Two-dimensional electrophoretic profiling of normal human kidney glomerulus proteome and construction of an extensible markup language (XML)-based database

Biochemical composition of the glomerular extracellular matrix in patients with diabetic kidney disease

In the glomeruli, mesangial cells produce mesangial matrix while podocytes wrap glomerular capillaries with cellular extensions named foot processes and tether the glomerular basement membrane (GBM). The turnover of the mature GBM and the ability of adult podocytes to repair injured GBM are unclear. The actin cytoskeleton is a major cytoplasmic component of podocyte foot processes and links the cell to the GBM. Predominant components of the normal glomerular extracellular matrix (ECM) include glycosaminoglycans, proteoglycans, laminins, fibronectin-1, and several types of collagen. In patients with diabetes, multiorgan composition of extracellular tissues is anomalous, including the kidney, so that the constitution and arrangement of glomerular ECM is profoundly altered. In patients with diabetic kidney disease (DKD), the global quantity of glomerular ECM is increased. The level of sulfated proteoglycans is reduced while hyaluronic acid is augmented, compared to control subjects. The concentration of mesangial fibronectin-1 varies depending on the stage of DKD. Mesangial type III collagen is abundant in patients with DKD, unlike normal kidneys. The amount of type V and type VI collagens is higher in DKD and increases with the progression of the disease. The GBM contains lower amount of type IV collagen in DKD compared to normal tissue. Further, genetic variants in the α3 chain of type IV collagen may modulate susceptibility to DKD and end-stage kidney disease. Human cellular models of glomerular cells, analyses of human glomerular proteome, and improved microscopy procedures have been developed to investigate the molecular composition and organization of the human glomerular ECM.

Contactin-1 is a novel target antigen in membranous nephropathy associated with chronic inflammatory demyelinating polyneuropathy

Primary membranous nephropathy (MN) is an autoimmune glomerular disease in which autoantibodies are directed against podocyte proteins. In about 80% of cases the main targeted antigen is the phospholipase A2 receptor 1 (PLA2R1). Anti-PLA2R1 antibodies are mainly immunoglobulin G type 4 (IgG4). However, the antigenic target remains to be defined in 20% of cases. MN can be associated with chronic inflammatory demyelinating polyneuropathy, an autoimmune disease of the peripheral nervous system where a common antigenic target has yet to be identified. To ascertain a possible novel target antigen, we analyzed kidney biopsies from five patients positive for anti-contactin 1 antibodies and presenting with MN combined with chronic inflammatory demyelinating polyneuropathy. Eluted IgG from biopsy sections against contactin 1 and nerve tissue were screened. Western blot revealed contactin 1 expression in normal kidney glomeruli. Confocal microscopic analysis showed the presence and colocalization of contactin 1 and IgG4 on the glomerular basement membrane of these patients. Glomerular contactin 1 was absent in patients with anti-PLA2R1-associated MN or membranous lupus nephritis or a healthy control. The eluted IgG from contactin 1-positive biopsy sections but not the IgG eluted from patients with PLA2R1 MN bound contactin 1 with the main eluted subclass IgG4. Eluted IgG could bind paranodal tissue (myelinated axon) and colocalized with commercial anti-contactin 1 antibody. Thus, contactin 1 is a novel common antigenic target in MN associated with chronic inflammatory demyelinating polyneuropathy. However, the precise pathophysiology remains to be elucidated.

Reckoning the Dearth of Bioinformatics in the Arena of Diabetic Nephropathy (DN)—Need to Improvise

Diabetic nephropathy (DN) is a recent rising concern amongst diabetics and diabetologist. Characterized by abnormal renal function and ending in total loss of kidney function, this is becoming a lurking danger for the ever increasing population of diabetics. This review touches upon the intensity of this complication and briefly reviews the role of bioinformatics in the area of diabetes. The advances made in the area of DN using proteomic approaches are presented. Compared to the enumerable inputs observed through the use of bioinformatics resources in the area of proteomics and even diabetes, the existing scenario of skeletal application of bioinformatics advances to DN is highlighted and the reasons behind this discussed. As this review highlights, almost none of the well-established tools that have brought breakthroughs in proteomic research have been applied into DN. Laborious, voluminous, cost expensive and time-consuming methodologies and advances in diagnostics and biomarker discovery promised through beckoning bioinformatics mechanistic approaches to improvise DN research and achieve breakthroughs. This review is expected to sensitize the researchers to fill in this gap, exploiting the available inputs from bioinformatics resources.

A proteome comparison between human fetal and mature renal extracellular matrix identifies EMILIN1 as a regulator of renal epithelial cell adhesion

Cell-based approaches using tissue engineering and regenerative medicine to replace damaged renal tissue with 3D constructs is a promising emerging therapy for kidney disease. Besides living cells, a template provided by a scaffold based on biomaterials and bioactive factors is needed for successful kidney engineering. Nature's own template for a scaffolding system is the extracellular matrix (ECM). Research has focused on mapping the mature renal ECM; however, the developing fetal ECM matches more the active environment required in 3D renal constructs. Here, we characterized the differences between the human fetal and mature renal ECM using spectrometry-based proteomics of decellularized tissue. We identified 99 different renal ECM proteins of which the majority forms an overlapping core, but also includes proteins enriched in either the fetal or mature ECM. Relative protein quantification showed a significant dominance of EMILIN1 in the fetal ECM. We functionally tested the role of EMILIN1 in the ECM using a novel methodology that permits the reliable anchorage of native cell-secreted ECM to glass coverslips. Depletion of EMILIN1 from the ECM layer using siRNA mediated knock-down technologies does not affect renal epithelial cell growth, but does promote migration. Lack of EMILIN1 in the ECM layer reduces the adhesion strength of renal epithelial cells, shown by a decrease in focal adhesion points and associated stress fibers. We showed in this study the importance of a human renal fetal and mature ECM catalogue for identifying promising ECM components that have high implementation potential in scaffolds for 3D renal constructs.

•

Proteomics revealed the differences between the renal fetal and mature extracellular matrix.

•

EMILIN1 has a significant dominance in the fetal extracellular matrix.

•

EMILIN1 depletion from the extracellular matrix reduces the adhesion strength and promotes migration of renal epithelial cells.

Proteomics for Biomarker Identification and Clinical Application in Kidney Disease

Treatment effectiveness for kidney disease is limited by lack of accuracy, sensitivity, specificity of diagnostic, prognostic, and therapeutic biomarkers. The gold standard test renal biopsy along with serum creatinine and proteinuria is often necessary to establish a diagnosis, particularly in glomerular disease. Proteomics has become a powerful tool for novel biomarker discovery in kidney disease. Novel proteomics offer earlier and more accurate diagnosis of renal pathology than possible with traditional biomarkers such as serum creatinine and urine protein. In addition, proteomic biomarkers could also be useful to choose the most suitable therapeutic targets. This review focuses on the current status of proteomic biomarkers from animal models (5/6 nephrectomy, unilateral ureteral obstruction, and diabetic nephropathy) and human studies (chronic kidney disease, glomerular diseases, transplantation, dialysis, acute and drug-induced kidney injury) to assess relevant findings and clinical usefulness. Current issues and problems related to the discovery, validation, and clinical application of proteomic biomarkers are discussed. We also describe several proteomic strategies highlighting technologic advancements, specimen selection, data processing and analysis. This review might provide help in future proteomic studies to improve the diagnosis and management of kidney disease.

Characterization of glomerular extracellular matrix by proteomic analysis of laser-captured microdissected glomeruli

Abnormal extracellular matrix (ECM) remodeling is a prominent feature of many glomerular diseases and is a final common pathway of glomerular injury. However, changes in ECM composition accompanying disease-related remodeling are unknown. The physical properties of ECM create challenges for characterization of composition using standard protein extraction techniques, as the insoluble components of ECM are frequently discarded and many ECM proteins are in low abundance compared to other cell proteins. Prior proteomic studies defining normal ECM composition used a large number of glomeruli isolated from human kidneys retrieved for transplantation or by nephrectomy for cancer. Here we examined the ability to identify ECM proteins by mass spectrometry using glomerular sections compatible with those available from standard renal biopsy specimens. Proteins were classified as ECM by comparison to the Matrisome database and previously identified glomerular ECM proteins. Optimal ECM protein identification resulted from sequential decellularization and protein extraction of 100 human glomerular sections isolated by laser capture microdissection from either frozen or formalin-fixed, paraffin-embedded tissue. In total, 147 ECM proteins were identified, including the majority of structural and GBM proteins previously identified along with a number of matrix and glomerular basement membrane proteins not previously associated with glomeruli. Thus, our study demonstrates the feasibility of proteomic analysis of glomerular ECM from retrieved glomerular sections isolated from renal biopsy tissue and expands the list of known ECM proteins in glomeruli.

Proteomic analysis of the kidney filtration barrier--Problems and perspectives

Diseases of the glomerular filter of the kidney are a leading cause of end-stage renal failure. The kidney filter is localized within the renal glomeruli, small microvascular units that are responsible for ultrafiltration of about 180 liters of primary urine every day. The renal filter consists of three layers, fenestrated endothelial cells, glomerular basement membrane, and the podocytes, terminally differentiated, arborized epithelial cells. This review demonstrates the use of proteomics to generate insights into the regulation of the renal filtration barrier at a molecular level. The advantages and disadvantages of different glomerular purification methods are examined, and the technical limitations that have been significantly improved by in silico or biochemical approaches are presented. We also comment on phosphoproteomic studies that have generated considerable molecular-level understanding of the physiological regulation of the kidney filter. Lastly, we conclude with an analysis of urinary exosomes as a potential filter-derived resource for the noninvasive discovery of glomerular disease mechanisms.

Mapping of polar fox renal cortex proteins using two-dimensional gel electrophoresis and mass spectrometry--a preliminary study

The aim of the present study was to establish protein map of polar fox (Alopex lagopus) renal cortex. Kidney cortex proteins of isoelectric point ranging from 3 to 10 were analysed using two-dimensional electrophoresis and MALDI-TOF mass spectrometry. Sixteen protein spots corresponding to thirteen different gene products were identified. These proteins were divided into following groups: lipid and fatty acid metabolism, amino acid metabolism, energetic pathways, regulatory proteins, transport proteins and structural proteins. This is the first attempt to create reproducible 2-D map, of renal cortex proteins characteristic for polar foxes, used as animal model for carnivores. It is worth emphasizing that the results of this study may broaden currently available protein databases.

Global analysis reveals the complexity of the human glomerular extracellular matrix

The glomerulus contains unique cellular and extracellular matrix (ECM) components, which are required for intact barrier function. Studies of the cellular components have helped to build understanding of glomerular disease; however, the full composition and regulation of glomerular ECM remains poorly understood. We used mass spectrometry-based proteomics of enriched ECM extracts for a global analysis of human glomerular ECM in vivo and identified a tissue-specific proteome of 144 structural and regulatory ECM proteins. This catalog includes all previously identified glomerular components plus many new and abundant components. Relative protein quantification showed a dominance of collagen IV, collagen I, and laminin isoforms in the glomerular ECM together with abundant collagen VI and TINAGL1. Protein network analysis enabled the creation of a glomerular ECM interactome, which revealed a core of highly connected structural components. More than one half of the glomerular ECM proteome was validated using colocalization studies and data from the Human Protein Atlas. This study yields the greatest number of ECM proteins relative to previous investigations of whole glomerular extracts, highlighting the importance of sample enrichment. It also shows that the composition of glomerular ECM is far more complex than previously appreciated and suggests that many more ECM components may contribute to glomerular development and disease processes. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium with the dataset identifier PXD000456.

Proteomic analysis of renal diseases: unraveling the pathophysiology and biomarker discovery

Current biomedical applications of proteomics have been conducted with four main objectives: to better understand the normal biology and physiology of cells, microorganisms, tissues and organs; to explore the pathogenic mechanisms and better understand the pathophysiology of medical diseases; to identify novel biomarkers for early disease detection, prediction and prognosis; and to define new therapeutic targets, drugs and vaccines. This review focuses predominantly on proteomic applications to unravel the pathophysiology and to define novel biomarkers for various renal diseases (i.e., glomerular diseases, tubulointerstitial diseases, renal vascular disorders and renal cancers). In addition, proteomic evaluations of renal transplantation and renal replacement therapy (for acute renal failure and end-stage renal disease) are summarized. Personal opinion, future perspectives and information resources for the field of renal and urinary proteomics are provided.

Proteomic approach to human kidney glomerulus prepared by laser microdissection from frozen biopsy specimens: exploration of proteome after removal of blood-derived proteins

PURPOSE

Abundance of blood-derived proteins in glomeruli prepared by laser microdissection from human kidney biopsy specimens has hampered in-depth proteomic analysis of glomeruli. We attempted to establish experimental platform for in-depth proteomic analysis of glomeruli by removal of blood-derived proteins from frozen biopsy samples.

EXPERIMENTAL DESIGN

Frozen sections of biopsy samples were exposed to repeated PBS washes prior to laser microdissection to remove blood-derived proteins, and glomerular dissectants were analyzed by MS. The depth of proteomic analysis was evaluated by dynamic range of identified proteins and detection of low-abundance proteins.

RESULTS

Two times PBS washes of frozen sections effectively eliminated blood-derived proteins in laser-microdissected glomeruli and gave an increased number of identified proteins. Analysis of glomeruli from single specimens by a linear ion trap-Orbitrap mass analyzer generated nonredundant, high-confidence datasets of more than 400 identified proteins with high reproducibility, which attained to a considerable depth of the glomerulus proteome as revealed by a wide dynamic range and identification of low-abundance proteins.

CONCLUSIONS AND CLINICAL RELEVANCE

Implementation of washing of frozen section with PBS successfully removed blood-derived proteins and resulted in an in-depth proteomic analysis of laser-microdissected glomeruli, suggesting applicability to clinical study.

Diabetic nephropathy: traditional to proteomic markers

Diabetic nephropathy (DN) is one of the major microvascular complications of diabetes and it is defined as a rise in the urinary albumin excretion (UAE) rate and abnormal renal function. Currently, changes in albuminuria are considered a hallmark of onset or progression of DN. However, some patients with diabetes have advanced renal pathological changes and progressive kidney function decline even if urinary albumin levels are in the normal range, indicating that albuminuria is not the perfect marker for the early detection of DN. The present article provides an overview of the literature reporting some relevant biomarkers that have been found to be associated with DN and that potentially may be used to predict the onset and/or monitor the progression of nephropathy. In particular, biomarkers of renal damage, inflammation, and oxidative stress may be useful tools for detection at an early stage or prediction of DN. Proteomic-based biomarker discovery represents a novel strategy to improve diagnosis, prognosis and treatment of DN; however, proteomics-based approaches are not yet available in most of the clinical chemistry laboratories. The use of a panel with a combination of biomarkers instead of urinary albumin alone seems to be an interesting approach for early detection of DN, including markers of glomerular damage (e.g., albumin), tubular damage (e.g., NAG and KIM-1), inflammation (e.g., TNF-α) and oxidative stress (e.g., 8-OHdG) because these mechanisms contribute to the development and outcomes of this disease.

Redox proteomics in study of kidney-associated hypertension: new insights to old diseases

SIGNIFICANCE

The kidney helps to maintain low blood pressure in the human body, and impaired kidney function is a common attribute of aging that is often associated with high blood pressure (hypertension). Kidney-related pathologies are important contributors (either directly or indirectly) to overall human mortality. In comparison with other organs, kidney has an unusually wide range of oxidative status, ranging from the well-perfused cortex to near-anoxic medulla.

RECENT ADVANCES

Oxidative stress has been implicated in many kidney pathologies, especially chronic kidney disease, and there is considerable research interest in oxidative stress biomarkers for earlier prediction of disease onset. Proteomics approaches have been taken to study of human kidney tissue, serum/plasma, urine, and animal models of hypertension.

CRITICAL ISSUES

Redox proteomics, in which oxidative post-translational modifications can be identified in protein targets of oxidative or nitrosative stress, has not been very extensively pursued in this set of pathologies.

FUTURE DIRECTIONS

Proteomics studies of kidney and related tissues have relevance to chronic kidney disease, and redox proteomics, in particular, represents an under-exploited toolkit for identification of novel biomarkers in this commonly occurring pathology.

The glomerular proteome in a model of chronic kidney disease

Adequate kidney function is crucial in sustaining vertebrate homeostasis. Certain diseases can diminish renal function and lead to end-stage renal disease. Diabetes mellitus and hypertension are the main causes of glomerulosclerosis and albuminuria in adults. The molecular mechanisms that trigger these maladaptive changes are still unsatisfyingly described. We previously introduced 2-D DIGE in combination with focused tissue isolation methods to analyze protein expression in glomeruli. Glomeruli, the crucial compartments in albuminuric renal diseases, were extracted using magnetic particles from subtotally nephrectomized FVB mice (n = 6); this 5/6 nephrectomy in FVB mice is a model of chronic kidney disease. Analysis of protein expression levels from glomerular protein lysates was performed using 2-D DIGE and compared with glomerular protein lysates from mice that underwent sham surgery. The comparison of about 2100 detectable spots between both groups revealed 48 protein spots that showed significant differential expression. Of those, 33 proteins could be identified using nanoLC-ESI MS. The metalloproteinase meprin 1 alpha, the beta galactoside-binding-lectin galectin-1 and dimethylarginine dimethylaminohydrolase 1, a key enzyme in NO metabolism, were found to be differentially regulated, thus implying a role in the pathogenesis and pathophysiology of progressive kidney disease. In conclusion, 2-D DIGE protein analysis of smallest sample sizes from specific organ compartments provides focused protein expression results, which help in gaining an understanding of the molecular mechanisms of chronic kidney disease.

Human kidney glomerulus proteome and biomarker discovery of kidney diseases

The kidney glomerulus is the site of plasma filtration and production of primary urine in the kidney. The structure not only plays a pivotal role in ultrafiltration of plasma into urine but also is the locus of kidney diseases progressing to chronic renal failure. Patients afflicted with these glomerular diseases frequently progress to irreversible loss of renal function and inevitably require replacement therapies. The diagnosis and treatment of glomerular diseases are now based on clinical manifestations, urinary protein excretion level, and renal pathology of needle biopsy specimens. The molecular mechanisms underlying the progression of glomerular diseases are still obscure despite a great number of clinical and experimental studies. Proteomics is a particularly promising approach for the discovery of proteins relevant to physiological and pathophysiological processes, and has been recently employed in nephrology. Although until now most efforts of proteomic analysis have been conducted with urine, the biological fluid that is easily collected without invasive procedures, proteomic analysis of the glomerulus, the tissue most proximal to the disease loci, is the most straightforward approach. In this review, we attempt to outline the current status of clinical proteomics of the glomerulus and provide a perspective of protein biomarker discovery of glomerular diseases.

Bioinformatic challenges in targeted proteomics

Selected reaction monitoring mass spectrometry is an emerging targeted proteomics technology that allows for the investigation of complex protein samples with high sensitivity and efficiency. It requires extensive knowledge about the sample for the many parameters needed to carry out the experiment to be set appropriately. Most studies today rely on parameter estimation from prior studies, public databases, or from measuring synthetic peptides. This is efficient and sound, but in absence of prior data, de novo parameter estimation is necessary. Computational methods can be used to create an automated framework to address this problem. However, the number of available applications is still small. This review aims at giving an orientation on the various bioinformatical challenges. To this end, we state the problems in classical machine learning and data mining terms, give examples of implemented solutions and provide some room for alternatives. This will hopefully lead to an increased momentum for the development of algorithms and serve the needs of the community for computational methods. We note that the combination of such methods in an assisted workflow will ease both the usage of targeted proteomics in experimental studies as well as the further development of computational approaches.

Proteomic analysis indicates altered expression of plasma proteins in a rat nephropathy model

BACKGROUND

Minimal-change nephrotic syndrome is an idiopathic disease in which protein leaks through podocytes into the urine. We used proteomic tools to examine differences of plasma protein expression in healthy rats and rats with doxorubicin-induced nephropathy treated with or without prednisone.

METHODS

Healthy three-month-old Sprague-Dawley male rats were randomly chosen for one injection of doxorubicin (5.5 mg/kg) through the caudal vein to induce nephropathy (n = 50) or the same volume of saline (control, n = 20). After 1 week, 25 rats in the nephropathy group received topical prednisone (5.5 mg/kg/day) for 21 days and another 25 rats (untreated nephropathy) and the control rats received topical water. At 4 weeks, protein chips generated from rat plasma samples were analyzed by surface enhanced laser desorption/ionization-time of flight mass spectrometry (SELDI-TOF-MS) to obtain mass-to-charge ratios (m/z) of proteins of 2-50 kDa.

RESULTS

Relative to control rats, untreated nephropathic rats had four significantly higher and seven significantly lower m/z peaks. Prednisone treatment significantly normalized the intensities of peaks 9069 and 15005 (which correspond to cortexin-1 and interleukin-17A, respectively, according to Swiss Prot database) by increasing the expression of 9069 but reducing expression of 15005.

CONCLUSION

Significant differences in plasma proteins can be identified by proteomic analysis using SELDI-TOF-MS in a rat model of nephropathy.

Proteomics and systems biology for understanding diabetic nephropathy

Like many diseases, diabetic nephropathy is defined in a histopathological context and studied using reductionist approaches that attempt to ameliorate structural changes. Novel technologies in mass spectrometry-based proteomics have the ability to provide a deeper understanding of the disease beyond classical histopathology, redefine the characteristics of the disease state, and identify novel approaches to reduce renal failure. The goal is to translate these new definitions into improved patient outcomes through diagnostic, prognostic, and therapeutic tools. Here, we review progress made in studying the proteomics of diabetic nephropathy and provide an introduction to the informatics tools used in the analysis of systems biology data, while pointing out statistical issues for consideration. Novel bioinformatics methods may increase biomarker identification, and other tools, including selective reaction monitoring, may hasten clinical validation.

Systems biology of kidney diseases

Kidney diseases manifest in progressive loss of renal function, which ultimately leads to complete kidney failure. The mechanisms underlying the origins and progression of kidney diseases are not fully understood. Multiple factors involved in the pathogenesis of kidney diseases have made the traditional candidate gene approach of limited value toward full understanding of the molecular mechanisms of these diseases. A systems biology approach that integrates computational modeling with large-scale data gathering of the molecular changes could be useful in identifying the multiple interacting genes and their products that drive kidney diseases. Advances in biotechnology now make it possible to gather large data sets to characterize the role of the genome, epigenome, transcriptome, proteome, and metabolome in kidney diseases. When combined with computational analyses, these experimental approaches will provide a comprehensive understanding of the underlying biological processes. Multiscale analysis that connects the molecular interactions and cell biology of different kidney cells to renal physiology and pathology can be utilized to identify modules of biological and clinical importance that are perturbed in disease processes. This integration of experimental approaches and computational modeling is expected to generate new knowledge that can help to identify marker sets to guide the diagnosis, monitor disease progression, and identify new therapeutic targets.

Comparison of human glomerulus proteomic profiles obtained from low quantities of samples by different mass spectrometry with the comprehensive database

BACKGROUND

We have previously constructed an in-depth human glomerulus proteome database from a large amount of sample for understanding renal disease pathogenesis and aiding the biomarker exploration. However, it is usually a challenge for clinical research to get enough tissues for large-scale proteomic characterization. Therefore, in this study, we focused on high-confidence proteomics analysis on small amounts of human glomeruli comparable to those obtained from biopsies using different mass spectrometers and compared these results to the comprehensive database.

RESULTS

One microgram of human glomerular protein digest was analyzed each on five LC- combined mass spectrometers (LIT-TOF, LTQ-Orbitrap, Q-TOF, LIT and MALDI-TOF/TOF) yielding 139, 185, 94, 255 and 108 proteins respectively identified with strict criteria to ensure high confidence (> 99%) and low false discovery rate (FDR) (< 1%). An integrated profile of 332 distinct glomerular proteins was subsequently generated without discerned bias due to protein physicochemical properties (pI and MW), of which around 60% were detected commonly by more than two LC-MS/MS platforms. Comparative analysis with the comprehensive database demonstrated 14 proteins uniquely identified in this study and more than 70% of identified proteins in small datasets were concentrated to the top abundant 500 in the comprehensive database which consists of 2775 non-redundant proteins.

CONCLUSION

This study showed representative human glomerulus proteomic profiles obtained from biopsies through analysis of comparable amounts of samples by different mass spectrometry. Our results implicated that high abundant proteins are more likely to be reproducibly identified in multiple mass spectrometers runs and different mass spectrometers. Furthermore, many podocyte essential proteins such as nephrin, podocin, podocalyxin and synaptopodin were also identified from the small samples in this study. Bioinformatic enrichment analysis results extended our understanding of the major glomerular proteins about their subcellular distributions and functions. The present study indicated that the proteins localized in certain cellular compartments, such as actin cytoskeleton, mitochondrial matrix, cell surface, basolateral plasma membrane, contractile fiber, proteinaceous extracellular matrix and adherens junction, represent high abundant glomerular proteins and these subcellular structures are also highly significantly over-represented in the glomerulus compared to the whole human background.

Renal fibrosis and proteomics: current knowledge and still key open questions for proteomic investigation

Renal tubulo-interstitial fibrosis is a non-specific process, representing the final common pathway for all kidney diseases, irrespective of their initial cause, histological injury, or etiology, leading to gradual expansion of the fibrotic mass which destroys the normal structure of the tissue and results in organ dysfunction and, ultimately, in end-stage organ failure. Proteomic studies of the fibrotic pathophysiological mechanisms have been performed in cell cultures, animal models and human tissues, addressing some of the key issues. This article will review proteomic contribution to the raising current knowledge on renal fibrosis biology and also mention seminal open questions to which proteomic techniques and proteomists could fruitfully contribute.

Toward quantitative proteomics of organ substructures: implications for renal physiology

Organs are complex structures that consist of multiple tissues with different levels of gene expression. To achieve comprehensive coverage and accurate quantitation data, organs ideally should be separated into morphologic and/or functional substructures before gene or protein expression analysis. However, because of complex morphology and elaborate isolation protocols, to date this often has been difficult to achieve. Kidneys are organs in which functional and morphologic subdivision is especially important. Each subunit of the kidney, the nephron, consists of more than 10 subsegments with distinct morphologic and functional characteristics. For a full understanding of kidney physiology, global gene and protein expression analyses have to be performed at the level of the nephron subsegments; however, such studies have been extremely rare to date. Here we describe the latest approaches in quantitative high-accuracy mass spectrometry-based proteomics and their application to quantitative proteomics studies of the whole kidney and nephron subsegments, both in human beings and in animal models. We compare these studies with similar studies performed on other organ substructures. We argue that the newest technologies used for preparation, processing, and measurement of small amounts of starting material are finally enabling global and subsegment-specific quantitative measurement of protein levels in the kidney and other organs. These new technologies and approaches are making a decisive impact on our understanding of the (patho)physiological processes at the molecular level.

Proteomics analysis reveals diabetic kidney as a ketogenic organ in type 2 diabetes

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease. To date, the molecular mechanisms of DN remain largely unclear. The present study aimed to identify and characterize novel proteins involved in the development of DN by a proteomic approach. Proteomic analysis revealed that 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA) synthase 2 (HMGCS2), the key enzyme in ketogenesis, was increased fourfold in the kidneys of type 2 diabetic db/db mice. Consistently, the activity of HMGCS2 in kidneys and 24-h urinary excretion of the ketone body β-hydroxybutyrate (β-HB) were significantly increased in db/db mice. Immunohistochemistry, immunofluorescence, and real-time PCR studies further demonstrated that HMGCS2 was highly expressed in renal glomeruli of db/db mice, with weak expression in the kidneys of control mice. Because filtered ketone bodies are mainly reabsorbed in the proximal tubules, we used RPTC cells, a rat proximal tubule cell line, to examine the effect of the increased level of ketone bodies. Treating cultured RPTC cells with 1 mM β-HB significantly induced transforming growth factor-β1 expression, with a marked increase in collagen I expression. β-HB treatment also resulted in a marked increase in vimentin protein expression and a significant reduction in E-cadherin protein levels, suggesting an enhanced epithelial-to-mesenchymal transition in RPTCs. Collectively, these findings demonstrate that diabetic kidneys exhibit excess ketogenic activity resulting from increased HMGCS2 expression. Enhanced ketone body production in the diabetic kidney may represent a novel mechanism involved in the pathogenesis of DN.

Proteomics database in chronic kidney disease

Databases which are useful for proteomic analysis of human kidney tissue and urine have been discussed in this article. Integration of the gene-centric and protein-centric general databases with those of human kidney tissue and urine proteomes may open a new window for research in nephrology. Proteins present in the kidney and urine provide basic tools for investigation of kidney function and disease. By comparing such databases between the healthy and diseased populations, we may be able to identify the following: proteins involved in the development of renal disease, proteins involved in progression of CKD, or new biomarker candidate proteins for either the development of renal disease or the progression of CKD.

Functional proteomic analysis of experimental autoimmune myocarditis-induced chronic heart failure in the rat

Experimental autoimmune myocarditis (EAM)-induced heart failure in rats is used to study the pathogenesis of heart failure. Based on a proteomic analysis of soluble (S) and membranous (M) fractions extracted from ventricles of rats with a stable chronic form of EAM-induced heart failure, we assessed changes in protein levels and their correlation to heart functions to gain insights into the pathogenesis and to explore new targets for the treatment of heart failure. Proteins were separated by two-dimensional gel electrophoresis and silver stained spots were analyzed. In the S-fraction, 274+/-3 spots were detected in the normal (N)-group and 273+/-6 in the heart failure (HF)-group. In the HF-group, 26 of the spots were increased and 15 were decreased in intensity. In the M-fraction, 277+/-3 spots were detected in the N-group and 277+/-2 in the HF-group, with 20 spots increased and 10 decreased in intensity. We analyzed relationships between the expression of these proteins and 11 parameters of heart function, and found all the significantly changed spots to correlate with at least one of the parameters. We analyzed 49 spots that correlated with over 9 parameters of heart function using mass spectrometry, and identified 15 as proteins with increased expression including glucose regulated protein (GRP)78, an endoplasmic-stress related protein, and heat shock protein (HSP)90beta, a molecular chaperone, and 4 spots as proteins with decreased expression. It is suggested that in the heart failure model, GRP78 and HSP90beta play a role in the protection or deterioration of the heart and may be new targets for treatment.

Two-dimensional difference gel electrophoresis urinary proteomic profile in the search of nonimmune chronic allograft dysfunction biomarkers

INTRODUCTION

Despite advances in therapeutics, graft loss associated with chronic allograft dysfunction (CAD) remains high. Urinary proteomic analysis is a noninvasive method that could be used to detect and evaluate CAD in renal transplant recipients. This study was aimed to establish the normal proteome map of stable transplant patients and to validate the utility of two-dimensional difference gel electrophoresis (2DE-DIGE) in identifying new candidates as urinary biomarkers of CAD.

METHODS

Morning spot urine samples that were collected from kidney transplant recipients with biopsy-proven interstitial fibrosis and tubular atrophy (IFTA) stages 0-I-II/III (n=8/group) under immunosuppressive treatment with tacrolimus plus mycophenolate with or without prednisone. 2DE silver staining and mass spectrometry analyses were used to establish the normal proteome map, and 2DE-DIGE and mass spectrometry were used to identify proteins exhibiting differential abundance.

RESULTS AND CONCLUSIONS

This study defines the normal proteome of stable renal transplant patients, which is composed of several plasma proteins, as well as of immunologic proteins that are probably specific to transplant recipients. The 2DE-DIGE study showed 19 proteins with differential concentrations, depending on the IFTA histologic score. These 19 proteins could be used as urinary biomarkers of the severity of IFTA in renal transplant recipients.

A gel-based reference map of the porcine hepatocyte proteome

The overall goal of our research is to characterize and identify gene expression profiles of porcine hepatic cells. In this study, we have prepared two-dimensional electrophoresis maps of cytosol and membrane fractions from freshly prepared hepatocytes which were pooled from three crossbred pigs (35-69kg). Following isoelectric focusing with three pH range immobilized pH gradient strips (pH 3-6, 5-8 and 7-10) and staining the second dimension gels with colloidal Coomassie blue, 728 protein spots were picked and digested with trypsin. Extracted tryptic peptides were initially subjected to matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF-MS) analysis for identification of proteins by peptide mass fingerprinting (PMF). Proteins which were not identified by PMF were analyzed by liquid chromatography-tandem MS. Utilizing publicly available databases [NCBInr, Swiss Prot and expressed sequence tags (EST)], 648 proteins were identified. Of those, 282 were unique proteins and greater than 90% of proteins spots contained single proteins. These data represent the first comprehensive proteomic analysis of porcine hepatocytes and will provide a database for future investigations of endocrine regulation of gene expression and metabolic processes in vitro.

Comprehensive analysis of the mouse renal cortex using two-dimensional HPLC - tandem mass spectrometry

Background

Proteomic methodologies increasingly have been applied to the kidney to map the renal cortical proteome and to identify global changes in renal proteins induced by diseases such as diabetes. While progress has been made in establishing a renal cortical proteome using 1-D or 2-DE and mass spectrometry, the number of proteins definitively identified by mass spectrometry has remained surprisingly small. Low coverage of the renal cortical proteome as well as our interest in diabetes-induced changes in proteins found in the renal cortex prompted us to perform an in-depth proteomic analysis of mouse renal cortical tissue.

Results

We report a large scale analysis of mouse renal cortical proteome using SCX prefractionation strategy combined with HPLC – tandem mass spectrometry. High-confidence identification of ~2,000 proteins, including cytoplasmic, nuclear, plasma membrane, extracellular and unknown/unclassified proteins, was obtained by separating tryptic peptides of renal cortical proteins into 60 fractions by SCX prior to LC-MS/MS. The identified proteins represented the renal cortical proteome with no discernible bias due to protein physicochemical properties, subcellular distribution, biological processes, or molecular function. The highest ranked molecular functions were characteristic of tubular epithelium, and included binding, catalytic activity, transporter activity, structural molecule activity, and carrier activity. Comparison of this renal cortical proteome with published human urinary proteomes demonstrated enrichment of renal extracellular, plasma membrane, and lysosomal proteins in the urine, with a lack of intracellular proteins. Comparison of the most abundant proteins based on normalized spectral abundance factor (NSAF) in this dataset versus a published glomerular proteome indicated enrichment of mitochondrial proteins in the former and cytoskeletal proteins in the latter.

Conclusion

A whole tissue extract of the mouse kidney cortex was analyzed by an unbiased proteomic approach, yielding a dataset of ~2,000 unique proteins identified with strict criteria to ensure a high level of confidence in protein identification. As a result of extracting all proteins from the renal cortex, we identified an exceptionally wide range of renal proteins in terms of pI, MW, hydrophobicity, abundance, and subcellular location. Many of these proteins, such as low-abundance proteins, membrane proteins and proteins with extreme values in pI or MW are traditionally under-represented in 2-DE-based proteomic analysis.

An open-source representation for 2-DE-centric proteomics and support infrastructure for data storage and analysis

BACKGROUND

In spite of two-dimensional gel electrophoresis (2-DE) being an effective and widely used method to screen the proteome, its data standardization has still not matured to the level of microarray genomics data or mass spectrometry approaches. The trend toward identifying encompassing data standards has been expanding from genomics to transcriptomics, and more recently to proteomics. The relative success of genomic and transcriptomic data standardization has enabled the development of central repositories such as GenBank and Gene Expression Omnibus. An equivalent 2-DE-centric data structure would similarly have to include a balance among raw data, basic feature detection results, sufficiency in the description of the experimental context and methods, and an overall structure that facilitates a diversity of usages, from central reposition to local data representation in LIMs systems.

RESULTS & CONCLUSION

Achieving such a balance can only be accomplished through several iterations involving bioinformaticians, bench molecular biologists, and the manufacturers of the equipment and commercial software from which the data is primarily generated. Such an encompassing data structure is described here, developed as the mature successor to the well established and broadly used earlier version. A public repository, AGML Central, is configured with a suite of tools for the conversion from a variety of popular formats, web-based visualization, and interoperation with other tools and repositories, and is particularly mass-spectrometry oriented with I/O for annotation and data analysis.

In-depth proteomic profiling of the normal human kidney glomerulus using two-dimensional protein prefractionation in combination with liquid chromatography-tandem mass spectrometry

The kidney glomerulus plays a pivotal role in ultrafiltration of plasma into urine and also is the locus of kidney disease progressing to chronic renal failure. We have focused proteomic analysis on the glomerulus that is most proximal to the disease locus. In the present study, we aimed to provide a confident, in-depth profiling of the glomerulus proteome. The glomeruli were highly purified from the kidney cortex from a male, 68-year-old patient who underwent nephroureterectomy due to ureter carcinoma. The patient was normal in clinical examinations including serum creatinine and urea levels and liver function, and did not receive any chemotherapy and radiotherapy. The cortical tissue was histologically normal, and no significant deposition of immunoglobulins and complement C3 was observed. We employed a novel strategy of protein separation using 1D (SDS-PAGE) and 2D (solution-phase IEF in combination with SDS-PAGE) prefractionation prior to the shotgun analysis with LC-MS/MS. The protein prefractionation produced 90 fractions, and eventually provided a confident set of identified proteins consisting of 6686 unique proteins (3679 proteins with two or more peptide matches and 3007 proteins with one peptide match), representing 2966 distinct genes. All the identified proteins were annotated and classified in terms of molecular function and biological process, compiled into 1D and 2D protein arrays, consisting of 15 and 75 sections, corresponding to the protein fractions which were defined by MW and pI range, and deposited on a Web-based database (http://www.hkupp.org). The most remarkable feature of the glomerulus proteome was a high incidence of identification of cytoskeleton-related proteins, presumably reflecting the well-developed, cytoskeletal organization of glomerular cells related to their physiological functions.

THE HUPO Human Plasma Proteome Project

The Human Proteomics Organization (HUPO) Human Plasma Proteome Project (PPP) is a prominent example of the inherently collaborative nature of the overall community effort to characterize the proteome of humans in health and disease. The PPP Pilot Phase, called "Exploring the Human Plasma Proteome", engaged 55 laboratories, four technical committees, and vendors and sponsors on an international scale. Among other outcomes, the PPP generated a Core Dataset of 3020 proteins identified with two or more peptides, fully accessible at EBI/PRIDE, ISB/PeptideAtlas, and University of Michigan websites, a rich resource for follow-on analyses. The PPP provided extensive annotation, correlation of number of peptides with protein concentrations measured by immunoassay, an algorithm for choice of a representative protein for multiple proteins matching a given peptide, and independent analyses from the raw spectra. The next phase of the PPP will emphasize standardized procedures for specimen handling, potent new technology platforms for discovery and for targeted proteomics, and robust informatics efforts, including comparative analyses of other biofluids.

Proteomic analysis defines altered cellular redox pathways and advanced glycation end-product metabolism in glomeruli of db/db diabetic mice

To attain a profile of protein expression during diabetes, we applied proteomic analysis to glomeruli of 160-day-old db/db diabetic and db/m nondiabetic mice. Glomerular proteins were extracted and separated by two-dimensional gel electrophoresis to construct a proteome map. Matrix-assisted laser desorption and ionization-time of flight mass spectrometry and peptide mass fingerprinting were used to identify 190 proteins. Of 105 analyzed spots, expression of 40 proteins, including the antioxidative enzymes peroxiredoxin 1 and 3, glutathione peroxidase 1, and SOD-1, was increased with diabetes, suggesting an adaptive response to oxidative stress associated with this diabetic model. However, activity of glutathione peroxidase and SOD was unaltered in glomeruli of diabetic mice. Expression of glyoxalase I was increased in glomeruli of diabetic mice. Because the cofactor for glyoxalase I, glutathione, is decreased in renal cortex of db/db mice, renal cortical glyoxalase I activity was measured in vitro with fixed amounts of exogenous glutathione. Glyoxalase I activity was decreased in renal cortex of db/db mice. These data indicate that diabetes-induced decreases in glyoxalase I activity are likely to be due to glutathione-dependent and -independent mechanisms and that increased expression of glyoxalase I may represent an insufficient adaptive response to increased methylglyoxal formation.

Diabetes-induced changes in the renal cortical proteome assessed with two-dimensional gel electrophoresis and mass spectrometry

To understand the spectrum of proteins affected by diabetes and to characterize molecular functions and biological processes they control, we analyzed the renal cortical proteome of db/db mice using 2-DE combined with MALDI-TOF, MALDI-TOF/TOF, and LC-MS/MS. This approach yielded 278 high confidence identifications whose expression levels were significantly increased or decreased >two-fold by diabetes, of which 170 mapped to gene identifiers representing 147 nonredundant proteins. Gene Ontology classification demonstrated that 80% of these proteins modulated physiological functions, 55% involved metabolism, approximately 25% involved carboxylic and organic acid metabolism, 14% involved biosynthesis or catabolism, and 12% involved fatty acid metabolism. Predominant molecular functions were catalytic (61%), oxidoreductase (20%), and transferase (17%) activities, and nucleotide and ATP binding (11-15%). Twenty eight percent of the proteins identified as significantly altered by diabetes were mitochondrial proteins. The top-ranked network described by Ingenuity Pathway Analysis indicated PPARalpha was the most common node of interaction for the numerous enzymes whose expression levels were influenced by diabetes. These differentially regulated proteins create a foundation for a systems biology exploration of molecular mechanisms underlying the pathophysiology of diabetic nephropathy.

Proteomics in renal research

Proteomic technologies are used with increasing frequency in the renal community. In this review, we highlight the use in renal research of a number of available techniques including two-dimensional gel electrophoresis, liquid chromatography/mass spectrometry, surface-enhanced laser desorption/ionization, capillary electrophoresis/mass spectrometry, and antibody and tissue arrays. These techniques have been used to identify proteins or changes in proteins specific to regions of the kidney or associated with renal diseases or toxicity. They have also been used to examine protein expression changes and posttranslational modifications of proteins during signaling. A number of studies have used proteomic methodologies to look for diagnostic biomarkers in body fluids. The rapid rate of development of the technologies along with the combination of classic physiological and biochemical techniques with proteomics will enable new discoveries.

Novel approaches to analyse glomerular proteins from smallest scale murine and human samples using DIGE saturation labelling

Loss of renal function is often associated with the injury of kidney glomeruli. It is therefore necessary to understand the mechanisms leading to progressive glomerular diseases; this may be addressed using proteomics. Until now, however, analysis of the glomeruli proteome using 2-DE has been technically hampered by low protein yields from scarce samples. To circumvent this problem, we developed a procedure which allows the human and mouse glomeruli proteome to be analysed. In this study, two different approaches were used to isolate mouse and human glomerular protein from kidney cortex. Mouse glomeruli were extracted by embolisation magnetic beads into the glomerular capillaries. Laser capture microdissection (LCM) was utilised to harvest glomeruli from human biopsy material. Human and murine samples were analysed using a fluorescence saturation labelling technique. Using 3 microg mouse glomerular protein a total of 2900 spots were resolved for differential proteome analysis. Moreover, it was also demonstrated for the first time that only ten glomeruli (0.5 microg) picked by LCM from a slide of a human kidney biopsy material were sufficient to visualise 900 spots. This novel strategy paves the way for future experiments aimed at investigating functional proteomics of glomerular diseases in humans and in mice.

Gene expression profiling analysis in nephrology: towards molecular definition of renal disease

The increase in progressive kidney disease, resulting in a constantly rising prevalence of endstage renal disease (ESRD), urgently warrants the development of more effective strategies to diagnose, prevent, and intervene in renal disease. Histological information obtained by renal biopsies (RBx) is a cornerstone of the current management of kidney disease. Renal tissue can provide critical information on the disease process not available by nontissue-based approaches. However, insight gained by conventional histopathology remains limited and additional strategies to define renal disease on a molecular level are required. The sequencing of the human genome, together with recent advances in genome-wide profiling techniques, has provided the framework for a comprehensive analysis of renal disease-associated transcriptional programs. In this review, strategies to apply these technological advances towards the analysis of RBx will be described, with special emphasis on their potential impact on clinical management, but also on their inherent limitations. Finally, an outlook towards the emerging proteomic studies of renal disease will be given.

SPLASH: Systematic proteomics laboratory analysis and storage hub

In the field of proteomics, the increasing difficulty to unify the data format, due to the different platforms/instrumentation and laboratory documentation systems, greatly hinders experimental data verification, exchange, and comparison. Therefore, it is essential to establish standard formats for every necessary aspect of proteomics data. One of the recently published data models is the proteomics experiment data repository [Taylor, C. F., Paton, N. W., Garwood, K. L., Kirby, P. D. et al., Nat. Biotechnol. 2003, 21, 247-254]. Compliant with this format, we developed the systematic proteomics laboratory analysis and storage hub (SPLASH) database system as an informatics infrastructure to support proteomics studies. It consists of three modules and provides proteomics researchers a common platform to store, manage, search, analyze, and exchange their data. (i) Data maintenance includes experimental data entry and update, uploading of experimental results in batch mode, and data exchange in the original PEDRo format. (ii) The data search module provides several means to search the database, to view either the protein information or the differential expression display by clicking on a gel image. (iii) The data mining module contains tools that perform biochemical pathway, statistics-associated gene ontology, and other comparative analyses for all the sample sets to interpret its biological meaning. These features make SPLASH a practical and powerful tool for the proteomics community.

Proteomics and diabetic nephropathy

Diabetes mellitus is acknowledged to be a group of metabolic diseases and heterogeneous in natural history, pathogenesis, response to treatment, and disease progression and remission. Diabetic nephropathy (DN) accounts for approximately 40% of all newly diagnosed cases of end-stage renal disease. The complexity of diabetes and its complications requires a broad-based, unbiased, scientific approach such as proteomics. Recently, proteomics (the systematic analysis of protein identity, quantity, and function) has been applied to the study of DN. Proteomic investigations into diabetic kidney disease have identified new mechanisms of diabetic renal pathology, as well as potential urinary markers of DN. Other current proteomic advances in understanding DN include identifying the role of advanced glycation end products in decreased mitochondrial respiration and also the rapid development of mass spectrometric methods for protein and peptide markers of DN development and markers to pharmacologic therapies. Proteomic analysis has only recently been applied to the study of DN, yet it has shown substantial potential.