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Saudi Journal of Kidney Diseases and Transplantation
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ORIGINAL ARTICLE Table of Contents   
Year : 2008  |  Volume : 19  |  Issue : 6  |  Page : 952-959
Detection of acute renal allograft rejection by analysis of renal tissue proteomics in rat models of renal transplantation

1 The Second Clinical Medical College, Jinan University, China
2 Key Laboratory of Laboratory Medical Diagnostics, Ministry of Education, Chongqing Medical University, China
3 Shenzhen Center for Disease Control and Prevention; Shenzhen, Guangdong, R. P., China

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At present, the diagnosis of renal allograft rejection requires a renal biopsy. Clinical management of renal transplant patients would be improved if rapid, noninvasive and reliable biomarkers of rejection were available. This study is designed to determine whether such protein biomarkers can be found in renal-graft tissue proteomic approach. Orthotopic kidney transplantations were performed using Fisher (F344) or Lewis rats as donors and Lewis rats as recipients. Hence, there were two groups of renal transplant models: one is allograft (from F344 to Lewis rats); another is syngrafts (from Lewis to Lewis rats) serving as control. Renal tissues were collected 3, 7 and 14 days after transplantation. As many as 18 samples were analyzed by 2­D Electrophoresis and mass spectrometry (MALDI-TOF-TOF-MS). Eleven differentially expressed proteins were identified between groups. In conclusion, proteomic technology can detect renal tissue proteins associated with acute renal allograft rejection. Identification of these proteins as diagnostic markers for rejection in patients' urine or sera may be useful and non­invasive, and these proteins might serve as novel therapeutic targets that also help to improve the understanding of mechanism of renal rejection.

Keywords: Proteome, Acute rejection, Transplantation, Animal model, 2D-electrophoresis, MALDI-TOF-TOF-MS

How to cite this article:
Dai Y, Lv T, Wang K, Huang Y, Li D, Liu J. Detection of acute renal allograft rejection by analysis of renal tissue proteomics in rat models of renal transplantation. Saudi J Kidney Dis Transpl 2008;19:952-9

How to cite this URL:
Dai Y, Lv T, Wang K, Huang Y, Li D, Liu J. Detection of acute renal allograft rejection by analysis of renal tissue proteomics in rat models of renal transplantation. Saudi J Kidney Dis Transpl [serial online] 2008 [cited 2023 Feb 2];19:952-9. Available from: https://www.sjkdt.org/text.asp?2008/19/6/952/43471

   Introduction Top

Renal transplantation is the best renal re­placement therapy for end-stage renal disease (ESRD) patients. Rejection is still a common problem in renal transplant recipients. Acute rejection (AR) is the major immunologic risk factor for developing chronic allograft nephro­pathy. [1] Therefore, suppressing the incidence of acute allograft rejection is a major task faced by transplantation specialists all over the world. At present, the diagnosis of acute re­jection can only be made by renal biopsy, which is costly, inconvenient, and carries risks of complication. [2] Clinical management of renal transplant patients would be improved if some rapid, noninvasive and reliable methods for detecting biomarkers of rejection were avai­lable. However, biomarkers that are readily accessible and can early predict the outcome of the transplanted graft specifically and re­liably are still to be defined. [3]

To search for these biomarkers, several approaches, such as mRNA measurements in urinary lymphocytes, urine flow cytometry, and measurements of alloreactive peripheral blood lymphocytes have been attempted, but none has reached clinical application. [4] Re­cently, Sawitzki B etc. found two markers (TOAG-1, alpha-1, 2-mannosidase) expression level of which showed a strong positive corre­lation with graft function in rat and mouse models. [5] In recent years, proteomics has been applied in the search for biological markers of acute allograft rejection.

A robust effort has been employed to search for biomarkers in the urinary proteome of kidney allograft rejection. [6],[7],[8],[9],[10],[11],[12]

Despite all the achieved knowledge until now, investigators have been unable to defi­nitively differentiate rejection patients from stable transplant patients by using urine bio­markers. [13] There are limited data available on expression profiling of kidney allograft's tissue, either at the protein or at the mRNA levels. Furthermore, there are inherent pro­blems of heterogeneity and ethics in studying clinical samples, which make a clinical study nearly impossible.

This study is designed to determine whether such protein biomarkers can be found in renal­graft tissue proteomic approach. Instead of using human tissue samples, the Fisher (F344) to Lewis rat orthotopic life-supporting kidney transplantation model, which consistently de­velops AR at day 7 after transplantation, was selected for protein profiling by 2-D Electro­phoresis and mass spectrometry (MALDI­TOF-TOF-MS).

   Materials and Methods Top

Transplantation model and sampling

The study was carried out in male Fisher (RT1 1v1 ) and Lewis (RT1 1 ) obtained from Weitonglihua Company, Beijing, R. P. China, (Charles River Laboratories), in accordance with the USA law for animal protection. F344­to-Lewis life-supporting orthotopic kidney allotransplantations were performed with Lewis­to-Lewis syngeneic controls. Warm ischemia time did not exceed 40 min. Nephrectomy of the contralateral right host kidney was per­formed directly after transplantation. No immunosuppressant was administered during the post-transplantation period. The cons­truction of rat renal transplantation model was considered a success if the transplanted animal survived for at least 3 days. Parallel groups of 3 allo-and 3 syn-transplanted rats each were sacrificed on day 3, 7 and 14 after transplan­tation and grafts were excised. Parts of the grafts were processed for histopathologic analysis.

Preparation of renal tissue samples

Tissues of the renal-grafts on day 3 and 7 after transplantation were collected directly into the freezing vials, rinsed with physiologic saline, and then stored in liquid nitrogen. Samples were grinded in liquid nitrogen with lysis buffer (0.1g tissue/l mL buffer) (8M Urea, 4%CHAPS, proteinase inhibitor mix). Samples were centrifuged at 14000 rpm and 4°C for 60 min, and cleared supernatant was subsequently stored at -80°C. Extracts were then treated with 2-D Clean-Up Kit. The total protein concentration was determined using 2­D Quant kit.

2-D Electrophoresis [14]

Two-dimensional electrophoresis of the sam­ple was performed according to established procedures. For the first dimension, 120 µg protein was diluted with rehydration buffer (8 M urea, 4%CHAPS, 0.4% DTT, and 0.5% Pharmalytes 4-7 (Amersham Biosciences) to a final volume of 250 µL and loaded onto 13 cm linear IPG strips, pH 4-7 (Amersham Bio­sciences) by reswelling the strips in the buffer. Iso-electric focusing was performed on the IPGphor II apparatus (Amersham Biosciences) for approximately 50 kVh at 20 °C, using the following voltage gradient: 1) 12h 30V, 2) 1h 500V, 3) 1h 1000V, 4), 1h 8000V, 5) continue at 8000 V until target kVh. After IEF, IPG strips were equilibrated with a buffer (50 mM Tris-HCl, pH 8.8, 6 M urea, 30% glycerol, 2% SDS) containing 1% dithiothreitol for 15 min as a first step, and thereafter in the same buffer with 2.5% iodoacetamide instead of dithio­threitol for another 15 min as a second step.

For the second dimension, IPG strips were applied to 15 × 20 cm SDS-PAGE gels (12.5% T, 3% C), which were run overnight at 20 mA/gel and 17 °C in an IsoDalt electropho­resis chamber (Amersham Biosciences). Gels were fixed and stained with silver. The im­proved protocol of silver staining, compatible with mass-spectrum, was introduced into silver staining performance.

Image analysis

The analysis of the 2D gel image was performed using Imagemaster 5.0 (Amersham Biosciences). The examinations of protein spots involved quantification, background de­duction, quantitative unification and matching of spots. Differentially expressed proteins spots between syn-group and allo-group on different time point (p < 0.05 by Student's t-test) were identified.

In-Gel Trypsin Digestion and MS

The protein spots, differentially expressed, were removed and collected, representing satisfactory repetition in the gels from diffe­rent groups; washed by ex-ion water and de­colored through acid ammonium carbonate of 50 mmol plus 50% acetonitrile; treated through enzymolysis by pancreatin at 37°C and main­tained overnight after the gels were dried by pure CAN. The peptide segments were drawn through 0.1% trifluoroacetic acid plus 50% acetonitrile and dried by nitrogen gas. The loading samples were covered by 5 mg/mL substrate solution (the solution of 0.1% TFA and 50% acetonitrile) of 0.8µL. After air-dried, the samples were analyzed by peptide mapping fingerprint (PMF) and MALDI-TOF-TOF-MS, which was rectified by the inner markers, in­cluding the base peak and the inscribed pancreatin peak. The PMF maps were ob­tained through searching by GPS software and the search engine MASCOT in IPI rat data­base.

   Results Top

Histological analysis

Histological analysis of graft tissue showed minute signs of ischemic damage in the syn­geneic grafts at day 3 after transplantation but a return to normal morphology at days 7 and 14. In contrast, the histology of the allografts confirmed specific gradual infiltration of mono­nuclear cells into the allografts over the ob­servation period [Figure 1].

2D Gel analysis

The 2D pattern differences of the renal tis­sues between the allograft and syngraft group were shown in [Figure 2]. In both groups, the renal tissue protein samples were separated by 2D-PAGE. The analysis on the high-resolution areas suggested that under the same condition 2DE patterns were obtained with high-reso­lution and satisfactory-repetition after 2DE was performed 3 times in one of the samples. There were 551 ± 53 protein spots, including matching protein spots on average, identified in the day 7 of the allograft group, repre­senting an average matching rate of 73.11%; while 457 ± 49 protein spots, including mat­ching protein spots on average, were identified in the day 7 of the syngraft group, representing an average matching rate of 76.32%. The above results showed that the 2DE technique used in this study for renal tissue analysis demonstrated desirable repetition.

Mass Spectrum

An analysis by MALDI-TOF-TOF-MS was performed after the enzymolysis of the pro­tein spots in the gels. Eleven differentially expressed protein spots were identified by MS/MS between groups, [Table 1].

   Discussion Top

The results from this proteomic analysis showed a better time window (day 3, day 7 and day 14) for early marker detection than the histopathologic methods and may possibly best resemble the clinical situation.

In 1989, Lapin etc attempted to identify urinary biomarkers for acute renal allograft rejection using 2-DE analysis with differential spot patterns illustrated, but no protein spots were identified because of the limitation in protein identification at that time. [6] Later, Hampel et al [7] applied gel-based proteomic analysis to differentiate the urinary proteome of acute renal rejection from stable graft function. Using ESI-MS and MALDI-TOF MS, (32-microglobulin, retinol-binding protein, and carbonic anhydrase were identified as bio­marker candidates. To search for serum bio­markers for acute renal allograft rejection, Tomosugi et al [8] found a candidate at 11 685 m/z and identified as amyloid protein A by LC-MS/MS. Clarke et al [9] used SELDI-TOF MS to detect the urinary proteome in rejected transplants (n=17). Various peaks were found, but the authors were unable to elucidate their identity. They obtained a sensitivity of 83% and a specificity of 100% using two separate biomarker candidates at 10.0 kDa and 3.4 kDa. Later, using SELDI-TOF, O'Riordan et al [10] found three peaks with masses of 4.7, 25.6 and 19.0 kDa as being important in distinguishing patients with acute rejection (n=23) from sta­ble patients (n=22). Schaub et al [11] found three prominent peak clusters from patients in acute rejection episodes (n=18) using SELDI-TOF MS. In most patients, the presence or absence of these peak clusters was correlated with the clinicopathologic course. These proteins were later identified by mass spec-trometry [12] as being derived from non-tryptic cleaved forms of β2-microglobulin, which serves as a tertiary maker of acute tubular injury and may prove useful as part of a panel with other urine biomarkers.

In our study, orthotopic kidney transplanta­tions were performed on two groups of rat models: allograft (from F344 to Lewis) and syngraft (from Lewis to Lewis, serving as control). Renal tissues were collected 3, 7 and 14 days after transplantation and histopatho­logic difference was compared. There were 11 differentially expressed proteins identified between the 2 groups by 2-D electrophoresis and mass spectrometry (MALDI-TOF-TOF­MS).

For many researchers, there are increasing interests in the concept that the human pro­teome is likely to contain most, if not all, human proteins, and that almost any disease state causes some specific protein expression changes in human tissues or fluids. However, the serum protein levels change dramatically only at the stage where kidney function is already severely affected. At the same time, the blood proteome is arguably the most com­plex, as it absorbs proteins from every tissue in the body. However, at the renal tissue protein level, some specific protein expression changes can exactly be found before the kidney function is already severely affected. Rat's genome and proteome are 99% the same as the humans. And the use of rat model can over­come the limitation of tissue amount and avai­lability in the analysis of human renal biop­sies. Therefore, in the current study we used F344 rat and Lewis rat to model the human renal transplantation. The IPG-2D-PAGE me­thod is the classical approach in proteome researches. 2D gels provide the most comprehensive tool for profiling at the protein level, in a wide molecular weight range at the cost of somewhat elevated sample requirements.

In this study, 3 days after transplantation, the 2D gels pattern showed little changes at the protein level in the renal tissue of allograft compared to the controls, while 7 days after transplantation, the 2D gels revealed a large number of protein spot changes in the renal tissues of the allotransplanted rats compared to those of syntransplanted rats. Some of these changes were already significant at earlier stages than histopathology was able to detect. However, at those early time points, quanti­tative differences are small, not enough for an individual protein species to have practical value as a biomarker. It is still conceivable that a specific signature for acute rejection can be derived at that stage.

In our study, 11 protein points were found differentially expressed between groups. The most significant were Chain D, Rat Trans­thyretin [Figure 3], apolipoprotein A-IV and Rho GDP dissociation inhibitor (GDI) alpha. The apolipoprotein A-IV protein is associated with chylomicrons, and its synthesis by the small intestine is markedly stimulated follo­wing ingestion of fat. Some researchers indi­cated this protein was also associated with ischemic cerebrovascular disease. [15] At present, those researchers pointed out that apolipo­protein A-IV predicts progression of chronic kidney disease, [16] it may point a new direction on the renal transplantation research. Other identified proteins may also give specific signatures for acute rejection. However, 3 days after transplantation, renal tissue proteins were not found differentially expressed between groups. This may be checked out in our further studies, using western blot. On the other hand, if the proteins that we identified were also found differentially expressed in urine or serum in clinical settings of renal transplan­tation, our present study might prove to be useful. Therefore, further studies are required to solve these problems.

For diagnosis of rejection in the kidney, non­invasive means are crucial. As a noninvasive and inexpensive method, detection in the urine would be most advantageous. Several recent studies have used MS, including SELDI-MS [9],[10],[11] and capillary electrophoresis (CE)-MS [17] to identify novel proteins in urine during acute rejection. However, none of these studies reached a clinical applicable result. The rejec­tion rat model we set up can help to con­veniently conduct research in urine, sera and biopsy with stringent control.

In conclusion, we successfully set up the rat model for acute renal allograft rejection research and demonstrated that proteomic technology can detect renal tissue proteins associated with acute renal allograft rejection. Our current efforts will concentrate on the identification of these proteins for diagnostic markers for rejection in urine or sera. Our research may help to develop novel thera­ peutic targets and improve the understanding of renal rejection mechanism.

   Abbreviations Top

IPG, immobilized pH gradient; MALDL-TOF­TOF-MS, matrix assisted laser desorption ionization-time of flight mass spectrometry; PMF, peptide mapping fingerprints.

   Acknowledgment Top

Proteome Research Department of Fudan University, Shanghai, China.

   References Top

1.Meier-Kriesche HU, Ojo AO, Hanson JA, et al. Increased impact of acute rejection on chronic allograft failure in recent era. Trans­plantation 2000,70(7):1098-100.  Back to cited text no. 1    
2.Kolb LG, Velosa JA, Bergstralh EJ, Offord KP: Percutaneous renal allograft biopsy: a comparison of two needle types and analysis of risk factors. Transplantation 1994,57(12): 1742-6.  Back to cited text no. 2    
3.Susal C, Pelzl S, Simon T, Opelz G. Advances in pre and posttransplant immunologic testing in kidney transplantation. Transplant Proc 2004;36(1):29-34.  Back to cited text no. 3    
4.Gonzalez-Buitrago JM, Ferreira L, Lorenzo I. Urinary proteomics. Clin Chim Acta 2007; 375(1-2):49-56.  Back to cited text no. 4    
5.Sawitzki B, Bushell A, Steger U, et al. Identi­fication of gene markers for the prediction of allograft rejection or permanent acceptance. Am J Transplant 2007;7(5):1091-102.  Back to cited text no. 5    
6.Lapin A, Kopsa H, Smetana R, Ulrich W, Perger P, Gabl F. Modified two-dimensional electrophoresis of urinary proteins for moni­toring early stages of kidney transplantation. Transplant Proc 1989;21(1.2):1880-1.  Back to cited text no. 6    
7.Nazeer K, Arthur JM, Barber K, Swartz M, Budisavljevic MN. Detection and character­rization of glomerulonephritis associated pro­teins using a proteomics approach. J Am Soc Nephrol 2003;14(suppl):408A.  Back to cited text no. 7    
8.Tomosugi N, Yamaya H, Sato K, et al. Serum proteome profiles in acute renal allograft rejection by ProteinChip analysis. J Am Soc Nephrol 2003;14(suppl):431A.  Back to cited text no. 8    
9.Clarke W, Silverman B, Zhang Z, Chan DW, Klein AS, Molmenti EP. Characterization of renal allograft rejection by urinary proteomic analysis. Ann Surg 2003;237(5):660-5.  Back to cited text no. 9    
10.O'Riordan E, Orlova TN, Mei JJ, et al. Bioinformatic analysis of the urine proteome of acute allograft rejection. J Am Soc Nephrol 2004;15(12):3240-8.  Back to cited text no. 10    
11.Schaub S, Rush D, Wilkins J, et al. Proteomic­based detection of urine proteins associated with acute renal allograft rejection. J Am Soc Nephrol 2004;15(1):219-27.  Back to cited text no. 11    
12.Schaub S, Wilkins JA, Antonovici M, et al. Proteomic-based identification of cleaved urinary (32-microglobulin as a potential marker of acute tubular injury in renal allograft. Am J Transplant 2005;5(4.1):729-38.  Back to cited text no. 12    
13.Clarke W. Proteomic research in renal trans­plantation. Ther Drug Monit 2006;28(1):19-22.  Back to cited text no. 13    
14.Voshol H, Brendlen N, Muller D, et al. Evaluation of biomarker discovery approaches to detect protein biomarkers of acute renal allograft rejection. J Protome Res 2005;4(4): 1192- 9.  Back to cited text no. 14    
15.Ejchel TF, Araujo LM, Ramos LR, Cendoroglo MS, de Arruda Cardoso Smith M. Association of the apolipoprotein A-IV: 360 Gln/His poly­morphism with cerebrovascular disease, obe­sity, and depression in a Brazilian elderly po­pulation. Am J Med Genet B Neuropsychiatr Genet 2005;135(1):65-8.  Back to cited text no. 15    
16.Boes E, Fliser D, Ritz E, et al. Apolipoprotein A-IV predicts progression of chronic kidney disease: The mild to moderate kidney disease study. J Am Soc Nephrol 2006;17(2):528-36.  Back to cited text no. 16    
17.Wittke S, Haubitz M, Walden M, et al. Detection of acute tubulointerstitial rejection by proteomic analysis of urinary samples in renal transplant recipients. Am J Transplant 2005;5(10):2479- 88.  Back to cited text no. 17    

Correspondence Address:
Yong Dai
Shenzhen People's Hospital, 1017#, North Road, Dongmen, Shenzhen, Guangdong, 518020 R. P.
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Source of Support: None, Conflict of Interest: None

PMID: 18974583

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  [Figure 1], [Figure 2], [Figure 3]

  [Table 1]

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