Preliminary study of the urinary proteome in Li and Han ethnic individuals from Hainan

Biomarkers indicate changes associated with disease. Blood is relatively stable due to the homeostatic mechanisms of the body;however, urine accumulates metabolites from changes in the body, making it a better source for early biomarker discovery. The Li ethnic group is a unique minority ethnic group that has only lived on Hainan Island for approximately 5,000 years. Studies have shown that various specific genetic variations are different between the Li and Han ethnic groups. However, whether the urinary proteome between these two ethnic groups is significantly different remains unknown. In this study, differential urinary proteins were identified in the Li and Han ethnic groups using liquid chromatography tandem mass spectrometry(LC-MS/MS).In total, 1,555 urinary proteins were identified. Twenty-five of the urinary proteins were statistically significantly different, 16 of which have been previously reported to be biomarkers of many diseases, and that these significantly different proteins were caused by ethnic differences rather than random differences. Ethnic group differences may be an influencing factor in urine proteome studies and should be considered when human urine samples are used for biomarker discovery.     

Quantitative analysis of the intra- and inter-individual variability of the normal urinary proteome

Urine is a readily and noninvasively obtainable body fluid. Mass spectrometry (MS)-based proteomics has shown that urine contains thousands of proteins. Urine is a potential source of biomarkers for diseases of proximal and distal tissues but it is thought to be more variable than the more commonly used plasma. By LC-MS/MS analysis on an LTQ-Orbitrap without prefractionation we characterized the urinary proteome of seven normal human donors over three consecutive days. Label-free quantification of triplicate single runs covered the urinary proteome to a depth of more than 600 proteins. The median coefficient of variation (cv) of technical replicates was 0.18. Interday variability was markedly higher with a cv of 0.48 and the overall variation of the urinary proteome between individuals was 0.66. Thus technical variability in our data was 7.5%, whereas intrapersonal variability contributed 45.5% and interpersonal variability contributed 47.1% to total variability. Determination of the normal fluctuation of individual urinary proteins should be useful in establishing significance thresholds in biomarker studies. Our data also allowed definition of a common and abundant set of 500 proteins that were readily detectable in all studied individuals. This core urinary proteome has a high proportion of secreted, membrane, and relatively high-molecular weight proteins.     

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.     

A comprehensive map of the human urinary proteome

The study of the human urinary proteome has the potential to offer significant insights into normal physiology as well as disease pathology. The information obtained from such studies could be applied to the diagnosis of various diseases. The high sensitivity, resolution, and mass accuracy of the latest generation of mass spectrometers provides an opportunity to accurately catalog the proteins present in human urine, including those present at low levels. To this end, we carried out a comprehensive analysis of human urinary proteome from healthy individuals using high-resolution Fourier transform mass spectrometry. Importantly, we used the Orbitrap for detecting ions in both MS (resolution 60 000) and MS/MS (resolution 15 000) modes. To increase the depth of our analysis, we characterized both unfractionated as well as lectin-enriched proteins in our experiments. In all, we identified 1,823 proteins with less than 1% false discovery rate, of which 671 proteins have not previously been reported as constituents of human urine. This data set should serve as a comprehensive reference list for future studies aimed at identification and characterization of urinary biomarkers for various diseases.     

Human urine proteome analysis by three separation approaches

The urinary proteome is known to be a valuable field of study related to organ functions. There have been several extensive urine proteome studies. However, the overlapping rate among different studies is relatively low. Whether the low overlapping rate was caused by different sample sources, preparation, separation and identification methods is unknown. Moreover, low molecular mass (<10 kDa) proteins have not been studied extensively. In this report, male and female pooled urine samples were collected from healthy volunteers. The urinary proteins were acetone precipitated, separated and identified by three approaches, 1-DE plus 1-D LC/MS/MS, direct 1-D LC/MS/MS and 2-D LC/MS/MS. 1-D tricine gels were used to separate low molecular mass proteins. The tandem mass spectra of positive identifications were quality controlled both by manual validation and using advanced mass spectrum scanner software. A total of 226 urinary proteins were identified; 171 proteins were identified by proteomics approach for the first time, including 4 male-specific proteins. Twelve low molecular mass proteins were identified. Most urinary proteins had a molecular mass between 30 and 60 kDa and a pI between 4 and 10. The apparent molecular masses of many proteins were different from theoretical ones, which indicated their post-translational modification and degradation. The effects of sample preparation, separation and identification methods on the overlapping rate of different experiments are discussed.     

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.     

Serial changes in urinary proteome profile of membranous nephropathy: implications for pathophysiology and biomarker discovery

Membranous nephropathy is one of the most common causes of primary glomerular diseases worldwide. The present study adopted a gel-based proteomics approach to better understand the pathophysiology and define biomarker candidates of human membranous nephropathy using an animal model of passive Heymann nephritis (PHN). Clinical characteristics of Sprague-Dawley rats injected with rabbit anti-Fx1A antiserum mimicked those of human membranous nephropathy. Serial urine samples were collected at Days 0, 10, 20, 30, 40, and 50 after the injection with anti-Fx1A (number of rats = 6; total number of gels = 36). Urinary proteome profiles were examined using 2D-PAGE and SYPRO Ruby staining. Quantitative intensity analysis and ANOVA with Tukey post-hoc multiple comparisons revealed 37 differentially expressed proteins among 6 different time-points. These altered proteins were successfully identified by MALDI-TOF MS and classified into 6 categories: (i) proteins with decreased urinary excretion during PHN; (ii) proteins with increased urinary excretion during PHN; (iii) proteins with increased urinary excretion during PHN, but which finally returned to basal levels; (iv) proteins with increased urinary excretion during PHN, but which finally declined below basal levels; (v) proteins with undetectable levels in the urine during PHN; and (vi) proteins that were detectable in the urine only during PHN. Most of these altered proteins have functional significance in signaling pathways, glomerular trafficking, and controlling the glomerular permeability. The ones in categories (v) and (vi) may serve as biomarkers for detecting or monitoring membranous nephropathy. After normalization of the data with 24-h urine creatinine excretion, changes in 34 of initially 37 differentially expressed proteins remained statistically significant. These data underscore the significant impact of urinary proteomics in unraveling disease pathophysiology and biomarker discovery.     

Temporal variations of the postnatal rat urinary proteome as a reflection of systemic maturation

The rat kidney matures during the first 2 wk of life, suggesting that temporal variations in the urinary proteome may occur during this period. We describe the urine proteome during postnatal development in the rat and demonstrate specific proteomic changes corresponding to developmental milestones. Urine was collected from 30 rats at five postnatal (P) days of life (P1, P3, P7, P14, and >P30) by bladder aspiration. The proteome was assessed by nano-ESI-LC-MS/MS. For identification, we used stringent criteria to provide a 1% false positive rate at the peptide level. The proteins in common at each time interval decreased during postnatal maturation. When comparing all five developmental times, six proteins were ubiquitously present. We detected 14 proteins involved with cellular adhesion, structure, or proliferation and differentiation only during neonatal development. Additionally, 30 proteins were specific to adults, of which 13 originated from the prostate or seminal vesicle. This is the first MS characterization of the normal urinary proteome in early postnatal rodent development that demonstrates distinct differences correlating with different stages of tissue maturation. Further characterization of the normal urinary proteome may provide the basis for identification of urinary biomarkers of diseases of the urinary tract.     

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.     

甲氨蝶呤对大鼠尿液蛋白质组的影响

甲氨蝶呤是常见的免疫抑制剂,曾被大剂量用于治疗癌症,近年来其被小剂量用于治疗类风湿性关节炎。文中尝试研究甲氨蝶呤对大鼠尿蛋白质组的影响。大鼠口服甲氨蝶呤构造用药模型,再收集大鼠10 h内的尿液,并且采用液相色谱串联质谱(liquid chromatography tandem mass spectrometry,LC-MS/MS)分析大鼠的尿蛋白。总共鉴定到31个差异蛋白,其中7个蛋白与甲氨蝶呤药物作用和类风湿性关节炎症状有关。部分大鼠的生物学过程反映了甲氨蝶呤对机体谷胱甘肽代谢以及对JAK/STAT信号通路的影响。结果显示,尿蛋白具有反映甲氨蝶呤对大鼠机体影响的能力。对单个大鼠个体差异蛋白的分析体现出不同个体对该药物的反应有较大差异。     

HLA-DRB1-DQB1 haplotypes confer susceptibility and resistance to multiple sclerosis in Sardinia

Introduction

Genetic predisposition to multiple sclerosis (MS) in Sardinia (Italy) has been associated with five DRB1*-DQB1* haplotypes of the human leukocyte antigen (HLA). Given the complexity of these associations, an in-depth re-analysis was performed with the specific aims of confirming the haplotype associations; establishing the independence of the associated haplotypes; and assessing patients'' genotypic risk of developing MS.

Methods and Results

A transmission disequilibrium test (TDT) of the DRB1*-DQB1* haplotypes in 943 trio families, confirmed a higher than expected transmission rate (over-transmission) of the *13:03-*03:01 (OR = 2.9, P = 7.6×10⁻³), *04:05-*03:01 (OR = 2.4, P = 4.4×10⁻⁶) and *03:01-*02:01 (OR = 2.1, P = 1.0×10⁻¹⁵) haplotype. In contrast, the *16:01-*05:02 (OR = 0.5, P = 5.4×10⁻¹¹) and the *15:02-*06:01 (OR = 0.3, P = 1.5×10⁻³) haplotypes exhibited a lower than expected transmission rate (under-transmission). The independence of the transmission of each positively and negatively associated haplotype was confirmed relative to all positively associated haplotypes, and to the negatively associated *16:01-*05:02 haplotype. In patients, carriage of two predisposing haplotypes, or of protective haplotypes, respectively increased or decreased the patient''s risk of developing MS. The risk of MS followed a multiplicative model of genotypes, which was, in order of decreasing ORs: *04:05-*0301/*03:01-*02:01 (OR = 4.5); *03:01-*02:01/*03:01-*02:01 (OR = 4.1); and the *16:01-*05:02/*16:01-*0502 (OR = 0.2) genotypes. Analysis of DRB1 and DQB1 protein chain residues showed that the Val/Gly residue at position 86 of the DRB1 chain was the only difference between the protective *16:01- *15:02 alleles and the predisposing *15:01 one. Similarly, the Ala/Val residue at position 38 of the DQB1 chain differentiated the positively associated *06:02 allele and the negatively associated *05:02, *06:01 alleles.

Conclusions

These findings show that the association of specific, independent DRB1*-DQB1* haplotypes confers susceptibility or resistance to MS in the MS-prone Sardinian population. The data also supports a functional role for specific residues of the DRB1 and DQB1 proteins in predisposing patients to MS.     

Platelet-Derived Growth Factor Receptor Beta: A Novel Urinary Biomarker for Recurrence of Non-Muscle-Invasive Bladder Cancer

Non-muscle-invasive bladder cancer (NMIBC) is one of the most common malignant tumors in the urological system with a high risk of recurrence, and effective non-invasive biomarkers for NMIBC relapse are still needed. The human urinary proteome can reflect the status of the microenvironment of the urinary system and is an ideal source for clinical diagnosis of urinary system diseases. Our previous work used proteomics to identify 1643 high-confidence urinary proteins in the urine from a healthy population. Here, we used bioinformatics to construct a cancer-associated protein-protein interaction (PPI) network comprising 16 high-abundance urinary proteins based on the urinary proteome database. As a result, platelet-derived growth factor receptor beta (PDGFRB) was selected for further validation as a candidate biomarker for NMIBC diagnosis and prognosis. Although the levels of urinary PDGFRB showed no significant difference between patients pre- and post-surgery (n = 185, P>0.05), over 3 years of follow-up, urinary PDGFRB was shown to be significantly higher in relapsed patients (n = 68) than in relapse-free patients (n = 117, P<0.001). The levels of urinary PDGFRB were significantly correlated with the risk of 3-year recurrence of NMIBC, and these levels improved the accuracy of a NMIBC recurrence risk prediction model that included age, tumor size, and tumor number (area under the curve, 0.862; 95% CI, 0.809 to 0.914) compared to PDGFR alone. Therefore, we surmise that urinary PDGFRB could serve as a non-invasive biomarker for predicting NMIBC recurrence.     

Uromodulin Exclusion List Improves Urinary Exosomal Protein Identification

Advances in mass spectrometry (MS) have encouraged interest in its deployment in urine biomarker studies, but success has been limited. Urine exosomes have been proposed as an ideal source of biomarkers for renal disease. However, the abundant urinary protein, uromodulin, cofractionates with exosomes during isolation and represents a practical contaminant that limits MS sensitivity. Uromodulin depletion has been attempted but is labor- and time-intensive and may remove important protein biomarkers. We describe the application of an exclusion list (ExL) of uromodulin-related peptide ions, coupled with high-sensitivity mass spectrometric analysis, to increase the depth of coverage of the urinary exosomal proteome. Urine exosomal protein samples from healthy volunteers were subjected to tandem MS and abundant uromodulin peptides identified. Samples were run for a second time, while excluding these uromodulin peptides from fragmentation to allow identification of peptides from lower-abundance proteins. Uromodulin exclusion was performed in addition to dynamic exclusion. Results from these two procedures revealed 222 distinct proteins from conventional analysis, compared with 254 proteins after uromodulin exclusion, of which 188 were common to both methods. By unmasking a previously unidentified protein set, adding the ExL increased overall protein identifications by 29.7% to a total of 288 proteins. A fixed ExL, used in combination with conventional methods, effectively increases the depth of urinary exosomal proteins identified by MS, reducing the need for uromodulin depletion.     

A novel fluorescence-based assay for the rapid detection and quantification of cellular deoxyribonucleoside triphosphates

Current methods for measuring deoxyribonucleoside triphosphates (dNTPs) employ reagent and labor-intensive assays utilizing radioisotopes in DNA polymerase-based assays and/or chromatography-based approaches. We have developed a rapid and sensitive 96-well fluorescence-based assay to quantify cellular dNTPs utilizing a standard real-time PCR thermocycler. This assay relies on the principle that incorporation of a limiting dNTP is required for primer-extension and Taq polymerase-mediated 5–3′ exonuclease hydrolysis of a dual-quenched fluorophore-labeled probe resulting in fluorescence. The concentration of limiting dNTP is directly proportional to the fluorescence generated. The assay demonstrated excellent linearity (R² > 0.99) and can be modified to detect between ∼0.5 and 100 pmol of dNTP. The limits of detection (LOD) and quantification (LOQ) for all dNTPs were defined as <0.77 and <1.3 pmol, respectively. The intra-assay and inter-assay variation coefficients were determined to be <4.6% and <10%, respectively with an accuracy of 100 ± 15% for all dNTPs. The assay quantified intracellular dNTPs with similar results obtained from a validated LC–MS/MS approach and successfully measured quantitative differences in dNTP pools in human cancer cells treated with inhibitors of thymidylate metabolism. This assay has important application in research that investigates the influence of pathological conditions or pharmacological agents on dNTP biosynthesis and regulation.     

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 ).     

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.     

The Urine Proteome Profile Is Different in Neuromyelitis Optica Compared to Multiple Sclerosis: A Clinical Proteome Study

Objectives

Inflammatory demyelinating diseases of the CNS comprise a broad spectrum of diseases like neuromyelitis optica (NMO), NMO spectrum disorders (NMO-SD) and multiple sclerosis (MS). Despite clear classification criteria, differentiation can be difficult. We hypothesized that the urine proteome may differentiate NMO from MS.

Methods

The proteins in urine samples from anti-aquaporin 4 (AQP4) seropositive NMO/NMO-SD patients (n = 32), patients with MS (n = 46) and healthy subjects (HS, n = 31) were examined by quantitative liquid chromatography-tandem mass spectrometry (LC-MS/MS) after trypsin digestion and iTRAQ labelling. Immunoglobulins (Ig) in the urine were validated by nephelometry in an independent cohort (n = 9–10 pr. groups).

Results

The analysis identified a total of 1112 different proteins of which 333 were shared by all 109 subjects. Cluster analysis revealed differences in the urine proteome of NMO/NMO-SD compared to HS and MS. Principal component analysis also suggested that the NMO/NMO-SD proteome profile was useful for classification. Multivariate regression analysis revealed a 3-protein profile for the NMO/NMO-SD versus HS discrimination, a 6-protein profile for NMO/NMO-SD versus MS discrimination and an 11-protein profile for MS versus HS discrimination. All protein panels yielded highly significant ROC curves (AUC in all cases >0.85, p≤0.0002). Nephelometry confirmed the presence of increased Ig-light chains in the urine of patients with NMO/NMO-SD.

Conclusion

The urine proteome profile of patients with NMO/NMO-SD is different from MS and HS. This may reflect differences in the pathogenesis of NMO/NMO-SD versus MS and suggests that urine may be a potential source of biomarkers differentiating NMO/NMO-SD from MS.