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BASIC SCIENCE |
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*Core Proteomics Laboratory, Kidney Disease Program, Department of Medicine, and Departments of Biochemistry and Molecular Biology, Pediatrics, and Pharmacology and Toxicology, University of Louisville, Louisville, Kentucky; ||Veterans Affairs Medical Center, Louisville, Kentucky; ¶Center for Blood Research and Department of Pediatrics, Harvard Medical School, Boston, Massachusetts; and #Department of Medicine, Ohio State University School of Medicine, Columbus, Ohio
Correspondence to Dr. Visith Thongboonkerd, Proteomics Center, Medical Molecular Biology Unit, Office for Research and Development, 12th Floor—Adulyadej Vikrom Building, Siriraj Hospital, Prannok Road, Bangkoknoi, Bangkok 10700, Thailand. Phone: 66-2-4184793; Fax: 66-2-4184793; E-mail: thongboonkerd{at}dr.com
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Abstract |
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Introduction |
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Recently, Clarkson et al. (6) demonstrated that at least 200 genes were differentially expressed in mesangial cells after exposure to high-glucose media. These findings indicate the complexity of the development of diabetic nephropathy. However, proteins, not genes, govern cellular functions. The study of changes in renal protein expression is necessary to understand better the complex pathogenic mechanisms of diabetic nephropathy. Conventional protein studies—Western blotting and other immunologic methods—are limited to a relatively small number of proteins that can be studied in each experiment and to previously identified proteins for which specific antibodies are available. Proteomic analysis is an innovative approach that overcomes the limitations of immunology-based protein analyses. We used proteomic analysis in the present study to evaluate global changes of renal protein expression in diabetic kidneys. The diabetic animal model used in this study was the OVE26 transgenic mouse model. OVE26 mice at 120 d of age displayed many characteristics of early-onset type 1 diabetic nephropathy, including hyperglycemia, hypoinsulinemia, hyperlipidemia, mesangial expansion, and thickening of glomerular basement membrane (GBM) (7, 8). Because a protein database for mouse kidney was not available, we created an initial renal proteome map for FVB nondiabetic mice (the background strain of the OVE26 line) and used this map as a reference to analyze protein expression in diabetic kidneys.
Comparison of protein expression in kidneys from OVE26 and FVB mice by two-dimensional (2-D) PAGE demonstrated significant differences in expression levels of eight groups of proteins: proteases, protease inhibitors, apoptosis-associated proteins, regulators for oxidative tolerance, calcium-binding proteins, transport regulators, cell signaling proteins, and smooth muscle contractile elements. Our results showed coordinated changes in expression of monocyte/neutrophil elastase inhibitor (MNEI), which was increased, and elastase IIIB, which was decreased. These findings suggested the hypothesis that elastin, an extracellular matrix (ECM) protein, accumulates in diabetic kidneys and may participate in the development of diabetic nephropathy. This hypothesis was supported by immunohistochemical studies in the OVE26 diabetic mice and patients with type 1 diabetes demonstrating increased elastin deposition in renal tubular cells.
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Materials and Methods |
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Urine Albumin Assay
Mice (120 d old) were housed in metabolic cages (Nalgene, Braintree, MA) with free access to solid laboratory food and feeding water. For obtaining adequate urine volume, the feeding water contained 10% (vol/vol) Glucerna liquid diet (Abbotts Laboratories, Columbus, OH). Urinary albumin excretion on 24-h collections was measured by a commercial ELISA kit using goat anti-mouse albumin antibody (Bethyl Laboratories Inc., Montgomery, TX).
Extraction of Renal Proteins for 2-D PAGE
Mice were killed at 120 d of age by injection with Ketamine HCl/Xylazine HCl solution (Sigma Chemical Co., St. Louis, MO). Protein extraction of the whole kidney was performed as described previously (9, 10). Kidneys were frozen in liquid nitrogen; ground to powder; resuspended in a buffer containing 50 mM Tris, 0.3% SDS, and 200 mM DTT; and incubated at 100°C for 5 min. DNA and RNA were removed by a buffer containing 500 mM Tris, 50 mM MgCl2, 1 mg/ml DNAse I, and 0.25 mg/ml RNAse A. Excess salts were removed by acetone precipitation, and the protein pellet was finally resuspended in a buffer containing 40 mM Tris, 7.92 M urea, 0.06% SDS, 1.76% ampholytes, 120 mM DTT, and 3.2% Triton X-100. Protein concentration levels were measured by spectrophotometry using HP 8453 UV-visible system (Hewlett-Packard Company, Palo Alto, CA) and Bio-Rad Protein Assay (Bio-Rad Laboratories, Hercules, CA).
First Dimension of 2-D PAGE
A mobile ampholyte tube gel running system (Genomic Solutions Inc., Ann Arbor, MI) was used for first-dimensional isoelectric focusing using 100 mM sodium hydroxide as the cathode buffer and 10 mM phosphoric acid as the anode buffer. Precast carrier ampholyte tube gels (pH 3 to 10), 1 mm x 18 cm, were prefocused with maximal 1500 V and 110 µA per tube. Protein samples containing 100 µg from individual animals were loaded into individual tube gels and were focused for 17 h and 30 min to reach 18,000 volt-hours.
Second Dimension of 2-D PAGE
The gels were extruded from the tubes after completion of focusing and were incubated in premixed Tris/acetate equilibration buffer with 0.01% bromophenol blue and 50 mM DTT for 2 min before loading onto precast 10% homogeneous, 22 x 22-cm, slab gels (Genomic Solutions). The upper running buffer contained 0.2 M Tris base, 0.2 M tricine, and 0.4% SDS, and the lower running buffer contained 0.625 M Tris/acetate. Protein separation was performed with a maximum of 500 V and 20,000 mW per gel.
SYPRO Ruby Staining and Visualization
The gel slabs were fixed in 10% methanol and 7% acetic acid for 30 min. The fixed solution was removed, and 500 ml of SYPRO Ruby gel stain (Bio-Rad Laboratories) was added to each gel and incubated on gently continuous rocker at room temperature for 18 h. A high-resolution 12-bit camera with ultraviolet light box system (Genomic Solutions) was used to visualize the gel images.
Quantitative Analysis of Protein Expression
Investigator HT analyzer (Genomic Solutions) software was used for matching and analysis of protein spots. The principles of measurement of intensity value by 2-D analysis software were similar to those of densitometric measurement. Average mode of background subtraction was used to normalize intensity value that represents the amount of protein per spot. The normalized intensity values of individual protein spots were then used to determine differential protein expression between groups by statistical analyses.
Statistical Analyses
After completion of spot matching, spot intensities of each protein spot from individual animals were compared between control and diabetic groups. Because the sample size was relatively small, both unpaired t test and Mann-Whitney U test by SPSS software v. 10.0 were used for statistical analyses to avoid spurious results. P < 0.05 was considered statistically significant. Only significant differences that were in agreement between the t test and the Mann-Whitney U test were included, and the data were reported as mean ± SEM.
In-Gel Tryptic Digestion, MALDI-TOF Mass Spectrometry, and Peptide Mass Fingerprinting
In-gel tryptic digestion and matrix-assisted laser desorption ionization–time-of-flight (MALDI-TOF) mass spectrometry (MS) were performed using techniques described previously by our laboratory (11). Protein identification of peptide fragments was performed by us-ing the "ProFound" search engine (129.85.19.192/profound_bin/ WebProFound.exe). The National Center for Biotechnology Information (NCBI) protein database was restricted to mammalian entries, and peptides were assumed to be monoisotopic, oxidized at methionine residues, and carbamidomethylated at cysteine residues. Up to one missed trypsin cleavage was allowed, although most matches did not contain any missed cleavages. A mass tolerance error of 150 ppm was allowed for matching peptide mass values. Z scores were estimated by comparison of search results against estimated random-match population and were the distances to the population mean in units of SD. Scores >1.65 were considered statistically significant (P < 0.05). Identities of protein spots that did not reach this significant level were not reported.
Bioinformatic Analyses
To examine potential protein function and sequence homology, we performed bioinformatic analysis using public protein databases. Inferred protein functions were determined by using data in the NCBI (www.ncbi.nlm.nih.gov/), Swiss-Prot, and TrEMBL protein databases (ca.expasy.org/sprot/). The similarity of amino acid sequences was determined using the protein BLAST format (BLink) of the NCBI protein database, as well as standard pairwise protein BLASTp searches.
Western Blotting
Renal proteins were mixed with 2x Laemmli sample buffer and boiled for 5 min, and 30 µg of total proteins were loaded on 10% SDS-PAGE for MNEI Western blot. Proteins were transferred to a nitrocellulose membrane and blocked with 5% milk/TTBS. The membrane was treated with rabbit polyclonal anti-MNEI serum (12) (1:1000 in 0.1% milk/PBS-Tween) at room temperature for 90 min. This serum cross-reacts with recombinant mouse elastase inhibitor A (EIA), the ortholog of MNEI (data not shown). Immunoreactive protein was detected by autoradiography using horseradish peroxidase–conjugated antibody and chemiluminescent substrate.
Immunohistochemistry
Immunohistochemistry was performed on kidneys from 120- and 325-d-old FVB and OVE26 mice (n = 2) and on human renal biopsies from patients with type 1 diabetes compared with normal biopsies, which were from candidate donors for renal transplantation (n = 3). Five-micrometer-thick mouse kidney sections were deparaffinized and rehydrated. Antigen retrieval was performed by incubation in DAKO Target retrieval solution (DAKO Corp., Carpinteria, CA) at 95°C for 20 min. Endogenous tissue peroxidase activity was suppressed by an incubation in 3% H2O2 at room temperature for 5 min. Nonspecific bindings were blocked using 5% (vol/vol) goat serum (Vector Laboratories, Burlingame, CA) in Tris-buffered saline at room temperature for 1 h. The sections were then incubated with rabbit polyclonal anti-elastin antibody (#RDI-TP592; Research Diagnostics Inc., Flanders, NJ), 1:400 in 1% goat serum at 4°C overnight. Slides were washed three times in Tris buffer before incubation with biotinylated secondary antibody (Vector Laboratories), 1:200 in 1% goat serum at room temperature for 30 min. After three washes in Tris buffer, the sections were incubated with an avidin/biotinylated peroxidase complex (Vectastain Elite ABC kit; Vector Laboratories) for 30 min. Immunoreactive elastin was detected by color developing with Chromagen 3-3' diaminobenzidine (Vector Laboratories) for 4 min. All sections were counterstained with hematoxylin. A section of mouse aorta was used as the positive control. A negative control was performed by incubation with 1% goat serum without primary antibody.
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Results |
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cells caused by overexpression of the calcium-binding protein calmodulin (8). Metabolic derangements in OVE26 mice included hyperglycemia, hypoinsulinemia, and hypertriglyceridemia. Hyperglycemia in OVE26 mice occurred within 1 wk after birth, and random plasma glucose levels were >600 mg/dl from 10 wk of age. Plasma insulin levels of adult OVE26 mice were approximately 30% of normal values as a result of the cell–specific, calmodulin transgene (8). The mice typically survived without insulin therapy or any other treatment for at least 1 yr. Mild mesangial expansion and GBM thickening were observed in 120-d-old OVE26 diabetic mice without azotemia. For further characterizing the renal phenotype of the OVE26 line, 24-h urinary albumin excretion was measured. OVE26 diabetic mice at 120 d of age had significantly increased 24-h urinary albumin excretion compared with the FVB controls (743 ± 461 versus 29 ± 17 µg/24 h; P < 0.05). When the mice were killed at approximately 17 wk (120 d), OVE26 mice had been diabetic for approximately 16 wk.
Proteome Map of Normal FVB Mouse Kidney
As a database of mouse kidney proteins was not available, a proteome map for FVB mouse kidney was produced. Renal proteins from individual animals (n = 5) were separated by 2-D PAGE. The protein spot pattern was reproducible from each animal. Up to 300 protein spots were visualized on each 2-D gel by SYPRO Ruby staining. Of these visualized protein spots, 150 spots were excised and subjected to MALDI-TOF MS. The remaining spots were not excised, as their expression was likely below the threshold of detectability by MALDI-TOF MS. A total of 92 proteins were identified in our initial mouse kidney proteome map (Figure 1A). Positions of all of these identified proteins on 2-D gels were in the expected range of their theoretical isoelectric points (pI) and molecular weights (Mw). All identified proteins in the proteome map are summarized in Table 1. Figure 2A illustrates mass spectra representative of a single protein spot (spot 70 in Figure 1) obtained by MALDI-TOF MS, and Figure 2B demonstrates peptide mass fingerprint analysis that matched those mass spectra with the mouse serine protease inhibitor EIA with a fingerprint z score of 2.43 (>99 percentile; P < 0.01).
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Coordinated Changes in the Renal Elastin-Elastase System in Diabetic Kidneys
We identified increased expression of the serine protease inhibitor EIA (spot 70, Figures 1 and 2
). EIA was recently identified as one of the four mouse homologs of the human elastase inhibitor MNEI (13). MNEI is one of the most efficient inhibitors of elastase-like serine proteases and is the product of a single gene (SERPINB1) in humans (14, 15). The characterization of the mouse homologs revealed that EIA is the only functional counterpart of MNEI on the basis of sequence, tissue expression, and inhibitory function (13). Western blot analysis in 120-d-old mouse kidneys confirmed the presence of MNEI in normal kidneys and its upregulation by diabetes (Figure 3). Therefore, MNEI and EIA are used interchangeably in the rest of this article.
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Discussion |
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We identified 92 proteins in our initial proteome map of normal FVB mouse kidney, 30 of which were differentially expressed in diabetic kidneys. The mechanism for altered expression of these proteins was not investigated but could be induced by hyperglycemia and/or hypoinsulinemia, as the animals were both hyperglycemic and hypoinsulinemic. Nineteen of these altered proteins were previously shown to be regulated during diabetes (4, 17–24) and are marked with a superscript b in Table 2. Involvement of the other 11 altered proteins in diabetic nephropathy had not previously been reported, suggesting their roles in novel mechanisms of diabetic nephropathy.
When we examined the list of proteins regulated in diabetic kidneys (Table 2), the only apparent pathway in which multiple proteins were regulated was the elastin-elastase pathway. Because the role of the elastin ECM protein had not been well characterized in diabetic nephropathy, changes in elastin-regulating proteins focused our attention on this pathway. Expression of the elastase inhibitor MNEI was increased approximately threefold in diabetic kidneys. MNEI is one of the most efficient inhibitors of elastase-like serine proteases by forming stable covalent inhibitory complexes with target proteases. Whereas the expression of elastase inhibitor MNEI was increased in diabetic kidneys, elastase IIIB expression was decreased. Thus, both expression and activity of elastase would be predicted to be decreased in diabetic nephropathy. These coordinated changes defined by proteomic analysis suggested the hypothesis that elastin expression would be increased in diabetic kidneys. Renal elastin immunohistochemistry was performed to address this hypothesis.
The elastin distribution in normal mouse kidney in the present study was similar to that observed by Sterzel et al. (25). Immunohistochemical analysis confirmed an increase in elastin expression in diabetic kidneys, particularly in the macula densa. The changes in elastin expression in 325-d-old mice but not at 120 d suggested that a gradual increase in elastin expression required long-term changes in MNEI and elastase IIIB. The pattern of elastin expression in normal human kidneys differed from that in normal mice with greater elastin expression in both tubules and glomeruli in human kidneys. In patients with diabetes, elastin expression was increased in renal tubular epithelial cells. The mechanism of differences in normal distribution and increased elastin expression in mice versus humans remains unknown.
A role for elastin in the pathogenesis of diabetic nephropathy has not previously been described. The major function of elastin is to provide vascular wall elasticity (26). Alterations in elastin expression and function are associated with vasculopathy of large vessels induced by diabetes (27, 28). However, we did not observe change in elastin deposition in the intrarenal vessels. Therefore, it is unlikely that altered elastin expression observed in our study is related to diabetic renal vasculopathy. In the kidney, elastin plays an important role in stabilizing the glomerular tuft (25). The increase in elastin expression, however, was located in renal tubular epithelial cells, not glomeruli. These findings suggest that elastin may play a role in tubular or interstitial changes, which accompany diabetic nephropathy.
Elastin deposition is a highly regulated process that occurs primarily during early development (29). Increased elastin expression results from increased transcription and translation. TGF-, which is upregulated in diabetic kidneys, was reported previously to stabilize elastin mRNA and promote elastin deposition (30). The increased elastin expression identified in renal tubular epithelial cells, not in extracellular spaces, occurred in parallel with an increase of vimentin (Table 2), a marker for cells derived from mesenchymal tissues (31). Our data were consistent with the data reported by Rastaldi et al. (32) that renal tubular epithelial cells can produce ECM proteins and directly intervene in fibrotic processes via the epithelial-mesenchymal transdifferentiation. The increase in expression of a myofibroblast protein (fibroblast tropomyosin) and proteins associated with proliferation, modulation, and differentiation of myofibroblast and fibrogenesis (calmodulin and cellular retinol-binding protein; Table 2) provides further support for this process (33, 34). In addition, Figure 6F shows a marked increase of elastin staining in the tubulointerstitium of an end-stage diabetic kidney. Taken together, these data suggest that elastin may play a role in tubular disorders and interstitial fibrosis in diabetic nephropathy. However, elastin accumulation might reflect advanced tissue response to injury. Thus, alterations in the renal elastin-elastase system may be the cause of or the result of diabetic nephropathy. Further functional and time-course studies are required to evaluate the significance of disordered elastin deposition.
Although our study is the first to examine global changes in protein expression in diabetic kidneys, genomic approaches were previously applied to identify genes in renal cells regulated by hyperglycemia. Clarkson et al. (6) showed that 200 genes were differentially expressed when mesangial cells were propagated in high ambient glucose in vitro. It is not surprising that our proteomic data and Clarkson’s genomic data are not completely concordant. Some genes, such as ferritin, were upregulated by hyperglycemia at the level of transcription and translation. However, other genes, such as myosin, were downregulated in Clarkson’s study, but the protein products of those genes were upregulated in vivo in our OVE26 diabetic mice. Several differences in the experimental approaches might account for the disparate findings. First, we studied the whole kidneys from diabetic animals, whereas Clarkson et al. studied mesangial cells in vitro. Second, changes in mRNA and protein do not always correlate (35–38). Third, differential protein expression can result from posttranslational modifications that are not detectable by genomic analysis. Finally, protein degradation is not measured by changes in mRNA expression.
Several limitations of 2-D proteomic analysis in the present study need to be noted. First, this approach identified high-abundance proteins, whereas detection of low-abundance proteins was limited. This may explain the failure to identify several proteins previously shown to be regulated in diabetes, for example, TGF- and protein kinase C. Second, we did not identify all of the proteins present in the 2-D gels. Using more sensitive mass spectrometric techniques, such as tandem MS, may permit identification of low-abundance proteins. Third, a larger number of visualized protein spots would be expected on individual gels than the 300 spots observed in the present study. This limitation likely resulted from the small amount of protein (100 µg) used for individual analytical gels. In addition, the extraction protocol used did not solubilize some protein components, especially membrane-associated and hydrophobic proteins.
We examined protein expression from the whole kidneys in the present study. This approach cannot identify localized changes such as those that may be confined to glomeruli, tubules, or even podocytes. In additional, the magnitude of changes is affected by degrees of changes in individual intrarenal structures. For example, mild changes in mesangial cells may not be detected in the whole-kidney analysis if there is no change in other structures or changes in other structures are in an opposite direction. Moreover, it should be noted that identification of the altered proteins in the kidney does not confirm that they are kidney-specific changes, as a systematic study of other organs was not performed. Changes similar to those that we observed in the kidney may be present in liver, muscles, or other organs. Finally, we examined renal protein expression only in 120-d-old animals. Defining alterations in renal protein expression at a single time point does not represent the entire dynamic process of diabetic nephropathy. We are currently performing a serial study of other time points of isolated glomeruli and blood vessels to characterize more thoroughly the renal subproteome during diabetes.
In summary, proteomic analysis revealed coordinated changes of elastase inhibitor MNEI and elastase IIIB, leading to the identification of increased elastin expression in mouse and human diabetic kidneys. Application of proteomic analysis may yield new insights into the pathogenic mechanisms of diabetic nephropathy.
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Acknowledgments |
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Footnotes |
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mRNA and protein expression in transitional cellcancer of the bladder. Urology 61: 851–857, 2003[CrossRef][Medline]
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