Concanavalin A-captured glycoproteins in healthy human urine

Both the urinary proteome and its glycoproteome can reflect human health status, and more directly, functions of kidney and urinary tracts. Because the high abundance protein albumin is not N-glycosylated, the urine N-glycoprotein enrichment procedure could deplete it, and urine proteome could thus provide a more detailed protein profile in addition to glycosylation information especially when albuminuria occurs in some kidney diseases. In terms of describing the details of urinary proteins, the urine glycoproteome is even a better choice than the proteome itself. Pooled urine samples from healthy volunteers were collected and acetone-precipitated for proteins. N-Linked glycoproteins enriched with concanavalin A affinity purification were separated and analyzed by SDS-PAGE-reverse phase LC/MS/MS or two-dimensional LC/MS/MS. A total of 225 urinary proteins were identified based on two-hit criteria with reliability over 97% for each peptide. Among these proteins, 94 were identified in previous urine proteome works, 150 were annotated as glycoproteins in Swiss-Prot, and 43 were predicted as glycoproteins by NetNGlyc 1.0. A number of known biomarkers and disease-related glycoproteins were identified. Because changes in protein quantity or the glycosylation status can lead to changes in the concanavalin A-captured glycoprotein profile, specific urine glycoproteome patterns might be observed for specific pathological conditions as multiplex urinary biomarkers. Knowledge of the urine glycoproteome is important in understanding kidney and body function.     

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.     

Kidney injury biomarkers and urinary creatinine variability in nominally healthy adults

Abstract

Environmental exposure diagnostics use creatinine concentrations in urine aliquots as the internal standard for dilution normalization of all other excreted metabolites when urinary excretion rate data are not available. This is a reasonable approach for healthy adults as creatinine is a human metabolite that is continually produced in skeletal muscles and presumably excreted in the urine at a stable rate. However, creatinine also serves as a biomarker for glomerular filtration rate (efficiency) of the kidneys, so undiagnosed kidney function impairment could affect this commonly applied dilution calculation. The United States Environmental Protection Agency (US EPA) has recently conducted a study that collected approximately 2600 urine samples from 50 healthy adults, aged 19–50 years old, in North Carolina in 2009–2011. Urinary ancillary data (creatinine concentration, total void volume, elapsed time between voids), and participant demographic data (race, gender, height, and body weight) were collected. A representative subset of 280 urine samples from 29 participants was assayed using a new kidney injury panel (KIP). In this article, we investigated the relationships of KIP biomarkers within and between subjects and also calculated their interactions with measured creatinine levels. The aims of this work were to document the analytical methods (procedures, sensitivity, stability, etc.), provide summary statistics for the KIP biomarkers in “healthy” adults without diagnosed disease (distribution, fold range, central tendency, variance), and to develop an understanding as to how urinary creatinine level varies with respect to the individual KIP proteins. Results show that new instrumentation and data reduction methods have sufficient sensitivity to measure KIP levels in nominally healthy urine samples, that linear regression between creatinine concentration and urinary excretion explains only about 68% of variability, that KIP markers are poorly correlated with creatinine (r² ～ 0.34), and that statistical outliers of KIP markers are not random, but are clustered within certain subjects. In addition, we interpret these new adverse outcome pathways based in vivo biomarkers for their potential use as intermediary chemicals that may be diagnostic of kidney adverse outcomes to environmental exposure.     

Dynamic changes of urinary proteins in a rat model of acute hypercoagulable state induced by tranexamic acid

The hypercoagulable state leads to the development of thrombotic diseases, but it is difficult to diagnose due to the lack of available biomarkers. This study aimed to investigate systematic changes of the urinary proteome in the acute hypercoagulable state. A rat model of the acute hypercoagulable state was induced by an antifibrinolytic agent tranexamic acid and urine samples were collected for proteomic analysis by liquid chromatography-tandem mass spectrometry. A total of 28 differential proteins were detected in the urinary proteome of the model rats, of which 12 had been previously considered as candidate biomarkers such as myoglobin, and 10 had been considered stable in healthy human urine. Of the 28 differentially expressed proteins 18 had counterparts in humans. Of these 18 proteins, 10 were members of the human core urinary proteome distributed in a variety of human tissues but concentrated in the urinary and digestive systems. Fumarylacetoacetase was verified as a potential marker of the acute hypercoagulable state by Western blot analysis. In conclusion, urine proteome analysis is a powerful approach to identify potential biomarkers of acute hypercoagulable state.     

Comparison of Plasma and Urine Biomarker Performance in Acute Kidney Injury

Background

New renal biomarkers measured in urine promise to increase specificity for risk stratification and early diagnosis of acute kidney injury (AKI) but concomitantly may be altered by urine concentration effects and chronic renal insufficiency. This study therefore directly compared the performance of AKI biomarkers in urine and plasma.

Methods

This single-center, prospective cohort study included 110 unselected adults undergoing cardiac surgery with cardiopulmonary bypass between 2009 and 2010. Plasma and/or urine concentrations of creatinine, cystatin C, neutrophil gelatinase-associated lipocalin (NGAL), liver fatty acid-binding protein (L-FABP), kidney injury molecule 1 (KIM1), and albumin as well as 15 additional biomarkers in plasma and urine were measured during the perioperative period. The primary outcome was AKI defined by AKIN serum creatinine criteria within 72 hours after surgery.

Results

Biomarkers in plasma showed markedly better discriminative performance for preoperative risk stratification and early postoperative (within 24h after surgery) detection of AKI than urine biomarkers. Discriminative power of urine biomarkers improved when concentrations were normalized to urinary creatinine, but urine biomarkers had still lower AUC values than plasma biomarkers. Best diagnostic performance 4h after surgery had plasma NGAL (AUC 0.83), cystatin C (0.76), MIG (0.74), and L-FAPB (0.73). Combinations of multiple biomarkers did not improve their diagnostic power. Preoperative clinical scoring systems (EuroSCORE and Cleveland Clinic Foundation Score) predicted the risk for AKI (AUC 0.76 and 0.71) and were not inferior to biomarkers. Preexisting chronic kidney disease limited the diagnostic performance of both plasma and urine biomarkers.

Conclusions

In our cohort plasma biomarkers had higher discriminative power for risk stratification and early diagnosis of AKI than urine biomarkers. For preoperative risk stratification of AKI clinical models showed similar discriminative performance to biomarkers. The discriminative performance of both plasma and urine biomarkers was reduced by preexisting chronic kidney disease.     

Urinary Neutrophil Gelatinase-Associated Lipocalin: A Useful Biomarker for Tacrolimus-Induced Acute Kidney Injury in Liver Transplant Patients

Tacrolimus is widely used as an immunosuppressant in liver transplantation, and tacrolimus-induced acute kidney injury (AKI) is a serious complication of liver transplantation. For early detection of AKI, various urinary biomarkers such as monocyte chemotactic protein-1, liver-type fatty acid-binding protein, interleukin-18, osteopontin, cystatin C, clusterin and neutrophil gelatinase-associated lipocalin (NGAL) have been identified. Here, we attempt to identify urinary biomarkers for the early detection of tacrolimus-induced AKI in liver transplant patients. Urine samples were collected from 31 patients after living-donor liver transplantation (LDLT). Twenty recipients developed tacrolimus-induced AKI. After the initiation of tacrolimus therapy, urine samples were collected on postoperative days 7, 14, and 21. In patients who experienced AKI during postoperative day 21, additional spot urine samples were collected on postoperative days 28, 35, 42, 49, and 58. The 8 healthy volunteers, whose renal and liver functions were normal, were asked to collect their blood and spot urine samples. The urinary levels of NGAL, monocyte chemotactic protein-1 and liver-type fatty acid-binding protein were significantly higher in patients with AKI than in those without, while those of interleukin-18, osteopontin, cystatin C and clusterin did not differ between the 2 groups. The area under the receiver operating characteristics curve of urinary NGAL was 0.876 (95% confidence interval, 0.800–0.951; P<0.0001), which was better than those of the other six urinary biomarkers. In addition, the urinary levels of NGAL at postoperative day 1 (p = 0.0446) and day 7 (p = 0.0006) can be a good predictive marker for tacrolimus-induced AKI within next 6 days, respectively. In conclusion, urinary NGAL is a sensitive biomarker for tacrolimus-induced AKI, and may help predict renal event caused by tacrolimus therapy in liver transplant patients.     

The discovery of putative urine markers for the specific detection of prostate tumor by integrative mining of public genomic profiles

Urine has emerged as an attractive biofluid for the noninvasive detection of prostate cancer (PCa). There is a strong imperative to discover candidate urinary markers for the clinical diagnosis and prognosis of PCa. The rising flood of various omics profiles presents immense opportunities for the identification of prospective biomarkers. Here we present a simple and efficient strategy to derive candidate urine markers for prostate tumor by mining cancer genomic profiles from public databases. Prostate, bladder and kidney are three major tissues from which cellular matters could be released into urine. To identify urinary markers specific for PCa, upregulated entities that might be shed in exosomes of bladder cancer and kidney cancer are first excluded. Through the ontology-based filtering and further assessment, a reduced list of 19 entities encoding urinary proteins was derived as putative PCa markers. Among them, we have found 10 entities closely associated with the process of tumor cell growth and development by pathway enrichment analysis. Further, using the 10 entities as seeds, we have constructed a protein-protein interaction (PPI) subnetwork and suggested a few urine markers as preferred prognostic markers to monitor the invasion and progression of PCa. Our approach is amenable to discover and prioritize potential markers present in a variety of body fluids for a spectrum of human diseases.     

Acute Kidney Injury Urinary Biomarker Time-Courses

Factors which modify the excretion profiles of acute kidney injury biomarkers are difficult to measure. To facilitate biomarker choice and interpretation we modelled key modifying factors: extent of hyperfiltration or reduced glomerular filtration rate, structural damage, and reduced nephron number. The time-courses of pre-formed, induced (upregulated), and filtered biomarker concentrations were modelled in single nephrons, then combined to construct three multiple-nephron models: a healthy kidney with normal nephron number, a non-diabetic hyperfiltering kidney with reduced nephron number but maintained total glomerular filtration rate, and a chronic kidney disease kidney with reduced nephron number and reduced glomerular filtration rate. Time-courses for each model were derived for acute kidney injury scenarios of structural damage and/or reduced nephron number. The model predicted that pre-formed biomarkers would respond quickest to injury with a brief period of elevation, which would be easily missed in clinical scenarios. Induced biomarker time-courses would be influenced by biomarker-specific physiology and the balance between insult severity (which increased single nephron excretion), the number of remaining nephrons (reduced total excretion), and the extent of glomerular filtration rate reduction (increased concentration). Filtered biomarkers have the longest time-course because plasma levels increased following glomerular filtration rate decrease. Peak concentration and profile depended on the extent of damage to the reabsorption mechanism and recovery rate. Rapid recovery may be detected through a rapid reduction in urinary concentration. For all biomarkers, impaired hyperfiltration substantially increased concentration, especially with chronic kidney disease. For clinical validation of these model-derived predictions the clinical biomarker of choice will depend on timing in relation to renal insult and interpretation will require the pre-insult nephron number (renal mass) and detection of hyperfiltration.     

Role of JAK/STAT signaling in neuroepithelial stem cell maintenance and proliferation in the Drosophila optic lobe

Human urine contains a large number of proteins and peptides (the urinary proteome). Global analysis of the human urinary proteome is important for understanding urinary tract diseases. Bladder cancer is the most common urological cancer with higher incidence rates in endemic areas of Blackfoot disease (BFD) in southern Taiwan. The aim of this study was to use the proteomic approach to establish urinary protein biomarkers of bladder cancer. ADAM28, identified by proteomic approaches and confirmed by Western blotting, showed significant differences compared with normal individuals, so it may be a biomarker of bladder cancer.     

运动性急性肾损伤与新型肾功能生物标志物

大强度运动中,非创伤性急性肾损伤（acute kindey injury, AKI）经常发生,表现为血尿、蛋白尿、血红蛋白尿等。一般认为,中低程度的运动性急性肾损伤是可逆的,可完全恢复。但动物实验与人类研究均发现,严重的运动性肾损伤会导致“功能性”急性肾损伤发展为“结构性”急性肾损伤,并增加慢性肾病的风险。运动性急性肾损伤对机体的潜在健康威胁已引起国内外相关领域学者的广泛关注。血清肌酐 (serum creatinine, Scr)和尿量作为肾功能的传统经典标志物,不能特异性反映早期肾损伤,而新型肾损伤标志物可进一步明确损伤的位置及严重程度。在运动领域,利用新型生物标志物进行无创性检查,识别早期运动性急性肾损伤非常必要。本文综述了反映肾小球或肾小管损伤、细胞周期停滞和肾损伤修复的新型生物标志物,着重论述了尿中性粒细胞明胶酶相关脂质运载蛋白（NGAL)和肾损伤分子-1（KIM-1)与肾功能的关系,以及长时间耐力运动、急性运动和高强度间歇阻力运动3种运动形式对肾功能的影响,旨在引起重视,精准识别风险,及时进行早干预。     

运动性急性肾损伤与新型肾功能生物标志物

大强度运动中,非创伤性急性肾损伤（acute kindey injury, AKI）经常发生,表现为血尿、蛋白尿、血红蛋白尿等。一般认为,中低程度的运动性急性肾损伤是可逆的,可完全恢复。但动物实验与人类研究均发现,严重的运动性肾损伤会导致“功能性”急性肾损伤发展为“结构性”急性肾损伤,并增加慢性肾病的风险。运动性急性肾损伤对机体的潜在健康威胁已引起国内外相关领域学者的广泛关注。血清肌酐 (serum creatinine, Scr)和尿量作为肾功能的传统经典标志物,不能特异性反映早期肾损伤,而新型肾损伤标志物可进一步明确损伤的位置及严重程度。在运动领域,利用新型生物标志物进行无创性检查,识别早期运动性急性肾损伤非常必要。本文综述了反映肾小球或肾小管损伤、细胞周期停滞和肾损伤修复的新型生物标志物,着重论述了尿中性粒细胞明胶酶相关脂质运载蛋白（NGAL)和肾损伤分子-1（KIM-1)与肾功能的关系,以及长时间耐力运动、急性运动和高强度间歇阻力运动3种运动形式对肾功能的影响,旨在引起重视,精准识别风险,及时进行早干预。     

Comparative proteomic analysis of differentially expressed proteins in the urine of reservoir hosts of leptospirosis

Rattus norvegicus is a natural reservoir host for pathogenic species of Leptospira. Experimentally infected rats remain clinically normal, yet persistently excrete large numbers of leptospires from colonized renal tubules via urine, despite a specific host immune response. Whilst persistent renal colonization and shedding is facilitated in part by differential antigen expression by leptospires to evade host immune responses, there is limited understanding of kidney and urinary proteins expressed by the host that facilitates such biological equilibrium. Urine pellets were collected from experimentally infected rats shedding leptospires and compared to urine from non-infected controls spiked with in vitro cultivated leptospires for analysis by 2-D DIGE. Differentially expressed host proteins include membrane metallo endopeptidase, napsin A aspartic peptidase, vacuolar H+ATPase, kidney aminopeptidase and immunoglobulin G and A. Loa22, a virulence factor of Leptospira, as well as the GroEL, were increased in leptospires excreted in urine compared to in vitro cultivated leptospires. Urinary IgG from infected rats was specific for leptospires. Results confirm differential protein expression by both host and pathogen during chronic disease and include markers of kidney function and immunoglobulin which are potential biomarkers of infection.     

Proteomic Analysis of Urine to Identify Breast Cancer Biomarker Candidates Using a Label-Free LC-MS/MS Approach

Introduction

Breast cancer is a complex heterogeneous disease and is a leading cause of death in women. Early diagnosis and monitoring progression of breast cancer are important for improving prognosis. The aim of this study was to identify protein biomarkers in urine for early screening detection and monitoring invasive breast cancer progression.

Method

We performed a comparative proteomic analysis using ion count relative quantification label free LC-MS/MS analysis of urine from breast cancer patients (n = 20) and healthy control women (n = 20).

Results

Unbiased label free LC-MS/MS-based proteomics was used to provide a profile of abundant proteins in the biological system of breast cancer patients. Data analysis revealed 59 urinary proteins that were significantly different in breast cancer patients compared to the normal control subjects (p<0.05, fold change >3). Thirty-six urinary proteins were exclusively found in specific breast cancer stages, with 24 increasing and 12 decreasing in their abundance. Amongst the 59 significant urinary proteins identified, a list of 13 novel up-regulated proteins were revealed that may be used to detect breast cancer. These include stage specific markers associated with pre-invasive breast cancer in the ductal carcinoma in-situ (DCIS) samples (Leucine LRC36, MAST4 and Uncharacterized protein CI131), early invasive breast cancer (DYH8, HBA, PEPA, uncharacterized protein C4orf14 (CD014), filaggrin and MMRN2) and metastatic breast cancer (AGRIN, NEGR1, FIBA and Keratin KIC10). Preliminary validation of 3 potential markers (ECM1, MAST4 and filaggrin) identified was performed in breast cancer cell lines by Western blotting. One potential marker MAST4 was further validated in human breast cancer tissues as well as individual human breast cancer urine samples with immunohistochemistry and Western blotting, respectively.

Conclusions

Our results indicate that urine is a useful non-invasive source of biomarkers and the profile patterns (biomarkers) identified, have potential for clinical use in the detection of BC. Validation with a larger independent cohort of patients is required in the following study.     

A proteomic glimpse into human ureter proteome

Urine has evolved as one of the most important biofluids in clinical proteomics due to its noninvasive sampling and its stability. Yet, it is used in clinical diagnostics of several disorders by detecting changes in its components including urinary protein/polypeptide profile. Despite the fact that majority of proteins detected in urine are primarily originated from the urogenital (UG) tract, determining its precise source within the UG tract remains elusive. In this article, we performed a comprehensive analysis of ureter proteome to assemble the first unbiased ureter dataset. Next, we compared these data to urine, urinary exosome, and kidney mass spectrometric datasets. Our result concluded that among 2217 nonredundant ureter proteins, 751 protein candidates (33.8%) were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48) that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease‐associated biomarkers such as ureter carcinoma. In addition, the ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery. All MS data have been deposited in the ProteomeXchange with identifier PXD002620 ( http://proteomecentral.proteomexchange.org/dataset/PXD002620 ).     

The excretion of lactate dehydrogenase in human urine after ingestion of aspirin

1. Cells present in normal human urine contain 5-10% of the total lactate dehydrogenase excreted. The enzyme released from these cells by ultrasonication contained a distribution of isoenzymes similar to that found in the bulk of the urine and it is suggested that these cells are the main source of urinary lactate dehydrogenase. 2. Cells were thoroughly washed before examination so it is unlikely that the enzyme found in urinary sediment was simply adsorbed. In addition, full recoveries of added lactate dehydrogenase isoenzymes LDH(1) and LDH(5) showed that adsorption did not occur. 3. Most of the cells in normal urine are of the non-squamous epithelial type and their excretion is greatly increased after the ingestion by the subject of 3g. of aspirin. The possible origin of these non-squamous cells from the kidney is discussed. 4. Starch-block electrophoresis and relative activity measurements of lactate dehydrogenase excreted after the subject had taken aspirin show that the enzymes present in urine and cells are very similar, confirming the conclusion reached above (point 1). They have slightly more M subunits than the normal, shown particularly as an increase in isoenzyme LDH(2). The isoenzyme pattern is like that of the kidney medulla and the possible reasons for this are discussed in terms of the concentration of salicylic acid in various parts of the kidney. 5. The results confirm the previous suggestion that the kidney is the main source of urinary lactate dehydrogenase.     

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.     

Profiling of lysine-acetylated proteins in human urine

A biomarker is a measurable indicator associated with changes in physiological state or disease. In contrast to the blood which is under homeostatic controls, urine reflects changes in the body earlier and more sensitively, and is therefore a better biomarker source. Lysine acetylation is an abundant and highly regulated post-translational modification. It plays a pivotal role in modulating diverse biological processes and is associated with various important diseases. Enrichment or visualization of proteins with specific post-translational modifications provides a method for sampling the urinary proteome and reducing sample complexity. In this study, we used anti-acetyllysine antibody-based immunoaffinity enrichment combined with high-resolution mass spectrometry to profile lysine-acetylated proteins in normal human urine. A total of 629 acetylation sites on 315 proteins were identified, including some very low-abundance proteins. This is the first proteome-wide characterization of lysine acetylation proteins in normal human urine. Our dataset provides a useful resource for the further discovery of lysine-acetylated proteins as biomarkers in urine.     

A stable panel comprising 18 urinary proteins in the human healthy population

Just as biomarkers specific for diseases, biomarkers indicative of healthy conditions are valuable for the early diagnosis, monitoring, and prognosis of diseases. Our study focused on discovering via proteomics a stable panel of urinary proteins in the human healthy population. Urine samples were collected three times during 4 months from 100 male and 100 female healthy donors and analyzed through four different fractionation techniques (i.e. in-gel, 2D-LC, OFFGEL, and mRP) coupled with HPLC-Chip-MS/MS. Thus, 1641 urinary proteins were identified with a high confidence, among which 70 exhibiting an intergender/day variation <0.25 were selected and matched with the previously published five largest urinary proteomes to get 56 candidate proteins. Next, a panel comprising 18 intact urinary proteins was constructed by comparing the urinary proteomes via SDS-PAGE and 2DE. Finally, such 18 urinary proteins were validated via enzyme-linked immunosorbent assay in eight healthy individuals. Most of these proteins had been related to multiple rather than to single diseases. Therefore, we surmise that this protein set could be used as a biomarker to assess the human health status. Further determinations of the normal fluctuations of the single urinary proteins in this series using samples from large numbers of healthy individuals are required prior to any application in clinical settings.