In vivo characterization of inflammatory biomarkers in swine and the impact of flunixin meglumine administration

Veterinary Immunology and Immunopathology 148 (2012) 236–242

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Veterinary Immunology and Immunopathology journal homepage: www.elsevier.com/locate/vetimm

Research paper

In vivo characterization of inflammatory biomarkers in swine and the impact of flunixin meglumine administration Sharla M. Peters a,c , Haile Yancy a , Christine Deaver a , Yolanda L. Jones a , Elizabeth Kenyon a , Oscar A. Chiesa a , Juan Esparza a , Rudell Screven a , Vicki Lancaster b , John T. Stubbs III c , Maocheng Yang a , Paddy L. Wiesenfeld d , Michael J. Myers a,∗ a b c d

U.S. FDA, Center for Veterinary Medicine, Office of Research, Laurel, MD 20708, United States U.S. FDA, Center for Veterinary Medicine, Office of New Animal Drug Evaluation, Rockville, MD 20855, United States Department of Microbiology, Howard University, Washington, DC 20059, United States U.S. FDA, Center for Food Safety & Applied Nutrition, Office of Applied Research & Safety Assessment, Laurel, MD 20708, United States

a r t i c l e

i n f o

Article history: Received 14 March 2012 Received in revised form 25 April 2012 Accepted 29 April 2012 Keywords: Inflammation Biomarkers Non-steroidal anti-inflammatory drugs Swine

a b s t r a c t Non-steroidal anti-inflammatory drugs (NSAID) are a family of chemicals that function to reduce pain, fever, and inflammation, and they are commonly used in people and animals for this purpose. Currently there are no NSAIDs approved for the management of inflammation in swine due to a lack of validated animal models and suitable biomarkers to assess efficacy. A previous in vitro study examining biomarkers of inflammation identified fourteen genes that were significantly altered in response to Escherichia coli lipopolysaccharide (LPS)-induced inflammation. In the present study, five of those fourteen genes were tested in vivo to determine if the same effects observed in vitro were also observed in vivo. Plasma levels of prostaglandin E2 (PGE2 ), an essential mediator of fever and inflammation, were also determined. Two groups of swine were stimulated with LPS with the second group also treated with flunixin meglumine. Blood was collected at 0, 1, 3, 6, 8, 24, and 48 h post LPS-stimulation. The RNA was extracted from the blood and quantitative real-time-PCR (qRT-PCR) was utilized to determine the expression patterns of CD1, CD4, serum amyloid A2 (SAA2), Caspase 1, and monocyte chemoattractant protein 1 (MCP-1). The LPS-stimulated animals demonstrated a statistically significant alteration in expression of SAA2 and CD1 at 3 h post-stimulation. Flunixin meglumine treated animals’ demonstrated reduced expression of CD1 in comparison to the LPS-stimulated swine at 24 and 48 h post LPS-stimulation. Flunixin meglumine treated animals exhibited reduced expression of SAA2 at 48 h post-stimulation compared to LPS-stimulated swine. Swine treated with LPS demonstrated statistically significant increases in plasma PGE2 at 1 h post-stimulation. Swine treated with flunixin meglumine had no increase in plasma PGE2 levels at any time. These results demonstrate that PGE2 production, along with two out of five genes (SAA2 and CD1) have the potential to serve as early biomarkers of inflammation as well as indicators of NSAID efficacy. Published by Elsevier B.V.

Abbreviations: GAPDH, glyceraldehyde 3-phosphate dehydrogenase; LPS, lipopolysaccharide; NSAIDMCP-1, monocyte chemoattractant protein 1 non-steroidal anti-inflammatory drugs; PGE2 , prostaglandin E2 ; qRT-PCR, quantitative RT-PCR; SAA2, serum amyloid A2. ∗ Corresponding author at: U.S. FDA, Center for Veterinary Medicine, Office of Research, 8401 Muirkirk Road, Laurel, MD 20708, United States. Tel.: +1 301 210 4355; fax: +1 301 210 4685. E-mail address: [email protected] (M.J. Myers). 0165-2427/$ – see front matter. Published by Elsevier B.V. http://dx.doi.org/10.1016/j.vetimm.2012.05.001

1. Introduction Inflammation is a complex series of events that occurs in response to tissue injury or other trauma. Inflammation involves a cascade of chemical mediators all acting in concert to eliminate pathogenic and non-pathogenic

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conditions. The responses (endogenous and exogenous) can be accompanied by a number of changes distant from the primary site of infection and can involve many organ systems. Fever, increased synthesis of hormones, increased production of leukocytes, and increased production of acute phase proteins in the liver are all characteristic of a systemic response. An inflammatory cascade that goes unresolved can eventually lead to organ dysfunction and death (Schmid-Schonbein, 2006). Animals, like humans, are routinely administered drugs for the alleviation of fever, pain, and other signs associated with inflammatory ailments (Lees et al., 2004). A popular and effective category of drugs used for this purpose are non-steroidal anti-inflammatory drugs, or NSAIDs. NSAIDs are drugs that target cyclooxygenases and subsequently inhibit the production of prostaglandins and thromboxanes, which are key mediators in the process of inflammation (Vane and Botting, 1998). NSAIDs provide a more targeted approach to treating inflammation because they lack the adverse effects of their steroidal counterparts (Salerno and Herman, 2006). Currently, there is only one NSAID in the U.S. that is FDA-approved for use in swine (Anonymous, 1998). This NSAID, flunixin meglumine, is not approved as an anti-inflammatory drug but only as an anti-pyretic for swine because pharmaceutical companies do not have an efficient model for determining the anti-inflammatory effects of NSAIDs. The lack of suitable animal models of inflammation and biomarkers to assess efficacy is further highlighted by the situation in the European Union and Australia, in which only meloxicam has been approved to control inflammation in swine to reduce the signs associated with non-infectious locomotor disorders and adjuctive therapy for treatment of Mastitis–Metritis–Agalactia Syndrome. The basis for this approval was on meloxicam mediated changes in clinical signs (EMA, 2011). The dearth of approved NSAIDs to control inflammation in swine suggests a lack of understanding of the inflammatory process in swine that could be used to support a new animal drug application. Thus, a swine model system with validated biomarkers is needed to test the efficacy of drugs to control inflammation. This study investigated the mRNA expression patterns of five previously identified genes (Peters et al., 2011) that may be altered as a result of an in vivo LPS-stimulation, along with the proximal mediator production of PGE2 . In addition, the ability of the NSAID flunixin meglumine to modify those same measures was also determined. We demonstrate here the differential expression of CD1, SAA2, Caspase 1, MCP-1, and PGE2 in response to both LPSstimulation and flunixin meglumine treatment.

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zolazepam HCL (1–3 mg/kg, Telazol, Fort Dodge Animal Health, Overland Park, KS) followed by intravenous administration of 0.014–0.04 ml/kg of a solution of xylazine (29 mg/ml), zolazepam HCL (15 mg/ml), ketamine HCL (59 mg/ml; Lloyd Labs Inc., Shenandoah, IA), atropine sulfate (0.88 mg/ml, Neogen, Lexington, KY) and butorphanol tartrate (0.59 mg/ml; Torbugesic® , Wyeth, Madison, NJ). Following surgical preparation, an 18 G × 7 cm long, thinwall introducer needle (Cook, Bloomington, IN) was introduced into the lumen of the jugular vein under ultrasound guidance. After the vein was entered, a flexible wire guide was passed through the introducer needle, and advanced into the vessel lumen. The introducer needle was withdrawn and a 16 G × 20 cm long term catheter (Mila International Inc., Erlanger, KY) was inserted over the wire (Seldinger technique); both the needle and catheter were sterile and pyrogen free. The catheter was flushed with a 50 U heparin mixture and secured with two 2-0 nylon sutures (Prolene; Ethicon, Somerville, NJ). The extension and catheter were secured to the animals using 5.0-cm wide flexible bandaging tape (3M VetrapTM ; 3M Animal Care Products, St. Paul, MN). 2.2. In vivo challenge The animals were randomly divided into two groups: LPS stimulated (n = 8) and LPS/flunixin meglumine treated (n = 8). Both groups were administered 2 ␮g/kg of LPS (in sterile, pyrogen free saline) derived from Escherichia coli O55:B5 (Sigma–Aldrich, St. Louis, MO) via the indwelling catheter. The dosage was established in previous experiments as an inducer of a trenchant inflammatory response (Myers et al., 1999, 2003). The LPS/flunixin meglumine group was administered two doses of flunixin meglumine in the cervical musculature at a dose of 2.2 mg/kg (Thermo Fisher Scientific, Wilmington, DE). The first dose was administered 24 h prior to the beginning of the LPSstimulation and the second dose was administered 30 min prior to LPS-stimulation. Blood samples were obtained with a syringe from the catheter and placed in 15 ml conical tubes using lithium heparin as the anti-coagulant. The animals were monitored throughout the stimulation period for any form of distress; clinical signs (flushed skin, labored breathing, and lethargy) along with body temperature and blood glucose levels were recorded at the time of each blood collection. A simplified scoring system for the three subjective measures was used; 0 if the particular clinical sign was absent and 1 if the sign was present. The animal protocol was approved by the Institutional Animal Care and Use Committee and all animals were sacrificed at the end of the study.

2. Materials and methods 2.3. RNA extraction 2.1. Animals and catheterization Sixteen Yorkshire barrows weighing between 70–75 kg were utilized for the in vivo LPS challenge. All animals had an indwelling catheter inserted into the external jugular vein. Briefly, initial sedation was achieved with a combined intramuscular injection of xylazine (Rompun; Phoenix Pharmaceutical, St. Joseph, MO) and

RNA was extracted from swine whole blood using the LeukoLock Total RNA Isolation kit (Ambion, Austin, TX). Isolation was performed according to the manufacturer’s protocol with minor modifications. Briefly, approximately 15 ml of blood were passed through the LeukoLock filter using a 10 cc syringe connected directly to the filter. Each filter was flushed with 3 ml of phosphate buffered

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Table 1 Genes differentially expressed in leukocytes from whole blood post-LPS stimulation. Accession no.

Gene

Gene symbol

GO biological process

Up-regulated CB475095 NM 214214

Serum amyloid A2 Monocyte chemoattractant protein 1

LOC733603 MCP-1

Acute-phase response Inflammatory response Chemotaxis

Down-regulated NM 213831 NM 001001908

CD1 antigen CD4 molecule

CD1 CD4

Caspase 1

CASP1

Immune response Immune response Cell adhesion Inflammatory response Proteolysis

NM 214162

saline, followed by 3 ml of RNA later, and then flushed with 2.5 ml of pH-adjusted Lysis/Binding Solution. The lysate was collected and treated with 25 ␮l of proteinase K. The RNA was isolated via RNA binding beads. Following incubation and centrifugation, the beads were transferred to a fresh microcentrifuge tube and washed several times. RNA was recovered in 40 ␮l of elution buffer. RNA quality was assessed using an Agilent Bioanalyzer (Santa Clara, CA) and quantified using a NanoDrop (Thermo Fisher Scientific, Wilmington, DE). RNA for qRT-PCR analysis was normalized to 50 ng.

2.4. Quantitative RT-PCR Quantitative real-time-PCR (qRT-PCR) was performed using the following five genes: Caspase 1, CD1, MCP-1, SAA2 and CD4 (Table 1), with previously designed primers (Peters et al., 2011) synthesized by Invitrogen (Carlsbad, CA). Total RNA was reverse transcribed using the SuperScript III Platinum SYBR Green One-Step qRT-PCR Kit (Invitrogen). Briefly, 25 ␮l of 2× SYBR Green Reaction Mix, 1 ␮l of Platinum Taq Mix, 21 ␮l of DEPC-treated water, and 1 ␮l each of a 10 ␮M concentration of forward and reverse primers were combined to compose the master mix. Twenty-five microliters of master mix was aliquoted into a 96-well plate followed by the addition of 50 ng of RNA. Real-time detection was conducted using Eppendorf’s RealPlex4 (Hauppauge, NY) with the following parameters: cDNA synthesis at 50 ◦ C for 3 min, 95 ◦ C for 5 min, 40 cycles of 95 ◦ C for 15 s, 60 ◦ C for 30 s and 60 ◦ C for 30 s. Cycle threshold (Ct) values were recorded and utilized for data analysis. GAPDH was used as the reference gene as well as to determine the metabolic activity of the cells. There were no statistically significant differences in GAPDH expression and thus it served as a stable reference gene.

2.5. Cytokine detection Swine blood samples (3 ml) were centrifuged for 10 min at 3000 rpm and the supernatant was removed. The plasma samples were assayed for cytokines by ELISA. Plasma concentrations of IL-6 and TNF-␣ were determined using the Swine TNF-␣ ELISA kit (Invitrogen, Carlsbad, CA, cat # KCS3011) and Quantikine Porcine IL-6 ELISA kit (R&D Systems, Minneapolis, MN; cat # P6000B) according to the manufacturer’s protocol. All plates were immediately read

at 450 nm using the SPECTRAmax Pro 250 spectrophotometer (Molecular Devices, Sunnyvale, CA). 2.6. PGE2 and thromboxane B2 determination Blood to be used for assessment of plasma PGE2 levels were collected using EDTA blood collection tubes into which indomethacin had also been added (10 ␮M final conc.). The blood was immediately centrifuged, aliquotted into cryovials and stored at −80 ◦ C until analyzed. PGE2 was extracted using the Amersham Prostaglandin E2 Biotrak lysis buffers (GE Healthcare, Piscataway, NJ). The concentration of plasma PGE2 was determined using the Prostaglandin E2 EIA Kit-Monoclonal (Cayman Chemical Co, Ann Arbor, MI, cat # 514010). The concentration of plasma thromboxane B2 was determined using the 11dehydro Thromboxane B2 EIA Kit (Cayman Chemical Co., Ann Arbor MI, cat # 519510). 2.7. Statistical analysis Relative expression was determined using the delta–delta Ct method (GenEx, Multi D Analyses AB). GAPDH was utilized as the reference gene. Data are presented as mean ± SEM. The Friedman’s non-parametric test was used to evaluate time differences within a gene for the qRT-PCR data; each gene was analyzed separately. A separate generalized linear model with binomial error structure and a logit link function was used to evaluate the clinical observation data. The model included the fixed effects treatment, time, and time by treatment interaction, and the random error effects among and within subjects. A P-value ≤0.05 was considered statistically significant. 3. Results Maximal plasma concentrations of PGE2 were observed at 1 h in swine treated with LPS, and remained elevated through 8 h post-stimulation (Fig. 1). In contrast, swine treated with LPS and flunixin meglumine demonstrated no increase in PGE2 production as a consequence of LPS stimulation. The elevations in PGE2 levels in the LPS only treated animals was significantly different than those in swine treated with both with LPS and flunixin meglumine at 1 h post stimulation. There was no increase in plasma thromboxane B2 levels at any time in any of the animals in either treatment group (data not shown).

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*

1500

*

LPS LPS-Flunixin

SAA2 LPS SAA2 LPS + Flunixin Meglumine

30

1000

Gene Expression

PGE2 Plasma Concentration (ng/ml)

40

239

300 200

20

*

10

100 0 0

12

24

36

48

60

∗∗

72

Time (hr) Fig. 1. In vivo plasma concentration of prostaglandin E2 in swine challenged with LPS or LPS and flunixin meglumine. Eight swine were challenged with LPS, with an additional eight swine given LPS and flunixin meglumine. Blood was collected at the following time points: 0 h, 1 h, 3 h, 6 h, 8 h 24 h, 48 h, and 72 h. Plasma was collected and evaluated for PGE2 content by ELISA. Data are expressed as mean ± SEM. *Statistical difference based on comparison to the 0 h controls and the corresponding time point (P < 0.05).

CD1 was significantly down-regulated at 3 h post LPS stimulation in swine treated with either LPS only or with LPS and flunixin meglumine (Fig. 2) as compared to CD1 expression prior to LPS stimulation. The expression of CD1 in the LPS only treated swine was returning to basal levels by 24 h post-LPS stimulation. However the expression of CD1 in swine treated with LPS and flunixin meglumine demonstrated suppressed levels of expression through 48 h post-LPS stimulation (Fig. 2). Serum amyloid A2 (SAA2) was significantly upregulated 3 h post LPS simulation (Fig. 3). The expression of SAA2 returned to basal levels by 24 h and 48 h postLPS stimulation. There was no difference between the two treatment groups in terms of their increased expression of SAA2. Expression of SAA2 mRNA returned to basal levels by 24 h post stimulation for both groups. However there

Fig. 2. In vivo qRT-PCR analysis for CD1 expression in swine challenged with LPS or LPS and flunixin meglumine. Six swine were challenged with LPS, with an additional 6 swine given LPS and flunixin meglumine. Blood was collected at the following time points: 0 h, 3 h, 24 h, and 48 h. RNA was extracted and evaluated via qRT-PCR for CD1. Data are expressed as mean ± SEM. *Statistical difference based on comparison to the 0 h control for each treatment (P < 0.05).

0

0

3

24

48

Time (hr) Fig. 3. In vivo qRT-PCR analysis of SAA2 expression in swine challenged with LPS or LPS and flunixin meglumine. Six swine were challenged with LPS and blood was collected at the following time points: 0 h, 3 h, 24 h, and 48 h. RNA was extracted and evaluated via qRT-PCR for SAA2. Data are expressed as mean ± SEM. *Statistical difference based on comparison to the 0 h control for each treatment (P < 0.05). **Statistical difference based on comparison to the 48 h LPS control and 0 h controls for each treatment (P < 0.05).

was a reduction in the amount of SAA2 expressed at 48 h post LPS-stimulation in swine treated with LPS and flunixin meglumine compared to SAA2 expression in LPS treated animals at 48 h and the expression level both groups at 0 h. Caspase 1 expression suggested a trend towards lowered expression levels at 3 h and increased mRNA expression levels at 24 h and 48 h post LPS stimulation (Fig. 4). Swine treated with both LPS and flunixin meglumine showed no trends of altered Caspase 1 expression. MCP-1 demonstrated trends of increased mRNA expression at 3 h, 24 h, and 48 h (Fig. 5), with no apparent alteration caused by co-treatment with flunixin meglumine. CD4 expression was not altered over the observed time points

Fig. 4. In vivo qRT-PCR analysis of Caspase 1 expression in swine challenged with LPS or LPS and flunixin meglumine. Six swine were challenged with LPS and blood was collected at the following time points: 0 h, 3 h, 24 h, and 48 h. RNA was extracted and evaluated via qRT-PCR for Caspase 1. Data are expressed as mean ± SEM. No significant differences were observed between any of the time points (P < 0.05).

S.M. Peters et al. / Veterinary Immunology and Immunopathology 148 (2012) 236–242

TNF-alpha Plasma Concentrations ( ng/ml)

240

120 Flunixin Meglumine LPS

100 80 60 40 20 0 0

1

3

6

8

Time (hr) Fig. 5. In vivo qRT-PCR analysis for MCP-1 expression in swine challenged with LPS or LPS and flunixin meglumine. Six swine were challenged with LPS and blood was collected at the following time points: 0 h, 3 h, 24 h, and 48 h. RNA was extracted and evaluated via qRT-PCR for MCP-1. Data are expressed as mean ± SEM. No significant differences were observed between any of the time points (P < 0.05).

(Fig. 6) in animals treated with LPS only in swine treated with both LPS and flunixin meglumine. All animals were observed for the following clinical signs: lethargy, skin flushing, and labored breathing (Table 2). The animals’ temperature and blood glucose levels were also monitored. At 0 h all of the animals were in good health and demonstrated no adverse signs. One hour post-LPS there were statistically significant differences between the two groups for all three clinical variables (P < 0.001). Significant skin flushing and labored breathing were observed in LPS-stimulated swine through 8 h post-stimulation. Lethargy was observed by 3 h post-LPS treatment and continued through 8 h post stimulation. The temperatures at 1 h demonstrated the highest alteration between the LPS stimulated group and the LPS/flunixin meglumine treated group (Fig. 4). Glucose measurements

Fig. 7. Plasma concentrations of TNF-alpha collected at 0, 1, 3, 6, and 8 h post LPS-stimulation in vivo (n = 6 for each group). Swine were challenged with either LPS or LPS and flunixin meglumine as described in Section 2. Plasma TNF-alpha levels were determined using a swine-specific ELISA. Data are expressed as mean ± SEM.

were recorded at 0 h, 1 h, 3 h, 6 h, 8 h, and 24 h. Both treatment groups experienced a decrease in glucose levels which began to return to normal levels by 24 h post stimulation (data not shown). Plasma TNF-␣ concentrations for both treatment groups peaked at 1 h post stimulation (LPS, 89 ng and flunixin meglumine, 93 ng) and began to return to normal levels at 3 h post stimulation (Fig. 5). Plasma TNF-␣ levels return to near baseline values 6 h and 8 h post LPS-stimulation. Plasma IL-6 concentrations for both treatment groups increased at 1 h post stimulation and peaked at 3 h post stimulation (Fig. 6). The plasma concentration of IL-6 returned to basal levels by 6 h and was maintained at that level through 8 h (Figs. 7 and 8). 4. Discussion

IL-6 Plasma Concentration (pg/ml)

The advent of microarray technology, the advancement in molecular techniques, and the sequencing of the swine genome (Sino-Danish pig genome sequencing project) have aided in the development of new methods for the Flunixin Meglumine LPS

1200 1000 800 600 400 200 0 0

Fig. 6. In vivo qRT-PCR analysis of CD4 expression in swine challenged with LPS or LPS and flunixin meglumine. Six swine were challenged with LPS and blood was collected at the following time points: 0 h, 3 h, 24 h, and 48 h. RNA was extracted and evaluated via qRT-PCR for CD4. Data are expressed as mean ± SEM. No significant differences were observed between any of the time points (P < 0.05).

1

3

6

8

Time (hr) Fig. 8. Plasma concentrations of IL-6 collected at 0, 1, 3, 6, and 8 h post LPSstimulation in vivo (n = 6 for each group). Swine were treated as detailed in Fig. 5. Plasma IL-6 levels were determined using a swine-specific ELISA kit. Data are expressed as mean ± SEM.

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Table 2 Clinical observations of swine following administration of LPS or LPS and flunixin meglumine. Observation

Treatment

Time (h)* 0

Lethargy Skin flushing Labored breathing

LPS LPS–flunixin LPS LPS–flunixin LPS LPS–flunixin

0.00 0.00 0.00 0.00 0.00 0.00

1 ± ± ± ± ± ±

0.00a 0.00a 0.00a 0.00a 0.00a 0.00a

0.17 0.00 0.50 0.17 1.00 0.17

3 ± ± ± ± ± ±

0.15a 0.00a 0.20b 0.15a 0.00b 0.15a

0.67 0.33 0.83 0.00 0.83 0.17

6 ± ± ± ± ± ±

0.19b 0.19a 0.15b 0.00a 0.15b 0.15a

0.67 0.17 0.67 0.00 0.67 0.17

8 ± ± ± ± ± ±

0.19b 0.15a 0.19b 0.00a 0.19b 0.15a

0.50 0.00 0.67 0.00 0.50 0.00

24 ± ± ± ± ± ±

0.20b 0.00a 0.19b 0.00a 0.20b 0.00a

0.17 0.00 0.17 0.00 0.17 0.00

± ± ± ± ± ±

0.15a 0.00a 0.15a 0.00a 0.15a 0.00a

Values are reported as mean ± SEM. The scoring system follows: 0, absence of clinical signs and 1, presence of clinical signs. The signs included lethargy, skin flushing, and labored breathing. * Within each clinical symptom and time, means with differing superscripts are significantly different at a P < 0.05.

identification of biomarkers in swine. A biomarker is officially defined by NIH as “a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” (Atkinson et al., 2001). In the past, biomarker research routinely focused on proteomics, whereas studies within the past decade have incorporated genomic approaches for investigating the expression of biomarkers. The research presented here focused on a genomic approach to verify in vivo previously identified inflammatory swine biomarkers from in vitro studies (Peters et al., 2011). The mRNA expression patterns of five genes (Caspase 1, SAA2, CD1, MCP-1 and CD4) were investigated. Porcine CD1 proteins are assumed to have the same function as the human CD1 cluster, presenting foreign and self-lipid antigens. Genomically, the expression of CD1 varies based on the species and the stimuli evoking the response (Stenger et al., 1998; Mariotti et al., 2004; Gagliardi et al., 2004, 2007; Roura-Mir et al., 2005; Hava et al., 2008). Although the CD1 cluster of genes is found across several species the composition and number of genes differ. The porcine CD1 gene (CD1.1) cDNA clone was identified and demonstrated to have high similarity to human CD1a (Chun et al., 1999). The literature does not suggest that CD1 would be expected to serve as a biomarker of acute inflammation; rather as a possible marker for chronic CNS inflammation (Teige et al., 2004; Bubhoff et al., 2001). We demonstrate here that CD1 could potentially be used as a marker of acute inflammation, specifically in swine. SAA2, unlike CD1, is a known marker of acute inflammation and has been thoroughly investigated as such (Steel and Whitehead, 1994, 1991; Malle and DeBeer, 1996; Uhlar and Whitehaead, 1999). The results from this study suggest that SAA2 might be a long-term marker of NSAID efficacy. MCP-1 and Caspase 1 did not demonstrate any statistically significant differences; however both display trends that can be directly related to LPS stimulation. Further research utilizing these two genes with additional animals needs to be conducted to determine their possible utility as swine markers of inflammation and potential use as indicators of NSAID efficacy. In addition to serving as acute inflammatory markers in swine, the findings presented here suggest that both CD1 and SAA2 could serve as biomarkers of flunixin meglumine efficacy. The data demonstrates that a statistically significant alteration in mRNA expression exists at the 48 h

time point (Fig. 3) for both CD1 and SAA2; regarding this particular time point the effects of flunixin meglumine on the mRNA expression are clear. Other NSAIDs also inhibit expression of CD1. Aspirin and niflumic acid both inhibit expression of CD1 in human dendritic cells (Buckland et al., ˇ 2006; Svajger et al., 2008; Bufan et al., 2009). However, suppression of cell surface is not a universal effect of NSAIDs for all cell types, as indomethacin and ketoprofen do not affect cell surface marker expression in dendritic cells (Matasicâ et al., 2000; Hackstein et al., 2001). There is a lack of information in public domain regarding the mechanism of action of NSAIDs at the transcriptional level. From the literature that is available, there appears to be a distinct difference in the effects of NSAIDs on mediators of the inflammatory response (Tegeder et al., 2001). All NSAIDs inhibit the production of cyclooxygenases; in addition some NSAIDs are able to alter the expression of NF-␬B (a key transcription factor in the inflammatory response). Specifically flunixin meglumine has been shown to weakly inhibit NF-␬B production in RAW 264.7 murine macrophages (Bryant et al., 2003). Aspirin is another weak inhibitor of NF-␬B production compared to other NSAIDs (Takada et al., 2004). Indomethacin, which had no effect on dendritic cells, was able to inhibit NF-␬B production in several different cell lines, providing further proof that the COX-independent inhibition of inflammation may be cell specific. Future studies will address the utility of the genes identified in this study as markers of NSAID efficacy utilizing multiple NSAIDs to ensure that the trends observed for flunixin meglumine are not based on the mechanism of action. The inhibition of PGE2 production by flunixin meglumine is consistent with similar reports using an endotoxin challenge model in cattle (Landoni et al., 1995). The data presented in this paper are the first to detail this effect in swine. These results are also in contrast with antidotal reports from pharmaceutical firms stating that it is too difficult to measure. The sample collection and processing procedures were specifically designed to ensure consistent, repeatable assessments of PGE2 production. As such, these results represent another biomarker for use in determining NSAID efficacy, especially within the context of a defined animal model such as endotoxin challenge model. It may not be possible to assess PGE2 production in a clinical field trial, as the precise onset of the inflammatory response will not be known. In those instances, the default measures would be genomic biomarkers such as CD1 and SAA2.

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The use of biomarkers as indicators of disease has become a vital tool in the characterization and subsequent treatment of several conditions. Swine are commonly consumed by a large population and are also used as models for human disease, thus having systems to assess and treat swine infections are essential. This study identified inflammation biomarkers in swine that potentially can be used to determine the efficacy of novel NSAIDs. Although, further studies must be conducted to verify the in vivo expression patterns of the genomic markers, the results which are presented here are promising. These markers may serve in the future as biomarkers of LPS-induced inflammation as well as markers of NSAID efficacy; which could assist in the standardization of the animal drug approval process. These same markers can also be used during drug discovery to identify lead candidates for further testing and assessment of efficacy.

Acknowledgments We would like to thank all of the following caretakers at the FDA/CVM for maintaining the health of the animals and assisting with animal restraint: Steve Rill, Steve Matthews, Mark McDonald, and Virginia Mills. We would also like to thank Krystyna Orzechowski, Heidi Swaim, Erica Geary, and Dr. Jeffrey Ward for their assistance with the study.

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