Leukocyte accumulation in graft blood vessels during self-limiting acute rejection of rat kidneys

Immunobiology 216 (2011) 613–624

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Immunobiology journal homepage: www.elsevier.de/imbio

Leukocyte accumulation in graft blood vessels during self-limiting acute rejection of rat kidneys Anna Zakrzewicz a , Jochen Wilhelm b , Sonja Blöcher a , Joanna Wilczynska a , Sigrid Wilker a , Hartmut Dietrich c , Rolf Weimer c , Winfried Padberg a , Veronika Grau a,∗ a b c

Laboratory of Experimental Surgery, Department of General and Thoracic Surgery, Justus-Liebig-University, Giessen, Germany Department of Pathology, Justus-Liebig-University, Giessen, Germany Department of Internal Medicine, Justus-Liebig-University, Giessen, Germany

a r t i c l e

i n f o

Article history: Received 7 July 2010 Accepted 18 September 2010 Keywords: Renal transplantation Monocyte Blood Acute rejection Chronic rejection

a b s t r a c t During self-limiting acute rejection preceding chronic vasculopathy, large amounts of leukocytes, predominantly monocytes, interact with the endothelium of renal allografts. We aim to characterize them and to identify targets for functional and interventional studies. Leukocytes were harvested by vascular perfusion from Fischer 344 to Lewis renal allografts or Lewis isografts, followed by flow cytometry, quantitative RT-PCR and genome-wide transcriptional profiling. Leukocyte accumulation peaked in allografts on day 9. The percentage of monocytes expressing MHC class II and CD161 was increased whereas CD4, CD11a, CD43, and CD71 expression remained unchanged. IFN-␥, IL-1␤, IL-2, IL-10, TNF-␣, and iNOS mRNA increased in allograft leukocytes but IL-4, IL-6, IL-12, TGF-␤, and tissue factor did not. During acute rejection, 1783 genes were differentially expressed. In conclusion, graft blood leukocytes display a unique state of partial activation during self-limiting rejection. Numerous differentially expressed genes deserve further investigation as potential factors in deciding the fate of the allograft. © 2010 Elsevier GmbH. All rights reserved.

Introduction Spontaneous resolution of acute rejection (AR) is poorly understood, although it is an interesting paradigm for the development of immune-modulating strategies and for the understanding of the pathogenesis of chronic allograft rejection. Spontaneous acceptance of renal allografts transplanted in the Fischer 344 (F344) to Lewis (LEW) or in the F1 (F344 × LEW) to LEW rat strain combinations have been described more than four decades ago (White and Hildemann, 1968; Mahabir et al., 1969). These allografts pass through a severe AR episode and develop chronic allograft nephropathy (CAN) in the long run (White and Hildemann, 1968; Mahabir et al., 1969; Beckmann et al., 2003; Andriambeloson et al., 2004; Bedke et al., 2007; Holler et al., 2008). Strong experimental evidence suggests that chronic allograft rejection, which typically involves intimal and medial remodelling of graft arteries, is irre-

Abbreviations: AR, acute rejection; Azan, azocarmine/aniline blue; CAN, chronic allograft nephropathy; DAB, 3,3 diaminobenzidine; F344, Fischer 344; H&E, hemalum eosin; LEW, Lewis; mAb, monoclonal antibody; qRT-PCR, quantitative real-time RT-PCR; TF, tissue factor. ∗ Corresponding author at: Laboratory of Experimental Surgery, Department of General and Thoracic Surgery, Justus-Liebig-University Giessen, Rudolf-BuchheimStr. 7, D-35385 Giessen, Germany. Tel.: +49 641 99 44791; fax: +49 641 99 44769. E-mail address: [email protected] (V. Grau). 0171-2985/$ – see front matter © 2010 Elsevier GmbH. All rights reserved. doi:10.1016/j.imbio.2010.09.009

versibly triggered by AR (Tullius et al., 1998; Joosten et al., 2003; Chapman, 2005; Serón et al., 2005; Nankivell and Chapman, 2006). After clinical transplantation, AR episodes are important risk factors for the development of CAN (Aita et al., 2005; Lerut et al., 2007; Fahim et al., 2007; Gibson et al., 2008). Factors triggering CAN during AR are completely ignored but would be promising therapeutic targets to prevent CAN. Leukocytes damaging allogeneic endothelial cells have been proposed to play decisive roles in fatal AR and in chronic allograft vasculopathy (Briscoe et al., 1998; Grau et al., 2001; Vos and Briscoe, 2000; Stehling et al., 2004; Reinders et al., 2006; Cailhier et al., 2006; Al-Lamki et al., 2008). A role in the reversion of AR remains to be defined. Blood leukocytes either belong to the central pool moving with the blood stream, which is accessible to venous puncture or to the functionally more relevant marginal pool interacting with the endothelium. Leukocytes from the marginal pool can be obtained by intensive perfusion of blood vessels, an invasive approach obviously restricted to experimental animals. Conspicuous amounts of leukocytes, accumulate in the vasculature of rat renal allografts undergoing fatal AR (Grau et al., 2001; Stehling et al., 2004). Most of them are activated cytotoxic monocytes expressing pro-inflammatory cytokines (Grau et al., 2001). We recently started to investigate self-limiting AR after kidney transplantation in the F344 to LEW rat strain combination. Strikingly, 150 million blood leukocytes accumulate in the vasculature of allografts until day 9

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post-transplantation (Holler et al., 2008). In comparison, about the same number of cells are present in the entire extrapulmonary circulation of healthy LEW rats (Grau et al., 2001). Monocytes (∼70%) and T cells (∼19%) represented the most numerous intravascular cells of F344 to LEW allografts, other leukocytes accounted for less than 5% (Holler et al., 2008). The properties of these graft blood leukocytes, however, have not been investigated before. In this study, we characterise intravascular graft leukocytes accumulating during self-limiting AR in the F344 to LEW model for CAN. The expression of selected cytokines and effector molecules is analysed by quantitative real-time RT-PCR (qRT-PCR), the immune phenotype of monocytes is determined, and differential gene expression is studied by an unbiased approach. Materials and methods Animals and renal transplantation LEW (RT1l ) and F344 (RT1lv1 ) male rats from Harlan Winkelmann (Borchen, Germany) weighing 270–300 g were kept under conventional conditions. Animal care and animal experiments were performed in accordance with current German animal protection laws as well as the NIH “Principles of laboratory animal care”. For allogeneic transplantation, F344 rats served as donors and LEW rats as recipients. LEW rats were used for isogeneic transplantation and as healthy untreated controls. Animals were anaesthetised with 60 mg/kg sodium pentobarbital i.p. (Narcoren, Merial, Hallbergmoos, Germany). Kidneys were transplanted to totally nephrectomised recipients essentially as described (Fabre et al., 1971). The ureter was anastomosed endto-end. Donors received 1000 IU/kg heparin i.v. (Ratiopharm, Ulm, Germany). Recipients were given 30 ␮g ampicillin i.p. after surgery (Ratiopharm) but no immunosuppression. Warm ischemic times remained below 30 min. To assess renal function, blood samples were obtained and urine was collected for 24 h, 6 months after transplantation. Plasma and urine creatinine levels were measured by the Laboratory of Clinical Chemistry at our hospital. Perfusion of the renal vasculature and purification of mononuclear leukocytes Graft recipients and healthy control animals were anaesthetised and heparinised. Perfusion of the renal blood vessels was performed as described (Grau et al., 2001). Perfused grafts were fixed for paraffin histology and evaluated. Percoll (1.082 g/l) isopycnic density gradient centrifugation was carried out to deplete granulocytes and erythrocytes (Scriba et al., 1996). Mononuclear leukocytes were analysed by flow cytometry or snap frozen and stored at −80 ◦ C for qRT-PCR. Immunohistochemistry and histopathology Nine days or 6 months after transplantation, graft recipients were anaesthetised and sacrificed. Cryostat sections (5 or 8 ␮m) of the kidney were mounted on silane-coated glass slides, fixed for 10 min in 100% ice-cold isopropanol and air dried for 30 min at RT. Endogenous peroxidase activity was inactivated with 1% H2 O2 in PBS for 30 min at RT. To stain endothelial cells, the monoclonal antibody (mAb) HIS52 (Serotec, Düsseldorf, Germany), diluted 1:3000 in PBS, pH 7.2, 1% BSA (Serva, Heidelberg, Germany), 0.1% NaN3 (p.a. Merck, Darmstadt, Germany) (PBS/BSA/NaN3), was incubated for 1 h at RT. Primary antibodies were detected with rabbit anti-mouse immunoglobulin conjugated to horseradish peroxidase (DAKO, Hamburg, Germany) containing 5% heat inactivated normal rat serum (Harlan Winkelmann). 3,3 -Diaminobenzidine (DAB, Sigma–Aldrich, Germany) was used as a chromogen. In a second

step, mAb ED1 (Serotec) directed to a CD68-like antigen and mAb R73 (Serotec) directed to the ␣/␤TCR were diluted in PBS/BSA/NaN3 (both 1:500). Rabbit anti-mouse immunoglobulin and alkaline phosphatase anti-alkaline phosphatase (both DAKO) in combination with Fast Blue detected the second set of primary antibodies. Controls omitting both primary antibodies were included and each primary antibody was used alone. In single-staining experiments, ED1 and R73 were detected by the anti-mouse EnVisionTM peroxidase system (DAKO) and DAB, followed by a light staining with hemalum. For paraffin histopathology, kidneys were fixed in 4% buffered paraformaldehyde. Sections of 6–8 ␮m stained with hemalum eosin (H&E), acidic orcein or azocarmine/aniline blue (Azan) were evaluated with an Olympus (Hamburg, Germany) BX51 microscope and the analySIS software (Olympus). To quantify arterial remodelling, at least 10 arteries with a diameter larger than 25 ␮m were investigated per experiment. Flow cytometry Flow cytometry was performed as described (Grau et al., 2001; Blöcher et al., 2007). Briefly, FITC labelled mAbs ED9 (CD172a), Ox19 (CD5), Ox33 (CD45R, B cell specific), and 10/78 (CD161) were used to analyse the leukocyte composition. Cell surface antigen expression by monocytes was analysed in double-staining experiments. Bound mAbs were detected with a rat anti-mouse kappa-chain conjugated to PE. MAb ED9 conjugated to FITC diluted in PBS/BSA was used to identify monocytes. In the rat blood, ED9 binds to monocytes as well as to granulocytes. Therefore, granulocytes were depleted by density gradient centrifugation. Unlabelled cells, samples without primary antibodies, and two isotype control antibodies (MOPC-21, MOPC-173, Becton-Dickinson, Heidelberg, Germany) were always included. A FACS Calibur flow cytometer (Becton Dickinson) and the Cell Quest software 3.2.1 (Becton Dickinson) were used and 30000 events were measured from every sample. RNA isolation and qRT-PCR Total RNA was isolated from 5 × 106 intravascular mononuclear leukocytes from control kidneys, isografts and allografts on day 9 post-transplantation (n = 5) using the RNeasy Mini Kit (Qiagen, Hilden, Germany). 1 ␮g RNA was reversely transcribed using the MMLV H− Reverse Transcriptase and 1 ␮g random hexamer primers (Promega, Mannheim, Germany). Quantitative RT-PCR was performed in duplicates in an ABI 7700 Sequence Detection System (Applied Biosystems, Foster City, CA) using Platinum SYBR green qPCR Super Mix-UDG (Invitrogen, Karlsruhe, Germany). Primer pairs for rat porphobilinogen deaminase (PBGD), IL-1␤, IL-2, IL-4, IL-6, IL-10, IL-12p40, TNF-␣, iNOS, TGF-␤, and IFN-␥ have been published before (Hirschburger et al., 2009). Intron-spanning primers for IL-12p35, tissue factor (TF), CCR5, CD74, CXCL9, ICAM1, and RT1-Da are indicated in Table 1. Primers were synthesised by MWG Biotech (Ebersberg, Germany) and used at a concentration of 0.6 ␮M. PCR included initial denaturation for 5 min at 95 ◦ C, followed by 45 cycles of 20 s at 95 ◦ C, 20 s at 60 ◦ C, and 10 s at 72 ◦ C. To evaluate the PCR products, the melting curves were analysed and the products were separated on agarose gels. Controls omitting the RT step or replacing the template by water were performed to exclude false positive results. The data were calculated as arbitrary units by the equation 2−CT , where CT is the difference in CT values between the gene of interest and PBGD. The mean of the expression values obtained for controls was set to 1 arbitrary unit. Individual values including controls were calculated accordingly.

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Table 1 Primer sequences for qRT-PCR. Gene name (accession number)

Forward primer (5 –3 )

Reverse primer (5 –3 )

Amplicon size (bp)

CCR5 (NM 053960) CD74 (NM 013069) CXCL9 (NM 145672) ICAM1 (NM 012967) IL-12p35 (NM 053390) RT1-Da (NM 001008847) TF (NM 013057)

GAA GGT GAG ACA TCC GTT CC GGG GGA AAA GCT AGA GGC TA CCA AGG CAC ATT CCA CTA CA CTG GTC CTC CAA TGG CTT C TCA GAG CCA CAA TCA TCA GC AAG AAA ATG GCC ACA CTT ACA ATC TTG GAG TGG CAA CC

GGC TGC AAT TTG TTT CAC AT GCC ACC AGG ACA GAG ACA CT TCA GCT TCT TCA CCC TTG CT GTG GGA TGG ATG GAT ACC TG GGA GCT TTC TGG TGC AGA GT CGG GGG AAA GAT AGA ACT CC ACA ATC TCG TCG GTG AGG TC

143 150 128 111 110 129 131

Microarrays Total RNA (40–50 ␮g) was incubated at 65 ◦ C with 1.5 ␮g oligodT (15–20) primers, at 20 ◦ C and on ice for 10 min each. Reverse transcription was performed in 40 ␮l Superscript II reaction buffer (Superscript II kit, Invitrogen, Karlsruhe, Germany) containing 0.5 mM dATP, dTTP, and dGTP, 0.2 mM dCTP, 0.1 mM Cy-dCTP (PerkinElmer, Waltham, USA), 10 mM DTT, and 300 U Superscript II at 39 ◦ C for 180 min, terminated by adding 10 ␮l 1 M NaOH and heating to 65 ◦ C, and neutralised with 10 ␮l 1 M HCl and 200 ␮l TE buffer. Labelled cDNA was purified using the PCR Purification Kit (Qiagen) and eluted in 50 ␮l water. Yield, purity and labelling efficiency were checked by an OD spectrum between 220 and 750 nm. Hybridisation was performed at 60 ◦ C over-night on Agilent G4131A rat whole genome microarrays (Agilent Technologies, Böblingen, Germany) as indicated by the supplier, scanned with the Genepix A4100 (MDS Analytical Technologies, Ismaning, Germany) scanner and analysed with GenePix software V5.0 (MDS). Statistics

was further investigated. The cellular composition of intravascular graft leukocytes from day 9 isografts, allografts and untreated control kidneys was published before (Grau et al., 2001; Holler et al., 2008). Graft histopathology corroborated data on F344 to LEW renal allografts on day 10 after transplantation (Bedke et al., 2007). Graft infiltration by macrophages and T lymphocytes reached a plateau level from days 9 to 20 resembling fatal AR (Grau et al., 1998). Thereafter, the infiltrate gradually decreased but was still obvious on day 47. Localisation of blood leukocytes in renal transplants on day 9 Next, we set out to investigate in which parts of the vascular bed leukocytes accumulate during self-limiting AR. Monocytes and T cells accumulated in all parts of the vascular bed including arteries (Fig. 2A), capillaries, venules (Fig. 2B and C) and veins (Fig. 2D). Cells located in direct vicinity to the endothelium, but also in the centre of veins (Fig. 2D). As expected, monocytes were more numerous than T cells and leukocytes were most abundant in allografts (Fig. 2).

Results are reported as means ± SD, presented in box plots and analysed by the Kruskal–Wallis test followed by the Mann–Whitney rank sum test (SPSS software, Munich, Germany) with p ≤ 0.05 set as the level of significance. Microarrays were analysed with R (R Development Core Team, 2009) using the limma package (Smyth, 2004). Intensity values from replicate spots were averaged. Data were corrected for local background using the rma algorithm and loess normalised before averaging. Gene set enrichment analysis (GSEA, using geneSetTest from limma) and over-representation analysis (ORA, using Fisher’s exact test) were performed based on the KEGG GENOME data (ftp://ftp.genome.jp/pub/kegg/genomes) from September 2nd 2008. Pathways with less than 3 known genes spotted were not analysed. The microarray data are available at the GEO database (http://www.ncbi.nlm.nih.gov/geo/, accession number: GSE18266). Results Intravascular leukocyte accumulation during self-limiting acute rejection Pilot experiments were performed to estimate the time course of leukocyte accumulation in the vasculature of renal allografts (Fig. 1A). Intravascular leukocytes, obtained by intensive perfusion of allograft blood vessels, increased in number until day 9, decreased thereafter, but remained elevated at least until day 47. Monocytes were the most numerous cells at each time point (>60%), followed by T, B, NK cells, and granulocytes (Fig. 1A). Until day 9, the proportion of allograft monocytes expressing MHC class II antigens and CD161 was high and dropped thereafter. In contrast, the proportion of CD43-expressing monocytes was about 60% on day 7 post-transplantation and increased thereafter (Fig. 1B). As intravascular leukocytes were most numerous at day 9, this time point

Fig. 1. Time course of leukocyte accumulation in graft blood vessels after allogeneic (F344 to LEW) renal transplantation. At different time points after transplantation, intravascular graft leukocytes were isolated by intensive perfusion of graft blood vessels and the cellular composition was analysed by flow cytometry (A). The expression of the cell surface molecules MHC class II, CD43, and CD161 by monocytes was analysed by two-colour flow cytometry of mononuclear leukocytes purified from the graft perfusates (B).

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Fig. 2. Immunohistochemical detection of monocytes/macrophages and endothelial cells in renal Lewis to Lewis isografts and Fischer 344 to Lewis allografts during an acute rejection episode 9 days after transplantation. Frozen sections (5 ␮m) were stained in brown with antibodies directed to RECA-1 to visualise vascular endothelial cells and in blue with monoclonal antibody ED1 to detect monocytes/macrophages. The arrows are pointing to intravascular monocytes. Monocytes accumulate in allograft arteries of the muscular type (A), in arterioles of glomeruli (B), in capillaries and venules (C) and in veins (D). In addition, infiltrating macrophages are abundant in allograft sections.

Phenotype of intravascular graft monocytes on day 9 Physical parameters and the expression of cell surface markers, known to be differentially regulated by monocytes (Grau et al., 2000; Steiniger et al., 2001), were analysed by flow cytometry. Cell

size and granularity were increased in allograft monocytes (Fig. 3A). The proportion of monocytes expressing CD161 (p ≤ 0.01) and MHC class II antigens (p ≤ 0.01) was higher in allografts. No changes were seen in the expression of CD4, CD8, CD11a, CD18, CD43, and CD71 (Fig. 3B and Table 2).

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Fig. 3. (A) Size (forward scatter, FSC) and granularity (side scatter, SSC) of ED9 positive Percoll-purified monocytes isolated from renal Lewis to Lewis isografts and Fischer 344 to Lewis allografts on day 9 after transplantation. Linear scales are used. (B) Cell surface expression of activation markers by mononuclear leukocytes isolated from renal isografts (Lewis to Lewis) and allografts (Fischer 344 to Lewis) on day 9 post-transplantation. Indirect staining for MHC class II antigens, CD4, CD11a, CD43, CD71, or CD161 (y axis), and direct staining with mAb ED9 (x-axis) to identify monocytes. Quadrants indicate thresholds for positive staining. Dot plots show single representative animals out of n ≥ 5.

Cytokine, iNOS and TF mRNA expression on day 9 The mRNA expression of pro- and anti-inflammatory cytokines, iNOS and TF by mononuclear leukocytes isolated from the blood vessels of isografts and allografts was analysed by qRT-PCR. PCR products resulted in a single band of the expected length. No DNA

was amplified in negative controls. IFN-␥, IL-2, IL-10, and TNF-␣ were more strongly expressed by allograft leukocytes compared to isografts (p ≤ 0.05, Fig. 4A). No changes were seen in the mRNA expression of IL-4, IL-6, IL-12p35, IL-12p40, TGF-␤, and tissue factor (Fig. 4A). When comparing allograft to isograft leukocytes, only a tendency (p ≤ 0.1) towards increased IL-1␤ expression was seen.

Table 2 Expression of MHC II, CD4, CD8, CD11a, CD18, CD43, and CD161 molecules by Percoll-purified ED9pos monocytes isolated from renal isografts (n = 6) and allografts (n = 5). For CD11a, CD18, CD43, and CD161, only cells exhibiting strong expression are included. Cell surface antigen expression was determined by flow cytometry. mAb

MHC II (%) Ox3

MHC II (%) Ox6

CD4 (%) W3/25

CD8 (%) Ox8

CD11a (%) WT.1

CD18 (%) WT.3

CD43 (%) W3/13

CD71%) Ox26

CD161 10/78

Isograft Allograft

17.6 ± 4.6 57.4 ± 11.1**

6.4 ± 2.5 19.0 ± 7.0**

90.1 ± 2.6 87.9 ± 7.2

25.6 ± 11.4 33.6 ± 7.4

89.6 ± 5.6 82.1 ± 8.1

83.4 ± 5.5 87.5 ± 9.5

66.9 ± 8.7 73.3 ± 10.4

12.4 ± 6.1 10.3 ± 6.4

67.6 ± 2.9 92.7 ± 1.7**

The data are expressed as means ± SD. ** p < 0.01, significant difference between isograft and allograft.

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Fig. 4. (A) Quantitative RT-PCR analysis of mRNA expression by intravascular leukocytes isolated from Lewis control kidneys, renal Lewis to Lewis isografts and Fischer 344 to Lewis allografts on day 9 after transplantation (n = 5 each). Data are expressed as arbitrary units which are normalised to one unit in controls. (B) Differential expression of selected genes detected by microarray technology was corroborated by qRT-PCR. The mRNA expression of CCR5, CD74, CXCL9, ICAM1 and RT1Da is analysed in intravascular leukocytes isolated from Lewis control kidneys, renal Lewis to Lewis isografts and Fischer 344 to Lewis allografts on day 9 after transplantation (n = 5 each). Data are expressed as arbitrary units which are normalised to one unit in controls. The box plots indicate median and percentiles 0, 25, 75 and 100; circles indicate data beyond 3 × standard deviation; *p ≤ 0.05.

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Table 3 Transcriptional profiling was performed on rat whole genome microarrays using RNA from mononuclear leukocytes isolated from day 9 isografts and allografts (n = 5). Candidates were selected at a 1% false-discovery rate. Probe ID

Symbol

Genbank accession

A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A

Cxcl10 Cxcl9 Cnn3 Hk3 Cxcl11 Fabp5 Vcam1

NM NM NM NM NM NM NM

Ubd Slc27a2 RGD1563454 C2 Xcl1 BC098786 Pbef1

NM 053299 NM 031736 XM 224476 NM 172222 NM 134361

C1qa Cfb Tgm2 Mmp14 Lag3 RGD1309798 Anxa3 Anxa3 NA Serping1 Txn1 Sgk

NM 001008515 NM 212466 NM 019386 NM 031056 NM 212513 XM 235463 NM 012823 NM 012823

Gbp2 Ccr5 Slc2a6 Cp Gbp4 Psen2

NM 133624 NM 053960 XM 238321 NM 012532 XM 227762 NM 031087 XM 231258 NM 019262 NM 031647 XM 001070959 NM 032612

44 44 44 44 44 44 42 44 42 44 44 44 43 44 42 44 44 44 44 43 44 44 44 44 44 42 42 44 44 44 44 42 44 44 42 44 42 42 43 44 44 44 43 44 44 44 44 42 44 44 44 43 44 44 44 44 44 42 44 44 43 44 44 43 44 44 44 43 44 44 44 44 44 44 44

P1039128 P1043157 P1029956 P114207 P175495 P362981 P499158 P901471 P602724 P997755 P433668 P332606 P13246 P623330 P570241 P918566 P487761 P419064 P1007347 P14927 P438013 P267706 P325508 P301936 P853254 P510386 P689013 P313542 P607386 P1053321 P113974 P472133 P404836 P257893 P466272 P326133 P781919 P465408 P21714 P164512 P150017 P334922 P16707 P450786 P174992 P139749 P527480 P673011 P822749 P993027 P824706 P14115 P199187 P306602 P301963 P158837 P372254 P666951 P305689 P451916 P16921 P549494 P367688 P10593 P130513 P1054883 P1028549 P13622 P130516 P704262 P210921 P102962 P368320 P194167 P325766

C1qb Sfmbt1 LOC684555 Stat1 LOC503164 Tfec Ccl6

139089 145672 019359 022179 182952 145878 012889

NM 177928

NM 199093 NM 053800 NM 019232

Ifi47 Hrasls3 Ccna2 LOC299339

XM 342644 NM 001004202 AW917984 NM 172019 NM 017060 NM 053702 XM 216791

Hrasls3

NM 017060

Lap3 MGC108823 Irf1 Psmb9

NM NM NM NM

001011910 001012353 012591 012708

Slpi Tnfrsf5 Lap3 Tap1 Lap3 Cd74 RT1-Da Stat1 RT1-Db1 AY011335 Casp4 Pddc1 RT1-Db1

NM NM NM NM NM NM NM NM NM

053372 134360 001011910 032055 001011910 013069 001008847 032612 001008884

LOC291758 LOC500591 RT1-Ba Icos

NM 053736 XM 219483 NM 001008884 XM 345084 XM 001054025 XM 001076183 NM 022610

Coefficienta 4.658 4.08 3.379 3.298 3.184 3.156 3.036 2.925 2.913 2.911 2.85 2.797 2.732 2.73 2.698 2.592 2.592 2.581 2.573 2.54 2.48 2.415 2.411 2.382 2.163 2.16 2.157 2.149 2.119 2.093 2.069 2.014 2.007 1.977 1.905 1.891 1.867 1.856 1.852 1.842 1.794 1.784 1.781 1.765 1.731 1.719 1.713 1.694 1.693 1.692 1.663 1.645 1.642 1.642 1.633 1.614 1.589 1.571 1.554 1.548 1.519 1.508 1.502 1.476 1.464 1.444 1.431 1.425 1.411 1.38 1.38 1.322 1.297 1.277 1.276

Semb

p valuec

Adjusted p valued

0.3904 0.1524 0.1919 0.1888 0.221 0.1886 0.3214 0.2037 0.1808 0.1348 0.193 0.2003 0.2538 0.3155 0.2662 0.1678 0.1509 0.2855 0.1426 0.1815 0.1601 0.1958 0.1574 0.2392 0.2526 0.1063 0.2034 0.2527 0.2563 0.2332 0.101 0.175 0.1711 0.1874 0.1152 0.2284 0.1715 0.074 0.1688 0.1341 0.0935 0.1761 0.0743 0.1383 0.1167 0.112 0.1372 0.1596 0.1888 0.0861 0.118 0.1241 0.1311 0.1666 0.1066 0.1339 0.1203 0.1487 0.1021 0.1431 0.0904 0.0938 0.1489 0.1197 0.1113 0.0589 0.1251 0.1083 0.1284 0.0923 0.109 0.1062 0.071 0.069 0.0982

1.13E−06 2.65E−08 2.50E−07 2.77E−07 7.21E−07 3.76E−07 7.06E−06 8.99E−07 5.55E−07 1.94E−07 8.51E−07 1.14E−06 4.14E−06 1.32E−05 5.76E−06 9.36E−07 6.37E−07 1.12E−05 5.55E−07 1.47E−06 1.07E−06 2.88E−06 1.23E−06 7.92E−06 1.99E−05 8.43E−07 7.38E−06 2.09E−05 2.47E−05 1.70E−05 1.02E−06 6.37E−06 5.98E−06 9.49E−06 2.45E−06 3.04E−05 9.91E−06 1.29E−06 9.84E−06 4.70E−06 2.37E−06 1.49E−05 1.72E−06 6.94E−06 4.93E−06 4.67E−06 8.30E−06 1.48E−05 2.80E−05 3.06E−06 6.66E−06 8.19E−06 9.68E−06 2.12E−05 5.93E−06 1.16E−05 9.59E−06 1.93E−05 7.60E−06 1.88E−05 7.01E−06 7.87E−06 2.63E−05 1.56E−05 1.38E−05 5.71E−06 2.17E−05 1.56E−05 2.56E−05 1.40E−05 1.97E−05 2.47E−05 1.44E−05 1.56E−05 2.67E−05

0.002576 0.001075 0.002576 0.002576 0.002576 0.002576 0.005299 0.002576 0.002576 0.002576 0.002576 0.002576 0.004811 0.00662 0.005299 0.002576 0.002576 0.006071 0.002576 0.002844 0.002576 0.004009 0.002612 0.005299 0.007789 0.002576 0.005299 0.008093 0.008541 0.007314 0.002576 0.005299 0.005299 0.005713 0.00376 0.009816 0.005713 0.002612 0.005713 0.005028 0.00376 0.006821 0.003181 0.005299 0.005029 0.005028 0.00535 0.006815 0.009181 0.004009 0.005299 0.00535 0.005713 0.008128 0.005299 0.006071 0.005713 0.007789 0.005299 0.007789 0.005299 0.005299 0.008889 0.006885 0.006688 0.005299 0.008194 0.006885 0.008739 0.006688 0.007789 0.008541 0.006793 0.006885 0.00897

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Table 3 (Continued ) Probe ID

Symbol

Genbank accession

Coefficienta

Semb

p valuec

Adjusted p valued

A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A A

RT1-N1 Hif1a RT1-Bb Klrk1

NM NM NM NM

Xlkd1 Olr87 Hp F2rl2 Bnip3l Fn1 Fn1 RGD1306812 DN934259 Exosc2 Nckap1 Pla2g2a Gfi1b RGD1563945 Npy Rnf11 LOC683960 Clu Klf1

XM 219001 NM 001000543 NM 012582 NM 053313 NM 080888 NM 019143 NM 019143 XM 215580

1.274 1.231 1.222 1.182 −1.156 −1.201 −1.248 −1.452 −1.467 −1.584 −1.649 −1.662 −1.667 −1.696 −1.706 −1.721 −1.922 −1.937 −1.94 −1.941 −1.976 −2.149 −2.166 −2.194 −2.251 −2.292 −2.363 −2.472 −2.583 −2.623 −2.652 −2.665 −2.681 −2.713 −2.713 −2.861 −2.88 −2.991 −3.004 −3.013 −3.038 −3.075 −3.097 −3.172 −3.199 −3.363 −3.495 −3.521 −3.607 −3.621 −3.846

0.0878 0.0443 0.0789 0.0634 0.063 0.0571 0.0859 0.0684 0.1289 0.1427 0.0754 0.1212 0.0957 0.1513 0.1339 0.1832 0.1598 0.2199 0.1974 0.1908 0.2187 0.2121 0.2702 0.2042 0.2778 0.2017 0.2601 0.2003 0.3424 0.3149 0.2891 0.2379 0.2709 0.3334 0.23 0.2794 0.3273 0.378 0.3227 0.2626 0.3419 0.2003 0.4026 0.2688 0.3054 0.3957 0.3801 0.3175 0.4809 0.426 0.4774

2.21E−05 1.40E−05 2.48E−05 2.39E−05 2.76E−05 1.96E−05 2.45E−05 6.38E−06 1.99E−05 1.60E−05 2.99E−06 7.19E−06 4.10E−06 1.22E−05 7.96E−06 2.22E−05 6.24E−06 2.18E−05 1.34E−05 1.16E−05 1.86E−05 9.12E−06 2.77E−05 6.69E−06 2.47E−05 4.70E−06 1.27E−05 2.70E−06 3.01E−05 1.71E−05 9.98E−06 3.57E−06 6.59E−06 1.87E−05 1.06E−05 4.95E−06 1.12E−05 1.97E−05 7.77E−06 2.50E−06 9.97E−06 5.86E−07 2.25E−05 1.98E−06 3.71E−06 1.17E−05 7.06E−06 2.37E−06 2.35E−05 1.09E−05 1.46E−05

0.008195 0.006688 0.008541 0.008541 0.009145 0.007789 0.008541 0.005299 0.007789 0.00698 0.004009 0.005299 0.004811 0.006248 0.005299 0.008195 0.005299 0.008194 0.006641 0.006071 0.007789 0.005713 0.009145 0.005299 0.008541 0.005028 0.006448 0.003918 0.009791 0.007314 0.005713 0.004526 0.005299 0.007789 0.005965 0.005029 0.006071 0.007789 0.005299 0.00376 0.005713 0.002576 0.008251 0.00349 0.004569 0.006071 0.005299 0.00376 0.008517 0.006071 0.006793

44 44 44 44 44 44 44 44 44 43 44 44 44 44 44 42 44 44 44 42 44 44 44 44 44 44 42 44 44 42 44 42 43 43 44 43 44 44 42 44 44 42 44 44 44 42 43 43 44 44 44

P379367 P397495 P500803 P238270 P331102 P588315 P487049 P388673 P306344 P13090 P681660 P210568 P461383 P592538 P283835 P788030 P247081 P532165 P457260 P771373 P733362 P714446 P311126 P217964 P373295 P440219 P631493 P184817 P367726 P559085 P306586 P534172 P11812 P17008 P289637 P19494 P541461 P798023 P576953 P151459 P139956 P508984 P953483 P869774 P196172 P545943 P17329 P10468 P481381 P804460 P306307

Alox15b Csda Selenbp1 Hbld2 Sos2 Hbe2 Cd52 Bgn Bpgm Slc4a1 LOC688972 Alas2 RGD1565175 Pspla1 Gp1bb MGC72973 Cxcl4 Kcnq5 RGD1563517 Best5 Ca2 Myl9 Add2 BF542359 Hbb

012646 024359 001004084 133512

XM 345336 XM 001067975 NM 031598 XM 234528 NM 012614 XM 237327 XM 001068230 NM 053021 XM 222473 BF557098 NM 153301 NM 031979 NM 080892 NM 181626 XM 001080400 NM 001024805 NM 053983 NM 017087 NM 199382 NM 012651 XM 001069014 NM 013197 XM 576511 NM 138882 NM 053930 NM 198776 NM 001007729 XM 575687 NM 138881 NM 019291 XM 001067182 NM 012491 NM 033234

Sorted by decreasing coefficients. a Average log2 ratio (allograft vs. isograft) of normalised signals. b Standard error of the coefficients. c Raw p-value from moderated t-test. d Benamini–Hochberg adjusted p-values (empirical false-discovery rate).

Table 4 Over-representation analysis of a whole genome transcriptional profiling of mononuclear leukocytes isolated from the blood vessels of renal isografts vs. allografts, based on a selection with a 5% false-discovery rate (722 genes). IDa

Name

Odds ratiob

p-Valuec

Adjusted p-valued

05322 05330 05332 04940 04612 05320 04620

Systemic lupus erythematosus Allograft rejection Graft-versus-host disease Type I diabetes mellitus Antigen processing and presentation Autoimmune thyroid disease Toll-like receptor signalling pathway

9.267 11.74 12.76 10.48 6.827 8.697 4.894

<0.0001 0.0001 0.0001 0.0002 0.0013 0.0018 0.0050

0.003 0.003 0.003 0.004 0.019 0.021 0.050

a b c d

KEGG pathway ID. Odds ratio from Fisher’s exact test. Raw p-value from Fisher’s exact test. Benamini–Hochberg adjusted p-values (empirical false-discovery rate).

A. Zakrzewicz et al. / Immunobiology 216 (2011) 613–624

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Fig. 5. Characterisation of the Fischer 344 to Lewis model for chronic renal allograft rejection 6 months after transplantation. Allograft recipients (n = 4) are compared to isograft recipients (n = 4) and to normal healthy Lewis rats (n = 5). (A) Creatinine clearance was determined by measuring blood plasma and urine collected for 24 h. (B) The percentage of graft arteries with intimal hyperplasia was determined. (C) To measure relative arterial thickness, the inner diameter of arterial structures surrounded by the external elastic lamina, including Tunica (T.) media, T. intima and lumen was divided by the diameter of the vascular lumen. (B and C) Paraffin sections of normal kidneys and grafts stained with acidic orcein were used. (D) The thickness of the Tunica adventitia was measured on sections stained with azocarmine/aniline blue. From the outer arterial diameter (including the T. adventitia, media, intima and lumen) the inner arterial diameter was subtracted. This value was subsequently divided by the inner diameter. (B–D) Only perpendicular cross-sections of arteries of the muscular type were included and at least 10 arteries were evaluated per experimental animal. Data are displayed as median (bar), 25–75 percentiles (box) and highest and lowest data point (whiskers). (E–G) Histopathology of the renal cortex of Lewis to Lewis isografts and Fischer 344 to Lewis allografts 6 months after transplantation. Paraffin sections (4–6 ␮m) were stained with H&E (E), azocarmine/aniline blue (F) or acidic orcein (G). Mononuclear infiltrates (E–G), vascular remodelling (G), glomerular damage (E and F), tubular atrophy (E and F) and generalised fibrosis (F) are seen in allogeneic but not in isogeneic kidneys. The arrows (G) are pointing to arteries of the muscular type.

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Fig. 6. Infiltration of renal isografts (LEW to LEW) and allografts (F344 to LEW) by monocytes/macrophages and T cells. Imunohistochemistry using antibodies to a CD68-like antigen (macrophages, A) and the ␤-chain of the ␣/␤ T cell receptor (T lymphocytes, B) was performed on serial sections of renal isografts, and allografts 6 months posttransplantation. Immunopositive structures are stained in brown and the sections were lightly counter-stained with hemalum. Arrows are pointing to small arteries. Data are representative of at least three independent experiments.

Transcriptome analysis Whole genome microarrays were performed using RNA extracted from mononuclear leukocytes harvested at day 9 from isografts and allografts (n = 5 each). At a false-discovery rate of 1%, 79 spots showed stronger signals in allografts vs. isografts, 47 spots showed weaker signals. Of those spots, 10 had no further annotation. The remaining spots corresponded to 109 different genes or chromosomal locations (65 up, 44 down in allograft vs. isograft) (Table 3). At a false discovery rate of 5%, 471 spots showed stronger and 372 spots weaker signals in isografts vs. allografts, including 69 non-annotated probes and 722 genes or chromosomal regions (394 up and 328 down). Results of the over-representation analysis on KEGG pathways are shown in Table 4. The results of the gene set enrichment analysis were similar with the exception that pathways related to energy and nucleic acid metabolism were ranked higher than by ORA (data not shown). To evaluate the reliability of the results, the mRNA expression of selected differentially expressed genes was investigated by qRT-PCR. We selected CCR5, CD74, CXCL9, ICAM1, and RT1-Da and unambiguously corroborated their increased expression (Fig. 4B). Chronic rejection after renal transplantation in the F344 to LEW strain combination To corroborate published data that the F344 to LEW is a model for CAN (Beckmann et al., 2003; Andriambeloson et al., 2004), creatinine clearance and histopathology of renal isografts and allografts were investigated 6 months after transplantation (n = 4 each). In isograft recipients, creatinine clearance was superior to allograft recipients (n = 4 each, p ≤ 0.05, Fig. 5A). Arterial remodelling was prominent in allografts (Fig. 5B, C, D, and G) and comprised the entire vessel wall. Intimal hyperplasia was more frequent (p ≤ 0.05) in allograft arteries compared to isografts (Fig. 5B). The ratio of the arterial diameter surrounded by the external elastic lamina (Tunica

media and intima) and the lumen, was increased (p ≤ 0.05, Fig. 4C). Only allograft arteries were surrounded by an enlarged adventitia composed of dense fibrous material (p ≤ 0.05, Fig. 5C). Macrophage and T cell infiltrates were mainly detected in the fibrotic adventitia of some blood vessels and occasionally expanded to the renal interstitium (Figs. 5E and 6). In addition, glomerular damage, tubular atrophy and generalised fibrosis were obvious (Fig. 5E and F). Discussion Our most important findings are: (1) monocytes strongly accumulate during self-limiting AR in the vascular bed of allografts including arteries and display a unique partially activated phenotype. (2) Intravascular allograft leukocytes express increased cytokine mRNA levels typical for Th1 cells, but IL-6 and IL12, typical for classically activated monocytes/macrophages, do not increase during AR. (3) Furthermore, we demonstrate that numerous genes are differentially expressed by intravascular graft leukocytes during AR. Vigorous but self-limiting AR occurs in this model and monocytes and T cells accumulate in the vascular bed of allografts until day 9. Between days 9 and 16 after transplantation, the cell number drops to a plateau level of ∼50 million cells corresponding to an approximately tenfold increase compared to levels found in healthy kidneys (Grau et al., 2001). Hence, leukocyte accumulation in the blood vessels of renal allografts is conspicuous and long-lasting. In this study we focussed on day 9 post-transplantation, when AR peaked and reverted. A prerequisite for a possible role of blood leukocytes in the pathogenesis of allograft vasculopathy is their accumulation in graft arteries, which was clearly demonstrated. Monocyte activation is mirrored by changes in the expression of several cell surface antigens (Grau et al., 2000; Steiniger et al., 2001). Resting monocytes are typically MHCIIneg /CD71neg /CD161neg /CD4pos /CD11ahigh /CD18high /CD43high and monocytes from rats activated by infusion of IFN-

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␥ or vigorous fatal AR are MHCIIpos /CD71pos /CD161pos / CD4neg /CD11alow /CD18low /CD43low . During self-limiting AR, the proportion of CD161pos and MHCIIpos monocytes increased, indicating monocyte activation. However, only minor changes are seen in the expression of other antigens, suggesting an intermediate state of activation. In line with a Th1-type immune reaction, IFN-␥, IL-1␤, IL-2, TNF-␣, and iNOS mRNA are more strongly expressed by allograft blood leukocytes. However, IL-6 and IL-12, typical for classically activated macrophages, remain at control levels. Moreover, the anti-inflammatory cytokine IL-10 but not TGF-␤ is induced. These results again suggest an intermediate state of monocyte activation similar to monocytes from lung allografts undergoing fatal AR (Blöcher et al., 2007). These unusual monocytes may play a role both in reverting AR and in triggering CAN. In search of potential factors involved in the resolution of AR and in triggering allograft vasculopathy, the transcriptome of allograft leukocytes was compared to isograft leukocytes. In accordance with monocyte activation, gene clusters involved in oxidative phosphorylation, in antigen processing, antigen presentation, and Toll-like receptor signalling are differentially expressed. The pattern of gene regulation resembles pathways of allograft rejection and related diseases. Selected microarray data were corroborated by qRT-PCR. MHC class II invariant chain (CD74) and RT1-Da were chosen because increased MHC class II antigen expression is a hallmark of monocyte activation. ICAM1 is involved in cell adhesion and antigen presentation (Lebedeva et al., 2005). Finally, CCR5 and CXCL9 are known to contribute to the pathogenesis of chronic allograft rejection (Yun et al., 2002; Schnickel et al., 2008). In addition, numerous unpredicted results were obtained. The role of some of them is currently under investigation in our laboratory. Among them is Neuropeptide Y, which to our surprise was abundantly expressed and strongly down-regulated during AR (Holler et al., 2008). Contradictory results have been published on the outcome of renal allografts transplanted in the F344 to LEW rat strain combination in the absence of immunosuppression. Self-limiting acute rejection followed by the development of chronic rejection was observed by some authors (Andriambeloson et al., 2004; Beckmann et al., 2003; Bedke et al., 2007; Holler et al., 2008). In contrast, fatal acute kidney rejection was also reported for the same strain combination, which can be prevented by sub-optimal immunosuppression (Pan et al., 2003; Paul, 1995). We clearly confirmed the development of self-limiting AR preceding CAN in this model. Around day 9, AR develops in allografts but not in isografts involving severe mononuclear graft infiltration and intravascular accumulation of mononuclear leukocytes. Typical aspects of CAN are obvious 6 months after allogeneic transplantation: allograft but not isograft function is impaired and allograft arteries are severely remodelled. In addition, glomerular damage, tubular atrophy, generalised fibrosis, and patchy mononuclear infiltrates are seen in allografts. In conclusion, this study demonstrates that leukocytes accumulating in the blood vessels of renal allografts undergoing self-limiting AR are dominated by monocytes, which exhibit a partially activated immunophenotype and express an unusual cytokine pattern. Transcriptional profiling revealed numerous differentially expressed genes, which deserve further investigation to define their roles in the resolution of AR and in the pathogenesis of chronic rejection.

Acknowledgments We are grateful to Sandra Iffländer, who cared for the experimental animals and for the experimental technical assistance of Petra Freitag, Gabriele Fuchs-Moll, Kathrin Petri, and Renate Plass.

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We thank Ulrike Berges for help with the art work and Mary Kromeier for correcting our English. This study was supported by a research grant from the University Medical Center Giessen and Marburg and by a grant from the German Research Foundation (FE 287/6-1).

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