[show abstract][hide abstract] ABSTRACT: Urine is an excellent sample source in the proteomic study of diseases. It is available in large quantities, is relatively stable, is not contaminated by cells or lipids, and has shown to provide information not only on the organs in contact with the urinary tract but also of more remote organs and tissues. In addition to these qualities, it can be collected by untrained personnel. For these reasons, urinary proteomic studies have escalated in recent years with the aim of identifying biomarkers that could be use for diagnosis or to predict the outcome of renal pathologies. In this chapter, we present one of the analytical platforms that has been successfully used in a number of studies for the identification and validation of biomarkers in kidney diseases. This technique is capillary electrophoresis coupled online to an electrospray ionization time-of-flight mass spectrometer (CE-MS). This technology has proven to be highly reproducible, sensitive with a quick analysis time, important features when analytical platforms have to be used in a clinical setting.
Methods in molecular biology (Clifton, N.J.) 01/2013; 919:203-13.
[show abstract][hide abstract] ABSTRACT: One of the aims in the field of proteomics is the identification of a protein or polypeptide, or a range of these compounds, that could provide pre-symptomatic indication of the onset of a disease. A number of analytical techniques have been employed to try and achieve this end. These techniques have been applied to the complete range of body fluids and tissues that are readily available from clinical studies. Of these sample sources, the urinary low molecular weight peptidome has been shown to reflect changes in the health status of the individual. The alterations that occur in the polypeptide make up of urine, which reflect changes in biological status, are known as biomarkers. To be able to determine these changes no single technique has emerged that can cope with detecting the large number of peptides present and quantifying them over the wide concentration range they exist in. In this investigation, we made use of a single reflectron time of flight (RTOF)-MS analyser to which we first connected a CE system and then a nanoflow HPLC. Two pooled male and female standard urine samples were compared on these systems. Both techniques had similar results in terms of number of peptides detected and the mass range the peptides were detected over. The major differences in terms of biomarker research were the ability in CE to calibrate the migration time of the peptides to allow comparison between samples. In addition, CE was shown not to suffer from carry over from previous samples as was seen in the LC analysis.
[show abstract][hide abstract] ABSTRACT: Polyphenol rich diets have been associated with a reduced risk of cardiovascular disease. We examined the effect of a polyphenol rich (P-R) drink on biomarkers assessed by urinary proteomics. Thirty nine middle aged and overweight subjects were randomized to P-R drink (n = 20) or placebo (n = 19) in addition to their normal diet. After two weeks urine samples were obtained for assessment of the urinary proteome using capillary electrophoresis coupled to a mass spectrometer. A total of 93 polypeptides were found to be candidates for differential distribution with a nominal p-value <0.05, though these differences did not reach significance when multiple testing was accounted for. Sequences were determined in 19 of these demonstrating that they originate from alpha-1 antitrypsin, collagens, fibrinogen alpha and IgG kappa. Levels of 27 polypeptides were greater than 4-fold different between the two groups. Of these, 7 were previously found to be part of a coronary artery disease (CAD) specific urinary biomarker pattern. Their direction of expression was closer to the healthy state in the P-R drink group and closer to CAD state in the placebo group. Our data suggest that the P-R drink may have beneficial effects on urinary biomarkers of CAD. The data encourage the planning of future prospective studies, aimed at investigating significant effects of polyphenol rich dietary products.
Journal of Agricultural and Food Chemistry 11/2011; 59(24):12850-7. · 2.91 Impact Factor
[show abstract][hide abstract] ABSTRACT: Human urine is an ideal candidate for use in clinical diagnostics. It is easily available, as untrained personnel can collect it. It correlates well with the pathophysiology of a number of diseases, making it a useful source for clinical proteomics.
In this article, we give an update of the human urinary peptide database derived from over 13,000 data sets of CE-MS by now.
Urine samples from both patients and healthy subjects were analyzed by CE-MS; these included 47 different pathophysiological conditions. Besides defining biomarkers by their experimental parameters, information on their sequences provides fundamental data into the pathological pathways of diseases. Therefore, we have sequenced 953 urinary peptides by using state-of-the-art top-down MS/MS. Identified biomarkers of all clinical proteomic CE-MS studies including their regulation are also listed in this work.
Biomarker discovery can be used in the management of a wide range of diseases, by combining these data sets of the database. Taking this approach, we can reveal details, at a molecular level, on the pathogenesis of a number of diseases, in particular those associated with urine production and excretion.
[show abstract][hide abstract] ABSTRACT: Preeclampsia is a major determinant of fetal and maternal morbidity and mortality. We used a proteomic strategy to identify urinary biomarkers that predict preeclampsia before the onset of disease. We prospectively collected urine samples from women throughout pregnancy. Samples from gestational weeks 12 to 16 (n=45), 20 (n=50), and 28 (n=18) from women who subsequently had preeclampsia develop were matched to controls (n=86, n=49, and n=17, respectively). We performed capillary electrophoresis online coupled to micro-time-of-flight mass spectrometry. Disease-specific peptide patterns were generated using support vector machine-based software. Candidate biomarkers were sequenced by liquid chromatography-tandem mass spectrometry. From comparison with nonpregnant controls, we defined a panel of 284 pregnancy-specific proteomic biomarkers. Subsequently, we developed a model of 50 biomarkers from specimens obtained at week 28 that was associated with future preeclampsia (classification factor in cases, 1.032 ± 0.411 vs controls, -1.038 ± 0.432; P<0.001). Classification factor increased markedly from week 12 to 16 to 28 in women who subsequently had preeclampsia develop (n=16; from -0.392 ± 0.383 to 1.070 ± 0.383; P<0.001) and decreased slightly in controls (n=16; from -0.647 ± 0.437 to -1.024 ± 0.433; P=0.043). Among the biomarkers are fibrinogen alpha chain, collagen alpha chain, and uromodulin fragments. The markers appear to predict preeclampsia at gestational week 28 with good confidence but not reliably at earlier time points (weeks 12-16 and 20). After prospective validation in other cohorts, these markers may contribute to better prediction, monitoring, and accurate diagnosis of preeclampsia.
[show abstract][hide abstract] ABSTRACT: Urine proteomics is emerging as a powerful tool for biomarker discovery. The purpose of this study is the development of a well-characterized "real life" sample that can be used as reference standard in urine clinical proteomics studies.
We report on the generation of male and female urine samples that are extensively characterized by different platforms and methods (CE-MS, LC-MS, LC-MS/MS, 1-D gel analysis in combination with nano-LC MS/MS (using LTQ-FT ultra), and 2-DE-MS) for their proteome and peptidome. In several cases analysis involved a definition of the actual biochemical entities, i.e. proteins/peptides associated with molecular mass and detected PTMs and the relative abundance of these compounds.
The combination of different technologies allowed coverage of a wide mass range revealing the advantages and complementarities of the different technologies. Application of these samples in "inter-laboratory" and "inter-platform" data comparison is also demonstrated.
These well-characterized urine samples are freely available upon request to enable data comparison especially in the context of biomarker discovery and validation studies. It is also expected that they will provide the basis for the comprehensive characterization of the urinary proteome.