- Email: [email protected]
Expression Profile of MicroRNA Biogenesis Components in Renal Transplant Patients
Expression Profile of MicroRNA Biogenesis Components in Renal Transplant Patients E. Celena, M.G. Ertosuna, H. Kocakb, A. Dinckanc, and B. Yoldasa,* a Department of Medical Biology and Genetics, Faculty of Medicine, Akdeniz University, Antalya, Turkey;bDepartment of Internal Medicine, Division of Nephrology, Faculty of Medicine, Akdeniz University, Antalya, Turkey; and cDepartment of General Surgery, Faculty of Medicine, _Istanbul Yeni Yüzyıl University, _Istanbul, Turkey
ABSTRACT Background. MicroRNAs (miRNAs) and the miRNA biogenesis components are potential biomarkers of some prevalent diseases, such as cancer and diabetes. In light of this information, we aimed to investigate the expression profiles of miRNA biogenesis components in renal transplant patients before and after transplantation and how these profiles are related to immunosuppressive treatment and clinical outcomes of these patients. Methods. In this study, gene and protein expression profiles of Dicer, Drosha, Pasha (DGCR8), Exportin5 (XPO5), and Argonaute2 (AGO2) in peripheral blood mononuclear cells (PBMCs) of renal transplant patients were evaluated by means of real-time quantitative polymerase chain reaction and Western blot methods before and 3 months after transplantation. Patients who had transplant procedures for the first time were included in the study. Results. Gene expressions were significantly reduced after transplantation. The reduction rate of expressions in 1 patient undergoing chronic rejection was higher. In addition, in patients under everolimus treatment, gene expression of Dicer did not change and gene expression of AGO2 increased. Dicer, Drosha, DGCR8, and AGO2 protein expressions were reduced in all patients, but no change was observed in XPO5 protein expression in nonrejecting patients. Interestingly, in the patient undergoing chronic rejection, protein expression profiles other than Dicer were distinctive from nonrejecting patients. However, XPO5 protein expression was higher in that patient. Conclusions. Our study shows the importance of the global effect of immunosuppressive treatment on the miRNA biogenesis pathway. miRNA biogenesis components are potential biomarkers indicative of graft outcome and pharmacologic target molecules.
A
LLOGRAFT functions, clinical progress, and rational use of immunosuppressive drugs are important issues for transplantation. For this reason, recent studies have focused on effective biomarkers that can enable efficient monitoring of pre- and post-transplantation prognosis and immune response to allograft [1]. MicroRNAs (miRNAs) have great impact on medical research owing to their potential of being biomarkers for diagnosis and prognosis of many diseases. miRNAs are small evolutionary conserved noncoding RNA molecules that influence diverse biologic mechanisms, such as cell cycle, inflammation, apoptosis, and 0041-1345/17 http://dx.doi.org/10.1016/j.transproceed.2017.01.019
472
Funding: Akdeniz University Scientific Research Coordination Unit, Turkey (grant 2014.02.0122.006). Presented to Akdeniz University Health Sciences Institute as E. Celen’s MSc thesis. Since March 2016, Ms Celen has worked at the Department of Plant Production and Technologies, Faculty of Agriculture and Natural Sciences, Konya Food and Agriculture University, Konya, Turkey. *Address correspondence to Burcak Yoldas, Akdeniz University, Dumlupınar Avenue, 07070 Antalya, Turkey. E-mail: [email protected] ª 2017 Elsevier Inc. All rights reserved. 230 Park Avenue, New York, NY 10169
Transplantation Proceedings, 49, 472e476 (2017)
EXPRESSION PROFILE OF MICRO-RNA BIOGENESIS COMPONENTS
473
rejection, indicating that they can be used for estimation of rejection [8]. In many cancer types, the implications of miRNA biogenesis components were reported, suggesting that cancer outcomes may be predicted by evaluation of miRNA biogenesis components [9e12]. However, there is no study investigating the relationship between these components and the outcome of transplant patients and allograft.
immune response. They regulate gene expression by binding their target mRNAs [1e3]. miRNAs are transcribed as long miRNA precursors and processed into mature miRNAs. In the nucleus the primary-miRNA is cleaved by a microprocessor complex formed by RNase III endonuclease Drosha and its cofactor Pasha (DGCR8) producing a 60e70-nucleotide stem-loop known as precursor-miRNA (pre-miRNA). Pre-miRNAs are transferred to cytoplasm via Exportin5 (XPO5). In the cytoplasm, it is again cleaved into a double-stranded miRNA-miRNA duplex by RNase III endonuclease Dicer. One strand of the miRNA-miRNA duplex is known as the guide strand and is loaded into an RNA-induced silencing complex (RISC). miRNA guides the RISC complex to its target mRNA. miRNA binds its target mRNA via complementarity in a specific seed region of miRNA: 6e8 nucleotides at the 50 end. Argonaute2 protein (AGO2) in RISC cleaves the target mRNA in the case of perfect sequence complementarity, whereas in the presence of mismatches, RISC inhibits binding of ribosome to mRNA [3]. There are many studies investigating miRNA expression profiles in renal transplant patients with acute rejection compared with the healthy individuals that reveal that the expressions of 20 miRNAs are significantly different in the patients undergoing acute rejection. In the biopsy samples of renal transplant patients, regulated miRNAs can be used as biomarker molecules for the diagnosis and prognosis of acute rejection with >90% sensitivity and specificity [4,5]. miR-142-5p expression change in peripheral blood mononuclear cells (PBMCs) is found to be related to rejection in renal transplant patients and is suggested to be used as biomarker [6]. In 2011, it was shown that repression of miR-155 may be a potential therapeutic approach to prevent rejection [7]. Wilflingseder et al showed that there are various miRNA profiles in different kinds of
METHODS Renal Transplant Patients Total of 16 renal transplant patients were enrolled in the study conducted in the Organ Transplantation Center of Akdeniz University. Patients, varying in age from 18 to 60 years, underwent transplantation for the 1st time. Blood samples were obtained before surgery (control samples) and 3 months after transplantation (study samples).
Peripheral Blood Mononuclear Cells Isolation PBMCs were isolated from whole blood by density gradients of Biocoll (Biocoll Separating Solution 1077; Biochrom).
Protein Isolation From PBMCs PBMC pellet was homogenized with the use of Triton X-100 buffer solution. The cells were disrupted by means of vortex and centrifuged at 10,000 rpm for 1 minute.
SDS-PAGE AND WESTERN BLOT ANALYSIS
Protein quantities in PBMC were estimated with the use of Bradford assay (Biorad Protein Assay). Proteins were analyzed by means of sodium dodecyl sulfateepolyacrylamide gel electrophoresis (7%) and Western blot analysis.
Table 1. Recipient and Donor Information Recipient Patient
H2 H3 H4 H5 H10 H11 H12 H13 H14 H15 H17 H18 H19 H21 H22 H23
Donor
Age (y)
Sex
Diagnosis
Age (y)
Sex
Relationship
Histocompatibility
Immunosuppressants
51 35 36 53 30 19 45 42 30 58 28 32 18 20 24 32
M M M M M M M F M M F F F M F M
T2D, HT Amyloidos TIN HT CRF CRF CRF CRF CRF HT CRF CRF SLE NM, EB CRF AN
25 34 55 49 68 64 70 31 28 36 59 50 44 40 59 61
F F M F M M F F F M F F M F F F
Daughter Wife Father Wife Father Father Mother Sister Wife Son Mother Cousin Father Mother Mother LURD
1 A, 1 B, 1 DR 1 DR 1 A, 1 B, 1 DR 2 DR 1 A, 1 B, 1 DR 1 A, 1 B, 1 DR 1 A, 1 B, 2 DR 2 A, 2 B, 2 DR 1 A, 1 B, 1 DR 1 A, 1B, 1 DR 1 A, 1 B, 1 DR 2B 1 A, 1 B, 1 DR 1 A, 1 B, 1 DR 2 A, 2 B, 2 DR 0
TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ EVL þ MFA TAC þ EVL þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA
Abbreviations: T2D, type 2 diabetes; HT, hypertension; TIN, tubulointerstitial nephritis; CRF, chronic renal failure; SLE, systemic lupus erythematosus; NM, neurogenic bladder; EB, ectopic kidney; AN, analgesic nephropathy; LURD, living-unrelated donor; TAC, tacrolimus; MFA, mycophenolic acid; EVL, everolimus.
474
RNA Isolation From Peripheral Blood
Fresh blood samples in K2 EDTA tubes were used for RNA isolation with the use of QIAamp RNA Blood Mini Kit (Qiagen). RNA concentrations were measured (Maestronano; Maestrogen). Real-Time PCR Analysis of Gene Expressions
RNA samples (200 ng) were reverse-transcribed with the use of RT2 HT First Strand Kit (Qiagen). cDNA concentrations were also measured and diluted with 90 mL RNase-free H2O. Real-time polymerase chain reaction
CELEN, ERTOSUN, KOCAK ET AL
(PCR) reaction mix was prepared and loaded into white plate, and amplification steps were followed for real-time PCR reaction with the use of Lightcycler 480 (Roche). Statistical Analysis
Fold changes of the interested genes were calculated with the use of the 2DDCt method. Statistical analysis was performed with the use of the SPSS 18.0 program. Paired-samples t test for normally distributed groups and Wilcoxon signed-ranks test for nonnormally distributed groups were performed. P < .05 was accepted as significant.
Fig 1. Expression changes of Dicer, Drosha, Pasha (DGCR8), Exportin5 (XPO5), and Argonaute2 (AGO2) of patients at the mRNA and protein levels. Values are shown as mean SEM. (A) Gene expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 of all patients, normalized to b-actin. *P < .05; **P < .01; ***P < .001; n ¼ 16. (B) Protein expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 of all patients, normalized to GAPDH. *P < .001. Dicer, Drosha, DGCR8, and XPO5: n ¼ 15; AGO2: n ¼ 16. (C) Gene expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 in the TAC þ MFA group. Values are normalized to b-actin. *P < .001; n ¼ 14. (D) Protein expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 in the TAC þ MFA group. Values are normalized to GAPDH. *P < .01; n ¼ 13. (E) Gene expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 in the TAC þ EVL þ MFA group. Values are normalized to b-actin (n ¼ 2). (F) Protein expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 in the TAC þ EVL þ MFA group. Values are normalized to GAPDH (n ¼ 2). (G) Gene expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 of the patients who had rejection. P ¼ .11 (n ¼ 3). (H) Gene expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 of the patients who did not have rejection. *P < .05; **P < .01; n ¼ 13; AGO2: P ¼ .10. (I) Protein expression changes of Dicer, Drosha, DGCR8, XPO5 and AGO2 of the patients who do not have rejection. Dicer: n ¼ 12; Drosha, DGCR8, XPO5, and AGO2: n ¼ 13. *P < .05.
EXPRESSION PROFILE OF MICRO-RNA BIOGENESIS COMPONENTS
RESULTS
General features of the patients are summarized in Table 1. At the 3rd month after surgery, the decrease in gene expressions of all components in all patients were statistically significant (Fig 1A). Dicer, Drosha, and DGCR8 protein expressions were decreased (n ¼ 16; P > .05), whereas XPO5 protein expression did not change (P > .05). Protein expression of AGO2 decreased significantly (P < .001; Fig 1B). Transplant patients used 2 groups of immunosupressants: tacrolimus (TAC) þ mycophenolic acid (MFA; n ¼ 14) and TAC þ everolimus (EVL) þ MFA (n ¼ 2). Expression changes were examined according to immunosuppressant groups to evaluate whether these drugs had effect on the expressions of miRNA biogenesis components. Expression changes according to these immunosuppressant groups are shown in Fig 1C and D. Gene expressions of all interested molecules in the patients in the TAC þ MFA group were decreased significantly (Fig 1C). In the TAC þ MFA group, protein expression of AGO2 decreased significantly (P < .01; Fig 1D). In the other group, Dicer expression at mRNA level did not change, Drosha, DGCR8 and XPO5 expressions were slightly decreased, and AGO2 expression increased (Fig 1E). In the patients under TAC þ EVL þ MFA treatment, protein expressions of Dicer and XPO5 did not change whereas expressions of other components were decreased (P > .05; Fig 1F). Patient H13 had chronic rejection and graft loss, and patients H22 and H23 underwent acute rejection at the 2nd month and 5th day, respectively. It is remarkable that some gene expressions decreased almost 3-fold in the patients who had rejection (Fig 1G). In Fig 1H, it is remarkable that there was significant decrease for Dicer, Drosha, DGCR8, and XPO5 whereas the decrease was not significant for AGO2 (P ¼ .10). When the level of protein expressions in the patients who did not have rejection were further evaluated, there was significant decrease in AGO2 (Fig 1I). The patients with rejection showed different profiles in terms of protein expression, and the differences were not statistically significant (data not shown). DISCUSSION
Recent studies show that miRNA molecules are potential biomarkers for diagnosis and prognosis of many diseases. In transplantation, there are many potential applications of these molecules, such as guiding patient selection, personalized immunosuppressive therapy, and estimating the survival time and graft outcome after surgery. An importance of this research is that PBMC samples of patients are preferred, which are obtained by noninvasive methods [3]. In the present study, this is the 1st time that expression profiles of miRNA biogenesis components in PBMCs are shown for renal transplant patients. The expressions of these components are shown at both mRNA and protein levels. The significant down-regulation in expression at the mRNA level of miRNA biogenesis compounds shows the global effect of immunosuppression on miRNA biogenesis.
475
This was an expected investigation result of the interaction between graft outcome and miRNA expression profile [4,5,8,13]. The decrease in AGO2 protein was statistically significant. Because of the important roles of AGO2 in miRNA biogenesis, decrease in the expression may alter the post-transcriptional regulation. There were 2 patients who underwent TAC þ EVL þ MFA treatment and 14 who underwent TAC þ MFA treatment. In the TAC þ MFA group, all components were significantly down-regulated at the mRNA level, and at the protein level Drosha and XPO5 did not show any change and the other components were down-regulated. This result showed that the immunosuppressants alter the miRNA biogenesis at both mRNA and protein level. For the patients in the TAC þ EVL þ MFA group, Dicer expression was not changed and there was up-regulation in AGO2 at the mRNA level. Everolimus might regulate these genes distinctively from the other immunosuppressants. However, more data are needed to suggest that everolimus has an effect on miRNA biogenesis. At the protein level, expression of Dicer and XPO5 did not change in this group. For the patients who had rejection, statistical assessment was not probable owing to the limited number of subjects (1 chronic rejection and 2 acute rejection patients). The significant down-regulation of components at mRNA level gave rise to expectation that there might be a decrease in protein expression as well. However, in the chronic rejection case, AGO2 did not change and DGCR8 increased. If more chronic rejection cases could be evaluated, there might be a possibility of suggesting AGO2 and DGCR8 molecules as biomarkers for chronic rejection. The fold regulation values of rejection cases were much higher than the other patients. At the mRNA level, there was w2-fold decrease in the 3rd month after surgery. In the chronic rejection patient, the fold regulation values were higher than the acute rejection cases, which was thought to be a dramatic result for indicating the potential interaction between miRNA biogenesis regulation and chronic rejection. Our results show that miRNA biogenesis was affected by immunosuppressants after renal transplantation at both mRNA and protein levels and regulated by rejection. miRNA biogenesis components may be potential biomarkers and pharmacologic target molecules for estimating graft outcome and guiding immunosuppressant selection, but a considerable number of cases need to be evaluated for longer periods of time. REFERENCES [1] Roedder S, Vitalone M, Khatri P, Sarwal MM. Biomarkers in solid organ transplantation: establishing personalized transplantation medicine. Genome Med 2011 Jun 8;3(6):37. [2] Sarma NJ, Tiriveedhi V, Ramachandran S, Crippin J, Chapman W, Mohanakumar T. Modulation of immune responses following solid organ transplantation by microRNA. Exp Mol Pathol 2012;93:378e85. [3] Mas VR, Dumur CI, Scian MJ, Gehrau RC, Maluf DG. MicroRNAs as biomarkers in solid organ transplantation. Am J Transplant 2013;13:11e9.
476 [4] Sui W, Dai Y, Huang Y, Lan H, Yan Q, Huang H. Microarray analysis of microRNA expression in acute rejection after renal transplantation. Transpl Immunol 2008;19:81e5. [5] Anglicheau D, Sharma VK, Ding R, Hummel A, Snopkowski C, Dadhania D, et al. MicroRNA expression profiles predictive of human renal allograft status. Proc Natl Acad Sci U S A 2009;106:5330e5. [6] Danger R, Paul C, Giral M, Lavault A, Foucher Y, Degauque N, et al. Expression of miR-142-5p in peripheral blood mononuclear cells from renal transplant patients with chronic antibody-mediated rejection. PLoS One 2013;8:e60702. [7] Zhang M, Zhang Q, Liu F, Yin L, Yu B, Wu J. MicroRNA-155 may affect allograft survival by regulating the expression of suppressor of cytokine signaling 1. Med Hypotheses 2011;77:682e4. [8] Wilflingseder J, Regele H, Perco P, Kainz A, Soleiman A, Muhlbacher F, et al. miRNA profiling discriminates types of rejection and injury in human renal allografts. Transplantation 2013;95:835e41.
CELEN, ERTOSUN, KOCAK ET AL [9] Merritt WM, Lin YG, Han LY, Kamat AA, Spannuth WA, Schmandt R, et al. Dicer, Drosha, and outcomes in patients with ovarian cancer. N Engl J Med 2008;359:2641e50. [10] Faber C, Horst D, Hlubek F, Kirchner T. Overexpression of Dicer predicts poor survival in colorectal cancer. Eur J Cancer 2011;47:1414e9. [11] Guo X, Liao Q, Chen P, Li X, Xiong W, Ma J, et al. The microRNA-processing enzymes: Drosha and Dicer can predict prognosis of nasopharyngeal carcinoma. J Cancer Res Clin Oncol 2012;138:49e56. [12] Diaz-Garcia CV, Agudo-Lopez A, Perez C, LopezMartin JA, Rodriguez-Peralto JL, de Castro J, et al. DICER1, DROSHA and miRNAs in patients with nonsmall cell lung cancer: implications for outcomes and histologic classification. Carcinogenesis 2013;34:1031e8. [13] Danger R, Pallier A, Giral M, Martinez-Llordella M, Lozano JJ, Degauque N, et al. Up-regulation of miR-142-3p in peripheral blood mononuclear cells of operationally tolerant patients with a renal transplant. J Am Soc Nephrol 2012;23:597e606.
ABSTRACT Background. MicroRNAs (miRNAs) and the miRNA biogenesis components are potential biomarkers of some prevalent diseases, such as cancer and diabetes. In light of this information, we aimed to investigate the expression profiles of miRNA biogenesis components in renal transplant patients before and after transplantation and how these profiles are related to immunosuppressive treatment and clinical outcomes of these patients. Methods. In this study, gene and protein expression profiles of Dicer, Drosha, Pasha (DGCR8), Exportin5 (XPO5), and Argonaute2 (AGO2) in peripheral blood mononuclear cells (PBMCs) of renal transplant patients were evaluated by means of real-time quantitative polymerase chain reaction and Western blot methods before and 3 months after transplantation. Patients who had transplant procedures for the first time were included in the study. Results. Gene expressions were significantly reduced after transplantation. The reduction rate of expressions in 1 patient undergoing chronic rejection was higher. In addition, in patients under everolimus treatment, gene expression of Dicer did not change and gene expression of AGO2 increased. Dicer, Drosha, DGCR8, and AGO2 protein expressions were reduced in all patients, but no change was observed in XPO5 protein expression in nonrejecting patients. Interestingly, in the patient undergoing chronic rejection, protein expression profiles other than Dicer were distinctive from nonrejecting patients. However, XPO5 protein expression was higher in that patient. Conclusions. Our study shows the importance of the global effect of immunosuppressive treatment on the miRNA biogenesis pathway. miRNA biogenesis components are potential biomarkers indicative of graft outcome and pharmacologic target molecules.
A
LLOGRAFT functions, clinical progress, and rational use of immunosuppressive drugs are important issues for transplantation. For this reason, recent studies have focused on effective biomarkers that can enable efficient monitoring of pre- and post-transplantation prognosis and immune response to allograft [1]. MicroRNAs (miRNAs) have great impact on medical research owing to their potential of being biomarkers for diagnosis and prognosis of many diseases. miRNAs are small evolutionary conserved noncoding RNA molecules that influence diverse biologic mechanisms, such as cell cycle, inflammation, apoptosis, and 0041-1345/17 http://dx.doi.org/10.1016/j.transproceed.2017.01.019
472
Funding: Akdeniz University Scientific Research Coordination Unit, Turkey (grant 2014.02.0122.006). Presented to Akdeniz University Health Sciences Institute as E. Celen’s MSc thesis. Since March 2016, Ms Celen has worked at the Department of Plant Production and Technologies, Faculty of Agriculture and Natural Sciences, Konya Food and Agriculture University, Konya, Turkey. *Address correspondence to Burcak Yoldas, Akdeniz University, Dumlupınar Avenue, 07070 Antalya, Turkey. E-mail: [email protected] ª 2017 Elsevier Inc. All rights reserved. 230 Park Avenue, New York, NY 10169
Transplantation Proceedings, 49, 472e476 (2017)
EXPRESSION PROFILE OF MICRO-RNA BIOGENESIS COMPONENTS
473
rejection, indicating that they can be used for estimation of rejection [8]. In many cancer types, the implications of miRNA biogenesis components were reported, suggesting that cancer outcomes may be predicted by evaluation of miRNA biogenesis components [9e12]. However, there is no study investigating the relationship between these components and the outcome of transplant patients and allograft.
immune response. They regulate gene expression by binding their target mRNAs [1e3]. miRNAs are transcribed as long miRNA precursors and processed into mature miRNAs. In the nucleus the primary-miRNA is cleaved by a microprocessor complex formed by RNase III endonuclease Drosha and its cofactor Pasha (DGCR8) producing a 60e70-nucleotide stem-loop known as precursor-miRNA (pre-miRNA). Pre-miRNAs are transferred to cytoplasm via Exportin5 (XPO5). In the cytoplasm, it is again cleaved into a double-stranded miRNA-miRNA duplex by RNase III endonuclease Dicer. One strand of the miRNA-miRNA duplex is known as the guide strand and is loaded into an RNA-induced silencing complex (RISC). miRNA guides the RISC complex to its target mRNA. miRNA binds its target mRNA via complementarity in a specific seed region of miRNA: 6e8 nucleotides at the 50 end. Argonaute2 protein (AGO2) in RISC cleaves the target mRNA in the case of perfect sequence complementarity, whereas in the presence of mismatches, RISC inhibits binding of ribosome to mRNA [3]. There are many studies investigating miRNA expression profiles in renal transplant patients with acute rejection compared with the healthy individuals that reveal that the expressions of 20 miRNAs are significantly different in the patients undergoing acute rejection. In the biopsy samples of renal transplant patients, regulated miRNAs can be used as biomarker molecules for the diagnosis and prognosis of acute rejection with >90% sensitivity and specificity [4,5]. miR-142-5p expression change in peripheral blood mononuclear cells (PBMCs) is found to be related to rejection in renal transplant patients and is suggested to be used as biomarker [6]. In 2011, it was shown that repression of miR-155 may be a potential therapeutic approach to prevent rejection [7]. Wilflingseder et al showed that there are various miRNA profiles in different kinds of
METHODS Renal Transplant Patients Total of 16 renal transplant patients were enrolled in the study conducted in the Organ Transplantation Center of Akdeniz University. Patients, varying in age from 18 to 60 years, underwent transplantation for the 1st time. Blood samples were obtained before surgery (control samples) and 3 months after transplantation (study samples).
Peripheral Blood Mononuclear Cells Isolation PBMCs were isolated from whole blood by density gradients of Biocoll (Biocoll Separating Solution 1077; Biochrom).
Protein Isolation From PBMCs PBMC pellet was homogenized with the use of Triton X-100 buffer solution. The cells were disrupted by means of vortex and centrifuged at 10,000 rpm for 1 minute.
SDS-PAGE AND WESTERN BLOT ANALYSIS
Protein quantities in PBMC were estimated with the use of Bradford assay (Biorad Protein Assay). Proteins were analyzed by means of sodium dodecyl sulfateepolyacrylamide gel electrophoresis (7%) and Western blot analysis.
Table 1. Recipient and Donor Information Recipient Patient
H2 H3 H4 H5 H10 H11 H12 H13 H14 H15 H17 H18 H19 H21 H22 H23
Donor
Age (y)
Sex
Diagnosis
Age (y)
Sex
Relationship
Histocompatibility
Immunosuppressants
51 35 36 53 30 19 45 42 30 58 28 32 18 20 24 32
M M M M M M M F M M F F F M F M
T2D, HT Amyloidos TIN HT CRF CRF CRF CRF CRF HT CRF CRF SLE NM, EB CRF AN
25 34 55 49 68 64 70 31 28 36 59 50 44 40 59 61
F F M F M M F F F M F F M F F F
Daughter Wife Father Wife Father Father Mother Sister Wife Son Mother Cousin Father Mother Mother LURD
1 A, 1 B, 1 DR 1 DR 1 A, 1 B, 1 DR 2 DR 1 A, 1 B, 1 DR 1 A, 1 B, 1 DR 1 A, 1 B, 2 DR 2 A, 2 B, 2 DR 1 A, 1 B, 1 DR 1 A, 1B, 1 DR 1 A, 1 B, 1 DR 2B 1 A, 1 B, 1 DR 1 A, 1 B, 1 DR 2 A, 2 B, 2 DR 0
TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ EVL þ MFA TAC þ EVL þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA TAC þ MFA
Abbreviations: T2D, type 2 diabetes; HT, hypertension; TIN, tubulointerstitial nephritis; CRF, chronic renal failure; SLE, systemic lupus erythematosus; NM, neurogenic bladder; EB, ectopic kidney; AN, analgesic nephropathy; LURD, living-unrelated donor; TAC, tacrolimus; MFA, mycophenolic acid; EVL, everolimus.
474
RNA Isolation From Peripheral Blood
Fresh blood samples in K2 EDTA tubes were used for RNA isolation with the use of QIAamp RNA Blood Mini Kit (Qiagen). RNA concentrations were measured (Maestronano; Maestrogen). Real-Time PCR Analysis of Gene Expressions
RNA samples (200 ng) were reverse-transcribed with the use of RT2 HT First Strand Kit (Qiagen). cDNA concentrations were also measured and diluted with 90 mL RNase-free H2O. Real-time polymerase chain reaction
CELEN, ERTOSUN, KOCAK ET AL
(PCR) reaction mix was prepared and loaded into white plate, and amplification steps were followed for real-time PCR reaction with the use of Lightcycler 480 (Roche). Statistical Analysis
Fold changes of the interested genes were calculated with the use of the 2DDCt method. Statistical analysis was performed with the use of the SPSS 18.0 program. Paired-samples t test for normally distributed groups and Wilcoxon signed-ranks test for nonnormally distributed groups were performed. P < .05 was accepted as significant.
Fig 1. Expression changes of Dicer, Drosha, Pasha (DGCR8), Exportin5 (XPO5), and Argonaute2 (AGO2) of patients at the mRNA and protein levels. Values are shown as mean SEM. (A) Gene expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 of all patients, normalized to b-actin. *P < .05; **P < .01; ***P < .001; n ¼ 16. (B) Protein expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 of all patients, normalized to GAPDH. *P < .001. Dicer, Drosha, DGCR8, and XPO5: n ¼ 15; AGO2: n ¼ 16. (C) Gene expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 in the TAC þ MFA group. Values are normalized to b-actin. *P < .001; n ¼ 14. (D) Protein expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 in the TAC þ MFA group. Values are normalized to GAPDH. *P < .01; n ¼ 13. (E) Gene expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 in the TAC þ EVL þ MFA group. Values are normalized to b-actin (n ¼ 2). (F) Protein expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 in the TAC þ EVL þ MFA group. Values are normalized to GAPDH (n ¼ 2). (G) Gene expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 of the patients who had rejection. P ¼ .11 (n ¼ 3). (H) Gene expression changes of Dicer, Drosha, DGCR8, XPO5, and AGO2 of the patients who did not have rejection. *P < .05; **P < .01; n ¼ 13; AGO2: P ¼ .10. (I) Protein expression changes of Dicer, Drosha, DGCR8, XPO5 and AGO2 of the patients who do not have rejection. Dicer: n ¼ 12; Drosha, DGCR8, XPO5, and AGO2: n ¼ 13. *P < .05.
EXPRESSION PROFILE OF MICRO-RNA BIOGENESIS COMPONENTS
RESULTS
General features of the patients are summarized in Table 1. At the 3rd month after surgery, the decrease in gene expressions of all components in all patients were statistically significant (Fig 1A). Dicer, Drosha, and DGCR8 protein expressions were decreased (n ¼ 16; P > .05), whereas XPO5 protein expression did not change (P > .05). Protein expression of AGO2 decreased significantly (P < .001; Fig 1B). Transplant patients used 2 groups of immunosupressants: tacrolimus (TAC) þ mycophenolic acid (MFA; n ¼ 14) and TAC þ everolimus (EVL) þ MFA (n ¼ 2). Expression changes were examined according to immunosuppressant groups to evaluate whether these drugs had effect on the expressions of miRNA biogenesis components. Expression changes according to these immunosuppressant groups are shown in Fig 1C and D. Gene expressions of all interested molecules in the patients in the TAC þ MFA group were decreased significantly (Fig 1C). In the TAC þ MFA group, protein expression of AGO2 decreased significantly (P < .01; Fig 1D). In the other group, Dicer expression at mRNA level did not change, Drosha, DGCR8 and XPO5 expressions were slightly decreased, and AGO2 expression increased (Fig 1E). In the patients under TAC þ EVL þ MFA treatment, protein expressions of Dicer and XPO5 did not change whereas expressions of other components were decreased (P > .05; Fig 1F). Patient H13 had chronic rejection and graft loss, and patients H22 and H23 underwent acute rejection at the 2nd month and 5th day, respectively. It is remarkable that some gene expressions decreased almost 3-fold in the patients who had rejection (Fig 1G). In Fig 1H, it is remarkable that there was significant decrease for Dicer, Drosha, DGCR8, and XPO5 whereas the decrease was not significant for AGO2 (P ¼ .10). When the level of protein expressions in the patients who did not have rejection were further evaluated, there was significant decrease in AGO2 (Fig 1I). The patients with rejection showed different profiles in terms of protein expression, and the differences were not statistically significant (data not shown). DISCUSSION
Recent studies show that miRNA molecules are potential biomarkers for diagnosis and prognosis of many diseases. In transplantation, there are many potential applications of these molecules, such as guiding patient selection, personalized immunosuppressive therapy, and estimating the survival time and graft outcome after surgery. An importance of this research is that PBMC samples of patients are preferred, which are obtained by noninvasive methods [3]. In the present study, this is the 1st time that expression profiles of miRNA biogenesis components in PBMCs are shown for renal transplant patients. The expressions of these components are shown at both mRNA and protein levels. The significant down-regulation in expression at the mRNA level of miRNA biogenesis compounds shows the global effect of immunosuppression on miRNA biogenesis.
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This was an expected investigation result of the interaction between graft outcome and miRNA expression profile [4,5,8,13]. The decrease in AGO2 protein was statistically significant. Because of the important roles of AGO2 in miRNA biogenesis, decrease in the expression may alter the post-transcriptional regulation. There were 2 patients who underwent TAC þ EVL þ MFA treatment and 14 who underwent TAC þ MFA treatment. In the TAC þ MFA group, all components were significantly down-regulated at the mRNA level, and at the protein level Drosha and XPO5 did not show any change and the other components were down-regulated. This result showed that the immunosuppressants alter the miRNA biogenesis at both mRNA and protein level. For the patients in the TAC þ EVL þ MFA group, Dicer expression was not changed and there was up-regulation in AGO2 at the mRNA level. Everolimus might regulate these genes distinctively from the other immunosuppressants. However, more data are needed to suggest that everolimus has an effect on miRNA biogenesis. At the protein level, expression of Dicer and XPO5 did not change in this group. For the patients who had rejection, statistical assessment was not probable owing to the limited number of subjects (1 chronic rejection and 2 acute rejection patients). The significant down-regulation of components at mRNA level gave rise to expectation that there might be a decrease in protein expression as well. However, in the chronic rejection case, AGO2 did not change and DGCR8 increased. If more chronic rejection cases could be evaluated, there might be a possibility of suggesting AGO2 and DGCR8 molecules as biomarkers for chronic rejection. The fold regulation values of rejection cases were much higher than the other patients. At the mRNA level, there was w2-fold decrease in the 3rd month after surgery. In the chronic rejection patient, the fold regulation values were higher than the acute rejection cases, which was thought to be a dramatic result for indicating the potential interaction between miRNA biogenesis regulation and chronic rejection. Our results show that miRNA biogenesis was affected by immunosuppressants after renal transplantation at both mRNA and protein levels and regulated by rejection. miRNA biogenesis components may be potential biomarkers and pharmacologic target molecules for estimating graft outcome and guiding immunosuppressant selection, but a considerable number of cases need to be evaluated for longer periods of time. REFERENCES [1] Roedder S, Vitalone M, Khatri P, Sarwal MM. Biomarkers in solid organ transplantation: establishing personalized transplantation medicine. Genome Med 2011 Jun 8;3(6):37. [2] Sarma NJ, Tiriveedhi V, Ramachandran S, Crippin J, Chapman W, Mohanakumar T. Modulation of immune responses following solid organ transplantation by microRNA. Exp Mol Pathol 2012;93:378e85. [3] Mas VR, Dumur CI, Scian MJ, Gehrau RC, Maluf DG. MicroRNAs as biomarkers in solid organ transplantation. Am J Transplant 2013;13:11e9.
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