A qualitative proteome investigation of the sediment portion of human urine: Implications in the biomarker discovery process

Qualitative and quantitative proteomic and metaproteomic analyses of healthy human urine sediment

PURPOSE

The healthy human urine sediment proteome and metaproteome are investigated, to shed light on the variations of urine sediment proteins and metaproteins associated with sex and age.

EXPERIMENTAL DESIGN

Urine sediment samples are collected from 19 healthy subjects. Protein identification and quantification are performed by liquid chromatography coupled high-resolution mass spectrometry.

RESULTS

A total of 2736 human proteins were identified, which were primarily associated with inflammatory response and energy metabolism. For the metaproteome, 65 genera were identified that were primarily involved in translation and carbohydrate metabolic processes. The median biological coefficient variation of the proteome/metaproteome of human urine sediment was 0.5/0.72, similar to the proteome of human urine supernatant. In addition, sex and age were observed to affect the proteome and metaproteome of healthy human urine sediment.

CONCLUSION AND CLINICAL RELEVANCE

The healthy human urine sediment were characterized, indicating that urine sediment might represent an alternative resource for disease research in addition to urine supernatant, but the influence of sex and age must be considered in the study design process.

Comprehensive Metaproteomic Analyses of Urine in the Presence and Absence of Neutrophil-Associated Inflammation in the Urinary Tract

Inflammation in the urinary tract results in a urinary proteome characterized by a high dynamic range of protein concentrations and high variability in protein content. This proteome encompasses plasma proteins not resorbed by renal tubular uptake, renal secretion products, proteins of immune cells and erythrocytes derived from trans-urothelial migration and vascular leakage, respectively, and exfoliating urothelial and squamous epithelial cells. We examined how such proteins partition into soluble urine (SU) and urinary pellet (UP) fractions by analyzing 33 urine specimens 12 of which were associated with a urinary tract infection (UTI). Using mass spectrometry-based metaproteomic approaches, we identified 5,327 non-redundant human proteins, 2,638 and 4,379 of which were associated with SU and UP fractions, respectively, and 1,206 non-redundant protein orthology groups derived from pathogenic and commensal organisms of the urogenital tract. Differences between the SU and UP proteomes were influenced by local inflammation, supported by respective comparisons with 12 healthy control urine proteomes. Clustering analyses showed that SU and UP fractions had proteomic signatures discerning UTIs, vascular injury, and epithelial cell exfoliation from the control group to varying degrees. Cases of UTI revealed clusters of proteins produced by activated neutrophils. Network analysis supported the central role of neutrophil effector proteins in the defense against invading pathogens associated with subsequent coagulation and wound repair processes. Our study expands the existing knowledge of the urinary proteome under perturbed conditions, and should be useful as reference dataset in the search of biomarkers.

A methodological approach based on gold-nanoparticles followed by matrix assisted laser desorption ionization time of flight mass spectrometry for the analysis of urine profiling of knee osteoarthritis

The aim of this work is to develop a nanoparticle-based methodology to find out biomarkers of diagnostic for knee osteoarthritis, KOA, through the use of matrix assisted laser desorption ionization time-of-flight-based mass spectrometry profiling. Urine samples used for this study were obtained from KOA patients (42 patients), patients with prosthesis (58 patients), and controls (36 individuals) with no history of joint disease. Gold-nano particle MALDI-based urine profiling was optimized and then applied over the 136 individuals. Jaccard index and 10 different classifiers over MALDI MS datasets were used to find out potential biomarkers. Then, the specificity and sensitivity of the method were evaluated. The presence of ten m/z signals as potential biomarkers in the healthy versus non-healthy approach suggests that patients (KOA and prosthesis) are differentiable from the healthy volunteers through profiling. The automatic diagnostic study confirmed these preliminary conclusions. The sensitivity and the specificity for the urine profiling criteria here reported, achieved by the C4.5 classifier, is 97% and 69% respectively. Thus, it is confirmed the utility of the method proposed in this work as an additional fast, non-expensive and robust test for KOA diagnostic. When the proposed method is compared with those used in common practice it is found that sensitivity is the highest, thus with a low false negative rate for diagnostic KOA patients in the population studied. Specificity is lower but in the range accepted for diagnostic objectives.

Urine sample preparation in 96-well filter plates to characterize inflammatory and infectious diseases of the urinary tract

Urine has been an important body fluid source for diagnostic and prognostic biomarkers of diseases for a long time. Technological advances during the last two decades have enabled a fundamental shift from the discovery of candidate protein biomarkers using single-assay platforms to highly parallel liquid chromatography tandem mass spectrometry (LC-MS/MS)-based proteomic analysis platforms. MS/MS-based approaches such as multiple reaction monitoring (MRM) are also being used increasingly for targeted protein biomarker validation. In large part due to the fact that the majority of protein in voided urine is soluble, such studies have focused on the analysis of urine supernatants, whereas the pellets were discarded after centrifugal sedimentation. Urine sediments are of particular value in the analysis of urinary tract infections (UTI). The LC-MS/MS methods now have sufficient resolving power and sensitivity to survey metaproteomes--the entirety of proteins derived from multiple organisms that interact with each other in mutualistic or antagonistic fashion. Challenges of proteomic analysis of urine include the high dynamic range of protein abundance, high levels of protein post-translational modifications, and high quantities of natural protease inhibitors. Recently, a robust and scalable workflow that can parallelize the processing of multiple urinary supernatant and sediment samples was developed and validated in our lab. This method utilizes 96-well format filter-aided sample preparation (96FASP) strategy and was shown to successfully identify large numbers of proteins from urine samples. Processing 10-50 µg total protein in single experiment, LC-MS/MS with a Q-Exactive mass spectrometer resulted in more than 1,100 distinct human protein identifications from urine supernatants, and around 400 microbial and 1,400 human protein identifications from urine sediments. The surveys are a rich data resource not only for biomarker discovery but also to interrogate mechanisms of pathogenesis in the urinary system.

Urine screening by Seldi-Tof, followed by biomarker identification, in a Brazilian cohort of patients with renal cell carcinoma (RCC)

PURPOSE

To screen proteins/peptides in urine of Renal Cell Carcinoma (RCC) patients by SELDI-TOF (Surface Enhanced Laser Desorption Ionization - Time of Flight) in search of possible biomarkers.

MATERIAL AND METHODS

Sixty-one urines samples from Clear Cell RCC and Papillary RCC were compared to 29 samples of control urine on CM10 chip. Mass analysis was performed in a ProteinChip Reader PCS 4,000 (Ciphergen Biosystems, Fremont, CA) with the software Ciphergen Express 3.0. All chips were read at low and at high laser energy. For statistical analysis the urine samples were clustered according to the histological classification (Clear Cell and Papillary Carcinoma). For identification urine was loaded on a SDS PAGE gel and bands of most interest were excised, trypsinized and identified by MS/MS. Databank searches were performed in Swiss-Prot database using the MASCOT search algorithm and in Profound.

RESULTS

Proteins that were identified from urine of controls included immunoglobulin light chains, albumin, secreted and transmembrane 1 precursor (protein K12), mannan-binding lectin-associated serine protease-2 (MASP-2) and vitelline membrane outer layer 1 isoform 1. Identification of immunoglobulins and isoforms of albumin are quite common by proteomics and therefore cannot be considered as possible molecular markers. K12 and MASP-2 play important physiological roles, while vitellite membrane outer layer 1 role is unknown since it was never purified in humans.

CONCLUSIONS

The down expression of Protein K-12 and MASP-2 make them good candidates for RCC urine marker and should be validated in a bigger cohort including the other less common histological RCC subtypes.

Proteomic Workflows for Biomarker Identification Using Mass Spectrometry - Technical and Statistical Considerations during Initial Discovery

Identification of biomarkers capable of differentiating between pathophysiological states of an individual is a laudable goal in the field of proteomics. Protein biomarker discovery generally employs high throughput sample characterization by mass spectrometry (MS), being capable of identifying and quantifying thousands of proteins per sample. While MS-based technologies have rapidly matured, the identification of truly informative biomarkers remains elusive, with only a handful of clinically applicable tests stemming from proteomic workflows. This underlying lack of progress is attributed in large part to erroneous experimental design, biased sample handling, as well as improper statistical analysis of the resulting data. This review will discuss in detail the importance of experimental design and provide some insight into the overall workflow required for biomarker identification experiments. Proper balance between the degree of biological vs. technical replication is required for confident biomarker identification.

Identification of differentially expressed proteins in direct expressed prostatic secretions of men with organ-confined versus extracapsular prostate cancer

Current protocols for the screening of prostate cancer cannot accurately discriminate clinically indolent tumors from more aggressive ones. One reliable indicator of outcome has been the determination of organ-confined versus nonorgan-confined disease but even this determination is often only made following prostatectomy. This underscores the need to explore alternate avenues to enhance outcome prediction of prostate cancer patients. Fluids that are proximal to the prostate, such as expressed prostatic secretions (EPS), are attractive sources of potential prostate cancer biomarkers as these fluids likely bathe the tumor. Direct-EPS samples from 16 individuals with extracapsular (n = 8) or organ-confined (n = 8) prostate cancer were used as a discovery cohort, and were analyzed in duplicate by a nine-step MudPIT on a LTQ-Orbitrap XL mass spectrometer. A total of 624 unique proteins were identified by at least two unique peptides with a 0.2% false discovery rate. A semiquantitative spectral counting algorithm identified 133 significantly differentially expressed proteins in the discovery cohort. Integrative data mining prioritized 14 candidates, including two known prostate cancer biomarkers: prostate-specific antigen and prostatic acid phosphatase, which were significantly elevated in the direct-EPS from the organ-confined cancer group. These and five other candidates (SFN, MME, PARK7, TIMP1, and TGM4) were verified by Western blotting in an independent set of direct-EPS from patients with biochemically recurrent disease (n = 5) versus patients with no evidence of recurrence upon follow-up (n = 10). Lastly, we performed proof-of-concept SRM-MS-based relative quantification of the five candidates using unpurified heavy isotope-labeled synthetic peptides spiked into pools of EPS-urines from men with extracapsular and organ-confined prostate tumors. This study represents the first efforts to define the direct-EPS proteome from two major subclasses of prostate cancer using shotgun proteomics and verification in EPS-urine by SRM-MS.

Screening for testosterone abuse in male athletes using the measurement of urinary LH, a revision of the paradigm

The primary screening method for the detection of doping by athletes using synthetic versions of endogenous steroids such as testosterone relies on measurement of the ratio of testosterone (T) to epitestosterone (E) in urine. In 2005 the World Anti-Doping Agency (WADA) lowered the T/E value at which samples undergo further investigation from six to four. This has resulted in a large increase in the number of athletes with naturally elevated T/E ratios undergoing investigation without a corresponding increase in the number of proven doping offences involving testosterone.Our objective was to develop a new simple screening protocol that can, with high probability, not only distinguish athletes whose natural T/E values exceed four from those whose T/E values have been elevated by testosterone doping but also detect those athletes with naturally low T/E values that do not exceed four despite being administered testosterone.Testosterone (250 mg Sustanon) was administered weekly to a group of 47 young adult males for five weeks in a double-blind placebo controlled study and urine samples collected. The samples were analysed for steroid concentrations using GC/MS and for luteinizing hormone (LH) by immunoassay.The elevation of T/E that occurred in all subjects was accompanied by a significant reduction in urinary LH concentrations to levels that are rare in normal subjects.The appropriate measurement of urinary LH, with the measurement of T/E values, can markedly improve the efficiency of detection of doping with testosterone by male athletes, particularly those who have low natural T/E ratios.

Application of free flow electrophoresis to the analysis of the urine proteome

Urine is a complex fluid, which is thought to contain valuable diagnostic information regarding general health. In particular, there is great diagnostic potential in the peptide and/or protein content of urine, but the information is present in low abundance. Most traditional proteomic techniques lack sufficient sensitivity/dynamic range, especially for dilute and/or complex samples. However, orthogonal separation methods can be applied prior to protein/peptide analysis to increase the success rate of urine proteomic studies and access this potentially valuable information. In this chapter, we describe isoelectric focusing (IEF) of intact urine proteins, via free flow electrophoresis (FFE), prior to typical peptide-based mass spectrometry analysis, facilitating the deep analysis of urine protein detection and identification, for biomarker discovery. Our work demonstrates that such an approach can be used as a preprocessing step and can be integrated into a workflow for the successful identification of protein components (biomarkers) from urine.