Hepatic Gene Expression During Endotoxemia

Journal of Surgical Research 154, 126 –134 (2009) doi:10.1016/j.jss.2008.04.033

Hepatic Gene Expression During Endotoxemia Roland S. Croner, M.D.,*,1 Werner Hohenberger, M.D.,* and Marc G. Jeschke, M.D., Ph.D.† *Department of Surgery, University of Erlangen–Nuremberg, Erlangen, Germany; and †Department of Surgery and Department of Biochemistry and Molecular Biology, Shriners Burns Hospital for Children, University of Texas, Galveston, Texas Submitted for publication March 1, 2008

Purpose. During the course of sepsis, endotoxins and cytokines activate Kupffer cells, induce the liberation and synthesis of adhesion molecules, and damage hepatocytes, which leads to septic liver failure. The interaction of the different hepatic cell types during these processes is not completely understood and may be clarified by microarray technology. Materials and methods. Seven Sprague Dawley rats received either an intraperitoneal injection of lipopolysaccharides (LPS) of 3 mg/kg body weight (n ⴝ 4) or sodium chloride (SC) 0.9% (n ⴝ 3). Animals were sacrificed 24 h after LPS or SC injection. RNA from liver tissue was isolated and hybridized on GeneChips (RAE 230A; Affymetrix, Santa Clara, CA). Expression of interleukin-1␤, tumor necrosis factor-alpha, and signal transducer and activator of transcription 3 was controlled by reverse transcription-polymerase chain reaction analysis. Immunohistochemical staining for intercellular adhesion molecule-1 of liver tissue was performed. Results. We detected 508 differentially expressed genes between LPS and SC. Two hundred forty-eight genes were up-regulated and 260 genes were downregulated in the LPS versus the SC group. Mainly genes involved in immune response and receptor activity were up-regulated in the LPS group. Genes enrolled in catalytic, transferase activity, and metabolisms were down-regulated in the LPS group. The microarray findings could be verified by reverse transcription-polymerase chain reaction analysis and immunohistochemical staining. Conclusions. The contemporaneous differential regulation of genes involved in metabolism, hepatocellular synthesis, and immune response reflect the liver’s central role as immune organ during the 1

To whom correspondence and reprint requests should be addressed at Department of Surgery, University of Erlangen, Krankenhausstrasse 12, D-91054 Erlangen, Germany. E-mail: Roland.Croner@ uk-erlangen.de.

0022-4804/09 $36.00 © 2009 Elsevier Inc. All rights reserved.

course of sepsis. A switch from metabolic to immunological activity is obvious, which aggravates the hepatic damage. The functional interaction of the single genes identified during this process must be further clarified. © 2009 Elsevier Inc. All rights reserved. Key Words: sepsis; liver; microarray; gene expression. INTRODUCTION

The liver plays a key role in host defense mechanism and initiation of the multi-organ dysfunction syndrome during the course of sepsis [1, 2]. Bacterial endotoxins such as lipopolysaccharides (LPS), which are released from the intestine, reach the liver via the portal vein. They activate Kupffer cells and induce the synthesis and secretion of inflammatory cytokines (e.g., tumor necrosis factor-alpha [TNF-␣], interleukin [IL]-6) [3]. These cytokines and LPS itself damage hepatocellular function and induce the liberation and synthesis of adhesion molecules (e.g., P-Selectin, vascular adhesion molecule-1, intercellular adhesion molecule-1 [ICAM1]) in hepatic endothelial cells [4 – 6]. Activated leukocytes adhere to endothelial cells via adhesion molecules, which initiates the diapedesis of neutrophils through the endothelial wall followed by the release of oxygen radicals and proteases [7–9]. These mechanisms and the reduced hepatic perfusion with decreased oxygen supply augment the hepatocellular damage [10, 11]. Consequently failures in hepatic energy metabolism and hepatocellular synthesis, which influence the general host immunity, occur [5, 12]. Because the liver consists of various cellular components (e.g., hepatocytes, Kupffer cells, endothelial cells), each cell type acts by individual response against inflammatory stimulation. Liver failure during the course of sepsis results from the interaction of the different hepatic tissue components which is not yet clarified completely. To evaluate the cohesions of different pathways involved in the liver’s response

126

CRONER, HOHENBERGER, AND JESCHKE: HEPATIC GENE EXPRESSION

against endotoxins, we investigated the gene expression of the complete hepatic tissue in response to LPS stimulation in a rat model of endotoxemia by microarray technology. MATERIALS AND METHODS Animals These studies were reviewed and approved by the appropriate Animal Care and Use Committee, assuring that all animals received humane care. Male Sprague Dawley rats (350 –375 g) were placed in wirebottom cages housed in a temperature-controlled room with a 12-h light-dark cycle. Rats were acclimatized to their environment for 7 d before the study. All rats received water ad libitum throughout the study. Animals received either an intraperitoneal injection of LPS (Escherichia coli 0111:B4; Sigma Chemicals, Deisenhofen, Germany) 3 mg/kg body weight (n ⫽ 4) or intraperitoneal injection of sodium chloride 0.9% (SC, n ⫽ 3). Animals were sacrificed 24 h after LPS or SC injection by an overdose of anesthesia. Samples of liver were harvested, fragmented, snap-frozen in liquid nitrogen, and stored at ⫺73°C for further analysis.

Oligonucleotide Microarrays Gene expression was examined using the GeneChip technology (Affymetrix, Santa Clara, CA). Total RNA was prepared from rat liver samples according to the method of Chomcyznski and Sacchi using Trizol reagent (Life Technologies, Inc., Gaithersburg, MD) [13]. Total RNA was quantified spectroscopically (OD 260 nm) or fluorometrically using Pico green dye and equilibrated to an absolute quantity of 0.5 ␮g/␮L. Biotin-labeled cRNA was generated by in vitro transcription as described previously and hybridized to the GeneChips (RAE 230A) following the manufacturer’s instructions [14]. For first-strand cDNA synthesis 9 ␮L (13.5 ␮g) of total RNA was mixed with 1 ␮L of a mixture of 3 polyadenylated control RNAs, 1 ␮L 100 ␮M T7-oligo-d(T) 24 primer, d(T)24-V (GCA TTA GCG GCC GCG AAA TTAATA CGA CTC ACT ATA GGG AGA TTT TTT TTT TTT TTT TTT TTT V), incubated at 70°C for 10 min, and put on ice. Next, 4 ␮L of 5⫻ first-strand buffer, 2 ␮L 0.1 MDTT, and 1 ␮L 10 mM dNTPs were added and the reaction was preincubated at 42°C for 2 min. Then 2 ␮L (200 U) Superscript II (Life Technologies, Inc., Karlsruhe, Germany) was added and incubation continued at 42°C for 1 h. For second-strand synthesis 30 ␮L of 5⫻ second-strand buffer, 91 ␮L RNAse-free water, 3 mL 10 mM dNTPs, 4 ␮L (40 U) E. coli DNA polymerase I (Life Technologies, Inc., Karlsruhe, Germany), 1 ␮L (12 U) E. coli ligase (TaKaRa, Genneviliers, France), and 1 ␮L (2 U) Rnase H (TaKaRa) were added and the reaction was incubated at 16°C for 2 h. Then, 2.5 mL (10 U) T4 DNA polymerase I (TaKaRa) was added at 16°C for 5 min. The reaction was stopped by adding 10 ␮L 0.5 M ethylenediamine tetraacetic acid; the doublestranded cDNA was extracted with phenol/chloroform, and the aqueous phase was recovered by phase lock gel separation (Eppendorf, Hamburg, Germany). After precipitation, the cDNA was restored in 12 ␮L RNAse-free water. Five microliters of double-stranded cDNA was used to synthesize biotinylated cRNA using the BioArray High Yield Transcript Labeling Kit (Enzo Diagnostics, Farmingdale, NY). Labeled cRNA was purified using the Rneasy mini kit (Qiagen, Hilden, Germany). Fragmentation of cRNA, hybridization to GeneChips, washing, and staining as well as scanning of the arrays in the GeneArray scanner (Agilant, Palo Alto, CA) were performed as recommended in the Affymetrix Gene Expression Analysis Technical Manual. Signal intensities and detection calls for statistical analysis and hierarchical clustering were determined using the GeneChip 5.0 software.

127

RT-PCR Analysis

Isolation of RNA Total RNA was prepared from rat liver samples according to the method of Chomcyznski and Sacchi using Trizol reagent (Life Technologies, Inc., Gaithersburg, MD) [13]. Total RNA was quantified spectroscopically (OD 260 nm) or fluorometrically using Pico green dye and equilibrated to an absolute quantity of 0.5 ␮g/␮L. Subsequently reverse transcription-polymerase chain reaction (RT-PCR) was performed. Total liver RNA (0.5 ␮g) was introduced to synthesize cDNA in a 60 ␮L reaction mixture using 2.5 ␮M random hexamers (Amersham Pharmacia, Freiburg, Germany) and Superscript II reverse transcriptase (Life Technologies, Inc., Gaithersburg, MD). The following primers were used to amplify specific rat transcripts for: 18

S rRNA (QuantumRNA; Ambion, Austin, TX) (488 bp): forward 5=-TCAAGAACGAAAGTCGGAGG-3=, reverse 5=-GGACATCTAAG GGCATCACA-3=. IL-1 (305 bp): forward 5=-CTTCCTTGTGCAAGTGTCTGAAGC-3=, reverse 5=-AAGAAGGTCCTTG GGTCCTCATCC-3=. TNF-␣ (209 bp): forward 5=-TGCCTCAGCCTCTTCTCATT-3=, reverse 5=-GCTTGGTGGTTTG CTACGAC-3=. Signal transducer and activator of transcription 3 (STAT-3) (according to EMBL Accession No. X91810) (436 bp): forward 5=-TGGACCAGATGCGGAGAAG, reverse 5=-AATTTGACCAGC AACCTGAC. The predicted size of each RT-PCR product is assigned in parentheses. Each PCR was initially performed in a thermal cycler (Biometra, Göttingen, Germany) as previously described using standardized amplification programs. Five microliters of each reaction was subsequently subjected to agarose gel electrophoresis followed by ethidium bromide staining. Absolute transcript concentrations were quantified introducing external cDNA standards by use of a real-time PCR cycler (Light Cycler; Roche Diagnostics, Mannheim, Germany). Each gene-specific standard was prepared using the corresponding gel-purified amplicon followed a spectroscopic nucleic acid concentration determination. After serial dilutions of resulting DNA standards final sensitivity levels between 0.1 pg and 1 ng specific transcript per sample were performed during real-time PCR as follows: Using 1 ␮L of each cDNA, the Master SYBR Green protocol was performed (Roche Diagnostics) in 10 ␮L sample volume in glass capillaries using the experimental conditions as follows: (a) 95°C 10-min preincubation; (b) amplification: 95°C 5 s, 55°C 10 s with fluorescence detection, 72°C 18 s, 45 cycles; (c) melting curve: 94°C 10 s, 50°C 60 s, then 0.1°C/s up to 90°C under continuous fluorescence detection. Confirmation of each amplicon identity was obtained through melting curve analysis as well as by sequencing of resulting RT-PCR products (TOBLAP, Munich, Germany). Sequence determining of each PCR product confirmed a 100% homology to the published rat sequences. As negative controls, water instead of RNA was used. Values were calculated by a standardized curve and normalized for actin expression.

Immunohistochemical Staining for ICAM-1 Snap-frozen biopsies of the liver were cryotomized in pieces measuring 5–7 ␮m. They were incubated with acetone for 10 min. A washing procedure with phosphate-buffered saline (PBS) buffer, H 2O 2, and pig serum (Dako, Hamburg, Germany) was performed following the manufacturer’s instructions. A purified biotinconjugated mouse anti-rat CD54 (ICAM-1; Pharmingen, San Diego, CA) was added and incubated 12 h at 4°C. After another washing procedure with PBS buffer, adhesion molecules were visualized by a streptavidin-peroxidase reaction (Chromogen K3461; Dako). The hepatocytes were stained with hematoxylin.

128

JOURNAL OF SURGICAL RESEARCH: VOL. 154, NO. 1, JUNE 1, 2009

Statistics Unsupervised hierarchical cluster analysis was performed between the LPS and the SC group (TIBCO Spotfire, Somerville, MA). Differences in gene expression between LPS and SC were calculated as significant for P ⬍ 0.05 (Mann–Whitney U-test) of the detected signals. Our selection criteria included a fold change (FC) of at least 3 in any direction of the average signals and an average gene signal of at least 250 in either the LPS or the SC group.

RESULTS Microarray Analysis

The unsupervised hierarchical cluster analysis, which included all 15,924 probe sets of the RAE 230A GeneChip, resulted in a clear separation between animals that received LPS or SC. Several subclusters with differentially expressed genes were evaluated (Fig. 1). Following our statistical analysis and selection criteria, we detected 508 differentially expressed genes between LPS versus SC. Two hundred forty-eight genes were up-regulated and 260 genes were downregulated in the LPS versus the SC group. Genes were classified and compared in 11 groups concerning functional aspects: immune response and receptor activity, cell adhesion and cross-linking, cellular growth and proliferation, catalytic and transferase activity, signal transduction, protease inhibitors, metabolism, transcription, cell cycle, membrane transporter, and RNA catabolism. Especially genes that products are involved in immune response and receptor activity were up-regulated in the LPS group. LPS-binding protein was elevated as expected (FC 11). Cytokines like IL-1␤ (FC 8) macrophage inflammatory protein-1␣ (FC 7) and TNF-␣ (FC 2) were up-regulated as well. Genes enrolled in cell adhesion and cross-linking were the second main up-

regulated category in the LPS group. The main upregulated gene in this area was kidney injury molecule-1 (FC 37). Vascular cell adhesion molecule-1 and intercellular adhesion molecule-1 were up-regulated with a FC of 3 and 2. Genes responsible for cellular growth and proliferation, e.g., pancreatitis-associated protein (FC 24) or membrane-type MMP (FC 4), were even highly expressed in the LPS group. Heat shock protein 70-1 (FC 6) and CXC chemokine receptor (FC 5) were upregulated genes in the category of signal transduction. Protease inhibitors such as ␣-2-macroglobulin (FC 77) and tissue inhibitor of metalloproteinase 1 (FC 25) showed an extremely high overexpression in the LPS group. Only few genes involved in metabolism were up-regulated after LPS application. Such genes, which are enrolled in fat metabolism like adipocyte lipidbinding protein (FC 33) or lipoprotein lipase (FC 7), were especially overexpressed in the LPS group. The transcription factors STAT-3 (FC 5) and tumor protein p53 (FC 3) were even up-regulated in the LPS group. Less genes involved in cell cycle such as nuclear RNA helicase (FC 5) were up-regulated after LPS application. A list of selected hepatic genes showing the highest up-regulated signal differences between the LPS versus the SC group is presented in Table 1. Genes with catalytic and transferase activity were the main down-regulated gene group after intraperitoneal LPS injection. Members of the cytochrome P450 family, e.g., cytochrome P450 4F4 (FC –5), cytochrome P450, subfamily IIC (FC – 8), or cytochrome P450, subfamily 2e1 (FC –20), could be detected. 17-␤-Hydroxysteroid dehydrogenase type 2 was the strongest down-regulated gene (FC – 66) in this field. Genes involved in metabolism were the second dominant down-regulated category in the LPS group. Members of this gene family were glucose-6-phosphatase (FC – 6) and serine dehydratase

FIG. 1. Unsupervised hierarchical cluster analysis of the microarray data which resulted in a clear separation between the LPS and SC group. All 15.924 probe sets of the RAE 230A GeneChip (Affymetrix, Santa Clara, CA) were included. (Color version of figure is available online.)

129

CRONER, HOHENBERGER, AND JESCHKE: HEPATIC GENE EXPRESSION

TABLE 1 Up-Regulated Genes in the LPS versus the SC Group, Accession Numbers, and Annotations of the Selected Genes, Average Signal Values of the LPS and SC Group, Fold Changes (FC) of the Average Signal Values LPS versus SC Group Average signal Accession no.

Annotation

SC

LPS

Fold change LPS/SC

AF035963 NM_053953 NM_030845 NM_022194 NM_017208 NM_031512 NM_013025 NM_053843 NM_031832 NM_053374 U14010 NM_012515 NM_023965 BI284739

Immune response/receptor activity Kidney injury molecule-1 (KIM-1) 20 Interleukin 1 receptor, type II (Il1r2) 21 gro (Gro1) 147 Interleukin 1 receptor antagonist gene 60 Lipopolysaccharide binding protein 876 Interleukin 1 beta (IL1␤) 132 Macrophage inflammatory protein-1␣ 70 Fc receptor, IgG, low affinity III (Fcgr3) 300 Lectin, galactose binding (Lgals3) 429 Interferon-␥ binding protein (Igifbp) 274 Soluble IL-1 receptor type I 249 Benzodiazepin receptor (peripheral) 271 Endothelial type phox gene (Cybb) 260 LPS-induced TNF-␣ factor 2.644

753 637 3.103 845 9.593 1.000 479 1.956 2.728 1.503 1.022 1.189 807 4.688

37 30 21 15 11 8 7 6 6 6 4 4 3 2

NM_053822 NM_031659 NM_019905 NM_021261 NM_031140 AI013902 AA875097 NM_012889 NM_012967

Cell adhesion/cross-linking S100 calcium-binding protein A8 Transglutaminase 1, K (Tgm1) Calpactin I heavy chain (Anxa2) Thymosin, beta 10 (Tms␤10) Vimentin (Vim) Annexin VII Fibrinogen, A ␣ polipeptide Vascular cell adhesion molecule 1 Intercellular adhesion molecule 1

22 66 275 104 340 148 6.230 201 303

1.410 794 1.244 520 1.323 576 20.112 531 675

65 12 5 5 4 4 3 3 2

L10229 NM_053289 NM_133298 NM_017125 NM_017259 X83537 NM_019242

Cellular growth/proliferation Pancreatitis-associated protein (PAPII) Pancreatitis-associated protein 1 Glycoprotein nmb (Gpnmb) Cd63 antigen (Cd63) B-cell translocation gene 2 Membrane-type MMP Interferon-related regulator 1 (Ifrd1)

26 42 227 987 357 720 711

636 839 2.240 4.269 1.324 2.529 2.288

24 20 10 4 4 4 3

NM_012580 NM_053297 NM_017051 NM_031776 NM_053990 NM_019386 NM_012495

Catalytic/transferase activity Heme oxygenase (Hmox1) Pyruvate kinase 3 (Pkm2) Superoxide dismutase 2 Guanine deaminase (Gda) Tyrosine phosphatase, type 2 (Ptpn2) Tissue-type transglutaminase Aldolase A, fructose-bisphosphate

490 151 398 556 348 1.067 865

4.332 1.316 2.517 3.041 1.507 3.979 3.011

9 9 6 6 4 4 4

NM_017214 NM_013170 NM_031971 NM_012614 NM_031114 AA945737

Signal transduction Regulator of G-protein signaling 4 Guanylate cyclase 2C (Gucy2c) Heat shock protein 70-1 (Hspa1a) Neuropeptide Y (Npy) S-100 related protein (S100A10) CXC chemokine receptor

34 53 154 218 255 99

1.011 731 887 1.210 1.225 453

30 14 6 6 5 5

NM_012488 NM_012674 NM_053819 NM_053372

Protease inhibitor Alpha-2-macroglobulin (A2m) Pancreatic secretory trypsin inhibitor (Spink1) Tissue inhibitor of metalloproteinase 1 Secretory leukocyte protease inhibitor

373 157 126 493

28.870 4.786 3.106 1.842

77 31 25 4

NM_053365 NM_031598

Metabolism Adipocyte lipid-binding protein Phospholipase A2, group IIA (platelets)

28 51

930 594

33 12

130

JOURNAL OF SURGICAL RESEARCH: VOL. 154, NO. 1, JUNE 1, 2009

TABLE 1 Continued Average signal Accession no.

Annotation

NM_012598 U13253

Lipoprotein lipase (Lpl) Lipid-binding protein

NM_012747 NM_030989

stat-3 Tumor protein p53

NM_053563 NM_019290

Nuclear RNA helicase B-cell translocation gene 3 (Btg3)

Fold change

SC

LPS

LPS/SC

102 654

684 5.092

7 8

390 236

2.072 725

5 3

183 155

816 646

5 4

Transcription

Cell cycle

(FC –28). Solute carriers as solute carrier family 2 A2 (FC –12) or solute carrier family 21, member 5 (FC – 41), were classified as “transporters” and showed a strong downregulation in the LPS group. Only few protease inhibitors, e.g., serine protease inhibitor (FC – 4) and contrapsin-like protease inhibitor (FC –5), were downregulated after LPS injection. Genes of which products are enrolled in immune response and receptor activity such as Kupffer cell receptor (FC –9), or involved in transcription such as D site albumin promoter binding protein (FC –19), or cell adhesion and cross-linking were less frequently down-regulated in the LPS group. Genes responsible for cellular growth and proliferation, e.g., insulin-like growth factor-binding protein 3 (FC – 6) or RNA catabolism like ribonuclease 4 (FC –7), were underexpressed after LPS application. A list of selected hepatic genes showing down-regulated signal differences between the LPS versus the SC group is presented in Table 2. RT-PCR Analysis and Immunohistochemical Staining

Hepatic mRNA levels of IL-1␤, TNF-␣, and STAT-3 showed significantly different values during the RTPCR analysis between the LPS and SC group 24 h after intraperitoneal LPS application (Fig. 2). The differences of IL-1␤, TNF-␣, and STAT-3 levels between the LPS and SC group found in the microarray signals correlated with the RT-PCR results. The immunohistochemical staining for ICAM-1 showed obvious differences between the LPS and the SC group. ICAM-1 was expressed more highly in the LPS than in the SC group. These findings correlate with the signal results evaluated in the microarray analysis (Fig. 3). DISCUSSION

After intraperitoneal LPS application, mainly genes involved in immune response and receptor activity were up-regulated. The liver plays a central

role in host defense during endotoxinemia and is thought as being an immune organ [1]. Under clinical conditions the main source of bacterial endotoxins which reach the liver via the portal vein is the intestine. Various hepatic cell types are activated during the mechanisms responsible for LPS clearance during the first pass of the portal vein blood through the liver [15, 16]. Overexpression of many genes, the products of which are involved in immune response as found in our study after LPS injection, supports this hypothesis. The high expression of LPS-binding protein occurred as a consequence of the elevated circulating LPS-binding protein levels in blood [17]. The complex of LPS bound to LPS-binding protein enables the activation of Kupffer cells via the CD14 receptor [18]. High levels of cytokines such as IL-1␤, TNF-␣, and macrophage inflammatory protein-1␣ mRNA reflect the activation of Kupffer cells in our animal model [3, 19]. Nevertheless, Kupffer cells are not the only source of TNF-␣ release during inflammation. The pancreatitis-associated protein, which was up-regulated in our experimental setting, is a pancreas stress protein and is usually overexpressed in pancreatitis. It induces the up-regulation of TNF-␣ mRNA expression in hepatocytes [20]. Endothelial adhesion molecules are overexpressed in response to cytokines and LPS on endothelial cells [4]. Vascular cell adhesion molecule-1 and intercellular adhesion molecule-1 as detected in our experiments become up-regulated and enable leukocyte adherence and transendothelial migration [7, 8, 21, 22]. Recent data indicate that a very high expression of kidney injury molecule-1, which was detected in our study, is even a member of epithelial cell adhesion molecules [23]. Kidney injury molecule-1 is suspected to be associated with partial dedifferentiation of epithelial cells and may play a role in the development on kidney interstitial fibrosis [24]. Its function during endotoxemia in the liver has to be further clarified.

CRONER, HOHENBERGER, AND JESCHKE: HEPATIC GENE EXPRESSION

131

TABLE 2 Down-Regulated Genes in the LPS versus the SC Group, Accession Numbers, and Annotations of the Selected Genes, Average Signal Values of the LPS and SC Group, Fold Changes (FC) of the Average Signal Values LPS versus SC Group Average signal Accession no. NM_012489 NM_012520 NM_031003 NM_012793 NM_032082 NM_031732 NM_022629 NM_031027 NM_012693 NM_012730 J02585 NM_022220 NM_053769 NM_017332 NM_031565 J03536 NM_053902 U39206 K02422 J05499 NM_031039 AI169331 AA892345 NM_017305 NM_017270 NM_130747 NM_053445 K03040 NM_022547 NM_019184 NM_012624 NM_031344 NM_019363 NM_053995 NM_017084 NM_012844 NM_031509 NM_017013 NM_030850 NM_031839 L46791 NM_019292 NM_031543 NM_012792 NM_024391 AF007107 NM_024143 NM_013112 NM_031640 NM_053507 NM_134407 NM_031855 NM_012703 NM_053433 NM_031705 BI277523

Annotation Catalytic/transferase activity Peroxisomal (Acaa1) Catalase (Cat) GABA transaminase Guanidinoacetate methyltransferase (Gamt) Hydroxyacid oxidase 3 (Hao3) Sulfotransferase, phenol preferring 2 Gamma-butyrobetaine hydroxylase (Bbox) Dihydropyrimidine dehydrogenase (Dpyd) Cytochrome P450 IIA2 (Cyp2a2) Cytochrome P450, subfamily IID2 Liver stearyl-CoA desaturase L-gulono-gamma-lactone oxidase (Gulo) Tyrosine phosphatase Fatty acid synthase (Fasn) Carboxylesterase 1 (Ces1) L-gulono-gamma-lactone oxidase Kynureninase, L-kynurenine hydrolase (Kynu) Cytochrome P450 4F4 (CYP4F4) Cytochrome P-450d methylcholanthrene-i. L-glutamine amidohydrolase Alanine aminotransferase Glutathione-S-transferase, mu type 2 (Yb2) Dimethylglycine dehydrogenase Glutamate-cysteine ligase, subunit (Gclm) Alcohol dehydrogenase 4 (class II) Cytoplasmic acetyl-CoA hydrolase (rACH) Fatty acid desaturase 1 (Fads1) Ornithine carbamoyltransferase 10-Formyltetrahydrofolate dehydrogenase Cytochrome P450, subfamily IIC (Cyp2c) Pyruvate kinase, liver, and RBC Delta-6 fatty acid desaturase (Fads2) Aldehyde oxidase (Aox1) 3-Hydroxybutyrate dehydrogenase (Bdh) Glycine methyltransferase (Gnmt) Epoxide hydrolase 1 (Ephx1) Glutathione-S-transferase, ␣ (Ya) (Gsta1) Glutathione-S-transferase, ␣ type (Gsta2) Betaine-homocysteine methyltransferase Cytochrome P450 (cyp 2C23) Cholesterol esterase Carbonic anhydrase III Cytochrome P450, subfamily 2e1 (Cyp2e1) Flavin-containing monooxygenase 1 (Fmo1) 17-␤ hydroxysteroid dehydrogenase type 2 Metabolism Soluble cytochrome b5 Bile acid CoA ligase (LOC79111) Apolipoprotein A-II (Apoa2) Glutamate carboxypeptidase (Pgcp-pending) Nucleoside diphosphate kinase (Nme3) Aflatoxin aldehyde reductase Ketohexokinase (Khk) Thyroid hormone responsive protein (spot14) Flavin-containing monooxygenase 3 (Fmo3) Dihydropyrimidinase (Dpys) Fatty acid Coenzyme A ligase, long chain 2

Fold change

SC

LPS

LPS/SC

6.551 15.358 2.231 5.312 13.409 11.349 2.453 3.058 6.688 13.683 9.355 6.418 3.632 1.113 2.283 9.371 5.463 3.751 6.005 4.394 4.302 7.789 2.845 2.861 1.194 1.830 4.962 8.834 6.731 17.530 3.372 2.592 3.917 3.173 12.559 8.139 11.240 13.766 11.861 13.567 5.243 17.180 16.009 3.385 13.559

2.151 5.048 727 1.730 4.354 3.561 760 936 1.973 3.485 2.327 1.584 886 269 548 2.195 1.230 745 1.189 974 940 1.234 547 542 214 310 810 1.210 922 2.246 432 328 473 379 1.467 935 1.170 1.279 1.055 1.211 357 1.127 795 131 204

⫺3 ⫺3 ⫺3 ⫺3 ⫺3 ⫺3 ⫺3 ⫺3 ⫺3 ⫺4 ⫺4 ⫺4 ⫺4 ⫺4 ⫺4 ⫺4 ⫺4 ⫺5 ⫺5 ⫺5 ⫺5 ⫺6 ⫺5 ⫺5 ⫺6 ⫺6 ⫺6 ⫺7 ⫺7 ⫺8 ⫺8 ⫺8 ⫺8 ⫺8 ⫺9 ⫺9 ⫺10 ⫺11 ⫺11 ⫺11 ⫺15 ⫺15 ⫺20 ⫺26 ⫺66

11.472 7.699 20.552 4753 1.240 2.026 3.294 13.563 7.007 5.268 12.307

3.682 2.452 6.496 1.440 372 599 956 3.910 1.988 1.483 3.317

⫺3 ⫺3 ⫺3 ⫺3 ⫺3 ⫺3 ⫺3 ⫺3 ⫺4 ⫺4 ⫺4

132

JOURNAL OF SURGICAL RESEARCH: VOL. 154, NO. 1, JUNE 1, 2009

TABLE 2 Continued Average signal Accession no.

Annotation

Fold change

SC

LPS

LPS/SC

NM_013120 NM_012883 NM_020538 NM_017074 M13506 NM_134387 NM_013098 J02868 NM_013215 NM_053962

Glucokinase regulatory protein (Gckr) Estrogen sulfotransferase (Ste) Arylacetamide deacetylase CTL target antigen (Cth) UDP-glucuronosyltransferase phenobarbital-i. Diacetyl-L-xylulose reductase (glb) Glucose-6-phosphatase (G6pc) CYP2D3 Aflatoxin B1 aldehyde reductase (AFAR) Serine dehydratase (Sds)

2.465 13.901 2.517 7.719 2.101 4.197 8.970 10.023 1.976 4.924

644 3.602 633 1.840 415 709 1.504 1.214 133 177

⫺4 ⫺4 ⫺4 ⫺4 ⫺5 ⫺6 ⫺6 ⫺8 ⫺15 ⫺28

NM_133554 M26837 AF147740 NM_031589 NM_012833 NM_080892 NM_021593 NM_053955 NM_017047 NM_012879 NM_131906

Transporter Solute carrier family 17 (Slc17a1) Alpha-2u globulin, clone:PGCL2 Liver-specific organic anion transporter Glucose-6-phosphatase transporter 1 (G6pt1) ATP-binding cassette, subfamily C, member 2 Selenium binding protein 2 (Selenbp2) Kynurenine 3-hydroxylase (Kmo) Crystallin, mu (Crym) Solute carrier family 10, member 1 Solute carrier family 2 A2 (Slc2a2) Solute carrier family 21, member 5 (Slc21a5)

1.461 17.473 5.220 4.466 4.705 3.668 3.669 1.989 8.117 7.496 8.280

468 5.608 1.250 921 739 527 524 256 940 615 204

⫺3 ⫺3 ⫺4 ⫺5 ⫺6 ⫺7 ⫺7 ⫺8 ⫺9 ⫺12 ⫺41

NM_133428 M22359 U51017 NM_012657 D00752

Protease inhibitor Histidine-rich glycoprotein (Hrg) Plasma proteinase inhibitor ␣-1-inhibitor III Kallistatin Serine protease inhibitor (Spin2b) Contrapsin-like protease inhibitor (CPi-23)

13.505 10.275 11.210 16.745 19.236

4.150 3.144 3.059 4.184 4.171

⫺3 ⫺3 ⫺4 ⫺4 ⫺5

NM_031051 AJ243974 NM_022177 NM_012844

Immune response/receptor activity Macrophage migration inhibitory factor BM1av1 MHC class Ib antigen, strain DA Stromal cell-derived factor 1 Kupffer cell receptor (Kclr)

3.920 3.552 1.821 2.357

1.794 978 459 257

⫺2 ⫺4 ⫺4 ⫺9

NM_012551 U20796 NM_057133 NM_012543

Transcription Early growth response 1 (Egr1) Nuclear receptor Rev-ErbA-␤ Nuclear receptor subfamily 0, group B, 2 D site albumin promoter binding protein

3.429 1.243 2.020 1.049

515 120 167 56

NM_022251 NM_012588 NM_133583

Cellular growth/proliferation Aminopeptidase A (Enpep) Insulin-like growth factor-binding protein 3 N-myc downstream-regulated gene 2 (Ndrg2)

1.282 1.125 8.322

366 195 1.390

⫺4 ⫺6 ⫺6

NM_053329

Cell adhesion/cross-linking Insulin-like growth factor binding prot. (Igfals)

1.972

270

⫺7

2.125

⫺7

⫺7 ⫺10 ⫺12 ⫺19

RNA catabolism NM_020082

Ribonuclease 4 (Rnase4)

The transcription factor STAT-3, which was 5-fold up-regulated in the LPS group, is activated through the IL-6 family of cytokines [25]. It may contribute to hepatocellular dysfunction during endotoxemia by activating pathways that culminate in cell death. Consequent to STAT-3 overexpression, ␣-2macroglobulin transcription, which is induced via STAT-3, was even highly expressed after LPS application

14.640

[26]. A further up-regulated contributor to apoptotic cell death in endotoxemia found in our study is p53 [27]. Genes involved in catalytic, transferase activity, and metabolism were the main important down-regulated group after LPS injection. Many members especially of the cytochrome P450 family were detected in this field. Cytochrome P450-mediated drug metabolism is impaired during sepsis, which can be explained by our

CRONER, HOHENBERGER, AND JESCHKE: HEPATIC GENE EXPRESSION

133

We were able to confirm recently described changes in hepatic gene expression during endotoxemia. These findings and the correlation of our microarray signals with the performed RT-PCR and immunohistochemical analysis are indicators for the reliability of our data. The activation of inflammatory cascades and apoptotic pathways as detected in our experimental setting leads to hepatocellular damage. Derangement of carbohydrate metabolism followed by protein catabolism can be explained by the evaluated differentially expressed genes between the LPS and SC group. The differentially expressed genes identified deliver explanations for metabolic and immunological changes as they could be observed under clinical conditions. Nevertheless this is the first time the complex interaction of various pathways involved in hepatic damage during endotoxemia could be presented in our experimental setting.

A

FIG. 2. RT-PCR analysis of IL-1␤ (A), TNF-␣ (B), and STAT-3 (C). The microarray data correlate with the RT-PCR results.

findings [28, 29]. Bile acid CoA ligase is responsible for catalyzing the first step in the conjugation of bile acids with amino acids [30]. Down-regulation of this enzyme as found in our animal model may contribute to jaundice during the course of sepsis as it can be observed under clinical conditions [31]. Underexpression of genes such as ketohexokinase or glucose-6-phosphatase is an indicator for derailment of carbohydrate metabolism. Protein biosynthesis can be induced by insulin-like growth factor in complex with insulin-like growth factor-binding protein 3 [32]. Down-regulation of insulin-like growth factor-binding protein 3 as detected in our study reflects the endotoxemia-induced catabolism that could frequently be observed in patients suffering from sepsis.

B FIG. 3. Immunohistochemical staining of liver tissue for ICAM-1. Obvious lower ICAM-1 expression was detected in the SC (A) versus the LPS group (B), which correlates with our microarray findings. (Color version of figure is available online.)

134

JOURNAL OF SURGICAL RESEARCH: VOL. 154, NO. 1, JUNE 1, 2009

The role of many genes identified is already not completely understood and should be elucidated by further investigations.

18. 19.

REFERENCES 1. 2.

3.

4. 5.

6. 7. 8. 9.

10.

11. 12.

13.

14.

15.

16.

17.

Sheth K, Bankey P. The liver as an immune organ. Curr Opin Crit Care 2001;7:99. Smets D, Spapen H, Diltoer M, et al. Liver perfusion and hepatocellular inflammatory response in sepsis. Acta Clin Belg 1999;54:201. Koo DJ, Chaudry IH, Wang P. Kupffer cells are responsible for producing inflammatory cytokines and hepatocellular dysfunction during early sepsis. J Surg Res 1999;83:151. Ring A, Stremmel W. The hepatic microvascular responses to sepsis. Semin Thromb Hemost 2000;26:589. Wang P, Ba ZF, Chaudry IH. Mechanism of hepatocellular dysfunction during early sepsis. Key role of increased gene expression and release of proinflammatory cytokines tumor necrosis factor and interleukin-6. Arch Surg 1997;132:364; discussion 369. Carlos TM, Harlan JM. Leukocyte-endothelial adhesion molecules. Blood 1994;84:2068. Ley K. Molecular mechanisms of leucocyte rolling and adhesion to microvascular endothelium. Eur Heart J 1993;14(Suppl I):68. Ley K. Molecular mechanisms of leukocyte recruitment in the inflammatory process. Cardiovasc Res 1996;32:733. Parent C, Eichacker PQ. Neutrophil and endothelial cell interactions in sepsis. The role of adhesion molecules. Infect Dis Clin North Am 1999;13:427, x. Lam C, Tyml K, Martin C, et al. Microvascular perfusion is impaired in a rat model of normotensive sepsis. J Clin Invest 1994;94:2077. McCuskey RS, Urbaschek R, Urbaschek B. The microcirculation during endotoxemia. Cardiovasc Res 1996;32:752. Sax HC, Hasselgren PO, Talamini MA, et al. Amino acid uptake in isolated, perfused liver: effect of trauma and sepsis. J Surg Res 1988;45:50. Chomczynski P, Sacchi N. Single step method of RNA isolation by guanidium thiocyanate-phenol-chloroform extraction. Anal Biochem 1987;162:156. Dürig J, Nückel H, Hüttmann A, et al. Expression of ribosomal and translation-associated genes is correlated with a favorable clinical course in chronic lymphocytic leukemia. Blood 2003; 101:2748. Schmidt H, Secchi A, Wellmann R, et al. Effect of endotoxemia on intestinal villus microcirculation in rats. J Surg Res 1996; 61:521. Secchi A, Ortanderl JM, Schmidt W, et al. Effect of endotoxemia on hepatic portal and sinusoidal blood flow in rats. J Surg Res 2000;89:26. Fang CW, Yao YM, Zhai HX, et al. Tissue lipopolysaccharidebinding protein expression in rats after thermal injury: potential role of TNF-alpha. Burns 2004;30:225.

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

31. 32.

Decker K. The response of liver macrophages to inflammatory stimulation. Keio J Med 1998;47:1. Roland CR, Goss JA, Mangino MJ, et al. Autoregulation by eicosanoids of human Kupffer cell secretory products. A study of interleukin-1, interleukin-6, tumor necrosis factor-alpha, transforming growth factor-beta, and nitric oxide. Ann Surg 1994;219: 389. Folch-Puy E, García-Movtero A, Iovanna JL, et al. The pancreatitis-associated protein induces lung inflammation in the rat through activation of TNFalpha expression in hepatocytes. J Pathol 2003;199:398. van Oosten M, van de Bilt E, de Vries HE, et al. Vascular adhesion molecule-1 and intercellular adhesion molecule-1 expression on rat liver cells after lipopolysaccharide administration in vivo. Hepatology 1995;22:1538. Croner RS, Lehmann TG, Fallsehr C, et al. C1-inhibitor reduces hepatic leukocyte-endothelial interaction and the expression of VCAM-1 in LPS-induced sepsis in the rat. Microvasc Res 2004; 67:182. Ichimura T, Bonventre JV, Bailly V, et al. Kidney injury molecule-1 (KIM-1), a putative epithelial cell adhesion molecule containing a novel immunoglobulin domain, is up-regulated in renal cells after injury. J Biol Chem 1998;273:4135. Kuehn EW, Park KM, Somlo S, et al. Kidney injury molecule-1 expression in murine polycystic kidney disease. Am J Physiol Renal Physiol 2002;283:F1326. Nagel-Wolfrum K, Buerger C, Wittig I, et al. The interaction of specific peptide aptamers with the DNA binding domain and the dimerization domain of the transcription factor Stat3 inhibits transactivation and induces apoptosis in tumor cells. Mol Cancer Res 2004;2:170. Andrejko KM, Chen J, Deutschman CS. Intrahepatic STAT-3 activation and acute phase gene expression predict outcome after CLP sepsis in the rat. Am J Physiol 1998;275:G1423. Hotchkiss RS, Tinsley KW, Hui JJ, et al. p53-dependent and -independent pathways of apoptotic cell death in sepsis. J Immunol 2000;164:3675. Carcillo JA, Doughty L, Kofos D, et al. Cytochrome P450 mediated-drug metabolism is reduced in children with sepsisinduced multiple organ failure. Intensive Care Med 2003;29: 980. Carcillo JA, Korzekwa KR, Jones GS, et al. The cytochrome P450 suicide inhibitor, 1-aminobenzotriazole, sensitizes rats to zymosan-induced toxicity. Res Commun Mol Pathol Pharmacol 1998;102:57. Falany CN, Xie X, Wheeler JB, et al. Molecular cloning and expression of rat liver bile acid CoA ligase. J Lipid Res 2002; 43:2062. Famularo G, De Simone C, Nicotra GC. Jaundice and the sepsis syndrome: a neglected link. Eur J Intern Med 2003;14:269. Svanberg E, Ohlsson C, Kimball SR, et al. rhIGF-I/IGFBP-3 complex, but not free rhIGF-I, supports muscle protein biosynthesis in rats during semistarvation. Eur J Clin Invest 2000; 30:438.