.9 0.9 1452214_at Skil SKI-like 0.009980 0.084921 1.2 1.1 S-phase kinase-associated 1425072_at Skp2 protein 2 (p45) 0.003342 0.010645 0.9 1.0 SMC (structural mainten of chroms 1)-like 2 (S. 1449253_at Smc1l2 cerevisiae) 0.024047 0.333186 0.9 0.9 Suppressor of cytokine 1449109_at Socs2 signaling 2 0.012145 0.066861 1.5 1.2 stromal interaction molecule 1436945_x_at Stim1 1 0.300714 0.006292 1.0 0.9 1419632_at Tecta tectorin alpha 0.130083 0.026672 1.0 0.9 transforming growth factor, 1415871_at Tgfbi beta induced 0.012945 0.081362 1.7 1.3 1421811_at Thbs1 thrombospondin 1 0.016508 0.116533 1.6 1.3 1449388_at Thbs4 thrombospondin 4 0.002207 0.005365 0.9 1.0 Tnf receptor-associated factor 1421376_at Traf6 6 0.009769 0.008403 1.1 1.0 1455252_at Tsc1 Tuberous sclerosis 1 0.030858 0.017043 0.9 1.1 Ubiquitin specific protease 4 1450892_a_at Usp4 (proto-oncogene) 0.014373 0.006179 1.1 1.2 1455098_a_at Vtn Vitronectin 0.006301 0.023605 0.9 0.9 Wingless-related MMTV 1450782_at Wnt4 integration site 4 0.055039 0.002473 1.0 0.8 Cell surface receptor linked signal transduction(10) 1450262_at Bsf3 B-cell stimulating factor 3 0.023794 0.110925 1.0 1.0 frizzled homolog 2 1418533_s_at Fzd2 (Drosophila) 0.002490 0.007660 0.8 1.0 frizzled homolog 3 1450135_at Fzd3 (Drosophila) 0.816189 0.028819 1.0 0.8 frizzled homolog 7 1450044_at Fzd7 (Drosophila) 0.027855 0.136167 1.3 1.1 1433843_at Hs1bp3 HS1 binding protein 3 0.068865 0.004363 1.0 0.9 1419532_at Il1r2 interleukin 1 receptor, type II 0.005018 0.007521 0.9 0.9 interleukin 3 receptor, alpha 1419712_at Il3ra chain 0.338864 0.010652 1.0 1.1 1423996_a_at Il4ra interleukin 4 receptor, alpha 0.046967 0.028122 1.1 0.9 1421620_at Il5ra interleukin 5 receptor, alpha 0.014250 0.723005 0.9 0.9 1452416_at Il6ra interleukin 6 receptor, alpha 0.017705 0.007794 0.8 1.2 Chemokine activity(9) 1422003_at Blr1 Burkitt lymphoma receptor 1 0.012633 0.109817 1.0 1.0 small chemokine (C-C motif) 1417789_at Ccl11 ligand 11 0.011516 0.039891 1.5 1.1 chemokine (C-C motif) 1449277_at Ccl19 ligand 19 0.042912 0.013891 1.1 0.9 chemokine (C-C motif) 1422029_at Ccl20 ligand 20 0.505971 0.011675 1.0 0.8

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chemokine (C-C motif) 1418777_at Ccl25 ligand 25 0.029669 0.504419 0.9 0.9 chemokine (C-C motif) 1419609_at Ccr1 receptor 1 0.014560 0.052440 1.6 1.1 chemokine (C-X-C motif) 1419209_at Cxcl1 ligand 1 0.024938 0.053037 3.7 1.1 chemokine (C-X-C motif) 1449984_at Cxcl2 ligand 2 0.003093 0.005381 6.2 0.9 chemokine (C-X-C motif) 1418652_at Cxcl9 ligand 9 0.027463 0.079618 1.4 1.1 Chemotaxis(9) 1425907_s_at Amot angiomotin 0.001339 0.056975 0.9 0.9 small chemokine (C-C motif) 1417789_at Ccl11 ligand 11 0.011516 0.039891 1.5 1.1 chemokine (C-C motif) 1449277_at Ccl19 ligand 19 0.042912 0.013891 1.1 0.9 chemokine (C-C motif) 1422029_at Ccl20 ligand 20 0.505971 0.011675 1.0 0.8 chemokine (C-C motif) 1418777_at Ccl25 ligand 25 0.029669 0.504419 0.9 0.9 chemokine (C-C motif) 1419609_at Ccr1 receptor 1 0.014560 0.052440 1.6 1.1 chemokine (C-X-C motif) 1449984_at Cxcl2 ligand 2 0.003093 0.005381 6.2 0.9 1421661_at Fprl1 formyl peptide receptor-like 1 0.028388 0.421130 0.9 0.9 1449399_a_at Il1b interleukin 1 beta 0.032167 0.077854 1.7 1.1 Chloride transport(5) 1427591_at Clcn1 chloride channel 1 0.010642 0.046952 0.9 0.8 1422314_at Clcn6 chloride channel 6 0.011792 0.251930 0.9 0.9 chloride intracellular channel 1438606_a_at Clic4 4 (mitochondrial) 0.015474 0.189780 1.1 1.1 gamma-aminobutyric acid (GABA-A) receptor, subunit 1460408_at Gabrg1 gamma 1 0.344352 0.000792 1.0 0.9 gamma-aminobutyric acid (GABA-A) receptor, subunit 1422187_at Gabrg3 gamma 3 0.321460 0.032642 1.0 0.8 Complement activation(6) 1449308_at C6 Complement component 6 0.027623 0.411528 0.9 0.9 Complement component 1423153_x_at Cfh factor h 0.548905 0.034331 1.0 1.1 1460242_at Daf1 Decay accelerating factor 1 0.009403 0.002233 1.1 1.3 1419727_at Daf2 Decay accelerating factor 2 0.072303 0.021838 1.0 0.9 Histocompatibility 2, complement component 1417314_at H2-Bf factor B 0.032363 0.184445 1.8 1.3 Mannan-binding lectin serine 1425985_s_at Masp1 protease 1 0.015980 0.169812 0.9 0.9 Cytokine activity(28) bone morphogenetic protein 1450210_at Bmp15 15 0.005381 0.661588 0.9 0.9 1450759_at Bmp6 bone morphogenetic protein 6 0.011121 0.073183 0.8 0.9 1450262_at Bsf3 B-cell stimulating factor 3 0.023794 0.110925 1.0 1.0 small chemokine (C-C motif) 1417789_at Ccl11 ligand 11 0.011516 0.039891 1.5 1.1 chemokine (C-C motif) 1449277_at Ccl19 ligand 19 0.042912 0.013891 1.1 0.9 chemokine (C-C motif) 1422029_at Ccl20 ligand 20 0.505971 0.011675 1.0 0.8 1418777_at Ccl25 chemokine (C-C motif) 0.029669 0.504419 0.9 0.9

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ligand 25 colony stimulating factor 1 1448914_a_at Csf1 (macrophage) 0.031029 0.023717 1.1 0.9 Colony stimulat fact 2 receptor, beta 2, low-affinity 1449360_at Csf2rb2 (granulocyte-macroph) 0.006565 0.009625 1.3 1.0 chemokine (C-X-C motif) 1419209_at Cxcl1 ligand 1 0.024938 0.053037 3.7 1.1 chemokine (C-X-C motif) 1449984_at Cxcl2 ligand 2 0.003093 0.005381 6.2 0.9 chemokine (C-X-C motif) 1418652_at Cxcl9 ligand 9 0.027463 0.079618 1.4 1.1 growth differentiation factor 1416900_s_at Gdf1 1 0.007946 0.013712 1.1 1.0 1417962_s_at Ghr growth hormone receptor 0.009848 0.002149 1.0 1.1 1448148_at Grn granulin 0.014851 0.262698 1.2 1.1 1448167_at Ifngr interferon gamma receptor 0.028805 0.253672 1.1 1.2 1449982_at Il11 interleukin 11 0.006186 0.150430 0.9 0.9 1420740_at Il17e interleukin 17E 0.024425 0.171937 0.9 0.9 1449399_a_at Il1b interleukin 1 beta 0.032167 0.077854 1.7 1.1 interleukin 1 family, member 1451957_at Il1f10 7 0.002253 0.029273 0.9 0.9 interleukin 3 receptor, alpha 1419712_at Il3ra chain 0.338864 0.010652 1.0 1.1 1423996_a_at Il4ra interleukin 4 receptor, alpha 0.046967 0.028122 1.1 0.9 1450550_at Il5 interleukin 5 0.016394 0.079383 0.9 1.0 1421620_at Il5ra interleukin 5 receptor, alpha 0.014250 0.723005 0.9 0.9 1450297_at Il6 interleukin 6 0.024003 0.036553 1.9 0.9 1452416_at Il6ra interleukin 6 receptor, alpha 0.017705 0.007794 0.8 1.2 1425873_a_at Lepr leptin receptor 0.026559 0.083588 0.9 1.0 tumor necrosis factor (ligand) 1420412_at Tnfsf10 superfamily, member 10 0.086384 0.026974 1.1 0.9 Cytokine and chemokine mediated signaling pathway(1) expressed sequence 1.7 1.5 1419042_at AW111922 AW111922 0.007551 0.150199 Defense response(14) 1418770_at Cd2 CD2 antigen 0.006564 0.002068 1.1 0.9 1437502_x_at Cd24a CD24a antigen 0.039489 0.022525 0.8 1.3 1423760_at Cd44 CD44 antigen 0.030655 0.576548 1.5 1.4 1422166_at Dcl1 C-type lectin 1 0.025818 0.597403 0.9 0.9 histocompatibility 2, D region 1451683_x_at H2-D1 locus 1 0.013383 0.063973 1.3 1.1 histocompatibility 2, class II, 1422527_at H2-DMa locus DMa 0.081721 0.025803 0.9 1.1 histocompatibility 2, M 1450529_at H2-M9 region locus 9 0.010813 0.057139 0.9 1.0 intercellular adhesion 1424067_at Icam1 molecule 0.002194 0.005712 1.5 1.1 inducible T-cell co- 1421931_at Icos stimulator 0.031666 0.233659 0.9 0.9 killer cell lectin-like receptor, 1420789_at Klra5 subfamily A, member 5 0.002233 0.034998 0.9 0.9 killer cell lectin-like receptor, 1426171_x_at Klra7 subfamily A, member 7 0.009971 0.169209 0.9 0.8 killer cell lectin-like receptor, 1426136_x_at Klra8 subfamily A, member 8 0.454839 0.016542 1.0 0.8 1420558_at Selp selectin, platelet 0.005809 0.049080 1.4 1.2 T-cell receptor beta, variable 1426772_x_at Tcrb-V13 13 0.010690 0.021768 1.1 1.0 DNA repair(16)

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RIKEN cDNA 0610041O14 1437281_x_at 0610041O14Rik gene 0.010256 0.024964 0.9 1.0 ADP-ribosyltransferase (NAD+; poly (ADP-ribose) 1422502_at Adprt1 polymerase) 1 0.038495 0.011376 0.9 1.1 ataxia telangiectasia mutated 1421205_at Atm homolog (human) 0.024916 0.008726 0.9 1.1 Alpha thalassemia/mental retardat. syndrome X-link 1420948_s_at Atrx homolog (human) 0.398837 0.033663 1.0 1.2 Excision repair cross- complemt rodent repair defic, 1448497_at Ercc3 complemt group 3 0.028229 0.120159 1.1 1.0 1416988_at Msh2 mutS homolog 2 (E. coli) 0.003842 0.006071 1.1 1.0 1416915_at Msh6 mutS homolog 6 (E. coli) 0.010773 0.011267 1.1 1.0 nth (endonuclease III)-like 1 1419433_at Nthl1 (E.coli) 0.028893 0.039335 0.8 1.0 polymerase (DNA directed), 1425371_at Polb beta 0.004997 0.004672 0.9 1.1 1455938_x_at Rad21 RAD21 homolog (S. pombe) 0.014211 0.008797 0.9 1.1 Rad51 homolog c (S. 1438453_at Rad51c cerevisiae) 0.007718 0.045002 0.9 0.9 1450862_at Rad54l RAD54 like (S. cerevisiae) 0.039066 0.015547 1.0 0.9 1448462_at Tdg thymine DNA glycosylase 0.000698 0.002412 1.2 1.0 1438289_a_at Ubl1 ubiquitin-like 1 0.813550 0.028902 1.0 1.2 1425753_a_at Ung uracil-DNA glycosylase 0.075064 0.011970 0.9 1.2 X-ray repair complementing defective repair in Chinese 1416587_a_at Xrcc1 hamster cells 1 0.034403 0.040857 0.8 1.1 Electron transport activity(30) RIKEN cDNA 4430402G14 1450968_at 4430402G14Rik gene 0.151799 0.011015 1.0 1.1 hypothetical protein 1434856_at A130096K20 A130096K20 0.785244 0.024997 1.0 1.2 ATP-binding cassette, sub- family B (MDR/TAP), 1425829_a_at Abcb1a member 1A 0.022431 0.047180 1.5 1.0 acyl-Coenzyme A oxidase 1, 1416408_at Acox1 palmitoyl 0.008536 0.002879 0.9 1.1 1420338_at Alox15 arachidonate 15-lipoxygenase 0.102293 0.024291 1.1 0.8 ATP synthase, H+ transporting, mitoch F0 1433562_s_at Atp5f1 complex, subunit b, isoform 1 0.091600 0.014195 0.9 1.2 ATP synthase, H+ transporting, mitoch F0 1454661_at Atp5g3 complex, subunit c, isoform 3 0.052259 0.031453 1.0 1.0 ATP synthase, H+ transporting, mitochondrial 1448203_at Atp5l F0 complex, subunit g 0.140627 0.022706 0.9 1.2 1416809_at Cdk8 cyclin-dependent kinase 8 0.015261 0.048170 0.9 1.0 cytochrome c oxidase, 1415933_a_at Cox5a subunit Va 0.051699 0.010101 0.9 1.2 1416727_a_at Cyb5 cytochrome b-5 0.049078 0.013081 0.9 1.1 cytochrome b-245, beta 1422978_at Cybb polypeptide 0.017000 0.921504 1.2 1.2 cytochrome P450, family 1, 1416613_at Cyp1b1 subfamily b, polypeptide 1 0.014125 0.021417 1.1 1.0 cytochrome P450, family 21, 1455691_at Cyp21a1 subfamily a, polypeptide 1 0.653278 0.015651 1.0 0.9 1422230_s_at Cyp2a4 cytochrome P450, family 2, 0.034168 0.005703 1.0 0.8

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subfamily a, polypeptide 4 cytochrome P450, family 2. 1419094_at Cyp2c37 subfamily c, polypeptide 37 0.008060 0.001113 1.0 0.9 cytochrome P450, family 2, 1419349_a_at Cyp2d9 subfamily d, polypeptide 9 0.032091 0.036929 0.9 0.9 cytochrome P450, family 2, 1426102_at Cyp2j13 subfamily j, polypeptide 13 0.536235 0.011890 1.0 0.9 cytochrome P450, family 4, 1417071_s_at Cyp4v3 subfamily v, polypeptide 3 0.029051 0.012353 1.1 0.9 1450646_at Cyp51 cytochrome P450, 51 0.021411 0.026946 1.3 0.9 cytochrome P450, family 7, 1421074_at Cyp7b1 subfamily b, polypeptide 1 0.055777 0.026480 1.1 0.9 endoplasmic reticulum (ER) 1431886_at Ern1 to nucleus signalling 1 0.017597 0.002814 1.0 0.9 glutaredoxin 1 1416592_at Glrx1 (thioltransferase) 0.031511 0.148000 1.2 1.1 1419192_at Il4i1 interleukin 4 induced 1 0.022306 0.016156 1.0 1.0 NADH dehydrogenase (ubiquinone) 1 alpha 1422241_a_at Ndufa1 subcomplex, 1 0.141369 0.033354 0.9 1.1 NADH dehydrogenase (ubiquinone) 1 beta 1436803_a_at Ndufb9 subcomplex, 9 0.013898 0.001894 1.0 1.1 1417151_a_at Ntsr2 neurotensin receptor 2 0.077337 0.023840 1.1 0.9 phosphogluconate 1437380_x_at Pgd dehydrogenase 0.168384 0.027172 0.9 1.2 Solute carrier fam 25 (mitoch carrier; adenine nucleot 1424562_a_at Slc25a4 translocat), member 4 0.004881 0.012793 1.2 1.0 sortilin-related receptor, LDLR class A repeats- 1426258_at Sorl1 containing 0.027082 0.073710 1.1 1.0 Endocytosis(5) adaptor-related protein 1416307_at Ap1m1 complex AP-1, mu subunit 1 0.039624 0.010252 1.1 0.9 macrophage scavenger 1425434_a_at Msr1 receptor 1 0.032199 0.078486 1.2 1.0 protein kinase C and casein 1417810_a_at Pacsin2 kinase substrate in neurons 2 0.569598 0.018367 1.0 1.2 sortilin-related receptor, LDLR class A repeats- 1426258_at Sorl1 containing 0.027082 0.073710 1.1 1.0 1448280_at Syp synaptophysin 0.032471 0.341750 0.9 0.9 Epidermal differentiation1) UDP-glucose ceramide 1.3 1.1 1435133_at Ugcg glucosyltransferase 0.008622 0.07186 Frizzled signaling pathway(3) dishevelled 2, dsh homolog 1448616_at Dvl2 (Drosophila) 0.015062 0.138111 0.9 1.0 smoothened homolog 1427048_at Smo (Drosophila) 0.019733 0.170278 0.9 0.9 wingless-related MMTV 1450782_at Wnt4 integration site 4 0.055039 0.002473 1.0 0.8 G-protein coupled receptor protein signaling pathway(35) RIKEN cDNA 6230410J09 1436730_at 6230410J09Rik gene 0.030559 0.534745 0.9 0.9 1418554_at Admr adrenomedullin receptor 0.620825 0.030569 1.0 0.8 1421659_at Adra1a adrenergic receptor, alpha 1a 0.090511 0.033784 1.1 0.9 1422003_at Blr1 Burkitt lymphoma receptor 1 0.012633 0.109817 1.0 1.0 1455571_x_at Calm1 calmodulin 1 0.199082 0.015133 1.0 1.3

178

1422414_a_at Calm3 calmodulin 3 0.001914 0.074259 1.1 1.2 chemokine (C-C motif) 1419609_at Ccr1 receptor 1 0.014560 0.052440 1.6 1.1 corticotropin releasing 1418810_at Crhr1 hormone receptor 1 0.030545 0.627404 0.9 0.9 corticotropin releasing 1450462_at Crhr2 hormone receptor 2 0.023775 0.056579 0.9 1.0 1422830_s_at Drd4 dopamine receptor 4 0.018041 0.031703 0.9 1.0 1421661_at Fprl1 formyl peptide receptor-like 1 0.028388 0.421130 0.9 0.9 follicle stimulating hormone 1450810_at Fshr receptor 0.014763 0.107594 0.9 0.9 frizzled homolog 2 1418533_s_at Fzd2 (Drosophila) 0.002490 0.007660 0.8 1.0 frizzled homolog 3 1450135_at Fzd3 (Drosophila) 0.816189 0.028819 1.0 0.8 frizzled homolog 7 1450044_at Fzd7 (Drosophila) 0.027855 0.136167 1.3 1.1 1422942_at Galr2 galanin receptor 2 0.630734 0.025569 1.0 0.7 guanine nucleotide binding 1419449_a_at Gnai2 protein, alpha inhibiting 2 0.001357 0.004683 1.4 1.1 guanine nucleotide binding 1448031_at Gnao protein, alpha o 0.016473 0.125914 0.9 0.9 guanine nucleotide binding 1426517_at Gnaz protein, alpha z subunit 0.040145 0.019501 1.0 0.9 guanine nucleotide binding protein (G protein), gamma 3 1417428_at Gng3 subunit 0.002078 0.080824 0.9 0.9 gonadotropin releasing 1421665_a_at Gnrhr hormone receptor 0.003801 0.006202 1.0 0.9 1422154_at Gpr27 G protein-coupled receptor 27 0.020011 0.206293 0.9 0.9 1421667_at Gpr66 G protein-coupled receptor 66 0.029303 0.882279 0.9 0.9 1423171_at Gpr88 G-protein coupled receptor 88 0.013670 0.015491 1.0 1.0 gastrin releasing peptide 1421470_at Grpr receptor 0.027103 0.066657 0.9 1.0 1426099_at Hrh4 histamine H4 receptor 0.030560 0.000896 1.0 0.9 5-hydroxytryptamine 1421757_at Htr6 (serotonin) receptor 6 0.010175 0.000229 1.0 0.8 muscle, intestine and stomach 1418800_at Mist1 expression 1 0.021434 0.006433 0.9 0.8 1417489_at Npy2r neuropeptide Y receptor Y2 0.177697 0.003325 1.0 0.9 1417151_a_at Ntsr2 neurotensin receptor 2 0.077337 0.023840 1.1 0.9 1450604_at Olfr140 olfactory receptor 140 0.023695 0.109377 0.9 0.8 prostaglandin E receptor 3 1425251_at Ptger3 (subtype EP3) 0.003525 0.005156 0.9 0.9 1425171_at Rho rhodopsin 0.497741 0.024490 1.0 0.9 1419222_at Tbxa2r thromboxane A2 receptor 0.028382 0.990822 0.9 0.9 thyrotropin releasing 1450356_at Trhr2 hormone receptor 2 0.033678 0.092601 0.9 1.0 GTP binding(30) RIKEN cDNA 1700093E07 1416165_at 1700093E07Rik gene 0.017340 0.013481 1.2 0.9 RIKEN cDNA 2300002G02 1449673_s_at 2300002G02Rik gene 0.208884 0.028762 1.0 0.9 RIKEN cDNA 2310057H16 1416431_at 2310057H16Rik gene 0.034228 0.183448 1.4 1.2 RIKEN cDNA 2310075M17 1428163_at 2310075M17Rik gene 0.198074 0.017349 1.0 1.1 RIKEN cDNA 2600013G09 1434299_x_at 2600013G09Rik gene 0.225921 0.014694 1.0 1.1 1427245_at Arfgap1 ADP-ribosylation factor 0.633200 0.030667 1.0 1.1

179

GTPase activating protein 1 expressed sequence 1419042_at AW111922 AW111922 0.007551 0.150199 1.7 1.5 1423910_at Centg3 centaurin, gamma 3 0.030559 0.041584 0.9 1.0 RIKEN cDNA D330025I23 1426799_at D330025I23Rik gene 0.021411 0.111063 1.3 1.1 DNA segment, Chr 9, Brigham & Women's 1434914_at D9Bwg0185e Genetics 0185 expressed 0.089141 0.026563 1.0 0.9 1428008_at Dnm1l dynamin 1-like 0.010232 0.090854 0.9 0.9 guanylate nucleotide binding 1435906_x_at Gbp2 protein 2 0.028587 0.465958 1.5 1.4 guanine nucleotide binding 1419449_a_at Gnai2 protein, alpha inhibiting 2 0.001357 0.004683 1.4 1.1 guanine nucleotide binding 1448031_at Gnao protein, alpha o 0.016473 0.125914 0.9 0.9 guanine nucleotide binding 1426517_at Gnaz protein, alpha z subunit 0.040145 0.019501 1.0 0.9 golgi associated PDZ and 1421191_s_at Gopc coiled-coil motif containing 0.008672 0.006598 1.1 0.9 1450873_at Gtpbp4 GTP binding protein 4 0.001627 0.003985 1.1 1.3 1451783_a_at Kifap3 kinesin-associated protein 3 0.019375 0.040160 1.1 1.0 mitogen-activated protein 1426759_at Map4k3 kinase kinase kinase kinase 3 0.028306 0.160489 1.1 1.1 RAB12, member RAS 1427992_a_at Rab12 oncogene family 0.000376 0.000830 1.1 1.0 RAB17, member RAS 1422178_a_at Rab17 oncogene family 0.001311 0.001504 0.9 1.0 RAB18, member RAS 1420899_at Rab18 oncogene family 0.072646 0.021650 0.9 1.3 RAB27A, member RAS 1425284_a_at Rab27a oncogene family 0.019885 0.023643 0.9 1.0 RAB3A, member RAS 1422589_at Rab3a oncogene family 0.002258 0.008040 0.8 0.9 RAB3C, member RAS 1432415_at Rab3c oncogene family 0.086388 0.007666 1.0 0.9 Rab40b, member RAS 1436566_at Rab40b oncogene family 0.007530 0.004818 1.0 1.0 RAB7, member RAS 1415734_at Rab7 oncogene family 0.193088 0.007705 1.0 1.1 v-ral simian leukemia viral oncogene homolog B (ras 1435517_x_at Ralb related) 0.441692 0.011599 1.0 1.2 1423846_x_at Tuba2 tubulin, alpha 2 0.003581 0.018608 1.2 1.1 1415978_at Tubb3 tubulin, beta 3 0.033807 0.035524 1.1 1.0 Heat shock protein activity(5) DnaJ (Hsp40) homolog, 1416288_at Dnaja1 subfamily A, member 1 0.366069 0.014075 1.0 1.2 DnaJ (Hsp40) homolog, 1417934_at Dnajc4 subfamily C, member 4 0.127087 0.030979 0.9 1.2 1416146_at Hspa4 heat shock protein 4 0.790087 0.034458 1.0 1.2 heat shock 70kDa protein 5 1416064_a_at Hspa5 (glucose-regulated protein) 0.000339 0.082050 1.1 1.1 1437497_a_at Hspca heat shock protein 1, alpha 0.058726 0.004368 1.0 1.2 Hyaluronic acid binding(2) 1423760_at Cd44 CD44 antigen 0.030655 0.576548 1.5 1.4 chondroitin sulfate 1.9 1.0 1427256_at Cspg2 proteoglycan 2 0.002834 0.006402 Humoral immune response(1) 1426199_x_at Igh-VJ558 immunoglobulin heavy chain 0.004476 0.012616 0.9 1.0

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(J558 family) I-kappa B phosphorylation(1) inhibitor of kappa B kinase 1.2 1.0 1426207_at Ikbkb beta 0.007348 0.024961 Immune response(26) small chemokine (C-C motif) 1417789_at Ccl11 ligand 11 0.011516 0.039891 1.5 1.1 chemokine (C-C motif) 1449277_at Ccl19 ligand 19 0.042912 0.013891 1.1 0.9 chemokine (C-C motif) 1422029_at Ccl20 ligand 20 0.505971 0.011675 1.0 0.8 chemokine (C-C motif) 1418777_at Ccl25 ligand 25 0.029669 0.504419 0.9 0.9 chemokine (C-C motif) 1419609_at Ccr1 receptor 1 0.014560 0.052440 1.6 1.1 chemokine (C-X-C motif) 1419209_at Cxcl1 ligand 1 0.024938 0.053037 3.7 1.1 chemokine (C-X-C motif) 1449984_at Cxcl2 ligand 2 0.003093 0.005381 6.2 0.9 chemokine (C-X-C motif) 1418652_at Cxcl9 ligand 9 0.027463 0.079618 1.4 1.1 1451925_at Eda ectodysplasin-A 0.004713 0.045651 0.8 0.9 guanylate nucleotide binding 1435906_x_at Gbp2 protein 2 0.028587 0.465958 1.5 1.4 histocompatibility 2, D region 1451683_x_at H2-D1 locus 1 0.013383 0.063973 1.3 1.1 histocompatibility 2, class II, 1422527_at H2-DMa locus DMa 0.081721 0.025803 0.9 1.1 histocompatibility 2, M 1450529_at H2-M9 region locus 9 0.010813 0.057139 0.9 1.0 1452348_s_at Ifi205 interferon activated gene 205 0.032813 0.961863 1.7 1.7 immunoglobulin heavy chain 1426199_x_at Igh-VJ558 (J558 family) 0.004476 0.012616 0.9 1.0 1449399_a_at Il1b interleukin 1 beta 0.032167 0.077854 1.7 1.1 interleukin 1 family, member 1451957_at Il1f10 7 0.002253 0.029273 0.9 0.9 1450550_at Il5 interleukin 5 0.016394 0.079383 0.9 1.0 1450297_at Il6 interleukin 6 0.024003 0.036553 1.9 0.9 major histocompatibility 1421899_a_at Mr1 complex, class I-related 0.005718 0.002001 0.9 0.8 myeloid differentiation 1419272_at Myd88 primary response gene 88 0.000760 0.000722 1.2 0.9 protein kinase, interferon- inducible double stranded 1422005_at Prkr RNA dependent 0.027580 0.035386 1.2 1.0 1449508_at Tccr T cell cytokine receptor 0.009872 0.148708 0.9 0.9 1418162_at Tlr4 toll-like receptor 4 0.034328 0.216325 1.1 1.1 tumor necrosis factor (ligand) 1420412_at Tnfsf10 superfamily, member 10 0.086384 0.026974 1.1 0.9 Tnf receptor-associated factor 1421376_at Traf6 6 0.009769 0.008403 1.1 1.0 Inflammatory response(17) expreexpressed sequence 1417483_at AA408868 AA408868 0.001981 0.010747 2.4 1.4 small chemokine (C-C motif) 1417789_at Ccl11 ligand 11 0.011516 0.039891 1.5 1.1 chemokine (C-C motif) 1449277_at Ccl19 ligand 19 0.042912 0.013891 1.1 0.9 chemokine (C-C motif) 1422029_at Ccl20 ligand 20 0.505971 0.011675 1.0 0.8

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chemokine (C-C motif) 1418777_at Ccl25 ligand 25 0.029669 0.504419 0.9 0.9 chemokine (C-C motif) 1419609_at Ccr1 receptor 1 0.014560 0.052440 1.6 1.1 chemokine (C-X-C motif) 1419209_at Cxcl1 ligand 1 0.024938 0.053037 3.7 1.1 chemokine (C-X-C motif) 1449984_at Cxcl2 ligand 2 0.003093 0.005381 6.2 0.9 chemokine (C-X-C motif) 1418652_at Cxcl9 ligand 9 0.027463 0.079618 1.4 1.1 1426099_at Hrh4 histamine H4 receptor 0.030560 0.000896 1.0 0.9 1420740_at Il17e interleukin 17E 0.024425 0.171937 0.9 0.9 1449399_a_at Il1b interleukin 1 beta 0.032167 0.077854 1.7 1.1 1449034_at Klkb1 kallikrein B, plasma 1 0.025215 0.440639 0.8 0.9 myeloid differentiation 1419272_at Myd88 primary response gene 88 0.000760 0.000722 1.2 0.9 regenerating islet-derived 3 1449495_at Reg3a alpha 0.013617 0.062088 0.9 1.0 1420558_at Selp selectin, platelet 0.005809 0.049080 1.4 1.2 1418162_at Tlr4 toll-like receptor 4 0.034328 0.216325 1.1 1.1 Inflammatory response pathway(9) 1423669_at Col1a1 procollagen, type I, alpha 1 0.033101 0.101588 1.1 1.2 1427883_a_at Col3a1 procollagen, type III, alpha 1 0.021391 0.093160 1.3 1.1 1449399_a_at Il1b interleukin 1 beta 0.032167 0.077854 1.7 1.1 1423996_a_at Il4ra interleukin 4 receptor, alpha 0.046967 0.028122 1.1 0.9 1450550_at Il5 interleukin 5 0.016394 0.079383 0.9 1.0 1421620_at Il5ra interleukin 5 receptor, alpha 0.014250 0.723005 0.9 0.9 1450297_at Il6 interleukin 6 0.024003 0.036553 1.9 0.9 1423885_at Lamc1 laminin, gamma 1 0.043456 0.027875 1.1 0.9 1455098_a_at Vtn vitronectin 0.006301 0.023605 0.9 0.9 Insulin receptor signaling pathway(3) adaptor protein with 1453389_a_at Aps pleckstrin homology and src 0.022462 0.089814 0.9 1.0 eukaryotic translation initiation factor 4E binding 1434976_x_at Eif4ebp1 protein 1 0.078345 0.012755 0.9 1.2 pleckstrin homology domain 1425721_at Phip interacting protein 0.015287 0.008662 1.1 0.9 Integrin-mediated signaling pathway(4) a disintegrin and 1460427_a_at Adam28 metalloprotease domain 28 0.009401 0.022022 0.9 1.0 connective tissue growth 1416953_at Ctgf factor 0.001810 0.004427 1.7 1.1 1421997_s_at Itga3 integrin alpha 3 0.010405 0.010786 1.1 1.0 1422445_at Itga6 integrin alpha 6 0.016780 0.046438 1.1 1.0 Intracellular signaling cascade(39) RIKEN cDNA 1110001A05 1422861_s_at 1110001A05Rik gene 0.050647 0.009604 0.9 1.2 RIKEN cDNA 2900057D21 1427190_at 2900057D21Rik gene 0.019104 0.039718 0.9 1.0 RIKEN cDNA 4921528G01 1417230_at 4921528G01Rik gene 0.017238 0.819994 0.9 0.9 RIKEN cDNA 9330170P05 1437946_x_at 9330170P05Rik gene 0.004283 0.122312 0.9 0.9 RIKEN cDNA 9430008B02 1449423_at 9430008B02Rik gene 0.078003 0.020114 1.1 0.9 1418098_at Adcy4 Adenylate cyclase 4 0.064273 0.026298 1.0 1.1 adaptor protein with 1453389_a_at Aps pleckstrin homology and src 0.022462 0.089814 0.9 1.0 1421164_a_at Arhgef1 Rho guanine nucleotide 0.008057 0.013208 0.9 1.0

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exchange factor (GEF1) Rho guanine nucleotide 1449066_a_at Arhgef7 exchange factor (GEF7) 0.031677 0.015773 1.1 0.9 ankyrin repeat and SOCS 1448431_at Asb6 box-containing protein 6 0.061777 0.000826 1.0 0.8 discs, large homolog 2 1421199_at Dlgh2 (Drosophila) 0.016315 0.021416 0.9 1.0 dishevelled 2, dsh homolog 1448616_at Dvl2 (Drosophila) 0.015062 0.138111 0.9 1.0 golgi associated PDZ and 1421191_s_at Gopc coiled-coil motif containing 0.008672 0.006598 1.1 0.9 guanylate cyclase 1, soluble, 1420533_at Gucy1a3 alpha 3 0.012164 0.001203 1.0 0.8 1433843_at Hs1bp3 HS1 binding protein 3 0.068865 0.004363 1.0 0.9 lymphocyte cytosolic protein 1418641_at Lcp2 2 0.004029 0.043866 1.3 1.2 1420685_at Mona monocytic adaptor 0.029651 0.071610 0.8 1.0 par-6 (partitioning defective 1423174_a_at Pard6b 6) homolog beta (C. elegans) 0.000660 0.007321 1.2 1.1 par-6 partitioning defective 6 1420851_at Pard6g homolog gamma (C. elegans) 0.003331 0.026196 0.9 0.9 phosphatidylinositol 3-kinase, regulat subunit, polypep 1 1451737_at Pik3r1 (p85 alpha) 0.010515 0.002568 1.1 1.2 1416675_s_at Plcd phospholipase C, delta 0.014446 0.063599 0.9 0.9 1448749_at Plek pleckstrin 0.025976 0.243752 1.6 1.3 1423292_a_at Prx periaxin 0.006638 0.051637 0.9 1.0 protein tyrosine phosphatase, 1452127_a_at Ptpn13 non-receptor type 13 0.018239 0.012167 1.1 0.9 Rab40b, member RAS 1436566_at Rab40b oncogene family 0.007530 0.004818 1.0 1.0 1426476_at Rasa1 RAS p21 protein activator 1 0.070484 0.001046 1.0 1.2 ral guanine nucleotide 1449124_at Rgl1 dissociation stimulator,-like 1 0.020519 0.085291 1.4 1.1 1449105_at Sh2d2a SH2 domain protein 2A 0.000139 0.001151 0.9 0.9 1454211_a_at Shrm shroom 0.045735 0.021017 1.0 0.9 Solute carrier fam 9 (sodium/hydrogen exchanger), isoform 3 1438116_x_at Slc9a3r1 regulatr 1 0.831915 0.023513 1.0 1.3 Solute carrier fam 9 (sodium/hydrogen exchanger), isoform 3 1431208_a_at Slc9a3r2 regulatr 2 0.010200 0.013769 0.9 1.0 1417646_a_at Snx5 sorting nexin 5 0.021072 0.891438 1.1 1.1 1423076_at Snx9 sorting nexin 9 0.024626 0.086241 0.9 1.0 suppressor of cytokine 1449109_at Socs2 signaling 2 0.012145 0.066861 1.5 1.2 suppressor of cytokine 1455899_x_at Socs3 signaling 3 0.003140 0.008609 2.1 1.1 suppressor of cytokine 1423349_at Socs5 signaling 5 0.011632 0.025023 1.3 1.0 signal transducer and 1421911_at Stat2 activator of transcription 2 0.002956 0.054310 1.3 1.2 1417306_at Tyk2 tyrosine kinase 2 0.002393 0.019195 0.9 1.0 Usher syndrome 1C homolog 1450001_a_at Ush1c (human) 0.614618 0.024739 1.0 0.9 Inositol/phosphatidylinositol kinase/phosphatase activity(5) Mus musculus similar to 1.1 1.1 1427197_at --- ataxia telangiectasia and 0.018962 0.055555

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Rad3 related protein ataxia telangiectasia mutated 0.9 1.1 1421205_at Atm homolog (human) 0.024916 0.008726 bisphosphate 3'-nucleotidase 1449211_at Bpnt1 1 0.011085 0.017388 0.8 1.0 phosphatidylinositol (4,5) bisphosphate 5-phosphatase, 1433941_at Pib5pa A 0.023166 0.316525 0.9 0.9 1431828_a_at Synj2 synaptojanin 2 0.007908 0.048805 0.8 0.9 Interleukin receptor activity(11) 1420740_at Il17e interleukin 17E 0.024425 0.171937 0.9 0.9 1449399_a_at Il1b interleukin 1 beta 0.032167 0.077854 1.7 1.1 interleukin 1 family, member 1451957_at Il1f10 7 0.002253 0.029273 0.9 0.9 1419532_at Il1r2 interleukin 1 receptor, type II 0.005018 0.007521 0.9 0.9 interleukin 3 receptor, alpha 1419712_at Il3ra chain 0.338864 0.010652 1.0 1.1 1423996_a_at Il4ra interleukin 4 receptor, alpha 0.046967 0.028122 1.1 0.9 1450550_at Il5 interleukin 5 0.016394 0.079383 0.9 1.0 1421620_at Il5ra interleukin 5 receptor, alpha 0.014250 0.723005 0.9 0.9 1450297_at Il6 interleukin 6 0.024003 0.036553 1.9 0.9 1452416_at Il6ra interleukin 6 receptor, alpha 0.017705 0.007794 0.8 1.2 1449508_at Tccr T cell cytokine receptor 0.009872 0.148708 0.9 0.9 JAK-STAT, JNK, MAPK, MAPKKK cascade(10) 1450262_at Bsf3 B-cell stimulating factor 3 0.023794 0.110925 1.0 1.0 ELK1, member of ETS 1421896_at Elk1 oncogene family 0.007876 0.026651 0.9 1.0 1449994_at Epgn epithelial mitogen 0.027167 0.007077 0.9 0.7 mitogen activated protein 1425393_a_at Map2k7 kinase kinase 7 0.024330 0.557126 0.9 0.9 mitogen activated protein 1.1 0.9 1425795_a_at Map3k7 kinase kinase kinase 7 0.060496 0.020979 mitogen activated protein 1448342_at Mapk10 kinase 10 0.021170 0.621306 0.9 0.9 mitogen activated protein 1451927_a_at Mapk14 kinase 14 0.001970 0.001970 1.1 1.3 1419646_a_at Mbp myelin basic protein 0.010852 0.517791 0.9 0.8 Nephrosis 1 homolog, 1.0 0.8 1422142_at Nphs1 nephrin (human) 0.057846 0.005102 Protein inhibitor of activated 1418861_at Piasy STAT PIASy 0.003481 0.008413 1.0 0.9 Leukotriene biosynthesis-metabolism(1) 1420338_at Alox15 arachidonate 15-lipoxygenase 0.102293 0.024291 1.1 0.8 MAPK activation(8) expressed sequence 1425847_a_at AV006891 AV006891 0.196712 0.023940 1.0 0.9 1415834_at Dusp6 dual specificity phosphatase 6 0.000638 0.003832 1.2 1.1 Guanine nucleotide binding 1417428_at Gng3 protein (G protein), gamma 3 0.002078 0.080824 0.9 0.9 subunit mitogen activated protein 1425795_a_at Map3k7 kinase kinase kinase 7 0.060496 0.020979 1.1 0.9 mitogen activated protein 1448342_at Mapk10 kinase 10 0.021170 0.621306 0.9 0.9 mitogen activated protein 1451927_a_at Mapk14 kinase 14 0.001970 0.001970 1.1 1.3 mitogen-activated protein 1419169_at Mapk6 kinase 6 0.024646 0.096238 1.1 1.0 mitogen activated protein 1420931_at Mapk8 kinase 8 0.005626 0.268061 0.9 0.9

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mRNA processing and splicing(12) RIKEN cDNA 2600011C06 1428908_at 2600011C06Rik gene 0.013033 0.026125 1.1 1.2 expressed sequence 1427135_at AI450757 AI450757 0.013753 0.010563 0.9 1.1 CUG triplet repeat, RNA 1426407_at Cugbp1 binding protein 1 0.954321 0.007492 1.0 1.2 DEAH (Asp-Glu-Ala-His) 1416145_at Dhx15 box polypeptide 15 0.025215 0.006044 1.0 1.2 LSM1 homolog, U6 small nuclear RNA associated (S. 1423873_at Lsm1 cerevisiae) 0.680289 0.014325 1.0 1.1 nucleolar protein 3 (apoptosis repressor with CARD 1451503_at Nol3 domain) 0.016986 0.050559 0.8 1.0 1427544_a_at Papola poly (A) polymerase alpha 0.008110 0.000745 0.9 1.3 PRP4 pre-mRNA processing 1455696_a_at Prpf4b factor 4 homolog B (yeast) 0.674344 0.027236 1.0 1.3 1419087_s_at Sf3a1 splicing factor 3a, subunit 1 0.194522 0.009394 1.0 0.9 1437803_at Slbp stem-loop binding protein 0.003499 0.793254 0.9 0.9 U2 small nuclear 1426613_a_at Snrpb2 ribonucleoprotein B 0.023461 0.539951 1.1 1.1 1424641_a_at Thoc1 THO complex 1 0.479803 0.008237 1.0 1.3 NIK-I-kappaB/NF-kappaB cascade(2) Myeloid differentiation 1.2 0.9 1419272_at Myd88 primary response gene 88 0.000759 0.000722 1418162_at Tlr4 Toll-like receptor 4 0.034328 0.216325 1.1 1.1 Notch binding(1) 1421827_at Dll4 delta-like 4 (Drosophila) 0.001767 0.231282 0.9 0.9 Oxidoreductase activity(52) RIKEN cDNA 4430402G14 1450968_at 4430402G14Rik gene 0.151799 0.011015 1.0 1.1 RIKEN cDNA 4933402O15 1424045_at 4933402O15Rik gene 0.854566 0.023780 1.0 1.1 RIKEN cDNA 6430402H10 1423780_at 6430402H10Rik gene 0.044296 0.013642 0.9 1.1 acyl-Coenzyme A oxidase 1, 1416408_at Acox1 palmitoyl 0.008536 0.002879 0.9 1.1 alcohol dehydrogenase 5 1416185_a_at Adh5 (class III), chi polypeptide 0.025901 0.055159 1.0 1.1 aldehyde dehydrogenase 2, 1434988_x_at Aldh2 mitochondrial 0.013260 0.010938 0.8 1.1 aldehyde dehydrogenase 1448137_at Aldh7a1 family 7, member A1 0.217920 0.016241 1.0 0.8 1420338_at Alox15 arachidonate 15-lipoxygenase 0.102293 0.024291 1.1 0.8 ATP synthase, H+ transport, mitochondrial F0 complex, 1454661_at Atp5g3 subunit c, isoform 3 0.052259 0.031453 1.0 1.0 1420067_at Cd160 CD160 antigen 0.041102 0.010104 1.1 0.9 cytochrome c oxidase, 1415933_a_at Cox5a subunit Va 0.051699 0.010101 0.9 1.2 1455393_at Cp ceruloplasmin 0.027762 0.514641 1.1 1.1 cytochrome b-245, beta 1422978_at Cybb polypeptide 0.017000 0.921504 1.2 1.2 cytochrome P450, family 1, 1416613_at Cyp1b1 subfamily b, polypeptide 1 0.014125 0.021417 1.1 1.0 cytochrome P450, family 21, 1455691_at Cyp21a1 subfamily a, polypeptide 1 0.653278 0.015651 1.0 0.9 cytochrome P450, family 2, 1422230_s_at Cyp2a4 subfamily a, polypeptide 4 0.034168 0.005703 1.0 0.8

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cytochrome P450, family 2. 1419094_at Cyp2c37 subfamily c, polypeptide 37 0.008060 0.001113 1.0 0.9 cytochrome P450, family 2, 1419349_a_at Cyp2d9 subfamily d, polypeptide 9 0.032091 0.036929 0.9 0.9 cytochrome P450, family 2, 1426102_at Cyp2j13 subfamily j, polypeptide 13 0.536235 0.011890 1.0 0.9 cytochrome P450, family 4, 1417071_s_at Cyp4v3 subfamily v, polypeptide 3 0.029051 0.012353 1.1 0.9 1450646_at Cyp51 cytochrome P450, 51 0.021411 0.026946 1.3 0.9 cytochrome P450, family 7, 1421074_at Cyp7b1 subfamily b, polypeptide 1 0.055777 0.026480 1.1 0.9 1430734_at Dia1 diaphorase 1 (NADH) 0.987369 0.009773 1.0 0.8 formyltetrahydrofolate 1424401_at Fthfd dehydrogenase 0.026088 0.200440 0.8 0.9 frizzled homolog 7 1450044_at Fzd7 (Drosophila) 0.027855 0.136167 1.3 1.1 AFFX- glyceraldehyde-3-phosphate GapdhMur/M32599_3_at Gapd dehydrogenase 0.015687 0.480969 1.1 1.1 1460671_at Gpx1 glutathione peroxidase 1 0.076771 0.031586 0.9 1.1 1449279_at Gpx2 glutathione peroxidase 2 0.019568 0.366521 1.0 1.0 1451695_a_at Gpx4 glutathione peroxidase 4 0.030996 0.011398 0.9 1.1 3-hydroxy-3-methylglutaryl- 1427229_at Hmgcr Coenzyme A reductase 0.008236 0.012335 1.1 1.0 hydroxysteroid (17-beta) 1449386_at Hsd17b9 dehydrogenase 9 0.025915 0.004363 1.0 0.9 hydroxysteroid dehydrogenase-4, delta<5>-3- 1417554_at Hsd3b4 beta 0.049094 0.006471 1.0 0.8 1419192_at Il4i1 interleukin 4 induced 1 0.022306 0.016156 1.0 1.0 isovaleryl coenzyme A 1418238_at Ivd dehydrogenase 0.008067 0.052118 0.9 0.9 malate dehydrogenase, 1454925_x_at Mor2 soluble 0.039315 0.013926 0.9 1.1 5,10- methylenetetrahydrofolate 1450498_at Mthfr reductase 0.177542 0.033192 1.0 0.9 NADH dehydrogenase (ubiquinone) 1 alpha 1422241_a_at Ndufa1 subcomplex, 1 0.141369 0.033354 0.9 1.1 NADH dehydrogenase (ubiquinone) 1 alpha 1448427_at Ndufa6 subcomplex, 6 (B14) 0.556641 0.019359 1.0 1.1 NADH dehydrogenase (ubiquinone) 1 beta 1428322_a_at Ndufb10 subcomplex, 10 0.280470 0.015454 1.0 1.3 NADH dehydrogenase (ubiquinone) 1 beta 1436803_a_at Ndufb9 subcomplex, 9 0.013898 0.001894 1.0 1.1 oxoglutarate dehydrogenase 1451274_at Ogdh (lipoamide) 0.013758 0.027703 1.2 1.0 Procollagen-proline, 2- oxoglutarate 4-dioxygenase, 1417149_at P4ha2 alpha II polypeptide 0.017581 0.016484 0.9 1.1 phosphogluconate 1437380_x_at Pgd dehydrogenase 0.168384 0.027172 0.9 1.2 procollagen-lysine, 2- 1416289_at Plod1 oxoglutarate 5-dioxygenase 1 0.047572 0.013340 1.0 0.9 quininoid dihydropteridine 1437993_x_at Qdpr reductase 0.136109 0.013430 0.9 1.3 1418808_at Rdh5 retinol dehydrogenase 5 0.003522 0.001113 1.0 1.0

186

superoxide dismutase 2, 1417193_at Sod2 mitochondrial 0.023860 0.167109 1.2 1.1 superoxide dismutase 3, 1417633_at Sod3 extracellular 0.038630 0.006084 1.0 0.9 1449064_at Tdh L-threonine dehydrogenase 0.169237 0.009577 1.0 0.8 1419632_at Tecta tectorin alpha 0.130083 0.026672 1.0 0.9 trimethyllysine hydroxylase, 1420725_at Tmlhe epsilon 0.099874 0.030325 1.0 1.1 1422604_at Uox urate oxidase 0.176989 0.007451 1.0 0.9 Oxygen transport(2) hemoglobin Z, beta-like 0.9 0.9 1450736_a_at Hbb-bh1 embryonic chain 0.008470 0.094501 hemoglobin Y, beta-like 0.9 0.8 1422374_s_at Hbb-y embryonic chain 0.054492 0.020873 Phagocytosis(1) Coronin, actin binding protein 1417752_at Coro1c 1C 0.026030 0.508136 1.2 1.2 Protein tyrosine/serine/threonine kinase/phosphatase activity(48) RIKEN cDNA 2210022N24 1426933_at 2210022N24Rik gene 0.015768 0.055198 1.1 1.0 RIKEN cDNA 9430008B02 1449423_at 9430008B02Rik gene 0.078003 0.020114 1.1 0.9 ataxia telangiectasia mutated 1421205_at Atm homolog (human) 0.024916 0.008726 0.9 1.1 expressed sequence 1425847_a_at AV006891 AV006891 0.196712 0.023940 1.0 0.9 1423502_at Brd2 bromodomain containing 2 0.014459 0.061970 1.0 1.0 cell division cycle 2 homolog 1448314_at Cdc2a A (S. pombe) 0.142416 0.031199 1.0 0.9 1422886_a_at Clk4 CDC like kinase 4 0.196981 0.024707 0.9 1.2 death associated protein 1427358_a_at Dapk1 kinase 1 0.007840 0.004753 0.9 1.1 dual specificity phosphatase 11 (RNA/RNP complex 1- 1452594_at Dusp11 interacting) 0.078002 0.019421 1.0 1.2 1415834_at Dusp6 dual specificity phosphatase 6 0.000638 0.003832 1.2 1.1 eukaryotic elongation factor-2 1449013_at Eef2k kinase 0.028161 0.136381 0.9 0.9 endoplasmic reticulum (ER) 1431886_at Ern1 to nucleus signalling 1 0.017597 0.002814 1.0 0.9 fibroblast growth factor 1427777_x_at Fgfr4 receptor 4 0.256456 0.019140 1.0 0.9 glycogen synthase kinase 3 1451020_at Gsk3b beta 0.139723 0.020217 0.9 1.2 homeodomain interacting 1421298_a_at Hipk1 protein kinase 1 0.026476 0.034072 0.9 1.0 hormonally upregulated Neu- 1418260_at Hunk associated kinase 0.866131 0.031202 1.0 0.9 inhibitor of kappaB kinase 1426207_at Ikbkb beta 0.007348 0.024961 1.2 1.0 LIM motif-containing protein 1452060_a_at Limk2 kinase 2 0.012146 0.017240 1.3 1.0 mitogen activated protein 1460636_at Map2k2 kinase kinase 2 0.899392 0.016640 1.0 0.9 mitogen activated protein 1425393_a_at Map2k7 kinase kinase 7 0.024330 0.557126 0.9 0.9 mitogen activated protein 1425795_a_at Map3k7 kinase kinase kinase 7 0.060496 0.020979 1.1 0.9 mitogen activated protein 1419208_at Map3k8 kinase kinase kinase 8 0.013991 0.035152 1.6 1.1

187

mitogen-activated protein 1426759_at Map4k3 kinase kinase kinase kinase 3 0.028306 0.160489 1.1 1.1 mitogen activated protein 1448342_at Mapk10 kinase 10 0.021170 0.621306 0.9 0.9 mitogen activated protein 1451927_a_at Mapk14 kinase 14 0.001970 0.001970 1.1 1.3 mitogen-activated protein 1419169_at Mapk6 kinase 6 0.024646 0.096238 1.1 1.0 mitogen activated protein 1420931_at Mapk8 kinase 8 0.005626 0.268061 0.9 0.9 1450775_at Mos Moloney sarcoma oncogene 0.648076 0.025322 1.0 0.8 NIMA (never in mitosis gene 1423596_at Nek6 a)-related expressed kinase 6 0.030937 0.017687 1.1 0.9 NIMA (never in mitosis gene 1424094_at Nek9 a)-related expressed kinase 9 0.026088 0.065800 1.1 1.0 neurotrophic tyrosine kinase, 1420838_at Ntrk2 receptor, type 2 0.409993 0.020303 1.0 0.8 p21 (CDKN1A)-activated 1450070_s_at Pak1 kinase 1 0.022053 0.036127 0.9 1.0 PCTAIRE-motif protein 1438314_at Pctk1 kinase 1 0.119250 0.008228 1.0 0.8 platelet derived growth factor 1421917_at Pdgfra receptor, alpha polypeptide 0.028578 0.093740 1.3 1.1 1435458_at Pim1 proviral integration site 1 0.032479 0.045328 1.2 1.0 1435458_at Pim1 proviral integration site 1 0.032479 0.045328 1.2 1.0 protein kinase, interferon- inducible double stranded 1422005_at Prkr RNA dependent 0.027580 0.035386 1.2 1.0 protein kinase, interferon- inducible double stranded 1422005_at Prkr RNA dependent 0.027580 0.035386 1.2 1.0 PRP4 pre-mRNA processing 1455696_a_at Prpf4b factor 4 homolog B (yeast) 0.674344 0.027236 1.0 1.3 receptor (TNFRSF)- interacting serine-threonine 1450173_at Ripk2 kinase 2 0.004239 0.002788 1.1 1.0 serum/glucocorticoid 1416041_at Sgk regulated kinase 0.010725 0.181970 1.2 1.2 1448062_at Stk11 serine/threonine kinase 11 0.112648 0.017707 1.0 0.8 serine/threonine kinase 17b 1450997_at Stk17b (apoptosis-inducing) 0.101693 0.003629 1.0 1.1 tyrosine kinase, non-receptor, 1425635_at Tnk1 1 0.020447 0.036969 0.8 1.0 tyrosine kinase, non-receptor, 1448298_at Tnk2 2 0.027850 0.002612 1.0 0.9 1449171_at Ttk Ttk protein kinase 0.032115 0.020382 1.1 0.9 1417306_at Tyk2 tyrosine kinase 2 0.002393 0.019195 0.9 1.0 1425006_a_at Vrk1 vaccinia related kinase 1 0.026768 0.622578 1.1 1.1 Proteolysis and peptidolysis(35) RIKEN cDNA 1700016G05 1449427_at 1700016G05Rik gene 0.175254 0.011422 1.0 0.9 RIKEN cDNA 2810003H13 1418329_at 2810003H13Rik gene 0.036513 0.032359 1.0 1.0 RIKEN cDNA 3110056O03 1434658_at 3110056O03Rik gene 0.065205 0.023251 1.0 0.9 RIKEN cDNA 4930453N24 1423976_at 4930453N24Rik gene 0.270209 0.018402 1.0 1.1 a disintegrin and 1421857_at Adam17 metalloproteinase domain 17 0.026272 0.034689 1.3 0.9 1419626_at Adam25 a disintegrin and 0.031802 0.542285 0.9 0.9

188

metalloprotease domain 25 (testase 2) a disintegrin and 1460427_a_at Adam28 metalloprotease domain 28 0.009401 0.022022 0.9 1.0 A disintegrin-like and metalloprotease with thrombospondin type 1 motif, 1450716_at Adamts1 1 0.005111 0.008136 1.2 1.0 A disintegrin-like and metalloprotease with thrombospondin type 1 motif, 1422561_at Adamts5 5 0.012162 0.092922 1.1 1.1 1418981_at Casp12 caspase 12 0.009171 0.034761 1.1 1.0 1424552_at Casp8 caspase 8 0.026036 0.065375 1.1 1.0 1430240_a_at Clgn calmegin 0.019832 0.015688 1.1 1.0 carboxypeptidase B2 1432835_at Cpb2 (plasma) 0.024562 0.238136 0.9 0.9 1450646_at Cyp51 cytochrome P450, 51 0.021411 0.026946 1.3 0.9 dynein, axonemal, heavy 1421434_at Dnahc5 chain 5 0.520729 0.010592 1.0 0.7 1449305_at F10 coagulation factor X 0.002631 0.002344 1.2 0.9 histocompatibility 2, complement component 1417314_at H2-Bf factor B 0.032363 0.184445 1.8 1.3 1448586_at Hsp70-4 heat shock protein 4 0.377276 0.018887 1.0 1.2 1451607_at Klk21 kallikrein 21 0.017359 0.097171 0.9 1.0 1419090_x_at Klk26 kallikrein 26 0.001104 0.180937 0.9 0.9 kallikrein 4 (prostase, enamel 1420763_at Klk4 matrix, prostate) 0.007237 0.031294 0.8 0.9 1449034_at Klkb1 kallikrein B, plasma 1 0.025215 0.440639 0.8 0.9 mannan-binding lectin serine 1425985_s_at Masp1 protease 1 0.015980 0.169812 0.9 0.9 mel transforming oncogene- 1449432_a_at Mell1 like 1 0.012656 0.014802 0.9 0.8 1434120_a_at Metap2 methionine aminopeptidase 2 0.023176 0.161593 1.3 1.2 macrophage stimulating 1 (hepatocyte growth factor- 1418267_at Mst1 like) 0.092804 0.026768 0.9 0.8 nth (endonuclease III)-like 1 1419433_at Nthl1 (E.coli) 0.028893 0.039335 0.8 1.0 1423060_at Pa2g4 proliferation-associated 2G4 0.020550 0.043374 1.1 1.0 Phosphate regulat gene with homol to endopeptid on the X 1421979_at Phex chromosome 0.033548 0.468689 0.9 0.9 phosphatidylinositol glycan, 1435352_at Pigk class K 0.002634 0.023237 1.0 1.1 plasminogen activator, 1422138_at Plau urokinase 0.069256 0.005559 1.0 0.8 1424689_at Prss32 protease, serine, 32 0.339388 0.018781 1.0 0.8 transglutaminase 2, C 1417500_a_at Tgm2 polypeptide 0.012232 0.020956 1.4 1.0 transglutaminase 2, C 1437277_x_at Tgm2 polypeptide 0.013736 0.039967 1.4 1.1 1450954_at Yme1l1 YME1-like 1 (S. cerevisiae) 0.067959 0.030778 0.8 1.2 Response to stress, oxidative stress, reactive oxygen species, hypoxia, peroxidase activity(14) 1419148_at Avil advillin 0.070712 0.026814 1.1 0.8 1423290_at Cab140 calcium binding protein 140 0.464023 0.010840 1.0 0.9 DNA segment, Chr 3, 1423997_at D3Jfr1 MJeffers 1 0.003763 0.009910 1.2 1.0 1431886_at Ern1 endoplasmic reticulum (ER) 0.017597 0.002814 1.0 0.9

189

to nucleus signalling 1 1460671_at Gpx1 glutathione peroxidase 1 0.076771 0.031586 0.9 1.1 1449279_at Gpx2 glutathione peroxidase 2 0.019568 0.366521 1.0 1.0 1451695_a_at Gpx4 glutathione peroxidase 4 0.030996 0.011398 0.9 1.1 glycogen synthase kinase 3 1451020_at Gsk3b beta 0.139723 0.020217 0.9 1.2 Homocysteine-induc, ER stress-induc, ubiquitin-like 1435626_a_at Herpud1 domain member 1 0.027786 0.067073 1.2 1.0 hypoxia inducible factor 3, 0.9 0.9 1421572_at Hif3a alpha subunit 0.033858 0.170804 mitogen activated protein 1420931_at Mapk8 kinase 8 0.005626 0.268061 0.9 0.9 protein kinase, AMP- activated, beta 1 non-catalytic 1452457_a_at Prkab1 subunit 0.030775 0.057931 1.1 1.1 Protein-kinase, interferon- induc dsRNA dependent 1426482_at Prkrir inhib, P58 repressor 0.019652 0.016947 1.0 1.0 transformation related protein 1416926_at Trp53inp1 53 inducible nuclear protein 1 0.182414 0.033879 0.9 1.3 Rho protein signal transduction(3) Rho guanine nucleotide 1421164_a_at Arhgef1 exchange factor (GEF) 1 0.008057 0.013208 0.9 1.0 brain-specific angiogenesis inhibitor 1-associated protein 1451028_at Baiap2 2 0.026660 0.020205 0.9 0.8 1451783_a_at Kifap3 kinesin-associated protein 3 0.019375 0.040160 1.1 1.0 RNA processing and splicing(4) RIKEN cDNA 0610041O14 1437281_x_at 0610041O14Rik gene 0.010256 0.024964 0.9 1.0 RIKEN cDNA 2600011C06 1.1 1.2 1428908_at 2600011C06Rik gene 0.013033 0.026125 Dicer1, Dcr-1 homolog 1460571_at Dicer1 (Drosophila) 0.180916 0.026579 1.0 0.9 1419087_s_at Sf3a1 Splicing factor 3a, subunit 1 0.194522 0.009394 1.0 0.9 Scavenger receptor activity(2) macrophage scavenger 1425434_a_at Msr1 receptor 1 0.032199 0.078486 1.2 1.0 macrophage scavenger 1448891_at Msr2 receptor 2 0.001168 0.000198 1.0 0.9 Signal transduction(77) RIKEN cDNA 1700093E07 1416165_at 1700093E07Rik gene 0.017340 0.013481 1.2 0.9 RIKEN cDNA 2310075M17 1428163_at 2310075M17Rik gene 0.198074 0.017349 1.0 1.1 RIKEN cDNA 2600013G09 1434299_x_at 2600013G09Rik gene 0.225921 0.014694 1.0 1.1 RIKEN cDNA 6230410J09 1436730_at 6230410J09Rik gene 0.030559 0.534745 0.9 0.9 RIKEN cDNA 9330170P05 1437946_x_at 9330170P05Rik gene 0.004283 0.122312 0.9 0.9 1450695_at Ahr aryl-hydrocarbon receptor 0.011523 0.034319 0.9 1.0 A kinase (PRKA) anchor 1419706_a_at Akap12 protein (gravin) 12 0.023479 0.021259 1.3 0.9 1419421_at Ank1 ankyrin 1, erythroid 0.045283 0.001768 1.0 0.8 Rho guanine nucleotide 1421164_a_at Arhgef1 exchange factor (GEF) 1 0.008057 0.013208 0.9 1.0 aryl hydrocarbon receptor 1421721_a_at Arnt nuclear translocator 0.023584 0.013710 1.1 0.9

190

aryl hydrocarbon receptor 1420669_at Arnt2 nuclear translocator 2 0.072019 0.008518 1.0 0.8 ataxia telangiectasia mutated 1421205_at Atm homolog (human) 0.024916 0.008726 0.9 1.1 brain-specific angiogenesis inhibitor 1-associated protein 1451028_at Baiap2 2 0.026660 0.020205 0.9 0.8 1450262_at Bsf3 B-cell stimulating factor 3 0.023794 0.110925 1.0 1.0 small chemokine (C-C motif) 1417789_at Ccl11 ligand 11 0.011516 0.039891 1.5 1.1 chemokine (C-C motif) 1422029_at Ccl20 ligand 20 0.505971 0.011675 1.0 0.8 chemokine (C-C motif) 1418777_at Ccl25 ligand 25 0.029669 0.504419 0.9 0.9 chloride intracellular channel 1429574_at Clic3 3 0.611970 0.003702 1.0 0.9 chemokine (C-X-C motif) 1449984_at Cxcl2 ligand 2 0.003093 0.005381 6.2 0.9 RIKEN cDNA D330025I23 1426799_at D330025I23Rik gene 0.021411 0.111063 1.3 1.1 DNA segment, Chr 9, Brigham & Women's 1434914_at D9Bwg0185e Genetics 0185 expressed 0.089141 0.026563 1.0 0.9 death associated protein 1427358_a_at Dapk1 kinase 1 0.007840 0.004753 0.9 1.1 dishevelled 2, dsh homolog 1448616_at Dvl2 (Drosophila) 0.015062 0.138111 0.9 1.0 1423136_at Fgf1 fibroblast growth factor 1 0.029586 0.048242 0.9 0.9 fibroblast growth factor 1427777_x_at Fgfr4 receptor 4 0.256456 0.019140 1.0 0.9 frizzled homolog 2 1418533_s_at Fzd2 (Drosophila) 0.002490 0.007660 0.8 1.0 frizzled homolog 3 1450135_at Fzd3 (Drosophila) 0.816189 0.028819 1.0 0.8 frizzled homolog 7 1450044_at Fzd7 (Drosophila) 0.027855 0.136167 1.3 1.1 guanosine diphosphate (GDP) 1456581_x_at Gdi3 dissociation inhibitor 3 0.371662 0.011699 1.0 1.2 guanine nucleotide binding 1419449_a_at Gnai2 protein, alpha inhibiting 2 0.001357 0.004683 1.4 1.1 guanine nucleotide binding 1448031_at Gnao protein, alpha o 0.016473 0.125914 0.9 0.9 guanine nucleotide binding 1426517_at Gnaz protein, alpha z subunit 0.040145 0.019501 1.0 0.9 guanine nucleotide binding protein (G protein), gamma 3 1417428_at Gng3 subunit 0.002078 0.080824 0.9 0.9 hypoxia inducible factor 3, 1421572_at Hif3a alpha subunit 0.033858 0.170804 0.9 0.9 1433843_at Hs1bp3 HS1 binding protein 3 0.068865 0.004363 1.0 0.9 1419532_at Il1r2 interleukin 1 receptor, type II 0.005018 0.007521 0.9 0.9 interleukin 3 receptor, alpha 1419712_at Il3ra chain 0.338864 0.010652 1.0 1.1 1423996_a_at Il4ra interleukin 4 receptor, alpha 0.046967 0.028122 1.1 0.9 1421620_at Il5ra interleukin 5 receptor, alpha 0.014250 0.723005 0.9 0.9 1452416_at Il6ra interleukin 6 receptor, alpha 0.017705 0.007794 0.8 1.2 potassium voltage-gated channel, subfamily H (eag- 1449544_a_at Kcnh2 related), member 2 0.335358 0.006533 1.0 0.7 1451783_a_at Kifap3 kinesin-associated protein 3 0.019375 0.040160 1.1 1.0

191

1425873_a_at Lepr leptin receptor 0.026559 0.083588 0.9 1.0 LPS-responsive beige-like 1449099_at Lrba anchor 0.010621 0.003959 1.0 0.9 mitogen activated protein 1420931_at Mapk8 kinase 8 0.005626 0.268061 0.9 0.9 myeloid differentiation 1419272_at Myd88 primary response gene 88 0.000760 0.000722 1.2 0.9 1418594_a_at Ncoa1 nuclear receptor coactivator 1 0.049787 0.005270 1.0 1.3 1451338_at Nisch nischarin 0.036809 0.004510 0.9 1.2 neuronal PAS domain protein 1421567_at Npas3 3 0.017390 0.052627 0.9 1.0 1423738_at Oxa1l oxidase assembly 1-like 0.012698 0.034953 0.9 1.0 protein kinase C and casein 1417810_a_at Pacsin2 kinase substrate in neurons 2 0.569598 0.018367 1.0 1.2 phosphodiesterase 1A, 1449298_a_at Pde1a calmodulin-dependent 0.020805 0.761315 0.9 0.9 phosphodiesterase 6C, cGMP 1450830_a_at Pde6c specific, cone, alpha prime 0.078294 0.014785 1.0 0.9 1416675_s_at Plcd phospholipase C, delta 0.014446 0.063599 0.9 0.9 protein phosphatase 2, regulatory subunit B (B56), 1425725_s_at Ppp2r5c gamma isoform 0.021964 0.236331 0.9 0.9 Protein-kinase, interferon- induc dsRNA dependent 1426482_at Prkrir inhib, P58 repressor 0.019652 0.016947 1.0 1.0 RAB12, member RAS 1427992_a_at Rab12 oncogene family 0.000376 0.000830 1.1 1.0 RAB17, member RAS 1422178_a_at Rab17 oncogene family 0.001311 0.001504 0.9 1.0 RAB18, member RAS 1420899_at Rab18 oncogene family 0.072646 0.021650 0.9 1.3 RAB27A, member RAS 1425284_a_at Rab27a oncogene family 0.019885 0.023643 0.9 1.0 RAB3A, member RAS 1422589_at Rab3a oncogene family 0.002258 0.008040 0.8 0.9 RAB3C, member RAS 1432415_at Rab3c oncogene family 0.086388 0.007666 1.0 0.9 Rab40b, member RAS 1436566_at Rab40b oncogene family 0.007530 0.004818 1.0 1.0 RAB7, member RAS 1415734_at Rab7 oncogene family 0.193088 0.007705 1.0 1.1 v-ral simian leukemia viral oncogene homolog B (ras 1435517_x_at Ralb related) 0.441692 0.011599 1.0 1.2 1448020_at Rap1a RAS-related protein-1a 0.025602 0.060831 1.0 0.9 regulatory factor X-associated 1425670_at Rfxank ankyrin-containing protein 0.024380 0.012418 1.0 0.9 ral guanine nucleotide 1449124_at Rgl1 dissociation stimulator,-like 1 0.020519 0.085291 1.4 1.1 1420736_at Sim1 single-minded 1 0.210893 0.014178 1.0 0.8 suppressor of cytokine 1449109_at Socs2 signaling 2 0.012145 0.066861 1.5 1.2 suppressor of cytokine 1455899_x_at Socs3 signaling 3 0.003140 0.008609 2.1 1.1 suppressor of cytokine 1423349_at Socs5 signaling 5 0.011632 0.025023 1.3 1.0 signal transducer and 1421911_at Stat2 activator of transcription 2 0.002956 0.054310 1.3 1.2 1424641_a_at Thoc1 THO complex 1 0.479803 0.008237 1.0 1.3 1422740_at Tnfrsf21 tumor necrosis factor receptor 0.008459 0.021600 1.1 1.0

192

superfamily, member 21 Tnf receptor-associated factor 1421376_at Traf6 6 0.009769 0.008403 1.1 1.0 wingless-related MMTV 1450782_at Wnt4 integration site 4 0.055039 0.002473 1.0 0.8 TGF beta receptor/ signaling pathway(8) 1450008_a_at Catnb catenin beta 0.029806 0.167067 1.1 1.1 1456196_x_at Fkbp1a FK506 binding protein 1a 0.015634 0.118600 1.2 1.1 1423100_at Fos FBJ osteosarcoma oncogene 0.002222 0.003066 1.7 0.9 MAD homolog 5 1421047_at Madh5 (Drosophila) 0.032424 0.038553 0.9 1.0 mitogen activated protein 1.1 0.9 1425795_a_at Map3k7 kinase kinase kinase 7 0.060496 0.020979 runt related transcription 1421467_at Runx3 factor 3 0.451473 0.009500 1.0 0.9 serine/threonine kinase 1.0 1.1 1419913_at Strap receptor associated protein 0.110561 0.024767 1421811_at Thbs1 thrombospondin 1 0.016508 0.116533 1.6 1.3 Transcription factor activity(85) RIKEN cDNA 2410197A17 1431092_at 2410197A17Rik gene 0.015610 0.512720 0.9 0.9 RIKEN cDNA 9130423L19 1418801_at 9130423L19Rik gene 0.024944 0.171835 0.9 1.0 expreexpressed sequence 1417483_at AA408868 AA408868 0.001981 0.010747 2.4 1.4 1450695_at Ahr aryl-hydrocarbon receptor 0.011523 0.034319 0.9 1.0 1419421_at Ank1 ankyrin 1, erythroid 0.045283 0.001768 1.0 0.8 aryl hydrocarbon receptor 1421721_a_at Arnt nuclear translocator 0.023584 0.013710 1.1 0.9 aryl hydrocarbon receptor 1420669_at Arnt2 nuclear translocator 2 0.072019 0.008518 1.0 0.8 ankyrin repeat and SOCS 1448431_at Asb6 box-containing protein 6 0.061777 0.000826 1.0 0.8 ataxia telangiectasia mutated 1421205_at Atm homolog (human) 0.024916 0.008726 0.9 1.1 1418811_at Barhl1 BarH-like 1 (Drosophila) 0.084789 0.008577 1.1 0.8 bisphosphate 3'-nucleotidase 1449211_at Bpnt1 1 0.011085 0.017388 0.8 1.0 1450008_a_at Catnb catenin beta 0.029806 0.167067 1.1 1.1 CBFA2T1 identified gene 1448785_at Cbfa2t1h homolog (human) 0.023286 0.279011 0.9 0.9 1422074_at Cdx2 caudal type homeo box 2 0.050165 0.022342 0.9 1.1 CCAAT/enhancer binding 1425261_at Cebpg protein (C/EBP), gamma 0.009603 0.233332 0.9 0.9 1423910_at Centg3 centaurin, gamma 3 0.030559 0.041584 0.9 1.0 cAMP responsive element 1421583_at Creb1 binding protein 1 0.013131 0.637070 0.8 0.8 1420595_at Dlx4 distal-less homeobox 4 0.008927 0.414338 0.9 0.9 1427563_at Dlx6 distal-less homeobox 6 0.011837 0.009900 0.9 1.0 diencephalon/mesencephalon- 1460277_at Dmbx1 expressed brain homeobox 1 0.009608 0.020878 0.8 1.0 1427462_at E2f3 E2F transcription factor 3 0.036173 0.008973 1.1 0.9 ELK1, member of ETS 1421896_at Elk1 oncogene family 0.007876 0.026651 0.9 1.0 eomesodermin homolog 1435172_at Eomes (Xenopus laevis) 0.007883 0.042168 1.0 0.9 E26 avian leukemia oncogene 1452163_at Ets1 1, 5' domain 0.033304 0.136406 1.4 1.1 E26 avian leukemia oncogene 1416268_at Ets2 2, 3' domain 0.018971 0.508112 1.2 1.1

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1418637_at Etv3 ets variant gene 3 0.027529 0.214393 1.3 1.1 1423100_at Fos FBJ osteosarcoma oncogene 0.002222 0.003066 1.7 0.9 1422210_at Foxd3 forkhead box D3 0.287660 0.018627 1.0 0.9 1425254_at Foxn4 forkhead box N4 0.006993 0.015650 0.9 0.9 1434832_at Foxo3 forkhead box O3 0.974317 0.031271 1.0 1.2 1435221_at Foxp1 forkhead box P1 0.032573 0.050937 0.9 1.0 1425463_at Gata6 GATA binding protein 6 0.020177 0.757133 0.8 0.8 general transcription factor II 1418426_at Gtf2a1lf A, 1-like factor 0.006365 0.061845 0.9 0.8 heart and neural crest derivatives expressed 1422221_at Hand2 transcript 2 0.517266 0.016217 1.0 0.9 hairy/enhancer-of-split related with YRPW motif- 1419302_at Heyl like 0.022814 0.772755 0.9 0.9 hypoxia inducible factor 3, 1421572_at Hif3a alpha subunit 0.033858 0.170804 0.9 0.9 3-hydroxy-3-methylglutaryl- 1433445_x_at Hmgcs1 Coenzyme A synthase 1 0.031372 0.831530 1.2 1.2 1426251_at Hmx1 H6 homeo box 1 0.007049 0.007662 0.9 1.0 1427361_at Hoxc6 homeo box C6 0.002462 0.167449 0.9 0.9 ISL1 transcription factor, 1450723_at Isl1 LIM/homeodomain (islet 1) 0.878566 0.028958 1.0 0.9 insulin related protein 2 (islet 1418676_at Isl2 2) 0.033783 0.514635 0.9 0.9 1421483_at Lhx4 LIM homeobox protein 4 0.031835 0.069812 0.9 0.8 v-maf musculoaponeurotic fibrosarcoma oncogene 1418616_at Mafk family, protein K (avian) 0.103455 0.023217 1.0 0.9 1421388_at Mef2d myocyte enhancer factor 2D 0.004307 0.008879 0.9 0.8 microphthalmia-associated 1422025_at Mitf transcription factor 0.168041 0.004611 1.0 0.9 1449559_at Msx2 homeo box, msh-like 2 0.017424 0.083020 0.8 0.9 1437457_a_at Mtpn myotrophin 0.072330 0.001436 1.0 1.4 1422734_a_at Myb myeloblastosis oncogene 0.005910 0.111287 1.0 0.9 1422773_at Myt1 myelin transcription factor 1 0.010885 0.258141 0.9 0.9 myelin transcription factor 1- 1430599_at Myt1l like 0.000445 0.007659 0.9 0.9 1427733_a_at Nfia nuclear factor I/A 0.005869 0.071050 0.9 0.9 nuclear transcription factor, 1419752_at Nfx1 X-box binding 1 0.018266 0.015770 1.0 1.0 NK1 transcription factor 1422049_at Nkx1-2 related, locus 2 (Drosophila) 0.032417 0.216550 0.9 0.9 NK2 transcription factor 1449566_at Nkx2-5 related, locus 5 (Drosophila) 0.036164 0.024981 0.9 0.9 neuroblastoma myc-related 1425923_at Nmyc1 oncogene 1 0.008077 0.136353 0.9 0.9 nuclear receptor subfamily 6, 1421515_at Nr6a1 group A, member 1 0.001077 0.026930 0.9 0.8 POU domain, class 2, 1419716_a_at Pou2f1 transcription factor 1 0.273334 0.006611 1.0 0.9 protein phosphatase 1, regulatory (inhibitor) subunit 1425414_at Ppp1r16b 16B 0.189268 0.025058 1.0 0.9 paired like homeodomain 1450361_at Prop1 factor 1 0.114505 0.018458 1.1 0.9 1432331_a_at Prrx2 paired related homeobox 2 0.017972 0.000924 1.0 0.8 1454906_at Rarb retinoic acid receptor, beta 0.004070 0.000442 1.1 0.8 1419416_a_at Rarg retinoic acid receptor, gamma 0.010772 0.158812 0.8 0.9 1424035_at Rora RAR-related orphan receptor 0.005456 0.010118 0.9 1.0

194

alpha special AT-rich sequence 1436182_at Satb1 binding protein 1 0.959809 0.009068 1.0 0.9 serologically defined colon 1427233_at Sdccag33 cancer antigen 33 0.022598 0.025226 0.8 1.1 1420736_at Sim1 single-minded 1 0.210893 0.014178 1.0 0.8 SWI/SNF relat, matrix assoc, actin depend regulat chromat, 1450889_at Smarca3 subfam a, memb3 0.405791 0.020694 1.0 1.2 synuclein, alpha interacting 1430463_a_at Sncaip protein (synphilin) 0.256342 0.028434 1.0 0.9 1450485_at Sox3 SRY-box containing gene 3 0.017539 0.336226 1.0 1.0 trans-acting transcription 1421504_at Sp4 factor 4 0.255831 0.007540 1.0 0.8 signal transducer and 1421911_at Stat2 activator of transcription 2 0.002956 0.054310 1.3 1.2 TAF7 RNA polym II, TATA box binding protein (TBP)- 1423169_at Taf7 associated factor 0.006971 0.055818 1.1 1.1 1426470_at Tbp TATA box binding protein 0.312436 0.003305 1.0 0.8 1422545_at Tbx2 T-box 2 0.037043 0.027502 1.1 0.9 1449592_at Tcf15 transcription factor 15 0.000201 0.004418 0.9 0.9 1421224_a_at Tcf2 transcription factor 2 0.623869 0.022170 1.0 0.9 1421909_at Tcf20 transcription factor 20 0.015688 0.649137 0.8 0.8 1436207_at Tcf3 transcription factor 3 0.165239 0.033354 1.1 0.8 transforming growth factor 1454758_a_at Tgfb1i4 beta 1 induced transcript 4 0.028071 0.104916 1.1 1.0 transient receptor potential cation channel, subfamily C, 1417577_at Trpc3 member 3 0.290331 0.002886 1.0 0.9 transient receptor potential cation channel, subfamily V, 1419615_at Trpv6 member 6 0.008474 0.024502 0.9 0.8 UDP-glucose 1434486_x_at Ugp2 pyrophosphorylase 2 0.007247 0.003220 0.9 1.1 1418926_at Zfhx1a zinc finger homeobox 1a 0.422125 0.024504 1.0 0.9 1426895_at Zfp191 zinc finger protein 191 0.022781 0.021026 1.1 1.2 1451281_at Zfp96 zinc finger protein 96 0.030906 0.047490 1.0 1.0 Transcription activator, regulator, repressor, corepressor activity(18) RIKEN cDNA 1110036E10 1448505_at 1110036E10Rik gene 0.189264 0.010379 1.0 1.2 aryl hydrocarbon receptor 1421721_a_at Arnt nuclear translocator 0.023584 0.01371 1.1 0.9 aryl hydrocarbon receptor 1420669_at Arnt2 nuclear translocator 2 0.072019 0.008518 1.0 0.8 activating transcription factor 1449192_at Atf7ip 7 interacting protein 0.154597 0.020069 1.0 1.1 1419359_at Clp1 cardiac lineage protein 1 0.355614 0.034659 1.0 0.9 1434832_at Foxo3 forkhead box O3 0.974317 0.031271 1.0 1.2 1435221_at Foxp1 forkhead box P1 0.032573 0.050937 0.9 1.0 KH domain containing, RNA binding, signal transduction 1438461_at Khdrbs1 associated 1 0.027944 0.076269 0.9 1.0 NK2 transcription factor 1449566_at Nkx2-5 related, locus 5 (Drosophila) 0.036164 0.024981 0.9 0.9 protein inhibitor of activated 1418861_at Piasy STAT PIASy 0.003481 0.008413 1.0 0.9 1426162_a_at Rpl7 ribosomal protein L7 0.041787 0.006193 0.9 1.3 RING1 and YY1 binding 1421111_at Rybp protein 0.011772 0.131609 0.9 0.9

195

1420736_at Sim1 single-minded 1 0.210893 0.014178 1.0 0.8 SWI/SNF relat, matrix assoc, actin depend regulat chromat, 1450889_at Smarca3 subf a, member3 0.405791 0.020694 1.0 1.2 suppressor of Ty 5 homolog 1424255_at Supt5h (S. cerevisiae) 0.018414 0.359052 1.1 1.1 1422545_at Tbx2 T-box 2 0.037043 0.027502 1.1 0.9 transducin-like enhancer of split 4, E(spl) homolog 1450853_at Tle4 (Drosophila) 0.378291 0.002148 1.0 1.1 1423176_at Tob1 transducer of ErbB-2.1 0.140039 0.018048 0.9 1.2 Translation factors(8) RIKEN cDNA 2700079K05 1426395_s_at 2700079K05Rik gene 0.048728 0.004405 0.9 1.4 RIKEN cDNA 3230401O13 1415858_at 3230401O13Rik gene 0.893377 0.011199 1.0 1.1 basic leucine zipper and W2 1423456_at Bzw2 domains 2 0.020243 0.041579 1.2 1.0 eukaryotic elongation factor-2 1449013_at Eef2k kinase 0.028161 0.136381 0.9 0.9 eukaryotic translation initiation factor 3, subunit 10 1448425_at Eif3s10 (theta) 0.021312 0.339390 1.1 1.1 eukaryotic translation initiation factor 4E binding 1434976_x_at Eif4ebp1 protein 1 0.078345 0.012755 0.9 1.2 eukaryotic translation 1435803_a_at Eif4el3 initiation factor 4E like 3 0.167437 0.008172 1.0 1.3 protein kinase, interferon- inducible double stranded 1422005_at Prkr RNA dependent 0.027580 0.035386 1.2 1.0 Transmembrane receptor protein tyrosine phosphatase signaling pathway(3) protein tyrosine phosphatase, 1.1 1.1 1418539_a_at Ptpre receptor type, E 0.004608 0.189936 protein tyrosine phosphatase, 0.9 1.0 1450122_at Ptprg receptor type, G 0.023299 0.067398 protein tyrosine phosphatase, receptor type, N polypeptide 0.8 0.9 1425724_at Ptprn2 2 0.026279 0.576421 tRNA processing and splicing(2) RIKEN cDNA 0610027F08 1.0 1.1 1431593_a_at 0610027F08Rik gene 0.000574 0.000103 1419680_a_at Elac2 elaC homolog 2 (E. coli) 0.078852 0.008702 1.0 0.9 Tumor necrosis factor receptor binding/activity(4) 1451925_at Eda ectodysplasin-A 0.004713 0.045651 0.8 0.9 tumor necrosis factor receptor 1422038_a_at Tnfrsf22 superfamily, member 22 0.152834 0.018847 1.0 0.9 tumor necrosis factor receptor 1422101_at Tnfrsf23 superfamily, member 23 0.023896 0.051631 1.2 1.0 tumor necrosis factor (ligand) 1420412_at Tnfsf10 superfamily, member 10 0.086384 0.026974 1.1 0.9 Ubiquitin-dependent protein catabolism and ubiquitin cycle(13) 1448146_at 1300010O06Rik RIKEN cDNA 1300010O06 0.156212 0.032837 1.0 gene 0.9 RIKEN cDNA 2700002L06 1456094_at 2700002L06Rik gene 0.000080 0.000195 0.8 1.0 1427098_at 8030445B08Rik RIKEN cDNA 8030445B08 0.030120 0.080892 0.9 gene 1.0 proteasome (prosome, 1460339_at Psma4 macropain) subunit, alpha 0.001692 0.003842 1.1 1.0

196

type 4 proteasome (prosome, macropain) subunit, alpha 1423568_at Psma7 type 7 0.029668 0.021804 1.1 1.0 proteasome (prosome, macropain) subunit, beta type 1438984_x_at Psmb4 4 0.026419 0.879852 1.1 1.1 S-phase kinase-associated 1425072_at Skp2 protein 2 (p45) 0.003342 0.010645 0.9 1.0 ubiquitin-conjugating enzyme E2B, RAD6 homology (S. 1423107_at Ube2b cerevisiae) 0.104267 0.025653 1.0 1.1 1448671_at Ube2e3 ubiquitin-conjugating enzyme 0.021427 0.010678 1.1 E2E 3, UBC4/5 homolog (yeast) 0.9 1416681_at Ube3a ubiquitin protein ligase E3A 0.028994 0.058112 0.8 1.0 ubiquitin carboxyl-terminal 1419453_at Uchl5 esterase L5 0.003606 0.007296 0.9 1.0 1455205_a_at Usp19 ubiquitin specific protease 19 0.046615 0.025721 0.9 1.1 ubiquitin specific protease 4 1450892_a_at Usp4 (proto-oncogene) 0.014373 0.006179 1.1 1.2 Wnt receptor/ signaling pathway(16) 1450008_a_at Catnb catenin beta 0.029806 0.167067 1.1 1.1 dickkopf homolog 1 1420360_at Dkk1 (Xenopus laevis) 0.023971 0.041229 0.9 1.0 dickkopf homolog 3 1417312_at Dkk3 (Xenopus laevis) 0.876513 0.004154 1.0 0.9 dishevelled 2, dsh homolog 1448616_at Dvl2 (Drosophila) 0.015062 0.138111 0.9 1.0 frizzled homolog 2 1418533_s_at Fzd2 (Drosophila) 0.002490 0.007660 0.8 1.0 frizzled homolog 3 1450135_at Fzd3 (Drosophila) 0.816189 0.028819 1.0 0.8 frizzled homolog 7 1450044_at Fzd7 (Drosophila) 0.027855 0.136167 1.3 1.1 glycogen synthase kinase 3 1451020_at Gsk3b beta 0.139723 0.020217 0.9 1.2 mitogen activated protein 1448342_at Mapk10 kinase 10 0.02117 0.621306 0.9 0.9 microphthalmia-associated 1422025_at Mitf transcription factor 0.168041 0.004611 1.0 0.9 plasminogen activator, 1422138_at Plau urokinase 0.069256 0.005559 1.0 0.8 phosphatidic acid 1448908_at Ppap2b phosphatase type 2B 0.016429 0.275237 1.1 1.1 protein phosphatase 2, regulatory subunit B (B56), 1425725_s_at Ppp2r5c gamma isoform 0.021964 0.236331 0.9 0.9 1436207_at Tcf3 transcription factor 3 0.165239 0.033354 1.1 0.8 transducin-like enhancer of split 4, E(spl) homolog 1450853_at Tle4 (Drosophila) 0.378291 0.002148 1.0 1.1 wingless-related MMTV 1450782_at Wnt4 integration site 4 0.055039 0.002473 1.0 0.8 Differentially expressed genes that were selected for validation by quantitative method are highlighted in bold.

197

VITA

Annapoorani Chockalingam

EDUCATION

2006 Ph.D. Animal Science The Pennsylania State University, University Park, PA 1996 M.V.Sc. in Animal Biotechnology Madras Veterinary College, Chennai, Tamil Nadu, India 1994 D.V.M. Madras Veterinary College, Chennai, Tamil Nadu, India

WORK EXPERIENCE

1996 – 2001 Assistant Professor, Division of Animal Husbandry Faculty of Agriculture, Annamalai Univeristy, India

AWARDS AND HONORS

2005 National Milk Producers Foundation Scholarship. 2005 BARC, USDA Second Place Award- poster day. 2004-2005 Donald V. Josephson and Stuart Patton Scholarship Award in Dairy and Food Science, Pennsylvania State University. 2003-2004 Obie and Mary Snider Scholarship Award in Dairy and Animal Science, Pennsylvania State University. 1996 Dr. Eswaran Memorial Award, MVC, India 1994-1996 Tamil Nadu Veterinary and Animal Sciences University Graduate Merit Scholarship. 1991 National equestrian show jumping, tent pegging and hacks ,R & V, India

SELECTED RESEARCH PUBLICATIONS

Bannerman, D.D., M.J. Paape, and A. Chockalingam. 2006. Staphylococcus aureus Intramammary Infection Elicits Increased Production of Transforming Growth Factor-α, β1, and β2. Vet Immunol & Immunopathol. In press.

Chockalingam, A., M.J.Paape, and D.D. Bannerman. 2005. Increased Milk Levels of Transforming Growth Factor-α, β1, and β2 During Escherichia Coli-Induced Mastitis. J.Dairy Sci. 88: 1986-1993.

Bannerman, D.D., A. Chockalingam, M.J. Paape, and J.C. Hope. 2005. The Bovine Innate Immune Response During Experimentally-Induced Pseudomonas aeruginosa Mastitis. Vet Immunol & Immunopathol 107: 201-215.