Urinary proteomics for the study of genetic kidney diseases

Despite their low prevalence, genetic kidney diseases (GKD) still represent a serious health problem. They often lead to kidney failure and to the consequent need of dialysis or kidney transplant. To date, reliable diagnosis requires laborious genetic tests and/or a renal biopsy. Moreover, only scant and non-specific markers exist for prognostic purposes. Biomarkers assayed in an easily available and low-cost sample, such as urine, would be highly valuable. Urinary proteomics can provide clues related to their development through the identification of differentially expressed proteins codified by the affected genes, or other dis-regulated species, in total or fractionated urine, providing novel mechanistic insights. In this review, the authors summarize and discuss the results of the main proteomic investigations on GKD urine samples and in urinary extracellular vesicles.     

Urinary proteomics: a tool to discover biomarkers of kidney diseases

There is intense interest in applying proteomics to urine analysis in order to promote a better understanding of kidney disease processes, develop new biomarkers for diagnosis and detect early factors that contribute to end-stage renal diseases. This interest creates numerous opportunities as well as challenges. To fulfill this task, proteomics requires, in its different stages of realization, various technological platforms with high sensitivity, high throughput and large automation ability. In this review, we will give an overview of promising proteomic methods that can be used for analyzing urinary proteome and detecting biomarkers for different kidney diseases. Furthermore, we will focus on the current status and future directions in investigating kidney diseases using urinary proteomics.     

Towards standard protocols and guidelines for urine proteomics: a report on the Human Kidney and Urine Proteome Project (HKUPP) symposium and workshop, 6 October 2007, Seoul, Korea and 1 November 2007, San Francisco, CA, USA

The Human Kidney and Urine Proteome Project (HKUPP) was initiated in 2005 to promote proteomics research in the nephrology field, to better understand kidney functions as well as pathogenic mechanisms of kidney diseases, and to define novel biomarkers and therapeutic targets. This project was first approved in 2005 by the Human Proteome Organisation (HUPO) as a Kidney Disease Initiative under an umbrella of the HUPO Disease Biomarker Initiative (DBI), and more recently was approved as the HKUPP Initiative in 2007. Several sub-projects have been planned to achieve the ultimate goals. The most pressing is the establishment of "standard protocols and guidelines for urine proteome analysis". This sub-project had been extensively discussed during the first HKUPP symposium (during 6(th) HUPO Annual World Congress--October 2007, Seoul, Korea) and second workshop (during 40(th) American Society of Nephrology Renal Week--November 2007, San Francisco, CA, USA). Additional data and references have been collected after the symposium and workshop. An initial draft of standard protocols and guidelines for proteome analysis of non-proteinuric urine (urine protein excretion < or =150 mg/day) will soon be released as the first HKUPP product.     

Urinary proteomics: a tool to discover biomarkers of kidney diseases

There is intense interest in applying proteomics to urine analysis in order to promote a better understanding of kidney disease processes, develop new biomarkers for diagnosis and detect early factors that contribute to end–stage renal diseases. This interest creates numerous opportunities as well as challenges. To fulfill this task, proteomics requires, in its different stages of realization, various technological platforms with high sensitivity, high throughput and large automation ability. In this review, we will give an overview of promising proteomic methods that can be used for analyzing urinary proteome and detecting biomarkers for different kidney diseases. Furthermore, we will focus on the current status and future directions in investigating kidney diseases using urinary proteomics.     

Urinary proteomics: towards biomarker discovery, diagnostics and prognostics

During recent years, the proteomics field has moved onward to clinical applications, particularly for biomarker discovery, diagnostics and prognostics of human diseases. The urine is one of the ideal clinical samples for such applications because it is readily available in almost all patients, and its collection is very simple and non-invasive. Urinary proteomics thus becomes one of the most interesting subdisciplines in the clinical proteomics area. This article highlights and updates recent progress in the urinary proteomics field for clinical applications.     

LC/MS/MS measurement of penicillin G in bovine plasma, urine, and biopsy samples taken from kidneys of standing animals

Methods for the measurement of penicillin concentration in bovine plasma, kidney and urine were developed and validated. Detection was based on liquid chromatography/tandem mass spectrometry (LC/MS/MS). Phenethecillin was used as an internal standard. Plasma was extracted with acetonitrile using a method with a calculated limit of quantitation (LOQ) of 12 ng/mL. Kidney samples were homogenized in water and acetonitrile, then cleaned up on C18-bonded silica SPE cartridges. The LOQ of this procedure was 10 ng/g. Urine samples were diluted, filtered, and analyzed directly. The LOQ of this procedure was 63 ng/mL. The overall accuracy for plasma was 103% with coefficient of variation (CV) of 3%; for kidney, 96% and 11%, respectively, and for urine, 98% and 4%, respectively. These methods were applied to the analysis of plasma, urine, and kidney biopsy samples taken from standing animals that had been dosed with penicillin.     

Using an Isolated Rat Kidney Model to Identify Kidney Origin Proteins in Urine

The use of targeted proteomics to identify urinary biomarkers of kidney disease in urine can avoid the interference of serum proteins. It may provide better sample throughput, higher sensitivity, and specificity. Knowing which urinary proteins to target is essential. By analyzing the urine from perfused isolated rat kidneys, 990 kidney origin proteins with human analogs were identified in urine. Of these proteins, 128 were not found in normal human urine and may become biomarkers with zero background. A total of 297 proteins were not found in normal human plasma. These proteins will not be influenced by other normal organs and will be kidney specific. The levels of 33 proteins increased during perfusion with an oxygen-deficient solution compared to those perfused with oxygen. The 75 proteins in the perfusion-driven urine have a significantly increased abundance ranking compared to their ranking in normal human urine. When compared with existing candidate biomarkers, over ninety percent of the kidney origin proteins in urine identified in this study have not been examined as candidate biomarkers of kidney diseases.     

Variation in protein levels obtained from human blood cells and biofluids for platelet, peripheral blood mononuclear cell, plasma, urine and saliva proteomics

Blood cells and biofluid proteomics are emerging as a valuable tool to assess effects of interventions on health and disease. This study is aimed to assess the amount and variability of proteins from platelets, peripheral blood mononuclear cells (PBMC), plasma, urine and saliva from ten healthy volunteers for proteomics analysis, and whether protein yield is affected by prolonged fasting. Volunteers provided blood, saliva and morning urine samples once a week for 4 weeks after an overnight fast. Volunteers were fasted for a further 24 h after the fourth sampling before providing their final samples. Each 10 mL whole blood provided 400–1,500 μg protein from platelets, and 100–600 μg from PBMC. 30 μL plasma depleted of albumin and IgG provided 350–650 μg protein. A sample of morning urine provided 0.9–8.6 mg protein/dL, and a sample of saliva provided 70–950 μg protein/mL. None of these yields were influenced by the degree of fasting (overnight or 36 h). In conclusion, in contrast to the yields from plasma, platelets and PBMC, the protein yields of urine and saliva samples were highly variable within and between subjects. Certain disease conditions may cause higher or lower PBMC counts and thus protein yields, or increased urinary protein levels.     

One-step sample concentration, purification, and albumin depletion method for urinary proteomics

Workflows in urinary proteomics studies are often complex and require many steps to enrich, purify, deplete, and separate the complex mixture. Many of these methods are laborious, are time-consuming, and have the potential for error. Although individual steps of these methods have been previously studied, their downstream compatibilities with fractionation technologies such as off-gel electrophoresis have not been investigated. We developed a one-step sample preparation workflow that simultaneously (i) concentrates proteins, (ii) purifies by removing salts and other low molecular weight compounds, and (iii) depletes (albumin) from urine samples. This simple and robust workflow can be multiplexed and is compatible with a diverse range of downstream multidimensional separation technologies. Additionally, because of its high reproducibility and flexibility in processing samples with different volumes and concentrations, it has the potential to be used for standardization of urinary proteomics studies, as well as for studying other body fluids of similar complexity.     

尿液蛋白质组在膀胱癌临床诊治中的应用

膀胱癌是一种常见的泌尿系统疾病,尿细胞学检查与膀胱镜检查是膀胱癌的主要临床诊断手段,但尿细胞学检查敏感性较差,膀胱镜检查为侵入性检查,易给病人带来强烈的不适感;且膀胱癌具有易复发的特点,大部分患者必须面临频繁的检查,临床亟需发展舒适、准确的检查手段.尿液存储是膀胱的主要生理作用,尿液可以直接接触肿瘤实体,肿瘤分泌的一些蛋白质分子极可能进入尿液中,并且患者尿液样本便于足量多次收集.同时,蛋白质组技术以及尿液蛋白质组研究的快速发展,为我们利用尿液研究膀胱癌提供了便利的途径.本文系统总结了尿液蛋白质组研究的主要技术手段,重点关注膀胱癌尿液蛋白质组研究趋势和应用方向,以期为利用尿液蛋白质组研究膀胱癌提供助力.     

Optimizing a Proteomics Platform for Urine Biomarker Discovery

Biomarker discovery approaches in urine have been hindered by concerns for reproducibility and inadequate standardization of proteomics protocols. In this study, we describe an optimized quantitative proteomics strategy for urine biomarker discovery, which is applicable to fresh or long frozen samples. We used urine from healthy controls to standardize iTRAQ (isobaric tags for relative and absolute quantitation) for variation induced by protease inhibitors, starting protein and iTRAQ label quantities, protein extraction methods, and depletion of albumin and immunoglobulin G (IgG). We observed the following: (a) Absence of protease inhibitors did not affect the number or identity of the high confidence proteins. (b) Use of less than 20 μg of protein per sample led to a significant drop in the number of identified proteins. (c) Use of as little as a quarter unit of an iTRAQ label did not affect the number or identity of the identified proteins. (d) Protein extraction by methanol precipitation led to the highest protein yields and the most reproducible spectra. (e) Depletion of albumin and IgG did not increase the number of identified proteins or deepen the proteome coverage. Applying this optimized protocol to four pairs of long frozen urine samples from diabetic Pima Indians with or without nephropathy, we observed patterns suggesting segregation of cases and controls by iTRAQ spectra. We also identified several previously reported candidate biomarkers that showed trends toward differential expression, albeit not reaching statistical significance in this small sample set.With ongoing advances in mass spectrometry (MS) and proteomics technology, proteomics analysis is progressively occupying a central position in biomarker discovery platforms. Biofluids such as urine and blood are the preferred media for proteomics analysis because of their ease of collection and extensive history of use in clinical laboratory practice. Urine, in particular, is an information-rich fluid that can be collected non-invasively and in large quantities. Many urine proteins are produced or shed in the kidney and urogenital tract (1), making urine a promising proximal source of biomarkers for diseases affecting these structures.However, proteomics-based biomarker discovery in urine faces multiple challenges. Urine proteomics is complicated by low urine protein concentration, variations in pH, and high concentrations of salts and urea or other urine components that interfere with sample processing. The urine proteome can also change with individual variables such as hydration, diurnal change, diet, and physical activity as well as variation in sample collection, processing, and storage. In addition, urine proteomics shares the usual challenges of biomarker discovery in other biofluids such as throughput, cost, and the need for a reproducible and quantitative work flow.Isotopic or isobaric labeling methods to reduce variation, increase throughput, and enable quantitative analysis have been developed to address some of these challenges. One such method, isobaric tags for relative and absolute quantitation (iTRAQ)¹ (2), combines relative and absolute peptide quantification with multiplexing ability to enable an increased throughput as well as simultaneous comparison of up to eight samples within one experimental run. Variations induced by urine sample processing have been systematically evaluated for proteomics analyses using two-dimensional gel electrophoresis (3–6), differential gel electrophoresis (7), and liquid chromatography-coupled mass spectrometry (LC-MS) (5, 8, 9). However, no systematic analyses of urine sample collection and processing have been reported for iTRAQ.Before utilizing iTRAQ-based quantitative proteomics for urine biomarker discovery, we evaluated the impact of variation in several processing steps (addition of protease inhibitors, the starting protein quantities, quantity of the iTRAQ label, protein extraction methods, and depletion of abundant proteins) on iTRAQ protein identification and quantitation. Applying this optimized biomarker discovery protocol to small quantities of long frozen urine samples from the Pima longitudinal study of diabetic nephropathy, we observed patterns suggestive of segregation of cases and controls by iTRAQ spectra. We also observed trends toward differential expression in several proteins that had been identified as putative biomarkers in previous studies. However, given the small sample size, none of these proteins retained statistical significance after multiple testing correction.     

Biomarker discovery for kidney diseases by mass spectrometry

By the development of soft ionization such as matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI), mass spectrometry (MS) has become an indispensable technique to analyze proteins. The combination of protein separation and identification such as two-dimensional gel electrophoresis and MS, surface-enhanced laser desorption/ionization-MS, liquid chromatography/MS, and capillary electrophoresis/MS has been successfully applied for proteome analysis of urine and plasma to discover biomarkers of kidney diseases. Some urinary proteins and their proteolytic fragments have been identified as biomarker candidates for kidney diseases. This article reviews recent advances in the application of proteomics using MS to discover biomarkers for kidney diseases.     

Applications of urinary proteomics in biomarker discovery

Urine is an important source of biomarkers. This article reviews current advances, major challenges, and future prospects in the field of urinary proteomics. Because the practical clinical problem is to distinguish diseases with similar symptoms, merely comparing samples from patients of a particular disease to those of healthy individuals is inadequate for finding biomarkers with sufficient diagnostic power. In addition, the variation of expression levels of urinary proteins among healthy individuals and individuals under different physiological conditions adds to the difficulty in identifying biomarkers. We propose that establishing the natural variation in urinary protein expression among a healthy population can serve as a reference to help identify protein abundance changes that are caused by disease, not by individual variations or physiological changes. We also discuss that comparing protein expression levels between urine and plasma may reveal the physiological function of the kidney and that may facilitate biomarker discovery. Finally, we propose that establishing a data-sharing platform for data collection and integrating results from all urinary biomarker studies will help promote the development of urinary proteomics.     

Liver, lung and kidney homogenates used as an activation system in mutagenicity studies of airborne particles and of expectorate and urine samples from exposed workers in a coke plant

A comparison was made between lung and kidney homogenates on the one hand and liver S9 from rats on the other hand in order to compare their ability to activate promutagens. The Salmonella reversion assay was used on extracts of airborne particles from the top of coke oven batteries, and of expectorate and urine samples from exposed workers in the same coke plant. The contents of benzo[a]anthracene and benzo[a]pyrene in the different test solutions were measured by high-resolution gas chromatography/mass spectrometry. Both mutagens were detected in the filter extract and in the expectorates from the exposed workers but not in the expectorates from the control groups or in the urine samples. The liver S9 gave significantly higher mutagenicity than lung and kidney activation with both filter samples and expectorate and urine samples.     

Urinary Prognostic Biomarkers and Classification of IgA Nephropathy by High Resolution Mass Spectrometry Coupled with Liquid Chromatography

IgA nephropathy is the most common cause of primary glomerulonephritis. There are different pathologic biopsy-based scoring systems in use, but there is no consensus among nephrologists yet regarding the best classification method. Our aim was to test urine proteomics as a non-invasive method for classification of IgA nephropathy. This aim was pursued by discovering novel prognostic protein biomarkers in urine, and linking them to pathogenesis of the disease through known signaling and metabolic pathways. 13 urine samples of the patients with biopsy-proven IgA nephropathy were analyzed via two proteomics approaches: nanoflow LC-MS/MS and GeLC-MS/MS. The results of label-free quantification were subjected to multivariate statistical analysis, which could classify patients into two groups, broadly corresponding to the primary and advance stages. The proteome classification correlated well with biopsy-based scoring systems, especially endocapillary hypercellularity score of the Oxford’s classification. Differentially excreted candidate proteins were found as potential prognostic biomarkers: afamin, leucine-rich alpha-2-glycoprotein, ceruloplasmin, alpha-1-microgolbulin, hemopexin, apolipoprotein A-I, complement C3, vitamin D-binding protein, beta-2-microglobulin, and retinol-binding protein 4. Pathway analysis suggested impairment of Extra Cellular Matrix (ECM)-Receptor Interaction pathways as well as activation of complement and coagulation pathway in progression of IgA nephropathy.     

Chitinase-like proteins are candidate biomarkers for sepsis-induced acute kidney injury

Sepsis-induced acute kidney injury (AKI) is a frequent complication of critically ill patients and leads to high mortality rates. The specificity of currently available urinary biomarkers for AKI in the context of sepsis is questioned. This study aimed to discover urinary biomarkers for septic AKI by contemporary shotgun proteomics in a mouse model for sepsis and to validate these in individual urine samples of mice and human septic patients with and without AKI. At 48 h after uterine ligation and inoculation of Escherichia coli, aged mice (48 weeks) became septic. A subgroup developed AKI, defined by serum creatinine, blood urea nitrogen, and renal histology. Separate pools of urine from septic mice with and without AKI mice were collected during 12 h before and between 36-48 h after infection, and their proteome compositions were quantitatively compared. Candidate biomarkers were validated by Western blot analysis of urine, plasma, and renal tissue homogenates from individual mice, and a limited number of urine samples from human septic patients with and without AKI. Urinary neutrophil gelatinase-associated lipocalin, thioredoxin, gelsolin, chitinase 3-like protein 1 and -3 (CHI3L3) and acidic mammalian chitinase were the most distinctive candidate biomarkers selected for septic AKI. Both neutrophil gelatinase-associated lipocalin and thioredoxin were detected in urine of septic mice and increased with severity of AKI. Acidic mammalian chitinase was only present in urine of septic mice with AKI. Both urinary chitinase 3-like protein 1 and -3 were only detected in septic mice with severe AKI. The human homologue chitinase 3-like protein 1 was found to be more excreted in urine from septic patients with AKI than without. In summary, urinary chitinase 3-like protein 1 and -3 and acidic mammalian chitinase discriminated sepsis from sepsis-induced AKI in mice. Further studies of human chitinase proteins are likely to lead to additional insights in septic AKI.     

Liquid chromatographic—mass spectrometric analysis for screening of patients with cystinuria, and identification of cystine stone

Analyses of amino acids in the urine of a normal human and of patients with heterozygous and homozygous cystinuria have been carried out, using liquid chromatography—mass spectrometry with an atmospheric pressure ionization interface system. A kidney cystine stone was also analysed by this system. Very intense quasi-molecular ions ([M + H]⁺) of standard cystine, arginine, lysine and ornithine were observed on mass chromatograms as base peaks. Mass chromatograms of the urine samples from a normal human and from patients with heterozygous and homozygous cystinuria were easily distinguishable. The retention times in the mass chromatogram and mass spectrum of kidney stone cystine was almost the same as that of authentic cystine.     

Urinary proteomics in chronic kidney disease: diagnosis and risk of progression beyond albuminuria

Background

The contrast between a high prevalence of chronic kidney disease (CKD) and the low incidence of end-stage renal disease highlights the need for new biomarkers of progression beyond albuminuria testing. Urinary proteomics is a promising method, but more studies focusing on progression rate and patients with hypertensive nephropathy are needed.

Results

We analyzed urine samples with capillary electrophoresis coupled to a mass-spectrometer from 18 well characterized patients with CKD stage 4–5 (of whom six with hypertensive nephropathy) and 17 healthy controls. Classification scores based on a previously developed panel of 273 urinary peptides were calculated and compared to urine albumin dipstick results. Urinary proteomics classified CKD with a sensitivity of 0.95 and specificity of 1.00. Overall diagnostic accuracy (area under ROC curve) was 0.98, which was better than for albuminuria (0.85, p = 0.02). Results for hypertensive nephropathy were similar to other CKD diagnoses. Adding the proteomic score to an albuminuria model improved detection of rapid kidney function decline (>4 ml/min/1.73 m² per year) substantially: area under ROC curve increased from 0.762 to 0.909 (p = 0.042), and 38% of rapid progressors were correctly reclassified to a higher risk and 55% of slow progressors were correctly reclassified to a lower risk category. Reduced excretion of collagen types I–III, uromodulin, and other indicators of interstitial inflammation, fibrosis and tubular dysfunction were associated with CKD diagnosis and rapid progression. Patients with hypertensive nephropathy displayed the same findings as other types of CKD.

Conclusions

Urinary proteomic analyses had a high diagnostic accuracy for CKD, including hypertensive nephropathy, and strongly improved identification of patients with rapid kidney function decline beyond albuminuria testing.     

LC/MS/MS measurement of gentamicin in bovine plasma, urine, milk, and biopsy samples taken from kidneys of standing animals

Methods for the measurement of gentamicin concentration in several bovine tissues were developed and validated. A novel liquid chromatographic (LC) technique employed trifluoroacetic acid in the mobile phase so that all gentamicin components co-eluted. Analytes were ionized by positive-ion pneumatically assisted electrospray and detected by selected reaction monitoring (SRM) with an LC-tandem mass spectrometer (LC/MS/MS). Calibration of plasma and urine samples was based on tobramycin internal standard. Calibration of milk and kidney samples was based on external standard, due to variability of tobramycin response in these matrices. The extraction technique employed treatment with aqueous trichloroacetic acid to both precipitate protein and liberate gentamicin from the matrix. Milk samples had to be defatted by centrifugation prior to extraction. Urine samples were further cleaned up with C-18 solid phase extraction (SPE). These methods were validated for use in several residue depletion studies (reported elsewhere) to monitor the depletion of gentamicin in tissues under various dosing conditions. The plasma method was calibrated from 1 to 5000 ng/mL in two ranges, with a limit of quantitation (LOQ) in the low range calculated at 3.3 ng/mL. The milk method was calibrated from 2.5 to 2500 ng/mL with an LOQ calculated at 4.5 ng/mL. The urine method was designed for use at low levels, and was calibrated from 1 to 100 ng/mL with an LOQ of 3.8 ng/mL. The kidney method was primarily designed for analysis of small samples (approximately 100mg). This method was calibrated from 10 to 50,000 ng/g with an LOQ of 26 ng/g.